Counties-US-covid19-nytimes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# County-level Covid-19 Analysis for United States\n",
    "\n",
    "This notebook utilizes data kindly made available by the New York Times at https://github.com/nytimes/covid-19-data and used for their U.S. tracking page at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.  It provides a temporal perspective that complements their excellent geospatial presentation.  The thing about exponentials with a measurable daily growth rate is they change so fast.  With cases increasing 25% per day,\n",
    "a week means a factor of 5 and a month a factor of a thousand.\n",
    "\n",
    "\n",
    "* Repo for this and other notebnooks at: [https://github.com/deculler/covid19](https://github.com/deculler/covid19)\n",
    "* Website for this repo: [https://deculler.github.io/covid19/](https://deculler.github.io/covid19/)\n",
    "\n",
    "## View and run the notbooks\n",
    "\n",
    "* [View the notebook with nbviewer](https://nbviewer.jupyter.org/github/deculler/covid19/blob/master/Counties-US-covid19-nytimes.ipynb)\n",
    "* [Launch it on mybinder.org](https://mybinder.org/v2/gh/deculler/covid19/master?filepath=work/Counties-US-covid19.ipynb)\n",
    "* [@UCB on datahub.berkeley.edu](http://datahub.berkeley.edu/user-redirect/interact?account=deculler&repo=covid19&branch=master&path=Counties-US-covid19.ipynb)\n",
    "  \n",
    "## Quick links to sections\n",
    "\n",
    "* [Select state to study at county level](#selectState)\n",
    "* [Cases by county](#sectionCases)\n",
    "* [Deaths by county](#sectionDeaths)\n",
    "* [Growth trends by county](#sectionGrowth)\n",
    "* [Projection of cases in one county](#sectionProj)\n",
    "* [Projection of deaths in one county](#sectionProjDeath)\n",
    "\n",
    "For dataframes it uses Datascience Tables (for reference see http://data8.org/datascience/tables.html) developed for introductory courses as UCB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.15.0'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# HIDDEN\n",
    "# This useful nonsense should just go at the top of your notebook.\n",
    "from datascience import *\n",
    "%matplotlib inline\n",
    "#%matplotlib notebook\n",
    "import matplotlib.pyplot as plots\n",
    "import numpy as np\n",
    "import scipy\n",
    "plots.style.use('fivethirtyeight')\n",
    "plots.rc('lines', linewidth=2, color='r')\n",
    "from ipywidgets import interact\n",
    "import ipywidgets as widgets\n",
    "# datascience version number of last run of this notebook\n",
    "version.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\".\")\n",
    "from timetable import TimeTable\n",
    "\n",
    "import locale\n",
    "locale.setlocale( locale.LC_ALL, 'en_US.UTF-8' ) \n",
    "\n",
    "import os\n",
    "import datetime\n",
    "\n",
    "# Tools for working with timestamps\n",
    "day_fmt = \"%Y-%m-%d\"\n",
    "\n",
    "def less_day(day1, day2):\n",
    "    \"\"\"Return day1 < day2\"\"\"\n",
    "    return datetime.datetime.strptime(day1, day_fmt) < datetime.datetime.strptime(day2, day_fmt)\n",
    "\n",
    "def format_day(day):\n",
    "    \"\"\"Return day \"\"\"\n",
    "    date =  datetime.datetime.strptime(day, day_fmt)\n",
    "    return datetime.datetime.strftime(date, day_fmt)\n",
    "\n",
    "def inc_day(day, ndays=1):\n",
    "    \"\"\"Return day + ndays\"\"\"\n",
    "    date =  datetime.datetime.strptime(day, day_fmt) + datetime.timedelta(days=ndays)\n",
    "    return datetime.datetime.strftime(date, day_fmt)\n",
    "\n",
    "\n",
    "def ave_growth(trend, window=4):\n",
    "    \"\"\"Average recent growth rate of single trend\"\"\"\n",
    "    vals = [x for x in trend.take[-window:]['rate'] if np.isfinite(x)]\n",
    "    return scipy.stats.gmean(vals)\n",
    "\n",
    "def project_trend(trend, num_days, rate=None):\n",
    "    if rate :\n",
    "        growth_rate = rate\n",
    "    else :\n",
    "        growth_rate = ave_growth(trend)\n",
    "        \n",
    "    day = trend.last('date')\n",
    "    val = trend.last(1)\n",
    "    growth = trend.last('new')\n",
    "    pnew = trend.last('% new')\n",
    "    proj = trend.copy()\n",
    "    for i in range(num_days):\n",
    "        day = inc_day(day)\n",
    "        growth = round(growth * growth_rate)\n",
    "        val = val + growth\n",
    "        pnew = growth/val\n",
    "        proj.append((day, val, growth, pnew, growth_rate))\n",
    "    return proj\n",
    "\n",
    "def cases_since(cases, threshold=100, width=6, height=6):\n",
    "    _, axis = plots.subplots(figsize=(width, height))\n",
    "    for region in cases.categories :\n",
    "        ctbl = cases.extract(region)\n",
    "        since = ctbl.where(ctbl[region] >= threshold)\n",
    "        ndays = since.num_rows\n",
    "        vals = since[region]\n",
    "        axis.plot(vals)\n",
    "        axis.text(ndays-1, vals[-1], region)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#URL for https://github.com/nytimes/covid-19-data/blob/master/us-states.csv\n",
    "\n",
    "countyURL = \"https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_counties = Table.read_table(countyURL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "states = list(np.unique(raw_counties['state']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='selectState'></a>\n",
    "## Select state to examine at county level\n",
    "\n",
    "Choose a state and run all cells below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "77acccd842b8415eb14a5214f28a7b64",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='State:', index=4, options=('Alabama', 'Alaska', 'Arizona', 'Arkansas', 'California', 'Co…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = widgets.Dropdown(\n",
    "    options = states,\n",
    "    value ='California',\n",
    "    # rows=10,\n",
    "    description='State:',\n",
    "    disabled=False\n",
    ")\n",
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "state = w.value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_state = raw_counties.where('state', state)\n",
    "counties = list(np.unique(raw_state['county']))\n",
    "cases = TimeTable.from_table(raw_state.pivot('county', 'date', 'cases', sum), time_col = 'date', \n",
    "                             time_less_fun=less_day)\n",
    "deaths = TimeTable.from_table(raw_state.pivot('county', 'date', 'deaths', sum), time_col = 'date',\n",
    "                             time_less_fun=less_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=sectionCases></a>\n",
    "## Cases to date by county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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wNM9Hw/TxL/R5d23mVaq+oaEhhoaGxMbG0qFDB/T19cutV1hYyKRJk3ByciI3N5fIyEhCQ0PZsWOHWr0ZM2Ywffp0zM3NmThxImFhYRw6dAgvLy+ioqL45JNPSEpKAsDAwKBSbZe6ceMGu3fvZsqUKRgaGpYpVygUj/2+9erVIyoqCnt7e9LT0xk/fjzjx4/nq6++UtUpKCjgs88+Y+HChbz88suYmZlx5MgRgoKCmDNnDlpaWixfvpw333yTI0eO1KjD3CVJE0IIUSGlW2+0bylDnZqio6NDTEwM4eHhrFq1ipYtW+Ll5cUbb7xB27ZtVfVCQkJU7+3t7VmwYAHt27fnypUravPMJk+ejI+PDwDjx48nMDCQq1evYmVlRePGjdHS0lId31jZtktduHABpVKJk1PlVwOPGDFC9d7Ozo6ZM2fyzjvvsHTpUurVezgYWFxczLx582jVqpWqrq+vr1o78+bNY9u2bezevZugoKBKx6EpkqQJIYR4qjt373Eq9TL16mnR2sNR0+E8N5Xt2dKEPn360L17dxISEkhMTGTPnj1ER0czdepUxo4dC0BycjJz587l+PHj5OXloVQqAcjIyFBLpNzc3FTvzc3NAcjOzn7igoGKtl2qtPyviI+PZ+HChZw9e5Zbt25RXFxMYWEhWVlZWFhYAA8TVw8PD7X7srOzmTVrFgcOHCA7O5vi4mLu3btHRkbGX45FE2ROmhBCiKc6cuIcxcUluDrY0siggabDqfP09fXx9/dnwoQJ7Nq1i5CQEObMmUNhYSH5+fn079+fhg0bsmzZMvbu3cumTZuAh0OVf6arq6t6X7ox8ZOSqsq0Xap58+ZoaWlx9uzZSn3Hy5cvExQUhJOTE9988w379u0jOjq6zLP09PTKLBQYPnw4R44cYfbs2ezcuZMDBw5gaWn52BirK0nShBBCPFVi8u9Dna1kqLM6cnZ2pqioiIKCAlJTU8nNzWXq1Km8+uqrODk5kZ2dXek269evT3Fxsdq1v9K2sbExAQEBLF++nDt37pQpf9yxk0lJSRQWFhIVFUX79u1xcHAgMzOzQrH/8ssvhIWF0b17d1xcXDA0NCQrK6tC91YnkqQJIYR4ovuFDzh6+gIA7WQ+mkZdv36dXr16sWHDBk6cOEFaWho//PADixYtwtfXl8aNG2NtbY2enh7Lly8nLS2NnTt3Mnv27Eo/y9bWloKCAuLi4sjNzeXu3bt/ue3PPvsMpVKJv78/P/zwA6mpqZw9e5YVK1bQqVOncu9p3rw5JSUlLF68mLS0NDZt2sTSpUsrFHvz5s35/vvvOXPmDEeOHOG9996jfv2at9hFkjQhhBBPdPT0BQofFOFgb8FLikaaDqdOMzAwoF27dixdupSePXvi7e3NzJkzGTBgACtXrgTg5ZdfZsmSJWzfvh0vLy/mzp3LrFmzKv0sLy8v3nvvPUJDQ2nevDlffPHFX27b3t6e+Ph4/Pz8iIyM5NVXX6V3797s2LGDhQsXlnuPu7s7c+bMYfHixXTo0IHVq1fzySefVCj26Oho8vPz8fPz47333mPQoEHY2tpW6vtXB1p5eXl/fUZfDZeamoqjY9VMgJW2pC1pS9qqrW1Fr97GgcQTvNPbjz7dOr6wuJ63mzdvYmRkpOkwRB33pD+H0pMmhBDisYqKijlyIhWAdnLKgBAvlCRpQgghHuvUucvk372PtXkTLM1qziagQtQGkqQJIYR4rMOlG9i2aqHhSISoeyRJE0IIUS6lUqk6CkoOVBfixZMkTQghRLlS065w4+YdTJoYYW9t9vQbhBBVSpI0IYQQ5So9q7Odh5NqN3ohxIsjSZoQQogylEolh48+HOps51n5g7GFEM9OkjQhhBBlXL6azW/ZNzBq1JAWzW00HY4QdZIkaUIIIcr49fcFA63dHalXT/6pEEIT5DdPCCFEGaXz0bzkQHXxF3l4ePDll19qOowaTZI0IYQQaq7l5pGWkUUD/fq4O9lrOhzxiJycHMaOHYuHhwempqY4OjrSu3dv4uLinvuze/bsiUKhQKFQYGJigrOzM/3792fDhg0oleqnTMbFxREaGvrcY6rNdDQdgBBCiOqltBftFdfm6OrKPxPVTUhICPfu3SM6OpqmTZuSk5PDwYMHuX79+gt5fnBwMNOmTaOoqIisrCx27drF6NGj2bp1K2vWrEFbWxt4eNC7eDbSkyaEEEKNnDJQfeXl5ZGQkMD06dPx9fXF1taW1q1bM2rUKPr376+qt2HDBvz9/bG2tsbBwYEhQ4Zw9epVVfmBAwdQKBTEx8cTEBCAhYUFfn5+JCcnPzWGhg0bYmZmhpWVFa1bt2bixImsXbuW2NhYvv32W1W9R4c7b968SXh4OA4ODlhbW/Paa6+RlJSk1vaaNWtwd3fHwsKCoKAgvv76axQKhVqdlStX8sorr2BiYsIrr7zCqlWrKv1zrCnkv0hCCCFU8m7lk3IhA11dbVq5NtN0OC9c0L7fXujzNviZV6q+oaEhhoaGxMbG0qFDB/T19cutV1hYyKRJk3ByciI3N5fIyEhCQ0PZsWOHWr0ZM2Ywffp0zM3NmThxImFhYRw6dKjS++J16dIFV1dXfvzxRwYNGlSmXKlUEhQUROPGjdmwYQPGxsasX7+e3r17c/jwYczNzUlMTOSjjz4iMjKS119/nYMHDzJz5ky1dn788UciIiKYPXs2Xbp0Yc+ePYwdOxZTU1N69OhRqZhrAknShBBCqPx6LAWlEjycm9JAX0/T4YhH6OjoEBMTQ3h4OKtWraJly5Z4eXnxxhtv0LZtW1W9kJAQ1Xt7e3sWLFhA+/btuXLlClZWVqqyyZMn4+PjA8D48eMJDAzk6tWranUqqkWLFpw8ebLcsv3793P8+HHOnTtHgwYNAJgyZQo//fQTGzZsIDw8nGXLltGlSxf+8Y9/AODg4MCRI0fUesqio6MJCgoiLCxMVSc5OZkvvvhCkjQhhBC12x9nddbNDWwr27OlCX369KF79+4kJCSQmJjInj17iI6OZurUqYwdOxaA5ORk5s6dy/Hjx8nLy1NN6s/IyFBLwNzc3FTvzc0ffvfs7Oy/lKQplcrH9sAdPXqUu3fv4uDgoHa9oKCAixcvAnD27FkCAwPVytu0aaOWpKWkpBAcHKxWx9vbu0wPYW0hSZoQQggA8u8WcOJsGlpaD/dHE9WXvr4+/v7++Pv7M2HCBEaNGsWcOXMYNWoUDx48oH///vj5+bFs2TJMTEzIzc2lR48eFBYWqrWjq6urel+aYD26SrOiUlJSsLOzK7espKQEU1PTcpOpRo0aqZ5bkWHW8urU1mPLJEkTQggBQNKp8xQVleDqaItRIwNNhyMqwdnZmaKiIgoKCrhw4QK5ublMnToVe3t7ALZt2/Zcn79nzx5OnTrFyJEjyy339PTk2rVr1KtXTxXTo5ydnTly5IjatUc/Ozs788svv6gN5yYkJNCiRe1c5CJJmhBCCOCPVZ3tWtbNoc6a4Pr16wwZMoRBgwbh5uaGoaEhycnJLFq0CF9fXxo3boy1tTV6enosX76cYcOGkZKSwuzZs6sshrt375KVlaW2BceiRYt47bXXCAoKKvcePz8/OnTowDvvvMOMGTNwdHTk2rVr7N69Gz8/Pzp27MgHH3xAYGAgixYtomfPnhw8eJD/+7//U2tn1KhRvPvuu7Rq1YouXbqwe/duNm7cyJo1a6rs+1UnFdqC4+DBgwwcOBAXFxcUCgXr1q1TKx8+fLhqc7vSV9euXdXq3L9/n4iICJo1a4alpSUDBw7kypUranXS09MJCgrC0tKSZs2aMX78+DJds0IIIape4YMHJJ86D0B7TzlloLoyMDCgXbt2LF26lJ49e+Lt7c3MmTMZMGAAK1euBB7uT7ZkyRK2b9+Ol5cXc+fOZdasWVUWw7p163B2dqZVq1YMHDiQw4cPs2DBAtatW6faI+1RWlpafP/993Tu3Jnw8HDatWvH0KFDOXfuHBYWFgC0b9+eL774gmXLlvHqq6+yfft2wsPD1Vawvv7668ybN4/Fixfj5eXF0qVL+ec//1krFw1ABXvS8vPzcXV15e233+bDDz8st07p2Hep+vXrq5VPmjSJ2NhYVqxYgbGxMZMnTyYoKIj4+Hi0tbUpLi4mKCgIY2NjYmNjuXHjBsOHD0epVDJ//vxn+IpCCCGe5tjpixTcf0AzW3NefslI0+GIx9DT02PatGlMmzbtifX69etHv3791K7l5eWp3nfu3FntM4CdnV2Za4/avn17hWM9fvy42udGjRoxd+5c5s6d+9h7QkJC1IYyJ02aRLNm6lvBvPfee7z33nsVjqMmq1CS1q1bN7p16wbAiBEjyq2jp6eHmZlZuWU3b95kzZo1xMTE4O/vD8CyZcvw8PBg3759BAQEsHfvXk6fPs3x48extrYGHu7f8tFHHzF16lQaN25c6S8nhBCiYkpPGZBeNKFJixYtws/PD0NDQ/bt28fKlSuZOnWqpsPSmCo7cSAhIQEHBwfatGnDRx99RHZ2tqosOTmZBw8e0KVLF9U1a2trnJ2dOXToEACJiYk4OzurEjSAgIAA7t+/X6EdkIUQQvw1xcUlHDlxDoB2kqQJDUpKSqJ///54e3uzdOlSpk2b9tjOobqgShYOdO3alV69emFnZ8fly5f59NNP6d27N/v27UNPT49r166hra1NkyZN1O4zMTHh2rVrAFy7dg0TExO18iZNmqCtra2qU57U1NRniv1Z75e2pC1pS9qq6W1dSM/it2s5mDZpzL3bN0i9fUNjcTk6ytYfdVnpvDrxUJUkaX8+L8zNzY1WrVrh4eHBzp076d2792Pve3RPlMftc/Kk/U+e5Rc6NTW1yv5CkLakLWlL2qqpbW3Z9QsGBgZ07dz+mdusyriEqOueywHrFhYWWFpacuHCBQBMTU0pLi4mNzdXrV5OTo6q98zU1LRMj1lubi7FxcVletiEEEJUDaVSyfGzlwGZjyZEdfNckrTc3FwyMzNVCwlatWqFrq4ucXFxqjpXrlwhJSUFLy8v4OHS25SUFLVtOeLi4tDT06NVq1bPI0whhKjzLlzOJO/WXZoYN6K5nYWmwxFC/EmFhjvv3Lmj6hUrKSkhIyODY8eOYWxsjLGxMXPmzKF3796YmZlx+fJlZs6ciYmJCa+//joARkZGhISEMG3aNExMTFRbcLi5ueHn5wdAly5dcHFx4cMPP+TTTz/lxo0bTJs2jcGDB8vKTiGEeE4OJf+xgW1tPVpHiJqqQklaUlISvXr1Un2OiooiKiqKt99+mwULFnDq1Cm+++47bt68iZmZGZ07d2blypWq87gAZs+ejba2NkOHDqWgoAAfHx+WLl2q2vhOW1ubDRs2MG7cOAIDA9HX12fAgAF8+umnVfyVhRBCwMOhzsPHfk/SZKhTiGqnQklaeZve/dmWLVue2oa+vj7z589/4sa0NjY2bNiwoSIhCSGEeEZnL17hatZ1DA30cWluo+lwhBCPeC5z0oQQQlR/O/YlAuDt6fTY43yEEJojSZoQQtRBuTducSg5BW3tenRsI0OdNc3Vq1cJDw/H1dUVExMTXFxc+Oijj8qciS1qNknShBCiDtq5/3+UlCjp0KoFikYGmg5HVEJaWhr+/v6cPn2aJUuWcOTIEZYtW8aZM2fo0qULly5dKve+wsLCFxypeFaSpAkhRB1zv/ABe//78Li9Hn7tNByNqKyIiAjq1avHDz/8gK+vLzY2Nvj4+PDDDz9Qr149IiIiAOjZsydjxoxhypQpNG/enO7duwMQHR1Nx44dsbS0xMXFhVGjRqnNO1+3bh1WVlbEx8fj7e2NpaUlr7/+OmlpaWpxLFiwAEdHR6ysrPjggw+YM2cOHh4eanXWrl2Ll5cXZmZmtGnThpiYGEpKSp7vD6gWqZITB4QQQtQcPx8+we38ezS3s8DB3pJz585pOqRqY+SKoBf6vOjQyi2Wu3HjBrt372bKlCk0bNhQraxhw4aEhoYya9YsVdL1/fffM2TIEHbs2IFSqQSgXr16REVFYW9vT3p6OuPHj2f8+PF89dVXqrbu37/PggULiI6ORk9Pj+HDhzNmzBjVQsHNmzczd+5c5s+fT8eOHdm2bRuff/45RshBNMgAACAASURBVEZGqjZWrVrF7NmzmTdvHp6enpw+fZrw8HB0dXUJCwv7Sz+vukaSNCGEqEOUSiU/xf8KPOxFk73Rapbz58+jVCpxcnIqt9zZ2RmlUsn58+cBsLW1ZdasWWp1/nxguZ2dHTNnzuSdd95h6dKl1Kv3cICtqKiIzz77THXE16hRo/j73/9OSUkJ9erVY+nSpbzzzjsMHjwYgDFjxnDgwAG1hH/+/PnMmDGDPn36AGBvb8/FixdZsWKFJGkVJEmaEELUISdTL3H5ajaKxgZ4v+Ki6XCqncr2bGnK45Lr0t6y0vLyTuyJj49n4cKFnD17llu3blFcXExhYSFZWVlYWDw8dUJPT0/tDFZzc3MePHjAzZs3MTY25uzZs6oErVSbNm1USVpOTg4ZGRmMHj2asWPHquoUFRWpYhRPJ0maEELUITv2HQagW+c26OjIths1TfPmzdHS0uLMmTOqU33+7OzZs2hpadG0aVMADAzUF4VcvnyZoKAgBg8ezMcff8xLL73E0aNHCQ0NVVtYoKOjnh6UJn1/nk/2pF7Y0noLFixQHf8oKk8WDgghRB2RlXOD/x1PRUenHgGvvqLpcMRfYGxsTEBAACtWrODu3btqZXfv3uXrr7/mb3/7G8bGxuXen5SURGFhIVFRUbRv3x4HBwcyMzMrHYeTkxNHjhxRu/bnz6amplhaWnLx4kWaNWtW5iUqRpI0IYSoI3bG/4pSCa+2cUPRWLbdqKnmz59PUVERb7zxBvHx8WRkZHDgwAH69u2LUqlk3rx5j723efPmlJSUsHjxYtLS0ti0aRNLly6tdAwffvgh69evZ82aNZw/f54vvviCX3/9Va13beLEiSxatIiYmBhSU1M5deoU3377LQsWLPhL37sukiRNCCHqgHsF94n75Sgg227UdE2bNiUuLo4WLVrw4Ycf0qpVK4YNG4aTkxN79+7F3t7+sfe6u7szZ84cFi9eTIcOHVi9ejWffPJJpWPo378/ERERzJgxAx8fH06dOsV7772Hvr6+qs7gwYOJjo5mw4YNdOrUiR49erBq1Srs7Oz+yteuk2ROmhBC1AH7E49z914hLZpb09TGXNPhiGdkbW3NokWLnlhn+/bt5V7/8MMP+fDDD9Wu9e3bV/U+ODiY4OBgtfLyzvAeO3as2qKA4OBg1Vy4UgMGDGDAgAFPjFM8niRpQghRyz267YYQz+ru3busWLGCrl27oqOjw7Zt24iNjWX16tWaDq1WkSRNCCFquaOnL3A16zpNjBvRrmX5+2sJURlaWlrs3r2bBQsWUFBQQLNmzVi2bBm9evXSdGi1iiRpQghRy5Vuu9G9cxu0tWXbDfHsGjRowNatWzUdRq0nCweEEKIWu/JbDsmnLlBfV4cusu2GEDWKJGlCCFGLlc5F69zenUYGDTQcjRCiMiRJE0KIWir/bgH7E48DEOjbVsPRCCEqS5I0IYSopeJ+OUrB/Qd4ONtja2mq6XCEEJUkSZoQQtRCJSUlqqFO6UUTomaSJE0IIWqhIyfOkZ17E7OXFbR2d9B0OEKIv0CSNCGEqIVU2274tqVePfmrXtR+rq6uLF68WNNhVCn5zRVCiFrm0pVrnDh7CX09Xfy8Wmo6HFHFcnJyGDt2LB4eHpiamuLo6Ejv3r2Ji4t77s/u2bMnCoWizOvRI6M0Yf/+/bz77ruaDqNKyWa2QghRy/wU/7AXza9DSwwa6j+ltqhpQkJCuHfvHtHR0TRt2pScnBwOHjzI9evXX8jzg4ODmTZtmto1IyOjcusWFhZSv379FxEWL7/88gt5zoskPWlCCFGL3Lpzl58PnwSgu48sGKht8vLySEhIYPr06fj6+mJra0vr1q0ZNWoU/fv3V9XbsGED/v7+WFtb4+DgwJAhQ7h69aqq/MCBAygUCuLj4wkICMDCwgI/Pz+Sk5OfGkPDhg0xMzNTe2lpaQEPhxznzZvH8OHDsbW1Zfjw4QBMmTKFNm3aYG5uTsuWLZk+fTr3799Xtfnpp5/SqVMnvv/+ezw9PbGxsWHQoEHcuHFD7dlr167F29sbMzMznJycGDlypKrs0eHOr7/+mtatW2Nqakrz5s3p378/JSUlFWrr8uXLvP3221hZWWFjY0NISAiZmZlP/dlUNelJE0KIWiTuv8kUPiiilWszLM2aaDqcGidpxrwX+rxXIsdXqr6hoSGGhobExsbSoUMH9PXL7yktLCxk0qRJODk5kZubS2RkJKGhoezYsUOt3owZM5g+fTrm5uZMnDiRsLAwDh06pEq6/oro6GgiIiKIiIhAqVQC0KhRIxYvXoy5uTlnzpxh9OjR6OvrM3HiRNV9aWlp/Pjjj6xfv57bt28TGhrKrFmz+OyzzwBYvnw5U6dOZdq0aXTr1o3bt2/z888/lxvDr7/+ysSJE1m6dCnt27cnLy+P/fv3q8qf1FZJSQkDBw7EyMiI7du3U1xcTEREBCEhIfznP/95pp9NZUmSJoQQtURRUTE7D/wPgB5+7TQcjXgedHR0iImJITw8nFWrVtGyZUu8vLx44403aNv2j57TkJAQ1Xt7e3sWLFhA+/btuXLlClZWVqqyyZMn4+PjA8D48eMJDAzk6tWranUe9c0337B+/XrV57feeouFCxeqPnfu3JlRo0ap3TNhwgTVezs7O/7xj3+wfPlytSStpKSExYsX06hRI9V32Lx5MwBKpZLPPvuMkSNHMmLECNU9r7xS/lFn6enpGBoaEhgYiKGhIba2trRs2bJCbe3Zs4eUlBSOHj2KtbU18DCpa9u2LT///DOdO3d+7M+mqkmSJoQQtcThY2fJvXEbK7MmeLo003Q4NVJle7Y0oU+fPnTv3p2EhAQSExPZs2cP0dHRTJ06lbFjxwKQnJzM3LlzOX78OHl5eaoerYyMDLUEzM3NTfXe3NwcgOzs7CcmaX379lVLrkqTqlLlJU5btmxh2bJlXLx4kfz8fIqKisqsOra1tVVry8LCguzsbAB+++03srKyVAnl05QO4Xp6ehIQEIC/vz+9evXC0NDwqW2lpKRgZWWlStAAmjdvjomJCSkpKS80SZM5aUIIUUuUbrsR6Nf2hQ7JiBdPX18ff39/JkyYwK5duwgJCWHOnDkUFhaSn59P//79adiwIcuWLWPv3r1s2rQJeDgM+me6urqq96V/ZkoTuscxMjKiWbNmqpeJiYlaecOGDdU+JyQkMGzYMP72t7/x3XffsX//fj7++OMysejoqPcbaWlpqeaQPS2mRzVu3JgDBw6wYsUKLC0t+ec//4mXlxdZWVlPbUupVD729+dF/15JkiaEELXAhcuZpFzIwKChHj7tPTQdjnjBnJ2dKSoqoqCggNTUVHJzc5k6dSqvvvoqTk5Oqh4pTTh06BA2NjaMGzeO1q1b07x5cy5fvlypNiwsLDA1NVWbV/Y0Ojo6+Pn5MX36dH7++Wdu3rzJrl27ntpWixYtyMjIICMjQ3Xt/PnzZGdn4+zsXKm4n5UMdwohRC0Q+3svmr93K/T1XsyWB+LFu379OkOGDGHQoEG4ublhaGhIcnIyixYtwtfXl8aNG2NtbY2enh7Lly9n2LBhpKSkMHv2bI3F3Lx5czIyMti0aRNt2rThP//5D//+978r1YaWlhZjx44lMjKSJk2a0K1bN+7cucOBAwfUVmWW2r59O+np6XTs2FG1ivXu3bs4Ozs/ta2AgACcnZ0ZNmwYUVFRlJSUMG7cONq0aUOnTp2q6sdSIZKkCSFEDZd36w4JR06hpQXdfdpoOhzxHBkYGNCuXTuWLl3KhQsXKCwsxMLCggEDBhAREQE83C9syZIlzJw5k6+//ho3NzdmzZqltkXHi9SrVy9GjBjBhAkTuH//Pl26dGHSpElq89oq4oMPPkBPT4/Fixczbdo0jI2NCQwMLLeuQqFg8eLFzJ07l3v37tGsWTNiYmJo3779U9uqV68e3333HRMmTKBnz55oaWnh7+/PvHkvduUvgFZeXl7lBnprkdTUVBwdHaUtaUvakrZqdFubYg+wMfYA7Vo6MS5sQLWJq7q7efPmYzdhFeJFedKfwwrNSTt48CADBw7ExcUFhULBunXrVGUPHjwgMjKSjh07YmlpibOzM++//z7p6elqbZR3lMR7772nVicvL4+wsDBsbW2xtbUlLCysWhw1IYQQ1dWDB0Xs+vkIINtuCFHbVChJy8/Px9XVlTlz5tCgQQO1srt373L06FHGjRtHfHw869ev58qVKwwYMICioiK1usHBwaSkpKhef95XBeD999/n2LFjbNy4kU2bNnHs2DE++OCDZ/yKQghReyUknebmrXxsrUxwdbTVdDhCiCpUoTlp3bp1o1u3bgBqG7/Bw6W4P/zwg9q1hQsX0qFDB1JSUtT2YCk9SqI8KSkp7N69m59++gkvLy9VOz169KhR3edCCPGiKJVKfor/FYDX/NrJthtC1DLPZQuO27dvAw8n7v3Z5s2badasGR06dGDKlCmqegCJiYkYGhqqEjSADh06YGBgwKFDh55HmEIIUaOdvXiF85cyaWTQgFfbuj39BiFEjVLlqzsLCwuZMmUKgYGBajsWv/nmm9jY2KjO7ZoxYwYnTpxQ9cJdu3aNJk2aqP1PUEtLi5dffplr16499nmpqanPFO+z3i9tSVvSlrSlqbbWbt5Bfn4+3p7NuJSW9kxtVZfvKKMmQvyhSpO0oqIiwsLCuHnzJt9++61a2bvvvqt67+bmhr29PQEBASQnJ9OqVSug/J18n7TzLzzbL3R1XdEkbUlb0pa09TSH/5fMufQcGjUyJGTAazQxblwt4pLpKUJUnSob7iwqKiI0NJSTJ0+ydetWXnrppSfWf+WVV9DW1ubChQsAmJqakpOTo3Zcg1KpJDc3t8yRE0IIUdcdPHKGkhIlHVq1eKYETQhRfVVJkvbgwQOGDh3KyZMn+fHHHx+7OODPTp48SXFxsapu+/btuXPnDomJiao6iYmJ5Ofnq81TE0KIuq7wwQMSks4CECjbbghRa1VouPPOnTuqHq+SkhIyMjI4duwYxsbGWFhYMGTIEJKSkvj222/R0tIiKysLeHjAaYMGDbh48SLff/893bp146WXXiIlJYUpU6bQsmVLOnToADw8d6xr166MHj2aL774AqVSyejRo+nevbt0nQshxJ8c/PUk+ffu09LVBqemVk+/QQhRI1WoJy0pKQkfHx98fHy4d+8eUVFR+Pj4MHv2bK5cuUJsbCyZmZn4+fnh7Oysem3ZsgUAXV1d4uPj6devH+3atWPChAn4+/uzdetWtLW1Vc9Zvnw57u7u9OvXj/79++Pu7s6yZcuezzcXQogaSKlUqs7pDPRtK9tuiHIpFAq2bt2q6TDKlZSUhEKh4NKlS5oOpdqrUE9a586dn7jz/9NOBbC2tiY2NvapzzE2Nuarr76qSEhCCFEnXcvN4/KVbBrq18f7FRdNhyM06OjRo/j7+9OuXTt27typ6XDEc/Bc9kkTQgjxfJw8+7D3wcHeAl3dKt9FSdQgq1evJjQ0lNOnT5OSkqLpcMRzIEmaEELUICdS0gBwtDPXbCBCo+7du8fGjRsZMmQIvXv3Zs2aNU+sP336dNq2bYu5uTkeHh5MmzaNgoICVXlUVBTe3t6sX78eDw8PrKysGDFiBIWFhXz99de4ubnRtGlTPv74Y0pKSlT3FRYWEhkZiaurK5aWlvj7+7Nnzx61Z+/evZt27dphZmZGjx49OHfunFr59evXCQ0NxdXVFXNzczp06MDatWur4KdU88l/w4QQooZQKpWcSH3Yk+Zob6HhaGqnxd9sfqHPG/Fu/79039atW7GxscHd3Z2goCCGDh1KZGQkurq65dZv2LAh0dHRWFhYkJKSwpgxY6hfvz5TpkxR1bl8+TKxsbFs2LCBzMxMBg8ezLVr1zA1NWXLli2cPXuWoUOH4uXlRZ8+fQD4+9//zsWLF1m+fDlWVlbs2rWLgQMHsnfvXjw8PMjIyCA4OJjBgwczbNgwTp48yeTJk9ViKygowNPTk/DwcBo3bsy+ffsYPXo0NjY2+Pr6/qWfT20hSZoQQtQQGb/lcPNWPsZGhpi+ZKTpcIQGrV69moEDBwLQqVMnGjRoQGxsrCp5etT48eNV7+3s7BgzZgxffvmlWpJWXFxMTEwMRkZGuLq6EhAQwMGDBzl9+jT169fH2dkZLy8vfv75Z/r06cPFixfZtGkTx44dw8bGBoCwsDD27dvHN998wz//+U/+9a9/YW1tzbx589DS0sLJyYlz584xa9Ys1XMtLS356KOPVJ/fffdd9u/fz6ZNmyRJ03QAQgghKqZ0qNPNyU5WdT4nf7Vn60W6cOEChw4dYsWKFcDD03reeust1qxZ89gkbevWrSxZsoQLFy6Qn59PcXExxcXFanWsra0xMvoj+Tc1NcXBwYH69eurXcvOzgYeLlxQKpWqrbRK3b9/Hx8fHwBSUlJo21Z9FXL79u3V6hcXF7Nw4UK2bNlCZmYmhYWFFBYW0qlTp8r+aGodSdKEEKKGKF004O5kp+FIhCatXr2a4uJi3N3dVddKT+vJyMjA2tparf7hw4d57733mDBhArNnz8bIyIjY2FimTp2qVu/RoVItLS10dHTKXCtN7kpKStDS0mLv3r1l7tXX11eL60m+/PJLoqOjmTNnDq6urhgaGjJz5kxVMliXSZImhBA1QElJCafOlSZp9uRdl3/A6qKioiK+/fZbIiMj6d69u1rZBx98wLp165gwYYLa9V9++QULCwu1Ic/09PRnjqVly5YolUqysrJUPWePatGiBdu2bVM7h/vw4cNqdRISEggMDFQN3yqVSs6dO6fWq1dXyepOIYSoAdIyssi/ex/TJkaYNFFoOhyhITt37iQ3N5chQ4bg6uqq9urfvz9r165VW30J4ODgQGZmJt9//z1paWmsWLGCzZuffYGEg4MDb731FiNGjGDr1q2kpaWRlJTEl19+ybZt2wAYOnQoly9fZuLEiaSmprJ161ZWrlxZpp39+/eTkJDA2bNniYiI4PLly88cX20gSZoQQtQAJ34f6nRzstdsIEKj1qxZQ+fOnXnppZfKlL3xxhukp6ezb98+tes9evTgo48+YtKkSbz66qvExcXx8ccfV0k8MTExBAcHM23aNNq1a0dQUBAHDx7E1tYWABsbG9asWcOePXvo1KkTixcvJjIyUq2NiIgIWrduzZtvvslrr71Gw4YNefPNN6skvppOhjuFEKIGOHk2DQB3Z3uNxiE067vvvntsmb29veoEoEdPAoqMjCyTHIWGhqreT5o0iUmTJqmVz58/v8wz/vWvf6l91tXVLffeP+vevXuZodm33npL9V6hUMi+aI8hPWlCCFHNFRUVc+b8wzlEbo62Go5GCPGiSJImhBDV3PnLmRTcf4C1eROMjRppOhwhxAsiSZoQQlRzf+yPZq/ROIQQL5YkaUIIUc2d+H0+mpvsjyZEnSJJmhBCVGP3Cx9w9mIGWlrg6ihJmhB1iSRpQghRjaVcyKCoqAR7azMaGTTQdDhCiBdIkjQhhKjGTqqGOu01GocQ4sWTJE0IIaqx0vM6PWR/NCHqHEnShBCimsq/W8C5S1fR1q6HczPrp98ghKhVJEkTQohqKuVCOkolONhZ0kBfT9PhCCFeMEnShBCimvpjfzRZ1Sn+kJOTw9ixY/Hw8MDU1BRHR0d69+5NXFzcc392z549USgU5R4Z9e6776JQKIiIiKhwe5cuXUKhUJCUlFSVYdYacnanEEJUUydSSw9VlyRN/CEkJIR79+4RHR1N06ZNycnJ4eDBg1y/fv2FPN/a2pp169Yxbtw4tLS0ALh+/To7duzA2lqG5auS9KQJIUQ1dOvOXS5lXENXVxunplaaDkdUE3l5eSQkJDB9+nR8fX2xtbWldevWjBo1iv79+6vqbdiwAX9/f6ytrXFwcGDIkCFcvXpVVX7gwAEUCgXx8fEEBARgYWGBn58fycnJT42ha9eu5Ofnc+DAAbXntWnTBjs79f9Q7N69mx49emBnZ4e9vT39+vUjJSVFVe7p6QmAv78/CoWCnj17qsrWrl2Ll5cXZmZmtGnThpiYGEpKSlTl6enpBAcHY21tjbW1NYMGDeLKlSuV+GlWf9KTJoQQ1dCp33vRnJtaU19XV8PR1B03zq17oc8zdgiuVH1DQ0MMDQ2JjY2lQ4cO6Ovrl1uvsLCQSZMm4eTkRG5uLpGRkYSGhrJjxw61ejNmzGD69OmYm5szceJEwsLCOHTokKqHrDy6uroMHDiQtWvX4uPjAzxMqEaOHMnatWvV6ubn5/Phhx/i7u7OvXv3+Oyzzxg4cCCHDh2ifv367N27ly5durB582bc3d2pX78+AKtWrWL27NnMmzcPT09PTp8+TXh4OLq6uoSFhaFUKgkODkZfX59t27ahpaVFREQEwcHBxMXFPTH+mkSSNCGEqIZKt95wl603xJ/o6OgQExNDeHg4q1atomXLlnh5efHGG2/Qtm1bVb2QkBDVe3t7exYsWED79u25cuUKVlZ/9MxOnjxZlWiNHz+ewMBArl69qlanPIMGDcLf359bt25x/vx50tPT6dOnT5kkrU+fPmqfY2JisLGx4X//+x/e3t40adIEgJdeegkzMzNVvfnz5zNjxgzV/fb29ly8eJEVK1YQFhbGvn37OHHiBElJSareu6+//ppXXnmF+Ph4/Pz8KvojrdYkSRNCiGpIzuvUjMr2bGlCnz596N69OwkJCSQmJrJnzx6io6OZOnUqY8eOBSA5OZm5c+dy/Phx8vLyUCqVAGRkZKglYG5ubqr35ubmAGRnZz81SXN2dsbd3Z3Nmzdz/Phx+vXrR8OGDcvUu3jxIrNmzeLXX38lNzeXkpISSkpKyMjIeGzbOTk5ZGRkMHr0aNX3ASgqKlJ9j5SUFCwsLNSGV+3t7bGwsODMmTOSpAkhhHg+cm/c4mrWdfT1dGlmY6HpcEQ1pK+vj7+/P/7+/kyYMIFRo0YxZ84cRo0axYMHD+jfvz9+fn4sW7YMExMTcnNz6dGjB4WFhWrt6P5pKL10iLA0EXqaQYMG8fXXX5OWlsaWLVvKrTNw4EAsLCz4/PPPsbCwQEdHBy8vrzJx/FnpvLMFCxbg5eVVbh2lUvnYIc3aMtQJsnBACCGqnZO/z0dzcbBFR0dbw9GImsDZ2ZmioiIKCgpITU0lNzeXqVOn8uqrr+Lk5ER2dnaVP7Nv376cP38eKysrtaHWUtevXyclJYUxY8bg5+eHs7Mzt2/fpqioSFWndA5acXGx6pqpqSmWlpZcvHiRZs2alXkBtGjRgqtXr3Lp0iXVfWlpaWRmZtKiRYsq/66aIj1pQghRzZTujybz0cSjrl+/zpAhQxg0aBBubm4YGhqSnJzMokWL8PX1pXHjxlhbW6Onp8fy5csZNmwYKSkpzJ49u8pjadSoEadOnUJbu/z/SCgUCpo0acLq1auxtrbm6tWrTJs2DR2dP1IPExMTGjRowJ49e7C1tUVPTw8jIyMmTpzI+PHjMTIyolu3bjx48ICjR4+SmZmpSvrc3d0JCwtj7ty5KJVKxo8fj6enp2qOXW0gPWlCCFGNKJVKVU+au8xHE48wMDCgXbt2LF26lJ49e+Lt7c3MmTMZMGAAK1euBODll19myZIlbN++HS8vL+bOncusWbOeSzxGRkYYGhqWW1avXj3+9a9/cfLkSby9vYmIiGDy5Mno6f1xeoaOjg5z585lzZo1tGjRgnfeeQeAwYMHEx0dzYYNG+jUqRM9evRg1apVqjloWlparFu3jiZNmvD666/Tq1cvTE1NWbduXa0a7pSeNCGEqEaycm6Qc/0WjQwaYGdl9vQbRJ2ip6fHtGnTmDZt2hPr9evXj379+qldy8vLU73v3Lmz2mcAOzu7MtcetX379kqV+/r6kpCQoHbt0b3MBg8ezODBg8u0NWDAAAYMGPDYZ9nY2LB+/fonxlPTSU+aEEJUI6Vbb7g62taqHgEhROVJkiaEENWI7I8mhChVoSTt4MGDDBw4EBcXFxQKBevWqe/IrFQqiYqKokWLFpibm9OzZ09Onz6tVicvL4+wsDBsbW2xtbUlLCysTLfqyZMnee211zA3N8fFxUU1GVAIIeoCpVL5x/5ojjIfTYi6rkJJWn5+Pq6ursyZM4cGDRqUKf/iiy+IiYlh7ty57N27FxMTE/r27cvt27dVdd5//32OHTvGxo0b2bRpE8eOHeODDz5Qld+6dYu+fftiamrK3r17mTNnDl9++SXR0dFV8DWFEKL6y/gth5u372JsZIilWRNNhyOE0LAKLRzo1q0b3bp1A2DEiBFqZUqlkiVLlvCPf/xDdXzDkiVLcHR0ZNOmTQwdOpSUlBR2797NTz/9pNqYbuHChfTo0YPU1FQcHR3ZuHEj9+7dY8mSJTRo0ABXV1fOnj3L4sWLGTlypMzNEELUeqVbb7g52cnfeUKIZ5+TdunSJbKysujSpYvqWoMGDejYsSOHDh0CIDExEUNDQ7Wdgzt06ICBgYFaHW9vb7WeuoCAADIzM9U2qxNCiNpKNR9Ntt4QQlAFW3BkZWUBDzek+zMTExMyMzMBuHbtGk2aNFH7n6GWlhYvv/wy165dU9WxtLQs00Zpmb29fbnPT01Nfab4n/V+aUvakrakrapoq6SkhENJJ7hX8ICGusoKPbOmfceKcHR0rLI4hKjpqmyftEe75h89V6u8rvun1SldNPCkbv9n+YUuHWqtCtKWtCVtSVvP0tb5S1epp12fprYmeLV9pdrEpcm2hKjrnnm408zs4WaLpT1ipXJyclQ9YaampuTk5Kit1FQqleTm5qrVKa8NKNtLJ4QQtc2J34c63ZzsNRuIEKLaeOYkzc7ODjMzM+Li4lTXCgoKSEhIUM1Ba9++PXfu3CExMVFVJzExkfz8fLU6CQkJFBQUqOrExcVhYWGhOgZCCCFqq9L587Ss6wAAIABJREFUaB6yP5qoAh4eHnz55ZeaDqNCcVhZWZXZ2ks8VKEk7c6dOxw7doxjx45RUlJCRkYGx44dIz09HS0tLYYPH87nn3/Otm3bOHXqFCNGjMDAwEB1nIOzszNdu3Zl9OjRHD58mMTEREaPHk337t1V3eIDBgygQYMGjBgxglOnTrFt2zY+//xzRowYIauchBC1WlFRMWfOXwYeruwU4kmGDx+OQqFQHWDu7u7OmDFj1PYejYuLIzQ0VINRVq84aqoKzUlLSkqiV69eqs9RUVFERUXx9ttvs2TJEsLDw7l37x4RERHk5eXRpk0btmzZQqNGjVT3LF++nAkTJqjOEuvRowfz5s1TlRsZGfHvf/+bcePG4e/vj0Kh4O9//zsjR46squ8qhBDV0rlLV7lfWIS1eRMUjcs/rFqIP/Pz82PZsmUUFRWRkpLCyJEjuXnzJitWrAAeHrL+vD148ABdXd0n1nkRcdRmFepJKz2I9dHXkiVLgIcT+ydNmkRKSgpZWVnExsbi6uqq1oaxsTFfffUV6enppKen89VXX6FQKNTquLm5sWPHDrKyskhJSWHixInSiyaEqPXkKChRWXp6epiZmWFlZUWXLl3o27cve/fuVZX/eZgxNDSUkJAQtftLSkpwc3MjJiYGeDhP/IsvvqBVq1aYm5vTsWNHNmzYoKp/6dIlFAoFmzZtolevXpibm7Ny5Upu3rxJWFgYDg4OmJmZ4enpyf+zd+dhUVX/A8ffM8ww7AzKqmwKiPtK7opopoRLLojlmprpL83SNE1LLdO0skzcTTO3L66pqeW+hpqaS6WIIqCCCAjIziz39wc6ReIODMt5PY+PzL3nnvO5I4wfzj3LwoULC40DICoqiqCgIJycnPDz8+OXX3556N7i4uIYMmQIHh4eeHh40KdPH65du1Y0b1wZU2SzOwVBEITnY9gKSkwaMLqFp6JKtL3/a1r9heuIjo5m//79j+zV6tOnDwMHDiQ1NdXQOXLs2DFu375tGJY0Y8YMtm3bxldffYW3tze///47Y8aMQa1W06lTJ0Nd06dPZ8aMGcyfPx+lUsmMGTP4+++/CQsLw97entjYWJKTkwuNQ6/X079/f2xtbdmzZw/Z2dlMnDiR3NxcQ5msrCy6du1K06ZN2blzJ6ampsyfP5/u3btz6tQpLCwsXvj9KktEkiYIgmBEuXkarly/iUwGtbzdjR2OUEbs27ePqlWrotPpDBPuPv/880LLdujQAWtra7Zv387AgQMB2LhxI/7+/jg5OZGZmcmCBQvYsmULLVu2BMDT05MzZ86wfPnyAkna8OHDDbsLAdy4cYP69evTpEkTgMdO9Dt06BCXL1/m/PnzuLm5AfnDpwIDAw1lNm/ejCRJLFy40PAk7dtvv8Xb25tff/2VHj16PPN7VZaJJE0QBMGIIqJuotXqqebmhLXlw3sjCyWrKHq2SkLLli2ZN28e2dnZrFq1iujoaEaMGFFoWYVCQY8ePdi4cSMDBw4kNzeX7du3M3v2bAAiIiLIycmhd+/eBYYYaTQa3N0L/uLQqFHBNfyGDh3KoEGDOH/+PAEBAXTu3JnWrVsXGkdERARVqlQxJGgAfn5+yOX/jLw6f/48MTExuLq6Frg2KyuL69evP8U7U76IJE0QBMGI/hKPOoXnYGFhQfXq+QnlnDlz6NKlC3PmzGHSpEmFlg8JCeGVV14hLi6O06dPo9Fo6NKlC5D/GBJg/fr1BRIoyE/w/s3S0rLA644dO3Lx4kX27t3L4cOHCQkJoXv37gXGpT3w77VSH0Wv11OvXj1WrFjx0Dk7O7snXl/eiCRNEATBiB6MRxProwkv4sMPPyQ4OJjBgwfj4uLy0Hk/Pz+qVavG5s2bOXXqFEFBQVhZ5c8k9vX1RaVScePGDfz9/Z+57cqVK9O3b1/69u1Lx44dGTp0KN988w0qlapAuZo1axIXF8fNmzcNPWVnzpwxJIkADRo0YNOmTVSqVOmhyYUV0QsvZisIgiA8n8ysHK7FxGNiIse3uuuTLxCER2jTpg01a9bkq6++emSZ4OBgfvzxR/bs2UOfPn0Mx62trRk9ejQff/wxq1evJioqigsXLrBixQp++OGHx7b7+eef8/PPP3Pt2jUiIiLYsWMHnp6eDyVokL9sSI0aNRgxYgQXLlzg1KlTfPTRRwV664KDg3F0dOSNN97g2LFjREdHc/z4cSZPnlwhZ3iKJE0QBMFILl+7gSSBt0cVzM0e/k9NEJ7FO++8w+rVq4mNjS30fEhICJGRkdjY2BAQEFDg3OTJk5k4cSKhoaE0b96cHj16sH379ifu+KNSqZgxYwatW7emU6dOZGRk8L///a/QsnK5nDVr1qDX63n55ZcZMWIEH3zwQYGEzsLCgl27duHp6cngwYNp2rQpI0eOLDAztSIRjzsFQRCM5J/xaGKXAeHpPVij9L+Cg4MJDg4G4OLFiw+dr1atWoFdCf5NJpPx9ttv8/bbbxd63sPDo9BrP/jgAz744INHxvrfOLy9vdm1a1eBY7du3Srw2tHRsdAxbRWR6EkTBEEwkosiSRME4TFEkiYIgmAEaemZxN5KxFSpoEa1qsYORxCEUkgkaYIgCEbwd2T+uCHf6q6YPmH/Q0EQKiaRpAmCIBiBGI8mCMKTiCRNEATBCP6KvL+puljEVhCERxBJmiAIQglLTrlHXMJdzM1Mqe7ubOxwBEEopUSSJgiCUMIe9KLV8nbHxMTEyNEIglBaiSRNEAShhP0ZEQ2I8WiCIDyeSNIEQRBKkCRJhv0664okTRCExxBJmiAIQglKSEohOSUda0tzPKo6GTscQRBKMZGkCYIglKAHjzpr+7gjk8mMG4xQZt25c4cPP/yQhg0b4ujoSK1atejduzd79uwp0nZGjhxJSEhIkdZZmO3bt9O1a1fc3d2pUqUKLVu25LPPPiMxMbFI6i+p+yhqIkkTBEEoQX9dub/0hq+ncQMRyqyYmBj8/f05cOAAU6dO5fjx4/z000+88sorjB071igxaTSa5772s88+Y/DgwdSrV4+wsDBOnDjBrFmziI2N5fvvvy/CKMsekaQJgiCUEEmSDDM76/iI8WjC8/nggw+QJImDBw/So0cPfHx88PX1Zfjw4Rw7dsxQ7saNG/Tr1w9XV1dcXV3p379/gc3MZ82aRYsWLdi8eTMNGzbE1dWVN954g+TkZMP59evX8+uvv6JWq1Gr1Rw9epSYmBjUajWbNm2ia9euODs7s3LlSu7evcvQoUOpXbs2zs7ONG/enDVr1jz2Xs6cOcPXX3/Np59+ysyZM2nRogXu7u74+/uzbNkyRowYYSi7cuVKGjVqhIODA40aNWLVqlUF6lq5ciVNmjTByckJLy8vevbsiVarfeR9AEybNg0/Pz+cnZ2pV68en3zyCTk5OS/8b1RUFMYOQBAEoaK4nZhKWnoWdrZWVHGqbOxwhEL88OvCEm1vcKf/e6byKSkp7Nu3jylTpmBlZfXQebVaDeT/QtCvXz/MzMzYvn07MpmM8ePH069fPw4ePGh41B4bG8uWLVtYs2YNWVlZDBkyhM8++4xvv/2W0aNHc+XKFVJSUliyZAkAdnZ2xMfHAzB9+nRmzJjB/PnzUSqV5OTk0KBBA8aMGYONjQ2HDh3i/fffx83NDX9//0LvZ8OGDVhaWvL2228Xev7B/ezYsYPx48czc+ZM2rdvz/79+xk3bhyOjo4EBgbyxx9/8MEHH7Bo0SKaN29OWloaR44cAXjkfQBYWFgQGhqKi4sLERERjB07FlNTU6ZMmfJM/y7FRSRpgiAIJSQyJv8/t7q+nmI8mvBcoqKikCSJGjVqPLbcoUOH+PPPP/njjz/w8MjvtV2+fDmNGjXi8OHDtGvXDgCtVsvChQuxtbUFYPDgwaxduxYAKysrzMzMUKlUODk9PMll+PDhdO/evcCxd9991/D14MGDOXLkCJs2bXpkkhYVFYWnpyfKJ+xfGxoaSkhICMOHDwfA29ubc+fOMW/ePAIDA7lx4waWlpYEBgZibW0NQL169Z54HxMmTDB87eHhwdixY5k/f75I0gRBECoaQ5Imlt4otZ61Z6ukSZL0VOUiIiJwcXExJGgAnp6euLi4cPnyZUOS5ubmZkjQAJydnUlKSnqqNho1alTgtU6n45tvvmHLli3Ex8eTl5dHXl4erVu3LpL76devX4FjLVq0YPfu3QAEBATg6upKgwYN6NChAwEBAXTt2tWQsD3Ktm3bWLRoEVFRUWRmZqLT6dDpdE8VU0kQY9IEQRBKgF6v51rsbUCMRxOen5eXFzKZjCtXrjy2nCRJj+yt/ffx//ZgyWQy9Hr9U8ViaWlZ4PX8+fMJDQ3l3XffZdu2bRw9epSgoCDy8vIeWYeXlxfR0dGPLVNY3P89Zm1tzZEjR1i5ciWurq588803NG3a1PBotjC///47Q4YMoX379vzvf//jyJEjTJ48+YUmQRQ1kaQJgiCUgOs3bpOdo8HJXo1DZbWxwxHKKDs7Ozp06MCyZcvIyMh46HxqaioANWvWJC4ujpiYGMO56Oho4uPjqVmz5lO3Z2pq+tQ9S+Hh4XTu3Jm+fftSv359qlWrxtWrVx97TXBwMJmZmSxdurTQ8w/ux9fXlxMnTjzU3r/vRaFQ4O/vb5jxmpmZya+//vrI+zhx4gQuLi5MmDCBxo0b4+XlxY0bN57qXkuKSNIEQRBKwJ/3l94QW0EJL+qrr75CkiQCAgL46aefiIyM5MqVK3z//feGR4vt2rWjbt26DB8+nHPnzvHHH3/w1ltv0aBBA9q2bfvUbbm7u3Pp0iUiIyNJTk5+bC+Tt7c3R44cITw8nCtXrjB+/HhiY2MfW7+fnx9jxozhk08+4aOPPuLEiRPExsZy9OhRhg8fzuLFi4H8wf9hYWEsW7aMa9eusWTJEjZu3GgYA/fLL7+waNEizp8/T2xsLBs3biQjI8Mwdq+w+/D29iY+Pp4NGzYQHR3N999/z+bNm5/6vSkJIkkTBEEoAf9sBeVp1DiEss/T09Mw+H/q1Km0atWKbt26sXv3br755hsg/zHg2rVrqVy5Ml26dKFr1644Ojqydu3aZ5q0MmjQIGrUqEFAQABeXl4P9Wb92/jx42ncuDHBwcG8+uqrWFhYEBwc/MQ2pk+fzooVKzh//jx9+vShefPmTJgwATc3N4YNGwZAly5dmDNnDgsXLqRZs2YsXryYr7/+msDAQABsbW3ZuXMnr732Gk2bNiU0NJTvvvuOli1bPvI+AgMDeffdd5k0aRKtWrXi4MGDfPTRR0/93pQEWWpq6tON2iuHIiMj8fHxEXWJukRdoq5irSs27g4ffbmS1NR7rJk3CbXNw0snGCOu0l5XcUtLSyswaF4QjOFx34eiJ00QBKEYZWblMHf5ZjQaHS/V9yqSBE0QhIpBJGmCIAjFRJIkFq7ZQfydFDxcHendqYWxQxIEoQwRSZogCEIx+WnPb5y+EImlhYqxQ3tiqhRLUwqC8PREkiYIglAMzv19jbCfDyOTwehB3XF2qGTskARBKGOKJEmrV6+eYdPSf//p06cPkL9J63/P/XdLC0mSmDVrFjVr1sTZ2ZmgoCAuXbpUFOEJgiCUqDvJqcz/YRuSBMGvtqVRHW9jhyQIQhlUJH3vBw8eLLBI3O3bt2nXrh2vvfaa4ZiPjw8///yz4bWJiUmBOubNm8eCBQtYsGABPj4+zJkzhx49evD7778/cVsHQRCE0iJPo+HrZZvJyMqhcV1venZuZeyQBEEoo4okSbO3ty/wevXq1VhbWxdI0hQKRaEbtEJ+L9qiRYt47733DJu1Llq0CB8fHzZt2sSbb75ZFGEKgiAUK0mSWP6/X4i+mYCzgx2jBnYTG6kLgvDcinxMmiRJrF69mpCQECwsLAzHo6OjqVWrFvXr12fIkCFER0cbzsXExJCQkED79u0Nx8zNzWnZsiUnT54s6hAFQRCKxd5jZzl88iKmSgVjh/XC0sLM2CEJglCGFflitgcOHKBnz54cOXKE+vXrA7B3714yMjLw8fEhKSmJL7/8ksjISE6cOEGlSpU4efIknTp14uLFi7i5uRnqeuedd4iPj2fLli2PbC8yMrIowxcEQXgu0TfvsGDtL2h1evp3b0uTOtWNHVKZVJIL4YrFbIXS4HHfh0U+H3zVqlU0btzYkKABdOzYsUAZPz8/GjZsyLp16xg1apTh+H8fC0iS9MRHBS/yA11aV9kWdYm6RF1lq67Ue5l8/cNuVGbmvNbOj76vvVIq4irrdQlCRVekjzsTExPZtWsXgwYNemw5KysratasSVRUFIBhrNqdO3cKlEtKSsLBwaEoQxQEQShSWq2OeSu3kpKWQU0vV/q/1sHYIQkVQFJSEuPGjaNevXo4Ojri4+NDt27dOHjwoLFDM5qYmBjUajV//PGHsUMpMkWapK1btw6VSkXPnj0fWy4nJ4fIyEhDcubh4YGTk1OBb66cnBzCw8Np1qxZUYYoCIJQpNZtO8DfkbHY2Vrx3pAeKBQmT75IEF7QgAEDOHPmDKGhoZw+fZqwsDA6duzI3bt3i6W9vLy8YqlXeLwiS9IkSeLHH3+kZ8+eDy2ZMWXKFI4dO0Z0dDSnT59m0KBBZGVl8frrrwP5jzlHjhzJt99+y/bt2/n777/5v//7PywtLendu3dRhSgIglCkjp/+i50Hf8fERM77Q3tiZyuWCxKKX2pqKuHh4UybNg1/f3/c3d1p3Lgxo0ePplevXgCEhYUREBCAq6sr3t7eDBo0iLi4uAL1XLlyhb59++Lu7k7VqlXp2LEjf/31FwAjR44kJCSEb7/9ltq1a1O7du2nqvfo0aOo1Wr27t2Lv78/zs7OBAYGcuvWLY4dO0arVq2oWrUqISEhDyWUa9asoVmzZjg5OdGkSRMWLFiAXq83nFer1fzwww8MGjSIKlWq0KBBA8LCwgznGzRoAEBAQABqtZqgoCAA9Ho9c+bMoU6dOjg6OtKyZUt27txZVP8cxarIxqQdPXqUa9eusXTp0ofOxcXFMWzYMJKTk7G3t8fPz4+9e/fi7u5uKDNmzBiys7MZP348qampNGnShC1btog10gRBKJVi4+6wZF3+B/3Ani/jW93VyBEJReHCxq0l2l794B7PfI2VlRVWVlbs2rWL5s2bY2b28CzivLw8Jk2aRI0aNUhOTmbq1KkMHTqU3bt3AxAfH0/nzp1p1qwZW7duxdbWljNnzhRY8/T48ePY2NiwadMmJEl6qnofmDVrFrNmzcLGxoa33nqLIUOGoFKpmDdvHiYmJgwaNIhZs2bx5ZdfAvnj2WfOnMmcOXNo0KABly5dYsyYMSiVSoYPH26od86cOUydOpWpU6eyevVqRo0aRYsWLXB3d+fAgQO0b9+ezZs3U7duXUxNTYH8Jb3mz5/P3LlzadSoEWFhYQwYMIBDhw4VGD9fGhVZkta2bVtSU1MLPbdixYonXi+TyZg0aRKTJk0qqpAEQRCKRWZWDnOXbyY3T0ubpnXp1LaJsUMSKhCFQsGCBQsYM2YMq1aton79+jRr1ozXXnsNPz8/IP9x6AOenp7MnTuXpk2bcuvWLapWrcry5cuxsLBg1apVhmTG27vgzhgqlYrQ0FBUKpXh2JPqfWDy5Mm0bNkSgDfffJMJEyZw6NAhGjZsCMDrr7/O9u3bDeW//PJLpk+fblgr1dPTk+vXr/P9998XSNJCQkIICQkxtLF48WLCw8Nxd3encuXKAFSqVKnAuqyhoaGMGjWK4OBgw3W//fYboaGhhXYslSZit19BEIRnIEkSC9fsIP5OCh6ujrzVN1AsWFuOPE/PljF0796dTp06ER4ezqlTp9i/fz+hoaF8/PHHjBs3jnPnzjF79mwuXrxIamqqoSfs5s2bVK1alQsXLtCiRQtDglaYWrVqFUjQgCfW+0CdOnUMXzs6OhZ6LDExEcifBHHz5k3ef/99xo0bZyij1WoN9RdWr0KhoHLlyoZ6CnPv3j3i4+Np3rx5geMtWrRgz549j7yutBBJmiAIwjPY+utxTl+IxNJCxdihPVGZKo0dklBBmZmZERAQQEBAAB9++CGjR4/miy++YNiwYfTq1Yt27dqxZMkSHBwcSE5OJjAw0DAB4L/JT2EsLS0LvM7MzHxivQ8olf/8XDz4Jea/xx6MN3vw99y5c584WfDfdTyo52nupTBl4ZerIt9xQBAEobw69/c1Nuw8gkwG7w5+DWeHSsYOSRAMfH190Wq1XLx4keTkZD7++GNatWpFjRo1HuptatCgAeHh4c80azMyMvKJ9T4PR0dHqlSpwvXr16levfpDf57Wg17Bf4+rs7GxwcXFhRMnThQoGx4ejq+v7wvHXtxET5ogCMJTuJOcyvwftiFJ0CeoLQ1rexk7JKGCunv3LoMGDaJ///7UqVMHKysrzp07x3fffYe/vz81a9ZEpVKxbNky3nrrLSIiIpg5c2aBOoYOHcqKFSsYPHgwH3zwAWq1mrNnz1KjRo1HDqZ3dXV9Yr3Pa+LEiUyYMAFbW1teeeUVNBoN58+fJz4+nrFjxz5VHQ4ODpibm7N//37c3d1RqVTY2toyevRoZs2ahZeXFw0bNiQsLIzw8HAOHTpUJLEXJ9GTJgiC8AR5Gg1fL9tMRlYOjet607NzK2OHJFRglpaWvPTSSyxevJigoCBatGjBp59+Su/evVm5ciX29vYsWrSInTt30qxZM2bPns3nn39eoI4qVaqwa9cuNBoNXbt2pW3btixduhSF4tF9N09T7/MaOHAgoaGhhIWF0bp1awIDA1m1ahUeHh5PXYdCoWD27NmsXr2amjVr8sYbbwAwYsQIRo8ezdSpU2nRogU7d+7kxx9/LPUzO6EY9u4sS0rrViiiLlGXqKv01HXlyhX2nYzg8MmLODvYMXP8m8+9cXppvcfSWldxE3t3CqXB474PRU+aIAjCY/x2Nj9BM1UqGDus13MnaIIgCM9KJGmCIAiPcOX6TX7adwqAt/sF4VHV0cgRCYJQkYgkTRAEoRDJKfeYu3wLWp2ewHZ+tPar8+SLBEEQipBI0gRBEP4jJzeP2Us2kJKWgZe7E/1f62DskARBqIDEEhyCIAj/otfrmbfyJ2Ju3sHF0Y7Br7VBoTAxdliCIFRAoidNEAThX37cso+zf17F2tKcD0eEYGmuevJFgiAIxUAkaYIgCPf9cvg0uw+dRqGQM3ZYT1wcxY4CgiAYj0jSBEEQgD/+usoPm/I3XH77jSBq+zz9IpqCIAjFQSRpgiBUeNE3E/h2xVYkCXoFtqJt03rGDkkQBEEkaYIgVGwpaenMWbKBnFwNrZrUJvjVtsYOSRCE5zBy5EhCQkKMHUaREkmaIAgVVk5uHnOWbCQ5JR3f6q6M6B+ETCYzdliC8FhJSUmMGzeOevXq4ejoiI+PD926dePgwYPF3nZQUBDjx48v9naexxdffMGSJUuMHUaREktwCIJQIen1ekJXbScq9jZO9mrGvdULU6XS2GEJwhMNGDCA7OxsQkNDqVatGklJSRw/fpy7d+8aOzSjKo/7sIqeNEEQKqS12w7y+4UrWFqo+HBEH2ytLY0dkiA8UWpqKuHh4UybNg1/f3/c3d1p3Lgxo0ePplevXoZyYWFhBAQE4Orqire3N4MGDSIuLs5w/ujRo6jVag4fPkyHDh1wcXGhXbt2nDt37pniyc3NZeLEifj4+ODk5MTLL79MeHi44bxOp2PUqFHUr18fZ2dnGjduzLx589Dr9QXKTJkyBQ8PDzw8PJg4cSJjx44lKCjIUKawHrz/Pt787+ugoCDGjRvHp59+SvXq1fH29mbKlCkF2i7tRE+aIAgVzr5jZ/l5/0lMTOSMHdaLqs72xg5JKCVCRs0s0fbCQj96pvJWVlZYWVmxa9cumjdvjpmZWaHl8vLymDRpEjVq1CA5OZmpU6cydOhQdu/eXaDc9OnTmTZtGs7OzkycOJHhw4dz8uTJp37s/8knn/DTTz8RGhqKp6cnCxYsoHfv3pw5cwZnZ2f0ej0uLi788MMPVK5cmbNnzzJmzBjs7OwYOHAgAKGhofz444/MmzePOnXqsGzZMjZu3Ej9+vWf6b0pzMaNG3n77bfZs2cPFy9eZNiwYTRs2JDevXu/cN0lQfSkCYJQoZy/FMX3G34FYPjrgdSt4WncgMoySUKmTUWeE4ki/RjKe/uNHVG5p1AoWLBgARs2bMDDw4OOHTsyZcoUTp8+XaDcgAEDeOWVV/D09KRJkybMnTuX8PBwbt26VaDc5MmTadu2LTVq1GDChAlcuXKlQI/b42RmZrJixQqmTZtGp06d8PX15ZtvvsHBwYHly5cDoFQqmTx5Mo0bN8bDw4MePXowZMgQNm/ebKhn0aJFvPvuu/To0YMaNWowe/ZsHB0dX/Cdyufr68vkyZPx9vamR48etGnThsOHDxdJ3SVB9KQJglBhxMbd4dsVW9DrJbp3bEG75g2MHVLZIGmRaZORa+4g195BpklErr2DXHMHpLx/yskUIA0yXpxF4Fl7toyhe/fudOrUifDwcE6dOsX+/fsJDQ3l448/Zty4cQCcO3eO2bNnc/HiRVJTU5EkCYCbN29StWpVQ1116tQxfO3s7AxAYmJigTKPcv36dTQaDc2bNzccMzExoWnTply+fNlwbMWKFfz444/cuHGDnJwcNBoNbm5uAKSlpXH79m1eeuklQ3m5XE6TJk0eSiifx7/vD/LvMTEx8YXrLSkiSRMEoUJIvZfJnCUbycrOo0XjmrzerZ2xQyp99NnINYnItHeQaxKRaxPuJ2TJQOHjeCS5JXqlI5LCEb3SEVlW2RnvU5aZmZkREBBAQEAAH374IaNHj+aLL75g9OjRaDQaevXqRbt27ViyZAkODg4kJycTGBhIXl5egXqU/5os8+AR54OE7kkelCvs0eiDY1u2bGHSpEl89tlnNG3aFBsbG5YtW8Yth8YpAAAgAElEQVTPP//8TPcrl8sfikur1T7xOuV/JgPJZLKnvr/SQCRpgiCUe3kaDV8t3Uhicho+nlX4vwFdxVIbkhZ5bgwmOZeoqvsT8zgNMl36IwrLkBSV0Ssc0SsdDAmZXuEAJgUnXEi3I4s/duEhvr6+aLVacnJyiIqKIjk5mY8//hhPT08Atm/fXuRtVq9eHVNTU8LDww3t6HQ6Tp06ZRjzFR4eTpMmTRg+fLjhuuvXrxu+trW1xdnZmdOnT+Pv7w/kJ39nz57FycnJUM7e3p7bt28XaP/PP//E3d29yO+rNBFJmiAI5ZokSSz4cQeR0XE4VLblg+HBFXepDV0WJjmXMcm5hEnOFWT6bADMyUSmswSZEr3C4V89Yw7oFY5ISnuQVdD3rJS5e/cugwYNon///tSpUwcrKyvOnTvHd999h7+/PzY2Nri6uqJSqVi2bBlvvfUWERERzJxZ9BMiLC0tGTJkCNOnT6dy5cp4eHiwcOFCEhMTGTZsGADe3t6sX7+evXv3Ur16dTZv3sxvv/1WYLmMESNGMHfuXLy9valduzbLly8nISGhQJLWtm1bJk2axK5du/Dx8WHlypXcunVLJGmCIAhl2f92HOLEH5exMDflwxF9UNtUoKU2JAmZNgGT7Esosi8hz4sB/nnUo1c4ojOvRVy2EleXl5BM1FDRexhLOUtLS1566SUWL15MVFQUeXl5uLi40Lt3b8MSFfb29ixatIhPP/2U5cuXU6dOHT7//PMCS3Q8L71ej4mJieH19OnTAXjnnXdIS0ujfv36bNq0yTC+7c033zTMqpQkiW7duvHOO++wZs0aQx2jRo0iISGB0aNHAxASEkJwcDARERGGMv379+evv/5i1KhRAAwdOpSgoKByvzacLDU1tew8nC1ikZGR+Pj4iLpEXaKuclrXoRPnWbRmJ3K5jEn/15f6NauViriKtS5JgzwnCkXOJUyyLyHTpfzrpAk6VXV05rXQmdXM7yErqbhKobS0tHK5AGpxatKkCQMGDOC9994r1nbGjx/P33//zc6dO4u1ndLgcd+HoidNEIRy6c8r0Sxdn78m1NA+nZ4rQSsrZLp7mGRHYJLzNyY5kQVmXEpyK3TmNdGZ1UJnVgPkKiNGKpRVCQkJ/Prrr1y7do127doZO5wKQyRpgiCUOwnJqazYcgSdTk+XDs14uXVjY4dUtCQJlZSAMi0ak5zLyPNuFDitV1a531tWC72pm3iEKbywTp06ATBnzhwaNmxo5GgqDpGkCYJQrqSlZ7Jswz5y8iReql+Dft0DjB1SkZJpElAlr8VNfw3lvfvj62RKdCrvfx5jKtTGDVIod551u6gX9eWXX5Zoe6WVSNIEQSg3cnLz+GrpJpJTMqhXy4tRg7ohl5efjVVMss6hursJpDy0WKK1bIbOvDY6lRfITY0dniAIRUwkaYIglAtarY65y7dw5fot1DYWTHg7GDNVOUlcJC2mqT+jyPgNAK1FI2KyG+BdqbaRAxMEoTiJJE0QhDJPr9czf9U2zl+KwtbagkHdW2Nna23ssIqETJuKKnkN8rxYwIQ8u25oLZsj3b1q7NAEQShmIkkTBKFMkySJpet3G9ZC++idvmiyH7Vyftkiz7mCKnkdMn0Wkoma3Mr90avK9+KdgiD8o0gGa8yaNQu1Wl3gT40aNQznJUli1qxZ1KxZE2dnZ4KCgrh06VKBOlJTUxk+fDju7u64u7szfPhwUlNTiyI8QRDKKUmSWL11PwfDz2OqVPDhiBA8XZ2NHdaLkySUafswS/wemT4LnZkv2U5jRIImCBVMkY2o9fHxISIiwvDnt99+M5ybN28eCxYsYPbs2Rw4cAAHBwd69OhBevo/v+0OGzaMCxcusHHjRjZt2sSFCxd4++23iyo8QRDKoa2/HmfngVMoFHLGvdWLml5uxg7pxemyUCWtQHlvDwAam47k2r/50B6ZgiCUf0X2uFOhUBTYZ+sBSZJYtGgR7733Ht27dwdg0aJF+Pj4sGnTJt58800iIiLYt28fv/zyC82aNQPgm2++ITAwsEytXi0IQsnZfeh3wn4+gkwGowZ2p2FtL2OH9MLkeTdQJa1GpktFkluQW+l19Oa+xg5LEAQjKZJtoWbNmsV3332HWq1GqVTi5+fHJ598gqenJ9HR0TRs2JADBw7QuPE/C0r26dOHSpUqsXjxYlavXs2kSZO4ceMGsvuLLkqShKurK7Nnz6Z///6PbDsyMvJFwxcEoYz5/eJV1u04BkDfoJY0a1DjCVeUcpKEjXQRB+kwMnTk4Mxt+atoZTbGjqzEleQv5WVxW6iQkBBycnLYtm3bQ+ciIiJo1qwZW7duJSDgxdcHHD58OBkZGaxbt+6F6xIerdi3hfLz82PhwoX4+PiQlJTEl19+ySuvvMKJEydISEgAwMHBocA1Dg4OxMfHA3Dnzh0qV65sSNAAZDIZ9vb23Llz57Ftv8gPdGndr07UJeoSdT3a7+cj2HHoHJaWlvTv0Z6uHZqXirieuy59LqYpW1FknQXM0Fq1QKbuSjXZ4z+eS9s9SpJESp6e5Ngo8fSjGA0cOJD+/fsTExODh4dHgXOrV6/Gzc0Nf39/I0X3aBqNBqVSaewwypwiGZPWsWNHevToQd26dWnXrh1hYWHo9foC2bfsP9uSSJL0UFL2X/8tIwhCxXYx4jrfrtyKXi/Rs3OrQhO0skSmScTszoL8BE1mSm6l18mz6wFPSNBKm6QcHbMupjDlbDLZOmNHU7516tQJR0dH1q5dW+C4RqMhLCyM/v37I5fLuXnzJoMHD8bDwwNPT09CQkK4fv26ofyMGTNo3bo1GzZsoEGDBri5udG/f39SUlIM5zds2MCuXbsMEwLDw8OJiopCrVZz4cIFQ11arRa1Ws3PP/8MYCizZcsWunTpgpOTE6tXryYpKYkhQ4ZQu3ZtXFxcaNGiBevXry+Bd63sKpZPAisrK2rWrElUVBRdunQB8nvLXF1dDWWSkpIMvWuOjo4kJSUVSMokSSI5OfmhHjhBECqmyOu3+GrpJrRaPZ39m9AnqK2xQ3ohJlkXMb27AZmUi17hQK79ACRl2ZqZKkkS++OzWXMtnWydhJVCRkLek68rzSxuTCjR9rLc5jxTeYVCweuvv866deuYOHGiYUeN3bt3k5ycTL9+/cjIyKBLly60bt2anTt3Ympqyrfffkv37t05efIk5ubmAERHR7Njxw7WrVtHeno6Q4cO5fPPP+err77ivffe48qVK2RlZbFgwQIAKlWqxI0bNx4Z239NmzaNGTNmEBoaiqmpKdnZ2TRq1Ij33nsPGxsbDhw4wOjRo3F1daVNmzbP9D5UFMWyX0pOTg6RkZE4OTnh4eGBk5MTBw8eLHA+PDzcMEmgadOmZGRkcOrUKUOZU6dOkZmZaSgjCELFFXPrDl8sCiMnV0ObpnUZ3PuVstvLLmlRpv6MKnk1MikXrXl9cpzeLXMJ2p1sLTPOp7Dsyj2ydRJN7VV8/ZI9nubGjqz8GzBgADdv3uTQoUOGY2vWrKF9+/a4urqyadMmlEol8+fPp27dutSoUYPvvvuO1NRU9u7da7hGr9ezcOFC6tSpQ/PmzRkwYACHDx8G8jtbzMzMMDU1xcnJCScnp2d+XDly5Ei6deuGp6cnVapUwc3NjdGjR1O/fn08PT0ZMmQIr776Klu2bCmS96U8KpKetClTptC5c2dcXV0NY9KysrJ4/fXXkclkjBw5kq+//hofHx+8vb356quvsLS0pHfv3gD4+vry8ssv8/777zNv3jwkSeL999+nU6dOYmyDIFRwtxPvMnPBejKycvCr78OIN4LKbIJmImVglrgUeW40YEKe+lW0Vq2hDN2PJEn8eiuL9dczyNFJ2CjlDPGxobmDCplMRqKxA3xBz9qzZQxeXl60bNnSkJjFx8ezf/9+VqxYAeRvhh4VFVXg6RVAVlYW0dHRhtfu7u5YW/+zM4eLiwuJiUX3L9ioUaMCr7VaLXPnzuWnn34iPj6evLw8cnNzi2SSQ3lVJElaXFwcw4YNIzk5GXt7e/z8/Ni7dy/u7vkLL44ZM4bs7GzGjx9PamoqTZo0YcuWLQW+OZYtW8aHH35Iz549AQgMDGTOnNL/wyIIQvG5m5rOjND1pN7LpG4ND8a8+RoKhYmxw3ou8pxruOvXIs+VI5nY3N89wNPYYT2T+CwtSyLSuJSmAaClgxmDfWywNS0/m9iXFQMHDmTMmDGkpKSwbt067OzsePXVV4H8HrKGDRuybNmyh66rVKmS4WuFomAKIJPJ0Ov1j233weNVSfpnYQiNRlNoWQsLiwKvv/32WxYvXsysWbOoVasWVlZWTJ06lXv37j22zYqsSJK0B9n7o8hkMiZNmsSkSZMeWcbOzo6lS5cWRTiCIJQD9zKy+Dx0HYnJaXh7uvDB8N6YlsXZYZKEIv0wpmm70ZGNTlWf3Mr9wMTK2JE9Nb0ksetmFmHX08nTg61SzrAaNjR1MDN2aBVW9+7dmTBhAmFhYaxZs4a+ffsaHkc2aNCA7du3Y29vj43N8y/jolQq0ekKzgSxt7cHMKzcAHDx4sWnqu/EiRO8+uqrhISEAPmJ3tWrV3F0dHzuGMs78euPIAilTlZ2Ll8sCuPm7WTcXOyZOLIv5mYqY4f17PQ5qJLXYJq2C5BIkb1ErsNbZSpBu5WlZeofd1l9LT9Ba+NkxtdN7UWCZmTm5uYEBwfzxRdfcP36dQYMGGA4FxISgp2dHW+88Qa//fYb0dHRHDt2jEmTJhV43Pkk7u7u/PXXX1y9epXk5GS0Wi1WVlY0atSIb775hsuXLxMeHs7UqVOfqj4vLy8OHTrEyZMniYiIYOzYsdy6detZb71CEUmaIAilSp5Gw5dLN3ItJh4nezWTR72OtWXZG40u09zGLGE+JtkXkWRm5NoPIlneCmRl42NXp5fYFpvBh6eTuHJPg52pnA/rqRlVS421smzcQ3k3YMAAUlNTadasGb6+/+xMYWVlxe7du3F1dWXgwIE0bdqUd955h4yMjGdavPfNN9/Ey8uLdu3a4eXlxe+//w7AwoUL0el0BAQEMG7cOCZPnvxU9U2cOJEGDRrQq1cvgoKCsLW1pUePHs920xVM2VqMRxCEck2r1fHN91v5OzIWO1srpox+Aztb6ydfWMqYZJ1HdXcjSHnolc7kVh6IpLQHysYOKbEZGhZH3ONaev5Yo3bO5gz0tsZSIZKz0qRhw4akpqYWes7Z2ZnFixc/8topU6YwZcqUAscGDhzIwIEDDa8dHR0L3dmgVq1a7Nmzp8Cxf8dRvXr1QuOys7N7aH034fFEkiYIQqmg1+tZuHoHZ/+8irWlOZNHvY5jZbWxw3o2khZl6m6UGUcB0Fo0JM+uF8jLxqNarV5iW2wmW2Iy0EpQWSVnuK8tDSuVjfgFobwRSZogCEYnSRKb95zkfMRNzFRKJv1fCG4uZWsha5nuHqrkNf9aXqMLWquWZWZ5jeh0DYsi0ojO0ALwsos5/byssRC9Z4JgNCJJEwTBqLRaHWt/OsBvZyNQq22Y8HYfvDyqGDusZyLPvY4qeQ0yXXqZW15Dq5fYnSTjRFwyOgkczEwY4WtDXTvReyYIxiaSNEEQjOZaTByL1+4kNi4RuVzG+0N6UqeGx5MvLC0kCUXGcUxTdwI6dKrq95fXKBvj6GIyNIReSuPSXRmWlhBY1YK+1a0wMxG9Z4JQGogkTRCEEpebp2HDziPsPHASSQJnBzs6t25Dk3plaIcRfS6mKZtQZJ0HQGPdFo1tIMhK/2K70v11z9ZFpaOVwF4pMaFhJWqrTY0dmiAI/yKSNEEQStRfV2JYun4XtxNTkMmgS4dm9AlqS2xMtLFDe2oyTSKqpFXItXdAZkpupT7oLOobO6yncjdXx8LLaVxMyd8J/WUXc1qQLhI0QSiFRJImCEKJyMrOZe22A+w79gcA7lUcePuNILw9y9b4M5OsPzG9G4ZMykWvcCTXfiCSsmysmH4yMYdlEWmka/P33Hzb1wY/ezMiI+8YOzRBEAohkjRBEIrd2T8jWR72C8kp6SgUcnq80orXXmlZtvbhlHQo0/agTD8IgNa8PnmVgsvE8hrZWj0/XE3n0O1sABpWMmWkry1qVRl6/wWhAhJJmiAIxeZeRharNu/l2O9/AeDt6cLbbwThXqVs9DwZ6DJQJa/FJPcaICdP/SpaqzZlYnmNK2l5hF5KIyFHh6kc+lW3plNVC2RlIHZBqOhEkiYIQpGTJInws5f4YdMe0tKzMFUq6NOlLUEBTZHLy9bMQZUUj3nCBmS6NCS5NbmV+6E3q27ssJ5Ip5fYEpPJltgM9BJ4WCkYXUuNm6X42BeeLCYmhgYNGnDw4EEaNWpk7HAqrLL1aSkIQqmXkpbOV8s2MW/lT6SlZ1HHx50vPxpG1w7Ny1aCJmlRpB/BVb8JmS4NvaknOc5jykSCdjtby9Rzd9kUk4EkQVc3Sz5vXFkkaOXEyJEjUavVjB49+qFzn3zyCWq1mpCQkBdqw9XVlYiICOrVq/dC9QgvRvzECoJQJCRJ4mD4edb8tJ/MrFwszE3p1709HVo1KluP1iQtiszfUd47iEyXigYdGqtWaNRBICvdH5mSJHHodjY/XE0nRydRWSXn/2raioVpyyFXV1e2bt3KF198gaWlJQBarZawsDBcXV1fqO68vDxMTU1xcnIqilCFF1CGfq0VBKG0SkhKYcb8dSxZt4vMrFwa1/Xmq4+G83LrxmUnQZO0KDJOYB4/B9OUrch0qeiVzsTLu6Kx617qE7R0jZ5v/kplccQ9cnQSLRzMmONnLxK0cqpOnTpUr16drVu3Go79+uuvqFQqWrdubTh29uxZevToQfXq1XFzc6Nz586cOnWqQF1qtZply5bRv39/qlSpwqeffkpMTAxqtZo//sifjX306FHUajWHDx+mQ4cOuLi40K5dO86dO1cyN1xBle5PHUEQSjW9Xs/Og6cI23GI3DwtNlbmDO79Ci2b1C5byVnmaZT3DiDTpQKgVzqjsXkZnXk9MtOvGjnAJ7twN5eFl9NIydNjbiJjiI8NbZzMys6/QSkScuh2ibYX1s75ua8dMGAAa9eupX///gCsWbOGfv36ER0dbSiTnp5OSEgIX3zxBTKZjGXLlhEcHMzZs2epXLmyodzs2bP55JNPmDFjxmPbnD59OtOmTcPZ2ZmJEycyfPhwTp48Kb7XiolI0gRBeC434hP5bvUuklLzl3Vo1aQ2g3p3xNba0siRPaVCkzOn+8lZ/TIxczNPJ/G/6+nsvJkFgK+NklG1bHE0Fx/tFUFwcDAff/wx165dw8rKiv379zNnzhxmzpxpKOPv71/gmjlz5rB9+3b27dtXYNxajx49GDhwoOF1TExMoW1OnjyZtm3bAjBhwgQ6d+5MXFwcVatWLcpbE+4TP8mCIDyT1HsZbNx1lP3H/yAjIxPXKk681Tew7GzpJGlRZJ65n5ylAKBXOKKx7VhmkjOAuFxYejaZ2EwtJjII9rSim5slJvKyEX9p9SI9WyVNrVbTpUsX1qxZg62tLa1bt8bNza1AmcTERD7//HOOHj1KYmIiOp2O7Oxsbt68WaDc087grFOnjuFrZ2dnQxsiSSseIkkTBOGp5OTmsWPfCX4+cJKcXA1yuYxWjX15d2gfLC3MjB3ek0laFJlnUd7bX0hyVg9kZWOIbrpGz764LFbFylFZaHExN2F0LTVeNkpjhyYYQf/+/Rk5ciSWlpZ89NFHD50fOXIkd+7cYebMmbi7u6NSqejWrRt5eXkFyj2YfPAkSuU/32cPHnFKkvQCdyA8jkjSBEF4LJ1Ox4HfzrNx91HS7mUC4Fffhze6BZCVnlL6EzRJiyLzD5T39v0nOXvwWLP0J2eSJHE1XcPeuGzC72STpwetBK+6mDPQ2xozk9J/D0Lx8Pf3R6lUkpycTFBQ0EPnT5w4wRdffEGnTp0AuHPnDgkJCSUdpvCcRJImCEKhJEnizMVI1m47QFzCXQB8PKvQ77X21PJ2ByAyPcWYIT6eITnbj0yXH39ZS85ydHqOJeSwNy6L6Ayt4Xh9O1MaqNPp4mtrxOiE0kAmk3H8+HEkSUKlengmr5eXFxs2bMDPz4+srCw++eQTTE1NjRCp8DxEkiYIwkMir99i7bYDXLp6AwBnBzv6dm1H80Y1S/8sLkmLtf4vzG9vQaZNBkCvcMifEGDRoEwkZ7EZGvbFZXMkIZtsXf6jJGuFjHYuFrxcxRxncwWRkclF0pYkSWh0GjTavCcXFkola2vrR54LDQ3lvffeo127doYZmcnJRfO9IxQ/kaQJgmBwO/Eu/9txiPCzlwGwtjSnV2BrOrZuXPo2Q5ckZLpU5JoEZJoE5NoE5Jr8P05SCjKt5f3krAM6i4alPjnT6CVOJub3ml1O0xiO+9oo6VjVgmb2ZpiaFF2CLEkSF2JPs/XUamLio7A8/uKzck0VKka2/LgIohMeZ9GiRU99vl69euzfv7/A+b59+xZ4nZqa+lAdHh4eBY63adPmoXL/LSMUPZGkCYLAvYwstvxyjL3HzqLV6jFVKng14CW6vdzC+GPO7idjsvsJ2L+TMaTCe3/yqISiUo8ykZwlZGvZF5fNodvZ3NPoATA3kdHGyZyXq5jjYVX0EwIS791m04kf+OtG/kKlJnIFSpMXb0dRBHUIgvAPkaQJQgWWp9Gw6+DvbNv7G1nZechk4N+sHiFd/KlsZ1OywUgSMm0qMs3tp07GJLkVeqUTktIJvdIJvSL/79ioOHwsS++SIDq9xB93c9kTl8X5u//cm6eVgo5VLGjlaIa5ouiTS402jz0XtrHvwjY0Og0WKkuCGvfBWVEN3xq+z1WnJEnk3EkkI/Ym2oxMMoo4ZkGoyESSJggVkF6v5+ipPwnbeZjklHQAGtauzhvd2+NR1bHkApE0mGT/hSLzDNX1f2IeX3hPzKOSMUzKyMK596VpYXN0Bvvjs0jOze81U8qhhYMZr1S1wNtaWWxj/v6MPcumkz+QdC9/Zl8zn7Z0f6kfNuZqIiMjn7oevU5H9u0EMmNukhFzg4wbt9Bl5wAgMzHBoterxRK/IFREIkkThApEkiQuR91i6aZDxN5KBMDT1Yl+r7Wnfs1qJRUE8rwYFJlnMMm+gEyfv2OBnDwkufpfyZjz/WTMEUysSia2YnIzU8uWmAz2XZdjbpnf1+RibsLLVSzwdzbHWll8j2ST0xPZfPIHLsScBqCKnTt9Wg7B27nWU12v12jJuhVPRuwNMmJukHkzDn2epkAZU1trLN3dsPJwJVmsmSUIRUYkaYJQQcTcusPqrfs4ceYvLC0tsa9kQ0gXf9q8VLdEZmzKtCkoMs+gyDpjmHUJoDd1Q2vRhOvZ5lSv+nSrnpcVcVlaNsdkcDwhhwepSzN7FR2rWlBXbVqs77tGp+HAxZ/55fwWNNo8zJTmBDUOpk2tTihMHv3Rr8vNI/PGLTJib5AZc4PMW7eRdLoCZVSVK2Hl4YqVuytWHm4obW0M95LyDL1ygiA8nkjSBKGcS0vPZMPOI+w//geSBOZmSvq91p7O/k0wVRbzQG99LibZF/N7zXKvGQ5LJjZoLRqjtWyCpHQCQHe7/Pznfidby6aYTI4mZKOXQCGD9i4W1Nem81Jtu2Jv/9Kt82wMX8mdtHgAmlRvRc9mA7C1eLhtXU4OOdE3uBl1g8zYm2TFJ8C/e8NkMsydHbFyd8XS3RUrD1eUVmW7Z1MQygqRpAlCOaXRaNl16He2/nqc7Jw85HIZndo2ppFvVRrWr1t8DUsS8txr+b1m2Rf/GfQvU6I1r4PWogl6M59SP+vyeSTn6NgSk8HB29noJJDLoL2LOT09rHAwMyEysnhXek/JTGbziVWciz4JgJO6KiEthlCjysP/3trsHO6EnyLx5BnSU1LR3t8WSGYix8LF+f7jSzcs3aqiMH/yDF9JksjJFWutCUJREkmaIJQzkiRx8txl1v50gDvJaQA0quNF/x4dcHW2f6ZB4s9CpklEkXUGReZZZLp/1k7SqzzRWvihtagHcvNiadvYUnJ1bI3JZH98FloJZIC/szk9PSxxNi/+j1mtTsuBP3fyy7nN5GlzMVWoCGzUi4A6QQ892tTl5ZF48gx3fjuFLicXAKWzA86NGmLl4YaFqwsmT7kivSRJ3E29x7XrMSTGX0Ehy6Gad9Mivz9BqKhEkiYI5ci1mDhWb91v2CnAzcWeAT1fpkGt6sXSnlzKRZFxAkXmGeR5MYbjkokdWssmaC0aIynti6Xt0iAtT8+22Az2xmWRp89Pzlo5mtHb04oqFiXz8Xol7k82hK/kdupNABpVa07PZgOxs6xcoJxeoyXpzDkSjp1Am5kFgHU1d1wC2hCXk4WLz9MvWXI39R7Xoq6TePsKKikJO/MsqlpIyOQm5GRnFd3NCUIFVySfInPnzmXHjh1cvXoVU1NT/Pz8mDp1KrVr1zaUGTlyJOvXry9wnZ+fH/v27TO8zs3NZcqUKWzevJmcnBzatm3L119/TdWqVYsiTEEot+6mprN+xyGOnLwIgI2VOX2C/GnfsgEmJsWwU4AuE9O03VTTH8E05f6jMJkpWov6+Y8zVdWhtG8f9QLSNXp23Mjkl5tZ5Orzx281s1fR29MK92JYfLbQGHLSWHnwO85EHQfA0daF3s0HU9u1YYFyep2Ou+f+JOHob+Sl5S+3YunqgktAW6yre+QXeore1fwes+sk347AVEpCbZZNFXMJuVyOhbk5FjbO2Dn6cjOp/D3GFoqWWq1m1apVdO/evVjbOXr0KF27duXatWtUrlz5ucsYU5EkaceOHWPo0KE0btwYSZKYOXMmr732GidPnsTO7p+Bqu3atWPJkiWG1//d5HXSpEns2rWL77//Hjs7OyZPnkxISAiHDx8unv9oBKGMy83TsGPfCbbvCyc3T4tCISew3Uv0eKVV8ewUIEmYZCjE9oMAACAASURBVJ3GNHUnMn0WMvToVN5oLf3QmdcB+cMbPJcnmVo9P9/IZNfNLHLu76npV1lFsKcVntYlk5zp9XoO/72b/x1diVJlglJhSucGPWlfr0uBXQMkvZ6UPy9x+/Bxcu/mP342d3LAJaANNjW8nmpm6d3Ue0RdjyI5IQKVlIStKgdns38nZlVQO/piZuOOXHF/zbrk8jMBpLRKSkpi1qxZ7Nmzh4SEBGxtbalVqxbvv/8+AQEBxdp2UFAQtWvX5ssvv3zuOiIiIlCr1S8Ux8aNG1m6dCl///03kiRRq1Ythg8fTkhIyDPV06xZMyIiIqhUqdILxVNciiRJ27JlS4HXS5Yswd3dnRMnThAYGGg4rlKpcHJyKrSOtLQ0Vq9ezYIFCwzfZEuWLKFevXocOnSIDh06FEWoglAuSJLE0d//ZP32Q9xNze8dadbQlze6B+DsUDwfNjLNHUxTtmCSGwWATuVNTHZDPB3L/xikLK2e3Tez2Hkzk0xtfnLWsJIpfTyt8bIpua2QbiZHs/74UmISr5GnzaFJDX96NRtMZWsHQxlJkki7HEn8oWPk3EkC8pfMcGnXCnWdmk9Mzu6m3uN6dBTJty+jkpKwMcvBSQVyuRxzcwssbapi5+SLytoduaJ8jjEs7QYMGEB2djahoaFUq1aNpKQkjh8/zt27d40d2lN5VB7wtKZOncqiRYuYNGkSCxcuRCaT8fPPPzN69GguXbrEtGnTnrouU1PTF46nOMlSU1OLfOXB27dvU7NmTXbv3k2LFi2A/MedO3fuxNTUFFtbW1q1asXHH3+Mg0P+h8vhw4fp3r07V69exd7+nzEszZs3p1u3bnz00UeFtlVcg6AFobS6fjOBn/aeIjY+f60xV+dKdH+5Kd7uzsXSnkzSYiedwk46gwwdOsxJkvmTLvMt1480AbJ18FsaHLwrI1Off681LCQ6V5b4f/bePEqOstzj/9TW+zb7TDLZl0ky2VgSQBAIoiwK6CVccQEPBxeuP0A5yi4gECAoB8EbICj+lMvFnwiCoAgiW+SyB0kIhCSTTDKZfel9q67t/f3RnU4mG1kmkGB/5tSp6u633n6rp7vqW8/zvM8z4WPUJ6Zt8uqGf/DGxhdxHJuQJ8KprQuZXN9abiOEwOjuJbt8JeZg8buhBPz4D5+FZ8pEJHnXbsh0Nk9/fy9GtougliTkLSarlSUJl8uF7KrDHRhdTCwsHVhROmUvYuP2l2QySTgc/tjebyRIJBKMHz+eP//5z5x44om7bPfII4+wdOlS2tra8Hg8HHvssdx2222MGjUK2Orme/LJJ7nppptYvXo1LS0t3HXXXcydO3eX/e7OktbR0cGcOXN46aWXOOywrTkPt3dvbv/49ttv56GHHmJgYIBIJMKCBQuGed225Z133uFzn/sct956K9///veHvXbvvfdyzTXX8MILL3DEEUeUj/EPf/gDixYtoq2tjWnTpnH33XeXj3F7d2cymeTyyy/nxRdfJJ1O09jYyPe+973ye0UiEX72s5/x/PPP88orr1BTU8N11103zIL3wQcfcM011/Dmm2/i8Xg47bTTWLx48S6/a7v7Hh6QyNarrrqKWbNmMX/+1jvsk08+mTPOOINx48axefNmFi1axJlnnsnLL7+M2+1mYGAARVF28AnX1dUxMDCwy/fanx90W1vbiJ0QKn1V+jrQfYWr6/j9ky/y+r/WANA8qoGvnXEixx81a6+Sou7NuGS9DXf8qVLyWQ+W/yiM8Gk0Kj4a97KvkRzXSPSl2w5DukOsYBMt2MQKDkMFu/hYd4gZNllLkM1m8fv9HBnW+M8JQWZE9mzm476Oa4d9elfzp1d/TX+yB5/Py/HTT+GMI8+lc1NXua/M5i56X3wFs6MTF+BvqKPhs8dQc/gcZHXnp3m9UKBt/QYGu1chGd00+R1wbbGYhfGGxlDTOB1PsBlJ2fNjHsn/4yfBxb/ZO3fZ/rLkwkf2qn0gECAQCPC3v/2No48+Go9n52ENhmFw9dVXM3XqVKLRKDfccAMXXnghzzzzzLB2N954Iz/96U9pbGzkqquu4rvf/S5vvvnmx5LgGuDJJ59kyZIlPPDAA8yYMYOhoSHefvvtXbb/4x//SCAQ4Nvf/vYOr1144YXccsstPPbYYxxxxBHl56+77joWL15MU1MTt99+O//5n//JihUr8Pl8O/SxaNEiVq9ezSOPPEJtbS2bN28mGo0Oa3Pbbbdx/fXXc+utt/LnP/+Ziy66iKlTp3LYYYeRy+VYuHAhhx12GC+88ALxeJwf/OAHXHzxxTz00EN7/fmMuEi75ppreOONN3j22WeHxZGdffbZ5e3W1lbmzp3LrFmz+Pvf/86ZZ565y/6EEB/bl6VChYORXL7AX196h3c+7MA0bVyayhknH8WZJx+Dx73vgmG32Glcib+g5lYA4GgNGFX/geP+mEpH7ScFp5jtf0gvia6CQ3QbMRYt2GW35e5wydDgFXx7dhWzqg5shYDtyRWyPLX89/zfmuLkqsZIM18/7rtMbNhaCD3X20fvi6+QWr8RAMXroeEz86mdf/hO02gIIejuHaB9w/uY6fVUeTJUawJHcfD5Q/jC46htnI47OBpJ/vjcuBX2HFVVueeee/jBD37Agw8+yOzZsznqqKP48pe/zJFHHllud95555W3x48fz5133sn8+fPp7u4eNhnv2muv5fjjjwfgiiuu4NRTT6Wnp+djm7DX2dlJQ0MDJ510EpqmMWbMmGFWuO3ZsGED48aN2yGmHYohVePHj2f9+vXDnr/88svLIVP33HMPM2bM4LHHHuP888/f6Xhmz55dFnnjxo3boc0ZZ5zBBRdcAMCPf/xjXnnlFe677z5+9atf8eijj5LNZrn//vsJBoMA3HXXXZxxxhm0t7czceLezbQfUZF29dVX8/jjj/OXv/yF8ePH77ZtU1MTo0aNor29GN9SX1+PbdtEo9Fh7s6hoSE+85nPjOQwK1Q46BFCsGZDJy+/8R5vvPsh0VgCv9/PcfNa+fqZC6ipCh2oN0bNvomWfKZYU1PSMEInYwU/C9LBmbHHEYLNGYs1SYN1KZM1SYPNMRl/79Bu99NkqHEr1LgVqt1yebtmy7ZHIaBKrF+fZkr1xzshYuWmt/jj6/8vyVwcVVH5wpyv8PnZZ5UnBuQHBkk8v4zMQDEGSXZp1B89j/pjjkTZiWUlm8uztm0DAz2rCCmDhDQDvODxuPGFx1GghsnTjkKSD87/8cfJ3lq2PgnOOussTjnlFF5//XXeeustXnjhBZYsWcJ1113Hj370IwBWrFjB7bffzqpVq0gkEohSFYmurq5hAqy1davLvLGxGDIxODj4sYm0L3/5yyxdupQ5c+Zw0kkncfLJJ3Paaafhdu/6N7e7m6WdGXa29eoFAgFaW1tZs2bNTve/8MIL+da3vsXKlStZsGABp556Kscdd9ywNvPmzdvh8XPPPQcUJ0W0traWBRoUJyfIssyaNWs+OZF25ZVX8vjjj/PXv/6VqVOnfmT7aDRKb29vOWBv7ty5aJrGSy+9xDnnnANAd3c3a9eu5aijjhqpYVaocFATS6T551urePmNlfQOxMvPTx7XyP/zrf9gyoQDd+KUjF7c8SeQjU0A2J4WjKovI9SDa1q6bju0pUzWJU0+TBqsT5nk7eFWMVWCRu+uBVi1RyGoSgedlT6Zi/Po678tVwyYUD+Vb3z2ezRGmhG2Q+LDtQy9/S7pjZspZLO4ImFqjzyMhuOOQt3OdeM4Dh1dfWzYsBo7006tP0Ojx0FRFHz+KqoaZxGpn4GsBWhra6sItEMMj8fDggULWLBgAVdeeSWXXHIJixcv5pJLLsE0Tc4+++xyRoW6ujqi0SinnXYahjG8KoS2TWm4Lb8HIfYtVF0uxT1uu79pmrvdp7m5meXLl7Ns2TJefvllfvKTn3D77bfz/PPP4y9VwdiWSZMm8frrr1MoFHYQcoVCgY6OjrJlcF/4/Oc/z6pVq/jHP/7BsmXL+OpXv8pZZ53Fvffeu0f77+6z25fzzYj8Kn/84x/zyCOP8L//+79EIhH6+4ulT/x+P4FAgEwmw+LFiznzzDNpaGhg8+bN3HTTTdTV1fGlL30JgHA4zHnnncf1119PXV1dOQVHa2vrboMjK1Q41DFNi+Wr2nj5jZWs/LC9XDaxKhzghKNmccJRs8mmYgdOoDkGWuoFtPQ/ARuhBDEiZ2J7Zx8UEwPiBZs1SZO1SYO1KYNNGQtnu/NgvUehJawxLeyiJewi351m6tS6nXd4ECKE4LV1L/Lk2w+TK2Rxax7OOvLrfHb6F7CyWfqWvcbQv1ZgpjJA0XLmHTeVGWefhRYcXkczmcrwYVs7gz3vE9Gi1LoLEJTwedz4w83Ujp6LKzgGSaqkNfo00dLSgmVZ6LpOe3s70WiU6667ruzVeuqppw74GLZ4wfr6+srPrVq16iP383g8nHLKKZxyyilcdtllTJ06lTfffJOTTjpph7YLFy7k/vvv5ze/+c0OEwceeOABstls2dCzhbfffrv8OWSzWVavXs255567y/HU1NRw7rnncu655/L5z3+eCy+8kF/84hdlUbh8+fJh7uTly5fT0lIMQ5g2bRoPP/ww6XS6bE178803cRyn3GZvGBGR9sADDwDskJjuyiuv5Oqrr0ZRFFavXs0f/vAHkskkDQ0NfPazn+W3v/3tMJPgrbfeiqIoXHDBBeVktkuXLq3kSKvwqWRTVx8vv/Ee//f2B6SzeQBUVebIWVNZcMwcZrWML3/321IHZmq9nF+DO/4Ekh0HJKzAMRjhUz+x8k1CCDqzVtltuTZpMqDbw8cswaSgRktYY2rIxbSwRpV7+Dmi7ZPXlntMf7KHP7z6a9p6VwMwc8zh/OdnLsQV0+l4/K8kPlyHsIufgbummrp5h1E9p5X2zs6yQLMsm/aObta3r4HcJuoDGcYEHFRNJeCvJtIwg2DtdBTXoTWTscKOxGIxvvWtb/HNb36T1tZWAoEAK1as4Je//CUnnHACoVCI5uZm3G43v/71r/nOd77D2rVrufXWW0dsDNFolPfee2/Yc3V1dTQ1NTFv3jzuvvtuJkyYQCqV4sYbb9xtXw8//DC2bXPEEUfg9/t54okn0DRtl27BefPmcfHFF/PTn/4UwzD40pe+VE7Bccstt/DDH/5w2KQBgDvuuIPa2loaGxv52c9+hsvlYuHChTvt/5ZbbmHOnDlMnz4dy7LK4VvbWu3+8pe/cPjhh3Pcccfx5JNPsmzZMl544QUAzjnnHG677TYuuugirrnmGhKJBJdddhlnnHHGXrs6YYREWiKR2O3rXq93h1xqO8Pj8fDzn/98v5LkVahwMJPO5vm/t9/n5TfeY1PX1mLb45rrWXD0HI49spVQYMcZRyONZKfQ4k+h5osnWkcbVZoYMPaAv/f25CyHV/p1XuiWGOof2CGg36tITAltsZJpTA5peJRDP6t9sd7mX3nm3ccwbZOgN8x/HP4NxmdCDPzvX8j3DxYbShLhaVOom3cYgQnjhrlMhmKJktVsDTWeOKM8eaSwhM/nJRhuoqpxFq7g+Ior81OE3+9n3rx5LF26lPb2dgzDoKmpiYULF3L55ZcDRYvWfffdx0033cQDDzxAa2srt9xyy7AJfPvD448/vsM1/eKLL2bRokUsWbKESy+9lJNOOokJEyZwxx13cPrpp++yr3A4zN13381PfvITLMuipaWFhx56aLdx7YsWLWLmzJk88MAD3H777QDMmDGDX/7ylzu1kN1www1ce+21rF+/nmnTpvHII4/s1JUKxckHixYtoqOjA7fbzbx58/jDH/4wrM1VV13FU089xZVXXkltbS333HMPhx9+OAA+n48//elPXH311Xzuc5/D7XZz+umns3jx4l0ez+44IHnSDhUO5fQBlb4Onb4cx+G9NRt56fWVLF+1DstyAAj6vRw3r5UTj57N+Obd5zgbsXEJh4F1jzPO/x6S0EFyYYQ+jxU8DvbB/bU/4+rJWfy9O8fLfXl0e2uqixq3zLSwi6klYTY2oCLvpdv1YP9OdAxu4P979X66osV6p8c0Hs0xzlQyq9eXi56rfh81h8+m9oi5uMJbJ4oYpklbeyfL33mbGl+a+kAal2LjcmkE/EEi9S34qqehevY8lvBg/bwONIdinrQKnywHoqTVx54nrUKFCjAQTbL8w5dY9uYq4sliLJEkwdwZEznx6DkcOWsKmrYPP0EhQBjF2ZdOHknkS9s6kpNHcnLbbOeh9Lrk6EhOjjoRRxJ+bM8MjKqzEGrVR7/nCCGEYEXM4JnuLCtjWwOYZ4RdTAmm+UJrHbWeT294g2EVeOKth3jx/acRjmBcoYrjpVZcy/Mk+QAA/5hR1B55GJEZLeUcZ0IIBoZitLWtIT64nqArQ2tdBs2lEfB5CYTridTPxBWcsFc5zSpUqHBwUxFpFSqMILZts3xVG88uW87bKz4sm9Qb66o48ejZHD9/1u7TZzgGkh1HtmJIVhTJiiPbMZrtzXh6PVuFF/au+/gITEIUar5RrLX5MU0MyFoOy/ry/L07R1++OHaXDMc1eDlltI/xAY22tuinVqCZtskHnf/iwVfvRVg6TQMSc40xNKg1yFIeWVOpmjmd2vmH42vcWqKmoGfZ2L6Kod51aE6MgGoRCIHb7UJVAjSOmY23aiqKp36fZ6oKITAdgWE7I3W4FSpUGCEqIq1ChREglcnx0msr+Psr7xCNF2tpul0qJx49mxOPns20SWOKF1FhI1lxJCuKbMWR7CiSFStuWzEkJ73T/j1kka1tYigkDSF7EZIHZF9xu7QwbNuDkHxbt2UfHes7mOL76DQ5I0FXtujS/Gd/vlyQvNYt84XRPk5q8hHUDv3Ysl1hWgaru1awYtObfNDxDmo0T2OXwYRChObIWLwuP+7qCLVHHkb13FmoXg9COJj5QWID6xnqa8PMD4FwCMggqzJeX4RI3UTCNRPo6M0RHNX60QPZDb1pnRfaB+iNFfAnN+33MauyxIKK97DCp5iPisEfaSoirUKF/WBTVx/PLnuHV5d/gGFaAIxuCPPlEycyrkpn0lgfsvUW0uCzyHYcyUqweyuYglAjOEo1Qq3GUYvrrnyCsY3TEbKnOPNyf+onHmDrmSMEK2IF/taVY1V8q0tzZsTFKaN9HFHjRpEPoemXe4Fu5vmg811WbnyT9ev+hW/IIJyEGSnwK168ah2j6scQnjqZunmHEZw0AWHnMXM95GJdxIfayaaTGKXcUkJICK2KqrpJjBrTistXu9Vi1rfvdYsdIXinJ8HbPXEQxRmzmrL//xN1N/VBK1SosPdURFqFCnuJZdm8/d46/v7P5Wzq2EhjKMcRzTmOmOrjsEke6oJdSHSQzWZxJXecQSSUEELZKsActRqhVCPUKoQSBmnHC50utSG0+o/j8PaZrOXwUm+e57pz9OtbXZrHN3j5wmgf4wKfzjJDuUKW9zvf4b01r9K7ehX+uE04AdNN8Lr8hLwRwg0RQqOa0UMBpp/2ORSPiZXrJd35N/KZQdKZHNlcHiEEuqWSMauI1E1k4uQ5VFdVj+h40wWL59sH6E3rIMHhoyJU5Sxapu5/yS8hxA4leSpUqLDvVERahQp7ghBkkp2sXPFPNm14l4AS47SxOaqmW9RWhamrDuN2O0AOkHDUOjJSE67gFIRag6NUIdSiENsvK9hBSFfW4tnuLP/s0ymUsszWeRROGe3jxEbvp86lKYQgoydZteEN1q98lUzHRgJpQZUhUaOoeD0hQuOChKprCY9pxttYh7ehBtmtMdDbhh5/Hsc2yeTyZDI5dMMiqXtJ5KtxB0czZdI0jhw3GlUd+fi8DbEsL20axLAcfC6FkyfWU23ptG+OkfB07XE/lm2S1TNk8mmyeoZsPkVGz+AIhxktnx3xcVeo8O9KRaRVqLA9TgHZ7Ec2e5DNXtLRNqL9a0mnE1Q7guom8Lg16msiVFdVI3lG42hNGK5RONpoHK0BZDd9mTaCkUMjFcHekijYrEoYPNEl0d29tUbmrIiLU5t9HF7j3uu0GQcDwjGxjSS2kcAuJHCMBJ58H8lNH2AYORLxXvKpGE5eJ2jC4R6gpQFFVlBVF55AEFcggOrzIbtcIAEMYuQGIQuOnmQoB4NJm1jOQyJfQ0EEmTZ5AgumTiASDn7ECPcN03Z4tTPK6oFizOO4sJejApD813LWDw6RzWbZ3N273YcBtmNj2iaWbWJapbVtYNs7uuxlQJbBmmwdkGOoUOHfkYpIq/Dvi1NAtgaRzAFkawDZHGSsvRZft4kQDolUloFogkxWByBd0JA8zTSPn8vosbMRrlEU1Jqduic/bWQthw8TBu/HDVbFDbpyxQtxNidRHZQ4vtHDKaP9jPEfGqcUIRwcM1MWY7YRxzGS2GYGEKU2gkIuS2qoj3iXjlOwkETxVSFkLFQkzYPmCyF5/dguD2khY9lgJ8C0BZYtsGwwLYFhOQzFZQpUYdgqoxrrmD9rAhPHjTqgVVWGcgX+sWGAeN5EkWCe1ybYtZaeWLE2rKyqSBE/IuBDN/KlJYdu6NjONoJLpXzFkFDwuLzFxe0rrjUPXo8fUzk0vgMVKhwKVH5NFT7dCAFOGtkcRLYGSoJsENkcQLJ3nKUjWyl6BhzWbDboGFLpS9WSMEK0TDuKE487lsa6YnzQpz1ZQcEWrE0avF8SZu1pk22zXrtliWkRjXpfmnMPqyNwkLo0hRAIWy+KsW2sY7aRRDg2tm1j2TamXsA0DPS8TiJpEEsYxBIW8axENufgIGHZLiRFRfEF8YeqcfkDSIoCe1GxyzRdzJs7nRkH0Gq2BSEEqwZSvN4Zw7Yd6vUkk9MDmMk4A5aBJdlkwzIxt04yl8Zv+0EBvKUFCbcWIOyvIuyPEPZXEw5ECPurCHiDyLu4OWlr2/cJDRUqVBhORaRV+HRQSm0hW/1IJUEmmwNI1mApr9jOUHC0WoRaz1DWy7J3+3n6lY0kzQi2I9PcWMMpJxzJ8fNn4XF/uhOEWo5gQ9rk/bjBBwmDtUmDbaszqRJMCWm0RtzMrHIxJaShyhJtbdGDRqAJIXCsDHZ+ELXQRmzTBox8DNvMY9k2lmVjGSamaWCbFpm8IJUWJFMWybRNIm2TyjnlAvcAQpZQXBqR2nrqGpvxh0JomoqmqsX1lm1VQVVVXJqKWnrNpaqo5bWCS9PY3NFBS8uBT3+SMyyeW7eJjQO9eGO9jE7GcZsG3baFo0rkIgr5kFyc1gl4NC+ja8eUBFlRlEUC1bg1zz7nX6tQ4VDg8ssvZ/Xq1Tz99NMA/Nd//RexWIxHHnnkEx5ZkYpIq3DoIWxksw+50IFsdDDW/hBfl8muUlsI2YtQ63C0ehy1HqHV4agNCLWKtRt7efIfr/HOqnUA5HJujj+6hVOOP5JZLeM/tRcoIQQdGatsKfswaZTzmEExlGpCQGVmlZuZERfTIgdPvUzHEeTyOplshlx6ACPbj1MYKlpGHR3LsikUCsSRQDiYhiCdhXRakMpCMu2QzFgUTBvZNlGFhSRbCNXC45eoqq+lefwkps04jMljp7NxY/uIlTmSD0DqEcu2SGRixNNRYukhOob6WN/fgz9t0pgFPzKKJGFqEnqtC29TPc3hGqqDdVQHa6gK1tCxafMhU8qpAgwNDXHbbbfx3HPP0d/fTzgcZvr06Vx22WUsWLDggL73F7/4RV599VUAJEmirq6O448/nkWLFtHYuPvydocCixcvRoiDp1pmRaRVOPixMyhGB3JhM7LRgWJ0gdiaf8tFFvAjlAhOSYyJkiBztDqQg8Nygwkh+Nf763nyH39jbXtxRptLKyaenTGhjmPmH/FxH+EBRwhBZ9ZiTdJkWY9Ef/8A6e0KmY/2KcyMuGmtcjEj4vpEZmU6jiCv66SzObI5nUwpNUU6myefyyDMGJpIEXTrBNwFZMkBIRC2g3AcjIJDPAHxpIOpqxhZgZkrgJVHmFlMdGy3heqxsEIWUsRL08TpTB4ziymNMxhdPe6gFuaWbRJNDTGU7Gdt54d8MLCcZDZRdOsKQTJnoCRsJmTBg0LA7cEbClI1ZQKjprQQDlQjV3KZHfKcd9555PN5lixZwoQJExgaGuLVV18lFtsL3/t+8I1vfIPrr78ex3HYvHkzP/rRj7j44ot57LHH9rlPwzBwuQ6Mx8JxHIQQexT7ebDVcq2ItAoHF8JGMvtQjM3IhQ4UowPJiu7YTK3Bdo3DcY+jM28xdvR8kN277dqybF5d/gF/eeENOnuLMxL9Pjdf+OwRnHbiPMJB/6cmnsZ2BJsyFh8mDT4suS+3iLJsVsLvF9S45bKlbFaViyr3x1+SybYdNnf3sXbDZta3b0J9fRVOKY2HS7EIeXRC7gJBt0691wAPCMdBFg6SKTByDvkEGBkZJy1BXiAZGRQjju41SShZ8lWQ80LeBx6fn8mNM5nSOIMpTa2Mqhp70IoWIQTJbJzBZD9DiX4GkwPEM9HyXf6WgvQS4NVCFAZtmhMmqpCJhLw0NdbTMKOFcPPog1p4Vtg7EokEr7/+On/+85854YQTABg7diyHH374sHaPPPIIS5cupa2tDY/Hw7HHHsttt93GqFGjAHjllVc444wzePLJJ7nppptYvXo1LS0t3HXXXcydO3e3Y/D5fDQ0FMuXNTU1cf755/Pzn/98WJs1a9Zw/fXX89prr+HxeDjhhBO49dZby/ttcSsec8wx/OpXv8IwDNavX8+sWbM4//zz6e7u5k9/+hPBYJCLLrqISy+9tNz3kiVL+P3vf8+mTZsIh8OcfPLJ3HzzzUQiEQAefvhhrrjiCn77299yww03sG7dOl555RVaWlq44YYbeOihhwD42te+tsNM5e3dnV/84heZNm0a4XCY3/3ud8iyzLnnnstNN91UPnckEgmuuuoqnnnmGQqFAkcddRSLFy9m+vTpe/hf3TUV0vdmxQAAIABJREFUkVbhk8XOFgWZ0VESZZ3DrGQASBq2awyOaxyOeyy2axwogfLLBalttwJNLxi88NoKnn7xzXLJpupIkC+eNJ/PfWYuXs/uxd2hgGEXY8rWJA1WJwzWpcxh7kuAGrfM9LCLUDbNKTNrafAon8jFWwjBUCzBmvUdtG3sRNcNJASKyFLvz1Ptt6jym3hUGxmQbBvJssAwMRM2Ii1hZ2SsjIxiySgYGN4CXe4Ym12DZAKQNIoCxuf2M7lx+iEhynJ6lqFkUYwNJfsZSg5g2uawNhJQHayhLtyAnjaYMamV7rZeutZuwGtJqIrGqNH1TJzTSrCpsSLO9oF3b/zZx/p+h91wxV61DwQCBAIB/va3v3H00Ufj8Xh22s4wDK6++mqmTp1KNBrlhhtu4MILL+SZZ54Z1u7GG2/kpz/9KY2NjVx11VV897vf5c0339zj787Q0BBPP/00Rxyx1QPR19fH6aefznnnncfNN9+MaZrcfPPNfO1rX+P5558v/wZfffVVQqEQjz322DAX47333svVV1/NpZdeyj/+8Q+uvPJKjj76aObPnw+ALMvcdtttjB8/ns7OTq644gquuOIKfvWrX5X70HWdO+64g1/84hfU1tbS0NDAkiVL+J//+R/uvvtuWltb+fWvf82jjz7K7Nmzd3uMjz76KN/73vd47rnnWLVqFd/+9reZO3cuCxcuBIrCbv369fz+978nEolw8803s3DhQpYvX47X692jz3FXVERahY8PYRXzjxmbaXDewdP7BLI1tGMzpRrbPbYkysbhaI0g7f1XNZnO8uyy5Tz3z3fI5IppNJobazjz5GM49sjWA5Is9OMibzmsS5l8mDBYkzRoS5ls572kyaswLexieqTovqx1y0iSRFvbII3ekf3pCyFAWAjbQDjFxbENhGMWH9sGBT3L4OAA0dgQhpFHlR1m1jp43TJBvxssE6+q4RQK2LqOlTQwU2BmZKy0jJWVkWQXUrWfWNCgMzTE2kIHSVUv5SMDTXUxpXE6YamWEw7/PKOrxx00oszSC1jZHPlEEsu2iGeGiKeKcWSxdJRcIbvDPkG3n+pgbXEJ1RAJ1KAqKgjB6rff4YNnXyOjF29qvLU1HD5/DtWjKuLs04yqqtxzzz384Ac/4MEHH2T27NkcddRRfPnLX+bII48stzvvvPPK2+PHj+fOO+9k/vz5dHd3M3r06PJr1157LccffzwAV1xxBaeeeio9PT3D2mzP7373O37/+98jhCCXyzF9+nQef/zx8uu/+c1vmDlzJjfeeGP5ufvvv5/x48fz7rvvlgWd2+1myZIluN3Db5RPOukkvvvd7wLwve99j/vvv59ly5aVRdr3v//9cttx48Zx00038fWvf52lS5eWf++2bfOzn/1smFXwvvvu49JLL+UrX/kKALfffjsvvvjibj9vgJaWFq699loAJk+ezIMPPsiyZctYuHAhGzZs4JlnnuHpp5/m2GOPLR/rrFmzePTRRzn//PM/sv/dURFpFQ4MQiDZCWRjM3JhM4rRiWx2gyhaBoKiVDBc0rBdzdtYycaCEtqvt+4fivPXF97k5TfeK9fTbJnYzJknH80Rs6YckhewrA3Lh3RWJwzWJE02Zkyc7UTZWL/K9JIomxbW9tt9KRwLYes4to5j5cvbwsrj2MXHnvwAyfaVRSHGjsG2Qgjy+QKZbI68XgDAI4HPK+Nzu/BIMrJhYA1m0JMFDN2FlZGw0jK2ruGursLVWEd2lMFmaZAPMm30Z/pKycoADRojzUxvnsP00bOZ0jgDTXXR1tbGmNr9L3O0rwghKKTTZIdiZAYHSfT1korHSecybHz9n9jbWchcgEuS0RQXmupCVd1oqgtZViBaIE936W9r/4PpPCgKRijC1LmtzJr6ycTTWZbNUDxJ32CcbE6nPnxoz4TeW8vWJ8FZZ53FKaecwuuvv85bb73FCy+8wJIlS7juuuv40Y9+BMCKFSu4/fbbWbVqFYlEomyp6urqGibAWltby9tbAv8HBwd3K9K+8pWvcNVVVwEwMDDAnXfeyVlnncWLL75IIBBg5cqVvPbaazvtY+PGjWWRNn369B0E2vZj2jKuwcHB8uNly5bxi1/8gnXr1pFKpbBtG8Mw6O/vp6mpCSiK2VmzZpX3SSaT9PX1MW/evPJzsixzxBFH0N3dze7Y3XjWrl2LLMtlAQnFuLYZM2awZs2a3fa7J1REWoWRwckjG12lWLLNyEYnkpPZoVkxlmwsgzkVpeFoHK1pn6xkO2NTVx9PPvc6r7/7YTmNwuEzJ3PW549h2qQxI/IeHwdCCLpzNm0pg7VJk7aUydpBGX/f1rxusgSTgxrTIhozwi6mhvcs0F8IB0QBqxAriS1969re8lgvijDH/Mj+JJHHcYrvK0kqkuJCkjVyusNQPMtALEPBEJiOF8v0EtJcVFkCVyxJLpkha0k4NuAo5G0XDS1TCU5vIhuS2Oj0sWboQzb0L8NKbU2q6nP7mdo0kxnNc5nePIcqf83ef8gjjGPb5OMJMoODxHt7SPb3o+dzmFaBvFnAtB0sBAXJQZJlkCRkWUNWPMiKG1nxIMkaxrYiS7CrCcsA5AIRvJOncNKcSVR7D6wwMkyTgWiSvoEYfUNx+gfj5fVgLFmOI/S4Na793lkHdCwVing8HhYsWMCCBQu48sorueSSS1i8eDGXXHIJpmly9tlnc+KJJ3L//fdTV1dHNBrltNNOwzCGh5No2tYydVtE/kfNbgyHw0ycOBGAiRMn8t///d+0tLTw+OOPc/755+M4Dl/4whdYtGjRDvvW1dWVt/3+HWsbbz+mLePaMqbNmzfz1a9+lfPPP59rrrmG6upqVq5cyYUXXjjs2Nxu94glid7deHb3WY3ETVNFpFXYe4SFbPYiFzqRjc6itcwa3LGZ7MNxjcFxjS3FlI0FxQdAMtZGvWv/hZMQgnWbenjk72+zas0mABRF5tgjWznjc0cxdtTBXZQcitn816eKYmxdymB9yiS7ne9SlWBG2MX0iMa0sIup4eEpMYQQJYtXrii6tli7rFzJCrblOR1vPkO6c+cnx22RJBlJ8SArXiS1tFY8yKq3/Hx0cw+jJrQgyRqZbIF17ZtZu6GDeDKDMCWsvErQsWnQ84zW87hK56wCoPp8BCePxT9uDKIxzBub3mGDNMia7hdItse3GYfE+LrJJWvZHMbVTUaRP1lXtVUwyA4NEe3tJt7bTTYawzALmKaBI4qpjg1JkFQFaa9A93oRwWq8mp+G+gl4vVXI8v6dfrV0nNMPa0EdIXduLl9gIBqndyDOwFCc3sHium8oXo7lHI4g4DYZEykwvkFhXL1MTUhgWbtRlhUOGC0tLViWha7rtLe3E41Gue666xg/fjwATz311AF77y1iKJ8v5qScM2cOTzzxBGPGjNlB4Owv7777LoZhcNttt5Xf99lnn/3I/cLhMI2NjSxfvrw84UIIwb/+9a/yZIZ9Ydq0aTiOw1tvvVV2d6ZSKVavXs3Xv/71fe53CxWRVmHnCAFOHslOItsJJDtJrfM+nv7nSm7L7erzSSqONgrbNbYkzMYg1JphqS9GAsdx6OwdYm17J2s3dLKmvYuOzl78fj8et8bnPjOX0xfMp7b64JpGvYVtrWTrUiZtSZOunLWDo7DGLTM15GJKUGVqUOD09TFxnA/HShQFVyxHtiTEisJMR+xRHQQJIblQXFXIqgdJ8W4jujzDRJgkuz7yTtB0orRt6mfN+g46O3uwcnmsXB5V12mwLUbLECxpCNnnRmqsQq/SSAQd+qU4fcm36F/7Z/T38+XZigAhX4Tpo4uibNroWQQ8++cC3x+EEOjpNLGeLoZ6OkkNDFBIpTEsA8fZ+plbbgkjIJHzeIm7g1ieKlRPFaFALcc21TGjPkjnCOZca2tL75FA0wsGiVSGZDpHIpUpLdnSc1kSqSztHV0IdhS+EoKQ12BKvcH4BpVxdRJNVQ61QYsqn47XBS5NQ5a3CDOTlfmDIwbw00osFuNb3/oW3/zmN2ltbSUQCLBixQp++ctfcsIJJxAKhWhubsbtdvPrX/+a73znO6xdu5Zbb711xMaQy+Xo7+8Hiu7OO+64A4/Hw0knnQTAt7/9bR588EEuuOACfvjDH1JbW8umTZt44oknWLRoEcHgvlfbmDRpEo7jcO+993LGGWewfPlyli5dukf7XnTRRdx5551MnjyZGTNm8MADD9Df379fIm3SpEmcfvrpXHbZZdx1112Ew2FuvvlmgsEg55xzzj73u4WKSPt3RAgQeSQriWwnkUoiTLKTSFaiJMySO8yyjIgsslG8iDpqXdlK5rjHjKjbclsKhsn6TT1FUdbeRdumbrK5wrA2Ab+Hc754PF84/giC/v2bSTPS5HawkhmYloFXMvBIBl4MWtUCY70OYzwWjW6bWs3EIxkIW0cYBURUkDWyZHp2b/2SZTeSWhRdReuXr7it+oaJsaH1Gxgzdu+EghACx7RIJZMMDsYYGkowGIuzrm0Tkm1j53UwLeplaJJtApaOqdpkwhodAZNeV4puZxDbdGCA4rINfk+QOs9ojp19ItNHz2FU1di9dhU4lkW6r59kdy+Jri7Wd/bs1f5bMC0TwyxgWAUMs0AqGqXdcbCdrRYiIYPllpECPgJ1tbhrG4k6foZ0D0Jy4QJG+VzMaQwzuTqAMsJJbC3LJp7MsH5TzzCxte12cZ1BL+zebS1LDh4pyYRGFxMaZcbUyTRFHGoDBmFvAY9LxqWpSNL2FjIXQvYj1BostQah1uCotdB98CQC/TTi9/uZN28eS5cupb29HcMwaGpqYuHChVx++eUA1NbWct9993HTTTfxwAMP0Nrayi233MLZZ589ImN4+OGHefjhhwGIRCK0trbyxz/+sXwD0tTUxN///nduvPFGzj77bAqFAs3NzSxYsGCnMWh7w8yZM1m8eDF33303t9xyC/Pnz+fmm2/mggsu+Mh9L774Yvr7+7nkkksA+OpXv8o555zD2rVr92tM9957L1dddRVf+9rXyik4Hnvssf2e2QkgJRKJf9tfVFtb2wje1R5EfTkGkh1HsuL0bl5Nc2OgKMSsoiDbmQDbGUJyI5QwQo0glDA9gwb14+bhuJpB9u37+Nj1MSZS2bKVbO3GLjZ29mPbwy1EtdUhpk1spmXSGFomjkHPxGlpadmv8XzUuPaEjGnRlUzQn46TyCbpjw2AIuEpCTKfZODBwCWDX5PwqzIBVcKnyrs1OEqyi3SmQFVNY1GEKb5txFhpW/EgbeM+K4oqE1svFGdLFgzsQgGnYLC5fSNNdXXF1w0DxzBwDBPHMLFNE6dgYBoFkrkCCb1A0rBImhYph21mkAocIbAsk5BkEbGy+EWGuE9nwJsnFSrmJWOb45IkiepAHQ3hUTRERtMYGU1DeBSNkdEEPKF9+uxt0yTd20+yq5t0Xz9OKefRtla57RFCYDsWlm1h2WZpvXV7+xgT27aRXSqOX8NXU0W4sYn6UWOpCdcTNxTe60/RkciV24+L+JjTGGZ0cMeSSntyjEUBlmYoniKWKK7jyTRDsRTRRIpoIk0yld3tMW6LS1MJh/xEgn4iIS9jagTNVTkag2lqvElCWhzLzBMJhYb9v8qflxLCKYmwLUKsuK4BeceL0EieCw80yWTyoEteWuHfj919DyuWtEONkhtSLomwohhLlFySpeecrVP560UWLbWTE7nkwlEiw0SYUCI4Sqj0OALy8Pw78WgbtZ6RO/kKIejujxYFWXsXa9u76BuMD2sjSTC+uYFpk5qZOqGZaZPGUFM13PXV1pYcsTHtyZgdK0s0m6Q/HSeZTZLTk9hmGs3OIUnFC3wA8Cg2mqrgVSUCqoxflfCrGm7NVXYtSluCxodtb10LNAqDURLrP8Dn1BeFlp7HLiSwC4Wy8LILRkmMbRFkBuwioDWbzWJvc3E3BKQEpAWkneJ2Vghs4eAIB1FaO0IgY6E5BWQnh0vSkZ002VqJ3hDkSqJMUzTqw000hEfTsI0Qqw834VL3PyedZRikenpJdfWQ7h9AbONy9FVXERo9iv50krqGGrJ6hkw+Q1ZPkdUzZPUsWT2zm2BfFbfLQ8ATwO8JEvAGyGQKzD38KIK+EJIkYTuCtliGpzckieaKNzuKLDGtNsichhCR3QTxW7bNYDRBNJEmGi8KrlgiVd6OxlMk09ld/evKSBKEg17GjG4gEgoQDvqJhPxEQoHSYx+RoJ8qn05AHkA2u0szrNfv5AZNI5H1YHsmItTqogjTanCUGoRaDbIbIQSGA7ot0G0H3RDoeYFuF0rPCQp2UbhP2oP/YYUKFfaMikg72BACRWSQC5tK1q84clmMxZHtxB5YwRSEGsFRIqRyFq7QFIQSxtlGkCF5RjxebHdkczp9gzF6BmL0DkR5Z+Vqosm/ks4OL37ucWtMGT+aqRNHM23SWCaPG4XP+/Enm3XsAo6ZoqCniGYTJLJJ8noSx0xTsC22zROrlBZJAqH6UbQQPk8IJ1dg1vjxuFzeYcJLknYe9C4cB30oSq6nj1xPL7mefvT+ARzLJpvNYu2B1WRbZJeG4nYju1xILg1L0zBVlUQ8QcznY0jPE8vr5EwTS1hYwsZ0TCzHwhIWqCZoBXAVEC4D4SqAbCNJRatYyBtBthqYPmFmSYg10xAeRXWgbsRzk1l6gWR3D7HOzaT7BrBsC8exsYUNfhd2yE0hIJMX/eR7NxGND+KL7eLz8kj4PUGCvhBBb5iQL0zQFyboCxHyhdHU4SKrra2NkD+Mbtl8MJBm1UCSnFG02Hk1hVkNIWbUBjELBeLRGBuTGeKlJZZME0ukiSfTxJMZevoG8Pl2/3+UpGKy5ZpIkJqqEDWRINVVIWoiIWqqgtREQkRCftrbi/FtRcugwDDjmHoXlr4Zs9CHlRqgN2FhOAoFR6EgFAynHl0KU5Dr0eUadLkaXYrQNZggZNcWBVhJdBWXZFmA7Uo3CiEQdg7byuLC4OZJFctUhQojRUWkfVJsySNm9iOZ/chWfzHRq9nPBCeOZ2DXJ3IhuRFqFUKpKomxqpL4qio+v02tyoFkG+Hwx+N6MEyT/qEEvQMxevuj9A7G6R2I0jsQI5nODWu7xVVTFQ4Ms5KNG10/YtOm9wTTttD1BHouilmIkUt3sPr9dyiYOnlbkLd3vDTlhQtdCqC4Qvg9Yar9YRpCVTQFQqjq1plMbW1t+CMTd/q+QggK0XhRjPX2k+vuJd/Xj2NaO7R111Rj1VZR3Twaxe0qCi+3G9mlYckKBaCAhOEUL7AZQyeeS5HIpEhlMmRyOfKZFKZtYFom+UIOKbmtH1IgqQXQCkiaAVoB1e1QFaymOlBHlb+G6kAdNYE6qgO1VAVqifhr0BRtRFxbpmWSN3IkslE6+mXyhRz5Qo5cJo0+EMUaSiHSOo5jFy1gEpgeGT0gY/hlHFUCB0ht26tUEl8hgt4QQV+k/DjgDRUTwu4BQggG0jor317H+50DpNJZ8tkcsmkQkmxkw+DtZJpEKruDW35X7IkAk2WZnC0Y0m3iBYehgk1nwebdgkOso0A0n2QwkUXrXIlp6TiODmJLzJgGjCkukoaEC9WS0QzQTIHLMHEZeVyFAbRCB66CjqznMTQNSTh4HAO3YxJytiQmLiYkRpjIwoTSNlteFxYSAgmQNQ0x8cZdH3yFChX2iopIO9CUxJhUEmDbirFdWcRsvMXZkUoER61CKBGEWlV0T6pVIHk/VivYtjiOw1A8RU9/UXxttY7FGIold+mmcWkqjfVVjKqvoam+GmHqfO6Eo6mrDu9zLpmM6dCXt1iZhp6+PAVbkLcdCtu4X4ZbBRxcdgq/EyckEoRJUiWlUKRtZuhZNqqpYAqFpAiQdPzIriB+d5jqQITGYISxIR8Rl7zH4xZCYCSSJQtZH9meXjK9fRi6iQPYopgOywaUUACtphq1ugq1KoISClFQFHo2d5IOR0hnMsSjMVKZNJlcDsMqTkQwbbMowmwT29lR6AFIsg2yjaXl8AdVwmE/tdVh6qtrqS4JsOJSR9hXtV85fmzHJl/IoRv5sujKG9nSOj/stS2lj7LZLMEuH+6sgzvjoOnbiB4JDK+MHXYjVwXw+gNEXD68bh/e0trj9pa3uzq6dxqnKIRALxgMxVKkM3mS6SzRVIbBRIahRJpYOke8NPsxlcmTymRJ53TU0o2DV1MIuTU8qszQdgFcQb+XqnCASDhAVShAdSRIdSRIVShAVThIVTjAQH8P01payNmCqG4TKzgM6RadusWKrEF8KEFM7yeeNzBsExwLyTGRhFlaW8X6tkLgLhRwWyZBPYu7kMNj6HgNE5dp4zKs0mKgmgaScAAHtl0Lu5g3DwfLNJBkis9LxdC0LUcn8VGnGwlFVlFkFVlosEubW4UKFfaWikgbKYQoxoPthRgTcgBHa0BoDThaA47agKM1srG9mykNn0zgrRCCRCrDUCzFUDzFYCzJUCzJYCzJug2b0E0Hy9q5xUCWJRpqIzTVVzOqvprG+urSdg3VkeCwi35bWxv1NZGPHI9hC/ryFr15m768RU/OpjdXfJwyi+PIZmX8qe3j0gRhKUudnKROTjJKTlIrpVAle/gVCMgKP0kpTEpEiOYEo+tGUedxM8krU+eSkIWDZdnFJRGlKzrARsPELBiYegHDKGAWTEzDwDJMTNPCMk3iQ1FedJ6nkM1hWTY24AjKiTJkVUHxuFE8HmS3C6EpWNhY+Szm5gTWRhPTNrFsk5yeBZkdBJgkOaDYIFug2uCycKsSEV+AiDdElTdAxBsm7A4QUP14FQ/ZeIZRjc3Dg8QtIAEkcmToIENH0Y1mF12KjmNjO9uvHWLxKANtKzFNE8M2sCyzKBp3IRS3xw14JQmX4qIm48GPiiIrKIqCElbx1tUQbh5FVfMYAoEQqrJjziXbtkllciTTWboG0yRSvaxZt57XVm0mmswQTWWIJ7NFAZYvoDtgSgqWpGDJCrasIBQVR1ERsoqjqgi5BieiImoUhKwUBZjfg8/rRnVrqC4XHvfWxe3WUEouXt1xiGbTpFMJ+jYncKU7cCdjuNJxrHSa12S5GEfnOEhlweSgCYt6YVMnHISwkYSFioVcWiRhIwm7KK5wsG1RrEggyYCySyUlAFMFSwOztFjq8O2skcfr9SLJEl7Nj9flw6P58Lq9xXXpsc8TwKOVxLDLh8flw6N6y9ZvSZLp3z49T4UKFfaZf2uR5hObUDPRYs4vYSNhlbbN0t2qBdggrNIdrLV1u/T8lscTnX68vTsPGN65GGsAZe9ijEYCy7KJJdMMRovia3shFk2kMM2dJ6Pc1kU5qr6apoYaGuu2WsfqayL7VA/TEYJB3aY3Z9Obt+jN2fTkLfryNkO6vcv7crcs0eSVkR2TSVU61SJOmARhkcAnkqjCLF4IhVO+KJqWSt5wkcurpLIyqZxMTi+gmz0Y5mY0XSehacQdwVpR3Ec4ori/2Hb7o4/Lti0URUXgICQJXAqOKmOrEo7mYMk2ph3HtAsYaR0kByQBkoMkBLIEiiRQZNA0A7/bhVuRCXkCBF0+Qi4fPsWLR3KjoaIKBdkudiGEKC5ZgcgIhMiiizR5BLqukxvoK7UpTgjYsi2EKE0WEB+Zdbx4jDaF7dzTKqBJIMtKUXBJCrJSWm8RYKVtWVZwBJiOIEcet9+PUlOLVFtH3hdgKKfz/mCW1MY1pFJZ0tmiGIvlDFJ5k1TBImc7WIoLS9GwNRe2UnQDCyWPo7gRih8nqCDCW4SEhKIoyIpcHJ8qoyoKLlVFUxVcWnHbram4NBXb0AkEAuXjE0Jg2AbkEsixLrT0IKTjeDIJ/Jk03lwWybFL7sfixAsLB1MIhLDLVqyy8MICHCQEpWIESJJUzGouSTiSjCNJCGSEJIOkIICCYyH5NXBrCI+G5HEhe93IPg+q14vi96H5fbj8AdwuD27Vi1tz41Y9uDQ3Hs2LSy2ue7p6mTltNl6Xb7+zpPe3te3X/h83QohDslRchU8HH3We/bcWaRHnXVzxHQt87wsyJkKu/kTEmBCCXL5AOpsjk9XJ5PKkMjky2Tzr1rejvPrB/9/emcdJUV17/Htr6W12hhkYh0UUECKCIFGURCOCKAblyUOMfvC5EBM0vk/c4pLEJUFcQI0iSVQE/BCNe54CCkZxCyCuEUWQJaKAsszADDO91/L+qO5mGgaYgVGamfPl03R3VfWvT1WfqTp17rn3snXbDqq217Ktpm6fPccK8oKUlhRS1q6IsnZFtC8ton1JIZG6Ggb9sD/BwP4X8tcnHT7bnmDRVoVdv5Wq2gjb6sKQSGAk4ujJOEYygZ5MEEwm6G7HKTUSlBhJCvU4eXqSgG7hNywMzUbTbTTDwohqmSyVA0SAWEKxo16xo17LPCet7JOxBujKK/w3FJiOjU/XSeUmUIqdrwFdA6W5oLlougIDbM3BxsFSSSwsklhYyiJmJ8AER3dB09BRaCg0V8NwFRoauq7QNA3d8GEqA0MZmBhoSst62KaTGbnbtVzcpAthcImm/jVAgaMrHB1czXt2dIWjIKob7NAs/Jl5PRumFbODLU2pVFBloCsNXTO9YEvTMDQDTdMJ10coa1+Gz/DhM334dD+m6cfUzYyq7UI0aVGfsNgWiVNdF6G6LsL2ugi14SixWJxoLE5NNEnEiBOxqonYK7B1E8fw4RgmtuHDMX04Rp7XASZPQYM/K13T0QzNCwB13fstTRPT0DENA5+h4zcNCgMGhX6DAlMjpFmECGO4dV7v6GQtrrUDJ1mLk6wlGa3D3laLvbmKfFthhBNeU2zUJRjX0G3YU7Qe99lEAxZRv03EbxENOEQDEMUiFPR7MyYoE0czQBloeoCQv4i8QCF5/nzyAvnk+QvI8+cT8heQH0i/zk+9LmDD19/Q+6jeLRJgRLclCfm//5vGg01eXh41NTUUFxdLoCYcFCKRCIFAYI/r23T1W53vAAAgAElEQVSQFlFdsfKO9O5MlZEajNXAVbr3OvPeyLx3lYHXtJC93X/+s5EjK/sekD2O45BIWtTWRfj6my3Uh6PUhaPUpx470q8jUerqG7wORzNz5+3KrmMppXuOlbXzAq/2qUCsrLSI9qllAf/uGUHXdVizeiV+E6xEBDc91EMigRWNEwtHCIcjxCJRotEosWicWCxGLJ5kWyRGTThOfcIilrRQjoOGjd/nUumHIwyXgA8CPvD7Uq/zwG+6GLt4qO26JB2HiOtiuV52wkq4OFGdeEyRiOsk4hpWQgNXw0Th0xSFSqNdocJQ3kNHoSuFphRKU2hKQ2mKZDKJ4TNT83d7w1DYrtfEZ7v2bsNSpO+C0j08/Xg+A+DqLspRKFehlOZ9l/Jq2TSloVAobefyLJQXYLkKbA0StoPtxwu8dA1HA2XoKNNAmTq6aaIMk5gRoF4LEHYD1Dk+6h2TOsdkh21Sa+skHI1EPOE1balsu3a1ryl1j2FfmFAySDxiEUt4j3gySTwZI5G0SFo2lmVh2w62bTe4azSBIqAILQAqqHCLnUyvUIU3+bFhGPgMDdPU8BnewzQ0Ck2XkgCU+l3aBVwKtDAhdhCiHj91xGu/IT/oYlk7sBJ1JBN1ROJh7+8pFqEuHiNhJ0k0mKVBtzTyIiahiI+8iI9QxEcgZjSaadGUi+N3sUIOVp6Gk2/g5PtQhUFUUT6mv4A8XyGGmY9pFuIzg/h0P9Vbt9GjW0/yUoFWOvDanwyWqW+VwOIAMQyDgoICduzYse+NBeE7wDCMvQ7w26aDtBptAGXtml/7ZVk29ZFYKliKUB+uYdWajazdnCSeSJJIWMTiCRKJJLFEIrUstS5pkUh6dUvJpEXS2nkhSwdaiXgcXzNGZTY0MH0GgYCPgM/E7/cR9Pvw+0ySsSiHdSgjz2+SF/ARNA2U4+DaNo5l4yYjOBt3sGXDWqqIY6g4ukpi6Ek0lcTARlO2V5eVdPj4Q4XjpIZrcxWOm6pFdgFXeVm61DLTBdNR5BvQpdBbvzPxoHtDVpCaAAEvQ+RY4IYhiUuCVGbMTT/cVB8yUgGE93BdF03XCaHIU6BMhfLt6eLlNeOlm59s5WJrLraysXCI6wlwSQ3v4KQKqxuQVc/mglIYmoFp+PAbfq9ZyQwS9AVJxm3KysoxTD9K19EMA2VoaLqBZhpohtcMqBkGemaZgaYbKF1D01KBnFJ8te4rDj+iO7WWxvakoiapqIo7bI15TcJVce/ZSqcSXW/IBMf1JotyNBdXQUiDIBFCgZC33nGwbAcraZN0HGzLxkoFVJbjPdtW6jn93nawrRh2shY7EQacVBOdF7xoqSZaQ7n4AE3zmm4N3UXXFL5UwGXqXsBl6ApDB82OUOJPEtLChFQ9PiL47Dp0N4LmRlFODOw4TiJOLGIRq7KIWhZbLWvXCQywLRt9L03vZkKjfSxASSJIUSxIXsyPP+7Vwxm6jqEZ6CEds8hE5ekUV3YkWNqOYHkFeWWV+Ms7oeeXgda8rPLq1avp0f3QGOi1rWAYhgxoK+QsbTpI+3j5Wt79ZA1JyyaZtEhYFlbSIpF6n7S8QCqR9IKoRGqZ1UhXeyuZzDRH7c/NrZlKXGiaIqj7CJgGhuY1hxlKoWual/nRQEOhp5rh0s1xruPgqCS2iuLYCZy4RSSZxFYW67d8gaa7GDromouue812PqUwlcJ0NQxXQ3c0dDv1nHqNu7ed2TV7lx5LKR1IpbdRqQu490BT2K4DSvO2V6nuZN4eZQIw1SAgU65LOtekaVqmZkehiCfj6H4TKxVoJUmSVBYJN0nCTRJ3E8SdOFE3QRILWzlYymui3HWE9YQTx+f3pfbExWf6KQqVUJzXjpL89rQvLKe0wHu0y29PYXDPzSRNGZ4ibrvsSDrsSDjsSDrUJmy2RWy2x222J2xq4g61CYsN2wtIfrsD23V3BqwNXtu2g2XbaLaFaScxknGMZAw9EUOLRVCRetxIPdFIhEg4QrXjkEwkcW2LoM8mZDqEfDZBXxLTiGKYUXQ9itJjoMdwiWOpOEk3TtJNYGOhK7dBT0Dvn5b6TTS85lxN8zKWXsYQz5+SeI9dsC0bzdCJAbGsNcrzDZX2Dy3lKwau8oGu4Tf8BHzBTFG7FXeoKKukIFBAnp1HKKLj2+Gi1SZhWwxitld0jwYBBQHQTINgx3KCHTsQquhAsKIDgbL2rP1Py823KQiC0BzadJD23uJ/E2tkXKo9oeH1RvMDuqalCo8Vpq6hBSEU0DF0MDUXU1eYuotPB5/uYurg01wM3cXUwNBcTM3F0Fy01LOuFBpedkPXdi/ed11Iui4xxybqOMRch7jtEHUc4q7TaK2ZchUmGrqtozsahqOhJ3UMR8MbHD91lU29bhhkOSgcDSwNLEORcG0Mvw90hY0i6rpEXQg7DpZXHo+t0sENBHSXgKnQNRdXudikitRxicYimD4fLk4myHFxcVwbB9ubtsexvKJ6O0HCimVCwF0Dq7AVJs+flxUzuul9S1/UDe8CbxoBgr4Cinz5+H0hAmae10PNzMNnBqmvCdP98KMoCpZQFCoh4Nvz3Gv1FtTXZYcTrusSsV22JxxWbHP4YPU2auIONQmb2rhFbdxiRyJBfdIiknRIOHZWMTl4HR007+ijlPc6na7Md6MUUE+BW0++U0++U0eetYMCt54CwhhuMhXIOV4m0HBx88DOS3UKwMWyEzh6Aos4SSdB2LYJWxb1lkXUtnBRJBVYSqWGX/ACZ4UX2PuVjqH5KAr48WkaAX/AG6A308swFUSl3ruZ16lnR6FZGlpSR7cUelKhWYpEJEFRQTv8ZgDDCOIzgqlmwgCm4cNn+PGZfq/uzTDxGQF8ug/T8HnNsw1Yv2YNhZsgumkzViT7NwIdPRQk2MELxEKph7+0HaqFB+EVBEE4EHIySJs+fToPPvggmzdvplevXtx5552cdNJJLf493cI1+MI78Pk1/H4DM6Dj8ylMU8fwaRg+DdNU6D4N3VAYhkI3Fbqh0HQHpbtoqYpy27bR0MHxBtZ0HIXrKtz0azv17IBrK5ykwnU0r+nQUdgK7HRw5Lo4SmG7LjbeaOIWpJrfIF3grcgkAbyWN61BnVXqkc5kpVvBvKYvcJSLpSCuOUQ1h4TmENdTz5pNXHnPSa8yC1yXmnCUuG1QH7NIOk4q0+VlOfy6RtDUCWkaAcMrkfd2ylvvZmVAIJE0MVXA2xeVHj5gl4yJpnmpN5/3XtNMdM1E1010ZaA0Aw0dM57EbwZTx9v7XjvVi8B1XFzbxXVcHNvFitpsr7Oosmxsy8KxkxhuDM2tRnPjuMkIn338FYZy0JWDrryMka5sNM3B0TTimo+47ieu+YlpfmJ6gKgKENWCRFQAR6Xm4nRddG2t1/yXagZUyuvh5zoJcOIEnBgBZwcBN4zPrcfn1GM4EQw3gu5E0JwYyomhuTFMN4mTCnQtxyGKS53jpoIyr1mTBj0Dvdqy7PcKheM4GIbeIFOpg+HDMIIUKJ2iYAFFwUKKgkUUhUooCrWjMK89RaH2FOaVUZTfkVCgPUoPseqLNRx+WCVWJIodjWFFo9iRqPccjWFlXkcz29jxxoekCYfD5CV2LV7fPe1mpR5R9kwkHEalajGNUMDLjh3WMZMl85VIobggCLlPzgVpL7zwAjfeeCP33nsvgwYNYvr06YwZM4Z3332Xzp07t+h3VfbJR8UKspY5kBrBPYVN5mrgBTkaDq7XLd7LdeCgsDNBRkOy36frqdxGltmpoMnRXJI4OI43z1/ShqTleoXjlkPSdrEy9Vkutpuu6XLAcVHpoUFIDVaJ68WNyrPRUSoVRyp2b7TdGwrwJlUP4iMEO4OAdLimIIEifQlOz2MJdiphpzLPju2Q1MKeruumnjMHZRdSOTQ33V3ZTdW+7dQPGC5+w8EwLAzNwqdbGIaNqdkYuo2uLDTDxtQsNL+NFnTQlA3KSXUOcLEdh4SjEcFP2PFT5/iIOiYxx0/MMYk7Jo6l0Nx6L9vluCgXNNdBcxxCuOS5LqZjESCJ6SbQnRiamwA3gXLiuK4Fju0Nt0BquIyd47UDyhtmAYWVbv7Fh2PpBE0/Jjp+pZGHhoHCdHUMFLqr0BzQHIWBlzE1XA3dVeiuhu4odEehuQrHcggGQxi6H1P3Y+gmpm5i6j503dgZvGVRQ4waYqzJqv8Kh8NEmjldldIUejCIEQx4zyHvtbN9O2UdOjRLa4/U1nBE/34EO3bALCyQgEwQhEOSnAvSpk2bxgUXXMD//M//ADB58mRef/11ZsyYwa233tqi37VwazV2wsJJF6AD6conJxV0OYrUunQQllV11Shu6v/dK7b2jZuxhJ3fo8jUYzUaC2Z9Pr1SeT1PXU/Pa3RKRXSkq/vZ+TrznU6D5TuDovQ6ldLDBeV6YzspF5Trppa7qWZUFy3VI8DbZudyb1vvMzR4nVmfee9mytrS35v+PrI+k7ZFpbZr8EjV1LmpUf0dUkGla6AwUtuQqqOCkAt5rsILFRKpx84J64FUYJqqsWNnXWDDZ1DYjoOu+1D42Vlr563TNW8oCy09dlj6WdPRlDd+l6bpaMpbFrfihHyhBr0wU5Vf6Z6i6Z6Ze/VMj3AknDXu14GgDB1fUUEm2NKDgVTQFcxelg7GQkE0v7/RoCm+ejWdWqj2K7p6NUVSRyYIwiFOTgVpiUSCf//731x11VVZy4cMGcLSpUtb/PtKNn9DaW183xs2oPHc2PeE2u1Fg1WNWZIKKlsqi+C2vFbz1BqPUD0pr91ZZYaOSAUsymtmVSrd3Joe7sLbTqWXpZpjHcfBb+ipThsahu49m6mhH3Tda5pVuubVL6WevYeO0lPfp+vU1ddTWlKKqfswdBNDNzB0E13TmxRMNaR62zbKOnb0eoCaBpppohkmmmmgMu93rlOmubO3qGmijJ29R9esXdtihfAtMXenIAiC0Dg5FaRVV1dj2zZlZWVZy8vKytiyZddO9h6rD2B063ZdKolvr26QR/PYme9I9UxMZ53SY0akt3Z35pi8Ma/SvRi9rIymeZdi71mlOjGqzHAFKt2LMVM3lF6/M3hwM9btbA7bn0DJy7KQCow8TU1lLPeydSo9RtXOQvGdr73vVJqWCYSUlsrmaKkASIGmdNDUzmJz5Q0lQTr7o3kjpnsx004tr8emnoqjvAFc0bRUlsj7DqVpKPSdr5XyAiOlYejmzqLv9PdngjSVqdVqcPAbvE/96g3sRmv63Jx7ouMeljevmdmjmEY7RDaOnfQeu9bLN+BA/m5ES7S+Sy0J+gVhJzkVpKXZ9eK4t2k7DuQPesS5E3IyoyBaoiVaoiVagiDkVH/z0tJSdF3fLWtWVVW1W3ZNEARBEAShNZNTQZrP5+PYY4/ljTfeyFr+xhtvcMIJJxwkqwRBEARBEL5/cq6588orr+QXv/gFxx13HCeccAIzZsxg06ZNXHLJJQfbNEEQBEEQhO+NnAvSzj33XLZt28bkyZPZvHkzvXv35plnnqFLly4H2zRBEARBEITvjZwL0gDGjx/P+PHjD7YZgiAIgiAIB42cqkkTBEEQBEEQPCRIEwRBEARByEEkSBMEQRAEQchBJEgTBEEQBEHIQSRIEwRBEARByEEkSBMEQRAEQchBJEgTBEEQBEHIQVRNTY17sI0QBEEQBEEQspFMmiAIgiAIQg4iQZogCIIgCEIOIkGaIAiCIAhCDiJBmiAIgiAIQg4iQZogCIIgCEIOIkGaIAiCIAhCDiJBmnDAuG7rH8WlJfYxGo3ium6LHq+2cOxzkbZw3MXnBeHgI0Had8CuJ5EDPanYtn1An98TjuPs92cb2qSUOiCtmpqa/f7srnz11Ve8++67LaL15ZdfMn36dMDbxwNhxYoVjBkzhs2bN6OUOiCfiEQi1NTU4DjOAdvVkr7aklri801HfF4QWi/6jTfeeNvBNqI1sXr1au655x7mzp3L0qVL6d+/P4FAYL+0Nm7ciG3bhEIhbNtG0/Y/pl63bh2zZ89m3rx5rF27lgEDBmROnM096a1du5a77rqLZ599ljfffJPhw4fv94lz1apV9OvXD9u2+fGPf7xfGmmWLVvGoEGD+PGPf0yfPn0OSOuzzz7j7LPPpqioiCOOOILS0lKA/Tpen376KSNGjGDNmjVomsapp56638dr5cqVTJgwgccee4yHH36YgQMHUlFRsV92rVmzhgcffJAFCxawZMmSA/LVlvJ78fnmIT4vAZvQupFMWgvyxRdfMGTIEDZt2sQ333zDK6+8wqBBg5g7dy7RaLRZWqtWreKEE07grLPOYuvWrei6vt/ZheXLl3P66aezZMkSXn/9dWbMmMFVV10FNP9uefny5QwbNoyamhqUUixatIhrrrkms765d8sffPABSinuv/9+br/99v3SAO+icOaZZ3LllVcyduzY3dY359ht3LiR888/n9GjR/OnP/2Jnj17Ztbtz8Vq2LBhjBs3jssvv5zFixcTj8eB5u/nF198wYgRI+jRowdXXXUVlZWVWb9jc/RWrFjBsGHD+Pbbb6murubVV1/lxBNPZN68edTX1zfbrpbwe/H55iE+f2DZOUE4FJBMWgth2zY33ngjPXr0YMaMGYwePZpx48axbNkypk6dSrdu3ejRowe6ru9T69tvv+WKK66gvLwcv9/Ps88+yxlnnEFBQUGzswtff/01559/PmPGjGHq1KmMHTsWwzBYuHAhw4YNo6CgoMla//nPfxg7diw/+9nPuPfeexk+fDjr1q0jGAxy6qmnAs0/oW/YsIHa2lpuuukmbrnlFqLRKD/5yU8Ar0moKdmYzz//nBEjRnDxxRczceJEbNvm1Vdf5Z133mHlypUcc8wxaJrW5Dvvt99+mw0bNvDwww9j2za///3v+dvf/saMGTMoKSmhtLSUYDC4T51///vfnHnmmUyYMIHbb7+dyspKJk6cSOfOnenXr1+zjlU8HufXv/41xx13HPfddx9HH300FRUVbNiwgVNPPRXDMJrsF5FIhAkTJvCTn/yEBx54gJEjRzJixAhmzpzJO++8Q2VlJT179mySXkv5vfj8TwDx+Ya0pM8LwqGKeHgLoes6tbW1HHbYYZllwWCQGTNmcMYZZ3DDDTewfPlyYN93kx999BGmafK73/2Oq6++GsMwuOCCC9iyZQu6rmNZVpNschyHV155he7du/OrX/0K13XJz89n+PDhrFmzhnXr1jVrH+fNm8eAAQMyWQSfz0cymWTRokX893//N+effz7/+c9/mrSPafr160c4HOaUU05h4sSJPPjgg9x3333cdNNNPPbYYyQSiX1qTJ8+nbq6OkaPHk00GuXcc89lypQp3HXXXfzxj3/kpJNOYuvWrU2+8/7222+JRqPYts2IESP49NNP6dSpE36/n2uuuYa//e1v+8wQ1dbWct1113HJJZdwyy234DgO3bp145xzzmHevHnU1NQ0KwtgWRZbtmyhb9++mWULFy7kzTffZOjQoQwcOJCZM2c2KQsWi8Worq7mtNNOAyCRSFBeXk7//v3x+/3ceOONfPnll8C+f8eW8nvxefH5XWlJnxeEQxXjYBvQmggGg/zrX/8CvItXPB7H7/fzyCOPMGrUKK6++mrefPPNfd5NnnXWWQQCAQYPHgx4J/8//elPXHDBBTzxxBN06NAB27b3mZ1QSlFRUcGZZ56ZqS+xbZt27dpRWFhIMpnc7TN7073ooos4+eSTyc/PB2Dq1KnMnDmTa6+9lpKSEl566SVGjx7NokWLCIVCez9YDdi4cSNbt27l8ssvp3379vz85z9HKcUHH3yAz+fb5+fvu+8+vvnmG8aMGcNhhx3GYYcdxuTJkykpKWHz5s1cccUVXHjhhbz66qtNupPPy8tj06ZNfPTRR5SXlzN16lSKi4sBuPXWW3nwwQc555xz6NKlyx41/H4/U6dOpXfv3gBomkYwGGTYsGFcc801rFu3jmOPPbbJmY68vDwCgQAzZ86krKyMJUuWMHPmTCZNmkTfvn15+umnmThxIgMGDKBfv3571QoEAliWxWuvvcawYcPw+/1s3LiR1atXM336dG644QZ+97vf8fTTTzfJtpbw+5b0+Y4dO4rPi88LQqtAMmktQLqX15VXXsm2bdu45ZZbAO+kFYvFALjuuuvYunUry5Yta5JWOssBMHz48Ex24cILL8xkFx544AG+/vrrRnXSJ8KhQ4dy8cUXZ5bpuk5+fj6FhYVZ2YknnngCoNGLVfrut6ioKHMy3Lx5Mx9//DHPP/88v/3tb7niiiv4y1/+wtatW/nnP/+59wPWgMMOO4xevXplLp4vv/xy5oL41FNP7fPz6X146qmn+OEPf8iOHTuYNGkSPXv2pKysjD59+nDttdeybt06Pv300ybZNHbsWHRd56KLLmLjxo0YhpGp77n99tsxDIP58+fv8fOO4xAIBDIXK9h5DC+88EKOO+447rnnHuLxeJMuVmmfePDBB8nPz+cf//gHL730En/4wx+45JJLMnp+v585c+bsUy8QCHDeeeexePFixo4dy0MPPcSJJ57I4MGDOfbYY7ngggvYtm1bk+vJrrjiigP2ezhwnwcvSDv11FMP2OfTFBQUtJjPp3/HA/X5NC3p8+edd94B+Tx4ftWrV6/M+wPx+TQPPPBAi/i8IByqSCZtP4lEIoRCoay7wqOPPprRo0ezYMEC7rzzTm666aZMfUlBQQGapjV6QWhMK0162bBhwwC4//77GTduHN27d+fJJ59kxIgRe9RyXTfr7j6tbVkW4XA4cxKdNGkSkydP5oQTTqB79+67aTW0I02HDh0yQUN6XW1tLV26dOGII47Y6z42tAW8O+alS5fyyCOP8M477/DCCy/wxRdfcOWVV6LrOtdff/0etdJNYYZh8Pe//53XXnst0/SWtss0TQoKCmjXrt0+7QLvon3NNddw3333sW3bNmKxWOYiWldXR+fOnencufMetRq7CKWXua7LySefzJNPPsnWrVvp1KlTo797Yz5x5JFH8sorrxCNRjn77LMzvflisRjJZJLOnTvTtWvXve6j67pomsa4ceNo164dTz/9NAsXLuTqq6/m6quvBiCZTGb5R0O2bNnCypUriUQi9OnTh06dOtG7d+9m+31DnWOOOYbKyspMRqu5Pp/WCofD9OnTh86dO2eGamiuzzfU6tu3b5ZdzfX5xvYx7avN9fnGtID98vnGtFzX3S+f39vxaq7PN+Zb3bt33y+fF4TWggRp+8GKFSs488wzeeCBBzjnnHNwXRfbtikoKODyyy8nEokwZ84c1q1bx913301dXR1z5szB7/dTVla2T62GJ7B0TYmmaZx++unYts348eNZtWoVb731Fj169GiyFnh385FIhGg0Sn5+PlOnTmXq1Km88cYbWRerpmjl5eVlbASYM2cO+fn5VFRUNGkf0/v1gx/8gJtvvpmKigqeeeYZ+vXrR9++fVFKMWDAgH1qpXsB6rrO0KFDM9um7Vq0aBGdO3ferWB8b/s4YsQIduzYwd13382YMWOYMmUKuq6zYMECvvnmG44++uh9ajW0oaFNV155JY899hjTpk3jzjvv3G2bPdmV/nwwGMQwDGbNmsWJJ55IIpHg0UcfZcOGDbsN6bCrFnjNe2VlZVx88cVcfPHF1NXVZR2bTz/9lKOOOgrDyD49LF++nPHjx6OUYvv27ei6zjPPPMMPfvADxo8f32S/b0znueeey2RhmuPz+9KCpvv83rQcx0HTtCb7/L7sao7P70urOT7fmNazzz5L7969OeOMM5rl80059mmb9uXze7MLaJbPC0JrQtXU1Egf5mawfv16xo4dy5YtW6itrWX69Omcc845OI6TCRiqq6t58cUXeeihh9i8eTOVlZXU19fz5JNPcuyxx+5Tq7ELfDp4uO6663jyySd5/fXXs5rTmqs1dOhQXNfl888/55VXXqF///77pQVeD7jHH3+cmTNnMm/ePI455phmaa1evZrbb7+d66+/fq+1Jc21a/Xq1cyePZvHH3+cefPmZY0jtTctx3HQdZ1IJMJ7773HH//4R9atW0dxcTG6rvPoo49m2dkcu9LB5IQJE1i3bh3PPvtsJmPRFK108DJ79mymTJlCfX09PXv2ZP369TzxxBNNtivtTw1tW7JkCfPnz2fmzJm88sorWRfltWvXMmLECC644AIuu+wytmzZwr333ksgEOChhx4iGAw2ye/3pBMMBpk2bRo+ny8rA7M3n2+u1t58vjlasHef35eW3+9vss831669+XxTfsOm+nxz7NqXz+9N689//jOapmEYRpN8XhBaGxKkNYNkMsn999/PsmXL+OUvf8mcOXN45JFHmDVr1m6BmuM4JJNJ/vnPf1JaWkqXLl0yTRRN0WrsAv/GG2/wv//7v8yePTsr2GuuViQS4fjjj6eqqorXXnst60TeXK1ly5bx9NNP8/rrr/Poo49mXayaomVZFqZpkkgk9lowvT92zZ49m9dee43HH388q4dYU7TSgVqa999/n6KiIoqLiykvLz+g3xHgww8/pF27dnTr1q1ZWukgLRwOs2bNGl5++WW6dOnC4MGDOfzwww/IroceeognnniCRx55JOt3jEaj/OY3vyGZTPKXv/wl85kHHniAp556isWLF2eW7c3v96WzZMmS3X73Pfl8c7X25vPN1dqbzzfnWO3L5/fHrj35fHPsSrMnn9+f3xEa9/nmaO3L5wWhNSLjpDWDdJ1FeXk5Z511FgMGDCAWi/H73/+e3r1707t376wRzQ3DoGfPnnTu3JnCwsJmaTVsMkifuLp168aYMWM48sgjD0grbdukSZM46qijDkirsLCQ8vJyxo8fv192pcc52rVprbnHfle7CgoKKC8v55e//GVWk1ZTtXbN5lRWVlJaWppp7jqQ3xG84vGSkpL90nJdF7/fT8eOHfnxj39M3759M/srWkoAABKeSURBVD3xDsSu448/nnPPPXe3C59lWXz++ef06NGDAQMGZI5Jfn4+zzzzDGPHjsU0zazfsjG/35fOeeedl6UDe/b55mq5rotpmo36fHO18vPz9+jzzTlW++qpur92NebzzbErXc+3J5/fn98RGvf5pmoppfD5fHv1eUFojUiQ1kw6d+6cuXMOhUL069ePRCKRdfGLx+N89NFHlJSU7PVOualaH374IQUFBQQCgd1OmM3Vev/99+nSpQvHHXdco0XFzdU67LDD6NSp0x4HCG3OPrbU8Xr//feprKykS5cuB2xXS/+OLaX1wQcfUFxc3GJ2FRYW4vf7Gx2w1DRNOnXqxJAhQzLLlFJs3ryZ5557jssuu4xgMIhSinXr1u12Id4fnS+//DKj05jPN0dr7dq1lJWVMWDAgEZ9vrlaHTp0oKKiolHf2t99PNDjlbarsrLygO3a2294MPdxX1qC0BqRjgP7SfqOr7y8PDPQ5cUXX8yMGTP48MMPeeqpp3jvvff2GFTtj1ZL2PX3v/+d999/f48B2v5o+f3+FtvHljheuWpXrvpEU7TS2bW0luM4hMNhLMvC7/ejlOKWW27h73//Ox999NEeg+OW0mmO1pNPPslHH320Wzb7YNslWi2vJQitDQnSmkm6l5dSimQyiWmadOjQgWuvvRaASy+9lMLCQl544YV9BkKiJVqHola6EDwYDKLrOoZhMHHiRGbMmMH//d//7fUi2lI6zdXaW4B2MO0SrZbVEoTWhgxm2wzScwhWVVUBXqo+Tfv27dm+fTuFhYW8+uqrHHfccaIlWq1SK11L5fP5KC4u5rrrruPBBx9k7ty5DBw48DvXES3REoS2ggRpjZAe96wh6Tu8r7/+mt69e/Poo49m1jmOw6xZs5g/fz4vvvhiVmGyaIlWa9Wqrq5m+fLlPP/88/zzn//M9L5sKR3REq3GtAShLSEdB3ZhzZo1TJ48menTp/Pll19y1FFHEQqF0DSNb7/9ltNOO40xY8Zwww03ZHrFKaWwLIsrr7wyaxwn0RKt1qzl9/vZsmULf/7znzNDWrSUjmiJVmNagtDWkCCtAcuXL2fkyJEUFxdTVlbGww8/TCAQ4Ec/+hHgTcHSvXt3Jk6cuFv38srKyqyeR6IlWq1dKz8/nyFDhmSmJGopHdESrca0BKEtIh0HUqxbt46f/exnjBs3LjNRdHl5OVVVVZmi65///OeZcdBES7REa+fwGC2lI1qi1ZiWILRVJJOGVxsxa9YsysrKuOmmmzJDNzz33HOsWLGCxx9/nI8//hjXdenRo0cmJS9aoiVauWmTaLUeLUFoy0iQBmiaRmVlJV27duWII44AYPLkyfz1r39lzJgx/PCHP2ThwoUsW7aMIUOGZM07J1qi1da1ctEm0Wo9WoLQlpHmzhRdunShU6dOgNezqKqqiqeeeoqhQ4cCcMoppzB48GA+++wzOnbsKFqiJVo5bpNotR4tQWirtNkgbd26dSxatIgtW7YwaNAg+vTpQ0FBAbZtU1payq233kooFMpMau04DscccwwVFRWiJVptXisXbRKt1qMlCIJHmwzSPv/8c8466yz69OnDihUreOaZZygvL+fRRx+lvLwc27Yzcxgq5U1I/o9//AO/30+HDh1ES7TatFYu2iRarUdLEISdqJqamr13/2plRCIRxowZQ69evbjrrrtQSvHiiy8yffp01q9fz2uvvZaVel+1ahXPPPMMjzzyCC+//HLWmD2iJVptTSsXbRKt1qMlCEI2bW7GgWg0ytatWxk8eDCmaWIYBqNGjeKOO+6gsrKSUaNGUV1dDcCXX37JH/7wB+bOncu8efN2O5mIlmi1Na1ctEm0Wo+WIAjZtLnenaZp8vzzz2NZFqeffjrg9USqqKigW7duLFq0iPXr13PqqafSrl07evbsyUUXXUSPHj1ES7TavFYu2iRarUdLEIRs2lyQpmkaa9asYfHixRx55JF07do1s65Lly6sWrWKJUuWcMEFF6DrOuXl5RQWFoqWaIlWjtokWq1HSxCEbNpcc6dSimuuuYZkMsltt93Ghx9+iGVZmfUnnXQSdXV11NbWipZoidYhYJNotR4tQRCyaXNBWiKRoLi4mLlz51JbW8tvfvMbXnjhBZLJJLZt8/bbb9OuXTtCoZBoiZZoHQI2iVbr0RIEIZtW3bvTdd2s6UZs20bXdb799lvi8TjFxcVccsklbN68mS1btvCDH/yATz75hDlz5tC3b1/REq02rZWLNolW69ESBGHftMogLRaLEQgEiEajBIPBzMCJuq7z9ddfM3z4cH7961/zi1/8gnA4zCeffMLSpUtp3749gwcPzkxjIlqi1Ra1ctEm0Wo9WoIgNJ1WF6StWLGCiRMnsn37dkKhEOPHj2f48OEopfj2228ZOHAg5513Hvfddx+u66Jpe27xFS3RamtauWiTaLUeLUEQmker6t25du1ahg4dyvHHH0+3bt0AuP322wmHw/Tq1YutW7cSCoWYNGkSmqZlpe1FS7TaulYu2iRarUdLEITm06qCtL/85S84jsOsWbM49dRT+elPf8oRRxzBbbfdRiwW4+yzz+aMM85o0olEtESrrWnlok2i1Xq0BEFoPq1q7s7q6mpM0wTAcRxc1+W8887D7/dz6aWX0rVrV6666qrdil9FS7REKzdtEq3WoyUIQvNpVZm0DRs28Pjjj3POOefQvn17HMdBKUWvXr3Iz8/njjvuYOTIkbRv3160REu0DgGbRKv1aAmC0HxaVYXn6aefzoknnsj111/PV199hWEYmUEVR44cSWlpKatXrxYt0RKtQ8Qm0Wo9WoIgNJ9DNpO2fv16XnzxRd555x22bNlCz549KSoqQinFe++9x5IlSxgwYAClpaWAN3XJ008/zY9+9COOOuoo0RKtNq2VizaJVuvREgShZTgkg7Tly5czatQoNmzYwJIlS3j66afRdZ0TTjiBo48+Gtd1+eCDD5g9ezbdunVj06ZNPPnkkyxdupQbbriBoqIi0RKtNquVizaJVuvREgSh5TjkgrR169YxevRoRo8ezbRp0xg1ahR5eXnMmzePoUOHUlBQQL9+/ejcuTNbtmzhjjvuYMmSJaxZs4bZs2fTs2dP0RKtNquVizaJVuvREgShZTmkBrO1LIt77rmHTz/9lMceeywzF9zbb7/NRRddxFtvvUXXrl2zPrN69Wry8vLw+/2ZNL1oiVZb1MpFm0Sr9WgJgtDyHFJDcGiaRo8ePSgpKcmarLdfv37k5+ezY8cOIHt+ue7duzfaNVy0RKutaeWiTaLVerQEQWh5DrkgbejQoZSUlAA7TxyhUAhN00gmkwAopXjzzTc5+eST9zhFiWiJVlvTykWbRKv1aAmC0PLk/F/b+vXrWbBgAY8//jibNm3C7/cDYNs2Sils26a2tpZYLIbP5wNg4sSJ/Nd//RebN28WLdFq01q5aJNotR4tQRC+W3I6k/bZZ59x7rnn0qFDB7766ivuvvtuRo8ezfjx4+natSuO42Rtn5eXx7333stf//pXFi5cSEVFhWiJVpvVykWbRKv1aAmC8N2Tsx0HampqGDVqFCeffDJXX301JSUlTJo0ibfeeot27doxadKkzIS/8Xic0047jfbt27N48WIWLFhA//79RUu02qxWLtokWq1HSxCE74ecbe6sq6ujurqaU045JVMvcfPNNzNu3Di2b9/OpEmTMqn36upqli9fzuLFi1m4cOFuJxPREq22ppWLNolW69ESBOH7IWfHSQuHwzz//PP07t2bfv36YVkWmqbRt29f4vE48+fPp7y8nGOOOQZd18nPz+euu+6id+/eoiVabV4rF20SrdajJQjC90PONncC/OxnP+Prr7/mpZdeorS0FNu20XUdgHHjxrF582ZeffVVAJLJJKZpipZoiVYO2yRarUdLEITvnpxp7qyvr6empobt27dnlj300EOEw2EuvfRSIpFI5mQCcNppp+E4DrFYDCDrZCJaotXWtHLRJtFqPVqCIBwcciJIW7lyJRdeeCE//elPGThwII899hiRSITS0lIeffRR1q5dy+jRo1mxYgXRaBSAjz/+mIKCgt0GVRQt0WprWrlok2i1Hi1BEA4eB72584svvmDEiBGcf/75nHDCCSxbtoz777+fuXPncuKJJwLw+eefM378eMLhMEVFRVRUVLB48WJeeeUV+vTpI1qi1Wa1ctEm0Wo9WoIgHFwOapC2fft2LrvsMrp3784999yTWT569Gg6duzItGnTsqYjmT59Ohs3biQQCHDuuefSo0cP0RKtNquVizaJVuvREgTh4HNQB7NNJpPU1NRwzjnnAGSKWI844ohMV/D0CNi6rjN+/HjREi3RymGbRKv1aAmCcPA5qDVp5eXlPPLIIwwePBggM9p1x44dswpadV2nqqoq8951d0/+iZZotTWtXLRJtFqPliAIB5+D3nGge/fugHcySfcmSiQSWSeQKVOmMGXKFOLxOMAeC1tFS7TamlYu2iRarUdLEISDS87M3alp2fFi+q7vjjvuYMqUKbz11luZiYBFS7REK/dtEq3WoyUIwsEhp2YccBwHpRTvvvsuruuyZs0apkyZwmuvvUa/fv1ES7RE6xCzSbRaj5YgCN8/OZNJg513fpqm8cQTT1BYWMj8+fM59thjRUu0ROsQtEm0Wo+WIAjfPwe9Jq0xhgwZAsCCBQsOeGJf0RKttqaVizaJVuvREgTh++OgD2a7J8LhMHl5eaIlWqJ1EHVES7QEQTh45GyQJgiCIAiC0JbJyeZOQRAEQRCEto4EaYIgCIIgCDmIBGmCIAiCIAg5iARpgiAIgiAIOYgEaYJwkHjiiScoLi7mq6++OtimCIIgCDmIBGmCcIgxf/587rzzzoNthiAIgvAdI0GaIBxiLFiwgLvvvvtgmyEIgiB8x0iQJgiCIAiCkINIkCYI3wPvv/8+p59+Oh06dKBPnz7cf//9uG72ONIvv/wyY8eOpXfv3pSXl9OnTx9uvfVW4vF4ZpsJEyYwc+ZMAIqLizOPhnVtzz//PKeddhoVFRV06dKFsWPHsnLlyu9nRwVBEIQWI6cmWBeE1sjKlSsZNWoUBQUFXHfddfh8PmbNmrXbFD1/+9vf0HWdyy+/nOLiYpYuXcrUqVPZuHEj06dPB+CSSy5h48aNvP322zz88MOZz7Zv3x6AP/3pT9x2222MHDmS888/n3A4zPTp0xk+fDhvvfUWhx9++Pe234IgCMKBIdNCCcJ3zLhx45g/fz7vvfce3bp1A6CqqooBAwawY8cOPvnkE7p27UokEiEUCmV9dvLkyUyaNInPPvuMyspKAK6++mpmzpxJTU1N1rbr16+nf//+XHvttdx0002Z5Zs2beL444/n7LPP5qGHHvqO91YQBEFoKaS5UxC+Q2zb5vXXX+eMM87IBGjgZb7OO++8rG3TAZrjONTW1lJdXc1JJ52E67p88skn+/yuOXPmYFkWo0ePprq6OvMwTZOBAwfy9ttvt+zOCYIgCN8p0twpCN8hVVVVRCIRevTosdu67t27Z71fsWIFt9xyC//617+IRqNZ62pra/f5XWvXrgXg+OOPb3T9rlk6QRAEIbeRIE0QvkPSnQOUUntcB14QNnLkSILBIL///e/p1q0bwWCQb775hiuuuALHcfb5XeltnnvuOQxj9z9tTZPEuSAIwqGEBGmC8B1SVlZGKBRi1apVu61LZ74A3nnnHaqqqpg7dy4/+tGPMsvfeOON3T7XWMAHZJpTO3XqRK9evQ7UdEEQBOEgI7fWgvAdous6Q4YMYf78+Xz55ZeZ5VVVVTz77LNZ20F2ds1xHKZNm7abZrrZcteOA2effTaGYXDnnXc2mnmrqqo6sJ0RBEEQvlckkyYI3zE333wzCxcu5Mwzz2T8+PGYpsmsWbPo3LlzptZs0KBBtGvXjgkTJvCLX/wCwzB46aWXqK+v302vf//+AFx//fUMHToUwzA444wzOPzww7n99tv57W9/y9ChQxk5ciQlJSWsX7+eV199lYEDB3L//fd/r/suCIIg7D8yBIcgfA8sXbqU3/3udyxbtoyysjIuu+wyysrK+NWvfpUZguODDz7IbJOXl8fZZ5/NpZdeyuDBg5k2bRoXXngh4PUYvfnmm/nHP/7B1q1bM70/u3btCnjTRk2dOpVPPvkEy7KoqKhg0KBBjB8/ngEDBhzMwyAIgiA0AwnSBEEQBEEQchCpSRMEQRAEQchBJEgTBEEQBEHIQSRIEwRBEARByEEkSBMEQRAEQchBJEgTBEEQBEHIQSRIEwRBEARByEEkSBMEQRAEQchBJEgTBEEQBEHIQSRIEwRBEARByEEkSBMEQRAEQchB/h95SYvJmVJ+2QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cases.top(15).following('2020-03-10').oplot(height=6, width=6)\n",
    "_ = plots.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=sectionDeaths></a>\n",
    "## Deaths to date by county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deaths.top(15).following('2020-03-10').oplot(height=6, width=6)\n",
    "_ = plots.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sectionTrends'></a>\n",
    "## Growth trends by county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>date</th> <th>Los Angeles</th> <th>new Los Angeles</th> <th>% newLos Angeles</th> <th>rate Los Angeles</th> <th>Santa Clara</th> <th>new Santa Clara</th> <th>% newSanta Clara</th> <th>rate Santa Clara</th> <th>San Diego</th> <th>new San Diego</th> <th>% newSan Diego</th> <th>rate San Diego</th> <th>Orange</th> <th>new Orange</th> <th>% newOrange</th> <th>rate Orange</th> <th>San Francisco</th> <th>new San Francisco</th> <th>% newSan Francisco</th> <th>rate San Francisco</th> <th>Alameda</th> <th>new Alameda</th> <th>% newAlameda</th> <th>rate Alameda</th> <th>San Mateo</th> <th>new San Mateo</th> <th>% newSan Mateo</th> <th>rate San Mateo</th> <th>Riverside</th> <th>new Riverside</th> <th>% newRiverside</th> <th>rate Riverside</th> <th>Contra Costa</th> <th>new Contra Costa</th> <th>% newContra Costa</th> <th>rate Contra Costa</th> <th>Sacramento</th> <th>new Sacramento</th> <th>% newSacramento</th> <th>rate Sacramento</th> <th>San Joaquin</th> <th>new San Joaquin</th> <th>% newSan Joaquin</th> <th>rate San Joaquin</th> <th>Ventura</th> <th>new Ventura</th> <th>% newVentura</th> <th>rate Ventura</th> <th>Marin</th> <th>new Marin</th> <th>% newMarin</th> <th>rate Marin</th> <th>San Luis Obispo</th> <th>new San Luis Obispo</th> <th>% newSan Luis Obispo</th> <th>rate San Luis Obispo</th> <th>San Bernardino</th> <th>new San Bernardino</th> <th>% newSan Bernardino</th> <th>rate San Bernardino</th> <th>Santa Barbara</th> <th>new Santa Barbara</th> <th>% newSanta Barbara</th> <th>rate Santa Barbara</th> <th>Sonoma</th> <th>new Sonoma</th> <th>% newSonoma</th> <th>rate Sonoma</th> <th>Kern</th> <th>new Kern</th> <th>% newKern</th> <th>rate Kern</th> <th>Placer</th> <th>new Placer</th> <th>% newPlacer</th> <th>rate Placer</th> <th>Fresno</th> <th>new Fresno</th> <th>% newFresno</th> <th>rate Fresno</th> <th>Santa Cruz</th> <th>new Santa Cruz</th> <th>% newSanta Cruz</th> <th>rate Santa Cruz</th> <th>Solano</th> <th>new Solano</th> <th>% newSolano</th> <th>rate Solano</th> <th>Stanislaus</th> <th>new Stanislaus</th> <th>% newStanislaus</th> <th>rate Stanislaus</th> <th>Tulare</th> <th>new Tulare</th> <th>% newTulare</th> <th>rate Tulare</th> <th>Monterey</th> <th>new Monterey</th> <th>% newMonterey</th> <th>rate Monterey</th> <th>Imperial</th> <th>new Imperial</th> <th>% newImperial</th> <th>rate Imperial</th> <th>Humboldt</th> <th>new Humboldt</th> <th>% newHumboldt</th> <th>rate Humboldt</th> <th>Yolo</th> <th>new Yolo</th> <th>% newYolo</th> <th>rate Yolo</th> <th>Madera</th> <th>new Madera</th> <th>% newMadera</th> <th>rate Madera</th> <th>El Dorado</th> <th>new El Dorado</th> <th>% newEl Dorado</th> <th>rate El Dorado</th> <th>Nevada</th> <th>new Nevada</th> <th>% newNevada</th> <th>rate Nevada</th> <th>San Benito</th> <th>new San Benito</th> <th>% newSan Benito</th> <th>rate San Benito</th> <th>Napa</th> <th>new Napa</th> <th>% newNapa</th> <th>rate Napa</th> <th>Mono</th> <th>new Mono</th> <th>% newMono</th> <th>rate Mono</th> <th>Merced</th> <th>new Merced</th> <th>% newMerced</th> <th>rate Merced</th> <th>Butte</th> <th>new Butte</th> <th>% newButte</th> <th>rate Butte</th> <th>Inyo</th> <th>new Inyo</th> <th>% newInyo</th> <th>rate Inyo</th> <th>Calaveras</th> <th>new Calaveras</th> <th>% newCalaveras</th> <th>rate Calaveras</th> <th>Shasta</th> <th>new Shasta</th> <th>% newShasta</th> <th>rate Shasta</th> <th>Siskiyou</th> <th>new Siskiyou</th> <th>% newSiskiyou</th> <th>rate Siskiyou</th> <th>Yuba</th> <th>new Yuba</th> <th>% newYuba</th> <th>rate Yuba</th> <th>Amador</th> <th>new Amador</th> <th>% newAmador</th> <th>rate Amador</th> <th>Mendocino</th> <th>new Mendocino</th> <th>% newMendocino</th> <th>rate Mendocino</th> <th>Sutter</th> <th>new Sutter</th> <th>% newSutter</th> <th>rate Sutter</th> <th>Colusa</th> <th>new Colusa</th> <th>% newColusa</th> <th>rate Colusa</th> <th>Glenn</th> <th>new Glenn</th> <th>% newGlenn</th> <th>rate Glenn</th> <th>Kings</th> <th>new Kings</th> <th>% newKings</th> <th>rate Kings</th> <th>Unknown</th> <th>new Unknown</th> <th>% newUnknown</th> <th>rate Unknown</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>2020-03-22</td> <td>421        </td> <td>70             </td> <td>16.63%          </td> <td>1.19943         </td> <td>303        </td> <td>40             </td> <td>13.20%          </td> <td>1.15209         </td> <td>205      </td> <td>46           </td> <td>22.44%        </td> <td>1.28931       </td> <td>95    </td> <td>17        </td> <td>17.89%     </td> <td>1.21795    </td> <td>111          </td> <td>27               </td> <td>24.32%            </td> <td>1.32143           </td> <td>127    </td> <td>40         </td> <td>31.50%      </td> <td>1.45977     </td> <td>117      </td> <td>7            </td> <td>5.98%         </td> <td>1.06364       </td> <td>45       </td> <td>15           </td> <td>33.33%        </td> <td>1.5           </td> <td>61          </td> <td>10              </td> <td>16.39%           </td> <td>1.19608          </td> <td>52        </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>41         </td> <td>10             </td> <td>24.39%          </td> <td>1.32258         </td> <td>30     </td> <td>4          </td> <td>13.33%      </td> <td>1.15385     </td> <td>38   </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>27             </td> <td>0                  </td> <td>0.00%               </td> <td>1                   </td> <td>17            </td> <td>8                 </td> <td>47.06%             </td> <td>1.88889            </td> <td>18           </td> <td>1                </td> <td>5.56%             </td> <td>1.05882           </td> <td>11    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>5   </td> <td>1       </td> <td>20.00%   </td> <td>1.25     </td> <td>12    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>10    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>15        </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>19    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>8         </td> <td>3             </td> <td>37.50%         </td> <td>1.6            </td> <td>12    </td> <td>1         </td> <td>8.33%      </td> <td>1.09091    </td> <td>14      </td> <td>3           </td> <td>21.43%       </td> <td>1.27273      </td> <td>4       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>2       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>6   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>1     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>5         </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>3   </td> <td>2       </td> <td>66.67%   </td> <td>3        </td> <td>0   </td> <td>0       </td> <td>nan%     </td> <td>nan      </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>2    </td> <td>1        </td> <td>50.00%    </td> <td>2         </td> <td>0   </td> <td>0       </td> <td>nan%     </td> <td>nan      </td> <td>0        </td> <td>0            </td> <td>nan%          </td> <td>nan           </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>2   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>1     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>1        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1      </td> <td>1          </td> <td>100.00%     </td> <td>inf         </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-23</td> <td>536        </td> <td>115            </td> <td>21.46%          </td> <td>1.27316         </td> <td>321        </td> <td>18             </td> <td>5.61%           </td> <td>1.05941         </td> <td>230      </td> <td>25           </td> <td>10.87%        </td> <td>1.12195       </td> <td>125   </td> <td>30        </td> <td>24.00%     </td> <td>1.31579    </td> <td>134          </td> <td>23               </td> <td>17.16%            </td> <td>1.20721           </td> <td>139    </td> <td>12         </td> <td>8.63%       </td> <td>1.09449     </td> <td>142      </td> <td>25           </td> <td>17.61%        </td> <td>1.21368       </td> <td>48       </td> <td>3            </td> <td>6.25%         </td> <td>1.06667       </td> <td>71          </td> <td>10              </td> <td>14.08%           </td> <td>1.16393          </td> <td>87        </td> <td>35            </td> <td>40.23%         </td> <td>1.67308        </td> <td>51         </td> <td>10             </td> <td>19.61%          </td> <td>1.2439          </td> <td>35     </td> <td>5          </td> <td>14.29%      </td> <td>1.16667     </td> <td>47   </td> <td>9        </td> <td>19.15%    </td> <td>1.23684   </td> <td>33             </td> <td>6                  </td> <td>18.18%              </td> <td>1.22222             </td> <td>17            </td> <td>0                 </td> <td>0.00%              </td> <td>1                  </td> <td>18           </td> <td>0                </td> <td>0.00%             </td> <td>1                 </td> <td>29    </td> <td>18        </td> <td>62.07%     </td> <td>2.63636    </td> <td>5   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>20    </td> <td>8         </td> <td>40.00%     </td> <td>1.66667    </td> <td>13    </td> <td>3         </td> <td>23.08%     </td> <td>1.3        </td> <td>22        </td> <td>7             </td> <td>31.82%         </td> <td>1.46667        </td> <td>21    </td> <td>2         </td> <td>9.52%      </td> <td>1.10526    </td> <td>10        </td> <td>2             </td> <td>20.00%         </td> <td>1.25           </td> <td>16    </td> <td>4         </td> <td>25.00%     </td> <td>1.33333    </td> <td>20      </td> <td>6           </td> <td>30.00%       </td> <td>1.42857      </td> <td>4       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>2       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>8   </td> <td>2       </td> <td>25.00%   </td> <td>1.33333  </td> <td>6     </td> <td>3         </td> <td>50.00%     </td> <td>2          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>3     </td> <td>2         </td> <td>66.67%     </td> <td>3          </td> <td>6         </td> <td>1             </td> <td>16.67%         </td> <td>1.2            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>0   </td> <td>0       </td> <td>nan%     </td> <td>nan      </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>3    </td> <td>1        </td> <td>33.33%    </td> <td>1.5       </td> <td>0   </td> <td>0       </td> <td>nan%     </td> <td>nan      </td> <td>0        </td> <td>0            </td> <td>nan%          </td> <td>nan           </td> <td>3     </td> <td>1         </td> <td>33.33%     </td> <td>1.5        </td> <td>3       </td> <td>1           </td> <td>33.33%       </td> <td>1.5          </td> <td>3   </td> <td>1       </td> <td>33.33%   </td> <td>1.5      </td> <td>2     </td> <td>1         </td> <td>50.00%     </td> <td>2          </td> <td>1        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-24</td> <td>662        </td> <td>126            </td> <td>19.03%          </td> <td>1.23507         </td> <td>375        </td> <td>54             </td> <td>14.40%          </td> <td>1.16822         </td> <td>242      </td> <td>12           </td> <td>4.96%         </td> <td>1.05217       </td> <td>152   </td> <td>27        </td> <td>17.76%     </td> <td>1.216      </td> <td>152          </td> <td>18               </td> <td>11.84%            </td> <td>1.13433           </td> <td>151    </td> <td>12         </td> <td>7.95%       </td> <td>1.08633     </td> <td>161      </td> <td>19           </td> <td>11.80%        </td> <td>1.1338        </td> <td>59       </td> <td>11           </td> <td>18.64%        </td> <td>1.22917       </td> <td>86          </td> <td>15              </td> <td>17.44%           </td> <td>1.21127          </td> <td>87        </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>60         </td> <td>9              </td> <td>15.00%          </td> <td>1.17647         </td> <td>39     </td> <td>4          </td> <td>10.26%      </td> <td>1.11429     </td> <td>53   </td> <td>6        </td> <td>11.32%    </td> <td>1.12766   </td> <td>42             </td> <td>9                  </td> <td>21.43%              </td> <td>1.27273             </td> <td>38            </td> <td>21                </td> <td>55.26%             </td> <td>2.23529            </td> <td>24           </td> <td>6                </td> <td>25.00%            </td> <td>1.33333           </td> <td>34    </td> <td>5         </td> <td>14.71%     </td> <td>1.17241    </td> <td>14  </td> <td>9       </td> <td>64.29%   </td> <td>2.8      </td> <td>26    </td> <td>6         </td> <td>23.08%     </td> <td>1.3        </td> <td>18    </td> <td>5         </td> <td>27.78%     </td> <td>1.38462    </td> <td>24        </td> <td>2             </td> <td>8.33%          </td> <td>1.09091        </td> <td>29    </td> <td>8         </td> <td>27.59%     </td> <td>1.38095    </td> <td>11        </td> <td>1             </td> <td>9.09%          </td> <td>1.1            </td> <td>17    </td> <td>1         </td> <td>5.88%      </td> <td>1.0625     </td> <td>20      </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>9       </td> <td>5           </td> <td>55.56%       </td> <td>2.25         </td> <td>5       </td> <td>3           </td> <td>60.00%       </td> <td>2.5          </td> <td>10  </td> <td>2       </td> <td>20.00%   </td> <td>1.25     </td> <td>6     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3        </td> <td>1            </td> <td>33.33%        </td> <td>1.5           </td> <td>4     </td> <td>1         </td> <td>25.00%     </td> <td>1.33333    </td> <td>7         </td> <td>1             </td> <td>14.29%         </td> <td>1.16667        </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2   </td> <td>2       </td> <td>100.00%  </td> <td>inf      </td> <td>1     </td> <td>1         </td> <td>100.00%    </td> <td>inf        </td> <td>4    </td> <td>1        </td> <td>25.00%    </td> <td>1.33333   </td> <td>0   </td> <td>0       </td> <td>nan%     </td> <td>nan      </td> <td>2        </td> <td>2            </td> <td>100.00%       </td> <td>inf           </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>1            </td> <td>50.00%        </td> <td>2             </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-25</td> <td>799        </td> <td>137            </td> <td>17.15%          </td> <td>1.20695         </td> <td>459        </td> <td>84             </td> <td>18.30%          </td> <td>1.224           </td> <td>297      </td> <td>55           </td> <td>18.52%        </td> <td>1.22727       </td> <td>187   </td> <td>35        </td> <td>18.72%     </td> <td>1.23026    </td> <td>181          </td> <td>29               </td> <td>16.02%            </td> <td>1.19079           </td> <td>156    </td> <td>5          </td> <td>3.21%       </td> <td>1.03311     </td> <td>165      </td> <td>4            </td> <td>2.42%         </td> <td>1.02484       </td> <td>107      </td> <td>48           </td> <td>44.86%        </td> <td>1.81356       </td> <td>108         </td> <td>22              </td> <td>20.37%           </td> <td>1.25581          </td> <td>112       </td> <td>25            </td> <td>22.32%         </td> <td>1.28736        </td> <td>71         </td> <td>11             </td> <td>15.49%          </td> <td>1.18333         </td> <td>50     </td> <td>11         </td> <td>22.00%      </td> <td>1.28205     </td> <td>53   </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>46             </td> <td>4                  </td> <td>8.70%               </td> <td>1.09524             </td> <td>54            </td> <td>16                </td> <td>29.63%             </td> <td>1.42105            </td> <td>26           </td> <td>2                </td> <td>7.69%             </td> <td>1.08333           </td> <td>39    </td> <td>5         </td> <td>12.82%     </td> <td>1.14706    </td> <td>24  </td> <td>10      </td> <td>41.67%   </td> <td>1.71429  </td> <td>30    </td> <td>4         </td> <td>13.33%     </td> <td>1.15385    </td> <td>19    </td> <td>1         </td> <td>5.26%      </td> <td>1.05556    </td> <td>25        </td> <td>1             </td> <td>4.00%          </td> <td>1.04167        </td> <td>36    </td> <td>7         </td> <td>19.44%     </td> <td>1.24138    </td> <td>12        </td> <td>1             </td> <td>8.33%          </td> <td>1.09091        </td> <td>18    </td> <td>1         </td> <td>5.56%      </td> <td>1.05882    </td> <td>24      </td> <td>4           </td> <td>16.67%       </td> <td>1.2          </td> <td>9       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>10      </td> <td>5           </td> <td>50.00%       </td> <td>2            </td> <td>11  </td> <td>1       </td> <td>9.09%    </td> <td>1.1      </td> <td>7     </td> <td>1         </td> <td>14.29%     </td> <td>1.16667    </td> <td>3        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>4     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>9         </td> <td>2             </td> <td>22.22%         </td> <td>1.28571        </td> <td>6   </td> <td>3       </td> <td>50.00%   </td> <td>2        </td> <td>4   </td> <td>2       </td> <td>50.00%   </td> <td>2        </td> <td>1     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>4    </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>1   </td> <td>1       </td> <td>100.00%  </td> <td>inf      </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>2     </td> <td>2         </td> <td>100.00%    </td> <td>inf        </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-26</td> <td>1216       </td> <td>417            </td> <td>34.29%          </td> <td>1.5219          </td> <td>542        </td> <td>83             </td> <td>15.31%          </td> <td>1.18083         </td> <td>341      </td> <td>44           </td> <td>12.90%        </td> <td>1.14815       </td> <td>256   </td> <td>69        </td> <td>26.95%     </td> <td>1.36898    </td> <td>226          </td> <td>45               </td> <td>19.91%            </td> <td>1.24862           </td> <td>199    </td> <td>43         </td> <td>21.61%      </td> <td>1.27564     </td> <td>195      </td> <td>30           </td> <td>15.38%        </td> <td>1.18182       </td> <td>107      </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>131         </td> <td>23              </td> <td>17.56%           </td> <td>1.21296          </td> <td>112       </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>83         </td> <td>12             </td> <td>14.46%          </td> <td>1.16901         </td> <td>61     </td> <td>11         </td> <td>18.03%      </td> <td>1.22        </td> <td>65   </td> <td>12       </td> <td>18.46%    </td> <td>1.22642   </td> <td>54             </td> <td>8                  </td> <td>14.81%              </td> <td>1.17391             </td> <td>55            </td> <td>1                 </td> <td>1.82%              </td> <td>1.01852            </td> <td>32           </td> <td>6                </td> <td>18.75%            </td> <td>1.23077           </td> <td>49    </td> <td>10        </td> <td>20.41%     </td> <td>1.25641    </td> <td>33  </td> <td>9       </td> <td>27.27%   </td> <td>1.375    </td> <td>30    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>27    </td> <td>8         </td> <td>29.63%     </td> <td>1.42105    </td> <td>32        </td> <td>7             </td> <td>21.88%         </td> <td>1.28           </td> <td>39    </td> <td>3         </td> <td>7.69%      </td> <td>1.08333    </td> <td>17        </td> <td>5             </td> <td>29.41%         </td> <td>1.41667        </td> <td>20    </td> <td>2         </td> <td>10.00%     </td> <td>1.11111    </td> <td>24      </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>17      </td> <td>8           </td> <td>47.06%       </td> <td>1.88889      </td> <td>12      </td> <td>2           </td> <td>16.67%       </td> <td>1.2          </td> <td>11  </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>7     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>9        </td> <td>6            </td> <td>66.67%        </td> <td>3             </td> <td>8     </td> <td>4         </td> <td>50.00%     </td> <td>2          </td> <td>9         </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>7   </td> <td>1       </td> <td>14.29%   </td> <td>1.16667  </td> <td>6   </td> <td>2       </td> <td>33.33%   </td> <td>1.5      </td> <td>4     </td> <td>3         </td> <td>75.00%     </td> <td>4          </td> <td>5    </td> <td>1        </td> <td>20.00%    </td> <td>1.25      </td> <td>2   </td> <td>1       </td> <td>50.00%   </td> <td>2        </td> <td>3        </td> <td>1            </td> <td>33.33%        </td> <td>1.5           </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>0     </td> <td>0         </td> <td>nan%       </td> <td>nan        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-27</td> <td>1465       </td> <td>249            </td> <td>17.00%          </td> <td>1.20477         </td> <td>574        </td> <td>32             </td> <td>5.57%           </td> <td>1.05904         </td> <td>417      </td> <td>76           </td> <td>18.23%        </td> <td>1.22287       </td> <td>321   </td> <td>65        </td> <td>20.25%     </td> <td>1.25391    </td> <td>282          </td> <td>56               </td> <td>19.86%            </td> <td>1.24779           </td> <td>241    </td> <td>42         </td> <td>17.43%      </td> <td>1.21106     </td> <td>239      </td> <td>44           </td> <td>18.41%        </td> <td>1.22564       </td> <td>185      </td> <td>78           </td> <td>42.16%        </td> <td>1.72897       </td> <td>151         </td> <td>20              </td> <td>13.25%           </td> <td>1.15267          </td> <td>164       </td> <td>52            </td> <td>31.71%         </td> <td>1.46429        </td> <td>93         </td> <td>10             </td> <td>10.75%          </td> <td>1.12048         </td> <td>83     </td> <td>22         </td> <td>26.51%      </td> <td>1.36066     </td> <td>69   </td> <td>4        </td> <td>5.80%     </td> <td>1.06154   </td> <td>59             </td> <td>5                  </td> <td>8.47%               </td> <td>1.09259             </td> <td>64            </td> <td>9                 </td> <td>14.06%             </td> <td>1.16364            </td> <td>47           </td> <td>15               </td> <td>31.91%            </td> <td>1.46875           </td> <td>50    </td> <td>1         </td> <td>2.00%      </td> <td>1.02041    </td> <td>41  </td> <td>8       </td> <td>19.51%   </td> <td>1.24242  </td> <td>41    </td> <td>11        </td> <td>26.83%     </td> <td>1.36667    </td> <td>31    </td> <td>4         </td> <td>12.90%     </td> <td>1.14815    </td> <td>34        </td> <td>2             </td> <td>5.88%          </td> <td>1.0625         </td> <td>39    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>23        </td> <td>6             </td> <td>26.09%         </td> <td>1.35294        </td> <td>24    </td> <td>4         </td> <td>16.67%     </td> <td>1.2        </td> <td>27      </td> <td>3           </td> <td>11.11%       </td> <td>1.125        </td> <td>21      </td> <td>4           </td> <td>19.05%       </td> <td>1.23529      </td> <td>14      </td> <td>2           </td> <td>14.29%       </td> <td>1.16667      </td> <td>16  </td> <td>5       </td> <td>31.25%   </td> <td>1.45455  </td> <td>11    </td> <td>4         </td> <td>36.36%     </td> <td>1.57143    </td> <td>12       </td> <td>3            </td> <td>25.00%        </td> <td>1.33333       </td> <td>12    </td> <td>4         </td> <td>33.33%     </td> <td>1.5        </td> <td>11        </td> <td>2             </td> <td>18.18%         </td> <td>1.22222        </td> <td>10  </td> <td>3       </td> <td>30.00%   </td> <td>1.42857  </td> <td>8   </td> <td>2       </td> <td>25.00%   </td> <td>1.33333  </td> <td>7     </td> <td>3         </td> <td>42.86%     </td> <td>1.75       </td> <td>5    </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>5   </td> <td>3       </td> <td>60.00%   </td> <td>2.5      </td> <td>3        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>1     </td> <td>1         </td> <td>100.00%    </td> <td>inf        </td> <td>0    </td> <td>0        </td> <td>nan%      </td> <td>nan       </td> <td>1    </td> <td>1        </td> <td>100.00%   </td> <td>inf       </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2020-03-28</td> <td>1804       </td> <td>339            </td> <td>18.79%          </td> <td>1.2314          </td> <td>591        </td> <td>17             </td> <td>2.88%           </td> <td>1.02962         </td> <td>488      </td> <td>71           </td> <td>14.55%        </td> <td>1.17026       </td> <td>321   </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>308          </td> <td>26               </td> <td>8.44%             </td> <td>1.0922            </td> <td>277    </td> <td>36         </td> <td>13.00%      </td> <td>1.14938     </td> <td>274      </td> <td>35           </td> <td>12.77%        </td> <td>1.14644       </td> <td>185      </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>168         </td> <td>17              </td> <td>10.12%           </td> <td>1.11258          </td> <td>164       </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>108        </td> <td>15             </td> <td>13.89%          </td> <td>1.16129         </td> <td>98     </td> <td>15         </td> <td>15.31%      </td> <td>1.18072     </td> <td>74   </td> <td>5        </td> <td>6.76%     </td> <td>1.07246   </td> <td>67             </td> <td>8                  </td> <td>11.94%              </td> <td>1.13559             </td> <td>64            </td> <td>0                 </td> <td>0.00%              </td> <td>1                  </td> <td>64           </td> <td>17               </td> <td>26.56%            </td> <td>1.3617            </td> <td>50    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>47  </td> <td>6       </td> <td>12.77%   </td> <td>1.14634  </td> <td>44    </td> <td>3         </td> <td>6.82%      </td> <td>1.07317    </td> <td>43    </td> <td>12        </td> <td>27.91%     </td> <td>1.3871     </td> <td>39        </td> <td>5             </td> <td>12.82%         </td> <td>1.14706        </td> <td>39    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>29        </td> <td>6             </td> <td>20.69%         </td> <td>1.26087        </td> <td>29    </td> <td>5         </td> <td>17.24%     </td> <td>1.20833    </td> <td>27      </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>25      </td> <td>4           </td> <td>16.00%       </td> <td>1.19048      </td> <td>18      </td> <td>4           </td> <td>22.22%       </td> <td>1.28571      </td> <td>16  </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>15    </td> <td>4         </td> <td>26.67%     </td> <td>1.36364    </td> <td>12       </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>12    </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>11        </td> <td>0             </td> <td>0.00%          </td> <td>1              </td> <td>10  </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>8   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>7     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>5    </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>5   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>3        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>3     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>3       </td> <td>0           </td> <td>0.00%        </td> <td>1            </td> <td>3   </td> <td>0       </td> <td>0.00%    </td> <td>1        </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>2        </td> <td>0            </td> <td>0.00%         </td> <td>1             </td> <td>2     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>1     </td> <td>0         </td> <td>0.00%      </td> <td>1          </td> <td>1    </td> <td>1        </td> <td>100.00%   </td> <td>inf       </td> <td>1    </td> <td>0        </td> <td>0.00%     </td> <td>1         </td> <td>1      </td> <td>0          </td> <td>0.00%       </td> <td>1           </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "date       | Los Angeles | new Los Angeles | % newLos Angeles | rate Los Angeles | Santa Clara | new Santa Clara | % newSanta Clara | rate Santa Clara | San Diego | new San Diego | % newSan Diego | rate San Diego | Orange | new Orange | % newOrange | rate Orange | San Francisco | new San Francisco | % newSan Francisco | rate San Francisco | Alameda | new Alameda | % newAlameda | rate Alameda | San Mateo | new San Mateo | % newSan Mateo | rate San Mateo | Riverside | new Riverside | % newRiverside | rate Riverside | Contra Costa | new Contra Costa | % newContra Costa | rate Contra Costa | Sacramento | new Sacramento | % newSacramento | rate Sacramento | San Joaquin | new San Joaquin | % newSan Joaquin | rate San Joaquin | Ventura | new Ventura | % newVentura | rate Ventura | Marin | new Marin | % newMarin | rate Marin | San Luis Obispo | new San Luis Obispo | % newSan Luis Obispo | rate San Luis Obispo | San Bernardino | new San Bernardino | % newSan Bernardino | rate San Bernardino | Santa Barbara | new Santa Barbara | % newSanta Barbara | rate Santa Barbara | Sonoma | new Sonoma | % newSonoma | rate Sonoma | Kern | new Kern | % newKern | rate Kern | Placer | new Placer | % newPlacer | rate Placer | Fresno | new Fresno | % newFresno | rate Fresno | Santa Cruz | new Santa Cruz | % newSanta Cruz | rate Santa Cruz | Solano | new Solano | % newSolano | rate Solano | Stanislaus | new Stanislaus | % newStanislaus | rate Stanislaus | Tulare | new Tulare | % newTulare | rate Tulare | Monterey | new Monterey | % newMonterey | rate Monterey | Imperial | new Imperial | % newImperial | rate Imperial | Humboldt | new Humboldt | % newHumboldt | rate Humboldt | Yolo | new Yolo | % newYolo | rate Yolo | Madera | new Madera | % newMadera | rate Madera | El Dorado | new El Dorado | % newEl Dorado | rate El Dorado | Nevada | new Nevada | % newNevada | rate Nevada | San Benito | new San Benito | % newSan Benito | rate San Benito | Napa | new Napa | % newNapa | rate Napa | Mono | new Mono | % newMono | rate Mono | Merced | new Merced | % newMerced | rate Merced | Butte | new Butte | % newButte | rate Butte | Inyo | new Inyo | % newInyo | rate Inyo | Calaveras | new Calaveras | % newCalaveras | rate Calaveras | Shasta | new Shasta | % newShasta | rate Shasta | Siskiyou | new Siskiyou | % newSiskiyou | rate Siskiyou | Yuba | new Yuba | % newYuba | rate Yuba | Amador | new Amador | % newAmador | rate Amador | Mendocino | new Mendocino | % newMendocino | rate Mendocino | Sutter | new Sutter | % newSutter | rate Sutter | Colusa | new Colusa | % newColusa | rate Colusa | Glenn | new Glenn | % newGlenn | rate Glenn | Kings | new Kings | % newKings | rate Kings | Unknown | new Unknown | % newUnknown | rate Unknown\n",
       "2020-03-22 | 421         | 70              | 16.63%           | 1.19943          | 303         | 40              | 13.20%           | 1.15209          | 205       | 46            | 22.44%         | 1.28931        | 95     | 17         | 17.89%      | 1.21795     | 111           | 27                | 24.32%             | 1.32143            | 127     | 40          | 31.50%       | 1.45977      | 117       | 7             | 5.98%          | 1.06364        | 45        | 15            | 33.33%         | 1.5            | 61           | 10               | 16.39%            | 1.19608           | 52         | 0              | 0.00%           | 1               | 41          | 10              | 24.39%           | 1.32258          | 30      | 4           | 13.33%       | 1.15385      | 38    | 0         | 0.00%      | 1          | 27              | 0                   | 0.00%                | 1                    | 17             | 8                  | 47.06%              | 1.88889             | 18            | 1                 | 5.56%              | 1.05882            | 11     | 0          | 0.00%       | 1           | 5    | 1        | 20.00%    | 1.25      | 12     | 0          | 0.00%       | 1           | 10     | 0          | 0.00%       | 1           | 15         | 0              | 0.00%           | 1               | 19     | 0          | 0.00%       | 1           | 8          | 3              | 37.50%          | 1.6             | 12     | 1          | 8.33%       | 1.09091     | 14       | 3            | 21.43%        | 1.27273       | 4        | 0            | 0.00%         | 1             | 2        | 0            | 0.00%         | 1             | 6    | 0        | 0.00%     | 1         | 3      | 0          | 0.00%       | 1           | 2         | 0             | 0.00%          | 1              | 1      | 0          | 0.00%       | 1           | 5          | 0              | 0.00%           | 1               | 3    | 2        | 66.67%    | 3         | 0    | 0        | nan%      | nan       | 0      | 0          | nan%        | nan         | 2     | 1         | 50.00%     | 2          | 0    | 0        | nan%      | nan       | 0         | 0             | nan%           | nan            | 2      | 0          | 0.00%       | 1           | 2        | 0            | 0.00%         | 1             | 2    | 0        | 0.00%     | 1         | 1      | 0          | 0.00%       | 1           | 1         | 0             | 0.00%          | 1              | 0      | 0          | nan%        | nan         | 0      | 0          | nan%        | nan         | 0     | 0         | nan%       | nan        | 0     | 0         | nan%       | nan        | 1       | 1           | 100.00%      | inf\n",
       "2020-03-23 | 536         | 115             | 21.46%           | 1.27316          | 321         | 18              | 5.61%            | 1.05941          | 230       | 25            | 10.87%         | 1.12195        | 125    | 30         | 24.00%      | 1.31579     | 134           | 23                | 17.16%             | 1.20721            | 139     | 12          | 8.63%        | 1.09449      | 142       | 25            | 17.61%         | 1.21368        | 48        | 3             | 6.25%          | 1.06667        | 71           | 10               | 14.08%            | 1.16393           | 87         | 35             | 40.23%          | 1.67308         | 51          | 10              | 19.61%           | 1.2439           | 35      | 5           | 14.29%       | 1.16667      | 47    | 9         | 19.15%     | 1.23684    | 33              | 6                   | 18.18%               | 1.22222              | 17             | 0                  | 0.00%               | 1                   | 18            | 0                 | 0.00%              | 1                  | 29     | 18         | 62.07%      | 2.63636     | 5    | 0        | 0.00%     | 1         | 20     | 8          | 40.00%      | 1.66667     | 13     | 3          | 23.08%      | 1.3         | 22         | 7              | 31.82%          | 1.46667         | 21     | 2          | 9.52%       | 1.10526     | 10         | 2              | 20.00%          | 1.25            | 16     | 4          | 25.00%      | 1.33333     | 20       | 6            | 30.00%        | 1.42857       | 4        | 0            | 0.00%         | 1             | 2        | 0            | 0.00%         | 1             | 8    | 2        | 25.00%    | 1.33333   | 6      | 3          | 50.00%      | 2           | 2         | 0             | 0.00%          | 1              | 3      | 2          | 66.67%      | 3           | 6          | 1              | 16.67%          | 1.2             | 3    | 0        | 0.00%     | 1         | 0    | 0        | nan%      | nan       | 0      | 0          | nan%        | nan         | 3     | 1         | 33.33%     | 1.5        | 0    | 0        | nan%      | nan       | 0         | 0             | nan%           | nan            | 3      | 1          | 33.33%      | 1.5         | 3        | 1            | 33.33%        | 1.5           | 3    | 1        | 33.33%    | 1.5       | 2      | 1          | 50.00%      | 2           | 1         | 0             | 0.00%          | 1              | 0      | 0          | nan%        | nan         | 0      | 0          | nan%        | nan         | 0     | 0         | nan%       | nan        | 0     | 0         | nan%       | nan        | 1       | 0           | 0.00%        | 1\n",
       "2020-03-24 | 662         | 126             | 19.03%           | 1.23507          | 375         | 54              | 14.40%           | 1.16822          | 242       | 12            | 4.96%          | 1.05217        | 152    | 27         | 17.76%      | 1.216       | 152           | 18                | 11.84%             | 1.13433            | 151     | 12          | 7.95%        | 1.08633      | 161       | 19            | 11.80%         | 1.1338         | 59        | 11            | 18.64%         | 1.22917        | 86           | 15               | 17.44%            | 1.21127           | 87         | 0              | 0.00%           | 1               | 60          | 9               | 15.00%           | 1.17647          | 39      | 4           | 10.26%       | 1.11429      | 53    | 6         | 11.32%     | 1.12766    | 42              | 9                   | 21.43%               | 1.27273              | 38             | 21                 | 55.26%              | 2.23529             | 24            | 6                 | 25.00%             | 1.33333            | 34     | 5          | 14.71%      | 1.17241     | 14   | 9        | 64.29%    | 2.8       | 26     | 6          | 23.08%      | 1.3         | 18     | 5          | 27.78%      | 1.38462     | 24         | 2              | 8.33%           | 1.09091         | 29     | 8          | 27.59%      | 1.38095     | 11         | 1              | 9.09%           | 1.1             | 17     | 1          | 5.88%       | 1.0625      | 20       | 0            | 0.00%         | 1             | 9        | 5            | 55.56%        | 2.25          | 5        | 3            | 60.00%        | 2.5           | 10   | 2        | 20.00%    | 1.25      | 6      | 0          | 0.00%       | 1           | 3         | 1             | 33.33%         | 1.5            | 4      | 1          | 25.00%      | 1.33333     | 7          | 1              | 14.29%          | 1.16667         | 3    | 0        | 0.00%     | 1         | 2    | 2        | 100.00%   | inf       | 1      | 1          | 100.00%     | inf         | 4     | 1         | 25.00%     | 1.33333    | 0    | 0        | nan%      | nan       | 2         | 2             | 100.00%        | inf            | 3      | 0          | 0.00%       | 1           | 3        | 0            | 0.00%         | 1             | 3    | 0        | 0.00%     | 1         | 2      | 0          | 0.00%       | 1           | 2         | 1             | 50.00%         | 2              | 0      | 0          | nan%        | nan         | 0      | 0          | nan%        | nan         | 0     | 0         | nan%       | nan        | 0     | 0         | nan%       | nan        | 1       | 0           | 0.00%        | 1\n",
       "2020-03-25 | 799         | 137             | 17.15%           | 1.20695          | 459         | 84              | 18.30%           | 1.224            | 297       | 55            | 18.52%         | 1.22727        | 187    | 35         | 18.72%      | 1.23026     | 181           | 29                | 16.02%             | 1.19079            | 156     | 5           | 3.21%        | 1.03311      | 165       | 4             | 2.42%          | 1.02484        | 107       | 48            | 44.86%         | 1.81356        | 108          | 22               | 20.37%            | 1.25581           | 112        | 25             | 22.32%          | 1.28736         | 71          | 11              | 15.49%           | 1.18333          | 50      | 11          | 22.00%       | 1.28205      | 53    | 0         | 0.00%      | 1          | 46              | 4                   | 8.70%                | 1.09524              | 54             | 16                 | 29.63%              | 1.42105             | 26            | 2                 | 7.69%              | 1.08333            | 39     | 5          | 12.82%      | 1.14706     | 24   | 10       | 41.67%    | 1.71429   | 30     | 4          | 13.33%      | 1.15385     | 19     | 1          | 5.26%       | 1.05556     | 25         | 1              | 4.00%           | 1.04167         | 36     | 7          | 19.44%      | 1.24138     | 12         | 1              | 8.33%           | 1.09091         | 18     | 1          | 5.56%       | 1.05882     | 24       | 4            | 16.67%        | 1.2           | 9        | 0            | 0.00%         | 1             | 10       | 5            | 50.00%        | 2             | 11   | 1        | 9.09%     | 1.1       | 7      | 1          | 14.29%      | 1.16667     | 3         | 0             | 0.00%          | 1              | 4      | 0          | 0.00%       | 1           | 9          | 2              | 22.22%          | 1.28571         | 6    | 3        | 50.00%    | 2         | 4    | 2        | 50.00%    | 2         | 1      | 0          | 0.00%       | 1           | 4     | 0         | 0.00%      | 1          | 1    | 1        | 100.00%   | inf       | 2         | 0             | 0.00%          | 1              | 3      | 0          | 0.00%       | 1           | 3        | 0            | 0.00%         | 1             | 3    | 0        | 0.00%     | 1         | 2      | 0          | 0.00%       | 1           | 2         | 0             | 0.00%          | 1              | 2      | 2          | 100.00%     | inf         | 0      | 0          | nan%        | nan         | 0     | 0         | nan%       | nan        | 0     | 0         | nan%       | nan        | 1       | 0           | 0.00%        | 1\n",
       "2020-03-26 | 1216        | 417             | 34.29%           | 1.5219           | 542         | 83              | 15.31%           | 1.18083          | 341       | 44            | 12.90%         | 1.14815        | 256    | 69         | 26.95%      | 1.36898     | 226           | 45                | 19.91%             | 1.24862            | 199     | 43          | 21.61%       | 1.27564      | 195       | 30            | 15.38%         | 1.18182        | 107       | 0             | 0.00%          | 1              | 131          | 23               | 17.56%            | 1.21296           | 112        | 0              | 0.00%           | 1               | 83          | 12              | 14.46%           | 1.16901          | 61      | 11          | 18.03%       | 1.22         | 65    | 12        | 18.46%     | 1.22642    | 54              | 8                   | 14.81%               | 1.17391              | 55             | 1                  | 1.82%               | 1.01852             | 32            | 6                 | 18.75%             | 1.23077            | 49     | 10         | 20.41%      | 1.25641     | 33   | 9        | 27.27%    | 1.375     | 30     | 0          | 0.00%       | 1           | 27     | 8          | 29.63%      | 1.42105     | 32         | 7              | 21.88%          | 1.28            | 39     | 3          | 7.69%       | 1.08333     | 17         | 5              | 29.41%          | 1.41667         | 20     | 2          | 10.00%      | 1.11111     | 24       | 0            | 0.00%         | 1             | 17       | 8            | 47.06%        | 1.88889       | 12       | 2            | 16.67%        | 1.2           | 11   | 0        | 0.00%     | 1         | 7      | 0          | 0.00%       | 1           | 9         | 6             | 66.67%         | 3              | 8      | 4          | 50.00%      | 2           | 9          | 0              | 0.00%           | 1               | 7    | 1        | 14.29%    | 1.16667   | 6    | 2        | 33.33%    | 1.5       | 4      | 3          | 75.00%      | 4           | 5     | 1         | 20.00%     | 1.25       | 2    | 1        | 50.00%    | 2         | 3         | 1             | 33.33%         | 1.5            | 3      | 0          | 0.00%       | 1           | 3        | 0            | 0.00%         | 1             | 3    | 0        | 0.00%     | 1         | 2      | 0          | 0.00%       | 1           | 2         | 0             | 0.00%          | 1              | 2      | 0          | 0.00%       | 1           | 0      | 0          | nan%        | nan         | 0     | 0         | nan%       | nan        | 0     | 0         | nan%       | nan        | 1       | 0           | 0.00%        | 1\n",
       "2020-03-27 | 1465        | 249             | 17.00%           | 1.20477          | 574         | 32              | 5.57%            | 1.05904          | 417       | 76            | 18.23%         | 1.22287        | 321    | 65         | 20.25%      | 1.25391     | 282           | 56                | 19.86%             | 1.24779            | 241     | 42          | 17.43%       | 1.21106      | 239       | 44            | 18.41%         | 1.22564        | 185       | 78            | 42.16%         | 1.72897        | 151          | 20               | 13.25%            | 1.15267           | 164        | 52             | 31.71%          | 1.46429         | 93          | 10              | 10.75%           | 1.12048          | 83      | 22          | 26.51%       | 1.36066      | 69    | 4         | 5.80%      | 1.06154    | 59              | 5                   | 8.47%                | 1.09259              | 64             | 9                  | 14.06%              | 1.16364             | 47            | 15                | 31.91%             | 1.46875            | 50     | 1          | 2.00%       | 1.02041     | 41   | 8        | 19.51%    | 1.24242   | 41     | 11         | 26.83%      | 1.36667     | 31     | 4          | 12.90%      | 1.14815     | 34         | 2              | 5.88%           | 1.0625          | 39     | 0          | 0.00%       | 1           | 23         | 6              | 26.09%          | 1.35294         | 24     | 4          | 16.67%      | 1.2         | 27       | 3            | 11.11%        | 1.125         | 21       | 4            | 19.05%        | 1.23529       | 14       | 2            | 14.29%        | 1.16667       | 16   | 5        | 31.25%    | 1.45455   | 11     | 4          | 36.36%      | 1.57143     | 12        | 3             | 25.00%         | 1.33333        | 12     | 4          | 33.33%      | 1.5         | 11         | 2              | 18.18%          | 1.22222         | 10   | 3        | 30.00%    | 1.42857   | 8    | 2        | 25.00%    | 1.33333   | 7      | 3          | 42.86%      | 1.75        | 5     | 0         | 0.00%      | 1          | 5    | 3        | 60.00%    | 2.5       | 3         | 0             | 0.00%          | 1              | 3      | 0          | 0.00%       | 1           | 3        | 0            | 0.00%         | 1             | 3    | 0        | 0.00%     | 1         | 2      | 0          | 0.00%       | 1           | 2         | 0             | 0.00%          | 1              | 2      | 0          | 0.00%       | 1           | 1      | 1          | 100.00%     | inf         | 0     | 0         | nan%       | nan        | 1     | 1         | 100.00%    | inf        | 1       | 0           | 0.00%        | 1\n",
       "2020-03-28 | 1804        | 339             | 18.79%           | 1.2314           | 591         | 17              | 2.88%            | 1.02962          | 488       | 71            | 14.55%         | 1.17026        | 321    | 0          | 0.00%       | 1           | 308           | 26                | 8.44%              | 1.0922             | 277     | 36          | 13.00%       | 1.14938      | 274       | 35            | 12.77%         | 1.14644        | 185       | 0             | 0.00%          | 1              | 168          | 17               | 10.12%            | 1.11258           | 164        | 0              | 0.00%           | 1               | 108         | 15              | 13.89%           | 1.16129          | 98      | 15          | 15.31%       | 1.18072      | 74    | 5         | 6.76%      | 1.07246    | 67              | 8                   | 11.94%               | 1.13559              | 64             | 0                  | 0.00%               | 1                   | 64            | 17                | 26.56%             | 1.3617             | 50     | 0          | 0.00%       | 1           | 47   | 6        | 12.77%    | 1.14634   | 44     | 3          | 6.82%       | 1.07317     | 43     | 12         | 27.91%      | 1.3871      | 39         | 5              | 12.82%          | 1.14706         | 39     | 0          | 0.00%       | 1           | 29         | 6              | 20.69%          | 1.26087         | 29     | 5          | 17.24%      | 1.20833     | 27       | 0            | 0.00%         | 1             | 25       | 4            | 16.00%        | 1.19048       | 18       | 4            | 22.22%        | 1.28571       | 16   | 0        | 0.00%     | 1         | 15     | 4          | 26.67%      | 1.36364     | 12        | 0             | 0.00%          | 1              | 12     | 0          | 0.00%       | 1           | 11         | 0              | 0.00%           | 1               | 10   | 0        | 0.00%     | 1         | 8    | 0        | 0.00%     | 1         | 7      | 0          | 0.00%       | 1           | 5     | 0         | 0.00%      | 1          | 5    | 0        | 0.00%     | 1         | 3         | 0             | 0.00%          | 1              | 3      | 0          | 0.00%       | 1           | 3        | 0            | 0.00%         | 1             | 3    | 0        | 0.00%     | 1         | 2      | 0          | 0.00%       | 1           | 2         | 0             | 0.00%          | 1              | 2      | 0          | 0.00%       | 1           | 1      | 0          | 0.00%       | 1           | 1     | 1         | 100.00%    | inf        | 1     | 0         | 0.00%      | 1          | 1       | 0           | 0.00%        | 1"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cases.order_cols().trend().take[-7:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f844caccd5f94da98f2ead88a61095ac",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='county', options=('Alameda', 'Amador', 'Butte', 'Calaveras', 'Colu…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_cty(county):\n",
    "    cases.extract(county).trend().take[-10:].show()\n",
    "    cases.extract(county).trend().select(['date', county, 'new']).take[-20:].plot('date')\n",
    "    _ = plots.xticks(rotation=45)\n",
    "    \n",
    "_ = interact(show_cty, county=counties)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sectionProj'></a>\n",
    "## Projection of cases in one county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "36fe4751f14d4f63bccc2206f276a401",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='county', options=('Alameda', 'Amador', 'Butte', 'Calaveras', 'Colu…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def proj_cty(county):\n",
    "    proj = project_trend(cases.extract(county).trend().take[-7:], 14)\n",
    "    proj.show()\n",
    "    proj.select(['date', county, 'new']).plot('date', width = 7)\n",
    "    last = cases['date'][-1]\n",
    "    plots.plot([last, last], [0, proj[county][-1]])\n",
    "    _ = plots.xticks(rotation=45)\n",
    "_ = interact(proj_cty, county=counties)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sectionProjDeath'></a>\n",
    "## Projection of deaths in one county"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67215cae67ca48f2850fbd00d7827e6e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='county', options=('Alameda', 'Amador', 'Butte', 'Calaveras', 'Colu…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def proj_cty_deaths(county):\n",
    "    proj = project_trend(deaths.extract(county).trend().take[-7:], 14)\n",
    "    proj.show()\n",
    "    proj.select(['date', county, 'new']).plot('date', width = 7)\n",
    "    last = deaths['date'][-1]\n",
    "    plots.plot([last, last], [0, proj[county][-1]])\n",
    "    _ = plots.xticks(rotation=45)\n",
    "_ = interact(proj_cty_deaths, county=counties)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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  "language_info": {
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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