experiments/2024-08-05-speed/01-measure-recent-versions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2b21d45f-cf7d-4a09-964c-bc6a81a1893d",
   "metadata": {},
   "source": [
    "# Measure the speed of the Markdown package across recent versions\n",
    "\n",
    "The current version of the Markdown package for TeX takes multiple seconds to initialize and process a markdown text:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "11e99041-b6c2-4947-b108-9ed4d7c4a46f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\markdownRendererDocumentBegin\n",
      "foo\\markdownRendererDocumentEnd\n",
      "\n",
      "real\t0m1.645s\n",
      "user\t0m1.430s\n",
      "sys\t0m0.215s\n"
     ]
    }
   ],
   "source": [
    "! docker run --rm -i witiko/markdown bash -c 'time markdown-cli <<< foo'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0eb626b-3eed-47a4-b5ef-6fbd39d38d54",
   "metadata": {},
   "source": [
    "This Jupyter notebook measures the speed of historic versions of the Markdown package for TeX and compares them with the current version of the Markdown package."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6ad6175-68c4-4e27-8e1f-b73d10856a74",
   "metadata": {},
   "source": [
    "### Experiment\n",
    "\n",
    "In my experiment, I time the command `markdown-cli <<< foo` with the Docker images for all versions of the Markdown package since version 2.23.0 on my Dell G5 15 notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d124af9e-3b7e-4661-89ee-50d121e62566",
   "metadata": {},
   "outputs": [],
   "source": [
    "from packaging.version import Version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4d863f76-7dd9-447a-a427-b0e95542dbaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.23.0, 3.0.0-alpha, 3.0.0-alpha.2, 3.0.0, 3.0.1, 3.1.0, 3.2.0, 3.2.1, 3.3.0, 3.4.0, 3.4.1, 3.4.2, 3.4.3, 3.5.0, 3.6.0, 3.6.1, 3.6.2\n"
     ]
    }
   ],
   "source": [
    "tags = ! git tag | grep -E '2\\.23\\.0|^3'\n",
    "tags = sorted(tags, key=Version)\n",
    "print(', '.join(tags))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d76ba61-e07f-466c-8f89-737e5a02e099",
   "metadata": {},
   "source": [
    "To determine the median times, I repeat the test five times for every version. To control for the effect of using different versions of the TeX Live distributions, I use the historic TeX Live 2022 distribution for all versions of the Markdown package. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b8367fe-f2da-45a2-9582-d2d3c970cac5",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "! pip install tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "95d6a816-9b92-4a75-af64-d66b1d8cceb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "from itertools import product\n",
    "\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "30cf12b9-89c6-4de6-a228-52d50f09a96b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████| 85/85 [54:48<00:00, 38.69s/it]\n"
     ]
    }
   ],
   "source": [
    "durations_all = defaultdict(lambda: list())\n",
    "parameters = list(product(range(5), tags))\n",
    "for repetition, tag in tqdm(parameters, ncols=50):\n",
    "    abbrev = 8 if Version(tag) >= Version('3.2.0') else 7\n",
    "    lines = ! docker run --rm -i witiko/markdown:`git describe --abbrev=$abbrev --tags --always --long --exclude latest $tag`-TL2022-historic bash -c 'time markdown-cli <<< foo'\n",
    "    for line in lines:\n",
    "        if line.startswith('real'):\n",
    "            _, duration = line.split()\n",
    "            assert len(durations_all[tag]) == repetition\n",
    "            durations_all[tag].append(duration)\n",
    "            break\n",
    "    else:\n",
    "        raise ValueError(f'Unexpected output for tag {tag}: {lines}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "454c335b-28fa-42cf-81c2-97334d7da9f7",
   "metadata": {},
   "source": [
    "## Results\n",
    "In this section, I discuss the results of the experiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "27af9f1a-ff88-45bf-b51e-57609ae5f662",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "26cc8b15-2bfe-4832-baf5-b1f46386e561",
   "metadata": {},
   "outputs": [],
   "source": [
    "durations_seconds_all = dict()\n",
    "for tag, durations in durations_all.items():\n",
    "    durations_seconds = list()\n",
    "    for duration in durations:\n",
    "        match = re.match(r'(?P<minutes>[0-9]+)m(?P<seconds>[0-9.]+)s', duration)\n",
    "        assert match\n",
    "        duration_seconds = int(match.group('minutes')) + float(match.group('seconds'))\n",
    "        durations_seconds.append(duration_seconds)\n",
    "    durations_seconds_all[tag] = durations_seconds\n",
    "    assert len(durations_seconds_all[tag]) == len(durations_all[tag])\n",
    "assert len(durations_seconds_all) == len(durations_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "80b9d16d-7e22-4565-81d6-e75652ac782a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statistics import median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2d74390f-f557-44e9-9bdc-bdfabe198cf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "durations_seconds_median = {\n",
    "    tag: median(durations)\n",
    "    for tag, durations\n",
    "    in durations_seconds_all.items()\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "572d1c39-e379-4f68-b582-ef227cd3762a",
   "metadata": {},
   "source": [
    "Below, I show the median processing times for all considered versions of the Markdown package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "92e12960-4533-4aa0-bb03-3824a8fda863",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "! pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "21d88566-a463-418f-9a89-547da4094773",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d842d771-d96f-41da-9592-aecc1f8defbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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bNkKj0UjLTZs2TTo2PvXUU+LLL78UixYtEkIU7i/Ozs7SsocPHxY1atQQPXr0ENnZ2VK7oe9rQ/eXJ598UrRs2VK6ffz4cQFAyOVy8euvv0rtffv2Fa1atZJuV/b4VKdOHVG/fn3h4eEhpkyZIubOnSuaNGki5HK59P1KCCH++ecfERoaKqZMmSKWLl0qZsyYIX1vunXrlrRcQUGB6NatmwAghgwZIr744gsxe/Zs8dhjj4mffvpJCPHvZ9Onn34qPWb48OFCqVTq5Gro9jx27JhQKpUiODhYfPzxx+Kjjz4S/v7+IjIyUhQvlww9RhZ34MAB8d///lcAEG+88YbO988dO3YIOzs7Ub9+ffHJJ59I66xRo4bOsais/a48n376qQCgsz5jc1m6dKkAIMaNGydkMpmYMGGCQc9NQrDofsQU/YD54osvhKurq/QBMGjQING1a1chhNAruvft2ycAiDVr1uisb+vWrTrtd+7cEQ4ODqJv3746BzPtQaa8orvoh5HW7NmzhUwmE3FxcVKbthCdMWOGzrLaLyblady4sejcubNee2lFNwCxdu1aqe3ChQvSB9nff/8ttW/btk0AEN9++63U9uKLLwo/Pz+dLxNCCDFkyBDh7u5eYs5aJ06cEADEf/7zH532SZMmCQDijz/+kNqKf8iXRZvTZ599JrXl5uaKZs2aCR8fH6nI1L4edevW1YkzLy9P+Pj4iIiICPHgwQOp/ddffxUAxAcffCC1derUSbi6uupsPyGEzv5h6Gv01FNPicaNG5eZm7u7u86X6pKUVnTXrFlTpKamSu0///yzACB++eUXqa1JkyYiMDBQZGZmSm179uwRAAwqukva3i+//LJwcnISOTk5ZT7WkNy023blypVSW25urvD19dUpLOfPny8A6BTseXl5ol27dsLFxUX64Uj72ri5uYk7d+7oPNc///yjt7+XpaQPfCGEuH79ulAoFOKjjz7SaT99+rSws7PTaU9MTBSenp6iR48eIjc3VzRv3lzUrl1bpKenS8vcvXtXABDTpk0zKK7XXntN1KpVS7o9ceJE0alTJ+Hj4yMWL14shBAiJSVFyGQysWDBAmm54vtRWc9bmWNWZY+r2i9pd+/e1Yup+DHDmG2h3deWLFmis+yqVauEXC4X+/bt02lfsmSJACD++usvqQ2AcHBw0CmITp48KQCIhQsXSm2l7Tsl0Wg0IiAgQGd/F0KIH374QQAQf/75pxBCiMzMTOHh4SHGjBmjs1xSUpJwd3fXadduvylTpugsqy1qNmzYUGZMxYvuN998UwDQeY0yMzNFSEiICA4OFmq1Wgjx7/Zs1KiRyM3NlZZdsGCBACBOnz5tVBzFGXMsL6lALU1Z28vQbV6Zz04h/v0eU1BQIHx9fcWHH34ohBDi3LlzAoDYu3dviTmVtN7vv/9eZ98R4t/31dChQ/WWL/re2r9/v3BzcxN9+/bVOcYb8742dH/59NNPhUKhkI7fn3/+uahTp45o06aNeOedd4QQQqjVauHh4aFTLFX2O1WdOnUEALFp0yapLT09Xfj5+YnmzZtLbTk5OVKsWrGxsUKpVOo89/LlywUAMXfuXL3n0r5WRYvu/Px88eyzzwpHR0exbds2neUN3Z79+vUTTk5OOsX/5cuXhZ2dnU7RbcwxsiTa93Tx96r2+1dKSorUdvLkSSGXy8Xw4cOltrL2u/IUf19WJBeNRiM6dOggAIigoCCd70JUNvYFeIQNHjwYDx48wK+//orMzEz8+uuvpXYt37BhA9zd3dGjRw8kJydL/1q2bAkXFxfs3r0bALBz507k5eXh9ddf1+mO8+abbxoUk6Ojo/R3VlYWkpOT0b59ewghcPz4cb3ltV1ctKKjo3Ht2jWDnssYLi4uGDJkiHS7QYMG8PDwQKNGjRAVFSW1a//WxiCEwKZNm9CvXz8IIXReu169eiE9Pb3ErsFaW7ZsAQCd7mIA8NZbbwGAXldEY9jZ2eHll1+Wbjs4OODll1/GnTt3cPToUZ1lR4wYobNtjhw5gjt37uDVV1/VuX60b9++aNiwoRTX3bt38eeff2L06NGoXbu2zjq1+4cxr5GHhwdu3rxZYpdvLQ8PDxw6dKhCo2g+++yzqFGjhnQ7OjoawL/bMyEhAadPn8bw4cN1poPp3LkzmjRpYtBzFH0dMzMzkZycjOjoaGRnZ+PChQtlPtbQ3FxcXPD8889Ltx0cHNCmTRud98aWLVvg6+uLoUOHSm329vZ44403cP/+fezdu1dnnc8884zUfdrUNm/eDI1Gg8GDB+tsf19fX9SrV086vgCAr68vFi1ahB07diA6OhonTpzA8uXL4ebmVuHnj46Oxu3bt3Hx4kUAhZe5dOrUCdHR0di3bx8AYP/+/RBCSPtERVXkmFXZ46oxjNkWQOG1yqNGjdJp27BhAxo1aoSGDRvqrOOxxx4DAL11dO/eHaGhodLtpk2bws3NrcLHcplMhkGDBmHLli06gwitX78eAQEBUlfMHTt2IC0tDUOHDtWJU6FQICoqSi9OoPASg6Lc3d0BANu2bSuxO3tptmzZgjZt2uh0C3VxccFLL72E69ev49y5czrLjxo1Sufa++LHporGYeix3NTK2+aV/ewsSqFQYPDgwfj+++8BFA6gFhQUVOp7uegxOicnB8nJyWjbti0AlPicxd/TRe3evRu9evVCt27dsHnzZp1r+415Xxu6v0RHR0OtVuPAgQMACo9l0dHROseyM2fOIC0trcT8K/Odyt/fH08//bR0283NDcOHD8fx48eRlJQEoPB4oe2GrFarkZKSAhcXFzRo0EDntd20aRO8vLzw+uuv6z1P8a7eeXl5GDRoEH799Vds2bIFPXv21LnfkO2pVquxc+dO9O/fX2cwsLCwMPTu3VtnfcYeIw2RmJiIEydOYOTIkfD09JTamzZtih49ekjfBYsqa78zVEVykclkUozt2rWrkqkwbRWL7keYt7c3unfvjrVr12Lz5s1Qq9UYOHBgictevnwZ6enp8PHxgbe3t86/+/fvSwNDxMXFAQDq1aun91xFi5nSxMfHSwcd7TVF2utfil+XplKp9IqAGjVq6F1jbgqBgYF6B3p3d3cEBQXptQGQYrh79y7S0tKwbNkyvddN+0VV+9qVJC4uDnK5XGfEYaCw8PDw8JBe74rw9/fXG3ijfv36AKB37V1ISIheXEDhjw/FNWzYULpf+2Fd1rzRxrxG77zzDlxcXNCmTRvUq1cPr732Gv766y+d9X3yySc4c+YMgoKC0KZNG0yfPt3gLw3FfxjQ7rPa7anNq/j2KK2tJGfPnsXTTz8Nd3d3uLm5wdvbWyqQy7v20tDcStpfi7834uLiUK9ePb3rsBo1aiTdX1TxfcCULl++DCEE6tWrp7cPnD9/Xu89MmTIEPTt2xeHDx/GmDFj0K1bt0o9v/bL5759+5CVlYXjx48jOjoanTp1kr6o7tu3D25uboiMjKzw81T0mFXZ46oxjN0WAQEBegOxXb58GWfPntV7vPb4Unwdxd93QOWP5c8++ywePHiA//u//wMA3L9/H1u2bJGuo9TGCQCPPfaYXqzbt2/Xi9POzg6BgYE6bSEhIZg4cSK+/vpreHl5oVevXli0aFG57+W4uLgSj5+lvf/KOzZVJg6g/GO5qZW3zSv72VncsGHDcO7cOZw8eRJr167FkCFDSrxOFyi87nj8+PGoVasWHB0d4e3tLR3/Sno9Szs25uTkoG/fvmjevDl++OEHvfeJMe9rQ/eXFi1awMnJSee4pT2WHTlyBDk5OdJ9xa8Drux3qrCwML3XtPh3Co1Gg3nz5qFevXpQKpXw8vKCt7c3Tp06pfPaXr16FQ0aNNAZ6Lc0s2fPxk8//YSNGzeWOGuEIdvzzp07ePDggUGf7cYeIw1R1vuwUaNGSE5ORlZWlk67KT6TK5LL5s2b8csvvyAiIgIbNmyQ9icqH0cvf8QNGzYMY8aMQVJSEnr37l3qaIoajQY+Pj5Ys2ZNifeb4gyYWq1Gjx49kJqainfeeQcNGzaEs7Mzbt26hZEjR+qNlqxQKCr9nIYq7blKaxcPB1/Sxvz8889Lg9AU17Rp03Kfv7QvB9Wl6C/FpmbMa9SoUSNcvHgRv/76K7Zu3YpNmzbhyy+/xAcffCBN1TR48GBER0fjxx9/xPbt2/Hpp59izpw52Lx5s94v1sWVtz0rKy0tDZ07d4abmxtmzJiB0NBQqFQqHDt2DO+88065I4IbmltV5FHV+4BMJsPvv/9eYuzFf0lPSUmR5tU9d+4cNBpNpQZx8ff3R0hICP78808EBwdDCIF27drB29sb48ePR1xcHPbt24f27dtX6nmq85hVUcZui5L2C41GgyZNmmDu3LklPkfxHyurYn9t27YtgoOD8cMPP2DYsGH45Zdf8ODBAzz77LM6cQLAqlWr9KaTAqD3hb/oWbqiPvvsM4wcORI///wztm/fjjfeeAOzZ8/G33//rVekV5Qhr1F1xGEq1fXZqRUVFYXQ0FC8+eabiI2NLbVXH1B4nD1w4ADefvttNGvWDC4uLtBoNHj88cdLPEaXdmxUKpXo06cPfv75Z2zduhVPPPGEwfFWlL29PaKiovDnn3/iypUrSEpKQnR0NGrVqoX8/HwcOnQI+/btQ8OGDfW+t1XH8WnWrFl4//33MXr0aHz44Yfw9PSEXC7Hm2++WeEZMXr16oWtW7fik08+QZcuXfRmbzB2e5bH2GNkVTHFZ7KxuWRmZuKNN95Ay5YtsXv3bjRt2hRjx47F8ePHLXI2D0vDovsR9/TTT+Pll1/G33//jfXr15e6XGhoKHbu3IkOHTqU+UavU6cOgMJfz+rWrSu13717t9xfS0+fPo1Lly7hu+++w/Dhw6X2oiOsm0p1FbHe3t5wdXWFWq0ud17TktSpUwcajQaXL1+WftEGgNu3byMtLU16vSsiISFBb5qJS5cuAUC5o3Brn/fixYtSl1GtixcvSvdr94EzZ86Uui5jXyNnZ2c8++yzePbZZ5GXl4cBAwbgo48+wtSpU6UPWz8/P7z66qt49dVXcefOHbRo0QIfffRRuUV3ebR5FR81uLS24vbs2YOUlBRs3rwZnTp1ktpjY2MNjsFUudWpUwenTp3SK1i1XdwN2beMfR+VtnxoaCiEEAgJCZHOjJTltddeQ2ZmJmbPno2pU6di/vz5OpdgVOT9HR0djT///BMhISFo1qwZXF1dERkZCXd3d2zduhXHjh2TftgpTVUdVypzXDWWsduitHWcPHkS3bp1M9lrUpH1DB48GAsWLEBGRgbWr1+P4OBgqVupNk4A8PHxqdDxuagmTZqgSZMmeO+993DgwAF06NABS5YswcyZM0tcvk6dOtLlDEUZ8/4zVRxA+cdyY1V2u1f2s7MkQ4cOxcyZM9GoUSM0a9asxGXu3buHXbt2ISYmBh988IHUru0VYQyZTIY1a9bgqaeewqBBg/D777/rnIk15n1tzP4SHR2NOXPmYOfOnfDy8kLDhg0hk8nQuHFj7Nu3D/v27auSHwCuXLkCIYTOti/+nWLjxo3o2rUrvvnmG53HpqWl6cwbHRoaikOHDiE/P7/cYq5t27Z45ZVX8MQTT2DQoEH48ccfpR/MDN2ePj4+UKlUBn22m+IYWVzR92FxFy5cgJeXV5VMRWdsLu+99x4SExPx888/w9XVFQsXLkS/fv3w2WefYcqUKSaPz9awe/kjzsXFBYsXL8b06dPRr1+/UpcbPHgw1Go1PvzwQ737CgoKpKkounfvDnt7eyxcuFDnF/j58+eXG4v2V7aijxNCYMGCBQZmYzhnZ2ed6TOqikKhwDPPPINNmzaVWHjevXu3zMf36dMHgP7rpz2D1Ldv3wrHVlBQgKVLl0q38/LysHTpUnh7e6Nly5ZlPrZVq1bw8fHBkiVLdKYA+v3333H+/HkpLm9vb3Tq1AnLly9HfHy8zjq029mY16j4FB8ODg4IDw+HEAL5+flQq9V63f98fHzg7++vN1VRRfj7+yMiIgIrV67UuVZ07969OH36dLmPL2kfz8vLw5dfflnuY02dW58+fZCUlKTzY1tBQQEWLlwIFxcX6bKOsmi/BBj6Xipt+QEDBkChUCAmJkbv7KYQQme7b9y4EevXr8fHH3+MKVOmYMiQIXjvvfekL3cApHmijXmPR0dH4/r161i/fr3U3Vwul6N9+/aYO3cu8vPzy72euyLPa4jKHFeNZcy2KM3gwYNx69YtfPXVV3r3PXjwQK+bpCGM3deAwi7mubm5+O6777B161YMHjxY5/5evXrBzc0Ns2bNQn5+vt7jyzs+A0BGRgYKCgp02po0aQK5XF7m+7JPnz44fPgwDh48KLVlZWVh2bJlCA4ORnh4eLnPbYo4DD2WG6si26uoyn52luQ///kPpk2bhs8++6zM5wX0e1lU9L2mnbqqdevW6NevHw4fPizdZ8z72pj9JTo6Grm5uZg/fz46duwoFcHR0dFYtWoVEhISKj02RUkSEhLw448/SrczMjKwcuVKNGvWTOpJolAo9F7bDRs26E01+swzzyA5ORlffPGF3vOU1AOme/fuWLduHbZu3YoXXnhBOoNt6PZUKBTo3r07fvrpJ50xU65cuYLff/9dZ1lTHCOL8/PzQ7NmzfDdd9/pvGfOnDmD7du3S98FTc2YXI4ePYpFixZh3Lhx0nfEJ554Ak8//TQ+/PDDKrsUxZbwTDeV2nWrqM6dO+Pll1/G7NmzceLECfTs2RP29va4fPkyNmzYgAULFmDgwIHSvI6zZ8/GE088gT59+uD48eP4/fffdX7FLEnDhg0RGhqKSZMm4datW3Bzc8OmTZuq5Brtli1bYvHixZg5cybCwsLg4+Oj9yu/qXz88cfYvXs3oqKiMGbMGISHhyM1NRXHjh3Dzp07kZqaWupjIyMjMWLECCxbtkzqmnz48GF899136N+/P7p27VrhuPz9/TFnzhxcv34d9evXx/r163HixAksW7as3F+W7e3tMWfOHIwaNQqdO3fG0KFDcfv2bSxYsADBwcGYMGGCtOznn3+Ojh07okWLFnjppZcQEhKC69ev47fffsOJEyeMeo169uwJX19fdOjQAbVq1cL58+fxxRdfoG/fvnB1dUVaWhoCAwMxcOBAREZGwsXFBTt37sQ///xT5hctY8yaNQtPPfUUOnTogFGjRuHevXv44osvEBERoVOIl6R9+/aoUaMGRowYgTfeeAMymQyrVq0yqBttZmamSXN76aWXsHTpUowcORJHjx5FcHAwNm7ciL/++gvz58+Hq6truesIDQ2Fh4cHlixZAldXVzg7OyMqKqrUa820H9TvvvsuhgwZAnt7e/Tr1w+hoaGYOXMmpk6diuvXr6N///5wdXVFbGwsfvzxR7z00kuYNGkS7ty5g7Fjx6Jr164YN24cAOCLL77A7t27MXLkSOzfvx9yuRyOjo4IDw/H+vXrUb9+fXh6eiIiIqLMsQW0X0IvXryIWbNmSe2dOnXC77//Ls3bXpaKPK8hKnNcNZah26IsL7zwAn744Qe88sor2L17Nzp06AC1Wo0LFy7ghx9+wLZt29CqVSuj4ipt3ynr7E+LFi0QFhaGd999F7m5uTpdy4HCgZ4WL16MF154AS1atMCQIUPg7e2N+Ph4/Pbbb+jQoUOJX/qL+uOPPzBu3DgMGjQI9evXR0FBAVatWiUVjaWZMmUKvv/+e/Tu3RtvvPEGPD098d133yE2NhabNm0y+jKGisZhzLHcGBXZXsVV5rOzJHXq1MH06dPLXMbNzQ2dOnXCJ598gvz8fAQEBGD79u1G9UYqztHREb/++isee+wx9O7dG3v37kVERIRR72tj9pd27drBzs4OFy9exEsvvSS1d+rUCYsXLwaAKim669evjxdffBH//PMPatWqheXLl+P27dv49ttvpWWeeOIJzJgxA6NGjUL79u1x+vRprFmzRudMPwAMHz4cK1euxMSJE3H48GFER0cjKysLO3fuxKuvvoqnnnpK7/n79++Pb7/9FsOHD4ebmxuWLl1q1PacPn06tm/fjg4dOmDs2LFQq9XSZ7v2uwpgmmNkST799FP07t0b7dq1w4svvogHDx5g4cKFcHd3L3e/rShDc1Gr1XjppZfg6+ur12tmwYIFCA8Px+uvvy6NoUGlqJIx0cliGTrlR0nzdAtROE9yy5YthaOjo3B1dRVNmjQRkydPFgkJCdIyarVaxMTECD8/P+Ho6Ci6dOkizpw5ozdlSklT25w7d050795duLi4CC8vLzFmzBhpKpGi0xKVNj2WdiqF8iQlJYm+ffsKV1dXAUCaPqy0KcNKmqaqtNcIgN60Trdv3xavvfaaCAoKEvb29sLX11d069ZNLFu2rNxY8/PzRUxMjAgJCRH29vYiKChITJ06VW96KWOnDGvcuLE4cuSIaNeunVCpVKJOnTriiy++0FmutKkttNavXy+aN28ulEql8PT0FM8995y4efOm3nJnzpwRTz/9tPDw8BAqlUo0aNBAvP/++zrLGPIaLV26VHTq1EnUrFlTmjP37bfflqaLys3NFW+//baIjIwUrq6uwtnZWURGRurNM1ralGHa+T6LQglTQK1bt040bNhQKJVKERERIf7v//5PPPPMM6Jhw4Ylvk5F/fXXX6Jt27bC0dFR+Pv7i8mTJ0tTzRXd74ozNLfS9tfiOQtR+JqPGjVKeHl5CQcHB9GkSRO96b/Kem2EKJxWLTw8XJpWpbzpwz788EMREBAgzYNddEqhTZs2iY4dOwpnZ2fh7OwsGjZsKF577TVx8eJFIYQQAwYMEK6urnrzDmundpszZ47UduDAAdGyZUvh4OBg8PRhPj4+AoC4ffu21LZ//34BQERHR+stX9JrWtrzVvaYVZnjqjFThmmVty2EKH1fE6JwKqo5c+aIxo0bC6VSKWrUqCFatmwpYmJidKZ3K+l4KYT+FFtClL3vlObdd98VAERYWFipy+zevVv06tVLuLu7C5VKJUJDQ8XIkSPFkSNHpGVKe62uXbsmRo8eLUJDQ4VKpRKenp6ia9euYufOneXmc/XqVTFw4EDpuNimTRud+YW1sZV0DNa+L7XvN0PjKI0hx3JjpgwTovTtZcw2r8xnZ2mf0eXldPPmTenzyt3dXQwaNEgkJCToHUdKe18JUfL+kpycLMLDw4Wvr6+4fPmyEMLw97UQhu0vWq1btxYAxKFDh3TywsNpngyJt2iO5dG+1tu2bRNNmzYVSqVSNGzYUG+/zcnJEW+99ZaUb4cOHcTBgwdF586d9aZxzc7OFu+++6703cfX11cMHDhQXL16VQhR+mfTl19+KQCISZMmSXkbsj2FEGLXrl2iefPmwsHBQYSGhoqvv/5avPXWW0KlUunlbMgxsiRlfa/auXOn6NChg3B0dBRubm6iX79+4ty5czrLlLXflae0qfzKy2XevHkCgNi4cWOJ6/3f//4nAOjMGU/6ZEKYaIQgIrIaXbp0QXJycpnXWpNxmjVrBm9v7yoZg4CIiMhSBQcHIyIiAr/++qu5QzG5/v374+zZsxW6rp+oKF7TTURkhPz8fL1rJ/fs2YOTJ0+WOF0JERERWb4HDx7o3L58+TK2bNnCz3YyCV7TTURkhFu3bqF79+54/vnn4e/vjwsXLmDJkiXw9fXFK6+8Yu7wiIiIqALq1q2LkSNHom7duoiLi8PixYvh4OCAyZMnmzs0sgEsuomIjFCjRg20bNkSX3/9Ne7evQtnZ2f07dsXH3/8MWrWrGnu8IiIiKgCHn/8cXz//fdISkqCUqlEu3btMGvWLNSrV8/coZEN4DXdRERERERERFWE13QTERERERERVREW3URERERERERV5JG7pluj0SAhIQGurq6QyWTmDoeIiIiIiIiskBACmZmZ8Pf3h1xe+vnsR67oTkhIQFBQkLnDICIiIiIiIhtw48YNBAYGlnr/I1d0u7q6Aih8Ydzc3MwcTeny8/Oxfft29OzZE/b29uYOp9KYj+WztZyYj2VjPpbP1nJiPpaN+Vg+W8uJ+Vg2a8knIyMDQUFBUo1Zmkeu6NZ2KXdzc7P4otvJyQlubm4WvaMZivlYPlvLiflYNuZj+WwtJ+Zj2ZiP5bO1nJiPZbO2fMq7bJkDqRERERERERFVERbdRERERERERFWERTcRERERERFRFWHRTURERERERFRFWHQTERERERERVREW3URERERERERVhEU3ERERERERURVh0U1ERERERERURVh0ExERERHRI0OtETgUm4qjyTIcik2FWiPMHRLZODtzB0BERERERFQdtp5JRMwv55CYngNAgZWXj8DPXYVp/cLxeISfucMjG8Uz3UREREREZPO2nknE2NXHHhbc/0pKz8HY1cew9UyimSIjW8eim4iIiIiIbJpaIxDzyzmU1JFc2xbzyzl2Nacqwe7lRERERERk0w5eTdY7w12UAJCYnoPp/3cWHcJqws/dEf4ejvBycYBMJqu+QMkmsegmIiIiIiKbIoTA9ZRs7Lt8F/suJ2PfpbsGPW7V33FY9XecdNvBTg5/dxX8PQqLcJ2/PRzh76GCkwNLKiob9xAiIiIiIrJ6adl5+OtKilRo30p7YPQ62tb1RG6BBglpD3AnMxd5BRpcT8nG9ZTsUh9Tw8ke/h6O8HN3RICHflHu46qCQl51Z8uLjsZeMzYV7cJ8qvT5yHgsuomIiIiIyOrkFqhxLC4N+68UFtmnb6VDFLkk214hQ8s6NRBdzxvt6tbEq2uO4XZGTonXdcsA+LqrsOY/baWCNa9Ag9sZOUhIe4CE9AdISMvBrbQHhbfTCm/fzy3Avex83MvOx9mEjBLjtJPLUMtNhYCHRXjRglz7t5vKvkKvAUdjtw4suomIiIiIyOIJIXD5zv3C7uKX7+LQtVQ8yFfrLFPPxwXR9bwRXc8LbUI84az8t9yZ/mQ4xq4+BhmgU3hrzwlP6xeuc4bYwU6OIE8nBHk6lRpTRk6+VITfSiss0BPT/i3QkzJyUKARuJX2oMwz765KO6kQ9/Nw/LdAf3htua+7CvYK3TGwtaOxF/8RQTsa++LnW7DwthAsuomIiIiIyCLdzczFX1eSse9yMvZfuYvbGbk693u5OKBjmBc61vNGxzAv+LqrSl3X4xF+WPx8iyJnhgv5VuLMsJvKHm6+9mjo61bi/WqNwJ3MHCQ8LMj1CvT0B7iXnY/M3AJcvJ2Ji7czS1yPTAb4uCqlM+N+7ir88M+NUkdjl6FwNPYe4b7sam4BWHQTEREREZFFyMlX43BsKvY/LLTPJ+p22VbaydEmxBPR9bzQMcwbDX1dITeiqHw8wg89wn1x8ModbN93CD2jo6r0GmiFXAY/98LrvVvWqVHiMtl5BSUW5Ynp/3Zjz1NrcDsjF7czcnE8Pq3c59WOxr767zj0i/RHDSd7jsJuRiy6iYiIiIjILDQagXOJGdh/JRn7Lyfj8PVU5BVodJYJ93NDdH0vRId5o1VwDajsFZV6ToVchqgQT6ScF4gK8TT7mWAnBzuE+bggzMelxPs1GoGUrLx/i/L0HOy7fBd7LpY/Ivu0/zuLaf93Fu6O9gj2ckZITafC/x/+C/ZyrvD15GQ4Ft1ERERERFRtEtMfFHYXv5yMv64kIyUrT+d+XzdV4Znsel7oEOYFLxelmSK1DHK5DN6uSni7KhEZ5AGg8IcIQ4puT2d7pGblI/1BPk7eSMPJG2l6y3i5OCC4prNuMV7TGcFeTpwOzUT4KhIRERERUZXJyi3A39dSHl6XnYwrd+7r3O/koEDbujURXc8L0fW8EOrtwq7Q5WgT4gk/dxWS0ssejX3/O48hr0CDuNQsxN7NQmxKFq4nZyE2OQuxydlIvp+L5Pt5SL6fhyNx9/TW4+umQrCXE0K8XBDi5YTgms6o6+2MIE8nKO0q1+PgUcKim4iIiIjIRGxxzmRjc1JrBE7fSse+S3ex70oyjsffQ77639JQLgOaBHqgUz0vdAzzQvPaNeBgJy91faRPIZdhWj/DRmN3dFCgoa9biYO9Zebk43pydrFiPAvXU7KQlp2PpIwcJGXk4O9rqTqPk8sAfw9HnTPj2r8DazjCTlHx7WmL7yEW3UREREREJmCLcyYbmtON1GxpKq8DV1OQ/iBfZz1Bno6FU3mFeaF9qBfcnXgdcWWZYjR2V5U9mgS6o0mgu95997LypGL8enIWrj0sxq8nZ+N+bgFu3nuAm/cKLxUoyk4uQ5CnU5FivPBMebCXE/zdHcsc+M4W30MAi24iIiIiokqzxTmTy8vppU51cT+3APuvJCMuJVtnGVeVHdqH1pTmzK5T07n6An+EVOVo7DWcHVDD2QEtauuOui6EwN37ubienP1vMf6wII9NzkJugUY6Y16cg50cwTWddM6Ma68lPxZ3D6+usa33kBaLbiIiIiKiSlBrBGJ+OVfqnMkA8P5PZxHi5QyFXA6ZDJDLZJChcP5lGWTQXsIskwGyEu6TAUCx23KZTFoGMkjtJT0eJaxPZ7li11AbktPSP69JbXZyGZrX9kB0PW90rOeFpgHulepiTIar7tHYZTIZfFxV8HFVoU2Ip859Go1AUkaOXjF+LTkLN1KzkVegwaXb93Hp9n399QI2O+84i24iIiIioko4HJuq0723JHfv56LX/H3VFFHFFC3GhRDQlFQBFdMrvBYGtQpC29CacFGytHjUyeUy+Hs4wt/DEe3DvHTuK1BrkJCWg2vJ9x8W49lSYX4jNbvEgltLO+/44dhUtAutWaU5VAW+M4iIiIiIKuFOZtkFt5aTgwJ2cllhcSEKCwkhxMP/AQHx8H/t/f/e1ojCv6vSv89t+BP1aeqH7uG1qiwmsh12Cjlq13RC7ZpOQAPd+zYfvYmJG06Wuw5D32uWhkU3EREREVEl+LiqDFrumxGtTXKWToh/i/GSinYUua0RussUL+aLP177Y8CR66l4be3xcmMxNHeisvh5OBq0nLXubyy6iYiIiIgqwdA5k4tf/1pRMtm/12n/O0GUaT0e4Qc/9/PVlhM92qr7PVTdOLoBEREREVElaOdMLknxOZOtRdGcikdtrTmR5bL1/Y1FNxERERFRJWnnTHZyUOi0+7qrrHaqI21Ovu66XXqtOSeyXLa8v7F7ORERERGRCTwe4YfFe67i5M10RPtq8HKfNiabM9lcqnIeaKLibHV/Y9FNRERERGQC+WoNzidlAgA6+WqqZc7k6lDd80DTo80W9zd2LyciIiIiMoFLtzORV6CBq8oOXtY5yDIRVQGzFt1//vkn+vXrB39/f8hkMvz0008GP/avv/6CnZ0dmjVrVmXxEREREREZ6tTNdABAE3832MDJOSIyEbMW3VlZWYiMjMSiRYuMelxaWhqGDx+Obt26VVFkRERERETG0RbdEQFuZo6EiCyJWa/p7t27N3r37m3041555RUMGzYMCoXCqLPjRERERERV5fStNABAhL8bRLx5YyEiy2F1A6l9++23uHbtGlavXo2ZM2eWu3xubi5yc3Ol2xkZGQCA/Px85OfnV1mclaWNzZJjNAbzsXy2lhPzsWzMx/LZWk7Mx7LZQj65+WpcSCwcRK1RLWeci7fufIqzhW1UFPOxbNaSj6HxyYQQoopjMYhMJsOPP/6I/v37l7rM5cuX0bFjR+zbtw/169fH9OnT8dNPP+HEiROlPmb69OmIiYnRa1+7di2cnJxMEDkRERERPeriMoG5Z+zgbCfwUSs1ZLymm8jmZWdnY9iwYUhPT4ebW+mXlVjNmW61Wo1hw4YhJiYG9evXN/hxU6dOxcSJE6XbGRkZCAoKQs+ePct8YcwtPz8fO3bsQI8ePWBvb2/ucCqN+Vg+W8uJ+Vg25mP5bC0n5mPZbCGf1YfigTMX0CrEGz17NrH6fIqzhW1UFPOxbNaSj7YXdXmspujOzMzEkSNHcPz4cYwbNw4AoNFoIISAnZ0dtm/fjscee0zvcUqlEkqlUq/d3t7eojeglrXEaSjmY/lsLSfmY9mYj+WztZyYj2Wz5nzOJt4HAEQGeUg5WHM+pbG1nJiPZbP0fAyNzWqKbjc3N5w+fVqn7csvv8Qff/yBjRs3IiQkxEyREREREdGj7rR2urBAD/MGQkQWx6xF9/3793HlyhXpdmxsLE6cOAFPT0/Url0bU6dOxa1bt7By5UrI5XJEREToPN7HxwcqlUqvnYiIiIioumTnFeDyncJB1JoGups5GiKyNGYtuo8cOYKuXbtKt7XXXo8YMQIrVqxAYmIi4uM53wIRERERWa6zCRnQCKCWmxK13FQWP+IyEVUvsxbdXbp0QVmDp69YsaLMx0+fPh3Tp083bVBEREREREY4pe1aHuBh3kCIyCLJzR0AEREREZE1O3UzDQAQya7lRFQCFt1ERERERJXw7yBqLLqJSB+LbiIiIiKiCsrIyce15CwAQFOOXE5EJWDRTURERERUQWcenuUOrOEIT2cHM0dDRJaIRTcRERERUQWdulVYdHOqMCIqDYtuIiIiIqIK0g6ixq7lRFSaShXdubm5poqDiIiIiMjqaKcLaxrAM91EVDKjiu7ff/8dI0aMQN26dWFvbw8nJye4ubmhc+fO+Oijj5CQkFBVcRIRERERWZTUrDzcvPcAANCYRTcRlcKgovvHH39E/fr1MXr0aNjZ2eGdd97B5s2bsW3bNnz99dfo3Lkzdu7cibp16+KVV17B3bt3qzpuIiIiIiKz0nYtr+vlDHdHe/MGQ0QWy86QhT755BPMmzcPvXv3hlyuX6cPHjwYAHDr1i0sXLgQq1evxoQJE0wbKRERERGRBeH83ERkCIOK7oMHDxq0soCAAHz88ceVCoiIiIiIyBpoRy5vwq7lRFSGSo9erlarceLECdy7d88U8RARERERWQVt9/LIIA+zxkFEls3oovvNN9/EN998A6Cw4O7cuTNatGiBoKAg7Nmzx9TxERERERFZnNsZObidkQu5DAj3czN3OERkwYwuujdu3IjIyEgAwC+//ILY2FhcuHABEyZMwLvvvmvyAImIiIiILI32eu4wHxc4Kw26YpOIHlFGF93Jycnw9fUFAGzZsgWDBg2SRjY/ffq0yQMkIiIiIrI02q7lTQM9zBoHEVk+o4vuWrVq4dy5c1Cr1di6dSt69OgBAMjOzoZCoTB5gERERERElkY7iFpTjlxOROUwui/MqFGjMHjwYPj5+UEmk6F79+4AgEOHDqFhw4YmD5CIiIiIyJIIIXDqJkcuJyLDGF10T58+HREREbhx4wYGDRoEpVIJAFAoFJgyZYrJAyQiIiIisiS30h4gNSsPdnIZGnEQNSIqR4VGfRg4cKBe24gRIyodDBERERGRpdMOotbA1xUqe15eSURlM6jo/vzzzw1e4RtvvFHhYIiIiIiILN3Jm9rruT3MGwgRWQWDiu558+bp3L579y6ys7Ph4eEBAEhLS4OTkxN8fHxYdBMRERGRTTt9Kw0AB1EjIsMYNHp5bGys9O+jjz5Cs2bNcP78eaSmpiI1NRXnz59HixYt8OGHH1Z1vEREREREZsNB1IjIWEZPGfb+++9j4cKFaNCggdTWoEEDzJs3D++9955JgyMiIiIisiTXU7KRmVMABzs5Gvi6mjscIrICRhfdiYmJKCgo0GtXq9W4ffu2SYIiIiIiIrJEp26mAQDC/dxgrzD6qzQRPYKMPlJ069YNL7/8Mo4dOya1HT16FGPHjpXm7CYiIiIiskWnpUHU2LWciAxjdNG9fPly+Pr6olWrVlAqlVAqlWjTpg1q1aqFr7/+uipiJCIiIiKyCKc4cjkRGcnoebq9vb2xZcsWXLp0CRcuXAAANGzYEPXr1zd5cERERERElkKtETiTwDPdRGQco4turfr167PQJiIiIqJHxtW795Gdp4aTgwKh3i7mDoeIrITRRbdarcaKFSuwa9cu3LlzBxqNRuf+P/74w2TBERERERFZCm3X8gh/dyjkMjNHQ0TWwuiie/z48VixYgX69u2LiIgIyGQ84BARERGR7Tv9cOTyJuxaTkRGMLroXrduHX744Qf06dOnKuIhIiIiIrJIJzlyORFVgNGjlzs4OCAsLKwqYiEiIiIiskj5ag3OJWYA4MjlRGQco4vut956CwsWLIAQotJP/ueff6Jfv37w9/eHTCbDTz/9VObymzdvRo8ePeDt7Q03Nze0a9cO27Ztq3QcRERERERluXQ7E3kFGriq7FDH08nc4RCRFTG6e/n+/fuxe/du/P7772jcuDHs7e117t+8ebPB68rKykJkZCRGjx6NAQMGlLv8n3/+iR49emDWrFnw8PDAt99+i379+uHQoUNo3ry5sakQERERERnkVJGu5XIOokZERjC66Pbw8MDTTz9tkifv3bs3evfubfDy8+fP17k9a9Ys/Pzzz/jll19YdBMRERFRldEW3U0CPMwbCBFZHaOL7m+//bYq4qgQjUaDzMxMeHp6mjsUIiIiIrJhp2+lAeAgakRkPKOLbq27d+/i4sWLAIAGDRrA29vbZEEZ6n//+x/u37+PwYMHl7pMbm4ucnNzpdsZGYUDYOTn5yM/P7/KY6wobWyWHKMxmI/ls7WcmI9lYz6Wz9ZyYj6WzdLzyc1X40JiJgAg3Ne53DgtPZ+KsLWcmI9ls5Z8DI1PJowcES0rKwuvv/46Vq5cCY1GAwBQKBQYPnw4Fi5cCCenig0sIZPJ8OOPP6J///4GLb927VqMGTMGP//8M7p3717qctOnT0dMTEyJj69orERERET06IjLBOaesYOzncBHrdSQ8ZJuIgKQnZ2NYcOGIT09HW5ubqUuZ3TR/fLLL2Pnzp344osv0KFDBwCFg6u98cYb6NGjBxYvXlyhgI0putetW4fRo0djw4YN6Nu3b5nLlnSmOygoCMnJyWW+MOaWn5+PHTt2oEePHnqD1Vkj5mP5bC0n5mPZmI/ls7WcmI9ls/R8Vh+KR8yvF9CpXk18M7xluctbej4VYWs5MR/LZi35ZGRkwMvLq9yi2+ju5Zs2bcLGjRvRpUsXqa1Pnz5wdHTE4MGDK1x0G+r777/H6NGjsW7dunILbgBQKpVQKpV67fb29ha9AbWsJU5DMR/LZ2s5MR/Lxnwsn63lxHwsm6XmczbxPgCgWVANo+Kz1Hwqw9ZyYj6WzdLzMTQ2o4vu7Oxs1KpVS6/dx8cH2dnZRq3r/v37uHLlinQ7NjYWJ06cgKenJ2rXro2pU6fi1q1bWLlyJYDCLuEjRozAggULEBUVhaSkJACAo6Mj3N05qAURERERmd5p7cjlgR7mDYSIrJLc2Ae0a9cO06ZNQ05OjtT24MEDxMTEoF27dkat68iRI2jevLk03dfEiRPRvHlzfPDBBwCAxMRExMfHS8svW7YMBQUFeO211+Dn5yf9Gz9+vLFpEBERERGVKzuvAJfvFA6ixpHLiagijD7TvWDBAvTq1QuBgYGIjIwEAJw8eRIqlQrbtm0zal1dunRBWZeUr1ixQuf2nj17jA2XiIiIiKjCziZkQCOAWm5K1HJTmTscIrJCRhfdERERuHz5MtasWYMLFy4AAIYOHYrnnnsOjo6OJg+QiIiIiMhcTmm7lgd4mDcQIrJaFZqn28nJCWPGjDF1LEREREREFuXUzTQAQCS7lhNRBRl9Tffs2bOxfPlyvfbly5djzpw5JgmKiIiIiMgS/DuIGotuIqoYo4vupUuXomHDhnrtjRs3xpIlS0wSFBERERGRuWXk5ONachYAoClHLieiCjK66E5KSoKfn59eu7e3NxITE00SFBERERGRuZ15eJY7sIYjPJ0dzBwNEVkro4vuoKAg/PXXX3rtf/31F/z9/U0SFBERERGRuZ26VVh0c6owIqoMowdSGzNmDN58803k5+fjscceAwDs2rULkydPxltvvWXyAImIiIiIzOE0Ry4nIhMwuuh+++23kZKSgldffRV5eXkAAJVKhXfeeQdTp041eYBEREREROZwkiOXE5EJGF10y2QyzJkzB++//z7Onz8PR0dH1KtXD0qlsiriIyIiIiKqdqlZebh57wEAoHEAi24iqjijr+nWSkpKQmpqKkJDQ6FUKiGEMGVcRERERERmo52fO8TLGe6O9uYNhoismtFFd0pKCrp164b69eujT58+0ojlL774Iq/pJiIiIiKboL2em4OoEVFlGV10T5gwAfb29oiPj4eTk5PU/uyzz2Lr1q0mDY6IiIiIyBy0I5c3YddyIqoko6/p3r59O7Zt24bAwECd9nr16iEuLs5kgRERERERmYu2e3lkkIdZ4yAi62f0me6srCydM9xaqampHEyNiIiIiKze7Ywc3M7IhVwGhPu5mTscIrJyRhfd0dHRWLlypXRbJpNBo9Hgk08+QdeuXU0aHBERERFRddNezx3m4wJnpdEdQ4mIdBh9FPnkk0/QrVs3HDlyBHl5eZg8eTLOnj2L1NRU/PXXX1URIxERERFRtdF2LW8a6GHWOIjINhh9pjsiIgKXLl1Cx44d8dRTTyErKwsDBgzA8ePHERoaWhUxEhERERFVG+0gahy5nIhMoUL9Zdzd3fHuu++aOhYiIiIiIrMSQkjdyzlyORGZgtFnurdu3Yr9+/dLtxctWoRmzZph2LBhuHfvnkmDIyIiIiKqTrfSHiAlKw92chkacRA1IjIBo4vut99+GxkZGQCA06dPY+LEiejTpw9iY2MxceJEkwdIRERERFRdtGe5G/i6QmWvMHM0RGQLjO5eHhsbi/DwcADApk2b0K9fP8yaNQvHjh1Dnz59TB4gEREREVF1OXmT13MTkWkZfabbwcEB2dnZAICdO3eiZ8+eAABPT0/pDDgRERERkTU6fSsNAEcuJyLTMfpMd8eOHTFx4kR06NABhw8fxvr16wEAly5dQmBgoMkDJCIiIiKqDkIInOIgakRkYkaf6f7iiy9gZ2eHjRs3YvHixQgICAAA/P7773j88cdNHiARERERUXW4npKNzJwCONjJ0cDX1dzhEJGNMPpMd+3atfHrr7/qtc+bN88kARERERERmcOpm2kAgHA/N9grjD43RURUIoOOJllZWUat1NjliYiIiIjM7TQHUSOiKmBQ0R0WFoaPP/4YiYmJpS4jhMCOHTvQu3dvfP755yYLkIiIiIioOpySim4P8wZCRDbFoO7le/bswX//+19Mnz4dkZGRaNWqFfz9/aFSqXDv3j2cO3cOBw8ehJ2dHaZOnYqXX365quMmIiIiIjIZtUbgTALPdBOR6RlUdDdo0ACbNm1CfHw8NmzYgH379uHAgQN48OABvLy80Lx5c3z11Vfo3bs3FApFVcdMRERERGRS1+7eR3aeGk4OCoR6u5g7HCKyIUYNpFa7dm289dZbeOutt6oqHiIiIiKianfyYdfyCH93KOQyM0dDRLaEwzISERER0SPv9MORy5uwazkRmRiLbiIiIiJ65J3kyOVEVEVYdBMRERHRIy1frcG5xAwAHLmciEzPrEX3n3/+iX79+sHf3x8ymQw//fRTuY/Zs2cPWrRoAaVSibCwMKxYsaLK4yQiIiIi23XpdibyCjRwVdmhjqeTucMhIhtj1qI7KysLkZGRWLRokUHLx8bGom/fvujatStOnDiBN998E//5z3+wbdu2Ko6UiIiIiGzVqSJdy+UcRI2ITMyo0cu19u3bh6VLl+Lq1avYuHEjAgICsGrVKoSEhKBjx44Gr6d3797o3bu3wcsvWbIEISEh+OyzzwAAjRo1wv79+zFv3jz06tXL6DyIiIiIiLRFd5MAD/MGQkQ2yeiie9OmTXjhhRfw3HPP4fjx48jNzQUApKenY9asWdiyZYvJg9Q6ePAgunfvrtPWq1cvvPnmm6U+Jjc3V4oRADIyCq/Xyc/PR35+fpXEaQra2Cw5RmMwH8tnazkxH8vGfCyfreXEfCybufM5dfMeACDc19kkMZg7n6pgazkxH8tmLfkYGp9MCCGMWXHz5s0xYcIEDB8+HK6urjh58iTq1q2L48ePo3fv3khKSqpQwDKZDD/++CP69+9f6jL169fHqFGjMHXqVKlty5Yt6Nu3L7Kzs+Ho6Kj3mOnTpyMmJkavfe3atXBy4jU7RERERI+yfA0w+bACGiHDtBYF8FSaOyIishbZ2dkYNmwY0tPT4ebmVupyRp/pvnjxIjp16qTX7u7ujrS0NGNXV+WmTp2KiRMnSrczMjIQFBSEnj17lvnCmFt+fj527NiBHj16wN7e3tzhVBrzsXy2lhPzsWzMx/LZWk7Mx7KZM5+TN9OhOXQINZzs8Vz/HpDJKn9Nt61tH8D2cmI+ls1a8tH2oi6P0UW3r68vrly5guDgYJ32/fv3o27dusauzujnvn37tk7b7du34ebmVuJZbgBQKpVQKvV/srS3t7foDahlLXEaivlYPlvLiflYNuZj+WwtJ+Zj2cyRz/mk+wAKpwpzcHAw6bptbfsAtpcT87Fslp6PobEZPXr5mDFjMH78eBw6dAgymQwJCQlYs2YNJk2ahLFjxxodqDHatWuHXbt26bTt2LED7dq1q9LnJSIiIiLbdPLhIGqRge5mjoSIbJXRZ7qnTJkCjUaDbt26ITs7G506dYJSqcSkSZPw+uuvG7Wu+/fv48qVK9Lt2NhYnDhxAp6enqhduzamTp2KW7duYeXKlQCAV155BV988QUmT56M0aNH448//sAPP/yA3377zdg0iIiIiIhwWjtyeaCHeQMhIptldNEtk8nw7rvv4u2338aVK1dw//59hIeHw8XFxegnP3LkCLp27Srd1l57PWLECKxYsQKJiYmIj4+X7g8JCcFvv/2GCRMmYMGCBQgMDMTXX3/N6cKIiIiIyGjZeQW4fCcTQOEc3UREVaFC83QDgIODA8LDwyv15F26dEFZg6evWLGixMccP368Us9LRERERHQ2IQMaAdRyU6KWm8rc4RCRjTK66M7JycHChQuxe/du3LlzBxqNRuf+Y8eOmSw4IiIiIqKqckrbtTzAw7yBEJFNM7rofvHFF7F9+3YMHDgQbdq0Mcm0CkRERERE1e3UzTQAHESNiKqW0UX3r7/+ii1btqBDhw5VEQ8RERERUbX4dxA1Ft1EVHWMnjIsICAArq6uVRELEREREVG1yMjJx7XkLACFc3QTEVUVo4vuzz77DO+88w7i4uKqIh4iIiIioip35uFZ7sAajvB0djBzNERky4zuXt6qVSvk5OSgbt26cHJygr29vc79qampJguOiIiIiKgqnLpVWHRzqjAiqmpGF91Dhw7FrVu3MGvWLNSqVYsDqRERERGR1TnNkcuJqJoYXXQfOHAABw8eRGRkZFXEQ0RERERU5U5y5HIiqiZGX9PdsGFDPHjwoCpiISIiIiKqcqlZebh5r/D7bOMAFt1EVLWMLro//vhjvPXWW9izZw9SUlKQkZGh84+IiIiIyJJp5+cO8XKGu6N92QsTEVWS0d3LH3/8cQBAt27ddNqFEJDJZFCr1aaJjIiIiIioCmiv5+YgakRUHYwuunfv3l0VcRARERERVQvtyOVN2LWciKqB0UV3586dqyIOIiIiIqJqoe1e3jTQw6xxENGjwaCi+9SpU4iIiIBcLsepU6fKXLZp06YmCYyIiIiIyNRuZ+TgdkYu5DKgsb+bucMhokeAQUV3s2bNkJSUBB8fHzRr1gwymQxCCL3leE03EREREVky7fXcYT4ucFYa3emTiMhoBh1pYmNj4e3tLf1NRERERGSN2LWciKqbQUV3nTp1pL/j4uLQvn172NnpPrSgoAAHDhzQWZaIiIiIyJJoB1HjyOVEVF2Mnqe7a9euSE1N1WtPT09H165dTRIUEREREZGpCSGk7uUcuZyIqovRRbd2Pu7iUlJS4OzsbJKgiIiIiIhM7VbaA6Rk5cFOLkMjPw6iRkTVw+DRIwYMGACgcLC0kSNHQqlUSvep1WqcOnUK7du3N32EREREREQmoD3L3cDXFSp7hZmjIaJHhcFFt7t7YRccIQRcXV3h6Ogo3efg4IC2bdtizJgxpo+QiIiIiMgEeD03EZmDwUX3t99+CwAIDg7GpEmT2JWciIiIiKwKRy4nInMwenLCadOmVUUcRERERERVRgiBUxxEjYjMwOiB1IiIiIiIrM31lGxk5hTAwU6OBr6u5g6HiB4hLLqJiIiIyOZpu5aH+7nBXsGvwERUfXjEISIiIiKbpx25nIOoEVF1Y9FNRERERDbvlFR0e5g3ECJ65Bg9kNrnn39eYrtMJoNKpUJYWBg6deoEhYJzHxIRERGR+ak1AmcSeKabiMzD6KJ73rx5uHv3LrKzs1GjRg0AwL179+Dk5AQXFxfcuXMHdevWxe7duxEUFGTygImIiIiIjHHt7n1k56nh5KBAqLeLucMhokeM0d3LZ82ahdatW+Py5ctISUlBSkoKLl26hKioKCxYsADx8fHw9fXFhAkTqiJeIiIiIiKjnHzYtTzC3x0KuczM0RDRo8boM93vvfceNm3ahNDQUKktLCwM//vf//DMM8/g2rVr+OSTT/DMM8+YNFAiIiIiooo4/XDk8ibsWk5EZmD0me7ExEQUFBTotRcUFCApKQkA4O/vj8zMzMpHR0RERERUSadu8XpuIjIfo4vurl274uWXX8bx48eltuPHj2Ps2LF47LHHAACnT59GSEiIQetbtGgRgoODoVKpEBUVhcOHD5e5/Pz589GgQQM4OjoiKCgIEyZMQE5OjrFpEBEREdEjIF+twbmEDAAcuZyIzMPoovubb76Bp6cnWrZsCaVSCaVSiVatWsHT0xPffPMNAMDFxQWfffZZuetav349Jk6ciGnTpuHYsWOIjIxEr169cOfOnRKXX7t2LaZMmYJp06bh/Pnz+Oabb7B+/Xr897//NTYNIiIiInoEXLqdidwCDVxVdqjj6WTucIjoEWT0Nd2+vr7YsWMHLly4gEuXLgEAGjRogAYNGkjLdO3a1aB1zZ07F2PGjMGoUaMAAEuWLMFvv/2G5cuXY8qUKXrLHzhwAB06dMCwYcMAAMHBwRg6dCgOHTpkbBpERERE9AjQzs/dJMAdcg6iRkRmYPSZbq2GDRviySefxJNPPqlTcBsqLy8PR48eRffu3f8NRi5H9+7dcfDgwRIf0759exw9elTqgn7t2jVs2bIFffr0qVgSRERERGTTtEU3u5YTkbkYfaZbrVZjxYoV2LVrF+7cuQONRqNz/x9//GHQepKTk6FWq1GrVi2d9lq1auHChQslPmbYsGFITk5Gx44dIYRAQUEBXnnllTK7l+fm5iI3N1e6nZFReE1Pfn4+8vPzDYrVHLSxWXKMxmA+ls/WcmI+lo35WD5by4n5WLaqzOfUzXsAgHBf52p7vWxt+wC2lxPzsWzWko+h8cmEEMKYFY8bNw4rVqxA37594efnB5lMt5vOvHnzDFpPQkICAgICcODAAbRr105qnzx5Mvbu3Vtil/E9e/ZgyJAhmDlzJqKionDlyhWMHz8eY8aMwfvvv1/i80yfPh0xMTF67WvXroWTE6/rISIiIrJV+Rpg8mEFNEKGaS0K4Kk0d0REZEuys7MxbNgwpKenw83NrdTljC66vby8sHLlykp36c7Ly4OTkxM2btyI/v37S+0jRoxAWloafv75Z73HREdHo23btvj000+lttWrV+Oll17C/fv3IZfr95Yv6Ux3UFAQkpOTy3xhzC0/Px87duxAjx49YG9vb+5wKo35WD5by4n5WDbmY/lsLSfmY9mqKp+TN9MxcOkh1HCyx6EpXfROFlUVW9s+gO3lxHwsm7Xkk5GRAS8vr3KLbqO7lzs4OCAsLKxSwWnX07JlS+zatUsqujUaDXbt2oVx48aV+Jjs7Gy9wlqhUAAASvvtQDvCenH29vYWvQG1rCVOQzEfy2drOTEfy8Z8LJ+t5cR8LJup8zmfdB9A4fXcDg4OJluvoWxt+wC2lxPzsWyWno+hsRk9kNpbb72FBQsWlFrkGmPixIn46quv8N133+H8+fMYO3YssrKypNHMhw8fjqlTp0rL9+vXD4sXL8a6desQGxuLHTt24P3330e/fv2k4puIiIiICCg80w0AkYHuZo6EiB5lRp/p3r9/P3bv3o3ff/8djRs31qvuN2/ebPC6nn32Wdy9excffPABkpKS0KxZM2zdulUaXC0+Pl7nzPZ7770HmUyG9957D7du3YK3tzf69euHjz76yNg0iIiIiMjGndZOF8aRy4nIjIwuuj08PPD000+bLIBx48aV2p18z549Orft7Owwbdo0TJs2zWTPT0RERES2JzuvAJfvZAIAmvJMNxGZkdFF97ffflsVcRARERERmczZhAxoBFDLTYlabipzh0NEjzCjr+kmIiIiIrJ0p7RdywM8zBsIET3yDDrT3aJFC+zatQs1atRA8+bNy5xu4dixYyYLjoiIiIioIk7dTAPAruVEZH4GFd1PPfWUNO1W0Tm1iYiIiIgskXYQNRbdRGRuBhXdRQcu4yBmRERERGTJMnLycS05CwDQJIBFNxGZl9HXdN+4cQM3b96Ubh8+fBhvvvkmli1bZtLAiIiIiIgq4szDs9wBHo6o6aI0czRE9KgzuugeNmwYdu/eDQBISkpC9+7dcfjwYbz77ruYMWOGyQMkIiIiIjLGqVuFRXdkEM9yE5H5GV10nzlzBm3atAEA/PDDD2jSpAkOHDiANWvWYMWKFaaOj4iIiIjIKKc5cjkRWRCji+78/HxpULWdO3fiySefBAA0bNgQiYmJpo2OiIiIiMhIJx+OXB7JQdSIyAIYXXQ3btwYS5Yswb59+7Bjxw48/vjjAICEhATUrFnT5AESERERERkqNSsPN+89AAA05iBqRGQBjC6658yZg6VLl6JLly4YOnQoIiMjAQD/93//J3U7JyIiIiIyh9MPr+cO8XKGu6O9maMhIjJwyrCiunTpguTkZGRkZKBGjRpS+0svvQQnJyeTBkdEREREZIxTN9IAcH5uIrIcRp/pfvDgAXJzc6WCOy4uDvPnz8fFixfh4+Nj8gCJiIiIiAylHbmc83MTkaUwuuh+6qmnsHLlSgBAWloaoqKi8Nlnn6F///5YvHixyQMkIiIiIjLUqYeDqDUN9DBrHEREWkYX3ceOHUN0dDQAYOPGjahVqxbi4uKwcuVKfP755yYPkIiIiIjIELczcnA7IxdyGdDY383c4RARAahA0Z2dnQ1XV1cAwPbt2zFgwADI5XK0bdsWcXFxJg+QiIiIiMgQ2vm5w3xc4Kw0eugiIqIqYXTRHRYWhp9++gk3btzAtm3b0LNnTwDAnTt34ObGXxSJiIiIyDy0XcubBHiYNQ4ioqKMLro/+OADTJo0CcHBwWjTpg3atWsHoPCsd/PmzU0eIBERERGRIbSDqEUGcRA1IrIcRve7GThwIDp27IjExERpjm4A6NatG55++mmTBkdEREREZAghhNS9nCOXE5ElMfpMNwD4+vrC1dUVO3bswIMHDwAArVu3RsOGDU0aHBERERGRIW6lPUBKVh7s5DI08uMlj0RkOYwuulNSUtCtWzfUr18fffr0QWJiIgDgxRdfxFtvvWXyAImIiIiIyqM9y93A1xUqe4WZoyEi+pfRRfeECRNgb2+P+Ph4ODk5Se3PPvsstm7datLgiIiIiIgMob2eu2kgu5YTkWUx+pru7du3Y9u2bQgMDNRpr1evHqcMIyIiIiKz0I5c3jTQw6xxEBEVZ/SZ7qysLJ0z3FqpqalQKpUmCYqIiIiIyFBCCJziIGpEZKGMLrqjo6OxcuVK6bZMJoNGo8Enn3yCrl27mjQ4IiIiIqLyXE/JRmZOARzs5Gjg62rucIiIdBjdvfyTTz5Bt27dcOTIEeTl5WHy5Mk4e/YsUlNT8ddff1VFjEREREREpdJ2LQ/3c4O9okKT8xARVRmjj0oRERG4dOkSOnbsiKeeegpZWVkYMGAAjh8/jtDQ0KqIkYiIiIioVNqRyzmIGhFZIqPPdAOAu7s73n33XVPHQkRERERkNF7PTUSWzOgz3d9++y02bNig175hwwZ89913JgmKiIiIiMgQao3AmYTCojsyyMO8wRARlcDoonv27Nnw8vLSa/fx8cGsWbNMEhQRERERkSGu3b2P7Dw1nBwUCPV2MXc4RER6jC664+PjERISotdep04dxMfHmyQoIiIiIiJDnHzYtTzC3x0KuczM0RAR6TO66Pbx8cGpU6f02k+ePImaNWuaJCgiIiIiIkOcfjhyeRMOokZEFsroonvo0KF44403sHv3bqjVaqjVavzxxx8YP348hgwZUhUxEhERERGV6NQtjlxORJbN6KL7ww8/RFRUFLp16wZHR0c4OjqiZ8+eeOyxxyp0TfeiRYsQHBwMlUqFqKgoHD58uMzl09LS8Nprr8HPzw9KpRL169fHli1bjH5eIiIiIrJu+WoNziVkAACaBnqYNxgiolIYPWWYg4MD1q9fjw8//BAnT56Eo6MjmjRpgjp16hj95OvXr8fEiROxZMkSREVFYf78+ejVqxcuXrwIHx8fveXz8vLQo0cP+Pj4YOPGjQgICEBcXBw8PDyMfm4iIiIism6Xbmcit0ADV5Ud6ng6mTscIqISVWiebgCoX78+6tWrBwCQySo2aMXcuXMxZswYjBo1CgCwZMkS/Pbbb1i+fDmmTJmit/zy5cuRmpqKAwcOwN7eHgAQHBxcsQSIiIiIyKoVnZ9bzkHUiMhCVajoXrlyJT799FNcvnwZQGEB/vbbb+OFF14weB15eXk4evQopk6dKrXJ5XJ0794dBw8eLPEx//d//4d27drhtddew88//wxvb28MGzYM77zzDhQKRYmPyc3NRW5urnQ7I6OwC1J+fj7y8/MNjre6aWOz5BiNwXwsn63lxHwsG/OxfLaWE/OxbBXN50T8PQBAhL+rRb0WtrZ9ANvLiflYNmvJx9D4ZEIIYcyK586di/fffx/jxo1Dhw4dAAD79+/HokWLMHPmTEyYMMGg9SQkJCAgIAAHDhxAu3btpPbJkydj7969OHTokN5jGjZsiOvXr+O5557Dq6++iitXruDVV1/FG2+8gWnTppX4PNOnT0dMTIxe+9q1a+HkxG5IRERERNbq01MK3MySYVR9NZrVNOorLRFRpWVnZ2PYsGFIT0+Hm5tbqcsZXXSHhIQgJiYGw4cP12n/7rvvMH36dMTGxhq0nooU3fXr10dOTg5iY2OlM9tz587Fp59+isTExBKfp6Qz3UFBQUhOTi7zhTG3/Px87NixAz169JC60lsz5mP5bC0n5mPZmI/ls7WcmI9lq0g+uflqNJv5Bwo0ArsnRiOwhmMVR2k4W9s+gO3lxHwsm7Xkk5GRAS8vr3KLbqO7lycmJqJ9+/Z67e3bty+18C2Jl5cXFAoFbt++rdN++/Zt+Pr6lvgYPz8/2Nvb63Qlb9SoEZKSkpCXlwcHBwe9xyiVSiiVSr12e3t7i96AWtYSp6GYj+WztZyYj2VjPpbP1nJiPpbNmHzOJmWhQCPg6eyAYG/XCo8xVJVsbfsAtpcT87Fslp6PobEZPWVYWFgYfvjhB7329evXSwOrGcLBwQEtW7bErl27pDaNRoNdu3bpnPkuqkOHDrhy5Qo0Go3UdunSJfj5+ZVYcBMRERGRbTp9Mw1A4SBqllhwExFpGX2mOyYmBs8++yz+/PNP6Zruv/76C7t27SqxGC/LxIkTMWLECLRq1Qpt2rTB/PnzkZWVJY1mPnz4cAQEBGD27NkAgLFjx+KLL77A+PHj8frrr+Py5cuYNWsW3njjDWPTICIiIiIrdvLhyOVNA93NHAkRUdmMLrqfeeYZHD58GHPnzsVPP/0EoLCL9+HDh9G8eXOj1vXss8/i7t27+OCDD5CUlIRmzZph69atqFWrFgAgPj4ecvm/J+ODgoKwbds2TJgwAU2bNkVAQADGjx+Pd955x9g0iIiIiMiKnZaKbg/zBkJEVA6jiu78/Hy8/PLLeP/997F69WqTBDBu3DiMGzeuxPv27Nmj19auXTv8/fffJnluIiIiIrI+2XkFuHwnEwDPdBOR5TPqmm57e3ts2rSpqmIhIiIiIirX2YQMaARQy02JWm4qc4dDRFQmowdS69+/v9StnIiIiIioup162LW8SYCHeQMhIjKA0dd016tXDzNmzMBff/2Fli1bwtnZWed+DmpGRERERFVJO3I5u5YTkTUwuuj+5ptv4OHhgaNHj+Lo0aM698lkMhbdRERERFSlTnHkciKyIkYX3bGxsVURBxERERFRuTJy8nEtOQtA4RzdRESWzuhruosSQkAIYapYiIiIiIjKdObhWe4AD0fUdFGaORoiovJVqOj+5ptvEBERAZVKBZVKhYiICHz99demjo2IiIiISMepW4VFd2QQz3ITkXUwunv5Bx98gLlz5+L1119Hu3btAAAHDx7EhAkTEB8fjxkzZpg8SCIiIiIiADjNkcuJyMoYXXQvXrwYX331FYYOHSq1Pfnkk2jatClef/11Ft1EREREVGVOcuRyIrIyRncvz8/PR6tWrfTaW7ZsiYKCApMERURERERUXGpWHm7eewAAiOAgakRkJYwuul944QUsXrxYr33ZsmV47rnnTBIUEREREVFxpx9ezx3i5Qx3R3szR0NEZBiju5cDhQOpbd++HW3btgUAHDp0CPHx8Rg+fDgmTpwoLTd37lzTRElEREREj7xTN9IAsGs5EVkXo4vuM2fOoEWLFgCAq1evAgC8vLzg5eWFM2fOSMvJZDIThUhERERE9O/I5Zyfm4isidFF9+7du6siDiIiIiKiMmlHLm8a6GHeQIiIjFChebqJiIiIiKrTnYwcJGXkQC4DGvu7mTscIiKDsegmIiIiIot36uFZ7jAfFzgrKzQsERGRWbDoJiIiIiKLd+rh/NxNAjzMGgcRkbFYdBMRERGRxdMOohYZxEHUiMi6sOgmIiIiIosmhJAGUePI5URkbSp0Qczly5exe/du3LlzBxqNRue+Dz74wCSBEREREREBwK20B0jJyoOdXIZGfhxEjYisi9FF91dffYWxY8fCy8sLvr6+OvNxy2QyFt1EREREZFLas9wNfF2hsleYORoiIuMYXXTPnDkTH330Ed55552qiIeIiIiISIf2eu6mgexaTkTWx+hruu/du4dBgwZVRSxERERERHq0I5c3DfQwaxxERBVhdNE9aNAgbN++vSpiISIiIiLSIYSQ5ujmIGpEZI2M7l4eFhaG999/H3///TeaNGkCe3t7nfvfeOMNkwVHRERERI+2uJRsZOYUwMFOjga+ruYOh4jIaEYX3cuWLYOLiwv27t2LvXv36twnk8lYdBMRERGRyZx82LU83M8N9grOdktE1sfoojs2NrYq4iAiIiIi0qMduZyDqBGRteLPhURERERksXg9NxFZO6PPdAPAzZs38X//93+Ij49HXl6ezn1z5841SWBERERE9GhTawTOJBQW3ZFBHuYNhoiogowuunft2oUnn3wSdevWxYULFxAREYHr169DCIEWLVpURYxERERE9Ai6dvc+svPUcLRXINTbxdzhEBFViNHdy6dOnYpJkybh9OnTUKlU2LRpE27cuIHOnTtz/m4iIiIiMpmTD7uWRwS4QSGXmTkaIqKKMbroPn/+PIYPHw4AsLOzw4MHD+Di4oIZM2Zgzpw5Jg+QiIiIiB5Npx+OXN400MOscRARVYbRRbezs7N0Hbefnx+uXr0q3ZecnFyhIBYtWoTg4GCoVCpERUXh8OHDBj1u3bp1kMlk6N+/f4Wel4iIiIgs16lbHLmciKyf0UV327ZtsX//fgBAnz598NZbb+Gjjz7C6NGj0bZtW6MDWL9+PSZOnIhp06bh2LFjiIyMRK9evXDnzp0yH3f9+nVMmjQJ0dHRRj8nEREREVm2fLUG5xIyAHDkciKybkYX3XPnzkVUVBQAICYmBt26dcP69esRHByMb775xugA5s6dizFjxmDUqFEIDw/HkiVL4OTkhOXLl5f6GLVajeeeew4xMTGoW7eu0c9JRERERJbt0u1M5BZo4KqyQ3BNZ3OHQ0RUYUaPXl60yHV2dsaSJUsq/OR5eXk4evQopk6dKrXJ5XJ0794dBw8eLPVxM2bMgI+PD1588UXs27evws9PRERERJbpdJH5ueUcRI2IrFiF5uk2leTkZKjVatSqVUunvVatWrhw4UKJj9m/fz+++eYbnDhxwqDnyM3NRW5urnQ7I6Owm1J+fj7y8/MrFng10MZmyTEag/lYPlvLiflYNuZj+WwtJ+Zj2UrK53j8PQBAhL+r1eVpa9sHsL2cmI9ls5Z8DI1PJoQQ5S3k6emJS5cuwcvLCzVq1IBMVvqvjampqQYHmZCQgICAABw4cADt2rWT2idPnoy9e/fi0KFDOstnZmaiadOm+PLLL9G7d28AwMiRI5GWloaffvqpxOeYPn06YmJi9NrXrl0LJycng2MlIiIiourz6SkFbmbJMKq+Gs1qlvt1lYio2mVnZ2PYsGFIT0+Hm5tbqcsZdKZ73rx5cHV1BQDMnz/fJAECgJeXFxQKBW7fvq3Tfvv2bfj6+uotf/XqVVy/fh39+vWT2jQaDYDC6csuXryI0NBQncdMnToVEydOlG5nZGQgKCgIPXv2LPOFMbf8/Hzs2LEDPXr0gL29vbnDqTTmY/lsLSfmY9mYj+WztZyYj2Urnk9uvhpvHfoDgMDwJ7ogsIajuUM0iq1tH8D2cmI+ls1a8tH2oi6PQUX3iBEjSvy7shwcHNCyZUvs2rVLmvZLo9Fg165dGDdunN7yDRs2xOnTp3Xa3nvvPWRmZmLBggUICgrSe4xSqYRSqdRrt7e3t+gNqGUtcRqK+Vg+W8uJ+Vg25mP5bC0n5mPZtPmcTcpCgUbA09kBwd6uZfaytGS2tn0A28uJ+Vg2S8/H0NgMKroNreABGH32eOLEiRgxYgRatWqFNm3aYP78+cjKysKoUaMAAMOHD0dAQABmz54NlUqFiIgIncd7eHgAgF47EREREVmn0zfTABQOomatBTcRkZZBRbeHh4fBBzy1Wm1UAM8++yzu3r2LDz74AElJSWjWrBm2bt0qDa4WHx8Pudzomc2IiIiIyEqdfDhyedNAzs9NRNbPoKJ79+7d0t/Xr1/HlClTMHLkSGnws4MHD+K7777D7NmzKxTEuHHjSuxODgB79uwp87ErVqyo0HMSERERkWU6LRXdHuYNhIjIBAwqujt37iz9PWPGDMydOxdDhw6V2p588kk0adIEy5YtM+k130RERET0aMnOK8DlO5kAeKabiGyD0f22Dx48iFatWum1t2rVCocPHzZJUERERET0aDqbkAGNAHxclajlpjJ3OERElWZ00R0UFISvvvpKr/3rr78ucfRwIiIiIiJDnWLXciKyMQZ1Ly9q3rx5eOaZZ/D7778jKioKAHD48GFcvnwZmzZtMnmARERERPTo0I5czq7lRGQrjD7T3adPH1y6dAn9+vVDamoqUlNT0a9fP1y6dAl9+vSpihiJiIiI6BFxiiOXE5GNMfpMN1DYxXzWrFmmjoWIiIiIHmGZOfm4lpwFoHCObiIiW1ChCbD37duH559/Hu3bt8etW7cAAKtWrcL+/ftNGhwRERERPTrOJGQAAAI8HFHTRWnmaIiITMPoonvTpk3o1asXHB0dcezYMeTm5gIA0tPTefabiIiIiCrs9K3CojsyiGe5ich2GF10z5w5E0uWLMFXX30Fe3t7qb1Dhw44duyYSYMjIiIiokfHmYdFd5MAD/MGQkRkQkYX3RcvXkSnTp302t3d3ZGWlmaKmIiIiIjoEXT6FgdRIyLbY3TR7evriytXrui179+/H3Xr1jVJUERERET0aLmfD9xMywEARHAQNSKyIUYX3WPGjMH48eNx6NAhyGQyJCQkYM2aNZg0aRLGjh1bFTESERERkY27kSUDAIR4OcPd0b6cpYmIrIfRU4ZNmTIFGo0G3bp1Q3Z2Njp16gSlUolJkybh9ddfr4oYiYiIiMjGxd8v/J9ThRGRrTG66JbJZHj33Xfx9ttv48qVK7h//z7Cw8Ph4uJSFfERERERURFqjcCh2FQcTZahZmwq2oX5QCGXmTusSrtxvzAHXs9NRLbG6KJby8HBAeHh4aaMhYiIiIjKsPVMImJ+OYfE9BwACqy8fAR+7ipM6xeOxyP8zB1ehWh/RLiSUVh0R/iz6CYi22Jw0T169GiDllu+fHmFgyEiIiKikm09k4ixq49BFGtPSs/B2NXHsPj5FlZXeOv+iFBYdI9ffxwxTza2ulyIiEpjcNG9YsUK1KlTB82bN4cQxQ/3RERERFRV1BqBmF/O6RXcAKS2KZtOIzdfA5WDAko7ORzs5FDaFf6tva1tc3jYZieXQSYzT9f00n5EuJORa7U/IhARlcTgonvs2LH4/vvvERsbi1GjRuH555+Hp6dnVcZGRERE9EjTaASu3L2PdYfjH54NLl3ag3yMX3/CqPXLZCgsyBVyKO0VD///97ZSIZcKdN3/FeXcLntZhVyGD34+W+qPCDIAMb+cQ49wX5u4Xp2IHm0GF92LFi3C3LlzsXnzZixfvhxTp05F37598eKLL6Jnz55m+5WUiIiIyFZoNALnkzJw6FoqDsWm4J/r95CalWfw40O9neHmaI/cfA3y1BrkFWiQW6B++H/h7QLNv6WuEEBOvgY5+Rogp6AqUqoQASAxPQeHY1PRLrSmucMhIqoUowZSUyqVGDp0KIYOHYq4uDisWLECr776KgoKCnD27FmOYE5ERERkhAK1BucS/y2yD8emIqNY8auylyPM2wVnEjLKXd/M/k3KLVLVGqFXjGsL8uIFem6BBnlqtVTES/+XtmyButjtktebnaeG2oDLFe9kln12n4jIGlR49HK5XA6ZTAYhBNRqtSljIiIiIrJJ+WoNTt9Kl4rsI9fv4X6ubpHt7KBAy2BPRIV4om1dTzQJ8IBCLkPHOX8gKT2nxC7ZMgC+7iq0CSn/0j+FXAZHBwUcHRSmSaoCDl5NwdCv/i53OR9XVTVEQ0RUtYwqunNzc6Xu5fv378cTTzyBL774Ao8//jjkcnlVxUhERERklXIL1Dh5Ix2HrqUUzq0ddw8P8nVPVriq7NAm2BNRdT3RJqQmIvzdYKfQ/141rV84xq4+BhmgU3jLitxvLdc/twnxhJ+7yiQ/IhARWTqDi+5XX30V69atQ1BQEEaPHo3vv/8eXl5eVRkbERERkVXJyVfjWPw96Uz28fg05BZodJbxcLJ/WGTXRFSIJxr5uRlULD8e4YfFz7coMsVWIV8rnKdbIZfZ1I8IRERlMbjoXrJkCWrXro26deti79692Lt3b4nLbd682WTBERERWTq1RhSewUyWoWZsKtqF+bBQeIRk5RbgaNw9HIpNwaFrqTh5Mw35at1zt14uDogKqfnwTLYn6vu4Ql7BfeTxCD/0CPfFwSt3sH3fIfSMjrLafc6WfkQgIiqLwUX38OHDOUI5ERFREVvPJBYpGBRYefkI/GygYOAPCaXLzMnHkev38PfDIvvMrXSd0cABoJabUiqyo0JqItTb2aTfoRRyGaJCPJFyXiAqxNOqt40t/YhARFQag4vuFStWVGEYRET0qLCVgm7rmUSMXX1M73rUpPQcjF19DIufb2GVhbct/pBQmX0uPTsfh6+nStdkn01IR7EaGwEejoiq64m2ITXRJsQTdWo68USFEWzpRwQiopJUePRyIiIiY9lKQafWCMT8cq7EAaAECq9JjfnlHHqE+1pVAWGLPyQYu8+l3M/F4dhUHIpNxd/XUnDxdiaKz2xVp6YTokI8pbPZgTWcqicZIiKySiy6iYioWpi6oCtQF58fuHAu4HLnHC5Q6803XPJjS59z+H5uPu7nlj5dpgCQmJ6Dhu//DpW9AvYKOezkMtgr5LBXyGCnkP/7t9Quh52iyDLyIssoiixT6noK/y++nsLHlHSf7rpkMhmm/d9Zm/ohwZB9rkWdGtKgZ4eupeLynft66wn1dkabkJpo+7C7uK87p7EiIiLDsegmIqIqV96ZYQB4c/0JdDhyA3lqUU7hXHi7eBdfS5SvFshXF5S/oBXQ/pDQ+dM/4O7oAHuFHA52cjg8/F9b1Ou2yYu0yUpoK7qcrMTHKu3+XV56DoW83IHIDNnnXlt7HOoSdqQGtVyl67HbhHjC21VZ6dePiIgeXSy6iYioyuQWqHH6Zjo2Hb2pMzpxSXLyNdh14W6FnsdOXliwKe3kD/9XSAWc0l77v0K6rSyhvaTH/3v733alnRznEzPw9sZT5cb1+ZBmiAhwR4FGIK9AgwKNQIG68Ax7gVqgQKNBXkHh/wVqUay96PKF//+7npKWL74ejd7zFv4IUHg7v0CDfI328Yb/gnHzXg5u3it7W1YH7TbXLc7/Lfxz8tXl7nPagjvcz02nyPZ0dqiOFIiI6BHBopuIiEwmLTsPR+Pu4Z/r93DkeipO3UpHXrE5issypHUQoup6wkGhKLHg1d4u3lbd3Z0b+blh7o5LSErPKfFMqgyF0x71bepvFV2xhRDYfzkZLyw/XO6y7/VthDAfF+SrCwv6/Ic/Ikh/S22ihLbiy4kSH5v/sLdD0bbiPwwUaAQK8tQASu/mb4iPBzTBkDa1K7UOIiKisrDoJiKiChFC4EbqA/xzPRVH4gqL7JKuh/VyUSLEywn/XL9X7jqfahaAdqE1qyJck1LIZZjWLxxjVx+DDNApvLUl9rR+4VZRcAOATCZD+zAv+Lmryv0hYVSHELPkpdEUFuhFC/b8h9fkl1TYn7mVjv9tv1TueuvUdK6G6ImI6FHGopuIiAxSoNbgfGLmwyI7FUeu38OdzFy95UK9ndE62BMt69RA6+DC6ZM0Aug4549yC7o2IZ5VnoepPB7hh8XPtygyMnYhXyscjR2w/B8S5HIZVHIFVPYKg5aPrueNNYfibWqfIyIi62QRRfeiRYvw6aefIikpCZGRkVi4cCHatGlT4rJfffUVVq5ciTNnzgAAWrZsiVmzZpW6PBERVcz93AKciE+Tiuzj8WnIztPtymuvkKFJgLtUZLesUwM1XfQHnVLIYNEFXUU9HuGHHuG+OHjlDrbvO4Se0VFWO+84YFs/JFj6jwhERPToMHvRvX79ekycOBFLlixBVFQU5s+fj169euHixYvw8fHRW37Pnj0YOnQo2rdvD5VKhTlz5qBnz544e/YsAgICzJABEZFtuJ2RU1hgX7+HI3GpOJeQoTdCuKvKDq3q1ECrYE+0DvZE00B3g8882lJBV5RCLkNUiCdSzgtEhXhafRFnSz8k2Oo+R0RE1sXsRffcuXMxZswYjBo1CgCwZMkS/Pbbb1i+fDmmTJmit/yaNWt0bn/99dfYtGkTdu3aheHDh1dLzERE1k6jEbhy9z7+uZ6Ko9fv4Z+4VNxIfaC3XGANR50iu56PS7lTNZXFlgo6W2ZLPyRwnyMiInMza9Gdl5eHo0ePYurUqVKbXC5H9+7dcfDgQYPWkZ2djfz8fHh6lnxNVm5uLnJz/73mMCMjAwCQn5+P/Pz8SkRftbSxWXKMhlJrBP6+ehdHk2Vwv3wHbUO9rf7Lji1tH8D2tpGt5QNUfp/LzVfjdEIGjsal4UjcPRy/kYb0B7rzR8tlQENfV7Ss7YGWdWqgRW0P+LmrdJZRqwugrtxg0QCAFoGuSPESaBHoCo26ABoTrNOcbO2YANheTtznLBvzsXy2lhPzsWzWko+h8cmEEIZPzmliCQkJCAgIwIEDB9CuXTupffLkydi7dy8OHTpU7jpeffVVbNu2DWfPnoVKpdK7f/r06YiJidFrX7t2LZycnCqXAJXrZIoMm6/LkZb3b8Hj4SAwIFiDyJpm2/UqRSOAqxkyZOQDbvZAqJuANddztraNbC0foGL7XFY+EJspw7WH/+LvA2qh+yAHuUAdF4G6bkBdV4FgFwGV2fs/EREREVmH7OxsDBs2DOnp6XBzcyt1Oav+evXxxx9j3bp12LNnT4kFNwBMnToVEydOlG5nZGQgKCgIPXv2LPOFMbf8/Hzs2LEDPXr0gL29vbnDqZBtZ2/j24Mn9UaNTc+T4dtLCiwcEolejWuZJbaK2nb2NmZvuYCkjH97T/i6KfFen4ZWlwtge9vI1vIBDNvnhBCIv/cAR+Pu4Vh8Go7EpeHq3Sy9dXm5OEhnsVvW9kAjP1fYK+TVlktRtnCMK8rW8gFsLyfmY9mYj+WztZyYj2Wzlny0vajLY9ai28vLCwqFArdv39Zpv337Nnx9fct87P/+9z98/PHH2LlzJ5o2bVrqckqlEkql/ki69vb2Fr0BtawlzuLUGoGPfr9Y4jQtAoUjx370+0X0bhpgNd1+t55JxOvr9Au62xm5eH3dSSx+voVVDcpj6Dbq3tjPKraRWiMwc8ujs8+NW3cSA1sGIiu3AEfi7uFuCVN3hfm4FLkeuwZqezpBJrOs3K31GFcaW8sHsL2cmI9lYz6Wz9ZyYj6WzdLzMTQ2sxbdDg4OaNmyJXbt2oX+/fsDADQaDXbt2oVx48aV+rhPPvkEH330EbZt24ZWrVpVU7RkjMOxqTojxRYnACSm56DR+1vhYCeHXAbYKeSQy2RQyAGFTAa5XAY7eeH/CpkMCrkMcpkMdgrZw+VkD5cD7OTyh8uhjOXKW1/pzwsAn++6XGpBBwCTN57CzXuFA1GpNQIFGgGNRkAt/v1fatMAGiEMWE7oLvfwb40GpS6nfrgOdZH1Su0aAY0ojC9frUFB8aGpS9hGDd/fWrGdwMJo8wn/YCscFHIoFP/uF9rtrP0nf7gfKeRynf1Cf7kit7X7lLQfPnxsmcuVtL7Cx8ogMH9n2fvcxqM3pTZ7hQxNAz2kIrtlnRrwdHaojpeWiIiIiMpg9u7lEydOxIgRI9CqVSu0adMG8+fPR1ZWljSa+fDhwxEQEIDZs2cDAObMmYMPPvgAa9euRXBwMJKSkgAALi4ucHFxMVsepOvkjTSDlstTa5Cn1lRtMNUkI6cAM387b+4wqBy5BRrkFtjGPgcAQ1oHYUCLQKOm7iIiIiKi6mP2ovvZZ5/F3bt38cEHHyApKQnNmjXD1q1bUatW4bWK8fHxkMv/veZw8eLFyMvLw8CBA3XWM23aNEyfPr06Q6dicgvU+P10Elb/HYcjcfcMesznQ5qhaaCHzllc7VnbomdxC88CAwUazcPloHNWV1PsDK/emV+d5fBwOY3OGecS1/fwdnxKNo4b8ENC8yAP1K7pZNQZTcXDv407k1p0ORh5JrXwTP6JG2l4/fvj5eb09fBWaB1c8uwAluSf66n4z8oj5S43/9lINA30kPaxoj0HdHsEFNmn1Lo9EfSXe/h4tQZqgTKWK2190Nsf41OzccKAfa5daE20CbH87UNERET0qDJ70Q0A48aNK7U7+Z49e3RuX79+veoDIqNcT87C94fjseHoTaRm5QEonHrIQSFHTilnFGUAfN1V6NvU3yqurz14NQVDv/q73OUmP94Q7UJrVkNElefv4YhZW84jKT2nxC7M2m3UtaF1zGfbtaEP/NxV5ebTL9I6ruk2dJ/zcS15EEkiIiIisgzmGbaWrF6BWoOtZ5LwwjeH0OV/e7D0z2tIzcqDn7sKE3vUx8Gp3TB/SDPIUFjsFKW9Pa1fuFUUPwDQJsQTfu4qvVy0ZAD83FVWdcZRIZdhWr9wALaxjWwtH1vc54iIiIgeRSy6yShJ6TmYt+MSOsz5A6+sPop9l5MhkwFdGnjjq+GtsG9yV7zRrR5quanweIQfFj/fAr7uumfifN1VVjfSt60VdFq2tI0A28rHVvc5IiIiokeNRXQvJ8um0Qjsv5KM1X/HYdeFO1A/HPG6prMDBrcOwtDWtVG7plOJj308wg89wn1x8ModbN93CD2jo9AuzDq6KxenLehifjmnMzK7r7sK0/qFW1VBV5QtbSPAtvKx1X2OiIiI6FHCoptKlZqVhw1HbmDt4XjEpWRL7VEhnniubR30alwLSrvyR0tWyGWICvFEynmBqBBPqyx+tGypoCvKlrYRYFv52Oo+R0RERPSoYNFNOoQQOBJ3D2v+jsOW00nSdF6uKjs80yIQz0XVRr1armaO0rxsqaAj68B9joiIiMh6segmAEBmTj5+PH4La/6Ox8XbmVJ700B3PBdVG/0i/eHkwN2FiIiIiIjIGKyiHnFnbqVjzaE4/HwiAdl5agCAyl6OpyID8Fzb2mga6GHeAImIiIiIiKwYi+5H0IM8NX49lYDVh+Jx8kaa1F7PxwXPRdXG0y0C4e5ob74AiYiIiIiIbASL7kfIlTv3sfZQPDYevYGMnAIAgL1Cht4RfnguqjbahHhCJuO1okRERERERKbCotvG5RVosP1cEtb8HY+D11Kk9iBPRwxrUweDWgXCy0VpxgiJiIiIiIhsF4tuG3UjNRvr/onH+n9uIvl+LgBALgMea1gLz7etjU71vCHnCMhERERERERVikW3DVFrBPZeuoPVf8dj98U7EKKw3cdViSGtgzCkTW34eziaN0giIiIiIqJHCItuG3AnMwcbjtzE2kPxuJX2QGrvGOaF56Jqo3t4Ldgr5GaMkIiIiIiI6NHEotsCqTUCh2JTcTRZhpqxqWgX5gNFsa7gQggcvJaCNYfise1MEgo0hae1PZzsMahlIIa2qY263i7mCJ+IiIiIiIgeYtFtYbaeSUTML+eQmJ4DQIGVl4/Az12Faf3C8XiEH9Kz87Hx2E2sORSHa3ezpMe1rFMDz0XVRp8mflDZK8yXABEREREREUlYdFuQrWcSMXb1MYhi7UnpOXhl9TG0q1sTx+LvIbdAAwBwdlDg6RYBGNamDsL93ao/YCIiIiIiIioTi24LodYIxPxyTq/gBiC1aaf8auTnhufb1sZTzQLgouQmJCIiIiIislSs2CzE4djUh13KyxbzZGMMb1cHMhmn+yIiIiIiIrJ0HNLaQtzJLL/gBgoHSmPBTUREREREZB1YdFsIH1eVSZcjIiIiIiIi82PRbSHahHjCz12F0s5hywD4uavQJsSzOsMiIiIiIiKiSmDRbSEUchmm9QsHAL3CW3t7Wr9wvfm6iYiIiIiIyHKx6LYgj0f4YfHzLeDrrtuF3NddhcXPt8DjEX5mioyIiIiIiIgqgqOXW5jHI/zQI9wXB6/cwfZ9h9AzOgrtwnx4hpuIiIiIiMgKsei2QAq5DFEhnkg5LxAV4smCm4iIiIiIyEqxezkRERERERFRFWHRTURERERERFRFWHQTERERERERVREW3URERERERERVhEU3ERERERERURVh0U1ERERERERURVh0ExEREREREVURFt1EREREREREVcTO3AFUNyEEACAjI8PMkZQtPz8f2dnZyMjIgL29vbnDqTTmY/lsLSfmY9mYj+WztZyYj2VjPpbP1nJiPpbNWvLR1pTaGrM0j1zRnZmZCQAICgoycyRERERERERk7TIzM+Hu7l7q/TJRXlluYzQaDRISEuDq6gqZTGbucEqVkZGBoKAg3LhxA25ubuYOp9KYj+WztZyYj2VjPpbP1nJiPpaN+Vg+W8uJ+Vg2a8lHCIHMzEz4+/tDLi/9yu1H7ky3XC5HYGCgucMwmJubm0XvaMZiPpbP1nJiPpaN+Vg+W8uJ+Vg25mP5bC0n5mPZrCGfss5wa3EgNSIiIiIiIqIqwqKbiIiIiIiIqIqw6LZQSqUS06ZNg1KpNHcoJsF8LJ+t5cR8LBvzsXy2lhPzsWzMx/LZWk7Mx7LZWj6P3EBqRERERERERNWFZ7qJiIiIiIiIqgiLbiIiIiIiIqIqwqKbiIiIiIiIqIqw6CYiIiIiIiKqIiy6iYiIiIiIiKoIi24rVlBQgPz8fHOHQdVEo9GYOwRwsgPLZwn7iSlxn7NstrZ9bC0fsny2ts/ZWj629plqi6xln2PRbaXOnTuHIUOGoHv37hg2bBg2btyIvLw8c4dFJpaYmIj4+Hjcu3cPcnn1v10fPHiAtLQ0qNVqAIBMJpP+tma29CGakZGB27dv4969ewAAuVxu1flxn7NstrZ9bC2fomxlnysoKEBOTo5Om7V8yS5JZmYm7ty5g+TkZACF+5w152Nr7yFb+0zVsoUctHJycpCRkYHc3FwA1vMeYtFthS5fvoz27dvD0dERvXr1QlxcHGbPno3XXnsNDx48MHd41cKWDh6lWbNmDfr164fOnTujQYMGWLduHYDqy/3MmTPo378/2rdvjyeffBLTp08HACgUCqv8QI2NjcXXX3+N3Nxcm/kQPX36NHr37o327dujV69eGD16NAoKCszyA40pcJ+zbLa2fWwtH8D29rkLFy7gxRdfRJcuXTBy5Ehs2bIFQOGXbGt09uxZDBgwAJ06dcLTTz+NL774AoD15mNr7yFb+0y9cuUKYmJikJ2dbRPHA6DwpOOwYcPQvn17DBgwAEuWLAFgHe8h69yLHnHff/89HnvsMaxatQr//e9/sXfvXjz33HM4ceIEXnzxRb1fhG2NRqORDoA///wzvv32W+lNZyvWrFmDsWPH4pVXXsGKFSswYsQI/Oc//0FsbGy1HPyvXbuGzp07o169ehg/fjxq166N1atXo0uXLlCr1Vb3gXrp0iW0bNkSM2fOxLJly5CXlwe5XG4Vv4yWJi4uDt26dUO7du3w6aefYtCgQdi/fz9atGiBK1eumDs8o3Gfs2y2tn1sLR/A9va5s2fPIjo6GgqFAo8//jguXryIefPmITEx0dyhVYg2n4iICHz44YcIDQ3Fhg0bkJ6eLi1jTdvK1t5DtvaZeuXKFXTo0AELFy7E+++/bxOF97lz59CpUyf4+fnh1Vdfhbu7O9asWYNjx46ZOzTDCLI6r732mmjVqpVOW05Ojvjyyy9FVFSUeP/990VBQYGZoqtaGo1G+vudd94R/v7+omPHjqJWrVqiW7du4tixYzrLWKOzZ8+K1q1bi2XLlum0R0ZGivnz51dLDF9//bXo0qWLyM3NFUIIkZeXJ/744w8RFhYm2rZtKy2nVqurJZ7KuHfvnujbt68YOHCgGDZsmIiKihLz58+XcrPW/WXTpk2iVatWIj09XWq7evWqiIqKEo0aNRK3b98WQgirORZwn7NstrR9hLC9fGxtn7t9+7aIiooSEyZMkNoSExOFm5ubWLlypRkjq5iEhATRuHFjMXnyZKntyJEjokePHuLSpUvi5s2bUru17HO29h6ypc/UtLQ00b9/fzFw4EDx9ttvi6ioKPHmm2+KrKwsIYT1bJOikpOTRefOncX48eOltpSUFFGnTh3xySefmC8wI/BMtxURD38BbdasGWQyGU6dOiW1KZVKDB8+HO3atcNvv/2m88upLdF2H5k3bx5WrVqFX375Bfv27cPnn3+OP/74A+PGjcOxY8es6tfi4lJSUiCTydC5c2cA/273mjVr4vbt29USw40bNxAbGwsHBwcAgL29Pbp06YJVq1bh7t27GDhwIABYRZcrjUaDBg0aYOTIkfj6668RHh6O77//HosXL0ZeXp7etUDWsu8kJibi+vXrcHNzA1CYZ926dfHjjz/CwcEBAwYMAFDYzc8acJ+zbLa0fQDby8fW9rkzZ87A398fw4cPBwDk5eXB19cXXbt2RVpaGgDLz6GoxMRE9O/fH2PGjJHafv75Zxw7dgxdu3bFU089JR2zrWWfs7X3kC19prq6uiI8PBwDBw7EzJkz0bdvXxw8eBD//e9/SzzjbQ3vpbi4ONSqVQvPPPMMgMKxHjw9PdGnTx+kpKQAgOXnZJZSnyolMTFRBAUFiQEDBojU1FQhxL+/Yt+7d08oFAqxceNGc4ZYpe7evStef/11sWrVKiFE4a+THh4eYv78+aJ+/fqiffv24vDhw1b5S57WgQMHpL+1vyI///zzYsaMGTrLpaWlVcnzHzp0SISFhYnVq1frtOfl5YnVq1eLJk2aiIMHD1bJc1eF5ORk6T2SmZkpRo0apXcmKC8vz5whGi0uLk4EBgaK2bNnS23aff6vv/4SYWFhYt26deYKz2jc5yybrW0fW8tHCNva527cuCEWL14s3dbmNWDAADF16lRzhVVhOTk5Ii4uTro9Z84c4ejoKFatWiUOHjwo1q9fL+rWrVttvdlMwdbeQ7bymap9r+Tn50tt2dnZIiYmRkRFRYnx48eL7OxsIUThfmkt7ty5I77//nvptjbPV155RYwaNcpcYRnFOn5+IolGo4Gvry9+/vln7Ny5E6+//joSExOlM8AFBQVo2rQpPD09zRxp1alRowb69OmDXr164eTJk3jnnXcQExOD8ePHY9q0aTh48CBeeOEFXLp0ydyhGk37K127du0AFP5SZ29vD6Bw22pHOxVCYOjQodi8eXOVxFHn/9u7+7ga7/8P4K9TnW6VUkrRDRFSqdx8TVhuowm7YYxpsmUjqblbMqKNzE0zNjZMvonh29xkMTZEGcpNuakkZDG5bdFKnXr//vA7185RKKpzneP9fDy+j+/Oda5znc/LuTrnvM/nc30+9vZwdnbGTz/9hCNHjgjbpVIp+vfvj/z8fKSnp9fLc9cHc3NzSCQSlJeXo1GjRli5ciXat28v9AQ9ePAA06dPR1BQkKqbWmNNmjTB22+/jb1792Lz5s0A/u1RcHFxgZaWFnJzc1XZxFrhc07cNO310bQ8gOacc0SEFi1a4OOPPxZuK06SpDhh7Lfffot169Y1eBtrS09PD3Z2dsJtZ2dnJCQkYMyYMejWrRveeOMNGBoa4ubNmypsZe1o2t+Qpnymyv9WdHR0ADz+7mhgYICZM2fC19cXx48fx6xZs1BYWIhJkyYJPcdi17RpU4wcORJA1fcE+SzmALBo0SJ88cUXDd6+muCiW83Ih4R4eHhg9+7dSEhIgL+/P9avX4+TJ09iyZIluHHjBhwdHVXd1Dohk8mqbNPW1kb//v3RtGlT/PHHH7C1tcWoUaOE+4OCgtC5c2e0adOmIZtaJ54chiWRSIQ3loqKCuG/Bw8ejMOHD2PMmDF13gYigpWVFebPn4/c3FwsWbIE+/btE+63sLCAm5sbjIyM6vy565tUKkVlZSUMDQ3x7bffwtnZGVu3bkWfPn2wZs0ajBs3TtVNrLFGjRohKCgIRkZGWLNmDdavXy/cZ2JiglatWkFPTw+ASIdZKeBzTtw07fXRtDxPUvdz7slZiBWHxpubm8PMzAwAEB4ejtDQUOFHanUyePBg9O3bF8C/BYSDg4Pw3Y3fsxueJn2mKtLR0UFlZSX09PQwc+ZMDBo0CCdOnEDXrl2xZcsWTJ8+XdVNrDXF9wgLCwsYGxsDAGbNmoU5c+bAz89PVU17Jgmp05nDqsjNzcXkyZORm5sr/JoVGxsLDw8PVTftpVy+fBmtWrUSbq9evRqnT5+Gra0tfH194enpCSLCjBkzkJCQgAMHDsDIyAhjxoxB//79ERwcDADCDJrqTCaTQUdHBx9++CGaNWuGnJwcnD59GufPn4dUKq2XjPIZ4k+ePIlPPvkEenp68PLyQp8+fZCYmIj//ve/SEtLU3qN1Ik8X2FhIdzc3PDw4UMcOnQIbm5uqm5ajcm/qGVlZWHOnDnIzs6Gm5sbfHx8kJKSgk2bNiEtLU1tfnzic07c1Pn1UVzx4slt6pgHqD7T0/ZRh3PueXnk73f+/v5wcnICEWHBggU4cuQIOnXq1IAtrZma5pGbM2cONm7ciAMHDsDBwaEBWlg71X3PUNe/oSf/7Z/crm6fqU/L8yT561VUVIQePXogPz8fSUlJcHV1bYBW1k5NMwHAjBkzUFJSAktLSyxYsADJycmifE8AwNd0i9GlS5foiy++oLFjx9KWLVuEay8UVVZWCteaFBcXU35+PmVlZdHdu3cburl1buHChWRra0snT54kIqKwsDCysLCgN954gzw9PcnFxYV+/fVXIiK6du0aWVhYkLW1NbVs2ZJcXV3V5pq1mpJft+Lv708SiYQ8PDyEjIrX7NTlcxH9ey1TdnY2hYeHk5OTE7m4uFDnzp3p9OnTdfq89eVZM/aWlpbShx9+SEZGRnT27NkGbFXtPS2HfHt+fj6tXbuWPD09qUuXLtS7d286c+ZMQzaxTmjCOfcsYj/nnjcrr7q9Prdv3xY+P6ub40Pd8hA9P9OTxH7O1TbP+++/TxKJhAwNDSktLa2+m1drtc1z/PhxCg4OJjMzM1Gec8/7Xqluf0O5ubkUHx//1Ezq9pn6vDxPevToEYWEhJChoSFlZGTUc+teTG0zhYaGkkQiISMjI1G+JyjioltkMjIyyNramnx9fWnAgAEkkUhoy5YtSvsovpEXFRU1dBPrXWJiIg0bNow6d+5Mv/32GwUHB9OJEyeIiCg1NZX8/f3Jzs6OfvnlFyJ6PLHckiVL6IcffhCK0LouRutaTT6Mn9xnzpw51Lp16zrJmJWVReHh4TRy5Ej68ccfld6o5B86il/AKyoqqKysjO7cuUMPHjx44eetLzXJU92/+YgRI0Q70UtBQQFlZmY+c5/qiqSSkhIqKSmpr2a9sMuXL9OKFSto8uTJtHfvXrpz506VfdTpnKtJHnU657KysigkJIQGDRpEUVFR1Z576vT6XLp0iSwtLSkgIED4nHzy9VCnPEQ1y6RO51xt8sg7GkJDQ6lZs2Z07ty5Bm/v89T29bl79y59+eWX9Oabb4ryB5EzZ86QRCKh5cuXP3UfdfobSk9PpyZNmtC0adPo6tWrRFT1B211+kytSR7F801+X3BwsGiL09pmIiJavnw5OTo6ivI94UlcdIvIpUuXqHnz5hQeHi70ZL733nsUHh5ebU/X/Pnz6fPPP9eI3u0nHThwgN58801ycXEhd3d3un79unBfeno6+fv7k4ODg1B4K/77iH0NRcU3jB07dtCPP/6oNEsr0b95ioqKKD09vcpjX6bgPn/+PJmZmdHQoUOpX79+1KFDB3J3d1da+1Tx31D+5UGs67zWNo8Yvww86cKFC2RlZUWjR4+m8+fPP3d/+SoGYp2xPyMjg5o3b079+vUjd3d3MjExoWXLlhFR9W0W+zlX2zxiP+cyMjLIwsKCxowZQyNHjqR27drR4sWLiaj6H63E/voQEf38889kYmJCvr6+NHHixCpFkGLb1SEPUe0yif2cI3qx1ygrK4suX77c8I2tgdrkka8FfefOnXpbheRlnD59mgwMDGjmzJlP3Ued3hOuXbtGDg4ONH36dKXtiiMjFb8niP0ztbZ57t+/31BNe2Ev+hpdvXqV/vzzz4Zp5EviolskHj16RGFhYTRx4kRh8XoiotGjR9Pbb79NAwYMoKioKDp27Jhwn7+/P7m4uFTbw6KuFN+w9+3bR8OGDSM9Pb0qv8qlp6fTuHHjSE9Pj44fP97QzXxhivlmzpxJNjY21KNHD7KysqK+ffvSqVOnhH3Kysrogw8+oP/85z/V9ty+CJlMRuPGjSN/f3/hOKmpqRQcHExNmjShtWvXKu2/dOlS8vHxoYKCghd+zvqkaXmIiG7cuEGvvfYade3alRwcHOijjz56ZuG9fPlyat26tWg/dK5evUpt2rShsLAw4ceiRYsWkYWFRbU/GIr9NdK0PJcvXyZ7e3uaNWuWsG3y5MkUGBhY7Y97Ys8jl5ycTC4uLhQWFkZdu3aliRMnCl/eFL9Iq0seIs3LVJs8AwYMoBs3bqiqqTVS29fn5s2bqmrqM2VnZ5O2tjYtWLCAiB7/yL9371769ttv6ciRI0IPpJw6nG8///wzeXt7E9HjPLNnz6Y333yTxowZQ5s2bVLaV+yfqUSal4eo9pkcHR2VluFTBzqqvqacPaarq4sRI0bgn3/+gaGhIQBg/vz52Lp1Kz7++GPo6Ohg7dq1yMjIwLfffgtTU1PExMTg5s2bMDc3V3HrX558ggfFiRP69+8PqVSKoqIiBAQEYN26dejcuTMAwM3NDZMmTYKjo6N4J0yohjxfdHQ0YmNjkZCQAE9PT2zduhUjR45EUFAQvvnmG3h6ekIqlWL06NH4/vvvlSbGq+nkEtUhIly6dAkdO3YUjtO5c2c0bdoUurq6iIiIQNOmTTFkyBAAQHl5OUpLS1FWVvYSqeuPpuUBgJycHFhaWmLhwoXIyckRlvcJCQmBs7Nzlf2trKzQqlUrlJeXN3RTn6uiogI7duyAp6cnQkJChImFxowZgx9++AEFBQVVljcsKysT7WukiXn27dsHX19fTJ06VZi8pqKiAjk5OejWrRs6deoEX19fDB06FIB6/A1VVlbCysoK9vb2mDVrFho3boxdu3YhPDwcly5dgre3N4KCgqClpaUWeQDNy1TbPI8ePUJFRYWqm/1UL/L6iPE9WyaTYevWraisrES3bt0AAIMGDcLNmzdx+/ZtVFRUoEePHpg6dSp69OgBQD3eE7Kzs4WZx/v06QNDQ0PY29ujuLgY77//Pm7cuIGpU6cCEPdnqpym5QFqn8nR0VHU7wnVUnHRz54iPz+fRowYIQyfJno8FFkikYhyMoeXofgLcEJCAm3ZsoU2b94sbEtOTiY/Pz/y9PR86nUoYh9Sruj27ds0efJkio2NJSKi+Ph4MjU1pa+//pqcnJyoe/fudPz48SoTwtXVMKfp06eTj49PlV6D7Oxsevfdd2n48OFKQxPlQ3jEStPy3Lt3T2lEy/bt28nW1pY++ugjpWuWFHshxTy3w5YtW+iLL75Q2vb333+TpaUl/fbbb9U+RsyXzGhanpycHKVLWD7//HMyMDCghQsX0vz582nUqFHUqVMnpdEWYv8bkuvVq5eQLTo6mpo1a0Y6Ojp06NAhpf3UJQ+R5mXiPOKTm5tLU6dOJWNjY2rVqhW99dZbwqRbCQkJ5O3tTe+//z49fPhQeIyY8xAR7d69m1q2bEnR0dFKoyaKi4spOjqazM3N6ejRo8L+Yr88Q9PyEGlmpidx0a1CN2/epLS0NNq3b5/SkHKixwWW/JofeUGZnJxMbm5uVYb2qDPFodIhISFkampKbdu2JSMjI+revTslJycTEdHhw4dp6NCh1KVLF6U/OnUkk8loz549dOvWLTpz5gy1bt1amKgkLi6OJBIJtW3bli5cuEBEdX+N1LZt26hly5a0YsWKKm9amzZtIiMjI7py5UqdPmd90rQ8iuR/+zt37qQWLVooDTWPioqi/fv3q7J5tSY/l4uLi6l169Z0+PBh4b7ExMTnThwnNpqWRyaT0ZgxY2jXrl3CtqSkJDIxMaF9+/apsGW1I5/QqWfPnrR9+3YienyplomJCXXs2JFCQ0OFz1d1oWmZOI+45eXlUWhoKPXu3bvKBFXff/89GRoa0rVr11TUutrLysoiHx8f8vLyon79+indd+XKFWrVqhVt3bpVRa2rPU3LQ6SZmZ7Ew8tV5OzZs3j33Xehq6uLjIwMDBo0CIsWLYKLi4sw1Fq+2Lt8bcRdu3bBzMwMjRs3VmXT6wT9//Lw8iHBeXl5SEpKwoEDB2Bra4vy8nIMGTIEU6ZMwfr169GzZ088evQI8+fPx9q1a/Haa6+psvk1Jl9jW5G2tjb69+8PbW1txMfHw9bWFqNGjRLuDwoKwr179+Dk5ATg5YaTV+edd95BamoqZs6cCX19fbz11lvCkFhPT0/Y29vj0aNHdfqc9UnT8iiSD1+WD4+XDzUvLCxEYmIi0tLSVNa2mqAn1tqUSCQgImhpacHQ0FC4lOazzz7Djz/+iJMnT6qqqTWiaXkUERG0tbURGxsL4N9Lfpo1awZHR8cqw+bFTEtLC1paWhg0aBBKS0sREBCAgwcPYv/+/UhKSsKPP/4IHR0dLFq0qM7fX+uLpmXiPOJmZ2eH4OBg3LhxQ/guIl+r28bGBvb29jAwMFBxK2uubdu2GDJkCD799FPo6uoiLS1NuFyxefPmsLa2rrIOuZhpWh5AMzNVocqK/1V18eJFsra2ptmzZ9Ply5cpKyuLWrRoQSEhIdXuf+3aNZo9ezY1btxYtOvq1caTa1guXbqUfH19acSIEfTo0SNh+8OHD6l9+/bk5+cnPPbkyZOinU1SUW5urtLtVatWUWBgIEVGRgrrj1dWVtK0adOobdu2dP36dSosLKTBgwcrLc9R18PmFf/tJk+eTE2aNKFZs2bRiRMn6O7duzRt2jRydHSk27dv1+nz1hdNy1MdxZEOP//8M0kkEjI1NaVTp06psFUv58GDB2RnZ0cpKSk0d+5cMjQ0FJYFVEealOfJkTWfffYZderUiW7duqWiFr24qKgokkgk1KJFC+HSpLKyMlq6dKnajn7RtEycR9yqG2n36aefUp8+fUR9WZMixQwrVqwgS0tL6t69OyUkJNCFCxcoLCyMbG1t1abnXtPyEGlmpupw0d3A/vnnH5owYQKNHz+eHj16JBRVq1evpg4dOlBpaanSyZeRkUGDBg2itm3b0unTp1XU6rrz6aefkpWVlTDMqqioiCIiIsjc3Jw8PDyE/eSF+Z49e8jCwoKys7OVjiPmwnvhwoVka2srFNdhYWFkYWFBb7zxBnl6epKLiwv9+uuvRPT4BxULCwuytramli1bkqura5VruV/E3bt3KTMzky5evEiPHj1Suk+xkI+KiiIvLy/S09MjDw8Psra2FmUxp2l5iJ6d6UmVlZVUWlpKU6ZMIVNT0xotI9bQapPn4cOH1LFjR+revXu1qxOIwauch+jxLO0zZ84kU1NTpWu+xaImeYqLi2n27NnC6yHmzw0izcvEedQ/j6IrV67Q9OnTydTUVJTrij8rj+LrEBcXR8OGDSMtLS1ydXWl1q1bi/J7gqblIdLMTLXBRXcDe/DgAY0bN47Wr1+vtH3Hjh1kbW1NRUVFVX5Z3L9/v8Zcx33mzBny8PCgjh07CoV3fn4+LVmyhLS1tSkiIkJp/19++YUcHR1Fv9SBosTERBo2bBh17tyZfvvtNwoODhZ6vVJTU8nf35/s7OyESfL++usvWrJkCf3www/C5Fgvsw732bNnycPDg1xdXUlPT48iIyOr9JgrHj8vL48OHTpESUlJlJ+f/8LPW180LQ9RzTI9KSMjg5o0aSLKJfJqk6eyspJu375NNjY21KRJE1EWdK9yHqLHa/SOHTuWPDw8RDlxZ03yyD9H1WWSTU3LxHnErbbvCadOnaLhw4dThw4dRNkBVNvvCSUlJZSZmUk5OTmiHMWjaXmINDNTbXHRrQKKsyzLT7hjx46Ri4uLUsEtn0hL05w/f546duxILi4uQuFdUFBACxYsIKlUSmFhYZSZmUnZ2dk0cOBA6tmzp6h/La7OgQMH6M033yQXFxdyd3en69evC/elp6eTv78/OTg4CIW34uv+Mh/Y58+fJ3Nzc5o2bRqdP3+elixZQhKJRGlIjjr9W2paHqKXyyTGiXheNE90dHSVCXrEgPM8lpKSovS+JRYvmkfM7xOalonzPH2bGLxonoMHD4qyA0TTvidoWh4izcz0IrjoViHFE+zo0aNkZ2cnLMEwa9YsGjBgABUWFqqqefXqWYW3np4e6evr0+TJk2no0KFUUlJCROrxB6lYPO/bt4+GDRtW7XDT9PR0GjduHOnp6dVZz+Xt27epV69eNGXKFKX2DBw4kI4ePUqnT59W+sBcvnx5lREXYqJpeYg0L9OL5Fm7dq0KWloznGc5rVu3TgUtrRlN+/sh0rxMnEfz8vB7QsPRtDxEmpnpRXHRLRKHDh0iMzMzKi0tpTlz5pCOjg6lpqaqull14mm/AJ87d65K4X3z5k1asmQJWVpa0qxZs4T95YW3WD3tB4GDBw9Snz59yM3NrcrrmZaWRl988UWdDUW7c+cOLViwgC5evChsmz9/PkkkEnJ3d6cWLVqQj48PHTlyhO7evUtdunShgQMHirL3lEjz8hBpXibOw3kakqblIdK8TJyH8zQkziPuPESamelFcdHdAGqyzvIff/xBXbp0oWnTpol2Ip4XoViMnj9/nrKysoTr0ysrK6vt8b5+/TpFRUWRiYkJffXVVyppd20oZkxISKAtW7bQ5s2bhW3Jycnk5+dHnp6eT31d66rwVpxNdPPmzSSRSGjLli109+5dSkpKoi5dutDcuXOJ6PE1wnl5eXXyvPVF0/IQaV4mzsN5GpKm5SHSvEych/M0JM4j7jxEmpnpRUiI/n/BZFaniouLUVlZCSKCiYnJc/c/evQoevToATMzM+zfvx+enp4N0Mr6RQpr2kZEROCnn35CRUUFCgsLsWbNGgwbNgwAcOHCBYwePRpEhEOHDsHU1BR37tzB+vXrMXPmTCxbtgwhISGqC/IMihlDQ0MRExMDKysr5Ofno2PHjvjqq6/g5eWFI0eOYOnSpbhx4waWL1/eIOuM5+Xl4e7du0rn0uDBgwEACQkJarFWqCJNywNoXibOI26cR/w0LRPnETfOI26algfQzEw1paPqBmiiCxcuIDQ0FLdv30ZBQQG++uoroaiUn0yVlZXQ0tISHmNjY4POnTsjJiYGzs7Oqmp6nVIsuFevXo0NGzbA3d0dQUFBGDVqFJYvX47AwEA4Oztj06ZN6Nu3LyZPnozY2FhYWFjA398furq6GDhwoIqTVCX/rUqeMS8vD0lJSThw4ABsbW1RXl6OIUOGYMqUKVi/fj169uyJR48eYf78+Vi7dm2DFN329vawt7cH8Ph8KysrQ6NGjeDm5qaWb2qalgfQvEycR9w4j/hpWibOI26cR9w0LQ+gmZlqTHWd7JpJPkNfaGgoxcXF0aeffkpSqfSpSyzs3LmT/vrrLyIiKi0tbcCWNozTp09Tnz59aO/evUT0OK+ZmRn5+vqSlpYW/fDDD8K+V65cqTLMWoyTp8nXEJe3benSpeTr60sjRoygR48eCdsfPnxI7du3Jz8/P+GxJ0+eVFmmzz//nOzs7JSuq1FnmpaHSPMycR5x4zzip2mZOI+4cR5x07Q8RJqZ6Wm46K5Dd+/epQEDBlBwcLDSdm9vb5o8eTIRKV/fnZCQQC1atKBZs2aRTCar0bXf6ubq1av0zTffkEwmo4MHD5K1tTWtWLGCiIgGDRpERkZGFB0drfQYMa9x+emnn5KVlZVw/XlRURFFRESQubk5eXh4CPvJC/M9e/aQhYUFZWdnKx2nIQvvrVu30qRJk8jc3JxOnTrVYM9bXzQtD5HmZeI84sZ5xE/TMnEeceM84qZpeYg0M9PzaD2/L5zVVHl5OQoLC/HOO+8AeDxsAgBatmyJe/fuAYDS0InBgwdj3LhxGD9+PLS1tTVyWIW9vT3Gjh0LbW1tbNiwAX5+fvj4448BAM2bN4ejoyPi4+OF4doAoK2trarmPtfYsWNhY2ODXr16oaioCMbGxvjwww8RFhaGjIwMzJs3DwBgYGAA4PE50LhxYxgaGiodR/HSgvrm7OyM27dv48iRI/Dw8Giw560vmpYH0LxMnEfcOI/4aVomziNunEfcNC0PoJmZnocnUqtjOTk5aNOmDYDHRbhUKsXnn3+OvLw8/Pe//xX2KywshKmpqYpaWf/o8SgKaGlpobKyEjKZDN27d8eAAQOwYMECyGQyjBgxAlOnTkX37t0hkUiUrnkXswsXLuC9995DRUUFUlJSYGJiglu3bmHdunWYO3cupk2bhrFjx0JLSwtTpkxBcXExDh061KCF9pPk56Km0LQ8gOZl4jzixnnET9MycR5x4zzipml5AM3M9Cw8kVodkxfclZWVwolERLh165awz8KFC6Gnp4fg4GDo6GjWS6BYOGtpaeH333+Hjo4OXn/9dQwcOBCLFy/G/fv3kZqaivLycnTr1k2tCm4AwsRv7733Hry8vJCSkgJLS0uMHz8eADBv3jxER0fjo48+gp6eHrZv3y78+KCqwlvT3tQ0LQ+geZk4j7hxHvHTtEycR9w4j7hpWh5AMzM9Cw8vrydaWlpKQ6blxdacOXMQHh6Ovn37akTBXVBQgLy8PDx8+BDA4+Hz5eXlkEgk2L59O/r374+bN28CAMLDwxEeHo78/Hy4u7sjLS0N2traqKioEHXBLb9MQFG7du0QFxcHbW1teHl5oaioCJaWlggICMCXX34JExMTGBsbY8eOHdDX10dpaalKe7oZY4wxxhhjqsHDy+uRvGczIiICf/31F9q0aYPZs2fj6NGjGrEO9/r167Fy5Urk5eXBxcUFnp6eWLZsGQAgJSUF3t7eWLlyJSZMmKD0uNLSUujr6wMAZDKZqH98UOydvnDhArS1taGvrw97e3sQETIzM6sMNb9x4wZiY2OxYMECzJ49G9OnT1dxCsYYY4wxxpiqiLfa0QDyYk0qlWLNmjUwMTFBcnKyRhTcu3fvxqRJk7B8+XJYWloiNTUVP/30E1JTU3Hw4EGYm5tj586d8PX1FR4jH0IuL7iJSNQFt/yadODxWuM//fQTKioqUFhYiDVr1mDYsGHCUPPRo0ejV69eOHToEGxsbDB+/HhoaWlh5syZkEqlCAkJUW0YxhhjjDHGmEpwT3cDSEtLQ9euXXHu3Dk4Ozurujl1Yt68ebh48SLi4uIAAGVlZTh27BgCAgJgY2ODw4cPA4BKr2OuKxEREVi9ejU2bNgAd3d3BAUFYffu3Vi+fDkCAwMBAJmZmejbty/69u2L2NhYAMCtW7ewefNmDBw4EG3btlVlBMYYY4wxxpiKcNHdQIqLi2FkZKTqZtSZgIAAnDlzBqdOnRK2ERGOHTuGMWPGoFu3bkJBrs7OnDmDqVOnYsaMGfDx8cGuXbvwwQcf4LXXXsPevXuxevVqfPTRRwCAq1evwtbWVmnJM0340YExxhhjjDH24rgaaCCaVHADwPDhw1FaWopt27YJ2yQSCTp16oTPPvsMWVlZyMrKUmEL64aZmRmGDRuGfv364dChQ/j4448xf/58/PLLL/Dx8UFoaCi+/vprAICDg4MwMZwcF9yMMcYYY4y92rgiYC/E1dUVdnZ2iI2NRXJysrBdV1cXvXv3xrlz53Dx4kUVtrBu2NvbY+zYsdDW1saGDRvg5+eHjz/+GADQvHlzODo6Ij4+XmmmesWebsYYY4wxxtirjYtuVmtEhBYtWiAqKgo5OTlYvHgxEhMThfsbN26MDh06oFGjRips5cshImGpMGNjY5SVleHs2bMwNzeHjo4OZDIZ7t69i++++w6HDx8W1hpnjDHGGGOMMUV8TTd7IfJrlU+dOoXJkydDJpPBxcUFXl5e2LhxI+7fvy+sw61O5DOsy///999/h46ODl5//XXMnj0bixcvRkBAAFJTU1FeXo5Tp05BW1tb2J8xxhhjjDHGFHHRzZ6qoqKiyrJeisWlvPDOzc3Fzp07ERcXBzMzMzRp0gRxcXGQSqWoqKgQdeFdUFCA0tJSmJubCz3z5eXlkEql2L59O95++21s3rwZ7777LkpKSrB48WKkpqbCysoKq1atUouMjDHGGGOMMdXhoptVa9u2bUhMTER2djbeeustdOvWDT169ADwb+H95MzcRISysjLo6ekBAGQymajX4V6/fj1WrlyJvLw8uLi4wNPTE8uWLQMApKSkwNvbGytXrsSECROUHldaWiqsNS72jIwxxhhjjDHV4qKbVbFx40YEBgbik08+QUFBAXJycvDw4UPMmDED/v7+ACD07j548AAymQxmZmZKveBiH269e/dujBgxAsuXL4elpSVSU1Px008/wdraGgcPHsSlS5dw+fJl+Pr6Co95MpPYMzLGGGOMMcZUj4tupqS4uBjDhw+Ht7c3ZsyYAQA4ffo0YmNjERMTgyVLliAgIAAAUFJSghkzZuDcuXOIj49HkyZNVNn0Wpk3bx4uXrworCVeVlaGY8eOISAgADY2Njh8+DAAXmebMcYYY4wx9nK4mmBKKisrkZmZifLycmGbh4cHQkJCEBAQgMjISOzZswcAYGBgACsrK7Rs2RKmpqYqavGLycvLQ2ZmpnBbV1cXPXv2RGxsLK5fv47Ro0cD4HW2GWOMMcYYYy+HKwqmxNjYGP3790dGRgZu3rwpbLezs0NAQADc3Nzw888/QyaTAQBmz56NdevWQUtLS1hiSx0MHz4cpaWl2LZtm7BNIpGgU6dO+Oyzz5CVlYWsrCwVtpAxxhhjjDGmCbjoZlV4eXnhjz/+wPbt21FcXCxsd3Z2Rt++fbFt2zbcv39f2C5fYkudeoVdXV1hZ2eH2NhYJCcnC9t1dXXRu3dvnDt3DhcvXlRhCxljjDHGGGOaQH2qJNZg/P39MWLECEydOhWbNm3CnTt3hPtcXV3h5OSEJ6cCUKcJxYgILVq0QFRUFHJycrB48WIkJiYK9zdu3BgdOnQQlhBjjDHGGGOMsRfFE6kxJYoTh02ZMgWbN2/GmDFj4OPjA3t7ewQHB6OyshL79+9Xq0L7SfKcp06dwuTJkyGTyeDi4gIvLy9s3LgR9+/fR1paGq+/zRhjjDHGGHspXHS/ojIzM1FQUAATExM4OTkp9erKlwMDgOjoaOzduxe///47XF1doa+vj8OHD0MqlYp+Zu+KigoQkdI62orLfMnbn5ubi507dyIuLg5mZmZo0qQJ4uLiIJVKlf4tGGOMMcYYY6y2uOh+BcXExCAyMhJSqRRXrlzB3LlzMWvWLKV9ZDKZUKzeu3cP169fh1QqhZOTE7S0tJTuF6Nt27YhMTER2dnZeOutt9CtWzf06NEDwL+F95M/GhARysrKoKenBwCiz8gYY4wxxhgTPy66XzEbN27ExIkTsWrVKvj6+mLNmjWYN28e8vPzYWZmBuDforSkpAQGBgZVjiH2Hu6NGzciMDAQn3zyCQoKCpCTk4OHDx9ixowZ8Pf3B/Bvb/6DBw8gk8lgZmam1Auu+N+MMcYYY4wx9qK4G+8VcvbsWURHR2PZsmXCOtSjRo1CSkoKkpKSYGxsjObNm6Ndu3YoKirCvHnz0L59e3z44YdKxxFzwV1cXIxNmzYhIiICM2bMAACcPn0asbGxCA0NRUVFBQICAqCtrY2SkhLMmjUL586dQ3x8PJo0aSIchwtuxhhjjDHGWF3govsVYmVlhfHjx2PIkCHCtkmTJuHIkSP466+/8Pfff8PW1haLFi2ClZUV9u3bh3/++adK0S1mlZWVyMzMhJeXl7DNw8MD5ubm0NLSQmRkJKytrTFo0CAYGBjAysoKxcXFMDU1VV2jGWOMMcYYYxqLh5e/YhSHjEdGRmLVqlXYs2cPOnbsiGPHjmH8+PEIDAzElClTkJOTA0dHR1H3bFcnMDAQf//9N5YvX45mzZoJ2y9cuICwsDBYWlpi1apVwvXaT7vGmzHGGGOMMcZeFlcYrxjFa7THjRuHM2fOoGPHjgCAbt26wdjYGHl5eQCANm3aQEtLCxUVFSpp64vy8vLCH3/8ge3bt6O4uFjY7uzsjL59+2Lbtm24f/++sF0ikYCIuOBmjDHGGGOM1TkeXv4Ka9GihdLtgoIC6Ovrw93dXWm7ui2Z5e/vj7Nnz2Lq1KnQ0dHBm2++CQsLCwCAq6srnJyc8OQAD76GmzHGGGOMMVYfuOhmICLh2m2ZTCZMsqaO5EPElyxZgvLycoSHhyMzMxM+Pj6wt7fHwoULYWJigqZNm6q6qYwxxhhjjLFXAF/T/YqrqKjAihUr8Ouvv6KgoADHjx+HVCoVltQSq8zMTBQUFMDExAROTk5o1KiRcJ9i26Ojo7F37178/vvvcHV1hb6+Pg4fPgypVMrXcDPGGGOMMcbqHRfdDOfOnUNMTAyioqKgo6MDmUwmTDImRjExMYiMjIRUKsWVK1cwd+5czJo1S2kfxQz37t3D9evXIZVK4eTkBC0tLdFnZIwxxhhjjGkGLrqZErH3cG/cuBETJ07EqlWr4OvrizVr1mDevHnIz8+HmZkZgH9nI1ecqV0R93AzxhhjjDHGGgp39TElYi64z549i+joaCxbtky47nzUqFFISUlBUlISjI2N0bx5c7Rr1w5FRUWYN28e2rdvX2WdcS64GWOMMcYYYw2Fi26mNqysrDB+/HgMGTJE2DZp0iQcOXIEf/31F/7++2/Y2tpi0aJFsLKywr59+4QJ4hhjjDHGGGNMFXh4OVMrikPGIyMjsWrVKuzZswcdO3bEsWPHMH78eAQGBmLKlCnIycmBo6Mj92wzxhhjjDHGVIaLbqa28vPzoaurC0tLS2Fbt27d0L17dyxbtkzYJvbr1BljjDHGGGOai4eXM7XVokULpdsFBQXQ19eHu7u70nYuuBljjDHGGGOqwj3dTO0REf755x+MHDkS9+/fR1JSEhfajDHGGGOMMVHgnm6m1ioqKrBixQr8+uuvKCgowPHjx6Gtrc1DyhljjDHGGGOiwDNMMbWmra2Nfv36oUOHDjhx4gSkUilkMhkX3IwxxhhjjDFR4OHlTKNwDzdjjDHGGGNMTLjoZowxxhhjjDHG6gkPL2eMMcYYY4wxxuoJF92MMcYYY4wxxlg94aKbMcYYY4wxxhirJ1x0M8YYY4wxxhhj9YSLbsYYY4wxxhhjrJ5w0c0YY4wxxhhjjNUTLroZY4wxkfL29kZISIiqmyEaDg4O+Prrr1XdDMYYY6xWuOhmjDHGXtAHH3wAiUQCiUQCXV1dtG7dGvPnz4dMJlN10zRSamoqAgMDVd0MxhhjrFZ0VN0AxhhjTJ0NHDgQ69evx6NHj5CYmIhJkyZBKpUiLCxM1U1TK2VlZdDV1X3mPk2bNm2g1jDGGGN1h3u6GWOMsZegp6eHZs2awd7eHp988gn69euHXbt2AQCWLVsGV1dXGBkZwdbWFhMnTsTDhw+VHp+SkgJvb28YGhrCzMwMPj4+uH//frXP9csvv6Bx48aIi4sDAMTGxqJz584wNjZGs2bN8N577+HWrVtKj9m1axfatGkDfX199O7dGxs2bIBEIkFhYaGwT3JyMnr27AkDAwPY2toiODgYxcXF1bbh4sWLkEgkyMrKUtoeHR0NR0dH4fa5c+cwaNAgNGrUCFZWVnj//fdx584d4X5vb28EBQUhJCQEFhYW8PHxAREhIiICdnZ20NPTg42NDYKDg4XHPDm8/Nq1axg6dCgaNWoEExMTjBgxAgUFBcL9ERERcHd3R2xsLBwcHNC4cWOMHDkSDx48qDYbY4wxVh+46GaMMcbqkIGBAcrKygAAWlpa+Oabb3D+/Hls2LABBw4cwIwZM4R9z5w5g759+8LZ2Rl//PEHkpOT4efnh4qKiirH3bRpE0aNGoW4uDiMHj0aAFBeXo7IyEikp6djx44duHr1Kj744APhMVeuXME777yDYcOGIT09HRMmTEB4eLjScXNzczFw4EC8/fbbyMjIwJYtW5CcnIygoKBq8zk5OaFz585C4S8XFxeH9957DwBQWFiIPn36wMPDA2lpadi7dy8KCgowYsQIpcds2LABurq6SElJwerVqxEfH4/o6Gh8//33yMnJwY4dO+Dq6lptOyorKzF06FDcu3cPSUlJ2L9/Py5fvox33323Sr4dO3Zg9+7d2L17N5KSkhAVFVXtMRljjLF6QYwxxhh7If7+/jR06FAiIqqsrKT9+/eTnp4eTZs2rdr9t23bRubm5sLtUaNGkZeX11OP//rrr9OUKVNo5cqV1LhxYzp06NAz25OamkoA6MGDB0RENHPmTHJxcVHaJzw8nADQ/fv3iYho/PjxFBgYqLTPkSNHSEtLi0pKSqp9nujoaHJ0dBRuZ2dnEwDKzMwkIqLIyEgaMGCA0mP+/PNPAkDZ2dlCNg8PD6V9li5dSk5OTlRWVlbt89rb21N0dDQREe3bt4+0tbXp2rVrwv3nz58nAHTixAkiIpo7dy4ZGhpSUVGRsM/06dPpP//5T7XHZ4wxxuoD93QzxhhjL2H37t1o1KgR9PX1MWjQILz77ruIiIgAAPz222/o27cvmjdvDmNjY7z//vu4e/cu/vnnHwD/9nQ/y//+9z+EhoZi//79eP3115XuO3nyJPz8/GBnZwdjY2Ph/mvXrgEAsrOz0aVLF6XHdO3aVel2eno6YmJi0KhRI+F/Pj4+qKysxJUrV6pt08iRI3H16lUcO3YMwONebk9PT7Rr10445sGDB5WOKb8vNzdXOE6nTp2Ujjt8+HCUlJSgVatW+Oijj7B9+/anTkqXmZkJW1tb2NraCtucnZ1hamqKzMxMYZuDgwOMjY2F29bW1lWG4DPGGGP1iYtuxhhj7CX07t0bZ86cQU5ODkpKSrBhwwYYGRnh6tWrGDx4MNzc3BAfH4+TJ0/i22+/BQBh+LmBgcFzj+/h4YGmTZvixx9/BBEJ24uLi+Hj4wMTExPExcUhNTUV27dvVzp+TTx8+BATJkzAmTNnhP+lp6cjJydH6RptRc2aNUOfPn2wadMmAI+HvsuHvMuP6efnp3RM+b9Rr169hP2MjIyUjmtra4vs7Gx89913MDAwwMSJE9GrVy+Ul5fXOM+TpFKp0m2JRILKysoXPh5jjDFWWzx7OWOMMfYSjIyM0Lp16yrbT548icrKSixduhRaWo9/4966davSPm5ubvj9998xb968px7f0dERS5cuhbe3N7S1tbFy5UoAQFZWFu7evYuoqCihtzctLU3psW3btkViYqLSttTUVKXbnp6euHDhQrUZnmX06NGYMWMGRo0ahcuXL2PkyJFKx4yPj4eDgwN0dGr3VcPAwAB+fn7w8/PDpEmT0K5dO5w9exaenp5K+7Vv3x5//vkn/vzzTyH/hQsXUFhYCGdn51o9J2OMMVafuKebMcYYqwetW7dGeXk5VqxYgcuXLyM2NharV69W2icsLAypqamYOHEiMjIykJWVhVWrVinN8g08nrzs4MGDiI+PR0hICADAzs4Ourq6wvF37dqFyMhIpcdNmDABWVlZmDlzJi5evIitW7ciJiYGwOMeXwCYOXMmjh49iqCgIKE3eufOnU+dSE3urbfewoMHD/DJJ5+gd+/esLGxEe6bNGkS7t27h1GjRiE1NRW5ubn49ddfMW7cuGoniZOLiYnBunXrcO7cOVy+fBkbN26EgYEB7O3tq+zbr18/uLq6YvTo0Th16hROnDiBsWPH4vXXX0fnzp2f2XbGGGOsIXHRzRhjjNWDjh07YtmyZVi0aBFcXFwQFxeHhQsXKu3j5OSEffv2IT09HV27dsVrr72GnTt3Vts73LZtWxw4cACbN2/G1KlT0bRpU8TExGDbtm1wdnZGVFQUlixZovSYli1b4n//+x9+/vlnuLm5YdWqVcLs5Xp6egAe97YnJSXh4sWL6NmzJzw8PDBnzhylIro6xsbG8PPzQ3p6utLQcgCwsbFBSkoKKioqMGDAALi6uiIkJASmpqZCr391TE1NsWbNGnh5ecHNzQ2//fYbEhISYG5uXmVfiUSCnTt3wszMDL169UK/fv3QqlUrbNmy5ZntZowxxhqahBQvEGOMMcaYRvvyyy+xevVq/Pnnn6puCmOMMfZK4Gu6GWOMMQ323XffoUuXLjA3N0dKSgoWL1783KHjjDHGGKs7XHQzxhhjGiwnJwdffPEF7t27Bzs7O0ydOhVhYWGqbhZjjDH2yuDh5YwxxhhjjDHGWD3hidQYY4wxxhhjjLF6wkU3Y4wxxhhjjDFWT7joZowxxhhjjDHG6gkX3YwxxhhjjDHGWD3hopsxxhhjjDHGGKsnXHQzxhhjjDHGGGP1hItuxhhjjDHGGGOsnnDRzRhjjDHGGGOM1RMuuhljjDHGGGOMsXryf4cbLH77E0P3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(*zip(*durations_seconds_median.items()), marker='o', linestyle='-')\n",
    "plt.title('Median time of processing a short text with different versions of the Markdown package for TeX')\n",
    "plt.xlabel('Package version')\n",
    "plt.ylabel('Median processing time (seconds)')\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d67d554-3ed1-480a-b464-7682776b8301",
   "metadata": {},
   "source": [
    "The results show a more than 5× slow-down in [version 3.4.3][1] of the Markdown package for TeX.\n",
    "\n",
    " [1]: https://github.com/Witiko/markdown/releases/tag/3.4.3"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}