manual_benchmarks/cpu_gpu_benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RADIS: GPU vs CPU Performance Comparison with examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is meant to provide users with examples on how to compute spectra using RADIS with the assistance of GPUs. It will also serve as comparison tests between the performance difference witnessed between the CPU and GPU comparisons."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our first example, where we use a very small part of the CDSD-4000 dataset to show how the GPU computation calls are made, we will observe that the GPU computes the spectra around **4 times** faster than the CPU. While this is significant, it is still not pushing the GPU in terms of its computation power. As the dataset increases, we see the contrast between the GPU and CPU performance become more evident.\n",
    "\n",
    "In our second example, where we load ~ 5M lines from the CDSD-4000 dataset, we will observe a significant difference in the time taken by the two methods to compute the spectra, with the GPU outperforming the CPU by a very significant margin (**~0.5 seconds on GPU vs 5.42 seconds on CPU**)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us first import some necessary modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import radis\n",
    "from radis import plot_diff\n",
    "from radis import SpectrumFactory\n",
    "from radis.test.utils import getTestFile\n",
    "from radis import calc_spectrum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing spectra using the RADIS test file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is primarily meant as an example to show the contrast between the non-GPU and GPU methods.\n",
    "\n",
    "First we define the SpectrumFactory object as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 1000\n",
    "p = 0.1\n",
    "wstep = 0.001\n",
    "wmin = 2284.0  # cm-1\n",
    "wmax = 2285.0  # cm-1\n",
    "sf = SpectrumFactory(\n",
    "        wavenum_min=wmin,\n",
    "        wavenum_max=wmax,\n",
    "        mole_fraction=0.01,\n",
    "        path_length=1,  # doesnt change anything\n",
    "        wstep=wstep,\n",
    "        pressure=p,\n",
    "        isotope=\"1\",\n",
    "        cutoff=0,\n",
    "        chunksize=\"DLM\",\n",
    "        warnings={\n",
    "            \"MissingSelfBroadeningWarning\": \"ignore\",\n",
    "            \"NegativeEnergiesWarning\": \"ignore\",\n",
    "            \"HighTemperatureWarning\": \"ignore\",\n",
    "            \"GaussianBroadeningWarning\": \"ignore\",\n",
    "        },\n",
    "        verbose=0  # do not produce any output while calculating spectra\n",
    ")\n",
    "sf._broadening_method = \"fft\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the data in memory, for this case we're using a CDSD-4000 fragment as an example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirpath = getTestFile(\"cdsd_hitemp_09_fragment.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "sf.load_databank(path=dirpath, format=\"cdsd-4000\", parfuncfmt=\"hapi\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute the spectrum on RADIS CPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_cpu = sf.eq_spectrum(Tgas=T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7ff3b0e0cc88>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_cpu.plot('absorbance')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "### Now let us compute the same spectra on RADIS GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_gpu = sf.eq_spectrum_gpu(Tgas=T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7ff3b0d00748>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_gpu.plot('absorbance')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now look at the calculation times for the two spectras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spectrum computed on CPU in 0.04 ms. Number of lines = 2284\n",
      "Spectrum computed on GPU in 0.01 ms. Number of lines = 2284\n"
     ]
    }
   ],
   "source": [
    "print(\"Spectrum computed on CPU in {0} ms. Number of lines = {1}\".format(s_cpu.get_conditions()['calculation_time'], s_cpu.get_conditions()['lines_calculated']))\n",
    "print(\"Spectrum computed on GPU in {0} ms. Number of lines = {1}\".format(s_gpu.get_conditions()['calculation_time'], s_gpu.get_conditions()['lines_calculated']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now compare the results of the two spectras:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 2 Axes>,\n",
       " [<matplotlib.axes._subplots.AxesSubplot at 0x7ff3b0d220b8>,\n",
       "  <matplotlib.axes._subplots.AxesSubplot at 0x7ff3b0c6a908>])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_cpu.name = \"CPU spectrum\"\n",
    "s_gpu.name = \"GPU spectrum\"\n",
    "plot_diff(s_cpu, s_gpu, var='absorbance')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "--------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A larger spectra: 2300-2400 cm-1 with 5M lines!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now look at a larger example with around 5M lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 1000\n",
    "p = 0.1\n",
    "wstep = 0.001\n",
    "wmin = 2300.0  # cm-1\n",
    "wmax = 2400.0  # cm-1\n",
    "sf = SpectrumFactory(\n",
    "        wavenum_min=wmin,\n",
    "        wavenum_max=wmax,\n",
    "        mole_fraction=0.01,\n",
    "        path_length=1,  # doesnt change anything\n",
    "        wstep=wstep,\n",
    "        cutoff=0,\n",
    "        pressure=p,\n",
    "        isotope=\"1,2,3\",\n",
    "        chunksize=\"DLM\",\n",
    "        warnings={\n",
    "            \"MissingSelfBroadeningWarning\": \"ignore\",\n",
    "            \"NegativeEnergiesWarning\": \"ignore\",\n",
    "            \"HighTemperatureWarning\": \"ignore\",\n",
    "            \"GaussianBroadeningWarning\": \"ignore\",\n",
    "        },\n",
    "        verbose=0\n",
    ")\n",
    "sf._broadening_method = \"fft\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirpath = '/home/pankaj/radis-lab/par-2300-2400/*'\n",
    "sf.load_databank(path=dirpath, format=\"cdsd-4000\", parfuncfmt=\"hapi\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>iso</th>\n",
       "      <th>wav</th>\n",
       "      <th>int</th>\n",
       "      <th>A</th>\n",
       "      <th>airbrd</th>\n",
       "      <th>selbrd</th>\n",
       "      <th>El</th>\n",
       "      <th>Tdpair</th>\n",
       "      <th>Pshft</th>\n",
       "      <th>...</th>\n",
       "      <th>polyu</th>\n",
       "      <th>wangu</th>\n",
       "      <th>ranku</th>\n",
       "      <th>polyl</th>\n",
       "      <th>wangl</th>\n",
       "      <th>rankl</th>\n",
       "      <th>branch</th>\n",
       "      <th>jl</th>\n",
       "      <th>Ia</th>\n",
       "      <th>molar_mass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2330.0000</td>\n",
       "      <td>1.110000e-82</td>\n",
       "      <td>0.4850</td>\n",
       "      <td>0.0446</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>29897.7097</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>267</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "      <td>1</td>\n",
       "      <td>175</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2330.0000</td>\n",
       "      <td>1.460000e-71</td>\n",
       "      <td>0.0975</td>\n",
       "      <td>0.0573</td>\n",
       "      <td>0.0639</td>\n",
       "      <td>24199.1858</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>420</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>262</td>\n",
       "      <td>1</td>\n",
       "      <td>107</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2330.0000</td>\n",
       "      <td>1.010000e-77</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>0.0690</td>\n",
       "      <td>0.0899</td>\n",
       "      <td>27482.8406</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-0.003147</td>\n",
       "      <td>...</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>922</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>622</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2330.0000</td>\n",
       "      <td>2.560000e-72</td>\n",
       "      <td>0.5220</td>\n",
       "      <td>0.0687</td>\n",
       "      <td>0.0768</td>\n",
       "      <td>24764.9686</td>\n",
       "      <td>0.72</td>\n",
       "      <td>-0.000200</td>\n",
       "      <td>...</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>463</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>265</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2330.0000</td>\n",
       "      <td>4.010000e-73</td>\n",
       "      <td>0.1340</td>\n",
       "      <td>0.0642</td>\n",
       "      <td>0.0633</td>\n",
       "      <td>24957.2457</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.005093</td>\n",
       "      <td>...</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>733</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>553</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4878704</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2389.9997</td>\n",
       "      <td>9.930000e-78</td>\n",
       "      <td>0.3730</td>\n",
       "      <td>0.0496</td>\n",
       "      <td>0.0674</td>\n",
       "      <td>27433.4246</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>585</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>406</td>\n",
       "      <td>1</td>\n",
       "      <td>135</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4878705</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2389.9998</td>\n",
       "      <td>1.200000e-63</td>\n",
       "      <td>0.1310</td>\n",
       "      <td>0.0692</td>\n",
       "      <td>0.0906</td>\n",
       "      <td>20286.3902</td>\n",
       "      <td>0.69</td>\n",
       "      <td>-0.002130</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>446</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>240</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4878706</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2389.9998</td>\n",
       "      <td>3.660000e-49</td>\n",
       "      <td>0.3680</td>\n",
       "      <td>0.0687</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>13689.6194</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-0.001324</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>198</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>118</td>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4878707</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2389.9998</td>\n",
       "      <td>9.750000e-62</td>\n",
       "      <td>0.3110</td>\n",
       "      <td>0.0653</td>\n",
       "      <td>0.0639</td>\n",
       "      <td>19716.7387</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>324</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>186</td>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4878708</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2389.9998</td>\n",
       "      <td>2.450000e-47</td>\n",
       "      <td>0.0488</td>\n",
       "      <td>0.0908</td>\n",
       "      <td>0.1173</td>\n",
       "      <td>11916.8385</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-0.001868</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.984204</td>\n",
       "      <td>43.98983</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4878709 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  iso        wav           int       A  airbrd  selbrd          El  \\\n",
       "0         2    1  2330.0000  1.110000e-82  0.4850  0.0446  0.0689  29897.7097   \n",
       "1         2    1  2330.0000  1.460000e-71  0.0975  0.0573  0.0639  24199.1858   \n",
       "2         2    1  2330.0000  1.010000e-77  1.7100  0.0690  0.0899  27482.8406   \n",
       "3         2    1  2330.0000  2.560000e-72  0.5220  0.0687  0.0768  24764.9686   \n",
       "4         2    1  2330.0000  4.010000e-73  0.1340  0.0642  0.0633  24957.2457   \n",
       "...      ..  ...        ...           ...     ...     ...     ...         ...   \n",
       "4878704   2    1  2389.9997  9.930000e-78  0.3730  0.0496  0.0674  27433.4246   \n",
       "4878705   2    1  2389.9998  1.200000e-63  0.1310  0.0692  0.0906  20286.3902   \n",
       "4878706   2    1  2389.9998  3.660000e-49  0.3680  0.0687  0.0814  13689.6194   \n",
       "4878707   2    1  2389.9998  9.750000e-62  0.3110  0.0653  0.0639  19716.7387   \n",
       "4878708   2    1  2389.9998  2.450000e-47  0.0488  0.0908  0.1173  11916.8385   \n",
       "\n",
       "         Tdpair     Pshft  ...  polyu  wangu  ranku  polyl  wangl  rankl  \\\n",
       "0          0.56  0.000000  ...     30      1    267     27      1    152   \n",
       "1          0.63  0.000000  ...     32      1    420     29      1    262   \n",
       "2          0.68 -0.003147  ...     43      2    922     40      2    622   \n",
       "3          0.72 -0.000200  ...     39      1    463     36      1    265   \n",
       "4          0.69  0.005093  ...     34      1    733     31      1    553   \n",
       "...         ...       ...  ...    ...    ...    ...    ...    ...    ...   \n",
       "4878704    0.57  0.000000  ...     32      1    585     29      1    406   \n",
       "4878705    0.69 -0.002130  ...     32      1    446     29      2    240   \n",
       "4878706    0.71 -0.001324  ...     21      1    198     18      1    118   \n",
       "4878707    0.70  0.000000  ...     28      1    324     25      1    186   \n",
       "4878708    0.74 -0.001868  ...     22      1     22     19      2      4   \n",
       "\n",
       "         branch   jl        Ia  molar_mass  \n",
       "0             1  175  0.984204    43.98983  \n",
       "1             1  107  0.984204    43.98983  \n",
       "2             1   35  0.984204    43.98983  \n",
       "3             1   54  0.984204    43.98983  \n",
       "4             1   85  0.984204    43.98983  \n",
       "...         ...  ...       ...         ...  \n",
       "4878704       1  135  0.984204    43.98983  \n",
       "4878705       0   38  0.984204    43.98983  \n",
       "4878706       1   48  0.984204    43.98983  \n",
       "4878707       1   81  0.984204    43.98983  \n",
       "4878708       0    4  0.984204    43.98983  \n",
       "\n",
       "[4878709 rows x 31 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sf.df0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that now we're working on almost 5M lines."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute the CPU spectrum like normal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pankaj/radis/radis/misc/warning.py:242: MemoryUsageWarning: Line database is large: 1210 Mb. Consider using save_memory option, if you don't need to reuse this factory to calculate new spectra\n",
      "  warnings.warn(WarningType(message))\n"
     ]
    }
   ],
   "source": [
    "s_cpu = sf.eq_spectrum(Tgas=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7ff3b027ddd8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_cpu.plot('absorbance')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute the GPU spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_gpu = sf.eq_spectrum_gpu(Tgas=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7ff3b01796a0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_gpu.plot('absorbance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_cpu.name = \"CPU spectrum\"\n",
    "s_gpu.name = \"GPU spectrum\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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QVApX748DjzwQEdvJfPrCB9+cgAXLFiAJk2aBAYHghmLIwgdHPvss48IW1566aW2QtISAJ0KY6Q37+9//7vQN+SgDZlXR/i1g0uGexkKZgh/586d4jsMh7/00ktgnh7zMf2OIABIm9mJaMt9ReEBZJicxUTqkOFht78VupyPbm+I3/UU1edyCQDzzfZRzaHu7ei2e1R8UPAAyPAYb+IEtsceeyxtD3os6LmgGDAfxk6DAMj8KlnVKD8nq0EJl3woBx1RTnCu5gBaH7ZBbSg/zzkgfBBaCCVeXl23/XgVgTh9l94yikc3bNhQFGq4DeaZMWzPQoOgLw8EMIa76dHmdhiC5GB4mJ4+FnvIIc/FCZ4kADKXjwUNKgAyDMzrw/EGsttuIgcvWwDo1S3FDQD5Xb7seeUA2oGcBMCgf8t0Lefi93RLYmTbJrkEgPlm+2zPdab70233KPnA7hwLJgQsK0SZp0TvnxysgGTokfIUDPE6DSabM6/p6KOPLvYR5tzR+8LqQz74gw7dE6zbRR30fHV+nmFkwiTP2ctTxONg0j4Fo2vVqlVCBiVTAJQ5eswP5NpyG5QuIXwR3sIUwdATRw82w7VMVeBLDcOzVgBk+kLLli1LHJJdCPjcc88V0i8EwDvuuMPXtLECm9dZ27ZtMWPGDF/f4YeCeAC9AJCV2cwRHDlypKjSVgc9/xdccIEBQN8zE+yD+XavySUAzDfbB1t58X1at91180HBAGDXrl0F4DFfSU3a59JhdR8LEJhfFXRQ2oI5gExs5w0j6NA9wbpb1QQ9X92fZz4nQ/R2RRLWfUvIYd4b89/UkSkAMizLfDF6Y5liULduXcdTpreO3j9Vg87LPlxn/DzXnHXItcg0B0qjWAGQOYsETuuwKwKRItlOgtY8P3rT+F2ZI0g78uWKeXDMh7MO/o5heobU6fmUg9cet8d/HPRuEp4Z2pbyOnI+vABw3LhxQprFrkqaRSs8f+MB9Fplmf093+41uQSA+Wb7zFZg9r+l2+66+aBgAJAaZsxvoreFSfzqYLiO+XwMGzKnyc+gp4WdJviwpf6X1dvgZxv8jO4J1u2i9nue2focL0gWg7z88suureAeeOABUS1rlXGxQpNdMYHXuchcOAIeixbsvHtcb1yTTEeg99nvoAQJAYowRUBSB4+VOYhWfT4JT3zxoXSN2m/YSQaGHm9VBkaKS8v9Pf7447jooovwwgsviGIUCW4EQubDskLZqis4ePBgoaXHNApK0shB6RmmaLCwSubW8pqkd51zyeEXANl+j4BH2RrK18jBHFnCOGVbDAD6XW3BPpdv95pcAsB8s32wlRffp3XbXTcfFAwAMszHkB8BQc2P4tJhT1iGAtWODm5LiiEuhtPYBowPXHoc3KowKTLLf3aDDyU7yYyolrRuF3VUxxnldnjO7NJBWOJc0evEogZ6lijj8tBDD4kQJUGNOXTqCwE9cryopfAww/oMg3Kw+MPPIOAQWKjJyCIjeqPq1asn1gvD1CziYFiVXjC1U4efbfOcqHfIhxPDnIQ02fmE3SiYzsDcQ6nnp8ITK97p5aaUCqvWme9HmHQSgl66dKkAMK5tVs7znKgxybXPFx6GjulxUwc97DxnvmjxHOXPtDO7d9AzyVCxOjhHBEbCIdMpCLJ8uaL+Hl/ICIZyPpjCwa4lLMah/Ip1EPSoMUgIpbevW7duonKbx8+qfYaoaTvOv9yGFMyWQtC0C3P+KleujEz/5mcu8+0z+XavySUAzDfb58q1odvuBgAjWgkSAAkBVr05VmxS68wvAPKQ+NAlNDJBng9bekL4wLAbMjHd7m+ED0KBLFiQLmWGw3isfPjyoSZ/5n/5//Ti8LPyZz7k+B1CBgFG/swHNoGXoTTminE4/czv8rzoseL25c88Bm6TduNxyp+5Xe6X/+Xf5M/8vuoaj/qcJEx7nRMlO+hhYwEP55bHQakcVrtefPHFQtTXek78Hb1IdoO29DtPhCpWJLMqlrJBBAnaiWuEXjLun3Al58nvOfGGQ4CkZ5EhZp4X54dhV0ISoYz5h+o8yXPi93gczFfldzno2WPOHKHKbp4IswQ3elS5LxarEKa57gmwXDPWtff9998LMCTUSU8lc2fpKSfgWdchX4CYv0i7c31z+zwmHjfD+XbedRZkEebs1h7Bm6kALOyivQjf7FhCjT6G/eWg55VzxOItimirg9IurIImrKpFY/wM/8Z90ANq/R7D/5xvjny7nrzOibbmWsyle4TbOfGFR+0FzOuf94sk3vd43dB7Lq+tQlt7cT2feM/kS6r6zPV7L/e6nrhNRm10OogKxgPIt3sCgZ1YqwwByxBUEOZkmIlvivQyqT1L1W3E6QHkvnkzMCO7FkiS3f2GT7NrIX17S5Lt9Z1l8racb3bPpVZw+Wb75K1u+yPSbXfjAYxoJXTp0kXIY9gVgch8JHo4Mhn04jG8lEkRie4J1u2izsRehfCdJNm90AAwSbYvhLUuzzHf7J5LAJhvts+V60a33XXzQcF4AIuKikTBhpMMDDskEBCdBnOGOBnWZHh+nmE9eg+5GIIO3RPM0IA15zHoMZrPB7dAkuxeaACYJNsHXzm5+42k2Z05pLJIib2ag45cAsCk2T6orXP187rtrpsPCgYAt2zZIjTiKPdhJwTN/KhmzZql1yHz8pjbJ4s7mEDPHKL777+/2Fpdv3690AZkDhVzAoMO3ROs20Ud9HwL5fNJsLssYLAWUPCFJZ9fCpJg+0JZ5+p5JsnuzEtloRNzcXkf//rrr9PV71JyyKv3eC4BYJJsX0hrX7fddfNBwQAgFyW9gJT+kK3gCG/s/kEPier9I8hR/4xJ6Oy2wEEApI4g8/zoLSQYrlmzRiSCM+mbAEl5iaBD9wTrdlEHPd9C+XwS7M41a1dlnO8ty5Jg+0JZ5+p5Jsnu9Py1a9kS8wCw7GdaSuuTL/adzjgDlTZuRMcHHxTFWBx8FrCqnl1tqKfJvOlcAsAk2b6Q1r5uu+vmg4ICQC5MQhyrGvlGyOod3gB44asyLpSQYL/R9u3bp3uaspqREhxsu8WqHFZbUUaCEjKsMGQhSSZD9wTrdlFncs5J+A5lQShczLQAglLUw9g9aov6356xvX9bRfnJJNmdqT5XdegASvtXBzB26lTRBYbXe5OiInRgBxogLT4ue1/THpQq4udY3HfBsmUYYPlslDaLaltJsn1U55QL29Ftd918UHAAmLRFpXuCCaqym0LSzj2u46EY8jHHHJPePUWIraLKfo+NMjxs6cYK8yFDhqS3a+zu14LRf87YPnqb+tlikuzuBIDs+jThm2/Q1gJ1lK4qDeB3QKT6UC0il3QAk2R7P2slXz6j2+66+cAAYMwrUfcE63ZRx2y+jHZPgWLCmhwU/qVMUCaDWnMyd5TiwQyvcljtTmHqiRMnCi8E0w3suoPI9nHU9LMTOc7k+ArxO2bNxzPrSbJ7JgDIRoQ3A7jDAwCpwckoElsh8l4Spo93VDOVJNtHdU65sB3ddtfNBwYAY15luieYHiqvZOeYTaBt96tXrxZdPygwzB697E5BsVSG/pkC4ASAbjd0/o1w1qBBA6H9yLxSdsxwGyzCYBW5HBQdp7AyO3LYDSavM79U7eYRxEiEUBY6Mb+VKQpJHxRVZnoFATqKcHwhr/k45zpJds8UAJkz2MEFAFlcorZStBYPxmX/JNk+LhvEsV/ddtfNBwYA41g1yj51T7BuF3XM5rPdPRX72cGB/WrPOeccAWoM+TJnk1qN7C7x4osvpr/LTi1sPybHN998I35kuIhDth/jz1u3bhU9ZtlmjBC5//7747ctW3A2gOmA+J21jdzy5ctF9XkVAJtTxUhdu3YV0kHsykGPAvtUy/1xP8wrZU/foINeREpe/LppE77efXeRr+q3hV3QfUX1eXZqYc6tU4/eoPspxDUf1EY6Pp8ku+sCQKaLqC9mffr0SeeJ67Cp320myfZ+jzkfPqfb7rr5wABgzKtQ9wTrdlHHbL4Su2dZPqu6CWn33HOPaD9mHQzbzBgyBD8DWAOIXr/8nXVIT+Crr74qtqkOeuhY+MMkYOYT0b8nk8ql7h6hknD5yiuvoEXTpmAjvhoAhhYViVZqHPw7vV/0gnF/hwH4FEDLVq1EP1zrINyyeIUeSLY4sw56OtmqjOEsHvHJGYJkNuc1agAstDWfzbly21esdp89G2jaFNhzT3GIugGwBwCqxl6UEACM1fZJWYAxHIduu+vmAwOAMSwadZe6J1i3izpm85XY/dVXXy360LZu3Vr0orUbhL3ZQ4bgTgAnZQiA3C6TxAmaRwDY6AGArZo2xU4ADQD0cwFAghsfLj84AGCLFi2E95JhKMoP1ahBpPxrsHcvQ6ncTnsAhw0ahLvuuitp01TseKIGwEJb80mZ3LjsvnLlSjRs1AiLW7fGP2bOFC9S06dPx4COHfGFpQrYrQiE14xXCFh6AOV1ukdCADAu2ydl7cV1HLrtrpsPDADGtXJS+9U9wbrfUGI2X7HdM7xLIGIT7QULFoiwohsAvpGCtsmTJ6N3794lPurmAeSHWdBBTckDAHwXIQAOBbDBAQB5TFSmvIr7q1VLPOzo9WNeIkO/FCRngroEwP/stZfIfZRj586d+Oc//ymOm99jC8PzzjtP/I5r0W4wZ5HQvGTJElBcmiFlJsBfd911qF27tu13CKeU2uE8UHuNuZeU2mBeIqWXZGcGt3xL6UHlZ9nVQQ56XendpSbnpk2bQK9v9erV0aFDh2Kwq3puJWTKbchty/8vXbq08OZycFvvv/8+rr/+ejz55JPinJlCcMstt6Bp06bic/yZ+aWbN29GnTp1xP+3bNkySZdD1o8lrntNlSpVsPm773AdgBZvvCHyXlUAPBTAndOmoVOnTiLNwqkKOAwA/v7773j22WdRtWpVcW1ke8Rl+2yfZ9L2p9vuuvnAAGDMK0r3BOteoDGbr9juWWXLaluKuDK/jg91PwDoVAXsBYAUC3/jjTdE2Ja1v24h4CAeQC8ApFejFjXMypfH1KlTBZwQ8vizgL9du9IAWOXyy0V+o8wvZJ4dP8/cJRbDsDhlxIgRIpeRoEchXHXQm8owOsPdzEmkd/Htt9/GoEGDBBhRF9P6wKPntXPnziIUTe8j98c+2w888IAAKkru0JPCwXxLgiU1N+lRVYtlKMfBf99//z34gJXnwPA58zl79eolzpX5nsx1pH4nAZf5lsy7VAGQLwU//PCDyLnkMVkBkJBKrU+2euRxn3jiiWjevLnIS1y3bp14QeD3aaMnnngCxx13nPgb98nj4N+4z0aNGiXpksjqscR1r+F1SngjAK5PvTg5ASBfXiZ++62tDIwVAO2EoJ08gNdccw3uvvtuYW966PlSlc0Rl+2zeY5J3Jduu+vmAwOAMa8q3RPMB2QSZAqyYWbZ+aJu3brioe00ZAhYegC9AJAenpdeekl4huRgqJW/ZxJwcwBzswiALFdh/TDBirmI6mCXGhaVWEPAcg2wQIX5UepgUQwh0FqEQTA77bTTBBzS00YYk+Odd94REETvC/9GmOTgz/Xr1wdDIxs2bBAwpQ4W5RCUWEwjh98QsDwHenJ4jnLwgUsxd4YCOdx6HzPnktXXVgDk95iHyXaRHARFPtTloLeRoMe8S64z9W+TJk0SEMq/T5kyJRtLPZH7iOtekwQAVO+xfDlhrm42R1y2z+Y5JnFfuu2umw8MAMa8qiKf4F9+AX79NX1Wut9QQptvjz2AcuVCb4YboMeGrfvoSSK8OI2gAMjtyJxChhsp+kxPI+GLUHTdjh0YnkUA7A/gAXoBa9USoUp1UJaCkOUEgHahcXqvCHIMba5atQrHHnus2CRDmmypRThkeyzrYLiZEjgsYpEtta688krRL7tLly7C22cdDD3Te0iPnRxBAfD1118XrRqdhvTM2hXv+AVAegRpEzkIvNIu1r/RZvSQ0vvHtVGoI657TdIAkPNPMMjmiMv22TzHJO5Lt90j5xxqRyoAACAASURBVAOLEQ0AxryqIp/gatWoRRLzWQXYPY/3SzZsCj/8ACCFm1lI8fuvv6I8IAoznN7YrZ5T5rHxgqd3q1q1akJehnp+7Zcvx+AsAiArjttxf7vtJkCUxyFbEToVgchzoUwN85RY+UzPGWGM4c2aNWti48aNuPfee8FCGsIg8wPpyWA1cqtWrUpMULdu3QTk8fvMo+RgTuAHH3yQ3o6fWQ0KgFYAs+4jLADKThDqdqmtyPxSu7/R68nQOf+u5ir6Ofd8+ozuh6GwFQXce/Xi20/adEkBwGcBkZ/7UAoACYEMRe++++5o27at1khMVmyfT4s1onPRbffI+cAAYEQzH9FmIp9giwdQt4s6tBki9ADKEDBDsyxCsBsEGoYAXxk7FgMBdEt9yO6NXUITQ7xUDfzwww+FqDbB6IADWPoBnHLKKWizZEkxAGROHL1PN9xww5/7euUVOOUA8jOEKIKDfJB55QDSt0DdwQW7716scIFFEIRgFlo4eQAJdosXL8Zlp5+O9SloZdurs88+W3jzpCQOIUvqBxKQ7cTEmVdHYVzuc+5cBsH/hGmGxdlzm3mAfkZQACSAu6U1hA0BM2xNkFaHDA+7/Y0pAvxcoQ7d9xpe00fVrYvVp56K+q+/nl6TXgCo9gL2kwPYvkIFkUMcJAdQHgPvOnVTAMhCJb5gcTD/lS9ruoZu2+s67lzfrm67R84HBgCTteR0T7DuN5QkWVMWgZQpU0b08mQxiN0YO3Ys5gwdilsAyDphNwCcw3CoQ1jHDgDpLWNxBPPEmEtGr2PrZs1sZWD4Gf6dIcYgAMgcwNfOPBP0wjGsytAuCyXobSDkOQEg4Yn5cmtGjwbPi4Ur9NgxhEsAHDx4MGgfFQBZ3SjDn3b2ZP4fPaLZAkCv8JqbB5C5fzfffLNrDqAdyEkADPq3JF0fuo9F972GVeTvbdiA8Ux/eOklkerAEQQAvaqA59O7HhEAWl9SvNZtmPnRbfswx5bP39Vtd918YELAMa9O3ROse4HGbL5iu1dlYNwq8XQD4BVXXCHe+OmRIzy5ASCrX5lXyFy7oAC4qGlTEYLmoBwJqxBZBcyxARB5iVIHUD6MWC1MeRYrANKL5xQC5rExbO5n0PvKvMT77rsPV11FsRrvEdQD6PUgpfwPt0m70xuqDtmT2a0IJCjkucGh99nnzyd032vk9UEAfKRhQ1GN7gcAg8jAEADbp1rBhfUAGgDMn7XtdCa617xuPjAAGPMa1T3Bul3UMZuvxO4pWUL4IATQK2Y3ZBFIFB5Aao61Xry4WAiYMiHdu3cXuXaUP+Fx2HkAZS5h//79heacXwBkjhFD0lsVAJTnyeNhiJc1svxnBUD+jeFaFQBZBc3CGWsRCAtfZs+enQ5lW23J3Dd6O1kkIsO9Uoibnkm24rMOekY5P6yqlVXV7NXMCmS1Cpk3VsrMsBBDhp/lA9ULAFnpzG4phG9CuDroNWKhjAHA6K9c3feabAMgr4kLli0DewlJiSerDEyZVP6rXQg4mwCo2/bRr5b82KJuu+vmAwOAMa9D3ROs+w0lZvOV2L3aCs6pelUCIDtuXJraQqYhYAJXq8WLMUR5SFCLjnCzZcsWjB8/Xggg2+UA8m/MuaPHjPp68iEyjHpmLVsK+LIOfuZiAK8yDGYDgPRaUGZlKaVMABw6cKDwDMqH0UUXXSQEn1UAHDhwoBBWZuiUFbZyMCTM82Pe1Pr164XYtDouvfRSketHQWmZE8liCcrTcDC0LEPD/H8CJrdHL6Qq08Nqara2+/vf/y56InPI/CnmYrH4hsMvABKmWbU8dOhQ4e2Ugzp/LNTgcRgAjP7Kjepew+uHhUeUGeK1I0ccANhp2TKRK5wpAPJ7HEzJ8HpxCTMjUdk+zDEU4nd12103HxgAjHnV6p5g3Qs0ZvPZ7p4PEIoFs7iCOnb8mVWylSpVEqLC7Hrx8vTp2Jb6NoWD6TGSg+LEHFJ4+DH2/AQE0KmN4PkZ5gC2XrKkGADy93yAde3aVVQNM7w6/4UX8AGAcwGcN3Cg+D29YAwVyy4kQQDwUUCAGTX9Dj74YHFsjz76qGiDJx849H1ZAbBHjx5CvLjCW2+JakXKPjNn0kkIesKECaC0CwGNdqPGIu1TVFSExx57TIhPd+zYsdg8UAiaeoSsjCVsH3300UL2haF3FsQQMlXBZBaS8DogGFJvkTam7VhQQpilTA0LTuR8sJKZg0DKz1gHgZrzTc8hJWm4BgipLLihrZ5++mmRn0n4ltv47rvvRAEHhaB5LARRbpt/z/RvSbw2dB5TVPcaFiQxtaFcuXLiJeKQQw4Rhx0FAPopAumQCgHTA+gGgD157aRawTl5AKnSuQPAPwwA6lx6sW07qjXvdAK6+cAAYGxL588d655g3b0KYzaf6+6ZI/Twww+LfDACCMGQ3iQWh/yxeTP+CeAyAFYhaKcKU6tQsgRAaxUwf0+7EygIePTkMb9u95QnoMqBB+L8889H37590/It6gOOHsD3XFrBfZvqF7x0331FRTKBjN012DKNMMtCDnocCIDVU72A5TmxUKRZs2ZY8eqr+B3Af1Mah/RGyget1aj0BLKYhV1PGJalV+/444/HkCFDhNfObtBjSO8bgY/QTXgjLNM7xzxB62AYmEBGbyCLSujJZKiY8jSyqtf6Hc4tK7+tg7YnOA4bNkyAHAGXEMj8SIaFWZktB4WbKeBMD6y18peFMdQ4zPRvSb42dBxbVPca9fpTJYZyEQClGqD0IPJFhsVqLNaieLhTt6Kg8xOV7YPut9A/r9vuuvnAAGDMK1j3BOt+Q4nZfCV2zzALk//5pi9DkdYPBRGC5g2cnsJ9AlQBc3+q3d1kYNRjUz2AbgDIY7oZwMImTcS5qkPVAbQDQNqHoXFrEQhBK19Goa35pMxbVHZXAVD1zvsBwHWp1IkoWsF5eQCZQrKHhwfQCoCyAp1zRo84X9aiGFHZPopjKaRt6La7bj4wABjzatU9wdRkYyilUMZ1110nPE98w6ZXid0q4gBA1e5BAdCPDqAfAGxvUwRSCABYaGs+Kdd2VHYn6DF0ShXJmkp6RhAApKd3UKdO+JxpEMyHnTYNbCEYZQg4EwDUVRgSle2TspZy5Th02103HxgAjHml6Z5g3S7qmM1XYvfqDZY5aAy9xgGAqt1zEQBpN4ap2bOXfXcZ/s6VUWhrPinzEpXdJejRN7bRBgDvB/CwhwyMCoDMILz7mWdErmpQAPSqAg7qAdQFgFHZPilrKVeOQ7fddfOBAcCYV5ruCdbtoo7ZfLYAeBAlUhiGdQjbJj0E7McDyCw2VQdQGsLaCq7K5ZeLile1gIIe0o/uu6+YELQ1BEz9PCmjs8ceewitwlwZhbbmkzIvUdldNwAWffst2iiVvbSf3Oc85s6G0AGk/ibrlqU8iDUErAsAo7J9UtZSrhyHbrvr5gMDgDGvNN0TrNtFHbP5bAGQN91nAFwQEQBuZ8VpwBxA1e5uQtDqCfjVAeT5+QXA/+y1l6iuVQcrW0/bts0VAHU9qLKxXgptzWfDpn72EZXd4wbAMK3g4gLAqGzvZ57NZ/6ygG676+YDA4Axr2bdE0zNM+bDFcqQDw+qyZ0QIwCqdrcCYP9Jk9CnTx9HeI3SAyiFoNWd+SkCyWUALLQ1n5RrOyq76wbAid9+i7YOHsCwreD8AOCDAH4GcGWE0jBR2T4paylXjkO33XXzgQHAmFea7gnW7aKO2XyOEOUGgLIV3Buph4BVBkZuVD6IMvEAqnZXAbA+gP5FRUKb0Dp0eAALEQALbc0n5RqMyu5RA2CQIpCwAPgegLoeIWBrWJjzR3klyhVRAimTEZXtM9l3IX9Ht91184EBwJhXr+4JZu4Wde9yfbAjBHXnqHlHPTcn2RI/HsAoAdCuFRxtrdo9LgBUZWAKyQOYL2s+167ZqOzuBYBhegF7FYEE7QXs1QrOLgfQ+jsK1lPPkmLs1Cy108n0WgtR2d5rP+bvxS2g2+66+cAAYMwrWvcE63ZRZ8t8t9xyi+jkwEERYnrt7IYOAHTTAbRrBcfjUu3OKuCWTZuKsI8fD6CXELTMAXzDRgeQ7c7Yhs4qBF1IAJgvaz5b11ZU+4nK7lEAoLUK+C6fMjBxAKCabmEnNu9nfqKyvZ99mc/8ZQHddtfNBwYAY1jNfGuQVZVsrcUuFbqGbhe1ruO2btdvTpofAIyyCtgJAK1C0BIAGwDo5xEC9uoFHAQAZSs4HQDIc5w3b57o2UroTMrIlzWfFHv6PY6o7K4DAP3KwMQNgLR1Jj2Do7K937k2n/vTArrtbgAwD1faqFGj0u2o2J/WWqUZ5SnrdlFHeaxu28o1AFTtrnoAowJAJyFoqwcwDACyGKWhSzW17NnKdnQfffQRDjjggGwtB9f95MuaT4QxAxxEVHbPFQBkL+DSvXtj8uTJaRmZTHIA/d7b3KYiKtsHmG7zUUuqjw6DGADUYdWYt5lNDyB7v0bVbzJOs/EmeR+A3gCYJu30lpwUD6Bq91wFQGopUv5G9jFV55/yB+XLl0//in13x4wZE+cSSe87X9Z8IowZ4CCisnsYAJSt4DIVglY9gGwF5yYETQAsE7AVnDw3mlVeV1EAYFS2DzDd5qMAdNvdAGCeLzPdE6zbRZ2t6eFNkhILtR2ARB5HUgAwrl7AUeYAugHgzp07UbFixfT0M4n94YcfztZycN1Pvqz5RBgzwEFEZXd5DQ8B8GHATiBhAVAVgvbqBZwkAIzK9gGm23zUhIDNGghrAd0A+Ouvv4KdHJI82L3ivffeA7tPUArBbiQVAE855RS0WbIEbFulespUu2ezFZwBQCAX1nySr8dMjy0qu+cKANr1AvajA2hXGbwcwDS2rMswBzAq22c694X6Pd12180Hpggk5pWre4J1u6jDmu/LL7/EUUcdhZ9++kn06nzmGfbwKDmCAuBbrBaOUQhatbuOTiBOOYBqK7iwMjC56gFM+poPe80k9ftB7f7vf/8bU6dORefOnXHuueemT8srBMxewI80aoS33uJV/lcbt+sArG/VCrNmzYJTCLhq1aoo2rzZUQja6gEM2gs4UwAkFK4DUC9DAAxq+6SuoVw7Lt12180HBgBjXnG6JzjpoQF2xJgyZUp6Ftxy+4KEgOMGQCchaBaBRNEJxA8AtgcQRgg6VwEw6Ws+5luOtt0HsfvWrVux7777po+F/88WhSrQ0au+MWAIWAIgXySvveACfAbgbwDueeYZ8YLpBwBlKzivHMAoPYBhATCI7bUtgALcsG676+YDA4AxL1rdE6zbRR3WfOeccw7mz2fq9Z8jXwBQtbtVCPqKiFrB2ekAqh5ANwBcO3o0ZqfC1h988EEJYW16YfwA4LEA3gFwcYJyAJO+5sNeM0n9fhC7P/300+jSpUv6VKZPn4727bli//LoRQmA9z77LDp06OAJgGE7gUTlAbzvvvswevRokRbz+OOPi3aeixYtwpo1a9CtWzew8l4dQWyf1PWTi8el2+66+cAAYMyrTvcE//bbb455dTGfutg9AXDh/Pk4DcDLEQJg3L2AVbvH1QnECQCHDx+Od8eMiQQA6bnoxmrIBAFg0td8Eq47HccQxO4GAItXAaseQKtXacaMGahRo4bQ2+QLcvPmzTF37txiUxjE9jrmvlC3qdvuuvnAAGDMK1f3BOt2UYc1HwGw4fz5oICIndyI3H7QHMBs9QJ2agWXjV7AXh5ApxxAAuDaMWMwJwIPIB9cfQH8kiAATPqaD3vNJPX7QexOAOzdpQt2pGSdHs8TD2CmOoAqAG7evBlVqlRJT3O/fv3w/vvvg8VkTpGSILZP6vrJxePSbXfdfGAAMOZVp3uCdb+hhDUfAfCk+fNxUw4DYKvFi0HJChVgrR7AVs2a5VwrOD8h4CQCYNLXfNhrJqnfD2J3AuCwLl3wKYCDANyvEQAPYXVtKgcwib2AZdGLLAKxA8Bly5Zh5cqVjgAYxPZJXT+5eFy67a6bDwwAxrzqdE+w7gUa1nyFAICZCEG/l6pmtNpXPiwIzH56AYfpBMIeyMw0svPMSh1AA4Bhr4D8+X6Qe41uAIxCCPqkk07ChcuXY4ByDfz444/Yb7/9RK9tFoGUiagTiJcH0ABgMq+TIGs+kzPQzQcGADOZlQi/o3uCdbuow5oiFwCQILSPQ35iXL2As9EKzg0Ad+zYAbYxTCIAJn3Nh71mkvr9IHYPA4DjKQPTsCHefvttYQr5UuRHBiZKD2CUreDsALA1AGb69enXDwTAdStXok6q6MpaLBfE9kldP7l4XLrtrpsPDADGvOp0T7DuN5Sw5gsCgMyv4Q3QK1eQN9Moi0AyAUDV7pl4ANe3bInZs1mnW3zIh102ANAtBOwHAL/77jtQ5ueHH37AAw88gHr1qHKmfyR9zeu3QDx7CGJ3PwAYphOIkwxMWACU8jW8x+gGQO6DddL79uuHpUuXou2qVbje4f4XxPbxrI783Ktuu+vmAwOAMa9L3ROsu0w9rPmCAGAQHcC4AdDaCaRl06YiB5A6gP2KinDZZZc5wt0wCtomHAD9hIAvv/xyTJo0SZwnxb7Xr18fdrn4+n7S17yvk8jBDwWxuxMA0rNVqlQp4VmOEgClDExYAFRDwHYAGEYGhlfH0QBkDiBt0J1pGCkA7LFqFa50AMAgts/BpZXYQ9Ztd918YAAw5qWle4J1u6jDmi8XAHA7AErU2mkU+gkBUwZGFoE4AaD64MsXAIyiyX0m6yvpaz6Tc8qF7wSxe1gAdOoEInsBWz2AugCwTJ8+4iVHeubjAsAgts+FtZQrx6jb7rr5wABgzCtN9wTrblXjZD4CDcVMGf4cMGCAEDS1G2wBdeK8eZFXAWerE4gTALq1grPrBGIFQK8iEL8h4OqDBuGuu+4qZvoRI0ZgzejR2mVg4gLAuNZ8zLeS2HcfxO5hAfBhhxzAsACotoLzKgKhBzApABjE9rEvlDw6AN12180HBgBjXoy6J1i3i9rJfG+++SZOOOGE9J95oVDN3jp0eQCzCYCtFy8GuxaouYlBO4GoADgUwAaPKmADgM4XblxrPuZbSey7d7I7e/Z+8sknaNOmDUqXLi2O0w8AxtEJhAAYdys4uxDwkiVL0HP1ahMCjn2VFz8A3fca3XxgADDmBaV7gnW7qJ3M17dvXxQVFaX//P3332P//fe3BcCT58/HKB/FHUFyAOMGQDchaLtWcLkMgJcD+K+NEDQ9gP0B8DXg4gyb3Gdyeca15jM51nz6jp3dV6xYAfbU/eOPP0RBkMwJTSoAqq3g4uoFbAXASn37iiIQNwA0az6eK0m33XXzgQHAeNZNeq+6J1i3i9oLAI9kQ3cA+QqAp5xyCtosWVLCA+gUAq4PoL9NEUg2ATDqVnBOnUAIgJsBVPaA+6gvwbjWfNTnkWvbs7N7gwYNRP9aOWQeLQHwui5d8IlFCFq9DuLwAOYqAJo1H8/VotvuuvnAAGA86yZrAPjf//4XZcuWzfpZ0gP4RVFROs/MDQCz3QnkjjvuwOwhQ/BGCkzopTj++ONL2EgmdrsVgRAAWy9ZUqITiGp3P72AM8kBfL1x42LtoXgCn332GapXry6qKN1awam9gD/88EMceSRR/a/Bcw8rBB0XAMa15rN+kSVsh3Z233ffffG/rVtRHcC7ihdYNwBOmzYNQy68UHQaORjAfc8+iw4dOqBq1aoo2rwZbS0vJfJaVwHQKweQQtB7RFgEYu0EolYBe4WAzZqP52LQbXcDgPHMa9b2qnuCdbuo3TyAPxcV4dHUjTZJADh27FjMGTo0EgAMWgXsxwPIKmCvIhB2AlkYEQB+8MEHqFmzZt4AYFxrPms3jYTuyM7uBMD7t25FVwtw6Q4BWwFwXKrVXNQAaO0EEqYK2A0AGQJ2k4Exaz6ei0K33XXzgfEAxrNusuYB/N///mdbfBHqtNeuBTp3Bt7lO739oAewkAFQtbsqA5MEAPRbBRy2E0hcHkAtaz7UBVMYX7azOwHwqa1bcV6BACDF6uumPJ3Sq8jZlwVibr8LA4Bmzcdzjem2uwHAeOY1a3vVPcHCRd28OXD22cBQ1pdGMMaMAYYPpzBezgNgKQDLQ4SAnTyAamjATyeQTELAC5s0AeFSHdYQsK5ewH46gfgBQNrmhRdewMUXX4xjjz02gsUJ6A7LRHKQebgRpxBwpgDoJAT9AICHPFrBqR7AvwHQoQOouxdwECFos+bjuaB02103HxgPYDzrJmseQOGi3nNP4NBDgU+ZERN+vNutG+o9+SQ2ffQRatSoYbtBHR7AqFrBqSFgXQCohgYyAcB86ATiBYBsFXfQQQeBb9EHHHAAvv7667RMSJhVqjssE+bY8vm7TiHgOAAwW0LQpXv3xuTJk9NC0Nn2ABJAKK1DOZLy5cvn8/JK5LnpvtcYAEzktEd3ULonmPpbhx1+OH6sVAllv/kGexIGQ4y1a9fiqfr1MYZtzerXxzvvvBMKAIMIQccFgJn0AlZDAwYA7fs333777Rg2jBmPfw7qxTVq1CjE6vzzq7rDMqEPME83EEUImHIx1At1awVHD+DDjRqJ9cIhw6rXAQgrBM0ikPYVK+Knn36CVxFI3K3gHnzwQdFSki/hCxYsAJ8lZmTXArrvNbr5wHgAs7teSuxN9wRTaHne/PmiGu7pMWOKPXAzOfV27dqh9syZAgBV4WPrtqweQHp76OWxjiAAGEQH0G8vYF0ewF9++QXlypUTp0sAbNW0KXa69ALO11ZwbjIwY8aMASVpogZA1faZrHHzncwsYGf3ffbZB09v2+aZA/jAc8+B9xY/AHg/ATBAJxC1CjhsL+CtW7eCeY0E1LgBkODbCgDvdWdffDEeeeSRzCbOfCtjC+i+1+jmAwOAGU99NF/UPsG77SZuVgTAwyIQ423dujXqzp4dGQDG3QlEFwA6CUHnYy9gNyHoOABQd1gmmis//7ZiZ3cC4NRt23CuRxFI1ADoJAMTFgB//PFH7LffflkHQDsZGOn5nAng8ipV8O233+bfokr4Gem+12jng112He4DGp1u0GXLloHhQYYc6T6nQGKFChWE7lLt2rVBvbTKlSkJG/+YOnUqbrvtNnz11VfiGC+55BKwMlK2KXI6wp07d+Lxxx8X/zZs2CDO8ZBDDkH37t0xaNAglClTJvDJaZ/gHADAODuB6AJAejJKleLWIQo1WjdrJjyArAK26wSiej4YFM2lHMAwAPjg8OFCKJze5KhCwKrtA1+Q5gsZW8DO7n4AsBqA8SmZFvU6yEQIWoaAnWRgogbAbPQCduoEYgAw46Ua2Rd132u080EYAKSA7J133gkCFasC3QYXK3MqrrrqKnTq1CmyCQi6oSlTpoDhSSYJM+Swbt06NG3aFI0bN8aTTz7purkuXbrg2WefFa72Cy+8EGTnRx99VLQ4atGiBWbPnh30cETexhdffBH4e36/IG8ScXgAdxYV4bHUw90pBEwPYD4CoBoayAQAvXQAc6UXsJcH8KXhw/F6xACoOyzj99ortM/Z2Z3h0qe3brX1AMpOIGEAUE2dUHMAs6UDqEMImp48Ok5kFbBfAFy/fj3at2+Pjz76SLTh5DPJDL0W0H2v0c4HmQIg83duvvlmIblAT8fhhx8uYIZ5Xuw8wURe/o3ewG+++QaERUIigYTeQF6grADM5qD7/rDDDgPDmI89RjT5c7CKi8m0fFA3adLE8ZAIfXvvvXe6n6X8IMGQwqZMxD3rrLMCnZL2CY7RA+gXAHV0AvHbC1iXB9CtF7BdKzjV80Gxng2tWmHWrFkl1pIEegJgpp1AotABpDe8YsWK4iGVaSs43kN0AKDusEygC7yAPhy0CtiuFVxQD6AVANenrpuoALDz8uW4WglfqyFgXZ1ArAC4V79+8BMC5nPowXvvLdF1pYCWYNZPVfe9RjsfZAKA/fr1E28YZ555pgh9EnoYSvUaDBEzfDphwgQBilzU1arx/S87g43IL7/8cjyXSjiWe6V3qkqVKujcuTOeeuopx4Mh5LFjwt///vdinxk3bhyuvvpqsKpxyBCqV/kf2ic4BYCfAeLGEDbiHyQHUAXAbHcCiRsA3ULAXgDopxOIHwDsCODQQYNw1113FVuQfnsB624FpwsAdYdl/F/dhfPJmTNnisgK0334M/PkOIIKQRsABDZv3iyeR16t4Kwh4J9//hmTd+xA5yz33i6cVV7yTHXfa7TzQVAAfOihhwTsMIR63nnUdw8++IZzwQUXCO0iQmC2RteuXQXg2bW+ojeSnswvv/wy8OHcfffduOaaa4RnkOHgIEP7BAcBwGeeAWbOBJ5+2vEUCIBHzZ6N2wJWAWcbALNVBXzaaaeh5aJFJXoBWz2ArZo1w8+pHECdAPj555/j0EMPFQ8PvwCYSS/gKISgdQGg7rfyINd3oXyWMHIDgOcBnDN4MKi1mesAePLJJ+PCZcuy7gEMA4DTd+zAOQYAs3bZ6b7XaOeDIABI7xG9ZPSi0fsXZjCE1KtXLwwYMAAnnnhimE35/u4JJ5yAN998E9u3b0elSpWKfa9hw4ZYtWoVeFxBtfJoE3oVP/74Yxx8MEUH/A/tExwEAKnBtnKla4ePfADAKIWg8wEAM+kFbAXA//boAb4cqsNLCNoAoP/7RNI/Kb1Rz7HI6cADhag3h18ZmPttikD8dALxEwJWcwx19wLOphC0nQfQAGB2r5SCAsDsmjb6vdWqVUvkIrJ6lzmK6mBLr8WLF4vK4CC5iSzg4HYZ/rCG2uT2mQvJf3ajbt26WSkC8QoBb9myBT/UqIGa27dj0RtvgPawG0FCwFH3Ao5LCHo7gL0dwudOreD4YOINmsOPELS1CthPEYhXDiA9gIcMHAh6qNXhNwdwa+q87fQek+wBVG0f/V3EbNHOAm4A6EcGJmoAZGHisM6d8QkAA4BmzeqygO57jXYHURAPoC4jZmu7EgApWyMlpK2r7AAAIABJREFUOuS+6clZtGhRIADk5Ldp0wYMuxEenVrxjBo1CjfddJPtadITyZC4lKAhnPJnbpvHSWkZwoH8mf/l/++xxx4CZOXPv/32m/gOC3AYWpc/S1V9WQXMPBEKFLN6iUP+PHjwYPR44AGwD0P5cuWEJ5TQyhs7j4HbpM1Ywa3qAHJ73Af/xmPgz/wO80R//de/8GgqHEGw3n///UucE+2nFoHwuOzOidtVAdDpPOi9ZfhThoBpL3ketBl/JhC9NHIk3gDA14DFS5eiQYMG4hy4H3ketCW3JQGQ+7TOEz3hrZcsSYeA+Rnai/bj/vhv/vz5aN+8uQgBUwew17hx6N+/f7F54pukLKpgDuC7LVpgzpw5JeZJnh9zAF8980wBl+o8sQKQeVg87g4ADr7qKvFiIs+J58gcwPfuuANzUnPDSnjmtqprj+euAiC/r669bdu2ifmURSA7unUTFfHWtadWAVvn7J577sG8ESPSVcC8/tgJRM6Tde3JllfWebKuPcIpbckR9fUkX+TsriH1euLPtKF17WV6TvI8knpOvPdxLUgP4KZNm8T1RI+bCoDyfsEijZEXXST0SVkKePdTT6FDhw5ijclt0QO4oWVLzJgxQ/yeNuc+2AnkweOOE9Ecrjd5TbAKeG1KjeGJJ57ADRdfnAbAu556Sig3UAamaPNmtE2tfR6PLFrktmUnEOaFn3HGGei8YgUGKJ/luqeDQApBl7r0UowfPz59DBSrPwoQx8V1LLul8yWK1xDvDervuH95/OsBHA2A/bxlGkd3AHv26SPOtceqVbhSORb5PYbd+1SuDN5DVA8gt831FvZ6SvraU59Pfu8RUZ0Tbc7CUPW+F+U9gvdlrSohhQSAxx9/vNAaY2WyfEBIKpMhYD48/BS08Hv0pPBGs3TpUtdiliR4AL1kYHijYOEEAdCtw0emHsAoOoHo8AASAJetWAGuDeuQXo2fAOwV0AMYtBdwJjqAXh5AAuChmjyAahVwGB3AecOH47WIZWB0h2Wy9cKaS/sJ6wEMIgSttoJzkoFRPYBMyhmfKvyLWgfQ2gtYAqD0DKmw5/U7CYB2OYB8xqgAqG6LAHhZlSripXPGzp042+QAZu3S0X2vyQkP4IoVK/Dyyy+7CkEzVHb22Wdjr734KI1nSLkWu5wnWY1MT5Wfcd999wkx6YULFwrvSaZD+wT7lIGJGgDpAdw5cWLaA+gGgCfNm4dRHjctHl8QAHSrAlZzAHUBoDUE7NUKLhMAXNikiZAuUge9B9WrV097AAsRAHWHZTK91vP5e1EBID19IgICCK/6h23aiKpiDrkPAuBDqVZwbgA4tHNn4WEkAI5L5RgaAMznVZj9c9N9r9HOB2E8gAz5EIIIVBxuEiO8eOnav+iii0Q4NI6uIJSuYa6ekwwMQwSUevEaTHan3Murr76KY445RnycOXT0LFJnMMjQPsExAuCOiRMTKQQdFAAzyQEM2gquUAHQ6AAGuVsk97NOAOgmBD2sSxcBaGqOXlQAqKsTSBy9gP0KQRsPYPavj4L0ABJ0OnbsKHKbmDPFvB2CkJsQ9Pvvvw96CikHwpsCO2qw+0Y2ByGNgtXMO7MTgub5NGvWLH1IzM2jnpXa4o3yNxSN5mfVsCG7g7z22muBG3JnCwC9ikCi9gAStP0KQcfRCWTOkCFYmMoB9AoBRwmAudQKzq8OYJgQsAHAbN4B9e0rkypgu04gYQBwOHNnW7YUHZkKEQCZ8/fcjh0mBKxvmZfYcsEBIJMdTz/9dBDoKOFCTUCW+vsZ9BD++9//xo033ijCxQxfOVWb+tleJp+hF/CKK65It4Jj+xx2/2Ayv+r9Y1EHz5Nhax4zx9y5c9G2bVsBrmxrp47Vq1cLOxAEg4xcBEC/OoB+ATCOTiC6AVANDfhpBac++Pz2AtadA+gXAJPWCUR3WCbI9V0on5UAOANAv6pVRfcnDjcZGLtOIOp14KcXsBoCdgJA1cPoJwTcrkIF0bWK9/gLly9PF4FwXzo9gOsA1ANEUWAmreAMAGb/atN9r9HOB0FDwKwW5RsWvV1B5FKsU3PttdeKHsIMHwfV3Qs7zRSDZtcOalVx3xdffDFGjhxZzNNHQGWHE/ZWpMAzByHx9dfZudR+cDu5DICsnGWPE68ikHwAwNlDhqSrgLPtAbQTgrYCYBQyMCwCqW7TCcSvDEwSAJD3GuoFsiJz9OjRJar37a5E3W/lYe8/+fh9NwAMIgMTFADV1Am1FzCfLTIHMIgMzMsA2roAoNoKrieAKItAnADQbys4A4DZv7J032sSBYCkXYIT8/iiaOFGsGJf4Hr1+N5TmEP7BPsUguYN3ABg8TUoH2peIeCWixeD/XtVcA7aCzgqAMykE0gUQtC/XHIJHn744WIGDCoE/fbbb4PV+HLIh7v8/5deegnnnMM+B+5D903Za/+F+HcVAPtbhKCzCYCyF7BVB/D+VBWwlxB0EADU1Qs4004gJgcw+1ee7nuNdj4I6gHMvonze4/aJzgAAPqRgWH+ZJ1Zs3y1gktyCDgqDyD1I89ftKgEAAbtBRwnAEbRCi7TTiBuMjCUT6L2mxzdunUTvcS9hu7+nF77L8S/h60ClkLQfjyAahWw1QMYNQB2Xr488a3gjAxMfFec7nuNdj4wABjf4uGetU9wjACodgKJQgeQGlu1fcjFqELQdpXpd9xxB3QDYC55APMNAHW/lcd7x0jm3nUAoB8ZmKgBkELQag6gFwCW6d0bkydPTkvUxNEKzgBgfNeE7nuNdj6IAgDpel6zZg3YhYBK6bwZUO/viCOOQP369X0LK8c3jfHtWfsE5xEABtEBlJ1A7AAwShkYp17A7GgivVfWIpAocgBvAfBa48aiE4g6ogwB+20FF6YK2I8HcDwAnu/ZPj2Aqu3ju7ILa89hAVAKQQetAs4nAIxCCHrmzp2gjoVMR7mqRw+MfuQR3HT11bjj3nsLa1Fm4Wx132u080EYAHznnXdw880348UXXxStUOwG29C0aNECN9xwg4BBM4pbQPsEJ1wH8Nxzz8WJ8+aBjfLcik+CCkHHDYBqaICQ5iUEHTQE7BcAdfUCjqoTiJsMjAwB06Pbny35fAKg7rCMuYeVtEC2AfDhRo1EV6ekAWDcnUBUAGRObddGjYSAPnuZr9y4UThlzIjOArrvNdr5IFMAfOCBB4QMDB9cHLwBUN9P9HHctUv0MGXFlPTAUC/w3nvvFT1QzfjLAtonOGIPoN9WcOwE4kcImgCooxOIXwAsDWBpiFZwTh5Aayu41k2bYkeqF3C/oiKhJakOA4AQD3RqisqRKQDqDssU6v2L9/IHJ0/GxrfewuUjRhQTvQ9bBBKVB3BdSgdQLQJhr2G5fa8ikCAh4KirgKP2ALJhwdiePdMAOPXFF3HeeecV6vLVct667zXa+SATAKRHg/p4fJsg0FEXr06dOsVkVGhtNr/esGGDCFNNmDBBhIgZDqO8ihl/WkD7BAcAwCirgP0CIKs6/QpBBwkB+20FpwsA1dAA139QAFyfepBZrxP5oL0ZgJcOYEcAhegB1B2WKdR714IFCzC/SRNRAHbqKadg0aJFaVOEkYGhTIus0g0bApYASE1XVWdQAqAfHcD2FSuKrk52OoA6ZWCcADBIJxDVA2gAUP+Vqvteo50PMgFAvkXwbZAaXQzx+hkMEbdq1Up8lHIOZhgApAVyHQApZN5q8WLRt1QNYfNBRq83B1962jRrFsgDGAUAUgcwTC9gvzqAmeYAUtdv3ogRoLImbeflAdzWtSueeOIJz1uHanvPD5sP+LbA0UcfjUHr1+NSm3SNTADQrhPI77//LhwJfnsBO+kAqgBIwHxgxgwh4m8A0HgAfS94Hx/Ufa9JJADuv//+ohWaGq7xYStxg+cDny3ZzMhvAAzSCi7bnUDUIpCwHkAnALRWAUsAdGoFl8udQKICQKsOoDUE7BcAdYdlCvXepQsAGaKVMjC6AFB6GMMCoM5OINIDmGknEOblGg9gdq9O3feaRAJgxYoVwdZnRx55ZCBrb9y4Eccee6xos2NGbgJgPugAZgMACS9ly5Yt4QHMRwAM0wpOrQKOCgBV25v7THQW8AuAfoWg7VrBRQWATkLQfgAwrlZwTgDotxOIAcDo1rrfLem+1yQSAOn5Yxj41ltv9Wsn8Tm2oGJf3ZUrVwb6Xj5/WPsER5wDmCkAUt2+cuXKJaaSHuFsewBVHUA/HsBMOoE4hYAJgF4yMGpLK6vBspkD6BYC5ktcpUqVRKguKgD0CgH7rQLWHZbJ5/uR27lFDYDDunTBpwCcPIBOvYDdhKDtikDUHEMvAPTqBKLTA5hpKzhVB9B4ALN7deq+12jng0xyAMePHy8qgJnoP3DgQNSoUcPV6ps2bcLdd9+NiRMnYty4caYSWLGW9glOOAAGkYEJIgTtVgSSDQB0CwHbAaDq+QgDgFYdwDBFIEEAUGcnkKAyMLrDMtl9xCRnb34A8DkAVyit4Pbee29M274d51ryBpmjFwUAqqkT1l7Awzp3xicpwPRbBZwEAAzaCo4A2KdyZbAXsBMA7gPgaVMFHPnFpPteo50PMgFAFoCwoGPu3LlC/uXQQw8VVcB8u9pzzz2FkbkYv/nmG1EF/Nlnn4miEeoBsnCE3zEjeSFgna3gnDyAuQ6ATq3g3ELAfgBQtrQK6gGMUgjaLwAyB/DXHj3AqkN1+OkF7EcIOigA6g7LFOq9yw8AzqCH2wKAz2zfDnZwVoukrAAoAS1oCNgKgHat4ILIwHgBoM4qYOkBzBQAGQJ+/uef00LQahUwAfCpuXNFDj5TLWrWrClk28wIZwHd95pEAiBNxgtvzJgxoDeFJfMcVrCTGoAMFQ0ZMgTDhg1LV0aGM3v+fFv7BKc8gJ+zIhRI6zLagUWUAEjv8E8TJ4KdW3njj6IVXFQyMFF6AJ0AkA+y0qUZYC5eBewUArZ6ALMJgGFbwYUBQB1C0Krt8+dOEf+ZZAKA++yzD6Zt25Z1AHSSgfHSAbQCoFcruD369MGkSZMiaQXnpgO4ZMkS9Fy9GlcqIC3TQWQImGkZTgBIIein587FI488gnXPPott1aph/XvviY5dZmRuAd33Gu18kIkHUDUXXaCUdVm+fLnQ+du+nRlTSLeCO/HEE0EvDwWizShpAe0THAAA/egA+s0B9KsDGIcQdDYAMEwIeBiA91q1wqxZs0osGHnT99sJ5NBBg3DXXXcV287w4cPx7pgxmJ16mDgBYDZawYUFQMqAUI+uevXq4h+H7rBMod7H/AJgv6pVRfSHgwA4dds2zxBw1B5AAuDwLl3wcSoEPCElAxM1AFp7ASepE4hVB/Dh555D+/btRd5uJ4rS33qryMs3I3ML6L7XaOeDsACYuenMN2kB7RMccQ4gO4HUmT0bt3u0bksyAEZZBezkAaTupdTIpA5g22bNQD95AwB2nUBUD2CUAGiXA2gFwA8++ECEhNRB0HQDwDhawdnJwFCIniLzFSpUwKpVq8R5qLY3d5noLKALANUijahCwAYAIVIy1E4gU6ZNwwUXXCAAsDeAP3r2xIMPPhjdAinALem+12jnAwOA8a5a7ROsAQCPmj1bdANgaJceGLucTr8AmOtC0E6t4NTQADuBtGnaNDEAyLf+NaNHY05qDp0AULcQNFNIgngA7QBQXXvMS6bXVHdYJt47Rnx7LwQADNIKrgeAJHgAZwK4vEoVeMnAGACM/trRfa/RzgeZAODNN9+Ma6+9Nl3w4desXKAMR91www1+v5L3n9M+wREDoDUEnOsAWAbAkiz0AjYAWDL/lAAYVgeQAFgHEKG+w+vUwXvvvWdCwJrumjoBcPz06SI8GdYDqLaCyyQErAIg05e6rFiBq5Voh84iEN2t4AwARn9hFGQImC2uvv76a1SpUiWQRalwXq1aNVFAYsafFjAA6F8HMKoiEDUErAsAw4aAvVrB+c0B1CUDE1UIOAoAZEjrDgAPpQBQd1imUO9dfgEwqBA0Q8A6AfBAABMzaAWXKwDoRweQVcCTTQg48ktX971GOx9k4gEsVaqU0PMLWkG0bds2oR9oAPCvdah9gmPyAFpbwUUhBJ1LAPjbb7+JnqYcag6gUycQaw6gFwDeDOC1s87CggULit3UsqUDqAMAMxGClkUxDwMYmwJA1faR3/ELeIO6AFAVgubcMXfWby9gJx1ANQcw1wAwaCs4A4DxXZS67zXa+SBTAAyj5WcAMPsA6EcGJpMqYKcQsF8AjEMHMBseQGsVsCwCyRcAVDuBZNoL2BoCjgoAdYdl4nvcxLvnTACQQtB+dABlL+CoAPCpp57CiK5dS1QBe3UCCZID2BNA6d69MXny5LQMTBRVwFYA9GoFJ4WgvXQAJ02digsvvNAUgUR4Gem+1yQWAHlgDAUHGQS/L7/80ngAFaNpn+AAMjArABzvUd3rNweQALijqCitA5gkIeioAfD8RYsw1GI3Nw+gHyFomctkvb7UVnBxegCtAOgkBP0tACaKqCLA8px0AaDut/Ig97yc/ez06UCbNkBKy5LnQQAcuH49etnMp1yXFIJWZWDCAKBTK7gJAB5s2FAIGjt5ADMFQC8haJ2t4MLoALITiBUAH374YdzeowcYOaEO4GQLAP7PRrw9Z9drTAeu+16jnQ8y9QBS5yloDiC/c/DBBxsATCgARukBtApBJw0AXxg6FAtZxReyCOTUU09Fy8WLDQA6dALxAsAoqoAZLmQI+PbatUXnId035ZieNVnb7Q8//ID99t8fXxUVodpll6X3W69ePQxctw6XBgDAoELQfjyAfgDQSQbGywMYJwDadQK5CEClfv3gRwjaqwrYDgBvvfVWTJkyBSeddJLoEmJGMAvovtckEgAPP/xwMFyz//77B7LW999/j+OPPx4ff8yaPTNoAe0THMAD6BcAa8+aldYBdKsCVjuBJAkAKQQ9Z8gQ3wBIaXO+QcvONurKdQJAtxBwEjyAa0ePTgtBZyID49cDuBlAZRcPoBsAMsG6bNmyImTVH4CTDIwVAHWHZfL9znXcccdh1erVuLBcORR9/bUQc5YewEHr1wcGwCBC0EEB0KmHthsATvj2W7SzrEnpwcxnALSrAn733XfxtxUrMA/AinXrULdu3Xxf3pGen+57jXY+yMQDGKkFC3xj2idYMwAyBMOiIOsI4gE8ad48jPIIPfMGHVURiNoJxI8H0A0AnYSgg4aA1Qef2tTeLQT8euPGoMagOvwUgUQhBB0FAI4ePRrzRozA66m598oBdAPAR+gBNEUgoe+m6vppDeCk0aNx3XVckX+GgJMOgLKFYlRC0BcuX44Byr3JKwTMexQRii+LEippO5kC4fa7MCHgyzLUAaRYNF+ghgPY0LYtZsxgEN8MvxYoSA8gu0EwF6xly5Y44IAD/NrKfM7GAoUOgHEIQQcFQHbwYMdMOw+g304g7Zo1A0HSqRewFQC9egH7lYFJcis4AuD8ESPwWuoByZyuhg0bpq8SNlovV66cLw+gCoC6pRny+UbGdp5HHnmksDkBsM6QIbj9dvb90QeAaicQPx7AByj5k8oBdOqh7VQFHLQVnBUAVR3AbApBhw0BO8nASABkQ7jVzZtj7ty5+by8Iz833fca7XyQiQeQYRleePT8MHegbdu2oAo/bxxmeFuADzb+46DL/YsvvvD+UoafkG+cnwFgp1Q7iBFvqLvthkxCwH49gN99953ty4IuAOS5nOBwvtkoArGGgHMRAN06geioAg4DgKoMjO6wTIaXYk58zQAg0LZCBXB989nWeflyRyHobALg0qVL0WPVKlxp40300wnEAKCey0/3vSaRAPjTTz+JNwW2XXrppZdAfT8CxFFHHSU8g/QQMtfPDHsLjBo1CjfddJP4Y6VKlbB9O31DekacALhj4kQ8lrphuekAnjx/flZDwNkAQGsruLZNmwoPoFMvYNXzke1ewB9++GGJlzeum2wCIJMI3grhAVQBUHd7Jj1XajK2GhYACSP9DjxQNArgYP6gVw6gDg+gWgWs6gAG9QAmAQAr9e2LZcuWOQKgXx1AqwwMq4BZKUxvr/EAZnb96b7XJBIAVVPRABSjff755zFnzhwh88KHx0EHHSRAkP8aN26M0oqcQGamzp9vxeEB1KUD6OYB9AuAJ82fD+KwW2/hKHMAVQDcA8DikK3g7GRg1NAA8/SSBoBrx4wJ1Qs4ag8gAfDNt95Co0aN0he6NQS8vVs3PP7448VuBKoQtKwC1h2WyZ87Uckz8QJALxkYKwBSBmba9u0415LjyxDtdV264BMAaieQsCFgKZ9EABzZtSs2ASAAFs2cKZwTUQKgLh1AvixTYYNg1p1Ogr59ITyAq1fjKhsPoBMAEu5u69ED1CakB9AAYPRXru57TeIB0GpSJnLPnDkTs2fPxrp16wQM0svVvHlzAYP8L//fjD8toH2CAxSBZKIDGBYArULQTlXFuQaATiHgKD2Ar8bYCSQOADRVwPrvmlEAYN+qVUHJLw43HUAJgGE6gThVAecyAGbSCcRLB9AAoJ5rpyBDwH5NuWnTJgGD9A7yDYb5Z2yPddZZZwkYZPPvypUpElG4I18BMFMh6FwEwJaLFmGIxcOhhgbYCk7mABIA+0+ahD59+hRb9NYQsFcrOBaBxAmATANhK0h6Kdw6gXjpAMpewH48gF5VwLeldAB1h2Xy+W7lBoCZ6ACGEYLmNfVhmzbiGcIhvb1uRSBeHkAvHUB2AmlfsSK4vuPqBRxVJxAvIeg/evaEKQIJdzXrvtdo54NMikAyMRk1AOkVJAwyJPbLL7/gxhtvxA033JDJ5vLmO9onWIMHUNUBdPIA6gBAhjJq+5CLIZS8lepqYlf0EnUI2A4AGb5ksRSHCoB+qoCZA5hrAJhpJxCpAxglAKq2Z4iG9506deqAAGOGuwW8PIC6ZWBU7UcnAFSFoIN6AP0AYLtUEUguAaAfGRirELQBwPB3A/VeE35rJbegnQ+yBYDqqdFtOm/ePFSoUAHNmjXTYbec2ab2CdYMgLwB27UEDKIDeOK8eb5yAJMKgHY5gGGrgP20gvPSAezEFIOBA3H33XcXux5GjBiBNaNHh8oBtHoAnQDQTQhalYGxA0C+JJYvXz6wDIxq+65du4LhQEYeVq9ebYRuPe6M+QiAVZn/lsoB9AJAVQg6LgC05gD66QXsBYB+q4B79eol7hdnn302Ro4cKbyuZjhboCBDwJ999hkOOeSQwIuD3hgpNGoW1Z8WSBIA+pGBoeRPreefT3cCiQIAVSFotxBwLgEgPaMSjIN6AMMIQVNSiNcmvaC5BoDWKuAgAKhWAau25wOsNIDfAdHqiqoFZjhbIB8BUC0CCQuAXkLQvEcdlaEQtF0rOBaBZAsAVzRtKqIVpwFYxH+LF+Mf//iHuVxcLKDea3QYSjsfZOIB5IONZf5BewEzt6FatWqmF7CyUrRPcAAPYNIBMKpOIFGHgO08gGFCwIUCgGPGjIGaAxgWAGUVsGp7mTfWlw+0evWwdu1aHffpvNmmCoBtmHIRUAia2XpqEYiTDMzUqVMxtHNnfAqARSAPPPcc2rVrBz8hYL85gCO6dgWbjuYKAOrsBGLnAbTKwMxt0ADvvPOOeHnk3Fe/6ircd999ebO2dZxIQYaAKQBNmAtawMHvUB6GXh4zjAeQFrAKQedaEcjpp5+OFm+8gaGW3ERrCLh9s2ZCV89PDmAYAFRbeTl5AP22gnPTAYwiBKwC4O6UgbHoAAb1AEoAVG0vAXASgPsNAHredr0A0I8MjB8ApAzMsC5dBACqOoBRAqCdDAw9gEF6AVt1AHV6AHUDoJcMjAqAFxCcDQB6Xi8FGQImAIbJDaDb1IzkAaBfGRi1CMRvCJjwb+cxjgMA1VZwYXUAnQDQGgKOGgD9toI7xCYH0AqAmQhB+60CdssBjBIA2QpOVgFbQ8D0aBgAtLnj/vYbsPvugNLLm8oNRxxxhGMrOD8AGEYIOigAOvXQjkoGJmgv4DAh4KgB0KoDWPT00+jcubOY294A3DyABgD9EUpBhoAJgJkOgqMBwL+sl6QQsAHA4qtaeo8y6QVM7xX72HIwr8YLANUHnx8PYD4C4AqLEHQQD6AKgKrtjQfQ/k7NfOzdSpXCtksvxd7/+lf6Q14yMAPWrUMvm0p8aWdrCNiPDEwYD6BTD+1sAeDuvXphypQpaYkaHQCYaSeQoELQL9SvjzVr1ghANADoj3DUe42/bwT7lHY+yCQHkAA4Y8YM7LvvvoHOZsuWLejYsaMBwITmAEYNgNsnTsQTPlrBqZ1AnGRlcl0IOigArm/VSrRatA75oM0HAFSrgBkCjgoATQjY+7Z8yy234PobbsDy3XZDmbfeQsOGDcWXvABw4Lp1uDQiAFQ7gdyfYQ5gtgHwxx9/xH777Scgib2AS2cJAKmj23P1attewG6dQG7v0QPMnbYTgrbKwBgA9L5urJ8o2BAwld4zKQIxOYDFl5B2wg9QBBI1AP40cSLYuItCAk69gK2dQPIFAJnLKD3l1L1s17SpyAF06gSiegCdegHTa8Nt8uGTKwDoJgRtBcAwOYCqB1C1vfEA2j/UpF2WsmijQQMhkeMFgEcffTS8dACDeADVTiCZFoHoDgEnpRdwWADcG4CXDqDJAQwOgOq9Jvi3vb+hnQ8y8QC+/vrrOOWUUwL39+XFumTJEpxxxhneZ14gn9A+wRoAsNasWRibAjvOqV2f50x1ALMNgJRqXqShF7BTCDiJAPjBBx+gZs2axa44AoJbEcj27dtFmy/C6GUAfr3kEtFYXh3cRhgA5Nv1nnvu6VsHUOYAmhCw981TBUAKfUjBdK8iEC8AnAGgn9IKzqkKWO0FHKYKOE4A1NULOJNWcH50AK1FIFYPoAFA7+vG+omCDAEHN5P5hpMFcg0ArTqABgBPgx8haBkCdmoFl00PYBRC0CoAshVcWCFouyp5omhtAAAgAElEQVTgIABI9DRVwP7vs0kAQFkFHBQA1U4gTgD45JNP4vpu3bDJIgNTtWpVFG3ejLaWMLa0hyoEfdJJJ8HNA5gtANSlA+inCOTUU0/FCy+8AApEn3YaFQLNUC1QkCFgswSis4ABwHOhdgLJFw+gGhqIqggkqhBwUgDQqwo4CACaEHCwe5ITAFqrgGsPHgzqZnIwBOynCjioDIwuALyhWzd8lALASc8/L/rPFzIABpWB+bVNG8x6/nm0AvBS2bLgS98ee1A3wQxpgYIKAfMBRGXwHj16lGhmH3RJfPrppzjvvPNEM2q+aRXqMAB4LtROIG4AqKMTiK4QcFAdQD9VwEEBUGcnkCg8gATA+cOH41Um07MIxKIDaAXArV26gJ4da5iZYWgVAE0RiPfdNKkASGFdVs9zTqmt+UGbNpg5k5mFSFfaqkLQbh5AOwD06gTyH4ogx9wLWG0FdxGASv36idQppyIQlor1qVIFO3fuxMydO8Hmqsy75rP19p49wfumXRGI6gEcCeAFRQiaVcDPADgLwILU9lghfMwxx3gvrgL6RMF5AF999VUh3nv99dfj2muvFb06g47XXnsNPXv2FDD5xBOsEy3ckS0A/ALAIUquj9XifCD4KQLJNATspAPIIhADgCjWAcFJBsYPAGarFVwUAMgikJdHjEgD4JsrV+K4445LL82oAXD80Ufj3XffLdybjXLmfkLArQHUsXQCicoDqHYCUWVg4gbApPUCDgqAz+/ciaYpYAsiA0MAnGORgSEAclu0CYHSAGDJW0fBASBN8K9//Qt9+/bF/vvvj969e+Oss84S4QG61+3Gzz//jI0bN2L58uWiMfvChQtFIciLL76Y1kor1LtyoQOgVQg6X0LAQmct1Ug9myFgA4AbREGDtL0EnSJ2AjEAmL7NZgKA9erVQyY6gNO2b8e5lpw7p04gKgAOAfBhlj2ASQNAtRfwpatX4wrFjnIOVQ9gpgA4AoC1CMQAoDeVqPca708H/4R2PsikCpin8fLLL+Oyyy7DJ598kr7ZskcwtQHLli0L/sywFj0FBEA5+Purr74a//znP00+AQDtE5yqAo7KA9imTRuonUDcikBUHUC/nUCSCIA7GIZx8J76bQXXoVkzbHVpBRc0BHwzgNcbNwYlZtSRywDoFQLe1rVriYiBfAiaEHCwh4sfALT2AiYARqkDaNcKTgcAMsewKJUD6BUCzkUAjEoH0ABgsGuIny5ID6A0Ex9a9OgxjLt48WLw4nUatWrVQqtWrYTn8PDDDw9u6Tz9hgHAc3Dy/PkYlXqzdWotF7UQ9AtDh2IhAD85gEkBQCYc8wXKTQfQDwBG0QvYGgL+r4MMjFsrOGsI2A0A+wHYbgAwsrtgJgAYtQ6gbgCUVcAEwIkzZ4Ivr0F6AZ944onosmIFrla8bqoQtK4qYDUHkB5AdgIJqwPoRwjaAGDwy6ugAVA1F2GQPUVZ3ME+oXyQU8OLFxzhj+FiM0paIFsA+DmAQyPIAeRNVNUB5LyXKVOmxIlRB9CPB9AqBB0VAL4N4O8O58uqRt0AaA0BR+EBtALg602aiDZzQT2AUfQC9guAXjqAag6gFQAZOahQoUJgHUC7ELDpBVz8EvVTBGL1AGYKgE4hYLtOIFYP4Ma2bUXXKQ55zGoRiJPnXJWBUQEwSBWwHwDMVis4LwDsU7myiLRZi0DG9uzp2AnESwbGhIC9iaVgQ8DepjGf8GOBXANAFoHUfP75tBB0LgLgHXfcgdlDhuCNPPQAfv755zj00EMFNDlVAUcNgJkKQTMN5D8jRzoWgWQKgKYK2PvO4wcAMy0CuWSvvcBCPwIju0VN3bbNNgfQrhNI0BCwFQBlC0UCoKwCVkPAfgCwXcWKwomRbwA4edo0XHDBBeLe0BuAnypgaxEIK41/+OEHoeAh82y9V1v+fsJ4AAPMLfPF+CbDvCkz/rRAvgJg//79sW3ChHQvYLcqYFUHMCoP4FsAjnfxAM4ZOtQ3AP4EYK+IcgCdOoGoDz6nKmA/IWAVADuy8nvgQNx9993FLrcoAHDbtm1gl4cwnUCCAmAYGRinIhD2W77nnntw9tln47rrriuYh5pOAGyXWm28z7PFnJcHUNUBjBsA5wNonwJAP0LQOjyA2eoEEhQAb7/9dgwdSnEeYNSoUbjxxhsL/jFuADDAEuDCrlatGpjob0byAHA5gBNsGr2rc+XXA0gA3D5hQuBewEOGDBF5boSUihUrpncddQ6gbgB0CgH7BUDpyVBt7wcAP/vsM1SvXl2AWTYB8LcePYTumDo4Z35zAJlEsMIiA2P1APoFQL9VwNJ7dCYLagAsXbZMeH0KYfjNATx8wADwwU8BYD9C0LTdAQC+T2k78k7/b8C1CjhKAFzXsiVmz54t9CIz8QB6ASC9X0xn4vXFHMBsAGCmnUCCysDY6QCqHkDObQUAewL4ziWdqBCuH3mOJgSszDbFKvnGx0RZO8jbsWMH7rrrLgOAis2y5QH0UwUcJQAG6QWs6gAyv+cPAF8PHy4qxeWwAmDz5s0xbtw4HHHEESWggzdnvx7AcgDe0NAL2CoELXMAnVrBqZ6PYQDea9UK9E6FAcAOzPv04QHMpBew6gEM0wpO5gBGCYB+Q8Bffvml8MBzvbA12GEDBghvYD4Mzs/LffuidKNGaD1oUAnPphUACdt8eeB9u/7RR+N3CiID4D1hnwoVcFqXLnhwyhQwl7KX8pK4YsUK8MWeBX60IwfX+DsAqBD7S54DYOnevTF58uR0fiJFl49KwZG0MW1CHT0JC9JO1t+tZ7cVQNiToWp+LqgMjJoDGAQA/cjA8DyoOdDYw0mQD9eP33MwHkAA33zzDc4//3ysWrUqbTfZXFx9gMsLwHgA/1peuQiAtZ5/HrenbgJuOYA/TZyY9gDahYA3bNiARo0aYfDPP6ergNWbI7dNTyIfMu+8845IZq4D4L6UnMoNp56KN95gJt9fQ950JQDaycqwCER6AKMAwBaLFoHQJm/oPBonAKwPoH9RkZBQUoc1BByFB5AAWH3QIPHSpY4oWsFFBYD/GTFCdBqIAgDH1KqF999/v5jt5XqwKwJRAZCdD6rlEQB27twZT0+dKtIcfkhJoHAN8B5M6a4aNWqkgY3r9tQ6dTB2wwb8AwD7Kl+SAkDK67CCVKxtANsA7J36/+OPPx5vvfWW2KbYdmqRHQtgdUAA/Ib72Wcf4flnFMBvJxC3IpBseACTBoBBdAD/6NlTeO1pa78ASEfCwQYA07dTA4AAunTpAiq7U8WfIZT99tvPtjKUibV8wzYAmDsA+PXXX4vqMulps3YCcQJAVvdWnjcvDYDr1q0TYRlKAF166aUiF/TK009H3f/9D/ThSRkYFQAfe+wxPHTRRaJIgA8gCYAUG6J8C3/HsCiBjjJE7ExDgXG5jSl8+N12WzpvRVo9GwBo7QXsVQUcVQ6gGgIOC4DbU/qHKthKG2YbAP3IwEgAVG1fqAAoz5sAeO6ee4o2YRzUYL1v3DjR4UHWjzOsx6xshmo51+yVQk8UPYDUmEt7sJS3iG4A2JSPGWH0UtWzAUC+XPFafQnAORZosHYC+TqlUvBZah9xAaCqA2iXA2gNAUcJgLy/1QVglYGRIeAwQtD7Ugtx6lRceOGFtkUgBgD9+vyKf66gegE7mYg5EXyoy6bhTp+jp5A5gDRanIM3n9tuuw1fffWVkJm45JJLQK9I6dLsSOo9ePwEWX5n2LBhIiE205EkD6C1FdyyZcvQuHFj4VGZMmUKevXqJUITl2zeXMwDeM011+CJKVPQoXt3EQ7hP3q4ugLpIpBTTjkFuy9eLPpSTpk1CwMGDMDMjz8W4SJazw4Aue8zFyzA9S4AyGrDwWeeKdrYlaLo9a5daQBMP7j4u127xLpjfmE2ADCsB1DmMqnrKmgOIAHwsGuuwZ133pmRB1A3ADLE/8rIkY4eQEIL80AJA/3pfQqhA8gikAfq1cPatWvTtsgFD+Avv/wi8u9KlSrlfIuhN7lZM6ADZzwFbCkBeAIg4Y42HHfuubj6pZfS3jV68TkyAUB+j11hp6ZgUXoI+Xs282MsyA0ArZ1ATgbwXOo65zbCAiC1aW/s3h0fAchUCDoXAdAaAr69Rw/x4mwAMNMntPv3jAeQN5AKFUQo4KijmP3gPFgFzDxBemniGgQZilE/88wzaNeuHeiZatq0qQAda6N5u2Nk+ITA+PHHH4ucGVZC5QsAWnNTDjvsMBz/6adg2PIGQHgR9q5QAb/JhwwgHqgnH3MMWClbBcC8lSvRsGFDUDxZPlz4cJA3dXoDOlWqJGQWGCYKC4AdOnTAodOng0FOdT/pByGALVu24JzGjfHj2rW45v77xb5lCLg6gOkeOYBuQtCnnXYa7ELAfHCzqT0Htfo6NmuGH106gfjxANJzzpcUNyFo6nBy3viZsADIcB+rn3V5AHUBoGp7t1ZwKgBeSFBIWAiYL1as4Garzfnz59u+oH7//fc4oHJlfH/QQdhjwwbstffe2DBkCI4aO1asgUUATlOAaqzysxcAUgZGZqGqgCevLS8ApJf+V4sHsKioCH369BERI1UImvuaaLmG/bSCcwoBEwBHde+OjSkAnDRrlshT9NMJxE0GJokewEw7gQStAua8f8lUCRMCTqOBeq/RwTTaHUSZtoJTT5ZvSgSrY47hLSG5g8UpfDi2bt0aDC/KIT1WfFA3adLE9QQaNGiAiy66SIS7+dl8BkA+PJmbww7PfADMnDkTfdu2BcM1HPwdQbpfp06iKkyEch97TNhHwqT8nARAJhG32nNPEVbOFgBSuqDs7bfjptQxs6pRAiDDXf+55x7hkfx80yb8+ssvOKIuAzF/Cc96AeD5ixaJUJgKStYQsA4AtBOCVgGwPYAa114L6h6qQ0cOoFMnEDchaFUGxi4HMFMPoF0I2E4GJskAuHXrVtFWk3PIB/zjTz0F5vWlx++/A7vvjq7duuHJp54C/Zp8UeN1x9AsQ7RBAJCv5C8GCAHzOHi3n5YKWzp5AHnEzClU7wN88aa4M4XpP00BRVIAUK0CttMBVAGwB3NXNRSBZNIJJKwQ9EgAfqqADQAWxwMTAgZE2f20adM8PWhxy8BMmjQJl19+OZ577jnh/ZPju+++E4KlvMGytZ3bYKstUjlDj3wzz3cAVB/gtNsV7dvjq4gBkGpSEs5UL6SfELAfD2D9+vXRb80asOyCDyoVAGWHlAULFuCPJk3QaNcuzHnsMXTv3j1d2RdFK7hsASA91MyzpB3dAHDt6NGYnbJH2CrgKISg/QCgXxmYTKqAk1YEooJ8KwC1FZCn12uPsmXx1Y034uCbbhJz7QSAvFQJd5S54UuKnQeQYksME0cFgLIIhP7vean98zhY088CLr4sctD7/kkMADjh22/Bu7/6wiY9xQYA3xHrideDtRMI50wtAlm/fj3uv/9+ML2HdQCFOEwIGMDChQsF/C1atAgXX3wxjjzySKGVZFUKZyiOD+y4ikC6du0qAM/ugXfQQQeJPBt6BfyMXANAayu4N998Ew8++CBatGiBli1bpmFHvqnLim0VAKdPn46rOnQQYQD5uSg8gEkAwEqVKmHLTz+JalQ3yQbr2qDYbYs33ijhAcxGCNjOA6gCIB9yRw4eXCI3N4pewFEIQbMXsKwC3oOSIxYdQKsH0AsAZRGIXQg416qAVQCkd6yWAoB82D719NOYXKoULvvjD/HApiebHjmrB1Bdr6xUZ9hX5tfJEDABkGHiIEUgfj2AKgDyO9ekwGJ46lgIgM1TMGgXAg7SCo7bfDelA6iGgBmyLFJCwPkIgJdVqSJSdMLIwLxQvz7WrFnjGwCZ8vXee8wwhJB/Y3Ss0IYJATP5vlSpPwFi1y5fSvpxAeAJJ5wAgg/7mPKBrw7mrVHGhhcRexh7jVwDQFUHkN02mAtTccsWEYIh9B588MHFZCHkXKpCvl4AeCSAGz1CwJT8OL98eVFYIkPAcQCg7AUs7cL5Zr6SBECG4GSnCwm7dPezepmt1ugF5nACQK5xFpxwZDMHkLmpUuLDLwCyhzdf2tTB69ktB1CGKAkTbh5ALyFoFQBXrFqFY4+l/+jPEQQAHwUwOiUDo9pezQF0KwJhDuCBV1+Ne++91+vS1/p3rjFGGejlq1mzprgmWY17pFLMI8+JwMTq6LAAyCIQHSFg5gDSo6ZmfBMACftjWKCU8gDyMzMzzAFUc2etACiLQFQA9GoFF9QDWLpXL5H+JOdEhw5gpb59xX3HTxVwGACc26CBkNvy6wHkhcDPngVgv3btRGSt0IZ6r9Fx7jmRA0gAPPnkk0W1mtvgTY2VpXEBYK1atcCHnV27sVNPPVVIibAymN5ArxEEAHmT4j+7UbduXXHD1zXkjUkFQBa+1KtXT1y87PzRYtQoUchiLQKxdnJ49tlncXXHjo4ewKQCIHNTr1i7Fn1S3j1RBTxkCBamQhqHpIyvAuCmTZtKaKVdeeWVGD9+vHh5WLlypYAmKwAynYBrjPuUnUziAkCKG9f04QGMAgAz6QSiFoHwzuEGgASdbV26lEgzketbBUC7ELBXFXBSALBjx46YPX069jvwQKGvKgFwQ+3a4r7F+8WcOXPE74MCoFMIOAwAMkzI0j+7HMBsAyBbKEr9TLUKmLp1E1JaiLkIgEFkYHQDoJoDKAFwMIBNBQqAJgSc8gDyZsU8OrcRtwyMBEA7cWBWczKErQMACVc33cQst5KDMMHcSClBw5u8qPTctUuAcpkyZYR8ifyZ/+X/E7b5WfkzK6z5nbJlywrvgfyZXigV7Ji3wW0QUPj7ZgBOHDFCdN1QPyffbFQPDsPng7t0EXkgHLzp80Y7oFu3dBHIyIceQs+ePSMpAjnzzDPR+LXXXGVgqEt4+MyZrlXAhN0r3303DYC33norXho5UojkytA4z0cFQIpU16lTp5hN1Nmj8DnfeGnv21L5VbQHrwEmcbdv3x6PP/64mCdWcHZp3lxUATNI0mvcOCFwrc4TvdJM+ucc8EG2pnlzvPDCC2CIgYMVxfSIcb3IKuAFZ56JV155RbxcEIS4ViiEzJZd/AwBsMagQSLnkeuDa4Eva+x5+/6dd6ZzALkmCLPq2uN5qR5Afl9de6w+pRdZegD/r3t3PPLIIyXWnrp+WPjD85DnRIHqBddfL2RgCIALly4VHkDajOfEzx9wwAFiH5SB+bFzZ5G2wHPgufCY6K3n3yUAvvvuu+J70ovPbfHvBMDxdesKD4e8njhPsmKaOU9Vr7wy3fbM6XqSL3LqeTj9TBvKuZHnJOeJc8/z4LUuf2bYt3bt2uJ4awKiglUCIKtxCcEM036c+j3PqW/qZ7ccQLlug+YA+qkCtgPAhgBWprQ6rR7Aa1NednoAmQPICISbB5DlS/PmzRPKEbQz7cFuQf869lihPMHuUtJTL68bAvKjjz6KW3r2xKaUcPE906aBcM01W7R5s7g2eL1yrXCe5H1SegD5IseXu65vvomrlc/S800pMx4Hi0BK9ewp8uDkOpQeQJGnmVp78l7JNcVrVL3PyrXK38lOIFwHsp0jNRb37NNHiOGrHkD1e1wbvStXFueiCkEz5/3uyy4T0luUgRmnRGd6A/j9kkvENct9swhk9jHHCFUHNw+gEwB+2Lo1GCEK+nzSeT3Je4S878l7IK9Bea/j3IR55vL4eU9W7+VRnhOjAFodRFFUAffu3Vvo4qm9W+1ghw8wapLF1URaKtdTBsR6rDIEzBsKZW28Rq55AOVNiGDDC0EFwFN9egCZ7zeoUycBTXJ7UeQAuukAnrVggbg5OQlBhy0CcQoB23kAec7sr0vP4d61auG+++7DeeedVwwA1XUjPc2qB9CpFzChqHz58uLmq4ay1O35kYHhcR95xBGinR5Dh7Wy4AHMtBWc1QNozQHktSiBN4gOoFMI+P6jjwYBUY6k6QAuX74cVFTgGjgFwBILAFrz+1QA9JMDqAIg8wH54sIRpggkCgCk+PIMJQTckjCiFK3wGNU2agTAhxo2xNtvvy0AW4IhAVDtBXx9t24CAJms8f/snQe0VcXVgHfsRgQbihqjIiJYscbeYokaSzRSH1VFBRULKqhgFyw0WxQ7KBbU2LFj7w2wF2wg9o7Jr0b/9Q13X+eNp957zi3vzazFAt47dc+cmW92vSCFBvCfiy9u3ISSRAFXwgScRgMYVgkkKA+gC4BJooDtIBDTLyLSnDWA3gQcR0o19Hucp0lAGhQEwq6OhgYwSUsDgFHXy93GX0gIGwWAW518soHyIBMwEXsUd9eUL+UCYJAPYDUBkB3tPG++xhrAMAC0tU0AyqcffSTjC9oAZIT3KPn3SDIUBIBhpeBcAHwloBYw11MNwqki8tD22xsNoN1cAFzjmGOMVstuSYNAohJB2z6AtQaA9WoCDgNAtFWkgnEBMK0J2A4CyQoAJxfKMyY1AaMBJN0+8KkaQBcAdR4ixQw1iUlpg4LhiCOOKGoA0wLg+f/+t+y1114mkb2tAdQydupKQNDKvhYA9njmGTnMCgwjkFG10mgAaw0AoxJB/+vaa02mC+QbpAG8s1MnE8wRpQEMAkDyNdrBOknWz6ZyjDcBp+jJaqeBIQkpSaDD0sBQJgdATNKaEgBGaQBtACTVz1FduoRqAPEBHH7VVSYSXCdxBU/dLaYFwLhKIJh1/jR5soyOSAQdlQamXAA89KOPTB1gfU8WC1JdsCCWCoC2L5M9Fl0ADIoCBgBXX201+V9BAxgEgEnzAGYBgHF5ALUSSJAPoKsBTBoFjFYIs57pk8IGKMgHkM2eBj/Vgg9gJQEQbaAdBVxqGpi0AGgHgcQBoI59TfCuc0gSDSDuKif06GE0gPj4npcQAN0gkDgAzDIPYBal4MIAkHrOF8UAYBINYJAJuDkDoD3XJOGGtMfkriBKawKm+kWpDZ8bInGrVQqO3Rs50tgJBiWCxldrR0oqFRrAGlbXuDkCINn7j+7aVXQEMDEDhQO7dDE+gHkDID4yOJzbtYArbQJ2NYBjP/rImIXDABC/nL59+8qDN90kX0ZUArE1gLYpq1wA7HDssabsod2aIgDaQSC2f089RQHbALiliDxe0PrZGkCylFJiUf0a1QcwrQk4TwBM6wMYpgG0AZCcgnjDqg/gISLG/w8fyiATMAB4fI8exl8SADz35psFf+E4DaANgEGl4FwNYCUBsN9LL8mhAWmq0A4HJYK+4oorREvBxQEgtYCTpIEJ8wF8eOONjR8cayZ+4XEFFUpliFo7z55r8ni2mgNATflSzstWKwqYZ0YLeMghhxRLweEAz2Al4MDW/hERjBPwTjvtJFOm4HrduDUlAExqAkY+x3brZhy3FXhsAKzVSiBRGsC0PoBpAZAci4wffHBKBUACH3CEp74yZQs1CCRIA/jOO+/IGgR0iAhO/B3LAMA0aWDCooCTagDR1z3tpIGxNYB5RwHXQiLorADwahEheMDWwvO9pg0CwYcUuNBv3b0eeQeDNIAKgG4iaK4TFARyf6EOsOYBdO+j5mXcJ6YX6g9rTRTcGcgnyTn2xom56rju3Q0AUnFkXB0DoKaBKQUAR/bta4JAkgBgkjQwYQBItfGlC+5CbxR8NsthhHo5t9mZgAFAqFRznKXpKMAPx+tqAiDPy+4Qv6g5c+aY6C1MlieccILxr9JGNBSVPojmJJpKG+fhj8Juh9JyBIwQUILD8K23auXM5FLJnfADfAB5dqCISRN9ZxQAfl74sJmEswLA3VPkAcw7CKRcE3CcBlCju20AXH3vvYVIZLt2dpgGkA0KUb12SwOAaw4ZIiNGEHP5W0uqAUwDgD/26SNoHOyG9q0aAKgRmAZcLBNwXBDI8lXIA4gPGvMLyfRJpXXYYYf9LggkzAcwbRBIHj6AN1KlxEkDEweA6gOoeQCTAuDOhcoiCqTuNwEAousm2wSVfWwAHFuo/hRXC7gWNYBxeQCjagFnDYBhQSAA4FNklGhmdYLtuSb5qp/8yNz5IK0JGABMkvIl6BU5D5+bagNgcvHnf2TuHVxBAEybB/BFESHtb1Qi6CQAuNKNN2buA0hCZS2pZi84qgE8ffXVTVqWJADIOf2IXCyYgEnZwWYDjQ81pWkuALKQoYUm9+JdY8cKu2r1hYoCwLfffls6rr66/FTQAFYbAKMSQRMF/OAJJwhhLFlqAMNMwC4AJvEBJGqYfsDVgOpGaRrXJ+fkaqutZtL+MHe6jcT0h2+yiTH32v1rRwGT0JtEybUYBJIFACYxAfPuNgC2L6T20crtqgHku+nTp4+x3CgA4ms4JgUAahRwkAmY9EetW7c2fdGH9EUVrAVcTiJoNqBuEMhPvXubdDmaBiaJD2BYEAjpekhbhBXILrGX5nupx2ObnQkYrdi///1vk3spbUNjRg3eqVOnpj21yR5fDQB008Ak1QCiOR3avbup36lQZKeBKdUHsJxKIEmCQEh5M3DGjMBawKWagNMCID5qvS0ARH4bbbSRqUzjAqBqatAuk2Jp1tixxtRmA8JpIjI1IArYBkBqyK49dKgxkdktaRRwlAaQbxn/WBaPUiuBpAFA0sDEBYGMXGMNIc1R0ijgOADEZ5mqLzh6kyaKtCNuwxUEbRP5H7Ek2BWGMP+Ty5F2c8EEqecD/zwrc+lKt94q5zn9a/sA2gCYxAcwzAQcVQqu1CCQUgAQO0tUJZAwE7ANgOrDaH8TE0UEXzbSVBkfwO7dTRCIC4BRpeDcKODuzzxTzAOIttYFwIX79zca3CwrgTDuGE/IAVM+GsAnnnhC9p82TfB9dEtVYnfqXygFF5UGJg4Ak0QBhwWBNFcAbHYm4CZLYlV6sWoAYKkmYCZV3VUrAFYyCIQouQ4lBIFUCwDtxK82AOLHdKSIXLHEEgKw4dv34YcfmmSvTPpo73B4bykihx9+eCoApKrHWu3bm6TWSQGwlEogLgCWWgnE1nxs93IAACAASURBVAA+49QTJV9ny5Yti4mg4wBQawGHmYDTloIbMmRIoxQ6X375pUnWrY1AMqBPG8nBSUKsza6FDszj00ij5ORBG24oA3/91WwKWNQrAYBRPoCUa7uzABcElOB0kMQHMAsALEUDGASAyBY/W/S0xgewWzcDgJiaR1sawFoHQAIpCFbJGgAvnDRJSIWmaWBK0QBG+QA2Rw1gszMBJ+Uk/Iww+eLA7lu4BKoNgDvhA3jKKTJ8+PDAPIBfUOexsDBcc801xci6IABMGgTi+gBWIw+g1gIO8wGMMwFTdxYT8JjZsxtFAROld25BXlEAiKah6xJLSENDg6kkoM1Nn1MOAJJQd50ADSCVQF4ZObJYCaRaAIgf5NRhw0JNwDYApgkCUbmbMRqRBiYuETQpowga04b2xzYD24BX7L9ff+tBfs+iiP4V8//f/vY3Y/rHrHziu+8a+EObkzUAXlPInRcVBOLmAawkACbNA1gE6YL5O0wDaL8n6Y+4Pibgt+69twiAo2680fhzx0UBp9UA5mECdgGwnETQGgXMtiUOAG9fd12ZPn16SZVA8AFsjgBozzV5cE7ufJDWBzDpS+LgTsJl7+8XLbHcOzjGBzAtAB7Xo0cjE7CrATzRKjdkT+D8m4k6bR7AvHwAywXAJCbgIACkEsi0gjM7AEhCZaCRguqY+pICIImgg6KA+ebWXmMNowFMCoBoIfFTsxvwEpUHMAsNYF4AmNQEbANgUB5AAPD2iy6S69gkiRjznwuAiwJ2InJWoXybJha24ROo4Bi7XVlwCUgLgDbcVTsIZO1CBQ/88exE0BoEgmzuFhHgUluaRNClAuAuhahivjU0gKuKyDkeACMBMGkamKQ+gLjmUBqOoKaxY8cmxYa6O86bgEO6zANgsrFcCwC4ZUQlEFsDSH6nExoaTGqFIA1gWh9ADQKJ0gBmkQi6FBNwnAYwSwAkryK5yuxFVOUbpgGMAsB11ljD5Er8Oz6HARpATJuvnnlmUQNYLgBGVQKJigLOGgBHFHwAwzSAaYNAAMAfLrrI1Bmmb4IAUN0StL/yAMB9CqDF5sD2AQyrBJLEBzCrSiA3UW7QGbsbigjekmkAkOsAtO43UJSrEwRim4BdDSAa+COog20B4NmTJ5tAnnI1gNQIVv+8vIJAbA1gL3wABwyQJ598Uvq9+GKsD2BUJZALrrlGevToUTQB/9irl8mHi/wAwFLTwJAI2vUBpN+IDid4jdzBK63EDNf0mtcAegAsa1RXGwDj0sAkAcABXboI6WLSAuBLIsIuvRIAeMiMGdK/sMCQyuf2Y4+VR0WkVBMwAEiSZ9cEbFcCsQvCuz6AagJGA4jTOuXo8gDA9Y47Tgi2sNuxxx4rr511VhEAyR3Yti3L5W8tjQYwLwCkHmurVq3MAhVnAkajpkEgQQAILF3g1AKOCwJJAoCuxjYKADGTfS0iBPCk0QCGAaCtAXyFgJ+ASGG7T/MIAskKAO1awGFBIGhR0SjS0gAgI/usnAAwyyAQrQQSBIBPPfWU9H3hhVAAPKB1azMfuQCoaWAwAUcBIPXWk0QBJ/UBZCyS7YC498efeMKkOGqKzQOgB8CyxnW1ATDOBIxTNZMHcBLkA0h1kEO6ds2tEohtAg6rBBKXBgYNYBgAUvl5xUIPojWjJBnvGqcBTOIDaAMgtYHZzWsy2zwBcN011jBBJGgAKwGARAGXmghag0BIGvy0EwTiAuC3PXqYKgMuqAIMNgBmaQKO0wCmAUA9lvEVBoD87hcRsaOAswLAPIJAggAwrQk4aR7AagCgWwrO1QDmAYBuFDA+gFEAGFUJRAEQP+4LnCAQWwMIAJYaBXw0JnbHB3BTEXmyMJcSwdxUAdCbgEPwh+oa1CVlIfUtXAK1DoBfFbLIJwXAPH0ASwXAqEogNgDiN0eKiiQAmFYD6AIgmoxuBR/ALDWAb7zxhqzXoUMRADsdf7xJOu1qAF896ywhXpV3LVcDWCsAqFHApQSBhPkA2gDI4r/MMssURakBJvoDN/+Z/l59ALMAwDAfQBzwV0+hAcwqCATNHfdN6gMILMxfSNistYCTAmDSIBA1AePV+k4hNx2+gIMGDTImz8u++kpIrm33l91X+y6+uLD5ILl/LQAgaWDIENDn+edTm4DTAGCpGsAgE7ANgOTR3HzzzZskBngNYJPs1sq9VC0AYJQPoA2ASXwASwHApImgFQDRbqExYgLHrydOA9hUAXB4QMklALBThw7yHxHZTUTWDwDAY445Rl47+2wDgJho3pk50yS9djVrafIAlpIGxvYBzEIDmDYNTFoTcBIAJDKc6i1rr722LLroosZ8XS4A/rMQ1BDlA0jfKYRVygcQMx8Jql0AVB/AP4oIRTTtIBAbALUSSLlpYMJ8AG0ABATRiJPqBmgtFQDRzmmKFnwAK6EBzAoAz4/wASzHBBwFgMwvjzVhAPRpYCrHSk3yTtUGwDgfwLQAOPyqq0xuNNc0Rue5UcBJKoHkHQSStQ+gnQaGBMILL7ywee8oDaAdWZc0Cnh8IQEzueXIMaeN5MLrd+xYBMANTjhBTj2VkJHfmguAM999V1ZZheX4t4ZGJAoAyYlHRKwmgq4EAH7TvbtxQ8jKBJwWAIOCQNz+Wm+99WTatGlCFQnMdnkCoO0DaANgWBqYMB/AxQtRzneVkAcwSAOYFgApv8Z14oJA0pqAFQDxTUZDSvLpxwo+mNTfKUUD6ALgIgceaFIFZZEIWn0AgxJBkzC+93PPxWoAwxJBYwKuFgA+8OCDQkonvo2VV0bv23RaszIB4+A8bNgw6dev3++cxtN2Kdc6++yzZeeddzYDo7m2agNgnA9gnAmYNDBpg0B2W2QRU/pMg0CqWQkkzAT83nvvGSiyzXYKsQR0JPEBzBMAdcGfNWuWKa9oA+AGHTvKDyKyq4hsGACARx99tLx+zjlFDWA1AfChYcMEE2CQBvCbb74xFYfSBoFkVQqulCAQdx5LC4BoTMhlZ/sAhmkAswRAKoGUkggaDSCAZZuAowCQNDCYgM8sJGimqhAawCRRwDYAonUi9Y4bOIXsxhUSrQcBIPWCtdUaAGLhIAF3NQCwnCjgKB9AxnPLVq2Eb5mk7uQcJYq6qbRmVwrupJNOMkXfKX/k5g5L2qm//PKL9O/fXyijhLlkoYVwvW+erdYBkKjFVoWJNsgEXEoQiAuA5SaCjjMBR6WBKTUIRH0AR8+eLZ0LQ5cFpRQNYCk+gEkBcKNhw+SUU05p9HG5APjue+/9bmdeKQ1gGgBMGgQSVAkkiyjgJCZgdLGYG4nq/rmg9U5jAlYAJO8g2ioAstIASPQm5t0klUDSAmAlTMAuAGKifqvgd4gWVNuaInL99OnC/BDkAxhUC9jWAJLIe9EMNYAKgEGVQLLQAJ539dUm8bxWAvm/nj1l4sSJkWlgsBChodWSe0mjgNUHENgnqIlydcyNnQcPNoqfptKanQkYeNtll13kkUcekf3339841rZrxx4wvhGmTnF7fH/4kB5++GHp1KlT/IlN+IhaAMAoH8A4AKTk0qHduhWjgEvxAQwDQAKJtn3gAcE/hQlIc67Vsg9gGgDsWtgZl2ICtgEQE/ADDzwgW2yxhZCgecM11yxqAIMAcPDgwfLmqFEmDQzA0dQAMGkUcFoTcBIAJCceuc+InOfbCdMAXiEi+JC5iaCzAMBSfABLqQQCJBKBmkYDGBQEktQHMKkJOCkA8g2t0b69qX6xyCKLFPtKg0BqBQCJAgYAez37bCoT8JVXXikj+vSR1wvVnFwA/G9Dg4mqZ4yGRQErADIuOS5pLeC/iMhTBW0vAMi5zI1fBrhx1PPy3qxMwNpRUC/wx+Bh54QJaq211hJghgLx+D3NP//8wnFEU7GjIdks2j6iZiiwftNNN5kC6829VQMA6QN2vXyUcT6ANgAmSQOTBgCTJIIOqgRiAyAZ5/80ebKMtnaprl9WUg1gFlHANgBi5taFJWsfQAVAaghTYuyVV16RNm3ayJQpU2SL9deXuSJCRYSNAzSARx11lLw9erTZlTOxv/f+++abtFtcHsCkPoBJE0EnMQEn1QCGmYDdWsBpATCJD2BSAAxLAxNkAt5XRKi56waBlGMCtqOAS/UBjANAtKH4FYYFgWgUcKUAEB9A2wRsAJAk7AstJA/8+KORL9H5XVq2NCZLooC7P/OMDLL8BVnL+M44tlIaQAXA3s8+KwOtZ1GtJd9x/2WXNaUp7TyAaQEwKgo4LQC6GsCmCoDNzgRsLxL33XefSTKLNlBbVH1MPhz8aliA/vhHYsR8qwYAAuZExvJR4gNYjgawHBNwEgDMOwikVB/AsDQwlQbA2267TfbYYw/jz9eFVBdDh8q4ESOKALjJ8OFy8sknN/rQ+P7eGT3aaG9qBQCpGvGUkweQJNlLLrmkGacHi8h3CfMAqu+lgeSIWsBpATCNBhCne/xnk/gAsqhTDRptYKUAUBMpI6NSAXCdggYQX7sgH8AwAOQd8QG008AAuGmCQJL4AGrwB1D+ZoAJmHcnz6nWOq9lAHzuueek1zPPhAJgXCLopalRHmECjosCLhUAqcuMXyaypeb11wHfcD1TgD3X5PEeufNBFrWAqamJCWrGjBny/vvvm4gfyBjIA/rat29vzFObbLKJzDcfQ8k3lUDuHVxmLWA7EhSN77CGBlNfUzVQAODArl1TVQLJ0gewVA2g1gIO8wGMCwJJ4gMYpwFUE3A5PoCTJk2SXt27y09o+0Rko4MOkokXXSTfF+rP/iUAAI888kiZOWZMTQCg+gDGASCVQL5raDA+S66mksUlSSLouFJwyx12mIwbhwFxXnODQBQASWx7wAEHGIuGq21WDWAcAIaZgPGZwnfQ9gHMQwPoAmCpQSBsIqoBgFGVQKg8e1TBNE30bxQAAumY67VGNxpANOdoAHfccceKagCDKoH0JIhiwAB5/vnnpeHpp0uuBJInAAYFgagJ2AXAr7p3N4GkpNJhc1fvrVmagOu902rp+ZsCAKapBDKV6FQnCjhpEEhQIugkABiUB1AB0E4Dk6YSCADIxz961ixhgVYgTqMBzMIHEB/Mnt26FQFwwwMPlKsvvjgWAN8dM8bkcKu2BjANACY1Af/vf/8zLii2BjAuCKSbiCwbA4BqAl588cWF9Du0WgTAtD6AaACzBMCNROQ5EUmjASQKmD6KqgWc1gdQNYBakzbIBIyLyxIEgxQ06JTUI0Th6z33lDlz5tQsAOKLjzKF8RdmAiZYUxNBlwqA5foAugB4QWGuJBIYqGX9q+dmzzV5vEfufJCFBjCPF28u18y9g2M0gHE+gK4GcHhDg4lytDWANgDG+QACgLstuqiBp7hawG4QSFAi6CQAmJcPYBwA6u6QSRq9Fbt5LQWHpiEvALzm4ovluwgN4BFHHCHvjx1rcq/VEgA+PW2acU3QZpuA0QAmBcAwE3CcBrDNoEEydiz6o2ANICksSJi9wAILyAsiMpl0QNZEBbwk1QCG+QBWSgOYxAeQZMlsEvRbt2GXn+EDCHy4GsBKAGAaE3AaANTupC+xWKX1ASQAqEMhQbtdKUZTzkT9LEwDSCLoF198UXo89VRRA5g1AIalgVEA1GjetEEgVFbSaHhcHS7EX5G6w/if9+4t+CnWc/Mm4HruvRp49moDYJwPoAuAJzY0mKSqYQCYJBG0moCTJIIOqgWcZRDIHBFZofA+dhBIUhPwmNmzQzWASQEwSxMwGkAbADc98UQZMmSIPProoybivnXr1nL44YfLB+PGxQJg0kTQTOg/9+0rl19+eaMvisXuUxFp7STd1YPIBmBrAMsBQEyqZ3XoIK+99prZXFCFw4zRCB9AXFf4/gAb/CeXdwBwwIABMvdf/xLyPmoajK233tr4PHMO0ZUs9jY0lAKAtg9gNQCwZSHvoJsIOm8A1Eog5IHM0gfQNQHTR/TVSBGx08DQb2oCVg2g3Zf8m2vZQSAff/yxLL/88qFBIJUCQNU8uRrAsETQQRrAJFHAOxTyNGYBgPgAogHkmdH2XrTuuiZpej03bwKu596rgWevBQDc6pRTZPjw4Y2SHpOo240ExQfwpIYGk1NLARAT5CHdupXkA5gEAO0gkFJNwGgAD5kxw+w8WcjPPPNMuf3YY+VREbEB0DYBJwVANw8gk9x5hfskBcBy0sDYJuBNKP3Wv79cO368fCsi1E7d7MQTDbDMnjpVvm3TxkTjH3/88UUAZGKfWUIewC+++MLUxWUyzwsASWlDVgFNBB2lAbQBMMgETICBGwVMEu2VVlqpCIArHH64jBkzpjgruD6AICUl9mg8E+ORXHKlAGCpPoDXikj3wv3LiQK2fQDDADBJHkA0gG1DgkBaFJJL21HAaO7MN1hmIug0PoBRAOiagLUvSciMKZjN7mHWBsYFwD8edJD861//yrQSSFAewJdeekm6P/lkUQOo0adpAHDcxInSs2fPYh7A//ToYSrrRKWByRIAVQPYlADQm4BrAKLq+RGaEgCScHVYTCm4PHwAV5w8WVi2VUsTlAYmDADLCQKpBRMwQTg9unY1ZhYAsNMBB8h1l1xSBMBV+veX8ePHm0l+WxHZe9w4mTlzpnw4bpypvgAAPvzooyaAa6eddiomd49LBG0D4AFE+pWgAaRE3SPDh5tKEEFBIDYAEgX8fcIgEA2+idMAIgeS2SMbknmvGAOAHIfZEz8x/v1y4f9ZAiA+UwT02EEgPBvmZu6ZBACT+AC6AMj9SqkEEgSAagKuFQDsWMghmsQHUPuS4onDiJytEQBEU9btiSdSAaCdBgYNYBwARqWBKVUDSIkHxjNjtykCoD3X5MEhufOB9wHMo9uSXzP3Di7TBxBfMiZy4AoN4MkNDSalQpAGMGsADEsEjaZu4cIz4QOYBAAHzpghB8ZoANOagOMAkMTnRMJXygdQAfD6Sy4xdXwx77exsv3vicZqyBATwDDn/PON2U0ndqq9zLfkkkJqFHIX1jMABpmAg4JAMEETkRgEgGhYFlxwQeklUjQBc9xfReTBwoJGxQxSoZQLgLYJOA4AJ4lIj8L9LxaRg6xAFA2gSFIL2PYBRANYCgACwyQTdzWANgBiVibARBsRo5oGRk3ApeQBjPIBVBOwVgBRAExjAg4CQPzu0M7ZJuBKaQABwO5PPFFMA0MuV8ZnlAbQBsBlMGfHaACDALBUH0DmoqdFJAoA8evdbrvtZKONNpIzzjjD+NbWW/Mm4HrrsRp73moDYJwPoAuApzQ0mEoHNgBqJRAm3OETJkivXr1+Fx3J8UxW5WgAgyqBlBsEUo4PYC0C4Hr77y83XHppEQCX79VLJkyYYGQPAHY89lhjAqe8GFolABBHbfwqVxKRERMnmnJRcYmgiYjFn5Dr7k+5pxANYFQiaDSADw8fbmoBkxX0KScIxDUBJ00Dow7ytgYwCADxiVx72jRBY4aW7U9HHCGjR5NSXIxzet++fSMBEO8lu4p5miAQ2wQcB4D4J94QkAg6KwAE/rcoJG3mHdBsYgKNMwHXCwBipsdcHwSAYSbgIABccL755Lhhw0xeTcY9iaCzBEAtBYeZWZNNEzhGEEgWADjGmpvR2rs+gFEAqNG8WEyWd6wtwLiayzUgSNPAxAEgm4NnCJKbPFn++U9mpfpq9lyTx5PnzgdeA5hHtyW/Zu4dHKIBXG/ddU2NRgAwygfQBkBysJ3as2coAJJ2oZQgkKRpYPIGwLQ+gADgqFmzGtUCxl+ITHIspJXQAGICbuja1ZhZ2HWvu99+MvmyywwAsntfwQHAH3bYQR6//35TKo4GAAJf9DOL/uHjx5scd2kB8H99+pga4XbjGnGVQDQIJAgA7WojcXkAbR/AMBOwGwW83nrryd+nT5fTRUwgz5+PPFJGjRo1b3Pzhz8Ii+R4a7PjagDxYV3feuFSAdD2Gw3SANoAmMQEnFYDGAaASYJASEC+quMDGGUCtjWAeSWCdjWACoDlmIDZ5FzqgA/a4cUy9AEMA0DyABofQEsDqDVoVQMYlwgaDWApAKg+gKUCIJYaLCtBJmC+aX4+XEQe3XZbmToV9UB9NW8Crq/+qrmnrQYA3nLLLTJ0yBADgEDC1hFBIC4Antazp4moszWA5QaBJAVA7ktKh1JMwFn6AFLW7bRCHkAXAIkYZAGqJgDeeNllpg6tC4BodN7o0EG+fP11A2blACBJkcnlpRrAWgLApFHAcQCoaYp0rLsA+LyIbBgCgPhcUWWCc+4ppORR31TGRlgQCNpYFkzbBzAtAKb1AQQAtwzwASwXAMkvSLoPtxRc3pVAXABkY4PfZjkmYDTI+KGyycKX9iwRox1ucfDBcuGFF2YSBBIFgMYH8PHHiyZgTT/CmMIMv3/r1mbDaZeCs/MABpmAbQ0gaWDu6tTJgCbX1DHnAmDSNDBqAk4CgID5PdtsIw899FDNrc9xD+RNwAESQoVNigWiLxdaCCWwb7YE+Hj5Q1tzzTWFaMS8mpt36t5775X9dtpJnsTpPUEpONcEfFpDg6CJCwLAvH0A8wDAsChgKtqsvPLKjSKjeWcmRxsA3UTQNgBSm3OxxRaL9QGMSwPz4dixxl/PDXLh/0QB9+rWzUCDagAVAJm8/9S7t1x11VXmGWoNAONMwLYGMC4IxNYABpmAg6KAXQD8YBMkKNKuXTuhwkocAD5bqL6i366tAYwDQBLm9C30qW0CjgPAPHwAXQDEtxHzbhYASGCJ6wOInACoSmkAowAwzAR8SkEzpUEgCoCPF8zl9DkA+O6WW5oUSzrPMkfhc6hZFGzoj/tZEAByj8UHDJDp06dLl8ceKwaBZAGAaaKAVQPoAbDxSu1NwAV5MLhJonr++ecLKTRoJE5t27atbLvttrLpppvKSSedZBzMm3tDDlqflaoC335L0o58mguAu+yyiyw+ZYrJfE9L4wOICfiMnj2NP001AdDNA1iNIJDT2rUT1P8uAB6OqaWwsCcFwHLSwGAC7tm1axEA1+nXT26+/HKT38wFQHwA38xIA/jpp5+ack7laADtKOA4E3AaAAwLArlw7bVNtLM2kk7vPmOGMQHjfURUNCXcMJ9TvzQOAPFdmoeMv30PSfMAhvkAKgACTaQpsrUx/DsPAKQSBj6AbhRwpQDwgUIewDSVQKKCQPj+BouIBoEAs/g1pvEBVADEnYNNXRAA6hxInV4CGeifSgGgXWYySSWQIA3gD927m40Ozx1WC1iDQJIAIOnBcAMySbQLQSCs9qg6okzAaACPw5y+2GKy9957mw0r61Y9NK8BxAH8l19kr732kjvvvNPsfMyH8Yc/FAFw8ODBJlfS+uuvL/fff3+zh8BqagB33nlnaXXPPUUAjDMBg6aYcvgcgwCQCeTQ7t1NHsC0GkDNA5jWBFwLiaAVAF0TcBgAYpZryKESSNYAOOjii009b6Ly7L7X71on5aQAGJUI2gXAp6dPN1YDbXaqmSwA8IK11pKXXwYF5jUbAPcRMYmxmb3IUUeUbBwAPiUim4YAYJQGENhVH0y+qyANYBgA4gPIYk01nqyCQADAzQtBIJhnkRB+cwTnsIlQ0FFtlr4yYBXlA5jUBFxNAAxLBK0AiDmZbzoMALGi4H/7WWHsZA2AGgTCuO386KNFDWAQABoT8Pffmz4zbgZWKbggH8A0AKgVPZIGgaQBQMB8aEGjyjw59eGHhYTr9dA8AJLR+6KLhKz5//jHP+Sggw4y5ZKAPfwW0ADS3nzzTVNcm0L0gwaxp/INCVTaBzApAFJ6iD60IYA0MGc0NBh/Ghq7Qsp5szAAgKUGgZwoIic7juRMYNtvv73YiaDVBFwuAI4cOVLuHDJEHhGRUvIARvkAVgMAe3XtanbZRN6t3a+f/Pvyy43/WVoNIAv6Jn37yv1XXGEggD5Q+HcBkHQYGqmIg/zPAWWd4iqBpAXAuT17mohmu6mG2zYBq6lNN6KMz6AoYABwjxkz5DQRsQHwloL5Mw4AcaPYrAQA1PQnClYKgEAYNXQx50cBIHWLaWGJoJP4ANppYMIAkG8acIgCQHz8eB+7hu/GIoJ5nLETZAJ208BkXQlENYBoY0lZxZYCvW8pGkCudUQEACIb/GnbFObBciqBMK/yDQZFAbsAaCeZtzWAdiUQOw0M1XhGO1HASQBQfQArAYB8p8xhXUePFspV1kOz55o8njd3PsgiCnjzzTeXtdde2ySc1YZp0wZAfo4G6dxzz5Vnn2V68K0WADAsCnjFBRaQET//bPzGbA3gyJ49DRzQWDjRRrBIRGkAmYgxD7hpYJJUArFLwTG5cq1SgkDsPIAA4B2UR2OyLaQ14H3sKOA4H8BTQ0zATFskEmFBJN9eixYtzHvnqQG0AXCtvn3lliuuKALgSn36mJQm6gP4+hpryFdvvBEYBGIWn6WXlq2/+MJow4B/csRpHVP7i80DAN00MLYGkIjB7y0AxMf41ltvlYEDB5p3S1IKDi2iDbJoG/d8+eVUAMh4x2TMPW1/MIUkNQGjAcR/Fphzg0DUJMk5RGGzHZ6XfGZefkvGoR0E0rWgleO7QwOoAOhqADG3sTkKiwJGywIE8ex2ImjbBGxrAPMCQPUBzKMUHAnR0dphAs4CAOmXI2MAkH5TP8OsARCrQcuDD5ZXXnlFOj/ySDEIxM4wkBQAR1lJ+olwd30AoxJBKwCm9QEkwTtjMokJmGPQqHepIwD0GkARWWKJJeS+++6TjTdm7zevBQHgO++8YwpsM7H7Nk8CuRO+lQZmORFB8mg74nwA+4nIZYVFzAbAM3v2NLtpmtbPjANAXRwVALcvnK8AqGPB1iLwbzcRdFYASB682449Vh4TMbVqkUsaAKQ2bJgPIIsFiUQqBYDXX3+99OzSxUADZpe1+vSR26680vQzSYv/7ACgGwWMFpdJGlgBTOYstZRs8+WXBgDVQT4IAO2SWCwmP5WoAdQ8gIuJyJNOHkAXADUPIC4nK2YxOAAAIABJREFUBGq8++67pt+CAJAkuTRNlkugzZ8pB3fBBSbhbL9+/czvADpyvu0tIv8uXCtIA4icgAuaghbjh+hZe/zaAEh0Jr519vh35z1yMZKCRpte29YAAoDXFQ7AB5BScDQXAPUaSQDQ1QCqDyAAyPcN0DCGANmw52e8oOEjmCNIA8jmAQ1hWBAI6WPoQUzAyAGNpn0dW6708d9E5O7CD5P4ACoArisi01NGAasJmG/5KBG5UETYhLjQ7/anmoA1OCBNEAiAj7bS1gAqAL766quy78MPZwaAaO3/m6IUXBIAtH0AIQF8ZJMCIFHIZKUAAFfce2+TIJqyda1aEaJUu80DIHnE/vhHef7556VjR+Kf5rUgAKRQO5CIZsS3eRKoJAByPxY7JhoFQKpj3L788jJnzpxixCs7c+AhDwAk0J/qBcBcqQBom4A7d+4sK9xwQ2wpOLcSSBwAxtUCBgDx5Tznww8b5QGsNADiA9i7a1ezy8Z8sqYDgCv37Wt8gcKigJnYgY4gAFT/qHIAEA0rgB10DdsEHAeAtg8gcw1O9wQpAGssHLYGkKjMPfbYQ+abbz4hkthehMlJwP9bLr202YhS7ovF3gZAHV92omc1a/INoQFkwcKFwIYboAkN3gsFcLK3uUFgw7XwHcM8p41vAxCyAVC1xxwTpQGMA0CgD/9G3t8GQNw4MD8Dc7YGsFQAJDUOKXJYuvERrGUAjIsCPqegTUwKgPQB4Dnmjjvk73//e6OxFxcFHASAVH1pdfDB4gKgHWAWpgG0fQAZY64G0DUB3xmQBkaDQJIAIHWTNRG0+gCWAoBUEKFRmvKee9Cf127zJmB2LeusIz169JAhQ5hWwgGQ6Fdy0JFryLfqACAaBCYMBUCewk0vguMxC2UQAJ7Vs6fZTdNK0QASXYnZi3vGASA+gGoCRkNxZSHQpNwo4LPOOktuOeYYs5tnAV628D5JE0FH+QDWEgCiaV0lBgDpZ6BFE0F/bGkA8SMkKpa+ApaWWor/zWtsGFZYYQWzwNkaQH6OhpUUOvj7kmYH/6gkAPiUEwRiVxuxAfDJJ58U3E7Ut4/fAYBorTt06CCvv/66GZtzCz+zAZD8BLzXBgV4JDJam20W5Wc2ALKgodGgXVAI3GAzQ044u7laQf1dUgDU5NKAKS4WPLuCONdKAoBpfQABQHwZKdvGtwmIsJWPMwED9/StziEqZ2QLBHNd5po4AKS0HpVO0mgAta9cuTK/uD6AVGuhL6N8ALk/1WC0qQaQChckr04DgPuJCGl+aKVoAPmGtNxcEgBMkgcwyAdwbrduJo1UkihgreiRNgiEgKf/xJiA6Rc2VPQdGkCgkXFOxRHX99j53Kr+X68BxIH/5JNN1CB/8Mkh1QsaQHIXERBCxBKml6FDh5pj+du3eRKotAYwDAAxr0wpdEoYAPJrzClMpjTMUpinbBMwJiMWsXlZDn9r7kSdFgC5EiYGIo1LAUA7EfTZZ58tNx99tDxRMHOpo3saAAzzAcRchNaA9/vuu+/Md5CnDyAm4F5duhQ1gB1795Y7rrrKLN5JABD4Y3KPA0Am44ajjxbgmRYGgASC3XvLLab/mdDtBcOdzF0NYBwAahAIi1b37t2LiyvPAwCSsw3bApqIRgtvYRjaY9COxNVR6pZ2A4Qwc9KCABBwUXcGvQYmwA4Bk1tSAIz6ZvidDYD3FoKn2MjYLcoEjIYPDWaYBtAGwDgNYNizKgCyXUBDawMgvnk8A6OoHBNwVgCocB0GgDwn5uY0AKig6bq0xGkAMb0zv7oAuMSAAcYH0DYB2/7FeQAgMIxZXoNA0gKgmoBLAUBcIphHgzaNAZ9WVX/kAZCd9ty5xrePnTeJn9daay0Df+zSERCDl78JFHnqqadk0UVhfN+QQK0AoJ3iwQZAFtQWhY+RiLoPCuZhnl0BEHMxfjyadyuoZ4kQZmHWlgQAcS0Y+sMPxk+LpgBYShCIDYDnnHOO3Dh4sEmGzQKgeq2kABjlA8gCh9agUgDomoA79Oold06YYABwOxFp26+fXH755aFBIJh/Me8oAM5ZcknZ7quvTE48BQBy5GkiahaeYcOGCVo4vmXGTX+CHQo+gBqVC4wR3GA7jZcLgO/vsotsscUWcsIJJxj5YvrVBgCSWJmgCzR16ptnL8LqC8Y5+JKx6bGbC4D272wA1J/baVL0Z7g2UK3GbVkBoO0DGDaDspHb1YJgPY5tN+9MZQ4bAPHhQ8POtQFAQIQ0MKUCIOXx2ASyGcSvMg8NYBofwE6FlD5pooDJSkB2glIAUPto50IAEPJXmHHzstpQqAD40UcfFbXr+HsuOWCAMQHv89BDxTQw9uYyDwB0K4EoAEYFgQT5ACYFQOZ4fGzRANoAeMMNN5ia4+QSrsXmTcCFXiEqsHfv3kKliaBGAmKiEelM336TQD0BoJsHTAFQ3yYKAN0+x0SE35e9WNqLJAsuseL4LCoAApCApA2ApKrZ5sUXjdnHzr2m91PzNuYl/B35fxIAJMAA7bWtSeKa/N8GQDcPYBoA7NKypUkCXk4iaDSAvbt0MWYWfAABwLsmTDCm7SQAyFYMACTiFx82GwDVBHioiJxXkB3a06OPxig2rykA/l+vXsUErvwMUyiRrI2qnBRyhOq5rgaw0+abG/9grAQ77LCDnHfeeXLccceZe2DmpQ9paJBoaBi1KQC64ywMvN4vBC/Yx+PaACQGtSAAvK9Qbs8+Pm8AtDWAUfNo0HsDfbsEAKBGe3M9GwDVBYCfh8nR/s70W1HgQrNOMJELgJoGRjWAmNKZS7IyARO5ywhlbqE/kgCgqwFUAMRnEm1jGg2gAqA9PggievDhh2WbbbYJNQsHASAm4CUHDjQAuPfUqaEAeMCyyxpFTFgpONxcRjlpYFwTcJAPoKsBTBsFXC4A6vi6/fbbjU9lrTWvAXR65IUXXjAQ+MEH6IrE+AKRe65TJz5D31wJNFcARA5onYgw1kaU5rxRM6+x6AQBoG0CXm211WT3d94xAIhmA8d8G1QVAO18hqNGjZIbjjpKSOSLEzi+SjRbAxgFgOoDSCqG0bNnNwoCYeFBa8B9gbuWLVuGmoCTAmBUKTgXANfo2VOmTJxoAJA9c7v99pPLLrssVAMIhLPo2wC4/VdfGY1fEAAiJyITCVZAyxYHgPTnSiHmnMMOO0xeP+88YcvIc5AcmWcB7LAiYDkAauknTRbL/bmnaoB0rOBzhQ+g2/IEQNzT0fLYDS05QQBJn4ModPVBTXJOUgBEFuqHptcNA0D7voAKIIIPoO17yP+1BGTA6zUCRPW5Y6uPJtk1AdPHgFVSAAQY0fYCr+qmEmYCRovEXMB3iCkek7xqJKNqAccBoPp9hvl42jIJAkCNLNfxq/ObrQHUIBBSHK244opmnIcBoD23aBCImwgazf/Ifv0MBJcKgBoEojV90/oA6ncdlwZmeCGhtqsBxEpDJPnZCy1ULJ8aNP6q9TMPgNWSfBO5b6UBkAWEycgNAkliAnY1gO5ipGkXknaNC4BomdA2aXMBUH9uAyCJxveYOTMWAG1N3ujRo+X6I480YAH4aKKBNACIDyAffzkA2LVVK/nmm28y1QC2b2iQe66+2qS3SQKAat7XKODZSywhf/36awOAGqFqawDpg4cLi7rCFSZgVwNIjkUW/igAxBy2RyFQgIWCnJSYDBXaSVeE2ZKoUpqWa6MvAQt+r60aAAiMACV2qxUAtCOH9fnIj0ewB1Btm4DDAFAjZPk9GliSaYe1IFM70d/4kVUSANk8qAYwCQCGRQGrBlChUTWApQIg3xIbKsbLvEKpvzcLayJoGwDZbC0xcKCQQWPvBx8spoFxAfDA5ZYz2nM7ETQAeGa/fgaCXQAkDcx/nFJwUVHAaQFQfQCTACAyJuiJiioAIP6HBNPpmCJVEOUkfv75Z5l/frYPtdN8LeAEfZE3JSd4hJo9pBYBkALkmAXdKOA4AExjAqZD1L9QO8cFQBYdSi2pCdjtRK1PqdU3ojSANgCOGTNGrj3iCCHdAM+gWsikAKgmYBcA0WASFBOkAcQxn928+qHhg5ZUAzhr7FizkCoY2e+CBrBPly5Ge8bk2a5HD7n3mmsMACYxAWuOR0CYgIesAJA0IIcVghaQi+3QPWvWLFP3k6hifRdAlCTaaHw5lnMw02JyYgwohEws9BmmRVK3aCPdyO4BX3mYBhAw5R52izIB22lg9ByiZvG1s5v6qbqPEvYceWkAdbyFTXz4aNI/Qd+UagBLBUCtvEGEMJq1MABkUZ9Z2FBgAg6rBawaQDsPYFQQiAKgai01KCWND6CWp8wSANGIEiHMvEpz/QKpsY4bBt8H6wLfBv7YLQcMMP71NgCycSRHHsewoT8oAADR/J+9335Gc5tEAxiVCDoJAAb5AKYFQDYo+AAGASAyw//4lFOI0a6Nljfb5M4HWVQCIWrJ5Dz69VeTE/Cxx9gn/dbw/yPp6oUXXmgGtm+/SSD3DrYSQXPXJBrAUgHQDfSI6+c4AARKWKjCAFBzTJUCgJOOOMIECygAqiZKJ+YkPoB8/GNmz26UyNdemOxdupqF1DyWBwCi2UEDeO/VV5tKH0FRwG4lEJL10hQAZ7VqJTt+840BThdOFEBdDSC+lf91fAC17xW0OPfuu+8W8itSLpLk8V9//XURAAFRgkZIfcKx5KJk528DIIl48Stj+ncBMGyspQFAwOe3SsSNrxgEgJimXK8k9VOtNgAmCRYJkhmbKoCBzdw3lnY8jQZQK50QOY6lwQVA7gFYpQXAJCZgWwOYBADDagHnoQEEAO0NAmOTIK6uXbua7wC5E3xjAyBzcYuDDzalVP/xwANFDSDfDt+QAuDBbdqYrAO2BtAFwNETJ5rkypxD6qbvu3Y19w9KA+NGAScBQDsPoGoA2diRjinKBMxYwARMABcAiKa/GAVcmAf4LnlmtNjMu2QaqYWmNZnzepbc+SALACTvF6ld8NshEGTwYFzhf2uXXHKJjBgxwqSDee6550yEk2/zJJB7B1cQAEkCSpH6pI2JgR2itvNFjJOztjgA5DgmUQVATIg4Xgf5ANpaM8biTUOHmiATnkEnKRyW9ZouALKDBkqARtUA4nMz9qOPGgGgmtZ4LnuXrguy+iMBgElNwFE+gEzg/bp2Ne/hAiDR2Sv17m2CM3h/yvq5AEgZMH7HYs/C/WHLlrLTt98aAAQitUqKyoW/cdpH26pwBQBSBPKtt96S1VdfvZH8FQABze8Zi7/+aqIr2SISOa79ghkeU7MCIODP/10A5Hk4H1MxiaDjWp4AiF+aBqSU+hwuZNvBLEHPntQHsFQAxAyJFopmB4egncW3LqzZz6oAyCyPZi8MAHW+YEMBKGJmDXrnND6AACDVO/ARBabQqmli6jQaQAXAEQU3hDQmYO0jfFuZk2jqTmFDNdG7moeS70CriHz44Yey0kormW+jN4UWDjpI3n77bdnr/vsDAZBvYeDyyxufYxsAL730Uhm1//5GBsxfaQDQjQJWAEwaBJIlAGIypz/4Nhgfbk7SuG8vz997EzCahu23N0RObU4tweQKHf+EXXfdVSjAfv75LPW+IYFKAyATMhNGlA9gqRpA3dEn7dmsAVAhJQ4A11xzTfnjq68aACR6FvDjWaIA0E76awPguI8+MjtWbWEAqIuCDYBJTMCDBg2S2ePGhZqAScI+c8YMo8kEAFfv0UPuv+YaU+MYB+4VevWSCRMmhAIgATCATBoAdDWAaOYAwE232EIef/zxRgBoR9uyi8fRnf7B3Io2VPuK50DLdIYDATid63aR32NWBAAxewG0cS0rAAyKAo67t/37pCbgcQVNKOcq+NjXSQp2SY+LegdXQx91rP1+WheX9DL0v91QDagGMCkAamBQWg1gOQCoJmAFwDRBIEkBUOXC5ofvT+sI2wDYh0o9Bx4olFG1AfCrr76SJZdc8ncm4JvnzjXQSX+4ADjm6quloaEhVAMYFQWMvg0XmbRBIEk1gHzTXD9IA+gCIHIjmprIYPKsVrN5EzCljFq3lptuukm23tre6/2+W+5nBzNwoLzxBkPdt2oAIFGyONCz0GhzF6dSAVCj+pL2rAuArg9gUg0g2gn8fmjuuwT5zXEc5hacxAkowZTsAuDMmTNltbZti7nmnhORjQr3KAUANWWO+iMlNQETKTvn3HONL5X7LqS5QLOA6SQIAFkI2vTsKRMnTgwFQHIgAoD4e6G5+WDxxWXn776L1AC6AIhYSGVDtC/NBnAbAAFlNLQsdi4AksKHYBIWXLsPwwCQyEe7ikfYmKs3AMTEhUabVg4AJtUURn2r+JXqpijum7blrKZXNiD0t90AQHw6+WbVZYQ5ie8jTAOoAGj7ANobLXu82SZgBVG+W77fqChgrWqkz6oAyIbkOKv6S5IgkCAAVE2vrQHUexGxTO5QAoj4pt9//31ZZeWVzXdJbsuF+vcX5qMwAORbOKhgAr5x7lyT61EBcPT++wta3SQawFIBELcX/J5tH0AtBQeeMTfFmYDTACA+glgPjjr9dJMmqprNm4AZoAstZFTUf/6z61bduGtIDUOpJkxnvs2TQKU1gEFyzwoAMZFqhFuS/kX7ZqcELxUAtfpGGgDURYNdJ7tbFwB33313ueP220MBkJ05DVOprQEkalUhxjYB6wKj5qikJuBDDz1UPj7vvEAA5P5E2xKIQBQvGsB23bvLA5MmGQ0gKUqWbWiQq6++OhQAAS8WzSAAtEt9qWz5OwgA+TkAyZeNY39YU6ADAIk0VnduxgKBC0Qn2uMxzASM+Qy/zbjWXAHQzdEZJ6eg32u0fZJzgwCQDUhwVth5V7QBkO8DLVtQfwVpAMMA0E4Do6ZoBUDN6We/T1gUcNYAGGQC1uewTe18j78uuaR8/dVXZu4hnc8CBxwguKTsef/9xTyA1LjWICq+hf7LLWfyAF6Ppa0gR3wAR+23nwFANOfnxPgAlguAQbWAkwIg8ma8JdEAMndjQzxxqaWEtHOkmqtW+9///pdrZHLufJCFDyB1C4lGjNMAPvLII9K5c2f5+GOWFt+QQO4d7PgABkk9CAAx05BaQ1O1JPFHCjL5RPWyJnTWY0oFQE2+rJASZwLmOD0G7Rn+Le45aC8AKOCSRlSrpiNBA0gVCHaipC6w05GwH1Uzpu2orQCowQRJNYAA4CfnnWdM9q4GkOfCb4jdNosIf7fv0UMeuOYaU4MXk9lSVqqHIB9ArqGaGhbM91u0kF2+/94AJ9fAkV+b3l8BMEhD5UJ9WP8DgGho7KQOmkQ5TAOIqVl9AMOift37pQFAu/Sbe51KmYDjNIBx0b363K5Gq5TZ1v0+k15DNYB2JYygczVrAJsYgDUNACYpBacAqN9cKQBI2Tzq1OZpArbTYaENZBwCzmzMiBqeb//9TfDU7vffbyK31Q9u6aWXNvMWwUj9Wrc2efImffut7FY45oorrpAz+/Y11g6+4xFXXCF9+/Y153Dd/1i1gEnDctu665oKXvze9QFMYgLG/xs3IJ5P83emBcDNC/OpHQSCUgFApBa8fs+sFchigQUWkNtuu00INK1G8yZgFsJ99zWRS5h4Se8Q1BDUTjvtJG3atJHJk9Gb+FbvAOgmT00LgMAXJYbCAJCJEVN1WBSwAp8mX9b/RwEg0MLv9Rg0BqS8cc/BZKTAFwSALHJAgRuNGgaAKqu0AHjIIYfI5+efb6K3mfzwh0Mrps0FwNW7d5cHJ00y8IYmYAlrkgcAp6+6qsx9910T4KGNlAuY0F0AtM2vKlv+xmRHlY8gAEz6VWMuYrEoFQCDInCD7h0GgFQoUZO1nhcVBVwNAFTNl/1eSQHQ/TaT9ot9nPt9Jr2GAqDtsxd0blIAZDPKd2pfL8oETLAKm0JNR6PfXCkm4HIA0K4EohpAW9unMnHzofJz3ADYDKARf6JjRxM4ufsDD5hIeRcA7xSRPsssIz/99JNc/c03JjKdYwj+Or13b+NbSO6NE8ePl/79+5u5DtPy/zkAeOs668iMGTPM790o4FIBkOAv3i/OBEyQB5vHNAAIaRDFTV+7ZSaTjtVyjwO6F14YFUI+LXcFURYaQGqCbrnlloImkB3GxhtvLMsuOy+//WeffSbPPvusKQNHjUNSxPzlL+wPfEMCuXdwCRpAnksL3UdpAF34SWsCRnsGfGlzNYBJAZCIP3b3tDgfQBZVTCsKfOyyWWDiAJDSdfjv0dAA4sBOJQxXBmgLWDR4DlsDqNGVChJJNYD4zH5xwQVFALSfk2cBAPma8C3i2gDg1EmTjLM2CwGLA02jgPEX4ssMA8D3FltMdsOUVHD4tuP1eSfM2yy+NCZ3FrSsWhoNIO+FpiOusXkgsjhJiwJAor+Rb6kNTQjj2W1upDXwgn8crRwAZIuNhrqc5n6fSa+lqY7YgJArMaxp4njqBl9a0LIFHcscwbMk9QEMA8BKawDtWtHqA5gUAFUOjA/MtzTeCzDkO/z8889lmWWWMd81Mu651FJCROqEr782+TA5huCv03r1MgCIc9bQCy+UAQMGFKOLf7IAkDQsNxeq7wRpADXlVlAQiPoABmkAbQBEg0+uR67P3/yffwPmNgDiUmPnAXSDQDjHXit4VyqnTJo0KdYKmXQMJz3Om4ALkiLHHw7rYSRO1n9qex58MLF8vqkEahUA9fmiANCNxEwLgO4ocNPA4DyMBhCoCmt8/AAJYEKLA0BNHq0gBQyy0LoA+AXmU+umWhaNHwGA7KhJsxIFgLhFdOnSpdG1gTUSUAOAarSIqgVMfs3F77hDiOoM0ma5ALjwllvKO489ZgCQhQC/HEKzLi6kTcGUTb8pzPI+mFtInYEGEFAFHNAgBWkAXQDN8ktOAoAsDuQ3DErCXO6zRAFgudcOO98FQPu4egVADXTAsZ+FPazZlYNI/xSWGwIrAdpI26Qc5QPInMGY1qTruukqBQDZPLCJKCUNjA2AqgEM0vYF/cyW2cACMJ1jgZENgFSk6bHkvIKWV371lfGNZa7A9/eUhgYDgMzNR44bJ0cMGmRMy6SXsQGQvprcsaOpOFIqAOL7SyCgbQJOqgHEFxj/4S0KJuA0AIjGGdeQpxdZxOQIrGTzJmBL2k888YTJ9zd16tRioAeJoSnsPmTIENl0U2oV+GZLIE8ABMbnm2++RgASJP0wMxnHRgGga4bLGgDZLbMoRMV58ewEXuB3lwQA0SZgTnKBL+r/rsyoRoEWjQUpDABZ3Fi4ACr72jg5U98yCADx08F0q0197thhs0sOA0C+KpzZWehIbYNmEr8qFgIWD61XS948tAluSS+NQlQAxKeRAA23kYj1khw/3yAAtKMm1RyX1yPUAwAGlXgLkgf9ZwcnlSIzvhM2THk1Il41H4SWGwy6FwY2/BHt/k9iAlZNZBQAxiWCdgGQ7wr3h6imUcBJATBIK+hen29WVSfMAy+++KKsv/76Zm7RgDL84S7/4osiAF5zzTVySo8exkqAxWLAOefI0MGDDUyT6eFnSwMIqE9q317eevNNYyHpVvDL3KEQyZ1EA0jidtYAGwBJccP7xZmAqQBEIB4m4CANYJAPoJYNZbNO8Az3RSakv9lgA3uLm9cIFuN32exNwK54UUWzQ6GhpgZCfAuWQJ4AeOSRRwplz+K0NmiyCKsPalEA6NZCzRoAeZ6gkl32c/LRA4gsDrQ4DWAWAIgfFtpBNHhuQmLX5Og+j0ZGMmlj0upeSKEQVB+Hc1ls8LkLejd+hoM3kyYLmQIge2B8dkiTAgBqMlr8foBAN3rWTv6Lj5GdIqga323YhgQncI2+rsZz5XHPKA2g+r7Z92XzQXmwqMZ4QeNkByeV8uzqBlLKuUnOsQEwysSuAGhfMwoA0ZSxaVIAVK17KYmgARMCJFQDmAYAmVOZW2lRJuAkAGi/uyZl5mfM7QSM7NuypcnGcennn5vvnm/o2muvlZO6dTMAiL/lfiNGyMlDhxpfOwDwJ6sSCBq4ie3aycy33zYaQspWYnVwATAoETQbSGRuAyCbUja6NgBGmYAVAINKwZFKCg2lHQRiW4sUAJkH8UO/e4klTCqdli21zlGS0VjaMdQnBrzzannygVlTsvABTPrygCHBInHpYpJerykcl2cHY3aPg784GWoy2KBF2c50z3XS5gF0762RdnHPZP/+KaLXIjSABxXMnyoHtHL4E5WjAWSHj08XPnauBpDFgslMWxjMqOxw9AbKghIZcC5+bmhaaUFBFzYAUj0DgENzg/kQDQS7eQVAN6o3jZwreWzSKh+VfKa87hUFgOr7Zt87iQaQscXGrVwABArwDcurkTyc3I+0qJQzbGb4vd0UAHFv0A0Sv2fsk5OOTWEnEXmp4COL20UaE7C+e9YAWIoJOEj+bNIAWr5pgk12mX9+kxZm/GefmQTpzB24oJzYpYvZJALbPU89VUYOG2by8rkAyHte2batvD9zppFhQyEtkwuABE+xWVXrBPMoQRi4kOCrxzzG74IAkM0oIB3kA4imlecKSgOTFABtTWCLFi1kypQpJjYhz+ZNwCmk+8knn5hoJhwnfZsngbwA8Pnnn5dtN9oo0PG8FNkHgYxdHYNrpi0F5z6HbeZI84yae49zgp7T/pnunssBQPzjuA47bdfZ3gVA/PBIWRLW7LQf7jE8t07A/C4ICPg5NUbR+NCIGsShXtsTBQ0h/0+T2DeN/P2xpUsgCgCDNF9JKnwABIDG3qU/ljkTrU7jop5lXrDE04PqMCsAutYLVhb8gdHEKwACI2wUgwAwzATsAqDOTUk0gJqD0dYAqg+gm/wekcT5AMaJDbhV5yo2pGwomTvItjF8331NKTj85DoPHy5jTznFBIwBgD926WIgkbkQC8olK68ss99/32yQ+T3aZlJEsaEgITiaQ2CMgBIbAFUDGASAlJrkfnEmYO6PHHgPfJDj0sDYGsAvCxYZBUD6jnuS2WDs2LGAvr90AAAgAElEQVRCKq28rJA//vij0bzm1fLiA33eTDWAs2fPlmnTpgllaoIgj8S4hx9+uAdAa7Tk1cGU59t56lRjCsmiBYGVDRfcwzbplHJPAhWoK5u26WLAeXEAqOkMogAw7j3wr0LDxkTrmq7SRJ3yvHbUp/velFHCk0U1HPjhBLk4E0VJiTmanXoirRz98ZWXQBQABvV3kvQuaH5ZTJPUSq78G6e/I5ojrAN20wodBARhqrab1vHVsosKgFrWzT5WE0G7clXNn4KgAmCaSiBTRWS7ws0UAIPK65ULgNwCzRlBGDwn4M88eOONN8qwf/7TACD+vXsed5z864wzBGDCjeAnCwCR50UrrSQff/ih8RHE1YJgNwCb8aT5/GwzL/dlHmX+Ba5tOFQNoA2AYSZg+oU/mMKDADBOA6gAaAfq8WyYhNEA79m1qxCkSum8rJs3AaO6/f576dWrl6kFHNUISsAsWU0N4HXXXScjR440KWnIWdinTx85/vjjE9vxyz3flU9eAEjATZenny6mlCh34AeBlTtxaemlUu9lm4TSXEOTwnJOHACqM3MUAAKhwGhYY5fN+ZjY2H3bSY1sbWSSd2CXSsRbWCNaj4mYBhCygNRT0wW2np65Vp6VhZyxZjfKOMaZdgEiNFtxx9XKe8Y9h52CyT02CAAxWwNuWnZRzwnyAdQgozAAVNC8iHJr5OSzNOphz61BICRM36ZwUKlpYOJkE/Z71dBRDxkfXyKi/3b00XLF2WcbawEA+GPnznLDDTcUU7Gcv+KK8tns2SbghgokVxQAlvGEzzNjyo705d7Mg5jbAThbAwiQIisbAIn0BuRdEzAyBiDpC+ZSklDbUcBxAKiaPxcAeT6eS6/9zDPPmBR1WTZvAubDOOggGT9+vKkJvOGGGxpfhAUXtDO8zRM5JeDYlVQLAC+55BKThoZBv/fee8srr7xiIpTRlhExFdfKPT/o+nkB4GabbSadn3oqMwCMkw2/V6frJMcGHVMqAOL7RlZ4WpDjPAl/8V2hqSnDBkAmKUBFWxwAss1hl4ypYlrhvfVcchLig5S0xfk92jVd3QUt6T38cU1HAlHVSvQtAQ9qLbGQNvWGiwQaKrvpPOKajqm3i7nSbqqRc03rqgHkW+abVusEgQ3ATVSLAsCgWsBZaADd50HzBZgBTwAg5vBV99pLnrzlFjM2XADkPccuv7x8OWeO8bekUgiVoPCxZDyR9QBwtMu9cU/mUdxe8OGzf6cAqODIceQwxHeRfwPURDWr+Zm+YQ4OA0CigAFS3eDb82YUAOL/iPkbdwp8G3ffc0+THzGrABFvAia1RJs2svPOO8vll18eWRePEnD4ABIMUumGWXqVVVaRPQsDQO8PuB544IGmislf/6oxW79/unLPD3vfvACQZNtdn3mmogAY5GOTpp+zSF5rw2DQvckezyRia9K0eocez06fCaqUpjn1kp6bxKSU9Fr+uKYvgSSpWcj1iKM+udF8+00CSauocIamf1EXDYVKV+MfJF8FQFw3ACiaagArBYDuc2lQh1YS4v8/7ruv8RMEwgCwUcstJ9988olxMyHlE77EmlJqxUJe0DcLEcW2DyBwhtkd2OpQmF+pokQ1JdJO4ebAPZgbsXjwb9JJEQDEv5E1QSSayaBrgAbQBcAgH8AgDaDtc0m/YC1CGYBvIMqgcv33qL4SpOzK6rvLiw/0+TLxAVx00UXl6aeflnXXRdEc3v773/8ap9PevTFsVbZdfPHFRlN50003Ge2fNiqVULWkW7duJpN4WCv3/LDr5tXBaGJ7vPBCpHmx3B5w86ZR3ot0A9VsJFUOSqmiz8QOlEjZqBanAYw6V0s4VVMG/t5eAl4Cv5dA0vrRnKl+hOpTq6b3NBpAe3OnABjkEpGHBjCs//U9mAPZLNMUAEcutZT858svTbAYcyDQqwBIdC8puUgpg4+0DYBoSzG7sx7ga8jvsAahhSRgBODiHhoswr/RLqJl5N+Y5tFA4ssXpAHE7Awkco5qAO2NvvoAqp+l/e5BPpcEuBBNz72POeYYOfnkk2WRRfAOT9+8CZjOXm89Y1ZdYw2GRm22Hj16GMB78803ZfXVG2MKJeyIEiKIJayVe37YdfMCQHY2I3/6KVcADIpoq83e90/lJeAl4CWQXALqR5j8jN+OVA0gkccanatwEgSAQZBSyn1LOYdAIdIuEfENoJG3j2dUH0A1AbcTEUq92Vo+hUcieAl+wx0GFRCQtlEhKT0rLaZhYEtLxvHvCYVqJPwbLSuAhykX4CRzAscq7AGeAPll1s/s7AlqAg4CwCi4RqsIeGpg3YMPPijbbadhO8mk6TWA2OavuEKmT59ukg5HNZJDb7LJJjJzJkxf2cZ9qUn87bffyuKLE9P0WyNrOJnV586dK1QuCWrlnl9pAMwiB2Ble8jfzUvAS8BLoP4loKZI20KiIBIEe1E5ECstDTvIhTTKRNKStB4/OrR/tp8fmRBwSVATsK0BVB9ANIJAI+l5NFgE6MPWRrJp/o0/H1pEfBNxwtq24FeoAAjYYVnBhK+pkTQxN/JReasm0JZZUu0qAVOAsPFpHDbMBKsmabAEyiGUSHm0vBRE+qyZmIA/+OADOeOMM+S9996Tfv36Sbt27WTppZf+nRA//fRTwTetGkEg7Slz89ZbQtj2/PMzdH9rJIt8/PHHTWRwWEeWcz7lYvgT1NZcc02THDvLhnzJTm4HOmR5/aZyLTtNQ1N5J/8eXgJeAl4CeUiAbATqvEXQHflHCQAhShh4Oq9wU0q0oQHkWFxu8AEk0vceEbmzYHpGm8jxaPKmF2p7k04GMy/pe/hju9MQeEfeVa0vHefqU+r7E/CDBjTp2klanK833FCeew6Px+xbXQAg5tOkxIyIqgmA3NtNCrnVVlvJY489lggASzn/pJNOMn4GQY1nyWv3wP3QeGYV8ZT98I6+on/2Skt83v3qWe71/vz1LPt6fnY/bqoz13i5R8udGIUw5VEWPZaJBhCIgVRdzZr7gMATfnbVAEDy/0Dp3333nVAmxm5qAiafIbkBg1o550dpACkknVcxaSbkVq1aCQm46w0C/bNn8Xmnv0Y9y10XEz/m0/d7uWf4cVOuBEs/v55l75+99H7P4szMAJAUL0TTRrVqpoHp3r27KY4dFARCahoaJuCwVu75WXRW2mv4jyutxLI53ss9GzmWchUv+1KkVv459Sx3v3Eov/9LvUI9j5t6fnbtr0wAcMcddzQJntl5RzUENmjQIBM0Uul20UUXmbw/YWlgunbtagAxrJV7fqXft94nNbSmI0aMkKFDh+amIc2rT+p5Yqhnufsxn9eIjr9uPY953q6ex309y97LPf7byvOITAAwzwfM6tpffPGFrLrqqrLXXnuZTODaNBH0vffeK4Cstk8++aRRRZO052f13OVcp54nhnLeu9rnerlXrwe87Ksjey/36si93jc91ZNa+XduCmO+ogBYzTQwdDdavEMOOaRYCu7VV1811T+23XbbRto/IoK33npr2WmnnWTKlCnFkZL0/PKHVjZXaAoDNBtJVPYqXu6Vlbd9Ny/76sjey706cvcA6OVejgQyB0DSrAB61MhzWzXTwOizkAz6zDPPlDlz5picf1QlOeGEExqVc5kxY4ZJCLnPPvsIFUDsluT8cjoky3P9pJylNJNfy8s9uayyPtLLPmuJJruel3syOeVxlJd9HlKNv2ZTkHtmAEhwxeDBg+W+++4LhD9bnNWIAo7vzqZ3RD37V9Rzb3i5V6/3vOyrI3sv9+rInbt62VdH9k1B7pkA4Pvvvy+kUvn666+FiFqiafmbZMQ0/OmoA8z/SRdTjUog1Rki/q5eAl4CXgJeAl4CXgJeArUngUwAsH///iaRMoEUAB7lUaZNmyZt27Y1b/zrr7/KrbfeKgcccICJFt5mm21qTxL+ibwEvAS8BLwEvAS8BLwEmokEMgFAomvPOecc4zNHcwFQZUn6l8mTJ8tdd93VTMTrX9NLwEvAS8BLwEvAS8BLoPYkkAkALrLIIkJErWr8qDrx7LPPyhprrNHojd955x1TC5ggEd+8BLwEvAS8BLwEvAS8BLwEqiOBTACwTZs28sgjj0j79u3NW6y44opyySWXyK677trorR5++GGTWiXP2nbVEaO/q5eAl4CXgJeAl4CXgJdA/UggEwDcfPPNpUePHjJw4EDz5jvssIMJ+rjnnnuKtXWpwQsQfvDBB0LQiG9eAl4CXgJeAl4CXgJeAl4C1ZFAJgB48skny9lnny0jR440iZYvu+wyE/BBbeBNN93UvNkTTzwhVNPg9+PGjavO24bc9aGHHjJ5/7SRG/DKK69M/Iz/+c9/jA8kpeTee+89k1+wY8eOcuihh0rnzp2F3IgkkUYrSgQ00dDt2rWTvn37yoABAxLfxx/oJeAl4CXgJeAl4CXgJZCFBDIBQHIAHnbYYbLccsvJVVddZaJ+99xzT7njjjsaPeO6665rTMX4CNZSI2n1l19+Kddff70cfvjhJjm0DYCUjgPmzj//fOnZs+fvHp3jOeaUU06Rbt26mSTTDQ0NBiq5zoknnmh+Ry1iaiF///33BpCRA/Dpm5eAl4CXgJeAl4CXgJdAJSWQCQCGPfBNN90k+P2R+HmTTTYxcLTQQgtV8v1S3QtYQyvnAuBuu+1mIpf524Xar776ytQMXmmllYx5W9sNN9wgc+fONddbYokl5IcffpBvvvlGFl10UXPIgw8+KM8//7wcffTRqZ7RH+wl4CXgJeAl4CXgJeAlUK4EcgXAch+u0ueHAeDdd98tw4cPl9NOO80Esdjt6aefNmbuLbbYwuRCdBtJsAmSITBm1qxZlX4lfz8vAS8BLwEvAS8BLwEvgd9JIDcAxC/uD3/4g5Aipl5aGABGPb/6D5LcOsici08geRJXXnll4x/om5eAl4CXgJeAl4CXgJdAtSWQKQBi7iXAg78pC0fD/LntttsaH8FaqQBCxZLTTz/dmGAJyNhoo42Mnx55Cm0TsMKbdpINee7v3I7EDxIADmvvvvuurLLKKtXuf39/LwEvAS8BLwEvAS+BZiiBzABwyJAhJhIY8AlqwNAxxxwjI0aMqKqY0fL169fPaOTOPfdcITAF8OP5O3ToIBMnTiz6AOK7+Nlnn5kIZqqc2ADo/m6zzTaTm2++ufhumH0//vhj+fDDD43/IyXySI6trXXr1jL//PNXVRb+5l4CXgJeAl4CXgJeAs1TApkAIJG/aM6WWWYZE/2KRg3AoQFQzz33nFx99dUmDQzl4Hr16lUVaeODR3USchS+9NJLss466xSf49NPPzUaOUzXbhBIlJnXm4Cr0pX+pl4CXgJeAl4CXgJeAmVIIBMA3HDDDY2v35QpU0JTvBABu8suu5gqIJheq9HIV3jSSSfJ1ltvbczUbgNMbQ2g/t4DYDV6y9/TS8BLwEvAS8BLwEsgLwlkAoAkPsavbsstt4x8zkcffVR23nlnkxKlGu2vf/2rSb9y5JFHyqhRo373CGeccYYcf/zxXgNYjc7x9/QS8BLwEvAS8BLwEqiYBDIBQMy9L7zwgsmFF9Xwh+vUqZMxBVej4eP3xhtvCKA3dOjQ3z3C5ZdfLvvtt58HwGp0jr+nl4CXgJeAl4CXgJdAxSSQCQDuvffe0qdPH9ljjz0iH/y2226T8847T+67776KvaB9IwVAAlEI+nAb/okEiHgfwKp0j7+pl4CXgJeAl4CXgJdAhSSQCQC+9tprpsrHpEmTZM011wx89Lfeekt23313ufjii6uWDkZNwEcccYSMHj36d89JVDCl2jwAVmj0+dt4CXgJeAl4CXgJeAlURQKpAZCatkHtlVdekRtvvNEEWHTs2FGWXXZZkwePurczZswwSZJJh7LDDjuYqhrVaDw7+f7CgkCoz3vppZd6AKxG5/h7egl4CXgJeAl4CXgJVEwCqQFwvvnmM2Bn5/vThMdhOQDtt+FYcuhVo82ePdukgSHVy7Rp02TttdcuPgZ+iauvvrpQ29drAKvRO/6eXgJeAl4CXgJeAl4ClZJASQB41FFHSYsWLVI/43fffSdjxoypGgDywJrmRRNBr7feejJz5kwZPHiwEM1MpHLnzp1NRZNFF13UwKImgtZkz/yc97eTRNuJoFu1amXODUsEzbmlyC+1wP0JXgJeAl4CXgJeAl4CXgIBEigJAAEbTLxpG+etsMIK8ssvv6Q9NdPj77//fjn11FNNgmo0kiSExi+Q9DQktNbWpUsXuf766393bzSE5BOkxm9QI5iEoJiwUnCYoTnfNy8BLwEvAS8BLwEvAS+BakggNQCiGTvwwANN4ue0DW3a+PHjTaCFb14CXgJeAl4CXgJeAl4CXgLVkUBqAAx6zLZt25ofL7XUUkar5puXgJeAl4CXgJeAl4CXgJdA7UogEwAkMGSLLbaQ4447zpR7881LwEvAS8BLwEvAS8BLwEugdiWQCQAS8EB937AcgLX7+v7JvAS8BLwEvAS8BLwEvASanwQyAcC11lrL5AAk/19U++9//ys33HCD9OrVK3NJX3fddTJy5Ej56KOPZLHFFjNBGNT1XWCBBRLdK+35BLIQ0cw9qCrigzoSidkf5CXgJeAl4CXgJeAlUAMSyAQAR40aZcCLv6PaJ598YqKAs84DeMkll8jBBx9s4JKydCSlJuH09ttvL9dcc02smNOe/9577xnAfPfdd+WDDz4wyaU9AMaK2R/gJeAl4CXgJeAl4CVQIxLIBAB5FwDs66+/loEDBwo1d5dZZpnfvWIeAEji5lVWWUX23HNPmTBhQvGeRBsTrUzKF0rAhbVSzid3IFrM9ddf31zbA2CNjGb/GF4CXgJeAl4CXgJeAokkkAkAzj///IlupgdlqQGktvBBBx0kN910k9H+aSNJM7kKtUZx2AOWcv6sWbPkT3/6kylvt91223kATNX7/mAvAS8BLwEvAS8BL4FqSyATACQKOGnLuhRcjx49ZNKkSfLmm2+aUm52W3755YVnowRcWCvnfA+ASXvdH+cl4CXgJeAl4CXgJVBLEsgEANEAzpkzJ7Y6CJVAVlxxxUx9ADfZZBN59tln5dtvv5XFF1+8kWw32GADefHFF2Xu3LmmzFtQK+d8D4C1NJT9s3gJeAl4CXgJeAl4CSSVQCYAiObt6aefNomgoxr+dphpp06dmvT5Yo9r3769vPXWW/Lzzz+La4recsst5fHHHzcBKmgDg1o55ycFwP/7v/8T/gQ1fCVLKasXKxh/gJdAmRJgU0e0O5u2sPb999+bqPuwsodlPoI/3UvAS8BLoNlKAFe2MHbIQiiZAGAWD1LqNRTg8Ct0TdFbbbWVPPbYY4kAsJTzkwIgEcInn3xy4CuitSQ4RtPVALL8+9dffzWa0gUXXNAswvpv/ub/Cy20kIFe/fdPP/1kzll44YXlxx9/LP77m2++MWX7+EMaHlrYvzmXwcZizvX13zwD10S+PJv+G+DmvvzN7/TfnK/vwf2yfif9IGr5ndA6I8Ok/VSL79SmTRujWadGNmMgaOyhWb/gggtMDW137FXrnYDSFi1amLHeHMde2jkiq35irDAe/BwxL/VYJccec/sSSyxRnOP9XD6fWZfyXp8ob9uqVatGa25W3xPrLMo1Yg7yarkA4KeffmrSowACK620Uq4aro033tiUn/vuu++Kk74KS03AqqUIEmI55ycFwCgNIMmz8+xgoNBrZ/L6fMKv2xTkzsTGos67hDXGFhH3BxxwQOWFHHLHpiD7mhFmigfxck8hrIwP9bLPWKAJL5e33Ak2zZMPMgXAm2++WU499VSZPn16I/GRNuWEE05oFKWbUL6xh3Xv3l2uvfbawCAQcg7SMAGHtXLOTwqAUS+RdwezQ6FSi2+VlUBTkDsaBTTI9QaATUH2lR2t2dzNyz0bOZZyFS/7UqRW/jl5yz1vPsgMAKmIQSWOsMUCTQEVM04//fTypW5d4aKLLjI5CMPSwHTt2tUAYlgr53wPgJl2ZZO6WN4TQyWE5QGwElJuOvdoCmO+lnoD9x7brenBBx+UwYMHywsvvPC7x/Syr07P5S33ugDAKVOmyG677WYSIw8YMEAwq7Zu3dr0CE6MROniJzRt2jS56667ZOedd86st7744gtZddVVZa+99gpMBH3vvffKjjvuWLwf/nYEq+DTREt7vv3g9QCA7iSSmeD9hSIl0BTknhQAqaSz//7718yIaAqyrxlhpngQL/cUwkpwKEqTZ555xqynNNwsLr300kAli5d9AoHmcEjecq8LANx1110NUGECDksKjWMyEcA4ZQKBWTa0eIccckixFNyrr75qKnRsu+22jbR/RARvvfXWstNOOwnQqi3p+e4z1wMA5r1DybIfm9K1moLc6xUAm4Ls6/Fb8HLPttcAQGrUd+nSJRYAveyzlX3Sq+Ut97oAQLR9QJ3uVMKEx24GWPz888+TyjfxcSSDPvPMM00+QiLRevfubfwOVdPHhWbMmGEqd+yzzz5CBRC7JTlfj+c+Y8aMMZE/pLYhDQZRh3/5y1/k1ltvTfzMHJh3BxMdRrSsb5WVQFOQ+5JLLmnKO8b5ANaaBrApyL6yozWbu3m5ZyNHvUoaAPSyz1b2Sa+Wt9zz5oNMfAABDHLxEfEb1T788EMT1qzpSJIKuSkfl3cH562ibsp9U867NQW51ysANgXZlzP2qnWul3u2kncBEDeLyy67zJuAsxVzWVfLe8znzQeZAGDbtm3lrLPOkn/+85+Rwpw8ebIce+yxMnPmzLKE3pROzruD81ZRN6W+yPJdmoLc8ZVFw11vGsCmIPssx2KlruXlnq2kAcDrr79eOnfubC4cBYBe9tnKPunV8pZ73nyQCQAShXvHHXfI7bffLp06dQqUHSXZ9thjD/OHgBDf5kkg7w7OW0Xt+zFYAk1B7vUKgE1B9vX4XXm5J+s1/OFptr/8888/L6QtsytWuQAYFQTiZZ9M9lkflbfc8+aDTAAQ0+66665rkjFvvvnmxhdQy5uRFJoo4CeeeEJatmxpIoHjTMVZd1ItXy/vDmayCQvMqWW51PuzNQW51ysANgXZ1+P493JP1msdOnQQ3CuefPLJ4gnAHusmfvLa0mgAveyTyT7ro/KWe958kAkAIlQibAmuAPjcyhOYkJZbbjm58cYbZYsttsi6D+r6enl3cN4q6roWfo4P3xTknhQASU2x33775SjNdJduCrJP98a1cXRzkvugQYNMeU8i5dM2XR9t1wp+RlWoV155pSQAbE6yTyvvPI/PW+5580FmAIiQqRrAYnDfffeZUnC0lVde2eThY4GgtJRvjSWQdwdTho66kL5VVgKlyp0awkSV10JLCoC1FgVcquxrQeb1/AzNSe4AG5kjunXrlrrL8gDA5iT71ALP8YS85Z43H2QKgDnKucleOu8OzltF3WQ7pswXK1XuLA633Xab7L777mU+QfmnL7300vLll1+WFQRCWiZSyXTs2LH8B0p4hVJln/Dy/rAQCTQnudcaADYn2dfSB5i33PPmAw+AVR5NeXdw3irqKouvZm9fqtxZWMaOHSuYmKrdkgJglAm4Xbt28s4770RCZNbvWarss36O5na95iT3pAB40kknmVrsZL/QlkYDeMMNN8i+++5rTvVRwLX3ReU95vPmg0wA8OeffzZBHjTy/Gkk00cffWQGPhHAmIKHDx9ukiX79psE8u7gvFXUWfQldZxJIRSVbiSL++R1DYKgyNh/9NFHF29RqtybGgAmySWYdb+UKvusn6O5Xa85yZ3vlBrz1JqPamGwxzlZ+gA2J9nX0neVt9zz5oNMAPDOO+80JisKV6MN6NOnjyn5ttFGG8nLL79cHOjshF566SUDib7Nk0DeHQycL7DAAjUt7uOPP17OOOOMWADkGCrOPPbYYzX1Poceeqicf/75jZ6/VLmzYIwbN04OO+ywqr9jFhrAJOXksn7RUmWf9XM0t+s1J7nXGgA2J9nX0neVt9zz5oNMABDge+GFF8zizAPT2B316NHD+P6MHz/elE078MADZfvttxdq7/pWGQDMW0WdRT8ed9xxMmLEiFgARItMcFGtaQqpQ01uS/u5SpV7LQHgMsssI1988UWsDyDVCfr16xc4FLIAwIkTJxoNMRvIJK1U2Se5tj8mXALNSe6VAkDbBEwg5eWXXx74PTYn2dfSN5i33OsCANdee21Th3e33XYr9s3f/vY3Ew187733yl//+lfzc0x91Od97bXXaqkPq/oseXcw4L3QQgtV9R3jbp4UAP/85z8L5tZ6AMBS5V6PABjlAxhnAsZNZMUVV4yFTGp39+/fP24omd+XKvtEF/cHhUqgOcm91gBQZQ+QzJ49W/C99S1/CeQ95vPmg0w0gC1atDD5i9DQ0EgI3bp1a2nTpo289957xV6gBNx6661nft+cG34D/KGR+2nWrFm5iSNvFXUWD14NAPz444+Nr2oWMBmkASxV7s0NAB999FHZeuutYwEQKwKVEJK0UmWf5Nr+mHAJNCe5u3V6w6SSxgcQa9mrr75avBTnJtUAquwPOuggYbOUxbzmx3q8BPIe83UBgCykaPrWWWcdI7EJEyYYP8AjjjhCRo0aVZTi66+/LltuuaV8/vnn8ZJtwkcQGUYSUdriiy8u3377bW5vm7eKOurB2R1NmTJF9txzz8j3qwYAPvzww7LttttmMlE2dxNwORrAPACwmmM+tw+5Di7cnOReKQCcPHmycX+gBZmAf/nlF1N4gZJkuEgw15JGygNgZT6YvMd8XQAgC+kmm2wiZ511lhmI/BuNICXgNthgg2JPAIajR482gSDNuVVSA5i3ijqqH6+66iqzEYibjKoBgA899JBst912sc+WZJwOHDhQLrzwwkbXKlXuTObnnnuuEFhS7YYWn81aVP/xvOX4ABLQs9VWW8XeI40GsFTZh8k76+tVu1/zun9zklZm118AACAASURBVJNbpi0LDWBQJZA4DaBaDND84eqz1157ya233prJvJbXOGlK1817zNcFALJL6dKli+ALSOJY/Hoo+cbunoaQKBXXu3dv+fvf/24WS9/mSSDvDiYae8EFF6yKuNEMYbaLA8ChQ4fKyJEjY4+jhjTm8rjrJXnZvAGwVLk3VwBUTUZQ3yGTNNVGSpV90L2z1BQnGZf1fExaufMdA/b4drrlQ2tdDnkAYJwJmECrK6644nfpY7p37y5XXnmlmec9AFZ25KQd82mfLm8+yMQHkJdCi0MCWzSA6667rvz73/+WVVdd1bwvEICWgMbCi8+Pb5UBwLxV1FH92BQAEF9BTCtRZQyDNIClyr2WAHDZZZeVzz77LFY7F6UBjAsCYWOIW0iWAFiq7IPGMu9GAt4sNh1Nfc5LK3cCugjsev/9983f9dQqBYC2CTgMAMm2wQaJeeof//iH3HLLLX68VmgwpR3zaR+rbgCQF8O0+f333wv5w+yGVlADPzRQJK0gmurxeXdw3juUpg6ATPRsaKZNmxb6qgMGDJB//etfjSbdUuXe1AAwLg2MAiAllcgjWmsaQA+AyWfetGMebT5afQIF3XUBBcLOO+8sf/zjH5M/QAWPDAJAxjLvY8NsmiCQIBNwnA8g1wcA0QyiAfQAWMFBIGLyHedpYcubDzLTAFZW7E3nbnl3cN4DtBYBkAAbUg+hWQprSU3ATLCLLLKIsNMLa1kD4HnnnScEllS7ZaEBTAqARNPNP//8NQeASbXY1e6rWrh/2rmGdCXMf0EAyHd3zjnnyFFHHVWxV1tuueXktNNOSxRt7kbo8pD8jEDI6dOnF585DQAGmYCTagDLAUDSt+GCo0GcFRN4E7hR2jGf9pXz5oPMAZDEsZSFY3fH4CfH1+abb/47rWBaQTTV4/Pu4LxV1FH9glkC/54489mQIUNMHsm445AVi0bccYw7xhw78koA4MEHH2ySm2eVCLo5ASBzBf7CWQKgO+YZD2iU8I9K2+IAcO7cucZ8TTR/c29p5xrNAfnuu+/KKqus0kh89BlBhXZ5RfuAGTNmGNP8008/nZnYueeuu+4qVLaKa2EAuMYaawjZLrRVAgAbGhqMLyUm4L333tuM9bg50n4/nhE/bCot+ZZOAmnHfLqr5x8jkBkAfvXVV2a3ds0115jJ3G6UIkNNTUoYfIJ8+00CeQNg3juUqL5kUqL6S9xkVA0AnDp1qqlKE/dsTI4LL7yw8W0NazYAYsokyh2zcSmmAe7XHAGQcRpWsrDcIBDOp7QeJfbStjgAbN++vamWwp+4xjvyLLVemjHuPcJ+HzbX4BqEG5DWiNfz58yZIyussIKQH1b9xW1wYlN4zDHHBN7ulFNOkRNPPDHy+yW9Fr67QHoSUzJ9gzbsjjvuKN6TZ0ejt/HGG/8OUG3tHL/k/HIAMM4EHOYD2LNnT+Njz3xDyhgKLsTNay4AHnvssUYL6Fs6CeS9vubNB5kA4Ndff23MbZrEkgVzqaWWMpLkw7eTHpP2AbOQb/MkkHcH5x2m3hwAkIkVOdLeeOMNo61gjGuzAZAkrKRkYMy7FVj4TuLGfqUAkOAOFpTbb789tAsxiX366aexQSCUp+rbt2/gdeJMwKoBRL5hwIxMonIN8vtJkyZJt27dzDO4Yz5PAAzS8IQJtG3btiY5Pu/cFFvYXBMUJMX7azL2d955R5CNNoWYIADEvYOxi3tCHAAClquttpq5D2M5rtGXZKmwv4lTTz1Vhg8f/rtvgGOzBsBSTcAAIN8H803nzp3Nc6UFQEAbefuWTgJ5r69580EmADho0CCjtSDal48dXwJ7YkRdf/7555tByk6caGHfKgOAeauomxsAMq7d3bKdff/ss882WosffvihUe1agBBfwiBzly3DSgHgddddZ4ApaqGoBAA++eSTxlxfLgCSbxI/KFqQCTgvDWAcAJILFQhhQxx3bL3PiWFzDWZVEsK7Y00B8O233zYbYbTylBBVOQUBoP4OEIwDQK67+uqryyeffGKAMa4FASDfOqZo99krBYA33nij7LPPPubRozSAbDwxAXft2lWuv/761ACIqZ339C2dBPJeX+sCAIl8YhcS50OAqQ8TMeH/vlUGAPMuVZMGADHHAEhuTdekJmD8SfEbitvdJvEBfPDBB02gSFT6Ed5NTXao+vX/TMSa1oif2QDIJMqiYZs0yX9JUAcJ0l988UXp1KlTqNi4H5slNlJ5tmuvvVbIH1YrABikMdX3T6IBtAHQHfOV0ADyrCpLe1Hg3kRm3nzzzU0eAIPmmrfeekswk9vy0X4FzNCI4jJBzliSnyPDJABINSX+RI1fBUC02CQ1j2vcd/fddzeVNLSFzU21BIC9evUy85G6WqENV7mwsdpll13krrvuKlotcNVijlIo5l34GUE3cY01nkTTWfpext2zln+f9/paFwDIzoM0Gfqhh3XYm2++aXyjovyparmz83i2vDuYCUDNlWGTJRCE/8kzzzwjLVu2zOw1XR/AoAmWm4Xtst0HSQOAm222WaSpLQ0Akp4E374gAHzggQdkhx12KC5waC1YNGyg4b3xhWSXDgAi52222cb4C7ktCQBiQqTCDhrFUlutASBzgm1Wt98rLQAGmYAPP/xwGTNmTCNxAelULIoC8rA0MPg0k88U+NfG96V+bep3xrPvuOOOplRmU9cABpnDNtpoI3n++ecDARAwQ8u8xx57mO8BCAkDwHvuucfIUSPFbQDEooTpk6TdgJ5+j6UAIM8C4GgLS1IfBoCsgbiJaAvq87CfBZmAbQ0gbhYkfLbnca4FABJwhwmYf0+cOLF4TFCgDefgD4tWXOe0I488slHZ1rB5BVM9Voy4TXip81K9nedNwCLSrl07o+JH3R7V+CBxvP/ggw8y62dMWTivMtAXW2wxU3rs+OOPT+xonfb8tMfHvWjeAIg2Qh2gwz5aFkImj+eee0423HDD4iMDhvSVG6GHzw67TTd3F5HfvI82BUB839D+MfEwwZKolHyRGjmZFABxGGeBdd+DZ2SXy2KuE1pcFHBWAKh5t7gvz6UAaJuAbQBE2wFwhEUb6uRMhKP2G/1A36BB1PdjAcQEVmpDSwDERE3kaGfQ0sSVgivHB/Cpp54SYD0NAOLc36JFi2LeQGRmawBJLMyzK1Dye+qSU4bSbgAhC1/U+9lBIFyHTSzzHP/G8mFbM7jOa6+9ZjZT9pgHSO67776qACD35lu9++67Sx0qjc7jG2O+BTLchrYPrZKdNJ355IUXXjCHKhSzmeI6BIVw/E477WT+DB48OBQAkff9999fhDvGPmZgBUbORYNlb9ZU+4jP4DLLLBP7/jo/2QAYVqaSY2040++yGgCIhYE8pChi+A4owaljOsjPkmcHmnHd0ucO+j6CBIY7A76VSQCQ42zfztgOqMMDvAlYRIYNG2YAgr+jGjmWALWsSsGx68EBn3qJhL8zqTDhAZmYmuNa2vPTHh93f36fNwCiolbnep0sWXT/8pe/FB9PtYQ8C5BBFBmNhZ0C5EH+L/S3Bvdw7DfffGMCHIBANHU0DYjQnS0TD8XK6R8mH72uAiAO2Ey+mhAY8CFqnB0nPlQKgExwuBzoTprFiJ2vXo+fJwXAqATEOjlyPZ5F/2+bgF0AZHFEa2CbgF0N4Prrr98IAIFFFke0F/pO3EvfB/MhfkD2+5Xrs8P3QfqIWgFAJtIwjabKRKNF+T9RoGh9GLPAIJokInE10pZFEW2J9hkbBE3vodcDIriOLQMCAAB04I7mAiDmQcyEXMP9dm0AZHPDhleDD2zNFtdlfGL2DEp+ffXVVxtfLjda+JFHHpG11lorVUqtIG0TY43NctrG9w4QAdJB44Z7uZGsaKrRemtDfmzYcIkAzBjzbIaoy82YtuXEucCj/gwlA/1IcwGQc3EvKRcAmZ/YoGo74YQT5PTTTw+cAysNgGE+gIx1xinjxT1GtazAMIoa/R7oQ6BP/898nMQ3n80P41r7H60kQTJuFLfCd9TGLu34q8XjvQm4UAGEHFsEf+C75GqG0NqgDWIhQ/PiVgoppWNJO4Nmig92woQJxUuo1ondIj5eYS3t+WmPT/pOeQOgBh8oUDBJk44HzYc2PlJ2j9r048bfA22qPdm719NzNDJPNST8nNx4ALp9b4CJRdHOm6cAyHG25kzBFJMpaRgUADmOXFtqQg0CQI5hLOJPp41FhgV/q622EjXdJgFAfX6dLIFiJlxaGADaEx8yx1TIO7MYugBIxQNMhC4kqNwBXnb2NgDyDgBBqQ3IAKKjABANDRoE9xi+YVJlsIjwbgRf8HxBLS4KWDWA2u+aVoF7Yn5F1gpJ5557rvET457UHsfZ3W2YATEn0lSjrRCENgqtoOaHDAJAPZbUH9Q2Z1FULSG/Aw7Q8gA6jEc2tNoAWPpZF1I2LWRBsMe//bzMi2gq3cZ9MHmiFePfBJJgSuXfQG/Qe+s1+GYAAWQWpP3Xb12vHzZ+AFS0xLb2n/sDETYA2OcHwSZjHa23NrSuVIUCGhQAmcPJBUnwlPsN2LJDi0mQCI3zFd7tTRPvrRtETLHMEWk0gC4Ach8igYM2wUEACCAxB2oLkknYz0o1AQOAbLYZ2wRiMjfp837++ecGspGFumhxfzvHIv9PGiSFPHk/ey5CPoCy3XAJYyMVlIIHKIUBMOczDhlr9ZpHk/UwzHWl1LnZPi9vPkgdBRym0kVDouYQBIJqn4GFqU8nQX6GWQsTYrlNtUtoq9D+aVMQIcKRCSyspT0/7fFJ3y/vDnYXgSAA5CNFi6JNP+4RI0aYHb89+alfjU7M/M01gXv6IQgAVYPG32iyMMcgT72uJi/lWvaEoYsVwMqxmHgAEhqmtg4dOph/u9qsIC2aPicTJJsE13dP352JDH8xNRm5kzX/Z2Fm4qKFAaBrAo4CQLRNaE7DAND1Q3OfiW8PGTLew/Kd0W+qAeC5ywFA4JN0Tvq8zAlo3ulTtykAor1Bbq7GCzMe5mz6nQVeNZ3METwvi4U6q6vZKgoA8ctTMFZtlD0e7HHLfbk/jTGBxgnQohGoxDxGdgMaG0C00WxoMLfRAGQgzm4ssjYA6O8AH9W46M/ColN5XrSVaMb4t/Yrm2zNU4cTPnCFJh7Z4rsLROlmg2cM+g7YpL/88svmffkWeH6ejc0ywKr57jgXS41u4PT7cecI+92DwGa99dZrVBmDe2HCB74VAOlzLA9sBLMAQDY2QKACIBDEHIH8omoO8/wuALqbBDZwbH4AwygA1HFbLgDa61uYDyCbL/qKTbwdkEbfoBVnLrPnS54Jaxybe+1XNlZssOIakMrm2wZAviHkgTYMIEK7TOYP/P2BfdYW5Mb/gT7ur9DIv9WawSYYP0/mfY4HDO3xxobOzccY97x5/77ZmYDD6nUmFTQdrg71Sc8JOg7/JSZGGzj0OCZmnpOqEWEt7flpj0/6bnkDoK3dYyJkMiBIQRc+TLdoLuzgD/241ZxpT0LIWzVv9iQANLFAh2kAMa1hOgMU0M7S7PNVXiwOpINg04BJ2I7eQ1sSBIDqzwbk4KNSKgCqrOxEzEEAaD+7C4Dq9K6VLVicWcgVHAi+YHNi+wDGAaBqUl156f/1uXG2B2JwhUB7RX+rtp33UE0qz69aU6CNdwCybI0UUImGK8gHEMjCfOku1vQ90MRiwGLLH/zB6FMakYiY8ND6YSXgO1X5AoBoFHEj4bqqQQBWeBcaGwHgDjcBFmrbVyvoe2NBBCpVI2gvJsCBbiDCvlXuy/1pOM2rz1TSbzvuODf/nR6PTGxTM/DCH+SHthhwwjSK3xtmT3uM8m/AkN/b3wEmOb4Nnb9xZwEA3WaPMb4DFmTkCDhxPbSLjG2+dQCbsYvLBxoc+zm03zjenu+RIzANfCsAMi8Ar8xLSQGQcaKaOfs9+TdzNRscAI2cgkAQ34Fu/vg5Wmu34gfnAtg8I7Ki6SZB5cKzaqJo2w/Xtoxwb9wreG8NWtHz+Vv7ADloXlDuHaQBTAKA+AszR3AvtyylAiBzAv1F416ALc+v/3etJWFjl2sAk/Y44XtnPQG8eXd+p3OQ7QvLRhYTNfdXFw3+jTsAY41/M6/wzarZnd8BfWxO8B/n2gAom07Ns4qSCRBLEukd902m/b3dx2nPTXJ83nyQWgPIIGMhSeJU674gu6JNN900EwBkx4hphMXFVR+r30lUBvi056c9PknnckzuHfyHP8Q+ipugmAWTP5hYtDHQMbthguIPDVBD08WkaTfVBsbdGHMVH67tNM5kpuZVZM5YC2po8JgY6HvVAGoy4CAA1Nq/aHaAHhZTfW6dzNBQ4azPTpjf4XuoEYUAEX/UL0vPQSuE/Gj2ZABMsRNWsFYNoL4LIIQvJLvfsDGgiWaZHDHRuACoMEkfoPlD24K5DZkwKRItzCSJmZLJE62QrdHRZ9HFlP8jF0zlrksA/YDfKM/A2ADEghZrvSbn81w2API7zd/Gv1lMNekuC65aBpC9Ls7/395ZQEtSnG+/0MV1YYP9cYIGd3cPHiBo8CCBYME9SHC3QHBLcCcECw7BXRdd3C3od37F997U7e2ZaZ3uvvPUOXt27kx1yVPVVU+9VmyKbDgDNdmY2nw0r0LeIYg5cxliZLc0hAcoMAnHwGzmkPIxD6J3K4fSS1OvR3FlzSQxd3n/2dyR4CDJoS0QFpvv4bPh3Ed9jrQnlN5aXt4tSAnzIPwdbQO2s+0IYGgDiKQeKVY0P21knTJnPbAzAggp4+BjBxjazN+88xCXuHXDJNS8T0i9sYvG5txS3CEWAsqahESLNYUE2cL0hfyQNBLkmfWONnJwakcAcWwibBPvNGXQdtrLGBNhANJKGUjyMHuxdhkBRCJnBymeC69+42/adPLJJ/t28XercFWUAbkL+81YQMaxT+UyCH4zZyjqtxiYZndI+TYWfGZeUjfEmLFgTWCe2Nhy8Odv9h37jjWL/YF1BjKLWQeEmvmLpJDveR9Yn+kLn6krHOMi1pSeUwEzSEhhkgTWjAKMNIFTvxnU5xkAVC2cauPuEOVWEiYEG1/0+iGrM+3zafOHfWOShA4T4W+89Bi3l5EgEJzKikicpDk5D8TEyRFpRN2T2V/VvZ1qX3IEID4cZCF80cRaG10rTQJnednwTU2dvNZyc1qbwoNFWCOHIg7uoVcvm3tIrML8kINWcTFDu8Bor1AhQpggipAUiCxELi4h0USLYYlyOVBCsJAWIqFkT0GSGF77h1SR78Jr1BByIOVOengJD0JIwDg4YU4FOTQ1aHh7jK3F7MGQaBKHPki6JZNYW9lI3LgjGOLHP+YRjnNoLIyQgjP95bDKIQ8pMaYpHFQhfZAqDiDsV/yN5oiD2zrrrOMldpgR0G6k63AEyqA/SI+R+DOGHHixKwUjDrA4j1A+cxgCCdHjGfYuNApmt8jvzCsIJlJIJNOQxTAhiY5q/ahr6NChww05/ebgzdpP2zhsZUkclOLseLOUFfcM+DIGZaXUEkBUhqHEJm3D8j5v9RkhizPiNxulJAQw6fN56gttjaJ4mcrMFnrzYuOkEveZ7/jNiG+7z2bjkXaMlF8ICAEhIASEQCsEIIqtTLnYk0xCWDSCZZUdlZYnbTfkEXJtto3h3cBpPptUF2Iefsa2s1YEMCkwcfk49XHKQoyeN6H+Q9RrRqZheaYC5rTXKtxB2ufT5g/bU5UEEDUQJ61OCXUNapt2KVS/WD5OTZwqLTEeZkQfLctOxfY9npXRuGyhAb/ls3APYXmcGlHPkjhRYgNnUhBOjxwALGEHx7xDdcHJGkkfp3NOxpY47aNeMWeluDAZoZSQsDp2MwhqHSTbJAzrw1tOkD4j2eA0HpdQwzGvwJ+EWgRVlCVUIahPkD6QkBRhE2TSBuzEaAsnXFPtUibOMqhgUAnT//BUjP0mdYb1MIZ2AsbQ3K5Ui2vzEkss4VCnR1M0Jl6nOZf091BqE5V+JS2jifnwfg5vm7E+RKUc0feqSX0N3+1W5gn0p91vSMZCZwHyW9B1zESQSiFNQkpFoGnsSMNkUlZUtahsLZmXMeYQmLoQlge1cvi+W96oWtwkdJhM2I0ZJomKk0KiybIYuggt+NvsVimD943fjQjwP9+xvlikC9TTkBHMJ1jLWetYjzEpQGqHSQr7IVIvJHlIN3nnIRuYjyB5Y+3ib35nj8ZWGeyQFLLGsuaZuRV/QwDZX1n3WLv4zPOY9YAVawmfaQNCI8pkHCiDdRuM+cx6xvqLpBDbUcYNe1v6wPqHrSvrHPOFepGKsQ4i/aRc3glz0mKthyTSJ/psdrzgB/as7fyjXtYT4wdZVcNlq4BrJwHMs8CwUWJYXoQTCBMGEXKcEwh1kMIQDdF2p30+bf6kOJVtAxh6AdMmXm4WDTNk5jteWmzFjNTwXTTMRpxtDpiwkJjdHniDPYa+Icm3EAS8ZBY6A4knKhJ+g3CwWKBWQA1AYuFl8mOozwIQJkgcxJ9FAfywVWJxsOj2cbY8lsdOpqifUCNY/5mToX0fixB9s36ENi8sqCxw3GPLwsKBg8WKPBY3LuoFbBsM3onYHbGhsMmTaBs2Q2AR13Y2ETZ6O9CQJ4zkTxkW29Ge539CluAsQeJvC9iMDRe2MSQWQ+YEaiw2HnMaCY3VGSuLJxaOg80tbHFaXQ1l7cExgU0retOM3bTApsZiD3k1RxAj82Y0T/w4JOYQZmyzsEOmXaiwGDtO4owF64zZr4bzFjUVqinsITEix66KTZJ/HEjYSCz+H/1E1cdhArWTOTXg2IIpRDRGH/k50ECueQbSQF8tsLq9G9F1gc0a72DmG4kNjOf4nvnPBoV9IE5DJNRoZqtl8SjjNq929plJ16as+SwgPCpTO7xYWRxUIGiECMGOlEMfCZtPyIs5UIR1M/+YY+SxuIoQALyHwzhsvFMQC5yDGH/WCDZ65iZEKrQ/tfLtUIG2hPlhiX2FsphvqKYxpeG95VCFg5Il1izIRhgHz8hiaMsKSeIf9UQPW2bDa2sR/9t6xLrIe8u7Rn+jdyoz9hy6wdLs3rB5s/UqGmbJ1gKzL7a/w+sniZ/J+k95Fs/PyrN9IlwPsamGPEJ8IdHMYcYKJ74wH/MBsm52rZg/8BkCiGAIlTKHcAh1dL0xG+6yJItZ53rPeQG3AgpmjriSgUfiAOuPJiY1i0MRBNA8I1uFgeElhCC2SmmfT5s/6YQqmwCyeJp4m5eZkyghTHg5ze6GlyokBUgeWHjwtjLPMfJw2mFxsOuvzM6EjZTTp21yOCzgkcsLjW1TuAiwQdvVUJzGWYjYENjMwk3LnrG7dfkb4koMuugigAEyp8mwHvC3O1j5zEYBcTSbUAszEi664AReYfm2udp32HuwWGG4bQkJBSSEPEjlIF2haQEG2NjvsVF0ik9JfXi+ga0RH7u1xMokTxjJP26uRT2ieYYNjJM6CckJm3NIVKPlRPse9z6zgbYjgJ2ujmp11VpYF+1oF6iWTZkYchjfkxhD5iBrEoS8Uz+idUHi2HAYL+YqGyxrGgTRPK0pkxtM2GztakubI2HIHcqCWFhMPzY3yrFba3iGwwTSFsg37xKSCkgGRJd62NxxwuEgZMb6fB8SQLuBgu8tTJH120hOKMXGThqpEQmHJOpH0gPZ4V3i3efdA1cS71hcoH8IEms+G3v0xqHQ05r3AuIdzn8IAe0gGaEL1wA8nKOHP+sTsRAhKeSHePC8ORlY7D4jgGDHHLXr48LxNmyiV3rZWNrBH4LEexklgJaPw4fFowVL9h5zPgnXGCNcSb+DyBru4TpjfQAP5hhEj/XCbl6JEsAw0DrPgJ858/F3GPmg3d7Fms4+EK61tIs9gfWJd4+DOQcgbPssH++IBXqnvjAMDPFmOQg2MdHfvJFR2vW7bH6Q2gYwrrFMLkTWnKQ7JQa/CALIy8WpixN5XCBoiylk7UEqgITBbsVI+3za/J1wsN/LHuAwDIwtApyukChAvjCkNbWlLa524wJtxMgZu00z0LYTpW209gKYmoWXgVhfkCTzbAwXCxao6DwJbxxBKoaky4Ld2r25tJ0FhYUlSgBDkmgLLETX1MRxY2HhbNgATPKZhABCmFjIwpce9YndbAIehOBA9RC92QIJAMTa5mBcuxiDaEwu6mQTMPUVeQzjpPOMZ0LPPtt8O13BFt2owvpMSsgG1Mpb27znW53cUXNbeIdWfaHtaW4+CTcbmw/hOLfDjLrCWxIMJySlED6kkkjoyEdIFsgb8yZJIFue4SDAQcxIC7jwz+KXMtZI/TDfgGwgqbd4gMw5NlqL8deKACKtYk2MEkAkYOAIUSPmHtcW2ntMv1jDWZv5DUks0ibeDaSiSOxCSaMRtTAgeRzRjoYNCbFHgg5xJIYleEC2wnIh4dHN1eowSWG4tti48a7g+GEEENMJ5igEkPp4jyyOp5lzhMQzDIpsoU0sCgDrVygBjDssUjaSWsY5DpM034VBlqPRAGxu844RAJ31xsJQWbtMexAlgMxbCLSVkZQAMncoK8Sdg0RU0svvdnCNvm+MB4cbDg9gEd2rk65pdcgXXWuKblPZ/KAQAsiLhcSCUxKidhYLFg8LusnpGQLBaZwFH/VeEQmpHKcyuwoOVQ1SIuyUQukfiziqBk7GtMtS0uez5k/Sx7IHOFQBc3Kz2ElxbYueHuPyhEGj4zZ17C5Q07Bwx6kB4shCEikQbWFcWeii9fIS8j0bsi1oSJ7aBRy3MAUsQibBSUIA4zBhQ7F7TO33rKqBTtIu619IUpLMs2geFm0273ZzIonkjDyQfQhpXLKbIFoRQL7HhjF6lVRYFnUQkDxU0bXrcxR7ng+lwe2etSv8rO8WMBwCEBIgVLRI8tLcasT6hAQQM4iQAIbtiRLAKA6hmYPdSEO7sO1EasfndgQQ6Rh5kLiggjOJfFTFRh6L22htiBJA1nfs6sI7ZckbjrUFGRn6ZgAAIABJREFUeY8bfyMnHEghAXY1IfW00uBYG8xsJI4A2vVtHCSRppptssXts/ty+R5Sz5gbAYSYhAQPqSiSc6snvNouegMG6w2eueFhAEkv7xjPRXGMI4/R78KAzXF3V4MHey4HY1S2SQmghcyy9cRu2em0lpgdXav3udPzA+33rOt8UhzK5geFEEDiTqHGg4yReAF4iaK3hrD4YMdjd3QmBaFdPiYyJ1mIB6cTRPEsAKGUBRUcpBMbiuhtBUmeD+tPm79TH8se4FAFHBcyJ2wfp2NO5e1ebk7VZsfVaRFAeoGzRbhIx6kLCTdgBsjt8Arjz7XLByHhRIrBcauEnQoGxNiRWQgYJB+orcK7QJOQIOafBbG1+rKqBjoRKluwo9f5dZpnrQggqq9WEskkfScPuIVhMMK62FB5/zrNlXbtp44wcG2nvkax53kIF1LqtIl1BamdxcdL+3yr/EjcWItCZxzymsQ+Lg5baANKn1oRQEgLtqZRCaCpE41Qo3oziTwaDt4ZSKTNsU4EMNq3uPmCOQTq37jxt5sdIEhmZ2dEzII5t6rDHK6SEEDU9vTTbqwwdS3PcqjgMGhxABFehHcXh3lpC4cVtAccNnmWg0na1EoCyHoUxlgkX6geRSVu1+VZneTBPhghB4fuVgQwejVlVgKIdJM9PC6IeFocBkL+rOt80r6XzQ8KIYCoLBDrmr0YBIGXyKKpW2c5AfPi2JVxSUEYyPnKHuBQAhiVYkRxTUIA4+4XbTU+UfWeLVaQzDDZ/c2dSEJ4A0URc4L2IMVp52afhASxEXDoCNuf9WRIfTgFRD2kw/6SBxUd0pesCQICnibxiisnSd9NmsRGFZfs6rFOY9uJAIa2UJ36HCcB7HSHbqcyu/W7Gf93ur82CwEM7a4skHKcSUYrAohUDmeYMBBwdF7ydzjWdnNG3PgjRUXNDQGEVDFXjAAaiW1FAO0mkzgCiKMF89EkgBBAiBsaICRYUaleSKZCG2W+N2lhtP1RcpZmfrQigFGzFfIhpTV747i72W1NRd2KBNCiVVh7LYB7JwIYdSpL059ezpt1nU+KWdn8oBACiFoDmxW7OBwVICe66BVM5EFc3SooclJQBlK+sgc4DWFLQgDBPupR22o8zCEiXKQ5rUYJoN2z3IkkWIDvTvmSzg8WT/BvdyCBaKHGtHALcWWjpjHPVfs968JAm/BIjYariG60cQbySftNPhwLeD/bSYWTEkA2XDCIS+HtAGnaF+ZF3YcK167N6lROHAHs5BTWqcy6/R4lgHjLI8nieyNPdrONOTqYOpE8FuYEiRGH9ziiFZUAkgccsc+NewexHca73DzMyY9WCK/luPx8h+kGph1h4mCCuhab37h2sYcwf3EoMe9o+mRmEeZZbuGcsMnlHbaEqhmv+zhSF8WjHQEMyVma+RH3XkGswY0DqSXyoV0wR5y4dZc8qLExVYAARm1ujQCGph48Q/+xuSTxtwhgmhH8X96s63zS2srmB4UQQMTmvLA4ZJB4QTGCj8axQs1HzLEm3LqQdIDy5it7gFnkLHh0pxtYkhLAOJu3OBwIx8CcCAkgYSDwFg9T9K7bVpiiorKrkPLibgtfVOWTpdyoFzJlmCQjbXksxkj2IJ6tEnlwfMGgP2uyjbedVDgpAYT8htcGhm3CoJ7xhmh2K0WxRxLNxmghRLrVjjLrSUIAbY5DALHTwzSC9YZnOUAwf9oRQOylV1hhhX7daEcA4+Y8xINYlCGxyYMLbbd7ZMNyQgJoXtVGAKPqdFSYkEecaKJlRA9fOG1hshRHFoskgHGYRN/z6L3ENr6s29j0kj8rAewUVSDPmA3kZ7Ou80kxKZsfFEIA8VokmC4vHioFJiqbIouHxVrjNMkpBaPgLLY4SQFrWr6yB9gkgHhAh1cYxeHESRIv304StqQEEFs6CzZKfdgPckqNxlCLC28Q176kBDXpHEBighF/lmsNwzriCGDWkyGLOA4lbNCtErauSEBaBd1O0v8kcbV4V3HgahXjzzagdgSQPGUvktH+ZsU+CW51yRMlgHaPLGY3OAvgWW3jg3NTSMB5x1F14gCVlgAS4oR1Pm6N6AbuSQgg/UaVDvnEPKnVvbbRsQxvV7LfIIlIoOMIYCidSzMvIOKop+3O81bPGlG3UDjYwXLQCttCHg7GRHNgbUX4gtTP8iDdhRR2kgCmjSqQpr8DOW/Zc75sflAIAcSeCKKHVxi2HBjYs8CgEgilCNgGsvigrlD6GYGyB9gIIESHk3i7VDYBbFU3EiLCJnQinknb1+25Faeaybow8L6g8rEQHWX1JRqnK2s9tDeNg0bWetI8lxX7NHVUnZdg1Kjwie3HGBgBjLaL36IE0PJwKMTeNC6+H8/FSQCRJOIxWiUBRC0bva0mlABa/yxigYXUyTJm7QhgXil8p/bQp9DW1+IbtiOAmNhwYOtEAHF6sbiZcdh1apt+/xmBsteasvlBIQQwbjLg2s/GiKSC0xinEGwz7HJnTaDuEEBTAVdBAPEwJRwPKpt2CRshbIU6EcDo4laXORRHALNKvZpIAC28Rl3GIyv2dWl/2nYwZ3DAs+DS4fPtCGC7eloRQDY8glXHHeK7gTvtSkoAkbJZRAq7bjEttu0IYF473E5toa+ht7/FN4wSQGyj2WfJH10jQ09rCwHGXkyAfsgFSQSw00i0/r3sOd9YApgd0t56suwBrlICmHQkiR+JGUEnAhhVbyQtv+x8hJeABIXtz3oyZDFuF1alqL5YkNZOmHeqj/ZaeI1Oebv1e1bsu9W+ouvhJg/CrdgNPVECiA1w2uD7jCtmPRZbM0mbu4F7OwIYDY1kIavwNsbDOEvCgxgHifCyASNNeT3xO7WHvoaq2VYEkHiehGdBBZyEAEbrFQHsNBKtfy97zpfND0qTAGaHtLeeLHuAjQCG8e5aIZxUxZrUBjDpSMZFuI97tq4EEMkLKmzs6ixlXRhYjAn7gIF5mckkA0UQwGhA3DLbnaTsrNgnKbtpeYqWALbrfzdwpz92P26U6EaDo1uszzwEsFV/o9K5MuYFdYTOGa0IIF7TkPV2BLDTjT9544qW0f8mlFn2nC+bH4gAVjzLyh5gUwFjK4Ravl2qigCGV6m1ax/ee9iYLrPMMhWPWufqs6oGWPQxlWgVV69zzclzYKMbDdae/Omfc9JenH2QQNUlZcW+Lu0vsh2MT1YJYJwNYLu2dQP3NASQKywJHUQgcqJSFJm6ITWjjjA8i91wElUBQwA5fJI/uoZzPzse2J3ifZYtzSwS+zqVVfacL5sfiABWPJvKHmCTANaZALLI4RmXVxpV8VD2qz7ryZBFPM21Z1X3GdUiTgZ1Slmxr1MfimoLjh445BH2JE1iHuJMgL1Y0tQN3NMQQOYmjjJcM4fnfJEpqp4tsmwrizqImYpal2QBrqMEkD5C1uMkgEnaRT2EbIuGxUnybK/nKXvOl80PRAArnsFlD3ATCGDcHZcVD0vu6rMuDCzG7QIr525YDxSQFfuBCA3hP5AAtrrur1WfCY4+xRRTpIKkG7jzfkBUojFm+R7HBsJOdSNF1bPdqLMVASSQNmHWshJAbujCqYd5opQOgbLnfNn8QAQw3XgXnrvsAba7gOssAUQVSYBoDJkHSsp6RyShHgiYbh56AwWPbvYjK/bdbONArKsbuLcigNj72R3l3cA2qp7tRp2YwOAwR/iZUErIPfdIeCFwdY2U0A18qqij7DlfNj8QAaxg1nAqt+vwCN/Q7i7avM0zCSDBjt999922xRF/jtAGnVSxRTuB5O1jHZ8v+2RYxz7XpU3CvpqR6AburQhgt3s8ySSTeNLFVYdVJvCAAF5//fVeApjUjrvKNg+kusue8yKAA2m2/P++2JU+/EmcKk6vZSW8v1gYkhBAiJ9JDNu1RwSw82iB+2ijjdY5o3IUjoCwLxzSRAV2A3cIz+abb97xFo1EDR4AmcCDO5MhgKw3kgB2d1DLnvMigN0dz67U1k0JoBG6JAQwaeeHDRvmb6ogRIFSPAJlqwaEe2sEhH01s6MbuEN4tthiC3fmmWdW08ma1QoeSy+9tHd0kQq4+4NT9pwXAez+mHa1xrIH2FTAQ4YMce+8805X+9bLlZWtGuhlbDv1Xdh3Qqic37uBO9oHHD3yhi8qB4HulzrddNP5uKFc6yYVcPfxL3vOl80PZAPY/TnTr8ayB9hUwMTBIh6WUncQKFs10J1eNLMWYV/NuAn3anCnVsNeNoDdHYOy53zZ/EAEsLvzZbjayh5gYmG99NJLbvzxx/d2gErdQaCO8fG60/PqaxH21YyBcK8Gd2o17C+66CJ3wQUX+LAwSuUjUPacL5sfiACWP0fa1lD2AJctoq4YvtpWL9yrGxphXw32wr0a3KlV2FeDfdm4l80PRACrmTd9tZY9wDicDBo0qOJe9l71wr26MRf21WAv3KvBnVqFfTXYl4172fxABLCaedM1Ali2iLpi+GpbvXCvbmiEfTXYC/dqcA9VwNW1oDdrLnvOiwAO8HlV9gCXLaIe4MOTuXvCPTN0uR8U9rkhzFSAcM8EWyEPCftCYExdSNm4l80PJAFMPeTFPlD2AJctoi4WjYFTmnCvbiyFfTXYC/dqcJcKeODiXjY/EAGsbu74msse4O+//96NPPLIFfey96oX7tWNubCvBnvhXg3u1Crsq8G+bNzL5gcigNXMm75ayx7gskXUFcNX2+qFe3VDI+yrwV64V4M7tQr7arAvG/ey+YEIYDXzpmsE8Ntvv3Wjjjpqxb3sveqFe3VjLuyrwV64V4M7tQr7arAvG3cRwATjeskll7jDDz/cvf32227MMcd0m266qdt7771TqT7TlsEdgMcee6yvh6t4DjjggAQtHT5L2QNctog6U6d74CHhXt0gC/tqsBfu1eAuFfDAxb1sftB4CSCXgv/+9793l112mVtzzTXd008/7ZZZZhm31FJLuQsvvDDRzEhbxtChQz3JfPXVV93rr7/u9t9//9oSwLJF1IkA7sFMwr26QRf21WAv3KvBXSrggYu7CGCbsf3444/dVFNN5VZbbTV33nnn9eU844wz3NZbb+1uvfVWt/TSS7edHVnKmH322d3GG2/s5pxzTl9+nQlg2SLq6l69etcs3KsbH2FfDfbCvRrcpQIeuLiLALYZ29NPP91ts8027vLLL/fSP0vvv/++v/d2/fXXd9yN2C5lKePNN9/03rt33HGHW3LJJWtNAL/77js3yiijVPeG9GjNwr26gRf21WAv3KvBnVqFfTXYl427CGCbcd1ggw08wXvhhRfc9NNP3y/nJJNM4kYccUT31ltvtZ0ZecpoAgGUWqaahUG4V4O71GHCvToEqqtZ60012JeNuwhgm3Gdb7753EMPPeQ+++wzN/bYY/fLOddcc7lHH33Uffnll26MMcZoWUqeMppAAMs+oVTz2tW/VuFe3RgJ+2qwF+7V4C4J4MDFXQSwzdjOMMMM7sUXX/RBMEcaaaR+ORdZZBF3zz33eM9gpIGtUp4ykhJAIuTzLy7NPPPMDpVyWUmLclnIti9XuFeDuzZD4V4dAtXVrPWmGuzLxr0nCCBi1DvvvDPxCK6wwgo+r5E3LmRG3RumRRdd1N19992JCWCWMpISQELEHHjggbH9Q3L57rvv9oWssVAKP/30k6NN2O8RcsY+8z9/E9uPvPaZicgzgwYN8jGh7POnn37qRhttNP/vm2++8W1o9ZlnIaojjDCCL98+0wbKBGNuFbHPkG7q5X9+s888H4aEKLpPRqbr3Cckz2CYdJya0Ke0c6+qPn3xxRdurLHG8nO9F+deVeOEJgZti9aIn29e6ubcY20fb7zx+tZ4reUj+n2p7P0J7jLuuOP223OLXPcwbStTQFSLMDCEVZl66qkTE0DIDWneeed1Dz/8sPv888/7FnwrxFTAbAbEBmyV8pSRlAC2kwAOHjzYO6yUlViUxxlnnLKKL7Vctb1UeFsW3mTc6VST26+2VzPnNW+EexYEyn5fcWhtpT3M0t7oM7UggJyU0rBcQr+Qfvvb37qLL7441glk0kkn9XlQAbdLecpISgCLGKgsZTA5OZ0gBWwaCVTbs4x4/meajLtt4prz+edB2hI0b9IiVlz+JmOvthc3D7KUVAsCmKXhPHPaaaf5INCtwsCst956niC2S3nKEAHMOnKdn9PC0BmjMnI0GXcRwDJmRLIyNW+S4VRGriZjr7aXMSOSl9loAvjhhx961fHqq68eGwj6lltuccsuu2w/NLC3m2CCCfpi42UpwwoUAUw+0dLmROx92GGHuT333NPbNTYpNXlRazLuTSeATca+yXOeeSPsq1lhhXs1uFutjSaAJgXcfvvt+66Ce+aZZ/ztHEssscRw0j+8ghdbbDG33HLLuRtvvLEPeaSAScsIh0sEsNrJW9fam74Z1hXXJO0S9klQKj6PcC8e06QlCvukSBWbbyDg3ngCyJASDPqII45ww4YN815om2yyidtnn32GuwHjySef9Dd3rLXWWo4bQMKUtAyeoa5jjz3We/5wlRxOJngdzj///O7qq68udpblKG0gTNAc3a/sUeFeGfTeAaSpNoDVoZa/ZuGeH8OsJQj7rMjle24g4D4gCGC+YRy4Tw+ECdrE0RHu1Y2asK8Ge+FeDe7UKuyrwX4g4C4CWM3c6UqtTbav6ApAJVUi3EsCNkGxwj4BSCVkEe4lgJqwSGGfEKiCsw0E3EUAC54UKk4ICAEhIASEgBAQAnVHQASw7iOk9gkBISAEhIAQEAJCoGAERAALBlTFCQEhIASEgBAQAkKg7giIANZohLg/9vzzz/f/nnvuOX+X5BRTTOE22mgjt/POO/fzaub6OzyXr7nmGvfss886rrzjto9lllnG7bvvvm6yySYbrmeXXHKJO/zww/3tKHgub7rppm7vvffuu4c4fCBN3hpBmKkpZeGeplxreC/hTp/TYJRlzhuub731lpt55pm9wbxdJRmdLL2Efdm4f/LJJ+7ggw/26xM3EXFX+GyzzeZ22mknt/LKK/eDvpdwL3vOM65HH320u/TSSx3XiI0++ug+OgV30c8000y59oRMi2uNHkoz56PNLnr9qMucFwGs0QTlWrq///3v7pxzznHcYsJGde6557qtttrKL5osppYsBuEf/vAHd+ihh3pC9+ijj7rVVlvN/fjjj46QN+OPP35f/jPPPNPfmnLZZZe5Nddc0z399NOeLC611FLuwgsv7IdCmrw1gi9zU8rCPU25NL7XcKfPaTBKO+fDCbHGGmu4q666yn8VRwB7DfsycX/vvffcwgsv7NcWQmaNN9547pFHHvHxVzfccEN33HHHZVqXMr/gNXuwLOyZ14svvrh77LHHfDgyQp5BAtlLHnjgAf9vlllm6Vns0+AenTJFrh91WmtEAGu0OPCiEsMsGqPQ7iu+7bbb/EtNYjNEMvjaa6/507WlU0891W277baeTGyxxRb+a2IVcn8y5PC8887ry3vGGWe4rbfe2t16660+eHbavDWCLldTysI9TblpxihXZ2v2cBqM0sz5sJtshkieJppoIvfQQw8NRwB7EfsycV977bXd0KFD3YMPPthvbTrmmGPcDz/84HbbbbeeXWvoeFnY33333W7RRRd1u+66qzvyyCP7XoGnnnrKS1+33HJLx5qvdb5/DOC4/bWs9aNua40IYI02RO4tnn766d0888zTr1UnnHCC23HHHf1pevfdd/e/oVZ58803+53o+P766693q6yyijvqqKPcLrvs4vNCKLfZZpuWdyavv/76Xp2cNm+NoMvVlLJwT1NumjHK1dmaPZwGozRz3rqJ2hjVLxsf78+dd945HAHsRezLwv2VV15x0047rTvxxBP97UrtUi/iDh5lYY9akbX8lFNO8doeS19//bW/IGGFFVbouwGrF7FPg3tZ60fdcBcBrNmGGNccTs6QOSYP6uB26ZBDDvE2gPfee69bcMEFfdYNNtjAE7wXXnjBE8wwTTLJJP6Ujo1D2rwNgC5XE/Pi3qryuHLTjFGuTjXk4aKwh4Rw3zeLP9dDxhFAYf+/SZEX9+OPP95LW8P1p9WUE+79kcmLPWY/v/rVrzz+3FRl6fHHH3dzzDGHFyKY+l3YJ5vzRa8fdcNdBLABGyKnussvv9y9+uqrsc4ddAFJB6ouTn4sABhgW5pvvvm86gsD+LHHHrtfj+eaay5vO4iBLKfENHkbAF2uJubFvVXlceUK9/5oFYE9Nk/YzmLvOmTIkJYEUNj/D/u8uG+++ebu7LPPdty7ftZZZ3nzEiRQs88+u9trr736TFioUbgXP+dNUICt9/LLL++1RNhdvvHGG35MzDlQ2Hee82WsH3XDXQQwF0Uo/2Fe4BlmmMETO7y74hIGqjiIDBo0yB100EH+pDfKKKP0ZeX5F1980XsVjzTSSP2KWGSRRfzCgGcw0sA0ecvvfXU1FIF7XOtblSvc/4dWEdgz1+eee26vhsT2idRKAijsf8a+CNwxP8EMZfDgwZ7wobEgQgHjcOWVV/qDLLbIJOFe7Jy30jD/2W+//by9JffVo/qFjE866aSZ9oTqVuHya24158taP+o250UAy59jmWvAq2v11VfvO73h0t8qcS0NRA6njgkmmMBdd9113ug9XGhZEEKHEX7DaBjj4SgBTJI3c8dq/mBRuEe72a5cWxh6GXfwKgr7ww47zN1www3urrvuciOMMEIiAtjL2BeFO85kOKvh8XvzzTf3vQJoKCaffHK/NmEnyJhozv8MT1HYQ1rWXXddb+aAs9+yyy7rPvroI28+xHuAFzwan7R7Qs2X68zNa4d7WetH3ea8CGDm6VP+g8Tou+CCC9x9993X7/TWrub777/f2/5tttlm/tRHmnfeed3DDz/s1cRjjTVWv8dNBcwpnVAyafKWj0A1NRSFe7T17coV7j+jVQT2L7/8spf+YYeGA4ilVhJAYV8M7uC86qqr+sMnoan23HPPfq8AKslbbrnFPf/88578Cffi5jwlnXbaaV5ThNPgDjvs0Ic9woGpp57am/8888wzXgsk7FvP+TLXj7rhLgJYDcfoWCvG1ARt5uQWddzo9DAvOkGhzbHD3NzjnEBMLYAEkJQmb6d2NPH3InEP+9+p3F7HHaw6YdRuPoVzHi9IyEdUYo405LvvvvP2gKR99tnHqyZ7HfuicAfT7bbbznuhxjmsEbaKAy0aB+IE9jruRc55ylpnnXXcP/7xDx9zcc455+z3uvz617921157rb80YMYZZ+x57NvN+TLXj7rNeRHAGrIUjKgJ93L77bf7+E0kPBmR4BHPj3TFFVd4lQpGpdGE6heJHsbX4ckQ+xuCQFsiSOjEE0/s41LhJZk2bw2hy9WkonG3xiQp107vScYoVydr+nASjNLM+bhutpIA9jL2ReOO6nGTTTbxTmgQ7DCtuOKK7qabbuqLRtDLuINL0divtNJKPswLTn14/YYJUyKcBHFsYM/oZeyT4F7W+lE33EUAa7Yh4r2FHR+qEsTFlrgdhEC4/E/iGjfUuSeddFK/HiDiJ9r7Qgst5G0CjTyiAmARiAsETV3Yi6TNWzPocjWnDNxpUNJyIfhJxyhXR2v4cFKM0sz5NAt4r2JfBu7Eapxyyim9BIoDrKWvvvrKX2s54YQTegLYy2tNmnUhzZzH8QPiHY0DiNR7mmmmcR988IH/h6mP5nz7/bWs9aNuuIsA1mhDxHsOj16uUFpggQX6tYzrfbhSKSSAxPbDzg8JHl6/TzzxhNt44429mB9Sx7VAljh5oO6yq+AgihhsIxUx6V+WvDWCL3NTysI9Tbk0Ps0YZe5szR5MgxGbYZo5H+1qKwlgL2JfJu6sSdxCRMw5biX65ptv/NrDOoNjDldQ9upaQ7/Lwh6NDjbdED6uFCXCA5ogbgYhEDoxYrGx7VXs0+CehgCmXT/qtM6LANZoQ7QNqlWTUK0YAXz99df9Z+w6cGVnkcXmiZd+jz326PP2Csti8+Q2hGHDhvmYf5SHmiYMGWP50+StEYSZmlIW7mnK7UXc6XMajLLMeerA050wSFEbQA5BeKX2IvZl444pA2sNuOPxy4F2//33d/PPP/9w72gvrTVlz3nW9gMOOMCr2pHG4uk666yzeiJOEOJo6iXs08z5EKcy1o+64C4CmIky6CEhIASEgBAQAkJACDQXARHA5o6dWi4EhIAQEAJCQAgIgUwIiABmgk0PCQEhIASEgBAQAkKguQiIADZ37NRyISAEhIAQEAJCQAhkQkAEMBNsekgICAEhIASEgBAQAs1FQASwuWOnlgsBISAEhIAQEAJCIBMCIoCZYNNDQkAICAEhIASEgBBoLgIigM0dO7VcCAgBISAEhIAQEAKZEBABzASbHhICQkAICAEhIASEQHMREAFs7tip5UJACAgBISAEhIAQyISACGAm2PSQEBACQkAICAEhIASai4AIYHPHTi0XAkJACAgBISAEhEAmBEQAM8Gmh4SAEBACQkAICAEh0FwERACbO3ZquRAQAkJACAgBISAEMiEgApgJNj0kBISAEBACQkAICIHmIiAC2NyxU8uFgBAQAkJACAgBIZAJARHATLDpISEgBISAEBACQkAINBcBEcDmjp1aLgSEgBAQAiUicPvtt7ttt93WDRkyxN1xxx0l1qSihUD3ERAB7D7mqlEICAEhIARqjMB3333nNttsM/fxxx+7oUOHusGDB4sA1ni81LRsCIgAZsNNTwkBISAEhMAAReCrr75yN998s1tjjTXcEkss4XspCeAAHewe7pYIYA8PvrouBISAECgKgZ9++skXNcIIIxRVZC3KaUcAf/zxRzfiiCPWop1qhBBIi4AIYFrElF8ICAEhUBACV111lZcyWdpkk03cOeecU1Dp3Svmsccec1tvvbW75ZZb3Ljjjtu9irtQUzsCeP7557vbbrvNHXvssW688cbrQmv5F1QFAAAPmElEQVRUhRAoDgERwOKwVElCoBIEpppqKvfaa68NV7dJZOyH9957z/3iF79wY401lvvwww/dKKOM0u+ZaDmLL7641F4lj+h///tfb2d26aWXup122sk1kQBef/31bp111nE77rijO+yww0pGLF3xn332mXv77bc7PjTJJJO0JK7tCCDlL7/88u6DDz7wRHCKKaboWJcyCIG6ICACWJeRUDuEQEYE3n//fffCCy+4RRZZxJfw4IMP+o0Ishem8847zxMM0r/+9S+31FJL9fudcp577jm35JJLumeffdZNOOGEboIJJsjYKj2WBgGkfr/73e8aRwCfeuopN//883sCWEfJ5QUXXOA22mijjkPxt7/9zW266aax+TrZAH7++edujjnmcGOMMYZ76KGH3GijjdaxPmUQAnVAQASwDqOgNgiBAhCYcsop3euvv+7OOOMMt+WWWw5X4vrrr+8uueQS//2uu+7qjjzyyOHynHDCCV4adc899xTQIhWRFIGmEsCFF17YPfzww+6ll14asNKvTgSQMbbx22+//dyBBx6YdNiVTwhUioAIYKXwq3IhUBwCW221lTvzzDO9TdkVV1zRr2CM1SeaaCKHWvfKK690M888s3v66aeHq3yllVZyCy64oNt3332La5hK6ohAEwkgXrFIizlYXHTRRR372NQMSQjgDz/84FAjEz7mzTffdGOOOWZTu6t29xACIoA9NNjq6sBGAGK35pprunHGGcfbJIU2fvfdd59bZpll3KOPPup++ctfeiCIb4bU0BL2aKh877zzTjfPPPP0fX/XXXe5yy67zP373//2z7DJTTPNNG6ttdZyf/rTn7zqK0xxXqAE1LWNlP+pw1Jo90b5hx56qA/BMWzYMG+XNe+883r7MmytLN19991u0UUX7VfGIYcc4nbffXfviPDll1+6WWaZxR100EEOUhumk046ye2www59X4XqP+qfeuqpY9sWV+fBBx/sdtllF/fPf/7Te4Mutthi7qijjnLTTjutw+YSSesNN9zgvvnmG4e07LjjjnMzzTTTcBMxJID0Y6+99vL9+OSTTzzWW2yxhcdgpJFGGu7ZPJj9+c9/dnvuuaevi/ZiN7r//vu7Aw44oOPLQpvOOussf+jgc6v0xhtvuMMPP9zdeOON7q233nKDBg1y008/vSePG264oVefloltx450yJCEAFLEuuuu69+Tiy++2K233np5q9XzQqB0BEQAS4dYFQiB7iCALRJ2exA0pDNI+ywh0YP8XXfddZ4YPfPMM+7UU09122yzTV8eSAAb8rvvvtsvlAc2TZNNNpn7y1/+4uacc05HjDQM3lF3TTfddA6CGJLAd955x5O4E0880dtf8RzEctRRR/V1ffTRR+7xxx/3NoiommkPRA8SsMoqq/h8eFXON9983rmFtt9///3ewWCPPfbwZdBHHFnMeWLllVd2n376qf8d6eZ//vMf75XKdzwbElraj/E+hIoNOySASHKwhYxzyoir8+uvv/YECtIIwfnjH//oJUFWP7dI4FwD7pBB7DKff/754SRERgBXWGEF77QAqWT8GAtIJs//5je/8e0KU17MrC7I6RNPPOFJDKQ+CQGkz5DPe++910uN4xIHD8YG0nfMMcf4fIwbtnmQYRIkl/kTHc+isM369uGUg3cz/0gQVeYk8zkuQdyZqwSQhhgrCYG6IyACWPcRUvuEQAoEIA0QMohQ6JEJAcLJYLvttnO77babl1Ktuuqq7pprrukrfeedd/ZSIDbnMEHyUPGx+YWJEBgbb7yxtyWE3IQJJxKIGKExkORFDeMhSjirmK0hJGDGGWf0hAfChmOBJaRnSMHsNySClow48TdlLbTQQn2/Yc8Iydt8883dX//61+FQxOj/3HPP7UcAo+XGeeWGdWL0H5JLCC/4zTbbbO7ss8/u95vZYPL7Bhts0K89YZmMCWNjCeIJ+YC0h2S1CMyQTq644op9ddF+2o4ktV364osv3Nhjj+2zYHca5/0K+Q7HNDp/zGQBL2gLoVIGtilen1xZre3MT+a2khCoOwIigHUfIbVPCKRAAFUbEqnZZ5+9T3Jh4V9efPFFr5pEerf00kt7KRRSF6QzJAjb3nvvPRw5aVU9hv+o8lCRoeKNJqQ9kDmIIpJFS6iakShCQs3z8uijj/YkEkkUUq1oQiUKoSU/JChK1FBr48EcpgceeMAtsMACbu655/aOCtGUlwCiyoWUhen444/34VzifkOqCclGukffw2TkAZX8q6++OlwwZSs3HNe8mCHBe+WVV1LMrv9lxX501lln9V9ABuNs3qx9kPI4pyLmBmYJqIUtdqDhUCS2mTqY4SGktBB3bG1555SEQN0REAGs+wipfUIgBQKoq1DTklDvoY4k/AvqKULFkL799luvKmbjRu277LLLOuy0UFWivmUDCxOSHMgL0iJUfqjmsBXjH+pUSKCVHT6H1A1vZOziQpu/Cy+80EsiaZ+pjrHvoy1IBlEVRpOVFa3LCANqRjbgMEF4Z5hhBi89fPnllwsngKirr7322n7lQk5RAcb9hkQQaWScitD6AQ433XTTcG2FQBHmB/tKVOhIzPJihuSPMc2SIG+m9kVCOfLIIw9XjLUPQsz8SZIMhyKxTVJvEXmwA11uueW8tJt3REkI1B0BEcC6j5DaJwRSIjDppJN6tSuEA7UvqseJJ57YIUWytPrqq7urr77aS6vYnAkdA8mKqq5QuyKVg0ChDuXf5JNP7okIkhukf0itIIbRhE0iBBSHDAgi5I3EM9j9nXzyyX2PIPFBgof9XzRANZmwzUMVDGGkPEtGGFBFo84Nkzl0tGpfXglgXJ3t2tPO09d+QwULYY8m8DPnHWLvgV8ZmCWdaqHTBh7mcY4/1j7sQZFKJ0lJ8GuHe5WBtE2yDhmGFCsJgbojIAJY9xFS+4RASgQgfWykOA1guwf5Q+qGg4Gl008/3TuAmOoU72FUenjNhmn77bf3RC1OMtWJYFGOtQWbsiOOOMITQerEIQW7NktGFlAD47zRKkE0UGNHCWDcxt+pfe0IoEny2tkAlvFbHLmhryEBRP2Kur4MzJJOtUceecSr1kkQczMjCJ/PQwCLxDZpn/LmwwkIj3PU2dhnKgmBuiMgAlj3EVL7hEBKBPBsxZtz/PHH91I+yBu2fqOPPnpfSah8/+///s//jVcqBvpsYFFvThwCkDhhz4X9Wpg6ESzymqRoyJAhPj4akiA8lHGeCBPklNAvrQJUt4KgnVStU/tQxyIlRfLJ5zDh6Yk3bJFEJIkEECJ++eWXD9fdOBVwGZglnWqo77HjJGHvFjUb4HtrXyu1flxdSTBKOyZJ+5Q3n713mB3wTikJgbojIAJY9xFS+4RASgTwqmRDRm1KqBWkM3G2Xkj8kCZxjdett97qw59E48whacKjN44AGilppWK1ZuMJyobILSTE3yP2XPSmEnOQiNoLWhnYG9IX7BtDG8E8BBBCS71xXsxIIVGLpyUbeQkMHtfYLkZTnBNIGZilmWp4AWNH+uSTT/Y5hITPW/uwXSSGZDRhboBzD/PBvL7z4lelCti8zqPe9WkwVV4h0E0ERAC7ibbqEgJdQgC7PeKzkdiYwsDH1gQLB8PfSAztmriwiaYmxWsYkhgm7AchJp0IIKpfwtLgeIIHMNIjCyFi5XUKGWIhZ3D0wOHDUh4CaHcjR/uOjSF2jqjxuk0A6Re2ZARJthSGgTG7Tn4rA7M009OcPAhAjk1pNIXtIy6iOSdZPkwUuJOa+WAq5CYTQBybTjnlFG/q0CmMThqclVcIlIWACGBZyKpcIVAhAgQPJlAzCYkSkqVoMqN1vg/jy4X5TD1M4GRueyCwMY4akEUkcXgBQ5ZQ6aJitnAeYRl4FhMn7vvvv/dlcHNEXCJoMDZUOIEQzgZnEconLh79QWoImSVFAzZDJiCj1E87kGaiAka13ap9OKlgj0heVL54niI95SYMHGkgW1buWGON1VeuBYkO6wSTMIB00t+4PYQ6rUxiCnKLC/3lphPK5G5ZiC+SWvKFDhdFYAaeBKhOm7ANxUY0GnMyLMfaR5gYpMiE5aFPp512mrdTxUQBQt9uPLNiG5o8pO1blvxzzTWXt21FYo7UW0kI1B0BEcC6j5DaJwQyIEDcOwLS4jBBvL64RDiYwYMHO4iQhYyJy0esO244wHYPIohTCRJBpGPEcbPUTv222mqreSJHbL5oQOCwTmwTifeHPSJt4gYRnAmQrmAfZ+QnemWblWFElpA23CISprj2sVljd0jwbNTMEDBC5oAZDiyWiI8IeQ2viQvrhKxm+Y1wLtzdHGKIzRzkHRU7Y2NXwSFxjbsKLi9m1E3f0ybaBrFHsstBIS4UDGVG24d5Ag4k++yzj5+jpHbjmRVbizGZtl9Z8mNKgb0sIZWwZVUSAk1AQASwCaOkNgoBISAEaoiA3avM1WfEN+zVtPbaa/sDDt7RFiC7V7FQv5uDgAhgc8ZKLRUCQkAI1AoBJIfc8oLEFhtR1KC9ljBLQDqLyUA3pY69hrP6WzwCIoDFY6oShYAQEAI9gwD2ezg9YNNHqJ9u295VCTS3tqy33no+lBBSQCUh0CQERACbNFpqqxAQAkKgpgig/uSGkrig0DVtcu5mEaAbO1VsaZWEQNMQEAFs2oipvUJACAgBISAEhIAQyImACGBOAPW4EBACQkAICAEhIASahoAIYNNGTO0VAkJACAgBISAEhEBOBEQAcwKox4WAEBACQkAICAEh0DQERACbNmJqrxAQAkJACAgBISAEciIgApgTQD0uBISAEBACQkAICIGmISAC2LQRU3uFgBAQAkJACAgBIZATARHAnADqcSEgBISAEBACQkAINA0BEcCmjZjaKwSEgBAQAkJACAiBnAiIAOYEUI8LASEgBISAEBACQqBpCIgANm3E1F4hIASEgBAQAkJACOREQAQwJ4B6XAgIASEgBISAEBACTUNABLBpI6b2CgEhIASEgBAQAkIgJwIigDkB1ONCQAgIASEgBISAEGgaAiKATRsxtVcICAEhIASEgBAQAjkREAHMCaAeFwJCQAgIASEgBIRA0xAQAWzaiKm9QkAICAEhIASEgBDIiYAIYE4A9bgQEAJCQAgIASEgBJqGgAhg00ZM7RUCQkAICAEhIASEQE4ERABzAqjHhYAQEAJCQAgIASHQNAREAJs2YmqvEBACQkAICAEhIARyIiACmBNAPS4EhIAQEAJCQAgIgaYhIALYtBFTe4WAEBACQkAICAEhkBMBEcCcAOpxISAEhIAQEAJCQAg0DQERwKaNmNorBISAEBACQkAICIGcCPw/S9Q6BGvchFgAAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 2 Axes>,\n",
       " [<matplotlib.axes._subplots.AxesSubplot at 0x7ff3b011cc50>,\n",
       "  <matplotlib.axes._subplots.AxesSubplot at 0x7ff3b00d6780>])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plot_diff(s_cpu, s_gpu, var='absorbance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spectrum computed on CPU in 5.42 ms. Number of lines = 4878709\n",
      "Spectrum computed on GPU in 0.43 ms. Number of lines = 4878709\n"
     ]
    }
   ],
   "source": [
    "print(\"Spectrum computed on CPU in {0} ms. Number of lines = {1}\".format(s_cpu.get_conditions()['calculation_time'], s_cpu.get_conditions()['lines_calculated']))\n",
    "print(\"Spectrum computed on GPU in {0} ms. Number of lines = {1}\".format(s_gpu.get_conditions()['calculation_time'], s_gpu.get_conditions()['lines_calculated']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thus, here, we clearly see the difference in the performance offered by the two methods. GPU makes the computation process significantly faster, as we see above."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}