{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "159cba26",
   "metadata": {},
   "source": [
    "# WB89_380\n",
    "Trey V. Wenger - March 2025"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4888afb4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-08T23:41:51.967377Z",
     "start_time": "2024-08-08T23:41:48.182385Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "arviz version: 0.22.0dev\n",
      "pymc version: 5.21.1\n",
      "bayes_spec version: 1.7.5\n",
      "bayes_cn_hfs version: 1.1.1+9.gf278c50.dirty\n"
     ]
    }
   ],
   "source": [
    "# General imports    \n",
    "import os\n",
    "import pickle\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import arviz as az\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pymc as pm\n",
    "\n",
    "print(\"arviz version:\", az.__version__)\n",
    "\n",
    "print(\"pymc version:\", pm.__version__)\n",
    "\n",
    "import bayes_spec\n",
    "print(\"bayes_spec version:\", bayes_spec.__version__)\n",
    "\n",
    "import bayes_cn_hfs\n",
    "print(\"bayes_cn_hfs version:\", bayes_cn_hfs.__version__)\n",
    "\n",
    "# Notebook configuration\n",
    "pd.options.display.max_rows = None"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa0a6c4a",
   "metadata": {},
   "source": [
    "## Load the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e46da6a1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-09T03:03:49.714415Z",
     "start_time": "2024-08-09T03:03:49.423844Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rms 12CN 0.005452432119031414\n",
      "rms 13CN 0.0029468342287699194\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bayes_spec import SpecData\n",
    "\n",
    "data_12CN = np.genfromtxt(\"12CN_WB89_380_freq.dat\")\n",
    "data_13CN = np.genfromtxt(\"13CN_WB89_380_freq.dat\")\n",
    "\n",
    "# estimate noise\n",
    "noise_12CN = 1.4826 * np.median(np.abs(data_12CN[:, 1] - np.median(data_12CN[:, 1])))\n",
    "print(\"rms 12CN\", noise_12CN)\n",
    "noise_13CN = 1.4826 * np.median(np.abs(data_13CN[:, 1] - np.median(data_13CN[:, 1])))\n",
    "print(\"rms 13CN\", noise_13CN)\n",
    "\n",
    "# boxcar smooth 13CN to 4 channels\n",
    "data_13CN_smo_x = data_13CN[:, 0].reshape(93, 4).mean(axis=1)\n",
    "data_13CN_smo = data_13CN[:, 1].reshape(93, 4).mean(axis=1)\n",
    "\n",
    "obs_12CN_1 = SpecData(\n",
    "    data_12CN[0:600, 0],\n",
    "    data_12CN[0:600, 1],\n",
    "    noise_12CN,\n",
    "    xlabel=r\"LSRK Frequency (MHz)\",\n",
    "    ylabel=r\"$T_A^*$ (K)\",\n",
    ")\n",
    "obs_12CN_2 = SpecData(\n",
    "    data_12CN[-500:-1, 0],\n",
    "    data_12CN[-500:-1, 1],\n",
    "    noise_12CN,\n",
    "    xlabel=r\"LSRK Frequency (MHz)\",\n",
    "    ylabel=r\"$T_A^*$ (K)\",\n",
    ")\n",
    "obs_13CN_1 = SpecData(\n",
    "    data_13CN[:, 0],\n",
    "    data_13CN[:, 1],\n",
    "    noise_13CN,\n",
    "    xlabel=r\"LSRK Frequency (MHz)\",\n",
    "    ylabel=r\"$T_A^*$ (K)\",\n",
    ")\n",
    "obs_13CN_2 = SpecData(\n",
    "    data_13CN_smo_x,\n",
    "    data_13CN_smo,\n",
    "    noise_13CN,\n",
    "    xlabel=r\"LSRK Frequency (MHz)\",\n",
    "    ylabel=r\"Smoothed $T_A^*$ (K)\",\n",
    ")\n",
    "data = {\"12CN-1\": obs_12CN_1, \"12CN-2\": obs_12CN_2, \"13CN-1\": obs_13CN_1, \"13CN-2\": obs_13CN_2}\n",
    "\n",
    "# subset of 12CN data\n",
    "data_12CN = {\n",
    "    label: data[label]\n",
    "    for label in data.keys() if \"12CN\" in label\n",
    "}\n",
    "\n",
    "# Plot the data\n",
    "fig, axes = plt.subplots(len(data), layout=\"constrained\", figsize=(8, 12))\n",
    "for i, label in enumerate(data.keys()):\n",
    "    axes[i].plot(data[label].spectral, data[label].brightness, 'k-')\n",
    "    axes[i].set_xlabel(data[label].xlabel)\n",
    "    axes[i].set_ylabel(data[label].ylabel)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b35029c-61ca-4c2b-9f6d-d01f95f644c5",
   "metadata": {},
   "source": [
    "## Reproduce Sun et al. (2024) model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d651feb7-f80a-40d2-a5d3-f6e123cdae15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "main line log10 upper column density 12.849858056215492\n",
      "log10 total column density 13.663493893907637\n"
     ]
    }
   ],
   "source": [
    "import astropy.units as u\n",
    "import astropy.constants as c\n",
    "from bayes_cn_hfs.utils import supplement_mol_data\n",
    "from bayes_cn_hfs.physics import calc_stat_weight\n",
    "\n",
    "mol_data_12CN, weight_12CN = supplement_mol_data(\"CN\")\n",
    "\n",
    "sun2024_tau_ml = 0.58\n",
    "sun2024_Tex = 4.34*u.K\n",
    "freq = 113.5*u.GHz\n",
    "\n",
    "# main line upper state column density\n",
    "sun2024_Nu_ml = 8.0*np.pi*freq**2.0 / c.c**2.0 / (np.exp(c.h*freq/(c.k_B*sun2024_Tex)) - 1.0) / (mol_data_12CN[\"Aul\"][5]/u.s) / (1.0/u.MHz) * sun2024_tau_ml\n",
    "print(\"main line log10 upper column density\", np.log10(sun2024_Nu_ml.to('cm-2').value))\n",
    "\n",
    "# partition function\n",
    "stat_weights = calc_stat_weight(mol_data_12CN[\"states\"][\"deg\"], mol_data_12CN[\"states\"][\"E\"], sun2024_Tex.to(\"K\").value).eval()\n",
    "Qtot = np.sum(stat_weights)\n",
    "\n",
    "# total column density\n",
    "sun2024_log10_Ntot = np.log10(Qtot/stat_weights[6] * sun2024_Nu_ml.to('cm-2').value)\n",
    "print(\"log10 total column density\", sun2024_log10_Ntot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "98346085-4810-417c-aa49-4b99e147bc61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bayes_cn_hfs.cn_model import CNModel\n",
    "\n",
    "# Initialize and define the model\n",
    "baseline_degree = 0\n",
    "n_clouds = 1\n",
    "model = CNModel(\n",
    "    data_12CN,\n",
    "    molecule=\"CN\", # molecule (either \"CN\" or \"13CN\")\n",
    "    mol_data=mol_data_12CN, # molecular data\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N = [13.5, 1.0], # mean and width of log10 total column density prior (cm-2)\n",
    "    prior_log10_Tkin = [1.0, 0.5], # mean and width of log10 kinetic temperature prior (K)\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = None, # assume Gaussian line profile\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = True, # assume LTE\n",
    "    prior_log10_Tex = [0.5, 0.1], # ignored because LTE\n",
    "    assume_CTEX = True, # implied because LTE\n",
    "    prior_LTE_precision = 100.0, # ignored because LTE\n",
    "    fix_log10_Tkin = None, # do not fix the kinetic temperature\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()\n",
    "\n",
    "# Simulate with Sun et al. (2024) parameters\n",
    "# We choose values for velocity and FWHM that look good\n",
    "sim_params = {\n",
    "    \"log10_N\": [sun2024_log10_Ntot],\n",
    "    \"log10_Tkin\": [np.log10(sun2024_Tex.to(\"K\").value)],\n",
    "    \"fwhm_nonthermal\": [2.75],\n",
    "    \"velocity\": [-0.5],\n",
    "    \"fwhm_L\": 0.0,\n",
    "    \"rms_12CN-1\": 0.0,\n",
    "    \"rms_12CN-2\": 0.0,\n",
    "    \"baseline_12CN-1_norm\": [0.0],\n",
    "    \"baseline_12CN-2_norm\": [0.0],\n",
    "}\n",
    "\n",
    "# add derived quantities to sim_params\n",
    "for key in model.cloud_deterministics:\n",
    "    if key not in sim_params.keys():\n",
    "        sim_params[key] = model.model[key].eval(sim_params, on_unused_input=\"ignore\")\n",
    "\n",
    "# Evaluate and save simulated observations\n",
    "sim_obs = {label: model.model[label].eval(sim_params, on_unused_input=\"ignore\") for label in data_12CN.keys()}\n",
    "\n",
    "# Plot the simulated data\n",
    "fig, axes = plt.subplots(len(data_12CN), layout=\"constrained\")\n",
    "for i, label in enumerate(data_12CN.keys()):\n",
    "    axes[i].plot(data_12CN[label].spectral, data_12CN[label].brightness, 'k-')\n",
    "    axes[i].plot(data_12CN[label].spectral, sim_obs[label], 'r-')\n",
    "    axes[i].set_xlabel(data_12CN[label].xlabel)\n",
    "    axes[i].set_ylabel(data_12CN[label].ylabel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2c07cfad-9e8e-44ff-b4d2-5695a10b3219",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'log10_N': [np.float64(13.663493893907637)],\n",
       " 'log10_Tkin': [np.float64(0.6374897295125107)],\n",
       " 'fwhm_nonthermal': [2.75],\n",
       " 'velocity': [-0.5],\n",
       " 'fwhm_L': 0.0,\n",
       " 'rms_12CN-1': 0.0,\n",
       " 'rms_12CN-2': 0.0,\n",
       " 'baseline_12CN-1_norm': [0.0],\n",
       " 'baseline_12CN-2_norm': [0.0],\n",
       " 'fwhm_thermal': array([0.08740951]),\n",
       " 'fwhm': array([2.75138882]),\n",
       " 'log10_Tex_ul': array([0.63748973]),\n",
       " 'Tex': array([[4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34]]),\n",
       " 'tau': array([[0.02095209],\n",
       "        [0.17150941],\n",
       "        [0.16750926],\n",
       "        [0.21752014],\n",
       "        [0.21834459],\n",
       "        [0.58001127],\n",
       "        [0.17227444],\n",
       "        [0.16830736],\n",
       "        [0.02105628]]),\n",
       " 'tau_total': array([1.73748484]),\n",
       " 'TR': array([[2.17718756],\n",
       "        [2.17688599],\n",
       "        [2.17650447],\n",
       "        [2.17620343],\n",
       "        [2.17190905],\n",
       "        [2.17186795],\n",
       "        [2.17174278],\n",
       "        [2.17160848],\n",
       "        [2.17144243]])}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_params"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cd374c3-a4b4-482e-b47f-1541b7aa2a8d",
   "metadata": {},
   "source": [
    "This simulation is consistent with the Sun et al. (2024) model, but it is not a great fit to the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "45183f49-7d7c-455a-a3ea-2a4c6ba42c8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fPN0LXNM1o/vAhByDwWA4QKlUtgg5Pz/Axwf+vJBj8616jrq6OkuPHAAj/01ssEOr2GtaFfrIBYO77hndBybkGAwGwwEWHjk+PIMX3wTFhJznUCgULR45XoAI/eSkbK7QVmloaLBpWhXKMRTMI9fdYEKOwWAwHGDhkeOFHPhRq2EA6lksOY+gUChaPHJ8J30vvu+ir1IJIvKMYd2E+vp68/RmwvUsCDoZmEeuu8GEHIPBYDhAqVSir7DAj1YVhEM4mEfOU8jlchuPnPeAAQCAMCI0sdAwTmloaLAVciKPnJLFSOxWMCHHYDAYDlAoFOgnLPTvz33zQs4fgJJ1rPcI9jxy3rxHLgItYWMY9mmuq0OQsGDlkfMGoGb9DLsVTMg5Yfny5Z42gcFgeBClUon+wkI/XtIFB8PEr1KXl3vAKoa9PnISUVBgOesn5xTiuwSQVGoe7IDAQBgkEgCAhr2gdCt69BRdrlBcXIyioiLzXKx1dXXm5ZycHCxYsMDTJjIYDA+hUChwmbAgeOSkUqj8/NBLq4WGxSzzCBZNq8Kk7/xgBybknENE5gEhJpkMXlLenyORQO3ri2CtFno2O0a3okcJudWrV2POnDkAOG+aIxE2bdo0bN++HQAsOsXKZDJIJBJMnToVw4cPR1FRUccbzWAwuiwWHrn+5l/QBAail1YLAz/fJ6NzsWhatRq12htAFRNyDlGr1QgxGLiF8HDL//z8EKzVwlBX5wHLGG2lRwm5sLAwrF69GuHh4QgNDXWYLiMjA0lJSZBIJEhOTrZI/84772DhwoXm3wwG49LFoo9cP/Mv6IKCgIYGGFlfIo/gLPxIBIDTTMg5RDzQQco3RwvoAgIApRJGJuS6FT2mj9yhQ4cQExODnJwcHDx4EHFxcTh06JDdtKGhoUhPT0diYiJWrlxpMfJMwvcRAGAWdAwG49Kkvr7erkfOyPcrkrJRqx5BKY6DxppW3UIs5CRWHjmDMDsGC6vTregRHjmFQoG1a9dixIgRqK+vR0NDA7Kzs1FQUACZTIZhw4bZ3W7s2LEYO3Ys1q9fj8zMTNYfjsFgWOBIyBn69QNOnEAgE3KdDhFBIo5zJnjkeO9SKAAl8yg5xG7oER4SYiUyIdyt6BFCLjQ0FMuWLUN+fj4KCgoQERGB8ePHm/vLtcbMmTOhUCjwzjvvsH5xDAbDjKa2tiVMg6hplQYNAgCEsMCpnU5TUxNC+b7NFBQEiY8P94dMBhO4ZiZdZaXH7OvqOBNy5hHA7LruVvSYplUASE9Px8svv4x58+ZhxYoVbm0bGhqKhQsXYt68eUhJSUFxcTELP8JgXMLodDoE8YFlKSgI4JudAMCL9/JHqFSeMO2Spra21rZ/HAB4eUETEAAAMLJBKA6prq6GuWcc3xwtIEw/58sCKncreoyQO3ToENLS0hASEoLQ0FC3hZzA2LFjsXTpUmRlZSE5ObmdrWQwGN2FhoYGu82qAOA3YgQAoJ9O17lGMXD27FnziFVJWJjFfzqhaZA1rTqkqqoKfYSFPn0s/pMOGQIAiGhu7lyjGBdFj2haBYD4+Hg0NDQgNjYWUVFRiIiIuKg+b3PnzkVWVlY7WshgMLoTdXV1ZiEnETWrAkDg5ZcDAAYRQaPRwN/fv5Otu3Q5deqUfY8cAENICFBdDQnru+iQyspKTBEWrISc78iRAIABWm3nGsW4KHqMkAOAoqIip2FH3CU1NbXd8mIwGN2L+vp62+m5eHpdcQUAIAxAZWkp+vMeOkbHc+rUKUQKC1YC28T3+ZKyUZcOqaqqsp0/mCfgyisBAEOIoFarEcA3VTO6Nj2maTUqKqpdRRwADB8+vF3zYzA8yZ49ezBy5EhkZ2d72pRugdgjZy3kpKGhUPChiuochDlidAynT5/GSGGB94wKePHCxIfNteoQi6bVvn0t/ut11VUAgP4A5Gz6uW5DjxFyMisXO4PBsOTfd98N5dmziIuL87Qp3QJnQg4Aavnm1IYjRzrPqEscIsKxY8dahNzIkRb/+w4cCADwb262mLWH0UJdZWXLrBhWHjlJWBiU/AtK0/HjnWsYo830GCEnDuTLYDCsOH4ce+rrUQbgEQAmk6m1LS55LJpWrZrwAEDJtwCozp7tPKMucUpKSlBdXQ2zH85KyPlHco2uMpMJShZCwy4GPjQLSaW24UckEpTx4Vx0J092tmmMNtJjhFxhYSEOHz7saTMYjC7JrrQ0eAHwAvAJgNKPPwY82XRSVQV0cU/WuXPnMEhYGDDA5n8t3yxlKi7uNJsudXJychAIYLCwwkrI+fCCOwLAxx9/3JmmdQvOnz8PX17gUng4ILWVABeEkb9d/P5ktNBjhJxcLkdMTAy8vLxw++23Y/ny5Q6n6BLDYsUxejo1NTXY98035uVQAENefBG46y7PGTVqFHDttcDp056zoRWOHTvWIuQiI20TDObkhHdFRafZ1GVJTwdeew3o4ObMnTt3wjysJDzcJg6acJ4mAHh90SJs2bKlQ+3pbiQmJpr7x0ms+scJVPMvLb7MI9dt6DGjVmUyGRYuXIisrCxs27YN27ZtMze3xsXFITY2FrGxsRgzZozFdgcPHryo/aalpaGurg4REREoLCxEXFwc4uPjOz2PbotSCbgTuuHcOeDDD4H5880PUoZz/vzzT3OfoiofH/TT67mF/HzuwdvZ3RJMppYpgLKzbTqsdwWICKePHm0Z3TdokE0av+hoAEDQpR7qwmgEnnmG+3333cCECR2ymyNHjuCTTz7B/cIKK28cACAuDjVeXhhkNOJeAHv++gt3REYCV13V+de5JzlxgvuIniNGoxF//fUXkvhliYOpK5svuww4dgyynu5pNhgAb/sSqLS0FFKpFAP5PpddnR7jkYuKisKyZcuQm5sLk8mEbdu2YcGCBRgzZgy2bduGpKQkjBs3DhEREZg+fTreffddHDp06KKm5EpMTATAhSlJSkpCeno60tPTsXLlyk7No9ty8CAQFgapO4GX778feP99YPZsy/VyOScQrNHpgN9/Bzo6An91NXCR07vt3bsXilZG2x0/fhyNjY1u5ZudnW3uU1Rz//0W/6lLSlrdXqFQoFocKd9oBDZuBKxtJbJ/DqypqhIZoAY++gh46CFAEJgdSElJCT7//HPHfQSrqgCVCpWVlfBraIAUAPn6mufxFBN2zTUAgFClEqtWrYLRaGzdAI3G7nEqFArMnz8fu3btcudwzBQVFUGjVgMvvACkpDhNS0SWx08ElJU596ap1cCPP6Lu1CmUWzfJiz2SLnpY9Xo97r33Xjz33HPQaDR207z++uu4++67oeLv3c2bN8NoNOJOIdSLPSHn64uV/Hl4HMCVW7YA11zDlYtzgyyPwxn79nHlZQ8ii/P78ccf44UXXsBnn32GsrIy531TNZqWc1BSAnzyCdCWeG4qFTB6NDBrFmcrT1FREbRqNcwTVz76qP1D4K/riIYG23u8vemMfowqlWWdAwBffAH4+AA//2yTXKPRYPDgwRg0aBB03SXgN/UQEhISnP6flZVFSUlJNG7cOJJIJCSRSEgqlZJUKm3T/nJzc8le8Tla31F5tIZCoSAApFAo2iU/AZ1KRUc/+4zq6+vN6wwGg2Uik8l2w5MniS5c4H5PnEjEVV20ceNG0ul0Fkk1FRVUVVVluT2fnvjyyc/Ppx+XLCGTjw/RpElEIntIqyW6+WZz+sabbiIyGi3zO36cKCeHaPNmooceIpLLiUpL7dvuCKORaMAAIn9/oooK2//Ly4nmzSPavdv2v/PniRYvps1r1xIA+vdNNxF99RW3f5OJ6JdfSP/XX3T48GHavXs3AaDp06eTTqezKDO9Xk87duywLEO9njQqFT0WHEx6vgwu7NhBRaIyXPn009x+Dhwg0uttzDOZTDR69GgKDw+nmpoabuVbb3HbP/BAS8K6OqL+/YnuvltULFZlzaPdtavlHD7/fMvvdeu4c9bQYJG+sbHRnNfevXstr2WjkSgxkWjBAm75zBmiggKbfe7bt4+2b99OISEhBIBWrVrF/XHhAlF0NLd9YSGRry9RbCxt2LCBrhfsGjbM7nHojx/nriuAAJCfnx99+eWXdtMSEVFtLVHfvkS33cYdZ3Oz+Ty/8sorBD6fgwcPOs6DxyQq29wtW0gG0L9jY1vKUi4no1JJxl27iG64gWjPHiLi7tHx48fTVVddRaWlpVwG33zDbfPZZ7Rz504aMWIEbd26lYjIfJ0Z3nyTCCClREIjJRKqra1tMWbPnpb9JiU5MNhkcU/9/fff5M0f7z//+U/LtE1NdOGXX8iX//+bb74h2rWL0idNIgB0ZMwYbl9vvWV3V+MDAogA0gJ0wcenxbYDB1rKLDeX5HJ5y0bx8UQAmV59lQoKCshoNNKxY8ds680//+Tyuuoq2x0fPUr09NNk8vGhP95/nwoKCggAXQ3QXIC2ADR+wABSKpUt2xQVEb38MtE99xB5eRG9+Sa3/tFHiQD6YsgQeuqpp2x2dfLkSerfvz+99957RBqN5b37zjstx7xsmXn1+vXr6Wphfa9e3HZ2+PHHH+kkn+7vF1+khx56iGpra6miooJMJhNRbi6RUBeI+e03or//pnNZWXTH4MH04osv2s1fwLRoEZkkEqLISDK89x5t3LDB5hlgTcXWrbT87bdpN1+XrlmzhubPn096O3UXtxMT0a23cnXzuXMt662eI2KE8waAzp49y608dozoiSeITp/ms3Xj+XARuPr87jFCbvz48W6lz87Opnnz5rVZyM2bN49iYmLs/geAMjIyOiWP1ugQIWcy0cZ+/cgI0MEnniDatYv+GjSIxvbvTxcuXKDfvv+emgYNIpo6lUgs7goKuBsqMpKreIYMMd9Ma9assbyJFy8mAugxb2/au3cv99ArK7O4ARWjR9OLAL0ovinvuotMRiM1NzeT/O67LW9YgJpyc4l27iTaupWzoXdvi//1gwYRAdQ8bRqtXbWKCuyIAuuyoH37WvJ4801q4h8QNTU1tPmzz8gk7OOaa7htDAaiw4e5bUeMMG/7sdjWK68kGjWKCCCdjw+F8hWL8GlubqaNGzeS/pdfiF57jR5/+GECQG/xDzeTWk0lYWEWx2a87TYyGY308O2301F+3QthYWRcsoRL8+9/c9uWllLzd9+RyWik0tJS8z6//PJLMplMZBA9HE3l5ST/4AMyPf20ed2Wzz+nX376ie7x86Nll11GO2NjySic24oKy3MiPJQBok8/JYqLI+rVixp27KBVq1ZReno6+fj40O5Ro6g5NJQGAvR2797UFBVFXw4bRs9ee23L9qdPcw8ogCgkhCg7m4iIGhoayN/fnwCQBKD1AP0VGEjGpiaucha2/+gjC9uEhxndeKP9c69Wm9OGi86NQqEgrVZL33zzDVVXVxMR0aeffkovDxxoTq+7/HLzb/XixdS3Tx+S8NsvWLCA9m3fTgq5nI4cOUL/lslI6+tL9PvvRES0f8QIqpVKqTYvj+jcOWr286NCgJ4U2V47dCgpAVJ6ebUc0x130M4//yQpQE8DlHjDDdxxiLbrD9AygG6XyYgqK0mn1VLZpEkWaVYB9OOPP7Zc/2vXtvw/aRLRH38QmUykUqnoxIkT3P3m40P0v/+RwWCgH374gV579FEqA2grQP3Dw+nohAmUe+ed9P4rr1BjUBARQJ8ANAqga0X7ngJQ/ciR3LKD+nHr1q10Unzc/Gf9ddeRSaejvX/+SQ8DpJJI6Ohrr1FTZaVFur4A+fr6kvDSRERERiN9mpREvwjXF1/X0PLlpFKp6Iy4DAA6e/fd9Nprr1EUQAbR+h8A2v7bb0RHjnBld//9NnaSXE76qCgigEoB8gIob88eooYG8wvN7bffTuCvu/pevehEr160Yf16ro4U2wjQmX/9i5YtW0bh4eE0V1g/darDKm3Pnj30Lp9uF0APi67tdUlJRBIJd9/yYuaXX36h16ZNsz0OgEy33GJ+uVWpVNTQ0ECkVpN8xQqbtL8vWkS/ffwxGfln1WcffUR7R4wgdUoKt69ffyUC6Hv+urh33DizXT+9+y73cnTuHNHkyaRfsYITdwcPtuzju++4F87CQst9NzYSJScTjR5NVF5Of//9t0Vdu2vzZov0Rx55hPz8/GjdunV04sQJamxsdFiWF8slJ+RGjBhh+abjInFxcW3aX1RUFMXHx9v9TyaT0bx58zolj9boECFnMNCeq6+2e+PafHx8yLhmDa1du5aaHnusZT1fUQmfUG9v+nHtWjJ98QX3MOfXHwVo5MiRdGH0aDKK365Fn3VWy0/07UuTHdhTyHsWCKDSzz93avspgN6LiCBlnz70vxtuoCKplM5ecw3RX38R7dlDlTt3kl70cBY+2yUS+jAtjfr37UtnrP5TVFYSzZ3rWtmJPv8AaA1AH/CVy7Lbb6fTIqG6AKD3AYoE6JFHHqHXhg2z2L46PJyrxIRTyAuYjwBSe3tzggKgydHRtM3Xlwigxd7e5OfnRwDIB6AnH3+cfucFtrPPHHDeB/G6H2+5havEnRz7b6Gh5t8lYWE0F6DfAVosSvMuQHLR8i9O7JAPHkyrPv2U1jz+ON0I0GSAYsTnQiaz3Oahh+znNXu2w1uhhr8mxwEUANBzANWEhdGvkycTALrrrrtox44d5A9QvhNbiwD6E9xD+zq0PPz3hIdbpLuQl9fyQJk4keimm8zL2S5cR//H74sAqgbonyKPNYETuRbXcnCwTR5qgN54/HHueho61P6+Vq+mxMREAkB1/MsRAbT02mvpv3wewro3xOfEKh+D1fLHABl5jxsdP+64jnrmGbt26flrW/yZZbUcC8uXpg+SkqjU+loRfdaEhdFGq3Vb+vYlKUBPWa0vByhfEMb//CeZRNe8o89DAJ3t1Yu0vr403teX1t5xB103diwBoFdE6aaFhpL63Xft5jEIIClAnwvrXnnFYdFduHCBbrKTRw5Au0XLZ99+m0irpVuioijPif11EyeSXqejL/r2pa8AyrGqm+x9TP362axr7t/fpiynAfShgzz2+viQ+s47W9YNHMiJUGf7fukl+vHHH+n/APoPf/6fdJD2foAkEgmNGDHCtuWonbjkhFxUVBRNmzbN7e1mzZrVpv0BcCi0oqKiHHra2jsPazQaDSkUCvOnpKSEAFBtbS3pdLp2+2z46SdKauVmdOczCqB/Oviv1MU8BNGkBaiA/722HW1053OKrwis1++34ylw9/O9k//OArQUIJXV+uzVqy3OnyEtze7271ktvwzQFQDVANR0kXbvkUioxs/PI+dD+FTbEd72PucBOhIYSKaAANJ//bXD+6Bx9Gin+eSA83C5at9HcC5O2/ujdzP9LtHvklZEyAcARXeQ3aawMNJpNA7Pi76VlzRnHxU4kXsUnFfweCech2/sCGZnn/cBigCoymrd3/z1/Rls6wCxKNbzzZj2Pmq1mq4YNYp+7ITjXgXQHZ2wH1c/ukGD6OfHH7dYV+ck/SyARgL03HPPtevzVfjU1taSK0Kux4xaLSwsxKpVq/DMM89gxIgRmDdvHkJCQlrdri1R7uXCiDsHyGSyVtO0Rx72WLp0KZYsWWKzftu2bQgMDHQ7P0eo1Gosl0rxhskEPwdpPgHQG4B4WEIRgCj+d5lMhkH8Mdob6N4MIAiA7XhB+ywA8DMAXwDRAAwAUqz2b48tAM4AeJFf/o3/rLCTVgs4PF4xlwMQAtt8B8AE4DEAE606xB8GcA7AOACb4uMxvrAQMfn5kAI4yNvwuVXeDznZ7wgAL9lZX+nvj82bN5uXA0JDMU30//8A/BstZSDwFv+xRgNAAuBXAG8DyHNik8D1RBadtzMAzLKTLgfAeBfyE1ADcHVGyD5WHfUNAN729cVrok7NaQDeCAzEJ59+iqLQUG60o6jsxEwIDkYvJ/sbx39cxVmXfHvXXi24a/cGJ9tdAPAUgO2idb9ERqJXaSlus5O+DsCTAF4BMEm0/t/g7pVT/HKkVUf4fRMnQnXggDnPf/EfexwEsA7AOyIbB3h5wcdoRC24a8sqsAjqROtqIyOxZ+tWB7kDQTodYvnfhwGEABAmXGwGd95PRkVhkmiAUjaAWHDXUgCAPgCu4v8zoPUQD5UA7gSQa+c/XXAwTgwdijHHjtnd9vHGRjTAcXlZ8yKAZ2B5PbwImGNDZgFYBeBWtNRDXqK0v2s0MDi4pgHgzbfewgfvvIN1+/Zhha8velt1+r/g44MhTgYnySUSXEmEFAD/dHIcNaGh2KpQ4Ctw19yn4K6NpwICcLNa7WTLFv4Ed5wCn4Crj4R609G5+z8A7/O/jeDKx6esDPeIQjUBgFXIZAvWgbsHb//xR2yKi2v3iQlUrg7Sc9vl0w2Qy+W0fv36Dsu/oaGBAMfetJiYGIqKiurwPOzRWR45nU5Hs2bNonv5N5MdACX26UOhUim9dOWVtACcW9oboFSA/gvQVfy6iQD1A0gqldKvdt5y9o8ZQ28HB9M9kyeT8qmnyCSRkN7OG6tS1LR4iM/7zMSJZJJKiQBawq/7kF929HkFIG9vb3o/MJC+B6gXQL4A7Z00yaLJQAlQVmSkzfZH+WMUlvf99hsd4JsrCaCbARoKUCW/vPqqq8g4ejTpRGWSnp7eUq5Tp1KwqPzs2awMCaEnAbrO359qAgPJ4OVFJj8/Mvr6kvHaa2nJxIkkAegZcH2M7J0/45QpRABt7N+fNm/aREZRM4TxppvINHasxT4PAnQnuOY/AOTr40Pgf5dPmULGceNox0sv0e8REVS6bBndN2AArQboQzvN8MsAiggMpAet1v+bz+9mgJ699VbS//UXmfz8SHfFFaTbt4+MN9zAXW/R0WSQSqn05pvJG6A3RXl8ZNUEY+/z5IABlA2uGdMPoGOiZvsZAL3zzjsu3QPG224zb/fiww+T5s8/6ZCd5mOTvz8ZPvmEdHK5zX+14Dxj+tdfp1K+fxgB9ARA1wPU5OdHhtdfpz1paXQKoG/A9Y2aDdBgWDYN7hX91syaRXsiI+m3J58kHx8fuhegdIAa8/JIqVTSz5mZVNenjzn9m/y9MB4tzYoPA/QrLPsALnjmGdL4+9scx5JbbyWA62f3JEBGfr0+OJieBagYXJPqPwD6z3PP0V23306a9HTaNnYsPXD99dS4cSMZ77qLvn75ZdqRkkLGKVPIKGo6brxwgUzR0UQAGVw4P4bXXqPDkZF0O0D/feEFquKb2MPB3eP15eVk4vvpFgN0n+hYzsPSg/XnyJH0yl13Ucn8+ZTx7rt0YsoUesfq+F/h87V3vemzs6m+utpi3WN8GX07fDj5+vqSP0AvTZ1Khv/+lwigPwYMoB+tmtatP+X8NWK9Poo/V1KAmqzuB5NU6tK1LZfLKT09neoqKkinUJi3rxg6lOpyckjHN1NmA2SSSKhR5KF9rVcvArh6Ty6Vkp6/vg54e1OtqG7U/fgjPfDAAzRmzBha/+mn9NSTTxLAtQIIaR4HaAZ/f9Z5e1PurFlkvOceqnjqKVrywAP05JNP0pPgWg2m8Mc9dOhQmgzQOwA9IMprM0ALAXpOKqWhffpQIbj62xvc88JROatbaUkpAej0unUe88j1SCHXGTgTYVFRUS6JsPbIozU6atSqkPeMGTNoGLg+VOvXr6eGhgbS6/U0Z84cioiIoPvuu48ee+wx80Ng1KhRNGDAAPPyJ1YVlenBB213VFrKjbBas4ZIIiH9hAlEGzZwHWADA4nACZZBgwZx6Y1GOr5pk3kfkyZOpC9SUqgJoI0ANRYUEB08SKYPP6Tc/v3p+ssvp40bN5JcLqf//ve/BIASEhJIr9fT5vR0s20FkyeT0aoPijw83Jx+z7/+RcfS04mISHP6NJkeeoi2Pvss3X333QT+ATKKt+mykBAaDVBAQAD98ccfFiM8n3rqKbPtb4r69Ik/hmefpddee43OnTtHpFRyo21FqNVqKi8vp08++YTy8vLsn8CKCm60rrBvk4lo/XqiRx7hRmkRmYUTAfTV889TZGQkHTlyhP78808qKSmhvn370r333ms3+8LCQlq6dCmp1WqiqipSbdtGGqmU8gFavHgxLVq0iACQv7c3FY8ZQ4Y5c+jbb76hDz/8kNauXWseKEBqdcuIR62W60yv1xM1NlKZaDDGcm9vOg3Q1q+/5kafAly/GDvlN4kfASl8Hhf998zkyQ5H3NqwfTu33XvvtayrreX6jt1/P1FTk+0Iv5wcon/8g0wHD9L7L79MgyQS2sFvb2xoIENCAhWK7pn1mZn86TFZ2Cx8Xl+0iI498ww9f/31dI/4pUU0gjo9PZ0AbmStBfX1RImJ1PjddwSAfHx8aNeuXfTZZ5+RwWCgV155hUJDQykjI8O8v3fffZd0dsRqgJVdt0uldPr664mKi+nmm2+mMIBuHTGCNm3a5FrZEnHX9Zw5RH//3WLv9987HHFpjUqlooyMDNJqtUREdM0117TcV0RcP7+XXqKjH39MbyxeTGVz59Lz/IP99cWL6esZM2hHv35Uc+qURb5Go5FuvPpqOuDnR7r77qNd991nHoVbcNttdDwykrQNDdzgj8hIrkM9ETdAAiDTNdeQXq+npoICMun1dObMGVqzZg03Gthk4gbqNDQQqVS0JTaWrgKofuhQMgUEEL35JhmXLSPVJ5/QqOho8vHxodqUlJZ6CjAPnJk+fToZT54k+vlnov/9j0uzZo3r5S+i+pNPqGTyZDIJ19XffxNlZVFjYyOZlEruGE+eJPrgA7p7xgwCQIGBgbT/779JytuzcuVK0jc3t1w3ublE1DI6WqfT0b59+yiBH0VMAKU//zydOXOGG+yTn29jV319PT3zzDP0/vvvk8FgoDNnzpBCoaDIyEjztfgvgN7z96eNq1fTmTNnuHqTiEijoczvvqMZM2ZQmLc3bRZdz+uGD6em22/nBur8/jsZn32WK//ERDKJBpI18CLzd3vProvkkusj19k4E2Eymeyi+8i5mkdrdKSQE6isrKScnBynQ7IPHTpEzzzzDJ07d46WLVtmvsHWfvst6X/7jf5aupR0x45xo1OdUVxsWYnn5ZHpo4/o+zVr6DQ/NJyIq8ADAwMJAP3xxx9UWlpKEb160ZOPPuo0e4PBQJs2bSKVSsWtMJm48BRSKVdJHT5s+QD74QfKz883Pygcceedd9p9CCcmJtqkLSkpoTFjxtCKFSu4FR98wO3ru+84ofXyy6QrL7cbsqXdKS/nQoS8+qrdkCx6vd510UNEVFFByrIyMplMpFar6Z133qGcnJyLMnHVqlW0Zs0aKi4upi1btnArDx0iSk/nbK6uJtq3j/RffcV5R1avpo0bN5Kfnx+tXLmSHn30UbMnRQPQ0b173TOglXPvDJPJ5HCQVlpaGj344IOcEOb5+++/6aabbjJfP7NFAzEaGxupuKiIO24r4WEymWjlypV0jBfo9jh+/DgdOXLEYp34Abt7926aP38+aTQabsSolZADQEFBQdTQ0EBFRUUWdtfW1tJPP/3k3rXSARQVFdHPP//stK7atm0bPf/88xb220Ov13NlQVw5LVy4kNavX29RZqTTWY7cl8u5EZInT7pss16vp/Pnz9v9Ty6XcyPrTSYilYqopIQG8iNup0yZYpnYZCLqoE751pw/f56eeOIJyueF14EDB+j1119vqVe//JLotdfMdYpFmQnk5BD98kubbdi/fz+NGjWKXnnlFSorK2sJn+QAc/gs/nouff997t4Wysxk4s4nEfdytn490ZkztHfLFjr90kuOQ6BcBEzIdTAymczhiFNnAq2982iNzhBy7mI0GmnDhg30zTffkMlksn8TtwO7du2i7du3m5cNBoNtrDtXKCsjEuIJcRlzgs6FeF8CVVVV9Omnn1J6ejrdyjdBeXl5OfaWiTEaiSorLVZ1VJn1ZHQ6Hf36ww/mMhOuhYKCAnr88cdp1Usv0f6vv/akiS6jUqlo//79HRr6gMjJdVZTYyHi/gluBN/y5cs71J7ugKfvzfz8fIqPj6cLQrzOboCny0yMeu9eql+61L1Yoh2Eq8/vHjPYobNJSEhATk6Ow/9dGUTRHnl0R6RSKe67774O38/kyZMtlr28vBykbAXraVqs8nWFvn374tlnnwUAzJs3D2fPnoVarcY1fBR1p0ilAD8ZOOPiMAa0DIsQrofo6Gh8/fXXnjKpTQQEBGDixImeM6B3b+Cdd4DaWmDRIqQolfiXSoURwqwLDI8xZswYZGRkeNqMbov/pEnwnzSp9YRdCCbk2sisWbOwcuVKyOVyyGQy8/rs7GwAQGxsrIMt2zcPRvfksssu87QJDMbFsWCB+eeAXs7G7jIYjI6ECbk2Ehsbi/j4eCxduhSpqanm9ampqcjIyLAQZgD31g9wYVLamkdbICIAgLIz5rRrI3q9HiqVCkqlEj4+Pp42p1vAysx9WJm5Dysz92Fl5j6szOwjPLeF57gjJNRaCoZT0tLSUFdXh4iICBQWFiIuLg7x8fE26caNG4fw8HBkZWW1OY+2UFpaisGDB7dLXgwGg8FgMDqXkpISREZGOvyfCbkejslkQnl5OYKDg9s9WGF7oVQqMXjwYJSUlLgUxJnByqwtsDJzH1Zm7sPKzH1YmdmHiNDY2IiBAwdCKpU6TMeaVns4UqnUqZLvSoSEhLCb2E1YmbkPKzP3YWXmPqzM3IeVmS2hoaGtpnEs8RgMBoPBYDAYXRom5BgMBoPBYDC6KUzIMTyOn58fFi9eDD8/V6ajZwCszNoCKzP3YWXmPqzM3IeV2cXBBjswGAwGg8FgdFOYR47BYDAYDAajm8KEHIPBYDAYDEY3hQk5BoPBYDAYjG4KE3IMBoPBYDAY3RQm5BgMBoPBYDC6KUzIMRgMBoPBYHRTmJBjMBgMBoPB6KYwIcdgMBgMBoPRTfH2tAGMjsVkMqG8vBzBwcGQSCSeNofBYDAYDIYLEBEaGxsxcOBASKWO/W5MyPVwysvLMXjwYE+bwWAwGAwGow2UlJQgMjLS4f9MyPVwgoODAXAXQkhIiIet6Vz0ej22bduGadOmwcfHx9PmXBKwMu98WJl3PqzMO5dLtbyVSiUGDx5sfo47ggm5Ho7QnBoSEnJJCrnAwECEhIRcUje/J2Fl3vmwMu98WJl3Lpd6ebfWLYoNdmAwGAw7EBFmzZqFRx55BETkaXMYDAbDLkzIMRgMhh2qq6uRmZmJ77//HlVVVZ42h8FgMOzChByDwWDYoampyfy7uLjYc4YwGAyGE5iQYzAYDDsolUoMBjAIQGFhoafNYTAYDLswIcdgMBh2aCovxwUARwEUnznjaXMYDAbDLkzIMRgMhh189u8HAIQBaDp61LPGMBgMhgOYkGMwGAw7hOTmmn8T88gxGIwuChNyDAaDYYfex46Zf/uXlnrQEgaDwXBMtw0IrFQqUV9fD7lcjqioqEsu2C2DwehAiBBRVmZe7N/YCCJi8xUzGIwuR7fxyCmVSixfvhzTp0+Hl5cXwsLCEBUVhZiYGMhkMnh5eSEiIgLTp0/H6tWrPW0ug8HozjQ1wctoNC9Gm0xobm72oEEMBoNhny4v5IqLi5GQkIDhw4fjwIEDiI+PR05ODurr62Eymcyf+vp6ZGdnm/8fMWIEZs+ezeI/MRgM96mvt1i8DEC91ToGg8HoCnTpptVVq1YhPT0dL7/8MtatW+c0bWhoKMaOHYuxY8di7ty5AIDMzEzMmzcP06ZNw4IFCzrDZAaD0ROwEm0DAJysq8OQIUM8Yw+DwWA4oMt65F566SUoFArk5OTggQceaFMe8fHx2LZtG0JDQ5GSktLOFjIYjB4LL+TO8Yt+ABQVFR4zh8FgMBzRJT1y+fn5mD17NsaOHdsu+c2dOxf5+fk4dOgQxowZ0y55MhiMHkxdHQCgBNzMDr4AmktKPGkRg8Fg2KVLCrn2EnAdnSeDweih8B65OgD1APoDUItGsTIYDEZXocs2rTIYDIbH4IVcPYBGX18AgI41rTIYjC5IlxZybQ0j8uyzz7azJQwG45JC5JHTBAYCAIw1NR40iMFgMOzTpYVcenp6m7bLzs5uZ0sYDMYlhcgjZwwNBQCY+H5zDAaD0ZXo0kIuNzcXGzZscDl9cXExJkyYgKKiog60isFg9HQE71s9AElEBABA2tDgQYsYDAbDPl1ayAFAUlKSS0F9ly9fjujoaOSKJrpmMBiMtmASCTnffv0AAN5KpQctYjAYDPt0aSGXlJSEs2fPYsWKFQ7FnOCFS0pKwvDhw5GRkYHhw4d3rqEMBqNHQXwzqtrfH968kPNlU3QxGIwuSJcWcsuWLTN/r1ixAkqrN+LVq1ebvXBJSUkoKCjAzJkzkZGR4QlzGQxGT0GhAAAYevWCDy/kAtRqT1rEYDAYdunSQk7MsmXL8Pbbb0OpVJq9cImJiRg+fDhyc3PNog9gMeMYDMbFIW1q4n6EhsJ/4EAAQLBW60GLGAwGwz7dRsgBnJhLSkoye+EWLlyIgoICJtwYDEb7YTTCm/e+SUJDETR4MAAg1GSClok5BoPRxehWQg4AVqxYgbFjxyI7O9vCC8dgMBjtguCNA+AVFoagyEgAgAxAAxu5ymAwuhhdWsg5mug+JycH69atc3s7BoPBaBW+L64WQIBMBml4OABOyNXz8eUYDAajq9ClhZyzeHCpqakOBRuLI8dgMNoML+SUAEJDQwGZDAAQDKCBze7AYDC6GN6eNsAZGRkZyM/P5ypTO8jlcmRmZkLGV7QCeXl5nWAdg8HokYiEXEhICCCqfxpLSz1kFIPBYNinSws5ACgoKHB7G4lEclH7TEtLQ11dHSIiIlBYWIi4uDjEx8e7vL1cLsfSpUshl8tRVFSE+vp6pKSk2M0jLi4OMTExmD17NmJiYlBUVIT09HTI5fI2T1HGYDAuAj70iFnIeXtD5eWFQKMRqrIyz9rGYDAYVnRpIRcTE4OcnBy3txs/fnyb95mYmIjo6Gikpqaa18XFxaG+vh7z5s1rdXu5XI7k5GSkpqaaPYV5eXkYN24c4uPjbWLc1dfXIy0tDWlpaeZ1sbGxyMrKavMxMBiMi8DaIwdA7eeHQJUKmspKDxrGYDAYtnRpIRcVFdWm7doq5PLy8rBy5UoQkcX61NRUjBs3ziUht3TpUgsRB3CCNDU1FcnJycjOzkZsbKz5v6ioKMyePRsHDx5EVFQU4uLiLP5nMBidjHUfOQCagABApYK2qsqDhjEYDIYtXVrIrVq1qk3bib1p7pCeno6YmBib9cK6zMzMVptYMzMzkZmZicLCQov1gjjLyMiwEGrh4eFISkpqk70MBqMDsOOR0wcFAXV1MPJTdzEYDEZXoUuPWnU0yKGjtsvOznboBZTJZC41d0ZFRdkNUSB46Fj4Agaji2NHyBmDgwEAJhZHjsFgdDG6pEfu3LlzWLlyJZYuXdpueaakpGD27NkYM2aMwzRFRUUOmzXDw8Nd6q/nSOwJI2knTJjg8P+cnByMHz/erlfQVbRarUX0eWF+Wr1eD71e3+Z8uyPC8V5qx+1JekKZn96zB1eBE3LBwcHQ6/UgXtChoaHLHVtPKPPuBivzzuVSLW9Xj7dLCrnhw4cjISEB06dPx8qVKzF06NA251VcXIzExEQkJyc7FXFyudxpPjKZrNU0zkhPT4dMJrPpZ1dfX4/k5GTExcVh3rx5yM7Oxrhx45CRkdGmPoJLly7FkiVLbNZv27YNgYGBbba/O8MGjnQ+3bnMNXv34ioA/n36oLKyEps3b0YfnQ4jABjr6rB582ZPm2iX7lzm3RVW5p3LpVbeKpXKpXRdUsgB3MT3P/74IxISEiCRSJCcnIzbbrvN5e3/+OMPrFixAgqFAitWrMDw4cM70FrnZGdnIzs7GxkZGTYx7wQBJxAbG4vZs2cjLi7Opp+dK6SkpGD+/PnmZaVSicGDB2PatGnmZqJLBb1ej6ysLMTFxcHHx8fT5lwS9IQy36TTAQAeeOop9L/nHgDAhXXrgNxchBBhxowZnjTPhp5Q5t0NVuady6Va3kKLWmt0WSEHcF6wbdu2Yfv27VixYgXi4+MRHR2N2NhYREREQCaTITw8HPX19ZDL5airq0N2djby8vIQExODl156CTNnznR5X864GG/crFmzkJ6ebneghL2RsLGxsUhOTnZpcIU1fn5+8PPzs1nv4+NzSd0AYi7lY/cU3bXMVSoV/HkhFz58uPkYfPr0AQAEarVd9ri6a5l3Z1iZdy6XWnm7eqxdWsgJTJ06FVOnTgUArF+/HgcPHsSBAwfMAXdlMhmioqIQHh6OefPmITY2tt09cPX19W1q6pw1axZSUlJcCl0iIOwnKyvLbSHHYDDaTllZGYShUoF9+5rX+/C/g3iRx2AwGF2FbiHkxMycOdNlL5u7yGQyh6NK5XK52/HpkpOTMWHCBIfhRWbNmoWioiLk5uba/Z+NcGUwOpfS0lL0539LwsPN6/0EIWcwgIguevYYBoPBaC+6dPiRziYhIQFFRUUO/4+Li3M5r5UrVyIiIsJGxK1cudL8Oy8vD+Gih4WAIOAcjXBlMBjuQyZTq2lKSkogExZE3S38+abVXgDUanV7m8ZgMBhthgk5EbNmzUJeXp5Nf7js7GwAcHnGhezsbMjlcrueOHHe8fHxdkfhZGZmArDff47BYLjP3489BoWXF167+mrU1NQ4TFdaWupUyIUAaGxs7CgzGQwGw22YkBMRGxuL+Ph4m/h1qampdkecRkdHIzo62mJdUVEREhMTUVhYiOTkZCQnJyMxMRGJiYmIi4uz6GeXkpKCxMREi+3z8vKwdOlSu/tjMBht4/LMTMgAvHHsGLI+/9xhusriYgQIC6L7T8r/DgYTcgwGo2vR7frIdTQZGRlIS0tDcnIyIiIiUFhYiMTERLuDDoRRs2Li4uJQVFRk0YQqRjx9mEwmQ2pqKhITEyGTyczNutu3b7+ooMAMBkMEkcUghaBt24CXXrKbVH7+PLeJRAKJOFwPP7NDCIASJuQYDEYXggk5O7g696m9QQruxn6TyWRIT093axsGg+E6VFyMIFH/uOCzZx2mbSwpAQAYAgPhIxU1WPCizhdAY21th9jJYDAYbYE1rTIYjB5N865dFsuDq6sdplVXVAAAyHq+5l69WtI42Z7BYDA6GybkGAxGj6Zp924AwFZ+OUqng0GhsEmn0WhA/GAkaUSE5Z9eXlDzHjqtk8ESnc2OHTtQXFzsaTNcwmAwoKqqytNmMBg9DibkGAxGj0Z/5gwA4MyAAagA4AWg0s5o8bKyMvOIVS9rIQdAzUdZ19bVdYyhbnL06FHcfuutuHb0aGi1Wk+b4xwi/N+dd+KmgQNx4MABT1vDYPQomJBjMBg9GqnQ723QIJQGBQEAqvfvt0knDj0isTNiXOvry+XTRYRcbmYmKgFs0euxeeNGT5vjlIInnsDH27bhjMmEPYsWedocBqNHcckJueXLl3vaBAaD0UkQEbxLSwEA3tHR0PDx4BRHj9qkLS0tRZiwYEfI6fz9AQDGi5h3uT0ZmJEBGYApACZs3uxha5yjFdl3959/gthUZwxGu9EjR60WFxejqKjIPBdrXV2deTknJwcLFizwtIkMBqMT2Lh+Pe7WaAAA0+bMQX1VFVBcDL2d0eUWwYDDwmz+NwRwEeZMdvrXdToqFW44fdq8eIdCAaPR2GUnFA8Xid9ogwEF33yDEXPmeM4gBqMH0eU9cqtXrzb/duZNmzZtGry8vODl5YWoqChzcN+3334bK1euBBFh+PDhdqfEYjAYPZP8TZvgDcAolWLUrbci+KqrAAA+djrdO5rVQcAYGAgAoC4g5FS7d6OXyYRmfjkKQMmhQx60yDGN1dUYYDQCAI7wYrhmzx5PmsRg9Ci6vJALCwvD6tWr8dNPPyHUOiSAiIyMDMyZMwdz585FYWEhGhoaYDKZUF9fj5deegnr1q3DihUr2LRXDMYlRD0vblQREYCXFwZMnAgACGtstBkgUF5e3iLk7NQ1JIQgUSo7xlg3KOb7xO0NCMB5vu9ezdatTrbwHEX8FIcKiQT1/Ew42pMnPWkSg9Gj6NJC7tChQ4iJiUFOTg4OHjyIuLg4HHLw1hkaGor09HQkJiZi5cqVaGhoMP8nkUjMvxcuXNjRZjMYjC4AEUEnBP8dMgQAEDFmDLcI4KSVmCgvL0dfYaFvX1jjxTe3doWm1ca//wYAaEaOREm/fgAAw759njTJIZV8+JfqXr3gddllAAAffgYNBoNx8XRZIadQKLB27Vps374d9fX1KCoqQnZ2NtauXes0btLYsWOxdOlS5ObmsoENDMYlTHl5Ofo2c42PgVdcAQCQDB0KAAgHcPLgQZv0/YWF/v1hja8QkqQLTNEVxPfxC50yBU0jRwIAAk6d8qRJDlHm5QEAmgcMQMjYsQAAWX29J01iMHoUXXawQ2hoKJYtW4b8/HwUFBQgIiIC48ePxxwXO8jOnDkTCoUC77zzjnkOUwaDcelw5MgRXMH/9ho9mvsREgK1ry8CdDqU7t0LzJ0LADCZTKioqMAAYWM7Qs6f99JJm5tt/utMqsrLEa1SAQBGzZ6Ns1u2ANu3I7isDERk0QLhaYgI2iNHAADBY8Yg5KabAACRWi20Gg38+JHADAaj7XRZj5xAeno6Xn75ZcybNw8rVqxwa9vQ0FAsXLgQ8+bNQ0pKCoqLi5mXjsG4RDh69KhZyOHKK83r1b17AwAaeIEBAHV1dZDq9S3hRwaYJZ2ZoIEDuW+dzqMBeP/46isEANBKJOhz3XW4Jj4eADDMYECOnfh4niQvLw9X8KJz8L33ojffRzEUQO62bR60jMHoOXRpIXfo0CGkpaUhJCQEoaGhbgs5AaG5NSsrC8nJye1sJYPB6IocPXTIrpCTDBsGANAVFJjXlZeXo5+w4Odnd7BDQFQUAGAggBoPTtN1bMMGAICyTx/Aywt+l18OvUQCfwA716zxmF322PzTT7iG/+07eTIkgYGo40f/HuxitjIY3ZUuLeTi4+MxfPhwzJ49GykpKRftTZs7dy5mzpzZTtYxGIyuTF1eHgIAGH18gOHDzet7jRoFAAhRKFDP99UqLy+3bFa10zwpHTwYADAI8NicoQaDAc38gC8/obnYyws1vPBs5vujdRXOZGTAB4A6ONg84MTAl395VhaIyIPWMRg9gy7bR06gqKjIadgRd0lNTW23vBgMRtdEr9fDh/e4GaOj4eXlZf7Phw+BMRjA2bNncd1117U60AEAMGgQAM4jd6KysmMMb4UTJ05gqMEAAAjmBw4AgKJfPwyUy+HrZCBYZ3PhwgWE8KOGpRMnmsVxxE03AXl5GCiX4/z58xjGe0gZDEbb6NIeuaioqHYVcQAwXPRmzmAweianT5/GMD4IrQ8fBNgM71kbAqCAF3vnz59v8cjZ6R8HAOjfHyYAPgAUombZziQvLw+X8b8l/GhVANDwo3Ejqqu7jJcrKysLQoO234QJ5vXe114LABgNrh8jg8G4OLq0kJPZia7OYDAYrXHkyBFE8b8lUVGWf/JNfGIhl5OT07pHzscHSn5mAo2dKb46g9zcXLOQw4gR5vU6vg/gNUYjKioqOt8wO+Tl5WGUsHD55S1/8E3CV4I7TwwG4+Lo0kKuKw2jZzAY3QexkIMDITcYQMHZsyAiHDhwAEOE//nRqfZoCgkBAOjOnWtPc13m5MGDMMu3K8xDOdDIB9odA6Cwi8STy8/Ph1m+iYUcLzoHAjhnFcuPwWC4T5cWcoWFhTh8+LCnzWAwGN2Mo0ePwtyJwro7xaBBMHp7wx9AYH4+ioqKUFdXh6uEF0eRQLLGxDe7Np850+42t4bRaITPoUPwAqAfMMBCcDYPGIBmLy/4A6jjZ33wJEajEYWHDiFSWCEWcr16oZnvb0hdbHAGg9Ed6dJCTi6XIyYmBl5eXrj99tuxfPlyh1N0iWGx4hiMS5sjhw879sj5+kJ+990AgFlnzmDXrl2QABgtCDnrPnUiAvjmTNOFC53eF+3UqVMYy8ev877xRss/pVKU8VN1qbuAkDt79iwi1WoAAPXpA4SHW/wvGTcOANC3tBQajabT7WMwehJdetSqTCbDwoULkZWVhW3btmHbtm3m5ta4uDjExsYiNjYWY/j5EwUOXqS7Pi0tDXV1dYiIiEBhYSHi4uIQzwfd7Ig82mN/DAaDo6GhAfqyMgQCIKkUkiFDbNL0evNNYMMGxBoMGP7Pf2IogECTCfD1teh7Zo3suuuAzEyM1GhQVlaGyMhIh2nbm7y8PFzP/5ZMnmzzv+6664ANGzCsC8y5umvXLnP/OInYG8cTcMMNwC+/YAwRTp48ibGiEbgMBsM9urSQi4qKwrJly7Bs2TIAQHZ2NrKyspCdnW0h7GQyGcaPH49p06Zh6tSpFzUlV2JiIqKjoy3ClMTFxaG+vh7z5s1r9zzaY38MBqOFXbt2IZr/LYmM5MSZFX5XXomy0FAMUigwtrEReuGPK64AvB1Xiz5TpgAAbgCwLz+/U4Xcof37sVhYsCPk+qakwLhhA65vbkb1jh3oe8stnWabNVu3bsVNwoIdkSZ45MYD2HXkSPcUcsXF+HH+fPz4xx+45t57seSNN+Dt5NphMDoM6sIkJCQ4/T8rK4uSkpJo3LhxJJFISCKRkFQqJalU2qb95ebmkr0icbT+YvNoj/21hkKhIACkUCjaJb/uhE6no40bN5JOp/O0KZcMni7z1atXEwD6D0AEEN11l8O0JffeSwTQhwClDxzIpX/4Yec70OlI4+VFBNAHzz7bvsY7oLGxkf7zn//QXT4+RAA1y2RERqPIpJYy3xkaSgTQXifH3dHU1dWRl5cX7RfOwfff2yaSy0kvlRIBtPzxxzvfyIvk9/feI5VwfACtAugf//gH96dW61njeiCerlc8havP7y7dR641z1psbCxSU1ORk5MDk8mErKwszJkzp837S09PR0xMjM16YV1mZma75tEe+/Mker2+9UTtRVMTsH07sG8fV3WKkcuB558Hdu7scDN27NiBPEcdtA0G4MIFQKezWG3k45m1hoEP9NomiIANG4CcHNfSG4225eiM0lLg/feBhoY2mdcqx48DZ89i9+7dqKys5GwrLbVMU1kJOAmtcfz4cfP9P0VYOWWKw/SDHn0UAPBo7954MiKCW9maF8vHBw1802vTb785TteO/edefPFFvPvuu7iHv9/8Zs0CpParbmNcHABAn5XFzQdbXAyUlLi+M6USMJnabKtarcZ1112HK41GTBRWTppkmzA0FBf4LjFDrO5bImrf/ocGA6DVQqvVtuke01hdc5t++w3+8+cjAEAjfx7mACj5/HNkh4bC1KsXkJvbZeL5tTtGI3D6tHmxrq6OmyHFZALWrAH4Ed0mkwlNTU2db9+xY8B3313UdewWXeE8d4aqbCsjRowgpVLp9nZxcXFt2l9UVBTFx8fb/U8mk9G8efPaNY/22F9rdIRHzmQy0fvvv08DBgygU6dOkclkonfS0mjbY48RbdlCdPYs0bRpRPPnk/H774nOnyfN2rX07r/+RYsWLSJjUxPRokV07P336V//+hclJCTQ8ePHiWpriTZvJnrwQZInJNCxw4fJZDKRYfNmMoWEmN9+aeVK0uv1tGDmTHr27rtJkZDArZdIiIqKiJYuJVqxgnRKJW3YsIE0p04RVVYSEdGpU6dIpVK1HEx1NVF+PpHJRFRXR/Tkk0Qff8wtE5HRaKTCp56i2ssvp92PPEIDAMr08iJVbCzVT5lCzT/8QLRrF5kMBjJMmcLZMWwYUXExUWMj5T34IH3p40OFvXuTdssWouxsoldeIWpo4Pav0ZDh2DGq6NOHnvP2pldffZUqystp56ZNRKdPWxa80Uik0xH9+itRczMpCwvp1J9/EuXkUN3y5UQAmcLCqLG6mj7//HOqXreO6IEHiPbuJVq7loynTtEbb7xBH7zwAhmCgsj45JNU/9571DBtGikOHaI3kpIoccoUUvBlJaZ4wgQigDTDhhEdO0bGPXvIkJxM9MEHwoVGhnfeId3587Rn0SIyPPMM0W+/Ed14I9GddxLx11/1sWN0Ni6OGm+4gfSvvkr01VdEhYVEAQGkCQqiXgBde+21pH/7bW5/b75J9M03ZJo+nQigxoAAKjtwgL5etIgOHzpEtH49mUaNoqw33qDYa6+lpQCtFHlK6MABxxeyQkEkvq4kEqKKilav/8ZFi4gAOg7Q5OHD6dyWLVR2+DCZlErSarX094MPkjooiOpfeYV+evVVenvkSMrdv9+8fUNDA6WkpNCuXbvoxIkTpNfrzfeVGK1WSx988AHJAHpXfEx//GGRTuyt0OTlcV47gNL+7/9IGxBARomE6u66i2j3blIoFLRr1y4y6HSUn5tLP//8MzU3N9PpI0do38cfk1YiocKoKKKsLDI+/TSZcnOJFiwgmj6d6I036NyxY1RXW0t5y5dT/po1pP7Pf4jOnyej0Uj/98gjdBlA14pt7dfPfC9ZU/Dee2Zbzz31FBnnziU6dYqef/55Cg4OpgULFtCh/Hyib74hzTvvUEm/fnTu3/8m2rCBSKMhMhpJExdHuqFDyVhS0lJ+Oh3RTz9x97PRSFVXXUWNvr50X0gI3TNkCL2TlkZ/btpEtG4dHUpNpfvuuYc2bdpEv/76K23fvp1+5e8v0unoj0ceMR9LvUxGtwUG0uP8skoqJdXJk0S3395yvPznq759KToqioqLi0mj0dDGjRvpwoULNmVQVlZGBQUFRERUvH8/Fd15Jyn/9z+iZ54h+u47IoOB6PhxKly2jE5edx3tGTCAfhg8mFY8/DBV5+URbdtG9NBDROvWkUGvp4cffpjm3HUXmUaPJnr2WSK9nmpffZVODBtGG5YtI4NCQVRSwl37CgXR2rVEp05RU1MTGQUvr8lEtGkTlX7yCZ1LTeXqGwGDgbufAaL160n+3//SRwEBNLRvX6pfurSlDIYNo0/i48nb25t27NhB9PXXRMuXc3XYrl3m+njdd9/R7VddRTk5OZYFYzIRZWbSmRdeoIzwcNrx6ae08aefSKfTkclkoldeeYXmzJlDR44cITpxguiee4i2biXau5fUQ4YQAWR8911zdrW1taRvaiJKTyeaM4eIrwvvuO02quLPi6mxkbvWH3mEGrZupfT0dNr48cekW7OGaN8+ItFzo6GmhjJefJGO791LxvfeI+XUqURHj9q9zi8GV5/fXVrIRUVF0bRp09zebtasWW3aHwCH4ikqKopiYmLaNY/22F9rdFTTavINN9CrAL00dSodGDOGFKJKTBcZaVOxEUAagO4EqGTECCKAGgCKAAgA3TxkCNUEBVmkfwGg2KAgqraTl9HOOutPbVQUrfLzIx1AFb6+9OTgwXQbQK+Hh9OFtDSiDz8kCgvj0l91FdHw4eZtcx94gCorKuiXm29udT8EUD3fTCR8LgQG0tnAQIfpm4cMIXrhBTIEB1usf8YqncHfn3RW5eLKJw0gnZvbNAm2BQaS4rnnqPH+++nXa6+lfzo5DgKIjh2j6muvJQJI7iDthYgIOp2URPJWbPgOoM9dtLdKVObnADptnSY0lIgXSY4v5OSW9JMmuXbxy+Wk5JtXxR+FlxcdkMns2roSoEfGjqWUl16iO0eOpF8BmgvQIwC9DNBhiYRmRUTQRx99RF899hjlXXMN/d6nD20BSCnOa/ZsG3Msmp1MJlKLxanV55hEQvsAMgCkBUgFtHpOxJ+jEgk9amf9Wf461gFUKf7vf/9zWIwmvZ4OWNnaHBVFswB6B6A5AH0hkdi1wyiRUK1w7wKUDdDIgQNp7ty59At/HysBUvv52WxbAlCpaHktQBKAZgD0JkAbATJKpaSMjrYse4Dq+LIjgI488ghX5jk5ZBo8mExWdYAcoK0AbQHoPYDeCgujzP/7P7r7rrvohVtuoeX9+tE4qZRWSqVUfvnlVG/nOBv69HHrHv4boJOiZZVIZF4AqMHf32Ybrb8/PQZQcr9+VDFrFlFUlE2azTIZ/TR7NtU++2zL9e7tbf5d48CelQAdtrNPZXg46V98kSr45VSplB6cPZv+85//0Javv6bS11+3PecAVQYF0QE/P5rOl+tuqzIXfwwA5T/2GGVFRVGZ1X+aoCBKA6gAoEaAfgwPpz2ie7peKqVbAMoX29yrF+276y5afsMNtNvO/s4mJ7tWf7hBjxByREQrV66kxMREeuedd1wWIytXrnR7Pw0NDeRMWMXExFBUVFS75dEe+7OHRqMhhUJh/pSUlBAAqq2tJZ1O124fBe+haY/PbrQuOvIBCgIor5326conl++TRAB9D9BZ0X8nHGzzA2BRIWsA+rqD7dR3Ypm05WMtulUAfQTQb3D8ALiYj0kmI9OIEaT/7bfWr+XKSjLecw8Z776b9Lt2uXz9lyxeTAYHIsPZx95Lifhz3Fk5PvYY6erqbGxpbm6mjRs3UnNzM+l0OjK89ZbFdpp2KNPFgI2ocXrOvb1Jd/p0q+W4dc0a+hKgonY69+68vIjL5X+tlNMRq2X9/ffTzxkZ5jLX6XSk02op64svWt3vQTfLUvw5ZUcUdbXPH23cbj1AhzrYNhVccwKIP1pwAt5ZmmKA1nz5Zbs+Y3U6HdXW1pIrQq7LD7GZO3cu5s6dC4VCgezsbDzwwAMubXOpsnTpUixZssRm/bZt2xAYGNg+OyHCwClTEHH6NIYolagCMAjAOQDfA3gFwE8AngwOxoFRo3D5wYM4MHkyrtu9GwBQCGATgOfADZu+gc/2MIA7ADQA+N3fH2ONRvjp9fgdwNfXXYfEyZMx46OPcKVej1AAI/v2xbO+vthTWorn+P0mAngBwN8AHgAwDMBcAH4i848AkAMY2L8/0qur8Y3JhNlSKfoEBOCr5makA4gFEKPXwwDgreBgaJ57DtkVFZgbHo6dJ0+i/PLLcVd0NIZ+/DF8ysowXKXCjrAwfDx4ML7SanHr6dPwAvAFgPmrVuGepUtxV1ERavz8kDt6NGLy83E7EcY7KOINACaBm9fzvwBuBzc3ZW8AwlnMAvAkgP5jxiDuxhsxMiICd/73v+jH9w05HxmJ/ddei/ALF/BNcDAWHDyIa0T9Gn+54grUTZuGpz74AABgkkhw+YABmFtejisB1AAYJZXiGn9/BKlUWADABGA6gEOxsSj64w98ZjJBCkAHwHZsKPAagG0AfgXQBKBOKkXzc89h4K234sP0dBRs24Z9APrw6bV+ftgRFAR1QwNKxo/HP/lQQm8DMPXujUW1tQCAb/r2RWx1NY4D8AdwEwCDnx/2v/wyaq+5hpug3WAANm92UMIinn6a+66tdS09AIwdi+D330fx999j+uHDCJdI8JufHwLValRPnoxezzyDhQkJIAA/RkRgYn09DETm43SEMDfphpAQ1AUHY05ZGQCg7oorsGvmTMBJjLisrCzux+jRQFISRqSlQQJgy2uvIS87G4/u3QvVoEEo690bKw8fxkeXX47ramogUSrhbTLBx2jEueHDcZdUCpm3Nz6RSDDm1Cn8WyrF+yYTmgCII3RqQ0NxZvx41BUVoXddHa5oaoIXf+0devRRlJw8CZw86fyAe/WC+tNPkdHYCN1HHyG5tBR6AAXDh6OPnx9OFRTgE4MBFwDEBgbibZUKagDlAE55e6PYYMAmb298ToQBRiN8+GxLe/fG//R6qBQKBPfqhZeCghDQ1ISZXl74h5cXIsaNwwovLwzLzcWy2lr8n8ikQgAXANzKL79z//14+ddf8eDgwfjPqFGonz4djcOGWZa5QHg49IGB8FGpUN+/Pw5OmIDAsDAE5eej/NgxTHNwz/8A7h654+mncePPP+PbiAj8VFWF3xUK9APwBoDgJ59E1H334UJVFfovXYrPiovxN4Dj4OrdBwEoJRLovb0RIbrP/wHgc9G+RkkkCPTywvTevVFaXY17TCZcAaACwGkA2QCGAvhAKMuwMPyuVmO6RoNIAJsBREmlGGUy4dDll+PAE09AmpODsPPnsd1oxGeHDuEO3ubeEgmGEQEAvgsMRJNKhdv5/GvA1c0J0dF4uLAQ1k92OYA7rrwSw6VS3HbsGO4HEAFAA+6eN3h54YMBA2AoLUWy1babpk7FX9u34/8AVAN4B0AogC0AtDIZ7pDL8V/evn3XXotQtRrXnD6N8kGD8OqQIZh/5gxG19UBAE5deSUSa2uxobraPI1frb8/ti5ciJFffomJpaXYfe+96BUWhs2u1h8uolKpXEvotsunBwM4b+p0xUPmTh7tsT9rOssjp9PpSKvV0s4//6T169eTVqmk/du307p162jnV1/Rkw8+SDt37iSdSkW68+dJp9WS4f/+j4yPPELbf/uNPv/8c6r45hsy3nADGf79b2pevZpO5uZy/Xw0GtJqtdTc3Ewfffgh5efnm/f566+/0j//+U+qqKgwr4uJiSGAa6L9+MMPKSIiwry8aNEi+m3pUjJ6eVGJvz99mJZGcXFx5v/tfa7y8aHKK6+kbD8/uhmgN954w3lZaLWkq662WCeXy+mZZ56hL/m3tFOnTtGiRYuopKSEdDodFRUV0ZYtW+jcuXOk2ryZdD/8QCb+bduQnEybNm2il5OSaN+OHTR06FCaPHkyJSQkkDdAd48ZQwfvuov+9eijVF5ebmuLTke6hgZbOzUa0uXmksnXl4wTJ5rXG15+mUze3qTfvJnkcjnt2rWLTp48SV9//TUdOnSIO4fHjtE0vtySk5NJp9PRnj176P8mTqT7AeoH0PJrryWtREIJAC339aUDXl40PCSE9u7dS99+/TU9/PDD5iZAnU5HTU1NdPvtt9MVffvS4sRE2vztt6Srr7ewuXrdOsq7+Wb6dsUKaq6qItNll5Hx5ptJp9FQTk4O/fLLL/TPxEQq//VX0pWVtfs17tJHqSSdXG6zfufOnfTwww9TyfnzpGtqoub6evrfzJn0zXPPker778kkkVDT7beT4d13SVdTQ7pz50ifkUH63btb8ikrI8PChaQ7dszh/q09csLnr7/+ot9++cW8rFarLd70bfKqr+fOtbAsl5N+717avGkT/fe//6XKs2dJf911ZBo1ivQ//GDfnnXrSL9qVct16Obn2KFD9MtPP5GW3762tpYuXLhAX331FR07dox2fPUVTbnpJtqyZQtptVpqaGggrVZL2vJyMrzwAhleeYX033xDuooKUigUtGPHDq5c5HLS1dSQVqsljUZjcb8Y4+PNnpXP7r2XVE1NlLN9O5XHxZH2q6/cKnOdTkf67dvJsHgx6RobLdbX1dWR9u+/yfjEE2SYP5905eWk//tvKv/qK0pISKCXX37ZIr1arabqPXsoNzmZ3nv3XUu7dTrat28fffLJJ3T48GG67957qXdYGOXl5XH/V1aS8Y47qOA//6EPPviAlC+/TKbAQNL//js1Nzeb7b7iiivM9V5RURElJibSFVdcQbNvuslcJrr8fFIqlbT4P/+hpJEjaXNmJun37iXDG2/YXPeNjY308ccf02+//Ub79+8nrVZLVfPnU8M995Cqvp4WL15M02+7jZ4FaLSvL7333nuklcvJNHgwV/clJtKR33+n5IAA+s+kSaTVakmtVtPu3btpfWYmNZWW0vz58+m/d99Nmpwc0ul0dPLkSdLffTcRQKbBg8nw1lukbWqixYsX08IFC0itUtFvv/1GAOj+++8ntVpNqampdNukSVR28GCL/cePW3i8Dc8/T6agINLt309qtZrUtbV06MABqt24kXRCvavRkK6oqMPqFlc9ckzIiXAmrGQy2UX3kbPOoz321xqXQviR06dP09ixY+mzzz4jIqLDhw/Tq6++ShkZGS19h06c4AY2ENHOnTvNlVd4eDidPn2ahg4dSt7e3jR79mzatGkTERFVVlbS119/TRqNpnMOpLKS6Oefuc7aIoROyCqVij799FM6f/78xe2nqIiovr5l2WSy6MjriJKSEvrhhx/IYDDY2Ldlyxaqra2lutpaWrJkCWk0GtJoNK0OVjKZTDb5tYqDzvPdjvr6djkWne7SDM3QbhiNRH//TfTXXy5v0tXK3GQy2QyWsUEUskYgOzubJBIJPW4vBMynnxKlpbWThS2YTCbatGkTFRcXt6wsLSXavt18P2g0mpbBF+RCedfWEr39tmW9ZkVVVVXrZWSNnTLrTFx9fnf5ptXORCaTccOo7SCXyzF+vKOGsLbl0R77YwAjR460CAlyzTXX4JprroFer29xdYvmz7z55pvx+OOP45tvvsGKFSswcuRInDlzBlKp1CKgZ79+/fD444932nGgXz/gnntsVkv5EAcBAQF49tlnL34/1nOPSiRAQECrm0VGRuLBBx+0a9/tt98OgAtJc+2110IqlcLHxwd+fn426S13LYGXl5frtgv29gTCwjxtAQPgQrlYT3nWzZC4ck/YCVkzdepUFBQUYAA/h7AF7VHX2EEikWDGjBmWKwcN4j48rdUbNkREACkpTpP07dvXvTwBh2F+uhrdw8pOIiEhwWnsujg+RlN75dEe+2O0jS+++ALFxcWYNWsWAMDX15dFZWcwGJccUVFRCHDhRY7RdWFCTsSsWbOQl5cHuVxusT47OxsAF4C4PfNoj/0x2oaXlxeGDh3qaTMYDAaDwbgomAtCRGxsLOLj47F06VKLuU9TU1ORkZEBmUxmkT46mpvRsbCwsE15uLu/tkD8iCGlUnnReXU39Ho9VCoVlEolfHx8Wt+AcdGwMu98WJl3PqzMO5dLtbyF57bwHHeEhFpLcQmSlpaGuro6REREoLCwEHFxcYiPj7dJN27cOISHh9sOQXcjD3fTuktpaSkGDx7cLnkxGAwGg8HoXEpKShAZGenwfybkejgmkwnl5eUIDg52rUNsD0KpVGLw4MEoKSlBSEiIp825JGBl3vmwMu98WJl3LpdqeRMRGhsbMXDgQPOgN3uwptUejlQqdarkLwVCQkIuqZu/K8DKvPNhZd75sDLvXC7F8g4NDW01DRvswGAwGAwGg9FNYUKOwWAwGAwGo5vChByjx+Ln54fFixe7H1yS0WZYmXc+rMw7H1bmnQsrb+ewwQ4MBoPBYDAY3RTmkWMwGAwGg8HopjAhx2AwGAwGg9FNYUKOwWAwGAwGo5vChByDwWAwGAxGN4UJOQaDwWAwGIxuChNyDAaDwWAwGN0UJuQYDAaDwWAwuilMyDEYDAaDwWB0U7w9bQCjYzGZTCgvL0dwcDAkEomnzWEwGAwGg+ECRITGxkYMHDgQUqljvxsTcj2c8vJyDB482NNmMBgMBoPBaAMlJSWIjIx0+D8Tcj2c4OBgANyFEBIS4mFrAL1ej23btmHatGnw8fHxtDmMDoad70sPds4vLdj57jiUSiUGDx5sfo47ggm5Ho7QnBoSEtJlhFxgYCBCQkI8c9M3NgI//ADcdx/Qt2/n7/8Sw+Pnm9HpsHN+acHOd8fTWrcoNtiBcWnxxRdAYiLwzjuetoTB6FrodMDEicCzz3raEgaD4QZMyDEuLerquO+aGs/awWB0NbKygIMHgRUrPG0Jg8FwAybkGJcWOh33rdV61g4Go6shbr4xmTxnB4PRhTEYDNiyZQsaGho8bYoZJuQYlxaCkNNozKsyMzMRFRWFnJwcDxnFYAAajQZKpdJzBvj5tfxubvacHQxGF+aDDz7AjBkzcMstt3jaFDNMyDEuLex45DZu3Ihz585h27ZtHjKqY6ivr4darfa0GQwXmThxIkaMGOH6OXvzTeCaa4D28gx4ebX8bmx0bZv9+4EdO9pn/wxGN+D7778HABw5csTDlrTAhBzj0sKOkNPw3rmeJHqUSiWGDRuGKVOmeGT/1dXVePfdd1HD+iK6hNFoxNGjR1FTU4PKykrXNvr+e+DoUU5MtQd6fctvV4ScRgNMmgTceivQTp5Ek8mE3377DVVVVe2SX0eye/duvPnmmzAYDJ42hdGJdMWRuUzIMS4thIeVqGlVEHAa0TqPoNMBBw4ARuNFZ1VcXIzGxkYcP368HQxzn48++ggLFizACuuO83o9sHUr0NTkEbu6Ks2ipkyXr0MhXXu9gAgvOYBrQu7UKffSu8D27dtx991345///Ge75OcKRqMRs2fPxjtujmS/8cYb8eqrr+Lbb7/tIMsYXRFfX19Pm2BDuwk5pVKJ4uJiHDp0yLP9PBgMZ9jxyAlCzuMeudRU4LrrgK++cn/b5mYLr4hKpQIAaD00qKO6uhoAUCeMEhZYvBi44w7giSfsbrd582YcPXq0o83rcoiFnMvXYUcKOVfqcHHTUjtdZ2VlZQC4AOadxdGjR7Fu3Tq3hZxAUVFRO1vE6Mr0KCGnVCqxfPlyTJ8+HV5eXggLC0NUVBRiYmIgk8ng5eWFiIgITJ8+HatXr25PmxmMttOVm1YLC7lvdx8MREBUFCCTmR/qgjAwGo0eafoR9m9TpkuXct8//WSzTW5uLu68805cc801HW1eu1NbW2sWIW2hubkZEQAi4cZ1KKTjRftFIxZjrnjYxIK7nYSccOxNneixdXitukhgYODFG2EyAdnZQH39xedlhcFgwOLFi7GD9WVsF3pE02pxcTESEhIwfPhwHDhwAPHx8cjJyUF9fT1MJpP5U19fj+zsbPP/I0aMwOzZs1FcXNwBh9E6aWlpSE5ORlpaGhITE5GZmdmhebiaNi4uDsnJycjLywPAvd0lJycjMTHRbfsYLmBn1GqX8cgJD2R3Rwyq1UB1NSfoTp7ks2jJQ6vVcg+KI0fapdnWFYT9q9wQGX///bfd9WfOnHErn86GiDB+/HiMHj26zddQc3Mz9gE4DkDn6uAF4Rpur7Jxt2lV7JFrp24JwktVcyeOmhWuLXfOnU5UVu0i5LKygLg44MUXueUdO4CnnrIYyPLmm2/i+uuvd7ts1qxZgzfeeAO33nrrxdvJ6JIeObem6Fq1ahXS09Px8ssvY926dU7ThoaGYuzYsRg7dizmzp0LgAvzMG/ePEybNg0LFixou9VukpiYiOjoaKSmpprXxcXFob6+HvPmzWv3PNxJW19fj7S0NKSlpZnXxcbGIisry61j7BKcPQvk5gKzZ1vGpOpKOPHIebyPnPBAdvfBLK7Y+Yrfus9V0P/+B7z6KvDMM8Bnn12spS6Y5L6QEzfDGo1GeHl54eDBg5g4cSJuuOEG7N69u93tbA/0ej3Onz8PAKipqcGQIUPczqNZocC1/G+qqGh9AyLP95ETe+Ta6d7xhEdOuEaNRiP0er1LHhdxDDF/f/+LN0JoSha8uoLoCg4GPvwQAPD555+juLgYubm5uPnmm13OWrg2Ge1Dt/bIvfTSS1AoFMjJycEDDzzQpp3Fx8dj27ZtCA0NRUpKSpvycJe8vDysXLkSSUlJFutTU1Nd9nq5k4e7+4uKikJqairi4+ORlJSErKys7iniAGDOHOChh7gO+12VrtxHrq0eObFY4kWAjUfu1Ve5hQ6I2n/8+HGMHDkSX375pXldW5qramtrzb+FB3lGRgYAYM+ePSAiAMDBgwcxdOhQ/Pjjjxdte3sgFqttvYa0oiY1g0LR+gZi0dURHrnW+sjV1pqvNQDt1rTqSY+ceP+tIRZyevFo37YiXDficwAAFy6Yf7a132tQUFCbTCoqKsKuXbvatK0F/H3bFaisrMTjjz+OvXv3tjkPsZAzdlILR2u4JOTy8/Mxe/bsdvOizZ07FwkJCTh06FC75OeM9PR0xMTE2KwX1rnSxOpOHu7uLzw8HElJScjIyEBqaipiY2NbtafLUl7OfbviUehATCaTbSd7ATujVrtMH7n28Mjxb/Q2oyDFMcLamVdffRVnz57F008/LTKpRcj1PnIEyM+3bNa147EtF64fwDxgatiwYeZ1BQUFAIAHHngAFy5cwIMPPtieh9FmxNdNm4Wc2BvpaugPAU80rZ4969iei0C4F1UqFUydNLtEW4R4vUh4t4snX8jDWqSJRFh7CDl3rs/o6GjcdNNNFzf46OmngeHD2y08zcWSmZmJb7/9Fh988EGb8xALuc584XCGS0JOaCJtT8aOHYsxY8a0a572yM7ORlRUlN3/ZDKZS94vd/Joj/11W4TmEA/3Z0pISEDv3r3th97o6R45O0JOq9V2qJCTiESZMLBC2H+AQoHJr70Gn+uuw9r332/ZKCDAJp9z586ZfzfyQkL80Nq5cycqKiosHqJmNm8GrrzSI97g9vbIGV156InFgyeaVuVyx/ZcBOLy66x+kW05fw21tRDuqHYZGe7II9erFwCuH2ZbhZyfaMaOtkwrtWfPHre3MfPrr8D585b9KT2Igvd2X0xkDS9RXdpVhJxbfeS6I0VFRQ69XOHh4S5Ny+ROHm3dX15eHnJycjB+/Hi7Hj1X0Wq1Fje6cMHq9fr2aQJwgndzMyQADEolyMG+BBs60pb169cDAD755BObNy9vrRYSANBqodfpAInEQsh1hF1EhPz8fIwYMQIhISEO0wnlZ2puhtENOyQKhflGNpWWwqjXW1RUjY2NIG9vSPiHRHsfY2hoqPn3sWPHMHr06BYhJ+rr9N2CBTD70FQq6LVaQMq9SxKRxUCo+vp66PV6c8ULcJ58Pz8/i+tbOBbjmjXwP3kS2owMSNv5pbM1xDYqlco2la/YI2dwJY/GRgh+AVNTk1vXiyOkKpVZnJgUCqd5ShoaLB4ehuZm8z1vc4/r9ZAuWQKKiwO1EqBaLKoaGhosREhH0SgSrY2Nja2XPRGu+9e/cATA1eBsvth7StrcDC8ApNXCoFKZz60xIAAmvR5ardbsoWxqanJrf2KPYVVVFfr06QPwdt94442YPHkyPvroI4fbKxQKp/tzWKcTwVsu554JNTUOnwmdiVAvuluGYsT1j1wuR+/evdvFNnu4aqNbQm716tWYM2eO28Y8++yz+KwTOlhbI7d+a7RCJpO1msadPNqyv/r6eiQnJyMuLg7z5s1DdnY2xo0bh4yMDIeePWcsXboUS5YssVm/bdu29hld5Qgi3MM/tE/m5KBowACnyZ15JkOLinBZZiZOPvIImgcNcssMcXNMbW0tNm/ebPH/rfX1EKTUgWXLoPf2Nt8sdXV1Nunbg5ycHLz55puIjIzExx9/7DDd9IYG+ANQVlRgZyt2SAwG9CorQ+OQIeibl4fr+fXyEyfw9+bNOHHihDntjh07MJbI/HBo72M8yY+UBYCvvvoKt956q1ncNImu9xutttu2fj0MfLOPUqm0eKBu374ddXV1NtPgWHsjhGPpv3MnrgOwd/NmKG68EcHnz8NXqUTd1Vc7td1gMMDLy8vCq+guZ86cMf/++++/29TUVig6zvKzZ1s9R71KSzFVSF9UhNx2OKejTpzA5fzvyjNncNBJnkP27IFYLufs2oUq3nskINzjffLzcUNaGho2bMBfrcRqKxRC8ADYtGkTBrRSj7QH4mssKyvLwgZ7eKvVuPP8efQG0AfAiRMnbM5XcXExvv76azz88MO47LLLWrXhqpMnEQ1AJZfjr8xM3MGvLygvx6nNmy0Gf+Tk5EAmk7l2cOC6Rgls2bIFF/h+d/n5+Th27BiOHTuGqVOnOhyNeejQIZfqDOs63UujwV28h/7wzp0olXp+/gGhXiwvL29zPSgePPL7779b3P/tjateabeEXHp6epuEXHZ2ttvbXCoIAk4gNjYWs2fPRlxcXKsVij1SUlIwf/5887JSqcTgwYMxbdo0p96gi0athoTv1Hrl0KEYNWOG3WR6vR5ZWVmIi4uzGf2TkJCAxsZGZG/fDgAYYDDA6KCz7f/+9z8EBgbaDCARx/K6+uqrMcPKDm9RP8/JixcDAPwBaABIpVKb9NbodDqcOnUKV199tcsP/++++w4AUFpa6jR/b74PWai3d6t2eD36KKTr1sHw6adckyJPmEqFGTNm4NdffzWvi4mJgbe/v7n5prW83WX58uXm30SEO+64wyy4AkQdnW+y2m7apEnA4MEAuBhyYq644grMmDEDv//+u9N9C8dyVig7kwmTZ8yAD/9Q0p89Cwwdanfburo6XH311Zg+fbrFQA13EfdBGj16tHvlSwQcOQKVyKs5ICSk9TxE/YsHhoai38WcU70eOHoUhn79WvLcuxf3pKTA8MsvdstPavXwGtKvH8bxNljf4xJ+EItMr2/1uL7++mvz7/Hjx+Paa691ktqSHTt24Oeff8bbb7+NADtN947466+/AABXALjVzw+jWytL0RRqIQAiIyPNxyXZuROorMQr5eXIz8/HpEmT8KIQUsQJUl5UBHp7I1bUIjNi6FBEzZhhUa9dfvnlbl1jp0QzcIwcOdK8bWhoqPmlf8CAAbjuuuvM6Uh03w4cONDp/hzW6SKbxwwdimvaud5pCz///DMAwNuFOtYRX3zxhfl3TEwMrr/+eiepLw5Xm4DdEnK5ubnYsGED7r//fpfSFxcXY9asWR6LfN3aW0trHjR382jL/uyFP4mNjUVycjIyMzMRHx/fqo1i/Pz87DZH+Pj4dOywadGxeWm18LLal8FgwPfff48//vgDw4cPx4wZMyzs0Wq12Lhxo8U20gsXILVjc01NDZKTkwEATz/9tIWnUdxhXqVS2R6zHVf1AADnwDWttlZGM2bMQHZ2NrZt24a4uDinaQXEI5uc5s+/fUns2W0NH/7HOzUVEHlgJRUV8PHysujrYzQaIfFuudXb+zoQDyzJz8+HyWQyH7NE5EG7wWo7H7Ua4G2xDpFgPndyOX4GsCEgAF/Z6b8kHIs/32zsJ2qWAgCf8nJgxAi7dq9duxa1tbX47rvvsGbNGlcOFQUFBfD29rYYhCGOKeZq+AozX34JPP007hSJQalG03oeomuqqaYGIRdzTp95BvjiC1jnIDl5Ej7/+x/wySe221h5CvRKpY3N5jqH985K5HK7x0VEICJIpVILj6tOp3OrLKdNm8btRyJx2lRojUajgQTACQB4/nkgPh7o29fxBiIbQ2F1zvk6IWT2bABcHyqXjoHPU6LTwUfkffMyGuHl42MR1NtgMLhVLuJtlaLzJBZreXl5uPHGFp+51io8kyv7Ky0txb59+/DII49w/chE14hXY6PNM8ETCPWi3WeDi4jLU6vVduhz1dW83fZ1JiUluRTUd/ny5YiOjrZ50+5K1NfXu+Wivtg8XE0rNKl2q4ER4rhPdjqAfvTRR3jiiSfw9ddf4/vvv7f5364LWdSscvjwYbz++utQqVQWacXCDbAUBAp7YRzsCDmh8VbcJFZSUoLMzEyLyq6ystLsXf7tt99s83aAzroDsz30ekCoINzp5K3XW6Y3GIDq6jaPWt2zZw9ef/11t/qPiMOGnD171mLf3s46ZovOz9q1ay3+EppZp+bl4R4AX6rVePzxxx1mFcDvx0+lsgiiCid9rNwN7FldXY3LLrsMo0ePthDnFzXYgR/pGyIqM6koj2PHjtmNA1Ys8rJUiQaJtAmRh8EGRzHSrDwFGmchUwShr1BwgamtuO2223D11VdDr9db3INtjSX3hbPjsYNKpYJF5D97I97FITRE5yoE9kethvPeqEZX56AV8tDpLGd34K/rtoRIERDXP9XV1eZ6Ubz+gNUgIfF/rp6Hq666Ck888UTL/Mpix8X27cBllwF8/2VPIdRNFzNIQVw3dpXBDm4JuaSkJJw9exYrVqxwKOaKi4sxYcIEJCUlYfjw4cjIyMDw4cPbw9Y2IZPJ7I9yA+chGz9+fLvm4U7aWbNmYdy4cQ736yifLon4grYjRMR9tuxVbkJFZXFBioTcmDFjsGTJEixZssTiYVlaWmqRj/ihZ9fjakdUCUJOrVabhdutt96KWbNmWUwvJ25+GzhwoG3eDnBJFInLzJ3KQa+3TV9WZjtq1ds15/vkyZOxZMkSvPHGGy6ltwn10tQEFT/PKgD4O4shxYuBoqIic5PHDTdwfjvhGgkQHUdEWBgcNZgF8WUcoNFYPgidiGixkHMlHpTQXK1SqSyuYXfCj5w4cQJKpRKZmZl47tln7aaR8HlUVlbi6quvtvD+CWSLXiSaa2pabV3Iy8szx+RzCweeKZOVcNM6E3LC+SCyGQ1rMBiwY8cOnDhxAkeOHDGLlH8BCG1jlxyVSuXay5Mo/VXiFdbXwnPPAaNGtdguEjahEHmvRCLVW9Sp3iWE60arbVXIuTtqVZw+JSUFkZGROHXqlMX6/fv3cyGCZswADh+2+M/VYxDquW3btnErxNfkX38BBQWct9ODCMdyMQJMfG11SyG3bNky8/eKFSts2m9Xr15t9sIlJSWhoKAAM2fObFsF0k4kJCQ4bdp1pXnMnTzcSZuXl4fw8HCbNIKAmzBhQqu2dRla8chZN3laI6yz6NocEWGT7s8//7TY3np+y1Y9cnYq+Ej+22QymSsjoX/ip59+ak737bffOj0GR7j0UBHnp9O1eOdaw9ojBwCVlc49ci4E6HQ12K5cLjcPMPEHsLupCQNuugmCH8d6eI0KgPndnz8/n3/+OYgI06dPx8SJEwG09A1pFj1Un9myBeUALMaIlZYCxcUI5M9boFZr6ZFzIqzEXRAc9kU5dQpYtgzQ61seUOBeWDds2ACdTmdxLTi7LoQRvbNnz0ZSUhK2OgjOLOXFjDjOpngQj8lkwi6RyPEnclrHqlQqjBs3DgkJCTaDR1rFgfenmo/pJ6Bz1pdHLPStBKdYMKjVaqjVakQC+ADAWHtNuk7oJ+rj507AV7VajdHiFdbH/NlnwJkzwFdfcctWHjnzMYiOxZevD5uamqDVah2+zBERJy4ceeT4uuNihJx1/dPU1ISFCxdarC8oKIDpjjuALVuAG2+0+M9uPWqHeAC/APAXngUudF3qFIjMdZ5QL2q12jYH8+32Hjkxy5Ytw9tvvw2lUmn2wiUmJmL48OHIzc01iz4A7R6Dzh1mzZqFvLw8mzdWoYnMlQC87uThTtr4+Hi7zadC0GBXpw/rErTikWtNyAmejGHilXbETHNzs8tCzl2PnNgOAWFEptFoxFlRENQOFXL2lh1hzyPX1OTcI+fAHnHfj7Nnz7pU0QnNqhKJBM8BiALgXVeHwfz/1kLuDwDmcNH8w1/ojH3nnXciODgYQItHrklkQ3RhIWQAhK7gvlIpN1hi+HBzZ99eer2lcDh3Dli0qGUKJBFicWTvYbV582bgiiuAlBQYVq3C1q1bzf9NmjQJDzzwAN566y2Xm1YFEbVnzx6cP38etzhIJzRHi71+4n1UVVVZNGUGAOaRiPYQBtsAcD+4q50HlVwux8n9+zlb+HV6Z14b8fmwimMmbiZUq9XQaDQQXm19VSq3YuSJ8/rzzz9d3s7GI+dIKAmeZiuPnMZOMF9/vtzq6+tx+eWXWwwkEPP4448jIiICaqFcTCagpsbGlvbyyAns3r3bxtMmreLPJi8+BVxtGcoAcDeAO4SmfhcFYIei0wFXXQVMnAiYTBb1ottxCv/8E3jzTS5sEk+3F3IAJ+aSkpLMXriFCxeioKDAo8LNmtjYWMTHx2Pp0qUW61NTU5GRkWHTZy06OhrR0dFtzsOdtCkpKXan+Fq6dKld27oa+fn5uPzyy/HTTz+16pETCy49HxdJjHBTWYyPs1MBWQs5Z02rRnsVUCtCzrr/iVarBRGhurraQui4Uwm41LRqXWbuCDnrtPX1mFVWhpH8oo1HzkHe1aImUYC7Fi0oKwNeeAH7vvzSLMwFIXd5ZCReEiUVxmBaC7m/AJh9N3xFX8U/QPr3728WcoKHzCg6X168qBvGL4fZ6QjsDVhMa4TnnwfeeguYPNkmrfhc2xNyL995p/l3xb59Fl474fr94YcfXBZyQpkplUqYTCZzyBibY+DzFr+IiB8YFRUVFk3MgRCJvsbGFsEBzuMj7vjv9kh4O/fy2rVr4c2XnZFvUTA4e6C56JFrbGyEtLkZFhNKuRrAtrAQ0aI6qEYshlrBZSEn9AUV7cfCIye6noL466CgoADnz59Hfn4+Dhw4gP/7v/+z6FO6Zs0a6HQ61IhfNOxMfeZKHzmdTocPP/zQYpSqsB4AlgDgJ+pDQ0MDV2+LMIi6GohfPl0JIuwlskkvvCB1BY/ckSPAiRNATg5QWmpxH7kjwurr62F84QXg1Vdxhaiu6BFCDgBWrFiBsWPHIjs728IL15XIyMhAREQEkpOTkZaWhsTERCQmJtodESqTyezGb3MnD1fTymQy8xysycnJmDVrFpYuXYrt27e7PVrVE8ycORNnzpzBzJkzLYWclVDQ6XQWFet8AHpRkyVMJvT/+GPcCSuPHF+JiQccWA92sPbICZ6JZwDsO3XKsiO30Wi3s3Wk6LfwIBaPhC0oKLARjO0u5Kzzs1dBHDtmu95gsF336qtYVFeH0/yiVqu1PG4HlU+F1dRq2/kwMGa++Qb45BPkPv00Hn30UQAtQm6Wjw/6iJLK+G+xkPsTwGcAhGqQ+ApREJD9+vVDSEgIpgEYx8/K4WvnoSqIfS9Hnk6xWBE8enY8cmLRZS3kDAYDnhItNzvwOAUGBrrcR856YE6kg3Q+/HGJhbX1AB/xEAQLITd5MtepnPeKVFVVWXjhCqyaRFvFzrVSU1NjjsVoCAsDwAWxdoj4hcrq4S4WJf02bsSxCxfwD3ECR1PtWUFTpmCX0YhgftnlQQYANM3NuEK8wpGQ44+DXPDIhfO/xV7tRYsW4YMPPjAP7BHXa+K+pDrxi4iVkJsK4PmNG7n+ZlZs3rwZL774IhYuXGixXqvVoi+A1wC8gZZ78vDhwxbp1CIh565HLlTUnUghhGWyJ+QuIl5jmxC/jJ461SYhp9frMXr0aNTxArmX6JrtKkLOrfAjKSkpNp4mgAtQ+Mwzz+C2225za7vOxHoSe0c4G2Xrah7upJXJZEhPT3c5366ExYNJfEFbXdyVfNwlHx8fDPL1xbvNzaBXXgHmz+ea/L79FsO++w6/AVgl3pCvTMRNAM48chqNxpzWHH76H//gRgbW1TmcA9Ze06r4jTQnJwf+VqP3dFYP9h9//BH//ve/kZGRgclW3p82CTnr5e3bgdhYYMIEy2moTCbbtFYPP41GY9nvJyaG6zMSHw98+KE5BIi10LAWr4J3JAQtgkAQcjOsykPGfwueo7qnnsJtX34JX19fNBsMgMmExrIyhKDFI9e3b1+UlpQgA0BIfj5QXg5/O2U3jP92OJDCkdcpNhaYNAl4800AliLCuo+cXC6H+FVK4sArERgY6LZHTqC/g3TNtbW45ZZbLOwTPzCshVwAgEalkmuqFkTbyy8DP/xg86A5az1Hamv9Je08qJqamlqEXHg4UFgIk+i48/Ly8Morr+CNN97Anj174GflkdNs2ADta6+h148/Quxbmsz3QbUQcq406+l0kJSVIQBcgN5G2BFyej3X4f766wGrwOgRCoVFeVoIOXH3Av44DHK5OVSLoz5yve1ct8IAQUGgiz1zfqIXrSNZWTAPibPqI5cNAOXlyJ80CbU//GDR51q4vipFce7A2yf2cgaA66tqXUZKqdQshMVCTqFQ4Pnnn8cLL7yAK66wkLxmZCJh6S0cuz0h19ZWJiKu/N2dRUEUDLmtQq6urg6VlZUQwl376/W4DFzIKiEPk8kEqQcDHru1Z2ed+FNTU5GSkuL2dozui0XzqBOPnFDBDBw4EMP4pjOJwdBSSYuC/tprWhW79lUqlcVySHEx8OKLQHm585F7sbGAgyj/AwEI74kajQY6nc6iGTUnJ8dC1MQB+Oqnn4CVK83rHnzwQVRUVODJJ5+0yb9NfeSsKxnBg3nwoO22QloHM3dotVrLh1NNDddMtGIFsG+febW10BA/aACYz3GA6L/a2lqEAhjHLwuBMKybVn/h+4LKZDL48yMh5RcuQKPRmEVUv3790JvILBKoogL+dvpJDrPK2xqTI6/T9u1cMysvOpw1rTbU1FgIfC8H/X2CgoLaLOQczVkQSISdO3dyIwl5mpubOTGydStqi4sthIcUfPgPcZiSjAzg3DmbZjgbIWfnYfYdANWoUQ7/b2pqMj/whQcr8fupq6vDlClTcPz4ceTl5eHs0aOW17ZcDv8HHkDosWOou+++1kNpuOKRE9U9gmCxEXJLlnB1wD/+AWvCrI9RfK+IfwtCTnQtOGpa7W/H8y/UIUL9VVpaivEAFsIyTI+FwLfTtAoAkro6c9w8AaH+s34p0el0FkJuzEiu04VQRkLrQ53IZp3Vefn000/x8MMP2xyTQJjoujILOXv3TFuD0i9aBPTpA/Cj2x1x6tQp7Ny5s2WFyCNHJ05YlGNzczP0er1tPWdFY2MjvNFS38xQKHAGQBq4FqG33noLw4cPN7+QegK3hFxGRgZGjhyJCRMm2HxiY2ORmZmJyy67zOY/ofM+owfjxCMnPMAGDRqEAeKI60IlLQplI26esyfkAMuH0bLqas6rFBsLJd98a3cqstOnbdfx+AAQgiyo1WqbN7WjR4+aK+E+ffrgZwA+JhMg9G8UTZdEdjwcYo+cuIM9EeGLL77g+qK15pET9/mxHoQgpHUQKkKj0ThuLhKJC6FpVZipwKaCE+ZPBVdOKpUKtbW1uB1ceRT4+UGQ5DL+WzgTp/nyCwoKQugQLmpXc0WF2Tvh6+sLmUyGCJEQ0lZWwl61L4h9R0JO0tqLI79PZ0Ku0Sq8kg//vzcsK03rplVnTe5iISdFy7VOQUEW6SyXOJqbm4EPPgDuuAMzvv/e0oMELiCvRd9AoxHYv998jEJ/27q6Osv7yc7Ddh2A0kceEQ7I5v/GxkbzeZH252SHEPi5rKzMMpisVdcHCy9NXV3rQs4Vj5xIyAnXhCBSLly4wMVIe+st7g+reIUANxuKBWKb7Ak50TE4aloNge15FK4TsZD7HzhBECQSXxYC34GQs+cfFoSc9bWs1Wot7qMYfiYY4WX1Sn65WmS/0Y64EY+itsbCIye8fNl7sbYjcF3i7be57+eec5ps+vTpmHXrraj9/nvOmylqPjaKQmAB3D317LPPYtCgQTZx9MQolUqL8hvLl9MEAD/99BMWLVqECxcuuB2/sD1xq2kVaEMfC+Ci5jFkdBOceOSEfmwDBw5EP/FDRBByIk9CqI9PS9BeO52+gRYhdwsAcxS+kycR9OGHADixZeGdMBhaHf0WCW4EnlqtthnNdfToUfNE0yNHjkSAdUfqxx5DNoBrAfjYaToQCzm9Xm8Oe7Fjxw58/49/IPPKK7HZql+LjSdEPBDB+liEh13fvhaiWMDGIydG1AwjCI1rrrkGe/futYwPJ7LJ3FxaV4fa2loIEfUKgoOh4Pdj7ZETroigoCD0iY4GDhyAvrbWollVIpFAJip7bWVli+dHxCAAvnAi5Fob6VhZCQwd6lTIqa1Ggfo1NcEbwDH+WISRs642rRKRhZDrA8ALgBGAdtAgBIqmvLJ3XCqViguDAWDM+fOwnrhMb+2RAwCNxnyMvXv3RkBAACoqKlBQUNAS2siOkNMB0AiDY+x45DQKBYTeVL78XMhS3utsfe9orLyQ4sELzXAhuK0LQm7r+vW4nf8tlJ3glbr77rtx7NgxOBt/HW59bzjyyNXUAEQwikSXo6ZVgBNk9p6WYiF3uZ3/LUJ32wk/AtgXckK+9jxyYiESJQrTAnBCLicnx6KektTUYB6AWfwxpAAY7GjeYiIEirxRvs6EnLsBs61x0vexrq4OFy5cwFEAvR95hOtTLDonEquXeZVKhc8//xwA8OSTT1rEOrXcZaO5PgOAcP5lXRiZ7+fnhy+++AIJCQluH0574ZZHLiYmBiaTye1PVxrFyuggRBW4yaoyFzet9hVH2q+r45odReIjTNTPwMhXXtYeuTNnziAN3HB3MX75+cgAsN5Bk6AzhI7nYo+cNx+yo7Ky0jzx9MiRI222Jb4j/WDYn6ZN3LQq/p2/Zg2yAbx+5kzrHjmxkLP+T+j758Ajt+333x0LOVEFLJynq/kKW/DIvfjii7jppptg4h8QgpCrra1FbW2t2fNg8PWFnP8t47+FB6tQfQcFBWEA32wnaWy0EHIAECx6COmrq+0KOYAra0dCzi7vvtvStM7v09lgB61V/0A/lQqRAC4HMBYt3jQvLy+XhFzTjh3Yq1abBYfgdakBoLSafcKhR04UGNg6wqKxsdGukBNEhr+/P0bwU5VZNK/aif+mBaAWXr5FfYBWrVqFlJQUGEX3o38kd+dI9XrO23zihMVUXwbr5ibRw73RaDQLOXvHDKDVptUzZ87gNdHc0tYeubNnz1p4wa0xGo3oa+3hdiTkNBpALjffB4BVQGCre8xRyHCxkHN0fVvvX6VSIUy02l5Dv/DCq1arLUSZtUcuyKovV3h4OAYMGGAW5wAn5JYCiAU3cCwBlnWbRqPBX3/9xXn1GhshFZWxj1CeLgo5IkJSUhK+/PJL1NfX448//nB8zpwIudO8UDOPQE5L4775fn1e1dWQAZgILualuPn95MmTDsO6+P/1l2WcQZ5B4ATUddddh4cfftj8vPAEbgk5e6M5XcGV2RMY3RzxFEM6nUXzn1jI9RZd7NvWrkVkr14W02YFi71XfJ7WQq6+oAALwQWGVQDY8dBDAICA8+cRD2CctRfBhYmHhSl6NBqNWcj169fPfM0L8eTsCTlBuPYCzOEzxIgrVePBg+bmnfP8ZN39DQYb8WsuT6Gp1lmQW+Fh6UDIFVlNcG6BA48cwL3hKhQKfPjhh9i1axca+bTWHjmhE7AxIMD8gHHmkQvim1ZlOp3FiFUACBJ5YHRVVXabVgGun5xbQu7qq1smf+ePw5lHzsCXhSCNAtVqiP0Ywtu4Vqt1adSq75w5uBbAFnBv8MN48VYJoM6qH6D4uIaCE43Nzc3mQSmA7by1xqYmmKy9sVqt+Rj9/f3NYZUsZuVx4JFTCw97/jp85JFHMG/ePCxbtswcQ87g748g3lPtD0C9Zg1umDsXovHoMFqFtIHoJUshCkPkqL9gax658vJyCzEkhKRpbGy0OTcAzEHG169fjzlz5kChUNgILlVDAz755BPuRcbaY1hebjFqNQTc4IUHH3wQ+aL+pgDgaD4jsZBrtceYSMiJy0ho4xIfn7jlQuyVs/bIBVi1kPn6+iI6OtpCyPmWl5vj+QHc9S72tj7//POYMmUKUlNTbULE+DjrI6dW2wywOXHiBN555x3Mnz8fzz//PKZOnYqEhAS3A/aeOXPG4gWHeK9ysa+veZag9wHsB/ADbEPxiONEmjl4EJMWL8avdvbnDaAfgJtuusktOzsCt4TcqlWrWk9kh9TU1DZtx+i62Nxk1kJEVMEIfa8GDBiAcFE8s6y1axFtNbrLWxzBns/Dumm1l+j3IABZvEckyFGnVSdvcWr+gSoIObFHLigoyOydErjsssts8iA+fS/YD74pFgyyqVOBhx6CcssWVPLdFIIAaKwfWCoVcN993Nuk9cPEUfOEAyFnb7ZREkbhioSccJ6u5T03arXaYjYDoW+Q0D9L8MiZhVxgoEOPnFjIBfIeuQFGI6p5wSQIOT9Rs7W2osLGYyHnXwSGwtaL47TaDwoC+P5cjQUF+Oabbxw++ACAeAEiNMb4GY0WA3HEwl/wyN0P4I2zZy2ut6qqKpw4cQJS0XFt3boVqf/+NwAuOHKt1b0kHFcYgGIA1eCFnMi7daXV4ekUCuTyccFIeJkQNa36+/tjCC+gLYIHOxByzSKPXFlZmcVcuL68V9kYGAi/UE6y+wPw549pjjgzK4+aeCCKkhdavQE4fNUX3RdEhAceeACzZ88290VVKpUW9cGA0FB4AXiosRHKnBwAsJzWjR+csWTJEnz++ef4/fffzQJJKIl1336LF154gZvb1/p+LiuzCQgMcKPWf7PqC24ttgUEIVd+4YJjT6SASMiJBadwTOIQNRbXc1WVWTRbe+SsX4B8fX0xdOhQCyEXYtWFagAshZzQH2zRokU2Qs5br+fOj6M+clZ1vuCVl8vl2LBhAwBOaH/wwQe22zvh9OnTuFa0LOGv0+zDhwHec/wE/999aHk5F9ixY4dtpq0E0B4M4MYbb3TLzo7ALSEXGhraeqJ23I7RdRFXGv7+/jBZi6UnngD27AGOH8cQvukxPDwcoaK3wQgAo5ztRKsFXnwRI6xmvxAqIoW3N5oBbLcKgGnNr6LI9tZU8QFNh4ITH2qVyizkevXqhWuvtHxkCs1TYiSi5iFzZadQAJWVMBqNdr0059avNz+A7Aq56mpuhNbp04D17B+OOtS7IeQ0wnFUVgKHD0OvUqGqqgorAEy+7z6M5gWTeKCSwUHTqnAcFBho45ET0oqFXMjll0MH7o1WwVemQtOql0hY6srLbR50xfyotzDYPpCsfD+WBAUBvFjM3bQJTzzxBH755Rfz3wqFAsjNBe69Fzh1ChL+IVgIwMh7p8SBFwSPnKS5Gd8eOoT3APwEYIZSyY2Q5Onfvz9Gjx4Nlei6v+WWWzCSP45KWHYyB7gykwIW/adUVoF+rQkEMJD37J0X4oE5EHLioNmOhJz5CmtutgmuK4gCU69eAP9C4AfAy473TCKs4+cmloiadX2MRjSUlCAfnIfELiIhWFVVhQ0bNmDdunVmD6q1kOsbHIy5AFYQoQ//gB0s+h/8i5uwfWlpqVkgCSOuL/AiZsuWLfaFnOj+C0aLd0xlJWhudnBIDQ0NICLI7cQ2tEHUR07skbMn5MQtFwPuvJMb5VlZaeuRs/KI+fr6YvDgwRZN4jJhdgYhP4jqti++wE8iGyRWgs2fCBq53OH0bqivtyhD8aAqcdcTYW5jGxyEzDlz5gzG2FlfDYDs1I3WfeLsBsu27q5gxWAA119/vdM0nYFLjbrnzp3DypUr2zUWXEpKCmbPno0xY8a0W57OSEtLQ11dHSIiIlBYWIi4uDi3g+66k0dHpe0qiDvC6/V66BsaLAXDTz9xb2R79mC1RoMcACEhIRaVSASsRqlaEahSAR9+iLvBdQDuO2AAKioqWh7gAQFAYyMOnD4NCgyExIHAWbV0Ke52sI9ymQzDKiowC1zH3n0bNqB0DudTuLe5Ga8tXYrjANaDC4Bs0wfOaIQX/wANB3DrhQvc/J+jRwNKJVQlJegNoBYtFT4AFJ04YfY2+QOQW3sTxfGPrCoYg1Jp/8Z1Q8jJIyMRcOwYt58xY6B+9FEQERIBQKPBc0FBeN5gwPr1683bCOUrVOCVlZVoaGhoEXK9epk9clMA7JNIEMOfb7GQCw4NxTkA0QBUvJATPHISUd+0RuvOx97ewIgRwIEDdvsW1cBJE53II+djJybcpk2b0Lx1K4KMRtT+/Tea+Qd+NQB1QAB6NTdbeMEEcTCprAyXabX4t+i/isxMfBoQYBGuoVajaekwLZeb+zVWAgiyc90GABD7LQwKhVMhF4qWY99dV8eFaLFqWh3KNy2fO3cOr776Kq6//nrMcCDkmoT7VKNBrVU/N7MoCA42CyNxhwOx7AsR+m+OGQOUl0Miuv+DAPTftMlhYGQAFh45sWipq6uDTCaDQqGwuBYi/P1tmkqHiBf4lyrhZa28rMycvhjAGFjdL9ZCrqYGUtH5koLzxDcC0PJlWTdyJMLOnMEocKPhrc+aTqeDWq2G0npErz1EHjmxsLcn5Iz19Xgd/HynfPO59tdfodVqLcrIWsj5+fmhd+/eFh65CKvBPgMhEnL/+AfuB/BvAG8DNh65AADNfFw/SCTcC+l77wGCx2vUKC4MSUEB4Otr8SwRj/rfv38/dDodfH3FlsFhPLnTp0/jPpu13PWoDwuDVS5mj1yfPn1QU1PTJiE346qruoSjyiUhN3z4cCQkJGD69OlYuXKluUJoC8XFxeaZDDpLxCUmJiI6OtqiiTcuLg719fUuz2fqTh4dlbYrIb75jEYjDEqlrWDYu9f8VvYEOM+sn6gZKQKAC1UZAK5PVP+oKAshR4GBGCyToaSkBOqwME742cHZg6LEqk/bpN9/x1cPPvj/7F13eBTF/37vLpdeLgUCCTWAFEUgFAuIIgnNCoRirwSxFyBg+Yo/CwSwN0BU7EpArLQEBKRIr4KUhNAhkAqpl7vP74/Z2Zvd20vu0oF9n+eeu9udnZ3dnZ1551MBAP+TjGe/DQvDpGXL0L17d5wTvPDIYFB4SCYB8D1yBGjTRl5Jm8aPx1kATwL4WjjP0YMHFYMrqY3ChcDUZZs2KQahrP37tQ2pPSBypxs1UpCe4G+/VdRZFhgIFBYqVOg+kkqETyLcaJ4TOUNAgEzkAOAaMSOH9B0QEACj0YgTXl5oU14Ou7Tyj4yMZCttQUoRKE3iVoMB5ldfBRo3RtcjR4BNm3BFkybYpwp8mgomqVNIYDgEiVyIi34SIF1rRG6urKY9C6DQ1xeBquj/smpVw47HcOQI3njjDUW4Bh9RnXT4sKzSPg0gQINYBhkMGDdunBw/0HzmjGbuYY4rwUhFMQCZCruQyO3fvx9vvPEGIiIikDV2rGKBATAiN/eHH+TMFnkqz1Pebw3BwbJEToRopt6UE7n+/YHFixXlLADaacVFFCGMM6JkMDs7G23atHGSyAWZTCgVPd+hInLS/eBELu/oUXk8yZS++RX5+flpEjmTSsIeDEbkynh+4MBAHAfzYu8LQCv41qFDh2CuzGMXYGrcxER0O3ZM8X7yNnIiRyUlWJ+bi6YAxKyux/ftc5LI+agcCbhEThxjzNJ1Z1osaJWXJ0vk3nnnHXDXEq5NKT97VkEk/AAUcw/Rpk2B225jH39/RqTz89nnv/+Aq692CnNkNBoREhKC3NxcbN++HdeonSVPnXIicjabDYcOHXIpkcv38XESGnDb5X79+mH+/PnIyMhwDuxbCZF7yI1c7XUBt1Wr3bp1w08//YQxY8Zg4MCBWLlypUcnWrlyJUaOHImxY8di1qxZLrNA1DS2bduGOXPmOGVa4KmxarqO2irb0KBO22LXcigQBryRAEICAxEgTEbhcN9gvQMczjYykfP1RffuLABJjhifTgXNiV1CpkbMucLCQoXRrG+7duixcSMMCxciQBzYvbwUKgJ5ShPUA/4//QQA+AhQDKal584p/hv4hMUlfkIWisL16xXty3IVE0+DyHlBm8gdDXC2zhGHy3Af56P4EX5gNlqlElEJkdSwxpAQTW86QEnkACBLIgDBklqmcePGTPoiTG58uVhsNgOvvgqMG8ekQGD3UnxyNgAfA7gOwEFfXzj5Ovr7yxK5EOEZOmdrZeCD/lkAFySJgJZqtUCDyDUBkyArwo2IUpD0dJnInQJQLLwT/I1pEhyMR6Q0aAAQIJW3ufCMe1L6/keoQyRyPj4+aN5c+SacO3cOx1V2QgDzWl2/Y4dMyPJVGVEs0rfRYtEkcpxY+QNoKpHU/F69nMpdCaBxJWSGXEjk+OSvJnKBBoPCKWQugM/FCouLYRO8ZcslyVMeAH4m3vODgoLkQMcyzp5V5BUFHGYEPBdwCSDHU3S+aobt27dX6OigCCH+2WdI/u+/ClWrZcnJ8n5xZi04dcrJRs4dIseRKTmzRAIwEeGFF16Q93EqlStJsvhS1A9AubTIO99IoE/qvrJnDwDneJWRkZGyA8HatWudQ+A8/jiwZIli09GjR1FaWgotd8wsAKcryGByww03wGQyoaSkxClNYWVEzqDOflNP8MhGzmKxYPny5Zg4cSJmzZqFsLAw9OzZE5MnT8bMmTMxd+5c/Pzzz5g7dy5mzpyJyZMno2fPnjCZTEhKSsKoUaOwbNkytG7typ+n5jF79mzExsY6befb3AlW7EkdtVW2oUEdY8xQSbqTaABhu3bBTyA5YdAmcnaNVCcdAbnf8GPsfn6ybVWui6wGQMUSueNiMnkA2RYLCgsL5TARAORk8RgxAr6C9MRgtVboSKGGOJg2AtBKGORkdV8jZ2VzsMqWZukPGhZFZrNm+hsfwCl4LAAcKS9XDKzng4Ig9sRI1X3xgUN87wXgXwC/HDgAbwAhUlmvkBCFRE6EmsjlSISMk7WmTZsylbQAPlmVChMzjwwfCEc/eAtMEncYTMJ7Q0gIHBRIPrEskQuT+mAEGJH6RqO9/ClkASiQzi9SKE6J7C6ydnSE4x2xQEWmDx5k0gipvaIKlZuTR/j5KUhtiDTZnQ8Lg2Lak9rGswG8AzjSXqlUq35+fnI8RI4VqsTpgINE8Gd2QZAWRwN4SfptbNdOVq2KCAAQbrGgCwAjEcojImC54QbkuHhHt2tuZTCUlGBdWhqio6PxiZCfmd9bNZHzNxhgENrklMdBHfBbmrhPghFYwPGsAgMDUapeoJ47J0ur7JLdI3+v+dtUQgROB1wp3Xbs2FFh6BGtOHFazg7cUcC+bp28TxyZizRs5HxUiw9vb2+0aNFCk8idbNwYJC0eIlX7eE8qkMgwX7b4AciVMios2rnToS5VL7alfMpqItekSRPZgeDvv/92HmPXrgWGDJGq+BcPPfQQli1bBjO0w9icBTCtgmC9bdq0kbWMiji5NptmjmYF3LFzrANUKTlY//79MX/+fOTk5GDSpEkgImzatAnz58+XSd6mTZuQm5uLxMREHDp0CJs3b2bJ1esYaWlpLsOmWCwWpKoNyatZR22VbWhQEzm+SnUlkQGAgMxM+AqTkyuJXJmGtEhLIgc/PwQGsmE8R2NC4aiIyOWp1FXnfXxQWFiIW8SNAsEwCgMmAEU4hcogDqaNAbQRJlVfPlhpEDmTagVdolIpAmBEJTDQabMPXEjkiooUROGCyaSQyImKi759+7r0rosCUwMCgKkCiZwYRw4A8iXSmQhgGoCmjRo57rNqwi8QV9MSAQwkkvvBBTDVFseZM2ccUikA5O3NpKeSRC7AbocfmD1UOCBn5RDBZZtnwZxq1GgORgKvdkHku8OhClRPgPj2W+DsWZQHBWEzHOQNYEFyAWbrJar1QiXJ5QV/fyimDoG87wPwJxyERK1aBSCrV0PABn8toqEmcoWS1Cc8PByfg71P+wB4vfqqpkQOAKJDQuRg3XukMstcqLRzwNLefQDt8WP1zz/j5MmTTDojgY8/ahs5fwBGtU2VAFthIV54/nm0BXAbAF/p/c0yGjWJXKGGE5KXRN7zpX7aSHXcUaH/+YHZxqolv5VJ5LSInBjLTK1aNQpSenEEsZ054ySRM6uInI+PDywWi+Y4UWCxwCC9N4OhzEvdCOz9KZHeW5HI5UvSejEfqRORcyGRa9KkiexAsGnTpgrjgI4cORLz5s3DuHHjXJLmLDikhVpo0aKFHJon+O23gblz2Y5Tpyo0ZwDQYIhctSPYDR8+vF4ImrvIyMhAnAs9dlhYGLZILuo1VUdtlXUXpaWlihAYPKyC1Wp1L3m7m1B7svGQBFo5PM5BIgbHjsEsDObh0F5BlQcEOK3COgIolSYhWbXq5ydPUFlm9VDpQEWq1VzVPTFZrTh//jycg4ww2JcvV6x+yk+dcvslUkvkmgrEK0BSQ9tbtIBRpUpVI1RjG/n7o9zb22nCcEXkDqljPxUXKyRyFmEAGzx4MA5LMe/UaAYgQCJaxuBgB4lQgT91X19fWK1WXAh3KK+TAFjXrIHt7FmYANivvBJGwXbKu1Ejue8a/PxY3kObzSm0iQgFkfP3R7nVCvj6wsvXF4aSEkTCQVa17iffdxZArotk2E0ADHYxybSHIxp/E/VOyYmjOC4O1kWL8BOAJwAUde+ORpJtZIi3N8oLC+W+FSEZ0ud5e+M4HGpwe9u2MJ49ixIADwEwGI0okYi/XfDA9vb2htVqhdFoRBRYtP7FqJjIcVJZmJWFNwGMKC5GO2n/vcHB+CcoCDh/XlM9HRUUJBO5/yTyvgbAXRplc8GSwaeBkSt1m85rqLeysrJgtVqRl5enkMj52mzwVxFvO4Anb7gBn/z9N0wAvvr8cxwGIyVnpXHrsL8/SqVn6QPmvPHDwYPwlaSAeWCSVTp6VH7/T0VGIjQjA+0B/A7He5Zx8qTcJ0PAQthcAEvpxCnUjh07UNGsmaexTeynokTu9/nzMURwThCv3iQFXRfHHi/VmNd27VrYjx6Ft9EI2O3I69ABFklifMFigb1JExiPH8dnALYKx7UEI0gmKa6gSOR8JbOCw2DPysfHh717wvH0778ot1qd5pLGjRvjyiuvhMFgwKlTp3D60CHndwhsThM9Ty3S93mDAaVE8jt8Dtoe7UYA3r6+aN68OVq3aoWbAXT7/Xfg999hfeABGDIyXI7tNjDzCTp1CuVFRQp1fk3C3Tm7/kIR1wEqTKIOJvWqrIwnddRWWU8wdepUvCaEP+BYvny5dg7SKmK74FXpB0daGa1V5jIA9wA4vXGjPCEBbODT8lo9D5aCSVxXdzQYsOz0aZhMJvhLK8pzRUVyDtS9LpKaAxVL5DLPnsXbALjlBxUXY9++ffKgoIY9NVVB5HatXAln5bgziqGcoBoDmivNTW3aoGOrVgjRSLXFoUU88gICsGbFCtxmNCqirHtDm8jtPXQIea1by2EG/MrKFFI43+xsvAFgEdiK3VnWx9AckBPb/1eBvQgnVgcOHMDixYuRqbJZOTx/PshgQHsAx0JCFDHbvEJDsVgylG+0bx+uB+BdUiIvArSU+iKRKzIYsEI6Pj4oCP4SkeN9zxcskbj90CHFvbODqal2FhdjqFBftsGAcKn9vi5sb8T7xSVyZwA0MhhglI7ZIUmYS8BsqR7s3BmPS0TOq6QE2//5B1IiLURIC7IjJSUQ7/L6IUOwKCsLs9LTUQSgWVSULCHJOn4c+6WJ4MpVq3A6Ph7HMzPRFeydvdHfH0c0pGRqIle8ezfeBGR70FkAjnp7Y/HixTBYrbhd4/qbBAbKRG69tLD8W/NOKaVP4vKtDKz/ntWwCd2+fTsWL16MsgMHFO9VeUGBkxPBWQD/CFIfPzgkS7wPrA8IgE0I7L0fYDa+ElE4DkYUDIKaea+fHzrBYTspq1bh6H+tAXlReCMAblmen59foUTuApjK3RU94ETu0KFDeHnUKJde+T65ubDb7YpznRNTIgK4bs4cAA4nli3+/uDihX/z83HGaJTt7+SUiBJEAwyRyDWSFhCHwcKItGrVCn3LypRjV0YGli1aJI/hHIWFhVizZg2io6Nx/PhxLJ4/Hw9rXNue557DSrMZd1qtKIBjXDxvNCLfZkMEWN+yQpvI+QPodPXV2DdtGt6dNw+7hH3LFi1Ck40bXcY3PGIwoJXJBGN5Of76/nsUa2hSagIV5W4WcUkTucsRkydPxvNCypqCggI0b94cAwYMQHBwpXHE3ca3334r/+YRwF0NPMvBiFzT0lI55hqHlrQsoFEjlJ0+rSByoUQYfsMNeDosDP7SCq5x69bo0aMHvv76axRpuKNzaCt/GEx+fngJgH/nzhi3ezd8wVRIrsT0XiqbqPaCZKkilEClWjUY4KtBrHvccgvomWdgHzcOO379FbEaon0+YB2IjUWbuDggLAyBI0diSLNmMAQGKjJZuJLIWa1WBCxbBtv778P0ySeyVI0jqqgIL4HZQ52+6y58L/QpES0A+EnEuudNNwEffqhZjtOj3r17Y8iQIVi3ahVOrlsn2/20zcuTY40169sXtH69HO4ksk0bDJFsYgxhYcBrryHYYHBbImcKDpaP92raFDh7FiFQqo83/forjB1FdwY2+NsApAUGYoqw/dWrr8bMnTvhC21SDSglzZzIrQFw86xZCHv2WSAoCNe88gpM770newb36dMH2fPmAQA6BAejm9CeZhIhKw0JURC5a269FR/s2oUiyeC8a9eucnqxxsHBaCKpxUYdOIDAwkK898wz+F0KtBpuMsG7USOWQ1QA73GcyAUL+/8B8DpY7tYhQ4Y4xfQ6BvZOt/DxkcO17JVUaqpgMjJywTQQOTk5CiJ3AowIBUrvXHtp2wUwFf0tdjvuENONAYjw92c2h6K3KwD4+MAOJoVRu0WVAyjq2RP44w8AwECNNp6AkPpJaoNXly7Av//K18nfs1I4+qQ4vY+Gg8gBqNBGrghAmcEAs+r+ngQzZ+DXcOHCBdlL9T84x+UMlfqNOPa0EEhHP41zn+jYEZBs3Jp37YpI6Xdl4EQuCIJ0EsBVV12Fvn37wjRzJrMPlWAgwsCWLZU2iwBu7toVt6anY2mvXvj9+HGESwINe2ws7E88Aa9HmOVj16VLYbBacSOYRNQiHV/i54ezFy6gIxwETssAJgBAYmIier31FgxWK64V9sXHxsLLlVMZgAKTCYbmzYHDh3Fzu3ag612Ff64e1IHKXaFKNnIXC7TyXopwR+LlSR21VdYT+Pj4IDg4WPEBALPZXKOf9u3b49prWdfnRE4dDrTMYEBBy5bgsbGNe/fKcaT4i8WlZWJ3NQYEaKrozKdPIzQ0VJ7AzcL1bTeb8RqASoIZOCEvLw+lAPKuZBYoXjYbigoLXRI5NaxqLycXKIVyMPUnglEjLphXo0YwN2oE2w8/4DkViSuVSOMV0kCc7+sLU3IyTElJMLduDbPZzIicAJHI8UlyE5hKxqtdO5jciA3ZeMkSBZERIcYPC2rqMoqbDJPJBLPZjLDISHQBZKcS49atMEoExNSyJSNsfJ/FIvc7r1BGnfzKy90mclZvb/l4kmI+qYmcWUOauEP6PpSXp4iN9vpff+HkPfewtrm4TlcSuZCHH4YhPR2GXbvgHRKiGAciIyPxr/T7KqMRXmLoF+m9OQsoiJw5KEgRZ6tjx46ys4OxtBRlZWUwAHJonuHXXIP/PfEEAJbr1lXIHsBB5LhrWm7LlrgO7N0NDg5m91Rlj8bf426FhTABOG0wYKNkR0RgZOYTOIIsA4zI3XTTTQCUEjmuLDTk5KALGFHhCv7c3Fx4afRdH5vNSXp8DsCZrCz5vqh9u/8BEN2xo0uzAIA9O7VTSonkfMXptkjkeP8Tl3nDAfgK113RsroYQKmGtHeH9C1mV+FEUmvs433PlY2clmHPXh8ffBAXhxsA+Pn7M6cWNyCGkvIGk6ieBEuXZjabYdRYuNp37XKSOt2waxdML7yAsVlZ2APgjj//BAAYQ0Ph9dBDLDYdAIOkvuXXZpG+S/385PeVf9vgbCIRAOCOO+6AQSPIe8nJkzBJ0tidKscvQCJyUrYIr1Onanx+FT/u4JImcpUhJyenUkJVk3XUVtn6wBtvvIENGzagT58+8mCVA+DYUKaEegVAfNOmWDpxopyvkocjKYXSVR1QeloZg4K0B9WsLISEhMgTuCk4WHZ2OH3mDKYA+MnD6+Bi/fZdWHIXc3k5ys+fd0gDm2hZZzhQruV4oAFvaAzcqqCbAACJwBQUFCjuyQUAdonIBUvqvwtauQhVjiIikfsHQL/WrdHPZEJxcTFL1aR2LNFQERgffljp/CFAlgAYDPCT2j4GwLGmTQEN2zJufG+xWHAOwAoAVpOJBRVdvZoVat5cKekRpZ4ScfcpK3MiclFRDr8+kciVmUxyEm6bdL1qIoeMDKe2mqWFytmzZzFb2B4aGopIF573vK9rSeTyfX1ZYu2mTWUPWvEdj4iIQG8pdmSfkBDNyPinysuVzg6+vorMIc2aNVN4rZaWliIMkNW5plOn0E4gyV6SNETrfVMTOaPwLgRqONacg8Nx40pJireZSJHaidsDlguTei6YpBbQJnI+hYXg4dG5bWB2djYQ6iwP9bZanQLengMLBcPvkloLsBjMc7GiQCglUEp1CgGUtWyJcrC+FAUHuWraqhXib2cKZ3EaDgMwROijFRG5Img/kx3C70jpXeBEbhuc09QFghFX8U30EmyotYhc9vnz2BQZibVgggG8/DL+aFZh2GYADokcxxEwSbyccUIjRFSpZEpgEDKfNJLMZNpISe4dFxPISBzve1K/5z0xWupTZQEBMoETl8rBqjzZ4+69FxEREfKYK6Lg8GGQ5LCxRBhneU8+7+XFximgQTg8XPJEzmKxOMU848jLy0OPHi6z/FWpjtoq21Dh5+cnS+SyAeS+9BKOL1qEtwBsyctDlt2OHAAlwqomH0oJHKAcJE2uiNyZM/D19ZUncC+ByHFCVqKxeqoIdrsd/v7+iJFScZntdhgkcTYZjYA4YWvk1LOrA/kCuAHAANW2QLgORaCAJDHKy8tTELmTAIzSQBggqZq0YpipPVdFIlcKAC1b4iop9t7atWsBkwlW0Ti8USO5De5AVv4FBCBQmljmAvjjlVeA9u2dyneTgnuGSpNwOYAzXJLHr6dZM5YZg2PcOMdvyWvVbLPJgzwncu2F84lELqesDBEREUhMTITVFZFTpSQCgKjbmOWR3W7HawDesViAv5mllylIWzGWKX1rSeSKNI5RE7lrpawi5v37nYPRAjhZVgbF0sHPTyHRsFgsTl6rCmp+4oRT/lMAznH34EzkfIVA8FpELhsOIhYjvY9bnUoxGIR7kQt27RCOtxqN8iQcBqXUtRlcEzkvqxW+qveCT+q8T3BKch7AwwDeBtCyZUuUu3BqAdi7I0pl0wH4hoQgQyIgJwDcJ+3r2acPnp40SbOeh6+/Hl+DLXSd5UAOuCJyO4XfV0hE4mrp/x5o24uqz2OSxo9oKNPAcWTl5cmpsnx8fICICHzZq5eC6OYBODt0KPK6OLKbnoYyGDQn4lpEjo/3JIUgiYyMRJhEqIIlR7dANUHifU7V93hPaist+GyBgbJ08ASAWbNm4fjx4zCpFuXj77qLZUvRSKFYtH8/S48IFmicg7eoUCdydYuRI0ciQ2O1zREfH1+jddRW2YYKf39/hUSuUVQUgvr1gx3MUPO0JLHKEQbuAqNRsfIGlBOJlyvvRw0ix8NZ8MGC3HDoWAzgnMGATEl6GBMTg1DpJfcF4CUNJOX+/sogu598AvzwA1ZFRWGPtMmgQcQz4Lw69UbF6cgAwB4cDJhMyMnJQW5urhORM0nX5idJagq0YphVIJErBbNF4jGaeDgHRXgPi0WWerkDeSoNDJSfBcDS3oihMQ4dOoR//vlHJluhwiScq7JNQ3Q0kJwMvP46CxLcqpVjn9CPZIIkfV8hrLjFSefwmTPIzc3FZ599hgNSf7SgciJnu/pq+Xc5gC+bNZPJvJcLssslckECKeDtLNMgHuJ9iIiIAHhu36wsp7h6AHC8pEQpkfP3VxC5kJAQx7W7SeRKoE0AjNLz5BIs7+ho+Rm7ksjx95oHx9UiclFRUTAKfSwXjDB06tRJPr7MbJb7fxiU6tArwVSKNo2FjFdpKXxUJgmcNPD7wq/nIIAvwVSAUVFRaCr2MxX8LRYFkfsbbOw7qKH+bNyihab0CQB6b96M+wD8H5SBe9UohjaR+xcOG8a20dEIgcO8odM998BLQ4ujVowapQXCFU4lGc7l58uRD7jaPlBIvwcAxmuvRaOff4bXtQ7LslwA5YIq0FsiOlpEbgMvc+AAANb3f/jhB3zxxRfwkxxTDGqCxd99DSJ3datW6C/FX7UHB+MzsLBG74KZG0RHRztrV265hUnG+fvQpw8ypDb6bNwIAxFOA/JYDzjMGi6YzTqRq0uMGDEC27Ztc7I5S0tLAwCX4T+qWkdtlW1wSE0FxozBe6tX4x5pUzbYC8ntZwDIRDVfGGDyTKaKJXKBgYrI5nJA2DNn4OPjIxM5Y0CA04SithHTwjEAkUT4TbLLiYmJgUV4yY3Si20LDFSqGps2BUaPxqd9+sgJtr00bBnzoS3h0EyrJaDIxwfr169HREQExo4dCyscE+NJACZpEjVLBsz5WkSuEomcmsj9+++/yBMnRItFmUjdRZwwrfOKRC4sLExB5Fq0aIFrrnEkDxIJTP4gIfyytzeLI9e1K/Dyy85SFy8vuU1q1WrLli3lfkcASiVpSZZAdP6U4gCGQEWsNRZURpX6VOxrJhf9LFCSJAYKqiJO5GwaDjlcImcymVjOxoAAgMeW3OpMg44WFuICgMNffgmsXAn4+spqSZPJBIvF4hQQWGETduKEIn8pABSazVBSHwajitAbmjSRn5sWkcs3mRQx8QAoPAE5WrduDaNKIufr64sVK1agp5Txx+rjI9vchkP57nQCU9Gf+PdfqGEqLVWmQ4NjbFGrVsUxJyoqChNeflmjtQzBjRopyv8N5nChFUy6SYsWTrEQOYLcya8KoNzbG05vt78/DkHwiG3aVPaYPxsUhPe//dbZVALORI47nGlZtJYDyM7Lk4mcjxSfMzAwUBHjL1iSovsK5LcEUEj3jVIZmcgJYwkncn5ZWRgLoENgIAYMGICHHnxQcwEDAKcLC9G8eXOcU5kc9AOw49gxdPj1V7YhNBRnAEwG85qVx6XnngPuuw9ooUja5nDAePppZEjjfbikVt0Bpp5NAjAlIECWMhb4+OhEri4RFxeHhIQETFUZxiYnJyMlJcXJDq1NmzZycMCq1FFbZRscpk0D5s5Fq7w83ChtKg0IYAb3BoOsKuGRsm3CAPNNSIgTkVMQH39/ZjclIZ/bSKmIHPz9nSYUhaSkAiNdO4D1Ury2mJgYBAuSN4Nk32MPDnYQObNZttXy9/d3xEVTxbsrB5NuhGucm4c8cGVenm2zYfPmzSAibJM8xfh9yfb2hkFFqnI9lMiFN22Khx9+WJ749+zZg59//lk5+YaEKLxesXUr8L//uWix8rwmkwm9evVCZGQkc4SRJsZjffs6FRf7tv+NNzp2uMiUoIBKRSnGqGsm2PJw6cAFQWrCJyMLKrGRCwuDn2oyFvuaQWPCBIBhkndvEFhu3f/BQeQMGvaWnBhFREQ47ISukvwjNeJIHpaejTkuDujHfA5ffvllTJ8+HXv37kVISEjFqtXjx50kcqV+fk62VQDLnKJA48Zye4M01MQ53t4KSXs5HAbwYl7tmJgYGIV7yYlckyZNcP1A5jNa7usrE7kwKAPRcqX7aY30YsaSEnirJHI5knRUrVoV70J4eDg6qXN6CrBERirU5RvBxoGfADlEDIdfaKhLiZzJnf4NwO7rq5DI0bRpwOLFCkeKVpGRcniMLIlU+Gp40as9WQ3FxfDx8dEkcmVg9tlctSpK5BQBnqTn5zV4sOJ4m+D8whcuWhK5TADnpLKzADzH09nl5SnSHor4feVKHD9+HPtUxOkGAAZhMWpU2bzJRK5XL+DrrwGVrZwcBsrPD3ZpXAqSFjs7pCLTAXzXtCneBUu3mBoZqRO5ukZKSgrCw8ORlJSE6dOnY+zYsRg7diwSEhKcylosFs1sC57UUVtlGxQefpjZMgmwCZMzTwXEJXJHu3cHDAbYkpKwPCKiUiJnE4hcoWQYDimwZEVEzixKcK68kiWwV8EiTdBctdimTRtFWh85En9IiIPINWkie0v5+/vLqig/lfifX1ebjh2d1Md8MnLlWXv0wgWn4Jj8vuQFBDhJx3I1bDvUErnPACRLvwfefjuuu+46NG7cWE53tnz5ciWRUy8eOnUCRKLlCtJ5165diyNHjrCYhddfD+uxY9j2zDNOxUMEwt2ocWNg9Gj2R8OuzgkqSRF/FuXl5Yp8onxSEdWGedJ3c6hC5XByM3o0G+y3b2dJ0xWXKNxbVyp8yQOuqc2G+wC8BocRvFd0tFNxTmgjRGkdXwSoJA/2gAAUSU4b4v3z9/fHhAkTcMUVV1SuWj150ikbSUB0NHw0ridXTQoaN5bbq7gXL70ENGmC9y0WZfgQg0EmiPcKeWNjYmIUqb04kQMgk3S7n59CtdpeON8jAKZARcQlGMvL4aWKz5grjSVqIifeBYPBoJlujCM8KkpB5EoAOS6nk/Tdx8d1/9DAGoloirI6NZEzJCTI76GsIo6IkOO6FUmSYKMGwb6O/+BjY1ERfHx8NDUEVjDipSWRyxML8ufRpQvub95cVtOKRI479GgRuXwABULMxl5cCleBxJJn4XGd54HBSyX5doqfql6EiZknVH1elCiHhYXhXwBPATgfEOAgcllZmvasdYl6jyM3c+ZMjB8/vtbPo05M7wpbNdQZntZRm2UbDO65B+jcGRCMXU3CC8QnJp5K5/SNNwIffQS7ry98li6tULUKf3+WHFxaFZZFRQE7dzKJXIsWCiIXoJZAiasxPz+gd2+WpFxAsJ8fUFSEE9KgERMTAxgMKDEY4EskEzljWJjDRk7wNhOJnBp81dqhQwdk//abIlYU/73VaMSNqrRbAHC6rAyrVq1SbDsEFoTzVEiI00STrbVyVQ1iin/C8c2aNcPhw4exe/duJeEMCWGx4J56Cvj4Y7bNRRo5BaSB3cldPjIS0HBAiYiIQI8ePUBEzH7l88+BDh0AdxYwLiRyZWVlysTwfn7AhQsKCSh/Ps70Xm4YU78A8FMFma6IyO1p1QpXTZqkdI4RUAAgpBKJnAwXjhRlQUFAYSGMRqOmahOAQrVKWqrVsjInb+mQli0R4usLCEG+ASC7WTNAyLCByEht1eobbwCvv468K65Q9KUjgiS0nSChbt26tew0AjByLRM5iSjaAwNliVwEAItq0fKq05W7xglJ1VqRahWA00KJR+8HgJDGjTHe2xvzy8qQJG3jBMHJStbHx6VETsagQcDSpQCAF4ODcSIvD3cAeI/v9/dXqruFxQu/jujwcPlajNwxThgPbWYzTFarg7B16ABs2AAUF8PX1xdNNWKUlQGw2WzyuM0lcgEBAZoSOQDIbNUKByWplEjkTNLCRYvIFQD43G5ngaYBnI+MROiRI/I90YJNOr4yIufdWNHjneYIrVSGvH0m1bFc5puUlIQ9exzWct7e3oz0+fqyBdeJE+6Nk7WEOpHIZWZmYuXKlfj5558xc+ZMTJ48GaNGjcLAgQOd1Io6LiIIXmwAYBYmKnVy7pCQEHmC8vHxcSJyisHQ3x82gRDYuR3GmTOIjo5WEDn1akuhWvD3l9VPIoJUAzZXpVullTG/Cp9GjdiAe8stwAsvyOV9fX1dqkcVRM5FmT0u7M5yAWyU0t1wPAlgCIC9zZs7TTTnJCJXVlbmSEz97LOY4uUFVUZY6YIEqaO0Ws7Pz3eWyD3xBFPBcW9RV6EHOghKGzdsE0UYjUZs3LgRmzZtgtFoZM/q1VeV3qquoCI6nLiUlpaisTAQc5tCkXTz56MViBqAQiLpiURuV2wsMHasy/twBiqyJoGrgluK75KLOgqlcwYHByvCNYgIFhyFDGVlKC0urtTJBqGhmmT7QsuWyhAyjRvjjjvuQGRkJPqp3yuDAWazWdGXjkvHJiQkKJ5LTEyMQoVuh0DkhgwB7r8fR0ePlseEpoAjpl6UlhxJgguvU7WNnL9quwzVQkmUDfmFhiIzOhqNAPD06/7+/vD29kYBVGE/fH2dbUvVku7bHfkwyv38kAmVc4O/vzKJvQaRiyKSFyTBkr2v2HeKVeMzuFORpFrld5KEsZY/Fe6kxiVyRqNRSeSEd1B8tiTcQx/JFk12RBPuST6AaXY77pfeMf+yMuDmm4EJE+AK3Ja3MiLnp+ojTkTOhVkE/Pzgo4qFeQDAhg0bMG3aNMV1ms1mpqHh53IznmhtwWMiN5cnlAWTprnCgAEDYDKZYDKZEBMTI9uDvfXWW5gzZw6ICK1bt5ZdjnVchAgJQYnwcvoJqiP1pCWqgnx9fRUrd/LzQzfJbgsA4O/PEp1LMPKAjefOYcJzzyGcT7D+/ixllzCp+osE0s8PuOsuRuak+FwAECgMNmazWZ5EyyVDXdmmyWJhq64//gBGjJCPadasWaUSufbt28see2rSl+Fios4FUw+KOAdgCYCQ0FCniSbfasWxY8fQtGlT3Hzzzbhw4QLsUVF4rbwcmgoKDSIHwJnIGQzMc5STBY2k8QCAG25w/PaQyAFscjBWEPLBJYRJpAjMsYHXJ44nXtLkx5+Vk1RBC8KEazabFe1rIRpJq4icmU+0LiaJ8rAw3HHHHU7bR4wYgc8//xxvvvmmY6OLOnKk5xFSQXgYk8kEs/AsSK1a1YLFoknkAiIiZPUYAKBRIzz88MM4deoUundXJ2tiUgrxvb7+rrvwyCOPYO7cuYrn0rp1aydbSE4YEBICfPUVrP36OS+EGjVihul3363YnA2wbS7UmZywWVX9mNcvk2LV+yWGefELDZWzZHAEBARg3bp1uOPOO0GiSYePDyOV4kJAvRi68Ua2LSoKZ6V7L96R2D59lBlZhLZxIhcgSVCP+vigFbfvE/oOqc0U+P+iIvgKNnIkSJF5oOZ8SRrNJXKlpaXaqlWoiJwwbvtJC3BO5IoELYQxJAR2AH9Lklbv8+c1HY5EnJLqcTX2cvgLRM5gMDj6FkcFRM5PeE7HDAYUwSE1F4UTchBufi5u41dP8HgUDQ0Nxdy5c/Hzzz9XOKCkpKTg0UcfxZgxY5Ceno5cKedbTk4OJk2ahPnz52PWrFlIFCZYHRcfLggDdLAwIKiJnJgeTC2RM/j7I2nKFMcGFZHzbtuWDYxECC4rQxTvd9LALa64gsTB1t+fDYArVwKzHSFd/YW6hw4dKksDbCoi57SKlvDAAw8g4f77NfdxotC4cWOMA5MmrFNNklYXqrNcza0MISEhTqv88wBSU1ORk5ODVatWoUePHnhUikOmabEhHO+SyHkQQw6iE4Mqwn+tQkXkXn/9dXTs2BFPPfWUgjCYpXJ84O/YsaMTkXO658L1GwwGhVROVA+qSYMPP87bWzOBdsebblLccw5fX188/PDDCicNV6T4lKQirGjcVbQFQP7Zsw4i54psuyBywcHBzFPb0VgAcCkNVBO5Zn36YO7cuQgJCUHLli0RFBSE0NBQFrhZ5Vnqq+rbwcHBLOiuuDE6mt134TmUArhvwADg22+diZyPD9CihSyxNaveO07wXnzxRUd5CeWAoq8EaBA5Pz8/9OjRA4sWLYKXuIDk9YhETu0pGRkJHDgA/PcfCiRbSPGdHZKQgA4u1PSyDaSknm4+dKjDpEF4xmYhfA4AhwSdCIHe3g5nB8GO2KYiu5wElZWVuVStigTHLCxEgyRVY25uLogI+UIqrmgpzA5//wxuOIEYJNvHyiRygcK7RETO/bUC1WqQ4IW7T9JycCLnJJEDLk4it2PHDsTGxmLLli3YvHkz4uPjsUNy01UjJCQEs2fPxtixYzFnzhyHnhzKgWBCBaJUHQ0fYo7TUCHViaZqVYKvr69StervrxyE/f0VxCAwKsph+3XmjMOrSTpGVHkpiJwLOxVfof+JCwm7dE6Fs4PW8b6+uFqInySCD3Yh0orzNACrapKyuyBy2qGhGSwWi7ONHIC9ex0ZLPfv348vv/wSAJxDFwAuJXIKGzlXntLr1wOPP87UrhzcuxLQzlJRWxAWBYGNG+Pll1/G3r17ER4ejo5CTDrjNdfACofnWYcOHZyI3H/qulXXLxK5tmIqHxVp8Bb7itaKX4PEuYQLicERaSKsjMidy8uTA7P6QojBpiERBMBUq7ew3B128d4GBlasylRBrVqFYK/o4+ODo0eP4siRI0zKqZq41USOX6PineBtEeq1h4Rg3jffMOmx+Eyio5l93+rV+OijjxAREYEbVHE5n37tNSxfvhyvvvoqb6S8z6qKdekdFISmAql1Sp8kapb4tYjtEW03jUZ2z/38gKAgOTOH4o74+cHfhbRathbcxUzxDaJ0VOg7PldeqbSzE96NKC8v2WbXIBA5u4rIcclT+/btXUrkxLHEW7BlDJWIj9VqRVFREdL/c7xtvaWQQwVQBhGuCNxCrTIi51tJNp6KJHLiHMYzrXIHHwVhvViJXH5+Pn788UesWLECOTk5yMjIQFpaGn788UdkZma6PK5bt26YOnUqtm7dWqEqVsfFiXLRU1UQ5YsSuWbNmilCujgROT8/Jeny91d4kQY1aeKYCLOyKiRyoY0aOQZkF6qWYGG7aOvD7Tsqk8gBcDkYiESOo1QY8IsBpvrSGGwqkshZLBYniZxI5G655RaYBKmKemUNABBWyxWqVrVw3XXM+UGU0IjeoxoZLmoNAhH2Vdm03HTTTXjjjTcwf/58YOZM9GrdGjvAVtVNmzZ1InL/qOsWnHcAR0oxoGIi5yuq1qpL5FxIDNKlkAiVEbkQweHBH0K+T1faD4sFGD8e+OILlAg2mj4+Pg6bpQHqXCXOUEvkSCWFslgsjrAlon0l3CRyXFoikCK/pk0dkhLxvgcEMGesVq3wxBNPICsrCxHNlZaRQa1aIT4+3jEpC++M1WhUvhc+Pgoi5+QJKRI5LYmcKHEND1fY82kSOX9/l56QTr7qYgYg4R4YQkLkALY2gN0/6bytJDXneQAGgaCQC4lcQkIChnDPcsClRM5LIHKBgYHymJSbm4vNUrgnALhFWlQQgAtqafCYMcBjj8l/rwbLycxNVSojcobKAppXROSEeeoUHHaQwCWiWg0JCcG0adPQvXt3xMTEoEePHujRowemTZuGVq1aoaCgAJmZmdixYwcKNLxhhg8fjjFjxmDGjBlIV3kR6rh4USZIzqJcSOTGjRvHckxKcHJ28Pd3InI+wsvtGxbmID67djkIiYZqNSwszPGiupDIWaKisGjRIqSnpytsoHicNnlKqWjCVA0GJBEgo8WCOXPmKBKZlwq/dwEICAwEfv+deTi+9pq8r1IiJ9rJGAwoAfCvFBS1R48eeEwY/OxayZaFBZdI5IrFlX9lqlVRhRocDLz/PlMlTp9e8XE1CdGO8LnnFLsMBgNeeukljBgxguV/lfoNTwFUCCikFBsAByGdPdsp9qCYJ1Th7KAiHv7iRK5FxGpAIsfj4VVG5N59911ZTdcEQmgCF1JkWCzsuT70EDNjkODj48PU5//+C/z8c6XNnjx5MhRTslqdKOKjj7C5Y0c5NIaayPF73Unc+OST7FskZCKBFsmV6h4aDAan8cBLtQiAIKm3qoMb+/jg1ltvlf/mqzyaFWErtBaSIpFTmZ3wPMBqZwctIvf00087E7nYWMdvlUMOl5OfANh7KrWpleQ4cNpgUPZllYmE6Oww2AWRE8cSL8GT3mAwyNKst99+G6eFeGtXC2pfxbjXuzcwZ47DkS4gAEeCg7FM2t23b190uf56VIjK7G4rIHJewnVlQRm4/JJRrQLA7Nmz8eKLL2L06NEYN24cBg4cCJPJhNDQUMTExCA2NhYWiwUmkwnh4eEYOHCg7CAREhKCCRMmIDExEZMnT0ZmZqYupbvIcV4IMRAoSEpEexJut8XhjmrVW1yl+fnJqh+8+67yOCgn2PDwcMeLql41f/01k7i89x7uvPNOp3iBBjXxq2jCVNVtkAKePv7BBxgzZoxin0h2t/H29ujBjHsffFDep0Xk+IChtpErkOo8Kqk0o6OjWRgPDi2bNWHAVdhriYN/ZUGoRRIVFAQ8/TRw/jxQl+nkOCG59lrAha0iBx98IyMjWd+AMs/vHgBYtgxYscK1xEoLRiNKhAnDX5zItSaKytQ9IlxI5Pi03lLtjajCiBEjECiRBW5lReHhrE+MHMk2iGRCmKzEBZe8GOnUyfXkJ2DAgAH4TgxiXFEstSZNsPD222WJqNognUtyPuMbJk50qAZFUiRKkMR7rNVe4f0+DBX5VqHcy8uJyHXt2pUFutaC+N7w91QcTywWx3PV8F4GNCRyqjiCAPDee+9hqEio2rdXSsZVUklOnXjqON6m5pJqO8tkUrZTNW6IC1LFNbqQyJlUbR4+fLjc7m3CdoPBwBZbUKlC+b3hdTZqhM6dO8u7W7VqhYc4oVfj55/l/KgVQqtveHnJfemvsDAcBTAfSiJ3SahWAWYj98QTT+DRRx9F165d0bx5cyQkJGDLli3IycmB3W6XPzk5OUhLS5P3t23bFqNGjUJmZqasbk1NTUVSUlLlJ64mpk+frgi4u2DBglqtw92y8fHxSEpKkqP4Z2RkICkpCWPHjvW4ffWFQImk/acyKO3UqRPeffddLFq0SLGSAdyQyPn5wVtcVRkMjPAEBDgCRhqN8qAjTj5hYWGOQUZNzO67D9ixw2W8H7VXW4WkRh3c9c03Way7e+5xKlomELCtULnDC7/VAYQBYPTo0bBYLLj++usVErlClQQjKiqKGZFLEJ1F0KQJI1xS1gFASeRM4nVWJpETjdR5eyoIpForGDkS+OcfYM0ahRRFC3zwFZNyi8P4u7/9xgjhzRVlvoRMAkWUCf2lLiRyfIrsolL/asEokSi5p/O+8fXXwKxZwE8/OQq76OetKsg96grR3bvDuns3lkq2mhVBJG9aDhSPP/44vu/WDSWpqSyTDIdoYyoY0ENIAVcZkdsLjbAUArSIHAD8/vvvGDRoEN5//33lAeIz15LIBQQ41K8q+2H5nOIfFxI5g8HAvIk51MRSbIeQUkq2YJXuwXVS4PHDZrPivhhV77KCYItjg4vwI7n8PZKCF3/yySd4+eWXERMTg05PPokLX34JSBk5vv76ayxevBiNxEwL/Nq4NLdFC7z++uvybm9vb9fOCoMHO2dt0IJGDE/xHnxz++1oDTYeuyJysslFAyFyHgUEHjBgAHJycnDNNdcgMTER4eHhTtIHjpCQEHTr1g3dunWTyyxYsACJiYkYMGAAxo8fjzFjxiA1NbX6V1EBxo4dizZt2iA5OVneFh8fj5ycHLc9Zj2pw5OyOTk5mD59OqYLaqm4uLhavyc1iY6jR2O3yYRIjfQ2zz77rOYx6vAjmhI5tXg8JAR44AGWuJ4fIw3+ZYLhdHBwsMvkypUhNDIS2L1beU5XuOoqJsngTjxBQcwmRwPlwmC4FcD14gQitLEsMNCRLkbCzJkzMW/ePKYCFuyXrMHBipyo0dHRikFXjOeEQYOYClSAv5QV48KFCywbxtGjTPVSWSBTlbdhvcBkUk7aFYBLr1q1aiWTMXGqGnjbbW7VE62RlaFMCFodKE7OwvO1g9mRenfqBLfhot/y0LxXq70RNWCUniOXyBn4hOPjw+LdiROPisgtW7YMJ06cUEhCPEL79ih1w3zGuxJP5495QOqKIL4vIqnRuofC4mcvgC4VjA92teOGdGxERASWLFnifID4TldE5I4edSmRU6il/f2ZyvSff5yJtviOqt8D1SLxGwA9wNJg3QPIbWghmT/9HByMe0Uip1oguiORE9O1XXjnHYSuWweMGsWuyWTC66+/riBjHL6+vhg8eDAghDST783NNwMffQT07Yt+nTtj8ODBWLJkCSvv6tm6mxdaNcYCUNzTjp06yQ4YIpETHZ/k/Oj8vSooYPVWIQxTTcBtidykSZNgt9uRnZ2NdevWYerUqR5nZEhISMDy5csREhKCyZMnA4CC8NQ0tm3bhjlz5jhlTkhOTnZb6uVJHZ6eLyYmBsnJyUhISMDEiRORmpp6UZE4js4jRqCxaAheCXx8fGCF4EbPJXJhYew7NFQRIkTGXXc5fgs2YKXCytVoNDI1zIgRmsGAK4KfOkF7RRI5o1EZfkNDjcRVyrddJyfJwb9QSQJ8fIBffwUWLJBjGInecCEhIQ47PoGc+aq8CaOiohRkQ3QWUae04uBSOV8+ePIYchWhIRA5D/D444/jgw8+wAsvvFClmJXPS1LMDz74wGlfqbDYCBKJnDCYXwtgz59/ehbWRTUZ2OfNwwAAO6X/7SrIIczB7T2dJHIcoaGOZ626LwMGDMBDDz3kfnurCKf4XlWBOCn3FLKeipI6DmEi3oeKJXJ2FxI5lxDff/7+qux+5fusInJ3SePacCFIMHx9gR9/ZOp+wUkAgFL9qZbIidfk74/3li3Dnf7+GPPVV2ybIJXPBPBvcLCinSbVQs6lRE50qjAY8Oabb+Knn35C8y5dmHe7hgTbJcRxl98bk4l5yEuLiV9//RVbtmzB0KFDtcmSeuyuCFrzgkjkBO/eUBf1ykQuKMjRnnoMCuwWkdu+fTtGjRqF2NjYSg1t3cGYMWMwcuRI7NixQ875WBuYPXs2YkVDUAl8mzsqVk/q8PR8YWFhmDhxIlJSUpCcnIy4uLhK23MpgBs2y+pVf39GjP76C1i9GggIQBOtVatAiCCEsylTxyAaPhyYP99lqqMKGqb8X9lgJOYg1SByc+bMQU5ODqKFdluhMpoHWJT34cNl1egVknrA19dXOZAK7bOocshGREQoVKtW0cawEiJX0ro1G4x69dIsp4A4WV4ECAsLw1NPPYXGjRs7q0fdmGxmzpyJ7Oxs3KiRb5bbyNkA+Ip9TZjkcqCxQKgMqsnUGBsLvrwzGo0K72SXqIzI+fkxc4BXX3UicnWFqqhuZXBpvygIEPu5KFnnEO6rV+fOsiG+FuwqD9xKiZz4TnOCrJbIcfW6ysli7ty5WLJkCRIfftix0WhkBv+zZyvChgBQJmlXS01VqtUBAwagoKAA93Nb0nvvle1KpwDwVqUTs6jMYJwkcsOGAXfe6bTIvfLKKxnJqgrEulxIK81mM7p3785U8NUlcm3asLSNon2+CyLniu/IRA5oENkd3CJyXEVaUcf3FN26dUNXyUC8tpCWluZk0M5hsVjckn55UkdNnO9ygCaRA4Crr5aJglHLjsFkcoQgEOBE5KreMMdvi8V1RgMOMRuFhkrSYDCwFd2992Ln6NFygmtXkgBOxHr37g1fX19cqU5XJUwmwap+ZjQaFUGXC0SjYxeDESdy/i1bMlXbr79qllNg2DDgq6+YJ+NFBi6RexZSeBY3PDENBoNLSR739i0GYBBNAVQJ4dWpviqF0aitqgOc7E1dQjpG9hvVigc3eTIgBuKuYwwbNgwTJ06sks0y3n4bOHyYERMRXDKqzmoAKKTJs9escRnYGGA2ph5J5LTIhfjcAwLY/X7hBaVmAczMYdCgQTDzxUJlwg3R4Ug9RqkkcgCUxN9gAL78Em/dfz++gkTUhHEvKCwMQ4YMkf87HbtwIbBoUeWSe08gkjB3JHnCNcojv4qbvPXWWwCAZ555RruOmBilc4zwrMQFhoKwCVB4LTcAOzmPbOQq6vgNERkZGS6lXGFhYdgieljVQB1VPd+2bduwZcsW9OjRQ1Oi5wlKS0sVqkYeCsZqtcLaANRiVqtVljJxImfz8YFd1TaTySSvMsR2G5KS4DVuHCgmBuXSdjHWV3Wu0Wg2y3YqFBEh1+8SXbrA1L8/YLfD5u/vWu1oMGD/0KHY9uOPABiR1WrnPffcg3379uGRRx7BpEmTEBISorx2Ly/5hbWrVqDq+vKFe1IeEADSON+oUaOwb98+DBo0iAUtttu1DYHV4BORG/eat6sh9D3uFPM+gCvfew8PXnddtVTFPAxECQAfoR5Taancd/PApAmeXr9XQAAMknrQajSiadOmOHXqFEaMGOFWXSYfH8UqvbxxY80+UBvw5Jm/8cYbbpd1QnS08/NbtQqmd96B7YUXnPYZiork96c8IEDz2XOjBpvZrAjzYTUaK+4rgwfDKyYG1K0bbFI5o6+vPJ5YzWYWO4/nFteqKyAAOHeOEauKzvXSSzClp8P+wgvOzzQgAGYAFBSEcpsN4DlqVciVFgRmsxnlZrNjXPHywgcffIB//vkHrVu3duu5VPcdNwYFyfep3GKpvJ/6+MjPqTAoCN7nz8Nuscj3HQBeeOEFDBo0CB07dnTZLoOPj+O6fX0Vx3NkZWUpjr/uuuuwYcMGjBo1St5ueOEFIDERdM01NW564u499YjIbdy4ETt37nTLa0rEuHHj8Omnn3p0THXhiklzWCyWSst4UkdVzpeTk4OkpCTEx8cjMTERaWlp6N69O1JSUlxK9irD1KlT8ZoQm4xj+fLlzkEs6wlqidzBEyewf/FiRZmAwYNx/T//4NAdd+CwuK9JE0S/8ALy2rZFobR9+PDheOutt3DrrbdisaoeT9Dp5Elw66Nckwl/u1PXU0+xby0DaAG7pCjsAHDw4EGX7XzllVdw6tQpnNIQ04ft2wee3XTHsWPo3Lkzdu/eDV9fX6f6zp13KIa2Z2TgpMb5fH19MW3aNJw4cQInuDdwLaGhSaMPHT1arb4CAAGSZKQYwDqhrtjMTPBIZ3YAf//9t8dSuTiDQfauXbFuHV5++WWsX78effr0cavdvfLzISrw1h0+jLxqXq+nqLdnftttLP3VgQOKzabgYPTq0gVnevZEhot70WXAALRavhxfNm8Oq+RdCQDLVq2CrbJnOHMmk1RJdXc4cQJcLrhkzRqnYLvVgmRjDvV1EKHDiBEoatwYRyt43sck9eyFCxfw95Yt4FZjR0+fxp49e/DRRx/B29vbo3ekqs87OjMTPKTxqj17UJhTUY4bwGC1glsT2qOjgf/+w4nCQmzTaOvRCjLONNqzBzwiXXZhIdYLx9966634888/cdNNNynuwRNPPIEbb7wR3bt3V94bf38W41QY52sCRUJcvorgUc86ffq0LDGKj49HXFwc4uLiKlWRLliwoM6J3MUATuA44uLiMGrUKMTHx1c5aPLkyZNlA22ASeSaN2+OAQMGKFRv9QWr1YqUlBQAjnAb7bp0QRtBnC/j0UfREUBH9XYeU07CkCFDMG7cODRu3LhaUmPjxo3AL78AYDZoQ7TaVEWIIVJ69+5dtboFVUCXm2/Gb888g0mTJuHJJ5/ENSrvtRJBstatb190lVLi1DWsVitSU1OVEfTrEV9++SU2bNiA1157zT1bswqQJl1PCaBUR333naLcnXfe6fG5vCwWOVtG/yFD0N9icRkhQAumb74BNm2S/1+fkOCcuL2W0NCeuQLDhyMUQAdX+wcPhvX8eRS9/jrKly+XNw+8/XbNHLoVwbhrF5CSAjKbMVh0ZKhtSOPjVRUU2b17N3766Sc0bdoUfYQYkM3btkW0h2NTdZ+3wWiU44PeOHy4W/ZutieegKGgAKFEwH//IerKK9HEw3YbLBY5IHt4s2aKd3jw4MHIy8vTdHYYyWMx1gG0kitowSMiV1paiqFDh+LIkSNYvnw5li9fLk+cWsQuMzMTI0aMQHZ2tmetrwFUZs9XmQTN0zqqcj6t8CdxcXFISkrCggULkJCQUGkb1fDx8dH0BnPKDViP4O3bB+A2AKYOHWCqZtua1cQkJdheGBs1grEG75coDQ0JCanasxDa5xUZiVatWuFHSV3L8fXXX2PMmDF4btIkeZDyCg/3eBKqaTSU/vfggw/iQSEIc3VQJAXDLobS01hUZ3l7eztlLXALQn3mwEDPn5/Q38hggLlZszrvAw3lmXuM8HCYzWZFejCzn5/ndmGSA4zB37/B3Qdup+vj4wOzsMA3+fpWeSyu8vMWPFXNERGVZ2YAWGgSAJDi0JqaN/e83cJ1GwMCnMZ7t+1RaxHu3k+PZb27d+9GamoqWrVqhbS0NKSmpiItLU1B7CwWCyIiInDw4EEAAAnR/z1BmzZtkFOJmFVEWFgYUlNT3VJL5uTkVFl9WZU63C3Ly6SmplaJyF0M4ETuJQDd338f/V0l865riATYhfdUVSF6f1UU9qBCiITARfvuu+8+jB49GuY1axwbG4Ak9lJEk9atge3bYVMPtp07y44UA9zIUaoJUQ1XlTAdQl8xNG5c70T+YsP48eOxatUqbA0PR/fBg6tm3M9VsVV932sRXDsTGBiodMqoppS6SmjZkpG3tm3dI3Einn+eORtUkuFFE+Jz8dQhqYHBIyLXoUMH7Nu3D5MmTcJjjz0mS+A40tLSsGDBAnzzzTc4INknVEfVVd2crBaLxSURzMvLQw8x2XAN1OFJ2REjRiAjIwNbt27VLO8Jgb3YYDQa4efnh+LiYlivuKJmPaCqAzeIUlVRI0ROdESowLvLbDYrJ/8aCBmkwxm9+vUDtm9HJ7WD0sSJgNUK++234zd3QrpoQSRynk5ugJK4qXOK6qgUkZGR2Lx5c+UFKwKXijZAIjds2DDs3bsX9913n3Lcc+EcUauIigLWrQOqIgGLjARceaZWBtFm/CInch6NEDz+1bRp0zBr1iwn/W1mZiY+++wzFBcXIykpCWlpaRgzZky9ebuOHDkSGRkZLvfHu5Ef0pM6PCm7bds2zbAGnMD1vMjidXkKTmY8Ds1Qm6hFIieKyKtM5MQJ2RMpmy6RqxVwlZSP2qzC3x94800Yr7mm6mNfdSVoYjiMRx6pXl06qgY+tjUQJzMRoaGhePvtt5kZlDgG1weRA1hg42pqyDzGJSSR84jI5eXl4bzkDTdt2jS89dZbKCgoQGZmJnr27ImxY8eidevW2Lp1K6ZNm4b+/ftj9uzZ9RbodsSIEdi2bZuTfVpaWhoAuNUuT+rwpGxCQoKmlw+PqeRu+rCLFRESUXIVObteUEdEzikgsLsICmKBLI8fr1yKKcaR8zQwsg73wCfoqtjAVYbqejjedRcQH88CY7tKMq6jdtFBcqlQB/RtaBDVqfVF5OoDl6tEzm63K+y2pk2bhokTJ6JNmzbYunUrJkyYgEOHDqGbKu9mTQYS9gRxcXFISEjAVB67R0JycjJSUlKc2tWmTRu0UUXM96QOT8pOnjxZM8XX1KlTNdt2qeGTTz7BBx98UPV8jrUBUR3pSYoZNyDaiVZZIgewVatG3k8niOrUqqjmdFQOPlbUhiShukSua1dg+XKWqk5H/eCqq4DMTBZA+2KBO3EkLxV4eztI7EVO5DwaLdLT0/HZZ5/hscceQ9u2bZGYmIhZs2Zhy5YtmD59Om6++WbN49xRYdYWUlJSMH36dCQlJSE8PBzp6ekYO3aspiOBxWLRVHd6Uoe7ZS0Wi5yD1WKxyCrZFStWVDso8MWAPn36oJ+HuVBrHbUokRMDO1aLyLmLHj2A//2PGRDrqB3ceSewcaNzmqSaQE3GHNNRf2jZsr5b4BkuJ4mcwcCkcufPX15EbvLkyZg6dSrGjBmD/Px8pKWlYdiwYdiyZQsee+wxl0SuIruxuoA6ib0ruHI88KQOT8paLBbMnj3b7Xp11DLEybOGiRxPdO7t7V3t+GVuwWCQw4/oqCUYje7lp60KdCKnoz5wORE5gNnJXQJEziOdi0jIQkJCMGzYMPl/cnIyJvNo0xUcp0NHg0WxkJSnhm33AgMDkZOTc0l7I+uoQehETkd9QMzjejmA28ld5ETOo9EiJSUF27dvR4iLcAZ5eXlYsGCBk33Xtm3bqtxAHTrqDEKO2tqYSBuUY4eOhg097puO+sDlJpG7HIkcABw6dMjjk9RX+BEdOjzCbbcB7doBDc12T8flhxEjWFDhFi3quyU6LidceWV9t6BuwW3iL3LnQo+IXGxsLLZs2eLxSdwJvKtDR70jMBDYv7/hBCjWcfli1CgWIPXqq+u7JTouB2zcCCxeDDz7bH23pG6RnAwsWQL071/fLakWPCJyVU1ppRM5HRcNdBKnoyHAYABcOI/p0FHj6NWr9hx3GjKuvZZ9LnJ4ROQ+++yzKp0kOTm5SsfpqD54/DJ1Fo76gtVqRVFREQoKChpcImkdNQ/9eV9+0J/55QX9edce+LxdWb56j4icKyeH2jpOR/XBM3E0b968nluiQ4cOHTp06PAU58+fr5BHGagyqgfg8OHDmDNnjlPGgupg8uTJGDVqFMv1pqPWYLfbcfLkSQQFBTUIp5OCggI0b94cx44dQ7CeA/SSh/68Lz/oz/zygv68aw9EhPPnzyMqKgrGCjL0uCWRa926NUaOHImBAwdizpw5aFmNaNWZmZkYO3YskpKSdBJXBzAajWjWrFl9N8MJwcHB+kt/GUF/3pcf9Gd+eUF/3rUDdzSabqtWu3Xrhp9++gkjR46EwWBAUlKSy0wOWli5ciVmzZqF/Px8zJo1C61bt3b7WB06dOjQoUOHDh3O8MhGzmKxYPny5VixYgVmzZqFhIQEtGnTBnFxcQgPD5dzlebk5CAvLw/Z2dlIS0vDtm3bEBsbi0mTJmH48OG1dS06dOjQoUOHDh2XFaoUvr5///7oL8VdWbhwITZv3oxNmzYhLy8PGRkZsFgsiImJQVhYGBITExEXF6dL4HQAAHx8fPDqq6/Cx8envpuiow6gP+/LD/ozv7ygP+/6h1vODjp06NChQ4cOHToaHly7QejQoUOHDh06dOho0NCJnA4dOnTo0KFDx0UKncjp0KFDhw4dOnRcpNCJnA4dOnTo0KFDx0UKncjp0KFDhw4dOnRcpNCJnA4dOnTo0KFDx0UKncjp0KFDhw4dOnRcpNCJnA4dOnTo0KFDx0WKKmV20HHxwG634+TJkwgKCoLBYKjv5ujQoUOHDh063AAR4fz584iKioLR6FruVu9EbubMmRg/fnx9N+OSxcmTJ9G8efP6boYOHTp06NChowo4duwYmjVr5nJ/naToyszMREZGhpyLNTs7W/6/ZcsWZGdn13YTLlvk5+fDYrHg2LFjCA4Orrd2WK1WLF++HAMGDIDZbK63duioW+jP/fKD/swvT+jPveZRUFCA5s2bIy8vDyEhIS7LeSyRmzt3Lh599FEAFUvTBgwYgBUrVgBg4kEOi8UCg8GA/v37o3Xr1sjIyPC0CTo8AFenBgcH1zuR8/f3R3BwsP6SX0awFhXpz/0yg/6uX57Qn3vtoTKzKI+JXGhoKObOnYuwsLAKGWJKSgomTpwIg8GApKQkRfkZM2ZgwoQJ8m8dOnRcgli9Gl6DBiHm3nuBIUPquzU6dOjQcUnCI6/VHTt2IDY2Flu2bMHmzZsRHx+PHTt2aJYNCQnB7NmzMXbsWMyZMwe5ubnyPpFdckKnQ4eOSwyrVsFQUoJGLsYIHTp06NBRfbgtkcvPz8ePP/6Itm3bIicnB7m5uUhLS8OhQ4dgsVjQqlUrzeO6deuGbt26YeHChViwYIHu2KBDx+WC06cBAL7CIk6HDh06dNQs3CZyISEhmDZtGrZv345Dhw4hPDwcPXr0kO3lKsPw4cORn5+PGTNm6HZxOnRcDjh1CgDgk5dXv+3QoUOHjksYHgcEnj17Nl588UUkJiZi1qxZHh0bEhKCCRMmIDExEZMnT0ZmZiZmzpzpaRN06NBxMUCSyPnk5QF2e/22RYcOHTouUXhsIzd9+nQEBwcjJCTEYyLH0a1bN0ydOhWpqalISkqqUh06dOho4JCInNFmA/QQQzp06NBRK/DIazUhIQG5ubmIi4tDTEwMwsPDq2XzNmbMGKSmplb5eB06dDRQEMmqVQDsd1RU/bVHhw4dOi5ReBx+JCMjo8KwI54iOTm5xurSoUNHA0FeHlBWJv81nDlTf23RoUOHjksYHqlWY2JiapTEAUDr1q1rtD4dOnQ0AEhqVRmidE6HDh06dNQYPCJyFoullpqhQ4eOSwoqIqdL5HTo0KGjduARkassTYQOHTp0AHCWwKkldDouLaxbB3z5pe6drENHPcAjG7n09HTs3LkTXbp0qa321BqmT5+O7OxshIeHIz09HfHx8UhISKi1OtwtGx8fj9jYWIwaNQqxsbHIyMjA7NmzkZeXh9mzZ1fpWnXoqHeoJXI6kbt0QQQMHw6cOQOsXQt8/HF9t0iHjssKHhG5vLw8xMbGAmAEJC4uDnFxcejatWuFx82cObNeMzqMHTsWbdq0UThWxMfHIycnB4mJiTVehydlc3JyMH36dEyfPl3eFhcXp3vz6ri4IRE3ioqC4eRJNsnruDRx5Ijj+X7xBUwlJTAMH1775yUCjh0DmjcHdG2RjssZ5AG6d+9OSUlJFBsbSwaDgQwGAxmNRjIajTRw4ECaMWMGbd++3em4kSNHenKaGsXWrVtJ6zJdba9uHZ6eLyEhgZKTkykhIYEmTpxIqampbrXJXeTn5xMAys/Pr9F6PUVZWRn98ssvVFZWVq/tqDGsWEH044/13YqGi3vvJQLINngwEUD2du3qu0U6agsLFxIBROHhRCYTEUDH+vShssLC2j3vvHnsvDNm1O55dLiFGhvjH3yQqFUrouzsmmnYRQx352+PvVanTZuGrVu3wm63Y/ny5Rg/fjy6du2K5cuXY+LEiejevTvCw8MxcOBAvP3229ixY0e9puSaPXu2LEUUwbctWLCgRuvw9HxhYWGYOHEiUlJSkJycjLi4uErbo6OeQQQkJACjRwOZmfXdmoYJLpHjZhi6RM4z/PIL8NNP9d0K97B1K/seOhRISQGZzWi2di1Md9+tCEFT41ixgn2vXl1759BRtyguBr79lo2r+nN1G9VydoiLi0NycrITsWvdujVSU1MxYcIEdO/eHdu2bavRRnuCtLQ0xMTEaO6zWCxuqTA9qaMmzqejgSM3l30AYM+e+m1LQwUncpLZhaGgACgqqscGXUTIywNGjADuvvvicBLh43tsLDB0KGzz58Pm5QXjr7+ya6gt8Hfvv/9q7xw66hbbtgHl5ez33r3125aLCB4Rucoka5zYbdmyBXa7HampqXj00Uer1cDqIiMjA2FhYZr7wsLCsGXLlhqto6rn27ZtG+bMmVOvpFeHmzh50vF7//76a0dDBidybdui3MdHsU1HJdiyhU1mdrtD2tVQQeRoY/fubNMtt2DjSy+BTCZg4UJmQ1fTsNkcE31GBlBaWvPn0FH32LDB8fvff+uvHRcZPHZ2OH/+PIKCgtwq379/f/Tv3x+HDx+uUuOqi7y8vAr3WyyWSst4UkdVzpeTk4OkpCTEx8cjMTERaWlp6N69O1JSUlxK9ipCaWkpSoVBraCgAABgtVphtVo9rq+mwM9dn22oKRiOHJFfHPvevbBdAtdUoygrg/ncOQCANSICZLHA68wZlB87BmrevJ4bVwXs3w+0agVwQlrLMP7zD0zSb9uWLbAPGFAn560Sjh+H+exZkMmE8g4dAGmcOdutG6hdOxj++w/le/eCajo924EDMPNxzm6Hdd8+4Mora/YcOjxCTYzxpvXrZekS7dmD8st8bHX3XnpE5Ox2OxISErBs2TKPGqMHEnYNTuA44uLiMGrUKMTHxyM9Pd3j+qZOnYrXXnvNafvy5cvh7+9frbbWBC4F1XKLtDR0k37nbtiAtYsX12t7Ghp8z53DQAB2kwmp27ahT2goAs6cwbbFi3GqksVOQ0Pzv/5C7Pvv4+DQodj7wAN1cs6ef/4JTnvOLF2KzZVEBagK/E+dQvv583G8b1+c7dat8gNcoMmmTbgGQEGzZlj111+KfWeCg9EUwN5ffsHhGraVa7phA3oJ/7f/8ANOXX99jZ5DR9VQnTF+wJo18JN+2/ftw5Lff2eS3csURW6ao3gcR+6zzz7DY489hrZt2yIxMRHBwcGVHhcfH+/JaWoMlRHIyiRontZRlfNphT+Ji4tDUlISFixY4HGsu8mTJ+P555+X/xcUFKB58+YYMGCAW8+qtmC1WpGamor4+HiYzeZ6a0dNwLh9u/w77OxZDBkypB5b4x4MmzfDsGMH7I8+WuuhGgySqs3QpAniBw5E3owZAIDuUVGwXwT3SobNBq8XXgAAtDl2DK3qqO1eTz4p/2566lSt9C/jiy/C9NdfaPHXX7Dffz9sM2YAoaGe17N5MwAg6MYb5Xbydz3i+uuBTZtwpbc3OtbwNRhVJijd/f2r3beMzz0Hw7ZtsP3yS5XuxeWOao/xx4/DnJ3NiJvZDFNJCQZfcQXQvn3NN/YiAdeoVQaPiBwAjBkzBmPGjEF+fj7S0tIwbNgwt45piMjJyamS+rKqdbhblpdJTU31mMj5+PjAR0MFZDaba5ZArVkD/Pwz8OyzTO3kJmq8HfUBwdbLcO4czPn5QEREPTbIDdx3H5CRAVPr1sDgwbV7rrNnATAiZzabUSJNiqazZ2HSevYbNgDvvQfMmAG0aOGy2v3792PPnj0YXhcxygBg0SJAkoob9++H0cur9uOVnT4NHD/OzkMEw5EjMBcUAOHhNXue48fln8avv4YxNRWYNQu4/XbP6tm5k9XRoweMqmdr6NABAGA6dEj7uVcH3D4uMhI4cwamgwerd47//pMDGRs//hjQ0GrocA9VHuP5AvDqq1n/37YN5oMHgauuquEWXjxw9z565OwgIiQkxC0SV9+wWCzIycnR3JeXl4cePXrUaB2elB0xYgS6SwbCWnBVT4PAq68C77/PJrvLDSdOKP83dIeHEyeYQTgA/Pln7Z+PE90mTQAApVy6oU7bxTFjBjB/PvD99y6rLC0tRf/+/ZGQkIC/VCq8WgERIAT0xvnzzs+9KlizhtXrKpWVJOFCx45A27bstyABrjEcO8a+X3iBSTxOnQLuuAO45x4WAsJdcMmY1jjWrh37PnCgem3VAvdY5XNQdT1XP/nE8fv995nnsI66xT//sO9rr3XYO+oOD26hykTuYsHIkSMr9LZ1R+3rSR2elN22bZumhysncD179qy0bfWGoUPZ9+VI5LjXKl8tNfTwB6In2J9/MpJSm+BErmlTAEAJNzlw4bV6QfLkzqlg0P76669xQiJSS5YsqZl2VoQVKxhJ8fMDoqPZtn37qlfnwYNMGjppkuv3hhO5nj0BbrtWG57sXCI3fDgjihMnAkYjI9MffeReHadPs3fBYAA00jYSJ3KZmTXrVVpSwu4lwOI5AuwdrGq/vnAB+Oor9ttiAfLzgQ8+qHYznWCzsfvrakFzuUMnclXGJU/kRowYgW3btjnZp6WlpQGAWwF4PanDk7IJCQmahqE8aLC76cPqBXfeyb7XrgWysuq1KXUOLpm59lr23dAlciKRy8ys/faqJHJctapF5LJOnICPJB3auXQpSGMyLi8vV6S7W8EDwdYm+PkefRToJZnVVyeuldXKpF3cePmPP7TLiUSOBxavaSJnszn6cPPmjKwmJwNvvcW2rV3rXj28XR06AAEBzvsjI4GgICZ9rMmg8Pv3s2sIDQX69AG8vIDCwqpLTL/9FigoAK64wpEn9t132baaxIwZrA/ceKMu8VOjrMwRxubaa4FOndjvi4DInTx50m2nhNrCJU/k4uLikJCQgKlTpyq2JycnIyUlxclBoU2bNmjTpk2V6/Ck7OTJkzF27FhFuW3btmHq1KmabWtQaNGCqVOIgN9+q+/W1B2sVgdx7d+ffTd0idz69ezb25t9V9fLtqgIuOUW4MMPtfdziYMbqtVpY8aAW4F4nTuHhQsXOpVJSUlBeno6QkJCAADbt2/HOSm8Sa1g61YgLQ0wmYDnn2dqTqB6Ern/+z9G0rwks+TFi53Vq0R1Q+TOnGFx6kwmWWoKAOjdm33zNlQGVfw4JxgMjBwBNbt44GrVq65ifZqP11V5D4kc5O3xx4FRo5iqOS/PfcmkO8jLcywODh5kgZJttpqr/2LHrl1M0hoWxlTyXCK3f78jQHADxZNPPong4GDMmzev3tpwyRM5gE0E4eHhSEpKwvTp0zF27FiMHTtW05HAYrFoOiR4Uoe7ZS0WC5KTkzF27FgkJSVhxIgRmDp1KlasWOGxk0O94HJUr546xQZ/s9kx8TVkIldS4phwH3uMfVeXyP39N6vj//5PW53lykYuK0sxef3+++84LKhJmwKYMGECSkpK5G12ux1vSZKi8ePH46qrrgIR1a6d3PTp7Hv0aObIU10it3atQ9r15ZdMSpWVxQL/isjMBLKzWd/q0sWhWj14sGalQ9w+LiqKkTmObt2YevXUKfekW2JGB1fgHoc1aScnEjmASQSBqj2fv/9m9fn7Aw88wO7Hyy+zfW+/zWwjawLvvsvIXMuWTAK6ZInjPGoQAbW5UGmIENWqBgN77/z9maSuCmG46hIbN26EzWartuNktVAnmV911BvcTbpbJfz7L0ta7e1NVEn9NZZQub6xfj275pYtiU6cYL9NJqKSkvpumTbWrWNtbNyYaP9+9ttsJiooqHqdX3zB6gGITp1y3t+6Ndu3bh2VlZXRrwsXkt1gYNtOnyYi1i+bNWtGk3g9AF0wGAgATZ06Va7q119/JQAUFBREubm59OyzzxIASkxMrHr7K8KhQ0RGI2vTzp1s25Yt7H+jRp7Xl5fHEoADRPfdx7YNH87+/+9/yrI//cS29+jh2Na8Odu2enXVrkcLKSmszuuvd97XuTPbt2hR5fW0aKHZNsW7PmUKK/PII+63LyODKDqaaNIk7f233srq/Phj9n/SJPb/8cfdPwfHiBHsWLE/Wa1Ebduy7cnJntepxtmzREFBrL6UFKLvv3e8Pz/+qCy7cSN7LgDRuHGsLRcJqjXG3303u+b/+z/Htu7d2baFC2uukTWMY8eOEQAymUx04cKFGq/f3fn7spDI6agldOzIVCdlZWyFeYni8OHDDgkQl1RERTG1VFAQkzI11FUjV6tefz17Vm3bMvWwKzuztDTX+zjEFGW7dyv3ETlJ5MhkAho1YtukfZMmTcLx48fRKzBQPjSACIEA3nrrLZw+fRpEhDfffBMA8MQTT8Biscg2ptzmtMYxcyZTeQ4eDFx9NdvGJT5nz3ouKXnqKSZpa9UK+OgjnDt3Dulcwqf2IBbVqhy1oV7ljg7Nmjnv4+euTL167hxw9Cj7XVHAYq5a9UQi98037D374ANtD1pXEjlPJeMnTzq0CU884dju5eWQls2cyezvqoMZM5hkr2tX5mV7113MuQQAHnoI2LGDSUnvvRe45hrHO/vpp8Ctt9a8rV5DhCiR47gIHB42btwIALjqqqsQoGUnWkfQiZyOqsNgaFjq1bIyNtkePMhe/hqwQbHZbOjfvz9uvvlmlgeXE7noaHb9VZ1E6grc0eG669g3D5qqpV7duRMYMIBNHhVNXqKt265dyn0FBY7JVyJyit+nTuHvv//Gp59+CgDozz1CJQzs3Bnnz5/HK6+8gr/++gubNm2Cr68vnn32WeDgQfQrLISXlxcyMjIqzf3sMU6fZqpPAEhKcmwPCGAqMcAz9V1KCiMlRiMzqA8OxrBhw3D9G2+w/Vu3Ku+lh0Tu7NmziI6Oxj333ON+mwCHalUrXZq7RI63p107oKJA41UhcrxvFhUB6ixC588zYgxUn8jNmcPsr/r0cZB2jrvvBmJi2Hgye7Zn9Yo4dcphS/rGG6wvAEzVPnAge1cGDmQq6O++Y/seeAD44gumWly2jLWPk+ZaQmFhIe655x7MnDmzVs+jiaws5gxjMDgciwDPHR5ycti9evbZGm+iK3Aid80119TZObVQJ0Rux44ddXEaHfUBTuQWL66fxNWHD7MX3t+f5cJs3JhNHlddBfzvf9Wu/s8//5RzBf/1118OaRQnIJVNIgsXuu8FWNMgUkrkACWRU9u3TZjAtpWUKALGOkGUyElErrCwEK+99hrmSiTFHhTEnglvikTkcvftkwOEP/rIIwhWhXKZItnxff7553jqqadYuUcfRWRkJHD//fAfNQpJUny1Gvdeff551oevvRbo21e5ryp2cty4fdIkoHdv5ObmYu3atcgCsEkqsuGVV5inrs3msGV0k8ilpqbi5MmT+OGHH5Dliee4O0Ruy5aKw3lU5ujAwUOQnDnDwnpUhrNngU2bHP9//lm5n0/qUVHMMB5w2OGdPOm+9MpqZUQOUErjOMxm4MUX2e/p01n5qmDqVEbWrr3W8e4BzBbvhx+YhDwri5W54QZ23+fNY5K6NWvYAmj3biapU9tU1iBefvllfP/995g8eTKys7Nr7TyakMgQOnYEJIcmAA6JnLve4q++CqxbxwJbu4rTWMNoKESuTmzkeog2HzrqFLVqI0dEZLMRRUUxW4Y//3RZrNZs5KZOddib8I+/v8OmqZrnGzhwIAEgADRs2DCie+5hdU+fzgq8+abS/knEjh0OG7pffqlWO6qEw4fZ+b28iIqK2LbiYiI/P6UNGBHR0qXKe7hihet6r7nGUa5rV7Lb7ZSQkEAAqK+0/T+AmjdvToMGDaKOHTvS/IAAIoAmSfeySZMmlLtnj+P+XHutbDM0evRo+Z57eXlRZmYmkd1OFBhIBNDJJk0IAI0cObLm7tUvvzjasnmz8/7nnmP7n33WvfpOnXLcI8ku8JdffiFI9+XTpk2JAPoZoFtuuYVOpqWxsgEBROXljnq4HabRSFRYqDgFtxcEQPPmzXP/Wvm91rI9Ki1lNq8Asxd0hYQE5XsgwOldb9KEldW6r2p88w0ry23KLBbWJo7PPmPbBwxQHsfPsWlT5ecgctgjRkYq6xdRWupox9697tUr4sgRx71MS9Muc+AA0cMPEy1YwPq4Vh3cbtHPj9mQnT/veVsqwIYNG8gg2acCoDlz5lSpniqP8S++yK7v4YeV2zMyHDbYldkK7t7N3l3VO1ebsFqt5O/vTwBoz549tXKOWrGRGzVqlEefgQMHomfPnjWvAtHRcGA0OmLK/fKL026r1Vq7MXa46nDKFCZaLy9nK/9GjdjqvhoJnNPT07FMUO1s2LABJKpWAYdETiu8Ag+lYbMBI0dWbntW0+DSuNhY5ikHAL6+jrApXIVlszFpnIADK1e6rldUB+7di+Q338SCBQtgNptxuyTROQ3g2LFjWLp0Kfbt24dDkqq2KYB27drh+++/h4XX06aNIzXX6dOYNm0afH19AQD33nsvWrZsyZ7phQusjtOnMRhMImeviZV3bq7Do3fCBEAr2wtX87grHeD9pnt3Fk8NwKpVqwAAQ4YMwaOSKUI8gNQ//8QkyfZvu9GIe+6/H//73/+wZs0aZocZGckkDCo19mZB/fn777+71y6gYhs5b2+HzVtF6tWKMjqo4Yl6lffJxx9n0qi8PED0UFbbx3F44rman888rgEgMdERlkcNb2+HRJEHINaC3c5U8Q89xKSwv/zCJPSvvcbMPfr1c7xzarRrB3z+OQvMrJX+rUULJtEfPJhJ7f73P6byff/9GtGAlJaW4pFHHgERIVxKA/fTTz9Vu16PoGUfBzBzBu65euiQ6+OJgGeeUZrS1LIqGgD+/fdfFBUVISgoCB14/6sneETkUlNTkZ6ejtzcXMXH1fbs7Gykp6e7lQZLx0UMrl799VfFy0REuPXWWxEVFYVjXJ2jASLCU089hWeffVYzIGwFBzqI3IABLECoyYTjp09jOc9N+e23nl6NjNmSbcyNN94ILy8vnDp1CuVHjrCdWqpVddu5WqhVKzYY3XGHMjhvbYOfi6tVOdR2cl9/DezeDWtAAH6Vivzy8cfaCZvtdgeRMxiAsjJ888orAICPPvoIL9x9NwDguqFDsXr1anz88ccYP348Rkhq0icTEnDgwAH069fPoY7u2NERz+zUKbRs2RIffvghevfujSlTprDtqv7zP6MR2dnZ2Cnl+qwWnn+e2ce1b8/UM1rwVLXKnX+EvLbcYaZfv37w6tkTaNoUgQDGXXkluDJ15fnz+P777/H6668jPj4e2Tk5murV8vJybBdSdy1btgyl7kzs5eUO1biWahWo1E7ux08/dQT45SFSKoK7RM5mA5YuZb9vvdWxQBTVq66IHH8+ldnJlZUxh4N//2UEWUutKoKnSauISPzzD1O/zpvH1OhDh7L2fPEF2//66xWfozIEB7MA0j/+yIjf2bPMDuyKK9g5qkHo3nzzTezduxeNGzeWF61//fUXzpw5U702uwubzaFKVxM5o9HxXCuyk1u0CFi5kpnWtG7NttUBkeNq1Z49e8IkhvGpD3gi5uvevbvTtrS0NEpzJTYmojlz5tD27ds9OY2OGkStq1aJmPoyNJSJtP/+W978999/y+L66dOnuxS7b9q0SS73/fffuzxNeXk5zZ49m7Zt28Y2HDrkEL0L4T/uuece6sFF7H5+VQq1UVxcTOHh4QSAfvvtN+rRowcBIKuPD6v34EFWsKTEEa7i5ElHBQcOONSap08Txcc7VEV19T7ExrJz/vSTcjtXuZpMTHUnqcb/uOkmkiLD0UcAPfDAA851ZmXJ6oviK68kAmgUQGPHjmX7k5LY/meeISKHusX63Xds+w03OOp6/HG2LSnJoSK//37ta/nzT7a/eXMi6RncKPWramHxYlavwcBCtbhCdrZDbVOZastqdbwPUp3nzp2T+/hprvZ55BFW5umnySqFWvjn2Wdp+vTpFBUVRQDol19+IXrpJacQHrt27SIAFBgYSE0kVfPy5cvZ8+nbl6kgtXD0qCMEjc2mXWbePOdnJeHff/+lOKm/HzYa6W/hfedwUrFNn87qGz264vvGQ+WEhrJ7uHy5I3QOVzdHRmqrUN9/n20fOtR1/TYb0V13sXKBgURbt1bcHiLHvX/sMddl5s5lZdq0YaYX3bszFTnAVNA1ibIyotmzHeYsAFFEBNHEiUTp6R5VtXPnTvLy8iIAlJKSQkREPXv2JAD0MQ/t4lHTqqBa3bXLoUoXTQo47r/fOSyJiKIiR3ifl14iGjWK/X77bY/b7ykefvhhAkCTJ0+utXPUimpVTJPDcfjwYfR3JTYGMGbMmLoX1eqoW5jNbAUNKLxX3333Xfn3H65SEgH49ddf5d8TJkxAoQuPyalTp2Ls2LEYMmQIiouLHSL52Fi2GgNw4sQJ/PTTT9gC4D+AqSPUBtNuICUlBdnZ2WjRogWGDBmC6667DiEAvPjqNyqKffv4MFUHoJQG8PvQrx9b+S9axAII5+Ux6WFtp8kqLGReqICzRK5VK6YqtNmY9ODkSaBlS8wsKQEPA9sMwFdffYWUlBTlsZI0xx4RgV8lNfOQZs3wAc9NqQo9IoP/F9N0aUnkXORjVYS6eOQRAMDLqGYYkoICploDmIRDfZ9EhIUxRxqx3QLWrVuHJ554AqdPn2YShtxcJiGWjKBXr14NAOjUqRNz3ABYdgwA+O03eElhXK558klMmDABt912GwAw9aqGRI6rVbt3745bpHp+//13ZkC/Zg0Lm6EFLtmMjnZ4UKrBJXLbtjlJ2J944gl0ldTZm+129O/fH9988412PRzuSuR4OJaBA1kIkJtuYrlPs7KYmcDZs8xpAnCoujkkyTj9959raVJSErs/Xl7M7KGiQMYc7kjkpHe5+KabmAZgyxbmXZuVxaRoNQmzmfXZQ4dYWJPoaBYKZvp01tbBg90y4SgvL8cjjzyC8vJyDB06FMOHDwfAzKeAOlSv8jG8Vy9lcGqOykKQvPMO82KOjgYmT3Z4l1cgkSstLcZao7UAAE7hSURBVEVycjJmzZqF7du3o7yKmSMajKMD4JlETgszZsyotEy1V801gOTkZJo4cSIlJydTYmKivAKprTpqq6ynqBOJHBHRzz+zlVDr1kR2O2VkZJDRaJSlECaTib755hvN1dpVV10lG7YDoJdeesmpzJYtW+T9AOj9998neuIJJwP0SZMmyWVe4ivWuDjNJp87d47mzZtHBRoSu+uuu44A0BtvvEFERD/88AN14vVZLMrCPEDpJ584tnGHgE8/dWzLyyPq1s2ltKNG8ddf7DzNmmnvHz9e4dxQ+uWXZDab6Rbp/3FJyhMaGkrHjh1zHLdkCRFAGcHBNI5L5uLjHfsHDGB1fvklEQmrdB48OjDQUVYy+Kd//nE4W3TurN1ebhD9+ONEmZlk9/IiAqivjw8VFxdX7R6NHeuQpKgcCTRx002s/FdfyZvsdjt9+OGHct98/PHHiV5+mZUbNUou99RTTzn2cxQUOIzhAaKwMNng/fvvvycATAvCJahms2yYP27cOAJA48ePl50oWrduTXYe4NZoZI4tavz4I9vfp4/r6ywvlx1LaPduefN3331HAOgnyaj8myuvlN+1F198kWyShM9JMrNvn+PZaxn0c3Ttysp9/bVjG5fIPPOMo0/HxDgfe+QIEUDlJhN5AfT5558r97/7ruM+i/UL2LFjB/3222/KjWvXsmNatnTZ7PM330wE0BPS83rxxRdp9erVVFZWRhcuXKC1a9fS+++/T/fddx/16NHDM8eUymC1suDN/L3jz37jxgoPmz59OgGgkJAQOiloEo4cOUIAyGAw0IkTJzxqSpUkcg884JCmSfjyyy/p8ccfp9LSUqI//mD7r7rK+dhjxxyObd99x7Z99FGlktnXX39d7rcAyM/Pj/r06UMTJkyo/Jr/+YfokUeo4N9/ZQeRU1pB0WsI7s7f1SZyj1UkcpbgDtmrTSQmJlKyKkJ3XFwczZ49u1bqqK2yVUGdEbnCQoc35Nq1skfdwIEDZaL23HPPOb3khw4dkoneF198QQDI29ubDgkec0VFRdSxY0cCQM2aNSMAFBUVRTZOiiTV4YULFyg0NJQA0NChQ6mVNLDZDQai48edmnzTTTcRAOrUqRMd5KpSItq+fbtMLPlLmpmZSXFSfbaOHZUVcVL09NPs//HjDnWdqG4lYt5vAJGvr7YqoSrQmhy5N60rz86VKx0Df/futGrlSgJA8Y0asXsWGSmrk/v37082m43WrFlDsyWPx8UA9ZPIFLVo4aj36qvZtqVLiUgY3NWqybw8x/+8POZBC7jOnnDffWz/tGnskh98kAigXwFauXKl5/eMe8wCRKtWuXfMuHGsvJRxoLi4mB544AHFpGCxWMjGCYkwYfN3wGmRxlXugMITk0eMNxqNlJ+X51DVSmYF/Nn89NNPdOHCBfLx8SEAVCY9PwKY1zSx/ty1a1d6/PHHqYBnWrjrroqv9cYbWbkvviAiory8PGrSpAkFAVQkvee2Zcto8uTJ8rXfdttttGnTJiotLVVO6KWl2uYHIsR35swZKikpIbvdTvTrrw6VOlef3n678/E2G9mlSb0dQJGRkVTIyfmCBY57IvUfNS5cuCCbUqwS+8Pp0452ucjecjIkhAigOKEfACB/f3/FYlZc1FZkjqSF9PR0mjt3LpVUlEHm0CEHodNQY9tsNvrjjz8oPj5ebosT4SXHIva9997zqI0ikSspKaE//viDkTFXmDeP3VeAqdGJ6Pz58+Tn50cA6Mcff1QuYtQEkWeD6N3bMQb+9ps8pmmhqKiIGjVqRAAoNjaWgoODFc/m7rvvrvgiBw4kAii/fXsyA9RCHPtqAXVG5KZPn06TXKVSIaKFCxdSUlJSdU9TZWzdupW0BI+utle3jtoqW1XUGZEjkidbW4sW1CIggADQ0qVL6cUXXyQA1Lt3byci9/bbbxMA6tevH9ntdnmQueOOO+QynBRGRkbSiRMnqHnz5uQHkI1PDkePEhHRJ598QgAoJiaG8vLyyM/Pj9bwAVy1mFi7dq3TBLxs2TIiYuQaAI0SJCp2u52ekQbs7J49ldfNbWT4RMxXhddd53SLMg8domLeJg9tWjTx9ttE4eGOdEUcXEr47rtExAbxcpE4lpYyCRBA9Ndf8ir10TvukCeu/3btkt3ruc0Wl3IuCg+nVJ7qCSDKzWX1Nm6sIBGKVTq3Gzp4kK1sASaVI1LY3mmGjOHEgq+89+8nmzQJfPDoo57ft3feIQLo0BVX0JQpU2jy5Mn0/PPP0zPPPEO///47IxFqfPABa8Mdd9DRo0dlMmU0GmnGjBnUsmVLiuTXAMghELKysuR+dvbsWWWdnJxAKZUgIoqJiSEAtGTJEqL+/VkZaTI3m80EgNKlPjR48GBqLZ4bIPr2WyovL6fY2Fj5/B+bzUQAlT33XMX354UXWB3jxhER0TPPPEMA6O3wcLb9iivkhchXX30ltwcAde7cmR599FGHLSARk3pWRJqld8jeqxe9++675OvrS3feeSdZCwoc/YbbfL74omYVpyW7sduldsyYMYP1K97Pn3jCpUTwo48+kts/YsQIxw4h7I1WCJJTR49SmXS/F8+aRV999RXdfffdFBERIdfXpEkTuvXWW2nKlCk0bNgw4pLuQxWFdxGwadMmCgsLIwD0xBNPVFx4+3bWVpOJSayIzQHvv/8+tW3bVm6T0Wikxx57TLOfv/feewSArtMYvyqC+K4PHz6cADgJKWSIJG7cOPm5/Pjjj3Ibhw0bxuwaudRNvP+ff+4g2JKto81mo/ceeqjCBSGfI1q2bElWq5VsNhvt3buXkpOT5XnApUTRbnf0JYDeVveVWkCdETkiotjYWAoLC6Nx48bRjBkzaMaMGfTYY49R27Zt6z2GXGJiIsXGxmru01whV7OO2ipbVdQpkcvJkQfs5QB17tiR7HY7/fPPP8RF2Op8dH379iVZVUpEe/fuldVUS5cupRUrVsgv9h9//EFE7GW8QXqZ7FFRRHY72Ww2ateuHQGgDz74gIiY00Min9S6dFGcd/DgwQSAhg8fTtdee608uL3++usUIJHQVapJ5zvJuH+nerWnVr/wSVdDEj1x4kTaIbUpn5OSqmLnTuZMwa9x/Hg28NntjNwBdHTBAnrxxRcpKiqKQkND6fDhw47jt24lksgrJ9AfffihQ92XmUmzZs2S77+/vz+t6NiR7Xv5ZVYHz7f5999MzaPKqaogcnwy//tvh0H9zTezemw2x7VoSE8pJobtW7NG3pTRqxfra2FhHt+6czfcQATQeCilJfzTu3dvWrt2rfKg1FRG5Bs1klf14eHhsnRlypQpdD9/FkIfmT9/vkxwnMAddgCnWIMPPvggAZIx9YQJrMzjj9PmzZvlc/OJ+JNPPnGcm38mT6ZPP/2UuAqte/futEDa95LFQvPmzVOSexFcBdujB+3YsYOMRiMFAlTK46p9842i+NatW+mee+6RJYMAyMfHh+677z7asWMH0eDB7DhXMcqGDSMC6Lv27RXP4emnn3bkQ+WfH35wOrykpIR+liSFn0mEJTw8nMq48XuXLi5jSpaXl1ObNm3kc3p5eSlVbFzyr1a7EtHMxEQigIqNRrIL99Jms9GePXucVHXFxcXUq1cv4pqAysblVatWUWBgoNw2g8Hg3C/VkEwADo8eTffee6+8GONEZfz48cpxQIUTJ07IasMjR45UfC4B/F3/6aef5PPddNNNzgXVJE5wuuFEFwD5+voys5cePVjZBQtYob/+cowVQr7i5cuXk0XsJypzCavVKi+O+BzBUV5eLpPvv/76S/sC+bvKBQgALXroIbfvT1VQp0SOiE1QoaGhZDAY5E99SuI4YmJiKMGF55DFYnEr+bYnddRW2aqiTokcEVm3b6cL0ku6Y+BAImKDWmRkJMnSBQlnz56VVQ+ZmZnydi6Ba9++PTVv3pwAZZL0kpISejM4mElUunYlIqLff/9dnrDOS16FS5cuJQtAJfzF3rWLiBwST6PRSAcPHqSSkhJ65JFHFBNIp06dnFar26+7jgigH6+4QnnR5845Bo9jxxyBKVUr7tLSUmrcuDH9IJXdOHx41W90eTlRz57sPO3aOc6fkEBlmzcTAVRiNJJZRVBe1JBmWK1WebLYuXOnIum93W6nWbNm0aeffkp5eXlEd97J9nEJoJjAXAxeK01qCiLXpw/bP3++w7tVtBmLjmbb1IFjbTYFueQ4LXk12gD67e23taVoWrDZqNDXlwigUTEx9Nhjj9EzzzxDEydOpLFjx5Kvr698v26//XbaunUr/fDDD3SvZAtVDpA3QF27dlVMiJmZmfKzzXnySXn7448/TgDoqaee0m5PfDwLaJuTo9j85ZdfyqSSfviBXf+118pShYHS+0XEbJvmSOe2SWrYkoEDZVODDz74gGw2G52TCPEd0vW1b9+e5s2b5yyFSE9nCyWzmW6UFjrfXXWVQxrnIkBrTk4Ovffee9SqVStFv1soEX77Cy84H1RaSlZJ6tIDzLRi7Nix8rHLH35YSeQEuz2OL774gl6W9lvvvZeuuOIK2RSCDIYKbcYWLVokkxzutTllyhRHAU4k33lHcVxBQQGNlqSFua1auaxfjRMnTsgS7ltvvdUlmf7zzz/lvtivXz+6++67CQB17NjRpYr16NGj9I0UrDkbID/pHnbo0IE++eQTeWysDHyB7YlZVFlZGX377bfUtGlTBRlTtLUCEldQUCBfr8ViIUCKYsDt6F57jUUD4GYGo0YpJKxPPPEEm+uk514qjfccXNoXHh6umeCem0k8//zz2hcovYP2Xr1oltRfy4KCmH1mLaHOiRxHRkYGZWRk1HS1VYaaBIiIiYlxKRGrah21VbaqqGsil5KSQiPEQVeyX3vooYdIrRrgE1UXlbQsNzdXlngAoDZt2jgNQOmSLdb/hYRQSUkJ3XzzzQQw428Oq9VKTZo0oYW8LRMnEhHJYv+7BDshbrRuMpk0V2xERNkSEZkQGOhMGiIi2DmefZZ9a0hfUlJSCAC9IrVnWXS0ezdVC++9x84THMwI1LffMjsSgM5L4TnWgK3gBw0aJJPj5s2by0bpHFzCY7FY2D5JWuUUtoSISJKC0aJF7P/kyez/2LFMwgc41KWkInI8G8AHHxBxFe6HHzrqlkJwOEk+eJYEg8FJqvKPZBP2CZgt33///Vf5vZPUT/kA/fjtt067jx8/TmPGjNG0b8qTnt0PL71ERTxbBofVSvmSpGDOgw/Km7l9588//6zdnvJyTWKUnp5OAMhsNlMRzxLi40OP3XsvAaCXuVSUl5ee+7+DBhEBlBUURADo6quvJiuvX3IwmffUU/JkyVVNH3/8MRUVFVFeXh6tW7uWiiWS0gOgSH9/KucTqAtnAY6ysjJatGgRrVu3jkaPHk0mk0l2jFkZHEwvv/wyTZkyhd544w2aOnUqfSz1izMAtWvTRg4v9Oabb7J+aTSSTerb5OXllInBZrNRx44dKYG/59deSz99+SUdkv4XV7Ig7tOnDwGgSZMm0Q8//EAAqGnTpg5yyx1tJDUzx7vvvksvcPLsoYpt06ZNsvRSK3zF/PnzZc3ErbfeSsXFxZSdnS0viP8nSKI41q1bR6GhoWQEKF1q17d9+9KGDRvcX+RI+PjjjwmAk0atvLycNm7cqEmEysrKZMn+FVdcQY0bNyYAtIZL0X/6ySWJI3I4+LRr145eeuklAiQTGx6+Jj6eLSIA5kwmvH92u11e9O/m1y6ET7Lb7dStWzdnki5gwYIFcts18fzzRAAVPPAAmQHaxPvbdddVO4OQK9QbkWtIyM3NrZAsxcbGUoyWB1QV66itsp6gpKSE8vPz5Q83mj537hyVlZXV+ocbyq6SjOLtAQFUtm2brF5q0aIFlZaWUllZGd1+++3yhKSuZ/bs2cSlZtwDTP6UlpJNssW6XrqHADMiPnTokKLsc889R0OlF84eHU07t2+X1Qbbtm1zOu+6devo/fffp+LiYqd95ZKK5TaA9u3bp9wnXW+xJHYv17gmPshNl8jQRoDOnDnj+X0+dIjs0iRb/tFH8nZrairZLRaZRK/q1YvS09OprKyMCgoK5Il76dKlivpmzJhBAGjIkCFUVlZGtpEjWd3Tpzud296sGZN6rFvHzimlVLJdey1ZJcN0e9eucvnCwkL65ZdfqLCwkMqluHHlEyeSXZIiWpcskcvahgxh2z79VHFO6/r1rN6oKKf2FEpetEUANZJIz6RJkygvL8/l/cuSYoMtruT+79q1i+68806Z6EyePJkKpQWE9fvvncpbV6+WJSEtoqOpuLiYjh49Slwldvr0aY+ec2lpKUVHRxMAWr5sGdkl1fQEyeFnwYIFjvJcGgrQU4IHoz+YM0hZWRmVXbjAHH8AKjt+nLKzs+mtt96SyQEA2dAcAC2R6hgH0CqJHNrbtqWyoqIK2y0+87KyMjpw4AB9KBH3fSpiDICm8/7asqVinCotLZWlUEskgmzv1MnpfFyidq30TtgtFrJKDkhHAXr1+eddtnXdunUyWc7MzKQLFy7I9+OHH35gz1VKC2aLi1NcY4sWLWQpaPmLL3r8Hs+bN0++B61bt6ZWrVpRy5YtqUWLFvIiYuTIkfJ9LCsrk8mO2WxWjF8///yz/Oy6detGW+69l92LDh2oTBpvPfkcO3ZMbsO+ffto3759NGnSJLk/xsTE0Nq1axXHLFmyRL6eFStWyAvmKVOmUNnJk2SXFgLliYlUVlLidE4+H0yaNEnWmnh7e1P+998rJLL2Fi2o7NgxxbEbN24kgJl/HJEkx4kmE+3evVvRNn9/fzp16pTmNZ87d0629dyzZ4/Tfpu0kN/w2GNsvOzYkeyS3XT5Cy94fI/d+fD4k5UROS/UAHbs2IGJEydi69atSE5OxqOPPgoAeOyxxzBy5EjcfPPNNXEaHW5g6tSpeO2115y2L1++HP5CEvPqori4GOXl5TBIaWUMBgMyMzOxYcMGeHl54fAjj6BjcTEa79yJ0iFDYExOhre3N44ePYpPP/0UTZs2xVIpintYWBgW8ywDEho1aoT7778fjRs3Rm5urmK//5kziM/KQrnRiK12O9ZLya+vu+467NmzB3t49HcALVq0wMcAcgGEnjiBrx56CESEXr164ejRoziqEW+oZcuWitRcHAMzM2ECcALArFmzWHYCCZZz53AjAF8pxtaa8HAUCG0+c+YMUqV0YS0HDwY2bUIHAC+//jr6S+mZ3AIRrnnzTTQpLER2x45YGxXlyNAA4Nhdd+HWTz9FKwBeQ4Zg9+7d2M1jlF1zDZYtW4Zp06ahpKREPmahlEosIiICixcvRqeyMrQDcHjtWvzLY4ABgN2O206dggHAir17UXL2LILy8nAzANvOndizfDm6AcgyGvGP6nmmpqaiXX4+OgE4uXEjotPTWT0nT6JEKtvFakUrAAfXrMEBHlcOQNMNG9ALQG5QEP5W1Qsi9G3XDqEHD+KNpk0x9tQpTJs2DT/++CNmzJgBs9nsdAtbfPcdGgHY17gxyirJtPHggw/irrvugtlshtFoxLmNG9ECwMHff8cB1fvU4bvv0B7ASi8vHD1xAtOmTcMFKa1Yy5Yt8Q+PmeUBYmJicOLECXzx5Zdo2a0brkhPR+/jxzEDQEFBgfxeNNm4EdcA2ANg7t9/438mEyJsNtzbrZtczu/MGQwggs1sxuLNmwGDAZ06dcIHH3yAFStWYNGiRTh79iwAIDw8HMfNZuD0aYzr0AFXrFsHANh+yy04tny5W21PFdLjXXHrrcCvv6KtwYBbBgxAOQC73Q673Y4RGzYARUXwT0jA2rVrFXXceeed2Lp1K+bu349BAPZHR2O/qg+89NJLAIAW/fuDfv8dhrw8mN55BwDwBIDUTz5BTJcuCBETskuYKcXb69OnD3bs2AEA6Nu3L1JSUvDmm2/Cz88PYWfP4gYAxbt2IU069+rVq3H06FFcaTIBNht2FBfjuLpvVgKLxYIRI0YgJSUFhw8fdtofHx+PUaNGKe6jn58fevXqhU2bNmH06NGYOnUqVq1ahY8//hh2ux3du3fHhAkTcNpuh3XhQpj/+w+b33oLZ93JwKHCVVddhV27dqFv375yv+DIyMhA3759cdddd2HYsGEoLy/Hs88+CwAYOHAgzp8/L6f8WrRoER5Ytw6tcnOR36oVVg8cCOIZPCQUFRVhiZQNpUmTJjh69CiaNWuG48eP473UVPxPKlfu64s1zz+P81u3Ko7/UYrX17lzZ9hCQoA9exBls2H06NF4/fXX5TmxX79+cvw3LXTq1Ak7d+7EzJkzcSfPLAIANhtu2bIFRgDfSfEQ7S1bYvNtt6HX9Okwvf02Nvn7I8udlHUewO30lh6LfFTYtm0bhYaG0ogRI2jOnDn0mSqi+IIFC+o1swMqkHrFxMS4JfXypI7aKusu6koiN3ToUKeVNf/ce++9rNypU2SX7J5KPv9c9vJ77bXXaOHChU4SOnc/1q++Yqug7t0V9hjqFSL/XHXVVfSptJpbKJVdv369dt1ffEG2wYOpTL1qKyqSpRmRYJkM+L4jR47Qi0I8sAyDgY5kZiqO5/Ht4uLiqOzCBSqX6rqvXz+3r3vBggX0jJQc3G42U9nOnU5lxo0bR8EAvXX77U771qxZI69Ks7OzqayMST24GptLPsvffptJIBISlHXwEBEAlXEpQVER2aVrt0keY7YHH5SPEaUz1jlzWNtbtmTfQUEKaUG5pMIqF+5tWVkZlc+cyeodPlz7mUlZI+zh4fTzt9/KdmE//vijc/mSEsqX1HRfPvaYx/2+/K23ZFWaep9dkth+3b8/AcyRZsyYMQQwo/2qvGdcxdWvXz8q27KFvUsAtW/SRNmu555jKlPJxihNek7nZs503Ccp5Iy9TRvNc124cIG2bt1KWVlZrPzChUpJiBvSOPUzF++7XbJLLNu717lNJhOVuZCOHjt2jFq0aEGdAWobFUWff/45lUgSHZ49hkvU7NwpBiDbnXdS165dCWB2T+p6Dx48KJtSbN68Wd6enp4uS6O2b99OZVI2DLvRSGXnz1NpaSl16dKFANB5SQpo3bChSs+3rKyMdu/eTX///TetXbuW1q1bR+vXr9eUCPHP4cOH5bAZ3KQEAN13332Ke17+1FPsPgwaVKV2cUcZgEmUBwwYQN9//z0dP36cRo4cKe+7oU8fmij9DwsLo5MnT1JZWRlt27aNANCNPBsOQNZVqzTPxaWTV1xxhTwfvPzyywSAbh0yhOzR0WQ3Gsn666+ax/PnPHfuXCr/v/8jAugb6dnymIsmk4kOHDhQ4TW/++67BID69u2r3Ldtm6xh6tu7t3yusrIyKh83juxhYWT97bcq9wFXH3clctUmciNHjlTYxKmJHFH9xpGriCxZLJZq28ip66itslVFbdnIcbG5+mOxWOjff/91FJSCo9ruuEM2+u7Vq5ec3sSlAXhFkAYoevpp+uCDDwgA9akgwOmMGTPkYL42gB525VZ/5ozD1X3mTOW+Y8fY8SYTGcAM3Tnuv/9+OZAuATRDGlQ5rFarTDi5J3KJNOEMNpmYE0ElSE9PpxaBgXSan+fVV53K2O122cj8119/1dx/xRVXEAD6QooPtm/fPgKYUbIc84mHFendW1kBD23QuLFyO4+b1rw5+xYcKsrKBBs5ng6Lf9RhXD75hG2/807ldsk2hbQM5YmYfRl30PjkEzm2megMwFG8cSOzcwFolzspmtT4/Xd2nquvVm7ndnwA7ZE8rc1msxz3UOt5uIO9e/cSwFSepSUllC2ZFLzbrZuyoBSAejb3Auf3WLxnPE3ajTe6d/KTJ5XPy81AtopnLqJzZ1bPn3+y/zt2EEmqKTF4shZ2795NLVu2lMeZbt260cqVK2Uvx4e496CknqfgYKLjx+mPP/6Q79/KlSsVtmLPP/88Acy2Ug2+UH2ChyzhIUj27aPU1FQCQE153EyAqI5skDlEb3IAlJSU5GwHd+iQwyZt3z6Pz1FcXEzPPfcc/d///Z+T96rdbqevvvqKIgMCZAefPwB6dcIE+bnbbDZqFBZGW/k9EuxG1eBq1VdeeUXetmfPHgIk9eqOHZpOLkSOIMZGo5GysrKYvTBAR4RwKwDonnvuqfSaMzIyZNKXIzofffEFI3I33CB7Ae/l4VCKi+VQLzWNOrORU3umNjQiZ7FYXHqGVkSkqlpHbZWtKmqLyJWXl1NZGZPolJSUUElJCRUXFzt7YEmTv93Xl76WvO0A5l0KwOPAmETkcEf/4Qey2+20cOHCCqNrnzhxgoxGI/0sDSinNCZ4IiKSpBoEOMJicEhxz6ySt5nRaKSCggI5tEobYcLrDYeEkIjkyPuNGjVykCUp3MIzAH1difG41Wqlh6+8kv6T6v8XoMz9+53K/fvvvwSwsA9axshEDgPyG6XJfM6cOYr/RES0YQO7FnU0e07EBBJLRI7o+/wjOIooJnVpVSt/BLJLRI7sINdco9zOvQYrClD64YesTJs2lH7gAHEpgtrxao+UzeEvX1+PDcCJyBGCwMdHGdBZkjbysCNi7DaDwUC5PM6eh7Db7XJYhHXr1tECyf7ngGiQXVgoh2P4S3IgmsJzcQ4a5CiXnMy23Xuv+w3gnsRt2rj0VFXDJZHjzi7vvsu8D3ne1N693cqsUVxcTMnJyU5BXAE4Fo+ffMK8xqXMIna7XbbbBZhj1eeff06nT5+mIMkZZPHixU7nSktLIwAUFBTEQmBIi5WC77+nG2+8kQDQTN4vBeeeuoLNZqOBAweS0Wikd1TetApwp6LExIqzalQFBw5QCXc+kD7nOnaksqwsucjsLl2IACr29WULZQ3k5+eTt7c3AaDdKrJ2pZQ95Cshm4oaPAagvJhfs0aWPHfv3l1+9jt37nTrsvg5FXm/pWDgZ+67T56/1E5jtYE6I3JqkjZHI05QRQGDaxt6HLm69Vp1gt0uxw/bNGGC7N7PpXdOg31lKCpyxBASQlFUhvj4eOopDTZ2k4lFDBdx/LicjJ0A5gEqpu7iaqZrr5W9o1JTU+Xreej++1kqsPh4GiNJG7t27Url5eU0ZMgQAkATJkxw1CcZ3M8CC3HhEqWltKpPHyqX2nXGy4u6AfTmm286FeVpdwaJk7cKR48elZ09MjIy6D5pYFJ4QPLE6l5eSs8yHvh48GBlpZLqU/7Mny/vUkzqgtSKAKK33lLW44pA8nRnCxe6vk8XLjiCdS5YQHFxcQQ4p3vbLknuflaTRXdRXu7oJ4cOsZX4ww87YktJ3oRcJQqg2pJ1LnWaOnUqDZLU0jaTiSg7mxXgqauio4nsdkpNTaUcLjkUU7Q9+STb5kmS70ceYcd4EPPQJZHj3p933MGeMcDiu3lIcrOysujJJ59UeHUqoPImPnXqFCUmJiocOThx0AozRMQIYHsppt17771Hx6+/ngig8ZK6zmg0Uhbv91qx0uoA5eXlzgGm1eB9A2CJ6bt3ZxkRpkwhEjUnWigtJXr9dRYPc+tW5cLl999laaq9SRNKf+EF2fDf3qULiyN55gyVSOr0j9TZcAR88803BLAQKepn8dprrxHAHLFcQXYi46lAMzPZ9Xp70/atWykkJKTyjA0CuBmMGNWACw9SH32UAGYiUxeoMyI3duxYFvBRgloiN2PGjHolclwMrl4Ru9pe3Tpqq2xVUe9EjoiF/QDoWJ8+NGXKFHkwdUfU7QRptUVNm3q0wtyyZQsNHDiQCjgpUEdI5+mXbriBqG1b9puH2CByRPUfNoxGjRolr+75ql2UCGZlZckeoi+++KJsb7NflKJJaq41YBI0zeezaxedF2LEHe7dm76VVMnt27d3GvR47KcPxZAeGugv2XBNmTJFVsXyrBZExFzpOTERo/NLtif0yCPKCqV4bvLn77+FqoRJvbxcEUyT1OE4eDoeb2/ls+XSJXV8OTV4jtNrrqH5UlDSpk2byqE37OXllC2d/+/qaAl4GrIhQ1iqNX49w4bJ5D8nJ0cOL/GCK5Wwm3j//fcJgCxZ2snPN3cuK/D66+y/mJYpN9fRLq6659IZMSdwZbhwwaVKyxVcEjkeBJp/2rZV9i8P8d9//9G0adPojAtJjxrZ2dmUnJxMLVq0kMcgLQ0SB7/vAOhNqc0fSe/9ggULHMR07NgqX0Otw25nklDxveMfPz/nBa0IyR5U/oSGshymPEcxJGmqlHatbPNmKuZe823byv1tK0DBAQGOEDgq3HbbbQRoh1Thph9eXl5KVaeEvLw82dNUHl/F8UuydfZE+s6z/lgsFtbmkhI5tNMIyc5bKx94baDOiFxubi6FhobSyJEj5YwOCxcupBkzZjSIzA5ERAkJCTRRiiHGERcXpynxcuVk4EkdtVW2KmgQRG7TJiKArL6+tFVIjTVfkNy4DR5TqIKkyBWC5xj19XVMIhkZ8otKq1c7bPDGjHEcxwPYPvWUnMKGf+SVoABuu8c/ThHOJZVzjkTyFGJ8IqL162UngrMAfSipPvPz82XJwkYhyGlOTo5suF1ZHMevv/6auKpXVBMrwMnTli2ObY89xrYJdixE5CxpE/LWOk3qkrMGAc52O8XFjn180C4rc8oW4RKnT8vSsrKVK+Xr+0XKmHBo0SIigC4AVOiGXaJLjB6tvN4+fYjWr3cq9uyzz5KXlxdtroyAVgKe+5d/ZvB4bvHxrAAPN/LRR8oDuVp03Tr2n6e40shQUJNwSeSkMDIESXrogUS9JmG1Wunnn3+mTz/9tEL1WG5urmwC8qwUgLzg2msdBYYPZ9dSkWqzoaCkhKW4WrSI5ZvlixFX8e9OnXLYBV53HZPmqYngk08qYvqVlZVR6qefkr1VK0W5OCnY+EaNoMy5ubmydHTPnj2aTbn66qsJcNj1iuBBftu3b6/cIYVJon/+cfsWcYhZHlatWiXPX3kSYQwICHDYx9Uy6jSOXHp6OsXFxSmyOjSUzA4cycnJNHHiREpOTqbExESXRCk2Ntal2NTdOmqzrKdoEETObie7FNm9LCWF+vXrR+3bt3c7yrgCQ4eyF1SDPLnbFllVxyXFPD8fnxil2GRcVUVEzK4IIJo2TY5ZBLDglVqJoa1WK3Xu3Fku951aNVVUJBOURgANVRFTuxTNfCVAvVq2VBAtHlvrSSF7AB/QOlagwuC4cOGCIu1Pd60E0zxrhGik70qiY7ez3IZ88Baeq9Okzh0jvLy0g2jyFT1X+4hSOndsUqSUSXT77TRhwgQCQLfccgsREaVK7d8SHl55PRXh44/ZOTp1YqTIxWrfZrM5Bw2uAsrLy2VCAYCe4umuTCblhCtoRohITvBNs2ez/zwPbi1HEXBJ5AoK2PONiNDMW9oQ8d9//9GqVavIylWUrVs7dvJMF9x542LCzp0OqZVW/ttHH2X7evZk753VykjRW28R3XUXS+GmgvzcDx9m7wZA9OijssRNa8H71VdfEVdxu8Ibb7xBrkxG+FioFoZQ797s/FURFhBzYOPS9HLJ/nYJmFOYyxRetYB6CQicl5dHaWlpcmRuHfWPBkHkiKj86aeJALJ5YKvgBLvdIdER1HceQwpcS0FBLHUPH9D46q2oiKkdADmtF0npmeibb6i0tFQmQjz/qxZWr15NAKhx48ZUXFzsXEDyXL1RGiDOnz9PRUVF9PW8eZQtSQj7G41OK9mlS5cSwFLNcBLJbd0UdngVgGfaAEDPPvuscwFOmHkqLiIHuVPlBCUiR37ZgADFZqdJXQosSx06aDeM53JdsYL956r0Nm3cui767z+ZIJ98+21Z4nj06FFaJWXfWK+2qfIUdjuTJrpp/F8TuOWWW+TnNX36dId0jau5goOVNkxEjsT3Tz/NJDKcaJ87V6ttdUnkiJjUtAZMRuoc3IPXaGRSKLWt5MUIbk7SpYuy7+zY4ZCCV5bXVYDiuefns0VOWRnNnDlTsaDiKC8vp+uvv564mYcr7N+/nwDmSfrhhx/KatKysjLZhMUp/+xdd7H2q6MPuMK6dUTXXsts/8iRH7ldu3b0l2RX+6bRqDRBqQM0qMwOCysyUtZRq2goRM66ahURwAxiNSRYbuHgQYc0pzqSDpvNsZrmEqDbblOWueUWWQJHRETt27P/K1cSEdHKlSvpB8lrtiKsX79eaRsnQspT+j9JBThgwAAKCQmRnTLyAfpYw1OTpx7jasPy8nIKDw93qALcwKpVq2RioJk6ihvGi7lZuapu0ybn8tzjt21bxWanSZ1LP9UhRjg4Yeaps3jIDE8Myrka3NeXEiWvteeeeYaypPt6ogYl3nUF7sgCSEm9uQcqX4RoObhIIRPo5psd3rZ+fjXvvahChUTuYoXdzhYpAFssZGQ4JMUucqU2eJw96xj/uNTWbncsykaO9Kg6V8+dpwAMDg5WRDXgHvT+/v6KnMVauOeee+T+P2jQIDp16hStkML8NGrUyDlaAh8Dnn668oYfOkQUHs7KN21KdP485efny7Z3u6RxY2Md2cWJaFBEbsCAAXVxGh0aaChErqykhIq5bY+Gu3+luHDBIRHq27f6DeIEgX/U6qaPPlKei6uvXJGyqmDCBCKA1gmhKgDQe5L3V2EFnlovvPACAaBhw4bR+vXrCWAu8e5OnjabjXr16kWRkZGaRsQ0bRq73vvv5wcwVR7APHzV4IbsqhhlToO7FGyYkpO1G3b33Ww/d0aYOpX9V4cqqQjl5XI8scLQUIoE6CrpORcZDFVfSNQjeJgbg8HA3mWucuYfDS9mbttDkZEO78V27Wq9rZckkSNikiuA6I8/HOYXFagELwq8/z67jogIJinl3s7e3oysegBXz91qtcqhXrZKsRvXrl0r2/R+KYWKqQg8F7avFPA6IiJCDgPz8MMPOx/AzR9cLRg5cnOZdkB8lyTpYFxcHPkDcsQAOnHCndtQo3B3/jaiBjBz5kz07NlT89OuXTukpaXVxGl0XMwwGnHq2mvZ7wULPDu2vBwYPRrYvBkIDwc++6z67Rk5EoiJYb9HjAC6dlXuHzyYfa9bBxw7BkiplhAVVf1zc3TqBACI9fVFr169kJCQgGXLluHpdu0AAP4JCS4Pvf/++wEAf/zxB7799lsAwKBBgzRTUmnBaDRizZo1OHz4MEJDQ50LNGvGvo8fZ99nzwI2G2AwAJGRzuVHjACeew54882KT/zUU+yeSul8nMBTc50+zb6PHWPfLVpUXK8Ikwn4/nugY0f45+bid5MJ8dKuY82bA97e7tfVQNCzZ088+eSTePPNNxEcHAy0agVcc42jQJ8+zgd17Mi+z5wBtm9nv5s3r/W2XrKQ3kscPAjs389+t29ff+2pCYwbx/rJuXPAK68A48ez7c89B7RuXSOn8PLyQh+pf65evRo5OTm4++67YbPZcM899+CBBx6otA6DwYAnn3wSW7ZsQZcuXXDu3DmsXr0aAHD77bc7H8DHiyNHXFdqtbJx67//2Hj3/vts+/TpwKlTeP7553FHs2YwAWzcr8mxv4ZR7VyrkyZNwpw5c9CjRw/E8IlRQHZ2NnJycqp7Gh2XAE5efz1aL1kC/PorMHs24OVG9yMCnngC+OMPwNcX+O03QMz/WVV4eQFffAF8/DHw9tvO+2NigA4d2Es+bx7bFhwMBAZW/9wcEpHzzcjAxlOn2LbTp4EtW9hvTiY1cPXVV+Pqq6/Grl278OmnnwIAbrnlFo9O7+Pj43pndDT7PnGCfZ88yb4bN9Z+bv7+gJTfskKYzcD117ve36QJ++b3gxM5TwlISAjrK716oWduLq6WNnt5kte2AcFoNOLDDz9Ubhw1Cti4kd3Tnj2dDwoMZJPx4cMAzx2sE7mqo21b9n3oECDlVL7oiZzZDLz7LjBoEPDRR2xbo0bAiy/W6GluvPFGLFmyBKtXr8bff/+No0ePom3btvj000/lfN3u4Morr8TGjRvxyiuvYObMmQgJCUF8fLxzQU7kNHJpA2DzylNPAWlpQEAA8PvvQJcuwA8/AP/8A/zvfxj82WcY/NxzwAsvaL9fDQjVJnIZGRmVErWRI0dW9zQ6LgFkd+oEioiA4dw5YPVqoH//yg966y1gzhwmCfr++4pJgKe48Ub2cYXBgxmR+/xz9p+Tm5pChw7s+/RpIDcXCA0FpMTR6NHDQWpc4P7778f48eNBRDAYDBg0aFDNtU2UyBE5iFxtr0rVEjk+EFeFgLRtC8yfDxo0CD42GwCgxX331UAjGwjuvZe9G/36AX5+2mWuvJIRuVWr2H+dyFUdokSuvJz95u/wxYyBA4HbbmNkBgBef50tWmsQN0rj7G+//QYigtlsxo8//oigoCCP6/Lx8cH06dNx3333wcfHB/7+/s6FWrZk39nZQGEhI2siPviACRP4vMI1Mm+/DfTuzRb5zzzDtEBAgydy1Vat9nTjApOTk6t7Gh2XAMhkAt1xB/vD1aulpUBmJlO3paYCK1YAK1eyiefdd4GXX2blPvwQGDq0bhs8ZAj75uL5miZywcEOwrRvH/v+80/luSvA3XffDaORvcLXXHMNGjVqVHNt49daWAgUFDgkZHVF5NQSOU9UqyLi4mCQJIU2f394XXddNRvYgNCoEes3n3ziusxVV7Hv0lL2zfubDs8hSuQuFdUqx9tvAxYLU9c/8kiNV9+9e3cEBASAiAAA06dPR/fu3atVZ+fOnXGFK+1MSIiDjPIxhGPjRuD55yE1BBBVs9dfDwwfziSuEydeNESu2hI5d3D48GG0riF9u46LG/ahQ2H8/HPgyy8ZmTt3rvKDJk5k6tW6xg03sJVcYSH7X9NEDmDq1ePHgb17mRRu+XK23Q01adOmTTFw4EAsWbJE206kOvDzA8LCgJwc1j4ukeNEq7YgqlYLC9n5gepJkp56CoiIgCkqCqhInXwpghM5Dl0iV3VwiVxm5qWjWuVo145Jv7293TN58RBmsxk33HADli5diltvvRXPPPNMjZ/DCS1aAHv2sOsSJaezZ7Pnl5DA1KZqTJvGzH+4dgRgY3MDRrUlcomJiZg5cyYyMzNdlpk9e3Z1T6PjEgH168fIQGmpg8R5ezNbnquvBjp3ZuqgTp3Yyzd5MjB1av001scHEG2qaovIAUyysm4dcP48s0Nzc+D47LPP8M477+C5556r+baJ6tW6Vq3m5TEVFsBW1iEhVa/TYADuvhu46abqtu7iw5VXKv/rRK7qaNKE2YJyEteoETOHuFQQFFSrC5133nkHU6ZMwTfffOORXVyVoeXwUFzs0AY9/TQbG9Ro21YpOGjThi1qGzA8ot4DBw7UtIcjIiQlJcFisSAsLAwWi0Xel5eXh4yMjGo3tDqYPn06srOzER4ejvT0dMTHxyOhAo/A6tbhbtn4+HjExsZi1KhRiI2NRUZGBmbPno28vLxLl/yazcyYdO9eNmlHRzNP1Lp4sauCwYPZ6gyoHSLHPQv37nXcg8GDAaN7a6zo6OjaIXGscmDXLubwUFeqVYuFTSalpQ6nD518VB0dOrC+xMmHfi+rDoOBTfK7drH/l4o0ro7QsWNHvPrqq3V3Qi2Hh99/Z4vlli2ZLZwrvPIKc3LLz2/walXAQyK3efNml96pPVxIEOrba3Xs2LFo06aNwk4vPj4eOTk5SExMrPE6PCmbk5OD6dOnY/r06fK2uLg4pKamenSNFx1atKi6zVNdQ/QcrQ0SI0rkuFTbDfu4OoGWRK62VasGA5N8HDkCbNrEtunko+rw9WXk48AB5sVaHcmmDqaC1IncxQHu8CASue++Y9/33FPxYjk8nNkNPv44C33VwOERkYuJicFybsPjAerLa3Xbtm2YM2eObGDJkZycjO7du7tF5Dypw9PzxcTEYNSoUdi8eTNiYmIQHx+PuIs0PMIlixYtgL59mRSxW7ear59L5Lj432QCBgyo+fNUBWIIkrpSrQLORO5iIf0NFVddxYhcs2YNV/J9sYA7PAA6kWvoUEvkzp0DFi9mv++5p/LjH3kEeOght7Uj9QmPWvhZFQOx1pfX6uzZsxEbG+u0nW9b4EZgWk/q8PR8YWFhmDhxIlJSUpCcnKyTuIaK335j9lp8hVeTCA9nNnEcffow9WJDAJfIHTniCAdSF0SOS/327GHfukSueuB2cvp9rD64wwOgE7mGDjWRS0lhYWNiYx2akMpwEZA4wEMi180DiURmZiYKCgoAoN48VtPS0jTVwABgsVjcUmF6UkdNnE9HA0RISO1KhcRBxcOgvrUKLpHbvp3ZWBmNStJZW+BETor9phOQamLYMEbK9Xie1Ycukbt4wMfsY8fY+CVlwMG999Zfm2oJ1aabkydPdtqWn5+P9PR0pKamYubMmVi5cmV1T1MlZGRkIMyFt0lYWBi2cGPqGqqjqufjKtlt27ZV2h4dlyBEItdQ7OMAh0QuK4t9u8rqUNNQB0LWVavVQ9eubDJ79NH6bsnFj44d2YLG39+R4k9Hw0RUFDNVsVqB9evZx2i8KGzePEW1R+X09HSnbSEhIegvRO2fOXMmbr755uqeyiPk5eVVuN9isVRaxpM6qnK+nJwcJCUlIT4+HomJiUhLS0P37t2RkpLiUrJXGUpLS1HKg38CslTUarXCarVWqc6aAD93fbahocJ4xRUwAaCWLVHerh0beBoCIiMhZm6lpk1R7mHbqvLcDY0bKwYma5MmDeee6KgUl/S7HhoKw08/AUFBIEDvlwIa4nP3io6G4ehR2N96C0YA9v79YYuIuGiem7v3stpEzp14MKmpqRjPk/HqkMEJHEdcXBxGjRqF+Ph4TYLsDqZOnYrXXnvNafvy5cu1U5nUMXT1sjO8Q0PRo3NnHI2Lw3ExCGV9gwi3+PjAS1oYnDGZsJEbC3sIT5575LFjuFb4v3TPHtgPHKjSeXXUHy7Zd91sBkpKHIbzOhRoSM+9T0AAwgEYpXF1e6dOOH4RPbeioiK3ynlM5CZNmoSMjAzk5+cDALZs2YKBAwe6LL9lyxa3w3zUJCyVGIxXJkHztI6qnE/rvsTFxSEpKQkLFizwONYdwFTdz/P0I2ASuebNm2PAgAEIruH8eZ7AarUiNTUV8fHxMJvNlR9wueGuu2AB5OTuDQWmFi3kwLyNu3TBEA9Vv1V57obISJZjFwA1boxBd97p0Tl11C/0d/3yREN87qYff5TTH5K/P65+9VVcHRhYz61yH1yjVhk8JnLTpk0DwDwwExMTYTAYnMJtcFgsFkybNg1jxozx9DQAgDZt2ngUgy4sLAypqaluqSVzcnKqrL6sSh3uluVlUlNTq0TkfHx84KMRndtsNjeIl6uhtEOHm2jWTCZyxmbNYKzis/PouQvODYbmzfX+cpFCf9cvTzSo596qlfzTcOedMF9kmTjcvY9VVq0mJCQgNjYWkyZNwvz586taTYWoqnqRw2KxuCSCeXl5LoMYV7UOT8qOGDECGRkZ2Lp1q2b5+gyirEOHDDHJel2EHgGYU4XBABDpHqs6dOioOkRHqUvQW5WjWl6rPKBtQ8XIkSMrTA8WHx9fo3V4Unbbtm2aHq6cwPW8CNKC6LgMUB9EzmwGIiLYb91jVYcOHVVFmzbsu1EjwI35/mJFtcOPDB8+vCbaUSsYMWIEtm3b5mSflpaWBgBuBeD1pA5PyiYkJGgahfKgwfVhV6hDhxPE/LK1nZ5LBA9BokvkdOjQUVX07w+89BLw/fd1EzqpnlBjYYt//vlntGvXDiaTCSaTCe3atcPnn39eU9VXCXFxcUhISMDUqVMV25OTk5GSkuLkoNCmTRu04Qy+CnV4Unby5MkYO3asoty2bdswdepUzbbp0FEvqA+JHOCIrde5c92dU4cOHZcWTCbgjTeASzxrUo1Q1JEjRyItLQ1xcXFy/LicnByMGTMGKSkpWLp0aU2cpkpISUnB9OnTkZSUhPDwcKSnp2Ps2LGajgQWi0VT3elJHe6WtVgsSE5Oxtj/b+9+dhu37j2Af51eIOiiGUraBfcCDYV0001LyS+QodJ1AtKTB7hDpvtWrFddFY6U2RYY0vMCtpjpOhHnCcbiPMCFOAEKdFVLTAbopkB5F+5hRZGUSJGyJOv7AYRkKOrwR/0o6+jw/DFNSJIU35J99epV5jJfRDshWuTua1UH4c9/vlvr8IH/ASYiqqpyRe7y8hKyLOd2zv/yyy/x4sUL/O8OZxXv9/uF9ssbeFCmjDL7SpIE27YLl0t07375S+AXv7hrIfvJT+7vuK3Wg+7TQkRUl8q3VqfTaTwlSZbnz58XWgqLiPbQT396Nw/Ty5e7joSIiDJUbpFrtVpr91nud0ZEB+S92rrSEhFRze5liS7OibY7YrLmojNEb8s///lP/OMf/8CPP/64P5NF0tYx78eHOT9OzHv9xPd23qILQuWKXBRFePnyJT7//PPM51+8eLE2CNqed+/eAQD+h9M4EBERHZx3797h0aNHuc+fRDXUsrrdLlqtFnRdj0d9BkGAq6srhGGI//v3Ej90//71r3/hb3/7G372s58Vaj3dFrHm61//+tedrvlK94t5Pz7M+XFi3usXRRHevXuHDz/8EO+t6OJSy/QjNzc3ME0zNYmtpmm4vLys4xC0offeew//vTgX2I598MEH/JAfIeb9+DDnx4l5r9eqljihtqmObduGbdvwfR/z+RzdbrdQAERERES0mdrXrOBktkRERET340Ev0UX74/3338cf//hHvP/++7sOhe4R8358mPPjxLzvTi2DHRaX6BKDHWazGVzXxaeffrrTJbqIiIiIHqqjWKKLiIiI6CHiEl1EREREB6pyRY5LdBERERHtRuWKHJfoIiIiItqNyhU5sURXHi7RRURERLQdXKKLiIiI6EDVUpEDANM0U8txiSW6uMIDERERUf1qq8gJb968wWw24xJdRERERFtWe0Uuy8uXL/H5559v+zBERERER6W2JbpWsW37Pg5DREREdFQqr+wAAM+ePYsHNmQJgqCOw1ANwjDE06dP8eTJE2ialrvfcDjE7e0tWq0WptMper1e7v5iX1F+p9OBYRiJfXzfx8XFBQaDAWRZLhyv4ziYTqfxv9vtdqrssvEeo0PKe5FyN4n3GO0q71X2LRMD8552KDkPwxAXFxcIwxBBEGA2m+H8/Jw530RUkWVZUaPRiHq9XmSaZuqhaVrUbDarHoYq0jQtMgwjMgwjAhCNRqPcfQ3DiAaDQWKbqqqRbduZ+06n08Q227YjwzAS20ajUQRg5WOx/Pl8njrmZDKJZFmOJpPJxvEem0PLe9Fyy8Z7bHad9032LRMD8552SDmfz+eRYRjRfD6Pt00mkwhApGlapXiPUeWKnK7rtexD92M6na78kIsPU5Ht4/E46vf7meUoipL4kA4Gg0hV1fgPzeJD07RIUZTE68UfpeXjSZKU+ENRJt5jdgh5L1Mu817MrvK+rVwy7+sdQs77/X7i38JgMIgAROPxeKN4j1XlPnKnp6dr9xkMBlUPQ/fEtm0oipLaLra5rhtv830/97a5LMuJ525vbzEej2HbdurRbDbx6tWrRLmu68KyrESZqqpiPp8nbtGViZfy7Uvei5bLvNdjW3nfVi6Z9+r2Ieeu66LT6aT2U1UVADAajTaK91jdy2CHt2/f3sdhqAae5+X2ZZIkCePxOP63LMtwXReO46T29X0/8eHr9XqZZbqui16vB0mS4m0XFxeQJKlQn6oy8VK+fch7mXKZ93psK+/byiXzXt0+5FyW5cylO8Xfg8XnmPP1KlfkDMPAs2fP8P333+fuw1GrhyMIgnh1jmXNZhM3NzfxvzVNgyzLME0TvV4PYRgiDEPoup74RQX855fW8rFev36d6rAaBAFkWUYYhhgOhxgOh7AsK/MPRJl4Kd8+5L1Mucx7PbaV923lknmvbh9yPh6PMZ/PU8f3fR9A8k4fc75e5VGrjx49wt///ne0221IkoRms5n4lS1GpND+yxt1LEiSlNpnMplA13V4nodGowFFUfDq1avENZDHsqzUBxy4+zCrqgrHcdDv9+Ptuq5jMpnEPww2iZfS9iXvRctl3uux7bzXnUvmvbp9yPkqtm1DkqR4lCtzXkzlFrkvv/wSjuPg8ePH0HUdjx8/RqfTiR+/+tWvCieRDo8kSdB1PW5d8X0fT58+Xfs613Uz+1eKD6XneakWm8FgAMdx4Hle9cCpkrrzXrVcuh9l8sNcPgz3lXPP8+B5Hi4vL1lnKKlyRW42m2E2m+G7777D8+fPU4/RaITHjx/XEStt2boPT9Yvn16vh2azidFohOl0ClVV4bou2u32yl9KlmVlzgEkYpBlOdUvQvxbtMhtEi+l7UPey5TLvNdj23mvO5fMe3X7kPM8uq7Dtu3E3wfmvJjKFbm8zsyLOGr1YZjNZokPlmmaiV9fsizHIxSDIEiNOhXE6KZVgxnyPsCSJBW+Vb8cL23mvvK+abnr4qXNVMn7LnLJvFe3q5zruo7z8/PcSYaLxnusKveRK1Ijfvv2LT766KOqh6J7IElS5mgi4C7X3W43/rfjOIgyluo1DANhGOLq6iqzHNu2V1bixECHvBg2jZfy7UPey5TLvNdjW3nfVi6Z9+r2IeeLLMvC6elpoj/0pvEeK45apYSzs7OVLV5FWmABrLx95nneyl9RqqrmfnABJD64dcV77PYh72XKZd7rcR95X7dvmRiY9+r2IeeC4zhotVqpStziDAXM+Xq1VOTG4zHa7TZarRY+/vhjnJ6exo+PP/6YE/YdEF3X4ft+quVLDDBYnE5CUZTcgQee5+HJkyeZz60aTg7c/ULLGu0shqabprlRvJRvH/JeplzmvR7byvu2csm8V7cPORfbwjDMbIlbjI05L6Dq0hBinVVd17nW6gEQy5qsWqNO07TUUiuqqqaWfJlOp5Esy6m19SaTSeZ6eVF0t8YegEhV1ZVx9vv91D6KomQuAVM03mN2CHkvWy7zvt6u8r7NXDLvqx1CzsW+hmFE/X4/6vf78dJ9WXEw56udRFHGTe0Sut3u2gn5zs7OcH19XeUwVJFlWQiCIO5wLkkSVFVFs9nMvPU9HA5xe3uLVquF6XSKXq+X2TweBEFqMEu73c7t7wAAjUYDhmGsHQTjOA7G4zGazSZmsxmePHmS20RfNN5jc2h5L1su855tH/K+zVwy72mHlPN2u73ydulkMkkty8Wc56tckXvz5g1+/etfr9yHgx2IiIiI6le5IkdEREREu1Fq+pGskak///nP4///8ccfcXFxAd/3IUkSvvjiC3z22WdVYyQiIiKiDKVGrY5GI7TbbbTbbViWlRih8ubNGzQaDQyHQ0RRhI8++gh/+tOf8Jvf/Kb2oImIiIhog1urZ2dnGAwGqT5vzWYTP/zwA7777rvEklxff/01Tk5O8Lvf/a6eiImIiIgIQMkWuWfPnmE4HKYqcd988008H8zyuqq///3v8fr16+qREhEREVFCqYrcdDpN9IkTxuMxTk5OcmdYbjQaGwVHRERERPkqr+wA/GeG5U8++STz+ZOTkzoOQ0REREQLKlfkfvjhBwRBkJq8b/H5R48eVT0MERERES0pVZF79OgR/vKXvyS2WZaFk5OTxPqXi7766qvc54iIiIpatRrAoRBrRhPVpfSo1W63i3a7DVmW4XkeJpMJer0evv3229S+L168wHg8xtXVVW0BExHR8fF9H1dXV2uX9tt3D+U8aH+UvrV6c3ODbreLyWSCRqMB27ZTlbg//OEP+PTTT/H8+XNMp1P89re/rS1gIqomDEPouo5Op4OTk5N4oJJpmom5IVexLAumacaP4XAI4G49xMVWk+Xj6LqeePR6PbiuWzhOXddhWVZmPGKfTqcDx3FKvwfLsXU6HTQajZV3HOh+hGEIy7ISlZ/l/IVhuLYcz/MS17y4lvI+E4vX2nA4hK7r8TXR6XSg63rpVkJFUdBqtdZeo0SFRUR0lObzeQQgkmW51OsURYlGo1Fi23Q6jTRNiwBE0+k09RoAkaIomTEoihIpihLN5/PcYxaJU5blVFzrFHkPDMPIjJ3uj6qqmddVFEXxdTcYDNaWY9t2JElSbj6LXA/ieJPJpFjwORRFyT0nojJqGbVKRIdHkqTEf4sYDoeQZRmapiW2y7K80a0iSZLw6tUr+L6fmoMya988lmVhPB6n4ipy/HVl27Zdqkyql2gllmU583lZlqGq6to8hWGIZrMJAPF/lxW5HsRry3xuspyfn2e2LhOVxYocERU2Ho9XfqGWrUgBd1+IkiTB9/1Ct8eWidu8eXHVQVXVrZVNq9m2vbbCY5omgiBY2TXg+vp6o+tzWzRNg+d5G13zRItYkSOiUlZ9WeZNCr6O+DIr28phWRbOz8+3Uolb7PvUbrf5hbsjnuetrUhrmgZJkg6u9VRVVfaVo8pYkSOiwnRdh+/7ME0zs2JjGEbpSpUY7FD21qxpmjg/P698iyvPYqXAMAzc3NzEAyAsy4Lv+xgOh6kBG2EYxgNALMuK37MsogO9ZVlxmeLcgLsRjuKYnU4nfl3e9qIxLL5e13WEYYjhcAjHcXIHlAiO48A0zTjmxYq94zjxgAHxPgmu6yYGEhThum7h6+ns7Ayu62Zel77vb71VtdFooN1uw7IsDIdDDIdDmKaJk5OT3Mpar9fDeDzealx0BHbdSY+Idgc5gxBWUVU1AhB3CjcMY+0gg6zjTKfTaDAYZA6eWPd6RVFyB1aUlRXbeDyO+v1+5v7inEXnelmWI03Toii6OydJkhId4bO2iXNQVTWxbTAYRIPBIC5vcd+sPKmqmvm+Fo1BVdVIVdXUQAFJkjIHD2iaFhmGkdjW7/ej8Xic2CbLcurcxL62bae25+n3+7l5WNwniu7OEUBm+YvbJEnKjE1Y95kwDCPz2ssaIJGXN2EymUT8Gqaq/mtH9UciOlDj8RiO48C2bfi+D8dx4DhOPHAhb5UX0eojvH79GkEQ4PLyMvc1WWWIaSh6vR50XcdkMql8TkEQwDRNzGYzhGEIz/PQ7/cz95VlGdfX13j79i0AYDKZxK2CpmlCVdXE+YjO+GJABoC49W0+nyfK7vf7aDQaqdYjWZYzp7mQJAmz2SyxrWgM4vWu66ZuSXa7XVxdXSXeA8dx4LpuKmbXdREEQSJm0WKXxTCMzO1ZgiDA6elpoX1lWYaiKLBtO3WMvMENq46r63rmc3mtq8v970SOp9PpypiBu+t6Wy3LdAR2XZMkot3BBi1yy0TrFf7dSpc1jUjecUajUQSgUIucLMuJ1hlxzDItPHllL8Y2n88jwzByW4KyWsHE65AzDYaY9kKQJCnV6rZY/vJzeVOgLG8vE4N4/fK2vOPlxaxpWip/Io7F3Mzn80JThCxSVXVtfhfzZNt2qrVsObZttcgttkqKlrYi55tVFlEZ7CNHRCutmyRYVVUMBoO4pefi4qJw2ZqmQVEUPH36tND+i/3oBoMBZFmORyzWRZKktf31slp4bm5uAADT6TRupRSPxdiDIEAYhlsZoFE0hnXnsiwMw9yYR6NRqjVKkqTUlCDX19elWuOAu/eqTGuaKH/xPJdbLLdlsUVS13WoqprbqruMA2moCt5aJaKVFjuKL8+uv0hVVaiqWnotSVmW4fs+giBYWbnJuvU0Go3iGfbruMW6eKxVHfKzYhEVjl6vt7NpLjaJocgtPVEZarVahWMxTTNe+UCWZUyn09K3D7NuHa+jaRqur69h2zaCIEC32y31+qrED4vF63HdrdNtTp1DDx9b5Igol+d5iS+ZdZU0RVE27uuzyWLiiqKg3+/HI0jrVHaUo+iTtq51ULyfdbQiLldyisZQloh5VX+vZaIiKSpURfu6LR+3bGuVGFHtui48zyvc/7IOnufF/UcXPwd5rdSbTrtDtIgVOSLKtfyFNJvNVs575Xkenjx5UuoYohVpsfJRplInbrFallV7Baasfr+fO5fZ4nqt/X4/d41ZcXt0Wd60Gsvbi8ZQlpjANkveNWEYRjxIYpNWymazidvb21KvUVUVsizf+5xyYr1WVVUTt5BXVUSDIGAljipjRY7oSK1r6TBNM3Mer/F4DMuyUq8fDodoNpuJL2wxAhS4+9IS/cOWjyPKFa6urkqdi7jdmzfScJ2yrT55+w8GA0iSlGoddF03EdtgMICiKKmKleM4mX3CshZnF7lZbpUrGgOAeJTusqztl5eXAJAajer7fm4/NtE6VrYyJnQ6nZV9NIMgyKz0m6YJz/NwdnaWei4Mw7W3a1ddD+K1y/uIfp6j0Six/eLiAu12O7Osm5ube7/1Sw/PSRRF0a6DIKL7E4Yhnj59mvgS1DQNzWYz/gK/ubmJv6gW/0SYphnfKrNtO95nNpvh9PQ01bk7awqKVquV2s/zvLhyI47TbDZhWRZubm4ScS6v6+r7fqKiU2TtTTGNyWLZoiVHtKos830fFxcXcUuapmmZ57x43qJP2fJ0IIv7hWGITqeDMAyhaRpM04QkSakKwXA4xOvXr+NblIqiYDQa4fr6GrIs4/z8PFGJXhVDEATxZL6LxxUtm2K7qqowTTNVbhiGaLfbkCQpfr/ztNttjEajjW5xBkGAdruNrK8pXdfjOMWgF5ELcY0vvofLy3gt5i/reli+1sT7L/KvKAq63W7cEtzr9aCqaty38vb2Fr7vw/O8zAEhIqZOp1N6EAjRIlbkiIj2SK/Xy6zIHapVA2SK6HQ6GAwGD3K923a7XarfIVEW3lolIqKtEC13VZyfnx/cGqpFuK57rwMx6OFiRY6IiGrh+37idvr19XVmP7UyNE1DGIY7H8hSN9u2K7VUEgmsyBER7ZG8AQiH4OrqKu5DFoYhms1mLaMybduuNOJ23ziOg16vx/njqBbsI0dEtAc8z4Nt24nBFOfn5wd1+y0MQ1xcXMQDLIqubFCE53kYj8cH34rl+z6urq4O/jxof7AiR0REB8H3/YOq2GZ5COdA+4UVOSIiIqIDxT5yRERERAeKFTkiIiKiA8WKHBEREdGBYkWOiIiI6ECxIkdERER0oFiRIyIiIjpQrMgRERERHShW5IiIiIgO1P8D1jdssHYTmOEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bayes_cn_hfs import CNRatioModel\n",
    "\n",
    "sun2024_ratio_12C_13C = 57.0\n",
    "\n",
    "baseline_degree = 0\n",
    "n_clouds = 1\n",
    "model = CNRatioModel(\n",
    "    data,\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N_12CN = [13.5, 1.0], # mean and width of log10 12CN total column density prior (cm-2)\n",
    "    prior_ratio_12C_13C = [75.0, 25.0], # mean and width of 12C/13C ratio prior\n",
    "    prior_log10_Tkin = [1.0, 0.5], # mean and width of log10 kinetic temperature prior (K)\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = None, # assume Gaussian line profile\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = True, # assume LTE\n",
    "    prior_log10_Tex = None, # ignored for this LTE model\n",
    "    assume_CTEX_12CN = True, # implied for this LTE model\n",
    "    prior_LTE_precision = 100.0, # ignored for this LTE model\n",
    "    assume_CTEX_13CN = True, # implied for this LTE model\n",
    "    fix_log10_Tkin = None, # do not fix the kinetic temperature\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()\n",
    "\n",
    "# Simulate with Sun et al. (2024) parameters\n",
    "# We choose values for velocity and FWHM that look good\n",
    "sim_params = {\n",
    "    \"log10_N_12CN\": [sun2024_log10_Ntot],\n",
    "    \"log10_Tkin\": [np.log10(sun2024_Tex.to(\"K\").value)],\n",
    "    \"fwhm_nonthermal\": [2.75],\n",
    "    \"velocity\": [-0.5],\n",
    "    \"fwhm_L\": 0.0,\n",
    "    \"rms_12CN-1\": 0.0,\n",
    "    \"rms_12CN-2\": 0.0,\n",
    "    \"rms_13CN-1\": 0.0,\n",
    "    \"rms_13CN-2\": 0.0,\n",
    "    \"baseline_12CN-1_norm\": [0.0],\n",
    "    \"baseline_12CN-2_norm\": [0.0],\n",
    "    \"baseline_13CN-1_norm\": [0.0],\n",
    "    \"baseline_13CN-2_norm\": [0.0],\n",
    "}\n",
    "\n",
    "# add derived quantities to sim_params\n",
    "for key in model.cloud_deterministics:\n",
    "    if key not in sim_params.keys():\n",
    "        sim_params[key] = model.model[key].eval(sim_params, on_unused_input=\"ignore\")\n",
    "\n",
    "# Evaluate and save simulated observations\n",
    "sim_obs = {key: model.model[key].eval(sim_params, on_unused_input=\"ignore\") for key in data.keys()}\n",
    "\n",
    "# Plot the simulated data\n",
    "fig, axes = plt.subplots(len(data.keys()))\n",
    "for ax, key in zip(axes, data.keys()):\n",
    "    ax.plot(data[key].spectral, data[key].brightness, \"k-\")\n",
    "    ax.plot(data[key].spectral, sim_obs[key], \"r-\")\n",
    "    ax.set_xlabel(data[key].xlabel)\n",
    "    ax.set_ylabel(data[key].ylabel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3d0df891-ca3f-4f94-bc23-b6ad2fa737bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'log10_N_12CN': [np.float64(13.663493893907637)],\n",
       " 'log10_Tkin': [np.float64(0.6374897295125107)],\n",
       " 'fwhm_nonthermal': [2.75],\n",
       " 'velocity': [-0.5],\n",
       " 'fwhm_L': 0.0,\n",
       " 'rms_12CN-1': 0.0,\n",
       " 'rms_12CN-2': 0.0,\n",
       " 'rms_13CN-1': 0.0,\n",
       " 'rms_13CN-2': 0.0,\n",
       " 'baseline_12CN-1_norm': [0.0],\n",
       " 'baseline_12CN-2_norm': [0.0],\n",
       " 'baseline_13CN-1_norm': [0.0],\n",
       " 'baseline_13CN-2_norm': [0.0],\n",
       " 'fwhm_thermal_12CN': array([0.08740951]),\n",
       " 'fwhm_thermal_13CN': array([0.08577554]),\n",
       " 'fwhm_12CN': array([2.75138882]),\n",
       " 'fwhm_13CN': array([2.75133739]),\n",
       " 'N_13CN': array([3.95063481e+11]),\n",
       " 'log10_Tex_ul': array([0.63748973]),\n",
       " 'Tex_12CN': array([[4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34]]),\n",
       " 'tau_12CN': array([[0.02095209],\n",
       "        [0.17150941],\n",
       "        [0.16750926],\n",
       "        [0.21752014],\n",
       "        [0.21834459],\n",
       "        [0.58001127],\n",
       "        [0.17227444],\n",
       "        [0.16830736],\n",
       "        [0.02105628]]),\n",
       " 'tau_total_12CN': array([1.73748484]),\n",
       " 'TR_12CN': array([[2.17718756],\n",
       "        [2.17688599],\n",
       "        [2.17650447],\n",
       "        [2.17620343],\n",
       "        [2.17190905],\n",
       "        [2.17186795],\n",
       "        [2.17174278],\n",
       "        [2.17160848],\n",
       "        [2.17144243]]),\n",
       " 'Tex_13CN': array([[4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34],\n",
       "        [4.34]]),\n",
       " 'tau_13CN': array([[2.42835648e-05],\n",
       "        [3.16703709e-05],\n",
       "        [1.23408989e-05],\n",
       "        [5.47863821e-05],\n",
       "        [3.31676646e-05],\n",
       "        [8.89079759e-05],\n",
       "        [1.02529302e-04],\n",
       "        [3.41650731e-04],\n",
       "        [6.81880498e-04],\n",
       "        [3.48554637e-04],\n",
       "        [1.04945647e-03],\n",
       "        [3.89948783e-04],\n",
       "        [4.62104220e-04],\n",
       "        [3.46448331e-04],\n",
       "        [2.97537399e-04],\n",
       "        [1.78005131e-03],\n",
       "        [1.30666953e-03],\n",
       "        [3.61300093e-04],\n",
       "        [2.65422406e-03],\n",
       "        [1.39886790e-03],\n",
       "        [6.18907003e-04],\n",
       "        [4.83459062e-04],\n",
       "        [4.96709732e-04],\n",
       "        [3.50498034e-05],\n",
       "        [6.00206687e-06],\n",
       "        [1.24841502e-04],\n",
       "        [3.23711079e-05],\n",
       "        [8.74301190e-05]]),\n",
       " 'tau_total_13CN': array([0.01365115]),\n",
       " 'TR_13CN': array([[2.25156137],\n",
       "        [2.25154682],\n",
       "        [2.25146073],\n",
       "        [2.25125198],\n",
       "        [2.2512473 ],\n",
       "        [2.25103856],\n",
       "        [2.24636192],\n",
       "        [2.24626152],\n",
       "        [2.24605331],\n",
       "        [2.24302354],\n",
       "        [2.24293752],\n",
       "        [2.2429184 ],\n",
       "        [2.24283867],\n",
       "        [2.24282725],\n",
       "        [2.24281681],\n",
       "        [2.24272441],\n",
       "        [2.24263028],\n",
       "        [2.24261098],\n",
       "        [2.24081397],\n",
       "        [2.24078178],\n",
       "        [2.24071351],\n",
       "        [2.24061319],\n",
       "        [2.24057398],\n",
       "        [2.24040509],\n",
       "        [2.2377537 ],\n",
       "        [2.23434092],\n",
       "        [2.23432968],\n",
       "        [2.23432098]])}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_params"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04ff221c-1858-4b97-b593-8289deb33172",
   "metadata": {},
   "source": [
    "## Ratio Model\n",
    "We fix the kinetic temperature at the Sun et al. (2024) model value and assume LTE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1b3fbb78-dd12-4172-a5b7-69140c3e2bc8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_cn_hfs import CNRatioModel\n",
    "\n",
    "# Initialize and define the model\n",
    "baseline_degree = 0\n",
    "n_clouds = 1\n",
    "model = CNRatioModel(\n",
    "    data,\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N_12CN = [13.5, 1.0], # mean and width of log10 12CN total column density prior (cm-2)\n",
    "    prior_ratio_12C_13C = [75.0, 25.0], # mean and width of 12C/13C ratio prior\n",
    "    prior_log10_Tkin = [1.0, 0.5], # mean and width of log10 kinetic temperature prior (K)\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = None, # assume Gaussian line profile\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = True, # assume LTE\n",
    "    prior_log10_Tex = None, # ignored for this LTE model\n",
    "    assume_CTEX_12CN = True, # implied for this LTE model\n",
    "    prior_LTE_precision = 100.0, # ignored for this LTE model\n",
    "    assume_CTEX_13CN = True, # implied for this LTE model\n",
    "    fix_log10_Tkin = np.log10(sun2024_Tex.to(\"K\").value), # fix the kinetic (excitation) temperature\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "942d0996-7f03-4d3c-b42f-0e51922ef9b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling: [12CN-1, 12CN-2, 13CN-1, 13CN-2, baseline_12CN-1_norm, baseline_12CN-2_norm, baseline_13CN-1_norm, baseline_13CN-2_norm, fwhm_nonthermal_norm, log10_N_12CN_norm, ratio_12C_13C, velocity_norm]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = model.sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(model.data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f6d627d4-553b-4dcb-a4d5-43e795a52d09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d36e75c9ba044639ad39ad56e443f3e7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Convergence achieved at 2000\n",
      "Interrupted at 1,999 [1%]: Average Loss = 731.11\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d3d4278ed64b4a84b7438dd8a1f8fb57",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runtime: 0.41 minutes\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "model.fit(\n",
    "    n = 100_000, # maximum number of VI iterations\n",
    "    draws = 1_000, # number of posterior samples\n",
    "    rel_tolerance = 0.01, # VI relative convergence threshold\n",
    "    abs_tolerance = 0.1, # VI absolute convergence threshold\n",
    "    learning_rate = 0.02, # VI learning rate\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9970ead6-1219-402b-8f0f-1823100c3da3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling: [12CN-1, 12CN-2, 13CN-1, 13CN-2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "55d372840bd7470fbe056c6c7c9e4fa6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4641d60f-f2de-4baa-80c1-7ba56d7673c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using custom advi+adapt_diag strategy\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1f38a1cc64c34896bf595d4f147be006",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Convergence achieved at 2000\n",
      "Interrupted at 1,999 [1%]: Average Loss = 731.11\n",
      "Multiprocess sampling (8 chains in 8 jobs)\n",
      "NUTS: [baseline_12CN-1_norm, baseline_12CN-2_norm, baseline_13CN-1_norm, baseline_13CN-2_norm, velocity_norm, fwhm_nonthermal_norm, log10_N_12CN_norm, ratio_12C_13C]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "82c08c0ed4c34452acd0600a7f2003b8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 8 chains for 1_000 tune and 1_000 draw iterations (8_000 + 8_000 draws total) took 17 seconds.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding log-likelihood to trace\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ac85defcba2a4f9083ebda90900ce983",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runtime: 0.82 minutes\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "init_kwargs = {\n",
    "    \"rel_tolerance\": 0.01,\n",
    "    \"abs_tolerance\": 0.1,\n",
    "    \"learning_rate\": 0.02,\n",
    "}\n",
    "model.sample(\n",
    "    init = \"advi+adapt_diag\", # initialization strategy\n",
    "    tune = 1000, # tuning samples\n",
    "    draws = 1000, # posterior samples\n",
    "    chains = 8, # number of independent chains\n",
    "    cores = 8, # number of parallel chains\n",
    "    init_kwargs = init_kwargs, # VI initialization arguments\n",
    "    nuts_kwargs = {\"target_accept\": 0.8}, # NUTS arguments\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8049a43f-9354-4f1f-924a-b0e2b6ae328b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GMM converged to unique solution\n"
     ]
    }
   ],
   "source": [
    "model.solve(kl_div_threshold=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e9fc203d-09e3-4470-99db-9df55a709d3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling: [12CN-1, 12CN-2, 13CN-1, 13CN-2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f37982c93c5345b39806f6822c3ae83d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b5e4c331-a23f-4d1c-a2d9-f3f45ac7bef8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "solutions: [0]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/twenger/miniconda3/envs/bayes_spec-dev/lib/python3.13/site-packages/arviz/stats/diagnostics.py:596: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  (between_chain_variance / within_chain_variance + num_samples - 1) / (num_samples)\n",
      "/home/twenger/miniconda3/envs/bayes_spec-dev/lib/python3.13/site-packages/arviz/stats/diagnostics.py:991: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  varsd = varvar / evar / 4\n",
      "/home/twenger/miniconda3/envs/bayes_spec-dev/lib/python3.13/site-packages/arviz/stats/diagnostics.py:596: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  (between_chain_variance / within_chain_variance + num_samples - 1) / (num_samples)\n"
     ]
    },
    {
     "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>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>velocity[0]</th>\n",
       "      <td>-4.660000e-01</td>\n",
       "      <td>9.000000e-03</td>\n",
       "      <td>-4.820000e-01</td>\n",
       "      <td>-4.500000e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>10037.0</td>\n",
       "      <td>6544.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fwhm_thermal_12CN[0]</th>\n",
       "      <td>8.700000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.700000e-02</td>\n",
       "      <td>8.700000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fwhm_thermal_13CN[0]</th>\n",
       "      <td>8.600000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.600000e-02</td>\n",
       "      <td>8.600000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fwhm_nonthermal[0]</th>\n",
       "      <td>3.263000e+00</td>\n",
       "      <td>2.000000e-02</td>\n",
       "      <td>3.227000e+00</td>\n",
       "      <td>3.301000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7629.0</td>\n",
       "      <td>6356.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fwhm_12CN[0]</th>\n",
       "      <td>3.265000e+00</td>\n",
       "      <td>2.000000e-02</td>\n",
       "      <td>3.228000e+00</td>\n",
       "      <td>3.302000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7629.0</td>\n",
       "      <td>6356.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fwhm_13CN[0]</th>\n",
       "      <td>3.265000e+00</td>\n",
       "      <td>2.000000e-02</td>\n",
       "      <td>3.228000e+00</td>\n",
       "      <td>3.302000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7629.0</td>\n",
       "      <td>6356.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log10_N_12CN[0]</th>\n",
       "      <td>1.372800e+01</td>\n",
       "      <td>2.000000e-03</td>\n",
       "      <td>1.372400e+01</td>\n",
       "      <td>1.373200e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7216.0</td>\n",
       "      <td>6121.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N_13CN[0]</th>\n",
       "      <td>6.963536e+11</td>\n",
       "      <td>1.368538e+11</td>\n",
       "      <td>4.521969e+11</td>\n",
       "      <td>9.556013e+11</td>\n",
       "      <td>1.443470e+09</td>\n",
       "      <td>1.491232e+09</td>\n",
       "      <td>8889.0</td>\n",
       "      <td>6392.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log10_Tex_ul[0]</th>\n",
       "      <td>6.370000e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.370000e-01</td>\n",
       "      <td>6.370000e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tau_total_12CN[0]</th>\n",
       "      <td>2.017000e+00</td>\n",
       "      <td>1.100000e-02</td>\n",
       "      <td>1.996000e+00</td>\n",
       "      <td>2.036000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7216.0</td>\n",
       "      <td>6121.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tau_total_13CN[0]</th>\n",
       "      <td>2.400000e-02</td>\n",
       "      <td>5.000000e-03</td>\n",
       "      <td>1.600000e-02</td>\n",
       "      <td>3.300000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8889.0</td>\n",
       "      <td>6392.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>baseline_12CN-1_norm[0]</th>\n",
       "      <td>7.000000e-03</td>\n",
       "      <td>4.100000e-02</td>\n",
       "      <td>-6.900000e-02</td>\n",
       "      <td>8.400000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8729.0</td>\n",
       "      <td>6114.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>baseline_12CN-2_norm[0]</th>\n",
       "      <td>-2.980000e-01</td>\n",
       "      <td>4.700000e-02</td>\n",
       "      <td>-3.860000e-01</td>\n",
       "      <td>-2.100000e-01</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>8960.0</td>\n",
       "      <td>5859.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>baseline_13CN-1_norm[0]</th>\n",
       "      <td>2.100000e-02</td>\n",
       "      <td>5.300000e-02</td>\n",
       "      <td>-8.200000e-02</td>\n",
       "      <td>1.170000e-01</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>10375.0</td>\n",
       "      <td>6784.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>baseline_13CN-2_norm[0]</th>\n",
       "      <td>-8.600000e-02</td>\n",
       "      <td>1.020000e-01</td>\n",
       "      <td>-2.860000e-01</td>\n",
       "      <td>9.600000e-02</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>10346.0</td>\n",
       "      <td>6116.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_12C_13C[0]</th>\n",
       "      <td>7.988900e+01</td>\n",
       "      <td>1.637600e+01</td>\n",
       "      <td>5.213900e+01</td>\n",
       "      <td>1.107800e+02</td>\n",
       "      <td>1.790000e-01</td>\n",
       "      <td>2.200000e-01</td>\n",
       "      <td>8883.0</td>\n",
       "      <td>6487.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 mean            sd        hdi_3%  \\\n",
       "velocity[0]             -4.660000e-01  9.000000e-03 -4.820000e-01   \n",
       "fwhm_thermal_12CN[0]     8.700000e-02  0.000000e+00  8.700000e-02   \n",
       "fwhm_thermal_13CN[0]     8.600000e-02  0.000000e+00  8.600000e-02   \n",
       "fwhm_nonthermal[0]       3.263000e+00  2.000000e-02  3.227000e+00   \n",
       "fwhm_12CN[0]             3.265000e+00  2.000000e-02  3.228000e+00   \n",
       "fwhm_13CN[0]             3.265000e+00  2.000000e-02  3.228000e+00   \n",
       "log10_N_12CN[0]          1.372800e+01  2.000000e-03  1.372400e+01   \n",
       "N_13CN[0]                6.963536e+11  1.368538e+11  4.521969e+11   \n",
       "log10_Tex_ul[0]          6.370000e-01  0.000000e+00  6.370000e-01   \n",
       "tau_total_12CN[0]        2.017000e+00  1.100000e-02  1.996000e+00   \n",
       "tau_total_13CN[0]        2.400000e-02  5.000000e-03  1.600000e-02   \n",
       "baseline_12CN-1_norm[0]  7.000000e-03  4.100000e-02 -6.900000e-02   \n",
       "baseline_12CN-2_norm[0] -2.980000e-01  4.700000e-02 -3.860000e-01   \n",
       "baseline_13CN-1_norm[0]  2.100000e-02  5.300000e-02 -8.200000e-02   \n",
       "baseline_13CN-2_norm[0] -8.600000e-02  1.020000e-01 -2.860000e-01   \n",
       "ratio_12C_13C[0]         7.988900e+01  1.637600e+01  5.213900e+01   \n",
       "\n",
       "                              hdi_97%     mcse_mean       mcse_sd  ess_bulk  \\\n",
       "velocity[0]             -4.500000e-01  0.000000e+00  0.000000e+00   10037.0   \n",
       "fwhm_thermal_12CN[0]     8.700000e-02  0.000000e+00           NaN    8000.0   \n",
       "fwhm_thermal_13CN[0]     8.600000e-02  0.000000e+00  0.000000e+00    8000.0   \n",
       "fwhm_nonthermal[0]       3.301000e+00  0.000000e+00  0.000000e+00    7629.0   \n",
       "fwhm_12CN[0]             3.302000e+00  0.000000e+00  0.000000e+00    7629.0   \n",
       "fwhm_13CN[0]             3.302000e+00  0.000000e+00  0.000000e+00    7629.0   \n",
       "log10_N_12CN[0]          1.373200e+01  0.000000e+00  0.000000e+00    7216.0   \n",
       "N_13CN[0]                9.556013e+11  1.443470e+09  1.491232e+09    8889.0   \n",
       "log10_Tex_ul[0]          6.370000e-01  0.000000e+00  0.000000e+00    8000.0   \n",
       "tau_total_12CN[0]        2.036000e+00  0.000000e+00  0.000000e+00    7216.0   \n",
       "tau_total_13CN[0]        3.300000e-02  0.000000e+00  0.000000e+00    8889.0   \n",
       "baseline_12CN-1_norm[0]  8.400000e-02  0.000000e+00  0.000000e+00    8729.0   \n",
       "baseline_12CN-2_norm[0] -2.100000e-01  1.000000e-03  1.000000e-03    8960.0   \n",
       "baseline_13CN-1_norm[0]  1.170000e-01  1.000000e-03  1.000000e-03   10375.0   \n",
       "baseline_13CN-2_norm[0]  9.600000e-02  1.000000e-03  1.000000e-03   10346.0   \n",
       "ratio_12C_13C[0]         1.107800e+02  1.790000e-01  2.200000e-01    8883.0   \n",
       "\n",
       "                         ess_tail  r_hat  \n",
       "velocity[0]                6544.0    1.0  \n",
       "fwhm_thermal_12CN[0]       8000.0    NaN  \n",
       "fwhm_thermal_13CN[0]       8000.0    NaN  \n",
       "fwhm_nonthermal[0]         6356.0    1.0  \n",
       "fwhm_12CN[0]               6356.0    1.0  \n",
       "fwhm_13CN[0]               6356.0    1.0  \n",
       "log10_N_12CN[0]            6121.0    1.0  \n",
       "N_13CN[0]                  6392.0    1.0  \n",
       "log10_Tex_ul[0]            8000.0    NaN  \n",
       "tau_total_12CN[0]          6121.0    1.0  \n",
       "tau_total_13CN[0]          6392.0    1.0  \n",
       "baseline_12CN-1_norm[0]    6114.0    1.0  \n",
       "baseline_12CN-2_norm[0]    5859.0    1.0  \n",
       "baseline_13CN-1_norm[0]    6784.0    1.0  \n",
       "baseline_13CN-2_norm[0]    6116.0    1.0  \n",
       "ratio_12C_13C[0]           6487.0    1.0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"solutions:\", model.solutions)\n",
    "\n",
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics\n",
    "    if not set(model.model.named_vars_to_dims[param]).intersection(set(\n",
    "        [\"transition_12CN\", \"state_12CN\", \"transition_13CN\", \"state_13CN\"]\n",
    "    ))\n",
    "]\n",
    "pm.summary(model.trace.posterior, var_names=var_names + model.hyper_deterministics + model.baseline_freeRVs + [\"ratio_12C_13C\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a62a429-6ac3-4a9f-8e1f-5a1dd310ac0b",
   "metadata": {},
   "source": [
    "We find a slightly larger $^{12}{\\rm C}/^{13}{\\rm C}$ ratio: $80 \\pm 16$ compared to Sun et al. (2024) who found $57 \\pm 17$ using the traditional HfS method and $57 \\pm 13$ using the satellite-line method."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29e2d0c0",
   "metadata": {},
   "source": [
    "## Single component LTE\n",
    "Mimic Sun et al. (2024) analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2fd81a92",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-09T03:09:00.472385Z",
     "start_time": "2024-08-09T03:09:00.457241Z"
    }
   },
   "outputs": [],
   "source": [
    "# Initialize and define the model\n",
    "baseline_degree = 0\n",
    "n_clouds = 1\n",
    "model = CNModel(\n",
    "    data_12CN,\n",
    "    molecule=\"CN\", # molecule (either \"CN\" or \"13CN\")\n",
    "    mol_data=mol_data_12CN, # molecular data\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N = [13.75, 0.25], # mean and width of log10 total column density prior (cm-2)\n",
    "    prior_log10_Tkin = [0.75, 0.25], # mean and width of log10 kinetic temperature prior (K)\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = 1.0, # width of latent Lorentzian FWHM prior (km/s) TIP: set to typical feature separation\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = True, # assume LTE\n",
    "    prior_log10_Tex = [0.75, 0.25], # ignored because LTE\n",
    "    assume_CTEX = True, # implied because LTE\n",
    "    prior_LTE_precision = 100.0, # ignored because LTE\n",
    "    fix_log10_Tkin = None, # do not fix the kinetic temperature\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc6cca70",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-09T03:13:22.617973Z",
     "start_time": "2024-08-09T03:13:19.536745Z"
    }
   },
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = model.sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(model.data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e669a5fe-715d-4afb-83fa-b971dce6e7e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.fit(\n",
    "    n = 100_000, # maximum number of VI iterations\n",
    "    draws = 1_000, # number of posterior samples\n",
    "    rel_tolerance = 0.01, # VI relative convergence threshold\n",
    "    abs_tolerance = 0.1, # VI absolute convergence threshold\n",
    "    learning_rate = 0.02, # VI learning rate\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cb31088-4388-448e-a0b0-2bff337c7cd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8ec46a4-e77f-42ad-9dde-7fadb90067a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.posterior)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f8b7d1ad-d34d-426b-af80-dcb01d79d069",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.sample(\n",
    "    init = \"advi+adapt_diag\", # initialization strategy\n",
    "    tune = 1000, # tuning samples\n",
    "    draws = 1000, # posterior samples\n",
    "    chains = 8, # number of independent chains\n",
    "    cores = 8, # number of parallel chains\n",
    "    init_kwargs = {\"rel_tolerance\": 0.01, \"abs_tolerance\": 0.1, \"learning_rate\": 0.02}, # VI initialization arguments\n",
    "    nuts_kwargs = {\"target_accept\": 0.9}, # NUTS arguments\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6215359-1c1c-418a-8abd-e6bdb5c5c71e",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.solve(kl_div_threshold=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa67868e-e58c-4387-a9ee-b2255211d956",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2009073f-8f3e-4f61-a6b7-c1ed3728aaac",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.posterior, var_names=model.cloud_deterministics + model.hyper_freeRVs + model.baseline_freeRVs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0b866af-3755-43dc-a1b3-039bd67bd92f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_pair\n",
    "\n",
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics\n",
    "    if not set(model.model.named_vars_to_dims[param]).intersection(set([\"transition\", \"state\"]))\n",
    "]\n",
    "print(var_names)\n",
    "_ = plot_pair(\n",
    "    model.trace.solution_0.sel(cloud=0), # samples\n",
    "    var_names + model.hyper_freeRVs, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    "    kind=\"kde\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97e72e84-d95a-439c-b1cc-4f27e9d5d5a4",
   "metadata": {},
   "source": [
    "We find a higher column density and optical depth, and smaller excitation temperature."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39ec64c9-afd9-4ef7-85c7-4830ae17523a",
   "metadata": {},
   "source": [
    "## Non-LTE model\n",
    "Fix the kinetic temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8944c3c2-7332-48b9-a969-8dc274fb699f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize and define the model\n",
    "baseline_degree = 0\n",
    "n_clouds = 1\n",
    "model = CNModel(\n",
    "    data_12CN,\n",
    "    molecule=\"CN\", # molecule (either \"CN\" or \"13CN\")\n",
    "    mol_data=mol_data_12CN, # molecular data\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N = [13.75, 0.15], # mean and width of log10 total column density prior (cm-2)\n",
    "    prior_log10_Tkin = [0.5, 0.15], # ignored because kinetic temperature is fixed\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = 1.0, # width of latent Lorentzian FWHM prior (km/s) TIP: set to typical feature separation\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = False, # do not assume LTE\n",
    "    prior_log10_Tex = [0.5, 0.15], # mean and width of excitation temperature prior (K)\n",
    "    assume_CTEX = False, # do not assume CTEX\n",
    "    prior_LTE_precision = 100.0, # width of LTE precision prior\n",
    "    fix_log10_Tkin = 1.5, # fix the kinetic temperature (K)\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31e4f441-a75e-4073-85f6-96e5739e9be1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = model.sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(model.data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af997715-8406-491b-b499-f64cdc85c533",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.fit(\n",
    "    n = 100_000, # maximum number of VI iterations\n",
    "    draws = 1_000, # number of posterior samples\n",
    "    rel_tolerance = 0.01, # VI relative convergence threshold\n",
    "    abs_tolerance = 0.1, # VI absolute convergence threshold\n",
    "    learning_rate = 0.02, # VI learning rate\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a66aba6-1dc8-48c1-847f-e32f4f504cd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd7f0566-335b-470b-ad5e-694661c7efe6",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.sample(\n",
    "    init = \"advi+adapt_diag\", # initialization strategy\n",
    "    tune = 1000, # tuning samples\n",
    "    draws = 1000, # posterior samples\n",
    "    chains = 8, # number of independent chains\n",
    "    cores = 8, # number of parallel chains\n",
    "    init_kwargs = {\"rel_tolerance\": 0.01, \"abs_tolerance\": 0.1, \"learning_rate\": 0.02}, # VI initialization arguments\n",
    "    nuts_kwargs = {\"target_accept\": 0.8}, # NUTS arguments\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41d727ce-dd7f-46f6-9bb2-370747c25cb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.solve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a151a8ed-b70f-4011-823f-8c5c00d6c702",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81facd00-d3e2-49c4-b969-b5f82e7312c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics\n",
    "]\n",
    "pm.summary(model.trace.posterior, var_names=var_names + model.hyper_deterministics + model.baseline_freeRVs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97001554-a106-4afa-916e-66c422aa0d5a",
   "metadata": {},
   "source": [
    "## Number of clouds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a08a3f7f-1c1d-4e34-a290-fe8fbddae0de",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec import Optimize\n",
    "from bayes_cn_hfs import CNModel\n",
    "\n",
    "max_n_clouds = 5\n",
    "baseline_degree = 0\n",
    "opt = Optimize(\n",
    "    CNModel,\n",
    "    data_12CN,\n",
    "    molecule=\"CN\", # molecule name\n",
    "    mol_data=mol_data_12CN, # molecular data\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    max_n_clouds=max_n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "opt.add_priors(\n",
    "    prior_log10_N = [13.75, 0.15], # mean and width of log10 total column density prior (cm-2)\n",
    "    prior_log10_Tkin = [0.5, 0.15], # ignored because kinetic temperature is fixed\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = 1.0, # width of latent Lorentzian FWHM prior (km/s) TIP: set to typical feature separation\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = False, # do not assume LTE\n",
    "    prior_log10_Tex = [0.5, 0.15], # mean and width of excitation temperature prior (K)\n",
    "    assume_CTEX = False, # do not assume CTEX\n",
    "    prior_LTE_precision = 100.0, # width of LTE precision prior\n",
    "    fix_log10_Tkin = 1.5, # fix the kinetic temperature (K)\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "opt.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81257083-7c50-4245-8b36-9a4e48547bc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = opt.models[1].sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(opt.models[1].data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "547d5b8f-ac3e-4526-9b97-2274b746bc83",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "fit_kwargs = {\n",
    "    \"n\": 100_000,\n",
    "    \"rel_tolerance\": 0.01,\n",
    "    \"abs_tolerance\": 0.1,\n",
    "    \"learning_rate\": 0.02,\n",
    "}\n",
    "opt.fit_all(**fit_kwargs)\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60d650da-77dc-4de1-b38e-9a6f6948afbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "null_bic = opt.models[1].null_bic()\n",
    "n_clouds = np.arange(max_n_clouds+1)\n",
    "bics_vi = np.array([null_bic] + [model.bic(chain=0) for model in opt.models.values()])\n",
    "print(bics_vi)\n",
    "\n",
    "plt.plot(n_clouds[1:], bics_vi[1:], 'ko')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "025831f6-30da-4252-b20c-d55975843b76",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "fit_kwargs = {\n",
    "    \"rel_tolerance\": 0.01,\n",
    "    \"abs_tolerance\": 0.1,\n",
    "    \"learning_rate\": 0.02,\n",
    "}\n",
    "sample_kwargs = {\n",
    "    \"chains\": 8,\n",
    "    \"cores\": 8,\n",
    "    \"n_init\": 100_000,\n",
    "    \"init_kwargs\": fit_kwargs,\n",
    "    \"nuts_kwargs\": {\"target_accept\": 0.8},\n",
    "}\n",
    "opt.optimize(fit_kwargs=fit_kwargs, sample_kwargs=sample_kwargs, approx=False)\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d9c6ae7-6712-4f4e-8716-665114046e3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "null_bic = opt.models[1].null_bic()\n",
    "n_clouds = np.arange(max_n_clouds+1)\n",
    "bics_mcmc = np.array([null_bic] + [model.bic() for model in opt.models.values()])\n",
    "print(bics_mcmc)\n",
    "\n",
    "plt.plot(n_clouds[1:], bics_vi[1:], 'ko', label=\"VI\")\n",
    "plt.plot(n_clouds[1:], bics_mcmc[1:], 'ro', label=\"MCMC\")\n",
    "plt.xlabel(\"Number of Clouds\")\n",
    "plt.ylabel(\"BIC\")\n",
    "_ = plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1192f6f-5662-4266-9a16-aff10c31699e",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = opt.best_model\n",
    "print(model.n_clouds)\n",
    "model.solve()\n",
    "\n",
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics\n",
    "]\n",
    "pm.summary(model.trace.solution_0, var_names=var_names + [\"LTE_precision\"] + model.hyper_freeRVs + model.hyper_deterministics + model.baseline_freeRVs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc8e06ea-058d-4b73-8309-7b742f31ad89",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "967eef9d-dcf9-4668-8b42-c59902159820",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_pair\n",
    "\n",
    "var_names = [\n",
    "    param for param in model.cloud_freeRVs\n",
    "]\n",
    "print(var_names)\n",
    "axes = plot_pair(\n",
    "    model.trace.solution_0, # samples\n",
    "    var_names, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    "    kind=\"kde\", # plot type\n",
    ")\n",
    "_ = axes.ravel()[0].figure.set_size_inches(12, 12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27ea78ca-f748-4281-9273-d6947008147e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics\n",
    "    if not set(model.model.named_vars_to_dims[param]).intersection(set([\"transition\", \"state\"]))\n",
    "    and param not in [\"fwhm_thermal\"]\n",
    "]\n",
    "print(var_names)\n",
    "_ = plot_pair(\n",
    "    model.trace.solution_0.sel(cloud=0), # samples\n",
    "    var_names + [\"LTE_precision\"] + model.hyper_deterministics, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    "    kind=\"kde\", # plot type\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b23d908a-acfb-466e-84d5-c4856cdfa3b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = plot_pair(\n",
    "    model.trace.solution_0.sel(cloud=1), # samples\n",
    "    var_names + [\"LTE_precision\"] + model.hyper_deterministics, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    "    kind=\"kde\", # plot type\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "384ff6c2-1ab0-450d-8364-1b4e6f2cf996",
   "metadata": {},
   "source": [
    "## Ratio Model\n",
    "We assume CTEX for 13CN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c831197-f9e5-4932-b797-0330b47bf5df",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_cn_hfs.cn_ratio_model import CNRatioModel\n",
    "\n",
    "# Initialize and define the model\n",
    "n_clouds = 2 # number of cloud components\n",
    "baseline_degree = 0 # polynomial baseline degree\n",
    "model = CNRatioModel(\n",
    "    data,\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N_12CN = [13.50, 0.25], # mean and width of log10 12CN total column density prior (cm-2)\n",
    "    prior_ratio_12C_13C = [50.0, 25.0], # mean and width of 12C/13C ratio prior\n",
    "    prior_log10_Tkin = None, # kinetic temperature is fixed\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = 1.0, # width of latent Lorentzian FWHM prior (km/s) TIP: set to typical feature separation\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = False, # do not assume LTE\n",
    "    prior_log10_Tex = [0.6, 0.15], # mean and width of excitation temperature prior (K)\n",
    "    assume_CTEX_12CN = False, # do not assume CTEX\n",
    "    prior_LTE_precision = 100.0, # width of LTE precision prior\n",
    "    assume_CTEX_13CN = True, # assume CTEX for 13CN\n",
    "    fix_log10_Tkin = 1.5, # kinetic temperature is fixed (K)\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa34a007-0697-4b00-9bb2-601b5f6e3df8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = model.sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(model.data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7742f1a1-af7c-41ad-a8dc-3f5baac99841",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.fit(\n",
    "    n = 100_000, # maximum number of VI iterations\n",
    "    draws = 1_000, # number of posterior samples\n",
    "    rel_tolerance = 0.01, # VI relative convergence threshold\n",
    "    abs_tolerance = 0.1, # VI absolute convergence threshold\n",
    "    learning_rate = 0.02, # VI learning rate\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a7242ee-8384-46d4-9376-15bfc7a0acd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4ba4c6a-1485-45fe-9333-3884bca8ea09",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.sample(\n",
    "    init = \"advi+adapt_diag\", # initialization strategy\n",
    "    tune = 1000, # tuning samples\n",
    "    draws = 1000, # posterior samples\n",
    "    chains = 8, # number of independent chains\n",
    "    cores = 8, # number of parallel chains\n",
    "    init_kwargs = {\"rel_tolerance\": 0.01, \"abs_tolerance\": 0.1, \"learning_rate\": 0.02}, # VI initialization arguments\n",
    "    nuts_kwargs = {\"target_accept\": 0.9}, # NUTS arguments\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e991426-f03b-413f-87c8-58d0430bd71c",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.solve(kl_div_threshold=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56683e0a-d9d8-48ad-ad0d-9d2bdc32c858",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "print(\"solutions:\", model.solutions)\n",
    "\n",
    "pm.summary(model.trace.solution_0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9379ab3-f22a-41f8-800d-80806c8a30a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b49af597-f760-4c69-b42b-d2dfb6413053",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 12C/13C ratio over all clouds\n",
    "for solution in model.solutions:\n",
    "    model.trace[f\"solution_{solution}\"][\"ratio_12C_13C_total\"] = (\n",
    "        (10.0**model.trace[f\"solution_{solution}\"][\"log10_N_12CN\"]).sum(dim=\"cloud\") / \n",
    "        model.trace[f\"solution_{solution}\"][\"N_13CN\"].sum(dim=\"cloud\")\n",
    "    )\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c725876-4ddc-42d7-8b0a-a6ba79e7f7c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.solution_0, var_names=[\"ratio_12C_13C_total\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90650e49-406b-4037-bbcd-b9cf63bf579b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.solution_1, var_names=[\"ratio_12C_13C_total\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5859c26d-291b-4535-9303-2a6f78a0e810",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_pair\n",
    "\n",
    "var_names = [\n",
    "    param for param in model.cloud_freeRVs\n",
    "    if not set(model.model.named_vars_to_dims[param]).intersection(set(\n",
    "        [\"transition_12CN\", \"state_12CN\", \"transition_13CN\", \"state_13CN\"]\n",
    "    ))\n",
    "]\n",
    "_ = plot_pair(\n",
    "    model.trace.solution_0, # samples\n",
    "    var_names, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb620c4d-96a6-4c8b-90d5-6bc5ab0cfbb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open(\"/staging/twenger2/wb89_380_trace.pkl\", \"wb\") as f:\n",
    "    pickle.dump(model.trace, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a6b06ce-e388-4bd0-acd6-eb5aae98de40",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ignore transition and state dependent parameters\n",
    "var_names = [\n",
    "    param for param in model.cloud_deterministics + [\"ratio_12C_13C\"]\n",
    "    if not set(model.model.named_vars_to_dims[param]).intersection(set(\n",
    "        [\"transition_12CN\", \"state_12CN\", \"transition_13CN\", \"state_13CN\"]\n",
    "    )) and param not in [\"fwhm_thermal_12CN\", \"fwhm_thermal_13CN\"]\n",
    "]\n",
    "print(var_names)\n",
    "_ = plot_pair(\n",
    "    model.trace.solution_0.sel(cloud=0), # samples\n",
    "    var_names + model.hyper_deterministics, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3441f003-0828-41a3-a518-52a696239620",
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = plot_pair(\n",
    "    model.trace.solution_0.sel(cloud=1), # samples\n",
    "    var_names + model.hyper_deterministics, # var_names to plot\n",
    "    labeller=model.labeller, # label manager\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f727cc4d-73ee-425d-96a0-7e656839593f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "var_names = model.cloud_deterministics + model.baseline_freeRVs + model.hyper_freeRVs + model.hyper_deterministics + [\"ratio_12C_13C\", \"ratio_12C_13C_total\"]\n",
    "point_stats = az.summary(model.trace.solution_0, var_names=var_names, kind='stats', hdi_prob=0.68)\n",
    "display(point_stats)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc4cb2a8-1777-421a-8f2c-ea54dbca4570",
   "metadata": {},
   "source": [
    "## Assumption about 13CN Excitation Temperature\n",
    "There is no evidence for CTEX in the 13CN data, and we are unable to constrain the excitation temperature of 13CN because we only detect the brightest transitions. Here we relax the 13CN CTEX assumption and instead assume that it suffers from hyperfine anomalies the same as 12CN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2cb3178c-8d3a-4884-840d-53aeb05c523c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_cn_hfs.cn_ratio_model import CNRatioModel\n",
    "\n",
    "# Initialize and define the model\n",
    "n_clouds = 2 # number of cloud components\n",
    "baseline_degree = 0 # polynomial baseline degree\n",
    "model = CNRatioModel(\n",
    "    data,\n",
    "    bg_temp = 2.7, # assumed background temperature (K)\n",
    "    Beff=0.78, # Main beam efficiency\n",
    "    Feff=0.94, # Forward efficiency\n",
    "    n_clouds=n_clouds,\n",
    "    baseline_degree=baseline_degree,\n",
    "    seed=1234,\n",
    "    verbose=True\n",
    ")\n",
    "model.add_priors(\n",
    "    prior_log10_N_12CN = [13.50, 0.25], # mean and width of log10 12CN total column density prior (cm-2)\n",
    "    prior_ratio_12C_13C = [50.0, 25.0], # mean and width of 12C/13C ratio prior\n",
    "    prior_log10_Tkin = None, # kinetic temperature is fixed\n",
    "    prior_velocity = [0.0, 3.0], # mean and width of velocity prior (km/s)\n",
    "    prior_fwhm_nonthermal = 1.0, # width of non-thermal broadening prior (km/s)\n",
    "    prior_fwhm_L = 1.0, # width of latent Lorentzian FWHM prior (km/s) TIP: set to typical feature separation\n",
    "    prior_rms = None, # do not infer spectral rms\n",
    "    prior_baseline_coeffs = None, # use default baseline priors\n",
    "    assume_LTE = False, # do not assume LTE\n",
    "    prior_log10_Tex = [0.6, 0.15], # mean and width of excitation temperature prior (K)\n",
    "    assume_CTEX_12CN = False, # do not assume CTEX\n",
    "    prior_LTE_precision = 100.0, # width of LTE precision prior\n",
    "    assume_CTEX_13CN = True, # assume CTEX for 13CN\n",
    "    fix_log10_Tkin = 1.5, # kinetic temperature is fixed (K)\n",
    "    ordered = False, # do not assume optically-thin\n",
    ")\n",
    "model.add_likelihood()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44f5b475-f09b-4715-9531-983d487a73c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bayes_spec.plots import plot_predictive\n",
    "\n",
    "# prior predictive check\n",
    "prior = model.sample_prior_predictive(\n",
    "    samples=100,  # prior predictive samples\n",
    ")\n",
    "_ = plot_predictive(model.data, prior.prior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddd8f634-2dcf-4815-8696-1e15129df2aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.fit(\n",
    "    n = 100_000, # maximum number of VI iterations\n",
    "    draws = 1_000, # number of posterior samples\n",
    "    rel_tolerance = 0.01, # VI relative convergence threshold\n",
    "    abs_tolerance = 0.1, # VI absolute convergence threshold\n",
    "    learning_rate = 0.01, # VI learning rate\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a7e0e64-fa14-46a8-842d-2b8da8222a63",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ce7974d-7157-4218-896e-d9b597a28859",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = time.time()\n",
    "model.sample(\n",
    "    init = \"advi+adapt_diag\", # initialization strategy\n",
    "    tune = 1000, # tuning samples\n",
    "    draws = 1000, # posterior samples\n",
    "    chains = 8, # number of independent chains\n",
    "    cores = 8, # number of parallel chains\n",
    "    init_kwargs = {\"rel_tolerance\": 0.01, \"abs_tolerance\": 0.1, \"learning_rate\": 0.01}, # VI initialization arguments\n",
    "    nuts_kwargs = {\"target_accept\": 0.9}, # NUTS arguments\n",
    ")\n",
    "end = time.time()\n",
    "print(f\"Runtime: {(end-start)/60.0:.2f} minutes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a764f97-1cf3-41db-9df8-c17da41f3d17",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.solve(kl_div_threshold=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26c0db89-bf50-4b78-b346-6c0bfc626555",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "print(\"solutions:\", model.solutions)\n",
    "\n",
    "pm.summary(model.trace.solution_0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82154de9-8516-45a3-baa8-cd6d3c7cc2cf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "pm.summary(model.trace.solution_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5185ad04-ecc7-49d2-ac62-06d8cacc7904",
   "metadata": {},
   "outputs": [],
   "source": [
    "posterior = model.sample_posterior_predictive(\n",
    "    thin=100, # keep one in {thin} posterior samples\n",
    ")\n",
    "_ = plot_predictive(model.data, posterior.posterior_predictive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5bd67b23-b21d-42cb-903d-9a968abc0d27",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 12C/13C ratio over all clouds\n",
    "for solution in model.solutions:\n",
    "    model.trace[f\"solution_{solution}\"][\"ratio_12C_13C_total\"] = (\n",
    "        (10.0**model.trace[f\"solution_{solution}\"][\"log10_N_12CN\"]).sum(dim=\"cloud\") / \n",
    "    model.trace[f\"solution_{solution}\"][\"N_13CN\"].sum(dim=\"cloud\")\n",
    "    )\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d355299a-89cc-48a9-ae6c-90ccd136859b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.solution_0, var_names=[\"ratio_12C_13C_total\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfb641ac-dbee-47dc-b0da-263b6ce6360b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.summary(model.trace.solution_1, var_names=[\"ratio_12C_13C_total\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23778358-007f-40ab-91f5-b724a2177b4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open(\"/staging/twenger2/wb89_380_trace_noCTEX.pkl\", \"wb\") as f:\n",
    "    pickle.dump(model.trace, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e9acdb7-70d4-4710-bc9c-ea18618ec102",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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