{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Import libraries" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from scipy import constants\n", "from scipy import signal as sigproc\n", "from scipy.fftpack import next_fast_len\n", "#from scipy.fft import next_fast_len\n", "import math" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data is read from ISF files, using the [`isfreader`](https://github.com/justengel/isfreader) library." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# !pip3 install isfreader\n", "import isfreader" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "shot_no = 40644" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Data loading" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "ds = np.DataSource('/tmp') # temporary storage for downloaded files\n", "data_URL = 'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/Interferometry/LukLob/DAS_raw_data_dir/ch{ch_id}.isf'\n", "scalars_URL = 'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/BasicDiagnostics/DetectPlasma/Results/{name}'" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "def get_scalar(shot_no, name):\n", " return float(ds.open(scalars_URL.format(shot_no=shot_no, name=name)).read())" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "t_plasma_start = get_scalar(shot_no, 't_plasma_start')\n", "t_plasma_end = get_scalar(shot_no, 't_plasma_end')\n", "is_plasma = get_scalar(shot_no, 'is_plasma')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "def load_channel(shot_no, chanel_id):\n", " fname = ds.open(data_URL.format(shot_no=shot_no, ch_id=chanel_id)).name\n", " data = isfreader.read_file(fname)\n", " data[:, 0] = data[:, 0] * 1e3\n", " return data" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "mixer = load_channel(shot_no, 1)\n", "ref_saw = load_channel(shot_no, 3)\n", "# phase_det = load_channel(shot_no, 4)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sampling frequency is 250 MHz.\n" ] } ], "source": [ "x, y = mixer.shape\n", "f_s = x / (mixer[-1, 0] - mixer[0, 0]) # ms -> kHz\n", "print('Sampling frequency is {} MHz.'.format(round(f_s / 1000)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Spectral analysis of the signal
\n", "\n", "The mixer signal is a base sine wave (the envelope of the mixing) at a frequency close to 500 kHz. The reference saw-tooth frequency sweeping wave has the same base frequency, but with a trail of harmonics forming the sharp saw-tooth shape." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "def calculate_spectrum(signal, target_dfreq=10):\n", " nperseg = int(f_s / target_dfreq)\n", " f, psd = sigproc.welch(signal[:, 1], fs=f_s, nperseg=nperseg, nfft=next_fast_len(nperseg))\n", " return f, psd" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The base frequency of the mixer is 540.0001080000216 kHz.\n", "The base frequency of the ref_saw is 540.0001080000216 kHz.\n" ] } ], "source": [ "ref_saw_f, ref_saw_psd = calculate_spectrum(ref_saw)\n", "mixer_f, mixer_psd = calculate_spectrum(mixer)\n", "f_base = mixer_f[mixer_psd.argmax()]\n", "f_base_ref_saw = ref_saw_f[ref_saw_psd.argmax()]\n", "print('The base frequency of the mixer is {} kHz.'.format(f_base))\n", "print('The base frequency of the ref_saw is {} kHz.'.format(f_base_ref_saw))" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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Y6d1ZRMqBPlHOWW+M+d5ug4gcDdwO3GqM+SrKeZRSKnsZDXo6q5EjR/Lee++xYsUKBgwYkOnmKKU6mZwPeowxd/gvi0jE/UWkCCvrAvBbb8DjOde9IjIOGCEihxtj5nk2nQf8K0pT3sMvUPK73gCsTNI04KYo51BKqeym3duUUkplQM6P6UnAcUAPYJkx5gub7S95fp7hXWGMecgYI1EeI4NP5MkQTcfKPo0zxkQda6SUUlnNLujRQgadwpNPPsmiRYvo29eRobFKKRVRzmd6EuCdJ+fzMNu96w9K5iKejNIUoAtQaYxpiPP4b8JsGlRXV0dVVVUyzUtIXV0dQEaurToXfa9lrwM3bmCXoHVbN2/kqwz+W5aVlVFWVsaOHTvIywv8LrC93ZpMdceOHZloWk4pLy+nvLychoYGGhri+pPXKeh7TaWD295n7e3ttLW1UVdXx6xZsyLu6/3bnyjN9ITay/NzTZjt3vX9k7zOP4ERwC3AQBEZ7nkcmuR5lVLKvUx7yCoxNtkflXGrVq2iR48ejB49mrq6Ov785z8zbNgwevfuzQknnMCbb77Zse/UqVOprKxk9913Z/DgwVx77bUhgc3o0aPp0aMHq1at6lh3ww030KNHD8aNGxdy/erqaoYOHUrPnj2ZM2dOwLbvvvuOyy+/nGHDhtGrVy8GDx7MxRdfzKJFi0LO8/TTT9OjRw/+9re/sXTpUi6++GIGDx5MeXk5r7/+erIvk1IqS2imJ1RXz8/6MNu9YWa3JK9zClbQ+VjQ+lVYleIiMsbsb7deRL4pKysbVllZmWTz4uf91j0T11adi77Xsti6f9K2IXBVz25dM/Zv2d7eznfffQdA9+7dQzI93m9Du3fvnva2ZVq3btafuba2Nn784x+zYsUKTjzxRLZs2cL777/P2LFjeeutt/jqq6+49tprGTFiBKeddhrvv/8+Dz/8MLW1tTz99NMd58vPz+84r/f1vPPOO3n//fd55ZVXmDp1akDwM27cODZs2MD111/Paaed1rH+lVde4bzzzqOpqYlDDjmEY445htWrVzN16lTeeust3nzzTU488cSO/UtLSwFYuXIlJ510EhUVFVRWVrJt2zZ69Ojhmn/bzvxeU+njtvdZe3s7+fn5dO/enSOPPDLkM9hfWVlZUtfSoCdDjDEDUnUuz9igcs9ioTd1qZRSrqOFDLLOnDlzqKysZPny5R03HZMnT+biiy/m8ssvp7q6mjlz5nDEEUcAsG7dOg499FCeeeYZbrnlFvbee++w5y4qKuLpp5/m8MMP53e/+x0nnngiAwcO5NFHH+WVV17hyCOP5MYbb+zYf+XKlVxwwQUUFhby+uuvc8opp3Rse+uttzjzzDO54IILWLp0KUVFRQHXeu6557jiiiuYNGlSRwCmlOo8tHtbKG+1ti5htnvDzNo0tCVWE4AVnseQ6urqzLZGKaXCsS1Z7eKgxxho3A4NNdn1SGFdnLy8PP71r38FfMt60UUXseuuu7J06VJ++9vfdgQ8AHvssQdjx44F4P333496/v3224+7776b2tpaxo4dy6JFi/j9739Ply5deOqppygo8H0/O2nSJOrq6vjb3/4WEPAAnH766Vx++eWsXr2a6dOnh1ynV69e3HHHHRrwKNVJaaYnlHcunT3DbPeuXxVmeyY8Abzjef7f8vLyARlsi1JKhWc3Oald9sctmnbQ/Z8HZLoV8fvjKigtT8mpBgwYwD777BOwLi8vj/79+7NlyxZGjRoVcow3u7N+/fqYrvGb3/yGN954g+nTpzN8+HDq6up4+OGHQ647Y8YMAM455xzb85xwwgk88MADfPLJJ/z4xz8O2HbKKafQpUu47zOVUrlOg55QX3p+HhZmu3f9gjS0JVYXAxO9CzU1NZlriVJKRaLd27JOuBLTXbt2Dbvdu62pqSnm6zz22GMMGDCAHTt28IMf/IDLLrssZJ+VK1dGbJPXli1bQtbttddeNnsqpToLDXpCzQa2A4NE5BBjzPyg7ed6fk5La6simwRM9jyfUVFRMSRzTVFKqQjsMj1tOk+Pm0UaWBzL9li99tprNDY2AlZ1tp07d3YET17eMat21d78HX300SHrSkpKUtJOpVR20qAniDGmWUT+AVwPPCgio4wxdQAichXW/DzvGWPmZbKd/owxNUANgIi0pOoPkFJKpZxtpsfFQU9xd3b85mu6d0u2YGealfTIdAvismTJko5xPKeffjpTpkzh//7v/3j88ccD9ttzzz1ZtmwZ99xzDxUVFRlqrVIqG+V80CMio4G/+q0q8qyf67fuFmOM/6jHW7FKSh8LLBGRD7Dm5Tka2Axc4mij46TV25RSWcMu09MaexeotBOxAohSd5R3zUWtra1ccMEF1NXV8dBDD3HRRRdx2GGH8cQTTzB69GjGjBnTse+pp57KsmXLmDp1KpdeemkGW62UyjadISXQCytY8T7Es95/XS//A4wxjcBJWBOH1gNnYwU9k4HDjDHL09DueExAq7cppbKBXfW2dhdnepTjbr75Zj755BPOOOMMfvWrX1FaWspTTz1FYWEhl112GevWrevY9w9/+AOlpaVcffXVTJkyJeRcTU1NvPTSS6xZE25+caVUZ5XzQY8xZrIxRqI8Jtsc12CMucEYM9gYU2yM2d0Yc7Exxo2fpJOAgZ7HEk35K6VcK9u6tylHzZkzh9tuu43evXvz2GO+uboPP/xwbrzxRrZu3cr48eMxnhLcgwcP5tlnn6WlpYUxY8YwZMgQzjzzTH7+859z4oknUlFRwU9+8hPbQgZKqc4t54OezsAYU2OMWWmMWQnomB6llHvZBT3tLSmdV0Zlh507d3LBBRfQ1tbG448/Tq9eAZ0uuO666zj++ON5++23mTRpUsf6s846iwULFvCb3/wGEeHtt99m+vTpbNq0iTPOOIMXXniBYcOGpfm3UUq5Xc6P6ekMdEyPUipr2I3pASvbU1CU3raoiAYMGNCRYbEza9assNvGjx/P+PHjI+7ftWtXli1bFvYceXl5fPDBB7bbBg0axIMPPhj22GhtUUp1PpoSyA0T0DE9SqlsEDbo0bl6lFJKOUeDntwwCR3To5TKBnbd20CDHqWUUo7S7m05QOfpUUplDbvqbaDFDJRSSjlKg54coGN6lFJZQzM9SimlMkBTArlhAjqmRymVDXRMj1JKqQzQoCc3TELH9CilsoFmepRSSmWAdm/LATqmRymVNcJlesKtV0oppVJA746VUkqlT7hMT7gCB0oppVQKaNCjlFIqPYwJH9xopkcppZSDtHtbDtDqbUqprGAifDZF2qaUUkolSTM9uWECWr1NKeV24bq2gWZ6lFJKOUqDntwwCa3eppRyu0hBj47pUUop5SDt3pYDtHqbUiorRMrmaKZHKaWUg/TuWCmlVHpopkcppVSGaNCjlFIqPSJmeiIERCrtVq5ciYgwcuTITDfFUfPmzWPUqFGUl5cjIogIK1euzHSzVAw2b97MRRddxO67705+fj4iwuTJk1N2fu//A+Eeffr0iek8S5YsobS0FBHhlFNOCbtfW1sb9913HwceeCClpaX06tWLn/70pyxatCihdsfz/673d4pk8uTJiAjjx4+Pqz1uot3blFJKpUekbI5WnVRpVltby5lnnsn69esZOXIk/fr1Q0To2rVrppumYvCLX/yCadOmcdBBB3HyySdTUFDA4MGDU36d3r17c/rpp4es79GjR0zHX3bZZTQ1NUXcp729nZ/85CdMnTqV8vJyRo8ezZYtW3jppZeYPn067777LkcddVRC7Vc+GvTkAC1ZrZTKCtq9TbnIp59+yrp167jwwgt58sknM90cFYfm5mbeeOMNBgwYwBdffIGTY5n33XffhDNIjz32GLNmzeKyyy7jkUceCbvf448/ztSpUxkyZAgffPABvXv3BuDll1/m3HPPZezYsSxatIiCAr1tT4Z2b8sNE9CS1Uopt9OS1cpF1qxZA8Dee++d4ZaoeG3YsIG2tjb69+/vaMCTjI0bN3LNNddw6qmn8vOf/zzivvfeey8Ad955Z0fAAzBmzBjOPPNMli5dyquvvupoezuDlL5TROSiVD1S2a5OYBJaslop5XaRAhvN9LjWjh07uPLKK+nXrx8lJSXst99+3Hfffdj1Kpg/fz7XXnsthx9+OL169aK4uJi9996b3/zmN6xbt872/F9//TUXXHABe++9NyUlJfTq1YtDDjmECRMmsH79+pD9Fy1axPjx4+nXrx/FxcX07t2b8847j2+++Sam38c75mHcuHEA3HTTTR1jGrzjFbzjF2688UYWL17MeeedR+/evcnLy+OVV15JuC1tbW3cfffd7LvvvpSUlNCvXz+uvPJKduzYwejRo+nRo0fAmKJZs2ZFHEcxfvx4RIRZs2aFbNu6dSt/+tOfGDZsGKWlpfTo0YPKykpef/31sK/JyJEjaWho4LrrrqN///4UFxczePBg7rjjDowxtm2orq7m+uuv58ADD6SsrIzu3btz4IEHcu2113b8+11xxRWISMRsx9ChQ8nLy2P58uVh9wEYMGAA/fv3B+C9997r+LcbMGBAxOPS7corr6ShoYF//vOfEfdbsWIFixYtorS0lNGjR4dsP/fccwGYNm1a0m2aNWsW/fr1o2/fvlRVVaXkfJHGPbltDFCq82STAfv/K+KnueYYaclqpVRW0JLVWaepqYnKykqWLVtGZWUlzc3NzJw5k6uuuoovv/wypNvP7bffzssvv8xBBx3E8ccfD1iB0L/+9S9eeeUVPvvsM/bYY4+O/efNm8fxxx9PY2MjBx10EGeddRb19fUsX76c+++/n7PPPpvdd9+9Y/9XXnmF8847j6amJg455BCGDx/O6tWreeGFF5g2bRpvvvkmJ554YsTfqWvXrowbN46lS5cye/ZsDj74YA455BCAjjZ7fffddxx55JFUVFRw0kknsW3bNgoLCxNuywUXXMBzzz1Hly5dGDVqFAUFBfznP/9h9uzZKc1YLF68mFNOOYXVq1czYMAATjvtNGpra5k7dy5nnHEGd911F1dffXXIcc3NzYwaNYqFCxcycuRI6urqeO+997juuuuora3l1ltvDdh/0aJFjBo1ijVr1tCnTx9OO+20juvfddddHHvssZx99tn86le/4sEHH+TRRx/lsssuC7nue++919HmaJm3c889l5UrV/Lyyy8HjLfZddddE325Itq4cSMTJ05k/fr19OjRg6OPPpozzzyToqKisMe88cYbPP/889x8880MHjy4I6to58svvwTggAMO6Hhv+TvssMMAWLBgQVK/x6uvvsp5551HWVkZL774IieddFJS5wPo06dPx5cHwT788EOWLVtGfn5+0tdJGWNMyh5AO/A5MDGJxxdAWyrb1ZkewDfDhg0zmTBz5kwzc+bMjFxbdS76XstSG74xZmJ30/qnHmbh0H07Hq1/6mHMghcz0qS2tjazcOFCs3DhQtPW1hayvaamxmxbs8a0bt+eVY/29vakXpcVK1YYrC8xzUEHHWQ2b97csW3p0qVmjz32MICZOnVqwHFVVVVmw4YNIa/xTTfdZABz8cUXB2y76KKLDGDuvvvukDYsWrTIrFu3LqBNZWVlpmvXrubtt98O2PfNN980hYWFpl+/fqapqSmm3/GJJ54wgJk4cWLYbYC54oorTGtra8D2RNry3HPPGcDstddeZsWKFR3rN27caA444ICO6/lve/fddw1gxo0bZ/s7jBs3zgDm3Xff7VjX2tpqDjzwQAOYO++8M+B9vWTJEjNw4ECTn59vvvrqq4Dfx3v9ESNGmO3bt3ds+/TTT01+fr7p0qWLqa2t7Vjf0tJihg4dagAzYcKEkNf966+/NkuXLu1YPvbYYw1gvvjii5DfY+zYsQYwzz//vO3vGczb3hEjRthuHzFiRMfvE+vjiSeesL2G3WOvvfYyH3/8se21d+7cafr372+GDh3a8Zp4/x1PPvnkkP3vv/9+A5gf//jHtuerqakxgNlll10Sfm2eeOIJk5+fb/r162c+/fTTgH9fY0zH7xWJ9/+JcO9Ff3PmzDHFxcWmvLzcfPfddxH3jfYZ7G/YsGEG+MYkeI/sxIio+caYmxI9WEQGAAelrjlKKaVcIWL1NndmeszOnaw/+RRCO1m52z6ffEx+9+4pOdfdd98d8C36oEGD+Otf/8rll1/OP/7xD84+++yObXbfHufl5XHDDTfwyCOP8NprrwVs27x5M4BtKd999903YHnSpEnU1dXx97//PWT/008/ncsvv5wHHniA6dOn8+Mf/zju39NOr169uOOOO0K+rU6kLd5uTjfeeGNAV6zddtuNu+66ix/84AcpafO0adP46quvGDNmDNdcc03AtsGDB3PPPfdwzjnn8Oijj3L//fcHbM/Ly+Phhx+mu99754gjjuAHP/gBr7/+Op999llHKeQpU6bw3Xffsf/++3P33XeHvEb7779/wPKvf/1rPvroIx599FEefPDBjvXbtm3j5ZdfplevXgHvpWScfvrpcXd3C678VlxczOWXX87PfvYz9ttvP0pLS/nmm2+45ZZbeOONNzjttNOYP39+R1c7r7/85S+sWrWKd999N2I2yGvnzp0AdOnSxXZ7WVkZYFUbTMS9997L1VdfzT777MOMGTMoLy8Pu2+0stWxWLNmDT/+8Y9pbW3l+eefZ5999kn6nKmS6qBnB1Cf5DkaPOdRSimVS7R6W9bZZZddOPXUU0PW//znP+fyyy/no48+or29PaBrVnV1Na+99hpff/01NTU1tLVZ/7YtLS1UV1ezdetWdtllFwAOP/xw3nzzTX77299y6623cvzxx4etUDVjxgwAzjnnHNvtJ5xwAg888ACffPJJyoKeU045xfZmNN62tLS0MHfuXAB+9rOfhex/+umnU15eTk1NTdJtjqVtAJ988knItv79+zN06NCQ9d4bV/8xVu+88w4Al156aUxdmH7yk5/w+9//nqeffpq77rqr43V96qmnaGxs5IorrogpSIjFddddl/Q5dt9995DxOMOHD2f69OmMHTuWZ555httuu42HH364Y/tnn33GAw88wEUXXeSKOa6uv/56brvtNg477DDeeustevXqxY4d4W+xw3VVAzq6g0bS0NDAWWedxYYNG5g0aRKjRo1KuO1OSGnQY4wpT8E5fgP8JvnWKKWUchUd05N1gr/F9urRo0fHTfq2bdvwFtB59tlnueyyyzq+vbZTW1vbEfRcc801fPjhh8yaNYuTTjqJrl27cswxxzB69GjGjx8fMBeKd4B/3759I7Z5y5Yt8fyKEe2111626+NtS3V1Nc3NzfTq1SvsN/r9+vVLSdDjbdvYsWMZO3Zs1Lb523PPPW337datG0DAfDOrV68GrMxfLEpKShg3bhz33nsvL774YscN9r///W/ACp6yxZ///GeeeeYZ/ve//3Wsa21t5Ze//CXl5eXcfffdMZ/LOy9Ufb19zqCurg7w/RvEavbs2bz33nv06dOHd999NyB7F06k0tyTJ0+OGvSMHz+ezz//nF/84hdceeWVcbU3HbTgt1JKqfTIwkyPdO3K7jPfifuGI9PyMtDeVatWdVRqmjRpEqNHj6Zv376UlpYCcOyxxzJnzpyAKmDdu3enqqqK2bNnM23aNGbNmkVVVRVvv/02f/vb3/jggw8YMmQIQEe1uEjfRgMcffTRKfudSkpKbNdnoi2R2mG37vTTTw8ofxzMbuC/04WQfvWrX3Hffffx6KOPMm7cOD755BMWLFjAiSeeaJthStTtt9/Ot99+G9cxl156aUghi3C870n/zNeaNWuYP38+ffr04Sc/+UnA/t5gdt68eR0ZIG/FPW9gHa7YgXd9uC8gwhk2bBhgFUCYOHEi9913X1zHx+uWW27hhRde4Pjjj49asS5TNOhRSimVHlmY6RERpFu3lI2PyTbff/+97fodO3ZQU1NDaWlpxxiBN954g+bmZq6++mrbb3nDlSIWEY4//viOG85NmzYxYcIEnn32Wa6//npeeOEFwMpCLFu2jHvuuYdMT80Qb1sqKiooKipi8+bNNDQ0dASC/uxuer3dvcJlzrzZluC2gXUTP2bMmKhtS1S/fv0AWLZsWczH7LPPPpx00klUVVWxaNEiHn30UQDbim7JeOutt3jvvffiOmbkyJExBz3btm0DfONt/G3YsIENGzbYHldTUxPSroMPPhiwSre3tLSEVHD7/PPPATjooPiGu/fs2ZMXX3yRyspKJk2aRF5eHvfcc09c54jV1KlTmThxIv3792fKlCkp66aYalrbOAeISLmIDPAUgSi0++ZHKaUyTicnzTrV1dXMnDkzZP1zzz0HwDHHHNMxnsN7I2jXRer9999n48aNMV1zt91248YbbwSsG0Ev79iiqVOnxv4LOCTethQWFnZkfbxBnL8ZM2Z0vH7+vOW6Fy9eHLJt69atHTfEybQtUd4CDo899phtximcX//614A1wP65556jZ8+eKQ/OZs2aFXdlr3jmk3n55ZcBXzlpsOYPCnfud999F4CTTz7Zv9ouAAMHDmS//fajoaGB6dOnh1zrpZdeAuCMM86I+3Xo1asXM2fOZP/99+fee+/l2muvjfsc0Xz55ZdceOGFdOnShVdffZVevXql/BqpknTQIyIHishDIvI/EXlQRIbZ7HOIiESebUolYwKwwvMYUl1dndnWKKWUnSzs3qbg6quvxv/vyooVK7j55psB+O1vf9ux3jvY/amnnuoYhwCwdu3ajhvdYA899BArVqwIWf/GG28AvmwCwB/+8AdKS0u5+uqrmTJlSsgxTU1NvPTSSxHnREmVRNpy+eWXAzBx4sSADNqWLVtCqqx5DRw4kL322ouvvvqKV199tWN9XV0dl112me2g9DFjxjBs2DCefvppbrnlloBxOGBNVTJ79uyo4zOiOeecc9hnn334+uuvufbaa2lpaQnY/s0339hm984++2z69OnDv//9b3bu3MmFF14YththJj366KO2XeSmTJnSUSjB//2fjKuuugqAa6+9lk2bNgVc67XXXmPw4MGcddZZCZ17t912Y+bMmey3337cddddHV8opMLmzZs75tZ68sknO7JWbpVU9zYROQ6YCSwFvgZOB34pIrcYY27x27UYiK8zoorHJKyJYQFmVFRUDMlcU5RSKgwT4dtgzfS40vDhw2lubmbw4MFUVlbS0tLCzJkzqa+v54ILLgioEHbmmWey//7789lnnzF48GCOO+44GhsbeffddznkkEM49thj+eijjwLO/9BDD3H55ZczbNgw9ttvPwoKCvj222/58ssvKSkp4YYbbujYd/DgwTz77LOcf/75jBkzhsGDB7PffvtRVlbG2rVr+fzzz6mrq+OLL74IOyA/VRJpy89//nOmTp3Kiy++yLBhwzj55JMpKCigqqqKvffemyOPPJJPP/005FoTJ07kF7/4BWPGjOHEE0+ka9eufPLJJ3Tv3p2zzjorIBgCKCgo4JVXXuG0007jhhtu4B//+AcHHXQQu+22G1u2bGH+/Pls2rSJ++67j+OOOy7h16CgoICXX36ZU089lXvuuYdnnnmGY445BmMMS5Ys4euvv2bq1Kkhk40WFhZyySWXcNtttwGp79qWKk8//TSXXXYZBx10EPvssw/t7e0sXLiwIxC65pprUlYl8JJLLuGNN95g6tSp7Lvvvpx88sls2bKF9957j9LSUp566qmwVQ1j0bt3b6qqqhg5ciT33Xcf+fn53HXXXUm3+6GHHmLVqlX06dOH1157LaQkPVgT/rqlSEWymZ7bgCnAgcaY84AhwDXAn0TkWREpTraBKjpjTI0xZqUxZiXQ4vRARKWUSohmerJOcXExVVVVnH/++cydO5f//e9/9OvXj7vvvjuk0lNRUREffPABl19+OSUlJbz++ussWrSI3/3ud7z99tu2s83fcsstXHLJJYgIM2fOZNq0aTQ0NHDppZcyf/78kJvys846iwULFvCb3/wGEeHtt99m+vTpbNq0iTPOOIMXXnihYwC30xJpyzPPPMMdd9xB3759eeutt5g7dy7nn38+VVVVFBfb3zJdcsklPPHEE+y3337Mnj2bTz75hDPOOIM5c+aEnXNlyJAhfPHFF9x6663sueeezJ07lylTprB48WIOPfRQHnzwQS644IKkX4MDDjiAL7/8kquvvppu3brxxhtvUFVVhYjwxz/+keHDh9seV1lZCVjdI4Pn83GLX/7yl5x77rnU19czY8YMpk2bxo4dOzjnnHN4++23ufPOO1N2rby8PF588UXuuece9thjD15//fWOuZY+++yzlBTE8FZxGzx4MHfffTcTJ05M+pzecvQbNmzgP//5j+3jww8/TPo6qSL+/QrjPlikBjjXGPNO0PqjgVeA5cBZwCDgI2NM9ELuKiki8s2wYcOGffPNN2m/dlVVFeD7MFPKKfpey1KLpsHzF9DWLCyesnvH6n3OWU/+D26AE65Ke5Pa29v57rvvABg6dGhI9Spv96FYyr0qlYwTTjiBDz/8kBUrVsQ9sWa2+dWvfsUjjzzCE088EddYGpU8t32mRfsM9rf//vuzcOHChcaYhCLlZFMC9UDX4JXGmI+BY4ByYC6wX5LXUUople0idWHTTI9SncKqVav473//y6677mo7UatSTkk26PkcK5MTwtPV6ljge+DfSV5HKaVUtotYvU2rTiqVy+666y4uvPBCjj76aBoaGvjLX/5iW7pbKackG/Q8CewjIj3tNhpjtgOnYQ2yty/230mJyDgR+UxEakSkTkQ+F5HzMt0upZRyjGZ6lOq0pk+fzlNPPUV+fj4TJ07k//7v/zLdJNXJJFW9zRjzAhBacD5wnxbAHWUb3KUn1rin+UAjcDbwrIg0GmNeyVirlFLKKZECG63epjo57xwtbhlrkWqzZs3KdBNUJ5dU0BNMRPKMiVSTVHkZYyYFrXpHRA4BxmIFQ0oplVu0eptSSqkMSXVt47Uico+IHJri83YW1UBoTU+llMoFEcf0aNCjlFLKOakOenoDE4DPRORrEfmjiPSLcoyjRORwEblORKaIyBoRMSIStU63iJSKyM0islhEGkVknYg8LiJ9U9y+AhHpLiI/A04FHk7l+ZVSyjUijunRTgJKKaWck+qg52jgQWAzMAxr8tIVIjJTRC4WkW4pvl4s/gr8DfgxEFPAIiIlQJXn2K7Aq8Bq4GLgCxHZO8LhMRORPkALsB14GphgjHkzFedWSinXiRT0RMoCOUhEfE3QCnJKKZVW3glOIfDz2AkpHdNjjPkU+FREfg+MAi4AzgROAkYC/xCR14D/Av8zJi2duOcAC4BPPY+VgP20xz5/AYZ7jh1ljNkJICJXAfcAj2P9PnjWlwN9opyz3hgTXMFuC3Ak0A04Hev1qTbGvBztl1JKqazjwu5tIkJRURHNzc3U1dXRo0ePjLRDKaU6I+9kqcXFxdkV9Hh5gpk3gTdFpAswBisAqgR+BvwU2CIizwFPeYIlRxhj7vBfjvaCikgRcIVn8bfegMdzrntFZBwwQkQON8bM82w6D/hXlKa8h1+g5DlfK/CZZ/FdEdkFKyulQY9SKvdE+p4rg4UMunXrRnV1NRs3bgSgrKysY1Zwb/ZHs0DKafpeU+nghveZMYampiZqa2vZunUrAD172s5+k1KOBD3+jDH1WJmd/4rIbsD5WAHQYcDvgCtEZAnwX2PM/3O6PTE4DugBLDPGfGGz/SXgIOAMYB6AMeYh4KEUXHs+Vhc6pZTKPS7M9ABUVFRQV1dHY2Mj69atC9jm7XqRn5+fiaapTkTfayod3Pg+Ky8vT0uWPdVjeiIyxmwyxkwyxhwB7AfcilWxbB/g5nS2JYKDPT8/D7Pdu/4gB659LFb3O6WUyj0unZw0Pz+fvfbai4qKCoqKigK21dXVUVdXl6GWqc5E32sqHdzyPsvPz6d79+707duXPn36dGTXneR4pseOiOyKNeZnFFCRiTZEsJfn55ow273r+ydzERF5F6sb27dACXAWVhbsshiP/ybMpkF1dXVUVVUl07yEeP8nysS1Veei77XsNHDlUgaG2bZ+3VoWufDf0/tec8NNgspt+l5T6ZDN77Nk25y2oEdESoGzsbq2neK5tmAN5n8OqwucG3T1/KwPs937iidbie5LrO59/TznXAicYYx5PcnzKqWUK0mEbI5oyWqllFIOcjToEatqwKlYgc7ZQBlWoNMITAWeAt7yDOjvVIwxE7DmNEr0+P29zz3V48o9izNKS0uHVFZWJtG6xHi/dc/EtVXnou+1LPX2e1bxfxt9dutFHxf+e+p7TaWLvtdUOmTz+6ysrCyp4x0JekTkcKxA52dYE5YKYID3sTI6Lxljdjhx7RTwVmvrEma79xWvTUNbYjUBmOhdqK6uzlxLlFIqnEiFDDI4pkcppVTuS2nQIyLXA2OBoViBDsAirEDnaWNMmO/4XMU7l86eYbZ7169KQ1tiNQmY7Hk+o6KiYkjmmqKUUmFE6sKWweptSimlcl+qMz23eH5uBJ7FmoMnXBU0t/rS8/OwMNu96xekoS1KKZU7ImZ6dEyPUkop56Q66HkWK6szw5is/Qs2G9gODBKRQ4wx84O2n+v5OS2trYpsAtq9TSnldi6dp0cppVTuS2lRbGPMWGPMW1kc8GCMaQb+4Vl8UEQ6Rk2JyFVY8/O8Z4yZl4n2hTEJGOh5LKmocFsVcKWUInJgEykgUkoppZKU6jE9uwCNxphw5Z5jOUcXoMQYszVFbRoN/NVvVZFn/Vy/dbcYY6b7Ld+KVVb7WGCJiHyANS/P0cBm4JJUtC1VjDE1QA2AiLSkY4InpZSKm0snJ1VKKZX7Un13vBn4e5LneBDYlIK2ePXCCla8D2+BBf91vfwPMMY0AidhjVGqxyq33R+rWMBhxpjlKWxf0kSkXEQGiMgAoLC9PWsTbUqpXKbd25RSSmVIqsf0CL6gItnzpIQxZjK+ymbxHNcA3OB5uN0EdEyPUsrtImVzsrdXtFJKqSzgxDw9x4vI48kcn7KWdB6T0JLVSim300yPUkqpDHEi6BnseSTDpKIhSimlXEQnJ1VKKZUhqQ56Tkrx+VRsJqDd25RSbhdpvKFmepRSSjkopUGPMea9VJ5PxWwS2r1NKeV2mulRSimVIU50b1NppiWrlVJZIQfG9LS3G6Z8sZaigjx+dODu5OWlrO6OUkopB2nQo5RSKj3amsNvy5LqbY/PXsGt0xcBkC/C6IN2z3CLlFJKxUJTAjlA5+lRSmWFxu3ht2VJpscb8AA888mqDLZEKaVUPDToyQ0TgBWexxAtZKCUcqWmHeG3ZcGYntVb6wOWu5cUZqglSiml4qVBT26YBAz0PJZUVFRktjVKKWUnYqYnwngfl9iwozFgud8uXTLUEqWUUvHSMT05QAsZKKVczxhojJDpyYLubSZoBrn2dp1STimlsoXeHSullHJec13ELmwmC7q3tQdFPRrzKKVU9nA06BGRiSKyp5PXUFrIQCmVBSKN54HIE5e6RGjQo1GPUkplC6czPROBFSIyTUTOFBHNLDljAlrIQCnlZn7jeRqNTQGALOzeZjToUUqprOF0EPIX4HtgNDAVWC0it3gyEip1JqGFDJRSbuYX9NQSWgBAu7cppZRykqNBjzHmNmPMIGAU8CJQAVwPLBWRt0RkjIhoMYUkGWNqjDErjTErAS1koJRyH78iBjtNaej2LMj0BAc52r1NKaWyR1rujo0x7xhjzgP6AlcD32EFQi8Aa0TkdhEZko62KKWUyoAomZ5smKcnuDubZnqUUip7pDUlYIypNsbca4zZHzgeeBbYDbgG+FZEZorIj9PZJqWUUmnQ5Bf0ZGmmR0tWK6VU9spIPygRGQScAZzst3oNcBLwkoh8IiL9MtE2pZRSDvDL9OzM0kyPVm9TSqnslbagR0QKReQ8EZkJLAb+iDU56r3AvsaY/sBxwJvAEcA/0tW2bKclq5VSruc3psc+0+P+z63QMT2ZaYdSSqn4OV5EQET2A34JXAjsAgjwEfAQ8KIxpsm7rzFmDvAjEZkLjHC6bTlkAlZ5cAC0ZLVSynX8Mj07bDI9koWZHi1ZrZRS2cPRoEdEPgSOwQp0dgD/Ah4yxnwd5dBvgCOdbFuOmQRM9jyfUVFRoUUhlFLu0hh5TI+YNmvQjEg6WxWX0EIGGvQopVS2cDrTcyzwOVZW5xljTH2Mx/0beN+xVuUYY0wNUAMgIlqyWinlPk1+3dvsxvQAmHaQ/DQ1KH4hhQzSEPNs2dlEWVEBpUXufV2UUiobOB30HGmMmRfvQZ5ubnMcaI9SSqlM8C9kYErs92lvgzz33tyne56eFz5bzR9fXkCf7iW8/rvjqeha7Oj1lFIqlzmdEvitiFwSbScRGS8ijzvcFqWUUpniX8iAMvt9XD6uJ3RMj7PXu/alBRgD67c38veqpc5eTCmlcpzTQc94rPl4ojkOGOdsU5RSSmVMlDE9gOvn6slkyeqF63dE30kppVRYbhn8UQS4+6+dUkqpxPmN6bGdpwdcn+kJHdOTvqCnpc39Jb2VUsrNMh70iIgAhwGbM90WpZRSDmhthhZfHZvcyfSk79oa9CilVHJSXshARKqCVp1us87/+oOAPsB/U90WpZRSLlC/JWCxhq72+xl339iHZHrSGPW0tml5bKWUSoYT1dtG+j03WAFNnwj7twCvA1c70JZOQUTKgXLPYmF7FsxsrpTqRHZu8j2llCaK7PfLukxP+gKRZs30KKVUUpwIegZ6fgqwHHgJuCbMvs3AFmNMiwPt6EwmABO9C9XV1ZlriVJKBavzZXqqTY/w+2XdmJ70XVu7tymlVHJSHvQYY1Z5n4vITcAX/uuUIyYBkz3PZ1RUVAzJXFOUUipInS/Ts4UIQY9mesJqbtWgRymlkuHo5KTGmJucPL+yGGNqgBoAEWnJy8t4fQqllPLx695WHTHoaU1DYxIXnNlJY8xDi47pUUqppOjdsVJKKWfV+YpzbmnvHn4/lxcyyGSmp0UzPUoplZSUZnpEZDlW8YJTjDErPMuxMsaYQalsj1JKKRfwy/RszuLubcEhjhYyUEqp7JHq7m0DPD8Lg5aVUkp1Vn5jejZHzPS4POjReXqUUiprpTToMcbkRVpWSinVCflVb9scqXqbyzM9wfPyBAdBjl5bh/QopVRSNChxARE5UERaRWRNptuilFIp51/IwGRvpic48NBARCmlsocGPe4wCdDJdZRSuae9Dep9mZ5cKlndlkVRT2NLGz97eA4H3fg/3vp6faabo5RSaedo0CMivUXkRBHpHbR+kIg8JyJfi8gbIjLcyXa4mYicDewNPJ7hpiilVOrVbw2oyrYl4uSk7h63EtybLZ3d25L13Cff8/GKrexobOXXT32e6eYopVTaOZ3puQ54F3xf7YlId+BD4CfAMOB0YKaIdLoJNUWkCLgb63VqynBzlFIq9fyKGJiCEnZSGn5fl2d6DJkrZJCsL1bXZLoJSimVUU4HPSOBhcaYxX7rxgO9gWeBocBVQCnwBycaICKHi8h1IjJFRNaIiBGRqH+qRKRURG4WkcUi0igi60TkcRHpm8LmTQA2G2OeT+E5lVLKPfzG85guuwISft+sG9OTRVGPUkp1cqkuWR2sLzAnaN1ooBWYYIzZAkwSkXHACIfa8FfgrHgOEJESoAoYDqwHXsUqv30x8CMRGW6MiWcOIrtr9Aaux8p0KaVUbvILetq79Iq8r8szPaGTk2aoIQmIEGoqpVSn4HTQ0w2o9y6ISD5wDDDPE/B4fQv8yKE2zAEWAJ96HiuB4ijH/AUr4JkDjDLG7AQQkauAe7DG34z07iwi5UCfKOesN8Z877d8G/CWMSY4KFRKqdyxdVnH07Ye/SLv6/JMTzaP6RHRsEcp1bk5HfSsA/b1Wz4e6ArMsmlHsxMNMMbc4b8c7YPfM87mCs/ib70Bj+dc93qzUiJyuDFmnmfTecC/ojTlPTyBkogcAFwADPcETAAl1iYpxwqQHHk9lFIqrbYs6Xja2nNw5H3bWx1uTHKC5+nR7m1KKZU9nB7TMwc4SEQmiMiBwK2AAaYF7bcfsNbhtsTqOKzCC8uMMV/YbH/J8/MM7wpjzEPGGInyGOl3jsFAEfA5sM3z+COwh+f5Jan/tZRSKgOq/YOeQZH3bXd39bZsnqdH8zxKqc7O6UzP34BzsLqEgfW5+64x5iPvDiIyAKuK22MOtyVWB3t+hqvp6V1/UBLX+BA4KWjdeKzxTj8BFgcfoJRSWae9Hap93dtaygcBW8Pv7/bubSHV2zTqUUqpbOFo0GOM+UZEjgeuBHYF5gF3Be12GvAl8IqTbYnDXp6fa8Js967vn+gFPOOZZvmvE5GRQJMxZlboEaFE5JswmwbV1dVRVVWVaPMSVldXB5CRa6vORd9r2aG4cQvHtXQM6+T97zYD+WH3X/DlfLasjTbkMr3832vLl7cEbatP63swmWtt3BDYY1r/33Ef/VxT6ZDN7zNv2xPldKYHY8znwLgI2x8GHna6HXHo6vlZH2a79xXvloa2KKVU1urS4PvuqKmoJ815XYg0JZm4fHLS4NZlU/c2pZTq7BwPelRsjDE3AjfGsf/+3uee4gflnsUZpaWlQyorK1PYuth4vzXIxLVV56LvtSzx8VL4ynpavMcBDB9+DHw4K+zuB+6/Hxzgrn9T//favJZvYbmvu15xSYmz78EZ0wMWk7nWG9VfwjpfEKr/77iPfq6pdMjm91lZWVlSx6cl6BGRLsARwO5EKBdtjHkyHe2JwlutrUuY7d5XvDYNbYnVBGCid6G6ujpzLVFKKS+/IgbsOoS2aGNg3J7pCSlZnZl2JEKH9CilOjvHgx4RuRn4PeGDCLA+jw3ghqDHO5fOnmG2e9evSkNbYjUJmOx5PqOiomJI5pqilFIeW/3mcK4YHFLyOUTWTU6aRVGPUkp1co4GPSJyLdZEn23AdKyqZG7KkNj50vPzsDDbvesXpKEtSimVvRq2+Z537R19DIzLq7cRUrI6e4IenZtUKdXZOZ3p+SXQAJzgKWiQDWYD24FBInKIMWZ+0PZzPT+D5xrKpAlo9zallNs01Piel5TTFi3qaQ1f5MANQjM9GWpIAiTJDm5NrW3UNraya1d3VddTSqlYOT05aT/gvSwKeDDGNAP/8Cw+KCIdo6ZE5Cqs+XneM8bMy0T7wpgEDPQ8llRUVGS2NUopBdC43fe8pEf0zEhLg7PtSVLomJ4sinqS0NjSxhl//5Ajbn2Hf81aFv0ApZRyIaeDng34SjxnhIiMFpG53gdQ5Fk/1+8xOuiwW4GPgWOBJSLyvOfYe4DNwCXp/B2UUirrGAONNb7l0vIYgp5wMwW4QyYzPZnsnjb1i7Us3mjV+LnjrW8z1xCllEqC093bngN+ISJlxphMBT+9gKNt1h8dtE8HY0yjiJwE/Ak4HzgbaxrxycBfjTHhJi7NlAlo9zallJu01EN7q2+5pAdt9dkd9ATHbJ1lTM/3W93976KUUrFwOtNzI7AIeE1EBjt8LVvGmMnGGInymGxzXIMx5gZjzGBjTLExZndjzMUuDHhAu7cppdzGfzwPxNa9rdndN9chmR4HUz1u6jrnoqYopVTCnM70vIEVWI0EFonIKmANoRNbAxhjzMkOtycnGWNqgBoAEWnJy3M6llVKqSj8u7YVlEJBMW3tURL+WZbpcTIYCD53sr3bgjM9xhgkxvSPmwIwpZRKlNNBz0i/5/nA3p6HHf1UTZCIlAPlnsXC9nZ3T/CnlOoE/IsYlJYDMXQHc3nQE9z+qJOtpvBasQYo4QUe39ZuKMiP7ZzZ1I1PKaXCcTroGejw+ZVlAjqmRynlJgHlqnsAMXQHy7LqbU4GA8HXSnUdg3h65mnMo5TKBY4GPcaYVU6eX3WYhFVkAWBGRUXFkMw1RSmlCCpXXQ7EkBlpzmixz6iCu3k5Wb0tNNOT3PmCj48nYMum+YiUUiocpzM9Kg10TI9SynWCylVDDDfPWda9zcmxLqFjepKLeoKPjjpRrB/t3qaUygVpCXpEpAK4ADgK2BWYaYy507Ntf2AQ8I4xxt1/8ZRSSsUmaGJSiKV7m7v/BIR2b3PuWibFw1yTyfQopVQucDzoEZGfAP8GumJ92WSAtX679AWmAuOAp5xuTy7SQgZKKdcJGNNTDsSQXci2ktVpHNOT6kE98fyZ0ABJKZULHO0HJSLHAM8ArcAfsDI9wR/dM4HtwDlOtiXHTQBWeB5DtJCBUirj7DI9Uau3ubuQQXDyxRjnurilOtAI7h4XT+U5DXqUUrnA6UzPn7Hm5DnVGPM5hJbdNMa0icjnwAEOtyWXTUILGSil3MR2TE+0oMfdhQzs2m9M8kUG7JigTEyq5+mJJ5DRmEcplQucDnqOBeZ4A54INgBHO9yWnKWFDJRSrmOT6WmL1qXK9d3b7NYZ8lJeUDr11dtCzh9XIYPUXlsppTLB6bvjLsDmGPbr6XA7lFJKpZPdmJ5oKYP2FmhrcaxJybLLjjgVEIQEPamu3hZXpkejHqVU9nM607MW2D/SDmL1dzsAazyKSoAWMlBKuY5/9zZPpiemm+eWesjv4UybkmTXfKfGuzidXdHJSZVSnY3TmZ63gKEicl6EfS4F+gHTHW5LLpuAFjJQSrmJf/c2z5iemOaGcXExA/tMjzMRQXDJ6mS7tyUTRGkhA6VULnA66LkdqzLbkyJyh4gM96wvE5FDReRm4O9YXeDuc7gtuWwSMNDzWFJRUZHZ1iilOre2Fmje6VvuGNNjf/PcZvzu6JvdW8zAPtOTnmslO6QnmYlVE/0V29qNdo1TSrmGo0GPMWYNMBrYAlwDzMb6/DwX+Az4C9YA/DONMZucbEsuM8bUGGNWGmNWAlrIQCmVWY07Apc9Y3rC3f82UuxbcPEEpenM9IQWMkgu7EmmlYn8in+fuYRBf36DX/13ngY+SilXcHxyUmPMHBEZCvwCOBUYgBVsrQHeBh42xmwPfwallFJZpWGr73leARR1BcIPnm+giO54urW5untb6Lrg0tJOXSvZTE8ygUcix97z9mIAZizcyNdrd3Dgnu4cp6WU6jwcD3oAjDG1WF2wJqXjekoppTKozq9oZ5cK8GSfw3VvazRFvgVXd29LY6Ynxf3mguvbxNPseH/H4LZv2dkU1/FKKeUE7QellFIqteq2+J6X9ep4Gi5jUB/Qvc3NmZ40FjIIOm2yVwkujBDfsfFpag2MsIoL9FZDKZV5Kc30iMhFyRxvjHkyVW3pTLRktVLKVYIzPR5hMz1ZM6YntnWpEBykJDsuJrnqbfHt39jSFrBcXKhBj1Iq81LdvW0yiX0hJZ7jNOhJzARgondBS1YrpTKq3u8zqGzXjqdt4QoZmELfgpu7t9mtS9M8PcleJZmMVLy/Y2NrUNBTkJ/wtZVSKlVSHfTcTOhn8yDgAqAemAGs9KzvD4wCyoCngGUpbktnMgkr4ASYUVFRMSRzTVFKdXphureFG6eSLd3b7Mf0OHOt0BLTyZ0vpLtcHOeLt3JcY0tgb4P8vGTLMCilVPJSGvQYY270XxaRIcAnWEHNBGPM1qDtPbFu2M8AhqMSYoypwSr9jYhoyWqlVGYFdG/zZXrCZRuaAoIe92Z60jumJyjoSTrXk7h4Q5bmVu1irZRyH6fvjv8GbAMuDg54AIwx27BKWdd49lVKKZXt6v0zPf7d28Jkevyrt7k402M3XDLcOKWkr5VEZsZOMt3w4p0iKHQ8UsKXVkqplHE66BkJzDXGtIXbwRjTCswFRjjcFqWUUulQZx/0hOve1uCf6Wl2cyGD0PY7dUMf0r0txeePJ3MUHPNEC6BCK89p1KOUyjyng55SYPcY9usDlDjcFqWUUungH/QEdG+z3z1gTE/TDocalTy7e/1w2auUXyvZTE8SxwaP6Yn2K8c7fmh7fUtIxTellEo1p4OeBcAJInJKuB1E5GTgRM++Simlsll7e1D1Nl8hg3BdwWpNmW+hcbtTLUuaXcbCueptJuJysuIqZBC0nMq2vPLFWg69ZQYn3/OeTmKqlHJUOsb05AGvi8jjInKaiOzreZwmIo8B07E+U293uC1KKaWc1lgD/j2ay3zz9IS7Wa6l1Lfg4kyPXczmVMetVE9OmkrR2hJPd7YJz8+n3cDamgYemLkkuYYppVQEqS5ZHcAY85qI/Aa4FxgPjAvaRYAm4HfGmNecbItSSqk08O/allcAJeUdi2GDHuMX9Lg402M/pic94Uiy10nq8KBUT7zninX/hevcG/AqpbKfo0EPgDHmIRF5A6tK2/HAHp5N64EPgCeMMSudbkcuE5FyoNyzWNhuV2JIKaXSIbhctd94kLYwH0076eJbaHTvja9tpsehmMfpTE8855OgqCda97ZEX5NWpyY9Ukop0hD0ABhjvgcmpuNandQE/F7f6urq8HsqpZSTwpSrhuzP9KRzctLQayd5fBLHxluyOvTasV29Vb+wU0o5SGexzA2TgIGex5KKiorIeyullFP8Mz1BQU/YQgbBY3pcOrFLWicndXgUTzzd5UJLVsd7rdj2a21z57+7Uio3pCXTo5xljKnBmuAVEWnJy9NYVimVIXV+meYusWZ6/Lq3tTVDayMUltrum0l2zU9X9zZrnQkpHx37+VI3OWm83dtivbJTE70qpRRopkcppVQq+Zer7hKYdQ43OWmt/5gecG0XN7vmO5fpsVmXwkslc6pUVm/zp0GPUspJGvQopZRKnYZtvudddgnYFG4izyYKafHveODSYgbpqtQW7lqZCgmCCxnE+zrEun+kQgbfbahl047GuK6rlFL+NOhRSimVOg1bfc9LA4Oe8Pe0wk7cP0Fpesf0xHb9ZM4Xq9DubVGulWD3ttYw5f2enLOS0ya9T+U97/F9dX2MZ1NKqUAa9CillEqder+gJyjTE657G0Cd+HVxa3Jr0BPbulRwevxQPOcKGUbkUCGDljAv5g2vfgPAzqZWbn9rUXwXV0opDw16MkRExouIsXmMzHTblFIqYQGZnvKATZHGbNRmaabHuS5vdt3bkrhWUs0M6t4W5WSJXiqWl3LNtoYEz66U6uy0elvmHQ+0+S0vzFRDlFIqaf5jemLu3pYlE5TmUKYnntAk/u5twTukruEurWaulMoCKQ16RGR5EocbY8yglDUme3xsjGnNdCOUUippba2BWZrg7m0R7lgDKrhlUabHqfICqT5rKuf9ib+QQcou7fj8RUqp3JXqTM+AFJ9PKaVUtmisCVwu7RmwGKl72w7/7m1N7sz0dNYxPXlBmZ7oJavj2z8emulRSiUqpWN6jDF5yTxS2RYvETlcRK4TkSkissY7diaG40pF5GYRWSwijSKyTkQeF5G+KW7iWhFpFZEFInJuis+tlFLp49+1La8AirsHbI6U6dmZpZmeSMUZUi1TWY7gktVOVayLhU7lo5RKVGcY0/NX4Kx4DhCREqAKGA6sB17FymJdDPxIRIYbY5LpyofnvNcDHwOlwC+AF0XkbGPMq0meWyml0s+/cltpz5DBIJFulndkQdBjm31x7Fp2RROSOV8SjQk5WXzXSm2GSqMepVRiOkPQMwdYAHzqeawEiqMc8xesgGcOMMoYsxNARK4C7gEeB0Z6dxaRcqBPlHPWG2O+9y4YY/4H/M9v++si8gHwZ6wgSymlskuEOXogSvU24/6gJ9Pz9KQxbgkQXMgg+rGBezgdqGxvaOG/c1YyeLeunH7A7o5eSymVvXI+6DHG3OG/LCETDgQSkSLgCs/ib70Bj+dc94rIOGCEiBxujJnn2XQe8K8oTXkPv0ApjFeB/xdlH6WUcqfgTE+QMHNPAlBrSn2VkZvrUtuuFEljHYMwY3qSmJw0iXYG/9WMN9BzekzPxFe/5pX56wCYdsXxHLhnjxReUSmVKxyfp0csF4jIiyIyX0SWichym8cyp9sSo+OAHsAyY8wXNttf8vw8w7vCGPOQMUaiPEamoe1KKZU5/mN6uoRmeiLdtNebIt9CS30qW5Uy9pkeZ65lN34nldeKb3LSoHl64uzelkp2r4s34AG4f+YS5y6ulMpqjmZ6PFmT6UAloV8WeZkI2zLhYM/Pz8Ns964/KJUXFeuvyo8Bu0DLbv9vwmwaVFdXR1VVVcraFqu6Ouvb2UxcW3Uu+l5zp71XfN5RwnNdTSPfBv37bNrSFPbYnW2FHV/D1dVs5mOX/Nv6v9cam0Lb//kXX9C8Oj/l111U3Ray7v3336esMLE/l5s2B7b9448/Zm232L73XL2mOWB59uzZVJSGP3bJtsC2f/7559SvjP4aNTc3Rf1/eufOyH/fqrdsztrPBf1cU+mQze8zb9sT5XSm5w/AycDrwBDgv1hBTjGwH3AjUAfc5VT1tgTs5fm5Jsx27/r+yVxERF4SkWtF5HQROQt4DTgGuDWZ8yqlVKYUttZ2PG8t7BayPVKmoh5fpievLXxwlEnpHEOfxp50KedoyeoUnksp1bk4PabnZ8BW4HxjTJ2ItAMYY1qA74CbReRd4F0R+c4Y87jD7YlFV8/PcP0rvGFm6F/0+CwGLgX29Cx/AfzIGPNGLAcbY/a3Wy8i35SVlQ2rrKxMsnnx835rkIlrq85F32suteU/Vl1KYK+hB7PXCYH/Po8tnwvV1baHNkpJx/PS/HbX/Nv6v9cKPpwBLS0B2w88+GBOGrpbyq9btGQLzPs4YN0Jx59Az7KiMEdE9vzaz2DTxo7lo44+in37dI9whM/7O7+B71d2LB9z7LHs2bNL2P27rtgKn87pWD700EM5dtCu9jvPmN7xtKio2P7f3W+f0i5dqKwcGXZ7r169qKw8Imzb3Ew/11Q6ZPP7rKysLPpOETgd9AwG3jfGeAOFdgARyTfGtAEYYz4QkdnAb7CqonUKxpg/Y1VqS5qnely5Z7GwvT3CaGGllHJKlOptrW0R5ulp9x/T05DKVqWMbaYqjWN6krlURis9a6pHKeUCTncpawP8a496g59eQfutBYY63JZYeau1hfsayxtm1obZngkTgBWex5DqMN+kKqWUo+ojFzKIVLK6LriQgQvnY7ErxOBYyeoUV2+L5fypOja4nRrzKKXcwOmgZy2+7lsASz0/hwftdxC+YCPTvHPp7Blmu3f9qjS0JVaTgIGex5KKiorMtkYp1Tn5V2+zKVndGiHoaTAlgStcmO2xu9l3rnpbbOuSOV+6pHNy0iizUiilOjGng565wAEi4p0M1DteZZJnAP+BIvJ3rKIGH9ueIf2+9Pw8LMx27/oFaWiLUkpljyQmJ20gaKyKC4Meu6yO0xNvBl7LnecKObdzp456bnFVMVillJs4HfS8DDQCowCMMUuxshJ7YZWyng/8FqtowLUOtyVWs7G65A0SkUNstp/r+TktbS2KbgLavU0plUnN9YHz63QJzTi3RJidtIHiwBUunKvHLmZzLNNjF2AlEU4k150tzslIg3ZPpt3Rzh1MMz1KqXAcDXqMMdONMbsbY6b5rfsDcD7wIvAO8CBwmDFmsZNtiZUxphn4h2fxQRHpKBUhIldhdcV7zxgzLxPtC2MS2r1NKZVJ/lkeiHtMTzt5mHy/wMeVQU/6KhnYXilLB7SkNEOlo3qUUglyunqbLWPMc8Bz6biWiIwG/uq3qsizfq7fuluMMdP9lm8FTgGOBZaIyAdY8/IcDWwGLnG00UoplW3q/TLMRd2goDhkl0hBDwCFpeCdo8eFQU86x/TY3dtnKngImXcnWiGDoCNS+RJpcVKlVKIcDXpE5F5gmzHmFievE0UvrGAl2NFB+3QwxjSKyEnAn7CyUmdjzTc0GfirMSbcxKWZMgGY6F3Q7m1KqbSr2+J7XmafbY5UyADAFJYijTXWQrMLgx6b23fHqrfZlqzO1lIG6aPd25RS4Tg9pucKrO5gGWOMmWyMkSiPyTbHNRhjbjDGDDbGFHu66V3swoAHtHubUirT6v26t9mM5wFojTCmB8AU+s0U4MpCBqHrnOpyZl+y2tnzx7pv1OAreP+UltqOUr1NCxkopcJwunvbGpwPrDo9Y0wNUAMgIi15efqSK6XSzL97W7igJ1qmp6DUt+DC7m12WZ20ztOT4vM5JaQ7nIPnDqExj1IqDKfvjl8BRohIN4ev06mJSLmIDBCRAUBhu3Z6VkqlWwxBT7QxPYGZHncFPcaYjAYO3jZkQsgYnXibkcFS28YY5i6vZtH6HalrhFIqKzkd9EzEmuzzDRE51OFrdWYT0JLVSqlMqvcb05ODmZ5wN9vOZXrs5gRK4nxJtCXuayV4sVjG48Q7rumpuas475G5jH7gA774flv0A5RSOcvp7m2vAk3AccBnIrIeKwhqtNnXGGNOdrg9uWoSVpEFgBkVFRVDMtcUpVSnFEv3tmhjegKCHneN6QkX3Dg2pseZ06ZE/Ime1P020arlBcdNf331m47jrnv5K/73+xNT1halVHZxOugZ6fdcgD08Dztu/ox3NR3To5TKuFgKGUS5Y233797msupt4Zru3OSksa1L5flTsS+koDucQ6rrmjLdBKVUBjkd9Ax0+PwKa0wPUO5Z1DE9Sqn088/0lO1qu0u0MT3tbu7eFuZ7Oae6t9l9D5jMtdI5Hiik2lsKLx2tB5xozWqlVBiOBj3GmFVOnl91mIDO06OUyqS6yGN6jDHRMz35Jb4FtwU94Zqe4eIGiZ8rmclJXZK6UUqpODjaD0pEHheRS2LYb7yIPO5kW3LcJHSeHqVUphgTdUxPtCwPQHuBe6u3hcuypLVkdTKZniTakuy10nltzfMopcJxevDHeOD4GPY7DhjnbFNylzGmxhiz0hizEtAxPUqp9GrcDqbNt2wT9ETL8kBw9za3FTKwX5++zm2ZG/gaOjlpvMenr+Xau00pFY5b7o6LgLaoeymllHIf/yyP5EFJecgusWR6Wv2DHtcVMnBDpid153MyDgkOcrQznFLKDTIe9Ig16vAwYHOm26KUUioB/kFP6S5gk22OKdOT7+JCBmHqwzhWvc1duZ7ApSjNcLKVmslRSiUq5YUMRKQqaNXpNuv8rz8I6AP8N9Vt6Sy0eptSKqNSMEcPQHuBiwsZhLuVz5JMT8i5Uneq6NdK48U0JlJKheNE9baRfs8NVkDTJ8L+LcDrwNUOtKWzmIBWb1NKZUoMQU9M3dvy3VzIIL71yUp1niepY0MOjjfVox3clFKZ50TQ452bR4DlwEvANWH2bQa2GGNaHGhHZzIJmOx5PqOiomJI5pqilOp0AiYm3cV2l1i6t7UFlKx2WyED+/Y7NUjf7rypnZzUfYFIKpqk8/QopcJJedDjPzePiNwEfKHz9TjLGFMD1ACIiFZvU0qlV1Ot73lJD9tdYitk4JfpadqZbKtSKnwhg8y3IRZJlbuOswhCcFfAdMZX8fye81ZtZfnmOs48ZA+KC/IdbJVSyg0cnZwUuBcYKCK7GmO22O0gIr2A3YFlxpg6h9ujlFIq1fyDnuJutru0+I3pKcy3/za+tbC7b6GxJhUtS5lw99LZUr0tnRItcZ2KJE2s11qysZZzH5qDMfD12u3cdNYByV9cKeVqTqcEfg98gVWsIJy9Pftc6XBblFJKOSGGoMc/05OXZ39321LslyVqbXRVFzengptw7AonhC2mkND5k2tLXNdKa6Yntv0mzVzSse9/5mhnFKU6A6eDnjOApcaYj8Pt4Nm2DDjb4bYopZRyQtMO3/MwQY//mJ6CMEFPc0H3wBUNNcm2LGXSnemJpw3pFq0ZTrZTUlSfraVVq5wq1dk4HfTsDXwbw36L8BVAUHESkXIRGSAiA9CS1UqpdGv2G38TQ6YnP0zQ05ZfAv5lq13UxS18IQNnrud0gBPP+eNtS/DuqcxQpUphvo59Vaqzcfr/+lIglv4JDUBXh9uSyyYAKzyPIVqyWimVVv7d24oSH9PT1m6gpNy3omFbKlqXEuEzPem7XjKBUGorv2Xu2lGvFeN+BWHeg0qp3OV00LMaODKG/Y4E1jncllw2CStTNhBYUlFhP0+GUko5Is4xPeEyPcYYKO3pW+Gi7m3hq7c5VMjAdl1mMibxXjW4glp6J0KN7WoFYaqcbq1r5sLHPuasB2ezdFOt7T5KqezkdNDzP2CAiPw+3A4iciXWzfpbDrclZxljaowxK40xKwEtWa2USq8Ygh7/MT35Yv8Z1W6A0nLfChdletJZmhpSP09PaMCURAlrF3ZXi1e4bOO9b3/HB0u28OXqGq545os0t0op5SSnS1bfCVwI3C0iJwOPYBUtAKui22XAD4Adnn2VUkplmxRletqCMz1ZMKan3aFoyD7TkxlJj+lJZ7GHiFt977tw5bFfnre24/m3GzTTo1QucTToMcasEZEzgZeBH2IFOP4E2AL8RCcwVUqpLNTeHvc8PeHGU7Sb4DE9NSloYGqEu2937Hbe5sTJTU4aeTmZc8W73VFJXjtMPK6UygFOZ3owxnwgIkOBXwInA/08m1YD7wD/Nsa4pw+DUkqp2LXUEXCnWdzddre2GEpWt7cHj+lxz5+GcNkK58b0pLZ7Wyalst3RJjBNtuudpGKGVKWUKzke9AB4gpo70S5sSimVW5qCugAV2xfibA2YnDTGMT2u6t4W3/pk2QcK2TI5aZZGZ0qpnKYj3pVSSiXOP+jJL4aCYtvdYsr0hFRvc0+mJ2xGJ53V27K1ZHUWBUGa51Eqd6Ul0yMiFcAFwFHArsBMY8ydnm37YxU1eMcYU5+O9iillEqRGMbzQIxjekLm6alJsnGpE75ktTPXs52nx5lLRZfkvDxpnacn2Wtp1KNUznI86BGRnwD/xpp8VLA+Ptf67dIXmAqMA55yuj25SETKgXLPYmF7e3v4nZVSKpViDHoCMj1hxk1Y3dvcmekJX8ggO8b0BJ8vteWvg7cHLWdR0KMxj1K5y9HubSJyDPAM0Ar8ASvTE/yZMhPYDpzjZFty3ARghecxpLq6OrOtUUp1HgFBj/14Hgge0xOpZHW5b4WLxvSEu5lO5/w96Sz9HHDdjFw1MVrIQCkVjtNjev4MtAOnGmMmGWM+C97BGNMGfA4c4HBbctkkrAleBwJLKioqMtsapVTnERD02Fdug9jG9JiQMT01rilZFq57m1PNS3X3ttAuZ6krfx31WglfKf3CxTwPvruU426v4qH3ltnvoJRyPaeDnmOBOcaYz6PstwHY3eG25CxjTI0xZqUxZiXQEq4yklJKpVyM3dtaE5mnx7RB885kW5gS4YOe7ChkkIxkf8dUvkbR8jCSZAc1u6O317dw1/++Y21NA7e/+S11Ta1JXUMplRlO3x13ATbHsF/P6LsopZRynViDnhgyPW3tQElQtqhxezKtS5nwJavTl+rJVPe2eGVTtbZgdt3bttY3ByzXNmrQo1Q2cjroWQvsH2kHsT5hDsAaj6KUUiqbNO3wPY+xkEF+pMlJ8wuhsItvpUuCnnABh2MxT4zrEj1ffPP0xHmtDHZvS3pMTxquoZTKDKeDnreAoSJyXoR9LgX6AdMdbotSSqlUSyDTk59v/6enxVt5sqSHb6VLgh43TE6aJYmeUFnUbrsxPVraQKnc4HTQcztWZbYnReQOERnuWV8mIoeKyM3A37G6wN3ncFuUUkqlWiJjesKMFm9t89wduzDoCZvpcapktV33tmSulcTcOfHOuxOaVUpf1JPsmB4NcZTKXY4GPcaYNcBoYAtwDTAb6/PwXOAz4C9ADXCmMWaTk21xIxEpFJG/iMhyEWkSkZUi8qdMt0sppWIWY/W21hi6t3VMYBoQ9Oyw3TfdwmV00tq9LYsyJk5xuqR0LKfXfwelspPjk5MaY+aIyFDgF8CpwACsYGsN8DbwsDHGHV/lpd9/geOAm4ClWCWne2e0RUopFQ//6mqxTk4aJujpCIz8gyeXZ3qcKmSQ8pLVwZOTxnG2eDM3wa9VtgcJwYFQlv86SnVajgc9AMaYWqy5ZCal43rZQERGY03IepAx5lvP6lmZa5FSSiUgxkIGsYzpabXN9Lgj6HFHpic7b7ezqdVh4nGlVA5IS9DjT0S85alrTLZ+gqfGeKDKL+BRSqnsk8iYnrDd2+zG9NQk07qUCZfRcS7TYzemJzOSzdxk01/65McEKaXcKi2zWIrImSIyQ0R2Yo3v2QLUetad5fC1DxeR60RkioisEREjIlE/gkWkVERuFpHFItIoIutE5HER6Zuiph0FLBGRf4rIThGpFZGn/YJCpZRyP/+gpyjGTE/Y7m1uzvSEK2SQRsnUMUimZnWy13KJRIcDBQdCnfv7WqWyl6OZHs8cPI8B4/CVRKnx/CwHTgFOFpH/Ahc7lPn5KxBXYCUiJUAVMBxYD7yKNRbpYuBHIjLcGLM8yXb1wcr2zMcq7LArcA/wBHB2kudWSinnGRNYaCDZMT1urt4Wbn0ab4AzNT9MsvFSrO12Q47F4ToJSqkMcrp725VYN/brgFuAZ40xOwBEpBvwc+AG4EKsm/9JDrRhDrAA+NTzWAkURznmL1gBzxxglDFmp6fNV2EFJo8DI707i0g5VhATSb0x5nu/5Tysz/izjTHVnvM0Ai+KyBBjzJIYfjellMqc1kZob/Et+wcrQTq6rgH5eWHm6XFz0BOue1u77eoUXC+110pjoie0aEIWJUY05lEqdzkd9FwG1AMnGGNW+G/wFDd4RETeBr7y7Dsp1Q0wxtzhvxyt3KWIFAFXeBZ/6w14POe6V0TGASNE5HBjzDzPpvOAf0Vpynv4BUrANmCZN+DxmOX5uR+gQY9Syt2CA5IIQU9bu/+YHvt9fN3b/Kq3NbmkZHWYgMOxeXpszpux2CHJMTxZFPPY3iOEVG/Lpl9IKdXB6TE9A4GZwQGPP8+2mZ593eA4oAdWQPKFzfaXPD/P8K4wxjxkjJEoj5FB51lE+C+VHPruUCmlUsg/6MkvgsKSsLvGNk+PezM94QsZOHM925LVSdxtp7KMtI5psfy/6QsZ+pc3+dsbizLdFKVUDJzO9GwGmmPYrwWruIEbHOz5+XmY7d71ByV5nTeAG0RkV2OM93evxPpS7OtoB4vIN2E2Daqrq6OqqirJ5sWvrq4OICPXVp2LvtfcofuO7zjC87w5r5QPI/x7rFvn+1Ow+vtVtvusXrOWqqrNdN+x1Hfe2i0Rz+s073vt2wVf2W5fv349VVXVttuSsXRFS8i6BV99RcHGhQmdb/v2poDlL+Z/QfPq/JiO3bgp8NjPPpvHtqXhvzP9Zl1rwPJ3335HVf2yqNdpam6K+v90Y2NjxH02b94Udntzk+/8a9cG3pp41zc2Noas31wf+D3knDkf8Xm+8OgH1r4Pv7+cA/PX0aUwuc5x+rmm0iGb32fetifK6UzPVKAyUkUyEdkF62b/FYfbEqu9PD/XhNnuXd8/yes8jFXU4VUR+ZGIjAf+ATxljFmZ5LmVUspxBa2+P0AtBWUR9231Sw4UhLk39CZ6Wv3OVdBa54r+ROFa4Fimx25d5l+GhKSz2U5cy657W31L4JWa2hy4sFIqpZzO9PwFOBaoEpE/GGMCwkoROQm4G1gG/NnhtsSqq+dnfZjt3r/y4csUxcAYUyMilViBzgue670AXB3j8fvbrReRb8rKyoZVVlYm07yEeL81yMS1Veei7zWX+GprR166rGefiP8ez6/9DDZuBGDw4EG2+1T02o3KysNg5yb4zFqXZ9qoPGE4FEUOqpzifa8dMGA/+DK0A0Dv3r2prDw05df9dtZSWPJdwLoDDzyAygN2T+h8f/92Nmyv6Vg+5JBDOGFIr5iOfWn9PNi4oWP58CMO57C9ws+usHXeGvj6y47lffbZh8pjB9jvPGN6x9PiomL795DfPiUlJaH7+G3v1asXlZVH2G4rKvad/+2aBbB2dcc27/qST6qgsSFg/eqt9fDBux3rjj32WKu75uxZvnXHHcvuPUrtf8cY6eeaSodsfp+VlSX3d8DpoOdVrO5thwNvi8hWwNuvYS+gwvN8LlbGw/9YY4w52eH2ZZQx5jvg1GTP46keV+5ZLGx3qpyQUkr58y8yEKGIAQSWrA4/psfz2VXcPXBDQ03Ggh6vdM/TYwwI7ZyUN5/VZjeWmD0zlukJKUwQpR2ZHPOjk4sqpcJxOugZ6fdcsIKcCpv9jrFZl6lPTW+1ti5htnv/8taG2Z4JE4CJ3oXq6tT3L1dKqRD+RQaiBD2t8czTU1gCBSVWSWzvdXqkal7oxITrxuZU9zaAqwte4LcFr9Fs8jmt+c6k/ijGG7ikUrYXPtDqbUrlBqeDHrdUZIuHdy6dPcNs9663H4mbGZOAyZ7nMyoqKoZkrilKqU4jIOjpHn4//AIaoCDcPD3+EURpT6hdbz1v2JZwE1Ml3I27Uzf0xhiuKHgNgCJp4w8FL2LMaEeuFb0tIWsi7x/X3vGJNnlopiZwVUq5n6NBjzHGTYFBrLwdkQ8Ls927fkEa2pKQvK1L4fa9ou+YYie0ttJc1BMqboCDf5b26yul0qwx9u5trX7dbvPCZnr8uua6LOgJ270tTSWry6llm6YYlFL+GnfAG1dbXYBH3w3l6b/3yyZOZ3qy0WxgOzBIRA4xxswP2n6u5+e0tLYqsgn4dW/DtGdkbotCoLC1DqZeBms/g9Nug/zCtLdDKZUmcXRva4unextYQY+XG4KeMEMlwwVDqZaXZA4jmexL3FdOsCtdKl5JJ8b0BE9YajA6cki5wwf3wILnreev1MP41zPbHpdztGS1iPQWkRNFpHfQ+kEi8pyIfC0ib4jIcCfbEQ9jTDNWRTWAB0WkY/SsiFyFNT/Pe8aYeZloXxiTsLoSDgSWZLYpHp88Av8506rCpJTKTf6FDIrjGNOTH657W1Cmx8sNQU+6Mz1By3liXDM2Jmohg6DWu6PVidMAR7nWJ4/4nq/8IHPtyBJOZ3quA/4P2A/YCCAi3YEPgd2wPkuGASM8WZWU37CLyGjgr36rijzr5/qtu8UYM91v+VbgFKxy20tE5AOseXmOxppw9ZJUtzOV2nvsBb96Je3XnTf3Q4Ys+zfddy63Vnz/ETw8An72X9jziMgHK6WyTzyFDNqyO9NjPP/9R+EDnJD3Fbe1juX5tpMcy/QEn1aSDR2CThhPAJXsrxjrtVIRXOiYHqVUOOmo3rbQGLPYb914oDfwDHATMBq4F/gD8GsH2tALK1gJdnTQPh2MMY2eOYT+BJwPnA1sxSoW8FdjTLiJSzNlAv7V27bXwe4Hp70R23tU8/nBtzFy56vw5bPWytp18MQPYPQ9cNhFaW+TUspBCVZvCzempyV4TI+XG4IeY9hPvudH+R8DcEfho7zZdiSG3lGOTPB6QTfvebS7pmpYtGa4pZ1OMSb7s1dKdUaOdm8D+gLLg9aNBlqBCcaYJcaYSVjFA0Y40QBjzGRjjER5TLY5rsEYc4MxZrAxptgYs7sx5mIXBjwQ1L2tosKuKnh6tOcXw9n/gh/cBXmemLqtGV77Hbz+e2htzljblFIpFlDIIHL1tja/rmsFYf7ytAZXb/NyQdDTbqCnBM5UcEb+XAertwUuW2N6Er9WcmN6krtWOjkzpiflp1RKZYDTQU83oN67ICL5WHPyzDPGbPHb71vCl4hWURhjaowxK40xK4GWvDDlYNNGBI6+DC56Dcr8kmifPQ7/+RHUbgh/rFIqeyQ8T4/9Z1RI9TYvVwQ9hryg2/k9ZbNj8/SEjOnBuCaDEm87UtlutwQgds1obWvn2U++598fLKehuS3tbVJKReb03fE6YF+/5eOBrsCsoP0KAE0BJEhEykVkgIgMAArbw5UZSrcBx8Fl70Hfw33rVn9sjfP5/uPMtUsplby2Fmip8y2nYExPi4vH9LQbKKQ1YF0+7c4VFwg6r2Swe1uyQU46x9mk41rhrvDOoo38acpX3Dp9Ef/+ILiTi1Iq05wOeuYAB4nIBBE5EKtAgCG03PN+wFqH25LLJgArPI8h1dXVmW2Nvx59YfwbcOgFvnU7N8Dk0Vbmxy1fXSql4tMU2NWL4mjd26KP6WkNW72tJt7WpZwxhqKgoKeAtvRmepI5XwpnDHVLFbl0ibXL3JXPze94fs/bi8PvqFTKuCT1mSWcDnr+BjQB9wDzgeOAWcaYj7w7eLITwwD96j9xk3DJmB5bhSVw5j9g9L2Q55m3p73FGuMz7f+gtSmz7VNKxa+xxvdc8qCoa8TdWwPG9GRh9TbbTE+bY3kFuzE96ZoTKFR81w0pWZ3lMVKs4WZpUb7DLVFKJcPRoMcY8w1Wl7angLewMj1nB+12GlYhg1ecbEsuc92YHjsicOQvrImzuvpVO/r8SXjih7BdE31KZRX/8TzF3SDK505bLPP0hBvT01xrdafLoHZjQoKeAge7t4VWb0uuZFjo3DmpK4oQsj2ke1v6OFHIIFi4f/M8tww4UkrZcvzu2BjzuTFmnDFmtKcaWm3Q9oeNMYcGzZOj4uDaMT129hpujfPZ8yjfurWfwSMjYNVH4Y9TSrlLQOW2yON5IHC8TthMT7jqbZDxLm7tBgrFJtOTniE9SJLV21LZlnQf7y8dQU0isj2bpVRn4MKUgErABNw6psdO992tjM/hF/vW1W2G/5wBnzyqfz2UygZxVG6DwExPfizd24rKfN1hIeNd3GzH9Ei7c13OQgoZJFe9LZ0fq5n8BHciMNQ/SUrlBg16csMk3Dymx05BMZwxCc54APKLrHXtrfDG1fDKb6ClIaPNU0pFEdC9LXrQ4z+mJz9MN6AW/yy1iKvG9dh1b8unzcFxNoEZ+zzaU3o7H0+zQ2ogxFvNrRNP5bl0Uy2PfbiCTTsaM90UlYu0S2VcNOjJAVkxpiecw8fBxW9Ct9196758Bh4/HWpWZ65dSqnImuLr3hbLmB5jAvdzV9BjVWvzV+Bg9zZptyuP7cy1Ui6ooelsd1rG9BDbvWZTaxtj/jWHW15fyMWTP3W8XaoTypoPBXfIortjlbP2PMIa57PXMb516+db43xWfJCxZimlIvAPQqIEPcaYmMb0QIRiBg1b425iKtlXb3Oue5uYwGslO6YnpLhAPJme4CAmSjty7TYs0d/n0xXb2N5gFeD4Zt2OKHsrpZymQY9yh2694aLX4Mhf+tbVV8OTZ8Gcf+q3GUq5zc6Nvuddd4u4a/BcNuHG9ECEYgYZz/QYiiR98/TkB2V6DKIfgzGIFJCluyNQ5kqMK6XsaNCTA7KqelskBUUw+m4465+QX2ytM23wvz/BlMuguT6z7VNK+dRu8D3v1ifirq1Bn0kRgx7/TE+XXXzPXVDIwC7T0+ZQ1CMmsCudQZKbnDTKclInC94cklXKrZv/WH8dHW6hlLto0JMbJpBN1duiOXQsXPIWdN/Tt+6rF+DxUbBtVebapZTyqV3vex4l6PHv2gZQmB+pe5tbMz1QaDOmx7HubUGZnjbyMhY8JHvVlJasjhJIpKekdWy/UHBbci34UyrbOBr0iMi9IvJXJ6+hgGys3hZN38PgslnQ/3jfug1fwSMjYdm7mWqVUsqr1q97m38hEhtNLYHBQlGYQgYQlBUqLfc9z3jQY1+9zbFMT1DQ055k97ZU3nBHn5w0eAxQ6mQibojltYulWRrzqJTTdGJcnM70XAEc5PA1Or2srt4WSddecNErMPw3vnUNW+Gpc2D2A/oXRKlMaWux5tby6to74u7NbYHd24oKIgQ9bs30tNvP0+NY0BOUVQJJbeASx7niL1GdOekpjx3bjWbw/aj+xVIqs5y+O16ThmuoXJZfCKf/DX78CBSUWOtMO7z9V3jpEmiuy2z7lOqMdm4i4BYuSve25lZf0JMnoSWr/au5ha/eltmgpy3N8/TktdtVb8tO6ezelh6xdm8LpIUNlMospwOSV4ARItLN4euoXHfwz+AXM6DHXr5130yBf58KW1dkrl1KdUY7/YoYlPSAwtKIu/sHPXZZnny/MT5urd7W2m4oDKne5mQhg8Br5aV4np54ThXv5KQhhQzSGK45MaYn4dc9ONNjYGtdM1O/WMPm2qak26WUio/TQc9E4HvgDRE51OFrqVy3+8HWOJ+BI3zrNn1jjfNZ+k6mWqVU5xNQuS3yeB6AJv+gx2Y8j39hA7dmetrbTUghg3wHS1bnhQQ92Zvp6QzsQq2QQgYYzn90Lr9//kt++vAcLWygVJo5HfS8CjQBxwGficgaEflIRKpsHjMdbkvOypmS1bEoq4ALpsCxv/Ota6yBp86FD+7VcT5KpUMcldsgMOgpLswP2V7oFwiFHdPTuB3ag8e5pE9be+jkpAUOTk6aF/S7Ciapm+RUFkGId3LSdH4sZyo0tLtqcFe8rXXNfLuhFoAVW+pYvkW7Z6tkuaK/Z9YocPj8I/2eC7CH52FH71YTNwErqwZA1pesjia/AEbdCrsfAq9eAa0NgIGZN8H6+dY8P8VdM9xIpXKYf+W2rtGDnuYomR7/MT2B1dt6Bu7YuD1w7p40Snf1trygrFIeqf0yy8lAxMnqbdl8ixf8Xml3Kk2olLLldNAz0OHzK8skYLLn+YyKioohmWtKGh14LvQaCs+NhRrP/D0LX4XNi+G8p6FiUGbbp1SuijvT47uBL7YZ01PgV3EyYJ6e4u4g+dYkxWB1cctQ0NPWHhr0FNDm2I2rtLcELOdhksvWpDD0iLsdOZaBj/XXyQtK9YSOdVJKpZOj3duMMavieTjZllyWsyWrY9HnQGucz6BK37rNi+CRk2Dx/zLWLKVyWpxjeqIVMijwL2TgH/SIuGaunjZjKJLgTE87bU51bzPBmR6TdFe6Y/O+5pL8NynDkx3PQemZnDQ27qg0p5TySsvdsYhUiMiVIvK0iPxPRK7127a/iJwpIl3S0RaVg7rsAmNfguOv8q1r2g7P/AzeuwtyeYyTUpngX72tW+Q5eiBwnh77TI9fIYPg/1/9u7jVb429jSnW1maT6ZE22hz6eAmenFQkuVzNnm1reKboNm4o/C83Fz4R17HJZijSGV45MaYnVRmaHEt4KVfQN1U8HA96ROQnwHLgXuDnwCnAvn679AWmAuc43RaVw/Ly4ZSJ8JP/QGGZZ6WBd2+FFy6Exh0ZbZ5SOSXlmZ4whQwAynr5nvtPiJpm9vP0OFjIwGZMTzKX+nnTix3Px+R/6PCYnsjLuSCWjFK0PXLxdVHKzRwNekTkGOAZoBX4A3AUoZ8DM4HtaNCjUmH/s+HSd2CXvX3rvn0d/n2yNdZHKZWctpbA4CPO6m3Ru7cFpU4Cgp5NsbczxexKVhc4Wcig3a5kdeLXyjeJV76L97rB+3eGYtt2lfWCu7d1htdBpZv2oYyH05mePwPtwKnGmEnGmM+CdzDGtAGfAwc43BbVWfQeBr98F4aM8q3bshgerYRv38hcu5TKBf5ZHoCuMXRvi1q9za+QQXAQ0XU33/Od7sr0OFrIwGZMT3KZgVQWMnDod07B/Zsjk5MGB3Ep+vU1CFIqvZwOeo4F5hhjPo+y3wYgeh8JpWJVWg4/fx5OvNa3rrkWnvs5vHubjvNRKlE71vqed6mAwtKoh/gHPcUFNvP05EXK9PgHPRvJlLZ2Q7EEVlTLp82xQgbBQY+kumR1PPvG+Ss62b1NXFodwP53jFy9DeC9xZu55fWFrNA5e5RynNNBTxcglq/mekbfRak45eVB5fXws6ehqJtv/Xt3WMFPQ03GmqZU1tq+xve8x54xHeJfyMCue1t+XoQxPV1d0r3NGEpoDlhXQLtj3dvyjV3J6sSvJanM9Di8fzKSzZ7EElOlKkOzdWcz4x7/hMc+XMFFj3+cknMqpcJzOuhZC+wfaQexvrY5AFjhcFtyloiUi8gAERkAFLZrFiPQfj+CX84E/+mLFr9ldXfb9G3m2qVUNvLP9HSPLehpavFlLezH9Pieh1RvK3NJ97Z2QylNAevyaXOukEHKu7cFiudccWd6kjw+k9LZ1ncW+YL41Vsb0ndhpTopp4Oet4ChInJehH0uBfoB0x1uSy6bgBU0rgCGVFdXZ7Y1btRrqBX4DP2hb93WZVaBg4WvZa5dSmWbgExP35gOaYqS6SmMVL3Nf0xPBjM9bW3tNpmedBYyaE8yv5DKiCnK5gwGOY6M6bH5fWLJ9ri0J57KJfomi4vTQc/tWJXZnhSRO0RkuGd9mYgcKiI3A3/H6gJ3n8NtyWWTgIGex5KKiorMtsatSnpYXd1G/tm3rnmnVdJ65s3Qnnh1I6U6je3+mZ7Ygp7AMT1R5ukJHtPjH/TUb4W2wGAgXaS9mXwJvNHNF4Mx7Y4M7A8d05P85KT+4umilWx3LncO2Le/WYype5tdEBTDOq3mplRmORr0GGPWAKOBLcA1wGys74jOBT4D/gLUAGcaYzL3FV6WM8bUGGNWGmNWAi15eY5Pv5S98vJg5B+tIgfF3X3rP7gHnvlpRic/VCor7Ih/TE/0ktV+1dtC5unxC3owUL8lpmumWn57k/36JOfPCSfP2JSsdsk9crSb9ZDtYXZPJFiMOvdNzIGE/X7pnL9IKZVejt8dG2PmAEOBq7C6u30LLAaqgOuAocYYHcGn0mvo6VZZ612H+tYtfQceOgFWf5K5dinldokUMvDP9NiWrI5Qva2oCxR19S3vzMz3YwVt4YMeJyq4iV3Qk8z5kmtOUmIOQ2LYMRNxg90YpZAKdTYt055HSrlLWlICxphazzw9o40x+xtj9jPGnGqMudMYsz0dbVAqxK6DrXE++53hW7djDTzxA/joH/q1nFLBWhqg3m/MYALd22wzPZHm6QFXTFBa0GY/0NypcT2hhQzak/pMkqBjHS1kEOP+bvyITWWg4sbfT6nOzNGgR0R0cIlyt+Ju8NP/wqhbQTwlpNpbYcb18NxYaNiW2fYp5SY71vmeSx50i216tWjz9BTkR8j0QOAEqMGTo6ZJQXuj7XqnKrhJUCEDScHImlSJPwhK3bWjxSTJFjKILdsU+m+RSJZKgyKl0svpTM9GEflSRB4QkTEaBPmIyCwRMWEeOlFrOonAsb+Di98M/Ob6u+nw8Imwdl7m2qaUm2xf7XvebXfIL4jpsKbWaCWr/YIeu6yJfze6mtWh29OgMMyYHqfm6nG8ZLVD+9oeH25MT5LntT9n6s+aaNCm3duUcheng575WPP0XAG8AGwSka9E5B8icq6I9Ip4dG77DXBM0GMesMAYsz6TDeu09joafvUBDD7Vt67me3jsNJj7kH4tp1QCldsg+uSkAd3b7DI95f382rAmdHsa5LdFyPQ4MDVa6Jie9oxW+xokazkz7yOKaY76UehENbt0cbJ7Wza/Lkrlgti+pkuQMeYIEekOnAiMBE4CDsYKhC4HEJFvgVnALGPMi062x02MMQv9l0WkJ3AQcGNGGqQsZRVw/gswexJU3QqmDdpb4K0/wqrZcNY/rNLXSnVG/hOTxjhHDwSN6bEpZFBcGCXo8c/0bP8+5uumUpGxD3oKHCpkEFy9zSqPncwZg+/AY4/UurVt5z9F11MqzUxtOw44Npkr+9ZnaRBgFTIIGiMVy3HONEcpFaN0VG/bYYx53RhztTHmcGAX4EyseXm+wKrs9mvgWafb4nI/BgqB5zPdkE4vLw9OuArGTYOufXzrF70GD4+AdfMz1jSlMsq/e1uMldsgeiED/0CoqcUu6NnL9zwT3dtMOyc1zrTdlC8OFTKwmTcspUFCe+zzHY2qf51SsSZm/XH+7Kg376EZjjD7BS3HlGWJso8jk5MmeJx2b1PKXTIxoUszUO95NABtWB9jjnw8iMjhInKdiEwRkTXecTMxHFcqIjeLyGIRaRSRdSLyuIjE/vVmfH4GzDPGLHPo/CpeA46DX38Ie5/kW7dtBTx2Knz6b+3upjqfHX49b+Po3tYUZXJS/3X++3bw7962Yy2O9Cezs2oOR332f1R+MIYTmj+03aWIVkcKGQRneiC5oCf4D2zw5KeRFBv7ynXhhAzYT2WOI1rXugg7pLTrWvByDP822t1NqcxytHsbgIiUYOXCR3oeRwJFWJ/Bq4Bn8HRvc6gJfwXOiucAT5urgOHAeuBVYABwMfAjERlujFmeqgaKyK5AJfDnVJ1TpUjXXnDBy9bkpe/eBhhoa4bpf4CVs+HMB6wKcEp1Bv7lov0rqkURNdMTEPTY3Iz38At62pph50bonoZ6Ly+Op2t95GpxJTQ7kumxDUriCFSiscskhd03pNx1an7fznfP3+l+YeU4TSfGw9GgR0TeJzTIeQ7fGJ5VTl7fYw6wAPjU81gJFEc55i9YAc8cYJQxZieAiFwF3AM8jhXA4VlfDvQJOUugemNMuM7oY7D+LV6Icg6VCXn5MOJa6Hc0vHyp78bvmymwYQH85D/Q54DMtlGpdNi52fe8LPY6NE1Rgh7/Mta2mZ7irlDa01dCfvua9AQ9O6OXx3Yq6Mm3yfSktnxbPAFUfNeNtXtbQlJ2j5fam8VEfkXR/m9KpZXT3duOxwp4vgF+CuxtjLnYGPOfNAU8GGPuMMbcYIyZZoyJ+hdMRIqwqs0B/NYb8HjOdS9WADVCRA73O+w8YFGUx5MRLvtTYG66XhOVoL1HWN3dBpzgW1e9FP59Msz7T2f82lJ1JsZAnV/Q03W3mA+N1r0t6pgeSH8xg8YdMe1WKk2OdG8rMM2hK5PK9AS2UeLI9AjxdSeMtTubE9XoYh/TE/u17YK4RP7JtXubUpnldNDzGlADHIA1QH+biLwmIld5xtq48WuO44AewDJjzBc221/y/DzDu8IY85AxRqI8RtpdTER6AyPQAgbZoVtvuOhVOPFaOr4pbG2Eaf8HU38NzXUZbZ5SjmmssSoZesWR6Wn267JmNzmpf/U22+5tAN39gp50TFC6bUVMu5U6lOkpMjbzAiVxHQkOeuIIoCSo0lu8rUjnzX2mynonNDmpzT7rdrbz3YbaVDRJKRXE0aDHGHM2sCtwGHA18B5WUHE38Amw1S8IOszJtsThYM/Pz8Ns964/KEXXOxfr36HTlOvOenn5UHm9Ndany66+9Queg0dOgk2LMtc2pZzi37UtrwBKymM+NNo8PUXRChkAlPn9v+afcXLKVvug53fNV7BzF1931lKakolFwrKfDDWZAg6JBz158WZ6Ynw9sjXRYQVWqW/8wuo2/vpRE6ff/z5vL9yY8vMr1dk5XsjAWF/xzPc87vNkdw7GV9hgFDAa6xPE8fbEwFsbNdwMeN71/VN0vZ8BHxpj1kbd04+IfBNm06C6ujqqqqqSb1mc6uqsLEcmrp0ZQtGBt3PAonsp3+GZdmnLd7Q9dCLfDf4VG/pUZrZ5Oazzvdcyr7zmG7zfTDUVdGP2rFkxHWeMCeiyNu/Tj1lLY8AgyCWLFuL9+N+6vdb233XvLfUM8Dxft2QB3+Y5+2+/1+qZDA5at8bsyrT2Y7mu6V26etaVSDNz5s7l+66p/Q6xwiZrvHb191RVxdbtLlh+0PxHS75bRFFjTUzHtjQFzlG0YMFXFG5cGGZvWLGiJWB59Zo1VFVtCtmvpS0wcGhqaor6/3RDfX3EfTZv3hx2u//5164N7D7oXd/Y0Biyft3OwNfu008/ozgoYTl37lyamwPPOe+zeUH7fBywvGZN4G3Gg/ObMAgY+OWTn/H4qFLb30MprxNaWyj0W47lb2I2//30tj1RmShZ3Q8rS+J9lOBgyeoEeP+W1YfZ7n3Fky7ZJSJ7YI170q5tWaq5uIIvDr6Zlf3O6ViX397MsMV/Z9/v/k5em923tUpln8KWmo7nzYXlMR/XZgK/Ey+0+avjvy7ckJ7mIt+kwEV+bXFKUfO2kHU7jXUT2pbnq4XjVKanCJsxPUlkF4K7t8WTvQk+Nl5hJydN6qyec6Ssklzm004NbW65DVJZw5WjRNwrHSWr98KX1RmJL0MiWHP2fIjV7W2W021xG2PMOhIMPI0x+3ufe6rHlXsWZ5SWlg6prEx/lsH7rUEmrp15p8Lin8PUyzoqTO2xsYo9zAaruluvfTLcvtzSud9rGfLJMqskC9Ctz94xv/Z1Ta3wzv86lk868QTK25tY7LfPEYcfAgu/BiCvoMj+3F9thWWPA7BriXH+3776SQjKv89pHwZAt4o+4Bl2UUozhx9xJAf07UEqrfqoNaQ325577EFl5TEJnW/uhzcHnG/IoIFUnnh8TMf+7+OHwO/7mwMPPIDKA8JXz5vf+h0sX9qx3LdvXyorDwzZr7GlDWa+1bFcXFxs/+86Y3rH0y5dulBZObJj2RgDb7/RsdyrVy8qK4+wPdb//G/XLIC1voluKysrERFKPq2CxoaA9Us31cJH73esO+KII+hSlB+w7uijj6boy7nQ4gtWDz/icPjko47lo44+CuZ80LG85557wurw9Yv0801F9UkB+BV6jOU9k81/P8vKypI63umS1csJDHKasIKcWViBzkfGmEb7ozPGW62tS5jt3lfcTSMNJwATvQvV1dWZa0lnts8oq7rbixfDmk+sdZsWwiMj4Yz74aCfZLR5SiVlp1/3pLiKGATeuRcV5BGcxIhasjr4mukY01PrG1NRV9qXKQ2H8ECrVb/GFPq6HTlSva2lkf6toWOK4q2i5i8/6Ni4Chk4VBzABcmVDsaE/9I8Ve10tJS36pz0PRQXp7u37QF8ANyCNflmT2PMCGPMRGNMlQsDHgBvLdQ9w2z3rndTeelJwEDPY0lFRUVmW9OZ9dgTLn4DjrnCt66lDqZcCtOuhBY3vuWVikFAueo4gp42m6AnSEDJ6nDV24KDHqfvGGvXdzxdMugS7jTj2EZ3a0WBL+hxZJ6e+U/ZrjbtyQQ9ga9rMkFPtJc+pEqZK2/MEu8WZPfrxPIrhgQ9eseqVFo53b2thzF2dTdd7UvPz3DV5LzrF6ShLSob5RfCaf8P+h8Hr/waGrdb6+dNhjXz4Kf/gYpBGW2iyrz2dsObX2+gomsRw/fOgi8q6hKcmDRokE5RfuhokuBMjzEmdOJG/3mBWhuhqRZKusfcjrgYE1AWu7moJ23+d6z+mR4cyPTMfiBMu5IIeoKDnDjm6ckjmfmBIo3pSf51S/yld2acUuRjgirouWYos8q49nbAWNVhlWOcLlmdbQEPwGxgOzBIRA6x2X6u5+e0tLUougnACs9jiHZvc4l9fwi/+gD28IufN34FD4+Ar6dkrl3KFf725iJ++8znnPfIXD5engX/zwZ0b4t9YtLmNt8Nc1FBnu0s9EV+lQyMCa3qBUBpTxC/P1lOdnFr2gGtvnEdTUW7BGRzTKGv97M1T0+Kr1/aM8yGDGV64owsYu3GlapY8bS8T1lYfDGvFv2FkvaG6AfYtSXBbR372OwULaTRTI8CrPL4kw6EOwbC9x9H39+fxs1xSVv1NhE5RkSuFZH7PY9rRSSxEZkOMsY0A//wLD4oIh2jpkTkKqyKc+8ZY+bZHZ8hk9Dube7Usz9c8j84+nLfuuZaeOli+O+PYfUnmWubypjvNtTy+OyVHcufrQqtFOY6CXZv8x+jU5xv/yenuCDwL7dtF7e8fOji99lWtyXmNsRtre/jvS2viJbCboHZHP+gR5pS372ttNx+fVLd2xIf0xN82x/tt033zfzDRffRRZo4OG85J22P9QulJLq3GZPYZKRxviwNzW18vXa7I5PfKhd54xrYsQaatsPTOvbXSemo3rYP8F/AW07F+0ljPNs/Ay4wxixx6Pqjgb/6rSryrJ/rt+4WY8x0v+VbgVOAY4ElIvIBVkGGo4HNwCVOtDVRxpgaoAZARFry8jJRiVyFVVAEP7gd+h8Dr15hfYsMsKzKegyqhJF/gn5HZbadKi2MMdz8+jcBNzI7m1ojHOESiXZv8wt67MbzABTlB3bpaGptt58ToGw3XzvqQud9SZlFvkT+1vKDQfICbzwLA8f0pLx7W9iJX5MJegLfY/EFPUHi/n3t90/kVbPLFPob0PhtjGdK7b+ZE4HemH99xML1O/jRQbvzj/PdMn+7Srnl7/qeN23PXDs6Aaert+2OVaWtN7AOeBFYifVpMwD4CXAkMEtEjjDGrLc/U1J6YQUrwY4O2qeDMaZRRE4C/gScD5wNbAUmA381xoSbuDQjgkpWF7Yn8W2gctCws6DPgfDKb+F7XxlTX/BzMoy8ToOfHPf2wo3MXhrYnW1no8uDnuZ6aN7pW46ne1ssQU/Q+vAV3Hb1Pd/u0Mfw1hXwxdMdi1t2PRpjTMBcPOKX6emCA5mecDfQSQRXBcHjctqTeM9FGQ+UziplqTq1NU+PfUAVWoAgNlG7t0U50cL11hdkry9Yzz/Oj/GiSqmwnE4J/AUr4LkP2NsY83tjzP3GmAeMMVcBewP3ArsDf3aiAcaYycYYifKYbHNcgzHmBmPMYGNMsTFmd2PMxW4LeDwmoGN6ssMue1vV3S58BfoFxeLLZsJjp8J/z4HVn2akecpZTa1t3Dp9Uch612d6gsfP+AcfUfgHPcVhgp78PKEw33eL2NQS5qa6j99cL0tnxtyGuHz1IngnFS7rxaZdjw3tplTqm5OnQnYEFjlIhWb7ubElmUIGQVmivHgyPSG/Xmq+WHNiQtB0DXGIJbOTHVXslOo8nA56fgh8Z4z5g2esTABjTAtwDfAd8COH25LLJqFjerKHCAw6yRrrc+FU2DMos7NsJjx2Cjw1BtZ8lpk2Kkc8/uFKvt8aekNb6/ZMj3/QU9rTqlAYo1gyPRDjXD37nOZ7vuJ9aNppv18y/DNIB4yhraCUkLoK5QM6nvaXjUmVkrbVYh/0JDWmxyReyCBElOArkzf7mYorYhvjo1GPUpnkdNCzO/B5pB2M9VXP5559leo8RKzxPL+YARdMgT2PDNy+9B3498nw1Lka/OSIJ+es7Hi+W7fijuc7m1oy0Jo4BIznib1rG8Q2pgcCs0Bhg569joEST5alrQmWz4qrLTGp98uUd+8LQHDvNdNzYMfzUmmmoD7F44ua7YM5k1SmJ/GS1cG36tECpljno0loTE8Cx/iODX90PG0xJrZqbdGrtykFyb6rVeycDnp2AP1i2K+fZ1+VmAlo97bsJQKDT4ZfvB0m+HnbL/hxU9FAFY/2dsP67b7JaS86pn/Hc9d3b1s12/e8e3zfTwWUrA5TvQ2Cgp5w3dvyC2HgCN/yxq/jaktM/KvCebrxBQc9eaU92C6+OYKKd3xPSoXp3pbUPD3BJavj6qIWVL0tzjFMqcz0hGaRUhs62NVJiKkrm7FpWwzHxMqJroBKdTZOBz1zgOM8FdRsicgPgeOAj8Lto6KahHZvy34Bwc/L0PeIwO1L34Z/V1olLTX4yTp1zYGBzZ49fYPhXV3IoK0Fvnzetzw07Me5rUa/yUlLi8JPvFdcGEP3NoCKwb7n21bG1ZaItq+1Mqr+VeE8VeqC7zfzRdiQ36djuaRuderaAdBcZ7s6uUxP0JieOAoZhGR6ogRMsXbjcuI+PtHvveNrS2INT+b31arVSiXP6ZLVt2ON65kqIs8Dz2BVbwOrBPTPgfOwRkXe7nBbcpaWrM4xIjD4FKua29KZMOtvsNave9uSGdZjyCir2lvfwzPXVhWz4GxO7+4lYbe5ypK3fYFAfhEceG7k/YM0NPsyDKWFEYKeWLq3gTX3lde2VXG1Jaxtq+AfR/oKGHh1qQBqQjM9ebAtz/flUkFjirPrDWHmbUpiHE5yk5Mm145U3q+nrstYct2C7LrwRevelszrEKm6nFIqNo7eHRtj5gAXAy3AWOB14GvPYzpwIdAKXGyMmRvuPEp1SiIw5BS49B0Y+3JocLNkBjxaCU//FDZ8lZk2qpj5Z3OKCvKo6FrUsezqQgbzfeWbGfpD6LJLXIc3+HVVK4k56IlwU91zgO95qjI930wNDXigI9MTHPTk5wnb88o7lotSGfS0NEBrg+2meLuV+QsZ0xNH4BKcuZFoKYtYS1ZnNHsR+8VjzdBE786W+C+siZ4cFmXuKZU6jqcEjDFPAUOBW4BZwGLPYxZwM7CvZx+VIBEpF5EBIjIAnacn93QEPzNh7EuwR9AkdUv+Bw+fCNOvDv8Nscq4Wr9sTveSAroW+xLtTa3tAVXOXGPnZlj8lm/50AviPkVjS6yZHr/ubS0RXotyv0xP7XpoaQy/b6x2rLVf7xnTE1y9LT9PqM0v71guakph0DP7/oDFRuOrlCdJzK1TGDQ5aXzd24JvyuKs3pYFt+zxtNEav2NC1kW/RvQ14dQ1tfL0x6v4cnVNzMcopQI53b0NAM/cNhPTca1OagJ+r68WMshRIjDkVKvr25K3rW5v6zzFEU07fPoofDMFTp4Ih15o9cFRruGf6elaXED32iU8X3QzW003rmn5FXVNrRQVFEU4QwZ89YJvEstue1jVBuMU0L0t4pieGLu39dgTJN+TqTCwfTXsOiTudgU2siZ0XWEZFJYCoTe4+RIU9KQy0zPrbwGLtXShBGuW9rz2kJkfYhYc9MRTyECCb87jqPwWSSqCocTPkPpv1538vv7alxYwY+FG8vOE2X+spE+PkugHKWUjr62JopbtVqTeybJMab8rEpGenkfneqWdNQktZNB5iMA+o+CXVfDz5wMHdtdXw7T/s6q9rdViB27iP25nj6I6yl76OUfnfcsP8j/ljPw57hvXYwx84ZeEP/g8yAsftITTEHOmJ8bubfmF0KOvbzkVXdzsMj27H9zx1K57286C8o7l4lRlempCq8A14cv05BubLnixaGsNKWQgSQQu0SZJNcaQRzt7imcsWJjIJDg7Er6ktOGEvAUMkVTODZ5497ZEe+slU8hgxsKNALS1Gx6fvSLxE8Vi9aewKXQSZeWUNN4OtzZz5BdXc+wnv4KZN0fe96uX4K7B8NzYlH3RkWlpCXpE5EwRmSEiO4EtnketZ91Z6WhDLjPG1BhjVhpjVgJayKCzEIGhp8Plc+CUm6xvpr3WfQ6Pngyv/S6wBK/KGG+mJ492/lh/D+I3CeZA2eC+cT3rvoBNC33Lh4xN6DSxj+mJsXobpH5cj3/Qs++PYOSf4NzHO1b5Bz0iICLsLPB9uVTcvDX5NoBVQc5Pkymg0fiyfwVtCWZ6bMYriYmje5sJuimLVkXOGKYUTeTD4glMLPhP0vmc3+a/yn+LbueNoj/Rvy3+8uCHy3dRA6Z4A5LEApjUdPNraXOwK+zn/7Umx/7XcbD6E+euozLjm6mU1Xv+X/jw3sj7vvwLa462b1+HRdOcb1saOHp3LJbHganAKUAXYLvn0cWzboqITNbMj1IJKiiC4yfAFZ/CAWP8Nhj4/En4+2HwyaPQ5rKb6k7GO6bnyoIpHNwUOGfz7lIdUtI64/wLGPQbDrsODr9vBAFjeiJ0bysKmKcnyk2d/7ieZIOe9nbYsc63XPkXqyqi33xE/mN6CvKsP1V1BT071pU0VVvnSVbQmLw/tFwekOkpaE8w09Nqc1wc5a9DJyeNfGzf2gUckrcMgIsL/ocJ89rEGgJcU/gCAIXSxmWNj0fZO9D5+TN5ufgm3iy6jmHtS/y2pPaWw5j4z+jKqXdeu8L6adrglcsz2xaVejs3JHbc+i9T244McTolcCUwHlgPXA6UG2N2McbsAvQAfu3ZdqFnX5UALWSgAKvLz7mPw7jXodd+vvWN2+GNq+GRkbBqTsaa19nVNrYwMm8+VxZMCdnWW7a5b66e5bN8zw85P+HTJFayOkpXCv9MT02SZavrq8E/g9J9j5Bd/L9YL/Bk0muLdu1Yl29aoT4FGVW/oOcr2YfX24+hEb9MT6JBj02GKC+ektXB43+iBD35piVguaxte8zXiqY7tYFNiRI43Fb4GAAF0s51bf9K6JqxFi1wsntbRtQmeIOslEs5HfRcBtQDJxhjHjbG7PBuMMbUGmMeAU4AGjz7qsRMAFZ4HkO0kEEnN/AE+PUHcPrtUOybNZ6NX8ETp8OUy/SPWQbsbGzlrwX/9a0oKO14ujtbA6q7ZVxrM2z1Gzew1/CET1Wf6nl6ILXd23Zu9D0v7AIlPUJ28c/0FOZb3+e3Fnan1vj+DdmegvEmjTUdT7ditaPJ+I/pSbB7W0t9yKp45unJCylZHfnfpzmvNGA5XNBjjOHEvC+ZV/wrphbdQJmxn5Q14NpJdBHb1ThX3TKWogzZFvOoLBDcSappZ7QDErxQbrx7nQ56BgIzjTFhR915ts307KsSMwktZKD85RfC8Mvhd/Pg4KBv6Rc8D38/Aj76B7S12B+vUq65fgeD8tb7Vvzovo6nvWUrOxsSr8yVcttW+uZxkXzomfjHc6zd24oL/cf0xJHp2bYqua/QvROvQkeJ6mD+MVhhvvVnsyBfWG/85izy7yKXKL9Mz3a6AgRkegoTzfTMfzZkVTyFDEIzPZGPDQ6oIgVYTxbdQYXUcmjeUs5vey2GtqRKEnPmhHm/aR/9TmTdfHhqDLxzU2q6tqbKIyOc+buedWlKe04HPZuBWP6St2AVN1AJ0EIGKqyuu8GP/wWXzIA+B/nWN9fCjOutwar+3ZiUY4rqfIPU26TAKkLh3SZttO7cnIlm2duy2Pe85wBr3FiCEqreFs+YnqYdyc1P5f+6l+1mu0ub3x/8Ak+mJz9P2BAQ9ISZ6ycefqWzd2AVJgkY05No9bb37wxZFVemJyizE63cdXDXuXDXCr6NOsJEn2Q56sSoCYp0WrttIRXdjN38RNGPUVnqyTNh6TtWMYAlMzLdGp/qpfDt9Ey3wrWcnqdnKnCBiPQ0xj6vLCK7AJXA03bbVfzqmtp499tN0XdMsQWb29ilRL/rcqW9jobLZsG8yVaZSm83mi3fwZNnwbCz4bT/Z82BohzRpd53U1xXugfdS8ppzCulpL0BgLxUZApSpdpvwHeSc+A0xJrpiad7W9muVrXCFk93qG0rocsuEQ8Jq84/6Ollu0tgIQNPpidPWGf8sur+le4S5ddVbytW19SUZHpsxBP0hHQpi3K3HlwZLtYuafnEXxY3rklFA3Ix6f9bFS5DpLJQo1+XzW+nBXyJlXF+3WRDJFwzLDfeu04HPX8BjgWqROQPxpgq/40ichJwN7AM+LPDbek01tU0cPHkTzN2/U/rv+Denx7c0Q1EuURePhz5CyvAqboZ5v2Hjg+yha9Y31ad8Ac49ndQUJzBhuam7o2+oKehbE+6i7CzsBclTVYJ3vy69eEOTb8tKQx6mn0BTOwlq6Pc/IpYGahN31jL21ZC38MSa6B/97auYYKegO5t1k1DQX4e881gzmOWtWHBi3DKjVDaM+T4mBgTMLfWQrM3EDimp6A9dd1W4ilZnReU2TFRusblBQc94TI9QfdRBTEFPam6+Uqie1uY9dFuJ0MzQYm1QWOnMBa+apXcPvQC2P/sTLcmdqkuXizxz6cWVY686Zy+K30Vq3vbwcDbIrJZRD7zPDYB7wCHePZ5VUSq/B4zHW6bcsi0L9dx+VOfR79xUZlRVgFn3G9Nbtr3CN/6lnqougX+ORyWvJ259uWonk3/v73zjnKjOvvwcyVtr1573XvD2Ma9YZpteu81dAiBEIg/JyEkgUAIIQmEhNBCr6GX0KuxsbGxjW1sg3td975eby+S7vfHqIykUV1tk9/nHB1pZu6dudLele5v3uZPHtGQa1jUqjI7+fZlVO8O6dNimN3bOgxs1KlqY3VvS4vD0gPQvq//9a7oblFhMdexCuve5n/tsPstPe+7JnJAG7E3NFTBovjSKQdQMgdqvPV+FD9ivL8AS0+iiQwsiJaMwEyw6ImWvS3UvS22a9mJLsSCkyoEoxNcQMYrQEIyuhHdna0tU1nn5JevL+GKZxewZlcF1a0txX5DDbx5Jaz/Et66CupDk3c0GS31d9baOnGBkhvO4WhqS88k02sFtPc8gjnSYl8KfV00L+kOG/075jb7dfcfrOSAx/ti+qrd/OzlxTxx+eiId3eFFqTbKLjuS1j2Knx5lz/lbulGeOUCOOw0OPk+KJIcI8mgg9NvyXEV9ASgNquzUbUMyKptRtFTtc+w5nQfC/agnwGtAy097RO39GitY3Zvy073j+NAVQyL++5j/QXzGlNEsdKcyCAW9zaPpcdmo4ZMXnadwK2O94yD62cY1tJEWPy8/3W/yRxcnws4A2J60hKN6el0hJG90URciQxCglGSI3qChYMjDpe7cMQe85P43fVExUxbFkFPztrA+0sNF9yTH5pNVpqd568Zy4S+rSRxUlVQTGTVHkjv3SJDaTb+9zOwsv7aZM0VjqYWPbJaagaUUoVAoWczrUe7TKZPO67Zx/H59K94Ylk9S/YaP3Bfr9nL9S8u4ukrx0Rc7AgtiM1muAIMOgNm3gcLn/YvaNZ8Auu/MgqfHjUV0rNbcqRtno5u/+JatTMC8Rty/Jae3LpmisOrLoWHR0HdQZhwM5xyX+Dxqn2BPuGNsPQ0uDQut3+lF8nS0684x/d63Z5K3G6NzRZhYdpjvP/19sVGxiJ7Wvj24ThgSi4ak3ubP3sbwDJ3P//BqgT+hi4nPHms31UPoO8k3OuMz60Gv6tphif+K/5rhIqlYBe0SMSbvS1Y9IRYisIQi3tbY1JWB9K484QmJdAxuLe1PdVTXe/k3o9X8eqCLQH7axpcXPXcd6y599QWGlkQbVlRJkL5TiMTqyVNEa+WGp9vk9rAtNabG/NoyrGlGFNpBXV60myKm4anc9oRnX375qzfx9XPf0dVa6pBIoSSVQin3Q8/+wZ6TvTvd9XBrL/DY+ONu+qH2g9LktBa01X7LTlp7XsD4Mr1F8LMb2im7G0r3jUED8D8x8AZtCA2JzHIame4QyaI2coDkUXPgE55vtfV9S62l0VZ4HcZAXaP65ezBnb+YLhlvnIh/Ph2bANcP93IduTFnArbhFX2Nq/Fp1SbamFVJZCEdN3ngYIHoMNhuD3XrND+mw3ZMdSx8WH+X6236NcY97YoKXpDEhmEE0lBXyexiqOAUwSLj0Td25Lw1RZ6iiiueG3g6/SZbzaFCB4vMbmhCjGQwJytKw9/LKJ7W4KCqC1M1hgQx7/U4CFaSZ0eh03x8CUjOXuEfzG3YFMpVz73HeW1UhOm1dN5KFzzCZz3DOT6xSsHt8Abl8N/zwt0fRJioqailALl9zFPL+5tvMjz/5+0czWT6AkuTFsyJ3C7ieJ5ADLTw//k5GY46N7OX9Ryza6KyCdPy4Quw/3bO5fAG1cYCTneuQ6qYrj58+2j/tc9j4Su1skQAiw9puxtAPswiZ6aAxCH2xhgnV626wi8BrIK/J9JljuGOIX9G+DhkfDQMNizythXH+r3H2yNiURIHE3S3NuCib4ga4ylJ7Bv7Iu/EGEVt7yJp1Hr4unZG1t6CLGR7GQAbZmGOG6OHGKI6EkBWludHofdxj8vGsEFo/3pjxdvPsAVzyzgYLUIn1aPUjDsQrhlEUy8FWwmL9gNM+CJY4zU1yly56c5qN3jd6Gq1WnktDPEjq3AL3o6uPc3z2daEZQlLrjGxG5T6uVGxPMA1NT7F782BelRMjoeZrL2rNkdRfRA4Ph2LDUsPr7tJZH7HtwWWKNqyh1hF07OgEQG3jo9xnsJsPSgDffBeEgLchs94kLI6+xLbxxo6YlB9Lx4lhGXd3ALLPmvMacsLD3xpayOz9ITkr0tAQtOcxPvf55V+3iztyXK6l3lnP3YXG58eTGV4kUhBPPhL2HFey09ilaJiB6hSbDbFPefP4xLx/X07Vu27SCXPj2f0liClIWWJyMPTvoz3PQt9J3k3++sMb5U3742sFaBEJa6/SW+19spJsPj5pVW5L8xkE1tZJeFZHEgyHN47Wd+seWsN9zfvHQd0ahLBRcmVVHuxg7sbBI90Sw9EOiOFixyqqNYetZ9iW8Z2q439DoqbFOzpccRFNNTRSYNyhRLVB2ni9vBbYHb5z4FYLL0xCl6yk3nW/k+uOrBHbowjitldYilJrJgsruD3dvCWHoSUAGNsfREj7oJz5G2FdzveJLxapWlerEqTtpUzN9YyrKtZXy2YlfTWmK0jqrk6pwu3lq0lamvL2HsX6bzpw9XRO6QkrTCG4BvXWW9P1GLWIrc5BTRIzQZNpvivnOHcvXE3r59K3eWc+lT89lbkbwie0ITU3wYXPEeXPgiZJtcJ1e8a1h9ti0O21UwcJeW+F7vVJ18i//sgk7Uab8lzV22Pbhr8jEVwPRte10W137qz4Jkz4Ch5zfqUrFmbvMyyCR61sZi6fEkhABg9/LAY2VRwkJ3LvO/7js54mLAnL0tPSimBxQV9kJ/g3jjeg5u9b++8AUjuQj+QpaV2u/eFldMDxhWJKt4HuJzb7OHWHoiL4DsQVnm4rEqNR9xLOJctbyW/hcucszijYw/o9wNMRUajdYkGcvIj35owqLGMSyQD7vjM37z9g+8t3QHeyvqeH5uCRv2WqRRbmra8qI8XiGyYyk8NakpRpLyiOgRmhSlFHedOZgbjvXX1Fizu4JLnprH7vLaFhyZEBdKGcXebpwLvY/x7y/bDM+dBN8+EtXl5VBGlfkDgfc6TBnbstLZo/3FLGsPBN31TzbO+lDLAhjB9OApWOth8FmQXdSoy9Wa3NtiSV3fs8hv1Yjp+yFM4gEgVNwFs3Op/3UUi1ZAIgNvTI/JVa/CVuhvHG8GN7PoKejhe2kV05OjqyMv7oKP2eyhYtDXNvb/13SC3JKjiJg0d7DoiS1ldSf2Gq6zFeHTtycve1vQWCJ8rmmVgTcj0mqtrIgxZG8LyfgW29haCneC3+lbSpuxRs6hyH/PN+rqRWP1x1C6KXq7mGjlkzVGRPQITY5Sit+dOohfTO7v27dhbxUXPzmPHdEyNAmti/wucOX7MPkP/gwxbid8cQe8dnFi2asOARzlftGzP62L73VOhp2d+IVFQ2kTi56DW7H88Vr9seH2tmGGf9+oMO4RcVBtEj3ZMVh6CrP9hTjLa53R76YX9gp/LJLocTXAbpMbjjkhglXzAPe2YEsPHLCbxGGEBXsIteWBLqIe0WN+3+aYnjScodn2zAQfUzb49HbLpvGkrM4gyCU5imByuAPbx56y2m24zr5+WVhFkDzRo5hsW8IN9g8poNK0N/pd93AjiDayYJHX2mPvaxpcVNQeYjFDpZvg1Uvgg1ubt8BpPMTqQvv6ZfDwiNizWR4CiOgRmgWlFL8++TCmnejPBlWyv5qLnpzHVrkr1Law2eG42+DqjyG/m3//ui/gP0fBptktN7ZWSrrpTnF5hl/0ZDjs7DHVa3aWNbHoORDmrt+WecZi07soK+oHvY9u9OWCY3qiUZDlj41xuXX0IO3cToYbnhXhRE9DrTFHXZ6FuS0NOg6OeBmze1twnR6AUpvJ7bMiDncj8/+KPcNXHNXsPWa29ACR476C7/4qW2g6bO+hOCw9GQSKKR3FAuDQgaIn7pie7YvAmagnQGxKomPtRp5Pf4Dfp73Grx1v+sdklZlNh54zuJXVe4nWpjVZemrqjdicQ553rjPcfL9/0ahb1yw0sfp957rGn6M1TdZGIKJHaFZuPX4Avz1lkG9724EaLn5yHiX7JMVim6PXRLhxDhx2mn9f5S4je9TM+4yii4nicsK2RbB3bfS2rR2tyan2i5nKrG4Bhw/Y/QtmXd6E/vkQKAR6HwNdR/q3N870vx53Q1JuQ5tFTyzubfmZgfWyy6Jle7TZAuN6zJTvMCw6ZvZvgH8NNlKve+lzLDjCCCcPAdnbbKGWnkDRE5QSPBLfm9wJi/r44nncpgVGDRk4temnui5CrFNw/I6ygbL+3OOJswmx9ESx3Njdwe2tF0wRl1G11uIu2NITuhaLbXF20q6nfK+vcEyPVlEnyjW9Y4tMiAhqRS5Dv3l7Gb95+4eWHkbLs90Uo7rw2dj6NJcgaKiBd29IrO+Tx3m+/1u5ebGJEdGTAiilCpVSvZVSvYG0RP1wm4ubJvXjzjP8d1Z3HKzloifnsX5PCwQ/Co0juwgueRVO+ZtxxxwAbRQ0fe5kmPswbP42NjeBhlpY8ym8dzP8YwA8czw8NhY+mhZ5odfaqTlAmsv//muyA0VPWVqx77UtOJ10sjGLnna94chfhLbJ7QSjG+/aBoF1emJJZOCw28jN8AufgzUxpLgP65qmjbo5ZhY/H5rV7fAzo17CKnub3VQaYL8yubeVx/g3dLtg8zz/9oif+A8FLKIUlWZrT6SMicGWHld9QKHCd1z+eDxlkdEtHMGiR0X5jUlzB1ppwiVNiOi+6HmfwW2StWRzK4fl/ljc28Cqdk8CUQ+tR/Pw0Q/J++655vmFzNvQMkXS/SRjpjTXHyjG6yx+EX54I7FL7FwKH/1fYn2BVjVZG4GIntRgKrDJ8xiwf39Lf9lE57qj+/Dnc4b6tvdU1HHJU/NiS1MrtC6Uggk3wfVfQpE/YQXbF8GXd8Lzp8Jfu8MTR8OHU43aIXtWG4kPag/CD2/Bm1fC/X3htUtg6X+hxlTrZNGz8PiRsH56s7+1pGASGpU6E5UTWDy4Ir2j77WjKg4rQSPHQrveMPjsQBdFgKP/D9KCXKoSxFynJxb3Ngh0cSuPRfT0Oz78sWCBs/37wO2sIuMziEKge5sKeAbYEyB6YszAt2cV1Hu+75QdxvpdUII1hTmuJ6J7W7ClZ89KcPs/w12mpBnxubcF/h10FCtRpivwBla4mJ6IN8hd4WKXovmIhV/smlu6zGnGTaeJyfpi8dmlVe+hWAfOt1B3tiCLUfQrtSiNkQ2XPj0/aeNoMWL9A6lmWEq7XTDv0ejtIrFhhqSsbukBCEnhIaCP57Guffv2kVu3Eq6Y0Iu/n3+E739wX2U9lzw1jxU7pPZLm6TrSPjZbDjiotBj2gW7fjTutL9/Mzw+Hv7eC+7vB+9eb9QTiVRF+uBWI2PNezeH3r1v7Zgyt23TxeRlBi62qjP8oiejuplFjz0Nxv/Mvy+3E4y+OmmXizemByDfJHpisvT0mxL+mLdQaF0lrPoQNs/1HxtynjFfY8hQZ5W9zW5yb9uhOvsbH9gUm4ubOatax8MhPce36QxSPUqZFhxf/y38OesjW8sPaH9K8Jjr9LicpBNcbDTyAihY9MQjsHx4LFFR11qJnBtwhbH0xETQNUeqdQx751g+ct/M0bYfw3dL/IpCi9Bcf7EYhMirFwdmekyUFBEviSKiJwXQWpdprUu01iVAg83Wdv6sF4/tyYMXDse7fjhQ3cBlTy/gh21lLTouIUEy8uC8p+DKD+CoqUbcSFqOddu68oC70IDRdvA5cP6z8JuNMOn3Jrc5DCvQYxPosP+7pnoHycdUL2arLg5w3wKoy/YvmDMaygy/7aZAazDVC6JdH+N57E+NuKzCnsbfLklWHgiK6YnBvQ2gMF7Rk9cJuo0OMwCP6HnrKnjjcv9+ZYOzH4XCHtb9gjC7t6X5srf5v2c30xUK/IWYY7JKmkVPp6EBh1xBdXC6K1O2pi3z4GAYa1KYOBgvNfhjl2IWIntXhe5zR7b0ZLkCLfZ2bf13dEdagIW5RkhMT4yZ4YLpXLshzPktFqBBn5URD+Ufx0Npj2Fz1ZGGk2fTHkhoPEIrJFaB0JRhMiVz4IH+sP7LJrxILKSGWGrErQ5BSA7njepOmt3G1DeW4nJrDtY08JOnF/DCteMY3atd9BMIrQuloO9xxgOMxcve1UZigu2LjGKme1f5FxLZ7eGwU2HQmdB3EqRl+s816bdw+Bnw3s/9dVUqdzFsxV/Z234sZK6EDgOheKCx6GyNgj/E0hP4tevK7ohLK+zeu/kVOwPdBJNFdanfnQr8NW7Ss+HS15J/PQLr9CTi3lYWi+gBI6bs2RND91eXGqmpg0VIx8EBlpVoBCQysEhZ7dQa+k8xasyA4UY30iSyrNi90v+605DA6wWJnvdcEznH/q1/x64foCDILREixvus0z2o1n7Rk1W3N/L4vCx/J3RfFMEUbOlJd1tnYovs3hbj3z5BS0+3mqAkKRHc24IFYnD2ul42f22mDOX0nEyFxixFcXdrCWobXGw7IBlUrYnZv63phvDC6ck93yHu3iaiR2gVnDm8K2l2G7e89j0NLk1FnZMrnl3A81ePZXzftuGuJ4TBZjcWdZ2G+APk6yqNhZs9HbqMAHuEr6JOQ+D6r2DeIzDzrz5f/+L9C+GLhf52jkxoPwA69DfctLLbG65L2R2M13mdjVTMzS2MDvgtPdt0MYcHubdlZ2WyjwI6UWbsKN/RNKLH7NqWntfowqOxkIh7W0G8lh6AHuPggudh9j8CUzRX74elr4a27zsptvN6CEhk4HVvM8X0ON06MKHCrvAuTj7MdYI6BabMDrb0/Md5VqDosSowCxFFz638hnrtj5NpX7XeSDCSnh22D2DtThpFaGQFix5tHZ8TcRnldW8L6RP0/5ug6IkHHWR1Uibrkp1Qi9T09N9wU8PU0POEWKlaFq01Fz4xjx+3W8+bYKtaFrXY0FQFp1EPw1OzN3DVxN5kOGL73291xGzpORQyorX0bE0OrfC2qHCocsrQzjxx+WjSPdmRqutdXPX8d8xdLwUvU46MXCPldfcxkQWPF7vDCLC/cQ50H2fdxlkLu3+EFf+DBU/AzL/Ax78yXJtePAMeHQMP9IPXfwLzHoedy6K66SSFIEtPsHtbbkYaO7U5EL6J0lZvNQUWt+vVLD/UNQ3+xWEs2dsACrITED0AQ8+Dn38Lo68xDaA0sOCqlwEnxX5ewiQyMIlnp0tD52H+RruXR55bFbuN9O5eori3rdE9ecM5yb+jdKP1ecOJntP+wVY6U6I74zLXnImULbCmDP53o996ZSZSIgOtQ9zb0nUYS0+kzyhMdjlXMkRPhHT66drJ7Y5X+ZvjKTpgfJ7B6b2VdqE13O54jeUZoTVQ+tt28ETav6IOo6Vvnn+3qTSs4AlmkNrC/Ixf8F3Gzxmt1sTU575PVvPkrDBztU3QSEuP1rBlQWLf6Tt/gMfGx98vKo343tcaPv+Dkf56XUu72yWGiJ4WRCl1lVLqB6VUlVKqRCl1v1Iqym231Ob4wzvxzFVjyHAYU7O2wc21Lyzk6zV7ovQUDgmKB8K1n7H88F+ztdsZRuaugtjiMgBjEbz6I/j8d/DksfD3PoYwqilrmvFqHSB6tlq4t+VlOtilTdbMphA99VUwx7QI63Ns8q9hgTl7Wyx1eiBBS4+Z7CABuTdogZbdAXoeGdcpzSLEn7JaBR4v9tcfo6HaOpnBmk/h7evgA1Oq8LyuhmUyzPW8lGhTsoSV71uvmM2BzmOug6nL4ZbvYdxPjfNiZx8F/jbhEi4464xEI8us3R4Lq0qs+wE01OAISnyQEca9zVcg1gqPIArNeBa0aHNGOEc46itCdnmtMGc7P+NGx0dc4viaO9Ne9hwMElbajaO2lBsdH5KlrK/fz7YzpgKmxjtqmTIT8fx//TPtPxSoanJUHU+nPxh7vy9NboSuBqhqZdllXU6Y/x+YdX9o9sNYCXcD6at74LmT4LEJUBmjO6mX1y8z3MJbE5/82sggt3MpvHJBS48mIUT0tBBKqfOAF4BPgTOB+4GfAdFvD6U4xw4s5vmrx/rcYeqcbm54aTHTV+5u4ZEJrQKbnT3FR7Gu33Vwxbvwf8vh9zvghllw3jMw+Q8w/kYYegH0nQydj/CkZbb4Yao7CAufgccnwJrPkj/Wqr3g9CcmsLb0OAItPas+TJ4Fqq7C+CFf8IQxFgBHFhz1y+ScPwpVdf7Fb06slp54U1YHk20SkCVzA60Swy816ko50uM6ZaClx+Z59s+nBpfbsF5mmf6O+4LEVvlOIzX78rdh3Rf+/SMuC1k0Bcf0AHzgMgm18u2B7opezFatriONRA3t+wF+8bDblLY6rKVn7efW+z2M3fKMUVfLKu7GwtrUtWFzaDvAcSCCFSCMpUcHpQd2LHom/DnCUWeR5U5rOFDCrQ3+gpRne10Kgy1b2o2tPnLSiGDScNJx80dMsJliubRmTsYv2ZR5OSWZl1FE+HP2U9v5Z9rjXGX/HNC0o5x0Evj/qC6FH9+OSXyY3dsG2/x/wyKVQE09l9OovfZAX5idxGQPbrch0oOZ9ffwFj2327D011XCD6/DZ7cbngGz7g9sZ/X/seZTi/Fb/LYsfwfm/NN4XXcQvv23cV2XE1Z/Av84DF65KLxoT0amNiu2LwrcXviM33Lsdhvu2C5nqEJf9rrRto0jMT0tx8XAHK31bz3bM5RSHYFbMMTPIc3E/h146bpxXPP8QirrnNS73Nz438U8culITj2iS0sPT2htpOdA1xHGIxy1B2HLfCMbzua5sGOpfzFTsRNeu9hIt33q35MT71JdGuACcFBnU04OuZmhoudt9xiuwbPQ3L7IqAQ+PsHK217mPQ5f/tFYPJoXiuN/ZsQ3NQOlVf4f9HY5sQmNRlt6zMLD7ELWbTSc+0T858PavS3E0gNGBjxvxriXz4Ur/udPqb30FQvLhrIsBOuyKP65nWK26E70VJ6bPw+PgHE3wDG/NjLY1R4MXKT1OSbkHOAVPZuMjc9/b9QpsgfGmQVUpQ/HXzpBTke47nPDUvr0ZGP/8EtDmha4PJ+J1gECr+DH58KfP0xMT3t34GI9/Zu/hvZ11oEjI8Rq6rMSWRQ7tpVtgqfDuBMFWXqKtn9N141vhh+7iQ4cZJxtFYNsWzhi/nu8ng7n1v2JJbo/A6sXB2Tm+0vas/yi4VYcuKjHwU/sX7Hc3Yeluj/PpP2DPrbdnGefwyjbOp8gu8D9ovG3zywwvnNeudD4PjzpXugyLHAwWhuB8XtWQlE/Mo70C7w7HS8zybY0oHmmamCa4026UEowDpw4cTDF9j1X2r/kG/dQnnUZQffpNFCPaU5tXwxz/20IDYAZ98Kxvwn9sFb8zyjAuXe1caPqjH9BXhfYNAsqd8OoK40MoeAveH2fZz3QbUzguZa+Yjy8nPWI0d9Zb1j5rbISzn0odF9tuSFe1n1pWMjnPx7aZvk7MOHnkN8F5j1m/MaUfBPY5ttHjIeZdbvgX4NDyzXcXUCT8eNbgdsf/yq2flHS4bcVRPS0HA4Iua1zELG++Rjbu4iXrxvHlc99R0WtE6db84vXlvBPl5uzR1hkLhKESGQWwMCTjQcYC58FT3ruCHoWoz++CRtnGj/IA06MLaHA9u+NH73yHUbgfHWpsdiuCnRn2KaLAcgLsvTkZDiY5x7C+66J/jvLX/0JBp1mLBYWPWe4QJ3yV8gqDL2+y2kEm1fvN+KaMvKMekjmH1ivuMsoaDYrD0BptX+RX5SA6CmrbqR7m5nOw6z3x4BVIgOvxQdMlpmGoCxYcx4ysgq+/3PYuiD0xBNuMoRSEFaWHoDVuqdf9AB895TxaD8A9q8LbJwXeHPIe8Y9ZktP5W54+xojXm7/BsjINxaKqz4IufaN9VN5Iv2hwJ1Ve+DhkYH7LFziMnQtfPpbI6nEMdOM62mNOy3X8n0CfktPkNUzX1cYi/y6CrBnhHQbWTUH/tLFMu6omAOGQLNYwOWHEzyPjadPTeCitO8Psbl3FW7+gkWZN4Xs/1/GXcaLoHwUp9oXssF+RdTznm1KavF21VXwNwxRbxarT5pE72VvwcCTjAQbezyWptINHPfxJEpMyTKtuNXxnuX+9ZlXBmxPsi+jgmxusn9AH1uQV8bTFifYvQLe/4UhcIL/b8AQ8E8GCffPfx9+oMEWjGA+uMV4xMvfTO7T5jTzZurK4bGx8Z8bQn4nhKYl5UWPUmo0cCIwzvPoBqC1trBHBvTLAn4HXAL0BEqBz4A7tdYxltyOyIvAWx43ty+BwzCsPP9JwrlThpE92/Hq9RO44rkFlFU34HJrpr6xlAaX5oLR3Vt6eEJbJiMPjv01DDrDKJjq/dGs2guf3mY4nrbrbdyp73Ockea4XW/DNUpr4+7jnH/Bxq9jutwSd3+AEEuPN8bnnoYrmGT/gQIqjUXZ4xMNtwgvB0oMdz5zHZ3vX4bpdxmCJxYm3d4sWdvAcKc6YLb0ZDeTpaewl/X+wWfFfy4PZkuPw8LS4/Sqor6TYJ8phmHTLHg0TA2hnhPhxD9bXy+M6CknTJrtYMGTVWRYOkx4a+IEuFKC4U656kPr83oY6HwNVxh3s1jo7NxhuFgCTL/buEmwfyPtIhUknv84uBpQVnWr/hYqFAOIlGjh72HmRzj2riZUWsXGoFk3JtgzASJZ5169sFmGcH+alboJw38mNt1ABCEMKS96gDuBs+PpoJTKBGYAE4CdwPtAb+Aa4Ayl1AStdaNSkmitP1BK3QS8Dj478H+BPzTmvKnIEd0LePX6CVz+7AJKq+rRGn7z9jIaXG4uHRflx08QotFxEFz3hRHMOuPegBgcDpQYlpZFHjccZTPuzNszQmM2rMgsoLbdQF7Y2oknnGdiU6Gpm70xPvsp4EF1Jfdoj/uEWfAAbPkW3r4WLnrZyGb37SPwxR2Rr9/pCDjrYSMGJLMwrMtTU1BR5wywWLRPwNJTXtuA262x2SLeowqk4yCYeIvJ0qXg+Dv9bmYJYOXeZq7T0+B9nyMvNywvkeg6Ek6937A8hclcGE70fOg6kgtsX0cfcE5xyC6vx9w89+CQYxE5ehrMVLiw8x/nmdzkiCyQYiKWlN5bF8DWBYfEIkUQhObhUPg+mQf8ACz0PEog6o2bOzAEzzzgJK11JYBSahrwIPAcMMnbWClVCERzkq/WWvvSOCmljgceAu4DZgIDPK/vByycXQ9tBnfN5/UbJnDZ0wvYV1mH1vC7d3+kweXmyiN7t/TwhLaOzQ4Tf2G4lH33jBEQbuXzrd3WAeTdRhsFVrPb+x/tjXpB63eU87dH5gCQn+FABQWtmy0/r9UfzZ8GrkBtmuVv0K4PHPDEYKz5BJ44GnKLYdPswDHY040kBfUVxjgHnAznPwOZ+dBtVCKfSqMorfRbeWwK8rPSIrT2Y/48tIZap4vs9Dh/qk6613iU7zRc/or6xNc/iIDsbR73NnPtkXqnG601qstwuG0T3B/heiffZ9QVikA497bZ7qFw1FTr2AMzFlnZvJaexXoge3U+xSrGQHx7mi+z2Vuu45IjegRBEFqAlBc9Wuu/m7eDFxzBKKXSAW8+0Zu9gsdzrn8qpa4CjlNKjdZae+3JlxDdLW0WJqGEIZ7e1Frf7T2ulKoCXlZK/VNrHaGAwqHJwE55vPkzQ/jsKjdSoP7x/RXUO91cf0wTFHMUDj2K+sIp9xmvy3fAhpmw4SsjbqdsS6jbTL/j4eip0PuYsGlLK2r9bkF5maELf3OMT4ML6s56gszPfg3uBiPmo/exRtavNR8bjfauChRk7XrD5e8aY1fKUAquhrgzlCUbczxPYXZ6gDtYJIItYTX1CYgeL/nJSXpSb4rp8abezkwPDL+sc7qNY9lFRkyYOcPTbZuM+Jm0LOPvFYVwlh6tFfqEu1En3G0EV897zNq1cdz1IbvcvmxMikvr72B6xm1RxwHA8EvRXxrzrVyHca8TBEFoA6S86EmAo4ACYIPWeonF8beBYRhpphcDaK2fAOJNCzQQeDZo3zLAjuFKJ6LHgr7FubzhET7byww3pHs/XkWd083Nk/u38OiElCK/K4z8ifEAI+tP2WYj4Ltyt2Hd6Tw08jmAilp/XEpwumoIjfGpTGtP5qWvBja64FmjbkNwoc0OA+HK942xelGqxQUPEBTPE5uVB0JFT3W9i/Zh2jYXDSat660hFlx3qLbB5d933O2g7Ebg85Q7DCEURyyV02UtegDc2hNPdMyvDKvPG1cYgrjvJNi33sjcNS4w85/WGrOOWq+786+Rn/N/S06OPJBL34CiPmgM0XOAXBq0nTQVW0r1Le5ietqiB2rPcg3jOPsPUdsd1NkUKIugd0EQhBgQ0RPKcM/z92GOe/cnngrIYCsQlPYGrw+KdVEDAYBe7XN8wmdLqfED+MDna6h3upl6woCo1jxBSAhHOnQYYDzioNJUqyZY4ICxyLcpfIvSylonHXKDPHDTsgxrzraFULrJk4pZGTEkzZSYIF72m0RP+5zYQ8FtNkWGw0ad0zCv1DbEtsBuShpMisFn6XEEix6TOcjugMm/S/h6blONDPNnAeB0u7HbPNe22eHSV42aOWmZ/toaQd+BVkUxq+z5cMZD8NHUwAM9jzRS+464zNTfOIELO5fU38Ebmffh0BZJJo6aatTyqK9kty7ksoY/MCdjamg7E79vuI5XXcdzjftTLk2bzcAwP393NlzNy66TKMm8zPL4vQ0/4Ur7FzGJLDMl7k70Ds42JghCSiKiJxRvZPy2MMe9++NMARPCU8DflVI7MJImDATuBT7QWkctya6UWhHmUL+qqipmzJgR5nDTUVVlZOJprmvfOlTzwCLF7mrjB/nfX61j3cZNnN8/NG5CSC2ae641hsVb/KKnvuqg5Zgz7VDtaTZzzjx65UfKXF/seQDzlyZtnMlm4Sb/othZXRbwvlV1dUAQ5OzZs9HZ2b5th3LjLTc4+9sFbC1ouUz+VVVV1LkU3gKEPy79nspNNiOGB38q6JnfzKFTdnLGuXyfX+g58H8WANNnfE2WI77vN6sYoc1btjAjuxdpR76I056NtjmMWDBlM3KVmv5eZtG0WB/GrZ1f4ZI+9fTY9iEOVxV2Zw01WZ3YoiaSN7gTO1fM4unKo9imO3J3w5XcnfYSbmVnb4cj6bTXiG9bNeDnLMycyKsLjc/sedepvKlO5bnxeyjet4C+m/2pryfWPswOOgDwc9sfedx9DwBzxj9Lhcrht19XUE4Oz7hO59Z285hWE1gP5d/O85jvPpzX0v8SsP/q+t8wyz2cJ9P+xUl2w1v9Ku5lcW1nlmcGugheX/8rZrhHMlBt43c9VuFKy2PK9kdDPtfdupBr629jpG0dd6e/wgznEb5zA6xy9+S/rhNY5+7Gsxn/JI8qZruO4MaG/2Nl5rXWf0ATwanDy3UW+coiw50gNDEtuc5MFBE9oXgLB4SzoXs/8bxGXuchwA38FJgG7AZexcg2J8RAUabit2Mz+MeiOnZUGb/Kn2wyMkZdPDBNhI/QKqh1+leM4RarWQ5FtaddjTO8a1NbotJkCMhNi+9/McOuqGowPof6CK5ezYXJ0EKaR9copUi3Q51Hn9Qn0SAVmC0OcFofixWrLt59DWn5/p3KWrQF99canI4cNvW+JKRtef4gnsnoww8Vxof2gutkSnMHcvHwTtRldmDFoGnY3HW47Zk0HHSDSdJpoCqnF1U5vSjpdRHK3UC928aOGX6r4RJ1ODOPfhOtbKDsuJ06IJX3nLSjGD9sGN23f0JVZmfOXT6eOgx3z2N5hpe7f0Sas5I7Gq7h6+3GvLypYSrPHbENd1E/Vs51UYmmf+1LtKecBybnsaYig+mLjPezWvfk+/b9ybDDC5tyeCztYfbqAqYf/lceWZlGRYPxGa5w9abL4afywPdObtevcqPjIwB+2XAza7VR++U3uX8jp3QFX7lHUk0mvWtf5cP033OErcT3fibUPsLx9iV0UfuZ7hrNUt2fT1zjOM3+HSvdvTit/j4yaKBYlXF/xvNMZBkuWzq7Ox6L05FDl11fkeY0QpMb7NmU5x/GjswB3LFzIptrs/g043d0UUbx0Rvrp5JDLe1UBa+6jqeb2sdI2zryqGaCbRUVZHOefY5vbM87T+Zx51kMsG3n1fT7LOeOFX9uuJw70/4bsG/ZkN8zfEXgOeaOe5q8yvVoZaf31ncoKA/MmFmXXoTNXe97f9HY1uUU8ivWkl8ZPfluZU4vcqv8VsfZE//LoLWPkVG3jxWDplGb2RGbdnLs3J9g04mncw+mKrs7OdXW99xXDJpG8d65dNy/gLX9rmdnp0nY5tzPMbborqHJxKXSmHPki816zWQhoqeF0Fq7gH95Hon0H+J97ckeV+jZ/CIrK2vAlCmJp2dNFK/qb+5rH3tMHZc/s4DVu4wq219sdtG5a3fuPnNIfKluhVbDhr2V3PzK9+RlOvjP5aND3L1aaq4lwsL61bB+AwD9enZlypRQz9gOy2azv9aYvwMGD2PK4E7NOsam4NP9y6DE+PE+YmBvpkwZ5DvmKi/HVM2GY489Fnu+f/FduORrSmuN+0uDjhjO5MM6NsuYrfjqq69ocNf6to87+kh6tTcW2Tlzv6TO48Y3bORoRvZsZ3mOeHGu2AVLDOtAQW42ZXX+e3BHTjya4rz4KsfU1Ltg+mcB+7p1686UKdFj0gD44uOAzZ49ezJlyuFhm7+8+TvY53UzU+wuGsNRpx0Z0m7Z1jJYMNe3bbc7Qv6naxtcMMM/9pycHCafcJxvu6K2AWZ84dsuLi7mqFNPBS7C6XJT94dPfcecGUX0ut5YrHV690fYbiRUdWFnyGnX0SE3g6zvZ0JNNU4c7KaIY08+neySUlg0z3eeYcOGkZ3u4P5F9Yyp+w/1OHhpzATS1i+FBr9AGzFqNHy/gH87z2Oz7sQ5U45h7Zf+eDvdaTDv7AuMWLum/rd8mnE7+VRzU8Mv2UV7XnGdENDmloZbeMq5iZW6F6CoI51tuiN35N7DjF9Pwg50NXeo2AW5nUhTivbArc/MZ1mtkQDjyLpHmGJbQgMOvnEHfjet091Z5zLq4T3rOh2At13HcrRtOa+5JrNVG99Te93tOLruIbRWbKcYhZuv06fRy7aHRe6BXFj/R6an/4Z+tp187RrOs67T2KC78nzhs6j2A+DytxmekQdV30DJN8bF+07mqNMuMo3mt/D6T2D1R5DVDqatIiMty1DgJXOMAtMLn4HaciOOrlfofAup7FexC3I6gicjI5u+gTWfwqgryW3XC56abCSNOfcpjh1+Jpx0JgABFYam7IG1nxn1wYr6GrXbOgyEYRca59uz0nBDTg9KArLqI3jDEy869Hwj8+a4n5LTdYSx76s/wzf/MF6f9QgMv4whphT3Az2PoXPTqax1kkE99TjY9Lcz/ddwNYDNYbi7rvsSXrkAAKc9m9UDbmRoxk4o6GEkzGmoNtLtz/23v3/7/rB/vW9T53ai6uYfwWZnDEZh7eYmJ6dxyVRE9ITivWWQHea49xOvaIaxxMpU4C7vxv79MRYqTBE65Gbw2k+NAqbLtxtpWF+at5l6p5v7zj1ChE8b5Pfv/ugTsQ9+sYa/ntfYELqWo9KUvc0qkQEExvpU1iVQkLMVcqDanMggvsQK5mQGtck0oSSASwdaOsypqjMdfstIQExPY69pjiEKih1yuuO/jtsiqCdMgrgQtEXfaF1jNUaFWJASHE8yiPe03jTeXisSeB0gQ6khk9dcx3N08SjChwsb7KOAiXWPkEVd2GK0Luws1XEk7skLrKgxd715jaCY4Y49pf237qF86w4Vy9u0/8aExsa59fcw1raaue6hvu2htk0sdg8E4Gv3CJy/Wk+a3WRdPOthI1MlCs58KPTi5z8L6780al15izQr5a8/1v/4mN8HEPK50OeYwFpmP5/nv0Y4bHYYdLp/e4qp1GLw+cwcfgbcNM8Qa16hY2bKHUainLRsGBgl4QiB89CH3ZRAZsCJMHU52NOYvXCl5xrmGwxFcOI9xqOh1nhfXsFUtgVWvs/y3Imc+afpAHTKz2DB7wPFeFug5RylWy/eWjohNwWC9remZAMPAX08j3Xt27d0rqPmp11OOq9cP4ERPQp9+15fuJVfv70sbPpXoXWydGsZCzaV+rb/t2R7QCawtkZAIoMM6yxmZjFkFkltmVLT36woxsKkXrLT/Qv96hYWPcGXz0zz/2xmmsZZ60zeOF3mRAZpgT/TkTK7hcNa9MR2Hqtm7ijfqcGHw7UOFjBWY4o2zEiHk/XNb3me4PeoYxGDgS3CvbcGHGEFT1uhlHw+d4+j0nP/uJwcvnUPDVich7z/or5w4xy48Rvr1O5pmXD4mVAQbnmWZJSKLHgaS6fB1oLHe+0h50YVPHGNrrBHqNCzIi3TEEze917YEybeQl1+4+qdtQZE9ISyzPMc7taHd3/zOlEKUSnISuPl68YxtrffxeTd77cz9Y2lNLiSdxdWaFqemr0hYLu2wc0bi7a20Ggaj7lOj1X2tuD9FXWpIXoOVPstVvGKHnM66JoWzt4WbMAJtPT4X9clcZyBxVAVDpO1OpHvMivjUMyWnhj3BRwPXs2G6WAVKxTveHTQe1MRloFJE0ExCBxvu+akrd3eG3jHp/S+/WMem7k+emNBSAIiekKZCxwE+imlRlgcv8Dz3JrKUk8FNnkeAw419zYzeZlpvHDNOI7s67d2fbhsB7e8uoR6pwif1k7Jvio+Wx5aTf7leZtxtlHhanZXywvj3paXgpae/ZX+APV4RU+Ae1uLi57ApWSGyaXNbPVJpnub2ZrjsNlw2P0LeatMbNGwtqDEaulJwPoSonnCFVsN3I7J+hTl3OYb8/GIjnBjjL1/9LvuMWrBxMfQ3CorSTzw+ZrojQRrxHs/LkT0BKG1rge8eSgfU0r5bMxKqWkY9Xlmaa0XW/VvIR7iEHdvM5OT4eC5q8dyzIAOvn2frdjFz19ZTF0SXVCE5PPMnI2+O9DdCrN8d7i3l9UwfdWeFhxZ4kSr0wOQZ9pvtpC0VRpcbspN4i3emJ7W6t6W7rAFxAhmNpE4M1t6bDZIs/l/qhOx9Lga4d6WSN9YBUTwIt3aqhS5TfBQbE3gjmQlVqw+gnhjndqoRhGENkvKix6l1OlKqfneBxgOpeZ9SqnTg7rdCyzASNKxTin1hqfvg8BeIHoyfaFFyUq38/SVY5gyyB9cOX3VHn760uIWv3MsWLO/so63FvlTdf5iSn9OGer3P37h200tMaxGE0sig66FWb7X2w60/Yrz5iQGkIClJ711ureZrTzQdKLHGeDeFmTpSVpMT4x9EzBgBfcJt7gPFQHRBxU1Dshs6WlCh69Yzt2U10+EzfuruO+TVS09DEvmbzx0PVQaQ3MaelrXbE6MlBc9GFX8xpse3jli3lds7qC1rgUmA3/GqNdzDkYx0heAUVrr6Enem5epiHtbCJlpdp64fDQnD/Gn/529di/XvrCQ6vrUcCFKJV6at9lXeb5DbgbnjuzGNUf19h2fv7GUVTvLW2h0iROLpadnkT9Z5NbSti96dpT5UzznZTgCLDexkJXm/5xqWtjSY3ZvM4scY9v/E1qTzOxtpoW83aZwmDJcJZS9zTKmp/ksPeETGUTetmwTcq0I4wivhywaRzoY/dzeYrWR+7TssvGaFxby1OzWtnwxuOSp+SwqKY3eUGgVRIqda82kvOjRWr+gtVZRHi9Y9KvRWv9Ra91fa52hte6itb5Ga21dNapleQhxb7Mk3WHj0ctGccawLr59327Yz9XPLQxYjAotS029i5fmlfi2r57Yi8w0O6N6tuOIbgW+/S9+WxLauZVjTmQQLqbHLHq2Hahp8xkHzdaqbu2y4i4UnJVuEhOtyL0tM615LD0ukwubw6ZIC0hkkKyYnljHkoSYnjAdYsreFrQdPJOC+zTWvc2qe4gbXrj3E/fVkvt/vreijoemr+Xb9fssj2/c27hq9k3N7979saWHIKQ4KS96DgW01mVa6xKtdQnQYLPJn9VMmt3GQxeP4LyR3Xz7visp5YpnF3Cwpu3HT6QCby3e6otlyU63c/mEXoBR9f7qib197dpa+up6p9tnvYLwlp7u7fyix+nW7DxY0+Rja0q2HfCPv0dRuJJn4clqpdnbMhzBlp6mSVntDIjpCbT0JJS9LckxPdHctmIVVLFYbYLHGSKg47HmxDKmJI49XnHYWKrqXTw0fR2XPbOA3eW10Tu0Mlr6f11IfWR1nAIopQqVUr2VUr2BNHciTtgpjsNu44ELh3PxmB6+fUu2lHH5Mwsoq247i+hUxOly88w3/nidi8f2oNAU+H7G8C50yDW265xuXl/YdtJXVwVZE8PF9GSl2+mYl+Hb3tLGXdzMlp7u7bIitLQmK93k3tbSoieSpcfRNEVUncEpqxsb09OIlNVWVsdofRvj3hZiVQlJSR18raDjCaqeeD5VI5FBaI+Wzt5m5s029D0pJE68VvRDHRE9qcFUJKYnKnab4q/nHcHlE3r69v24/SCXPr0gIL2u0Lx8tmKXb5FvtymuOzqwAFqGw85l4/x/s//O39xm3L/MLpRKQU66teiB1Irr2Vrqt/SYrVixEmDpaUUxPcGWnpyMpskyZ06vn+GwNTp7W2MsPYm4xoUUJw2byCD6uSMlKrA6bj6ciCXF0r3Nol3IPp1IcdKm+x5rI1+RAWw7UMPqXbHFbbrcmme+2cifP1oZUAhZaDpSIdugiJ7U4CEkpicmbDbFn88eyrVH+RfWq3aWc+nT89lT0fbcAdo6WuuAwNozhnWxXCT/ZEKvgPTVS/e2DWtmea3ffTI33RGQ7jgYs+gRS485QUALx/SYplqwpSfbJGKTKXrMqfUzHPZG1+mxdFGL1b3N4nrR+sZeA8hiX9B2JFFjdY5E73x7zxPzwq6VLwBjFbWtjcuf+Y7vNpWGjUvy8tnyXdz78SqenbOJO94zYoHeXLSVcx6byxsLtzTHUFsF0aZ7vdPN07M38sw3G5NapL2tGpjC33YU2gxa6zKgDEApJTE9UVBKcecZh5PusPHErA0ArN1dyakPfcPoXu0Y3DWfwV3yObxLPt0TCMIWYmf+xlJ+2HbQt33DsX0t23XKz+TUI7rw4bIdAEzf4mR0p/gygrUEAemqw8TzeOkRIHrabkyP1jogpich0dOKsrcFJDKIaOlJXmKUAEtPmq3RMT1WIiRWa6m16IncJ7hLuAW41W631thN0ib4XMHfx5Hc25oqZbS1WAvN3haakjvy8WTi/ZtX1zv5+6erA+pmtWb2VdZx0ZPzAHjo4hGcY4rFNfPwV+t8rz/5cRfV9U5ue/sHAJZuLeOMYV3JCeNOfCjxwrebuO+T1b7t64+x/o21ory2gXcXb2N4j0JG9mzXFMNrdmRGCIckSil+e8phpDtsvi/P/VX1fLFyN1+s3O1rl5/p4PAu+QzuaoigwV3yGdApN8TNRUiMJ2dv8L0+un8HhnQtCNv26om9faJnzQE3Wypav7UnIF11lB/gVLH07KusD0jekJB7Wyuq01NriqHJCkq9bXbDq0qqpcf/+aXbbaQ3MqbHSic1JqbHynJkJvhouDHH4t4WzWrkTrIfV6z3uCzHHq1PjG5/ycD7N3r2m028OG9z012oCZn6xlJOHNwpJvES7OK2v7L+kBA90aarWfDc+/Eqrj+mLzur3Gw86GZCvTPAWh3Mb95axucrdmO3Keb9bkqSRtyypP6MOARQShUChZ5NSWQQI0oppp04kKw0Ow9+scbSbaS81smCTaUs2OSvH+CwKfp3zPVZhLxWoXZxFmA81Fmzq4Kv1+z1bf/suMh3oEb1LGRY9wKfZeirLU6ujnINrTUl+6tZWFJKdZ2TC8b0iCo+kkksNXq89GyfGjE9W02ubfmZDgqy0uI+R2uK6ams938vtMsO/B83L6qSaempawiy9NgaWaenMe5tCViJgs8drn04S0/gduDxqJrE1D4ePeQVMbHUCgKN1ipKm4hDa3K843l05vpmvGryueW1JTx39diWHkaTs7u8lnqnO6Fsl/FQXtvAPfPrqHPBNr2UJ68YE7bt5yuMG8Aut+bleZs5ZkBx2LZtBRE9qcFU4C7vhiQyiI+bJvXj/FHdWLq1jJU7y1m5o5yVO8sDXHTMON2a1bsqWL2rgnfZ7tvftSAzwCI0uGs+PdplR4zjOJQxx/IM7pLP0f07RGzvTV897c1lAMzf6eLleSXkZaaRm+EgN9NBboaDBpeb77eUsXBTKYs2l7Kv0n8H8JMfd/H6DROa7W+yYU+l73V+ZuTFv9nSU1pVT2Wds1kFWrIIdG1L7Ac8uxVZeipNWe3bZQf+Dc3jrK5rnpieZNXpiVUQWFlSosUVBV8unFCLZQihKasjX8vcPqSGT8D/feMkiJXICY03is8ilkzaZkRPKDNW72npITQ5y7cf5IInvqXe6eY/l4/m5CGdY+4br/v9O4u34f2q8oqaWHC5dYsX100Gbe8XVbDiIeAFz+sv2rdvP6DlhtI26ZifyUlDOnOS6cvmYE0Dq3eWBwihdbsrqQ/jU7/jYC07DtYyfZX/Szo3w8Ggznl+q1DXfAZ2ygup7H6osfNgDe8v9QvGG47tG9OX9+nDunDfJ6vYV1lPgxvufH9FXNf9rqSUVxZs5ooje8c75LhxuzXvLvG/xwl9IycYKc7NIMNh87k2bS2t5vAu+U06xnhZuaOc295ZRpeCLB6+ZGSIuxcEWqkSieeBwPo3LW3pqWowWXpywlt6qpJp6QnK3mZ2p02kCKp1yurGWHoiW5uCXb/CW3qiZ5ULTWSgIh43a8KQdNemruHeQsIpr2PJ3taMi0ZfYoZmu2LT8eK3JVxlqtcGoXOsLcfe/vqtZdR6rLs/e3kxJX87vcmuZY4XbAxt9dMW0ZMCSCKDpqEgK43xfdsz3rRYbXC52bC30hBBO8pZtaucFTvKKau2LnJaWedk0eYDLNp8wLfPpmBgpzzG9yliQt/2jOtTRPvcDMv+qcju8lqueX6h725xt8IsTh/WJaa+GQ47Vx7Zm39+uTauaxZkpfkK0f79szUcf3gnuhYmtiCPlfmb9vusHjYF542yDsj1YrMpehRls95jHdrShKJn074q1u6u4LiBxXEJ8H98sYbl28tZvr2c5+Zu4ubJ/UPaLNlS5nvdtzg3ofGZxVS9y43T5Q4I5m9OAkRPkHtbU1l6glNWmxMmJCICG2PpsYrHiRZXFHw8nGXIMhV0nHEvIdneTNcKFmw2ZU6QENmNLvAawammExMToYkNmk6SPDtnI/M27EvaIrclueuDFYzrUxTX92FTJbFoCtabPALiJV7xkein0nY+zciI6BGEOEiz2xjUOZ9BnfM5b5SxT2vNrvLaACG0ckc5Jfut4zLcGp97nDfA9LBOeUzoa4ig8X3bU5Si8UGb9lVxxbMLAlygbprUj7Q4FrQ3TerHpk0b2VrhJiu/iMo6J5W1TqrqnFTUOWlwuRncJZ+xvYsY07uIMb3a4dKaE/45i7LqBirrnNz53nKeuWpMk94dfHvxNt/rYwcW0yk/M2qfnibR01RxPdvLajjt399Q0+Di/FHdefCi4TH1c7k1C02xbW8v3sbPJ/UL+Axdbs2CTX732vF9ixIaY3aQEKt1usltIdFjdm8rDHJvM9ddqm5wobVOypwKsPSk2QOCjRNJmNCYlNVWgimae1twhrlkWnqi1bqJ6N4W4W8TrwAJKaJK9MKpzUmDS7PMlBmzrTNj9Z6IoqetWh6g7aZ/bouI6EkBJJFBy6KUoktBFl0Ksjj+8E6+/ZV1TlbvLGeVyUVu9a6KgAWNlzW7K1iz2y+CBnXOY0Lf9kzoW8S4PqkhgpZvP8jVz38XEGNz06R+/GR8zwi9Qkmz2zizr7H4nDJlfMz97jh9ML9+y4gH+mr1Hj7+cSdnDOsa17VjpbLOyac/7vJtXzC6e0z9miOD28c/7PDFyby7ZBu3TOlP7w45Ufut2VVBhSkxw6Z9VXy/5QCje/mFzcod5VR4UuPabYqxvRMTPcFuc9X1scU3aa3ZXlZDt8LkpZqvjNHS43Jr6pzupLiummN60u02ctIblxrbakEfaxY4K8ESXfTEZumxik8KsdxEsfwEHzePN1I8UKjVxXKIlmiL/lbnFFIXrTU/bDtI18IsivMOHU+Nto6IntRgKpLIoNWRm+EwLA2mhZ/T5WbjvioWbz7AvA37mb9xP3sq6kL6ei1BL3xbArR9ETRvw35++tKigGxmd5x+eFw1AxrL+aO68d6S7czxFL27+4MVHN2/A4XZyf8sP/lxp09Y5Gc6OMEkhiNhjoFpKtFjzpinNTw3dxP3nD00ar/Fm0tD9r29eFuA6Jm/0f/dM6x7QcKJGIw4Fn98U8m+ajrmRbeU/ebtH3h78TaO7t+Bl68b12jh43JrqgMSGQSJnqD3V13vSpLoCczeZr5OVQJudFZhiLXO2M5jZemJFtMTq6XHyvUqOA4n1NIT0iNs+5DCpRHOGzHGKZbMbAmkb0uBuPBWS1N/tg9+sZZHZ66nMDuNGb+aFNdv8kc/7OC3b//AkK4FvHTdOE+cmkyG5kCCP1KDh4A+nse69u0jB0wLLYfDbmNgpzwuHdeThy8dyYLfH8+MXx3HfecewVnDu4a9Y+QVQDf+93tG/flLTnloNnd/sILPlu9kf2Vdq86q8tnynVz13Hc+wWO3KR68cHizCh4wLHL3nXsEmWnG196+ynr+8vGqJrmW2bXtrBFdY14IN7Wlp7LOycKSQPHy1qJtlFXXh+nhxxyX5uWjZTsDYkzmmUTPkVESN0RCKcW4Pn4x9fWa6Bmcquudvs99zvp9fG+KLUqU8pqGgKVIYU6ge1tW0N+1qi45yQwCUlY77I229Fgt6GONDUokpifE0hMm+Yul6LGInzETIoIiWHqCxZbZvS2cxSjWr9JYsreFiJzg9yYL3Zh5fOb6AAtoS+NNBV5W3cDT32yM0jqQX7y6hKp6F9+VlPLW4m2N8s2L977OO6bfpnhINI6ttSGWnhRAEhm0XZRS9C3OpW9xLpeN74nWmk37qpi3cT/zN5Yyf+N+9sZgCbIpI74gO8NOTrqDnAwH2el2/7NnX06GER/gfc7LdNCtMIue7bOjplROhNe+28If/vejb0GRmWbj8Z+MYsqg2CwfyaZn+2ymnTjQV7DtrcXbOHtEN44eEDlddjxs3l/Fd6bYlwtG94hrfF62ldbgduukpteet2F/yIK0psHFKwu2hCQl+HrNHu7/bA1Du+Vz7zlHsKgkVPRU1Dn5fMUuzhnZjQNV9czb4Bc90bLVReO4gcV8s86wys1cs5fbThkUsf32oBTzP24rY3SvxlUR32wSntnpdvKCLDt2myIv0+Fz6dtbWZeUOhuBKauDLD1JSmQQaxa4ROr0xGrpsXL1DXVnC1EOEdubtyPF9IRkffN0jPbejDEBKtQCFe+iUDzRY6eq3sXL8zY3+82yWLD6jQZj7q7eVUHn/MywdfyWN3Pc1bpGJE0w01az5YnoEYRWhFkE/WR8L7TWbNxXxfwoIsitjQWoEXNh/QUcjcLsNHoWZdOjKJuenkcvz3aXgsy4smdprXn86w088Pka3778TAfPXT02wN2vJbj2qD58sGwHy7eXA/B/by5l2okDOX9Ud9IdjbthUF7bwIvf+quf9++Yy/DuBTH372Gqa1PvcrO7opYuBcnLMme2mKTZlU8APTlrAxeN6eGzNH67YR83vLSYepeblTvLyclwsL3MLyomHVbsc5N7e/E2zhnZjee/LfG59BVmpwVYahJh8qCO3OuxxK3aWc6ug7V0Lgjv4ratLFD0fL+ljKuPatQQWLe7wve6f8dcyx/6Ph1yfAVzN+6tYlTPxgktMNzkvGSm2cnNMGeJS8DSY+Xe1hDbituqb0MUYRBs2QkX01Nvcec+Wla1kFiceNzbzCmrw4grK9ETS5a5WAjVb6lw77z5uPfjVWFFT0uuwcPNhYemr+PfX62jQ24606cdZ+lKHWvq+PA0zxtPlbkqokcQWjFKKfoV59IvjAiat2E/+yoTEznBlFU3UFZ90LeAM+OwKbq1y6JHu2xyMxw47Io0uw2HTeHwPfv3bTtQwwfLdvj6d8zL4KXrxjGoc8vXnXHYbfztvGGc/dhcXG7N3oo6fvfujzzy1TpunNSPi8b0iNkdrarOyQfLdvDxDztZu7siJD7rgtHd47ojlpPhoENuui/Zw5b91QmLnq2l1Xy9di892mUx6bCOaK0D4nmmnXgYj89cT0Wdk/JaJ3/6cAWTD+vInPX7+GLFroB6VM/PLfG97lGUxc2T+/vONWf9PhZvLuWFuZt8ba47qk+jY1v6dsihR1EWW0sNMTNr7R4uHtuTOqeLr1btoWNeRoCADrb0LLZwx4sXcyrZAR3zwo7TL3oafxfV5dbsr/K7G3bITeeAyf1wV3ktd3+wArfW/PaUQQG1gsJhVeA11qKvFbWh6fijx/TElsjAquZZsNtdqDtbkMgJOoVXtGitI7rChRNXVpatYDQabbHYDM3eFjkeqRV7Jbdafvn6En4+KTRVfjDN+dGGEwT//modYLhSPz+3hP87caBFtsHEZYvWOqG6XWZmrN5Nyb5qzh/dnYKs5Ht7tDZE9AhCG8JKBO2rrKeqzklVvZPqehdVdcZzZZ2T6jonVfUuquudVNX5n6vqnVTXuThQXc+2AzVRF0BOt2bz/mo2h0nDHYk+HXJ46dpxSXH7SRZDuxVw15mD+dOHK32LpB0Ha/nj+yt4ZMZ6bp7Uj8sn9Apr3Vq9q5xXF2zhf99vD8hoZibNrjh3ZOTaPFb0KMr2iZ67P1yJw6aorHNSU+/CpTWje7bj6qN6M75PEev2VLKwpJSaehd2m6LO6WbXwVpW7iwPcLH7x4XDOaJbQYC15vxR3cjJsPNHT4HXj37YyUc/7Iw6vjOGdWVMr3b0ap/tmw/n/2ee73hehoMrgwoJJoJSikkDO/LyfMNy9vWavfQoyuau91ewbk8lSsHL1473uSZuD7L0bC+r4WBNAwVZaew8WMPr323l6AEdImaUK6uu54uVuxnTqx19i3NZY7L0DOhkXXPIXIto496qkOMfLNvBzNV7OHlIJypqnUwZ1DFiXa79VXUB1oaO+Zk+9zmAbQdqfG6t+ZlpXHd0Hwqy0iK6QVrFGsUqeg5Y1CCLVPtFax0iZlxuTb3THWJJrbOwNpV7RNZXq3bz8Iz1dA2y7kWz9JRW1fPMNxt5dOZ6xkRwbwxefH6zbi8aHVDnJx6q6pwhYwvWdK8v3Bp0XFRPvLy/dAffbthPYdACPbhorRe3W7Nk6wH6dMhl24FqHvh8DcO6F/Drkw4LuCFVWefkLx+vwmFT/OmsIdhsKuYU9NsP1DBj9W6OGVBMmt1Gdb2Tsx+dG9Bmb2Ud01fu5vqXFgXs11pbunkCfLeplH99uZY0h40bj+vL58t3cfHYngzums+63RWc+K/ZFp/PdpRSzF67lx+2lUUd+7UvGOO556OV9CjK4q2fTWTZtjJ+9vLigHbfrt/PsQOKfduxfn+0NkT0pACSsvrQRSlFcV5Go1JmeoXTltIqtpRWs2V/jfHs2d5dnrglaWi3fF64ZhwdWmHx1SuP7M2kgR35z6z1vL14m+/u9N6KOu7+cCWvfreFu88cwsT+/nif7zaV8siMdb5YEyuy0+0M6JjL9cf0jak2TzA9i7J9BT5X7SwPOf7Zil18tmIXuRmOgGx4kfjTByvoW+xPS314l3w65mfyk/G9eGfxNst6HrkZDgZ3yec7U+KDUT0LmXrCAJRSXDSmR4D7opebJvdL2h3DyYOKfaLn0+W7+HS5Pw241nD5swu468zB/GR8rxBLDxiWssM653HpU/Mp2V/tu/P6wjVjmXRYx4C2WmtueGkx35WUkpfh4N2fT2TBRv97HxymRoj5c924r5KK2gZmrN7DqJ7tWLu7gltfWwLA/5ZsB2BI13w+uuXokMXUqp3l7Kmoo8jkApOTbic3wxH2hsGjM9fz6Mz19C3O4fxR3enbIYfhPQqx21TA3LOyetU73bjcmgaXmwyHjd3ldbTPTaey1km7nHQq65y8umCzL/7NzNrdlTz81TrOHdktYGwLS0p58IvQOQGGy+S7329n8qBizh1ppHC3svRU1DqpbXBx3YvGYmxZoE6gwelmd3ktDS43nfIzeff77QHHV++q8LlFTl8VmABjze4K3li4hbNHdAuxEN0bIalJsEXG6dJsLwu8ATTtzWUh/W78b+DCcdnWsoBtq+QgQnT2VtSFuHm/831ggP7kf3wdtv836/bx2MwNXD2xN2N7F/HVqt28u8Q/j16ev5nxfYpYYLpxdGTf9lTVO5nYrwPvLw2ccws2lQa0teLVBVt4dcGWkP3m63rpffvHIftmrzUs696yFuH45etLIx6PxNbSGib89SvLYz9uP8hPnlng2y6tip78pjWiWnPWJyE2lFJ3Y0pZXVxczJ490bMdJZsZM2YAMGXKlGa/ttB01Da42Hagmi2l1Ww7UENtg4sGl8bl1jhdbho8z063xunSON1unC5tZKkb3zPhtMWRSPZc21FWw5OzNvDawq0hd7FPO6IzZw3vyvNzSyx/2PIyHJw3qhsnDO5E/465dM7PbFSQ55uLtnLb2z8k3D8WHrp4BOd4rFArd5Rz8ZPzqKhzkpfp4IxhXZjYrwNH9e9AdrqdMx6Zw/o9lfQoyuLdm47yCeyaehf3fryStxZvo97pJjPNxm0nD+Kao3pHff+u8nLWjvPXWBr43QLs+aGioqbexfB7vki4qvwjl47kYE0Dd7y3PGB/UU4639w2mZwMB9X1Tlxuzbo9lZz3+Le+NmZRmWGHZXefYumyt3JHOac9/I1vu1thVojVKZgLR3fnjjMG+8Th8u0HOeOROSHt+nTIYeavJ6G1Zuhdn8eVxCAzzcbJQzoza+1eyiysNeGw2xQPXDCM2Wv38t7SHVHbv37DBMb3KWLmmj2+u8bROHlIJyYd1pHfvfuj5fGXrh3Hlc99F7a/TYXG5MTD6cO6UFHr9C0kI+EtGv3Q9HWJX1AQUpCSv53e7NccMmQIK1euXKm1HpJIfxE9KUCQpeeLQYMGDVi1qmlS8UZCRI/QXDTVXNtTXsuDX6zlzcVbo/rbH9GtgMsn9OTM4V3JTk+esHO5Ne9+v40Ne6t8VrzCrDQy0+yUVtXzyoLNPkuTUoYFolthFi63xm5TdC7IpHNBJkf2bc+6PZUhAuq8Ud3450UjAvZtL6thW2k1w3sUhizsy6rrWVhygAl9i8izyPBXWlXPd5tKGdGjMGKigYD3GKPoAZj2xtKAu6Ejexbyw7aDjXYNOuHwTvQrzuHJ2RvJSbdHFBSjOtp4d9qplsdq6l0c/sfP4r5+5/xM3v/FUXTKz+R37/7Ia9+F3gU+a3hXHr50JADnPj7XZwEUBEFoadqi6BH3thRAUlYLQnLomJ/J3y8YxmXje3LXBytYGuSOAjC+TxG3Hj+Aif3aN0naTrtNceGY8GmuTxnamU37qth+oIbBXfMjFsUb0aOQz5bvYsZqw/LbtziHP1sUIu1WmEW3QuuECYXZ6Zw4OHyK8aKcdE4Z2jns8cZy77lDmdCvPTvLahnSNZ/jD+/IltJqbn/nx4C6QPEyfdVupnvuDUWzoEzoEv6nMivdHpN1J5hd5bWMv+8rBnbKZe1u6wQI547yx4SN6FHY4qLn+EEd+Wp183sRCIIgJANZHQuCIAQxvEch7940kQcvHO5z5zqqf3tev2ECb/zsSI7q36FF6xT06ZDD0QM6RK0CrpThqnTC4R0Z36eIZ64cE1O2r9ZEdrqDi8b04JcnDOCEwZ1QStGrfQ6v3TCBkr+dzke3HB3zuZ64fHRcKcQBCtJheHHkn8pjB4av85TusPHABcM4PExMUDjBk5VmDyjwevoRXWIYbXR+dmzidU5uaERfQRCElqZt/foJgiA0Ezab4vzR3TlrRFfKqhsalSyiJWmfm8EzV41t6WE0GUO7FXDeqG68+/12CrLS+N2pg7jdIlbk5CGdOGVoZyYdVsxzczdx/2ehAffnjuzGqUM7c4Mnc9GQrvmc37OOtCgFYv94xhCK8zJ58dsSRvdq57OsAXQtyOTCMT24cEwPyqrr+XzFLn77jnUsi5lfnTQwwNVwTO8ifj6pH49/vcHyvRXlpPPad1tDjpl56OIRnDm8K0opnpgVep5InDS4U1zp0wuy0rjxuH78/bPQRAiCIAgtgYgeQRCECKTZbW1W8Bwq/P38YZwxrAv9inPpUpDFM3M2sX5PJR1yM9hXWYdS8FNPUcPMNDs/n9Sf647uw4NfrGXj3kruOH0wXQozyXAYIuP9m4+i3uVmTK92zJw5M+r1s9LtTDtxINNOHAjAWY/O8dXuue2UQb52hdnpXDy2Jy/P3+wrjmvm+avHkpVuJyfdwREWFqnbThnEbacMYvn2g9z6+hL2VdTx8KUjfZnoinMzeHjGeo7s254Xrh3L8u0HuejJ+bjcmmeuHMMJHjfF208dxGXjevLk7A28YpFRysvJQzrRrziXnAwHl4ztQWF2Oj2LstlSGj51/edTj6XB5aZX+2xqG9wxi54/nz2E5+eWsHFfaNrvaPTtkJNQP0EQDi1E9AiCIAhtmjS7jSmD/HFHn9x6DDsP1tCjXTYb91WS4bCHpH3OcNj5/WmHW55veI/CRo3ngQuG8+SsDYzq1Y5TLeKdbjquPze/+n3I/kmHFcfkNjm0WwEzfjXJl7zCy7STDuOG4/qRk25HKcXoXkXMvm0yLpemZ/vA99+zfTb3njM0RPRMO3Egpx3Rmf5hirE+d/UY/vLxKmaaCt3++ewhdMzPZPJhHQNq8eRlwqDOeaze5a93tPiOExh97/SAc/7y+AFccWRvrjiyN/sr60KOA0w9YQBnDu/K8Q/OCtj/qxMHcsWRvaiqd3HU32b49v/s2L48OXsjYMTJTZ92HLvLa7nkqfm+NpMPK+a5q8fypw9X+mofReLM4V35cFn0jHbxcPXE3jFdWxCExiOiRxAEQUgp0h02erU36ueEW7w3JYd1zuOfF48Ie/z0YV0Y1n0ydpvil68vYdnWg/zxzMFxx4nZLdzuglPEh0tQAUbM13kju/my4106rge3Hj8g4jX7d8zj6SvHcMI/Z1Gyv5rjBhZzxZG9w7Z/+kpDJHUpzOQPpx2Ow27jT2cN4a4PjKK4fz5nKFdM6OVr3z43gw33ncZny3ehlOEmN6Z3OzIcdrTWpDtsvhTmC/9wgs8KW5gN06cdy98+Xc3xh3fi0nE9+fnk/ry/dDuHdcqjT4ccerfPZniPQpZtLePsEV359yVGZryLxvTg1QVbLOsGHdW/PXPX76dbYRb3nz+MRy4dSb3Tzbcb9rGnvI7Th3Xh3e+38d/5W5g8qCMXjunOvR+t5LxR3Xlu7iZf8onv/nA8095Yxpz1/hpfa+89lXSHjaP7d+A3by/zFYI9aXAnnrpyDG635mBNA0/M2uATcNZ/k1y+/L9jefCLtTw6c73n80jjkrE9yXDYfPWpvAzrXsDL144nI83GuY9/a1kPbHyfIvp3zGV0r3a+GkTtc9I973d7zDXCYiUv08GdZwxu8nT9qcTlE3pS1+DmrcXbojdOMuv+Yp3NsrUjKatTDKXUisGDBw9esWJFs19bUlYLzYXMtbZNPCmrW5qmnmveiuxWNYCag037qpj6xlJyM+w8/pPRMReWPVjTwJItBxjfpz1Z6fGN3e3WzN2wj3bZ6QztFl9iiW837OOFuSWcdkQXX62peHC63KzfW8lhnfICRObW0mqq6p0M6JiH3abYU1EL2sjouO1ANR3zMgOsWLGwfk8lryzYzLEDipk8qCNbS6s5+7G51Da4eO7qsUwwJaoA+OzLrygpd3P9OcfjsAdea29FHbUNLmas3sNdH6zApmBUz3bkZTp44MLhvgLQTpebdXuM92cLEsVaa0thvX5PJSf8cxZKwV/PPYJLxvWM+T1anbOm3kV1vZPpq3aT4bAzvEchvYqy+WH7Qa57YSF2m+LOMwZz/OEd2Xaghp5F2QHz/8lZG3jn+20BST42/fU0fvXWMr7ffICLx/bE5XYztncR4/oUoZRia2k1095cysKSA5w/qjt3nzWYmWv2+ooDA3xz22T+8N5yKmsbuGlSf3aV1zKyRyFDuxUwa+1eHv5qHReP6cFzczexelcF1x7Vh9+fNgiH3cbdH6zwWeRe/el4OuZl0r1dVsC4vevp3/9vuS8F/QmHdwwpknvW8K5oYM66vfQtzuX6o/twqilRSVl1PQ98vsbS9XT1n63rhf247SBLth7gnJHdeHPhVu79eBUXjO7O388fxoJN+/nv/M1cd3QfRvZox2fTZ+CwwegJR7Onoo6cdAez1u6hMDudYwcWU17TwDH3+9163/zZkXTITadkfxVZaQ6O7Nc+5PrNhdTpEaROj3DIIXOtbSOiRzhUqXMaxZ2tijbHOtd2HaylKCc9bhEWiXqnm1qni3yLWlzJpM7pwmGzWVopg3G5NZv3V9GzKDtEBMaC0+Xmno9WsmZXBX84/XCGdS9MYMR+1u+pwKYUfYtzY7r2/qp6OuZlNDrTZ3W9kxmr9zCiRyHd22VH7xCFWObZj9sO8uycjVw2vhfj+hQ1+prJQur0CABTgbu8G/v3J167QhAEQRCEpiHDYaexWeNjLQIcD+kOW1JFVDi8yUJiwW6LTWCEw2G3cY9FXbJEicdV1mG30Sk/OX+n7HQHZwzrmpRzxcoR3Qt4yOP+mUpInZ7U4CGgj+exrn37ljM9CoIgCIIgCEJrQyw9KYDWugwoA1BKNdhsomUFQRAEQRAEwYusjgVBEARBEARBSGlE9AiCIAiCIAiCkNKI6BEEQRAEQRAEIaUR0SMIgiAIgiAIQkojoqcFUUr9XCm1QSlVq5RappQ6o6XHJAiCIAiCIAiphoieFkIpdTnwCPAKcBbwPfA/pdSEFh2YIAiCIAiCIKQYkrK65fgj8JzW+o+e7S+UUkM8+09ruWEJgiAIgiAIQmohlp4WQCmVDfQHvgw69BVwvFIqo/lHJQiCIAiCIAipScqLHqXUaKXU7Uqpd5VS25RSWimlY+iXpZS6Rym11hNzs0Mp9ZxSqlsShpUJKKA+aH8dkA70ScI1BEEQBEEQBEHg0HBvuxM4O54OSqlMYAYwAdgJvA/0Bq4BzlBKTdBab0x0QFrrUqXUAWAs8J7p0FjPc1Gi5xYEQRAEQRAEIZBDQfTMA34AFnoeJUA097E7MATPPOAkrXUlgFJqGvAg8BwwydtYKVUIdI5yzmqt9RbT9pPAL5RS84C5wCXASZ5j7ijnEgRBEARBEAQhRlJe9Git/27eVkpFbK+USgd+4dm82St4POf6p1LqKuA4pdRorfViz6FLgP9EGcosTEIJuBc4HPjQs70d+AtwF7AryrkEQRAEQRAEQYiRlI/pSYCjgAJgg9Z6icXxtz3PZ3p3aK2f0FqrKI9J5pNorau01ucAXYGhGHE8FcAerXVJ8t+WIAiCIAiCIByapLylJwGGe56/D3Pcu39YMi6mtd4J7PRkbLsGeCGWfkqpFWEO9auqqmLGjBnJGF5cVFVVAbTItYVDC5lrbRtVXR3gDzx79mx0dnaLjScSMteE5kLmmtActOV55h17oojoCaWn53lbmOPe/b0acxGl1FkYVp41nuepGH+P+xpzXkEQBEEQBEEQAhHRE0qu57k6zHGvzMxr5HVcGLFD/YBKjNie27XWB2PprLUeYrVfKVW+a9eujFtuuaWRw4sfrwLPyclp9msLhxYy19o4bjd1m/wJMDN+8xuwtU5va5lrQnMhc01oDtryPNu1axdAj0T7i+hpIbTWHwMfN8Gpq+vq6li5cuVWi2M2oD2wn/AZ4qK1iXS8n+d5Q7yDbgXE8tm0xms15lyJ9I21j8y18MhcC2b16sZcS+aaNc05z5J9veb8XmvOuRatv8y15r9Wa5xr8p0Wnp6ATSlVqLUui7u31vqQegC1xtsOe/yfgAb+Geb4cM/xxS39XhJ47709Y++daJtIx4EVwIqWfp9N9dm0xms15lyJ9I21j8w1mWuN6RtPe5lrLT/Pkn29VJ1rMcxDmWvNfK3WONfkO63p/v6t05+gZfHW0uke5rh3/+ZmGIsgCIIgCIIgCI1ERE8oyzzPo8Ic9+7/oRnGIgiCIAiCIAhCIxHRE8pc4CDQTyk1wuL4BZ7nDy2OtXbKgD95nhNtE8s52iJlNN/7Sua1GnOuRPrG2ieWdtHaxHqttkYZMteS2T6WttHaxHO9tkIZzfueknm9xpwr3r7xtI+lbaQ28Y6trVBG2/xOa+z54u0ba/tY2kVrE+/Y2gplNOJ9KY+P3CGDUqoWyNBaqwht7gX+AHwLnKS1rvLsnwY8CMzSQcVGBX/tIB0ms5wgJAuZa0JzIXNNaC5krgnNwaE8z1I+e5tS6nTgTtOudM/++aZ9f9ZGNjUv9wInABOBdUqpbzDq8owH9gLXNumgBUEQBEEQBEFIGilv6VFKXQ08H6XZNVrrF4L6ZQG/Ay7DyAleCnwG3Km1Dle4VBAEQRAEQRCEVkbKix5BEARBEARBEA5tJJGBIAiCIAiCIAgpjYgeQRAEQRAEQRBSGhE9giAIgiAIgiCkNCJ6BEEQBEEQBEFIaUT0CIIgCIIgCIKQ0ojoEQRBEARBEAQhpRHRI7QISqkxSqmXlFLrlVJaKXVvS49JSE2UUhcppT5WSu1USh1USs1WSh3d0uMSUgul1FVKqUVKqTKlVJVS6nul1CUtPS4htVFKHaGUciqlpH6gkHSUUld71mjBj0ktPbZEcLT0AIRDlqOACcAcoEMLj0VIbaYC64CbgUrgGuArpdQ4rfWylhyYkFK0A94DlgK1wDnAa0qpWq31ey02KiHVeQjY39KDEFKeowGXaXtlSw2kMUhxUqFFUErZtNZuz+sS4L9a6ztadlRCKqKUaq+13m/atgE/AnO11je03MiEVEcpNQfYqbW+sKXHIqQeSqlzgH8BrwNXaK27t+yIhFRDKXU18DyQprV2tvBwGo24twktglfwCEJTYxY8nm03sBzo0zIjEg4h9gNpLT0IIfVQSqUD/wBuB+paeDiC0CYQ0SOEoJQarZS6XSn1rlJqm9eHM4Z+WUqpe5RSa5VStUqpHUqp55RS3Zpj3ELboyXmmlLKDowF1ifjPQitn+acZ0oph1IqXyl1MXAi8GQy34vQumnGuTYV2Ku1fiOpb0BoMzTz7+d2T+zYD0qpC5L4NpoVcW8TQlBKvQecHbxfa60i9MkEZmLE6ewEvgF6A+OAvcAErfXGMH1LEPe2Q5Lmnmue/r8EHgRGaq1/bMTwhTZCc80zpVRnT1sw/N9/rrV+qvHvQGgrNMdcU0p1AtYCp2it5yml7gauF/e2Q4tmmmsnA6OBBUAWcB1GvOI5Wuv3k/NOmg9JZCBYMQ/4AVjoeZQAGVH63IHxTzQPOElrXQmglJqGscB8DpjUNMMV2jDNOteUUuOBvwH3iuA5pGiuebYPw4qYB5wCPKqU2q+1ficp70JoCzTHXLsP+ExrPS+ZAxfaHE0+17TWnwOfm/p/pJT6Bvg90OZEj1h6hKgopWqBjHB3Dzy+xXuAAmCU1npJ0PFlwDBgjNZ6sUX/EsTSI9C0c00p1RuYD8wGLtby5XfI0tTfaaZ2TwPHaa0HJm3wQpsi2XNNKTUUWIyxcN3kaXY7cAUwBKjWWtc3yZsRWjXN+L32a+AvWutoAqvVITE9QjI4CuOfaEPwP5GHtz3PZzbfkIQUJaG5ppQqBD7GuBN2lQgeIQrJ+k5bCvRN4riE1CPeudYfSAe+Bw54Hr8FunpeX9ukoxXaMof8Wk3c24RkMNzz/H2Y4979w5phLEJqE/dc89zdehfIBqZorWuabnhCipCs77SJGEJbEMIR71ybA0wOanM1cDpwIUasjyBY0ejvNaWUAs4FrERTq0dEj5AMenqew1WE9u7v5d2hlCoGjvNsZgODPBlBqrTWnzbJKIVUIO65BjyOMdd+CvRRSnlTVdeFudslCIl8p80E3gFWA5kYAcaXAVILSohEXHNNa70P+NrcQCk1CeP7LGC/IASRyPfa28B3GLFDGcD1wJHAWU00xiZFRI+QDHI9z9Vhjld5nvNM+4YAb5m2z/c8NmNkEhEEKxKZaydguPI+G9RW5poQjkTm2TLgFqCH5/hK4Eyt9UdNMkIhVUhkrglCIiQy19ZiCB1vZsAlwBla60+SP7ymR0SP0CJ47kiFTasoCMlCa927pccgpD5a66kYtVMEoVnRWt8N3N3CwxBSEK317zEytaUEkshASAaVnufsMMdzPM8VzTAWIbWRuSY0BzLPhOZC5prQXBzyc01Ej5AMtniewxVG8+7f3AxjEVIbmWtCcyDzTGguZK4JzcUhP9dE9AjJYJnneVSY4979PzTDWITURuaa0BzIPBOaC5lrQnNxyM81ET1CMpgLHAT6KaVGWBy/wPP8YbONSEhVZK4JzYHMM6G5kLkmNBeH/FwT0SM0Gk/150c9m48ppbx+oSilpmHkfJ8VqcKvIMSCzDWhOZB5JjQXMteE5kLmGigpTC4Eo5Q6HbjTtGscRqa1BaZ9f9Zaf2zqk4lRO2A8sBP4BiPX+3hgLzBBa72xaUcutDVkrgnNgcwzobmQuSY0FzLX4kdSVgtWFGP8AwQzPqiND611rVJqMvA7jIJ85wClwAvAnVrrcMWwhEMbmWtCcyDzTGguZK4JzYXMtTgRS48gCIIgCIIgCCmNxPQIgiAIgiAIgpDSiOgRBEEQBEEQBCGlEdEjCIIgCIIgCEJKI6JHEARBEARBEISURkSPIAiCIAiCIAgpjYgeQRAEQRAEQRBSGhE9giAIgiAIgiCkNCJ6BEEQBEEQBEFIaUT0CIIgCIIgCIKQ0ojoEQRBEARBEAQhpRHRIwiCIAiCIAhCSiOiRxAEQRAEQRCElEZEjyAIwiGMUupWpdQKpVSdUkorpb5u6TEJ0fH8rcyPC4KOf+3Z3zvG873gaX91LNdtxLgLLcY+KdHzCYIgxIqjpQcgCIIgtAxKqfOAfwMHgA+AKmB1iw5KiIcq4G3P65IWHEc81AMvel4fDfRrwbEIgnAIIaJHEATh0OUcz/MFWusZLTkQISH2aa2vbulBxIPWuhq4GgzrEiJ6BEFoJsS9TRAE4dClu+d5Y4uOQhAEQRCaGBE9giAIhxhKqbs9cRmTPbs2BcdXmGNClFKXKaXmK6UqlFJlpvMopdSlSqkZSqkDSqlapdQqvWlyNQAACDpJREFUz/mzw1y7h1LqZaXUXqVUtVJqsVLqcs91QmKKTLEmk8KcTyulSsIcG6+UeksptVMpVa+U2qaUekYp1TPcZ6KUulopdYRS6gPPe6pSSs1SSk2M8HmOV0q9rpTa7omN2qmU+kop9VPP8Qyl1D7P+y0Mc46JnuvPCnedZKCUKlBKzfZc6xGllErCOUss4nQCHskYuyAIQmMQ9zZBEIRDj6UYcRWnAJ2Ad4BKz7FdQW1/B1wPzAU+AnoAKKVswH+BSz19F2HEBo0B7gJOVUpN0lrXeE+klOoDfAt0xrAuTQe6AS8BjyXzDSqlfg484tlcCHwDHAZcB5yllDpOa73KousYz1g2AJ8Dg4Bjga+UUmO11suDrvNL4J8YNxEXA7OBDsAw4AHgaa11nVLqRWAa8JMw7/WnnuenEnvH0VFKdQI+A0YA92it70rSqd/GeM/BdAZOBtxJuo4gCELCiOgRBEE4xNBavwe857GqdAJ+rbUuCdP8SmCK1jrYAvErDMHzNXCp1noXgFIqHXgcQ1zcBdxu6vM4xkL4OeBnWmunp8+ZwP8a+768KKUmAA8DO4GztdaLTceuA54BngcmWHS/Gfil1vphU59/AVOB2zA+D+/+Y4F/YYi+c7XWX5mOOYCTTOd9Evg/DHETIHqUUvnARRii8Z2433AMeLK4fYkRQ3Or1vqRyD1iR2v9a4vrZQLeOXN78HFBEITmRtzbBEEQhEg8Gyx4PAv62zCyh13iFTwAWut64BYMi9ENHosQSqm+GJalcmCaV/B4+nyIPwtZMrgdsAM3mgWP51rPYmSqG6+UGmnRd65Z8Hi41/N8rMV1FPAXs+DxXMeptf7EtL0WmAkMV0qNDTrPZUA28LLWujbqu4sTpdQQDEtdb+CKKILn+SS5qT0NjMN4Tw8kPnpBEITkIJYeQRAEIRIfWOwbheHO9KXWenfwQa11jVJqMXA6MABYg5GeGOAzrfVBi3O+Blzc2MF6RNbxQDWGe5oV3wBnYSzKlwQd+yK4sdZ6v1KqFOhiuo4DmOTZjNUl7QlgCoa1Z6Fpf1O6tk3AsCxlYVijPorSfi6wPsLxq6JdUCn1W+ByYAH+9yYIgtCiiOgRBEEQIrHFYl9vz/OJMdz974Aherp6tjeHaVcS98jCXy/X87o+Spy+VRzKtjBtK4Ai03Z7DCFRqrU+EOPY3sOwgF2qlJqmta5USo3CEJHztNYrYjxPPLyM8Vt/cQyCB+AZrfUL4Q4qpSKKHqXUGcB9GJ/jOVrrujjGKgiC0GSI6BEEQRAiYeVu5XWNXo9hGYjE/uQOx4/XdS4I775KosfHWImMJgu611o3KKWeA34PXIIRW3S95/DTTXTZ14ArgHuUUrPNrojJRik1GHgVqMMQPE12LUEQhHgR0SMIgiDEi9casjqO4pg7Pc+9whwPt7/e85xrcayHxb59GELNDVyjtW6qdMn7gBqgSClVqLUui7HfUxixQD9VSr2KEc9TDrzRJKOEPwI7gN8CMzwZ9fYk+yJKqfbAh0AeRpzX4ihdBEEQmhVJZCAIgiDEy0LgIHCcUqooWmMPczzPp3iylQVzSZh+XrE00OLYicE7PAkSvgbyMWJ7mgSttctzHYAb4ui3GSNt9DiMBAkFwCta6+pkj9F0zduBfwCHYwif4mSe3xPf9BbQF7hXa91UAk4QBCFhRPQIgiAIceGJ07gf467+u57MbAEopboppa4w9dmAkSQgH3hQKWU3tT0NuDDM5byZ427yWBO8fUYA94Tp8xcMS8/zVkVNlVK5SqlrlVJZ4d5jjPwd0MAflFKTzQeUUg7P+7LiCc/z/3mem8q1zYfW+jcY9YSGYNQcsopnSpSHMQrdvodhWRIEQWh1iHubIAiCkAh/wyjceQWwSim1BNgEpGMUAR0M/IARSO/lJozipNcDk5VSCzESHByDUcPnZovrzMQQPscBK5VSczESEIzHWGyH1IjRWs9RSt0MPArMVEotB9YCDRhJGEYAGcC7GC5qCaG1nqWUug1DAM5QSi0C1nnGN9xzjUKLrp8AWzHc8xZprYMzyDUJWutfecTmLzGEzxStdaNirpRSPTD+rgAuDKFpde2rG3MdQRCExiKWHkEQBCFutNZurfWVwNkYRS/7AOdjpKauBR4Arg3qsxFDrLyKIQbOwbD8XIPhfmV1He25xhMYVpXTMLKo/dJjvQg3vieAMcCLGBapM4CTMWKDXvFsW6XOjgut9T8wBNn/gJ7ABcBQ4EeMAq5WfVz4LVhNbuUJuvZU4BFgGDA9DvfEcNhNr8/HSGlt9RAEQWhRVNPFeAqCIAhCbCilemNYimZprSe17GiaFqVUNrAdw9uiq9a6IoFzaGCz1rp3kofXbCilXsAQRJO11l+37GgEQUh1xL1NEARBEJqXmzEsXY8lInhMdPAIB4BHtdaLGjuwpsYj+B73bB4dqa0gCEIyEdEjCIIgCE2MJwnD34FOGC56lRhxUY0hB7/r2EdAqxc9GDFf4u4mCEKzI6JHEARBEJqePOA6jLpDS4Bfa623Re4SHq11aLaANoCnnlGbHLsgCG0biekRBEEQBEEQBCGlkextgiAIgiAIgiCkNCJ6BEEQBEEQBEFIaUT0CIIgCIIgCIKQ0ojoEQRBEARBEAQhpRHRIwiCIAiCIAhCSiOiRxAEQRAEQRCElEZEjyAIgiAIgiAIKY2IHkEQBEEQBEEQUhoRPYIgCIIgCIIgpDQiegRBEARBEARBSGlE9AiCIAiCIAiCkNKI6BEEQRAEQRAEIaUR0SMIgiAIgiAIQkojokcQBEEQBEEQhJTm/wEVDnWpGhZ2qwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(dpi=150)\n", "ax.set(xlabel='frequency [kHz]', ylabel='power spectral density [V$^2$]')\n", "ax.plot(ref_saw_f, ref_saw_psd, label='ref_saw')\n", "ax.plot(mixer_f, mixer_psd, label='mixer')\n", "plt.axvline(f_base, label=f'base frequency f={f_base:.0f} kHz', color='C3')\n", "ax.loglog()\n", "plt.grid()\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Extract the baseband from the signal
\n", "\n", "The instantaneous phase and amplitude of the base signal can be inferred only for the baseband, i.e. by removing higher and lower frequencies (i.e. extracting the base sine wave from the reference saw-tooth signal)." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "base_band_hwidth = 50 # kHz\n", "base_band_filter = sigproc.iirfilter(8, [f_base - base_band_hwidth, f_base + base_band_hwidth], fs=f_s, btype='bandpass', output='sos')" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "def freq_filter(signal, sos_filter):\n", " signal[:, 1] = sigproc.sosfiltfilt(sos_filter, signal[:, 1])\n", " return signal" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "mixer_filtered = freq_filter(mixer, base_band_filter)\n", "ref_saw_filtered = freq_filter(ref_saw, base_band_filter)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "cut 0.1 ms from the beginning and from the end for better signal processing" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "mixer_filtered = mixer_filtered[(mixer_filtered[:, 0] < (mixer_filtered[-1, 0] - 0.1)) & ((mixer_filtered[0, 0] + 0.1) < mixer_filtered[:, 0])]\n", "ref_saw_filtered = ref_saw_filtered[(ref_saw_filtered[:, 0] < (ref_saw_filtered[-1, 0] - 0.1)) & ((ref_saw_filtered[0, 0] + 0.1) < ref_saw_filtered[:, 0])]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define signal processing functions
\n", "\n", "func find_peaks - finds peaks with optimal output array" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "def find_peaks(data):\n", " peaks_indexes, _ = sigproc.find_peaks(data[:, 1])\n", " return np.vstack((data[peaks_indexes, 0], data[peaks_indexes, 1])).T" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func initial_phase_shift - mixer and ref_saw signals are in general a bit phase shifted from each other -> it calculates \"initial\" phase shift and removes it" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "def initial_phase_shift(peaks, peaks_ref):\n", " phase_mean = peaks[0, 0] - peaks_ref[0, 0]\n", " peaks_ref[:, 0] += phase_mean\n", " return peaks_ref" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func cut_edges - cut first and last data point, which is distorted from the spectral filter" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "def cut_edges(peaks, peaks_ref):\n", " peaks = peaks[(peaks[0, 0] < peaks[:, 0]) & (peaks[:, 0] < peaks[-1, 0])]\n", " peaks_ref = peaks_ref[(peaks_ref[0, 0] < peaks_ref[:, 0]) & (peaks_ref[:, 0] < peaks_ref[-1, 0])]\n", " return peaks, peaks_ref" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func smooth - classic func for signal smoothing" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "def smooth(y, box_pts):\n", " box = np.ones(box_pts) / box_pts\n", " y_smooth = np.convolve(y, box, mode='same')\n", " return y_smooth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func without_correction - a sum of basic operations" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "def without_correction(mixer_filtered, ref_saw_filtered):\n", " peaks = find_peaks(mixer_filtered)\n", " peaks_ref = find_peaks(ref_saw_filtered)\n", " peaks_ref = initial_phase_shift(peaks, peaks_ref)\n", " peaks, peaks_ref = cut_edges(peaks, peaks_ref)\n", " return peaks, peaks_ref" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func find_nearest - finds the nearest peak of the given one" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "def find_nearest(array, value):\n", " array = array.copy()\n", " x, y = array.shape\n", " array_data = np.zeros((x, 1))\n", " for i in range(0, x):\n", " array_data[i, 0] = array[i, 0]\n", " idx = (np.abs(array_data[:, 0] - value)).argmin()\n", " return array_data[idx]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func calc_dphase_unchanged - calculates dphase from unrepaired data" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "def calc_dphase_unchanged(peaks, peaks_ref):\n", " x_peaks, y_peaks = peaks.shape\n", " x_ref_peaks, y_ref_peaks = peaks_ref.shape\n", " dphase = np.ones((min(x_peaks, x_ref_peaks), 2))\n", " for i in range(0, int(len(dphase))):\n", " dphase[i, 0] = peaks[i, 0]\n", " dphase[i, 1] = peaks[i, 0] - peaks_ref[i, 0]\n", " return dphase" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func calc_lost_phase - calculates lost phase in the signal - to define how much the signal was damaged" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "def calc_lost_phase(peaks, peaks_ref):\n", " dphase = calc_dphase_unchanged(peaks, peaks_ref)\n", " time_interval = 0.1 # ms\n", " indexes = np.argwhere(dphase[:, 0] > (dphase[-1, 0] - time_interval))\n", " data = dphase[indexes[:, 0]]\n", " return 2 * math.pi * f_base * np.average(data[:, 1]), dphase" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func optimizing_cycle - defines the most probable parts of the data, where the signal was damaged and deletes the corresponding waveforms from the reference signal, because these waveforms did not travelled properly through the plasma" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "def optimizing_cycle(number_of_bad_peaks, deriv_sort, distance, peaks, peaks_ref):\n", " bad_peaks_indexes = np.empty((0, 1))\n", " k = 0 # help variable\n", " l = 0 # help variable\n", " while k < number_of_bad_peaks:\n", " index = np.argwhere(peaks[:, 0] == deriv_sort[l, 0])\n", " if (len(bad_peaks_indexes) != 0 and (abs((index[0, 0] - find_nearest(bad_peaks_indexes, index[0, 0]))) < distance)) or (t_plasma_end < peaks[index, 0]) or (peaks[index, 0] < t_plasma_start):\n", " l += 1\n", " else:\n", " bad_peaks_indexes = np.vstack((bad_peaks_indexes, index[0, 0]))\n", " peaks_ref = np.delete(peaks_ref, index, 0)\n", " k += 1\n", " l += 1\n", " return bad_peaks_indexes, peaks_ref" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func repair - creates the most plausible repair of the given damaged interferometer data (probably caused by the scatter of the probing wave from the plasma, plasma instability, ...)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "def repair(lost_phase, dphase, peaks, peaks_ref):\n", " # make repairing cycle\n", " number_of_bad_peaks = round(lost_phase / (2 * math.pi))\n", " if number_of_bad_peaks >= 1:\n", " smooth_factors = np.zeros((0, 1))\n", " distances = np.zeros((0, 1))\n", " varieties = np.zeros((0, 1))\n", " for smooth_factor in range(1, 50):\n", " deriv = dphase.copy()\n", " deriv[:, 1] = np.gradient(dphase[:, 1])\n", " deriv[:, 1] = smooth((deriv[:, 1]), smooth_factor)\n", " deriv_sort = deriv.copy()\n", " deriv_sort = deriv_sort[deriv_sort[:, 1].argsort()[::-1]]\n", " for distance in range(1, 50):\n", " bad_peaks_indexes, repaired_ref_peaks = optimizing_cycle(number_of_bad_peaks, deriv_sort, distance, peaks, peaks_ref)\n", " dphase_final = calc_dphase(peaks, repaired_ref_peaks)\n", " dphase_final[:, 1] = smooth(dphase_final[:, 1], 100)\n", " smooth_factors = np.vstack((smooth_factors, smooth_factor))\n", " distances = np.vstack((distances, distance))\n", " varieties = np.vstack((varieties, calc_curve_length(dphase_final)))\n", " all = np.hstack((smooth_factors, distances, varieties))\n", " varieties_min = varieties.argmin()\n", " best_smooth_factor = int(all[int(varieties_min), 0])\n", " best_distance = int(all[int(varieties_min), 1])\n", " else:\n", " best_smooth_factor = 10\n", " best_distance = 10\n", " deriv = dphase.copy()\n", " deriv[:, 1] = np.gradient(dphase[:, 1])\n", " deriv[:, 1] = smooth((deriv[:, 1]), best_smooth_factor)\n", " deriv_sort = deriv.copy()\n", " deriv_sort = deriv_sort[deriv_sort[:, 1].argsort()[::-1]]\n", " bad_peaks_indexes, repaired_ref_peaks = optimizing_cycle(number_of_bad_peaks, deriv_sort, best_distance, peaks, peaks_ref)\n", " dphase_final = calc_dphase(peaks, repaired_ref_peaks)\n", " dphase_final[:, 1] = smooth(dphase_final[:, 1], 100)\n", "\n", " return dphase_final, number_of_bad_peaks" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func calc_dphase - calculates dphase" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "def calc_dphase(mixer_peaks, repaired_ref_peaks):\n", " x_peaks, y_peaks = mixer_peaks.shape\n", " x_ref_peaks, y_ref_peaks = repaired_ref_peaks.shape\n", " dphase_final = np.ones((min(x_peaks, x_ref_peaks), 2))\n", " for i in range(0, int(len(dphase_final))):\n", " dphase_final[i, 0] = repaired_ref_peaks[i, 0]\n", " dphase_final[i, 1] = mixer_peaks[i, 0] - repaired_ref_peaks[i, 0]\n", " dphase_final[:, 1] *= 2 * math.pi * f_base\n", " return dphase_final" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "func calc_curve_length - calculates the length of the dphase curve as a key parameter to decide, whether the repair is good enough" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "def calc_curve_length(dphase_final):\n", " x, y = dphase_final.shape\n", " length = 0\n", " for i in range(1, x):\n", " length += np.sqrt(((dphase_final[i, 0] - dphase_final[i - 1, 0]) ** 2) + (dphase_final[i, 1] - dphase_final[i - 1, 1]) ** 2)\n", " return length" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Final signal processing cycle" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "# prepare data (without final data correction)\n", "peaks_no_corr, peaks_ref_no_corr = without_correction(mixer_filtered, ref_saw_filtered)\n", "# calculate lost phase\n", "lost_phase, dphase_zero = calc_lost_phase(peaks_no_corr, peaks_ref_no_corr)\n", "# make final data repair\n", "dphase_final, number_of_bad_peaks = repair(lost_phase, dphase_zero, peaks_no_corr, peaks_ref_no_corr)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Estimation of the electron density
\n", "\n", "The ordinary wave (O-mode) with a carrier frequency $\\omega$ traveling through a collisionless plasma with the plasma frequency $\\omega_{p} = \\sqrt{\\frac{n_e e^2}{\\epsilon_0 m_e}}$ has a refractive index $$N_O=\\sqrt{1-\\frac{\\omega_p^2}{\\omega^2}}$$\n", "Under the assumption that the carrier wave frequency is much larger than the plasma frequency $\\omega>>\\omega_p$ this formula can be expanded into a Taylor series as $$N_O\\approx 1-\\frac{\\omega_p^2}{2\\omega^2}$$\n", "A wave traveling through a medium with a refractive index $N(l)$ accumulates a total phase shift $\\varphi = \\frac{\\omega}{c} \\int N(l) \\mathrm{d}l$. Therefore, in comparison to a wave traveling in vacuum (or clear air) with $N\\approx 1$, the wave traveling through the plasma over a chord with length $L$ accumulates a relative phase shift of $$\\Delta \\varphi = \\frac{e^2}{2\\omega c\\epsilon_0 m_e}\\int\\limits_L n_e(l) \\mathrm{d}l$$\n", "Therefore, it is possible to estimate the line-averaged density $\\bar n_e = \\frac{1}{L} \\int\\limits_L n_e(l) \\mathrm{d}l$ from the detected phase shift between the reference and mixer signals." ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": [ "omega_carrier = 2 * np.pi * 71e9 # 71 GHz microwave generator\n", "a = 0.085 # limiter radius [m]\n", "L = 2 * a # central plasma chord estimate\n", "prop_const = constants.elementary_charge ** 2 / (2 * omega_carrier * constants.speed_of_light * constants.epsilon_0 * constants.m_e)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "ne_lav = dphase_final.copy()\n", "ne_lav[:, 1] = ne_lav[:, 1] * (1 / (prop_const * L))\n", "ne_lav = ne_lav[(ne_lav[:, 0] >= 0) & (ne_lav[:, 0] <= (t_plasma_end + 5))]" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "dphase_zero[:, 1] *= 2 * math.pi * f_base\n", "dphase_zero[:, 1] = smooth(dphase_zero[:, 1], 100)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "ne_lav_zero = dphase_zero.copy()\n", "ne_lav_zero[:, 1] = ne_lav_zero[:, 1] * (1 / (prop_const * L))\n", "ne_lav_zero = ne_lav_zero[(ne_lav_zero[:, 0] >= 0) & (ne_lav_zero[:, 0] <= (t_plasma_end + 5))]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Comparison of the final line-averaged electron density between the damaged and repaired signal" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(dpi=200)\n", "ax.plot(ne_lav_zero[:, 0], ne_lav_zero[:, 1]/1e18, label='damaged signal', linestyle='dotted', color='red')\n", "ax.plot(ne_lav[:, 0], ne_lav[:, 1]/1e18, label='repaired signal', color='deepskyblue')\n", "if is_plasma:\n", " for t in (t_plasma_start, t_plasma_end):\n", " plt.axvline(t, color='k', linestyle='--')\n", "else:\n", " ax.set_ylim([-0.1, 5])\n", "ax.set(xlabel='time [ms]', ylabel='$\\\\bar n_e$ [10$^{18}$ m$^{-3}$]')\n", "plt.title('Line-averaged electron density (repaired waveforms: {})'.format(number_of_bad_peaks))\n", "plt.legend();\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Final figure of the temporal evolution of the line-averaged electron density" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(dpi=200)\n", "ax.plot(ne_lav[:, 0], ne_lav[:, 1]/1e18, label='$\\\\bar n_e$', color='deepskyblue')\n", "if is_plasma:\n", " for t in (t_plasma_start, t_plasma_end):\n", " plt.axvline(t, color='k', linestyle='--')\n", "else:\n", " ax.set_ylim([-0.1, 5])\n", "ax.set(xlabel='time [ms]', ylabel='$\\\\bar n_e$ [10$^{18}$ m$^{-3}$]')\n", "plt.title('Line-averaged electron density (repaired waveforms: {})'.format(number_of_bad_peaks))\n", "plt.savefig('icon-fig.png')\n", "plt.legend()\n", "plt.grid()\n", "plt.savefig('icon-fig.png')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Save data" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "np.savetxt('ne_lav.csv', ne_lav, delimiter=\",\")\n", "ne_lav_plasma = ne_lav[(t_plasma_start < ne_lav[:, 0]) & (ne_lav[:, 0] < t_plasma_end)]\n", "for m in ('mean', 'max'):\n", " v = getattr(ne_lav_plasma[:, 1], m)()\n", " with open(f'ne_lav_{m}', 'w') as f: f.write(f'{v:.3e}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 2 }