{ "cells": [ { "cell_type": "markdown", "id": "5e01da03", "metadata": {}, "source": [ "## Range bias between Sentinel-1A and Sentinel-1B" ] }, { "cell_type": "code", "execution_count": 1, "id": "f09f8d7c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Go to directory /Users/yunjunz/Papers/2022_Geolocation/figs_src/S1\n" ] } ], "source": [ "%matplotlib inline\n", "import os\n", "import numpy as np\n", "import datetime as dt\n", "from matplotlib import pyplot as plt, ticker, colors, patches\n", "from mintpy.objects import timeseries\n", "from mintpy.utils import ptime, readfile, writefile, utils as ut, plot as pp, s1_utils\n", "plt.rcParams.update({'font.size': 12})\n", "\n", "work_dir = os.path.expanduser('~/Papers/2022_Geolocation/figs_src/S1')\n", "os.chdir(work_dir)\n", "print('Go to directory', work_dir)" ] }, { "cell_type": "markdown", "id": "38350f32", "metadata": {}, "source": [ "### Read and fit time-series" ] }, { "cell_type": "code", "execution_count": 2, "id": "3f34d0f4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "warm up utils functions.\n" ] } ], "source": [ "def get_timeseries_with_bias_est(ts_file, lalo):\n", " # read data\n", " lookup_file = os.path.join(os.path.dirname(ts_file), 'inputs/geometryRadar.h5')\n", " dates, ts_dis, ts_std = ut.read_timeseries_lalo(lat=lalo[0], lon=lalo[1], ts_file=ts_file, lookup_file=lookup_file,\n", " win_size=20, method='mean', unit='cm', print_msg=True)\n", " # estimate S1AB bias\n", " (bias_AB, flagA, flagB,\n", " dates_fit, ts_fitA, ts_fitB) = s1_utils.estimate_S1AB_bias(os.path.dirname(ts_file), dates, ts_dis)\n", " print('S1 A/B est. bias [cm]:', bias_AB)\n", "\n", " # shift S1A to median zero\n", " shift = np.nanmedian(ts_dis[flagA])\n", " ts_dis -= shift\n", " ts_fitA -= shift\n", " ts_fitB -= shift\n", "\n", " return dates, ts_dis, ts_std, bias_AB, flagA, flagB, dates_fit, ts_fitA, ts_fitB\n", "\n", "print('warm up utils functions.')" ] }, { "cell_type": "markdown", "id": "9182f2ef", "metadata": {}, "source": [ "### Plot (a) - Point Time Teries" ] }, { "cell_type": "code", "execution_count": 3, "id": "711ee6ae", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "input lat / lon: -21.45 / -69.15\n", "corresponding y / x: 119 / 208\n", "S1 A/B est. bias [cm]: [12.13312]\n", "S1A/B # of dates: 77 / 97\n", "S1A/B date range: 2016-09-29 00:00:00 / 2020-02-29 00:00:00\n", "save figure to file /Users/yunjunz/Papers/2022_Geolocation/figs_src/S1/bias_TS.pdf\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# input file & pts\n", "ts_file = os.path.expanduser('~/data/geolocation/ChileSenDT156/mintpy_offset/timeseriesRg_SET_ERA5.h5'); lalo = [-21.45, -69.15] # IW3\n", "#ts_file = os.path.expanduser('~/data/offset4motion/SaltonSeaSenDT173/mintpy_offset_v4/timeseriesRg_SET.h5'); lalo = [32.82, -116.05] # IW2\n", "\n", "# read data\n", "dates, ts_dis, ts_std, bias, flagA, flagB, dates_fit, ts_fitA, ts_fitB = get_timeseries_with_bias_est(ts_file, lalo=lalo)\n", "flag = flagA | flagB\n", "print('S1A/B # of dates: {} / {}'.format(np.sum(flagA), np.sum(flagB)))\n", "print('S1A/B date range: {} / {}'.format(np.min(dates[flag]), np.max(dates[flagB])))\n", "\n", "# plot\n", "cs = ['k', 'k']\n", "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[6, 2.5], sharey=True)\n", "p0B, = ax.plot(dates_fit, ts_fitB, '--', color=cs[1], alpha=0.7, lw=2)\n", "p0A, = ax.plot(dates_fit, ts_fitA, '-', color=cs[0], alpha=0.7, lw=2)\n", "p1B, = ax.plot(dates[flagB], ts_dis[flagB], 'o', color=cs[1], mfc='none', ms=4, mew=1.2, label='S1B')\n", "p1A, = ax.plot(dates[flagA], ts_dis[flagA], 'o', color=cs[0], mfc=cs[0], ms=4, mew=1.0, label='S1A')\n", "\n", "# axis format\n", "ax.tick_params(which='both', axis='both', direction='in', top=True, bottom=True, left=True, right=True)\n", "pp.auto_adjust_xaxis_date(ax, dates[flagB], buffer_year=None)\n", "ax.set_ylim(-18, 24)\n", "ax.yaxis.set_minor_locator(ticker.AutoMinorLocator())\n", "ax.set_ylabel('Residual\\nslant range delay [cm]')\n", "ax.legend(handles=[(p0B, p1B), (p0A, p1A)], labels=['S1B w linear fit', 'S1A w linear fit'], loc='lower right', ncol=1, handlelength=3.0, frameon=False, borderaxespad=0.2)\n", "\n", "# output\n", "out_fig = os.path.join(work_dir, 'bias_TS.pdf')\n", "print('save figure to file', out_fig)\n", "#plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "cdc5d730", "metadata": {}, "source": [ "### Plot (b) - Bias Map\n", "\n", "The 2D map distribution of the range bias between S1A and S1B shows clear subswath dependence." ] }, { "cell_type": "code", "execution_count": 4, "id": "47e34d26", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "save figure to file /Users/yunjunz/Papers/2022_Geolocation/figs_src/S1/bias_map.pdf\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# read\n", "ts_data = readfile.read(ts_file)[0]\n", "date_list = timeseries(ts_file).get_date_list()\n", "dates = ptime.date_list2vector(date_list)[0]\n", "length, width = ts_data.shape[-2:]\n", "\n", "mintpy_dir = os.path.dirname(ts_file)\n", "mask_file = os.path.join(mintpy_dir, 'maskResInv.h5')\n", "mask = readfile.read(mask_file)[0]\n", "\n", "# estimate\n", "bias_est = np.ones((length, width), dtype=np.float32) * np.nan\n", "bias_est[mask] = s1_utils.estimate_S1AB_bias(mintpy_dir, dates, ts_data[:, mask])[0]\n", "bias_est[bias_est == 0] = np.nan\n", "bias_est *= 100.\n", "\n", "# plot setup\n", "vmin, vmax = 7, 14\n", "cmap = colors.LinearSegmentedColormap.from_list('magma_t', plt.get_cmap('magma')(np.linspace(0.3, 1.0, 100)))\n", "extent = (-0.5, width-0.5, int(length*0.65)-0.5, -0.5)\n", "\n", "# plot\n", "fig, ax = plt.subplots(figsize=[6, 4])\n", "im = ax.imshow(bias_est, vmin=7, vmax=14, cmap=cmap, interpolation='nearest', extent=extent)\n", "ax.plot(208, 119*0.75, 'ko', mfc='none') #from print out msg above\n", "\n", "# axis format\n", "ax.tick_params(which='both', direction='out', bottom=True, top=False, left=True, right=False)\n", "ax.set_xlabel('Range [pixel]')\n", "ax.set_ylabel('Azimuth [pixel]')\n", "\n", "# colorbar\n", "ax.add_patch(patches.Rectangle((130, 3), 100, 33, ec='none', facecolor='white', alpha=0.7))\n", "cax = fig.add_axes([0.57, 0.64, 0.3, 0.03])\n", "cbar = plt.colorbar(im, cax=cax, orientation='horizontal', ticks=[8, 10, 12, 14])\n", "cbar.set_label('S1A/B range bias [cm]')\n", "cax.xaxis.set_label_position('top')\n", "\n", "# output\n", "out_fig = os.path.join(work_dir, 'bias_map.pdf')\n", "print('save figure to file', out_fig)\n", "plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=1200)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "6ba9a7a2", "metadata": {}, "source": [ "### Estimate bias for each subswath from ChileSenDT156 + write to HDF5 file" ] }, { "cell_type": "code", "execution_count": 5, "id": "f5c344a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Median S1A/B bias in IW1 / IW2 / IW3 [cm]: 8.7 / 10.6 / 12.3\n", "writing S1A/B bias to file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/S1Bias.h5\n", "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/S1Bias.h5\n", "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/S1Bias.h5 with w mode\n", "create dataset /offset of float32 in size of (157, 232) with compression=None\n", "finished writing to /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/S1Bias.h5\n" ] }, { "data": { "text/plain": [ "'/Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/S1Bias.h5'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# estimate optimal (median) value for each subswath from SenDT156\n", "geom_file = os.path.join(os.path.dirname(ts_file), 'inputs/geometryRadar.h5')\n", "hgt, atr = readfile.read(geom_file, datasetName='height')\n", "flag = hgt != 0\n", "mlist = s1_utils.get_subswath_masks(flag, cut_overlap_in_half=False)[:3]\n", "blist = [np.nanmedian(bias_est[mask]) for mask in mlist]\n", "print('Median S1A/B bias in IW1 / IW2 / IW3 [cm]: {:.1f} / {:.1f} / {:.1f}'.format(blist[0], blist[1], blist[2]))\n", "\n", "# create S1AB_bias.h5 file for SenDT156\n", "bias_file = os.path.join(os.path.dirname(geom_file), 'S1Bias.h5')\n", "bias_mat = np.zeros(flag.shape, dtype=np.float32) * np.nan\n", "for bias, mask in zip(blist, mlist):\n", " bias_mat[mask] = bias / 100.\n", "atr['FILE_TYPE'] = 'offset'\n", "atr['UNIT'] = 'm'\n", "print('writing S1A/B bias to file: {}'.format(bias_file))\n", "writefile.write(bias_mat, out_file=bias_file, metadata=atr)" ] }, { "cell_type": "markdown", "id": "eb0b4652", "metadata": {}, "source": [ "### Plot the history of bias estimate" ] }, { "cell_type": "code", "execution_count": 6, "id": "1344156a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "save figure to file /Users/yunjunz/Papers/2022_Geolocation/figs_src/S1/bias_hist.pdf\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "clist = ['C0', 'C1', 'C2']\n", "clist = [cmap((bias - vmin) / (vmax - vmin)) for bias in blist]\n", "\n", "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[6, 1.5], sharey=True)\n", "for bias, mask, c in zip(blist, mlist, clist):\n", " ax.hist(bias_est[mask].flatten(), bins=70, range=(7, 14), density=False, alpha=0.7, color=c)\n", " ax.axvline(bias, color='k')\n", "# plot median value\n", "ax.tick_params(which='both', direction='out', bottom=True, top=True, left=True, right=True)\n", "ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())\n", "ax.set_xlim(7, 14)\n", "ax.set_xlabel('S1A/B range bias [cm]')\n", "ax.set_ylabel('# of pixels')\n", "\n", "# output\n", "out_fig = os.path.join(work_dir, 'bias_hist.pdf')\n", "print('save figure to file', out_fig)\n", "plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "6a584717", "metadata": {}, "source": [ "### Generate S1AB bias in HDF5 file for other Sentinel-1 datasets\n", "\n", "+ ChileSenAT149\n", "+ SaltonSeaSenDT173" ] }, { "cell_type": "code", "execution_count": 16, "id": "3282bde6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "writing S1A/B bias to file: /Users/yunjunz/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/S1Bias.h5\n", "delete exsited file: /Users/yunjunz/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/S1Bias.h5\n", "create HDF5 file: /Users/yunjunz/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/S1Bias.h5 with w mode\n", "create dataset /offset of float32 in size of (792, 677) with compression=None\n", "finished writing to /Users/yunjunz/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/S1Bias.h5\n" ] }, { "data": { "text/plain": [ "'/Users/yunjunz/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/S1Bias.h5'" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# create S1AB_bias.h5 file for SenAT149\n", "#geom_file = os.path.expanduser('~/data/geolocation/ChileSenAT149/mintpy_offset/inputs/geometryRadar.h5')\n", "geom_file = os.path.expanduser('~/data/geolocation/SaltonSeaSenDT173/mintpy_offset_v2/inputs/geometryRadar.h5')\n", "hgt, atr = readfile.read(geom_file, datasetName='height')\n", "flag2 = hgt != 0\n", "mlist2 = s1_utils.get_subswath_masks(flag2, cut_overlap_in_half=True)[:3]\n", "\n", "bias_file = os.path.join(os.path.dirname(geom_file), 'S1Bias.h5')\n", "bias_mat = np.zeros(flag2.shape, dtype=np.float32) * np.nan\n", "for bias, mask in zip(blist, mlist2):\n", " bias_mat[mask] = bias / 100.\n", "atr['FILE_TYPE'] = 'offset'\n", "atr['UNIT'] = 'm'\n", "print('writing S1A/B bias to file: {}'.format(bias_file))\n", "writefile.write(bias_mat, out_file=bias_file, metadata=atr)" ] }, { "cell_type": "markdown", "id": "94e1cd5c", "metadata": {}, "source": [ "### Obsolete: Bias in the residual range delay time series for all 3 subswaths" ] }, { "cell_type": "code", "execution_count": 8, "id": "8dd52100", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "S1 A/B est. bias [cm]: [6.1962175]\n", "S1 A/B est. bias [cm]: [7.8526363]\n", "S1 A/B est. bias [cm]: [12.131431]\n", "S1A/B num of dates: 77 / 97\n", "S1A/B date range: 2016-09-29 00:00:00 / 2020-02-29 00:00:00\n", "save figure to file /Users/yunjunz/Papers/2021_Geolocation/figs_src/S1/S1AB_bias.pdf\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1QAAADMCAYAAAB0vOLuAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAACb0UlEQVR4nO2dd5hU1dnAf2d736VsoTepNgRUQEGxRVQsMSqKLRb0wxKUxMRooklMYhI1xC5YKLYYjSaoWKMIoohgpUpv21jY3nfO98eZOzM7e2fm3tmpy/k9zz67e+eWc8/c897znrcJKSUajUaj0Wg0Go1Go7FPQrQboNFoNBqNRqPRaDTxilaoNBqNRqPRaDQajSZItEKl0Wg0Go1Go9FoNEGiFSqNRqPRaDQajUajCRKtUGk0Go1Go9FoNBpNkGiFSqPRaDQajUaj0WiCJCnaDYg1evbsKbt160Zubm677VVVVR22+dpuZ9/y8nLy8/NDfl47+0b6er72jYW+iJU+NuuLrvI9x8L4WLNmTbWUsuPOfvAlG0LRnnCNiVh5nkNxvXCMiVi+Zy0nA+9r9Zmwe95g5ENOTo4cNmyYpevabU+szh1iZfxoOelGy0lFVOYOUkr94/EzduxYef3110tvzLb52m5n37Fjx4blvHb2jfT1fO0bC30RK31s1hdd5XuOhfEBlMsQyYZQtCdcYyJWnudQXC8cYyKW71nLycD7Wn0m7J43GPnQs2dPy9e1255YnTvEyvjRctKNlpOKaMwdtMufF1VVVezcuZMlS5a02z5t2jTT/c2229nXF509r902RPJ6dvohVtoW6T6OhTbEQv/4ItjrLVmyhJkzZwK0WL6YE1+yoTPtCbSvL6yeI1aeZy0nQ7evL2KhbbEqJ62etzPyITk5mZkzZx5Sc4dYGT++0HIyOm2IhWfQF+GcOwilcGkMxo0bJ7/88stIXo9IXi+W0X3hRveFIlz9IIRYI6UcZ7MtEZUNzmvq58CJ7guF7gc3h7J80M+BG90XbnRfKKIhG7SFKso4NV4Nui880X2hONT74VC/f090Xyh0P7g5lPviUL53b3RfuNF9oWjXDw4H1B9Qv8OItlB5EY1VaI1GE1niYQVao9FEBy0fNJouwt418PLlULMPsnvD9Oehz9igT6ctVBqNRqPRaDQajebQwOFQytTwM+GWter3y5er7WGwWmmFSqPRaDQajUaj0XQdGiuVZWrCzdBjiPpdsw+2L4O/Hw5/HaR+710Tkst1GYVKCJEqhHhGCLFTCFEjhPhKCDHV4/NThRAbhRD1QoiPhBADotlejUaj0Wg0Go1GEwZScyCrCFY+AhVb4bNHldvfG7PMrVadpMsoVKgixbuBk4Bc4DfAK0KIgUKInsC/ndu6A18C/4xWQzUajUaj0Wg0Gk0Y2LsG5h4JtSWwdiE8MgY2vQPnP2ZutWqs7PQlu4xCJaWsk1LeK6XcIaV0SCnfBLYDY4EfA+uklP+SUjYC9wJHCyFGRLHJGo1Go9FoNBqNJlR4x06NuUpZqmZ/B4NOVlaqzx51W61y+kBaXqcv22UUKm+EEIXAMGAdcDjwjfGZlLIO2Orc3o7y8nLGjRvn+pk3b56l6915553MnTvX0r4//vGPeeeddyztq9FoQsO8efNc4xroaff4YGUDtJcPH3/8MX379vW57+23386TTz5pt3kajaYTREs+WJ076HmDRmMR79ipibcoS1VTNSQkqEx/m95xW60uWay2+8CybJBSdrkfIBn4AHjK+f8zwP1e+3wKXO197NixY6VdysrKZO/evWV9fb2l/VetWiXHjBnj8/OPPvpI9unTR0op5YsvvihHjhzZ7vPTTjvNdNuf//xnKaWUjzzyiBw7dqxMSUmRV111lY07Mae1tVXeddddslevXjIrK0uOHj1aHjx40HTfOXPmyMMOO0xmZWXJ4cOHy4ULF3b6+hpNqAG+lDblSjCyQcqO8sFzfJuxb98+2bdvX9nU1GT6+fbt2yUgW1pa5MqVK2V2drZsbW11fX7dddeZbrvhhhuklKEdozt37pSZmZntfgD5wAMPmO5/8OBBeeWVV8r8/HyZn58v77nnnqCvrdGEi0jJBztzh3DPG2bMmCGLiopkdna2HDp0qJw/f77d22nH9ddfL4cNGyaFEPK5555r99mCBQvkmDFjZHZ2tuzTp4/8xS9+IVtaWoI6l0bTgbY2KR8YIeWS2VLu36J+PzhSbffcp66i/TYL+JMNXc5CJYRIABYDzcDNzs21QI7XrjlATSiuuWDBAs466yzS09Mt7X/cccdRXV1tqYrzSSedxIYNGygvLwegtbWVb775hvr6+nbbPvvsMyZPngxA7969ufvuu7nmmmuCvKP23HPPPaxcuZLPPvuM6upqFi9eTFpamum+mZmZLFmyhKqqKhYuXMjPfvYzVq5cGZJ2aDTxiF350KtXL0aMGMF///vfgPuOGzeOtrY21q5d69q2fPlyevfu3W7bJ5984pIPoRyj/fv3p7a21vXz3XffkZCQwIUXXmi6/2233UZ9fT07duzgiy++YPHixTz33HNBXVujiXfsyIZwzxvuvPNOduzYQXV1Nf/973+5++67WbMm+OxnRx99NI8//jhjxozp8Fl9fT1z585l//79rFq1ig8//JAHHnggqHNpNB2wYoVKSICM7urvEKVP71IKlRBCoKxRhcCFUsoW50frgKM99ssEhji3d5qlS5dy0kknuf4/ePAg55xzDvn5+XTr1o1zzjmHPXv2tDvm5JNP5q233gp47t69ezN48GA++eQTANauXcvhhx/OSSed1G6bw+EwzJH8+Mc/5vzzz6dHjx6dvreDBw8yd+5c5s+fz4ABAxBCcMQRR/hUqH73u98xYsQIEhISOP7445k0aRKfffaZz/P/5z//YfTo0eTk5DBkyBCXS8PJJ5/M3XffzcSJE8nKymLatGlUVFQwY8YMcnJyOPbYY9mxY0en70+jCTfe8sHgT3/6Ez179mTgwIG88MIL7T6zKh+Sk5MZP368SxaUlZXR3NzMJZdc0m7b5s2bXRMnu2PUDosWLWLy5MkMHDjQ9PMlS5Zwxx13kJGRwcCBA7n22mt59tlnfZ5vxYoVTJw4kby8PPr168eCBQsAuPrqq5k1axZTp04lKyuLE044gZKSEmbPnk23bt0YMWIEX331VUjuSaMJF2aywdc7EcI7bzj88MNJTU0FQAiBEIKtW7cGfW833XQTp556qulc4f/+7/+YNGkSKSkp9OnThxkzZvDpp58GdS5vGhoamDNnDgMGDCA3N5cTTzyRhoYGduzYgRCC5557jn79+tGtWzeefPJJVq9ezVFHHUVeXh4333xzwPNr4oQ+Y+G2dXDHdvXbrJjv3jUhTZ/epRQq4AlgJDBNStngsf114AghxIVCiDTgt8C3UsqNobjod999x/Dhw13/OxwOfvrTn7Jz50527dpFenp6h4E6cuRIvvnmG+9TmTJ58mSXEPzkk0+YNGkSJ554Yrtt48ePJyUlJRS3047vvvuOpKQkXn31VYqKihg2bBiPPfaYpWMbGhpYvXo1hx/eIVQNgC+++IIrr7ySv/3tb1RWVvLJJ5+0m4i9/PLLLF68mL1797J161YmTJjAT3/6Uw4cOMDIkSP53e9+F4pb1GjCird8ACgpKWH//v3s3buXhQsXMnPmTDZt2uT6vDPy4cQTT+wgHwYNGmQatxVojNpl0aJFXHXVVX73UV4T7r+///570/127drF1KlTueWWWygvL+frr79m9OjRrs9feeUV7rvvPvbv309qaioTJkxgzJgx7N+/n5/85CfcfvvtIbknjSZceMuGQO/EcM8bZs2aRUZGBiNGjKBXr16cddZZIbjLwHzyySchk0E///nPWbNmDStXruTAgQP89a9/JcHDMrFq1Sp++OEH/vnPfzJ79mz++Mc/8sEHH7Bu3TpeeeUVli1bFpJ2aGIAwwplFh/lr+hvsJfrRFNjCmddqRuA0UCJEKLW+TNDSlkOXAj8ETgIHA9MD9W1Kysryc7Odv3fo0cPLrzwQjIyMsjOzuauu+7qMEizs7OprKy0dH7PVaXly5czadIkJk2a1G6b2Qp4KNizZw9VVVVs3ryZ7du38+qrr3Lvvffy/vvvBzz2xhtv5Oijj+ZHP/qR6efPPPMM11xzDaeffjoJCQn06dOHESPciRd/+tOfMmTIEHJzc5k6dSpDhgzhtNNOIykpiYsuukivQGviAm/5YPCHP/yB1NRUTjrpJM4++2xeeeUV12d25cOKFSuQUrrkw4QJE/j8889d23zJh0Bj1A7Lly+ntLSUn/zkJz73OfPMM7n//vupqalhy5YtPPvss9TX15vu+8ILL3Daaadx6aWXkpycTI8ePdopVBdccAFjx44lLS2NCy64gLS0NK688koSExO55JJLtHzQxDzesiHQOzHc84bHH3+cmpoali9fzo9//GOXxSqcPPfcc3z55Zf8/Oc/7/S5HA4Hzz77LP/4xz/o06cPiYmJTJw4sd19/OY3vyEtLY0zzjiDzMxMLr30UgoKCujTpw+TJk3ScuNQwVfR306kT+8yCpWUcqeUUkgp06SUWR4/Lzg//0BKOUJKmS6lPFlKuSNU1+7WrRs1Ne5wrPr6em644QYGDBhATk4OkydPprKykra2Ntc+NTU15OXlWTr/5MmT+fbbbzl48CCff/45EyZMYMSIERQXF3Pw4EFWrFjhcuexy+GHH05WVhZZWVksX768w+eGb/dvf/tb0tPTOeqoo5g+fTpvv/223/P+4he/4Pvvv+eVV15BeWJ2ZPfu3QwZMsTnOQoLC9u1w/v/2tpav23QaGIBb/lgbMvMzHT9P2DAAPbt2+f63458GD9+PLW1tXz//feuleisrCz69evn2mYmH6yMUcOlLisrq4NbojcLFy7kwgsvJCsry+c+Dz/8MOnp6QwdOpTzzjuPSy+91GfGQy0fNF0db9kQ6JmPxLwhMTGRE088kT179vDEE0+YnjvQvMEqb7zxBr/61a9YunQpPXvaTqzYgf3799PY2KjlhiYwaXkhT5/eZRSqaHLUUUexefNm1/8PPvggmzZtYtWqVVRXV7tWhDxdXTZs2MDRRx/d4VxmDB48mN69ezNv3jz69+/vmrBMmDCBefPmUVtby/jx44Nq+7p161wB5ZMmTTK9N8DnhMuMe+65h6VLl/Lee++Rk+OdC8RNv379OuWjrdHEA97yAVRsYl1dnev/Xbt20bt3b9f/duRDWloaxx57LG+++SbFxcWuFe1Jkybx5ptv8u2333aYOFkdo0uXLnXJhxkzZvjcr6GhgX/9618B3f26d+/OCy+8QElJCevWrcPhcHDccceZ7qvlg6ar4y0bAj3zkZw3tLa2+mxLoHmDFd555x2uv/56lixZwpFHHhnUObzp2bMnaWlpWm44HCFLtNBlCSJ9esBThrB5hyxnnXVWO5e+mpoa0tPTycvL48CBA6axPsuWLWPq1KmWrzFp0iQeeuihdsLrxBNP5KGHHmLcuHHtsgS1trbS2NhIW1sbbW1tNDY20traGtS9DRkyhEmTJvHHP/6RpqYmNmzYwD//+U/OOecc0/3//Oc/8+KLL/L+++8HTIpx7bXX8txzz/Hhhx/icDjYu3cvGzeGJKxNo4kZvOWDwT333ENzczPLly/nzTff5KKLLnJ9Zlc+TJ48mblz5zJx4kTXthNPPJG5c+dSVFTUbsXWzhi1yuuvv05eXh5Tpkzxu9/WrVupqKigra2NpUuXMm/ePO6++27TfWfMmMEHH3zAK6+8QmtrKxUVFXz99dchaa9GEwt4y4ZA78RwzRvKysp4+eWXqa2tpa2tjXfffZeXXnqJU045Jeh7a25uprGxESklLS0tNDY24nBO8P/3v/8xY8YMXnvtNZ8LKlbP5UlCQgLXXHMNt99+O/v27aOtrY3PPvuMpqamoO8j7ghxooUujZXEFTYIi0IlhBhs8WdgOK4faa688krefvttGhpUHozZs2fT0NBAz549GT9+PGeeeWa7/VevXk1mZqYlQWJw0kknUVZWxoknnujaNmnSJMrKyjqsPt93332kp6dz//338/zzz5Oens59990X9P299NJL7Ny5kx49enD22Wfzhz/8gVNPPRVQcQ6ewaS//vWv2bVrF0OHDnW5BPzpT38yPe9xxx3Hc889x2233UZubi4nnXQSO3fuDLqdGk0s4i0fAIqKiujWrRu9e/dmxowZPPnkky7LUnFxMevXr+f888+3fA0z+XDiiSeaygc7Y9QqCxcu5Morr+xgyV6+fHk7F8A1a9Zw5JFHkp2dzZ133tlBfnjSv39/3n77bR588EG6d+/O6NGjLQfkazTxgLds8PdODOe8QQjBE088Qd++fenWrRs///nPmTt3Luedd17Q93bGGWeQnp7OypUrmTlzJunp6S5vnT/84Q9UVVVx1llnuWSQp6I4derUdjLJ37m8eeCBBzjyyCM59thj6d69O7/85S9Nla8uiZVEC4e69cr7/v0lrrCJ8HRDCxVCCAcggUB+Yg1SyswA+0SUoUOHyilTpjBt2jSmTZtm+bhf//rXFBQUMHv27ID7XnjhhVx77bURy6Cj0WgUS5YsYcmSJcyfP3+LlHKonWODlQ1gTz7MmTOHIUOGMGvWLFvX0Gg0nSMa8sGqbNDzBk1A6g8oy9Qta1WihYqtyp3tju1Kadi7RilYNfsgqxdc8DgMOjkkykRc4Hn/2b2Vy59Fq5QV2RAuhapGStkxrVXH/Q5KKbuFvAGdYNy4cdJK4TyNRhO/CCHWSCnH2TlGywaN5tBAy4cuhMOhMrel5XV9xcHhUG5+w89UWes+exQ2vwuznaUpjM8GT4HXb4CWemuKRTB9GGv9btY3m95Rrn422udPNoTrLn9mcb/bwnR9jUaj0Wg0Gs2hyqEWT+Qv0YKRJnz8LFj6SxjutHQOmeK//lIwfRiL/e4rTfq610N2ibAoVFLKZy3utyAc19doNBqNRqPRHKKEoXBrXOAr0YKRJnzFQ0qRAJUm/MTb3fWXvOOLgunDYI8Jd1yXWZr0lCwo+S5kl0gK2Zn84Ew+cRTQrkCJlPLFSFxfo9FoNBqNRnOIYGaR+PJZtT2je7RbF16MRAve26Y/Dy85y19sehsueAo+f0wpVhXb4JUr2scXdRtkvw/t9ns44rpqy6H0eyhbD7WlcPrv3ff/8uWqPdm9YcJNULoOWpshKSX46zkJu0IlhLgT+C2wDmjw+EgCWqHSaDQajUaj0YQOT4uEETPTycKtcU+fsXD7eti+DN6YpRSo7N5wySL45xXt44tevhxmf2e/D+30u6c1y4jrWnyB7YQR1JYr5alsvVKQ6so7fp6V77beGbFdJd9C8TdQsQUKR1m7lh8iYaGaA4yVUq6PwLU0Go1Go9FoNIcyZhaJ6c/HRoKEaJKQoOKmPBULX1alpmr7fWin3z3juhaeq+K6vn/VHdflK2FEbTmUrYPS9ep33X7/91y2DrJOdrfPsJTlj4BTfgM9DgvYbVaIhEJVAeyIwHU0Go1Go9FoNJqOFolDXZnyxFOx8GdVCqYPrR7jL67r6xfauwmWbYSt/7OmQHlTtgEGn9xxe3IaFB1h71x+iIRCNRuYJ4SYC5R5fiCl3BWB62s0Go1Go9FoDjXM4okOJaykLw9kVQqmD41jjIQTZtcPFNfl6SZYU6xcFS1dOwl6DoXCI6BgJPSwVVIuaCKhUKUAZwCXeW2XQGIErm+LqqoqZs6cGVTxTo1GE9sYxfmAXLvHatmg0XRttHzQdCnsFLK1YlXyp5yZfWbl+r3HwA0fwzcvw/IH3XFd3m6ChYf7vk9DgSoYpX56DgtJkglPrMiGsBT2bXcBIfYC9wAv0z4pBVLKtrBePAh0cT6NpuujC3dqNBpfaPmgiXusFrK1WoDXn3Jk9lmvY3xc/3uVNGL3KqjcpVz56p0ufFLC0DNg3DUd2yIl/OdmtW8EFChf+JMNkbBQJQHPxaLypNFoNBqNRqPRdCmspC+3asHyzMbnmQXwtnXqc7PPbljuvn5KFvQZp67//EWwawW0NkFSqrJQpTmNPkJA5Q5zxU4IGHMlpGRGVIGyQyQi9B4AfiWEEBG4lkaj0Wg0Go1Gc+hiVsjWMy7JTgFeM+XMKAbs/dn4Wer/HcsgNQdevAReuxY+/jMkpiplKrMABk5Sv/etVdYng4pt0NJofk/9j1dJJGJQmYLIKFS3AvcCtUKIXZ4/Ebi2RqPRaDQajeZQwkiGYKYgHAoYCR82vQOPjFG/L1nstv74U5K88aeceX62/r/w1GR1zBuzIG8AVO2CHcuhrgyKjlSWqW4DlaWp20D1P1IljzjyIjjlLuXSF4dEotWXR+AaGo1Go9FoNJpDHTvJGDyxGk8UL/hLNGGnAK93FsCsQpg0B354F4ZPdWfq+/JZSM6AixfDJw/A/o0w8CSQrZCQrM6VlKpipw47FfZvhYyecNFCSMkIf3+EmbArVFJKi3kONRqNRqPRaDSaIPEX7xNs0oV4wUwh9JXy3GoBXimhthQaKmH8jbDvG2iuVTWhUrNh2Jmqn25cAQ8MUbFTPQ+D6j3wzp1KmTLingpGwVEXw3t3q2uKBJAOeGRsfPa3F2FXqIQQ/wb+LqVc7rFtEvAzKeVPwn19jUaj0Wg0Gs0hgJVkDN54K2ErH4GXLlNKWGInpsmRtHgFUgjN2mJmwTIUqNJ1ULYeStdDw4H21zJSIjTVQNVuyOuv+ja7t6ohNeFm2LsW0rvBGfcpZSox2X38qPOdGQCnwsRbrCm9dvoySpbGSLj8nQRc5LXtM+CNCFxbo9FoNBqNpmvS1dzUOosdVzYDTyWssRI2vqVifv5+OFz6YnCWk0havAJZ5fy1JSEB2lpg2/+U8lS2oaMCZYaU4GhRildef3OL1+WvmdePaqqG2hKlTFlReu30ZRQtjZEYfY1Apte2LKAlAte2jVGcz1nAS6PRRJsQBhcvWbKEmTNnQicKd2rZoNF0TeJOPuxdoyb9fx2kfu9dE7lrxyqBkjGYYShhKx+BF6erSX1WobKg+Mp85w87GfRCgb8EE1basnEJfDEfdn5qTZlqrlP7bv0fLPmZ+7kzLF53bFe/fSkygTIQeuLd/mE/UtbDttbA+4aw363IhkgU9n0WSAdukFJWCyFygMeBVinl1WG9eBDo4nwaTQwRptUmXbhTo+lihNBSExfywWrh1kMVu8/D3jVqol5botJ5X/ayOvaRMUpB8OUuaEb9AaXk3rJWKTj7f4BHx8EvtkJmzyBvyA9mz8Lmd2H299BwEP42GM59FA4/H2rLOt7Tzs/g07m+z5+YDD2Hq0x8BSPh+QuVstmZ587qu712v4rNunkNNFUphbeuDLKKOloPvfu9Ymtw358fol3Ydw7wPHBACHEA6A4sBa6IwLU1Gk28Ei6/do1G07XoCgkF7BJMrJDBoeAm6J2MIdA9G9YVI7YnLc+au6AZnhaYwVPg9RvU9icnhefZNMvCd+Lt8Nkjyo0vKRWW/UUlh9ixvOM9FYxsf77EZMgfobYXHgHdh7jfufUHoKa488+dvwyEBnvXqOyBAE+eCMlp6t6EcFsPPRW5YNw9Q0gksvwdBM4WQhQB/YDdUsqScF9Xo9HEOeHwa9doNF2LYLO6xTvBTh4PReXT1z17K1mJSerd8vLlsOY535nvAmEoON6pxLf+Ty0Kzv5OZcoLhUIrJdSUKEvU8TNVFr6Wetj2kXuf3mNUAd1Xf2p+T+l5MPhkyCpor0AZ/SP8pFtf+YiyFqXm+G+nr+8gUKKQEVOVUvrvmeoeE5Ld1sM1z7VX5KxmLgwTEVvmdSpRWpHSaDTW8PRr3/iWEpq+VqY0Gs2hSWcsNfFMMJPHQ1H59HXPFy+GV67oOMG3Yjmxgncq8aYq96LgHwtVunArCq230mcoUGXrnEkk1itFwxMjC59BWi4MOhmyC+Gcf5jf0/j/a/+/LwXI+7kzUp/PPdL3vQTz3HmP6/zh8NhxcNhp/q2Hofr+giAsVxJCbLO43w/huL5Go+kCuIKLl6qXUP0BuPQllRnIV0V3jUZzaJGao1bIVz4SOMC9q2E1CYCBv+QFXRVf9/zPGb6TFxjugp2djBupxD97VMX+pHdTCkiPoSpOa9iP/CdNMEs6UrkT3pztkUTioPmxniSmQK+jYMipHZUtMwIld+gzVlnZsopgzFWBE0AE89x5j+tVT0JmPmz7WMVFbVwK5z1qfmyovj+bhMtC1UcI8XsL+xWG6foajaYrEEq/do1G07UwVtFrS2Dtws65acUrvgq3mhHlGJOoYHbPWUXqmQm3VdPl+neZWhSUDvUz9S+w+HwYc2VHtzUpVYxSS4MPq873Khaquc59HSOFeUKyUpiSUlUSicJRqpiuZwyUFeoPKIVn/E2++8dO6nO7z52vcX3ZP6HXMbB9GbwxCxZfEFNuq+FSqF5ExUsF4uUwXV+j0XQVQuXXrtFofBNviQrMktZsWqpWznXSGnOiHGMSFXzd8z+vDE6xNMZJao5SKgKNF89FwWFnwqa34Z1fqeQKaxep67bUww9rlRtf2QZldeo5zIcraxXkj4S9zoySjVWw7ytobVQWsLP/DiOnBT8GPBNBPDUJLnhKxWN5948dJcnOcxdoXDscSpmKQbfVsEgdKeVPw3FejUYTJ4R6chZFv2iNpssTj4kKvN2IJt6iFlyaqrt27FRnORRlqdk9B6NYeo4TI3bIOLbXMb771HNRsK4M6verY79/DfqPh7fmdLzWwR2Q3ctcYek9GtqaVCa+d+6Eo6fDxFvVPu/+GkadF1w/eSeCeP0GFWdm1j92+9DqcxdoXMdwzKRexvHCKM43bdo0pk2bFu3maDT+icVV5XBNzuy4tvhgyZIlRuHNoAt3atmgiRusyIdIlScItawKg/vaISMfgpGlsfiusYP3PdtVLI1xMuxH7iRJ9QfU/y9crOKUzN55UkL1PrXvcddD8bfKXU+2ul30zGhrhjPvVwqTt8Iy9HT1U39AKWgTbw2NcuGtrBSMVPWzblxuXj/Lbh9aee4Cjesoua1akQ1hL+wbb+jinZq4IdZWlR0OVWX9yUkxX2wyLgp3ajSdwap88CyG2Vjpv3BmKNqS1QsueFxlHeusTLByj0EoAlo+eBFr75poYIyT6/4HT58CV7yh4qCu+xCePhVGz4BJc9Q7b+NSleEvozssux+Kv/F9Xu/4J1DKWf5wOPJi6HGY7+fXX0HfYMZWqM8XLIGetyg+j/5kg1aovOjSQlHTdTATfNFUXDwFHKiUtKPODUul8lCgJ0yaLo0d+WDs67ny3nAQhp+lJlP+ZIpVC5jRFsONqKU+dBMhf20IcuKl5YMHsfauiRa+xsmQU+Cbl+DmNdDzMFj/X+UmB+qZGz0DSr8zP2djlaoP1doEKVkw6XYYcY69JBKhVi5iRXkOJFuiZDH1JxvC3gohRGK4r6HRHHLEUvpbT5ehm79URQxfvwH2bzk0skhpNLGGHfkQbHkCs5TO/toyfhYs/aVS1ACGTPGfMtoqvlIkB0r9rLFGMO8ah0M9R12pr41xsvldNU7KN0FtKXz/urIoLX8Q9v+g3n3JmUrBGn4mrH1OWaE8SUqFoqOgfKNSoG5aDUddDF88rVKq23G1tZs6P9LnC5ZAqc+jlBrdH5FoSbEQ4h9CCFurPRpNO7qigO4Mnn7E0a694vnC7TlUZQVqqYdHx6qVzEsWx5TQ02i6PHblgzGJyiqCEWcHLk/grawM+5GKu2pr9d2WFQ+5Ldg5feDE20O7CNRcpya5P3wATTWxtegUz9h9lqwq2vGClFC1Bza/B9s/gQEnKKvUYaer34NPUuPnh3dVvFFLPVzwpLJWTbgZ6vYrd75eR6vkEWfcBxc+qwrpNhyEKXdB/rDOPZ+hVi5iUFmJByKRlGIqMANYIoSoBBYDz0spd0Xg2pquQLAm6HgNorXS7mCyFAXTH1aO8Q4S3faR+v/GFSqNazz1vabrE69ywQ7ByAc75Qk8lZXGSuUCVVemJtDecVeuWjzOVMyb3laLLp8/FtwiUEuDmuBW7lK/q3ar354FTjN7KgvAoVZzKRx0JuV1DKW0toyhQJWtVz+l61WGOU8SU5x/OH+n5cKknysr05OT1Duw8HD3M3fxwo5Wp0OxJlgXJ2IxVEKIBOAM4HJgGrAWpVz9U0pZ5+9YG9e4GbgaOBJ4SUp5tcdnpwKPAf2BVcDVUsqd3ufosn7Q8Uqw/tux4gdsF7vttjo5DCYo3E5b4qy/dYxEFyOYcRAHz6kpdhTCcC2iBBN35XC4C3Ja6f+WxvYKk/F3fUXgezjmChh5jo6hCiVWngvPBCc9hsRsDK1Pir9VWS69FSgwTx5hkJSqLFfH3xD8e9N4Lw+cbK2+lSYq+JMNEUubLqV0CCE2AhuB8UAflOXqASHEz6SUi0NwmX3AfcCPgHRjoxCiJ/Bv4DpgCfAH4J/OdmhimWBqDsTrKlkw7baShtTzvEZQeKAK43bbEkwK2q5uJdBEBqsTmHiVC57YVRC85YNV67eVye/5j8PrNyrLFMBlL6vzrnnOXD4nJKi4KStywuFQMV3fvOQ7rbQ/qvaoc3QbpAqC6glq5wlFyutwYvWdIiW0tUBSSsfPsgrMlSnP5BFJqdDveOg/EQpHqVpQ6d0ho4fa18670NjXWGhYfEHH+lbxtuATJ+yqqOfahavZVl7H4PxMnrnqWPr3yOjUOSORlKKbEOIGIcQKYA1KkbpSSjlMSnkqSvl5OBTXklL+W0r5BuC9hPVjYJ2U8l9SykbgXuBoIcSIUFxXE0aCiRWKV9/5cLU7mKDwYNpi1e+6q/nYa6KHncQD8SoXDDqbZCFU4844z+LzQaImklbirlqb4MA22LkCNr8Dn/wN/nMT7PvK/PyvXg3bP1aTWSuIRMjtqwqligT3vc49Eg5u18oUhD8W2ZXg5B1lmdq4FM57NDzX8sTfsy0lHNypFPTlD8K/r4d1r5ufJ6tQual7IqV6RgtGwdS/qSQS+3+Ak36pnrdF58MDh7W/rt0YpDdmKWtvZgH0HKZ+D/uRTqISBnZV1HP6Q8uY/LeP+KGsljYp2Vpey7ULV3f63JGwUO0BPkIpTf+RUjZ5fiilXC2E+E+Y23A44CoEIKWsE0JsdW7fGOZrazpDMLEAqTkquHrlIypTVbz4Jodrdc9fUPjXL5ivJpu1Jbu3Eu4OR/CTk1BYCRoqISERUrODa4Om62DHgh3vMQvBWOsN2lpV0ojhU90yMRjrnNn4Xf9f5eZnxF1dtEApMGUbVNuq9ylXvdpylAbmRdUe6H1Mx/OPuxZemq4sA4NOdluqRAJkF0FuP+dPX8jrp2R+YpK5m3i8WSLDQaTcXc2sLuG8XofC1I+q5+acuSqLXul6aK5tf0zp91B/ekcLkhBKcdq7RhW1LRilZMQP78KFz6hxd9ipSllsOBAai7cxro+5Qo2hH89TixVjruxo7dWeHZ3m2oWr2Vre/nlwSNhW3vnIo0goVIOllKX+dvCMdQoTWUC517YqoMOMrLy8nHHj3O6RM2fOZObMmeFtncY/dkzoxkujtgTWLgwcXB1LBKM82jmvnaBw77Zk9AQBPDCkcy9HO5PC1iZn8PlOFYBeuQsqdyuXDCNGwgbz5s1j3rx5xr897TZdy4YYxI6SFK7x5U24Jj127tWzDcVfKWWqtkTFO425wp4y5omv8Xvdh7Dxbagrhw/uae8e1XuMCtr3RdUe3+cfciqsXQDDzlSFTnP7Qk5vSEz2fb76A06L/E22FM8uLR86s5AV7PP8xizz60Fox0fDQfV9Fx2lLE/V+6C2DFY/7ZE8woPGKvhiHqx82PxdNu6nMOEmtWgH6v7Nxp0k+AUOT4xx/dViZZl651fKUrZ2UfvxbaYQ9zpGK1g22VZeh8NrXSdBwOD8TJ/HWJUNEUlKIYRIAYY7G+JyiJZS/i9M17sP6GsoakKIfwDJUspZHvt8B9wrpXzN89guH1jalfFemVz5iDLz37bOXl0HK9cJR6B3Z85vtQ1Wg8KNNqTmqN9PTgpNYUdfldiv+wCq9rZXnmpKMF3RBhh0EkyYZf6ZBQ6JoPNDZTUz2EQuqTmBY2vs9mG4rQBWzu8d6C5bYMQ0d/KI+gPKRe+H92D294Hvq63FaWXaA3n94ZkzOo7fy/+tFClDxmQVQLeBcHCHirEadLLvWKjuQ2Dyz1UfS0M+eFjSNr9rrZ3Gvb80A2qLVT28C55SGdfsnIMuKB+CTRYR7PPs63pXvGE9KUkgpFRK0b5vYNObShlxPXPl6h3h/cxJqdxIs3vDtH/A+jfUuyxQnJ0vZcbsXWbjOTM9v1kMldl7c/1/lcIYzwl2osDpDy1ja3ltO6VqaEGW5Rgqf7Ih7AqVEOJE4F9AKpADVKMsQ7ullIPDdE1vhWomcJWU8gTn/5koi9UYKWU7l7+YForeHCoTJqtEIsNQMC+YWMssFui58W7v+Y8pt41Q9avn+VMy1Qp2YrJ59iRfdBsEU++3f20nXW7C5E2sPXPhJhyKj93MmOFe0LGiCHq3YfkD8PWLqshoUxW8OF0pOFlFHdObt7Wqe/XMqFe5WxUvlc44jtGXKSuRd9/lj4DnL1R91tasJnp9xkJCEuxYDgMnqWKn2QVuN73cvspa8PYvoKbYbQWv2++eVFrNSOp970bynZb6oJ7/LicffC1k+Zv8B5Nh1/MZnXtkx2MhNAtzBh/c63Qt9UgakZiirFUZPdzvk+R0yB+pXEPf+D81Hnoe5n6XZRUpC66VRUbPcRdKOetvfHvPbfb/oGpejZ4Bk+aEpi+7AhbeA51NRhHtLH9/B/4qpfy7EOKglLK7EOK3QH2oLySESELdUyKQKIRIA1qB14G/CSEuBN4Cfgt8661MxRWH2oTJCuGOkTBzm3hphqq35CsA1Y6rRaQUZH/Zmsza+/os+/3a1uKuFZOZr7IhGRgunDX74NVrYc8X1t2DQClfSSlqtdF4YerFBTddIZudVTy/d6vKvZX+CSYzpp3aTP7uw+oKeaA29BjijJN8UcVPTpqjLFObl8JP31EW4G9fcStQNcVuxckMKaF8s7J2ebtgOxxQ/LWyEtSVqQls8bfQ4zClHO1YDtm94OQX3O1ua3VboybcBE9NVttvXuNegRdYj8HxvveCkWrSeeNyVZfqUCYYd1dfrpMNB9R3ash/T9dSz2f01Lvhw/vc1zMW5gK5yEmp3htlG6BsnbKOnvWA+WJb4RFqv7RcpXTXV0Dpd7D3SxVjO+nnMHKaWoAzntMP/6Dc3Y1FD5FgLbbQ7L1pN7utPzzPHyj+c8VDavuJt3fO3bArYVFG9u+Rwfu3nxSWJkRCoRoG/MNr2/3AduCBEF/rbuAej/8vB34npbzXqUw9CjyPqkM1PcTXjhyH0oTJDuGOkfB+YQ+eoq7jL67IasxQKBTkUCgVvtpruGp496uUyr3CFeO0U61qe07OBp3kVqg825jdG0q+be+q4R2AnlWg3IzyBjh/91eriZ73pxcX2tOZ5AXxRLDfu5X+8cyMufBclRnz+1fdmTHNZK3xTK98xO1eJ4SarPmTz4Huw4689554ff64WtDY+pFKQJPdG878i4rTMPBXX8fVZ04LwA/vqr7ybmNjpSq4O/1RSEqDV65Ux5R+p5S4037Xvt3ecV2jzlXWJFD9NuEmFf/quQIf6B1ndu85fVRKa439WGQj5vapSW7Xycx85f5ds6+9RdFwLR15rvsZ/fC+9q504GNhLldl4fMspOudRKJ6r7JoelPgfK8kZygr6aonlAJ10p1KaVr1FEy81X2v3nOErCL1npp4S/Cy0mqZgc7Qod291CKBoRjGW4KdUBMjc+JIKFRVKFe/SqBYCDEKldY8K9QXklLei0qJbvbZB0DXSJN+qEyYgiGUK0beeL6wx89Sq9bJmXDDJ0qwmQ1gK1azUAiDUCkVvto76CS4aRWUOvt271oVAFy5G1ob/Z+zcpd5G89/TE2iuo1VilOPw9Qk6uhLVZX5vH5qpdsMQzFLyQpN9rKuRLxns7NCZ8aMlf7xlRnzhNlKMWk40NHq4Ur+cpn12kxW7sOXvDcsBanZzkWN3cpNb8Q5qo3G4sdl/2wfvN7WpOo7Qcf6OmYWYimh+BvIHwVH/gQObO3YRqO/NvxXtW/E2Sr5TW2pUqa82/3y5WrMGornazPVpBihLCPBrMBHKulIPGOnbuGIqW7r7CtXqEk8Uj2r42e1tyiueFBZQr2tWU3V7a/n+f2kd4cjLoB/z+yoQHlTut5coeo5DH70J2WBaqyEj/8EJ//a/zPjOUcwXBPjQVZ6z20Mi6B+1mNmThyJ3v834Cx8wzOoFOprUHFVmmAIpjbToYTdGhBgrT6HZ42NR8cpZeCCJ5Uvtq+aNt51OTa9A5csbt+2ztbH6Wx9GivtbWtS9Ts+nQtrFsCWD5QfdyBlSkpVe6a1qWMbX5+lshnl9Ycpd6nV8Zw+MOo8yB/mW5nyrDlyX4F7lbuxMv5qC4UDK89cvONrzDQcsDeOffWPsc+Wj9T/m96G42bCPKeryJOTzOs4GZOerCJ3baaVj6j/U3Os34fn8+tp+dq1Ct7/rVKiHh6txsCf+8Kr1ygl5Lt/QdUuGHiiGlO3rXPGMnnIxOR0FV8ipVKmMgtUjFNmgXLbKzpKtf2465XL1NkPKln3k2dg4s3mbfTu083vwvQXzN9TRna0ibcohbP+ANSXQ1I6pKTDo2NVvxsr8HbecUb/37Hdfe8ae3g+k6POVQuGAFcvUdaoCTer56elXv1kdFeKL6hn0Nf3VfK9spT2nwBDToG+x6pERIYyJaWKvzOL69+/2bytiUlq3CQk2JsXGeMhMSm+ZKXnONbPupsYmRP7TUohhNiNzzRbbqSU/S1fUIhJKOvUu1L6c9iODjEdWOrJoeLmFO7YGDuZ7zyPaTjQMfOdvyBff/cRTMCwJ8Em45BSvSCrdrld9rKK4OhLzNv7n5vU/nbY8Sk01yjFqba081mfjL4a9iOlRKV3g4ofoMdQlT7XYvayLhd0bkYkxk604tbMxsyGJcptzW62v0BZ/rYvg9f/r2PmOH9B4IGydvm7D8+x31AJXz2vzrfpbbWAYaSCzir0n0nPX+KWzx5XsSmfPQLnPQZ9j1OT2SdPUHLj4PaOmQI93bl8ySfvPrWSHW3lI6rQ7+zvVV/5iskx67swPX9xLR862y++nsmffetONOGyUAmlcBkxb0kpyt3b7Pva8anKymeGt6W0/wToP1G5iheMUs+5kcbcH8HOi3z1mY7NjR8iNCcOOsufEMJS5JaUclmQbYs5YkYoWqGrD/ZIpCA2S7FrNVtOKNvXmXNZUcia65RLkCvOaZdyD2ppaH+ubgNh6l/Mr/PxX9RLz5vkDOWe5xnrlNMbHj2u/aRp7UIYc1XHdMhg/Tk2lMfr/gdPn6IUssXnq9Xsuv3m2ctMiOsJUywQCws6ZunBPSf9ocx6VbtfxUoa2cGMLFu/2Oo74YFn0gXjmfdskxF/uOV9eP9epRR592VLI/zrKvW3EeskpZJTAyepLJnNdSrpw5BT2tfdSUyGixf7jouyMnEORYrmzmRH8/WOC/PzF7fyIVT94us8ntvNsjKmZMHpv4exP+2omBzcDu/c6SOV+TKlOI2+DHZ9DjtXBj92QzUvigUZp7FHBObEEU+bLoRYjjXL1uSQX7yTDB06VE6ZMoVp06Yxbdq0aDfn0CWYlK3BnH/Iycr3+4ifKCF+1RLlcmI1JXgoB3BnalV5Ty4n3gzpee7aTvUV1tqQkAQXLzJfDfz2XyojX04f9TItGKFWwY3ge098Wc2spKcNdN+eFqqM7soyNWyqCpif/b3fFNVLlixhyZIlzJ8/f4uUcqidS0dNNsTawkm4x6bdtjRWqt8PDAlfyYRgUnJ7joHUHDVRfOVymPIbZeGu3qNW5AEGTFTFqs2+Y2/LsFFLx0jmcmA71O+H426ErHwVV5LXH3L7KNdAf5hNGrsNMh+7v9jqzu4WKhkczHMdxucvLuWDQaj7xafVpg1KvlMLciXr4dOHVLIKw1raVA137DBXnpMzoNfRKuNjwUj1k9MH5k8JbuyGs2ZjrMg4TUxgRTbYUqiEEKOBSXQs0Ptbr/2usnI+KeVCyxePEDGxyqQJf00p4/w3f6myeA2YqLJ4jZ4B2z4OrjhfpPC1cubtvmg1Dbk3Zz+kJmN2ru2Nv9XvQMVUPc8RaHXanzuVH+JmBToWV0l91UTxZ60JN511m7VCIIs2Uik3TVXKna5yF3z0RzXZzO3nv+CoX8vw/bDvK/V3SpZSlqQD1i5yJ6aQDntjwXNsQccU6JEokB4sEag3GDfywRN//ZKWF7zi4XCoRTkjA1/5BmUVBeUmuvV/Ha2lxnfh/Sx9+DvY+RncvsH9LAU7dsMpGyNR01ITl4SkDpWzOO7fgfeAqcBS4AzgP977xqKipIkzwp2pzDj/54+riczrN6jtWz+CSxbFjkXA4VCTs+YaVSvm4Hb44Hdqknb0pSrA3Mi4BUqZGn4mJKTAprc6piH3JjldTfZc7nr91Ll9tcVqZjWzNK8XPK4mfVZeSP5elt5ZmqwqaPFGNFLBWlnx9RybhrUGVExhtBS+SGR46zNW1Zx7YAjcsFy5/hUerq63fZkqGFpT3H4ho+goNQYP7nAXHDWjeq/qe7P2Hn6BytyX16/94sgpv3Faa89U8VUZ3dVEcNiPOpem3bsvDUVt7pGxodAfClksg8FXv1RsU1n67Cgerc3KFbXUmcrcSGnvTUKyet4P7nBbqJLSlKcDdEy6cuo9SjHxzP4XzNgNt2zUz5gmCOwsN90BnCmlXO4s0HuBEGIqAeo5CSEEcB1wKdBTSnmUEGIyUCSlfCXolmu6NuGeIJlN+Ke/CCnZ8E+bL59Q4WhTEzIjQcSuz+Hbf6qXmTFJS05XWZF6HwNNNapGi5EeFNwvrz2rVVHEqt0q7iIpHXJ6OV2B+rljnTK6q4BgKwpJoPTN3ucwFB/Dama1QGdba+BU6P6KIHYVIp0K1uqKrys9+AzVnuQMFauz7aPopqwPdckEKZU7adUeNY6MQtVpue0Lg2YWKmVq+FTlWrt3rXshw6zgqKfClZyh0kHn9VeZNEnt2P784ebta6pW7rNjroS1C+DH81Q84ZgrO5em3ejL2d91jAGLhZIEOj26OWb9cski9T6zq3gkJKmMkd4xtt4IoZ7lfV+rMZLeHS582u1qalUxsTt2wy0b9TOmCQI7ClWBlHK582+HECJBSrlUCPFCgON+D5wOzAWedG7bg7J2aYUqlol27IaZkA1lm7zPDx1dDyIxgfj6RVXnpWoPOFrVtnZxEmPdRW8HntR+RfCTv7V/QRkvr2FnAlLFOp39oFKiEpPbX3fvGpWpyaryaPZy9Cz06OschtXMSp/uXdO+4OeYKw7dOmuRXCW1osR64s9aE83vKZgim56KU/Vet+JUtcd8ZX7wFOXm52m9MbaXbVBWImMhw0gSUfo99BimCgTvW6PG+6zPVfppw3ps14XJeD6+WqzkxDu/Upn/1i7y/ZzYmYgaCltnip6Gi3DWG4xnvPvF1/dd8o2Kr21tVLXFvElIgPyR5kmIQLn35Y90Z+HL62++MGdHMbEzdiMhG2P5GYv23MyDXRX1XLtwNdvK6xicn8kzVx1L/x4ZXeZ6drCjUO0RQgyUUu4ANgPnCSH2A80BjrsaOEZKuV8I8YRz23ZgsN3GaiJIrMRueArZcLTJ8/z1B0K/6tXSqCZm9RXQ/3jzfar2KAXJE0eLCljvNlC9vLoNVJM02epcEVyr/s/MV4U7DaHq/fKa8Qp0NxlqwbhMeL8cM51V5of9yPck3M4EztUmj4KfL05XqdB9vCxjWbh2mkitkgarxGZ0d7rNPhZ/bjFSwpfPuIvhGjEhVnC0ws++hrlHqWd1wk1qYeL1G+CUu5RylpYL465RE82ULOXmdPHC9vEYjVVqRV+Izo/HujKVmEI6nDWgfDwndiaise72FIzyfCjg2S/Gd/jRn6D/eFXwOSkdPvqzeu6S05VLqVkSosJRboUqJdOZRGKUs+j6gI5u5L6+i3AoJpGSjbH4jMXK3MzJtQtXs7W8FoeEreW1XLtwNe/fbilBeFxczw52FKq/AiOBHSir06tACnBrgOMSgVrn30YGjCyPbZpYIxqxG7HQps5MIBwONSE13PWMn9oyQCoXir6LzF9cef07Fgn19E3vPlgFs6fmqLSy3QapdiWl+nazC/Tysuu+533+7cvg9RuhrsL/JNxOnxptmniLOt+L09VEcdNSlQrdpD2xLFxDQrhXSYNQYl0EG/sQiZXVxiqlLLU1q8UI7+sJAcXfqtpodnG0QsWW9tabC55ScSrv3qX64YrX3ZMch6P9GPjgHjXGHhnTPrNeZ8aj1XhCuxYD7fYUfzja1HvDSCKRPww2LlFJlwx3U0MZamlQ+/YY0vE8fcaCSFSKlZkCZYdwKCaxbEEKF52YB4Vr8XFbeR0O58zeIdX/4STS17ODZYVKSrnA4++lQohuQIqUMpBi9DbwkBDiNnDFVP0BWGK/uZqgMSYyVl663pPt8bPcL/doZfGKRDyJ1QlEQ6W7jpOhOFXthrYW3+d2tKr4qNy+HT/L7ef+Oy3XnSBi6Bmw7C9KecnuDVe+YW0lysrLK1j3PYM3ZlmbhNuZlHm3acTZ7oKfPrKLxbJwDRnhXCUNQolth51JTThWVhurnTFOe1SB6iqny15TtVKqir+Fljrz6+X2UwqVUd8pIVlNGj3/T06DnL7OOKd+6ndOX7d1znhWt32k/r9xhSo27c/tSSSoZ/u037knRLO/C3482o0ntPOdxdqkNYZcnWKKyt1Q/LU7C59n7FNSmorj83zGPSlb316hMvo4qwhGnBX+tneGWLQghZNOzIPCtfg4OD/Tdd4Eof4PJ5G+nh0sK1RCCG/p1Qq0OmOpHH4OvR1YBFQBySjL1HvAlTbbqgkWu2mmYzGLV6TcTwJNIFY+AjtWBHfuyt1qQuY9KSg6Ak65WylS3inOx13TuXS3vo41S8qBtLbyZXcSbnVSZqp8veA3VXMsC9e4IAgltgNWJjWdtTA31XgoTkaCiN1KcTJDSuWulFUEMz5W2Txfuqx96u/cvrD1Q7Vfa5Nyaxp2pkoD3XBQxSNNfwn6+pB3ZgsFmT3M9zXGwMHtyjJ12u/aT4iaqoMfj8FgZyIaK5PWGHN1iim2faQWt3whRPuizylZyoWv8HCV4MggGn2slWTrdGIeFK7Fx2euOraD5SucRPp6drBch0oI4cBHsV4ppYkfU4fjC4H+wG4pZYmdRkaSLle806wQav0B58Tp3QDJAfzUXOlMG4O913AJeymhpsRtaaraDRNv7eie53Coyc4P7wV2f3CtcqdATpFSlob+SGXy8r6HXscEX9DXF3bqRdktjGpWp8buJDwU94h9N4a4LtwZLuyOK58FP/18b52t6/LfW+2553nWx5lwkzq+rkwpWJe+qO7v4E54+hQ47HSY/Av1HK9dCGOucscEBpJ3dmVZoJo7kSpUHG9EqNBqROSD3WemrUXVeitbD4edqiyg3uxZA5/81fc5PBUoI4mE9zssGsVstZJsnyD77PSHlrVbfBySn9W13OPDTEgL+wohBnht6gX8ClgipXzGa19Loy+AZSsqdLnincZE5rr/qcnDFW+o1LrXf6Sqk/t7QdfuVy/1m9eoLF5WXuqBXhadvdfOKp5GbIVnnFOVM9bCk7MfbO+e59lus4K5UirXiu6DldL07cuq77N7KSuLUXjX+4W1/r9q5dBKfwRbVNdKYU67xRXj/EUYl4U7w4n3uPLlIuzrew/0PHg/Xyvmwg/vwPlPuN30kMpSa8Ynf4M9Nvo+IUnVlCsYpaxCmT2V1Wn4We6FpMbK9krenjVKRl7/EfQZEz4lxsrYiUSh4ngiwoVWwyYfrHz3rc0qRq/MWQNq/2a3O/nEW2DgiR3P21wHr16La807Jcudgc+XAuVNpIvZRkOB6yoEMQ/q0gmcIkhICvtKKXd6bdophLgKWA084/VZKz6sWV4EtGx1eUKRbMHf4Aomta6B3SxeViZVnb1XO+4nNSVQvtFDedrtrtcUiMrd6h6MSaXR7iN/Aq//n4rNmPJrFfDeXAfv/1YFqSMAaV6bx1ds2ugZqp6Uv/6w03ee12msVJbJujL18jJW58361U4AeqzFVmg6h69smp4uwpcsgn9e2fEZnP2d72ezrcntpjf6Mlj1lHq+jEWJL+Z7tCFJpW83lH5PuZbb31yhSkhSMinXGeeU64xzysyHHctV4pT6/eo+LntZncuo0eTtPvPVYrXf2kVqsSRabsWgE0J4E+sZB63gS4bf+hUc2OZMIrFOKVBG+QxvStebK1QpmcrrJLOnskLl9rOfRCLSfRzpOntdiSDccPv3yNAWKS+aWtvYWlbHxpJqBudnMbpfXqfO11n/nBwg32T7II+/zwZ+AvwZ2AkMAH4JvNbJa3cNOitU7FS9t5pa1+zYQC91KxP+cCS7MCysZi+PbR/DuteDO+/2ZfDqNaq9WUVKWZpws7JAXf5veHSsmiCm5bmLX258S03EKn6AYVNh6S/hqiXu79P7hbXiIXWtE28P/N3beU6M66x8xO3mKYRqY6DaQnaUpCjGVhzyq23BuN1ZPe/Ll3d0ER72I7XdGAeez2DlzvbPZsEotf31mSr2yZMBE30Hxzta1flz+3aUayff6SxK7aU4ZRV2dM3duwbmn6KOzSxStZ5GnK36xHOSaCbfznsUPrxPKV3hVGKsjB29aOEmCAUz5mSEIcOPv1HVf+pxmPr/lSuUIm+FsnW+PxtzRefaF2klvrNZdfW40ATAWwY8ecVYWtskG0uq2VhSw9ayWtqcgWXHDeoeOYVKCLGY9lanDGAy8Lz3vp7WLCHE7cA4KWWlc9NmIcSXwJfAE97HHnJ0VqhYrXpvJ7WuJ1Zf6kYNp/E3+Z7wdzbZRVNNx7TkVbvhR38yz56X19/9t3cmL29SspzZ9ZyTtv/cpCZhE26GTx+GrxbByodVbNXnj7m/I+MlecwVahJ2wZPw/I/VtWr2KaXJ1wQuq5dSJK1YAO08J87rtL5wKUn1ZZTVNvG7rN9y16gJ9DZW531N5mwoSdGcsHT5dOn+CNbtzhuzSYn38/zjecpF+JjL1f9ZhaqmzchzYPsn6hnMG9D+2fzmJeX+2ljdcax5B8d7Y1iGveXax3+2Zsk2k4nr/6sWkMyUJDP5dtSlsTNZi5WEELGATQUz5mSEIcOXPwjV+1S68qQ0lFdDADJ6OGtAjVLvss6kMPfE27W31zGRU+KDVeDi3N08HrDybo+5BQsTrln4BVvL65AStpTVcu6jKxg/yDxx0MaSGqSUiE6MLTsWqi1e/9cBT0opPwhwXC5K+ar02Jbh3K7pzKqQHauF3dS6vo41w0hgAfDUJHcCC18ptF+aodpp5haXkKD8xQ03oYM73enJGw6aX79yl3+FqrHKnckrKU3FUfQZC90GqJXuvP4q0NcYSPUHVAC84TK36W1l1Vu7CNYsaP8debtUvvtrVaxzi3NYbP3I/wSu+Kvw1ITpM5azE55gkbyG99vGsv6AYM3Lv6d3CAvkRnPCEvPp0sOZZMZsEcWf252dGDjjeV6zUE3i/nsLJGfCs2eq4xoOwIb/qpo2RnxgYlL7ZzM1FwqPaH897wUNkQDZRe2tTbl93W62wVrtfR37i62+6zl5yzetxMQuFr4bQ5b9UFbr2hYTMsJThnvG4ppN4FwKlDOJRFZB6JQoA7vZf8NBICXZLLYz1mpkdkGsvNu997ny2VUkJyZEVcFyOCQ7D9SzodiwQNW5rEASqGtq83lsdUMLxVWN9M5LD/r6dmKofhfkNRYCHwgh5gK7gX6oYsALgzxf1yNY145Y8Cs3BNyIqW6r0ytX+J7w9xmrarU8MARuWK6SXRQeriY9y/6sCsXWFCvhbpXKXcqVyJvsXtBnnOqXIafBxJvg23+p1eoLn/Hdz75c5oZNdWaz+84d5+HLpTKrF0x/EQad5H8CZ/W7dzhU8c/Z31m2MG6paOJ65vBUyt+5POlDipu7w9Wvmh5nRzmKhQlLTKdLD+cKqi+FwdvtzlMJMSypZpOS426A5Q/ACxfB6X9QK+e9j4HvXlYLEFSo64oE6DUa6ivUYsPgKTBtroohhPYFn1+7FvZ+qSxRRUcpl9mdy5SFOaMHTHsEhp0Bicnm99gZuebr2PTuesJ1iGDIMk9iRkYY42TZ/bDva7eSlOGMfSoYGT4FypNArr2RUFA8lSUzJdlMjvoqgH2Ix12F2lpkZcHSe58dFfUkCEznEOGyZkkp2X2gweXCt7m0hoZmt9KUkZJIncf/mSkd0zb0zEpleFE2I3plk5fh451kEb8KlRDiGisnkVI+6+fjO1DWrUuA3kAx8Cgw388xhx7BrIrGQuCy9wSvYCQ8Og5uXN4+Lqq5Trnz5PQ2T3aR0RP2faP29eea58Gupiyu3XEK277LYvCHyzoO0oREOPZa+Og+OOMPqn1ZRe6gdH9ub9OfV3Vr6srUNiOgfe0CpdB4HtsZl0rjeoEsgEFM0AfnZ/J9+RAmNj1Mnqgnv2cB7/k4zo7FJ1wTFjtCN2ZrUYR7BdWXwuDtdmdsr9imFjh8TUrW/0clb6mvUFYnwx1v0MlqHDocsP1j6D8RUrMgNVtZjIVQypehUBm8MUvVcsobACv+rhQr70K2b/8chvuJBQE4/3F1LsM19oLHrfVPZ2SijsvoEnjKMoMh+VmxIyMSEtRCW1qeM5X5EZBlFooeRny59o65MvD7MRQEm8DKrAB2vCUnCQOh9haxsmDpvY9D0m4OsbWsltMfWsa28joSEqDVIZFe7bOraEkp2VvZwMbiGjaV1rCppIa6plaf+x/dN49v9lRS19xGZkoiR/fNo1tmCiOKshnZK4fhRdn0zEoNup+8CWSh8oxyFMAJQAluS1MRsALwqVA5U6M/6fzpOsTKyzfagctmE7ysQijb4Cy+6Yx1qt+v9j/hZ8qaZBYM/uk/PFzzTFKTJyQphSyvP+T249q30tna3OoSItctWMV7/3d0+37wNQFNzVErcr76zOhXI+GEd0C7N51xqfRHJybonkpHz/winvYzobBj8QnXhMXzpfBDWS2T//YRQwuyTIVszGYsCnfmKl8Kg8vtzulOm9EDjp0Jz5+vntkr34BVT3aclHQf4o7lSPBYnTNinRKkGouVO5XydHCHctXtN0HFHZrd+4m3wcJzlRL1/avKYrtrlVLkAvWH50QrqxdM/ZtSzBZfYH0xIRiZqOMyfBIPsRKeeMuymKy3M/AE9RMtOpP9t7MEk8DKVwHsQz37pRN/C6LBjF8rC5be+7S0Odh1oN417hIThGsctnl42nm2L5AiKKWkpLqRjcU1bCypYVNJNTWNvhWohua2DgrUj44oojAnlf98vY/Pt1cwpDaLW08ZGhYZZqcO1SPAVinlXI9tPwOGSClvDXnLooSl4nz65atiIuoPQNUuFSe04u9K2CWlKZchT0XIk8MvgKOnq789lVLZBn/uq9Iddxuosn1Vl8DUv6j/8/qpvvaoozTkzrdpcz6/R4mtPJXyd3qJAx2/E+/v69S7VSavUNZ+ChcRqg1iR+h6Fwjs3z3Dp++0nfN6fp8GoZ4Qhb1wZ6TqB7U2w/5NKvFD9V5nQeo9UF2sUpUnJCsLk1Hc9rzHVBY949k5uN1/XTVQYzG3nxqbq59WVizPumq+7n3IyfD1i3DET2DnSnXdujJV3+mrxb77w6x+mmehXaOe2uzvoLk2dAtIuh6OKWauvTGroHjQGQXwkCr8Ha0YKivvtEC1FGNlQTtG8Fe0N1IFfb3HnXFNXyQnClra2u+QKASf3XkKG0pq2FhczabSGqrqWyy34fNtFS4XPwEM7JnJ/+acxBl//6TTfRDqwr4HgZ5SyjaPbYnAfimlSenu+CRgcb5IvXxjVWA4HLDrM1U/prXBvT1QFj2DPmPhpDs6bjeE7IzXYMAE5YYUQHEwBIWUDlam3sqXKccx7cY/mX8nntmM5h5p7/uL5ncR5gl6MJMP72O8V6aCFeae+3qSKARb/3xWp+/Vk7AW9g2XEr5rFexaqVxna0qUouMPKZW7XmYBnHqPOtbz2XE4oHw9fPa4ctFzpSTvq1apk9Pc57I6BowENbXFypJ1wVPw3SsqTiPQhM17ouVZaBcJL05XilmoJ3+RLmgaA1gZ98GMx3izZvnikCn87auAd7ivaeWdFgtJM+IEf+POe6EyHO9TMzzlhwCSTBQoTwSQlZbEcQOVzDWzNqWbxEClpyQyvDCbEb1yuGHxl+3klXGvoewDf7LBzsgpAc712jYNKAuqVfGKmSm6Zp/1grFW2LtGCZy/DlK/964J3bn94WhTq9zbl8MXT6sig2btWnAWbH5bZc8zMFyEfClTIkFN0rIKzT83XBA2vaUmixZ8o5+56liG5GfRXdTTSxxg7PTf+v5ODJe8pmr7359xbDQUWyMF+oal8MgYile/wU1tt7PrYGNITm+Y3NukdJncA2G4223981m8f/tJ7D7Q4NPdwE5slvF9ehIzweR2MFzO7tiuflt5+be1qIyWOz5V1iczqnbDrs+VRSqQMgVqLPYeo5SQf1+nFg4uWex+jhMSVPzG+Y/Dyb+EY2bA4JPUuPBUpox9rYyBPmPh9vVwxRtq7L5yhVKMrn3PvD8cDqXQOBzt3XMrtroL7a5ZqJSp9G7q/x5DlZJoBNA7bCSwMcP7uodAXIaVcW/m2htoPAYjTzRRxBjXiUmRe8cZbsub3lELF95yyaDPWGWNzipSVupb1iolLBRjvovh/U72XMQYnJ9JgnNaFon36a6KeqVMldWSmCBIEHBYQRYf3n4yiX4W2zNSEjmyt9tLwlCmAOqcyhVAWnIiR/bN5aJx/fjNOaN4ePox3HLqUE4fVciQ/CzTe41UH9hJm34r8KoQ4heoGKr+wCjgonA0LGYJd2a9SKQFlVKlID+4Hco2Klee6r1KmaqvcMcxpeXBFf9Wgs2zXeNnwfMXqv0GndxRiUrv5q7p5Ix3Irev76xeBp6B6BZ8o/t3S+P9G4+E1BNg7r303vA05AX4TmIhM6Jd+ozlrIQnKG8qo1JmIJsSeMtPfJEdjEmTwEGOrGN7uTWLtSf+4q+8Tf9tUnL6Q8v8ugW+fP14fvOf7y0lnGhudVBe20RJVQMlVU0kCJh6ZC/b9xByfCUaaWtVCnzVHndpgMrdKnOekdnyzPuh+6COx5qVBjAjo0dHa1NqtpqYRGrCNGRK4DgmM0ueWWzlB79XSqF0qJ+pfwltAH0sJPfxJkxWcTsZOs3cdgLFSnovoPxQVsuQO9+Oa2uVJgxYjXNsqlbu/xNvUQs9453zg4YD7ZNeaXwS6QROrrgoAIdkYI9M7jv/CD7aVEZmaiLVJjFQmSmJjB/cvj6UZ3Y+gIaWNu46eyQDemSSmCBMrXK+7jVSfWDZ5Q9ACNETmIo7W99bUsqKAMekAr8FLgV6SClzhRBnAMOklI8G3fIwYclsH864mlC7n7S1qEDyyp1q4mYkiaje61acjPTG6d1hxzK1+tttoMrMV1PiFnye7Xr9RlXAc+y1Kr4pf7g71ik1214bvQPRL3hCxX34c0GIQFxULLmv2IkvshsPlbn/G55IVvFn5aIH+df9y9bz7O96VuIwArkFSik5UNdMSXUjpdWNlFQ1qb+rGqmoa8KzW7plpvDARUcHbHPYXXraWtVEoHK3M77JGeNUUxrYujThZhg0qeP2qj3w1hz3/xk9lLKU21eNu9x+6v+UOJi0+nOdhvYTrbZWte+wM1VNuIzuakFo+Fnww3uhi0+LFTfrML5fzNz4QiFH/J3f3zVilYi4/MXK8xbLeMoJoyxLS712/YthzOYqp44oANq78QlUbahMp8veptIa5d6XmsiPj+nL++tLKa1pRPqYF0QqNswbf7LBjoUKKeV+YLHN6/8d6APMAJY6t61zbo85hcoS4cysF2oLSm0pvHd3+21SKmUqs0BNykq+c9eNaWtWilFKppq47Fvrvk/PdiUkqaD1zUvbv/jtKlNmFrnXrlNtsZNS9cP7rNdosvj9RbNwrTdmq8W+VpbttPuZK8eS/thPea91DO/l/oRHB660bRH1l3HP+MxTyAZyC9xaXssbX+2luMpQoBppabPm4nGwrpnGljbSkjv6WkeU9W/Ad/8K7tiqPebbs4rguOvdFt+UOHOF9CRQNkTPxaPEJLj0xY613ja/G1pLUiwU9A2zh4KdDJ3BZNL0XAn2nFR5jvnOLFQFc2xLm4PymiZKqxsZWphNVqqtaU946IzSfCgpYq4SJs7spckZcPFi2PZRTBf0jaXF2HBT29TKppIa5081ackJPms/pZtYohITBKt3HKDeeUx9Uxsvr95FW5skKVHQ5pCmMspOOEGk8CtZhBDvSCnPdP69HJBm+0kpJ/s5zQXAYVLKOiGEw7n/XiFEnyDbHBvYefnaEYCB3E+kVOeq3N3e6tR3HBz5k47ny+6llB+Hh5nV0aIsU3kDYO9qVQOjpkTVgqrZpzKHDT4F9qxyK3Pe7cosUpOaYT9S5vhgX/zeEyvDpD96BkyaYz+lqtXvxML3F8yADZcgNSYq3pYeM19gO+3un9EMsoIZs//KjB5DoOI4eGRRp92ovPuhX/d0V+IKUK5/E/78IReP60dOehIHPTL5pCcnsuSbfUFfu6y6Kfovr9x+9o/J6Ol00fPhspiYBIed1rl2xQp2F446W+stXghz2v1wpxT3VMK8V5ANWdWZhSpfx7a2Odhf20yp04pdWtNEmfPvA3XNLiv2z04bylF980J2v0HRGaU52llno0GfsXDjCnhgCNywHHoepoogx3BB31hajA0luyrq+emCL9i+v46eWalMGtqTqoaWdl4iZrWfPElIEAzumamK6RblcFhBFiN/845LuZDgTl7hVKbM+s5OqZdIEWipZpHH308HeY1m7+sIIfIBv66CXYZgBKAxeagthaYaqN4DaxY43fV2q8mEN+k+Ei0mJKpJ2sEdHtuSVXrz+v1Kseo2WAn5S1+CeSep6/7vdx2VOaNd25cpl7+6CpW9a8wV/l/8/hRK74nViofU9hNv9z2h8D5m5SNq9T41x3+/2iSYARtqQRpMfJGtdochpkxKydXPfcH2ijqkhC1lteSkJ5OVmtTOf7q4qpGnl28LKID9IQR0y0ihKDeNotw0CrPTyEmPgRXoPD8KlXeMUzy56oWKYOKWwlXrLZYIc4xnuGIJ7MQzmMVZecdVmp3/moWr2eIV+7WlrJZfvvptB9dfX5RWN3X6XjuNHaXZ890J4Y+vjlUyuqtx8fljIRkX4bYgxaL1JFgaW9r4obSWjSXV/PGtDVQ2qMXPspom3vm+pIPFydsKJYRgYI8MRvTKYURRNocVZHXwIPGVZt1f30U6NswKtmKogrqAEA8AhwG3AWuAw4G5wBYp5V1hvXgQhDT1qd0U6y2NsOG/7jin2jJAsqspi2t3nMK2phwGp1bzzIAP6Z98sH2K8syeqtaMWRu+fEZl5Os20J0oomqvKgLqmd5420fKjeZn3/peATbuadiPlDKV0V3FfY042zyewYpC6R1DJVtg5LlRT6kajNANdYrSYPyEbbc7yJiyx2eMISUpgZKqxnbxTaXVjbz1XXGH408dUcCHGzsmBTX8q/2RnpJIr9w0CnOcilNOGkU5aRTkpJKaZN+9L+wxEo42eHO2UvQ9FafcPvHtqhdqopG2OQSEdUJmcxHOaMvWsloSvVxkQm2p9XXf/uSUvzILBsYx78yeTEVtE6XVTZTVNFJareTJc59utxzM7o8pIwq4fPyAgPuFVT4EkzY8uzec/5gqcH0IpfdvR4Bx0ZlaiqG21EYrvicYvPvticvH0NTqcBbTrWb7/noMPcHK+1sI6Nc9g5FFOQwvymZYYbZpunNfbUhIgFaH9Bk7FW38yQY7daguBb6WUm4QQgwH5gFtwCwp5UY/x6UAfwWuAzKAemA+8EsppY/8wNEjpAqVrwQT//cZFI7quL+jDV65sr17HnD6pnPZ2pSDgwRGix+Yn/J38kVlx4KcP3m2/WQt0IvZ4VDWpjdmeSSEeFxl7vM1qfG8p8ZKd22YrCIV5+B9fqsKpedKXPFX1iYURrD68Klut8MoFeS0UwSzM8Vuw1YDxocVsc0hqahVSSBuWLyGkqpGl2ne32TGs8Ce576+toNyBSjITqUoRylMvfKU0lSYm0Z2ahLCX30zm8RUnZlDKSbCjDC4MYV7BTrsEyYbz4SdRBOdxdd9+5NT3sf0655BghBs399+5VkAp40qxGFSDdRsIuevNo033TJTKMxJ5Zh+3ThtlI/SHZ5tCbd8sPJu9n53blyqZqvhLhoey/gZF3bGZLhrM8VTDNVpD33M1nLlTSJQ6cuNd7J3LSiHlDS0uOOZjfd3327pLgvUsMJsMjsRpxjrfReqpBT3AROdfz8ArAZqgceBU3wd5FSaZgOzna5++2W4zWKdoKqqipkzZ3a+2nlzvXKdS+8O/7lZZcHb9rFytVv/X3OFysw9D9jmVKYEDp5I+QfvtY1lxrgiqNgC5ZvgyjfciSQMrPhpe6Y3NhSrxRf4n9R4u6SMOBs2v6OEeqLX42THtcHTncdmStV9o67nqoV7aCs/kv+lPsue4mL69gldiJ6VAW64+nniK9jbjlugHfe9YN0NpZTUNLdRWpNMyd4KZXFyWp3Ka5poc05wiqva177yTmvqiS83vqP75vHdvipqG1vpmZ3Kz04dypF9cinKTaNnViqJCaFTmswwqp0DuXaPDZls8CRUykS8KmVhSsIQ7hiGsLv02IjRNUs04d2mUE1SfN23mZzaX6usS57KnkOqtpwyooCy6sZ2MkQCK7fsN1WSMlMSfS7EGORlKKWpMCeNwpxU8rPV74LsNFKSrD1LEZMPgd5xvt6dV7xhq7RIl8PPuLAzJsMdfxNMQpdI0drmYPv+OjaU1LCxuJqtZXXt4pc8x5l3Laj05AQyUxKpb24jPzuVe84dxeSh+WSnBSiJY4Ng+i4SSpgV2WBHocqXUpYKIdKAE4GfAC3Afn8HCSEGe23Kdq40NwHFUkpHx6OiR25uLvPmzbN+gKMNaopVUc4qIy35Tqhzdkv+cNi3BnatdFuUqnf7Pl/eAA+FSkBWAYOzmtlam0oOdfQSB3gv7yJmnH+p2+KV289tpTKwG9z8xixrkxrT2IcXOipT0Ll4ACsTCuf517z8e1prz+DaxLfYJ7tzzcubeW9O6BQqK5Mz70lNohA+hYLdYrdW/YQDnbeptY2yamVtKnFm0CutbqS4qpEGP8qRgdmkxhd5mclccmx/CnNS27noFeWmRTUDnzHZmT9/flXgvdtjWzYEIlTKhF2lLJaUrzAlYQi3whNLAdFm8QfebQqVgul93wN6ZLBuXxXXTR7Eg+9uprymiezUJApzUvnlq98CKsmMp9zIcMoNz0UXA6OAp9kKubHUkpeRzBXjBzCiV45LYcrPTg2JXImofPD3jvP17hx0UvgyDMc5dsZkLMbfhIvWNgc7KurZWFLNppIafiitbZc1N8PPe71jLSgHg/MzWXD1cRGzGtlZ0A5nEhArssGOQlUuhDgMOBJYLaVsEkJkAIGWlLegFF/P/QzR7xBC/BflNlhqoy3RR0p4/zdwYHsHF712pOUqFzpHizvmqW6/qvFkFksxaDIUjIDc/spalZzGMyeoB2p7OZSLHiq1dcVxoStga3dSY9WCFETgua2VBuf5x837CR+lvkOx7M4NzbexdX+Dz/MHg5XJmR1hbqXYrYGd1RrP8woBBTmpPP/5TpfSdLAusIett4nfc7W4g9WpXx4FOakU5aRTmJNKQgI8+r+t7D1Yz+D8LH515siYMtXHHKFQJuwqZbGWJcyGnLIjG8Kt8MTShMxoi1kMlUGwCqZRA67MmXb8x8f04ekV2zlQ10x6SiJ56clc/ORnLpkwYXCPDtYlT7khUJO0z7dVcHTfPMYP7tHBna++uY3DCrIoyElj/ifbqG9RkzoRg/EUYSPQu/NQiJmyiZ0xGcsWpM7S5pDsOlDPxuJqNpbU8ENZDU0tvu0WnuMzPTkBh5T8b2MZPbNSKMpJpaymqd1izY79dRHNWmh3QTuaSUDsKFR/QCWVaAMucW47FfgmwHHXAycBvwN2A/2B3wArgWXAX4DHUBav+EEIFcPjT5ny3DcxRf2dlKosSk015gpV0REdNrUb/Ht7KSH7yCL/CoodZSYYS5JVlxSbNbtsrzT0GctVOc9Svr+MSpmBEAkMCfHkycrkzI4wN0uB7nmvViaOtU2tLiuT4Z53eO8c9lU1UNfURkZyIoN6ZPKRSeyBP7xN/N/sqeT0UYUU5Sql6cqJA1yJIfKzUklKdH+fpz+0jD0H67tcqtiwEYqMbnaUsrZWeOmy9jGH0c4SZkNO2aqvFmaFJ5YmZFba4k+GSSk5WN/isliXeSSEKK9p6lADbnS/PNffnjGR3tYlg3ST+Mm65jY2lFRz8ylDWbevukMBzzvPGgnAn97a4MreF+/Z0mwTznqXXZBYGpORRErJnoMNbCypYUNxNZtKa2i04HFikJ6SyNQjezGyVw7PrtjGPmecdEVdM/27ZzAkP6vdXCXS4zDUC9rhxLJCJaVcIIR4xfl3vXPzKmB6gEN/h6pDZQRgbBFC/B+wWUr5lBDiauAHe82OEfL6w8HtPj4Uqp6MkVUvb4D6nZnvzswXDHaEbBgtSbYwlC+HQyW18NOWYFYanr76eK5duJrqME2erEzO7AjzQMVuPSeOW8pruezpz/n1WSPbFbqtazJX5McPsp7xypPkxASKctP436b2Clhji4O504+xdI5YWSWKKfy514Vi3FlVyvauUcpUbYm1UgeRxKKcslVfLQYnV9EMtn76qnH89LnV7Kiooyg3jQvH9OGxj7a4FCirhbO98XYJ8vw/Ky2Jwpw0CrJTKchJ4yMv2VLd0Mq1Jw7i9JGFPuVrrEyUokYsFJvWhJzOyAIpJcVVjWwqqWGD042v1iQDpj9vk9yMZEYW5TCiVzbDi7LJz0pFCNFhAWP3gQa2/vksnzXlIkGoF7TDid1UHOnAWUKIXlLKvzqPD/T2TwAGAp6ZAPsDhl9AbRDtCAohRHfgGeAMVOzXnVLKF4M+oVFrJr2bsjrl9Vfb8vpDTl9ISglBq02wI2TDZEmyjUVXo2BeoKGePJkJu3BMzrxd9ApzUnn5i11sKat1B4lK2HOwgdfW7On09YSAHpnumKZeuSrteK/cdLplJCOE4NMt+4MWnOGa/MR61h+fWHnmOznudh1s5C+OOdy9+o/0+vJZWjN7kXTZC+3P43ILnOoudfDidJVQJoQ1jjqFBTkVi5Nrf8+mdzpzV7FKwmPBlVJS1dDSIeV4WXUjZTVNDOqZyaCeqs9W7zjoOs574jW8MJtNpTWmEzHvYzwRQJ+8dO4+ZxSFOalkpLR/rT/y4Q+m358/+R0rEyWNJpTYsbZLKSmtbnLFQG0sqaHaWQvKH97eJptLa3jg4qMZUaRiD82y5vqSsdEch6Fe0A4ndtKmnwS8BnwJnCClzHZu+7mU0mdKGyHEHagsf8+hXP76Aj8FHpZS/kUIcT5wg5RyamduxApCiJdQCt61wGjgLWCilHKdsY+t1KdNtar+UVpoC8p2OWykTw/75NlCQH44UiI3NLe1SwZRUt3IlpIqVq7fSnFTGhkpya6Ji7/U4lbITE1yKktpztpNqRTlppOflRow21Vn+t/OsdGuGRL+OlQ2a9AFidE3UjrIE/Xk9yzgvTlT2u9kp9RBDBPMsxlqeeKvppL3s2mWztyTYFI1SylZv6+aWS+sZffBevKzUzlvdG+aWyVlNY1+YyV84S1vBO4gZ4Cs1CSmH9uPAmcGvYLsNH7172/Z7VVLamiB/9pX8bQwErWyCiFOGBNPfR4LhFteGOcLlLa9vEYpUBuLlRWqqj6wAuVJZmoSS77d167YtRV5o5+XwIQqbfpc4BIp5YdCCGN5axVwnL+DpJR/FUJ8C1wEjAGKgWullO84P38DeMNGO4JCCJEJXAgcIaWsBVY4E2JcAfwqqJOmZoWugV0ZG3EeYV1psGgls+Na5CmABuVn8JcfH01iominOJVWNVLV0NJuJfj4lO08nvR3eoj9HMjsyWMF97IjRSlNvlKOe5KUKJzpgd3Z84zYpqxO1IAw63+rQtbOd2dnhS4uXQl9PfMNB1Qh6hBNmNx9k8BBmUW1WUIWO6UOYphgZEOosz95n89TofB+Ns3SmRt4W9i8x9g/po8mJSnBZWUyrE5l1U18vKnMpQCVVjcx75PttmoyeePttufd5IbmNu4+p32Zjz0HGixnNTUI9ypy3E8Gw5AwJhLZz+IZfwsk4ZAXxvnMsmWu3LKfDSU1bCqppqLWWolWY05R39xGt8wU5pw+jMnD8unbLZ0NxdVR9/Y51LDzNh0opfzQ+bchSputnMOpPL1js22hZhjQJqXc7LHtG1TCjPggTOmOw77yayHOIyKWKYvZ0AIFcBtuNSXVjfziX99QXtOEBLaU1XHls6t8WpPcma4czBUP8n7bWL7pezlnVP+Lm8ru5Y6+LyJFgiuIG6B7ZkqHtONFuWl0z0ghIcw1mwzC8VKOpZohYcHsmc/MhycnhXTCZKlv7JQ6CAGxNLENtTLufT5Q/W7W/2bpzA2G5Gfx8KXHsLW8ltLqRm7759eUVSs58kNZLWc9vMKnkmRW/81XQghP0lMSXTFNhTnK3bcgO40dFXVs31/nuofEBJUp0N8zFW73XrOMhYGeobhWHsJUjy0uF6MiiJ0FEl94yrt+3dMBFXvkPf49z/f3S47mhsVr2VfVQFZqEkU5aTyzwlc8fkdSkxMYWpDNK1/upr6lDQlU1jezYOUOZowfAGh32Whg5426XgjxIynlux7bTgO+83eQECIFuBrlYtfOpCOlvNLG9TtLFuCdP74KyPbcUF5ezrhxbmvezJkzmTlzZvhbF4gwpjsO5kVk6xgLwfdhfxnasJI9c9Wx/HTBF2zfX0fv3HQuPb4/8z7ZqpSoqkYaW9wTmrKapnbH+it2a3yW66wn9kTTVA5L7sOyHtOZUvMmk/unkNezkF65SnkqyEklNSl6NZsMwvFSjkbNkHnz5nnWielp93hbssH7mc/qBciQT5gs900EM4ZFc2Lrrcz1657eziWvsxN/7+e2f/cMkhMTTPvfkCPbyuuUkiIlPTJSmDKygIbmNh54d5Nr39Lqpg7X8qUkedeD89w/LTnRwzXPXeS2ICeN7NQk07iJ564+rl2f/eG8I/jNf773+0yFa7LmenYAhzPmLNAzZHznnc1EFlH54E2Y6rHF5WJUBLGzQOILT3m3o6LetX1rea0qVO9cnBACumel8OvXv6O0qpERRdmMKHJPP/0lkUhOTGBoYRbDi7IZUZTDwB4ZJCUm8Oj/tvjMgunL2hRLC17xglXZYEehmgO8KYR4C0gXQjwFTAPOC3DcQuBoYAkQzVpTtYB3sFMOUOO5IT8/n1jzgw7X6pVBMBNmK8d0HLir6Z/RbNovYV9JM7EYyJw+lLekUbKnsp2LXklVEwN7ZDKwhxKmn/7gu3a11WK3CQmCnLQkahpbqSKTYtmd2zLf49QzTiRrzYtwoA9XTjk6JlPjhuOlHI2aIZ4THCGE34LkZtiWDZ5KjMMBDwwJ+YTJVt9EKGNYNFfFvZU5I+1vqCb+Zs9tj6wUSqsb+XZPFRc/tZLSmiZy05IZM6BbOzlicMDEncefkuTNsYO68dWuKqo8AtOFgEE9M3n0smNMlSZ/mD1D0XLfM3OTDPQMGd+5J8HIqYjLB09CUULBBG2l8I+dBRJf+HLtdUi1KJCbnkRVQysZyYkMzc+itKqx4850TCKxclsFRTlp/OXCI5l4WE+SEzvODYJ5N8erJTeaiqBV2WAnbfrnQoijgMuBZ4FdwMXAHaj4KF+cCQySUlZavVaY2AwkCSGGSimNNO1HA+v8HGOfcFiSwrR6ZRDMoLRyTIeBu2iNz4Frpw12BpaUkpqmVkqrGqk94VGGf/x/ZHz5LFXJ+Tyafy/bXu/c1+8d73Ti0J4Myc8iJSmBf67eTWl1IwN6ZPLs1ceSKISr3fdl3cU/eICkeceFPk29F5116ezXPZ3+3TNcbgyheCkfMr7aniUDwjBhCjfBPDuhVsDttMFbmTPS/naW+uZWVzzTzaccRrmz0O0D721ylTDwTO5Q2dDCqm0VlpPJeMoRT3pkpjD1yF7KypStrE256Sojp1m/2FWmYg0zN8lAz5DZhNa7sHHME6bSJYeMnLWA2XgxUzjtTtL9ufZmpiQybkDgOVpigqDeZPGkrKaR+97aENIsmPHqBhoPimDALH9CiAzgTpTL3g/AvUA+8ADK5W+RlPImP8d/A5whpYymdcpoy8uo+K/rUPfzNp3J8udNuDJ7Oc9bM+A0bt4xkTOqXuX0pK9pvOkb+vfsfGKMcMVQBcpkE2wbzLK+vXnriZQ5JzxGNj2j4G2DZwYr6SDDUUt9QhZS2PtOPANAc9OTmX5cP0b2ynHFNxXmpLlM9JYy04UpJs6bYLLkhSOzXigI1SpVVLJ4hdFtN1wE8xyEeiXRThs689w2NLe5ituW1jS50o2XVjdSXt3k0x3H4EOTItqnjijweb3kxASXO55Rq8khHfxhyQZ2VtQfku44wcRQxWUWUF9E6J1wKBLK56ShuY1PNpfzm/98T1lNkyszZnqy+s4aWhx+E8UkJAgG9cxkRJGqA3VYQRbnPLzCVDELJhuoP2L13R4IO/PJcNLZLH+PAccA7wJTgSOBEcAC4HopZSDT+CLgP0KIf+Dl8iel/J+F64eSWSjrWhlQAfyfpzLVacJlSXKuXjU+fREL5SKKE7ozs+k26vxYfOwQzCqWlWPsrFRbOZ/DITlQ39wh0HNLWS2znl9rqd1SJFCXGDjNvRCC/OwUt7KUm8Y9/1lHgzMAtLqxhQ83lPGrqSNNj7e0CtQJF6zOrNqHyqUzGsTDKpVPrMYxxdCkKpjnINSr4nbaEGjFtrGlrV3WvNJqpTiVVjdSY1Ic08DbHcdKbFNmSiLJiQnkZ6e2U5yM7JxG7TdvpgwvDNgngQhGMYmF2Ipgnp0u5damC/l2Gl/PcWfeaY0tbWwpq2WjMwvf9v31fLZ1v2u8S/yXN2loaWP9vmoqG1pIShA4pBqPlx8/wDXGjOfYMxbQroXfyhiO1/ESD/GAVhSqHwGjpZRlQohHUK5+J0spP7F4jZudv//ktV0Cgy2eIyRIKQ8A54f8xMYEKDUnfG49fcYyofFhMmUd1WQgSSAxCpNcOy/dYAdubVOrO6bJaWUyVo5b2yTpye0nLhlBpAo2yE5Loig3ncKcVGfNJpVFLz8rlSQvn+XrDn4ZVGY6gDYpOf2hZSGbpNhRLMLl0hkNYlXRs0ygCVOMWbFi4TmwuzCz5BantbqmkW/3VvL+hlJLSpM/vF3xPP9PTBAU5KQy/dh+LPm2mP21TfTtlsEjl47mqL55pkrTrop6Lnnqs7ApL8Ekd4jXxQrt1qbxxGqqcn9ypLnVwdbyWjYUq2K62/bX4fAyHfmTCUJA324ZKvFErxzmvPI11Y0q5rHV0X48es+TXr5+fMCkMHbv3RNjvBhzuSkPfBwX1vB4UAStKFRZUsoyACnlHiFErQ1lCinloKBbFw94T4BOvRs+vC+kftAGg/Kz2VoukFGc3Nh56fp70bW0OSivaXK55xVXNVJWrX4bMQm+sFKnyZPkxASPOk3uFeJeuWlkpFjPyxJMZjrP1Sar2aqCsTr9UFbrU2ELRhDFqvCKhQl+2Ahz8plgiIXnwKwNjS1tLqXJcPU1/q72SNYQKjytTwLolZfG7WcMozCnfQmD30w73DWOf/z4Zz7HcSA52llrUTDJHeJ+sUKjwfdz7E+WtbQ52FZep4rpltSwtayWNrOgKA+8LdK56cmcOrKQ4U43Ps96kDv21/scj96y4Df/+T7oOYKdMRxvCyjxsHBiZTaZJISYgnqPAOD9fxRc92IDswnQh/fB7O+gqTrkLjuWJjdhdheyM2CllBysb3FZmlyFbqsbVe0m//LKJ+kmpnUhjJpN6RQ5laWCnFR65ab7dK2xSzCZ6Tz9fkMp4MwCYQOtSNkhVoVXLEzww0aYk88EQ7ieg137a5m94CO+rRAMys82VRiaWx2U1TRSXtvEbacPo9QZ0/THt9ez4of9fuOZgiExQdAzO5VCZ/IHo1ZTYU4atY2tXL/oS0sKjpVxHEiOdnayE0xyhy69WKGJCLHgNurrOfaUZa1tDnZU1PHmt/vYWFzDt3sqWbPzoC2ZcurIQj7bVkFFbRMDe2ay4OrjfN6rv/EYSiXIzhjWCyihx4pCVYaKOzKo8Prfr+ueECIHlcjiJFT+dk9FrL+NtsYeviZATdVhmQAFnNxEwF3IbMA2NLe5FCXDRa+kqpGymkaaWhwhvX5mapJTWUpzuuilUpSbTn5WKilJwSuQVl4EwUwurQi4YOqomFnA7AjFWHjxBUOsKnohoROpk6P5fdq+9t41pD99Ef+WFRSndOfG/bcx4+k27jp7lDOuScU2HazrmF4c2mfTs1LQ1pOEBEFaUiKfbt3PwfpmeuWk8fvzjuDofnn0yOxYLHtXRT2XzvvcdW8f/fzkgP1qZaISyCW4s5MdQz6YxVAFOqZLLlZoIoKVhYBwyyqz57jNIdlRUcemkho2ltSwpaym3dzEUKbAt0wpyEllRFGOs35UDrkZybbbZDYePfuss0qQnTGsF1BCT8Asf52+gBDPA32BvwPPo9Ku/wJ4TUr597BePAiGDh0qp0yZwrRp05g2bZr/nc2y+m1+F2Z/H3kXnXBlGHTS2uZgf20zX++u5HdL1lFS3UheejLHDezu8gkOFUmJwuWWV+SMaTJimzzN6KEkXJlvrLw8PK9tEO5sfPGa6aezLFmyhCVLljB//vwtUsqhdo61JRuCJchFkWh+n4Gubbj3llY3UlrVwKQ3T+L1uiOZ33Y21ye+xamJXzGx6WFOGVHU7ry+Cl0GyqZnJJRRacbbF7jtkZXKmXM/CWvWQCvHmC2ieO5rdo5QpHjW+Cfm5UOQRGrBxUomtoDjw4aXja/7cjgkuw/Ws6G4hk0lNWwuraGxpWNacgMzmXLxuL5KgeqlFKjumSmW+sAunc1wHKycj9dF1WhhRTZEQqEqA0ZKKSuEEJVSyjwhRB9giZRyTFgvHgS2U5/GShB5/QH46yC4Za2yllVshUfGwB3bLVvLpJRUN7QqC1N1I6WGtcnpoucdlNlZumWmuCxMRU7lqVdeGj0yU9h9oMF2lqrOEM2UnN7XBhhaYO1egxWKsZKCNFpELS2yFYJw242l5zdBwO/OPdyVcvxAXbPLvTezrYqHd1/IVMc/2NCczwBRwrLU25noeIaRgwe0O6+nJQrcWbQ8twsgPzuVP11wpEtp6p6Z0iGhjL/2+uurYPrVzpj0dX7vOnAAOyrqXfsdSosg0SCm5UMQRGrBsKXNwa4D9X6v43dM2ZxPed6XEFCUk8Zlx/VnU2lNu3IpgfCWKYN6ZvK/n59s+fhwYCZHAK0ERZnOpk3vLAlAlfPvWiFEHlAMHBaBa4cfq6mQw423u9DKRyCrSGUe9MII6C6uaqC0pqmd4tToQwj5Wi0O2KzkRIpy3anHDcWpICeVsuqmDsKhZ1YqEFyWqs4QTfO397XtvOyCdYHT5v4YJojUyZH4Pg0rtXetpszURKo9suc5JNy/dKOpjKhPyOZAYk/mZLzHg7VnMMPxFsWyB4P69O5wPe8sWg0tbfzstKHc1HYYd7z2DdvLg6vVZKevgulXO2PSSryHMWn0RMc86BV2O4QrXsbbxa9/9wyG5Ge5vpM/nHcEpz+0rN135HNM2UjKI6WktLqpnWeHlFBc1cjXuysttT03PZnhzix8N085jDte+zam3F09+/aHslom/+0jywutmugQCYXqG1T81IfAclRdq1pgcwSuHRmCqR0R6uQRXpXWpUhASActDx7OmgmP8EPycEqqGiipaqKy3jw2wR/+6rAkJAjys1NdypJLccpOIYdaRHo303v0528dTJaqzhDN+IFoXFvHS3QtQvV9GkqTUaOptLrRVeB2f20zUsoOiyvDC7PZVFrTTgHyFYcgRQKPFdzLTWX3sjThLQ4k9+T5AX9iTFEPV3Fbw9K085lVLjlgLDQc5czo+cHtJwfbVbb6KtzjxMr5zWShXgSJvyxl0SRcCy7eitruAw3tLLieFiRfacJdz7yfpDwyvRvlNU1sLKlRqcxLa6iqb+lQQiXTzyJvdloSw40YqF7ZFOWktUtWFWvPjtm418+5NaK12BIJhep63IkobgX+DOQBV0bg2rFJiNwEpZTUNLW6LUxVBZQe/W+u/PxsvkqfwDs5F3FG9b84+uP/4+m+LyJF8Iqb2WrxLacOpSgnjZ5ZJi42e9fAk/7v0d+qWTBZqjpDNJMdROPa8ZDcQa9AW8fO99na5uBAXbNLYTLSjZfVNFJeo5Qmf3gvrmwqrWH84B4d4hA8ZYbh3qtimvqxM/ssmlKb6NGjgFuTzV9Dz151XEBlw84z4r2vlQQT4R4ndgukGwRKMHEooLOUWSdcCwOBFDWz78jnM+/lZdPwyT9IyChi8ZcH2Fi62zRJjb8SKpmpSSqFeWE2I3vn0Ds3LSTZfiOF2bjXz7k1orXYElaFSgiRCFwN/BFASlkOXBfOa8Y8QdSaaW51tEs57k5B3kS9V82mzLYqcloreCfnIsqS+/BezkVMqXmTDEctdYkd3f+8SU1O6JgMIieNHRV1bN/ffrV4dL+8Tt2jP2EcTJaqYCbgetIeu+gV6OBpc0gqapvcVqYa43cj+2ubOxUP6augZXZaErWNrUjUClqfbun87rzDKchOCyoDpxVlw84zEq/Pk05GYY52W7ZOuBYGAilqdr6jgw2t7D7xMYb87wYyv3yWhsSePFZwLzu2HfR5jGcJlfSURIYVZruy8Ekk1y20VuogFjHL5Gv0oZ63+Cdaiy1hVaiklG1CiJtQadM14NOsLRsrqXBkqrTjVe2Vp4P1zZZrNhkxCmdU/4v3nBaqA4n51CdkufYxsmAVerno9cpNIzc92ZUQwnOwPnd14NViX/e4b+R19P7yWcbc9So98gtdg9+fMA7mBRDMhCmYY7Qwiwx6Bdo/Doekoq7ZpSiVVje5it2GI4kMQF5GCt0ykqmsb1GKk4AB3TN4/PIxlFZ1jIns2y2848LOMxKvz1M8WJOjgXZbjj6Bnk1/31FVfYurkO7GkhrKqhuBbETR84imKj7b10rtdklmSkWHeMyG5ja+2VtJfVMbRblpPHDR0UwY3KNd2QMzd8N4GkdG35rNN+J1cShSRGuxJRIufwuBG4HHI3CtmEZKSTWZZGQWUb70Ab7udzn9Nz5Dv+QCfvnqFlocnTdHe8YoTKl5k+rkfJaN/TsX9uuvkkPkppGfleo3C5avwWp5wHqZ7te8/HuQ3Tko06n0OF+oJwrBTJiCOUYLs8igV6CV0nSg3qk0GS56TqVpf00TbWFQmnIzkjukGy/ITiM/O5W05ETTF3xqUmJUJv7hTjChiV20ohn7eH5H1Y0tbC6pYdkP5Wwqqaa4stH0GCkS+Gyfg7pmJduMeMxJQ/MZUpDJiKIcHnh3Ew3NbUigtLqRe/+7znbx7HjB7DnvKvcWLqK12BIJheo44BYhxB3AblQhYACklJMjcP2IY2TRK61ppLhKBXUXV7mz6A3MuZubtt/LWVte5EBiTx4uuDdoZSo5MYGiXJU1z50UYiRpOZdAWy05aXlMs5n0otOD1StBxjjZnRuab0OSgAzj4A9mwhTMMfEqzOLNsnaorEB7xzS53fOaqKgNk9KUnkx+TiqF2e4kEIU5bqXJH7E0kY2lBBMajcZNbVMrm0pqnD/V7DnYYPlYs5jtRy47hmTnQvDsl7+2VTy7qy2gdOV7CwXRekdFQqGa7/yJC6qqqpg5c2bA4nwOh2R/XROlVU0d6jaZBU96siN1BHf0fZEMRy31CVkBk0UIAd0zU9z1mnJTXe563TNT/ARa2sw86CQkg9UjnfxVT3zDlv2qhko4B38wE6ZgjolXYRZvlrVwCEWjOB+Qa/dYq7LBjDaHpKJOueSVVIU2pskXOenJFDitS4bCVJitFl8CKU3hItRKvZ1nJJYUQU1sEi350BWob27lh9JaNpZUs6G4hj0H6y2HKoDKFjy4ZybDi7L5oayWPQfb17NKTrQWf23QlRdQuvK9xSpWZEPYC/vGG1aK8/3t3Y38UFob8pXjzNQkVyKIXrlprqK3+VmpQQV1B0tnJj2HQjG6eLP0GBzqxXw9CVfhzurGFnZV1FNeExn3vOy0JOWe5+GaZ/y2UicuUhhjxjvAWhen1cQiXa2wbzhobGlzKVAbS2rYWVFnS4ESQjCwRwYjeqlU5ocVZLkWegK9Y+P1HayJf6Jd2LfL4ZAEPTlKSXJm0ct1F7gtyFb/Z6XGxtcRzEqu2YQpqPirOCBeV7rj1bIWT6zZcZDnP98Z0nNmGUqTUafJGdtUkJNKRkr0ZIadSY1hHfUkntxlNZpDnabWNraU1bKxuIaNJdVs318fsMSCJ0JAv+4ZjCzKYXhRNsMKs30u+gR6x8brO1jTtYmNGXycUZSTxuaSGp+fCwH52UpR6pXrUeg2J428jOS4qoVglViaMOnVK3O0m0D4KchJDeo4s5gmIxFELFmaPLHjQqqL02o08UVzq4Ot5bVscmbh21Zu3yunb7d0lwVqWGE2mTGyaKzRhAP9dAdBYU4a4HS3yVVxCZ6uevnZqe38fQ8FrEyYIqXoxFusUKTQq3rhx5ANZuSkJ7utTDES09QZ7CRn8VWc9g/nHcHpDy2LyOJHS0sLe/bsobHRPLuY5tAhMTGRvLw8evbsSYLNpE1dldY2B9v317GhpIaNxdVsLa+ltc2eAtUrL40RRTmM7KUUqOy05DC1VqOJPcKuUAkhLpJS/stk+0+klK+G+/rhYPKwnkwa2lOvtnjga8LkaQWJlKITr1n4NPFP94wUhhVl0zMrNaZjmkKBHRdSX8VpI1krZs+ePWRnZzNw4MAu6SWgsYaUkpaWFkpLS9mzZw/9+/ePdpOiQmubg50H6l0ufFvKamluddg6R2FumquQ7vCibHLTg1egtGeJJt6JhEbwDNBBoQLmAXGpUEUzbiHWMITg1rJaEhMFOKRLkfIWhpFSdHSskD0cDgd79uyhrq5rKZ6ZmZn07ds3oivQCQmCX545ImLXiyZ2XEh9WUcjufjR2NiolSkNQghSUlLo06cPmzZtinZzIobDIdl5oJ5Nzix8P5TV0NRiT4HKz05luFOBGlGUTbfMFNP9glGOtGeJJt4Jm2YghBjs/DNBCDEI8HyLDQa030UXwCUEwaVM+RKCkVJ0dKyQPfbv348QguHDh3cZ9xeHw8HevXvZv38/BQUF0W5OlyQULqSRXvzQypTGoKvIOl9IKdl9oMGVhW9zaQ0NXvWdAtEtM4WRzhioEUXZ9MiyFiMajHKkPUs08U44TS1bUEV8BbDV67MS4N4wXlsTIewIwUgpOjpWyB6VlZUMHDiwS00wEhISKCwsZOfOnVqhimH04odGExqklOytbGBjcQ2bSlVB3bqmVlvnyM1IZmRRDiN6ZTO8KJv8rNSgFiGCUY60Z4km3gmbQiWlTAAQQiyTUurZbRfFjhDUik5s0tbWRnJy1wseTk5OprXV3oRCE1m0TIh9rr76avr27ct9993H8uXLue6662LCVU5KyTXXXMMbb7zB0KFDefDBB2OmbZFASklJdaMzBqqGTSXV1DTak3fZaUmuLHwjinIozAlOgfLGbF4QyA1QL65o4p2wL0nHmzJlVDt3VkQ+pNlVUc/pDy1jyJ1vc/pDy9hVUd9hn2euOpYh+VkkCtEhCYUmfuiKrlBm97RkyRJmzpwJfqqd+0LLBk2ssGLFCiZOnEhubi7du3fnhBNOYPXq1QAUFxdz7rnn0rt3b4QQ7Nixw/QcV199NUlJSezbt8/ydSdNmhQzCsuKFSt4//332bNnD1988UWHtg0cOJAPPvjA1jljWT4oF756PlhfymMfbeG2f37N3a9/z/Of7+TLHQcsKVOZqUmMGdCNGeP784fzj+Dvl4zmxpOGcPLwAopy00L2HjCbFxhugG1SutwAwT3PmPLAxwB89POTef/2k3RCCk1MYUU2CDuF2YLBGT/1R2A0kOX5mZQy5tLrHGrVzv3hmYErQeA3PkoTv2zYsIGRI0dG/LorVqzgjjvuYN26dSQmJjJy5Ejmzp1L3759ueGGG/jyyy8pLi5m+/btDBw4sMPxV199Nc8//zy7du2id+/eptfwdW/+qp37QsuG+CZaz3moqa6upn///jzxxBNcfPHFNDc3s3z5coqKijjqqKMoLS3ltdde45hjjmHixImm46euro6ioiJSUlL41a9+xS9+8Quf1/O0UEWL1tZWkpLaO9Q8//zzPPnkk6xYscL0mIEDB/L0009z2mmn+TxvLMsHKSXFVY1sKqlhQ0k1m0pqqLVpgUpPSWR4YbbLCtW3W3rUFs+G3Pk2bR7zzUQh2Prns/Q8QxNX+JMNkUhX9yIqhmoO0NHEoYlZdJCoJlxUV1dzzjnndJgUpqamkpCQwJlnnsmdd97JxIkTTY+vq6vjtddeIzc3lxdeeMHvhFATPaxm+4p0yuRrF6wO27lDwTNX+7b0b968GYBLL70UgPT0dM444wzX54WFhcyaNcuvu+trr71GXl4eP//5z5k/f77l8fPxxx9z+eWXs2fPHkApLTfffDOLFi1i586dnHnmmSxcuJC0NFWP7c033+Tuu+9mx44djBo1iieffJKjjjoKgPvvv5/58+dTVlZGv379+OMf/8gFF1wAwIIFC5g/fz7HHXccCxcuZNasWe0UumeeeYabbrqJlpYWsrKymDNnDlOmTHG17YorrmDXrl1MmzaNxMREfvvb33LHHXdYusdoIaWkrKaJDcVKedpUUkNVQ4utc6QlJzKsUMU/jeyVTb9uGSQkxIb3ga/wAD3P0HQVIqFQHQ6cIKW0l59TE3V0kKgmXASaFIZrQqiJLFazfXnut6WsllMf+hiHA12PxoRhw4aRmJjIVVddxfTp0xk/fjzdunWzdY6FCxdy6aWXMn36dObMmcPatWsZM2ZMUO155ZVXeOedd0hLS+OEE05gwYIF3Hjjjaxdu5ZrrrmGJUuWMG7cOJ5//nnOPfdcNm3aRGpqKkOGDHFZ1v71r39x+eWXs2XLFnr16gXAqlWrmD59OmVlZbS0tFcsrr32WhITE3n66addFqqPP/7Y9fnixYtZvnx5QAtVtCmvaWKj0/q0obiGyvpmW8enJidwWEG2KwvfgB6ZJMaIAuWNrxgpPc/QdBUikdbrE+CYCFxHE2J0fJTGF1bi6/zhOSlcunQpBw8etHW854Rw48aNrF271tbxmshgdfXZcz8JtLTJDrEWGkVOTg4rVqxACMH1119Pfn4+5557LqWlpZaO37VrFx999BGXXXYZhYWFnHrqqSxcuDDo9tx666307t2b7t27M23aNL7++msA5s+fzw033MDxxx/vGuupqal8/vnnAFx00UX07t2bhIQELrnkEoYOHcoXX3zhOm/v3r255ZZbSEpKIj09Pej2xRIH6ppZuWU/z6zYzh2vfsOvXvuWBZ/u4LOtFZaUqbSURI7qm8fFx/bj7nNG8cilY7j99GGcdWQvBudnxawyBe4ENFv/fFa7GCk9z9B0FSJhodoBvCuE+DcqXboLKeVvI3B9TZCEKwOXroge/3S2CKMxKfzLX/7C9ddfT0lJCWeddRbz58+nsLDQ77HGhPDBBx9sNyEMdoVdEz6srj577ueJdgEyZ+TIkSxYsACAjRs3cvnllzN79mxeeumlgMcuXryYkSNHMnr0aABmzJjBnDlzeOCBB4LK9llUVOT6OyMjw5XkYufOnSxcuJBHHnnE9Xlzc7Pr80WLFvHQQw+5kmbU1tayf/9+1779+vWz3ZZYpqK2iTte/dbWMfFkgQoWnelT01WIhEKVCSwBkoGuJSE1QaErosc/ofB7D3ZSGOoJoSZ8WE2F7LlfQgK0OiQyjC5A/mKU4o0RI0Zw9dVX89RTT1naf9GiRezatculCLW2tlJRUcHSpUs599xzQ9aufv36cdddd3HXXXd1+Gznzp1cf/31fPjhh0yYMIHExERGjx6NZ5KsziZPiLXMpd0zU+iemcKBOt+WqOTEBIYWZjHcmcZ8YI8MkhK7Tn1Au+jFV008EXaFSkr503BfQxNf6CDU+CfUfu92JoWRmhBqOo/V1WfP/cwmURo3Gzdu5K233uKSSy6hb9++7N69m5deeonx48e79mlsbKStrQ2ApqYmGhsbSUtL47PPPmPr1q189dVX5Ofnu/afM2cOCxcuDOn4uf7667ngggs47bTTOO6446ivr+fjjz9m8uTJ1NXVIYRwteG5557j+++/D9m1QSXn2LZtW0jP2RmEEIzolcPKLW4rXGKC4LCCLFcWvkE9M0k+hBUob7wXX698dhXJiQlawdLEJJGwUAEghMgGegKuZSMpZexIO03E0EGo8U9nizAGmhTGwoRQEx20C5B/srOzWbVqFQ899BCVlZXk5eVxzjnn8Le//c21j2fM0YgRIwCVRW7hwoWcd955HHnkke3O+bOf/YxJkyZx4MABunfvHpJ2jhs3jvnz53PzzTfzww8/kJ6ezoknnsjkyZMZNWoUc+bMYcKECSQkJHDllVdywgknhOS6BnfeeSe33HILd9xxB3fffTc///nPQ3r+YDiidw5lNY2MLMpheFE2Q/KzSEnSCpQvvBdfd1TUkyDQ3i2amCQSdahGAS8AR6PijYXzN1LKxLBePAiGDh0qp0yZwrRp05g2bVq0m9Ml0Wb82CIa9Xn27t3LbbfdxqefftphUpiTk2PqriOl5MYbb6S8vJzXXnut3WdGYc/i4uJ2E0Lve1uyZAlLlixh/vz5W6SUQ+20WcuG+Kar1KHShA4tH2Ib7xpV3jGWRi0rjSbcWJENkVCoPgbWAr8HtgMDgT8DK6WUz4f14kGgi3dqDjW68kQzlgt3aiJLV37ONcGh5UNs47342tLmYNeBel0EWBM1ol3Y92jgdCllixBCSCmrhBC/AL4HYk6h0mg0Go1Go9FEF2/3Xx1fqYllIqFQNaIy/LUA+4UQ/YGDQI8IXFuj0Wg0Go1GE+fo+EpNLBOJaMjlwMXOv18FlgLLgP9F4NoajUaj0Wg0Go1GEzYikTb9Yo9/fw2sA7KAReG+tkaj0Wg0Go1Go9GEk4jm65RSOqSUi6WUT0gpQ1Z8SAhxsxDiSyFEkxBigcnnpwohNgoh6oUQHwkhBoTq2hqNRqPRaDQajebQJSwWKiHEYpyp0f0hpbwyRJfcB9wH/AhI9/xACNET+DdwHbAE+APwT2A8Go1Go9FoNBqNRtMJwuXytyVM5zVFSvlvACHEOKCv18c/BtZJKf/l3OdeVHKMEVLKjZFsp0aj0Wg0Go1Go+lahEWhklL+LhznDZLDgW+Mf6SUdUKIrc7tHRSq8vJyxo1zp5ifOXMmM2fOjEQ7NRpNGJk3bx7z5s0z/u1p93gtGzSHIldffTV9+/blvvvuY/ny5Vx33XVs2rQp2s1CSsk111zDG2+8wdChQ3nwwQc71TYtHyKLWQr0/j0yot0sjaYDVmVD2JNSCCGmADuklNuFEEXAX4A24NdSypJwXx+VAKPca1sVkG22c35+Pro4n0bT9fCc4Agh9ts9XssGTaywYsUK7rjjDtatW0diYiIjR45k7ty5HHvssRQXF3PDDTfw5ZdfUlxczPbt2xk4cKDr2JNPPpnPP/+cpKQkEhMTOfroo3nsscc48sgjA1530qRJMaFMgeqD999/nz179pCZmQnQrm0DBw7k6aef5rTTTrN0Pi0fIsu1C1eztbwWh4St5bVcu3C1TomuiUmsyoZIJKV4HKVAATyEqkklgXk+j/BACPGxEEL6+Flh4RS1QI7XthygxmL7NRpNGFixYgUTJ04kNzeX7t27c8IJJ7B69WqKi4s599xz6d27N0IIduzY0e64k08+mbS0NLKyssjNzWXy5Ml899130bkJjSbCVFdXc84553DLLbdw4MAB9u7dyz333ENqaioACQkJnHnmmbz22ms+z/Hoo49SW1tLRUUFJ598MldccUWkmh8Ura2tHbbt3LmTgQMHupQpTXyxrbwOhzPS3iHV/xpNPBOJwr59pJS7hBBJqKQRA4BmVCKJgEgpT+7k9dcBVxn/CCEygSHO7RqNJgoYk8InnniCiy++mObmZpYvX05qaqprQnjnnXcyceJE0+MfffRRrrvuOlpbW/n973/PFVdcwddffx3Zm9DEPy9eEtxx3QbB1PvNP1v6Kzi4PbjzXvbPgLts3rwZgEsvvRSA9PR0zjjjDNfnhYWFzJo1y1QJ8SYpKYnp06dz//0+7sWLjz/+mMsvv5w9e/YAygp08803s2jRInbu3MmZZ57JwoULSUtLA+DNN9/k7rvvZseOHYwaNYonn3ySo446CoD777+f+fPnU1ZWRr9+/fjjH//IBRdcAMCCBQuYP38+xx13HAsXLmTWrFncd999rnY888wz3HTTTbS0tJCVlcWcOXOYMmWKq21XXHEFu3btYtq0aSQmJvLb3/6WO+64w9I9aiLD4PxMl4UqQaj/NZp4JhIWqmohRCFwErBeSlnr3J4cqgsIIZKEEGlAIpAohEhzKnAArwNHCCEudO7zW+BbnZBCo+kkDgfUH1C/beI5KUxMTHRNCo866ijXhPDYY48NeB5jQrh+/XrbbdBo4pFhw4aRmJjIVVddxdKlSzl48GDQ52pubuaFF15g/Pjgk96+8sorvPPOO2zfvp1vv/2WBQsWALB27VquueYannrqKSoqKrjhhhs499xzaWpqAmDIkCEsX76cqqoq7rnnHi6//HKKi4td5121ahWDBw+mrKyMu+66q901r732Wp588kkmTJhAbW0tv/td+7DtxYsX079/f5YsWUJtba1WpmKQZ646liH5WSQKwZD8LJ65KrC812himUgoVI8Aq4EXgMec207AJCFEJ7gbaAB+BVzu/PtuACllOXAh8EfgIHA8MD2E19ZoDj32roG/Hw5/HaR+711j6/BQTQpDMSHUaOKJnJwcVqxYgRCC66+/nvz8fM4991xKS0stn+PWW28lLy+PrKwsHn30Ue65556g23PrrbfSu3dvunfvzrRp01yW4vnz53PDDTdw/PHHu8Z6amoqn3/+OQAXXXQRvXv3JiEhgUsuuYShQ4fyxRdfuM7bu3dvbrnlFpKSkkhPTze7tCaO6d8jg/dvP4mtfz6L928/SSek0MQ9YVeopJR/AU4DTpBSvuzcvBdVFypU17hXSim8fu71+PwDKeUIKWW6lPJkKeWOUF1boznkcDjg5cth+Jlwy1r1++XLbVmqOjspDOWEUKOJN0aOHMmCBQvYs2cP33//Pfv27WP27NmWj3/44YeprKyksbGRN998k5/85Cd8++23QbWlqKjI9XdGRga1tcoJZefOnTz44IPk5eW5fnbv3s2+fcrbf9GiRYwePdr12ffff8/+/e547379+gXVHk3XY1dFPac/tIwhd77N6Q8tY1dFfbSbpNF0IBIxVEgpN/v7X6PRxBGNlVCzDybcDD2GqN9fPqu2Z3S3fBpjUgiwceNGLr/8cmbPns1LL70U8NiHH36Y6667DofDwaeffsq5557LsmXLXPEZGo0lLMQs2cZXbFWYGDFiBFdffTVPPfWU7WMTEhKYNGkShx12GO+9915Ix0+/fv246667OrjrgVK2rr/+ej788EMmTJhAYmIio0ePRkrp2kcI0anrd/Z4TeygMwJq4oFIuPxpNJquRFoeZPeGzx6Fiq3qd04ftT1IjEnh999/b+s47wmhRtPV2bhxIw8++KArMcTu3bt56aWX2rm9NjY2umKVmpqaaGxs9Hm+zz77jPXr13P44YeHtJ3XX389Tz75JKtWrUJKSV1dHW+99RY1NTXU1dUhhCA/Px+A5557zvbYD0RhYSHbtm0L6Tk10UFnBNTEA1qh8qKqqoqZM2eyZMmSaDdFo4lNEhJg+vOw6R14ZIz6fclitd0igSaF4ZoQLlmyxKgnkWu5sU60bNDEAtnZ2axatYrjjz+ezMxMxo8fzxFHHMGDDz7o2ic9PZ2srCxALVZ4xyDdfPPNZGVlkZWVxRVXXMF9993H1KlTQ9rOcePGMX/+fG6++Wa6devGYYcd5rJIjxo1ijlz5jBhwgQKCwv57rvvOOGEE0J6/TvvvJP77ruPvLw8HnjgAUvHaPkQmwzOzyTBaXDUGQE10cCKbBCeJnYNjBs3TurifJpDiQ0bNjBy5Ej7Bzocys0vLc+WMgWwd+9ebrvtNj799FMqKyvJy8vjnHPO4W9/+xs5OTmm7jqGrPIsTAoqhuOmm27itttu63CMr3sTQqyRUo6z02YtG+KboJ9zTZdFy4f4YFdFPdcuXM228joG52fyzFXH6iQWmqjgTzZEJIZKo9F0QRISbMVMedKnTx9eeeUVn5/7W+j5+OOPg7qmRqPRaOIPIyOgRhPLaJc/jUaj0Wg0Go1GowkSrVBpNBqNRqPRaDQaTZBohUqj0Wg0Go1Go9FogkQrVBqNxm/MUrzSFe9J0zn0M6ExcNgoRK7RaDSB0AqVRnOIk5aWRkVFRZeabEopqaioIC0tLdpN0cQIXfE519hHSklzczN79+4lM1On39ZoNKFBZ/nTaA5x+vbty549eygvL492U0JKWloaffv2jXYzNDFCV33ONfZJSkoiNzeXnj17RrspGo2mi6AVKo3mECc5OZlBgwZFuxkaTVjRz7lGo9FowoV2+fNCVzvXaLouVqqd+0LLBo2ma6Plg0ajMcOKbNAKlRe5ubnMmzePadOmReR68+bNi8h14gHdF250XyhC3Q/Tpk0zzlll99hIywbQz4Enui8Uuh/cHMryQT8HbnRfuNF9oYiGbNAKlQlmK0y+Vp06u6+vLz2SbYj09XztGwt9ESt9bNYXXeV7joXxQRAr0HavEQtjIlae51BcLxxjIpbvWcvJwPtafSbsnpcgLVRWr2u3PbE6d4iV8aPlpBstJxXRmDtohcqESD98sdCGWBgAvoiFtkW6j2OhDbHQP74IwfXyLF8syGvEwpiIledZy8nQ7euLWGhbrMrJIM6bZ/mCTiorK8PWnlgdE7Eyfnyh5WR02hALz6Avwjl3EDqFbHuEEOVAJR3Nerkm23xtt7NvT2B/GM5rZ99IX8/XvrHQF7HSx2Z90VW+51gYH0OllLZWof3IhlC0J1xjIlae51BcLxxjIpbvWcvJwPtafSbsnjcY+VAF/GDxunbbE6tzh1gZP1pOutFyUhHxuYNWqDQajUaj0Wg0Go0mSLTLn0aj0Wg0Go1Go9EEiVaoNBqNRqPRaDQajSZItEKl0Wg0Go1Go9FoNEGiFaoQIYRIFUI8I4TYKYSoEUJ8JYSY6vH5qUKIjUKIeiHER0KIAR6fTXFuqxJC7PA6b38hRK3XjxRCzIng7dkiXH3h/Hy0EGK58/M9QojfRui2bBPmfpgohPjCed5vhRAnRui2gqKTffELIcT3zuO2CyF+4XXugc5j6p3nOC2S92YFLR8UWja40fJBoWWDlg0GWj4otGxwE1fyQUqpf0LwA2QC9wIDUYrqOUCN8/+eqEwhFwFpwN+Azz2OPQ64ApgJ7AhwnUFAGzAw2vccjb4A1gN/BBKBIUAxcG607zmS/QB0R2WvucjZD5cDB4Fu0b7nMPXFHcAYIAkYDuwEpnt8/hnwEJAOXIjKxJcf7XuO1Jjwuk5MywctG8LfF/EmH7Rs0LIhEn0RT/JBy4aQ9UVE5UPUO6sr/wDfOr+kmcBKrwekARjhtf9pFoTiPcBH0b63aPUFUA+M8vj/X8Cd0b6/SPaDU6Cs89q2Gbg22vcXzr7w+Pxh4BHn38OAJiDb4/PlwI3Rvr9IPAsm54w7+aBlQ2j7oivIBy0btGwIdV/Eu3zQsiH4vvD4PKzyQbv8hQkhRCHqC1sHHA58Y3wmpawDtjq32+VKYGEo2hgpQtwXc4ErhRDJQojhwATgg5A2OEyEsB+E88d72xGhaWn4CbYvhBACmOQ8Duc+26SUNR67fWN2bCyh5YNCywY3Wj4otGzQssFAyweFlg1uYlk+aIUqDAghkoEXgIVSyo1AFh2Lg1UB2TbPOwkoBF4NRTsjQRj64k3gJ6hViI3AM1LK1SFqbtgIcT+sBHoLIS51vhyuQrkwZISyzeGik31xL0puPef8PyRjK5Jo+aDQssGNlg8KLRu0bDDQ8kGhZYObWJcPWqEKMUKIBGAx0Azc7NxcC+R47ZqD8gO1w1XAa1LK2k41MkKEui+EEN2Bd4Dfo/xl+wE/EkLMClWbw0Go+0FKWQGcB9wOlAJnolba9oSoyWGjM30hhLgZtcp6tpSyyc6xsYKWDwotG9xo+aDQskHLBgMtHxRaNriJB/mgFaoQ4jQpPoNaCbpQStni/GgdcLTHfpmoVYF1HU7i+9zpqMC7uDDZh6kvBgNtUspFUspWKeUe4GXgrJA2PoSE65mQUi6TUh4rpeyOCkAdDnwRyraHms70hRDiGuBXwKnO7x2PYwcLITxXlY7GxtiKFFo+KLRscKPlg0LLBi0bDLR8UGjZ4CZu5EO0g8u60g/wJPA5kOW1PR9lSrwQtTryF9pnIklwbp+KykKSBqR4neMy52ci2vcZrb5ArR5UOvsiAShCZWn5Y7TvN9LPBHAMkOzsk7nAp9G+1zD2xQygBBjp47yfAw84j72AGMzkFc5nwblP3MgHLRvC/0zEm3zQskHLhnD2RTzKBy0bQtIXEZUPUe+orvIDDAAk0IgyJRo/M5yfn4by220APsYjdSlwsvNYz5+Pvc7/LvCHaN9ntPsCOAVY7RxEJcB8ICPa9xyFfnjJ2QdVwD+Bgmjfbxj7YjvQ4nXckx6fD3Qe0wBsAk6L9v1G8llw7hMX8kHLhoj1RdzIBy0btGyIRF/Ek3zQsiFkfRFR+SCcJ9VoNBqNRqPRaDQajU10DJVGo9FoNBqNRqPRBIlWqDQajUaj0Wg0Go0mSLRCpdFoNBqNRqPRaDRBohUqjUaj0Wg0Go1GowkSrVBpNBqNRqPRaDQaTZBohUqj0Wg0Go1Go9FogkQrVBqNRqPRaDQajUYTJFqh0mg0Go1Go9FoNJog0QqVRqPRaDQajUaj0QTJ/wPK36GiBRvl+wAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# input file & pts\n", "ts_file = os.path.expanduser('~/data/geolocation/ChileSenDT156/mintpy_offset/timeseriesRg_SET_ERA5.h5')\n", "pDict = {'IW1' : [-21.30, -67.39],\n", " 'IW2' : [-21.30, -68.25],\n", " 'IW3' : [-21.45, -69.15]}\n", "\n", "# plot\n", "cs = ['C0', 'C1']\n", "#cmap = plt.get_cmap('magma', lut=6)\n", "#cs = [cmap(0), cmap(3)]\n", "biases = []\n", "fig, axs = plt.subplots(nrows=1, ncols=3, figsize=[12, 3], sharey=True)\n", "for i, (ax, label) in enumerate(zip(axs, list(pDict.keys()))):\n", " # read\n", " dates, ts_dis, ts_std, bias, flagA, flagB, dates_fit, ts_fitA, ts_fitB = get_timeseries_with_bias_est(ts_file, lalo=pDict[label])\n", " biases.append(bias)\n", " flag = flagA | flagB\n", " if i == 2:\n", " print('S1A/B num of dates: {} / {}'.format(np.sum(flagA), np.sum(flagB)))\n", " print('S1A/B date range: {} / {}'.format(np.min(dates[flag]), np.max(dates[flagB])))\n", "\n", " # plot\n", " p0A, = ax.plot(dates_fit, ts_fitA, '-', color=cs[0], alpha=0.7, lw=4)\n", " p0B, = ax.plot(dates_fit, ts_fitB, '--', color=cs[1], alpha=0.7, lw=4)\n", " p1A, = ax.plot(dates[flagA], ts_dis[flagA], 'o', color=cs[0], mfc=cs[0], ms=4, mew=1.0, label='S1A')\n", " p1B, = ax.plot(dates[flagB], ts_dis[flagB], 'o', color=cs[1], mfc='none', ms=4, mew=1.2, label='S1B')\n", "\n", " # axis format\n", " ax.tick_params(which='both', axis='both', direction='in', top=True, bottom=True, left=True, right=True)\n", " pp.auto_adjust_xaxis_date(ax, dates[flagB], buffer_year=None)\n", "axs[0].set_ylim(ymin=-15)\n", "axs[0].yaxis.set_minor_locator(ticker.AutoMinorLocator())\n", "axs[0].set_ylabel('Residual\\nslant range delay [cm]')\n", "axs[0].legend(loc='lower right', ncol=1, handletextpad=0.1, borderpad=0.3)\n", "axs[1].legend(loc='lower right', ncol=1, labels=['S1A linear fit', 'S1B linear fit'], handles=(p0A, p0B), handlelength=3.0)\n", "fig.tight_layout()\n", "for ax, num, IW, bias in zip(axs, ['(a)', '(b)', '(c)'], list(pDict.keys()), biases):\n", " ax.annotate('{} {} - {:.1f} cm'.format(num, IW, bias[0]), xy=(0.05, 0.88), xycoords='axes fraction', ha='left')\n", "\n", "# output\n", "out_fig = os.path.join(work_dir, 'S1AB_bias.pdf')\n", "print('save figure to file', out_fig)\n", "#plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)\n", "plt.show()" ] } ], "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }