{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"This notebook shows the electron density measured by CoMP and populations entering the upper energy level of Fe XIV 530.3 nm. Link to [Figure 11](#figure-11).\n",
"\n",
"(The internal hyperlink only works on [GitHub Pages](https://yjzhu-solar.github.io/Eclipse2017/ipynb_html/comp_density.html) or [nbviewer](https://nbviewer.org/github/yjzhu-solar/Eclipse2017/blob/master/ipynb/comp/comp_density.ipynb). Do not click when viewing the notebook on GitHub.)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from astropy.io import fits\n",
"from astropy.visualization import ImageNormalize, SqrtStretch, ZScaleInterval\n",
"import sunpy\n",
"import sunpy.map\n",
"aia_193_cm = plt.get_cmap(\"sdoaia193\")\n",
"import juanfit\n",
"from juanfit import SpectrumFit2D, gaussian\n",
"import cmcrameri.cm as cmcm\n",
"from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
"from matplotlib.ticker import (AutoLocator, AutoMinorLocator, FixedLocator, \n",
" FixedFormatter, LogLocator, StrMethodFormatter, MaxNLocator)\n",
"import scipy.optimize\n",
"from scipy.io import readsav\n",
"from scipy import interpolate\n",
"import skimage\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def plot_colorbar(im, ax, width=\"3%\", height=\"100%\",loc=\"lower left\",fontsize=14,\n",
" bbox_to_anchor=(1.02, 0., 1, 1)):\n",
" clb_ax = inset_axes(ax,width=width,height=height,loc=loc,\n",
" bbox_to_anchor=bbox_to_anchor,\n",
" bbox_transform=ax.transAxes,\n",
" borderpad=0)\n",
" clb = plt.colorbar(im,pad = 0.05,orientation='vertical',ax=ax,cax=clb_ax)\n",
" clb_ax.yaxis.set_minor_locator(AutoMinorLocator(5))\n",
" clb_ax.yaxis.get_offset_text().set_fontsize(fontsize)\n",
" clb_ax.tick_params(labelsize=fontsize)\n",
" return clb, clb_ax"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Filename: ../../src/CoMP/new_l2/20170821.comp.1074.l2/20170821.174607.comp.1074.dynamics.fts.gz\n",
"No. Name Ver Type Cards Dimensions Format\n",
" 0 PRIMARY 1 PrimaryHDU 84 () \n",
" 1 Intensity 1 ImageHDU 38 (620, 620) float32 \n",
" 2 Enhanced Intensity 1 ImageHDU 38 (620, 620) uint8 \n",
" 3 Corrected LOS velocity 1 ImageHDU 39 (620, 620) float32 \n",
" 4 Line Width 1 ImageHDU 38 (620, 620) float32 \n"
]
}
],
"source": [
"# with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1074.l2/20170821.comp.1074.quick_invert.median.synoptic.fts.gz\") as hdul:\n",
"# hdul.info()\n",
"# header_1074 = hdul[0].header\n",
"# intensity_1074 = np.copy(hdul[4].data)\n",
"\n",
"with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1074.l2/20170821.174607.comp.1074.dynamics.fts.gz\") as hdul:\n",
" hdul.info()\n",
" header_1074 = hdul[0].header\n",
" intensity_1074 = np.copy(hdul[1].data)\n",
" enintensity_1074 = np.copy(hdul[2].data)\n",
"\n",
"comp_nx, comp_ny = 620, 620\n",
"comp_xcoord = np.linspace(1 - header_1074[\"CRPIX1\"], comp_nx - header_1074[\"CRPIX1\"], comp_nx)*header_1074[\"CDELT1\"]\n",
"comp_ycoord = np.linspace(1 - header_1074[\"CRPIX2\"], comp_nx - header_1074[\"CRPIX2\"], comp_ny)*header_1074[\"CDELT2\"]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(4.35, 310.5)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"header_1074[\"CDELT1\"], header_1074[\"CRPIX1\"]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Filename: ../../src/CoMP/new_l2/20170821.comp.1079.l2/20170821.174303.comp.1079.dynamics.fts.gz\n",
"No. Name Ver Type Cards Dimensions Format\n",
" 0 PRIMARY 1 PrimaryHDU 84 () \n",
" 1 Intensity 1 ImageHDU 38 (620, 620) float32 \n",
" 2 Enhanced Intensity 1 ImageHDU 38 (620, 620) uint8 \n",
" 3 Corrected LOS velocity 1 ImageHDU 39 (620, 620) float32 \n",
" 4 Line Width 1 ImageHDU 38 (620, 620) float32 \n"
]
}
],
"source": [
"# with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1079.l2/20170821.comp.1079.quick_invert.median.synoptic.fts.gz\") as hdul:\n",
"# hdul.info()\n",
"# header_1079 = hdul[0].header\n",
"# intensity_1079 = np.copy(hdul[4].data)\n",
"\n",
"with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1079.l2/20170821.174303.comp.1079.dynamics.fts.gz\") as hdul:\n",
" hdul.info()\n",
" header_1079 = hdul[0].header\n",
" intensity_1079 = np.copy(hdul[1].data)\n",
" enintensity_1079 = np.copy(hdul[2].data)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Filename: ../../src/CoMP/new_l2/20170821.comp.1074.l2/20170821.comp.1074.mean.synoptic.fts.gz\n",
"No. Name Ver Type Cards Dimensions Format\n",
" 0 PRIMARY 1 PrimaryHDU 90 () \n",
" 1 I, 1074.38 1 ImageHDU 56 (620, 620) float32 \n",
" 2 I, 1074.50 1 ImageHDU 56 (620, 620) float32 \n",
" 3 I, 1074.62 1 ImageHDU 56 (620, 620) float32 \n",
" 4 I, 1074.74 1 ImageHDU 56 (620, 620) float32 \n",
" 5 I, 1074.86 1 ImageHDU 56 (620, 620) float32 \n",
" 6 Q, 1074.38 1 ImageHDU 56 (620, 620) float32 \n",
" 7 Q, 1074.50 1 ImageHDU 56 (620, 620) float32 \n",
" 8 Q, 1074.62 1 ImageHDU 56 (620, 620) float32 \n",
" 9 Q, 1074.74 1 ImageHDU 56 (620, 620) float32 \n",
" 10 Q, 1074.86 1 ImageHDU 56 (620, 620) float32 \n",
" 11 U, 1074.38 1 ImageHDU 56 (620, 620) float32 \n",
" 12 U, 1074.50 1 ImageHDU 56 (620, 620) float32 \n",
" 13 U, 1074.62 1 ImageHDU 56 (620, 620) float32 \n",
" 14 U, 1074.74 1 ImageHDU 56 (620, 620) float32 \n",
" 15 U, 1074.86 1 ImageHDU 56 (620, 620) float32 \n",
" 16 V, 1074.38 1 ImageHDU 56 (620, 620) float32 \n",
" 17 V, 1074.50 1 ImageHDU 56 (620, 620) float32 \n",
" 18 V, 1074.62 1 ImageHDU 56 (620, 620) float32 \n",
" 19 V, 1074.74 1 ImageHDU 56 (620, 620) float32 \n",
" 20 V, 1074.86 1 ImageHDU 56 (620, 620) float32 \n",
" 21 B, 1074.38 1 ImageHDU 56 (620, 620) float32 \n",
" 22 B, 1074.50 1 ImageHDU 56 (620, 620) float32 \n",
" 23 B, 1074.62 1 ImageHDU 56 (620, 620) float32 \n",
" 24 B, 1074.74 1 ImageHDU 56 (620, 620) float32 \n",
" 25 B, 1074.86 1 ImageHDU 56 (620, 620) float32 \n"
]
}
],
"source": [
"intensity_1074_mean_grid = np.full((comp_nx, comp_ny, 5), np.nan)\n",
"with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1074.l2/20170821.comp.1074.mean.synoptic.fts.gz\") as hdul:\n",
" hdul.info()\n",
" for ii in range(5):\n",
" intensity_1074_mean_grid[:,:,ii] = np.copy(hdul[ii+1].data)\n",
"# hdul[0].header\n",
"wvl_1074_grid = np.array([1074.38, 1074.50, 1074.62, 1074.74, 1074.86])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Filename: ../../src/CoMP/new_l2/20170821.comp.1079.l2/20170821.comp.1079.mean.synoptic.fts.gz\n",
"No. Name Ver Type Cards Dimensions Format\n",
" 0 PRIMARY 1 PrimaryHDU 90 () \n",
" 1 I, 1079.54 1 ImageHDU 56 (620, 620) float32 \n",
" 2 I, 1079.66 1 ImageHDU 56 (620, 620) float32 \n",
" 3 I, 1079.78 1 ImageHDU 56 (620, 620) float32 \n",
" 4 I, 1079.90 1 ImageHDU 56 (620, 620) float32 \n",
" 5 I, 1080.02 1 ImageHDU 56 (620, 620) float32 \n",
" 6 Q, 1079.54 1 ImageHDU 56 (620, 620) float32 \n",
" 7 Q, 1079.66 1 ImageHDU 56 (620, 620) float32 \n",
" 8 Q, 1079.78 1 ImageHDU 56 (620, 620) float32 \n",
" 9 Q, 1079.90 1 ImageHDU 56 (620, 620) float32 \n",
" 10 Q, 1080.02 1 ImageHDU 56 (620, 620) float32 \n",
" 11 U, 1079.54 1 ImageHDU 56 (620, 620) float32 \n",
" 12 U, 1079.66 1 ImageHDU 56 (620, 620) float32 \n",
" 13 U, 1079.78 1 ImageHDU 56 (620, 620) float32 \n",
" 14 U, 1079.90 1 ImageHDU 56 (620, 620) float32 \n",
" 15 U, 1080.02 1 ImageHDU 56 (620, 620) float32 \n",
" 16 V, 1079.54 1 ImageHDU 56 (620, 620) float32 \n",
" 17 V, 1079.66 1 ImageHDU 56 (620, 620) float32 \n",
" 18 V, 1079.78 1 ImageHDU 56 (620, 620) float32 \n",
" 19 V, 1079.90 1 ImageHDU 56 (620, 620) float32 \n",
" 20 V, 1080.02 1 ImageHDU 56 (620, 620) float32 \n",
" 21 B, 1079.54 1 ImageHDU 56 (620, 620) float32 \n",
" 22 B, 1079.66 1 ImageHDU 56 (620, 620) float32 \n",
" 23 B, 1079.78 1 ImageHDU 56 (620, 620) float32 \n",
" 24 B, 1079.90 1 ImageHDU 56 (620, 620) float32 \n",
" 25 B, 1080.02 1 ImageHDU 56 (620, 620) float32 \n"
]
}
],
"source": [
"intensity_1079_mean_grid = np.full((comp_nx, comp_ny, 5), np.nan)\n",
"with fits.open(\"../../src/CoMP/new_l2/20170821.comp.1079.l2/20170821.comp.1079.mean.synoptic.fts.gz\") as hdul:\n",
" hdul.info()\n",
" for ii in range(5):\n",
" intensity_1079_mean_grid[:,:,ii] = np.copy(hdul[ii+1].data)\n",
"# hdul[0].header\n",
"wvl_1079_grid = np.array([1079.54, 1079.66, 1079.78, 1079.90, 1080.02])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n"
]
}
],
"source": [
"FeXIII_1074_fitmodel = SpectrumFit2D(data=intensity_1074_mean_grid[:,:310,:], wvl=wvl_1074_grid,\n",
" custom_func=gaussian,custom_init=[1074.6,0.1,0.2])\n",
"FeXIII_1074_fitmodel_3point = SpectrumFit2D(data=intensity_1074_mean_grid[:,:310,1:4], wvl=wvl_1074_grid[1:4],\n",
" custom_func=gaussian,custom_init=[1074.6,0.1,0.2])\n",
"\n",
"# FeXIII_1074_fitmodel = SpectrumFit2D(data=intensity_1074_mean_grid[:,:310,:], wvl=wvl_1074_grid,\n",
"# line_number=1,line_wvl_init=1074.6,int_max_init=1,fwhm_init=0.2)\n",
"FeXIII_1074_fitmodel.run_lse_mp(ncpu=\"max\",prev_init=False)\n",
"FeXIII_1074_fitmodel_3point.run_lse_mp(ncpu=\"max\",prev_init=False)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:10: RuntimeWarning: divide by zero encountered in true_divide\n",
" # Remove the CWD from sys.path while we load stuff.\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:10: RuntimeWarning: invalid value encountered in true_divide\n",
" # Remove the CWD from sys.path while we load stuff.\n"
]
},
{
"data": {
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7/uOlmW2NT7yI7zaWU2rSJU88OeL804+cKT+ZnaWPFHtc5hRCrDCfSylXGptXoNyozccs3dO2yWpQYbEcKMcF8IQ5LrO6AiBdkdSxzmbSs+OAI1SCtBBpxSTPdeJQBrX6qPMYNDrPQXsvHEeQy7mMjNQpFn08z0nERUdvL2tXrcfzHCYz6sHOX8tMZJkPT5jlUswpkR9JwAgpchwlGqSUSbggoU5mhrFahO85SdiSGZKoFwRUyJISDNVaFN8XBLV6lNwvSkVPba+G1Kp1wjBicKg+8YnvJ3b+WmY6E3kbwqjl2xmaqxRecI7Hx99zTWafXKWXWy88a9yxv7/vABbpJjFheiZUW9rbFVwKDMSu0zVCiHcJIS6Kt7Vqc63bYe9pm8VyxJjnwpnzPHorfhJSpIwMmWlLL6WM/ylDJIrAc5XB78UhTea9pB4bFY0wQsZCQyVIK0+E5znUaiFSwvCwMjDCMGLH9mH++Os78AMvTpie1Eotdv5aZhR9Dpzc41DKq5+uSGbzDKSUceWjiEaoxIDOR1BzV4UeuQ7UG0r0h5GMk6YjxqoR9UaUeCBBFUBwXUE+51CrRzgO5AKHwTjXIZdzWbt2ANd1Mp6LScDOX8uM5WCTmJsX2n7xu+xv5+vfeDoLn/6qg/qMDI44+H8ziL3d6bqAFVJK3b3ualTM5aQghHh/7L6ZSaFglinKkzvgqQs8KmU38TJEUdbwmAid5KyPS4VH9jgd7qQqLqUCo14P46ToiEYjSsaLYuPG89xYdEzqDcbOX8uM4bx2OHeWQ3vBwREk+UWemxY2EEJ5IhqhCn3wPYET/8rVY8+gzocIQ5nJRwK9UKDExNBIg6GRRrJ9eKSBE5dwHRkN6azkGB5pEAQuixdXOOaYLkolfzK/sp2/lhnJ4ah+dPV/3c27LvzbCbefvDTr3viGHOMbcuwQn9XMYW/iYQ2qWgMA8Q2sErtGW61k6BWPPW1LkFK+X0opZoILxzJ16RDwjB7BSfNzdHd4iYFuJkSr16LFeyoMwo1DjBphpBIlGxGRlERS5T7osCbT+E9FRurZ0BWWGg3lqQgCF9cV7N41ghCCctukxkzb+WuZETx/tsPyWT6VkksU913QIUe6D4P2FuoFPpUc7STeBi0aRqtp6BGQWUBwnbSYAaSLA4W8m+zjCJJwxcB36N9Z5fH1u3h8/QCDg7XJ/Np2/lpmHEeibOob/v6cce8tXVzav0HMcokH+m8GsbfSLmsYfxMaQN2cVmIkZWmklGtiA6rltgM5SYvlQHlGj6BSdKiU3STmWXsKTBGhhYMpGjJCQEqisPUCnc6DML0Q5n1CGyphGBGGenwByDg3QiSeiQVLZwGbJ+vr2/lrmfY8uUOVUG7E3jwtDsJYkHtu2oCxESqx78diX6PLKevKS2GkVs4aYYTnClwHqnWZJGpqr6IQat/h2AOhvR2+79BoqIUEfS5hpMIbJxE7fy0zhoMRDc96ss/PbjnwfKIvfOb2ce/98Fejmdd7Pb8ZFnZ0sOxRPMQ3ojVCiIqUciBe8VgTr4AMmMZVvO3bxnEtt1ksh4vTCrB0dkAucGjEddt1mVRdXSUbtqQeTVEhZRrmYHolzOdmtJPuPO0gkoZTpiECqtSr6wrCEEZH65nkaXd/ykzsBTt/LdOZU/LwhHketUY69zxXJAJACCUWdFJ0GJFUWkrnq8D3HEbHVOdo3yPJgUiTpElEQBLOKEFI3evBScKZAl/gOA7VWkQ+5yIa6fz3XIeN/dVJ+/52/lpmCgfrbTgY4bCv6JClb84wD8GhYl+Kyl8KvFsI8QiwDLjQ3CaEeBdqheQsKeVl+7jNYjmk/OU8h46iiyOIhUO6yg+pF9F1RWa1sDmkyTRaTAGhH3WOg2PccPRzLUy0iHCM1dAwrgbj+64Kh2qok7j/nnWTeyHs/LVMQ57dJygGDq4j6GxzGatGSXM2HVqk+rKkIUjas6gLHEgHQFJvyGTe6f4MflzZzHEEujpyFIt8s7xrsuAgIDSqsbmOYKwaUq1F8TmpcxmuTq7rATt/LdOcGdPd2YqKDOJQdMQ8EGzSlmUy0GUcZ3f548KT1HP1qA0H9VyO20fKNNdB76+9CqYXAUh6PLT6PD1eGCoDplTyM4naQeASBKqEay7nUq9HfOCmAT3etLlb2flrmQwWeXBSl6CnzU3KNQZeVrh7rkgM+EaYhgl6pichlEnlI71wIKWqsASQD5xELOhjtXBQlZiU98FJwpXV2LnAST5nrBomXpB6Q5LPqaIH/3nPmP7caTd/p4o9YJn+TFfR8E2U91DPXz03nGVvOeixo0c+mxl7OjPpHaksliPFM3oE5y30mNsTJF6GVqJAPzfRidHaI+EYMyOMdKx1KiR012knjoHWAkSXa9XiwHGU58GNDZ4wtoiklEm4UqMRUS4HhKEkn5/cDtMWy3Shz4FTuh1621VRg5wvCLy0ZKoQIs4vUsZ6ta68CjoxGlKvQS5w8D1BMe8S+E6yXc9RXXlJRwnW6lHSG8KsyhT4Tiw80nwIIVSOUz7nks85SeM4KWXyORbL0cxkCIfjF0X823c+CsDSeZPu0dt/bKnWDPZOZ5kRXNApWDIroNLmZ0KLdKiQFhPmo15lMztKa0GgUVVdzPCFtFa8WZ1Jo8fyPJF0izZLu46NhYRhRKHg09aWS85xeLiG7zu0dRQO/cWyWKYY57bBxYs8uspOUjGpEarV/1o9SsqxAkl5VoDAVzkNxbwK/3ObfqCrtTApy+q5At9T/0xBkoQXOlDIq+pnhbybeC50Wdgw0nNZUoobPfrxAsA55x1DpWPSu0tbLNOOAxEOn77zp+PeW7XO4V9e/E8ArNlwaE3VfSrTOoniYcZ3mLZYpjrHBXDGXI+2olpp1CEKCu0VMHMYMhM4eR7F+xG/5TSpAm3kQ+p50PHPJqmXQWTEi85p0K/DMGL3bnWz8n2Xru4SI8NVapPbJM5imdIs8pS3oZxP51Za2VAJBuGouRRFSizU4txJVQJZhS4Nj4ZJUrPOY6jV1ZzTngIdmqTH1fNZJ0RrHKHmtm4gp+e6ur+YXaiVKHEdwX13raVejxKvhcVytHEw3oa3nfHsce/tLYJOV007EOb1SjZsO3KegJkQtmTFg2Xa8vzZDj3tLqWCqsGujQFHCCL0nUcAcpyXQOc06OeaMFLGgF6Z1GFInuMkHoSJ8LRxEUpcN7vN913CMCIIXPJ5j3JbHikhXwwY2jVC79xuZi1ayPpVq4FNB35RLJZpwoVdgq6SQ94XSeUz7VFQeQ0y8QxoUaGSn0n20fOx3kgTp6WUhJFI8hxcB0pFj2otwnWUN6Nal0nlpbTMqySMVId4x2gGqXFdJ9O7JZ/3GBqq47qC855+Br/43u02bMlyVHKo8xs++8At/PuTz2fTdjMq4MDHaxYO+3T+NmE6g73TWaYd55ThkvkuC/sCSgU38SAkHoEmC9/0GDRjllrVK55R3NQtyVtIKjDFFVsM74aZV6EftXFjeiE8z6FQ8CkWfVzXodLTwYJj5vPS/7iG5acfR9gImXviWeOSrS2WmcYpebi4WzC34lLMOeQCJ/HiRZLkUYcqaW+d54q4J4Pp2SMjLpSXIO0UrccaHmlQrUXKCxEnReeCOOcoTsb2PXUugZ9WYnIdJRR8TyTCRgjI5z18303uBfWxMVxXkMu5e/n2FsvM4eUif1gSo99ywpMzwgHgVS+df8g/N4PNechgxYNlWvHkDjhtQcCcbj9TfhHSSiFRNF4UmMnQ+l9z/wW9v35f1373fSebRyHEuORqIVRoUhiq1VItGsJQEoYRo6P1eCyXY09dxpnPvRQ/l+O773sFpz7rVSw/62xOePb7+JurHzgMV9FiOTKcWYIT+1wW9fr4nqCQcxiNy7D6nvIyNEKVtDxajWJPYFpi1XWF6jAdmgUKZFKeVfds0ILC9xxe9baXcv4Fxydj6G7T9XqUJELr3/VqLUo8IHphwIs/U38OwOhog1pNdXwcGW3w65/fQxTJ5D2LZaZzuKopvfb+h1u+/7VrHj8sn29pjRUPlmnBBZ2Cly/2OHFeMC40wMxn0AJChxY4Troa2QotAPTzZu+FqqI0/hjVmEoksdlB4OD7Dp6X5joEgZskTbuuw9hYA+E4vOhDt3HCc97Pcz9wM21dHZR6ljCweQNrf/dfk3OxLJYpxnnt8NKFLisWBuTjSkhhBKPViJyvREQjzOY6SAldHQFtJZ8wXhDQDd4cJ7uQ58VePrPHohIhEdvXPcro8KjqAh3GnaCNikuOIxKPh+r9khY6cOLqTmE8Vj7nUK9H7NhZZdfuGlEE+ZxLqehRKnqUy8Fhu6YWy5Fgf70Nz3nawRUSuOi8f6WteFBD7BN7TZpuXn08kH8zCJvzYJnSLPNheUWwsNePSzW26suQlktVNn+6PUzqwGdDm0zvg9o+vlu03j8MZSb+2bwXuK4KffA8h3o9xHWduPGc8jj4vkujEcUhTA7l9gLfetvpVPp6eeZ7r6derZGvzGdkcJAl578JeNMhvJoWy+FlkQdL2wTzO106yl4cHqTmpy5w0AiVt0Cv6gdeGr60eXtVVUdyTA+hTJKghSAOY8r2WdFzPIokP77u9ng8kXyObiinuk47cRnlVJhoj4b2TOgysb7n4MSexUolT60WMjhYY+GiThYet5iR3YMQ92mxWGYS5//HdYzWGvzNyRErH3So7WNtj5/cdHBd11+285sMHtQIk8QMCzs6WKznwTJlObcNnrLYZ1Gf7tuQbtPGeVr1SCTeBv1o5iK0Ev6mWGgWFaokqxMnaUZGmVfTOEk7RjfifbRIyOc9tVpZDykUVFnHtrYcURgxNjLGM997PQCPrtqAX+zmmLOfcsivp8VyODmvHZ6y0OOkBTnaS6qBms47AJXIHPgO7SUXz4VCzkk6uSujPU16DmNPX70hEy+iym1IjX1oDlXMNn5z46aP2psQ+A6FOEfBXDSQUuUr6RKtixZ2UCoo4VMuB5TLPm1tAa/5+Bd5wWWvoq0tYGDnCI/c9wiLTjntcF1ei+Wwceejm7l61t0c94G/5S/e/Dbe8oFLk21/d9mpR/DMDo5vdr7sSJ/CtMV6HixTjjNLsLjTpb3oZGqtt8LMc8i+D5CGHmlDwhQaJtrzoAWGzneIpOrzoEMYzDyL1JsRN5XyHFxX1al3XZdi0adWC1XJxxBOOucUTrjgEm766qeoj/bjF7p4zy+28+hvP8/XP/J5+hzYOgV64VgsB8N57bCoy6OYd8gHadiemkMwOBLiCOKeC2lzNd9zGB5t0EAb7iAjSSjTfgy6dGoYzz8d3qTCmmLBkSROS2QsIhphWrlJz/FanPOgPZf6vhCGqgFco6FyLB5bt0t1hy96NBoRH7x5gC/+zTK++S9vZmy0RrHo014p0jOnh69+4ltH8MpbLJPLZf97E7VGyDU3/onbztoJwH+88T+T7Te9+T/57D9fBFedwANXfIUT/t+rj9Sp7jOfued6/v60iwHl1QD23uMBZlzY0cFiPQ+WKcXF3YLTFwT0VjwKOScRDZHM/jOJYmNCG/zmHNciQSdROy1USGa1Uqgmca4jkrwHLRoiY3zP02Ub4zjqMK3Q5LoOjYYqy6opFHxWvOitLHrSZSw84Th++4XX8MMrzgdgyflv4pynnkSbLdRimeY8o0dw8vyAnoqv5q+jeyXIpGJSzhe0lTzyOTcR4a4jqNWjeJ6qnARd+SgNcUo9BzqE0Qx38tzUw6grnunxzHwJ0HlNujyr6lat85vqjYhqLaSQdxMPo5SqwpJOiB4bqbJl8yC7d1fZvn2EzRt3cf9da1i8sO2wX3OL5VDQ94Yv8ODGfha9/1m0dxRZ8YMennf7nwDo//i3edKNd/DOX72Z3kuu5p8+9tfTQjgAiXDYb2yTuAxCNi/BHiGEEFPjRCyHnT4HTupQcdGFnJP0WAA131TIAhkh4Yj00aRVqVMdagS6tGMa1qQ9Do5DUgLS3E83i0oTsEWS46BCldLkbM9z8H03KdfouioPAiCX88jlffLFHJWeCpd+/M7k/Nbd/iUWnvNaLn9imQuedy7PuuIGYHo1krHz9+hlngsnVgTzuzzyOVXmVJU7VUb7rqFGUuo08J1xAj6KJKPVkMB3GB4NkXGZ1o42j3o9YmhUJVXXG+kCgVmaVQiSIgpaIOh7iPY06Mpnep4DSdWmwFdhTPnASTwbrgNtZZ+R0TDxeICq3uTFzeOKBY/RsQaFWFQsWdrNroER3vvLHfE5Tr/5O1XsAcuR4/0LA659xZepN0J+dPoGPvDKDybbXvvaE3n6vU/HXdSDjBufbnjvE3j7Wc8bN84pP7mVPz3nSYftvA8G7Xl4ucjzTVSOhp6/em44p7/zoD8nuvtjmbGnM9bzYDliLPJUiMNfLHBZPsenVHBb9mRw9/JXqksqmo3gmnMczKpJjkOSv+Aan6dFgOsqceA4EMS14LUBopMw6/Uwea4FhRYOepVTr1iqkpBxeEUjZOe2nYT1ER6+8aMALDzntay/43849vjZLD37wkm5thbLoabPUVXQzp/ncsycgHycs1CrR4RxB6eRsZBiXlVXqjcku4YacUO3tI+K6wo6yn7ihdD3gB0DdcIIygUnKdOaVkNTiwr6sd6Q8ZwjTspWngk9llk4QXsb6g21f3N3aX2fGByqpyViHeUdUQ3o1GdVqyGNhsq96uoqMDw0Rn//6OG6/BbLpBO8+KM8tN7hFxd7PPbY9oxwAPjSl+7n5vP/yPlnLePFzziNF158Ksd8bhXXPOGt48aaLsJhn7HVljJYz4PliHBxt2BORXkakoZPZkK04VXQVVIg632AtNKKprl6kul10O9D2p02m8OgwpGUB8HJ5EmMjNQRQnkQgMSjICUEgZs0gYuiKInv1iEOnufQ0VmiUW/Q3tnG0O5hALpndfFXn7573LUxcimmzd3Gzt+ji2f3CUo5h642N6lWJISgWgsZq0k6yh61uhIQucBJSqTW6pGRCK0M+HLRIwwjxmoRhZzLWE0dlw+UJyKS6fzU81uHEeYCJ06ilklTNyfOe9DN58z+DM0dq3WJ1yiS+F66SqEFg37UCdi6I7X2SKpKak7aUNIRfOZuJSCm4/ydKvaA5fDx6i/fyP/96E46ett4+hf/AYBrnv5eXvrLfwdUiFIh8Hjnus/wuY/eBMDxiyIefEzNl0/c9h3+8dwXA/CpO36UeCHee/U/8u+v/8Rh/jYHz4SehzPeddBjR3d+JDP2dMaKB8th5ZQ8LGgXzO/2x4UnQSoKTOEAE/+o6ZVKs7+DKSZMb4QON1DPnUzIkR7e9524KVzsmXAdwjCiWg2VcRIbDInxEYuNtrYcle42dm4fxA+UwBgeGiOKJIViQKGYI8j5jI1UCfI+URhRrzXwA49TnnIej95zD6/43J+av/O0ucHY+Xt0cFoBFnU4LOj1k+IAtXpELs7vqcehDKYhrudZvZEKh+HRBp4rGBmL8D1BtS7J+Sq0qd5Q4UVa4OumcdpTGMnUGxn4DvVGRCMkKeeq57LuCN3cTFLlSSjvRHqfgVzgJvcR3aHac0XiWdThjdqzGPhO4oVQHgk15n/eo0IgpuP8nSr2gOXQ4579z5x08amc/B+voe1/fs73bn2Q75W/y+c+/hu+/Zx/pW9xL4Wcz+Prd7BkSR8fvOvtXPDha3ntb0cpv+3FR/r0DxlWPOwbttqS5bDQIeBpsx26yi65IDXcm3MZYLxwCCOZlE1s5flr9i7oH3mNXkHUq4itkqZ1cnS9HuF5aUfpMIyo1yNyOeVdUNWTlKAoFn3Kbfk4B8KlUQ+RUpIvBtRrDYQQ5HJuvDIZkS/m2T0wTKMRUqs2KBQDokiy/oH7aeuqcMNHn8NF//STg7vQFsshoEPAX8xRnoZiPs3sb65i5DoiCUsCMivyYaiERrnoxZWVwmTOayNdCOIEZgBJPhBxTkNcptUQDuqzo+Rzoog4KTsVGVEkcWRaFlZ7Q/QYOl+iHocfRXG+hqvPK85tAjO0kbjsbGiUkFafq7+vxTKV6Xrd52H7IGd//DVUHXj2KYu44Z61vKfnDczjNzzvmafzsicu5+LuGt/bILh19Wa+/5Fhvn/9szn9e79h9ZH+AkeCGRZ2dLBYz4PlkLKiCLNKgjmdHr6XJiQ3l0Y1E6BbJT3rY5q36VBCcyxz5VFK8Lw07jmMJLk4zEgbBbpSEijDxXMFhYIXhyHFRkUc6uDFpSUdR1Ao+BSKOYrlPPVag4XHL+Phux/AcRxqtQZCQK3aUCVcPTcNz3IdkDC4e5Tuvna6ZnWzY9N2Oro7kFLyss/cE3+P6bM6YefvzOTEHMwrC5bNDpKVfLMZm7nSrzE9gSbVWkS1LvFi7aG9BTqHQecbhJERRhhXUFK5FKl40GKkOWdBn5ceK/CdpG+ETnYeq0VJWVedwK1DoMaqIWFE5rvqgg2AkfeQnofKi0jvQ1/4c3blcjpgPQ9HB2e8/1scP7eb5bMrfPL7f2Bk1wgvuPAUls+uUAg8FnSVWbt9kOWzK3SXciyp5Ck/eisjW9fzLy/+pyN9+oeFCT0PZ//zQY8d/eHDmbGnM9bzYJl0+hzwBZzR69BZdinmnUwuAowXDkII3KbplCY/i3HHmq/1c+1h0D/8aYIzcfO2dF8hVK5CtdpIEqiVEaMExthYmJRd1cnTWjzo5Oi2SpGRoTGKbSWGdg3h53Icd8bJPHz3/bR1FKmO1QgbEWEo8QPB7IWzcFyX/i07aO/qYHRkA4O7RpCRpNhW5KWfuguAl31m2t9XLNMYPX/PnqXmr66UBNmwoHojSqoqNUKdcyAyq+/1RsRoNUr6PYAy6KNIxh4K3Slajd+Iw4GqNS3m1f2hgUwEhvYc+l7avwGyhRXCiOR+YoYlhpEkHzjJuauwx/Qe43kO+bhRXRiqz9SV2Tw3KxQiCULq+0xapclimYrMftPV5AKP17z0PAZGazz7K+/ggSu+wt899US+evJynnhyxPN+tgoW5hBRnf951jF89X77B21pjRUPlknl4m5BX7tLuZDmDWT7KIwPT9I0r2K2SnRuFgxmczidkwBQKgUMD9fSMAU3XfkHMqEI+rERqphsHbYURRLPg86uIo1GxOhIDd938XyXfCFgbKQGwPwTTuTcv/sffvCe82OvhMPYSJVatU6+EFAdq+H5HuVKhfa+2Wx+bDMnX/AsgvyvcD2Pjr5ZrH/gwQO84hbL5HFeO/SVlWjIBU6Su6CrJ2kvgS42UK1FcYO3dKU+ikutDo2EKndAqmpIga+M8qGRkFygvADVup7wMvEUhqFMhIGUqklcJLMLCFGsJEwvBajQJi/uDq29FjpcSYsWnd+gx9OLDmZStQ59ApJ7iP7OZkik2b1eSjJ5XBbLkSb3ko/TeGgTC//iJP7x+WdxxqIejq/4FEujHPdfb+U/3vhqapc8yOWffC1jO7ew/rufxA1y3Hnqa/mDFQ5ZbNhSBiseLAfNMh/68nBsn0c+SPs0JLkMZEWBIwAxXhyo1+mOWRf6+BAJRwhwVAfo1KhQIkCM1PF9NymZqj/DSWKdBWEYZarEOELEXaLTvAjXdRgZrlKvqxyHf/zBZm7777/hsT/dw3mv/Ad++7VP8NAdf2So/zkMbOsnV8jh+S5RFOEHHo7r4AcebZUyj69eS+7xjSw9ZTnVoQG2bdhCz5xenvrW6ybhf8FiOTAWedCbgxNmeQS+YLQqKeQcxmpRpieCns96/kaSOBRRGfDVulrVd+M5lQscfKPEarWmk6mVkS+lSpIeq8lkDJ3zoMWIxhHquKTqWuzhcITaqIWGrp7kOippu96IEEKHJ0HguwRx9adqLUz6QzRCFcaUz7vUamlBhNDoSK0xizjovhEyzvWwOQ+WI83LRZ63v+/5fOoDP+S+x9fx+d8+xNOWz6OrFHByfpjfb484o6fI6PaNfPhnX2BN3uPKf/gSAJd/8rWEtSonz6nwiyP8PaYcLXIlj2aseLAcMGeWYF67Qynn0FZs0fxJhxnExoamOW9BGwK6F4P542w2bTO9BGYHWceNkyeNH+6G8UPuGFVYdHgSqJAkxxHU60o4uLHh4fsuuixr35wKpY421q/egBsHa5/7uv/hgdccy+3f/ixRGDG0a5h7f3c3ubxPz7zZjAyN4nku9UhSrzVwXYfh3cMIIRgZGmX5ec/mwd/8CMdxGN41yO++8HLmn/pUFj3pssn5j7FY9oFz22BOu4PvCgJPUMipxOFCThn3WjjoikJ1CTlf5S2ZeQ+Oo/avNySgwvTyOScx4B1HMFYNqTVkknDsudAIRVJFKRUHkA9UfoMpXHQXeV19yc0UREg9kGEk4zDEtOhBqeBSrUVqsQGoVlUJ5ShSgkaXY/Y9J7m3CKHEgC7Nqu8f6X0qzaNSidrK6xCGVjxYjhwvF3kAPvWBHwLwxw276Lz8L7gmLqv66Tt/ylmej9jps3vtAyx94ZvZtCvtTaJFBG+7GoAP/eRzPLrsGVx9/DGH8VvMfOI8ig9IKd9/pM/lQLHiwbLfnFOGue1pPHSzaGiuomQSSXDIegPMR3W87v5shEJEaXgAxF2iRVpWUYcwmSEE+odc/8B7XtopGkT8Yx8lcc9+vAqpPQ9BzuMlH/4+v/+fd7Hpsc3k8j5XvXIJ9VpDVVsZq8fjqwTMWrXOw/c+jOepZneNRkgURoCH6zlUejvxfI+HfvsTtj2+CSEEjXqDNXffjeN6VjxYDgtP7oC5HS6eK5LwwpGxUAlnLysOAEbGoqRakYpekpn5PVYNqdVl3AzOYXC4wfCoWtUv5MweCqosa+Cr+dUII9pLLoMjyphvL3uMjKo+EbpvA6QVjBqkHs1M2dR43mtvha7+1CDuCO05icciiiSRlEmXeSnT0KNaPaLeiOJwJ6HERpwn5QhBFN+30pCqeFssZFy7Mmk5Alz7zF6+94tBXvSMNj736N3sDLq4ac0Onra0m/u3jST9GP7+imcxun0D63/5NcYGtlOet5Tff/CV/OjajclYb1z1CP913LLk9dDjD7HsCc9lQZ9k/dY9/31/7rF7efOiUw/Nl5wKTGLY0kxImLbVliz7RIeAJ/c5lPOCckGJhuY/HTMB2sQMeVD7ZXdoToRuhemRcIyVxuYEbLPSkg45UE2elFgQQiVFhqHE8xzq9TDxSASBi+sK2jsKlNoK1Kp1PN8FCSPDY+TyAflijupolVq1weiICmfyfQfPcwnDiCDn0dHVRnW0ysiQqvder4cEOZ/ZC3rpnNXH4w8/Skd3B14QEDYazFqyjPbeueTburj7599JGsdNpxuMnb9Tmw4BZ3YKCr5gVkWVW1WGdLafgjbATeM4K+yzlYfqjYgwNsTrDUlb0U28Ebr0qTaqR8ZCykWPkbEwGU9XMSsV3GTcWj2iVpdxCFUaQqSrKGnPgD5Wn6MpfPxYMJgLGea5JPeq2BOZyaWAcQsiGiFUjxidJA66GV167CfuHImv1fSbv1PFHrDsnYc3bGXgS3/PubefwlnnLmfJv7yKle/6Ii859zjeunCIh771EUa2buC0t3wCGYUE3fNY95MvMrrlMaq7+zn17Z/nzceclRnzX758ObMveBmfu2+I+593PgAfeHwdD/3DE/n6tRv5p4/9NR995/8eia972Jio2pJ7/hUHPXb42/+XGXs6Yz0Plj1yYZfAc2B2xSPnp16GPf3GmGLBDAFOEqUNz4MeywyDMJ9nxo0HMFcLTc+FKSAi4wSlBN9PxY5u6lStNozVQ9WTIZdXza8Gd43g+y6Dw9U0pntsmJ07htJ467hsYxRJHNfBcdUqroyipLyrH3iqQksjZNvGHYwMjqiyrY7Diz50G3f87+vZvPpBnvymb/GL/3g68447Hrh7H/93LJY9c147FH3Bwh4vMe5Hq0p5O7FF3QhlMl9VuBKZkCUT1yFpDgckOQOgxEEkVZUjPT8c0nyCYl41YdN5UbV6hB+HAkaRZHg0TCo71RuqpLIuyRoac1/fL8wEZ9cw/tOmbpKG0dvFFWk/ChmHQXnxdRBC3xeygkJ7OLRX0xFpNSndeVqfj+eJTAEHi2WyWffLr/HPz/g7Flz3az7xtZt53+veyVuPG2Plo1v58C++iF9s4/+tHaU250R2vuILnOtv5m4xjxN33k1txwY2XvAO/vJD3+W2D72clSM13rjqEU4YW8NKdxFfPXk5I5vX8qt+n1edsYC2VbcigiKPfuM9HPuiy/iHk++i+NL/x5u3rOO4V76Xvz/tYgDyPsROeMtRhBUPlgzLfMg5cGyXQznvUMo7hoG+Z7GcWcGTTQLDWP0zQ5fMla40lEkk+Q/6h1kLhnRf4lKq2R9snd+QvBZpQqc+kSiKEhGkjQzfdyiWcgghaO8ss6t/kJFhtQKhwpJUadcwDBPjRBNFkrHRGp6njKN6bbeKma6HSVUnxxHUqnXCUDWhGxwY5iuvOw4ZRTTqaiV2ZPduRnbv3uM1tlj2xCIP2j2Y3ybwXUFPu5tUNgKdbyAYHg0p5JykX4FZblQIkVm1dw1jXM9HPUfNOV8qeBnj3FwUUJ+twgX1/r6n+ioU8srjVy56DI00KORdIgnVWtiys7Seyq4kec8xPAqqBKvax3G0NwJ0MYZEYBjnqXtGtPI4tLoO5vfXHpDQ8NZYLJPFplt/xNznfhdncQ9ibicvAdZfcgE/vHcVlYLPjQ9u5PcrH+Vbp/8Fl/bfTuD34BFx2rbf0X/Cxfz713/Hvas3c8HpS2hEf0ZGkr+++kbe9+JzyLku//6g4I5H/kDHJ69l3hMdfrZxJ5VCwBNEyK77bmHOeS/g/s7TObZ7LqWB1ex6w1d4oBHxoY2P8e65i7j8K/+Kf8HreOid5/O/31zH59as5M1LVxzpyzb52LDEDFY8WBKe1SvoKrsU4mRHk+YcBY02ENKk59YlVjVaQCijJSsgdO5CIjKM5ENz3uofbEjzGswyrI4QmRVTvZJoCgYhBEHgJOFMxWKA57n4OY/BgWEajQjXdQhyHmOj9eQ76jEajYhGI0rGDkNJvV5PDAudN6HDorRhImphYlwND40l2z72vFm4nou0S5eWA+SpFUFXUTC3W3nPqrUwKbWq//4bYUQucCg4IhG2kVQ76LmswpBSgzkJUzISglPvYPr5upwrpHM6U6VJ91KJ0jmrqzU1GrrvAwyNhElYVSMMY09i2lBOi52074JMhIDOXdDN34jSIgyOo+4NtXqU3KdMz2UUJ1vrc0tFS1YR6O+RhkwJQGbGs1gOlnfPyfGRzjfCgm7cc5Yh1+/gMxs+wJ+/9ku+8F+/5EnbdvNXx1e4xXN54FOvoiQayMcW8M+LluLKkAfmPJlPXPN7Hly3nSDw+M6/f5env+O5RPWQdZt2cu0fVtNRzNE/NMb8rjZ2DI3x547TCbduZrQWsqo0D/fE+WwdrPL921fz+qdcxDH+CHMfvhn/hKdwT79aXMv/xWt599yFyXm/eekK/u6yU/niVfceqUt3aDiMk1sIsRS4BFgJrACullIO7GH/i4ArpZRnNL1/JfAI8G3gJcAaKeUNk3GOVjwcxZxWgKIHCztd8oFDPjCN/vEri9C6k7N+nrr6jSpJxrHNVQx1iIO5rZW4d5LPax2PbPaTMM/VNHzSfXU/CId83htnBI0OVxkeqmbyJ6IoSkq+1uthIpKklIRp+LZxPdT7WlClnpTsoxliUauF4zwxFsueODEHeRfmtzt4LuR9JfpHqxGFXNpdGdLOyFEkiWJjWs+59O889RqYTeE0Oq4/DRlM5109FiLaoNdIqUo161AmNaZIPs91HUbHlMgpFTxygWRgsB4fK5Mu1M2Y892P+7KY560LISgvZzxWA1yXjBdFf04aqpRdhDAf9b0NlAjTn68XOezCpOVg0dWS/u3aK/lw9eWUz1rKm55/Fv/53dupDo4RDcJfnDifL8R/kw8MOTxt+WzqEbhOiDv3WFYOhLz4oz9kZNcIp5yygEWzK6zfugvn9EVUijlOOnE+9/3pMa791u/oPn4uvZ1lfvvGs/ncvbv5wV1rec15y7n54S2M1Is8pbGKRY5L4ZyTWLT9Hqj0kav04Y0NcProBl58559599xFANz3ni9z8n+8BmDmCYfDz1VSyosBhBBrgCuBlhVVYuHQjxIZrbgy/vehyRIOYMXDUccpeTiuR8UZl/JZwQBZAQCmUMi66lsd02xQQBq+ZAoKMznRjC3W+0P6QzxRcnX6Oh1TrxJGUmbOxzw/13WSxOhCMWBstKbyGaoNiuU8jbqqOlOvqx4QY2N1tboZSur1MMmXSMMVZOLJ0JjeCHUd9QUzr2FcdjL2XihBJG2deMseOS6AZRVVCSjvCwqBiJuvqe1tRdeYu+pvKil5GovVSEIUr/Kr/VLPhF7V16ShRzKZm56jvX9R8jmJId3095uGS5niObvwkDSiiyRjcRnVWl0Z/6rcq0ieJ+WfM8Z++hmmV0DG+5oCXuUuCEwBr5OvzQZwjnENIql6yehrJOPXYTJevB82bMlyYGjRcM3y1/PPH3o5nSe6wN0Ix+Fj//YdcATnv+RcfuB9m43X3sZf/fVTed4Jfazqr/Lu627jn56lFpzf/907mdtdxvMcFizu5dSFvQDc9/Am/vbSJ7Gsr4Pf3LeOJcfOwXEcSgWfeV1tRG6OwHM5eX43O0Zq/NVJPTw+5hB4x4NweMLINkYXnM6W73yYOee/kGh0N9vu+jXnP/ckvhN/By0cZiyHaXUg9jp06ddSyjVCiJcwgXjQgmCCsPI7pJSXH4rztOJhhnNOGcqBiu+d2+klP8Z7IjW2hbFa2By/bFZAkuO26WPUaznuD1u9bBYuaUx0q1V4c7XRFA0q1CldJTSNoWQV0ai4pM9xdKSWJlY2InbuGBoXDpV2oh7//ZLQjCgVK2YYl7mv8S0TY8sUITrmem95JZajixVFaIsF/ux2lbugw3fCSP1dF3JuYribwiEMozicZ/z803/nqreBJEL9NjaLf0gXAISYoJIaqSDQDSG1mE/ej72M2rh3Yw9FvRExMhbnBenwKEdQzDuMVtOwQG3U6zKq6jum70XxvaNejxKBoas+gfYCZs9d34OaFz0y3haZbUKpr23zvSm9J7T8b7RYMmixAHDDZZ9i9nu+zGsvOJlr3v9trvziDXx40wDPuOJFXP+d25XrzXe5/e61PPnMZZQKAWcsVqLglf/5U4YGx3jz5gEajYglczv55c0P4OY8nrB8LpsGhukuF/jSW5/NQ5sH+PZtq4giyfPPPpZKIWDr7lEqxRx3DgiGxuqcOKeTFYVh1nz1QxRe+VH+7dZNXHH+Ah7/+VdZ+Pw38ecL/pEF+V3cF3axYM4S/mHu0iN1CQ8/h++3eQXKk9D08WKplHLNgQwohFghpVx50GdmYMXDDOO4QD3OLwt6yg7FnEMucDIhSOZKnabZ4Nfbm0OUmg37ZpHR3BXaJDs2TT/I8Y+9SBtCQXNitTYassLBPN58rVcm9TGpQS/xfZdaLaReT1cLR0cbmfNpNK3OmiEbzQLCFA+QXe00z6v5e2fDJw5rWKVlCnJcAA0J80uC7pKgEDgEnvIW6KpIWjjkA1WVaHg0xHEgH+fwmB4A/VqXXk3nh/YyZA1eM1dIhzo1G8TN3gWzOILpSdTN3PS81piCXjZUf4haPaIRaq+CqvpkekK8OIdIexddJy0vW62FiWAwT838rvpRz9fm+5c+d/0ohVGVSepcLLVQYo4vZXbOWyzNmEKhFRdd9XYA/vHnfw+BR3jHGrzzl/OH+x+HwCN6YCPuOcu48InHAvDqp5zId//4CO/+7xuJanXe8rLzufHedTyybhtd5Tmcc9ZSzlo2m2tueYBj53fzl2cu5cw5Zc6Z10Yx8Ag8l98+tJEzVizl/GNnc0K7w9DvruUYz2fXDXcjn/cGyvOPJbjru/zrOU8jAuY86Xnsuu8Wuk96Hv13/gpOvYTqzi2H+ModtXQBA03v9QOVAxhraRzW9Mc4/+GayRIRVjzMAM5tg86CCmWYVXGTH+tmQzQ1FPQPqHrf/M1zjH2bMd8zV9ZNQdHqUe2XehXMsfaU42DGVmshoAWN54oknts8j2YDPI1vlsnKYxRJhoZqmR/7NMSIzJjjDXrZ8n2zIpT+rvpz9fVOV3/TsCXzIxcv7WLblsHxF8QyozmnDO05VRJ5TqeXVBgyxbT+W9V9Gbo6vMR7pTo7kzRwUyvx8eCxoe0IwFiN1zkBWeGgHk3jX7+GvfRvEWmzNvMY/TyMIAojI5dCxIJBlW4tFbykSZuZj6E9DXqueJ7qPt0IZeIddByBkKkgUAa/KeglOmFaL0A0Gtnwyeb7nW4i1yqM0jxO97jQ3hWb92DR7Ek0/PLvPsmO6/4AjuCSD76Em+9dC6u3cMZTTuDOkdtZfsJ8SoWAcH4Xd4/WkJHk5z+9C3n/Bn6e93nzB1/K7ws+cxb18LTl8zhjUR833r+eV567nF89sIFLz1jCW5+8nPu3jfDN2x/mY1sHuPjkRSzra2dOR5Flve08sW0U6tsZYTadpz6ZB7/8L7QtPJ76wFZ6z3oGa777GYY3PkLbwuN593PeDMArLv0QH792Iycu/ifuX9siGekQcuoxEfeuPryfmWESJ7fI9kU6ZJ2mpZQfMT7zKuB6YNnER+w7VjxMM44LoM2Hee0O7QUnMaTNUKRmt7r5o2oa+vuyUNa8kmmOZ+zV8nNbrbw3Y4YYNB/bHCqgOspmwws8V1eTyRoAOhY5rQATr2jW00RHcz9TfIz/jtmT10abPmezE65+3QhDXEdVfYoiks61jVAmq6hS6tju2BBpRNRqIZaZi5nkXM7HHc0dszsySRlRXdZYz9VS3mF4LKKt6CYN2qJIJgnFeoqaRr/riKScsf67TTqva+9eHI6kQ46kzJZE1ftExjbifRsZb5zZtE1k9nMEeL6TeCmFUAndI2N1wlBSKrjJXHCEOjfXUfNFVUkCEIyMhsk2fV1Mw95BZoSDTspu9hDoCk3mAoS+VaSla9W9dbQaUW9I8oESPGEkaS95SsDEx4ShTCqsWY4+tFCotEkGBvf8N/DZ9Q/QfeoHARC+y3f+/bvIeogzv4s1j+/g4r95Km+58FQ+e+O9rHp8B2zdDdsHYW4nc//yLHYPjvH71Zt4zrnH0dde5Oqb7+OEed1ceOICjqkEdJ+xhH+85lYuPnkR3eU8zz19Md2lHIs68hTu/wX5JRdw4/pRBh69ie333sLYjo10nXA2P/2/6wnDG6g1Psv5T+ziuBe+lrH+zTz64y/yxJMj5szroPu404CNvPDytxF9+NNJ9+rDwbotkz+3XvvaE/nSl+7n5S+exTe+sxdPyiSGBcg9N4lr5WVo5Y3YK0KIiq7SFOdOTFqcmRUP04gLuwSz2l2KeWecZyFrz6diwawsYrroIWsEpEZ8Ooq5bzaJsnklPYvpbdiTcBgfX5w2p0qNc/V9zMZNOgbZc5zEWM+soIZaSGTr0+vcAjMUKXsOqQhIv0tWfOn3gsBldKxBGEoCX9WrHxmLEoPiG2sbfOttp/NXn76bSxe41BqSWRWPnq4chYJPqZwjl/fjECoP4QhkJFm2fBbcar0PM5G/nOfgu4JS3kn+LoHEsNfCUkplAGv0310uUMeFkQrVcV0n+fvU/RoARLyPbrZmimIhRFISWY9tpgLocwqjrOdQn4+ugGSel+mNM0ZCCNXl2WwK6Tgk3Z+HRhroPKTBETWo65Cce2aVX4IjpTEXZVKK1fzu6juShHeBEu5aiKjrLRmtRsl18Vx1DiNjETuHQ27dLjm7S3D9DrX/3xzjU2nzKJd8KpU81WqDuQt7GBup0ju3h0WnrqBRHWNgy0aCQoEvvPPHe/1bsEx/Pv+EHL+9O/vjtifhcM05/8BLb/8kt779afTf+TO6zvgo+C6ipw1v2SzChzaRz/tc/53bCTyX67/8a/6398v83bkfoL2jSKMR4joO//aKp/DL+x5jWV8Hl56xhAe27GZxV4kHNu+ibdc6SrUx/vuV59G2+T76+06mc/M9jD62jt1r72dgy2M4v/8JS8MGj25ay4YHV/HouiqbvngbS+bC3Q+r87/jzh0c/5cuQVsnQrgsPmYWiy54ETuf8S5efkmDq596HNt3HV4vwJ6u7TfkGAClV32akZ/czct2fpNvdr6Ml+38Zma/pfMiPnzKv/KSn6tOzxd99zToPI1v/grohO5LzoYvvumQfYd9ZCVGwrRmf/Md4nClK4Ez9rbvgWDFwzThGT2CuZ0egT8+PhfGVylqjsMdH8JkhhNlPXLNxrh5fLZCUioiUkN8/HM9vhAiWfGD1GjRPR+ycdFZ40E/6tV8h2wYAijRYFZGSaupZL9zFIuJpIa7JD5GJtvVd01XL4sFj91DdeoNSa2uvAgj1YhvPZb1FHzwwk51zdcOUGgr869P7WD5SQsYHhzm1tseZ8fOKsFQndyuKlEkyefdJJSk0VAN5Cwzi3kuPP+EHFKSdHc2y6Ka3gVt2Ov384GqpCSkMnhdB/I5l5HREMdJ55/umQJqDN8TiWGs5+u4EqqRWi3PeBO0V9IoAqDnvPZgpIsQ8cq7zOYbpEndMglTAiUa6g1V9lglS6tzNkMGw0gk565FiTmG4wiiUF0rEV8joT87CQXU3gcV3lQqeHS0B2zaOkq9IRmpRly7Pp23bz4lR6Ujx/pNI5x9UgevOHE+2zf3856nnMN1X/opb/3IFdTHhvnP93yCWi2kVPLZuG47o6MNqmM11UQyitixpZ98ITepfzuWqYPoenVijPZ1Svo6JXN6YNP2fVuRfuntnwTgBasv5aVLV+A86R2waYBo7XboKhOt72fLuu289NaPc03eh3ldvHHuv7NkdoVVd6/lPZc9nW/ftopHtu7ilU86nou89bz/lgf5+6edwK9Wb+Vn9z7GC5/ex6bffp/RresZ6pnLgufMZvXPv8pn3/8d3nzF8/nF//yQ0argBa95Jg/deR+/WQngMKtLcvfD6iZw8tKIF7//X7nvm//JqX/zTirHns4Dv78T+eR/4Jrjj9FXY5Kv7p7R4sBEdL0a2f+VzHvDX3tb/OwrfCN+bEbJhivUuC0+S0wkHg6TVzH2EKTno7wF32563S/30Pch5o9AUmlJCHEJcN1knaeYKnXlm2LALDGLPDimXbC418v8iJqr4ObrieJumw3odJxsqFArzJVL8xi9/0QhDiatSq9qIZGsbsYH6U6uacxy6nHQvRPM89JiwHxPeV1UWFMjjDKlF8MmI0qvYuok5zBUDeKGRxvU6pJ6KDMi4f0XVOjpbSPI+7z+f9ViwCdeOIdc3mfD+p38922D+ALMolYNCRv2MyJpL67NKYWdvxPz3FlOkoukQ4aa50dS5StKV84jCYGnKg8B7B4Ok/ClQt5leFQ1U9N/2rV6lHjuICsYdIhdI8w2ZtTJyGYYY/OcCKO0PGrzOdcbMlnQMHtK6C7Prmn4C8HQSINiwWVoJKRai5pChVLPoxDK01LMu1Rr0bgwS7Mggc47iCKoNVQYV2e7z/BoyH8/WOPvTy+weHGFf/z+pnH/N8+f7XDpi07AzwXc84fVfOn3gxQcNV/LLuxsQI+v9r2/uuf/52am4/ydKvbAVOTXbzj7gPoX/Nt3Pkq+azb/dMGrkveuOf4yXvrgVVyz7HVE/cMA/PY1G3jqg0+jMreTXVt3EW0c4Oznn8G/vuBsXvKxH/DqZzyBDzypl98PFnhicTe7V/2B3Sc/l3s27mLH0BivPKEDgMe+8W8MPf4wJ7z6Azz0jQ/z+Y/dRG9FctZpeR54eJT5sxy290csP7aN718/3PKc33L5hXQsO43e576JLXWf+fWtjBR7+ae5i3n7+57Ppz7ww3367qcfGyWiZF9pJRQOJ8bCqohfSwD3Gf920GOHv/iXzNh7OAfdJG4NcJZZblUIcS1wvZTy6vj1RcDFwLuAj8TbdPnWFcBFqJCnZZNZttWKh2nA644PMiFGpmBoNuxhfAiSGbJkegLMEox6P2hOJBSGQT6+5KO5vx6ztXgZn8NgVmjKKu3xiYlp8nRqYOh8AiepO5+GF2nDxREiIy70eOajNmCqtYgdgyE/3KzeeOPJOWb1FqjVQubM7eCt1z4OwMsXe5QL6j/k9rU17hkd/30ng+lofFiyPKtXMKfTS+aQNsQh9ThAOh/MEBzHEXguyd94rZ4mUqvwHtXXAdKuyiat8o/CiHG0uoc0h/Tp+a8XMHQSt3lv0fNY5/Rk57vqIh1GqjqUbv6mv68O49Jz2429F2ajO30eqvN0eq3qScUmybbdIT/eEmW++5PaBbcdgUjA6Th/p4o9MJW4/m9PYdVdD/HnRwS7WtvaB8yn7/wpAG8749mc+KPf8oEv/YrH/mEZp39jG57ncubyubz+qSdxyYe+S1dPG/e95XSq/ZvJLTiRsUfvJt+3kOGOhTirfsPD3/44J/zt+1n7k/9mznkvYPV1n+aEv30fI5vX8sj3v8BXv/YIb/3niwmro/zg/25haER9n8VzIpYtcLnrwYiTjxGc/VevZMkL38JjwRxcAf93xxpyrsu533o5X7vm8cm9ADEvvLjEy0beyL++6wW87/lnHZLP2FcmFA/P+n8HPXb4sysyY09nbNjSFEU3c6uU3fQHO2qOX259rCkcWoX+6PcdJC1sicw+2WNNz0fW4NcGkelJ0CufZilE0yhp9oZoA8rcL03CzI6TrmjKJJRJb0vHUo2bzHN2dBKmUCEkX35IdbN9/myHzrLL6ce18cPNuwDo6coTBC63/WkXv/hdan18Y21a0tVimYi/nOfQUXRbinxzlV89ysTrEEbgueq9Wl0Z1mFDYlYOa4Tq2F1DDRxHhfrU6mo2u66I7xnJj2Dyuc3hS/G7GW+H3r3Zo6jzMnRYo+eKjBgxwx11xTEzOTkdwwxDzN6XQr1QEKnww2otypxDGKrx8oEKgarWU6/g644PWDY3xxt6sne1IyEcLDODf+jOsaU/nUuTzdvOeHby/P7nnc+lwH1ty2gEb+aZZx7DK89dzp2PbefUE+dz6sJebq32cm57nR1OG4O3/4zy/GMpzlrE6PaNnPrur7Pp51/iwRt/zsiWdRS657Dhpm/j5grc98eHAYf//PD1vPWfL2bDNsELLy5x4++GKebglpWSShsMDUcsfsGbqO/axsL2iO13Xs9L1t6Pmy/yqe8cGuGgPQ0vOSSjTyITGVxHKdbzMAU5rQDH97p0lNxMbwJIV/g05n+faDLcTZq9Ac3jaJpzJ/S++hwmCkdqPjab+xBvj9LKRFootAqF0EZ+kqMQD+x5aclG3xPkci61OKRBG07mNTGTqVVll5BGKBkZi/jG2gZvOTXPZ+9VN67/vHQ+O7YPcdufdpH3BX/cGu13mNFkM51WJ+z8zfL82Q69HcoroEsEu8YigM5p0EJWe9S0N6LZMNfHmYnWrW7dgS/wPYfAd9ixq44jVAhPrR5RrUVJCFQypkznaxiND/8DZeCnFZzSeZsNo0wrHzULDo2af6mnIYoks3ty1OoR/bvqSZUp89ykVPkbvqdCmHburvOVh+str/mZJejICRoR3Dxw5P8cp+P8nSr2wFThVW4+mYcrjovo7HC58Q+H9hoFHqz+wP+x8L2vBCD3pZ9Qfe1zALhi3Tq2jtS49o5H+PunnUB59c0UjjmTAadEeeM97PjTb9m99s80hnfzuY//hkuf20mps4uvfu0Rzj4x4s4HneT7fHb9A2y98X8ZWH03jeFBvvWlW/jXG3/M8MZHuP//PsLXr92YfO/71ziMtZh2HSX22RujRYLoejXAuHyFqcKEnodn//tBjx3+9L2ZsaczVjxMQS5dEAsH0bxSP76cqcmePBHZ/VIxYBr5JqZnoXnc5vwHs1Sp+RmtciVM8WCOHY3zHKTPk5AGV2Rqu+sQBrOikv4cUAaPbo715YfqvGa5z5cfqvOhZ/Ywe343f/j9WspFj+/eNcwjre2RI8p0usHY+ZvygjkO3W2px0HTbPinf/u60li6b/N81J61tqLLyFiUrL5X6yr52DTYXUftt3s4xHMFbSWPweEGjpMWASgVtLBJD9ReB3Oetvp50EJHCPWdxqphUh2pESc/m/eYekOSCxx2DaUVlXxPiaOcr0KcTA9DFOlyxupzli3p4PKfbht3Hhd2CW7sn7p/dtNx/k4Ve+BI87t3PZPPffSmzHuL50SMVgXzeiUrVx2+whafvP37/MM5L8y897nH7uUL9w3xhmMd1v3ki/Q/eAcLL3oFm//wMzbeeycLzngS3/vvn3PisT6OI9i0ucopKxZy+63rmDfLYc6iWcw69Vy6TjyXf7lUhcG/88Mv52P/nKYQL+iTrN96cH/Cb7n8Qp704Z8c1BiHm4nEg/fc/zjosRs/fk9m7OmMFQ9TkMtOVG2iTdEAWSHRKvdBo1f/dC30bJJx1qhvJThaxT+bIUzawEg+zzDk1fasR8EMXWqOhdZjqVALB8chU4c+DLMixhQZ+nuZPRfUcao8Y60u2bwr5IkntTM8XKe9PaBej/jeHbvJu/D4GGzdU9zWEWY63WDs/FW8/oRgXC6DxswJag7FUfsa70VpToDOewCVRKwSjVt7IpN5JlTycCGn9tfja49HPhCUi2nUqhkuaOYYmKWTNdW6THINAt+JE7klxZyTSZoG9VnVelqwQIcp6bwNLe51crgQ0NedY3Cozu7hkK+tmb4hgtNx/k4Ve+BIcv3fnkLUaLBxzTrmLl3Izk2bWbd+mLEabB8QnHKsYPU6yWgVhkZEyxX5w8HbH3mU29Zs46+XeRCF4Pr8cCM8beB3SVO3j//uWu7vPJ1j19/E8IbV/OhDH9rvBOYD4UgnPR8ME4qH533ooMdu/OjdmbGnMzbnYQrQIWCXhFct9ZIVQUW2T4Ju5OQYIZi6VGEzbmKkp0Z7ujKvHpuN+FaiYqIE6VbvpyurwthXl1RNhYNZNUmfYxCoqjG9fWWiMGLz5qE4RCIa51UwQ7n0yqYQaYjSaDWiu8OnvT3gtHKOu+7bQbUuue7OkfEXymI5SE4rwOySKqWsew9EcYfxZu+h/tk2k6Z1wr9GymwOUXPoTyt0yFMx7zBWjZI8g1o9ylQSE0J9aK0u2T3UUD1jHGF4BEk8AVIqj4HujTJaVdWRtLfPdUjCBXO+k/SUCCMyOUiuo0u3js9l0iKpEDi0lzzqjYgP3zY0Wf81Fst+0b/+EUZ3DfDgn7dQLgna5i8l39GF6z9EZfZsfvqjh/jNSlVS+EjzqWVLALgd+H/f+wR3LXwGb7nqJxyzsJcT4n2+X1vCXxWGefMz/i5+59AIBzMkaaqGI00lYkFyyDpLHw6s52EKcE4Zjp/tU8w7LcMEdMfTiUKWWr3f7J1o7uugnme9F+kY5vNsydTmsVudr7lf1iMiki6snuckIkTXm0/2cwQjI/WkM7M2NrQBlAucxGip1iJ2DoX4rqCzzWXe3DKPrR9k7uwS7/vVzvEnN42YTqsTR/P8/etlHh1lj3pDJoa1DiXScxdSg9kMXwKyScci2+vBcUTS9FCv0DeHPukcIN3fQSVTq31KBTcRE+Y9I+enzeJqdSUSmvMNzApvWhho0aDLowKZykm6YpJ5vs1NFxuh8nyUCi67hhps2RXyi+0yCUM6t21mJDlPx/k7VeyBI8GjP/wC62/8Jie/8WOs/tZHGd68lq7jz0LKiB1/vp2hbVu4665tXPji87j+ut+xbrPDqcdG/PGBo683z3T2LOyNCT0PL/jwQY/d+ME/Z8aezljPwxFkngtz8rC8z8skMjYb/vo9XRUFWguDdN9UQJihPuP3TcN9mh0JzWNoknAE0jAHs4dCJKURsiCTbtDmymYQKO9KsegzNtaIDaQoMZbGxhpJmIYQutGVSMKYxqohYQSPb6/z4y0R7zmvjVIpIF/wufn2rdyzPeKx+2t7vPYWy8HS58CxZZLuxanIVgLCAcO7pkiN71RQuE2eB9Oz1rzNFSClyIQXJUa9hLGazPRkGKvqkKU0GVkIFXqkw/0cR3WidkRa7SjnCwp5l8Fh1QVaixN1XmocnTCtu0L7XuoS1SLIje9bugzt8cva6KgUGdw9yhXX92eu584xyWmFmSEcLNOL/vWP0HH82Wz87ffZduf1LP3Lt+IEeW694hJmr3gKD991P79ZCYHnELR3MzCovNxTWTjM6ZH73MBuf5jJwmFPiFY16I9irHg4gvQEcOo8n1zgJIZ4kjTZ9HfaWkzo5+PzCPQ+2rBIwwXM0J9seFHzqlNz4qTZgMoRgjBeSRXxOYdRKhYAfNfJCAdIjakwlIyO1qnX0467Jjq5E2Dxki7e8u31fPJFc7nnvu0Mj0WM1SWLZwW8wKkxNhbyH7/bMcFVtlgmn9MKkHdh+SyfwE8rEDUXAtBiAtI5rEuyqtfZHKQoDjfS4Yh6HzPMSc8hszqTzmvQYVJaCDSvCmRDINULVRZWva8aNKpjR8fSRGhd9UgLfGHkdDiO7qmS9Uh4rjq/MD7fnC8YGKgyOFjjo38YX6JlpY0qtBwBfveuZ9J1wjnMuuivKc9fzs4H78ArtCEcl7UPb2bL+uviTsxQa8CnP/hj+jqhfoSr8e2NyRQOR6tgsEyMDVs6grx8sUdnm5v0HoDWnZjV6/HvtxITzSJDjZktm9rcYVk/Nv8tjG/slh0z8xlGKEZzfwgzWTqKJJ7nqJXIMBpnPKlzyXpKwlDyF89/Ild86EZe8MROVdfed/jfX23f766v04np5No8GufvW0/LJ3NKh9Fpoax7j5i5Bvq57p+g55yeH80lUXWYU/N8NkUIkKzq6+fNnsLmSkxq/Ow2M4l7XJ6GkTOhxzDH1B4Is7RyvaHmdl9Pni3bRmmEki+tmoIlzQ4h03H+ThV74HCxZuNWKuEgG370eaJGHa9QRjgOpWe/lcc/+Tf8+Gu/ZsVp7QztHuH625Ra2J/ypNOdo1E0TBS25P/lRw567Pp335UZezpjPQ+HmUUePNaAVyzxqJRV+M746kYH9nflCAFNYUbNxofpQQibDA2zCZt6TSYEqRlTGOjnrcbThlMUr0qaIUrN4+n3tcGikyfrjVt5yvEF1m8cZmg0TBpDWSyHk3kueALOnedSb6iwItd1Mn/7ZkM09Zjtn6BX53WCf1olTCTjKGM+2wslk/QMuE48riMQQs0vM3Eh8UKQfna56MWhSKkA0H0XnKaEZnWM9k4Y4zoCNwl3FEnCtxZMge/Q3ZWnVArYuXOUq2wIoWUKcu9n387sF7+Tv/3eg3z2+NMpzV0GQP+ff0fb4AYe+u0tdLZJfnnzIMOxDV3MHR3C4WgUDXvDhi1lseLhMKOFQ1sxraqkPQFOxvBunYyst5mPrbcl6rnlmHoFNNlsjKVFhUp4lBkvgxYjkZS4LbwgrerDm0nXyeqlEQ6RJn5K8nkPKSUDu2rsGkrLNPbvqk/rso2WmUGXD2cuUKGG2gCv1aNEaOtmaa4gyW0wvQHm/NMhSSbaII+M/fRx48V2PIaUSCnGeQTS8dKQxbFqmIzX3IzR91IxE7VYGNP76v4LQjiZrvdCQFen6sq+afMwH7hpAIBn9Ah+sf3oWtG2TG36H1pJ74oLqT3wW776zOUMrdnGf60N+Lu+7az50ZeJGnVOe9HL+POPruFuoynhyAz2dIPqH9G5cPmRPg3LNMCKh8OI7hxdLqi1QF3zHdIV/qyBnx6bxBoLMsZAutrZbLTLjOHRSnBMFJbUbKRIKfEcZShENIsJaRhC2fPUwkAbMKaw0ImaSax1nB+xc6DK6FiI7wkWzy/x7N27WLVTWuFgmRKcPtfL5DjoMKDmKkhaRAihhLLeX4cHjfc2ZkMIk3GbXmuSe4dyrGfuJSZhlAr0MFJNE7WnIBU0ca+FxHsocFvcL1ReQ1oAQS8GOI6gUPDI5Tx27BjllgeGuX1I3e/uGcUKB8uUYsd9t3LvZ99Oz6lPpu9F72BdzaWx8pO8ZMkWdmwZ5M7bHqF9wW2s+f1vaO9s529fVeHr33iERXMiinm4d/XUTZI+EHwXPvjDz7HkDXfwzdM/ZEutToT1PGSw4uEwcUoelve4VMpuxmif6EcfsknMpuHdSjToXIbxhv14Q8U02lvlJqSfn36ePi6K0nAF83hdarV5RXOiMfX5+b5LELgMDdVYvW6YRXPyRJFkYLDB5/40MOH1tFgOJyfm4Pgex+jDov6I0wRmQYReBJAZgeA6ION50DCaHqZJ1nGCs2TcvUGTzVsQOGTzi9LQpOx8cxzllQB1f9DzM4zSsCZ9XCQBqRK2tZhX5ybG3R/0PahU8imXc0SR5PENg3zm7lGe0SNgSHLP6IFebYvl0LB943ocz6dvxQUUZy/B2fQgmz/2Bn5942Nc9Ky7OfN913DSD7/C6t/dxM9uqdPXOcZznt9FPYR1mx1qM2wN6y2XX8gVXa9j8St/aEXDXjjQcPKZik2YPgwcF8ApfS7d7alwaBYM46u0tA5nyB7T2mNhjjNeJGSTpyFbRtXcxzy+FWY4xrhGVMb30oZH88psELjU6xFDw3WKBdVg67f3DbJ5RLLKhklPq6SqmTx/Tyso4d8Z5yiZXdJbJT1HMt2WCAGjaZo5V529eBx1BaN0saB1nlGzd9EskgDZnCW9IKC7s2t0V3oVUkj8fcS4Oa0PaW8PCEPJivNP5vZf38PdDw/x060z9s9gv5mO83eq2AOHij/+x6uY/cTn4OZLrP/l19i5+k9s37CRXQNjzJnfxZxTz2bVzTdy76o6m7YLFs2WbNlx5LpIH0retfYxnvCEf7aioYmJEqZzL/34QY9dveYd5stp3STOeh4OA6fOcumKqyo5TYa1SSvh0Kp8anZ1Unkb9pYfocfNehqa31NPmo2jVuOY56ZFg9PkzR1fujKN/67XI7b3V/mX//0in3nzm3hs4yjfWDvDlnUs054LOgXdJYeuNiX8s2FK46sWmcJBd1s3RbP5ONFClln5SIc+6fuGGVKYSdJ2sl5Icz8pwWmu/RyjKjVlhYUpPszwJLVdif7BoToPPjLItsGQ9o7VrN0waoWDZcryf79/iNPv/iLiZR9luyOYtf42dq7+EwsvfAnHds5i212/YvVvrucHX/45jTAtc/rY5mmj//aZv7/iWZx3wwl8Y9EsKxz2A9Fs4BwE02lhYSKseDiEnJiDBW2CrjYX31N/eM3lTM2VSHP1UJM2cRPJaxNtMGgRoVcY3eTHfmIjxfyM9HnrykmtPltnWbtuaii1+kxtLPm+6mexa1eVUsln2ZIib37eq/nh5giLZapxWgGW9nmUix5hmDWyIWvUa5pFvCkcdIhis5eh+ZjmpOf081pPZC1gEsPfMPjNRYBWn+W6Ai9TtCDdZjarAygUPDzP4b2/3MHg5nt5zvGnccsuuP4Hm1ufsMUyRXjOrAabc0Xmbvg9jWXnsvWP1+N4HsVZC9l4y/epj+xm4ekr+MlNtx3pUz1kvPWfL+bcD/0IgPDfjvDJTENstaUsexUPQogrgUeAbwMvAdZIKW+Ity0FLgFWAiuAq6WUA3vbdrSwoE2wqNdPhANkw3dMWtkF5n6t8gxa0dx/oTlkyDy+VT8Gc9WylVdios8XIv2O5meFocTzBL6v8hrCMKK3t0h//yh/fmTQCodDjJ2/B845i4Mk2RlSobCnPCWzBKsQqafNPKaVMB+Xl2R8li6B6jnj56HrmN4H5f1r9vhN5MlsJUaahU0YqrykcjnH8HCNO+4b4Nv/eAa1sSq37JroylkmCzt/D56bVj2OKzpo37Wdzbf/lL5GHeH5BKV2aoP9DG9Zx6bVayh3lAHI+xzxMCVVqY1JOZ+Lz3W5922/4NyXnj85J2exsO+ehyvjfx/SN66Yq6SUFwMIIdbE+1y2D9tmNH0OnNQhmNXhEvjKqM7GJWeNds14o2LvSjcyVjZb7W56LEyvgv7sVoIhPXa8kJgo1Mr8PNNACQJBvR5RrTaYM7eDRiPke7/axM0DNsThMGLn737Q58AplbRnQZo3kCYrT7wIkBX4adO48QsBqVcguzBgigxXZHObQPVcMHu0NM/tVsIhfZ49v+acpOb5XSyq+9fu3WOsWjvMDzZF/OCTK/fncloOHjt/D5BVj29l+ZbbiRp1Ht/2ON2nnk91YBvl+csZXPcgW++4nsFtW/F9j2t/vBNQhroQsGRuxJoNh7+yUrNY2BfhUGmTjIwKigXJ4tmSWh0q7YIL3/7PfMq9gKuscDhomqtQHu3si3i4Q0p5efOb8cpGl34tpVwjhHgJcNmetk3COU95lpVUuEM+SIVD82OrPgzqNUkpxXTf1onLWeHRvM00GtL3J/IqmCKiVe5DWj3JHGv8jVWfqx+oGPHREZX5HIaSP9y5iUe3N+yK5eHFzt/95NgyLJvl47qpQZ02cpNG48Q9j2NWWwqjdD6aydMmzcLBvE/oe4Kecp7bLBLS5oqt5njz/G0dlugk8zdf8HFdh7HRGsPDdcJQcutG25jxCGDn7wGy/oavU4giBrc8xu7HHqA+spvHf30tc897Ptvv+Q3XfeVmFsySFAsOhYKH70I9/hOXkiMiHHwXigVJPq9eDwyK5P18DnxPUshBI4RqLCq62iVd7eq+MqsvR7mjzHEvfC19z7qMVZ/6O676yAcO+/eYidhqS1n2OedBCLFCSmkuOa0A+lvst3RP26SUaw7kRKcTs9sc8oFjCITxxv1EVS2klESRaHpv4lAlp8kgaF7VbI59buVJMEWDaYCYBocQAtEiHMLs5aBPVFdeqlXrdHSW2LB+J1+9bTcbrO1xxLDzd99Z0Onie+NDfdLO0TLpEq3JLgZkJ2sYZaswpWFNaSdps4qSGq9VWCF4cQlVPU6zOHBdMW4u67FaCQiz+7UOuXI9VdxhdKTGfasG2Lo75Pod1lN4JLHzd/+4bfVGju1byI57bmZk6zrC6gjFvoUMPb6aNT/5Kt/5/uOMVAVb+vWcOzLFOprDBE9aGpHPwdCIEghzuyVdFYHvCTo6SwzuGqGrr0L/1oFkEQIE85fNJ2zUaZuzkHlPfhEfHVvBVXMX0PORnx+R72WZ+eyLeFgqhLgI+GMcf3lNfBPrAgaa9u0HKnvZliCEeD/wvv085ynNmSWY1elPaAiYP9QmrRKix3kNhMiUXDTrr6f7TjSO+TprVGjx4LpObHzEj66D4zhq34xB4oAWD5Gk0QiRkYz3F1TH6qj2VvDNnz7GmiGscDhy2Pm7j/Q5cN5sh54OP5mrrQocNML0PUj7qSjM99I5Z1ZhUscq4eA4omWPhmZvZXMuU9IfwpiXrpvOYfXoIJx0zjbPY1CrlVEYEYYRnu/i+x6jI1XaO8vcde+jfP1RWwHtCGPn736y/J/+h6tfdyH0LGb3o5+j/6F7KM9dRNDejVco8bVrHmfRbEnOlzy0Xs2+Yu7IdI8u5qC9LOmtqFCjYkEwZ16F9r4+HM/HK5RwPI+o0SAoV/AKJYTnM6+mTtYrtVPt34JwHLpOfhKN81/NMQv6uOrwf5UZjw1byrJX8SCl/Ih+LoS4CrgeWDYZHx7XuH1/PPa0Xtpa5MHpvQ5zunw8N/tHtjd3V3OcNIwv6wgQMbFwmGgcMwQp27wNQwwow8Pz3EQ0uK6TiAfXc3BdN3lfOOp908ASQhCFIcODI+QLAffes5FHt9RsiNIRxs7ffWOZD6f1qfkLZn+EbIUkKWWSc5AKgdSTYGIKCF3OuBl9XLOXwWmay2b4kin+9fz1PCf+1zSH4/mrXruZBYFkcCmTMoT1ao21a7bz4Kod/M/qGVjcfpph5+/+85sX9zDSFjD24K8Y27mFqFGncuwKVn7tPxkcrPHyF8/m3rs2cd+aNCzpSAiHjhLkAsmcbsnpTzqBoK1C0N6FbDRwcwW8UjturpjMTeG4uLkCjucjnLjnTJCj+6RzKc5ewo9G5vCaBX2H/4scJVjxkGVfqi1VdJWGOHZyabxp3EoG6YrHnrbNSI6vCGZVvEQ4aGMj/X1OwxlMD4Tepg0Qvb0VZg32PdEqIRpIVx+bPA6J0eHFxka8Yul5sWDwXLWS6XnquefiuG7sgRDkCgUatRpDu3YzPDjG5s1DfO5PR+BubBmHnb/7xqmx8G/ORdLhRNrbAODuYX5qmoVCa69CNjQqmZMtPYrxZyedn1PR7/tuIh6Eo0WDiOeqE8/jeA77nprH8SKAEIJ8qQRAUCiw+u4/87+3D1pP4RTBzt99xz3x7Wz86jOJamPs+uYVBO09jO3cTt9p5/Hg977EnffVaITQO2uEObN8Ht/WSHIKjgTL5kcce1wvvSecjl+uQBTildpxXB/h+Tiej5sr4uaVgHD8PG6QV8+DPMJxEY5L4Zgz+dQft/HBF55wxL6L5ehjj+IhdpdeCZzRYrN2nWaIb3BMtO3ATnPqM7vikQtaJRCPNxCiFpmW2TCmbK5EujqptuqeDq3G0B6GVgLCFAw6TMmLVyW9WCAgSASE66XeBtfz8HwPL/Dj5z5+Lofr+0RhyMjgINs39fOdm7Zw2+BBXEjLpGHn776xogiVkmv0NciWVm3u72AKiYlyl7IhTa0NlPTYbM+XSEpcYYYlZXOVdF6D6W1IvILx/HVcB893Yw+iEvye7+EHPq7vJ/PXz+VACPKlNk6/5H38x/ITrHCYItj5u39sueEdPDzi0nPn19lw2y9YfNFL2L11Kz/54bfo65QsngO7h+GW3+9mx25Bb+XQnk/gQbkoiSQcM1/SaMDIGMyb5dDV28GcU88k3z0HN1dMjpGhKiPrlzpwghyur0SCE+Rw8yW8fFE9lis4hXaG8t28+/oHuOqvn3Zov4xlUpvExZ6+Gd1h+o9AUulBCHEJcB1kblJ621JULeo9bptpnFaAk2Z5tBXdcduUQZDGR6vkxPHVlfS+6XvpKqQpHJzMNc16FbKfa8RaRxLXzQoJHRft+2kYgw5TglhcaPHgCBzXTYSD5yvjI18q4bgu9WqVwf5+bvjpvVx1f+2ArqHlkGHn7144pwwnzvEpFdxE1O+pilJzM7Wst2Hi49LcBTMUKjsvNa4pYoz5myZFK9Hg+9pbKJIQpUT8x6JCeyI8X4l/1/fxg4B8uYwX5KiPjRKFId/+vxs5/43f3M+rZznE2Pm7j+x89H7u/dBfM+vMC/n9/32evoXz2fLHG1l0/tO59Y5v8+dHHV749Db6/7wL34dyAbbuPLReh1oD+ncLAg+27IAFs6G702HxKSdQmrWA9qWnJPsqL4L6/Y0adfxSB16xDeE4NEaGiBp13EipescLEO2z+PnGBi87exZX/fWsQ/o9LIrJDFua8R2mpZQDQoh+IcS7UC7PZVLKS41dLo23rQHOklJeto/bZgxLOx0629zEANDVS1rlHejtJs0hTJrmqi0ThSqZn2UaI9l47DQsKhEicchRIkDMeGsjVEkkiZYqxMELAortHURRyOjgIFsee5xf3bTWJlZOQez83Ttz2x1KBTeuEJb1JJjeh8QLIQ0PQdxroVlQ6EUD0/vgOoJIjhcOGu01bO1RTHMmtBfCrKqk/+kiBq6bhirpues4ai77QUCp0qm+X9jg7ltW8r3fbLXewimInb/7zq925jj5qX/JrofvZvbSxezeupWx0THylR6OXSjorUQEuYB6Q7Bpu6CnQzK4D32UJoNaAzZuF8zpiah0txO0dZDvmYvj+cgoSjwMYX0M11c1Wp0gj1dsI2rU8YplnECFLPnt3Xhdc7ljl8vLzl5yWM7fYmmFmMjtfriZbglbHQKe2K06SAe+kzEiWoUqNZd1nLjMY/pes5fMLMuq98m+TmOhzdetYqSTykpuNs9BhysFORWepMSE8jzky2VyhQKO69Ko1fjjTXdyxfXjKgJaJonptDox3eavbgS3uNejkHOT+dt8P4xkVqA35yppzMRo9TotyapfQ7Yz9fj5G3eIFqanIfvoeQ5BoOdvOoe150E4As93CXIBrqd6rTiugx/4FMplcsUiQaFIob2T3//457ztOxsm4WpaWjEd5+9UsQf2lTXf/zy7n/Bi2n1BeeM9bLj5WoY3rGHLg3/CzwWsXrWFex5yWDI3YnhMMDQi2DV8eM8x76veDcsXSpadMJ/2eYso9i0k6OhBOA4yiij0zEM4LlFYw82VcDxf5UEAUaOmKkUV2wm7F/LxW9dz5YvPPbxf4ijCsMdE/FoC9F72hYMee9tVb8iMPZ3Z5z4PlizLCirPQXeQbk6OnsjbsKdESvO1aUSYwmTi49LnzbHUJml1pOxrc8xkNVOXdXRdvCDADwIa9TrbH32Mxx7Zwr/cYIWDZXqysABL+nxyvpqfYZQ17JtpDk8yPXsmpnB3DI9eeqyZC9HKA5E9JlvgIA1nys7f1uejxYSr529eJVtuW/cYo8MPWuFgmfbUdm2j888/ZuvKX9HvOIxt30R1dz+5Yp6H7t/Etp2CegjrNjtUG2qeuA7kAxgeO/Tn19cp8T1YMEvS2Zkj316hMTpMFDZojA7iFdqQUUhjdDCuplRENurI2FMovAA3X8QrV1hfWsLpc2Zx5YvnH/oTt4zDVlvKYsXDAbKo4lAuZDtIt2J8jsP4sCX1ftbb0OxlMP9w0zAl/Th+m1mS1awFnwmTMsQCcTiTcFLjBsD1PIptZRCCeq3Glsc2cM2PHrFNoyzTmnntDjnfDAtMt+2tc3QaQiQy8xdU5+fxYny8+Nfd2XUYoVlJzfQ26HHMztGmd8McI5nDSaiimr+l9rakyMHQzp185Wsr+elWO38t05v1m1QZ1g2/+S6OH1CctYiB1ffy+18/gOfBui2CQg4qbTJTVUk1eGw95mT2exACqjVBMR9RyDvki3nGdg/gOA5B+w68gqpyJhyXxugQfqkjPdZxCWtj5MudeD3z+dV2lxefaHMbLFMHKx72k2W+KuvY3AjOpClZDdhz1RW1n3p0m9St2Y3W3NcMR2p+Xx+n32sWD6bASJKlHfNfOmaukEdKSX1sjB2bt3PtTx61wsEybTkugJN6HXo7vLTj834uKJnFDHQCtJ5Tge8QSUmjEZd6NeZhenxWKOgxzW3Nwt91zf4sxmJD89w1XgMUSkUc1+W4pzyf3uMu4OWnP8EKB8u0Z+WVryHfM5fBdQ9S6J1HdWAbYXUEv9ROrQFrNjjMnxXhubBpu4PvQj1UXocwgiCQjFRF8r7mTf/2SupDA3z6gz8+4HOL647Q1yVpK0h6OgWLTlCtOWojQ+A4RPUqYXUUUELBL3cS1sbwCm24+SJ+uUJQ6SWatZzOOXN58cIDPh3LJGE9D1mseNhPlrYLeju8ZIXRTEROVzPSPAfzMRvuMH71o3m7aVBkH1s3iGt+T69WNjeGM8MgPN9NO9C6aXK0nwvIl4qEjQYjg0Pc+MsHuOfxOn88zPGiFstksrhd0NPuxY3e1HsRqYBoznHQJGFIBlHT2I6Aai0cN2+T7Y657/heDqbAV/vvaf4qL6Hvu0mukin+/ZxPsa2cFDr43Dvew87ddX68pfmsLZbpR+cJZ7Pu+q8ztGUDrudR6J5FzylPZujxh1n9uENPh6R/t6DSJnEdKKo8ZHxPcvwSuOtBQd4nuQdoPvau/zug8+kowaI5Ee1lQankk8v5DO4epaOzTEdfH47n4Xi+qqRULNMYHaYxvBu/2I4T5EGGgENYH8Mvd5Drms3O7uM4do5t+maZmljxsB+cWYI5FTfJc8gmRrc+ZqIwJdMD0Hz8eGGgH1sJgPGCQT+OX7FMDRHVNTrbSVrv4wc+fqAqQYwNj3Dzrx7iS6tst1nL9OacMvS0ufhe1riXUgmBtPyqSjxonn/NNFdiUvuaHoTxXaObFwWy83V8uKHpNdT7paVZRdLMUcQLAKoimk+QzwHg+T43//QPfOLOkYO7eBbLFGHDTddSmruMTfffR++SJWx+5BEW9M7h0Z9+hdtuWgU4bN8lOPvEiN3D0FGWDA4LinnYOSi4/U9Zb4OJ9kzsK76rFhxygaS9LFhy3IK4A7RD37ICtaHdOJ6HG+QIyhW8QolcpRchHKKwDo6L4ykzzM0XcXPK67C18zhOnGeFw1TCncQ+DzMBKx72kT4HFlZUWceJGB+C0BxSNLHI0OFKE4UiNYuD5rCGZjGxx1VLo69DUqnFVd9L93OIIkltbITf3vwwVz9g+zdYpjd9Dizr8WgvuS1zGpq7Q4/zGhieCTB7MWQbMppjpM+zuQz6PXOeThSqZM5fSLvE6z4Onu74Hu/nBT65Qh7X81j9p0f4px9vPfCLZrFMMR776ZdY+7OvMrZzO3NPPpVC73wef/Ahfvmd2xgaEXS1q/3yPjy0XiS5DnkfhkaVMAhRIiHnq/yGwIvfj/YuHEp51fht+4ASI4tmRyxaWGDb1lF6Z3UgHId8Zw+un8OJBYOUIV6+TFSvErR34RfbEZ6XNIdz/DxOkCPX0UuhbwFruk7l3AVWOEw1bNhSFise9oF5LpzWrcIdzJyEVp6DZqOhlVjQxkQY14l3WhgfrWgtKsYbHnpVMkmyNPbT4Q2quVQqHFxXhSrp2vC1sSo3/HIVX3nYehws0xs9f3WBg2ZMD4QOT4qMfAYTJzPns70cYIJwJcP4l1KFLzWHKJlCQosGs49DIjCcJo+hnuuuS66Qw/M9csUiD65cxTd+ve1gLpvFMuXYteZP5Ltm4ZfaqQ/vZudDd9M3fzbzlpf42Y8eZHhUcOoxyuOwY5ea713tKoTJJIygWleiYmw/fuKGx0BKJRwqZUngQxRGLDmml66ly/GL7eA4FLrnMrZzC1Gtipcv4xVKhJ6H6+eIwjoOIN06bl4JCL9UoTT/WO7yl/L0Y+ZO1uWyTFHEUdBh2gL0BNDbnpZlNTEbrymhkK20op6n+5o0J0ebiCYjRRkmaZUXvU/zaqcpGpIcBtMA0fkNjurnoGOi/VyAnwuoV2s89tAm1qzdZYWDZUYwK6fmr2rC1loQmCuO5vY9LTZlPQ4Tew4jKXGayibruZvNecjmOehFAIz5m87rdAFAOA65Qo5CuYQQgkfvX8PlP7XCwTKzuPmtT6Y8dylursCuRx9ARhH5ji4GHl/L7beuY7Qq6KtI1m1RE61eh3m9kuoEjnM955uTpici8FTDN99TfRvm9EhGxiBfzOP6HlGjQRQ2cJyAKKzjlyu4uQIyinBzBYL27jhMyQfAzRVUfkNHL6WFx/NfazyueK7NjJ6q2A7TWWwQ115YUYTje13KBaelZ8B8zzTUoXVCdGsDYrxYaBVG0VzFyQyPag5TSl87qSfCbc5zUNuDfKBClcKQh+5bx1dv2MoX/jxJ9eosliPIKXk4vs+jXHCSKijNvwFhZFZAym7bU9nW5nkLzX1TxhdAaA5t1M+zIUxa4IuMp8FMilavXRxXlYDMl4r0LlrCwLZ+rv7Jxv29TBbLlKfn1CcjZUTfmU+n7wlPQUYhbq7Aw6u28YQn9FIpS8550kJmd6lJ116W7B5W5Vrzfusxw2jfhIMQkAvU49AoHLtQdYwPfBVK6AU5XD9HvnMW+a7ZqnO05+MVygTlCm6uSFivIsM6jucRtHXilzvId8+lvPRUPvTniCuee+YkXi3LZOM6zkH/m0lYz8Me6BDQWxRUym7mx94kKxCyYQytkp6bQ5RUGENT/wXGGyV7wlyxNJMr9bbU25Bt/oYQ+IGH53tEYcTqPz/G1TfvZMM+3EwtlqlOh4C5ZUEx72TKspqCIE2Sjt8w5t04D4WT7RidFQb7fl7NFdiy87e5xwOJ8B/vQRTk8nFVtHqd23/2K67+2WZW2RQlywziO8+exTHPfClrrr+WhU96OjsfvIParh0E5Xbu/fUt9PYEDOzYxdZ+h/4t2xitCtoK6titO8F1VWjSiuMiVq46MANOl2X2HJWAvW6TpKcCS5Z20rVwEUF7V9KvQdSrBOUKYb2KX+pIvA9eoYwM67i5Il6pA79cobzoJN7y6218/fUXT94Fs1gOA1Y87IFdEvraXTx378IhFQPS2JZWbTHLP5qrjxOFNJn7mftOFCs9zgBJKiiND1nSY/mBj+t5SAkP3vMon7tpJ1ttJUfLDEHPX9eZuBRrc95CGGXnup5zUkqiSI4T5uox20W++fjsWOkxrT0O5nzNzmFXC4h4HuuqSsO7BnFch3f8YPPBXzSLZYqxe2AI4Th0LVxKbXc/2/50Gx2LjmOkfxtbd0iqm1V47UhVcP1vqyyeI9m0w8ERqunb/F7VJO5AhUNyHiPQW5HsjEvAzppVoK2nh8bYKF6hiowi/GIbXqFEY3Qorp5USMKUlLgYVH0cim2U5h9L57Gn8/VjD/oSWQ4DNmE6ixUPE7DIgxV9DuXi+OpKrTrIZrenz5sFQzPZcKXWAqO5wpK5b1ZQpEZHWlnJNFLSBnAqOdohbDRYs2oj191qhYNl5rDMhzPnuJQKbsu516pLtHY7NM/vMJI4iYjIzk31mG7TNHeKb1VWWe3XOuQQY1HAnMNaOAQ5JRzCRsi133uAH262k9cy81j97U9w9t++BeH6FHrnEVZHmfPEZ7Lqx1/nrj8N8bQLl/Hwn9YwsFuydJ6apw+tV5NPJ0Pft0a91osI+xKm1AopYbQqWDA7oqsdfN9Lqis5fg7H9cFxVdO3tk6Eo2wH4bhEjTrC8/Hbugjaumhbdjrvu2OQz5w4KZfJchjYU47qZCOEWApcAqwEVgBXSykH9rD/RcCVUsozDmac/cGKhwlYWILupupKZjzzROjNzSuUTgsLpjm0Se+bPs82kGp+zOY3mMmVqqqSyLyfnp8feLieS9gIeeDe9Xzo1sH9v0AWyxRmdgFK+TRPKWoKT5qoR0vqJYw9eHv0EspMyGHzFJ9IODSXaG3lOXSNnKTme4QfeASFPNs3bad/+5AVDpYZS3VgC4PrHyKq1xjevI5C1yyq/Zsptpfp7hjkgbse4c4HHRwh6OmUPPX8Prb0b2NwRJVU9euCwbjFSU9FsmtQZMSDGX7YTBBbR7WGemwrQiEnVehSh0/3wkX4pTa8fBkpI3Jds5Jj3VyRqF7FDVQZVifI4fh58l2zKc5THofPWI+DZWKuklJeDCCEWANcCVzWasdYOPSjxMEBj7O/WPHQghVFWNrrk/PTlcWJSrGaTBQO0Uxz3LRpWDTXjR+fWElGNHiek2kYpau06K6zSWK1hLARxsLBQ0aSRx7cyI9XWuFgmVmc2wbLelV1tPHd31t7AfXCQOvwQZHs0zyG6QHUOBPO2Wxukpq7aVUlc96a4j8RQFFE4Ks+Dsed+1SuesOn+fXOPS9mWCzTmXW/+g7bN26ho7vCji39zF44SlmGFLt66e3ZAcC5p9bpH5Dcv9bhmh9sQ0rlddg9LJg/K2JwRHketvS3WsBr/bm6shKoub1kbkR7US1CHHd8Nx1z5lGctYCg3BnnNrTjl9pVYnStihvk8IplHM/HzZVwPB+/XCHft0B5HKxwmHYcroTn2FvQpV9LKdcIIV7CBEa/lPKG+LiDGmd/seKhiUUeLKo4FHKOYdC33tcUAeZjKyIpm4wKMuM3HztRqIMZJ91KOOhqLE7TH7qUEicuNyOl5JEHN/CpmwfYZW0Pywxingt9ZYd8kK2OZs7jvTgPx92EJwpT1LkOUmovhSAyKi01l2E1564SCOOFQyIudFGD5BzA9Rz8wCcMQ1bf8Vse2m0nr2Vmcs9n/p6wOkIURRx/0XMY2bYBAOE49K95iOroGFEkWb+xzuZ+wcCg/m1Tx4/FZVof33JgBp8jlIDwvbgDfaRCEZct7aRzwSJKc5cRlCsQhyg5cdM3N1/EK7ThBHmi2pg6pyjEL/eS75nHZ1e7fOblTzzo62M5/BzGnIcVKE9CBiHEUinlmiMwTktmVu2oSaA3B7M6/aSsI2hvgHpuGgPp9vQfZMMP9H5mlSWzy6x+NA2UiUIdNOMaSTWVZRWZkCmRCAc/TrBcdd96vnKLFQ6WmcesHPS0u8kcc5L5p+aZ62TnrzL+pRFCKJJ9WjFe5GffMDtJO07W06CPby6tbHoldDlWEy0cCsU8L3z/t2jv6uTSj/3RVkWzzFi2rvw1Yzs20XPCCoTnk++aRbl3Fl3LTyff1s7WLUNEYcRYLQ0vqrRJutolfZ3qh23DNpF4D/YFfV8o5lTIU6VN0tsZsXxhRHtJCYhcMY+bK0AU0hgdIhwdIqyOgHARnk84NkIU1olqYzRGB5EyxC9XyHXN5mdDPbzv+WcdgqtlmWF0AQNN7/UDlSM0Tkus56GJee3j+zmYiZKtvAQabbC0CmUwPQ/NoUn6M5qfN5ddHR8nbQqM+PimnAkgCVXKFXI89vAGvvuH3Ty2HzdVi2W6ML/daVkdTec8NOc+mCThQUZFJrPEa6v9tcchfT0+T0mTrahkzlsR5yoZ9wcExOP4gU+Q87nwsn9htH8tV1312wO6NhbLdGH+U/+SofWrCKujVId3q4Rkz2PHgyvp37KN7TsljSikWhdUa2reVMqSwEsTpveFrnZJLoBN29VvfE+HZPFcydAI5AOo1eHxraq60tw+h+rIGLXBXcgoIihXcPwcbhTil9ppDKv3o8GdOJ6vmjd2ziJo7+IefzGvfOKCQ3W5LIeByUyYFqrDtGZadpq24sHgxBx0FJ2kFryD7uzc7CVoTmweP9aeYqxbxKYlz1uXgkwftYAY/3mSKAKISHs5OHi+h58LcF2H0eFRHn1sN/fb/m+WGci5bdDZ1JOluTQrNL/eexy0rrSUHGHO13FzufV8T4SGk/UkJnkWEYREcQhU7JEQDp7vx92ji3z7397BP3xv0z5fD4tluvE3Xp6/fd2pdJ/8JOac/0K23nkDo1vWcc8vr6dSKTA8NMaDj0YsX+TQM7uTX/56J0OjyvuwdtP+B1JEEnYPpRN215BgwzboLKvu0ZGEub2S3i6XKJJEUcTowA5kFBJWRwFwXJ+xHZvwSu24uQJurkBjNKLQM49cpZfNc87kwkWzJjoFyzRhMnMe9tJhupV3oJUXYW9M1jgtseIhZpEHT5jrUcyr8mrNBkPrMqoTj5dZcWyx40RGhvlokoY0ZFcowxBcVEBmRthICMOIQKjKLbVqnZtvfpT/WV3fy5WwWKYf81xY1OWS87N5SuZj8wKAieuobrOtMPs4ZMOPsh7FieZvNiRJJONFkSoZq0IQHVyRxlZHEQihqjkVykUeuncN192y4yCvksUytXndW8+l9/Sn0f/AH8h19rH6+u8xOlLF99ScyhcDTj0+4o57a0QP9bNrWFDMwQXn5vjJTfu/KjYyKigXJWEo8H3o7Yw4dnHAhk01RkcEne2SpUvaGB2pUm4vsW3LLnK7R+gFhnbuZmBglFLJJ5cP6DvmWPxiO1FYx8uXKfYtwDv2HE6fY4WDZb9YiZHorDmAPIXJGqclVjzELC4LSvnxScbNSdNpkqR+nR1nX4SF3j5RVSXI5kWYsdGum02kND8vkx8hIMj5OK7L2MgYt976mBUOlhnL8nZBMee0FA4m2quotqfhg1GL+awdfM2V0/YWrtT8XvP8VdsF48IXhciENuUKAXOXLeaZ772+5YKCxTLT8MsVaoM7yXX0sO3OX/HQw4OUi6o0qp8LyLkOURjRXq6yZoNDKa/E9h/vHaOVF7EVgadyGnYNCQo5Nc87OySdZUl7GbZsrTFShd5O5X2o1xs4jsDPBSxYNpfhgV0M7dxNGEVs3RHRPlZl9uzYlHIcCMErlOg942K658w/dBfLclg5XH0e4qpIyeu4atK3m173761fw97GOViseECVZl3c4+F7IjEiNGrFURj5DGk1FfV6fHzzRF6HVnHQ2rhI9jdyGfTr5lVLMxdCCLJN4WKjpFDMIwTUa3V+d+t6KxwsM5YVRZhbcfE90dLIVoZ++jr1QmT3dVt4pcfPV/WiuYeD/pyJejpk568eR4uLtKSyHr9QyuMHPit/cxfPfO9BXByLZZrwgxfMY8GTnsHg2vvxyxXGBrbxxAtOAOCPtzwADFEoBNy3aphKWfVdaC9JNmwTjIyJlt5D31VN4czSq7WGOrbeUCVYdw4KGiF4HmwfgEobtBch8KG3J8B1HPKFPI7r4AU58qUiYaNBFEb0dVepVAr4uYDG2Cj5zlkUuufSe8aFdJ/8pMN6/SyHlsNVqjXmUiHEu4A1wFlSSrO86pXA9cDVAHGfB93L4Urgel2+dS/jHBRWPAArR+DcQvqHYYYFqdfjm8OlRsr4VUnIrkpmjyNjVGgvhrlCqcdvXrU0K7c0r1SahofjOkgp8QOfm25ezdfW2Oxoy8xl5QicVXAS4azm1fj9WnkXtKfCaRIIptcxm5OUHjfeG9GcDN16/ur9dQ8Hc/FASonve3T2dbH18a18+dc7eK/1OliOAmaffi4jW9aR75nDwOp7iRoNCt19DG/ZwLHHdjKwYzf9/SPM7hZs2ErcCE6J/o6ypH/3+HlSD9Vcq7RJcr7ab9eQEgv1OuwegbEalAqSWh08V/3raHMJch4d3RVc32dsaJh6tUZQLFOv1vB8j6BQYE78CBDWajRGh+k88RyWfGYdjYsO9xW0zBTi0KKPxC+va9p2adPrG4AbgMv3Z5yDxYoH4K+XZS9Dc3yzeq91srRGGxWtPA36udov+7p5hbJ55XJC48NxMmLCxA888sU8/VsHuHeTFQ6Wmc1LF7rj5ipk52mzR9Hc3uxZyM7brOfBNcS9Ptacv0mJ2BZdo819hYhDEJtylYQQPP8dH2DB2a/m8y9bxCPWYWg5CvjOs2fRd9yJ5Dtn4eYKyCii85hTCKujyGg9Q7uHmb1oDn6+wI2/WJ00fKvH88MUDrO6JI6jKiiBWhgYHhXsHoJcIOnukJRLApD0dUKtLAn89LfZ8wRBzqPcoYRCvVrDicOlBrdvT4RDec4ColqNKKzTGBslaKvQvvRkjnvFe2i84rBePsth4HCFLU0XjnrxcHG3oK3oJq+dJqPeXMFs7jI9blWyydDQRoPGXJk038saGeNfm94FRNM+cV14LXh0d9qtG7bz41u2cs/o5Fwni2WqUm7hNdTsqSSrpnnOm89NT6Kecwc2f/V7TiognLTJo56/hVKeBWe/GoA3f2vdgV8Ui2Wa8HKR523/+lzqgwP4bZ2MbFlHoWsWu9Y+wMrfPoDnwTHHzeLPdz/O4sVt7B4WSXjS9l2qjOrAYDopt/QLfFd1mXZd5VXo6ZCM1aGYh+5Ol239IcsXqWqEu3bVKRVdeuf2IKOIXKmEG+SS8UZ3DZBva6c2MoRwXLwgR1BuA8Bvq+D4AfWhAdxckf6L33lYr53l8GHFQ5ajWjycVoA5FSUcWlVIaWbf3xsvLsxVzubt5mrkeG9Damw4rvE8Fg6uIR5UqJLH7oFhfvibrdw8YLvAWWYufQ6c1inw3D13ajcFhOuM90KY1ZSgqVjBOE/E3uevFgTNIUyua+QmxcLBdZ0kzFAIgeu5vO0JRT5zt1X9lqODi891CaujjPZvYWxgG+0Lj2N0cIDhHds5/qRZrF29hd/dupXBUcGSpQ6VNsmu4XSih2H63HWUQHDdWFDUYU6PxPMgqkJ7WTA6FuEI2DEQARHloiCKJGGjQb5UotDZm56c4yBVDXSKXb2EtSpevoDj54gaDfxyQK7SS67Sy+xzns2c42yCtOXo4KgWD8d2u3SUPRqhxIlzF1pVVjFDCsz3W9EsFvTzVvHR2XClrJGh/qVLn81hTY7jJP+EI/B9H89zCcOItWsHrHCwzHgumO/S1e4RhrKlcNCVlVLvQfaxFeoeoMIQHZHNUdDb9zR/ze7vWizo4x0n9Rw2d4f3A5+Onk52bd9phYPlqGL+8qXsXvcwXctPpzh7ETv+dCvVwQE65i3g/tvuorungOOMMTIqGdgxSFtRJqvAYaRyHzT69eI5ktldkq4OQaMBpaJDFEV0dRUZHa1RyEd4vkt7p/IgOI6Dl8vh5Qt4pTaielWFTNXrFHvm0BgbQrg+fin2OBTbcfwcwvNxXJ+OY05nzvkvPNyXznIYmcyEaaGaxE3L5nCao1Y8vGCOw6xOjyhqrt9uGvk6fnl8zsN4Q6W56ko2pEGPN361cvy+iQGSMT6M/AZjfwDP9yiUCkRRxP33Psqn77LGh2Vm86K5DpWyatzUaj5qtJGhPQuRzIYp6W2Z6mUiFQ7m2HsSDmaIkhYObuwp1ANoT2L6OeoYz/do62xn1/ad/OSXk1KC22KZFvzP+WVOevaLKM87hvrwbnat+RO14d1sWbuO9s52Fh07j9roKPlCnkdW7+TPj0i27hxvxJ28NOK+Ner9Yg7qDcH8WdDWFjA4WANgzixV7rVn0ULqI8ME5XaCtg6iRgPXzxGFddXkzc/huH7icdB9GwCC9i6isI5w4n5Qrkd54fEsfu7fHY7LZTmCTGbY0l6axE0LjkrxcFwAPe0ujqPclfGCYCbRslXpVdOw0O+1OqaVcBhfpjFrQOh9E6Mj8Syo1Um1f3MZVxXuEIWqq/SOzf18+LahQ379LJYjyXEB9HZ4eK6KfTbnoullMPOW9JxzjflpFkZoFaqkX08s+lt7HZKyrC29Dw4kY6f3hks/fifve1qF726YoFOdxTLD+PnLl3Pi059LWB1l/a+vY8f6x5l/2hns3roVgPY586iPDHPnHx7HEarEqu+pykld7ZKNWx3G4oTpRQsLdFWqrNsU0dUO+ZxgaFjS1eVRKqnFgVw+wM8FOJ5PvtJFUK4osVAoq5wFUcBvq6jO0Y160i06HB1OnrsFJSJko47wfEpzlzJy5kuO1CW0WI4YR6V46CuA7znxqqXpcUiNCdN4cJLV/vFx1aLJEDBXIfdmeDSLi6QevOsYIiI1bNR+TuJ5kFISBD65Yp6hXUP85vebD+2Fs1imALOLgnpDZpKXHQER2c7wqVBvHcJneh70/s0eh1bztfk5kAgHz3MzwiERD4bgN+8fuXxA38J5AHzgpgE+OJELxWKZYeTaK4zt3MLQpvW4QY627k6GNq/DzwUsPu5E2hYeT31wJ3MeeISVD8CuYZjXK6nXBdt2CnIBFAuSsapg06ZRoggqZehoc2hrL9DfP8Lw0BgAsxfNIRcnOXuFEl6hjJcvqUU61yPX0YPf1klUr+K4PvWR3Xiej+N6+MV2hOfjlzpUqJLjUB/eTdDWSd+TL6Fzoe0gfTRwmPs8THmOOvFwXACz2twkydKkufwiNK9Cjj+meX/TO9AqbKk5v6HZ62AKB8doLJWGKonEY6I9FNWRMX5zy1quezw8FJfMYpkyHBfAvIpLLnAyTd2EEEneEmSTnpuLITQjhMBt0Z/B9CjosSYSD9rjoMuvJknTbraBo4hDl6IownVdcoUcd/32Xp5rRYPlKOLdc3L8zYffw9aVv6I0ax714UEGt2+nva+Pnes20ndiO+HYCEMb17BzV8SSubBzUOC6kgWzZNLwbcsOh852SUebQ0dnCdfz6N+2Cz8X0DvLI1fIMzY8QrFLVVJy/Ry5Si9+sR0AN1fAK3Ugw7pKgvZ86lGI43q4hTKunwPHVWKjWMbLlZBRSL57LoW+BXQuXH4Er6LlcOK69h5tctSJh2UVwZxuH5g4uRlUfFtz92jT69BKeGTHGV+yEWgpHvYkHHQp1sT7kIiTiCCfI1fIsereR/nfR2w/B8vMZ2mHoKPs4sRzK5uLND7UsPm5xmma060WDswchuS4pvKrzXkOuv+K9hqm3kNn3JwvtZcpVTq494cPHKrLZbFMSV502QsQnk+u0ktUq3LvTb9nweIehnZsp3t2N9WB7eA4NMZG6e50GRwKmdcHm3eoxnD5nKCrq8js7SN4nqBaU+G7+VJAR2eJKIooVzoIyu3kSqN4hRK1wV0E7V0I4YDj4OaKePkCyBDh+siwjowiZKOBV2rH8fM4nq/mtOfj+nncfBEnyBO0d3HlYx188khfSIvlCHHUiYdVOyVLZ2ujPn3fEYJIykxpxqwhkT42i45Wr1slUprHjzM+JhAOZv6DOX5QKoAQbFy7mZ/8vv+QXjOLZarws22Sy3olrpca4zA+L0ljNm3UZOfp+PeaRUEr7+H4XIfx4Ybme8JJcx8cR5ArFgjyOX707du4dr31GFqOHl4u8vz9Fc9ieOOauCFcyLITFpCvdKnfOj/H7g1rGdmxhWL3LBadtJy7b32AIIBqTTBWVZ6GQrnIvGKeoFAgrNcZ2T1E+5x5FEaGAch39iCES77LI2jvJtfRS9DRDaCEQ6GME+SQjTqN0SGiRh3ZqOMEOdxcUXkQc0XcfDEWGkWEp0qzDsxdwSef2HckL6PlMGP7PGQ5qsTDBZ2C4+cFKrTACEsCZTy4IrvKqDHFhH6tHsd7EZr3bxYPWc9D2mXWNEBMj0NSD97zEAKV4O0I/FxAvVrj4Yd3cNvgob1uFstU4Nl9grldPrlA92ZJt5nzWXsUzG3NoUtaZLSau9C66VurOZ0835PX0HVxPdUFW1V2cqj09hA2Glz9QO2QXS+LZSpyxX+/EzdfpD64k6Cjh4FVd5JrryTbC91zcP0c1d391IZ3UxsZ5viT5xDWG/jeDvKFAN9Xpkv7rDl4hRKN0WFc36cxpioN5jt7CNq7cXMFoloVgKCjG8fP4QY5vFIHfqlCY3SQsDGCcByielWVY82XQbi4QQ7huIlwcII8bpAn6JzNcfOtcDjasDkPWY4q8dBZFPieM87QmDjcIRuukL6fbm/2JDTvbzZ8S4+JjZCkmVQ2OTo1OrQxkhofLuD6Hn4ux+03/5nP3js26dfJYpmK5DxBPlA38GavoSadj+q1WVq5tYAYn7/Q/H6rAghmJTQ9h83XaciSFv9uUqa12FbmGe/5Jbd/+dWH8GpZLFOPG15zGrPOvIjuU86ntnsHu9fcixPkCGtVaiPDeEGO9iVlepaczMDquxnetJZSsYSbK9AYHaaycClRvcrglk0UOio4noeXKxCUKxR65uCXK7GXz8HTlZEKEVGjnpxD0NGDX6oAJCVZHT+PV4gIa1WiRgOvEIcouao6k/ACvGI7Xr7Eh+8d5cpjj8TVs1imDkeNeDitAJ1lF938qXm1sdnj0GxstFqlNN9X3ozxydWp4ZENf6Ap3ME0PrRgUEJCCQfXU6utrucR5PP0b97Kw+ttPwfL0cGKopq/2mtoegzVY3POEclKf7a8sTl3JxL444sdtPQgOo5x7PhQJcd1E+GgPIeqp0OhvZ1Pv3geb//uxkN5ySyWKUfv6U+l2LeQ+tAAo9sepzE2imzUKfbNo7PSi+P6EEXgOFSOOR0hHBpjwziuh+Pn8IvtSBmRq/TiuB4yivBK7fildmQU4vh5orpaUPOKyoMQVkcQrk/Q1hmHJJUAcDwfJ8jjlztojAwqr0QcriQ8H8dXngY3X1SPQZ7GnBO4csWcI3kJLUcIG7aU5agRD4srDqWCl/wBmDkNE4Uu6P30e+MEgDGObghlioVxgqRpBTMTG50xPlKjQ4sHx1X//CCgNjbGN767il9st12kLUcHs0qCQs5JhIMpGkB5IkwxkHaKHz9/JxL540OVsm7qxLuYhBya4UmpgPCS+armsOf7aqHA8yh3deHn8vzXj61wsBx9eIUyfnsXw5vWUB/cSVQfozE6TNvC4/FLHcgoJNfRy9jOLQTtnXQcezojm9fi+HnC6giyUSfo6MHxc4RV1VpaOG5SQtUN8uA4yEYdN18EIGqU41yGPG6uiOP5hLUxwrERZBQq0eH5qvGb4+DlSgjPxw1yOEEeL1/CzZfwu+dx6r/9iM2ff/2RvISWI4TtMJ3lqBAP57XD7E7VVApST4HGDFlqVY612UPRHKbUKga6uT9DdhyRNTpcB9d1k9VMc7XS9Vxc31dlHYtFHNflobtXcVe/FQ6Wo4MVRegqK0GtmSg3Sc9BKU0Bkd0+UcnkcQKixfzN7pv1NiSCwvAWup6H53u4nkehrY2wXuc7/3Mjq2yqg+Uo4wcvmMeSiy9l+z03k6v04RXK1HbtQMpIhQ55Pm6ug/ZjTiPXv5nqwDaEcAnaewirIyrB2fOVAAhyePmiqprk54nCOo6rBIBXLBM16jieT9SoE9WqRF4NIVx1fCwqwtoYMqwp8ZHXFRjV8cIL4ipLgRIdxTZWjrVZ4WCZFGyH6WnC8lk+7WWfMEwNbjOcYXws9J5jo7UR05z8bK5MJuUa423SyODUpRu15yEVE268QmkIB8/DDwKCQoFcscTG1au5+udb2Gob0VqOEpZ2uVTKbua9iXIZpBxffhXGz99WnogkdFCQiHg9hJmAbQp/s3dDc5ihFg5+LkeuWKRz7kJKXbO56oobDun1slimIrlSieENj6iyqY6DjCJynb3UhnZCFDK8eS2Fnnn0//lW2hediF+uUN25WXkcokh5AvycCj3y8yq0KP4XNep4xTZkFEEU4hVVmBEokdAYGVRj5EsqCTpfJKyp8CbXV/sl4wXpsU6Qxyu2IyvzuHDugiNz4SxTAhu2lGXGi4dlPkSSuJv0RJ6F1nXiJ85hyK5UJtvN6itm4nMcRhFFygJprv2eiZ92s8LB9Ty8IKDc1UOjVuX23z5sVy0tRw3zXFQJZUdk8pVgfN+VVqGImub5mw1RMsIRDa+CWcQgimSyAGDmJ5nHC13kwBD/juvi53J0zJqL6/nc8q2vHeYraLEceV4u8rz5HU9BeB5hdZShjWuQUUTbwuNo/H/23jzetrQsD3y+Ya09nPHeW7fmoopbFEMhU1EIiCAKSDSOUdB2amMMaGJs/dmBdDpGNGlN2WkTh3QLsWO3Q0eRNmrsOADirCCUQAlSQN0aqKpbdzr3THtYa31D//HNa+9z7r11z7TP+Z7fb7OHtfY+5y7q3ed7vvd9nmewgfLUdZYkSEApyHoMVY9Biy56J29BvX4JxfwSWNEFtS5IAIyo2XYJABjyYEHLrukqlN3kHP/Z3OgrtJLQWoICIPazzQgTA+vOgc4fxy9/ahXfk8lDRobHoScP13eBE0tpKNw0uEVHeJyOHU2bi/bkIVpwAEidk+xoAwDQicUHnbr4IDS9Mc5BGceTn/kb3H86i6Qzjg5u6gLHF7ippW3qF9i62+AQ65IShyTbLXQdxZjcBwel+AfFXYrwxREMEIzewemUWFGgv3wSn/zj9+K7fvmRHboyGRmzg69944LRKYwGKBePo+gvgvfmACXBOj2jayg7KBevgxhtYHj2URRzSyj6C1CiC1VXKBeOAzCkQIvaLOytVoG4e8qglYQSjScOWjQgffO6tq5L5lwFwgtAAFC281DaYDhegPISrDuHS+VxfM+XZGvWo47ceUhx6MnDC28zuQ6h8zD9vFiPYO7TxUg8npToG1qOK8nCItrBjH5Q0m2YJA/RwoNSI7bkHOceeQj/+d0P4E/WdvVyZWQcKNzzjBLdDpsg9u6xQ1xH7ljbPrndcZhqtUrIBPGP69eRhTCmmD73Lmk22JEXBXoLS7jzNd+J+37gJ3b7cmVkHEjc+pJXgHAOyAbjS2dR9BdRLp7A6PzjxkVp4RhYp49ifgnN5hqajRXw3gJYdw5y/SJ4b8ELm6GkIQZO5Ax4ogAAEADvll44HR9T9diQCF6CAV4wrUVjRdJdEF564oC54/jnv/XX+JXveuM+XbmMgwKecx4SHGrycO8cEpF0jHjcKEabJLRno5PuwxSrRr9wYGl3YYIsxCMP/nU3a83gAuLKXg9lt4eP3P9B/NZTWeiQcXRwdwfYHCn0ugx0SiewPZ7kdExpZkPbSW0yk6FN9tsjh4jeg/Z3Q1LTprNhOoUMhFJ05+excPJmnPvU+/DLD4s9v4YZGfuNbyJd/MCPfgO6192Cev0CqtXz0EKAWg1D5/gN3mlJ1WN0T9xkhM1lF0rURstQdqGVNAt6mEW/Iw5uPAmwHYUy0kdRY/vqnJQoABYRBtAuiNVfANa+lZem89Dp42PDTiYOGRlTcKjJw/Nu4Fhe6qCqJIB4LCleXEwuMMLrabJsOBaPKrWIQ+Sc5HYh/eLDdhQmPs8TDGoJCQ1dCF5g5ckn8NefWNn165WRcZBwxxLB8UU+QQ68PsEi1TO0O4fpRkH79ZgsBLckmtSvIwY+6K01GhXXeFy/xmFpGY/89V/iB781dx0yjia+6etuwPjSWYwvnQUrOsYOtTeH0bnHoWQDKIVmsIbOsevBO3Ngligo0QCiQbl4HCoaSUo0CaURTgNIyITTTngiQal1UDLP3XEAfuRJCSMmdORB95bw2ltv3eOrlXFQkceWUhxa8nBnAZx6xjw2N2u/oNA6Fjyb89pdhcnOQ/t42jWIRxvaritu99IcDw4sIARaqUSAaWauWaJzKHs9yKbGb//6h/Erj8r9upQZGXuO2zlw502didfjxb953q7Z1P2sndvgNwmS8cHJjqHLWkmNDELYm2rVLyHEdxsopWBFge78ApZuvB2/8X/+Oh7IQfAZRxDfRLr43n/xZUbrsHwSo/OPY+7GO9A5dj20Uhid+xw6x05CDDeN65EdDXFjSbIeW/tVM3bk3JRI1CGAUmYsyREEVgCygRa1JwsOhBUgXIIoS0Ts+wkvQAHfpSDdBfzxeeCrM3fIsNjJnIfDgENLHgDgwsWRn5eePjOdEoP0tenz0RO2jjRegIRk2XgxYsYYTEeCl8b1QUnpCYTb2TQLFrMAKTod9JeO4+GP3o+f+1S2V8o4ehiMJBbmTLBjWwjt7tvEP81xmGJuACTjhoHwh2RoQsPIoatfV9e8LEEphVLK1LAflQoCacoYim4Xx289BQB454cGe3/xMjIOAL7uy5YgqxFYbw6yGqJcPG5TnvvQSqJ3/W1Wz6Cs1ar0rkisO4diftlYp3bnoEUDJWqo2vztjAXRoBS06AK8BAAQJQFeghBqciREDSgJUAbCS0NAUACUmddhOxCsADp9bBZL+Lp//h8hfudf7Nu1y8g4yDi05OHemxiKInJTwdb6hnZgVCANQHt3Mt7VDBkNNCITkdYh6kDwovDWq4xzaK0hhQizltai1Y0w8bKD8cYaPvpXD+/1pcvI2He8+CRFv8sS4hBvAoTnkx3DWJfUJvnmffGx1JI17jTQVsfQWycXBZRSU+vXjSWWvTkcu+1ufOD//LdYy3mOGUcUN37eS1D0F8E6PQCA1grNxio6y9dDNZV/nffmTfdAyYgsGEcl1l/wCdFuxKgtdCa8NESAUEArQxKoJRKihgbMmJLTRhTmZ2kdvUYo0OmjKfr4zb89l4lDRoKdHFsiOWH6YOINJwhuPFEm/2dPEz+n7izpzmUqikwXIgDQFldO27F0CxO34GCcg0bkwXUgoLXVN3C7aGHgZQcPf/zj+F/zrmXGEcOrl4AbljkYS92TtqvftNPQHm1KiUVsWuCIRXtEyQumXccwIv+Uc1AYwqCEgLb1648xjlf+g3eBdxbx7a/4zn25hhkZ+43/+LIuXvClb4RqKgDA3C3PgmoqKNFAViNQztFZOglRDdA9doNxUoJ1PKLUdA5cpwBW06AoiJKgtBssWllhOg5KAs3YkIHCjjwqRySY6fRHQmtQBgIWSITFmirxPV/ygr28VBkzgJ0kD4chYfpQDnGdG2qMKznRUZi8n/a4PSud7laSlhNLvGMZe7y7HcsQ+sbBHIFgDLwoUXQ6KDodMwrBOXhRgpcd9JePQ4oGv/lfP7XPVzIjY++xXptgR84mx5XSrmB75HBy3JAQWH1DEEiHGo7GlqzGoV2/cceBWdtkV9O8LFF0uyg6HX+clx0snLge49XH8Cv/w4v35wJmZBwAvODvfBl6J28F4QWUbFCtngPvzWPxjrtRLhwDn1sC78+js3QSrNuHEo0lELAWqxS02wchRsug7XiR1zpQaoiCIwNFByi6QNGBpgU0NZ+VjCW5c5UEWOHfQ0hYCn3goQt7c4EyMmYYh7Lz8LER8Po+by0qUpeWmBgk9qskXXi0uxFOdBkclmhCHGJxdDzKEB5zL4qmlJrkaat/MDPVHTBe4PTHHsBnLmaRdMbRw8dGwBf32UT9Tj4ONeoC4Nx92/TAiZrjLqLPZGFpxyGu3/gWLFiZJxxx/RqtUhfdheP41O//NH75Vx/Yt2uYkbHf0EJgfOksuiduhpYNmsE6xGgTqq7AewugZQfF/DJkPQbvLwJKgs8v24TpESgvTQK0VkboTKgnCtoKopOfRwtoRkG0gqIcRCv4rYd4NMk+17wDwQowZdKloRWaoo/ve+d78JbX3L0XlyhjhpBzHlIcOvJwPQW+7FSBorCuDa3RJOe4tJWz0rRdS8CSDkcmnIsSCSNL7VGHZNERuSj513kByszlV1IYWzpCUfbmMFq/hE9+/HF8LIdJZxwxXE+Bv/NMjjKqX3Mf6retS3L3zHUTpnYY0/HDZOzQdR44m1q/NKlf13ko/C5pXL+duUVIUeOP/9/fwm+fzbksGUcTf/Uj34judTeh2ViFasYoF69DuXgCqqlsGJsZK+L9RRBeolw8YUTP/WXoeghswuc+mL+1YdEPmBEmworwmtU6SFZAo4ACQQER3Jta70fRQcM6EKAABQjvQBOKj64oDH/5+/bqMmXMELJVa4pDRx5edIzg2CL3i4jYGz48D+e3H7ftWCc1EBHR8FasQRztZ6ejcaWwADGLEFaUYEUJynj0+5lfhBUdPHX6oax1yDiSMPVbbFm/wKRVq7tPu4Sw2QuTdRunwAdntFC/cachvlHKQnewKMG4EU6b7wmzKOnML2P1yYfxA7/51H5cvoyMA4HO8RvBOn2ouoIYDUCLLpgNhTNiZ4XO8kkAAO8vgPYWoDvzkJSDASB8AILC5zFo2RiyQCggG/NDIqckUGqOAajBQKGhCAElNhPCnWddmJQlDhwKTEkoyjEgJb70+Tfs8ZXKyJhNXBV5IIS8U2v91uj5KQBfD+B+APcAeJfWevVyx3YLSwRY6lF0SjZltGG60NKck2oe2sTBdR1Sh6XWzmW0GEnIgxdaFn5sifECrOiAEAIlhR9lYryAbCp84Pc/sZuXKeOIYlbqtywoJgnD9OftY3H9+vFC23WIR5gmnJXiYMeWTil0GrgZWWIcrOiY0ScIgHFoqlB0eugunMBv/8JP7+ZlyjiiOOj16/CJd73dJ0Z3T9wIEEOsWdlBuXTSdN3LLvj8MuR4gKI7By0bYHgJrDsPaOWD3gii7gJgnJR8xyEQBk1Y+9cA1docj3UO8XFoMG1eawjHJy+McftNO3wxMg4NcuchxRWTB0LIPQDeAuCt0cvv1Fq/wR4/DeC+6Ph2x3YFNxbA8jwDY1vPSrsFh5unnq5zmMx3cAQhvNZyVooD3iYWICV4YcaUqB13YHbkAQAUBAgoyv4i/vZP3oc/f6jazcuUcQQxC/V7S5nWr/3ZE7Xbfi1Olm4fT+s3NTiILZWJ7yC60cO0flPib7oOIAREaxCtQQnD3PGb8NAHfx9//InN3bxMGUcQs1C/Ds1gHbSoTHdh6YRPgOa9BfO3r9sHAMjxAGK4AUIZitKKlquhF0ETykAINV0Hd08ZUHBowkC0hGYFiJbmMQxhKImEVztoBTAeSIQTT2uFQgsQrSBogZFm+J7/6wN46H/79r24RBkziBwSl+JqrsYpAKvuid3ZOO6ea61PA3jz5Y7tJm7sE8z3WdQZINarfTK3wf6eE8QBWyw84gRpt/BAi2QEUSb1OgdqbR5j0uDmpU3HwXxJsqKD0fpFfOhPP521Dhm7gQNfvye6wFxvsn4nMlcmiAOmPLY1S9rEgfosFULDcRbpmByBSDuIpe8+GN2DGWNynQje6aOphvirP/gw/mJjt69UxhHEga9fB1VXpsuwcAys20e5cBy8M2d+F5vNwGy4G7VJ0XJzFaoaQjVjE+Bmuws+hyHWOAAAocZNyd6bm9kLJVBgaJmNtBZ+RDWgSkATCgGKz14aZ+KQkXEVuCLyQAj5eq31e1ov3wNgZcq5py5zbNdw6zGGXpe3xpDaJGHa8yDAtL/n5HmtMSXv4GJvmLLoMLdo1IEXkVtLeI3xAmV/AU8++En8xEeGu3mJMo4gZqV+bzvGk0T4yU5g+njSBS2IIfz73bnWRalN9imbXr+hhiOy4N3SWCD9diOgt3QdLj76IH7wfROXLSPjmjAr9evAOj2Tf6IkKCshx0Mjhra1IsZDKNGgGW74DAdQClWPoUVjRphch4BQQxooM1kOlJnsBgCKcghWQFEObceXiFbgsgGXDYjLblDK3Jxo2uooAEARgkpTfOnzn7EXlyZjhsEouebbYcJlyYP9wjk95dBxRDshFisAli9zbFdwZwF0S2KDpSYdV9o7mfECJF54xAQCLTem9pz0hGOL94sPI0zxKERwa7ELEPvYzE8z/O1ff3a3Lk/GEcXhrt/puQ9+hGnCTQ3eVtmbHGxXv8l7SUL2A6EowMsuFm+8Cw/+1V/v1uXJOKKYlfp1+Ni//8dGz9CbRzFvdA+s2zdEuzsHwkt0lk96IgEloUQNLYwI2uUwaK3grFl1M4ZuxuYHMA4ddyAsNKGeQEAr01mQ0fgvpebmiIhWgFbQoLgwzpboGZfHTpIHQogmhLxj//41144r6Tzco7W+fzd+OCHkHfYi6mv9rJv7wMIcnzraEC8yGKNgjIBzm/7MWrPQySiSG09yZCK4svidzJbeIbnFCxkgEIZo8WFGlkpc/Nxn8PBjed4hY8cxc/XrkqUnxw9N7bq6dY89gXDjSROEwQmpg86BcbZt/Tqy71kJkBB+txFAKEPRncPm+Udw9szqtV6GjIw2ZqJ+AeChX/9pEF6A9+bB+/NQtbFlpdaalZVdr3kglJkkaW4clZTNbHBEQovadyAIKyZGlhTlxk1Jm19dEQJFWju7SoGIyhAFpYyoOhJZA4ACwYceyaFwGXsLrTXRWr9jv3+Pa8G25IEQ8noA79vi8LSdDLfjsd0xD631O+xFvOZ+zvE+Ra/LE+LQ3qkMiw5z49wuInj6evCBT9Ok3c6kW3C4BFq3W5mEwlFqBV8kIh40GXtwXQetNT77kfvxc5+qL/8Pzci4QsxS/R7rUXQ7cTDc9DHDuHa5q13uyHxUwz74zWkZ7GcmAY6RKHoiCM54y9NWByKpX+uaxoouHvzT/4Z/+f5L13oZMjI8Zql+AUA1Y++yRIsuuiduQtFfAGDzHOzoEit7oGUXtOyG8b+yZ0ebzBhT3IHwQudo3IhoBaqNHWtDOCQYdLycUcqShrSr4F2ZiCERI83wPV/ygp3452cccnBKr/l2mHAlbktvjnbPlwkhb4H5QrsfkSjLQWt92p4/9djT/1W3xi0MOLHAwPnk/zmh+xDpGqLuQtxpQEI6DIHwuQ3eVSkiDq0QKe8H7zzhHYGwNxBqX3di6gK838fqk5/FL/9GHlnK2BXMRP1et2jqN+0YTnYNPaFIugyxviHVKXmdAw1dxrh+GXddhGCtHOuW4volUe0a8lCi6C2iHlzCz/yHP96NS5ORceDr16FevwRCKcqF4ygXj4NQBiUaEJh6JbwElDTkgpe+6wClvCMTgAlxs3ktsmrVaqJ7oEDAoaAJxVQmpJVxZHLdBxjNxGcvjXHq5h27BBmHGIdNs3Ct2JY8aK2TXQ9ifKbfFT2Pj50C8G77vtNbHdsNdCkw358mlI5JQ8vb3b7mAqPiHc4k5yGakWZTuhCOMHjyUJiZaDfW4GekvZOLGX1wuy2s6OLjf/BePLC6I53jjAyPWapf47KU/K5TiX+cEt0OdCS2lt0mwATxd53DpIsYdQt9IFwRCEK8QWDrl7LCdg27KPtL+Itf/Vn89Uqu34ydxazUr4OshuieuAm8vxB1FJgfSQIAwgtzzJIF12kwT6gXN2vAW7WaY8wTBqIloCmIVlB2nKnRBJyYjgQI9RauMcmIsyA0YWgIx3/+4CezWDoj42nginIeCCHLMB7TIITcB+MhfRrAmwghb4MRdL0sDrC5zLEdxYuup+h142C4aLFBUuKQahzSBUgIlGrnOUTiSsam36KFB+UhWMpZPCaz0nYBwjt91MM1rJxfwzm1W1cn46jjoNfvC09S67I0KYJOOg401jiE0cK0fqfoHyKTg1jfcCX1S3kBXpRJ/bquYdGdB7TGaHOU6zdj13DQ69eB9+ZBmSHecjwAALDunNU2GJLAyh4A+O6D7zIoZbrzlJluhD3Hax2UNEPWkSgaAJiS0G4TENofI9qOOE3pYmhaQBOKTcXw89/xul24EhmHEXvZeSBXEfK43bn2++IhmM2DNwM43d6UeNq/o9YHY8fsWkRb33QHxzNv7YPzuKtApi48ps1DJyTBj0RM5jp4UmE1Drwsg+ahCETBWbKyorQz0Z1AHHjpdy17yzfiiQf+EC//9p/bwSuZcViwU7PIe4Frqd9vvJ3hmbf0URST9RvXME3qN81emUoYouwGytIMB8b5Zes3aBrKyLLVEoqyh/6JZ+Diw/fjBV/zYzt5KTMOCWaxfp/ueuAT73o7Oss3gFuNA3XBcP0Fo2/gZdJx8PeWLHjL1pZGgRTd8CROlobtJFiXJU1MJ4IoEYiDA6VpAjWhEKzAh84JfMWL7nha/96Mwwu3Ce3q19XG//b7H73mz/6BL31x8tnb/A7vjUIeTwF4+1YbANuda8nDW+ypP6a1/vFr/kdYXHHC9EHFi3rAQp9GDi3puJJzW5kYe4jdkuKFRrSDGS9Aggg6PhbtWBYleFGahUYUBMe4fc0uOmKBGCEUj/3NR/f7EmZk7Bte1AMW+6xl0drKYojIvbs5EsFYNIpk7ZNdt7HdcaDWPWm7+vVBjo4wOAJhSX975PDcQ3+z35cwI2PfwTp9Y9HaX0CzuQrQLor5ZdN1sHoFwouIPASyQHgZxpMYNSJpIOQ7ACYl2iIWPTviQJUAUU34haKORgJ7foUCX/GiW3fs35+RsVMgU0IeCSFvxpSE+Cs496+01m/fjd9z5snD8S6xeofJhUd63158xLPPYREyuXvJ/E6l26V0C5AwM1144uC7DRF5MGMQhe86EMrQmTuGeriKP/y9B/b7EmZk7BuWO3H9tol/K1slHl2KiQOjib6BtAlHS5sUbwC4UaWkfm3qra/homPGMRgHszuonfkTkPUQv/VLO9IBzsiYadCyC1Z2oOqxt2QlbgHvtAwAVD0GLbvQVgfhiEUMl++wLSItA3EiamCSLNCgk9CEQRMKSRk2xMw0hTIOCPZwbGnLkMcppgdXdC4hZMctn2eePJQMKEtmxxumjSsF+8Z44TG5+DD3xBKLeEQpdlIybkrBkcWkzPKgb7BjSq7b4J4TVnh7Vso7KHpL+Jvf+7/xgU9Xl/9HZmQcUnQ5UJbU166r23b+SkwYQh2zVh2HTmI77T2pXxbZsU6p36TbwAuwoutJP+WlEUrPX4eP/9ZP4b2fHO33JczI2HcUc0sgvAS3GQ6gzAS/RQnShBeAwIQWIRFFO9DIUhWT7wEQQuHsedqd7mxaSSAt8XslGO5/YhV333b9tf/DM44M+A6Sh9aY7w+3Mh+uJuTxcueespbPH7YjTL+6UyRi5snDrSc4Oh3m9Q4uPCpxVYpmpClzAVGTxCHOaPBdCPc8FlTaeWjnpmSepzuVZhFiFhrmsUmRJpSBFl1orXDxyTP4ZOYOGUcYpn75RABc7KrUJv6cs4Q4mLqN3JPatZuIoouwAdCqX6NFKu2ooatfk+NgjhcAIeCdeRDKsX7hfK7fjAwYYbQby4XNQCG0m2gboJTpOijpzyMxAXB5DpGzknk9JQ1ESyONJunr6UlbH1Mg+JZXPPtp/CszMnYGe6WHijUOhJB3AngvgDt34rNnnjwszHEUBQtps8nOZZzVEDzfJy0bI+IQLUBoQiZsfgNLXVmYG2uIRpRY0TUz0bw092XfulAY8sA7C7j06Efw3T/z8f2+fBkZ+wpTv3HAW9vIINRyMDpIOw6xc1I7tDHcnB1rEboPdlyJel0S96SBW00DLbrgnTlv0UooA+8uYv3JT+At/+bP9/vyZWTsOx7/g19B0V8AcQFw3b7PbnBuSVo23kUp0TgAkx0HEo07IbVYjUF0NKKkt7E7c+TDfq6YngSRkbEt2BTnrl3CFYU8Xsm5hJBl57xk9RCnduqXnGny8EXLBHP9IrgsRTaObSvHrRxZ4hnoRA+R7Fqm4w5t4sCKDljZDaMORTchDrzsgxY9o3tgBXh3CRce+RusHQyjq4yMfcEXHwv1GzsqxcTB65SiMUSX5xBbKk/omaJugycOcR23iIMhC+2OodkE4J150znkRvtQ9E/gsQ/9v9meNSMDQPe6WwAYQTQtuoYAsCIkPFNmCEOU9wBga9IAXJY4eDhxtZbbn2Y/RxOK22+64Qr+VRkZKfZQ87BlAOTVnGvHle4D8NId/w0x4+Th9hMM3S5PhNFOeOkQJ0eH5yGVNiYSaN37TAbqkqJpmH1m3IwyRASClz2z88I7XtvAeAe0MAsQVs6BlXPQSuIv/+vv7NNVy8g4GHiGHTl0dYuofpNatvUcQhyjUEdbp3HtTqvfoHNwXQjjnJTolMoeeNnzI0qmvm39ln2wzgJ4ZwEgFH/6nvfs67XLyDgIuPTIpwDAjyM5aFaAyAaADWrTCnC2q3FCNJ2uS4hJgyMGscvStthih1gTCnk5MpKRsc+4XMijfb6itV69zLkfBvD26NjXA9ixP1wzTR4KTrxFq4NfiCBN4LQv+EVHWKi0XZqCN3y8KKGeOIRuBLXuK8GStWsWGWXPjjhwENttoKwEK3ooesdx4dPvxdmn1vfwSmVkHDxwBjNSGNflFpio6alE4zL1S9MxJsan6Btst9C4KvFgdMC7YEUPvHccq4/8Gc6dzfWbkaHroRlPKrogAHQzBgFARBX0C26kSDamI0EoNO8AAIhqoO1r4UNV8lzj8p2FK8UYmTxkPD3sZUgctg95vA9Gu/Cu7c7VWq8SQlbssVUAd2qt37RTv+DMkocX9YD5PgelMetyITcEW401am3PsWE4Wmt/i5+Hz0x3Rf2upd3BJDY4ilgrR9Oh4H7MwZEH9zphJZ78mz/Aj/7Zxq5dm4yMg457+kbv4LJYYmxHIjx83aY1vG39+g4Eb9VxEboN7uZrtwRlpa9fxrt48oHfx4/80doOX5GMjNlDkgBd2EwH12lw5EHUXgytZWP+VkYEgUD5IDdnqZoQCJvN4OAek+10DlE3Iw6Tu1QDt+/4Vcg4CmCX63jtIOyIkhM7v6d17E1Xce79MKNNO46ZJQ/zBTBn/eFjpC0c+N3IsEMZOg/T3hOTCLQWI2FsgvkuRPJZWkMrCSUbUGtRRykHofYyEwoxWsHf/ukHdvx6ZGTMEuYKYK5fbE0cWh0FM740Wb+hEZHW8LT6decl9etGnQBoraBkAyIbTyAcmTBvpmjGq3jwz96/K9ckI2PWoGVjxM9F13QWAACGJEBJ042QjbnXKgillQQoEitWZ7PqXmo7KunW4k0TavYIp5GIeBzK/VaE4cW3Z71DRsZOYGbJQ5cTdDohHM53BuKE2UjvEM9Lu3Pi0SU/6rDVyJNdhCilQLWG1sosTJSCEjUIoZBRypWyu5b+7UqCUI7hhc/gZ38xB8NlHG2UjEzROwTC74l+omW6/A1o1W6LSGxVv+59hBh9k6TMdB54x5xr63d86RH81M99ZD8uWUbGgYOux0DZhR6uTtqvumTpzpzpPigJsIg8AAAia9Z2/kPLkpVo5ROl3fNt0dI+COzdznHG4cMejy0deMwsebj1OAfndGLBEUNrDaIJlDI7HuYeUISAknRnMt6d9Gh9pl+EKAklhf+S1M7xgRBQVkAzCa0EtBJmJ5MVZg6UUKx+7qOod2Z8MyNjZnHrcT6hd5isXwB2LEkpDUqielUKmpDpdYuoO9H+3Hb9WiIBANISByILUCV9/brOA2UlNp76W4jsspSR4aFFDSgFrRRIyaK/h4EouNe0ViCufhyBsCNP5vH2BCK8rpJkaTfytOXvSGi2aM3I2EHMLHlYnDPZDjGUUgAoXHgfoQSAAgWFhAIDMPH1QgiIUuFG6dSxB20XHVpRSNHYt5rFjyYESgp7a0BV6ceXiKzBdNfMUFOOj/23X8LDw92+OhkZBxuLc8zrlQxJMPoFM2mgQDSx9QtQPUkqNLNiaEWn1q7rMJjzp9evhx9lksYxxi5KjDe9gNbaaiBK3P8bP4vHcv1mZODSQw+A8MJ05VwYHKGmU+d0DoAZZ3JdiPbcuDsn1jhEBGKaVetlOw4RYr3DhbHOeoeMp41dSJhuJ0vPFGaWPBTc7frD7ErC7EQCCpSaLgMFhfmaUaCEQikNRoLI0n9AdJuYlW49N58rIAGzS+nFmMwuTsJNyQbMLloo76AenMfFM+eyP3zGkUdhu4ampsz4s0KsYXCvma6hVho66hYCmKjd5Aak9aukJfkSFGYTgRACTRm0olHNikD8melAQCtQ3oEYrWDlqXN4IncOMzKgRhvenlWj8X8D/fF6bEaZABC70tDRwp8QGkTVW8ALqAFAq7R3EH9WdF7b2tVZtL70mTc+rX9nRgawsyFxe5UwvZuYSfLwxusIul3zxWBGkewOJQW0NqMMk5qFKR/UGnnQUwiEUtLsaCppnBuUhAJAiR19oBRU82QcQoraWzwqUUHxDsR4HWc/+fv4qV/57C5ckYyM2cGXnTT1a8rP1KAjEDCTRK1xQXdvanLat+6E25LTM7j69YRCQSli6lcpECnMAicyO5Ci9i5MSlRQsoGoNnDuU3+An/ylT+3mpcnImBmoegwAvuvgtUOWDGjRANwc16IBqBU4O12EIw1bBMQBoXNgP3jL36XdoWhnQmS9Q0bGzmImycNCl6Ismek4tFpJ09xXnHB6GuKOArEdC39v56rNfLS918wucowdnVugUK2sCDOMPMiGAHaOmvIOBitn8LHR7lyTjIxZwfxE/QayH+7Tx/ExAEl3QSkNEDu6RKzGSUo/krhV/WoloTX3dWtqV/suhGzGAKGgbABWdDFeP4/788hSRgbOnXkccjwA7855YmB0D9KsKmLtgn1Mog6D1z5YV8KtxpbiY7HbUnt0aarewb5HE4qhyuQh49qQBdMpZpI8cDaFHJgHredtu8c0XTpYNMKLMM2iQvkRB69psLZvxHY1wg6nSkYpaLSLopWEEhVERYze4X3/bS8uT0bGgQZr/R0Pounw3DxA4poWzo1rNx1jcl0HT/5dLU+pX/Mee447Tk0KtXNYUs0YgjLQoocH3v/bu3ZNMjJmCXzjHJp6DKEkeH8RcK6DlHmL1JgsOEF13H0wr7fGlqalTLfsWp3r0pY2rS1IwnDXzdc/vX9oRoZFJg8pZpI8MNpOloW3X43dW6i1ZQ0kIiUTwKQla9KJsAQChABSQCsSZjitRzyhzAgzoxEo6mwe3TiE1pD1AB/8s4f27iJlZBxQ0KROU0IQ1267Zk0tT0+Jj+tPKQVKiOkKXkn9Rr+b/1l27BAwmwBaNvizD/ztXl6mjIwDi2b1HGg0rmS6dQqsNDVDS+Oe5DUQcechHluKiYNWRvjUni1vJ05bApGcEukd2iNMKrssZWTsOGaOPDynBK5bLqzNY0QGLFEwN2r94ad0HiK0xyIcJuaqXVfCnqgkgRTG6pFQZkSW1jdeKWnGmAAQVkArAcoKjFbPYFRlpXTG0cZzSuDksQKMtch+VLsp4Q+PgUmy3+46TsV29UsoFON+8WNGELUZV+IdaCXAeIl6eAl1k+s3IwOwYmheRGScJWS7fdwjzoHYBu2uQzsgzsOlWU95nxtZynqHjJ1A7jykmDnyUFJgfq4A5yHsLSw8zOJj2sKDmKAFTzR8+JTdgaR+J5KCMgbGGKi9kdh32tqzAvCjDU4orURtguLgdk8ZaNFF0VvCx3/7Z/FHDzfT/kkZGUcGaf1S3zWMiUO7gzhx8xsFdOJxXL/u8dT6jXQOidFBbQOo4vrtH8cD7/k3+MPP1vt12TIyDhRcZ8E5LPlxPyX9se0/oNV1mMhxsB2EqOsQdxx85+EKxpY2RF70ZVw7dtJt6TBg5sgDnTKiFD+fNqJEKTFEwN4zzsxChVFPEOLFxsSNsoR4UEc2Em1DA+mSLwmFZAUoK0B5CcIKKCnxUOYOGUccaf0iEPhkHCkl/75W7T3jcb1ST/Q9ceD88vXLOHxInCUPaCoAk/VLeQdKKTyYuUNGRgIzsmTHlSj1o0weVkg9/c1upIlNjCa1cTXZDsmPIARrlXha783IyNgaM0ceAEThUjrZVYwRLzz84qS1CDELi9B1iBccbgHCeOF/hst1MOdw+x6ezkbb0QclG2P72IxRrT+FjZWVvbk4GRkHHHE43FabOW3dkicOUf0SSic6hGyihnlU/5P1S6zBQZwJEdevEjWq9TPYzPWbkZGA8tKLpAll3poVsH8r7diSts+TToMTStOWKJrSidGja8Urn3XzNX9GRsZOhsQdBswcebht0SwmjFsKsX/sAWLD34iebsvqR6Jb2Q6x6JJGO5eMF6B28WFGoYhfgLjFhyMO7jFl3O+8aCkg6xEoLzG48Ch+49c/tqvXJSNjFpDWr8llcenSW2a0TIHWaZkTQjxxiIk/5cWW9TtRu/YGmB1VWY/Aii42LzyK33jPR3bjcmRkzCT8uK5owMquF00zykI6tGgAam1X21qHmDRs01VwzkpAGFu6bBciFldnvUPGDoFdwd+lK0VOmN4H3LDMwDn1iwwTKGWOOctVArsIsYsRtzgh9t5lOeiYSMTuLdFiI8xSp6RhGnkgjIPxEsSNRBBq/OHFefzyw7l1mpFx4zEOxkLdmjoFAGd/DFu/04PffKbDVh3HuMuQaJmefv2KaoBfeCjXb0YGAFz85F9ae2OZdOUBQyp8EFyr06ApMBEOZ95sn28XAre925JHS2CdxdIZBxE5YXof0Fa8u8WHCZwCwiIkZDG4BQdAzcKDwPq/m3tFSPCEd/aOMCNPSgpQhNGksDBhfuHBig4oL8DLHljZMzoHykEpw9x1p7Dy6Mf39iJlZBxQuIwH1zl000Jx/cIThxACR4ipUwqT22BqlZjatRsBLqvF2bP6juIW9QtCfLeQFR2wogve6U/U72Dl8f26XBkZBw5icxVQEnJcg9quA2mRhThdOh5Z8uFw7tzLaB2mBcNdKXHQhKLSmTxk7Ayy21KKmSMP8cjStBGHuOOQ7F7asCi3e0msdSOJ8hy01iYYrmlAGYMSws9SpzuXjjSU4GUXhZLg6EPxEgywQssOeGcOvLuIB96fw+EyMgD4biGALUeUXPfQPGlnr9DwWFEQYgi/FCLUrx0/5IWAZBFJaNcvL8A7PRSdHgihoDbttl2/9//2f96ry5ORceCh6jHEeADmsxzCYp7y0nQfnHBaKdgB4wC3g9AOiIsxJVE66ThcgYBaEYJTN+VwuIydQSYPKWaOPHRKOjGutC384sMQCikVGAAp3O6n+fIjNk3ajS0xziGFAHOLj8gK0mkieKfr3VqkaCB9WI4E78yBMo5mtIozj53f1WuSkTEr6JTb7wTG40zajx2azgQjtosI69ICAWjmSUhsjDCtfuHF0gy8KME7XW/VulX9imoTT5x+ctevS0bGrEDWY7CyC9adgxKN6fwpBS0aY9VqSbizcPVdCBueCsoCcVASJhTJEQoFMBf4toXeIe5WbNG50IRmvUNGxi5ipsjDy+cBzrZmDMmCQwGaEJs2S6GUCXFznQtKbTdCaZsT4dyXCEjYGjXEglIzMsEYeFF40mFIjDI2j/a5YNyn01JeQozXUdd5Xjoj4+Xz08cO3b6kjsaVTP0GEwRldzeJ0tCUGDKhqKlfeeX1Syn1pgmu67FV/bKiCyUqSNkyWcjIOMKQ4wHY8vWGaIvauylpJQFl70X0moPrMsSvtdHSPcQdB991iIlDCy4YThGS9Q4ZO4qdFEwfBswUebh5kWJ+vowE0o4swC4IiB1pMN9BfrxJGWsWsxghoP58BhAFCmqPuYWLgrTD2MEX3rhIeEtH9/OVgiYKYKGTARhhGCv7ENUA43EmDxkZtyxRLC7G9ZuKpm3pAQj1a57b0UKtQCgBQEGhfP+BgkG5c0BNwNQW9RubJTh9BCEUmuq0fikDK/tQskbTbLPYycg4QnjgsbNYcvoF0UArZRwGXRdBSQDF9DfHoumpx1VwarIk4KqclaJRJw0KMc12MSPjaSKPLaWYKfLgAuFif/h4pxLULUhCDoS5D/PVJOpcxEQAsOJpTeyYA4EEwNxHsxA05X8ZIPjG8wKsKK3wsgPenQcv+3joT38F771/bXcvTEbGjIBEdQPEBMHWdLy7E9yYbf1qUEJ9zROEGjddQA3tNA+WXEyr3xBAF9kzF2VSv0V3Abwzj4f+9D/jdz94cY+uTkbGwcatWMMgSpAmlEKJBoAZX3ICaRJbttpOBLit2a0IxJSuA4CpWQ+kNa4Un6MIgQKBnH1Dm4yMA4uZIg/OlcUFSLnHZv0QiSz9GwANlwNBAKS7iw7JeiWan45941lRgBcFeNkxj8sOeNk1pIEX4HbRwYqudW2ZBy16UFLiLzZ286pkZMwGXP0yZtKkjX7B1eV04bQbXyIxcQcwTWgd45rqt+yBlX3QogstBf4kc/+MDACAuPC4t2jVMOJprSRY2QUtu8FxaRvb1QTTBNO247BVQFzSjZiieaBaQxONcW4YZuwgcuchxUyRB7tZCK0BKe2uhO00TNvRNA9gHFp9Wi01ZCESRzt3FvM50blRWm0smPap0u48G0bFyx54p4+it4iit4Tu4k3QV+AKkZFxFBDXrxDKE3pXd+4cIGwIGH0SBUio87jWTX1uXb8uMO6q6re7gKJ/DN2lW0HYTH1FZmTsOsTQ7IY5ZyXenQOsMJqUIW2a8CLVPFjnJSgJUnSD9sFrIdKxpfjeYYI4RGifOxL5b2/GzmEbue2RxEz9ZWSUJFatlJJowRBGF4AwT01jthg9pJSCcQbGWRBakjgbQhkbVx+CE5yWeNkB7/TAy665dXoouvMo+kso546j6C2hnD+J7vLtkCLrHTIygFC/MXwQoy3imDQQEs6f6DxQCspoUr8Ocf3S2InpKuq3M38SveXb08VPRsZRB6Xg/QUA8MTBjSppRUOeSkQIaNn1LmbO9lxrFUaXCI1IA0tEz4DpJJiMF/u32Dkuufe24N5Xy0weMg4mcsL0PsCESbkFRbqo8LPQEZkwB+DvCSHWatXuWNJg/eqTbAFQKMDuevKyRNHtoeh0UfbmvDc8KzpgZRe8M4eyvwTeXQBlhcmSEBUG5z+Fj/3hn+31JcrIOLCQUsPIDwwxSMiEy2QhYVPAvBxSpikxhIEX3Nevfas/FwAYsYJpQsCKYqJ+HXHYqn5lM8LmuU/gr9/3B3t5eTIyDjRG5z4HLWo/opToGVruSm7jTdVj0LILWOIAygxx4KUnDpqEtOmYOGhQKNIiAZcZWwIABYJXPuumHf23Zxxt7KTbUk6Y3mPcfmM3IQ5AEFwGwmB1loREZMIsUhhnKEoOxjkITUmHfRBpHhhYUaDs9dCdX/CLDsYLP/ZgRNJd8LIHEAolKhsmV0DLBrIe4md+M6fTZmQAwJ239qJuYVp7oYYJiGH53k3NdRBN/RaG+EedQiecjsXTsKShXb8uHC4kS0+pX96BVhJivI5//55H9+tyZWQcOFBeQNn8BsoLK5aGiVyh1snMZj1oe8yRCgJsGQpHtPRdB6KV7zKETBekdq2XgcpOSxk7DHaFMp6jgpkiD2KLNqQjCWajg/i5akcwKKPgBU+Ig3uf94+P5qh5WaDsdtHp99Hpz6Ho9lF0+6CMe4ZixiYKsKIDyktQ6wvPyz6I9YkXwxWIbBGfkQEAGFcS3S5HPD84OaYUiL+ryVC/gTgEcpGmVJtO4Tb160CITZIuQRhP6tflPIjxeq7fjIwWXNdB2VA4wBIEUYP41Gk5cb55YoPiHLS1SYQhEFCY2kkwx1vjSlOIhCLEdCsyecjI2FXMFHnglvq5nctg4Qj/HDCe8U4QzQuOslME4mC2Kf17KQ3JtEYDwVF0u+j0euCdrnFniboN5rzIkrUzB95dAOMlKO+AUO47GM1wdf8uVkbGAQNnNNEoxWOG1BN6O5rIXP0yW7+BOGhtbJUBS/oprLMSBS+Ky9dvYZyWTP32UfSWkvrVSgJaQVSb+3m5MjIOHJRowLv9CfIAhC6EIwte/2A1EQlxoMwQANkkZIFQ79AMoCWC3kYs7V+2RCSrHTJ2GlkwnWK2yAMPowrOG95sOsZuLXZkgVHwgoEXZlEBwIgoW3aPTkRp5qgL8LJE2e36hQflhfeI9z7wvAS1WQ7l3HGwsm8+UCs/+sA781vuoGRkHEUUBfVdQWPTauCIvyMVlKb1y5h9n1Leu913CimZqN+YOFBemNnrdv3y0tcv78ybX8TVLyvAOgugvNzza5SRcdDRbK6C8BJa1AAMWQAAZu8JZSC88PWT6BwSAwL7uKVbIFoameJVhsQ55K5Dxm4gk4cUM0UemkZ5pyVA+7nn+N6IKM3iw4sxtTa7mTBWcM6uNSYORVkaYXSnYz3gO+BF6XctGS9RdOfAyp4fVyp6S2BFF5QVULKBEhVAKCjrgnUWzPOMjAwAQF27sSVTw44oJPVra5glYmhbvzR0HV3HkDIjnuZFYWu3tLVb+Po1txK80wfv9JP6dWNKrn4J5aCsAO8sQMtmX69XRsZBgxhugPICuh6D2Q4Es25KhJde86BFA21JBACfLu3gNdC8NISCYpIIZJvzjIwDi5kiD2bnMni5x8QhFlADQSytlfaiSm8LSUky5sDcwsOHR5U2WMosRJi1c3TiSh8kVXSh7W6lEYl1wMo5Qyh4F5c+9wmM8/dfRgYAU78AfL3G4ul26Jt3WFJhxNDYM5v6pTFxKEtP/pmtZ5cYbULhnDWrrV07brhl/ZZ9UN7FyqMfzZqHjIwWWLcPrVQwDenOQQzXTSfCjipJexwAQO2IoVttxFatW1ghE21e9y5M26Bt7QoAueefsdPInYcUM0Ue2osOGgmfXTcCClBEgxANqrUPl/LahvaYg11s8KIA5dzeCu//7nYtGS+tQ0tpug+8A62VmfkkGrTogncW7Nw0A+8u4/SH/xRPZJv4jAyPUL+hnuNsFgMzXugzGghCyBsx+gbGjRta4QiDrV3GC0saovotOqZ2GffEIa5fDQlW9ifq98E//T08mmNaMjI8WNmx910oUQMIQXBKNCBU2TwHBmHPcyNMWjTGrhVIXZfcY62MWGGbdGrnyrTlccROTRkZO4f8X1WKmbkeSyR0HhzcOINSGlIqSKmgXKfBj0S4RYeza+VWRN1BYW+8KGwarRlx4H7HsrRuSoVxZLGiSsoK83msACHUuCsRCq0EtKxBCAWlPFjAZmQccSwRoCzTMDcAU+vXwWiSSEIgTEeQh9q1XUJfv0VpxpX8zemWChBWpPVr57DplPolhOb6zchowXQbSqslYtBKWVvjIcRwA83mKlQ9Ts6HUlCinh64qGToPmyjESRa+m7E9OMmEJJqbQlErt2MgwtCiCaEvGO/f49rwUx1HpzQ0vCHNEmaEALGwo4mtdoG36VgzBMHt1vpSIOZnQ4LEE8WKPN6Byey9BkPrAC0gpQNiGygeQklGz/6AABK5rZDRkaMUL+As2gFQv3aJ2CR7sFpG0y3YbJ+J24uxyGuX+uO5l2XqPnqk80IIBRMyVC/HZegm2cOMzJiFPPLAEyXQY4HYN051Kvn0WyumcTp/gJgx5koL3wXIr558XQMJYORflR3xOoUHZKuAwmJ0y4fQhOarVozdgWU7BwhzSFx+wC3Mxn7u5tRhjDKxJgZTyLUuSmFhYfbpaTRF1Kc8UBsCiYh9p5x33VwM5xaa4h6BNmMAa3M7LQSINQsTNziQ4o885CR4RBcljTiTf14jMkLqO3NhcO5VOlp9QvAdgtIukghxNev6w46G2VVDyFF7esXWoHIxoulgVy/GRltEF5ADDdQr69A1WPUGyugrISSNSgrPWlwQmnnvGRIA/XEwWseHCibnhbtTBOmjSpFmQ+OOAB5dCkjYy8wU+TBjTc4UBrcWsKiI7gtMUbBHXHgYcGhlAKxkbaE2vEEY780VcBpRhokZD0yzk2ihqhHUKL2dnRaKxTdBfDOAlg573/fjIwMgzbxj/UPbaclcwu1a8Id7UJCKW+7rGMSQehE3TqWopWEbMZm0SIqSFe/hQ218vU7D1r0k983IyPDoNlchRwPPXHQSqF38lbbIWS+6xDnPAAIJCASVWuKyQ5EdG6My2kdnGjaQeTOQ8YO4/LS/aOFmSEPa9pYPXY65v9CxtKFfkwgGDdOSm4kyfnIx2nSWinoKMk2BM9paCWhpDAptLb1KuqRCcaRwhy3Htfmtca4uHTmwbuLoKz0PycjI8PUb1VJlGXqmDZh0xrXbxTgaOpSmQBaQkCUMsTBjT0l55n6laL29SvrERRloKKG1tp0DQEUrIASta9f1lnw9dvWZ2RkHHWI4QYAmL951qrVaRl816FFGrSSQNzEs6sOygpj1epwmVykLQmEVhOhcmOZazdjZ5F1NClmhjzEiMeVEq94ajsNfl46CpWz+oMQMqdM+Jv9IPeZWilIm5SptQbjJaRts1LGoUhlCIRW4GXPtE61cVsqestgRQ9KGmKRxx4yMgLaXLo9qhTnszCrX3BE3/UbWUQkYr0EgIQ4uNdYtDhxCdNO5Mk7fT/60K5fwkpIkTVLGRkx6o0VAIAcD9E5doPJcxANaNn1YXFaSa912AqEl8FliVD7d9SOLcVao/Z4oiUQWxEJohVAGGRe52XMMAghpwB8PYD7AdwD4F1a69WrPfdqPudqMVPkwY0RtO1a07El4u1ZzXvs4oCFwKlgDanNDLRSUFKCUGHJhYISAqyQ/jnjJZRooOwXYxBeGvcJXvZBubGxU8JoIfLiIyMjYFr9Or0SY9R2G0JnArAjSqBGrKajW/K5CkQKUMagFYVsaighQHkDQgh4pwfKuFnUaA0thdFBbFO/hFDIbHiQkZFA1RWUaFDML5nnskExtwTWnQOUhBIhaVorCaKioLgIScaD4wcuLA4wJIJGRIJSTxqIloBSvlHhSESsexiJbHaQsbMg2NP/pt6ptX4DABBCTgO4D8Bbn8a5V/M5V4WZIg+cx6NKrbyHJDDO7UQCsONJ5rlddDjSYDsSbuQBdlcS1q1JKQmtrTbCdh+cAwstraMLK8DKvrGBZCUI5dBKoKkHEE3uPGRkOEyr35hEeGtWGhN/OuFyEQLkDOl39SqF8PVLCAFToetQdOfMpoA0NVmUXe+axoquTZY29QutIMarkLl+MzIS0LJjNtHqsene9Yy5AOUFgMKPMRFEIukIjlAkiC1clQSYS6WOFmtKTS7eVOTEFImtqdaoZSYPGTsLukfW3bZbcNw911qfJoS8GVMW/dudezWf83QwU+TB2TyGRUcYfYgXJcloUlt85UiDUoA0nQVidxgdkaCMQTMOJWWwW9Xajz0420fCjKWrA2GlbbuK4ASRkZEBAJBSoyja9Us8cXdEArAWzFGXEFG30NUvscSBUArRNKBR/ToPemVHEAH4TQCf/2CdmPwxygFCoWUdTBQyMjISdI/dADHaiDp3obPgHrvRQKJMHSYkgpqNOABA0wTrViu4jl2U3PlQavJvqrdqTUeYFCHYqDLxz5hZ3ANgpf0iIeSU1vr0lZ57lZ9z1Zgp8uB2Lh1cnkM6BmFnojUBQfj7r6NuQ7xzaTQOAkpKL7CONRLMEgwAPq226M2DlT0/T+3El1oJKAG7cBE5ZCojIwLnk6ShvQEAANCOJCDxTHGvucWIc00TTWM6hTbbRSsFQiUkTM0SalzSXHI84yV42TNOaVoby1a4+q1ssFUzMR6VkXHUwXsLJl1aGqcyyguvdWBl1+odTP25pT6hDFrUweo80kI4W3StFYiCHV2yxymCBmIL4oAWMTFhcdmmNWPnsYdjS8cBrLZeWwGwfJXnXs3nXDVmijy4zkNYbFhy4HcvU02DgyEKGoooTw6cCFM3Zi6aMgattVmEWOLgyIRszE4kL0xQnO88UAZZj8zYg02oVcISCdnkkKmMjAhB82AogUuAjwlFTO5ddgNskjyItWclhjhQGFMCQgi0I/6ufv3GAoGoK2t+0PgNAFp0QVkB2YxBree81gqq2vAdimzVmpGRQgzWwLt9b3FMLFkHTHCcVjKyarXW6KI2wmolwfuLqRbCEQUlg3VrTCCeZge/zpqHjB0G2cFpEkKSWdwf1lq/Y8c+fI9wWfJACHk9AlN5GYBf1Vrfb4/tmcp7iUzOTLfHlTx00Dcopf3/6YRaTQO1ixRpBJSMhfA3bRNtCSGgRQFCiB1xEkBRgvECvOyBFV2f90BZYfUQZucSWkHUw7z4yNh3HLT6jXMdzM9B4nYWw3UAtaag1lJZ0zC+JKUEhEiIv6tfSimIzYZw40uMm7BHVvbAio6p32qIkhk7Vy0b45SmlXVtyoLpjP3FQalfB6d5cDv+WikQJYMlqz/Rjg3WY6ORsOODhJfgvDDniwZAE7JaItKQfBu0XZsuY+makXHQcZmE6WndgWldhMudezWfc9W4ks7DrwF4ptZ61f6B/48AXmqP7ZnKe00DUioQwqaOPbRhFh7KLFQYs65KGprqiDiY9yo3cw3ASDQBWhRgRfCsppSCd7oounPgnTlQVqAZb0KJGko2kPUQsh56wRgrelMXRBkZe4wDVL8pmY5zFOJaCboGk0bNAChQEGVGEtyGgBNHO/LhahcACOehfrU2Ns6dHopuH0V3Hox3IKqhqV1RQ9YDyGbk65cWPb9zmpGxjzgQ9etACEMzWANlhc9QUcKNBzJP1oklEmK4AVmPoZUC7/b956h67AXRcRq11z1s+QtMJlBrwvzrzm2pysQ/Y4exk52Hy+B+REJnhy10Cluea78vrvRzrhpX8tfxpdGOxXFYAcY0JTeAN1/u2NPFEmkHw03ftdQ6GlNSys9IKxWEllJIKKmSgLjkAwgBLwq4ZGkAYEVpiUPfzEoTYsJpqNn1FNUAYrxuZqatW4Szh83I2EccoPqd7BSm7miuqwBTv7ZGXe3GtsouQyUWWTsQQkyXIQqw4mUHZW8evNMPImk7rmQ6haO0frXKIXEZBwEHon4dWLdv3cmYz3IIye8SSjSQ9RiyHkOMB0k3QisJVY8hxwPI8cAHrQKOOFgBNKEmPK5NJGLiQOnUJGqH6+e7O/HPzcjwIFpd8+1K0F7c23p+d/ycELJ8uXMv9znXist2Hlq/wJtgdjCAfVB5t/+YbzXq4CUPOn09dU6iYJxPti3cwoMxKCWN0JJx8LILXnZBeem7EYQV4CXAS9NlcGJLQjl4dxGc50DzjP3FQapfQ/6nCKTT3xeA2ZRkLCX1SmlASBCqzXcBpVM/g3EOxnmo38LUr3FZMloHwCxYeKcPNq1++0vm+yEjYx9xkOoXAFh3zhMHPw5Ydrz5iBa1FUxbIkAZWLc0o4Tc3IvhBigvTDaEIwCUgvAS3nUp+cUnuw0A/OgU0dL8qY/O45n4Z8w23kQIeRuA0wBeprWOu4b3AXgvgHddwbnbHbsmXNFfR/uF9FYAv6a1fp99ed9U3qlgOl5gABo6WXiYnUtr5+ZdGBgoiXYztfYzlpQx8KIAbOYDZQy87ICXHZvrwL1DBGXc2MyxAiAUSjZAPQQINYFTeWwp4wDgoNRvXA6BRITXtNZ+btCJp6FD3gNgapgBfoER1655mYEVwS6SUApedsCKMtQvoWZM0botmVqlkKIyvxvl0LJGRsZBwEGpXwCAFUTL2tgiK9GYRb8jC2XXkojGdw4IpWA2VwUAWGnE0pQbAxJQah3OJMDo1t0GYMLyFcBE0rQiBL0ib9xl7DD20ADHkvwft0/f0zr2pqs4d8tj14ormquxv8CPAXgpIeTrd+qHE0LeQQjRLeX5lpjwhg+/H7RdZGgV5qXd6JJyY0tKQcoQ9IZ4JALGOYIXhdFI2OdmXMkILN1KR0kBKWpoJSGbMZrhKqqN8xivn8V44zya4SWIagMqB9VkHAAcrPpNbw6uRl3dBjtlc5NS+tr1lq2+zl2KvCEOvn4JAS87vn6No5KGkg2UFKaOo/qtNs5jvHEe9eAimtGqH43KyNhPHJT6BYBiftmPIhlybh0Jx0No0US6hzCuZFwJx96NyRGHtsiaMOu+pFp6hag70YYnDoR6vQMA9FjeuMvYYWh17bdDhCvuy1vB1q8BeC8h5Bh2QOVt7aneAUxYV22JeD5aa2K92I0jkutGGOGz2a0kzoWFaCO2Dj/c2D0S4j+Xe5E0tZ0FhqLTDcRBa8imAkbr0EpCVAPIpjICS1aAd/oo+0uQzRhaNnlmOuPA4CDUb6x1CJbKxKfAx9MIgILWzm7V1nCkiTDnKbAgngDj3GiVnFsa47br0LEWzcqQhTGDlg1ENfSbAIQyFN15FL0FyKJrX8uapYyDgYNQv4CzYw2LIEIpVD32WQ8OrDsXaSJYGPW13QZPIABT8LxM3p/YtQLb6humoc5OhxkZu4ptyYO1ibtPa+3cHT5s749jH1Te8ZiD23WkAEA0tF2YMEb8+IMmdnFi/i2glJi56+iLyLxmRpWKbhdFp+sXH4QyM5oE021oxgMoKUDZBpQVh7mdE8oFWNk14xCMG3FY/gLL2EcctPq1v5P9LOOeFkIe07wnkzBNvKkBiHE8IzYXwn+eTZTmRYGy2wXvdE2qvK1DX7+igdAaSgoIW8fuRgixAXI9X/NaiZzTkrGvOIj1azIcgp7BG4qUxrpc1WMQ68Lk6senUEfiargE6ijnAbHBCLUOStNIQ/RF0U6XdujmzkPGTqPdETviuFznYQXAO6Pn9wI47b6E4rGDtsp7q2NPF2saaBplveIB120AwuIDbk4aBIBOFh6cM/CCg3HmHZqcsJJZ4lB2e6C8gJLC/d7GT76pIJvKLixGfkHi3JZcKI5xm6jRjNatBiL/x5axrzhQ9VvX0o8emr//oV6dbbLpKlidEjGaB0qZr1/KmCEPvn4DcSi6PSuUjhb9Whv3F1e/VrgJwHYMOYjVQWitTP2ON0Eoh8xjhxn7iwNTvzEIL6Gto5L72+eck1zHwXXu3N9HWnYTsgEgkIeYICg50YWIyQHRctsuhCYUGhQlzRt3GTuMQzZ2dK3Yljxore8nhBwnhLzFvvRSAG+ITtkzlfeS7zikSdPx94gXR9sxB8AsUIqCo+iU4AWPRhqMvoFxDl6WYJxbolB7/3htd0dgk24ZLyBJbYPiOiCMg1mxGLU7KKIeQTYVlGwgRCYPGfuHg1a/hCAh9yGmwXYYtDNIM8cB49DEC+br13UVGKOB+JclqK1f0TR+rklHu5um5s34BJMyGCDwAjTaERX1yCTiygaiyZqHjP3DQarfGKoeJyNJAKBFA95fMJkOLmm67PqOA40Igct1iB87e3M/qtQSShOd/5ZmHB7YMcGZTJZ2IG6OeL9xuZnLJQL8ky9cRLfL3fl2TMml1tp5atdVYBRFye2tsLuW1O9cUsaMwNLOSSe2rXYb1HUnjK2rJQxWRN2ZW0qCcSgvjTYCZkel6C3iyU/8Ob7xn/wKnsjfexlPA5dJoTxQuJL6/d5XL6Esme8IUhpGCc1nhLqmtn7LToGiLMA4Mzdm641RMFu/zNbvRN6DHWkydV5YxyUGVpQo+wuB+DM+Ub9lfwnrT53GV3/Tv8OjmUNkPA3MYv1ebj3w1F/+f6hWnoKsK/t3z3UeGtCya3Ic6rGxQe72Ucwve30D4QWgVCAMvACxpOJy5GE7aOt26ATTghYYaI5TN19/VdcgIwNIdLXEPtcAsPKZj17zZx+/68XJZ88yZsbIfE0Dn31sgOfduehHHxyc80o8vuSOK6kgGgElpV1IhM4DYwys4NBKQdSRNSMh0Q4nA+VhdjqcYpNtKQUrOiH/QWvvYbVw8mbwmf9PJCPj2rGmgc88uonnnlpIhNNAvGAxHYfYiUlJhaZuIIW05CF0HozWgYNH9evr0tYmpdQnTXM/1ggQEkTVjji067e7eGKPrk5GxmxADDegRAPA6IjMKJIC6/ahReNfc45Lsh6DOl2g/Qw1rkNehKhN3dmxQf+14E9uCadjkEj3APvtQSgIFIorN5DKyLgyZM1DgpkhDwCiuegghPa6BjgSAdCIOChrz2qE0jIINJndyZQmbdrNUce7l4xzaM5RUGoIRlNb+8eub9lSVvgbAGgoEMLAeImyt7Cn1ycj4yDD1O/WwXAGwRVBSYVGadMxpARSuvq1Y4ec+fr2SdORe5rrLLqFjGgMwXAdRFe/zBJ/QqivX+oCqzIyMjyUtVzl3X4kiLZ/H61dKy07oLzwIXKOYIjhuqkzXhiigXSESYsaUNJ0IdxCjZdpF6I9d05bxwgF1Rqc5Pn0jIzdxEyRh/Zupd+d9DatxIsujWe8NPPU1NqyUgpC7AJEKigpIQUzu5p2J9N9Hou84qUQaKoxqDDjDwDCuIMXXBKjjYDLiGB+DCIjIyO4pcVcId4IALR3UnKZD4QATGsoQkBidyZGDekXEpwL31V0n0kpRdEpQakxLhB17buPLuAxrV9DJuL6JWymvh4zMnYd3etugXrqEZOZZMeTKC+gxoOWGFp5G1dYATXlhRlvAqB5CSgKXRtthFbSOjDZRb+zdlXSdCEcgSDUk4SMjL1Edt9LMXN/HY1DCzxZcN0IIFqYKAVnlGL83QkgAULcDqUCoQSCEFAqvAsTY9KPLGlqwqeUlJZkCPvzlP+SdAsMv/BgBQghIUQuq/MzMjyo1Tm0LYzNYj/UswtXjDcDgh7C1rBQENS4N0lfv85imdo6lFCWPMjGjFpQxoybmtamdmkgC6bbYOpX2fyHjIyMAD6/DAAhKM52EJyA2i2wnI25S6NWogHr9m29FZDjAQAkOgjvviQAUrLQ+XMEAjCkwb3e9ncGQNzf3DwunLHTyH8PEswUeWgvPtqz0s69BYjutTKdTks2/MaG/cJhnKajSoz6ACulNJjvaLixJgopGsimBi97yTYqjWYzlai95WtGRoZzR2vXbzxyqOF01444EAIzytAyRHBkwhEGB8ao+Taw9es/i4bzDLlvwOJ0W0KS+pVNBZ3rNyMjxfx1Jk3aJUWXHajaBKVqNNBaQo1qUFZaQqDsCJO0GRBllI1Ugjr7VmWIgAaMravTQCiE1Om29mGbvAeGvNDLyNhNzFTvrxYaTRN2853GQSkNKTWkVMnNvK4gpYaSClJIq4PQEEJOOEuE1FsD4wZDrcWjG4lw3QgBJRt/M4sVaboN9kYZx1tfl0WXGRkAUDVp/QJhkR/qtv1cpcekCjelvc2r/TBPQgBTv8QGyxFrgKC1hhTCk3uXMG1CHdP6JYzje7/8hr2+TBkZBxZq5XEAZoGvbdq0GG1AjDYgm7FPoFYy1FUzWIWqK4jx0Ni8WsE1gIRYwOqQtKvD6P5ySLMgcsc/Y+fh/nu+ltthwkyRhzPrEoOBET26hb5bfLj76Y+VfWyIBhKrSBprNAEgsXL1O5aWqXiCYb+gtHtdSWjZ+FwIrTXK/hKe/7Ln7celysg4cIjrF4i1SVd6U76mneMSsTUcdx8oNU5qxpY5rV/zg1uLC1fXU+r3eS/7vL24NBkZM4HrXvhq0MhwQIsG0oqoxXATWjRWD1gaciEaUFZ6YiBtRgS1NsnJCLDLjVAKuh6nPzjuOjiCD5jug1ITORBUa3zk4ad281JkHDXY/9au6XaIMFPk4c/WASl1S3CJiEAgIQ7htUA23AgD59TatgYHGHcMlljEguy4K2HOc25LIR8iJhZaK1BWoDs3t7cXKSPjgMLVLxCT/+n1G2o21C8AT/oZo2FkyfEGX7dIx5SU8jVsBBRmbppSZkaVIi1TXL+EMvCynPZPycg4snDaBtmMUW+sAABUU4XjxDoqaQntEqFtYCO12Q5e32A/j9i8iKloE4f4cfScaOmfE61wrDNTy5uMjJnCTGkegDjAIywoApkwM9TTXJncfDSNFh3U+sBTO9bgOhGMsWQns00cKGNe/+BuWisQTWC6rA20HYnIyMgIcKJoB0cQ3GO3+I+TqF39mtok3roVVkMRdxFdMFy8KRB3DU3gI/ebBMmXBUxr2omlVa7fjIwJaCUhRhsADElXdlyJApA1fA4Edc6ElkzQ6BYnU8MGxcWEIrFgdeMeMYlwoultRpQ62a41YwehdzDl/DAkTM8geQiP40WHPRoJpoOo0iXZEhoe+64Dbb3H5j1MW1iYxOnCJEtbwuDn2AiBsuNLfo5am93Oe+eADw9275pkZMwK3Jo97SwEYu7Qrl/TaSCe/HvSb0mFeU8gE9PyJGhsr0yoHzcEAGg9vX6VwsvngQ9u7v61yciYBRTzy2ZMabAGQhnEeAQAPnGaRs5JLnnaHLdW6KIBKx1JsPdWLL1l9yGGs2u9DDgyecjYOeykZuEwJEzPXF8vJgzx+qCdWusWEm68wS063OP2AsMJo6ntQLQXMv44Y+FL0HYXRD2CrMcQ1RCiGkLWY8h6jHqwhutPPRevvTuPLmVkAGHss21WsHX9TicOnvQ74h8Jo31XIfowktQvtcYHAko0kE0FUY/QjDfRjDeT+r3l7pfiS16Ywx4zMhxY2fVjSFpJ8G4P5cIx8N6C1zEo0YDwwiRPO1tXJUGs1sGMLxW+O+G6fGlWhExF057otzVLh2+ePCPjoGPmyMPpJ0eR1WN4PfjAI3QayGTHIQ6T84/ppP4hfG44xyxKrOuS/YKUTWUWH9UQzXiAphraxcgYzXgArRQYm3mSmZGxI4jrN8a0+g1jhMFq1WkcQh2n55I2A2nVrx+XUIY8yKayxH+EZjyAqMdJ/cqmbjcgMzKONG76wq/xVq1aKRBW+L+HgHFi4v0F+3e18O5KZlyJgvKgI0qE0g6uk0iZ70wkBKK9A5wD4zL2ANltKcXMjS09tqrw4lYoXEwIYoLg5qeThYV9L6WtbkS0YxnPWPsZarvwIISYL0opvO7BjTcA8LsiUjS2Pdvdh6uUkXEw8diqwotbQXEJ0W/VcMh2mEIYfCfRdRQmNwbijqIPndLadw3d87aDmutK2MMZGRktUF5Ajoc+ObqYW7ILfqODYJ05nxwNBKG1WUSFjgMre4l4OsE0vcMVjDYRrUDy2FLGTiJ3txLMHHkATBBUWHzoZOERHodgNwDRMZp2I7wdK5L3uJ3KZDdTB+tXKRovxg4OLdZBRknIpoaSEoRxXH/9HIA8NJ2RAZj6BZRdlE/Wb5sAAKGufdchFkjTcA5i0uC6DcSZLBh3FiUliGgMWYiEl9Pql/ICt9y6DGBjry9TRsaBBe8vQNZjELoJwgvwsms0DrIGRQlCWLBh5QVY2fFuSzHiLgRgR5uAVDA9DbHuIa7jac8zMjJ2HDNbYZPCaLQWHWgtRoifk467Cn5UyY0vUQLGmPGJnyAOyncdZFOb2eimhhKNCY6z3QbZ1HbxISDrCi941T37d6EyMg4YHOkGJms1JRFB+zDZUYxzWsLjZEMgIQ5R5outX1GbkUMlGt8pDK+b+hV1hRd/yav383JlZBw4aCUhqyEA04GgrICSNUgU1uZ2alnZid43ZffWEYVIRwGlth/zmEYQpuQ9PHrm7JX/ozIytkEeW0oxc52HRgHDYYNez/zq7d1KagmBS5eNnZYCaYgWIwlhiNKk7crFLThACKhS1t/aEAbKeGucSUEpaYiE/ZJUUhhr14yMDDQKGI0Eut3J+m13D31CdKR1CF3DFmloEQZH/E0nQUHb+tS2a6iksLPWNGQ92JyHpH5Fg6Yab/dPysg4clA2AI5QCjkeevGzkg2IlnD2rIAhDP7vZCSWnuqspFQylpTYt7bRznwgJk+CUEATCqo1OMkzhxkZu4GZ6zx8bAScvTBOhJFxF8Lfu3npCMRas5pk2th9KRCGRHDpxxiUJQZm5EFJCdE0YYfS7VxKkQxIO1EmIQRfe/PMXeqMjB2Hq98YqcY5HTmMj8W5LDSqY8rC+FI8qph0G2xInNE6CIimSWtXNL7OTfiU9vULAN90x8zts2Rk7BqcDausK2MKUnRBCAMruqCstOTA6ggBr3UIuoew8HeCalAKRKnT1/w7agWKTB4ydga585Biple002ekw+vmnCgMLhJGx6TBjS+14YmDF1S6xUfjFx0JiZDC71i6robWGr3FY/jS1962l5cmI+NAY3KsMN4ESGvYiaNd1yEWSU+zXQaiBOsoWVo78u/Gk5oaojYjho78+8wJ+72gtcb8iRvwZV/2nD29PhkZBxlOw6CaCs1gDdXaBZMoHY0dqdqkThvSQEGtLgKAsWC1ZMKJrAlloLyc0EFMYJrjkpKTnQggk4eMHYMjvddycyCEaELIO/bvX3PtmMnttNgjfpreASQdf/ALjtaOpT/fp9kiWWiAEGhCQAFoQqCkTH6+2e1UAOPmHACE2kRcymCMYgh42UF/vren1ygj46CinfEApGQ/7h7EnQafDj8li6X1A8zPUMrsZioFRQiITBccRCmAGS2TCY4jAFF+5MmNI7qNh4yMDAMlGrvY59CKQlntECuYSeKN1vFtO1bXjZiaJt3CZUPjHInwrkz+f7zj0m9/7BF8xYvuuMp/YUbG7iGHxO0TVjYkhEiFV+1QN0IcSQj3bobaIU631RqRZWM06uDGleyupRQCSsqwi+l0DtE5se0jALujCdw+k1QtI2NncWkzrd/22KF7zBiNug6hwxCLoB1Mneqk4+DrMdr5iWvY3eKxRHcfQzQ1pJC5fjMyLJ75Vd9l3JOKLmjRAS1SUbTWQatAy67XP/isFZ+3IqdbYPpxp0AOfNZDGxNdiPB5VGucOt5/uv/MjAwPLeU13w4TZpI8/JcnVbL4iElA7NDi7RyjRYknC24cKVk0hBnpeLHhbjJeeMStKEs43OcbUaZxanG3Z93zErzyliyczsj49SdC/frGn4XTJaVGB/D5LEA0kqQ1tNJez5CQhpgsuPoVRu/gyYSO3xt0Du36bcZDPP/Vr8UXZfaQkeHByq4nAzRKi2adPmjRBev2fc6RO8eBbNFtCGRBGS2Eu4/hxpZcTkv8uqgBK9qGViBa4Rg/XIu2jP1B1jykmNm/hiFjoTU7TSdnoE0nwAbKaQ2ltCEYUFCg9h6g1pEFhJhJSTc6kYxJWYcmwIi7vCgz/Iehld0ZVSF0qrewBEZnvlOVkbFjSOu35bLUHkmyGwRK6bRutQYFs68AmjCz4EA0ChXXr9ahhgkBQayPsMGPOugkHIpu3r3MyIhByw6azTWbHM1AWdAqOGIB67AUw2Q5TLotxc5KWy20tHabDs7eVZouhu1MhNeN6xI0zbqHjIxdwEx2HgBgfSPsRsRCS3PvshnCwgAadkdS+9GisFOZPpbSnTfZfYh3NxNYi8dEYA3XiZCQosE9Lzix25clI2MmsL7RTKnbKSdqmFpUyncZlErrVtnun7dZlQpKqqiOQ+cw7jQmHcPWmFPcSXR5LV/wilv34MpkZMwG7vqGfwpmSTXhhV/wO0tWv3nWuieUQYsGKu4cxO5LU4iDdt2Gy4wt+dEmrcxn5qTpjJ2CVtd+O0SYWfLw4OPG7nHawsPtUIaxBhcOpcwIQ7T4iM9LbFkdYYje746bn5d2Ntoi0DjtVmsN2dQ49fxTu3tRMjJmBA8+PvZdB6BdT4Hot2t4GoGAq/dYnxQRAXfMaZnsDww/PNI6eUQCbq01RFPjjuc/ey8uTUbGzGBipMhararodWJfI5T6IFWddOqjUaXWmIcStddFaPs+LWpo2fguhNYKWjaeXMTaCKIlmJJ44LEcFpdxbchjSylmdmyJUYAxYhYPFlrDOKuAghAN2Hsz4GDWA4wQxOMPoDTZfdTRgp8QYnYvCIE28w2TrjD2B/s0W0JM6BQAQNnkauPaUnQ6eE4JPNga1czIOGpgFCgKOqFdcnWpCQGgoLUdZbI1DChQ4sYF4Rf+tjxBkBJ5U/cEihBQex4wSf5d6JwbabIn2TvzXAmBuzvAJ6tduigZGTMGQhnEeAhCGaSS8H/5lAItO9CiBngJQinEeAhWdj2RcNkPQDSyNCUULt6WI0CUSC2hKSKnJTa1M0G0wnXF4dr1zcjYb8xs56ESQNO4nQdEHYK4q6CSHctpIkvzfvcc5jw3BuFGHOxCZWIcqeUJTxkH40XkQc+9BaSSEkvX34hv/aLj+3PBMjIOEKbXb9QNjOo56fzZGlWtrkNwPou+BzRaNRxvNIROg6tfZkWfvm4p8ynySjS47vY78Za/e/O+XK+MjIMIrSSgJWQ9Np0BHRbvrsug7LHYolUr5bMeks8CoEQdOg6A70hMhdM8OFAWdA/hg8FwuHZ9M/YeufOQYmbJw/tXNC5cHAEAkvEjuxDxiwqVLvwTO0f/errIiBcgyagDwo5lcHcikeMEB2XMj0TEAm6tNRgvsLDYw/Uze9UzMnYG71/ROH+hXb+TI4dJrSakoeW65LoQsVNaRDAQ1SuAMKLkQySZJ/2uqxg7tSmloESDTrfI9ZuRYcF7CyCsMPUmGqi6gguLA5B0F8zzdAHljrdvhmC0xpZaTkyxjWtMICZ0DwCYkvjtjz2yexci49BjJ0PiDgNm+s+gG1mKiUG8+xiLHoPjUto9QPw80joEK8fWOTFpiG4uzMo9tif531UrhaYa4TkvfT5uCpbYGRlHFu0uXtpp0FF9pjWcvjc8b783WLIi+TkeUSBdSJonE+4w7gdVw0288mv+Hp6ZjZcyMgAAxfwStFKm884Lq3lIcx4csZDjIVQ99oRACaNTUPXYfoY934qpJ7QPtosRC623dWVyBAJmdOlF1+eg1oyDgcOQMD3T5OHRszWkdIuLqIug269Fi5EW0uPpCJQnDZG+YcIOtm0RY1um8Q6n+7lKSnTn5sGyY2tGBh49W/u6m1j4T6lhPUEcIq1SWyytwvkAQidwG0tnc1rqwJDoJ6TE5spZNIdrAykj42nj9i//B9CygaxGkNXQdB6U3XwTjRdUa2VGm4xYOnQRpCUOyh5T/vyog1iPJ8Y+fLjcdiNNFsSOUnXQbHteRsZ22MmxJa010Vq/Y//+NdeOmSYPv/WUQtPI1uJ/+lxz8hoQdSGQ6Bvi+ehYjA1gkkD4BQiNfp6Kf9jEbicvO/jm19+wg1chI2M28VtPmbC4mBjESLuE4TV/394waLeJ250GCz+SFImk45/Z/vntdvM/+KpnXOs/PSPj0EDWxkFACeEX9a57Z9yRDGGIg+TcWJIDodRqI9yYknVVsl0GY//K0seUAnZkmBDqbx7RmBO0SvKaMjKuFlnzkGKmyQMAjMdi2+Mxf4jD4tJ56SjnQQbP+PRzUpF1vIOJdgci+gKLCYzWGpRx3PHc23fgX56RMfsYjUz9Tlvkm9eR1I+7b48iTQil2zUcE/lIk2RGDdMU+qQb0SITjBe47a5cvxkZDi/63p8CAPDePAD4DkMzWIWSDZSsPYFwVqvKdyHcwkr5eyUayNpasVMGWKKRLL4i8bXXOzhy0RZMWxCt8ODj53bjEmRkHDnMPHl49MwYjNHJxYLFtOCptgZi2sgEontEz90tHlnadudSSSjnPQ1ASYEbnnkn/oeX5PnLjIzHnjL1C7RrZ/r5be2SI/XtrmH7Pe2aTkaWohGldv0qW78uQV6KBjc+67n4Z6+c36lLkJFxaOCclFRdGXJgSYODd2CyegcvtPY6CNNpMAnVrtMQLVPaeiTnrtSydw0/0OgeiJYgSmCZbb/ZmJGxJeyY3DXdDhFmNufBQaWbi/7eL/C3QbwQSQkAgW9RYOuFDDCpbdBag6iQqOnGJ9wCRdQV+ssnsLhQAhhd1b81I+OwQYXSSOq3vfk/NXxaa7jwWO+CBlezBKQ1DhUTCE8SWqYGACB9/crULIFIiGqM3uJxdLsz/9WZkbFjIJRCNWOAOJG0EUwr0XgDEVWP/bgR5QBQ+Pdr0QCU+RwI9xkAoGsJwkubA6FsnoMC4YXPeiDJtLC1gYVMvjcIUeA0123G08NBHDsihJwC8PUA7gdwD4B3aa1Xr/ZcQsh9AB4C8G4AbwZwWmv9vu1+9sx3Hp5al9jcrLckCm3B5YT40tk+Wm95856ghWh/2IRDk5u1jkafpGigpP0PrbWrqbVJm773NS/Y8WuRkTFraNfvdh2HaTUcdx+mdSXi92/xwbY7aN3VpLD1K5L3xj+nGQ/w1p/6Tzt2DTIyZh3l0nWGOGiZaBto2TEkQpqOgtNE+JEl22mgZTfRSbixJQdnh054EfQOEbRW8EnTrdcBhA6Eyp2HjEOFd2qtf9wu9N8D4L5rOPc+AA8DWL4ccQAOAXn4kzUTNnWZJkOKaFwpHnsApo8uJK9FJCG4vMikNWvON19maH+eUmiqMRavO3lN/+6MjMOAP1kDhNCg9MoL2JGEyVC4SUvlLes5HnVqO7a0RhTj16E16tEQD//Ff7m2f3hGxiGDlo3vPBDKwLr9xK7VLf5Z13gdy7qyrkw15HhgNt4saXD1SHgJWnbByp7pNMQ/b5oIdVpgnBVgA8Z56dyZx3f8355x+HHQch5sJ8GnDmutT8N0DZ7OuX+ltT5mbz9+JT9/5skDAFS1tDPMqTja7UxOQyANLacmHY5N7m6mCw//H0T8M+wsdXvx4ToWSkk04yF42cHPvPm23b40GRkHHvUU8j918d4+bruFE50IlT6Hr9kWcbB5LmkIpDVAaGkk3GMlBZrxEIRS/Px3Pmc3L0tGxszg2f/d270DobNbdcnS7QW+Ox4/dxoIp4Nouyu5e/c4mSGPyIGHIy1uE8//sOy6lPH0cADdlu4BsNJ+0RKFp3UuIeSeK/3hh4I8/OGD463HEix01G0wC/9oXCkiB+7YtMVHezxJSRkJNc0x48DEgq2rS6l1hCRybJpb7OPOYrvfOiPj8OMDnxpBJ9qHUMuOiEO7PAiVdBriWlYRQUBcu66W4xpukX+/CUAIKGX+l6HOTQ2t0UPRgBcczyn3/HJlZBxMEAbVVIDNVaBl148ZaSUhm9BVoLyAdsFxlkxIm+eASC/hxpXc+6Y5Lnk4EhGTifh8JY21q1b40Okzu3MNMjL2DscBrLZeWwGw/DTOPUUIeT2A04SQ+66ERBwK8iB1avnYXny4zkBKEjSkVIEsTBCGoGdIEm/R6ky40SUZvtio955u2bnCkAlKGbTWePbL7sVr7sjsIeNow9SvDYfaZhNAewJh6s/UbyD9aG0QeB2DijQRCHUdjywqO34IhBp1lq40WqS4Y0pKPO9Vr8EX3ZnZQ0YGAPD+PGjRAWCJQBQQBwRRtWrGURicnHChcfqHJCvCnjdtB3fqzu6W7ktG93BH7+CJXzMONnay82ATpt3tHfv3rzJwWggroH4ngF+73HsOhfXAJyvgledHuPOOxYlgN7NgIOaLx442GT7hHJassxIAKEAT97oCiCUfRIGB+c8LI0gmDEcr5UxfjGc8s50HQn3LNHVzUpBNDV6UeNWrbsfPf+azu3p9MjIOMj5ZAa+8MMap2xchZbqQcPWrlDb8m5jugGkSRLUL4kk/KKA1gbYbBGYDgcYf6gkEJuqXgDCejB/aA9F7Tf2KaoSvfPMr8a4f/qNduzYZGbOCxWe+AKsPfji8QCkoKyDt6JJCGg5HWZmKoBFGk9xzVY8tmZhCBmz9bov4ffHmQB5dyrha7KBmQRtLz6kghLwFwJ3bvP29VtA8rcswrcOAy51LCFm2xAFa69NbjD4lOBTkAQBEayPBjTiQiDBQatYW7YWH1uE7iNhFiE1lMEFSNkfCnxw9dgsPCuMaGY8rGZYS/U52t5NSCqkbjDfXceKmkwAyecg42phev9rWrk7q2G8AAHCkgVLz3e54v9KmKglJO5FKab9wcJ0Ht/xI69eILbUOv1hc61I3GK6vgrEtdjgzMo4YyuWToLyAGDegvICqK2jRgFAGWVcgovGiakIpeH8BrOhadyUzyqQEgPEAEvACaa0U0AVY2cpGckUfjTY5kbSWTSAOzs7VhccpBaIVTj95Dqduvn5Prk1GxpVCa/2uKzz1fkQi6Oj9p6/mXDuudB+Al17N73koxpYA4JELwo8uxQ4sYYTBjh6pSPyYzE5PGWWK5qbN50aiy2jkQScjEgpKCmP16BYpsdbBnyMh6gpzy8v4wdcs7dt1y8g4CHjsovBp8ZP1O1nHrpbD+FH7eKhJIB1VClqJqHYj7YOSEkoK3zWMtUqx2FpUY9x41/Pxf7/luft23TIyDgpO3P0KM46kzYhGvXEJ0obFAUH4rJoKshpBjoeQzRiyGpqb1T+I8RBiPEze4x3R2qNLUzoPiT0rMDnCRCmIEuiRPLqUceU4aILpNkmw3YJ3x88JIctXcO6HAbw9Ovb1MFau2+LQkIc/WtWoaxnNRMf2jUgIQlh4pJqGaQ5LHonjivROLTEpiPUPUgi7AGkH0AX3FqUUeNnB8rEelq7GajYj45DhA5em129ay9iWRKR1bD43zo9wounYZUm1CIUjBkoIk9WyRf2696+fewKXLqzj+kPzTZqR8fTxvL//wxDjEZwtZb1+AeOVMxCDNUMQ6gomQM64MonhBpSzZ9XS6yQcWNkF6/aNwNoKnj2c45JS4X1TnJcIoaHr4ALmtEShBf7k00/szoXIOHQ4aFatFm8ihLzNLvjfqrV+a3TsPqR2rFPPteNKK/bYWwC8TGv9psv94EMztgQAn3p0iJfeXUTjDuZ1M7KUjikF7QP8LLXTRJjvJ5IsGpTSIEoDQgDgAJF+LlrBLCoY7OiDdVhS9sNJD1ZlbwAArfNJREFU9MO0UlDRzHWNIV74qnvw4j/6HfzRap7DzDi6+NtHhrjneYtJ/cYjh34sCWktA26syeZFTARIwZN+4nRMEEbTYOsXWvvRQ0opNDE6Kee2FLs+SSF8/VbDAe553avx/A+8G+cu5frNyKhXz6Fevwgo28ETDVinh0KbcDhqNQ60MONFCrDOSjYbQtbgvQUw69ZEeWRKEOkcXIo1AKtdkommwpwvAft+n/lgC53KGs9eaI1CZWTMEGxHweUyvKd17E1Xce79MKNNV4xDtV+2Ptb2jzz8TuW0nUy3y+jcWqRUkDI4LrURxpEktNK2syC9VatjlVLKsDMZdSi2uzVjs+vypjfeuteXKyPjQGFQazBGo/HBdKQwvkmpE7clKVUiR3IkwY8tqfhcCSWVvY+6ELbTEHcXpO1AuJsUwt+UlKhHI4hqjL//5jy6lJEBAM1wA/XqechqBAAQowHEaGBSpUUDQiiajUsQo00oIaBlAzHaBGBtXIuuT6hW1r41tmtN8h4c7K7utNEQLWqje9AqGmUySx+CXdkNzjiEOGhjS/uNQ0UePr2u8cSZQUQIFIRQ/rFbcEg5fZ4aSF2RAAAaZmHiFh8xcXCLj3jEKSIfEyNOUSci9owXdY3b7rod33rqUDWCMjKuCp9d13j8yU1oDVur2tavTmo3kP5Q59MC5Xwmg5Rh3MnWr3R1HI0duvck73djTFYTQSLrVvf59WiI57zyVfiR1x3bu4uVkXFA0b/hGYZ4VyNUq+dRb66iGa6jWjkLMR4Y0iAb1OsX0QzW0AzWIUabnhiYUaU5P+ahrFsToQy07AIIJOFKFmUx0UgC4wAwJfG5M2d38p+fcUhxQMeW9g2Hijw8IU1arVkw6C0WGvHOpfYLD2BS5xAE0ToQB0ckpL1FokxEhACI563Dc5f7wBgD4xyMcygpcezGm/DM2+b28GplZBwsPCoAIU2tTBL+rUh/6DAC6TgiXNfRdxlUUr+JZglICL35rGDPmny4JRCUMVDGIIVAp7+A+YXuXl6ujIwDiRd///8B2VQYnHvChMbBjPLKagQx2oQYD0zytGjQbK5C2sR2VnZRzBnzEDkeRF2GsEzx2REtEXabQCTdCcomLVuVApENiBLoINVZZGRkXB6HijwAwO891KBpYgeWyRGH9sIDiBb2rQW/H6GwCw8V72J6EiGn7lwSt8Bo7VQ6BkpbBOLul1zWWjcj41Djdz/boGkmhdNt4hDXM2A0TbE42tyHsScdjSspFQTPrqb1NvXrU+Ldh7sORFS/q2cexTPuyqOHGRkO5fwCZF2Dcg5CGJRswIoOaNExbkuWWLBuH/O33gU+t2QcmKzrkhFIM1BeettWJWrz4Ulwo7NkVeG5vcVdh0Q4rRWgjXCay0weMi4PreU13w4TDh15eEIC48r8n9S2YnXCybjb4OB85JOxhciW1Sz6U/vWeKShbQvpOgzUJmXGJMJ/vtvhtKLMW5/7PPzAvf3dvDwZGQcaT0hgNHb1G7RLjiQ4IuHrEMEYAUiJg3diSuo3slp2mwFSot1BjLsLLu023lhokwwQgpuf/Tz8T1+wsMtXKCPj4OOLfvpPUK2voRlugnfnIcaboKxAtXoBo/OPQ4wGkNUIrNMD781jfPEp1GsXUK2ehWzGZuxpPEw6EEAaIqdFA1WPA6FwsFkP7vEElASsDgJSgKgGF594dJevSMbMI3L3eto3i4OSLH0tOHTkAQAePlOB2WC3yBl1QnzZnm9WylmotmwgW6NMsfjSLULi8QcHRyDINgQCdgeTUore4nG84rV340XZACLjCOPRszWKIq7f6cLpuNySc3xXQtmaDqQirt+Q22C7gW2zBDeiZOvTEYn0FHOcEILuwjJe/toX4J7M/zMywMoSlBcYXjiD8eqK0T6MNlFvrEI2FbQQEKNNyPEQYrRhdQ8KzeYaxGjDiKd5AVWPIccDHwanlfSkQYk6sXdtdxpiOL2D1ioVTysFogQ+88S53b8oGRkAtNZEa/2O/f49rgWHkjyMGtNdcMJkt9hw4st0VjrNgZBSh9noaIcxDYeLdzOdxkJOjD+4DgSNOhAJmbA3xgtorSGqEU7d8wq8+q48O51xdFEJU2Ohfs2mTdOoZFzJ1e7UDAgZsh7iunU6CB8KF2U/yGj8MB5Pam8CxJ0ItykAAPVwA8+85wvwmudm9p+RUS4sQyuFjQsXsLFyCWtnnkC1uYHx+qpZsHOOen0F1er50FlghcmAqMem82DdlgCjc5D1yBOHLR1trLOS1moqgUheU9KML8kGJ9TGXl2ajBlEdltKcSjJw3svaqxtNKCUTOxcugUHMEkcYlLg0NZAOARL1qDCd+FSfhczFlpGn+eElpTzZDezqUaAVviiL/28Xbw6GRkHG793QWNzIMBYbLucBj5Oq91AIia7gIbIY+K1tGNhwx1VunEQO7C5DoTTOpj6ZYb81xVENcTrvvLzd/0aZWQcdLzmJ/8Ioq7AC47+4gLKXg9lfw5lfx71YN2IpasRRhfPQI6HoJzDpFMH7YIWjfnbanMgCGWWOEQjILFoWqlkkTaRNh29prWClo0ZYZINyCGbSc/I2E0cSvIAAH/0mQpCuF3KeHTJHI+Fl26Gug3SWvQ7xFkOPgMiXnxEOgj/3iixzo8wMQbKuN/F1EqhHg1wy7Ofh3/+qjw7nXF08QcPjo3RgdI2VDGtX0cq4k6iQzA/CHkP7fpNNhNU0D64DIfEWq/1/kTHZEeaCCFQUqIabuL6O56Ff/X643tynTIyDjKG6xtYuuU21KMRVp46D1Z2AADV5jrE2GgeCKWo1i6gunQeSojk/YQXoKXJfZD1qJX54BzT5GTOw1a7vPZ1J54mhAaCIQVWHn94h69AxmFBtmpNcdlgAULIPQBeb5++DMA/1CbOGoSQUwC+HiaZ7h4A77qSY3uBgTRe8ab7oGESo80x97ythTC/N2ASbMN5DlprEB2OmdEKBVCz8FeEgNhgKRItKKhbfNiY3AlHF0pBGQcsgejMLeCF996Jez/6UXx4sPvXKuPwYpbr13ULtAak1mA0bR2E7gNJCETbYTWcbz/T1b5SUNKNJdl6jkeYCAGREiyyZ3V5Dw7OSpLxwnvE8k4Pz33xKbz8L1fwwc1dvUwZhxyzWr8O/cUFPPSRjwEAGqFx7qGHcONznoNyfgHNMIimxWgTojsHaskFtEQxtwzABMWZB9K7LoWwt9iCVZnceQGAKhC3unHuSxGx0DRoIgih/nOIqHD6yXM4dfP1O34tMmYbh23s6FqxLXkghCwDuFdr/eP2+dcDeD+Al9pT3qm1foM9dhrAfQDeegXHdh2PCuCJ8xXuuLmHpjGm726Gur0LaQihAkDtTqUGpZOC6tRthSQ7mCCuywAoSsMok1KgOoTDgVKQKW0OYgkEoUYoetfLvxDP/s2/wYcHYuLcjIwrwazX7+PnKtx+UxfjSiXEXykCSk09GgIfsiHMTmIcwug6he79k2NPvvtg/q1Q1HQhqKtjV/uWQLRHogBYYbUZY1JS4K6XvwbP/vWP4oObuX4znh5muX4d/u67T+PdX3oCAFB0SiipsHnuDOauuwFKCIjxCLw3B1mNUK+vgPACWkkUc0toBquAzX+gvADvLwAC0FNyGaalUPvXtlj0ef2DO8e+f1luAMjkISNjO1xubOleAG+Pnr8PwD2EkGW7s+F781rr0wDeDPhdj6nH9hKfOi8xGssps87+95rq4DIhnI7sXl1oXKJ5iOYp3My1FALSJkv78SXKwHgBygu70OAJISGUghUdEEJQdPv4777tC/bsWmUcSsx8/TriMK2LkAql0wyIJJslsWyFDX0MgmroVO/kkqi9havLZaEMlBemht3IYWucifHCdxK/6TteuzcXKuOwYqbr12FjbYjTD2+AcY5jt96Gsj+P8eoKKOfYvHgB1dqK70LI0SaajVXUaxdRb1yCrIbmQyiDrMeQ9ThkQABeL+gE1Mn4kh1pmhCrui4DoQAv0xA5fbhGSzJ2EDto1XoYsC150Fq/D8CbopdO2ddXYVqhK+332C+u7Y7tGT42AhqhkvCotlg6fj2eg26n2yqpEgKRiCp1qpkw9q3S3+J5Ny+Y5tzPToPQZBECAEo0uOXuF+OHXru825cp45DiMNSv6SzYjp6erk2aZuUqhDLuakImBMLpk9qZD9GHGTIR1a+aUr+MF5Hz0qSXvGxq3PzcF+NfvyFrHzKeHma9fh3+wQdHoAT41CfOWuEzBeUFqs11dOfmAAC824OoRpDVCM1wHfX6RW/jKusxtLVkVaKxFq2NJRFqouvQJhBXCyKbrH3ImIBz8LqW22HCZQXTWuv7o6ffAODH7ePjAFZbp68AWL7MsT3Fxx+rwFgqeGzbtALhcbqLme5eKksiwkIkWLUmCxG3mIkXIFJCSeFHICjjoQPhvOPNtigAQIoGvOziRa947l5fsoxDhFmv3489OkZZhK8ppXVUv8EFzdXx1CRqW8NSKkgRarid+QCddhjlFvULEtKlXffBjUR6IiNqUMbxgs9/3l5fsoxDhFmvX4c77ljAHXcs4OzDj6AeDlANNiEbAd7tobN0HFopEEqx8eQjEKMBqvUVjC+egRhtQjVjk/1gQ+PkeOh1ENo6L7U7DC77YTsCkWQ9tCxdiWpw7szju3Q1Mo46jlRInJ2/vEdr/fbLnXsVn/kOexGn7CfuDC6MgUtrNVx69LTOg4P7w99egMSLj/h58rqUIbE2XpjEDkzxAgTwLi3uZ4dxCQHZVBitr+CW534evu+e7BufcW2Y1fo9NwJW1xswa7sMpAQCmOwaThtjCpsAoXaVVBBC+tp1x30GRKt+zb1IrCQd8Q92zeYc0dQYrp7HTc++O6fGZ1wzZrV+HZauvx79xXkAwJMPP4mLZ1cgGoH1c+cwOPsEhivnIesKAIx9KgBalFC1IQ6yGUOMNiDHQzSDVYjxEGK4bsaY7M0Rh4nEaYs4ByIWTycEwpEIKcBFtUtXI2MWsZM5D/qIhcTd5wRYFtN2MtyOx3bHPLTW77AXsaVK2Dk8WANSaRTF5f+p7ayHNoGIQ6h0tCjxJCKyeHRah2T30tpAmiyIaGbTDnVrJe3iwxEIM8f5Vd/6Rvz3zyp26xJlHA3MdP12Osx3G2hiXGDOMzv/qSVzm0BopaMabm0ACBF1FqNajyxcXQ0rKbyOKbZxVSraIPD1q/Cm734z/vELOrt1iTKOBmayfh3e+Et/i8/+7RlcWhljYbGHXq8EZRRNVWP9wkUU3T4oL1DOL0IrhWawDjEwqdOyGkGOh8mIoKrHEEOTSO20EHI8DJ2HieC4MHc+1TVHq6B3sPdETgqzM44uslVriisiD4SQt8EKt+wOCGAs4CYGeq04a7tje45PPtlACAU6xeoxtXgkySIEiAkF/OKjPaYkXdehlXyro91L0TRJ98H4yZuZTefk4s7XKiTd1qMh+kvH8LJ7btzTa5ZxeHAY6lcpDc4m1zixY1LsyBRvAMSp1H7s0BiwTWwMJLXtSIYj/RMbAaZ+vSgDbtES7Jir4SZYUeLF99y6V5cr45Bh1uvX4a7n3wqlNEajGvPHFtFUNVZXR+jO9U1AHABZV6jWV9EMB2iG6xg89QiGZx9FM1iHqiuI0YbROmhDCprNVcjxwOoh6mDrGkFbgfUEaYifu8dulElJQDZY+dxDu3U5MjJmGpclD9Ye7j06eES/GZj8IrJirHdf7th+4C82gPMr9bbdh3icadprfiwiWowE3UNrweFclmRYfEyML4kGUpjxBiVdcA2B1srvjEJrUEohqjE+7ws/H19786HN9MvYJRye+q3Q6dhdx2mq6RbaXQg/FpjUcGqC4GpW28BHp2ma6D5ICSkayKaGdPUbf2+4nSZtNgaqwQae98qX4023TQqrMzK2w2GoX4e/++7TOHasA84pRptDdHpd3H7XreguLAIwXXje7YGVHVBeQIxHUE3lXZjEeIhmsAYxWIOqK5/5EO/oujRqraTRPSgFUDrRhfAdipgsuFtkgEBEhQtPfm4Pr1LGQcVOji0dBlwu5+EUgF+zj93LpwG8yz5+k90VOQ3gZVrr2Ed6u2N7jtPnBY4tShsaZ16btHB1oXBOPO0nimz2g31s7VgpJVDKeEUrpUAVgVIUkAqAAGXMuMQAIFLaMCoKRWn8Qw1JcPaPlCULEUIpRF2ht7CMb/mWe3HhnR/Cn6zt8sXKOBQ4TPX70DmBxXnh61FBg/paDW5qQAiEDCYIodZNDae2rZqEjQAX8qh1WEAwAMrWr4zT4i201oAVT7ePufqdWz6B7/xHr8fmT/w+fuf8ro+YZxwCHKb6dTh+40k8+pkn0O13sXpxDcAa5hfncN0znwXem8OFz3wCnbk5UEsMlBC247AJdf5zoEUHxdySz39QojEjTDC1xrpzJivJa5EkKC/DL+DyH+xjFxgHAJBR7gMrfBeCidEeXqGMA4tDNnZ0rSD6Cnbx9gJ7Idp6690lFucLSwYASomdOCB+pCm+D+cQMGbOoZQa9yZKwRg1rzH7mFFwzqwHvEmO5gU3jxmzPvAcrCjAC0MWnN0jZdwcsw5MLpBKKQVRV6CMgZcd/ObPvQc/9ucbu32pMg4A9mIWeaewF/X7Xc/vYK7HIKRJm96qhuPn7rivVUrAeahbSkPtMkbBOIvqmYFx66pEg8OSq19Tt8xbLjNegBWlrWtmOolKQTQ1KKXoLZ3Af/2Pv4R3fGB1ty9VxgHALNbvbq8HPvyj34qP/eZ7MDffRdMIFAVHb76PuRPXoXf8BgwvnMHqU0+h7JToHzuOoj8HwgyR6CweB59bRO/kbeidvNWQhLjrIBqwbt/cyi4IL60tbGm0EpZQmFT48Ny9BsD8rDj3wXUoOvM4fuszd/XaZBwMRCY2xD7XAPDX//Yt1/zZL/kf35V89izjSM3BrG6GwLjpXYfWiFIr/6GtZ4jHIFIRtYQUMgim7fiDFAJNXUPUtblvGi+gVqKBbBpI0UBZzYN3ZWIMSjSA1njNl78cd2ftZcYRxMZQWtvlQBBixLat04If0/qFH1eKb06/JEWa0aKU9vXbVBVEXdu6FV4TIUUTdBDRIsylTjfjAV79Fa/O9ZtxZHHvP/9FdPsllk6ewOKxRcwfW0Q1GmO8voqNJx/BaG0VlFJceGoFFz/3OMarK2BFB6zoQDbG/aiYXwIrO0YgbTsPzm1JK2nF1BupFkLUQTBtX9Oi8aNNXhcR27cCIVAuOy8deeSchxRHijz87uck6kb58aPtdllSUXR7dtrpHGKL1bYVpFt4WOJgFySiblCPx2jG47AAcUFU2oqr6wqiHqOpxhB1ZWaqCcV4sIFjN92K//Fbno1b8vh0xhHDbz8iIKUGZzQSSptj7cfhtXgzwBGJlPRP2C9HwXKxfaur36aqTQ1XlddBBKtWU79NNUIzHiaapvHmOuZP3ID/+R++ALdvOzCakXF4cfNznoOiP4f+sePYvLSO5RtvBKEMGyuX0F1YBGUUi8fmUVUNLp45i+GFMxivnocYDaCVwvCpR7D5xENoBmuo1s5DjDaMgFpLM+I0HvoQORWRC0ciZD0yZCNKqgZgSURtFnnO7tVpILJ4+sgjax5SHCnysKaBJ87X4Dz8syezHuIQuUkhdezu4nYkkx1ML8RE0oWQ0Q5lUzeoK7uDaV2Ygqd8A1FXqMd28VFXXgAGmPC4z3vNF+GVN2X2kHG0sKaBx89VKEu6pWg6DnucrGFMJRBJCGRs1Rx1IUQjwq2uUY8r30X09WvFmqKu0IxHqMcjiGpsFjC2GyGqEe5+9evwiptz/WYcTXzxz34IFx59DNXmOqRSGK2tYrC6BkopmvHI2Lde2kRdCZQdM3pU9OaNrbmSIKxAtXoOzWANqql80rSqK8jGuC0p0QBKJmnUqh6HboTLhVDKdCFiMbUjEHEWBABSDzOByMiwOFLkAQA+cU5iMAzCSyAsKLbqREzbyfQLlIhAwC1U7OJEKxNCJYWAbIQlERKyEX4HU0TjS7JpIOoasmmiTIhg8QrAe8d/5z96Hb7pjrx9mXG08MBZieFI+NC4dtjjVmYI8fE0YT50IMxxnXQljCOaubn6FY3ZAGiqMH6opPT1K+rajyMmo0yA2RgYbeK7f+Cr8R3PztktGUcTCyeO4eznzqE/30dnbg6dXheA2d1lnGNuvmv0SQUHoRSyqcB78xCjAWQ1BCuMIxMtOiFUruwYQxJLIJzjUgiPC90IWY+NzWs98u5LaSaEhJaN+ezIiSmPLx1d7GTOw2FImD5yq89PVsBzz1V4zu1zEMJYNQaBDGDcWmCfayuunuYvb1xdDFlwjwO5gAIkFKg73voM6rIlnIiLEGhmRJaUGTEXgSEhIBKUEOMQQSjq0QA33Hk3XvaSB/D/PHJmh69QRsbBxScr4O5zNZ51Ww91nc6Qulp2tZnmPgDGSS285r7LGXMhbxqEGPclFwKnFMAmyzepW3+j1IunXZAdlIImBJooEFvf9XATx2+9Ey950Q3Apx/fycuTkTET+LvvPo3f+cZnYXN1DeX8Ini3hyc+/RCUUli9uIEbbj2JomNckpQQ/n3KEgVZjbweQVvNAnjhcx4IYeY1SsG7ffvYiaDH1mnJnkuZd2TSSplVkQBAJQhl0IiSgZsxLj38SRx75t27eXkyDiJ20G0pC6ZnFJ+5qDAaC+/O0m44hAVIOvLg7pNdyy3mq70OQkg0dqcyHn3wO5p259KHyKngPx+n17rfixACxguIeozXfuM34Eded2x3L1ZGxgHDgxckxlWwXW6PJbn6jevTIdUxpfkscSdCStc1VKbLUAuIRvpb0oGoGz++5DMfdLoJAcCqvI1DUzVYwxd/y7fhJ77mpr26bBkZBwrd5eN4+PQanvjUg+gdvwGikeAFx/U3n8DFsyvo9Lvozs1BKwXKC6i6gmoqiME6muE6VGNGAgGgWruA8cUzkNUQ0obJiWoAMdrA+OIZ1OsrkOOBudVjaKdpgOtI1GF8KQqcc9oIOR74x2qwuk9XLCPj4OBIkocHxsDF1cbvOAKTmoZ40T45Mx0vPuDF037cwYov3QKkvehQMhpnEqkmwju12B9qLCdZsH+0O5tKNGC8wL1f9BK88bqZJ7EZGVcMV79FQaPuApJOQ9pNbOsdJl2X4sdKqVDHlkCIxmwCCCumDnVrQ+Nc+GNM/gFjucyYt3SllIIQalzVpMDdn/8CfNnJXL8ZRw9f/LMfwl3POYFOt8Ro5SxO3nwdhptDiEZgbr6LtYureOox01knlEJWI9QbaxhfOgtCKLQQaDYuGcG07T6I8QhaNpB1BTkeQtUVtJIQow00gzUTMjfagBhuWmF1bTQOynYZnE6iHifOTLEjEwCsfPp+fO7M2f28fBl7jCyYTnEkyQMA/OJpgbpWvvvgEI8nmJ1+87itdZicm07F027xMXHzdq6BYPjU6Wjx4X8H6vzmbYgc42ZhRAjq0SbufMUb8J3f/tK9uGQZGQcGv3haQEqVbAA4pN26lkvaBIGIBdKhhmV7A8CSCBXVrkoMESJr16jjQW2Gi6tdyswMNyEU1WAdp172Onz3d33hnl23jIyDhK/9r2eweN0JDC5eAACUnRLj0RijYYUnnhiBc4q1c+cMKdASlJtJa0IplDQEXCsVdA+88LPlzWDdhMuJBrIaorp0Ds3GiulgyGDV6roX7QWeVtKMD1MGwgtzs4+hJOaH5/byUmXsM7JVa4ojSx4A4NOfG4Ex6j3jw70PCUk7DDruUKTiafeaSkhEenMjEXHHIl58yGjx4QiE7za4DoT9MnP34/WLOPWSz8fbXzG/L9cwI2O/8KlHzeIizn0IdWzOaRshTI4ftkYRndXytNrV6eZAGG1Kyb8TxzkdBKEUINT9kiEYklKM1s7jlue9CP/slbl+M44miv48lm+9A505UwMLy4u46dTteMZtc5hfmsfS9dd7UlAuHgcrOsa2VTQmUBVm9Ehr5XMems1LkNUQWknU6xchxtaeVSnUG5cghpuQzRjN5hrEcMNauTbhsyISkZAHbkLkSNEFKMPK4w/v/QXLyDgAONLk4ckNhcGwsbPTgRTESBce29tDQuupO5rTPjtdjARbSLf4wBY/y49B8BKMFyCEYP66W/Hm7/12vPXu8hquRkbGbOHJDYXhSEx0Dx3cJsDkCNNkHcYbBJhSv66uJ94XbwBIlWonWjVMbGq8SZMvvEhz7viN+Ibv+058zwu7O3VpMjJmBnM33Q5Qirnrb8H1dz3XJLh3ezhx261gnKN34nrwTg9KCLCiY/QOssHo4hmML55Bs7kK1VQTYyGEUjvWtIl6/SLqzVXTiajHEKNNQxpk7Z2XHLlwiPUPE2JZZ98qqmzfekSwk25LhwFHmjx8eACcv9T4HUs9xVkp7kQ4TDsv7UDEr00hI63j3nM+0jp4EWf8hUiIGX3gJVhRGqs6XkDUIxy79Tn4mm96zTVekYyM2cGHB8DKWpPktoQEeZI8n4a4NlPSj8m2RPSeuKQTwbXTOrReg9VgEGK6hYwXJjXX1q9sKizdfBe++lu+ZEeuS0bGLOEV/+q/gHd66Cxfh+7xG7B06yn0TtyEcmEZCzfchGZgQ+CURDNcR9FfRLO5arORGshqZEmBEVPLaoRm45JxZLJw7mhyPLTnb0A1VhdhhdeyHntSkCz03N9h91qcRH3IRlEytkFk2fu0b4cIR5o8AMAvPywghNE+pHqHVPOw3SIEiNYXU3YdJ0gEmU5KkkWH1skMNUjbEtIKqImJyx6tnsUd97wa7/q2U0//YmRkzBh+4SGnfZj8KmvX8JUgHU2cPJY+bzuyhc0A+E2BaHFhaxeWRJj6JdBKYnTpDG574RfgP33HXVf+y2ZkHBK86t/+PprhBsRgHaOVsxDjTQBAuXgc5cISlBAoF5bBOn0zWljXqDdWoYQALUpQVhhB9eYlQyiaCmK0iWrtAmQ1gqxGxjWpGplxJiGMqNoJq22oXNuJyWE7wSuRTR5fyjhyOPLkAQA+/OkBqiqacWxpIMLrqTvTNB1EOL7ND2wfizsQTjRtZ6ilEJ5ETPtwJ8SRNknzlV/7Zvy7r832jxlHB3/14AB1HddvqF2zKTCFqGOK3qE9voStCYP7OclYkzIuTCEtPgTFuYXHVtaxUpjxiVd83TfjP3zjM3boymRkzA6q1fMgvMDSHc+DVgqs6KCzfBKUFRDjkelAiAbV+gpkXYGVHVDOoZoa1dp5iPEAqqkhBusQgw3I0QAAbKJ0BTEeGL0RL4zYujHjS7KufPfBdSCcTau3cLV6iGR8yZEJrUBEhYtPPLrHVyxjL5HHllJk8gDg/SsaqxvNFiNLhky4zkR7JzMVUMMLoVNy4c51H5y+Px5xMDaQIr01tbd2NERCmufuJgWgNarhOrSSeMlrX4k33cZ28YplZBwcvH9FY21TTDgvxVoISknSXTR2ruGxbjkwucRpcxye4E9DMnqoQv0qX7+NT4vXSkJJYciCJfzaOsZUw3WI8QCf96rPxzc8I9dvxtHCF//sh8xCXzbgvXn0b7rD2qMq9K8zG2Lj1QtYefxzqIebYJ0eAEBWQ9Qba2gG6+Y2XPfHfLq01UTIprL2rcqGw5mUd2U7EFDSjwuL8cDavY69/sHDjS6J2o8vUVll+9ZDjJ10WzoMCdOZPFh88JEprUodshbi+/bj9s6lezG8f/LndbqFPQ+ps0tk2xozVreTKUUD0dQQ9djcmsrY1WkNShlEU+GGu16Et37v38HfuyX/35txNPBXj9bWOS0UmyMAW40thbqd3klsi6TNZ5kP6/TK8BmWNIRuoc19sGNL5nVTu7KpIZsKsh6bm69fZeq3HuOGu16Mt37/V+YNgIwjh+6JmyCrEcYrZ3H2I3+IZrgB1ukZsfN4BFlXGG6OcPGpi7jw0KexeeZzGJ5/CrKu0AzWAaWghDBjT5Sa51IAlIIVHWghoGSDuZueaUZ+AcDqKZSs0VjnJd8ptONKPkguCo7Tog7aByUBKTAnNvfx6mXMCrTWRGv9jv3+Pa4FeXVp8VgFPP7UaMK5JV5YtLHVTDUh2CIdOiw+mlpEo0rBLz7kQSj78y2hiDoNZlZzDFGN7AKkNl+QAChlGK1fxK2f9wr8w+/+ErxqceeuUUbGQcUjY+CJp4YT3YeYHJjnlxkpRCq29vVtR6AcmloYpyUV8iCmWS477UPcSRR1haYao6lGEAmB0CCUYbh6Drc8/+X4ru/7crx6aUcvU0bGgcbx578SzeYqAJNAvf7YZ7B55hE0wwE2V1aw8sSTGAwajEYC49EYm6trqAabqIebZizEkgTKCkApsE7PJ1ODUhDOQVmB8YUnrdh6CDE2gmsjph5a3YPpMhBqCbwnEXUSFpeIp5UEqYd5fOmQIofEpcjkwWJNA49cEBha61aHdGdySrr0FGIxbcwh0UVo+KRaFS1A2l7xsfbBkAvbdWhqiLpKxpm0VmaBwwsU3TlIUeOuL/gyvPFlx/bi8mVk7CvWNPDoBYHxWLbq140VtW2Tt/6sdp3Hn+WOi8ZZs4YNAEcitAoaiCQA0nceTP2KukrGDgkhYLxA0elDVEPcce8b8KUvO74r1ysj4yDimV/1XXjt//6XYJ0eCKUQVtswXFtFU9UoOiWuOzmPXo9j6cQyFq+7Dlop8LIDwIwnyaaytqwDo53o9EALc5wVHaimQr1+Ec3GKlRdeScmMdo0pKHtcmihRRPIBBBSp0UNLRsTVKckaDPKBOIwQqlrvx0i8P3+BQ4S/mhVg58e4QtfWNqd/xAWZ7Ig4J/HWgijgCY+zdY/h7ba6PYxc0eIOUNrEukkwsy1FAKEEMg49QpWuMPMlxih1NjFaR2sIIsOqP2S+4a3/VMQ8m/xg+9b2eWrl5Gxv3j/igYwxKtesIimScl7u34pJVBKT6lf8zi4GlgLZ1vL2tWtXexrrUG0/axY/+RGDSmd6EJqxUGZ+UOimAJRyryXkFC/jEPLBm9+2z8FIf8r/sV7c/1mHB1snn0Cq+cvQjQSo80hAKA33wcAKKWwfGIJhDJsrqygv7gAKYxuqB4OwDhHOb8IIUbA+koYX2oqoL9oBNN15WfQnZBVicZ2Jwr/e7TD4mQ9NhbpADSV/nVQBcIBMArIBpTmfdmMw438X3gLj29qXFwZA4DvDPjFvFQTu5LtBNqtRpziY+1dUDMWAfuY+NmKVOsgIJrGiC+bGrKxHYdopto8N19olJcAoZi77hn45n/5w/jXb8g7mBmHH49vaqxcqkBIWr/t7kNc1+2Mh+mOSLAjSPHN7iSl3B4Akm6ijITTommM9sEbIAgvoo7rl9jk3LkTt+Gbf+hf40ffeGK3L11GxoHBybvvBQBculRDK4WF48dAKAUrOCilEI2AqCr0FxdQj0bgZQfMdh8oL0AoBe/0AEqhZQNaliCEedtWJRvQouOF1Uo0/v3ueRhdssskyvxjX6fWchnudTfCJAUuPfKp3b9QGXuGg+i2RAg5RQh5GyHk9fZ++TLnv54Q8pFr/Rwgdx4m8GAN3H2hxvwcj5Knw+5kLMJ0x92upt08jAiE6T6AuF1P815nHwn7UrxWUUqDKA2iFCAJQOyXlN29VNGOhpIMUjTJyoUQAsVqKMZBGUc9uITO/Al87ff+YwwG/x4/9ucbu3XpMjL2HQ/WwPMv1pjrm682V7+OFLhSMWUU6jqt39AlnGbxCgQ9hCEV4XXvnEaIJ/YAIKOMFv8Z1I4jNnX0uRSE1abzwApUmyvoLl6Pv/f934/B4Mfxv/zp+g5dqYyMg4vPf8e78fkAfv4L5tA0AoPVNaxeXEe3b4wKlk+egFYS3eXjIHTVkIVuD7KuQDmHrCugBIrOIlB0wHtz/rMJL0CISXoHDDkglIEw57w0Dt0HSw6cK5NzafKfRVumBkqa7oOSAAUuPfZpjIsF3HRTtk/P2BW8U2v9BgAghJwGcB+At047kRDyegArAO65ls9xyJ2HKfgvTyp8+rGhXzhsld/QHjNKdzEjXUSLcSbuTdGupX9PS0QtYx1ENEMtnOYh2sVMHF1EDa0kqsElLN38HPz3P/i23IHIOPT49SdM/brguImQRkw6LU3Wr+sSRunvFrHxQdu2WatUv2RMEIKAOslvcbVqbV2do4u0c9vK1e/GeSxcfwrf/sP/Evd9+cndv4AZGQcEg4HAxQsjUEZxy523odvrYn5x3mscqvVViLrCaG0Vo9UV1KMRqs0NW08CWktoLU02RDXyNqxaK9+FEKNNM7IEo2vQOqRMa5vz4OCIhjvX1agTUbvP9hkQUqAjhnt4xTJ2C+6/pWu57SQIIacA+AWd1vo0gDdv/fvr92mt77/Wz3HI5GELPLGmMBoJ3yWYFE8Ga8fJcYh00TFtFAKAT5qO4Rcy0jgv+ZaX//zJIDk3vmTE2CqMQdiFiBI1RqtPoX/iNtz7xffilQu7ffUyMvYXT64rVJUE5zSp30lzg9QQwdVvm1z4bkRCIojfAAh6ClizA23HpqLvgVYLO9SuDPPXfvPAZkE0YygpMLz0JLqLJ/GSL8r1m3F08OLXvRp3Pf8ZUFJhsLoGAGZ0iXP0lk+AUIbO/CLKXg+UUvSWltFdXAbv9sA7PWilzHhS0THBcLKBFqHmtJIhdVoGR0Ntbyq5rz35iNHWRXi40SYtsfL4w3g0Z0DMNA7g2NI9MJ2EBJYM7PrnZPKwBT64CVxYrac6t8TCyxjx6xOLD5XOWZsT4zdHIw+JfiJ0L+IdzLAAcZav0v8C5nhYmADmS63evIi7X/eN+L7vvAd3FsjIOLT44CZwca2x2Q/TzwnjSeG5uW9rJCY1S9M/0GwaOJJvajSya42yH3R0H24uhdrujrr61WZUotq4gOd+8Tfg+/9hrt+Mo4Ev/In3gZUdjEdj8IKDMor+8ZN+jKizuARCKZRSfmyJd3omG2KwbkTSrUWbaipQVoAy7g0KAJhuRVNBDDeNjWsztq/bjAdh3JRc2OMEop/jA8Gs/oGICgs5AyJjZ3EcwGrrtRUAy3vxOZk8bIPffVhs6x2fvjZp8di+hw5Cy2nWr3FKbbB6bNk9Tll0+BGIyLY1bs9CK9/hGK2dxUu/8pvxo99zD67P/+9nHGL8zukGT54d2u5DeD3uBLaJRZsgTHYlQh37cSgdBNKJTasKpCEZX1KpDbMTUPv6VQpKSb8hENs8j1bP4J6v/Fb82D/J9ZtxNHDd81+Ok7fdis7cHPpLy1CiAeUcrCzRDI0d6/zJm1D050B5AdlUGF+6AFZ2QFgBUY0AGHIApYKjEmVQsgHhRvvQDNZs4nsDOR5CC3OvRGPC4dxokhtVUhKqHifWrtoFxgEhPM5tAIgKlx779L5cw4xrx052HmzCtLu9Y//+VU8fWTC9Dc4p4MwlgeuOSRTF5F9qJ7CMoZROLFwDyQiWj+4x4GweFbQmoDpoISixHQqiQCS8XSuhZgxDOftWIdLfSUlwpaBLE4fu3CBY0QUIBSEUUtS492u+Hf9eCPzkz38cH8wbIhmHEKF+le8gOotV99hZtMbP0arR+LFSwRHN8AhTv4QQKMTuS8yS/1DTkhBQW7/a3mRUv46McCkAa79Mff12/O8t6xFe+tXfjp+SCj/5nz6Kv8geCBmHGPe8/T8BAP7wH70CgwvnQChFMWfSTykvwMoShHOIwQisLP0in3V6UE2Fom/O5c5ZqakABBclWY1MqBylkNUQQB+sY/6Wuu4DoRSMMr8A1KKBps7qVYLyEgrG5VDDdPq1VibFOiYUosalhx7AsTtfsNuXLWOnsYNjR1rrLfrhACHkLQDu3Obt79Vavw/TuwPTugiXw9P6nEweLoP/dk6jkQO84vmLE5oH5/MeLzjihYibtZ7c3UzfT2Dupd8NDQpqt9OZvl+Dua6F3cGUTQPBOXhRGhFmp0bR6ZrPsCMQhHFAazNLXY/xsq/5Nnw//SV8409+dFeuXUbGfsPV7+c/b8ES+8nv7EkSEVzTtjqfRBkw7nxiuxDhc2j0+em9q1/XgZBCgNYmPK7odKGEAO80fiSRidq7wxihdYWXftW34PsoxV/8uwkNXEbGoYMSAoxzzN14G8r5ZchqZO1bO6jWV1DMLYD35jFeOYuiH2xV681VlPPLAKVmZKnoQI42wXrz3o4VJUBhuha06EIr6cXRSjbQow2TDaEkaNkFAFC7etJKQioFImqgVElOBNpuTAAgm0wgMraE1vpdV3jq/YiEztH7T1/lj3xan5PJwxXgqYHG6lqF5SU7G6n0BCEAWoRgihBaRwFTbtcyBFMZY1elNIjPk6AgLacX+2GWFCgoSkEpNfdKTSUays5psqITnCKURD1cw4ve+LX4ZSHwM7/wN3kHM+NQ4qmBxvpGjcWFMqq9SacktwmQhsBtQSS09vUbv18pBbhxaLtJwNikRkJrDapUqF0pwThvneMcmgR42ZhwKsqM9bOSqAereNGXfi3+HyHw0//Xx3P9ZhxqfMm7Pow/e9vfgRYCg6ceQdFfNB0DwBCH7jzEeNOThmawYcabig7EeNOnTAOAkgJUNF6bIKsRFKmgmsrYuPLCpEYrZR67FOrxEMx29h0Itd0FXkKJ2s+CE8owWfkWmUDMHHbaLelaobU+Hf9NsgLnd7eer2itV6/lc7ZCJg9XgAfGwPonxvjGe/kW40th51JrRCMSgBtd2moH04xBBFIBBSiiwy6m/SyBSWcYqhQoYwBjJvEyGoPQ2mkjzJy1Eg2YaMCK0gvF3O/w8q/7+2D8F/HQT38U5w5XgnpGRlK/Lptlq9GlGFsRB98MVAoKk3oKQjQklPku0MR2GoLuyRB/DsZNUjy1afGQbRcXOytrbZhZUYLx0oRgEWJqXAq8/Ou+A4z/Ah76yftz/WYcarzqx38X7//Oe0At0ZbVCPVg3egbCEO9sQZCKcR4hM7CMkApKOfQSnlhtKxGKPqLRhRdjcBsWJxsKshqZDQRNvitmDOCbNbpp4JoH8YadRlEDU0plKhBlPSf4f7WeicmSqFFDSiJS5/5KI7d9eJdv24Z147dCHnbAbyJEPI2AKcBvExrHWcz3AfgvQDeBficB5flcB/C+NPlPmcqMnm4QjwqgEeeHOFZz5ibMiMNuLElNxftNA/xvLSZjzZdCwVHGszCxGVHaSOMsIsVBQoaZqkBGBqRIl3YRELsSFDNyw64XYTwsmtmRbkJ3BHVEPd+9bfiP3CGf/ZTH8FDzc5dt4yMg4BHBfDomRFO3doHEMh9TA7aI4gx8XcialenvsaVCYQzNajtMQ0KQGkFgJqNAAtfvVMyZNwvFY8jOjtXJhrwsgtVNBP1Ww/X8NKv+lb875zhf/7Jv8KDNTIyDi16193kLVYJ5yj6c+gsnTTiZ0rDzZKGYn4ZcjQAYALi9GhgzrVdByUFiBSmi9GbgxYCzXDdEIrKCKY7lKYOS8qGxSlpQuco8xt1jlC41ykvDWFQMgi2KQOo2dy79PAnceyZd+/5dcyYfdjRoh+3T9/TOvam1vP3AXgfgLdfzedshezXcRX41cck1tbb9q3THZbi0Cl3k1L5m4pv3hPezkSr1No1JgMuA0KK4OAyzYXJO7k0Zo5aVCOIagxRjyGqIWQ9hmwq78gkRY2XfvW340fe+gLcO7fVFcjImF38yqMSG5tN4p7mmgEh3yG1aJUyrl0NIRSEUFEta5/HEme8uIyHYLUc7FulVCH8UQYL5riOlZRQQkA0NZpqDFFXaKoRRD1GU418EKSyoxWyHuGer/w2/NBbX5jrN+NQ4wv+zf+H7rEbQFkBLQSK/iJkNcLgqc9BiQb15ga0UmgGG6jWVlCvr2C0chb15iqawTpoaUi3VhKs6HjnJLfYJ3ahL6sR5HgIKAVZV3aMSUKOhxDVALIeQ4yHxpHJujE5S1cXHKfqMWQ9MsfrsQmV8+5N5rGuBrj00AP7fFUzLocDmPOwr8idh6vEXz8yxis7DL1euHRBCAnEu5YA8cfMRqO2wVKmC2GcVwAKt3sJfy4hxokJgHdhMlxPJj8z/h201gDnxpWJ2PlrQgApoCiFaMyWpA+RkyLsYNZjNKMNvPQrvgE/dPwYPvzHH8cP/+HqDl+9jIz9xf0Pj/HK5zCUZdg3caUUdxJDLYdpBWdw1jZFcJsJhAAgOq1lqezoIfXjTP5ntcwQ3PiSc1Mzi5ggqHa/mMt34UUJykswa09ZjzZwz5e/CT90bBkf/fO/wQ++byL3JyPjUIBQhnLxuE+JZp0eOgvLYJ0eqnXz3z3lHIRSVGsr0DYHAoBPmgZC5oMWAopWEKNNaCFAuBntJYSCzy1CNZV5D7E1KhpAKdCyA6261nHJ2r/CjSg1YGU3ODMpCVAGQm32UuzSBOQOxAHHYVv8XysyebhK/Nk6/v/23jtMkqu633/vrapO05M35yDtKksoIISEiCJZtrENAoTBBgzGAfsHxoC/DghjE50NNshkjASIYECIIJEkhJCQhHLcvDsbJofOFe7vj1u3qno2aLU7s7szuu/z9DNd1dXVVTV9qu+555zPYcW+BhvXlp9QvSVbfJnWPZjCSgXEBZNxOkScRh2nRsQpUKG5tegvrohvXlGkEpnWtpzqGCFEWw51QAtHT4EiQzeJTEjXI3RacR2EJPRbbLjkJSzdcDq12uf5yB3VGb+GFsvx4tZJWD3U5OQ1ZVqtsM0ZyJKthTB2rp0F2px8KU3kwiwLBCqxZaVCHCd1VBwkOPqHKKuybBSYsrTfW1qp4xBFOGGACgOk6xM6blJMHfpNNlz8Ypafdg6Vyqf50C+sDrNl/nHuuz7NT9/6LNx8kcKCpQTVSfJ9i3SUIK6DCBp1Cr0LEFLi16o0JyeQrkvYalLsXxx3lA5wi5lQXcapcPIlXUgd+nilrjgyIeNUJJewldY+GISMknoH4XpEgZ8WVBMXURu51zj1SeDp/TSrjD1+D3gFetecckyuo8VypFjn4Qi4c09IZ6nOkoWFTNTB/PDvXwNxsHUHcyDSMUScdx1pGVelSBRc9GyngwjDJOrgRE5b2pJ0HBzXTf6a16QTIuPZSycMdEGYm3bcrAwPUOxewBVvfS3ex7/I+2+1Mi6W+cPtAwGlQo1F/fm2qEO2bsHUQ7T3h4BsLUR2rG8cCVMLYRwIY+dKReCknyUdiQOEoYjFD4xsa4TjOvvZsLFf6TiJ7UZhiBNvIwIf6bhIKakM76LQ2ccVb30dnve//MMtk8fislosx5Rn/+ct3PqOF9Ic3UdteA+5ji7trOeLBCNaxtWvTtKs6N+v0NfFfF4+rxvBtXQkPqhX8atTeB2dSMdLUgGl4yPzRSK/RdCIJ9HiaEMUeDg5/XuaOgm6n5JxMmRcA2EcDiEdVCvtGyHcXJvzoQIfFfg2l/xE5UBdxY8QIYQC3quUumrGdnqMsc7DEbDZBza3uMwRLOjLJzOTZpYSpqc4pK+bmUoTXTAOhJllNMXUaQE1pA5GmvKgHJnkaEtpiqMVIhTJAEQ6jh5guO5+f2UYIuNlKSVREOi0iVgyqjE1huPleMlrfg2lvsMHfm4dCMv8wNjv8wX09xr7TWuWDG0yykl6Uur469TAbFqiTjcEuV8EQkp0B2qliKRI+jw4CpTU+5GhIHJ0R2onjHAcmdhwGGvcZ23XpC9JR08Q6DSLuJP81Diul+PFV2r7/cefWQfCMv/wyj34lXFKC5ZSG95Dq1YlV+qgVa8zOTZJqxnQ1VtGSomXzyEdXUxdHx0GwMnlyXf2EMTpTyG6G7X08gTNOsL1COoVwmYNJ1/Sg3svj1ssE/kNpFcAFYKIayVyfuo8eAWEbOrnroeIBQ6cXEE7FfE5RK2GVkvMDE7HHr8HpSL6Npx7LC+n5RAYWd+Z2dfBm8TNFazzcIRs9uGsMZ/e7rj4Sk3v/ZBNc0ifGynXVLlFtA1epIzVWZTpJg1KCcJQd8mN0N2olVIoGRd2yohICGSkZzRRehZTOpGWg4xnLM1fPaMZIAN9w5NxkZgw3k48YKpPTeDlC7zkyhcTBDfws4erVkveMi/Y7MNZEwF9PWnvh+k9Wqbbr4n4ZScGjC2n9iviHxmZTh5IXXgtTe1DLMMcRfpvKEBKiZOZEFCRInIkjqtt2Ynt1zyXcUG1UZYxNmyOG6AxNYGby/OiV72IVusGfv5IlVutD2GZRzz9Ki1Hf9MbzgagVa8zPjRCraK7SC9a1k+z3mByskYURixY0oeQDrVJXVTdtaBfi4k06kmNRBQE5MralqJWM2lGp38/PYTfRKkIJ19EBUHScM4tFAnqPtIrxLUQcapx7Eg4ucyym0MFrbgrdRx1iJ2HKIq0QxE3o7NYTkSs83AUfGN3xOVhldPWFNsiB9P/phGIVMrVjNGNVKv5q1QUD0DigiqZ7VKtBx5SyiSNycxkSpkJdiqFkGl3ahVFCFPjEOvKCyESh8E4DeZ5dgDVqtdxPY9f/73LuWjndj73uTv45h5bOGSZ+2j7rXHKqmK8RiXRwzRCmDr+WUffRBR1o7is/ZroYphEK2S8TRTbrHEwpBL4sT3jpHUPUWQcCactHTEMQ5wgIHSM0y/b7FakB5bQrNVwPI/LX/sSnrl7gP7P3M639lr7tcwvJvbuJV8qIKWkVmkSRjA8GrFoGTQbOj3JDxT1So3OfJ5cPseeXSM0Gy26ertwvLhvhB9Q7O6hOTkBQNCoJ6lHNOpI1yNX7iGo61qiSDS1/GsUJpEIGQRIvwHC0bVIcQ+KIEijErqAu5Q4/GGr3ibzCuBXxhi65ycsPOc5x/BKWg6GLZhuR+ynM36ciHPA5iRvPjVHX08uk8KQVU4yM5XtzoWewUzXmeX9n8t0tjN5rgclInYazHPHceLnep2Ml7POgnRk4miI9CCT5zKjky2lTBVgpKTc28/eLZv4wv/eZR2IY8BcCm3OZft940aPvu4cYaja7NM47dPt90A2fXD7FW02K6XeoZxmuybyIB3t0Bs7NX8TW49tej+nIT4Q/TmpDTsZ++3o6WXf1i184Yu/sg7EMWAu2u+JMh44Ev5hbY6usk4TXL6ym1/cNYkUsHopBIFiyZIOmk2fKFLU60FSzxRFimLRpW9hD/VKjWJZD+rDICBXLCad351cHq/UgXB092mv3IPj5RFxvaCTL+EUy4TNGm6xnDgCTr6U1D2Y5VzPQrxSZyIPGzaqce8HBxW0khQnmcjHOiw893nH4ao+9chEnkW8rABu/P2j7wZ+2Wfvb9v3XMZGHmaA27a2uPRkQUcpK9/aPgmYlXM1A5OsjKuJQpjXpDQpEZkUCBXFEq86/UFrMEXJ81CFKEcilUKpOAUiSZEy0o+S8ADyMskAJ45MOK6bFF44cTi3NjnO0pM28MY/KHDpfY/zF9/cOzsX1GI5hty2zefSkySlgpPUPGSV1IytpnbaLtk6PYpo7C3baV5HI7RdSmm001LbbWsEmegrpGmJQgiU4xBF2fqozN9kQkE7DMZmQUtWSimpT02yZP3JvOENeZ79wGb+4lv7Zu2aWizHmpFJwfAEOA4UClP0dykmKoLJiv4rZZXJCuweESzoVizoUVRq0GhBqeAzMjpEzoPceJ3Orjye5+I3WwgpyeVz5EHXBrquThl04uZwfhMnX0R6ecI4IhFUdZM57Rw0dPTCiWshcnnCRhUnV9C/20EtTlnyka6X1kNEIVEARLrIevDOG1l0/mXH5+JaLNOwkYcZ4sIyPG11nq6ydiCy0Ycs2VnLbHRC/00LM9PcatE2ENGRhPYIhJmZPHBEQmbWyyQtKT0W0T6r6UhdmOk4OJ7XptZkRkmFzm5cL8dt13+ft31jz+xf3Kcoc2l2Yj7Y79krc5RLxn7Zz1YMJqKQXU4jd+22KwQ4jtzPlpPtTJQwY8cHtOm2NEPSYxLptk5sv8ZeXc9rU1wzzkS+oxMpJb+44Ue849vWgZgt5qL9nijjgaPhP87MsWVA0FNWDI4LXAmR0g9XQhBBT1lRbwpyLuRzCin061JAuaSjF4U8uK6gs1NHAQqlQpLC1L1okY5CSIlX7kE6Hm5HVxzd14pN0jGRB50WKVwPJ5cn170A6RXwSp1JpMHUN2Q7VetlXR8BuqDaLXXSHN3L6pe+8Vhf1qcMB4s8/OB1R9+D44Wff6ht33MZG3mYIW6vQGNLkxef7SXFlekUosYUVR5IwtXkSxsZyLQxlYoLpDPpCURJQbXpiGsGGVGc8qCkIhICRLh/ekN8LCJJlUibUyGFVm7KNKhK3hOnMtXGR5GuywUvfA5fXP4A37vhYb6wJSNab7HMMW6vQGNbixee6emO0pHCaSsjanci2gdZxp5pq2cCUyQdJXURIOP7gymejlARhEIgZZRx+qPEZpMUx8ztxGwnHQcchcQhElFyT1BKJbabTE7EtUy1iTGk43DBC5/F/658hO9/7xFrv5Z5w+p1C9m6e5hCHlYtVvR0SQZHIiaqAt+H7ritg+vAZFXQ7ykmq4K8B/UmlEvalis1cB2F5/pUaxGdzYCOcoHQD6hPjKe1EGgHwTgMukA6j8hLLZ7QBOG6OHEaUxToouoo8AGfKPBxCh3xskbG8q9aRTFuDBuFtCZH8co97L75ayy79HeO3UW1JGqXFo11HmaQ4RbsHmywbFEh1nZP1VogqwufdSBInrdv175sCjX1sk5/EFGYzkQmDgLIMJ3pNJEFaJ8dFVLguuhOtiLSTkPsiCAiRFxkrWLlJscoNsW51FEYUp+aYOUpp3BFXy/F637B1Q+3ZvcCWyyzyHAL9g43WbowT5g4EKmIAJApmE5Vl7IN5dJtROJEZJXVjGqaToWK2uw0EiBElEQcstEKIC6Q1n+V1HLNaTfqOMUpilBCF/eFkDgSIgzjyISTFGw2qxVWbNzAy/t6yF13O5961D/QZbFY5hS/+c0BRp/ZwfZdPqtXeKw85SQGf/QwAE1fUG9CMQ9jU4LusmJ8ShCGglagbXzfqKCjoCMTHUXFyHiEFDBVCYkiLeUahRGBH1Du68OvVeN0plTm1S2W8WuTRH4Tt1BOog9usYzjFSCKaI7twy126v3FzeSkmyMKWknHahWFRKY3hOslMq8yV2DgJ9ex/DmvOKbX1mIxWOdhBhkI4QtbAl6jGixdkG+bgZyuYgTtzkQ6QNGORDa3uq3jdDKzmQ48DGaGMqR9ACJluzMBEsfkZjvpsZjBh/avA1BKDzbMcQuBY/Ko47/NWpWO3j4u+7Wz2Dp4FzeOzP2wt+WpibHf1wILe3OJOlK2cVwW0ygudSKy8q5Z+21XaTL1EVEkEuWldieh3XlI05diO3QAZOowqFRZLZ0dC5KIot4aHU1UCgHJjGmzVqWju5sXX34WO4bvtvZrmRe8/udVPnhyjoXLFrBn0xYAFvfq388w1E5EGEGtrm0un9MpTbWGjk5ECvKe3j4IoNbUkYqWr+2rF598IcBvaAnYQmcX0nUJGnXyXT20psaTJnSF7j7cYgduRxcAfnUCFXeh9qvj2oGIQpCSsNVABfp9MlfQxdI5J4lKmMJrFTsYW/7vv6jseoyz/vTfjuXlfUpi1Zbasc7DLPCTHQEvzgkWxA2ooD3NITsgMelK+zeXy0pEZlWazHK6v7aIghlwRGnutSnSNo5I27FEUZzepJ2RCJ3ekMUROpWJeMYy6wjpvhEBe7btYceUHXhY5j4/2h5wSaBY0p8jQvdikPs5/Qe332xaYlYUIW0WmXazTicAVOI87FcfEYskRMh2+zURybhJZAjIjBCD2czYqym2VqaXTGK/Ibu27Lb2a5lXvPvxFv9yWo6hMZ2SVKlDf5di0y6Z2IbjaKfAcXRRtR+CI8EfFyxbqGj6OiJRLsLgmGCqBsW8IlIR1doU3ZUGritp1nVR9MRYlVJ5n3YoSgXKPd2EfpNcVx9+ZZx8dz8q9ImCACdfxCmUdCO6hi6adnKFJGUpbNTwyj1a+alRBengtxo4hY6kNiJqNRIVJ8vsMpPOg7Adpi0HYiCEXSMBvV25TPTBkP6wm0GDWYb2GUszENEDk/aoRTqD2a7qlEYqTGdbEc9Ipt2t9eeptF4iM/jQk5oySX+IhECaGc1M/QNxGpNQiomhIR54cIhHbdaSZR4wEMKXd4S8fWHamyGK7dQ4ESal6UADde0ctNuhfi21wXabNftIaxxM9FE/4nqoKEKJtBFc8sjYrhICoXR+ru5aKzLRxBSVaQo5MTTMAw8NW/u1zDve/lCL1zoFejthQY8i50F/j2JwVLB6iWL7Xm2IBU87Dp6jC6rLeeJUJpiqSlSvohXE9qR0bURnSVGp+eQ8kLKJlFDIC0aGdfpSf9zNGnSmgAp8WlNjWtI1l8cplAgbNVTgg5FyjSJULo+QukdE2KgCEDRq+oQi3fTVKZRoTY5y0hVvP/YX1XLU2IJpy0H5/rCiFdY4a00Bz5X7FVymudJZycdsIXU6c5lKPqrkPdk+ESYKkP6FNidF6Q8xhZoqUkRCYQQjRQhKST34iEc3aSG2LpqeHo1Idg7cdMN9tt7BMu/41ZY6Z64uIITuEA2gMkXUYaQSp8FJ1JfS+ofp0UTjDIB2ItIIY7szkbVjbYPZDtjpuqwNy4zzEiGRIrVhwhAZ7zPSH9CmvPaj7z9g6x0s85YvhA2uFAWGJwQFD7rK2liCzFyY4wA++CHkXOjtivADwb5RbZjVOvi+oNqABa4uqg5CHbUIQhgZE5yyRlAq5wn8kFYzIJfPEcYRBunlyHX1o4KAINJyrk7eJ6hXdHG1lHjlbkK/odWWVIiT79DPAx8hHdxSmaBRozU1iheFhM3asb6UT2lUdvLUYp2H2eTHYwpocObqAp6bTXvYX4kpfoV2JaZUNz4dXLS/b3rdRPtr2lmIIoVQkVZhMlEEAbp/hCIkwiEuno4iJJKISKcrKUUYDz7aPjR+bfeWHTw8YB0Hy/zD2O9pK3KJs36gugchtCMhBEjSVMF0m3QCYLqdpimEB7LrrP3Hn52kH5ktdZcISGsrZKZrROIwAARxHUQs5yaEYM/WXTyy2zoOlvlPztWOg+NAGGmlJUO1AZ0lmKrBsoXaYrKvm5SmBd2KRb3aZhs+tALIedDdoXA9l4nxBsWiS2dXkVazRQlw80W8UhdOvkTkN5LIg1+dxOvoSlSVwkZNKy/lCnH0fyr5fEc6OrUprn1oju0jbDWPwVWzGKzaUjvWeZhlfjymkKLBKctz5HMOaURgutQjyfrpqUsmfclEK6Y7FOb1dGZTtW2fFGHHaQ8m+qCEHohIITNRBr1TR6QysNnBiG5apcOxzVqNxx7ey0/Hba60ZX6iHYgWG5Z6eK5MbK49WpDab6gUUWzbTiY6mFVpUioVPkgdCSPfOj3ySBzFSBvKKZE2mVRxWpWKFGForNRBirSAOokamhSrWGKy1Wjy+KOD1n4t855rlFYsulIUknVT0ybuzfK2PZLp+PGkczGvo4aVOizq1YXV41NQLkLgh/T1lfD9gHq9RS7vUuzp0zKufhMV+rQmRykt7gThENTHkF5ed6vu7MWfGtMRQbczLqiWRLGDYOa8Ha+AVyjRaNQ4/U3vn9FrZLE8GazzcAz44agiUi2etq5IGKkkb7q9MHr6rKZqG6Bk0xymqzFllZjMLGe72ksmJ1sSz1zK2IEQEA9ETP0DJs87zptOYxHonMvYebjr1kf4yB3VY3MRLZbjxI/HFJHyOWdtgSCIaK89ml5IbdYT23rWRslEEVTGPqc7GCR1D9l6Cd0vIu6/EkcO9TqnrQbCRCYiIZCkQgcREqUCnYcdhvzqF4/xT7+09mt5auJIKOR01OFQ5FwdYQBd67B7WBLFv5kdBYXrQKmoa5XypQLju8fo7MrTs7Cf+vgoTr6IW+xAenmcfJHavu3kexbqFKbqBFGoZVq9jm6iwMevTBD5TaSXBxWCcBKVJSElqqFlXC3HFqu21I51Ho4R+2qKiYpPZ4ebzEyiSBpRZWsisk5Dtp4hOyO5X1RBgePo94ahSpwNKdPGVaCLJ4Ujk5lLM9CQSJRIiy8BJA5KKESc/mRGMpFSTAyO8vgOm3NpeWow2lBUagGlgqNtLHYM5LRJyumTAKlaE0l/ByHa65iMsIGpkzC2rdWWMsIHZAUPTOQhjUoImUYK0+xcJ6l/IIrLviPFxMg4j1n7tTzFuEY1kuhDGEHjMDJuW5n+icMT2g4X9+mah4mqIFJw6ildTI5V2L5lhEiBI5sE/iD9S/pxvLz+vGYdmdMOhF+dRAW+VlzKl4iCIO4sHRLUK0k9g9fRjZP3CJt1HcEIfISM2Pjav5nZC2N5QmzaUjv7x+css8JDTbhps8/YpL4TmRSjbNFltpj6QGQdiihSGQfADCLM8/Z1SWqDYto6/cH6fVH8iHs9xOtUvF53m9aPVrPF1k2DfHWXLSCyPDW4v6Htd3wq0M52bItRxn4N0+3XaZNgbX9f1m6DIMrYcLs9pzatEhttl2yN7TOKdPqSytwfQi16EMYPv9li2+Zhvj5gfwwtTz2uUQ064uyl8DBMYHGftrPOEqxbrt/QaApWLlb4Afg+TI5VuOvhiIEhQa0OfqCoVnV9QtisQxQR+U2cfJGwWSesV/A6e5C5Al5HN2GzRmtqjLBZpzU5AuieDmGzhj81lkiyRq0mG179rpm/KBbLk8RGHo4h2wO4e5fPuSugu+we0EkwKUZpWlJ7p9r2ouisIlN7hCEbmYgiFUcl4nQnUuUlPTGaVWGKkDJOg8hqx2e87q2P7eard0zO6rWyWE40tgdwz+6Ac5ZBueQkNiqTNEKxXyQi2x9iuv1m654OZrvT7T67Pn0oRCLprIURTP1DFEU4jkRFqeey7fE9fP3OtBjTYnmq8T/1Rlv9w6Go1LTd1BowWYknAqRidAL6uhTVuuCRrRETFUGrBb2dKhFIicKIqX27cHN5uldvpDU5muw3qE4iHY/ckjWoKMSfGkPhE9Yr1Id24ZW6iEIft1gm37NQOxO2SPq4YdWW2rHOwzHm/gbs2+Lza+uhu1Nf/kipRNkoitqjD2bArzFpS+lytpFclmxKU3vaE/GsZHvjKBODUvFsp1AhSsnEcTCDl3q1weZtU7OiCf/3z+/llnvG2TKp2GwFYCwnIPc3YN+2gJesE3SWdHMmk2KUHcybZWPbkVLIjD0eLnpfMnH2sxMLWgktQimB6zqZQmzdxEopheNIwkweZL3aYPP2yqzY78detYrv/ngXj49FtmeE5YQnm8J0KJ52iuJn9+iO1BMVweI+RWdJcfpp3XQvWsT2hzfzyDbFkn5F3otrIMp5CsUCXl7LsDarVSK/SdCokO9eSK5vMWGzztSORwn9Jk6+ROg3aU2OEDbr+NWpOKWpSNRq0poY4Zy3/fcxuCqWg2HTltp5QudBCPEC4ENKqfOmrV8HvBy4GzgXuFopNf5Er1lgMII7d+oIRG+X/heYgQaoRKUlTWfSf6MoWwzdXnRtIhTZv4bpRZ1RpOI8aJNPncmbFgpCkFIiVNRWBRpFip//Yhef2zTzI/tXrnLoX9jJyy7rZPvWEXbta3LNtuCJ32g5JNZ+Z57BKI0glouyzVbDUM/0Z/s6mIZyYaQdiWz6UrZ42okLoKbbr3EggCS6YJSXiCOOQRDq9wsIifR9QrXfA6Io4vZf7ubzm2ferl65ysFxJL/2/JVs3zrCwL4GX9hi7fdosfY7u2QdiDVLI7btkSxfqBgaE0mtw+33C557PuwZili9IkexlGfp6WcR1Kv4tSr3P64j/y964UqElFTHJ+hatAgVRQxs2ka5q0T/qtW0KuNM7duDdLbQtXyNLpIudTG141HqI/soL1mFX5ukOTmOVypT2b2dzhXrUIGP19lz/C6SZcaZ9x2m4xvXKPoGNJ1PKKUui7fbAnwI+MPDeM2CnsFs7fB5xirtQARxkfM0VcW4iLI9EpGNKKT68en2ZrsDNZGLt9IRBtKCaoh0YacjiUL9XEgRf7bez/C+CbYMzbzjsNqFtcuLeDkXvxWwfEUPixYFnHcW3PzLIR4Yjmwk4giw9jt73N+A2nafZ6506e3yaLZCPFersDjxNtl0Q0N75MCoqKWSrtlCauOUpKlLqbNhIg4OEqQWSTBOhlQC0606K8QwMjTF5qGZH9Ab+xVSELRCVqzsZfkKxXOfW+L6723i3kFrv0eCtd9jg3Egxia1gz4wJLj0XLjtXi3R6oewdSBivCLYuS/g0gsEfnWKu2++jxXLOzjzZEHfwm6KfQvIdy+ka1XE8KP3AbBzt89Sf4pW83HKXWXcfB6vUKQ2tIcwCOg/+Uxy5R4mdm1jdOujSY1hfWoKL58jbNZ0MfXwnlm/DmOP3wNege/slfzuMzbM+ufNNWYy8jAfOkwfsmBaKXWTUuru6evjmY2+zHZbgCue6DVLO4+24Gfb24uo0xnL/bXX26UgU3nH6dtkt2vPjU614XXRZbYgM1VfimLN+CiMCIOQMAhpNlrsGpjilomZvw6Xn5pnxapeWk2fKNTqT67nsHBpH5e/cC0vPa3ASxbOeVs75lj7nV02+/DznQFT1SBOU9KGF4ZRPJhPnQMT5QunCRiYeoZsdLHd2VDJ31TsYH87ZlpBdRRGuvdDoAuomw2fnQMVbp2FUqWXnpJnxcpe/FbQVrTtOJIXPW81l59R5KWLrP0+Waz9HjuuUQ0mMqrFN99N0hQOYGBQMj6lO0zvHGhy9833cf8mya6BKme++CWsesZzCVstBh+6m9FNDxAGARMj47QCqDciJsYb1Cs1gmaT+sQ40vUo9vQxsf0xqvt2MLJvlImRcYrdPUgpqVVq5MtdBPUqKvS55F9umvVrEPkNwskhXtpXYXDPrln/PMvc5khrHs5Fz4i0Ed+4DvpafCOzZNjsQ2mXz9OWK3q7PJ3moFSs0JIWYmYjEtnmcPsXUrbPUGabUmXlH82+iHQShBBxvrRJkUgiEvp9jz82zMfun/lirWd1w5LFHfGgQ2UGSzo/O1fIsX59H329NU6dajE26ROEyqZEHB3WfmeIzT7kd/icv8Klq8PVUTspdPcoFGG4f4qheW5I5VrTdcYZMbUN2iyipJbCCCEoFcXvlUiZSVkSAoiS+8Xjj4/w8Qdnx36XLi7pyYYoytynYoWank42bAzp7Znk1FUtliwp09FZ5I+v3T7jx/IUwtrvLHCgGggjzepPq5U97znn8PjO+3hoi6T7e99laDTi9DMW0qw3eODuKZYsEGwdgPEpSV9XxPiUIp9r0Gz69C7sZWJwkMqklmPdutNn0y7J8oUB66ub6ezK02oGjO/dS61S5/d+Vpn1cx+6+0cEjSoqaOGWunCjkEXvvZ6pyTqnbVjKXVe9ataP4UQnOhxprqcQR+o89AHj09aNAj1P8JrlANzfgB1bAl62XtBd1v8Skyet0T/E2RSlRDlJtDsT2XQHMwAxdRL6fSYykXa5dRJ9eZUMOmTcYRqgVmmydc/sqDysW+jRUc7jmwTTOPQShorR4akkF7yrK0+5nGPDKSVcz2X96mG+dfs4m+swsX+QxnJorP3OIA81YWBLwMs3CHKe7qESoX2IMAJHmuhC2qshDA+ktJRGHrP2Cu19HrKRybRnhK6D0HlTQqcfxr91tWqLbftmp4J5P/tFH1tnd4mu/l4Gd+2lOtWgszNPR0eO857/THqWruL9o1/kyzePsK1h7fcIsPY7SxxOEfWuIcH/fOK+ZPnHdwJIli+dYP3Tn8HgvltYsLDM7qEp/EAwWYHVKzyWn7SGicFBCp1dus/K1oCpGlRqukaqo6DYugs6inU2rO+gZ8kS5ODg7J5wjIpCWuODNCeGkY7Hxg/tJdo6BMBN73sBw7t3smDZymNyLCcqtmC6neOqtiSEuAp4z/E8hhOFCQW/3Olz/godgciSTWfKNpIy3abbIw6pY5FGLVQyW2miGWZfus5CJLrwevZT10SYIsuhoSrf2jvzhvNbyyQnrenEbwWJ02NmVoNAT/UkM7VSkvMkjXoL2fRZvLSb339pB48/PkKx4PDh222n3GONtd+UCQW3bdMRiI5iLOMqBY5URCqVc42iVPjAkaksa3a9Qdtnu9iBSVfK1kik6UxRvL2I96XXDw3VuH7fzNvvby6VrF9dju03PeZ8wWPh8kXUK1XGRyr6WIXAyznce/PtCHEH3b0dvO6FHps2j7F6ZSfv/u7wjB+f5dBY+z0wT+RAjE8dOAXv+7cG9Nx3C90dcPfDVRq+pOBBIQ8rTzmJsNXi/gcnGP75JAu6FUEomKqKJKrx2E4detywUrFjZxXH28srvjc04+c3neH7bqE1OUJjZA/V3Vvof90HiN7ybgC2f+l51Acewy11MbT3cVQUErYaLH3mr8/6cVlObI7UeTjQTIaZ8TjUa23EleZXQVJ9/pTmoSY0dwRcukbQVXYJ49xnJ5GBbI8iGIfCRCZM6lJ21jKr+pLKtppPzDgeSg/Qsyil2Ltnkq//auYH5us9WL0kj+MIgiDKRE3SvO7swEjEtRCOI5FSEgZaPnbDhgW4nsMH+4q4rsMPfzHIfaOKASvJfCis/c4Cxn6fuVL3gfDj76iIs5iiUHel3r+LPImUq+4On9pw8nqUnRwAY8vppEL7gEZFCiUE+/ZO8c37Zr6T9HoP1izJ4zgS348yxwW9CwrUKzWa9QatVojjpMem7VcQBiGu67BxQz/9i3v5xxcquntKfPOHu3ho3NrvE2Dtd5Y5XBnXvi7F6GT6/R6fEoxPwVknRUxWdY+IUgHu+8XDjE7Czr0SP9zfAekoQLWhn3eV4c6HJcuXz77e8e6bv0YU+NSHdlLdu4360C7WnP7u5PVH/veD9J96PoX+JUivoDtkewW23/ApwlaTya33P2UkZKPQmkiWI3Ue7iZTlGVQSm2Jf8QO+NoRftZTis0+uNu1ClNXh5OsTxyGJIKQFkubgbZ+bhwCMFEGvW26DynJ5EVnFGBoH4S0mj4799RnRSnluetz9PUW8P0omUnNqtPo54IoEnjetLp+EUvJCpMCElHqyBNFipc8exmnbx8H4J9+aaMRB8Ha7yyx2Qd3V8DTV0CpIJPvMuyfdugHqU06014zKmdRXDuRSjTrbbL2ko0kZmsqmg2fHXsbs2K/z1nn0ddboNUKkxQqKQULFnXieS6tRpPdO0fjiQFJFEXISBDFqZFGVhZgfHiCjnKeVivgxRcv4pTtEwgh+I976jN/4PMDa7/HgMNxILKOQ5b7NumoQ8PXdRPdHdBs7V87YTCOA+h0x74uxWt+PAvqJNNQUURt33Ymtz5AfWgXl35uTfLa7X9W5d7vbEZFEcX+ReS6+hDSQXp5cuUenEKJzpWnsOMHX8AtlFh26e/M+vEeT2zaUjtH5DxkblJAUqj1lSd6zXJ4PNoCZ6fPecsV3WU3UWTJBgayaQJZhaVs6pJxIg40kwnExdPZHhHprGgYhjzw8OisFCZf3AWL+vOxqpMZeJhBU6om47oS15WpQ5HUZSgiovh89fG7nqsLNiPF6jW9CCH48KIOms2Aex+ZoNqM+O6QnTkAa7+zzaMtcAYCzlriUC46oMCJZZhFpnbBRA/aHIz4+xyGpvdD+r8wkwVCgOfJ5DVjx3obXfsQRREPPTbOl7bP/BT+RZ2woDcfF0mrtvuJ4+jUwupUnUYjiDvbZycFIqLMvUjEEwFpkzvJ+vV9KKX4+37tnNz3eIW6r7hxxNovWPs9lhxuBOJANDJO+8QTzGMZRwPgjock16jGod8wAzz+5Y/gdfRQ2fEo23/2A9Y9/zeB9KDv/va36F/YiZPLEdT1CaggwMkXaY0P4XZ04VcnyHUtwCt3s+X//gsnl2fPbdfzjPd9Y9aP33J8OZw+D0Yv+kPAjUopoxn2CiHEO4EtwAVKqayO9KFesxwGDzVheFvA81YqukoO+Zwkikxtg0LG9QH5vEMQRBl5R5GZhcwquQgcRyQDjdRpiB2LNtUmmJxo8Mje2RFn37jEw3UlQZB68mZwYQZNqTOUHlcYRIkkZTZy4jgSFUfdpaMLvaMwIpd3cT2HZzxtAdVqi5NHG0xUAn6yzacgYa8/v4s1rf0ePx5qwvDOkEuWKjqLDk5OOwmhSMWYHCkod3g0GgF+EEcRRVrPJARxGpOOwhm7MEIISonkuUlXNDVOU1MtHhucHUWyDYtT+zWOvhCCzq4CfiugVm0yMlInl3MyTo2WdlNKIGMnQsQ2LGUaeTQ1G2EYUe7U+7vwLI9mM+CU8SYTlYCfbg+s/Vr7PWaYgfyBnIi//sSf869/9u/UjlJPJDoO3+OwUWNyywM88J2v8f1bA679hf69l8t6+OuJj7Fy/QoKXT3ku/pojA+hgoDQb9KcGsctFAn9Jv7UONWBLeT7FpPr6ifX2cuCM5/F9hs+xdSORzjjLR859ic2S9jIQzviQP0Ejgc25/LgXNwFpy/PUcjrNCbjGEiRrX8Qiaa8iTQ48UBapwmIJN94PwdCisw+9ODjscdH+e8HZl5h6TeWSE5ZXWwb/BvCMEqO1cxiuq7MHGsaaUiiKXEKhO7qawZVKpkVzUrACiESR6uru8gjjw7TUXT5xj3VE7KJ1VxqJGPt9+BcWIbTl3m4mUiB+eq7jkgii+b7bSKMXvzdz6b1GbswkwHZwmltN5IgCNm8bZJPPTrzX+qXLhKcuqqYRD2UAteV9PeXAKjXfSqVVnI82XtO1inKTl5IKXBc2TZRYPpX6GZ4aXTD2HVvXwcPPjREV9nla3db+z1ajP2eKOOBE5EjjUAcLj2dilZL8MnG7Ecd7rjqClqTo3zzf2/hxb9xOi/4+tkAOBeu5/2b/55TTl9M97JVhH4TJ1/Er07qBnZBgJASv1Gn0NWDikKCRp3SwqXkuvoo9C0h37MImcuT6+xDuh5Bo0auqw8V+Kx68e/P+rkdLZn7kIiXFcBnLiod9b5ff1tb/dn87TBtOTG4dRJc6XPKMsjnnDTPOZ6llMKoKOm/JtIQhtE0R6E9ImG2F7RHInZsH58Vx2G9B8sXaCWpbKpG9gcr6wyZ7cyx6uMzqR6ps2OiEUkKV5SNxJiZWj0I8zydHlGtNFizqouOcoEriy5SCvYO1rhvZ4tIwSPV+T2raTl23F6B3D6fkxd7ibMAcRF1ZJSTFI5M0xC1/WZTglI1MmPL5jvvujJxJJRSDOyuzIrjsN6DFf3aftMmeILe3iJCQKXSYmKiievq6IGJSmSVpFL7TZWlsg5SmrpoUrTS6KhJZQSYmqyzemUnXT0lXhk7WUMjDe7ZoYtMrf1aZppDRSBmgvEpcUzSlb75m8tx83m+eN1uQCSOgzxpMVd87x/gZBjaPUyhswu3UKQxNszE4CD5ohZC6F7YT+j7RIFP0KgjXY+pPTvJTYwS1qs0RvdSXLiSsFEj16nrJMKGHjTv+MEX8Eqd5Bcspzk8wNJLXjbr53siMpcmFg6GdR7mCD8dVwRRi9OX58hlCoiFACXbB91SZoumNdmZfilNRCIt4jQ/0s2Gz6aB2bmBnbFA0lF0CYJUOcacQzaqkI1ImJSMMFQ4TrYwlFiK0gxMjBRm1Hbe0/drFJyEcAjDiLFRncvZbAb09eS5tCuHUoo1exqsXFxg6dIyN/9yiG/usSFLy5FzywQEkc+pS7UDEUapfLIjFaHOyMNzMzUCShEGKlFbA/1ddl2J74eJ05EKJ+jO1ltnqafDqX2SQt6h5Ufx5+majFYrYGysQRAq3IwTo2unSBwG7fCYrtvp+YShIop0bYapoUjttr0Dt4zDMkLoqMTI0BSOI2m1Qnq6clxyiovjCFbtbrB6SQGlFP9858yrTVksc5Vf3jXEloF2EZJXj10Lv0yX9w2HVGuPU6lBuQT9C4oM7humWJCE0RCdPV2M791LLp8jV4Tq+ASteh23UETWqzhenshvoEIfFUU4+RLS9RCuh5NbR1ibIr9gOWOb70fly6jJffSf9oxjfCWeHOHxyC07gbHOwxzi1kmQosXpK/I6LSlTfCmE/nK7TipvmlVg8v2IXC5Vb0qciXhQbXThZ6unw4VlWNrnEYRRMjjy3HbZymwWU7Y4NOtkaFKde7MuDPfvbqtf1wOQ9FpkBzZR8mg0Q5qtCD/Qcpqj1YjVEgqlPKev66DSrHDqijx7R30m6hGuBM8RPDgSnZApE5YTj9umQAqfkxZ5uLEpJrUL5nsctcu5GifCydhpGBqxgHZ1Jdd12Dc4xQ2DM/8jd34HLO7RDnekoFRwqNa10tLERJOWHyU2Zu49WXlZLQst217Xdp8qxk3HvJYVdVDKOC66Pko/IpqtkEZTpzh5rqSzKMnnHaJI8dvLJcWc5ItbA87vgM6cvt7nb+jgZw9VuHVyxi+XZR4zWxGIYxF10Mcsueqa93LVle8BYschwz2PSzasjBif0s7+4BgMDDZoBZBzIzpLdRYvaFIoekgpadbH2Ltnis5Oj1xxmFLfAl1gLR2ao/twimXyPQvJdfbiONqJAIhaDUQUIqWDAobu+Qn/tDnPR97xBdSEVlpTo5+Z9WtyuETWeWjD1jzMQdZ7ehZw5UIvmelzHUGkFK6TSph6Xppv7DgiTm/QP+BOvJ0Tq5xIKRgdqfG12yd4aBaaSb9uvZsoRyXHlM39dmVbJAQyaUmkeeLZHG+9jd52f/Wp1MHIbh9FKnn4fojvR7T8iCCICEJFy1e0YgdCSsHnNu3vGbx2nUtft0ex4LBvuMnaVWVcV5IveAwNVvjgbRUWSfAE+PFxFSVsf5L1q3MptGnt9/BZ7cIpPYJlvW5SpxSbpbYNMf27rycKpBSJnRhbNt93xxGMjzf59r1VHp2FwMOrVjt0dzjEfktS9C1j5yAX32vM/SiNDrbXU6URhKxDkH7OgZaz25u0pihSBEF0UPst5PT95eqH2y/GhWUIFZy/Js9LfusCbvzWnXSWPQoFl3rd579/UUm2Lcf/E2PDg09yTmUu2u+JMh6YK8ykA3HsnIfDQwhYtVixb0TQ8OGkFRE5F1oBdHVAb7dDoZSj1QyYmPBZtryTfLGA47l4hRKF3gUQRRQXLsfr7KFj2Xry3QvI9SzCLXTglHug2E3TLVHwpwjH96GikKH+0zj97He1HcuxdCIOVvNw9QVH/79+8y8bbfs+WmI1tZej5ZvPBa5WSo0fYvsXAB9SSp03bf2HgM1oZbYrgC0ZcYYD7+tEuVnYwceTo1vA85ZKVizMYYosTQG1yQuWMu2R0F54nCm6dGVSnHjvgyOzIs360kWCVQtzaY62kw6ClNLLWSUoM0hoV2AhMyjJqsy0k5WNzL5uojFm5jYMFc1WSBgqPfgIFUEIfqCIlH6ec3V6Sd4T1FuK63a2y15e1i8S+ciPvnIlg3sn+fufTgDwnuf0sH7jUqYmqng5l+f9/p+w++E7+MonvolSiko9YuP6LkZG6snsshdL037g51PxMc+9wYfl8OgW8JwlkqV93rSO8bQ5Esa2ndhxMOs9TxcY53IOQkCzGfLgpim+umvmpVlftEA7Oo4jyHuCpp/WJHSXPar1AC+uuzBOjkHXYrSfj7FpE3EE9nue3Ydel0o4m2hDy48Oab9dJX29Gi3F1pGA26baz+vKNS7XbNP3uz85M0+jFbFvPOT6fRGvWu3wst86i4mRcSZGq3T3dfCV72zDldBfdqg0Ikp5fYwLezz8OBWz2Yr49GO+OeY5Z78nynhgLjETDsSxchze9r7f4V//9mvJurf82YV8/D9uP6z3d5ZgYW+E7wt6u/QEW6koaPmKRhM2buyl3NdHZXSUfKlAvtxFvrtPRx26+igtWUO+eyFOoYSQDoUFy4kWrmUszFFwFAX0vauFQ0dQof/sfwDgLz7xJl71+H9zwT+5iRMh+l7fdmyvHrt2xq7hwZyHj5+XP+p9v+WuZtu+jxYhxI1KKaPItg5418HU1WLHYRS4a/rnx87Dm+PFDyilPvyEn32i3Czs4OPI+I0lkgVdDp0dbmZ2Mh2EA8mMpSmqdGNlEylFIpe4d88kH7595puqrXbhBes9PFcSxD0dHJnOVEaRIp9zkhnY6akYZnZVL7erS5ltDAf6KmcHHTraoGcpW75OUYoiRRAq/EDnnUfx9q14WaeDgR8qRuqK/qKgIy+oNhXfHz78r+zmn/wbxd7l/PXLr6Sj6PDR+/SN7j3P6cF1JfW6T6nkkcu5vPM7g+bY59zgw/LkeOkiQW+HQ2fJSZwIL3YSTIGwUpDPybbom+7zIBNFo917KvznvTM/AFnvwTNXuolSVGeHS87TEw6tuMFjEGrH1zgF2ZRK4/BknX6zrP+mNn2giINZZ4qogyAiCFKHwXx+y2+3Xz/Uy6a/hh/qlLCCJ8i5+jNrTXVUKZrnluDuQ5RTzEX7PVHGA3ORI3UijmXE4dreVwMweve7+JO15zzp/Zy0ImKqJugsKfxAcPZpJaYm6xSKHp7n0tnfS21yip4lS8h19kAUUViwFK/cQ9fq0/DK3YStJh3L1pFbuIo97gL2VJr0FDx68/peMekrFuYUexvw9i//nJ995ie88rGrk2M/FNMjFMbJMKlZB7vWzhlvI3zgX/V7DuI8/NfTjt55+ONfzZzzEDsL12WjCEKIMaVU7xO8Tx3AeXi5UuqrT+bzbc3DHOdbeyPOHI84fyX0detcQnP/Nz/c03P12lIIlKJabfGrTbNTVHhmvx78tPwoGVSY3G2TbpFNZTJSq9k0o7R4Mj1+w/TfOvPjl12fna00jkMQz1iGccG1cRDMe8MIgkj308i5MFRVOAIaAfxqNGIw0gOrw613WP+c/y+zlL7pvT8ZP7wdWOYlNwwqziwEnLkE+rpcglARRnowbqJlRiDB2ETaeE3XS0xNNblv+yzkGgIXLtfphmNTAeWiPo4gjHAdyVQtxIm71cu43srYchjpQu9sfYORoBXTfjbT+qY0Wmgk1U100ki06hQldUD7DSOV6OUHobbfMBIUPMHeqZCco+uf/BCu3xfxW8vSotELy1oV68lwKMfB8tTjaBrKHQv+Y+Bxrj3j7wDov/CfeNUR7GPHXjOxAaWCIl8qsGNnFSaaLF6kGH18gKUr+ti9aSurzzoDr9wDQNisM/bIHRQXrcQtlgFwS10s7XIpdPewdaLJYCViXW+RDldQiwRlD77xmrN58Lcv5Hf+5TT4yhNHSKZHJAzG8bjmIO+Ldo8/qetwgnAuOpLQhhBi3ZF2lBdCnKuUuvtwtpVPvInlROf+Btw74DNRCZKBt+nxoJSKZyenz/ilyiYDe6qz0r31wjL0dsg4pUC1OS3RtNSEbD501rmYHjkAkvPKPqZjtjcOg++HtFppxCFpyqXSAUes+korUIkjEUaKjryknNMHt7emktznFR3to6D13tFdrxctECx3nng7y/zi/gY8MhjgB9rBNmaR9kpol2bNqoaFYcTAvgY/HZ95+z23pGfuJyracTCD+yBQ1BtBm22aY06KvKPsczXNflPnPivJmsXYdWrDimZL//WDCD/ToC47N6IUNH2VRB7CSFHMCbryuibshkHF9fu0AU82FBd16vfdXoEzj3Lc9/IVDi9fYQ34qcyTjSIcq6jDtb2v5pcjEUuvfCbDN7+JW9+w70nvx3Ogv0exYVVEMQ/LFgoCP6DWgDVrOulf0s9JZ55EoaODnv7uuCeEgwp8anu2oaII6enZexWFTG17kLG7b8K559uc1uOyqJxPaqkiBe9duYpwaDvLyx5Dh+E4HO61EH2v3+8BtD0/ENl6ySN9zDB9wPi0daNAzxHsa12c1rRFCPEhIcS5T/QGG3mYJ9xdg4nNLTb0+JyxtpTUOqR50e3NqAx79kxx86bZmbVc0+ckaT+O1IMiz806DMT9GvRyqnnfTrsGfLq+PeWhPeIwvcbBzFamfSOyg5bpkZk07SJCMTgZUmmp/WYmpw/YjlZ16cmkQVnmF3fXoLqpxbIOwYalHq5LUnwMqcOQVVBzXcm+wRo/2z47cl+nLHLp6nBotPQMvxSKaj1iqh4hBeQ9HWEQQujIXRAlkxQAkQSh2vtWgFGKak9RzNqgcS6McxIEaYphGKWytgcjsd84+jFSCWkE0JpWDvLD0fad3H+U47jZqDexzD0ONwJxLBwHgPp/fh3+7jqe0d3kOR97K2/92JHtxw9hz7Bgz7C23UZLkc9NMTgu6BmY4pQF/USBz94de1i4bAHF/qV4nT00x4cY37WNoFnH7egCoLuzj3zfEqa2P0T3hnNpIFhRiBAEhDhsmtL3ibv+6S386ne/NFOX4pCpTya16dqDvB4eeYbjfkxL8z3uzeKyNQ5CiE8ANwLrD/Ue6zzMIzb7sHlIIUSN09eUyOcdcjmZyLBCe8pAqxXy8I76rKgrPbtHxAXHJOoxkYIg1GkYOS8tmDa1CLpour2XQ9YZyEZL2htlpVEVM+DIFkaHoUpmKo3zn2rR6+ZcYUSc161nMs1xSyFoBornndXJ7y7v5q3X7UrO8ewi3Fuf+WtneWryaAsebSmk8DljtYPnSTzPaeuQnnWuG42ARwZasyIV/JKFgu6ygx/3mWj66W+dFyu7CZFKzBqpVodUblYpEUcc21OSQE8cpM3hALKpiCrj+McOQxjFToNx+lMnQwrtkjhSH5epczAHV/d1LcSTTUuyWI6U2W4od7iYmfSB/7ucP1l91oztVynYNyoYnYDVSxW5nGDLw9tZsLDMylNOYmz3bqYGtlDoXUDYrON4LkJKWpMjSMejMbyL0Qdupe+MixFujlJlL5XtDxLUpnSq04pn8aKLXToWL+fSH72bV4/dDBx68P+Exzyt2NosH4//0aFqHoQQb+bQA/cbYyWkA0UZDhSNeEKEED1GpUkptSWupzgk1nmYh9wwqLhhsMofnJJjzUqdX6iUroFwjbqSgtHR+qxowq92oa8kkoJjPROoZyrzOYdSyUUIQasVks87tGLVoyBQuMk3Us9UmoFHmjudRhiiiMzgI3Uuso/sDGWYWZYClCDpiwFxDYZMu9mCdjY6coJzLjyZZ7/x73jrdS9L9mcdB8ts8MNRxQ9H6/zRGXmWLPLiHiZivxqmicnWfrPnM8FqF3o7tOOglKLe1J/hOrrIOFKKnBsP/BMn3jjs8U4cQcuPcGMVNXPMYZjacbauwfRuSbpvx46DKYqOVGqTUmi5Vcioqqn0PgM6IiLRdQ9uvG56hNFimW2uUQ3+oFCg1tx//WxjBsn/n7iGdzz7YPPpR4cf2/vOvVrCdefeCs8oDlPq6uSG6zfRbG3m1LURHSWHNT39FBeupHPVKYw9fDtjm+6nPrKHvT//NrmuPlY871Vs+84n8UpdLDjpYa69z+f7t942K8edZT+HZOyzB9wumsHIw6FQSl19mJvejXYWpr//SdU7GPlW4Lwn2jaLdR7mMT/f2qKQq9Hbk6erK4+XcwlDnVc9MdHg7s2zM/o9s18mKQ1OrP3eVXZxHd24qa+/g90Dk5TLHvm86f2gnYAgiNpmV03UJKvxng4y0llI2L8+Iop0cWcW4yyY1WGcR67zo/UMpdkuVWpR3PDt+9n6yB/wrG4IIqgF2rGYDHT/hvM74M4qnJaHc5a6RErxpe0hz+4RdBcE39ob8dJFYlacNcv85AePNrnck5SKLuVyDscRNBoB5XKOiYkG98xSkfQFSxwKOYFvUv2UtuMgjAfoQiCFXg5CLWWcRBFV1iFPI4PZBpZawABATVNfUsmEgIqjlNPrJIzAgnmPBKLYMTApTVLo6IgQ4MbLka+4uIsnbAi32tX2/NxewVRLq6vtrSo7UWA5Yj7ZaPCHHQWmascuVcmw+YEP8TfLZ8dxMGzaJcm5sHSBYvtewe7vjLBxdcTgmF4fhPDYtohm60EKPQu45yuf5tEtLdavdCiUdnHzHU36uyN+vV6lY9l6hJREgc+rXv+M/WRkXz127QGjD195+vVcccflyTawv1NwpSiw7Cs/2u+98vy1RHdufcLzPFbOw+ESRwiS5Tha8JVpy6OH6vsQcyeQNNYQQrwceELlJSvV+hTgsn7B00/tpK+/RC7n0mz4/OqBEb64deZ7OlxYhlW9adFgwROUSw5dZY+Npy3l6b/5Cm64+pMsWNLD6z/5KA/f8F6++i//TqHgMTnZIIjTi8wgIdspezrtqkvpjKUZaARh1DYYMTOYriOSWVX9XmKp1nTwkVVfCiOtG2+otnRaRivUzkbOEeQcPXBqxJe0M5+mdBg5yFetdtg+GnLqUo9PP+bzrG54dOrgzafmotSjZea5rF9w8VnddHTkWH/6WjY/uJW77h/hS9tnPsf+Wd2wpt+NZ/q1DZhGcGGki5GLcQM241Q4Mo3YmSZ3WQEEU7thetFkydZwCCESmzXrssIGSdRQikT22UQwjO2GsUJaGOlmcaDt0jzXNqttPIgnCwquiKMT2n6lgKKXNu5r+Ol+Ki21X7+IgzEX7fdEGQ9Yjg7R93rkmgW88lf/eUw+z5FQLsJErPa+fKHilLWSH97R/n06/9SI0diBX9ANJ526lC9/Yx8XnwMLF3dz/wNjrF7hsWjFYm792S627ZGcsjrike2pts9fX/12qgObWPz0F/Ff9dN4/inLOWXnj3jJT11WLuzixo9+n//+7J/why/7CL9+1cv59lV6HJztpH1t76sReRfVPMAYKI48TJdq/edTc0d9nf4iblo5C03itgAXKKWyTsB16BSnq+PlFwCXAe8EPkya/kRcIP0CdMrT+ux+DoaNPDwFuHFEMXL3JGcvr7PxpG5GR+vcOTDzjgPAyh4HKcygw0QdPD4Y/+J+5g82ctIZa2nW9QzMqS99D29YvJ4f/NffMzKitQ/NLKYZcJh6B6DNmTADimwtRHam0myTRQqSVIhknRR4LohQp2YAyLjIO9tRt+GrZGARKYXngBT6pmbyvEueHmToAZUeLF3Wr493pBJRcAUDowHP7tHrFniKwXgC+VndcMvETPwXLPOJG0cUk78cZ8Mine531/0j/GrP7BTnGsehFTvTQJzjp9e5ThqhMyII2kZMZEEhHZlIuGbNL4ogVFGbYxGF2gEJM+IGyfaxw2/2Ywb9WdU1IFGk0vUZ+r3GmQlCvSPPEfihohhHRINIO/jGSQoiKOW0LLNx+s0+zD71ecOzumMJZ4c2lbpn94hZUb2yWJ4s3S87n5vPfZwPvvXYfF4YpY4DwMCQYGBI28JlFzk8tClgYEjw+A7J+acLTn7G07nnR7exb+cgKxdHPPtP/4odP/wKj+2coK/bZ+LBXYShNkTjOAgBb3rLOfzjm/8FgI/s/g9+459fx8derushNr/y/Tz0iR8CMFJpsOvBD3DT1nG+HR/Ttb2v5qs3/Q1fO+90+l/+dMYe34u6d8dhn+OJFnmAJEXJFDt/ddprr5i2fBNwE5koQ+a1u9FpUIeNlWp9inB3DT7zuM9dD4zxwNYaj7Zm/jOe26sH1a1A/7jmPcGi/jxv/tD7k20u/d0/YuemXdx/1xa++pcX8IW3nMbAAz8lXyq0ddBt7w6dLYo2jsP0BlLpspGGTWcw4+3aiq9T9Roz0PFcEc+SpspQnqsLv10Hcq6u2yjmBJ4jcKXAi9eb2g7jOOjIh3Yq8m4ahQA9++lKKLiwtENwUacuUO0tysSpsFiy3F6BL2wJ2LFzkrFqNCv2+6IFeoBdb0WEkWKkqmgFUG8p6i3VltqX9HHI2FTWHrOKSOZvWjidSrnq1EJd32Aig2G8DmirlzCvZ0UPTOTD2KpJkxRCd4gv5vR9KBfbsefE3brjXz7P0X0gynlt047Uedz6c1SmsWUcURHgSkHJ09KVL1qg7fWliwSdecFLFlr7tRxfXvwv3+LWiwb44Fs/frwPhRdd7HLjbSEDQ9ouJqpw/+MRux+4jz3Dgh/eoXjmM5cyfPGbUZGeEHnp336Q8154MSuXwCmrI97w+o2Avl9c/d/3JPv+y2VrqOzdyaXnwuIv3UTzB/cDcNe7BH+4LuTNX/4lz6vdhTx3TfKeHzywE4CRr97B0jNXAiDPXcO/feVt3PH2Q99Uzb3naB7zCZu2ZJkRNuZgY59MZu4dKegsSp73go285mPaqCuDD1JedDpf/JMzqU5WmZqoMTxc5acPVLjs3G7e+5NxrnnrWdx/19a2YumsrGq7I6E/K1uMKYRIlJWyr2ULoPdXaGqXeg3jegkz02kKrcNMNMIPTYF1mtKhVNrh1lwDU2RqPsukQHixpGX7rKZ+73eHkmOeMyMRa79zm405OG2BTBTSWoHuvvz8vnTQ3FVMu8S7jh6My1h0wEi2mhQnM4A3namzqYdGptWR2laz9mg6RhtFNaXSVEJju3of+98bIJ1IMGlMQBJByaYkmnUmumDSnbLP/VAltRNB3Dei2tJRC+N8mEiGl5l0+MbuyJzLnLPfE2U8YDkynDPfzjf/98+45pxTDvs91/a+ui2l51hxzskR9zyuDenP/t+LqOzZxp23PEzOg9Vrevnad9vD8Iv7FPtGU5Natzzi4ktW4Teb3PaLQZ7z/HUseN+P6fzF57hj7W9xw0VaXerrr3w/N7//1Xzr0tVsGTjwfPnHHvsFfRf+u144SNrShzYcfdrSux6b2bSl44mNPFhmhJN7JcVcWoysFCzqz7N4zSreenaR3zvJo7zodN50ap4H79nOpscGuffBEcYmWpyzOs8Dm6aY3H03OzbtSQYIB4pAtP/dvzdEVq0l25TFRBnMGGb/9CbIRjekTFOY0sGO3o/r6MF/Lp7plEIkywVPD8DMbKeJwJhoRUdeP4q5dJ2Z/czHM6UWy7FmY5/+3rYCRcNX1H3F5YslbpyaVMoZB4HEaQhC3YytFSg+vzlIlM9S9TORpPpko4NRZAqw04aWJlpoHAfIvietVTJF16nSWjaFMX2vcWSyET8dWTBRRG2XJr3QRBf1vvQ5FLzUmTC3kqKnIwzlvKAjl9Z7gN5+JrXgLZYny+YPnHrYjsM/fEOn/6jRz3CNasx6MXdfl2Ld8tRAjOMA0Bjbx4++9zD3bZLU6vD17+2fv7t+Rfr8mWcpXvKq5/DwfTvoW7uR3/6j32LhmRfxz+vWcNWV7yF8x7m86GKdlf/bX/5//Nv6tQd1HAD+ZMMzkMt7D+lEaUW5o3vMJ2zkwXLUXFiGJZ2yLVe4u0PyyUe0l/3e5/WybGUfb/rcZoQQvGGDhx8oKo2IyYaiEShOX56jkHcoFZ2krsEoJmV7PjgZxZbpX10/iJLog9HGB5NKlI4iTH71gQquTW51WmRN2/uAuLAzoyefvK4HIu3pUe01G9kUjuzsaBqtgC/vCM0xzRlPwtrv3OWiTm2/5rtohAKyYXaT0iNj5wHSiAPo737BE+Rz6Q+054q277t5j7G9tGZBy0ebiKGZ6TfRB3M/cCRJp3rTbVvvu1361Rx3FBmJ11RFDXQdUqTSSIOJIOqajlQlzrwvW/dknmejEVEc6XDiNEYbebAcD17rFJ7Qeb2299Xc9kejvG/hH3DD338dSPsdwLHveSAEvOAZDlNTPr94IL13ZKMSB2L5QkWlJrjyTRfx/etu5c+v/wGPXfNB/Mo4V//3Pbzn83+Dky9x5yfex7d+9OSk0q5FFyFOjzz847qjjzz89RYbebBYAFgkoaegZ/magaIZF1WetLY72WZktMF3b9qWDNY//ZjPF7YEfGN3RFdBsHGJx8O7W2za3aBQcJMUB8eROE7aiVYIknSmtGg6TjUK29MXdFFmWhAJJv1IJWowaXFlml5hSDvgmoZW6b7N9tO7/roOSeqCE0cuTFpTut/2BldAkurhWGu0HGMWSSjnRJKSM9FQ+znbyax7rLLkhypp+KhrDgSlvEwcB2MfZhfGETeOg3HOzcDbRA2y9mpsC1LZZK2Q1t7bBWKHJm462b4/E61Iow4G46QYm/Pj+0oQCz2kr6f3CXMc2ffr66Piz1bzLq/ZMje4Uhye4wBw0X/3JY6Dea/oe33SF2Kmee0rV7Co98CGoRT86qGA5/5Re2W3cRyeeVb6Pi8VcWRgSDBRBa/UxZYByZ8/7cV87CM/4er/vodzN0a8//X/wC3/9rfkSwW6O/R73v/t/2TN0hNj+l8IoYQQVx3v4zgabOTBclS8aIGgsyCTmbcwUnQWJcW8ZHA84I59EQOxMMz0/OTpvOX0PCuXl/H9kEYjwHEkYRjhOLJNYcmPu9kCNJt656ZeIDvbn40mpAOD9POM/nySytTmhLQPEPxAJYMJUwuRXT89YuE6om0gkZ0FNfsPp400jIzlNdsCc65zZnbC2u/c5EULBKWcwA/1ALoV26or9Y913YecA/1lp232Pts9PueJjGISFPKSYt6hGe/MOAImumAaxxm5ZBNhAG2jnmsih9pGvLjAoOWbGf20rsLYopF2brTav4ZZRbZ0XXvURH9u+rqpddDHnkrWTo+iZN9vBm6OhK8P2MiD5dhysIhBttfBwfofTH99ptmwMuKxnYeeGfvzv7ucia0P89kvbH5S+z5jXcT2vZKp2tEcYTsHizy8b+3RRx7+dquNPFgsnFuCjnx7LvQ5p3TT2+Xx8QebfH0gTByH6VzUqfseLJJapenTbziZ9Wu7KRR147hi0cPzJOVyjn+4ZYK//+m4LqYMomQgEoZRovwCGcWjafUOBjMI0duKJAoRxDOpRmEpTYcwEQijyhRHNUSqzmQiI/mcLhZXSg+mzKymeUz3l2Qyq6lnOU0KhY0+WI4VG3OQdwWTDZWkKrlSd2VuhTDR0N2ZS7n2eoBy0aGYl7po2kvtIueZyIOgWNQRxELeIedJFi0stg34TeF1tgt9FCkKOZn0YTF1DqaI2hRhO7HzYZrImb9KafvVx2n6U4gkSmg+L4yMvQqKeUkhJ+ntdHCd1HGIlEqU1ky6VtZpMGNs42TIxN7n/JjAMseYHjEw9QvXqAZq9DNtaUnTMa8fapvp+z0Uyxcq/vKfXte27okcB4BfXX/9k3IcFnRrA9x43cPk/+dGXnTrPftt88yzFH/x/lcecj8mKnE42JqHduxQxXLErO6RmZl4wbv/5e08/Xnncf0DB84xNANxgIoPlzxjGa87r4OJpmJgxwitVkiz4dPVU4odhzzFUurtm+JKPRuoZzmlEOQ8ievIZACedq0VmfQjMe040hlRN05pEELv38yMeq4ZIMnEATADpOyAxgxwjEykYXoxtsw4FJAOOPKeHpwZ5RqL5Vhw2gJtS0GkH0ZCWApBECnGmml/k+GpkFagi6OjSFFrRPHAHUanwtgGTV8WRaMRxDUBilojZNnKfp5xyUlJ9E8KKBUcOoqOjgKEptO7ouVHSQqUsWHXEWkdRGwiXWWXnKejnP29eYBEttVELUCnHBrKRW3L9aaur2i0dCO6elN3tk8dfpE6Jpk0Lp2WqO8fnqPTtbKTAKYexGI5VpiIwaEG9wcqij7SSIPZx1knRbzpD89qe21gSPCRd3z+sPazeolKjumPth44GnKwz/+PcR0d+Np5pzP8msv4/sXn7Lfdz+8T/PP/+/Ih9/Xur3zssD/X0o5NW7IcEc/qhoVlyURdN15a3u/yyG6feyYUedHeNXnLLR9j7SV/jBCCX3zq97nwDZ9JBvMffeVKTjr7VG654Rc0GgGLF5fZtGWcFcs66Osvs3D5Qh64azOOI8jlHIIgIggi6nWd2qPTINIB/fSvs5klNM3msipLQqTRiOnbBYFOl9JOShqZKOQdncYQRMlAyKQjZWdAs2lP2ZQmk95hBiNBmOZvm/SNz23yzfnMmZGItd+5xXN7BT1FwXA1IlLQXRBMNBQlTxBEUPMVoYLegmD1Qo9SwWHT7gbVFmxc6lFtROTjCFshJ5M0pHLJpeVH1BohhZxsS1VUSlEqurHzEbYJHzjTnO5CXjI2GcR1RCKpl+jryTFV8Wn6iiULC4xPtHBd7XxU6yH5nKTlR4mak+kZUcgZe4NiXjI8EdBZlImDYWyvGadGeZkISdY+s/ZriqwhvQe4Dknn77lovyfKeMByeJh0pSNVSsqmO03fx4FSocw2R1pYfe+7P8nZH/wDAG798/9i+7+9AYA/7srzX5PNw9r30R7DE3GwtKX3rDr6tKX37rBpS5anMKtdKHlp19exuh5IjzYUX/7HF7J5zwMszxQ3rb3kj5PnF74hDY8qpfiTL+3g0bsepLu7wE8frvHdnw8xNBFQq/nc9ss93H/nJqQU9PSWOPmMNbRaIa1WmPygm8G/6UQLaUqEe4BZQFPgnBZo6jxs/RpJV2zPk3ERpsB1dQ53seDixK8tW1qmryefDGxcR0s/mlSmnCdThyX+PTaa8m4mn9qkVKRRkJn5H1ksB2O5oyMMfghVH26dhMGqIucIFnY6nH9yieEmDDW1NKkfKEYmtEO7tFvSaEV0FLTdlUsunieZrIasX9vNlt11tu1tsmRhgZwnKeQdOkouXZ0erisJQ4WTidaFEUlKYFpHFFGrh5TizwhDHY3wXEG1FiT2PTjc0FGOZkSzFdFRdBLHoRSnVpUKko6CjJvR6QmAqVpIKa+jJCZKYZwT0NGD6TUSprjb1D1BquLW1+VSLsik+7bFciy4UhQOK5XocAbjB9rHgdZfKQp89Oz8E773YLzpW29Inl/87+m4YHyq/bf6WEjHGt676/C6TJuayqN5zCes82B50mwP4PvDitVL8py8xOOj//P/ce8un/NXevjNJmGzwoVL0kE9tPdQmF4w/Wdf3cVfXr+PO6uwss8hjODTt1cYnAx5380TXPXjMYqlPGGo6x08z4k70qYpSqbuwgxMPE/iujJJJfJcmaRWOLEDYVIQZKbuQEqRdLrO5SSFvH6u9ycol3OsO3lhUlfhOGlqFOhBiEnF0J9DkpIkZZrfnU2lkMl7Z+XfZbG0MRDCjSOK6/dF3F2DZ/cIpuLC6IHxkB/cXyVQ8LIzi/zNh97I7rGA0UqoIxN5SUfRSdIDC3mH1at7eGyfH9chQH+n/iJLKVixshultLDBzsEmjqMdAEjVi4w6UrnDSxzrMFKJ7HKqagTNVqSdkpzEcwX1ZqQbzSmdUui5ktGpkChK1Zm0JLJKCqtdRzBRi/CDbMF0KskahOaRRhUg7Rxv6qxagSJSiuGJgIlamAgeWCzHgsMdXB9qu8PZR7aG4hrV4E/vbR72MU7njof0D997v/Q+QDsjxrn5mxW5wz6mmeQ9K1Yd08+bL7jH+wAsc5dzL1jD1sf3cs4V/8qLP/ppzjz/JC6/6icA3LXviafgLu0R3Dze7o7fvjOgEUGvC+uX6JtJY3IXHV0d3HvHJgoF/ZV1XRnXQAh8P8B19KxmLufgB0HsXCi6u/M0mwFB3AMCSJwMyEQpHIHr6tQok7YEUCi4eJ7eptUKqdcDBvdMMDnZTGogwjCdQW35Oq3KpDs48TFmJWb9IC3ollIXUiXylrbg0nKMqfqKnpxWVOosSb7xSIvBCP7tbi1hEr3tk6xfmmd4wk/SgoJQz9qffcE61p/3dD77vU/y4COjdBa1w12p+kxWAuqNUYQQTFQCygXJZEU7GY1GSGeHixA6hSkIFY1WM5nldx1o+opyURJGaUfqZiuCVpQoo5m0QFCMTvh4rqCUF0nalKmTyPacKOZ1T5pWoFC+SiJ+1UaUpCtlRRhymZQq3WFepy4VXJHpNK+fl/ISOIhKhMUyxzDRjelk1x1J+tB7XvW3+62b3sTtUGlTx4P5VvB8tFjnwXLEvO4TDwPwHiF4zVqX8YmHuCJ+bbueXDyoLGs2t/Yzb9zA6z/1GGcWYGWX4IZBxcVd8Ozn606Z3/y7X2dw9wgLFnYwOlJj5eo+BvdOMD7ejCMRkq6uPNVqizDWafcDXXTZiuUizcA+K+eaKLkEEVEkCCNBqeQRBLp4Ug9OFMWimzgexnnp7s7jOJKxsTphpPfhujJJo5KyXQXGOCt+EBeMZlKXwljlSQraZkMtlmPBlA+PtqArHzJeC3nxWpfzzlkMwH1f+0sGa4pLFxRxXcH92xqcsjxHvRmxeZ/Pz6++j1devJN1vZJqI6LeUnR1OExMBTR9xace1T/2f/60Ep1lj6mKHuA7UuD7EY1WlEYWIlOHlIoLCCHwXG0/QaBitaRUJc04FSbtSEsn6x1O1cJkcsDUJkmhiFxBIS8RIkrsMYp0nYOUgjDYv3bK3CtagUq6ygPkPYlSOo2r2rCjC8v84nAjEzNVf3C4+znWzews+2MLpi0zivk+rXAFlQgWuLDZP/S2WX53ncdoJWRBp8NjgwELOyQXnd1L34IynT2dPPCrbXzg51MA/MX5HfT3F5maampllCAtbiwUXM44dy37dg2xa+cEQsRFzkEaARACgqC9E3Ux7yQ9I/I57ZSUOws4jmRkuEK16tPyoySyUe7w8P2IZitM6haARKnFdJxu+VEyqHGkkXqVLF9WZtfAVPJasxXyiYfmXlGVtd/5wfP7BL0lyVQj4ntDEXsf+Aa//9zf4ZW/eTKBH3DLz3Zw3jmLWLJqMcO7h9myeYTdw03CCNYtL9JshXR35fnsz8a5YInDaevLrFm/iF/esQPXEUxWQ8arIYt7XLrKHs1WyGQ1TCRWTWqQiRjougLo6fSoN0NqjQilVDyY19u1AkVP2aHWSFWasj0hQEuwylhNKdsgsumrRKGp5afOiRFIMPcTKQSFnKDppyprpnBaCtiwrovHtkwSKfji1rnbp+VEGQ9Y5ibTB/WHU9yc3WY2i6Ff9bKFfOn/hp7wGA5WMP3/lh19wfT7d8+93/aDYSMPlhnlpJxgSRFO6xHkXUFfWbJ5c3DAbYUQTOz6JV3Lz0/WfXFrwG8u1fKLL3/OInJ5j5HhChNjVWqVRltaj5SCqakmQaCoNwI8T0Jcu9Bshjz2wA5arbCt54OZtdS9IvRfE1UAM8jXzxvNiGC0wfh4MynIDqdpy09WtGcURQop09lQKYyyk56xNBEJvV0s6+hJhodrOI7gX+/SKSJ//rTSjPwfLJYjYVdF0QpDco7g0h7ByYs9uoqSge3DTE01KRUkjXqLV/7r3XzmjRt4z7du4Y8uvpCX/c6Z3PLDh+juyjE23uQNl/YyOtZgcqrF3oFR+nvzBEHE6GTA2qV5Gk3tBDiOoFyU7Br26elwUHHdTxhBIe58HYaKyWqQ2LFWbtL9VAp5mdhjYneZ8W/OExRykko9SlTTiCVm9b1A76vaiJJoghDgZAqjzS3HRDEKORk7OYLuTpdGM2Lbzqm4v8ucHxNYLAlHq+Z0InEwxyHLNarBtQex4ZlMW4odkvcqpa6aub0eW6zzYJlRNvv6cWZBsbpbpyf8yZl5OssetzxY4ZLTytz9eBXQcpBZx+Her/4Fly+WrF9WoLMzh+M6DA9VeNvnrmfnXd/k//7rUzSbIe+8sJzkO69Y2cfw0BTd3XpwMjXViusKIiqVFq4riZSKUx70gF86aQqTI0klWeNogu73oItBW60o6ekgorSLtVZVStVgVKzg5LhxTrgp0oxTKozDEJo0C1ck9Q75XFopfdY5y+GeTcf2n2axxDza0o/VrmJVh06jK+UlzWbAVDWg0VI8tnmCN27MccH5y/i3176AMFJUJ6am1Q/pQf3oZEC9MYXrCBqtiDDS6kh+EPHmf3wPH3vX+yjkHbpLYVw4LdqUj1RcnOy5AiV0LUQQageh0VJIkTaJNGpmrVaUdIzOefpzswgBxHUKuVgdrSiIjw/yJvVQpLUPYaTfk3NFUqid8wR7R1pM1CJa8TF15KzzYDnxuFIUuLb31bx67Fqu7X31YTWFg4M7DVeKAje/9aNc+p9/+oSfezjH9mS2P1wW9yn2je5vjyeCIzQfIg82bckya3QLWOLByb2SYk6wqMcln3MYm/RZvqTI2HiTj97XYGz7rfSuvpj3v2gBAHv3VcnFdQyNRkB/f4lWK0ApGBtrkMtJmk2tE/+WD13Fptu+z4+//YtMqpDpQBvFnR3TgYgfpy11dnjUGwFhlKYRSSmSQunUMYjw4qJoSNOPPFckna4dR7TNWtYaYVIo3WjqUUw+56CUorPs4XkOvh/Sv6ADvxXwtEvP44Xv/h4//teXUR0f49f//mZzvHPmBmPtd36y3oONvQJXCs47rZuBPVU+8ZAO649s+iH3fuvf+d6Xf8Qf/dMH+bc/eyeQKoq5jqTRDFm6pIM9e6sUCw6NZpjYR293jsERva8o7pFgnPMwEz7QKUK6mWLTV0ld0JL+HENjrSS1yWwXhO3vLRcl45VQ1xSFaapRPqft2kQvzL3B1F6YSKNpFNfV4eAHur/E5JTPtr1NXAeKOUmlEfGTvRETGSuYi/Z7oowHLMeGA6UKHc7g+kD9IQ534H+0xdZHyxOdn4keTk9beufio09b+vA+m7ZksTwhEwomWvBorLz0rMmQdQs9ussujUbIyhWdAPSuvpjHbvwg+wZr9PXmWbK4g8//ZIRfP1vPzg8PV4kiRWdnnnLZo9EIkqZTV//Ve+no8JLCZKWg3gxjWUapZRzjCIDJYVYqzYkG4gGHloB0HEkYRoShLoA2sq093XkG9tbI5ySlgoPrSoIgon9RiTBUDA3rrtpSkuRd67oJJyneNlz14zE+88YNDO4ZY+v2SVbuGgDglzf9nI6yLQSznDhs9mHzoAIUY/Ux+kqS5tRuaiNbeNflL0EIQTEveeQn3yAMI5q+or8nx8SUTxSFFPIO4+ONJOpgHPnJWkgQpo5DENcktAKVRARNXYEfqMRZBxPd0DYspUBCKkwg074MOVc3ijPNHKvNiL5ON5ZwTY+l1ojiBpCSRjOi1owo5SWVeojn6IkC1xHUGhFjlZCWX6Oz5OBI+NqukE0/+mc++Md/xSt7XCaqIV/eYdWWLCc2hzPbP92ZyC4fqEj6iZyIN77xND71qYeO+JgP5HQcKjIy0xEGq7bUjnUeLMeMWybgvkmfc7oDVvQ6PO3pa5PXNlz2bnp7PkQ+7+I4kkvWaoeg5adyjPVGjdWrumk2Q+oNH8eRdBZd+vo7qNX8JDpg0oL8uGEUtKsYyTg6oBu0mbUizolO1VkASkWX7u4877phiI9cvphdA1N4nkwiCqOjjbbZOqWguyuHEIKx8SbFgkM+kroeAzj51GUMPXIDz/id1/D4bTfx9q99k/e8YA1XrHLZuKaDiYnjH1K1WA7ELRPARMQlS5ezpCzp7ZCUClo+9TvX3Uq5w6M53qLRDKk3dQdq4zgvXVRkcqpFEET0ducIhrTUcRAqSgUndvKhoyApl1yGx/UMnZZtFXFNQyqBDFpNyfRPCRDkPJ1OJITAkSpp6uYHCj9UlAuSvCdYsbTEvqE6LT+i0dIF1x0FmdRLdJacRFmplNfH/vDWCh15/f5vbgmAIIkyDDzwcz75SIs/O6eIaxWXLHOA6QPxJ1PYPJ3DjVj0bjwXeGhGog1P9FknQmrSfMemLVmOC8sd+J0zi1TrAZ98RA8U/vjMAhOVkM6S7kyb83TkwJE6/SeMTEMpkxqhVVM6Si71RpoeZNKRTMQBYknUUCUKKWYAYhpDFTKRASOrWsg7/NG//DOrL3ozAO99Xi+Vik8uJ8nlHKpVnw/fXmFk84/40JW/Qb2hO1+vXtVNtdqi0Qjo7s5TKOYY2DXBGees5OXv/xb/8bvPxPdDRscaSaH0K1a6PP3sfqrVFu/9yTgwt0Kb1n6fWix3YGkBegu6K3Vfl0sYz/5X61o9qavsUquHSWM2P1BU62GcUqhVjnKeTOqPSgWpG8r5OjLgSJGoIZUKuui5FSg8x/R90MdifsKy+zXrcnGHbEdq56Llq7jQ2mFgqEUpr+uyIpWmN4aRrmkqFSRjUwGrlhS4/dEa2yqKhXm4s5peh9PysK5H8u29Ib+2WDJSU9xeMcc19+z3RBkPWE4MDjSDfyxSjQ70mccqynCwtKW/WHD0aUv/PGzTliyWo2IghP+4R6f6fM8VPH2xpJiT9HY6Sefaai0g50macVMo4wyYgX8+p/sq1OphoqLkxzULJmc5VWgh/ms62BJ3s1VJOpOUgmJBFy+byMLU4DY+/YaTeeTBPZTLOZYsKbNt+wTdXSLp+dC79lJWruph7ekncdfN9zI52WDjmauoTlbxWwFdvZ189+Y9nPfMIqX+k3n3d4d4Tq/kp+OKf42vx1Al4i+v3wfAe61ii+UEZyCEgSpQVSwaCzi9O6QzL+jpkOlsvx/hOIKxqYC8J6k1dXrQVCNkYZdLb5fLmjW93Hv/UJK6FMUTBB1Fh0otJO/pVCYzCeA5aTM2E3Vo+SqTKqgFD6bqIYOViFOX5egsyaRRnZSCjqKLELC416XRiujvyfHA1ho7JxVreyS9ZYfxakh/t8d/3d/gilUu403FKT2CB8baB9clFxZ1O/zxmQVcKVjVK7m9YtOWLPODQzWIO1TE4plnKX5+n0he/6dTctz9qDyoI/JEdRDHMj3pYERzf7w/o1jnwXLcGQjhG7sjFsmIpfmARSXB2kURpaJDd3ee0bFGXLwYJvnLQayM5Doi6Xrb8iPCKEocBl2EKZK0B63UomdHXUdHLRb2F1m1dgFbNw0SBBHLlnczOlLlpvsqLO+SDG19mImxKvm8Q7mcY3y8QV9vnoWLOvnTr+zk+vc8m+u++HOGJkMurTRZvX4xSimu/M/72HXn57nn25/ilz+9lzWLPF75r3cn5/yTMZ1eYZyZN2zwjsu1t1iOlsEIBscUi6RicS6iKwfrF7qJw1/MSXKewHOdJAoQRYqRcZ+hXw2Sc7Ui0qJeTw/8qwEdRZdaI6Kr7LJ7uMVEJeTSi1dw2jMv5Cuf+CaT1YC6r9iwpsz2gRp+oHhsn885q/NMVnWU8tZJWFQOiOJaqK3j+tgarYjeTlcrstUjdgzXkr4OoOsx7hmK2DJWY8cvPkmlEbGyS3LFyzbyueseYWBUsUjC0/oEvR26i3V1MqC/04mjltZ5sMx/pg/aX/kb/TzrYz/jT1eeylt3XsmruTZ57R2PtA7bKXgyzsBMOQ626dyTRz7xJhbLsWEwgnvrcOOI4v8ebfHg9gb3PDKRKLQIAcsWF5PoQBjpGc583qG7K0ch78TSq2nDqVQmVedAe67kD979e7zvG99m7ZoeXFfSbOhQYhAobrl9L1f9eJzTl3pc+apz+Mn//Zjb7hqk0QhpNgN+649eR19/B5e98S0ADGzewW9dcQE5V/BX3xtmfGSS5SetZXTrzdx3w2eZHBnlrKdvoHaQXOjXrHX59Bs30NPp8bbzbI8Hy9xlMIL7G3rQ/vnNAXdva7Jz2CcIFUMTutdLECom6xGVhu6nsns8ZPdYQN7TUb/BsRZBqPu2fPbxFi+94lK6SpJiXlCZrNOoTKKUohJ3s77z4UnKRclUXQ/Ye7py5D0dnXxWNzR8XevQXZKs7ZGcv77IzwZCdo/4bNoXMDgVMdZQ3DQS8cmr30LeE2wZizh7geTkfsmfvOwPWdrrUvAEY8OTtELFs3sElyyVnLqqQLnoMDQZknMFtWaUnKfF8lTiGtXgN785QN+KtVyjGqjRz+w3sD+R6xBMEfihjlErNx7dYz5hax4sJzyLJCzNw7penVLQVXap1HRe9TnnLGN0eIpmU0u5Viot/EAlPRSESLs9m5nFj96nbxA/+OCL+fa1P2XF8jKTk03u21TllkEtt6iUYs+9X+H9r/s9Nmzo54EHh9i4oY/JiQbrT1nGwLZBHn58nM9t0k3i3nlhmVo9oJB32HDKYt70+U3svP3TDD7+S/xGnc//+1f4z7uHcXNlbvrIr/HIL+/jT7+yk3deWGbxYp0KVa2HvPjyM5MIxVzKi7T2azkYxn6Xd+rGkT0dDq1AsWxhnjPOWclNN23CcwWTtYglfR4TlYDJeoQjYXGvR09XDiFg71CDK37/udx+0y95z4/G6BZw2XLdEf5neyKW5uGidXk6ig6P7mwwUovYXAVPQLcL1RBcAVOhdnQ25uDpK1yGp0JuGNS/7CvcdpNb0wHlnGB3RX+9T1noMFmPWNarg/Ynre1i87ZJAIYnQ57zjMW8/f/2AHPTfk+U8YDFcrw4WM3DW3vyR73v/xxvZhdtkziLZTYZjGCwDvfWIzbmIvryPl15wYp+l5GhScqdBV79d//I9//rg9x/3x56unNMTvlEkSLnSfI5XTfhOoLlK7p53wv6CIKIsy/cyIUXr6err4df3nw/ORfWFHT0464v/jGDWx7l9DMWs+mxIRqtiFq1xdadFX5238PUfMUlp3Ykx/jh2yu8+6JOokixfeswH3vlakrlAotWLmPHY9vo7vT42X+/juf8+dfZ+cjjVKYa7Ln3Kzz38gt5yd/+kI+/Zg0/u22A679533G80hbLzJPar2K1q1iYj1hYEvzvFl1Z/Nk+SX+HpNaK2LK3SbUFroS+DsnSxSVarZB7Hqvw9nf9Os992//x4O1LAS0Ffd3O9pn+3zvJY9+Yz8OjEV/57B/zj+/8OEEIL33+Kh5+aB97R1qUi5IdwwE3jige3aLfbwYMr1rt0N3h0N3psXV3g+FKRG+H5BWXr+Vr39nMkj4POebHfSwEY2MNak3dlK6nQzK4b+oYXlmLxXI0TK+5EH2vPyafO5cmFg6GjTxY5jTLHXjHbyzlF3fp3OmeTpfly8oMD9d5/d+9ndMu/3veenYxbgIH516whtd+/CE+9fqTue76zXx/WPHadS79PR493Xn+9Oqvct6pL2BZES45tYMdexvkXMGivhyFgi60fN/NE/zggy/mJ9/+Ob4f8ZE79CDojRv1DKlRj/r+B17Ei/7q+/ztpd0IIajXA93NtujieQ71unZwli3vYWS4wu69VQZGAq6P+2LMpRuMtV/LkfL8PoEroauoI4sL+vLsGWxw504f0xz60Rbc/39/xRm/+X6EEPjNKf7lt9bxzu8Mtu3rvA7B3TVY7cIvfvV1zj/nt/mDZ/WweGk33/vxTsbqEX0lna37zT16569a7XDLrpBnLnNYvjDHypXdeJ7DfQ8MEUW6KVyzGbJ3pEVHQVJtRPR1uRQLDtv3NGgFuq6j4Uecvr6T9908AcxN+z1RxgMWy/HiYJGHP+06+sjDRyebbfuey9jIg2VOMxDC276xh24BJ5fAGwrYNdRiUY/LaZf/PaAlV9/43ndSnxyhe8k6ACZGpzh7fYlSrs5ELaLht7h/W4PCn72KNWXBOWsLrD95IfXGXqp13c36nV/6IY/+8GoAXvju7/Gz7/YAOmUpn3f4h+uuYcmZv81tn/w9auMjbLrnYV4ENBohI+Mt1q/pZN9gjXMv2sDJT7+Yj131cXYMB7x0UZm/++Eof31Jlz6puAulxfJU4IejKu5GH9I3HnJ+TlIqSM5a6iIF1FuKR3eFnPmyD6DU+3n0Bx/AzZV553cG+egVK3nf13YxGGnZ1GGdRcj2AJae+dsAbN1ZoVJpsWpRjpVxl/lqI+K3l8O9gxGPDel6ia6SjlDec/8wZ57ahx8odo8F+EEdKQV7J0IqQwEnLXSpNyM272kyVlecutTDcwXd0uE1f/UO3nfz3x6vS2mxWGaJyPrVbVjnwTIvmFAZ/fWpCHa3uK9LsKgsKXiCyvAA1bFhrv+fL/CLK95GM4BTlufwQ4iUYnVfjqbf4t3fHebdF5W1Xv1UnclqwOODAaPbfSqXXQzA5/7p83iexHUkUqKbxjVCKoNbmNpzD9/4n6/F3a4Vf3ZOkdf9xes4/7Wf4B0X6DSne+94nPHhMRotxbkndzA8pA/c9yPqzXlWVWWxHAamGz0tuO1enUKw3IEzegWVluI3lkg6izpiUB3ZzSXdgt+9fDXNhs8zFkmmmorekqAVwFRTUfUVGxe5KAU/3R7wjnOXcOUHv8AfPvsF7JkMefVLVrJj2ygT9RprF3lIoVWWcp5WhqrVWuQ9QTmvpWJXLMqxoMdj00CDqXrEr3YH9ObhtinoLQZ05CU/2BVy++9Yx8Fiscx/bNqSZd7TLaDH0cWSazoFC8oSRwr2TYYs7nIQAu4cCKiE8LzVLr/zqqdz47fvoukrzjhtAZMTdXw/wvdDqjWdepTzJK4rmar4CCHo7spRrfo0WyGeJykWXMIwwnUl5XKO1Scv4+YfPUq55CKl7srbUXJZuKhMq+nz2OYJlII1K8u850djwNwKbVr7tcwW3QLKUtvvwjxsWKgb0t2zN2RFWdCRE+Q9wZI+Dz9QPDzQYnmPgxenG176kvP5h3/+KRdtKFKrh4xOhWxc08Gdj0zRX3aoNiPOWF9m71CdHcMBS3sc6i3dS+KxfT4/n9Rf7Uu6BTlHsLTboZDTik4P7fa5bUo7Or6CZyySfGvv3E07PFHGAxbL8eJgaUtvKR992tLHKzZtyWKZM0woMAqKm0cVjOo0hXNLIEWIFLCoCE/vdxmrRnzsE7fRCBR9JV0AOTreouVHfOpRnU70/51boloLCEKF50pAUa36uK6gVMozMdniac84mWf9/v/jqlddyRnnrmV4zwhrV3dx4+0j/OU7LuP6L93MyFiTkbEmY5WQ63aGbMzBwj6bsmSxZJlQMBG3TtgewJ3VtEi6o6FoBIr+uI5hqhZy0akdtFoRtz1WY6oesvjuR3Bj9bUwUpTygr1DdRZ3OzhSMDCu2Dfc4NQNfewZG0QIQWdRd6Ze0eMkn9WVF4kq019f0sUtD0xRidOkBkLt5IzVbeTQYpmPKGvabdjIg8UyjfUebOwV9HY4nLK+i/sencCRcO02PWjx66N8468v40tfvifuUq17SnQUdMfrjqIT96bQWvYdRQfPlVTrAc970RlUJyvc96ud3Lu1QStUnL48x8fuGeEFi7s4eYmXFFzPpdkJa7+WE4X1HvTmMmmM6J4PC8u6ILveVDy4L8CP4GnLdF3FSCVkaa9LtRFRLjq0/IiOooNSMDwR8NVd2nuZ/nt5Sbfg1kkdeShIKDm610W87Zyz3xNlPGCxHC8OFnn4w9LRRx4+UbORB4tl3rLZh82DCghg6ygbc9DpwTO74m7Qv72eRx/aS29Zz0pKKTjl5F62bhtn17BPwQvo63Jp+oowUrzpnVfyjDd+lku6BR//l7sA+P2Tc5y+Mk/Lj3h8r4+bK/OSi/rZu696sMOyWCyHwWYf8NvXDdah6kcMTET4EWxY4HDdzhB2B3gS9jThPKW7UdeaiomGYqoVIAX4mRnHFy+UlHKCrw+EPPydq9hb1+vXdMDPJvTA2ww+LBbL/MEWTLdjnQeL5Ql4NC7kNNz2uc37bdP96D7O7xXkXVBKN6bzQ6ULp+PWkku7HF612qWQk7r7tSuYqEQs7XZ448YcY5WQhm/vUBbLTDPdhu+u6UjCQ3HPpm6hBwd7q4qCo/AjuLuWbv/cXsGiTkm9dWAH4dbJ2Tx6i8VyvJlvHaKPFpu2ZLEcA0xagysgznSi4IBJ33YENCMIlM7rhrkV2rT2a5nPLHeg7EAjHkBsD/bfZr2n/26Oox5z0X5PlPGAxXK8OFja0hvzR5+29Kmm7TBtsVieBAMhEB7vo7BYLEfC4djvZv/Qr1sslrnLTPrVc2li4WBY58FisVgsFovFYjkIUTTnx/szijzeB2CxWCwWi8VisVjmBjbyYLFYLBaLxWKxHASrttTOrDkPQoh1wMuBu4FzgauVUuOz9XkWi2XmsPZrscxdrP1aLDPLiagl8GTsXAhxLvCCePEC4E1m2yO5X8xm5OETSqnL4gPbAnwI+MNZ/DyLxTJzWPu1WOYu1n4tlvnPYdm5EKIHOF8p9eF4+eXAD4Hznsx+ssxKzUPsxfSZZaXUFuCK2fgsi8Uys1j7tVjmLtZ+LZaZJ1JH/5hJnqSdnw+8K7N8E3CuEKLnSO8Xs1UwfS4wOn1lfJAWi+XExtqvxTJ3sfZrscwwJ5rzwJOwc6XUTcArMqvWxevHn8x+ssxW2lIfMD5t3SjQM0ufZ7FYZg5rvxbL3OWI7Xd652yLxaK5lsbxPoTpPCk7V0rdnVl8JfDhI9mP4bhKtQohrhJCKNud1mKZe1j7tVjmLtZ+LZbjg7G7+HHVMf7sHuBcpdS7nmjbQzFbkYcDeS37eTdxa+6rzLIQQs2HzntHgj13e+4nENZ+nyT23O25n0BY+32S2HO3534wjvW1EUK8GVh/iE1ujNOQDsvOD8CHTHF0zBHtZ7ach7vJFGAY4kIMi8VyYmPt12KZu1j7tVjmKEqpqw9z0ydt50KIdxIXTgsheuKahyO6X8xK2tL0D40LL74yG59lsVhmFmu/FsvcxdqvxTL/eSI7F0Ksi1OUzPLLga9m+jdccTj7ORiz2efhFbGXswW4QCl1OBrT753F4znRsef+1OREPXdrv08Oe+5PTU7Uc7f2++Sw5/7UZK6f+6Hs/EPAjcDVsUNwHbSJImwBrj6M/RwQoU7EtnkWi8VisVgsFovlhOO4qi1ZLBaLxWKxWCyWucNspi0dNnFI5eXowo1zgaszeVlzHiHEC9AV7udNW3/Q854v10QIcS7wgnjxAuBNh3OO8+H84/97T7x4AfBlo7U8n859rh3vk8Xar7VfrP3OWaz9WvtlHtvvcUMpddwfaOkp83wd8InjfUwzeG4vQH8B1ZM57/lwTdCG++bM8suBu55C5z8G9Mz3c59rx/skz83ab7o8b7/DBzl/a79z/GHt19rvU/Hcj8n1Pe4HoP85d01bN3a8j2sWzlMd7nnPl2sS37g3Z5Z7ABX/fSqc/7rM8zebm9J8Ove5drxHcZ7qcM97vlwTa7/WfufLw9qvtd/5aL/H83Ei1Dyci25S0UYcOprPHOq858U1UbqRySsyq9bF68d5apx/VgLtFWj1A5hf5z7XjnemmE//wwNi7dfa7zxmPv0PD4i136eE/R43ToSahz7272R3oI53841Dnfe8uSYqzjGMeSXw4fj5U+L845vOHwLXxTdzmF/nPteOd6aYT//Dg2Lt19rvPGU+/Q8PirXfeW+/x40TIfJgeQoQNys5Vyn1ruN9LMeSePbjA8B5cZMWi2XOYe3X2q9l7mLt19rvTHMiRB4O5NUdyPubbxzqvOfjNfmQUuqyzPJT5vyVUuNCiOuAG4UQvcyvc59rxztTzKf/4eFg7dfa73xiPv0PDwdrv/PTfo8bJ4LzcDf6n9PGtHy1+chBzzvuADhvrkncufBd8fOeOOdyXp//AeQB74z/9jG/zt3ab4Y5+j88JNZ+AWu/84359D88JNZ+gflrv8eN4562NP2fEueofeU4Hc4x41DnPZ+uSRwq/KpKdZKvgKfE+Y8Cn8gsnw9sUUptmU/nPteOd6aYT//DQ2HtN8Ha7zxiPv0PD4W134R5ab/HE6G0FNXxPYi0KccW4IL5lJcXe8CXAe9EFyvdaAp3DnXe8+GaxOewedrqLUqp9ZnX5/P5v4BY4QI4Dz0TsiV+bd6c+1w73ieDtV9rv/Gitd85iLVfa7/x4ry13+PFCeE8WCwWi8VisVgslhOf4562ZLFYLBaLxWKxWOYG1nmwWCwWi8VisVgsh4V1HiwWi8VisVgsFsthYZ0Hi8VisVgsFovFclhY58FisVgsFovFYrEcFtZ5sFgsFovFYrFYLIeFdR4sFovFYrFYLBbLYWGdB4vFYrFYLBaLxXJYWOfBYrFYLBaLxWKxHBb/P95C728QAimUAAAAAElFTkSuQmCC",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, (ax1,ax2,ax3) = plt.subplots(1,3,figsize=(10,6),constrained_layout=True)\n",
"\n",
"norm_1074_mean = ImageNormalize(FeXIII_1074_fitmodel.custom_fit[:,:,1],stretch=SqrtStretch(),vmin=0,vmax=2)\n",
"im1 = ax1.imshow(FeXIII_1074_fitmodel.custom_fit[:,:,1],origin=\"lower\",norm=norm_1074_mean,cmap=aia_193_cm)\n",
"ax1.set_title(\"5-point fit\",fontsize=14)\n",
"\n",
"im2 = ax2.imshow(FeXIII_1074_fitmodel_3point.custom_fit[:,:,1],origin=\"lower\",norm=norm_1074_mean,cmap=aia_193_cm)\n",
"ax2.set_title(\"3-point fit\",fontsize=14)\n",
"\n",
"im3 = ax3.imshow((FeXIII_1074_fitmodel_3point.custom_fit[:,:,1] - FeXIII_1074_fitmodel.custom_fit[:,:,1])/FeXIII_1074_fitmodel_3point.custom_fit[:,:,1]\n",
" ,origin=\"lower\",vmin=-0.2,vmax=0.2,cmap=cmcm.vik_r)\n",
"ax3.set_title(\"Relative difference (3-5)/3\",fontsize=14)\n",
"\n",
"plot_colorbar(im3,ax3,width=\"10%\")\n",
"\n",
"for ax_ in (ax1,ax2,ax3):\n",
" ax_.tick_params(labelsize=14)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:296: RuntimeWarning: invalid value encountered in sqrt\n",
" self.custom_err = np.sqrt(np.diagonal(pcov))\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/Desktop/Solar/MyPy/juanfit.py:221: UserWarning: No input errors, absolute_sigma=False will be used in the Chi2 fitting.\n",
" warn(\"No input errors, absolute_sigma=False will be used in the Chi2 fitting.\")\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/scipy/optimize/minpack.py:834: OptimizeWarning: Covariance of the parameters could not be estimated\n",
" category=OptimizeWarning)\n"
]
}
],
"source": [
"FeXIII_1079_fitmodel = SpectrumFit2D(data=intensity_1079_mean_grid[:,:310,:], wvl=wvl_1079_grid,\n",
" custom_func=gaussian,custom_init=[1079.8,0.03,0.2])\n",
"FeXIII_1079_fitmodel_3point = SpectrumFit2D(data=intensity_1079_mean_grid[:,:310,1:4], wvl=wvl_1079_grid[1:4],\n",
" custom_func=gaussian,custom_init=[1079.8,0.03,0.2])\n",
"\n",
"# FeXIII_1079_fitmodel = SpectrumFit2D(data=intensity_1079_mean_grid[:,:310,:], wvl=wvl_1079_grid,\n",
"# line_number=1,line_wvl_init=1079.6,int_max_init=1,fwhm_init=0.2)\n",
"FeXIII_1079_fitmodel.run_lse_mp(ncpu=\"max\",prev_init=False)\n",
"FeXIII_1079_fitmodel_3point.run_lse_mp(ncpu=\"max\",prev_init=False)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:10: RuntimeWarning: divide by zero encountered in true_divide\n",
" # Remove the CWD from sys.path while we load stuff.\n",
"/Users/yjzhu/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:10: RuntimeWarning: invalid value encountered in true_divide\n",
" # Remove the CWD from sys.path while we load stuff.\n"
]
},
{
"data": {
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",
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