analysis/test_wavelet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# import modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib qt\n",
    "# %matplotlib notebook\n",
    "#%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math\n",
    "from scipy.interpolate import griddata\n",
    "from scipy.constants import elementary_charge\n",
    "import matplotlib.tri as tri\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['font.size'] = 14\n",
    "\n",
    "import shutil\n",
    "\n",
    "# scientific format of axis labels\n",
    "def sci_format():                                                               \n",
    "    fmt = mpl.ticker.ScalarFormatter(useMathText=True)                          \n",
    "    fmt.set_powerlimits((-2, 3))                                                \n",
    "    return (fmt) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# class definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CosyrAnalyze(object):\n",
    "    \n",
    "    def __init__(self, gamma, data_dir=\"../..\", # path to data\n",
    "                 pid=0, # particle index\n",
    "                 traj_type = 2, # 1: straightline, 2: synchrotron, 3: undulator\n",
    "                 load_data_all=0, # if to load all data\n",
    "                 wf_xy_rotate = 0, # rotate wavefront positions and co-moving mesh from x-y to x'-y'\n",
    "                 wf_xy2polar =0, # convert wavefront positions from x-y to polar coordinates\n",
    "                ):\n",
    "        self = locals().pop(\"self\")\n",
    "        for name, val in locals().items():\n",
    "            print(\"setting \" + name + \" to \", val)\n",
    "            setattr(self, name, val)\n",
    "        \n",
    "        if self.load_data_all:\n",
    "            self.load_trajectory()\n",
    "            self.load_wavefronts()\n",
    "            self.load_cmesh()\n",
    "            self.load_cmesh_polar()\n",
    "            print(\"done reading.\")\n",
    "        \n",
    "        if self.wf_xy_rotate:\n",
    "            from scipy.spatial.transform import Rotation as R\n",
    "            if not self.load_data_all:\n",
    "                self.load_trajectory()\n",
    "                self.load_wavefronts()\n",
    "                self.load_cmesh()                \n",
    "            r0 = np.sqrt(self.curr_x**2+self.curr_y**2)\n",
    "            alpha0 = np.arctan2(self.curr_x, self.curr_y)\n",
    "            print(\"alpha0 = \", alpha0)\n",
    "            r = R.from_euler('z', alpha0)\n",
    "            rot_matrix = r.as_matrix()\n",
    "            print(\"rot_matrix=\", rot_matrix)\n",
    "            print(\"curr_prime = \", r.apply(np.asarray([self.curr_x, self.curr_y, 0.0])))\n",
    "            self.wf_xprime = self.wf_x * rot_matrix[0,0] + self.wf_y * rot_matrix[0,1]\n",
    "            self.wf_yprime = self.wf_x * rot_matrix[1,0] + self.wf_y * rot_matrix[1,1]\n",
    "            self.cmesh_xprime = self.cmesh_x * rot_matrix[0,0] + self.cmesh_y * rot_matrix[0,1]\n",
    "            self.cmesh_yprime = self.cmesh_x * rot_matrix[1,0] + self.cmesh_y * rot_matrix[1,1]            \n",
    "            # axis range\n",
    "            self.xprime_lim_cmesh = [self.cmesh_xprime.min(), self.cmesh_xprime.max()] \n",
    "            self.yprime_lim_cmesh = [self.cmesh_yprime.min(), self.cmesh_yprime.max()] \n",
    "            \n",
    "        if self.wf_xy2polar:\n",
    "            if not self.load_data_all:\n",
    "                self.load_trajectory()\n",
    "                self.load_wavefronts()\n",
    "            r0 = np.sqrt(self.curr_x**2+self.curr_y**2)\n",
    "            alpha0 = np.arctan2(self.curr_y, self.curr_x)\n",
    "            self.wf_alpha = np.zeros(self.wf_x.shape[0])\n",
    "            self.wf_chi = np.zeros(self.wf_x.shape[0])\n",
    "            for i in range(self.wf_x.shape[0]):\n",
    "                r = np.sqrt(self.wf_x[i]**2+self.wf_y[i]**2)\n",
    "                alpha = np.arctan2(self.wf_y[i], self.wf_x[i])\n",
    "                self.wf_alpha[i] = alpha0 - alpha\n",
    "                self.wf_chi[i] = r - r0\n",
    "\n",
    "    def load_trajectory(self):\n",
    "        # electron trajectory\n",
    "        self.traj_x, self.traj_y = np.loadtxt(\n",
    "            self.data_dir+'/data/trajectory_{}_0.csv'.format(self.pid), delimiter=',', unpack=True)\n",
    "        # Current electron position\n",
    "        self.curr_x = 0.5*(self.traj_x[-1] + self.traj_x[-2]) \n",
    "        self.curr_y = 0.5*(self.traj_y[-1] + self.traj_y[-2])\n",
    "        # predefined trajectory according to trajectory type\n",
    "        self.rotation_angle = 0.0\n",
    "        if self.traj_type==2:\n",
    "            self.traj_x_predef = np.linspace(0,1,1000)\n",
    "            self.traj_y_predef = np.sqrt(1-self.traj_x_predef**2)\n",
    "        \n",
    "    def load_wavefronts(self):\n",
    "        # positions\n",
    "        self.wf_x, self.wf_y = np.loadtxt(\n",
    "            self.data_dir+'/data/wavefronts_{}_0.csv'.format(self.pid), delimiter=',', unpack=True)\n",
    "        # axis range\n",
    "        self.xlim_wf = [self.wf_x.min(), self.wf_x.max()] \n",
    "        self.ylim_wf = [self.wf_y.min(), self.wf_y.max()]\n",
    "        # fields \n",
    "        self.wf_vfld, self.wf_afld, self.wf_tfld = np.loadtxt(\n",
    "            self.data_dir+'/data/field_{}_0.csv'.format(self.pid), delimiter=',', unpack=True)\n",
    "        self.wf_vfld /= self.gamma**4.0\n",
    "        self.wf_afld /= self.gamma**4.0\n",
    "        self.wf_tfld /= self.gamma**4.0\n",
    "        \n",
    "    def load_cmesh(self):\n",
    "        from scipy.spatial.transform import Rotation as R\n",
    "        # positions\n",
    "        self.cmesh_x, self.cmesh_y = np.loadtxt(\n",
    "            self.data_dir+'/data/comoving_mesh_pos.csv', delimiter=',', unpack=True)\n",
    "        # axis range\n",
    "        self.xlim_cmesh = [self.cmesh_x.min(), self.cmesh_x.max()] \n",
    "        self.ylim_cmesh = [self.cmesh_y.min(), self.cmesh_y.max()]\n",
    "        # fields\n",
    "        self.cmesh_vfld, self.cmesh_afld, self.cmesh_tfld = np.loadtxt(\n",
    "            self.data_dir+'/data/comoving_mesh_field.csv', delimiter=',', unpack=True)\n",
    "        #self.cmesh_vfld /= self.gamma**4.0\n",
    "        #self.cmesh_afld /= self.gamma**4.0\n",
    "        #self.cmesh_tfld /= self.gamma**4.0\n",
    "\n",
    "    def load_error(self):\n",
    "        self.error = np.loadtxt(self.data_dir+'/data/error_map.csv', delimiter=',', unpack=True)\n",
    "        self.exact_field = np.loadtxt(self.data_dir+'/data/exact_values.csv', delimiter=',', unpack=True)\n",
    "        \n",
    "    def load_cmesh_polar(self):\n",
    "        # positions, fields\n",
    "#         self.cmesh_polar_ang, self.cmesh_polar_rad, self.cmesh_polar_vfld, \\\n",
    "#             self.cmesh_polar_afld, self.cmesh_polar_tfld = np.loadtxt(\n",
    "#                             self.data_dir+'/data/comoving_mesh_rad_ang.data', delimiter=',', unpack=True)\n",
    "        self.cmesh_polar_ang, self.cmesh_polar_rad, self.cmesh_polar_afld, =\\\n",
    "            np.loadtxt(self.data_dir+'/data/comoving_mesh_rad_ang.csv', delimiter=',', unpack=True)\n",
    "        self.cmesh_polar_rad -= 1.0 # change r to chi=r-1\n",
    "        # axis range\n",
    "        self.xlim_cmesh_ang = [self.cmesh_polar_ang.min(), self.cmesh_polar_ang.max()] \n",
    "        self.ylim_cmesh_rad = [self.cmesh_polar_rad.min(), self.cmesh_polar_rad.max()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## wavefronts, co-mesh & fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gamma = 1000\n",
    "ndirs = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "setting gamma to  1000\n",
      "setting data_dir to  ../build\n",
      "setting pid to  0\n",
      "setting traj_type to  2\n",
      "setting load_data_all to  1\n",
      "setting wf_xy_rotate to  0\n",
      "setting wf_xy2polar to  0\n",
      "setting self to  <__main__.CosyrAnalyze object at 0x12aa84080>\n",
      "done reading.\n"
     ]
    }
   ],
   "source": [
    "a=CosyrAnalyze(gamma, \"../build\", pid=0, load_data_all=1, wf_xy_rotate=0, )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_wavelets(path,filename,assign_field_value=True) :\n",
    "    import numpy as np\n",
    "    data = np.genfromtxt(path+\"/\"+filename, delimiter=\",\") # read CSV file\n",
    "    #data = dat[:1000,:]\n",
    "    nwavelets = data.shape[0]\n",
    "    field = np.zeros(nwavelets)\n",
    "\n",
    "    def get_field(pos):\n",
    "        x = pos[:,0]\n",
    "        y = pos[:,1]\n",
    "        ymax = y.max()\n",
    "        ymin = y.min()\n",
    "        x_fact = -0.0000001\n",
    "        y_fact = -0.0005\n",
    "        return np.exp((x_fact*x*x) + (y_fact*y*y))\n",
    "        #return np.cos(5.0*y*2*np.pi/(ymax-ymin))   # test case, assign test field of cos(x)\n",
    "\n",
    "    if (assign_field_value) : \n",
    "        field = get_field(data[:,:2])\n",
    "\n",
    "    # ensure we pass different array addresses for wavelet x,y coordinate \n",
    "    wx = data[:,0].copy()\n",
    "    wy = data[:,1].copy()\n",
    "    return wx, wy, field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wavelet_x: (min,max) =  -5.036766987143398e-06 1.0513008183041598e-05\n",
      "wavelet_y: (min,max) =  -5.000000000005039e-05 5.000000000016063e-05\n"
     ]
    }
   ],
   "source": [
    "wavelet_path = \"/Users/hoby/dev/csr/cosyr/input\"\n",
    "wavelet_filename = \"wavelets_adaptative.csv\"\n",
    "wavelet_x, wavelet_y, wavelet_field = load_wavelets(wavelet_path, wavelet_filename)\n",
    "# unscale if necessary\n",
    "wavelet_x /= gamma**3.0\n",
    "wavelet_y /= gamma**2.0\n",
    "wavelet_type = 1\n",
    "if (wavelet_type == 0) :\n",
    "    # convert to global (x,y) coordinate\n",
    "    wavelet_x_prime = wavelet_x.copy()\n",
    "    wavelet_y_prime = wavelet_y + 1.0\n",
    "    rotation_angle = 0.19989890421779444  # positive for counter clock-wise rotation\n",
    "    wavelet_x = wavelet_x_prime*np.cos(rotation_angle) + wavelet_y_prime*np.sin(rotation_angle)\n",
    "    wavelet_y = -wavelet_x_prime*np.sin(rotation_angle) + wavelet_y_prime*np.cos(rotation_angle) \n",
    "\n",
    "print(\"wavelet_x: (min,max) = \", wavelet_x.min(), wavelet_x.max())\n",
    "print(\"wavelet_y: (min,max) = \", wavelet_y.min(), wavelet_y.max())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12d3aa240>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#%matplotlib inline\n",
    "# plot\n",
    "fig, axes = plt.subplots(1,1, figsize=[9,7])\n",
    "ax=axes\n",
    "ax.set_title(\"wavefronts & comove-mesh\")\n",
    "#ax.plot(a.traj_x_predef, a.traj_y_predef, 'k', linewidth=0.5, label='predefined traj.')\n",
    "#ax.plot(a.traj_x, a.traj_y, 'r', linewidth=0.5, label='actual traj.')\n",
    "#ax.plot(a.curr_x, a.curr_y, 'r.', markersize=20, label=\"current pos.\")\n",
    "ax.scatter(a.wf_x, a.wf_y, s=.1, facecolor='C0', label=\"wavefronts\")\n",
    "#ax.scatter(wavelet_x, wavelet_y, s=.1, facecolor='C0', label=\"prescribed wavefronts\")\n",
    "ax.scatter(a.cmesh_x, a.cmesh_y, s=.1, facecolor='C1', label=\"comove-mesh\")\n",
    "ax.set_xlim(a.xlim_cmesh)\n",
    "ax.set_ylim(a.ylim_cmesh)\n",
    "ax.set_xlabel(r'$x$')\n",
    "ax.set_ylabel(r'$y$')\n",
    "plt.legend(loc=\"upper right\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12d9d5c18>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "#%matplotlib qt\n",
    "#fig = plt.figure()\n",
    "%matplotlib inline\n",
    "fig, axes = plt.subplots(1,1, figsize=[9,7])\n",
    "ax=axes\n",
    "ax.set_title(\"wavefronts & comove-mesh\")\n",
    "#ax.plot(a.traj_x_predef, a.traj_y_predef, 'k', linewidth=0.5, label='predefined traj.')\n",
    "#ax.plot(a.traj_x, a.traj_y, 'r', linewidth=0.5, label='actual traj.')\n",
    "#ax.plot(a.curr_x, a.curr_y, 'r.', markersize=20, label=\"current pos.\")\n",
    "ax.scatter(a.wf_x, a.wf_y, s=.1, facecolor='C0', label=\"wavefronts\")\n",
    "#ax.scatter(a.wf_x[:ndirs], a.wf_y[:ndirs], s=10, facecolor='b', label=\"first wavefronts\")\n",
    "#ax.scatter(a.wf_xprime[:], a.wf_yprime[:], s=.3, facecolor='C0', label=\"wavefronts\")\n",
    "#ax.scatter(a.wf_xprime[-400*ndirs:], a.wf_yprime[-400*ndirs:], s=.3, facecolor='C0', label=\"wavefronts\")\n",
    "#ax.scatter(a.cmesh_x, a.cmesh_y, s=.1, facecolor='C1', label=\"comove-mesh\")\n",
    "#ax.scatter(a.cmesh_xprime, a.cmesh_yprime, s=.1, facecolor='C1', label=\"comove-mesh\")\n",
    "#ax.set_xlim(np.multiply(a.xprime_lim_cmesh,100))\n",
    "#ax.set_ylim(a.yprime_lim_cmesh)\n",
    "ax.set_xlabel(r'$x\\prime$')\n",
    "ax.set_ylabel(r'$y\\prime$')\n",
    "plt.legend(loc=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5.00024999992e-06 -5.00000125157e-05\n",
      "5.00025000004e-06 4.99999999919e-05\n"
     ]
    }
   ],
   "source": [
    "print(a.cmesh_x.min(), a.cmesh_y.min())\n",
    "print(a.cmesh_x.max(), a.cmesh_y.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '$y\\\\prime$')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "wavelet_path = \"/Users/hoby/dev/csr/cosyr/input\"\n",
    "wavelet_filename = \"wavelets_adaptative.csv\"\n",
    "wavelet_x, wavelet_y, wavelet_field = load_wavelets(wavelet_path, wavelet_filename)\n",
    "wavelet_x /= gamma**3.0\n",
    "wavelet_y /= gamma**2.0\n",
    "\n",
    "fig, axes = plt.subplots(1,1, figsize=[6,4])\n",
    "ax=axes\n",
    "ax.set_title(\"afld @ wavefronts\")\n",
    "#sc=ax.scatter(a.wf_x, a.wf_y, c=a.wf_tfld, marker='o', s=5, cmap=\"coolwarm\")\n",
    "sc=ax.scatter(wavelet_x, wavelet_y, c=wavelet_field, marker='o', s=5, cmap=\"coolwarm\")\n",
    "#ax.plot(a.curr_x, a.curr_y, 'c.', markersize=5)\n",
    "#ax.set_xlim(np.multiply(a.xprime_lim_cmesh,1))\n",
    "#ax.set_ylim((a.yprime_lim_cmesh[0]-1)*1+1, (a.yprime_lim_cmesh[1]-1)*1+1)\n",
    "ax.set_xlim(a.xlim_cmesh)\n",
    "ax.set_ylim(a.ylim_cmesh)\n",
    "fig.colorbar(sc, ax=ax)\n",
    "#sc.set_clim(-1, 1)\n",
    "ax.set_xlabel(r'$x\\prime$')\n",
    "ax.set_ylabel(r'$y\\prime$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "setting gamma to  1000\n",
      "setting data_dir to  ../build\n",
      "setting pid to  0\n",
      "setting traj_type to  2\n",
      "setting load_data_all to  1\n",
      "setting wf_xy_rotate to  1\n",
      "setting wf_xy2polar to  0\n",
      "setting self to  <__main__.CosyrAnalyze object at 0x12d3aac50>\n",
      "done reading.\n",
      "alpha0 =  0.19899990873666304\n",
      "rot_matrix= [[ 0.98026478 -0.19768908  0.        ]\n",
      " [ 0.19768908  0.98026478  0.        ]\n",
      " [ 0.          0.          1.        ]]\n",
      "curr_prime =  [-2.77555756e-17  9.99999751e-01  0.00000000e+00]\n",
      "[[-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]\n",
      " [-1.47860202e-04 -1.15002919e-04 -8.21456351e-05 -4.92883515e-05\n",
      "  -1.64310678e-05  1.64262159e-05  4.92834996e-05  8.21407833e-05\n",
      "   1.14998067e-04  1.47855351e-04]]\n",
      "[[-5.00016470e-05 -5.00016470e-05 -5.00016470e-05 -5.00016470e-05\n",
      "  -5.00016470e-05 -5.00016470e-05 -5.00016470e-05 -5.00016470e-05\n",
      "  -5.00016470e-05 -5.00016470e-05]\n",
      " [-3.88901616e-05 -3.88901616e-05 -3.88901616e-05 -3.88901616e-05\n",
      "  -3.88901616e-05 -3.88901616e-05 -3.88901616e-05 -3.88901616e-05\n",
      "  -3.88901616e-05 -3.88901616e-05]\n",
      " [-2.77786762e-05 -2.77786762e-05 -2.77786762e-05 -2.77786762e-05\n",
      "  -2.77786762e-05 -2.77786762e-05 -2.77786762e-05 -2.77786762e-05\n",
      "  -2.77786762e-05 -2.77786762e-05]\n",
      " [-1.66671909e-05 -1.66671909e-05 -1.66671909e-05 -1.66671909e-05\n",
      "  -1.66671909e-05 -1.66671909e-05 -1.66671909e-05 -1.66671909e-05\n",
      "  -1.66671909e-05 -1.66671909e-05]\n",
      " [-5.55570552e-06 -5.55570552e-06 -5.55570552e-06 -5.55570552e-06\n",
      "  -5.55570552e-06 -5.55570552e-06 -5.55570552e-06 -5.55570552e-06\n",
      "  -5.55570552e-06 -5.55570552e-06]\n",
      " [ 5.55577984e-06  5.55577984e-06  5.55577984e-06  5.55577984e-06\n",
      "   5.55577984e-06  5.55577984e-06  5.55577984e-06  5.55577984e-06\n",
      "   5.55577984e-06  5.55577984e-06]\n",
      " [ 1.66672652e-05  1.66672652e-05  1.66672652e-05  1.66672652e-05\n",
      "   1.66672652e-05  1.66672652e-05  1.66672652e-05  1.66672652e-05\n",
      "   1.66672652e-05  1.66672652e-05]\n",
      " [ 2.77787506e-05  2.77787506e-05  2.77787506e-05  2.77787506e-05\n",
      "   2.77787506e-05  2.77787506e-05  2.77787506e-05  2.77787506e-05\n",
      "   2.77787506e-05  2.77787506e-05]\n",
      " [ 3.88902359e-05  3.88902359e-05  3.88902359e-05  3.88902359e-05\n",
      "   3.88902359e-05  3.88902359e-05  3.88902359e-05  3.88902359e-05\n",
      "   3.88902359e-05  3.88902359e-05]\n",
      " [ 5.00017213e-05  5.00017213e-05  5.00017213e-05  5.00017213e-05\n",
      "   5.00017213e-05  5.00017213e-05  5.00017213e-05  5.00017213e-05\n",
      "   5.00017213e-05  5.00017213e-05]]\n"
     ]
    }
   ],
   "source": [
    "a=CosyrAnalyze(gamma, \"../build\", pid=0, load_data_all=1, wf_xy_rotate=1)\n",
    "x1, y1 = np.meshgrid(np.linspace(a.xprime_lim_cmesh[0]*10, a.xprime_lim_cmesh[1]*10, 10), np.linspace(a.yprime_lim_cmesh[0], a.yprime_lim_cmesh[1],10))\n",
    "print(x1)\n",
    "print(y1)\n",
    "mesh_tfld = griddata((a.wf_xprime, a.wf_yprime), a.wf_tfld, (x1, y1), method='linear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x131a6c3c8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/hoby/dev/csr/cosyr/venv/lib/python3.7/site-packages/matplotlib/image.py:455: RuntimeWarning: overflow encountered in double_scalars\n",
      "  newmin = vmid - dv * fact\n",
      "/Users/hoby/dev/csr/cosyr/venv/lib/python3.7/site-packages/matplotlib/image.py:460: RuntimeWarning: overflow encountered in double_scalars\n",
      "  newmax = vmid + dv * fact\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%matplotlib qt\n",
    "%matplotlib inline\n",
    "plt.figure()\n",
    "plt.title(\"remapped field\")\n",
    "plt.imshow(a.cmesh_tfld.reshape([201,201]).T,aspect=\"auto\",cmap=\"coolwarm\", origin=\"upper\", extent=[a.xlim_cmesh[0], a.xlim_cmesh[1], a.ylim_cmesh[0], a.ylim_cmesh[1]])\n",
    "#plt.clim(-1,1)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "cannot reshape array of size 40401 into shape (101,101)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-16-41f7bfd30597>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"exact values\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexact_field\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m101\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m101\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maspect\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"auto\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"coolwarm\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;31m#plt.clim(-1,1)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolorbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 40401 into shape (101,101)"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "a.load_error()\n",
    "plt.title(\"exact values\")\n",
    "plt.imshow(a.exact_field.reshape([201,201]).T,aspect=\"auto\",cmap=\"coolwarm\")\n",
    "#plt.clim(-1,1)\n",
    "plt.colorbar()\n",
    "\n",
    "a.wf_tfld.min(), a.wf_tfld.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "cannot reshape array of size 40401 into shape (101,101)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-14-550878d4a5e4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'matplotlib'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"error map\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m101\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m101\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maspect\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"auto\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"coolwarm\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;31m#plt.clim(0,0.5)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolorbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 40401 into shape (101,101)"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.title(\"error map\")\n",
    "plt.imshow(a.error.reshape([201,201]).T,aspect=\"auto\",cmap=\"coolwarm\")\n",
    "#plt.clim(0,0.5)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DYTSNPxZPNFogGMLXclBPM/IIVwNVvkJGF2WR1l5HfaiAUmGjIVRIYbAZc+FoGp1eigKH9Da2mZT203jrGUJIQplo5pAs1NuvVNiok0r7RaP1hide+UZZyFADTTtvMNSxUaOp9yoaTZNvkIUMU68RYJj6HHR3/7U0TV4719polKlFf7a056ieIaRbzBQFDun8TRRRQqt+3mopxRsIMpxm/bm1mYdQEGxW6yYYThN2/RlXaIdkIcNNdupk5//AbhlCoXr/eqI1ykJKTTb9v1ZKk35tbZYheJqqpcPtH3TTwkVFRXLkyJE98kmAw/gBZ7FYMJvNPfKFQiFCoRAWS/RuOxAIYDKZMJlM3coYz6WUBAIBrFYrfr8fQJcNSYmg67UbFoqmEA+EaiGttV3kuc4mOu2UDbxCTwpPkyi218Z7sn379mYpZUlvq3aSKVu26Qal0bEX7w6UKT8Nj0gpH1GPx6FYkj0hhDgRxWPv1bKbfYx6g0E5MBH5Zfzt7U1MNFUTKjmOFpeXEncloZLjMDXtJFRyHM4DW8kdcyKmpp00ZY6nOCddT9Pi2t2fMmLyyfp5i8tLWstufMWTKXFX0pQ5Xj8H9GMt9tRsI2PkVNJadnMoo5zC7DQ9zVOzDXfhJGbmNkLpcUrFD+1UjruLDTwtVVsoLp8eldYbnmi0yDTj+e7QSCYPz4NDO2nKGk9JRyVNWeMxNe2kuHw6TU6v3rbGeE9oFKWeKnzFk7G1+7Dv/5y23Ins2f4Rq/dmM1ZWk5k+mrKCTE5Mr6c5azwTRQ2HMsoZEziAK38Co/37aclWfLZNMlXzZWgUk0zV1FrHMclUw5ehkYzL7KDB4aaodBQ5jj3UpY1jkqma+vRyaNxBwdhpHGzpYJKpGnfhJDJtX+r5uAsnEajfQckx07G1+wjU78AyfAqZti/JGDmVpr1bdFqm7UvchZMo9VRxKKOcUk+Vno/2HGj8xufhy9AoxpVkh6Vp8sZnxtbuY6KpOuzZ0p4Z7Rk18htj7Rn11GwLe241Ge0ZNT7jzgNbOZRRrpdp/B9o9683NO3/pf3XTnqkjnFUs4dRuJafvecI/O37HCNHjmTz5s1d0o2dvNbxG6ENAEB5kXSRkRJhMiFDIeVFo9IiX+jayz8rK0vPJxaklIRCoW4HMcFgEJPJFJZXpEzkeTAYxGw2d7mmUCgUlocWSykJBoM6TyAQIBAI4PZ48LjdGCEAk9mM2WzWB0xmsxlJ5wBIqMdSLddYd5MQhKTEbDJ1tqmUCh/KIMtssSBDIaSUej4yYiCmlaXLqvfE2A5GPiGE3pZh52azUj8p9QGbXl+Vx2wydQ4aotwvrQ0j71MgENDrbGxvY5to51pdpaH86poaPa9jxo+P5VivC9pkkOWWSJ+c4fhhYI9HKmbw0WBB2ablKinlx0KIFSh7Ps2Ppx5h6G+zoETChOG5snLbx1I+9zMpnYeU8NzPpGzYET1Olicl37/yg6GOR5n8mRUr5au3fE+eWbFSTigytfZ3n5BImDp1qkwhhcGIUCjUJW1vZaXcW1kpgU9lPO9TU4Z8LXdyzBArTxSfS/sN57OAV+KpQ5c8kxHur5A3bLT88KsmpcPUoB13FyfLk5LvX/nBUMevoXxz5WdRecZUvCzPrFgpx1S8LLOsfbMB3pEOqYFJCoMRbrdbHmps7DI4SXhgYs6QrxcdFzP0lCeKj5pJ6vFtwL3x1CEyDLp5YYChwkam7UvYsAhcjUrYsEiZoogWJ8uTku9f+cFQx6+hfEvVFg6sn09L1ZYuPPvnjWOedR0TqaasOHdKf/cJKaRwtCA9PZ28vLxeTf/1CiYwZ5pihl7gKuAZIcQXwDSUbT8SRzKjmv4KKY3JUSg/GOo4iOUb2zxRad1pTKSUusYkt3RUUA6AfiHekNKYpDDQ4fP7pc1ujzp1E4lENSYT0zLlW2Omxgzx5plsGJQak2GilVJPFby5oPMr7s0FypdetDhZnpR8/8oPhjoOYnnP6/NZsu5dmhuqu9CKN96taEyiyC/KW8tEqhlusg3KfiSFFAY6BMoi4Ei43W5s9nA3IePLy7vw9Qp9ozHpUwzaDqXN7e/vKqSQwqBDs8vbJS3DYqJi9mSG5HTdm9AbCPHnt/fiDXTdr+ykMUWHpY4ppHC0osPtRspO6y2LxRJ12sZqtZKeltYnZQpAmEXMcKQxKB2s5Q8fI19/b3PCprjR4qas8WFmx5GmxZopsdE8Uzuv3f0pGSOnAkQ1JdbMRDUTVM1MVTMp1kxUAd2sdbKpplf110x7ezQpjqCFyWnnuelhNCOPZi5cXD6dlqotUU2z9x5y6ua1NO7gM89wtn+2kY0dwynKNDMjq4H2wklMEtV4Cicz1F0VZi6ck26h0LUXW84xjPDvoy13InnOPXrM0Cm0uf2U+fbhyp9IjmMPluFTCNTvwJU/kYIsa5gpcH16OcO9VV3aOFr7Z4ycGvUeGc1+NZPw7u6x8f5H8mjm59F4tDiaubDRbL07k3Zj3pFpkc/snS/v5M6Zpi7yRlNgo3y08o3/kf9+uonWv/6GtvoDR773ShInnHCC/OKLLxKSlVLS2tqKz+/v6pvCwCNDId0vRTAYVNTUBj8jev8rpc4npWJGHFLV2hrMZjMjR4zo1o8JQEdHB2azmfT08EGm1+slGAqRlZkJKOaxLpeL3NxchBC4XC5dxuvzkZGejsfjwWw2E5KSYCBASDXLlVISCAYJqqbCgWAwzLz4cCHamgrRSVSODf49NBmjnDEHjcek+g7R7o2UnWa4Wl6a6bKxDK1cIExGr2tEmrFMY92M99vn85FmtSpyEdcU0Ri6nPG5czqdHDN+/GbZvWlvF0zOypaPTZock+c7n38WV57JYlD6MSkVNmUqZ/MDcNb9SuKGRXD6jdHjHng8by7kVudF7GpwcE/6U7yQ/TPOan2Slwp+zjn2p3iq6CpqWju4kcf4e8HPOdv+FA8yl9+yjvW5P+Ns+2oWmS9BILiZx3iQufw6uJaHzT/mN6xlIZfg9koWpj3BUu8crrGuY6XpPH4dWssK/1yutq5jgf8SJHCH9XGWvXU+T457i7z/vTVm/T1vLuQh94+oyPwbGWcv78LTMuMPHFg/H3nRSuVrOJrcGbfgeXMhS3wXUzF7MjlvKbR51vU85J9DRebfcH1vMQtf3slFLX/CcdYCWl+5nRdyfsZc52qey1La6vH837K3sZ07055gmXcO86zreMc/l3nWdXzFJeCGcwJPs6xlLhda17HsK4W2TOVZ4b8EgDutj/OwmvZYRDzfwKPJLYtCW+6fyzVheXe2MWobG9v/Gus67jZdiscXfo8eNv+YK1nLUu8c/pC2nlt8F5OVbop6j+/iUgBu5jEe4jx+w1qd5xHz+fwx7UXm+35JEBnGo8WLxGWMKsziotYHeJC5/Ia1rOLHXJv2Ikt95/Jr1rJafQ5v4FGdtsw3h3lp65nv+yVSwELrk3qaJvd3w3Pc0NpBwz86eZb55nBt+os8mvtbDrS0c7v1iS407f/weP5vaWzzcmfak3rauWW/5J/YDvt/fiCio6MDn99PZkZG2EsLOgcc2svc6BtE8wPS5aNQSkIxPhRDoRDBUChmpx0MRneUFQgGCRlomg8SrW6BYBCrWr9AIEDQYtHpwVCIkDr40AZXQfU4eIQGJdDVDwzQ1RlZN4h8gSOlfm68FyIiLdInjNBoUfKNHCgYBx6R5UbLV6L4dAkGg/pAyVgf4wBYX4+h+nLR5CMHpL2CAGEeWJMng1Jjkjd8jHz+jY+YXWrrM43Ja4cK+d2az3jyBzlMnvatlMYkpTEZ1BqTSMdsxuc4mlZE05hEyztUchy1uz9lxXYrl88q1x0banmOLcn+st0TiP3JNQCRjMYEoKamBq/Pl/jcfgpHNdqcTmQoRH5+fo+80bz6er1eAoEA2dnZYbxCiLi0G8fmZMsnpx4fk+dbH206ohqTgTVM6iWGCRuTTNV9aopaIhwUSQfH7XmQko5Kync80BkLB5NzPWFpk001+vm0qlVMzvXoPJNNNUqayjM518PMYSHKdzzAzNxGnTatapV+PnNYiJnDQsyqe1QZlPSy/iUdlTF5ij9ZGpWmyxmuX+PRaMa8S4RDyUvNs6SjUo+1NtKucXapjdktf+XmGYI1k95h/y0z+Ozab/Dw6Ld4+v/ymZ/zT+76toWrLeu5eYbgIt9zXHNqIZedlMsc19NcNtnL7Ja/cv5YV1g8u9zM+VMymFX3KLNLbcyqe5SZuY3KeblZbz+tTWeX2qK2cbT27+4eaeflOx5g5rBQzHtspEXyFH+ytFseTb5EOLrQij9Z2vmsGZ5DI82Yd/EnSylxV2J/7Q5K3NGf4zA5NS4RDoYIhy4XRlOf8XtnD2fmsFD4fe+oZES2HNrffUJCSNLccjB+1KUwcJCZkUFmVlaveNucTlwuV1haenp6l0FJYhCYzLHDEceRNAHqq3A4zIVf3Vonx1S8LN99d0NC8j3ypORT5sKHSV436Y2WFmf53cqpcWObp0vaoHWwdsIJMhkcOHhQ7q2sTCqPFI4etLW1SZ/fn5BsMBiMajLsdrtlR0dHWBpxmvYem5MtPz391Jgh3jyTDYNUY9L35sIlwkEJDqbsWjqgTDlT8oOkjv0k31K1hdp1FYqpr4FWvPHuhMqPKqfGzQ3VLFn3Lp7X54fRRuaZet4JbwAi2e/APnNwlcJRgWAohExwPU7k3jrGPLtbV9RrCBAmETMcaQyYxa9CCDPwKVArpfxhT/yHw1xYGH5TSGEgotnlVfc4VlCcnU5OaS7pUUx9+xpDctKpmD2ZjLcG7vdMPP1I0hMxMjWVk0L3MG7MB1DQi7Uk8SK7l1NBsSCEwGwdYP/pI6meiRWAPwDPAi/3xJs/fLTcVefo02mCD79qkuMqXpZbNr2fkHyPPCn51FROkvKNbR55xVOfJjZNE4UnllfXeKZ7BtJUTjz9yAlJTuUcrK5OTeWkEBWBQEDW19dLf4JTNy6Xq9fTPh6PR3p9Pv2cOKddjsvLkVtnnxYzxJtnsmFADJOEECOBs4BHe8M/FBuemm19uvjV6m5mCA5GfbEiIfmYPCn5PrlHA7qOR0C+RDhYeOZQfRFyMuXH2geHQzvxvLkwqnxzQ3W43KGdjMg1lR3eHqJ3iLcf6aMyE5bVzG27CzKlkRm0MJvNlJSUxPQ5Ewv+QIBgIBCWFggEsNntXZ4Lj9eLz9vVcWKvMQCncgaEubAQYh2wCMgF/ih7UMEWlI2RH23e1mlSC0rnmYS58O7QSM5d+T4v/3gI5cefEre8kacpa7xuQhzLlNRoUqqZshrNVaOZEhvNY4d7FdPcSaZqps34dsw6Njm9YebBscyNjWmaubEmbzQl1syFtRjAeWCrXv/69HKqd3/C6qosqu1eTs6oxZU/gRPT62nOGs8J1noaM8sZE9hPR4FyjcXte/EWTabQtZfAkGPDzIXbcieSl2klx7GHurRxXcyG7R1+hnurdDPhWObCxjStzSPbXzMpNpoNa+bCmgmxdh8jTYm7i2M9BxBu7nsoQzHNNZr/Gk2KuzMlNpoHR/Jq8pqZ+4jJJ0c1JX78xVe45NyzuuQH6HKmpp00ZY7npHFFA8JcON5+5MQTT5Rbt25NuLwDBw8SCAQSMhdub2/n0KFDYY7A+rIvLh83LuqgqdVmIzMzk8yMDEDxZ9Jqs5Gfl4fVasXpciFDIXJzc2ltbSUnJweXy4XValX8m4RCuj+TkHqs+TsZTAjzXYIyrRfNd4kRupM11aeIJqM5R0MqPkq09SDa17+en+zqw0SHmh/QaRIsO32taHUNhUJh602i+WAZPWpUXKa9xxfmyRdOnxGTZ8pLbx9dDtaEED8EGqWUm4UQp8fguxy4HGBofgZpLbthR984WGPDImrHXU+Wz07Wh49DyR1xy2s8njcXsqjlh5zZ9DiPxHC+ZXTCdUVwLQuCl0AIFqYrDr6ujnAMJlGdr0U4FnvMP5c/WNfzacYDnDyuKGrdmk+7myWv7ebOtCfIOOMWnRbNQZsxrX3mdRxYP5/Wc1fwyLtVzDc9xkP+OcyzrmeF50f8P9tfWZd7EXOdq3mi4Cr8gRDnNy/nfo9Sf62Obv8lDAEuDb7AskUfpbUAACAASURBVENzOV2lzbWu4xX/XL7Tg/M0zcHavQaex2I4WIuUj3Swdrv1cT1tRWCu4jzNezEIujjBuzK0Vne0dotXcbB2E4+x1DuHa9PX8xDnhdGi3WMtjvUc3MWlmIRgofVJlvrO5XJeYJl/DrdkvcQy/xyu4IUwJ2wrOS+q8zXNCeA59qd4SXUGqPEu8F9MWWEmP299QHce+NgHnc7X6mxu3XnaD1qf5MHng3o+59ifYs2QqwG4oHkFj33wcy50P8v93nMpK0gfn1Qn0AdIpB8ZMWJEUmUafUrEC6vVigTSrFZyc3OBzpeb5rAsJCUB9avZZDLpXmS1F5G2kDIYCoV5is3KzOz25ZqRkUGa1aqfCyHIzMjQv+zT09L0l2lGRgZWq1WPtYGJVketfpoHWK/Pl3B7RKKLozI6PbBGmnnraYYXtIxCi+o5VuXVHZhFeo4NZw4bXEjZ6VBNhkL4AwGlbQ2DDxkKdZZr8CZrhHFwGulRVueR4V5npbGNpOLwziQEIsFnMlG5w4V+15gIIRYBFwEBIAPIA16UUv6sO5nD4ZJ+o3MoP330Y/42p0DRPiShMXntUCHLn/07l/zoB8zIbvjaaUwiNSXRNCZaHfds+5jnD2RT1+ZjWlo19pwJfCOzgcbMcqZa6ziUUc6YwAFc+RPITrOQZf+SjoJJjPLv1x2t1VrHdcaFWdC4g7bciZT59oVpToCwNqlPL9e1KZoGpyDLqrep1p6aU7iCLKve/pqjO01jot0jTSuilWHUmGj3L5qDNaNWJDLNqHE5khqTaE4Eu9uSIVJjsmK7lfkzwFc8eUBoTBLpR5LVmNTW1eH1eikfNy5uWb/fz8HqanKysyktLU24DkcSbW1tSCA/Ly8sXUpJc0sLuTk52B0O2l0u/QVrsVgwm82Kd1J1kGBSX9zay9BscANvtVpxezxkZ2Xham8nPy8Pp9NJdna24iLfYsFiNuN2uykqKsJmt5OmDp5abTYKCwoIhUI42toYUlxMIBDA7nBQXFSEyWSipaWF7OxsMjIycLpcBINBfVGqkaZNmxQVFWE2mfD7/WH5SClpaWkhNzc3MW+rfYzW1lbS0tLIycmJ28Ha8UX5cv2Z34rJM/mFfx1dDtaklDdKKUdKKccCPwHejtWZwOExF7a6mynBwegtSxKSN/LkOPZwvXUNZb59lG+9t9Ox1tZ7FWdZEfG0Pct151/lW+9VHHztWd4Za87XDv5ZcSh28M+K87A9yzl/rItpe5b3aApaIhzRzaQ7KrvUX087pJqdGuRNTTupXVeheIHdeLfiaG3j3Yq5tXBQvvVeJpqqyd94F5NM1ZxW/SD5IQdDcHCVXENRRyUXOp+gzLufM+tWYmnezayDf6axoYazxls4peoBmvd9zv8cWkXtV5/xnYMP6vGXVVUck93BiM+WcEZJCzOq/sTubR8z7avlvL15OzOGBpi8cym7t33M5J1LOSWngfyNdzHRVM3knUt5e/N2JuS4mbZnuV7HiaZqyjYv1mnG+pe4K5m2Zzkl7kpM/7mdCTluJud6KNu8mE2b3qds82L9Pk7IcfPie1vC0jS5Enel/hwMEY7wNFMNZZsX8+J7WxgiHBRvvFuXn5nbGHauO2FT5Yw03fna1nsV52eGeLKphuz3FobJR/LoztfUe9odT4lwMG3Pcu47zarnPTJHDjsinUUMJNKP9Cf0L+pBNAWSmZlJprrXjhFCCLKzskhLSyM3Jwerqn3Jzc0lNy+PvLw8cnJyyMnJITcnR0nPzSUrM5OszEyys7P1vNPT08nOytJjq9VKlpp3ZlYWmRkZpKen647JMjMzSc/IwGQykZ2Vhdlsxmq1kp2VhRACi8WiHwN6XqBoj4zXY6SZzWays7L0nX0j8xFCkJWdjdWgfUoGdocDj8eTsHxhYWFSztYG2hqTfp/KGXhI/ibkZlhoUeOvG3Tz1OzuvxJ0npIcvMPzWP39b/Knt/Ywvb2Q+06dxojNbzB21mRy3sunQo3nf/84huSk4x2ex7xZE8ndaOF3M48Jiyu+p+yA69XKt5j43axwmpaWsdFEhrGuFlMnT+R1xKLR1SQ3w1CGhmimtNHaakhOOrkRaRkR5fc1Wtq91DY4KXN54y7DGwgRTaI4xv0/WpDMoEJfFzDAVOixEOslnKUOFLKzsxN6QRrz1qaVsgyDDyBsN11tjUyGQVuRZTCd1Y6FEGHpxoGINWJhqpEWKRd5DugbIvYFrFYrZrO5V7yBQEAx8TXwG/diihdCgNnau7KPGI6kCVBfhYLDYC68q84hj7v1VVm57eOE5I08r26tk2dWrJSvbq0bNKaoA15+MNRxAMtH8w7bk3xjm0fe9pcXwr29RslzIJkLxxOSNReuqamRlVVVCcn6/X65t7JSNhw6lFQdUjj6YLPZpN3h6JLe2NQkXe3tcZv2Hl+cLyt/cVbMEG+eyYbBM1w3oASbsvi1D01RXc11ZPts5H98X9KmmMO9VcyzrmO4t2rQmKIOaPnBUMcBLt/dnkm6aXAUWklHJRWZf4u6H5PR3HigmAsfcXRnYRFXFimHjil0D6fL1WWKJz8/nzx1wbQRBfn5CWlxhACTxRwzHHEcyVFQX4XDsVdOXzpY+/CrJnlmxcq+rePRLj8Y6jgI5cO0InHKH/Uak9paWbVvX0KyusakoSGpOqQwOBEKhaLufRMJl8slPR5PXHkTp3Zj6pB8uf9XZ8cM8eaZbDDfdtttR340lCSeXHrrbVdc8P8o3HgXlJ8OvnZ47TooPV5ZtBkZ94LHM2oWG3ZU8TvvX0gvOyFueSPP9sBITqt+kPaCSUzYdl/CdawyjUW+uYCaglPYV9tI7oab2BUYRdqGO6hPH4//jfl85hlB7vsL2ZE2nV0H6sl5+0Y+84wg8507+MwzAsvbt/O2ZzK7D9ST+5+bqBJjGPbJPVHLb25tJeutG8NontfnYznmv8DXjuef12IZPlVJi4jtw06lw9WG6Y0KDlrGYdlwO7sCozC9dRvPHBrL7es/ZugHt3Lduz7GfX4v92+1UPbpYp7cm0XxxkU8c2gMX1TWUvjuLbxcX0DBxrvZ6Cwl7Z072OgsJevdO/XrKHr3Zt51DCX/g4X6tX4kp7KvtpGCd27m044yct9fqMdfhkaTtuEOPgweT2urjYw3b9DT6tPHI99cwI606dQ1NndpY/nmAj2uKTiFVpsN8dr11KeP168x+/2FHMyb0YVWay0PizWetH/f0C0t++2b9PbTaK78SQT/vSAqj5Emfe0EX72OXYFRFGy8m4OWcWS+d6fO6xz+bWoPNevyme/dSUvWMZxRt5Lmkm/p8lqervxJmN6+Xefdl3tyGE/2ewvZ7h/Jv9Y9mXHV9QvuOeIdQZJYtWrVbVdeeWXC8k6nk0AgQGFhYdyywWAQR1sbFquV3JycXsu5PR6am5txOp20OZ1K3NZGW1sbdodDCXY7bU4nDsO5zW5XYpuNtrY2rFarvtBTg8frxWw266awPr8fi9lMIBAgJKXut8QfCBAKBvH7/fj9fnx+P263m472dlptNpqamrDZbN0Gu82G3eHA4XDQptbfqV6L0+nE6XLhcjpxtbfT3t5Oh9uNq72djo4O2tXQ0dFBh9tNR0cHbu3Y7VbqocZutxu3x4PH7cbj8eBWY4/Xq8Qqzauee71e5djrxevz4VV5fD6fHnt9vjA+n8+H3+/X07yGc43f5/crfD4fPjU42tro6OhAAj61Hf0qn0+V8fp8CJNJaXMDj9/vxx8I4FfL8gcCiqzXS0tLC/fff3/9bbfd9khvn6mV9y2+7WfHj0eYTN2GZZ/uiivPZPH1W52ZIBwdfjw+iT+Q/Cr54fmZtKgxhxLLw+kNcM0Ln3GNtHPbU5vw+CRL0mzcs2cb11vtLH/hM66WbSw+sIsbrHYqqj5DAoutSlqFHjtZ+OpuABZbndz3t208M9ZPUUR5zS4vi1/bzUJT52JH46JJgLoGJzlNLlwRcVu9k4df2g7AZa0OFu3bylXYuHvPNq63tvHIgf1KhlZweiROa5DttU4arV7eam3iZKubpz+uBmC8tZ3VDdWUWV0sq91LhR4br6ONZQf2Gq6xjYoD21SancVVu6hQ4xusdpZUKW1WUbUNofJoaSvWbuHqkJ0bqj4DQVgbazQtvmP1J0gkC4J2Hlj3OddgY9FX27gx3caCKLTlB8PjBas/AeD2bmgmIVhssbNYbb/lBz9nHjbW/mMH59lt3BrB83sD7banP2VUYRaXtNq4p3Ibt2fauXffF1xv7eR97IXPqbO5udtiZ4lKU+I2bnp6M2WFmVzaalfztPPSy7u40OXgHpXXyPPSy7u4wGlnwZ5tYMnoi73XBx1EElM5mlxvFzxqsNvtdHR09MgXa2O3QDBIa2tr2CJVKSUOh4PCggLS0tLweDy42tspGTIEl8uFUP2ohKTE5/MhhCAYDCrO1UIhAnFsJCcx+GBJdgO6AYZo1la6fxLDs6LR29vbu+YBur8a3XeJwfmbFkeDsdw4at0ni7Dj3e8uZl6JXUj/orBsjNx4GDy/zln1Af88rzhpz68bnUO5/dF1LLhsbsK+Vt577x0uesXFnd+EGd+aha3d18UradPeLbo/E3fhJOwdfnIce3RvqK78ibrPD4A85x4Kxk7rrFMvfJ1ofkwA/TharPkx0byBan44AvU72OwexvrPqsm076UxYwyn5jXSnHUMU6212HImhPkxKW7fS0v2MYzy7ycw5FgszbvCPMACXfyX6NcKMT2/RvoxMXp3jeZHxuj5VYuBLt5gNd8lkbRkPb9qNKM/kkgeI03zUWL0fxLN14mWFhlH83FivJ/GMjTantAozjh+WL/7MUkEyfoxqauvx+fzMXbMmLhlA4EABw4eJD8vjyFDhvQsoKKmthav15uQt9meEPnCM74IY8lI2elwLRgM0tHRgcPhAJSXbGZmJhaLBZPZjMlk0v2YGNfoGMs1OjvTzjUHcibNIRrdr88xvrx741E3zAGaxqs5MosYDEgpMZlMujO8qMdKw3RxwBcy1iOyThHX2hOCwSBOp5O8vLwu5Vit1rh8jpxYWiRf/cmZMXlG/umFHvMUQvwBOBnIS3Zg0u/zvImECcNzFeuZ534mpfOQEp77mTL3HS3uBc8nX+ySM254RjY/el5C8kaeLZvel6/e8j1lvUqCdax/eI48s2KlrH94TvLXONjlB0Mdv8byzZWfyc1LzpJN9Qej8kwoNtv7u09IJCS7xqS2tlbu278/IVltjUlTU1NccjW1tamNA1OQwWBQOhyOLutUAoFA3OtBThhaKGuv+UnM0FOewEjgLeC/6cUGmj2Ffu8cEgkFw8ccFnPhKQv6xlz4w6+a5PeTXPz67rsb5JiKl+W7727om2sc7PKDoY79JN8rU+Aky++ujMY2j8wpKnHIAdAvxBsGwuLXpubmuMtMDUwGH0KhUMI7DcdbTtwDk9IiWf/HC2MGYD/KNI0WLjfmAawDTgJO74uByaA0Fy4VNkrcXU0YkzFFNXc0MQQHQzYnv3Nrpu1LrrauI9P2ZcJ1nLDrASZSzYRdDwx4U9SUuXD/yWtmu80N1b2W727n4ETMjUs6KhkuWgfffHAfQKju1ZPKo4/qksLAhtfrpaW1VXuJd4tQKITD4UjCWVqCa5569vzaLKU82RD0hbDGfaoSKjwakh3Z9Ec4HBqTD79qkuU39J25cEpjktKYHCn5eDQmUZ2mGfLW84qj/KPVXLiuri75qZw4NSa1KY3JoEQoFJKBQKBHvkAgIFttNhkMBsPS29raZFtbW6/KIk6NyYnDiuWhm34RM8TKE2VH7xoUrUoD0AE8HU8dIsOg1JgMpUVxsNaHe+UMEQ5Gprcxftt9CckbeTJtX3KddY2iMUmwjlN2LWUi1UzZtTT5axzs8oOhjv0or+1n1Bv5EuGgwvpc2H5IGq25oZradRW0VG3pVr65oboLbWSeaWR/9wn9gbDFjAki3u/bYIJf0in0LyJdyHcHs9lMYUFBlwWtaWlppEXZLDCg7uzcF/WLFWJBHoZ9qgblwASgze3v8zx7tx66t3klB7c/GBankEJfIcMS/W8/JCedSaW53e6Do5mUewOplyPQaV2SDOKUT3mKPTqRnp4etleQBld7O+29MB+PCSEGnOfXlLmwwVz4x498yEtzipI2F94dGknFqjUs/vUFCddRMxdefVYOs2adFrf8a2++ScHYaQTqd2AZPkU3Ja5LG0eecw8MnQKNO6i1jmOEfx+11nG4vAGK2/fiLZrMZZO9MU2Jm7LGU9JRGRaDYi4cKjlONzPVTHE/rmrhww/fZZOnjJMzanHlT+DE9HqceRMZEzxAW+4EstLMjPbvpyX7GL0eha69XcyFteNo5sLacaS5sNYOQJi5sDGGns2FjWbbmpmw0ZRYM6vtzmzYyNMdzWgCrNE0k16t/EgezRTYKG/kiWUSrMWxTIm1GAhLC5Ucx7iheZUut/eYPvp7HzH0hbmw3+9nzOjRccsGg0H2HzhAYUEBRUWRXoVilFlXh9vj6bW5cGNjI06XK+76jRs7FpPJhJQSR1sbuTk5hEIhPB4P6enp+Hw+pFTMhAOBgO7kKxAIJLw+oq9gNCnWzXANx5EI4zP4IREG2cgBofGtGWne3MmkcJlMpjD+qLx0+i/R62/wf6K9p6UMN0MOhUKKabKqjZFSUjZ8eFzmwtNGlMi3rvhRTJ4hC/4SV57JYlA6WCsVdmXx6ydL4az7lcQNi+D0G6PHveCpHXc9JdLBkM1PQsmtccsbeTzlv+bK0Fo8NcdD1aqE6njcngeZyH9z3J63Yfqxccm/VvwLeOceFrw5l3nWdcz3XwLAndbHecyvpC1T4xfUeJWBZ5l/Lt/b/gbj5t4FGxbRfNrdLHltN3emPUHGGbfgeXMhD7l/xDzreh7yz2GedT0L/RfjC4S42P4A63Iv4ty21SzxnsOvgi8Yyn8eO3O5NLiOZYfmcrp1HcsOzuX/Iuq4OqKOWnxvjOuYH1F/I225fy7XWNdxq/8SBHC79XFW+OdytXWdHi/wXwICFqY9wVLvHK6xrmOl6TyuDK3V47tNl+LxSYXHN4dr09fzIHP5dXAt95gvA+BmHtPTHjb/mN+wloc4j9+wlru4VOfR0iJpt/A4fy/4OWfbn+JB5vIb1rKKH3Nt2ovc7PsFHb4QC9Oe4B8Fv9B5fss6VhddRU1rBzfyGH8v+Dnn2J/iJTWflZzHtWkvssB/MWWFmfy89QFeMvCcY3+Kp4quos7m5nbrEyzzzWFe2vou8QL/xYwpzuYy54Pc7z2Xa9Nf5IXsnzG8IK3vnWoMEiSqwUj4gzDO8lyqA6/e+PPoFoaXYkhdAxAKhfQ4GAoRCgZ1z7D9DW2KTUKYvxDdH4lyomu1pTqwEICx9tGcmmlx5GDGOJBBSiTobWGxWMIGFmHlR7mfQW1Ao/l6MdCklISCQcUhmjrAkVIik3BUJxD6wGagYJBqTMbKjZu/6DONSdX2TZz7oo2xRdk89oNsxaFYEhqTvnSwlojG5Pn9OTz2t1c57Tuz+G5+c0pjktKY9JnGpDgnXb+3g11jMm3aNPn5558nLF9XX0/A72d0AhoTzcFaYWEhRXG4tI9XY1JVVYWEw+KQLYXY0N6tR3r6TQgRl3Zj+sih8u3fzo3JU3TTyiOqMRmUa0xKaO3T3YWHbF5KfqiVW04bophFxikfyVPqqeIP6esp9SS+u/Bxex5kEtUct+fBuOXLfPuYZ13Hd/ObmVX3KDOHhZhdbmZW3aOcP9bF7Ja/MrvUxuyWv3LZZK8Sn5TLNacWcpHvOWVQEpF3iXB0MRMNi4WDEuGg+JOllHRUUvzJUiabaphWtYqZw0Jcc2ohLxz7LvvnjWPdse/x+k9LWVz8Gg+dmUVFxkvc9T/DuPn0Ei7yPcc1Jwb1esxxPa3X+fwpGZw/JUM5HutiVt2jzC61KXG5Wb/G2aU2plWt0uOZuY16O8wcFtLTwmKVVr7jAT1Nq78e53rCeMp3PBBGm5zrCU8z1ejn5Tse6MLTHa2ko7ILT/EnS8PKj+QpEY4u8nrsrtTlS4QjOo8qr923qLEqb0wr6aikLCvQ+7mIrxE0F+2JQHtZRS5y7HOk1qT0G3q7ZUEgGKTD7T4CNeoeA22NSb+b7CUSSkaOCzd3lDIpM80tm96X4298Ody8N1lz4RuSMxfesul9Oda423Ec8s99dECeWbFSPvfRgX4zZY00O21s88jmys/kTeu3yi2b3pe76hyyctvHenpjm0e/p8Y07VyPDXkby4ikGeXC0mPwxKQZyujuGqOl9YYnWt6x5OM1Jb7iqU97Z1Icixaj/oPVXPjEE0+UyeDgwYOysqoqIVnNXLi1tTUuuXjNhav27Tsi5sWOtjbZ3t4upZTS7XbLQ4cOycq9e2Xl3r3ywP79sq62VjbU18tDDQ2ysalJNre0yJaWFtlqs0m73S5tdru02+3S6XLJ1tZW2d7RIR0Oh3S1t0un0ynb1djj8Ui73S6DwaBsaW2V/kBA55FSSpvNJr1erwwEArKltVUGg0Hp9/tlS2urvqNva2ur7uysTc1bSuWetKp8UkrZ3t4eZqLrdDqly+XSz9sN5Uoppdfrla02W9xt19HR0Wu5aLsSBwIB2dLSIgOqiTFxmgtPGzlU2u/9fcwQb57JhkGpMSkKNuE8sLXPTFHHb7uPEWltDBGOPjHlzLR9yXWW5MyFyz69hwlUU/bpPXHLl/n2UWFdQ5lvX7+YsrZUbQkzO21uqGbh8xvYtfoPfLLpQ1r+cRM3PLyGmnUVLHpiPQeev45bn3mbhc9vwPnKzax49iUOPH8dK559CecrN/PQ8//A+crNLFn3Ll9VVlK7roKq7Zv0Mjyvzw+jaWkPPf8PPK/P1+vT3FAdZhJr5Ik0lw2jHdqpl6GZy0ZeYzRz297wRMtba9No8vHeo+KNd3PXt009mxRHoXUxG+6m/kerubDFYsGS4Nx8ohqTeKcFlPfU4YfFbNbNYU0mExarVadZrVbMZjNmi0VvM7PZrB/raQaaSTWv1WOTCZPJpJjdWiy6+a1JdXKnla3xanQhhFIfw33S0gHMJpMuG2nSazZckzFvDabI84hyeovMzEwKCwp6xet0ubDb7WFpQgisVmtSzv6ExRwzHGkMysWvhwOWPhyj5WVacZgFeZnWnpm7q4/ZjFDjeOHy+klT4/5AcXY6OaW5pKtmp0Ny0pn/w+PIfaOIsyzDmN5eyNJTp1Oy6XWmnH4sOe/lc+f3jwcg9y0L806fSM57+YyZNZHcjRZ+N/MYcjdaqPjeZIbkpOMtzSW9JEeJs9PBYgqnqWm/m3UMGRtNZGj1yVHqkxuFR6tnd7QMQxnRrrGLfC95ouXdXTsmcz9iwRvo3FHamPbnt/dygzWcFq3+Ry1E4ruyJjxgGKBTM1lZWfpxWloaRWlpca2dMSIjIyMmPU01m83PywOUF7uG3Nxc/VijCyHIU4+BsGNjvc1mcxgtPcJviLEcgIwIusViCSs/WWg+SoztkZ2V1WWBsclkSqrcZHbJPmw4kuqZvgp9PZXTXPmZPPuB96J7w0ygjF11DnnOgoeT8k67ZdP7ctwgnsrpc/nBUMdBKB/mCTYKrTdlHK1TOXV1dfJgdXVCsj6fT+6trJSOXnrz1Musr49raqayqirlKXaQor29XdoSmBoizmmX6aNKZduf/hgzxJtnsmFQTuUUBpuVqZw+WvxqfW8xbS212Btr+mQfE0/NNi4PvoCnZlvCdRz1xQomUs2oL1YkvPi1zLdvUO8DM6jqOEjlSzoqqcj8m7K4OQqtN2WMyDWV9Xef0C9IYq8c5f1x+PfK6e1UUSgUwma302qz0drais1ux+5w0NbWhsPhwG6343Q6D3NtUzAiKyuLgl5O8SQFIRBmc8xwpDEozYWHjiqXO3bu6jRfhe5NaLU4Bk/V9k2cs76VFy4/tdMEOQ75SJ6NzqHc/vg6FlySuLnw5598wLnr7bw4p4BpM74dl/xrhwpZ9uzfmffTs5ldautV+Y/uTmdEYRY07qAtdyKW5l1UW8dS3L6XluxjaPcFyHF8xQHLGKan1XHRj87S5VuqtlBcPl03KW7KGq+bDWvmqvua2mmu/Iz5H8NEqnHklHNSVj1teROZJKqx5Uwg02pmTGA/HQWT9HJH+fdjyzlGN2nOzbCGmTuHxSjmwpbhUwjU74hqNmzv8OvHkebChdlpunmz0VzYXThJNxHWeDRTYKPZsGbKazTzjTQbhp7NhY3mvUYeo0lwNB7NFDiS1p1JcCxapBO1WPJHq7lwfUMDwWCQkSNGxC3r8XioraujqKio1+sLtDI7Ojp6bf574OBBAoFAj/wHq6vx+3ue+s3MyGD48OE0NzeTk5OD0+XCbDbrztUCgQDBJHxqDFR0N9UR6RvFeKw5TJPS4KzNkE+P0ydSIlQnd0ipO13T5bW81cGnpm0YN3ZsXKa93xgzXL574y9j8uReeU/KwVpP0Ba/lmy9F85+UEl8cwGccXv0uAeekk2LKJLnY+5ogo/il4/kKT3xOm5Ie45Szzfg48TqOHrLEiYym9FbHoFj/xKXfM7o31FhXUOa41jY9uceyz/wwnWsqr0QgMXWh3nMfwEV1jU8rMYr/FfotFf8F3CWdQ2rgYs6nqRl5k3Urqugdc5KHnm3ilvlQ6zw/4RzW//C09mXcE7rX7hZ/gq3V5GfiJLnYtcFzPGuYXHjBVxsXUOFoYzFarmrI+qxKgqPFhvl71TTlkXEN/ivQKo89/ov4DrrGj2+MXAFGWmCBaFV3Ou/gOuta1hh+im/Dz3LvYELuCHtOa73XU5GmuC20CoeMF/I1TzLPd6fcGP6c9zKFbi9knvTH2E5P+UanmUZF/D74LM8YL6Qa3iWBfwagNtZpfNosZH2Jy7kButzLPb/hKt4huX8lHms4bGiP1DT2sGtQ9tEzwAAIABJREFUrOzCc7u4klGFWVzaupRlXMBN1udZ7P8Jv+dZ1hZcyo/tj/Fo0R+os7m52/JwTNoS9fqX+JXrfibnEn7U+pdu5UcUWI9KJxkmIQglqDHRNBlp1vjWoR0uDYs2KMnJziYQDOoDjMgP1+LiYoQQ5OTmkp6WpqjdTSZCoRD+QICA34/X58OdpPmrMLzYI9dAaB5pjZ5Z9UFBBK/ozLBzwBDDA6zx5R/m2MxYrpHPMGDQ09VytOuQoVDYuRCCkDp4i/QKq+UpVOdqenlSdtZdpYdkuNM3j8eT2FoRQb9oRWJhUA5MTEKQn5X4wtJoMPfxXz753EREfPgg1H/GD6aWMtmey7xJxzBhZw4XjRrFuAPZXH7MWDr8QUZUZvK9khLG2bL53qnj4E3DAs3SXCpmTw5bvHrzrGNJ21DA46d9k4MtHYz7MFvZexIozrKQa7IwfXgeQ13p/GBEKRkWM6PrsrhorFLuRWNGMaE6hyvGj2Py/lzmTTyG7HQLk7flMv+EYyn/ojNePENxcHb85nyWnDyV4Z++yvzjj2XKrkLmH6vEK2d+A4fbz/TPC7ln+lRGb3ldjx+a+Q3ys6wUv/W8nrbs1OkUfPga90yfyvhtb/DQjE6e+0+dRsmm17hnqkJ79LRTcHT4mfRJIfefotCWnqLIa7x/OW0GAMPeeV7n0WIj7d5TTmTE5tdZctKJlGx6tZP3B9OwtfsY9k5hF56HTzuZwuw0TP/IZ4I/l8mZeSw5RaFNOX0KaRsKdPnR7xfoctFoi086gRGbX9Nj7T52J/+vuzzth/0hHYDQv44TgDCZFE+jA0Rjrb3gSktLe8WfqS7INC4eTaH3cLlceL1eiouL+7sqQOKLuA8bjuSClr4KQ0cN7MWvfeXHJNHFr69urZNnVqyUr26t61X5615+XY6peFn+ZcPeAbUw84iX8TWRT/g57obW03/taF38Wl9fL2traxOS1Ra/aj40el1mQ0Nci1n3HzjQK/7KysrUItkjiFAoJAOBQMLymn+WaCDexa9jh8v2J26LGeLNM9kwwIZJvUNBYGAvfu0Lz6/lOx9ganoN5TsfiFs+x7GHedZ15Dj29Kr8Uw4+whAcih+XAbQwczAsHh2I8l0WrSZRvufNhYo/lzcXpha/RkCYTAmb7yasKUlUrqdsD0uuKXSHSJ8p8aKjowOHw9FXtVGe41jhSONIjoL6KvS1xqRy28dy2m2vh5v3JvE129/mwh9+1STPrOi9xialMUnJx6J9XTUm06ZNk8mg4dAhWVdfn5Csx+NJSGNSU1NzWDQme1Mak0GFUCgkg6qn10gQr8ZkXJnsWH1XzBBvnsmGfteYCCFGCSH+I4TYKYTYIYS4uieZolALpqa++xov27qcEwp9faYxSGvZzW9Ym9R+PsO2LOMYqhm2ZVnc8oH6HcyzriNQvyOlMUnJJy2va2C605jkmfvd82si/YjShydZbsKCqufXOL+a410L0NvFkId9z54U+hSaR9tIJGYRJcDUQzjSOJKjoGgBGA58Qz3OBfYAx8WSKRw+JiltRDSNyTduf2NAaUwqt30sj53/iqzc9nHc8h9+1ST/Jw6Nyav//rccU/FyuEO2gfY1P4g1DgNNPtpePT3Suimjsc0jc4pKHHIQ9iPJrjFpaGiQ9UloTCqrqqTH44lLrq6uLq79eQ70UmOy7wjtqZNCbAQCAdnc3Nxl/Ynf7+9WQ2JEKBSKW7vxjfIR0v3c4pgh3jyTDf1ulSOlrAfq1WOnEGIXMALY2Z3MMNFKibsSNt7dJ+bCZZsXc3zBLzv3yknSXDjtxOuYxxrSWqZBgibNBR/exWj/bAo+fBjGxmcunDnxGq63riHTNhU+Xt5j+SfsXs4Qfkq6txneXNRj3b565lr+M/JK/qtmJU/l/IIf2x/nT9m/x+0P8GjhajL+9048r8+nfdYtZL+3ENf3l2Nr91H81o2sK7iU8dvuZ7H/AhZkPs8zub/kcv/TrCm9jnSrmQvq7+W90b/hjLpVfDDmt3y35iHeHfkb/rt2JRsm3Up2uoUZX9zKF5Ov4YTdy6k68TrKt97L7lMWATB18018efwfmbT9Pr48/o9M2bWUHcf+gSm7lrJl2kLyM62Ub7yRg9Ovp+zTe6g7+QZGb1lC1czFqsWNQhu9ZQkHp1/P+G33UTn1j4zfdh9fzlik89hPvZmCD+/S45bvLQXQaSWbFtF0yo2UbFqkyzecdp/y/L5zs07T4mg03+m3krbhji48o96fT91JFbp82ebFVH9nSReaUd7I43zhOqrPuJ3JO5dSd1JFF5rj/+4Ok9di7w/+hK3dx6j3lXubtuEOTKffSpnJ1u+2hon0I33hhjvRPKSqrYlXPm734b3l7YEvEAhw4ODBqLScnBzd/XsgECAQDOLxeGhv772xlmZuK1Q3/1JKXSsgpQxzZGc2mwkZ0mSUPCSE+QERBmd4up5MyrC21MrSfZBI2amVUK2WtDxR+bR8gM6yVH4tXaPpZarm1WHla3WTkkAwqDuz08yGO9rbMZnNZGVmKuuTZLhvFCllp6ly3BAgBpbGrN8HJkYIIcYC04GPo9AuBy4HGFYQey+FeOEPhqizubG1+xjSB/nlZ1lpsZqSMmm2WkxkpAuslvgfGKcnEBb3iDie5kfe2ct4WwfrGusYb+3g40Y7p1u9bGltA+Bjewujmly01Tt59rXd/KStjYfWfUFls5NbgnbWVdVRoTaLJxBib6ObFquPt2zNAJxmdbPuszrGW9tZ3VBNmdXF6tpqyqxOltXsBWCxelxhdbL4lV1UWJ1UvLhNpbWx+MAuKvTYzuIqJa6o2oYAFlvtLK7axvXWNpas30aF1c4N+z5TfZTYWVK1jeutdpbs28YNaTbu+UqJr/+qk2fF2i1cbYjvWP0JEsmCoJ0H1n3ONdhYflCJF321jRvTbSxY/QkAtxtoWhxJm4eNtf/YwXl2G8sMPCYhWGyxs3jfVq7Cxp8ObuUGq53rV3+CMNB+b5BfofLc9PRmygozucQb4E+v7OQGq50l+77gegPtUm+AJ97cw3l2uyr//9m78vgoqmz9VXVXd6c7K0lYgmwBQiAgBNSRmXF0FmeGcRZHcRnn6bynPnXmjaPMPAmIDChrQFlEWVScARdUAm4sOqIPWUTWgEBYTCcknYV0lt737rrvj+qqVO9V3TEkY77f7/5u1z3n3Hurert16pzvdtYb3zmJJpMLSxkL3thxDrd2cDIo1T0qZ1Tq78hVV3XBE6hkFyZIbo8S2Q+fiDQLkkCvvaMjpsxut4NhGPj9fvh8Pvh8PtmPFPg/VhAChO0F0xtAiRYW4te8TFg88G2coNM+rD+n04lgJ/wAABDCD0OiLU4kvt8R6GE8Jj2G+ZWiqHQAnwNYRAjZHk934NBCcvps1zG/ttdU4pGPXVj7H1M6+5RhH65znr0Kcza8jUUP39XJJCtzjjVnjuA3FR14f3o/FI6/Tpb9IVt/zHulAk8/KI15dv/+z3HvTjvW3TO5kyk2Rt+rTimw67P/g25ICablm3DYOQDDA3U47RsMp9ePTb/MRG5hKdprKsHmjxMYYNvtHrgbTmNnSzY+P7AfFzEEP8i8jI70USjVNKNdOwoaRoFh/jrYs0ZjqO+SwPxqYIZjDG0IYX61ZhRFMsCCY361ZxUJtZj5tVldiGwtIzC9+pvPQjmoJCbzq5jxNRrza3gNIILpNZwdFpDG/CpmZQ3XicYKO/cQiz//cBSKaEMEq6uYCTYaO2y4TMwGG17zzK9iNtiexPwq53ektLSUVFZWJj2W0WgERdPIz5N/O+N0OmFsbcVVgwdDqZR+f9jS0gKX243hw4ZJ0pfK/JpIj2eczczMTHi+LMuCZVl4vV40X+aIi1QMA7Vaze2CK9opONouy+HsqIlYV8NtwuXiOhbCFxPhbeGvE/UXDYGgJ0mn08myE89FjGjnTgiBUqmUxdI6ZdRQcnDZ3+LqpN3+eLcyv/YI/w1FUQyAbQDeSPRjAgA5XRz8qju0HFkBEyhH1wQWqtrP448pBr9mHX4Wgz2XkHX42W88+HX4meeRBws85uaEfec6qjGDqcBtBVY8RLZi47QMzE3/EO/8x2jsuH8sco+uAFqqkHt0BfKdeq6mLCjOcGNSzXrMuZbCv0oP4tKMEdg8ci923JWPBVk7sfbWoVhxy2A8ptyGOddSuNf7Fh6fGMDt9tfx+MQAprVvwoNTMnBXiQbT2jfhruF2TGvfhGkDTFxdqMC0QgVuaHoF0waYhHpSzfrOulCBqQNZTKpZj6kZRtzQ9AqmZhi544GsMEehLcOIwrNrOmuRTjHdEFpnuENkhWfXCDVvz+uIZUIdRZbv1EfVyT26IsJ+9a8GY+pANkQmts89ugLFGW7kU5bQtigy3i6iprgAaf695WUFWn+/b/5XIjHk/o6kilRu6pK1lGsXvhNtzH4TnIucPYFomoZSqYRWq8XIwkKMLCzEkCFD0L9/f+Tk5CArKwsZGRlIT0+HTqeDTqdDWlqaUDQajVDUajVUKlXUwjBMyOvwolQqI+pYRaFQQKFQxGwLfy1uk1pUKhUyMzNl2ykUCmExJy4KhYJjfPV4QtqSgkIRv3Q3ujOgJVoB58XaDGCVVJsB30C6cFcGvxqtbvLnla+lNEf96cOkZN6ubgl+3bdvLxlWtiOUkC1G3ys/Pk9uLltHVn58vi/49Vtmb7S6ycObj0UEyPaEdOFkfke6Il3Y2NqalK3dbie1ly7JJtlqam4mtZcuSda/VFdH9FKCXy9dihv8yhO7tRiNksfuwzcPl8tF2tvbQ9ogN/h15BDiev+FuCVenwCGAPg/cPFcZwE8Jmf8aKUneEy+B+BeAD+iKOpksPwinkFXe0wKTq1CaT9fl6XL2upO4TfmzSmRwOUdX4HRMCDv+ArZ9mmmC3icqUCa6YKk8UefW4M8WKByt0n2mOQ6qvvShb9l9vmUBQtv7i94xYR04Z5BsCb7dyRVUEg+zZYQIjzOkAM6RppoPHRFkC8f69AlffWhy6DRaNCvX4oOS4pK1WPiB/A3Qsg4ANcD+B+KosalNKdUVzZXonS1x6RNf4Lc89KhLqOkP9dkIbfPeynldOEJ83cn7TH5WQ/1mBitbtKmP0FmvHWCVB45QIxWN9GfPkyMVrcg42tCiHDM2/Jt0Wrx+xcuE9sLr8N0o8nCj+PJpNjH0onWd/j8E9nHvf7foMelJ3hMkimpekxajMaIu1WpsNls5FJdnaQUUDGam5tJvcEgWb+uvp7U1NZK0ovnMTG2tpJqvZ60STxflmWJ2WIhNXo90VdXE0N9PWm5fJm0tbYSU0cHMVssxGq1EqvVSmw2G7HabMRmsxGH00kcDgexOxzE7XYTq9VKvD4fsdlsxOfzEZvdTgKBALFarYRlWWK324nP5yMej4c4nU5CCBHaxHp+v5/YbDZCCAlpJ4R7L3jPldvtJk6XSzgPftxoduHHLMsSq6gvQghxud3EJeqvOwC5HpNRQ4lr54a4RU6fAN4HcLOcOYSXnuAxkY1+bBvnMdkzr/NOb8887i4uWp1AR7d/ITL5GJMk7MN1VO3nMVv1NpfSnOQc848swUhSj/wjS2TbD3DXYJb6LY4SX8L4Y8482+kxSdD3EN8llDFbMMR3Sfo1CsrcH83F6jffQ9Xmv+JM5WG0f/Ak/v7S22isKMPsTXvw9zc+Q93bT2D55u0wvDMTNWeOwPDOTKx+8z3Yds7Bsop9+FqvR2NFGWrOHAmpv9brsaxiH9wfzUV7TWWIrL2mEu6P5mJZxT60XTbA/dFcjmZdpNt22SDMkZehpSrkuO2yQRgjXCY+x1j2sXSwZ15E39gzT5hbe01lxHUMt0/5e5CC/VWZ9BUnWLsSEO8aK9uWcOmuyXgg5FpIGSP4h9JlYFkWfr9foN73BXcd9ng88Hg88Ho88Hq9QuGzefji9/ngDwS418Fsn0DwmGVZ+Hw+EEKEdl7GjxUIBEL0xHLxa7E+AGEsQRbcZZm/Rnx//DmKj4W+RHE9/uD8ezSkeUzyKIo6JioPRe+KGo4YGXFy0KPSha8UKAA+f9ekqHn8LNZ/rsfdV9DlaXX5wLIEVpcvsTIAOXukatWKkFoONEoaM24uQvr+fvgx8lHqycGkn0yAam82xv7iagBAxsdZKLuhGOn7M6HOT4dnUCZm3FCEjENKlP24GHnpangGZHAycR3c3VjzKQ0Nv+MxL9OpASUt2ENJ4883jILmkEg3XS3MkZeFH2vS1cIY0XQT2cfSAYC8sL4B0c7NOnXEdQy3TwSPn4U6sVofZIBP+U0GLCGd29jLRRLcJwnnkyhIlojSXCVAoVAgt18/5Kb4mEEX3L2Y381YreY+xfzji+zsbEE3LS0too3X44NkAYBhmJDHHzk5OZ3jhWXM5Ij6UigUIXZKpTLkmKIo9BP1BXAcL1LAX/8rxsCbmMekjSTIyglmxG0D8DghxJrSdLp6pdwd6Op04ZozR3DHdjPe+O/rO9N7ZdiLddprKvGXTz1YMJXm0nxl2ovndPs2E7bdniM7Xfg8exXK1m9B+SO/k5SuLCdd+JXzaryz+xPcOe1mPFjsiarzy7dbMdhTi6rAVchzVWPmvdMxakAGbHWn0KIpxL6Dn2PdOQ0mKA1wZRdhHNMIR1YR1EoFxlANMKYVYpj/EpzZY5DrqIanXzFy7NUwpXMZqYN9tUK6sDWjCAXeWjSpRiAzjYmZLpxuuQjlIC6lODxNmK8BRLTxacJppgvQXDUBJoc3IoVYnErMp/CGpw2LU4qlpgtHSxvmdcJTiflUXt4uPKX41e07cf9tt0TYh6cCx5LRrVUxU4p7UrqwHEyePJmcOHEiafuWlhZoNBpkZWXJtrVarbDZ7RhcIC88p7m5GSwhku3q6+vBEpIwvThRunBrWxusViv69esX8mcNAPqamgh9nVYLB8/FcYVBAQL5mJhwjf/vE3OB8Asw8aKREBLCOxI1XVi00AzXD5kL34doDN4TAwBMMHU8nHhNDH7edJBIju+LsCwomkbBoEHy0oXHjCAH1z4dVyftJ3+I22cwI24HgI8JISukjh0LvdJjIgS/Hl0B3PIc17h3CXDT7Oh1Ah0u+PX3ncGvMu3FOrpDyzHA9UsUnNoB5D8l2148p+9n/QIFpzYBw1fJsncXPoI/slvhbhgP1KxPOD4X/HpbMPh1Wdy+B+f+ATOYCsA3Cti7KULn4Ct/hdd2K25lKlDrm46HmAo8+komigfq8AfzC1juvh0zmAoUYTr+RFVgZdt0TGMqMLf5fgDAr5hXsdM3Hd9nKrDSNx0zRPUSH6ezgHkVG4NtfL1cJAu34+u/B3WeYV7FKt90PM5UYLVvOh5jKjAvKHuaeVVoW+2fjr+qtmGF53Y8zlRgMf0A3F6Chap/YIX3dk4WrJ/y/he0ahpzsBEvYjoeCWzFBsWd+BO2CsdLFQ8CAOZgI9biDvwJW4V6ER6IKvsfVOD97PvwG/NmLAQ3x6fwqtD2Iqbjf1CB1/o9ioYOJ2bhFazHnfibajtWeG/DI9gq6C7Zmo6GDidmYyPez74Pt5o3471gvTloL5ZVZPwHpttex85+/4k7Ha9jrvc/UZCThvs61gh272Xfh0HZqvgkGf/GSNZjEggyf8qFbAuKkvS8PtF5UGF1bwIR1VSUay4sJNC5gEEw1oFnbBWzqvILA/FNffh1EcaKwo8S3h8AKGgaBJ27Tgvp2WGLKH4Ro1QqQQWDUgkAsCynk+RniqTg4ae4D89GAOe6YlEC9HlMBIK1v3zqwaq7S1MmWOO9L1tvy07ZY3LbdhO235acx2TWhi1Y+rA0j8nJowfx221mvPngdzoJ2ZL0mKx+4z2sPM2gVG1AW9qoPo9JD/CYJPKKNJ4/hsHF14TIGs8fw+ozDB4b78Pg4muiekx4u2+rx8TY2gptWppkd70YZrMZLrcbgwYOlGXX1NwMmqYxcMAASfqGhgYAwJAELLf1BgN8Pl9Mj0lbezssFgvy8vIE+nkevMckEYlbH+TD6/VCqVQKj3gIIfB4PFCr1SGLyUAgAIfDgYyMDNA0LctjMnlMITm4YVFcHe0P74nZJ0VR3wewH8BpAPwzwScJIbukziEcfcGvXRz8WnC8HDdmt6HgeHlKgYXZXyzCKNaQVPCrqv18cK+e85LGH1q5DPmwgHElDn4d7KtFGbMFg321UXV+2rweRTBgccZ72P9fBXi36FNMHchy5F2nlmNqhhFlyrdwacYIfDj2U+y5dyCez/sAG6ePwNpbh+IxvIFF31PiId9reHxiAPc6/4kHiz243fwKHpySgQenZGBaywaOYC1Y31D/Ake8VqjADfUvcARrwXrSxVXC8dSBLKYOZLnXGUZMuriqsw7KQtoyjMKcJ11cheIMN6YOZIW2kDpIvlZ4ajlHunZxFUd0Jj7mSdSCbSF1HFm+Ux+hI7TxOkESO74t99DiCHuxDt9Gt1aB/r+nQTmMIbJJF1fh2RsZTLq4iiPKO7S4k4RNZEe3VmGwzt8VOzl0O1K+KQt358sBRSVFhiU3RTnikUPM6STQkRlj0oeugdVmg8vtFo4pioJGo4l4v/gA32RBKCpuiWtLyAFCCEUIuZoQMilYkl6UAL30UY5GqUBuWEBgKujKLxsFQKmgUuqz3eFBXbsTT90yFhkXP5Ztb3X5ZI4vXTtdzcAbrKOBd0WyvdAT921Ebljwb7gsoV0Xfg+7Gz1hEz+5YAmBUsaY/EZ4qaLv+3xlkNuvn6TPmFKpDAnilQWKAuietVfOFecSSKYMHFrY5Twm//nq4S7hMeE5UWLxT0iZ47kmC5k+7+WkeFDa9CfI9LUHyYzVb0i+RpVHDpARZTtCeU9izO3lvdXk5rJ15OW91VF1Nrz9PhlWtoNsePv9pM8/aZ0++z4eExmltLSUJAuWZcnllpakOSra2ttJa1ubbLvGpibS3tEhWb+uvp40NTUl1Kuvryf6mpqYcp7HxGq1Rsiq9fq4HCh96F5AJo9J6ZhC4jhQEbfI7TPV0isf5eQE2rqU+TX36Ao8+YNc5HcB86vu0HIM9tZCd2h5UvbYuwT5Lj1mqLZxPCgy7Zn95WBbzmKO7j0uXkaC/ZCvViOPf5STYG5j6AbMYCowhm6IqvODpo0oggE/aNqY9PknpdNnf8Xsewjza7eCEALCsskzv7KsrP1neLBJ2NFSHhklSF3mJUnvxdKHHoz4j3FSCYxNGt25CuqqMn5cMbc07POYRNhHMMZ2scfkrS/ryM1l68hbX9ZF1dm8fQcZVraDbN6+I+nzT1qnz77PYyLnTjEFj4nf7yctRqPACioXRqORmMxm2XYNDQ3EYrFI1q83GEirhP186uvr4+7B0xr0mDgcjghZn8ekZwFyPSbFI4nt0Ptxi9w+Uy290mMSsDRxbJhddDeuO7QcGk97l+wu3FUek7+ptyflMck7vgIjST23x47E8Qur1uAqtVXSXkEF3lrMYCpQ4K2NqnO94WUUwYDrDS/3eUy+Jfa91WOSSowJISSl+A0C+d4HNsg0yzDR47uijkOIpDkSIo1mkZJ4vvqaGuhrauAWBW72oaeC4uJM4pXunhG3wOpdGDRsJPnqTFWXpgv/7+c+LJs+MeV0YT71+Pkfq5FbWCrbHi1VaNWOxPLN2/HEfbfJPscIYjYJ4588ehC3bzfj9QcSpwsfsvXHvFcq8PSD0yN1Abz27k7MPQws+A5w729vEWR3rj8I66XTOI8heO/2bNy6zYwiGNChHYEpac0wZYxGXroagzw1cOcUY5j/Elq1IzHUdwntulEY4rskpAvn2KvhzxsrpAtn2i4C/UtgdflQ4K0NSRfm04T5FGGz0yekEA/y1CRMF+bThN0Np+HKGYMcnUpI/Q2v+VRiPoWXTyUWH4tTiqWmC8dKCY6WShxOrBaePizWCU8pbrd7ImThdTSCteH5ugsOt7+4677h3YNU0oW9Xi9sNhv6SQxOFIMQAqPRiMzMTIGtVAp8Ph+Mra3Iz8+HSsLihBACQ0MDsrKyIlJ8w1FvMIACMGTIkKhynmBtyFVXCQyqPMLThRsaGuDxeiWcUe+GmLgNQa4RmqLABhetPP8ICTuOBkkLXEIEThY6SBTHDd05Dk3TGD5smLx04bGjyeebV8fVybzuFll9popemZUziOrg/rD3zAN+8yLXuGce8JOno9cJdHT7F2L5tFWcxyAJe7GOau8zGMHeDd3+dwDdgqTmSE99EndbN4JuLQYOLZZlX3C8HN/P+i0Kjr8E5Esbf+TpZ3GV+k5J5+8f+meUMVvgbx4LHH4hQucHDWtRhF/hBw0fAi0jgD3z8N/mP6DGYEU5swXlvt+h/YNlKMLvUMZsQbnzd7jTtwVl7Q+jBkA5swHlX/8OP2K2oMLH6bwWrJf4HgZ4nWDbxmBdJpKtDLbx9YJgPSOKznLf7/AEswWzg7IlzAahbbnvd5jJbMFq+h78hX0Ts/0PQ6OiMJ9dj9X0PXiMfVOo59OPwO0lWK5+CatwDx7Dm1jquRuz1W8JxzM9D0GrpvE01mMV7sHjeFOo5+ERAIgqW4V7MANbsLHfX9HQ4cTfsU5o25r9AO4wb8Tf8TBoikK58iWU++7Go3gDq/F7PIY38Dx+j1nMW5jlewiEAsqVL2FZ8NzKfXfjL3gTG/v9FU0mFxYrNwiy8PpJ/8MoyEnDgx0r8E72A7jTvBHv9vtvDM5W9zoOEyA1j4nP50uakp7fS0WO5wOAsOeKUqKnJRAIgBAisInGA0VRcWNXSHDOUs431UWJwMAa/DMXF/Ec+D9ifkEQFIbY8wsFmqaFtlhjignUqODOz/yfP8+yiqAM4gVGcDyK9y7wcxf1JxzzCxSWBQHgcDiQlpYGpVIpLGBiIiiP+rkLjpFwa4HoJy+Fkr5b0SsXJh5/AO0OD3K7oK92hweGZhu6YheyNrsHDUYH7v/lCGitAY1SAAAgAElEQVROpfpGJ/ej6QuwuGx2w5fJQiNrNGnjZWiU6AjW0RAIkJAaAHxhX5bSITlAkMU6W6NAulKB0oGZ6KdTob9RjVsGD8RQoxbTBxdgRJMO9w4bgtGGdMwYy/3/jT6XjhnjRqH4QgZmjOHq8msnwOb2YfzZLMwdPxZFZzrrZddMwKBju7D++5NhcflQejIHc8eORcm5HCwtnYChlR9h7dTJAIDCQ51tfL3yu6XI/mI31k6djCwtg9xP3xba+Hrjj6+DxenDmKM5eO66Scg/shtLJ0zAyNMfC8drr+XsB37+ttDG1y/feC0ARJUJ9S8mweTwYuDnnWOU3FQC1d5swX7ogXewbMpE5B/ZhWev4+rl103E4OMfYf33rxF0yqdcjcHHdwu6fN9DD2QLsvB6yeSrMTxfB/WubIwLjjv4ulHYubgXul1ThEKhgDrMcyAVAb8ftEIh+1GO3++HQqGQ/PiIZVlQFAWlhIUJED9Iln+EI2chRlEUCkeMkKz/bUQqewm5XC54vF5ki7ZESGZhQgCQvnThnhX8arS6yZz1b3GBr0nYi2uj1U2eeOHNlLekP9dk6ZxTEsG309celBV8ywfMhgTbxgl+/VnZuuiBsoSQXZ98QoaV7SC7PvlEkN3/jy/JsLId5KkNWySdf9I6ffbfmH2b/gR5ePOxqJ9trVpxnvSA3wW5ZfLkySRZ2O12YrXZkrJ1OBykw2SSbWcymSQFsvKw2+2koaGBsCybUPdSXR0xGo0x5ZcvX44Z4Boe/FpbW0uq9fq4wbR9SB1er5c4nM6IdsgMVJ00djQxH/8kbpHbZ6qlZ/lvJCJgae6y4Nd8px4zNe9yqcIpBgZSDiPutL/emcqcRGChe89CvP7Bbm5OEtN9xTrM/nKMYOtkBd/mHV+BfsQMhbM1bt/Wj57B27s/xtyM91BEG6LqFF94EUUwoPjCi4IsM2BCHiz4jfm1vuDXXmqfe3QFFt7cP2pK/WAd6X+lfxO6Gz6/X9Ijkmjw+nxJBc0GAoGI+I548Pl8wiOJRKAoCoo458P930kD711JJh26D9LBMAy0MmKUYoMCoZVxS7ejO1dBXVW62mMy/+V3usxjEuGpSMLjkWy6Me+xkWuvP32YTJr/UUKPSeWRA6Rw1g6yb9/emDr79u0lw8pCdf742lEyrGwHeeaVtxOef0/1GPTZx9bprenCU6ZMIcnCbrcTr9cr284fCJC2tjbZacZ+v59cbmmRNWZra2tcLwiPQCBALtXVRSVP49Hc3ByTgK1aryd6kcek3mAg1Xo9qTcYJM+1D6Hw+/2SPF3RALkek3FFpOPk3rhFbp+plm+9x4RurUJZWuoek7bLBiyr2BfqqUjibjYZj4fYYzPd9hoWTKWRe1R6unDW4Wdx/QA2YbpwYdUajFc1YGLNupg6w888jyIYMPzM84Isj7IgDxb82tTnMelJ9u49C6PKhO+WxDF6a7pwUoGCANxuN/x+v+zgVYCLHGMYRrbHxO3xQKlUSo4XIYTAHwhAI+GO2ufzAQA0mthRaQTxM0fEacTcfyOS2um2DxxMJhOcTmdIm8PpjGjrChBQILQibul2dOcqqKvKxPFjuaVhind6/HNzwbsg0z7c85IqQRvvvYnquZBgHzU2JYH9uSYLufPpl7mYkQTnz3tMKo8ciKkTzWMy460TZFjZDrL0nxUh+kv/WUG++LqV6E8fFq5fm/5E1Jq/xoSQyDaRLKJN9F7zEHuTxDpR9RPYh8vC+5SjE9cu7H2Uah/rcxDiKRTJIr4TfR6TCHi9XmKz25OybW1rI/YoJGXxwLIssdpssuzcbje53NIiyTNjtliIIUEsSkNjI7kUI2YkPJ7EEPSYNDQ2EkIIaW5qIjV6PWk1GonZZCI2q5XY7XZit9uJ0+XqLE4n8Xi9xOPxEJfLRbw+H/F6vcTldhO/30+cLhcJBAIhNcuyxO12k0AgQPx+P/F4PIQQQlxBWSAQELYNEMvFr8U6vG0gEBD03EE9QgjxeDzE5/eHXGdel5f7RXLxOOL+E3lDonlMHA4HcUaJKQkHZHo3Jo4bQ9pOH4xb5PaZalHMnz+/+1dDKeLl5U/Nf/h3v+bSVAtvArwOYPcTwIDxXFt4HUOH/uxp3PD9G5F7aHH8fhKM4f5oLhaezcf3h6VB++ls2fa8jsthxY9qn8XA0dfItm/rPxVrPjqFOfQ/kDOiVLI9NXA8SqpWovA7t0ALT9zz1/3fkzjo6I8HPJuhLrg6qk7anln43DIAD3k3QTd0ErBnHs5pSlHdaMRc+p/ILZwM7JmHn77ZgTstG7HwmAIl51bgj19ose3LCxh/ajHmHSYoPPksFh6jMPzkcpRXKjDm9HOYeSIbjS2t0H46G8tOKDDh3EosPkZj7NkVmHUiB7TPgbTPZmPJCQVKqlZgyQkFJp5biYPW/vB9PA9HyHicr2sG2TUTegyD8rOnseykEqUXVuJLMgGrd1fi+vNLccI9GI5dT0GPYcg4sBDHnAVw7n4KVepS1DYa4fnwb6jGMPT7cjGO2AcJsoDbjsCO/8WzJ5WY8vVqXGCHQndgIc75h8D84ZOCDrV7JpZVKjDl69VoVo+Ecu/TOK2chBU7K/Hdi+VCG2/XohkJ3YGFqM+8Fh0mE1SfzMKS43SIfX3mtVj83jHBPm3/AtQrR0C592nYs8Yg8Mk81GdeC+J1ILDrCZjSR+MnTetgSh+NtP0LUJtxDYjXAfUnszCy5DoUHC9HvXKE0I9YJ7DrCdizxoD+7GnUK0fgwy2vah6dOW9pN/8MpIwNGzbMf/jhh2XZsCwLQgjS4ngX4kGpVEKtUsnKbrHb7fD5fAm5SHgQQuBwOKBQKqHVaiX1r6Bp6HS6mDpWqxVKpRIZGRkRMpPJBIZhhPnZ7Xb4/X5o1Gq0GI1CarXH44HT5YLD4YDdbofdbofNZoNNVFutVlitVthsNlgsFliCr80WC2w2myALr3kdu90Ou8MBa7CN79vhdAptTqcTVqsVdrsdLpeL68Nuh9vtFmydLhcnC9p4vF44HA5YrFY4HQ64g+ditljgdLm4Y6cTFtGxy+WCzWaD3W6H1+eDM+jxsFgs8Hg8cHs8cLvd3FhOJ1wuF1xuN1y8vdsNd3AeLpcLfr8f/kBA6Nvt8cDtcsHtdsPj9XL6bjfKy8ub58+f/5KkDwuA9WtfnH/vnbeBUHTMsnztK7L6TBW9Ml3Y7Us9Xbjd4UHjZRsGpziXdocHuUoaZT8uRl6UHVqlwONnYbN7UL77PBam8HCtbFoxMj6V95ZanD4oZLiVlQme/rl9LGiEci1oGe61guZ+jD89b4ywc3kBgIWXYWF2++FlWLS6vfAwLJpMbjQxLuh9TuhbnZjABGBwuFHLOFDtc6CWceC8z46Fu86jnLHjgs+G6mB9nrFhZUM1yhgfFu46DwAoZ3xYtvMcZjI2nPFZcYaxYnbdaRAAZxgrltWdw0xBx4xltecwS+XD7O2nAQpYpvJh6a5zmKUyYenXQdm7p4McJ1ZcoK04TVmwpPY0ZqtNWFV/Fo8RTofjMbHgIqw4DQtWVZzE4zBhXv1JEJCQtlX1Z/E4/Fi18yyn89rRIFeJFdU+m6A7AyZs3FmF+g4HTsOC5ytOYRZjRnntKfwFJmz94CzuMJsw//VjGJKjxQMdJqyuP4VZjBXLKr7CTMaMJ18/joKctKCsCrMYM5bVfhU8/3AdM97bcQ6/t1uwtPYrQKmJ/Y/Wg8HdXMqDw+mEz+tFP5lpnna7Hf5AICS1MxFYloXb7UZ6erqsx05OpxM+vx95uYl/IQOBAHw+X8J5EULikrqJv+/8Y514wbSdyvICZPnrECA8LUEgpF3cxtfhr3k+GKDzMVa89mjHbo8nROZyuQTeEwrcIkz8+fJ5vRB/2vyBQAgxGiA9FTvikRohSXPqcAPjirC7xkOvZH6dNGEcOXm6invOnQLza3tNpXR21hj2cw6yWPQ9mutHpj1aOJbXtW9/gD/d9WsAkM0826odCbq1CnMOslhw63hZ9jVnjmBZpQIzSwMcS2yC+decOYKy/X6s/1la6HUL1oeq27DgHxW47ac348FijyBbdUqBVZ9VC2ywt/59PU56h6AIBtTRQ/Cd9MuwZRVBp1ZiDGWAKX00hvnrYM8ajXynHs7sMch1VMPTjyMXHeyrRSMzAoN9tQLzqzWjCJlpDGA8C/QvCWF+tWcVCWyvAATGV54NNhHzqytnDAa4a9Ci4ez51+G1mBX2m2B+jcfuGs4KG87qyrPD8sytYp1wVtdosmjMr3RrFVrTRmLKiH69kvn1mmuuIceOHZNlI/dPhIfP5wPLslCrpd+8uN1uOJxOyVwXLMvCarUiPT0dACTFo5hMJrAsG5fB1uv1oqm5Gf3z8yM8MIFAAJfq6pCdnS3M83JLCxwOB/rl5KDDZALQyQrbh28eFEXJYmmdOH4c+dfW1+LqDBx3Tbcyv/bK4Fels6VLggYlB4jGsV/0vWCgaZKBiflOvRB8K3d3Y/eehVj79gfQHVoeM5Uzln3NmSMw736GW5ScXZNw/m2XDWjbMT8yMFekw7ja8ChdgWu0l0PPMRj8+v2mV4CWKjxKb0cRDCjTbMeFx0Zg88i9ePcPY/D63SMxN/1DrLhJjceU2zDnWgoPka14fGIA93rfwoNTMvDglAxMa9+EB4s9mNa+CXcNt3N1iQbTChWY1r4J0waYcEPTKyH1pJr1nLxQgUk16zE1w4gbml7B1AwjdzyQxdSBrCALrwvPrhF0Cs+u6WwTyYoz3JhUsx7FdEOITDgO6ojbhDrDHVsWppN7dEWELJ+yhNiLdfKdesE+n7JE6OQeXRFfFkUn36kXZN+mdGExA6kcMAwja1ECcMGocgi4xAypiRYlfr8fHR0d0Gg0yMrKintONpsNGo0mKn2+N8jyKk5b5RdvUgN1+3DlEe8xDrkSrLDdGdDSVWXK1SVclI/MwNJkA2SljnEl7OORsMWS8QGOUncg5gNT56x/K25K8Rdft5LfztsQofPWl3UhpGv3LHiZDCvbQe5Z8LKk8SXr9Nl3m734s/XvHPwaCARkpeharVbidrsl6zudTtlka2azOSRYU8oY4UGwgUCAWG22hEGYJrOZtLW1xTyntrY2UlNbG9JPU1MTqdbridvt7tt5uJtgs9mE9wgyA1WvLhlHGs+filvk9plq6ZUeE2JrTiqVNyQ9UoJXob2mEnXb5qLtsiEpr0x32MciYeO9Ke49CyNkvKen8OyaiPHDr5F7z0Isq9gHymHEU+nvo5huiHmNN+85ipnq9zp3RQ5LFy6tWQ+0VOFPVAWKYMCfqIpenW77bbUP+Wz14nRh7jc8PhxOJ2w2m+Q+KZqW9bw+GU+KkmFk0dm7PZ6IGAmappGRnh7iKSGEoL2jI0RXqVQiMzMz6hy9Xi88Hg/SdbqoHpdk0qn7kBwIkouZEuwpKm7pdnTnKqiryqBhhbLp2v9dPSbx7JO5RhEppJdDU3Gjzi2o85+vHo70wlw+S774upUML+tMM5754htkWNkOMvPFNxKef0/1GHzb7f8dPCalpaUkEViWTZroqreBZVlis9lC0l+j6RhbW4nL5SJut5uYLZaI61NXXy94Sfo8Jt0PyPRuTBhfQuovno1b5PaZaukRHhOKon5OUdQFiqKqKYqalUg/ZHdh/k5vzzzuzi5abTdy8RcJdKL1k3toseQxepq91Gvk/miucI3KmLc67YIygXxOZNdeUwnDOzM5Mq4985BPWbB82iAUnloe0TfjakN/yoKhlcuAlircZ9+EIhhwn31TwvOXco367LvfXvwZuSqT7oo9MFOG3N8RKSRnycaU9FQQQiIyfPjsH4qikJ6eLlwXj8cjxJDwoCgKKoaBSqWCWq1GVmYmqOCutn6/H0ajEQzDICc7u9vOqQ+pg4CKWxJB7ncvEa74woSiKAWAFwFMAzAOwO8oihqXwKY7ptbr0GbvTGHz+CPTC6O1tTs8uHjZJthqlHRMWSRC3wdxurTHzwr2w/N1ePGeydCpuWA4FcONkabqYTta9qHXIpnfkX9neL1eEELgdrtDHkU5HA6YzOYQXbfHA0cURlF3lIUJy7Lwer0h6bcA0NbeDq/Ph4yMDAwcMAAKpTLCtg89FyyliFvi4Zv47iVMF6Yo6hMA/0sIOZXKQHH6nwpgPiHkZ8Hj2QBACFkSy+aaiePJsVNnuDu5FNKFZen0YPuaM0eQMWwiZlacwrM3MmDzxwkpyHz6cKvNE9HG2wtp01HGkCQLm6M4BZpurUJuYakw/l23/Ayvbt+J95szMcxvwEUMwXWaJlizRiEzTYUxtAGOLC49159bjHynHq3akRjquySkC+fYq2FKHxWSNoz+JbC6fCjw1qJJNQIF3tqQdOF0y0UoB5XA7PQJr9NMF9CsLhTSh4HY6cJppgvQXDUBJodXeO1uOB2SSsynAovThMXpw97cYpgc3pAU4mTShaOlBMdKJQ5PG+ZTivkU4mipxOEycd1u90SkEEtJF+6RvyNJpAv3Bly+fBk+vx8DBwwQPBk8eRrLsmBZtsszZnw+H5RKpXDTyGfymM1mWK1WTqmH3VCG3OASwnGBcIKoN78CT4lIFusmme+H75t/TVMUWEKENt6eoihQiB0rwssRNmcE54TgvCiaxuCCAlmpvRMmTCAfvPduXJ3CUaNj9pnMdy8RpHw6ywCsoijqEoAnCSHNyQ4WA4MBGETHDQC+E65EUdRDAB4CgKF5us6AvFue4xT2LgFumh29TlWnB9vXlDyKS9vmIvO21cgMmKA7tAmanzyFGcw2ZDpLBPt8CqFton5yj64A+kcfI6FMFznH/Jtmd44VtBfGp0tQpnkXJ/0/wgymAit90/FfgQrMbbkfbQD+i3kVK2um42amAivPTccMpgIVPq6e67sfALCAeRUbgm3vRJFtDLatDKvFOqt80/G4SDYvKHuaeRWrfdPxGFMRUj/OVGAx/QDcHoJnmFexjr4Dj7Bbsdo/HX9VbcNT3v+CVk3jSWzECs/t+Jt6G17EdDwS2IoNijvxJ2zFQtwPl4dgkfofWIs78CdsFepFeAAAMAcbI2TRdNbjTvxNtR0rvLfhYbyDRXgANEVhIfNPoU2s8wi24rV+j6K+w4E5eBXvZ9+HW82b8V72ffiNeTMWUw9gSI4W93WswXsimbje3O9RNJlceJr5B1Z6b8cM1Tas9N6OgmzNSAnf8573OzJ0aBdPoWdAvKMwIYT7IwyCIPoeQeF/uPEQTTfAsiF/JmwwVoBNcOPbXRAWAIBAdBYS+Atu0UCJZESkL36kx59/rGsmXtwQ0QKEEAKKpkGzLCB6jCjWDwRJ3sJJLymKClnIsCwrvM+EZTkZTUt46BIdbOKU4DyKosSr+JcIITwTrKTvnhxIJlijKOp2AH8HsB3AMkKIK5WBRf1OB/BzQsiDweN7AXyHEPLnWDZ9HpNIj0nh+OvQavMIHoae7DF5/YPd2GvKg9b8dZ/HpBs9Jt7cYizYUYUnJgUwuPgayR6TcBK3ZDwmou97z/kd+Tf1mAAcs6hSoYAnmJHDk645HA54PJ4Q5lqeKj0vLy+kD7PFAgVNh9DQsyyL1tZW5OTkQKVSCe2tra0CQ21aWhrsdjvS0tJQb+D+r/oI1qTB5XZDqVAkzGiy2e3wer1ReW7kEqxNmDCBvPveB3F1Ro8qjOcxkf3dSwgpEbLgFnXjATwCoA3ciujeroi+BTAVwMei49kAZsezmTIih8sIeH06IbYWrrw+vbMtvE5Vpxfau/55W4QspC1Yt+lPkFPlN5PW5vqIMRLJKpf8hMvMiTG+2P7oV+eE8S8+93Nyc9k6ol85rVdf495o39pcL8ve9c/byPyX3+Heuxg6Rbm0uVf+jiS5iV9vR3gWTSAQiNhojhBuQzpvlE0AzWZzyEZ1fJ8+n4+0traShsZG0trKbQral5XTNQi/3oFAIOYGjZCZQVMyfgK5UF0Xt8TrM5nvXqKS0H9DUdRBAI0AVoJz2fwngJsAXEdRVFds6nMUwGiKokZQFKUCcDeAuMs30kPcgz0Z4iDWeG25OjXGDMgQAlfFAbLhskiEOg7FQbIaJS3YX2p14H/ePAGnhwuYc/u52uH1ow/di3j7OUULctYoafz5R6OifnbkoCf+jkjZf4YQgoCMfWp6A8IfP9A0DZVKBUIIrFarENiqUqnAhMWiEEK4zeT8frjdbphMJuGRhlKpRF5eHthAABY+rqQPKcPv96O1tTUk4Jim6S6NE0oxK0f2dy/xhBLfiZQg+MgniuxcKqsiUT+/AHARgB7AnET6fTwm0uz7eEz67KXqGK1u8vDmYyHvqVR7rVpxnvTC35HJkyeTRLBaraStvT2hnlhfDvOr1+sldodDsj4hHMtnNA9HLLR3dBCHhDFYliUdHR0hd+LWOGN5vV5iaGggLUZjSHtjYyOp1uuJ3+/v85h0EWJ5R8LBsmxSHpNz1Ya4JVGfcr97iUrC2yBCyFlCYroobklmMRRljF2EkCJCyEhCyKJE+oNoc0zG028b82ss+3jMr3zf4fb5lIXbt8epD+lnWcU+tF02RFw/8V5DlMMIjacdlz+YF9G3s6MZubBgYOVKoKUKt7RzPCa3tG+Ke/5SrlGffdfY51MWLLy5f+j+URI/owVZqoQBBD3xd0RKsGd6erqsHYH5IEWp4Hf3lQOWZWV5jbVpaRHMrSzLwmK1hvRDURRycnJC7sQJy8Jms8HligwFYhgGaRoNnE5nSD88K63P3+cR7SpI9Y7I2YW6ExRYQsctiSD3uyelw15X+vbKkeYV6e69cnadaiI/n7WOfPF1a4js5b3VZFjZDlKx4yNCSN9eOf9u9lI8Jj2x/LvFmAQCAdJhMkXEI0SDz+8XPCmJ9gJqbWsjTU1NURlwXS4Xqdbrid1uF9qaL18m1Xo9MZvNfR6TKwDI9JiMG381OfN1U9wit89UyxUnWEsK9mbZd4oxd95N0E+inYMF70CS9rxXIhl7sVckmlclllcp9+gKzCwNwLz7GdScOSLpbppyGPFr0ya8un1ndM+T3YhROidmqLZhgLsmRMbvlXNd/UtASxXu97+NIhhwv//tHuMx6LNP3v7btLswISSCXEwKvF4v3G63LBu32422tjbJ+hRFCTwZicjNlAoF+uXkwOv1whrmOQlHVmYmvD4fnFG8JnxmTjSCNvHdu76mBvqaGtTW1qK5uRlGoxEdHR0wm82wWCyw2Wyw2Wyw2+1wOBxCppDL5YLL5YLb7RaKx+MRCr9fj9frjVl8Pl/U4vf7I47llkAgkLAOfy218Jwz4SWRTTJgQcct3Q3J6cI9CZMmjCMnT1dFpKnKTcWNle4qx37OQRaLvkfHTKlN1Lc4tRZARCqvFHu6tQpzDrJYcOt4WfY1Z45gWaUCM0sDKBx/XcL515w5grL9fqz/WVrodQvWh6rbsOAfFfjpjT/E4xMDgmzVKQVWfVaNBd8B7v3tLfj13PX4yjcEReAI1qZoGmBJH42MNAZFlAG2zCIMC9TBmjEaw/yXhHThdt0opKuVQrpwjr0a/ryxyLRdhDWjCADipgvbszidQZ4aIU04PF3Y33xWSCUWpwLzxwBC2vi0YT6VmJfJTRcWpxvHShcWE6QlksVKGwYQQbomJk+LRr7WFQRrPRGlkyeTyhMnZNnES9OMB4fDAX8ggKzMTMk2PMuqSqVCgGUjAlFjjuV0wuV0Ijc3N+HjqkAgAGNrK7IyM6HVamPq1dfXIy0tDfn5+REyfU0NNBoNBhdwezlebmmBw+FARno6bHY7RwQWDz2MeO2bgMBpEgRN04J3QKwj5fEiRVHCNWVJJ5cKX48YPlxWunDJhElky/Z/xdWZWDRAVp+pQjF//vzuGqvLsGbx7Pl33/pzaPctAApvArwOYPcTwIDx3P4d4XUUnfb00WisKINy0PjE/cSQafctwNTv/gC5hxajrf9UaOGRZY8986AbMhHX166Bb+gNWPbBcfxAvxzKQRNk2Wv3LcD1P7kNlM8B7aezJY+fc2gRxk2aCuuOOVCO+mHC+Sv/VYb3mrJxu+kVqAuujtAZkk4w9UI5Vp5W42fNa6EbOgnYMw9fYjyqG4143PcKcgsno/+RpTjPDkUZswXn2aGYQW3BDnsxrFYrHnFuwIeXc3GnZSPeMWTjV20v4Y1LmZhm3IAV+gIcq27Er5pX4aULWvykeR3WnNXgRsOLePpsf3xxvh4/uvQs1pzVYOqlNXj2FBNSP3kqF/93+hK+V70Mz55iMLl6tVD/77Ec7D6hxw8vPYtFxxSYXL0ai48pMOHCSiw6SqM0qPNRpR7XXViKhUdpTKlejYXHKUw8vwp/PZaJHcc42aJjNCZcWImFx4Grz6/C4hM0xlatwN+OZ+LDo3p85+JSLDpOYWzVCqH+29FsfHyyGqVVS7DoOIVxQdm4qhVYeBwoqVqF8gv98daBcyitWoKFx4FxVSux6DiFkqqVKL/QH28eqMLkqiVYcpxGSdUKLDhCoTjYz/iqlfjrkSzsPFGNa6qWYMERCmOrVmLdOTWGnliGpcG+J1ctFdrWhtVLL/THOwfPY3LVEiw8QnNzO0LDeeaTnEf/d84z3f5DkCJeefnl+Q899JAsG1VwN2Ap++yE2KlU0KjVcLvdoEUEaPHAZ7rYHQ64nE6kpaVJnqPP54PL5UpoQ9O04HHg2WGjwWqzIcCyyIyysDKZTKBpWlh02e12+Hw+KGgafqlxJjGYVvk5UgAUwYUZH2+hYhgQQqDRaEAIgUqlgoKmQSsU0KjVYAmBTqcDBc5DpA1eC0aphFarBQGgVqmQFlyQqRhG2CuIpmlkZmRArVKBZVmk63TQarVQKBRQ0DQyMzOhSUsDTVFQMgyyMjORlpYmvGdZmZnQabWgFQrQNI3s7GzotFpo1GoEWBYZ6enQpadDp9VCQdNQBHW0aWnQarVcSUsLLWmwqYkAACAASURBVOJ2rRZpwWNdsE4Lti9ZsqR5/vz5kjPdXly3fv5v7/pD3KycDWuWy+ozVXQtL3E3QcMokKtTJ1aMg1ydGukDMmBPcS65OjU8fhblu8+jbFox8hKbRECjpKFJV6NsWjGoj5OfS/nu8/g78SMjsaqALC0DEyvda+ZHfFdhtpZz7SqjbMtucnLu5R8X90f56UhbGoBSQSFLoYQKNHJVDDSsAgO1agxm0jCETYMCwFBGi+H+NAxVajGK1WGEQodiko4fjM5D5ikG904egswqBg9fPwKZJxnMuHEUii9koITNxG8nFmD82SyM8WZgvCoLM0aPQvYRBkt+NQEAkPkJg6d+OhZFZ7Iwzp+Jq9XZmDN2LLT7OZ2sNAaFh7JR4slEiTILK28ohW7/ToyncjB98lWYciYHc0aPhe4Ag/k/GY+hlTmYV1oCdg+D537JedXGHM3BvAlc27yflGDk6RysvXYydw12dLY9d90kZH+xC0W+TIxnsvDcryfB5PAi99NsFPkyMYHJxnPfnYT8I7vx1I3jsOKTi5hAZ2P5dydi8PGPsGzKRGR/sROjfRkoTsvE+hu5G56hB97BsikTkX9kF0puKoFqbzae+wXX98DPs4W2cWE1rzP0QDbKp1yNwcd3o3zK1Zj2gtsh+QPUy0FRFAKBAFwul0BaJgdOpxMsIcKfpBSk63Swg/vDlzpmWloa2tvb4fP5EpJ1MQwjPM6JtWBSKBTwxwnSZUWPt3gvQCAQwMjCQng8HnR0dAib//F/1rzXAAjdUJF/zbIsaIWCo4snBEqlUqC+9/v9UKlUgkeJb+cfZdA0DZ/PJ3ibSJCG3+/3C2P7fD4ognPx+/2gggsElmVDPFRerxcMwwheD7/fL1zTQCAgzC3acUbw0Yv4PdDpdEJ/ABdgHa7TrSAAIT3Ma9WdAS1dVSaOH8tF+aQYtMcHgUoKUE0wBh8gmkpgIZ+uGzXAVIL9uSYLmbP+rejziGF3rslC7nz6ZbLrVFPC8688coAUzupM+42ms2/fXjKsbAfZt29vyBgjynaQm8vWkYUfnhH09+3bS976so7oTx8m55os5FyThbTpTxCj1R1Rh1/jqDXpDBYOr8U64YHB4vc/Qj9GEHKilOrwtNton7GI1NxobTGCmKO9x7E+f5LTxuPJ4gW/MjhDesDvgtwyadIkkgzcbjexWK1J2QYCAWI2m0kgEJBl53Q6SXt7e9QA1GhgWZY0X75MzBZLQl23203q6uvjpjk3NjWRmtraqLJqvZ7oa2o6dYPpwrWXLkmaax+6FpAZqDq2ZBI5er4jbpHbZ6qlVwa/ek1NCYNOpQa2LvoeDd2h5SkHBlIOY+yUZBkBujOYbXj9g92h/Ui0z6Ms+LVpE2x1pySPX0w3YPXAj7DyvQP4Wq+Pe/6FVWswXtWAwqo1MXWGn3keRTBg+JnnO8fIcOPnIyjMYCrAtpwV7G5oegV3Dbej8OwaFGe4UZzhRu7RFch36iNqPgiXD2IW2kQy2I1Cumt4LdYJCQwOCzAO0Y+hEy4L7zt83FhBzCE6UcaPF8QcPn68AG9JqfWpBL9m0AVX+jchGSiiePWkQK1Wg6aopHfPDbCs7D1kVCoVfMFgTSmgKAqKICV9IjAMA5Zl4+qKvRvREE2WbCBmH7oXBCkTrH0Dk+oBdy5yy/hxxdzSsAvSJENIxZKwF9f8HX6y9oRwd8z3vHQo6t20lPGfeOFN2fZt+hPkN2v2J/T4VB45QEbO3kF2ffJJTJ1dn3xChpVF6vzxtaPk5rJ15I+vHe1x6a599vI/o+K23uoxKS0tJcnCYrHIIlITw2QyEbPZLNuurb1dlp3ZYiFNTU2SdOvq60lbW1tM+eWWlphpv+EpwQ1Bj0lfmnD3wOf3E5vNJhxDpnejuGQSOXTOHLfI7TPV0is9JgFLc5d4TPi7yRnMtog73mTuJimHEbVbn4pKXiZ1jrpDyzGCrQOzvzwpj8tT6e9jsLeW8wJJtGf2l8PW1gizsSHu3Iovvoif5rVDeaC8M804TGf81+tQBAPGf70uRJbh78AMpgKDPDUpXeOemC77bbJvu2xA3ba5IZ/x3uoxkbqbbjTQCgU8SXpMVMEASLlQKhTwyiBjYxiG885IHCvenPgr1ecF6XlIhqQvHIRQcUu3oztXQV1Vutpj8peXP+I2N0vCXlzzHgs5MR7RdKLGiki0b9OfINPXHpTlMdGfPkwmzN8dlzyNf73rVBP5WVkkiRqPih0fhZCp8bI71h0gN5etI3esO3DF7/j77Ps8JoSk5jFxuVzEmmScicfjIUajUXK8CA+bzUaamptljXOprk4SfX1dfT1pbGyMKTe2tpJqvT4qGVu4d6SxqanPY3IFAZnejTElpeTAWVvcIrfPVEuvTBd+ccmTKacL87Xrqu9j38VW3FK7KDJNV4K9WMflsGLYkfmgBpQg59Ai2fa8DjVwPAqOLUXOiFLZ5xjY+QTeb8rBbeKU3gT2yr1P413LSNw6Lge5+56KOzdH9hiUVq9G5rBJGHh0aYSOZs9sHLIPwn97NyNnRKkg+1elHo+4NuDTjv64teMlbPpaC+uOOfjjvzwYUlmOGUcy8FFlNYYeno+151QYcHgp/lGtxYDDS7HNkInMg4uwrb0Q5+uakf7Zk/jSPgCqz5/Bp215yDq4CJ+5i3G+rhn99s3BPkt/ZB1cKNQn3IOR9vkz+JJMQG2jEdmfz8ExZwEyDiwU6rOqUpyra0b253NwgR0K1d5nIuqG7OtQ22iEZs8sXGCHQndgIc75h0B3YCFOKyehydiGjL1PopEpBNkzD83qkUKt3Ps0TisnwWG3QPXJLDQyhVDufVqwr8+8Fh0mU4gsvA7XSdu/APXKEREye9YYBD6ZJ9jxx/WZ14J4HQjseiLC3jboe2hsaYPusyeFNt6Or3mdvANzUa8cIdh/uOVVzaMz5y3tth+ALsJLL700/+GHH07K1hMk9orH/REPDocDarVaVpwLSwhcLheXAisx3dhms0GlUglEaLHAb7oXLR0YAFxOJzweD7KysiLmbDKZAAD9cnIAcOfG38GbTKYuLWazGSazGWaLBWazmSNoCx5brFZYgu38a6vVCqvNxtVBIjfhOCiz2e2wWq2w2e0cyVuQ6M1ut3NtweJwOoV2u8MhvObbHQ4HV4LkcPYgUVx4uyNY+NdOlyuEVI4nluP5aJxBkjmXywVnsLhcrlASOrdbIKJbVl4uK7X3hbUb5v/6jvvB+cWil3+sXdyXLpwIamXq6cI88tLVmPvLcSml6Yr7UvdPR/nBWszVsEhthsm5z1QKGgOzNVAppD+l8/kJXB4CizOxO9Dm9ofU4VDSVEjNo9Jgxd3BbLgjtR2o8DWhjAFYAH6WwGDywGDywMT4cNhixk2MG592tOIaxokKYxNGMk68dOASAGAg48DKPdUoY+zY0FiLbMaGhbvOAwDKGStW1lWjTFSX151DGWNFWd3poI4Z5TXnUBasZzFmlNWcAAGwjDFjWc1pzIxSz998BG4PwVLGjGW1pzFLZcLSr7l65sUTAAUsV5uwsr4SfwmYsXprJR5jzVhTcRKPw4Qnvj4BrZrG0zBhVT3XtuTr05itNmHea0cBIEQWXot1nq8/hVmMGeW1p/CoSPYMTNj6wVncYTZhZf1JzBAdz3/9GIbkaPFAhwmrRfZ/gQkbtpyA0erBYmVnG2dnFuqN75xEk8mFxUozltV+xV2b2q8ApSY2AUYPBndzmRwYpRKuYB9yHwnxPCbitFMpUCoUIIQIqbKJIKS3SmCqpYKMsYkgJa1Vq9VGZYLtCvDvWSrvXSoQE6UJRGfBtmifA75NLOdfi/UJywpcLrxMfI4CiRogvE/hcwm3kQpCgEAPSxfulcyvg4aNJF+dqepkOQViM5bGYT7l61abB6vffA+P3XOrbObVcJ32mkr85VMPnv+xWjqrbJhOq3Yklm/ejifuu032OdacOYLbt5mw7fYcjs1Vwvg1Z47gV1vbse2R76GYbog7t90tOVj55vuYcc9vMG2AKULntXd3Yu5hCCyvYtlPZ63HRQzBZ/+Rjy2XdPjii/04xw7BRLUBJt1o5OhUKKIMaNOORBHVgBZNIYopA1q1I5Hv1MOZPQbpaiXUHeehKpgAZds5mNJHYbCvNirzazQGWCA286vZ6RNe80yv4ppndw1nheVrABGMr2Lm12jsrmKWWABxmV/DdcLZXXkZz9QqZoXlj3PT1cJr3t7dcBqrzzB46IZCFNGGEFbYxvPHMLj4mn9L5tcpU6aQ48ePJ2Xr9/thMpmQm5srm2wNAIytrUjTaJCRIZ11iBCCpuZmgaxLCgwGA3Q6HfolYKptaGiAPxDA8GHDoso7OjpgMptRMGhQBGmbvqYGADCysHMvR6vVGtP70gfpsNntYAMBZIk2kkzEPkxRlCyW1jElk8mGtw/G1fnhBG23Mr/2yuDXnEAb6NauC/rj94ER+kwhsFB3aLns4NNwHbq1CrdZX0vqHPOOr8BwUoe845GpqLHssw4/C53XBHtbU8K5pVsuYgZTgXTLxag61xteRhEMuN7wcoTsX6UHcWnGCBSeXYM511LYOfEgamaMwLvjDmLvnybg3T+MQXnubmycloEyzXtYcZMaD5GtmHMthYfIVjz+3Rw8OCUD93rfwl3D7bjd/joeLPZgWvsm3FWiwV0lGiEFWVxPG2Di6kIFphUqMKlmPaYNMIXUUweygmxqhjFqXZzhxtSBrNBWeHZNZz2QxdSBLJf6TDdw+qKa1ynOcAs6Yns+XVosi6jDdHKProgqy3fqQ+yE4ww38ilLhP2kmvVYPm0Qpg5kQ/qkW6vABj+PhWfXIJ+yCCndYvveuldOKjdlFE2DJUR22q9gD8jec4eiKBCWlc6mCi4VVErAKht8th9ncADS59y3KOkaZKSnhyxKAI5wT86O14lBIUDil25Hdwa0dFXpyuBXQhIErSYRGJhsui//+lyThUyf93JoMKpEez6QVerOwbzNuL/vkhz8enPZOo6QLYrO5u07yLCyHWTz9h1Jn3/SOn32XW4v5XP8bQx+ZVmWXL58OemU4ba2NtLe3i7brrGpiZhkpAzXGwyk+fLlhHoGg4HUxiBQI4RLca7W64klCmFbX6BrzwJkBqqOHjeZfHLKHbfI7TPV0is9JgFLI5euuGde5938nnncHXq0Op5O0GNyj+1VzkMh1z5MR7d/Iecx2b8wKXvsmYd8lx4zmS3Id+ll2+cfWYIiNCB9/wLJ42d/sQg6T9BjkmBu6ZaLKGO2cB6TKDrX177AeUxqX0j6/JN9H/vsu94+99DihDpXZdJXXenfhCuFZD0mdDBeJKkxZXpaJKX4Jogx4ftINS21Dz0TLKHilu5Gr1yYdDXy0tUY2T+9SwJqqbA6GVicPrh9LAzt8gPIMtRKPPaj0TjfYkdNq9SdgKTP1mh1h9Qxu+pZsVR96EOXgg9GlLtIECMZLhMQAp+MRzlAMLBSUtexFybJxNH0oZeAAGyC0v1z6gEuVbll4NDCpDg+4j3KibnHzBV4lEMIx7Ia0o8M+3NNFnLrvA2SHwVVHjlARpTtiM5NEmb/1pd15OaydeStL+ui6iz9ZwUZVraDLP1nRUrn31MeZfTZJ9bprY9ykt0rR7gMLS3EbrcnZWsym8llCY9YwtHU3CzLrt5gIIaGBkl68R7HWCwWUq3Xk9Yo7LB9j3J6FiDzscuosZPJzuPeuEVun6mWXrkMHkibpO3/cYWCXwe4alIKfkVLFQqr1sDTeJpjgJVpr2o/jz9hK1Tt5yWNP+Sr1ciFBYyrLWHfmTYu+DXTFj349Zb2TSiCAbe0b0rp/Hsq82mffaTOt5H5lUdSXg8AINLSeMNBQX7QbleytcoN2O1D7wALKm7pbvSlCwfThSPSc2XYi3VqzhzBHdvN2HpbtuR03Wg6NWeO4LbtJmy/LZj2K8P+PHsVZm3YgqUP/64z/TeO/f79n+PenXasu2dyZApwWN9vX0rHxnd34YHf/gJ3DbdH6JRv2oZ15zSYommAUTMS/d163PDdm/D7qcNBt1bhIjsE/uaz2FKnQ1t1JarYAoyjm2DUFiJdo0SJsjEkXXiYvw72rNFCujAADPFdgil9FHLs1fDnjYWy7Rz8eWMBgFsw9S8BjGeB/iVIt1wMSRvO1jLwN5+FPasoIm04W8tETRMW1wCE1GF3w+mQtOEcnSoiTTheurBYlky6sLjmU3nD28LThnkdsYxP+wUQkQos1v13SxcunTyZVJ44kbR9i9EIjUaDrCQyUCwWC+wOBwYXyFvTNTc3gxCCAol2DY2NYFkWQ4cMia/X0ACP1xuS8iuGzWaDsbUVWq0WgwYODJHx6cJi6LRauNzuXkVhH8ILEt4O0UKWcNwl4TwihJCQmuc5CbcV+ExEY9DBMSLGjzKOgGDffDsvG3LVVbJSe0eNu4as2Hw4rs5vrlV2a7pwryRYy+bThY+uAG55jmvcuwS4aXb0Op7OLc+BcniC6bnFXJ9y7MN0Ck6two3Zv0TBqX8C+U/JtufbCk6twg2Zv0DBqU3A8FWy7N2Fj+CRwFa4G8YDNesTjj/u4ovIw62du9PG6VuZ/h+YwVTA2TYCuPR6hM4PmzfiU/waDwYqsNI8HQ8yFZj7WQY+P1mFJ/wv4Rnrb/DY/7N35vFRVXf/f5/JLElIICEECBCWsIgKKlX7PHZ52qe1C91sC7S1O+rj0ufXqrUVLFK0uIEtSLWiVmzrbgGtrRX7iBZ3xQUBWYQkkAWyL5OZyexzfn/cJXcmk8lskAncz+t1XmfuOd/vOd97594z537nfD/Htonq4EKutm1ibXAhi22bWN55EW7gf20PsDa4kIVq3efU/GrbJpYHLwJgpe0B7jXox9atjanbkITM8uBFCOA3tgdYF1zIlbZN/fIVqv5vbA+w3rKIyyMbWRdayM/tm7k+sJh8u+BXkQ2styziishGPb8371tcwUau9y+m0GFhGRv4Awu5PKzU/YSN3MzFACxjA3eziJ+wsV8+kMz/somHRv+Uxs5elnK/XvZ0yQ+5oPtB/sDCKJnr2KDXrWcR19ifZHngx0gBN9n+zNrAAq62b2ZN4JtczkaeLvkhX+9+kAdH/5SjXV5utP1Jl1kbWMCEkvwZmT/Vxx8ZvwdKmfT6jX59p+utESK1dS1SJjU5yPYLal5eHhaLJScmJsbJAqheJ5TJwEDkaCK6gb4ybaIQiSiTAYuFSDjcp29oRxiPtT5i6o0TC0VM6uV6LkS/e1Ua2tD6TcebpjV2LNeRCCFuB74KBIAaYLGUsjuhznD0mIyfXCV379mXNY/J/qYelt/7V1Ze9q1BCcaSIVj7xUtBrpwT5KxzP56RxySKKC0F/f2RSSy55zFWXZ6cx2TL1q1csdXPqm/M7e8FSdFjQstevv8PJ6M91ezwVpgekxPcY3IgUskX/vN0d097S/JMYTmCefPmyR07dqSt39Lais1qHZS8LB56XC6c3d1UDuLJiEVzSwuhUIhJEycmJT8YcZqGuvp6QqHQgB6T3t5empqbKcjPT9pbY+L4Q0qJxWJJzWNy6jly9V+2J5RZ8B95aXtMhBCfB16UUoaEEKtUO5ck0hmWa0xGR9r7QnuzECY5RjhZan+8Lzw3Ff0YmbI3buHKOUFc/7xe2YE3TRvLt9/KVFlH+fZbU9b3Ne7mZ5FH8TXuTqr/sw+uYwxOxgjnoG1b2/exxPYY1vZ9A8o8/NVR/H7M33ll8QQ2z9zKVR8rpVw4KXvjFmZZGvhk/V2s/FgeGyY/y8NfLWHD5Gf544Kp/PlbVVyfv5HV/2XnSh5l2blwWeghLj8twKXBh/j+GYV8/4xCvtx+H5fM9vPl9vv49lS3kp+ez2enCOa33MtHi5r1/JP1d3F+eQefrL+L+VV5zCzyKp/HdTF77xqFYO3AHZw7NqSQpx24g1mWBs46cAfnFbcye+8ahWDtwB3MLPLqMrMtjXpd1c7bOW98hDHCqdeddeAOyr01+nHVztuZWeRVSNB23q7ra3UaQdqEd1f1lal5ubcmSiaqTJMRyvcXVdZbEyWrEaRpdVpfZW/cordd9sYtfWWx7WgEawaZ84pbqaB96F+LhwCWmDfgVJBnsSjejzQ8Cim9TCZJU24Z5Dz0KKQU+tb2s2lsbORQbS21NTUcPnSIhvp6jjQ20tzURFNTEy3NzbS0ttLW3k57ezsdHR10qvvidHR04FT3tOno7MTj8dDR0YHX66Wrqwufz0dnVxehUIiOjg4ikQhd3d36vjLdTieAXqbJhcNh/IEAHZ2dSCkJBIN0dHToiy87OjsJqLtHu1wuXC4XoKyx6ejo0EnuvD4fXd19L/+9vb16n4Bip6E+EolE6ce2r0E7t1SRjidOcmyjcqSU/yel1E74TWBQeoFhOTE5FsjGQjgNlWWF5NssjCpMfh+MbCOVs7Gqm3KNKji29vpDEe56sRqXP8SqLft5r76LpU/u5r36Li5/6B2u+ev77Kjv5uZn9rH3aA+rtuxn79Ee1j5/AJc/xMpn9rL8bx+wv8lFbZubA819+cEWF6u27MflD+l9GHN/KEK728+qLfvxhyJ0ePwcaHbR4fHjD0VYtWU/7W6/bmMiGSCqDohq23iuxuNE+lobsWWx7QxUFtt/ItmB+s8Aw8/tmg1kMGZIlB+pVD3WIo3JTFJ9JHkuqfTtsNvJz8+nsKAAR34++fn5FBQUUFBYSEFhIfkFBRSqn0cUFlJQUEC+Kqclh8OBw27H4XCQ73Aox/n52Gw2HA6Hnufl5eFwOBBC6OU2mw2HuqeQVqbJWSwWbFYr+aqONS8PR36+bnu+w4HVqqx0sNvt2B0KlYTFYonafNFmteJw9NFMaPZEHRv2NdLsM26EaHc4+u19pNl7vCBl4gSMEUK8Y0iXptnVRcCWJAwa+rC9VNO4ymlZDxfOFvOrFq67YMV9aTG3ap/7MbimoP/6wTb5haXro8N/E+i9/PI2OWXJM/FDgGP01/5rv/zckvVy7b/2pxWKql3j1h6frNn9lnz9YJus2f2W3HfUqZe19vhke817Ubmmo5VJKfvlRrl4uVHGqKfLxNiYSCa2Lrbt2HaS0Y9bFtvOAG3H6z+R/kD9m+HCyaOltTVu+GwycLvd8nBdnQyFQinpNTc3y9oEDK2xqG9okDW1tUnJJQr59Xg8srqmRh46fDjpvk0MDUgxtHfaKWfLx16LJEyDtQlsBT6Iky4wyCwDnkJdQpIoDanHRAhxuxBivxBilxDiKSFESTJ6pZGOrO+VE7U3TYahlPaO/VyeQrhuPJkx766hStvzJkX9cb5afm7fzDhfbVL9z9x3J2Nw8ti2d/BtvSlh22Weaq62baLMU51WKKoW5q3t32LcK0bbx6W8t4ayt9dE5Wy7lXLhVP4SelvZBygqd7fqi3eNfRhzo4xRX2s71sZEMrF1sW3HtpOMPu7W6LLYduJcx0T9J9IfqP/hGC6c7jiSKaRMbmFpPGgLQ9UBO3nE7EqbDFLuIwFyYTGriexjIE+J7POYDKIvz5dSzomTngYQQvwY+ArwPZnMDZnKzCrbCfg8YFU/rwJWJaOXbY9J3L1pMvCYtPb45P9b+1BGNu7Y/qqsWvqM3LH91ZT1Xz/YJj+/JHmPiWzeI2/6xwdyypJn5Msvb0vYdqYek2MqY+oPif5Qe0zSHUcy9pi0tMjW1ta0dL1erzx0+LD0+/0p6aXqMTlcV5cU+dlgHpPe3l5ZXVMja5Pwvpg4vgiFwzISiejHpOExeejlSMKUapvGBHwR2AuUJ6szpB4TmcaiGMi+x2SMcHK1fbOy+DULHhNX3U4u6H4QV93OtG2s2nsnZziOULX3zpT1Q017uMq2iVDTnqT7/8+xEcbgZOa+O4+pxySt7+h49GHqJ60f61Ubao9JuuNIprBYLBkvrpGpejNS9JYkSyWvLX4dyCOirYEwLn4NBoO0tLQQCAR071FE3f04EAjQ6/XS2dlJXV0dNbW1ejp0+DD19fUcOXpUWfza2kprW5u++LW9o4OOzk66urro6uqi2+nEaUjaYlEtud1u3G43vb29eq4lr9erp9hjr9eLz+fT82ST3+8nEAj0+xwIBNJKwWCQYDA4YHkwGCQUCsVNwWCQzo4OnE6nrpcqFP4UkTBliLuAYuB5IcT7Qoh7BlPImXBhIcQ/gCeklA8PJpvL4cK0KOG61937OLde9p2kwnXj9VH7wXa+tqmDvy8sSzlceEtLKWsffZqrv3tBH2HaIPpPHC5iyVO7WX++g/nnnz9g23fszOPZF//NiMrTmV/exfuBCVT4a/lQVuLxh7j0FD/zzz+fjtodlFXNo6N2B5Hy0/Qw1Q8jlfQ27OKFrjL8R3azLzyJGdTTWlBFgd3KtEg9zuIZCcOFyzzV+EfPHjBcuKd4FhMCh6LChIucB3CPmgWgfx4oXFgrGyhcWAsPjg0bTiVcuCW/inG+2n6hwLEhxInChY0hvYPVGUOCBwoXLity9CuLDRuubnHxzxde4Muf/SyzLA05R7CWyjhy1rx58v0Mw4WllIwfNy5l3UAgwNGmJsaNHUtBQUFKfXo8HqqmTUtKvvHIEfx+/4BhwLFylZMm9VuICRAKhairrx9Qv2z0aAKGH1Bzs7/+iEfIZqwzlsf+LuucKFJGTU6llDo5m9ZG1bRpKYX2TjvlHLni3ncSyiz+b3FiEawJIbYC4+NULZN9/z8tA0LAIwnauRS4FGD8qHzFY/LGLXDBHxSBrSvg/Bvj54lkLvgDY4RfDRc+W2kzFf04MvYzf8lVPIq94yzYeXtaNpa8fjOT/PMpef0emPrHlPQrZl3FEttjlPnnwtY7kurfUXkdY3Byxv5HYe6EAduuLLmEJbbHWNVwIdObH2NT8EIW2B7j6eBlANib72WzP8zMPb/D+aWb6HlmGXcVXcWhdjfL5XrW+r/DEttjXL3/bgAAIABJREFUVAcvVNoJXsiPbI+xpEfR/3+2+1h15EK+q9Z9Wc2X2B5jidrHKtu9elm8ug1qmZavVfPlBpm1ceoEcJuh7vbghfzSkF8XvAwErLbfx23+73Ct7THWWb7LzyKPcl3oMvLtghsi97DO8l2ujDyq53fmfY8reZRr/ZdS6LBwA/dwm/87XOd4nDv4LlfxKCu4HIlkRfge7sz7HlfxqF5nlAG4kXv4Pd9jqe1xVgW/w095JGGddrw0eClhJL/hXjaWXMyi7g2s47sstT3Or0KXMaG0gIs71+hlq4LfYYma/4xH2TD65xzt8nJz3r3c/rCLa22PsTp4IRNLHMecYO1YjCOTJmXmWLEIQTiDF7t0yNlEGmtMkmp3kPq8vLx+P6YaRowYQVFRke41CUcihIJB/IEAvR5PUtT7Qgg9/NqinqNQvT0Coj4bPVXGa2EMebao4djaD7mRpEwa25QyisRMPz9NV/2se57UsoiU5Kl2yEgksWcqHqma7GOH1f++sFii8njXyO/3EwwGKSoqUs2ROrlaupAkt47keOKYT0yklOcnqjcsivmsTOC+kVLeB9wHMHtCsXT2BinLpqFZRqZDh81qwWEX2Kzp/duWdv+DKC44p5L6miIWjp/A5COFfHLkaMZ2OPjoqBJ6AyFmW4qZeE4l/vZiHOVF+CtGctsXzqDLE2D8S6Usn3kqU3YU8ckRoyk8mke5w0pBxMKMkgLy7XmUuGz8R2UJ4535fHZsORPbClg4Wenr0plTAZhWPYLLZk5jZk0RV582g5l7i7j+LOWFffbuYq4+ZQZzDo7i6plKvnzOqcz6YBSrzp4LwJx3lbLT95Wy/FQlX3XWXEYV2Kh6o6/stnlzmbzjOT2/+7yPAHDK26XcNlcpW/uxeZS8voW7z/sIowptlL3whF6m5b/72FmUb9/C3ecqMuNfeoLb5s5l+u5/8buPKnV//NS5AJS98IQur9XFyox/6Qlu/+iZTHz3OVaffSbl259NWKcd3/OJc3SZ0z99OvZtJXrd3Z84m9IRdhzPKmXl25+lylvE7IKRrFaPf/els+jyBJj8aimrzj6Die9uYdXZZzD/Lp8n3dstWRyLceSss87KaDiO92abLNL+GyiDPhPCwDwav1ok7aUBQPMCjRmTqWUmDHA4HAQCgZS8bMkgnGtrmtNd0JKNRBqLYqSUjD0Gi1/7hffmwOLXaUvSW/z67M6j8nNL1stndx5Nuv/H36yTU5Y8I599/vmMz/+Y6Ofw4s8TVT9u+HEcvRxY/JrWOHLmmWfKTNDS2iqPHD2alm4wGJQ1tbUp707c3Nyc0k6+DY2NSckfOXJEVtfUSJ/Pl5I9JnIPpLhQdcrMs+V9z8uEKdU2M01DTbCW8qIYgNFZXvya19sWHd6bhcWvX+v+S0aLXyt3rWOWpYHKXetS1q/w13K1bRMV/uTChdl2Kw5/O2NwMufg+txbmJljiz9PFv14Icm5GC5MmuNIxpBJxlLGgfYXRKq79abCvAokbZ9U5cxw4JMPEgiHE6fjb9QQvumkm7LtMYnr4cjgbTRVgrOBPCZTj6PH5I/bquWUJc/ITc88l/H5HxP9YehxOFn0h9pjkm7K1GPS2toqG48cSUs3FArJmtpa2d3dnXKf1TU1UeGhiZC0x+ToUVldUyPdHk9K9pjIPZCid2PyzLPl3VtkwpRqm5mmofaYpIXSUJvijcjSXjndrY18q3sD+99/M+O9cti6gnG+Wq5zPK4QnKVp4+QdqzlFNDB5x+qU9YucB1hie4wi54Gk+x8jnIzByX8eujPj88+6/vHow9RPW3/SSMtxCc/NNSi/ARm2kaK8tgj0WHk2Utq52MQJASkhHJEJ0/HGsJyYCCGyug/NzHHFzBpXzJ0vHsTlDw2ucByQyeLX4nxrVJ4MPOp5D8VNaMLEcIQkswlCvO3shwqWYzzhMZHbkDIz5tdsI2d4TFLB6AlT5evv7kqbIyReXUftDi5+1sOGL42grGpeavoxMvsjk1h672PcdtmFadv4/tuv8c3N3Ty5oISzzv14Svrp8JjcsTOPO16s5uKZHmbN+U+s7ftosE2lMniY/VJ5IS7vrWG/rGRKqI4rv/d1XV/jLGlz+SnvraGtcDqWtr1Eyk/D0rZX58/wNe6myVFFe817vOEZR37Xh+wNTWBKqI4jjmkU2q1Mi9ThGqlwjHQVzRyUx6SraAYTg4c4YptGcb6Nka4DMPZ0aN2j85kMxGNS5DyAteJ0Qk17sFacTndvMC5/SZOjilMsDbTkK1wQxrpkeUy0XLsOsVwlRo6TePwl8bhK4tXF8pfEcpbEyhjrkuEx6XD7+9XlEo9JKjjrrLPk+++/n7Z+W1sbfr8/rbDjcDjM4bo6SktKGD16dNJ6HR0ddDudTJk8Wd9kLhGOHD2Kz+cblMektbUVl9uthO1aLAOufRldWkppaSk+n488q5VQMIgQglA4TCQcJhwOK+RgoRB+f1Y2iBwUegi1lHp0kXYcFVptCM/Vw4NB5wExtmfMITrMV4IeKqzJaW1q9UbeES0sOSp8WauHKF1i+paRSF+Z8TyMesYyYGx5eUqcI5UzzpHXrHk7oczVF1hOLB6TY4Fxli6FpfXtNfDl3ymF226FT18XP08ko9bZXlmFtf2z2F55AUb8Onn9ODK+qsu5PLwRX+McqL0nLRsrd61jFp+hctdf4NSZKekXTbiEq22bKHKeCvvuH7R/39abePXIIsbg5ZzDD7D2YCdX2zbxbHAhV9s28VTwIgBW2h5gU3Ahn7NtYt0jcKV1Mx3n/py6zcvp/OY67nu5luWWDazzfYOvdf2FTcU/4Js9D7HM/yNCRFga3sBatc1qNf8guJCv2zaxXO1jse0B1tYv5Ku2TaxV+9J0lhvs0MruVfN74tRtUPNE+vHq1gUXcqVtk56vDS7kF47NXO9fDMCNqsxVtk2styzi8shGVoQuIt8u+FVkA+sti7gisrFfflveJUgk14U3cG/et/gJG7mbRVzBRq73L6bQYWEZG7ibRXqdMb+ZiwHiytzMxViE4Cbbn1kT+CaX8VfuZhH/yyaeLvkhF3Q/yE1cFCVzORv1ulvExVSWFvKDzjtZzyKusT/J2sACrrZv1mUfGv1TjnZ5udH2J71ubWABE0ryp2f8UJ9k0HaXDYZS89Cmy2ESDoejdrSNheYxkVImXJDb7XTqExOb3U4wEEACoWBQ4S9RydWOp+dFW5egHhzTvqImIQPJ0MeVIomZ4MSQrGm7RWsTFaOsdl6DfeexHCvpINcc5cPSYzJucpX8IIvMrwC1H2zn65s7+duC0QrTagYekzdcY7nx/k2suGQh5xW3HnePyROHi9jw1LNc/I0v8e2p7qT6byucziNvHOYUSwM9xbNMj4npMTE9JoOgrb0dr9fL5MrKtPRramsZNWoUY8qSZ2TqVGnaJ1dWYrMN/nf20aYm3cZE8lJKAoGAPqGQUmK1WuOywJrIbQiRGktr5Yxz5JWrtyeU+eWCvOPqMRmWa0xKQu0ZheLGqxvz7hqmy3plN99U9OPIjPPVck1+8rv7DhguTHrhwhMCh7jatokJgUNJ918unFz1sVLmd/yFb091s8D9MFedGWaB+2GWfbqcZZ8u51K5kTWfdnCldXOUfrzdfY27A88u9jG72MdZtfcwf1wXPwg8zt2fK2TN2Od47rvjuHfyCzxz0an89fszWVW2hbs/V8jyon/ofS07V3Cp3MhVHyvlqo+V8oPA41wy288C98NcMtvP/I6/cMnZxXz79Hzmd/yF+eO69PP45NH7mT+uS8mr8phflRdVdl5xq5KPjzC/Ko+zau/hvOLWqHz+uC5lJ+TxEc4bH4mqm21pVI7HR/Rz1Mr65YbrMNvSqOyqrOaavrGsX67qJ6ore3tNvzptJ+d4MsY6bXfn2ZZGXSZKVjij9LV84gg5dqjHhCFBEm+ziaC771PVIYW1IGr7g72ACiFwOBwUFBRQUFBAYWGhOSk5SSCl4jFJlIbAqKEP20s1lU/KbriwlFLW7H5Lzr1hi6zZ/Vbq+jEy+4465QUr7okmbEvRxkzChR9/s05+bsl6+fibdUMeSmqGC5/4+idzuHBdfX3a+jW1tSnvTtzV1SWra2qk1+tNSr5RDRc2idNOHpBiaO/EqrPlLU+EEqZU28w0DUuPyehwdsOFcbdSvv1Wpst6yrffmnEopa9xNz8LP4qvcXfaNk545zZm0sCEd25LWX9C4BBLbI8pHpMhDCXtqN0RVed7bjm07MX33HI6anfge245tR9sx/fccg7W1NDe3BBVF5u3Nzfo7Whta7mxTuujXx7HDs1WTT/K7hgZ3K2KXBJ1se3E9hFP32hbousYr+14/aeqP1D/g90HwzVcWBnDh04fUg8XTrXvvCQWyGYDoVCIbqdTt8vv99PjctHd3U1baytNR4/qqaW5mdaWFtpaW+lob6ezs1P/i0rbQbjb6cTZ04Pb7cbldtPT00Nvby9OpxOv19tvF2Ft52C3200oFMKp2uJyufRdd3t6egAUea8XAJfLpS/Sdblc+NXdeT0eD15VJhAI4HK59HPt6enRd/E19qWdt1E29jgUDkddp1gb4l1LvR23O9OvKS4kuReVMywnJscKMuNNzBWMLLBhsQhGFqQf0mzNy0Ooeapw+4NR+VDAH4pw14vV+EOKy7nd7edAs4vaNjf7m1ys2rKfPUecLNm0i92N3fzk4XdZumkXe4/2sGrL/rj5ymf2crDFxf4mF2ufP4DLH+KuF6tx+UOs2rKfgy0uvY94ebvbH2XHgWYXHR4//lCEVVv20+72R9nd4fHrMto5rNqyf9C6eOdv7APop2+8Rsay2HYGKovtP1X9gfpPErkS9XpcEQqHCaW4eDVT6GG9Sf5aGDeuO+aIY5McoG9JEueQ5i+iHOBzVNlAbavlg7WRNjL5lU9CN637USbmMBkSConj6Z7JVjoWf+Xs2P6qnH6d4a+TDNzcQ838mit/5cR+R+017+l5a49Ptte8J/cddeq5VpYoN+ob+zDWJcrjlhn0Y+02ykgpk67rd/4xfcTTj1sW5zrGazte/6nqD9R/rExs20Wjy50yB8aFVNMZZ5whM0FTc7M8dPhw2vo1tbWyubk5JZ0el0tW19RIl8uVlLzGFOsxGV1PGpDi3y4Tpn1E3vhwMGFKtc1M07D0mJSEs7/4tWrvncyxN1K1986sLH79uT2zxa/jd6xlJg2M37H2uCx+TeYapaqv77Wi1pW9vUZfLKsvjNUWUaqLL411/XLh1NvR2tZzQ52+IDc2j2OHcfGvZr9xjxijjHGB72B18faaMfYRT99oW6LrONA+NrH9p6o/UP+DfccVonP4hfZlARaLJaPFr1Km4aOVyS1mNfYBJnGaiYEhJYTDMmE63hiW4cKlE6bKN7JMsJaL4cJf39zN3zIIF/7UJz7Jl8d10+SooqTQRqhpD+5Rs+ht2EVh5Rl6SK21fR9dRTMAcHTup942lWXnirgkdBr5XFvhdD1c2xgubAwTjpSfpoefdnkChJr2cNQ+jcDR3ewITGCE80M+jFQyKXiYRttU7FYL0yJ1dBTOYEq4jpb8qoThwo7O/dgnzMXavo/QmFMBGOk6QE/xLD3XwoVp3aOEEQMV/lqaHFV62LB2XFJo08OD44UNe0uV/rMZLtySX8U4X22/UOB4IcUDhQtrYbuJ6rRjY0jwyR4ufOaZZ8qdO3emrd/a1kZvby9Tp0xJS7/20CEKCgqoGD8+aR23201Layvl5eWMLC5OykbjGodkMW7cOIpGjACUNRU2u518h4Pu7m5GjBiBx+PBarUSVPlLIiqHiZZONMTyi2gcJNrvp85vohzE15cyuk7KqC0GRAyPiU6ypnoREnKnGAjWpkyenFJo74RpZ8tLbngjoczKHztMgrXBME5kn2BNCRf+DGPe/TOUZ0awVlB1OVfaNlHQNRfeTY9gbfyOtczifMbv+FPKBGsTVIK1O16FjwxELPZKNAnZrQaZh4ILWVC9hdkX3qq33e72U795OSxYyYg3budu7zdYUvAUnvN+qROs3fXvar7Xvo5NxT9goeshHi/8Pl/q/DMrWUyvT/Ib2wN6fx+o+VvBhSw22Pg91cZkCdbWvtW/bkOaBGsC+I2hLpZobYWqny2CtSvYyBr/Aq5xbI4iT/sDC7k8vDGKhG0ggrV7+BbX2J9keeDHhJFx6zTCtVvFJTqJ2h9YGEW+lizBWmNnLyvtfzYJ1sicUj6dl0KdCC1JD0i+w5HWxEQn7UIhg8tTj61WKxaLBavVqjPPWqUkIiV5Fosim5dHIBBI6/wygcbgGhWGHcviqk4OjBOF2B987XuNqBMNYbgW2gREShlNbBaHRC0ey2w8gjXU9mIZYY2h4Tobbcw5SykJRyLYrNY+ZtkUoXlMcgnD1GMyRb7x7u7c9phs2MSKi4fGY8K403jllZewVpyuewBMj4npMcnUYxIom83KZ/ay8jxLlMxw9ZicccYZcteuXWnrt7a24vZ4qJo2LS392kOHyM/PZ0JFRdI6Ho+H5pYWSkaNoiwFYjYTJya0iKHRo0cbqfRT8m5UTD1bLl7+ekKZWy/JP64ekyFfgJZOmlVRpCwKfXihlK4WJT28UFmUFy9PJKPW9Wz4urxgxT2yZ8PXU9OPI1Oz+y35719/SuFESdPGxju/LD+3ZL1svPPLWTvHYas/HGw8SfTbmur71c0qs3QP9ZiQTpo7d67MBK2trbL20KG09Wtqa2VDY2NKOh6PR1bX1Mj2jo60+zVxYoMUF6qOn/IRueQ+b8KUapvxEnANiuNozGCyw/KvHCCjUNx4CIYkPr8kGMrcg9TjDRKJSHq86YfrWvMsUbkJE7mAMUWOoTYha8hk4araQEbqMg1vtXHdgQkT2YCUksgx/itHCFEJfB6oT9qo4ZZKKiZnxKoar65m91tyzorsML++frBNfmFJZuHCL7+8TU5Z8ox8+eVtWTvHYa0/HGw8SfWHK/NrpuHCLS0tsqa2Nm396poaWd/QkJKO3++X1TU1srWtLe1+TZzYIEXvxrjJ8+Q1d3sSplTbjE3AJuBM4DBJeEyG5et4OV3YO/ZnNRR2zLtrmE5dVvbKKej6UF38+mHaNs7cdyezaGDmvjuHLNw3Z/SHg40nsf7EYsuEoR4T0oHM0Ougb2efmRHpqZnhvyayBCkhHI4kTJlACHEBcERKmXwIXCazoKFKx8JjsmP7q7JqaRYJ1kyPSXb1h4ONJ6n+cPWYZLzGpK0tc49JinvtBAIBWV1TI5tbWtLu18SJDVL0boytnCev/L0rYULxdLxjSJca2wC2Ah/ESRcAbwGjVLnDnKhrTMbSqXhMdt4OF/xBKdy6As6/MX6eSEatm777t8yxf5Hpu++HyaXJ68eRKZh1Fb+0PaaEC791R1o2nvLBb5nFlznlg3/CvFOzco65oL9l3GWc8sEa/lF+KecfWc/jJYtZ0LWB+0qupthh5cKW2/nX+Mv5Sst9bJ14BZ9vuodXJv+E/25cz79nLQfg/Oqb2DHzSs6p/T3vVP2Mc2p/z44zVwIwb+dy6s+6lqqdt7Nr9lWcfXAd7868krMPrmP32bcAMPfdX/HhnF9w+r417Dn155zywW+p/8TtOL1B5r1/PfXzrmXCO7dx9JylTN6xmvp51zJ5x2pqz1sFQNUb1+ll3R9bRsnrN1N73ipGFdooe0Gpm777t9TM/UVU3vyp3+LsDXLK28to++h1lLx+M90fW0b59lv71ZVvv7Vf3vyp3wIw/qX+MvHqAp/+NfZtv4mSKR1hx/GsIjPh3VUcPXtJwjqjjP9Lv6fLE6Dy1eVRdZNGWirTfZaHMwSZeV0y0o+jp3GJxPJfxH6ORCLYHQ4lxDRG38ilEY5EsKjH4XCYvLw8wuFwVMisse2IymcSiUQIhcP4/X5CoZDCdRIO9z9/IcizWBAqUZ3Wr0WIvjJN1mLBIoQeEitUGe2zsU3DQb/wWmM/UiohvxEplbYHgDF0Wj9vIRLqaH1J2Rc2rOkYr7OMsT/2OEHjSkZ29nxKwivSLhNE5Ugpz49XLoSYC0wDdqrnNQl4TwjxUSll80DtDcuJybFAMCTxB7Kz+NXlC0Xl6cCal4cFCEYk7xzqVH70PEG629yUeILU13cx2RNkz4E2TvcEqT3UidMbZE6PnwMH2phlyN94rxGAc7u97Np9lPkD9Nnu9jMmpswfiuCI87nD46fMkGt7wBSHIrg9fuz+EAE1//BQJwAFR3tYu7uaJTYP/2xuZo7Nx1ud3XzaFmB7VzcAn7cFeGFfG+fYfPxzdzNzbF42vXeU6bZe7nv1MADTbR7ubT5Eic3NvUeU/KZn9wOwyuZm1T/3scTmYm1jNUtsPaytU/IldbtVmR5W1e1jia2bVbX7lLpH3gNgta2bVbW7udbWw+rNu1li62Z17W6utXWztFaRuc1Qtm7jDq6MdLP00Hvk2wU3RLpZfWg3S+1d3HawL7/O0cWvH9qO1y+53dHF2vod/CzczZ2b3ucqouvuqFfKYvMVD70NwI1J1F1NFxv/vodF3V2sVWVufPgdKksLubizi3X1O1lq62bVoZ38dIC61Yd2ca0q8zO62PDX9zna5eUWa1/d6kO7wJo/IuUb/ASAkd8iHSS1X0wMtI3l3B4P7trajPqfXlUVddztdJKXl8eokSMB6OzsZERhIVarlc6uLkaXltLZ2Ul+fj4BdbIRiUTUH7Yw4XA4pR9JKSWhcBjiTFpOdMTymUD0BCOWbM04EYwHS6b34jHaD0dKuRsYqx0LIQ4D50gp2xPpmTwmBh6Tr27s4B+LyrLCY7Li/k3cmAHza+0H27lgUyfTqWO3fxL5dguVgToa7FOo9NdxgEpm0sCHVHIKDRygEgnMUj/H5hjq1p/vYP7550f131Y4neV/+4CbP26J4iq5+4m/85Nvfw1A/2xp28uy1yJcOy/M6h15XDsvzMq3IRCKMDFwiEOWKdCyl+CY2Vja9/K+byIRtf858/6Defaj7JeVjHQd5ICcxARVZ2S+jbLeajyjTmGcr5ae4pmM9dYOyGNS6q6mq2gGpe5qncfE2r4viqNlQuAQR+3T+vhMoB9/SZHzANaK0+nuDer8JaGmPToPTKo8Jt5SxX6No8TIVdLlCeifY7lKjHWxfCSJeEwGqjNylMTjMUnEcXIyML9mymPS0dFBt9PJtKlT0/phqFEnFrEThEQIhkJ0d3UpExrN9W2oj4TDSBRStEgkohN7aW/p2ng/sriYUaNGRbUdCoexCKGfSygUIk/dRDQcDmO1WgmFQrqXQVvnom2Kl4nHRPPMaIRneqJvAmi8xlq5iG5QJyzT2or1LGk6QgjdU5KOxyR24hAPsR4RiUoCZ5iQpOMxEUYiOUUpatJSUFCQEufI2Enz5IIr/51Q5p5rS7PCY5LsxGTI/+dNJ82sKFaiZx7/fh//wuPfV/7zjpcnklHr2u9fJL+wdL1sv39RavpxZF5+eZt89vrPKutDMrCxZvdb0vnnb8u3d+2TB6qrZfv9i2TN7rdk+/2L5I7tr8r2+xfJl1/eJtvvXyTf3rVPbn1rl2y6d4F8+eVtUflTL70rn3rpXVl/9zfls88/P2D/bU31/eq8D1+o2+Z9+EK9rr3mvai8raletjXVS+/DF8r2mvek88/f1vO3d+2Tb+/aJ+vv/mZ631EK36Opf/z1Z462dA71mJBOynSNSXt7u6yuqZHBYDAt/eqamozWqJgwEQ+kuMZkzMSz5GW3dSZMqbaZaRrywSGddKzChU/79bNZCxf+XIaLX3NlYWPO6A8HG09S/ZN18WtHZ6esrqmRoVAoLf3qmpqMdic2YSIeUp6YTDhTXnJze8J0vCcmZriwWjfqrd9S6a9j1Fu/zTiUMtS0h6ttmwg17RnyUM4TQn842HgS6w/XcOGMIVPb6TcezF1/TeQCBpso5JxBuZiOVbjwtCXZCxc2PSamx+Rk0T9pPSYdHRn/lVNr/pVjIssgRe9GWcWZcvENLQlTqm1mmnLCYyKEuEYIIYUQsUEhcaGHC29d0fcWt3WF8hYXL08ko9ZN3rGaWaKByTtWp6YfRybUtIcltscUj0kWbcwl/Y7aHcnLqHW+55ZDy158zy2no3ZHVN7e3EB7c0PcOi3H3arLaO1oeXtzQ78+Yu2IlYm1sb25Qbc/GZmk69Rjrf9krlEimYGuf2z/secxmP5A/evtDHCPTBppmXSsx4hkkOo4kiks6sJQ5bcgPaQalTPU6PV64y5kBWVDOb9fic7r7e3F7/fj9nhwuVz09PTgdDrp7u7G6XTqqaenB5fbjdvtViKN3G48Hg9erxefz4fX68XT20sgENDLgsEgHo+HcDiM2+MhEon0y71eL6FQiFAohNfnA8DT26tHD3l6ewEIBoP41Hqj/cbySCSCx+PRz1NrO16dUS+2TVAWFGuRVaDcO26PJ+oe8gcC+AOB6Ouu2m7U86jnmjmU3aETpeONIZ+YpMyhryKTfWjiwWa14LALbNbML0lxvjUqP9HgD0W468Vq/KGBH4pYmXa3nwPNLmrb3OxvcrFqy372Hu3R8+V/+4Dlf/sgqsyY729ycbDFxcpn9rK/SWnH2N7KZ/ZysMWllx1odtHh8et2uPwhVm3Zr8sY6/yhCO1uP6u27McfitDh8Q8qE3uOieq041Vb9uth1YmuUYdnYJmBymL7B6LOI5nvL17/xnaMtuca0h1HMoH2Y5LJj0OGu/Ucd/h9PgIxP5p6nd+v/6D6/H59YtHr9eLt7cXb20uvx0Nvb6+SPB792Ov1KhMPv79Px+dT2vT59M8+v59AIIBPtcPn8xEKhfD5fEQiEfw+H2E1IigQDCoTA3Wi4Pf7CQaDBINBfbJgnDj0m5ion7X2te9baztenVEPIBA7UTH0Dcq9o9muy/j9BPzRz5pPtT2qTD3XTCGBSDi0QXDeAAAgAElEQVSSMB1vDHm4sBBiE7ASeJpkwog4NuHC77/9Gt/Y3M1TC0o469yPp6YfI7OlpZS1jz7Nt+Z/jm9U9gy4Jb0xXPTDSCXTykfoZVrYaWyYapOjKirM1T1qFrTuUcJ/BznHjtodeiiwsU4vV/XbCqdT3lsTFUpcXuzQ5TpqdxApPw1L214i5adR3ltDW6Fyjq66nXqYqjFctrs3CK17OGKbRqRlD3XWqYx0HaQubwplvdV0FM7AHwozNVxHk6OKKeE6Xb+neCZTQof1PiYHD9MxYgZlnmrsE+YSOLqbjhEzqBhVgLV9H6Expw4YNgzoocNFzgMctU/jFEsDTQ4lZFMLHQ417YkKKdbCiI0hxbGhxN29QU6xNOh2fxip7Hds/I7tHftpya/Sw46BqO/fKKOFEWv3kbEsNtzYGCZsbEcL99X0Z1ka+oUC+xp3M3H2Of3ChrXyeOHC51SV17i9/hkpPPZZRzrjSKbhwl3d3XR2djJxwgTy8/NT0pVSUnvoEACjRo3qP8lRXdoRKYmEw3qILlL2hedKA8FZJKKX51mtTJwwAau1/4tRIBAgEolE2av9UDocDv0NfkRhIeFwmGAwiN1uxx8IkGexRIUEa7aGVD6TcDiseymGau2MgD5iNS1cWCMjiyFik7J/aK4WXi0MOrGTRyn7yNK0X09j6G5UOK+hf63eGNYcFfZrtMOga5SNOs94OsC4ceNSCu0tqzhTzr9oS0KZR26ZmJVw4WQxpK/0Rg79JGK3LwUuBRg7Kl/5K2fPnfDl3ykC226FT18XP08ko9aN37GWmZzP+B1/Uphfk9WPI1NRdTlX2zbxx3/ncZr9SZYHfkwYyTI2cDeL+Akb+QMLuTy8kXvzvsUVciPL/YspsMMy+QDrLYu4PLKRdcGFXGnbxIrgRQDcaHuAtcGFXG3b1C//m300X//IpAFta3f7qd+8HBaspOztNXpdx7k/p27zcuQP1jOmyIFv603c7f0GSwqeIv/86/FtvYnVgcVc+l9VuJ5cjnP+r+ne8htK5v+azn/eyN9Kfsi1+U9xU3AxHl+IC9vX8beSH3JB94P8gYVcwUaW+RYjgZW2B/irau8mNX8huJCv2jaxXD3Hheo5flU9t8+p+Sdsm7hPlVlpe4CHtPN/S8nXGer0a/OKkm9Qj2+PI6PVLTfU3RFcyFWGaxvve1inymjf1YrgRSDgJvufWBNYwM/tm1mn5trxisBi8u2CX0U2cG/et6Lug9vyLgFgGRui7o2fsFG/Z27mYl1GK4utu54HeNpw/TWZ/2UTD43+KY2dvSzlfu7hW1xjf5I1gW9yORv1uuvYwIbXFP31LIqSWfvGTzna5eVG259YG1jA1fbNrAl8k4oSe/JEHMcA6Y4jEyZOzKhfaZgYpIpgMIjVaiUSieByufQfSe0/du0HMh2EQiH8fn/ciYnGKWKcmASCQZBSn5gEAgEK8vMJhcMEgkEsFgvBQICIyvwa1iYmKmdKOBwmHArp5UMJbXKm5RjzLCBqckP0dxTLR2JRJ3KxPCj6pClO29q9pE+MVFn9vhjk/k6PaE0OiVckEY65x0QIsRUYH6dqGfAr4PNSSmfSxCvAqIop8rlX3k2bvOxYe0wYdxrvv/0a+ZPm6m+VcGJ5TIyek4E8Jtq5ah6TIucBPoxMwtG5n3rbVIqcB6mzTqHUfZCuopn4gmHdUzIlVEdrQZVOsDY5eJh621RG2K1UBg/TYJtKZfCw7h3pKppBcb6Nka4D9BTPYqTrAIw9HVr3wNjT9WvV4w3qHpJYorWSQlsUsZrRU5IMwRoQl1jNmGskbEZiNe3YeI/EyqRCsBaPWC3WYxJLsGasM+onQ7B2zoxxh90e77TBnttMcCzGkUw9Jj09PbS1t1NRUUFhQUHa7ZgwkS2EQiFsNltK3o3R48+QX/jhMwllHr99ynH1mAzZinhgLtCKsqnPYSCE8v/w+MF0jxnB2pLsEKyZ+lnWHw42nqT67TXvyRljCwLDcRzJNCrH2dMjq2tqpNvjyagdEyayhUgkknIETem4uXLRzw8lTKm2mWkasolJP0OS3HVQSsmoHA8XNvWPgf5wsPEk1S905O2XOTCGyBTHkTkZTkxcbresrqmRLrc7o3ZMmMgmUp6YjJ0jF15VmzAd74nJkEflpINxdOJr3J39cGGyEy5s6mdZfzjYeBLrTyqS8f5iyX3IzP7G1v7tlyZJmolhDH2dUIJ0vJEz8axSyqmpyI8ssGXZAhGTmzBhYrghpXEkme3lE6r3bc5mwsSwhTx2uwunjePpnslWGjl+ctZZVc2/cnJcfzjYeJLqD1fm1zlz5shM0NvbK6traqTT6cyoHRMmsglS/NtlVPnp8muX70+YUm0z0zQ8/8oRXYzz1WZ1j5DKXeuYRQOVu9alpp9CH6a+uVfOiah/su6Vo3tMZI69bZowkQok/fhp4vHVHE8MOcFaOhhZMUU+8a83mT+uK2vhwq+88hKLt7i58zMOzvmPT+phr5a2vXq4b2zoZGxIbOkIe9xQTmOdkVArUUiwfm5J2B8b7hsro4X79iszhAQz7jTaXH69LDY0GOgXHqwRrGk5oF8vY9irRj6mkZ1Z2/exX06ivLeGOutUxnprqbNOAegXJqz1Vd5bQ2+Jco0qg4fpKppBqbtaz0NjTlXuDUO4sJFYTSNVA/Qw4WyEC3tLT9FDgbU6I0FabK6RoMULCTbWxd4/sQRrA4ULG+9RY128sPWBwoWNdYnChbWyaWNHDjnBWjqYO3eu3L17d9r6nZ2ddHV3Y7fZ+ki1UL3QRkH1OBKJIKXsx3eBlDpXxWAYOXIk5WMGZtz3+/309vZSWloaVR6JROjq7mbkyJHYVH4Tt9uNlJLi4mICgQAut5vRpaW43W5A4cQIhcO6XeFwGBmJ9PGVSKkQq6nkatrb7omMeFwjUfXE/2svlrjNqK/dE0IIIpFIH0lczH0Se+8MhGlTp6YU2juq/HT5iQueSCjz7Ia5Jw/BWroYJ7qo8NfCtnuyQrDW7vZT8PpqPlP6LeyvPsJvPmjm690P8s/RP+ZbnodZ5v8RUsBNtj/rZFNPx5CILVfJs67ngSjyqyvYyPX+xRQ6LPyKDazxLYgi5opH3nVHcCHzqrYy/oLfDGp/LEFarIxGkLZk/mzGvNRXZiRRY9uttH/qFlZv2c9K+5/wnPdL6jb3kanJH6wH4PDG63VCtXW+b/C1rr+wqfgHLHQ9xJ9KfgrAj7ru5Lf+b3AZf+UPLOSy8EZ+HbxIJ1jTCM1eiiFae8hAcPbPGPK4TXFI0O5Vy+6NU7chhjwtHolaLEFdOgRrV9o2sS60kJ/bN3O9fzEAv7EpBHlXRDb2y2+xXIwvILnZ8ad+JGo3cRFev1IXe/+s8S/gGsfmQQnWLELo9+hl/FWv08jUjER/AxGsGcnXjCRqmoxGsGZ8DoaaYG2oYLPbKRoxQjkwsHPKSKTfj05E/WExEm5pP1b6D7pxgqJNbgyTHAEUDMIwa7Vasdvt/cqFEDjsdvIMBFw2u11fAGy1WnE4HAC6vhCCvLw8/RzCKsOrdo7a+UQikSj2V41s7Xgh3g+5XhdDiBbFCothRaGqLyORfm0J4kxCDN+TxWLRJ6PaZyNbq84QKyXCYuljg1Vzoz1G3SgGWeizzWBD7HVIZuLSDzm4xmRYekxKJkyRb2aZkl7zBhgJwkyPiekxMT0mpsfEhInhBCFEah6TMafLj33lsYQyz/3lzJODYC2TNKuiSFmk+vDCPtKnhxcqi/Hi5YlkMtU/Hn2c7PrDwcaTWH9WmaV7qMeEdFKmi19NmMhFkOJC1eLRp8rPff+9hCnVNjNNw/KvHBMmTJgwYcJEdpBzXDzHcxaUrXQsmF8z0s/hUM4TRn842HiS6p+s4cImTOQiSNVjUjpbfubbbyVMqbaZaRqW4cLldCnMr7kQZpnjoZwnhP5wsPEk1j9Zw4VNmDgRoESMyYQpUwghfiqE2C+E2COEWD24UTnw5pJqGjl+snz8zbohf1McDm+zJ4z+cLDxJNU3PSYmTOQOSNG7UVRyivyvb7yWMKXapjEB/w1sBRzq8djBdPJuuOGGjGdDxxsPrl1xQ9vI6Zx/dD2eiZ+g192D5V9LqLdOo+CVlThHzsLy4o36cff4j3GkpZ0RL/4qSsa3ZTmNJR9FBjyEn/0l7lGnEH5+BUdsVVi33agf1488l86uLuzPL9XrjtiqkFtX0OSYjnXbjey2noXH7URsuZYmx/SoOsfMz0DAA1t+CePmKHuMxOZVn46S8T23HGvF3Lh1Rr2OopkUvrwyrky8Or0sjszBhmbKXr4+qn/fc8uxzvhv2js7KXzhOjqKZmJ58Ub9Gmv5oeJz6Ozq0q+xdduNbHdXUPzqTeyxz2P7h/UU//tXPN9WxohXb+KvdcWMfO1mNjeMJP+lldzfWMnzO2sY/9oKHjhYwLi3buPh2iJGvXYzTzWOVGQ7qnhlz2Eq3ljBX+uKGbP9Vl5oH0P+Syt5KXAq7x5ooOzl63m+rYxRr93M821ljHnzFp5rVfLnvbM50tJO0YvX8bJzLKNeu4mXnWMpe/MWXg/P4dCRVopevI6DTCH8fyuoFVOwb/sN7/RO0M/jaGs71n9dy0Gi6xpLPsqhI6163YhXb2K7u4LRb97CvlAlI169iVeDpxP2ubE/v1Qv02S0eyz8zC9oKZih32PWbTfqsvUjz+XQkVbyty7V760jtioKXlnJ+3ln4nE7B7xHC15ZqX9H2j1a8MpK/btyVXycvYeaKN72K71NrU5rz1XxcY60tGN/finuUafg27Kc3tLZbHzo/sKfXvvrW4doOEgb69evv+Giiy4iFAoRDIUIq3koGFTK1Fz7HAgGCQYCeH0+QqEQgUBAScEggUAAfyBAwO/vK1eT1+slEAjg8/vx+3z4/X58Ph9enw+fz0eexUJeXl5SNgeDQSwWS9ywUCkloVCoX1uhUAjoCyXVOEe00NZQOEyexYLP5wNQQpuBcCiEEEIJBTbsm6JdE6/Pp1yXQAC/34+ntxePx4Pb7abb6aSnp4fOri49dQ2SnE5nX+rpwel04urpocflwu1yKbnHQ4/LhcftxqN+dns8uFwuvX9Pby/e3l7cHg+9Hg8ejwefz4entxefz4fP68Xt8eD1evH5fLg9HgJ+Pz6/n16PB5/62dvbq3x/Ph+96me/30+v14tf/b61dsOhkKLj9Sr3QDCoHwdVPa0tn99PMBTS7xXtOgaDQfyBgN5v0HCP+Xw+5ViV86n3kXb9tfsvGAhw6623Nt1www33Jfsc3LrqrhvGT/0qavB63FS//08ptWnEjTfeuBpYJ6U8CHDDDTd4BtMZluHCowqtEVlcEakQnbIhNMoHUGl15jfJ0VSITppCxf4Kq8uhHTeESvzkWR2Vol00ydGyQnTSFB4ZqLC6CxsiZWHCQX+lzVnQFCr2FgQ6C7z5YyMVli5LU6jYW2F1FTRExkQAKi3tlqZIqVIXKY1UWLrzmiIl4QpLl6VRliOljFRaOtSyvrrDXcEDMhjwTSu1TG3siTROGmmZFJsf6oocBphWapna6BbNk0rsVY3dgdpJRXJ8VF20XuVRWUahv93e5ZUfxshUHpVlTBAdHOqKHFLrpmlljT2RBqPMYbe1KW/U+KrKyBF/o4sjk0rsVUec4fqJo/ImH+4O11pGlI6fbGnPOyrL5ASrq6ApNNJfYe1xKLnL0SDHAIJK0Saa5GgqLF2WJlkmKkQnjXKMRAgxSbShf0dyNAW9LXgLx6HIlAMQK2PME8kkrS9hkiVGBoO+pY2mSKmssHSJpkiprBBdok9/jAQo8jYJb8HYqLqGSFlYCGGZZGlX9TpRzr9D9umPFVJGwpWWdktf/4qMfo/ldeQ1hZX7Rr/X9D7GRIQQlkmiXWj3VlOkNFIhOmlkrEW5/+LfowW+VuHKr4gAQr9HtfO3dFkaQiVekWcrmCTa0NrUv0e1vYbgKC95NnulpT2vKVTsq7C6C5pCRV7haS9w9gaH3SZTQog2oC4LTY0B2rPQTjaRazblmj2QezZly54pUqoDWhIQQjyn9p0I+YDPcHyflDKpiYoQ4n3gaeCLahu/kFK+nVBnOE5MjiWEEO/I4xmvnQUMR5vBtPt4YjjaPFyQi9c212zKNXsg92zKNXtSgRBiKxBvl/FlwM3Av4GfAecCTwBVMsHkwwwXNmHChAkTJkykDSnl+QPVCSGuAJ5UJyLbhRARFA9N20A6wzIqx4QJEyZMmDAxLPA3lAWwCCFmAXYG+cvK9Jj0R1oLfIYYw9FmMO0+nhiONg8X5OK1zTWbcs0eyD2bcs2ebOEB4AEhxAdAAPhRor9xwFxjYsKECRMmTJjIIZh/5ZgwYcKECRMmcgbmxMSECRMmTJgwkTMwJyYJIIS4RgghhRCDxXgPOYQQt6uUv7uEEE8JIUqG2qZEEEJ8UQjxoRCiWgixdKjtGQxCiEohxL+FEHtVWuUrh9qmVCCEyBNC7BBCPDPUtpzIyJUxI5fGg1x61nP5OTaf0T6YE5MBIISoBD4P1A+1LUnieWCOlPIM4ABw3RDbMyCEEHnAH4D5wGnAhUKI04bWqkERAq6RUp4G/Cfwv8PAZiOuBPYNtREnMnJszMiJ8SAHn/Vcfo7NZ1SFOTEZGGuBa1E4eXMeUsr/k1KG1MM3gUlDac8g+ChQLaWslVIGgMeBC4bYpoSQUjZJKd9TP7tQBpCJQ2tVchBCTAK+DNw/1Lac4MiZMSOHxoOcetZz9Tk2n9FomBOTOBBCXAAckVLuHGpb0sRFwJahNiIBJgINhuNGcmBwSBZCiKnAPOCtobUkadyB8oMZGWpDTlTk+JgxlONBzj7rOfYcm8+oASctj8kgFLq/QnHJ5hQS2SylfFqVWYbirnzkeNp2skAIUQRsBq6SUvYMtT2DQQjxFaBVSvmuEOLTQ23PcEaujRnmeJA+cuk5Np/R/jhpJyYDUegKIeYC04Cd6m6ck4D3hBAflVI2H0cT+yER7S+AEOLHwFeAzw5GYDPEOAJUGo4nqWU5DSGEDWUwe0RK+eRQ25MkPg58TQjxJZSNuEYKIR6WUn5/iO0adsi1MWOYjAc596zn4HNsPqMxMAnWBoEQ4jBwjpQyl3ah7AchxBeBNcCnpJQD7kGQCxBCWFEW5H0WZZB6G/iulHLPkBqWAEL5xfkL0CmlvGqo7UkH6tvYL6SUXxlqW05k5MKYkSvjQa4967n+HJvPqAJzjcmJg7uAYuB5IcT7Qoh7htqggaAuyvt/wL9QFp/9NZcnJSo+DvwA+Ix6fd9X33BMmMhF5MR4kIPPuvkcDwOYHhMTJkyYMGHCRM7A9JiYMGHChAkTJnIG5sTEhAkTJkyYMJEzMCcmJkyYMGHChImcgTkxMWHChAkTJkzkDMyJSY5ACHGTEKJdCNEshJiqbgQWl2dGCHGDEOLh421jLsK8FgNDCPGAEKJVCPFBltqbLIT4PyHEPnUTtKnZaNdE9mCOI+nheFwL83lMHubEJAcghJgMXAOcJqWMx+SYTpuFQohrhRDvCiE6hRANQohHhBDzstG+iWGBPwNfzGJ7DwK3SylPRdkDpTWLbZvIEOY4kvP4M+bzmBTMiUluYDLQIaXMyo0lhBgPvAFUoeyTMR44FXgSeFgIsTgb/ZjIbUgpXwY6jWVCiOlCiOfUH5pXhBCzk2lL3YHVKqV8Xm3bLaXszb7VJjKAOY7kMMznMXmYE5PjBCHEUiFEjRDCpbrdvqGWn4+yRfkEIYRbCPHnOLrThBAvqbrPA2MG6e5RYJ2U8nIp5U4pZUC9cTcDnwCuEUJMT2Dr/6juQc3Wj6jlpwohtgkhuoUQe4QQXxvknKUQ4idCiINqWyvVB9EphPAIIf4qhLhFCHGnKv8VlfCoWwjxuhDiDENbS4QQR9R2PhRCfNbQlV0I8aBat0cIcc4g1+dkxn3AT6WUZwO/AO5OUm8W0C2EeFIIsUMIcbtQtrQ3cRwxDMcRjxCiV7X1fiHEnVkcR14XQvSo44jdID+cxhHzeYwHKeWwTMADKK6rD7LUXhh4X01/Pwb2LgImoEwGvw14gAq17tNAo0F2KsrW6Vb1+A0UemkH8F+AC3h4gH4+BfxL/VwJvAh0APcC29Xy7wG/TWDnEeBcQAAzgCmADahG2azMDnxGteOUBOcsgaeBkcDpgB94QT3/V1B2Gn0fyEPZ5bMV+A/1+EfAYfWcT0HZoXSC4fpMVz/fAPiAL6l6twJvDvX9eSzuY/W7fw9lU7aFMXWrgT0o7Jq/p488carWNlAEeA33+fvAPrXum8AHcZJ2Ly0EnChvz1aUvUYuHurrd7KlYTiOXApsA36utuHI4jhSBYwC9gI/UmVzehwxn8ckr9NQG5DBF/xfwEfI3sTEfZztfx+4QP084ICC4p4NASMM9Y8mGFBuAharn59Qj63AfCCilp8OPDOA/r+AK+OUfxJoBiyGsseAGxKcowQ+bjh+F1iifn4JaAH+oB6vB1bG6H+IMkDOUAeb8wFbjMwNwFbD8WmAd6jvz2NxH6v3xRko/y0vNJR/DHhNHVDzUH6APm3Q0QbCkUBTmnb+J/CS4fgH2ndnpiG9f3J+HFGf9XdRKPKzOo6ox78D7lA/5/Q4Yj6PyaVh+1eOzOL/dccDQogfGtyL3cAcBnelgvJ21CWl9BjK6hLIj6Vv9865wKNSypCUcgugbSpWycA7fFYCNQPY0SCljMTYMRFAdX261fRJg0yL4bMXaBHKbqwVQBDlTQYUr8w12vVRr1ElyttNNXAVyuDRKoR4XAgxwdCucQfXXiBfDBCJkGtI5T6WUh6WUu4CIrHNoOxKake5njair7vWVw9wSAixSO1HCCHOTNLUt4ESIUS5evwZlDdVE8cRw20cMTzrASmliyyOIzHHRernYTOOmM/jwBi2E5MBkO7/daDchO8IId4UQnw9m0YJIaYAf0TZzKpMSlmC4pYTSag3AaVCiBGGsskJ5NtRBgKA3cB3hRBWoew2OkYIMQO4Gbh/AP0GIN7/xkeBSiGE8Z6ZjDowSSlPl1IWqemVBPaNAh4BLgACKNuga/3eLKUsMaRCKeVjavuPSik/gTLwSGBVgj6GO1K6j6WUbwD/RrlXmlDcvfuEEI+heE9OEUI0CiEuRnG/XyyE2Iny188FyRgkpQyrtrwghNiNcu/+Ma2zM5EWhuE4Mo++Z92t6mZrHBkIOTuOmM9j8hgWb5XJQAhRhOLS3iiE/pw61LpvAr+Jo3ZESvkF9fMUKeURIUQV8KIQYreUMp7nIB2MQHkI2lR7FqO86QwKKWWdEOId4EYhxK9QwsK+Cvx9AJUXgStRtvb+hZo3AM+huFTvB66VUr49gP79wBohxKso6xmmo3g23kJ5i7hWCPE7lF06v4qyFiVZWICfAleoP5yvAtr1/yPwlBBiK7AdKERxTb+M8pY1EeXvCh/KG9KJs9DLgET3cQKdGSjREtok73khxCellBcOoJJWyKJUIgDOGFTQxLHCcBpHHkRZP3U1sF/9fDNwHpmPI4mQs+OI+TwmjxNmYoLyo9ctpTwrtkJK+SRKiNuAkFJqM/ZaIcQ2lNl+ViYmUsq96kP4Boob/kGUhyNZfBdlYOhU23gQKBmgr61CIQv6npTyERQXnw4hhFUqW5EPZOtGIUQZyv/PE1EWjv1AHdi+ivL2fh3KG84PpZT7UziPCHCT+kAB1AP/UPt9RwjxPyjbtc9EGTReRRlQHMBtKD++QeB1lEV1JyIGvI8T4BsoC/XcAEKILSg/AOm8cZrIUQyzceQRIUQxysRkNX3jSCAL48iAMMeREwPayv1hCaEw3T0jpZyjHr8OrFV/XAVwhpRyZxLtlAK9Ukq/EGIMykN7gZRyWP5nJ4SYCPwf8AzKG0Qtilv2IuA/pJRfGULzTMQg1ftYKKGgz0gpN6nH3wb+B+XNS6C81d4hpfzH8TwPEycWzHHExFBh2K4xyeb/dSgz6HdUvX8Dtw3XSQno3p/zUNyVf0N5Q3oJZX3Hj4fOMhOxSOU+FkKcK4RoRAnFvPf/s/dmIZJl62Let9YeYsec81RZY9bYVdVX91xxr40fPMnoIl18ZewHoQFhy8gvFjbG2JbB4AcZLDDYejAWF3kQ2HDBMkgGC8tGIBC2kU736e6q6q7qU9VdY1ZlZk0ZkTHscS0/rB07dkRGREZk5jmn6qh+SGLYa/j2vyP3+vda//8vIcS3aTN/GzO7dxf4Bvjmk1HySU4qn+4jn2RaEULMCSH+thDigTA5sP7ZE7X3Mc+YfJJP8kk+ySf5JJ/kVytCiL8F/COt9d8UJtldSWu9f+z2Phkmn+STfJJP8kk+ySc5jggh6ph8Opf0KRkUH6Xz69L8vD67sox0Cyi/iywWUd0O0iuhwgDhOJAkprBloaMoLdtBFkuobhfpFVFRgLBs0Bq0AttBhwGy4Jn2iiWU7yMLBVQUISwJCHSSIBwHHfimnV7ZwEe4BYhjEAKEQCcx0slzpn1PzemhovAwZxCYYxln13BPw+n7iMIviXOiPo1DvE4SpOOghs9pKn32yk7iHDqngeuuwbZHcHYRBQ+dcWp0og5zeiVU2OOMQMiMUzgF9IycXz/64Y3WupebYKL8lizrpk4mlnlE8Pe11qe5cdivjSwsLOgzZ84AYCchImjTcNd487qLkAI0xFFEqVpi4d3P8epFosVNHBUg4wCkhQZE6Ke/IwfQkMToQhlflijGTfC7+JUVYmXhWjEChaViQCO0IpEOibCRaFP/AxWB+X+RWqGFJMkyoJvoMZ29631i4Jvxkj/n0eX7beseSfZZpPV1+o1Epd9KRJryxxzr1xNDeh4kGDymkIi0xZ4OIlw0AksolBbESuLIBIcAJWw0Eifx0ULwxq9QLGhKbx8jF5d50SxSrdh4dowfmyG43n6OsCzeuhu4tqbCAaFVpBs59ILzDhMaE1oAACAASURBVFoJti1Zt9+gnAKvwxpaabSG5XIXq/mO9l6TnSCgoZNpFA9MfR/5FrOk15M/0Fr/Qfr+IiZS7H9M87B8iUmu1+aY8lEaJufWVvkH/9VfxT17ie53X1O89RM6d76kdPs3CZ78gLt+hrjZAK2x6/OEL59TuHCZzr2fUfr8j9K99xXFm79B+Owx1uIyOvDRvo+zuo7/+CHFy9dp3/kZpd/4Lfz7d/Gu3SJ8+QyrUgMhSJr7OGfO4T+4R+nG57TvfEnp9k8Ifvwe9/wW8etdRKGALHjEb/cyztKtn6RlJ3BevEzn7s8o3f4tut9+RfHmHyF89hh7cRk1xOltXTdlf+O36N6/Q/Ha7RwnJM0GzsY5/J/fo3S9z+n/8D2FC1vEezsIz0s5X+Oeu0D3228o3fpNc/63f5Pg8SPcjbPEjfcAOX1u0bn3VarPn6WcP2IvrgxxPsLbumY4P/8tug9Szu2nWLU6YDjdM+fpfn+3z/n5T/AffY938TLR7qsc5x7uuYs5zlT3eU4hsGt1wpcv8C5cpn3vK9P3vZ9RvPmbhM9+6HMGAc7KWsp5nc7dL0dzakhaTdyNc3S/v0vxxud0vvmS0ue/mXJeGeLM6fP2T2h/8wWlW+l1H9DnHOGrbbzzW7TvfcXKn/23JyW9GpAmCX+9eGFimT/Z/X6a5Fv/VMqZM2f4O3/n7wJQ6+5R2fuB/2fpX+f/+v80jmPc714+3+eP/GSFP/PTv0jl2hUe/85fYD7eo3zwitgpoaVF8f0LRBwRV+YRKsHqtmitbPHCvcylg5/h7j3lhyu/x35YYdl9jyNCilELqSLsJKTlLdIRVRwRIpk8QIyS/AB8nOPT1hNaI3WCm/jE0qFrmZxmWovMKBge1KcVIfShtvLtZUaHUCgt0UgkCVIoLGKE1kTCRaCxdUQibBJtYYkES8dEws3qCRS26AcU6SFjqGeASJ2QCJtIu1gixsK0JbTivV4k0RYFKyBWNo2wzHzhgCW1g2+XibTLgv+SxHL4B29+wuZ8lz/6T/4a3d/+Xf6nh7/DzQsxZ6tvedFaRGv4F5/8DbRX5P9c/LdYLPvcVF+zW7zIs9YSjkzQCO4+camVBX+68L/RnTvD/73/O4SxIE7gdzfvsvj9P6Lx//5j/tjfHBcBPlqmvI/4WutxewfZmOzVf1lr/Y+FEH8d+E+A/2wmkKEGPz6xHey1TdwzZ4n331E4f4n47R7OmfOobgd7dR1ZroJWWNU5tEpwz10gfv8G9/wl4vdvcdfPosMQe2ERHYboMMBeWiHpdnDOXcR9+4bC+S2Sxj7O6jpaJViVKgiBLJVx186gDpq45y8RvX2Ne+4iSbuFu7qOdByE7SC8IjiuGYj236Vl93A3L4zldDYv4L57g3vhsqmTcS6hwyDH2cU9f5H4XY5zbZizgru+gWrlOM9f6nPaNsJx+5zr54jfv8c9v2XKZpxryHLZPC1Va4bz7EXc92+NIZbXZ8/QCwPsxeVBzgtbxqjLcwKyVMFZWyc5aOT0eYmk1cJZWUNYFsItIAoeose5vz+as1QybVbraKWwz17Aff8mx7mZsR3mvED87vUgZxJjVWumzVa1z3lui/jNa9xzWyStNs7q+njOc5eI3uzhnr2I8rs4qxuGUwhkpTrAOYsIIZD21A9Gn2SMaATN4goH55e4yEv+nT82XOIxB5/9pxwABXy6ToXuwpXsaKO8NrLdGk3ezl2CuUsU6VIsdLNjXacyUNYlmMA32bAYd6xXb1qjZHCG4XCfWggSYdOVht3qGVGn+ROcoi1LHDbetBAZjxbCGCip8dE7Nqqe6XK0MdVrxxX9a6OEBCGpcpADgmrRfPalyV9ni5iDonkm+Gc2HgOw+8//eQD+tc+fZFWvVF8A8PLzPwHA52ky3garFPCz4wAXb5rXXUwmgd8u9tsJKPHy5h+Hm38c/o+vRp7PODmF+8gLzFYI/zj9/Lcxhsmx5aM0TOJmG//7b9FhQOfOl1jFIp1vvkAWPPxHD1DtFnFjH9DYcwuEz5+gtabz9U+RpQrdO18ibYfgyUPspVV04KN8H2f/Pf7D+wjLov31P0GWy3TvmYscbj8zA5SQJI33qG6Hzt2fIRzXlC0V8R/cRUch8etdZMEMUNHr3RxnyXB6Rfyf30e1DsyMCemT84unfc5yhc6dLyZzSkn763+CVTKcQgiCF09TTkHS2Ed12nTufYVwU85iEf/BnYxTuC7SKxrOKKRz50tkj7Pg4T/M67PH+QxUT5/ljNN//BBnOce5uo7/qM8pS2XD0uPszZg09tHdziBnqYT/4A7EEdHuK6TnZfpUYWj6nJbzmy+wevp0HPwfc5xBgLPyPuUU/XO69xUIQfj8CVZ9DrQmOWiiU31KZ1Cfw5zxmxynl/t9PryP6rSJ99+P5JxJJFjFI/JDHUw+/En6MjwY93bsEKipBvlemVFl8wP+qEH/OIbHUTLrLMo055mvNw3XcWdrpq2b31VlnFGVv47T9DGqzWHJ62rc8XFtjOM4quyk39eJ5IT3Ea31jhDiuRDimtb6e+Bf5oTp8T9Kw8SulSle/Qz34hY6iihcv0XS6VC4egNhWdirGzjtlnnCr9SQpTLelc/Q3S7e9Vsov4t35TrCdbHnF9FRiAoDnKUVsG28a7dQnQ7etVvoMMS7fB2rUkGWzZOzajVx1jdBa4rXbqE6bbyrt9BK4527SDS/iHQdRMHDnl+kkHHeJOm0DaeUhrNlrris1JDlCoXLNwxnj2Ei501Ut2POKQopbF1DlsuHOYHi1Vuodtuck+5xLiBdd5AzDE27nTaFa5+BlDhrZ0ZyKr+Ld/02qpvq03HMTEQYGM7F5QHO4vVb6B5nqYysDHJqrfucVz9DK4V37iLW3DzSLSDcguG8sIWOQryrn6FaB0dwXkcFPoVr5jfiXb6OsMdx3kJ1uxmnt3UNawynd+0WSaeNd+2m4bywNcAZLyxROH8JHYXmN9JuUbh2M+XcxGk1U84qVqWKu3UNFeSXcKcQAcL5NGPyi5JJgwuMWOo4YsA+ySA9a3ujBudxhtLwIDuu3Vn5j2rnqD5HGQyTzmlcvWn0MG35Sf2cRGY5j9PsN23wNO4jfxn4X9KInB+Bf/MkjX2Uhol5On2JcAtEL58TLS4RvXyGvbBIuPMShCRu7hvfjbl58yRbLBG+fI69vEL08hnh3DzR7ktUFEIQoPwuKEW08xK7UiV8+Qx7aYXo1QusWp3w1TZW9QAwPiZYlilTnzevi8vEO9uEXtH4bhQKSK9I/Gavz7mwRLj9DHtxaZATjV0bxfmccH6RaGcbHYXoIDCDV5IMcS4TvXx+mPOggZbStFObSzmXxnMWDnNGu68Q0urrsz7EuZTj3H2JTmKU30UHASQJ8e5LokrtMOfOICeWNcRp9Bl5RaK9HWTBQxQKxG9f9zkXlw3DMCdg19pEu6+wimXC7Wc4i8uDnHGU+Zj0OMNyLet7kLMFmBmTjLPe54x2XmKVykYvPc53bxCua8ouLg1yWpaZMRECuzZHuPMS6ZUIt5/N9G8gpMAqfrSpiD4aGTeATho4Z50VOY5MmiGYNBsyqo1pBr1Z+Y8a0PP8o2R4FuEog2NSn5NmGcbNmvTKn9RHZxYDcto2xv3WjrMv72ncR7TWXwPjfFBmlo/SMOmKIlalZp42a3WschWrNmdeK1VkuYylEtDGf8GqVLHKFexaHatcw6rOIcsVU75cRTsFhOMgS2WsatputY5VrmBVa1ilsumvXDUe0kohi2Xs6hyyUjFlK1VkxdTR1RrCdRGFIpbv9zmrNez6nGm3x5lGZ8hy+TBnrY5V7vedcaZcslpLOdP2SxWsSi3z3UBr8121jqzVsGtzWOUaslIbzZm2IyszcGbXIKcj20W7PrJcMTMX1eqRnLJYNn3Xajl91rJzFelMhBUEfc5y1XBWqmM5ZbmCXZ/L/VZynI6DdgsZp1WtGB2lepXFcsqZ+gNoDHuqox6nVa1lvx3hegjXHeI0+pS932epghXnOKu1jHMmEXzyMTllGR7gJj1hTxo4pxnQpl2qGDcAHbXMMMzxi5itOe45TLtckm9jXNlJhsWoc59m1uQ4MkrnszCPKzNsbEziP9a5fID3kY/SMJESE/3gOMiCBwWzri9c8/QvHNd8rzXSLaTr/gWEV0QUXKTnIR0XUTRlTSgqWT3hekivaN732vM8ZMHspSaLRYTjGIZ8n17BOL2mzo/CdRGeh7BTzswx0tSRbgHteaZN1zOcruGUhX67wvNGc/ba6Z2/42RtAEgvGuAU6dO8TJnGcYqCm+P0hjgLR3A65iIJTHveDJyFnD7dIU63MMiZXsujOU2ZQ5zptUTIPqfrZWV75zLIGWecIs/Z02OP03bMbyvjLOTObQRnoc85iwgBlvtpxuSk0nN+nGY6fZbjRy1FTDOITBqAjjI48gPjtMsz0xoA08ywjPO1mcWoGa53VPv58qP4pu1zGgNwXJ1R/U7LN02ZU595+wDvIx+lYeLGHcKXLxC2Q5CG/JqQWjNlrtEkjQagsbptou3niEKR8NljnKUVU2dugXD7ObZvIjO034UkJtx+hixXCJ49xllaNc6PlRrhyxd9p9LmPlpIc2xuniAN5w23nyGcAvGb3Wzgit7sGs7nT/qcC4uGU2uSZspZnxvP+fIFThigfB8d+BmnNcD5FKtqQmStShWkNJwYB067vjDI6RZS51czWEZvXiOcEZzbz9HQ1+cw5/IUnKUe50qO8zlWtd7XJ4Lw+dNDnLLgEe3tHOZ89hhrYSnlXBriBKteJ9p+DgXPlBmnzzA4zLmc6rNSM5y1vvOrcYh9il0fvO7S88wyTcHrc9q2KbOwPIJzHxCG8+ULKBQInz2e8T9BmHwbn+TEMutA1Bsk84OlnJALwkR4jJ/On9zX4WtsQlqnM4pm8ZM4qk2NJJlpQ95xZa3sdVRUTP67vOEotM59pxBa9Y9rdbiuzulB9K6ZQAuZvSohs/NSWhJjm1dtEytJqGwiZRElFkFkEStB25fECfghBCHsN2PCQNHtxjTfd+i2A+IoIQoidp9sz6Cvk8vj5+GMNT68+8hHaZhI16WweY7CpSskB028q5+R7L/Du3QNHYQ4Z86S1Ex+EKs+D0JSuHSNpLFP4epnxM0GhQtbkCTYSyvGCdLv4qysocIQ78pnJI33uFeum9wVZy+ClAN5TArnLqA7bQqXPyN5/w7vynWU36Vw9oKZUUkNE+kVD3NuXUeHEc6Zc8ZfBczgN5LzsuFcXkX7PirocxaufEY8zCnEwIDvnr2A7nZwr1zH23+Ld8U4rRY2L+RmJopIr0Th4hWS5iCnCiPcM+dIanlOq8955TPixgjO0MdZXh3ivEHSOuhz1szSRdLcx90c5vwM5Xdxz5wfmKGQXonChSskBweG832PMxzJ6V26jmo00nN6T+Fin1P5XXQYGM4oonDlhuG8fJ3koIl77pK57kOcqtPGvXIDb/+d4ex2cDfPp7Minpmh6nG2WhSu3iB+/xbv0rWRnEJY5lgaoTWtmCedX9qu7f9UyKQBffSSQT9/x7Bh0hsI04JDx8YPBHlDZNgo6X22SKaeeZhlyeAoXwiNINbOxPZmlUEjpG9cCKFzRkn/VWiF1EnufWqg6AShdWas5I0SYNAYkTZKWiTCRksXJcx5RdqmE3tEyuIgcPEjSaMtOWhD8yDh/fuAbjtk9/lbuq0OzTfvT1UXvwr5EO8jH6VhogIf/4fv0Ymi+903WNUanXtfI0tl/B8eoPyOmYnQyjwhP3+CEJLOva+wqnW6975CugWCJ4+wG++z8NakdYD/8+8QToHO3a+wqjW6D+4ibJvwxVNkNuC/RwU+3ft3EMWiCR8tV/F//p1xTM2FC8dvdtFJknJW6dz9Clkc4kRj1Uy4cJ+zNgWn2y97/zCnau6P51QqdSrNcSp1iDP44QE648Q4hG4/Qwhh+q5N4DxomrDmlFNWhjhrdYwz8XuU3zXHepyVHOdQGK5Wiu63X5sQ4HtfIctTcFZrdL/7BlksETz+eZ8zCEiaDfxHD5COk/Zdp3v/DtgO4YvH6YwJqIMGOvDp3r9rQoB7+nx4H4Bo52WOcw+tErr3vsJKw49lqUzw6D466KYzJn1OhKBzd7b8Awg+uCedXyeZZjZBoOnlBE2knT3RTzI8ju738GzBJL7Tcsycxg9DoHHErE/k08lRMydg8ogIBEr0Z1ryBshw+VEzJjA8ayKy87JFhOtEaARzrplBieZsEiWJtSRRFrHyCJNzJEoQxJI4EbS6JtFZGEG7owhChUo0cax5+7qNUhopBX4n5GC/TbvRwm91iIJfjC5nkg/wPvJRGibS9fCu3sTZOGvCZC9eNknDzm+BtMwTcLtlypYryFKVwoVLZqbg0hWSbhv3whaiUMCuz6HjGB0GWPOLCMvG27qM6rYpXLpmZgzOb5l2iiZ5juq0sFfWQGu8S1dNeOvWVdAad+Ms9vxC6hthwkb7nOYJ2r2wBdYIznItx3mVpNsZzTm3kHJeQXU7FC5eNU/iF7ZMGG6pMoLzymHOufnMxyTjDIOMs3DxstHnygTOi1dJOimn62LPL6CjqM9pOxmnd+kqOprACX3Oi1dA5Thd4/g7wLl1laTdMrM14gjOnj7PXzJhzfMLJrFeFGLVFxCOa86708G7dAUdBRQuXMIqlQ5xaq0pbF0x4cKXroBSuJvnsOtzqY+JTby4jLO+aWaMLl0xnJeujNZnpYZ77iIlv5+AaxoRQnxwa8Mfq4wLYe3JOCOlv6RjUqBrMd6vYZpcFeO4Zjk+iXvYL+MoX5JRTqRyinpHyTS+LOOuiRaD56aFPbatSe0Oi4VJyGaLqNfB2Pp5Gaf/ybNvVQTlkcfGfTfp+/yx3/9T7sjj4+RDvI98lIaJTmKTxKxUJt7bIV5dI97bIVlZI36zi3Rs4mbThLdGIfGbXaxqlfj1LvHrHeLXuyTLq8Svd0Gp7AkfIYnf7BLPzaflXhG/3sGZXyDaM22YGZOG8dHY2yFeXCZ+vUP0etf0Xa4Qv97LzUTsGc70ePx6l2R1vc+Z+kQchzPqcb7ZId7bwZlfJHq9h1XtHuKMFkZx7mYOqYazNMAZr64Tv91Fuk4/cVkUEr/dxapWRnNqnc5E5Djrcynnbo5zF6vqQ5o6XzjuIOcboyOrUklnoEZw9v5W0+s+gtPu6bOn++W1Ic4AhBjgjFJOu8dZM/lFkmYT2dPn4hBntTbI+fY1slgkfr1L9HrPMLzdG835Zhe7YjhnFSE/rBvKxypHORqOGix7cni55fSiJkb5vowyPKZxrD1uHpDed0f5wsxybvn2RkU3TTK4JtWdhu+4zqPTGnOTdHqUQ/C4NofbGXX8JE6xH9p95KM0TAATmoNIX83GaQiJSFMGCyHQWqchPCaaBZGWz74TIMXQ535b0C8rRK9PY2EOtiXT74ba6bU9grP3l/0gsn4GGbO+DrHn+7SyY+M4hczXETmOnA56fHlOTNmMU5gtsERWd5hbZDrpl8331eNM++1x9r6XOf2Qez+gz5yehTDnL0ZzDpbLXceB6276EvlrOaz/XpN5/tx1zNrJ/5ZSTtP8lJyziBBYzod1Q/l1kXGD8FEDdO/4UYPKqP4mPc2PGoDy/UwaoEbxjjNSjgpJnnVW4rgzPqOXkQ7POk1infT9MGv+u+HzHGUUTjI0jppxGsUwS3vDfMPtzSwf4H3kgzFMhBAW8AWwrbX+vYllLQtrYQlrbg57YQl7cQlrcRl7foGkuWScP22ze6xVqWF3u9jzaZmFJeyFJZP3ZGEJqzaPjiNE2UdW61jzi9gLy+bY4hLW/JL5fnEZq1wBBIntmpwYC+a41Wvz3VusWh2tEhOeaztopQ3n/OJoznSHXatcxV7oYs0vZu3Zi8vIHme6lCPClHMhbW9hCWthEWth2eTWyDgxnNU61sJy+jfMGRtnzZRT1ueyfjPOxghO38eaW+jrM8/Z02fomzwrveuzsJTqNeVcWM7yg4zidBYWiReWTBtJdJgz7dtwzh/mLFWwF2bkXOjr3lpYxqrVUd0cp+P22ReHOeuDnDrPuTzIWZsb5FwMMs7Z/mf44NaGf1kyfL8QQlwE/hBYxOxu+ue11idawB9nDExjnIySo6JjZgnpHTXIzcIzzuCYxiiZNPNy1KzHqPKzzPYcNUN0VFvjWKcpP62hNs6oGiXHbS//fpYltJEMH+B95IMxTIB/D7gP1I4qqIKA4OF9iCPjrFmp4n/7NVapZPbK6bSGnF/Nxkjdb7/C7jlBFjyCJw9RS6uoNPOrWk2dNW2H7rdfY1dr+A/uIG2L8MXTfrRL4z0q6OLfv4P0isYRs1LBf/gdJHHm/CrTrKUk8QjO73OcGmtunvD5ExBkfXe/+wbpeQSPH6GWzG64KghQKymnNcTp2ITPnyCrNYQw4cKG07STcf78W1BJ5vxq9soZw/nwAarb7jtr9vZ2Eak+a6P0aZac1Oo6/qMHCMvuc97/5rA+R3DalephzoJH9Ga3z1mu0P32K6xy2exBcxTnt1+n+sxxBgFqZc04v9qG0xrmzMKFG2i/i//gDlbGOUKfPc54DKffIUn3yrHqc8b5VSu6387u/CrtD8ub/pcow/eLvwb811rrPxRC/A3gLwL/3XEbn3YgGZaTPLlPesrOPykPf540OzGq3DQ80/BP2/a4Y6MG7XHnMmkJIy+zGHiT5ChDaNoZpnFtD5/TJMajfG5OYpSkIB/cfeSDMEyEEJvAnwT+C+A/OKq8LHgUtq7iXb6O8n2867dImg2K125ljp0mhTrY6f4l3tWbqHYL78ZNktYB3pUbIAXO0mo/XHh1AxBm75mDJoXrt1C+cdoUrpfmMTE+EYWzFyCKKN74HNVsULzxOTqMKFy6bLKGFgoIr4Ss1gxnuk/PSE7Ars8jC57ZK6aV47x8A8QYzhu3UK0hTqeAVTP36jynd/32Yc5KbTTnjR7n7dGcXrHPef2WCd0doU/j0DrE2e3gbV0zWVx7m/iN4PRu3E4dRy+bbKlpsjtZq5vw4Dzn1VvGATXPWZsbzdnT5/Ia2u+iAj/jLFy/ZcK6b9xGT+DUUWT23mk28G58jsr0Wc18TDJOf0rOa7dR7fas/zlI62RPOkKI3wX+OiaxxN/UWv+XJ2rwlyDD9wshhAD+JeDPpEX+FvCfcwLD5NhsMwwSo5YQhj+P+35cuUmOmdPODAwfH3VsFPuk7yad67CMqnPUjEpeMoNHD0XokIyNlhrkM2VUOjz2Pmvd/9wrn/RYtaAXnaV1r75Ea2PeACgtsnKxkigts5BopWV2VloLlDaRQgCxMtFDJoQatDYMcSKIlXkVAiyp0VrQjQsT9TNKYye9j5y2fBCGCfDfAP8RUB1XQAjxl4C/BHB2dYXw2ROEtPAfPcCq1fF/MK/hs8foOM5mTJKG2csGx8X/4QH2/DzBD99jlSuEz56gO530Cb+L8n2Cpz8gPc+0N79A8ONDpFckfPEsDW8F1dxHJwn+jz83Ya0/PMCamyN89gPCtoj2dgeenIU1jjMiSZ10k/p7w2k7g5yV6iBn+hc8/cHsbPvDA6z5efwfH5r9Vl48RaaJ4FSzkeOsjOA0e9AYzj2ElIc4g2c/Gn2mMxEZp+Wk7S2M5/RHcD5+iCyO0efjhznO+ZTTJtp7NchpWabPiZxzA/o8ijN81ue05xfwHz9EFItEL54i0zwmqtkAZTitcp8zePoDwrGzvXLy+pyGM3r5POOcRcQJn3TS5ZD/FvhXMFuX/1QI8b9rrU+0M+gvQYbvF4vAvtY6Tj+/AM6Mqpi/j2xsbGTfT/vE3/s8SabxqzCvoj/goHPHj85jAmQD4LiytojhCJ+PWfxI8mUVkkjPFv0xToYz7+ZzmGR/OjUHdGJymGT5SxKkSrLcJmiNUEnWXi9cOEuuJqwsj0liOSTSIbI8YmHRVUVibdOKPMLEYr/r0vElbxqaVkvRbIa8ftXkYL/N3tNXqGR8Qr1fpey8mm1L8ZPeR34R8is3TIQQvwfsaa2/FEL8C+PKaa3/APgDgJ/cvqULZy/grK7jXbyCu7FJ8u4KztoZdBTirKyR1OqgwapUEJaFu3YGdfEKzvomhYvvcdY2QCms+QWza28Q4MwvouMoLXPV1Gk2cFbWQUhk6ruh6vMmQVenjbt+hvjiVZy1TVTXx1ndMH4GrmOSghVLOCtDnOt5ThM2apXHcK6uQ5JknDoIs5DcXt/u2iaq2TRlhRjDuTnA6Y7iXN3AS/v2Lo7QZ55z/QyqcQV3/QzJ/pVBzjBAh5HhjPOcZ1POjZH61AOcZ0zistX1dMfeQX0W8pzrEzhTfc7C6axt4qXXXQxxOitreO02zsYmhXdXTUhwt4O7so50CiZNvuMezVmtg8hzbqAuXpnxn+fEa8O/DTzSWv8IIIT4Q+D3OeGW5b9ImfZ+MU7y95Hbt2+PTBJy1EA9rY/JqGWL4fo9w+Q4IoQeME56OVVGsRx3aWq4jVNZOjhVGfH7700rwGCSu6NaEhq0ee1NrBgffZH6ppsMqUIKpBSoD9MumV0++ZiMlH8O+FeFEH8C8ICaEOJ/1lr/ubE1lCJpt7GCgKTbRnU6JJ22SVzV6WB1O6hOB7RC2DZJu3esV7aFCnySThvheagwQPsBqlxBddpov4PqtI0vQLeDDgOSTjuLsEnaLaz6HKrTJul00jpd8xr4qG4bYhc5jtPvcZo6aI2wxnCGhzlluTzQt/LTdoc5O22sMBjB2UKFgeFMUs5On1N3TXuqx+n7Wd4NYdkknU6fszten4c52+l18lNOY6X39JmM0GfWbuIik6TP2Wn1ObsTOP3OIOewPoMQWSoZzvR6ZJxhQNJu9Tk7beyUJ+Pstk2dtKxICkg3znQ/wOn7fc7OMKfR52wikPaJvOnPAM9zn18Av3OSBn8Jcuh+gVmKmhNC2Omsp0KqTAAAIABJREFUySYwUx7w4zisHrfN3jE9Jl37tAnW0gLHYhoX3TJtfYmiIPzZOj+BaJEm4RcSON3Ms2D0XBRdilaXarqsca6UzkKdyS/nCMBGcw4TFdVbtukv04Apr3Tf+ARItMyWYZSWJFpk5q2iPwOmEdkxIbRZytEMBO1pTbocJIgTOWBM/ft/rjLz2Z/wPnLq8is3TLTWfwX4KwDpE9B/ONEoAVAK1W2huh1U68AMDO2WGUzSQVJ1WmbAd1101ww0qt3KyqpuOkCXSll+EOV30zIdVOfADD7tA5O6vNNCpZEUqpPWbx+kA9NBaky0SLodknYLWfDQOuX0hzi7nZQzNUxgLKfOc/p+f9mpbQa8jDNl0p0WKg1Z1QOcnRxnu88ZeyilTP0hTtVN9el3UN2OeZpwXXSnNVmfec5Oe7DvEfrU3Xafs9Me4OxdS5kMceb79juDnPQ5Tbvpb2WcPoOq4cz33T4w+uy2UXa6ttxppbrPc/aMri6q20aqpM/ZHeLstPqcnY55UhninEWMN/2RN5QlIcQXuc9/kM4afJQy5n7xZ4UQ/yvwb2Aic/4C8HdPo7/TnB0Y5zMx/HnaUNuj+prUxqxOoLPUP8o58zTOa9Y6MHrGZ3SE0wTHYDGh/wlG4qQQ4lFlpvk8TjxrtmC0Ke8jv1T5lRsmxxFhOzir6zir6yTv3uBsnsd5vZtNqztLK0ivDCisSh0dJzgbZ4nfvMbZPI/79jXO6gY68LEXllBRaN4vLqPaLdPem12zp8n+e+ylVXQcI8tVkAKrWMJZXiVp7ONsXsB5vYu7eRZ10MBZXkVYNsJ1ka5nMryurJOs5zjXzqA67ak47ZUNlJ9yhgE6DCZwrqDjKONUA5zncV7vDHJKK+UsICy7z3n2wpA+V3OcNXRyhD7HcW5eINnf7+uzYpx0M85mw/T9Zhd38xzqoIG9tAJCHuZ8+wbnbO66d9opZxEg47Q3NnHe7OGcOYf7Zg9ndVifIfbi0khOZ3kVkhxnqYy9tIqzPo5TmOWmHufqBsm7t33OjbM5fRYBiVWpGM71Mzhv9mb8R5gq/8AbrfUfHXNsGzib+zzzTMMHJP8x8IdCiL8KfAX89ydtcFw0xLFyRaQyTf1Jg9Y0g9NJjYGjwnmHy0xynB0XYTM8YzPt+Q3Xnea8JhlJ44yukxhkk/o5ia/PuN/DUVxHyqc8JpNFa/0PgX94VDkV+HS//w4VhrTvfIkslujc+cI4rT58gGodkDQbaK2w6/OEL56itaLzzU+RlQrtu18iHJfgyUMzSKYzJs7qutn3xLJof/1TrFKF7r2fIQQEL56mUTmSpPGepNOmc+9nCNel/fVPkcUS3Qf3UFGUZlQ1mV+j17uoKBrNedAkTvd2setmrxy0NmV6nK5L8DjHGQQ4K+8Np7TofP3FeM7mvuH89itEwaXz9Rcp5110HKe79rppuPAuKjL6FCP0mWUq7YXhJkaf1lH6fGQ421//1ITN5jl70S6NfZJuJ9WnY/RZKg9wDuozNH2WytNx3vmiz+m6+D8+xFnO63NtgFOWKnTu/QzQJly43tvEr4HqtM059Djz+hza00eFOc5vfjoV56xywiednwJX0hwg28Cfph/Z8sFL/n6R+sn89rHbmuDgOrzcMewjMq3MMniMG5Rmjfo5Tr2jBshJhsik9iYNyrPIpL4nGXSj5KQzStO2l293FMu0M1DD5XvtndT359OMySmI9Dy8KzfMniZhaMI82y28a7dASNy1MyTtA0Cb0N1iGe/qTXS3i3ftFqrTwbtyA+E65qk+CMzT/tIqwrJMmXbbhA2HAYWta4hiCatiHBaTZoPC5jlQiuKN2yYM+fotSBLcC1vE8wvmyblQwJpfwLt4BR0EhznXz5C0hjlvmJDaHuflG2Zvl1Gc12+iOpM53R7n9dtZ2GyP00r3oBnm9K7fMufU49zYJDlo9jlLFcPpd9Nzak/W5/WbZl+Za7dQwQTOJOlzXrsJcYx74TJWfc6E4BYK2AuLFM5fTjlvoloHQ5zpJn7jOI/QZ9JpU7xxGx0GeJevI4tlY0BpSFoN3I2zaKUoXrtFMqDPQc64xxnOxjmLnDQxktY6FkL8u8Dfx4QL/w9a62+P3eCvgYye2j88QzBNG8c9NuuMx0mXW2Y5dpJ2xxlJsw6u0/RxVJ/jys/a5zRG2rhlnGllWsPvuPIpwdopiY5Cop1tpFsg3H6KvbhkXhcWiXa3QQqSRgNQWPUW0e5LRLHUL/viKXZ9nujVNjoMswRrJAnhq21kudov+/K52Qfl1QtU9YBeQjAsSfjyGVZ9vl92Zxvhmf1RRBYuvDeeU5j9V0D3OUtDnHMLOU4fHQR9zsoQZ62ecjazGRPD+fwQpyyWzIxJyhm/fU3oFgi3n2EvLJqy8wtD+uxxbiOKxbS9ZVNniFP5vuHcMZzR9lOCxSXC7WcT9JnnXBzLKRyXcPsZTo/z0HVnPOf84tScsloj2nmR+SslBw2ElOYcanNE208Jc/oM0xmTPqczgXN/kNPzCLefzvifIE4c5qe1/nvA3ztRI78GctTSxSwDy6QlmEnGzXGNgUmsR9Wdta9xSzD597MYPcdhnLWPaY+Nk2mWaIbfjyuT/27asPJJZU8nSurk95HTlo/SMMGysecWsepz2AvL2LU5k3K+NodVX8Sq1hFSmnTwtTqq08Guz2PPL5nXhSWTUn5uAas2hwhDpFfEqtaw5xeydq20jlWrY7cXkWlqcqRMyy6ZMr2yc4vYtTo6ChGuhyy46DjBqtZHc9bmsn1trGrKmZbJOKu1lLOOCI2jrlWrj+Bc7JetVAc5F5aw51LO2pzRXbWGCoNsxqTPuZTpyqrPY9UXsgytYHw3BjjTbQGsWt2Urc8hghDp+abv3HWy8rpvH8FZX+hzBkE6E+EOcFpzCzl9TslZrR3NObeQlVV5fVqW0f0A53zGaR/inBvDOZfjHPx9ziQf4JPOxyrTLHscx09jWj+IvEyaNclHfUwvckx5C4tkoL/hwbD3fphNYaEy48oaaPPwd4f7HRZBfulMZ6/ZNdG9fCZqzKtOc5boLHdJPsFaL7GaTvfFUtIyrQuLRDokwibWNgk2gXKJtYUfO0TKohvZdENJN5C0fegGmv39mG43obnfpdMOeL+7T9Du0m11fuX5TR4/n3Enhg/wPvJxGiZg9hqREmHZYFkI20ZYFsK2EJYF0kZIjZDSfG9JsGywbIRtG4OgV9eSaMsybaZlsEx7WJbZsK7XLsI4t0oL7F4Z27Sfa1dY0oSZjuKUfU5hpVt2S5k7h17/eU4bYSXoPLvMc9oI0W8DhHkvZHpeaRm7z5TVTc9lNKc9yDmga8OQcdo2yGF9WimnNYLTBnSO0+5zWrLPaef0mefs6ewknJk++5yyx5D2M57T6nPmPx/JmX6PMO/znDOJSK/1JzmpTLN0clw/jfFPzJYJERWH+xw1IwGQaAs1YmDPGx5qyAiZlIitKLtYuZmcaWcAEhy6qjjy+LSSN0AAhNAZixTG4LAwidQsFSF1gqUisyeVipEqQiYRMg4RKkH0XpMEVGxialMjpbfRpnYKaGmh3CKJ4xG7ZQKnTGJXaKsyndhl96DEQUfy5EXM/nufF49f8erR83Gn8Wsgp3MfmWW/u6PkozRMdBwTv94x0/w7L7BX1gh3trFX1sy0v22RNJtopdBhQPR6B1muEO28IF7bIHq1jb24TPz6FagYHQQo30cIQbz3Crs+R/TqOfHqGvHuNtHcPPHrHVTXOJWq5j7CcYh2tnEWl4l2XhCtrhLvvUKWSsR7u30nyLd7yFJxkHN5tc+ZLj3oMDAZTstlwlcvcFY3iHa2sZdWDnNCn3PnBfHqmmGZX+hzIlAHDYTtEO28xFlY6nO+3sEqV4h7TqVe0XAWPaKdFzgTOX3jjJpxrg9xJpnz64A+d7aJ03Pqc3aGOLdxFhazcxrgzOuz6JmyK6u56/5qPOfO9mTOvD5fvSAa5kx9P9RBA+m46XVfJHr1gnh1vc/5encKzmF91s11Lxl9ziIf4trwxyrjllxGlel/Pqz7o6bcTxpFIYSZEei1Y4mYUYnVBiulDPpwmaPypIxbTpAovFPMYyLEkJGS41JCgnRQ2sxuCMtkee3PlKSZX7OMr+msST4lfW7GRCNILActLBJpkwgzDJZkB8eJcOsxcdVmfd4ljIu0f+sCre5Fmi1NoxnT6cTsvmzgt3zevnqD3+qcmh5+FXKK95Gp97s7Sj5Kw0S6Ls7GWbzzl0ia+xS2rpG8e0PhwhY68HE3zpJUUp+IdAO2wsUrJPvvcS9dJW68o3D+IjqOTYht6gTprKyhAp/CpavE79/iXr5G0moax0xEf6+cShX37AVUu4W7dYX43RuzL0qni7txLs2oWjCDlFvAO3eJpNHoc140TpEjOS9cIXmf57yAjqPRnFvX+pwHTZwzZ9Ga3J4+ddyz5w3nZXNOPU5n4yzCLYzkdLeuEU/iRGScha3rxI33GaezvIry/ZRzdYjzKslBYyrOwtY1kk4b98xhzsK5iynndeJ3bylcuDz6us/CmToPD3Bunjec2d5DdZwzZym0DnC3rpq+85yOa5Zy8pzNcZz75jdVqxvOi5ezjf2mFvHhrQ1/rHJayzizOn4eVfeoPntLMVPJjHk2hvvPv5ckSPGLX7LosSghzazHKbfbE4HCFQGuCCjJDgLF2lRbzsynf78YrlHfHfVb/P0/NeNWAadwH5l1v7uj5KM0TJTvEzy6D0lM597PsMoVOnd/hiyVzO6tnXYaLqyx5+YJnz9FC0Hn7s+wqjW6d79COgWCp49IGu+zJ+ekuY//6D7Ccenc+RKrUqX73R2EtAi287sL76P8Lp3vvkF4RTp3vkSWzS6zOokHn/Bf76CP4IR0l9nnT0HIQU63QPDkEcn+u3RzPJ/koIH/8DuE4/Q5799B2DbBiyeGE0FysI/yOymn1+f8/p7ZBTk/Y/Jmdzxnt0PS2O/r88VToKfPap/z8cNBfR40zC7Iec7vvjnM2TSc3QHOKv7330KS7tqb0ycqoXvvq0HOn/c5M30OcNbGczb3zS7Itm36rtT6nM+fpEYOJAf76KA7yFmqjOXUSUz37ldYpcP6jPffI4Q4xDmrfGhhfr9OMp0z5/RPmrP6qPRkYFDSIvM1kSQj2x0VQTRpsDuNKKDjOJxO6zh7mrNQ00RdjeKYxDDc96w+ReMMwVEO03m/pVGss4Ze9+QUEjUeud/dLPJRGiay4OFdu4mzeYFyFOFdvk7SbpswVGlhr6yZLJoarGoVWa6ap3/fx7t8DdXt4m5dRRQK2HMLqChCRwH2/CLCcShsXTNhuFduoKKIwsUryHIFWa4ghDCzE6sboKF4+TqqY/pGadyz50y4sOMiHZd4YRFn84LZObfHeWmIE8zOtOUqhQtbZsfkHuelqwh3BKdtU+jtstvjvHAZWSr393ZpHeQ4b6A6nQFOawxnYavPibTMDM1Izm62I7HhdLHnFnOcCwjbMZydDoXLN8xOvBcuI4slZOpUeoiz3aawddXsxJtxFpCOk3HqMJzIaa7XsD474zkdN+P0Ll837Y/h1Er3Oa9cB63Hco7TpzOGcxYxm299MkxOW4YHhNOK4jjN6JhR5cYNZEdxztrvrHVG8YzSzTi/nuHBdprrM825TePwPNzmcDsnjYiZZFxNOq9JepxVpryPjE3UeNL9q0bJR2mY6N7Tvlci2n1JuLxGtLeNs7xC9HoHHNs8OWuNivzMByDae0n4ap1odxt7aYloz/gamHT0xtcger1rQkH3XhG+2ibafWVCYfdepU/4mBwUjmvaW1wk2n2Js7KW+rKUifd20in9ItGbXeMLk+dcGeIEVJjn3CZ8tWY4Fwc5dZDjrM+Zdl+tHc25MMhpVSrEu69ynHsZp720mnHGr3cQmT6HOV8S7myYOovLRHs7oLRJOZ9x7mDVjR9FtPOSaO+lCUN+vYOV+m4c4tx7hbM3itObjhOwwrlBfe6sDXGqIX3mObeJ9l6N5BRuYZBz9+UYfe4ei3M2EVlU1yc5PTnWzZ38/jZHD1pHPdlOrjt6lmYWZ92TDmbHkWkcgo+qN6ncaZaZts9pnKSPyrtykmXC07l2J76PzL7f3RHyURomgFnPtx2E65oIF6dgvnNcE0nhuKBB2C7CcfrH0l1q+3UdhKMQSqXv0+97dVzHRE04rokOEdKUS7/L6vT+bAd6ffXKpCnqM047x2mb9cCsHTvXb48jx6nznFnfw5xOv808Z3ZejokK6X1v26Z+j9NxcpzOZE7bHuI0/Wml0uvgDOqoV8Z2xnPm6/Q4s2PuYU7LOcw50Pfw+Q/pc5jTdvr6TDmFEDNwjtL5GM6B389Ui9q5fwJMBNEnOXWZZrBIA1gHjJJJswKHlwusrJ2j+uwZMr2y4/o8jfM7anli1kRox8nBMZ3+x+dEGdf3rP4aR5WZdclmXJ1Zc7/MYvwcKSe8jxxrv7sj5OM0TCwLa24BWa0i6wvY9XmTv6NaNd9XapkXtlWukNQXsvwVdm0uLVPFqqdlvRAReiYbaX0eqzqHNbeIVU9zc5QryPocVtlM6WspsCumL6uelk1ziMhSGWtuziyRuAWsJEFWa1NwVg1nrY41t5hyLk7mrM1P5MSSfc65Xg4Nwykmcs7lOBcHOGXZ6LzH2Tv/jLOa4yyV0xws831d9Tjn5sdzzvUZMk63gHTc0Zw18/kwZ3eA05RJdX8MTi0FVrmS41yczFmpTsVpfj8mr85sIj5F5fyCZJab/KjZklFt/KJmJo47M3PUrM00S1LTtDGp3HF9IoY5hj+Pm7Wa9Hk8oyC/E3R+xmrg/Ziw7GGjEiaHdPcM3nGS34V4oI4WSKFI9KxGxod3H/koDZNAeAQ/fA9K4T+4i12t4d+/g1WpEDy6j+qmTqWps2bw/ClCCFO2Pof/4C7SKxI8eYRaWkGFgdlJdm2D4OF9hO3g37+DXavjf/8t0nEJXzwxERRCpo6oIf7397CKJVO2WiN4eB+SpJ/5Nd2DBqUI8pzlYU6w5+ZSTvp937+DVSwRPH5oONPMr3p1fTSn6xI+f5JFeiTN/bGcQmui3VdTcWq/Y/Z2STnDFxM4l1fTpZwcp2Xj3787xPk0jXYZxXkXu1o/zJlm0h3N+QCCbsZp1etE288QUmScwYO72KVyX59hgPZ9w/noAdJ2Us45/O/vDenTpM4nio6tT7tSIfzhAdrvmHBhkdsjCY1//85s/wgCk5fmk5xYhgfhSVk38wNNLw/JNLMmw0/MRznO5sv3OExyM4GVDl/j+PMS6gI6bWVsXyNCiV0RYot4gGVYJ7G2CfWMUSC9dtIQYUk/RFiSIETvLMFSsclfomOkigdymFiRj1AJMg5BJcgoNPlL4hi0MvlMeiKFSa7muGjbQbkllFMgdsv4Xh3fLtNManTjAi+bJRptyeNnIe/ednnxaIe327vHOsdfhTx7MdvWFqd5H5l2v7uj5KM0TFwRU7h4meLla6iO2a8kaTYoXv3M7K9y5jxJ04ReWvV5hONSvPaZ2a/k+m2S9gHFy9dASJylFVToo/2uccBUisL1W6hWE+/GLVS3S+HiZYTrYFXqCCmIG/u45y6iwxDvxm0TEnr1M+MweXGLqFpLw1uLyErtMOe1zyAZx3kz3afnNkmribd1FY0wnEEXHQY4K+uG81q6B8uNWySdNoWLVxBOjrO5j3u2x3lrkPPClnHmnZLTHst5K8cJztJqjnNtiPM2SaczwIkw0UNu6tB6iPPi5UHOap3i1tXRnJvnsRt9TukWKF79LNsjKDlojOfU4F79jOJB87A+q/2oHHfzAioIJnMWUn0OcXpXP0PHhjNpjNbnLCIQJuHbJzk1GX7SnuSQKdBZCG5+SWfUk/v45QxxqOxwP4fq5JKyjePOt58g02ie0YbJpO+PWsIwBo/sc42RnhEy1AEmB4tOjZGURZOdn0gNMGOMJFhJiExCrDhERj4iiRChD3FsXpMEHQWgNHrIMMHKLfkXE4SKUZaDVDFCa5PtNbFptCXvGpqd7SZ7L95+VEbJceRDvI98lIaJCDoETx4BAv/7b7Gqdbrf38OqVgme/ICOQpNgrbe78PZTsB1Tpj6P/+AellcifPII1W6asNFuF9Xt4P/4EAoe3e+/xarN4T/8FuE6ZpfZXLiwjiOCh/exSmXTbq2G/+P3aEHq/Np7ct4BIfC//67PWalknNnuwrW5lNOm++Cu6fvBt1ilCuGTh6hWI02w1kV12vg/PkQUvLTvOsGj+1ieZ8Jbe5zNfXSUcpYHORH096BJ9/cZzxkRN40zcV+fPc56jvMRqn2A9v3RnPW50ZyNE3A+uJtyPupz5vXpOH3O77/DKlcPc7Zb+D98jygUJuuzsQ9xPPK6I0h3Fy4iPG8C5w+jOVN9zvaP8GnG5LRleMZk+FhPBAov6SLQvBdLKCRl2T5iDmR2GWVoKCSCaPRgP0K0FljC5OmYrW+d9jnax0EjcUSUzaqcRMYleoulAzhEMvW/KvTLZqnn80tp+ujlsl6Stfx7LQTz9j5ztmDjvIVG8ru3LRQLJHqZWEmUlkTKQmlJkFgoLQhiSZwIolgQRAI/hERBkkC7o4giTacT4/sx+2/Ng4dlSfxOSOiHxFFCkiS03jdRcYKQkqAz44zHSeUDvI98nIaJ41K4eBV3/Qyq06Kwed7MDmycRScJ9tIq1rzZeE2Wq4hCgcKZsyQHN3HPnCM52Mc5cw4tBPbcPCoM0VGIM7+I1orC5nmS5j7u5jmSbht34xzCcZClNAx3sYW9tIYKAtzNc3iN97ib51FhiLtxFlkqZ74bslLD3dhEtQ8MZ1pWK5VytgGNLFUM5+Z5koNmn3PjLBpGcrqb5/F6nJ02zvpZsO0+ZyfPeR5vv8/pbJxFzMRp/B8OcW5eMMnIMs4Fs0QyjrPdOsy52MJZXh/BGZyc88y5dPfi8Zz23AIajXsmvZZnz4/WZ8pZ8H3cs+dN2TOG0z1zLsfpHlufM/8vfGBrwx+rDM84TBMBoYU0SwZCZ3u5DByfIg/KNJI3iBJtBkgpFXIKp81Bfj3WwJhm6anfzrCOpnOMnSZ8ebiPjFHk/TMsc3zCU/645bdR59GTXl4YS8RoJK7IlRkzbk+bi2VUvV6vRn/zh46Pa3fcdekdnznBGh/efeSjNEy0UiYpV32OpLFPfNBENfZJ2sZnQ5bKqHQmAilNQrT5Fkljn6TVIGk2UJ0DVLOBsm3jY+L7WF6RpNEgaR+QNBskrQNUo2F8QRoNUGaOMTloIMtVkuY+SSste2Be1dyCYXAL4HmGs5bjbDZIWq3DnOkTeXJwcIgzae4jR3G2mlnfqjnMCclBs8950Bzg1POL4zmbjT5nY3+QEzJO1WyQHAzp03HMrr1BYDibzRxncyKnSsv0OZvo+c50+hzH2TrMmTT3kY5jwsTDAKvgTc1pVWqDnK0mSbOJmm8f5qzPD3Km13YS50wiPu2V86uQzL9CmqgyW8eHllZgspEzi+QHqFjbRMpCWgpbRyYj6oR6esJmeqP4JjnvHtXOUXWOau80w2FP6ng8bdTLNA6307Q/6vi4fC2nESE0WPHDu498lIYJ2uyBo8MQHfgmI2pgclLowEdHISoMzdNMGKDDgCR9zeoEofEtiULzXRiaJ+gw6LcTBKZMGKJDHx0WQIj0fWgcJ9M08Srl0FFkvgO0Jc138RBnOMQJiChM64dD5xb1vw+CHGfaX+onYfwlpuQMfFSvvVGcUY4z7dvoUw9wZueccqqMKUh1F2TnnelzAqcKuhlnr84ApxTj9ZnnzOszPMype9c5bdv0cQQnjOEMBzmF6HNGwSBnFOR0F5gbQo8zMGVmlk95TE5NpnniHb2scXivmuOEpR7FIVCsJ0+RKuFBcpNYSc6WdrGID9UdlkmOr6ctJ50hOs22T6P8qFkkGDQejnN9R3130naOLR/YfeSjNEyE5eCsrGEtr2KvbeCub5qEWGsbJJ029sIKsmB2vrQqVXQU46xuEL/Zxd3YJHqzh7W0ghP4Zho/ClFRiL2wRNJuYa9t4rzexVk/Q7z/FntxCRVFWJUKAhBeCWdpmaSxgbN+Buf1Ds76GZKDBvbiEkiBtF2E64KUWIsrg5yrGyTtEZxhhL2yhrO63udcXMbxu9NzxjFWuWz0lOfc2BzkXFjC7JEwivMs0d6O4Wy1Ruqzz3k2x9nBnlscz7mxeUif4zjttQ3s5n6fM80RgmWlnGcG9TnEKcszcM4vTsdZLGMvLuGs5fS5doZ4Ws6V9fGcq+s4b2ZzshMf4JPOxyz5J9JZBihTRw99Pv4T+6Qn43LzFTLs8s77CW3f4kxRYonDdaeV4+Qnmba9X0S9k858HKf8pBmh48yKTerjF2XQTZIP8T7yURomKvDpPvgWHYZmDxavROebL5Fe0exFkk7JD+yVoxWdb75Alit073yJtB2CJw+xl1azPWiclTWzV46UdL76KVaxTPfe1wgEwYunabhwuldOp0Xn3ldmX52vf4oslvAf3EOHodllNt2DJtrbQQ1zFjz8Rw9QraYJb4WME61NmR6n4xA8TjnTJZKRnHe/Qgh5eA+aHqeb47x/F6JocK+c1znOYrnP+fABqtMa3Csn4/wCq1wd5FxeQ/vdHOcDw/n1T43D6Ek4Cx7xm92U8wtkMXfdf35/kLM+R/jiWaZPq1wxdfL6HLjufU6Z1+dQuLDuts2x3nX3hjjTDfwmcrYPiBv7/b1yctd9VvnQ1oZ/XWTc4HF4JuR09D+tr0Jj/gJCK1ZVh6Rs8lYc3bY4ZDj1ZNSSwTDPLDLJZ+WoeqPZp0uU9suWX0b/0y59nQbLh3Yf+SgNE1Eo4F25YcIxg4DCDRMC7F29CYC7vknSOsgGKFks4V27he528G58ju508K5+hnAc7KXlbBrdWV4FKSneuI1qt/Bufm52nb18zez0PEf4AAAgAElEQVSZUq1l0S7umfOgFMXPPke1Dyhev42OY7wLl4nm5rOB1KrPU9y6is5zXrsFQuCubxK3DtJolx7nTVS33ee88hlYDs7yFJxb19KQ2nQ33INGn/PG56jWIKdVn8s4ozxnL1Q5z5k6Ztq1+gBn4cbtdF+hMZyW1ef87HNzvWbhvNjj9BCFAtHcIt6lKxCGeNdvm7Du3nXfONuPcqrWkKVyjvNzsw/OJM7rhrN483N0qk/heQMp/t0z59FJ0ue8cRudTMl57Vb2+8z0Wa0N6HO2fwQTAvlJTi7TDny/qBmFcb4Kw+UjWUALgRvHaZnpInOO6j/JDQV9Y+vwb8vkGjlsxCjkkJFmjXl/uL3h9z0nXaE1khihFVInpm+dGEdjrRDpe/OdQqjELDf39DcUoaOFRAsLLSRK2ihpoaRDZBWIpUOoC0TaoZN4hIlNO3LphhaNtuSgA6224t27gHYrZG/7HZ2mT2Pv7dhz+1XJ4+fhbBU+wPvIR2mYqDAkevUC4TiEzx9jzy+YRFhzC0SvXgBku/aq9oEp63qEzx5jzy8RPH+MVasTvnqRJS0zPgAR0asXBOUKwfMn2AtLJky4UiV8+QxZqYMUqKbZsj58/hirWjdl5xeJXj5HugWzT0qadyN6szfI+ezxWM7w5QtEwSN89sRwPvsRq1YnevU89UuZxPlkkFMI/n/23jxGtm096PutPddcPXefeZ7uPTeYYAZbYQhGOAJkQxIroCQ4RDwTiShBQRjjRPIfSHEAJY4CQn4KiWyCCEhATGQDMUaRwAG/9+59547nnnfOvfdM3ef03FXdNexx5Y+1q2pXdQ17V3ff0319P6lVVXuv4Vdrd6397bW+IdpPcJbL/Zy2o3L7DOOsjuE8qKvxtOPxnO3nxFerEJHbRgYB/toL3Hwh5lyYjjO5YrK9ibAM1Wd1Fu/5iOterqTn9P0hnOq6+2svCEv7qs39PYTQ1LkO5+wgZy+njzCTnGpcR3PaeC+eZv4tnLb4A2dNOqsJ02y9ZF0tmcZj5ZACIAQRGpqIMislo7kEzSjfF+tk1HfTiCjqB4fOtiMHL0rnDdJxc+7wd76LIUJ0AjQRYcoAPfKxgiZ6FGC6+2i+i97eR7RbCLeJPDhQGcX3DwhdD79+QOgH+AdtoiAk9AJkbLiuWwa6ZWBXChiFHLn5WfRqBeaXcecvUi+e44V7jo19h3/9Xou1Z9u8ePjFFKN5NuW0zSNnUjHRTBNjfhGjOou5tIIxO69sCWbniQ720Wfmurly9HIZ6bqYc/P4SyvKRmBxGX1mDqPZwJiZ7RqUGtVZwvlF9Nl5zMUVjLkFjMVlFSLdbSvXYwGhaalji532VtBn5zEWljBiF1nNshGW3XVN7XIurYznnJ3HX1pW7S6tjOecW+hxLvRzAkRWgnN2oZ+zOouMwpjT6uec6+c0Zuf7OX0/5lTfKcmpz8yidTgrM4QLS11O1Xc6TmNuAaO2e4gTITAqMefMHMZSfN33632cWqmUnrM628dpxGOkV2cx2i0VQj7JubDU45xdwFg4zNk3njNzGDFD2OE0LBCgFTucC/iLy9l+CEKcuvgDXyUZ5ZY5TIbFFBkVyn1U0LZ0TCra7HEpJR2JYjdkQwvUysSILSKd4QqRKXyEno1JG1whifvtGBNHQsc3coQyJBI6mh2iO0W00EcLg26ANdP3MEOfnKciwBL4yChS7zsiNGVHEUd+lfkSoekQOEXaTpVI6JStJlo54t9+p8CtG3k+v77A5us6n7//hMA/eqyWUyuncB45k4oJAPEynYwiFSlQyvgv6r0HpJTqL5K949FAWeJjyN5nGak6UVwmitQxKRJ99Y7311X9ibido3PK4Zwy6nEe4iED5+jxlFEUH5Pd8+pvxHiqUj3OTr/J75uCUw58Zyn7OTsuvF3OmLXD2WMfGLvE2Es5nFMi+5nGckYZOKMeJ7I7zjKK4iamuNmI07U3/FWSZMyIpCSPjY6aejj2xDADR9VWOLSNSX0OKkPTxk2RCPxI3ZgsIkzhYwq/yzopJoiI61iMD+CWNr6HQMUtCYXR22IyCpnaySKd9sp6nYq+x/lz8Ykb8et/vDRVn5MMqEeVGTyXte9p4pictnnkbComYUCws41eLBNsbRLsbRNsbhAsbxPsbCNsp5srRw8Dwp0tgkpVldnbwd/awFw+p8pqGlEcUVWYJsHOFsbsPMHWBuHeNsH2BuH8IsHuNprvI2IbE5HLE2xtECyuqLK7OwTbW+ilCsHONpptI52c4izFnLtbhzlj49fxnFsITXS3HlJz7tcSnMv9nOVqgtMh2NnpcSbGM9zZQnPScsbjmYETAVF9GOcWwfam4txNcqrx9Lc2MIdxjrruuxk4dxOcO1vogZqkw3oNbZBzbyfBuYVmO11OrVjq51zZ7R9PIXqc5QrB5ka238Ep3Bv+qsk4I9g09aa5sXRkmHIzqJQMJhCc1Nfom2CcTDSxRZTWU+Q4PWom3cjTtpNF0nzPLGMwaEw8Sikd1+64OuPKTiWncB45k4qJMC2s5XNYF66oiJpXb+Jvb2Jdvk7UbmOtnCcslNRyerkCkcS+fJ1gdxvr6g31euEy0veVS2gcd8NYWEK2W1hXb+DvbGFfu0lYr2GunEdGEr1URghBUChin7tIdLCPffUm/vYG1tWbRI0G5vI5lcLeUknnhGFgnb9CsLeLde0W/s7WyXGeuzCBczPBeR5hGD1O0+5xXr1xsuMZcxpltUUSFOIoqX2ct4gazYycFw5zXrqWkrPd47w6mtM8pwyru5xXbhIdDB9P+8JVwtpej/PSNaJWSxm/xttYfeO5t5P9t3DK4g+cVcmybZO2vazeJKO2fobdrNXxwytsw9pOJhsc1Vcnz41ATgx1P+zmehxxWtL0labdrH0ci1dLyi27Sf0llZovix1O3zxyJhWTqN2m9fhToiCg+cF7yl32g3fRnZxyb201em64cfZWKVBliiWaH76HZtrKXXg3dsNttzHre7SfPATDoPn+dzAKJVofP1D5C14+Qy+VQWiEtV2iVpPmxw8Qlk3r/Xe7uVOiwD/sLhyGhzmfDHBWZ7rGj2M5XbfHqRu03n93BKdQkU7bLcVp93PKMDjshhv4ND94T7nLjh3P511OI814djiLJcUyyFnbI2o3+zkLRVqPPjzE6W/GnB++h5YvTuYU4hBn+4vHmAvDOPW47wHOpLvwIGe+MJrTH+DM5ZU7+5jxzCQCxoXl/lrSy5f1FJ71qXwwDPmwRHnTLPkPlvMjHV1IdBGgjbm5TwqLnqXvdAbG032nLH0cN8ckhqOszBy1/IhGTt088sYVEyHEReAXgSXUrvs3pZT/87g6Wi5H7vZbKsOv7+Pcvqeywd66B7qBtbRMeKBy0OjFMlqhhH3jNrLdJnfzLWSrhX3jNsKy0WfnII7EaczNIwwT59Y9olYT+9Y9It/HvnYTrVBEKxQBQXRQx1w5DxCXbeDcjl1WL1whnFVGrcJ2MGbmsS5dUZlzD3GqgFtdznwR+8ZtIjfBef3WaM7b94jaYzgb+5jL50BKnJv3lFtvh/PiFYyZWWUsatkYswtdztxtVXYkZ7GMff0WkduOv/8Ap+cSed5hzpt3iTwvHeeteyDleM5bd4kaB5M5261MnM6tu0g/yRkb6cacMsN4Evg9zpv3QNNjzn1AoBeLfeOZ6bfD6QuMdNIyar4QQswCfw+4AjwFfkxKuXuUvk5D7IzBLSHFIUaWmUY6NiZSizDwEVL25aYZd8MfFgOlv+3DCsw0q0Zp6h6nDHJ/WSsXSRm9Una8/5OncR5544oJEAD/jZTyPSFECXhXCPGrUspPRtYIA/yNV8otc30N7+Vz/NerGPMLBBuvELretYmI2i2CzVdohQL+65d4a8uq7Ow8/sYahL6yMXHbICX+5itlw/BqFW9+CX99FaNSxX+91o1jEtVrYBj4r9diF9BVvPlFlV02l8ffWEezrdgNdxPNsfHXV/FeLqo6wzjdFsHm6wHONcW5+WoI5+supz8ff6fqEE5d73G+TnIW1BjaauvB39nqca4uJsZz7fB4bqyh5fOqvdXEeA7ljMfzdYdzDaM6M4FzDW/+Bf762mHO7c54ruG9fDb+unc51f+I93pVufduvIIo6NqYDF53f35pJKcYet2TnA6abXc5vdcvMebm8V+vYs4vDhnPKsHGGnq+gP96NdsvR6DSuZ+QCCH+Q+BngLvAb5dSfufEOksvQ+cL4MeBX5NS/qwQ4i8CfxH4yWk6GLUacJTl9UlBx8atQJzUkn539UMKGq6JbYY4QQOJwDXyQ7mTjONWVMZ9p3E31rTbX+O2SYb1Oc0YvimlaFx/R91GGyonPI9MI29cMZFSvgJexe/3hRAPgfPASMVEStCcPMLJoeXyiFwOLV9As3MIJ4ewbbRcDqSMA17l0Z0cWq6AsG1ELq/KOHmEnUMIDU2IePslj8jl0fIF9FynjqOO2TnQBNLz1A0o0bfeYYnjgghbrZhoTi7mLMRl811OzbaRHU7LQTi5Ac74u9i5mFMkOHO9751TLNogp+/3c+YUZ6dv9f0thOX0mOLv2xvPfD+n7SCcfPf7ao7TG8+hnL2+O5zCijmdHIhhnHl0x+n23ceZvO4dhu54OooTBjhzaE7cfueaWE78exzgzBdU8LckZy6epH1fMQxc9x6nul5dTttR45ngVWVjTtnj1Gy72096EaCd6JPOR8AfA37+JDvJImPmix8Bfm9c7BeA/5cpFZNRN9lxKwPD6k9qc1Kd4U/Iw28gk9ofV8emzQ8av04zN8evvXqH+bLPrfLLQ+22ZK4v1klSHK2NTkhL5ojk5G2BroGtkLELcoQmInRCdBlghm00GWH5DUQYxzEJPLR2A+E2od0iOthHui7hQYPQ9QgOmoRegN9oEQUhUdAbB8My0AwNe6aEkXMwZ6volSrMLeLOXeCguMyL8BJbjTzf+SRi7WWdT/71x6nG8bRJ5gBrJz+PZJY3rpgkRQhxBfg+4DeGnPsG8A2Ai+fOoZfKaHYOvVhCzxfRCyX0QgG9WEbPF+i4dWr5vDIGzcXnCiW1zJ8rqDbyeYRlIi21wqEXO+2U0PJF9ZrLdT8DIKVSIkpl1XexhIhf9VweWSp1DWB1z+tyGoVSH6eWL3TdYrV8Hr04gdM0kbHioziLPc5SWTGl4DRKZdVGh9O00P3eeBrF9JxqjLJxZhnPiZzFcoIz33XfPcSZZTwLA5y5QpdTyw1wFkoJzrLawjNNxRn33eXM5fs5occZj2NmOUGjNSnlQwBxylwJOzIwXyzFSgvAa9RWz7A63Xnk3Llz3eOTnk6P+qScRbGZVHZcQr5pOI3II/fpb2Bdvs2771/m5o0it8qHFSI/Mgnk8BuYJTx0ERJEBr6cfFvRYiNbISWRCOOgaspLT8gIPfIxQg+rVUPz22j1bUSrQbi3S1ir4+7WaK7v0t5rUlut0d51qT9qpvq+hSs2K9+3ROXSAqVbV7AsByM3w17b4fmGzq//s/dp1Q/SDd5XRb42fh0uQogi8A+A/1pKWR88L6X8JvBNgN9y66Z0nz5BAu0nn6JXZmg/eYheqeA+fYL0XZWuHtCrcS4S3VBlZmZVnWIJ9+kTjPnFbkTVqN3C/eIxwnZoP36IXp2l/dkjNCfXy+0SuwvLIKD95FO0YlGVrVRpf/4YiVBbMt0cNOvpOV8+A10fw9nuuja7XzxGsx1aaTkLhT5ONE1t6XSNXzd6nOVqgvNxP2elgrf6fDJnu0203OM8PJ5JI909ZDjIOYP7xROEpg0Y6Z4A51JzDGcnp48KSU8YqnOpOR+ilyuTOQ3FmfFHc+rc/L4sGZwvksqTlFKKEa4lyXnk/v373TKDWwd9fY05N0ombQukrTdOkl45R1nO9zWb/fu/l6Zd5Xf9tgJzxV48kv5VI4EuOpFf+4e387mgZ0yrkKjbeQ01g7ZZAhOadlWFpJ+PQ9JHIUKGaFFIUYYUpWQx8nsh6QERqVD1SenYzES6qbZlNZNINznQLQLdxtdsrprrnC9afN9P38KNdOpti5arsbMvqO9H1Go+m6/32d9rsvliHbfZyvxdT6WcwnnkVCgmQggTNcn8HSnlP5xUXrMd7EvXsK/dVDlYbt8jrO3i3LyL9H2s85cJ67sgQa/OIHSD3K07RAc1VbZew752E2SEMb+slBJXJXOTYaAMJet7OLfeImwcYF+5rrLvVqoAhLU97EtXidw29s23CPd2sW/eU3lgrlyLt0EcNNtBzxUyct6N86pM5rRv3SNMy3nrbfU55rQuXetuK2i2g54v9jjvvKXaHcZZmUEY5slwtpOcd4ncNtbl64hcYjwLKTgBvZyRM4pSc4bt1vFz3rxLtH9IH0/x45l4o5wXQiRtQ74Z35xVdSH+OTAs5OxPSyl/KTvQycuI+WJdCLEipXwlhFgBMgaFSbTPYOyQwzElRhmids5NqyRMazMwziZj0FV4kBUR0bSrtMlRzgU4hj+03Y6ozDjDg8LpKfjT2IFE8f91NOL/O9nGJEUy7Zia+FjCpWjvqzZzcXvLw+yB5of2l/b7pTk+TTmJxo9OFWBt+hWTaRxYJskbV0yEetT5W8BDKeX/mKaOdNu0v/geEmg9/AC9WKL1yQdohSLtzx8TeZ0nUqmyt8YrEa1PPkAvVWg9/AAtl8f94jHmfr2XM6WxT/vxpwjTpvnJ++ilCu1HH6NZlsrFU1K5csLaHpHv0370EVquoMoWy7hPPlWGlMmcKZuvY84P0UvlIZxx4LKRnDncL56M5OyUncSp53uc7SefIgBv/VWCc6M3nn2c3xvPWa6O53zyaDRnuQoCwlqtj7P1yQdjONeRcth1n8Q5YTyffIowrW7ZQ5zQW4F69HFvPEsV2kOv+3ScGX88aZ50tqSUv23kb0nKH8rW6ZuVMfPFPwb+JPCz8WsmpWqUEeaosup1vL3HsPbT3LQHFaNxLNPKYLwMFwtfmjhmgKWlC78+qBwM8yCaZE+T1dU5jUFtst1R54e1O6z8oGI6eG4Y++D1GmccPGrLbth1H6UAJc9NpRAffcUkuwPLBHnjignwg8B/AnwohHgQH/tLUspfGVVB2Db2jbtY5y4qt94r1wj369iXrgICc2GRsKH2CPVCCc3JY1+6RtRoqCfexgHWxSugGxjVGaTvEfkuRnUOKTScy9cIG/tYl6+pp+ELl1WW2VxR3UgbByoORuBjX75GeFDDvnydKAywzl1EK5fRTAth2miVmR7n5avqqT0T51XQzfSc8eoHQNjscVqXrpHb73Ga5y4iSqXJnBLMxWXCxv5ozoP9dJxXhoznEE5nKKeNMK1+zuR1l2AuLiXGszjAeY1wv8NpqNw2Hc7KLFIbGM92yvG8dJUo8BPXPQ1ncjz7OTPLKbX/OEEZOl+gFJK/L4T4z4FnwI8dtaNRk3xaRWHYSsukm/CkG4xEGxvLZFTdSQkHI3QitDiWyeFQ9+NYR53LokylVVbSGg6nHe9hMmksh/UxjmlUuXEK3Kg6adkyyxHmkWkcWCbJG1dMpJT/ipELjSMkDAl3t4mKJRU+fHeHYHebsLZHuLsdh/xWKyZEEeHuNmF1RoWE31NhwaP9GuHuNkKja2OiGZZqb2+HcGdbhW/f2cacXyTc3kaW1BJntF9Hc3Kq3b1twp1tgj1VPipXCXe2kfGS/klw6h3O2u5hzp1tpJ+CszKTnjOXG825u9PHqWmiu0WiGZYK2T6MM+14juPc2SbY3RrgVCsRRBHh3k6Cc1vV7XJq/Zy7IziHjGewk+TcOTpnYjwziRCgn9xPWAjxR4H/BVgAflkI8UBK+QdPrMMUMmG++P3Ttjvqxjh4biJfos44T5nBm/akm+ekG/00Wz/JPsNY4dFEdCjyqyrb/0Q9rQ3NYN1hYzRsxeg4ZVybvdWwyS7Kk9pJu0qTVcmdpq+xcozzyDgHlizyxhWTqSUMkFGIDANkEKrPYaQ+h+o4AJ0yUQhhGH9Wf4QBRFH8PuyV7Z4LIfTjZHCBOqZpqu0oivvs9d37HPcRhf2cYZIzHM4ZBhM5e987GM0pxFhOokHOcDhn1BuXLmfncxgmvkfyu/bGkwSnOp6RMwyhM16d9mR8naMoZojiNuK+h4xncswPcYbDOFX7nXaBRJ9+gjNMcA677mGCM5zImVlOcMVESvmPgH90Yh2cAhkX1n2ayX6cMtI5rnLpan1utZNWZ9KyTOMu3AlZLxFoDB+T0XXTbdlMOp52xWAaOeq2T9rto7TnBsuk2fobt4JyLDJ5Hhlrq6aaGO/AkkXOpGIidANjYRl9dgFzcRlzaYVgYxljfoHooI4xM4dm2wBohRKm56PPLmIuLmMsLmMuLaPPzmO0mxjlGXVjcF30ygzmwhLm0jL+xjLG0grm7hZ6dRbTc+NIpaDZNvrMnGprcRk/fg1ruyr6JyAsS0UBFVqPc3GFYHEC59xSj3NxaQzn8gjOdjdSqeY4XU5rcaWPU6/MQCRHcC73cerVOYQVc+aLfZzm4jLB5mhOY743nubSCsHOZjbO6oxyJ05yzswf5mxk4Gw11VZO4CvO6mHOcMR4GjNzhH2cK4S1vR6nbSMMMzGeSwnORaKD/bGcGX8Jpy7+wNeiZLyioRNJLfVNJcu2yCTFaJSMylicpp6qm/0G2Z+AUKlrQsYtSpVMUI98kt44ehQor5soRJO9950/pERE8UNU0jNHCBCa8srRdELDItItAsMhMJRXTlOU8KRJzSvQDgx2GyYHLcH2XsTOjsfOVpOttV0Odus0avuZv++XJScUx2SsrVpWB5ZJciYVk8ht0/7eJ0jf6+Z2abz/rnLzffIpVmN/wLjwOTKKaLz/HbR8keYH7yEMC/fpY4z5RM6UpRXajx+CptN8/zvKwPHD7wIC7+UztFJF2ZjU97AaDVoffhdh2TTff1fll/n0Q6Tv4Xdy5cQ5aLqc+QKN97+TnvPD7yJMm0H31h6nRjPO19L88AEgYjfcQc4HCNOi+f53epyBr9yFHafn3jpsPB8/VJydrL2d3EMdzkKSc9R4CsVZKNL66AFCaAPjWVOcH3U43x3DuT7AGY/n40+xDkZxvjt5PJ98GnN2xr4znk/RS9X+8fwozXgqzsb77yISnK1Hn2AfGs/edc8kglMXf+CsiUSkWiE4ioxTEHo39sltTGuzkUaSHKPGY5htS1s6NAMnU1+dh3NDKBdgS/PRCbBwcYIGlt/Aauyguw3E5hqycUDr+SrtrT3WH79m+3u7NJ664ztJKXf++A3O/8EfwLv7/fwb94f49oMW//qfnIYAx1+iHHEemcaBZZKcScVEcxyc67exr98mardx7t4nPKj38pacu6gmfiR6ZQbNyeHceUvltLn7DmHjAOfWXYSuq6dYz1XGjotLIDRyd+8TNfax776jXICv3+4GABNAUK9hXbwMYYBz922i/Tq5u/eRgY9z9QZaudqNBBpUZuJ8LW2c2/cJ94dxKsXkWDhtR2WsTXJGIc69+0QHB4rT93Gu3UArVYZz3hk1nqCXKz3OZgPnzjuEB5M431G5Yu68rVyCj4vz7jvpOIeN58JSHLvmMKdz722kO4LzQpJzPwVnS7Ubc0opsc9fGsmZRSQC+fWKyZFk8CY8zLZhcCm/97kXvXRQxnlTjJJxNgz9Xh7jFZmsWz9JyaqkRVLDiwxMLcQQKnrrpDY646Wh7Fk0VIA1pIph4hsOwikjDQtDRohym7zt4Kzsk1+eY+GtGq2tOrWXezS3mux+mD0Y2uLvnGH+5gIL33cbFlcIrAIzhs/VK3m+bRoEfjrPpK+CHMM8ktmBZZKcScUk8jy81Wdg6LhPn6BXZ3GffoZerqpgVVFEEE/8xn4db/UFwnZwv3iCMTOH++wz9LIKbBW1W0Sui3Tb4Lt4L5+i5/PqqXpmDvfZ52j5At7qcxUQDAj360gpcZ9/gV6qxAwzeC+fIQyTYHM9DnmvViJ6nCoY13DO2rFxhvUBzmefoxfKuE8fq0Buq8/QbAt//XWCc7PLaVRneuP5coCzXMFbe6k4nz7BmJ3t53RbRO1xnJ9l47Qs/I3XQ8fTSI7nOM7OeD59gl4qH+b0XLzVZ1OM5xP0mdkBTgfNsRPj+RlGdbbL6a++QEg5kjOznLKsoGdRJnlQjHbv1EbehI9inzKKK+t2TtqyEl3ZmAxZEYHhdgydsQilTjswse0AS/NwtDbaFN8dQAqBpzt4ukPTUg8DzFxXr9cPl6/EfytT9aZkM/H+Oqtcvw0//Fezt5hm1WuaslnqdYyX/9iP2tkbP8I8MpUDywQ5k4qJMAyM5fMYc4tY5y9hLiyp18VlonYLY36xm3dEK5aQYYQ5v4h14TLG4hLWuUsYcwuxfUHsNuq5GLPzmM2msu84f1nZJuzuYM4tIMMQvaBCk2v5IubcAuG5SxgLcdkFldnWXFgEXUezlBsuhhlzXsZcWMa6cPlkOYMAvVg8zLnYz2nMLSCF1uUUhtXlNJLj2WphLCz1c0YywbmckfPS8PGcXxzOOb+A1LSh42ksLPXGc5CzUOznXFhSdeIVHaM6h/Tj7MKzc5jtVqLvJcxzF9ON5/wy4f7+sXFm+yF8vWJyVEljkzHM+LFjxKoMRg/HokgbZCxt+X5miSU8tcowpn1fmgQYR7gRJmOd9P+fdVgjqRFEGhoSU/hdW5G0bac9nqa9QbaskuUaHjaYTefJM8ibfcttzPiIXqlMcgrnkTOpmCAl+B4EAdL3wPeQvqeMGT0PGQREvjIAEr4fnwuQnov0fGTgKa8J31V1Om3E7UnfB98jil9lGNe1VEQ9GR/DU/VV3U4boXpFIDQtwemO5pQSEeR6nL43PWfn+CFOr8spPfcQp/TdBKff44zb63L6Tj+nHxzm9KYYz8CfyIkYHM8RnIDo9N336ioPGt9TnjWe371m0nPTj2ff9faPlTOz/OaLY9dl4JYAACAASURBVHLsMioAVkcGVyuSAdayBFkbJ6PclQ/f6FR/hggYFX21I740CaV+iHHYFlFsetq3LTVsG2lQQilwAw0hJIYIhq4gpY1HMu74tO0dRdJ43UyKK3KU73mc9SY3fLrmkbOpmEQRYX2PsDqjYlXs11U8if064X4NvVjs7uELoamy+zUVp6JeU3UO9gnrewjTUtE/220VS6O+R1ivqTgi+zWC2g7hwQFhfU8pRLGxplYsE9R2iTpl63WC2h76TJ2wtoewHaTv9Dhru/2c9b1+Tk3vce7tHDtnWK93OcN6jSg2vB3OWRvDqU3mbLeR7hDO+l6Pc7+WmVPLwhnn4OnjrO2OGc9ahvHcSXDWCOt7x8aZTQTylOW4OIuSJh7H4I1Iog3dshim5KSJyTEqGFtaGf1kfviGc5hvYDUkoZyMKtM5t+fm+eylxs23XeZrn7FfXMHX7UP1xzGPsutJ40abZgzSlBnXd5qAeCcho1bqpvW8Gi2nbx45k4qJME2MpfNY5y4R7O1hXb6Gv72BdeEKUauJsbQSZ66VaKUKMgoxL17F2t3GunKDYG8Ha+Ui0nXVEnwcuMxcWCJstbAuXyXY2cK+fJ1wbxdzaQUZhejFEgiBli9irZwn2q/FfW9iXb6mIrUurSAMA82yEbZa0h/PGW9nnBTnsuK0r1wnSHCai8vxlpPddXHtcV5X36nLeW6AM+pxXr5OsLudjvPKDcLa3hnnPJeecyU7Z7YfAl/bmHzJMulGMM5eZZydyFFvMGmVkqyRQycpFY4RUClZBFKnnZsh1MyhfWVpe9S5Sds1R/k+6WyKvlyZ9B2PjesUziNnUjGJ2h13YV+59To55boZu41GB/s948KE22jzQeze+sF30AwT9+ljjN2ee2tY26P9+CFC02g8+JbK2/LxA4SmDWTDrRE1GzQ/+i7Ctmk++DZaLkc7dhcOEu7C/uZ6l1Mb5GwcEMTuwkZ1Bu/F06k5m+M4P36AsG0aD74Vc34Aga+MNS1LeZFsbRB1OHP50ZwJ99bmg2+j5QvjOZ+k4KztEbWaqTj9zXWiIDunPmk8E5zaOM4J45m87lHgqz4zcGaT07c3/FWQtE+iUWxnohNmXBl4c9dsNOPopfxhylTn+1y017h0WfJF+wKPG7+FW7ObFMTB2L6S7Wa50aY1AD4J+5VpVmcmlUtrhzTtKlB6OX3zyJlUTDTHIXf7LazLV1W+mttvETYb2LffUq6gS+cwD1QAHK1UQSuUsG/cQbouzu23iVotnFt3ELaNMTOnjDXdNubcAsI0cG6/pXKc3H6LyPewr99GKxTQCso7IzqoY65cACB3622iRkO5rEqJfekq/sycMoK0bYzZ+S6nc1u52I7kzBePzpkvoBUncUbYl66hV2e7nEGS89Y95d57+y3QdMzlBGex1D+ed+4r191bdxCWhTE7Pz2nlCM4Z7orEd3x9LNx2rffJkyO5+wc0hvO6dx+C5nkjAOshY061vIFpJRxBuKYM4qwL1+LXdOd7jjYV64hPU9xHuxj33oLhIa5ch4j5tSLJXXdb95FttuZfwvylD3pfFUkzc1IxFYm6v3wiJw949Hx4ceHnZ+kRIzacjiuaKBpVjxCYdDJseOYEbqIiNBpS2ekl09nq8hA2aSYwkOPAqywjeUdYPhNzMYuot2AzXX1MPBsldZ2ne0nG+x9UTuWOCaaKbj7J26z/EO/C/fO9/Ovot/NB08Ev/x//PqR236Tkj3A2umbR86kYiJ9H//1KsKy8Nee48/O4a89x5ibx3u9BkIjqMdPpK0G/voaWi6Hv/Ycb35BvVZn8V+vKsPDOMssUYT/eg29UMZbe4Exv4D/6qV6qn21il7ah9hmBV3HX3uBV5lRZefmFZOTI4izzIrYvbXHOX+inHq5gvc65kQQ7teQmjaEcw0tV1ABwTqc25tDOf31NYSu9T3hJzn9uQTn+poy8JyCc/h4rqE5eRWwzrJ7nLZ9NM6s41ksKxuTWg00HX/tJX51Bn/1Od7sPN6rVbRcvufWbDv4WxsI28JfVZzeao8TXSes7QIQVWbU98znlQt5FhFfR349KUnzBKolVkrSPv2PWjEZVTeL3USaLaOx7QzYrfa3NzxXTiANXGmjiYicqRQNiaAR5PpC7qt2enFfVGC1AEMLMPEwIxenvYtd30Db28J98pjmq02++BeP2Hn/ZKKsRr7k41/4lNcfrvF9PzPDd7Z/N7/698+2UjKVnMJ55EwqJmgaerGMViihlypohTJ6qYKeL6on0EIBPc47ouUL6IUSeqEYl+nUyatMufki0jAQptl9iteKRfRSWdUrltFyBfWaL6mtuChSx0oVRKFTtoxWLKMXishiSdkZWA56sZ3gLJ0op2o3wSmlOlaqoBVLfZxavoCe5GyP4cwX0IMEZ7HH2auThbPQvX5CKM7OeB7iLBTRm41+znwxO2fxCJzFDifo+SJGuaKudbmiypUrijMxnobrouVLKnBesYxRqap2S2XlJh1fd71QICqr/xujUs30M5Co2A9fy/FKFjuEQWUgXV21SpD8PKrvcasmHa+c8dsBou/1KBIh0AZWiCJ0gshAAwyt3x7D0EJK+uHgZ4MKCoCn5wjzi7SdGbT5a5iX3iYX+bzzRw/Q/DZaowbtFtF+najRIDho4u3V8RttWjsHBG2P5k6TwA1p77qEboi/H6IZAmEKrLKJ4eiUlos4lTyVy4vYC7OY584Rnr/O3sxFfvhqk++7+4P8y2+5vHy6zYuHXxx5zM6CnMZ55GwqJkJDOA6aaaI5OXUzcHIIS0Xd1Cwb6agwyZrloOVUmHDh5NAcR5UxbURO1e3kURCmFS/Fx2VsR5WJ+9EcGxBojo8wTYTjoMftdQKACdOK69gqv0suN4bTQTrel8LZiUiajtMaz+nkjshpxZ/jfDHjOA3zeDjtDJzOFJzHNJ5ZRYrT9aTzVZFp9u3HrXQcXlmZzvZAIFNFVx0lY9sWoJO97Yjhoex7sU0me5FEQiPS7Z5Hjz2jXiuj++20pwFW/DepbEf247/kuUU2WbQ2ud/Nn31+TIuT+xh1fFrbkbT/kz/yo+NGYkRfp2weOZOKiQw8vLUXCNNUUThn53GffY4xO4e3+hwppdpuQYV691dfgOXgPvscc35RRWytzuKtvsBMRlQNA7yXz9DzRdznn2POL+E9f4peLOOtPY+X9OMtEgTei6cYlVnc559jzC3gvXyOsGyCbqTSnFrSNwzFObcwPWdsqHlcnJrt4K+/SnBu9jgHxxPZl9NHcdqKcyEr5xcx54uut8vU45mB0+gbz+dDOJ8nOBenu+6b67Hy4YznTF73chV/rceZTcQb3xsWQvwB4MeAvyGlfCCE+MZg1tGzKMfhJTPOBXhabxVLpLetGOcqPEwMEVLUD8ZGbo0G2owQ3S0gPbECMkyO24jzuMoel3dLWpfitP1NWy+7vPl5ZFDOpGKimTb2hSvYV28S7u/j3LpHuLeDff0Okedjnb/Ud4NC6DjX7yg3z1v3CGp72FeuQxjGkUBVPAtzcZnI87Bv3iOo7WLdvEN4UMe6eBWEQC9XAOWdYV+6gmw1sG7exdnbxrl5Vxl4XryinoAtO35Kz/c4b94l3N0+GqfrYi4sTeBUWwLjOK0Ll9VT+jDOYeNZGsJZ31MMe0fkrO9hX8wwnlduZOZ0bt1T45GK8y7hwf7Jciavu9a77pnlzU8ofwr4L4D/VggxC/yWN8xzbHLUWBmTPC6y3GgidKI4dsqkwGpJEUh0EWKIw3X6YmJIEeetmSaGyvFsA0zaDpvMMdnLZXD15qgeLcfRzrCAd5PaPL4YJrG8+XmkT86kYhJ5bdqfPUJGEa2PH6AXizQ/eoCWK+B+9gjZbvYlx/NePkNoguZHD9CLFVofv4/WyfVS21Vuo65LeLCv3HBNi+ZH30UvlWk9/BBhmngvnqLFiklU3yPy2rQefoTI5VXfxZLKpCsl/uZrtHjZ3t9cn46zVKb18QM0J3eYc78+nNMw8FafK28XIYjqtQHO78acnwLExq+TOD9Fuq2BLMgx58fvo5crPc4vHo/hfHCYs1Tujac7mbObBTmKaH38vnIBHsv5fCSnWd/r5h86PJ6VlJyJ6w7KXdiysnHGOYY61z2LSCGI3rzR2r6Ucg/480KInwW+/00DHZccd6yMrGWSEkgDT1pxLppsikleazIsVHzaJ/xx0smxMyyR4TRylJttGnfjwffHsTJ21HZGGT5/Gas8cGrmkT45k4qJZjk4t+9hrlxEei721ZvKbfTqjV7m2IYyutIKRfRCCevyNWS7hX3tJlG7gXXlOsK2MCozyDhkuF6dRRgGzrWbyFYT++otpO9hXbqGlsujFVTOlKhxgLG4jJBSlW00cK7eBCmxzl3EqM4qWwTLQp+dm47z6i21snH5GsIyE5w+enVmOOfl67F7a0rOyszZ4jRNgrn5fs7mSXDeRPpues4owjp/aXrOYrnLmVnevNHaLyfe/3Vg9U2BTCvj9vKn2edPs9KS9mm4814XITZud0VjEvOgTPtUL9FoyRxBZBBJgXZMCshgH9NwpbHpGVUXDo/JoLt1GqZRKybHtRIzrK1xnFO7ir/5eaRPzqRiIsOAYHNDubxurmNureNvbmAsbuFvrasbQ8dt1Pfwt9bRiiX8jbjsxjrG/DLB5gZEsvuEj9AItjYIKjP4m697ZWfm8Tc30F0VZyKs1xGWjb/xGn1uEX/zNcbWigqsVij2BVgLtjcTnBvpOTdfj+EUR+bUCyXlhnuWObczcI697kfk3NpAL5aPhTObCKI3bLQmpfylxMf/G/glIUROSjmFlvVmZNxKwjT7/MNuIsPaGXXzGta/ToA+5t4xWEe1rVIpDEqWLQ8APzJxwziia0bFRFmdDCYA7Pfs0WSIJkMEsvteDz20SL0KGaL7bUQYoAUuIvAQgY/w2hCGyk4sCsHzkGGIDEOIoj7/Z2EYoOuIXB5hmEgnh8wVCAozeLkqbatEXZulEeZYrZeoNXQef+Gxt9vm1bMtXn/+MtP3fpOSPY7Jm59HBuVMKiZArOGJ+LWjJfaOCU1DStktJ0RctvPXaePQ8c45rde+ED2FsvM+eVxoqn0EQmjD20y2nYZT07JzQmrOkW32ac7HzTnIk2A+ac4J113K2G0OwWH7vYHZXQgQKl6DiOt2ikgG0OjMj3GhTlkh6OTgUfcPMfQmMklOmdHa9wN/FvgNIcRfk1L+4psGSiOT8o8c5el33FN0NjuOw3UnceW1Zly2XxE4DtuKfrbh/7heZLDjH3aBN7UQXYQUtX2coEFp9znmzhreo095/a2HPPm/nhL5x78yM07e+dNv85PRX2Zn7fGX2u9pkVM2j5xRxUTXMeYW0KtVjLmF3t/snEriV64qDRmVqt5wXfSZubjMvKpbqWI0F9ArM8jAR3NdtFJFlZlf6GtXK5Ux5hfj/CaC0LTQyxWM+UX0bt/zGHM7qo0wjJf0ldvWWE7TVHE8joWzckyci+k54790nIsYcxvHOJ7HyDm/gDmn/oz5RYytRbSyOq7HWznCtFT9uF+zwzm/cJhTCrTKDMb8Iub8Av7cAsbMLOH+InqpCoZ6AtVzBYx5D31WcWYSIU6Vm5+UMgB+TgjxC8DPCCH+DPCTUsp/+YbRxso4pSR5/rj6GZQ0SsIoZWmUUqVeJyfCC9GJpIYuQjTRby9xlAiyHdsTT6oYJ5qI0ETU9dzpKEsSgdQNpGmjFwvkZovM3C+x/V596r6nEWemSFmW2Fnb+FL7PRVyyuYROKOKifRc2o8/QQa+MtYsFGh+/F20fF7lImke9IwLqzN4L56BjGh+nDAqtR3cp48x55eIYtdRc2lFGTJqOs0P30MvFml98j5C1/FePusZQe7XiNotWh+/r3LlfPgeWqFA69FHyDDo5kxREUDX03HGxpqK87vopVKC8wnm/OKXyFmk+fGDKTgnjWdpOGdsiDod5zTjOZxTaEbCmPh9hDHIWSNyW+qcY8dGukXajz6GMDzEaYeD41mYwJnR+JXTFRhJCHEN+IPA7fjvBvC/CyFM4KmU8ve8Sb5JMmyvPosdyCSPisM5c6ZLEjdJKRnFl/yeHdZmmCeUOmWjfsh+JVkujSSVDYAI8CMdUwuxtZC83jrk7uwaedzZm4iZG3D1BxG/T7ICnJdxoMTEq5ASIUOEjOL3KuaKiOJAc1Ev4JyQA2MvNCSaygkj1NZFpOmEukUoDJqayc+IgFBeox05+NKg6dv4kUbLMzhoa9QaAj8A35e8XG3RPHDZWa+xs75Dq344kNxZkdM2j8AZVUw028G+dgvnxh2V2+TOfcL9Ornb92NDxMsq1LuUGHGeldzt+0TNBs69twkP6ji37oKmYS4sIdstIs/FWFwGBM7dt4kO6th331F5YK7dQlh27C4MYb2m3EZ9D+fOO0T1Orm795Gej33tBnqpHIdQz6GVK+k5bSfBeZ/wYP+YOP0UnFWcG7djzrcJ92vpOO++nYHzPlG79RXgTHPdp+PMKqdsb/jXgJ+PX/8m8Fm8ioIQ4vKbBMsqRzXGHOb+OahMHHV7KK0tzKhVIImGrXmEHXuUEWUdzUWP3Y1HBXezdR9DBGgi6iomGmBrqp4bmti6O3I1pnNj7Co18daCxJ64opVsb1oDVIkW2/EEWLpSnuY6d8fCkAr3kx8qQCWzYXTagGxZZZoAa6dsHjmbiknkuXjPnyJ0Hfez76GXq7SfPEIvVVSG3jBUbrhxICtv9RlYFu0njzCqs6pOsYz34gtks6GenN02UbuF++wzlTH2s0/RZ2Zof/49NCennpzjG1RUryHDEPeLJ+jFEu3PH6FXq3gvPkeYBv56/OTcCbSVktNffd7l1CtDOD31hB+1W3jPY87PH6HPzOB2OLvurUnOx+jFYo/z+WcIw+g94Xc5NdVnZSYb5+ejx/NYOW0Hf3sMZxSplQgpCWu7ceCyMZxjxrM9ijOKetf9s09Hc44YT/fFF/3jOcCZTU5dYKQ/IqX8aNgJKeWzLxvmuGRSrIphSkjyXPImnPbGNW5VZBzP4OpNkmGY8mKL1kSPEku4WMI9VCYpjuZii9hIPDZ21USEqYV4kUE7NAilPtKOKk101GHfdfB4GsVv2PiNajt5bpIikdUwelQ7k1gHyx49lsqpm0fOpmIiTAv74hXMxRXsKzcwVy7gXL2BuXwe6XuYi8uEJaVE6MUiQmhYS+eJ4jL2lRuYiysQhugzs0jPJfI8zJk5pO+rMldvYi1fIKrXMReXQQhlEyEEUbmKsbhM1GxgrVwguHIDc/kCUauFtbiiwp5bZhwFNJ+eU+txWivnCXdTcF65MR3n0op6uh/GuXz+9HLmJnDGGYv1YhGh61hL5wmvZOcMx3E2DhTn1ZvTcybHM8GZRSS9J8tTIr8ohPiTUsoP3zTIUWVwpaPzviPjViGO46k4jdHsOCPdLArRqJv0JHaJhqO1MU21WgKwH5bwpdFd+fAjHSkFhojQRozftLY941aoJtXLstU2WG+wz2GK6TjFZpxCNcg/Sjmd9L+YRU7hPHIE66ZjFCHEDwshHgkhnggh/uLEClFE2Gyo4FitBrLVJGw2kW6bsNlUT8GtJlGrQdRuE7aaKqhVs0nUahG2mkS+Oh61mkTtFrLVJPJcomYD2e4dD1tNpO+p/trtbn3puUStJmGrRdRqqm2BZtxGq6HabrezcTZHcDYb/Zy+d8ycrZPhPPbxnI5THcvCqV7fBGfGH47aOx/z9yXLTwB/Rwjx5w+jin960p1nnkeGyDCFZFy5YTeScTfMYTevYTfTpIIz7ml43I143CrAMO5xkmRN8ugEWMJFZVoW+NLAD42u8WtHQdGFHBqELa1SMm6sOsfTrhgMKgGDisKoFYrBMsOYk+dH/S9kUbgGP6dZBcosxzCPHMdvLylvfMVECKEDfwP4A8BL4NtCiH8spfxkZKUoImoeqIn9YJ+o2SBq7BM2D5DNA3VjaR6ABGGayOaBulE09lW9xj5Rs0XUOCDK5ZBttfWgFUvqWLNJdFAnbByo9ltNtfQfu8bKzo3tYB/ZUO2FjQPVdrtF2DhACxyiKFJsR+VsHhDl8yk5DwY4Wz3OTtmhnMcwnuM4G3GdoZwH/ZyNgxScByfEuR9z1idzphrPbJxZ5ST3hoUQfxX4I4AHfAb8Z3GU16Eipfy2EOJ3AH9LCPFrwD8A/i3gB4BXJwbKlPMIow1Ju+1OWO0Y9TQ8qm6yr3ErMaOepsc9OY/iG2XIO0o5GXZzG+RKuyIj5eG9m0GeSVsyo1Yyhn3PUVtY02zxjFtVOaqMYhp2vcatwB0Xz1HmkWl/e+NkomIihPhV4M9LKd+ftpMJ8tuBJ1LKz+P+/k/gR4CRX0oYJubiOcylc4Q725gXr2BurWOeu0jUbGDOL6E5eQD0YgkZBJjnLhJsb2JeuIy1s4m1fA7ZbmPMzRP5HtJ11fvGAeaFy5hbG1gXrxDWdjHml5BBoEK9A1G+gLmwTFivxX1vYF28THRQx5hfBKEhLAvNchCa8YY5lwjre18SZwtjbmE054XLhHs7p4BzwnheuEK492bGM6scV56SEfKrwE9JKQMhxP8A/BTwk6MKCyH+MvDHgRbwAfDfoQxhf1hKedIRYTPPI3D45tU5NqlOUrLs8R/lRjLpybnDoFyATQwRMCwU/bg2hh1Pb1sjsTWvm5cnklovMBvwE3/uewD81D/5xsjvmFX++3/vm932ku9HlZnU1jD5qX/yjb5zyc/Jvied++E//oP807/7633npmUabCNZLnuAtSPPI1P99sZJmhWTn0TFJngK/CUp5XE/+ZwHXiQ+vwR+x7gKkdum/fhjIt+j8cG7Km/J+99Bsx3ljtk46EXW7LhjRpLmg2+j5QuqjmHhPn2MsbukIoB23EafKPfWxoNvoecLND/6LkII3JfP0Etxltl6jbDZoPnhewjLovHgW2i5HK1PP0QGQV/W3mBr/exx5gvDOaXsurfKMKLx3rcU54PvgGHifv5YJcSLOa3lFVrfe4gUGo33fgMtn6f5wXuHOWt7PU7TUmU7nL6Pt/4KzXG6OX0mcqYZzx3lfi1dF3NphdajT0DT1BhN4vzgXYRpDue0na4x8TScWUQiTnTFREr5/yQ+/hvgP5hQ5ceBd6SUOwBCiAXgfwX+mhDiJ6SUJxmcIvM80pG0S+xHqX+UPrLW8aSFH5kU9AYG/pHbTKuoCSIKWs+zzJcmXlQZumrym1E6Sslpk2OYR6b+7Y2SiYqJlPI94PcJIf594J8KIf4h8Fe+7JDTQohvAN8AuHjuHPbNuzhXboLv4tx5m6ixj3P7bRACa+UC4YGaA/VSBS1fwLl9j6itXHZlq4lz867KmTK3QOS66sl5fgF0Q7XXbKhXz8W5cRuRK6DHT87hQR37/AWIInJ37hMdHODcuQ9hhHXlGnplRj05Ow7+zOzZ47z9FtFBfSSnXiji3L6HdFs4d+4TtZrkbt5DMy2M+cOcubtxmTv3ka43nvPufcLGAGd1tsupZ+DMNp66+i7NFJxhRO7uO4SNxmjO2bmpOLNKivgD80KI7yQ+f1NKOfoxbLT8KeDvTShzS0rZ/RJSyk3gR4QQP4FSbO5N0e+xSnIeOXfuHJDdrXTSVkCassctyb4s4WFoQZ+x6XHxTNpWaEQF5X2DWjH5WinpyR/4sR/gV//+//emMYbKlziPpJJUNiZCxQd/hIpN8JeBPy2E+Ckp5d8+BoZV4GLi8wWGJAKLB+GbAL/17h0ZvF7Ds2zcl88xZufxVl9gzM7jr6+BphHWaoDEqDbw19cQuTze6nOMuUXcl8/Rq3P4r1aRntd9ciYK8V+/RC8W8VafYczN4629QC9X8F+9ICpV4pWIPdAE3upz9MpMr+zrl2i5HP7G68RKxMbp54xzu0zL6b18jlGdw3+9ivQHOVfRiyX81We4c/N4r16gV8Zz+qvP8I7IqVcOMo6n4lRlJ3CuPUevngxnNhFEcuKTzpaU8reNbEGIfw4sDzn10508OEKInwYC4O+M6yiplAwc//nY5uQkJfM8cv/+fQnHt3pwHErIoHFs2i2iZDmDiEkr82m3nTptj+ozWU4icCMLPxx+W/n5/+kWedGAn/vloeenkb8N3faS70eVmdgWQ773z/0yfTe6n/tlfrEzfsm+J53jGf/pD5zvlksjg0yDXIPlYJo4JkeeR1L99rJIGhuTXweuAh+jnnp+HPgU+K+EEP+OlPKoG4bfBm4KIa6ivsx/BPyJsTU0Db0yi16qYMzOo5erGDNz6OVK97jKRQJasYxemcUoVzFm5jEqVVWnpI7r5QrCyyFdF71YwqjOqrDjsypsuTEzp8pWZ9GLpV7/pTLGzBxGuYIxEzNUZ9FLZSLXVTcoy0L6wdngDMKvFKdeKhM1m1Nwzr9RzizSze1zBJFS/tC480KIHwf+MPD7pZRTJzCRUj6Ztm5KyT6PDJFJrr5pXIE7kmUVplN+Gi+OtHE0Bg1vp+Efb2ty+OYmhDzSqsmoVaisHjid90neUXJUO6GjrKhlcZ0+rhW5Y5hHjuW3l5Q0KybfAD4ZMin9l0KIh0fpHCA2rPuzwD8DdOB/k1J+PLaSEGAYoGkI3QDDQBgGQotfdR1NN5CA0PXuMXQDdEPV0TTVhm4g9BCp69Apo8WZKOPPQmi9NhAI3UBouqpv9PpX7avj3f6+5vyaMwtnRolO0ONfCPHDwF8Afs+o1ZAhdf5dKeW/6LyeGNyATDWPZGn/GONHDIuPMezcOG+cYe0MW20ZJ+POp73phajAaR1DW1MEoEMQxy/pSETsoZPx/jfIMKisTfKmmnS9Jik6WQ2ax5Uf9V3StDvseFoFOY0cZR45id9eGhuTcR38oaN0nujjV4BfSV0+CAg2XqHlHPxXLzAXl/BevcRYWMLfeIUwdMJaDSkl0mvjb7xCyxfwX78kHoGOLgAAIABJREFUWD6H//olxvwCweYriIKu26gQAn9jDaNSxX+1SrC0ospWZwg2XhMVSyA0wvoewjTxX69izs7jv1rFX1om2HiFXigSxBFAheMQbG2eMOfLDJwvR3Nuf1mcq4c4o/3aV5BzayxnsKeMX/s4X72Y8J8/KOKoTzqT5K8DNvCrajeXfyOl/DMT6vw14LcmXr80yTqPDJO0ise4p+9pnqjHrXqMUlSSN99xys6ovtMoPOOe6iUa7cjhIMhTMQ+wRZuSvk+Izo5XBaH+QxEgo/Q3vuPyXErT7jRGyeMUjLSrbWnbztr/dHL0eeQ4fntJOVIck4570JctmmVhnruIfekaYb2Gdf0Owe4O9tWbSM/FOneRsBgnSStXAYF99SZhbQ/7+m2C2g725avIIFSGj55L5LqYC4tEnqvK7G5j3bhNeFDHungZEOjl2AiyVFZuos0DrBu3CHa3ca7fIWo2sc5fRFh21whSWI7irO19zTmKs/6bj7NjUDvImUUkysDwpERKmS0Ubb+cCavHUTE1ksfGlR92fNy5weNZFJhBRWQU4zjmQddoV+aQiDjk/HBxZY4gtkEQQpIbEsa+HdmEQkWC7WMespUzbntlUvySSd9xWL1xdYaN5WA/4+K6pOlv3PgPtpVsb9LK2TCmcWM0Sk56HplG3niAtWkkardxP/sUopDWh99FzxdpfviuynXy+KGKzNmXvfUZIGh+8K7KcPvhd9EsG/fpE8LaTtcNN6zvqSyzhpHIhvsBQjdwXz5VtgEoI8heNlwnzoYbZ5mNIvzYvVXYDsHWuuL86AF6ofQ15zDO/VPE2Sn7hjizygmvmHzlJe3T57gn6zSeOpNuGNM89Q4+qaexTxhUbtzIIpQ6puGNvEG3I7sbj0TXIhyjjUbY14cbmngYWKbXF+E1mXFY/fWirSb/dyN6YexlHNJexWRR5SOpykspiNDiV4GU/edUW4dFQylJAhWB1tRCNCJ0EWKIUCXvkwF65ON4+2hRgOE30d0men0bEfjge4Tbm0RN5ZAaeR5bH36O33Rp1122PtqhvT7cPfvLlHaYPS3VaZtHzqRiotkOzq17mBeuID0P+/odwsYB9rVboOmYcd4VIolWKqIVSthXrquMsXHGV+vaLYRlYVTnlCeJ72HMzCEMA/u6KmPfuEPk+9hXbqDlC2iFIiCIGvsq5wqQu3GXqNHAvn4bpMS6cAm9OoMwLTTLJpid+5rzq8rZPH7ObCJO3ZPOWZTBJ9rk+2lsB4adS6t4pDG4HcaXpY+k5PUmkdRohAU00YtDMkmhGs4pYo6eYtJxHTZERDNwaAuLdmjhhTrrNZtaAx4/abD6+Sarj99snsefffbnqH2SPcP32ZfTN4+cScVEhoHK5JrL46+vxXv3a5iLSwSbrxGmSVjbBUD3qwSbr9ELRfyNNbzX51SduQWCzXWIpMqZ4rYRCPzNdfRKFX/9Ff7rV/jrrzCqs/gbr1WgLSDcr4Fp4a+v4c3M4W+8wtxYUWUKRYL1Vwg7Dgi2td7HGWy8IjiFnMH2Ro9zfolg4/UIzpk3zLk5wJkcT6O3EnFSnIbZ41x/hbnY4SyNvu4ZODP9DoDolD3pnEUZtmpylJv+Ubw/JvWdxQYmqSgMbiN0tgoMIiKhE0q9t2JxDLYQnS0cTUR07UziG6Afqr+2B42mZG+7wc76ztj2vgz5zamUnM555EwqJgDCtJSXhGUhDFN9NiyEacaeDhZIqcqYZqJMXMc0weiUNZFRpN53y5oIo/M59r4wDECo87oet2f2+jRN5YXROa4bhzgxzePnNI0jc9Lh7fRpGiM49TfH2fGE6eNMjqcxBWeYjdMwRnDqfZx91z0DZyaRp29vGDiIX7Mn/jkFMo0x5Kg2jlo/i2vssDLNKI9EUNAafbed4zDATCOWFlAxaoeOz1mK5lpJ/e/+oXcMQnmeCI1Q6gSRhhcZhJFOO1CfW55GEAransD1wfWg7UYEgaTVjgj8CNcNicIIzwsP9Wk7Boah4eQMLFNjtqpTyEG1GDKbdymbTZb/yt8l19zC+vRd/K0tdj/5nGf/6in1R9kDH54pOYXzyNlUTHQdvTqLViqjVWYxKlX06hx6qaReiyqEOIBeKBFV2yqGRHWuW1YrllQb5Qr4HsJzEYWiiltRnlHtVGdVmXwBfWYWLV+M+9cwOjEuqqo9ozqjIn/mC+jVKsKy0UwLPQpPnrMy86VyhpXWm+MMv9qcWeW07Q1LKX938vWrIlmMTdO0NckmpdNX53MY22Bo6vZ9qN5w2xfRZ3g6aLA5LeNhTjny/3Bcrh49rmLixSsqcZsnkGUhjTtwUy/TtMrwO6+pk38YLvyFk2M5rjgkg+06P/pHp6h7uuaRM6mYSM/F/ewRRBHtTz/EKJVpP/wAvVCMjQsbcWRNMKod40JJ+5P3McoV2g8/QHNyuE+fEM33cqbIpQbu44cI3aD98AOMcpn2o4/QTAvv5bPYO0MZlUrPo/3oI/RcXpUtlXG/9wlCyl4OGlvlTBnG6T55iGw3u26jeqWicqYcmfNpN4DXcXEOjqf74hlCEPedhbNyOjifPSGaO0bOxw8higgSkV+n5cwm4pDHw9dyMnKcN5BpPHFCqeNJC0c7bHiaRsbHThkSGK2vrDzkXXOc43GSbU5qe1pj5uNgSevBk6XdabxyTuM8ciYVE812sK/eJHfjNlFL5YoJ63vkbt+DMFBZbGt7gFT5YEyL3O234lwxbxMe1MndvANCKFdR10W2W5hLKyAl9u23iA72ce7cJ2y1sK/dRJgWRuw2GtRrWBevIH0f5+595bJ86x7Sc7Gv3kDLF7sh6bVSZThnFGKdv4SR8M7QLFtxNg5wbr81grONubScklO5vI7ldByVeG4CZ9KLpDuemTnfJmw1TxnnsOs+ijNx3e+83c957SZ+oTT5uo/7/2wckEVOg5ufEEKXUobxe0tKmT216RuUce6qwz6PayPZzqjzw8oMc4sdLPP/s/fmMZJsXWLX78aea+1r7/vyuj/bM54ZGQsh2wMaEPAZYSH4x4xBGtvCsgAjo/HIGAksg23ZgwQCRuYPbA2LkSXb0ngMHjMYLGP8vfe9fenX3a/X6qX2zMrKzFgvf9zIzMisiMyIrOr3qsbvSKWsirjLL05kxT1x7znn6iLEEV20BOe4NgdtC9pRGUOE2KI7tmyWlLQOlubTCkpHzgkxMFqyBres65omjLpIvpWs/o+bgyYrfHeSoZH3Wqbhylsmvd53/xwZlTNpmESui/f0EQhB96vP0at1Og8+R6/WcJ8+Rvo+QTPevbU+q/YgMUw6X3+OPjNL98Hn6OUq3tNHRIcHKtFWt0PUadP95muE7dB58Bn6zCzuwy/QbRv3xVOC5JtzEOB+/QV6uazK1ut0v/kaNE2FjdqOSrS19Tad88kjpOelcz74HL0+jvOQ7uMMzpfPCKr1BKd/spy93XB7nDNz03Ee0ee74HyWzvns8dH7npsz/b5Loamkf5M4R7+fI5yF/xdO4h/qePLnhRC2lPKPAf+fEOIPSik//a6hikjaTEJaXoxx9SdF06QNaEkn1ElldYKhUNvRvrNEIgji8FtbjJk5EIOwXhKDqSDCFB46IUIMGyZ5387HDbh5j6WdK2KgpM0YpZUtYiRNqleknbwO1+OM1+PM5JyC58iQnEnDRFgW1pUbWOvniQ4PsM9fImjsYZ27iIwijMUV9Ll5kBItfou1z10gPGiot9WDBubaeSTqzVr6PtL3MOcWkDLCOncBp3EX69wFwsMW5toFMIy+r0HUbmEsrhK5Xazzl3D297DOXyKKk2eJUjkOG7XQqvXpOM9dPL2cVoJz/SLhzf13xOmdXs5zF3FuDjjtcxfQyj1Oe2rOItKLcviOZQ9w499/AfhVIcRflVL+xWQhIcTflVL+3LdON0GyBqK8b6dZ5ScZGlllJw2ynrQJ0eLZk3DoGo4ObNlbG6W1HUidRjCDpXmUtXZqGY1kjpKEj8mYpYBx+VXyDvyTBuRxM1+TfGvG3ZNx92LSPc9zPWnXkXUN49qfFN49nuVUPEeG5EwaJkQRUbNBNDtH2GwQHDSJmg3Cw0PCZgOtUiU6aIKUaifXZoPosKXKHDTV3x31t2aaRG6XyHXRnRJhs0nYOiBsNghbB6qfTpuw2YBIAoLwoIFWqQ+1Fx4cEDabRPNtooOmirBwnOk5Y4bvhLOVwtmMB80jnAX0edjjPBzmbGVxNr5jznY252FriDOcOyx23zM4i8opWBv+aeDvAUgpfySE+Bngf4h3E/4bwG8D/hng9XeHOL1MO6iOG3SSobwSfciAmDSw9QaR3jb1aYPVdH4G6jEUoGHkqJ927RHDTpQRAl+aR+pG6EQIgsggQsMLDfxIxw0NOp5B19dotgVdF3b3Q7rdkK23LTqHLvtbDVq7Dbyue6TdImKXSyxdWOHq7XXu3rC5stTirvdjSq+/5sVf/Rt8/b89OVb736VMlWDtu3+ODMnZNUy8LtJTPgLSc/s5KaTbjf+O11M9V2X49DxVxlP+D9L1Bm24vTIu0o3LuB2k6xK5HaSn2o1MC6FpiT46cd1O7Eip2oi6XTQpkZo4JmcnH2f3hDnjjKhDnK57fM5Oj9M9Qc7OGM5OzNk9ec5ud4hTxv2k3/ckpzuGs2CCNQnhd/xAkVL+q0KIOQAhxH8O/FtAB/gE+NPA3wd+Tkp5rG3Q36WMexMd55OQx6cg3XAQ+NLq/24IHyPjzTzbMJJH+klnVBEzgwys+WaERq8Hjs6WSDRlYmV8BYNIZz+q9/+OpPKQ6QYmfqixc2By2IUXGx7bm4c8++obmtt7ubiOK267w8sHT3n54Cn/N/CTP/s7+E9b/zN//8/85rfS/6mSU/AcGZUzaZgIw8RcWkNfXMFYOYe1fh5/8zXG6jph+xBzYRnNLiElGLWa2htleQ1zdR1r/QL+1ib64jJmt4sxN68ygHoexvwCYauFsXoec+st5vp5gr0djIUloiBAr1QRgHBKmIvLhI09zPXzmFtv1LT9QQNjbgEQaJal3p41Y5hz683Jc547T7BfkHN+cQznBfytt6eDM9ansEw00y7G6Qcx55spOReJAj+nPhdAJDn1AefaBfzNMfe9z7le6P/gBLYrPxGRUvZGk58HfiCl3AUQQiwBfwX4i0KIPyylbH5HiGNl0iCdZYCMJjBLKzvOsElrc7T8pJmZNENj3JT+OF8IIdSsSVrZcZE7PYOl99YtkFSMjnKIHfl+SgRlwyOUGlXLxAt1VuZMOu4se79tjp3dkL09l1fPdmjuNGls7qRex0nKnZ+5y+/+qSqlzu/mJ/+DAz74y++/8z5Pk5yW50hSzqRhErldul9/RuS7tD99H61cpv3x+2i2Q/fhV0SHB4SNfaSUA2fNKKL98fvolaqqY5q4Tx9iLK0iux2ibhdzZY3uoy8Rmkb7wx+hlyt0PvsQIQTuy2fo9cQeNO1D2p99iLAs2h/+CK1UpvPlp0jfV1lpbbu/Z8oQ50c/QrPsPmewr57pxuwc3otn2ZyLK+rt3XUxl1ezOTeexXkytKk59XKZ9kfvDzhbTYI42qUQ58oa3YdfDDhLMaemqT1oTpLzUQanlDFnLb8+k5wvnqrMrxM4I99P7C5cIth6Q+R7irNUGnw/Uzmf9jkL/y9Ep+qBclNK2c9GJaXcAn4ohPjDwD8G7n5nZAUlLdLm6GyGGnj1RPhumi/EJMfMZD9ZMybDPPLIuSIzIKO+MWlGx2j5vMcBNEJKogNi1LgZqdMbfSrpfFBG4BRiy4qYgaP3YfB5gKDBa34X/JHfxd2U/bOzInuS7Y7jy+tjlOfvtH6SHNPkMTllz5GzaZhotoNz4w7O1ZtIz8O5fZ/ooIlz6x4gsM5dIDhQL2dGrY5WquDcvKv2NrnzA8J2m9KtuwjTwFhYVks2vou5uAy6TunufaJ2C+fuD4hcF/v6bUSpnEhN3sQ6dxGiiNKdHxC1DijduY8MApwr19Fn59BMG2HbBHPz+Tmd8qngtG/fI+xxCoG1HnNKiVGfmczpuURezKlpA873ftDfxVc4paFU79a5S5M5nQmca+cJWgcZnPcJ24dHOd0u5tLKsD4ncYZhKqef5JydG3DeuU/YOsjFWUzU0HJaJGmUjBz/72OfkzMjWX4lSdHGlMkzIOXpN8/sR16jZFzZLEfZrP6Tjq/DET3Z/UwabIs4j07qY3QGaVyZae9LjzlPnUnGSx4H3LxsxeV0PUfgjBom0vfwXm+AaeK9eIIxO4/38inG3Dz+mw3QRD+fRTQzi/9mA+E4qszCoqpTn8F7vdH3DYi8rno7f/0St1zBe/EUY35JJVar1vBfvSCszYCg76TovXyKXq/HZRfwX79UybW23qBZDprj4O9snSynG3O+epHNWa2DJtI552JOp4S/+Xoy5+sNEAnOwwP8Ny+n5Fwcwymm4JwrwLmUfd+DoBjnxjOVEC/JmbzvJQd/O4PzjdoPJ4zvzShnof8DTt+bTpZIKR991wxZMikSpsiMxKgkB7+iESjJNsZFkxyHL49MmlUpKlmzGkVnZsaVmVbX487liaTJqj/OiTrr2HH588ppfI6cScMEw8BYWMKYmcdcXsWYW8BYXsWYXyRsHagU4bryBtdqNaTnYc4v4sdlzOVV9LkFjPahSjnueUSeizEzR7i4jL6whLG8hj6/iLG0gj47j+F20So1ACLTUseWVjHmFlXZuUWMxT2M2XlkFCnfDctCQi5OvV4vxrm0Mh3n/CJGYw9jZg4ZBmiWXZzTdfNxzo7qc+kYnBbCsoc55xcLcC4UuO85OOeXhjln55FRONCnHMM5t6D2yknhLCqnbW34LErWm+2kN9Yo9jPRRzKxTjNYTBMKOsnoEfFiU9p3pOjSzzgpGpac3ka+6Ka8ZfIaOeOMkuTn6Pcgz+xO2veqyPdinCP1JP6ictqeI2fTMAGQ8Q2J4n8KKeOf3o2Sw2V755GqTv/vuKxMthMN2pHyaNvJskmWXvv9n/ycMj4mowRLXs4hxgKcckpO5IBTjtGnPCHOpCQ5++3LQfsJTilzcibbHvquJPgRw8ei6Chnlj6LcBYQKSE8ZW86Z1Gy3oyzfBV6Mm75o6iMezMf/l31GUgDTWgq8VmG8WQKHyEkfnQ0ZDcrR0lE9v46eWXSoD3OoJp2hiTv+Un+JnkZTs4gSM+XkuYwneTM8nGZKo/JKXyOnE3DJAwIdnfQqjX87U3MvR2CrU2C1R2CnW2E7QxSk4cBwc42Wn1WldndUXVW1wl2txGa6C89CMMk2NnCmJ0n2N4k3N1Wn4vLBLvbaJ7XX8oRpTLB9ibB8qoqs7dNsLOFXp8l2NnqT+kPON/m46zNxJzb+Tn3d6bj3N1O59wvwLmXQ59zC5M5nVI6Z20mW59Jzt2dI5zh7jZBPebc3x3mFCLOYxJzbm+m63NnK4Xz7QjntuLM0ufe9gTOrT5nUSloy3wvCRFI9Cgg1IyR41lGwehgpDHqiDq+v8nLM+n9DItE4EobTUaUtaNuPT0WS7gYBAQpj/m02ZVpJa1ukQFytGyeupPKFDmfNRP1bcgk/5es8seZYUqT0/YcOZOGiTAtrLVz2OevEO7vY129gb+7hXXpqsrKuXaOMJ5+1+t1iCT2pasEeztYV28S7O1inb+M9D0Vuup5SLeLsbhM1O2o9vZ2sa/dIDhoYK6fR0ZysGdKRWX1DFsH2Fdu4u9sY125SXh4iLm6rra9t2w0x0GY1jDnzgTOy9cV39Ub+Tmv3iBoniDnlZyc+yfIGWdbPcK5dg5hmsfnvHKdYHfnhDhT9DmO8+pN/N3tDM6ZIc6ictryD5wl6Xz2iE/v/BCAuw9+rVDdXrhwcgpcY7IvyTRvtHl5ii4XpPpmyNHw3vHXonKyGGgiwgDaUTnVKViVV/oKIo1Q6nQCFS580DFou4L9A9jbD2g0XN682ONgt8nem+1c13Ic+cmf/R38zE/U+KHxtwn+n9/gH/6p/+Od9/kuZZoEa6ftOXImDZOo21W7CAcB7c9+jFap0vnkA3SnpMJb24eDcMxeuLAQdD75AKNaU3UsG/fpQ4y93X5CMbOxT/fRVwjdoBOHwnY//whN046GC3fbdD7/CM2247IVug8+hzA8Gt6a5Pz0A/TSBM5PP8CoTeL8ss9pJDk3nsdRJBmc5XI+zix99sJwY33qWfp03WxOXT8ahpvBKcNwEIY7wqknOR99m5wfo9nOMGcQEGy97YcL+5tvBpzlygTOp33OIjK6rf33cjKSJ+RUHRP9e9CLTEmWyQ79TXckzevMmuY3kuVTMU6O4/vRO6eWfkATEZqICCINMvqNpDJkuqFBGGk0OiZdT2N7H5oHIW/fHPLmxQ47LzePndm1iHz4m5+wvv670GvbfPN/Fd3h++zLu36OCCH+AvCvAB7wGPhDUsr9cXXOpGEibAfn5nuY8U6vpZt3iA5b2DfvgqZjra4Ttg4A0Kt1tEoN++pNom4H58ZdwnYb+9pNhGWhzy+C7xG5Lsb8IsI0cW7dJeq2cW7eQQY+9tUbaOUKWjV2gmwd9JNhOTdUmKdz4w5EEdaFK+iz82i2DaalnEOHOA9iTgNrdW08Z6eTzrkwzGnfvEPU46xU0SrVdM7DQ5ybd0HKyZztw2x9lqt9ztKNu0R9Tht9fmEy55XrSp9JzrVzw/pMcAaz84jY+TXJ6dy8o2ZZbt4F3cBaWftuOecWBvqcWxhw3rqrdivOwVlIJITf3qzzb1kpnbdSjYJxTrHjJGnE5DEyRrO4phlDeZc3kn2OM4KOcIgBx2h7o+WS5x3RxTbzGxH9VPxScL4skGgEqzoSQSh1IjlLIOfxI51IanihThgJuoFOFAlcX+AHAj8Ez4cwBC+QhCEEgSSK1O8DXtA0MAyBpglKtsA0oVaSlOyImu1TtVxK+jY78mdY//N3ufEffYNo7eM9+Yb2xiavPviGV//g3c/cfGfy7p8jfw/4RSllIIT4L4FfBP7jcRXOpGFC4KsQUsfBf/MSb2ER/80G5uIywdZrhGEMwka7HYKt12iVCv6bDbyNFYK3rwgWlvA3X0MU9n0ikBJ/8w16tY7/ZgN/cRX/9QbGzKza4bZ9CEKosFHDiM/NqXYXVxRTuRrPRFgqhHRna4TzFebiCsHWK4Shj3C+GeZ8s0Ewv5jB+TqD8xVavLvwEc63G3ivkpyv0WxbheRubw44F5fwX7/EXFg6qk93RJ+vVgecW68h9IlclR8EpuTs6/MNWrnSn9lJ5ezd983XCF2fjjNNn29izjev0GonwNnT5yjnyPezqJw2b/qzJK9nLvHn/tlfAeCvpRgFeQyLNMnvo1KsnSzjZFy46nFknFEyOK+hjUQlJfvOvObE19YWJ+f0OrbPCeU8HLySQ+PSijr/njo/C8wcIyS4iOS9hrT+ezJNgrV3+RyRUibXxv4x8Acm1TmbhommodklhO2gOWWEU0IrlRG2g7BLCFut8wMI20bYJXTbQSuV1fq/U1Zl7BLCchCAJkR/uUCUSmiOKquV4jKOg2aXVHCG4yKs+FxcVndU31rct7BtVWYMp2bbyKk5B32Lkj3gtEtHOZ0szlI6Z8wwpM9SCaREi/vQ+2XsBGdcXgjFaY3jTNHnEU4n9tkoxTMm74gzTZ/OyH3XBNLLwVlUn/YwZxGRfD9j8q4lK6ok76CftpwzTTt5GNM+c8+YjHF+zZtEbBo/l7R2pimTFVI9rp08uUWyombSyh7x15kiP07aNYwzeLIieIpIzufIohAimZr6V6SUvzJFd/8O8L9OKnR2DZM4o6tWq2NUa2i1OnqlEh8vIyOlab1cIazVEeWqOlepoVVr/bqiXEYzDaRpocVZPvVKVZWpxHVKJVW2VAGhwuq0UgmtWkeP2xWVGnqtjuaU0Ko1NZCaFpqnMrr2OasDTlEqI4Y4a8OctRyctTp6pTbgrNcRTswpZZ9dL6trEuVqPs4MfWrlHk+y7wzOUhmtVuvrc4izWkeUMzjj9vVaHb1UJsrkrCc4a9mcldowZ7WuDIs0ziP6nFH61ASajDL1mclZLcBZrad82cfLafOmP0uy1njGL/76L6g/fnng/HqSCcvSBz6JLsLY52JYjjvIJNs57gxET/IaOJN8a6btf5ykhXYfN3dKWpmsnDbj+swTpZUW9ptHd0WvY5LkeI5sSyl/ZyaDEL8BpCVi+iUp5d+Ky/wSEAC/OqmzM2mYSM/De/YYhMB99BVGfRb34Zcqq+fTR+B7hI04s+bMDN7Gc4Ru4H79BcbsPO7jrzBqdbxnjzEOlwe76XY7uE8e9vc0MeYWcB9/je6UVVbS2gwI5VRKEOI+foBerdJ9+CXGzCzuk4cITRtxKt0c4fwCo17Px/noK4xqCqfbHXA+/DIu+yDmfDaUQp0wwfnoK4zZuZycXyodFeF8+hhjcZjTe/II3S5N1meYps9HIDS1xNXfg+ZtBufjYc7ZWbwXzxTnoy8x5heG9ZnF2dPnpPteqyX0OY7zS1Vm3PfzZazPh18U+z84hfkHfivKtAPo6KCVbEcnAmEQSX2o7DTLAmlv5tOEAxcJ+530Fp/FMjqrkmcmIe/gP8komUan464hzwxRkRmXcbNr467luAbeSTxHpJQ/O+68EOLngX8Z+H1STjaDvlPDZBpvXQDNtrEvXcO+eoPosIVz+z3Cxj7O9TtIP8A6f5Gwsaeyb87OIQxLOXQeNJUj4kED++oNkFJt5hZvS28sryHDCPvmXcLmPs7N95RT7eVroOtxVI5KJ25fuIx0u9g37xE29rFvvkfUdbEuXVNvwfESjN9zaG0nOG/cRQbheM6bEziDMJszTp0fNhvYF1M43TGchymc5y4QNvf7nBhmJqe+uAyem855615hTvvyNfRKRTmsOiX8nqNomj5HOXUjF6e5MgXnjfcI9/cmc/b0ub83+H6eu0B40FChyCP6LCpFVG26AAAgAElEQVTvcsZECPGfAT8EImAT+Hkp5at31+NEnsznhRDiF4F/FwiBPy6l/N+LtD3NMkRWVtXB+fEDcFrZUZa0gUwIjaQNMa0fy/AywPhkcaMzJuOMij7nmGWwcbMDWcZHHoNjnJGTZylltM+0ckVmNorMoqQZJXlmVSZdSx55x8+RnwP+JPDPZe2nNSrf9YxJYW9diHcX/uZrpJR0vvwEvVqj8+UnaNUq3W8eEHnd+I1UEvTCcHVNlZ2ZofPFJ2hOGffJQ8yDhkq01e1iHbboPv4KYVl0vvgEvT5D58HnCMvGe/EEvT6rBqjGPpHn0XnwOVq5ospW66quAH/zTT+fhb/1FgmqTCXJ+fVkzi8/Lc7ZmzEZx/noKwTgvX2NZjsDzp4+a3XV9xhOoesx5+yA8+kjxRk76R7hrBXTp/voq75D8hHOuMx4fT5L5+zpM+aMxnH2Z0yGOUUpyfkgm/PI9zPJCcHMzBBnEVFrw+90xuQvSCn/NIAQ4o8D/wmQsvfqtyapzwshxF3g3wTeA9aB3xBC3JRSHvXKHCNZyygTp9LFyTzV0wbmIksTWTLKd3TWotg+OL1U/EoGho1AEvUH0bS9fQYROaqdXjSOxiAqRyOUgiAyCKXAj3SCSMMPNYJIReQEofrxApWAOQhVdE4QQiTlIFk1IGIMyxDoOjgWGDpUnAjLiChbPhXDpWx0mY12sL0W5cYrtMN9wscP8Xb32H+0wc7jbd7+o+J5hr4LKZrH5Ft4jvzXgA38PSEEwD+WUo59jnynhsk03roAwrKxb9zGWrugwjsvXSU4aGBfvAKAubRCeNgCUH4DpTL2xasqtPTCFcLWAdaFy2DoGDPzRJ6LDDyMmXmkpuFcukp4eIB16Spht4N1/iLCttHLKmw0bLcwl1aQoY918SrOQQP70hWiMMBcv4Co1RCGhWbZaLNzirNz+O44L54gZ7eNfekKQXM/J+dlwlYzvz7dYpzW+gXlN2NYanbnlHDal64Stgpw5rzvhaR4FvtizUuZnMKpMPSe/u3LmOfFD4H/RUrpAk+EEI+Anwb+3yLtj85SpL2pHq2TPmuS9ZZdZAmk93vyM0vGzV6k9ZO+LDJ+KUcgCaROIzjqC1XTW5jC5zCs4Mv0YSWSIg4BNggiQctTeUz2W4KDQ8nOjsf2Zou9rSavH70Ye70nKVfuX+dn//l1/g3tH9D8tV/jN//SP/nW+j4V8u6fI9eL1vmuZ0ySMtZbVwjxC8AvAFxYXSXc3SGq1Ah3dwj2dwn3dgkb+4S7O2hOqR+OSRSpczPzhHu7BI09VfegocoKLQ4b7aAZ1lCZcG+XcHeXaPGAcHcH6fuqyYMmWqlMuLtLuL8TM+wR7u0Szcypdm0HbEf1Va0f5dzbjTkbI5xzMcN+Jqc+yrmf4NxL49zJwbk70OfeBM7dnQHnflKfu0c5d3cIFopw7hLuJTjrs0f1OZFTpnPu7U7PGYcLp+pzf5SzNPL93MvNWUS+DW96IcSfBf4g0AB+TyHAdyvJ58U5lKHSk5fxsSOSfI5YpRX+3O8bDhee5ANxHMfKNIMj7dzwEkt6+az+8s6G5F+u6pXTMDUfPWMSShOqnKEFaDK97V6CNUMLiaTA1CN8S6Nsmbh1weKszdqqzWF7jp0bK7TbPpsbu7SbbRqbO7l4i8rle9f47T+1xuqcjx/OM/MT9ymd/4jOS++d9Hca5TRG971zw+SkvHXjh+mvAPzE3TuSMEBGITIMkGEIgY8MB3/LOMuODENk4CNDX5UJEnX6ZQM1F9grGwTI0I/L+MgoissEIMSgj36fPjKMkIGfaCdAGr0+ghHOKFE3GOEMYs5gmDMacMpRziD+O4qQQRpnkOAMj3Kavesc1WcGZ3w9ozof1Wf/XIKzr89MzmDQZ9C7B0nOxH0PEpzJvgGiYU6iZHv+yXD2viNBMMIZHOUMg1z6LCrv2pteSvlLwC/FPhx/DPgzhSELyEl7949K8jlSnb11RHuTlnFGZ1Iy+8nhqMmYGZlJ/U67gWCmL4SQY+fDBBFlccjo5NBoe2llRsv26/T2FqyMRQYcknbmyUb5dJE8RRCxw1X4qatc/vt/IJc/yyQZ5/ycp71prkei4fz+HxaqA+92xmQaeeeGyUl76wII3cBYWkWfX8JcWcNcXiNYWVN7nrQOMOYX0SwbQGVr9X30hZW47CrBdrxdfaettqv3PaTnos/OYy6tYiyvYi6vYa6sEe5to8/MYXpunAFUoDkOxtwC1uoa1vIa/vIaxvIKZmMPfXZOMZomwrRA01I4l4hazWNzmitrmJtrmKtrhPsZnPOLw5xLq5iN/aOcIuaMrz0358rJcZorq1gr6/hvX/U5jbl5hBADThKcK2sEmwnOuYUhTtMbcBpx+ZPjPIf/9jXG0iphs5GDc3WY03ZAyr4+jUXFWVSiYz5QJv1/JuRXgb/DOzZMpnxebAAXEsXOx8eK93+CocJFB6K8bahdgKeTaSM5sgbXPO2N+s7kHYiL/j2OM61OXofVcf2NK5P1mdfRepr7M+1397jPkZOW7zoqp7C3LsTOrw8+Q/oe7Y8/QHPKHH78PsIu0X34BdbhwWD31tgJUkYRhx+/j1au0v7kxwjDxH3yEGNpdbAHzcoa3YdfgiZoJ8qCwH35FL0WO2s297EOD+l89iEYpipbqtD58hNk4KsssXHirWDrTQqnCvNN44yi8Cjn00cqKieDUy9XaH/6YTbnpz9OcJbTObffKs5PfoxWqhTj/PiDKTkHYbiK80OEaQ04v/oU6XvKqTSpzyDmLCc4H311lPNFmj4t3KcPMzi18ZyNJKc9dN8jz1V7+qRxZupTos/MDXEWESkZSr990iKEuCGlfBj/+UPgq3fXWy6erOfF3wb+JyHEX0I5v94AJjoKXLlg8z/+8sV49qH4W/CkMqnXUHDgOK4Rc5x2xw2yRdqblinr7yyWPAZT2u9F+IpEV00rRYyrk+j3XT9HppHv2seksLcugOY42Nfv4FyL95W5fZ8wDgVGyjhstAES9JkZNKes9kFpH6qy7Zba40Q3MJeWibou0utiLq2CplG68wO1r8yde0i3g33tFsJ2MOJw4aDZwDp/CaIQ5859olaL0u17yMDHuXIdvT4TZwi18WfmUjjfA0kG53vIdnuIU80QpXDe/W1Eh4fYd+4TuV3F6ZQw4jwmQbOBdWGU8z4yCI7JWcK5fU9x3vnBMOfiMpF7DM67KZwzs+mct+4TNoty3kHouuL0XGS3g7m8FnP+QIUJ5+K8R9Q6GNz3y9fwZ2ZVNFapNLU+i8o7noL9L4QQt1Cj9jO+24gcyHheSCk/F0L8deAL1BLPv5cnIkcQocsAKcTQseMaFuMGk2nyggwbCNk3fNrBqb9XT2rK+ckybgAdbSfP8sa4snm40gyqIrMtRVjzXMeojPYxenzU1yhrWW/0/HFm+/6pW8oZJ9N46wJEnoe/8Rxh6LjPvlEJsZ49Rp+dw3v1HJCD3Vtbs3ivXiBsG/fZY5Vo6+lj9NoM/sZzpNtRA77bRXquCrctqdBXY24e99kTtHIVb+M5YbMev+E3kFLiPnuiwkWfPkKfm8PbeIZmWXG4sBpIg+0thGkMc87MFuL0Np4TFeGsDTiB/Jyj+hzL6cSc8wPOVy+m5szSpzAtgq2Ys+QQbG32OfXZhQHn6xcgI4L4mo3WLN5GknMhndPrIn3vKOfzCZy1mWFOwyTYfjues/f97HNKjNac4rQUZ7H/n3frtCal/NffXevFZdzzQkr5Z4E/W6i9DGeIogNNHklvczpflXFle30N950+6qQOeiOb9OUd/NL6zlq6yDuYp81o5OEZt+RURMYZCGnLU0UMp1656Y3J8UZWEXnXz5Fp5LueMZlKhGFgrK5jLCxjrV/AWFrBOncRc3GZqN3GWFhCc0oAaJUqMowwF5exzl1UZdcvYCwsEbldjNkFpO8SeR7G/AJmu42xtIJ57iLm0grm+gXMhSVkEKBXVdioVqpgLiwRxn2b6xcwF1cJm02MhSWk0NBME2HZYJgY80vDnMurRJ1OcU6vS+T7hTiN+UXMtfODsosr2Zyj+szDubw6wjmP9Nx0zuVVzL3dbH2Och4cYC4uqS0ITBNhOaAbfU5zaXmYc3FZ7TcT+270OM3eNa1fHOb0vaP3ff1CPs7FEc6lZdD18ZxLK+r72eNM6jMuU1RyumV9L6kiCIXB6O6+07wF92T0DXh0EDqJAXOcZM70pOQyyWxjTF6WLMNgksEyjjXvTMSkWZDRupPaHmVM1kn+nZc978xFke/ZKFPyeJ5jeeW0PUfOpGGClOB7Khoi8MH3lSNjGKjPICDyVbiXCAbH+p+BryItfE9FX/g++N4gyiNQ56L4M9kuUvb7oncs8FWbcdQPvocUAqHrcR/hMGfgT8fZ45nEGYfhSt9DRsNlB7wpnHHfYznDcJjTT3Kqz15fJMrie0Q9PadxJqKRSNTpcyIQuj983/u68pFBNie9soHX51T8/lHOwE/nFGKE00/nFCOcvqfKT+KMP4vKaVsbPkvS/exrvrr1cwDcefDr/eNF3urTJI/vQ1qdrAGzaL95mHv9qR+BlOrHEBGR1HCl2lw0GplV0omwhDvEJ9HwpUkwYTiRUqVh6yVS8yOdQGq4gYEf6XQ8na4n6HiCVhu6bkSjEdDpBOzvtnHbLs3dA9rNFt1W8WXPnpi2xfLFVZbPz3P5So1Lq7Bab3NHfkp5+wnNv/PrvP7wKRu/uTl1H9+lFE2wBqfvOXI2DZMoImzux7kfdggPGiqnRbNB2NxHr1b7yxhCCMLm3nCZvR3CgwPC5j7CtPr7pWhOiaCxh9FsqJwjzX312VJlewtxYXMfrVqPyyTKNvYw5hYIG/sI20E6juJsNQac+ymcsse5X5BzP50zikBTzppHORuq7vziUc7ZOZXDI42zkdRngrOxn+DcQ5jmEGfY2Bvw9Tlbw5zNRianntSn76j+ZuP73kzoqrGPVq6M6HNw34MeZ2scZ/JejtHn3g5RYz/BuY8+2xjWZ2Ogz6DZHOhziFMOOBv7BEXzmLzjxEj/NMkkv5Bp/QeKGDVpBtE0b8B5mQeGjE4vY2svH0k3so+Ul1KgixBT9xAMG0K+NPEiK7OvCJGaYM3zNRqHgnYX9hoBeztdGntttl5u09pr4rsnn0/Edz02Hj5n4+Fzvvqgyk/9nvf4iffK/HaxTfjJj3n/n7IEa6fxOXImDRNhmpgr57DWLxLs72Fduoa/vYl14QpRp42xso5WVsHxWm0GGYaYF65g7W5jXbpGsLuNde4C0nMxFpeQrqum9xdXMNttrEtXCHa3sC9fJ2zsY66cQ0ZRf3M8rVrDWj1HdNDAvnyNYGcT69I1wlYLY2UdDAPNshG2jTBMxbnX49wa4awCss9pXbyi+Hqc6+M4rxLsbic41xVntQZCoJWrKZxXCVsHGMtraukhhdO8eBUrL+fl6wR7O6mc5tIKYSrnGjIKc3Gay2uIhD4Z4ryClbjv5uo6eqU2nnPtPNIdx7mVS5/W5Wv4u1sDzpV1hGmmcloXrxBM4rx0hWBvu/D/wmlbG/6tIGlT5Mlz0xgpo3WzDI5RYyStrzRn1WmXndQSk6SstTN9bkb7TvNZcbQutuaO7y9ORS9NgUQjLGtIKQgXlGEUSo0w0ghkGT+6QhQJvFAnCDXcOBW9H6hU9EEInq/eGTxfEoaSIIhfHBOxr5oQCAG2raFr4DgCy4CKIynZEXXHp2J2Kev7NOQVnN+7yO/9jZ9Aa+7hPfmG7tttdh5s8OqDt7+lk66dtufImTRMom6XztdfEPk+7U8/QCtXaH/yAZpTovvwK6L24cBZs7cHjYT2Jx+gV2uqjmnRffIQcy8RNtrYp/voS4Suc/jRj1SI6ecfITQN9+UztYmflIQHTWT7UJ2z7bhshe6DTyEMhnbt9bfeEgVJzvfRHKcQp/v0IcYYTn2Us+es2dgn6rSHOUvlIU5hWWoGZjvm/KQYp1apZnKGjX26DxVn+6P3Mzg1wuY+UUKf7Y/ejzk/QwY+wdbb/q69/uYbZMypl8rDnIetgfNrHNaMRIX19vRpWSpMPI3TGOizk8bZ2FOcn32IsJL6HOGM73sm5xF9PkOiOIuKPG0JCM6QOPducOdv/i0AJPkjbvLMYkwK6VS/H83+Oloum2O6+57ls6Ex3skzjS/5t57DRyTV7hGTI5KSfSaPjbJkzTjl9R3xcHBLZZoXltSB99SHhcaVCb4s08qkiKNxx7P6dn7/v1ac45Q9R86kYaLZDqXb72FfvAqBj3PzLrLdwr71Hug65uo5zJba5kOr1tGqNexrt5FeV+0G2+ng3LyNsC2MuUXlBOm6mAuLCNPEuX2PqNtWobu+h33tFlq5ilarARAdHGCunUNKSenmPRWGfOs9iCLsi1fQZ+fRLAth2SrB2aUr4Cc4b95N56zUsK+PcN6YzGnfeo9oDCejnFIe4QzycErQasOczq17yG435rQx5hbGcspgDCeMcIJ98TL+3ILijNvvcdq33lN7EPVClVfXhzkT9925dQ/Z6eBcv63uSxrnrXtEnZyct+4RdcZwJvSZxSkj0OsDfeJ2C/0fnEZv+rMmEhHPAuRzqMyzxDKtA+K4mZlJbWY5iqrf0/fAGefAOa5MGm/WtRw3eiR9xmig/7TomHH103iyoobS+svjLzTOuMsqN8n5dbTOOGfhonIanyNn0jCRgY//5hXCtPBePceYX8TbeI4+t6iOaxpBYx+BQJ85xH/zCq1Uxtt4jjG/hPfqOfrcAv6bV0jf70/pE4X4bzbQKzW8jRcYi8v4r1+qt9o3L9EPVR6T8KCBMHT81y/xZlS4pzG/1O/H33yjpvQdh2BnC2HbA85XL9DnB5xho4FEYswc4r99hVbO4AwCZKeTzrmwdJQz9gVB106WszPMqS8kOTeUI2e8a28ap/fqJXq9xzmYMUnn3FBsW28VZ6lEsL2Z4Fzoc3pvNmI/kARn4r5ncnrugLM6zKnVZtI5X73Amx3D6Tg5OSNkd25In0UlOmVvOmdJnrzw+Lf/faXzv/bLyuCcNEBMM6uSd6BKk+RAVNQ4SSufbrhMHhTT2i7ibDvaXp5BOU97o9c4OnBPM/hnGUPTykn5L6XJJMMsr5y258iZNEzQNLRKTb3NVmfQKonPSg2tXEEPlJuxVq6gVWro/bI19VkuqfrlKtIwlB9DqYxWqaNVq+i1Onq5omYySmVVr1IFCTKK1LFqHVGJy1ZqqkypjF6pKr8Ny0HrdNBKlQRfXbHEnPIIZ+UoZ6WGVqogdV35MZQrw5yVWoKzHvuDgAzDuO8UznJlmLPbTXDWcnPq5RHOnj77nLUxnDWENp5TL1eQSc5ydcBZHuEsTcHpJjgrw5x6T88pnNokzkpn8P0swFlEpNoD8Hs5YZlm+nxUJr0hZ/XZq1tkgBkXstrbxE8bM2sybpAcfROfdA15DbDRWYhxhk6eQTzrXNoyTtaswySdZM1ipRk2k5jTZmiKXPeowXocI+c0PkfOpmEiNLRSCc2y0EslhFNSg53toJfKaJaDdFQoqmapY8K2VZlSCb1UQjMdtLI6jhCg6f2sncKO24vbFaal2rVVCB1hgDAtZYQ4jirjxHUtGxHXEZaFVi4f4RRHOGWC0znKWSoNOIUW953kdBKcJTQnyWmOcMbtmdYwZ1Kfsa6EZU/mdOJrGeXU9L6OhF1SuhzSZwnNsQGBXoo5ndIwZ7k8pE/Ntkf06Qxz2k4cgpyPU2iCqK/PApzJ70aPM6FPrfddM83CnMVEEp02d/rfAjLpzTp9JiLdETXLpyNPv+OMASFk39hIW2oYN0ClDWqjdcYt3Uxy3J006KYZBnkNuSxjJqt8WvvjZnqy7tWkvkavc/Tak8yj/NPes7T60y0jnr7nyJk0TGSgMnUKw1AZNecXcZ89wpifx9t4hpQqnBhAr8/iv3oBtqXKLC7F2Tjn8V4+w+x2VAp1t5cB9Cl6uYL79DHmwhLes8foFZUBtBeVEx4ovxDv+TcY9Rncp4/V8sfLpwjLIth8owZ328Hf3hzhfHyUU6q9XfxXL8BK4dx4jul2ibpxttLAP8r5/BvF+eo5ejWRqRTwnj2ezLmzdZRzbjKnubg0yGq68TzWZ5eo60KS89k3GIvLA86N52i1ehwuG3M+/wZ9ZnbA+eKpyqi6FXM6Jfytt0fvexbnxvMJnK4KGQ58vBdP0ErlBOeT4ft+EpwLCyOcaq8cf6OX8fdRsf8DIApP1wPlt4rkfdvPOp/2+zg5zvJB3jdlFXWjuKN4JkUd1zNqpL+Jj86gqDid7PZ6fw8+Bxy9HCr93+P2ovi4Ojb4PZJafK7XDoNyMiOTr4hbiT91IdFFiIg/DQL1KX10GWAFHbQowPA76KGL7rbRAhfhdREHDWS3jex2kUGAt71L0OniNQ7x2y5+26W50eBwq0Prmw6R/+3/fxbNY3IanyNn0jDRTBvrwmUV1tk6wLl5l3BvJ3Z09LDOXyLYj6MeZmcRmoZz7TZRY1+Vbe5jX76GDAPMxRUiV+WzMJdXkUGAfeOOCkO+cZewdYB96araJTjeKydsNrAvXCbqtLFu3MXZ28W5cYeo28G+cBnNVhu5abaDKJUV50E+TvvaLaLmyXLKqTh3lYOr72GuX+znhTFmZ0EMOO2bdwhGOb0usqs4I9/vc9o37hCNcAoBQWPAad9Qffc5L17ub4yn2Q7CKeXglBizc/k5V9bUvjw37xI29vuc1sVjcNol7CvJ7+cu9tVbSNfFXL9IdKDS2/c5r94ibOwV+0c4hVOwZ13G+ShM4xsy6U17kmNqnn7HLYuAGphDqdGRJbJCgtOO28LFFP7Yvn1p4sqjOU+G2k4YFaEUBJFBIDW6gYEfarS6KrFaqw0HhxGH7ZCdrTadQ5ed13t0W20OGwdj+5hGqnMzXLpzgfs/WOXWeY+f1N6n/PILHv03v8qzv/v6xPs7tXIKnyNn0jCJvC7u468hknQ+/xi9UqP9+cdolSrdxw+I3G5/l9mgFzaqabQ//xi9PkPn84/R7BLuk4dEzUb8ht8lbB3EYaMW7c8/QqvN0PnyU4Rp4r14ihYP+FGzgfRcda5UisvW6H79BUjZ37VXi8NGFedHKgS4COdnH03gNGl//qEq+1XM+fIZWq0OCKLmPpHbHc+ZeMMfcKqwXq1cofv461ROoafo8+lDwsa+SkmfylkvxvnwS4iifvj1RM5up29AjeV8ksVpDXMaRmJmJw4XzuIMQ/ztTcVpO/hbb0BGA84vPkKrjHJKgpm5mFOn/fnHhf4PJMM5G76X40uaD8HouaPHs9O9j1u+GJW0MsmZiaOsMvF7liGl0qdJoVpONYRk+vFktNLRc1G/jDbBWOttkqhmLTQgQJMaUhfoIkLaYOgamtAwDA3bFuhahW7XxnZMum2Pva0GbrvLwc7+2L7yyuKFVeZXZllerVKvgK2HhMJElios3lqn23R5+4+KJTw8q3IanyNn0jDRLBvn5l3M9fNIz8W+fF29iV++jtA0jKVVosOWKlupoleqWBevIjsd7Cs3iOJkWsI0MWbnkL6v9kyZm0cYBs7V60SdFs7VG+C7WBevKh+MinIqjQ5bGEtrEEU4V28QHbZwrtyAKMI6dxG9PqvCRk0TfW7h+JyWiTGTxnlDhaFevo70epxltEplwLm8hpCyIOcNolYL+8p1tRPv0soYzpvjOXU9wXlDzRQNcQqiw4PxnDNz6ZxXRjgXl4nah8fgVPfdvnwD6XtYl67FzqkpnFdizsvX+5zG3ALCNBOcF5CeN+C8fB2hZXBeuobsFEyzLTl1+QfOqmT5G0yzZp+1LDNutiTNH2G0rSRLmjNrVj+9FPJjgKcWQwQYIihWKWvlaESGZ3Gs+KeecT6fDBtgbaDdP9ZintaFn0b80Z9i8Y/CUs+HRw6MMCGjfvne70LKfhl6ZRLH+vXCWE9CIGSIkBFaGECvrtAGRlwUovkuWuASmQ5SN4fOqfNdpKYjNQOp6cqvL/Sp/aE/UUwpp/A5ciYNExmGBNubaOUK/vYm5s4m/vYmxu628ukwLRUuLAS67+Fvb6JXZ1TZ7bjs0irBttoLQcb+BkLTCLa3CGbmCLY2Cbbf4m+9xZhfxN/aQnfVP3jYbKLZ6u3dWFwm2NrE394i2N5Cr9YVW5wQLJ1zZ4gTwIg5tWr9KOfWpvryxDMmRzh3NvucwfYmmlvvcwrLGeHcLMj5FmGaKnGZlBiBP8y59Sahzy2IZH8mQug6wc4Wwez8EU5/axM9jXNhaYhTq9ayObdH9TmGc/ttNqempXBuYszFnN16P8T3COfO9jCnZeXiDA+ayCgacNYUZ1EJT9na8FmSKxcs/uovXxg6dtzwzXGStSSUnJk4zrLRaD95HUrTzuWJSsnqI6vdotEjPbMj77JYnr6zzvd+B+i5qvTriXzRWUWub1r2PPV8szT2fJqctufIdJmAToOILGtZDJ8TaleHYm1knBeq7UnV8vXRa0skyuXkTGszq58jxxP9HdFTNmdqGwDayFdoXNlEv/1ivd+H9DBSr39utP1jvOrl/I4cOZWq+8xOJhU4lkgpJ/58L8Ukz8CbdzBOfhapn2fwSTNm8sgkX5XR39NmcUZZk595+i5q+GUN9idx3aPXl/xJ1ktbnsvqI5/RNT7CaVK9k5Rv6zkihPgTQggphFicVPZMzpioLeUX0WfnMBeXMRaWMRaX1cZ0B030+izCNAG1Vb3huujzC6rM4jLGwhL67CxGexF9Zg5ZrqL5Hlp9FmNxaVBufgljaQWtPoO5tNzPDxJZNlp9BmNppV/eXFwibOyqNqKoH4YLEn12DmNhKcG5QHjQSOU05hf7/ZuLy8Ocvq84azOqvf71LGMsbikmd8Cp2Q76KOfCouKszWCEoVp6sOzpOReWinPW6hiLSX1ainNx+QinXp+DSAvkgDUAACAASURBVA44ZZJzqc8ZtRroM3NK55FEq1SPzzmqzyHO5fGcSNVXXs45xVlUTtubzlmV0Qd+2mA8boAe9dGYdhDu1Rk/s5HuEzJJ8s6WFJE8szOT+swzm5E2k5PWb9bsUdEyo/KuZtGO02fWjMo08q6fI0KIC8C/AOTKInkmDRPpdel+/SXSD2h/9qHa2+WzH6OVenvltPrOmnp/b5eI9mc/Rq/V6Hz+EZrj4H7zEHNppe9Uaq6sKSdITaf96Y/RKrX+nik951eByqhqddrqnGXR/vTH6JUKnS8/RQbBEedXGQTKCbJSTXB+mc35qeLs7cniPknnJObUqwnOEadSs9Om89mAU0tybr5Bi/fK8bfeIv2AzmcfjnCm6fPZQJ/V6oDz6UOMheX+EslRzuoRzp5Tqdlu0/n8Y4TtDDi/+gzp+wPn1zhbbRan1TroO78OccY6SnL2opwyOb/4GCHEEefXAad9lDPeK6d/330/m/OgCTJCj51fkZL2pz8u/r/w/azIO5FpZ0qSMm7AzSrf6yffYDn53mflKTkpyWNUTOLJdtxND1VOfk7Lepwlu0l1iyzB5Fk6y6vfY13Tu3+O/GXgTwJ/K0/hM2mYCMvBvnYT59ottafNnXuEzQalW/diR8RLBHEeE6M+q/bWuXWP6PAQ5/Y9woMmzvXbIATG4gq4KoW6sbIGoNprNXHu3lftX72JsG30+iyACuM9d4nI93Fu/4DooIlz5z6R52Ffu4leralkbLaDVp9RnJ18nM7N94Y5b9wGLZ2zdPce0WET+859wk6CszZISW+fv4xMcJbu3Affx7pyPZ0zpz6dm7E+79xXIbE3boOmqbd+zyXqdlI4f0DY6RzlbOxhX7iiQnZv3yc6aAxz1upotkqMptXqA87b9xOcEuvcRcUpJcbM3DDn3XsTOZ077yU4uzjXbiEcJ4MzRZ9JzvoMzvXbRN2O4jyYxPle38E4r0j5/YzJ8URMPfsw2sqo5En2NZrvI2sQSxoyPYfPvAPQtDMkWbMVo20W9f3I66+SdylptM88S1WTjJ9JkneWZpJRkmaIFp3J6ZU7nlGS6zmyKIRI7jL6K1LKX8nFJ8QPgQ0p5ccipx/EmTRMpO+qpFaahvvN1+gzc3QfP0CfmcF78RQZhv0357CXaMu0VJm5eVWnFpfttPsJwSK3i/f8G7Vj7OMHGLPzeE8eopfK6g0/ES5MGOE9eYhRrcV9z+G9eIIwTfy3b9CcRII1XR9wfvMAvR73HQ0Sgg1xfpPgrNbTOeOEYEc44zf8HqdM4XSffwOGMYHz62HOeMbkCOdsgvPlU2T7kMhL16c+O3eEs59gLYxwnzxEr9boPv56wKnr+JtvFWcvcZmu4z4e0efLp8gwGNz35v4QpzE3j/vNA7UfzosnCc5uzPlE7U7d43z6EL3k4G28GHA29kc4e/p8MsxpO/hbmwgtwfn4gdoj6MUTxXnQgCginFXJ4Xrfz8L/C6fMm/5syXBUTE/yDtj5e5nOaXOUpxf+2zOElJeJRjJZ2USWkSRkugjp+auMWzrpHetxReiEMl94TT8RGip5Wih7nzoSgR/pRFLDj3SCSCOINLxAI4gEXU8jCAVdD4IQXA88X+L7EZ4nCSOJ74WEoSQIImSksphqQiA0ga6pT8vSMQxBrWZgmYJKCSqOZKYcMGO7VMwOS9FrnM4+pe2niOYe3UePab/e4vWHz3n9D3dyXetpkKIJ1iDXc2RbSvk7s04KIX4DWE059UvAn0It4+SWM2mYCNPCOn8Jc3kN+9J1zNVz2JevY66cQ7oe5vIqYU0ZEXqlihAa1uo64eXrWKvnCC9dx1xaRQa+2mXWc+Ow0QWk7w/aW13HajYwl5W+++HC9VnVx2ELc3W9XzbqtDGX11Ra8njXXuGUMJdWB5zxp/Rizmr9KOelBOfyGjIMpuY0llaILl1LcJ7LyXktnbM6yrne5yQM0efmhzk9r89prZ4nbDaPcOo15QcTtQ+x1s4RXL424FxZV3xxqndhO4rz8nXMlfWj+uzd9xHOftlxnGvnsfd2EpxrgFCcQqRwXs/mdEqYy6vYl68N+l5ZR3ou5lLMKSV6rRZzniO8fL3Q/4GUkvC0bQt6hqS3id9/95duUdHyzVYNGxjZhsC4WYWhcyItf0h+59pAHjVKohGuUWMkWbYkOmiEmf1mzWpEaHSlM5Gz179EEEidSAq80CCSGp3AwA80Wl0N1xcctKF1GNHuhOzvdlSCtTf7dA87NLcLJh/MIcuX1rlx/zy3rle5smxwMfyc0osvefnXf42n/+czum/9E+/zNMpJPEeklD+bdlwIcR+4AvRmS84DPxZC/LSU8k1We2fSMCGKiDodIs8j7LRVuG88oxB22uhulyjOCSEMQ5VxXVWm0yHstIn8LlG7TVSqIL0u0nWRlSpRu4104/bidqWv+kFX6go7bQzfI+q0CbuqL9l1VV3PVbMbUYiIpOqjEGf3mJydIU79CGcnnTOpz05blU3jNEc4u90+Z9hpIxxH7dzrushqjajTKcbZ6aRyEoVEclSf3QxOOQVnG9ltZ3IKLYuzO8QpwwB6nL5/lLM9wmmZMWenr+Mi8v2MyfHlj/yHD/q7CxeV3lLQpOWc4/h3JNvRRTgxodmR+mOmz4u2laxX0jr5+h9NOW/EixdSUz91jVBqhJFGIDXCSMePLMLIxgvmCCW4vkYUgesLglDNnviByljqBxIpIQjUPQhDiaaBiCP+dF1gGKBraqbE0KFsSxwzoup4VIx9SrrLoVwivOKw9oeXOfcHW8hXzwl292h+85K3n26cqVmTovKuniNSyk+Bvle/EOIp8DullNvj6p1dw+TwgKhzSNQ6IDpsER0248/4eLxeLwxdHWsfxmUOiFpNonaHqN0iKpeRnQ6R56JVqvH5FlGrSdiO2++0iQ4PELquBp3D+FjrAHnYK9vqHw8PW2hBgAhD1UfnUPXZ42xnc4ZDnAfDnPGyQzpnM+ZsIjQVkjvgbA44D0c4fR9RChP6bMa6OkhcU4LTNIY5262BPg8PiBxHGYF9zuaAs6f7nj4ncbZbhO3DYc6+PhuxHpXuZe94n9MsyNlS153g7NVN5Wwn7nuPs32I5vtEURSz9fps9fXZ52y3kFLGnK1+X0Xkex+Tk5OieSWmba9IG6PtqE8NjTCX82MRB8mizpQaYX+mZWLfIqO9EXsp7zLZcfwp0trpfXo4eCWHZmlJFbg6KDMHzB27x2KOs5DfoE3Wc37/D4sxncLnyNk0TAwTc2VdTX/v7WBeuIy5/Rbz3AVkt425vIpWUtlP9VoNoghj/TzmzibmxStYe9tYq+vIbhdjYYnIc5Fe/Hv7ULW3s4V1/jLh/h7G4goyCNASyy7G4grm2n7c9ybW+YtErSbG0gpoGsJy0CwboRlHOdcvqH5GOGUYYq5fINjZOsKpLywiPQ/pdTEXc3KWK5jLa4TNxoDzwiWVwXTxKKeZwik7bcylEc4gGHBeuIy1u6U43S76/BjOC1cIG/uKMwzRKrWJnObSKkI31M7PU3FeVJznLx3l9D2191Cf8wrm9oDTXFqFKErnPH8Fc2tw3/ucpqX2ytEMzLUxnOUKyKOcxeT7XCUnJUVCRkcNi/R07pNzXQxvfJcdtZHm51Fk2aUIV9qxfHlV8vmojGvvpBx68xouJ1HmuI6zo22Mm2HL41Q8ncH27T1HpJSX85Q7k4aJdLt0HnxO5HkcfvIBolSh/dGP0GyH7sOvCFsHg4yqcRiuDCPaH7+PXqmqOqZFNw4Xlm6XyHUxl/foPlJho4cf/ZM4DPlDALyXz9TmeLETZNQ+jMNPLVW2VKLz5ScqbDQOFxZx2GjkJzg/fr/PGR22jnASSdof/WjAaVh0nyQ4u13C/bVUTiEE7stng91wG/uEh61szs03iES4cOR7HH58lDNNnz1OrVzpc7pPHyqjI8n5cMCpF+b8lMjzCLbeKs44XLjHqTnlYc6Dpsr82ud8howixZnQZyanPuDs9O57f3dhFS7c5zTTOXt+MEqfLoeffIBWyuJUUTney2dIqfRZ7B8Bou+XcqaWtcYzfvHXf0H98cu/dqy2po1+GVc/GWmSNegWnekp+gaexZb3GtL6PW5UzDQc43PQ5DfA8vSV7DNP29Po90R1dgqfI2fSMFHhlXfVPiW+i3PzLtHhAc7te6DFjoQtNS2uV+tolaraBdbtYN+8R9Q+xLl+R8289GZMXBdjcQkMA+f2PaLOIaU795GeR+nGbbRyFSOOdgkOmtjnziMjSen2fbVnyu37yCjCvnRVJdCy1Ru+PrdQjPPmCOeNO2CamAuLRL6vZnkyOJ3rtxClyhFO5JSct96byOnc/gGy087F2Qupdq7fQitX0KvjOYkirEtXCWbnFaftoM/O9znt2/cI2610ztpMn1O6XUq37yPbbRUuPMTZUaHDhoFzK9Z5glOvVNEqdbW78EED+9wFxXnnPlF7DOfcgtrvx/fycxb0MVHblX/v/HrSkifx16S6WXXGGTCj5/POiowzVkZZT3qwHNfG6DWNWy7KuoZp8nVMCkXOO2OTZ9lrnD7zXPfotWZxjB6fpPMichqfI6fCMBFC/AngLwJLk5xiAGTgE7zdwLMsvI3nGHMLeC/Vp//mVfwWHr85zx7iv9lAc8qqzMKyegueWyB4swGBT9TtIt0uhAH+mw30Sk21u7CE9+o5Wq2G//oFUWuQH0ToGt6r5yqR18Zztf/Lmw10p6RmImwHzXEItjcHnPOLCc6NIU59phVzloY5Z1M4oxD/zSv0SnWIU6/X8d+8JGrV+5xoGt6rFyqceeM5xvxSYU6haQT7+yP6jDnnlwacbzfA94hcd8D5+mUK5wze6w30avMIp5Hg9N5sIGxHzZiMcLovn6MPcWbd9yTnM/TZ+RTOKOZM3PfXSp/e65fKgNLUzA6ajrfxAqM+uO/DnCqseZhz6Shnb0+fHqddwtt4Uewf51vafKvo/+e3zSOUu/9/BfxLqJ3Zfl5KWTxbXa/9AgOilGLIVyJrQMyzFDKpr6zj44yVcYPZcYyPInlDRv9+F2xphsw0S0ZFZ4ry3KO89/5dGokTKp46J/rv3DApmqoWAE1Dr8+hV+vocwvo9VmMuXn0+iz6zKxKiKVaR6vW0Wfm0Gv1uMyMqpM4Liwb6ZXQqnWMmTmVdnxWtWfMzqNX60Rx2RgavVrDmJ3HSJadmVP9uV3lE2HbSN8fcNZmBgwzcwlO9eYctQ8T1xJz1mojnA5apYYxMzvg63PGZStVQMQhrqOcMwlOVy2R9DhrM6mcWrWOLgGk+r0+N+CcmR1w1pXuhKd8N/o8Rzirql4chpvk1EY49doM0vMSnJ7im1/ASOpqZlYZEEKAlGi1GfR6q89p9DnrCU4f6XYSnKP3PaHPeNMcvVbDmJtHm5kbuu/jOWeGv59pnDOKs5i8+3Dhqf4/36Fk8PyLwI3452eA/zb+HCvOvRvc+Zu9RJT5/TN6A2Ay2ZmQcmz0S1KyBvq0cml/T+M4e5zyo7MNWXxFZHAtR3U2emw0Ed248OcsSfoB9UK0+7sEI+nlchFEaDJK7Bwcock414uUg12Bo/D/b+/cgxzL7vr++d2XpH6o34/p7pnZnffM7toYzCsJlHkkNg6FIRUqpKCKR6pIzCMhxKFMnFeRVBEgFRyTBOMQV2ICMRjMIwQDNmXKvIyNvY/Z3Zmdnd2d2ZmefszsTHdLakn3dfLHuZKu1JJa6ume1uyeb5VK0tW55370u7rnHp3z+/1O/XOJI709jvT2KEDiCCWW/jz09YEtG1QMSukyUYRUtyGKtAeqCMrNIHEIlTLh2hqVtdvkFuexRkZAEnuHASqOIYqQbBbJDhG9dpuoUMQeGcYt9Bs9NHhpBw69Y0KfqWoB3ag7Ltg2YrvgumC7iG0jjofYNpbjgkiyzUUcp/Fs6311HQ7iRDpCwrGT9y44LpbjgOM26rAdfb93k9dO7aHr1fvaTe9xXKgd03Xr9UhSr+V6+ivVj2G3cDrNnHFcP0btswanU/+edU7LTnF6zZxuC2fKnuJ6iJXmdPUFZdvJ92/YZAenHaFcT9fXkTM5tkgTp6Tt6bgtnC44XoOzdk6tRn2Wk3BaVmJDO9kvsYtlpewZoyK3zlk7ppUcSyy72Z5OF07barFnG87UcZo4E3tiu31dOAoGLpX0A1A7nncBH1HaGJ8VkXEROaKUWulWUS1BWbeQ2b36QdzPNEn6RrvzJt17jhJHwh5u2e25Oo/YCIHyeuoMQCOnSpwkVYuV1ZTPJFQWfmgTRBaVwKIaWFQDKJWh6iuKxYggiNnarBL4IdulKtVtn8p2hep2hTAIqZbKxFHUlWNkYozMUJah/BC54Swz83kmJjyOzFjMjQdM5rY5xjWGCyvYFz9LZXmVVz/zPMuf7n/F78NWIbrbV/kH1I70pUPtmOwlVS2ACkPC9RWsbIZg5Qbu7BzByg2C2TmC9RXEthrOmuPj2hl1aBj/1k3cuSMEKzdxpmcJ11cgDuthuKJigvVbOPkxgpWbBHNHCFZv4oxPEKyvEFe0D0C0tYU4LsHKMu7ktC47O0+wfgt7eJhwfVVHZmSzhHduN3H6t27gzMwRrN1CbLvJqTRYu9XCeQNnemYnJ4pgbRlnNJ9wLjQ411aIR0uN6QLbSXHeIJjTNqpxipfFyiWcuSzByk3NuXwDZ3p2J6dfSXHewJ2bb+aMgnoYrihFsNZqz+UU52gHzpsEc/OEaytYuaHE+TWjOW+v1zmd2Xn8Wze1PddXdnKur2ANjRCs3CCcP0Jw6wbOVBtOEs6x8Tacq032FDc571MzKc5bmvPOuo7KqXFms/grNxLO5Lyvr3a0Z7DS/1ROFO56s3ygqaQPUl14FoG08W4m27p2TKrPXuGFs28H4MIL7Z1f9+qc2fs0TO83hH46JZ3r6N1ZttO2XjslrZyNZ+pJ15QSYiVEKnkdk3robK5BEBMGEWEQEVRDgmqQPHyiINy1UwIQVH0s2yKoujiOTRjGRJEiiiFOjl3/WlFEHAQE5TdGgrUe25EHqgPvmOxXqloR+X7g+wGOLizgLhwlc/wkcWEL7+Q5wnt3yTx6GlWt4i0dq0+72PlxUELm0dNEmxtkTp7Ta54cfxQVBrgzs0l0RhV3dg7l+2ROnSPcvId36ixRYQvv6HGQWl2KKL+Jt3ScuFTEO3WGcOMu2VPnUOVtvKXjiJvByuroDPGynTkXjzZz0o7zhA4nTXPOzbdwniEqbDY4U2vleEvHUdulBufJc6jtbbzFYzs5j50g3tpsz5lPMpWOTTTb89QF/Xz8BEQhzrTmjCpVvLl5lF/tbM9atMvWBt7SI205M0vH9PozGW8HZ+bkWaJ7rzU4F5Z2cp44rdcMOnW+bs92nHE1sefG3c6cmxt4Rx9pnPd7r5E9cbYz5/ETxIUunLFeKbnOudlvdsuewvweaCrp+9VB86TbkZkem7/uPgmih/hR9Rt2O2fFTp2S9qHGqu3rNgX71l79JhrTWIqMVPo9aLPsHkaCaOnMNI0i5YActcwi/Uzl6O8RI7yGiGo6B2VGqEycwnrbowiKhe+KWFQxdhwCCiuOsOMgmbIJ9FRsrKdwJPSROESiEAmqEIZgiV5xvJo4tduunsqJI5TvQxgQbW2hghAVRYgI1sgwKgiICkXuXrrOylPLLL71KENzE1i2rbO0VnziKEKFEe7oEF5+hM2XlimtbzI8O8bQxx/+tAMH3jHZr1S1yb+8DwG85cxpVX3pMioK2b74JDI0wnYSllm5eom4sr1zNVwRti9+Qa8ye/FJxMtSfeUK0ea9Rtjo1gaVq5fBcXR9w6OUn38abFuHC4+N695lYQNVqegVaLPZ5NjDlF94DhVFejXcJFw4vL0KccT2xSexhkbYvtgD5zNpTr268K6cl55BHIfqzWvYo+Mger2YuFxu5hzqwHlnrQ1nrg97Zqheu4qz0eCMC5s6DDfhtIdHWjgbHag6Zy7X4LzyPHEU6RGorvZs5VTJ2kXXUULDns8+1YXzecR1O3Am9tzcIK7U7NkDZxRRuvjFjpxKKZzxNGd//ppKQRTu/m+xex37m0r6frUXHmAZOJoqvpRsa1d/vR05Ldmm1rhTFEl6+25+Ff06XPY6erFb5E2/ESz9RNN04t2tjm7H3a0rUd+/TcF2UUf92LHT91BYKIFY7ORzd9cRpk6/kX6ihjqW/zbdQ4+AQoe6al1EhUWGmBCI//TbOh67Lc8+tCP7rUObytlrqlpIwoXPPoa7cAyCgOzJc8SlIpkTZ8CycOfmiYtFEMEaHsYaHtWjFpUy2VN6pV/vxGkk4+GMJ2vQBHrNFHFdMrXVgE+dRQU+2UdPJ2GjOtFWXCrgzM6jlCJ36jzxdonMqbOgYryjj2CPT9bXoAmnpnEXjukRjpNniUpFMidONzhLJd3zHtH1Zx5p4Xz0NJLJNDh9H2eyPaf3yEmsoeE6Z1TcwptbgDTnybM6vPXoI9gTk1huinPxuB7hqHOeActuwzlC5pFTxJUymZNnunM6jl5lt7xN5tQ54iBocA5pp9Imztq5PHkWVLISb5pzchp3qQPn7Dzx9k5OVam050wicxqcZ4nLpe6c84uJPc8RbxfJnOjOORz0x7mH66jvfXqsd8/X54PmEZHfAX5IRD6Kdnrd3M2/BGBl7Dg/+TV6VuuX6HzT7RQC2jqV0lp2N/UTBtstaqVbVEev9d1v3pJeQ2X7rXu3KKR+69vNqbnTZ/3U2+s+u5XvZwpxT9E46WO90UZMDkIqCpN/pzmC9RWctWXC9RXC2XnC26uI6ybD4oI9Nk54exV7eIRwfQV/dUX7E0zPEq6vQhQTV8oov4ogBLfXsMfGCdZXCNb0wxmf1H4Z+bKeyilsIa5HsLaCPzlNsL6Cu35E7zuSJ1xfScJbc4Svrac459pwJv/w/QnNOZLiXF9JfCJSnNUKIjVO7fsSrCacE1ME66vYo9v1kQjxMgTrq/hTM204V7XvRppzbQVn5lbCOddiTxLONeyRUcL1FYK11facfrUHznwbzoY9w9trWEPDKR8TnQjOytU4V1rs6SThwqo3zmoFVSm35QzXa+e9HedKg3P2iB55SnNmcwR31lL2bOVsPe9r2MOas6/rQCniAZsbPiT9HjpU+Co6XPh776eyfn1KatEZ9aiJlnp6HcnYy41xv3S/jr176QDdT7398u1H2f2qby/H3G/OproHsB0ZmI5Jr6lq66pFdySRLrip97VoiFpUjusirluPmmhE1TQiWVQcNco6qegZ122OLkHVoz1q9dQjLmrRFakojN059Slo7J/iTEd/JAwqClOctWiU5H0SiYLjAJKKBHG6cDrNtkhzOm4qAsejHpWTjjJKsTRxNtkzObbrNHPaSVROE6ebsl2Krek71DjtFs4kgkbFjQil3TidIHVsu85JimmnPZsji5p+T2lOp5Uzdd5bOROb96tYPZgGpe/r84CV5kmicX6w3zqOH83yiz97Ck+qQPvcH22PvUvIbLqefqZ29hoBlN53t229fLab7ucG2W3ffqeJ7jdPyW5l96Ldpt3up96D1INqR3rVwHRM+pJt6/wao3nssUmc8QnssUnssTH9XMsTYVnYuWHisbLO0TGW5LMYn0r2ncDK5yHIIlUfGR5J8lkk9Y1P6Pcjo0T1/CAgtoNVK5sc20nKyvAIdi0DqOthR5HOVdGNE7CHRzXn2HgHzjEIfKSaa8M5meQbGdXTSEN6vRgsS+fiGJ9sz+lPIhkv4QyxRsew0pyJfXWCMUs7lQ6PEo9PNTiTsjs5qzs5xyZ2cIoIYRdOa3gEOwganGE7zlHNMJLXYeBxjD08SjQ2uTtnNlvndMYnmzmTc9meczI5T0m9rZy72bMDZz8axH86D5MEvRhd4/3eOwvNDqvNN75e/A/2MpXSfPzOqd87le+k++kgtaur3fH22rlol9tlv0ZH+u1QdEru1utUTi9+Pr2y3I8GsR15KDsmyq9SffkKxDHlyxexR/NULj2DPTJK5erllBOkYI+N6bVdBCqXnsEZG9f7DA1TfeVF4ulZnVHVr6JK81SvXsZyXSqXL+KMjVG58hyW5+HfuKadX4FoaxPl+1SuPIc9NKzLjuapvngJUQo/WSvHStZM6c5Zy/zantPKDWnOmTnixFlTzRWpXr2MOK2cGfy6U6l21lSBT+WF9pxBfSonS3BnHeKYygvP4uTHEs6RFk6VOL924Lx2VduzxjlfovLipQZnvh2naMdeX3NauRTn1csQx81TOeurmjMpk7ant4PzOiJS56x047x6Wa+f1MTpaafnNGfQwpnPU716CeIoNZXTOO/tOBv2jLWTboqz72thwOaGXy9qvaG23kwUlo7qUDEK0Q6TybloTbS2W2eh38Rpnepqy9hhW7eOQbsOUi2hXL+hwnpfAeymCBuFXp8YmnOcxMoiRohivS1MPyuIlJWE90IU6zDfKAk/rqmWxFQpcGyFnXwkonDtGMeK8ewIx4pxrIiM5eOJT06VcGKfTFDCDit4hTtYlRJsvEa8cQ//tXuUltepbGxTvleivFFh/bP9RtIdvCrR9b73GbR25KHsmFiZLNkTp8mePEtc2SZ79jGirQ1yZy9AFOEuHiPe0lEkVn4cy8uSO3NBr4Ny9jGi4pZ2GFXgziYdk2oShgt4Zx4jV9gie/YJ4u1tMifOIK6Hk9eZWsOtTbyjj6D8Ktmzj+tw1HOPEwc+mROnsYZHk9TkWez8WIPznC6bO3O+O2epWOfMnT6HWIIzvZMzc+5x4sIW2XNvSjhPI66rs5qmOPH9Oqd39jHN+WgzpzUyRu50irOwSe7MBYji9pxnH9uFs4I7dwSllOYsbuk1aMrbZE6cQlwPO59v5gx8cucfJy40OLOPniYYyWvOXA5rON/gvPCEPnYbe9rjCee5x/SaNqnzXuesVlGVcjNnDoNFzAAAGmJJREFUIc15GnEzmlOEcHMD7+ij4Kc4zzym19Vp5UzbsxOnUtgTE1heRte3XezvQhhAb/qHTekQ3359PmwiLImJcBAUTuzXKtVPkp7yaQmH7ZIXppcEazadz3vXzlTqs15HRmodpn4Sq0H75Gqxsghim1hZVGObKLaoBEmCNV8o+4IfQHFbEQSKYjHE9yOKWxUCP6RUqOBXfPyKT7m4TVj1Cap+V47MUA4Ay7GZOjLN0GiWuYU8+XyW6UmbxamQ2eEi4/FthopruK88S7CyyvO/8ees/Xl/ycoeSg1gO/JQdkziapXqtZdQiB4NGB1LnvNUr11Fhf7O1XAdm/LlZ7Hz48kIwgj+qy8Rbxfqicviconqy1ewvAzlF57DHpugcvUSksni37xGmK+NmGxAFFG5ehlrWIff2vlxqq+8iFhW0+rC4e21BudIXpetcQa+Ti4Gev2Y5VfBdXTZsYk6Z/WVq0TFQiO8tcaZyVK+8hz22LhmyWaTVXvH6pwqDKlcvaQ5rzyPnR9r5qwlgru9BlaDs3L5Wezhkbo9o81NFCplzzac117SnDV7VsoNzro9L2Nlc41w4VbOoZo9NScizQnr0pyjY5pzZJTq9YY9FXGyau+r4LiNY195vpmzWiEul4nL21RfvoLU7Dk+QeWlF3ax50iTPRHRzrpepsEpULm8C+dGM2c/UijUgM0NP0y6dqPCP/inLwPwkfc3oo17CQmuKT2FE4vdrrjep48Eda15TNKdgfRn/TpaduucdOfR5RwJ+h4xqSUuU0i9oxbZOqJpmGSEJGMRKSFStn6ObcJYiJRFEFnEsY0fZYhjwQ+FOIYohjDSz1GMTg+SGimpDQC4LjjJabEEchk9ijKciXDtiJxbZdipkrMr+FYORmbJnXwzzuJJnjh2nMe+9y7lV5fZenWduy/dZuVP+033PvgaxHbkoeyYiOfhPXIK78gScalAZvEo4ZkLeEeOoqIId2ZeJ9gSwR4eRbwM3uJxnTRr4SjRmQu4R5ZQ6LwcKghQgY87PolSMd7SMbJbG7psqYi3cBRxHR02CsTbRdyZeTKVMt7icbJn7ul/wX4F78gSkhvSKd1dF2sk3+BcOqYTjaU4o5KOULeT0QvvyFGiM5u9cS4eJbt5AW/pGNF2CffIEjjNnM70PHG1grdwjOzpezoxnF9tzzm/SHT6fINz8RgqjjXneEH/wx/Ra/Z4C0d1UreFY0RnNtpzTkyh4qjBuajt6R5ZBMfGyo2AtHAuHSO7WeP0ySwc1T4eroflec2ci8f0eV+o2XOOqFRs4swsLhEVLmjOrXacVdyJaZSKySweI9q8l+JM7JlwRiV93uNqWX+njfN4i8c6cx5ZJCoVduXE9cgsanv2JcXAzQ0/rOrkF9JL+ZradT56vfF3/3zv2m0UaDd/l3Q5ey8+Dp3g7+NL7Ze/RWs9obiE3hjbXrKG2fybmspPUEvp1hvLXvxf2k2/9ftdst/aXx6TQWxHHsqOCXFMXNgkHp8g2tokLBSItzaJtktEW5tYwyPEBb1ybS2VuCoViAtbxKUC0dYmcblEvLWJ5bo6bNT3ibM5oq0tomJSplQkTspGW5v1db6i4ib2yBhxYZMoqU+VCkRbW8STZeLClh7S9zJ6/xpnsQMnNDi3k2Pu4PSIfT2VU+csFYm2NomKBW2PcnkHpzWcT46ZlC20cHoeViZb54wLW5qzsEVUauFUCiyriTMqbe20p19tz1lqwykQFVKcpTTnJtHEVJ2TTK6Fc2tXzriY5tzawRlXKtjZoYSz0JUz3tokHskTN9m+2MzpepDtxrmlOYsFiGPEsvXvMuHsT2rgvOlfL+rHcbSf/COddJDOjf0evx8H0X7qvZ+y9+sc3E79Rs50m+6731Dndt9tN779s8ngtSMPb8ekqv0YVKWM8iv1HB+qqnNoxNUqAJLN6iH7apW4vK39HyplfeP0E6fXqi4fV6t6/+S5Nh0R+1U9PeFlQClUpaKPWS7r19UyUaWc7FMlrpSxlEIBcbXc4Ky24UySamnOxv5NnFX9HetTJDXOcrnOG5dTZVwPRBJOXV+Ns2Y3fZyK5hRJOj0pzvJ2wllp5vSrTZwq8dNosmeN02/hLCf7JMeKXQ+xrGbOcrmJs3bsOme1ZsftnZzVGqeqc0Z+mnN7B6dKc1Z24azzbKc4qy2cMcqqcVZbOBu/r7hS0eHCfqWJsx8pBfGAzQ0/TDqyeZ0f/8T3A6De/4k930B7HXXoVtduTqp74eqnTK836V47Lb2ETPdjx35tki67W92tn3catdiN4SDzk+zHqExHhgFsRx7Kjok4Lu7MEeyZeZz5O3gLRwnWV3HmF4m2i7hTs1gZ7fBkj4yiwhBnfhH3zhre4jGC19axZ+ZwKxWciUnioIryA5zJKT2tsHAU9/Ya7sIS4b07uFOzuo5kiiQcHsGZmsWdv4e7sIS7voq3cJS4sIUzNa1zc3gulpsByzlYzjvrCedrOFOzxGnOoWHc6VmizbspziXiwmZnzrnOnEqBM5pwzi1ozoWjBHfWmjlDH1XVmV+jYopzcYlwYyen5IYanIvHcG+vpThnQCzN6WXrnO7cHW2jNOf0LFa2mdOdWyBMc07PJpwTxGHQxOkuHMW9neacaXAKSCaXcC6kOBeJCxsdOOdw5xZTnEd2cubzqCCoc/YlBSoeLG/6h1X93Oja3bRap376vdG3dlD24qTa7eZV+7zdzbS1jn5t0a7z0G0koZew2nZTabvZpF1Ho1d7tdpotw5cp/O2F/Vyfjt1sPZl9GgA25GHsmMSVytUrjxL7Ffr69RsP/1XWNkclSuXiEtFwg0dxlV31oxitp/+K+zhUb2P61F95UWc6bn6CII7O6/XoBGL7ac+jzU0zPazT4FYOmw0Pw6oZOqmSPnZJxHP02VzOcqXLqKCQGcCzWSQbI7w9mpnzmJhp5NurBLOZP0fx6N6bXfO8rNPISLaWTM/BiRr0JSK9TVidNmhnZzJWjlxUNVrugwNs/30F7AyWSovXm7mTNZ2aXCO7sJ5CbE0pz00rG1mWVRvXGvP6TZzxr6vnUoTewbrq3VOOzfU4LyqOaOtzdQaNNdQsT7v1vAI5We+2Mzp65Emd+6I5rRTnM89vdOem/eIyyW9NlCdM9eWU5/3il57p8aZzVF58RJxcWsnp9L27EcKRdTDyqpGe9NuN7rd/u338lm7Mv3mxej1htbPdEM//8S72aHdcXu1Ry8duk6dxH5v2OnRlX6mSPbSMehUf68jMd1+F/2GnOt9Bq8deSg7JlYmS/b0eTInTuuQ3XOPExcLZM88BkrwFpcIk/l6J5/Hyo2QPXtBr+1y/nGiUpHsmfOIbeNMz+sbaVDV/3ptm+z5x4nLJXKPvQlVrZA9eQ4rO5TcoGKiQgFv4RgqisidfxNxoUDuwptQYUTm0ZPYYzpUVTJZwvGJHjnHNOeZCzpU9fwTRKUS2bPnEdfBmUpu+H4FZ3oWLJvchSeIS8U6Z+bkOSQ3hD06CmgfC2/xGNQ4S0Wy5x5HBSHZE6ewxyew3EyD8+QZVDXFefZxwNrJmR1u4Sy25XRn5hqc5RLZC08QVytkTpxFsrlmzqU0Z0FzhiGZR04ma9BoTmdsvM7ZOHaNc5GwoJ1005yqvE32nA791pwuztRMMuWX4jz/BHGxqDn9ant7pjm3i2TPPYGKYjLHTzTWysnkCMfGyZ48q9dIqnGeuZCc92ZOyebInX0cVd7u70JQoOLBmht+mOQ9fpYTv/kJMlJB0f4fdLeGvtcbSGuZTvvWtncaEehn6qDf0YN23605+qj5fb+5V/Zyw+x3v9ZOWE3tRrVay7TW0etxO3WGOu3fOpqUriP9WpKp626jct14+tIDaEdE5IfR2Zkj4P8ppX6sW/mHsmOiAh9/ZRlcF//mdZyJKfwb13DGJwhWb4JFfTXcuDROsHoTyWZ0mckp/Ju6rL96CxUEOgTXr+hRhJWb2EPDuuzENP7yq1ijeYKVG0SlLe3BXNhERPCXX9WJ0Zav40xNEazeTJKA6TBcnbjsdsJ5bRfOQhvO65pzZVk751a174YKQ4LVm1SHh/Wxr85oltE8wa0bREmCtXhrE4QG541rOBOTzZxewvnabfC8/jmnprtzrtzQnDeu4UxO786Z14nRnMkpgpXlJEndqubMJfasc072wJnFv3EdZ2pGl82P4a/crHdK4kqKc2RE1zs1jb98HXtkdCenJfqz/Hhy7CmCWzexvIxex8fLNDjdZk57fIJgbTnFqYhLE4Sry1SzQ3okqr8rgXjA/uk8TBIUtyvjfOwPA77pbUN8w/WfJ1g4QXFsief8c9wpeNgWZN2Y+dECUWxRDDJ4doRrRRxxVxmqbmDHAYGTZcU+zpi9wZFrf0Fh/izXndOcrFwkd+c62zOPUsnkWZcFXCtgvnINhRBbNtveOD4ujoRIna33qYhephyg/5GEQjRKIcgxk7lHhgrb5FBKyFllFEKoXKwkl4tC2i5quFeJ6DRssbLq75USIhwsImxp/O5DpZdyqG33oioVe5hSNMyIXcSLqgR2hhiLSNkICo8qsegQ5dqx0qHZ9bwr2ATKQSldImtVsSWkEI5iS8Sx8iXK2XEuV09zcugGcy//KVtLT/Cat8hWMEwQ23h2iGtFDFnbHH/1M7z8gQ9z4h9/H5eW3oFn+QxTZPr3foFwu0zuTW/iC+/7EPcuFln8ulle+nd/zFdOXmZ84zo3J99MMRoiiBzefPcP+PTb3gfAm//hE0x/9VtQR08SDk/gRN3zuuzUwbYjIvJ1wLuANyulqiIyu9s+D2XHBMfBmZrBGZvEnZnDmZjEmZnTvgKFTZ0S3tbrm1ijo6hqBWdiul7GnZ7DHp/EKRb0Cru11XDHJoimZrCndFl7chpnehZnbAJVKeuU50oRe57ef3q2Xq89MZUwTaCisL66sIqV5pyew5mYShimU5zJRZVwupPTBEkZd3ZOp0qf7MA5OdXgnEnKVsp6dWERYreVcx57Yhpn6u5OTtXCOaufmzkV1mhec05MESRl3JkunNOzDc4JbU97fLIL52Sj7NRdnPEJVBy1t2fyvbtzTmp7juvfij0+iVMqJpy6E1XnnJjCma3ZaDZlzxEQi9hx9bZp/TvStp/C2ZhuzznezOlOTBG3cNr5MeJKg7MvDeDc8MMkQbEdODz56c/z1rd8LdWXruKN5LFHZrlX8ri5rlcOGB2yGc+5+JHNvZJH1o3JeSHixDhBGTvSjvZVXLCB9WXcqSUquLiVLVi9iZufJnCHqOAhKBy/pCPx7AziKUKcetK0g4rQaTdV0O1Y1dil6HtMZByyKMLYoXELF0JlY4uACmlOCre30ZG0LBWh0B0RAFuF9U6CK3pEQUT/9iN0XhRHwCKu71uNXYZtwVYhARnNjNMU9hzhYKuwKXy51ikJcYiUjR+7xEpv053HmHLk4lmCWy3ieyNslD0kFxPfvI47d4rQtSkFHn5kk3FssnaI5/mwvswrv3uTE3/vBtUjLhYxYilu/dlFtu9uc3osz72LOtHi8qfXuXXHwpqIcAqvEU7YlEOPcuBgv9ZY8PPpX7jIl48Okc9kcWZB4j47GQffjrwb+A9KqSqAUmp9tx1k0FLR9iIRuQ30n3d3p6aBQ1nGvYsGjWnQeGDwmPaT57hSaqaXgiLy+8mxu+mOUuod94/1+pNpRx6oBo0HBo9pv3h6bkOg53YkC1RS7z+klPpQj/U/Bfw28I6kjvcopT7fbZ+HcsSkH6N3k4j8lVLqrftR135p0JgGjQcGj+mweEyH4/5k2pEHp0HjgcFjepjbERH5FDDf5qP3ofsZk8BXAV8O/JqInFBdRkUeyo6JkZGRkZGR0WBIKfWNnT4TkXcDH086Ip8TkRg9QnO70z73PxloZGRkZGRkZNRevwV8HYCInAE8dpmyeqOPmPQ0R/aANWhMg8YDg8c0aDxGD1aDeP4HjWnQeGDwmAaNZ7/0YeDDIvIs4APf3W0aBx5S51cjIyMjIyOj16fMVI6RkZGRkZHRwMh0TIyMjIyMjIwGRqZjkkhE/pmIKBHZLZ77oDl+RkQui8gzIvKbIjJ+iCzvEJEXROSqiLz3sDgSlqMi8mkReV5EnhORf3KYPGmJiC0iT4rI7x42i9HBqbWNEK0PJNfHMyLypamy3y0iLyaP705t/zIRuZjs8wER6Ttdarc2QkR+PKn7BRF5e2p722tZRB4Vkb9Mtv+qiHh7sc0uvA+kHenURojIpIh8MjkXnxSRiWR73+dvj1xN7UMnm4tIJnl/Nfn8kVQdbc/r61ZKqTf8AzgK/AE62dL0IbP8LcBJXv8U8FOHxGEDLwEn0F7UTwMXDtEuR4AvTV6PAlcOk6eF7UeBXwF+97BZzOPAzvGONgJ4J/AJdN7QrwL+Mtk+CbycPE8kryeSzz6XlJVk32/aA0vbNgK4kFynGeDR5Pq1u13LwK8B35G8/iDw7n222wNrRzq1EcBPA+9Ntr83Za++z98euZrah042B34A+GDy+juAX+12Xg/7mjjIhxkx0fpZ4MeAQ/cEVkr9oVIqTN5+Flg6JJSvAK4qpV5WSvnAR9HrHRyKlFIrSqkvJq8LwCVg8bB4ahKRJeBvA7942CxGB6p2bcS7gI8orc8C4yJyBHg78Eml1F2l1D3gk8A7ks/ySqnPKn3H+Qjwrf2CdGkj3gV8VClVVUq9AlxFX8dtr+VktObrgV9P9v9fe+HZRQ+sHenSRrwL/d2g+Tv2df72wtTaPuxi8zTnrwPfkJTvdF5ft3rDd0xE5F3AslLq6cNmaaPvQ/foD0OLwI3U+5sMQEcAIBnifAvwl4dLAsD70Tcss8zv61Rd2ohO10i37TfbbL8fpduIfnmmgI1UJ+cgrvFDaUda2og5pVRtcZlVoLYoVb/22ota24duNq8fN/l8Myk/sG3xQekNkcdkl3S5/wI9NDoQPEqp307KvA8IgV9+kGyDLhEZAX4D+BGl1NYhs3wzsK6U+oKIvO0wWYzuT6aNeP2otY1Iu/EopZTUVv87eA7TPuxRb4iOieqQLldEnkDP2T2d/HiXgC+KyFcopVYfNE+K63uAbwa+IRnyPQwto+fVa1pKth2aRMRFNzi/rJT6+GGyJPrrwLeIyDvRi1zlReR/K6W+65C5jPrUXtoIOl8jy8DbWrb/cbJ9qU35nnlSXN/Dzjai2zXbbvtr6OkLJ/mHfhDX+ANtRzq0EWsickQptZJM1dRWt+33/PWrHe0D8J/pbPMaz00RcYAx9DkauLb4wHXYTi6D9ACucfjOr+8AngdmDpnDQTt9PUrDae2xQ+QR9Jz8+w/7d9KB720Y59fX/SPdRqB9B9LOk59Ltk8Cr6AdJyeS15PJZ63Or+/cA0PbNgJ4jGYnyZfRzqcdr2XgYzQ7Yv7APtvrgbUjndoI4Gdodn796b2ev/tgq7cPnWwO/CDNzq+/1u28Hva1cJCPQwcYpMeAdEyuoucTn0oeHzxElneiPdtfQg8hH6Zd/gba8fCZlG36btQPkM90TN4Aj5aOiQD/Nbk+LgJvTZX7vuRavgp8b2r7W4Fnk33+C0n27T4ZOrYR6Kmnl4AXSEX8dLqW0dEyn0vq/BiQOQCbPZB2pFMbgfbT+CPgReBTNDqJfZ+/+2BLd0za2hw9qvKxZPvngBO7ndfX68OkpDcyMjIyMjIaGL3ho3KMjIyMjIyMBkemY2JkZGRkZGQ0MDIdEyMjIyMjI6OBkemYGBkZGRkZGQ2MTMfEyGgXiciHRWRdRJ7dp/qOicgfisilZMGxR/ajXiMjI6PXg0zHxMhod/1P9rhWRgd9BPgZpdR59JoX67uUNzIyMnrDyHRMjIx2kVLqM8Dd9DYROSkivy8iXxCRPxGRc73UJSIX0CvDfjKpu6iU2t5/aiMjI6OHU6ZjYtRWIvJpEfmbyet/LyI/d9hMA6YPAT+slPoy4D3Af+txvzPAhoh8XESeFJGfERH7wCiNjPZBIvJ/ReRfich/StK+P4hjnheRD4rIr4vIux/EMY0GQ2+ItXKM9qR/A/yEiMyiV+n8lkPmGRgli4T9NeBjqQXCMslnfwf4iTa7LSul3o6+5r4GbdNXgV8Fvgf4HwdLbWS0N4nIJDpjahbIKqWCB3FcpdQl4B+JiIWe/vz5B3Fco8OX6ZgYtZVS6jOi77o/CrxNKRUdNtMAyUIvXf4lrR8ovXBYtwUGbwJPKaVeBhCR30Kv02E6JkYDKaXUXfTicw9cIvItwLuBXzqM4xsdjsxUjlFbJauqHgF8pVThsHkGSUqpLeAVEfl2ANF6c4+7fx69uuhM8v7r0QuyGRkNpETkMRH5lIhcSaZzfk5Evny/6hGR0yJyTUROJeVcEXlKRI4qpX5HKfVNwHfu+xczGliZEROjHUqWBv9l4F3AB0TkHUqp3z9krEOTiPwf9CJc0yJyEz3N9Z3Az4vIvwRc4KPoFUC7SikVich7gD9KRqS+APz3g2I3MrofiUhtYblvR69qexn4glLq86kyfwKMttn9PUqpT/VSj4h8CHg7egG7HwJ+BzgpIv8cPU36ewfyBY0GUmYRP6MmicgQeiXOf62U+qSIfC3wU0qprz5kNCMjowcsEflm4O8rpb4zeb8C/F2l1J/tZz3JlM03Av8W+AzwlUqp0r59EaOHSmbExKhJSejqV6fefyb93sjI6A2lLwGeBBCRBaDY2inpZcSkh3quAD+I7pj8R9MpeWPLdEyMjIyMjDrJBxaT1z8JeK0FlFJfsw/1vAR8KTAG/MieSI1eNzLOr0ZGRkZGnfQrwNeKyAtoH6q/EJH373c9SQjyFvBepVS8D9xGD7GMj4mRkZGR0aFLRF4FjitzU3rDy4yYGBkZGRkdqpKFLK+bTokRmBETIyMjIyMjowGSGTExMjIyMjIyGhiZjomRkZGRkZHRwMh0TIyMjIyMjIwGRqZjYmRkZGRkZDQwMh0TIyMjIyMjo4GR6ZgYGRkZGRkZDYxMx8TIyMjIyMhoYGQ6JkZGRkZGRkYDo/8PDcHKuWu4yDQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 648x504 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# read data\n",
    "# a=CosyrAnalyze(\"../..\", pid=0, load_data_all=1,)\n",
    "\n",
    "#gamma = 1000\n",
    "#a=CosyrAnalyze(\"../\", pid=0, load_data_all=1,)\n",
    "\n",
    "\n",
    "# plot\n",
    "fig, axes = plt.subplots(2,2, figsize=[9,7])\n",
    "ax=axes[0,0]\n",
    "ax.set_title(\"wavefronts & comove-mesh\")\n",
    "ax.plot(a.traj_x_predef, a.traj_y_predef, 'k', linewidth=0.5, label='predefined traj.')\n",
    "ax.plot(a.curr_x, a.curr_y, 'c.', markersize=5)\n",
    "ax.scatter(a.wf_x, a.wf_y, s=.1, facecolor='C0', label=\"wavefronts\")\n",
    "ax.scatter(a.cmesh_x, a.cmesh_y, s=.1, facecolor='C1', label=\"comove-mesh\")\n",
    "ax.set_xlim(a.xlim_cmesh)\n",
    "ax.set_ylim(a.ylim_cmesh)\n",
    "ax.set_xlabel(r'$x$')\n",
    "ax.set_ylabel(r'$y$')\n",
    "\n",
    "ax=axes[0,1]\n",
    "ax.set_title(\"afld @ wavefronts\")\n",
    "sc=ax.scatter(a.wf_x, a.wf_y, c=-a.wf_afld/1e4, marker='o', s=.1, cmap=\"coolwarm\")\n",
    "ax.plot(a.curr_x, a.curr_y, 'c.', markersize=5)\n",
    "ax.set_xlim(a.xlim_cmesh)\n",
    "ax.set_ylim(a.ylim_cmesh)\n",
    "fig.colorbar(sc, ax=ax)\n",
    "sc.set_clim(-6, 6)\n",
    "ax.set_xlabel(r'$x$')\n",
    "ax.set_ylabel(r'$y$')\n",
    "\n",
    "ax=axes[1,0]\n",
    "ax.set_title(\"afld @ co-mesh\")\n",
    "sc=ax.scatter(a.cmesh_x, a.cmesh_y, c=-a.cmesh_tfld, marker='o', s=.1, cmap=\"coolwarm\")\n",
    "ax.plot(a.curr_x, a.curr_y, 'c.', markersize=5)\n",
    "ax.set_xlim(a.xlim_cmesh)\n",
    "ax.set_ylim(a.ylim_cmesh)\n",
    "fig.colorbar(sc, ax=ax)\n",
    "#sc.set_clim(-6, 6)\n",
    "ax.set_xlabel(r'$x$')\n",
    "ax.set_ylabel(r'$y$')\n",
    "\n",
    "ax=axes[1,1]\n",
    "ax.set_title(\"afld @ co-mesh\")\n",
    "dim=201\n",
    "cmesh_polar_afld_reshaped = a.cmesh_polar_afld.reshape(dim,dim).T\n",
    "cmesh_polar_ang_reshaped = a.cmesh_polar_ang.reshape(dim,dim).T\n",
    "cmesh_polar_rad_reshaped = a.cmesh_polar_rad.reshape(dim,dim).T\n",
    "# rescale\n",
    "cmesh_polar_ang_reshaped *=gamma**3.0\n",
    "cmesh_polar_rad_reshaped *=gamma**2.0\n",
    "img=ax.imshow(-cmesh_polar_afld_reshaped/gamma**4, aspect=\"auto\", origin=\"lower\", cmap=\"coolwarm\",\n",
    "                extent=[cmesh_polar_ang_reshaped[0,0], cmesh_polar_ang_reshaped[0,-1],\n",
    "                         cmesh_polar_rad_reshaped[-1,0], cmesh_polar_rad_reshaped[0,0]])\n",
    "cb=fig.colorbar(img, ax=ax)\n",
    "img.set_clim(-6, 6)\n",
    "# clevels=np.arange(-6,8,2)\n",
    "# p1=ax.contour(cmesh_polar_ang_reshaped, cmesh_polar_rad_reshaped, -cmesh_polar_afld_reshaped/gamma**4,\n",
    "#               levels=clevels, cmap='jet')\n",
    "# p1.set_clim(-6, 6)\n",
    "# ax.clabel(p1, inline=1, colors=\"k\", fmt=\"%1.0f\", fontsize=7)\n",
    "# cb=plt.colorbar(p1, orientation=\"horizontal\")\n",
    "ax.set_xlabel(r'$\\tilde{\\alpha}=\\alpha\\gamma^3$')\n",
    "ax.set_ylabel(r'$\\tilde{\\chi}=\\chi\\gamma^2$')\n",
    "\n",
    "# cbax=ax1.inset_axes([0.1,1.15,0.8,0.04])\n",
    "# p1=ax1.imshow(coeff_x, origin=\"lower\", aspect=\"auto\", cmap=cmap,\n",
    "#           extent=[gamma[0], gamma[-1], theta[0], theta[-1]], )\n",
    "# ax1.clabel(p2, inline=1, colors=\"k\", fmt=\"%1.1f\", fontsize=7)\n",
    "# cb=plt.colorbar(p1, cax=cbax, orientation=\"horizontal\")\n",
    "\n",
    "#plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Benchmark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## realistic beam-size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### some estimate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beam charge: 1.6021766339999997 nC\n",
      "inter-particle distance: 133.06700394914688 nm\n",
      "delta_alpha=0.003, delta_alpha_tilde=3000000.0\n",
      "delta_chi=9.999999999999999e-05, delta_chi_tilde=99.99999999999999\n"
     ]
    }
   ],
   "source": [
    "gamma = 1000\n",
    "r_beam = 50 # um, beam radius in radial direction\n",
    "l_beam = 3000 # um, beam length in angular direction\n",
    "num_part = 1e10 # number of particles \n",
    "Q_beam = num_part * elementary_charge / 1e-9 # nC\n",
    "print (\"beam charge: {} nC\".format(Q_beam))\n",
    "\n",
    "V_beam = math.pi*r_beam**2.0 * l_beam\n",
    "V_part = V_beam/num_part # um^3, volume of single particle\n",
    "inter_part = V_part**(1/3.) * 1e3 # nm\n",
    "print (\"inter-particle distance: {} nm\".format(inter_part))\n",
    "\n",
    "delta_alpha = l_beam * 1e-6\n",
    "delta_alpha_tilde = delta_alpha * gamma**3.0\n",
    "delta_chi = 2 * r_beam * 1e-6 \n",
    "delta_chi_tilde = delta_chi * gamma**2.0 \n",
    "print (\"delta_alpha={}, delta_alpha_tilde={}\".format(delta_alpha, delta_alpha_tilde))\n",
    "print (\"delta_chi={}, delta_chi_tilde={}\".format(delta_chi, delta_chi_tilde))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### interpolated acceleration fields in (chi, alpha)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,1, figsize=[5.4,4], dpi=120)\n",
    "\n",
    "gamma=1000\n",
    "\n",
    "home_path = \"/Users/hoby/dev/csr/cosyr\"\n",
    "#data_path = home_path+\"/build\".format(gamma)\n",
    "data_path = home_path+\"/build\"\n",
    "# data_path = home_path\n",
    "num_gridpt_hor = num_gridpt_ver = 101\n",
    "\n",
    "\n",
    "a=CosyrAnalyze(data_path, pid=0, load_data_all=0)\n",
    "a.load_cmesh_polar()\n",
    "\n",
    "# reshape as 2D arrays and normalization\n",
    "cmesh_polar_afld = a.cmesh_polar_afld.reshape(num_gridpt_hor, num_gridpt_ver).T / -(gamma**4.0)\n",
    "cmesh_polar_ang = a.cmesh_polar_ang.reshape(num_gridpt_hor, num_gridpt_ver).T * gamma**3.0\n",
    "cmesh_polar_rad = a.cmesh_polar_rad.reshape(num_gridpt_hor, num_gridpt_ver).T * gamma**2.0\n",
    "\n",
    "extent = [cmesh_polar_ang[0,0], cmesh_polar_ang[0,-1],\n",
    "        cmesh_polar_rad[-1,0], cmesh_polar_rad[0,0]]\n",
    "\n",
    "ax = axes\n",
    "ax.set_title(\"$\\gamma={}$\".format(gamma), usetex=True)\n",
    "img = ax.imshow(cmesh_polar_afld, aspect=\"auto\", #origin=\"lower\", \n",
    "              cmap=\"coolwarm\", extent=extent)\n",
    "img.set_clim(-6, 6)\n",
    "cb = plt.colorbar(img, ax=ax)\n",
    "cb.set_label(r\"$E_s^{\\rm acc}\\ [q\\gamma^4/R^2]$\", usetex=True)\n",
    "ax.set_xlabel(r'$\\tilde{\\alpha}(=\\alpha\\gamma^3)$', usetex=True)\n",
    "ax.set_ylabel(r'$\\tilde{\\chi}(=\\chi\\gamma^2)$', usetex=True)\n",
    "# add contour lines\n",
    "# clevels=np.arange(-6,8,2)\n",
    "# p1=ax.contour(cmesh_polar_ang, cmesh_polar_rad, cmesh_polar_afld,\n",
    "#               levels=clevels, cmap='jet')\n",
    "# # p1.set_clim(-6, 6)\n",
    "# ax.clabel(p1, inline=1, colors=\"k\", fmt=\"%1.0f\", fontsize=12)\n",
    "# # cb=plt.colorbar(p1, orientation=\"vertical\")\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### wavelets in (chi, alpha)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x420 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gamma=1000\n",
    "home_path = \"/Users/hoby/dev/csr/cosyr\"\n",
    "#data_path = home_path+\"/run_real_beam_size\".format(gamma)\n",
    "data_path = home_path+\"/build\"\n",
    "a=CosyrAnalyze(data_path, pid=0, load_data_all=0, wf_xy2polar=1)\n",
    "\n",
    "def sci_format():\n",
    "    fmt = mpl.ticker.ScalarFormatter(useMathText=True)\n",
    "    fmt.set_powerlimits((-2, 3))\n",
    "    return (fmt)\n",
    "\n",
    "# usage\n",
    "\n",
    "\n",
    "fig, axes = plt.subplots(1,2, figsize=[8,3.5], dpi=120)\n",
    "\n",
    "ax = axes[0]\n",
    "# ax.plot(a.wf_alpha*gamma**3, a.wf_chi*gamma**2, \".\", markersize=.1)\n",
    "ax.plot(a.wf_alpha, a.wf_chi, \".\", markersize=.1)\n",
    "# ax.set_xlim(-0.5, 0.5)\n",
    "# ax.set_ylim(-0.5, 0.5)\n",
    "ax.set_xlabel(r\"$\\alpha$\", usetex=True)\n",
    "ax.set_ylabel(r\"$\\chi$\", usetex=True)\n",
    "ax.xaxis.set_major_formatter(sci_format())\n",
    "ax.yaxis.set_major_formatter(sci_format())\n",
    "\n",
    "ax = axes[1]\n",
    "ax.plot(a.wf_alpha*gamma**3, a.wf_chi*gamma**2, \".\", markersize=1)\n",
    "ax.set_xlim(-50, 50)\n",
    "ax.set_ylim(-50, 50)\n",
    "# ax.set_xlim(-.5, .5)\n",
    "# ax.set_ylim(-.5, .5)\n",
    "ax.set_xlabel(r\"$\\alpha\\gamma^3$\", usetex=True)\n",
    "ax.set_ylabel(r\"$\\chi\\gamma^2$\", usetex=True)\n",
    "\n",
    "# ax = axes[1]\n",
    "# ax.plot(a.wf_x, a.wf_y, \".\", markersize=0.1)\n",
    "# # ax.plot(a.curr_x, a.curr_y, 'c.', markersize=5)\n",
    "# ax.set_xlim(a.xlim_cmesh)\n",
    "# ax.set_ylim(a.ylim_cmesh)\n",
    "\n",
    "\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "file_extension": ".py",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "mimetype": "text/x-python",
  "name": "python",
  "npconvert_exporter": "python",
  "pygments_lexer": "ipython2",
  "toc": {
   "base_numbering": 1,
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