{ "cells": [ { "cell_type": "markdown", "id": "3f1ebf8c", "metadata": {}, "source": [ "# Example Use of the `Stokes_drift` Kernel\n", "\n", "This notebook shows how the `moacean_parcels.kernels.Stokes_drift` kernel\n", "can be used in `ParticleSet.execute()` as a custom particle behaviour kernel that\n", "adds the effect that waves have on particle trajectories." ] }, { "cell_type": "code", "execution_count": 55, "id": "a6941dd5", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import sys\n", "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "import os\n", "import math\n", "from cartopy import crs, feature\n", "from datetime import datetime, timedelta\n", "from parcels import FieldSet, Field, VectorField, ParticleSet, JITParticle, ErrorCode, AdvectionRK4_3D\n", "\n", "from moacean_parcels.kernels import DeleteParticle, Stokes_drift" ] }, { "cell_type": "markdown", "id": "1eccd4e5", "metadata": {}, "source": [ "Dictionary with the paths\n" ] }, { "cell_type": "code", "execution_count": 56, "id": "941b8dd3-eebb-4149-af84-781e66652a11", "metadata": {}, "outputs": [], "source": [ "#Careful with changes in the keys, these are used throughout the notebook. \n", "paths = {'NEMO': '/results2/SalishSea/nowcast-green.201905/',\n", " 'coords': '/ocean/jvalenti/MOAD/grid/coordinates_seagrid_SalishSea201702.nc',\n", " 'coordsWW3': '/ocean/jvalenti/MOAD/grid/WW3_grid.nc',\n", " 'mask': '/ocean/jvalenti/MOAD/grid/mesh_mask201702.nc',\n", " 'out': '/home/jvalenti/MOAD/results',\n", " 'home': '/home/jvalenti/MOAD/analysis-jose/notebooks/parcels',\n", " 'anim': '/home/jvalenti/MOAD/animations'}" ] }, { "cell_type": "markdown", "id": "cf052eed", "metadata": {}, "source": [ "Some useful functions" ] }, { "cell_type": "code", "execution_count": 57, "id": "d1a0aae8", "metadata": {}, "outputs": [], "source": [ "\n", "def make_prefix(date, path, res='h'):\n", " \"\"\"Construct path prefix for local SalishSeaCast results given date object and paths dict\n", " e.g., /results2/SalishSea/nowcast-green.201905/daymonthyear/SalishSea_1h_yyyymmdd_yyyymmdd\n", " \"\"\"\n", "\n", " datestr = '_'.join(np.repeat(date.strftime('%Y%m%d'), 2))\n", " folder = date.strftime(\"%d%b%y\").lower()\n", " prefix = os.path.join(path, f'{folder}/SalishSea_1{res}_{datestr}')\n", " \n", " return prefix\n", "\n", "def get_WW3_path(date):\n", " \"\"\"Construct WW3 results path given the date\n", " e.g., /opp/wwatch3/nowcast/SoG_ww3_fields_YYYYMMDD_YYYYMMDD.nc\n", " :arg date: date of WW3 record\n", " :type date: :py:class:`datetime.datetime`\n", " :returns: WW3 path\n", " :rtype: str\n", " \"\"\"\n", "\n", " # Make WW3 path\n", " path = '/opp/wwatch3/nowcast'\n", " datestr = [date.strftime(fmt) for fmt in ('%d%b%y', '%Y%m%d_%Y%m%d')]\n", " path = os.path.join(path, datestr[0].lower(), f'SoG_ww3_fields_{datestr[1]}.nc')\n", " if not os.path.exists(path):\n", " raise ValueError(f\"No WW3 record found for the specified date {date.strftime('%Y-%b-%d')}\")\n", "\n", " return path\n", "\n", "\n", "def p_deploy(N,n,dmin,dd,r = 1000):\n", " '''p_deploy returns a random deviation for the number of deploting sites and particles and the depth'''\n", "\n", " #r is radius of particle cloud [m]\n", " deg2m = 111000 * np.cos(50 * np.pi / 180)\n", " var = (r / (deg2m * 3))**2\n", " x_offset, y_offset = np.random.multivariate_normal([0, 0], [[var, 0], [0, var]], [n,N]).T\n", " if isinstance(dmin,int):\n", " zvals1 = dmin + np.random.random_sample([n,N]).T*(dd)\n", " else:\n", " zvals = []\n", " zvals1 = []\n", " for dept in dmin:\n", " zvals.append(dept + np.random.random_sample([n]).T*(dd))\n", " for i in range(len(zvals)): \n", " zvals1=np.concatenate((zvals1[:],zvals[i]))\n", " return x_offset, y_offset, zvals1 \n", "\n", "def filename_set(start,length,varlist=['U','V','W']):\n", " '''filename,variables,dimensions = filename_set(start,duration,varlist=['U','V','W'])\n", " Modify function to include more default variables\n", " define start as: e.g, datetime(2018, 1, 17); length= number of days'''\n", " \n", " duration = timedelta(days=length)\n", " #Build filenames\n", " Rlist,Tlist,Ulist, Vlist, Wlist = [], [], [], [], []\n", " Waveslist = []\n", " \n", " for day in range(duration.days):\n", " path_NEMO = make_prefix(start + timedelta(days=day), paths['NEMO'])\n", " Ulist.append(path_NEMO + '_grid_U.nc')\n", " Vlist.append(path_NEMO + '_grid_V.nc')\n", " Wlist.append(path_NEMO + '_grid_W.nc')\n", " Tlist.append(path_NEMO + '_grid_T.nc')\n", " Rlist.append(path_NEMO + '_carp_T.nc')\n", " Waveslist.append(get_WW3_path(start + timedelta(days=day)))\n", " \n", "\n", " filenames = {\n", " 'U': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Ulist}, # NEMO u velocity \n", " 'V': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Vlist}, # NEMO v velocity \n", " 'W': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Wlist}, # NEMO w velocity \n", " 'T': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Tlist}, # NEMO Temperature \n", " 'S': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Tlist}, # NEMO Salinity \n", " 'R': {'lon': paths['coords'], 'lat': paths['coords'], 'depth': Wlist[0], 'data': Rlist}, # NEMO Density \n", " 'Bathy' : {'lon': paths['coords'], 'lat': paths['coords'], 'data': paths['mask']}, # NEMO Bathymetry \n", " 'US' : {'lon': paths['coordsWW3'], 'lat': paths['coordsWW3'], 'data': Waveslist}, # WW3 u component Stokes drift \n", " 'VS' : {'lon': paths['coordsWW3'], 'lat': paths['coordsWW3'], 'data': Waveslist}, # WW3 v component Stokes drift \n", " 'WL' : {'lon': paths['coordsWW3'], 'lat': paths['coordsWW3'], 'data': Waveslist}, # WW3 wavelength field\n", " }\n", " variables = {'U': 'vozocrtx', 'V': 'vomecrty','W': 'vovecrtz','T':'votemper','S':'vosaline','R':'sigma_theta','US':'uuss','VS':'vuss','WL':'lm','Bathy':'mbathy'}\n", " for fvar in varlist:\n", " if fvar == 'U':\n", " dimensions = {'lon': 'glamf', 'lat': 'gphif', 'depth': 'depthw','time': 'time_counter'}\n", " elif fvar == 'US':\n", " dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time'}\n", " elif fvar == 'Bathy':\n", " dimensions = {'lon': 'glamf', 'lat': 'gphif','time': 'time_counter'}\n", " \n", " file2,var2 = {},{}\n", " for var in varlist:\n", " file2[var]=filenames[var]\n", " var2[var]=variables[var]\n", " return file2,var2,dimensions" ] }, { "cell_type": "markdown", "id": "97c4bf2f-db05-4d5f-b4bb-bdaad6578599", "metadata": {}, "source": [ "Define particles deploying locations" ] }, { "cell_type": "code", "execution_count": 58, "id": "28a99025-a33d-4d66-9e39-aab453f279b2", "metadata": {}, "outputs": [], "source": [ "start = datetime(2018, 12, 23) #Start date\n", "# Set Time length [days] and timestep [seconds]\n", "length = 10\n", "duration = timedelta(days=length)\n", "dt = 90 #toggle between - or + to pick backwards or forwards\n", "N = 1 # number of deploying locations\n", "n = 30 # 1000 # number of particles per location\n", "dmin = [0] #minimum depth\n", "dd = 20 #max depth difference from dmin\n", "x_offset, y_offset, z = p_deploy(N,n,dmin,dd)\n", "\n", "# Choose horizontal centre of the particle cloud\n", "clon = [-123.901172]\n", "clat = [49.186308] \n", "\n", "# Add the offset to obtain a random distribution for the particles at each deploy site\n", "lon = np.zeros([N,n])\n", "lat = np.zeros([N,n])\n", "for i in range(N):\n", " lon[i,:]=(clon[i] + x_offset[i,:])\n", " lat[i,:]=(clat[i] + y_offset[i,:])" ] }, { "cell_type": "code", "execution_count": 59, "id": "92d6511f-3d0c-4a98-ad32-0d4cb970a2da", "metadata": {}, "outputs": [], "source": [ "#Set start date time and the name of the output file\n", "name = 'Waves' #name output file\n", "daterange = [start+timedelta(days=i) for i in range(length)]\n", "fn = name + '_'.join(d.strftime('%Y%m%d')+'_1n' for d in [start, start+duration]) + '.nc'\n", "outfile_w = os.path.join(paths['out'], fn)" ] }, { "cell_type": "markdown", "id": "0c4e63f2-3fb8-4526-b45a-ce5644646287", "metadata": {}, "source": [ "Setting up NEMO and WW3 fields" ] }, { "cell_type": "code", "execution_count": 60, "id": "922eb3dc-e34d-4102-b1d4-4df9de8b2f06", "metadata": {}, "outputs": [], "source": [ "#Fill in the list of variables from NEMO that you want to use as fields (If you get the a NameError, make sure that the field paths are included in filename_set() function)\n", "varlist=['U','V','W']\n", "filenames,variables,dimensions=filename_set(start,length,varlist)\n", "field_set=FieldSet.from_nemo(filenames, variables, dimensions, allow_time_extrapolation=True)\n", "\n", "#Fill in the list of variables from WW3 that you want to use as fields\n", "varlist=['US','VS','WL']\n", "filenames,variables,dimensions=filename_set(start,length,varlist)\n", "\n", "#Load the fields from the WW3 data\n", "us = Field.from_netcdf(filenames['US'], variables['US'], dimensions,allow_time_extrapolation=True)\n", "vs = Field.from_netcdf(filenames['VS'], variables['VS'], dimensions,allow_time_extrapolation=True)\n", "wl = Field.from_netcdf(filenames['WL'], variables['WL'], dimensions,allow_time_extrapolation=True)\n", "\n", "#You can either add the fields by themselves or as a Vectorfield the second option is more convenient to use inside the kernel\n", "#field_set.add_field(us) #field_set.add_field(vs) #field_set.add_field(wl)\n", "field_set.add_vector_field(VectorField(\"stokes\", us, vs, wl))" ] }, { "cell_type": "code", "execution_count": 61, "id": "53f87621-a497-4575-85ba-18ec93118e44", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO: Compiled ArrayJITParticleAdvectionRK4_3DStokes_drift ==> /tmp/parcels-2894/libeb71f11a04abb21bd764d4246e78c1a3_0.so\n", "INFO: Temporary output files are stored in /home/jvalenti/MOAD/results/out-AAIVXQVC.\n", "INFO: You can use \"parcels_convert_npydir_to_netcdf /home/jvalenti/MOAD/results/out-AAIVXQVC\" to convert these to a NetCDF file during the run.\n", "100% (864000.0 of 864000.0) |############| Elapsed Time: 0:06:05 Time: 0:06:05\n" ] } ], "source": [ "pset = ParticleSet.from_list(field_set, JITParticle, lon=lon, lat=lat, depth=z, time=start+timedelta(hours=2))\n", "\n", "kernel_Sd = pset.Kernel(Stokes_drift)\n", "\n", "pset.execute(AdvectionRK4_3D + kernel_Sd, \n", " runtime=duration, \n", " dt=dt,\n", " output_file=pset.ParticleFile(name=outfile_w, outputdt=timedelta(hours=1)),\n", " recovery={ErrorCode.ErrorOutOfBounds: DeleteParticle})" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "#Set start date time and the name of the output file\n", "name = 'No_Waves' #name output file\n", "daterange = [start+timedelta(days=i) for i in range(length)]\n", "fn = name + '_'.join(d.strftime('%Y%m%d')+'_1n' for d in [start, start+duration]) + '.nc'\n", "outfile_nw = os.path.join(paths['out'], fn)" ] }, { "cell_type": "code", "execution_count": 63, "id": "69a1b820", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO: Compiled ArrayJITParticleAdvectionRK4_3D ==> /tmp/parcels-2894/lib918e1a0a223fbcb0da9d0fdc6c4710c8_0.so\n", "INFO: Temporary output files are stored in /home/jvalenti/MOAD/results/out-QHPURZRR.\n", "INFO: You can use \"parcels_convert_npydir_to_netcdf /home/jvalenti/MOAD/results/out-QHPURZRR\" to convert these to a NetCDF file during the run.\n", "100% (864000.0 of 864000.0) |############| Elapsed Time: 0:05:14 Time: 0:05:14\n" ] } ], "source": [ "#Fill in the list of variables from NEMO that you want to use as fields (If you get the a NameError, make sure that the field paths are included in filename_set() function)\n", "varlist=['U','V','W']\n", "filenames,variables,dimensions=filename_set(start,length,varlist)\n", "field_set=FieldSet.from_nemo(filenames, variables, dimensions, allow_time_extrapolation=True)\n", "\n", "pset = ParticleSet.from_list(field_set, JITParticle, lon=lon, lat=lat, depth=z, time=start+timedelta(hours=2))\n", "\n", "pset.execute(AdvectionRK4_3D, \n", " runtime=duration, \n", " dt=dt,\n", " output_file=pset.ParticleFile(name=outfile_nw, outputdt=timedelta(hours=1)),\n", " recovery={ErrorCode.ErrorOutOfBounds: DeleteParticle})" ] }, { "cell_type": "code", "execution_count": 64, "id": "2efb87d9", "metadata": {}, "outputs": [], "source": [ "ds_nowaves = xr.open_dataset(outfile_nw)\n", "ds_waves = xr.open_dataset(outfile_w)\n", "mask = xr.open_dataset(paths['mask'])\n", "colores=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']" ] }, { "cell_type": "markdown", "id": "cff38a1c", "metadata": {}, "source": [ "Plotting both with and without Stokes drift" ] }, { "cell_type": "code", "execution_count": 67, "id": "ab7a8b10", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmoAAAIeCAYAAAALYSOoAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOydeZxcVZn3f+fWvu/d1fveSchCQpYOJJIgEBxAQEXBEYXwOnEccVBewXFX9HUUlFFkxoFxCIyoMCKIAsoelkAWwhoh6X3v6qWWrqVrv/f9o3Jvqrqrq2vtWvp8P5/+dHfVvVWn6rnn3t99zrMQjuNAoVAoFAqFQik9mGIPgEKhUCgUCoWSHCrUKBQKhUKhUEoUKtQoFAqFQqFQShQq1CgUCoVCoVBKFCrUKBQKhUKhUEoUKtQoFAqFQqFQShRxsQdQKD70oQ9xMzMzS24XDocRiURSbkMIgVgshlgc+7oikQg4jhN+WJbNaoyEEMjl8rTGkA8IIShkORZCCCQSCUQi0aLbcByHQCBQsDEUAkKI8Jv/EYvFwuNA7HOFw2FEo9FiDbMsIIRAKpWCYRiwLItQKFTQY5JCoVDKhffee+8pjuM+NP/xihVqMzMzeP3111NuMzc3h4GBgbQuFIQQMAyD6upqaLVaTE5OwuVyZX2RIYSguroaRqMRJ06cyFrslQKEEKhUKtTX1wtiNhkejwcjIyNLflaHwwGj0ZjvYeYVk8mEmpqaBY+73W6Mjo6WtT1zJZX9GIbBmjVrQAiBzWZDOjdTlOWjHOYeZXGo/cqb9evXm5M9vqKXPicnJ9MWWhzHIRqNYmJiAidOnMhJpAGASCSC0WiE0+ksa48CIQS1tbVoampaVKRxHIepqSkMDw+nJWDefPPNfA8z7zgcjqTeM7lcXtb2zAep7KdSqQRPpMfjWa4hUdKkHOYeZXGo/SqTivWopYNGo8Hc3FxGF1Z+21wuxoQQ1NTUgBCCqampsrywE0Igk8nQ2NgIqVS66HbRaBQjIyPw+Xxl+TlT4XQ6YTYn3gBJJJIijab0YRgGOp0OQOy4CIVCRR4RhUKhlD4r2qNmMplSLtUVCplMBq1Wi9nZ2bIUL4QQVFVVoa2tLaVICwQC6OnpyVikzRc/pQjHcZienl7wufj4tZXMYvbjOA5qtRoA4PP5EmL8KKVBOcw9yuJQ+1UmK/qKQghBXV0dhoaG8iqY+IDz+fDvUVtbCwCYmpoqq1gmPlmgsbERcrk85bYulwtjY2NZfa/r16/PdojLCsuycLvdgpeIRyaTIRwOF2lUxWcx+0kkEkHEut3usjr2VwrlMvfKhfiks+Vg3bp1NKGpDIhPTEuHFS3UAECtVkOpVMLn8+X0OkqlEiqVCiKRCAzDgGGYRf9mGAZer7csL+Ymk2lJkTY5OYmZmZmsT04vvPACzj///Kz2XU742Lv5Qk2hUMDr9RZpVMVnMfvFf08r+fspZcpl7pULHMfBbDZDr9cviwfZ7XZDq9UW/H0o2cNxHFwuF2ZmZqhQy4S6ujr09PRkLCz4cheEEDQ2Nma05FWOsWn8AWYymVJu53a7y+6zZUsoFMLc3ByUSqXwmEwmK3gplHKDYRhoNBoAse+M3vVTVgIcxy2bSKOUB4QQ6PV6TE9Pp73Pio5R45FKpTCZTGlPJj7Tsbm5GSqVCmazOSORFggE4Pf7sx1uUQkEAkteZHM9KZVTjBfHcRgZGUnwjvJCbaWSzH4Mw0ChUACg2Z6lTDnNvXJhOc8FK/m8U05kaicq1E6RqkjrfMRiMQwGA1QqFVpaWlBdXZ3Re5WjN42HELLkshXD5HZY7dq1K6f9l5twOIze3l6hkK9MJoNIJFqxJ8359ovPcgZiQq1cj/9Kp9zmHiUR3mvNc8stt+Cuu+4S/r/sssvw+c9/Xvj/X/7lX3DnnXfi8ccfx09+8hMAwJ/+9Ce8//77wjYXXXQRjh07lvJ9WZbF//2//xdbtmzB1q1bsXPnTgwODgIAbrvttiXHPTQ0hC1btiy5Xbbs27cPjz76aNLnbr31Vjz//PMAgIMHD2Lz5s3o6urC4cOH8de//rVgY8oEKtQQC3xPVzwRQmC1WrO+CIfD4bL2KLAsC5fLlXKbXIXaUoWKS5FoNIr+/n7Mzc2BYRh0dHTAYrGsSLE2335yuVyIm+E4Lud4UErhKMe5RznN/Lm1fft2HDp0CEDs3D0zM5Mgwg4dOoTt27fj0ksvxVe+8hUAwOOPP44TJ05k9L4PP/wwJiYmcOTIERw9ehQPPvigEJN6++235/KRCko0GsW3v/1tfPCDHwQAPPjgg7jxxhtx+PBhdHd346mnniryCGOseKHm8/kyyk6USqU5BWsmK+lQbni93pSfIVehNjs7m9P+xYJlWQwMDMDtdoNhGFRVVaGjoyOhyOtKIN5+fJgA//n9fv+K+i7KjXKde5QY88NS4oXae++9h7Vr10Kj0cDpdCIYDOLkyZPYuHEjfv3rX+PLX/4yDh06hCeeeAJf//rX0dXVhf7+fgDAo48+ig984APYsGEDDh48uOB9bTYbrFarcO6vr6+HwWDAt771Lfj9fnR1dWHv3r0AgDvvvBNbtmzBli1bErx9PAMDA9i+fTtef/119Pf347LLLsM555yDCy64ACdPngQAPPLII9iyZQu6urpw4YUXLngNjuPw5S9/GWeddRY+8pGPYGpqSnhu9erV+OEPf4jzzz8fjzzyiOBt279/Px555BH867/+K6699lp8//vfxx/+8Ad0dXXh4YcfzsYceWPFByQsVeOL78fJX2DiLzqZEo1G4XQ6sx1qyUAIgc/nE2pizSdXoVbO8DFrtbW1MBgMkEqlaG5uhtvtxvj4OFiWLXuhngkajUaITWNZdsW316JQlpPa2lqIxWKMjIzg0KFD2LZtG8bHx3H48GHodDqsW7cuoRbm9u3bcckll+Dv/u7v8JGPfER4PBKJ4OWXX8Zf//pX/PCHP8QTTzyR8D4f/ehHccEFF+DgwYM477zzcPXVV2Pjxo34/ve/j//8z//E4cOHAQBvvPEGfv3rX+PFF18Ex3HYtWsXdu7cCYPBAADo7u7GZz7zGdx9990488wzcfHFF+POO+9Ee3s7jhw5gi996Uv4y1/+gn/913/FY489hrq6uqQrPI899hh6enpw9OhRTE5OYvPmzbj22muF5+VyOZ577jkAwDPPPAMA2Lt3L1577TXhs//617/GG2+8gX/7t3/LjzFyYOVeUU+h0+lSCi+dTof6+noAp0twZIvdbs9631KCZdmUd965CrVt27bltH+x4TgOExMTwv+EEOh0OqxatQpGo7HiPUq8/fjYNCD2nQwNDZVlSZqVRLnPvUpgJhzGv42PYyaLuZLs+nT22Wfj0KFDOHz4MLq6utDV1YVDhw4Jy57pcPnllwMANm3ahKGhoQXP19fX4+2338att94KhmFwySWX4IUXXliw3WuvvYYPf/jDUKlUUKvVuOyyy/Dqq68CiPXn/sQnPoF7770XZ555JrxeLw4dOoRPfepT6Orqwhe/+EXYbDYAMUH5uc99Dvfee2/S5LaDBw/i4x//OEQiEWpraxfEXl555ZVpfe5SYcV71GQyGcRicdILCCEEFosFExMTUCqVMJlMQjmOTOHjAyrFm+J2uxf1LuYq1CYnJxcExVYCDMOgpqYGBoMB/f39FetZmpychFarhdlsFlpqTUxMZNyujbL8VOrcKyd+PT2Nb4yMAAC+fKo4erqEw+EFiXG8MDt+/DjWrl2L+vp63HnnndBoNPjMZz6T1uvyXjeRSIRIJJJ0G5lMhosuuggXXXQRqqqq8Oc//xnnnXdewjap5r9Wq0V9fT1ee+01nHHGGWBZFjqdTvDGxfOLX/wCR44cwV//+ldheXd+2ahU1+n4ckrlwIr3qAGAwWBIqBTM/5jNZoyMjMDr9WJubg4jIyMZ1T6Jp1zbRS0Gy7JCluN8MsmgTUayO7ZyI9VJQi6XJ2RBVhpDQ0NgGAYWiwVAzJPsdDor6vivVCph7pU7n7ZY8P8aGvDpU/MnE5L1zz377LPxl7/8BUajESKRCEajES6XS/CwzUetVmec8Pbmm29ifHwcQOzacPz4cTQ2NgKIdSThHSE7duzA448/jrm5Ofh8Pvz5z3/GOeecAyAmBh966CH89re/xUMPPQStVovm5mY88sgjAGIi75133gEA9Pf3Y9u2bfj2t78Nk8mE0dHRhPHs2LEDDz/8MKLRKCYmJvDSSy9l9HmAWNhGqRTmpkINgF6vB8dxUKlUOOOMM9DR0YGGhgb4fD4Eg0Fhu2wvNHwF+0q6UHEcB7fbnfS5ShUgudDX14epqSnBTa/X61P2SS1n+MxohmHg8Xhgs9kq6tinUAqJWSLBl2trYT7ljc6VdevWwW63Y+vWrQmP6XS6pL1BP/7xj+NnP/sZtm/fLiQTLMX09DSuvPJKbNmyBdu2bYNIJMI//uM/AgCuv/56bNu2DXv37sWmTZtwzTXX4Nxzz8WuXbtw3XXXYePGjcLrqFQq/OEPf8AvfvEL/PnPf8b+/ftx3333oaurC5s3b8bjjz8OAPj617+OrVu3YsuWLdi5cyc2bNiQMJ7LL78cbW1t2Lp1K2688Ubs3Lkz068N5557Lt5///2SSCYglXoC3bJlC5dJqvns7CwkEgkGBgYAAEajEXa7PWEZj2VZ1NXVCYGPPD6fDyMjI5BIJNBoNFCr1VAoFAl1o0ZGRipuqUsqlaKzszPhMT4WKZc7kZGRETQ0NOQ6vKIiFouxevVq4f/33ntPsL/VaoXZbMbc3BwGBgYqSsQQQjA9PY1du3YhGAxW9BJvJVIJc6+UiEajC86RhSQUClXsDWCl0d3dvWD1af369cc4jltQUG7Fx6jx6HQ6weul1WphMBigVCohEomEPp383/HY7XbBYxCJROD3+4VYNLlcLgi+SrtYEUKStpJyuVw518laqpdoOcLHXHg8HuHzKZXKrJYZShVCCKqrq6FSqRCNRjEwMFBxx32lU4lzbyVBVzMqE7r0GUdVVRXWrVuHxsZGyOVy6HQ6wTvGJx3wE4EvNZBsWYcvwRAIBBAIBBKWTysBvkzJfKEWDocxMTGRs4eIj0MoZxZLstDpdJDJZMJjFoulIsqZMAyD5uZmmM1mPP300xgYGKD9PMuQSph7K5lybU1ISQ31qGXJ4OAg5ubmkj5HCBFqjDkcjopb2mpoaFhQ9JevH0Y9KDHSvbOVSqVlfXwQQoRacRKJBBzHIRQKJQ1qplAoFErmUKGWJRKJBCKRCBzHJYgTqVSKUCgEn89XcaKFYRg0NTUlrdXjcDjydjeXae/UUiRdoVbOTbAJIdBqtairqxO8gpOTkzCbzWUtPlcylTD3VjKSPCUgUEqL8r1KLCNOpxNzc3OoqqoSJkJDQ4PQt9DpdAoZkLwnoRJFWktLi1BlPp5gMJjXzL74IPyVgEQiKTsPFJ/ZKRaLMTQ0JIh3u92+4uxXSVDblTc0xrAyKf/gmGVgbGwMTqcTJ0+eRCgUgtfrxejoKN5//30MDw8LNdIq1YtACEFzc3NSkcYveebzs7/44ot5e61ikUlQb7llaYlEIlitVjidToyOjsLn82FqakpIoqkE+61UqO3Km0pJTKIkQoVaGqxZswarVq1CY2Mjent7MTw8DJfLBZZl0/KclXsmDiEkqUgDYvVzKi1ZIh9kYvNyuQsmhEAkEkEmk8FmsyEQCCQI9ErzIlMo5c4tt9yS0Pj8sssuw+c//3nh/3/5l3/BnXfeiccffxw/+clPAAB/+tOf8P777wvbXHTRRTh27FhexnPbbbct+tz999+PrVu3Ytu2bdiyZQv+/Oc/AwB+/etfC8V0U7F69WrMzMzkZZzz4ZvWJyP+u5uensa5556L7du34+DBg7j77rvz8v5UqKUBX3ojHA4viElbCoZhoNFoylqsLTb+QCCA6enpvHsS47Miy5VM7C2TyUr++CCECMf+Uq2gKsF+KxVqu/Jm/nmEb68EnG5jGC/C+H6fl156Kb7yla8AiAmPEydOFGR8t99+e9LHR0dHcdttt+HZZ5/FkSNHcODAAaxfvx4A8MADDyT0Ti4lIpFIwnd34MABrFq1CocOHUJ9fT3+67/+Ky/vQ4XaIkQiEdjtdvT19eHkyZNC4c5MRAmfIdnQ0FC2J0C+pMR8WJbF8PBwQZZ7s6kiXWpUglCLLxvC97hNx96VYL+VCrVdeTO/T2u8UHvvvfewdu1aaDQaOJ1OBINBnDx5Ehs3bhQ8RocOHcITTzyBr3/96+jq6hI6Ezz66KP4wAc+gA0bNuDgwYMAYjfq+/btw9atW7F9+3Zh2Xy+9+mjH/0oXnrpJXzrW9+C3+9HV1cX9u7dmzDO6elpqNVqoVqCWq1Gc3MzHn30Ubzxxhu4/vrr0dXVBb/fjxdeeAHbt2/H1q1b8bnPfW7Bio7f78dll12Ge++9Fz6fD5/73Oewc+dObN++XfDSvffee/jABz6Arq4ubNu2Db29vQu+y//5n//Bhg0bsGfPHrz22mvC4/v27cNXv/pVfOhDH8I3v/lN4fO+/fbb+MY3voGnnnoKXV1d+OY3v4n+/n50dXXh61//eubGjIMKtSR4vV6cPHkSNpsNfr9fuEhlssRHCEFVVZXgjWpqairgiHODYRihk8J8wcC31prP5ORk0kb2+SBZE95yo1yXPgkhUKlUqK6uRnNzM+rq6oTPkq4orwT7rVSo7cqb+R1hamtrIRaLMTIygkOHDgnLiocPH8Ybb7yBdevWJcTIbt++HZdccgl++MMf4vDhw2htbQUQc1y8/PLLuO222/DDH/4QAIRlvaNHj+L+++/HP/zDPyza/xkAvv/970OhUODw4cPYv39/wnMbNmxAdXU11qxZg3379uGJJ54AAHzkIx/BWWedhXvvvReHDx8GIQT79u3Dr3/9axw9ehTRaDTBa+Xz+XDllVfiqquuwvXXX48f//jH2L17N1555RX89a9/xTe+8Q34fD786le/whe+8AUcPnwYr7zyCurq6hLGMzExgR/84Ad47rnnknoYe3p68MQTT+BHP/qR8NiZZ56Jb33rW/jYxz6Gw4cP4wc/+AFaW1tx+PBh4TvLFirUkhCJRBY8xrJs2uUn+LIF8X3UfD5fyRY2ZVkWYrEYq1atWvCcXC5f0I1hbm6uoPXhSqURbi5kItQYhkFVVVXRvWqEEBgMBrS0tMBisUCpVGZl50qw30qF2q4EmLNDfPjfgTl7xrsmC8s5++yzcejQIaEJe1dXFw4dOiQse6bD5ZdfDgDYtGkThoaGAACvvvoq/v7v/x4AhBjunp6ejMcMxBKUHnvsMfzmN79BR0cHvvrVr+IHP/jBgu26u7vR3NyMjo4OAMCnPvUpvPLKK8Lzn/jEJ/DpT38an/rUpwAAzz33HH7605+iq6sLF110EQKBAEZGRtDV1YXbb78dP/3pTzE8PLwgBvvo0aM499xzYbFYIJVKceWVVyY8/9GPfnTBdbGQlKZyKDJarRb19fWwWq0wmUzQarUZeT1kMlmCJyIajcJms5V0sDV/go5fouUFZzyFXPKsJDIVXUajsehCXiwWw2q1Cv+Hw+GUd8iU0kUikRRd+FOyQ/zug5Ac+D7E7z6Yl9fjhdnx48exdu1abNu2DUeOHMlIqPFeN5FIJDgyFrsGiMXihGtduitRhBBs3boVN998M+6//3489thjC7ZZ6rqzfft2PP3008J2HMfht7/9LQ4fPozDhw+ju7sbq1evxlVXXYXf//73UCgUuOyyy3DgwIGk41mMZKtMhYQKtSTwcVkmkwk1NTVobGxEe3t7WsYRiURobm4GwzBCS6UTJ06UfDsdjuPgdDoXfMb5MQ8TExMF/yxnn312QV9/Ocj0IskwDKqrq4t2ceWX5+PFosvlyuq1KsF+5Y5Op4PBYMj4eKK2Kz6R9VcjvPtbiKy/OuN9+RiveM4++2z85S9/gdFohEgkgtFohMvlEjxsyV4jnTIfO3fuxIMPxsRkT08PRkZG0NnZiaamJrzzzjtCm8XXX39d2EcikSQNmRkfH8ebb74p/P/OO++goaFBGA/vSFi1ahWGhobQ19cHAPjd736HD3zgA8J+3/rWt2A0GnHjjTcCAC644AL88pe/FITbW2+9BQAYGBhAS0sL/umf/gmXXHIJjh8/njCerVu34qWXXoLdbkc4HMYjjzyy5Pcxn3z2caZCLQOWUvOEELS0tCASiWB4eBjd3d2w2+0lX2ONEAKlUgm5XA6tVguxWAyxWAyVSpXgYfN6vXC5XAX/LCMjIwV9/eUgG8FlMBiK0qmAj6ec7zV2Op1Z2boS7FfOMAwDlUqFqqqqjO1HbVcCKE2IdH0BUJqW3nYeyQpnr1u3Dna7HVu3bk14TKfTJYTn8Hz84x/Hz372M2zfvl1IJkjGvn37wLIstm7dik9/+tO45557IJPJcPbZZ6O5uRlbt27F1772NWzcuFHY5/rrr8e2bdsWJBNEIhF8/etfx8aNG9HV1YU//OEPQsmLT3/60/jnf/5ndHV1geM43H333fjUpz6FrVu3ghCCz372swmvdfvttyMQCOAb3/gGvva1ryEcDguxebfeeisA4OGHH8aWLVvQ1dWFkydPCku4PDU1NfjGN76B8847D5dccknCZ0gXk8mEs88+G1u2bMk5mYCUsoDIhS1btnDxSj4fjIyMYHZ2NulzfHxPIBAQEhDKBYvFsmTrmGg0iu7u7mXxDD733HM4//zzC/4+hcRgMCwIUE2H2dlZjI6OLuvxo1Ao0NraCkIIotEoZmdn4XA4EAwGsxpHJdiv3FmzZg3cbjfGx8czsiG1XX6JRqPo7Oxctvdzu90LwlUopUl3d/eCOLf169cf4zhuy/xtaQupDIj3kjAMA5FIBLFYLBT+5IvglhvptC8aHx8vy89Wbmi1Wkil0mUrIswwDBobG4Vje3JyMmtPGqU0kEgkYBgGU1NT1I4USgVAhVoG1NbWwmq1QiQSgWVZOJ1OTE9PJxQDLUeWEgVutxtut3vZTvpr1qxZlvcpJLOzs0LGUCYQQlBTU4OhoaGCf9+EENTV1SU0cp7fbSAbKsF+5QwfG5ON95varrwppVI/lPxBY9QygGEYiMVi2O12nDx5EpOTk4hGo2Ur0HiSlSOJf265l+KWM+25UOSSHatWqwt+wiWEQKPRLChmnI/m8JVgv3KFr4OXbZY5tV15QzN9KxMq1LJgeno64y4FpUwkEkn6WTiOw+jo6LIL0fkZOOVKMBjE5ORkVvvW1tYW9KQrEokWxNDxrdJypVLsVw4wDCMUqlYqlbBYLELGeTZQ2+Wf5bxOpFvrk1JcMj0m6NJnhrAsW/KlNjKFEIJIJJKwBAbEljx9Pl+RRlX+cBwHu90OjUaTcd0dhUIBlUpVkAKkhBA0NjYu8J5EIpG020RRio9EIkF1dTUUCgWkUqlgu76+PmrDEoEQApfLBb1eT71dFAAQ4tkzOR6oUMuQcDhccRczQgjC4fACobZU8+1CUVNTs+zvWSg4jsPw8DA6OzszXlaqqalBb29vXm1ACIHJZIJSqVzwXL6O7UqyX6lCCEF9fX3CDQDvAc8lEYXaLr8QQjAzM4Pp6elleb9k53FK6ZGsXWMqqFDLkFAoVHFCDYh9rmQX72LQ1tZW7CHklWg0ipGRETQ1NWXcrF2r1S5aEiYbpFJp0lIsHMflLbO30uxXiqhUqgSRFo1GMTQ0lHNpIGq7/JLpBTlXIpFI0eMM4z9vpV0niwWNUcuQUChUcQcfy7IFa7CeDfG92yoFn88Hp9OZ8X757FbAL3kme72xsbG8lQSpRPuVEoQQ1NbWCv+Hw2H09fXlpX4jtV15U2z7qVQq1NfXo7OzEw0NDXS5N09QoZYh2RYBLWUYhqHu8gLDcRwmJiYyFkNSqTSrVkBA7ILOB5srFAo0NDQkdJrgcTgcmJ2drbjjuhLhl675si/hcBi9vb0VeQNJKT+USiV0Oh0kEgk0Gg00Gg0Va3mALn1mSCU2qeY4rmSWPYFYIH0lwnEchoaG0N7enlED9qqqKqHvZqqLMcMw4DgODMNAqVRCrVYLbcAWO1nOzc1hYmIirxf5SrVfKcAwDKqqqoT/XS5XXpObqO3Km2LajxCS0AJvfHwcHo+H3kDkASrU0sDn88Hv90Mul+elzlSpQQgpKY/aOeecU+whFIxwOAybzZawdLUUYrEYq1atgsvlgsPhEI5BQghYloVMJoNKpYJarYZCoUjbluFwuCCFdSvZfsWEEAKr1Zog8vPV9JmH2q68Kab95gs16qXPH3TpcwlYlsXAwABsNhump6eT1pla7oDRfKNUKktq/K+++mqxh1AwOI6D0+nM+AIrEolgMpnQ0dGB9vZ21NTUoKmpCWeccQY6OjpQW1sLrVabtkhjWRZDQ0MFKTVTyfYrJlKpFHq9Xvif47i8182ititvimk/juMSCnUnC7OgZAcVakvA3yXwJSykUimkUimUSuWC1PhyhK9kXkpUetFGjuMwMjKSdXFZmUwGo9EIlUqV0RJq/PvnM3lgPpVuv2LAt/uKv6EKBoN5v8GititvimU/kUiE1tbWBHGmVqtLygFQztClzyUghGDVqlWYm5tDNBqFVqtFOBzG5OSkUDahXEUaUJpCbSXAt5hqaWlZlpMZx3EIBAIJiQPlfNxWIrxnPpltNBqNYDuZTAaJRAKfz0dtSCk6EokELS0tC/oaWywWKBQKuN1ueDweofQPPWYzhwq1NODFTCQSwfj4OJxOZ8UcbPPd1aXAzp07iz2EZcHv98Nut8NsNhfsPcLhsBDbtlirsHyzUuyXT/hzTGNjI0KhEJxOJ1wulyDarFYruru7hW0XE3S5Qm1X3hTCfnySEg9/Y8lfO5qbm5PWbmMYBlqtFlqtFhzHIRgMYmBgoOI6+ywHVKilCcdx6O7urjhPhFQqzWr5rJD09fXhjDPOKPYwCg7HcZicnMx7E3aWZeHxeGC324WlkOU8ZleK/fIJx3FCMW25XI6amhpYrVahO0i8t6KQ5yBqu/ImX/bjxZlarYZOp4NarYZIJEI0GkU4HEYoFALLstDpdGldPwghCAQCy943ulIorSt0CRMOhytOpAEoyWXPiYmJYg9h2eBLduR6AuM4DnNzcxgdHcX777+PsbEx4SK/3MfsSrJfPgmFQkIZFuC0l02tVoPjuGVZIqe2K2+ytR/vpZVIJDCZTEKiUlNTE/R6vRCnLRaLoVAooNPpYDAY0r7Jj0ajeS8DtJKgHrU04QN3K+lAYxgGarW62MNY8UQiEdjtdlgslqz2DwQCGBwcRDQaFY7PSjpOKw3+osiyLMRiMeRyOZRKJRQKRdIbJz75g0LJN4QQyGQyGAwGaDSaBXFm+WJqaop603KACrU0qcTK3xzHlWSBy3Xr1hV7CMsKH+ifC/EirdisNPulAyEEUqkUCoUCSqUScrkccrk8LY+EzWZbtppU1HblTbr2471jtbW1Bc/ODAaDcDgcJXN+KkeoUEuTSmwdBaCkCt3yrMRg01wKKcvlcohEoqzLfeSblWi/xSCEQKlUora2Nqu6UlNTU8t6kaO2K2+Wsh/vza2urobRaCz4cjrvDa7Ea+dyQoVamoTD4YRsFx6+lyLDMAk/0Wi0YsVdoXn//fczqtxfCYTD4Zz21+l0sNvteRpNbqxE+82HEAKRSIS6ujpoNJq09+O9qz6fDx6PR4gzXC6o7cqbVPYjhMBoNKKqqipplmYhcLvdtDZfHqBCLU3q6uoQjUYTxFiquxGO4zA8PAyv11uyYq1Ux7USydWTodPp4HQ6aRxICUAIgcVigdlsXnJpk2VZ+P1++Hw+eL1e+P3+gpXeoKxMCCFQq9WoqakpWAxaMliWpQkEeYIKtTQRi8UJfcyWghCCxsZGDA0NlWVhymg0mpCBtpzU19cX5X2LCcdxiEajWd/pllKs4Uq0HxCb8xqNBjU1NSlDCjiOw9TUFDwej5CkFC+wi3muWKm2qxTi7ccnCtTW1kKpVC77WKanp+lSep6gQq2A8GJtcHAQfr+/JMVasrR/juMwOjpaNO9MQ0NDUd63mDAMg3A4nLVQI4RAq9UWTVzHs9Lsx5c1qK+vT+uCODU1hZmZmZLM0F1ptqs0GhoahFCcmpoa6HS6orRxCoVCCcc4JTdoHbUCwzAMmpuboVAo8jJh8j3pkk0kp9NZ1CXb1157rSjvW2wySQbgg3Snp6cFO+n1+pIoXrxS7Bd/Qezo6EhLpAUCgZK+gK0U21UihBAcOnQIVVVVWLVqFfR6fdF6bY6Pj5fsMV6OUI/aMsCLtYGBAQQCgawOYEIIrFYrWJbF1NRUXiZBsrpwwWCQxhUUAY7j0k4oYFkWQ0NDmJubAxC7e62trYVKpaJ2yxP83FisdiIhBHq9HlarNW0vKMdxGBkZoTai5B1CCHQ6HWQyWdb1GPOF1+uFz+cr6hgqDSrUlon5Yi2b/flK0BqNBsPDw0K3hFyYv38pXEhWYhFevoXQUkSjUQwMDCRkFLtcLoRCITQ1NUGj0cDtdhd6uCkpd/vxJTXq6+sxOTmZUMOMb/FUV1eXcduv6enpnMqwLAflbruVxvzyLyaTqajjCYfDtBxHASCV+oVu2bKFe/3114s9jAVEo9GEukjJPFoej2dBE1yr1ZowCfmMGr5xczYQQtDZ2ZkQ+NzX10fTqYuETqdLGSPEsix6enqSet74wOGqqqqixheWG3K5HGKxGKFQCJFIBCzLQq/Xo66uTlg24ltzRaNR1NbWQqvVZrSkFIlEMD09TYt+UvIOwzAl0Zs1Go0ue82/SmT9+vXHOI7bMv9x6lFbZkQiUUrXNMdx6OnpEe68+TgYg8EgbBONRjE9PZ1z4Pj8bDMg1vuz2ELtlVdewc6dO4s6hmKwlLclEoksGsfGe+SCwWAhhpYR5WI/PtknvmQBy7IL4vyUSiU6OjqEfdIlHA5jenoaTqcTQGklDSxGudiOEmP+8fjAAw/gmmuuWbb3Z1kWDodDCMcph2O8HKFCrcQghKChoQHj4+NCD0CVSiUU0bXb7UIwcj4mxfzXUKlUcDgcRfXIlILYKAZLxaixLJuy3yx/0iz2ybJc7KfVahfUlVosGSNTgTY1NZWTt7tYlIvtKMnh41azJZNWdF6vFxMTE2BZtuyO83KDCrUSRKFQoK2tbcHjExMTee/5N/+1FAoFnXRFYqmaQ+mI51w7HKwU+DY6+SQcDi+IaaNQCkk+szodDgfGx8fTfs1kKzKUwkCFWhmRypuSLfNfTywWC967YrFr166ivXcxWarobbkUjywH+yXzpmUKy7IIh8MIhUKYnZ2tCIFWDrajnGa+qLruuuuyep25uTlMTEwASH+JvtyP9XKCCrUyYn61cz4DLf7CzrekyWWyKZVKeDye3AabAydOnMC6deuK9v7FYqmit+Vy91rq9svEm8ZxHPx+P0KhkBADGAwGEQ6HEY1GhSbX5WKbpSh121ESmS/UXnrpJVxwwQUZvUY4HMbg4CAVXiUMFWplhFgsXuBVa2pqWtDayufzYXh4eMnYAY7jknoVVCpVUQveTk5OrtiLRaqit+USC1Lq9kvXm8bXPfN4PIuKsUoLoC5121ESmS/U+vv7M9qfZVkMDg5WzI1GpVL8MuaUtOEFGd8QXqVSJe0/qlKp0NnZuWT7EJ1Ol7QnoVKpLFpF65UMnwywGJkE+lYivPdKKpXCYrHAZDJBJpMJmdHpvka63rTJyUmhVA69kFFKkVzO03yrwFKv7UehHrWyQqlUoqqqCnK5XKj/tBgikQj19fXQ6/UYGRlZ4I0hhKCqqirpvmKxuKiCYMOGDUV772Lj8Xjg8/mgUqkWPCeRSAoSp5hv8mk/hmHAcRzkcjn0ej20Wu2CmwuWZREIBODz+eD1eoWl/2ResHS9aQ6HA3a7veS/63yzkudeOTJfqF100UVp7zszM7OgZielNKFCrYwQi8UZtwdRq9Xo7OxckDGa6oJVzPg0AFl1bqgU+Lvczs7OBSdhnU4Hv99f8gJiKful4/3iOA5qtRo6nQ4ajSZlmyaGYaBUKqFUKmGxWISacnNzc/D5fPD5fMKScjreNLfbvWLbqK3kuVeOzD9HpHvu9nq9eWtFSCk8VKitAHjvmk6nEyqsp7pgFTt7rbu7O2WF/konEolgZmYmqSivrq4Gx3ElUS9tMRazH79sWV1dnVKsMQwDuVyedYN5vkuDTCYTCkVHo1FEIpElvWl+v78k2qgVi5U+98qN+ULt1VdfTSvGkJbxKS+oUFtBaDQadHZ2wu/3L3rB4rNGKcWD4zhMTU1Br9cnzfS1Wq3gOA5Op7MsBAUfW1ZTUwO9Xl+U+EeRSLRk8/RQKISBgYGy+E4pFCA973Qy9Ho9JicnUyYvUUoHmkywwhCJRCkbL/t8vqInEjQ1NRX1/UsBjuMwNjaW9Dle9CyVLFIs4u1HCIHRaMSqVatgMBhKcrxAzIvZ39+/4pMG6NwrL+bPpzPPPDPt/ZbybFNKB2olSgKzs7NFv1jlu2J8ueLz+RaNOSGEoK6uLmVCSbGorq4GIQRqtRodHR2oqalZ0ptVTPgSBdS7QOdeuTFfqLW3t6e9r16vL+l5STkNFWorkEgkkjRomOO4oicSAMCRI0eKPYSSgPeqLSacCSHQ6/XLOiZ+GXOxH4ZhcPToUTQ1NaG5uTnn6v/xRCIRuN1u2Gw2DA8PY2RkBCMjI7DZbFndXLAsi+npaZw4cYL2uDwFnXvlxXyh9oc//CGjfalXrTwovdtxSsHw+/2Ynp6G2+2GUqlEa2trwvOhUKhs2hStFKLRKKanpxf1dOj1eszMzBQ8rooXYWazOeVduEgkglwuT7m8ng58rCSfuen3+4Wm9PNFGSEEHo8HLS0taXkYo9EoZmZmhOxZGpNGKVdyDSXQ6XSYnJws+ioKJTVUqK0A+BYhoVBIuCgplcoF20mlUjQ2NiIYDCIQCCAQCCAcDi/7JNbpdMv6fqUMx3GYmZlBVVVV0pOyTCaDWCwuaBYXH2eW7t33YvX5UsGyLGZnZ4VyGuFwWKihFi+kkokqjuMQDAbR09ODlpYWyOXyhNeNRqNC1qfX64Xdbl/0tVY6dO6VF7Ozs6itrRXODZnOPT7edXR0lIq1EoZU6slqy5Yt3Ouvv17sYZQEbrc7oeQAwzCor6+HVqtNa3+n04mJiQk6kYsEwzBobW1NECDxTE1NYXp6Ou/Cg+8lW19fD5lMltfXns/o6GheysIQQiCRSBCNRoUiz/yyLFB5LZ8oKxuGYVBbW5tTCATHcejp6aEdCkqA9evXH+M4bsv8x+ni9ApAqVQKrXaA2MRUKBRp77+YQCgUL7744rK+X6nDNwZfjHzHqRFCIBKJUFdXh9bW1oxF2n333ZfR9rOzs3mr3ccXu41vt8W3gCqXXqnFhM698oKPs+TJdO4Bp71qpZqRTaFCbUUgFovR3t6O1tZWqNVqSCSSpD0+F0MqlS6rN41m3yXCcRx8Pt+iz0ulUhiNxrycaAkhMBgM6OzszLrmWSZ35qFQCGNjY1RAlQh07pUffBcO/u9sUKvVeU38oeQXGqO2glAoFGhubk54jM/0nJmZgdlsTrocyhcLnZ9owF/E4y/mHMehoaFhRVd3LwT8iXgxrFYrRCJRWkugfL9QhmHAMAzEYjHEYjEkEglMJtOyeVA5jsPw8DBdUqdQcoDjOExPT+dUA4/3qg0NDdHzdglCY9RWOBMTE0I7Ip1Ot2j7mMnJSfj9fkG0icViiEQiMAyT8FsikUAsFmNsbAwul2tBI/h0jjeWZWnKeBLOOOOMJb8Xu90Om8226PfMx7QUslhuuvaLP/YopQGde+UJIQSdnZ3CuThbent7ab/XIkJj1ChJiV/qSOW1qa6uRnNzMxoaGlBbW4uqqiqYTCYYDAZotVqo1WooFAqhPAJf9BSIeeTa29thsVjSEgfvvvtujp+q8mAYJq1aXyaTCXV1dUIJDd5rxsNxHFQqVUHjUZ5++uklt/F4PFSklSB07pUvTqczrbmXChqrVprQpc8VDp8x5PP5Fl2C4h/P5E5NLBajuroaDocDzc3NkEgkkMvlkMvlSy6LzszMZPYhVgAcx2Fubi6tJBC9Xg+9Xg+WZREKhTA7Owu73S7UISt0N4Ph4eGUz0ciEbo0XqLQuVeecByHQCCw5NxbCpVKBblcTvs9lxhUqK1wRCIRNBoNNBqN8FgkEoHNZoNKpYLBYMDQ0JAQzN7U1ASVSoVwOIxgMJjwI5fLUVdXJ7yOyWSCyWRKeD+tVguj0SjUsqKkB59QMP/7TAXDMJDL5XC5XILYjs/+LQY0Lo1CKQz5qqWoUqmoUCsxqFCjJBAOh3Hy5EkAELw31dXVQqHQkZGRhDiW+AvuYt4elmUxNzcHt9sNt9u9ZPeDTZs25eOjVBzZnjxDoZAQH5is0HG+ueSSSxY8xt/xz8zM0ItACUPnXvkSDoeTzj1K+UOFGiUBkUiE6upqGI1GIc5JqVQK9Xr45ar5HhGGYRbU8woGgxgfH8fc3FzS1j+L4fF4YDQac/8wFQbfJSLTYOH6+nq43W7MzMwkeE4LxfT0tOBZDYfDcLlccDgciEQidLmzxKFzr3zh283Fr2pQKgOaTEBJgGEYWCyWBf0c3W73khfZ+R61QCCAubk5oeBouvT29qY/4BUEwzBZeaN4Ed3e3p5zD850OHLkCGZnZ9Hf34/u7m5MTU0hHA5TkVYG0LlXvnAchyNHjhR7GJQCQD1qlLRwu90pn9dqtQtin8RicdolOShLwy8hq1SqrPafnJwEgEUbvOcC3z3B4XAgEAhgbGyMxqFRKMsI3xs3V9LJLqcsL1SoUZaEb8mzGLzHhmVZeDwezM7OQqPRZF04taWlJduhVjw+nw8WiyWrfQsh0MLhMJxOJxwOh9C2qbm5mYq0MoXOvfJm3bp1Oe0fDofh9XrzNBpKvqBCjbIkHo8n5fMsy8Llcgmp4SzLwuv1Zt0AO5PMxpXG3NxcSRQlDQaDGB0dFYpjxtuZ2q98obYrXziOy/omjmdmZoaugJQgNEaNsiRLNcwmhAglIHhPSi4NsGlHicXhOA4TExNFH8Pw8DD8fn9SMU7tV75Q25UvHMfh2WefzXr/aDQKh8ORxxFR8gUVapSUsCy7ZAD7/As1rWxdODiOg8vlWtLLWUhmZmaybv5MoVAKRy4hB1SklS5UqFFS4vP5MhJehJAFGaOZYjAYctq/0uE4DqOjowntv5aLYDCIqamplN5Sar/yhdqufCGEZB2HynEcXfYsYahQo+QNQghqa2vT7um5GGeddVYeR1WZRKNRjI6OLuuJleO4tFo/UfuVL9R25c1HPvKRrPabnZ2lCUAlDBVqlJSo1eqMRJdGo4FOp8vpPZ9//vmc9l8p+Hw+uFyuZXs/u92eVuo+tV/5Qm1XvqjVatx3330Z78dx3JJeckpxoUKNkhJCCMxmc1pijRCCcDgMsVgMg8GQtVeNnjDSg+M4jI+PL0u8WDAYxOTkZFq2ofYrX6jtyhOGYWAymbLyivl8vrz1CaUUBirUKEuSSUsZfsLX1taiqakpq3g1moyQPnwGZqEusH6/H0NDQ+jt7U37Paj9yhdqu/KEYRioVKqsyvZQb1rpQyrVQJs2beLefPPNYg+jYhgdHU1rmc1qtcJsNiMSiaCvrw/hcBhWqxVTU1M0BqJAEEJgsVhQVVWVl9fjOA4ejwdTU1MIBoP0JE6hlDB8EoHZbM5430AggL6+PjrHS4T169cf4zhuy/zHK9ajFgqF4PP5ij2MiiHV8ichBAzDCI3XOY4TRBoA6HS6jE4Eb7zxRl7GvFLgOA7T09PweDyYmJjI+qTLsizsdjtOnjwpFLPN5rWo/coXarvyRK/XAwAef/zxjPaj3rTyoKI7EwwNDaGlpWVBs3BK5sjlcsjlcvj9fhBCIJFIIJVKIZfLIZPJIJVKIZPJhKXOaDQq9PkUi8VgGCZlG6p4nE5nIT9KRcJxHMbGxhCJRDA7O4vVq1dntP/MzIxw0s71xE3tV75Q25UfGo0GYnHsUj4+Pp72fuFwuKj1GCnpU9FCjWVZDAwMoK2tDTKZrNjDKXuam5vBcRxEItGSsSyrV6+Gy+US+sbJ5XLq4Sww0WgUGo1GWK7MJN7I5/PRpWkKpczgk72yYWZmJs+joRSKil365GFZFv39/TSrJQ+IRCKIxeK0BAAf1Op2u9HX15e2Nw0AtmxZsERPSQOO4+D1elFbW5txULhOp8tb/1Bqv/KF2q68EIvFCStGl19+eVr78e2i6LJneVDxQg2IHZRUrBUOm82Gvr6+BY/zYiEQCCAQCKQtHux2e17Ht5Lgi9JmIoyB2PJJvk7a1H7lC7Vd+ZCsdNLo6Gha+9Il7vJiRQg1ILYe39PTQ+8i8kwoFMLMzEzSdkYGgwHr1q3DunXrcMYZZ0ChUKQl1gYGBgox1BUDy7Jpn7B5RCJR3sIDqP3KF2q78oJPIuA5duzYkvvwyUf0Olg+rBihBsQuYBMTE+jv70+rwjplafg7M6lUmnI7hmHQ3NwMuVxOazUVGH4JNNOuBXq9ntqGQikTdDpdVnUq/X4/FWllxooSakDsIub3+9Hb20tTk/NAVVUV2tvbUVtbu+S2vFiTyWQpBUF7e3s+h7gi4bsWZLLcr9Fo8vLe1H7lC7VdeUAIgclkWvD4tm3bltxXJpPR616ZseKEGg/v/u3p6YHf7y/2cMoWQohQoiMdRCIRWlpaUgau50swrHQ4jsso01Ymkwlp/rlA7Ve+UNuVB1KpNGnZKYvFsuS+IpGIlqwqM1asUANiF7JQKIT+/n5MTEzQ8gTLxFInCtpRIn9keuHVarU5vye1X/lCbVf6MAyzaEmOJ554Iq3XoGEO5cWKFmo8HMfB4XCgu7ubZoYuE0qlsthDqHiyiWHRarV5K9NBoVDyD8dx0Ol0Ob1GPm7IKMsHPSOfguM4RCKRjCo7U7JHoVAsKgiyLeBIOU22hTAlEknO8SvUfuULtV3pYzAYFj13NjY2pvUaybL0KaULFWrz8Hq9QjV9SuGQy+WLCoL169cv82gqD769V6Zkk0U2H2q/8oXarrRZLImAZ8+ePWm9zvj4OE0oKCOoUJsH3zORxqsVllQdDl544YVlHk3lEQ6HMy56C8TiX3I9gVP7lS/UdqWNTCZLmbj1q1/9asnX8Hg8NIGuzKBCLQmRSIT2QSswhBDaf7WAcByX1TFMCKFBxhRKiUEIgcFgQHNzc06vw5ftod608oIKtSTwpTtoYkFhWSyhIB8lIlY6vFDL1quWC9R+5Qu1XWlBCIFer0dnZyfq6uqWtM9ShcdnZ2dpfFoZQmflIvBLoLnewVAWh08omL/MvGvXriKNqPKYmppCTU1NRvswDJOVwOOh9itfqO3yA8MwIIRAp9OBZVlEIhHhh2VZsCy7wHsdfx4khECr1aK6unpJ8RXPddddl/J5r9dLvWllCBVqKfD5fPB6vVCr1cUeSkWyWLD766+/ji1btizzaCoPvuyMxWLJyFMiEoly8iZT+5Uv1Ha5QQiBQqGA2WyGRqNZNIyArzIQjUYTRFw4HAbHcTCZTFmFhvzxj3/EFVdcsejzNDatPKFCLQUcx2F4eBitra1ZZdBRUiOTyZImbczOzhZhNJXL1NRUWi2+eHLN/KT2K1+o7bKDjyEzm81pecAIIZBIJJBIJGBZFk6nE06nU+hBXV1dndU4pqamFn2OL/BOKT9ojNoSsCyL/v5+eidSAPiTFaVwcBwHp9OZUVxKPkp0UCgrBX6Js7a2NqNlSp5AIICJiQkEg0EolUq0tLQIXu3e3l709vbmZZzBYJAmCpUp1KOWBizLYmBgAM3NzbSifp5RKBQLltnSaSxMSR8+OSbdWLVcA8qp/coXarvMEYvFGXms56NQKNDZ2blA5I2MjCAQCKCuri7t1/rYxz626HOBQIDGp5Up1KOWJizLYnBwEHNzc8UeSkWhVCoX3OVNTk4WaTSVSaalUHL1qFH7lS/UdplBCEFjY2NOmdKEkKSeuPr6eqxevRoGgyHt10rlfZubm6NCrUyhQi0DeM+az+cr9lAqhmQeyqGhoSKMpHJhGAZ6vT7t7VMVI04Har/yhdoufQghqKqqgkKhKMjrS6XSjL3bb7/99qLPUSdD+UKFWoZwHIfBwUF4PJ5iD6UiUCqVqK2tpbETBYRlWUxOTqbdbYM2ZadQlkYul5dNb1SO44REBUr5Qc/IWcBng1Kxlh8MBgNaW1uF/zs7O4s4msqDL9PR09OTVn00kUiUk3Cm9itfqO2WhhAChmHQ2NhYcjeY55xzTtLHafH28oYKtSzhxZrb7S72UCoChUIhnPRoKZT8w3EcotFoWssfucaoUfuVL9R2yeGL08rlctTU1GDVqlUlmbGu0WiSPh4IBEpOVFLShwq1HOA4DiMjI7T2UJ7gl9zeeeedIo+kMmFZNq0yM7kKNWq/8oXabiGEEJjNZnR0dKC9vR1Go7FkS9g89dRTSR+fm5tLO/SBUnrQ8hw5wnEcRkdHwXFcRgHblIWIRKKcWhdRliYdjxrDMDQ7jEI5hVwuz7oAbalAEwnKG+pRywN8X1Cn01nsoZQ1/F1quZ8US5lAILDkNrnWUaP2K1+o7Ray2HJiKRIf6xtPOvOeUrpQoZYnOI7D+Pg4HA5HsYdStvACYfXq1UUeSeXCN4VOBcMwqKqqyjqmhdqvfKG2S4RhmLLq9XzuuecueCwSiVAPeZlDhVoe4TgOExMTGBoayqhlDyUGL9RefPHFIo+kcmEYJq00fZPJlHUcDrVf+UJtlwjHcQWrk1YI7rvvvgWP+f1+mkhQ5lChlmc4joPH40F3dzccDge9k8mAXJfcKEvDcVxaCQUMw8BqtdITPGVFE5+NXq74/X6aSFDmUKFWIFiWxcTEBPr7+2mhwTThK+Jn0u6IkhnpCjUA0Ol0kMlkGV+oqP3Kl3K3HcMw0Gg0Qi3AXEQWISSr+LRwOJz2HMs3yTq90ESC8odUqsdn7dq13EMPPVTsYQA4nd6dS9zPSmB2dhZjY2P07q/AyOVytLe3p7Uty7Kw2+2Ynp4Gx3HUQ0wpSfh+mU1NTZBKpeA4DqFQCF6vFx6PBz6fD4SQtI9h/vVaWlrS9vSzLIvp6WnMzMwAAGprazPq01koTpw4QUNxyoT169cf4zhuy/zHqUdtGeA4DjMzM7DZbMUeSkkjFovBcRwOHz5c7KFUNMFgMG3BxTAMLBYLVq1aBYvFktaNBrVf+VKOtiOEwGg0or29XWhuznvmTSYTmpubccYZZ6ClpUXozcl3F1js9RQKBVpbW9MWaW63GydPnsTMzIwgBsfHxwXRtlw8/PDDCf9Ho1Eq0ioAGhS0TPBtfLRaLVQqVbGHU5IolUqoVCra9H4ZCIfDwkUtHUQiEaqqqiASiWCz2VIKPa/Xm48hUopAudmOb+W0VGYmL74UCgUsFotQ/Nnj8cDj8SAUCgkeN41Gg4aGhoxWP6amphbUgOQ4TuixW1VVldXny5T4qgMsy2J4eFj4XJTyhQq1ZYRvO9XZ2Vmyla2LCSEEDQ0NxR5GxUMIQSAQyEio8eh0OuoZphQdXng1NjZmlYTEMAxUKhVUKhWsVqvQXi0SiUCv12ccoiKXy5PWKuM4DtPT04hGo8uanMOyLAYHB+H3+6lIqwDo0ucyE41GMTIyQifPIohEIlx11VU0lq+AsCybdQFMsVi8pEf47LPPzuq1KcWnHGxHCIHFYskofmwpRCIRNBoNDAZDVucelUq16H78asrY2FjBz/tXXXUVWJbFwMAAFWkVBBVqRcDn89EuBino7e1FTU0NFWsFxOv1Zp20YTQaF43vAYCRkZFsh0UpMqVsO0IIRCKREGtWSueHpcp4cByH2dnZgt+kv/vuu+jv70cgEKAirYKgQq0I8IVxadmO5Pztb3+D0WiEVqstqZNxJeH3+3HixAmMj48jFApltO9S8UCjo6O5DI1SRErVdoQQqNVqdHZ2Ji1BUWxkMtmSNz58jc2hoaGCZba/8847GSULUcoDKtSKBB+vRifU4tTV1UEikRR7GBUJx3FgWRYOhwPT09MZ7cswDHQ6XYFGRqEkQghBTU0NGhsbSza2ly/nsRQcx8Hn82FwcDDvYo3jONouqkKhQq2IhEIhGpidhF27dgGICYKmpqaUy2yU3BCLxbBarRnvZzQaF/V2rlmzJtdhUYpEKdmOEAKJRIK2traUx1upkK6njy863d/fvyBTNBdcLhfOOOOMvL0epXSgV8AiwgeZ0nIUicQHCMtkMtTV1ZX8SbocIYSgqakpKy9Fqgr2per1oCxNqdiOEAKdToeOjg7I5fJiDyctMsmi5jgOwWAwb2KNzy6l58nKhAq1IsMvgebzzqrcee655xL+1+l0WWdjUZJDCIHVas264fT4+Piizx0/fjzbYVGKTDFtxxehZRgGdXV1qK+vLxtvOn/Tnek+4XA4Ly2efD4fwuEwnXsVSsXWUeMnfTm0I+JLdjQ1NVExsgg1NTWYm5vLuqwEJX+4XC7Mzs7SWBhKTvDnZ4lEIhS7ViqVWfWXLTZOpzPra00+PuvU1BSdjxVMxQo1uVyO+vp62Gw2hMPhkj+IfT4fXC5XSfSGKzadnZ0LHuOX6Xp6espCfJc6vAfAZDJltF8wGFyyHlRNTU2uw6MUiULajm+SrlAoBFGmUChKZrk1W+I7EGRDrl7DQCAgNIGnc68yqVihBgBarRYajQZerxc2mw2hUKhkBRtfskOn05WNu79QbN26NenjEokEDQ0NNFs2T4RCIYRCoYxia5xO55LffVtbW65DoxSJQtmOYRi0traWpbdsKXLxpgG5C7Xp6WlhTtK5V5lUvCIghECj0aC9vR1NTU0pg6CLDcdxsNvtxR5G0fnNb36z6HMajUZoDr7SBW0+mJ2dzWj7dBJfXnnllWyHQykyhbAdIQQtLS2Qy+UVJ9KA3Jcdc/lOwuEw3G638D+de5XJirnS8QUTW1paSvZkEd8XjrI4VVVVWL16Nerr62E0GgWPEBVumcEfb/En+qW2pzGClEwghKCxsTHrpJVcCQaD6Ovrg8vlKth75HK+5jgup/MWvbFfGay4K5tYLC7pmjzUqxZbsk6HkZERSCQSdHR0YM2aNVk1GV/psCyLkZERDAwMLHnBCQQCac2bYl2UKbmTT9sRQlBbWwuNRpO310wXjuMwNTWF3t5e+P1+zMzMLPsY0iXbaxFfsDrem0fnXmWy4oQaAFgslmIPYVE4jsPMzMyK9qpdffXVS27DsqxwMu7v7wfLsjTJIEs4jkurRIDP50trieecc87Jx7AoRSAftuOTBqqqqoqSHOX3+9HT05MQuxUMBuFwOJKeV+fm5jA+Pl6Uln65eNSSxYvSuVeZrEihJhaLYTabS9qrlmlbn0riwQcfXHIb3nZ8le+enh6Ew+FCD60iIYTAbDYvmX2XrlB79dVX8zU0yjKTi+0IIZDJZLBarVi9evWy3xCzLIuJiQn09/cvSBzjOA42mw0nTpzAyMgI5ubmhO4AAwMDcDgc6O3txdTU1LKOGcjOo8ZfI+bPRzr3KpOKzvpMhdlshsPhAMuyCROF47iiZxTyy59mszmhSv9KIZ2YKbFYjJqaGthsNqFvJSU7eKG2FOkW5uRLBVDKj0xtx3uDDAYDjEZjXpK1OI6D1+tN6v1a7NzMe9ej0eii2/DniNnZWeEcM1/MORwOVFVV5foRMiIboebxeJKe8+jcq0xWngo4hUgkwqpVqxCJRBCNRhN+WJZFJBJBJBKB2+0umgiYnp6mdXFSYDKZoFarMTQ0JNiOkhnpetPC4TAVwxQBQghUKpUwB/O1OhGJRASPV7LXTHUTnckN9mLbZvM5FApF1t0FCCEIh8OQSCQZ7Tc1NUXn4wpixQo1IHY3uFQAejAYxMDAACKRyDKNKgZ/d2exWIrnVfPZgbceADovBrqfBDZeA6gyK5CaDZ/61KfS3lYmk6GjowPRaFRY8qCkTybeNEJIWhfDnTt35mNolCKQju0YhkF9fX3aST/p4na7MTo6KgiQYqxsZCPULBYLRkZGshJOHMehu7sbWq0WVVVVaXskF8u+pnOvMlmRMWqZIJPJ0N7eXpRCjbw7vyj47MAf/xF45tvA01+P/X7rgWV566NHj2a0PSEEYrEYjY2NJRt3WIoQQlBdXb1kMHM0GoXdbk/7QtTX15eP4VGKQDq24zgOKpUqb+/JsixGR0ezFjv5JJvzR64eRY7jMDs7i97e3rRik1MJWDr3KhMq1NJALBajra0NKpVq2YWA0+ksTpD8Ww8APU8DHXuAPT8ELrw15lFbBrq7u7PaTy6XC8VwKUvDMMySWXlerxfd3d0Zxb5MTEzkOjRKkUjHdnK5PG9tnziOQ39/f8n0js3m3MF7pfNx3sl19YTOvcpkRS99ZgLDMGhqasLExERabXTyBd9Hrr6+flneT4AXZfxyp+XG5X3/LLFYLLDb7TRebQkIIbBarSm9aePj48t6rFNKH0JIXpc8Z2dnEQwGS+YYy1ZsGQyGrFc/+JACQgh0Ot2S2xfb60hZfirWoxYOh+F0OjE3N5e3A5sv4FhdXb2sXpvZ2dnlj71SmWIi7a0HYsugy8j555+f0/70RLY0HMctecHN9gK6bt26bIdFKTLp2C7dArZ89vpiKwIsywpZ26VCtjXNxGJxVoV9473aer0+rffnRV0y6NyrTCpWqEUiEUxMTGBwcBDd3d15vXibzWbU19cvm1jjvWrLzlsPLIhNmwmFcPvwMGYKKBxzSdygnrT0IIRgaGgo5UWyoaEhqwsXtUH5Mt92fPFahmGg0WhQV1eXVsA7x3EYHR3FxMTEooVkFytAW0z8fn/W14pMwi4IIVAoFOjo6EBtbS3a29tRXV2d1r6p5mypfZ+U/FCxQg2AUK2eD4bOJzqdDq2trcvWX9Ltdi9/5eyN1yyITbtrbAy39PfjrrGxgr3tiy++mPE+wWAQo6OjmJycpDFqacAXCh5LYUexWJzVDcn777+f6/AoRWK+7bRaLdrb27FmzRo0NTVBr9cveTywLIuhoSG43W4h0Wc+0Wg052bmhSCXYuMKhQKNjY1pXRPUajVaW1uFshyZxP2lEpJ07lUmFS3UeArV7FyhUKC9vT3jGjjZUBSvWorlz7lotOCetXTx+/2YnZ2Fy+WC0+mkS59pwmebpbqJ0Wq10Ol0VPyuQBiGgV6vzyjjPRqNYnBwMKGLRTIBUooiDTjdwi/bBC6NRoPW1taUSQEMw6Curi7rOZVq6ZNSmawIoQYUri2TVCpFe3s7FApFwSeP1+st6OsnZd7y5w11dbittRVKkQi39Pdjv82W97dcu3ZtRtsHAoHilTGpAJa6gamtrc0oG23ZE18oeSPedhzHZdTkOxKJoL+/H36/XxBhHMctEGrhcHhBM/FSguO4nLIn5XI52tvbIZfLF1wT+DjnXLI7U31vdO5VJism67OQbZlEIhFaWlowOjoKj8dTsBMQx3GIRCLLWwA3PvsTgFkqxc2NjZgJhaASibDXas37W2YaEKvVajE+Pl6yJ/5Shu97mwqGYdDY2Ij+/v60vuOGhoZ8DY+yzMTbjmGYtM814XAY/f39CzxRfHxbPBMTEyU/Vz0eD/x+f0ZCNR6xWIzW1laMjIzA6/UKn1epVKaV2ZmKpeJKKZVHxXrUksUJLLZ8mKy/ZyAQQE9PD0ZHR9MKbmcYBg0NDQVt9k4IWbQidcFQmYAdNy7oSMALNgB5XwJ96KGHMtpeJBLltY3NSiOdY0qhUKC+vh4ajUZY6mcYJuk8e+211/I+RsryEG+7dEVKNBpFb29v0uXC+cdHIBCAx+PJbZDLAMdxGBsby0lQ8jc4/DWBEJLTkidPqtAOOvcqk4r1qEmlUjAMs+CgdjqdsFgsCa2jRkdH4fV6YTabYTQaMTs7K9z1hUIhuN1uWK1WGAyGlJOMr/QulUoL4uHhOA7BYBBqtTqvr5sWfDupeW2k9ttsuKW/HwAE4ZYu0WhU6HOXbiBtKBTC9PQ06urqEh5vaGjI2KNJCIFMJsvIQ1mU5ecCEg6HMTAwAL1eD6vVmtIOOp1O8Abwx2IgEIDdbqfNoCuQdLsPhEIhRKNRwXvGsqwwB+cLtXLyfAeDQbjd7pw8YPw1QS6XA8CSLQvToVy+P0r+qFihRghBQ0MDJicnwTAMRCIRRCIRxGJxwskjFAphdnYWQCzAdXp6GmKxOCHGgo9ZsNvtqK+vX/JO02AwIBQKYWZmJq+Tis/UKwp8rBoQ87Cdgl/6zHQJlGVZ9PX1IRwOC8GxYrEYEokECoUCMzMzUKvVwgmOZ3JyErOzs9DpdMJzIpFI8GjabLa041/4k2gm9Y9OnjxZnE4RBYTjOLhcLrjdbtTW1qZ1YSKEQC6XQy6XL4j9LMqNBCUv8LZjGAZKpTKtfWQyGaxWK9RqNWQyGWZmZoRkgfibIK/XW1aCnj/vazSanLP7c13ujGf+OTEeOvcqk4oVanyAuUqlglKphFwuh1QqXeARk0gkMJvNsNvtSZdAeXgPQn9/P3Q6HaxWa0pPTPxr5pOinejmxarxxC+BArE6a/ttNuy1WmFOcfc4Pj4uiDQg9v2Gw2GEw2Fs2rQJNpsNUqkUnZ2dwj7hcBhutxsAMDQ0JDyuVqvR1NQEQghqamoglUpTFtJkGEawdaZ3uCKRqOKEGhD7/qPRKEZHR+F0OlFXV5dWNnMkEllQjLmrq6tQw6QUGN52LMumFATxMAyTEOdosViEhAHeQ8txXFl503j40k4Wi6XYQxGQSCSoqalJ+n3SuVeZ5ByjRggREULeJIQ8fur/MwkhrxFC3iWE/JkQkrT8OSFk8NQ2bxFCXo97vJYQ8jwh5DFCiPrUY98lhMwRQqritku5BsV7n+x2O8bGxtDb24v3339fuNDHvQ6qq6thMpkEEZfqAsV7H3p6elKedEQiUUH6ToZCoeKc7PhYNQA4+PNFuxXwS6GpskGdTmfK3n6vvPIKgIWfdXp6eoGnk+M4eL3ehBpzJpMJDQ0Ni373IpEItbW1sFqtGQu1ZU3kKAL899nd3Z3WjUayeBnefpTyg7edWCzOqZ9nTU0NtFqtUBzX5XKV5Q0Ox3GYmprKqQh3IdDr9UmXpuncq0zykUxwI4D4Knu/AvAvHMetB/AogJtT7Hsex3EbOY7bEvfYPwP44qnXiXffzAD4v9kMkI+ZYFkWIyMjmJycTLgA8X0PTSZT2i5/3sOWinjxl0+KetJI0q0gnr1WK25rbU25FLpUDSX+e2UYRvg7EonA6XQm3T5ZkohWq0VLS0vSJQuWZWEwGLKyT6ULNR6O42Cz2dDX15cy2UAqlQp1o/jvctkLM1PyBm+7dJc9F4MQgsbGRlit1pJsFZUptgKUIcoFQgjq6+sXnN/o3KtMchJqhJB6AJcgJqp4VgF46dTfzwD4WIYvKwLAnvqJv4reC+AqQogxu9HG4AsaDg4OLqgfZbVa0dnZCblcnlZMwlKTgmGYvPcFLUrmZzxJuhXEwy+Fplr2bG5uTrtIML/Uy7dcWey79Hg8C+yhVCrR1ta2QFxFo9GsLxorRagBsbkSCATQ39+fstcs3wpHpVLRzNsKgBCSdiJBOq9lt9vLugg1Xxi61ERQtp1DKOVHrh61nwG4BTFRxXMcwGWn/v44gMUKu3AAniaEHCOE7It7/C4AdwP4RwDxbhsvYmLtRuQIx3GYm5tDT0/PgsknFovT6mXHsmxa8WIGgyHB25ArLMsWV6gtUq5jMZL1BpXJZGhvb4dSqUz6vezatQtA4nfM16qzWCyLll5JdtfOvxdfXZ0QklPA7UoSajx8S6BUF1uRSISmpiZUVVVh9+7dyzc4Sl7ZtWvXom2fsiW+jli5wvcuLTXBOb9zCH/upFQWWQs1QsilAKY4jjs276nrAXyBEHIMgAbAYrfiOziOOwvA353a/lwA4DhuiOO4czmO+zDHcfML7twJ4NrF4t4ygS8e29fXt0BwSaXStCbk3NzcktswDIOOjg7U1NTkTbCVU+bUYjFrvPBK1p7oxIkTwt/x3zEhJGWGptfrTeopFYvFaGtrg9VqRXt7O5qbm7O2w/ys4ZVCKBRKqCvl9Xpx/PjxBSEERqOR9hssY06cOAGWZTE2Npa380w+SlKUAoFAAN3d3fD5fMUeSgI1NTVCPGH8uZNSOeRy27QDwGWEkIsByAFoCSEPcBx3DYA9AEAI6URsaXQBHMeNn/o9RQh5FMA2nF4yTQrHcS5CyG8B/NNSg2ttbcVzzz0HAGhvb4dGo8Gbb74JIJaRuX79erzwwgsghECpVOKzn/0s/vjHPwqtiDZu3Ijx8XEhu5BfEn3nnXcAANXV1TjjjDNwzz33AIgts11zzTV4+OGH4XA4AABXXXUVjh8/jr/97W8AgHPPPRfhcBgvvRT7mFarFW1tbUIAqEKhwDnnnINXX31VOEnu3LkTfX19QkuTdevWYWpqCn/9618BxNotrVu3TigSazQaceWVV+KBBx4QRM51112Hl156Cf2n6p1ddNFF8Hg8ePXVVwEAZ555Jtrb2/GHP/wBAFBVVYUrrrgC9913H0KBOWDOgc/+w+fw9MFjGB7sB+YcuOSyj2La7sCRgwcApRGbt3ahvr4ejz32GIBY26FLL70U6r/+FbeGQlB3dwP79uHxxx/H+Pg4AODyyy/H5OQkDh8+jEgkgra2Nmg0GvT29mJychJmsxkbNmwQvmOpVIprrrkGR44cEUqqbNu2DZOTk4KdVq1ahZGREbz//vsghKC1tRXnnnsu7rvvvrTttGvXLojFYuH46ezsxNatW/Gb3/wGLMtCJBLh7LPPXtJO0WhUEC319fVoaGgQClKq1Wp0dXXhlVdeEby6u3btwokTJ4R4uw0bNggXBwBoampCdXU1jhw5AiCW8r9lyxa8+OKLQtzieeedh3fffRczMzMAgE2bNsHj8aC3txcA0NLSApPJhNdfj+XvGAwGnHXWWXj++eeFMikf/OAH8cYbbwgxgVu2bIHdbsfg4CDEYjHOOeccuN1uvPnmm3j11VfR2NiIPXv24Fe/+hVYloXdbse6devw+uuvL2qnZPNp9erVePHFFwHEPKE7d+7E4cOHhdp1Z599NkZGRjA6OgoAWLNmDUQiEY4fPw4gdsHKZj5Vmp0GBgYApD7vAbGbjl27diXYKRqNQi6XY2hoCIQQ7Ny5EyaTCU899RQAZDWfNm3aBLfbXTF26uvrw+DgICQSCTZv3pz0vMfPBYZh8NnPfnbBeW90dBTHjsV8HNu2bYPFYsETTzwBAAnzCYid96677rqE69PHPvYx9Pb24u233xZs73a7hXMnnU+lMZ8yPe8tBsmHS5oQshvAVziOu5QQUnVKfDEA7gNwgOO4e+dtrwLAcBznOfX3MwBu5Tjur4u8/ncBeDmO+wkhxAzgKIAajuMWzR9fu3Ytl6rCPSFE6GXX0NCw4K6vv78/LY8Zf3BnAsdx8Hg8sNlsCSUq0oUQgjPOOKPwsQk+O/DHfwR6ngZ2/Qt8IhmO2m3Y/fbdiBjbIV79d8Crv4jFrO3IbUXa4/FgZGQEHMfh2Wefxfnnnw8g9lk7OjoE+3AcJ1wAUsEH2+azfhEQ82YODAyU3BLIckEIQUtLC/r7+9HU1LTAwzk+Po7f//73gv0o5cVzzz2XYDuGYdDS0pJ1KyUAmJ2dxdjYWEXNGf4Gv6WlpdhDEThx4gSeeuopOvfKmPXr1x+bl1wJoDAtpD5JCOkGcALAOID9gFB248lT21QDeIUQ8jaAIwCeWEykzYfjuBnEskmXDiRL/TqC0EkmeNI5MTEMs6DcRzoQQqDVaoUl0WwEV6rg7rzx1gMxkdaxBwAH1fPfwwsuF95T1EHs6AVsxxcmFvjsKct3AMnj1jQaDdrb21FVVYWNGzcKj89Pnkg3foaPKcl3X0GRSFT28Ta5wHEchoaGsHbt2qTL0F6vFxs2bCjCyCj5YL7tWJbFwMBATsuglbL0OZ98JVzkAz6Uh869yiQvEaMcxx0AcODU3z8H8PMk24wDuPjU3/0Azszg9b877/+bANyU7XjjXgd+vx+9vb3o7OxM8IwZDAa4XK4F8U7xsCwruLMNBkPG78/H9ACZNSomhCAYDKaV9JATnRcDg68Ae34IKI142hvEv8s2w964Cz/72x3w7LwFvxLXY69EA6Hc5SIdDOJZrO2UVCqF2WxGIBAQ4sD4zEOt9nRYokQiSatECcdxcDgcCAaDaG5uzvjjJ2OlCzUAQrugZI+Hw+HiJrtQciKZ7Xixlq1nTSKRVOScyeacXyj4OUnnXmWy8qKik8CyrLD2zyOXy9HR0ZGyJARwuuL2/DY6mWA0GmG1WtP2rC1b5mf3kzGPWveTOAk57q46D7/1vIQ7Rh6E2NGL7jcewpmPXIO+P9182oMWX75jEe9aslprvJfNHg5jaGgIbW1taG5uRkNDA/R6vbBdJBLJqHAmL/TyxUpMJEgXn88HQogQW0IpPxazXS6etVwK55YqSqUy7RJDy0EoFKJzr4JZebUGksB7Xsxmc8LkE4vFaG1tXbJ/JF+9OhqNCvW8qqqqUFVVlXT7ZJhMJkEwprr75NsfLcvJL65t1A09Pdh48hHs6b8/9ljHHmyaPQmp623A9TZ8egv+o/MzsdZR8R0MknjX5redAhK9bCqOw52Tk1ivVOLLfX3Yv2oVtkulCIfD6O/vz7jgbz49j/GNpymJeL1e+r1UMNl61gghEIlEJVfdP1sYhoHJlF55ouViWUJhKEWDCrVT8NXt6+vrEx7n+0eqVKqUdXT41lJ8PEY2d1sWiwUcxyW0SuK9bCKRCFqtFlqtFkqlcnk8O3FtozapnbjXegEsITc+5B9Am7EDKjYIjMSyed7yehcuZy7SHzQZ8c3d72lqwjf6+2ERizEdiWDvyZN4e9OmrEQakF68YSaIRCIqSJLAZ5M1NTUVeSSUbFnKdtmKtXTDFcqFVGWCikEoFALLsnTuVShUqMUxOzsLi8UieGBYlsWJEycgkUggl8thNBqFuLVkXi+9Xg+j0Yj+/n6hqGp80kI6VFVVCWJNoVBAp9NBo9EUPh5tCW5pbIRSJIJ+9iA2jD4K2N8Cdv0LsOurAAhWb7oOt7nDuF4rge+lO7Dfej6ubl5z2rvms8fi1zZek7RYbryX7RMbN0ISCmG9Uokv9vbifL0eI5OTWZ3oGYYpiFArx76FhSR+Sbq6urrIo6FkSzq2y0asyWSysqr/mApCCKLRaEkVv+ZLXdC5V5nQgJs4OI4T6sEAp5e5gsEgZmdnMTMzk+BJYRgmQYTpdDpIpVKsWrVKmMwnTpzA8ePHM2o/Ul1djbVr16KtrQ1ms7noIg2ICanvtrTgg7u/gN+s3ovpc26CY/XlODAXhn3TdTBJpLi57wGY/vR5qJ7/HmYO/geOP/Ovp+PTlugRGs/zf/oTbm5sxIfMZuyrrcW/T0zgRpsNyLIcSb6/v0qMucmVubk5YS7w9Y4o5Ue6tuPFWrrxn5WU+RmNRkuuRA9/faFzrzKhQm0ePp9PqJ9GCEFTU1OCGOMbvM//mxACr9eLUCiE4eFhnDhxAhMTE7CeWtLr6enJKPOpVPu3PeoHrrFegftW78U7b/weu4/egXcP3hMTYC/+GOh/Ad7W83GhwYDdR++A79j9uKv7bfj8npj3LY1l0Hj2Wq1YrVDgCZ8Pt/v9GYs1lmXzfpEopSDiYjH/IuXxeErqwkUpPCzLYnh4OK1tpVJpRSXihEIhDA4Olkw2a6rqBJTyp3R8tyUC71VrbW0VGoEbDAY4nc6Uk5LjOESjUTgcDng8sc5XXq8X9fX1MBgMGS+BlirxsWREuw8HAKzfsQ+QSHF4oh+zo29ieOON+GzbOkCnxVuOKUz3/TtUQw/FskH5Zc8US6HxSRhmqRR/XLcOVxw/jv/xevFhnQ5rQqGMSplEo9G8XiRKacmjGPDZZTU1NdBqtcJNCk++iwxTlo90bUcIgUwmWxDTmww+freShDxf2ml0dLQkGqOrVCq4XC469yqUlX3FWYRAIACv1ysEjFqtVjAMA6/Xi2AwKHQ1mC8W5sct8HWlJBJJ0SdyvkjI2JTWYPcl3xGeW1fVBNXx++BzHcOM5GycnHVjx1u/xETH1Zja9U1U8d60+I4HwIJ6a1dccUXC/6tUKry8aRP222zYVV2NOZtNEMNLwXEcenp60NDQkLcAYKlUKhwDKxG+uObo6CikUimqq6sT4ge3bFlQWJtSJqRjO4ZhUF1dDaPRmNZ5bWpqquT6Y+YDjuPgdrths9lQU1NT1LHodDq43W469yqUyvFF5xHeqxY65blhGEZo6L1mzRo0NzejqqoKKpVKiFPjPTdGoxEGg0G4kKfThqpSUG2+FrjwVqg2X4v9NhuedsZ6/70b4nB/21U4CTkueecdTB2593THgyRLoXwfwXjMUin2Wq24b3ISXIYxZ/wSTS617uIxGAxJm8mvNDiOQzAYxMjISMLjS/Wto5QuqWxHCIFarUZHRwdMJlNax7/H48HMzEzF3tTwpZ3s9sU7sSwHKpUKHMfRuVehUI/aIoTDYSGuTCQSQSKRQCaTQSaTQSqVQqVSwWAwCBmAPp8PUqkUEokEdXV1qKmpgdvtznvGYUkTV87j+nAIJwxGTNfdBEvzFbjaasUX3z6EM95/GN9suxD38EVxVabTy6CdFwPdTyIUSB4Dxtdaq25owJYsapnlq9YQIQR1dXWQSqUJpVRWKvM/fyWVYVhpLGY7hmFQX1+f0CFkKUKhkNC/t5LhOA42mw1KpbJo53uGYaBWq+ncq1CoUFuE+JNLNBpFNBoVMpzi2xvxjb/nB6wzDJNQUX+lYfrb/2LHW78ELrwVN3TGuoX9wvECzP33Y6baBFz0HcyEQrhrYADnHL8Pe479LNauqudpQHtz0tfk4+Mu1OvhHB3NaDy8VzRfEEJQVVUFiUSC8fHxir8YUVY2er0+I5HGsiwGBweLGpfG91TmwyQKORa+pFLjvELey4ler1/xXv5KhQq1LIif8HyczorynKVDkmK3ZhKrs9XncQChEPbbbPje0BBMss14eOtN2L3t74Hmnfjshr9PmmzAx8dFo1HYMzjpEkJQX19fkLIaBoMBEokEw8PDFRUsnQvnnXdesYdAyZLFbJdJ5jTHcRgZGSl6rUGlUomGhgZwHAev14vR0dGCZkd6PB5EIpGiJRup1Wo69yoUGqOWIxzHYXBwsOgnpZKDXwaNz+iUqAAAf/EEcNfYGPZarbhTz+HVobux4ayPA5YOYMeN+NPLR3HgwF2L1l0TiUQZ3TnK5fKCVhJXq9VobW3NWQjyn6ncyxi8++67xR4CJUuS2Y5hmIzEx8zMDLxeb1G9zHx4Av+3QqFIeSPFzz2xWAy1Wp21Z8rpdGa1Xz4QiUR47733ivb+lMJR3leEEiEajRbdzV8WbNuHpzd/CXfVXQIg5iH74js/Q+fYKzA+8zWhMftb/f24UrIJB7betGjdtUxqmS1HHzy5XI729nYhIzQbOI6DXC5HXV0dVCqVkKRSbszMzBR7CJQsWcx26Qo1n8+3ZL/iQkMIgdFoTPACLiWgZDIZzjjjDKxevRoWiyWr9+U4ruiJE3a7vSzPGZTUUKGWJ0KhEN577z2cOHEC/f39GB8fp0UI56My4ayLvoGvrt6IT1ZV4fbhYcxZ1saeq94gJAuII0EcHr4HZ665EHjrAdhdE7h9eBgz8YIrgzt8lmWXRaxJJBK0tbVBoVBkfbIMBoNQKBRoaWnB6tWrUVNTA7lcXraijVIZpCvURkdHix6vyZcP4eEzMxcbFyEEBoNB8GRPTk5m/Rn4ZdZiQbumVCY0Ri1P8BM7EokgEonA7/dDKpXCbDYXeWSlBR9ndvvwMG7p74ei7SrcoK0GNl6DvZLY8uTHT/4nmkdfBh7/AuDox7suF25R7YIi4MQN0weAjdegL+BFQ5r3GYQQISs3EzweD8bHx1FfXw+VSpXWPiKRCC0tLfD5fLDZbAgGgxmf9J1OJ6qrqyESiWA0GmE0GhEOh+FyueB0OhEOh4t+MUzFpk2bij0ESpYksx3HcWl7sJejD26qGoYMw6CmpiYhfMDv9y9508wXivX7/Tn1JGVZFtPT00Vr2n7ppZdibm4uo5aFlNKHetQKRCm4wUuZvVYrbmttxdXNazCz9fO43R4riHlzYyNcqs7YRm3nAxfeijPXXIje3p9gb99DQtzaxpnXQaLpnYxYlk27QC6Py+XC8PAwwuEwBgcHM9qfrzfV3t6O5ubmjDxsi939SyQSWCwWdHZ2or29HRaLBWKxeFm8bHzP23R/vF5v2cfZrVSSHed8Lcl0KHTmISEESqUStbW1i76PXC5P+N/hcKQMS1EoFILHMBdvGo/f718WD34ypqenafZnBUI9agWEZVn4fD6o1epiD6XkiO9wwHvXgJiAe9xpQu2ub+J/6/bg6uY1MP/+UzCMvgxIRbE2VBuvgfHxWzCraENUwgFiOZY6tfp8vozaeM3OzgonbI7jMDw8LJRiyQSVSoW2tjbMzc3BZrPB7/cveSGIRqMpjxuZTIbq6mpUVVUhEAjA6XTC5XIByG8JAkIIJBIJjEZj2h5FAHjppZewY8eOklgGo2RGb28vmpqaEh4jhIBl2bSW1bRaLSYnJwsyNr5tFd9/eXp6Oqn3LhgMJog1tVqdMJ/jYRgGBoMBQKwjTT46KPAts+Jb4S0XR44cwbXXXoupqallf29K4VgxQq0YLX8qpb9noYnvH7rfZsNIKIK9povw5LgDM5IxtHV+Bp+090O8+5tA41bMhEL445rP4Lq/7EVUpIRn/XWYbf8IAoGAcFHh4b9/vp1XusufDQ0N8Pl8mJ2dhdvtBsuyQvHObOrjKZVKtLa2wu/3w2azIRAIQCQSCT9isVj4EYlEaZV74bPZFAoFampq4PP54HQ64Xa7F3wP6cJ7TnQ6HYxGY1ZlZxiGgU6nw9TUFF2CqRBsNpuQRZkKqVQKsVhckOVPiUSClpYW4RiVSCQL3odl2QXHnE6nw8zMjFAHMx6O44T6cMVOgsgXMpmsYDagFIcVIdSUSiUYhhG8KssBn3mUiSdipRLvXdtrteK/NmzATW1t2K3XwxeN4p33n8GnHb3wDb6M/QEpOk8+gtuYTqxv+zC63D2QERfMVj1YhQGzs7NCAVpCCMxmMwwGA7xeb0aBtgzDQKPRQKPRCA2Y3W43fD5fToWM+USBfMMvt6rVarAsC6/XC5/Ph1AohFAohEgkgmg0mpCUwAs5/n+5XA6z2QyNRpPT0uXmzZsBAGazGRMTEzQbuoxIdmzyHiK9Xp/W+YwXRvlELBYnlMDxer2LxpLFP87XdFvshkGpVEIkEiEUCmUcHpGKYt2g83MvmYillC8rQqiJxWI0NDRgeHh42er78LFGkUgEVqs1o3ISKxmzVIrrN2xAtUqFm1UqzIRCeHD7/4GvuRn/btkN38F/xw1DD+Hp2u1oHj8U6xf66i/gkxvxH81X4rrqajCn2ktVVVUJqfZGozHrMfFxMUqlMl8fs6AwDAOtVrugkjzfTD0cDiMcDgsiTiwWw2AwZJxssRj19fUAYhfsiYmJvLwmZXkwmUxJH+cFT2dn55Ii3mg0wufzCR6sXM+3DMOgtbVViCPjOC5lN5D4Nko2mw0ej2fRZU/+vJBPbxof01kM+LlHY0QrixVhTT7ourGxEVqtdtnudjiOw+zsLLq7uzE7O7ss71kJPPbYY8LfZqkUN3SeCdW5N2FObgBBzHaTxtWY2vVN/LrzMwg178LxqSH8+MRbuG9yElVVVaipqTldD8lnBw7+PPZ7BcPHnCmVSuh0OlgsFtTV1aG6ujpvIg04bT/+QkiX/8uH119/fdHnotFoWvFnUqkUbW1t6OjogNlszqlkBMMwaGlpSTg+Z2dnF+1pSQgR4kgDgUDKshwcx0Gj0SASieT9/FysYz5+7lEqhxVhTf5EwbcS0ul0yzqR+DtAugSUGzfU1cG845/wwpmfw188AXyGbYHhtX+DdPBFdB2/Dw/7XoEvGgWn0YBVq0/XXjtydyxb9Mjdxf4IK47FPDSU8oNfJZibm0tre6lUiurq6qwLyBJC0NTUlBAnybIsbDZbynMpL9SWqv3GL/FPT09nNb5UFPvmhAq1yqKircnH48hksoTH6urqYDAYlnUysSwrZOZRUlNbW5v0cd67ts1kxXeHHsQNf/sPXOo4hhl1AwCAA/C9oSF88r33cNfYGG7p78e1J07AFz11Ug/5U3vWpnuA/7kCePqbFeN94zgOc3Nzy1ouIN5+EomExmmWEXwG5GLwS6CZ3HQu5v1KBX9TPf/YcTgcKWuiyWQyIcxELBYvKlgkEgnq6uoQjUZTet2yoZhLn/zco4VvK4uKjVETiUSorq6GWq1OEGpAbCLV1NSAEJL3SboYHMdhampq2QViOXLppZemfF61+Vo8PTuLm5hOjFi34N9UZ+IuthtvtV8O08goNr7zCJRbr8MFej2edDhwu/Ui7DrTjYbBw2ifOBx7kR03Lnzhp78O9L8Q+1FZkm+TDfEN5oEFzeYLAcdx8Hg8mJycRCgUgkQiQUdHR9Jjz+FwQCqVCm2rcmW+/SwWC+bm5qhHuQw466yzltwmEolgamoK1lPZ2kuRaVA7f36eXwqHZdmUsWR8h4F4ZDLZAg8gwzBobm6GSCQqaCmRYsDPPepRqywq1pp8VwC+/c58+JOB2WxetknFsiyNVUuDX/3qV6k3ONWK6opVXbi94SNwSDSQRvz4wuDDODxwF27vvx9fev3/4cLoDL4y/Aje9HrxpCeA9onDOFK9Hfa1n0j+unt+CLSeB2z9ByDky96rNj8mjl96/cP1icuwBYqbCwaDOHnypJDtxnEcwuHwoks84+PjGBwcxIkTJ4RuCrkw3358Zh2l9Hn++eeX3IbjONjt9qTlLpKRqUdNKpUumvyzVMP0+eJuvkeOj1WWyWRgWRZ2u70gN+rFEmr83KPzrbKoWI9aulSfyhLkCwRmW38qHViWxeTk5LLHyJUb6Xz/ZqkUf5ubw0AwiNvsL2L3ydgJqg1AVGGCtO9ZfNgfwJrxV/CoVouerdfhHoUCX9ftgPb9QTTKbbi7sxOr4k/klg7gM3+MCahnvg1IVdl51d56ILY/cGr/U7buPxD7e9dXY78TtskfLMsuuDjyHl2TybTgJG40GoUlpZmZGdjtdpxxxhlZH6Pz7ceXSbHZbBVRp6qSSdc+fBHoxby08eTrfMowDBobG+H3+zE+Po5AICCMl2EYqFSqBXFparU6YdXEarUKhaTzsZqyWH3OYp3f40vuFKN2KKUwrHihBsSWZsxmM8LhMILBIAKBgPDDx/bk64CPRqPweDwLSidQTpOu2/6LtbU46nbjrJ2fA6xmHLbbMDv6Jva43kao+Vy8KarBQ01Xg9Sdi139f0Zj19/D/sr92B/ejK32w7jafTEurGsHAJA5O9pOPoIP7v4C2vklSv73fOKXMvnly/jH5u+/bR8QngNOPB5bVm07L/acVLn4e+SAQqFAVVUVpqenhXpyIpEINTU1Qi9Gu90OrVYLpVIJk8kEp9OZ0Ikhl2LNyexnMBhgs9ly+lyUwpOJzXkv7VIV+GtqajA4OJi2YFvqXKtQKNDW1gav1yuU6bBarUnPqSqVCmvWrFnwON+TM9fzOj9P5r9OsZYe+felS5+VBRVqpyCEQCqVQiqVLmio63A4MDExkRexxi9/UqG2OJ/97GcXfW4mFMJ+mw17rVb8dHQU05EIfmSfw/nnfQ16nw8/e+8YNnoPo2fWjr9/65e4ufVaNPc/g93v34O+iaP42ujLWG98C5c6juFx13FcF/wS7FItvjL8CPb134//JgTtV/4o5uXy2eF76Q7st54fa2XFlwhY4DFL8li8l0xlAlRmwNEPKM2AZW2i0ONFXufFQPeTp3/Pfz6DuDY+Lszn86GqqgomkwmEEIyMjMDtdoPjOKEunEwmg0KhgN/vFzzKuXgEktmPb9XjcDiyfl1K4fngBz+Y9rYcx2F6eho6nW5BHHA8SqUSLS0tGBgYyOtqhVqtRmdnZ1b7ulyunMdCCIFer0/anqpYHjV+7jEMQz1qFQQVamlgNBohkUgyznZKBl9BnrI4jz/++KIJBfttNqEv6Ca1Gs+6XNh06vv83dQUHvSx2GQ9H3vDf8YPm67GfusFOFscxoc870N07s144v2z8GvdJhjf+yUunTqM33peAkAgFc3hdctmnLftk6ff7K0HoHr+e5hpOok3Tlqx54P/HBNK8zxmM6EQHrTsxt4PfgeqxTxkG68Bjt0POPqA/70GiJyqnr7jxtMib/AVoOfp07/nP8//Dywp3vhYHI7jhKXOaDSK2dlZYVkkPn6nublZ8B7Hdy/IhsXsN99zRyk93njjjbQSCng4joPNZlvQH3Q+CoUCra2t6O/vL3pSCR8GkOtxKJVKodVqk8YdF0uo8XOPetQqCyrU0kSj0aC1tRUDAwMp08PTfS3K4oyPjy/6XHxfUDJnx8UnX8R6876EbTb2PgbLsZ/B2Xot7FItNo78EW2jL6PvJeDaxn34autGnLP1d5h76afY8t6fYfQMn975xO9h11bh3YP3YMNZH8c7Z47h3IFX8MGhB+FTSPAfnZ/BXqsV5jiP2X6bDbeMO+FvvRI3p/J4KY0xoRbxA8bW0wkLvLjrvBho3nn69/wl1HgROF+8JRFu80/WIpEIq1evRjgcThBw/LbxjaxzYTH78Z67dOtwUZYfp9OZ8T7pln6Ry+Voa2tDX19fSrGWyjuXD2ZnZ3M+hzMMA6vVmjRon+O4ogklfu5RoVZZUKGWAXK5HO3t7RgYGBAudpnCNy2mpE/8ciffF9TumoDr4X/A7tGXAb0e2HEjbqirg0okwmbtKvh0Ovw1uhoA8FrrpQAzhraep/FwzVass34ICHsQOCXSQowMUjaW6Rh552GIj96H3WEPBkZfxdbGzVC5/wYAODjrwo9PvIWqg8/iwwoC99QJsB+6DZwviqc8L6BV0Yrbh4dj4wx7EoXTWw8Ao0djH0gkAyRq4MUfx/4/7+unPWWWeb+B2P7zEw7mi7dkXrck8I3fi4XFYsmLZ5pSOmQqelKdNwkhqK6uznVIKd87H940iUQCtVotZFXzEEKg1WqL3jKQCrXKgiqGDJFIJGhra8PQ0BD8fn/GE35++jhlIZdffnnC//HLnXzz9ncP3oPdoy9jsHY7mkM+2F0T2O8O43qtBKa//S+w+Vo8OufD8wf+HeNrroT9kjth+tv/YnfnxcCBW4E4T5qUDSKirkEo5IPSOwHeQi0ThwBvbBuHSIXnVB34zXs/wUWutwEARgBHnrgF06pV2NN/PwYnDsEracK92/8RG3sfw55jP4PPH2v0fNw1jU0N50A68ioQDQKT78TeZHYc+J/LgeoNwM4vpV9bbb54ixduWcS05ZP59otHrVYLvVgppceWLVsy3icTW6bq0QnE4tny5dlNhtfrzblZOcMwqK6uFuKa5XK5kIEqlUpRV1dXtKVPfu7RqgKVBRVqWSASidDS0oKxsbGkgaSLQQihy55pMDo6mnBXHb/cyYuQxvVX4L/9flyuAPDij3Fi1o1b9B/CVt+L2H30DhxwubBWAuz723/iTscQfOw0TGIGeP/Ppz1bcYi9ExADCBIxZFxcaQtPbCnBGPXh+yd+CalrAADgt6yFP+hB1flfRxP0CJExNPc9i+/hEP5HLsfBQABv1X8En+h/Gc3jh9AF4ODGz2MHQ4ChgzGvWjQI9D4LeCdipTukSuC8r51+7/mCK5UAixdufHkRIO+lP9Jhvv3i4Ut1TE5O0li1EsRut2d8M8mybFpZwnNzcymXvQkhaRfRzZZ8HHdisVg4jzMMg7a2Nvh8Ptjtdlit1qJ6s/i5xzAMnV8VBPWPZgnfispisaR995LPOKBK5tixY8Lf85c9+SW+iTd+hxNzc+jzx4Lyt7rewy9qDdhw1sfRV/8B7EM7XrPFRNXHnW+gcfJ1YOxIUpEGAAd0a/G8dq0g0oYtG/CCdi0AoF9qwXD1Zkg7zhe2V4S9MLqH0Tz2Kq5uXoN7ur4N386bcXDj59EXCOB7Qw/hCm4azeOH4GrYibvaroFqw8eB5g/E4tOip4rKhn2nBzH4MvDCD08XweWXM996IPH/pYrlbrwGuPDW0961xbad/1yemtfH2y8ZS7UpohSPgYGBrPZbShTw/Y5TbadQKBL6euYbn8+XczFnfml2/jlfpVKhsbExoXl8MeDnHl36rCxWnEeNP1HkwzVMCEFVVRWkUinGxsaWjL0opku8XOGXPRUBJ24YewII+eHbeTN8sy7c3n8/fI0fAFp3Q9p/AH8X+QZkzdvRNvoyXvOMQi6PlUDxM1LMEQkkXAQScAiBgRQsIlINxCEPTspr8G9n/z98bOBRwP03PK0/E29t/zZ2jDyLaeVFeLL5ClzdvAYIewClCRg5EquHBgDgTicTnEo0eHPwffjaVqNzzYeB7ifxeekmPOhj8as3fo+Nx3+JA2s+jbZgEA2+MSDoBvRNgK4+5mkbOgiE/bFyHp0Xx95ifjxaaC61xyyZdy3kixXwjS/9MT+uLYvs0mwQiUTQ6XS0922FIJFIlhQGHo8npUgqdGwagJwyjvnPZzKZyqK0EvWoVRYrTqgND8dijhobG/MmmvR6PSQSCYaGhpLGaxBCYDQay2KClwLbtm0T/haWPQcfFoLvj269CX+vORf3Gd/ApcMvA63nYbA2JtB+o27HVcZ2mBy9QDC2hNPoH4OYO20XKWJ/i8+8GiHHAF4+85+xQ6JBXyCAO9uuwa3VF+G34y9jx1u/BDr24IYdNwBSKSA1xQL/ffaYVwsE2LYPeyUaYax843h0nhl7M8uN+K7PB3dfH3at/SccUChwpWQTYNiD507+BGfa38bvzWej5fyvwvznz6N5/BAi7/4BYs8YfO5JqP7uh6e/GF6A+ezJi+UmE1XzxV186Y/FskpTZZdmaL/FMJvNGYUNUJaH9vb2jLbnz22p4DhuyTqUMplsQbunfOM/5X3PBIZhIBKJYLFYoNfrS95Txc892pmgslhxQi0ajWJubg6Dg4Nobm7Om1hTqVRoa2vD2NgYgsEgotGo8NoymazgsReVhMViEf42hz24eeRRYM2HgWgAAMH6TdfhBmcA7zX8BLuP/gDq/uegOucm3GPYiK/rdmCu5Tz8w4EvAf5YcVVepA0bz4C54zwoRQwgUQHb9kGqMuGzAHwv3QHV0EP4btPV+JnjOezQqYDGHTFRc+SexNgx1SnBxo8Rp5MckmGSSLBbr4deZ4X+wq/h+uFhvOn1oo47H3jtbfQHghg88O/4r7rP4HEiRufYKwCA0N8eg0quhn3TXvzCGYAy4MQXpg9Atfna5KIpvh7bFf+Z6AFbd2VM3MWX/pifkJBOdmkaxNtvMeRyeUIQNqU0yCaGNp2YtlQB/AzDoKGhIeP3zQSO49IuIwLEhI5CoYDFYlmyv2gpwc89vk6i1+st8ogo+WDFCTWDwQCJRCLcbeRzAspkMrS2tgKA0Ag7FApBoVCUzUQvBZ544gns23eqNtqRe4AXfxTzCJ3yZpneegBfXPsJ3Os24z+2fhNzUQt2+Xx4qvFi2P1Are15QaTxDFVvxoWN/wf3sL3Yfe4NsQd57xMA+GYwUL0Zn/F3o3XoDQCAQ9MIIxBr/3Tw54mlMBZrH5Xksf123+nl2+kDuG3jNYCqHZhWwTv5NtYAuOzkr3DOxs/jjzu/Dxy8E590HkGDdxR48cfwnXgOnLwNcyBQDT0YE6xSFexrP4F73eHT8XsbrzntMXvrgcWXM5XXpL+cmUy8ZWK/FDQ2NsLr9SIUCiEYDCIUCiEcDgs3OfwcpUJu+XjzzTdx/vnnL73hKfhuLqlI5d0hhKC5ubngtdPSzfQkhECn08FsNpdlPHH83NPpdPD5fHT+VAArUqgtRzBzfEsqSvb4Ah6o4n7zwuOYw4Efyzbjfv/rsCqAzW/fDUn/AXy8aiMC0SDmiARK7tTJuXU3NBf+K57+85fRPH4IUJ6yyYs/gs/vwdFgFLuP/jtaTr1nVG7AhKYR9dNvo6/+A2iTKE6LHWDp9lHzHtu79fOx34MPA89/7/R23U9C3f8cLmvdHXtIp8WqtnXYr7oVv/PNYONTX8Ie19tonHwd38PreHr9Pvg++B2ookHgmW/jXZcLP5ZsgvHIq7jighth0tfEPGnxAjTLYrnLgUQiSToX429y+N98391IJIJoNCosQVEhVzzSWfbkYRhmQb01Qgjq6+uFVmaFJJ1jhI+TM5vNBR/PckArDFQOK06oUUqfxtoq4IV/BcDhxKwdm4HY74M/BxrOATr2wKbvwMGDN2NVwIaQug4AsNNzEvCcTHitiKYe9228CVc/882YSAMAnD5pPzozjS8Zz8fv13waSttbMM1NoT0wiSrrBhxovgnrd+wDJNJYIH682En29yKP8UV6YboWEImE5+xrP4F3XS5sOOvjMPY/k7DtTMiKBy/+BXYM/xnHXdN40uOH6oxP4m2VOVYrTqrE+rWfwM/++iNcc+I+HIYfpprW2GvvuBEnfT7c9M47uKOtDauSLWeG5k53RuCFG59wkKNga0yxDJwOS93ksCyLcDgsiLhQKASn0ymUiaBkT6YiJd1SHiKRSPCUisViSKVS6PX6ZasrKZPJoNFo4Ha7kz5PCIHBYCh7kRY/98RiMWQyGQKBQBFHRMkHVKhRSo49ukHguR8BAM40xJaS1wcmgGceBFp3A/0HcMnE32AK2AAAwyIl2gGwIhmY6OnMsqjcgEe2fwPWA9+D2nEMT+vPhKr5HFSvuwbfGhzE3vUO9Ljd+JCcg2jyXXQ538XrujXwWjuhvuSn2G3pAHCqREjDR7BXooktMc4XPsmWB9N47F53GLeoduG2sBo3n3o8vhwJn5TQFgpBbbPBF43ie/39UNQasDcaxX9PTGDjqQrom7wDwDP3xV54x424qa8PT55qgP7Ehg0LxyFVxsRZvADlEw5808D0SWDPD4FT30Em7NmzJ+N9MoFhGMhksoTlMovFgrGxMXg8HirWcmD9+vVpbyuXy9PuctHa2gpCSNKWS8uF1WpNenzw8Vw1NTVFGtnizMzMCGM2m81LJqTNn3s6nW5B9wRK+VHaKSyUlYfPjl8dcQNb/gEwtkLs7Adaz4O09kxg11cBa0x0nCBxje2lp4pPRoPwklNeGLkOooATV5z4H1zqOAZf4wegaj4Hq3ffiG8NDqL+/Yfx3twcvjf0ED731h041/EWAGDL7PuYjCLWl/MUfImQ/TZbXj/qXqsVt7W2Cpmti70X72W7oa4utr3tOaie/x6mj96Hv9eciwNbb4L0kp+erp0G4I62NlxsNOKOtrYF7zsTCuEuy274PvidxKSCbftir2E7Hotze+iTWdVU+9WvfpXFt5EbIpEIjY2NqKurK/nMvFLmhRdeWHojZLbsCcS8O8UUaUAsns5oNC6IF5ZKpXmtApAvwuEwJicn4fP5MDc3B1sa55/5c49WGqgMqEctTcbGxiCTyWAwGIp+wqk44mOkjtwNeCYAxzjg6Ac69sBn7IDq1Tvh23kzVDu+hCmJFvdLV6PT9wa65/zYK1mP/XXvYg38GB86ilaFAkqvDQjMQjo7ArSeB5V1HXa8+gvA14fbjGegof9+fKfpKnyn6Srsdh0HALxu3IAoI0bX6MvwHbsfqnNvAnC6RMhlJtPpXp55iD0UlkTjiO/CEO9dAyD8rTJdi6loFP3KrbjeVI91jbHepb5oFP8+PIQ5uRs31NXFPGk+O3DwV4IgmwmFcO2JE3jSkaSJPC/YOi+OibSZnpg98rAculzo9XqoVCoMDw/TjNICU44ioKqqCgzDCMVvGYZBS0tLSYr76enphOM3HA4jEAhklOQgk8kgEokQiUSW3phSslChliZOpxNArAWJSqWC2WyGWq1eYi/KosSJM9+x+6F6/nvwRaNQhf2QIoJRjxOGnTdD1XkRgr+/HioAbzonQZ65HQj7UOPtwUM7voBPVlXhnoP3YE3XZ4DfXoV1nmHYAtVQ+icBuR5wjwLuURzUrsbW5nMh7XkaY6v0eNu4GX1tl+CTzmM4b+gheFvPx0/XfAnPOF3Yq30Wq/Sb8dlTmZ5mlQk3Nzbi9uHhBT1H8028eIt/PwAJ731/21V4pL8ft0mlMEul8B2KfYfTrYPYb70Au9/7H+zefQOmjtyLqhd/gKlQCFXn3Yz9NhuedDhwsdGY4MlLwNIB7H0qZp/44rob08sWLXYCjUQiQWtrK2ZmZvLSgHslke5SpkqlKssbVpFIlFBYN9+Z//kiEokI1xwejuPgdDpTLtEmm3s6nQ52e27dRijFhQq1NKmtrYXNZgPLsvB6vfD5fGhvby94WnnFciqA/YDLhSOtH8Z062BMHL11B67DAWAaOFh3Dra++CMYPcPwygwgQKwILYAdAEJkAgDB7sEXEez7E2SnmqzP8UWHQ36gZhMOm87E5cpz8PNAAJ/CS7C4h7DdcQxtJ+7Bwe23YEqrwY3qLjzoY3FBVSNUHV/GZYMPAy/+ICYe53nWFhU4eSbZ+81/TPC2Wc/HUOsg+ld9FL+degG7j/0MPo0Gl4vPxM7WazGq7sLv5u2XzCuY0LJrx43AdA8w/kbMy5Zm8dvrrrsu14+eM4QQWCwWaDQaDA8PIxwOU8GWBrt27VpyG4ZhKqYNWCmKNACLCiuXywWr1brouJPNvXTFN6V0KT1/b4liMBgS3OMcx8HhcKTYg5KSzovRV/8BfDVsxcbex7Bq48fwmbfvBPoP4FHRhwEAG9VqPLT6OkyKtVAHndhoqMb/rLoWt9V/BL01XZAOvgTp4IuYEmsgc/TiBe1aHDjzc3jugz9FUKQA2CAw8SbWVTWhy9qMG40fxIGtN4H83e04Ur0da8Zfwcm3/oC9povwoI9Fu1yOTWo1bqirw//W7cF3m67GW44pIU7LLJVir9WK/TYbZjIonpktvHfNfMprxv89/zkAuLp5Dap2fwV3bzoHez74z8CFt2K/9XwcikrxSsul+Ln3MOCzC5/hrrExfHdgQPgcM6EQbh8exl1jY4kxct1PxuLV+LZTcXFwi/UG/eMf/1jw7yZd5HI52tvbk8YmURby+uuvL7kNx3G09EOBWaz+Gcdx8Pl8SfaIkWzuZVLol1KaUKmdJoQQ1NTUYGRkROij5nQ6U97dUFJw/GG0jb6MPzgHUO8bBZxvAf0HAGMrph0awNwBVedFuOrFH0EacSPUdgGmGz+A+pM/wL/XXYmN0V60t3QhNP42qgZfBABIW8+F+cJv4fa+Pvxq/ffwl767YFx9EVSbr8X9Eg326/VYZ/0Q9tts+HHbF/Db+u1oWvVRfLauDSGWxbMuF24fHcXf5uZwR1s7hsxW7Dj2M3jd3bhv+3dwdfMa3DU2hu8NDcEXjeK7LS0pP+JykhDvJo3Fml0dCsEvt+GfBh+G6sUfAFIpZrZ+Hl98+xDq338Y+60XQCUS4ebGRiGJ4TtNTYkJDvGlR+Znsi7iYZuamlqGT5w+DMOgpqYGWq0Ww8PDtIxHCmZnZ5fcRqPRlGRMVyVhtVoxMDCw4DhlWRYOh2PRsJtkcy/XRvSU4kOFWgbodDqo1WoEAgEEg8G0q11T5uGzAyOxmmb1vtFYUVnrhphQW30p8EY4Fsh+4AeQ9h8AWndj+EP/hoEHr8eF9qP4k/MEqiNuvHDm57CtfhvC1etwNBDBkVWfwNzUVCwGq/VssBfvjfXo9NlhPvpL3LzxGswAmA6FsKmqEdrmc+GfV1dJQQiedDiwVqnEiPV8hIwv49L+5zCEetzG/DPeLKOWLMnqt+232VD//sO4vf9+XGgw4CzrhwAsXBLlPWzCEmgysmgvVUxUKhU6OztpGY8cqKRlz1JGqVTCbDZjZmZmwXHq8XgQjUbTjhGk16nyhwq1DBGJRFCpVAVvIFzRvPUA0H8AEX0L3rZ2YbW5Aei8CJg+AWz6DD5WMwa88BQQiImog9o1uKO/H9sUdWhRjKHdP47HjZvxumsW5719Nw5svQnnGfYAk258p8mQ4BG6fXgY1/Y9JATU7zVdJNQXGz15Eif8ftw7MYETfj9UDAPfqfi2N71ePOtjgbO/i/DYM9iv3Ip1Hg9enJ3FxUYjbqirK853lw1xnrC9Eg0e3P5/4Kutwh4RA4Q9QBhQHLsfCuv5AE5nmN7S348DLhfuX71aEG9C/JpUGnvdJAkGH7v4/NMtt0osU5Qv4+FyuTA+Pg6Wj2ekADjd1DsVNIlqIYFAAGNjYwse57svZJNgU1VVBa/Xu6CZPMdxCAQCSa9BH/vYxxY8RjM+yx8q1CjLT+fFwJu/hnimB5stHcArD6J74DV0jr0CX8PZ6H33JEyOWIZjd91O7JWsxyNv34Z14wfxxLrP4gGPF51iDmsjfhy1bIZ+zaW4mdXhTa8XHzIY8LLbjd65Oew9JcR6pKtxmXEz/iRdjScdDpyr1WI8FMIJvx/tcjmmZyfxI/uLuN20C1UaCxpkMny/uRl73G7stVpxr1qNvUfvA2P9FFSnapPlozxHMTBLpbFCutMHThe8BaB6/nsYah3EXZIv47stLdhrteKAy4UnHQ7st9kSlkeBuKzXJMufvS//AaaT/y/hsXRZriw8WsYjOZOTkynjz7RaLQ31SMLs7OwCQQXEPGPZBvMTQtDY2Iienh7hf71eD4PBsGiJjt7eXphMp2+OotEoPbYrACrUKMtP95Oxpc2OPcCeH+KAfh32oR2Xy9rQZD0f0uMSVNVsx+PECLNcg98O/jfWTcc6C9jDYZyj1WDPu/8lvNwvX/9fvNn5STzrcgGDg3jW5cJqhQIn/H5sF4VwR/fdUDuOYeeJ/4Rnw1fRoNXi9tFRXGw0okUmg6L7t/hq//3YtFmNVzuuw/eGhvD94WHcv3o1AGBj72PY038/9os5sBGCxyTX4ZY1ZxXpy8sT85Ytn3Y4sF+2GbcEnMDBP8G88Rrcv3p1Qh23y0wmHHC5cFnchSDZ8ufbs2p0xScdpMnExISQ7bZmzZqCl3+gZTwWMjQ0hPb29qTP8W2WKAvxeDwJ/xNCoFar0dDQkFM8n0QiQUtLC6LRKFQq1ZIi+e2330ZXV5fw/+zsLBiGoZ7jMocKNcryE9fr8ndTU/iEUonPWtdgrqkT6/72G5yYU0H72fugfPbn+OTxWDmOGU0DqkXAnpP346BpE17QrcV5s39Dt7wGD+g34VWXC6aQGzf3PYHvikSQrdqH70x78R9TT0I99DIAQD/yCjqZOqi2/yNecf0VGyNq3GveAXs0iO80XQXLqo/ihro6HPV48KTDgduGh/HozAycss344dp/xLjXhduHHsTTBgNQ7kJtXmLAWRd9A1+12fBP3f8DvHI7EJqD+byvJdSL+5PdjicdDuzW63EZgJv6+nBHWxtMWz8fE3R8iy1GDOz4p4yHZDKZoFAowHHcsgWrx5fxcDgcglibX2h0bm5uRQs5/ntajgbqxcDn8wklXPhkk2g0mvA3/xz/E79tsuXF+vr6vBzHCoUiq/1YlhVKSlHKGyrUKMvPKZHwu+630fzXL6PKcQy3XCjFAZcLu9++G2Z0wvQ3PT6y4zPonToEhWcCdZ4RmDGCUVUddtjfxH82fwzNgSl0BiZw1cBjUHZ9FTePvIA9794DAAh5evCRM/8ZI84xhGXVaA9OAgA6FUpcMX0AqlP12P6u5iW0TxzG05u/hFaDAcef+Vf8Yv0VuHHoBXxt7Gz0cnKYANRJZQhuuhpPm63Y/IF/LNY3VzCExIM+/sISEyV21wTePXgP1u/Yl5BwEOtu4EC/34+rqqrwvaEhALEl0XPOOSf2EvEdJ9KIVUvViL3QyOVy1NbWLvp8IBDAxMRExQu2zs7OhP8JIZBIJGhsbMyoIn4pwbIsCCGLeqO8Xi+GhoZACEkq1LOB4zgMDAygtbV1WTNkhbmHhZ0NKOULFWqUorHX9hxUjmPortsJ09pPYD2AAyEfnF4GNWs/AdPf/hfGqTcBAN3yGnQGJmBUmzEK4HKtCjWD0wCA62ZeBsE+7FBIgHO+iND4O5D2PQur04mdjmOx/au7MFi1AWNn/D0CNTVQDb4E9L+AR0S12Lb1JuzZfQMOHLgLu4/eAXv3o9gzO4CQ8WXc1PZ/sH/ofuyYOowDYhHWXfQNmMIe+F66A/ut5+Pq5jVlG6+WlG2fS2jUfuzl/8SeYz/D0yyLPR/+nuBh+2JtLV50uXDiVFxOfAKHEOOUrHxHhuKtVJDL5WhpacHc3BwmJiYqNq4tXozx/Tyrq6vLthyHz+fD8PAwamtrodPpFjzPcRzGxsbAcVze7RkMBjE0NITm5uZli+vj514kEkmaMUopT6hQoyw7fPbg9Rs+iaMeD66UbMJX3WHcbFIBUhWemVRgbGoKN4Tm4Ov6At70ekHAodndA+XIa1ACsI0chl+igSLsgTbsQctL34fKcQy48Fbcc873McP9B9ZKAF/HdqjkGnRu24fH7D58tb8fRGXGzR/7b/he+yV2eL1YvWMfoDJh/Y596Js4irbRlxExtOJSxzFI2Qh2uN5GX/0HYuO02XDzyKNC8P1++VcK1k6qKMxbEn2r/XI843TC0n459uC0h+2/zLvgY4HVCgVuqKtLEKtPPfUU9u3bl7x8R5rdDUoVpVKJtrY2eL1eTExMIBQKVdTF8J133sH5558PkUiEpqamjJY6A4EAQqFQSbSX4jgOU1NTglhZ7HPY7faCZUXyxWlZll2274OfezabraKOy5UOFWqUZUfIHmxtxd4Lv4av8gHrB3+C3UfvwBvKL2Gv7TngxR9B0nYBiKYj1jpKerosgHF2EFI2CKe6DlJ9A2rUzfCd8UEE1n4CM84AzjFbsefYz4CWWxNKUwCnaoZJpVApNNjxyu2ApQbYcSNM+hqYPnk/8NYDEPtmgFfvhK5+E3xnXQH9hk/iBmcAvmgU9rWfgDwaxSr9Znxy8OFYnbIy8g5lwvVt67Bf9RVcr5UAB3+OE9MT2P3WL/H+GXNwd34Sd3V0LN6Kyu7D3q2fT3y+zGqvLYZarUZ7ezvcbjdsNhsikUjFXBgJIWhoaMhIpLndboyMjAjLhxKJBGq1Gmq1etmFWzgcTsjmlcvlkEgkC7aLRCIFTyKRSqXLLlqDwWBahYsp5QMVapRlZ35x1dMeqdjywAazGKrN1yI0dBDSvmfxTJMZa7SNMLqHhdeQskF4ZQb0138Am088iM04BOz6F9zuDOB7Q0P4cfvl2GM0JgiCxPdComjgl+Q6L449tukzgMqMrs6L4Xv/z/jd1BSU0Simj96H/956HZTW87Hv8K2Q9j2L0NBB/GzLNzAnNyzwLpU7wnd28OfAM9/Gxp0347/XfR7f0p6DG3Q6/O5UJfT4z93a2rp4B4f53Q3KGEIIdDodtFotXC6XELhdzoKturoaUqk0ozqRTqcT4+PjCcuHoVAIDocDLpcrQbhpNBqoVKqCLqUODg4K1fgXy1TlOG5ZAu2Xu9VWa2urYAtK5UCFGmXZsYfDQpmHBFGzbR8gVeLcMz4BAHhTUY9Z/ZlwN++CLDoIxAk1n0wHddAJ3cALcKlqoPdNAOAwF40CAGYk2qTFWGM7nxJlDecAg6/ExFn3k7ElucFXgJ6nccDlwroLvwbz0V8Ky5wdCgVu6b8fTxsMeMbphLT/WcDcAWnfs5jm6vCTxo/iqMcjFIitKE6JWtXGa3C5RAOHzYbpUAi3j44CAMxhN26YPgBsvAbnnnsuXklS/FOgTOPUFoMXAzqdDg6HQ/DSlOPFcs2aNRm1xZuZmcHk5OSin5UXQvHCjWEYNDQ0FKxoOMuyYBgGKpUKWq0Wer1eeC4cDsPlcsHhcBS8ECzDMMsu1DZv3ozx8fFlfU9K4aFCjZI1CyrVp8lNfX1Cd4AnNmw4/cQpb8t999yDfR0z6Dp+HwBg69D/QjV6CF5GBjUbRBQMVMFZRBUmtPsngSCAxh2wb9qLF3piwsEeDi8eD8U/bu4AZnrQ5/eDu/w/MOpyYcNZH8c7+nWn49E2XgNfNIpRxRbsd7rQuVWJ1m17MTo4iKmGBlStuwK+9/8Mi2U3LggyeNLhwCffew87dLrK8q7FecLMiGV3fndgAABwgV4fW6p+/ns44HLhvVErbti7FyqRCJeZTKdbUfHfRZnHqS0GwzAwm80wGAyYmZnBzMwMgNwzCJeTl156CRvi52QKvF5vSpGWDL60xeDgIHQ6HWpqavK+NNje3g6GYQSxGY1G4Xa74XA4EAgEACyPTVLFxhXq/R544AGcd955y/aelOWBCjVKVsyEQkKJBiC2jJmuaLujrS3hd3JO3dE37cAB6LD2VNYnCwIRWIREckjbzgN74nEwkQC8hMHVg5N43ecDALw7PQxEfcDZ/wyEfDEvjsoU+x2KPe4LenGS6HB1zSfRMeHCk6pduC2sToybk0qhOvcm/OKUKOWbuj/oY3FW21W42dIIleUm3ALg+rjv5FmXS2h4XqncUFcHlUiEvVYrVLMq9HU/j31ox6fDTmHJ9Pbh4YXdDJLFqVWQl00kEqG6uhomkwlTU1NwOp1lIdb4UhzpetN8Pl/Wn4vjOMzOzsLj8aCurg5arTar10mGSCQCx3Hwer1wOBzweDwghCx7PTGZTLas2bKzs7NlcZxRMocKNUpW7LfZYs3PjUZBpC24IC/CKpUq0ZMWj88OZWgaWPcJQKoEQnP4yIs/AgCEiQgSLooIEUMaDQDHHwYD4D1FHW5qvC7WmQCASSzG7wOHgFd+HOt+0PP06ZITf7g+1vy9dTdU/Qfwu9Zr0dGwHne0tWG3Xp8kbi5G/GNJK/Sf2ub+1atx16llPz4Wr1JJ+J66n0Tb6Mu4p2YrBrSnY9L2Wq3wRaPwRaOYCYVO9wid70k7cg/w4o+A0Bxw3teW8VMUDrFYjNraWlgsFkxOTpb8hZSPI0sX36mbomzhC8mOjIxArVajsbExL2Us5ubmMDQ0JBSk5d9rOSGEwLqM859lWUxMTBStDiGlsFChRskKXqzwfS/jEwTSYdFl07cewDUztwHd6tjF3GdH5J2HIHYOQMJFMSdRw8vIUBWMtRoKNe/C99d+BU/5WFyg159ecgyvARSKWPxZ886YSDtyd0ykAYCxA1MNOzGq7sIdbW1YpVLh5nkxM8nGOBMKCUu3u/V67JVIErYxS6WJwfMrhVPesd0br8HuUx6xmVAI9/YdR+3xh/B13Y4lPIzcvN+Vg0QiQX19PSwWC2w2G7xeb8rtiyHmGIZBdXU1rrkmvWzcaDQqLCPmCsdx8Hg8iEajWffF5GFZFsPDw4ieilUtBoQQNDc3FywGLxl2ux0sy2Lnzp3L9p6U5aM8qxhSig7fTuhPp3oz8t6VeEFz+/AwZkKhBfvyy6a39Pdjv82W+OTGa/Bw1Vfg83twV/fbmJFoIP773yOii13gvYxUEGkRXSOk/5+9Mw+Pqr73/+vMmslkmyV7yE4Im4CIqKBEQbRo1SpVbGkRa7W2tPZ6L9r2d1u0d2mFXltbWq1VkV5bscVWvUorogYFlU1AQNbsCVlnMslkZpLZzu+PyRkm+zYhk+S8noeHJHO2me8k5z2f5f358hb+NSODjbX/x8+S43gsJ+dC1Gbuaji+HRyNgYiNw3rhPBodW/Pu4p1mG7XFvwCHpcc1S1HCLXV1wcc219Sww2plWUICjW43d3/+ee/PY7IhRcn0JrZv3x5c48YDL3L/iWf4bsP7XN2Z3ur1vXH5A3D9TwP/T1C0Wi1ZWVnk5eWRmpra67/k5GSUSuVFH3wujUHavn37gNt6PB5KSkrCKiiVSuWIRRpAXV3dmIo0hUJBTk7ORRVpXq83OIVg3759F+28MhcPOaImMySkKNMtJlPPlFYIfaVCQ2vbpLRpF/QmrO0C+j2bqMht6DSUnUrL2p28+s6vWHb2VZI6N63TGDB8/DSnmhpZf/pF9tuOw8rNcPiPUPcZJF8CH/86eOi2jCuQEjv7WluZHR3No5bdFJ1+jmKgeMbXu4xCCk1xSs9nQ1YWG3Nzcfh8wW0l0fbIuXNEK5UTq4lgGFit1mBqPGra7fxMpeI35iL2lJfzzty5vb83uqdDJ1DNWneioqL6HcdkNBppbGy8qM7yoigGC+77o729nbKysrCLoeHOswzF5XKNaT2gQqEgOzv7os9DDfWCGyhaKzM+kYWazKCQBFqoQAGCX0vpvlAhBz1ToaG1bU/m5QW3fafmXGCk1Pw1EG3EcdkGslKWsqpz/5cbGmhsa+Zdwxy09hMIqmgyGo9C41FWzLmH/clXcHn9J7DzR4GaNMDt93Ng7oOIHge72tzM0sBKPgFgh93FK5/tY1V7G5vzVvOYeh6PtDfzvmM3s+OmAV2HkHf3fuseKQx9TYptNrbPnBncbjidseOd0NdroykDS3U18zrrnwaVJp+gnaGDQUpDqlSqi+ow73Q6+328ra2NysrKsBflC4IwpNq43pBSnmNZAxgdHX3RRZrb7R43zSoyw0cWajKDontEaW1KSrBovrftoPemgtCbtLRtsc3GjCPPoy/dCkol16/8Kr9zOlmbkkK5pZptu/6HuzrKSKzeGzhu7hq+W7MjeMym+s8pLnqCmY3F6Kd/ERILoe4z/jj3Yb5pFdmQlYVeqWSuDvbqDUzT6ThjvJYvntzOYxXbOHXVo5CddcHA1voZmxf+hFvS84PX2r3BILQWTRJtf6yro6yjg90tLWypq2N9ZuaQmiwmCnfddRfxIa/XI5mZJGo0QauO7k0YvSJ1hBasCJjtTsDI2kAYDIYh21+MBEEQuOWWW3p9zGazBWdijsZ5RypwGhsbR90XbSAkk92LSW1tbZc1ufLKKy/6NciMPrJQkxkU3SNK0NWeobftQgmNLEk3cGmbW0wmPuQO3EINmoIVbP34Yx6PjWWn1cqyk//LoyUvAVCWegVnzbN5PWoe36t6A4BWhZZqp4PnSk9CbhGL9j7P3JgY9He8wG3qWJq7RbPybwt0kP7G7ea7wHogK/umgFlryQUD2woxnTeKBjfHUxJtdyclse7sWebFxPR4HdampEya6Nrx48dZtGhR8HuzRsN6k56d723kCe18diZlsstmQ9feHDTJ7SHCpFRo50QEoG8D4wmKQqEgMTFx1MccSfj9fo4ePdqlW1EURRobG4M1UKOBQqHoNxU8EO3t7RExgNzj8SCK4kWrL3Q6nT1SnVVVVUybNu2inF/m4iELNZlh05eNxS0mE2tOnQp2U0LPSFtoivTlhgauqngPTcmuwISACiXMmsUum40Z01fya2870QoFGxOu4Ict+9he9VumeJoBUIoi17We4M3zf6bcf1lgJijg0ESzJXtln6LIrNHw2Iz5PKxN4L70PEjPAMCaez0HD75CYv6tQ7bXmKbX887cuX0+3udYpQnGiRMnugg1AI68xPJDv2Jt7hqE3O+x3Ghkbfl2eO/xwON9pTdDPdcmYTrUZDKNqkgKRRAESkpKgt+LokhNTc2o2ooolUry8vKG7TcmiiJVVVVjLtIgIDjdbjdarXbUzyWKYq+joqqrq2WhNgGRhZrMoBhKCm/d2bPsstlw+/1B4dI9whSa9txhtTJVUcA/Mq7GkHs9HH6Pa+LiONFUzfKKg7xUeBfbHH6eqvorazujawB+lQ6914XXmE/Bbb/CpI5hr6+DeVoFR6wNPNF+BJjb5/W+3NDADquVBbGxAeG06CGer6zkkdhr2ag3hyXqJT1Ph8/H3sk8KLlzwkNWylJWdXYHW+Lu5oDdzuyZd9JnfCy0yWCCDHQfCtK0g9EWawqFgtTU1GDnpd/vp6KiAqfT2ed5BUEYcndjqEmuUqkkNze314Hpg0HyDnP30lk+VnR0dFwUodba2jomqVaZsUEWajKDYjApTUnYTIuOZpfNxrSQupPu0bfQtOeC2FiuOv4+edUf8vzeP7It5TJWGQw8Xvt/FB1+CrFiD+XzfsBUVeAP/MHobLKVPsxf/BWU7UZV/xkApoRUFl2/Hl77FovO7mT7Ah2zUm4c9HNscrtx+HxsyMoKm1mtdByHz8cum40VRiPr0tPDcuxIZcmSJT1/qDehv+Zh1nV+e9rh4LbTlZzSL2Fjq4f1CYMYSTaBBroPBZPJNGqpPUEQ0Ol0TJkyBbVazZIlS/B6vZSVleF2u3s9pyAIqFQqsrOzhyxKnE4n5eXlAOTk5Axb1DidzqBfWiRE0yAgHNvb28M6ZaE3RFHsUZsmMX369FE9t8zYIAs1mUHRW5oTukbapAaB6M40hrmfT8qhx3ssJweSvkexQsGj6nnM9ii5OymJaUnrcFs/4+aSXXD457QapwIg6E2YGw/Bgd+Dzx0wsd35I5q+/CeOF2+m6OxOvMZ8zk0pYlY/z+nupCQO2O3cnZQUfC6PV1SwwmgcxivU//NscruD9XwTuT4NGJQf1sMlJZxyuSjU6YL1e6EjySZL48VgUCqVoyLWJPd8o9EYrKtSqVRUVlb2Ga0RBIHY2FgyMjKGla6Mjo4mr3N03HBEmhRFs9lsESPQQrkYUS6r1dqnPUq456bKRAay4a3MsOkegZJEW7RSycbc3MFHjhwWHIe2Upy1grjYRKafPMHuHT/F4nGjufHneI353Gw9xE2eGvbOfZCc2zdfGA1lLYOsRbD8v9lSV8dK9TxKMq5GZT3H6SOv9tqZKl37urNn2WG18nxtLZsqK5kdHU2iSsWOTh+wcNLdEHgi8+677w64zZN5eawwGnlt1izMGk2PkWRDwmEJNB04LMO84sgnKSmJrKwstFrtiIvVBUFAq9WSn5+PyWTqcrxdu3bhcrn63C8xMZHk5OQRzbDUarXDEmkOh4MzZ85ElEiThr/rdDpSUlJGfWyUz+frtxP4+PHjo3p+mbFBjqjJDIomtzsoeiRDVykCtTE3t8cYqcEIEinV9e3y7ejfe5zLjPPZXPh9kjwt3H/iGc40HeZU6qUssp6jTWsgpuJDFqi0aOKS4bZnYMsN0HQWEqdB4lTWut3o2rNIUVxBsWkGW/SLg6m27ueUUpEA++12dre0UKjT0ej1BqM8MqNH93mvPd47/Rnedn9sEjQZSF5j+fn5OByOYG3WUAWLJLYSExN7FXy9RWoEQUCpVJKZmUlpaSkNDQ2kpaVhDGPkeSBcLhfl5eURI9AgEB00m83o9fqLFsm6WI0lMpGFHFGT6UFvI34kUfZ4RUUw2rQ2JSXoqQZd05l9jY8KJTiiKWUpbblLudl6iD8495MQE/BDKqjfxzvNzexPvoKYjmY+16UHOkP3/hJe+xYs/3kgsrb8v4PnX9dYjH7PJhaYUni0cG6PqJ50TqfPR36nJcDlsbFszM1ly7RpXaI8MsOjoKBgaDs4LOg+2YyuvfnCzyTxdeSlntt3f2zu6sD4qUnQZBAq2DIzM4MRNoVCEfwnCEIXEaZQKFCpVOh0OnJzc0lKSuozKpeSktJFCEgNA1OnTiUqKgqTyURcXNxFHf7t8XgiTqRBwBZEpVJdNJHm8XiwWCz9vg6pqakX5VpkLi5yRG0S01fxdm8dnmtTUnB0ftoOFWZSyjP0GIPtEJWOsyolhRfZQAUZZM34Misvj2XfR+3MtJeQMf8rGFNzeLb4t/wi+hI2+8+wvPoAVO4Fnwe+/lrXg3Z2F76cMD8QqdN9EcfJ/+O3iUU4owzcaDAEa9DOtbezwmjkkZCU5FsJCSN4RWUAFixYMLQdjryE/r3Hqcgt7xwZloll5p0cs9l67wjt3v05CZsMpFqxmJgYnE4nPp8PhUKBUqkM/j/UmaEul4usrCwgMOYqOjoavV5PXFxc8DgXWwj4/X7Ky8vHdH5nX/j9fkpLS8nPz8fj8YRlwkJ/DGZKhVT/JzOxkIXaJKYvQdVbh2eoE/9AxxjUiCAuCL3NNTU4FXr0V/8Lq9LT+duLL3L/zFw4/iJC7CxI/TZfTU7GnTKLS7O/DMU/DQi1lJBWgZB02O+yV9JQ/Av0pVspOfMeedUf0phbzi8yb2dvSwu7bDYWdEbRJkNx/8XmT3/6E/fff//gdwi17uh8z7zQ6uGRkI7QLkxCYdYXw7HI6IuoqCgOHjzI/ffff9GHwveGKIpUV1dHlP1GKIIgIIpi0HtOqvsLFx6PB4/HQ3R0NO3t7bS2tg64z549e1i6dGnYrkEmMpCF2iSmL0HVV4fnYI8xlP231NWx+ewx1tbtInrBPWwrb0Vhr+d/NXOZmnwFT+hmY931FOtPP8c685/hrpdh0b+APrFrqiukTmntggfZdsU32GkwsE5RwDf00zietQLcMC8mJmC2Kgu0yKGbdQfA1XFx5EdFUeFy0eR2D32tJvBQ99FCSplGgkiDQD2W3W6PuJSnhCTUpOsbadRPFEWcTietra20trbi9XoRRZEZM2b0am4rM3mQhdokobc051AEVV/0dYzBjktam5LCnAMfsLx0K3uUTozVH/GZaz4xH7/PFdZDPOv3c3/2PXwjLhNj01n4x/pAulOKqEg35IIVge/nrg7UqhXMoSl7OsrDh/mBPp1l0QlszJAF2sVgpD5STW43a0+f5lx7O+dqa8nS6Yb+Pp0EDQajQTg9wDo6OqioqECv12M2m4fU6dnS0hLxhfPdh9MPZ1i91+vFbrfT0tKCw+FAEIQux1EoFDQ2NvbZidsdnU435GuQiXzkZoJJQrBwf4i2E701FoTzfGaNBr0y8HmhsO4TZrhqWKnbS/OV/0Jb7lKKGvez2X8Gbf6ywA6mbjUY0g35zI7ADTkkemLWaHht1ixWGI08nW7k2+Xb2VZ+csjPRWZorFq1akT7b6mr45TLRX5UFOszMobXgTuJGgzCyUjXLhSv14vb7cZutw/JX6y9vZ3q6uqIFmmhCIKARqMhPj5+SPuJosjZs2c5f/48bW1tiKLYq/gbimC96qqrhnQNMuMDOaI2SRhs3Vh3hjI6arjnS170bZ73wtJLvkDCPx9mu3UGt7vO8vLch0ix2ajLuo7llo8CG0ebu+7cz1ih0w4Hj31+iN+1fER1qY38I093KViXGR22bds2oht+d6sO6cNCn9HQ3tKcch3bsBjp2oUSHR1NQUHBkDpEpakI40mkZWRkDFmkQSDi6Pf7B3yuUop1MHz00UeyWJuAyEJtkjDcNOdAgquvFOdgz9fkdvNQrY0d5hvZGJWD7sYXaHh1O6/rLmNjzbtMsR6iqbYYFq8DTXTgZtz9xtzHDfnhkhJmnNxOVulWtmStwjH/+2RNuz1YsB4OQofLv2GxyKlVGFTRc390f++EzoXdWliI2WOfdD5qF4vBrJ3b7UatVveoZWtqasLtdpOcnBzsOB2KSIvkDs++iIqKGna62OFwDGq7oYjWwaZIZcYXcupzAjLcdGVvDOSoP9yUauj+O6xWliUk4PD5WBEFBn87hxqq+HtTEwBtFZ3RNCm12Z/HVghP5uWxJ+dm1ueu4fSsr3LpDf+PVdnT2VJXF5bXRhp79EhpKbcdPz6i10GmFzonDtwbp2aF0XhhYsQk9lEba+x2O2fOnOHcuXNdhIbb7aa+vp7m5mZOnz5Nc3NzP0fpiSiK1NTUjKtB44IgkJ6ePuzmCyndKSMzEHJEbQIy3HTlcBhuxC10f117MzknX+VfVNP4zumN3O+pZ2rJIe4p/D6LW09x6flPYP+zcO0PAzv1k+4MxaRWc0PGVMj4F36Tno7ZY6e4eDNPqOcBc0f82kgis1Cn45TLNbzxRxOQr371q+E5UKcgMwFPzr0PgFtMJjAN00dN7gQdkP7Wzuv1UlFRAQTSduXl5aSkpGAymboMCZdEV0JCwqBFjM1mo7W1ddwIF0EQiI+PJ6rTNHuoiKI46IjaUFi8eHHYjykz9sgRtQlI94kBQ2UoEbmRRtykaQI3HX6KJ0ueJ7G1nH26IhJSZ/LIlAymTbu2c0vxwkxH6NE40Ne5H++8sWwrP0nzX79B0YEn2eo62OO1Gcpzlra9xWRiQ1YWX+z8f2th4aRPewIcOHAgPAcKiZS9YbGww2rlDYvlgjAbqtgaZCR2MtPf2gmCEEx5SgJMrVbjcDhoa2vrse1Q/M8ivcOzO6Iojmiup9frxe/3o1AoMJvNxMbGhuW6JE83mYmFHFGbgIzUdiOcEblBNRUUrKDk+FuUYqR4zgOcK4nm/hO/ZLE5Fa58EHSxAfuN174VGMQOg4qgSOd0+HxUfPI8hvL3edM4nz+lLeOmboJqKM85dFu9Utll3qkMnDlzhqKiopEfKCRStlYdi8Pno9Ht5rGysuC82SExyEjsZKb72rlcLlwuF/Hx8SiVSqZNm4bH46GtrY329nZiYmI4d+5cD5ElCAIdHR2DsuRwuVx4PJ5wP5VRR6Ua/u1TpVKRk5NDdHQ0giBQV1eH3W4f8TXV1tYyY8aMER9HJrKQhZpMD4bbIdobvYrG7imoMzvIq93H9wDH9A2cKgn8wWpye9hicbB2wYOYDzwdEGlTlw/5RnujwcAzOcs46jrL9hkP8tiM+T22ucVkothmC6TWBiB0W5NaDYTntZLpm4CNizIYIdUrlb2OL+s3vSl3gg4Zu91OQ0MD58+fJy4ujpSUFDQaDQaDAQCr1dqryPL7/bS3tw+q0F6q1VIoFMPyIhsLFIqRJaO6T5QYieiTmfjI745xzmCNZYdCOIxw+6UzBeXw+fhd9krunXknUS47R9ramD71RrLPPsMZbyr/LmbyVynKFRoNGWTKS4p8Fep03Fy2izm1H3FPxhVM09/SY1sptVaUkMBatbrLa9r9NX65oYEdVisLYmN5LCdHtvroxmiNsLnFZGKn1cq8mJigSOsRBZU7QEeEtHZutxun04nb7Uan0wVTnt07MltaWvpMWQ429Wk2m4mLi6Ojo4OWlhbsdnvEC7ZwD2JXKBRDsuHoi1mzZg28kcy4QxZq45yL2TgQylAFYpftO0XXlsSiwLXn5hJlXkTO5//BO23NzK3aTwG1fP3M/+Io+lUgWqXRDHjj7X5N98apMTb9k0fjrqJ02u28FZ9Aafo1zHh/E39JX86q7OnBaw+NInZ/TcfqNR6veL3eUTnuGxYLu2w2lhuNwTmx0C2aOdT0ptxg0AVp7aqrq3G5XIiiiEaj6XPYd29rLRXaJycnD+qcgiCg1WrRarW43W5aWlqG/wQuEiONqHVHsjMZqVAbT9YmMoNHFmrjnHCmKYcivoYqXnpsv+ghVrnduKIC57O+dR8F1kO8523nde0XuE34Gx8W3MVfbLvQe9JBM/BNtPs5TCf+wjeOP03eAh2z5v2QLXW5NBT/gqTSrVTkVnUxvg2NInZ/Tbv/vy49PZh6k+nJ7t27mTZtWtiPuzYlpUedWvC9Fyq4hhJJkyNwXZDWLnSGpdvtDha+d6d75EuhUJCWlkZCQsKwzt/e3j6s/S42Q/GHGwzhEn4nT54kLS0tLMeSiRxkoTbOCWeacijia6gCcaDh7afMhRTU76PFVEBUjZeCjlq+UfUG+po9oFT2eRMNFZc9ztEZVSmauxo0Gm4xmfjRtNv5e1wcidNu7/Pau7+mA30vc3EwazSYPa1UfPI8m1OWoVcqe6Q8i202Zl3/w8GXAcgNBr2SmJhIdXU1fr8/2BjQ2xzJ3iI4Q5np2Z3x4KMmCAKJiYlhPWa4U6kyEwtZqMkEGYr4GqpYGWj7GYu/RUlLKTcYjBwuO0R52hWobvhvio+9RkbBl/h79xFCnRGUbYlFPHI+YK653qRnfdXfAz5bGlOX4vEmt5uHS0rY4YK/JSxjo9487Jq+0agLnEjMnDlz1I69tu5d9KVbud5g4NKUGy88MHc1xTYbK9XzeLSubvDvTbnBoAvS2sXFxVFQUMD58+dpbW2lvb29V6HWPaImiiLqzgab4TAeuj+joqKIjo4O6zHDJdQyMjLCchyZyEL2UZMJMpAnWjjo7ldmsdVS/NbjaE/8jbzqD4m2nGQWp8jOvpxXMXCtfgkP1dp6erF1RlDW1r17wTOuH58syZw2PyqKDWY9a0peYfOZo8OaUDDSaQwTndEsaNbPXwPX/5T5V3+r64QJvYlZ1/+QRwvncm+cOuC357CM2nVMVELXTqVSkZmZSU5OTpcORYnQaFqot9pIRMdwXf4vFoIgjMg/rS9GIm5DmTJlSliOIxNZyEJN5qLSXeQc2/ssRQee5HBzA2WpV+DucPIKtwAit5hMrDAa+XFmZhcD3ya3m82JRTiu24B+/poL4rKfUUJrU1JYYTRyrr2dooodJO3+Tyo+eX5YYmukhsITnVdeeWX0Dt4ZAftNczuPlJayuaYm+JD0QcN04i+yse0w6W3t9Hp9rzVZoc76arWaqVOnkpKSMiKxNdL9RxutVturaB0pCoWCnJycEdeqffzxx2G6IplIQk59jkPGc+otNL3a5HazP/eLuP1+9O1Wcmo/6dxqBtQd552ac+ywNlOUkNBjSPcT5RXM8tgpCj14P2kss0bD1sJCNtfUsL/9i8yIjiYrffmwBrTLNWoRjlx3dlGIi4sjPz+fpqYmzGYzGo0G0yB8CAc6plarjcimgtGKpknodDqysrIoLy8fV1MaZEYfOaI2Dhmt1Fs4h7l3QRr95LB0Sa9urqnh0fpWdk3/Gm7VhfoXg9IJpe+Tc/JVNmRldYmkSaObtnsOU3TgyX6jJr09nwN2OxurqjnSbeSNTPgwGo2jfo516elsyMrC6fPxWFlZ1/fscEdMyQx57aKiosjIyBj2zMvujHTQ+Wii0WhGJZoWil6vJyMjY9jPPyYmJsxXJBMJyEJtDJBGsAyX0Uq99ScARyTiutWOScdydta4NNR+DmV7qDHNhKxFtN+4kvW5a1ijuwy9UhmMGkrX94bFQlHRuj7TnH09H6lO7YnWj1h+6FfDTn2OmqCdIKxcuXLUzyFNKthUXc3jFRU91nHEaxTy4WIycTHWbiAi0aVfiqZdDAEZHx9PamoqEEiJSh5rg2HhwoWjeWkyY0Tk/UZMcERRpKKiItjunp6ePuR29tFKvfXX9Tki09duqSjpWBuystiYm8uDxd8npvUEAMW5D+P83Ir+mn9hXbdrkXy0HD4fTepYzIseunBDnbuaJnVsl5RwXz5ot819CEdSElkpS4eV+pQNcPvnpZdeYvXq0Us7Sqn/W0wmHJ1iP/g+6ewGfi12Lg1HXmXbFd9gXcGcoZ9kkvqrDXft2tvbaW1tJTo6Gp1ON+yGAlEUqaqqirjUn1qtvqjRKqPRiMFgQBAE2traqKysHNRrsmfPHhYvXnwRrlDmYiILtYtMU1MTHR0diKKI0+nk3LlzpKenD9sgMpz0JwBHZKzbzSbD4fOxISuL7xqiAoXfRT8EfBzSpLCvthSxyct3DcsxJQQ+VeKw0LD/BR6KWcgUQxqbqqsveGiF3FC3TPlSFwHVw//MY+fb5dv5bWIRzilfGt5g75G+FpMAp9M5qseXhLKuvZnHGosDHwCkdex8P3w9bxma0l04srNhOEJtkta5DXft2traaGhoCH6vVqvR6/UYDIYhpQubmppwuVzDuobRQhAEUlNTL3o6djhdtOPBh05m6MhC7SLi8/loaGjo8slIFEXsdntECLX+CFcUb0tdHY9XVLDCaCSq6u/w3uNgngq3PM3s9/6D+dW7eZavBLpBb9oQ2OnISyTt/k8yctdw+JJ7u6Z9Q26oa9WxQD8C6shL6N97nMbccn6ReXtXw9QhIDcTjC1BoVy+Hd57PDgzNnQ8maZgBZzZgX64Qkv2VxsSer2+179hQ/FFc7lcPf4+jjUKhYKMjAxiY2PH7BpUKlVEvSYyFx9ZqF1E+vplG8oA4vHc8QmBm2yxzcYOq5UtaUv5lvFPqJrOYv/Tl4ntCBjXLk08R4o2PZDG0puwzLyTT5oslKZcx+apU5mm1wdrkNampARSoICZnqnI7jNGd1qtbNHOZ1lCghwRGyXuueeei3Ke9kvuRq9UBmfGFttsbC0sDL4fSJSF1lAZ7trpdLoRma36/X4qKioiRpAIgkBMTAzp6elhqZmrr69HFMVhdY0qlcpBvy5LliwZ8vFlIh+5meAiolQqBz2GpS/GXcdnNySbjI25uazKns6LRU/yuS6d2I5mzkSlcqhwFWXuHPR7NsH+3wPwQquHm+Ov44rUXKZ1plE219T08NHqgcPC8Xd+xhOnjgReL72JS2/4fzxaOJeXZ8wYl0J3PPDBBx+M6vGl34EXWj2BmbHZ01lhNLKvrpzj7/ysSwOA3PgxNEZ77fri/PnzETNQXKFQkJ6eTlZWVlhEmtfrpampiebm5mEJUYVCMei066lTp4Z8fJnIRxZqFxFBEHptvR5KRG0sOj7DSfeI4G2FV/Lmsl9TFZ1OQXsts9trKW0J1GTsbWmlye1mbUoKG7KyAk0EQ7nhHnmJogNPst1zOPh6SU0GXVztR/BcZBHQk9LOOsHRovvvgCT+e7NskadIDI3RXrveaGlpoaWlJSKiaRqNhqlTp4a1FKWxsREI/J0fbg3ZYOvU6uvrh3V8mchGTn1eZDQaDWlpaTQ0NKBSqVCpVF3qH6Q/Vn19groYHZ/hTK9Kx7o3To3pxF+CszkdPh96pZK1KSlcXreXKc5AZEwjeiAmmb35D3Jr9FVd5jY+XlEBwGM5OaxLT+9yDrPHDkdewjLzTl5o9XSpV5KGskvX4vD5gscayWspd3+ODaFiW3qPmjWagGVLQkKXBoCwNX50dpMyd7XszxZm7HZ7RIg0ycMtXOOcJJxOZ/D5ORyOYXnOKZVKvF5vWK9LZvwgC7UxwGAwYDAYEEURl8tFe3s7NTU1uFyuoG1Hbm7uRb2mUAG4qbIybAJEEjMLHLspOvAka6/bgCt3JQ6fL3iOexfdz16PiwWWI2gqPuKGOYvQr/gpj3beiIGg55ozJD1SbLOxu6WFYpuNt+zvo3/vcWwn3+GJzPuBuYFrDykI724LMtKbt9z92Ts33HDDqJ+ju0hucrvZYnGwdsGDXT5cmD121lf9HUyrQTMCgTVJ7DouxtpFKlFRUaNiaJudnR1M6w5XBKpUqkFF4y655JJhHV9Cmtk6lCyPzOgjC7UxpLW1lerqaqBro4HT6cTj8YT9k91gCacAkY4xO24aJCSgn7ua9XpTZxSslbtObaGqoYzLmo7wuXkuc4GDNhezunWLRXeG/qX/t5WfZMGxLRxPWcbuFvhtchF3ZLxHXvWHbE9dwKyUG/t9XuGoT5O7P3vHbreP+jm6vEcdFj5979f8QVHAnKNnWH7d9y5EvcIlsCaJXcfFWLvuJCYm4nA48Hq9YxZZG83xUEqlckSD6mFwJsCSMa5Op8Pn8+Hz+fD7/YiiGBRgEqIodnmtBUFArVaTkZGBz+fDYrEEZ7lGQrRzsiMLtTFEGsDb/RdGo9EM+Is9mt2f4RQgZo2Ge+PUHNv7LLMX3Y+p8wZq1mhY11gMHz1JYue2GfZG/lS4lr3V8bxQUsIOqxUIREzuTkrigN3O3UlJAKytexd96VYA/pK/ih3tAhsz72d76oJACkxuFBgzPvroI2bNmjWq5+jyHj3wEssP/YonjfNZbj0ERiNNCx4MpNxn3okJRi6wJoldx8VYu+5otVry8/OpqqrC4XCMiTAYrWhauBjoQ7sgCGRmZvLhhx9SVFTU5TG/3x8Ubl6vt8vXXq8Xj8eDTqfDbDYH70mxsbF4vV5aWlqwWq243W5ZsI0hslAbQ2JjY0lLS+P8+fPBTz06nY7s7OzgL0xfjKf6qGN7n6XowJMUA7Ou/2EXu4xGhw3bsdeZai/B7GvjxpgoSqOieSgvj6JOC40mt5uHQ4Tb1sJCzPPX4ACqdZdR6XBT6XazLCmT4vjZzFLHYg45f7hr02QijLmrcfh81CXMx2E7hH7u6uDvhyMrC/2UL7G223tCJrJQKpVkZWXR0NBAU1PTiEWBFD3qXusrHTc0yqRQKEhLSxvR+UYblUqFIAi9vi6CIJCQkNCn0FQoFCgUiiFnaFQqFSaTCZPJREdHB1arlebmgIWSnBq9uMhCbYyRnLsrKyvRarWDHsgb7vqosEfoQoqvZy+6n2Jg9qL7ebn8JA2fPB8c7fNi4VocNed5zF4CgKn0bZbP+x/MnlYWHNuCEHc/Lzc0MOPI81hzbg74r3U2GOiveZjfuN1MqazkcFsb82JieLyiooeRbbhr0/pivHvchYs5c4YxCWAk6E3or3mY+wAI+EhJ5sehtZCyOB+Yi752IQiCQHJyMjExMcFUqMfjCUZ+fD5fUGBJ4kOahalUKoNfq1SqLo9131b6OhIHv/dFf0JNoVAE07ajtX5arZbU1FRSUlJoa2vDarUG51XLkbbRRxZqEYBGoyE/P39I+4S7PirsEbqQ2iDTooeCUwbWfvYy+tKtOLKzacqejsPnI33GClzNe7F5Oki1lpLu+JRjez8MRuHWxsaiL91Kw5QpbM27q4vQMms0JGo07LLZANiQlcW9ceou8z+lkVXDHRk1WMZTlHM0Gep7eTSQfj+a3O5gd/GImQSdn5Gwdnq9PqLTkGNBXzVqgiAwZcqUYKnMaK+fIAjExsYSGxuLz+fDZrNRX18vR9hGGdlHTQYIrz9bk9vNRuPV7Jz/fSwz7+zymH7+Grj+p+inf5HTO36C7t3H+PIHj6JrraLdL/JY1ir+eFpglgpeKryHmEu/xpaUpTiu20DS5fcGZ3h2v/YVRiO7bDacPh+v7XoK3vkJjkNbWXPqVDDKNtpRrtHyuBtvvPrqq2N27u7edpJgM3vsAfEeYoY7ZKQPHyE+bRONsVw7mb4JnU4gFf4nJiaSn5/fZVj8xVw/pVKJyWQiPz+fqKiocRWhHG/IEbUJRKSk3rbU1fFofSvEXsvGVg/rE0IelIqy9z7FoiNPsyjkoZyORhYYk6lqdmL++EmO5q7h5cY2dlibceWuZH0fUQzJ8HRLXR07rVZeiLsKZoErZSk7zltZYTReFPEkd4GOMZ3dn09o5+PwzeaxnJwLj4Wj+3OSdH7KRB4ajYaoqChiYmKIj48flhfbaKHRaMjLywtbfaFMT2ShNoEYSeotnGm7tSkpODp9g3oTSE1uN9sSi1h15cOU2K1MbTyKsf4wrSmXclOcjtfS0nFctoGslKXcl36hqWAw3JeSwnfa2vhoyhoeSc9kY5RlzIXrZCOpszP3onMk0P25NncNTJ3dY86rw+djS2IRq9zu/t8PDgvsfxYQ4fIHLqQ5J0Hn55itnUy/KJVK8vLyBtxurNZPqi+MjY2loqIiaAsiEx5koRaCNOKjt3mc44GRNBiEsznBrNHwWE4OFlstx975WcCWIyE1+Pjmmho2l1egaXXyo/il3CIm8VTj5+wS47h998+5/roN6K95mHWd268fRL2KJDQTVSpwWjGW/oXXuYdHpl864uczXCIlwnmxue2228bmxJ1iLCtlKavS03t8+Phd9koeKS3FFVXX/4eRIy/B7p8Hvj5/GG57ZsLWpHVnzNZOJiyM9fpFR0dTUFBAdXU1bW1t/Xq3yQweuUatk9bWVk6fPk1JScm4HdURrMcZhijoPplg2PMrHZZgLZBky3Fs77M9Nltf+Sr3n3iGXQ1/4w8nnyTW38Fy66esz13Dr45rBj1HU9ruFpOJFUYjjV4v99e/y6bSrcw889rwnkOYmKxzJl988cWxOXFn9+e6gjnBMVOhNYODriGcuxqW/ACyFsHZnZ3RNbq8tycqY7Z2MmEhEtZPslopKCggNzeXzMxM0tPTSUlJITExkYSEhBEbAE825IhaJw0NDfh8PgRBoLW1FaPRONaXNCaMNAXqOLQV/XuP4/D5mL3ofnb6/RzJ/SKzQtJN69LTsXuqACiofBelPyCMFVOXcZPexOcOYcDrOO1w8HBJCTlRUfz2/Hka3W5ytFpMKhXPJi/FI4okFtzGTcN6FcLDZB0x5Y6QIfXdawYHXUOoN8G1P4T3RajYC1WfQONZ2PmjgHCDCZsCjZS1kxkekbR+arW6T++2jo4OSkpK5G7RQSJH1DrR6/VBnxrJ1G+iMZgo1Ug6F5vcbu7TXcb63DVsSVmKKSGVo3O+wcaqaj59+7947rPdOD54ErPHTkPibAA+Vxmx6VMh43KiE9IpOvAkKldz8Dokqw2LrbbLtUsGuG93muAebmvjt7W1WLxeiDbiWvgdnFGG4UcGw0BohHOwEUKZMOCwULHr51z54U4+6bRtkX4+pIjY5Q/A1OVQWnxBpE1dLjcTyMiMEK1WS3Z2dhfT4fHmbXcxkSNqnaSkpKDRaKitrcXlcuHz+SZceLa/KFVoPdVwmwm21NWxzeFnxdz7eDS7EAgIvzlHD7H80K94s+xD9NZDUPUxU697nLLGz7is/tPAzo5azvkEUhev576FD6CQoh97A1YbL1RW8kjqF4PX/uPMTEpdLn6Zl8cxp5NbTCaer62l+HwJS0r/Rqn6dn7rChy6S/ffGNDkdrPm1Cl2WK0U22yByQoTuGbtvvvuG9sLOPISWXt+xuLcNazVxHNy4cLgz4fU+ak3BerTjrwEBSsge/GE9lCDCFg7mRExntYvOjqanJwcnE4nGo0GtVqNRqOhrKyM9vb2sb68iEKOqHUiCAImk4mcnBwUCkVwIO1Eor9oWTjqqe6NU/O+Yzd/zEwMChGzRkNl1nW8aZzPvsJVeI35cHYnxnd+RI6jNrjvmahU8mv3caDDxxsfHrgQfZq7mudnPcgTpiUkqlTcYgrcJD9sbeWUy8Vvzp9nbUoK0/R6HsnM5D9bPmJT6VburXsPgGKbjcfKyi5aJKu3yNmWujp2WK0U6nTByQoTmZ07d47tBcxdTcXiH7In52a2TJvW5edc/9OhRcSkTs/EqYH/J7BIgwhYO5kRMd7WLzo6GrPZTFxcHDqdDqVSSXx8vBxZ64YcUeuGXq9n2rRpE/KN0l+NTjjqqaI+e5miA0/SpIK32n28kHId/z1rAXfbDqG3HuLGUy2orOfw6QwoS98P7ueNz+S1a35JQuk7XHrp13jzlTf4n+hoHD4fj+XksPgLPybx+HFOuVw8XFLC1sJC1qakUGyzdRkptaWujie089m+4GGuWHQ/Kyob2WG1srulhfebm7nWYAjbdIK+Ojp7i1pKr+ktJhNvWCwTvmatsrJybC9AbyJr2Q/4uJefd4+kDbozdxJMJYAIWDuZETER1i8uLo6GhoaxvoyIQhZqvTDRUp6DobuIG461xMsJ80kxzsfVeJ4vn9vG8YwKHAd/ij77Usi6ClXFR6AzonQF6sps+hQSzHm03vgLdtR1sDvxC1xTa6Ow04NNuo43LBa2TJvG2tOnuwgzyeRWqmO7d+adUDiXWSk3YtJo2Bpt4u7PP2eXzcYHra180NraYw7ocOkrjdyb4A19bQdjNSIzcprcbjbX1AD0K84H3TwTDsNcGRmZAdFqtSiVynHrvjAayEKtF9xuN+Xl5ZhMJgwGAwrF5MkQSwLN4fPxeEUFMLjuzya3m8yK91huPURN9nw+TlrICsdZZjefgMZDAasDAJeVc6kLUfq95NQfwjHva9xV72Z3SwsQSEGnXnMNG8xm1oV4Ya0wGjnlcnWZMmDuVsdmAtaH3ETNGg0vz5jB5poanD4f0Uolt5hMbKqsHJQA7U+s9hWBlKcTwE03jWWvbYBt5SdxfPI8W1KW9RTnIdGxQUeSJ8lUgkhYO5nhMx7Xz+FwdOlW1ev1ZGdnU1NTQ3t7u+y9xiQRaq2trVgsFjQaDWlpaQOmNdVqNSqVitraWurr6zGZTJjN5n4jbV6vN9i50hd+vx+LxYLL5SIzQm/mkjDakJU1pO7PLXV1/EFRwD8yrqbJ7ebKhn1UJ84JPJhxOaTPh4q9lKddwYr0r/N29R8BONLWxi6VDYB4hYJZ0dFcYbNxTKnE4vEEB6rfaDAA8GReXk+B1c9NVDLfldhUWTlo+5H+oi2yIOubxsZG0tPTx/Qa1ta9i750K9cbDGSZlnYV5yHRMfOihwZv2TEJImmRsHYyw2c8rZ8oisGxU6GoVKqgB1tbWxvnz5/H15llGYxpbn/34PFqujsphFpLSwsOhwOn0wkwoFgTBIGMjAzOnj2L3++nqamJpqYmkpOTMZvNXbbt6OigtraWtra24MyzvgRdaDdLe3t7RM1rkwiNMAy6lsth4Z5TW7iufDd5jYdIET1UJ84hpaPTBiHvOrj8fhxRBl40Xs2/H/tfcmo/wZ29hL3T7uQqp8hHdjstfj+/ra1Fefgwv543L1iDtjE3lw9bW9lhtVKUkBBIH3avGRrkTbR7BKW/FNlk9UEbKfv372fu3Lljeg36+WtAqWT53NVssli6Cu5JEh0bDpGwdjLDZ7ysn9/vp7q6Grvd3kM4eb1ebDYbBoOB2NhYCgoKcLlceL1efD4fPp8Pj8eD1+vF6/Xi8XjweDyIooggCEyZMgWVqndp09DQQFtb27gTa5NCqGk6b76iKGKz2VCpVCQnJw+4T0pKCnV1dcFFra+vR61WEx8fH9zO4XDQ1tYGBFKmpaWl5Obm9irWJHM/URSxWq2kpaWF5fmFE8nRfbD1aRZbLbbt3ySv+kMSgUalnsSaT5AqsSzxOTDvHkx6E1tSluL45HlaXI0A7NVl8Wh9KzlaLQDXxMWhUSho9/tZYTTyZF7XOZ+69mbWlm8H05ph1wx1j4RtqasLpni7p8jkqNk4JkS8r1XHBv6XBPdwo2OTpKFARmY08fl8lJeX95nWFEWRuro64uPjg95q0dHRfR5PFEVOnz6Nz+fDbDYTGxvb57aZmZk0NTXR0NAwrsTapBBqarU6aGYriiJNTU2oVCpMpv7/2BqNRmw2Gy5XwJBLFEWqq6vRarXBaJjBYMBisdDR0QEEImx9ibWsrCwcDgcOhyOiGxaGMp3g2N5nKar+kHOpC2lztzPXchQAb1wGn2mTWZX9DaZWNvKkOo6C039jXelWqvSB0Hy5T8DkbuWOyl2UTrudvLg4AKJnzeK/Or3GQovv1zUWw3uP4wC2pCxl7XUb0A8iKjJQrVl/A+Rlhs78+fPH+hK6EDbBPQkaCiJt7WSGRqSvn9/v59y5c3g8ngG3s1qtPTJYvSENhG9qahpwKL0gCCQmJhIVFUVVVdW4mYww6YQaXFDsSqWShISEPveTwqhnz57tsm95eTlTp04Nii2dTofb7Q5u43a7KSsrIycnp4sg02g0aDQaDJ31VgPh8/lob2/H5XLhdDrxer1kZmb2GdYNFwOl/JrcbraVn2Rt3btccumXKQbmTL+e7P/7DgB+lY4/L/gha3wZLFB0MOPIc/zIdTu7tfP5KH0xBTV7KMm4mlOzVrP2yEtsKt3KToOBG1zXAnBHX5+eClZA+R5eTpjPd88348pdyfpBRDYGqjXrbog7WYeph4uMjIyxvoQu9LmeQ42QTYKUaaStnczQiPT1czgcwXqz/pDq1wwGw6CCGgaDgYSEhEHbasXGxpKXl0d5eTlerzfio2sTtp3R4/HQ1NRES0tLr+pdFEVqamqw2+39Hkej0ZCcnNzlDeD1eqmoqMDr9VJWVkZLS0uXhRZFkY6ODsrLy4et2B0OBydPnqSiooL6+npaW1txOp3UdNZTjSbdh7t3N3HdUldHxSfPo3/vcYyl71BUtA7Dm99B1VyKX6FC4XVxxYmtAGxo3sum0q08UP0Wa+t28dql/0LxgodJWPkHdLGJbElZxs7532f+1d9iQ1YWyxISMO3fz+aamp4jl87sgLM7udt2aEiNDkMdizVZh6mHi9dff32sL+ECDgvH3/kZT5w60nM9pQjZkZe6/LjPcV9SynQCpz0jau1khkykr19ra+ug74miKNLY2DjoYw/V+1Sr1ZKfn090dHSf+3YfbaVQKNBoNBfdZ3XCRtS8Xi91dXXBDpC+cuGVlZXk5OT0mwM3mUzYbLYuYy1cLhenT5/uU4mLokh7e3swstZXJ4rVaiU2NrbH8FqVSoUgCME3tUKhQBTFPofcjibdI1JrU1J4YcE97DQYmD/zTkz7fw/WwOOKzgHrDaZCfpNmoMirgSWPMr29g+XHnuXvcXFcm7CMja0e7k5K4oA9m7jMa3ihtZV16encnZTE87t34+zNHqQzkqGfu7pHJK2/KNhQU19yE8EE4shLFB14ku0LHmZWyo3AhffKvTPvxAQ9ImRDSf3LyMgMnoECI6GIohh0SUhMTAzO4w4nSqWS7OxsGhoasFqtqFSq4CgraayV5AIhZeYg0AxYVVXVJZM2mkxYoSYxkHqXUpl5eXloO4vauyOlQM+dO9clBToQklgrLy8nOzu7V7F2/vx5AAoLC7ukNLVaLUlJSTQ0NBAbG4vBYECv14+Jp1sX4eKwYD7yEtGJRdwQey0rKhv5i8+PHmhS6jH7HFREp/F00jK+cvJV9Iefgut/yiMxi8nIbWa38WrWp2XQ6HbzwJkz7G5pwe33s8tmo9hmY0FsLJ/rdFymVF6IgoWmqPqoDQrnzTUc5r+TmYhqkukUYUVzV0Pn2gXfK7m5XXz3JAYU6hO4qSCi1k5myETy+nV0dAwq7RmKKIo4HA5cLhdKpZLExEQSEhLCeh+UatwGajAMJSoqivz8fCwWC/X19aMu1oRIz80Ol5kzZ4qvvPLKoLdXKpUkJyfj8Xhob2/H7XZjMBi6FDM2NDTQ2Ng45EURBAGdTterWPP5fJw8eRKNRkNBQUGPfaWW47FGEivfLt+O/r3HcVy3gTsTlrHDauUPRoF73nsIla2MNkFDjOhmfe4atqQsY7vnMLMX3c8TTQ7+3tTEufZ2CnU6TnU2aACsz8jghNPJDquVDVlZ6JXKrqKo09CW638Kix7qYqlxd1ISb1gsXcYzhVtMSd5rG3Nz5QjLBGDEwrvb+1FGRmZgmpqaRixqBEFAEITgvXksMkzd8Xg8VFdX43Q6RyzYZs+efUgUxcu6/3zC1qgNFZ/PR21tLY2Njdjtdjo6Oqivr+8yxiIxMXFYhfyiKOJyubDZbD0eUyqVzJw5k7y8vF73jQSRBiF1WylL4fqfop+/hq2FhWzMzeVu2yFUtjIAYkQ3LQm5lE67nXtzZ5Ba9G98vbKRTdXVZEdFcWVMDKdcLq6KjWV9RgYbsrL4RmoqC2Jj2ZCVxbr0dGL++U+21NXR5HYHRFliEY7rNgSjI5KlxuMVFTz2+SEain/BOzXnutTVhZPQGrc+65dkgjz33HNjfQn90r0GEwhEyfY+Ffh/IIYz3H2cEOlrJ9M/kbx+Op1uxMcQRTFoHH/mzJmI6NpUq9Xk5OSQkZGBUqkclXv2hE99DoXe1HBTUxMpnSkQQRBQKpUDthb3deympiYMBkOPhZSOG8lIaaBVKSlQEJg4YHE4+LS+HJe9AX1cBrRW06TU849FP+XVGbPhyEts9hexw9pMoU7HLpsNU6fQjVYq2ZifDwQiVo9XVLAhKyswvsrt5vHONCbAI906PEMtNb5dvp2k0q04srOD1xVuQlOhQ5lsMFmJhD+e/dFrRG0o1hsTeEpBpK+dTP9E8vrp9XqMRiNWq3XEUbW4uDiSkpIiarxjfHw8er2eU6dOhf3YslDrB8mYNjExMSikRvKL4PF4cLlc/TYuRCqhYkW60e20Wpl7cjvm0q0XtvM5WHjkGRwtR9Hv2cSdS/6df5hu4MeZmfxHZSU7rFYKdTo2T50aPJY0JgoIjK8SBH6TZmBt+XY6pt7IAsduZsdN63ItQUuNpHtBoxmUn1o4kESiw+ejye0e0vSG0LqmiVz3Fkl/PLvQuQbbEot45Hwz0LNRZSJGyYZCxK6dzKCI9PVLSUnB4XB0acwbDFJww2AwkJiYGBEpz97weDwoFIqwC+bIXtUIQPJcs9vt2O32IRdDdj9W97lmY4HP56OkpITW1tZh7b+t/CQNxb9gkcpD9fSVtGVdDUBF8nzOpCykoGYP2xsbcFy3gRdTlrLDauWfzc3BVOmH8+YxrdPIVkpjHrDbuTspiY25uaz75jdZ11gcsP94bwNFB57EdOIvvacd9SaaFjzIJotj1NORkrgCeLyigjWnTg36nI5DW+GdnwT+p28LkImQWr3vvvvG+hJ6pzNqtrbu3Z6pbHVsn9YbE2FNBkvErp3MoIj09RMEgczMzEELSkEQUCgUJCYmUlhYSFpa2piINKkxcKAh8eGoU+sNWagNgCiKtLS0UFVVFRYnY7vdTk1NDVarFafTOSLhN1yam5uD7cWVlZVd6vAGw9q6d9lUupVvNxYzLyaGgwkzeH/OA9yZehd2n5dfp36BsvYOtqQsxRl1wdw3dDyVdNNbm5LCCqORHVYrb1gsrM/MpPif/7xQl7b8v4P1QH2JG+nnQxFOfdHfTXlzTQ2PlJbyfnMzyxIS2GG19u211q3maUvK0s4Gi6XB592bt9tE8HB78803x/oSeqeztkw/f02wRm0wr3ef2wylrm2cELFrJzMoxsP6aTQa0tPTB6zlkkqCCgoKSEpKGpPyIJ/PR1lZGZ9//jmlpaWUlJRw5swZ6uvrg9OIQhmtOaJy6nMQhDOMKYoizc3N2Gy2oE+aUqlEq9Wi0+nQ6XRERUWh0WhGJYwtRfWkN1NrayttbW2kp6d3mWHaH9LA678kFtH4yfMUlW5l5/zv8+f6/yOv8RCZcdkk1pZzxluN4ran0efmcovJxKbKShwh/miSaOs+0/NkZSU/iYuDtKWsO7MjmC7sMbOxk7UpKcEB7tvKTwZGTQ3TOqE3mw8pkubsFNUftLayISuL5UZjl+HuXVKZndGbYpuNWdf/kFXZ09kS9W+BGj/69nbrzRpivKVJJcuZiKOX2rLBeOb1uc0EHCkVsWsnMyjGy/rFx8djt9t7mMWHIooiPp+P0tJScnJyxiSSVldXF4ySSdfp8XhobGykqakJtVodnIqgVquD4ybDjSzUxojQhff5fDidTpxOZ1Cc+f1+VCoVUVFRREdHk5iYGJZuEofD0UN4+v1+qquraW5uJiMjY+DO1s4b3iq3mxd891AcG8U8rYJ/znmAKSoFiQmZWEv8FNTsoXj/FtbftCFYhL8+I4MVRiO3mEx9ep+Z1OpAtKl8O7z3eOCHix7qVdxIIiYo9rrt0xd9iZ/Qm7JkA7K3pYVdNhsbsrKCtXTr0tO77Lelro4nTh1hwbHDFBWtg7mrKbbZWKmex6N1dazPzBxU80Fvz1E2YB09ehXM3eoJ+zRMluvaZGSGTVpaGk6nE3c/WRBRFHG73Zw+fRqVSoVGoyEqKioYzJBMaUej09LhcGCz2foVkm63m4aGBhoaGtBqtaOWIZOFWoQRKqK8Xi9tbW04HA4SEhLQjDCaIo3k6C1CKIoibW1tnDlzhpycnEG1Ups1Gh6ZfimOznqyc1l3Ud7houDI/2IE9idfQcbla8Fh4dvl29GlLaVJqWSH1cqC2FicPh/LEhK4xdS1uP6O224LmA+a1oCvA9yOwM2zlwhZqIhZm5LClvalrL2OAZsL+hI/oTflx8rKgtG/ZQkJPcRZKGtTUgIi7cCTkJAAix5i1vU/5NHO5zQSxtukhFtvvXWsL2FI9BUNBfqPlE3A7s/xtnYyXRlP66dQKMjMzKSkpGRQ6UKv14vX68XpdAb91KSAh8FgID09HbhghxUVFdVlMpHL5UKn0/Up6jweD16vN2h8X1VVNWhje2DIDRJDQRZq44BwfFpwu91UV1d3Cc1Kb3boKhDdbveQPG9eTpjPlIQ5FNmOU9ByAoBPEy9jdebXeXb/FvKjNeh3/5y118GmKV8KRqU2VVcD8HBJCTOjo9lUXY3D5+OLVivJyck0qWM57nQHxI9GH7gpOiw4Dm1lS8pSVmVP5xaTiWKb7UKETrLygED9UB8p0KGKn0WdaeFNlZV9jqkqKlqHIzaWLYlFXO9whM2Ad6gjsMaa6urqIbl8jzU9RPskjpSNt7WT6cp4W7+oqChSU1Opra0dUm1XaEYKwGazER8fj0KhoKamBrfbjSAImM1mTCYTVquV+vp6VCoVZrO5y7B3yd2hrq6uSzlSJFmdyEJtEmCxWKirq+vyxhYEgaSkJMxmM3a7HYvFgtPpxO/3ExMTM6Tj32LZT5LtKACOzKs5YpxF8qJv8+z+LRQdeJKXCu9h+ZJ/5y8pS3m8ooJlCQnMi4lhfUYGh9va2GG1csbpDB5v38GDvJeYiMPn48/k84+Mq8krWEGT283x4s0UHXiSitxytkT9GwA7rNYuNW5rU1LgwNP9RkUGI37WdX5Ck77uEb2rq+PeODWmE38JCsLfZa/kkdJSVrSXsMNqBSZfuvLQoUPMnz9/rC+jf0LSm9L7RqqjXJuSgnmCRcoGy7hYO5k+GY/rZzAYsFqtI4pIiaJIRWf2I3TMY2NjY5fB7l6vl/r6eurr64O1ZbW1tcFuztBypEhCFmrjAKkBIDU1dcjRNb/fT21tbZefCYJAfHw8ZrM5aB4YFxeHx+Oho6NjwO6a0w4HD5eU8GReHtP0ev6SvpzGrLNcm5DA8ZlfZVX2dMwtFeRbDvN6zpc452rnrZiF/CZ7Ov9oP8UOq5VdNhsbc3N5ecYM1pw6FfRXuzspib94PPyktJQNWVk8yznyqj+EMzvYMuVLPKGex5/nf5+sabcHC/OBYORKElDfyL0e49Q9ULBiSK9XKF382ugahZNE2wLH7kDED2ha8GDQE+7upKQu4lEmwghJb5oXPcT6zMwhmRmPtwYPGZlIRRAEEhISRjxeqrd9+/uZ1Wqlubn5ogxVHymyUBsHSJ2iDoeDrKysIdeqabVaPB5PMJSr0+l6bY9Wq9UDdtY0ud3cdvx4cFbnW5dc0tnR+O8U+3xsPnuMWWdfo8hyGErf5yadiVtdFqpSUjj+zvs8dflaZkZHc7itjVtMgZTkgtjY4GD2lxsaoLAwOE5KMNxPMZA5pYg5R5/nkfxbuTTvRpaHvAahN1VJQF1l+yeLzu6EtEvh2h+G5cYaGoWTBFiGLpdiYPbMO4OecBtzc5mm17O+0ytust3UL7/88rG+hIHpJb05lHR4j3TpBBnUPi7WTqZPxuv6xcXFUV9ff9HPOx5EGshCbdwgiiIdHR2cPXuWtLQ0DAbDwDsRKNic2jkFQJqTplAohl33trmmhlMuFzlaLTOjo4Pu/OszM2lyu7n+6O9ZdORpLHPvwRGTSWZbJT6dicMNldxS9reA6Jp6G+JnL/C69h7OWWu448AmvmjOIb6tlt85b2fhqX/QYP4+lqQkbjtdySn9Ep7b/zLfOP40GoUC8/RLu15U503SMvNOGt1uliUkUOCWauwCv4jh7pw0e+ysr/o7mxOL+K5+CRtbPT1u9JJAC7UkmQxp0MTExLG+hIHppRFgKLWAPUTdBLHqGBdrJ9Mn43X9pO7N/jpAJzOy4e04QxRFzp8/T2Vl5ZDz6JKBYDiaE5SCwKbq6i4moGaNJlh0X15zjC/nr6NBFY/SZSGquYTnZz3IJZd+mfv3/ZRNpVuZe+51bjn0S26wHWX+udfIr9vHTw/+hJbWNG7a8xOa/3g7vqZz5EdFsWTJtyle8DAZl6/taUjbeZM8tvdZNlVXc7ihkjNOFyz5AVz+ANC3wexwaHK7KS7e3MPlvvuwb0kcOn2+oCXJZOCtt94a60sIH32Y2vYY7D5BBrVPqLWbhLz11lv4fL4B/0VSobzEYH08JyNyRG0cIooidruds2fPkp2dTVRU1EU797r0dA7Y7cGasu7i49ysr9J4spgrGz7hxz5I8rbgFlQ456zmtnlfJOb/1qEp2YXXmE/+nNt5MrqAon3niHG30KaJJ8bdAoCurZ4r2uvZ3OHi46R/J/Ofmyie8z32NzXReOBFtl3xDdZJQ9jnrsbh87E/sYgNPh9f+XgTBTV7AjfOzjRUODsnt9TV8YR6HtsXPEzR/DXBYfHdkUShw+cLNjxI6VCZCKK/OayT2KpDZnzhdrtpb2/n5MmTXX7e2wdzURTR6XQYDAbi4uIG9s68CMTHx3cxY5e5wNivjsywEEUx2MGS1Wl3EYrL5aKmpoa0tLSwDoE3azRsLSwMNgA8XFLC1sLCYGThx+XlTNNl80FGCkZPGx0o0Ypebv7saVTlr0HFXpqUMZit53h17x/ReTzEuFv4JPkKHkq9nSfKtqJq7+D/4mdzf3s9h2NyuPvQL9DU7SPT0khh+hwWl/6R97Uij6kfZl16OhaiuE27iMaqavZVPktezR68xnxejJ3L1WG0yZBu6PfOvBMK5zIr5Ubo55hSc8Pmmho2ZGVNmsaCzPGW3u0mxrqkySeZVce4WzsZIOABVlpaiqmXqH1fwsflctHe3k5tbS1RUVEkJCQQHx9/0USb3W6nqqqqy3XKIq13ZKE2zmlra8Pn83Xp1PT7/ZSUlAABf5lwCjXoKdbWnDoVFGtPte0jqWIbbxrnc7P1EAB2hZYzyZcz/9S2wP6+No6Y5tDWbuds/HTORKVi0afxFftnFLWc4Bo+59faL7E+dw3/mHIj2tK/UAA0mwopcgRqvTy1R9l89hgLPtvCv8Yu5LRCz28a3g50iBpzUVnPcfrIq/wdQ1hsMkKtQUzA+gGiJ1JUptHtZlN19QXvuD582CYSy5cvH+tLGBrdxNjalBQcPh8On48mdeyksuoYd2snE5xH6fV6mT179pD2lYSRJNrq6urQarVB0TZaY5t8Ph/V1dURmYKNROQatQmAzWbr8r0gCCQmJqJSqUZt9pgk1qSB6lKtmqrwJkpSF5JgymPftLtoy7iCz2fcjenSr3AuaR61uoAZ4yxHBY9XvMLm05spaK/lptK/cVPNO1RoTDzH3Sg87eh9HdxR/hq/S7me9blrqLjsW2iu+zHehBzikwt5veUdbjr8FKsq3sCkUnF3QmAWKLlLaVjy71RPX8mPMzPDUpu2pa6Olep5FC94eFDRFWmA+367vcsxxvvA9cHw3HPPjfUlDA0pbRmSJtcrlTxeUTGotWpyu3vWTY5Txt3aTXL8fj9lZWXBIvz3339/2MeSIlrt7e3U19dz5swZzp49S1NTU9iL/M+fPy+LtCEgR9TGOZKrcmjIWxAEkpOTSUpKGtVQsiTWNtfUBKIPbjfHP/0rRbX7yGMfLHkUNDNZ+M5PKLGVkN9wmCcybuP+hmIM7TYA4nwBk0MvAvntF9qzp7lquKF2BwAL7Of4w+x1PNZYDHUdqGxlLLSVQW4RAFe1nORTpYeoqIBRryMqgbWmG9hXV84De59ifdG6flOUAyKNwMpeyqzs/tOd3bk8NpabTKYuQnGypEDHM7JVh0yk4/f7KS8vp6OjI+zHlu4bHR0dQYNYaQB5fHz8kCyi/H4/LpcLp9OJw+HA5XLh9/vlNOcQkIXaBMDtdtPW1oZerw/OP5PGQ/XX4en3+7t8qhlObYIUfXiktJQDdjtPXb6W8pqPyD7/CSAEo0/ClCJ+tmcrHR0ODG4b1rhMnoubT6VxGj87/kti/R34ACXgUwjE+Dr4deoK5jgquNl6CPOJ36Bv+pQ9M7/O5VOuRCMo4Irv4m2uYHnzUfaeeplr8+7gP2d/E7W9lX3+cp5o/Yii40+D7Tjc9syQb5pS+vLb5dvRv/c4665XgtTAMADr0tPRK5U90pyTwZ5jpDNpI4E+m096EWETyapjIqzdZEAURSorK3G5XF0Ez2jUl0nHDx1APtT9FQqFHEEbAbJQGyUkkeT3+9FoNHi9XoBRebNKv7QA0dHRuFwufD4fWq2W/Pz8PsVaWVkZLpcrKO4KCgqG9Yd6bUoKxTZbcNh6xhU/4utHf41m1spgWumPZWU8nnYLy7yNNAv1/GnuQzjjs1l39mVi/R14EVAh4gMe9P8J7OBWKPEqAm/REiGGHFUcJ5vOs7j+48CJ94CquQwAvULBAb+WdxxuNpVuZfsCPZcs+jrU7YKzOwM3zyHcNJvcbr579BMyTm7n5bl3cN8QrRcG6jKdyCa499xzz1hfwvAYTCSsFxHWY63HcQPCuF27SYQoilRXV+NwOHpEpZYsWTLq5x4OskgbGbJQCxPSJwaVSoVOp0Ov1xMdHU1UVFTwsZaWlmC+P9xhX7/fjyAIeDwekpKScDgcA/qlJSYmUl9fj9vtRqVSDbtwVEqBSuaup4+8iqZ0Fxz/a2CY+tzVODs93+ae/xBD+fvktLZyaN73+bS+HEVUKgXtgTFXSuA1buA23ibL1UCuu5G3E+ZwffNhkrx2vtB2ko7YdLT2Gs47bMQvXs+RtjaeU8/mR1V/56+mhVyv1xDvshLz9qPQdJaSjKtJmHkng42nNbndrDl1ihknt7OpdCuO7Gy45uFhvTZ9EW4D3kjitdde47bbbhvryxg6vYiwHoJ6MCJsHFt1jNu1m0TU1dXR2tra6z3k4MGDXHbZZWNwVTKjiSzUwoRWqyUrK6vP0LNCocBgMGAwGHA6nTQ2NtLW1hYWwSYIAtHR0SQlJaHv9OnqrU27O6EzPiWhN1ykqMJph4PHpq+kKtGA7+zuzhQoRKfdAkBjzjI6LO9zs/UQMz58mFx3YGBuoyqWRK8dp6CmQQxce667kT0x09D72kny2rEo9fwtbg63eqvJstdw2gP/yF5FdHszv9/9I65t3M8MtcDU5qPk1H8KwP7kK1iReT+PtnpYnzDw85BE2g6rlbjpK3FkZ6Ofv2bYr0tfDKUGarwx1NRIxNCLCOshqMexCBsM43btJgl2ux2r1drnfaOlpeUiX5HMxUAWamFCpVINuj4gOjqarKwsPB4PFosFa6d9xFDDw4IgEBsbS1JS0ohMb8PVgt3kdvNwSQk7HH6WOTr4xvlPKMm4mry5q1mnjkWvVLKm5BW0LYE0rSTSzkUlk99ez86EOTQroxEtFwTjpW0lRBNIG2t9br5Xu4ODMflo9Bn8LHMlX/r0D9Q5mrm2cT/7k6/gtvho9KcCIq1Kn86KvO+wMCV70IJoc00N++rK+X3LXu6Y+330CdeE5bXpTjgNeGXCRC8i7BaTiWKbbdJMlZCJbLRa7VhfgswYINtzhAmFYugvpVqtJiUlhcLCQlJSUlCr1QiCgEKh6PefIAgYjUYKCgrIzMy8qJMJ+mNLXR07rFZWGI3BkU/irb9jc001uk82c2+cmodiFvJExpc4ZphJqSYwl+6QPhe7QotVGc1dlo9ZyYUxNtF4kQZlxeAB4LK2c6Q6qvlB5XYe/PwZ8qKieGveQ+Td/SL6zs5Pmz6VCkUMzzTs4I+ZiV3qwAayU1hbt4v7TzyD6cRfRuFV6spEsnaQuOOOO8b6EsLGGxYLO6xW3rBY+tym3zXsYwRVpDKR1m4iotFo0Ol0fT4+Xoeyy/SPHFELE8MRaqH7Go1GDAZDr/Vr3b/XaDRdDG4jhdB0nlmjIf+mDWw8+Slz3/4+ettRjjdUkOEUOTLnXta27SNp93/ypnE+S22fEevvYKUlkCY9Rw4mDgePKz1TX8jXAHkdDWwp+DrrTcuYac7gptpavuPzo7/qe8Sc/D8WN58G+2lKtlfDyj9gSkgF+q8P+64hilNx0TgWr0d/EYrBJ2Kt2rlz5waVeh8P9Jui7mw+2JZYxCPnm4Fe1nCcdYBOpLWbqCQmJlJVVdVrBqa+vp7Y2NgxuCqZ0UQWamHC4/EEbTGGiyAI4zq03T2dZ7HVcvX7P+BK21EA5rWcZmHVxzjSktBf+SAOpZLylKWk7v0vzBVvo0LEgYqjTGdhiFCT6C5Nszoaqehws7ZuF1tYxuV1u9CXbuVM+mIKmsvAmEupOoG86g95//1fcm1SOsxd3evNVyoaX1PyCouOPI3jug0XxQNrItaqHT16lIULF471ZQyPbp2f/aaoO0XY2us24Mpd2fsajrMO0HG9dpOEmJiYPu0uKioqyM/PH4OrkhlNZKEWJhwOBzU1NaSnp49IrE0kThU/xaKGfRTHz8SduYjFah+aqo8RPE7Qm9Bf8zCr3G6On8iGCiiJSqZRGQuOC8fw03d+3imo0fnaeaxiG8usRzgfM4WdCXP4ceIt/CRpPi+lLSNJrcZw+EVW1x6Ao78HtwPztT/qcfOVIlufxiwkI3cNWSlLWTdaL0wIcq1ahDGUCFin+NLPXc36vkT9BG8+kLn4CIKA2Wymvr5eNo2dJMhCLUyIohjsuJnMYi3UzmBuTKBerENQcXTG3ehP/4VFwN9aHKyo/Rzjexv4R8HXOWezoZ77IFECXHH4aTwaIx1uBVr8/RZRRose7m74kDZU3GA7Cp2Ru4POy/h/addz99HnudJZwVFtKvkNn3bu1fu6SNGQa9VejlZEs8RgmNBeZ6PJVVddNdaXMHx6iYBJ74NbTCbesFiC74cmdSxbpnyJtepYzGN0ueFmXK/dJMJgMFBfX9/j5wUFBWNwNTKjjSzUwsh4EWvSTDdpjIdSqRxRjV0oXWqurnwQd+1hbijZRcXxV9AufoDnvfCEbjZf2PYVaCnjK9WHULosOPI28HLCfHSn3iDTVYOW3jtgvVx407pRkOm+UKRdqTHxtmEe8xsOonRaeLT6NQBSojrnNWYtAkSstZ/z8f5t/D7pWi6NjWG99UPM89ewPjOT4rce5xvHn6ZYp+Pvs9detPqxcScK+zGHHdc1Mr1EwKT3tGTqDIH3w0SsLxzXazeJUCqVxMfH95jzHCmNZTLhRRZqYUYSa16vl5iYGNRqdfCfSqUKu3jz+/04HA7a2trwer34fL6gAJNGREnCLPQf0OVaDAYDZrN5xCNkutRcaTRobn+W5/+xiR/FXcWSykoe0Gr5vfsoppYyfKpolC4LzdnX8ofEIqae/hszXDX8QnUfRdp3ucwRmDoQmv70CipUYsCuQ9NNzGW6LXyp6RPMvjbyXHX8Lu0mrvLW86v8Ncyp+4QbWk8wY/cTeA79iZvaqinOteEA9KVbA/9f8zAZl6/leZeLJZevZVb8xasfG3c3fSlFWL6nx3iut99+m/vvv38ML24E9DMi6haTiaKEhB51hYN+f4yDGaDjeu0mGWazmZaWli7pz88++4ylS5eO4VXJjAaDFmqCICiBg0CNKIo3C4IwB3gGiAHKga+KotjabZ8pwB+BFAL322dFUXyq87HHgG8CjZ2b/0gUxR2dj20CrgX+VRTF3YIgZANlwPdEUfxN5zabgYOiKL449Kc9uoiiSFtbG21tbcFIlSSQlEplcAqARqNBo9EMWcx5PB5aW1tpaWkJjoAazoiO0F9wq9VKc3Mz0dHRJCYmBueGDpUeNVd6E4u/8GMWlpRwb9l2lh9+ir1zH4Spy1Ge3cmbxvk8nPlNzta3Yoq+nKNZq1DURfGVGev578q/cGvDh6hFX/BwUZ0irTttqIjBi9nXBkB+Rz07RD/L8h/iOzVvMtd2nBktJwBIbqumQRnDbHsZue31FMfP5FzCfG5zu3mo1sZZ3WyKXv825lt/yfrMqUN+DYbDuGsqmLs6INKGMZ4rohlgRNT6TkPpLj93WODAIATYOOsAlYlsoqKiiIqKwuVyjfWlyIwyQ4moPQScBOI6v38O+LdOIXUvsB74cbd9vATE1qeCIMQChwRBeEcUxc87H/+lKIq/CN1BEITCzi+vAV4Ednd+3wA8JAjC70VRHDemU90FlM/nw+fz0dHREfxZf2JOq9Wi0WhQqVQ4nU5aW1uDc0MloRWuglJRFHE4HLhcLpRKJWazGYPBMOK06DS9nrcuuQRLZiLFKiWzF90PnjaaPR5+Y76JW6vfZktKwGIj2ZbA1I4j2C129umzWCkWA9CkSyTKZQt6qUk4BRXRopcYvJyMySPK00pyh41oPHyh+QgWTRyPV7zSZR83Akm+Nr7e+EHwZ6rT29kYnc4Oq5X3yl8kr3E/vHI3rH0b9CYstlqO7X2W2YvuD9p8hJNx11SgNwUiaVKEKCRalJubO9ZXN3y61ah1T0n3mqIerAAbBx2g43rtJiGJiYlUV1cH7zPJycljfEUyo8Gg7sCCIGQANxEQZxLTAOlO9w7QwylRFMVaURQ/7fzaTkDopQ9wOiWB6JtI18rvRuBdIPzzfMaY0BQlEBRybW1tWCwW6urqqKmpwWKxBG1ARrPbx+/34/F4qKur49SpU9TW1uIOgyGrKSGVops2BITOmR0Yyt/nu6Uvs6l0K58d+3dyHNU05CzFYeigNfVyrtdr2ZW/kj2meRxMu7qHSAMIfRmyHJXkdDQSjYc2QcNj2aspsh0PPl6pNmBR6tHQ+TqHHGfK2bcosVQD8ED2PdTFZUHT2cBNGDi291mKDjzJsb3PBnYYJSPTSDPA7fd6pHouvemCWDnyEtdcMzrTHEYVaT3hwnPiQkp6S11dr98DAeF1/U8HFmChr1eEMi7XbhITGxvbJfNRWFjYz9Yy45XBhkp+BTwCXYqCjgO3dH79ZWBKfwfoTF/OA/aF/HidIAifCYLwgiAIBgBRFE8A0cAe4Oluh/k58K+dadhJg1RvNlbntVgsnD17lvLychwOR3hE4tzVOK7bwBvz/4XPdemk2St4Yvd3mHXiT9Q3T+WJypdZfuxZYuzVLLYcRmUpCe7aHuKopg+ZXBAtXhByMaKbn5S/xLWd6U6ATE8zJt8F7w8lF8RaltvCzw4+Toa7lbP6dG6av5HiBQ9jzb0e9j7FJZd+mb1zH2SBVnkhetQpTMJJr0JgDJGuZ3NNTf8CMkSsvPjiixffkX+k5+tjPW8xmVhhNAZHSHX/HhgXAmywvPjii2N9CTJDQBAETCZTUKzt3r17gD1kxiMDCjVBEG4GGkRRPNTtoXuB7wiCcAiIBfoMAQiCEAO8Cnw/pI7taSAPmAvUAv8jbS+K4ndFUZwviuJ7occRRbEM2A98ZaDrlgkvUt1dRUUFZ86cwWq1BsWjKIp4vV7a29txOBy0trbS3NxMc3Nz3wKz00ftvxfcwEdfeBpPlIFkbytLGvcDUOG08+vUFZhFN8/lrOTbUx9gX0zAyPGU/kKKsPu0Aqsqhl+nruATfT7T2msBKNMGRlWVahKDx3AJPbP+BY2f8scTP+fnFdswqlRcq1/C9j1b4Z2fYCx9h0WJqej3bILin8GhF2HBN8OexlqbksLG3NyIqVWTrgfoX0B2FyujJGT7pPv5BiPcQrfpFJqWmXeyqbKS0w4HmyorebmhocsIqT5HSo2zUVEyEwej0RixDgMy4UEYKDoiCMLPgK8RqDeLIlCj9jdRFFeHbFMAvCSKYo9BY4IgqIE3gbdFUXyyj3NkA2+KojhroMc7a9i2E0i77u+rmeCLX/yiuGzZMgDy8/OJjY3l8OGA273ZbGb27Nm8//77QGCg+pIlSzh48GDQXuPyyy+nvr6eiooKIOBPExUVxWeffQYEagEKCwuDn2C0Wi2LFy9m3759tLUFCtqvvPJKqqqqqK4OpNSmT5+OUqnk+PFAOi41NZW8vDz27NkDgE6n46qrruKjjz4KFoguXryYkpISamsDomPWrFn4fD5OnjwJQEZGBlOmTOHjjz8GAq7VCxcuZM+ePcE6uCVLlnDq1Kmg784ll1xCe3s7Z86cASArK4vk5GT27w+IpPj4eC677DJ2794drIe79tprOXbsGE1NTQDMnz+flpYWSkpKEEWR3NxczGYzBw4cAAJdpJdeeinvvfdesEnivvvu48033+T8+fMA3HrrrVRXV3Po0CForeHytp3E5C/gryVxmEQLaSoLK7w7eUZ5D02xGaTay/mm7395Vn0nbf4Y9H43K8U3OaqYxkHFHOJ8ThaL+7FooznmmYPG7yFVqEUXa6G0NfDWEhQ+vul/hVeEm2kRA+WWd/EGxynkBAEPoiV8wqnoNM51TMOl1JBhVNJ61a0IH3wMrTWYxRbu9mzjj+pVtJkvRSX6+Oq0Dg54CzlTVgXA0qVL8Xq9wffHzJkzmTVrFq+8EqiXMxqNrFy5kpdeegmn0wnAPffcwwcffEBpZ/fnDTfcgN1u56OPPgJgzpw55Ofn8+qrrwKQlJTEbbfdxosvvhhMTd93333s3LmTysrA4PubbrqJxsbG4NrOnz+fjIwMXn/9dQDS0tK4+eabee655/D7/SgUil7X6VR5OR8cOIBJreaqhQtRJyTwtzffxKRWk5uVxfLly3nuuUBlRHNzM4+uu4/X/vR7GvwJoFBxxx13cO7zoxw98BFEG7lq8TXExsby9ttvA4HaqGuuuSYY0YmOjmb16tVs374da6clxl133cXx48c5ceIE+L0sSXGimrqUd/ceAL+XAr2dBTd+lT/9fQe0NRDXeppV11/GtqpkWm1WcFr56tfu4cCJc4H3flsDS1v/gnfu19ndEHgvNKWn84RSyQOnT9Pi9ZJqNqO/9lrMxcV42tvxiiJty5YxvaSE2vLyC+t08C98dKwU4tKZs+j6vtep3QlOK/d98wF27j0U9nUK/j4R+BuWmJjIW28FZudmZmZ2WSeNRsM999zDa6+9RkNDAxD4Wzhz5kyOHg14El511VUjWycCf39UKhXvvvsuEPhbumDBAv70pz8BEBcXx6pVq9i2bRutrYHP8V/96lc5cOBA8G/URPt9Guk63XHHHZw7dy64Tpdffjnt7e28++67xMTETPr707x587Db7Zw7dw6AnJwcTCYTBw8eBLren6SJQtdddx2ffvopzc2BcXCXXXYZFouFsrKA+8DF0BHf//73D4mieBndGFCoddlYEIoINBDcLAhCkiiKDYIgKAgU/ReLovhCt+0FYCtgFUXx+90eSxVFsbbz638BFoqiuKqP82YTIuQEQfgLcAXwk76E2syZM0Xpl1hmbBEEgejoaNLT0/u2/5DSiW4H7H4CzFOh6SyOKAP69mbK064g+/wndCTk8Ef9DL5Zc2Fw+69Tv0B+RwMrrIdoF5REiT72xBaS7GvjnwmX8N3zO7Aq9RhD0p4AHhSo+/BrC6V4+tf4zGbh6017SPC0cqhwFdm1+1iR8yArL/0C66v+HojmXP/TSdPNt6mykkdKS9mYmzv4Joi9T43sdQq1t5AiaH0dq7sVRue5Hddt4HfZgXFPZo8dx6GtbElZyqrs6V2aBbqb2w7p2vpLgY70NZCR6YeWlhbOnz/fpeZZZvwwe/bsXoXaSHzU7hYE4TudX/8N2AIgCEIa8JwoiiuARQSicccEQTjSua1kw7FREIS5BJoGyoEHhnDu/4JehkHKRCRSN+nZs2cxmUwkJSX17CSVUmcOC9tPw8o7vgzHt0O7nb0dfuZqFXD+E7TGbPK1JqgBp0JDtN+NVRPPnw2zuK75CFGij3pVHP+ady8l0an8pOxlGlSxJHntAFRoTOj8HpK8rb2KtFBDXYm5Z16lyBf4lN6sSSB+6f+jGbh/9+9YomPUuvki2QS3PzuR7du3s3Llyp47jfR1Cu2uHOhY3Y1rO7fbkljUxa/ud9kreaS0FFdUXRfBaVKrexWgfa7JYEdFRXjnZ59rJzMueOedd/jSl75EfX09zc3NslibIAxJqImiWAwUd379FPBUL9ucB1Z0fr2HPmb2iKL4tSGctxyYFfL9UQbfCCETIYiiiMViobm5mdTUVOLj43vWVuhNWBVmSJwKmmj0u3/OIqmjznoWzu5kUfYSqvUZZDiqaVNEcTj5cjZ+toko0YdToSXZ28rtTR8zr62U5Z1jpZyCmmjRQ010GmmuOvAG6tu8KFHhR9nZCdrbL0RCp0hzA4K3g6Ov/RsWdSz3l2+nrHE/e1Mvp7DoIUwQiJiEydA0kk1w+7MTkVJgPeguZgYThQrdJlTkDGGGZpPbzRaLg7ULHmQV4Iqq69O0dqDXvNfHh2JkG+GzP/tcO5lxgdVqRalUkpaWhtFopKqqCrfbLQu2cY48mUDmoiKKIj6fL2g3kp6e3vfYk+435tuegde+hebsTgwLv4P10B8xeu38/rP/Ru8N1EyUxmQzq/U0dzR+RH7HhVl4n0dn4IpO5D+Sv8AzZ34HBJoQlCEmHR0IaOn6B00SeG4UaPCj8bu4o+ZtLIqA8WlO/SFy6g9xru5T7AqB7POfBHYMw814vJngStEm/WBvCgP5jzks8Nq3Aqa60jbDeF27i6tQAdZdcA70mvf6+FCNbMfBhAKZ8U9UVBT5+flYrVbq6+vHxDlAJjzIQk1mTBBFEZfLRUlJCQaDgeTkZJTKQP/mXXfdFdioe/QhxGRVP3c17X4/HHialPZAAalboaHDkEODo6aLSAP4KK6QRwofZPvRx8l1N+JFgapb6lMSaaEjq6JFD+0KNVH+gPWHh0CI2OS/UO/mBfLrAq4zZ1IW0thYy/TazzGWvjOim/F4M8GVBNHPr756cDuECvHexMuRlwIizTwVClYM+jq6pyeHInj7e817TXs6LOB2wpJHB5/OjOAJBcHfPZlxSff1k+w74uPjOX/+PHa7XY6ujUPk9KHMmCKKIs3NzZw+fZqamhqampo4ePAgLpcLr9fb849KiA2EqWg9LPkBLdFJAGj8buZX/JMkXxsVaiPlURdcugtd55nTfIoEdxtNypgeIq1FqQt+3f2XQhJpEIjCdf90I33frIwm1lbGoiNPY/37d+Cdn+D+6z1hsWyINCPc3pCsPOZ1dl4NSB+GuUGri4IVkFsUMB4+/tdBX0d3LzpJfPVX5zeY17dXj7sjL8Hun4NGP3hBPliD3DFA6viTGZ/0tX4qlYrMzEyysrJGZea0zOgiR9Rkxhxp0oLUFn3ixAlSU1ODIk2pVAbnokojtdRqNWpNHKqiH+ArvJWyN/6FdMGL5nyg/Tre106Cx8rB+OlYBA032I6Se7qBfFegjfycNgmLOo6FbYH2bY2/9xmiEk6URONDAbgFJQ2KGDJ8LThQoO8UfQafEzrr2VItgSlpmvIP4NV74Y4XRpTmiuR6NQlJED37z3/CUB3uQ6NroRGnKVdAaTF9lLr2ynBSxtLrW2yz8WReXrDjU3psbUpK8Pt749QXahGH0xwQwXVqJ06cYNGiRWN9GTLDZKD1i4mJoaCggMbGRpqamuTo2jhBFmoyEUf3SQxerxev1xv0R+o+G1WlUqFe9jvqFSLC+X0IZe+Rfm47AFneFj6Km4NRpeKkEBMUavkdDahC6tF0nVMNpOHu3YnGR5k2EVGEt0wLcCq1PFr9d9R9PAe9r/3CN6XFIx5cPt7q1SQG3bkaKl66ix9NdL9CqPs5hpMyXpuSwk6rlR1WK26/n102W/CxoEA26QNWLJKFDAy7bg6Qa9VkxgSFQkFycjIJCQmUl5fj8fQczScTWchCTSbimD59er+Pdy+KlYScCyB+DsydQ1pSOsKp/yPRWsr3HAGjSVPypQC0qPTEex1kdzRSFZ3OFGcNELDuUPl9xHhtPc8J5HQ0AvDd2h1sybgZDwKakBRqi6AlXgyYOPoEFfXGaWinLOAUOgpn3slIbsWh4iOSbTsgYGApMaxIYPeI0wBCKBzRRrNGw6L4eHbZbMyLiWG50dhFFK9NSYEDTwcifUt+EJ7UZQTWqoWuncz4Yyjrp9VqycvLo6SkRBZrEY4s1GQiDqmpYLgoFAqE5QFD0ZKX7iavNlDon5s5H6J00HAGvA6qopI4uHQjLx9/iy84zjK74UDfxwz5+mD8dLLtZagRu4ywkkQagFL0UtrhpaJd4PHY2Ty791mKitZNeNsOCNTDSFyMSGC4zrEuPR29UtlDAK836QMiTWpoCFcELAI91ULXTmb80d/6SQ783bfPy8ujtLQ0OI1BJvKQmwlkIo6RFjSHCr2UJcUwBAAAXB9JREFUvGs4VLgKR+bV7HN5oGIv8a5AZGxKewOJH/6MOc0n+FHyTXxonMfe2GkAFMfP5NepKzikz6fZOAtnwrTgMTMd1TTHZADQoogG6CVZCovbTvPVU1v4+Mwmig48Gba5l5E2D7Q70qgg6L2QP9yNEYNpFugL6VpOOxx9RymlyNeZHeEdvh4aOYyQOaGhaycz/uhr/Xw+HydOnKCioiI4/klCpVKRm5vb99QYmTFH/vgkM+EICrUjL+FsqGGq146+8kN2ZKVRNXUVpvpjnNWlcH3LcRbbAqJwSkcTM1w1bMz5CvqZt7DdqeRnx39JjN/NsaX/RKGJYfrrN4LHTpLXToKznjeN87nZegi7Qkusv6PXa3Er1JhaymiMy0ZtKCD6xS9yOCaX/GU/wJSQOqzn11sNVqSnQ0MJR0QwXM83tIlgR6fZa49rGu3IVwSmQGUmFlJdr91up62tjaioKJKSkoiJiUEQhC6RNWkGp0zkIAs1mYgjNXV4Akaio6OD8+fPkzLnqzjb/0Z98lU4pnyR2pgMvjLjUtYd/YSHDv4XOe0Br7U2TTzfz7uPK9ur+G3StWyMNnLi4N3E+jtwCyqmHPkfai7fgCshn5jGw3gRMHZYaYjJ4UxUKr9J/QKPVW2nOH4ml7adI6ejMcQg10OjKpbE1nIcbzyIpr2ZhXzAXpWORbf9HAiP6IikdGhBQUG/j4cjVRmu5ytdwy0mE0UJCV2vKbTYfzQFVASlQAdaO5nIpq/1k8SYZHnkcrmorKxEpVKRmJhIQkICSqWS3NzcYBpU7giNHIY0lH08IQ9lH790dHSg1WpHdAxBEFCr1TzT2shXVVGolRoQfcQlxPLO/uf45vHfscc4j8vjYtGUf0BJxtU03/RrvlbZyCmXi+ubPmX72acQb9zI4Y+eo6hxf5/nalLHY/a00KbQEtNHZK0xLpvE1nJ8OgNKVzOOxevRL/t3oOeA8+EIt+77DHSM0MeBsEbjHA4Her1+SPsM5jmP5jX3ylgOUB+jjtDhrJ1M5NDf+lVXV9PS0tJDgAmCgCAImM1mTKbAe62srIyOjg5ZrF1k+hrKLteoyUQce/bsGfExRFHE7XZzry6BGqUGRC8KhQq7rQ1D4Z08PeMBdl23Cfttz+KechV51R9ieu0bvJkSxcvucxyNy2f+ta9wMucGnpu9jg+M8/h16goOZt2AWxEw5TgSnUmJLo1v5d1Pgyq+T5Hmi0og8eb/get/ivLuv8LU5ejnXHAQ715z1qux6gB0r9Ma6Biba2p4pLSUzTU1wW0319SEpXbsT3/605D3Cb3e3mrYmtxu1pw6FdxmJHVpoceU6tN6fd5jaUwbagB8ERnO2slEDv2tX3p6OqmpqT0aCiQ7pMbGRk6dOkV9fT1TpkwhKipKNsaNEOTUp8zERhTJUygQRXWg60mhROsV+XXWHZxqclDsqeNnba1cCeTUf0rZuxuYdfl/8qq9hqvb21l7+jQ3l7/LNdbDtM9fghXQVLwdPHye6zzrq//OGV0KSqcXk8+BF6GLR5uy3UbHPx/lf4ueZFXxz4gpfRe334/m9mdBb+p33uSw0qIOC98u344ubSmrBpFelM7n8PnGLH0a+pxD05rS9w6fjx1WKyu62WaMhH7r08ba4yyC0qEyEwNBEDAajcTGxlJVVYXL5eoSMZO+tlqtNDc3o9frUSgU+P1+ObI2xshCTSbi0Ol0A280BIJ/ZDo/HWYqBFytjSTqEtjd0sIH+nyubD7OYeMcHLFTmPvBQ1SnXc2G/Jto9noxix4ey1pFU3QBT1S8jF2lJ9brYIazGiA43aBOFYcfuog0gA4UaK3nuOofDxLjquGcNpn8kl04Pvgf2q/8Lsf2PsvsRfdjUmvgyEuY564OCgYpLQqDEE+SuHA0of/o16xb0g4Fc7ps0uR2s7mmBqfPx4asLNalpweFYpPbHbSnkLYdTnoxLi5u0NtKhIrV3kTbhqysYNQxXKnOfuvTxrrAf4ymFwxn7WQih8Gsn1qtJicnB5vNRm1tba/D2kVRpK2tDUEQgn8/JdEmc/GRhZpMxHHVVVeNynGlIL7a5+L/tZ/jfvVclsTHs3fmPbyVmEVp1rVYDm9D9Hq5+sgvubp6Dx/q83i0YhtvGuejOXYSve0oruhk8DrQ4OecNokmdRxmr5389vpez6vFT7tCywxXDTsT5hCHn/yOehqrDnHG+wzLD/2KnX4/y41GeOcnFNtszLr+h5g9dtaUvMKnMQu5xdRHVCc08iOJi9yibs/4Alvq6ni8ogKAjbm5XURP98he94L9wQq3VatW9fnYYOhLtIWzFq37c1nfva5nkka0Rrp2MmPLYNdPEAQMBgMxMTFUV1fjdDp7jZp1F2lqdaDsw+v1dnlcZnSRhZpMxPHRRx+NmlgD8KtjmFOwnA2aQORuXfpMzJprcXzwJPqKbexMmMPbCXO4oekAPq+bD+JmcrP1EL9Pv4mdgMnrYD71vB83k7O6VO6v38XWlOvxO0opsJcAdDHCBYjqrF87EpOLa85XUO3/OW3xUzmSdjXvNDeTmH8ryzOzKLbZWKmex6N1dayv+jtJu/+TjNw1vGyecsGM1WPvKc7ggqiYchUoNTBrZY/nvjYlBYfPBwQiSZsqK/sUQd27Mwfbablt27aw3fCHMw5qMISmPbcWFvZ8/hE8j3M0CefayVx8hrp+arWa7OxsWlpaOH/+fHAsX3ekSJrP5wuKPJVKhd1up729HUEQ5GjbKCILNZmIo7sh42ig8PiYcuz3PBp3FQfs9sDNev4a3KXFLC/fTXH8TN4zzGF581H2mQOjp4RoI6eVWr5b+TcAcr02plsD46dubdjDG6YFJLedJ1rsQE3XP1qtCh1xfhfLW05g3P8f+FtquKzxEEl1n7InfjrpJ/7MOfP3KJ7xddbRKY5Mq3H4fGSlLMXZ3kzDgRf57vSVPOc6iP69xwMHDo38SOJi71NwdidkL4bEnmJDEnwDiZX+aueg79Roa2vrMFfl4rE2JSVYm7alri5yatPGmPGwdjJ9M5z1EwSBhIQE1Go1FRUV/UbJJDHW3NwMgMFgICMjg/b2dmw2WzBdKou28CILNZlJidrv42ulf8M6xcMjmrjgzVqTdSWU76ao5QTF8TP5Z9YKrrYc4WBMPuk+B9Pq9wLQptCS5ayho7NxOsHv4uuNH/Q4j59Aa3WcPyA+59rPgP3C4zOaTzCj+QQA+xuP8efMr/Oo6xiKqK9D6Tvo569hnd4UiPaVbuVN23H+vPAhrsu4GkPu9Rh7i/z0k7brXqgvDSLfXFPDYzk5/b5mA6VGxxNmjYathYVd7D6Asa9Nk5G5yPj9fhwOB9bOhprB0L3xIDY2luTkZDIzM3E6nbS0tNDa2oqvM3ovp0hHhuyjJhNxhMNHbSCcfj8l5z9i6pzlvO9RXYgKOSzw6r1QWgyAXWsgtqO5y76f69L5w6zv8v3P/oesjkaaFdH8NfEqLrefYabfyembXyf7n6vQtJ1Hgw83ClzKKOJ9TgAq1EYS/O3B71uU0QgIxPkcHEycz2WNh2iImUJSWxXnUhaiWLGJxv0vMK96NxpbGY2xU0i0V7F12hpuuuMXF6JZg4gGnXY4eLikhCfz8jCp1dz9+efsstnYkJU1oFDrTl8RtfHgxdVnvd0kj6iNh7WT6ZvBrp8kzpqbm7Hb7T2iYKFNBKE/683aI3S7goICNBoNoiji8/no6OjA6XTS2NgoR9kGgeyjJjNuKCkpGfVzRCsUNCUu4GeVlcw5+jyCs3POot4Ed7wAS37A3rkPcsfU71GqS+OcLjAt4Uh0JkfSFrPS+Tl6XyBK5lUo+VHeGlyqaJTuQOqh/MZtqJQqfAho8BPvc+LUJgBwIHs5TbO/wnHDTNrUscT7nMT5HADYzTN4O2EOSW1VAOTX7aPy799j4fEX0djKcGoTSLQHHitr7+jqkzYI7603LBZ2WK28YbGwpa6OXTYbK4xG1qWnD/k17GuO51O7doVtjudo0OR2c/fnnwe947ogRSgnoUgDOHDgwFhfgswI6G/9/H4/drudyspKTp48SVVVFa2trUEfNYVCgSAIxMTE9BoBU6lUpKSkkJSUhNlsxmg0kpCQQFxcHNHR0URFRVFaWsrnn3/OiRMnOH36NOXl5Wi1WvLz81Gr1bIv2zCRhZpMxFFbW3tRznOlRkPu6b+x/NCv+KD4t9z02Wd8YrOxyeLg9OXf4505D1CWcRV5C5/G2CnAZjmr+UrJKyw68UfM3jbaFFoSvXZePPUrYvCj8LuZuX0xGfs2IPi9KDutOqr06XTc9TI753+fY26RvCPPodMbifHY8cZnUW2cwbmkS9lmvKJLr+Y5XSrHotKC30d32KhMnMOemV+nKCGeb6jbYOe/wx9vCzQRSAatDgvsfQqLrfaCmWunv9pv0gzcYjLh6LTo6LWYfphsqauj4ty5LgIy3EPYR0KT283KEyfYZbON9aVEJGfOnBnrS5AZAd3Xz+/309raOqA40+v1pKenM336dDIyMnoVVF6vl7q6OhoaGmhqasJisdDc3ExraytOp5P29na8Xm8wciZF26qqqnA6neTn56PT6WSxNgzkGjWZSYtGEHgv4wusB3Ybr+aA1UpJUxVfrH6bx6av5J1mG1tdB/nX2IWURSVhdJSh6tYkcDoqFYsmnputhyiPSgZAQCShahdeAr9gDoWGl29+iUdyL+UjIZXfnj1GeoyB59W5PN3hYlruQio6/Cw68jRf9Aostx1lZ8IczGo1lzYeREhfys6EOSy3HQUgrbWMNGc9KkcdvlMvQ0dARDodVjRuO0erPqfQPAX9nk0cs9l4RL8EgPVVf0f/3uOsu17JY+o4Np89xp87DmFO+h5owhNBWpuSwtNabZe6r0iqZdtSV8fulhYAcrTarpHESZ72lJkY+P1+2trasNlsPdKaoigGhZJOp8NgMBAXF4dSeaFH3e1295r67KsjdCBEUaSmpobU1FRycnKoqanpdZSVTN/IQk0m4pg1a9aoHFf6AyUIQuCTnU7HbdHR+HIK+bXBEJhCcPpvbCrdSlWigdryT7i8/hMWLPl3Pkycw3xHGS2KKOL97cEmgfnOcjYav4RG9FLUcgKXoEInBjyGbKpYVKKPyuh0VuoDfwjXpadj9rRye9lhLjv3Cpc2HoLGg3jmPMDPp93HC3GXUpWyAPvswIipaY3F3H3J3TxfW4vl4DMsrdhBUkdrUJwpOy50eWnqj6IC5jeXsnfugyy6/qfMnnknG1s9wS5SICBEGlpZW7eL5aVbwWgMW+G8WaPhK1/4QpcI3WC7RS8Ga1NSeMtiYXdLC5lRUV0flBsJWLp06VhfgswwkMTZrFmzOHnyZJ/iLCoqKijOVKreb/9SA0A4EUWR2tpafD4f6enpKBQKmpubZbE2SGShJhNxhOsPhUKhQBRFlEol0dHR6HQ6PB4PCQkJwRD8j0O2/3DePLYZomiYMoXd9dWsrv+Ekoyrybv8Xu7g91AONnUs8R3tKLjQ0Znqa2NWW8BEVhJpAGavnTaFlkvsZznz9o/YdMPT3BunZt2B/4SzOzEDe4zzaEmbzxr9Yu6dPYOpTifX5d3GGxYLj5SWIuSuZH1CKo8kpPJY1A/ZYFzC25XPM6WtGpWjq8Gu9MtcnTiHwqKHICEVVUsLX2itoq61lRadjrxOAbIuPZYXFtzDToOB+TPvxARhiyhJZpjB16GfblHJJuRiiTazRsPvCwq47fhxdre0dLXmmKQmt6F0XzuZyEUSZ83NzUFbjLa2NuLi4rqIM41Gg8FgID4+PmhY2x+j9R4QRZGGhgb8fj9er1cWaUNAFmoyEcfJkydJS0sbeMNeEAQBtVqNVqvFbg/4YOTn56NSqTh37hzt7e3BNvTp06d3CfmbNRrWFcxhU5SBJzxHcM6MwpZ7PXPf+zWXXXYXRo0eMXEup1//HnmOiuCoqCLbMcy+NgA6ENCGjJCK8XdQokvl7ZnfwPHuf9HqLsdU+wmfJl7G69F5/Db9ZuYlZbIuPh6ArYWFADS63SyJj6fR7abJ7cbi8fB+czNpaTOwXPocyte+SaajHgQliBeEba0uGd1XX8GUEGh+UKlUxMTEIOh0vNDaSvGnnzJbr8es0eBUx3FD7LVsaG7nsQR6mucOU7Tt3r2badOm9fn4QHM9bzGZeMNi6VW8SSOwAO5OSupzu/54w2LhlMvVc27oJDW5DWWgtZMZW3oTZ6GRs1OnTpGeno5arQ6KM80QPwD5fL5RE1GiKNLU1CSLtCEiCzWZCYVWqyUvLw+r1YrdbsdsNgfFWGZmZvDTolRI2xuBm/dczvtmIxb/jOUVr/C+18WBwlXMPf06SVHxqByBPzRtqGgRlUwBHCjQ07MFfbvpCr504nkKavYAsD/5ClbkfYe42ERmRUXxdLqR6v1bWKmeh77zWjdVB+aI7m5p4YTTidvv54NOM8sTp7ZwWf3BwME7RVpVQgHejjZWTfs+K1s9rE8IPKzX69Hr9WyqrOSnnQJHOs41IXMBm9xutiUWsfa6Dei7TzwoWAE7fwTL/xsSpw5lOXploLmekhGtw+e7MI2h82YTOgLrgN3ec5j6IOhzLJVcoyYTwZw/f57m5uYe4gwCH1BVKhUqlYr8/PwR2Rt5PJ5RFVKySBs6slCTiTgyMjKGtZ8gCKSlpSEIAiaTCVO3+ZgajWZQny5Dh5QfT0iACvD4/TQeeJHlpVs5a7xQQxeDl1ntAQHUXaS5gUatiTtc58i3HIPca3krOo81cUvQx5gp6+jg6ykp1O/9HUVHnub1uQ8yLeVGbC11NFT+jddNC7nVso8t7mWsyprGWZeLio4OEkJrSzIup9Ljp8Tl4lrXee73lnFzL3NB16akIDaeYdG+jfz71PsoViexMC6Om81m1qaksLmmhsfPN9OU9SUe05u6pgElXzmfG77++oCv38yZMwfcpvtrLV0jXBiS7vD5ejQhhI7AujspiaKEhAFHYfWFxePpmnaVa9SGtHYyF5eozppKSaQJgoBSqSQhIYGEhASioqJoamoasQelnP6OPGShJhNxTJkyZVj7xcTEEB0dPeB2UmGrXq8nNja2z8iaWaOhaPmjkJTOEePVbKmqZoYKZtfvD27jFNQoRR/aTpEm1a0BaID0Dgt0WGjLXco3p3+fEw4Hayv/wduZX2CFMR2nz8fOZiuLANHj4NP/+39MqdzNppbTPFT1BhmeZqY6aph9rg1D+nJWn/wDZxLnsm/WPcxKSESvVJK5++ekRCdTNu/fuDLvVhpLS/irRuT6jHxebmgAAk0Mj5z6PTTs41+9XlTXPMkj3TzQJJrcbrZYHKxd8GBgrqjXE3gg+ZJBrcNwm0FCRdt6vZ4mtzsYUQttQAg15l3fGS0cSs1b98gddApBuUZt1Bp5ZEaO0WhEr9dz/vx5oqKiguIs1O4iHOvn8XhGfAyZ8CILNZmI4+OPPx5y95mUDggtou0Lp9NJc3MzNpsNURSJjY3FYDAEarm676s3YZl5JzN3P82CxCVUNSpZ23ISgCZlTLA2TaI3yXcmcR6rsx+gtNnGK2d+zdKmA9zWdopb89exYOpsoq/4Fs/GGDjfZuOxij8G98vwBCYi3GbZR5LXzmWNB1GLXqZV1bKneRp7c6+lOe9WCm66Ao02oTOlEGhzsHz8DA9f+mBQiOiVStZf/QgNtScpi0pmkcqDWaMJCqC7k5J6zADVtTcHGh8q98LU5bD4+4Nai1deeYX7779/UNv2R6hwCxVj3dOcfdW89ZYObXK7g/5xUkSuS53aJCdcayczOmi1WnL6mSASjvWTI2qRhyzUZCYEoijidDqpqakhPT29X7EmGT5KtRKtra20tQUEV1xcHEajsYsx46EPn+Gmw09RnGvj1ynLWFy/j+taT+BUaKhUmsh0W7oc3wdILQoV2kSumvowFr+Wxxr+ydKmA1TGZLKoYR9b069gY3MGCe4WClwuatMW8aHfgVmpJKv8TaLxYlHG8Pri/+JLBzdhbqtCRKA9oYDsvC/RMmUZiShR6+LoUvUh+lnmKOGmxBgWxMYCARHTsPcVktqq+G5bFTvLCmgqmMOaU6d61HkFhU/59sBw96nL4bZnxrRuayCLj95q3nqzAZFq3Dbm5jJNr2d96LgdOfUpIzMq9hwyI0MWajIRR0xMzLD2E0WRlpYWNBoNSUlJfW4ndYOGItV92Gw2WltbUSgUwW7RI/m38k5zM1tSluHWxrPXMJvrWk+Q6bFiVfacq6cM+bpEG7gOg1LJnwyXscx0mE+1qcSlX8sf9bMpOvoMN2UsRH/J1xAVahRJ0/CponB0nCe6dj+22av4ZtEavDTRVH0KS/6X8UYZEBVqUKjordleRGSh7XP2fPq/3F30b9x/+jTFNhvxusuYm3UXeoWC26/4Blvq6thhtfbofjRrNKw36aGkA8fi9WzJ/CKr1LGYB7cMGI3GQW45eAY7EL6vKFxoR6n0vYQk6O6VbEomcepzNNZO5uIRjvWThVrkIQs1mYhj4cKFw95XFEUaGxvRaDQkJCT0eNzr9Q5YgyGJtvb2dmJiYrg3bxabfV/jv09u57qi7/AHwzfY6OvgK017yWhv6PUYbhScVxu4rvUE36l5k5/mfIUftn7KIsthFnGYJzJu43cVPybZPJ2axEsQVbrAuRUqlP4OEm//HeKZHSQVrKS8vByH+QYwLkVUDPwr6xVU7L10HbOvXMO6zw9RdPwlBAQ+LVzFvszlrDvxO4pry1hbeCVwofsx1PpifdXf0e/+OQcWPMx3zzfjiqobdGflypUrB7XdSOgeYRtomx7CzmGB4l9B3We8NvdhHrGK6NIMrBv1K49sLsbayYweI10/abSUTGQhCzWZiGPPnj0sXrx42PtLI0skD7FQJO+hgVrERVHE3Tmb0qzR8FjLR3DiGUhLQxd/FQ6lBsHXdy2HBj/ZnkBKNKPdQuX+bxOTezXb0pZzedNhvln7Dkafg1NzngmKNAmFNoY6XyxWw/XQ2HLhD+cgRBqAWqHgyqUP0wqsPv80N1W8AkDFlBxSaw+gsR7izL6NKBI3sf7DDVive5xNnhgcPl/Q+sKctpR11yu7TjboZKDJAi+99BKrV49uVKp7hG2gbXoIuyMvwUe/Dvys9jNm593CLG8i7NkUeHySpj4vxtrJjB4jXT9ZpEUmslCTiTg6OjpGfAxRFKmsrCQ3NzfY1g6BerTB/DESRbHrdXSmw6y51/PFvz7AfOtnve4XWp92JDoTq9bItbZjTOmoh+PbuFpjIr2zpq1BGYO9rZzo6MQuwtHr9dLU1DS0JxyColOIbj5/ns26y/hJ3mqsXi/R6cvRmReyoK2NhxJvYce2r0BLGa2OVhqippG44B42ZGUBcH1SEpuiDKyNNrE+oasYG6hg3+l0Dvvah8tA4rGHsJu7GhxNcPgllC4rC4+/CEt+cGGo/SRlLNZOJnyMdP28Xu+gPsjKXFxkoSYzYfH7/ZSUlKDVaoNmkFKUbDC4XK4L33S61n/290co6hRpLQod8X5Xl31aBR0a0YMeL9F+N3Obj/Dr1BU8UP8OWr+HKEHFmeV/xqeKxhZlIFatRexWExKOP5LSMSyaOB6a8mWujItjeZSBR+tbYfoP+X3jPzC1lIExlzSlgk2lW3FkZ6O/5mHgQn1Xsc3Gk3l5XSYADCbteLEZ8uB3vQmW/wfM+zr8Yz2Y8gI/l81uZSYxPp9PFmoRiCzUZCKOJUuWhO1YoijS3t4e/L6vQcS90ZuoEx0XOjybYjOIbjnbpaDfIAaEW5ugYX3BtyhoK2NLyjJu9NZS0HiYsigzUTEZoFASCzBKA5AFQWBdejq/rKqi1e+nsr2ddenp7G1pYZfNhm3WXZCWBm4Hmt1PgHkq+ulf5LTDwcMlJfw4M5MVRmOwIzS0M7R7dKp7NOuee+4J+3MaiGGLx8Sp8PXXYO9TgY5PTfSkTXsCY7J2MuFjpOun0WhkkRaB9O70KSMzhpw6dWrUju31evs0uO1t2+5/tDJq9wGBFGdeN5EWSozo5irrkeD3K3Pu51DylRxPvhJBHL2uKkEQMBgMaLVazBpNcIqBkkD67+UZM9iYm8u9ebMCguTyBwL2G01n4cwOHi4pYYfVyi3Hj/PjzEw25ubyZF4eG7KyaHS7eaysjKZuAlaKZm2pqwPggw8+GLXn1xeSeBz2YPe5qyd92hPGZu1kwsdI10+lUmE0Ggf0opS5uMgRNZmIo76+ftQc0ocS1pe2Df7RcljIcVQBXS04uiNNJ1hoP0tRywkAfpF5O4tm/JAflm1jUVs1HbGZg24OGApqtZrU1NTg96/MmMHa06fZ0jlou0etlt4U8EjrnHH5JFEcaG2l0evlPyor2VpYyOaaGt5vbg7OCHX6fCR2pkB7S4WWdqYgxxXyQHZgnK6dTJBwrF9SUhLNzQGzbTm6FhnIETWZSYUoiqjVfcXBuqLX67tG3468FPxkI7UjeAAvcCBmKlKcSdpjiuDjZ9l3878pywDoEEV+k/YF2P8zFN6utW3hwuPxUFVVFfRCuiIhgZMLF3JFL1YlQSSRojcxjXaOez5mlV7BjzMzufvzz3m8oiIo0gBe6BZBC41mNbnd1LvdPaJuMjIy4wOlUsm0adNISUlBo9HI0bUIQBZqMhHHJZcMbqbkcBlM+lOhUGAwGIAQb6G5qyk1TA88TsArTU0gLH1J2zk0BASclNjMs51ivu1z/qXyVZ449yIbyl4mTiHwxKzvkLj/PxC87T1PPEJEUcRut3PmzBkaGxvp6OgY2qfiIy+RtPs/edl9mA9bW9llswFwZUwM18TFkaPVYvF6KdTpgu7/myorg8JsS10dz2dksKWursdjMpHPDTfcMNaXIDMCwrV+SqUSk8lEQUEBubm5QU9KWbSNDXLqUybiCC3+Hw38fv+Af3CkGaBer5fS0lIMah+JH/4AY/uFZgKnNgFNh5UOlIiIgNjlk0+boGG57SjLbUeDP9P52omLSyaxbi/1p7chTLurh4/aSBFFEZ/PR0NDAw0NDSiVSuLi4oiPjyc6Orrv5954Fs68DVmLoGAFa+NTcIQ0OzxeUcH6jAxOOJ38ODOTLXV1Qe+1YpuNrYWFrE1Jwds5P3PInZgyY05vUztkxg+jsX46nY6YmBhaWlpITEyktbV16B8AZUaEHFGTiTjOnDkzqscXBAFNt6Lz7uIlJiYGv99PaWkpbrcb77G/QWkxCa4LkwiU3g6qdSlo8RHFBW+2DpS4Y1LZsewpzi74Hr9LXYFFERg1dbflY3YlXcn63DXcHjMPReORUYmsAcF5pl6vF6vVSkVFBZ9//jkVFRW0tLT0HBWz80dQsTfwb+ePMLdU8Fj5Nh4rf5nVMUqWxMezr7WVH2dm8h+d9h17W1pYlpDADquVLXV1mDUaTGfOYNZouMVkYkl8PG82NXHa4RiV5ygTXj766KOxvgSZETAa6yeKIufPn0cURaxWKzk5OeTn52MymVAoFINuzpIZPnJETWbSIQkYhUIRNL+VhrBLhpFxcXFBkQbgE5Sg1ILOgNfvQ+VsJNbn4HRMIRmuuuCx/YAWH6U+gZMaM39Iv4P/396dh8ly1veh/77V+77M9PRMT8++nHN0jhASQlhiEQoBDMIGAkbm4sTA9WM7iXITxw557CQ2xM8Tx+Ab3xvzXC9XwfINGJSLrlnNRdiWDwgJHXRAC5LOMvu+9Ezve1e9+aOn6vTsvVR1Vff8Ps8zj870dFe9Mz919a/e5fe+dudz6JGqicpwfhPvXPlb3ISAss2LnysxfKmwAzj7AeGkJQqtk3/XdDqNbDYLzjn8fj8ikUg1UX3HfwLEEiCWq5uxA8p/V3JlXHZVy6Z87Pp1XMvncd7hwN8kEvidkRG848B+oQDwxa0tXE4mAQD/enYW39R4SJsQoj7GGAYHB7G1tYVisYjFxUWEQiFYLBZMTk6iUCggFospdSdP6mmTkzr5GkzqQ4kaMZyRver4WiqVSvt60ex2OyKRCHK5HHZ3d7G1tbVvT1DJGQLEIpDZgBlAwhlG0tWPaGgCS+llDO/t+SnfW47n1/CRv3kYf/S6P8BC9J14d+w5PJB6GU96LyItifjM3H8HUF0N+s3Zr+Nnbvs5SEJzm9E3o3YT+nw+j5GREVhCU8A/+Wp1H8znPw9MvxuI3AWAY3jiQfxfP/hLfGvop/GRkRH8+4UF3Of14qG+Pny4rw9f27k1JHzHHXcAqK4OBYAxmw3/ZWKibb8baZ4cO9KZtIqfz+eDz+dDLpdDPB5HKpVCPB7HxsYGHA4HAoEABgYGkEqlsLu7qyRi8uItm80Gh8MBm80Gi8WCxcVFStQaQIkaMZxwOKz5OQRBgNVqVbaJkgvhOp1ObG5uHtq4XTQ7q/9gAsAl+HOb8Oc2ge3q/LMKDr+ZJoub+PTsX+ATE7+I8l4pjh/2vAaP9LwJ5xLX8dWeN+BetxtXJn8Gv7jyLewMvUf1+WqnkQsC37x5EyMjI3C5XPtLVTzwm0B2B/yLv4h/uvI9WAWGRxwBzBQKmCkUcL/Pp5TuyIoiPrk3LAIATlO1h/CDoVB1ZwOLpfk6Z6Qt5NiRzqR1/JxOJ5xOJzKZDCRJQqlUQrlcxvr6unL+vr4+FAoFmEwmWCyWI+fEWiwWVbYKPCtocJkYzpUrVzQ/hyRJsFgsGBoawsTEBEKhkPIzm8126OIi9d0G9E4B7/9vEO3+Q8c77o7noc3L+EzsO3hH4gU8GboHnx54Nz6WvIp3pW/gDyvX8fXJQXy58gKy0x8CN9lU/A0bI0kSFhYWEIvFDt/pPv95TKx8Dy/03IGhlafxpvIWAntJ2OVkcl/pDgB4/PHHAQAPDw7i0+PjcJpM+8p5EOOSY0c6U7vi53a7lWvn+fPncdttt+H8+fPKtdPhcBxb2qNUKjW0lR+hHjVyhuVyOQwPDx+6mMgFY+PxuJK0SGYn8PBzAADTxo+Ap//o0PGK3mF8I3gXzsdewsXMLADAhTLet/odPHvuQ8hZvLjf58WHhj+AV2//KC4KJTie/H3EkzEUvPcDTN+3I+ccm5ubyGazGBoaujVJeK9a/4Wbf4M7Fr6L0ef/T3xy6t8AAO71evEmrxdOkwkPDw7uO55cXy1WKsFlMhlqb1BCSH1isZgyd7d2SFO+Ntb+96THjvqe1IcSNWI4Pp+vLeeRJAnFYhF2u33f44wxRCIRmM1mbG9vH764vPHXgBcfBzJrEAU7iiYzzD2TsG08D5s5hPdf+HVcvfob8EjVi1sgu47JjR/iDcl5uBxeDC5vYHby48jAhuzYR8BNVoBpu5CgXpxzZDIZzMzMYGRkBDabTRkKtU6/u7oa9B98Cm9ZL+C7qRTW9oYvPtzXp+z32dfXt++Yh3ZDIIZ1MHaks2gRv2QyqSwUIPqgoU9iOHfffXdbzsM5x+LiIiqVypE/7+vrU3rX5Mn3AKqJy+0fBACYoq+Ds5yB9dxP49XIm/Ce3av4WPIqeN955el5swv5N30CV8I/heHb3wfzm38NECwAE6pz0gySpMk45yiVSpidnUWqdlgzNAV85P9FcOA2PLBXDHixWMRnVlbw8M2byvDm+973Pn0aTlpGsetsWsTv4I0saT9K1IjhXL58uW3nKpfLmJ+fP1xTbE8wGMTQ0BAcjgOT/N/0r6qbeP/DT1U3Nb/0QXz9zb+LT0ffjwdW/x6IzyuV1RyVLJzf/T3cs/kDrP/oizD1TYFrsM+n2iRJwvLyMjY2Ng4NVzw8OIh/PjAA/95ctawk4XdGRvCx/n48+uijOrSWqIFi19m0iJ/dbqcdCXRGiRoxnON6uLRSKpWwsLCwv9eshs/nO75kyOx3qrXGbvw1Pj5xCa8vruKnsrPwFuPKmytvciCYXgIAnLdUh1ZNJmP1oh2Hc46dnZ1DyWyv1YoRhwOJvceeSaWUchzLmQxtG9WhaJJ3Z9MifkctriLtRYkaOfPkEhVLS0v1T3R9/vPAd34bAAPu/7dAKYdgKYXh9/wBEubqLgRyWlO0uJSXLaTjANAxiRpQ/fvkcjncvHlTKZQLAB/r78fvjIxgxFZdrfpsKoXPrq5ipVjEZ1dX9WwyIUQlVquVFgDozPjjL+TMeeCBB9p+Ts45stksVlZWEI1GT7+D3FsJib0J9rj5BDZ5L8xDb8ST0bfjzvXvI1hKw8sL2HGEIApm9OQ2cD55E0C1blun9V5UKhWlUKXdbofb7cZvhEIoVSr4vdVV3O5y4fvJJP7urrvwH/RuLGnKL/3SL+ndBNICLeJnsVgoUdMZ9agRw3nppZd0OS/nHKlUCuvr66dfmOSisDf+ujr06exF0jOJdL6Mn115AqPFbXh5dQ/PuATkXdUivqnECv7+rz4BCe0d3lWLJEngnCOfz2N7extLS0v4X4pF/CAUwts5hymXw8Orq4dKdZDO8MQTT+jdBNICLeLHGIPFYlH9uKR+lKgRw4nFYrqdm3OOeDyOeDxe3wte+wvA1DtQNDkhWr1ggoBn7/0knvKcU55yd/JV9FksSJndGMhv4q0v/Cli85e7Yt6HPK/PxTkmKhX8nteL8d1dbM/OYnFxETs7OygUCnRH3iGWlpb0bgJpgVbxs9KOIrqiRI2QA+Qeo7q4eoD3/QkK594PJlXAwWD3X8DHz/9L1C5NsK49B28lo3zfM/NlWM2dM0+tXhYA4ByiKCKdTmNjYwNzc3N45ZVXMDc3h62tLWSz2WMXbjSiWCweu1qXEKIeKtGhL5qjRgznzjvv1LsJt6ry18PVA/db/gX4YnW/O5vZha/HvomZ/nsxvfHM3pMYYp4h9KaXkBScmFr/AeJr/z/W+t7edb1NtfGrLRacy+WQy+UgCAIkSYLVaoXb7Ybb7YbT6VT2WwWqq9dSqRTy+TwikQhMJhM45ygWi0gkEkgkEhBFEWazGRMTE/teS5r34IMP6t0E0gKt4ieX6Oi2a1WnoKsbMZx0Oo1gMKhrGxodljR5Q3C6M8hmswATELD24Pn4CpyhOxDdfgEARzC9AgDw7e1YkL76OYQ+/D5sJ7JddQE8LX5yb1qpVMLu7i4SiQQ45zCZTHA4HCgWiyiXy8rzy+UyPB4PdnZ2IIrivr9VuVzG7OwsxsfHaR6NCra3tzFI8ws7llbxk0t0dNN1qpPQ0CcxnJmZGb2b0FiP2p5AIABBEMAFC3bPPYS3J15An90FhF8DmOwQsH+4bziziNDffwJWs6kr5qvJGo2fvEChUqkgnU6jVCrt208wl8thc3MTlUrlyA+KcrmMubm5fckdac6VK1f0bgJpgVbxoxId+qJEjZAjNJM4eb1e5WIm2vyYnfwArMtPA5svVncyeP0vQTLfmushAmA3v42Jr70XPZZSVyVrWmCMHfs3qlQqSCaTbW4RIWcDTS3QFyVqxHDGxsb0bkJTSZMgCHC73QAAkQPX+/fqwXmjQCkHvPW3IPzKUyibnQAASagWihWyG+j/xkcwOTkJl8vV8QmbVvHjnCu9lrUYY+jp6UFPT48m5z1LXve61+ndBNICLeNHUwv0Q4kaMRy9P3AZY00NfQK3hj8FAEOhi+DMBKRWgGf+K/CVXwUAWHomqv+VirdemIvDZrNhbGwMQ0NDMJvNHZuwaRE/QRBgNpvhdDr3Pc4YQ39/P/r7+zv272Uk0WhU7yaQFmgZP1r5qR9K1IjhPPfcc3o3oekPfbfbrQx/SiYL/uT2X8ezlz4KjD9QLYz7rd8ANo8o6CuVgewOgOoQ6vT0NHp7ezsy+dAifhaLBefOnYPT6dw3V0buTSPq+OpXv6p3E0gLtIwf9ajphxI1Qg44aS7UaQRBgMfjAQCYwfDa8++H7+3/EZ/9qU8he9fHgbUfH/1CqVzdP7TmOOFwGFNTU10xHNoqeYXowZ7OTtozlRBCmkGJGjGcQCCgdxNaSoxq51F5JAn55WX8xXYGhdkngcIRE95dYSB6D5CNKb1qMqvVirGxMQwPD8NsNjc9JNtOWsSPc46NjQ0UCoV9jx+8y5dXjtLCguZEIhG9m0BaoGX8aNWnfli3/vEvXrzIH3vsMb2bQTqQIAiIRqPwer1NvZ5zjldffXVf9f0KgLXSDt7+vV+DxeIEtvaGP4PjwO0/B1z+/er3428F3vUHwE++DIADl36uup/oa38BkiOATCaDdDqNTCaDSqUCxpgqVf47hclk2rcbgdfrxfDwMABgdXUViURC6RG9cOGCXs0kpOusrq7Wv7Ueacrtt99+lXN+98HHjX97Ts6cv/u7v9O7CS31qDHGDiV5ZgC9liCefscXIE69/dYPht4I3PMr1TlsADD398BjHwYu/+dq8vanbwa+89vA//jHEC7/PrymMmyhEL5oteJzJhMeKZfB3G5YLJaWFkGoScv4iaIIm82m/J61PWpy/TVJkgzxd+hEjzzyiN5NIC3QMn7d2qnTCag4CjGcbrggeDwepFKpfb1dTsbgFEVc73sQY/5vwpG4DiRmq/uFfuC/AVf+FFi+Asw9We1ZW38RyO9WX7z4/eqX1YnPRn4Wn1pcVI779XweHwmH8c+Gh2ErlZBOp5HNZnXrcdM6fqVSCYFAAOl0GjabTXnc6XSiUChAFEWa+Nyks9Q7240oft2JEjViOHpPnJckCevr63C5XE33zBxXRR8AJJMdMw/8MSIv/BGC/UNgQDVZe+C3qnPUnv888NpfAHbmgK/8MnLRe/GSZMGEJ4gvhd6K3N7Q371uN7YrFcwUCvjU4iIe29rCVy5dwrm9JfqVSgXZbLbtiZvW8eOcIx6PY3R0dF+5jnA4jHA4TB9WLaCeyM6mZfy64Qa6U9EcNUKOwBhDIBBoenLu+vo6dnZ2TnwO4xXYnE58zWzDg729+NrODj7W349eqxWxUgl/vrGBj/X34883NvCJuTm8OxjEX+/u4ndGRuAymfCx/n4AwGdXV/H/bGxgvljEvW43AlYr/svEBM65XPvOp1fipgW5fhqV5iCkPZaXl2mRjsaOm6NGPWrEcH70ox/hrrvu0rUNcq+N1+tVdhuoV7lcRjqdPv0czIxsvoTbxDyeSKWwls/j6UIBr/d48MN0GluJBJ4pFPAhrxfmsTG8u7cXb/X7lWRO9smxMeREEZ9ZWcFCsYhnMhn8JJPB1bvv3vc8s9kMn88Hn88HoJq4pVIpbG5uKvttqqEd8WOMwVrzuxF1fOMb38B73vMevZtBmqRl/Lq1U6cTUKJGDMcoK4s451heXsbU1FTde90lEgmsra3V3UtlAhA1mRAF8IDTCZRK2NnZwTiA8b3vMzs7eAcAl8mE/y0chu2IBOUTeysf/+vqKgBgaa9H7tejUVQqFYiiqPzXbDbD4XDAbDYjGAzC7/djc3MTu7u7qlyM2xU/i8UCSZKQy+WQzWYhiiKVl2jR2tqa3k0gLdAyfpSo6YcSNUJOIIoilpeXMTo6eurcq6WlJaTTadUvaPLxEokEkskkHA6HMuRXqVSUr7vzefy51wu/IMDHGLypFF555ZUjC/hKkgSr1Qq32w23241QKIRgMIi1tTXkcrm2X5QFQQDnHGazGaIonproSpIEi8WC1dVVpFIpcM5hMpkoUSOEdB1K1Ijh3H33oSF6XeVyOayvr6O/v//Yybqcc2QyGc0THM45crmcUviVc66c8zbGgCNWO9Y+p5Zc7T+RSCiJTiAQQDAYxPr6OkRRbOr3aTR+jDEMDg7C4/FAkiRcv369rteYTKZ9Q7b19nqS4733ve/VuwmkBVrGj3rU9ENLfIjhnDYJv93k+WrXr19XkpqDGGOHNgzXkiRJqs0rk49TqVQQi8WwsbGBoaEhhEKhplZwNho/xhjsdruy8Xo9K9eOSsqoJEfrVlZW9G4CaYGW8aNETT+UqBHDmZ+f17sJh3DOIYoiVldXMTs7i3w+f+g5brdb99IireKco1wuY2FhAeVyGRMTE/B6vQ39Xs3Er/ZD4LS/41EFhQHsq6lGmnP16lW9m0BaQPHrTjRWQEgDOOcoFAqYm5uD1+tFIBCAyWSCyWSCw+EAY8xwd57yECFQ/10x5xyJRAKpVAqDg4Po6enB6uqqUh9Oq3l4ADA4OAjO+aH5fnKC1tfXdygpo1WghGjLaNe1s4QSNWI4k5OTejfhVJxzJJNJpQyHfBEz2sWMMQafz4eenh4kk0kkEgmUy2UAp7dV7kVcXl6G2+3G2NgYyuUycrkcMpkM8vk8JEk6VIutmfjVvl4QBAwNDSEej2N9fR2ccwQCAfT19R0a3nS73chkMmCM0dCnCu655x69m0BaoGX8jHZtO0soUSOG4/F49G5C3YxeLFaeXycnOn19fSiVSkilUojH4yiVSsrzTjpGOp3G2toaRkZG4HQ60dvbC6C66jSXyyklMgqFArxe74mLLmr/KwgCBEGAyWTa95xisQhJkmC321EoFJBIJJThTrPZrAyNBoNBbG9vo1KpUKKmglAopHcTSAsoft2JEjViOD/+8Y/xtre9Te9mdA3OOVZWVjA5OakMEfb29qK3txflchmpVAqJRGLfStKjyKtaa+ePmc1meL1eJYninOPP/uzP8NBDDymbxB/3VXuc0l79uHQ6jVwupxyrti1LS0vgnMPtdmN0dBTArR0KVlZWKFFTwTe/+U388i//st7NIE3SMn7hcBi7u7vIZrNH9qQT7VCiRsgZIJfiOLjlksViQU9PD3p6epSdChKJBPL5/KELMWMM+Xz+xNWtcs02v9/fUPsWFxdRKpVO7dkDoAy7OhwOAFB2WqjtlSOEqEuuuQhUryfZbBapVAq5XK7hObCkMbTqkxiOPKxG1MM5x+bmJiqVyrHPkXcqGB8fx/nz5xGJRJQVmIIgQJIkZDKZU881vLdLQiPkgrf1mp2dVT4c5MSw01fcGkEzsSPG0a74Wa1WSJKEdDoNt9uNwcFB9Pf3w+PxKL3lRno/ynUX5V53I7WtHrQpOzEcSZLqqqVFGuf1ehu+mMsX5K2tLTgcDkSj0VOf32j8SqUSZmZmGhpKsdlsmJqaaug85GT03uts7YxfoVDA/Pw8RFFUHvN6vfD7/bBYLMqio3YUAj8JYwyBQADhcBgmkwmcc+zu7ip7HBvJcZuy0zuSGM6TTz6pdxO6VjqdrqtXrJYgCHC5XCgWi0gmk8ocsuM88sgjDbfLarVibGysoTvdYrGI3d3dhs9FjtdM7IhxtDN+drsdFy5cwNTUFILBIAAglUphaWkJc3NzyGQy8Pv9GB0d3bcAqF3k+bjj4+OIRCLK1IhOXCFOiRohZ4i8CrTRWmgmkwk2mw2ccywsLBxZ8LdVDocDw8PDDV3Q19fXDbeTBSFnic1mQyQSwW233YbBwUHY7XZlpfjKygoWFhZgtVphs9nalqwxxtDX14epqSllLmutTus17qzWkjOB9mzU3vb2Nm7cuIFsNlvX8xljGBkZURYYzM/PH5ustVJ41uPxYHBwsO4LOuccGxsb2N7ebvqc5BYqGtzZ9IyfIAgIBAKYnJzE5OQkAoGA8rNcLodisYhgMKhpsiZv5Tc1NXXiFng0R80gaI4aIUfz+/2wWq3Y2toCAIyPj9e9T2k8Hsfa2ho45xAEAWNjY0fesbbquG26jsMYQygUQl9fn+ptIYQ0R5IkJJNJxGIxFItFmM1mjIyMYHl5GeVyWbW5a/LihUgkAp/Pd2oiViwWMTMzY7hVqjRHjXSM5557Tu8mdDVBEBAKhXDhwgVcuHChoUTL7/crK0HlnjW5/prsK1/5SsttbPSOl3OO7e1tbGxsGO7i20nUiB3Rj9HiJ/eyTU1NKb1sNpsNk5OTdSVU9ZC3ljt37pyy+rtYLGJzcxOrq6tYXFzE3NwcZmZmlBEEm82G8fFxpdyI0dEYEzGcZDKpdxO6mnz32UzdMcYYotEobty4AVEUIUkS5ubmMD4+DrvdDgBKT127cc6xs7MDzjn6+/s7bnjDCPSKHVGHkeNnt9uVawQARKNReDwerK6u1r36kjEGm82GYrEIoDpNJhqNwuVyAaj24G1ubmJ3d/fIGzZ5Wo28Z3MulzPk/swHUaJGyBnT6kRak8mE4eFhLCwsgHN+ZLKmF3npvSRJiEQilKwRYmA+nw8OhwNLS0soFovHvl8550ppIIvFgmQyiXK5jJ6eHqUGYzKZxPr6OiRJOjLxcjgcsNlsKJVKWF5eRqFQMHyCJqNEjRgObQytLTWSF5fLhZ6eHqUHS07WJiYm8IEPfKDl47vdbuTz+aYupJxzZW/QTto31gjUiB3Rj1Hjl0wmkU6n4fF44HK59i0Ys1qtmJiYUHrJZJxziKKobDlXu2q0dueTQqGA1dXVExMvQRDQ29uLra0tbG9vd0yCJqNEjRjO5uYmfcBqSK1epnA4jHQ6rVxg5WRtd3cXb3zjG1s6dm9vL3Z2dvYV02yEPGeN/j9qzMzMzKFtxkjnaGf80uk01tbWlKkUB/fytdvtyi4z8vCmPK3FbDYrW1K5XC6IoohSqYRisYh8Po9isahsKefxeI4s2yOKIjY3N5VyQydhjKFUKnVkkgbQYgJiQIuLi3o3oauplajVluyQiaKIq1evHro7bpQgCOjv729pmFa+4JP6vfDCC3o3gbSgnfFjjKFSqexLsLLZLNLpNJLJJLa2trCwsABJkjA2NoZgMKhsL1UulxGPx7G6uopr165hZmYGKysr2NzcRCqVQrFY3Le37/z8/L79ROPxOK5fv153ktbT04NEItGRSRpAiRohZ4rae/BZrdZDc8E455ibm0OpVGrp2H6/v6WN1jnniMViLbWBEHI0h8NxYuLDOUcul0MikYDD4UAkEsH58+cxOjqKQCCwb39fefrEccfJ5/OYn59HLpfD7Ows1tbWjp2LdhSv19vy9UhPlKgRw5menta7CV1N7Qn2gUBAKdkBVOMniiJmZ2dbujgyxhoqfnuURCLR9PDpWXTffffp3QTSgnbGz2QynVpgV16lWfu90+nE4OAgent760q05JtL+Qaw0UUAHo/n1G3vjI4SNWI4eq8c7HZarISMRqPKMKUcPzWSNbfb3XJB3Xg83tLrzxKa09fZ2h0/uSzGcSRJOvZ6c9qew4IgwGQywe12g3Pe1DQGxhh6e3s7etgToESNGNCLL76odxO6ltpDnzKTyaTMV6uNnyiKmJubQ7lcbvrYrZTZkGurkfp8+9vf1rsJpAXtjp/b7T51HunCwgKuX7+OWCyGSqWiPG6xWI58XwuCAIvFopTeyGQyDe9NXHsOm82myd7E7USJGiFnjFa1xZxOJ3p7ew8dv1KpYHZ2tulkzW63t9RTQLXUCNGG0+k8NYHinKNcLmNzcxPXr1/H/Pw8UqkUBgcH9xWmlodJI5EI7HY7YrFYS9tMyb1pmUym468BVJ6DGE44HNa7CV1Ny4tWX18fBgYGDj1eqVQwMzMDn88Hl8sFp9MJi8VS93EHBgaQTqebumhrsRdptxofH9e7CaQF7Y6fxWKByWTa11N2HPm9m81mlR6ugYEBTE5OIhaLwefzKTXR1BimZIzB7/djeXm57p0PjIoSNWI458+f17sJXU3LRI0xhne9611YXFw8dLEVRRG7u7vKfBFBEOB0OhGNRk9d3WmxWBAMBo/dGuak9lCiVr+3vOUtejeBtECP+DmdTqRSqYZeIydOa2trCIVCiEQiWFpaUoY51RAIBMAYO3UuXCegoU9iOJcvX9a7CV2t2Yr/9frLv/zLE+eVycvqRVFEJpNBOp2u67h9fX0N11VjjNHilAY8+uijejeBtECP+NWu+G6UXJh6dXUVlUpFteuSXDstm812/LAnQIkaIWeKJEnY3t7G/Px8SxP8TxMIBODxeE69SHLO607UTCYTxsbGGkrWOOeUqBGiodNWfp5G3qeTc95S3cRaTqcTVqsViUSi44c9AUrUiAHV1t0h6pMLUd68ebOuyt6NcjqdAIDBwUGYTKZDW8vUfjHGGqpxZLfbG07Wtra2OnppfjvJsSOdSY/4Wa3Wlnut5PIbJpMJdru9pePJ+3pyzhsekjUq1q0XsIsXL/LHHntM72YQYmiMMbhcrkNbQalF3mLmqPPK6imceVAul8P8/HzdBTN9Pl/LxXMJIUebn59HNptV5Vgmkwkej0fpZWuU2WzGuXPnUCgU9m091Qluv/32q5zzuw8+Tj1qxHCeffZZvZtwZsi9a2pdZAHgy1/+svJvs9kMp9N56MvhcChfjSZpQLXn4KiNmo8iD60sLy9Tz9opamNHOo9e8WtlntpBoigilUohFAo1fEx5btru7q6yz2g3oFWfxHC6YZVOJ5EkCVtbW3C73aocb3d3V5XjnMbj8WBoaKiuBEyeC7e4uIjh4eGWNnvvZu2KHdGGXvFzuVzKNk9qkOfS9vf379sCTh4iPTiFQv5ZPp/H1taW8n23oESNEIJ8Po9CoaDrxHtRFCFJUkP11bxeL6LRKFZWVupK1rLZLBYWFjA6OkrJGiEqOW2D9mZwzrGxsYGBgQEEg0EAwNLSEtLptNLTJu9YcHCD925DVypiOPfee6/eTThzOOfKnWirHnrooaZeJ1cun5ubQzKZrHvYopH5Z/Jd9/z8PG3WfoRmY0eMQa/4aVWvkHOO9fV1bG5uIpVKKUWvJUlSyvwAt0r+dGOSBlCiRgxoeXlZ7yacSel0WpWSHT/5yU+aep08Ty6Xy2F1dRWvvvoqVlZWkMvlTr0A+/1+DAwM1J2sFQoFzM3NUbJ2QLOxI8agZ/yGhoZgNqs/SMc5RywWw9LSUtcmYqehRI0YzsrKit5NOJPk4pOtevnll5s6d7FYVL6X75ATiQTm5+extrZ26jGCwSDC4XDdyVqxWMTs7Gxd29+cFc3EjhiHnvGzWCyYmJjQLFk7yyhRI4Qo4vG4br1Mcs21g+SELZFInHqM3t7ehlaLlUqlljaMJ4TcomWydpZRokYM58KFC3o34UxrdeXY/fff3/BrGGM4f/48otEoHA7HoUSLc461tbUja7Id1NfXh97e3rqTtXK5jNnZ2bqO3e2aiR0xDiPEj5I19VGiRgxHrW1ESOPk+SCt1B9q9gLNGIPX68XExAQGBwcP9a5JkoTFxcW62tbX14dgMFh3slapVDA7O7tv+PUsog/XzmaU+KmRrMnvfypSTYkaMSCa0KwvuUBss/72b/+25TZ4vd4j56WUSiXEYrFTX88YQ39/P/x+f90XelEUMTs7i0Kh0HB7u4UasSP6MVL85GQtGAweO63hKIIgwGq1or+/X9XabJ3MGOk3IcQw5AK4jSQ5ahMEAS6X68jix+l0GoVCAYwxDAwMHHvXzhhDJBKBJElIpVJ1XfAlScLc3BxGR0dp30tCWmSxWBCJRDAwMIBcLod4PK7sv3mwZ5wxBpvNhnA4DLfbXVdtxLOCEjViOAMDA3o34cyrVCrIZDLweDwNv3Z6elqVNgQCAeRyuUMX9Hw+j3w+j2AweOpdOmMM0WgUS0tLyGQydSdr8/PzGB0dhcvlaul36DRqxY7ow6jxk/cUdrlc4Jwjk8kgHo8jnU4DAOx2O/r7+5X3Wy6X65oN1dVAiRoxnImJCb2bcObJBXCbSdRe//rXq9IGj8cDs9msrMiUC1oODAzA6/XWvYMBYwzDw8NYXFxENputK1njnGNhYQHDw8NN/Q06lVqxI/rohPgxxuDxeODxeCBJEsrlMqxWK3K5HNbX15FKpVCpVKg3rQbNUSOG89RTT+ndBAKgUCggn883/LovfOELqpxfEARMT09jcnISfX19sNlscDqd8Hg8YIw1tOBBTtaOWlF6HM45lpaWWpqv12nUih3RRyfFr1KpIJlMYn19Ha+88goWFxexs7ODcrlMSdoB1KNGCDmS3Ks2MjKiaztsNhtCoRAkSUIsFsPMzMy+7WJCoRDC4fCpxxEEAaOjo5ifn0ehUKi7Z02eK+P3+1v9VQghABKJBFZXVwHcKmZLydnxqEeNGI4We8aR5mQymYbri3m9Xo1aA2Wfv9qLejwer/v1giAoq8kaOefq6mpLJUs6hZaxI9rrlPjF4/Gu3ptTbZSoEcO577779G4C2cM5x/LyckPbLP38z/+8Jm0xmUxHJliiKDZU/6yZlayMsTMxuVmr2JH26JT4UXHpxlCiRgzn6aef1rsJpEY+n8fNmzeRy+Xqev6XvvQlTdoRCASOTbLkDd3rUW89p1qSJGFnZ6fh13UarWJH2qNT4jc2Ngan00nFbOtEiRoxnGYmsBNtiaKI+fl5bG1tnTpcoVXPk8lkwuDgIBhjEARBWfIfiUQamj/WTKIGVBdXdHtPwFnoNexmnRI/q9WKsbExZQeSs5qwydey0/4GtJiAEFIXeXGB1+uF3W5v23mLxSLW1tYAAKOjo+jr64PVaoXb7W5qu7FWqp3H4/G6Fi4QQk7GGIPf74fH48H6+jqSyWTXzlkTBAGSJEEQBJjNZlitVthsNlitVlitVlgsFlit1mNfz7r1D3Px4kX+2GOP6d0M0oRisQibzaZ3M8gRbDYbJicnT7z7y2azqhaKTafTWFxchMPhwPj4eMt336Io4tq1a019KJjNZpw7d65rewDUjh1pr06OXy6XU+bDdlNewhhDOBxGIBA49caSMXaVc373wcdp6JMYzuzsrN5NIMeop8jsD3/4Q1XP6fF4cOnSJUxMTKiSILXSoyaKIm7evInFxcWu3MBd7diR9urk+DmdTkxPTyMUCnXNjZAgCBgeHkZvb29Tvf/KcVRsEyGqWF9f17sJ5BjZbPbUPfhu3LjRxhY1rpUPAc45SqUS0ul0V+5FaPTYkZN1evwYY+jr68PU1FTHLzYwm82YmJhQZWcTStQIIXXjnCOVSmF1dbVjkxS1Lv6FQuFM7VpASLvIiw2i0eixZXmMijEGh8OByclJ1abwUKJGDOfSpUt6N4GcgHOOZDJ5bLL2tre9TYdWNUaNCz/nHOvr6xBFUYUWGUMnxI4cr5vixxiDz+fD9PQ0/H5/RyRrjDF4vV6Mj4/DbFZvrSYlasRwuumDr1vJydr6+vqhZK2R4rh6cTqdqhxHkiRsbW2pciwj6ITYkeN1Y/zksjxjY2NNl9ZpB3nYNhqNqp5UGve3JmfWq6++qncTSB0454jH49jY2Nj3+OXLl3VqUf0ikYhqvWq7u7tds7CgE2JHjtfN8SuVSoadbsEYw9DQkGYLIShRI4Q0TU7WOm0fTJvNduJOB42o3bidEKK+fD6/b6oFY0z50pu8aEDLfVap4C0xnGg0qncTSAPk6uKyixcv6tia+oXDYSQSCVUSrEKhgFQqBZ/Pp0LL9NMpsSNH68b4lctlLCwsKO9Ti8WC8fFxCIKAYrGIxcVFXabLMMZgs9kwOjqq6ny0o1CPGjGcoaEhvZtAGnBwW6lOWQxiMpkQDodV61VbW1vruJ7FgzolduRo3RY/SZIwPz+vJGKCIGBsbAwWiwUmkwlOp1NZXalH71o7kjSAEjViQM8884zeTSANKJVKiMViyvedtCNIMBhU7UIrSRI2NzdVOZZeOil25LBuih/nHEtLSyiXywCqPVijo6OHtlqyWCyYmJiAy+Vqa7LmdDrbkqQBlKgRQlok7wGay+X0bkrDGGPKRu+t6raFBYToaWNjA9lsFpxz5X163GptQRAwMjKCnp6etiRrgiCgp6dH8/Mo52vbmQipk9vt1rsJpEGcc8zPz2Nubg5er7ejJta73W7V9kfknHd0MeBgMKh3E0gLuiV+8Xgcu7u7SpLW29sLv99/4msYY+jv78fAwEBbkjU1dhyoFyVqxHDe8IY36N0E0gTOOXK5HG6//XZsb2/r3ZyGqFWuA6iuUEulUqocq90++MEP6t0E0oJuiF8ul8Pa2pqSpHk8HvT19dX9er/fr/mNUrsL8FKiRgznqaee0rsJpAXf+973UCqV9G5GQ6xWKwYGBmA2m1u+AHfywoLPf/7zejeBtKDT41cqlfat8LTZbA0XkBUEQdPCuIyxtvdcUnkOYjg0x6eztRq/2dlZuFwu9Pf3q9Si+gSDQQSDQWUPz2QyqUxkbvQOXZIkJBKJjhuK6sR5huSWTo6fKIqYn59XbnDMZjNGR0ebSrrMZrNmN4sWiwV2u12TYx+HetQIIS2rLT4p1xdqltlsRiwW022el91uRzgcxvT0NKamppqaoCwXAiaEnE5e4SlvgSWX4Wh2VeXBlaFqYYy1dRGBjHrUiOHcf//9ejeBNEgQBExMTMBisWB6erqlC+Xw8DAWFxeVOSp6slqtCIfDyGazyOfzDb22UCigXC7DYrFo1Dr1ffSjH9W7CaQFnRq/9fV15HI55T0/MjLS0s2ezWZDJpNRsYW3nLaoQQvUo0YM59q1a3o3gTRAXjpvtVrBGMN3v/vdlo/X7JCHFhhjTW+0nEwmNWiRdlqNHdFXJ8Zvd3cX8XhcSdIikUjLq7Dla5Ha3G43TCaT6sc9jTGuhITU6PSioWeJvCqrdp+7ubk5HVukDZvNhmAw2NDFvxOHP7sxdmdJp8Uvm81ifX1dSdJ6enoQCARaOqYoilhfX1ephbcIgqDbnFNK1AghdTlqNZUgCBgcHNSpRe0VDocb7uUrlUodtwKWkHYolUr7pji43W6Ew+GWjysPeao9x1Vuox4oUSOG85rXvEbvJpxpjDElITGbzXC5XOjt7UUkEsHo6CjcbreyeGBwcPDQUMA73/lOPZqtOUEQmqq31knDn90au7OiU+J3cIWn1WrF0NCQKsOVWvViBwIB3ebM0mICYjiFQkHvJpxJjDFYLBYEg0F4PJ5j53mMjIwgFouhXC7vG/KUpdNpTdon3yHrucDA6/XC4XDUXQZB3lYqFApp3DJ1aBU70h6dED/OORYXF5UVnmazGWNjY6rMSZUkCdlstuXjHMQYa3lIthXUo0YM58aNG3o3QXe15S7aQRAERKNRTE9Po7e3Fzab7djzM8YQCoUQiUSO/PnTTz+tSRtnZmbw8ssvN7z6Uk3NLCyoVCodUxtQq9iR9uiE+K2trSGfz4NzDkEQMDo6qtrm5ul0WpPrps1ma2kVaqsoUSPEgEwmE4aHh2G329uSsEmS1Na965oxNDQEQP+inlarFb29vXXHhXOORCKhbaMI6QA7OztIJBLKvLShoSHVisem02msrKyoviMIYwyVSgU3b97EtWvX8Oqrr+LmzZtt3XmEEjViOCMjI3o3QVfyBczj8WBiYgIul0vzZE3NHrw77rhDleMcZLfbcenSJV0KTh4UCoUaWqYvlx8wOq1iR9rDyPHLZDLY2NhQ3geCIKh2c5hIJLC0tKRJ7UXOudIrXqlUIIoiSqWSJitLj0OJGjEcNVb+dCrGGPx+v1JHSE7a1BoaOOm8avX6TE5OqnKcenDOIYpi284nk1e71vuhIIpiR8y9bGfsiPqMHL/Nzc19Nytq7R4Qi8WwurqqJGkulws+n0+VYx9H7iXXYj7cUShRI4Zz5coVvZugG8bYoYuMyWTSvACsJEnY2tpSpdfn8ccfV6FFp1tZWcHLL7+Ma9euaVaF/CQej6fuwpydMvzZrtgRbRg5fgdvqFod8uScY2NjQ0kA5Qn/IyMj8Pv9mhfM5pxjeXm5LUOglKgRYiCSJGF3d/fQ4zabrenq+PWqVCrY3t5GLpdDuVzWdahuZmYG165dw8LCAra2tk6sRSavItNj7lojvWryKjdCzqLahIYx1lKixjnH6uoqdnZ2lCQtHA4r5XNcLldbrl9aFdc9iMpzEMPRutva6FKp1L5ttKLRKNxuN7xeL3p6epSLk9o454jFYsqG6JxzWCwWDA0Nwel01n2cvr6+lttiMplQKBSQyWSQyWQQj8cxNTW17y7Z4/EglUpBkiRwzrGwsICxsTE4HI6Wz18vi8WCUCiE7e3tE2NiMpmOXSVrJGrEjujHyPGTJEmZC8s5b3oVpSRJWFpaQjab3bcoobZUkCAIcDqdmg9Nyj3lfX19mu7pyzphgmszLl68yB977DG9m0FIy3w+HyKRiJKkLC0tIZPJtK3HizGGgYGBtm6fEovF9s1pYYyht7d33/zFSqWC69ev7/s7CIKA8fFx1VaS1YNzjhs3bqBcLh/5c3nv0lb3LySkkyWTSXDOYTKZYLFYTiwBdBxRFLGwsIBCoaCU9zju5mx3d1fZnkpLjDH09/erssiJMXaVc373wcdp6JMYzuXLl/VugqGk02llGFAURYyMjCAajcJkMrWldAfnHOvr63UvfX/00UdbPufBla5yb588IV+SJGxvbx96nSRJmJ+fb2vdstraagfjISeYpyVpqVTKEIsN1Igd0Y+R4+fz+eD3++HxeJoqO1SpVDA7O6skaRaLBZOTk8f2oB9VjFsLnHOkUilNz0GJGjEcmsuznzwMmc1mcfPmTeRyOfh8PkxPT8Pv97ctWUsmk5ibmzu250imxt6Wdrv90J2wPHk3mUzi+vXr2N3dPfJuWRRFzM3NtXWPTZfLhQsXLiASicDhcChJm91uPzQcVSwWsbu7i2w2i3K5jGKxiOXlZSwsLLS1NtNRaF/Sztat8SuVSpiZmVF+P4fDgcnJyRNXjprNZtVWlp4ml8tp+t6lOWqEGFxtMiLvkRcOh9HT04PBwUEEAgGsrKxovgCAc45CoYClpSVMTExodh7g1mTjg7sQlEolrKysnPp7ysnaxMSEpnNHagmCgEAggEAggFKphGQyeWQiHYvFkEgklLk68u8iiiLW1tYQjUbb0l5COkGhUMDc3Jwyx83j8SAajda1qtPn82Fra0vzNjLGkM1mNSsaTnPUiOFIkqT50upOJ69sGhoagslkAuccm5ubiMVibTn3+Pj4sUMOasVva2ur5YusxWLBxMSE5nXoGnHjxo1jez4YYxgeHtZtlwh673W2bozf4uKisjVUT08PwuFw3aMIhUIBs7OzbZnP6/f7W77JojlqpGO89NJLejfB8GqHQsvlsrI8vR3zMuSk8DhPPPGEKudxuVwtf+iUy2XMzc3pUhT3KHJV8+NwzrGysqJbe9WKHdFHN8ZPnrs5MDCA/v7+hqZ62Gy2tiWu6XRas4SQEjViOO3oFeoG8tYmq6urAG5Nam/HvIxsNnvshP2lpSVVzuFwOFS58JVKJczPz+s+/wsA8vn8qR8coihiZWWlTS3aT63YEX10Y/wsFgtGRkaaWnXOGGvbogJJkjRbEESJGiEdLpvNIplMAqjOkxoZGdF8gQHn/MhVl2oSBEG1pLNYLDadrBWLRWxubuL69ev79ipsRjabrasNmUymI3YyIERr4+PjLU0F8Pl8belV45wjnU5rcmxK1Ijh3HnnnXo3oaPIVbrl4TJ5FwOtJZPJI1foPvjgg6qdw+12q3IceSFEIz1VmUwGN27cwMzMDGKxGMrlMnZ2drC4uNh071y9W11xzrG2tnbqClu1qRk70n4Uv8OcTmfbak7KN8xqo0SNGI5WdyXdTP5gl/l8Ps0L1DLGjpxvpWZPm9vtVu1uWL7jrbf8S6VSUVbSyhd6eW7g7Oxsw0mUnCzWS5IkLC8vt3UrL617SYm2KH6HCYLQtmLTpVJJk/JSlKgRw5mZmdG7CR1HLrpY22MzMDDQ1gr9sitXrqh2LKfTqfrcsnrven0+35GlPTjnKBaLDc8HKhQKDQ9J5/P5I/d+1YqasSPtR/E7WruGPwFoUvyWEjVCuoS8YlDu6WGMYWRkZN8Fqh3FcdUkbzejFs553YmPvHXWcX+zQqHQ0N1zPp9vuHeMc46NjY227rRASLdpdl/RRmm1S0HX1lFjjD2ndxsIIYQQQuoU45z/9MEHuzZRI4QQQgjpdDT0SQghhBBiUJSoEUIIIYQYFCVqhBBCCCEGRYkaUR1j7HOMsS3G2E9qHvsMY+waY+xFxthfMcb8B14zzBjLMMZ+o+axtzLGnmOMfXrv+/cyxr5S8/PfZIzN1Hz/M4yxr2n5u3WDRuLDGLuHMfb83tcLjLH3H3PMx2qet8AYe37v8VHGWL7mZ39S8xqKb4s0iuUnGWOrNc9994FjP8cYu3/v+79ijL2v5ufXGWP/vub7xxlj/0j937wzaRSv415P770uQYka0cKjAA6uXPkOgEuc89cAuAHgNw/8/A8BfOvAY/8UwJsBmBhj5wE8DeDemp/fCyDFGOvb+/4+AN9vufXd71HUH5+fALibc/7avdf8KWPMfPCAnPOHOOev3Xve4wD+v5ofz8o/45z/as3jFN/WPQqVY7nnD2ti9tcAsBcjAHgLgH++9++nUY0LGGM9ADI4HMOnm/vVutKjUD9eJ11b6b3XBShRI6rjnH8XwO6Bx57gnMtFp34AQNnjaO+OfA7AywcOJQDgACRUVyhvA0gyxib3fj6IalJw397394E+FE7VSHw457max+2oxuNYjDEG4EMAvlhHUyi+LdIylkcwoRorDkAuLvd97I/PNwCEWNUYgDznfKPB83QtLeJ10rX1BPTe6yCUqBE9fBx7vWeMMReAfwvgU0c87xFULw4C5/zVvceeBnAfY+wcgJuoXpju27vTfA2AH2rc9rNAiQ8AMMbewBh7GcBLAH615kPhKG8GsMk5v1nz2Bhj7MeMscuMsTfXPE7x1V6zsXx4byjtc4yxAABwzl8G4ATwFIA/3nveVQCXGGNWVD/MnwFwHcAFUC9MM1p57x16Pei91xWO6/YmRBOMsX8HoALgC3sPfQrVYZYMO1ABnnP+bQDfPnAI+Q7ehOqHwhUAvw3gTgDXOef1b6ZIDjkiPuCcPwvgImPsAoC/YIx964S/84exvzdtHcAw53yHMfY6AF9hjF3knKcovtpqIZZ/DOB3Ue1x+V0A/zuqCQA45/+i9omc8+JeInEXgJ8C8GkA46jG8E5QL0zdWn3vHfF6eu91CepRI23DGPtFAO8B8BF+q9LyGwB8mjG2AOBfAfgtxtjDJxxGnhNzH4BnOOdpVIcF3gq6e2/JMfFR7N15ZwFcOub1ZgD/CMBjNa8pcs539v59FcAsgOkTmkHxVUErseScb3LORc65BOD/BnDPKad7GtV5ax7OeRx7PTGgHrW6qfDeO/R6eu91D0rUSFswxn4a1SHOn+Wc5+THOedv5pyPcs5HAfwfAP4T5/yzJxzqFQARVIfYfrz32PMAfhV099604+LDGBuTJzAzxkYAnAOwcMxh/iGAa5zzlZrXhxhjpr1/jwOYQnU+4nEovi1qNZaMsYGab9+P6qT2k3wfwK8AeGHv+xdR7V0bxuF5p+QAFeJ13OvpvdclKFEjqmOMfRHVrvNzjLEVxtj/CuCzADwAvnNwqXgj9u4Wn0V1T7Ty3sPPoDrcQheTOjQYnzcBeIFVy238FYB/xjmP7R3nEcbY3TWH/nkcXkTwFgAvMsZeAPBlVOfZHLsrOsW3MRrF8tOMsZcYYy8CeADAr53SjKdRjc8zALA3j2oLwHN7vXJkj0bxOu719N7rErTXJyGEEEKIQVGPGiGEEEKIQVGiRgghhBBiUJSoEUIIIYQYFCVqhBBCCCEGRYkaIYQQQohBUaJGCCGEEGJQlKgRQgghhBgUJWqEEEIIIQb1PwFxtRlPvPZ/TQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': crs.Mercator()})\n", "ax.set_extent([-124.25, -123, 49, 49.75], crs=crs.PlateCarree())\n", "ax.add_feature(feature.GSHHSFeature('high', facecolor='lightgray',edgecolor='lightgray'),zorder=2)\n", "gl = ax.gridlines(\n", " linestyle='--', color='gray', draw_labels=True,\n", " xlocs=[-124,-123.75,-123.5,-123.25], ylocs=[49.25,49.5],zorder=5)\n", "gl.top_labels, gl.right_labels = False, False\n", "\n", "ax.scatter(ds_waves.lon[:30,:100],ds_waves.lat[:30,:100],c='c',s=1,label='With Stokes drift',transform=crs.PlateCarree())\n", "ax.scatter(ds_nowaves.lon[:30,:100],ds_nowaves.lat[:30,:100],c='tab:orange',s=1,label='Without Stokes drift',transform=crs.PlateCarree())\n", "plt.legend()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.9" } }, "nbformat": 4, "nbformat_minor": 5 }