SNN_Training-Visualisation-Time-Samples.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3c0b54b4-64f2-4313-b4bc-10ca42558d6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ef92803e-0e97-4c95-bf37-2408638a1701",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import snntorch as snn\n",
    "from snntorch import spikeplot as splt\n",
    "from snntorch import spikegen\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import scipy.io\n",
    "import scipy.signal \n",
    "\n",
    "from matplotlib import mlab\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d5bf93b9-a825-4077-bffe-a29a62663e31",
   "metadata": {},
   "outputs": [],
   "source": [
    "def psd(trials):\n",
    "    \n",
    "    ntrials = trials.shape[2]\n",
    "    trials_PSD = np.zeros((nchannels, 101, ntrials))\n",
    "\n",
    "    # Iterate over trials and channels\n",
    "    for trial in range(ntrials):\n",
    "        for ch in range(nchannels):\n",
    "            # Calculate the PSD\n",
    "            (PSD, freqs) = mlab.psd(trials[ch,:,trial], NFFT=int(nsamples), Fs=sample_rate)\n",
    "            trials_PSD[ch, :, trial] = PSD.ravel()\n",
    "                \n",
    "    return trials_PSD, freqs\n",
    "\n",
    "\n",
    "def plot_psd(trials_PSD, freqs, chan_ind, chan_lab=None, maxy=None):\n",
    "    plt.figure(figsize=(12,5))\n",
    "    \n",
    "    nchans = len(chan_ind)\n",
    "    \n",
    "    # Maximum of 3 plots per row\n",
    "    nrows = int(np.ceil(nchans / 3))\n",
    "    ncols = min(3, nchans)\n",
    "    \n",
    "    # Enumerate over the channels\n",
    "    for i,ch in enumerate(chan_ind):\n",
    "        # Figure out which subplot to draw to\n",
    "        plt.subplot(nrows,ncols,i+1)\n",
    "    \n",
    "        # Plot the PSD for each class\n",
    "        for cl in trials.keys():\n",
    "            plt.plot(freqs, np.mean(trials_PSD[cl][ch,:,:], axis=1), label=cl)\n",
    "    \n",
    "        # All plot decoration below...\n",
    "        \n",
    "        plt.xlim(1,30)\n",
    "        \n",
    "        if maxy != None:\n",
    "            plt.ylim(0,maxy)\n",
    "    \n",
    "        plt.grid()\n",
    "    \n",
    "        plt.xlabel('Frequency (Hz)')\n",
    "        \n",
    "        if chan_lab == None:\n",
    "            plt.title('Channel %d' % (ch+1))\n",
    "        else:\n",
    "            plt.title(chan_lab[i])\n",
    "\n",
    "        plt.legend()\n",
    "        \n",
    "    plt.tight_layout()\n",
    "\n",
    "def bandpass(trials, lo, hi, sample_rate):\n",
    " \n",
    "    a, b = scipy.signal.iirfilter(6, [lo/(sample_rate/2.0), hi/(sample_rate/2.0)])\n",
    "\n",
    "    ntrials = trials.shape[2]\n",
    "    trials_filt = np.zeros((nchannels, nsamples, ntrials))\n",
    "    for i in range(ntrials):\n",
    "        trials_filt[:,:,i] = scipy.signal.filtfilt(a, b, trials[:,:,i], axis=1)\n",
    "    \n",
    "    return trials_filt\n",
    "\n",
    "def logvar(trials):\n",
    "    return np.var(trials, axis=1)\n",
    "\n",
    "def plot_logvar(trials, trial_no = None):\n",
    "    plt.figure(figsize=(12,5))\n",
    "\n",
    "    print(trials[cl1].shape)\n",
    "    \n",
    "    x0 = np.arange(nchannels)\n",
    "    x1 = np.arange(nchannels) + 0.4\n",
    "\n",
    "    if trial_no == None:\n",
    "        y0 = np.mean(trials[cl1], axis=1)\n",
    "        y1 = np.mean(trials[cl2], axis=1)\n",
    "    else:\n",
    "        y0 = trials[cl1][:,trial_no]\n",
    "        y1 = trials[cl2][:,trial_no]\n",
    "\n",
    "    plt.bar(x0, y0, width=0.5, color='b')\n",
    "    plt.bar(x1, y1, width=0.4, color='r')\n",
    "\n",
    "    plt.xlim(-0.5, nchannels+0.5)\n",
    "\n",
    "    plt.gca().yaxis.grid(True)\n",
    "    plt.title('log-var of each channel/component')\n",
    "    plt.xlabel('channels/components')\n",
    "    plt.ylabel('log-var')\n",
    "    plt.legend(cl_lab)\n",
    "\n",
    "from numpy import linalg\n",
    "\n",
    "def cov(trials):\n",
    "    ntrials = trials.shape[2]\n",
    "    covs = [ trials[:,:,i].dot(trials[:,:,i].T) / nsamples for i in range(ntrials) ]\n",
    "    return np.mean(covs, axis=0)\n",
    "\n",
    "def whitening(sigma):\n",
    "    U, l, _ = linalg.svd(sigma)\n",
    "    return U.dot( np.diag(l ** -0.5) )\n",
    "\n",
    "def csp(trials_r, trials_f):\n",
    "    cov_r = cov(trials_r)\n",
    "    cov_f = cov(trials_f)\n",
    "    P = whitening(cov_r + cov_f)\n",
    "    B, _, _ = linalg.svd( P.T.dot(cov_f).dot(P) )\n",
    "    W = P.dot(B)\n",
    "    return W\n",
    "\n",
    "def apply_mix(W, trials):\n",
    "    ntrials = trials.shape[2]\n",
    "    trials_csp = np.zeros((nchannels, nsamples, ntrials))\n",
    "    for i in range(ntrials):\n",
    "        trials_csp[:,:,i] = W.T.dot(trials[:,:,i])\n",
    "    return trials_csp\n",
    "\n",
    "import torch\n",
    "import snntorch.spikeplot as splt\n",
    "from snntorch import spikegen\n",
    "\n",
    "def spike_latency(trials, trial_n, cls, num_steps):\n",
    "    input_data = trials[cl1] if cls == 1 else trials[cl2]\n",
    "    \n",
    "    tensor = torch.tensor(input_data[:,trial_n])\n",
    "    device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "    tensor = tensor.to(device)\n",
    "    \n",
    "    spike_data = spikegen.latency(tensor, num_steps=num_steps, threshold=(np.mean(input_data[:,trial_n])+1)*1/2, bypass=True)\n",
    "\n",
    "    return spike_data\n",
    "\n",
    "def spike_rate(trials, trial_n, cls, num_steps):\n",
    "    input_data = trials[cl1] if cls == 1 else trials[cl2]\n",
    "    \n",
    "    tensor = torch.tensor(input_data[:,trial_n])\n",
    "    device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "    tensor = tensor.to(device)\n",
    "    \n",
    "    spike_data = spikegen.rate(tensor, num_steps=num_steps)\n",
    "\n",
    "    return spike_data\n",
    "\n",
    "def plot_raster(spike_data):\n",
    "    \n",
    "    fig = plt.figure(facecolor=\"w\", figsize=(10, 5))\n",
    "    ax = fig.add_subplot(111)\n",
    "    \n",
    "    spike_data_sample = spike_data\n",
    "    splt.raster(spike_data_sample, ax, s=1.5, c=\"black\")\n",
    "    plt.ylim(0, 60)\n",
    "    \n",
    "    plt.title(\"Input Layer\")\n",
    "    plt.xlabel(\"Time step\")\n",
    "    plt.ylabel(\"Neuron Number\")\n",
    "    plt.show()\n",
    "\n",
    "def plot_snn_spikes(spk_in, spk1_rec, spk2_rec, num_steps, title):\n",
    "  # Generate Plots\n",
    "  fig, ax = plt.subplots(3, figsize=(8,7), sharex=True, \n",
    "                        gridspec_kw = {'height_ratios': [1, 1, 0.4]})\n",
    "\n",
    "  # Plot input spikes\n",
    "  splt.raster(spk_in[:,0], ax[0], s=0.1, c=\"black\")\n",
    "  ax[0].set_ylabel(\"Input Spikes\")\n",
    "  ax[0].set_title(title)\n",
    "\n",
    "  # Plot hidden layer spikes\n",
    "  splt.raster(spk1_rec.reshape(num_steps, -1), ax[1], s = 0.1, c=\"black\")\n",
    "  ax[1].set_ylabel(\"Hidden Layer\")\n",
    "\n",
    "  # Plot output spikes\n",
    "  splt.raster(spk2_rec.reshape(num_steps, -1), ax[2], c=\"black\", marker=\"|\")\n",
    "  ax[2].set_ylabel(\"Output Spikes\")\n",
    "  ax[2].set_ylim([0, 10])\n",
    "\n",
    "  plt.show()\n",
    "\n",
    "def plot_snn_spikes(spk_in, spk1_rec, spk2_rec, num_steps, title):\n",
    "  # Generate Plots\n",
    "  fig, ax = plt.subplots(3, figsize=(8,7), sharex=True, \n",
    "                        gridspec_kw = {'height_ratios': [1, 1, 0.4]})\n",
    "\n",
    "  # Plot input spikes\n",
    "  splt.raster(spk_in[:,0], ax[0], s=0.1, c=\"black\")\n",
    "  ax[0].set_ylabel(\"Input Spikes\")\n",
    "  ax[0].set_title(title)\n",
    "\n",
    "  # Plot hidden layer spikes\n",
    "  splt.raster(spk1_rec.reshape(num_steps, -1), ax[1], s = 0.1, c=\"black\")\n",
    "  ax[1].set_ylabel(\"Hidden Layer\")\n",
    "\n",
    "  # Plot output spikes\n",
    "  splt.raster(spk2_rec.reshape(num_steps, -1), ax[2], c=\"black\", marker=\"|\")\n",
    "  ax[2].set_ylabel(\"Output Spikes\")\n",
    "  ax[2].set_yticks([0, 1], ['left', 'right'])\n",
    "  ax[2].set_ylim([-0.5, 1.5])\n",
    "\n",
    "\n",
    "  plt.show()\n",
    "\n",
    "def plot_snn_spikes_modified(spk_in, spk1_rec, spk2_rec, num_steps, title):\n",
    "  # Generate Plots\n",
    "  fig, ax = plt.subplots(3, figsize=(8,7), sharex=False, \n",
    "                        gridspec_kw = {'height_ratios': [1, 1, 0.4]})\n",
    "\n",
    "  # Plot input spikes\n",
    "\n",
    "  neuron_numbers = list(range(59))\n",
    "  currents = spk_in.tolist()  # Currents fed to each neuron\n",
    "    \n",
    "  # Create bar chart\n",
    "  ax[0].bar(neuron_numbers, currents, color='skyblue')\n",
    "  ax[0].set_ylabel(\"Input Currents\")\n",
    "  ax[0].set_title(title)\n",
    "\n",
    "  # Plot hidden layer spikes\n",
    "  splt.raster(spk1_rec.reshape(num_steps, -1), ax[1], s = 0.1, c=\"black\")\n",
    "  ax[1].set_ylabel(\"Hidden Layer\")\n",
    "\n",
    "  # Plot output spikes\n",
    "  splt.raster(spk2_rec.reshape(num_steps, -1), ax[2], c=\"black\", marker=\"|\")\n",
    "  ax[2].set_ylabel(\"Output Spikes\")\n",
    "  ax[2].set_yticks([0, 1], ['left', 'right'])\n",
    "  ax[2].set_ylim([-0.5, 1.5])\n",
    "\n",
    "\n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0f9d2b61-e4b2-441b-830d-bf478b3c9d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "m = scipy.io.loadmat('BCICIV_1_mat\\BCICIV_calib_ds1d.mat', struct_as_record=True)\n",
    "\n",
    "sample_rate = m['nfo']['fs'][0][0][0][0]\n",
    "EEG = m['cnt'].T\n",
    "nchannels, nsamples = EEG.shape\n",
    "\n",
    "channel_names = [s[0] for s in m['nfo']['clab'][0][0][0]]\n",
    "event_onsets = m['mrk'][0][0][0]\n",
    "event_codes = m['mrk'][0][0][1]\n",
    "labels = np.zeros((1, nsamples), int)\n",
    "labels[0, event_onsets] = event_codes\n",
    "\n",
    "cl_lab = [s[0] for s in m['nfo']['classes'][0][0][0]]\n",
    "cl1 = cl_lab[0]\n",
    "cl2 = cl_lab[1]\n",
    "nclasses = len(cl_lab)\n",
    "nevents = len(event_onsets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a4b8e6b1-c762-49b1-a3c1-2834cde6d88b",
   "metadata": {},
   "outputs": [],
   "source": [
    "trials = {}\n",
    "\n",
    "win = np.arange(int(0.5*sample_rate), int(2.5*sample_rate))\n",
    "\n",
    "nsamples = len(win)\n",
    "\n",
    "for cl, code in zip(cl_lab, np.unique(event_codes)):\n",
    "    \n",
    "    cl_onsets = event_onsets[event_codes == code]\n",
    "\n",
    "    trials[cl] = np.zeros((nchannels, nsamples, len(cl_onsets)))\n",
    "    \n",
    "    for i, onset in enumerate(cl_onsets):\n",
    "        trials[cl][:,:,i] = EEG[:, win+onset]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "02cab55d-2ee6-4ea2-b173-78322d7b334c",
   "metadata": {},
   "outputs": [],
   "source": [
    "trials_filt = {cl1: bandpass(trials[cl1], 2, 30, sample_rate),\n",
    "               cl2: bandpass(trials[cl2], 2, 30, sample_rate)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "886326e2-8579-4eb8-ac3b-66b19466e54b",
   "metadata": {},
   "outputs": [],
   "source": [
    "W = csp(trials_filt[cl1], trials_filt[cl2])\n",
    "trials_csp = {cl1: apply_mix(W, trials_filt[cl1]),\n",
    "              cl2: apply_mix(W, trials_filt[cl2])}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7db7b713-d09a-4d50-bde8-a1ce6086451a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtype = torch.float\n",
    "device = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "24797234-e175-42b5-99e8-c09d4fe08257",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import torch\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "\n",
    "class CustomDataset(Dataset):\n",
    "    def __init__(self, data):\n",
    "        self.data = data\n",
    "\n",
    "    def __len__(self):\n",
    "        if len(self.data.shape) > 1:\n",
    "            return self.data.shape[2]\n",
    "        else:\n",
    "            return 1\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        sample = self.data[:,1:,idx]\n",
    "        label = self.data[0,0,idx]\n",
    "        return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e9ddc963-32bb-4816-91ba-94763053865a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(59, 200, 100)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trials_csp[cl1].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8f8f53cc-7eaa-4335-98e1-e60bb4155e4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = trials_csp\n",
    "\n",
    "# Additional column for class identifiers\n",
    "class_column_left = np.zeros((59, 1, 100))  # Assuming all instances belong to class 0\n",
    "class_column_right = np.ones((59, 1, 100))  # Assuming all instances belong to class 0\n",
    "\n",
    "# Concatenate class column along with left and right arrays\n",
    "left_with_class = np.concatenate([class_column_left, data['left']], axis=1)\n",
    "right_with_class = np.concatenate([class_column_right, data['right']], axis=1)\n",
    "\n",
    "# Concatenate left and right arrays along axis 1\n",
    "result = np.concatenate([left_with_class, right_with_class], axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8d487a11-91b9-4505-b46c-c3060f0a6a8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(59, 201, 200)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "475f6d0f-346c-4e1d-adfb-702767c659d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([32, 59, 200]) tensor(0)\n",
      "torch.Size([32, 59, 200]) tensor(1)\n",
      "torch.Size([32, 59, 200]) tensor(0)\n",
      "torch.Size([32, 59, 200]) tensor(0)\n",
      "torch.Size([32, 59, 200]) tensor(1)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\2584680384.py:18: DeprecationWarning: an integer is required (got type numpy.float64).  Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.\n",
      "  return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)\n"
     ]
    }
   ],
   "source": [
    "cl1_split_idx = int(result.shape[2]*0.5*0.8)\n",
    "cl2_split_idx = int(result.shape[2]*0.5*1.8)\n",
    "\n",
    "train_data = np.concatenate([result[:, :, :cl1_split_idx],result[:, :, 100:cl2_split_idx]], axis=2)\n",
    "test_data = np.concatenate([result[:, :, cl1_split_idx:100],result[:, :, cl2_split_idx:]], axis=2)\n",
    "\n",
    "# Create CustomDataset instance\n",
    "train_dataset = CustomDataset(train_data)\n",
    "test_dataset = CustomDataset(test_data)\n",
    "\n",
    "# Create DataLoader\n",
    "batch_size = 32\n",
    "train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
    "test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False)\n",
    "\n",
    "for samples, labels in train_loader:\n",
    "    # Your training code here\n",
    "    print(samples.shape, labels[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "83aa766e-32c4-4758-aff4-43f1d056ac83",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_inputs = 59\n",
    "num_hidden = 1000\n",
    "num_outputs = 2\n",
    "beta = 0.99"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "029343f6-1daa-4052-831f-e38b989eca38",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define Network\n",
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "\n",
    "        # Initialize layers\n",
    "        self.fc1 = nn.Linear(num_inputs, num_hidden)\n",
    "        self.lif1 = snn.Leaky(beta=beta)\n",
    "        self.fc2 = nn.Linear(num_hidden, num_outputs)\n",
    "        self.lif2 = snn.Leaky(beta=beta)\n",
    "\n",
    "        self.spkIn = []\n",
    "        self.spk1 = []\n",
    "        self.spk2 = []\n",
    "\n",
    "    def _delta_coding(self, x):\n",
    "        tensor = torch.tensor(x)\n",
    "        device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "        tensor = tensor.to(device)\n",
    "    \n",
    "        spike_data = x\n",
    "\n",
    "        return spike_data.permute(2, 0, 1)\n",
    "\n",
    "    def test(self,x):\n",
    "        print(x.shape)\n",
    "        print(self._delta_coding(x).shape)\n",
    "        \n",
    "    def forward(self, x):\n",
    "\n",
    "        # Initialize hidden states at t=0\n",
    "        mem1 = self.lif1.init_leaky()\n",
    "        mem2 = self.lif2.init_leaky()\n",
    "\n",
    "        self.spkIn = []\n",
    "        self.spk1 = []\n",
    "        self.spk2 = []\n",
    "        \n",
    "        # Record the final layer\n",
    "        spk2_rec = []\n",
    "        mem2_rec = []\n",
    "\n",
    "        spk_in = self._delta_coding(x)\n",
    "        \n",
    "        num_steps = spk_in.shape[0]\n",
    "\n",
    "        for step in range(num_steps):\n",
    "            #print(spk_in[step].shape)\n",
    "            cur1 = self.fc1(spk_in[step])\n",
    "            spk1, mem1 = self.lif1(cur1, mem1)\n",
    "            cur2 = self.fc2(spk1)\n",
    "            spk2, mem2 = self.lif2(cur2, mem2)\n",
    "\n",
    "            self.spkIn.append(spk_in[step])\n",
    "            self.spk1.append(spk1)\n",
    "            self.spk2.append(spk2)\n",
    "            \n",
    "            spk2_rec.append(spk2)\n",
    "            mem2_rec.append(mem2)\n",
    "            \n",
    "        return torch.stack(spk2_rec, dim=0), torch.stack(mem2_rec, dim=0)\n",
    "        \n",
    "# Load the network onto CUDA if available\n",
    "net = Net().to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "374246aa-11c9-4769-b1e7-c860581cf5e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\2584680384.py:18: DeprecationWarning: an integer is required (got type numpy.float64).  Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.\n",
      "  return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)\n",
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\3181884480.py:17: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  tensor = torch.tensor(x)\n"
     ]
    }
   ],
   "source": [
    "for samples, labels in train_loader:\n",
    "    spike_data = net.forward(samples)\n",
    "    #spike_data = spikegen.delta(samples, threshold=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4e0f2158-9ae7-4c1a-bfaf-db14c9fac710",
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_batch_accuracy(data, targets, train=False):\n",
    "    output, _ = net(data)\n",
    "    _, idx = output.sum(dim=0).max(1)\n",
    "    acc = np.mean((targets == idx).detach().cpu().numpy())\n",
    "\n",
    "    if train:\n",
    "        print(f\"Train set accuracy for a single minibatch: {acc*100:.2f}%\")\n",
    "    else:\n",
    "        print(f\"Test set accuracy for a single minibatch: {acc*100:.2f}%\")\n",
    "\n",
    "def train_printer(\n",
    "    data, targets, epoch,\n",
    "    counter, iter_counter,\n",
    "        loss_hist, test_loss_hist, test_data, test_targets):\n",
    "    print(f\"Epoch {epoch}, Iteration {iter_counter}\")\n",
    "    print(f\"Train Set Loss: {loss_hist[counter]:.2f}\")\n",
    "    print(f\"Test Set Loss: {test_loss_hist[counter]:.2f}\")\n",
    "    print_batch_accuracy(data, targets, train=True)\n",
    "    print_batch_accuracy(test_data, test_targets, train=False)\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c58a6092-5d1f-4e70-8e99-360890edfd2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "loss = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.Adam(net.parameters(), lr=1e-4, betas=(0.9, 0.999))\n",
    "\n",
    "dtype = torch.float\n",
    "device = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "609113bc-321b-40fd-b3a2-dc4b6547e5db",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\2584680384.py:18: DeprecationWarning: an integer is required (got type numpy.float64).  Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.\n",
      "  return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)\n",
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\3181884480.py:17: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  tensor = torch.tensor(x)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Iteration 0\n",
      "Train Set Loss: 160.88\n",
      "Test Set Loss: 89.67\n",
      "Train set accuracy for a single minibatch: 40.62%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 0, Iteration 1\n",
      "Train Set Loss: 147.01\n",
      "Test Set Loss: 79.38\n",
      "Train set accuracy for a single minibatch: 43.75%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 0, Iteration 2\n",
      "Train Set Loss: 94.01\n",
      "Test Set Loss: 77.43\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 0, Iteration 3\n",
      "Train Set Loss: 76.08\n",
      "Test Set Loss: 70.47\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 65.62%\n",
      "\n",
      "\n",
      "Epoch 0, Iteration 4\n",
      "Train Set Loss: 89.91\n",
      "Test Set Loss: 70.40\n",
      "Train set accuracy for a single minibatch: 46.88%\n",
      "Test set accuracy for a single minibatch: 68.75%\n",
      "\n",
      "\n",
      "Epoch 1, Iteration 0\n",
      "Train Set Loss: 89.66\n",
      "Test Set Loss: 71.89\n",
      "Train set accuracy for a single minibatch: 43.75%\n",
      "Test set accuracy for a single minibatch: 68.75%\n",
      "\n",
      "\n",
      "Epoch 1, Iteration 1\n",
      "Train Set Loss: 80.38\n",
      "Test Set Loss: 75.43\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 65.62%\n",
      "\n",
      "\n",
      "Epoch 1, Iteration 2\n",
      "Train Set Loss: 95.50\n",
      "Test Set Loss: 78.97\n",
      "Train set accuracy for a single minibatch: 40.62%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 1, Iteration 3\n",
      "Train Set Loss: 87.97\n",
      "Test Set Loss: 84.30\n",
      "Train set accuracy for a single minibatch: 46.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 1, Iteration 4\n",
      "Train Set Loss: 69.73\n",
      "Test Set Loss: 87.23\n",
      "Train set accuracy for a single minibatch: 40.62%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 2, Iteration 0\n",
      "Train Set Loss: 83.59\n",
      "Test Set Loss: 90.74\n",
      "Train set accuracy for a single minibatch: 43.75%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 2, Iteration 1\n",
      "Train Set Loss: 79.02\n",
      "Test Set Loss: 92.17\n",
      "Train set accuracy for a single minibatch: 43.75%\n",
      "Test set accuracy for a single minibatch: 43.75%\n",
      "\n",
      "\n",
      "Epoch 2, Iteration 2\n",
      "Train Set Loss: 89.87\n",
      "Test Set Loss: 91.24\n",
      "Train set accuracy for a single minibatch: 37.50%\n",
      "Test set accuracy for a single minibatch: 40.62%\n",
      "\n",
      "\n",
      "Epoch 2, Iteration 3\n",
      "Train Set Loss: 84.20\n",
      "Test Set Loss: 91.56\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 2, Iteration 4\n",
      "Train Set Loss: 91.03\n",
      "Test Set Loss: 89.43\n",
      "Train set accuracy for a single minibatch: 31.25%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 3, Iteration 0\n",
      "Train Set Loss: 88.72\n",
      "Test Set Loss: 86.27\n",
      "Train set accuracy for a single minibatch: 37.50%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 3, Iteration 1\n",
      "Train Set Loss: 78.70\n",
      "Test Set Loss: 84.61\n",
      "Train set accuracy for a single minibatch: 46.88%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 3, Iteration 2\n",
      "Train Set Loss: 81.14\n",
      "Test Set Loss: 80.96\n",
      "Train set accuracy for a single minibatch: 43.75%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 3, Iteration 3\n",
      "Train Set Loss: 85.28\n",
      "Test Set Loss: 79.25\n",
      "Train set accuracy for a single minibatch: 46.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 3, Iteration 4\n",
      "Train Set Loss: 73.70\n",
      "Test Set Loss: 79.60\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 4, Iteration 0\n",
      "Train Set Loss: 90.59\n",
      "Test Set Loss: 74.80\n",
      "Train set accuracy for a single minibatch: 37.50%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 4, Iteration 1\n",
      "Train Set Loss: 79.12\n",
      "Test Set Loss: 73.61\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 4, Iteration 2\n",
      "Train Set Loss: 67.08\n",
      "Test Set Loss: 72.78\n",
      "Train set accuracy for a single minibatch: 50.00%\n",
      "Test set accuracy for a single minibatch: 65.62%\n",
      "\n",
      "\n",
      "Epoch 4, Iteration 3\n",
      "Train Set Loss: 75.71\n",
      "Test Set Loss: 72.46\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 65.62%\n",
      "\n",
      "\n",
      "Epoch 4, Iteration 4\n",
      "Train Set Loss: 73.89\n",
      "Test Set Loss: 72.23\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 5, Iteration 0\n",
      "Train Set Loss: 81.72\n",
      "Test Set Loss: 73.13\n",
      "Train set accuracy for a single minibatch: 50.00%\n",
      "Test set accuracy for a single minibatch: 68.75%\n",
      "\n",
      "\n",
      "Epoch 5, Iteration 1\n",
      "Train Set Loss: 73.02\n",
      "Test Set Loss: 73.48\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 68.75%\n",
      "\n",
      "\n",
      "Epoch 5, Iteration 2\n",
      "Train Set Loss: 71.32\n",
      "Test Set Loss: 73.51\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 71.88%\n",
      "\n",
      "\n",
      "Epoch 5, Iteration 3\n",
      "Train Set Loss: 79.89\n",
      "Test Set Loss: 73.48\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 68.75%\n",
      "\n",
      "\n",
      "Epoch 5, Iteration 4\n",
      "Train Set Loss: 79.99\n",
      "Test Set Loss: 73.39\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 65.62%\n",
      "\n",
      "\n",
      "Epoch 6, Iteration 0\n",
      "Train Set Loss: 70.83\n",
      "Test Set Loss: 72.95\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 6, Iteration 1\n",
      "Train Set Loss: 77.72\n",
      "Test Set Loss: 72.51\n",
      "Train set accuracy for a single minibatch: 50.00%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 6, Iteration 2\n",
      "Train Set Loss: 67.18\n",
      "Test Set Loss: 72.83\n",
      "Train set accuracy for a single minibatch: 56.25%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 6, Iteration 3\n",
      "Train Set Loss: 76.27\n",
      "Test Set Loss: 73.37\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 6, Iteration 4\n",
      "Train Set Loss: 81.69\n",
      "Test Set Loss: 74.61\n",
      "Train set accuracy for a single minibatch: 56.25%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 7, Iteration 0\n",
      "Train Set Loss: 71.97\n",
      "Test Set Loss: 76.75\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 7, Iteration 1\n",
      "Train Set Loss: 69.92\n",
      "Test Set Loss: 77.46\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 7, Iteration 2\n",
      "Train Set Loss: 72.95\n",
      "Test Set Loss: 78.05\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 7, Iteration 3\n",
      "Train Set Loss: 82.88\n",
      "Test Set Loss: 79.03\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 7, Iteration 4\n",
      "Train Set Loss: 68.91\n",
      "Test Set Loss: 79.77\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 8, Iteration 0\n",
      "Train Set Loss: 64.11\n",
      "Test Set Loss: 79.65\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 8, Iteration 1\n",
      "Train Set Loss: 75.66\n",
      "Test Set Loss: 79.88\n",
      "Train set accuracy for a single minibatch: 40.62%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 8, Iteration 2\n",
      "Train Set Loss: 69.15\n",
      "Test Set Loss: 80.77\n",
      "Train set accuracy for a single minibatch: 75.00%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 8, Iteration 3\n",
      "Train Set Loss: 73.24\n",
      "Test Set Loss: 79.50\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 8, Iteration 4\n",
      "Train Set Loss: 73.65\n",
      "Test Set Loss: 79.27\n",
      "Train set accuracy for a single minibatch: 56.25%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 9, Iteration 0\n",
      "Train Set Loss: 72.88\n",
      "Test Set Loss: 78.83\n",
      "Train set accuracy for a single minibatch: 46.88%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 9, Iteration 1\n",
      "Train Set Loss: 70.87\n",
      "Test Set Loss: 79.54\n",
      "Train set accuracy for a single minibatch: 53.12%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 9, Iteration 2\n",
      "Train Set Loss: 72.61\n",
      "Test Set Loss: 79.05\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 9, Iteration 3\n",
      "Train Set Loss: 72.04\n",
      "Test Set Loss: 78.69\n",
      "Train set accuracy for a single minibatch: 65.62%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 9, Iteration 4\n",
      "Train Set Loss: 58.74\n",
      "Test Set Loss: 77.63\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 10, Iteration 0\n",
      "Train Set Loss: 66.41\n",
      "Test Set Loss: 78.03\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 10, Iteration 1\n",
      "Train Set Loss: 72.98\n",
      "Test Set Loss: 78.23\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 10, Iteration 2\n",
      "Train Set Loss: 67.55\n",
      "Test Set Loss: 78.10\n",
      "Train set accuracy for a single minibatch: 40.62%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 10, Iteration 3\n",
      "Train Set Loss: 67.70\n",
      "Test Set Loss: 77.95\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 10, Iteration 4\n",
      "Train Set Loss: 62.51\n",
      "Test Set Loss: 77.99\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 11, Iteration 0\n",
      "Train Set Loss: 63.74\n",
      "Test Set Loss: 77.56\n",
      "Train set accuracy for a single minibatch: 56.25%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 11, Iteration 1\n",
      "Train Set Loss: 66.84\n",
      "Test Set Loss: 78.14\n",
      "Train set accuracy for a single minibatch: 65.62%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 11, Iteration 2\n",
      "Train Set Loss: 65.15\n",
      "Test Set Loss: 78.98\n",
      "Train set accuracy for a single minibatch: 50.00%\n",
      "Test set accuracy for a single minibatch: 62.50%\n",
      "\n",
      "\n",
      "Epoch 11, Iteration 3\n",
      "Train Set Loss: 66.25\n",
      "Test Set Loss: 78.36\n",
      "Train set accuracy for a single minibatch: 75.00%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 11, Iteration 4\n",
      "Train Set Loss: 69.77\n",
      "Test Set Loss: 78.44\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 12, Iteration 0\n",
      "Train Set Loss: 62.34\n",
      "Test Set Loss: 78.84\n",
      "Train set accuracy for a single minibatch: 56.25%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 12, Iteration 1\n",
      "Train Set Loss: 66.35\n",
      "Test Set Loss: 79.42\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 12, Iteration 2\n",
      "Train Set Loss: 59.10\n",
      "Test Set Loss: 80.30\n",
      "Train set accuracy for a single minibatch: 65.62%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 12, Iteration 3\n",
      "Train Set Loss: 71.94\n",
      "Test Set Loss: 80.13\n",
      "Train set accuracy for a single minibatch: 68.75%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 12, Iteration 4\n",
      "Train Set Loss: 63.74\n",
      "Test Set Loss: 80.55\n",
      "Train set accuracy for a single minibatch: 62.50%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 13, Iteration 0\n",
      "Train Set Loss: 65.28\n",
      "Test Set Loss: 80.80\n",
      "Train set accuracy for a single minibatch: 59.38%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
      "\n",
      "\n",
      "Epoch 13, Iteration 1\n",
      "Train Set Loss: 62.41\n",
      "Test Set Loss: 80.90\n",
      "Train set accuracy for a single minibatch: 75.00%\n",
      "Test set accuracy for a single minibatch: 59.38%\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "Epoch 66, Iteration 0\n",
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      "\n",
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      "Epoch 66, Iteration 1\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "\n",
      "Epoch 82, Iteration 4\n",
      "Train Set Loss: 27.18\n",
      "Test Set Loss: 122.24\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
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      "\n",
      "\n",
      "Epoch 83, Iteration 0\n",
      "Train Set Loss: 26.72\n",
      "Test Set Loss: 122.70\n",
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      "\n",
      "\n",
      "Epoch 83, Iteration 1\n",
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      "Test Set Loss: 123.92\n",
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      "\n",
      "\n",
      "Epoch 83, Iteration 2\n",
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      "\n",
      "\n",
      "Epoch 83, Iteration 3\n",
      "Train Set Loss: 26.93\n",
      "Test Set Loss: 122.97\n",
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      "\n",
      "\n",
      "Epoch 83, Iteration 4\n",
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      "Test Set Loss: 123.81\n",
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      "\n",
      "\n",
      "Epoch 84, Iteration 0\n",
      "Train Set Loss: 26.92\n",
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      "\n",
      "\n",
      "Epoch 84, Iteration 1\n",
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      "\n",
      "\n",
      "Epoch 84, Iteration 2\n",
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      "\n",
      "\n",
      "Epoch 84, Iteration 3\n",
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      "\n",
      "\n",
      "Epoch 84, Iteration 4\n",
      "Train Set Loss: 23.50\n",
      "Test Set Loss: 124.62\n",
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      "\n",
      "\n",
      "Epoch 85, Iteration 0\n",
      "Train Set Loss: 23.47\n",
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      "\n",
      "\n",
      "Epoch 85, Iteration 1\n",
      "Train Set Loss: 25.43\n",
      "Test Set Loss: 123.51\n",
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      "\n",
      "\n",
      "Epoch 85, Iteration 2\n",
      "Train Set Loss: 26.42\n",
      "Test Set Loss: 124.12\n",
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      "\n",
      "\n",
      "Epoch 85, Iteration 3\n",
      "Train Set Loss: 23.41\n",
      "Test Set Loss: 124.92\n",
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      "\n",
      "\n",
      "Epoch 85, Iteration 4\n",
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      "Test Set Loss: 124.94\n",
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      "\n",
      "\n",
      "Epoch 86, Iteration 0\n",
      "Train Set Loss: 26.80\n",
      "Test Set Loss: 123.43\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 86, Iteration 1\n",
      "Train Set Loss: 24.05\n",
      "Test Set Loss: 125.02\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 86, Iteration 2\n",
      "Train Set Loss: 24.49\n",
      "Test Set Loss: 125.73\n",
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      "\n",
      "\n",
      "Epoch 86, Iteration 3\n",
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      "\n",
      "\n",
      "Epoch 86, Iteration 4\n",
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      "\n",
      "\n",
      "Epoch 87, Iteration 0\n",
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      "Test Set Loss: 122.82\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
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      "\n",
      "\n",
      "Epoch 87, Iteration 1\n",
      "Train Set Loss: 23.88\n",
      "Test Set Loss: 123.72\n",
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      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 87, Iteration 2\n",
      "Train Set Loss: 20.15\n",
      "Test Set Loss: 123.79\n",
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      "\n",
      "\n",
      "Epoch 87, Iteration 3\n",
      "Train Set Loss: 26.95\n",
      "Test Set Loss: 123.23\n",
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      "\n",
      "\n",
      "Epoch 87, Iteration 4\n",
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      "Test Set Loss: 123.49\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
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      "\n",
      "\n",
      "Epoch 88, Iteration 0\n",
      "Train Set Loss: 23.29\n",
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      "\n",
      "\n",
      "Epoch 88, Iteration 1\n",
      "Train Set Loss: 23.73\n",
      "Test Set Loss: 123.95\n",
      "Train set accuracy for a single minibatch: 90.62%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 88, Iteration 2\n",
      "Train Set Loss: 25.62\n",
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      "Train set accuracy for a single minibatch: 100.00%\n",
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      "\n",
      "\n",
      "Epoch 88, Iteration 3\n",
      "Train Set Loss: 24.29\n",
      "Test Set Loss: 123.69\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 88, Iteration 4\n",
      "Train Set Loss: 23.84\n",
      "Test Set Loss: 123.91\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 89, Iteration 0\n",
      "Train Set Loss: 25.61\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 89, Iteration 1\n",
      "Train Set Loss: 25.49\n",
      "Test Set Loss: 124.96\n",
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      "\n",
      "\n",
      "Epoch 89, Iteration 2\n",
      "Train Set Loss: 21.72\n",
      "Test Set Loss: 125.11\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
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      "\n",
      "\n",
      "Epoch 89, Iteration 3\n",
      "Train Set Loss: 22.04\n",
      "Test Set Loss: 125.38\n",
      "Train set accuracy for a single minibatch: 90.62%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 89, Iteration 4\n",
      "Train Set Loss: 23.71\n",
      "Test Set Loss: 125.38\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
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      "\n",
      "\n",
      "Epoch 90, Iteration 0\n",
      "Train Set Loss: 20.77\n",
      "Test Set Loss: 125.35\n",
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      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 90, Iteration 1\n",
      "Train Set Loss: 25.29\n",
      "Test Set Loss: 125.34\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 90, Iteration 2\n",
      "Train Set Loss: 23.17\n",
      "Test Set Loss: 125.42\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 90, Iteration 3\n",
      "Train Set Loss: 26.10\n",
      "Test Set Loss: 125.95\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 90, Iteration 4\n",
      "Train Set Loss: 22.25\n",
      "Test Set Loss: 125.62\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 91, Iteration 0\n",
      "Train Set Loss: 25.36\n",
      "Test Set Loss: 125.86\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 91, Iteration 1\n",
      "Train Set Loss: 18.34\n",
      "Test Set Loss: 126.48\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 91, Iteration 2\n",
      "Train Set Loss: 22.20\n",
      "Test Set Loss: 126.77\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 91, Iteration 3\n",
      "Train Set Loss: 24.45\n",
      "Test Set Loss: 127.04\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 91, Iteration 4\n",
      "Train Set Loss: 25.97\n",
      "Test Set Loss: 127.21\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 92, Iteration 0\n",
      "Train Set Loss: 24.70\n",
      "Test Set Loss: 127.05\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 92, Iteration 1\n",
      "Train Set Loss: 21.70\n",
      "Test Set Loss: 126.94\n",
      "Train set accuracy for a single minibatch: 90.62%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 92, Iteration 2\n",
      "Train Set Loss: 20.38\n",
      "Test Set Loss: 127.71\n",
      "Train set accuracy for a single minibatch: 87.50%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 92, Iteration 3\n",
      "Train Set Loss: 25.67\n",
      "Test Set Loss: 127.96\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
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      "\n",
      "\n",
      "Epoch 92, Iteration 4\n",
      "Train Set Loss: 23.04\n",
      "Test Set Loss: 128.18\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 93, Iteration 0\n",
      "Train Set Loss: 24.32\n",
      "Test Set Loss: 127.23\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 93, Iteration 1\n",
      "Train Set Loss: 24.12\n",
      "Test Set Loss: 127.36\n",
      "Train set accuracy for a single minibatch: 90.62%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 93, Iteration 2\n",
      "Train Set Loss: 20.95\n",
      "Test Set Loss: 127.82\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 93, Iteration 3\n",
      "Train Set Loss: 20.73\n",
      "Test Set Loss: 126.39\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 93, Iteration 4\n",
      "Train Set Loss: 23.82\n",
      "Test Set Loss: 126.42\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 94, Iteration 0\n",
      "Train Set Loss: 22.25\n",
      "Test Set Loss: 126.99\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 94, Iteration 1\n",
      "Train Set Loss: 21.41\n",
      "Test Set Loss: 128.53\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 94, Iteration 2\n",
      "Train Set Loss: 23.78\n",
      "Test Set Loss: 129.53\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 46.88%\n",
      "\n",
      "\n",
      "Epoch 94, Iteration 3\n",
      "Train Set Loss: 24.07\n",
      "Test Set Loss: 128.66\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 94, Iteration 4\n",
      "Train Set Loss: 23.09\n",
      "Test Set Loss: 127.80\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 95, Iteration 0\n",
      "Train Set Loss: 22.08\n",
      "Test Set Loss: 128.16\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 95, Iteration 1\n",
      "Train Set Loss: 24.69\n",
      "Test Set Loss: 128.09\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 50.00%\n",
      "\n",
      "\n",
      "Epoch 95, Iteration 2\n",
      "Train Set Loss: 19.16\n",
      "Test Set Loss: 127.93\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 95, Iteration 3\n",
      "Train Set Loss: 24.88\n",
      "Test Set Loss: 128.39\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 95, Iteration 4\n",
      "Train Set Loss: 21.77\n",
      "Test Set Loss: 128.34\n",
      "Train set accuracy for a single minibatch: 90.62%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 96, Iteration 0\n",
      "Train Set Loss: 19.75\n",
      "Test Set Loss: 128.60\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 96, Iteration 1\n",
      "Train Set Loss: 23.97\n",
      "Test Set Loss: 128.89\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 96, Iteration 2\n",
      "Train Set Loss: 22.98\n",
      "Test Set Loss: 129.64\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 96, Iteration 3\n",
      "Train Set Loss: 24.35\n",
      "Test Set Loss: 129.82\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 96, Iteration 4\n",
      "Train Set Loss: 22.05\n",
      "Test Set Loss: 130.25\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 97, Iteration 0\n",
      "Train Set Loss: 21.81\n",
      "Test Set Loss: 129.91\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 97, Iteration 1\n",
      "Train Set Loss: 22.16\n",
      "Test Set Loss: 130.58\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 97, Iteration 2\n",
      "Train Set Loss: 22.61\n",
      "Test Set Loss: 131.13\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 97, Iteration 3\n",
      "Train Set Loss: 23.05\n",
      "Test Set Loss: 131.61\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 97, Iteration 4\n",
      "Train Set Loss: 21.41\n",
      "Test Set Loss: 131.82\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 98, Iteration 0\n",
      "Train Set Loss: 20.24\n",
      "Test Set Loss: 131.59\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 98, Iteration 1\n",
      "Train Set Loss: 22.93\n",
      "Test Set Loss: 131.16\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 98, Iteration 2\n",
      "Train Set Loss: 21.53\n",
      "Test Set Loss: 131.01\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 98, Iteration 3\n",
      "Train Set Loss: 21.25\n",
      "Test Set Loss: 132.24\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 56.25%\n",
      "\n",
      "\n",
      "Epoch 98, Iteration 4\n",
      "Train Set Loss: 23.41\n",
      "Test Set Loss: 131.30\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 99, Iteration 0\n",
      "Train Set Loss: 19.34\n",
      "Test Set Loss: 133.30\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 99, Iteration 1\n",
      "Train Set Loss: 21.24\n",
      "Test Set Loss: 133.76\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 99, Iteration 2\n",
      "Train Set Loss: 22.40\n",
      "Test Set Loss: 134.36\n",
      "Train set accuracy for a single minibatch: 93.75%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 99, Iteration 3\n",
      "Train Set Loss: 24.55\n",
      "Test Set Loss: 134.63\n",
      "Train set accuracy for a single minibatch: 96.88%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n",
      "Epoch 99, Iteration 4\n",
      "Train Set Loss: 19.59\n",
      "Test Set Loss: 134.79\n",
      "Train set accuracy for a single minibatch: 100.00%\n",
      "Test set accuracy for a single minibatch: 53.12%\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "num_epochs = 100\n",
    "loss_hist = []\n",
    "test_loss_hist = []\n",
    "counter = 0\n",
    "num_steps = 100\n",
    "\n",
    "# Outer training loop\n",
    "for epoch in range(num_epochs):\n",
    "    iter_counter = 0\n",
    "    train_batch = iter(train_loader)\n",
    "\n",
    "    # Minibatch training loop\n",
    "    for data, targets in train_batch:\n",
    "        data = data.to(device)\n",
    "        targets = targets.to(device)\n",
    "\n",
    "        # forward pass\n",
    "        net.train()\n",
    "        spk_rec, mem_rec = net(data)\n",
    "\n",
    "        # initialize the loss & sum over time\n",
    "        loss_val = torch.zeros((1), dtype=dtype, device=device)\n",
    "        for step in range(num_steps):\n",
    "            loss_val += loss(mem_rec[step], targets)\n",
    "\n",
    "        # Gradient calculation + weight update\n",
    "        optimizer.zero_grad()\n",
    "        loss_val.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        # Store loss history for future plotting\n",
    "        loss_hist.append(loss_val.item())\n",
    "\n",
    "        # Test set\n",
    "        with torch.no_grad():\n",
    "            net.eval()\n",
    "            test_data, test_targets = next(iter(test_loader))\n",
    "            test_data = test_data.to(device)\n",
    "            test_targets = test_targets.to(device)\n",
    "\n",
    "            # Test set forward pass\n",
    "            test_spk, test_mem = net(test_data)\n",
    "\n",
    "            # Test set loss\n",
    "            test_loss = torch.zeros((1), dtype=dtype, device=device)\n",
    "            for step in range(num_steps):\n",
    "                test_loss += loss(test_mem[step], test_targets)\n",
    "            test_loss_hist.append(test_loss.item())\n",
    "\n",
    "            # Print train/test loss/accuracy\n",
    "            if counter % 1 == 0:\n",
    "                train_printer(\n",
    "                    data, targets, epoch,\n",
    "                    counter, iter_counter,\n",
    "                    loss_hist, test_loss_hist,\n",
    "                    test_data, test_targets)\n",
    "            counter += 1\n",
    "            iter_counter +=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cbfc55ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Loss\n",
    "fig = plt.figure(facecolor=\"w\", figsize=(10, 5))\n",
    "plt.plot(loss_hist)\n",
    "plt.plot(test_loss_hist)\n",
    "plt.title(\"Loss Curves\")\n",
    "plt.legend([\"Train Loss\", \"Test Loss\"])\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "a570a55f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fxjvf+U7cfvvt8mCeccYZOP3003Haaadh//33x8qVK3H77bdzDyUGg8Fg1IU1AwWccvVC/HvR2lYPhcFgtCFc18VoqdKSn6Qde2bPni1/pk2bBsuy5P+FQgHTp0/H73//exx22GHo6urC9ddfjw0bNuBjH/sYtt12W/T09GDvvffGjTfeqCxXT73bcccdcdFFF+Ezn/kM+vr6sP322+PKK68c1/699957ccABByCfz2POnDk466yzUKlU5Pt//OMfsffee6O7uxtbbLEFjjzySIyMjAAA7rnnHhxwwAHo7e3F9OnTccghh2Dp0qXjGk81tFRR+shHPoKPfOQjke9bloVzzz0X5557bvMGxWAwGIxJi3sWrcU9i9Yhn0nh8D22bvVwGAxGm2GsbOPNZ9/WknW/cP4x6Mk1JjQ/88wz8eMf/xhXX3018vk8CoUC3va2t+HMM8/E1KlT8Y9//AOf+tSnsPPOO+PAAw+MXM6Pf/xjXHDBBfjf//1f/PGPf8R//dd/4d3vfjfmzZtX85hWrlyJ4447Dqeccgp+85vf4KWXXsLnP/95dHV14dxzz8Xq1avxsY99DBdffDE+9KEPYWhoCPfffz9c10WlUsEHP/hBfP7zn8eNN96IUqmEhQsXTnhz4JYSJQaDwWAwmomK483Y2k5Leq0zGAxGU3D66afjxBNPVF77+te/Lv/+8pe/jFtvvRV/+MMfYonScccdh9NOOw2AR75+8pOf4J577qmLKP3iF7/Adttth5/97GewLAvz5s3DqlWrcOaZZ+Lss8/G6tWrUalUcOKJJ2KHHXYAAOy9994AgI0bN2JgYAAnnHACdtllFwDAm970pprHUCuYKDEYDAZjs4GgR8yTGAyGCd3ZNF44/5iWrbtR2H///ZX/bdvG97//fdx0001YuXIlisUiisUient7Y5ezzz77yL9Fit/atfWlLr/44os46KCDFBXokEMOwfDwMFasWIF9990XRxxxBPbee28cc8wxOProo3HSSSdhxowZmDlzJk455RQcc8wxOOqoo3DkkUfiIx/5CObMmVPXWJKiLVzvGAwGg8FoBkQNgJOwFoDBYGxesCwLPblMS34amUamE6Af//jH+MlPfoIzzjgDd999N5566ikcc8wxKJVKscvRTSAsy4LjOHWNydQLVdyTLctCOp3GHXfcgX/9619485vfjMsuuwx77LEHFi9eDAC4+uqr8dBDD+Hggw/GTTfdhN133x0PP/xwXWNJCiZKDAaDwdhsIPgRK0oMBmNzwv33348PfOAD+OQnP4l9990XO++8M1555ZWmjuHNb34zFixYoJhWLFiwAH19fdhmm20AeITpkEMOwXnnnYcnn3wSuVwOt9xyi/z8fvvth29+85tYsGAB9tprL9xwww0TOmZOvWMwGAzGZgOhJCV1l2IwGIzJgF133RV/+tOfsGDBAsyYMQOXXHIJ1qxZMyF1PgMDA3jqqaeU12bOnInTTjsN8+fPx5e//GV86UtfwqJFi3DOOefga1/7GlKpFB555BHcddddOProo7H11lvjkUcewbp16/CmN70JixcvxpVXXon3v//9mDt3LhYtWoSXX34Zn/70pxs+fgomSs3EkgeAgRXAzocDfbNaPRoGg8HY7BAoSkyUGAzG5oPvfOc7WLx4MY455hj09PTgC1/4Aj74wQ9iYGCg4eu65557sN9++ymvnXzyybjmmmvwz3/+E9/4xjew7777YubMmfjsZz+Lb3/72wCAqVOn4r777sP8+fMxODiIHXbYAT/+8Y9x7LHH4o033sBLL72Ea6+9Fhs2bMCcOXPwpS99CV/84hcbPn4Ky53k02qDg4OYNm0aBgYGMHXq1NYO5op3AmueBT7xJ2C3I1s7FgaDwdgM8ev7X8d3//EiDtp5C9z4hXe0ejgMBqPFKBQKWLx4MXbaaSd0dXW1ejiMBiHuuNbCDbhGqZno3cr7PbKuteNgMBiMzRysKDEYDAajGpgoNRNMlBgMBqOlcNj1jsFgMBgJwUSpmWCixGAwGC0Fu94xGAwGIymYKDUTvVt6v0fWt3YcDAaDsZnCYTMHBoPBYCQEE6VmghUlBoPBaClciNS7Fg+EwWAwGG0PJkrNBBMlBoPBaCmEkDTJDV8ZDAaD0QAwUWomOPWOwWAwWgqXzRwYDAaDkRBMlJoJqijxQ5rBYDCaDlmj5LR2HAwGg8FofzBRaiZ6fEXJLgLFodaOhcFgMDZDuGzmwGAwGIyEYKLUTOR6gNwU72+uU2IwGIymQxAk5kkMBoPBqAYmSs0G1ykxGAxGyyD4EStKDAajU2FZVuzPKaecUveyd9xxR8yfP79hn+t0ZFo9gM0OvVsBm5awosRgMBgtAJs5MBiMTsfq1avl3zfddBPOPvtsLFq0SL7W3d3dimFNSrCi1GywRTiDwWC0DIE9eGvHwWAw2hSuC5RGWvOT8MY0e/Zs+TNt2jRYlqW8dt999+Ftb3sburq6sPPOO+O8885DpVKR3z/33HOx/fbbI5/PY+7cufjKV74CADjssMOwdOlSfPWrX5XqVL24/PLLscsuuyCXy2GPPfbAddddp7wfNQYA+MUvfoHddtsNXV1dmDVrFk466aS6xzFesKLUbHDqHYPBYLQMDitKDAYjDuVR4KK5rVn3/64Ccr3jWsRtt92GT37yk7j00kvxrne9C6+99hq+8IUvAADOOecc/PGPf8RPfvIT/O53v8Oee+6JNWvW4OmnnwYA3Hzzzdh3333xhS98AZ///OfrHsMtt9yC//mf/8H8+fNx5JFH4u9//ztOPfVUbLvttjj88MNjx/DYY4/hK1/5Cq677jocfPDB2LhxI+6///5x7ZPxgIlSs8GKEoPBYLQMQY1SS4fBYDAYE4ILL7wQZ511Fk4++WQAwM4774wLLrgAZ5xxBs455xwsW7YMs2fPxpFHHolsNovtt98eBxxwAABg5syZSKfT6Ovrw+zZs+sew49+9COccsopOO200wAAX/va1/Dwww/jRz/6EQ4//PDYMSxbtgy9vb044YQT0NfXhx122AH77bffOPdK/WCi1GwwUWIwGIyWgRUlBoMRi2yPp+y0at3jxOOPP45HH30UF154oXzNtm0UCgWMjo7iwx/+MObPn4+dd94Z733ve3Hcccfhfe97HzKZxlGCF198UapYAocccgh++tOfAkDsGI466ijssMMO8r33vve9+NCHPoSenvHvm3rANUrNRtc073dxsLXjYDAYjM0RXKPEYDDiYFle+lsrfsZREyTgOA7OO+88PPXUU/Ln2WefxSuvvIKuri5st912WLRoEX7+85+ju7sbp512Gt797nejXC43YOcF0OubXNeVr8WNoa+vD0888QRuvPFGzJkzB2effTb23Xdf9Pf3N3R8ScFEqdlIZb3fdmNPSAaDwWBUBytKDAZjMuOtb30rFi1ahF133TX0k0p5YX93dzfe//7349JLL8U999yDhx56CM8++ywAIJfLwbbtcY3hTW96Ex544AHltQULFuBNb3qT/D9uDJlMBkceeSQuvvhiPPPMM1iyZAnuvvvucY2pXnDqXbORSnu/nUr85xgMBoPRcAh+xESJwWBMRpx99tk44YQTsN122+HDH/4wUqkUnnnmGTz77LP47ne/i2uuuQa2bePAAw9ET08PrrvuOnR3d2OHHXYA4PVHuu+++/DRj34U+XweW265ZeS6Vq5ciaeeekp5bfvtt8c3vvENfOQjH8Fb3/pWHHHEEfjb3/6Gm2++GXfeeScAxI7h73//O15//XW8+93vxowZM/DPf/4TjuNgjz32mLB9FgdWlJqNNCtKDAaD0So4rvqbwWAwJhOOOeYY/P3vf8cdd9yBt7/97XjHO96BSy65RBKh6dOn41e/+hUOOeQQ7LPPPrjrrrvwt7/9DVtssQUA4Pzzz8eSJUuwyy67YKuttopd149+9CPst99+ys9f//pXfPCDH8RPf/pT/PCHP8See+6JX/7yl7j66qtx2GGHVR3D9OnTcfPNN+M973kP3vSmN+GKK67AjTfeiD333HNC91sULNed3NNqg4ODmDZtGgYGBjB16tRWDwdYdCtw438Cc/cDvnBPq0fDYDAYmxXO+9vzuPrBJdhySg6PffuoVg+HwWC0GIVCAYsXL8ZOO+2Erq6uVg+H0SDEHddauAErSs1G2s92tDn1jsFgMJoNlxUlBoPBYCQEE6VmQ5g5OJx6x2AwGM2Gy2YODAaDwUgIJkrNhqhRYjMHBoPBaDpkjRJLSgwGg8GoAiZKzQbbgzMYDEbL4EIoSi0eCIPBYDDaHkyUmg1Ro8SKEoPBYDQdDtuDMxgMAya5t9lmh0YdTyZKzQYrSgwGg9EycB8lBoNBkc16cdno6GiLR8JoJMTxFMe3XnDD2WYjzWYODAaD0Tpw6h2DwQiQTqcxffp0rF27FgDQ09MDy7JaPCpGvXBdF6Ojo1i7di2mT5+OdDo9ruUxUWo2UmwPzmAwGK2C43i/Oc2GwWAIzJ49GwAkWWJ0PqZPny6P63jARKnZEESJFSUGg8FoOtjMgcFg6LAsC3PmzMHWW2+Ncpnjs05HNpsdt5IkwESp2UhzjRKDwWC0CmzmwGAwopBOpxsWYDMmB9jModkQZg6uHVQVMxgMBqMpELdd1+X0OwaDwWDEg4lSs5EmIt4kUJVGS1xrxWAwOgeUHDFPYjAYDEYcmCg1GyliU9jhdUq/f3Q53nz2bfjdwmWtHgqDwWAkAuVGnH7HYDAYjDgwUWoy3BRRlDq86ewZf3oGAHDWzc+2eCQMBoORDJQcsaEDg8FgMOLARKnJeGjJYPAPW4QzGAxGU0FFJFaUGAwGgxEHJkpNxrJNBdiu38isw1PvGAwGo9PgcI0Sg8FgMBKCiVKTUXZcVIQr+yQwc2AwGIxOAtcoMRgMBiMpmCg1GbbtoAzfo7/DFaV8hk8fBoPRWXCVGiUmSgwGg8GIBke6TUbFcVERRKnDa5SYKDEYjE6DWqPUunEwGAwGo/3BkW6TUXHcSaMo5TLcvZrBYHQW1BolZkoMBoPBiAYTpSajYjuwpaLU2USJFSUGg9FpYEWJwWAwGEnBkW6TUbZJ6l2H91FiosRgMDoNDtuDTwgcx8V1Dy3BcysHWj0UBoPBaBgy1T/CaCRsx0XZTQMWOl5RyjFRYjAYHQc2c5gI/O2ZVfjOX54HACz5/vEtHg2DwWA0BhzpNhllxwnswTu8Rimf5RolBoPRWaCKEvOkxuHlN4ZaPQQGg8FoOJgoNRk2Tb3rcEUpn26P02fjSAn/fHY1ShWn1UNhMBhtDrYHnxhk2+R5wGAwGI0E39maDNX1zm7tYMYJmnrXSveoH9++CKf99gn867nVLRsDg8HoDDhs5jAhYKLEYDAmI/jO1mRUHIeYOXS4okSIUrGFas6G4RIAYNNIqWVjYDAYnQHKjRxmSg1DNm21eggMBoPRcDBRajIqtouyqFHq9NS7LCFK5dYRJdtXszjmYTAY1cCpdxMDVpQYDMZkBN/ZmoyK46LiTg578JQVzCAWKq1LIxSzwhz0MBiMaojqo3Tfy+twxh+fxnCxs+/LrQIlStzIl8FgTBYwUWoyKrYzacwc6LNwrNQ6olRhosRgMBLCiVCUfnnfa/j9YyvwwCvrWjGsjkeOEKWyzfdiBoMxOcBEqckoK2YOnU2UaJDRUkWJU+8YDEZCuIo9ePCPcM1sZb1lJyObCTIMii18HjAYDEYjwUSpyfDswSdHjZJClFpZo8SKEoPBSAhVUQpeFy/zfaQ+pFPtYe7DYDAYjURLiVKlUsG3v/1t7LTTTuju7sbOO++M888/H44T3GRd18W5556LuXPnoru7G4cddhief/75Fo56fPBc77zd7nYAUXpqeT/+33WPY+mGkdB77ZZ6x/ENg8GoBsX1zpCG53CMXxeoOsdEicFgTBa0lCj94Ac/wBVXXIGf/exnePHFF3HxxRfjhz/8IS677DL5mYsvvhiXXHIJfvazn+HRRx/F7NmzcdRRR2FoqDO7gFecoOGs0wFE6aZHl+HW59fg78+EexTR2di2MHOY5Ll3D7++ARf+4wUUypzWwmDUC8X1jsTz4vZh84xLXaC7rcj3KAaDMUnQUqL00EMP4QMf+ACOP/547LjjjjjppJNw9NFH47HHHgPgPdDmz5+Pb33rWzjxxBOx11574dprr8Xo6ChuuOGGVg69blRI6p1TaX+iJFLqTDOEygxiCx+Mm4s9+E/ueBm/un8xHnptQ6uHwmB0LFTXO5e87iq/GbWB7suSzYoSg8GYHGgpUXrnO9+Ju+66Cy+//DIA4Omnn8YDDzyA4447DgCwePFirFmzBkcffbT8Tj6fx6GHHooFCxYYl1ksFjE4OKj8tBMqjoOyKxSl9m+QKh54FcODjz4Yx1pIlDYXe/BRP72RFSUGo36o5Ii+7v3mGL8+OIqixDuRwWBMDmRaufIzzzwTAwMDmDdvHtLpNGzbxoUXXoiPfexjAIA1a9YAAGbNmqV8b9asWVi6dKlxmd/73vdw3nnnTezAxwFPUfKIkltp/34dwgmqbIgeKC1ppZlDUKM0uYmSOAaTXTljMCYSUTVKrv8Op97VB65RYjAYkxEtVZRuuukmXH/99bjhhhvwxBNP4Nprr8WPfvQjXHvttcrnLNLYFPBuyPprAt/85jcxMDAgf5YvXz5h468HnVajJIJzU18MpUaplal3zuaReieOBQdyDEb9cCJS70S90mSfcJkoKDVKbA/OYDAmCVqqKH3jG9/AWWedhY9+9KMAgL333htLly7F9773PZx88smYPXs2AE9ZmjNnjvze2rVrQyqTQD6fRz6fn/jB14mK46Ds7/ZOcL0LiFJ8jVJLU+/czSP1rrKZmFYwGBOKCHtwcf+w+fqqC45Ss8qKEoPBmBxoqaI0OjqKVEodQjqdlvbgO+20E2bPno077rhDvl8qlXDvvffi4IMPbupYGwUl9a4TiFLFe/iZiFK79FGqbC6KUkWk3k3yDWUwJhBq76RwvdJkv49MFOh+YzMHBoMxWdBSRel973sfLrzwQmy//fbYc8898eSTT+KSSy7BZz7zGQBeyt3pp5+Oiy66CLvttht22203XHTRRejp6cHHP/7xVg69blQcF2VZo9T+RCkwczCk3pFnYaNc7yq2g388uxoH7rQFZk/rSvQdZ3OpUXJ4xpvBGC9cmBUl8TortvVBUZQ49Y7BYEwStJQoXXbZZfjOd76D0047DWvXrsXcuXPxxS9+EWeffbb8zBlnnIGxsTGcdtpp2LRpEw488EDcfvvt6Ovra+HI60fFdlDpINc7oSSZZghpwNGo1Lt/L1qH//ndU3j/vnNx6cf2S/QdezNJmRHHYpLzQcYkxFChjOdXDeKAHWcilTLXlzYLau+kMGlixbY+uONMvXtqeT9uf34Nvvye3dCdSzdyaAwGg1E3WkqU+vr6MH/+fMyfPz/yM5Zl4dxzz8W5557btHFNJDwzB3+3O53jemdUlCbAzGH9cBEAsHEkOYkUgc8k50nyGLCZA6PTcNE/X8SNC5fjqpP3xxFvMteXNgtRrneyRomvr7qg2IPX4Xo3/86Xcc+iddhn2+l4716zGzgyBoPBqB8trVHaHOHVKHm7vRNS75KaOTSqRkmsp+IkX5747GSfCRaq3mRXzhiTD6sHCgCANYOFFo/EXJdE/+bUu/ow3tQ70SdurNz+E4gMBmPzAROlJoPag8PpBKLkmzkYggf6UqNS7+IUrCjYm4mtb0Wm3k3u7WRMPkg1tA1IiNpklpKmzcMUZqKgmDnUoSg5sgazUSNiMBiM8YOJUpPRafbgQsUoGx58qqLUIKIkFaXk0YqzGQQ4tuPK7WuHYJPBqAVC9W2Hc9dUl0T/bocxdiLG23A2sGdnpsRgMNoHTJSaDNvuNEUpOvVOyUlvVOqdb0deS+pd0HB28gY4dP9zHMfoNNht5NhYrUaJFdv64IyTKNmSqDZqRAwGgzF+MFFqMsqOExAlu/1zsYWSZEq9m4iGs+UYO/IoBESpIUNoS6hEaRJvKGNSQqTw1qIUTxRM6Xbe395vNnOoD+rEWe3PgyD1jpkSg8FoH7TU9W5zRMUO+ih1guudrFEyzBBOhOtdPal3gihN5plgShzbYVaewagF7aQoUUmJqheuTP1q8ngmCSgBrafhbFudIwwGg+GDFaUmwnVdzR68ttS7B19dj1X9YxMwMjNc1yXEJb6PUqFBDQZFEXAtD0tb1ihN3gcsp94xOhli4qMWpXiiYEq38/72fk/mCZeJhKsoSvXXKLWD6shgMBgCTJSaCBH8i9Q7q4bUu5fWDOITv34EX73pqYkYmhFlEtSUTX2UyLNwrNQ6e/DNIvXOMQd3DEYnoCKt7Vsv19CrxzWQJlY06kOjzBz4/sZgMNoJTJSaCDFTJlLvKpUSfn3/64maq64d9Bqxrh0qTtwANVAVw2zmQDuxt0ON0uR9wNLURw7kGJ0GOUnUBuduNde7NhhiR0JtOFv786CdzhEGg8EQYKLURFQ0RWnT0Ai++48Xcf3DSxN81wuUG0VIkqAaUVJSLeqYQTRB9lFK+LCkzSEnMU9SFLbJTAgZkxPiem4Ho4SoPkpCa+Lrqz6M1/VO2rO3QXomg8FgCDBRaiLEA0D0UbJ8M4dNo9UVJaGwNIqQJEFJIUqmhrNq8W4jlA7pjpWwGNiOqDeYbChVyHbyjCujwyBT79ogCHYNKhL9mxXb+uCMc+LMbiMyzWAwGAJMlJqIsq8KVFxPUUq5HlFK8lARM7L1dDyvF2qNksnMQYUY2+vrhvHgq+vrWmetrne2UrtT1yo7Aqqi1MKBMBh1oNJGaVWqJXh4omUyT7hMJBrXcJb3P4PBaB8wUWoihCpk+7s94xOlJORHEJVmKkq0LqZajRIQ5KX/1/VP4BO/fgQr63Dok6l3CWeeFaI0iR+wlLTyjCuj09BO1s+qihS+fzBRqg/jrVl12ugcSYqNIyX85qEl6E+QFcJgMDoTTJSaCKEKiNS7jOU9TJKQH/HwKNlO0wgBTb0zERc9nij4lrBrhwoAgA3DtRtPlKU7VkKipM0Iu66L0VL796eqFYo9eAcFEgwGQN0sW3/u0rYG1ITPNbzGSA56aOvJfLA7UFG65sHFOPsvz+O3jyxr9VAYDMYEgYlSEyHIhjBzyMInSglm3yhRqaeZXz2gD7uK44b6i0QpSrJJbR3jFN8pJ4xWaM2D47r46k1PYf/v3ok3Bgs1r7udUdG2k8HoJASKUutZSJSiJP5kxbY+jNfMQTwuOokoDRa8SbmhwuSbnGMwGB6YKDURuj14GskVJUocmpV+pxMd3dBBjyfEuASRMxlAVIMgZ66bTDlRFSXgmZUDGC3ZeG3dcM3rbmfQY9EknsxgNAzS9a4Nzl163zI54LFiWx/G64LaiQ1nBanjJsUMxuQFE6UmQqTeCUUpI4lSjYpS04iSq/2vrldXNgq+MlaRRKn2cZbIOpM8MFV7cFf+P9meW0rqneti00gJKzaNtnBE7YXHlmzEsg28P9oVlTZSlEwGDvRvVmzrA70X19NHqRP3v92BY2YwGLWBiVITEaTeeTVK2RoUpco4H0L1IKwoqf+bFCXbcWVqS9l2MFQo11QzRNdRSRBU6YrSZLX4LWupdx/55UM48pJ7MVgot3BU7YGX3xjCSVc8hHf/8N+tHgrDANd126qZKB0BHU6QetfU4UwaNMoevB3OkaRwJVFq8UAYDMaEgYlSEyFT71xNUSonIEp281Pv9FooXWEK1SiVHYXojBRtHPHje3H8pQ8kTk3Q66KqQa/dmay9OChptB0XyzeNolB2sGGY3ZaeXt7f6iEwYkAnLdphAsOkIgEBUWJ1oD4offUqTs3paNJ1sA3OkaQQ5zOfMwzG5EWm1QPYnGBrqXdZywbgJjJnoKShaal3lWSKUiZloeK4KJRtZVvWDRWxdqgIDBVRsh3kM+nq66zitKfDCSlKkzNnnB5zxw2cudohlanVqKcWjtE80HtXO6gFao2SIfWuDcY4GVCsOOjKVr/nC4jJrXY4R5JCPK4m2eOGwWAQsKLUREg3OAQPjwzsmmuUWqUo6cRFBBbd/sOwWHEUcjVG3PySjrnm1Du9RklazCZaXceABg+O48p9M9m2sx6UmpSKOpFYvnEUA2OTM42y0taKUvj1dhhjJ0JXVWp1Z+3EtOkg9a5zxsxgMGoDE6UmQq9RAnyilCT1jpCG5pk5qOvRH3ziedaV84hSoWwrs/vDxaA2Kck2AiqhSqIoKQ1nXbcjLWaTQHG9c4M6sCRkcrKj0xWlFZtG8a6L/419z7u91UOZEFAL/7a4Lg3kiL7cDkPsRJhSsWv6fgc2nGUzBwZj8oOJUhOhu94BnqFDIntwRVFqkplDJd71Tsym9eSIokQ+M0qJUsIxqzbYCYgSnR12Ju8MXzki2GSe1Ly+YhOFx5ZsavUQJhRlp7ZreqJhUpRc1+UapXFCP7S1Pqc6seFsUKPU4oEwGIwJAxOlJqJiTL2rJHqg0FqUWmfq6kXtqXe2auZQqif1ziV/15Z657jupJ3ho/uiVGN64mRHPTb07YROCgzrga3UKLX+WNG9LSZWTP2UGLVBrwutJUWcEtVOuh5cV/3NYDAmH5goNREiV99FCo5rARA1StUdgiiBqHcGvVCubYavWuqdGJEo2C2UHWWc1BY8CbmzHTexQ9bGkRLm3/my0juHNqntpIdtElDXw7Ji7DC5trMedDpRmuzHsL1rlMITK+0wxnZHqeKEaup0Dkzv+dWeb3SXd5aZw+Q0D2IwGAGYKDURdDZVqEpZ2HDd6nUW9Lv1pN796LZF2Oe82/HCqsHE39ED0Ipeo+TEK0rDRaooVR9zaH0xD8w/Pr4c8+98BVfe/3owHlK7M9mCz1KE0pakjmuyg147nRiwTLZzVUdFUUBbv62qeuS/Bvpa68fY7vjkVY/gkO/frZClUI2Sf8//4+MrsO95t2Ph4o2Ry9MzAzoFndgkl8Fg1AYmSk0EfRgUkAMAdFtFANVVIsX1ro7Uu4VLNqJUcfDC6lqIkl6jpP4vng3dpEapFFGjFGdAIQKpaql+FEMFb9n0QW3TPkqdLTKEoChKtF6JH9DKudWJasBkO1d1tJuiZEqzU1SmSX48GoFFa4YwXKxg9cCYfE0/tOJYf/0PT2OwUMGpVy+MXB7d/+1AppMiOH9aPBAGgzFhYKLURCiOcOgGAPSiAAAoVkmLU/oo1RFZjfn1QroqFAc9x7ysRRCyRom63pHvJKlRunHhMux5zm247+V1ITIVV88g9gEljbSP0mSb4aPHv1bDi8kO3RGw09CIc3XDcBGf+PXD+OW9rzVgRI2FUqPUBgqoS/QjU41JJ55DzUbQHDZ4TVdz9XsTfR7oUA1qOmf/c8NZBmPyg4lSE0ENGUbcLgBAr+UTpSqFr5Tg1KMoiXqhWuo59M/qDWhljVKGut5F1ChFbN83b34WxYqDH9z6Uk2pdyLgonVXtI9SJz1sk4CSSCZKKuj+6EQ1oBFB1ilXP4oHX92A7/3rpQaMqLFQjk8bBJT0kjEFup2YvtlsmExz9GNby63JVhSlzrmIHQPRZmzeGCyU8cobQ60eBqOBYKLURFASMeIrSlPgpS5UI0rlBilKtfSc0YmR/t1AUfJOo2LZUVSnkSo1SpT8zZ3eHbIjj5t9FsEXJUq0RmmyzQor9W3t1pemxYhLRRwstH8T1/GS+ieXbcKzKwcaNJrGQ3W9a/356hqCe9dAniYTbnp0GQ75/t0NC+CCFGe6L9XPiH2bTVtVl+eSR00H8aRJm8HAqB///dsncNRP7sOS9SOtHgqjQWCi1ERQYjDsK0o9IvWuitmBrdQo1W7mMFoWRKl+RUmf6RMPxp6c10C3UNFS76o0nH35jWH59w4ze8I1SjFPTDE2SjAdh8wQT7Jgh5JIVpRUlCL2x1+eWol9zr0df3hseSuGlRjjzUb73cJg++ZM6xrnaBqPdqtRokMwmb+0QXZgw3HHC2uxsn8MC5dEGyrUAmNtV0hR8v6f0ZOrurxOVZS4jxJDx8pN3uT3KlK/x+hsMFFqImjAMAovoJkiUu+qpNOprnf1pN7ZoTFUQ0mLGPQaIjEzK+zBi5o9+Fg5vkbpyeWb5N8VxzXUKMUpSm7oM6ZGkpMFVKmLIgabK8oRZg7P+w6Pz9fg9NgKjJfUj5AU13Y8H9qpj5KeVhc0qI7+zGRAo1OSjSmLEZ+Z2ZsLvRa1PKCziGqgSHbQoBkTCpmW2jl8n1EFTJSaCBHUWxYw7BOl3qSpd1RRqpEo2YSExLnPhdcZT1zEv1H24BQmxeypZf3y75LtGOzIq6feRb3WjgHjeBDViLeRKYZrhwq4Z9Hatnroj5YqMm00CsUIoiTO9VYH59Uw3rSddrdWVs7XFkfB+u4xBbqT7d4BmFPl6oVLU5xjzBzEv9O6s/K1jSMl4zLVPlbtfb1SiKG24WXHaBHktcYnxaQBE6UmQlxAXZk0Rlzf9c5XlKoRGPqAe/mNIXz4igX490trE62XmiqIoNFxXDy3ciA2FS9k5qA3nBU1StmgRimqfsqsKPUHy66EiVLcA9M07nYPGMcDpRfNBNUo/e/Nz+GUqx/FY0s3Vf9wE1C2HRz543tx7E/vi50J1+vUBMS53g5Oa3GgD9R6SGrSJs2tQjvVKOlrD1Lvwq9NJojrohGXgskMAwjPoMtmrOS1dUPF2PEB7X+9UphMLRibNwJHSD4nJguYKDURIrjvyqYwIlLvEtYoUWKw4LUNeHTJJvzxiRWJ1ktn5MVD6PJ7X8MJlz2Ab978bOT3dPIWNnPwfgd9lGIUpbKuFjl4dW1Qo1SynbpS76Jea8eAcTyg+3WilLO1Q965GBXMNBsbhktYNVDAkg2jShqnjkKEoiTqumoxMGkFTA1Qa0G9RGTtUAGX3PEyVvVPbC59VHpsKxBVR6MYPEyyewdASEsD9n+UQ2DUvqXnp7jHRI3PtJx2Bps5MHRM1qb3mzOYKDURUlHKpjHsK0qBmUO1GqXwRZfU1GGUECWh+Fx29ysAvK7pUYhTlOgDUtYoVZyQU54cq0YE9e0p22E1qtbUO5piNdliHRrsU0LZyBn6IFWtPXbeEHGsE0Tp+VUDuHHhMuX8o9eBQpSEotTmqTzjDRLtOoP83y1cjkvvegXXPby05nXWAnodN/vc2jhSUtK99N3ryqAmeG0ypsw0MvVOrSei5676OfE/VcPXRilK5BJtl/tPEkj1oHOGzJhg2IYJAkZnI9PqAWxOEMFuVzaNUeQBAFMsUaNUpeGsgRgUEvZTGjUoSt3ZdNXvCzOHXCaFkkaC6D1Aut6V7ciHnE4E9ZtISevBBFRTlDav1DtVUWrs7HfFdpBJp+Q62qVGgFp7C1X0O39+Dk8s68e82X3Yb/sZAKJT76ThR5srSuMmShGBazUIV8pR4k45EaDnUzNrlEoVB2+94A4AwCsXHotsOhVWPQxKy2S7dwA09a6xihI993S1SnyO3sej1Op6yX6rEfRR6pwxMyYWAXnmc2KygIlSEyEChnwmhWG/j1Ivol3vXNfFf9/wBKZ1Z82KUhVyJTBWDgKhIP0vDSC+x4wgRr25tEdkIh6KXaJGqRJXo6SOVX9gl2yD611c/VQlvD8mc+pdJcLMYbyzrzc/sQLfuuU5XPGpt8lltUuq2uAYbVjsnT8DY2XlN6C6KyppaP5+qsUSvxWg11I9z9a4OpE4iOM90TP4dPmNXpfruvjK757C7Kl5fOv4NyvvbRgJgvLRko1p3eEECmON0iS7dwCNbZugkqPg9SSpd4lqlDpo/7M9OENHoCi1eCCMhoGJUhMhAtB8No0Rv4+SMHMwpd6tGyrin8+uAQDsslVv6P2k7ndUUZJjyFTPuhQBZk8ug02jZSXgpA+GbiX1LkJR0oig/sA2mTnEKkqGiHAyK0qlCHI03u18+PUNGCvbeHzpJkmM24VkqoqSb0LiD42SOaqMKql3dnulEkbBHqeaoRKR5E9nk8XzRGCizEcArxfb355eBQD43+PeBMsKmpualMTIGiXQY9DQIbYFxK5oRPBGT7G4hrO2nHgJvhBJlBSy3zkHgGuUGDrY9W7ygWuUmggRxHRlUhjRFSWDOkQJzqjBIrlQR42SqijFIyBK3mcrClEKbgLCzKFQjrMHr5J6Z6xRqs31TiFyHfSwTYKoAHi8aWVj5cA2viRT1dpjKmywEChKQjUS5w0dI70O6MNJkKl2V5TG67jmaMFq0jSgZrkC1kvkkoASHP3+Yeo3Fq5RCisC7TJR0Eg0Mh2IXmNxJF/8m8jMoUMVJcdw/jA2b5jSeRmdDSZKTYRq5qD1UTKk3tGUohFDHUFyRSlsD55PQJTE8nvynvBIZ/HpPUBRlOpMvSvX6npnUK7o5yfbbE6UUjfewEfU/pRJH6t2CVQGSXqdIENie0UQ7LpuZB8luT1tkkoYBZXojE9R8paR7HvNmvm0NZOVRgYQ2XTwCNNrLosGpTGsKPm/J7EaDTRWPVRTPaPTRgNFqXrqXadmAzTSTZAxOSBO5ck44bK5golSExGYOaQwKuzBRR8lA8EQStDH0nfhn+5p2NVSHerqU5T8MdSSeucTIcX1jszkCkXJdtxIG2edBOkTy6UGp961uYhQM0zbC4yf1IhziBKldrnBDxpc70RgJsiPPllAd1O7bU8UFLvlOs5bPbBMur1iH060+qrXvDXyeGRSQaqdPhlTqIRr1/Q1B/bg4dcmE0z1QuNdlve3+fWodUY9HzrW9c4f6iQ8ZRh1gl3vJh+YKDUR4sLJZ9IYhlCUPKLUP1pW+goB3mz/VAzje9mrsK21Hh9N/1t5v5qi5LouVg+MKX2UTKl3UYGSCHB682GiZKpRAoDhgtlBSx+rnoJTsk0NZ104josv3fAEfnTbIm1s1bd9MiFqe8d7MxaBCyWq7WLmMETOJUHoxENIjFWfLDCm3rWJi18U6KGtS1Gqk4jINMYJfqDr42nk+uiidFWenhvifqMTURnoEgo12SZZgMaqh9H24GaiRI93VGP1KCe9dgfXKDF0sOvd5AObOTQRSsNZ0UfJKiIFB9c9vBTXPbwUl35sP9iOg9fXjWDvbabhM5lb5fcrUNPlqilKv31kGb795+cwd1pXsAyiagmMlm1MyYdPBTHeXkPqHb0JUNI1FGE1HDfzD/g1MiHXOxevrx/B359Zja5sCl8/Zo9gbBGpaAKd9LBNgqj0sXETpRIlSmImrD0iRVPqnQhihQOjPkPdkal34zRzCClKiWuUmvNA14lRI69NOnb9flgwuCG6mqZkqlGabJMsQHBO1LppC15bjwv+/iIu/NBeeKtvxx+VeqcfVvE/nRSLIkp2hxKlZhmiMDoH7Ho3+cCKUhNBa5RGEJAX0XQWAL5y45P46k1P47K7X8XzS9fg1HRAlKZDVZyKFQdPL+/HF697DEs3jITW98LqQQDAqoFg+SLFL0Ny+031TwBwQvk2nJr+lzRzUFLvyE0gnbKQ85dHm4SqY01QoxTqo+RgYMxrFlkoO0oAU01RmnQ1ShNElEQwOVKiFvKN23eFso0Fr66vy1BBMXMoqTVKFakoaQScFoV3iJlDnHNYEtRLRAJjjAkmSjWk1NYKpfFwRVeUTDVK6vdNisBku3cAAaGp9X7x8V89ghdXD+Lk/1sYLCuK2GuLlioWbZYdcS1SwtVRqXdsD84gcF2XNLHmk2KygIlSE0EbzhaRRdn1CEgvzE5AU1Y/jGnWqPx/pjWkvO+6wDf++DRue/4NHP2T+0LfpzPyAiJooQ+vYRNRqpRwpvMrnJO9DtPTRX/8Zte7lGUh7ytUxmUhnBajP7DLtmusUaL9cmggVC34nWyudxOdekfr2Bo5o3vFva/h479+BL9/bHnN3x1SapTUeqOo1DtTv6l2D7zojHs9aoZ+rieuUXKE5XrnKkr0skikKEWYObgdqmgkxXjrJuh9Xa0FDZOmtF83JvYpTX0t267x3hylUrU7TOcPY/NFp5qSMOLBRKmJsIk9OGBhFHkAwBRrzPj5nTY9CADY4PYBAGZoRAkANo54ikux4oQchYYM9UKmJpNGRak8igy88U5Le+ugQSi9BVjw6q6A5DVK+k3EnHrnoH+UEKWy+sCNQwc9axMhyrJ7vLPfgijRc6CRNT2r+71JgFX95nM8DkbXO81JSw+O6XlVlvbX7a0oVZSU1jq+P05FaaKJQbhGqXHHQ029U5c7ptQoxStKijAyye4dQJDqXG/wRvvuRSlKOlGKOr9MqhL9SLtPbFDYrvm8YmyeoOdBqyZclqwfwTt/cDd+89CSlqx/MoKJUhMhHgDCmntY66WUSVl4375z/U+72Gv0EQDAzfa7AAAzESZKs0n9kT5rP2hIgxNkhAYrRnJTCVSuKWm/106EomRZwYPURM6AcOqdnu5jMnMIK0phU4ooTLb0mYlKvRNKkqIoNTAVS5AVk/19NQwazBzEeVeOSL1TapQqKqmKwu3Pr8EJl92PV9eGr69mYLwNhPVzIOkyTJMmEwGdqDayBC6+RsnQRylUoySWg9BnJxPGS4rFRJi3DBj/FovO+kQpqFFKQpS0c7hDjkFQ49YZ42VMLNrBlOTxpZuwYtMY7njhjZasfzKCiVIToTvOjYheSr5F+JvnTsVlH9sPR8zbGrtYqzDbeQNFN4N/2O8AAEy3hkPL3Dhckn/f8uRK5b04RYlexKZ0OacYpPz1Zr0ApGIwc7AswLIsaQ6R2MzB/76w96WKknD8rdgqURKBj+u6VYO7TnnQJoHrupEqz3huxrbjyn0+ovTaaiBRirDxTgKqKI1prneVCEVJbVwZnhQw4W/PrMZzKwdx78vrax6j67r4n989iR/c+lLN3xWISmlNCv0cqFVRanbqXSMVJTr0cI2SKfVO/b6pRmkyBr3jVT6oohSVXuRqipLjurAdN7TPTYYOE+mMOJGIqn1jbJ5oh9S7RrYCYHhgotREBPbg3m4f0RSludP8//MZvDv1DADgEedNWOluCcAzc0hBfchsHA2I0spNanqTqUbJ5ARGg2SBQiEwh+jLCNtoWkvh/U5Zlr9NHvmLcjWKqlGijnlC1ejJeS57FcdVUu9EX5QkZgOT6SZhCjboe/WCBpKjxbCVciMg1ARdUayGYsVWAt8g9c77P6pGiRJkqZ5WOV9k3V4d271qoIC/PLUKV92/uObvCtBjWM+zVVdPa+2j1OzUu8bWKEUrSkVD6l2YKInfrQ9wJhLSdKBeRSmbJPXO+y2aADuua7yXGIlShLV4u0Oefx0yXsbEQnVvbM0YxBAmUwzUajBRaiJEgN8tFSWvRqkXHsHZZkZAlOZaGwAAL7g7YBOmAADSloupUN3taHrJWNnGKCE9RkXJFuk2JPWuGA5iC6OBehVPlLzf1G7chGLFVgumXRNR8sYrGthWbEche4JsJXExm0z3iLjZ1fHcDGkNR1Sx9nhRr6Kkn7vSzEGm3vmKku6maHDPKtsOVvaP4fePLjcGaWJZ9Wy2WF7Jduou6I6y3U+K8SpKE/1A1Sc2GttHiRAl7VwYMyhKUSle9OXJGGBIM4c6z9EuJfXOnF4UrlFSJynSJHtAh37ttIuitHDxRjz8+obI902pm4zNF47hemj6GDgdtOFgotRE6CqKUJSm+Kl3c6f7/+fTmGl51t6b3D5UkMGg2wMg7HynY4Ofile2HWMX9JLBCUzUKL2wahADvoJDiVLOqvjLNKTeQVWUouC4Wi2G3BfBKSiCdWFHbjsu+sdMilISojR5bhJRlrrA+AIK2ohYdRRs3L4ThLxazy8duhoqxhp2vYs2CaGudz/410s440/P4O6XwnnbQkmqJ0Cm9Tf17jeqZNVzOENEKXGNUv3bXQt0pa6xfZSCv/VzwVyjpH8/TJQmY9AriWIDFCXboCLRv1VFKfiAuK+b7mf6S+1AViu2g1OvXohTrl4Yef+yOShlELSDe6NYbTtcQ5MFTJSaiBu/8A48+Z2j8K7dvVS6Yb+XklSUpgeKkjBu2AjP8W6jcL4zGDpQrB/2nO+iTBUqptS7YgWvrRvGcZfejy/d+AQAoFQIapSybkC+BGiNkjfmeKIEqMG4eIDmMim5DJF6JxQ33cxBPKyakXr33MoBnHDZ/bjv5XXjWk4jEJc6Np6bceTDv4E32EqDFKVixdZ6rUTYg0uFwJXnScV2sWHEuy42jhgs88cRRNJzsd5+TQ03c2gzRSlUo9RAIk73l57eaapR0vdN1OzrZKpxBEgfpbpd74L7O1V/6H4K1Sg5rnJuSaKUoEapHYK8su1ipGSjUHYizWi4RmlisGT9CD58xQL8+6W1rR5KTVBS77hGadKAiVITMSWfwYzeHHpk6p1PjHxFadsZ3cHnfOVok0+QNvmEKUpRmjXVS+MTipKpPgmgqXdEUSpWsMKvbxK/i6RGKQc79B29RmlqVzZyuwVozYB4wGZIs1qhKMnUO8dRXe9qSr0b303is9c+iudWDuLTpNFiqxC3veNSlCKIUmPNHOpzvdMdG8dKtvLgKfmOdlGud3Qbyo4jHfBMNROyVqeOc6asKEr1ESU1pXX8RCnp8auMM3hOCp0YNXL2nQbq8fbgEY1OZerUxI2xHdBYM4fwcr1l+/f0dOB6JybmUlZAtkyTJvr+bocgL0kTYvEy91FqLP69aC0eXbIJN2sGVe0ORZlu0TkszsXJ5vzbSmRaPYDNEWLGrYAcAKALHrmZa1KUXE1RiiBK28/swRuDRTlzHqUolQyF6yPFCsqi1sL/XR4LiFIGZQA5ZSZQr1Ga2p2AKJHvi4s4ZXlEqVhxZC+fHlmjFGXmMPFE6Y3BYvUPNQlx2zue7aSpdxSN7DskgvFazRwGx/QaJVvZ1orj4Ks3PRVyehSfUXp+ufFGIEHj1ZqGqHwXiE+RjINa5zG+75v+r/a9iS46DrveTUzqXTGBPbh+vYigQh+R7bqT6uEo+yjVsO/pfSDK9c507gonU5uk3mVSKeT8ZXSKoqTfb0zg1LuJwXhTRVsF5dpomaIkxtKS1U9KsKLUAliWhUzKQgUeIcj6is2MHo9s9OYzmOFbgYvUO6EoHbpNCtO6s5g3u09Z5nYzvBqm9UJRMvRQAkjvFBIwDhcrMsgTZKZM7MEzTlzqnVCUqocVClFygjSNrHABLIZT7wYN9uBJU+++efMz+PKNT3b8bF/c9naKoqTP9leDOH/78hn/+7bSf6dQtkMkCQgeDjppESTcRAIbl3qXnKD8+cmVeGOwEPpeXal3BlvmJAhaBUzsEzVco9S49cX1UaLkPNoeHP7reupdw4bYFpBmDjWc46Nkf9LUO5MlOH09nUrJ98RzJpMOMgeS9FFqh9lwpf4q4nzg1LuJQbNaFzQa4530agSC1LtJdhNrIZgotQjduTTK/pzlITtPw/+dsr8kHX0ZG32WlwKnK0rH7ZLDY98+UqbpAUAuncLWU716p2qpd7bjwnHcUOqdCGhLfnBhE6KUhbcsUy2FlUBRyqbDbkfUIUlPvRNpfEOFsvJQLdagKJUqDm5cuBx/e3oVNo2a90WnIE7hmYgapUYqSoHrXW2Kkki53MpPKS2UHSV4GjE4NQLB/tC3QdS/mUjgeFLv6IRDOWEd1nf+8hxOv+kpfOuW57z1KgXAta3fdYM6EHEdtZ3rXdNqlLTUu5KhRikixU7fBZ0WoFWDPNY1bBfdf2n/Hk6X5f0dfF4sWipKTmAPnk5ZsYpSiCg18BypF5QEmhQlE0lk1IdC2cYTyzaFaunaQVmsBYpdPps5TBowUWoRLvzQ3jhk99kAgD227MJ75s2S701zPce7ipvCEDylSNQqWWMbkU2nkCe22j35NLac4qXxVUu9A7yaDRpIjhQr8uElgg2nRBQl1wtaVUXJ+y1rlGKIUp9PfGiwLIKllGUhm7GUz4tlbRgpKa8XaqhRMhGsTkW86139pKYZilJFUyqT4rmVAwCAN82ZCsAba1ST5C2n5DHNP2d0+3ABoSiZzp1xKUo1pt65rosbHlkGALjzxTdCY6o14KJDFoFo4j5K40g5TIKNIyVced9rWDNQUF6fONc7LfWO3m+EohTxff3Yt4Oi0SgolsW1KEqEKJlaO+h/hxvOBvs9m66Weqf+38hebvWi2gTGePufMQL84NaXcOIvFuAO/57YqbbrUWmpzYQbMfnDqB9MlFqE9+87F/vvvLX3j6OSmqmObw2OKXD9QyRS8DDq9XSgOeM92TS2EERJS70TTnoUZTusKIkgT/SDsUtB89qMK9KWwg9FWaMUY+YwxU+fKhoUJWrmICCCXrEtAoHrXTJFyfR3rajWH6oZEARR1G5RjEf8GSuZvzzeGf/hYgWX3fUKXls3TGqUkg/UdV08sngjAODQ3bfyx6q63gnik0lZeOzbR+IdO88EELYPFxBBn5Eoybq9OohSjefZsz4BBCDTZ00mKUlBA8paiZItjV0mJij9+h+exkX/fAmPL92kvD5hfZRi7MEDG3B13VE1Sm7r4/SGwWS4kAS0J1+U7bGqqni/RQYBTb1Lpyz5zCrZ4QmaKDfCVoIOyUSc6fudnt7daojJlFX9XtzRqal3SQxAJhpitawoNQ6TqV6185DyyYWtpoZNsb1gSqhI3t9e09mAKFFFKYMter0UJWEPPugrSofP2wpT8llsM70L3/nL8wC8wNBWgk5bBnyumAUsB4pS2rcHpwGV+HagKKmnUk8ujdGSDcsKAvzHlmzCjlv0Yqu+vAzwUylL9t0QEERpQEsflPVTCQL58RAl+vneXOsvEVGk3pPLKLO8wPjykKMUpfHeYP/xzCr8+I6XsXj9CHG9S67qLdkwinVDReTSKRy08xYAPHVATb3zzm8RfGVSKknQCZGpNk9gPHUGirteAtb6p8dXyL/TJEVJoGZFiaxSpt7VWKM0UZP3d0dY+zZUUSLL0pVjmjomjnu4RskckE0mRUktME/+PTV1MWJ5hnOXntfifTohliT1rh0azioqmuEicQwkkVEfdEvrziVK5O+Wpd51ZtpiO6P10+WbM9I+UXJUQtBT8YkSAqK03p3m/THsSdNU6ejJEUVpRK1RmtqVxVnHzsMn37GD/HzZdpWgzqtRCi6qUsWBWw7SZVJ2WX7P1QILK0JREuQoR9IEf3DrS/iy36dJFqBblqKOAcD0HrM6VaxBUaIKRq1uZBtJyl8u0/pLRBAaU6+q8Yg/kTVK44ychVPhYKEsA9RCDWR14WJvMuAt203HNP9ccF01cBOpd+L4pDTSEUWmTa+XZQpaHYpSjQ1nFy4J1BWTylXrGEyKUtLDF1ipTwxTirp2mtVw1mjmoH/f/4q+2ydTkFFv3QSdlFFJQVTqnfc7aDgbXFuZdHyNkk5M22H/K4pSldS7Tgvo2w1iV9I+eEB7nAe1oL1c7zpr37UzWhoF7rjjjrAsK/Tz3//93wC8i+Xcc8/F3Llz0d3djcMOOwzPP/98K4fcWKR8tUJTlLrK/QCADe5U+doa10stwuBqwHFURSmXxpZTPEVp40gJjuPKGiVR72NZlkyJKIcUpYpCJkoVB1YlSL0TihJAbTshlwsEKlAwJm/bcumUQoQefn2j//1g9lFXlKLS+AJFqXpgV9a2pxaIOi+6zkZh+cbRmmumgtS7sLo1LkUpyh58nDdYMd6SHRRzlypO4vQUkXZ3wE4zpQMiAIyQVKARf+ziOhC15iJgiTpHTKRApKDV82BRzBwM67zyvtfw6/tfl/+XyLEXqU3jcUoyKUpJiU/gelfbOpOiK4IoTVjqXajhbLBhlYgZ6ihFaTKlUtVbNzFqMMPw/g4+4xjIAnVfDBSloEbJ2EdJrxFrgyCvmj24YyCJjPqgEyNBMjptv7aV612n7bw2RkuJ0qOPPorVq1fLnzvuuAMA8OEPfxgAcPHFF+OSSy7Bz372Mzz66KOYPXs2jjrqKAwNmXsJdRzS5tS7bNELFGnq3RuYARspT30aWaspShnM6PEUJdtxMTBWDuyViW23ICQVrUap4rhKPnpRJ0pOSfksEFyMUX2UpKKUScVaMuupd7l0Sjac1RHUKCVIvRsPUSK1UWMlG8s3juLK+16T6V714rElG/Gui/+ND/18QU3fk4qSsUap/pthpJnDOGuUZM+iiqPs+6Sk86ll/QCA/XecgWw6JV20qNOddHqLVJTM6zIrSvU/WBRCrq1zuFjBRf98CRf980VJjunxChQlGnA1QFFKuIyJTm/pypqv44lKvQvXKJHzJSLwEv+HFKVJFGTQGL8m17tycL+LUpGUVCNZdxqch+L6UFLvDNdmO/ZRqmbmQF9jRWl8kIqSnLQSr3fWfm0H17tOVePaGS0lSltttRVmz54tf/7+979jl112waGHHgrXdTF//nx861vfwoknnoi99toL1157LUZHR3HDDTe0ctiNQ8qcemf5dUgbSeqdjTQ2WTO8fwZWhhSlXCYVmCCMFDFUCFLvBETAWbKd0KzuMHHJK1UcpCqBqpIi49MDUFGjJPrdCPT6/2fTKTzhB75AYOzgyJlGS0nR6c2n5Th11G3mMI7Uu7GyjWN/ej8u+udLuPjWl2pajo4/PeH1/Xlh9WBN3xPb3ZM3KUoTQJTGmYolxqufZ0mJ0pBPSLfq81RSEXCbiKpQK9NW0OQSiFYtjKTdFvV5dRAlWqOkbZ+YfHDc4Hyk4xor2b69d9hNMinE9loWrQ1J9l1xnBtpB08RNeHRyFQ/ur+oUlvWzj3bNqdXRilKkynGMDnTJUGUokQDwNiGs6RGqZo9uD5/0Q5BHt1VJoJZr0kGIwy990+nBvvt4HrXFql3dhkoThJBA21Uo1QqlXD99dfjM5/5DCzLwuLFi7FmzRocffTR8jP5fB6HHnooFiyInpEvFosYHBxUftoWEYqSMGygihIArE97DmAYXBGqUQIg65TWDZUwOOYFaVRREg+qiuOELqIhEoSWbBtph9QoUUXJVgMLQWlSGrkRKVO5TArvmbe1fF0E0eIhk7JURak3n0EmrS5LpBXWkno3HjMHYYghIOphREpYvUjXebUVJkhRKkxw6l3ZdhR1KmnKoQjcxXkhiBJVPQXy/nUg032EohRxzI19lJz6H8qUZOhqVbEcfo/uj4rjemRyHA1nabF8QJSSne8T3SyzK9MERYnsL7q/9fq7oPbB/P3Q600OMjaOlHD782smhLTWG7yZ+lDpf5uaz4r7t+MG+71ajZJO4NohQFZUNDZzmFCI/VfW7sWdxj/bwfVOTv608qS88aPAD3cDBlZU/2wHoG2I0p///Gf09/fjlFNOAQCsWbMGADBr1izlc7NmzZLvmfC9730P06ZNkz/bbbfdhI153JBmDloAKBQljShtFEQppCh5ZEhYgb+6bhhDRV9R6qaKkne4TbUpVFEqVhxkbGrmUJIpdmU5M+v9L2qUgCBYBQKL2GzawoUf2gtnHTsPgPfgpDVS6ZRqdd6by8hxCojmulJRqlS/AejmFLVgo9a/SSAfkUqUFPp2JYUkSk1SlMYbpAjTjVLFUfoMFcvJjoMgDoIodedEQ+LweEU6T0pTU/QmpwJme3A13aMWUJKj2x5TBU2sVydqYyVb2Uf1EqWUZdWhKAn1bWIUJd1aXygNE2cPbpO/HePnwkQpvByg+YH69//1Ir5w3eOyt1YjoQZvyb+n9lEKXo9SUnRFyXECe3Bao2Tuo9TuRMnwPhnjZKppawWiapQ6LQVWSUVttaLUyn336p1AZQxYcFnrxtBAtA1Ruuqqq3Dsscdi7ty5yus0EAe8C0p/jeKb3/wmBgYG5M/y5csnZLwNQYQ9OEb9GiVoRCkjFKWVRkXprdt7qXlPLN2EgVGRekdqlPzGrjRAFrtySEu9y7pEVbFLyPgBqQhAZY0SOYNo4b0IcrPpFOZM68aph+wo3xsr20rhb5YoSL35tEK4AGAbSZR8pSJBYDee1Du9f5NAVHF6UujblRSxNUrKw7y2G2Mja5Rc18WV972GhYs3yhqlQtlWAqykipJ0yvL3l1AmzKl3aeWzYuY3UlGKtQevfbvpuaUTeLq9Qeqdnp6nNtKtdQiKoqSlH8bBcdygqWPM5bFuqBhSWJNCn1jIS1e+ZhClCEVJ871zIwlUc4OM9f49543B+vZ1HKLS5qpBSb2LqL1QjB2kohTUKNnkWs6no80cQq53bRAg011lNIFhM4eGQZw7uo1/p6U0toOZg7intYPFPpY/0uoRNARtQZSWLl2KO++8E5/73Ofka7NnzwaAkHq0du3akMpEkc/nMXXqVOWnbRFhD04VJRpcb8r4KWwDK0I1SgDwth08onTnC29gsFBBNm1h9rSg4WzWZzV0Zl/0CRouqopS1iEP7EoRWTEbrNVzpAhppTUJWT8oEsFRLp2SqlSBBIdJUu+29ZWyIjEJqAYawNbqXLdhwhSl+oiSIIjdBtc78WD5+b9fxVvOux0vrUmeahrtele7wvDXp1fhon++hI/88iE5Xr3nkz7LH4WwouQTJUPqnTRzCNUoRZk5hF8fjz24qijp9tRhRcnWiNpoyVbUz7oVJZJ6lyQYVup3ItZZqjh4+4V3Yv/v3pko3VWHbvsvUigbqiiRYdH9rRMlW6YMa9+PCMiaHaCJ4zie5tjVlq3/XQ1jEQ1no0gTrTsVnxPndrUaJf2cbYcgT2mma1KUqHrQYQF9u0HsX0GsA3fdztqvToL76oSPoR1S7wRWPZm8X0Uboy2I0tVXX42tt94axx9/vHxtp512wuzZs6UTHuDVMd177704+OCDWzHMxiPCHhzlEQDAKPKYTlLnBrI+UQopSt5y3rL9dFhWUG/0zl23lOYJQJA7TpUEQbJ0opSPUpS0GR9KlHoIUcoRRQnwlEGhOI2VbWUmPFcl9S6kKNWoeIzHHpxCD/xqhV7HlRTieHVlA7IpIG6KP7xtEYaKFXz/X8kNJyL7KNWhKD2+dFNouTpRSkJYXddV6hoAUqNkSL2TZg5a2lkpqo+S9vCgykpdNUpOmAwJGGuUdBMVTSWr2cyBXEepGlLb9ODZlDpExyZ6Y9UCPXgU1/lE1ShVHFdO5OikXO/Pon8/ikA1C2IctarftSxb/7saIvsoRQSD4k9xLbpucKyzaZJ6Z9hGfX/rEwqtgKLWG/abao3elCFNWjiaChJ1XbY7oiYRmgn5PGsVedfj2bWd39Kn5UTJcRxcffXVOPnkk5HJBEG9ZVk4/fTTcdFFF+GWW27Bc889h1NOOQU9PT34+Mc/3sIRNxBRZg5+s9eCm1Oarw7khKIUdr0DPIe7PWYF6XrH7T1HWawgLVRJEN+lqXf9oyV0WWRMdkmmx1Xk7Lv3Fo3baeqdmFWkJEgoA5Qo6fbgvflMSHmZ66ti0na6xhmKRtUoRdkdJ0U6JmU0DoJ4dGfTCjEFwkGx3pMqDtGud7XfYKkKFxAllQQUI9YXtW6hgIr9rpMKIFD5aO8WINrJrWI7+N6/XsQHf/4ghgrlcdUHASppDxGlmNQ7kUYpGkPXOwbZuDllKbUh1aArbqav0Muw1t5fQDgVMS/NZCaGKAFBY2P93K5GiFptJiAmJyZaUaqXKCUxcwjswQPXO3Gs09QePEmNUhsoNIqtelUzh9aPt5OhT1ZFuVG2O9rJ9c51W0TWyqPq/6/f0/wxNBgtJ0p33nknli1bhs985jOh98444wycfvrpOO2007D//vtj5cqVuP3229HX12dYUgfCZA/uOIDtKRoF5GR/JAAYyPoph8Nr0JUObtzUNno/v04pk7Jw1JvVFEWhCokgIpOyJOEaLgZj2DRSQhfU1Duh8oRc70gwRYmESL2jgbt4f6xkBwGeZSlKzZR8Wkm9y2VS2NK3iRYz9EnMHChqnaWlxhYU41WU6q1RKkhFKR1SpfQbYS1kTpwHOn+r5wa/gdSxiNl8fTFJFCWqZonzoNtXT02ud9LMwQqCMyCm4azt4pf3vo6nlvfjl/e+Pu4HW6zrnaFOTgSOfb5tv+h3JlBzHyWS2qSnH8YhSfF8PdbuFPqEhjg3x9MkWYc+bHGtRNUoIapGSVtus4McccwmWlGqreFsVOodWTatr/N/0xqlwMHSQs5/1hgbzra96134/VpqC5dvHMW1C5ZEpjtv7tAVJVv73SloB/JMnyEtmXAoF9T/146vrUo7oOVE6eijj4bruth9991D71mWhXPPPRerV69GoVDAvffei7322qsFo5wgSEWJBICV4CQrQFWUxnIzPXLlOphSWi9f7yHB8bt32xIAcNgeW2M6IVkAkPMDTxFEpFOWtFemqSobR0roAlFV7JIMWgPXO18RojVK/jj6MIqtK557E1WUukjqnUNmGimZ6smrqXdbTcnLNENZo1RjMFHrLK0gEDN7tf03TqJElbJaAmJZo5RNh1QpfXa+O1uDolTylqv3wKqnHoWqcENFc5pWElWCBtfinBNkfsQQZAT24N7/AVEy71+6/HtfXqfVB1UdXnh5MY2N9RolmuYnbPuFjb8cQ4273iETDvo+iIN+3pi+Q4PgegI8/TxqhqIk9nmoRknOVJu/ry+n2fHFxNYoBX8n2fViLFGpd2oghtBnMkTdVRSlmNS7dnK9+9V9r+OTv35EUSXHqyjNv/MVnPPX53Hr86sbN9BJhKCPknqddpigpDUhbtEYxmHw1BBUxuL/70C0nCht1jCZOWhEaZetpgQfT6eBqV46XW8xsJHtyQdE6b17zca1nzkAP/rwPqHVCQJSUBSl8CnQPzKKnEUCjUpRkhkZ5Pi/TGYOv8l9H19+4T+xFfrljD8QEKlC2ZYPbz31bopm5rDFlJwMlGl/nlpQS/Dhuq58QM4gJBWoX8beOFLCaKmiqEG11FmJ45U31Shp9SXdNShKYrnUQh6oV1EKiNLGCNfAWhUlkXonGyUbvi/Or3QqmMUG4hUlgWdXDiifq+f4Kg1ntXWWNKJESZrY57qiVOsspAxE09QevA5FybBe+lpUmmbs2LRzXFzHjaw/0Y+ZOKf18Ub1ZQnMHNTXJ2Im9tkVA/jJHS8bawOrKaHjQS2q6QV/fwFvveAOrBkoaETBvAyjPbjoo+QEiqtqDx7e/tD+byFR+u0jS/HAq+vxzIoBMp7w52oxc9g06t0T66n12xwg9qWsURKKUocxpfG40DYKLTcZ0RWlSuOdPJsNJkqthMke3CdKbiqDG75wCP7nyN3kW5l0Cuj2UuvylWH5ek9Ore06dPetQmoSEKTDydQ7UmBLMTw8or5gl2WNUriPUvAxQZR2sVYh7Vawg7VGsf4OiJKj2MaqZg5pRXmZ3pMzKEoTl3pXsh0ZTM3Q9mGt6wW89JVDf/hv/MflDynbVUtANEZrlFJhRYkSkKSpd5QQTtOIUiWiuF/gxdWDuPW5wI2yWLGVGiWT8gMk66MkAquUFZhfCAJg2mdSUbJUI4MoQwp9Gc+uJMFQXa53cYpSsB9o7zAgsO0P1yjVtn6pzFqWJIt1KUoxtulA2JgjCfTrThyrRgY/Ual3+rkWZQHvSAKlvT4BAcYPb1+En971Cu59eV3oPWnmMAGKUi3Kx0OvbcDAWBkvrh5M1kdJST8T6lFwnKkxSz7O9a6NUu8qBtJqnEiowcyh3myIzQXS0lq4g3ZojZITMYnQ1DFoBjdNh64glVlRYowHpoaz/kllZbpw4M5boCcXmBtk0xaQ8+qz8k5AZnoM/XVMEBbfIuWK1ihRjAwPqy/YQY1SOVSjFATux+41G4CLHssje9OtETX1LheuUfLswYlzXj4jc9wBYHp3VvbRKdsubMeVD5uk211L8FEoBZ/VyWYtttmu64113VARQ4UKXl83rNQo1TQmP+jrMpg5OK6rGHEkTQ8U+xKA4owoEBeo/M/vnsT/u/5xLFnvnYMrNyW7ERYSpd6JwCrYDjFDbdpn4vwVHxcPqihyrAcqd7+4Vv5dX41StKJEg/VSxVUeWqJGaUirh6u5RomkNonLKMkDWidGZlev4O8xQ31Y1bFFKUrNSL3TzjVx7YYVpXgC1UgIUjwwFlYVmmbmUGW7aArUWKI+SmGyIJ4z4h4IdFbqndhUOgliSr2zDSQxCsU6HVs3F4QUJaH0dliNUjsoSvRUbI2Zg556VzB/roPARKmVkPbgJFVJnFSZLvlSjlog5z2ilK3UTpR0e3DqREQxNqYRpUoxcL0L1SgFHzt+7zn4zaf3RQbeZ6ZhBLtuHaQOivqZMZJ6l07pZg4ZTVHKyplowJuZEwFp0jSzWgrRRYCVTllKs16gNtvsz1zzKN7z43vkrKweiNUysyhd73LhZrwVx8UQSd9KOoNEA0k99a7actYNeVK6aES6IiFRqkVRypLtjFWURB8lLe0sav/qysiiN4bk3/VMANKgT7ck12uU6Pkja5RCqXe1rZ/W+un7IA466Td9Z7ypd6EapexE1Cip/0eZOQSpd7pyBP91GD/fSETVT3nj8NZXnIjUuxqKu10SsEaaOSh1GOEZ9HQ67HqXTaVkw9l2d70TY6lEbLMAHWK14Yr7BCtKZoRqlCJqCtsd7eF61+Ix6ESJFSXGuGCyBxf5ndmgUawIBjOpVECU7IAo9RoakQLwpoQHVsh/RS2QeFBn0ymFhAgURnVFydBHyX+LKhyWZeHdO/TI/88+ai4+/66d5f+0Rkk+VA324JQMUEXJ+64jx0Brs+JQyyytmEXtzqalAiZQy0Pu34vWYemGUTy6ZCMA74ZFb2C1pANK17tMWFGyHVVRirLFjlqmZZkVpbhgVihcInhevmk08rMUicwcbIOilIoOsGQfJb3hbASpHdEsxqOCQRMeX7oJF9/6khLoxipKWuqdICcpss/Haw8eKEqpUPphHJLM4NNZ9HpS7/TZ8/xE9FHSlhU1cy+Jkv79KrbhjYQ4H0zGGJLgT0TqXZWAXxkHCVgVMwe6DENdkusGRiVZWS9IXBnTVRrOaud9KxvO2lrQ7v1tIHc1pDSK87KeHnXNwMr+MfSPmmtLmwFdUYpKlW13tIPrnVPDxMiEQFeQJoGiFBFhM5oCUaPk2t6UlGUF+Z1EUfJSVvw6oZSn0GTLI/jcO3dCoWJjRm+4HgkA8OR1wN++Arzn28C7vxHqo6SrOQLFsRGAigyVolR5ghSWsKIEQDbLBTxFCQazh7ES6aNkaURJq1Ga1pNDyle+SraDQjlQlHqyyU7fmkhJJWju2qWlJSZ9eNNAIEOCBjqMmsibVJTCZg624yr9hZKmdogHdz6TMqqKUQX3tLZJEKbEilISMwcnsBMWEMTZ9P2c1nBWBHRJFSXaxLbaQ+U/Ll8AwKvp+uKhuyjjNa0zSlHKpFKyrnCwoDec9T7z83+/ilfXDuPHH943tlFx0EeJFtEnUZSqz+DTzWmM6513PTUyWAz1UfLPTX0deiNLAfFvKPVuAgKMojbBQCFd7ybYzKHadsmZfdeNrNExpd7RxdKeZhVDLWoSotTKlKvgHhJPMOuqUWqgNX6jsHaogEO+fzcAYMn3j2/JGFxJTtWMlU5LvWsP17vg75YqSuk8YBcnhaLERKmVSJPdb5eBTI4oSuHUu0w6BaT9HlLFIXz7hDfHL/+hn3u/7/4ucPBXZPApyEAmbRlrWrKONwYHKaTg+GYOQR+l0VIluCHoTXhKxAhirF95i9qDB7nral1Nbz6j1D1N99PC8hmPKBUrTpB6l7hGKXmQJwLCrmwa3Tl13yRVlKhKQUlfXM+dOEjXu0w49c7WUu+SjrFYCbYzmwkH4lEPdBr8i4BvVX/CGqUkDWcJmRCQrndxqXdSUfJej9q/OkGImjWPw5INwTke23CW1iiRmrBM2pLpsrqiJOLFH962CADw0bdvhwN33iJyLILQplOp8fVRmgAzB13dDBSlxgWL+iET52dUamFUjVIzzBzE+VswpKDKPkoTUaNUwyw3rc9RA6745dHlSsJOzRyo652xRkn9vz0UpXgzB/2ccV1XeXZRiONaaw/AZuBZ4u7XKgSNwtXzqcN4UpvUKLV4DEJB6p4BDK+ZFIoSp961EmmiBAmLcFmjZEq9C2qUUApqKyKx9bzg72f/GDScLYUbzlJ0Wd5Yimm/vsguyoffU8v7se95t8tALjTZTYlSoV95q9tIlFKaoqRyd9FHKk/S9mTqXQ1mDsPFSqJAnfYs0mugkpKQkYgi6LJClJIty3XdYEw5c+rdoJJ6l+zGWFAUpfB+jLrB0n0o/h4pJguikyhKYr9kDIpSnJmDrqYkP1bBvksaHNNrRu2jpKWBEYJeqjiK8YIg+bqZg+O6NT3ogsbNYVUtDkkUJbo/6qtRUpcpG8421PVOXZaYNCjbwb4Gwqk84jIKiJK63AmpUYqon6LrGw9RcjUVSIByxmrbFWWvr6QUGRQqutgMcV+kkwNCuTY2nA2lgrZOeTEqSgkMKOJ2bRSBbwe0kpQKiCHojWY7zR68HVzvVDOHFgxAKEi+Q/NkUJSYKLUSKZLfZmtEiShKoo4ok0pJ1zsUExAleoIu/KV8UAUNZ1PG1DvRbLaU9ddll5CxAqJUtl1ZBK8H7iiR+iZNUVL6KMkAT03/6/Xrjg7bYyvssEUPDtnVa6DblQ3GXqvr3dqhIg666C7855UPV/2srAfKpkNW20lJyChJhSuSoIgW+yc1mNCtv1Pa4bJdF8Mk2E6a2kG306goRRANOhseVTgfhURmDqL4O21QlGJS71KyPqe2gER19kr0FUXJjK9R0lPvgjQkqSgZzBzo96q5GNpkxj5VU41SAjMH8lqtqXeu64bOxWbUKL38xrC/jmAigK5TfDpoigrlt1zuRKTe+cc1tkZpHKl35/3tBex1zm14fZ1aYxqVNmeCGId+f4oqUjfVktB9WybnfFzqnR4Qt9LzIKiXoYpS9OeC/6P3rdif7Wjm0EqHQQGpKGkmDrW6gLYa7aAoqfbgLTjfdKLEihJjXEgToiQswstRNUr+rHm+BqJUGAz+fuMFiHh4TJo5mFPvuuG5mVUEUQLQnfbGpxfD16QokRqlwK0LITMHALj6lLfj7v/vMElWRMCjpt4lyxx9ftUghooVPL28H0s3jMR+VjrMGYhSOeGNjypKerBs+hvwHgi/eWgJnlrer7xOg6quTFCwH3xPDbaTkjkxrq5MWrpRUUTd5McMipL43dcVfzySmTkEgZWA6MsSl3oXKAfe67q6EwVKKuKCSJpGRmvXKBkI91Eix5soSpl0UKOkp7Q5rmrLnJQopVLBPksyC6ufJ6bjTffNaI324LbjhlQa6XrX0Bol73eff994YbV3zxNqgDg/xLYEtZWW8n+4RqZhQ5TrkUQpRlGqxaGTYmX/GK5ZsATFioP7X1mvvBdlxGAep/dbn9SIKhAX+8lYo0QVJc0evFqqYysVJel6p9QoJairitm3MvWuDc0c2kJRijBxaAcSVwuirPObOgaqKLXSzIESpQ4jvDqYKLUSlgVYftAlLMJN9uBpQ+pdUXOmM6FIiJJTRnfKC6ipPbg59c4bi52fKl/rtrzvDGtEycL4apRSqaCPEjWXsCxLqcfpUlLvhJlDMPaI1PAQ7n5pbez7Yt/ks6lQ6l1SRzmqKJUiiJIeVD+3chBn/+V5fOfPzymvi3qybNpCJp0KK3hQu70nnbEMFCU19VEg6uFJ1SPRj0vssy2iTEV8JDJzMLneiWbHcWYOVlAX4Y0/bApRDXEPNnredxGnyPg+SuaGs1RR0kHNMgDD9RUx5kwqVVPqXRLXO/qQrbVGyXT+ZLQ0uEZABO17buPdq15cPQjHCUwEZLqfVqOkK0p64N7olB8aIJuIkmw4W6ficM2Di+XfU7szeGHVIO5+6Q0AtZkORI1DSSkyEC+X+AnSGqUyqaHL+ym+rhs+P8Kpd/HjnEhI50wl6DV8Thtz1CnjOG5b24NTEtgq8wSxWrF/AsLUkuHUDbW3VmvGoNqDt2AAuqIEdLyqxESp1dAtwsVJRu3BRepdOgXk/bqhWhUlAFNcj1ypDWfDp0Ae3ljc/LTgtZQXKA5rNRWhuJ2m3kXWKAVBY9oKZhp7c+nIYlgxzih7cFOwb0JSotSdTYfMIpLOhNejKInaCj0VS5pL+ITW5IBGbV2TzlgGNUppZA3nQNS2KoqSsDv2X5tZhSglMnOIcb0zK0rqftFTmJL22gLiZ99oLRH9VNwxpce+ZAf1I+kYouS4KimpFrDTCYeUpqrFIRSoGl3vgteSplcK0GO15ZQcDthxplQGGzmDLQjOrltPQT6TwmjJxtKNo3LseuqdWHUqpRJrfUQ6cXp2xQDO/9sLxmaxSUDVVNO+FPuknhqlsZKN3y1cHizLdnHabx/HZ655DKsHxmpKvZP9nPTUuyhFKaZGyXGDIFw3DtK3U7/dtFJREseeToyZro+kihK9FtrRHpzeL1qlLoX6KEUove0OxQClDWqUWmrm0MNEidEoiDolkXpnUJREsJfLpACh8iQhStpnelyv3414UFMnIgpRo5TK9cimuF2+ojRS0lPvaleUCiVSo5SyMGtqFywL2G5mD6IgvksbztJgM2sgECY88vrGkCpGIQhEl8nMIeHDm6YpKQ1JSTqYHlSLB5T+IJXj8bfVtJn9Y7ThbG2KUj5rtgePWo6qKPmpdyVBlPKx60xm5hCoLgLibxMJDFLvvP+DYnTvd1JnRPpdE2iAXI5SCUMNZ82KUjadihyX47rKPq5q5kBUKtlLKsE5oC/XFCDRoLpmRYnsiwVnHYHffeEdE6IoiWOWTacwb7antr+wapCk3umKknp+ycaWVRSNK+59Df/34GLc+cIbicf2rVuexeeufQyO46pukQ2uUVqxaRRDRdWUZOOIdw/fNFKuKfVOrF5Pk1UNIejr4YBWtQcP9nccURLLEZd9OzScpanWJoITZTWvQ50waT9FqRohbAbEaoOGs/54OkxSijI9adUYWmoPnusLMqbKnU2U2B681RAW4SEzh0BR+tgB22OsbOM987YOTrhqrneOE6TeZXuA8ih6nWEA+YAopc2KUs5XlNLZbs8L36kg7zvh6dedbi6gECXhoe9vi7DbVl3vLMyd3o2b/+tgzJ7WhSiIh2yZzMz3kBolL1WrejBXsh08sXQT3r37Vsb3aY2S3ow3saJEXOD09Cv5ekSxtB4o0b5OgIGYQk29q7lGKasqSikLSqNIHTSIL2qK0kSl3umW6BS6mYO+H71zpBj6XjZtRTYlNWFIMcwgART5u6qZAznno5pEO66q2lULXERAmSKpqolqlBKk3tHl1EqUqHqm97pqxMO7ULb9xtXe/ynLwpvnTsXTKwbwwuoBGfyJ60YQf/F5MRaxifqQ9H0oJj8KCVsNuK6LGxYug+t69UNUCTam3o1DUTIZIcg6G8dR3nfdeBtrQSTDio85AJSpd+TjWWoPTq7ndMo7R22SiiaXSQhvkdTzNRuu6wZmDhF9pORr2qGKulYp6Uyavt1MqCmGrQ3uZcNZg1LZCbAN10az0XJVS2ZFdXmxX2k46A/aoWBFqdUQFuHCHrwcVpTevftWuObUA7DN9G4gR1Lv4i6C0jBkQsm0bQEAPY6XFkdn+fKG1CRBijL5LpkaKBQlHbGud4CiKtEaJXFjFAHLftvPwJxp3YiCbHhLGndSxSdp6h0QNqSgoLU7ddcoRShKapqWeUY/RJRKAXEDzKSBpt6J9S3fOIov3fAEnlnRbxwjdb2jZg5iPdE1SuGZcfHaFlPMREkEq0nMHEypd5kYohRY56spVuIc0Q05BKbkw0Ql7qEc1asqvkZJI0pELYurUVJS76pECvRa1g0t4tBo17ubn1iBhYs3yv/FvjAdx0YEwZ/49SN45w/+LZW+lAW8eY6ntr+walCuQ9zfgs1V7ztRKT566p3uxlUNxYojb8+DhbJCPExEaTypd+F6s4AcUSUz6vMUThRRiggA5cy/QVGihE0ce6FeRy1fkOpW18oAurtfEjMH8zLptraDcYIO1SWttUQpZObQYal37eZ615rUO48UbSqlMVjxn7MdrigxUWo1UlqNUiVco6RAmDk4lfi8T6EmpTLAlFkAgG5HdXxLp8xpV3l4gX4m1wVkvHQqQZ6qoqS5ypE6JVmjVCJmDgldGDKkvqEk1QJKlJIX7ZdsB1//w9M48RcPhoJbWROUC9coJXW9o4GuGixHB9UmpyWAKkoi9c5AlGjqnb/c3z6yDH9/ZjWufnCJcYxiuflMSrEHF9tsIoWjJbUXVaHsKOYDUTVKgpQksQcPUu+oohR9m8ppqXeyH42sUTJ/d4rBoS/uoUJ7VUWl3ulmE2ofpcBgIJO2olPvHNX1rmpNCVGpggA1gXKXRFGiRCmmRum5lQP42u+fxkd++ZB8TRzHbCqsDDai/uTlNUMYLlZks+OUZWH7LXoBAGsGi/I6ClzvNEVJmn+Ylx/ukeMrJwkDN3qdDBUqao2SgXSOx8xB352248rXShU3cUBP3zMRNlOaorHhrH/MaV8ncexzxL1UXa9PlNLBfb4VoMdd6aNkOCz6tRl1biipdxPQUHi8oM+cVhNUeZ06tV1v7QK6/1o1dLrPWpJK6ZOi218ewKDtP2dZUWKMCyL1TtqDC0Upot5DKEpAvPOdqE/KTwW6pgEAuh31856iZCJKnkKRy/d4qXcAcokVJY0oEUVJBIeFsi0fPHFpVRTpdKAoBfbgQbCZqYEolW0Xf3x8BZ5Y1o8Fr21Q3pPEJDOehrOkj1JC17sgL14nbkGKHBBl5kBrlLzlvOjbJC/bOGocY1HWYqmud2Kf6oHij25bhH3Pux2PLglUg7GyrWxflKIkiFKStKVKjBJhgjRzEKl3WiF2FCGZks+GXos3czArSnE1Skp9GlGU0qmUkjaqjgEYKwfnT7UZVZrOF6Qfxn7F/4yZCER9Ji71TpAVZVziOJK0TnGN1hIEP7FsEz7x64fx0hrVmEav6aPumRXbkQFXuEbJ+346Ha8o6UMU60kaSFLldXCsrEwSxNmDl2235uAwlHrnqv3EkqaIAcH2GZvCGmb5dZMMywrSsWnDWXFsonoptY+iZJ6NN5s5xP8vQI99OypKtB61lSmPQLDPbe3/TgG91lqmKFFzjlaYh/ikyM10o+h6z9nV6/ubP44GgolSqyEVJWEPLvooRShKqRRJvxs0fwYIHO+6AqLUZWtEKbJGyQvU0rkuIOMFv1GKUmwfJcCsKJVtOauclChlSdqOuPhpsFlL6h19SG8aKSnvCWLSnUvWcHbDcBG/W7hMMYgYpTVKWkG/6W+ABDYhMwddUYraKg9i20RguTyCKFFCmEuQevfoko0o2y4eeT0gSoWyragfUWYOojdWIYmiJFN1ktUoCaKvW2NLM4esmZD0mVLvEtYoUUJEj1dJI4KKmkjqLrK++mNS4Lw+SskDF6ooZbR0sjjo55nRzIEsZyymjxIt0pe1NoZ+WHodGUXZV3n/8Nhy5fWPXPEQHnx1Az7xq0eU13XlMGUFagStBwtqlFRClJZ9lMS2quPRzwWTu1scxkKKUjRRonUxdJuSwpR6J14q247BqCKGKGmpd3TCwhS8yholWitHrPoDIu8dB5l6pyvq/iKzLVaU6DkflWIroBPUJK537WgPTp+HrTJzCBQlMSGhvt4piOo31kxQq/5WKkrdPb0owHvGPbRoRfPH0UAwUWo1dHvwil94no02NkjUdFaQKKIo5XWiFGUP7pMiK5OXipJIx9NRS42SQpTEzG7C1DtqLWyyfs7GpGfpoIGKbvcbEIgUZvTksFVfXpIT00PuC9c9jrNufhbfuuVZ+VoSRSkq9aTiqDPKgV252i8oChXHc7x6Y9A7j9YOFY12xEXi7kdn/cUMvO56J4jCuqHAGKFQtuX4cumUse4HCFIkk8ywCSWCKoRxaqEIvKQ1NqnNAKIVpd58+PW4B9vgWISi5NDjq35fP/bUwASAV3OowXXVGrdqM+uKolSDWUJIUTKm3gV/j5btSKWDEm2xzSKwpBMYmRh78CeX9eOPj6/ApXe/orwuPrtBm9AQ52dZEiVLGoCUbZek3mmKkv/9ajVK+rmgE61qUFPv1BqlQlklL/qxqJae9dq6YRz6w3/j948uN45JTfF1DYpTHFHyxyCVXUqCvd/06zrRTFnUej1cc5iPUJTEuZVNJyf7EwF6LJRm1CZFKYEqC+iGPu0X+bdDDZV8/tnh66yT0u/aw/Uu+LuVrndFKy+J0mOvruqo46iDiVKrkdJT76ooSkAyolQY8H53TQuIUkX9fDqVMjacFal3yASKUi5CUQr3URoJvgsoipKwuHbdIE8/saKUDoJAcTMXLnpAstQ7MbtNzRxCREmYJ+TSyGVSuPNrh+LOrx0KwPwQeXzpJgDAX55aJV+jihJ9CJWUAEZTlGzzAzqkKFXZXxXbCaUprTSkRkl78ExKmjnk0qkgPUp7oIv+TtSGuFB2JFHqyqaM5IOOPYkZhinAjlWUtIazYhWmpsQUU7rCqXdxw1Nc75KaOdAaJZIOJvaxiSjVag9OFRJxCSQipNpnTOe27pYW5VpIibY4H0xmDnGudxtHPAI+VIhWrgQchzqTBUqGWFeZpOcKxVG3B9eJkv4MDxEnx/w5scyV/WNKIECP4aBWowSo+1Lf99WI0oJX12PphlHc+vwaZWymZZvMHOICuKCPkmh0HRxbo6KkEUjLClJAqeudXqMUnXrnXa83LlyOT131SNMVGDVtiR6j6mYOUXFg1GRZMzFaquCYn9yHc//6fOi9IrUHb1m6mJgoFLWE0RMJ7Yx2cL1zW73v/KyoInIouF78ODw8nMj1tl1RF1Favnw5VqwIpLSFCxfi9NNPx5VXXtmwgW02CClKwh48gaKkqzcUskapT/ZeylfUz2e1JoAyj1yoR5mcdOXLueYAJmQzK4jS1Lneb4OiBECmqlUL/AXEg5am1UzrziGXSaEvn0mUeje9x9sWqvhEKkr+WKd1ZzGt2ztGtpOsfiBKUarEpGAoM5l2OODqTph6V7ZdvLRaJcSm9DuTPXg2bUU6kw0aGm2O+RbNYjk9EWlu+qx+7PgFmTD0UdKRy6Tk+ReZehdZoxR+Pe7YDhpqlFySWgR4+4wWIYfswTWjim1mmIiSWg8UNUvtajOw6bQVS0R0JHG904OmKOc7OkShhpkUibg+ShtHvP07XKhUvcZMluweUQoUK7GOrqgaJdIU1Xs9nkzohIDikjtexiHfvxu/J2mDNM10qFAOBQlxFvDVVAdxfoht18eqKAR2rWYOrrIM+nzQ60foa+J7KYv0QnLUPkoAMMO/By/dqKZoS6JEiPX9r6xXnBSbgSgHOBO/SVLnB+jHozXB4p+eWIlFbwzhmgVLQu+1Qw2V2HXyHFPUvFaMKB5jJRtrh8JmWu3hehf83RpFydsvReRQhBc75a3S5keUPv7xj+Pf//43AGDNmjU46qijsHDhQvzv//4vzj///IYOcNJDNpwV9uAJFCVqER6FBKl3aS31TqRO5f0+Ssh0SaKUtaJS77QXBFHyLcmpopRNpwJVxw+okqbeiSDIdlz5sJnalcHVp7wdV5/69tiCf4GZvd6+popPuEZJJUqA2tMnSeqE4nqX1MyB5saTIJY2wAWqK3Blg6K0fFO0okTNHLKZlDE9ynFcY5PeAiFK3QaXQAFRJ5LENdDcR8l8m8obVKekZg75TDrklBg3A6jUKFVUMkZRlilhrkIgynYQvItzdVsjUXKVINoUV531p2dwyPfvxmChHDRutiy5n+rpo2QK8vTPjEY431WU89X7jPE4SjOH8EZt8i3uK45KME026vThT2uUxHlcrjjyXMtH1SiRU0qvEfI+Z16n6RS+7O5XAQBn/ilIv41zvQOgHePaFCVxfxH7WD/eqopdqz24uoycknrnKr+BgGCKIdB+Xq5L7eu95Ry8yxYAgPteXqet1/ucPuGV1BW1UaD7spobXH2KUmuC5+EYpZbWUNFz44VVg/iPyxfgIc3waCKg91Giu7tVaZhx+PT/ee0JNgyrPfrawfWu5XVSvqJUQE6m3uVRTtQepF1RF1F67rnncMABBwAAfv/732OvvfbCggULcMMNN+Caa65p5PgmP6IUpSjXO4Ck3tVm5qCn3mXTauqdsEwWDWeRzslxZBFl5hChKPmW5Lq5g1BGxI07seud/7lSJShUzqRTOGTXLbH/jjMTPVClokSC/nXajU4nJoCaPmQK8nTQ5ZcUMwfX+DcQrSiJgCof03CWouK4eGmNd5zn+g18VxgUpSD1Lo2p/nHv68rItDCqOIyUKsYAcaxsB+YX2bSSekdnosUxr6VGKYnrHXVs1NUUkeaoOxfS8enW+PENZ8OKkulcEMdVfyiUbUeSqPgaJdUe3PSgu+ultVg1UMArbwwppihic5Kkz+jbajRzCClKarB138vr8M9nV2v9ltTaIaoQCHXHpEzRCQtKyk3ugIpLF3G9E+dJ2XGChrNVFCXAC8qiUu2CdUYrSiaoqXflkDX+WEyvrJIdH1AUtPTGuO9XCEEXiHW9k6l3BkXJ5Hqn1XhZUE075Pnpnwei0feCVzcoE0diiDpRog6QzQA956u5wYXJtXm/Rhn6NBNxZiyUWNNz5aNXPoTHl27Cp//vEdPXGopA2RWptVRRaj+itGjNEEoVJzQJ2Raud5RktlBRokSpC6VE7UHaFXURpXK5jHzeC6DvvPNOvP/97wcAzJs3D6tXr27c6DYHCKKk1yhF9VECZCpdvD04VZS8z2fLeo2SmnrX6wcl0uEu0xXYg7s11ih1Tfd+O+oNWtQpiWAoKVESATwNQOh3k3g5zOjx9jVNjVs/rCpKeqoboDqw6QTHNOMdpSjRB5IuQys1SuRuG069M+8vqdrYDlYPeDeqg3fdEgCwfJOJKAU1HDtvNQXnvO/NuOhDewfBJhnPYMRsZFGpUUrLoBSAJF+AajleLa3K5HoXlZ5JiY7uqCaCnKjGrrl0Sjn3gfiHCt0HFaIahcbvH1f9+JYqwcy+CAajUu+UtCzDmESQPVYKrJ+pPXiS9JmQolSlRkmsj+K03z6BL93wBDYSkiNS78oGRalHtgcIPzA3kqbJdPbblCJpulaU1DtCDvQapaCmi2yn41atUYrr6yJScymoFf5QoRJyeYurQ6uWoiJT7yLIW0lTsauRQAHXDfaDWEYmZcl7vNgHao2S+K73OxVRoyTuK3tvMw0ze3MYKlbw5LL+0Jj0a3K42NxZaEVRUtK/DNeHth+jbm3tYJYQ1wetGEGUxD2vGSqYnvJoqoNrF7iuixH/Gixq+zWJmjMwVsY3b34Wj7w+MUqdG3EONwWuC5S9eMOrUfLujV3YDFPv9txzT1xxxRW4//77cccdd+C9730vAGDVqlXYYostGjrASY+QPbivcGTiapQSpN4ZFKW0RpR01zuReicVpUxemjlkIlzvlBolxw7szbune79tlYiIgF5cNEldvcWDlgZZVHVIoijNkIpScHOjLm4AFHMC03r0HPNeg9NbktQ78ffl97yGqx5YrNxgaVA1ppk5RBHL6d05uVwRhO0+yztPXl83gv5R9TgUtVqsUw/ZCe/abasgfYvcYKmaQlGyHamedWfTSKUsSeimErMEqs5Ve+jVpigFy6WKkuO4clx0HHTf5TKp0Ox13NAURclPvaPngjj9xHHVHwq0RkmMY9vpPaH1OK6rnD/hYMyVZITa7GdIw9kkM7BJ0rH013Q3vuGipzTStMQ4MwdBlEYNs9tRipLp+qIPf6Eceql3AVEU11DQcNYnOv73MoqiFCbw+j40pQQJbDczILzinFD6KBUqYUWpHK0aJq1RqkhFSX1fJ0r6+1HXIH05uD9boea8ptn+wMwhmLSi9uBif6dSFt7pT+Dc+/La0HJ0ojRiSPmdSEQp+9Xs803/CyjPgBYFi3FEiWY9mLbBNBHQaNDVint4MKYJX31NKJJJr0KEey0QPfH275fW4saFy3Dlfa9PyPhaqsbZJYi77BhyKApFySptfql3P/jBD/DLX/4Shx12GD72sY9h3333BQD89a9/lSl5jIQIpd4lUZSS2IMTMwefKKW0VD29j1JvqEYpH9QouWqgLaAQFJpm1z3D+22rQXaX5rKXNAddPGjpTK2iOiQhSn7fGhqIbRwpKg9Hk6Jkkbx7/YFpssSmgWDUbGLZdrBk/Qh+cOtLuODvL2imD8HnRIBlMnOgmzzdV8sqtiu/s9vW3nny0pohvOX8O5Rcc1OKIUCCTRJdDY5FByuCgAnVSKTf9RFFqYucY9VmuAIlIuyWpoOeu7R3y9qhIsq2i3TKwlyS3kbVpVwmrCjF2oMrfZRURSmTskL9YfSZRsX1zt+eqd2GXk6upjZoYyqS1NMx0rg5larNzEF3NTSaOWjrpjVK9DjSc1fWKElb6GAfi3PN1Lx2E2marBAlknpnUjRM9uBA4F4p1hm42/nESqlRMtUk6f+b1RtA7R+2wk/Foal1Q2Ph/PzY1LsqwbRIR4tOvVNrYpLW0tDPUaIkFN37XlmHM/74tHI/0PtLpTRiZbL7f/tOMwFAMZ0JzBxaS5TovqGpd8YapVBKo3mZSupdgtTtiUBcw+hqitecaTGTtg2Cqig5yr6sN32sYjtY8Or6SBOaekHvT/p9PonrnbhH1tovLSnoKdZ0Na4cpCIWXC31roMVJbNNVRUcdthhWL9+PQYHBzFjxgz5+he+8AX09IRnSRkxCNmDixql8brekdQ7P1XPKo+iJ21j1BbqRAqZdAopy7vJ5/26jcD1jpg5RLjeKTGsIEpWOjCc0IiSHpwmTr2TipIdeg0wpAAavi9IjTIz7nqF5FtO8YIdXcGh37cdN5RjTutyCmUbuXRKeSiVImYTSxUHr60Ljl9RCUJNilK4RimXTsmbj5j18x503s1xt1lTMLUrI4P851YO4CC/mFoQTr2PlokQRilKALDRD3DF+ARh6qOKEiEo1YhSQCbCbmk66LkkPm47Llb2e9L/7KldSh1Tby4j1Y9aUu8KZTs0S09/Z9Je2lex4sjPhRSlCpld94PGkGMkhGIUnXpHH/qFkllRqsv1LkFqUVRwTwNBmRbmq25ZQ+qdmJGl1/6miNS7HnJ9DZcqmNqV1WqUfKJEyCpAavuEoiSdCr33dUWpmjoQZ+ZA1ajF60ew45a9yoTOoNZwlo6PLlugVjOHcOodVUUc6EOOCuAUVdsff4YQn5//+1Us3aCm8eq26ynLkue1yfUOCCz7qblLUKOkXhMmE5korOofw/SerLGuLSmiFCWj4qq9lMT1rlVmDnFkwZR6R5+Rs5tMlGxH7f1Vrypy9YNLcOE/X8RRb56FX316/3GPUYCS96h+iIB3r3FdN3SfF9fERJGYKOfGpkDU2MNC0c1Ie/DNskZpbGwMxWJRkqSlS5di/vz5WLRoEbbeeuuGDnDSgypKjgPYouFsEte7ODOHAe9317SgpgnA7FyQaiYeXsLQIevPsssapXRgDx6VemdUlHJT5Pf01Lu6iZIfBI2VxQyyWrtSTVHqzWdkIDWi5b2L9DvXdWOUlqCZJQVVyAbHyqEUBxpEFm012Ka23VHOSKE+SpQokX0pFCWKGT05/OVL75QpeHQGqxixnSYL58EYoiQUJbGcudO883b7LYIJE7qP7CqBQtBHqUZFiaSdiVn9bWd0qwGaZjYRMnOIeCDrvX0CMwd/rKlgWYGZQ1zqXfRt16li5kBVHa9xcxCgpq3kRClRH6UYokTJCn0AytQ7g807DWD1Jsi0zonWENLvC4t6tXeV2H5VtZA1eJqZg9gkek45rhsiEzpBrWiEgIJOnixeP6KsHwg3nPXep2RYXV41MwdxHEqJFKXkrnd0HIqi5O8q/b7pfUdTlCz1WqzYLmZgEFu+dgtQ8u53GYNqLdVCbWhJFaW1gwW8++J/4zPXPBr5GcdxsV4z79ERVaNkuj70cyGq/lInIs0osC+Ubfzx8RXSwjo+9S5MlFYSk4LecRDPpKC7pGw3JvXud48uAwDc8cIb4xlaCPQ60O9jYeOU8PfFeT9RaXF0sU03c5A19j1edoRMvdsMXe8+8IEP4De/+Q0AoL+/HwceeCB+/OMf44Mf/CAuv/zyhg5w0oPag1eIL3+soiTMHBLag6czQM5ToWblg6BXPLDErHven2VXGs4KohTVR4n+IxSuXC8xqdAUJS04TWoPritKmZCNbPz3p+QzkliMaDUS4uFJH2i6rTRNSaMXPH2w9o+VQ8tWHwBEUbJdLNsYPIyiUu90okQDPEoURI0SRVc2jZ227MU7dvZUJKpaBTVK6n7MGAhhXOqdCHBFauD8j74Fv/3cgdhnm2nKOOS2VUk9KUmVhipK5tsUJYqU4AmitM2MbkXRoA/8XCYVUtPEDKAOXVET+0bWU5F6p7KWeicOV4n0/6LB/wF+GpKA48abOVD3Ki/1LlimmDhIYgmbpAlpqEYpQgVRauqkohTsGwF6rlHVrGw7Chmlf6u1ct7rFcO6U5al7FddiQ1qlMLHwHENClJIUYoObugYl2zwiJJ6rTkhQ5Qo0gmoipAJYtuiFSWa6hVWy7qW3g3c8/0QQ6uWemcKdPS6Ja/hrP+aryh9OfNnbHfvV4FnfgcguJ6VPkX+91dpzbGTKkrLN42i4riSqJpw7t+ex9svvBPPrhiI/Izieqe48lW/PqJiUp0kNyP97m9Pr8LX//A0Lr3rFQCIValN9uAryHFI4vQ6Huj3XNtpjOvdPttOl383Mv0uqk8iEJ2ySxFX79gI0GmfptuDS6LUhYrjTJrUu7qI0hNPPIF3vetdAIA//vGPmDVrFpYuXYrf/OY3uPTSSxs6wEmPtB+82ZUaiJKoUUrQcNZ3vBO/t84F6xDBgiAvnl14Sms46xGedIQ9uGVUlHrDtVdi6JqCUavrnQhAstr3qilKU0hT2tEIRYnODnVlzATiv294AvuedzvWDnr7kZKagbFyaNkU9J5VqtiKGx1dd1lJvdNqlMh2UxKgK0pZ0oBUEAKqaEnlLBOlKKkz4lHo91PvxPjmTOvGIbtuqYwtmw6Cp+pmDuFAVj9HBEGi1vbU8W2l/5Dfdnq3ojLQGqW8oUYJUB9eD722Af9etBavrFWvMxH4SFKXspDNWPK10VJFpiiJdE9vZj9cr/GrT+2P+f/5Fnz8wO399bux9Ss04BkrBUSJ2mMnmUXUZ8jNqUXqawUluCdBdTlMlAK1jabHBmYfdBv7R9XziwbHVGEQRMk01pTlLV9P3RLniKmWRoC6vQmEa5aigxu6L0Sgrs/g60pGXMPZarULesPZuNS9ciWsKG314HnAPd8D1jytvG4KSNMkpdMU6Oj24F7D2aBGyXYczLI2eh8eXiuXCZgVpdlT1edeUte7KCWX4qU1Q3Bd4JW10ROMysRWFUVJvz6iYtI4h9OJgrimxERWbN1j2UCUiKI00Y7m+q6tOOo5Wy9R2rovqB18blU0ORb4xzOr8dzK6p+j9yddUUpi8BGnTjcCjajvqhuVoA+o7bikj9JmSJRGR0fR1+cF67fffjtOPPFEpFIpvOMd78DSpUsbOsBJD5GiRhWlVCYgUCZUc70rDgNjm7y/ezyHIWHosFUmuAGKmT2hKGUzlq8ohRvOpp2o1DvyDyVKKTNR0hWlKOtnHSIIHItQlEz1HhS9+aDBqB6IiCBGLDubtkLLFwHfy28Mo1B2cNOjywGoKlH/aFhRikLZdrGEzH5GmznoqXfBMmigP1VzJqIkQnyOPhBlH6WQomTJ8QlE2YMDQW2JrsDRsXmNhsOzyCaYTAAyWvA73d9WahiRJiRhJVGUqBpFHdRMNUpAECiUbQcf+9XDOPXqR3HLEysBAPtsO02+B9A0QaIoVRycevWjOONPz/hjzPrfCVslA8C0niw+uN82klC5rlofoMdUlCgVyraiUo1HUTKaOcSk50XVKIlrSFxjurOgdL4j/XF0R0aabkXHIAi7aYZbbLu+Pr3hrIhmQ4pSFYUtzsyB7guRTqsHUHFEKc61zoSxakSJLLCi1XsAQKroB4MFNSg0XZqZVEqq/qZxBbbp/rIt9Tys2C564W+7bxss7sOmwvePH7g9vnT4rvjo27cDkDz1TlxbcXUQgpjF9TJSa5TizRzC5Np83elKXDOIUllrYRDft4sQJVcQpVHy+YkNcE31gHSI9dby0PvVE0s3xX526YYR/PcNT+CrNz1VdblJa5SAeDfRSVmjJGrss12oOK5qDx6T/tnuqIso7brrrvjzn/+M5cuX47bbbsPRRx8NAFi7di2mTp1a5dsMBdQevByw8VhUc71b+TjgOsC07YApXoM/QZRmZkiNkki984PqXDqN/bebiqzln9DpwPUunaRGiTr2RdQohcwDkqbe+QGQUEL0Av9qfKuXpN7p2DAsZt3MKgtdv4BIKaI3u4Gxcqy7EEWhbCuF0YrzkMEeXMzEpzUzB4GpXRlFeaFpTuL4ipt6haSBhRWl8HaJ2hCKXj/g7ZdmDuaaLvF3MIscf+NO4np3/D5z8JUjdsOXDt9Vvib7KLlEUZrRI4Myy1L3ialGCQgeMjQF6Nbn1wAADvTT5PSGs5m0pdQoPbJ4o/yuIEC248r9r59LYnyAF5DR+pY4M4exsi3fpzbOSQIxnWyYzRy072gBuAA9d/W0MH1bBaGm20Hrk4AEqXeG7RPHX78viPPb9clQUEtTpUYpwh7cFAvTSQUx26z3itKJ0mjRljPK4dS7aoqS2t8mro9SyXZC51BK1MGWC8rrJjJAU+9MsF0XZ//lOfzkjpe9ZZPUO9e3B++2xPrG5DLp+Ok2dOfS+Poxe+Cdu3kTfElT7wJbfjtypl6srxRzfagpX2Q7E6SmJrEH99Y/8TPrtpYeHNdyQK1R8v6mipIebN/+/Bpc8PcXGhbom6413RShHtDx0Z5dJojn2KbR6OwJAZo1Eud6B5jvq+JcnSgO0wiSWTciFCXPHnwzU5TOPvtsfP3rX8eOO+6IAw44AAcddBAAT13ab7/9GjrASQ+ZekcUpWwVlxlRoxTlerdiofd727eHvjMzHdwAxQNLpt5lLPzoxHnBdzL5IPUuScPZih/wpHPBdmlKVL1mDuJzQY1Sbal3fV2Z0GyzgHgYi+Cty9CkVF+fbG5JbkT9o6XEM6BLN4wqD0w19c4NvS6CfCvCzKEnl1GCRJOiZHJkizJzKCupd+Ftmu73pBJBrr6cXCYYSyZtBQXcVWYnZd1PjOvdtO4svnbU7thtVp98LVCUgtnQbaZ3Y0ZvDrlMCnOnqeqSyR4cCB7ayzeOhd47cCev1ksEXIo9eEatURKYQlSvInES0yHO37LtGGd4BfTUuwolSg3vo6TXVhAFgKqelChpakdOu256DERpk6Yoqal3JkXJRJS83/oxpYqp7Qb9kiwLSi1NtRol8X61/RQQJU1RGvK2UTRi/tm/X8XB378bI8VKyMwhTvEACBl1hKKkvq9PuujvW+I5U1HP8cjUu5h7q+sCv3loKe56yUursywopiIVx0Ev/PVJRSk8GSP2gfiuUH+T3k9p8Bk1iy4+E0dEowLLJEQpcepdE2qUxD6QilKEtT+gKl7iXKFmDvp58YXrHsdVDyzGnx5f0ZCx6vvNdhrTcJbu5yeWxStKdsSkhQnDNShKrmFxulNko+EqZL9VilK316pEpt6VO5oo1WVnctJJJ+Gd73wnVq9eLXsoAcARRxyBD33oQw0b3GYBaeZQIdbgVRSlHEm9cxy1KQgALPedf7YjPa18RWm6FagYWS31Lp9OwaIKEOmjlHYS1CjZlChFuN7pZg4JiZJQBiRR0rY5ykgsm7ZQtl305qKJkgg+CxEGB4AauANBAEhvrIM1KEr6TGmxiqIUmDmQMVGjAr8GSyxHVZT81Dt/+2gQF1L4RFqMknoXPvbTe7JY2T8WUrwEcung/2zagslNzwTdQhsInyMmUiw+U7IdwN+8OdO7kM+k8dcvHYLeXAY/ufNlMr4UcgblUIyP1o8BXoC7x2yPmMWl3umzxXTs4twwnfPSWawUP0M5opk5iAdhrfbgSfooRRkaAJrrnSH1rhylKBl6KemzuFGpd4OxNUpCUdKIEjm/aUqPZVnIZ9IYK9soVpxwGlVE2mFczQHgKUm244ZqlMT/03tycjtWDxTw3MqBUN1mXCBPFcey7RE//TjpdtR0zBYcpBz/nqwrSobThhLwJKD24I4LuI6LnrQgSpqiRM4hcUzFe1NqJEq6wmm61+u2/iZEpa2aXq/WpFhATwcsVzHraARoCjEQn3pnsgdfMxCcG1EK9eIN0cYZtSCkKNmNMXOg27l2qIiK7RjVfPrZJGp8XOpdMkVJ3EuqrqouqFbr5s9sGC5i/XBJPtMaBjLZb4+5mpnDZpZ6BwCzZ8/Gfvvth1WrVmHlSi+H/4ADDsC8efOqfJOhgJoeVALHkFiI1Du4QFm7WbkusMInStuGidJUQpT0Yv9sOgVU/DQJK+XXSnkneipJHyWR0kEIVqPswYWlsky902aqo2qURGDmEQnzZ0aKFdzy5Aqc+IsFAMKkyLQ+sR30xto/Vq7bXcfUp8dkV073F92XU/IZZYxxipLoJp5Lp0JpNYLQVAwBKlVCZvaqLnvdOS01kYwlk0rJ41e94Ww4PU0Pfs1EQ31t1tS83AfzZk/FdjN7lOMamXrnH4ZlG1WitN/2M+SEgh5weUQpqOOgw3ueFAcLcmAK4sT4R7UatziL7kLZludfSlGUQosPIZmipP4f1VcmTlHSt7Vb1iiFU+/E8VixaQzfvPkZPLFsk6YoCdc7Q42Sv/+yGfU8UB0XgxS7lEXqpUp2KBjTC6LF26aYTQ+uRkuVyFqZaVotYf9YOaTcxaVm6QSs4oTtpmlqmW4PnqemPJqiZJrh9mrfIocTgmWp16frAj1a6l1cjZI4jsKhMrmZAyXu5v0nleAYIho1y59kIiHqutOPZzNc78R9tuKrM0n7don3VJXJvGGNcpLTF6/XKNVLKPTrMu7ZI4lSEkWJ3KPD9uDm5aqvmWsLGwW14ax5ez5zzaM49qf34Y3BgvH9uuGrxsh0o+I4KJIaJT0duZNQF1FyHAfnn38+pk2bhh122AHbb789pk+fjgsuuABOizpPdyyoPbhUlPLRnwe8GiDLDwB057sNrwFjGz0jhtl7B6/7rndTEASAIrDOkT5KckYg0+U/9bwHVpSipNYoCUUpGzTStdXAT1cwqqXMCWSpYoBw+lJUeojo3dLXlTEGxoAXKP3hsSCNgBb9C4RqlAw22gNj5appM1GgDSpNDk4iwFRS72gzz3xaCUrjapSijBwAat1LUu/8GqU50z0Cn7JUIwXAoChR626iKFWbsZMqTYzrnemc0c+HbaaHVVlKJL3Uu/ByRPCzXCNK79ptS7m/Hdd7yOkNZwGh8gTf68qmQ9b2JqInjqseGMa63mmKUuD8V/0cTOJ6p5MHeq5Xr1ESRElPvfPOG+qgt8knStvO8I7ZsysHcOPC5TjxFws0RSncR0lABPP6JIeiKNkk9Q5BX62RUsWY/iP/rjK7HVL9ira8nvXrRHenXDdUDAVXcSkqumJdsV1D4Ktar9Pxd4FMXGmKkmn2O03OqySgNUoCPVrqnZw0IcdRNqz1D5fYb8PF6jUjgHpuRs1cJ1KUIt5KMpEQrSip46n3GVELRIBcsZ2QwRDdFtd1jam+yqRIxHY1jijphKYxrnf6PS5uv4v7zHgVpVpc7yYqLS6JorSyvwDHRcOI0oOvrvccA4mZg1qj1Nl9lOpKvfvWt76Fq666Ct///vdxyCGHwHVdPPjggzj33HNRKBRw4YUXNnqckxfUHlyw8WxP9OcBj8Dkp3iuRcUhAHOC91Y/5f2es69n7y3gK0pT3IBYSdc7P5jIpVNqnRH5nYqoUVIVJfHdiVCUzDVCxnEQvG2HGfjXc6ux77bTQ+ue1p3FgN/7iAZ7H9xvm9BydDvywLkm+N7AWLlulxk6Ay0CXZNduSCElqUG/lPyGWWMdCY9VKMU0WwWiG84u830bizfOIbubDr03WpmDklrlEQdjKooaaTYwHd1ZWxmb3iygY4pX8XMYbmfo//Tj74FU/IZHLr7VlpT4MAQI5sKejLRh+i82X349vFvxud/8xgqji2DXHONkvd7VEs10h+mSh+lki23KWVZSp1WNYjjK1JTzWYOOpkKzzwDZkWpRNISKaSiRLZDpN5tM6Mbr2t9cEyKUlzqXcj1jjY7JjbgKcuSqsVoMawouUqwER+06ef0SKkir92t+/JKjZ9+zq0bKmKXraYor8UFdHpwWrKdWHvxita8UyFKoRql8Pqq1SjpsCz9WnRJjZK3vkC1NqTeaTVKhbITmzIlN8XQTFuHNHxI6HpX7fV6Gs56Y52gnCu6Dn+8JdsN1ZjS/e6lbwbviWvclBapY7TcmMBXr+PRm7o3jijFKEqyRsmbTIlz0R2NaTibxPVOHP+JKh9SjmekQuoT6QaoWhtHSvjErx8BADx39BCmAJ6Zg6ul3nWwolQXUbr22mvx61//Gu9///vla/vuuy+22WYbnHbaaUyUagG1Bx/xCmLRu1X17+WnEqJEMLrB+z11rvq6T5S6nSAQEYHVLltNwR14Aztt1QtUPIcv2cdJEKVENUoi9S7ovxRqOKv3J0pco2S2sRaImvU8+eAdcfFJ+6A3n8HTy/uV92b0ZGXvI/EQ/f0XDwo1ATWtr2KYgeofLSsP7FpAgxu9ADeTCuzKxe5Kaw02e/MZJZigM+mhGqWYWixjw1n/QTvXV2m6EhAlvRls4holotIIpBMca51IT+0yqII0bTGdNps5+ONb4StKu249BXvO9a4dOvSS7SiKkgjIaVDyty+/U6bljZWDINd0zqelohSfeqfagzvozQtimXwfA0GwlEunULZto+OZvpyovjKmGiXTcQRIjVI5HGzMmhpOOaYcJN7MwTKuL5dJwbK84KHiEFJhqaRNLDJl+YphhMWuadfqge9IsSL3w45b9OK1deF7rsDaoWJsKpSOUOqdHe6TpLve0fe7LEqUVCe+elzvdHiKEkkBRhlpy1+uPxGYMaXeOUJREkQpuJ+MlGxM644nSmXlfKyWehd9fUQF5clc78zL1I9nU1zv5PPJwbBGlOg1pY9F/EvP6ShiN5awFUY1xLk2emOqL5jX087ins166wP9PkIRZ+aQxAmxuYqSeZvlGBpAlGh7h0dfWYXDAWnmUHA34z5KGzduNNYizZs3Dxs3bhz3oDYrUHvwIZ+k9M2u/j1Rp1TSiFJxUH1fft5LveuyqaLk3Qy+ccweuP+Mw3H4HlsHCpBQo3zCY0USJfKP6JmUJkRJ76Okp97VqSiltRSbqBmgdMqSs5M62RLObcPFCob8m98UQ9qd6bvipqvU8oxDUaIzU+LBVNCazQLB/kqlLOXBPCWn1mAZFSVbS70z2aBrwXahbMsH17aEKOmpdmEzhwh78KpEKVBp9DEJmFRIfdZ7iokokTFFud7ZrouRYgUb/HSw7WYG6i7dv+WKIwMv0agZCKzUUxZp6OzvZ5l6Z6pRSokaJS31znXx4Kvr8cyKfu99jWDIANOiqXfVz0HxPWEkYGyoSVQnwDvnr3t4KT7x64cVy3hTw9nA9U7dVpPrndgvW0xR69768hnloR/Yg0fXKNFjLOplxHF4ec0wBuTxIYpSKbCUFt+nq9BTlXRU5DHw/h8p2vLa3XVrVS36+IHb45g9Z+Gdu3r21+uGirFmDDr0GjaqBtLUUDk2TS1UapTKeo1SeH2ZGhWllKVeizLtjqxPZDKo9uDeb/HdfCboe5fE0IGeE1H7L0nqXSRRMryuXzLRrnct6KMk7MEdN5S+SBWlMClxpK27QNQ+UZomOy7O+ctzuOXJ2p3wwoqour/q5RP6fi7H3BcpYah2/6SpjPqxDaXeGU41ca4m6XdXD5Kk3gU1WeMfA13GyyvWeX9khT24FwfmrQpK5ZLp6x2BuojSvvvui5/97Geh13/2s59hn332GfegNivQ1Luh1d7fSYgSdb6jEP8LC3EBX1HKV4LPi1mTdMoKAkJaowQQRSlJHyV/hjKdT9xwNnkfJS31LmEfJUVF0GpSZvj1AqOlinwYJyVKwYMouBMNFiqx8r4Jorhbcb3zlymCSeqKJfZX2rIUchWuUQq+IxUlP3gzOeMJBClyrr9N3vGzLGD2tG75Pf27esPZbEYlSqb+TCaIlI841zujmYO2KabjSIlONm0pznwCtuPKHiLTurOY2hXUlFhExfMayAZ1OKLeSwTznpLhE6W0SoJMipIlg2z1OusfKePk/1uIz1zzGIBwHyWxPz3DDD/1LsEDWBzfXDr6uIgHuSDUFcfFbx9eigdf3YCFpFcUnZWWrndyXJqiZCJKfrCx1RQ1XXK7mT1aH6UE9uCKiYg/qeDv3E9e9Qh+cc9rAPwapVy4Rkl8JzL1zhB4iPdF0+dRknq3i0aUZk3twi8/tT8+fdAOAIB1w8WwmUOcoqQR6TLpk2Qi/vR9QE29e3LxGiwmqY7mGqWw4UscPNe74P9ei6hWJV9RMiif4pylz5NaLMJVM4fx1CiZrx3TzHuSehRvPMmVjUZBptDZTij1LqpZtPdeeB/Q641eF3RS5/YX1uDah5biqzc9XfNY9V1b0hS/+hUlbTsSHvdqNWTDSupdvKIUl9I8Yal35O+oc1Ic00YYStD9lXOD+NF2XIwiyBJwy+GWG52CulLvLr74Yhx//PG48847cdBBB8GyLCxYsADLly/HP//5z0aPcXKDmjlIRWlO9OcFoprOFiIUpa7pAIBMOVyjpICSHUASJcsxzwaYa5Syakqh68pIULfCTeqopI81aeodDarjFCVBcExKhLd+PfUurChVHKfmh+CcaV0YGCuHLH2BIICkjnIiaEmnVKJE64AAc+qdCGhFcbGxsa40XfA+K9I2puQyktR1ZdMhw4s4RSmTDupnqj2EAsttGvBWVw91wt3XlQ19JkkfJdcNjBy2mxk2hMimU6g4XqpmmZAUQSYEsVQUtUxg9OB93lSj5M+ea4rBptESKo6LjSPedTmq2YMHtspB7VaSh1+gKEUTJSUAL3rHRlclAU1REkTJP5+z2j7uyfoqjuH7uqI0pSujNGqNrVHy92lGUSJT/m8LRf3zlqWoWyKgMFms08kQU+AhzumpXVn0j5YxXAxc73bTiJK4Frf20wzXG8wc4q4RXXEskz5JJlfPsuOCzt10EUVp0fK1OPen9+GlC46N3DZ6XiWBZal24t10z2upd3Q7g9S74OO9uYzcn9Wgmjl4y/3b06uwYbiIUw7ZCa7rBg1n4+zXqwSWFEkbzor1ibTOZqTeBX2UnHA6LxmnSVGKM3qhf1PSvm5Iv8KSQ1dp9f3TjBolJ2JixATVzEFTlLRDa1qWeG5MVOqdWnMWoZA2UlEi+zUvJmKy3ag4LorIwkYaadiwdOOxDkJditKhhx6Kl19+GR/60IfQ39+PjRs34sQTT8Tzzz+Pq6++utFjnNygKWpDb3h/T6kh9U4/+SIVJe//TGlQvmTMw60Qi28yvujUO1qjJNL2gka13uvBd/ONUpR0M4eIMzmTjiZKIvCnN1CaGx+3vrLvNkVvShXblTfBKCtyii16c3K5auqdH4yWwoRGBNTplIUxbTaLBomqouS73pVFkOv9Nrne6TbeIjjt68pgv+2nY2ZvDu/efSsc9aZZysxxqEaJEoVUYJ+duEaJbIvOK0znjK4ymQgvtY6OTL1zXKz2nYDmTjMRJW8ZJdtR6nBEABwoSrSPlE+UhKJkODfE8PXZZ/G/43rERW84a8sAP7Bgp7Pfjy/diE/8+mG8tGYQFOLhJhWlmJlPsW3eRIBK4r0xBn+L8VGjCwpB+k2K0vRulSg5jmpEIAKUuBolSsyoYq7DsoAeqVgEToVZQ/oaDX5Mp6/YT+J+MlSoyGBv+5k9ynkmJoq26vPur57rnXbM44iSwR5cpt6ZFKWKpiiRGqUuS7XsNduDp2pOvVNUoZjUO5OiRI9V4HyXJPUurJKc+adncO7fXsC6oaLq0tgg17uwAYj5u+IaFqmezUi9o32B9Bolun5TPVAcUaLPyrgmtrUgrCjpRKm+5eomK3ETEJWIbTSBGu6EFKUEKqO43ptToxReh+sGTplRNUy1gO7nLsuP9XxFCbBQSnvZSim9lU0HoS6iBABz587FhRdeiD/96U+4+eab8d3vfhebNm3Ctdde28jxTX4IG22nxtS7vEi9UwOggCjpitI0AIBVGoKFmAtVGjKoqXeWnaBGSapROZUoEZJVr+tdtTqVqBqlTIyiNKNHDcxymZSxbgcIB7fUHlqgTIJnk1qjY8speWPtjvg7UJQoUfJ+p1NWaDaLkhNKgqJqlIyKEqlHAYIgZUpXBnOnd+Oxbx2JM987D7vN6sN79wzOUz0Vj5ISqihV7aMkVBqyv2nKG2Ce4bY0W2KTmYPSRykdXaMkipRN6XviO2Vi5pAjNUoiPSyvpR4Cwf7X6+uAILjUL8mSkpLpKgSjWAnGkE4FBJLu4y9e9wQefHUDPum7Esnt1NK1jGYOMvXOJ0p2cM6PlWiqk1rzQK8Nva9Rt6wLCgcbOnGnJAAI9p+5Rsn7TVNyM6k4omShl5g5uFqgTu+NNBAwOZ1VNKIk+kJ525tWrOrFNbqlr56VbEfWw8ntjFE8CrrrHSFCpv5cFcdRAxmSekfVJSDa9a52M4fg/x6LECW7CDi2kt4r9qfuegeoqXe3PLkCR15yL15bZ56VVlLvfKc8QdrHSrbyfj2pd0mIUnTqnTcOsT3NsAenilJ86p0e6IevL4UokXOJ3ouiyN8rbwzhKzc+iVfXRqsJ4TYEDVKU9D5Kca53EaqZCcNxilKCc0I2nJ2g06AaUVLUcn2frH4GGK3NZ4ASyy5FUfLTP9Pe/S9V2QyJEqNBEISiNAKMrvf+TpR65ytGkTVKZjMHCy6m+LN8urUlAKIo+STCTw207BJMXERJeVPMHAgJIRbh9RMl3S1PU5QiFpPWgmOK3nxaUX76IuqTTOszuU1VyGycSa3RscWUnDldRhKaMOkS+ytlWSG7TUou6HeCGiXf9U4QJYM9eFarUQoUJe88oEHT/3f07gA8QiH64wjoqXdJa5SCup/o8yRJmqWJ5Mi+YWmvfkhXNwGPMASBu2n/UNIQkDrxWeEQSIlSTldDY/oo6VCsnh0nlHolrGq9WhLvNUouROra+mE1GJeud1ItMgSCGpmqOME2U0VJD+wL5SAw1a+bHn8/UTU06nx0XFd16KqE010FxHmZVc47728TMbUsStqC1DtxbKICpzj7X0GUNpB0wa5MGlv3BbVX4r6Qz6RlT6U3BtReJrWYOSiKkuF89pTv4H9q5qBYhcN8bdZj5mCROqUePemxPKZMetg+WRKrpvcXQSyGizb++ewavLp2GA+8st64XhrAFytOqOaTOt3FKQZRFt9jZRsfvfIh/PTOV5SxU5huba7ryuMpVO44U4FGwSZmDkPF8DkjEHZtc0L7RyFKhlYA+jIp/vD4Cvz16VX40xPRJg/VXO9qdWZbM1AwPp/jGv3SMcQRWdd1MaI5j8aNNY6oTJiiRIZkyhTQHf4kVjwO/PJdwFVH17S+SgRRkqpmxlOU0qL9TQeCiVKrIWqUBlcG//fMrP496Xqnp95F1Chlu2Td0VR4zJ7OCkuEzByC1EDTjKVao0TS9lIkUCVNZ0NmDkmJUij1LrpGiS5SNXPQVI90SgnwTY1mo9ZXdtzQbAydSY9SpiiooqQsW87a+wFkzpR6F7YKzkQoSnrDWXGjN6UZiv0hZs2EQmIiHrtu3Ye/f/md+ON/HWQ0XDhgx5nYY1YfZvbkana90xVEVVEynzP0HDDWKPn7R5wHkYqSv1/1uitAVYfkWA2KUs6gKMWNP+oyCClK2jEXQVBa6aMU7ONZU4Mgnc4US0VJpJoZjosk/cTMQRCsYkzazWjJVhwBKYK6oLDFrq5w2o6rkRTzBAVgtgcXpCeqb1UvNXPwXxdW9FGzsvqq6bZP7fauEaEQ5TKeEcLWxPacEmhhXrFGa/oYW6NkaF4aZ+ZQqqh9lvJa6h2FKXBLpWprOCsIvyBXiusd4BElck5UtPRluq4poiFwsRLcEyN69+jpZAXt/KRBchwRjXIiGxgr4+HXN+J3jy6Tr+nnQpQVtPicVJSaYJOs1Cjp9uCxNUrhlDVTtgMADJcq8tyLSuESxyGuOW2cig6Ej8mq/jF86BcP4i9PrQwt66U1g3jH9+7CGX96JnRfGi5U8LlrH8UNjywLfU+xQ495RhUr6v1HbyYcSr0zhVgTXqNE7lfVFCX6/tM3eL83vIJaQK+tbkGUMl2BYUSm13upspnVKDEaCKG8DPv1SX1zYJRudES63vlEyU+1U+C/NtXymP2ec6eGPxPRcBZ2yTgTblaUsn7nQWJ9Loat24MnrVGqknpHl0MfxKqZg/qdXCYlgyUg2vHOW6b63YrthB4oAJ0dr35pbTklbzTU0OtAusg+S5FARFcElYazJOikioDtuJIEmYihrAvwH6409c6EvbaZhnmzw+eRZVm46YvvwD//513I0IazVdJOxE03jlxEEaVqipLYP3FEyXHij6E4h8qV4PhnU2FFKY4omSccIhQlSpRsN6QoiLqddCogSvRhTet+aD+fihZcm+2PvdfEfqjYjgzy9JlUikLZVhwBKbpkulvYHjyfTeHyT7wVc6d5xMJ2wo1wS3a42Bygrnfk2o+rUUJg5jBKapTE9RhNlKJnjKdKRcm734nrlipKdHyiTml1DYqSyfUusHE3p94pfZSU1DvvbxFMRdmDJzXcAYLjIM7nXksnSqPKvVxPr1RS78ikjSBKuqIql6O53hW064aSz/gapfjgVbE01z5rUqPosRTPmmpNtxuBwPXODbkGmuq56PfCE4DmtEXX9ciSWI8J0kCjBkt2/bP6bn3g1fV4clk//vh4WKVa7N/jXls7HDqWjy7ZiDtfXIurH1wcO4a4uh29Xi6syKmfNyo6dlB3OhGgyzXdKyMVpeG1wd81kDhFUbKIoiRSDLMeUcpWOldRqsn17sQTT4x9v7+/fzxj2TyR1g5BkvokINr1Lir1DvCI0sha/PZTb8KqaW/Fjlv2hj8TYQ8Op+wTEPXGqoQgIce8rFefRGqU8nWm3lULNmmcmUun5ANKVyJE80mxjB4SUEeRAW85YTMH001IqkAGNULHln05vL4+vP2vrRvBR375kAwyaY2S2Ox02kCUqtiDA96DezTGCr0vHxSkAwFhMtX8VINlWRBxcqZWRUkLsCn5jUy9UxSl6D5KOe03heO6cr/GKUpl4gBH+yiJ806pUUpwzkddBjSQoXUXAuL/NEmRcl0viEulLNk3CACeXTmAPWZ794XAqKF6H6UcrVES9XMRM/uAN+tfilKUROodrbUSKabZNI7dew6m9WTx8V89AttxQ8FoqWJ2ljQrSiL1zry/hXo6WrbRl1bVJxorqfbI6nLoezL1zncoFNftVoQo0RRL8foanyiJe1NcUKkff9onyZzG6ypBICVKwqFquFTB1K5shOudlfgeDQTHIeU/Kqql3lVsR/lfcb0jNUqyCXdEk9OSEvw7yky/7bha6p2Du196A6+tHcHn372zspxqs/yKU18C9YAG0kGN0gRFyAT0vNRVSBocmxWl6MkAfeyDY2VM7crG1Hb5hC3WaVD9v1oTVzFmE2kWx0Q/7wHSh814rwv+jjs+o0V1ncWK13dKXNdJUu8a2ezVBKcGRUkZ38g6+WdlbAD3LyvhrTvMkPe1KND7cRdRlGzXe/a4/qR+1t5MiNK0aQaVQnv/05/+9LgGtNkhpZ2EfbOSfc9ElFw32h4ckM53M1NjmLlNxLG0tRolJfWuSm2FTcwcxHfLUFzvQjVKCRUl/WEdUpgURcmsPliWhSwhUbqiFFejpG97xaGF9Ja84YjUEJ0QmnDILlviiaWbQq/f+eIbyv+K650oULes0AMmyh48pxEl0QdCrysCAoIhUsiqNeJNinSCGiVaGK8T0ySKEl2yiSiJYyj2h05gxPgKJHAPLyMwcygSEwL9eNN9rtcomfsoJVCUnMDMgZ5z4n+6X2zXRQoW+seCwPi5lQM46W3bymUBwXlifqDC/0wwEy4einFd1kdJ8bxOeMU5J64TxwkIp1BgaD2bqRlrrOudVhvnLc+8v0Xq6WixItO8TKpcnKJEgwTRc0uYOYjzZ860LpgglCaReteby2C4WKlKQimS9FGqpigNjEYHu5maU++83+I74dS7UeU89VLT1PNYYIpClGpRlBxF8Sw7jpIeVLYdfOuW57B6oIAj3zwLO5EJw2piD12PvrtMdzYx0ZFJBc6YTTFzIMG+riiZDFLke4YWF2rxv/re4FgFmBE9AVapR1EKud6p78edC4HttROa1BiTjpzhsdB9Emf6IBSl7mxaXovFiiOv9SSud4GiNFFEKfjbXKMUTsEGAGxaKv+87+lF+Mxf1uNT79gBF3xwr9j10Zo71R7c/zvnXV85ZzMhSmz9PQFI60QpgZEDYCZK5THAtdX3KUQ6XmEgerkVs+sd7BIyhgexMfUuE07bE6APc8tCYkelOIUBUJejBEtawE3VplzaUtLPYhUlbX0VO6if6MqkZN3PWEyQLXDVyfsjn0lj3+2mJ5qt7TbUKJn2W5Si5AU73g20WLFJc93wGAXBGCl5PXrELNyUfPysUjWYFKVV/WO46oHFOOXgHbHdzB7lPZ2YKrPOEbuMpqUZzRxSWo2SQVHyXO/CtWH6uEq2Ix/+uXQ6VJOm2KNr69HPJSAm9U5r5ir20YyerGLQoLuTefU9thIwPrdyQHkfoNbf4QeqeJDTPlziY7HBfClIvdP3cbeWekcJl0hflP2gXDcUvOs1AgLS9U5Ju41WlHQzB9lwVtQoRcy6RqXepVOWPOfWy9Q7b3veu9dsvG2HGaFUZ3HvCa4xjyhFkQHAlHpHFaXqRClvlUN/94+Wsd1McypQKkZREvcUCr1GSWk4CwDlMeliWfHrPOky6HVAz7uKVJQiiJJWN0LNRnSH0lLFkUqrXr8TVaMkhx+TemcKfKnCLK6FZtqDAwaiRI0vDPbWuqISZ50t+sZFpauJIDounVRPWdSJZFQNk0ldpLboOkbl5Ex4DLZmmhMF0eduiyk52Zi8WA6IUsj1LkbRmajUO7o/q/X/ku8XBoChVfL14Y1rAaSU/lhjJRu5TCp0P1AUJZp65/QDACzfoTlvd27DWa5RajVSDUy9k39bQQ0ThSBKuqU4RUVXhUTqXQXZVHSAon7XTzVJBWqUHDYhSrW4KYVd79Tv0kXRWp10jAlEbWYO4dS7wPUsJcdTSJB6t8tWU/DO3baU360GasyQJoHI9Z89ENtM78a1nznAWxatUcpSQmpJclCsOPJmb9peShaHixU5g2ZSaGqBOA70gfThKx7CVQ8sxnf+8hwA9eGm75ckrnf0mWDar9T1DgiTdsB7yJhqwwQiFSWtnikXoejp2xJsk3GTlEBmkKTRzexVre0zKdVC3XFdJe0OABavpzVKgaoKxD/QxWdMvY9M8FzvgmuDojunpt5RwiX2t+zlZYdT74pRipJ0vaPXd3yNErUHD/r4hGuUKgpRUpdTIURJv566iMPdn/7rYJz/AXVmVj8vxLUXV/iu16jRhrMmFbsSk3on/haqo7mPUrTrnZnwe7/FV7oNZg5AcEz0Gip6bQvFt1RxqypKij24rZo5lG3V9Y6aPZRsvWFoFaLkOHI/hfsohb8rJgLy2bS8/zSn4WywDlO6poA+FlHHCgTHMM4RTtyTogikCKLjVDR9l5t6O1HEGXuIz9JaRnGdjco+bCZFKfg7Lj1cPA+ndWdJ77tgHKHUu1h78IlhSnSpYh1rBgryeUCPvyS46xYpy8iWvEwXsS/WDxex7/m34zPXPBpan8n1zpV9lIC0H6vmHCZKjHqhK0pTt0n2PZPrHW02a3q4CUvxmhSlYHzd6fCFrayGmjnQ3zT1Lh1OI0uCsKKk/h9l5qATKkp4cpmU4vwWm3qnz6KQB3wmZcnxjCUwc6CBmyktSAdNvRObmU5ZeOduW+LBs96DQ3ffyhsjCZR0okad7+LMHPKZtHywDBXKgevdOIlSVgZGwTm0st+7cS5a4523ND2mHte7ahApNjtt5f2mgaX423aCQLXboCjRPkriAZnPhFPvqMKkq1tmFzYz8aeKi1AesmlLpnnR79NlHHjhXbj8nteUz4gAZMNwUQaOcWYOuupUUCy94wueZR8lPfXOPy9Fw16xfd415BMlke/vRqTexdYoha/9ajVKIyXScFam3gWfpYGiHgxTl8Ze7XypVqeoq21iMiJOUQoFvU61PkpBOqtlmfsoiQDKFLd5tvPm682kyNKG2IBJURpVxqqTYdV8R6idTmxwDIT7KNHrxibpnYB6vMN9hOKDV9cNrosk9uBioiOXTinbPNFQFKWSriippJHCcQKHwC5D/aJOMoR5TZSTmiAFcam6tabeiXo003UiPqtnfADBfjD2xFLGHKMokWenuMfTe2GSurUJtwfX0oaHixW858f34KTLFyjrB8ixWvuisoycT5QEkfrrU6tQqji49+V10GFyvbNTQbpxusubtO9yxyaMHE40xhf9MMYPWqM0fQdgj2OTfc/kelf0CZAp7Q5IlnoXajgbjK8rFZa6jTVKGWLmAEQ2nK1NUYomPIBmCR5Ro6R/T1eU4l3vwql3tA4jm06hUHbkjG+cPXiqxqBfNXOIDv4omYuqmfHMHHx7cEONEuAZN6wfLmGoUBmXmQOFVAn8G+XaoWCm+S3bTffeIwFE6PgqBd/1EaXdZ/XhgTMPl0X0ah2Rd/xsx5WOWaaGvFJRqrhKrZseFNNl68WwOskHwvMauXQKxYqjBHgioO3OpkPro019Aa+27IaFywB450Kx4qBoO3h+1QBOuOwBmc4SEMRootQlex+FnepMGBgrK814Kei5PFa2A8c7el8gpFoMS6R5lSLtwb3fprRbc40StSq3JQESx0ZJX6Gz5SFFKSB6YUUpnijp16i4/4yVbWnGoSOUeleJT70DgmA9m06hi6TeeaTJRf+oSJ+qVVGKJvzRNUq6oqSSYbrJ2ZSLPaxlqFS2kveNyNS7GDOHiu0q5FpM/gDhVLIkgVzFcZFJJ2suKhSrfDalqNETDUpW4mqUdNc7kQ4JeGMeK9uKOYzJzEFfn8lBLlZR0t6q1nBWb5+hj9/77cD1raa6c2kMFoKUVmM6WpUmrQLi2Tkln0GXv39URSl6uXL8jqhRilzNuOBox2LdUBGjJRtLNngZBUbXuzXPKsvIlbwYURzudcPahAdBcO256PZT7yrpwMAm0+1N0PdaBZRsB12p6kZX7QZWlFqN3i0Byz8MH/2t2dbbBKEOlUeDPkVxjndAjTVKWuodgO5U9Eyu8l2DtbgcdgKTAxOqpd7RcSgWwdpDXnEjS2v24DFkwGTmEChKwUMwMAKIUZRoekkC790uQxBpIkqUzIUVJZF6ZxNFyXzDEj2IhgpB6l2japTEPlu4eKN8T5BVEcxYVrx5Ry0EW8e2M3okic0p6mKQY16IUZSkPbgTzFrnM+lYM4cQUTIcc11RMhXmi3qAnlwmdHxTVjigFURua7+XUtl28NzKASXnPxdHlLRGpianOnUM3u/+0ZIMSkznofjcWCmoJaGfo/2gxENfOBBWNXOgaq3WPFn/fI/o01OqhOzBa204m0mnQtdTNbcondhQlTAqtXGkpCrWZSfezAEIguFcOqUoSinLRQ4VScBNqWOpGHtwEzGTZg4pQZSiFKUg9U6M37LUibc9Vv8Vt+XPwuEbbpKuaaNls+sdLSgvVtTaPNooGVAVgLB6YVy8AjF5oX+2mqIk7mFxjU8bBbVGKbnrneMEvdLoPS1wk9MVpXCNkkmxiKtR0q+pYogoqZ8X50LFcY3j98YZED5x7xD3JNug6KmGFdEnwbBBUdLVS9N4TOuauD5Kwd8e8RVk1bufho7P4vuBx6/2XujdGgCQ1xQlWqukQ/aOJM2sqaKU6fYm9XtRMD43OgFMlFqN3i2Bk/8OnPYIMHvv5N/Lkxqkkk+QBFHqmhr+PJCQKGn24Km0JHK9mWD2VECJZ2XqnU+QRP0VbThruPkmQVwqFqA+YEWAlLLC6gN9uOczmj14nKIUKmAMHiiZdFAfEsyQxyhKZFF6DZUJNGC3tBlbZYxkWTpRo4qSSEGI2l7ZS6lYDgrNG1SjJB5CD7++Qb4nbrQi2DGRx3QqTBajYLL1NiFnSL1zaI2SsY+SUJQcpVA7zsxhqhYwG1PBtFWZJhTEsejJpUMkLuObOZg4pGhs6rrhGXSTPfhVDyzGF37zGKmv8IkSmaU31Vls4a9nZX9BflevpbIsSwlcigbzE8XMwb9HiO0tRZg5iH2qpN75fxtT2axAUXXdoPbH1BiZ3qdCQZu/P9MpK+QiOW9OxISVD53Y9JBjGpV+JwKWudO6vfVXnKqKkiAGmbSlBDOApyr1j/r9lAy34zjXu7jUO3GK94g+SuKZoCtKxMxBJ/rTR5cAALYqrZD3hsgaJRKsFisOdFv9KEWjWj2MCeIepn82vkYpJVOjab3UREFRlPxz22QmYWruKt6n12SUScLgWNhym14vYr/H1WVVbTir7WfF4KZkJoFlUqPUpbUkqGZwkCT1bko+LZ8PVF3XJ5fMrneNIUqu6+KL1z2GT/76EbXJrKaO0Xt+Sev/6FZKwJ8+CzgVYK//APb/DAAgX+pXxrqeKEo6+ZMOqmQSxqgoYSykYHYKOPWuHbDjIbV/J5P3iIhTAUqjQPeMBilKWsNZ8XelgE+8fS66ZnozVCJXNRWbehfvepfkoSSQIs5tgMH1jqbexbhdZTNqDnzyhrOamQO5AWVSlgxSpD14jKJEyVuiGiUaRGo1ABQ5hQRG1yiNxNQoAcF+GCpUZJrKeM0cZO2Hf5N++PVAURIPxgpJZdShkvP4fdZjUIJMMBEl23Fje2HlZPqMG8zUm2qUyPHXlQWTzX5IUTIEoeJYdGXT6NbOL6k0WhYq2gN4675gdo+m4bxn3tbYdWtvwoU+/C74+wvaWJLtzy16c1g3VMTr67y6yXwmZTwW3bkMRko2RktRqXdBQCc2RRIl2zYGMmL30X0rzhk99Qjw9jcl1GLW3WRuQWfL9WBYNns1pN7tOTc+O0AnStlMCl1ZLwVUnINifZZloWI7skfTNjO68fr6EaX4XrehFxDBejadQr5cUt7LoxSk3tXYR8l8Hovffo2SSL3r3QoYXCkVpQxJxRXr1Se18rZ3HuWcMXlviHa9U1WisKJkDn6rpXnFfScu9e66h5fihVUDePduXv1oPpMmdZpNSL3TGsMC3jVUGnPU1DuDFbhJUaoQAkIh1EhFdTWoM3HksF57cMBTGKchuL8KTlCxXaQsP4DPBsqxPlb5vQgFWYdosNuTMytKNIW3ZJuXVWlQ6t3i9SO47XmvlciGkRK29Ceq6HIdVz33i2V1oilb2AgMvwFYaeADPweevB4A0FUWilKYKOnpc+JcEzWPNtKwCbVI+5P6vVYxtlatncGKUifD96cXD5/YHkpAUNdUGjG/D4QVJUASniN2m45ffOJtygy52cxBd8wLZjFpwFsLUfK+S2eLo1Pv4tyudDOHpA1nQ6l3tp56570vzRxiFCWl51OS1DsS0IlNMqbekWVFubDR5o1RREmQosGxcuB616A+SmXHa+j62rrAhKRMUgO87Qhvm+p6F78uU8qcCb25DLJpzxEwT+xdC+VooiTOn5JNU+/Crnf5dDRRMttVV0+9E7Pp+WwqpJqJZZrqWkTqHRCQhg+8ZS7+75S3BymRrpixD5OKONJPIWq/Xvfd9Wb25oz9obpzwaRCQc64hycD6MwxTb0z1yj5qXcGMweTCmHB21diueI8l7PuSuAUfC/UR8kPetLpsJnDm+dEKPs+dDKctgJVatSvm/rUVQvxyau8GeP1wyW4rnesBfn1LNurpN6VSeqdpRKlLquEfmnmYCBKhpRO+V6MKYn43S1S73o9l0+hKIn7t01S7/T15PwGlTmnEDScjTRzoKl3quudPqtOUY+iFEmUyKLm3/Eybly4HM+t8iYlqZlDsxvOCohJC7qNQtEVh5LuKzrZFig16nLFflad1Aypd+PooxRWnIIXwoqSyE4IlBORuh7UKIXHoihKMeeAYuZgUpTExEmMotSo1LvHSQ9GJ0JRopkvAFC0beXcSFf8WDDfB2S7vQl3AF1l77wVn6Wpd3r6nDgnun3jlnIqJwmrZQGpLi8eZUWJ0Rpkez11SDjfVVOURN2RHZ1vKtWfDFWUVPc6GsgqgVCoRimjfC/0+RohZmmAcHqWUgScFkXc0alT3t9WYkUprS1LN3OwXe99cY+KK+RWFKUEqXcKUSLKgQ419c5co7RhJAiU9MBOQNQorR0qytmp8abeBYGRi2UbR5WHn3iIihu6KYWoFte7pIpSdy6NSz+6HzLpFH7271f98QWpSqYUPqFIlm1HMXMIpd6RoFV3qDNtn75JpqBXPJCz6VSox5NMPUtZKGnf8wiLd26KZsMiSKfHBQBWbgpbuCatK9zCT7MTD1U97S5YXkB6igaXSJGmSQMmcSwi7cENREn8PWxQlMTl05v3GkeKz+j7w/s7GIceY9EGybrqLIhjFPSGx+kUTUv06gMfeHU9AM+cQxigbDklJ88P6u4VaeYgFSVLqVECvFnguBqlTNoKke9drJVY7m5tVHZlarA/lF6RetejESVRr0PGHzLe8YO4rDNWveGs0htIrVGKS6WqVg9jQjkq9Y78Lc6nTb5al88G50czzBxMhE+cW/T6EURjSj6DwUJFUSjpNUkbuVKIe7dSp6NY6/upd7E1Sur/4Sa4MYpSiCh5v103WCdN2xXrc11XiUXUhrPRYw3MHNJyMtRUoySuRdOixPnjGsZRCx5dEmRl0H1EL2NH64ulK0qZMnFKBoCeLQAA3ZV++f2K7Sg9+zyyEzzTJCH17y1lK684AosJ/R6riH6uUWI0HUJRKvmKkuiPJE56HSJvtKKHUgQxipIgUfQBKZ9trhuQrBgzh/EgHRMsqzVK0al3SgF/OqWoKnHpZXpDvbJuD66tK6k9eCLXu4Spd1T10hUtEexu8olSPhMO7ATEfljVX5DrSlr3EwVak0D7+QDBg09aLRvIo6IoVSVKyUndsXvPwVFvngWxygppJGsiu4J8l+36zRziZuJN3xcQQUE2HT4eUlEyPHRn9OTkg1vMiIrli8+Lc3lFv4koJUy9m6ISg2iiFBiLFIgqJ7fFsA1dhCiZa5S833GOlxRS8fCDKLFfsgZFKcrRCwjOWX1dc6Z1oRryuqKUshQnPj3AWTvoEdBZU7tkml2F9FGKIkolOaGTMhClEgb8YN6UEZbWXO8OTz2Ju/LfwA+yV8b2AxPfkWYOvV4Kmp56Z5PUO/2wC6KUdwpBrUvE8aepXXqNkm4Prn6v9tQ7EUjr+0t813FceW8QJDSfCbIO4gLxRsE0mSDOddrLTih0YpLQIWmK2XRKHhMRDOuKkiAfdP/S/SKuj/gapWgiBMQrTrrCqCor3m/TsyvOdCFJHyWqKCmud/5XxfUZ13aBfr4ePLYkUJSiDGdsx1Vr0kjzZgDIVPxJdlHzLoiSUJRsF2sGC6oKqV0zYnlT0n5PLSsfKO0pS2YyTcEYp94xWoBcj/dbpNJVI0qidihOUapodUZArKIkAzOnAjmnJtQoQ8PZ8UBXgyiU1Dsyux5eRvBaLpNSLLLjnN1KdjhAok019SAlVlGi6leiGqVg2bvNmoKUBewxO6waijFYVnj/6IpSnHom0uxWD4zJz45HCQSo650jiRJNpwKCB6RJCVQC4AbVKFGIoI/OUJoesEEfpaBGqVofpandSfooaesxBL1jpUBR2lIjJWKf6D1TAGB6T1YG5SLHXlddJVEah6Kkj2lGTzxRoo0/Ta53FHRW2Fyj5H2H7rc4tVa800tS3QDa3yc8SwyE04CUmVOCHbboiVy3gKkRsTh3R0u2EhAWKzbW+krd1n15OclRIg1lo1LvBLLplNnMwW84awrqhEmIwPmZawAAH0o/aCTlauqdG9iDa6l31DRjSLYg0NwhfaKUcwtKQGlKD6VOckWtRqmsBYsU1dSLuO9ENZyljoXCPjuXSTc19c60HTL1jrwliZI/OUbtwWkjdbF79WtPEiVKTE1mDrUoSrXUKMU00xUwPYt1MpTU9Y4aIRn7KDnBvgPMrnd0/PWk3/WPlnDrc2tkirM+foUoueEeY6qiRFLvgIAo2QMAPHVRzzLQyY64Hqam/SbOVk4pSxBEqQeFjk29Y6LUyRA1R+Jkr5Z6JxSeSgKiRFxLAsLjPVCpU5t8VtJlSkVJ/d54oTRqDc3GgrwXp7qoqTk9xNI3yi4bCM88lol7DG04KxAXXNIAQ0/pM4EG7PtsO/3/Z++9wyw5qrPxt7r7hrmTZ3Zng7RJG5TzSkIBlJDIwSIjm2CDSTbGGPMZw8+WE9h8NsY2mM8GG4MNxgYbMGBMTkYIkEhKKK5W0mrz7uSZm7p/f1SdqlPV1X37zs5GzXmefe7svZ3jeet9z3tw2zuuwzuecXpqOjom1ShMARt6qB9UDldZ9UmAkd7tnJBJTh6oKhoRq1F6SD3gtyiwR4kDvbx8ReLduN4tBCgFHqDhO4clJgvjrndCCGt6nrT2uwmg11a5M6M0x6R3Tz97ldc90ffeHewpaZkXMSe0rXRYc6V3BWuURvtsYJTFKJU1o2RYOc6AeoFSwRolfh/mWe8Lh1HS2+aV3mUzSpSgu/f/1nUjmevW63LOccBrlJq2acV8M8buSXk/Lu+vGutzVivpA9fW+kKha5RiBRUroqnNHLz24EJYz9Y1gWk4mefeGATSYS9UBfWUgKXswduxdt1L2egTo5TYvZi8/XOsGqW2BVbah8v1LmXmID958j7JGCU6Z0ekj5JnHQQYuDqCBirofRAniQX+6b6idx1v4QCYJJkfRx870409eCfLdtv1LrtHFIVP3eGeZ7smMXtbSbpcKzNGyeN6R+c6r0Yp6/dO8Ruf+Ale+y+3Wd/ZrDdfl33tu653UcsFSvK5FSUt9GEOrTjG7t278MLwG9rVLtV7SzNK8lw0REVvT8ikd2XRRqOefr8cD3HUgdKOHTvwi7/4ixgdHUWtVsN5552H224zF0GSJLjpppuwevVq9PT04KqrrsKdd955FLf4GIqSyyh1qlEi6V2BGiXX9Y795q1R4mCIQJZuOOvvfdFtcPbFfUnbZg40Wu6R3qX6KBkQkNWAFUi/3LiWmxrO8siTK9mArwijZC9rOKNIno6P78VA+31AMUp5YMJI7+as/x9K6NqPdqJHwk5dIYG+MXMwEqHU/F243p083Hk03w0NlJj7mU/ix5tGcumd/LRlnRSuc5ifUXKBUvr8zDHp3UhvGc88Z7VZR84xGaqV9fZQA2HaD5qPXvCPHpxNzd8pAadYVhAocbeouscl0rcvGii1/TVKNA+/D/Os93WNknPP69qfDClOO0mwb7qOO3ZIaUpbS+/kfH/9kvPxrHNX4w1Xb8pct7suisiS3rWshNBllMrsOuyGUSLp3Xwgk5cqGtr8wIcRotAky8thpD47kxGvqYoAMUpACey5T46rHkaJgNpwryNRbUpZUNUFSh5DBw4MZO2b+f/hc72T/9esi5qXA7lxS3p3aDVKP3t0HO/+n59nOv/xyGOUsmqUAKWU4AOAKUZJJcXqvqF9yeolpF3vujFzOIQaJR+D43sXu8+Q2GLBchgl1oOQBnfm2b7TYAPdnz4Leb7uhfg5cCMkCtrvtCunva/1Ztt2vdPSO5Uzlnp0XjksptCOE6z/2V/i3aUP4mXhl+UyXOmdujj6IwWkUjVKppVNey697cdDHFWgdPDgQVx++eUolUr44he/iLvuugt/8Rd/gaGhIT3Nu9/9brznPe/B+973Pvzwhz/EypUrcd1112FqaurobfixEm6NUifXuyI1QwRqQvbScqR3XgcyWqYIjInDYtco8dFiJwkSHqDkS5TKFqMksGKgglIosGakJ7f2xUfVG5e2ILU9RRvOFrEHL6p6I4DhezHoGqXZAtI7xYDQA3ExgBJPjEh6t2WFvE61mUNB17ssRul9Lz0f1542ht+8bsuCt49kPVk1WTzZ0YySOtfcuS2vR05ebYee3ye9Y4wSALzy8vWp7fLFUE9Jm1BQw1LavpSZg69GqWB9Wk8psvazUI2SxyXSd99WmfTON1ruswfPk7VS8u8OGEQswZlvtvHVu3ZrcAnI5PjSd30Nz/yb/8UdOyYMC6rW9exzV+NvXnJ+IedF95wFgdDzudK7+WaMvcrMYWygYjG0ncwc+PrIwnc2kPdeVY8Sx16QEAaBPlZXBHfo72eTivd5qRvOCpELlOg4t9qJZpSGeuzrxQAle2DPZ+jQsBil2GKU3Iaz1nwLqFGiZcVsoEzOK3/nLmhGesdqlBZYmPKer9yLv/3mA/jq3bs7Tut3vTN1SBSpGiXWR6kUBuy5bQ9muQYJ/Dj6zBxaceIFMUDnPkrpGqb09vvWTeG7F10AYzv15Zk5MOmdZpSyzRyyGlRn/b9IELj99Osv03LnlgZK9rS85gxIm+FQHSAHM8T+LsMk2kmCFQdvBQCcEzwol5HheqcZJZTt2s0wQgPy3m7PH595+1F1vfuzP/szrFmzBh/+8If1d+vXr9d/J0mC9773vXj729+OG264AQDwkY98BCtWrMDHP/5xvOY1rznSm3xshQZKCqVP75KfVDjrRleMEgdKts23d3Tfx0TphrOLVKPE7cFzXO9o+/Jc78qhlEsN1cr49OsvT+nj3bhkgy2labZjTdHL9XVRo1TQzOGKTctQb7V1c8lOQS/iXEZpurP0znW4c6VjCwk6JxNzTe2KtpmAku60boqIs+YHbJklj2ees9piWboJOifEKGUBXQIw803zwilrgGrmcWV7veVI12IUYZR8sj8XKJ2/dhh//oJztcU5j5UDVfSUQ0zONbFysFrYzOFQXO/CQGC4VsZsQy4jEyiRMUOTSe9yGCUhzDFuZLneBWlGiZLxV12xAR/63232MtWnC5SMmUOMj3//Yfzh5+/CCmavnjAXqW/du1fXIhUxZXHDbw9ugFIzg1Fa0V/VJgFNJkX0SVatfQsSVIScbzroxzLs1FI8LuHjETE29IrQAKUSWl7mj9coRZDXa4wAgZaJk5mDScDJGW6oxp4z7SYCVUtbE3UIxEjUM9YHlFzXOy6HarXjzKJ5d3S8CNlD58Wqw0CsE3pLejdPUldTo/Sd+/bhF/72u/inV1yMwVrxZysxb7ynTVb47pFqB9c72ifu5krn3rjeyc/eSgRM1TPMHPz1Pm7/HT19B0Ypr4Ypq+EsD9+glwuGLEvtgmYOhlEyPc9o1pIegHLXm81kFQ2Shy/rq5jm3Gq5KWDmuN7JgSbz/3KbGCVW1778VGDiEVwf3or/aG3E8sZDAIBNYodchquuUf/vC+T1WRdllLj0DsB8UEM5biCuLzFKXcd//dd/YevWrXjBC16AsbExnH/++fjgBz+of9+2bRt27dqF66+/Xn9XqVRw5ZVX4uabb/Yus16vY3Jy0vp3wgbvoxTHwIS8kDG01j89SeLipt/iCEj3QuJ/k+udj1HSjWornvkWByjxZCTXzEEldnkNZ3liedZJg1jbofh66/oR/PtrLsU/vmIrANfMQRRmlNxNymKUhAD++Vcuxidfe1lHlzcKehH7QBoluwcKMUr2b4tToyT3gWQDo71lbSdNL2ZKBNxaBcA+l4dqLOELOn0EJLIZJWFNBzBGKaNGCYBVC+fbfvcrb40Sk95RPP/Ck/Gc805KTTvcW8YX3ngFvv6Wq1AthUZ657i70XGNFYOyZyqdhHUDlPi568QoNdrGzKGSY+YQsvqveqvtTYZoFqvXmvry7c84Hbe87Vo861wDoumeqjnXNq9RomOxe5J1pU/sJJPLb7sN97hGoalRmkuZORjXu7GBih40asXFzRxqgUkqZxxGqRUnXhmQrFGS+3ayMPVJJdHOMHOQn2EgUFaMUhyUpKQH8DJKBPosoFS3R565W1/nGqXYAkB50rt0Ul6gRkk3DLWTQQIIc56+OuUosK7NHz88ji/esbPjunjQvULPSR6fvPURXP6nX8fdOyeRsDojiigQ3vo7n5kDt2snSSkxNXQcqZ5X24M7UkcKtz7GF53MHLqzB7enFSJ9X6wTuxDd/yXrO379ZJk5JEmiGfnecppR4qvWzHSq75oLlLyrygz5nJbrq5XDlBmPuzzpeucySub/1KvMUiFt/RUAwIvDb+Ds9l0IlEnXKWInQtiDEIDpO9VLQAll2/UOQCOQ93+yBJS6jwcffBAf+MAHsHnzZnzpS1/Ca1/7WrzxjW/ERz/6UQDArl2SIVmxYoU134oVK/RvbrzrXe/C4OCg/rdmzZrDuxNHM3iN0vQuCYBECPSv8k/Pneyy5HAEagKWQOT1UaKxWXLS8zFRiyS947UrrgmCz0nO73oXqM/uE5uLN4xg9ZC84Vux3XDWZa+yapTcJDDLortWShsydAqSGPjYInpZ0EM2z7hiwAVKiyG9U/tJsrt1ozXLQQ4A9iu2yzUFABxG6TAAJdfMIYsRJBDOe/MYRilbepdX/8bX7y6Th8so5cVwrYRaOdLAhTcc5v/nkkgy73CjUwJOEQXCqjPpaObQNO5k1Yjf284gSGAYsyxGia6JcsRkreoeF0Jg5WDVe0xdG33uTOaT+PHxpZlGi8lFu3+V+swcLOld2x453ztNNUrGzKHRhZlDLTAJ9kwgGZ4KA0o+kMBrlDhYKaEF3y4bRgmIhGKURMSAkrz/jQtmouXAlkuiA5S0zTj8rncNJxmctxil4vbghVzvWvboPb1LaE5fDVUlCqxrEwC+ec/e1HR5QcslYMnjtz/1M+wYn8Ov/NMPvftQjgIDejpJ77ScNNCMhVtrRIDexyj5Gs7yad3obOaQzTh1Akq+1h2fLv8eRj77MuC+r5j5CvRR4q0JeiumJQQxSlbtjzbXcRgeB4T5DFTygl9btXJkPb8Bv9SPN9BttO2BpkqbzByY9G7LU7AvWoVhMY3fan/ITCtaWCv2eOzBVU4RyPuyDqdGCUAjVPf/ElDqPuI4xgUXXIB3vvOdOP/88/Ga17wGr371q/GBD3zAms5NGPOadL3tbW/DxMSE/vfII48ctu0/6kFyhsYMMP6w/HvgJFMj5IYFlDLo+7gzo8RBij4NulEtZ5Qie5mHGPyB547gdttHqUiy6d8Gk0hxiYLbPDKbUXKAUgZb1NNFLyCKS08ZxcsvXYffuHZz6jcXuOX1GnKldqsGOveE6RTufg4zgwFKVkhS4tpMA9253i0kiGGgF28mUHKYmTAQpjaMnfOU9C4HmAIe6Z3n+plrdAOUbJBC82gDCpdRShJt3uFGFASFjnkYCKvOpEiNkrZY502VnVWFQhjpXTurRiktt7XAS6uOX33kt/G58u/iT6J/QJTIZ1LJSV5No8jEC8h4IjJbb6cSgm7CPY9RIFBTx2Gu2bIkM4+Nz6EdJxBCmmZwG3OarNN1QUCpjRBzQiYuVLOUJU+TrALUtAYoldH0XhOm4ayR3iVBlFIX6Iazcexnkht2QtUjzPuqk5kDAC1zBWzLazcOhVFyG+XS8fMxXj5W9rv37+vK2IGeTT6gRPHYxLz3upVACdZ28221zBzYe81lLOg4UrNyr+tdhowta19dsNBJnta0BhBaudOGQdpoaUSoa+snHzfzZYA7HlxF0FuOWNNnm2EE7OeIte1x98CcB10DQsgcgw84AP72BRaj1LQHmio+RikI8fXB5wIATsYea3mbxaOZfZR6lKx3ntmD071RD+SgvmguAaWuY9WqVTjjjDOs704//XQ8/LBM+leuXAkAKfZoz549KZaJolKpYGBgwPp3wgbvozSuAGGW7A6wwU9W09m8GiWP651O8FqeGqVFlt7lWf8GIg2i8hiloqPk6fnVCA5z34qCIFU4XpRRykpAe8rdb1+1FOIPnnMWnrQlXaPm7m+enM797YUXHTor6+5ntRRqcFlvE1AqxigVlSJ2tX3a9Y4YpfwapWnHZjv9t33+OzNK9v99iRW9oIrIvFwHMZdtIIAQsRHJrAQsDIoBgTAQlnxqyCOhBGzXO80olWxpomvewS3Fc6V37NhY2/zYj3Hq1PdxdvAQboy+htUTP5bbkjoupkbJV9TNE5GZRksnPguqUXIZJWbmMFO3pXfU32q0t6z6timg0TZF8mEgvE50FDWqRwrKqAs5GEE1Snw5PKLANJztYaxOGa1c6V0gHOmd+w5hMrDxLhklF4jEcZICefxadi2SeaTYiwKJKy2LrgUCE5TwZwGlSzaM4sJ1w3jzdVsw2lvGVL2F27Yf7Lg+ivkGSe/S724+KOEFSqFhlDT7EJvGuL0eMwden2akd/KTJKt0/NwGv3pbHDdCX+R4J6htsv/Pl5Pqo5RilOwehxE3GNl/n3e+bKBE1uAhgkDoHESbexQASqlGt11K74hNJcVJ4AAlL6PkyB/9jJJtAPa1/ufgttgMuG6PxwDIOiX3PBJjVVODGfOJ00cJQDNUQIkcmo+zOKpA6fLLL8c999xjfXfvvfdi3bp1AIANGzZg5cqV+MpXDEXaaDTwrW99C5dddtkR3dZjMniN0oRilIZykloh2AvLwyjFbSBRN0HAgZJtymC53tEV5DVz8DecXcjoqzufmyzyRZZzGCVu5rCgbSAWJLb7TaT6KGUk2q5sLGsUuFZaXJ+VNMORvXxe4H7dGSuw4jAwSpUST/ZkIXQuo9RFw9mFhNtwNqtGiRL6g8pmnSe71TzXuw51XkX6KOnfcq7dJ58uB5Becdl663uX8SyHclu5mQMfMeURiLR8xReRMnMAJDuQJSv1ud651yc/x4Gwm9R6pXdq++yGs2yZDkNRieUL273/eB2Hj4WwGCVWo7QQhjoKhFWbFgrD9LpmDiS7G1Dgk7sv0jYEgUCeBJBGfJtBRbtQmRolv+tdwJKxqjDPccvRzple7ksnRskkmePeGiX7fPXCyELd5NgdpQeM2xyto6g9uM81LT1PYk1LzzFtD+6V3oXorUT4j9ddhjdeu1kPZn3jnj2paX2RJAlmqUbJM6BxyrJe/fe2velkVNZI2Uk1dwbs5w1ndd2dYZJpHl2jpN4RzXasnNXMcaPj4AJYN8HeOTGHd3zmdty7J98JLV2jlJYO6nW7QCm0383DYOvad5++Hm17cP+1wo0cANZTzzH3AMxzKI8NA7qX3un3k3pOuOe0k5lDilGKiVGyCYVGEuL1jd/AY8koDoaj+Ex8BQBgc7DD00dJDXYRo4Sy3UcJQCtSpjetJaDUdfzmb/4mbrnlFrzzne/E/fffj49//OP4+7//e7zhDW8AIJOHN73pTXjnO9+JT3/607jjjjvwile8ArVaDS996UuP5qYfG1FirnckvRvsMPof5jjfcUBTkFFK1ShFnFHyN5xdKCPgK9TWy7SauKZlOBSUgC5UekfMUYs1MZQPY2dkOkOu5Ob4WSPR1QU0Tc2LNKOUvXwhBM45eRA9pdDb2HYh4R6fHmYwkCTyQb9/hoBSJ0ZpUTbJCjovhlHyHx9KKIyblZ9RcsFM3vEGfPbg2dPnXbt/90sX4qe/dz02jdkjhOXQD8R4IXoWUIqCIBP08OCM0miG7I6vu8EbzjrHO80o5Tec1dI7x/5fR9OWFUbtNNCV85hR907Su5m6qVFaCKMkmKQQkHV8uo9Ss2UllgTMiZnkZgjaVECI3HujqqR3TVFBHfI8aaDUTrMycj2GUeLSu1AkSDz98Wj9QhgwlQSl1LvAJHix3rchi1GatJabJ73zWX/PNGyGg+qK3FiI651uOJshvZv3ASVn4Oya0+QI/f/csatQstxsm4G5ibkmPvSdB/HGf/2x91740cNplor3haN5OODk1uEt9l7Tia5uCm7XKDVV/VcJLXyg9Jf4/6J/RlKXybcLYF2Z43/+aAf+5ZaH8ZGbH8rd95Q9eBeud1FgGy0tFxPmx9Y8sPOnqfmy5HBUv0ogseRK79juZbneHTqjZFgtgNeYpg0l5DbZAz6Ndow226gqASVuDw75/NuNETyt9Rf47ZX/iNvjDQCALXnSO+rRxhklGgyN5PLD41R6d1TtwS+66CJ8+tOfxtve9jb84R/+ITZs2ID3vve9uPHGG/U0b33rWzE3N4fXv/71OHjwIC655BJ8+ctfRn9/Rq+gx1PwPkpFpHeABDIN+IFSXAwo2Q5k6g+v9M7fcDYKBDKEf/mbzmU1TuJm+newUU0vo6RGnhcovYv0SBFrkOpZD71k3AdjyswhI8GqFexdUzS6qVECgE/86hMw12hj1MPuLCTc/ayWQuscNNsJ9k3Jq8Jfo3RkGKWZDn2UXCaunCG3S/dR6iC9c45P3vWZJ70LA+G1HE4DAvseacWJlVza21bM/ITswQHpupcVFSaj032UnEQyT3rnG/Glyfl2WveaC5RUE9NUnRAD7z6pEM/ZZhttnaAslCUvR4FOPMIcMwey0Kbfy4yNNYxS/r1BQEcCJZtR4o1reUSBYZQq7lPbI6kW1rOXGCUuvVOMktr+ejPWgw4Wo+QwgHlmDlzeVSuHHjmWX0YJLI70zu2Z47MvdwdOrjltDNVSgO37Z3HHjkmcffJg7jo5IJiYbeKPv3A3AOBFF63B5ZuWWfeEFyiFhlGiAQBaZsXp8cTNHNxmugRKec3l1HwL54v78LTwh3L/v3A/sP7baCX2M8A91rR+3/HikZLe5Zk5eGqU+IDpqLABOLZ/Fzh5qwVosnpupRglR3rH1x1lMkppxqeb0NI7ByjRelLmEUmSss7nA3rV2C+9o+VNxWXMooqHYqnyOlU8gu/M28eQADE9H+ZRSjFKzZJcfqnpHP/jJI4qUAKAZz7zmXjmM5+Z+bsQAjfddBNuuummI7dRx0vwGiUagcuT3gGGUfJJ7yxGyccMmQJ2inQfJZ89uP2CXRTpXQajFDJdtS+hNIzSwraB7zvVV0RhAHdppTDwJi2FXe8WmVHqRnon1x91TO67iXSNkq0dr7famlHygTNvXdwiBp2r2XraXICHywxxcJTfR6lLRmmB0rusSEnMIrtWr9GOMxklfk/lRRgIXHnqcly+aRQvuih7wIb3UaKu9i6Qd58xnIXy1yjJ6X19lADo/j0UJfX8c48zZ958zIAtvWsxmdICgZLl5Gnu+zlHekesC/1uNZxljFLeeSLjBi69o75K7QzXO2o4GyBGRdjXR+BxM+U1SoKm50ApaQNxW9fL7J8xy7Bq2nJrlJwaCZZ8eoFSF9K7Yg1n/WYONKtXeldKP3+vPW0FvnD7Tnz+Z491BkpsmfyYcZdGih8/PJ5ef8RldHL76fqulUNLYsetnem+ouvcdb0DJIBYGxgJYW3iPuDBb6K17jprG1K1LWpZnQwtcu3B3YazHWqURuEk6o/9RM3H7M0ztofeDRooRWawwl23BpidapQWaOaQYpTaBJTs6duO42PdqVGqJmoAyQFKLV13JffvMSzDQ1iN9eIxrNr/PQDnp6YloDSblJ0ek0CLgFLr+GSUjqr0bikOMSzXuy4YJcBv5qCBkgB4Y7giZg5eEwi/9K6IjMcX3PnMTUzogSGE6MAo2Qlit1HyJFKyRskZmQ78dR15rnf8p8MtvXMtwA93uMeipxRa3+2bbuiXvU+2xc/94TBz0A1nOzBKfRWbrbHAEUuG3OPtM9jg0U2N0kJkoy64ou3uV/uTJNCNgF2QHor82heKKAiwrK+Cj73qCXg261nkhuV6V5RR4q53OTVK/NhYBisZjFLK5IL935fw8lXP1Nva7tdtV1A0+HkOg8BqOMsTS+p/poESMeONSVzT+CZqmE8BWvf5V4M8BnVRxbyS3pHhQpaZgwRfHjYJgPC4mWp78ECgpBglhJH9Xmg39XOU6hL7K5H9DHWAki29cxgllZSVw8BrotPKkd65crBuapQIVLlJsd/MIb1dzzxHtvH4/M92dpTf+SzRAWYuFMfoxyz+rfyHePrUpzzTcaAkv6Pru6cU6oEibuZQYvU9lPjSb/wZMVNvYY1waq0a0ynA4bIpdOyzHAkp+LFx3Rld1zufgoO/s5dx6R0AzEn2jW9CpvRODSSR2ZGps7Nd7wJh3ifu9ZSuUfKuKjPmNFAqXqPUyqhRitBCJZH3VVy2gRI/BvQcurV0IQBg7YHvefepop6pc4mpUdJAWy2/0syvRztWYwkoHc9BfZSmHgNacwAEMHBy/jyRKsz3Mkoe+Rz/v8ceXL+Lffbggc1E6cUtMNHlDzw3caM8k17scpr0eigBzqpB6RR8vfSi8TWcDQNhGRDw77P+z5PuxZfemWWvHqzivLVDi7r8TuECyapy7aFEdZfq4dNfibznJspJABcjaJH0fshyvXNtvotK77auH8G//eoT8L23XZOxfnufXDc2HgthL1wzB9Oc2Mhrdk3Kc+BaiwcesxJfFMUKXHpXpEYpYA1ns2uU5GeUJb1z3JYi9fxz7cH5eXO1+IBTo9RoacenQ5Heme0Fekp+MwdKVuh3um+eM/9pvKP+l7gx/CoCByhVnXNeVUlRXVTRUGKSMtmDxxn24KqPEq9PaibKCCQPKAlm+BCW7XdKu6G3k4DSkOPSmGaUcswcWobV85notOJkUaV3rh00l2MDfqDkG/i48lQ5eLJjfC7X8hvwg3aAmywkuCy4E5cEP8fLg//2rp/XhfHtrDJGqRXzRuppcEXXJF/e5HwTa1gzYgBAYyY1oNFou7VlsV5nXnCw4YKtlJmDAxTcQcxlSno3179efjE/LufjNuYZ20PSOwKJLpvHGxBr4NnR9c5Z1777gfecAXzjnd5tMGYONqNEx8jddNcenLvecYOUF3z4dguQ8mNOz8GfVS8CAJwy8T0L4dH562lLtmgyqaVqlNplaRZRaS8BpaU40kE1SlQD1L/SNlPwRZjDKOkeSs5LK6/hLP1JNU85/Zf0152kU7MHvEMtPAlwgQl/QecxSlefOobnXXAyfvWJp+RvQ0bw9VJHbrfhbCkUEBlOYSlGiVueh4E+nj2HkVH6k184e1FldUUi7XoXWtv12IQc7V7W76+JOlI1ShSZNUrOcStq5gAAl5wyilWDPd7ldiO9WwxGiZYvhNAGFQRWBx1b77Cw612x7eKgp4jrHa9RarRibw0B3Vd8P63j5DBKJQUaXNMMvg9uB3rAfizNNdpGYrII0rtACCa9a3lrpAyjJOcbbcsEdZmYSEnvXPBZUYlRPaiioRkl6qOU0XBWgS+S7dWTSBtB5LV9sF3vSkgzSnL7qSUA778lV+QwSlaNkt/1LgqEn1FqZ9uDp2tGsvaIz2NLrejeSFTL2ayGs27UypF+n2QBIQqfDFRui5HEEauzShxAL+zrvcykd7pGiTNKjBXjdXd0H9J1TvteCgJ9T07Py0akgAHRaM6mjnlKetdKgxpfWM55zjI7mjmEwmKWiVGaG1Dv//mJ1HxZ0juXUeKtQvgyApG2VdfLdoGTe8/9+8uAyR3At/7Muw2zjqGE60qYqlGK7YaznFHqF/IamU9KuO3R6cymwXTtPdh7LuaTEgabe4E9d5l9IkapJUHowaSXmdyoQQQNlJZc75biSAcBJYpOsjvAMD55NUouUApsCZ1t5kDSO1+jWjJzsF+ouYzAjtuAd28APvXKFFjKrD+ALfnIc70brJXwFy88F5dtWpa9DTnBe7zMMekdH5mm9fr2090k18mPCkQXGyidt2YIW9cN49ev2YSrlePSkYwsIEIvm53jMonLcks73K53LoDNYhyDQFj1RnaNkgF/WQ2xi65/sWuU0rU45v99BJSIUXJG98Mw3bTRF0WZPruPkr/Brysh0+CqHVv1BHoa3XCW3Yc5rnchMUoOwIlCY9lNNYg8ODNhWSkvmCXn9z+T3jXbuUCJtrsay/2qomGNZAPpY2oYpQrqiWKUBEnv/GYOJOejfkt1lNFUbFQQp98hdB0LYaR3IixJKbdQ2+NjlFwDEmXmEKvqzxqX3nlqkOQxCTDsMTJpxYlOyl1ZaYpRKiK90zIn+X+6zjSj5AE1WfcznSMfC8Ujy/CAN4Jdy+Rvp4id9vo9Vt/zHqDkXtMuuOI1ebRPMw0jvbsnUTXSjdmUpK7h/N8FUlmDUxbb48yTMnNISe9sx85RSGA0079BfjE3npovi+GabjhmDloOrK6HmNZp5P/tOC0d5GEBm5n9wJ47+Y+pbXDtwXVvrFYbeOzHwIzN7LWTxHIJ5M9PAtNT6FHbxrczzSiVq724Nd4iv3z0h/p3AutVBZTGk97UIEJcGZTb3V6qUVqKIx0uUOpkDQ6gkD144DJK/maBAK9RIntwbubgH3m8bOMogAzDgu03y887Pw386KP2ZuSaOZjtuerUMVy4bhg3XHBSevmLELRuXaMUBlYDXNPwNn17uWyInRAGet7F7qNUK0f41Osuw29df+qiLrdopF3v5LGhl81OYpQyXPaOVB8lvX05QJUbYdh9lOTfebK5rHB3KQ8MLYRRcgEBXwbVKU1p9zEbrHYyCaAoChasGiWS3uWYOQhhW4r7EhktvQ0M0LG2R5k5EECIYlWj5DZ9FWY+t18IkK6nIFZ5cWqUzABJkgBTHnONHkf2U0vkflXQlCPZ7Dy7MrSKAlXzokezQhUtvfPbg4eq5pMYnTkLKPmkd2ZfjPROvQfYe4RG+cdnqYeSn1E6CJlgWWYOKXtwxXKEATYut22OAWUP7jEhANLyykKudy2yg6ZkUB7n/Iaz/ucJgYNOjFIWkCI2rRXHFlDaKB6zpuOMkmsP3lN2GCVtDx6wGiXDXAHyWNMzanZmCivEOADgnkRJ/5se6Z1zrF12KOuZy8Fryjmv2bYlYx3swcn1TgOl+QkgSSxmp7CZA+tlFscJHtov2ZJAmMbP/+9bD+CGD9ycYp3MvrH//Ogj9god0AOkzRyiQOAi8XM89WvXA39/FYb//RcgYLY/SWxwWW+29XnpU0BpJunR+0HBt5PukVo5xB2JOm67bte/y8GjRDvaHYh7jcEMsa2qT1M1XgJKS3GkI6oC3G+tEKNE0rtuapRswMNHv3Uu0vKYOWQ0nP29Z52Bt1y/BV944xPT28AlF//zNqvxoF2jZCdl3JZ2w7Je/MfrLsO1qvnmYgc9IOcsM4f0tvlyJ9eIwHXyo//3lE+sWzMFRCI74dupZF+jnh5KwJGoUXK3L/v49zEjDJ/0biFGId0wSguqUcowcwBMbygKd1Q+DNJmJb4ozCipBH6+yaR3eWYOgtuDt1PJhhDm/hfCsLLWQIVilMYhE+koJumdW+toQKGPUXJHtKm2ZDFqlKT0zpyLidk0EHHrI3qUa1VFNNOMkpOca6CEKhqJW6OU4XoXkvSOalB7dH2TFyjRs08IRIIxSoD1HnGBZYoJUs/9A8Gw3E/UTWLuSu9Y359NY2mg1Gwbe3C3xjDVcLZIjZKapruGs/77h4Avl9bFcYLv3r/PqlvKrFFSwL3RirFW7Nbfbwp2WNP5Gs7OMTbXYpSYmQNvSA0Y9qDEWGahjKQmkx7sTOQgKBqzqbowF+S4gw6ZjBKbjM4XXeZJYt+nrnRSmjnwGiXJKE31qYQ/aQON6UKMkpHe2axuqx3jnf99N172jz8AIHMi/vz68cPjeGg/9ZbKqVF68Jv2CsmgC7IO7Bv37MHUvLwm6DkQCIGXRF9H75xkEEsH78MTgrutxdRdRqltS++mFaNkSe94jZK6TvoqEe5SNuEWUGon6MMcgkROdzCupZn2qhrwiJekd0txpEMIu1FYJ2twIN8enGqdQofNyGs4S392YQ/eXy3h167ZjA3LHEYMAGb2mb+bM8DEo2ZxlqwmPRLMPw9nUKJq7MHtRJL+LsIoucXnOgE6wjVEhzvcRJ0SBEogqD4mk1EKqKYm7RC3GOEClTzpY18Go+TWXR3K+g+79C4XKDlmDsLW+WdFUaBEdUGzjZYxz8hhlLjrXb0VpxIs956iBMaW3slE5WAi3ZeiDHvwgDn8+ZJTN5E+OJtm2bsJnkBT7zX6zlfg36MbzqoBFXDpnT0Qc+6aIWvesmLR5kUV84lilJT0rtWOvQ5cUSBHx8lGvKfWi+F++c7xASVau3S9k8sW9B5gLqju8XLr4mjAbFwBpZqoa5DjMn26708YeIFS25Le2df6QqR3lFDGzqh5t2YOAGOUmOX5x76/HTd+6Pt4uUq8s5YJmH2P4zZOZoYKLqMk7cEDax5aJknvNolH8dL2Z5Aw0yYXXGm2KQj0dVqaehgA8EgyhtlEPb+bM6n71AWlRaV3/J6jefgzmDsCuoygPYiZaHvwmepKk5/MjTs1ShnSO23m4DJKCT70v9v0dGEgUgOiD+6dVvuSA8xn99srHN+u/3ztP9+GV374h/jY9x+2tiEKBE4SKmdSYOR54XesxXAQzmuUiFGa9kjv/IxShLsSAkp3aK1hsx1jEBIA1ZMSpuOSbmobOkCpktT99fHHeCwBpeM9qJcSAAx2wyj57ME7MErqxeivUSouvcsN92HBOrS7hgk8jJnD4UdKtB229M6sl/721iil7MG59MY81LNeGsdr+PooAeZlo80cMhglOt2H6/y62MNN3Hnwl7Svj1LW6HFeHGkzB0t6V7WT1JT0LijYR6nguSH2iAOBFKNksdbCkd7ZyUbaIMXHKNlAKYz9DWcFDAjxSe/cEWFqBLtgRskxcwDMaLEPKJEbJrFmvY70jm/Hs85ZhbdcL2sKxvoriLT0rqJZIQOUksz+VNz1Lomq6O2RiVWQpLePF7RroBSlpXfu8Ur1dWso6V0wIvcbdT1NVj+eKPAzSryPktvPLGUPXtD1rs3c4crqGbAQRqnKpHffvGcPHtg7jY9+TybIP3lkXE+XVaNE98Joez/KwkyTkt6FgX7G0XbyPkpRIPD58tvxpvif8YzxjwOQ71hXrqcZpciYOdRmJPPxSDKGOaj3f6OzmUNR6V1iSe9UPUwp1MeUH2/32RCFZuCjH3P6ep8tjwDVITnRvAOUMhwS55qO7E09J9z9cJldAHhwnwQSrnmIhcsp91mm5PEThlG6+QE7L9J9lEIGlJ702wCApwXfR68wjnYpRolc79Q0Ux7pnVuLCUg2dluySvZga84AB7fp34eE3L8J9KIdI8UoBVVmP85yuuMlloDS8R68TqmI9K5Iw9nMGiW7qzrAa5Q8RhAZZg654QIl5UoD5MuvKCc6HLIsN2g7aEQucuh9k6h5gJLznVt3RQ/1xW44e7Qj5XpH0jtlgkH1MQPuyLKKUB3Tw1GfBKTPS559fG8lS3q3cEYp1Udpke3Bu2OU7HMQiM7gTIji/a3omJlEM+ho5mCkd2kba/eSoG31mTkcJOldO6tGyYANr5mDkxSNz6ZbJnQTrpkDYEaLx31AqWzfN2TxW0HTKiKX2yTwa9dsxn+/8Yn4t9dcilJbHoM5MEaJmtDGfjMH43pngBI910PPc50SJAFo17vAld7FrZQiIAWUlPRuMiTp3bweoHDriprMzGHM45rZimNdy1Nz1tOObYBYpP9ns53gkQOzaMcJylGAFWqduuHsAmqUbt1+AK/48A9x7V98S4NvHnn24EmSYFWyCwAwoxid9WIXQph5ypxRaqeld4EQqCrW8II52ScnCtJOecb1zrzzemelzO/hZAyzUO1HmrMee/B8RimrJYZtD256ZpVD+zkCGEMFCtlwVu6Dlt0lPWiKCtAzJCeaG7eu/SzpHTcNoW2Q38epAQ/3WfjAHmKUMqR3SWJyn9Xnyc/xh73bAbBaRbSxEgfkl2fegObgKegVdTwzNGYL/H6pt3iNkhxkmVHnLO84AvK51EaIh6L18otdPwMgj8uAAkrjSa9lCELXXLlU1oCM53THSywBpeM9SgwoDXbooQQYxifPzCFlD16gj5K2B+8svcuNPKBkNZNM1xbI7TkCQImkd62MGqXQZpT4Jrn5JmfGApYQnuiMkluUTtHnJkwq8uq+FiPc68atZeDRlwGUKIldyLlzMUYeK7UwMwd7Hg5c3WPOHcikOULnPkrdMCpu0uhrfmz1UQoEKmH2MXXPHd1TpRzpXRiT6537HElfq08MfobzxX0A0on0wZlGel1dhFWjpP7syWOUrGaXiU52qqJh2RIDZj/OWD2ADct6EbWJUapi3q1RameYOThAKQ6r+rmexyjFScIYJZLe5TBK7sCQep/MRkPyd1HX91e61oUMBoRXlstd71LrgZ2wF3K9a8e4XyW+pyzr1QYauuGsB9RkXR90rn/K2COSc/Lgg3L2tkigR65zP4o3Yy4poyzaVhNYb42Skvv1lEOLfR2KZeLN2Rg6Lsb1zjBK5Ybc9n3JAOZIetdIS+/STKBTo5Rp5sCWwfo4lfSAi7+2BrDl7OR4tz8ZwMP7Z3H/lHruzE8Ukt5x23TAlt6tGzXKnrlGO4dRStubf/vevZifmTB50qrz5CerUXKD7oWR+CAiEaMtIqB/FSZPez4A4IbwW3paLr2TfejkNowIydpOJL2pbfOxavROvF9skF+oOqVmHGMI8n6YgFpWyz1WApNQx2gJKC3FEQ+S3tWW2TK8rND24Avpo5SuUUq53llmDupB1E67N2UG1SiRjNCS3hEYSo9eG3vw4qtaaNAD0kjvbEbJFJPLbeKjTXmud1EgsFzV6KwcrB6GLT964SakxCC4zElqZFkFHafDxSi5y80CbO5vHNBccsoInnnOKvzqkzZ2vf7DXaPEj79rX54nvfPZbvuiGybXBYED1TSLyO/vUKSleXnrXjNcgxCwe1Y5jBLZg7vbwmuUAGAQ0/jH0v/FP5X/zHKTophUTOhCmWzL9c6V3uWYOZTDQNYlCZnUEaOUx7pHmlFi9uDEKCnnLh4EkiXbwBkleX34GCVKVNtxou3Bg9ADlBzgkLrvW5Ipmw2lW1ZPrvTOJO9Aulk0l94RW5fVWLiI9K7ZjvGAqjnZNNan792sGqVKTrsAGlQRzJTJtw0EvlYM2O+FdixrTsjxbjtW4uFEtn84WZh633IYGmMGRyLYUwqt9+ZwfBCAqk8jRon1awJk4kvPobAlwfosqpgl6V3TY+bQgVHKavJt2YO3zPrpWrcT/OwaJQIG+zGAL96xC4/MqueOI73r1HMrchjrZju2FCBT9VZq4MvUKNnb93ufvRMv+8cf4M8/c4va4CqwPC29c4PWN9qSBh7TlRVAEGBqy/MRJwKXiLt0zZpVo8RcQ1cJCYjJgCOrRsmsU9479wbr5Re77lCMJjCoGaU+vR7APMfLUYCpZAkoLcXRCpLeFZHdAR3swYu53lk1Snpe9dKMDoFR4vTziBq1mGdASRdppy9bY+Zw5KR381bD2TSjFHiAUtr1zq5Res+LzsVHfvlinL5q4PBs/FGKtOudGo10ElW3oSuFYZSOjPQuC7C5v1UYe1QrR3jfSy/AM85Z1f36D7PrnWU64dw/XHoXBsJieOjy7NRMtmizWXdb3PWb5TnSuxxw6N7yH3z5Vnz1zVdi9RAHSo6ZQ1aNksMojYlxlEQbg2IWw8i2tl0M1zu3PtFNLPlvUSjQB1OHoKV3eUCpZaR3dSW9k6yPZCVcNoWAm+V6V+rRda5hkh4AI0etdpxo17sgcqR37aaHUWLXQBzrQbv5SD4Ha5b0zjVzsEev3WdnK471saRR8X52D2fZImdFq51oRkkCJfl9AmmtTeui6zKPHaYBI5/MkgeBmmtPH8N5zKSj2ZbW58Qe7QlX4kAi938ExkGWM0rGzEGev55S6L1/ozDNQln24Gq/NABPKgYoefooNd0aJef/vBaRh2UPztZf8krvPIyS2jcCSgeSfsw2Wpr9wNy4xURlXQNubyAj/YtTclD3fXJwtokDM40UkLtnt9ym798pGWvURk0uN/6w1nO6fcYItCxrS6A0VVkpt6VvNW6OzwAA3KBMHawapZapUVotZK71WCJ7SmY1nKUgNvaBWL3fDm7T1wOZOUyqY1pv2QxoKQyWGKWlOIpRUhdfEcc7wJg5+MALMT+Bk7ikpHcMKNHbQEvvOjeczYz5cWnXCRig5GGUfEmJfqkfEeldWsaUV6PkWgDby7ITm5OHa7hyy/JF3+ajHe45y5LeZUneNKN0mICSe93kASWe2C+E3fHF4e6jVGbXWSkHqNTKoXalAxij1AGcdXNa3MTRZbT4euWyJQDIAiPuPTXYU0r302kQULIZJZ8pDF/PIANHK9UIrC+K2Kf7Is/MwRe8kLxPzOrvK1DSO6dGydrGtpx+DhXMKUYpRIwIbW8fJZpfmjnQQBhjlJL0O0S7sHWU3uXc9+zdNF8aAgD0CMMoxYldK9ZkciwA+MsXnofNY3140dY1epsoaacEs1oK9bHnCXsB5R0a7Rj3exilJAHm2bLIya+cYwxDbSD2T6cHLvm1QSzVmuEaPvOGy/GMs2Wy2lb7NqQS1dloCPshBwOGhQ2USCJI0itdo1QOEQh7xwcxjRIzcSEg0dKsinnnUb3fLCpGetecSZs5OP93QUMghBdU8tl4PRq35zbT2ssssV5QBBwPJv2Ya7a15Cxt5uC/CLgNvfwkWWK6bq7OWBwCOQ/unc6U9RGIQ23ElFA0poE5ye6NOI3Y6Tkw1JQAeVIBpTgBPNX7pQAAuYdJREFUPhtfDgC4MpA1RLzWkjNKqyEZx8eSEbnfOcwcYN6JD7VVfnJwO1ptuZ9DQt4PLqNE10+FM0pLZg5LccSD7MG7ZpTm0791ZJTSQEn/qeubPECpqOvdrEpEyv1Ar7oZLUYp2yTB9FEptqpDCTe5itjoFpB2vfPJa/S8OSPAJ1Jk91EqJnmjxOqwmTk4i/XVMvh+y5OEdbV+ZwMOq/Quh1Hqq0TaKIBvVyfGpBugEIWBdT0M9OTXKPnuo6xpM0NL71SNkhoF9zWc5csjSQkArBAHMxe/KNK7gIBSNkjX1sRBoI0cAKBKfZRynie0z7OoYj5mYB8tNNux5S4GmHMeBkZ6h1KPfsZHnhql2CO9E56Gsy7wtu579m5qlIlRqlvTNCygZI/0r1/Wi6+8+Uq88KI1eltc17uecmg5KVK4NS6+4DVKm8b69LsnThJLdjekgFIeo0QM4f6ZNOgc7jUDCLTcquO41lINYvtUT5xm1KdZ0xFh3p3lKNDPTmPmEOttCNt2PrBe7LLc2whIcEZH941T7OwcbEbJBS1ZboUUgfCb6Niud6xGiYBuOwamdgHzk2lWlA1iEnA8gH7MNtqa/cD8hC3vy5DeGUYpUMfAXMPTTnPoR8fn9N9nnyStsR/cO5OyB6cYJvavNirvsf7V8v/3fglAejBJ1yg1pYnHRJmAUoLb41MAAJvFowASC7Q1WrKPkkCsB35IetfsIL2jwYxH2iNyML1dR3tCuisSo0Tgs5GqUVpilJbiaMbGq4HKALDpumLT59mDZ9YoOa53QTqR8tqDZzSczQyqT6qNyH0CvIySb0T9rJMGcPqqATz73JOKresQwk0aZR+ldIJiHqjpgm13Wt9yT6TgI8jcIc0dbXVdqSiMMcbhl95VS0Fu4s/ZpsVilNxTn8caHar0Li19M/e7ZJQYO0rXcof97BYoWA1vKx5GqQug1HHVSZI2c2hnmTnYPdEoAQDygdJi2IPTfub18KLfgkBgKODSuwZC18zBrYdUtSRzialRAmSdks8enBiIQABVqOd7ibvepaV3lGS2EyACKRR8DWftbbPue8YoNUoyyewVdTDcgDobJW85tSMUuoaFjaLTeqolw0h0khy5sXNiHlPzsg5l/Wivvv44UOophTrpLwKU/FIn1iuIrKnV9NqNrh2jGSfoVT1xWlEvDqjBAC69qzAZnbYHZ9taahl2EgDWid1yQEOzNjajVAqM9K6SKKDEpXfN2ZSVfqpGySO98x2rOMP1Tje8ndkH/MWpwP+73FujRNMRa3Mw6cc8Z5Tmxq35sq4BY2SRzkNmGFAa7Cnh0QMGKK0flet5+MBsysCCwjBKqmHvxa+Wn19+BzB3MCUppH5qxChNlFcAkMfqwWQVWggwIGaxAge16RRgXO+WYRJl0UacCOzGMID8Wi/ADNLMtgQwKAchkgMPyX0WtpmDZpToWEUBJnWN0hKjtBRHOs59MfB/tgOnXFls+iL24B2Akr9GycNG0d9xs5imYVYBpd5lQFUBJY89uC8p66+W8MXfeCJ+48mbO6/nEMMvvWPSJipy9TFKzrZbIOpI0GFHKSLP8ZF/OwlThmOcOfeHYeNgn5c8IwfAZmAWjVFKObcFmeDjUF3v3GOeZpTS12tHM4cur11+T3RilOjYcFDB5+8Inlt1APL5o80c4jqQJCmgK4S9r5xROizSOy+j1Fl6BwCDoXmGV9BEEPgBpv6/qlGaQQWNJEA7UccVLWUPbq+LzmnAapQEY5T6SunRce16FxvpHXxmDs6IUV/ZwyhFVdSV9A4ABsWs3qeGR3qXZvrl/7kcjurvesuRPvazjbbl1ufGO3/hbFyyYQRve9ppAIDt+yWoWDNS09bacl671442rMmrUco515zd0qCGGCVWb9RsxegnRqnUq2uUlgVGNirtwc08ADNzKAcIWnb93QaxyzJM0NI7qgcLzTuvCi69Y/bgLRtIp/so2cdaOEBJ+0R5XO9KbP39j/2v/HH8YSRtu36NWFYhDGtzAP1othNTozQ/7oCxDtI7z4At9bn6w+eciS/+xhNx/ZkSuJy2sl8bM+2enM8EYVom2SNlcLj014Dlp8mc6HvvTwEXYkaHGpJROlhagSSRxgoNlLBDSGnmluBRa3+aythklapP2o1htFRPNcv9MQe4N9oxkuH1AIAH7pXOd0NKBjwtSHpn1yiVwwBTilFK5se9x+BYjiWgdCJEN1ZvRezBU32UbGbIZgfU06zlA0psOUVYJTJyqI0aRomNPlAvnYUkiosZqRdyEFjHRGuYfWYOea53C7QYPh6C7ydvzsuPTW85zDRroJGpI+F6l1ef5P6e1R+l23B3y5WA8Th01zt7mzkwrJUj7/Xa6do8JEbJV6PUgVEqqeRHbmOHlTXNaDnVKAEAWvOp2ifXYtuS3uEwMEoeWW4Wo1Ry3DWHQkd6J3KAUquBQJkvzCZVWVcB+awuiybabY+ZQ2DuOapRCiIDlF5y4UpsWdGHf/6Vi81qYpNQk/QOobq+cuzBa7xGSb9LKohKJT0S3RdP6OuGM0rcYIAHPZNnGyZhv+a0Mbz4ojX4tWs26WP/3Pd/Fzd84GYkSfoYAMDlm0bxb6+5FKc5JhEblslEm3YlSRKrNxG5uFVy2gVkDQwBtgvZbNMYLwAGmLfaCVpxrGWYLSa9WxY4Zg66Rsl1vYu00QfFumA3oiAwTnmxlGbyGiHdykKB6FkuvQOQNOxlFpHe8edpybEm5/NwM4do1tigVxNzvwKM/QkCy8wBACYZo1Sk4awrvZN9y+xprtoyhtVDPXj5ZevxoZdtxb/96qW6t9fuqbru5+XGCBxGKSobVmnX7an+bT3lEEgSDDSkmcNOLMeT3/MtvO0/JXDZJiTjs1nsSK1rrtHWQGmnqk8CDEBMksTPKLF7tD24DgDwvz+8DQAwrBilKQJKTapRUvLM0DBKyXHIKOVnBEtx4kUhe3C3RolecBJc+WuUcswc9LKd5bqhpXeMUWLSO0qwjzagcJtLutI7epAGngQvZeZgJTYn7riF7QrI2Q3zd5bsjs9/uFzv+GnJct6j6Dss0jtbgilEuru7/n0B13+loPSutxJ65WAdXe+63CaeEPn6KPHjQafcdogLELZitJKkM3hWQCkJy5iBYxle6kE5CtBSI8KByygVlN4ttEap5DnWtZL/+nP7cw0GdbCeogjiRraZQ9Psx2xSRpw00RARaqijgiZaqnEpD1+NkijXgJZ8jp/UH+HLv2krGWLNKAEl4TBKul1E07peeL0JAMYolVEKAxxI+jEgZtHfnkQ56sNso40GYw5aTgKrt58YJQaqBntK+NPnnQPAPvY/fWQcM402fOUpdC2WnHM8omz0dY1SbEBZTznU58t1meSRJ7PkCftcBqPUjmM0WzH6lPSuXerzmzmEHPQkqWUGTZtRWiP2qD5KhoXiybO0B5fbUlOyzPmkjDn2jk+aNmhxgVEaKAmLoQ8DAbQz7MEZ8KtObde/97YnAQzp/9M1EYUCI5C5BAFJXjNjSe8yGSVbeif/DiwASPWdpTDAk8+QrBJZuu+ZnM9c9pArvQMAxdrg4PYUE1UOA2DX7ajEs5hLyvjBwV48sNcc721iDa7CLapOyY7ZZgtnacc7sz663rLUp/y9ON+3Bn2AtqWnhrPTgTy2dadGqRwFuiYsnhs/7hia4217l+JQo5A9eL7rnb+PErkieaR3fNl5oRmlEaA6JP8uaOZwJMN9YUaBbV9cymGU3IRKsBHsE5hQyqzF4slvnuTtsLvedSG9s/ooHQbpXad9PVTpXdm50Pj+9FYii2XRjNIiS+86MUq+ZwwHV1Fg7puO0jtl5IBSD9oI0UxC63tX/moZTVjSu2ygtBgNZztJ71yTh/7ALsAP40Y2o6Rc/xpJiPkkRDtO0IAyG0ATzXacbtYZmmtAS+/KhlHyvUMo4WwnCSJCcbpGyS+9Sxmn6HrXKkphoA04aq1x/SzlLmOtLOld6llrHxN3kGPvVN0rOaLLy3WLHFBmDfR7nCS6Zw2X3uU9I3zmBRScUeK1T4ABAM04Qasxh5KyYo/LzMwB5t0p7cHlPGlGKUTogJoBzMp7jDXT5dtDDWcDxKgI+e6fRQUJAjQDmWMETbvuqVMfpSCwnwt0Pn324BXGKPVOPqB/74sNOATM+S6FgWY9qIaLu95ZYCyTUUpfZ+41pP/fnAd+8nFgarcGSrsn51N1WxQj5K5ZMwwPhtbLz/HtaDqSQiEE8PMvAAC+HZ+DqZZ9HT0USnOvLYEHKNU5o2SAEgG+LHlgtRToa31fSUr7CCjRgJIrvTPHXxjXu7kJ7/KP5VgCSo+3KGQPnlGj1PK53pH0jhglbubAC3QLNJ0loNS7jJk5mJvK2IMf3cvWHT2PArv4n/72SYZ8dUgmMT5xb0eezJYyGKUsa3DAjGa5o+qLFfyaztsO+fviS+94TscbK/tiIUl5nplDGAidrGpXNecazqrBKTvTFQ2ePFLC6W6T+7cLKrR9dafbhhI21Uphnka9FXNRduoi+P1tM0rZNUoLvXcrYfrZkMUyuABqQNjSprA1nwOU5H7MoaJ7JjVATWdbaLU99uCePkphqQeuCyoPSrK4611aemczSulms0adEIVCS6V62xP6urF6w3hG+lP7D3lN8+eQaxywb7rudb3LqtMjJtSqUWrI7apG3Zk5+IIDCV77BMCS0cXzDByUevXxGkwmQbV53holctIrBQgaMlGfVjVG/WJW1kkKMw8HOpJREqgx58WgIpPkZqBYWzUQ4bdhT1K1QEIICzjSMyjbHlz+3jf9oP7dBUp0zmpBS9dx0fHhZg78vGdZeNP3/F53n8X6WXLHp4DPvA74+h9ixYDMiQ7ONnXvKgq6pIa5PTiA9371XrzsPx9DAgE0ZzHQHk9vkAJKX25v1dcHxcMhSe+k8x2PWSa9sxklc++6QSoHupYfE5ItWyv2IEQb/ZDP2BmHUeLvD12jtGQPvhTHfCyo4WxeH6WceYVgznfdMEqjTHo3pY0gTP+Co0u9pMwcQrvOoeS8WO0Ez7O8ggXzJ0pYshv2d54t8tknDeJNT96MdzzjjMOyTRzAdqpR6uN9lHKSoG5CFGSU6IXVbeSNggKG1emr2AXopnDZv056cXYLlPg2+BrOWoMx6u8ql94FonjvNJWwCRcoOYkcoFzvWCLEa5RGxRTKqlbHZUEWs+FsJqPkAHiXUQriut1wlh8XxRjMoqp7JlHT2TKaaMZpe3BzHUJL74JKD1xzHx5GvuMzc/A3nE0xuC3DKJUtRmnCm3S3MmqUUv93zpF772YxSlp65yyPAL6uUUJi9SYqYuaQJ73jCSuvfQKYmUM70TUfs6iiXCoZC3zEGFBAnwMl1+q7EoUQCigRwzCAWeu91lY25BTkekf1SXEi0FuTwKMZSqAkFDinfeTmDb4aGFmjlL4ffPbgpUiaOQxiGj31/fr3/sSWEBIjNhrIbWklJmHX9uDtOkqxyU98MlTAME1ZMnKAnesD2+Tn/gcx2FPS3z824WnLgrTr3Xu/eh++/eAUdiXDAIDlqrGsjoMPAbtvR4wAX4/Ps2r2AODR4GS0EWBAzKVqK2caLdZs1gAlAua+Gi09WKX2d5vqpbRcTGAlzADSbGDXKPFjNReo4930H4NjOZaA0uMtomzZhKlRcl5cVNcUN4E4ti7+FFCKXJDVRdNZ1VwNPSOGUUpi2XgNxa2KD3e4L1y3yJoe8LyQkSIr+c367USMLEYpT/IWBAJvevIWXLF52WHZJg6UOknvuFY7b7S4u/Wbv11GksdCjUzKGcecgsCKyygFnmuzytggGuE/lBqlTkCJEv61IzXzXSgsaVhuuIxSks0o5dUoAcCYGJff95QWpQeaz8zBBUpZtUtUl6KjVbeTOM5yKendbCIZJUt6J6Q9OOVHdDh1raUQqBCjVK7l1rnSMtpxB+kdr01MSe/Mu4RqlACg2hzXRiSW9C42LAMP95y4gMWdfu9U3WvmoKV3LlCqElCihB5aetdTCoyZQ17D2TxGiTkIUp1VLeV6Z96Ps6KGSilAHWXNDFECXg5toBTHxg6+FAq9DCru7xPzCNHW93+b1SgFQj4XylGAHiHziDmUMdInr4tmINctlOU4bTMHt75eRdIenMtr5fHLMnOIwgCbHLOC/sRmK+g4jSpji4PoQ6LS3mlUtfNjzWGifKyKNnMoIr2bVsBm6jEIITSrtOOgfc/KRSZ2HyUWjyQSkKyM5fLG+iv4/WedAdzzRQDArqHzcRAD+rrT2xqUMBnJZbm1lXONtnbw3OUxc/ApD+naJ2OS7bNlbYxzYXCvnKg6qHumudI7ALg32oxT5/8Jj/7id9IrOMZjCSg93qKQPXgG2AGA2O6BIcggvOUxc+DzFnG9oyLeUlU2XSPpnhoxO3fNEFYNVvHk08Y6L+swhgvUwiCwRtwJIPkYJR8bkJcYn4iRVaPUick5nMFPaaftCAOhwdRiSQF9NUo+ALAYtTC+EW5iyWi/NFPkGU0nMCUEk+h1W6PEpXcFXe9OXdmvvysFRhbUcdWsRgngjJJM5PgxdWuUhoQNlFao0dMwFBjuNc+6hZ4Xr5mDw6zqa80BFLzhLACgNW+dB0sNqPZ1DhWdbNa19K4pwZNKSF05ZcBc78JyT+4znUaj/dI7oy7gz4C09M7Yg5fCQNfcVJvj+rr0Jd0uq1dy5JDuetz7IEt6ZxglR3rXQ/cBSe9MjVK1YB8lt0bppZesxSnL5cg7Jea8Dw5dA/SOacWJljLNiZpe1wFdpzSlt4GzQ7wOpxQFQF0CJZ44l5sz1jyazWHus2TkMIsKRtX90FDSO9G0gRIHR82W/zj7apS4Ek73UYoClMMAm4LHrGW4jBKBrWWqPomuJQBIYAwG+p0BEZfx4lJBn8MtIO8b/X6f2Ss/p3YBSYKVqk5px7gzuAGgH6bGjOzBCWRroJRIoPSJX30CXnn5Bi272778agBISe8CITAdjah9nwBgzkMrTjCsaqL2wzg5NtsxvnLXbty/1z6GgHkWaOnd+By2JbLJ7TXhj+VEIxv14JVr5iCPVYQ6yin3w+MhloDS4y0WZA/O6o5adetBkZD+NRNk5dREucFsYSEEswiXN/qqwR7c/DvX4NevPfy9kvLCVzRsO7mpBMMnvcupUXr8SO8yapRyZCiHO7qR3gHAW596Kl5x2XqsG611nLbb9ecxjAtllGx78PQyCKzQvrvXML82e5j8Z6EmGzwh8gIly/VO/r1lhUlywkDobevIKDWIUSKgpNanJCD82GTVKNFIO43OBkJo1zO5PQtk+gqYORi2zwVKTtLVtGuUbEZJ7scMqjqJIUapjBaa7ViP3Lv1abxGKeBmDp7BNqtGyXW9y6pRciW3rNVEKRS6+L7aPKiPlxcouQNYznPaXY/fzCG1S9nSu6otvYstRinEKco+fJ1qOOoLF/y++omn4JOvuRSAPIZJkugePYCsfQLMNdpqx0Bd1Z8FNc3I6KazxChZNUqxVR9UDgOgIacbRx/mFOMatab0dc0ZJToOUnqnGKWkgtE+AkoSFIRteX0S8G9YdWXpAy2EPYBC59MnvZMNZwU2ChsoDST+GiWqASJZIgVZVrvMsQuU+H8tmX3Wc3VaWZa35oG5gxhTQGnvVPqeWa5Y6nbYA5Tl9tD5eTSRg8Krkz1q3QEwewDY/l35+woJlFxGKRDAbHlULV/mT/Rsr6CBHiWl1RbpAG7fMYFXf/RWvOnffpzaRnof+IDSVcFP5USjm/Qzp6FrlNLveh+beKzHkj344y3ygIuuM8owcwBkV/XIJIf6xeKzBwdYjVIBRkm7HSlgVh0A5g5YFuELqc9YUMRt4P6vAesuBSr2w9VnQ8vBU5TDKHmT38BOSk/0sJrzHjOMEpfedQZsL7t0/aKun1/W+YzSIgAlzzJ+6QnrkED2meHT06Q+6V0YmBqGbg1WuMSmz2cPbjFK8pMzSu04KS5ZJeldWSYFxsxB1ShxxhdCv9wraGhHr7vidVgVHsB6IRs8hkJguNc8Jxdco8TNHNQy3ORZ1o/Npb6vJbarGFrzCKmQHg6jRGYOSUUnMbxGaSpOdE/wUmgf10AILbHiDWf5O2TjcmlP/PSzpRuWdL1zzIEy+ih1ZpSkxKfSGEelJneqzlgWKrJ33RxzezUh7WK3d6rulVzRYrJrlAyjxGuJnn/hyThvzRA2Lu9DVnBG+gnBXeif34So9xSzb3Fimy44AxetOIFQ78d60KMTWWJOhhlQovMbx8ZmWy9LMUozSRWTqKEHDUSNKYSBHKzkNUoE0sohl95VNMNKQCloElAqLr2rOs6WtG6KBjNziMIA64SSuA2uASYeyaxRIgfA/YndC4uazg6IWcvzwO1bxLc3q3m6BZSIUQKAqV1Y0V9N7S/FBrFTTta7FkOAlsYChlG6BrfiN6NBlNoXA/d+RZYkrDgb870nA5hIGbEEQmC+JIHSMkig1FeJsHeqruvW2onAFGuXQLLAXZ46KmOoE+pptsWrgJCx7qObEG7PZpTo+NSXGKWlOOYjUjest0aJRgAdoBQErAdG3RrtjZNEirO1rrxiz9uV9M4Bap6ms0csvvBbwMdfAHzjXamfvK53HicctwASyHC9c+zET/TIsqo+mkCpW0bpcK4/l1GKFirx8ssdKZ58xgp89Jcv1l3kywWkd1FgRqm7JVRo+X2VKLduDzDHgRo3AsBD+2f0MevGHhyQYEF+n2aUeI3SIEsobosli31a8IicLhAYYdK7hRrMWGYOGdK7LEapJ0nXKHGAaYFXBRZnUdGj+ZpREn5GyeqjBHq++6V3//G6y/APL9+KX7liAwBZV5MvvTPblhqY0ANmdo1SqX7QK72baRhwwiMFlJzj59aa7pv21yhpcOJK7xxGKUlMLVG1FEIIgc0r+nMHwAgorRO78InyH2PZhy5GaWaX/r3VTjQotOp31DlqtRMIxQbNB72akTmgJFWjCiCUw4CBq1gn/toynVzvUNU2zlHTMErc9Y4zSiS9qwdVY7QhFKPUypbe+ZzlAodRovVk1SiVwwBrCSitPh8AMAhXeif3mfoUcekdYJzvOjFKdg+p9LseYO/5JDGMEgBMPaZrlHxBrNjB2nprHwHgkVgOXC0TE/iN6D8x8KP/p2V3OO3pmdeWEAL16qieFzBurmRQM4leXa8FANP1llq/z/VOTkeDZLun6tiWrLInGt2oj7evRomO1fHIKC0Bpcdb5NqDZ7jeAay2ye7VESeJDYKyapSKmDloVooYpUH5eTTsJG/7sPy85f2pn9wXcLVk1yhFDvDhHbz9rndLNUrAUZbeWYzS0QBK5u88OZtbd1E0hDC9voqwUml78CxGiZLqbhklOb2v2SxfLwAvIIoTznh0WFnTlt7VHUbJrVHSQIklFHclshP9qUICpVAIDDPp3aIwShlmDnQ9ugCqRzFK9STS+2P3n2ITM3twyjvJHrwCaebQdqRVtvROPb9LVetdQDFUK+Pa01eYBD72ud4Z6R0/v6lG06zVRCkUWi5Vbhz0jkrvViPg1K+Gwr1/3OM3OW9bNWeZOWS73qnlsYazhlEqdj8QS7hBGHBU/e9fh4Dcv2YcM/CVBtXtOEGgzu08l94pQLC6PIuBaoT+akk/4+LEHD9tmU6MEnp0I9awMWnWk5g+SgQwy6xGqRlU9XGqO9I7ctScnG9i2z65rT7pXcrMITTHlYLXKEXC9PHBSRcAAAYcoERAb0iZPBxwpHfEKA06tYgukOONYu3kn4EmGsSqT9qy1Kld1rV5tngQXyz/H7w6/DwAYKNilPaWZe8jfm0/nNj12NW7PgHc+yX5n9OfnfncCQTQ7CFnunEABpQPqWM0ntiS0Jl6dgsXOhdkqNOOEy290zG6UR8bX3NeYqOWapSW4tiPXHtwqlHyJC8EeFq2bCIB7IfCYtQoRQ5QUjVKRyz23W/+XnNJ6meuhV8/WkN/taRshW0Z0umr5KjeaSv7c+VUS653Mo6q9I4zSjk25YcrbEYpUN+lp1uo9E7OS/KJzsvQjJKnRqm6KDVKchm+ZrPu8vjfyxmrVFx6R4wS2YOXrO+5jj4QQr/caXR6IunFPbFMYjaKx1BGE0FgA6XFrFHiErswEPr/rnFIJZZASRdkt+r6OgqEw7QpsDiTmISNN5xtxbEGUO653zDaoyWINqOU/UyPO7je5bpdcnvwyDBKUWMSPaGytmbJ1s5JeR5XDdpAiT+TgfRAzIEZe/v3TTcybauBdG0qbbepUUqsGqUiQQMGvDls8OA3cJG4B4BM0Clx5iCC1xsFTcmWNMJeZuYgr4nnnVrB5379CtVw1mx/ndX6yJmN9I4YJVGfNK537UQbdUSMUaoq6V07rOltqgs5IEGM0oZlvbh4/Qia7QSv+5fbMNdoe1kF3qcHMINCsbdGSWAoGUevqMteQyvPAWBAgF6Gvpfl8Z0O8muU6BC528fNL2xnSQ+jNM1kdwAwuRNjilEaxDQ+UH4vTg8ewdtLH8eTg9uwURlSPFZaa+0jAOzEKD7XewP+qXU96kkJ4eSjctD55IuAlWdlPncCIdDukQ6xy8UESqHpUUWgkEAixfR8DlBS+8nlzw+5QGlkYwq42Q2elxilpThewrH6tiLLkIHP125Yo++Jyyi50jst2SvQcNatc9JNZ48wo3T3Z83fHtDIJRsXrB3Wf1OCRQ/n5114Mn7ye9fhBVvXmATGk9QtNNk8XiNL4300mByKblzvDkf4apQWU3oHmATYV6OUmpbswYUN/gHDeISBARULbTirR+Wd8Da1BnDRenO/0b3UWXpnGKXvvPVqXLBxtfpeMUp824VZN08odmIEE0kNkYixUTyGMIDlercYfZRCIYB2EzWWZJfDAMuV7fIYl+8kCaptBZSo7oI1nE0xfA3qo2SWYWqUWqq3ErOLBrsO+UBYqWqez61soHTBumGUU2YOBmBZjJLLJLds6d0E+hArG2dKhImRSJIEuyfk9C6jxPcBSDNXB2ft7W+0Y4zPppUPWYxS5NwjCUz/GFcGmBVCCPSUQtNHR8XJwT4AMkHX4MDjCNdqJwhUj6xGaFzvtismonfyfm0mwY8FAToN/upy/dOMUcK8YZRacYJGy74+uPQujnoYUJLXWKltGNv3vfR8LOsr4+e7pvCNe/Zk1Cj5+yhlSe+WNaQ1+ERpDOiXSbvLDNE29SeKUQ3tGqVJyPqxATUfnTe3Vo3+HwZ2HzvbTVSd85k91ryYegzrRnsRoYX3lt6Pk8U+NBI57V+UPoCtyl57e3CytY8UH+z5FdzUegW+Hp9nvrzoVQCynztCAHFNMkrLMIFSGDBGST3XErt2brqRB5Tkfp7GgNIsqrrP03gwAlQHUu8Bn3pkCSgtxbEfljGD86LTfZQ8o7wZTkftGObFJgIgCDPm68Ao+eqcqOnska5RIg0w4AVpnFE6f51J3GgEjP8+pEadddLhtQdPj9qfyMGTOJ60ZzXaPBLBX35HA7AJIUz/Gqc/UKaTWZfBaws6RYpRYuCWRrYPhVGi894to/RHzzkLl28axV+/5Hx9LxWX3vVizUgNJy0fkf9XpgGRJb0zx3hQJxS9AAR+nsgR39PEw9L1jps5HGKNkhBAMLUDePcpiL74FiaTFPi1azbh/z7/HNxw/slmxtY8AsXYEHuA5rx+hqQuE2bmoL9i9uCtdpJZo6TNFQDFKHV+pv/xc8/CYEXN79YoxS2LnUmxL23DKEWBQIwA42r0e0gxA3WV6B+YaWjQ5ANKea6aB6bN9mdJQAHeV8qfIPMapbkuGSVAMoijwn7PLA8kIGzHvEaJs49G4hg2FXiMevV2kVQUu+/Sg5T82UHbGeUwSpif0PdenJjtIEDA7cGTkgFK88Qotef1OsYGqti6Tt53+6fr2X2U1HELEOtzx1Vw3MxhpCGZmP3lk4Ae+R6WQNrMQOesN5b7V48cMwenRonW6TZdzbSg95k5TLtAaRdWD1Twnp5/wtXhTzGXlPHCxu/j3vgkDAr5bIoToRkaV5pGZh6fa0s3RPSMAGc8F0C2AZQQQoPH5WICUSC0aU4Wo+RRneowLRrs47ctlnVKu0onAUi/n/ggFx2rJTOHpTj2gzM+LcfdJLdGyT+K2FeJ2HyegsWiQMlX51RWIx6NtK//YY2D283f9anUzzxxu9DDKPkAT+hJevV8JLV6nACl0rHIKFlmDkcHsLnAiD6rfNTyEKR33TBKLqtA12gpZCxSyOWm3V27JCcb7MkASp6+UgAw2lfBx171BDz73NWmGW5hMweVSJOhjfqeD2zwPkq8RgkAfh6vAQCcGjyCQLjSu4Xdu8v6ylgxUMGZqweAHT+SAzMPflMfn3IUYllfBS/YusZ2vaubZ6Kuu2jNM1c05xwzMwcK3nC22Y5BuSuZVNAgjz5+QUmCngIGPUO1MvqjxMwHWO8Cfrwqbj0Ptwd3XNwGVa1JXW3sTlWftKyv4h0AsJkr+/nyjHNkkrd13bAl6XTDVyPHB3VMHyXD1KT2KSd6SqHud0RBDFPLkt55GKU4RqQYpWbYpwcxticr0Ah7JejcJxkLfknQdupngVWjpBLo+qS+t1qxsSkn8w3ecBblXj2tZpRidX8Rq6MS9cn5lmaneARC1mG9M/ogflB5PUYxDsC2B28ydm1EMUp7S6s1UIpEbDViJkDZp2zD65EjvVPs2aCYQRgY91rX0KDVtgcRKPhzr0K/keMdPWcmH4N47Ed4dvJ1tJIAb2i+ET9JNuFf2k/W8z6GURxoKBt1B0RSH60vxhcjfvIfAS/6F/0sy6tRCvolozQgZtEbtNBfIaBENUrZboxu0HFZPVjVywkEdJ3SjkCy9ClGyWMi5DOLONZjCSg93iKPUSJ5nLdGyQY877rhbLzxmk04Y/WA1Uk9PZ9aVtxBeseZKgJzys5X90E5UtFk66unQRoVpAK2ZjdyR2JZ5PV8WWiyebxG5BuFw1F2vWNPwqMC2A48qN2J3NqbKDTucockveuKUVIjuyS907LSwDCnzPWuW6Dw9LNW4bozVuDGS9Z6f+eDBlk4KMq5p6yggRYaeFGmDhooOTI/18yBRp2JUTpdPIwwEAZIYOEmG5UoxDffcjX+83WXy1YIADB3QCfiruW1DsV0TydVwxK16uyYONMzMweKpu6j1JSNS1VCev0ZK/Du55+D337KqWq51AhcHTcmw84NV8rNABZPOHntjbW+yDipERgciIlRksnk7kk57cpBP9DhgzLuAMg7nnkG/u/zz8GHXr4Vy/rs+S1G03N9ccbIZw/ePaMk730MyJH50UDuZ4s1evXWKLUTRC15fTcj43qXIMD+PtVvcNftAGzwTAYR+vgw17vJRJ3n+XF937fjWBf7E+Ash6aPUliu6Xt2XrnekfSOrkliNKbrrZwapRDXhT/CMjGJzfW71Lr90rvBeQJKq4BSDxIFTHiTaMMoKWndwIi1Ts0oiRmEwpjTuNK7FpPe8ShFnncZMUorzpSfU7uA+74MAPhSvBVfjy8AAHymfbmet4Z5TM7L+yXNKKn/iwDBFW8E1pv5sp67gRAo1Ua00cvycNIwSrAHgIoErUcIgS0q5xnpLeNT7SfhJ/FG/Hd0LYA0s+7ro7Rk5rAUx34Iwdghx9Ahj1Fy3PJecvFavPn6UzvPV5RR4kyVZpQIKB1BRilJHKCUZpSy+iLRS91tfMin8z3XTLL5+LgdL2Z1JnmJzJEM/vA+4oBtei/w1+fj25F0u3KNP7jE7dDMHALrM39aG7zzT16XtFDHxrWjNXzwZVuxdf2I9/eoQ6IK8BqlDitTIEEDJd0igRI5czx4w1kamZ5So87kQLVSHEAohCXXstjgiUeBf3gKcOdnOmyYjJ5yKJ8pswSUxkGqPrfXj9knYgCqqJM5RWueAVuXUZL7Msuld4LVKDF78EopxAu3rsHqIZUw0/FTZhiFn+layk3SuwxGyd1Hxx4cAMYVo9SvgFLDYZRWDvTAF3w9PQ6j1FeJ8IKtazBUK+tmqRRRB6DO2T1j5gDLHrxo9JRCjFKN0nL5TiWGqdWOjfGCZSVvpHelljw/rajXOpYH+tX7edfPrO0EjPSuFAayVllL73r09Y75SX382nGigRINJPEapbDSC3qUa6AU24wtyWyn5pspaZvcPoFq0NaW5iva0gkwtqR3dCwEBucfBQDsDlfj499/GPNKVsctwqNQAEmCXtVf6dIzNlrr1H2UMIsgMNeLC+Roe11DD17fqM8P1SitOtf8/97/AQB8k9UZTaIPd8TrAQBfaW/FlDJTSDFKJJPMUaq4EQigpxJpo5cVwYQ+/kOKUXKNLfKCP09OZUDpR8kWPLfxR7g13iK3J69Gaanh7FIcVxFV5UtuQTVKnpcjs3NNRdGGs/RyFKGpcyKg1DyCjFJKjliXII6xZb9+zSaMzzbwS09Yb03qmjnw8NWbUGg73iPVTPcoxVfffCW+v20/XnyRYRGOFde7OdbZ/IjXSu2TDlcV0cS54kFEgUzIeX1QKRBo4NBqlLT0rgCjRAmX6SFjQBavYTlcRiRZNUrWNOrrzowSASX1PNGMkqqhcJJiLdchoKRG2GfUZw11BAGwjMm1LDnjjz8GPHKLTD6H1gBf/QPgae8Gxk7L305ilJBgeWke97vL5UHF90kPszufRxhlsGwKKGUxSs12ohPS1HPIPX4FXO/k7+Simt9wNs0omRolepZSY8weyHNGAxvUHNN1vKPg90te+wGXRS6HAeqtGEL4zUJ8jFLCXe+6eIZI6Z2qUVp+GvDA17X0rtn21yhxkwUCSu1Sn3UsDw6cLv/Y+VMAcj/CQKAdJ5hvMKDUNAyMZJQUUGLSu3ac6H5Vhu000ruo2qfv04a6HktxXa1DSe/UMZ7Okd71NQ8gEPK3sZasQYoZUiImsRKF6J+VVv13zI3gM5++HReUKzgtUEAgYcepMQOhFC1h7xAA40pH+zogZhBCMEmjX3qXYpR8jbzJ9W7sDFlPNHdAn4PvtM+25r+x8bu4Mfwa/rV9NcqKUWq6jJIGSp4B2AzGWQiBWjnE3mQIq8UBLBeT+honRmm2G6DE9vt0BZSW9VVw724FsOut1HSAM5Ds6YF2vMTjYwh7KezIZJTygFKerbjTKNaar+BLVb8cGdjSjNJMevrDFc259HcOo7VqsAd/e+OFuHTjqPW9aw/Og56hea53Cy0IP15i01gfbrxknffhCRxloNQwD++OLmqLHU0Dzp8a/iBl/MElbuVDkN51Yw/ugncaOS2FttzucMlGva53P/wH4O+eBEw+ptZZkM3KBEo04u2X3vUJ+fu0StJnIJPxmpDMzUC1hA+9bCs++LKtdmK84zb5ufsO4IPXANu+Bfz3Wzrv9OxB/edYKAeHMtm/OkmleozdueV65wIl1XNJmAGfpjA1Sm3mepdlBGGAUgFGKUnYwFtaesfvsZ6yW6Nk3E9p/4kJq6omu8SyaEYpCyixc+vWKPFwnz2uoYobdo2S/OT24FUX/OVEtcxc7xSjNKwYpXacGHDAwFnIJHGltmKUSjajND6kgNKu23WlvjZcUOCrFAX6WmojwDzKjFEyZg4txij1MkapRzUiLveYxrrzCihFsfyN7lOqUZqa90vvgkCgr2FAzPKW7C9k2YOr+SqihZ6GHFi4Z062EZnQhh8mXwiDAJgfVyuIkES23Ez3UcKMcvFUTJ1bo6SAk/tu90rviFHqXwlc9TYz8fLTsQt2zjCBPvxt+zk4iAEcnGlivtlOMUptve70tZhXo9RTCrEvkcdmGSb08Sdp4my4MEbpWeeuxjPOWYXXXGnYuZl6usGsu330/vH10DrWYwkoPR6DJBQuKHBHAHnkFfC6bnW++TrWKHnke6WjIL0j9iqsSIcnwCu/84UeafcAHm3msNRHyQrL9a4LucpiB2eUjnjQixzAU4MfgrAQvZNlkXFx2VxWnLpyAIEANi3vXMRL58VljCJm5nBYGSWfmcOtH5Yjs7d/CoA5Pp2ld26NEjHVttMVYJs59CtGaVoxScTG1FDX0zz5jBW47owVZl1JYoASD3aOM0MzSsBoKLctE9RSTUnSg3rCGKWs86Ge9Q1hAEVLgaay6qOkgVKKUaLj1wVQ4s97j/QOkGYK560ZwrknD9nzskEzOjcEVqtKztVQib6uUfI43gF2opYn7XUZJWP97Z+eS+u0mQNrOJsCfznRH7bQr0A5lkmgNJRMAFD24CQ34/3nApPQl5VNfLvUZzWlnelXiez8uL7+6HiQk1opEPr9NidqAIRhlJj0LmZmDr3MzKGmGL5yjZk5EKOUKLaJGCWS3mXWKAG1+m79/1HlaseBErkd9jb3AwAaSYhH6/LaIHMCkpbp/aU+jNWhlCSVapT6xDwqos2YOkd61+4svSuFCnTuvlN+MbQO2PrLwIqz5P83XYvP//oVeMczTsczzl6V2v9GO8Z379+nGRd3XXl5hRuBkP3XCCiNYlxf4wMKSM5HC2OUhmplvP+lF+DKLcv1d1ms1xKjtBTHb2TV/uTWKFEBr4dRauUxSkVd7zxg62iYOWiHrB6goh4kBYESL3h3Q5s55DBKJ7r0zhfDtTKiQGCsv+Kt7TpScf7aoaO2bm5Bvz7YjfXtbQBgsQOZ/XG6iD957ln4wdufLA1YOkTJkd5tHOtDfyXCuWuGdJLGAdwRkd6NPyw/H/2B9X3X0jvnuWKzV8hklJqBkn+JBkJkvOzHHwZm93l2KNtVTccsA0rKHjpbeievGatGqTmf7a7ZSgOlJqtRarYT3VYvxajS4FEKKOXIqflvHukdALz/pRfgM2+4PH3ft9PSu1nVKLecEFAiRsnfbJbC7v+VzSi5QIkS4Cx2ueatUTKMUkpOmBPLA8UeiRAYOQUA0I8ZhGg7jFK6NrbVjlFRjFJc6rfWK0pVKWUHNGtN14cxcwiAWQk6pgL5XOjEKNFxLDHpXanal2KUygSUSMragVEKhUBt3lhrDzV3IUDsrVHqqct7bC+GMKXYDAJKwwwohYEA5sblf6qDqfuCGxoMBHP6Ha4ZpZ0/Az7yLJT33mGWxyJlD3735+T9MrIRWHm2HCR40T8Dl70RuOLNOOukQbzqiaek6vKoP9xX7tqtj417vfpqmPPMHGrlELsga0BXJ7v1NU5Acj4a9M7ri6KKAXd7QhdI4visUVoCSo/HyAJKNAoYel4oeRK6XHvwotI7zzKOhvSOFy5X1Ah0QaDUX5H76nNNyzNzoKT08cgoDdZK+Pirn4CP/srFR3U7Llg7jE/86hNw8+9cc+RXTiOeKk5pyJol7jhneiAt/BoJApFy98oKzSip1S3rq+AHb38y3veS8xmjFCwKgPNFSno3Nw7U1XF65AdAkujEoeN9U3cYEee5wkdqBWOUjJmDBEj10BgG1IRnwAgwbJI72DS5I38bAYtRomQvk1GypHfFGaVWwGqUSHqHpmXm0LlGKUO6zYM/7z3Su9zwSO9mFJtXUexJ3alRKiK9y2OUXOmdfiZnACV/jZIBIN3UKJ0/KhP9VmUUqElpVoAEQ5hGsx17a5S0fX97HoEC7Um5L13HRDJTBZRJsqfNHKI0UJpMjD14ZNUoOWYOrI9SpaffgDB1rsqxyyiR611T90PiEQiBypxhlKKkhVXY7zBKBJSkRG9vMqR/o15bI4Hjekdsbs9QipVpI0RdDYAMiRn9TNHJ/Od+A9j2bZzzhWfJ45XRdBhQ5+en/yr/c+5LDNU9cgpw/R8BvUZ25wLwp5wpbba/evcefQ25NXW+2ucsub4QUv5JLQ3Wt7croJroGqVGqRvpnX89r7hsPQDgV67YIKdznjt8QOF4bji7ZObweAwCAC4AyXWvoxolH1Dy1BdRaDOHgvbg3GL8aNYolXrYcSom/fudp52G79y3N1W7BORL7244/yTsHJ/D1aeNLWybj/O4eIPf+exIxxNOSZ+3IxJOQ+UVTZlUG0lmgChkI8BHIMoOowSY5I9LTA+XbJSvNwwAjG83P07vBsa3MzOHnAXFbZ0kauld2ZHeuXUHav80o6Skd0lQQSsJEIkYPYlj+kJBQOnsFwB3ftqwMVO7JEDwse4UjFEaUjUqvuQIgG3mkFCNUr0jUGoyoNSmkX/RQpPXKLmrdKWL9H5I2vL4uk3GAUd652eUMoOZOdB1OKvqw8qxYZQePTiLmUYbgZB1o76wpHddMEqZNus0PXc8VNNw+W43rnfP2VIGfgBUBsfkIGV1CJgfx7CYUg1ns+3B+9py8KCRhEhKtfQ0UVWeP8e4xPRREpoBnQqG5KcaGEC7gUixQtL1zjZzqJYCjFbaQBNYPjKEcNxhlOA3c5iab6UMCwCZ3Jdnd1vfrQ324JHYmP9Q/6zyvNzmPQwoTWhGaQalUKDZTiSQmTbSOx8rMxv0oxLPYUjMYiIwwFAeWJN79GMWYWCz8dy+fyTeB2z7tvzPOS9MrYeHe11dtnEZ+isR9k3X8cOH5HOgVnEZJZ8axf8+CIRAEAg8FMrGw2va27GnFKAPc4iEPIaN0iDAek7lRdZ63v6M0/Gc81bj7JMGvds4wPrk0eDbkvRuKY6PyGrkmlujlOd6twjSOzaKaLaTJTR5baMXMyixKdWAMknvJrOnZ3HumiH82jWbu5beXXv6Cvzn6y/HhmXF+xosxQkUilEaV71iVjSl7e1iS++6ics2jmLlQBVXn5oG7xwcHa4aJbe3kZbdUTxiTC9yzTf4IEsBRgkw+6JrlFTiGIWBbthK7mupeOzH8nP9FcCNnwJe8gn1TEuAqZ3Z25kkwJwxcxhMCCjl1yil7MF9Ml7W8qARGEDRDAyjJM0c5Pep45nlegdks0P0vA8iM7LetQy7jGV9FVywdggbT5J1YNSbp96K8e17ZbJ8/trhTAYnq0msGylGSdco2cfijddswsqBKn79ms2pdRDjAthNojvGjJJqKjYJvcsAAKOYQqtt+ij57MFXxvKaejRZjlIUWPK8UhikrPBDByhx6V2jMiQ3B1XEkNORrM9nDy6EwMqq3Lag0quvvbmEpHeumQPZg2eYOQiByAFKa8Qe/epPEtZTak5K9PZYjJLMawbFtC0JZtI7n4RsOpDzDYhZ0+uHtk+dCwB4VfTfeFLrZisX4ffn6vo2AAmw/HRgeF1qPe6+8ugphzh/nZTf3bVT5htZ1ySPLMaTvt5bOgnzSQnVpI6B+qOaTaonJcM2FohSxvO9FAY4f+2w6SHpPEsHqh6gdBw2nF1ilB6PQS88t5lqnutdlPOSy5XeUcPZTvbgHjaLtjNuyd99jNVih7dG6dDNJDJrB5ZiKRQQv0tsxGXJT7BcASVLeqeSjUNpONtNnL92GLf87rXe33hjZd5TaTEjZeaQAkrfRyBkPUfuqinJF6F5fpCZDQElr1NTYtmD95ZDBIHALKoYwFw2UJpRrl1Da01jyIHVwMGHZH+lIX+DXcxPSIZGRb8CStnSu0m9bVx6F/kGZNoNIJGJH5fetXSNkgRK7YymmpnSO1p2ySN78w26hQXVBazhbBgI/MfrLoO4ZwL4BFBS0rtGK8a375XHmheVu8ET8m5qlOi6dvPQN19/Kn7zui0WAKP7VBskhKK7eksCSr1qP2rLgP33Y1hMZUrvaPtWtSVQ2p6sQCkMrJq2MBDm3KiBSFOjpIrvw0AzmWdtPgW/f8kZWDFQhfjCADA/gXJTXmftxNiDj9YfAe6+DTj9mcZavGTMHAgoRWgjQsv0JVMsXDtOdM8gHoEAwmm5P/fGJ2FLsANrxR58W12X3C0tmiWgNKy/G0+M653lxsmkd77n1IwwTWf3uTVK06Zm6jei/wQmAdw2Bmx9pTl+KnoTdSxqnZUJ7oBpKAT6lDR0Yk7eO670zs8o+R9+dE1WymXcO3syzhHb0Dt+j3a8G0dvV4NuRZ/vbn80zqyWlswcluK4inKG9G6hfZRINpc7X0FdOgdDJcawHCn53SGYOeSFd6R3KZYC0IzS3WITAOX2FMdeRimzuP8Ihq6PYDVKi31dp8wcCCgNSy08tn+vGEjjzWZpG+n515wF4jiV1IaBkL2SVD+X33nuRXjPi85DIIAZZSqQKb1zQQUADJwsPydy6pRYfRJgGKWhWoZUr06MUo/FKBlLeXZMWB+6ZuBzvVONLlUCky298wGljOe6rndl269l2N3Vqwoh9LrDltyXmUYL371fAow8oMSTMu4I50bKzIEYJc+15TJuNAkxLt3I7gAY8w9iL1SiPSomHemdU38E4CTFKD2UrEQUBggC0wsoCoRxbm3aNUrGzEFooNY/shKvvHwDnn72KggF6GuT9wOQwGFWMWZn3vJbwL/dKG3HyWipXNMtMLRdPYAqGjoh7y2H+hbcP5O+BgIBiCnZZPYHsew5tl7s0pJQfi5DBZT2whgSaEYJDqPEXO98z4opz3za9Y4GPnjc+g+aVeLS2BoBpWpnsxx3M8JQoKckr8HJOds0g8JrD54hzaVJe8ohfq6ki6W9d2NAAaWJpLerwa2iwJ+Dr8Ee+9m1ZOawFMdX+MwckqRDjVJOAS+9LHNrlBbAKIWRYamOGFBiDk9d1ijlBT3klnDSUqRC1Sg9EKxHPYlQShrA5KMGXFvJz9F/ZK8flc+PdaM1XLVlDKsGq7hi87IOc3UXKTMHAkrnvkR+7rkT/bE8bvnSOyfJd/9uzqYZpVBoNilGgOddsgVPOXMlAiGM9C4TKDn1PAAweJL8nHw0eztZDyUAOKk6h99/1hl4w9Wbctczg6q3RslK8GnwJ4ggIpO8cEYJgGYu0vbghjVQC5eSOsDvggr4e+vRsz1u5kupNaPEjX3k8YwUUHr04Bym6i0M10o466Rs9y7OQuRdJ67RAzG4HR0V2TRUo9Q1UKJkvKbuIVX0P4wpNDP6KFHielIigcXDyZiWR1Gdks0oUY1SYG1rmUnvLCZk9fkAgL79twOwpXeVaXUdH3zIDK6WarqOZS7mQKnJ2DmhAelBD1Aqt2cgFEP1nVg2Zj1VPKoloXUGlIJpKdHz1SgNYBpXnzaGtSM1nLK8N9f1DjAmEIOY1s+CZjuRgF2xUbde8Gd4beNNaKAkAaKS2HI5XK09rdfTKdzrKhRCW8pPKkbJlYr6QFHW9UnXek8pxD2JNHTAnjvxtEA6hj6cjHXV+24hrncDDlA6nu3Bl6R3j8fwMUox6yMTeC6LPGZI1xcdiutdhiFEuQbM1U8cRmlJercUbqgRzynRh0eSMWwSjwH770copKxEusupEeAjJL3LiydtWY5vvOUqrBnuQRQGeDLvI7RIkckonXQhsPw0YO/PsXn+dgAb85NZem5UGHAp9QCQ8jo0ZlLa/zAItJHDfFBDTS1fAiXFKPmkd0mSwSgpoNQFoxTNj+OVl2/Inl49kyzpXTOj4ax+ptWs49oO5HwVIZ/pBCpSh7PBBo8owrKRRPsiT3pHv0eeATnAbw6k1h207PfAZRuX5T5TCWR0CpdRovGIIkCJJmkquVZPt0CJrouB1fLTYpRMH6VKmGaU1kACpYeSlThL/V6JAkzXFSiiGiV1DbjGE6VMoHQB8KOPomffzwBcLqV39TYEYoT1cTnNwe1m+soAwkAuJwYkk9WaQ1U0LLOUgWoJU/MtHPAApd66ZIkmkhp+EssBgg1iJ0LVuFbXaoUBxHS29G4A0/jz55+DBAowcNc7z7VCYGt5ckDLw1rt2DB9QYSHVj8d/xPfjltrt+Oy2a8Bt/0TcNIF1rOjGtOzZgGMUiD0dUPn2wXvPkOFvIazgGSU7k6U3Hf7zXhxOA4A+GDrmRjsilEqNi3fHpdRIuOLJUZpKY6P8DFKlp2rr0Ypp49SXm1T1w1nXaBEMpkjBZRo9LSHmTkcOlCi58wSUFqKVCigNCP6sC2RNrHY/4DT5FXZgx8D0jsA2LCs97D2vbIYJSQmKRtaC6yTtT9b5n4qp827pXzAhUm50JxJ90YJDKNUD3ut2WYT+Xyq+hildsM85/j6NKOUA5TI8a46pP6/P3taIFN655X4aoOaHiuRabOGs4BJRNM1Sh5Wjp7rPhdUwC/jdmubssJn7KOAbugMmG0cy2+e3CiYlHEXO8AApCKPa5epypP4eYOui0El0VTMkqxRSkyNUqqPUoK1CihtT1boZLbC201oe3CbUapbQMkxkwA0o9Sz92cApInCXLONfsxCqHo3HHxIflYGgDDSx6wdJ5rJqqJuJdkESA/Mps//wLxsMLszGcVuDGM27EckYqxPHpHbrK7PagRgJtvMoYImMLULgravg/RuRyyP91iyV7NyzXZi6pNqy0AkyPf7Vd3mQ99Rx88sr6cbRsmtUWJASS+v5O/t5c7nXb46F7VyiNvjUzAVDgOz+1EWbXy7fTa+n5xeGPwAC2SUnHtKM0pLQGkpjovw2YNzs4Vc6V2X9uALcDqy4khbhLPR18VklAo3x1yKx1+owvzZoIZtierYfuBBY+YQCLs4+XEQ/D6ptKaAhroHh9ZIRzkAG2d/mpo2FT4pHGA9V1wL7jAQmlHiQCkQAjOKUarEnibY/BnF6yt1jVKO9I4YpVEltZs9kC9PY/bgJAdEYxpnrR5AXyWyLfcZS85Hpcn1Ll2jlCG948eQDDHIet0N3+BZEaCUJJY9uA51vkTcQAlm0O3k4Xznrjqz7M4LN0nt5nnt3pJdMUpJYq4LDZQkYBnBlN1w1jFzWIZJ9Io6YgjpeqcGLoZq8jj3VyPzTqYaJe16x2qUCKRzoDR2BhCWEdYnsFbswdS8PJ8jgr0LCYj0DFnLlkBJXh9VNKz7i3op+aR3oxNS5ndnsh6AwK6qNGs5JZFsMl2fY+EMELeQQGAfq1GaQRXNRB37v3sS8P6LgcnHHNe7dMr7cCzvlbF4nx78acaxkUT2LUdT6f8eq54qvzuwLcVGVzRQKsIopZ85VUdqV4485hxOdAJKPaUQU6jhAxs/AJx5A7ZhNf649Ytq3uLpf/EapWxGSTsKHofSuyWg9HgMnz04dyLq2h7cMwKo5+tSeucyStqhypOYHI44XNI7sQSUlsIT7Za+D2eDPjxkMUryzzAwjFKpG9vh4zj4C7e/LkfNUVsm70vFKK2avx8DmO6+RgmwnO/c5CkKhbYGb1hACZhVZg5eRonWFVVhNe3uhlEioNSuWyYM6XUpoISqaRDanMUpIxX85Peuw1uecqqZlp5pkc0oxYGfUUpL7zysHL1Dsp6NPuldEALKdjrfBEIBRD5oxoAnlz2uGa75l0ObXnD02r2GRBeMkvtMr3QDlOYOmvNM0rseKScbFDNotWPNpLj24OuEvC/2BsvRQEmf23fdcDb++Lln4czVA8bMgRglBVpmm8p4QjTNdcuBUlQGVso6oXPEg7pOaJQ1c8XBbfJTsaDEYsZJokFuFQ0rISeg5GOURsclUPqxkt2N90kL9s0KKBGztlrJx+LaKNrgx1roeiPM7JE5x6O3dnS9296Ux3tZvFeDulY7MUCpdzna6jqarYwod8IE2HuPDZRa6l4oVKNk/z/yMErlUFisj88ePGvgjC5Jss2frJ0MvODDeEn5fbhX1SzRvEVUCsUZpWwzh/KSmcNSHFfhswcnICNCI9DmUUh65wFK3TacdeV7Ppng4QzeR2kRzRxMv5lDXtRSnEjBenTNil7sTxQ4n59g0rsAy3rlvTXam1HXcYIFT2h6msrooE/VQvWvAPpXI0CCdWJPMXtwFyixOs10H6VAS+8aDqNE7E3FB5TqGaCsT4Hf2QPZz0FilIbWmGcma0BrRZLodU0nPZgCAwtz4+nRXzb4w/dVS++ErD0hUJHNKLH9omdjVusEn/ROiM4KgxY7rpxRisp63l6Yd9CakXxGqbnAni10mHJBOGga+/9dMUrEJtEgAADUJMMxDCm9a3gazkahwHohDQ0eE/L6okGUc9cM4RefsE5uu2PmQKwUNY8dUIYoCKJ0gq/kd2cHD+qvVpQYeKe6QQXsAotRkvvSIxpWkt2n+uqkydJEA6XrrnsGXrR1DdacfhEAYDO2A40ZnPKZZ+MPog9jZSCldHFvujaSDB107P25Jb3zJfzbFFDqT6bRq0B4qx0b6V3vGFoKKZYCAYydLr/fc5cNZFrqXihSo+SR3rnmDeUosMDRQhklwEgueb8xLc+rdL5ei5YM8OPhmjmUlqR3S3FchdfMIafOiH/vGwls5zFKRRvOkvQuo0bpODdzWJLeLYU36CVeqiEOIsyTjKo5a0nv/s/TTsNfvfg8XHv64hsnHJVI5IisZSLDgr+Yqw0FGFjzR/TL47BcjHewB88AL0x657PhJeldMzKJlxDQZg7VxCM5ywJltRFABAASUw/iBoGinhGdKLsGDzpadf28nkEPYgSYVr1g9PXEgw3+8ESxFZjndRktDSqya5RYEprVtJwiq261I1DitbLuu0DuY00YMLVywNPDaYGRclqEf8zQDfeZ3lWNkiu7AzTwGBIzyh7c00cpEDhZSMbjUahmvN4BTrIHn1fbphgG5azWF6vrpTaaRnzLtgCAXg8ArAjZe5jOoSO9ixMgVueuigYGmcV9v1O3QrFB7JI9m6IqrnziVfiz55+DZOwMAMAWPAxsvxl9+36Kl0dfwbXxzWphq1LLoTolHTt/aq7/DNe7adQwmcjBhpGWvD+bMWeUlmmgFAYBMHam/H73XRYbU252wyh5pHcuoxQFlmzRlQgD2S6otJvDXIYJG8TTs6A3o78Yf1ZkNr52gh9fl1EiM5Jm6/hrOLsElB6P4av7yWOFAPPS8tqDZ9QXAczMoZM9eIb0rqxGS/NkKIsZFqOkRoYWASitG62pz94OUy7F4yqIUaoMIBBCN2tEc46xkAIrBqp4znknFX5hHfNxx3/IGoJvvsv7sx8osX45fQSUJjpI7zz1NYD1XLn61OV40pbleP1VG/W6iVFqRk6NUkI1Sj6glFEPFYRG1uTrywIYUFQbkWAJyGaUGDihmqkZDZTG09NbNUpp6R2gCuBpczOld4y56jSI5JPeAfkDboBhlIJSGqWo40qj/r3lcFENRWosieym752b9HbFKLlGDoAGSgNiFq1Wg/VR4klugEHVE+eAkl56i/MdRom2jRL/fg6U3FBAZJUw1+HyyDNgSYwSM3NohnK9taCJfuYo2F/xJ+XnCdmvCavO1ddIvFwyNyvEQWDP3XrapzS/Ktdzxg2p5ZDznY5t0nQBYTkTKAHAjkTVhbUkS9ds8RqlMckwQYGVFRLAYc+d1vM46goo2f8PRVp6Vwo7M0pZQJ7OxS9dug5vvHYzbrxkHQCbUaKeWq67HgWXehZmlCwzhxOHUVqyB388hh4NZC85/WLLuCTyao2cBoH++To1nO1k5nCkpHfMzKGTDr+L+P1nnYlXXXEK1i9bAkpLwULLQgYRNGEK8x1G6YSL7d+Vn7vu8P5sAaW6DyiNAQCWYxwHFyS9M8+VKAzw0V++WP9UCgX6hR8o0fkpx74apQxQBgC9YzLxIjmPG90wSgSuS72I52XyMYVeyStQ4ToPy/XOJD+xiCTTlcSooAGo+g4LeLYaZpDLV6OUyShl9OTjvZS88+UYA6n194p5IAFWLCKbBADVcogp1SuILr+FmDl01UdpQjq6WUCJnA8BRPVJY4vtMEr9kOf1YFuyRt5BFKfhrCvv6m3lACVla7+SAaVlged8K6DEzRwaqKACYLTcsq6nLEbpvEABpZMu1N+JSj92JcNYKQ4CD37DnqFvJcTZNwCf+rr19YTLKNXV/q2/AghC61kaBUIDxp3JKE7HIxhu7QYgpXaNiV3SeL93DM1ZOV0UCotR4uC0O6Bk5hNCAvMej/TOWr63RikDKanZVgxU8ebrtuivfYySy6hTVKIAs422NW2nyOujdPZJg/jmW67qvs/YMRAnyPDkUnQV3PWOxMJ5zWYBVqOU43qXW6NUtOFslvTuCDFKDZNU6FHTRQBppTBYAklLkQ7VbBZVxSgxoMRrlE642Huv/FSNI93gL9yKT3rXq4BSR+ld5xql9LoD9KkktF3yS+/8jFLGuvi2ZzJKqg6rNqITz0xGieqCWG+oKaH+zmWU7D5KQWj67FAvJcABB7wtA3fy61ijpGqxQicJ6yi96wyUaopRWt7vmcaJU1fIZ/g5J3dOXnkSScepiFI6bQ++gBolDpTCCHOBarDbGGeMknkOBIEB8wc0UCrAKDnJeK01rv4YQSoGJKM0JsYRyO5IGBGe8+0xc2io+rehss0euP2qKM4NHpB/MKAUCGHMbbbfbM9wya+iVEoD5XG3Roli81PkNlr1UmZbHlOM0mBDDmQ02zEeeUTWYO1s9cm6KyhgMnaanGlmj66fDBAjbC6s4Wzo1BNRlMLAklP6wEqnGiU3qp5rPIsBdYF5kchzvauWQqxf1ouVg4s7wHEk4gR8Ay9Fx6AXOW8Y2LFGKecFRyDIK70rag9OL0hnGcyd6ogEl97RcWo3svuFLMVSHEowRkkIgXmP9O6EZJT2/lx+ZjAslj14XfUUypDeLcgePMdNk9cotViNUiCE7qNUzpXeeYCSYsA6M0rDZnSfwJMbxHDTQA6ASTJ06CC949dSKITlTmZ9T0HP3bBsP5uL1ih1Lb3LaV7uSO/GCjBK//jKi/D6qzbigy/b2nFazrYY17vDzShRs9mTrK/nIyn7LjcnvH2UAGBQyGt3PJZAycsuOA1n3W0zQGkZUtG3AhAhIsRYBvmcGkI2o0Srb8eJHvAZKtnmJf1KjrUK+3GGeEjuFxo4Q2yXE5xszlMggG2xAkoK6H2y9SR8pf+5wCWvRRCIFFCwpHc04AAAW64HYB8jXpvzWCL3f7ApB25a7QT9bXn/ffKeurQLh3oWl3uBESnTHTggDShoYEXuUHf24LQP7rmpOGYOvvObDZT86+VAWbveOTbkZv3cPKRojRJrLtxz4gjWloDS4zH4yCCNCOY1jQXy+ygVsgcvKL3LKOA9KmYOJeao1PJIbZZiKQ41rBolJr1rzaMckC7+GH5MP/gt2bNkx23F55k9YEwNZvZ4+wXxhL7sBUqGUTpjVU5iUkB65wavUWqzZ2UQmJogP1DqIL0D/IxSq26YmxqT3nWqUWLrmaSR9FzpXS1tWECMEqtRsrBB1vHrWKPUQXrXkVHyvEsIKCkzh7ECjNJJQz1461NPKyTTs+o3ugBKLqO0INe7wTXW13ORZCWi+kFtssETV0DWMAHQroflyLOtkb9GiaK34bm3KIJQD0iQ/G4AnvPt6aM0F8v3/kBkm7WM9JYBJPhY+U/wX+V34IzgYZwhtqMs2qhXRoChdXraMGCMkop/aT8Znxr7dX09uoNInBnFZgmOsGwLMCJ7MoWenk6AYZQGVCuCk6Z+ijExjkYS4mM/Z82Yaf61T5DL2HOrnE+dC0Q9/mvXCb7ZdNxSrnehI73z1ShlXJ5Z1+25jFklUFNy1qPXv8iM0vEcx/AbeCkOW4SReYDSS5deXL4eSkAHRilHtte1mYNbo6QSgOZRYJTCMrTYdwkoLcXhCF6jxKV3AJ5z1iiefPoK3HDBSRkzHwNxx6eks9Sdnyk+z957zN/thpcF4Ql9eT7bzOHCkSZeeJGdZFqRZdmdI72LmKypXTasjaxRKgKUfIyS2nYfUCJAJAKgMmjMHDJrlNKM0gT1j/G63vntwYMAWprFGSUrycps2NuBUcqU3qn3QRZDr5UFHmDjSO+etMWT3B9CcBBBl18R6V2aUSqYVsVtYOox+fegfY/XSxL8B+zeKDs91PpVck6ObV5GiQb7MoBSbW6nWv/J8Ibq7USGDv1kJ85DMTeUJLeTBDOJAkqh/d4/d80QThWP4JRgFyIR4xdL39D1SRMj51oHXAiBbQ5QejRZbgFGlwkJwaR+pz5Nfp7/i/ornsj3VtJAiXq2XbvnIwCAT7WfhN3NHnzrHnnfaincmkvkMnbfho1iB84W1FOqM5sE2PbgWgJX9kjvOKPkATNCCC+IyTK4ecVl6/GW67fgs2+4XLcqcZkrCrvBcbFrmmq+gHSN0vEcJw43thTdRblPPjzp5a4TtowbPbePUoa1N7AAe3AXKB1p6R1jlGjEtTVnvj8RojkH/OzfgE3XpV7QS3GEw6pRAuowL5fNQyE+9PLOkqGjGiQPy6q98cW+e+z/T++xZTKwgVJpnka9mTxIMUrBTIaUjSKTUcp20+SMUlzmNUqHIL0jkOeT3s0x2V0QdGaU6HtWCzGR5EnvTN0ll8aEAWOURFP3ebXkPJmM0gIazgKMifIk3ABTFvgYJbkNr7tsJS5cewGuPJxAiTlOdoqU6125IKM0Nw4kKrF3GJ35EjFK4/q7iguUYDNKXtc7Lb3LqFEioDSUMdgwsArYAaxQQKm37QHiHte7mbZMLftDW3o30lvG8wfvBvUMfpb4Dm4OpIvc5MjZGGPTBgLYlhgL8GZQxX4M2EyHs8//1HoKnlv9MVZd9SrgjOcCb77bshEPM4DSfYl8Dw7MPYorgttx5twP0UoC/G37OQCAB/fN2OtbeykAoLrrNnyt8j2zAQXqk+S+eYBSB3vwLFYnZKYUZvn+9UZhgF+7Rjby/drP5bOoFIrOQKkgozRTN+e7L8Mk4niMJUbp8Rqu9GRWJSM+rTKQL6HLk96Ri17hhrPHkPQOSBXDnhDxww8Bn/sN4P9dcbS3ZCnIebLcDyEEEgRoheRUdYSu+UMJknpl1d74gowcKDyGDjp5wDzCtronPYwSmjPZhgIAAy/99vc5z5WINZyNS5xRMtK7Unuh0jvPcSLgQ7VJnRil/ffJTyUnAoDxWAEln/SOnl2lHtkwU4WU3qkGuln24LRPVNNFoR1BM459Sx0flxkiRzcfoOPbmsMoLSs18fSz0z10DjWqnmacFTQ7vrvcwftqVBAo0TEo96Uk7w0CSo0JtT1OspokBigpkOyrMzGMkjwfNlBKUNWMUhZQkgBCMkoJeloK4Aq2HDJzoD5KcYLJttyfWpDOF66Nbtd/92MWTwmlfG1y9DxrujAQeDgZQ5zI5U5WVwMQFlByE/zdGMHvrP4wcMVvyhMzsNo6Qbz+jluVH8QA9pQkq/a70ccBAF+ML8ajCYdu7Bws2wz0jEDEzgBwgfokwL7HaJn+Pkp8YMOfrnttwwtQofQsqESh1whkIfbg0wwouU11j+dYAkqP13ClExooeWxCgQ59lHJ6MB0yo9Rlw9n6NHBwe7Fp3UgSk5xSIhXZ0oUTIh6VLybMHQDi46CnwfQe4Pt/r0dFM+OBrwOff3N2EfyxGE2TxNJ7pR3aBdjHdGhGqRug9HP7/x6QRS/mZUKNYEc9NqtR6TO1lhnOeQAKuN6lE/0oFFrWlLjSO9VHqdz2uHAWkt55Gs5qRkkBpE6MEh2/5afpr8ZzGSV/HyUJlOTzjUvvLNlOpxqlRgajROssOwCLmMOse1QDpWwzh8M1aMb7KIVCoIQW/mrijcDfXpILltykNMsCOxV0DBw2FTBAqdKU1385Cuzz0pxDBFn/MwVl5uC1B3cYJbaPQ5hG1FLXsZLYpUKxMSvEQfSgjlKirpOhtWYal1FKEky25DHoFc57vz6F9TMSKP1r62r9dZwITC8725o0EAJ1lPEYZE4yXpYyvEoOUALyk/ogEBo3uf2DHuqRtt9nBDJ/+Gr7gtT8+hgLoeuUrFgAo6RBeRRYoFvWDvF9zWaU0svvvA3Xn7kSF68fwXPP9/fnKzPAn7VuN2YbHQbEj9NYAkqP16g4L50ZAkoem1Agn1HKswcvXKOUYebQjetduwn809OBv7kAeOzHnaf3bQNJIWgkjl7YnZL04ynGTjd/uzKoYzHedxHwxd8GfvB3+dN95g3Arf8A/Mvzjsx2LUZoWVTVJBqaUSpgiX/bRySI7MTYHq6gZG+6G+mdYpTI6cvHKKljsQxqBLt3eXrovpOTHJCd6Oe53iVNbYPcYgy7ZJTk8yBMmulnYa49OKtRcgcnNKOknr2dGCWq8WJA6SAxSt4aJVN3yaVKUnpXkFFyWTItoctglBqs1pOHKvz3Ml98W33H8DCrC3gxfRAAW4N7sKb9CLD/fmB6V+Z8dtILPOGUjMFGN+gYsL5JFI2y/K6qGBzXyIHOczsRmuX0N5x1GCUGlE4SzMiBGxfxUPfo6b1TGCbHu7Bs7t0g0ufFMErARFOupyqce+Tbf44gaWJ7PIZ3tH4ZN1Xfig+3noL/03o12hX7ONBxfSiW7PHBkgRKNqPUPZtCDE6vY1W+vfcs6///G9vAjc8LwJhF8ChYo8Q3kZYpnKazlShA2b1fPdFNjRKPU1f2499feyku3Tiqrx2rLUPUmc1yY6S3s8HK8RhLQOnxGu5LZ9ZTB8BjwTVKRfsoZfTPoO0skjR+/+9kYXncAv73vZ2nd4Ovg17wzovmhIiYORE99L9HbzuKxOwBM0pOTFhWUGH0jtvSfTcOJZpzwE8+LgHJ9pu9Lm0LDj2C3oN1o/JaDyrZSbwV85NSQvnF3wY+/FRT73Qkg9coFWEn69Omyeb6J8rPHOndqFD71Lc8NY2W32UxSnHMGGLXjCA76S7NyuXVkwhx1SS9QgjMgUnC3HmzjA8AA5TiVpr1yWKU5ifSAHjuoNnfZZv11wfaOdK7TEYJ+vlWZSP/hWqUOpk50HHPBEoZjBLvY+fGYW4+fsE6w+wIIXBV8BPzo48JVMEP18UbRjDc29n1DIC5DuiYsGgp0EANYd36JKrxmkYPEpXGlbz24PZAH5ferRZqn7Jkd4DupXRqbRofefEmtb0jZpt7hnXWr13vkgQHmxKEcKYSt30E+O57AQAfKb8ICCLsWfNU/EHr5fhk+6oUwClHAUZ6y/hpIq24H61uVseCMx2+Jqz5IIG2s98BSo/UDFC6G6dgP9LskLXsC14OvOrrmP6FfzHfFWSUrPuQ/c2BUikMLIOOLEOFhUrveJBsc4CxoXm1YFnxisvW40Vb1+AfX3GM19Z2GUtA6fEa9NKhYtyO0jsmoXMTRV2A63E56VZ6l+V6l1eHAEhG7JvvMv+/+7+6l+BRQhFEZl+0vaoHIB6vwWWEiwkoDkfc9VnzdxbbqX9n1+433rk463/4+8BfnQt85nUKkDwNePiWxVk2YEnv/vR5Z+M7b70a1R5yeuwAzmf2QlfgP/pDCeaOZDTnzeBC0i4meaT6mtoy07gxR3qngZLPvrgTo8RrvFwJWE6iX5qRQGR3MoyIN/kUQBMRGolKZlJAKYdRiiomiXK3VzNKKlHnDIMLqvYyNo6NXhvXO2d6wGaUAr4/WYxSN2YOHRgl97jTvmVdK3pbfYxSB3CWFe0m8IkbgS+9PXeyZ5+7Gn/yC2fhC2+8AqEQuLogUOKj99edsTJzulTQMfAk182y/K4Wy/ez20OJBkXIyAHIkEdF2YzSamKUshzvAC3JC8Yfxubv/678bmitOY9MNsjNHA7U5XrKCXtv3vK38vPK38Fv/fZN+N7vXIPlfRU2f3r1G5f34q9bN+A7T/xnfH/gqQA6u7F1qqehe6DPkUju7dmAViSvu2/H5/jn5esLAuDkC9G36VI2RTFAwe8xDr44kC1Hne3BgYVL73jQeqjPFbAwM4eecog/e/45uOa0Fd1twDEeRxUo3XTTTRBCWP9WrjQPmiRJcNNNN2H16tXo6enBVVddhTvvvPMobvEJFKS914ySehF0AkpAmh3Kks0BxvUobuWPxGfJ94oyOrtvly/QobXAKVdJCd0X3pztyuQL1sE+tf7joV6kaHDQt9gMyWLHHf9h/iYw74sksUfTt9+cXePRTfz0X+UI/sDJRm6y//5DXy4FcyQrhQHWjNTM9deJRXWTt8kdi7ddRcJNyovUKVGiv/zUXEZIAyXV6NLLdGuglCGLontfhB4zguxjHM3K5e3CiN2gVf1NFuFdASUgu5eSrlVRAwFhZJJn9xomqeyyLQCAJ26Wx+XSM5Wxw/xkmtnLYJSk9M5Xo8T3KcseXL0/WnN+2Sdvs8CDEmufRNCaz8MouXLxorHjNuDnnwe+9z7gwLbMyYQQuPGSdThz9SBGGjuxJWD3U46rY8Ken9ef0UWCSM8rT40SMUr9ibyGU0YNdXn8JhMje/MChBIb6JsbRy1oYL3Yia+W34K3Rp+Qv+UxSoNrgRVnSen8zp9I+/qnvNMwSgzU8/UfaCiWi4DS9B5VWyeAS16D3kqEsYGqxab4WJBTlvWhjjJujU/DXNvU8lCUfdK7goxSX6VkAYogjLD35OtRTyJ8pnmJd14vYODPpgMP5q5br4uvN4NRchvBZrE6Plv4Lgklzczx+jobKD2+OZWjvvdnnnkmdu7cqf/dfrtxRHn3u9+N97znPXjf+96HH/7wh1i5ciWuu+46TE11kfwuhT/oZf6/fwnc+ekCrnccKDnsipbe5dQoAfnyuywzB3phthu2ZMwNSgZ6x4Cr3ia39/6vSgYgq2dHahmelzRJF04kMwe+L9O7FgdQHI6oT9nSwLztbExLVgOQbmBJG7jvy4uzDQBw6RuA9colMKt2hGLffcB9Xy22fOZIpiMnibdi1gFKeUDycITLChRxviMjgmVbchkhSmZOFipB9TFKCizggW/418Ws11OZQ470LpyWEs5dyYg1gkyJ3IwGSg6zked6BwD9ahCQWDUKt0YJyK5TcuqT3n/jBfirF5+Ht/0CFZYnaett3kepkOsdNw3IAC4Vto8+hier1qiT9C7LBAIwjmLdmrXsf8D8ffungN13dlQobJr+of1FDlBaN9qLM1cP4LnnrZYDHUUjR3pH9TqDCihl1SiRkcNwreSvS+FmRO85A5v+52X4xfCr2BQ8hl6h3uN5jFIYAa/+OnDdH8manFd8DlhzkZdR4o5y1A8uaqvn20PfkZ8rz7Kuc349+jZ/45i8fh7YO41GWw4AlDsxSh1AgnGZC7CWna8wELj/kj/BJfX34+5knX/erH5Cq86Tn6c/K3/lKkQBRqkUikKMkg/DdCu9I9nmgMUomW0pKr07UeOoA6UoirBy5Ur9b/ly+UJMkgTvfe978fa3vx033HADzjrrLHzkIx/B7OwsPv7xIywxORGjzKQa//FqYEqN6mbJm3jtULspE9g7Py3/n2cPzoFSnqFDlj04f0HnsTr8hb72CcAr/ls+xHfdLmV4RcK1BgfMi+ZEZZSAYxcEHtwOLS0DcuUvenQ2LANnPV/+/fMvdF7HzP4OAIyxBJS85gGS+UngfVuBjz1PJmSdgq6riF1zmsXsklHqppfRYoSbsBZZ/76CjJIQKKOJp4YqYV13eXpZZ94gZbKP/QjYc3f6d09jVh26kfVsioEJFUO1Kxmx7LQpuZnKcpjL66MEAKdcKT/v/pz9vVujBGQ732mgdCoAmdg857yT0NvbZ2TC7nYxdidVG6H7KGXUKGnA4wCAqGLUAj6glFVrpF3vnG3U82XUNgGm59vEju5YcG5Y852/AD5wGfDp1+TOsqz+sP1FzrVdjgJ84Y1PxHvPfAD48DOKD5LkmDnEVXn++8UcIrQypXfUbHaollEXRYwSADRn0LPrB3hh+C17mjygBMhzffkbgRs/Caw6V363fIv9CTthn1cNZwW9W7Z9W36uf5K16NCVgjqxcbm8Tx/YO4N6U96nlQ5mDp2MB+j6LkcBNo0ZwB8IgbBcwTg8zwsVmRK0X/o08OJ/BS58Re663W2g9VJwi/BKGNoNZzP2y88odQmUIpLeZdQonUBW3wuJow6U7rvvPqxevRobNmzAi1/8Yjz4oKQut23bhl27duH6642zSKVSwZVXXombb86uq6jX65icnLT+LYUnhtmISdw0QCXLzCEITe+EVh34t18CPvlKYHKnAUA+6Z3FROUwO5pRcpbB+2nkAiUH5Ky5CLjkdfLvWz6QPR8P/ZJmiQ6XLpwo4QKjYxUojatkhRKyXIAyLj+rQ8BpT5d/3/+1fLfCdhP42ycAf74FuPUf/ckXT3472TYDUt5DUaSWSV+37DrX0rsO4NyVy+YBycMRCwFKPNHXUrR9KflWGApcG/wII2Iard6VwMZr0svqWw5skXUL+MHfp7dHyZNQ8RRY80TcAaRiSvaW2Z0Mp80PAIxDJVfuddBJenfmDfLzwW8Zl1G+HB+j5F7zdE+MbEgvX/cocmRtGYxSKKCvuypjlKwcyydHpsirU2p6nqV8GzsxSr71kfS1NdcdC76PMXgk4f7553PNUkYaklU8EKr3YZF765YPANv/Vw6SfO/9nafPYZRiVn82iJlMM4dJVaM0XPPUBwP2AIyKAeHsdyeg5IvTnw285jvANb+nv+L3yjzUe5/O5zbFKG2wgVKK4XTiFAWUtu2bxnxLKgby+ijJ7cjfdNrOUhhgIwNKUZBuvDrkHNdMZqU2It87vjptT1h9lNgyLTOHyN6erHUvSo0SMUo9WTVKRx0qHNU4qnt/ySWX4KMf/Si+9KUv4YMf/CB27dqFyy67DPv378euXXJUb8UKW/O7YsUK/Zsv3vWud2FwcFD/W7MmR3/7eI4LXg688n+AsTPNd0GU3zCNQE99Uo2CJsDEo+x3z0MiMCMUuRbGus7JGRljvT5y65T0yDxLOLe+Ui5vx62dHdP4MnjSqs0cTmBGqZPRxtEKSgpPUv0s8vo+ab3/kJRB1EZlsub27HHnmdkjgf7nf9Mv1SOgVOk3iWxWkjezH7iZAaUijFLLkxjmWFen1gcYm+ijDZQ6Se9aDaPhX3Yqq4dMUsl9KAReGH5TLva0F8qBGl+cd6P8vPUfgf+7Cdj+PfMbl965UeoBhHr9OYyImJRJ8s4M6d3BRCVXfP/bbLApCyiNbgRWniNloT9nrFIeo+RK7/Ik0j7r7SRx7MFdMwfFKLEaJVt6l9cAlizCPVL4Tn2UmjN+SXRejVJUMSwkOScWCQLnIxvt99H272bOMliXYPmBMt1bBQYBuKTyRx/tPH1OH6UoLOGAus5GxaTV0wYHtgFTMgcidnM4i1EKI7s5rIrvtM/C3fFaxL1jmp3sKoQAVp1jSeX5daOBUmtOPscPPCDvt3WXWosJPAMRPNYM96AUCsw3Yzy0T14bnVzvOpk5WIzS8j7r+xRQ6nGA0iIBBs74cMmiVaMUBhZjls0oHbrrXUm73mUApSXp3dGLpz3taXje856Hs88+G09+8pPxhS9IqcxHPvIRPY1LISZJkksrvu1tb8PExIT+98gjXTxQH08RhPKhtfo8811tNL8KkB6KXCrD//bZgwthGIG8hDzLHhwwwKUQo8RezH1jcuQLAO79Uva8FL4aA6dh3wkRKUbpGGXLKBkiuUcS+129AJtREkImRQBw8KHs5bvg19d7yyu9yxjNfuQW22lt18+y103hA/hFzRyIUaJEx61ZOtyRYpQ6AKUDD0qQUO6XblphlFl3Erbn8MRA1qvOnv7C7GVuvh447ZlymXELuP2T5rc86Z0Q2ezGlKlR4okK5SMaKPHrgNc6ZdUoAcCZvyA/7/68/Ixjs34vo8TWEccGOPlMd8gAgt8j/N6OqpnSO97vxl+jlMMo+ZrOZvVR4g5veQ59WWCT2A8+QJcXrbp5Brzi88BbH5SDhIBknDNiqC6vgQcrBYFSq26D/QPb8mtqgVzpXRQK7E3k98vFuElaH/sJ8NfnaQe5KXQASoAXdP5PfDGe2/hDTL32R9nHusuILEaJ2ZLf+Rn599rLUg5/kUfaav0eBrptwo5x+awse5qw2vdpflJP6yyHjvQuECnQ4UoaF0uCxreR35PUyysQct8jS3qXUaPk2d9uN7OkXe+WpHe+OKb4tN7eXpx99tm47777tPudyx7t2bMnxTLxqFQqGBgYsP4tRU6wXhyZRg4UxPZMZQAlX40S/z4LKLVbptGrbxlFpEi+ongAWHGG/CzyYqUXPk90tOveiQSU3BqlYxQojW+Xn6ObTEKdJb/jjBJgpEkHs12uUteTDwDVPdK7LDMHSpSoa/3uO/OTpbht7gmv02LBGqXlp5vpD1MzTm9Qgk/b3qnp7M8VOFhxphmQyQAr0Z47EIkYu5MhxKMbs5cZRsCLPwY870Py//d/xUgoydQgiyX3SSnjWMqJkZbeUSKnaxjmPEApKPlNbShIerTzJ/Jzftw8+zoxSvUJM62vlpT2kzM8Vm84V3rnZ5RCCyh56jYp8lo3ZPVRCkKTLHfo+eSNboESgfPKANC/Sq5707XytwcygNLcQVTbcp8eqhRka2l7QlW71a533sYc6V0UCOxRQGkMDCj95GPWdFOJPE5DvTmSLz4Is/l6fDK+Gv/ZvgJ1lFGueADwAsOS3iWMUSLn0rN+IXeerFx843IbyPF6LQISg4z56ZTUrxiQx2PlYNWS3s3WWylGqb8aZcrkDiX4ajhTVFVAibaD10hmut55vu+2RumJm5djsKeEyzeZHJAD0k4s3YkexxRQqtfruPvuu7Fq1Sps2LABK1euxFe+8hX9e6PRwLe+9S1cdtllR3ErT7AY5UCpQ58aqkHidrwElESYLY8J1ShFnCG94y56PqAUFWGUMiQbA+rFOlkEKKmXO3d0OtFd7wB/E+FjIUh6N7SWJbUZQIkzSgAwvF5+HnxINiHmzlcULhDxASDNKPV3ZpQIKK0+XyaIzVn/ein4eeByz25d74bXmXvkSMrvCNzQYEseo9SYMX1ULvoV8z0liQ67EOz6KQDg9nhDsZf0+ivks2P8YXPM86R3gGFl+DU1ux+Im4ghsAfDVuJUiFGq5LBJADB2OgAhGYrpPcADX5ffD6+3ARbJsfg66O9yv59599UM0XaFZSAspRklX40SzwpaOcBFM0o+oJTjXpdXp+SrE+VBVtadpHf77pfSPjIPWbbZgPMNV8r31b57/WBG9d/bmwxgf0k2XMXM3nwDCdqe4XXSdROQcrO8yLEHj8IAezAEABgT42Z035FATqr+WYUZpYtejT+JXq8bJ3t7Ly0wZIsX+fc8GHDb+RN5UZ3+nNQ8WaYGPNY6ToI8gS97JGOd7MH/5qXn4z9edxk2Lu+z5tu2fzYFOipRgFrZsCyLJb3j+8oXSdI7Ot+lAmCFvueHr1vp3UsvWYuf/N512MqaLldK+RLHx1Mc1b1/y1vegm9961vYtm0bvv/97+P5z38+Jicn8fKXvxxCCLzpTW/CO9/5Tnz605/GHXfcgVe84hWo1Wp46UtfejQ3+8QKstgFsnsoUVAN0pQHKPle3Hq+DoySJQ/xSe/Ug7JIjZL7Qu9mBJKzB3p7Hg+ud8dqjZJKPgbXGLYzCwhovf+Q/BxWjNK27wB/9yTgby5Iz+PKKV0AlCR+M4e5A/6kiRLznmHZewTIl9/xa8pyvSto5jDD6lXo+BxJ+Z0GSkr6l1WjNHtANvuc3S8BAZkaAMwFzU6aA8W43JFsSFsj+6LSB6xV9Q/3K9exPOkd4AdKSnY3Ew1j48phrBs1SVqgGSWqUWLXC4HkrASfotxrEunddwA/+3f599kvcLbNUw+n65MyBrTKHimcIyeO3BH8jjVKC2CU2i0/U0qheymNp39bDEbp3i8B77sQ+Ozrgd13ye/oGgXkM4LkqvQ7D8VkP5qMYSYakt+162nbdWseeladLGvRgA6DJA3Duvmkd4ErvVP3gLPfVKM0kgeUOLgaWIWaSoCFWHymgNhIXaNEsf6J0nzF3bQCQGnloH0t8ASe5u9njFLYASSM9Vdx4bo0OH1o34y2yaYoR4GWwwGLxyjZ9uBmnQSUiEGMCrje0f7y+qaFnFYhBIJAaPC8xCiZOKpA6dFHH8VLXvISnHrqqbjhhhtQLpdxyy23YN066cj21re+FW9605vw+te/Hlu3bsWOHTvw5S9/Gf392faNS9FljGwwBa5ZjncUBGK43I6Ksz0Pex26RinDHlwDKGEX21J0U6PkuvzoF2sBS1lfc0XtencCM0rH4r7Vp0wiOrTGn9TycEdniVHio7puQteJUWrNm95MvEYpbvkL2ClZrg4CK8+Wf+/8qX97AXPNhhV7WJGSxDwzhyQxoKh31Ny7C2WU5sZlP6IsswzvPCqJX32+/JzckZZTNeeA918C3PZh+f8nvsUwzEB2X53HfgIA2HL+kzDSm5ME8tj0ZPmpgVIH6Z2vV9GEbDLav3wt/udNT7JAmjFzUO8fDqy3fUt+jp3eeTtXKhD94DfNtp7zIv+2WYwSAaWMAS0ChPzadJ5poZv8UB8lVqNUWHpH63NrlHidnhcoDclPH6OUVxMFFANKt6ka59s/aRxP1zoNRIkFdXtaAZpRejRZhlZYNe+DvHuLtmdwTTGgxEGiU7cD2EBpjNcoOUwa9VFy3dms4BRh/2pL3tWtRKtTEJvTgvMev+yN3ultaat/masHbRbNqlGK0tK7bpP6l10q883fuHaztsnWyw8D9FYi9v/FqlFif3v6KGnpHTdz6OB6ZwGlQwA2dHxtiePjGyh5stIjF5/4xCdyfxdC4KabbsJNN910ZDbo8RhhSY6+77+vOKPEgdJeJW3wjBal5ssCSsRwRBX/07JUgNXJeqEPrAYg5IjgzL787fQBpehEBErkztUvk5xjUXpHI7TVQfmvE1BypXc+++SZvbY0qlONklWg3yulpVFVXgtzB9KSLm1HPWCsr5XVtDd0XZ3jKEasRJ70rjFj5q8tO3Sg9D+/A/z0X4EXfhQ4Iy2R8QYluqObpDxy/GEJDKlfECDP48weCQZ/4QM2mwT4++o0ZnTvm6df/7Ti+7BGJcPUU4mAUqb0zgNGdt9h9skJejQZ1zs2H/VGKtJwcsVZwF2fBb77V/L/qy+wa0X5ts35gFIHRokPCGhWzccoCT2wxBklrz24x2baADO38a66bkXgVwjk9VLK6ttE0QkozU/KOjWK+oQ8l+SOSEFKCpLm8VCM0iPJmDxGvcvku2FmrwFBbhCAGWLs9/77/dMCZt8rg17JehQGGUDJ3u+mSuGG8wYTOCirjeiEunQYWAIOsh9Z8yysaT0MPOMvgZMv9E5fjFFygBK3B1fzDzATgm5Bwu8/60z8yhUbsG60F3un7HdhObQZpU49mopGaDFK5u9qjvQuq/aKQExPOQTUK+tQ8G85CjDTaKMShQgEECeyp9PjOR7fwsOlkDGmClapc3xW0CjfOBvVonolsm31BQGlrIazBKB8fZiAYvK3rBqlsGT2q5Ou3dcH5UR2vaME8liU3unEQxkj9BZllIbkZ9+KdHLnOlfRcehfrZbhjHATcC7VTDKTV6eka2IG83vMUGSNnhcZGCA2KaoqWSABpb2yb8zn3gTsuC17fjd2SYe5Qr2fKLi9MbFKj/3ImUYdp4FVwFnPS7/BffUqu26XpgX9qzo/k3gQizi5Q17T8x0YJR9QojYCJ29NTZ6S3s2qbR5/2NRhnPr0zttJskwKX5NKfp0RE96RUfLUDLmMUgooKUaJ1Sh1L71zGSW6rnv9GVtujVKOPThgapSmd/lNaO75b6lQ6F9lmJTr/zjduoJqc/d5wMxBAkrLFVBSg2t5zndUTzm41oDsvBqlHCMHQJk5qBql5RiXQKjVMLL34fWYD2q4K5ZsSG6NEj/OQhig5PZmWoTg19dDT/pL4DXfzgRJgGMPnrE5q1zpHdtu6vsz1m/AVNxNM2K1zeSs5zJGJVd6t0jgkjN5/H6rpRiltHGFG4FHeidwCIySOr7lKMBvXX8qXnfVRgzmMZaPgziqjNJSHCNxzf8nnbPOel7+dAMqofQ5idEIui86ut4Ro5TVXbxA4pjlegfIUcipnXI0jnry+IKSWs46aNe7E7BGqTqokspjEARqIwfVGLlbRkkImTjvvdtM4yY6lNANnixrU+qTMhmh69BXs1YbkdP6jB+49C6jR4+9/oweNUVc73h9Eo16A9Jh6jvvkSPp274N/Nqt2RkIRZIYC2UCTJ2i3TQAo2dYsiJ3fRbY4QAlPU0GC+KrV6H+UyRfLBp9YxIct+Yk0O7oeudcU0kie64BwEk+oCQ/tfSuPgH849PMPGsvzWesKVaw3nXD69NsB2BAXNyU11ClvwvpncfMoZxOBMMA+lqrWjVK6g+nB1MqMurLOrJCWTVKcczMIzJqvWqjhtWd3GHqvSju+qz8vPAVUgY5e8A0JeZBDF4HRmk4YECJ1+a6QUzP0BpTH3lwu7xPfP0F3ZpKJ6LQuN4tF+NYMVBRhkSJvMbf8EP84Sd/gImfymdOZsNZIPXedeVdixkcR+SCNxVFGKXl/RWEgUA7lgCIA6VfunQdqqUQzzlvNf7xuzIvabe7A0rW9jjHRDJKzMzhMEjv+DHQZg4h1Sj5mSce9D0HdIeC5wgohULgDVenmfXHYywxSkshC1uvebtXK20Fjeb5Ii9BoLqjrIazefIO4NDMHADT0X1yR/b8QAfp3TEoT1toEDCiBPJYbDhLxgB9CoAXrlEaMt8Rw+Auk4Kumf6VAI3A8aTP11dLu5F5RsN5Yu6rF3EjiwUtF5De8fokwAClXT8zEsADD8gR9k4xu99c+7tu71zL15wDPv4iOU+5Tx4/GoBwe1Hl9f0B/Mk2SXtJZlU0hJCuY4AEfnTsi7reHXxI/h2UvCCNErkJsCT+4ZvN/eMaMmTF0FozeHTN/2fXbFGUaoZhJ7BJn5nSO0/NkCO949KhIKtGibKsdgOAuhZceSiQfU92YoWyapT48z1rXiHy5XdUM7v2Uikh3fpKP6vFnRq5BLDdkj2QADyUrEQoYBiib/+5ZpusiGPzbhk8Wd4PpV5Z3+ibHsjtoQTIwn2S3g2IOazsYc3dB08GojL2t8w5GewpPuLvJuOLGZxRyq2b0tOnXSV9y+R1irxucKy/ijdcvQmrGevUihcOlFxGqRwF6K1wRmmRpHfcpp/9TfVQBGbLBaR3dAyrlpnDwpFSf6VkbcNSLAGlpegmcoFSnvSuA6Okk9wMoHYoZg5Acee7PKB0orjexW0jgdTSu2MQBOr6kiH52S2jBKTrCVKMElkY97HkjVs+e66HPJtyziiVPTIoN7JY0ELSO8YoAWbUG5AA8dJfk3/f/DfZy6DgTXnnxzvfJ9//O9mDplQDnv9hmYSvOg+AkEwO76fUqa7GlzQTUMp7pmQFt4XX0rsM8x/XzIGkiivP9gIDksu0EaJZYuArqgKv+IJpZNophABe9l/ADR/MZvGFSNcpzXYAnV57cLqG5THIqlGqWjVKahqrB5OHHcrqK6Z7KGWwQj0Z9xC/3rPMHID85zndgxlMjY5Kv5TnAXYt0fh2aQ8fVnHKxlPxgq1rgCe+WSoupncBn3ldelnTu+S7TYRSxisEMHpKetk8aKAjh1GaQg/mVD+i879+I/CpX5Y/qv2fmm+x6YuncoZROgw1Suz6KsIo8c3OM5YYZUCp7JEMcglfqxtDGidSrncOo7R4Zg5+oHT5plHccP5JeN2V8t0VFTBzoHuaA5tDqVF6xzNOx5uevBnnrRla+EJOsFgCSktRPIZygFJvDqPUCSj5klweReyS8xilor03fDVKJ5rrHQdFlWMYKHHQAeTXBiWJn1G67NeBS14HnKvaCWQBpVKPf/kNn/ROJale6R0zD9BJax6jlAHu6XrPc70j0wbaHn7vXPk7ct+DCHjkluxRbQoOlABjaOCLJAF+/M/y76e+C9hyvVr/gBml505/RaV3fFTfZRO7CQJK49u7l9498gP56alPAuwR71ZlyPzn7OfLPk7djDavuxQ454X5GY17TdJ2Zh1LX82QIye2RrIzapR00PUZRH75mD5+LlDK6aEEyHo1QDf2NfOp6z2q5h/LIkAp65zz8MnvFLAJRjfio6+6VDbg7BkGXqBcGx+9Ne0MSdfNsi2GHRxRgzRZdUo0z9iZ3p9l8iuwN5HPv+qen5rnl3oPc6CUG1f+jvx89vsAGEapG3BVNAgAuCYIWWEzStn3AgddPqDEo71wnIQgENZ9Xo4C9FpmDotVo2T+5suslSO850Xn4clnyEEizmBl2oN7pHeH4mZ42aZleNOTtzzuLcF5LAGlpSgeeVKYXEapQ8PZDnrt7hrOel7Og0p6N9FBeuerUdJGEicKUGL7QYzSseh65wKlPClbY9rYeHPA0L8SeNqfAqvOlf93pXe8maZvdNzXRDQLsCWJn1HKNXPIAPd6YCAHKLkj5yvPlgnt4BqZgPevNKYBrsGCG27NYV6d0sO3yGSy1JtmQwikqF5EAJj0rhNQWiRGiWra9t2fNi1xg7ZpfgL48juAH/y9/D+55znBE7lWZdj84JozLFa4vZQWZOZgD/5YjFIgWB+lHKCUxe74zDAAJr3LAkoZUuhO81FkDXy1m+ae6SQjB4yhwx7WS4kYoGWb0tMGkXxW8usbMNbw3O2R5Ho+RimOgYe+k56HBYGYPRhO/6jqgafrBYHSVb8DvPlu4IJfAmAkWoejRomS66FaqVCynurrlREjfQYodUrg24fAKAE2gCyFAXosRmlxjlkWo+RGOeo8HX3PpXdLsbixBJSWonjkSu8OwcyhI6NUwFAhy2oZ6KJGyVOTcqIySiJktV/HEVDySdkokQwrfkaR6ue6ZpQ8DGOW3Kg1bySNvEapOZPdm0gDtQwzh7iZbanvsiXD64Bf+yHwuu8ahz6qG3INFtwgRomOwT1fNLUebvz4X+Tnmb+QlrR5e/90AErcAY1qozSjdAjSu90M7JUzpHfVIejatJv/BkACnP+Lct88wQd0LUZphZ8VOORwgUhHoKSuBUt6pwYWvK530NdeJGJEcBJvzXh6nqmAOd/NGXsQS0vvsoCSMgWaH7ct+Dv1UKLIYpSI0QWKMUrrLpOfd/ynqZ/dp/oqEYiiCCPjwHnAGVh48JvycwMHSjm9lPbcJc9lqVeaoHiCbK+H4RkYWi5daqfmM54NbghhjjkM81A+DNI7AgBFZHeAx4UxI0aL9lLDodUoAbZtuttwdrFYlhSzmxGcRcoCaVp6x4BSfIjHYCnsWAJKS1E8qoN20sGbw+YBpU4NZ32yKR5d9VHyaelJLuUpwKdIklRSAeDE66NE+xFVTY+T4wkotebT15HlNud56WTZ+3IzBR8AqnuuhyxGibZBBHJ6Pk9WnZJ2vctglPg2uuEeH0A6gPH/UxLmGiy4QdK8s5+vpv8R8HdXmu+5ucPDN8vPs5x+SID/GGq2uAOjFCs2IEkYo7QQ6Z1ilMg1sdTrN0sA5Pf8eG15GvCc93v72gC2nCUJWeJ2uBglXkMVt82xzAJKvC6OzplmyalGybzypfTOgKAUq5QnZwbU/aaOFb8fOknv+Htk8jE5kPA/vwvc8rf581FkAqVxNX9/9jnncfqzZI3f5A7g3i/K74gB8vTRMm52DCiNPyIHFUQIrL/cfK8ZJQ9Q2vZt+bnu0kynV0qk70/UIF9tFHjtd4Gr36H7nNVbC2NOeg4jo0R1NEWMHAAbJOQRUIWbTuPQQQK3TS+HwnLZc2uYFhqW9C4HsJbcBtGeCDzSu3aXFulLkR9LQGkpiocQpk4piEwxbFjOZoMAo2/PSsiLMkqFzBw8o5+UjLXms5fRmpe9W4CMPkoniJkDb+5L+3Y8SO848HDld04ymAqyrk+53jGg4qu38DGMejqnsSs3DggCec12sgjPSkSjipk367rj9VBZoZ3ofpLNagGGUTr7BcAvfRpYdqpkrH76r8DfPUn+q0/LZZB81ZdIehmlTk1Se82Ay9xB+Swg5jmv5UBWkPSOIu/4ADbo2PCk3El5nlKZY023s/btUIMzSnPj0A50WevTEtHEXLt5fZQCGyhxQwcAnRken+EEYNadxwwRwzG5QwLzW94P3P5JNV8GMKPQ0rtHbRCvnxkF2CRA3mcXvEz+/YMPyk8tvducnp6aWB/YJo0/6lNGdnfSBc6ghWKUJh9N38MElHKuN5J//VHrl/CNgecCr/kOsPIs4Mrf1uDqb2+8AH2VCH/14vMK7KyJw2kPHnbLKDGQkMcobRrry/zNjUNllPhgQjkKLKC0ePbgxRilUgF78JJuOGsGB9pLjNKixhJQWorugkbzeoYNAOldnj8cRE0jXW03RSdGqVPD2XbTyJ58L9lKvxn59HWDB2y5imXmwGRQcds/7/EUnFGiUfEiDWfHHwZ+9M/ZrCCP6b3Al94O3P35zlbTWcGbtwIyOaCkLgWUyAI5AygRMzE/bu+rJb1T13In6R3ZcFMfI70NzvYK4e9rw6OVAZSEYIYOM/BGJ6MCQAKeqEcypfvvy9iGhhmZH14PbLwGeIJy9vrOe6Qxw66fAd/4EwkO23UAtpRHR81Tb9TJzEEIu06JwGx10C+j7RSVPuMECGRfExQ8qd7wxNxJeXITZ7UyWMzgjBIBkcqg31gBkNcMAWy6J9waJTcxFULbkKcYpTw5M4XPjVL3UcpwvQMYUHos3Ri5k/SOpNTNWfta87GsnYKa/W77luyTNKUMJnwDAdSz6bt/BXzwGuCLvwNsVwzreufaqY2Ygb93nyL7bU3ulM+NB74uvz/l6szNoqT40WQ5vrz+LabOlsUTNy/Hz37/ejznvPRveVHVZg6HQXpHksHeYoxSkT5KAPD0s1bhlZevx1++6NyOyzxUkMDBSSkMUI4WX3pXtEbJbjjrn+45552Ei9eP4Olnm+bcyRKjtKixBJSWorug0byeYQNsOklkuGWvLzr0lDA1Shnyt062sm4y5gsaeS3VbOkNydPy1u/GsfyQshglkt4V2K8vvR34r18Dfv6F/Oma88AnXgJ8733Av90IfOz53R+POE4DDyDbcluDhpxaFC0RYkwQHzH3joyT9M4DlGb3OaPZ42ob+PZ6+trwyJM26XqTyfRvQDFGKYyMkUVWndLBhwAkUqJGEsXTngFA2EzjLR8Afv55+Xf/Sn+y7jJKSdK5jxJgO98dipEDxSlXmb871aqMM0OADAcyCp7cPHbpH0jJ3Ys+toANLBicUfrJx+XfeYY6QqTvEceghiemOgdTQKgqumSUgAwmtkMfJcCuG+0WKJWqhm3khg4LAUrD64A+lWDe/Tn52bvcP2hH0jsyjrn/q+a+Ovkie1ohDNhqzkrJ6j8+RQ44tOvSTj+noTJPivPqc4IFJO6nrpTPpc1jHQYRFhBdM0qCA6Xs6YJA4PefdSZ+4fzOvdUOmVFix74cBSngtBjBF5MHlOyGs/51P+GUUfz7ay/FaSvNs+5QnP+WIh1LQGkpugvNKI0wRqkDUCI5TJZNMSWZHWuUMuo1dKIvbGDDI6vJIYVPZgXY9SNFnO/23A382Trgq3/QedqjEb4apSINZ0mSQrUfWfHVm4BHfyhBgghkMtFpHjfqk9AyI57oZjnfNTpI74LAgAAuv+Mj5nlmDny5xFa0G/Z2+ICLr68Nj7zeX52APTWVrXRICledIz/33u3/nZimZZsNK9w3Jht2AvI6OeUqAIkES0B2su6CzfqUcbrMk6dxQ4dDMXKguOhX2H86JE0cGHeoP+AD3o3RM6RxxunP7H77igZdkw98Dfjue+XfV78tfx73HtFgP12jpIFflvNdpxolgDGxHkYpq48SYBgSL6NUgK3z1Sn5BleKBJlxkO392On+6Uh6RzG9y9xXq89PT89l4L1j0rL+1n+Q/7/oVbkqDH6eRvuK1+cUiYvWj+D7v3st3vGMjP08hNCM0gLMHA7F0prHIdcoOa53FauR6yEtWgff1yxJHeA0nO2CAVyqUVrcWAJKS9FdUN3D8lNNgtORUaIC6wygpBmlYf/vGihlMUpsBDPrYVuUUXLlIkHAJGoF6pR+/C9yZPN/3wM89N3O0x/p4IxS2IWZAzkGurU5btzz3/LzOX9jAHInt0E3aGQ4qtqynyzg0Ul6BzDnuwxGiZiiiUcMU+ST3pVrZsSbHwvfaHanprN50qZOwL4IowSwkfud/t+ph8yyLfb3575Yfp7/S8CpT7enzQJKLtgkEBL1FEu258cPzciBgkAekE7C3Xj2+yTb+IKPdFwsZ5QWqaY7Pzi4TGJZQ3b6s/Ln6cAoeV3GsnopdXK9A/xGOVp6V6BGafddaQvtPMkehQ8oddNDiQcBJer/teYJ/ulIGeFG/yrTG4oHgei1lwKv/V9j+lEdym40rIKfp26MDIrGioHqgtioTkF5fVEzB1sKujjbcP7aoUOav+TUKHGwslhgzn6W5DFKvI9SF0DpEC3Sl8KOAtYwS7EULDZcCbz+FqnX/qEaHetkj0sJ8+x+mdS6CW0nRinqwCh1M/LZCShV+tK/RT2SQSgCKLjD2Od+Qx6rIg5MRyq8rncdmLL6tElC3NocHtyxbPX5Mpk5uK1z/yo3siQ0WXI0nzudG8R6TjHAwK+bVefJ+Sd3yLqD9ZebJNNN3GrLgImH5bGgugVfzVBHRilH2uRrxEqRJMVHzykh5fs9Ny73NYyMHbILlC54mSweX3kO8PD3nGVm1ERwRilJOhs5UBAo2vNzc68cCqMkBPDMvwQ+/5vAtb+XP+35N0q3vywmmgXPU45IM0Ze11UZBJ76p53nca+5nBolvQ/q+VoVDZuA69RHCWDyQPZc6EZ698gt6d8KMUqeXkoLkd4BadfCjD5amdvlY5MAYOsvy3ffxqvlvK/4AvDNP5UmDp2c/fjmDSygVu8oxUBVAqTVQ8Vq+Io2nC0SX/+tK/Gte/fipZesPaTl8HukEgYdSemFBH985AEg/ls3DYKXvBwWN5YYpaXoLoSQ0oSoAlzyGunGc/Gv5s9THTAvfVd+124akHKoNUp5BdYdpUy2O5QVlER1cr5r1WXndor993Ue0T7S4atR6iS9m2QmHLM5QKk+ac5R75hJhsYfAj7zBuD7f1dsG7NAQGaNUgfpHcAcq5hdL3e9q/QZy2uS4GiW0Vlur8f5LpdRyqpRYqDVDS5Hc6MxbRwaO42ekzMlncOdPwX+70bZYBVgjJLj8iUEcNKFshZp7Az7t6x+anSPxy0JXmc7WINTnPo0+XnHpwzzRVLJhcbWXwbedAdw+Zs6T1sAJAHFnaoWLTjAfNJbDOuZF/weabcMC66u4ZTrHdCZUcoDLr4aJd1HqYCZg94YxkDkzUdBKoXdrFnsgoESH+gTwMlbs6c970Z5v172RvNdRi8kRBXgtKeb49czJBtgn/b0Qpv16iduwNPOWomL1x8mV8XDEDc9+0z88XPPwqWn5NQksrBrlA7tnjpleR9eefkGVJj5wkLCajgbBbh04yhWD1bxxM0F7r+CUbzh7MIYpaU+SosbS0BpKRYeQShrIDL6jlhBLzbX0IFebkD2C66TPXg3jBKxV25k1SgBxZvO7viRLNTtXQ6cpmQX7mj80Q7L9a6g9I5L5/Kkd1RfUhmQI6ZUh3DLB4Cf/AvwxbcW28YsCU1WjVInMwfANJAkBgWwJZsAcL6yCr7zMzJh90nvAFOnxGV83hqlBbreAYZd9V2vtK4g6jz6zhmlJAHu/bIEMvf8t/x/lvSOR+8yG7hkSe/KNQP6uFNbJ0Zp03USTE3vBu7+L/ndoTBKFENrij2bCoYoKJdZtOgZBs68AdjyVOCS1xabR19zk/aAgsfMQf+prqGUPXje9Unhdb3r0EcJSAOlC19u/i7CKK2/Qn5uv9kMOCwUKC3bYizqx07PVjYAwLP+Gvite4AL2PaelMEoHWK8/Rln4AO/eOGRudYWKbas6McvPmFd4W22apSOkWzUajgbBqiWQnz7rVfjo7988aKto7g9+EKld0tAaTHjGLk0l+KED9J3u3VKJC3KaxLYCSjpF3qORCFvhB7IrlECOtuTU1AzzrWXmjqJhz3SkqMZGihVTLPDjkCJMUozeUDJqS8hRoknUUUs1jOldxnAo0iN0jIfUHKum5O3ShlOaw744NVmf9xrgjvf5W1zpxqlPICfx4BymV+nUVhilJqzcht33y7/P75dNsqcn5AZCkkIs4IXuOc5r/E6pdmCQCkqGzaPrk+f/fhRDkt6dyQYJSGAF3wYeOm/ZTYmTUWZSe8I6AclzRrxxDQsWqOUOwDlc4ss4JZXHZKyNBHIJr9PeL35rQhQGjtDXtutOelWd+uHpb03ULyPEkVUllb6ALCmQzIcRhJIjW4Elp8mB01OymGgliI3Unb1x0C4Zg6AZJkWqz4JsGsc8xrODtdKuOH8k/BLT1jXlfRuycxhceMYKp5YihM6spzvOtUnAWaUOm5KOYkLqIpo6Q+pRqkg80KgaN1lwMnqhfvILdLu+ohUfxcILb2rFm84a0nvDmRPR4kK2e36JFrzE50T50ygREmgU6PUyfUOMEDpwIPyGgpCBrDVdSME8MKPAp94KbD35+n1UtAoOgeNdF3xbe5Yo5QjvdNmDuPp34oaOQByVL86KI/p1E5g1x3mt7s+Kz+H1nXuWTR2pmmUmSW9A+S5nXpMJs4zimHsJL0DpGnErR+WifPFv2oYg2MogkWUCR22oHugMe0d/LFc75wapcoh2YPzGiXWaiErhABe9TV5Dw6ttZ+tRdoVCCF7fv3kY8B/vsr+rVtGCQA2XQvsuRM4rYNZBl//r3xZPkvy3l1LkRv2PXUUN4SFaw9+OKIooySEwHtedF7Xy1/CSYsbS0BpKY5MZEnvOvVQAuwXbmsOCJ2EeDHMHPJqlHSNVAdGaY9KrledJyWJpZpc3757gbHT8uc9UsEZpaINZye5Be+EnN43wq2tnRWj5GmSiNkDhwCUFDBI1SgVYJQGTpYJYWtOsimDJ5s6H37djG4EXvVV4DOvNzIw99rUjBJLDokpHWKFxB1rlBZo5lCk2SyP/tXymO6/XwJFijs/LT/zZHcUxChF1fzzp+2iD5p6vSy7ZR6rz5POYNVB/3VzDARP5I6VcY9UcHDuqd3Lc707a6yCzeez5xQB+VzpncdWf2av/OzkXNjH5Jy8TiyPteZBQMmNhQCla/4/4OJX2/dvp1jIepbCiqINZ49kcEapvEh9k9woWqO00FiS3i1uHKuP+6U40YKa9e2529+oM5dRqgBQDxOf/G0xzBzyapRoxD+vj1JzzjgwLdssi+CpKJgkecdCWIxSQdc7zigB2YYObrNQnzvaXA4jRaEZkwwzh1SNUg7IpQgC0wBy3322g6J73VT6JbP07L8BnvneNDBwa5TithkA4BK2rJoqijx7cAJn3hqlLmsxyLr4/q/BsnDa9TP5WQTInHSh/Fx+Wr7cj47VzB7ZTwuQDGuRWHHGMQuSALtG6Yi43i0kODjXPZTMfVGyXO/oS3n9v/ycGn71SRvNsugeybMH718l63sa07JfWn3KDGQstM6sqDX8xmtsEwiKhQCYqNwdSFqKRQm7j9JR3BAWHLwdPkbJ/H1YgNISpbSosQSUluLIxJqLZUI68TCw63bzvU+y5IYQ+XVKi2kP7q1RKmDmcGAbgETa+JIchdyQ9mQ0+zwaYdUokfSuC9c7INvQgYBSv0qQqoNp8JIn3aNYcI1SB4ZlmQJK++8zoFeEEtS6IYS0yN76yvRvbo3SxKPyGIZlGxyWO0nvFthwttvGmv2q3ue+r8hPt2r6nBd2XsbKs4CXfVYCyLwgmd2D35SJdnUIWL74jS2PRhxx17uFBAfnumGyuQe9jNL6J8rPH37IDFIAxSTN5Zpk0AFg+/eM/LYy4Jcx58XL/gu48BXApb9WbPraCHDjvwPP/X/2952aMC/FMRPHZI0SA0elLpq8dhN8X7sxaSgaS653ixtLQGkpjkyUe6UOHDCSJqAYowQwVscDlIq4M+XVfAAMKOVI77KK8gFjOz260QyN9atanSJSkiPVII4zSmFRMwflekejt0UZJSHSrFIhRmlcfro1OJUsRmnS/j0rSGK2715b9tbtC1ozSuo4kJxteL3tsvb/t3fv0VGV997Av3uSmYTcJgkJuZBAuCrITS4qVA3lZkUUDmct0FLvtUXBkletb63nLGitgJxTXrB4qb1JsX2x66is1lMVVAgiLzUEOESggHIJl4QYICHcEpI87x/PPHvv2bPnBsnMJPl+1sqayd57MjvJk8n+ze/3/B51Pm3dzCHchTVVRkmVUPb9trGv8Obg66ApfccbJbT+qIzSwfXyttfYGK5TC4936V1sXNT5cNmU3vmbo6TG/fD7ZLb14mng/60yvlZzCKV3gJExPPq5sV6Xeu0LR99i4O6V4TVj6DcBGHGf0bQEYElcB9KW7cHbijMiGaX27aA5ugO1lO8IOsd/MOoYBt0jb/f9zdgWyhwlwHhX026eUDgZpcZzcgKulX7xaTPPRXXsM3dMs1Kry6vyLsBoqaxq9v3Z8n+AZX2A8jcDH9cW7BacbWn0P/uz6aJxsa5KtPwFftY5SoBvKVWgdZgUPaOU7r1dn6huCpSECK2ZA2C0CD+w3lgYOFgTAzvWdZRUoJTZz/u4QBml1hbfZhJmKrC/ctE3kA2nmQPgfREJyAVWlVCySeGwNm7oPbZtv34UOWJwPoUPvfTxG9vSO6+ud+p+XDwwwbOuVvmbxmuBtX2+P3qgtBVosLxZEinmktdwu95R1CS64qBpQEK8I4aaOZjmKLVXoGT6sm2ZUSr98XismD0CM2+M3RLmjojNHChyBt4hsxLf/BOo/UqWQoXaQtgZIKMUyj9080X35XrjYlep88wvspsjod5xr9nru0/RAyXTxbJddzSrEzuAT34uGwv8bYFslHBzkAV8r4XdgrOALB2zW3hTZYmcSXLR1urd/oMdveud6SJJzU1TrqX0zmUz56f5slwXCAgeKA28Q57P2cPAO4/KbaG0IrZSGaUrF4GPnjd+RtYW23aBnaL/HDQjiPd6rFvug5BvJqSafqbhNnMwt9rO6AMMniHLBWsPyG5zbcm6KGqvEOcndQDm2ChmS+/Umzpnj9g2c/A7eX7gd+Rco/On5FzL9F6hvQEFAL1uAaDJktbq/5HbrMF5e0vvLTNaQMgLCFP0pSU68dLMYejmimvT9tvXwlxu52ynbHh7ddDs3T0ZvbuHsGAzhYWBEkVOt3TZDe5EOfDNPhko6d3CgpT06HOULnpvP3MI+MazaGagZg5x8fLCsvGczJCYA6XWFjkRGTAuNMxUoHRqr3y31e6F7bQnqxBORkkI4G8/kkFSem/5s1j/b/J7/eTnwO0/bvugyW7BWUAGUHYXGOagRQUIdoFSyxVje4qp7OZbP5KBwOU6OQciWOnd2aPGmAhljpI5aHIG+QeRmAY89inw24lGFijQ/At/ElLlz66l0btUKdMSFAbKKKnW2UmZ9uuHORyett518sMcKIWbUTKvezTjVTmvpDjExX/DNWAK0H+SvMguGG00NOkEvMtlongigajXr8ZzRjmwKVByODRomnzp8ZpE7uwm1xCr2iW7FXoFSkH+RrplyNfIU1/KxZqBqyu9uxY5gyP7fNRmZo0JsNxAFKjyVGec1m4ltl5zlNppHhS1nVh9uafOSl201XvmvZwNMVDSF301NVQ4cxh4dRxw8CP5ebAyKn2ekmXex7mTco0mR7x9p7buA+S+xnr5Trwdu4ySCpQunrZfaPV8jWxsoTnkBXzvW+XF91/nywvpTYuNxRvbijmjpOYombdbmbMXgTJkF2oBCNkcwZwdzCgCJv67saBjoIzSpTrgD1NlcJbZD8gb7r3froucuu9KDe3qNSlTXswrgTp6+aNpwK3/y+gEp/jNKNkFSp7gOTlAhy9/85TCzSjlDAFufxaY8VroHeiuVlIm8L13gIf/Dkz+eey0smoD7d2pqk04uxnNOw545omZ37yBkVXy+RZUUHuiXN7qzUZC+BspvFneqs6fkc4ojXpYnsPtP47s81Kno9qDO9upNThgme/YiV4jOysGShRZaZ5A6dxxeXGuGgXYZXLMVEbJ3C75k595z1kK1B4aMMrvrFkN1do5vZf3ZHwl3mU0ArArv7t8zsgQZNqU3kHYT8pXGZhuGbJkafLPvPdfOgvsftvPN3OVzBklh8No0OBv0Vlz9sLa7c1MlZ8lZ9v/DFXw5K/rIAB89bEcF2kFwEPv+2a4VHOElkZj7Se9410YHbYKxhj3ryajBADffk4Gt/0nGdu6W+YoqUCppcm3tfx5FShZStXM/K2l5K99uj+aBkx4Hhjx3dCOJ1sdYsFZwMhsnveUwlqadaggz+fdcvV3oda/CjWjBPi+aRDpjFJCilwAVs21IrpKqvSuveYnAd5/e/Exm54mhb8hiiw1B6j+uCc7I+Q/4kAXjIBckBIA9r0vb49v9yyYqcl3ywd+B7juzsBfQ82dURf1igqUAgVrevndl777TnuaPCT38C6Hios3Jrfbld+pgE0dUzAauOmH8h3gMY/Jbdtea9tlts0ZJcDU+jyMjJJdVkgFT/5+j3YLU1qdOSxv+xZ7z6tRXKY5SCpLE2ojBzNzoHStF7y3PG7cTyvw3pfoNi4yrZlIFVgHWjPGXwa0MczSO2oTHSZQss4L7OFdlqbmXfjMs+rpyShV7ZKB/RVPe/FQ5vH5BEoRzigRtRFVCte+GSWb9cwoZnGOEkWWufTurOfCOKMo+AXriO8Bn6+UZXbnTsoAApCtbSc8H9pzq4tv67pAak5MoEBJXWycsskoqW12C3cmZ8uA6MI3ACz77RpZTF0mby/XA9t/B9TulyV6qW3URcqcUQJktqwJ/gMlc0YpUOldsO6FKhgMNEdJHw997PfHxcsSzOZLMpOUlGnKKIURKJkXlvxmf+iPs9NvIjD9FTl/yzrXSNPkmKrZK4PxLFMJ1LWU3oWy9hi1uQ5Regd4z5VL6+nTKCcuTpXeWb6H7v3k3+/lOtmZtLVZBvqhZIeyBsg3MlTjkkhnlIjaiMrwuCJUehfHjFLM42+IIksvvTsRWiZHyR4o12QRrTJI+qcns3TTY2E8twqUTnhvDyejZLd47Kk9nmOG+O5TGZZQMkpmiW4j6AilpXao9IySZ36Saujgr/TOnFEKVHoXbD0sc0bJX4ZMZZSsTRHMVIndB/9btmvX5yiFUXpnvkD0t3huOF/rxu8B133Hfr+ae1d3xHt7KKV36vdvLjdtaTa6C9rNp6N2490ePIonEoz578dmjSx9jpL1v7+mGfOUdqyWtz0G2ZfSWjnijKw/wECJOixVcpcQodI7ZpRiH39FFFkqo9RQZXSKC9bIQRn5gLzd+rLMjGQPAvJvDP259UCpynt7KIGS29OZp6HKd1+NCpRsOi/pgZLNBXmw1uhJAbIwrS1Gticc+mKunmyEKsFTc358jldd79JMXe/O+C6QqzJK/gIlFQy2NPp2LlSCZZQAo6nHgQ+AjxddXUYJAMbOl7c3fi+8x4XL3K7ZLJTSO7VQ7MldwIGPgD/fC5yqAESLbMQRKBtFbU61L3ZoiJlWxrYyAgdKKhtm2+Jcld8d+Uze9gijm5wqv0tMv7q2+0QxQL2RELnSO16Gxzr+hiiykrNlAwHRChzbJreFklECgKGzZKmTMuK+8OaY+Cu9CyVQUvObLp3xDiqEMGWUfC9KjBbhduVqKqNks44OYAQXdvN63pwGLO0F/O4OoOafxnHrngD++d/2X08IU8mX57z0QOmy/WP0jJLbKL0TLd5ZDsAUgKXbfx1XstFlz+77uXLJCEIDZZT6fdu4X11x9YHSpEXAnP8C7lwW3uPCpQdKR723W38PdgZNl7dfbQD+PEsGh+v/XW5L6xnDPao7J3191phOJ8H776eHXUZJjhvb1sfWdu52WXJ/1Nw/d0Hg44himFpwtl2bOXSENdlIx/+0FFkOhxGwqDa0oQZKcfHArD/KRSxTcuT8pHCoUiVz6V3jeeOiNdB5dMswOsSpbAAg5w9dPC1bfGdf7/u4QGsp6Rml7r77AP8ZpZYrQOVWAEIGm1+8Ibe/NRPY9Sfg3R/af73GBtmBDTCyQyp4afGXUTLNUYp3GS2preWAat6Mv4ySphmB37s/AI594b1fBasJbv+BIwDcvRJ4xtM8o65S/vyB8AOlOCcwYLIM4NpThidbas0onQ9hjlL2QKDwFvmmgnJih7xNj621R7oCh55RivELm24ZRotwm4x7coIspUty2ZTUWZsyhLM+0cA7gG8tAKa8EPpjiGKMU2/m0H5/594ZpRh/PSEGShQFbstFXkaIpXeAnKPy0H8DT+0LXLZkR3ViulxnrE9U61msNql74MnxDofxfOaueaoLXmY/+3KTQHOUgpXe+csona/x/rz2AHBoE3Byp/xcTai2UufgTJaLjgLhdb0D/Dd0CNbMATCes3IrsGGh5+uclpkufX5SUeAsoabJ30NSFgABHC/zfO0w5ihFkgq+60wZJSFMpXcBMkqAb2mg6kTm7uV7LLUrdT0T84ESANz7FjBrjXcDEY9F99yAn9x5PQbn2XRNTMr0XuLAJiPlV5xTrp3Vb8JVnDBRbNCbObRrRomBUkfCQIkiz22ahO5KDT2jpDgcoU0wtkp0yyABMMq8VKCTOzT441X5XYMpUFLrKvl75zUpwBylQM0cAP8ZJWt782/2A1tWGJ9rcb5ziAAjC5RsymAFK70zZ5QAU0MHS0ZJzWUKlA0yv1t9cgew6/8C/9FXZsFCmZ9kpjoMHvdkprr7XhDGBDX/7nK9kXVrPGdk8AKV3gHADf8iL1ZdlowZM0oRp+YldYgLm56jgMH32O4a1y8Lc4v7+Z9npcrvUvO8XyuIuoAEvZnDVVxjhKjDdNAkAAyUKBrMmZs7fhG5ib+a5tv5rrpC3oYTKJkDFTU/yN+k55BK7/xllDxBx0VLe2j1/Co4uFADVG4z9osW+4Vd7ebFBCu985dRsnaLCyWjNP0VYF6ZfM7my8DnK+T2Ax+F1vHOLPs678/NC7/GEleSUV6nyu9U2Z0rNfjYT0gBntgKPG3ptsh5IBHnMDVz6NR63SJv80ZE9TSIoqH4umxMHpyDh8YVtdtzmDNK8Z3+BaXjY6BEkVd0m7ztOx4Y+WBkn9va0EEFSjmhBEo2pXfq4tdcrmIWUjOHMDNKqj109/7GXITmS7IjnApoLljK88znkGRqSR209M5TxqcySv4yZHp78AAZpfgEOe9GBTnfeILM2gPA6a/k/VAzSub5YHnD226dqfZgbeigfjfBFlk2S0g1fteAb/kqtbsO08zhWt14PzDlReCOF6N9JkQRl5WSgN88MBrfvr79uopqzCh1KAyUKPIG3Q38cLPsOhbpen9zoNTaClSHUXqn1gYxB0r6YrV+5lmp4KqxXnZ2U1pbjazP1c5RSsmRgYeSN9yYh2UtzwPsM0pqPaVgC86qAEyV4vg0c6jznHO6/dcxswalp78CqnbJ+6H8HgDvxX37Tw7tMdGismS1niYU6vcQ7hy7rAHGfZbeRZyjI5XeXYs4JzBuvlyAlojanKZpXeeNl06AgRJFnqbJi/o4Z+Sf2xwo1R2RjQ/iErwvQv3RM0qeQKW5Cag/Lu/7m2eV6DayNubgpbHe6GYW9hwlT0YpJQfIMgVKPUeaztGu1E/NUTJlMgItONvSbDQPUOWSSTZzlFquGA0kApXeKdY26q3NMmh0OO1brNvJNgVKA2I8UMobLm9PejrWqfETbH6Slf671oyFmyli1Hs6Mb2GEhF1CF3mjZdOID7aJ0AUUSpQqj9ulN31GBRa0JbiySip0rf6YwAE4Ezyf9GraTKgqTsqm0CogEpliVwpRlbHKlhGKTXHOyvRc5QRjNmW3qmMkilQcnqCuKYLvser+UmA0X7bruudauQABO4cqOT6WZslZ7DRXCKY5O7AmMdkgKXWb4lVqonFiXLZ8U4F12k9/T/GjgqUUnP9jxlqN/qFDQMlIrpG8vVEMFDqABgoUdeiLjZP7QGqdsv7/i7crfRmDp4gRM1PSu8duIRQBUoqEwQYwY+/bBJgyiidlRfY6jkaTBklc2DScyRwfLv3OZqp4MYc1GX2lbdqvpCZCpScSUYgqXe9MwVKquzOlSrXugrGvIhlUncjOxXu5PG7/jO846Mld5jsRHj+lMxkqvlx7jADpUJPQKgyVBRRfAeYiNqK+nfON15iH0vvqGtRF5n1lcD+v8v7PUf7P95MNQw4Xy0DFxUoBWtvnmrTVvxSkI53gBFEiRbvrI0+RylXzulJdMsAMKOPsS5PoEDJ3Mwhd5i8VUGjmXV+kvmx5iyX3sgh3f/3YpacBRTcJLvBmdcJslkcs1NwJRldEU/uMDouhptRyr8R+OFnwMw32vb8KCT6Okr8r0lE1ygrJQHxDg3pSVGYgkBhYUaJupZEN9B9AHD6oLEGUu9xoT1WtXluaZLBQaiBkirZs8soBQqUnIkym3PlogysuqXLAE2fo9RDdpl7Ypuca6TK/AD70juVBTKX3qnA8exhGYyZM1Qqo5RoCpSSbUrvwmnkoDz4N6D1CnD4MwAr5bb8EaE/vqPpeSNwqkKW36nSu6tp8Z03rG3Pi0KmsfSOiNrI6kfGoO7iFaQnsYw61vG9Mep6eo407id1926IEIgz0Qgk9n8InDkk7/vreKcEyigFKr0z71drKV06a6x5pIKitHwjgEm2NJxQhDCV3pkCpaRMo9W0mrOl2GaUPM/TfMmY16QySqE0clCciXLek1qoN76b/7WoOoN8z5g7vt0ovQs3o0RRZWSUGCgR0bXp3yMVo4uC/P+nmMBAiboec4lXr7HhtShP9wRF6+YC/3xf3g81o9RQZWyrPSBvg81TSfKsS6QCKxUAJaYbjRi8nstP6d3lepnBAbxL7wD/5Xf6YrOpxjZXitEpT80tUm3Ow8koKRlFwMzfALPfCr2RQ0ekGjpUbpO/B81htHKnDsFYcJaBEhFRV8FAibqefFNGSa1CH6p7fiXn1bhSjG3pwTJKNusvqaYLwTq2qQyOKtUztwa3o5fefSPXalJUNsmV6htgqfK7qv/x3n7ZpvRO04zOgTvWAG9OA/7+jOe49MDfiz/DZgEDJl3dYzuKHoNkm3gVrKbkhtb4gmKGmpvE0jsioq6DgRJ1PblDZRcyAOgV4vwkJX8EMP0V4MG/yrK45Gyjc5w/KnhR3eoaG4z5UcEaSajSO2tGKdVPoKQ62okWI9MDGA0EkrN8H6PmvVSbMkoHPgI++LG8by69A4Bv/Ujebl4GHPnMdK7pfr+NLi/O6d2tLtyOdxR1ao4SS++IiLoOBkrU9biSgKnLgFuf8p6vFI6eo4CS3cD87fYlcGYqo3SxVi7OemKHXGzWXQikBSm/0jNKnjK3hiAZpTinbPAAAA0nje2HS43zturhWbz19NcyCyUE8M73TedvOceRDwG9vyXvmzNrKvgke+ZM5tU0cqCoKszo5nVLRESdH2s/qGsa8/3gxwRjnrsTSFKWDCJEi8wIHS+T2wtCaEuuMkRqsVhVvucvUALkOkVHPgOObpXZMwA4uEHe9rcpcUvrKefMtDQaz9N4Tm6b8G8yMDJzOIB//S2wdRUw/F5g5xrgizeAfhOCfz9dmTlIZSOHDqd/j1RsemY8ct1B3hghIqJOgxklovbmcMhW3oCcYxTq/CTA1JwhjEBpwGR5e3C9vG04ZZTV9Z/oe3ycE0j1zDuqqzTanqf1BG572uioZ5aWD3xnsSzbm/ofwE8qgb7Fwb+frqwnM0odXVFWMhKdzJwSEXUVDJSIIsE8T+n4F/J+KIGSnlHyzE1SgZIq57PT3xMoHdkCXLkEfP2J/DxvhBGwWaX3krd1R+UHELxJhZl5/SWyl9nX+Dkxo0RERBTzGCgRRYJqIb7nPTnfKD5RBi7BqHWRVEmcWovJX8ADyDlHaT2B5ssyWNqzTm63K7tTVKBUfww4e9T7nKltaBow+lEZMIW6yDERERFFDQMlokhQZWkV/yVvC8YA8SGsyK261Omld6qZQ4CMkqYZQdGmJcDBjwBocj6RP3pGyVR6F2whXQrfpIXAj3badx8kIiKimMJAiSgS9EYHQt6ornHBqMzRlQtyLaXL9fJzf+3BlTGPAg4ncKJcfn7DDCBrgP/j0wvlbV3l1ZXeEREREXUyDJSIIiGjCMjsZ3xeFGKg5EoB4j3tiE99KW/jEoIv7po3HPjOEuPz254OfLxXRkmV3jFQIiIioq6L7cGJIqXfBODM1zLTE2yhWUXTZEOH+kqg2hMopeTI7cGM+T7Q2iLXjVJtwv1RgdKZQ/IxAOcoERERUZfGjBJRpAyaJm+LbpXBS6hUi3CVUQrUyMFM04Bb5gIjHwh+bFoBAA1obQYgZLOJQC3IiYiIiDo5ZpSIIqXveODhD4Du/cN7nOp8V10hbwO1Br9a8S4gNQ9oOCk/T+8VWtaKiIiIqJNiRokoknqPCz0jpKgOaeFmlMKVM9i4nze8fZ6DiIiIqINgRoko1qnASLR6Pm+HjBIA3PMr4KuPZQOJQGsuEREREXUBMZNRWrJkCTRNQ0lJib5NCIFFixYhPz8f3bp1w/jx47Fnz57onSRRNCRbMkjtlVFKy5fzmYbMBBLT2uc5iIiIiDqImAiUysrK8MYbb2DYsGFe25ctW4bly5dj1apVKCsrQ25uLiZPnoyGhoYonSlRFFgXJ+3ez/44IiIiImozUQ+Uzp8/jzlz5uA3v/kNMjIy9O1CCKxYsQLPP/88Zs6ciSFDhmD16tW4ePEi/vznP0fxjIkizJxBum4qUHRb9M6FiIiIqIuIeqA0b9483HXXXZg0yXtOxOHDh1FdXY0pU6bo2xISElBcXIytW7f6/XqNjY04d+6c1wdRh5Z1nVxkNiUXmP4Ku9ERERERRUBUmzmsXbsWO3bsQFlZmc++6upqAEBOjvdaLjk5OTh69Kjfr7lkyRL87Gc/a9sTJYqm1BzgyXIg0c25Q0REREQRErWM0rFjx7BgwQK89dZbSExM9HucZnn3XAjhs83sueeeQ319vf5x7NixNjtnoqhJL2SQRERERBRBUcsolZeXo6amBqNGjdK3tbS0YPPmzVi1ahX2798PQGaW8vLy9GNqamp8skxmCQkJSEhIaL8TJyIiIiKiTi9qGaWJEyeioqICu3bt0j9Gjx6NOXPmYNeuXejbty9yc3OxYcMG/TFNTU0oLS3FuHHjonXaRERERETUBUQto5SamoohQ4Z4bUtOTkb37t317SUlJVi8eDEGDBiAAQMGYPHixUhKSsJ3v/vdaJwyERERERF1EVFt5hDMs88+i0uXLuGJJ57A2bNncfPNN2P9+vVITU2N9qkREREREVEnpgkhRLRPoj2dO3cObrcb9fX1SEvjZHgiIiIioq4qnNgg6usoERERERERxRoGSkRERERERBYMlIiIiIiIiCwYKBEREREREVkwUCIiIiIiIrJgoERERERERGTBQImIiIiIiMiCgRIREREREZEFAyUiIiIiIiKL+GifQHsTQgCQq/ASEREREVHXpWICFSME0ukDpYaGBgBAYWFhlM+EiIiIiIhiQUNDA9xud8BjNBFKONWBtba24uTJk0hNTYWmaVE9l3PnzqGwsBDHjh1DWlpaVM+FOgaOGboaHDcULo4ZChfHDIUrVsaMEAINDQ3Iz8+HwxF4FlKnzyg5HA4UFBRE+zS8pKWl8UWFwsIxQ1eD44bCxTFD4eKYoXDFwpgJlklS2MyBiIiIiIjIgoESERERERGRBQOlCEpISMDChQuRkJAQ7VOhDoJjhq4Gxw2Fi2OGwsUxQ+HqiGOm0zdzICIiIiIiChczSkRERERERBYMlIiIiIiIiCwYKBEREREREVkwUCIiIiIiIrJgoBRBr776Kvr06YPExESMGjUKn332WbRPiaJk8+bNuPvuu5Gfnw9N07Bu3Tqv/UIILFq0CPn5+ejWrRvGjx+PPXv2eB3T2NiIJ598EllZWUhOTsY999yD48ePR/C7oEhZsmQJxowZg9TUVPTo0QMzZszA/v37vY7hmCGr1157DcOGDdMXdxw7diw++OADfT/HDAWyZMkSaJqGkpISfRvHDFktWrQImqZ5feTm5ur7O/qYYaAUIW+//TZKSkrw/PPPY+fOnbjttttw5513orKyMtqnRlFw4cIFDB8+HKtWrbLdv2zZMixfvhyrVq1CWVkZcnNzMXnyZDQ0NOjHlJSU4L333sPatWuxZcsWnD9/HtOmTUNLS0ukvg2KkNLSUsybNw/btm3Dhg0b0NzcjClTpuDChQv6MRwzZFVQUIClS5di+/bt2L59OyZMmIDp06frFykcM+RPWVkZ3njjDQwbNsxrO8cM2bnhhhtQVVWlf1RUVOj7OvyYERQRN910k5g7d67Xtuuvv1785Cc/idIZUawAIN577z3989bWVpGbmyuWLl2qb7t8+bJwu93i9ddfF0IIUVdXJ5xOp1i7dq1+zIkTJ4TD4RAffvhhxM6doqOmpkYAEKWlpUIIjhkKXUZGhvjtb3/LMUN+NTQ0iAEDBogNGzaI4uJisWDBAiEEX2fI3sKFC8Xw4cNt93WGMcOMUgQ0NTWhvLwcU6ZM8do+ZcoUbN26NUpnRbHq8OHDqK6u9hovCQkJKC4u1sdLeXk5rly54nVMfn4+hgwZwjHVBdTX1wMAMjMzAXDMUHAtLS1Yu3YtLly4gLFjx3LMkF/z5s3DXXfdhUmTJnlt55ghfw4ePIj8/Hz06dMH9957Lw4dOgSgc4yZ+GifQFdQW1uLlpYW5OTkeG3PyclBdXV1lM6KYpUaE3bj5ejRo/oxLpcLGRkZPsdwTHVuQgg89dRTuPXWWzFkyBAAHDPkX0VFBcaOHYvLly8jJSUF7733HgYPHqxfgHDMkNnatWuxY8cOlJWV+ezj6wzZufnmm/HHP/4RAwcOxKlTp/CLX/wC48aNw549ezrFmGGgFEGapnl9LoTw2UakXM144Zjq/ObPn4/du3djy5YtPvs4Zsjquuuuw65du1BXV4d33nkHDz74IEpLS/X9HDOkHDt2DAsWLMD69euRmJjo9ziOGTK788479ftDhw7F2LFj0a9fP6xevRq33HILgI49Zlh6FwFZWVmIi4vziYxramp8omwi1S0m0HjJzc1FU1MTzp496/cY6nyefPJJ/PWvf8XGjRtRUFCgb+eYIX9cLhf69++P0aNHY8mSJRg+fDhWrlzJMUM+ysvLUVNTg1GjRiE+Ph7x8fEoLS3Fyy+/jPj4eP13zjFDgSQnJ2Po0KE4ePBgp3idYaAUAS6XC6NGjcKGDRu8tm/YsAHjxo2L0llRrOrTpw9yc3O9xktTUxNKS0v18TJq1Cg4nU6vY6qqqvDll19yTHVCQgjMnz8f7777Lj799FP06dPHaz/HDIVKCIHGxkaOGfIxceJEVFRUYNeuXfrH6NGjMWfOHOzatQt9+/blmKGgGhsbsW/fPuTl5XWO15lodJDoitauXSucTqf43e9+J/bu3StKSkpEcnKyOHLkSLRPjaKgoaFB7Ny5U+zcuVMAEMuXLxc7d+4UR48eFUIIsXTpUuF2u8W7774rKioqxH333Sfy8vLEuXPn9K8xd+5cUVBQID7++GOxY8cOMWHCBDF8+HDR3NwcrW+L2snjjz8u3G632LRpk6iqqtI/Ll68qB/DMUNWzz33nNi8ebM4fPiw2L17t/jpT38qHA6HWL9+vRCCY4aCM3e9E4Jjhnw9/fTTYtOmTeLQoUNi27ZtYtq0aSI1NVW/vu3oY4aBUgS98soronfv3sLlcomRI0fqrX2p69m4caMA4PPx4IMPCiFkS82FCxeK3NxckZCQIG6//XZRUVHh9TUuXbok5s+fLzIzM0W3bt3EtGnTRGVlZRS+G2pvdmMFgPjDH/6gH8MxQ1aPPPKI/j8nOztbTJw4UQ+ShOCYoeCsgRLHDFnNnj1b5OXlCafTKfLz88XMmTPFnj179P0dfcxoQggRnVwWERERERFRbOIcJSIiIiIiIgsGSkRERERERBYMlIiIiIiIiCwYKBEREREREVkwUCIiIiIiIrJgoERERERERGTBQImIiIiIiMiCgRIREREREZEFAyUiIiKPoqIirFixItqnQUREMYCBEhERRcVDDz2EGTNmAADGjx+PkpKSiD33m2++ifT0dJ/tZWVl+MEPfhCx8yAiotgVH+0TICIiaitNTU1wuVxX/fjs7Ow2PBsiIurImFEiIqKoeuihh1BaWoqVK1dC0zRomoYjR44AAPbu3YupU6ciJSUFOTk5uP/++1FbW6s/dvz48Zg/fz6eeuopZGVlYfLkyQCA5cuXY+jQoUhOTkZhYSGeeOIJnD9/HgCwadMmPPzww6ivr9efb9GiRQB8S+8qKysxffp0pKSkIC0tDbNmzcKpU6f0/YsWLcKIESOwZs0aFBUVwe12495770VDQ0P7/tCIiKjdMVAiIqKoWrlyJcaOHYvHHnsMVVVVqKqqQmFhIaqqqlBcXIwRI0Zg+/bt+PDDD3Hq1CnMmjXL6/GrV69GfHw8Pv/8c/z6178GADgcDrz88sv48ssvsXr1anz66ad49tlnAQDjxo3DihUrkJaWpj/fM88843NeQgjMmDEDZ86cQWlpKTZs2ICvv/4as2fP9jru66+/xrp16/D+++/j/fffR2lpKZYuXdpOPy0iIooUlt4REVFUud1uuFwuJCUlITc3V9/+2muvYeTIkVi8eLG+7fe//z0KCwtx4MABDBw4EADQv39/LFu2zOtrmuc79enTBy+88AIef/xxvPrqq3C5XHC73dA0zev5rD7++GPs3r0bhw8fRmFhIQBgzZo1uOGGG1BWVoYxY8YAAFpbW/Hmm28iNTUVAHD//ffjk08+wYsvvnhtPxgiIooqZpSIiCgmlZeXY+PGjUhJSdE/rr/+egAyi6OMHj3a57EbN27E5MmT0bNnT6SmpuKBBx7A6dOnceHChZCff9++fSgsLNSDJAAYPHgw0tPTsW/fPn1bUVGRHiQBQF5eHmpqasL6XomIKPYwo0RERDGptbUVd999N1566SWffXl5efr95ORkr31Hjx7F1KlTMXfuXLzwwgvIzMzEli1b8Oijj+LKlSshP78QApqmBd3udDq99muahtbW1pCfh4iIYhMDJSIiijqXy4WWlhavbSNHjsQ777yDoqIixMeH/u9q+/btaG5uxi9/+Us4HLJw4i9/+UvQ57MaPHgwKisrcezYMT2rtHfvXtTX12PQoEEhnw8REXVMLL0jIqKoKyoqwj/+8Q8cOXIEtbW1aG1txbx583DmzBncd999+OKLL3Do0CGsX78ejzzySMAgp1+/fmhubsavfvUrHDp0CGvWrMHrr7/u83znz5/HJ598gtraWly8eNHn60yaNAnDhg3DnDlzsGPHDnzxxRd44IEHUFxcbFvuR0REnQsDJSIiirpnnnkGcXFxGDx4MLKzs1FZWYn8/Hx8/vnnaGlpwR133IEhQ4ZgwYIFcLvdeqbIzogRI7B8+XK89NJLGDJkCP70pz9hyZIlXseMGzcOc+fOxezZs5Gdne3TDAKQJXTr1q1DRkYGbr/9dkyaNAl9+/bF22+/3ebfPxERxR5NCCGifRJERERERESxhBklIiIiIiIiCwZKREREREREFgyUiIiIiIiILBgoERERERERWTBQIiIiIiIismCgREREREREZMFAiYiIiIiIyIKBEhERERERkQUDJSIiIiIiIgsGSkRERERERBYMlIiIiIiIiCz+PxUAfPEaWw6NAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Loss\n",
    "fig = plt.figure(facecolor=\"w\", figsize=(10, 5))\n",
    "plt.plot(loss_hist)\n",
    "plt.plot(test_loss_hist)\n",
    "plt.title(\"Loss Curves\")\n",
    "plt.legend([\"Train Loss\", \"Test Loss\"])\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "id": "10d546fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Loss\n",
    "fig = plt.figure(facecolor=\"w\", figsize=(10, 5))\n",
    "plt.plot(loss_hist)\n",
    "plt.plot(test_loss_hist)\n",
    "plt.title(\"Loss Curves\")\n",
    "plt.legend([\"Train Loss\", \"Test Loss\"])\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "8548ce3d-0a0e-4983-b71f-a8200246ba69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Loss\n",
    "fig = plt.figure(facecolor=\"w\", figsize=(10, 5))\n",
    "plt.plot(loss_hist)\n",
    "plt.plot(test_loss_hist)\n",
    "plt.title(\"Loss Curves\")\n",
    "plt.legend([\"Train Loss\", \"Test Loss\"])\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "id": "0c8afd20-9f56-43a6-b61f-0802262e8ccd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_19420\\2584680384.py:18: DeprecationWarning: an integer is required (got type numpy.float64).  Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.\n",
      "  return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)\n",
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_19420\\653768458.py:17: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  tensor = torch.tensor(x)\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 2 is not equal to len(dims) = 3",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[285], line 4\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m samples, labels \u001b[38;5;129;01min\u001b[39;00m test_loader:\n\u001b[1;32m----> 4\u001b[0m     output \u001b[38;5;241m=\u001b[39m \u001b[43mnet\u001b[49m\u001b[43m(\u001b[49m\u001b[43msamples\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      5\u001b[0m     \u001b[38;5;28mprint\u001b[39m()\n\u001b[0;32m      6\u001b[0m     \u001b[38;5;28mprint\u001b[39m(labels[\u001b[38;5;241m3\u001b[39m])\n",
      "File \u001b[1;32m~\\anaconda3\\envs\\classifier\\lib\\site-packages\\torch\\nn\\modules\\module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1516\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[0;32m   1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 1518\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\anaconda3\\envs\\classifier\\lib\\site-packages\\torch\\nn\\modules\\module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[0;32m   1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[0;32m   1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[0;32m   1525\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[0;32m   1526\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[1;32m-> 1527\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m   1530\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[276], line 43\u001b[0m, in \u001b[0;36mNet.forward\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m     40\u001b[0m spk2_rec \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     41\u001b[0m mem2_rec \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m---> 43\u001b[0m spk_in \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_delta_coding\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     45\u001b[0m num_steps \u001b[38;5;241m=\u001b[39m spk_in\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m     47\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(num_steps):\n\u001b[0;32m     48\u001b[0m     \u001b[38;5;66;03m#print(spk_in[step].shape)\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[276], line 23\u001b[0m, in \u001b[0;36mNet._delta_coding\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m     19\u001b[0m tensor \u001b[38;5;241m=\u001b[39m tensor\u001b[38;5;241m.\u001b[39mto(device)\n\u001b[0;32m     21\u001b[0m spike_data \u001b[38;5;241m=\u001b[39m spikegen\u001b[38;5;241m.\u001b[39mdelta(x, threshold\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.75\u001b[39m)\n\u001b[1;32m---> 23\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mspike_data\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpermute\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mRuntimeError\u001b[0m: permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 2 is not equal to len(dims) = 3"
     ]
    }
   ],
   "source": [
    "for samples, labels in test_loader:\n",
    "    \n",
    "\n",
    "    output = net(samples[3])\n",
    "    print()\n",
    "    print(labels[3])\n",
    "\n",
    "    tensor_output = output[0]  # Extract the tensor from the tuple\n",
    "    numpy_array = tensor_output.detach().numpy()  # Convert tensor to numpy array\n",
    "    plt.plot(numpy_array)\n",
    "    # Plot the numpy array\n",
    "    plt.plot(numpy_array)\n",
    "    plt.xlabel('Index')\n",
    "    plt.ylabel('Value')\n",
    "    plt.title('Plot of Tensor')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "82add137-6812-4b3d-98dc-68e71d611b7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\2584680384.py:18: DeprecationWarning: an integer is required (got type numpy.float64).  Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.\n",
      "  return torch.tensor(sample, dtype=torch.float32), torch.tensor(label, dtype=torch.long)\n",
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_13404\\3181884480.py:17: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  tensor = torch.tensor(x)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n",
      "        1, 1, 1, 1, 1, 1, 1, 1])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([1, 1, 1, 1, 1, 1, 1, 1])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for samples, labels in test_loader:\n",
    "    output = net(samples)\n",
    "    print(labels)\n",
    "    spk_In = torch.stack(net.spkIn).unsqueeze(1)\n",
    "    spk_rec1 = torch.stack(net.spk1)\n",
    "    spk_rec2 = torch.stack(net.spk2)\n",
    "    plot_snn_spikes(spk_In[:,:,0,:], spk_rec1[:,0,:], spk_rec2, spk_In[:,:,0,:].shape[0], \"Fully Connected Spiking Neural Network\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9ece0ec-708d-4bbb-817a-7e3887ebe8cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(net.state_dict(), 'model.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "id": "fbf261c7-5eab-43e6-801a-8fe7d92e8b12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spk_In[:,:,0,:].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f4ee9be-a705-4e7d-b01c-d2f2a507f526",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}