{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Uses For PCA Other Than Dimensionality Reduction Part 2\n",
    "## Imputation, and Noise Reduction\n",
    "\n",
    "Principal Component Analysis (PCA) is frequently applied in machine learning as a sort of black box dimensionality reduction technique. However with a deeper understanding of what PCA is and what it does we can use it for all manner of other tasks e.g.\n",
    "\n",
    "<!-- TEASER_END -->\n",
    "\n",
    "* Decorrelating Variables\n",
    "* Semantic Factor Discovery\n",
    "* Empirical Noise Modeling\n",
    "* Missing Data Imputation \n",
    "* Example Generation \n",
    "* Anomaly Detection\n",
    "* Patchwise Modeling\n",
    "* Noise Reduction\n",
    "\n",
    "In part one of this series of blog posts we talked about decorrelation, semantic factor discovery (by analyzing the principal vectors), and empirical noise modeling. \n",
    "\n",
    "<a href=\"other_uses_for_PCA_part1.html\">Part 1 </a>\n",
    "\n",
    "In this post we will be talking about using PCA to make clever guesses for missing values in our data and/or reconstructing a lower noise version of our inputs. Replacing missing values in our data is often called \"imputation\".\n",
    "\n",
    "First we load our data and redefine some helper functions from the last post. \n",
    "\n",
    "Changes:\n",
    "March 1, 2019: Altered the implementation to include an ortho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy\n",
    "import scipy.ndimage\n",
    "import sklearn\n",
    "import sklearn.datasets\n",
    "import sklearn.decomposition\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "plt.rcParams.update(\n",
    "    {\n",
    "        \"figure.figsize\":(10,6),\n",
    "        \"font.size\":16,\n",
    "        \"image.cmap\":\"afmhot\",\n",
    "        \"image.interpolation\":\"nearest\",\n",
    "        \"image.aspect\":\"auto\",\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "faces_ds = sklearn.datasets.fetch_olivetti_faces()\n",
    "\n",
    "faces = faces_ds[\"data\"]\n",
    "#divide by the global standard deviation\n",
    "faces /= np.std(faces)\n",
    "\n",
    "subject_ids = faces_ds[\"target\"]\n",
    "\n",
    "im_shape = (64, 64)\n",
    "\n",
    "def as_image(arr):\n",
    "    return arr.reshape(im_shape)\n",
    "    \n",
    "def view_as_image(arr, ax=None, **imshow_kwargs):\n",
    "    if ax is None:\n",
    "        fig, ax = plt.subplots()\n",
    "    ax.axis(\"off\")\n",
    "    im = ax.imshow(as_image(arr), **imshow_kwargs)\n",
    "    return im\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Injecting Missing Values\n",
    "\n",
    "It would not be a fair test of PCA's ability to handle missing data if we train it on a datset which has no missing values at all. So in order to make things interesting we will first replace 20% of the pixel values in our input data with zeros. Because we are dealing with image data and neighboring pixels tend to share a lot of information it is much harder to deal with lots of missing pixels all in the same area than it is to deal with pixels randomly scattered around the image. To make things even more challenging we will try to mostly cut out image chunks several pixels wide at a time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(1234)\n",
    "\n",
    "occlusion_fraction = 0.2\n",
    "\n",
    "hole_scale = 3\n",
    "#generate random uncorrelated noise\n",
    "occlusion_mask = np.random.normal(size=[len(faces)] + list(im_shape))\n",
    "\n",
    "#Smooth the noise locally to make the noise fluctuations change only on several pixel scale\n",
    "occlusion_mask = scipy.ndimage.filters.gaussian_filter(occlusion_mask, hole_scale)\n",
    "occlusion_mask = occlusion_mask > np.percentile(occlusion_mask, 100*occlusion_fraction)\n",
    "#flatten to match face data shape\n",
    "\n",
    "occlusion_mask = occlusion_mask.reshape((len(faces), -1))\n",
    "\n",
    "occluded_faces = faces*occlusion_mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f69291a9f98>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6929243e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "view_as_image(occluded_faces[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Although we can still feed this data directly in to the PCA object in sklearn like we did in part 1 the results will be rather less than satisfactory. PCA tends not to deal well with large outliers in our data and each of these occlusions has a much more dramatic effect on the data than the more subtle differences caused by changes in facial structure or orientation. If we don't give the missing points any special treatment the principal components that we will get will tell us more about the distribution of pixels we randomly decided to remove than it will about the structure of faces."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PCA(copy=True, iterated_power='auto', n_components=None, random_state=None,\n",
       "  svd_solver='auto', tol=0.0, whiten=False)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "occluded_sklearn_pca = sklearn.decomposition.PCA()\n",
    "occluded_sklearn_pca.fit(occluded_faces)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f69291df438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6928aeeb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6928ab0748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(3):\n",
    "    comp = occluded_sklearn_pca.components_[i]\n",
    "    mag_max = np.max(np.abs(comp))\n",
    "    view_as_image(comp, vmin=-mag_max, vmax=mag_max, cmap=\"coolwarm\")\n",
    "    plt.title(\"Princpal Vector {}\".format(i))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These principal vectors leave something to be desired to say the least. However in principle we have done something which is informationally equivalent to removing 50% of our faces leaving us with just 200 instead of 400. We should still be able to get reasonably good results even with 50% of our data missing.\n",
    "As I mentioned briefly in part 1 of these posts PCA is equivalent to the solution of a least squares problem;\n",
    "\n",
    "$$\n",
    "X \\approx \\hat{X} = W~H\n",
    "$$\n",
    "\n",
    "where W is a N by k matrix of weight coefficents (which we called the principal components) and H was a k by m matrix where m is the number of features in our data matrix X. It turns out that SVD (which is how sklearn computes the PCA expansion) gives the solution to the least squares problem where each point is given equal weight. However we can easily reformulate our problem to include a quality weighting for our input data giving weight 0 to the points we have occluded. That is we wish to minimize a metric $\\chi^2$ which we define as follows;\n",
    "\n",
    "$$\n",
    "\\delta_i = X_i - \\hat{X}_i = X_i - W_i~H\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\chi^2 = \\sum_i^N \\delta_i^T C_i^{-1} \\delta_i\n",
    "$$\n",
    "\n",
    "Here we are using the subscript $i$ to indicate the row index in the original dataset so $X_i$ is the i'th observation and $W_i$ is the corresponding row of weights in the W matrix etc. The weights given to each input point are encoded in the matrix $C_i^{-1}$ which is the inverse of the noise covariance matrix of our data. In our particular case there is no correlation between the noise in each pixel and so the covariance matrix is simply a diagonal matrix with zero entries for missing pixels (corresponding to infinite noise) and non-zero entries corresponding to the inverse of the noise variance in each pixel. \n",
    "\n",
    "There is a complication to the use of least squares for finding a PCA expansion that we glossed over earlier which is that there is some amount of degeracy between the coefficents of W and H. We can always decrease the entries in W by a factor of 2 and double the magnitude of the vectors in H and end up with the same approximation matrix $\\hat{X}$. We can remove this degeracy by requiring H to be orthonormal. There is still some ambiguity since any permutation of the columns of W and the rows of H will also give the same approximation matrix. This is easy to handle since we simply need to reorder the columns of W in order of decreasing total variance as a post processing step.\n",
    "\n",
    "Solving this optimization problem is far from trivial. We will try and make progress on the large optimization problem by solving a much simpler sub-problem repeatedly. We shall begin with a set of randomly chosen H and W and then propose updates to H and W which slightly improve our model. We will propose updates which affect only one component at a time and iterate through all components. Focusing for a moment on just a single row $X_i$ in our data it should be intuitively clear that we could perfectly reconstruct $X_i$ by choosing to update our principal vector by choosing a new principa vector proportional to that row $H_j \\propto X_i$. \n",
    "Since we have many rows instead of just one we can pick the optimal $H_j$ simply by taking the weighted average of all of our rows. We want to take into account both the data weights and the fact that each row has a different \"amount\" of each principal vector in it as indicated by the magnitude of the corresponding W coefficient. Iteratively proposig updates which take the weighted average of the residuals to our data in this way and then enforcing orthonormality by simply orthogonalizing our principal vectors every now and again actually works reasonably well (see the code below). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def partial_outer_product(\n",
    "    w, #(nrows, rank)\n",
    "    h_t, #(ncols, rank)\n",
    "    row_indexes, \n",
    "    col_indexes, \n",
    "    output_format=\"raw\",\n",
    "):\n",
    "    \"\"\"\n",
    "    Evaluates the product wh on a small footprint of matrix locations corresponding to the row/column pairs\n",
    "    passed indicated by the row_indexes and col_indexes arguments.\n",
    "    \"\"\"\n",
    "    #find the weights corresponding to each row and the basis vector values corresponding to each column\n",
    "    wvals = w[row_indexes]\n",
    "    hvals = h_t[col_indexes]\n",
    "    \n",
    "    #calcualate w and h as arrays and sum over ranks to find the corresponding dense matrix values\n",
    "    result = np.sum(wvals*hvals, axis=1)\n",
    "    \n",
    "    #most of the time we will not want to convert back to sparse matrix format so just return the result as a vector\n",
    "    if output_format == \"raw\":\n",
    "        pass\n",
    "    elif output_format == \"coo\":\n",
    "        # just in case we want the data back as a sparse matrix. \n",
    "        #Note this matrix is not really WH but rather just the entries evaluated at the input rows/cols\n",
    "        result = scipy.sparse.coo_matrix((result, (row_indexes, col_indexes)))\n",
    "    else:\n",
    "        raise NotImplementedError(\"don't know how to return output format = {}\".format(output_format))\n",
    "    \n",
    "    return result\n",
    "\n",
    "from numba import jit\n",
    "\n",
    "@jit\n",
    "def sum_into_vector(values, indexes, n_out):\n",
    "    out = np.zeros(n_out)\n",
    "    for i in range(len(indexes)):\n",
    "        ci = indexes[i]\n",
    "        out[ci] =  out[ci] + values[i]\n",
    "    return out\n",
    "\n",
    "\n",
    "\n",
    "class SparselyObservedLowRankApproximation(object):\n",
    "    W = None   #weight matrix\n",
    "    H_t = None #transpose of H matrix\n",
    "    mean = None #column wise data mean\n",
    "    \n",
    "    def __init__(\n",
    "        self,\n",
    "        rank,\n",
    "        max_iter=100,\n",
    "        convergence_delta=1e-5,\n",
    "        orthogonalize_freq=5,\n",
    "        mean_subtract=True,\n",
    "        H_damp=1e-3,\n",
    "        W_damp=1e-5,\n",
    "        verbose=False,\n",
    "    ):\n",
    "        self.rank = rank\n",
    "        self.H_damp = H_damp\n",
    "        self.W_damp = W_damp\n",
    "        self.max_iter = max_iter\n",
    "        self.convergence_delta=convergence_delta\n",
    "        self.orthogonalize_freq=orthogonalize_freq\n",
    "        self.mean_subtract = mean_subtract\n",
    "        self.verbose = verbose\n",
    "    \n",
    "    def fit(self, x):\n",
    "        #convert to coordinate sparse matrix format\n",
    "        x = x.tocoo()\n",
    "        \n",
    "        n_rows, n_cols = x.shape\n",
    "        \n",
    "        #initialize the coefficients\n",
    "        if self.W is None:\n",
    "            W = np.zeros((x.shape[0], self.rank))\n",
    "            self.W = W\n",
    "        if self.H_t is None:\n",
    "            H_t = np.random.normal(size=(x.shape[1], self.rank))\n",
    "            H_t /= np.sqrt(np.sum(H_t**2, axis=0))\n",
    "            self.H_t = H_t\n",
    "        if self.mean is None:\n",
    "            #sum up the value in each column\n",
    "            column_sum = sum_into_vector(values=x.data, indexes=x.col, n_out=n_cols)\n",
    "            #count the number of entries in each column\n",
    "            counts = sum_into_vector(values=np.ones(len(x.data)), indexes=x.col, n_out=n_cols)\n",
    "            mean = column_sum/counts\n",
    "            self.mean = mean\n",
    "        \n",
    "        target = x.data\n",
    "        if self.mean_subtract:\n",
    "            target = target - self.mean[x.col]\n",
    "        \n",
    "        last_err = np.sqrt(np.mean(target**2))\n",
    "        for iter_idx in range(self.max_iter):\n",
    "            if self.verbose:\n",
    "                print(\"iteration\", iter_idx+1)\n",
    "            ortho = iter_idx % self.orthogonalize_freq == 0\n",
    "            self.iterate(\n",
    "                x,\n",
    "                pre_orthogonalize=ortho,\n",
    "            )\n",
    "            mod = partial_outer_product(self.W, self.H_t, row_indexes=x.row, col_indexes=x.col)\n",
    "            cur_resids = target - mod\n",
    "            cur_err = np.sqrt(np.mean(cur_resids**2))\n",
    "            if self.verbose:\n",
    "                print(\"Residual RMS {:4.5f}\".format(cur_err))\n",
    "            if cur_err > last_err - self.convergence_delta:\n",
    "                break\n",
    "            \n",
    "    \n",
    "    def estimate_W(\n",
    "        self, \n",
    "        x, \n",
    "        component_index=None,\n",
    "        H_t=None,\n",
    "        W_start=None, \n",
    "        W_damp=None,\n",
    "        copy_W=True,\n",
    "    ):\n",
    "        \"\"\"\n",
    "        Estimate the decomposition of the observed part of x as a linear combination of the basis vectors H_t.\n",
    "        \"\"\"\n",
    "        n_rows, n_cols = x.shape\n",
    "        \n",
    "        if W_damp is None:\n",
    "            W_damp = self.W_damp\n",
    "        \n",
    "        if W_start is None:\n",
    "            W_start = np.zeros((x.shape[0], self.rank))\n",
    "        \n",
    "        if copy_W:\n",
    "            W = W_start.copy()\n",
    "        else:\n",
    "            W = W_start\n",
    "        \n",
    "        if H_t is None:\n",
    "            H_t = self.H_t\n",
    "        \n",
    "        row_indexes = x.row\n",
    "        col_indexes = x.col\n",
    "                \n",
    "        target = x.data\n",
    "        if self.mean_subtract:\n",
    "            target = x.data - self.mean[col_indexes]\n",
    "        \n",
    "        if component_index is None:\n",
    "            component_indexes = range(self.rank)\n",
    "        else:\n",
    "            component_indexes = [component_index]\n",
    "        \n",
    "        #evaluate the model on our footprint\n",
    "        mod = partial_outer_product(W, H_t, row_indexes=row_indexes, col_indexes=col_indexes)\n",
    "        cur_resids = target - mod\n",
    "        \n",
    "        for comp_idx in component_indexes:\n",
    "            csub_h = H_t[col_indexes, comp_idx]\n",
    "            raw_prod = cur_resids*csub_h\n",
    "            prod = sum_into_vector(values=raw_prod, indexes=row_indexes, n_out=n_rows)\n",
    "            w_denom = sum_into_vector(values=csub_h**2, indexes=row_indexes, n_out=n_rows)\n",
    "            w_delt = prod/(w_denom+W_damp)\n",
    "            W[:, comp_idx] += w_delt\n",
    "            #adjust the residuals to take into account the change in coefficients\n",
    "            cur_resids -= csub_h*w_delt[row_indexes]\n",
    "        \n",
    "        return W\n",
    "    \n",
    "    def estimate_H_t(\n",
    "        self,\n",
    "        x,\n",
    "        W,\n",
    "        component_index=None,\n",
    "        H_t_start=None, \n",
    "        H_damp=None,\n",
    "        copy_H=True,\n",
    "    ):\n",
    "        \"\"\"Estimate the basis vectors from their weight vectors\"\"\"\n",
    "        n_rows, n_cols = x.shape\n",
    "        \n",
    "        if H_damp is None:\n",
    "            H_damp = self.H_damp\n",
    "        \n",
    "        if H_t_start is None:\n",
    "            H_t_start = self.H_t\n",
    "        \n",
    "        H_t = H_t_start\n",
    "        if copy_H:\n",
    "            H_t = H_t.copy()\n",
    "                \n",
    "        row_indexes = x.row\n",
    "        col_indexes = x.col\n",
    "        \n",
    "        target = x.data\n",
    "        if self.mean_subtract:\n",
    "            target = x.data - self.mean[col_indexes]\n",
    "        \n",
    "        if component_index is None:\n",
    "            component_indexes = range(self.rank)\n",
    "        else:\n",
    "            component_indexes = [component_index]\n",
    "        \n",
    "        #evaluate the model on our footprint\n",
    "        mod = partial_outer_product(W, H_t, row_indexes=row_indexes, col_indexes=col_indexes)\n",
    "        cur_resids = target - mod\n",
    "        \n",
    "        for comp_idx in component_indexes:            \n",
    "            csub_w = W[row_indexes, comp_idx]\n",
    "            raw_prod = cur_resids*csub_w\n",
    "            prod = sum_into_vector(values=raw_prod, indexes=col_indexes, n_out=n_cols)\n",
    "            h_denom = sum_into_vector(values=csub_w**2, indexes=col_indexes, n_out=n_cols)\n",
    "            h_delt = prod/(h_denom + H_damp)\n",
    "            H_t[:, comp_idx] += h_delt\n",
    "            cur_resids -= csub_w*h_delt[col_indexes]\n",
    "        \n",
    "        return H_t\n",
    "        \n",
    "    def orthogonalize_basis(\n",
    "        self,\n",
    "    ):  \n",
    "        H_t = self.H_t\n",
    "        W = self.W\n",
    "        \n",
    "        h_norm = np.sqrt(np.sum(H_t**2, axis=0))\n",
    "        H_t = H_t/h_norm\n",
    "        W = W*h_norm\n",
    "            \n",
    "        #scale each row of H by its captured variance to preserve variance ordering\n",
    "        column_scale = np.std(W, axis=0)+1e-5\n",
    "        column_scale /= np.sum(column_scale)\n",
    "        H_scaled = H_t*column_scale\n",
    "            \n",
    "        H_t_old = H_t\n",
    "            \n",
    "        #orthogonalize principal vectors\n",
    "        H_t = np.linalg.svd(H_scaled.transpose(), full_matrices=False)[2].transpose()    \n",
    "            \n",
    "        #rotate weights onto the new basis\n",
    "        old_vector_decomposition = np.dot(H_t_old.transpose(), H_t)\n",
    "        rot_mat = old_vector_decomposition\n",
    "        W = np.dot(W, rot_mat)\n",
    "            \n",
    "        #permute W and H to order by variance largest first\n",
    "        permute = np.argsort(-np.std(W, axis=0))\n",
    "        H_t = H_t[:, permute]\n",
    "        W = W[:, permute]\n",
    "            \n",
    "        self.H_t = H_t\n",
    "        self.W = W\n",
    "    \n",
    "    \n",
    "    def iterate(\n",
    "        self, \n",
    "        x,\n",
    "        pre_orthogonalize=False,\n",
    "    ):        \n",
    "        if pre_orthogonalize:\n",
    "            self.orthogonalize_basis()\n",
    "      \n",
    "        H_t = self.H_t\n",
    "        W = self.W\n",
    "        \n",
    "        W = self.estimate_W(\n",
    "            x,\n",
    "            W_start=W,\n",
    "            copy_W=False,\n",
    "        )\n",
    "            \n",
    "        H_t = self.estimate_H_t(\n",
    "            x,\n",
    "            W=W,\n",
    "            H_t_start=H_t,\n",
    "            copy_H=False,\n",
    "        )\n",
    "        \n",
    "        #keep the principal vectors normalized\n",
    "        h_norm = np.sqrt(np.sum(H_t**2, axis=0))\n",
    "        H_t = H_t/h_norm\n",
    "        W = W*h_norm\n",
    "        \n",
    "        self.W = W\n",
    "        self.H_t = H_t\n",
    "        \n",
    "        \n",
    "    def transform(self, x):\n",
    "        \"\"\"transform a data matrix into a weight matrix\"\"\"\n",
    "        return self.estimate_W(\n",
    "            x, \n",
    "            W_start=np.zeros((x.shape[0], self.rank)),\n",
    "            copy_W=False\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "class WeightedLowRankApproximation(object):\n",
    "    W = None\n",
    "    H = None\n",
    "    \n",
    "    def __init__(\n",
    "        self,\n",
    "        x,\n",
    "        x_weight,\n",
    "        n_components,\n",
    "        n_iter = 5,\n",
    "    ):\n",
    "        self.x = x\n",
    "        self.x_weight = x_weight\n",
    "        self.n_components = n_components\n",
    "        self.n_iter = n_iter\n",
    "        \n",
    "        x_mean = np.sum(x*x_weight, axis=0)/np.sum(x_weight, axis=0)\n",
    "        self.mean = x_mean\n",
    "        \n",
    "        for iter_idx in range(n_iter):\n",
    "            self.iterate()\n",
    "        \n",
    "    def orthogonalize_basis(\n",
    "        self,\n",
    "    ):  \n",
    "        H_t = self.H.transpose()\n",
    "        W = self.W\n",
    "        \n",
    "        h_norm = np.sqrt(np.sum(H_t**2, axis=0))\n",
    "        H_t = H_t/h_norm\n",
    "        W = W*h_norm\n",
    "            \n",
    "        #scale each row of H by its captured variance to preserve variance ordering\n",
    "        column_scale = np.std(W, axis=0)+1e-5\n",
    "        column_scale /= np.sum(column_scale)\n",
    "        H_scaled = H_t*column_scale\n",
    "            \n",
    "        H_t_old = H_t\n",
    "            \n",
    "        #orthogonalize principal vectors\n",
    "        H_t = np.linalg.svd(H_scaled.transpose(), full_matrices=False)[2].transpose()    \n",
    "            \n",
    "        #rotate weights onto the new basis\n",
    "        old_vector_decomposition = np.dot(H_t_old.transpose(), H_t)\n",
    "        rot_mat = old_vector_decomposition\n",
    "        W = np.dot(W, rot_mat)\n",
    "            \n",
    "        #permute W and H to order by variance largest first\n",
    "        permute = np.argsort(-np.std(W, axis=0))\n",
    "        H_t = H_t[:, permute]\n",
    "        W = W[:, permute]\n",
    "            \n",
    "        self.H = H_t.transpose()\n",
    "        self.W = W\n",
    "    \n",
    "    def iterate(self):\n",
    "        x = self.x\n",
    "        x_weight = self.x_weight\n",
    "        \n",
    "        xdelt = x-self.mean\n",
    "        \n",
    "        if self.W is None:\n",
    "            W = np.zeros((len(x), self.n_components))\n",
    "            self.W = W\n",
    "        if self.H is None:\n",
    "            H = np.random.normal(size=(self.n_components, x.shape[1]))\n",
    "            H /= np.sqrt(np.sum(H**2, axis=1)).reshape((-1, 1))\n",
    "            self.H = H\n",
    "        \n",
    "        H = self.H\n",
    "        W = self.W\n",
    "        \n",
    "        for comp_idx in range(self.n_components):\n",
    "            #find the current residuals\n",
    "            mod = np.dot(W, H)\n",
    "            cur_resids = xdelt - mod\n",
    "\n",
    "            #leaving H[j] fixed find best update to W[i, j]\n",
    "            w_delt = np.sum(cur_resids*H[comp_idx]*x_weight, axis=1)/np.sum(H[comp_idx]**2*x_weight, axis=1)\n",
    "            W[:, comp_idx] += w_delt\n",
    "\n",
    "            #find the current residuals\n",
    "            mod = np.dot(W, H)\n",
    "            cur_resids = xdelt - mod\n",
    "\n",
    "            #leaving W[:, j] fixed find best update to H[j]\n",
    "            c_w = W[:, [comp_idx]]\n",
    "            h_delt = np.sum(cur_resids*c_w*x_weight, axis=0)/np.sum(c_w**2*x_weight, axis=0)\n",
    "            H[comp_idx] += h_delt\n",
    "\n",
    "            #keep the principal vector normalized\n",
    "            h_norm = np.sqrt(np.sum(H[comp_idx]**2))\n",
    "            H[comp_idx] = H[comp_idx]/h_norm\n",
    "            W[:, comp_idx] = W[:, comp_idx]*h_norm\n",
    "        \n",
    "        \n",
    "        self.orthogonalize_basis()\n",
    "            \n",
    "        #recompute the best fit W coefficents after orthogonalization\n",
    "        for comp_idx in range(self.n_components):\n",
    "            #find the current residuals\n",
    "            mod = np.dot(W, H)\n",
    "            cur_resids = xdelt - mod\n",
    "\n",
    "            #leaving H[j] fixed find best update to W[i, j]\n",
    "            w_delt = np.sum(cur_resids*H[comp_idx]*x_weight, axis=1)/np.sum(H[comp_idx]**2*x_weight, axis=1)\n",
    "            W[:, comp_idx] = w_delt\n",
    "        \n",
    "        self.H = H\n",
    "        self.W = W\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "solra = SparselyObservedLowRankApproximation(rank=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.sparse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "solra.fit(scipy.sparse.coo_matrix(occluded_faces))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "solra = SparseLowRankApproximation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "wlra = WeightedLowRankApproximation(\n",
    "    x=occluded_faces,\n",
    "    x_weight = occlusion_mask.astype(float),\n",
    "    n_components=50, \n",
    "    n_iter=20,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904b81160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904b4dd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904af1b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6924b529e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904a9feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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vWMP72CnkzJbdqJ8G8N+gn0H0+yGEX8WjdbYm6Kcxrz56/3YAn4V+cPYX0T99qdCHu5+DPpSLGOM7Qwjfhb521XtDCP8c/TTpJ6GfFfVD6OvmXMtvo/8X7wsAvDWE8Nvog9UvQF+f6CuPtf85AHshhLei/1flFH29qXsA/C+pQH+M8U9CCN+LPo/y7hDCz+PROlvPBPCjK7/6Wqtlbuuty32NeOyvCo/+90U89kv1yI8B+EIA/y36bNdvos+m3IP+M/oc9CUXUpmUv4t+MPfyEMKz0Q+WPhl92YJfA/DleOxA9f9D/zl+QwhhH8tgeIzx7y1f/yb0X0b/cplHeyf6L7mno38a8wiWof0Y4/tCCD+Afgr9u5bnPUff996xPCfX60PoP8NfRP9rtm9E/2vnly6f5N0yMcZfXtZ9+qsA3hdC+Bfoj/9pAP4C+gD1Lwmb+k0Av7PMH15F/9l8KvpZir+50u7V6AdW/y6E8Avof/39Fegzltc74/Ja3rB8n1eg/945/itExBjnoS8k+6sA3r7MHP7xsv0z0D9lehv6c3C994o3oq879uMhhDegn0n77hjjv4ox3hdC+DH0uc0/XPaBCn2NtzsBfNcJ/2C5bjHGNoTwrQB+A8CvLc/1xwA8H/11928AnFTTzf4siKeg/oT/uz3/Q/8v1e8G8EcAZuh/hfdrAL70Gu3Pof+Sfh/6mkqXALwdfQmC421fiD6se3m57Q+gn9n4mSttXoMTauegv0G+fvl399HfaD8PJ9fZehmAX0Y/0JqhH2C8GcDXH9vmvbhGnSj0ZRLeir5WzgH6p2vfdkK7lyy38ZLreS1x/l++/Dt/eMJrH8ax+lontHnx8txcXn4eH1p+fi/DY2tOXes837V87dLyPP8W+l9r/siy/bOPtf9C9DMI95avx2OvX1j2jz9GnyG6ir4O1f8J4Pkn7P+3o/+V6Bx9raVXoP+V2I3U2ZoC+IfoBxcz9IO9rzuh/YnnIvX6jX7u6EsCvHl5Hg7Q/2r7xwE89fj+H/t7r1pu895j5+gD6AeoxbH2Af0Tp6Pz/mH0g6+t5d/5wPWcg8S5Pqq1d4hj9cOOtXsaHi00PF/2z3cv+9Xn3si9Ytnue5bbrI/3keU5+Db01+7Bso++BcDXnPB+nzi/13P8K3//s9A/6X9keXzvXfbd6ka25/9uj/+OismZma3F8snUF6IvBrrH2j+RQgj3of/HweNqYNyulmUTXgngeTHG+57YvTEzwJktM7tBx3Myy599A/pg9m+e9oGWmdmt4syWmd2oXw8hXEE/s22B/tcjz0f/K5jvfCJ3zMzsNPGTLTO7Ua9Bn3V6Mfow97PQV+R/boxxqJIXZma3HWe2zMzMzAbkJ1tmZmZmAzpVma3dt/8yfcyWz9PrA7eTk1ZceKyY0eXnEB+/QO/jzCbnkq93WUm3MS+mtM0ipJcmO+x4kWdlslUnjL3ZdvLQJl8HgBD409RAVsIoQ5N8fZ0i0sc87/iKJl3k57Yj7wMAeUiv410I56UQPqMi1MnX2ecDADn4vkShz7VkuUilbyt9jlE+Q+V4WH8CgCamj1nZF+WY2blT9rXu+P1U6v+kTZmv55qvsnTfVih9btby+8KiS38FK+/TrmkibZml7wu50J+2Kz4nZhxm6dfb9Hc8oPXLh4WVux463Eq+vjvjQ6Sv/fxc+gD8ZMvMzMxsQB5smZmZmQ3Igy0zMzOzAZ2qzFbMhd259lJ12usAQsvbdOXj1ud9/FuF9FhVyX0pv3tu4635mLLkmss9dkzrymxlJBOUgb+PohUuAZalUvJLGclaAbfuXz5KNqyJ6byhcv6VY1Zygkreh5FyXeRzVPJYCqW/sFxdK2xDymyRvtCS7BigZXmKTMjvkc9I6bdKlpO9j3R/Evr2Oij7wj8hCHd2Tsnmzdt0vhgAmpC+507iLt1GLnzP57lyj0qf31GhnDnlE/CTLTMzM7NBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YBOVUAeJHAOACAFSUMrFL4TgutKm7xNF8drhaKmeeT7G0gYUwncrqOQKMADtazoJqCFq1nQXtlXibSZ9GWyrkkB6yj8qEy4YJMP1kXZF63NGgLywvvwgPx6ikdKEyrINZIJfU4qsEruc8oEBqWQroScXq0wMG/DrldlolBNJpAAQJ7x7ZTkc1YKlir9UpnEoEwiYZT9ZSVA2cQzAAgd73PKZAn2GYWghd8VfrJlZmZmNiAPtszMzMwG5MGWmZmZ2YA82DIzMzMb0KkKyHdCBXkWnsuaOd1GO9qgbZpyStt0JKyfCVVulTrorFpxiEKV4TUF1+k2hPdRAsI50uFG5ZgVStC4xCL5eksqIgNaiFUJ97Lqy4p1TC5QJgWsS1hD/WtlpYCC9n8huLuWWt3rqVAehWukI9Wvlc9ZmXChVH9nAe084/uyjkkmrVARXAnRK/MpWJ6chckBYNGt52u8IGFxpT8pKw5Ecp1dzc7TbVxoPkLbjMIhbVNm28nX82x9QyQ/2TIzMzMbkAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3oVAXkM6H6eyBV20MrBHfHW7RJKwTjOlIhPggBeakNCaDeqqrtwK0LriuV9dchdPzcsUkZ7JwAQLemSsQj8jqrCA5onxHbjjL5Q6q4LgT+WfV9JRSdC4Fmdp1la6qUroSri5i+z0mV94W+wALyvE76+irrs/2VKpwLTdZxLSoTIRrh67VcQwV/ZUGUtrv55ypFzr8f1vE+ijav1rIdtreZUHl/Xe9lZmZmZjfBgy0zMzOzAXmwZWZmZjYgD7bMzMzMBuTBlpmZmdmATtVsxHy+T9uw2YZdNabbUJYFUrAZi8pMwybjsyrWMdtHWf6DzYACgKpNL4GQd3wbUZgNpJw7hi2nBABZx2fYsNmIHXldpczwY+eF7WvfRpjJRvqc8j7KrC9l6SC6HJJweSgzAFkbZQaa8hkWXXr5JwAo2nQb7fwrywvd/Gyrdc1GZOdO6bcK1i+l5bfWdP6bkJ7vqcy0DRn/DJVlvlj/lz5n4VZYkFm9yuzuec6X01Ow78W6Xd/zKD/ZMjMzMxuQB1tmZmZmA/Jgy8zMzGxAHmyZmZmZDehUBeShhKLJcj3INvgmcrboiRacZmFlJfy+oAuwAHVMhygLIVBYxTltU7Yz2qZo09vJO74vGfsMAYAsKaOElfOaH09X8M+oE8Klp0Vc2+QPEtyVlrPiAXkpRE9CrMo2lHA167tKmLxq0hNIAH4NAeI1cgtkwoSXINwrlaXYwLaj9Ceh/0eynbbgk6xqoY1yjdRZ+v6vBPGLjJ/bWeT7O2/5dxGzjtXa2PJc/RspTfi5G+fpiShnxsrzKGVRKz/ZMjMzMxuUB1tmZmZmA/Jgy8zMzGxAHmyZmZmZDehUJX+zGa8gD1ZBvuRBwLbgQcA2V4LT6aDlPJvQbbDwu0KpDp+fksAtAOQND67ni3TQOAjHE4RQLluRAABiRsLVSgV5pWq7UpWa9G8lIK9MCljHnUE5HmWiwzoKlEvV+UnqVqv8LoTfG76dcpG+Fyr9X0HD7cpEIeVabIT9Jf0lFvxemQl9uxlvJl/XJlysZ/KHco0wGfhnVAXe59h97qDl361lJvQXEoCfdfx9cuF9lIr3bHLBJF/f96afbJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAZ0qgLyECruhsjD1YwSSqyFKvMsAJkJ4d9R4IHaLpLgaORBwHk+5e8jjL3zIh1MzKIQXJxcpG0qUs2+VCp1N/zcslUAAKCc7yVfz4RK9UEIRQehWjf7hLrAJ2UoFb/Z5IIgBYR5f2KV6gF+vSrV4YNQ2jon51/pT0rl96I+oG1YMJ1VQQe0fpktyDEJK0IoIXplEkksSGX3kbA6SMX7/2xyPvn6QbVNt9GBn/8m8u8zNrlJubcrbZTVD8qQ7rvj/NY8m2kjP7etcP7LKExoIauv0MlR18FPtszMzMwG5MGWmZmZ2YA82DIzMzMbkAdbZmZmZgM6XQF5QWQheiGs2QlBfCW4W7XpkLZSQXgGHlyfdemw/qJbz8d40PDqy22XHp/Pan7M67Ax4kHkEQnzA8C04CHijc10Ne/N+grdhhLor2ZXaZt8LqyyQCgB+YxUVkbLg6O5sApDnfNq0U1IX4tKpWgEHvRmQXxl8kcQ2mQ1D9qzFQc64dzSeyUAIL0vseKfT6esyDHi97nFKB1MPxidpduYBf4+V9ut5OtdzfvTohVWaiATmwAekK9y3m8zUpEdAIrA+2VO2lQkQA9oK0LQsL6yIIcQ+FcmzozYhLv15eP9ZMvMzMxsSB5smZmZmQ3Igy0zMzOzAXmwZWZmZjagUxWQ70a8+m9GKho34026jVYKjnKsKvtOxwOd844H8ffrdAB13vBQ+t6MH/PVA54G3CPFrx9+hIco9/eEKttF+t8BozE/nlyY5HDhPO8v57fvSL5+duPJdBt3THmw/exZHpCfdrvJ16uGVydXKqHnLQlOCxXBO6XKuRAon4EEmoUgshIQjqRCdqz49VEKwXUl3A5S8V6pIA9+O0XYTJ+XGQmtA8Bhkf58AOByw++FDx+kK8Tv7fJr/mB+84nmRiiIr7QhBfEBACNyiyoLYeWDTGnD96XM0+H2acXD+mdH/P5zLnuE7wyhBOSVVSOKLl1lPuauIG9mZmZ2W/Bgy8zMzGxAHmyZmZmZDciDLTMzM7MBna6AfMmrFWfzdCXuvOYVwXOh+vheLlQrjun9fWTOw9eLlqcoG1Kte1bzMfPOPg/6PbLDq/8eHKTbXL7EK6U/eD8PSO7tpAPl5+7kn4/igXPpUC4A3HFXus3dF3kQf+8sDxrfuc2D05P8TPL1MufJ3VHFA/JbcYe2YZQQfR2UsDh7mfftVgjRd2R/FzlPnCttQsWvs3GT7v/K+8whVH9H+v5zacH77ZU9/j4fv8y/au7/WDqAvbPDw9exE0LRZPJNWfF78sYGP56NDd7nzm2l+64SbG9a3qgSgvZsdZAQ+DHPGz5ZIk7Tx7yR88lEyjWvrODCgvYlmSh0Pfxky8zMzGxAHmyZmZmZDciDLTMzM7MBebBlZmZmNqBTFZDPD3kFbZAK8hBCuYsiXfkdAK40PBi6t0hXdr864+HfvcObH++2PG+L3QMekNzZ4RWC9/fSFXdnB+nXAaBkZZMBjCakav6Mv8+YbAMAdq/w0G05Sgctq5J/hmXJw5qjkveXBdlOkfHOsD3i4dIsT/eXceDnbRH5+W8ivwU1XbrNYcvfZ5TzSTEtmayihHJzoVJ9FXjf7Uj5ceW8PTg/T9vsL9LX4sNX+bW6y+fE4GMP8PN/6aF0n5od8m10Qmn36VY60F/UQnl4QSasVJKREPfGhPe5sTDHRMHC+KOCnxdlNZOrdfr8t5Efs3Sfy/l4gq1gMSv4BCqVn2yZmZmZDciDLTMzM7MBebBlZmZmNiAPtszMzMwGdKoC8jHnu1NvpkOfTSmE38GDoztzXqH5YJEOAyrh931e8B4Z2Uzk2XcUOQ8dViO+v/MZq77MP8NCCIuzEKvyPpVQCXqx4KHPSLKYsxnfxs4uP7csLAsAI3LupmMeHFWqqWdjUlm54CFvJSyeQ2hDwrBKcH2U8f1tYvrc1h0Pi5cZD3FPIq+Q3ZJq3Ycdr9R9UPP9fWQv3WbB58xgNuM3oKbm/ZJVf8+Fe9jOw/zcZmTyQSWs6pELpd2zTKhyTk5LK1SHD6QKPQC0HW9zdjO9M6zaOgBMSt5hipB+n3nL++1CWCkgDzzcXggTZ9bFT7bMzMzMBuTBlpmZmdmAPNgyMzMzG5AHW2ZmZmYD8mDLzMzMbECnajZiO+KzBw6nF5KvNzlfuuOgSc90A4BamAVSN+k2B3O6CbTCyhBzPpGKCnwyimQ+T+/w/h6fXjka89km40l6DYoRWUIHAGYzPjNmY5OvdcFmQRUFP7nzOZ+NdTDjx8RmpiozYBthts+kSJ+XKuPX0DjjfSEH/4xGMb0eTJHzmcOb9RXapsnS5+Ug5zMAF5H3p1ZYxuUgpu+FuzU/5p0D/j6H5B4lTPrCfMEbFcKSVnfclT7m2SHvK42w1M72mXTfnQv3jf1dfnOvhZnOh4fpz2i+ya/VouCWvRTLAAAgAElEQVRtpvxyRdOm72PKLGY201ChzC5uOr4vLZldDAB7IX1Nb8Q9ug2Vn2yZmZmZDciDLTMzM7MBebBlZmZmNiAPtszMzMwGdKoC8jHjgTYI4TmmynkA8syYh3ubLh1SjUJALwjD3XqeDqAqy/XUwnIZTcM3dOGO9DHfcScP7lZCWPbOC+k2G2Q5GQC4ssf7yoTPp0BLTt1+Or8NQPuMlPP/yE769cmIH/P+TFjepkwnakfCMhdn4yXa5szV+2mbYv9yuoEw+0O5tyw205NvijE/5vvD02mbOvJAc92l9/fSPk88P3iZn5eSfAOwCRkAUJb8fZ5ylh/z9jTd/xcN30b+Gfz+c2Er/TlePeQTtR6+wo/54cvCWkfE/h7fxgMP8vvGmTPKV336w65y4fuZf0QoyPJbbeTnthaWVFIC/cwCwheEyE+2zMzMzAbkwZaZmZnZgDzYMjMzMxuQB1tmZmZmAzpVAflixqu1llU6vNjkvILzZs7fpwg8gLpDqmgfkmA7AOzv8+D6/n46JLm3y0vMK0H87W0eBvzMT013GaXi9Ece5G3Ob6XPy8XNA7qNccXDsvNaqIqcpw/qDM/TSgH5K3t8X/70A+nK1eMJD46OKv4+4yq9nfNTfp1Nmqu0TXnl47RNmJEZCAs+mSWevUjbVHvpQH8n3FvKEQ8015HfdiMJCV89UFYK4J1OmVDBjCq+DRZ+B4DpOH3Nj7v1LINxbpzuT5XwOZ+dCvcNsgoDADzzrvS9+8MP8++hhx7h3yE7O7xfLhbpaz4TJpnceUZYTYDMugiBb2Nc8OPZzPl3xGaXXlmiC8qkPY2fbJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAZ0qgLy2Wyftsmn6TDstOXBuTjlQct54GHxK/vp0/fhD/OA3uyQV6Xeu5oOdC5mfBvn7tiibZ76ZB7ovHMrvS9XZ3wbO1d5oPPBaboU8bzmqfRHdpVK6bQJ2KoFd5/jfY71FQBoWr4nFQm3d0IouijWEzRmspb3S9R8ckdklasnvC/U23fQNi0JNGct39epEMq9Um/TNodtumMqEy62hPvc5iS9odmCb+PsJt+Xu86kJ3YAQE6C0R+/ysPidSNUds+nydcPSVAcAOY1f5+F0P3vnqYD2ltP4pN87p/yD+DDD/Ab3e5++gZUCwXx2WQigPfdjZJfZxsFX7ZjGndpGxaAn87Tn8/18JMtMzMzswF5sGVmZmY2IA+2zMzMzAbkwZaZmZnZgE5VQB4dTwiPLqcrTncVD7Y3JQ8dorpAm+ySLGzX8iD4wS6vfj3bS7cphZT3nXfzEPGYZ9txUKe7zFwIqGY5b/OxB9JpzEdG/N8JB4c80Xn+HL8E7iFdocj459zxJlKgdnPz5i9ZljcHgIvb6WsxC8IBKUbpsDIAYJ6+0Lqtc3QTTcHD1fPxGb4vRA5+DxvnPADM3HWW94O92c1PyiiF7qaEoln4HQC2qnTo+UFhVY9H+KIF+Pil9AXQNHxf65r3/3vu5BfapTmfuMSUBd+XqbCyRJ6nP+ywpnk1I1L9/WzBP0Tl/pMJ44myTX+35sKkGJWfbJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAZ0qgLy3ZiHuDMSls1mPBTdZUJwNPI2F8+mQ3qHz+DHoxhP08n1ICQXz5/jIfrpiAdDMxJ0PTflgcJPfTqfxLB7mD6mTAhrzhf83xITnrnFqEx/zntz3leEuRLYVrrLRvrAlUBznvHP+dw0HVa+WF2m2wgLHlCNwgcZSKI/CtdzueCrU0QSEJ5XvFJ30QlV5pVjRvozOj/h22g73qHYraNu15OKnjU8oD0p0tfrHVt8MlGW8XvLjNwXlCr0nVDB/9wmv+jrNn1e6pbfw5Tg+pkNYYdJd1Heh30/AECVpb+jJ5Ffq6PFHm1TCOH2cpYO48dMmE0k8pMtMzMzswF5sGVmZmY2IA+2zMzMzAbkwZaZmZnZgE5VQF4RDtPhuVjwIHiIQqX6jIfrzm/Mk6/XF3j6Os946Ha+SIcOlYrHXeRtZguegNwmxfenJS+DfvdZvi8Xt9P/DmABYgBoI/+3hHBa0MX0eZk3/H3GFX+jgzk//yXJayrVvM9t8M9okqfbKCHWIFRwhhBAbTfPJ1+PhbD0gSC06eCuUpE6CJMP8sgn8QQSNJ7mPCw+KXlY/Oosfe6UiR258E92Jei9V6fvl1XOz9tdW2RZDwB1t77Qc0ohVDmPYNc8/4rOhQkXIyGszyj33M2Sf2+yFTekSSa7D9A2MRfGAuSa7oRtqPxky8zMzGxAHmyZmZmZDciDLTMzM7MBebBlZmZmNqDTFZAXwrJxlq5sHSoeYi0XPES5VfAK2bMqHUCtN/nxbI75eJcFsA9mwjZ4Jlqqirw7S3cZJQiriCSUzgLE6r40QoVsdl6UitPK+VfUpHtXQp5zKoVYSVhcmGSyGG3TNnnNg94dCcArQXy2DUWd88B5LVQw56FoIHZkpYDAO5QyWYUF5PeFe4syyWRjLFS8J9d8IawUwMLXShulUrqijjcfxFfOrdJGWTUiJ4H+KufX2aRITxoDgK18N/n6eG+HboNNZlFl5P7TVmRG2PW819q2ZGZmZmaP48GWmZmZ2YA82DIzMzMbkAdbZmZmZgM6VQH5drRB22RNOvQpZAVR1DwgX7Y8uLtVpYN+rRJ+b/lHcFCnQ6yjgr/P7iEPax4KFeQP5+n3mi2UUDptQikhViU4uo59yYR/shRCVnZzwsO9LOh6fsoDqmdKXv19mqWvkTryIHhb8b5djoRK9JEEmoUPusv4zIE2T19nMfAPuo78fTrwzsAmgGRCdfLz5RXaptlIH1MXeUB475CfF2V1hEWTPi9VwT/nIHxGrOK9UjVfuf8ooXS2nVyYCKTsy1Sovs/61IisKqFsAwCqLv3dWs6u8vdp+H2uE04MC9pLq2CI/GTLzMzMbEAebJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAZ0qmYjZov0UjwAgPLml93I53wGVDni+zLJ95KvN7kwMynyGZhseZVJwWddFGSmFQBUcz5LqiPLiCiz+4IwSyQjs3CU2X0KZeYRm700HfGDHhW8zWbJZ9hUZFbRRibMNOzSs2gBoJqnZyNeHV2k25h0wowhYZZg3qa3E4X+FJWlwMhMtjbw22Uj3FLrjh/zJrm35OCzy/LI29xJJpVOi026jUtjfg87rPn5Z8tesetQxWZ6KvenIuezBAthNmKZp29Ak4LPAFSWLqvI8lv9dtKvl0Hoc4Hf56az9CxZ5fs5NMLxCMsLhTp9b/FsRDMzM7PbhAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3oVAXk80Me3MXGVvr1PaHU/wFvk0/P0jYVWfZnNB7TbWwJ4XamiTx8OhaCltvC8iptJAH5yMfvbcfbBLLwkrJERUf2VVWRoOVmyZd2KgM//6OMB8pzpPelavnEjo3DS7RNU6T7Lvt8AKBshAkvArpMjvBPRmWpnS5L9/8u8OusEZbfUq5XJu94QLgSlhwbxfQ9rKzSk3MAoJryNsoyRrMmPYmn7vh5Y/cnhRI4VxTC0jVFlm4zzvm5VZbIUa5Xfs/l25gEfs0XCx6Ap8gSXgCQzYX7D7kv1CMy3rgOfrJlZmZmNiAPtszMzMwG5MGWmZmZ2YA82DIzMzMb0KkKyIcDHpCPZbrkcaiECvMzIcQnVLFtqnTlZCWgCiErG2I6mNgIVbiVEOWGUBW5QzqA2gkB+Sbemm4nhbgzHlyvQjqkOup4f8oir0TcRN53S1KVPQjBUUVNAvJF5OdNCaUrMx1asi8KJdzeCVXmmUiuD0CbuFGTvjCJ6QrzANAJ539EJjFMF3wyUZkLKwUI578epe/tnfBsYNbxvsI+oyh8Psq+KFjFdWVFCKXPKTKk7x3KPWwi9JeMVWUn33eqMOPXSLt1Pv26sPKKyk+2zMzMzAbkwZaZmZnZgDzYMjMzMxuQB1tmZmZmAzpVAXmw4ByAwCon5zwsrlSfzYUq89kkXWU+K4VAYc1DfCwAnwdeTboQKpgrIVa+DaGCvFBBO5J/B0jHDH7MUiXuJj3RIQjBUVadHADKmgeNGxLYLMm+Alrok4Xbi45Xtm6FiRuQVlBIB2aj0G+jEMRvsvR5USZ2KBNElDYtadMGvi/TxRXaJpB7btmlK8wDQCZcQ0q4mt1/lAkM20JYvCXXotJvlfOvYCs+hI6HxZV9Uc4/O27lmlfuP+z7N+bCuVWWEKmFe9R4M72JNUzOOeInW2ZmZmYD8mDLzMzMbEAebJmZmZkNyIMtMzMzswGdqoB8XPBAG43FCSHKOElXfgeAWPIQcdalA9i0Ui60cHVJ2jR5uvJy/z58UkCpVLxn1ZeFgLxS8Z5tJ3TK8fDAed7yPqcEgNeBhZUBYEz6HFvVAADmJW/DJg6wkDGg9QUl9MyC00oFbWU1gXUIgb+PUqGchfFjxs+tcv6rWXoikDKxIAh9TrrPtem+3QmTnzKyDYCfl25dVcOFSuhZTF9nyme4jhUWAKAuJsnXCyX8rmDHJBxzFK4zTNPhdwCox9vJ16uaTxBR+cmWmZmZ2YA82DIzMzMbkAdbZmZmZgPyYMvMzMxsQKcqII8Ld/M2s3TF9VjxsKDSph0JIXoS7lWC1UoAlVXlLYSQt0IJaLNjVqrQryNoqQSeleNR2rAQaz7nIUplgoISqG1H0+Tre+MLdBs5CdkDQEb2V6lIrUwQKYRJDKxqvjBtBqwKPcAraFc531dl4sA88KD3vE23Och4+Lco+X2hGKW3U+0/wrdBWwBdIaxaQO4t5cEO3YZ0nbH9EALaQQniC4F+Vi2dnRNAmxSgTC5g5y60wveZMuGFfW8K21A+54aE3wF+/y/ier5bAT/ZMjMzMxuUB1tmZmZmA/Jgy8zMzGxAHmyZmZmZDehUBeSbjTO0TVaRaulCyLgrhRC9ENKj2xDC7woldM7kDQ/3sor4gDApQBi/50IomoVUlfC1Qgm6FvskmKtUmBf6pbJqwc6FP5d8vQ58Gzn4MTPK5A8lxFos9nmbkJ6AkDVCiFUIPS9IoJZNGgCALOf98jDj95/9Jn2fO2z5NprsIm3TTdPX89n6kG4jq/mElyD0f6wh3K5cz6Em/UW5t6zp3h4LElxXqqkrkw+U1RzKdJ9rhe9NCB9hRyaiKJMpgnA8yrkryQoKh5t38vcR+cmWmZmZ2YA82DIzMzMbkAdbZmZmZgPyYMvMzMxsQKcqIC9hoTcht6gECuuKV5C/VdWKgXRgk1XkBYCMVCruN8TDpbkQhmWUsGwgoWclCJsthH1lYVkAoU4H+uOMh4jDSAg0n+FhTBbSzsGD66Oah9JL0qYgKzkAAIR+Wexd5tshYfxwyI8nTrdoG9bnClK9HwCqgn/O2YgHsK9UfCUApgj8fRYhvb81qTAPALlwb1FWamArMeSHu/x9hNUcMCcTdHJhQlLBj5mG3wGENn3/jyXfF+U7hFWqB/jkp7imZzNsBRFpJROlz0kTZ9IDBmW1DZWfbJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAZ0qgLyUiVoQgrFVZObfh9ACBRK4Xee6G/zdKBfeZ9WCaUL1a9ZoFDZl1z4jFiFciUgL1lH1eoJn0zRnr2DtllM+AoKeZs+d+cPPkC3Mbp0P23TffBPk6/Hmgfx8y0erm53edC+IW2aAz5BYXTHedqmuPvu9OsbQsi+5dfQVJgssXXHU5Ov1yXvc3XJ73Nssoq0ekVOVvUAkIOvGsEqmCuh6GwkHDObfNMI9xapsjsPyNPJWsr9SahmH1p+vWZs1Q5hG8qqKex7U1ptQDj/0gQ24a3WxU+2zMzMzAbkwZaZmZnZgDzYMjMzMxuQB1tmZmZmAzpVAfku54HCjASju5KHTxVSFVsS9MuEbbDwO8BDh3XGA6pZxs9trVS/JqFDVh0Y0M5tIJ9jEPoKhKBlVvLzzyr0t2MenJ6Pbz78DgDT3YfS2/jge+k2Fh/5KG1z5d9/OPl6fXDzk1kAoJnx7TTzdDA3dvxz3rrnLG2z8eDDydfLTWEixCHv//mEX2ejpz2Yfv0CX22g3eDHvI6Adj3i/b8LQsXvLH1fUELeUbgvsIC8EmxXAtrtiPcXJfS/FsL+KiuRMMp3nhK0Z5QJUsr3DO3fSlhf5CdbZmZmZgPyYMvMzMxsQB5smZmZmQ3Igy0zMzOzAXmwZWZmZjagUzUbcTE9R9uMr348+TqdXQOgKad8Z5QlEMhMhizy2RCdMNsnkiUzlCU1lBmLijymZ5Ioc0GV80LPvzLTUJkNOuJ9gc2SPZzwpWAOCz5ja2NxhbaZPPAnydfrB9OzFQHg6vv5bMTdj6X35epHduk25jt8pmEo+XXWXE1/jvmE/5vx4NIBbbP5UPqYyokw0y3jxzM5z5cxqvf2k6+P70jPVgSA8ilPoW3iVnrGYjfh+wphNmIjLB20DsWML/8UatIvlWVelJnzubBEkfA9w7BZ8YA405DsizRDX1muh8zAZDPeVcrScWyJwHLO73MqP9kyMzMzG5AHW2ZmZmYD8mDLzMzMbEAebJmZmZkN6FQF5HenfAkKGlhTllEo1hQWb9IByGKRDrkCQDPh+xKRDh0qgXMluNiBhyiLLh0o7ITzP6946LYi22HBRgBohVBuKyxjNKvSAeDDICzjEvmllpf8vGxN0vtSnONLtJz7LN7npndfSr4+2voQ3cblD16mbfY/zoPrswf40hxMPhL69ujwpt9nfIb3uawQwspkCaJMWPIHwrIz3Tjdd+sNPmmpEyYlHVbbtM2IhLjLmp+3rOah9FCRpcAWfMklhbQsGWmjhLylfVFC52TOkbIvSlif7YvSn/IFv1Yz8v18q/nJlpmZmdmAPNgyMzMzG5AHW2ZmZmYD8mDLzMzMbECnKiC/CDy4W4/TQcu84eHGVqn+K4QbaZCv5aH0vOVB73mRrnIuVcoVApJlxwOFRZcOKytBfOXcNnn63Codty54WHmv5IHyOqb3Zd4JqxZEHhxtM/455nd9RvJ1XsseyIUA8MZT08H18ZPvpts496GP0Db7H0sH8QFezb6Z8/6kVH9n4fbNe/jZndxzkbbJN/iqBfnF9GSh7ix/n/km39+aVH+fl3zyR53zsD6b5KNsRwl5B/L9oBCmLyC0yveDMPmJ3buViU3C99k6KOH3KDy/Ydsp2vQqJcAaw/rku6ipeP9X+cmWmZmZ2YA82DIzMzMbkAdbZmZmZgPyYMvMzMxsQKcqIN9EHvSri3SIsgs8FNdlazpsktdsS/4+UdhfViFeqA28NiwArwRhFQsyKWBeCMHdjAdU91u+nY78myRGIfzb8r7QdLwv7CF9Xi7ffQfdxjTjVds36p3k65sX7ufbeOozaZvN3XT4HQDOf/SjydfbA15NOh/zvpCfPZN8PYyFqu13PIk2aUnVdgDY3U5PQFiUPGQ/K/iKBC2Jg887YbUNUnkcAEaZUNk9S2+oyYXAubBSAAudR6GCeSZUMO9KYX9JiDtEfnI7YRUMRcYmPynh91y4z5HJT8okN+lbRjl3ZBJDQ8Yb18NPtszMzMwG5MGWmZmZ2YA82DIzMzMbkAdbZmZmZgM6VQF5BQuUN4VQqTvwww5BCSamX1fC760Q1g8kgapMCig6Xqm+VYKWJI3PwvwAr4gP8GNagIdPZx0PN7ZCZfeOxDEzJSEsuDLj+7s3S/eXtuOh6NmCx0s3J+kP+sLmp9JtPPmOh2ibSbtH22w/PV2JfnTlAbqNrhL6wigdXFcqUh9s8AkKhyWvcr4b022UVQvqOb+3sMk1yuSPcZEOVvfvI/y7nhVTz/hUIKWyOEhV8EXFr6Gq2OXvI2CBcuXevq4VUYqGTBwQ+r/yHcI+o1aYCJHVfMJFVvPvvKa8+VULVH6yZWZmZjYgD7bMzMzMBuTBlpmZmdmAPNgyMzMzG9BtF5CnVW6FgGQWeZtO2E4k4Xapmr3U5ubHxE3GA7XKvrDh+SJMxD1KY5Wta2G1AUUWeAAyJwF4pWp+mTf8fYTPaEFCrA/zgux46GFhskSbPubtbR5ifcpdT6Ntzm3y83Jh+tTk6xfPXqLbUALaShicqcH75UHDw/qXDtMh7iv7yiQf2gTjKt3/pxUPViuTiTZzvmpBRuL6yj1stNinbYo23f+VSUuHk3O0TU6+qxTKJKtGCKWX4IFyVi1dWXlFOXcZCZ2z73hVV/L+wigTvuRtrW1LZmZmZvY4HmyZmZmZDciDLTMzM7MBebBlZmZmNqBTFZBnldIBIMR0m6I5pNvIMx7AmwtVhFkleiUs2JEgOMAD2EoV9CiMq+uO728V0uHSKEw+UAQSli3Ag9VCbl3qc6PAw6XMYccnDpwb8xBxR0Lc+zMhLFvxz2jv0iz5+u5Vfk52dnhA9fx53mZzYyv5+sUz/FpVQtwbo3QYdqPi942GLSshttmfp6/p/Rnv3JlwKU7IPIcyFyqPC5NMFNPmavJ1aQKPcNE3ebrPKaF05b7RCJXQtWNKUybohDUGvW8WC8Cvq2q7UkG+I6tGrOPzOeInW2ZmZmYD8mDLzMzMbEAebJmZmZkNyIMtMzMzswGdsoA8D8ZFUha5qIWQcc5DxLMqHcoFeHiOVcoFeMgeABpSLb2OyjaE6r9rqKxfZEKldOFzZiohtK6E6HOlTUy3qYRJGVMhLFsXvM14I33c21U68AkAZzZ4m4+QNkoV+nrBQ7kPPcQ/x4ODdP+fzYRVGITq8NNJ+n0ubPNriFVkV5VFOoB9dpO/T5ELld1J6F8Jv+eZsC+BTy4omnRfUCqYQwiusxC9VgX91gTOlerwyveMsrIKC9HnpPK+2ibr0vfTrOX35Kzl/SkW/HOMGfsOdwV5MzMzs9uCB1tmZmZmA/Jgy8zMzGxAHmyZmZmZDehUBeQzIYzJKsizwBsA5HW6OjYAVA0P2rdVOryoVPZVqr83pI0SfleqViv7ywLyUQgit0JYc0QCteNmn26DBW4BrVpxudhLv88s/ToAtKMpbaM4W4yTr+9NL9JtjC7cxduU28nXz5/hYf4dflpwOOPnv2nS1/zB4ZoqTpN+uV/xvl3kvM3WmAeAx0W6zTjnQeQy4+HePKTblEGYQCK0Gbf8emVKYSKKoi7SqzkUQshbCdEv8vS1ui7KPUxpw8LgSig9b/h3KxOE94Ey+YxUhweApkz3hUzoCyo/2TIzMzMbkAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3Igy0zMzOzAZ2q2Yjjjs8ApDMmGj57QJmxWJEZaAAwLzeTrytL8RTCTJ6aLNejLLOjzHpUZhIGthzGmpaXYMv+sFmpAFAtdmmbcv8ybZPtptuEBZ+BkwuzEeM03Z8AICdL+pyt+YytcpPP0tw6fy75+u42X87qA1fO0DZ7h7zvXiUT2ZqW94WMLPMFABMyeSwX/mk6Knjfnpb8HrVVpj/HTFjyaiPj97BJnW6jzABU7rkQzj+byaYs41KP+DXEzMh9HVjfMi51rJKvV+DXatnxNlnH95fNNlRmGma1sC/kfYLSnwQhF465S+9LKyyzpvKTLTMzM7MBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YBOVUBeWS6GLbUw6i7RbQQhaBmEQOGYBLBnFQ8RRyE4Os7SwcROGDN3QvhdOf+MEtafdzxEz/ZlVPClGIqSBzqLjIfosXc1+XJcCJMydq7QNmHMl/coxumgfSzTgVsAOCNMCtiYpsPt5ybpAD0ATC48jbbZbfjEgd1F+rzsHAr9SZhQwZbRyTO+je2KB8rPFLzPjWN6spASiq7mfMLRZOdj6QbCfVAJv3dkYgcAtFX63q6E3+ej9DJTAF9GZxH4virB9Sjcl9kSdcrSQbnQJuuE7zwS+s+F/qRgy/EE5X06fi3mwsQlNlmuna5vySU/2TIzMzMbkAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3oVAXkldAnC5Qr4Xcl0JkteNC1ytPB6boQAs8dDzfOSBi8FKrQN0I1+0YYe7PgupBD5lXoAczbdOj5Ms7TbTQTITgd+DGPy3Rgtrz0UbqNsMsD8mjSwVEA6C6TCSAdryyuqC7enXy9HD9ItzE6w4P4i8lZ2uZwnA49zzb4ZImDjgfxq5A+/2Pw4G7V8vvG+CB93wCAcpEum69M4MlnPIgf5mR/c34NdcKkjJp8hgBQV+nPaFHwz7AWKn4vYrrNbsOD+KNMCKULVf4nIX3+2SQsACiEKv9KWL8g33lBCdkL1d9Dm+67Yc6D7ciFFVGENuwLSxpPiPxky8zMzGxAHmyZmZmZDciDLTMzM7MBebBlZmZmNqBTFZAfz3ZomzZPhzFD5KHEIFSWBaksCwDlQTr0XArVjLuMfwSjJh3M7Qq+r4vAg64h8OB6FCrRM0oQv+3Sx3RlzsOyOyFdkRoAdoUq/9Nz9yRfP7t5J91GNd+jbYqaB7DLqw8nXw8HPFAbZzxQizoddFWuobLh4dJsW6iEXqUD5dWUT5aYCsFpNllCqeZdzfn5z9s1TASiWwBaEjgHgFCmJ/F0hRB+H/FraH9ygbY5DOmJDsokh7rm90I2P2reCpOJyP0JADYKfp2VMd0X8ob3lbwWvs+EiUAZ2Y608goJvwMA2L1DmWWlECYcFWSyijKeUPnJlpmZmdmAPNgyMzMzG5AHW2ZmZmYD8mDLzMzMbECnKiCvqMt06HmxcY5uY/zg+/kbCQF5FOnQ+WjGq4bPx7yCNkjFdaXyfpHxavaLjodhs5AODOZBCEh2PKw/j+k2h7USYuUx4r0ZP+YiTweAz47P0G1sbPCw7DTjAfn8XDqkujkjFeYBlHW6OjnAK5QHIcTKQt6A1v/ZJBJlFYBFzidLsJUN6oyH7BUx8P6yyNPXaxb5daYcM1vBYhZ4KH1OKrIDwH7D96UmofOmE6qgZ4ITOfcAABGHSURBVDcfaK5b/j6TgofFqyBMqCCTYoqGh98zoWq7IrQ8UE6RiTWAMLlGuJ4VQQjIx5Del6xY3xDJT7bMzMzMBuTBlpmZmdmAPNgyMzMzG5AHW2ZmZmYDOlUB+abgIe6MBHcX1SbdxliochsWQuiQhCSLXKmIz8OlNakEXbU8RFmRiQUA0AY+KaCN6TZd5ON3pVI9CysrFjXfl9mCh7jrNn3Ml8hEiR6vsj2ueLj37DQd+tyqLtJtjCoeHGWfURmUgDCfuNFEfguaden7QpXx41kIkzIO2/S1WGX8mItCCL8L+1KTCSAsTA4ArbDaAwuDLxphdYqWv0+R8+u5IxNaqoJfH2WutEnf/yvyOgCMCyH8LvR/tiqBEloPSkBemKwS83S/DEKleiWUTimhdKVSfS5McsvS50WZfKPyky0zMzOzAXmwZWZmZjYgD7bMzMzMBuTBlpmZmdmATlVAXlE2vBI3023yqtXZ/lXaJnTpwGwmVNPNohC6bdJBy/mIV0HPwQOFGXi4NCIdKJwL4d9MCMizStCTkp+3PBNCuUJAO5Bw6SO8q2D/QAjuljzEev5MOsS9MeZ9YSoE8QsSNFZCxEqVbWWyBMMmbQDAouOf836dPnePCFXQhcL6mAkTN/Zn6TYzZf6OkA+uyUfEXlcJtyic20yfvIKEmQEAwjGXWbrvbhQ82L6Z79E20wW/MWQsAC90KCVEH0s++awr0h9SMRe+e4XPKBbpCV/sexWAFH6Xwu0FmaCmrCQj8pMtMzMzswF5sGVmZmY2IA+2zMzMzAbkwZaZmZnZgE5VQL6oeQAvb9PhRaki+8Y52qYileoBIOynK8RHISyY1zyMyY4pEwKFVcvP7SLj544phCr0WeAB7RGp0DzKhVCoUEF7u+KB/gf20oHOhlThBoCq5G0ODnkY9pAUcZ4IQWR+9oGOnLuDBT9vbDIFAIzym09g78z5qhHKigSHdbrv7uwrfZs2wQG/5LEg3bsTPkShaDiaJn1eFjU/b5nwT3al/2dkQsuo5Pfk7YpXOZ+QAPxWxoPt0wVfHaRUvs+a9P7SAD0ghbjjGtq04w26jVwJt7Pg+qFwzMr3s1CJPsb0heQK8mZmZma3CQ+2zMzMzAbkwZaZmZnZgDzYMjMzMxvQ6QrIk7AgALSkym3M+SE1ZBsAUOZXaJu1hOdIQA8Aso4FBnll6zbjgeY88HBjS8bnRca30UV+3ligucp4Ce1x4P3pMOPnbjZJ96m24/1pJFSHZ6F0ABAKxPP36fj7FEU6gLrolLA4D1c3Ql+o2/R7SVXbG76/LFA+KvkbKfsyroSJA+Ry7YT3UfaF9ctFw/e14VllbE/5zmyM0hs6Ozqg29gseCi9DOl7x8b8Mt+GEH4PUQhxk6B3J1R+h/B9FnNhQgu5AKLwPt1ki7Zh4fb8cJ9vQ5j9EUfpiU0A0I3S9/9GOR6Rn2yZmZmZDciDLTMzM7MBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YBO1WxENjNDaROL9Ywf6+lZ2qZqyIy4dS2jQMbEQZnRKMyMKcFn+C2QnpFSBb7UQgN+zDlZ0mckzDTMo7CMkbC8UE5m1W2N+fsshNlwXRT6ApnUVRZ81ldQZgl26T6nLPkzF45ZUeXpvqvMEtyoeJuaLLs0Fu4t7LwBwKwWttOmZ1spy/W0wqzTnC6Rw7cxHfFze2bKr5GN8uaX6FLuC5NmN72NGV+KJ1vDdxUAaTY60wmzBIMwNbUt0jMfI5nF2Tfix8O+87JaeJ9GWPNKqBbQVekZi8ryfyo/2TIzMzMbkAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3oVAXk25KH0ZoyHWiblxt0G3nHw5pRWFIjn6TDmKEVlq4RllFgSxMoS0d0wnI9WcYDnSOyvxHCMgpCG7akRtHxEKUyKWARtvm+sPOypqvowhYPlx4u0uHSggSeAWBBwtcAMCrS+5LzTdBgOwBMSx56Zks3Kcs/ZWTCRS/9QSr9thHepsr5Z1QIbRhluR66H0J/ElZO0fpCQQLygYeip/VV2oYF4LOW98mMTY6CNvlJCbcz7DsR0CZRseXnFiN+r8xLvvwZ3Q/hvCnnX5mgsL91d/L1TtgXlZ9smZmZmQ3Igy0zMzOzAXmwZWZmZjYgD7bMzMzMBnS6AvKkgi0AtFl6l+ucb2MhpHun8QrflyodBlRCfEpwnQUXs44HOouGV1aOQrhx1KXD+OsIvwNA0abbKOH3qj6gbbbG/PwfZumJG20UjllJlAuqSfq4F60QLs34vrBAc1nxwC0LtqtttHB7Wp7xbYzI6gfKvkpV25Uq/+S9lOC60i870kY6b8LEmjLnk4WmefrestHx8HtO7hsAUM7TFeSViU3KrAAl/K6EwdexLwth4hgThdU2moJPcmOfUSvck8t6n7aZC4H+nfKO5Ot5EFYBEPnJlpmZmdmAPNgyMzMzG5AHW2ZmZmYD8mDLzMzMbECnKiA/rzZpGxauUyrllkL1cUVNQod54Ke3rnj1X1bxPgqVcjOhar4SLlXaME0uhCjJ/gYhIF8Lgf9W+Iy2i73k67OMT8rYa3gb5V8+DamWrgTkFS15n7bhe6uExZXq46Mi3RdohX8AUdkXEkoPgYfScyG4vq7QOZMJAfmC7IsyOWGU8Qk644xP0JnG9HVWNXzCSyGspkED8GsKvysTvmhAXlgGoBUmWSkTxzoSgFcmJeWRf8+0+c1XzVcquyvHfNClv38XHf9++GTaoucnW2ZmZmYD8mDLzMzMbEAebJmZmZkNyIMtMzMzswGdqoB80cxpGxaAnyx4lWElXJcJofOGBCDXEQQEgI4Ec5URszJxgIXSAV4VP0CoLF4KFbTJ/rKq+oBWzV5pw6oIb+S8mnEbeZ9TwphVSH9GbSEcsxCcZrlcFqAHeHVyAJiWPFw9LdJ9TjmeTthfFoAfCVXQizVUuwe0ED3DY9NAQfq2UkFbCb+POx5uH9XpgPxotkO3kbW8P7F7SycE29dVHb4u0pN4lIlAyvfMPOcTsdg9qgr8+zkXqu/XZEUO5d4OYR7QIvCJWHWd3lDdrWfCEeAnW2ZmZmaD8mDLzMzMbEAebJmZmZkNyIMtMzMzswGdqoB83vFwIwvPKYHCYsEDnSz8DgA1qYSuhNJZ1WqAf0hKEFOhhMWZvObnVmnD1KMt2qYpeECyE/69kYOEiIWqyZt5OvwLAHMSHAWAJqZ7g1LxW/mcWaB80fJbxyjn12IlhM5ZhfhMmJShYAF5JYhfFcLkD+GaZ22UfquclzKk77kFmZABAGXHg9Nly9sUZHUKLfwuVFyvyMoSQkC7FVbBaITgOpuspcyTUMLvdeT70pCAfL6GVQ0Uc/Dv3lYYuuzVfAWReZueRsJW7LgefrJlZmZmNiAPtszMzMwG5MGWmZmZ2YA82DIzMzMb0OkKyDdCcL1MhwHbjB+SElxXqsw3WTpcp4QSx5FXVl5U6cDgWNjXsj6kbTJhcgEThArCmbJSANmOEoStSx6Q3Gyu0DZduPkJCGXkfbvK+f6yfrkQQvaLyGuLs+DopOB9RQniK2FxFkzPhBQxq5Tet0kHsJWAvDJBQVlNgG1H2Rel+jub3KEE28uG31tY+B0Q7h1CcL3Lbn6ST1Nt0DZKlfNGCNGz/q+E7BdQJtbwPsf6ZUYmCgFipfqQ/o5edPyYZx0/5r1amOTWkgl3N9+dPsFPtszMzMwG5MGWmZmZ2YA82DIzMzMbkAdbZmZmZgM6VQH5TAhXB1KVWokytyTYDgClENYP5Xby9Ufqs3QbG0KV84wE+mMhVJPuhHPb8rCyUuWfEsLtoSVVwxd8YoEyKWAd1fdDt57KynnJz21G3mte8nDvQgjiZ0gHXZUK5kqIW8HC4lXg4WslLF7E9PlXwvzKeVEWaigjqaaurJQhhNLZfUG6Dwr9PxP2pSP35S7nX1dKcJ1Rvh+USVYKFihXJue0ZFWJvg3fDrtGlAlfC6FNifR1pgTkDxthX1p+zIcLMikg49e8yk+2zMzMzAbkwZaZmZnZgDzYMjMzMxuQB1tmZmZmAzpVAXklAMkoFeSV4KgU4iaB2d0FD78rWEC4UarmVzzQOan3+HbWEAbPWiFkT6rMh4Ifc3VwWdgZYaWAKh0oV45HmfyRC9W6WQBYCe5mJf8MQ0EmZQj/Tgvg+6Jsh1WiV4LrSqC87NLnPxcmmSj3H2VfcnKPku5hArZqx7omf3Q5D50zSvi9Eyquz6vNm94XNlEF0IL2LADfCOH3WmgjTRAhbTph+tl+wyfflFn6M1p0/HhmDW8zb4R7VEjfO4RhgMxPtszMzMwG5MGWmZmZ2YA82DIzMzMbkAdbZmZmZgPyYMvMzMxsQKdrNmIQZhiMtpKvK7NE1jXFgM0qGpGlhQA+0xAAyowsXSNsQ1lqASWfpRNDembYWJgNF2q+BAjIcj1hwbdRCG26Sbo/AUDFlgZawxIhABAaPsMskhm7uXBu2Uw3AJjgSvL1RcWXBbpVorCkiTJLs5rvko3wdXYyYTkr5T6XRTLzUbiHKbNk1zHbMAozDZXzz5bOmo3O0W3MCt4viy7d/3N27gHsVXxfFGy24TzyGe3KUjxlxo+pIdtRltGZt7wvNDF9v7xyOKbbaIWlwA5mwuzVNS0ppvCTLTMzM7MBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YBOVUB+QcLvAHBQbCdfH7UkzAwtIKwsqcGwpQAAoO14uLEgAfi5EH6vcn7Mex0//12R3t+s4uetGvEQa8aWpRHC72HO22S1sOxJkQ59xpKf/0AC/wAQc94X1iGf8WWZYpE+JrbMi4qFogEeKFe2oSyFxJZUymckQA8gCsv1KEF7FoBXjllaFosE5DuyVBUAdMK+KEvtsGNSQvZs+RsAKMgkBiVk3wnPKQ47fu4ysqRVIyxdwwLn/fvw4DpbJkdZRkf5ztuZpQPwD1wRjln4ej6zwfdlRJYlKwtlMp02jPKTLTMzM7MBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YBOVUD+oEqH3wFgr01XOa8zHlaOIz7GrJpD2uZqOJt8nQXbAWBc8ID2NEuH/ncaHmzfJecNAM4UV2kbVq14XkzpNkYT/jlXpJp6UEK5lRBcXwgB+YYEjYXwO5TK+kKIONB9EULRyrmbkpUa5vv8fYTj6UpeLZoGo4Vzu44q/9mc3xOkfVFWsCDbUVY+UKrD01A6mTQAADn4ZIlW+ZxDen+lkD345IOObIetkgEAUag8HsA/Z7a/SqX0dbwPAOw36Wr145z3hbrj79OQNg9e4tfQbMb79vhpwsoGZHcnmXA9i/xky8zMzGxAHmyZmZmZDciDLTMzM7MBebBlZmZmNqBTFZBfxHRADxAC2p0Qis54WLzIeHB6A+lK3G0pVLYmoVAA6ECqtgtVexuhUn0beXdYxHTocBR4WHY+4gH5ggSwlWrSseKh3IxMPgBAq2wrwkLYRsvPXTxIn5dY84B8qPh1xsLV0gQFUnkfAPIgBO3pGwkhVqEv0M+ZTU6AtrKBFNYn51fpt8r5B6nOnzW88n4r9AXleg1k1Y5WqM6f4eav1UyazMLvuYWwLy2p/p4rq5AIIfqGfG8qDhvenzphXw7n6WPe2xOuM2ERhkPedVGRLlW3whuJ/GTLzMzMbEAebJmZmZkNyIMtMzMzswF5sGVmZmY2oBCVasZmZmZmdkP8ZMvMzMxsQB5smZmZmQ3Igy0zMzOzAXmwZWZmZjYgD7bMzMzMBuTBlpmZmdmAPNgyMzMzG5AHW2ZmZmYD8mDLzMzMbEAebJmZmZkNyIMtMzMzswF5sGVmZmY2IA+2zMzMzAbkwZaZmZnZgDzYMjMzMxuQB1tmZmZmA/Jgy8zMzGxAHmyZmZmZDciDLTMzM7MBebBlZmZmNiAPtszMzMwG5MGWmZmZ2YA82DIzMzMbkAdbZmZmZgPyYMvMzMxsQB5smZmZmQ3Igy0zMzOzAXmwZWZmZjag/x8dX5y/9msIoAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904acf5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904c626a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904c80400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dfxbAL0fEj+CxOltzAC87kYH4QgAfjKFz9ucxvH2ZYAh3vwhDKBcppbdExJdhqF312xHxrzHUznkmhlFR34Chbs7N/CyGf/F+IoA3RcTPYghWfyKG+kSfcqL99wHYj4g3YXhbs4Oh3tT9AP5eLtCfUvrdiPgqDHmUX4uI78djdbaeB+BbN371tVXr3Nab1tua8PhfFR7/73vw+C/VY98G4MUA/nsM2a6fxJBNuR/DOfoQDCUXcpmUv4+hM/cl69FUv4ChztanYigH8kl4fEf1P2E4j58dEQdYB8NTSv9g/fnnYugw/tt1Hu0tGL7knovhbcwVrH/VklL6nYj4Ogx1tn51fdxLDNfeL66Pya36Qwzn8Acx/JrtczD82vkV6zd5T5qU0g+v6z79NQC/ExH/BsP+PwfAnwHwCgwdE+YnMUwD8z0Yfg32qQA+AMMoxZ/caPfNGDpW/zEifgDDr78/GUPG8lZHXN7M69fr+WoM3zsnf4WIlNIyhkKyPwLg59aZw99ct39fDG+Z3ozhGNzqs+INGOqOfXtEvB7DSNpfSyn9+5TSgxHxbRhym7++vgYmGGq83Qvgy075B8vtevv6fvtdDNfsJ2J4Bv4YgK/Y0jrsLEpnoP6E/3t6/ofhX6pfDuA3ACww/ArvxwC85CbtL2H4kv4dDDWVHsEwTcUXn9L2pRjCulfXy34rhpGNH7TR5tU4pXYOhgfk69Z/9wDDg/bDcXqdrVcC+GEMHa0Fhg7GGwF81ollPoCb1InCUCbhTRgKoh5ieLv2Bae0e/l6GS+/lc8yx/9L1n/n10/57G04UV/rlDYvWx+bq+vz8Yfr8/dKPL7m1M2O8zPWnz2yPs4/g+HXmt+0bv+hJ9q/GMMIwv315+nE53etr4/fxJAhuo6hDtW/BPAJp2z/F2L4legSQ62lr8bwK7HbqbO1g2G02DvW18FbAHzGKe1PPRa5z2/3vGMYufbG9XE4xPCr7W8H8D4nt//E33vVepkPnDhGb8XQQa1OtA8Mb5yOj/vbMHS+zq3/zltv5RhkjvVxrb0jnKgfdqLdc/BYoeHl+vr8tfV19WG386xYt/vK9TKbk9fI+hh8AYZ793B9jf40gL9wyvree3xvZf/Xf/fbMfzD42C9jp/HcL+Vt7os//f0+u+4mJyZ2Vas30y9GEMx0H3W/qm0Hn7/kpTSE2pgPF2tyyZ8DYCPSyk9+NRujZkBzmyZ2W06mZNZ/+yzMQSzf/Ksd7TMzJ4szmyZ2e368Yh4FMPIthWGvNcnYPj1yJc+lRtmZnaW+M2Wmd2uV2PIOr0MQ5j7hRgKM35kSmm0ofJmZk83zmyZmZmZjchvtszMzMxGdKYyW294/w+mr9nKaX7quOe8+Ll0PXf/aT5Hbvm896dtmsun1cd7TFvz4suJFlQHujI/Y0Zf8NPYkmUAwFHJC4p3KX/8ez61H8r3TgeXaRP5+Vir1NBlTLoj2iaEN7tB5s6OxOeOrboVX0/Hj0vVHGY/TwU//so+92X+mlKuW0US/r1XJH5cmL6o+baQY9cJy1Cw+xkAenJ8lW1JeHIGWE66BW3D9gcA2iJ/XDrhOadcT03KH7sQZuFRnnOFMKf0BMvs5zurR7OfA0DZ8/tDuRZK8owqev7MLVr+nKsOSdm64NsaDV8PhDZBjl33Ll5mbvd/+FrpRvObLTMzM7MRubNlZmZmNiJ3tszMzMxGdKYyW6sr/HfPO8/Ob/Ls0jm6jOre+2ibfrZL2zSTfBslS6VkX5rqCXMFPw7LOshtSJYBAJqU36c+8f0phX2uSN4hCb/XF2IVkppkUsp8pAuAlpmre57xYLkiLUvFN5hmnITcVyK5LxU7LMp6lIxTT46tcj8rebhVmb+fAZ5PUrJJvdCG5ZNKIS+n7I+UTQ22z/yeV9oUkb/+lckEui29p2D7vKp2sp8DwKTN5zgBMddFzlFb821R7vhU5Z+FxdENvhDhekpz/h0e1x7Jf15u6UsEfrNlZmZmNip3tszMzMxG5M6WmZmZ2Yjc2TIzMzMb0ZkKyDfXeUB4ej4frpvfe4mvqOZh5W7Kw3UsMKsUL1SC000xza+HhCwBoCXB9qENDwOyACoreqq2SUW+gJ4ShO2UwoMkLAuABu27Qihq2gtF+AR9SQoyCiF7VqRVWU8fwnkWrm2lIGxBji8LtgNiEVASumX3oaoJflwYZSCKgobFQxhYAH5cIvjAgYIM3NhWQH4by5gEv5+3cY6WJQ+lK0VY0QoFnsk9XQpFTbuSXwtpN/8dPRGeYcWSDwqIJl8wFgDSJD+4wwF5MzMzs6cJd7bMzMzMRuTOlpmZmdmI3NkyMzMzG9GZCsjvPZ9XIt69Ox9cL8/t0WWkioc+FSyYq4TfpcruJKSqVH5Xwu9KiL7pSQXzLQRUAaDt8kHLSgi2K6HcOnjokx3/ioT5hzb8HNXCQAdW0bsQKkVLAXmyvUoFf+XaVrYlyvx5lAZLKAF5shx2Hag64T5j29IrldKF4HTT5/epFO6zTgmCCxludi8qVfNDmB1hG5Qq89JyyHkswe9nZbBKKwTXWQBeuVdLYSAQO4+JDM4BtO/w4lCoRN+zZ8v2+M2WmZmZ2Yjc2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRGcqIK/YuSsfgI9aCLEKVWG7yZy2SSSYqFR2V6pJNynfphECt8uOH5dVLwR3STBUCSsrFY/ZclZbii7WZBYAgFfZroTK4koQvxaWU0U+MFslvh6lErRUlZpQgrsQ2rBrQQnr98JsAjSULgTBtZkNhOWQ+0wJrm+D8mzZ1nFZ9fnnnDLbwzau221Uu1eXEynfpiCzGgBiZX1lOez7rNzOs71o8yH6bsqr5hcrXkE+HR7QNlGS63tLg+kAv9kyMzMzG5U7W2ZmZmYjcmfLzMzMbETubJmZmZmNyJ0tMzMzsxGdqdGIRcH7fvO7zueXMeGj+0Cm2QGAXhhJ2JGRbI0wumzR8ymKGjIdz2HL93nV8f1pe378tzEKSpreYwvIQB8AQCmMRiyL/D7XRUeXMRGu7SSM9mnJLVuCXwt1yafUmPSL7OfK1B2VMHWHNKUPGeHUgo8YUkbMKaPH6DKU0VjKiDmyLco9pOwPu587Mj0XoB1bNs0XALRbeC6UyghAcvyV+7kTpuuZFHyqHTaSVhmBqYw01C65O3+2S9O1kX1OwvdzkGl2VGmRH9XY7+9vZT2A32yZmZmZjcqdLTMzM7MRubNlZmZmNiJ3tszMzMxGdKYC8vUu35xqh4TOhfL6/ZRPxRPCdAws3Mum2QGARc9D9A0Jty9bYZodIbhYlzwYysKjShBfCQh3vRC03IKahN+B7QSnleCuokZ+qh0lUFuAn2emUqb8SXw90pQ+hBYi5tdTyY6Lkv0VnhvKVC8sdC6MpUAZWzjPJT/PS+EZ1iVlSqs7v0cKYRkVOS5sSixAHHwgnOdJLPPbIgwymXT5wSy6/D6VHb8WtLA+WU+TPyZbRYL2MeXXrcpvtszMzMxG5M6WmZmZ2Yjc2TIzMzMbkTtbZmZmZiM6UwH52QVeTb2c5QNrsZevMA8AfcVDb33Bg/YsDNgmHv5lYU0AYIWVL055cFEJy04LHsasIr8upZr0Shg4wLCq+oBWzVsJw7JzpATOleNf90IwlOxS0d95KBoAps1B9vNeqfIsVKSetPkKzgDQlvn7tUxKoFkIrpPtVfanEAYFsHsI4ANalH0ue6FNl7/nlYEFXcnv54acQ0CbTYBRAuXsPis6ftyU+6xqtxVczyuEwSrSdBpb0AvXAhtEolxz/YRfT+WU9yfS4ij7ecz4MlR+s2VmZmY2Ine2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrIn7uPh9urvd3s56nkwd1U8t1ulRA9CcjPIx++A4BJz0OUs+5G9vOqEdZz9ChtE0KF4GjzAdQgFXkBIFVCxXsWwBYqFfelEKIXgq70ehHCp8p6+gmf2YAF05ezC3QZSnCazzjAz6ESnI4tBHeV2RGU9bD7uRQC8sqgDCXQXJI2tXDPVw0ffFCuSEB4SwMutkI5/kK4PTqyT0t+3BR0PQASC3ELzzDlOy9aYVAGWU4StqWb7dE2fZV/LtBnP4B+skPblMJxYWLG16Pymy0zMzOzEbmzZWZmZjYid7bMzMzMRuTOlpmZmdmIzlRAvqh436+Y5sN10fAKwkroUwnUztp8le3pMh9sB4D51bfzbXn772c/bx5+mC6jE8KahRBcL3byIe5eWE9/yMO9QcKNzY19vp6Gh2X7lRBWJtfc9J7LdBnFHg+OVnvnaJu0k2/T3/f+dBmdMPiD205FaqUqOwv0K5XH2+DhXqaCMIBE2B8FW07Z8dkGioa3KQ+v57dDCYsv+Xr6G9dom9SS+7UXjq0SFr98F2kgvIMQqpynJR/8RL+vpsK9Wmznazy6/D5FJQwymQjfM2QQQ1vxqu1tzYPrxTnhuXyY/w7fJr/ZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjehMBeR37rnIG22hKqxUfVyoYjtd5UPas2vv5Jvytt+jbRZv+6Ps50rIOyq+P8UFXsE/6nzQOAkB+aN3P0LblLN86Lm5wYO7R1f4AIVuxUP09U4+pKoMCqj3+PbWd/NtKcm1G+Ah4kKoIH84u5RfRhIGQgS/5lpSTVpdF6PM1MC2V9kOpYJ82fFBPPUqf71UCz5ApDwQZo24fjX7eX+NL4MG2wGkVjiHbHCBElwXpBU5/hfy1z4ApFl+JhN5W8hgLaUKvXJclFk7QjiPTClcl6zKfCkMPlhM+Dk6uPxc2maHPH/KRx+iy1D5zZaZmZnZiNzZMjMzMxuRO1tmZmZmI3Jny8zMzGxEZyogX58TqsJO89Vlu0v30mUc7d5N2xxOLtA2M1K5t57zwHlx37P5esiggJjx44ZCqHh8JFR2382HGwshZKlES9MyH2KdP+s+uowdocp8e8D3uZrnA/LVRX6tsIEFABDk2h5Wlr/mlOD0tcvPo21YGPyo4tXuFfsdr6xfRn5baqGye1nwoHGV+HKYBOE+EwYOMC0JGQNAuZ8PvwNAavP7LF23u8Id3QszDpBnVNS8mnra48/cbi8frj469wy6jOWEH39F3eafP2ygxNCGV0FPwoCvbSgaPhClaPPP9ma6nWfLsubXZbmX7wvMujt/Jhzzmy0zMzOzEbmzZWZmZjYid7bMzMzMRuTOlpmZmdmIzlRAfnbfPbwRCZQvz/Nw440ZD8g3iQdD99or2c+VKvTLy8+ibcrz+ePSTHlYs17y4DSt4AwetGwnPJQ4vYdX5U2TfOh/uaV9nh/yCtmsQnOQkDEAoOFVw1n4HQC6eT48mkq+jFKoIL8q82H9w54Pyrje8DZV8GtuUua3d1bwUK6iiXw16bbkz4RZx8PKUfCwODuPxXI7+0zN5rSJNEBHeLaADK5JF+7ii9jlg1UOzt+f/fxazb+HOuGrs038+b87zV8vs1IYFCB8zygh+iBh8NUOr9oeNb9eqiY/KEB5hnUln3liWfLrsiGzg5RkW2+F32yZmZmZjcidLTMzM7MRubNlZmZmNiJ3tszMzMxGdKYC8sWly7wRCRovp7yC8FHiIT7FYpIPKzcVrwi+Kvm2sGreAR64nQgVjwshON2TqvmNEOg8nPPzHCRQKx23HV41fGeHB+QrUuU5er6eTrgWlNAnaxPkWgGAyUoYLEE2pa74tdL1PLjbgLdZ9eSaE9aj6FP+355tz/9teteUn8PddJ22maYb2c/LJQ88K6F0Gm5XKo8Ls1OgFSrIk+1NwgAS5V6suvx3yKRe0mX0wa//AnxABfsu6ip+/Mt+O1XOJ4f5GQcmR9foMg73hEFuRHT82E6VZ5iAfY/0wjNZ5TdbZmZmZiNyZ8vMzMxsRO5smZmZmY3InS0zMzOzEbmzZWZmZjaiMzUaEZf4SIb2XH7Khv36Il3GDHyqiwQ+wialfJu24CMZ+uCjTdrIj2rZa/iIOmWk4eGUH7tV5Ecb7rXK6D4+2idF/tgqx23a8BFbjTC9BBsBuKz4tBCJTPkDbGdU0USYOqjs+PEvu/w+p4rfH8uOn6ODJX8E7R+R6ZKEwXALYbakmmzK+R1hOivhudFM+D7X0/w5YiO1pPB8AAAgAElEQVTHAKAQRhKmvfw93+7w0d2FcD+zKa8kwujKouHP9opMXbMnnMODGR9R3QijESvkn8t14hfuSnj+LOr8yHkAuNjmj10tTG2mPNvZM3e65KN12dROAFAKIwmjyH+frYTp51R+s2VmZmY2Ine2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrId0IY8+DcM+54PfM2PxUGAOyXPCzekalrktCXPex5uLFny+E5TKlNlXi4+vLRO7KfK8H1kkyXAQD787uzn086HoRlU/4AWqCzrfIhSmWfWeAfAHphqqOKhOgj8WlRlLA+O3b7rTCwoOf7XJf8HNUkjK+sZypc/3WVP3bKtipTZylt2OCaZn6BLiOV/PHe1vnnT0eufQCY7b+Hb0vFw8qL+aXs58oAkpKEvAE+ddZ0waelUZ5h2L2PNtlbPJL9XBlw0ZX84l5WPOi9v5ff3rkw5Ribzg3ggf5CmHKpFJ7byvRn7D5bTvhzjp/lgd9smZmZmY3InS0zMzOzEbmzZWZmZjYid7bMzMzMRnSmAvIHF55J2yhBP74MHkrvEj80BfKB2WXi4dIuCZXQi3wYs0+8z7zb86q8O0dXaJujWX7ggDKwQAl90mVUfJ/ZAAYAOCr3aJtpf5T9fAV+ntm1AmjVomcrPriDWU75QJQr9f3Zz9sVP7ZlwYPgRfA250hG9fohv4cu7AmhW7K9s5pXrT4/OaRtpiFUXCeH5XDOK5j3O3xGjiLlj0vd5q99QAvrK9t7vci3mQYPv188fCdtwyrIN0rVcGHAS9Xz+3myyD+X66t8f9oL99I2scevhf1pfnaWfi7MdlLwsP5hyh/f5Zx/P188ehdtM13t0zYPRb7PQQen3QK/2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRO5smZmZmY3oTAXkWWVZALgR+TBm2/FdUgLaLJQO8NBzBR6o7YVq3mXkl6NUpJ4vHqVtmppXy324yNfLPWp4WHyn4kHXnSIfNC47Xk16UfKgaymcI3a91MGvlVYo4X8IHtavybFblfwcHgjrafr89lYFP26VMkCh4W16UiG+EP7JqIT1dyf5a2oi7LMSfleul1Xkq3U3iVfHVp5zkyK/vauSVw2van49KarIH39lfw5mPIjf7uRnIVFmYVCeubUwy0WxIgMQOmFgxyF/tlczPigmpvnvsy74vdoJXYrDllxTQq9EmbVjRgYfAMB0nr8XV0mZnkXjN1tmZmZmI3Jny8zMzGxE7myZmZmZjcidLTMzM7MRnamAfCdUn2XV0lc936Vlx9fTlDyAV1b5wGwPvgyl+vuN9lz2872SV8q9uvss2uZ6x0OUN5b5AHZd8ECnEnRdpHyIsiv4sVUGKChhWEY5z8t+O7MJHFRkgIgQ6Hx0xQPN7LpUzrMSfj9aCbMfTPPrmvGsOPrEr7m2z2/LvOKzABTB2yiDJRLZ3la4VhbCNbeIfBtl5oN5wavMKzNY7LbXsp+3BT/Rh6Fc2/ljV0AIpQdvU4MH5PtJ/nna3/1svgzhWahUvC9S/lwrz22lDfuO5sPkgKbiAzcKYVBAR943Kde/ym+2zMzMzEbkzpaZmZnZiNzZMjMzMxuRO1tmZmZmIzpTAfnz+++kbdpz+XDpUcdDoRE8FL3olArN+QBe1wsheyFozChVexc9DxQeCNXfl11+n24sefhX2eedklRKBz8/ynHphUBnQa6XGw2PdC5aYXuFEPeiyi9HGSCyaIXjQralFsq23zhSrn/ahFZ/3y35QAjFilzbR8I53C359X/UCVXZSbX6g4bPFKDcZxW5tpVBG8skPHPL/CAfAJj1+VkjlKrhSnCdhZ5LISDfJn4PNUL1/YO9fDX7Vhk0JhwXpeJ9kIB8W/DzfNDxWTu28YZHObbKgLuWPC8b4Tyr/GbLzMzMbETubJmZmZmNyJ0tMzMzsxG5s2VmZmY2ojMVkE9CJVylQi2jVG1n1aQBoEv5wOxMCO4q28LCjVKlaCHcqzg3WeYbCKthgXOAn+dKCMIqVbYVR31+p5Rz2AjXk3LNHa7yYfy25/eHUEwae5Mm+3ld8srKh0u+onNz4VogTQoSoAeApuPHdtHk2yxbfp9NCh4QVq4XNsvF1YVQQVu4z3bq/DNKGbQB8LB+LRyXWZUfcFSHMCOEsM+TyF/b26qUvgQ/R31NKpiT0DoArMgsAIA2QIo9U1thwJcSxGeDP5RBGSshrK8M3LhBBpoo15PKb7bMzMzMRuTOlpmZmdmI3NkyMzMzG5E7W2ZmZmYjOlMB+dVkj7ZpSChdCZ8erHhlWSVcOifhUiXw3Arb25HldEseflQooc+qyAc2leM2K4Wq7SRo2Qa/dFcdb6Mcf3ZNbaMiOwAsW74tKxLiVkxqHrrdIwMhHj7kgefFim/L+R0h0Fzlg7ulcM2x6vAAUJGg/fkZ36Ei+LGthcru11b54K5yn10/4tfl/iLfpq74/nTCoIymvfOBTdNaeCZP+LGdV/nn9vlJvpK9Sqlm3yD/XcQqnAParBFKG/ZkmZb5gQUAD78D/H5VvsOPej4oQ5kFhj0XlMFEKr/ZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjehMBeTLjgdQo8qH6xqhyq0S6FS6oSxcp4SilTYNCU4vhfBp2wlVkYViuQU5LlMhfH1U8suuKvLhxnJLVcNboU1FqqUry+iEY6uco6rML0ip7K4FvfPr2V/w+6wQbrP5hG/vTpXfXiVwroR7O/LsmJHtALRQdBLu+XmV317luaHcI+yaC+Ga3BYWoj9YKNvC78WyyIfSd2d8wNFMeM5Na34tKAMdGKVqeyeEztm2KIM/lDbsHlEGailV5pX7jD0vlWWo/GbLzMzMbETubJmZmZmNyJ0tMzMzsxG5s2VmZmY2Ine2zMzMzEZ0pkYjHkwv0TYd6R8qoweUUWpJGJrHRjIoI01WyhQtZESQMopNadPxgSTCCDNl+iF+XIrIL0cZddcJ14Lyrw02ZUMI57kURtjMZspItvznUzK1DQDMSj6qbtGSaUSE6+niHj8u56Z8W3bKRfbzOvhIw8SG0QJYpfw+nyuu02UsE59GRLgU0JMrU5mKSplqhF1PNRn9DfBpjgCgFUaAl+Qczad3PnIP4KPRhccTfSYPhBG7wrGjaxGWoYxY7MmFqYz0V0YjKs8fpk38+p+UfOqgZcemS/JoRDMzM7OnBXe2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrI1/2StpmU+WlchIw3lo0QFudZQOxMyPQGQnCRhUIBPjUEC5MDwLRWwvrbmdJnG1gAfvYkTYWhmAoh4rkwXUwvTKlxfTXNfq4M/jiK/DIA4MYyHxxl0wYBwKVdvs97dT78DgCTyAdqq+BBWEWB/DVV9Xx/WjIVDKCdZxb6r8l0VgAwrfjTcLHKfwWUwj2kDHJQrCb5h+62pqVhlOeGsi3KtDPKtEuMMv2cMqCIUfZHGZTBrn9lwFEhfNMry2FTfRXKDon8ZsvMzMxsRO5smZmZmY3InS0zMzOzEbmzZWZmZjaiMxWQb4XQ5yrxNowSFj9Y8H5oM8sHOneEUPSsvvNwb13yNL8SxKxLpcpz/tgpeUIlXDojldCV6sDKbAJVwZfD9qkUqiYrwd39JQ+u7y/y5/quPWWQCd/nqsw/Gi7u8Gv77vk+bXOuvEHb1CkfwC56PlhCUSN/7IrE1zPv+D4vyx3aht0ju7UwU4Nw/bMK2ex6A4CLc379T4T7jDxO0SW+Lco+s+eCEqxWKAMh2HluhWWUwkNXGaw1JWFx5bhUIcyCQYL2ynO7LvjzR7FT8QE63J7Uym+2zMzMzEbkzpaZmZnZiNzZMjMzMxuRO1tmZmZmIzpTAflIPGjJqkWzirDA9gKQyzbfV70w5dsyFcLVqy5/mgqh2r0SHCUFnAHwY1cJ+6NgIW7lPEvrKXj166bPVwVvemWAAv93TdvzNudm+eOiVKpXAvLnJ/nrRRlYcKG8xrelO6JtlMrtTAjh9rrNh2VDCOJXqwPaZjm/RNscTS9kP58EHwgxn/FjOynz63nbo+foMvbJrAYAsCeMa9qtyD4JjxZhjA8N2hfCM0z6nhEGAq16UsFfeLYUW6gODwBzcvyV4LriepMfIDKvhBkJhF3eKQ5pGzZwoCIzOdwKv9kyMzMzG5E7W2ZmZmYjcmfLzMzMbETubJmZmZmN6EwF5KctD5eyLZ6WvJrr+RkPvS0b3g89WpI2u3QRmJU8DMjCmIuWp0/zEe+BErNkR2UqBLSVAGpJKhEry1ACnVIbVvGYfK62mVc8dM4GOijX00Sovjyf5MPidfD17K6u0jZVJ4RhiaLlyyiEkH1JllOshMDtgj/DqgN+XCbn7s5+vhBC9k01p22CzaZxkS4CVxe8Iv61xYy2WVb5h3stBMG1Z0t+n7XBLEI19eLOg/ZK5X0liK8MCmPLUZ4bi54PlmD7PC95VXflHCnYQJMC2xmINSzLzMzMzEbjzpaZmZnZiNzZMjMzMxuRO1tmZmZmIzpTAXlWwVmxV/MQa1vxqryXdnk/9GCZP3zXlzwsqAQ6pySYqITSWyFQqFSzZ3ZLHhDeRrhdCZw30rAAjlWZT4mfZ2wp0A9SUZoNLACAvSRUdm/z1ceLngd3p4tHaZui48tpJ/mgd7XYp8tACIMYyFQMIQTx0QqBZqFNVef3icfNAfB8PJoif+0WQrB6b8Kr2R+s+CCeVZc//so9v1vz6195/jDKtijBdUa5nxXbGMSzSvx5yiriA3yfWIV/QAvI18LsIKXwHNsWv9kyMzMzG5E7W2ZmZmYjcmfLzMzMbETubJmZmZmN6EwF5KMXwo2kzQw8IL9T8aBfQ4LIAJBI/lHI5OKg4eHqZZHfXlZVXDXfQvX3g46XzVcCqixcqlREVgLnvfDvjQr5EKUSYlWCo4uOt2FVqSdCZffpigfKp4t8iL7ohGul4cHpohXaLMmgCxJsBwAIzxZpOUy5hWUAKI5uZD9XHtzT4Nf2ss7PuDEr+Pk5EmawODfh1yW7/puO748yKGle5+9n5bnBqqADQFLakHUpIft5kR/MAgBLYRAPW5cSsmeDuYDthP5nBR9MV3f82m2L/LVbJFeQNzMzM3tacGfLzMzMbETubJmZmZmNyJ0tMzMzsxGdqYB8veTB3a7kYUymAA9o71ZCcJcEvUshxK2E21ckOKqsR6mZrAwKCCF0yyjby45tJYTseyHQORECncxRJ1SQFyihWxaQr4JXRK4bHqitD65mP1cGs0hV24XrqWhIBX8hlB5HfGYDFGR7hQB9P+MDRCIJA0TIPpfX3kOXwSriA8Bu9Uj286Mdvj+K/YY/t2dV/trdqXjIXpkpg7XohOeG8jxlz22AD/RRBgIp4Xdl4EwPMoOCENZPyqgwYhL8u1cJ6y/LHdqG7VPVC7NGiPxmy8zMzGxE7myZmZmZjcidLTMzM7MRubNlZmZmNqIzFZAvj67TNtVknv1cqfjaJR4cVaqcX6iF0C2hBP26Kr+9SrC9F4KjChroFEKULOQN8EEMSuX3gm+KdFzY8VWOv1Q1XwjDTgpSzT7xgHwlBORZKB1CBXmpIvsWKq4r4fdY8YrTaZlvE7v5auuA+K9XNvUEALAQfcvPs6Kt8uFqpdr3Xs2P7UM3LtI2V7r8TBkXd/k+79R3PgvGtgYcKfc8W5fyPFXW0yQ+a0od+WPHAvTDeniXgj1zS/KMA7TrsgBvo1SZ3xa/2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRO5smZmZmY3oTAXkaSgUvHJ13fPAWylU6lZC9CULWmI7QT8mlTxkrwQtlX1mIe5WCGIqwUV2XJSqyUfdjLZZdbyyNQvAHzbCPguh252aVyuuScX7neWjdBnVfr5qOACkKv9oSLUwk4NSTVoIiwep4qyE39FtoeL9kj9bQlmPUH0/TfPVr/uLd9NlLHfvom32p/k2rRB4VgaIlMI/6/eP8sf/qrItM76i3Wn+HpqVwiwMW5jtAQAmRf7aViq/d8JxEcZh0aC9MvNKJww4mhb5+2gKYTCLMPOKMliODSjqYntdJL/ZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjcidLTMzM7MRna3RiMH7fl1Npuvp+UiSSclHeCzBR7u1ZPReL4zGUkYJMspolGnwKVqSsL1sREoNfmz74KOX2CgoZeRkK4ySUkYSstFWRyu+nlUrDAfa5U12qvzx7YUpcto9PkqtrfIjOVdTPnXN7vV30jbVtYdom2jzo8fSdT4CM/XCSOeaXAsFfz6lmj83IIzkbPcuZT9fzfn0N1d3n0XbvGuZH9U4L/n0N4tWGJkqYI+fXhiB1va8TdPlz2MlnOdyCyOqAaBG/vgq3w+1MGJRmcYryMjgXvh+DmWONKJu+WjEtuDX3LQ9FNaW396GTGd1K/xmy8zMzGxE7myZmZmZjcidLTMzM7MRubNlZmZmNqKzFZAXsHB1EsLXWnCRBwr5eu58GQDQkykQpOlvhIEDFQlrbosS+qRhTCGHuer45X3U8DbXDvNtGuE018Kd1gnh3kMSRr4+FaZxqXgSn011UXd86hppKp6lMNVOSw7whIdli4oPhEBJni1zftzYNDsA0O7mw+8AcLD3jOznq5JPRXW15SH6g1X+2B0GP7arVghOC9NVsctFGOMgDUTpyeCbtuf709a8jTJF16zMX/91UgYcCQM3lMFaLCAP/t3KvqsA/v2rhN8rMoUXAIQwXc+yzg/0UbZF5TdbZmZmZiNyZ8vMzMxsRO5smZmZmY3InS0zMzOzEZ2pgHxx7RHaprz4zOznSgXtBKVSOg/XseUkoeJxJYToWaBw0vHq8AqlsntT5CvqVomH7BshdHvQ5cPIN5r8TAIAcGPJQ9FLIdzLgq4zIUM5rYWwuFBk/rDJr+xK8FB0Eedpm6rIp5EvTK7RZUzm+3xbLvKAfHSkgnzFT0CvVIImz45OqA7flbzNYsqP/5Xi3uznhx0PyO+v+LawauqKRSPM/CEM/mCDSKY1T8hXJb/PSrIpSrBdCdE3wgCdFQlgF+Q+BLQBR0oFeUb63gy+vdvYFiW4noSBA20hDJzZEr/ZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjehMBeSVhDCrCsuq4AJAAR7iUyruslyiUjVZoQQTGa1qOw/Is4EDq+Ch3DYJwfU+30aqVFwIwVGhzc4s36bc0nlmoXQAKEmb/YYff+VaKMhxaSvh32n54swAgN0Jb9SQ0HknhFyVe2iJfOi8FR6XhXBslz0P9z66zFei75Qq50IbNohnKVRkL4VLoSr5tb07JfeZcK8qj20WgFfuQ+FrRviWAVbkWlC+QyYhVFMXnu0dqRCvPHOVgDz7bi16PjhNCcgrzzmGzaRxS8va2pLMzMzM7Anc2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRGcqIJ+WvJp0fXQ9vwyh/zipecX1VckrlPekQq0S0NtGNfttBYSV7WUDEFi1ewBYgYcbKxK0VMKnSli2EkK3NQn3ss8BYFLyqsl7Fb/+p0U+DHu9zVfeB7Sga0eC08r1dNDzbTms8kFwAOjJPb1s+fXf9vxRx/ZZOW6KZcfDyj3Zlp2az9QwFa65ZZE/LtNaqRouhLhL/lyYFHdeWXzZ8WuBnWcplC7sT13wNk2fvxbK4NdtJRw3ZZ+2cX0rs6awCvLbCLYD2jOq6vP30c7yUWFNz5e2x2+2zMzMzEbkzpaZmZnZiNzZMjMzMxuRO1tmZmZmIzpTAfmY8bAsUzWHtM2k5W2UauodCZcqYX1WtRfggcFVCAF5IbhYxZ0HVFeJVzDfBqVq+4UpD5yzsCzAg67TgoeVlYEDu8U+bTMl125dC9WkhQAquy6V66kBvy5r8GO3SPnK7goWRAZ4cF0JgrNgOwA0HX8u7Ezyx0UJX1dSm/zgDqUKvRK+3q2WtM2syLdhA4UAoJjwwSo3unO0zTZIM5VsYXYQbWYDZVvy57oUvh+UZ0vZ3/n3DAvZA0DV82dh2eXblC3/DlH5zZaZmZnZiNzZMjMzMxuRO1tmZmZmI3Jny8zMzGxEZyognyoh6M2qtvdCZd+GV5BvSx70ZiG9puDLYFXoAR6ibBM/br0QxFRCzywAqQQ+p8HDsi2pnDyvePiRVVsHgIJUqgeAnTjIfs6qEANA3fF9jla4dklgc9rktxXQBpGsJvkQcVPx0PpSqA7fCiH61OevKRbyBrQK/ix0rlwryvWv3GdzEijfKYRBPsLgG9akTXwZlTD4Qwm3X168I/t5V/JrJRI/RxUZfLCAcN0Kx0XBBhcoVd2V60nJ4bMAvBKyrxJ/FlYklN6WfIYRRSH0BXauvyv7ebV/ZSvbAvjNlpmZmdmo3NkyMzMzG5E7W2ZmZmYjcmfLzMzMbERnKiCPCQ/dsgBkEiq/FySgB2hVbvsiv66656Fopbu7xJ1X0C6Eyr5K9V8W6NxJvAq6sBrMyLFVjsgMfCBEKYTbmZ3lo7RNteLBdWVwR3R3Xn256IRAPwmGNruX6DKq2QXaZlnv0TZ8pgae/lUq+CttGCXQrATt93Aj+zmbSQDQwuINGQjEBiQBPPCsKtv885J9rtpj95nwcGkLHtZf9Hf+3J4VvIK5MkBKCdFPQCr4J+EeEiq7M8r1tKrmfFuE5RTsmhKuf5XfbJmZmZmNyJ0tMzMzsxG5s2VmZmY2Ine2zMzMzEZ0pgLyqeKbUzT5wGA34dV/q6VQZXuyS9u0yFe6ZWFyQAsd9lU+LN4mYT1CKFdRIh+AnHQ8lK5U1p9Ffjl1x4OjSuBfQWccEI5/ueLHJVoe6GQh+miFwL8SxF/wADbT1TzE2pV8n+dl/n5VZmGYCm2CVMieCNdcrwzQUWa5aPPXSyWExZWA/AT5AS2tMFNAJczIUQgDUdj2FsL9oWDn+fzhu+kyltP8DAsAEBV/LnSkEr3yDGPPZEAb/MEGmijB9UqZKYM8L9nAMwCoeuFZqTz/2bO72c41B/jNlpmZmdmo3NkyMzMzG5E7W2ZmZmYjcmfLzMzMbETubJmZmZmN6EyNRoyD67zRQX4ai+K+59BFpJJPb6BMnVInMjJSmNJBMSOjRFYlH/XFRoAMbfjoJTbCQ5k6RcGmI6laYWSYMKpFmpaJjDBrKz66srn4bNpGOf5se6VpgYT1FE1+VFE35aN+FxM+Yuuo4m3alH9MFWR0GaCO6iJTgQnXtjIaUbGo88elqIRR19IIwPxzbiJcT8pIwyTciyBTyvRVfvQ3ABTCdFZsSreeTA8FAJOGj9ZVroW2yO9Ti+18hyhTx23r2mX4lHvCeRae29L0Z2x0t7Aeld9smZmZmY3InS0zMzOzEbmzZWZmZjYid7bMzMzMRnSmAvIs/A4A7Tvekf28ungXXUa3c4G2UULEifRVS2F6A0WKOw+dJ2G6Em2qhfxx6YVBAcpUCyx0q0xzVLQ83NjUPGh8Y3I5+/n19jxfT8/Dp73wb5+izB//nXN84IAydVNBAuWrnp/npdCmW/Ljsujyj6mdil9P05KHuKvIXy9RCFN49fyRKgXtU/5a6IVlFMJ0YVHk2+zs8iA4ew4CQAF+v7IpZWbddgZ/sEEmynNbCZMrz1P2HItC2B9hW8rEn4VsW5TvkK7k4fayz19T0nevsM/Ks31a56ejihm/blV+s2VmZmY2Ine2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrIp0MegFw89Ej28737H+brOX8PbVM1R7RNX+YPX1flw3eAFjpk1d+VKugQKmgrwcSKhEd7oWpvu4XjolQnV0Ks14p8+B0A3nY9P+ii7fg5XLY80FwK//TpyCmqKx7inpCQPaDtE7No+DLqSqj+Tg5dXfBr7rAVgrskUK6spyr4vdglfl2uyKAAftSAwxUfoNB0+YPb9ReFNXE7E37sJmW+zfkpH/wxK3gofa/MD8SaBf8eqlv+/ZBIRXyAV0JX6sezKvSANqBoG5TBBR2p0K9Uh1dm7SiE7yI2s0E/5bOzqPxmy8zMzGxE7myZmZmZjcidLTMzM7MRubNlZmZmNqKzFZAXKn6vbuSrz3YP84B8dddV2qbd5VXmU0WCiSTYDmhBP2474XcWxAeAggQgQwilK1iIflXy4OIK/Nj+wfW7aZv3XMvfJgthooDDI35sFSwgX1U8lDuf8nO0S8YwVKVwbZPwNcArpQPAxZ189fdVx/en7fl6WI35Bfh6dmq+z8r2bmMZq5bv85Ub+TbXD7Zz3V7Y41HvaZ1v05zj+3xxKgzKqPNnOgnnkM1wMbQRAtpkUEZPwuSANiOH8mwPGqIX7mdhBhE2I4oysEmZhWHa8hlpii5/Hnv2HX8L/GbLzMzMbETubJmZmZmNyJ0tMzMzsxG5s2VmZmY2ojMVkEcvVDCf50PPqys8/D4XwuIQKrsnEuRj1WkBYFXxoDer/quEBeuOV1YupKBl/tiFEArtSx6irNp8teiJcH6OSl5NXVGTu+TqDR4+feQKD9QeHSkzAeTtCkHkshDCpSRofNclfvwrIQcerDw8gEWbX9Cq4fu8N+PHdkkC5YsV3+erQs3vRphNoCCrUgZlKFgAvmn4tb1a8TZNw/f5/F5+py/sCM85ocp/EflnWCWE3xV1wyvRs1lGouHfVb3wPaME11mgXxnMpQTx2eAmaTCXMCisJN8hANDX+ePfTLbzHQL4zZaZmZnZqNzZMjMzMxuRO1tmZmZmI3Jny8zMzGxEZyogX95zL22zc3iU/bxb8CB4HPLKsv3FZ9A2iYS0GyH8vih2+HpSPhhahhAKpdWBgaLnIeKuzIckpcrKpGovADR1/tixYw8ABfg+X57nr6dBflualt9GiwVvM5sJAypIYDb1PDh65VEeHGUWC1JiHsDeHt/nruPbu7tDBqIIRc6nEx4QZll9ZT1C3h8tvywxIYfuUWFQhqIn14swZgk7cxbBy6gAABEaSURBVH4vzmb8wNx3OX9gLsz4s31e8mu7InMFKM/KUnhWKtiAoij5sVVC6QpWrV4ZiNWWvOI6C8B3QtX8ScfPcyuE29kgtoMdPsPIZdpi4DdbZmZmZiNyZ8vMzMxsRO5smZmZmY3InS0zMzOzEZ2pgHx397Nom+qIBJofeoguIy15uK5cHtI2y9nF/OcVD7+vEg8U9infJ5YCksKZVqry0mr2QgV5JWnM9kmpMjwJHqi9d/IwbbNHzuOz9niw/Tl379E21xdK9fH8ieyEQPOy4dfcwZ1n6KFM1FDXPHTLKtErgXMhZ0zb7M74datsC6sODwBVmV/X3lwIK3e8DavgXxbCAIYpP9H37PJq6nt1/pm7i326jDLx4DqrlD5p+LNfCYuzwUQAr3KuDATqJnwgVgih/5XwfcUox0XZp22sRwnrt+Qc7Rf57/hb4TdbZmZmZiNyZ8vMzMxsRO5smZmZmY3InS0zMzOzEZ2pgHw74yHi6TwfBiz2eNVYLHjV8KLl4epVnQ8ULsGrbDc9D0WzCvEHLQ9I9hXvV5clD5eyYOJMCMgrVeZZNWOlgnOhhOg7HtydIz/jwPzoCl3Gc2kLYHHuEm3DqivXLb+2+4Jfc2w5LFgKACthBgVFU+TXJYVyhTYF8tdLL/zbtE382CrKyF/fk8SfT8o+76dz2c8rYXaKncRn5NhbPELboLnzQTGsIjgAdOT6VyrIK9vCqsMD/F6U1iO0UcLvfeSPnbKeZcHveXafKQO1lDYHE/48Zff0Uce/w1V+s2VmZmY2Ine2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrI9yUPl/YX7sp+Htce5Suq+HqUoCUL7irV4RXLPr8cJQi7EoL4RyUfXJCq/LqUUHoiVasBvk8szAlogc6yW9E284N8lfn6Bg/Io+ODAiYzXs2ehW6LG8L1L2wL2PUvVIFOc2GwirAtaUrCvUqpemF7e1KJWwpf1zxQWzZCeX42g4IQvla293Kdf4ZJs1Mo99lKGLhRkeelcg5L/pUWVf4cKd9DhfDcKIRruyWDrNqKD0RphMEqXfDjwgYGKOH3lISBKGTQRRLeAR2VfDDduxZ30zb/6Z35Z1QvXP4v+gDeBvCbLTMzM7NRubNlZmZmNiJ3tszMzMxG5M6WmZmZ2Yjc2TIzMzMb0Zkajbicnqdt6sm17OflhI/M6Pf59BLbUAYfpdMJo31Yk6NWmH6lEEbyCCNJejIaEcJsJcqIRbodwsgkZSRV3fBRUmy0YSijEYWRYdJxIcNj0uKQLiKmfMRcIiN2o+Oj4bASRt0JoiFT07R86qYQtiX2LmY/76d8NJY0SlC4dukylOtJGPXItlcZ0auMRixWfHohsGMn7HMvjFJjow23NhWPMKqR6Uo+on1VbmdaLGWUOBPBn7mHKT8CUBnR+OhKGI14nU9RdH0/v70Xz9/5MTnmN1tmZmZmI3Jny8zMzGxE7myZmZmZjcidLTMzM7MRnamA/GR1QNv0ZHqJsuCBtpgI0+gIAcgny7LLBy3bnveZm05o0/MAKiVcUX3i2zKNfKC2BD8/056HxevlPm3Tk0EXxS4f2IFCODDKNDpkv2PGQ6Ht5ft4m/k5YVvuXNHyaU+iywfglWlRQgiLd7P8PndkOh8A6IVAszLVC11PwcPXJXlWAkBHpnopOx5sL5f8PiMzjgHgoXMpq68MnGFTXvX8eiqUgLwQOGcBeGVasg68jTJ1XI38fvfCegL8JC27/DV32PJtPWi2MxXebJY/R8psVSq/2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRO5smZmZmY3oTAXkm1qohEsSa5M9Iazc8IrTSak+3ufDozeCb0shVJlngfKu50HMVgjIKxXkgXy4MSBUxIcwiKEk5xk8ZKyEZbvqzgdLpF0eVg4hxN3XF2ibRKpSFyteEb/Z4ethszm0JFgNAMuSh/UVZcrfr9OWB7RLIZTek0EM0vUkDISoW36OEg1G8/us6PnzlFUNjxV/PknDaoRj19f5a5td+4BW/Z2G/pVUtLAe5XrZRtV2ZcDRShmhQBajVHbvhSlErq3y1+Wy3cJALQB1xc/R/Zfz+9R2yvnRzqHfbJmZmZmNyJ0tMzMzsxG5s2VmZmY2Ine2zMzMzEZ0pgLyPBQK9CTQ3J27TJdRLnlVZHS8QjALuqZaCIILQdeyyG/LquPhx14I0XdC0FIJ2jOTkg9QWAQJYAubMQefkSAVwjVHKnEXDb+e+ukubdPWPFCeSnLLTvfoMlY135bDmgTkE390LHuhgnnix58NqKhKHvif1byCvBI0Zqrg1/aqnNE2QULaReLPp6rngwLqNn9clEr1vVBZP5SZApQS8URBZhsA+OAnJbSuPDeU/WHfeV3w+0yp7L7q+HLYTCRVwfdHmc2EBeCX7XbeAdVkkBUAXJ7nB9eUocwkc0naHr/ZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjehMBeTbUqhySwLlSpXhtMtDxFjxQG1BKosXEKrDC/1dVrm3DB4EPGr4eiqhcG9DtkWpILw7ESoRk7ByVfPgYgjHvxSCu6wqe/Q8lNuxYDuEytYAUp+vRK8EmsuC73NZkX0SiiYrwd2m59u77PJtqoJf29cbPvhgSgZuzAp+fqQZIYR7fpry15wSkC+F65JV1i/I9aZSwuIsRB/keQtowXVp1ghC2Z9OmGWhJ9vbFMIyhMruq/7Ov+pTy9fDBnMBwIoMslIq1Yfwnac4V+cHUe0EH2TlgLyZmZnZGeDOlpmZmdmI3NkyMzMzG5E7W2ZmZmYjOlMBeaVabkECeFI14518dWwACKEScUfC+EqVbSVQ25KweFnwsGAjhBuFwsl0OZ1QQTgJx6Uu88HRacmDu60QhG0rXs17usyHJJXq2JUQ7u1rvi0sAFwU/LgoAwdYnLyteHC3FgLlVcW3d1Hkj4sSlq16fi1MyMABJSyrhNKVyu4lCaYrAe2q5ce/JBXky4YPFFKeleXRDdqGr4g/W/opf/4rIXq6DGXwhzAjxFF1Lvu5MsOCMshkG6HzBan8PuBtFqv8eZzWdz6TAABcnucHmQBASZ6F1ZYGiAB+s2VmZmY2Kne2zMzMzEbkzpaZmZnZiNzZMjMzMxvRmQrIr0gQFgCCVJBXAs8xEcLKQsVvVkG+YlW4ASSlFDfR9XwZQpFtKUSfSBb5YKEsg29MQ3KWyykPhS4qHlDdrXmgtibBdSlE3AiV6mkLLlohoF3xa5vF35Uwv9RGuM86ck+v6l2+HiFcXbQkLEvC5ABQCqF0ZYBCIldDvdxC4BxAwaq2d8KAiwUfOBALHlZONRnEIJxDKAH5yD9cemEWEjawAABWFd8WNpuAMgsDm21DtWjz9+Lhit+r1w74tuzN89f/+Rm/5pSq+fOS34t15K//WrifVX6zZWZmZjYid7bMzMzMRuTOlpmZmdmI3NkyMzMzG9GZCsifW12hbaruzgNrq/kF2iaEit9FyreZFzwUqlQIrot80HvZ8mreVcmrbK+aOw/rL4TT03Z8PTOSlT1shIB8zY9LIwyoqCb5AHZBKswDQPT8+Ctimb+m4pAHp+/8LAOx5AHhquLnSAo9F/kt3tm7SBdBw9cAEtmWQqmCLuyPsi10NULgHGQWBgBAl3+GRSPc0GzUDKBNT8GOHbkOAKAXZo1gFeQbIdjelvzZosyI0qT89i6FmQ86ISzeCDN7HK7yx+X6IV9GKdzOu1PyvSnMKqGYCLNpTHr+HNsWv9kyMzMzG5E7W2ZmZmYjcmfLzMzMbETubJmZmZmN6EwF5OvmkLZZTfayn7eT83QZrAo9AFQdr/gNshxlPQ14iLjpSaBTqPyuVHZXMqy1kLlllsKhZduybPm/E240POhaTe6lbS6TxSgVwSshRF8olehJuBfscwBJCVen/D6lA74/nTBaIpGANgBEnX9MRfFuugwlLB6ksn6/4hduKOuphYEDbHCBMAtACNNGpJ5cu8rUE8ogByWsTwYO9BNhRgIhIM9mHFiVfD3LQgjRJ36ej7r8uo46vgzljckj+/y4sO+IlZBbv/8ufj9fmuWfP7NS+e7ldtN12mZn+Wj2857MNnAr/GbLzMzMbETubJmZmZmNyJ0tMzMzsxG5s2VmZmY2Ine2zMzMzEZ0pkYjLqfnaJuDKj/VThImI1FGCc7AR1vtHj5M18Qc1XxUy6xss58rUyQshZEkwmwYtI0wSAqtNKVP/vMbh3yUSBl8BM5UGHm0U+dHwKYdfgLmBR9VNAk+eoaN/CqEaaaU6XrStav5BsooNWU9jXBhkhFzykRISZhSho0kVLZVGWmojVgkIzCl0X3CqEe2z8KUS9KArYpPb8Okkm9LJ0yj05N7SBlpeNDlRzQC2ncRG22o3GWLjj90H7oqTOnT5O+Ryxf4Mu7a4SOdL9XXsp8vEz+HRx1vc37xTtqmPsxvSzfNT5V3K/xmy8zMzGxE7myZmZmZjcidLTMzM7MRubNlZmZmNqIzFZA/rPhUO33K9w9niU/50xQ8XKeE6BOZGqUteUD7XMoH9ADgIPKBzcWKBxeVEL0wuwpIbpd+DmjT9bAs8gGf2QZdzzdmXvNrYbfKH/+24OtJM36OWiFEPF3mQ/RCJBoFmYoHAOIcuRcPhemH2FQwAKIS0tUkxN0f8lCuNCiATR2kTH+jTD+khNvZupRlbGEanZjyASTKqJh+7yJt083yA6TaCQ+ur4RBVvtlflv22/yAGIBPoQbw7yoA6Mhy9lt+bK8d8jZtx7/PHrmSf+iWwvfZ9Jn5wVwA/46+e/E2uozFhJ9nZYq08iA/XU90wgAekd9smZmZmY3InS0zMzOzEbmzZWZmZjYid7bMzMzMRnSmAvIKFq6re57y7qWSx9zRLB+0rDq+LW3NQ4fzMr+cquThx2nNI8I7QpHnGySLrATxhWLeaFrWiO/PSsg2PjwRBktE/jxfnPJBGWWpVHYXBmVs4dpVQvSY5wOoZfEeugglXJ3a7QVQs5TgOgl6p5aHfxH8uix2efVxFm6XguuKaf76V4LtbKAQACz37qFtmkm+Wveq4tW8Dwo+yIpVf2+FYLvSRgnIX1/kn/+HK76MVSMMvqHPU+DoKH99Tyf8u6oKfp9Nuvzopnq5z9ez4uH3+pE/om2wzH+3lkd8PSq/2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRO5smZmZmY3oTAXkC/BwXZnyIb6i5yHWouDrqTpe5vyozoeIZ6sbfD0lX09EPtx4bi6Ef4VgtRJcr8p8GFMoGi6ZkEC/EvhUAvI3DoWBA5N8pHy35sf2auJB4z2hQnNNrpdeCCtPKx6uLluhRD8RvXBdNsK0BeTCLGc8OA2haj5dBJvWAEAIAy6UiuuJzGyghNL7Ka+43pNQeifMsNDUPPC/nAhV2cnMHkfg67nW8PVswzbC7wCwvyADIYSpD67yrxnJzk7+upwLl/ZeycPtu9ffnf28XPAd6qb8WkhT/lyIPv9s6ff4gAuV32yZmZmZjcidLTMzM7MRubNlZmZmNiJ3tszMzMxGFElJRZuZmZnZbfGbLTMzM7MRubNlZmZmNiJ3tszMzMxG5M6WmZmZ2Yjc2TIzMzMbkTtbZmZmZiNyZ8vMzMxsRO5smZmZmY3InS0zMzOzEbmzZWZmZjYid7bMzMzMRuTOlpmZmdmI3NkyMzMzG5E7W2ZmZmYjcmfLzMzMbETubJmZmZmNyJ0tMzMzsxG5s2VmZmY2Ine2zMzMzEbkzpaZmZnZiNzZMjMzMxuRO1tmZmZmI3Jny8zMzGxE7myZmZmZjcidLTMzM7MRubNlZmZmNiJ3tszMzMxG5M6WmZmZ2Yj+P0UdoIzJUtfGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6924ce67b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "principal_vectors = solra.H_t.transpose()\n",
    "\n",
    "for i in range(9):\n",
    "    cvec = principal_vectors[i]\n",
    "    max_mag = np.max(np.abs(cvec))\n",
    "    view_as_image(cvec, cmap=\"coolwarm\", vmin=-max_mag, vmax=max_mag)\n",
    "    plt.title(\"occlusion weigted principal vector {}\".format(i+1))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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aokMFAADQEh0qAACAluhQAQAAtHSjofQn7vvVu9B5MmODC01LWXCx02nufx5N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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e32819b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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u1qCCT/46r+Srk7amiq+2vhI22d/kXliV6f1tqn/mk2XaOv26kFQkKpjuaLX1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\npKHzU1s5TVIFFUw9k1To2eq7pLIuqTJ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Kzd/xTwIAAEASAyoAAIDZGFABAADMxIAKAABg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\nMBMDKgAAgJkYUAEAAMz0/wPcGdmCUAw4+QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e3246710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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nLPLPReVZB/KsU8LvXcY/Fzc5P0d55PcRQyYkAABMJrzR0UH68+rokBclAduD\n6/6GyszMzGwkd6jMzMzMRnKHyszMzGwkd6jMzMzMRnKHyszMzGykS63yayNP5B+v05s4LXl12OGU\nV5PM4yO0DVPPr9E2i507aZt1zqtsAtKVCkXHq0AmmyPaplzepG2yOl0JuN67iy5jM9mjbZqCTF8g\nVOEo1TzllFd/tUL1CxN37qBtMmHaHoZVxAH8egKAtVAVyuTCOao2vMqvqNPnKJvx60k5LhCOf1eN\nn4ZIqdrKFumplwAApOKt2eHTsNTCdCObilccHlXp524defXdquPVp3WX/hyZF7xSeRb4PT9pF7TN\ndJOuLs2EKWM64WM5lvy7EFZRyKamAYBMqM7rgrAcpO+1POPPn/KCqvwyMp1aU9/6M9ffUJmZmZmN\n5A6VmZmZ2UjuUJmZmZmN5A6VmZmZ2UiXGkovhKlnrkzTYc1JwZdRBGHKgMDD7Zt5OmTZCoFnJXC+\nBh/KvyT7VEYexFSCyO2Eb28zTQdU9/eeSpfxwIaH9a8X6YB8GXiwN+/49aIEzlmgOQpT3DQZD+Uq\nNiEd3I2RX9vK1D9V4FMyrGL6eikLfo52hZBrXaaD4MVEmJqDTJkEiFNvlOl9zoTwe9kIoWhhOiP2\njDqa8UKIm+BFPEc1fy7cPEhfl/vH/NjeOODXJZsF557beMj49jl/Xk4L/jmyO00H15VnlPJclqbq\n6tL3a53xwP+84YUQG/DlHDfp+7UTnlGZ8PXPZMIbFSTdfnRTmJLqHP6GyszMzGwkd6jMzMzMRnKH\nyszMzGwkd6jMzMzMRrrUUPqm4yHLGQmdK6PgVpGHaZcTPoIwCzQvSj7C8DrywHkbeT83C+mg6ybn\nozevCx4s3Ux54HAd022WG76Mh5d8W5hZwc/zRAhWK4FyJpCRgQF+3ADgnvrPaZsqT4fbVwUf4fxm\ny0f5V378YtduTULrALDK+T0yLdP3fdVdTFGGMgr0QUw/O4rAQ9Gzgo8OfzjlgfJIimv2Wx4437T8\nY2FNRicHeND42g4vELltl5+jpktfc/OKh8mVwHkZ+PYeNOl7bc4S9KKb9fhZC5TzfMeU368dOf4A\n0JJrYdPwZXTCxAbK4Z3N0/2Og30+Iv55/A2VmZmZ2UjuUJmZmZmN5A6VmZmZ2UjuUJmZmZmNdKmh\n9LUQimPBuZ2ShxZX4AHtKhdCcSTxtujGB6sBLSy76tLB3ZsdD8ivGmFkd+EcMWXG04TXpzxEvFum\nw4LTwJdl3a9+AAAgAElEQVShaKIwUjo5R7kQRFbaKHaO7k832L2bLuM4S492DwAHDW8zy9Ohf6Uo\n4GrzMG0DcuhC5Md2LYT1FesuXRTQkAISAMiFWSOU0bEDGf09E4ol2H0GAFdLvpxVlS66mGV8ROpG\n+Ihio3CXGb8WdjJeFNBBCOKT7yhWHS9EyZRiCaFw6XCdvi67jl9PHSm4AIDdkt/TLSliUEbNX/DV\nYLMRZv9o020mU/65eB5/Q2VmZmY2kjtUZmZmZiO5Q2VmZmY2kjtUZmZmZiO5Q2VmZmY20qVW+SlV\nZmxagWXDqyYW4FNZ3FOSSikAB6Ry7rjm26JU6lRCxc/BJr1PylD+a6FN0/LtvTpPb+9OuaHLuFYe\n0jZFSE8PUXa8DESZSkSpLGIVP5FMtQAAe+0jtE3R8mO3nqanjVH2OQReHVMI1Zp3Nm9la6LL2Dl4\nG23TVunKrnzDK8jKOZ+GZTHhU/KwKUmqjE9rolR8Zqy0EXx6rCLnzxYFq2YDgLlQXcco9xGreKuE\nakLluawcf+ahBa8sVZ7LuxN+Hmdlus3NZboKsN8W/uxYN7y6vczTz46bR3QReOTmxVRFd216W576\ndF7ZeB5/Q2VmZmY2kjtUZmZmZiO5Q2VmZmY2kjtUZmZmZiNdaig9E4KwNxfpTWyF6V72JjzYuwJf\nzs1NOgi7v+Ch9CtTvi11y8OCNxfpQH+R82ObZ7zNzoQHASdFOvyYCVNvlIEfl91NOsS9qPh0O1XL\np6cJwnFZgE3Dwn9WWRZ7tI0SKI+BFG4EHoRVpu2pcn6Opkfpc9SWfBqorOHriVn6uNRTfi2w4wZo\n00CxKVRq8OKbPPKQcRP4ctos/bxUpixRAvLLjp/HgixHuef3cEDbXMvTUxVFYZ+bjB9b5dmxIJ8j\nyjP3HTeEIPiGt7lGHi8TYdq2puXrWW14oJ99HpGceL+elTCd1Jq3aZr0yiKZvinF31CZmZmZjeQO\nlZmZmdlI7lCZmZmZjeQOlZmZmdlIlxpKz4VQ+qZOB97mV/goxEqw9GbNQsbA0SodFl+shZCrECzd\nP+JBQBYo7IQRhivh7N8540PYXi1uJt8/7ngoWhmFePeRNyXfz6/cQ5eRCyOPQwglNnvPSL5/1PLr\naQ1efNCQkDEATJAOyyohYxb4B4Ci5SPRI6Svu8nhg3QR2fE+X0+X3qd6wgP/5ZqPzq8UBRxO0iOu\nL1s+U0NVCIH/bkHbHIX0KM+bjj9/rmX8WrgK3mZSHyff3znks1McXXkv2qYi61FIMygU/Dzmefq6\nvHueflYCwOSp/Nnxxod4UcADN9LPsb0d/hlx5zWeFm87vpwpedTdLgxOfvNAmPEh49uS5+k2RXHr\n3zP5GyozMzOzkdyhMjMzMxvJHSozMzOzkdyhMjMzMxvpUkPpk5wHyksSBJwJy9h0fDcPNjxwuKrT\n/U9l5PcbhzxYV/NBk2nITxkpvSp44LDI+MawUZOrwM9RFvm2bHZuI8vg4euiTo9qDQDl/jtom/ns\nWvL9WPBw5HHLw/odhAKFNh1Wzjp+DmeL9GjTABCEsH5bpC/M4uG30WWg4dubb9Ih7nnNQ97NbjpM\nDgDVhgfXQSZIUApEysi3t+iE4HqRvhaqnF9PU2GfJ2s+gnm5TLfJ1jxMHvZ4ocmqShcgKPvT5jys\n3wkj6x/VbKR0/oy6UvHig6fexrdlWqXvxYf5KcT+kTCyvvC1DPs8yoQR5Hd3+Yr29/nnyM5O+lyX\nJb9fz+NvqMzMzMxGcofKzMzMbCR3qMzMzMxGcofKzMzMbCR3qMzMzMxGutQqv6OalMeAzmSB/TUf\ngl8ZGn9S8OqLQKr41qQKEACEkfFxlzDc/+076elG7pzw6TuU6V5a4RLpcOtVESemNa/Eyci0MdmG\nVxPmQmWRYvcwXQm4E/i0Gsv57bRNVo+vXCw3fJ+zDa8sWl19Cm3TZukKmplQwRen/J4Gq1YTKhtD\ny68XkKpFAJgifezykm+Lcp8pVZZXF+nrLgqVaplwXPKGVxzSKj5hW6bLG7RNW6avl0CmKQKAas2n\n2FoI9+vtVXpKnlXk1eSzjFciZzP+GTHJ0xWHRc7vs8WKn6OKTIMGANOSnwNmUvFKzKYRtmWa/rxi\nU9Ok+BsqMzMzs5HcoTIzMzMbyR0qMzMzs5HcoTIzMzMb6VJD6cqUDDuTdJht3fA+4U7FQ6FVzkNz\nOQvcTngg7vZdHua8Z54ONgLAlZgOnc9XPJRernkQvCnTwUYAiFk6INzkPNg7P3qAtikfeku6gRBy\njTM+3UssebFEcZSeqiUKYeYq5+thxxYApvtvTb4fGh4y7qb8uNRkGigAmB8/lG4gTH2inEe06fs1\nVnxb80M+3U6+5GHla+QcLWY8zKyExZWpT1hRgDT1klDEAGGqqK5KPzuCsAypDQmdZ50w9ZUQsi8b\n/izcI58jV4WAfCfc8xMhuB4q8nm0SxeB5ZQHwfPAzxH7fD2u+fOyFmpIdnb4sWOPoLtucyjdzMzM\n7NK4Q2VmZmY2kjtUZmZmZiO5Q2VmZmY20qWG0q9P+ejMLLjeRWG03ZwHDpXRaXeKdHA3DzxweD3w\nIGwmBBdrEmjeCGHyQgifSqHQNt1Gucik8Ptdz0y+n7W8+KCuePg6gO8zG01aCbnm7Zq3WQqjJh+S\nAgThesJsjzZRrgVeOMADn2GTngVA0e1e4+sJ/ByF45u0zbRJn8dwJz9urRD4L4XRvDfTK2Q9wuwU\nwvWf1/wc0YIKpYhEaNOQYxcDHxG8FJ7/MfDAc0fabMio7v0y+D5vonAeycj6OyV//swLfo+sW2EE\nc/I5PSv4s/ue2/knyZuFIrVJlX4GKbOZnPtvb/2fmpmZmRngDpWZmZnZaO5QmZmZmY3kDpWZmZnZ\nSJcaSlewQLkSiNvJefi6jEpwPb2cSSOsp+FhzlXFA8KLmA5XH4SrdBnZ3j20TSEE7ZkOPOWXC0HY\nKdJFDFnk26qcIyV8PVkfJN/vhJHS2QjPAJCt+fbGSTqUGzb82q5n6TAzAEyXfAR/kIB8vJ1fc1jz\nYhUWXM+WfBYAScPDslilj8sk58+o1e1Po20yIQhektB/IxRlbCo+hHYuhOhz4VnHROFn/sj2WZiR\nYF3yfV5nPFC+6tLHpe74taCIwiwjRZa+dquMPxcy8Nk/lGKsjpzHuuOB/50JP3Z7O7xLw+pipmyE\n+X4pW1/1N1RmZmZmI7lDZWZmZjaSO1RmZmZmI7lDZWZmZjaSO1RmZmZmI11qlV8jJPunWXp4/HnB\nK0mqyIfYLzpe8VA26ekJqg2fGkKpWpmtyFQiANp5uuLhIONTbygVJwc1nxKG7VEWhAo+YXqgkKWX\nc6W7QZcxW/Cpf/INn4YikKlnYsZvrYxMWQKI07B06aqUOOdVo8p0R+WDb6JtAqk4bCtecZUJVZax\nINduy/cnNOlz2K+IbwstG6qFaYiECr624lVmOamQlKZEEtbTCpVzXUbOkTINkXBdsilW8k6o1BTk\nbH8AhJDeFratgDadGlsPAJQhvd85+HGJQoX2VVL9DgAPNHcm3w9CNeG84ttb5Py5uyKP3cX61uee\n8TdUZmZmZiO5Q2VmZmY2kjtUZmZmZiO5Q2VmZmY20qWG0qUgMgnf7cWbdBmThk9lUda8DZtKQQn2\naiFX3s/dWabD1ZOCB+RXJQ8r75KQsUKZ1mda86lCyhUpCljyMH8mBM4zIUQMFigXzmFYC4FzZVuK\n9G3c7vJpiIpjPq2MEpCPe7el3xfC+rEUpu1h2yIsQ5pgghQfAEAgAXllPUohhDKdESt06IQgeHX4\nEG0Theu7m6SnuWFTxgBAzHjhUtaSe0RYDw3QAyhKXkRSFuk265wX+SiUEHce0yFupRBL2d6KFGsB\nQEY+x6uM32fKNHMXoRkx25q/oTIzMzMbyR0qMzMzs5HcoTIzMzMbyR0qMzMzs5EuNZSujMLadOlN\nVEZ7rdY88Jy3wmjqi3QAvit5gFsZHTvmPHw3XadHp1W2ZRaE8KkQCmWjGSujMwelDQkIBzJiOABA\nCRkrYfEsfe3Gko8kHad8RGqseLEEZiT8K1xP2SEPpUO4Ftop2xYhlK6MbM2Or1D8EaLw+FvwhGqc\nkXuNFA0A2ijo0n1EwvqZMFK3UnyQLfno2DkJgyv3iHLs2Kj5yvXfTndpm6zjz45yk75f58r1rwT+\nA78X6TKUwH/k17+yLdOQ/twrgrAeYQT5iZBbr8njZS1MoHAef0NlZmZmNpI7VGZmZmYjuUNlZmZm\nNpI7VGZmZmYjXWoovcp4yPKwTodcs4yH2UohlK4EPqURtC9gGTHnodzQkiD4iodGpVHbFSxEKQTB\noQTKyfYGZX+U9SjI8UfFCy4gjKwfKh7cba7cnnxfCeUG5bpUQvRsVGohcCuNMs+C0+z8AEAuBHsr\nXtwRmvT13ZGigX4hfJ+l4DopVmHbCgBxIpxnQThMz1wQGqH4QCkuYKF0YdR85XmpHBdWxKPci0oo\nXSnu6Mi66ooH8ZVnaq3MuBHSn8Fr8PtM+bSaTXirB26kn1Gt9LG4fRn+hsrMzMxsJHeozMzMzEZy\nh8rMzMxsJHeozMzMzEZyh8rMzMxspEut8tsFr747BJnKQpi+ZjO/TtvM3/462iZO5sn3lele2PQp\nABCEaR3Y1CdKNQ9WS95Gqcq6iGpBZT2kKitu+LQ+QZn6QajKCjVfFyVUHLa3P4W2aWbpKptidUSX\nEee84keZKkS5viml+pEdf6GCLAoVfLHiFWLsXlPu51x4djTC9CjdhFRFb/g9H9bCc0GYtgSsuk6p\nLFWeY2SqqDDhx/ainnOhSN8jXSlUGRfCNSc8fwKZZihm/Dx3mVCVWF2lbfKYvh+X8WIqS5drfh4f\nuZm+piaV8j3T9jb+hsrMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEa61FB6G/jqA9LBukVxhS6j\naHmAr5vz5WTLdLg3CFNDtDO+nlwIfIZFelsimY4BAEIpTM9Bgo19m3RAPtZCEL8UQq5kOhEpfKoQ\nwqcsuN5NhWC7MN2RUuiQk6BxEELeHSm4ALRpk9iUSMq0SnT6GvDpOaRpiC5IzMhzjBSQAEAmBMEz\n4Vpgx0V5/pTHN2kbZWofVsTAQtMAEITpgdjzJW6EKcOE9QRhOfS6LIQpY5TAv6AjBTiFUKBwvCd8\nLkZ+LTQk3L5c84KXTcOPy8GCNsGD70h/dr7P+17jCzmHv6EyMzMzG8kdKjMzM7OR3KEyMzMzG8kd\nKjMzM7ORLjWUXkcenJ4V40ekzjth1GQWLAXQ7qZHXGeBREAMCCsjru+Q8KMyYnXOjz+Ukd1JWDOw\nEZOhHX8WFpeCyMII2sqoyUqIm4nCeS4OHxaWkz6+LRk9GwCyOj3adL+iiwh6C4FbJazMtkW4toPw\nXMBGeHaw67vg10oUgusXMQp9JAUkAJ8RAgDC8QFvQ0bzVkaqD2ueMg5Tsr1CMYV0bQvPbrocZRmC\nVnh2tGW6SEr5vNoo164yW0lMh87zjB+XZc2fHTcP+Hmc7aTv150535/z+BsqMzMzs5HcoTIzMzMb\nyR0qMzMzs5HcoTIzMzMb6VJD6WXgIUvWpux4aD2TRqTmI7WyEam7ioevlVBiaIWw7AWgYVpowVGQ\nAeKVEbYlJEQclcCnELhVRjmPbDRjIVidH92gbcKah8W7a3eO3pYohLijMLI+K6hQgtXZht/TdBTu\n5TFdBhvhH4A0Ijiq9M+lnXCfKYUokYx8DfDRx5Xjr8yy0N12N98W8hxjo+oDWlifPaOC8vxRRidX\nguukuKar+PNHCpwXFzBqvlAIVDV8NHVlOTHfS77fRf7dzrTkx78s+bbcfnv62OUjvmbyN1RmZmZm\nI7lDZWZmZjaSO1RmZmZmI7lDZWZmZjaSO1RmZmZmI11qlV/R8eqLTZZO5LdBqHzBRUyZAVqhJ1Xn\nBWGKCamaJF2V0lak9A6QplhRsIq3mPNKEWWfWdWKsgylmmozvcKXQypbyppXmeXH+3w9e9doG3ZN\n5Rs+fYcyPU0rVCjR61upOCyESthm/JRUyjREUaiyxIwcO+GejwWvBKwnu7RN3qS3V6hlAyK/dus5\nvy4z9rxUKp6FCm12fINwbJXrUsHOo1JNqzzHpGNHlqNUv69m/Dx3gV9VyvQ0dFtq/nmVCxf43m66\n0USYke08/obKzMzMbCR3qMzMzMxGcofKzMzMbCR3qMzMzMxGutRQetXywGdAOizYZDxBtp7wkHEl\n9C1Z6FyZGkLRXUBwkU6NIq5HCdTSQKcwrY8S6GeBz1YIn3Y5b9MIbVjgNhP2p5vxkLGETTciTL1R\nCAHteu82vi2kcCCrhZC3EhDuSJtCmA5DCZwrU8+QJKwSRFau3U3JCwdmJJSuBNvriq/nIuRCsFq5\nXuhzVyi+Ca0Qfr+AYiFFpqxHwD4DOqGgiz3nAGBZpaeVAYCjOl0kdXPNi4VuHPJju17zY8eC6zP+\ncQWcE7L3N1RmZmZmI7lDZWZmZjaSO1RmZmZmI7lDZWZmZjbSpYbSOyEsmMV0KC5CCDwro3ALgfLN\n/Hp6PUKATwmLK8th2oIfl1YJpQsj3GZdOtDMzqGKhcVboUBBUbR8FO6chFiVc7jeu4tvS81Hme/I\nNRXmQlBzI4xmf0EzATDKvdhevzv5fr46osuQfpqc8YB8O08XvXQXVCyhPMdW0/Qzqtrw43I8v4O2\nySO/FgIpLqiE2QSCEJAvVwfpZQj3YjcTZkdQrss8/dxVnv/KPaSMTs6eC5uCz3ywznmbw5aH0m+s\n0ufxcMmP7TF/RCETbupJlT6+00r5vNq+In9DZWZmZjaSO1RmZmZmI7lDZWZmZjaSO1RmZmZmI11q\nKD0nYWaAB+sUSviOBSiVbVFGld2UfFuU4xJI0LvO+cizTSaMGh540LuLZHTscDEj/zYxvS0BfD3z\nyEO5Vb2gbbKuTr6vjEi9nF6jbaZC4cb08IHk+13JrwVldPIojD6+maX3Sbn+SyGIzwohpg0f+TpO\n+LbEgl//NQk0K8+Fcs2vy8WEXy8FuS4P57wQYhF4yLgKvHCj6NLnQJnlIgrXf0XuNeV66jJ+bTcF\nv49qEkpXwuRRKARSlsM0ke/zouX3yHHDC6DWTfo8rmthn4WPkabhz7EdchuN+ZbJ31CZmZmZjeQO\nlZmZmdlI7lCZmZmZjeQOlZmZmdlI7lCZmZmZjXSpVX5lw6sv6mKWfF+ZAkEZPl/BpjZhVS3qtsSc\nVzy0MV3lsYq8IiV2fD2rllcC5lm6/CK/oCq/GNPbGwKv8CjzdBUUAOwIU+VcxBQTylQ5dZm+/gFg\nIlRCMasr6alcAOBwyqckYdVHxx2fSmQ248+Fa8t30DZMO+PVbK1QCbieXk2+r1SqRaFqS7le9sPt\nyfdXHa/Iajq+LTtCxWcZ0usqMn4vBvB7elOln3VlwSsSlaq5OvBn4Sam2zQdP26d8D1HJlQ0Mxth\nW5ZCBd+q4cdusUrv04p/dGKx5PtclkJVKNnt4/WtP0/9DZWZmZnZSO5QmZmZmY3kDpWZmZnZSO5Q\nmZmZmY10qaH05SQd5gSANqQ3UQmCLzMehO1y3rekU59kwvQdJFgNAC2ZygUANl06/KgEDjetMN2C\nEFxn29sKywi8Cao8HRbPhVB6qITg+pSHWCd1eqoQZSqjnEwTAmhTYhxdf3ry/YYE6AFgmfOpcg6a\n9BQrALBo0telco6qSkioEl3OA9yKRpgq5+YkPZ1LK0zxUQttWiEs/sAiHbTvhOcPu88ALSzekOfC\nvODneTfnU/Kw5/ISvLBD2B06xRYArNv0trD3AX7cAO1zhD2Cmk74nBEC50qI++ZxenuXa+WzU3im\nZsIUNsK5vlX+hsrMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEa61FB6VS9omxuTpyTfX4MHbjsh\nfJcFHhbcdOk2q4Yvo8r5yO5KWLwmAVUlfHq84etZbYSwfpteV6aExYVQepGn93la8pF0s8BHkM+r\n22ib2SQddK26FV2GMoL2Gnx7FyEdnI4QigJafo7YNQcAizp9D5Q5P0fLjoeIj6bpEcE3Qpg874RZ\nFgq+nOM2XfSyv+HLUMK/y5q3YfdrkfPz3FVC4Fm4ptZkn9qK708+4QF5RhmdvBWel0qhDyscUMY3\nXzfC878RnsukGIg9twFgXQuzaQg1JBtSf3N8LDy7ha9/lMA5y7YrRVTn8TdUZmZmZiO5Q2VmZmY2\nkjtUZmZmZiO5Q2VmZmY20qWG0ouGB3eFzDmlhAmVkX+XTXpjVkKwdH/JQ8bK6OQFGZV9IYTJ2ei1\nALAWAodscNogjF4rDFSPQJLrV3f4ekphBO1Jnh7tG+CjJh+Dj86vjJqsBMGPN+ntXQjFB+x6AoAg\nFBcwubCeVcuP/zpL30fLnB//JhNC3sK2HGzSIXoWzgaA+/eFWQuEfDYL3BY5v0eOlvxmvLar3Gvp\njVGec4c1L1BgW6sEwZUR/JWR6mtSAFW3F/MdxkYIlG9IoHy54ctYCh/Ryijnm036LBwf8wKRnZ2L\n6a4cklo4YUD2c/kbKjMzM7OR3KEyMzMzG8kdKjMzM7OR3KEyMzMzG8kdKjMzM7ORLrfKr17SNleb\nh5PvvyN7Gl3GquGVOoolmRLgeC1UgTQXM9w/q4rb8KIJHB3zcobjBa+RKctbH6r/RCUsYzplU9yM\n3gwAvJoTADbZ+FuHVecBwIMHvA2b+uFwwc/zpOI/W13hM6jQqU0uqsppXqTPEavCBIADYUqYwzWv\nxFQqFxnl2j1eChWSq3Qbdg8BwESYemYqXC/lLF2WqExfo9wjB0sy3VHBn2GzkpdQKtN5bcj1rTz/\nFcpyjlfpNspzoRUqS1kFHwCs1+k26zVf0WTCP18PD/kHX7eTXk7TKPfz9ue/v6EyMzMzG8kdKjMz\nM7OR3KEyMzMzG8kdKjMzM7ORLjWUjsjDbFV9nHx/MuNzo8wKYfoOIYjckOH+O2EqBRYUBIB1TZvQ\nEOtCCLAulvz4Nw1v0wrTIDBVyc/RDpm1Zz7hwcaq4G2UKTEaMp2RErhV2iiB5wW5phqhQGG14uc5\nkmk1AOAKmf6HzB4kY1PCRCFAnGfK9cKvSxZW7oT7Y1rx87wzU/Yp3ebomO9zLkzJc7QUpp4p0tfL\nQwf846cqhGlNSED7+Cbfn70Zb3Nlhx87FhY/XvF7qBbu1+Wat1lv0sdOuecz4SsXFjgHgOUyfezq\nDT+2x8f8g3E+59fUI4+kl6N85jmUbmZmZvZu4g6VmZmZ2UjuUJmZmZmN5A6VmZmZ2UiXGkqPQvix\nC+k2ATy0WGRKyGy8RhhVVgkcsjAhwEewVUZ7bTveJggp4hjTyxFWg03NG7HAbS2Ef/MgrIeM9g0A\nm3b8dam02Z3ya7e7mt4WqRBiw9ss18I+kXM0FwL/HQm2A8BxnS4iIZckAKAVRlNXllM36eW04wdS\nB8CLMhStUFig3IsQCioKNp2DYLHm66nIp9ixMCJ4I4w8vmn459XuLL0u5TPimE8gglp4vi9J0ZEy\nOnkrXLxKiJuFzmthao/pjHdXlM+9iozyz95P8TdUZmZmZiO5Q2VmZmY2kjtUZmZmZiO5Q2VmZmY2\n0qWG0ptyTtu0eZl8fxPT7wPAqkmPqgxoo5yzUavZSOqAFkpXRrZWwndMJwQOs5zvU0u2tyiUYDtt\nApZbPF7x0Oik4NdLK1wLszK9MauG31plzsOcZcHb3L6XbpNnfFvWJd/nA2X0d7K5rVAfsiEhbwBo\nSfh9LSxDuV+npTBTALl2lVHbS2FE8CjMoHB1J/3+rOLbciiEopW8OStGmQmjwy+FYomaZKtZ0QwA\n3Dzg53m9Ub5/ICOlP0GBcwBYrdIHphVuRiW43tTKbBrpNsq2RKW66QJMJg6lm5mZmV0ad6jMzMzM\nRnKHyszMzGwkd6jMzMzMRnKHyszMzGykS63yq8sZbbOoribf3zS8autww6v8qkKoZpCqPNI6ocpJ\nqaCpSeWKMmWMgk33AgArUmaTC1MMKZWA+wfpfZ5OlX3m14tyjh5o07fOhK8GV+e8nJNVEwJARqpP\n7yBVgACQCVPy3Jjy+0ipaGOU6sejdfr4K1WjhTDFUN3ym3FFKtE2wrQmU6HiLROeC6wS+dqOcC0I\n9+u04ss5XKQ3+HA5floZRSY8wzpWnio6WqTfV6b1USq4lelejo82yfcz4YNGqb5rWJklgIbMuaN8\nXilTpZUl36eKVLp66hkzMzOzS+QOlZmZmdlI7lCZmZmZjeQOlZmZmdlIlxpKbzOe3A0kXaqETxWb\nRpi2pEwH66ZSmE2YhkKYBoRNm6EEG5UgoBKEnUz4sbsIuTANDqNcL0pAuFuTYKMwlUglTCvDAucA\nMMnS1+XO5IhvS+DzmsyKPb6cLB2in+UruoxOuEceyK+l11Pw/ZkXfFuajj8ij5tJ8v0bi/T7gDbF\nTZEJ043U6Xtxb8KPSyY8l6XpgcjmCllxOt0UwIt4SmXqKyGTrkxhsyGHdyJM/bNY8pB3UfDj37Ht\nlaZ7oU0kLZmfSQmCK58z8zlfTkE+R65dufXPGX9DZWZmZjaSO1RmZmZmI7lDZWZmZjaSO1RmZmZm\nI11qKH222qdt4mx8ny8KIddVLYTiSIhYGMgVU55PxQMP8VBiTvJ5tRJKFw7tdMIbBTLKthKQvwhz\n4djuTHnKcm/Kg7tX5+lr6qKKJVjgXHFc8xkJQsk3uBC2ZSc/Tr4/i+n3AaDo0iM8A0A3TV+Xk7Cm\ny5iAh9KDEAQvq+vp9eT8egpQikhoE+yR0LOynqYTRhbveHB9PiEzGwjFH0fL8eF3hVLwojzHWBGP\nUgg0I9c2oM3mkJF10dA6tM+I9VqoHCA64cNzd5dfc0pB15zMqPGMO/izA5hufdXfUJmZmZmN5A6V\nmZmZ2UjuUJmZmZmN5A6VmZmZ2UiXGkrPWh4+Ldp0QGy3XNJlrMqKtrm54MFdllusGx6IO17w8N1q\nxc1NqoQAABPmSURBVMO/ZZnuCyuj+iqj7SqhRBbWVMKPdS2MFE22t4vjR5gHgFIIIld5Ooi5bIRZ\nAEiYHwBKsh4AyEN6e5uOn8Qy8PW0gY9U3JBHSh75epTg9F3NW5PvR+HCnaxuCtsijGY/T9+vs3KH\nL0NYTyf8/MsKcDaRPwuVIp5CGMG/yNPXghKyV+6R/aPxMzVMJsqsEcKzg4zKPt+eZX4XFXm2A8DB\n0fjneysEwaXZNITz2NTpe6SY8eflVAjrs8A5ABTkcqnyWy8E8jdUZmZmZiO5Q2VmZmY2kjtUZmZm\nZiO5Q2VmZmY2kjtUZmZmZiNdapVfefwIbRNiuvrl+g6v8FiVfE6SacXbsOlplCkQpDYXMJeCMpS/\nMpUCm+KmX056e1lFIqBNcbNHpnuphKt5tREqAYWpN65W6erTu6sH6DJKUsEKAOt8TtsctbvJ92fC\n1Cfrjld/KWoyJUmd8ftsVh/QNvPjh9LrmaSPCQAUjTD1TMcrfiZlejqdsuXrUXQZv8DZ8S0yfi0U\nBa/EnOb8PHZIn4O65Q8XpRKQPep2eAG39IwiH0UXhlWhAVpVdJan96lphMpeYaeVKdeqafq5MJ/z\nKr8ru/ximPDF0OnHMlI1nfy3t/wvzczMzAyAO1RmZmZmo7lDZWZmZjaSO1RmZmZmI11qKD0/vDF6\nGeVkj7bZnR3RNjsVnx5iuU4Hd5tbH7H+XSjD/bPQ+XrNN0aZema9FqZboNPg0EVgUvH1sMOyR6YA\nAYC9CQ/l7pY8RLybp6+pK8sH6TJaIWQ83RzSNsU0vU9KKJpN8QQAbT4+uD5Z8P3JOn6Osk16yqlK\nCJNn63SYHNBC6fMmPYVWV/FUdBTu+abkBQpFnj6PG2EZuTANUZHxNpNpelv26yt0GTHyuVpm1fgp\nqRQX9XxnjvlsaqiFgiI2/VjbCtOgLfn0cMrUM2zanrLiSfwdYdqeXJgSaW+avnaVIp7z+BsqMzMz\ns5HcoTIzMzMbyR0qMzMzs5HcoTIzMzMb6VJD6Wh5yi8W6SBsF3iYLQdfT5nx0VHrJh2sWwtZtkI4\n4mzkcUWe86RgJnSnlVFw2XI6YXeUEdl3pumNuTLlAcqrFU98Xsv5CP6TZpF8f13yIoe8E4K9K164\nUdZkpO4jvox8n4foIQS04zodgO+OeIGIVJSxSZ/rfCokWIX1BGEGhWJC1jXhy4jCbA7lhIfbm1k6\n6J1P+D2i2FR8JPpNnj4uRcWv/y7eQdvUs/QDaLnhD5elUHyjPC9ZQFsJtq83/KG7WfOHKgudK4Hz\n5REvVlFcuyN9vVy9yoc4n0+EfRY+a2Zl+roLQfjQO4e/oTIzMzMbyR0qMzMzs5HcoTIzMzMbyR0q\nMzMzs5EuNZSuBDFbMspwU/BldEK/senGj6ZbC6F0IYcvjWBeb9ILUkaeXa14KHQ255fIcpVOAl7Z\nu5jLbEZCiVeEEc5nmTBquDBSd1WnQ+nKqOLS6OSkKAMACjJquDLaN2oeUO0OD2ib5kY60F8fpY8b\nACwf4CH69UF6n2e38dB0MRMC5zs8CF5dv5p8P1T8HGYzPoJ5dvU6bZNn6fs+kvcBoMt5QFgZzb4I\n6edYHvnz544JfxZ2uC35finci13k+7za8M+ImuxSw3dZwmbKUERhGfWGb3AQhkrfrNPL2dvh53la\n8mtOqDNBRUb5z8OtD4nvb6jMzMzMRnKHyszMzGwkd6jMzMzMRnKHyszMzGwkd6jMzMzMRrrUKr/6\njqfRNqtZurKlznilTgCvZmgj71vOp+kqs/0joZqw4dtSVXw563W6EmG54BURWc7XkwllExkZqv/o\niFeK7O0IlUXk/TbybW0ir3JSrqmiTFd/ZUJlXdbwyrpamMKGtZkKlV1ZyadqyXd59V11LX2/lmRq\nGgAoZm+mbSYH6Sls8gmv7ArCfEflFV4tyKr4lAq+sMvXE+d7tA2beqae8GW0Gf9YiMKUX2xasHXO\nj0sb+bZM8vTzZZPzZexO+f3adXyfj1fpZ5BSnLciVdMAECNfUEPmuWlqYSopYd6wKEz3UpTpY1fy\nxz/ybHxlIwCUWXq/J+HWp9vxN1RmZmZmI7lDZWZmZjaSO1RmZmZmI7lDZWZmZjbSpYbSN9N0gBIA\n1mU6rLnO+NQQ0rY04/uWlRCsOxaWk+U8XL23l17ZwQEPPE8mPGTZNDxxyIL20ylfT8GboMjT29IJ\nhQWtEEp/YHMH35YsHb6+Uh7SZexK4V++TxHjp01q9u6hbfJrT6Vtpsv01DP5mk89MxGmpKpYuF2Y\nDiMUwg1b8bB+nKTbRGEZbIotAOiEwoHl/Pbk+03Oj61imfMQ/WGbDsC3F/DMBYB1m76PhPw2iow/\n54IQxGeXnTKpSdvyDd5s+PYuDtPhaiWUnpcX00Vg61oJOfC65dfL3oR/7lVZus063vo94m+ozMzM\nzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxspEsNpSvKNp1WWwQejswCD/Apo7B2XTpxqIQfFcro5JNZ\nui+8XApB8JL3p0uhTUeGyp2RbQWAiZAPZiOyN0IofdEIwd6G3xYlGWV73aZD6wBwM+OjVu/mS9pm\nEtIB7TbjB7ds+QjmnbCcpkyPft0WQsj7qcIo5216JoCY820Nwkj1seDbwoaKroXim03Fn2ObggfX\nN1n6+CpFGavIz9Gm4cf3kVX6WmD3M6DNctF06fteKdpQ1iM8li/ERYyCDvBR2ZX1KK7exmdzqKbp\nZ+p6w7dluVFm9uDX5Q65p5XPkXPXf8v/0szMzMwAuENlZmZmNpo7VGZmZmYjuUNlZmZmNtKlhtJD\nx4N1NRnZtwzpcCoA1FFIPAsCDVHy1CIbVRwAypIvJyejqc/n/NSuVg1tM58JQ5gTwqDVyISu/V6V\nDhHPCj7c7mHNg70rIZTedOkgshaE5YHnVcnbTPP0PimjQBcZvxaqwEPcobgt+f684yPItzt81HYW\nos87vj9lwwP/tRCiDySUzmZ7AIBVlg5wA0AjPMeOm/S1oOSQm45f/0c1vy4PV+nl1A2/R6aVMoJ5\n+v1CKDjKheePUrhUkOfymt9Ckk4YTZ09d4OQsm9r/vmqLGdvL/05Xgg9kZYUhQHAYsM/r/bJ83JS\n8GfHefwNlZmZmdlI7lCZmZmZjeQOlZmZmdlI7lCZmZmZjeQOlZmZmdlI7/FVflWzSL5fBl7ZtSr4\n0PhlrkxPk64gKISCOFadBwCTCW9DCouwu8s3pmn4PrdCNUlOykmUfZam/mHvC1MGbFp+XJRtYdNd\nbBq+LbxqVKsWpPhthhj5epQpnKo8XSGzJlW7AJDRMw2Uebr6bpqlnxsAcFxdo22CsC11TFe8bcj7\nAFC3vIKvFa5vVsW3avm2KNeCcn2vyFQhtVBMVRZ8W+ZV+gLftBfzvUGRK1V+6fc7ocwyE56XHZtX\nRtC2wmdeybsI9YafyLpOr2u55NuyXPNnt1IJePM4/exQpkF7/jmv+xsqMzMzs5HcoTIzMzMbyR0q\nMzMzs5HcoTIzMzMb6VJD6UXNg6PVcj/dQAj5zSd8WocHdu6kbTISIj5e8WkqCiFkyULeAFCRbO+G\nzxiA+Xz8tDIAcP1a+jLa4zUBWG34Ph9v0oHaruQ/H9RCQFUJNjJK4JyFdtVtYdelMvWMsr2lEqIn\ngWalcGCapaeVAXhwfRP4vaiE31ngHABWMb0uZSqX44aH9QuhKIBNIdRKgXP+XFDuI0Yp4lGmymH3\nSCfcQ3nBj62yLWwKm0yYpuWisNx6Lsy3U5T8JGXCcuo6XTiwXPH1PLTP16MUMWzq9IGZT2/9HPkb\nKjMzM7OR3KEyMzMzG8kdKjMzM7OR3KEyMzMzG+lSQ+n56oi3ObwxfkXX7qZNbrtGwu8A2u725PvX\nd/mIsTeP+CFfb5RRcNPBuUI4s0EISCoZyrpJb68SxFxt+HoeOU4PYdvMxo8kDWjBXRZ0VULeV+f8\nelkLI1LfXKSPy4yMJA0AlRDKVcK9uxWfuYBRRupukQ6xtsKjrRNGoa87PmxyE9PbclTzwHmZ8XOU\nC202QgCeYbMAADzwDABVkW6k3CNC3pner4Uw80GV82MbyXlWZML+NOR52i9HKFyq0tvb1HxjGhIm\nB4Drd+7SNqzQannMq6iUgi42gwjAR21vdpV7aPux9TdUZmZmZiO5Q2VmZmY2kjtUZmZmZiO5Q2Vm\nZmY20uWG0oXAeTw6SL4fSh74zI/4evauP0zbPJJdTb7PRqwGgCnfXNzY58m66ZT1hXmAb1IJ4V8h\n5MdClEr4fS2E0h/cTy9HCY0qIfsiHx+WLYVlKEFYZXunZfokBQijoAvbogSnJ1k6XMpG8gaAjgTO\nAaAIJMQa+Xou6vFXhPRxmRf84m474doVziN7Kig/QSsj61c5vzAb0kQJiwuPH1osMZvwayEXnt3K\nrAXsfm1avp71it9nmXD8C3IfTWd8FoAoVPFMJvza7ciJ3Kz5OXrwfj6zynrFw+1Xr82S73dKxYVD\n6WZmZmbvHu5QmZmZmY3kDpWZmZnZSO5QmZmZmY3kDpWZmZnZSJda5RcXx7xRnU7/d8slXUQQ1lPd\nzdtM5ukKgqbl/dMJn8lCquxSpmRglKH8W2kanLSlMBuJUv3IKgEXa2E6hgu74tPHZVIIFXEFr2wp\npIqT8aZCJVoReM0Vm05EmVZGKFCVKt6YMgjVd4HfaBVZzo5Q8bnqprRNFA4Mq1arlWpC4fjPKn7t\nsilslGrCVS1UkCkXDKFMg9MIVX4Nue3rWplWhjZBJ1QLskrAK1f5Ndc0/BwVBd/gg4P0h4CyP4tj\nfr8e3DikbVjV+c6e8GF0Dn9DZWZmZjaSO1RmZmZmI7lDZWZmZjaSO1RmZmZmI11qKB0dD+62R+mQ\nWXvMh6OvnnIPbVOu0lPcAEC1Q6bVyHmAb1LyPuxt13kQk4WrFyu6CCl8qkw9wMLtpK4AAFAKV+KE\nzJQgbCpqfsmh4IefTzFBArmAGNAWVHn6ABfClDE7OS/uUMK/k5AOnyrB6i7yY8dC6bvtPl1GFALn\nOTm2AJDF9H2vnOdO2BZlSh62HCV8PSv49B3KctZN+qZWrgVlGqhAiiVyoZhCmVZJmU6KhdLXa2GK\nGyGg3QgPsis76SlWtGc7vy6V7d2s0veRND3Zglc3PfyWB2gbJs+v3/K/9TdUZmZmZiO5Q2VmZmY2\nkjtUZmZmZiO5Q2VmZmY20uWG0oW0crdKB9GyQtgFYbTp0PJtqWN6XYsND42uax6+u74rBD7Jcq7s\n0EXgkOf5JRnZJWV0YCW4y0aHn6QzmACAjRCQV0ZcLwsyInUjhNJLZZ95+DS7gFDuRQTOAaCM6dGM\npzUfybjL+D2ddekTmbc8WK2E0i9CnfGRl4vAL8xN5M8XNhL6JOfHZdPy488C54p1w/cnE8LvbFYC\nZUYCpYhEwWZzUAqBlCB4NeXHn4XOJxN+/G/u83u+EAqtWOi8KPm25EKbDekvAMDx/lHy/d0rc7qM\n8/gbKjMzM7OR3KEyMzMzG8kdKjMzM7OR3KEyMzMzG+lSQ+lxwwNkWUWGx1YIw3DHjAfeWhIKfdpV\nHrh9y8092oaFvAGgadONlPB1LowIXgrBaboeYYc2QnCdUbZVObYs/A4AxysyIvWMB8Hrlq9oVgiB\ncjKyeIBwMQgy8G0punQqN5BRxQEgE2ZQUELnTFPwsLgSKGejtisuYhkADz0rswmshVC6cu22XXpj\nWqEQRSlW2ZukP0eUAH2RKYUztAkuos6hafg90tS8zd5e+gEfhIdh2wrPH94Et9+ZDnofHZI0P4DF\nIZ/NQbE8PE6+r+zzefwNlZmZmdlI7lCZmZmZjeQOlZmZmdlI7lCZmZmZjeQOlZmZmdlIl1rll129\nRtuE3XTFT1ykE/sAgD2+nljwasK741uT7/9Z8750GfOKVzDdXPDTwqr4rsx5ScrbHx5fwQcADdmW\nKFTQKNV3rPhi/4BXZ+zM+M8Q2ZRvS02KzCKpvAOAHWHqh1qYzqjK09dUHvg1V2bClCRRqHjL0+dA\nqfJrMqGyt0hXDWWR77NSWdcGfi925OdSVoUJAA2Z1grgVcYAsGrK8dsiTMOyEar8WFXc/hHfnzuv\n8grVlky3o1TwNaQiEdAqG9mzcL3h1/9ywe/F7AIq9NgzDACqSpgSJufbMp2ml/PAO3iVXydUP7Ip\nbgAgJ1X/SvXjefwNlZmZmdlI7lCZmZmZjeQOlZmZmdlI7lCZmZmZjXSpoXRp7pMNmcpiIiSIi3RQ\nEwC6nB+KvE1vS31BYU42ZUPfZtz7qlqYEoYFJJVpZTKha9+SnHEU5oZQpoZoeJ4Za56hpB45upjb\nbzZJ71QehOMi5DDLwAPCkVwLdc4D51kQgusxfU9nQhC/Ap/6SgmLr7r0MyiCH9xGCJw3JHwNAJs2\n3Wax4c/CVphihU19BQBFnl6Qcp8pYXGlDVMLx/aRI/7wODhM79R6JRRLCDfjRChoyckcWp0wZ0w1\nET4XhVB606SvhVqYK63e8BR9OeHPF9amqm79uexvqMzMzMxGcofKzMzMbCR3qMzMzMxGcofKzMzM\nbKSgBHnNzMzM7Hz+hsrMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZy\nh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzM\nzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxsJHeo\nzMzMzEZyh8rMzMxsJHeozMzMzEZyh8rMzMxspP8fdgyN/67kkpkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e31c7eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KGzfdSA0qPk/KgW3jqvhOBn/+rwZ/+2uLr2AaTPldMjVNUtm4qnu2jZ16Jqj4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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e3132be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rymwm844/f1Ylb9ORfse04iH7s/gTKjMzM7OR3KEyMzMzG8kdKjMzM7OR3KEy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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e31034a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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sjgfKPed/QUb7BgBzFG40WbzoYpnzZSwz/p6PGr698yp+fhu5nwK+a5EVZUxy\nXrk0HjpmhCD3H4AXC3kKa/KUb6/nflmSUeaXqePcbvi1mJPzHwCa8ZXo65OUfxbRkfcBJDs8uJ7O\nScGW43q98Fdv+TdFREREBIA6VCIiIiK9qUMlIiIi0pM6VCIiIiI9qUMlIiIi0tNGq/w8lrzIgJov\nHZUijmkotsbxYe13skO6jGnhqc7j1S+0WiTw95OVvLLFUy2Vz+PvOz14hC6junwHbbOYxqc4SAb8\nPbPqPMBXzVOSKZHY6wCQpPw4D1M+lcK2xfe/Z1qlxlF95JkSo07it5TgqNqqHdWnbO+ao1KwclQN\n5aSC1cNTkVWRKWMA35Q8iyxexdfQPQcc1byyd2/JqwXnZfxcyBJ+vXqMsvg9ynM9Zzm/zw2MV7MN\n6vj5MljyqWdY1TQANI5KtIRU1Ca5Y0owx77zfF5VSfxaKx1TGXmq32vH1EoJqVw3xzRQFy77ln9T\nRERERACoQyUiIiLSmzpUIiIiIj2pQyUiIiLS00ZD6ScnPHDLpp4pK8dQ/hkP1t0+5AG9a+N4+He7\nuEGXMZ7xNovxZdqGBRfz+QFdRrokQ/ADyAtHKHc//p6Kt72NLiLb5VNZbD39WdHXRzs36TJOtu+k\nbRY5D0iyP0WW4CHjIvBQ9DjhhQPj4ij6OpsaBQDKjIc5Pco0Pt1I5QicH4xup23yQKbbcUyZMUt5\n+HoQPEHk+DGqjd9mPYUD5ig0YWaNY7qdhm+vZzqvySB+f59mfN/uZvFzGwC2673o67mj+GZ0xO8d\nLk08OJ0WM7oIz1RF5ihiqMnUM57zqXYUbgyX/BgtSbFElfH3kzS8vwDHFE7ZmHw2ZrfeLdITKhER\nEZGe1KESERER6UkdKhEREZGe1KESERER6WmjofQH/5IHp/GU3ejLV6/GQ7AAsDXmCcprEz6C7TRh\nIW4efl+OLtE2jSO4mxXx0cezIx5+x/V30ib1CQ+uLx98OPr6wVsfpMuoFjxweOnp74i+Prn3vfgy\nrvHAc9jmxwgkOFqPeeB5uRUf+R0A8oLvf6viAWzX6MFkGQBwMuHby0cz5ud2FXibcRO/XsuE3xca\nx6jtnhHk2bpmxs+FaeCzLKSOEPGwioeeU8dMAdsZD0Vfyfkx2i7iQW/PqOHjd/KClub+N0dfLx7h\ngfPFMQ+LI3GMuD6Oh6trVmUFINvl50t+F7/XgUw+Ue7cRRfhuY7KseNaI7MFsBkWAN+sHZ7ZD/bv\nfE709e299/R2AAAgAElEQVQD/rl4ET2hEhEREelJHSoRERGRntShEhEREelJHSoRERGRnjYaSl/M\neRDWLB4E3JrwoOClCV9PZjysWSMerCsco02PyKjWALC9x4OY6V/+efT1+uGH6DKO/iIe8gaAxb4j\nlH4YD3SWcx44N0fgc7EXD7FmUx4+DSU/zuk2DwiHOh6QzC7x0e7TcTzMDwA44eeLDeNB2GwaL+wA\ngGrCRxgekpGXAaDK4gFVcwyxPasd6yFFAUdFfGRmAKgcofRLAx6cHlp8xO/a8XerK0RPgr0AMCrj\n2zuex0cVB4DBfJ+2SWf8GsGNeDFKWPBZGOpjvv/3//gt0deLY76ecsY/I6olv3fk43hYPx3wj9zB\nFh81fPIQLzqaPCt+754+zTHc/e7dtMki5yH6AuT8djza8Zz/npkYpsv4NdCkGildREREZGPUoRIR\nERHpSR0qERERkZ7UoRIRERHpSR0qERERkZ42WuW3/xCvOFk89Ur09eMZH2r+wX3e5vKIt2F2S15Z\nN93/S9omuf+PaZv52+IVevWSV60kOT/8wx3HtCVZvF9+5zOfQpeRX40fZwBItrbiDRwVfBjw4xxm\nvLKxmc2jr5tjigkb80o0lPw4glT5Ycmn1Shvu4e2KfIJbXOSxKsFg2N6psbRZl7Hq4YenvHzNjVe\n5ZQYf89XBvGKzwR8PUc1r5S6Dfz+kpfxYz084stITngFX/OO+2mb+jh+HWVXHJWwO7z6dPvpZBqW\nhk/Z47F4hFc/zm/E952nmnldbcI8fi7kD72dLmM05Oe/p8qvIRXyJyD3dgCJ43pNA/8MCGQ6qXLI\n389F9IRKREREpCd1qERERER6UodKREREpCd1qERERER62mgoPXEEd1MSvrt+nU8rMBnzgOr+kofv\nnr51EH1954E/ocuo3/xHtM07X/f7tE0gQcvJVR7mvPTcZ9E2yWUeFjcyVH+Y8sBhM+ZBwConU6wc\n86lnPCFvW/Jzqiniy7ETHmzP5rxNyPhUCoEth0zTAgD5whFEnlyjbRKLn5ee8PWNOQ/r1w0P5TI7\nI0fgfw3MEUo3T+C2cUx9soxPVRRSfj7BEXgGmRIMAJJhvAAklI4pqRz37uGznxN9vd7m97BmyM+5\nXUeIe/qO+LRh9TxezAIAs3fywgGPUDmKdAhr4gUXAGCBh/5L0tUoG35e5gk/XxaBT+GUDeL75bZD\nXnBxET2hEhEREelJHSoRERGRntShEhEREelJHSoRERGRnjYaSp8fHtM2j1yPhyzveQYPHM7mPPBZ\nVLxvuV3ciL5uB/HXAWD+zgdpm3K2pG3SQfzQTe66SpeR3PsM2qba4UFkvOFXoy9nd9/NlzHhIXpP\nEJbK+4+IDwDFzXiBAgvkAkAy5UHYZsED8paQc9ex39Jr/FosEjIiO4AmxLfFE9A+mvPb0qKIv6dL\nUx6mLer+RTEAUJBArSdwvpXw/T+axc85AEjK+L0j279Ol+Ep3EhGjnNhDcsIt5NR0AEER9EFs5g4\ngut38fNyMIkXXdS7/H56+ToPRVdveyttk7BAv2O/JTUPtnuuaTazwaLi98s04cH144KH0stR/H0P\nprxw4NIFP9cTKhEREZGe1KESERER6UkdKhEREZGe1KESERER6WmjofRiwcPXhzfjYc3wtMt0GcfH\nPKDqUabxECUbvRwAxvfcRdvcfYmPJs0CnemUj/xeb/EgZsh4WLAhxzFzjNibHPPArU3ixzEMeMgV\nwTFq9ZAvp5rH33O1Fy+mAIDUEVxPJ3yk6JoE180zI4HjON8o+bWWkZHS9xwzEtw45EFwlrO/vMWP\n86Lk+6UO/BaZJ/Hz0vNX6+3Ju/h65vwayW7ElxMcswCwmQ8AwHb5uZCkZPR943vGKj46drUdL2hJ\nKh6yHy74vq1yfi0Gcq01jpHqm+kubZPdcy9fzlZ8v1Qj/jlTjHix0Mz4TBhFHT+nHjri99ws5df0\nIOOfwcye8YKuey74uZ5QiYiIiPSkDpWIiIhIT+pQiYiIiPSkDpWIiIhIT+pQiYiIiPS00Sq/7dsu\nGsD9UVUZrxC7/80P02XcdQ+vSDma8wqOajdeCVXfzadysTufStsMZqQ6BoAdkzaOyi5UvMrSal5l\nk999Z/T18oEH+DICr86gtV9rmlbGY+ve+HQ6oeaVpZ7qu+x2PlWFZfHKoeZgny5j7+p70za1Y6oW\nS+KVOFXD/4bbnfJqnu1xfP9eGvNqtrLh7+fGsWMqC7KcRclvs8ttXv24U/L3FFiFqqOC1TOVi834\nVDkg5yUcFXy24NOAJKP4fgmOyjrzVAIuT/hyivi2jB74c7qMQKavAYDiDl7lN9u6Pfr6Qe6YVszh\nsOJVfsdF/N58OOOVvVv8IxpkRjYA/Hpd1vz9XERPqERERER6UodKREREpCd1qERERER6UodKRERE\npKeNhtKf/n48oL33SHwKj6M9Ho58xrPj4TyAT2UBACeIh9Wyq8+iy0gDn4Zl++CdtE1OAp2BBULh\nC582Ax6WtXueGX09dwRh4Qhxg0wtw6Z9AIDkiAe0MeDh9uzueCgdjul2XO95mxdusOUkd/Dpjm4m\n/BopHVO1sMDnNOfhX3NMG5On8SIGz1+KqfH1VDW/MRwu4ueLY7YjLOCY1sQxPRCbfqke86lEEkf4\nPXFMG4NpfF22nNFFhJwXBbApbOqBY/qmlK8nX/LppBIWgHd80NTDKW1z83L8ngsAByF+75iX/D0X\nDe8izEr+WXO8iC+H1J4BAE4WfN8dzfj27g3in+NbpOAlRk+oRERERHpSh0pERESkJ3WoRERERHpS\nh0pERESkp42G0u99Og9IWhIPok22eeDwzms8NDce8iBaCPFtOUr4iOwj40FMPk4uUG9fib5ujpHH\nm5yHxcsBD0iiie+78LT3o4tIF46Rl0mI3jPacbPDj1HwBG5JuNTIPgGco007gvb1Vjx8utzmgfOH\nF7u0zcmSX0dXp/Hzm11DADDOeUK1IKO2zyt+a2PBdgBYlnx7j+fxbckdd9m3D/gxum37DtpmmB9E\nX28chSi1476QZp6wONl327fRRVSeQHkW397KETj3XPPFkI+gnU6vRl9PGn5uV459W5jjPTXx/Z8Y\nP/+HqWOmjMRxr0N8e4uKF1yc8FoJTBynZZbGq0Rqst9i9IRKREREpCd1qERERER6UodKREREpCd1\nqERERER62mgofTLm/bndS/HA4W3X+Ejelxwpb0/PsgzxUG4ADxzW5tjljkA5C3wG4+HTdH5I2ySO\noDcLpYPnGmE1b2RlfFvMEWxnI0kDQDPhAe2GhGVdAfkpD8h7wu0sRHx9673pMg73HCPrewLl6TL6\n+l7Bixw861lW/PxmzPj1enWHt7l51P82+vAhD+Vev+te2uZq+q7o66njOvOoHMUqZUauEcd9Lqvj\n5xMABLDzhQ9V37gKURzB9Sz+eZR73o9jNPXMcVOdpPECkWHCz9uCfOYBQBM8+yW+rktTfp0Nc74e\nT6CchdKnjgI14Pz7j55QiYiIiPSkDpWIiIhIT+pQiYiIiPSkDpWIiIhIT+pQiYiIiPS00Sq/g0Oe\npt/ZiVcZLJe8UmQy5G1qXgiCZU2q/Mg0OQCQGX/Ph5eeStuMF/vR14eH1+kyrHZMGdDMaRtU8coV\nq3hFSsh4NQnSeJtmyqvzgmPqjZD2r8QspvGpgQCgyHml1KA8oW1YNdUjS75fbh7x/fK0a3zuhzqQ\naVgc01R42ozSeFVQ7agUNOMXfXDcF4xU7i4chbKZo2jRMz1QOYhfI7dlD9NlpA2/Xj1tqiS+LfOU\nT+Vijgq9IblHDUte/ZtX/NxOAj8vqzRerempvq4SXvEZHM9C5k38vpA6Pos8FXx54jhfyDU9yvj1\nmjru3fOCtxlk8Xv3MOMVh8D5x0hPqERERER6UodKREREpCd1qERERER6UodKREREpKeNhtJPTniY\nbTqNBxuHQ94nXJY88HZpygN6ZRMPvK0rCIv0Km1STVj4ke+XwYJPPePCppDwTOvgUJHpXjxBTU8o\nvcqGvE0ab1Omjilu1rRfjvNL0dcfuRHfb14sCA4Ac1K4Mcl4QjtzTAkTUn6tMYuah3/zAb8vbI3j\n73m27D9NDgAUjul2jo2cd/k1uowRmT4IAMYpL5ZgPIFzPq0MMLN4uH055Od/Asd0Xw58ejJ+zS8a\nfv9pKkconVyLnuIPD1co3fO5R2QJP0YDR7i9IdPT1M2t35f1hEpERESkJ3WoRERERHpSh0pERESk\nJ3WoRERERHraaCi9dgxPnufxANnVy7xPWDvyhp4RkROLL4iF1gFgVvEgbJU43lMab7OYTOgysikP\n/6aBtzESSs8bHnL1hE8bMsqwayRjxyjEZeIIhZK/RSoSTgWAIfjozGy0aQDYr+IjaB/P+fl0Zdsx\najJtwXkC57mjDVM7/lbMyPUM8NkRPIaORXjuP55Q+iSPB4Q9QXxPWNwcAWF2v/SMwu1RBPKeHPu2\nCvyjsHKEldl9zPOeg6O4qXIshx3H2vF5NXIUkSSe84W0GaT8/jOv+IXEAucAsKzibYakzxGjJ1Qi\nIiIiPalDJSIiItKTOlQiIiIiPalDJSIiItLTRkPpizkPn968GQ+I3X4bH5F6kPHQXFXzviULFHpC\nrp4g4NIRSmThx9IRZvaET1mwFOCjDA9SHmx0jSBPeAKfNMAKoK75MWL7PzUesrxS7tM2R4MrvM0s\nfg2Mh/wYbg35teg5d8dZvADBc84NjBcxsKKA4DjOnmO0bPj9hYWIt8Z8/x/N+Ll7suRt8iz+vllo\nvcWLMjzY/vVc83Xg5xxr4wl5N46imHUUKHjec1Gv52OZzWyQOkZK9xSRVI5jxEL0S8d79hRuVI5Q\nek3aJD0+i/SESkRERKQndahEREREelKHSkRERKQndahEREREelKHSkRERKSnjVb5ZTnvz5VlvBLh\n6ISvZ2fiqSbhy2FVfJ4KjsMlrxTJEl6pkJGpH4qaL8OzvZ4KmZRsS2nrqThkVXye6Rg878ezX1gl\nyCSZ0WXM823aZtbwKYSY6ZBX84wyXv2VO6qCtrJ59PWh8el2BnV8GQBQkyrWGrzyyHOded7z9shT\nOReXOK6RRXHrU2KcOlzw6sfpkL+fzLFfiib+8TJM+XqKhu+XmkwJ45nWal33BVah13gqDj33XEf1\nNWvBrxDffdlTicnu3azyDgDGOa84nBW8SzMZxPfMVs6rjIHzq3/1hEpERESkJ3WoRERERHpSh0pE\nRESkJ3WoRERERHraaCg9dYRCDw/iIdb9Qz5Nwm27/G1e3uKBt2keD8uelGO6DE9A0oOFBT3TsMxK\nHvhcR0AyT3mA0hP+Xcd75lsCJI4ChRE5FzxhzgV44HxW8alPxiRQPsn41D8DMk0FAEwTXgEyCvEw\nvjnmj8hrHgplofQReLB9hi2+LZ7pOfL4WcWKNgBgkPL1PBz4ubAoyfRYjpP7xFE449kvjCfMPK/4\ntiwrT7w6zhy35bLq//zBU/zkCchPHVNF8anS+hdTAL7PNFbQxYqsAF8Rw4BMvQQAk0F8OSPHVGkX\n0RMqERERkZ7UoRIRERHpSR0qERERkZ7UoRIRERHpaaOh9Lvv5iHu0Ti+iYkjTejIwdKRrwEe8ptk\nfBToBRlJFwAqMvIvACxrHtZkPKPTegKH7BgUNQ+Net4zCy72CRM+kfWsy6zm5/845QHtQRIPWSbg\nAeIh+Lk7Lg9pG5DzZZnxIH6d8Gska+LHukx4sYpnv0zJyO8AUDQ8CMt4Qt6Xxvz8ZteRp8jkYMb3\nf546wr95/LycVXw9s4Lf5ypyH6sdl/OShPm9sjT+OTIio3QDviIez0jpg4QH15nM+Hnp2RbW0/CM\nQu/5zNsZ8vvl5eFR9PWBKZQuIiIisjHqUImIiIj0pA6ViIiISE/qUImIiIj0tNFQ+j138DYns3ig\neTjkIcvRgAfeqpr3LY/L+EjF22T0bADYHfA2JxUP1LLRdFlQEwBKx3uuHSFWNuBx6hideegYqZup\nGn46e8KPlSMsOyKjj5fGA5SXs5u0zbCKjzwOAIe4Lfp64giNetaT1nyk4jKPB+2D8XOuTPmI4Ovg\nGc0+g+O8JG/JM9q95xjVjpkALo3i9xfPbAIA396jBb9GWCjd834OyP0f4KHz1PGWPYVLpWNweHZf\n9swOMhrxFXlG1mcj9OekmAXwFW6w2REAYJTGzxfDLl2GgRdCeO7vbIT+YeCf0RfREyoRERGRntSh\nEhEREelJHSoRERGRntShEhEREelJHSoRERGRnjZa5Xd1m093ce22eNXQ0jFKfOMo4cgcw/2zCplF\nzasQCkcl2jokjsq67SGv8lg6po3xTGHD18P3yzrWM8gcVSuOisPM4m12wj7flvLWq0nOMnLueqrZ\nipRPgzPLdmibNPSv1vRsb23x86UGP2/LwCsxWUUQwO8Lews+3c6i4usZ5/zcZfvurvxBuoxpxiuu\njof8PZVN/D1t5fzmvZzw/fLwYbzN4QldhMuUXyKoyCFaFJ5nGJ6pfxzT09Txc2FR8fN/mjvuy46p\noipyLngqYbM1TKUD8Gu6JhWJMXpCJSIiItKTOlQiIiIiPalDJSIiItKTOlQiIiIiPW00lO4J/962\nEw/WLUseVJ4OeZjTE3iekylJ2OsAsDvkQXzPdC8sxF04wuSeKWE8+6Uh25s4igI8oVwjm+IJak6z\nJW1zOT+gbXaWD0dfHy74MrIlT8ue7N5N27AgcuUIX+/XPIg8Tvm5ux3i79sTOK8Svr0sUN44QumJ\nY1saR5vDIh7QnhX8vnB9j/9te3nbMfUMmbWKhfkBYAAeFp9kfFsa8vf6VnpMl1GH+LRKAGAWf9PH\nQ34uzJaOqbocmWg2zQ2bJgcAzDE909GSXyPLNP6+E8c0LZ6pXELq2HcklF45piHKHTVJOSkWAoBR\nEr+PJcFxkC763Vv+TREREREBoA6ViIiISG/qUImIiIj0pA6ViIiISE8bDaWzoBoAjPJ4QKxuHGE2\nR1jZM4L2JIuHNWvH+0mNr8eR8cNkFN8Wz75lIzx7nZTxEeLLmq9n5BgFekpGVt7Oech7t7lJ24zn\nh7TN8ORG9PXsKP46AMARPs2mPJQLMkC/wXH+J3zU/Aw88Jk38dD/yBHWX4x4QL5M42+6aHho1xW4\ndRSIlOQetCj6j/APAO96hLe5th0fcXqS8eG+K8dsDgH8Pd2OB6KvZwUPv6cjx8wG2eXo63nKR3Xf\nGvFrcV7we+rWKH6NeIp8Bhm/Xl2BclJQwYp8AN/53zjOhcTi7ylP+HHOHJ+dk3RG29SBzLLgKNy4\niJ5QiYiIiPSkDpWIiIhIT+pQiYiIiPSkDpWIiIhITxsNpc9KHhxldic8KDvJeeB2mPI2ozQeomwS\n3j/1hH/XITMeoPTwhE/ZvvME8cfJnLep4yMr5yUfBX1Q8NGZ8yVvk1QkUOsYHR4lH3k8L3jQfjCJ\nv+/K+HU2Nb6eLDiC6xU5Bo79ktY8rFym8fdUOILVHp7CDTZTgCf86zEc8AXtzeJh/a08HloHgEHi\nKD5w3McmJ/ECEAv8vuBpE4bx/bK1xYPKy4ZUdgAoSZgZ4OdCRsLZgK9YwsNz32XqwD9HMsfo5CUt\nEuHb6jnnEkcBTmLx+wsrrImvX0RERER6UYdKREREpCd1qERERER6UodKREREpCd1qERERER62miV\n3/V9Xn10+2482T/KeYWBp4JvnDoqxEh1QHCU87Ah+AEgdVQ8sOo7R0EQnZrAKw3xYzCoeQVfvuRt\nWPVXVvJleI5Rk/LLwirytwipQvNqEkeVTRPfL+P6iC7DU1lXk+leAKDKhtHXPfu/dEyPkiN+TTeB\nTzfimZ4pdVRcjbP4tuQZP5/GpFINAIa5o0Iyibd56GSLLuP2Ka9yvZTs0TasWtZzndGqUQDbiM/J\nMxtcossYJbwS0HPuVohf9557rqeyugrrub8wuaOCz/U5Qm6Xmaea3Pi5wD6LACBxVI7eKj2hEhER\nEelJHSoRERGRntShEhEREelJHSoRERGRnjYaSq8c2TA2lH/T8DCbZyqFzDFM/wDxUJwnnNc4+rCj\nik8DwtTGD22d8GAjCzwDgIV40N4TLM1L/p6tiR8jY9PBADBHyBtkPQBgdTyIHFK+npDzkHfi2Ja8\njk9hkzkC51nJQ7lZxUP/y+Fu9HVPQNhz7h6U29HXPVPPeApEPFiIeGvI7z+eW/GlMT+OTO2YSsdz\nv2TXPABUg3hxQUKuoXZF/P7O7i+jpP/9FPC9Z6ZO+HGuEn5fyBzTsBQhXiDiOf8D+fwFfFPl5KSg\nq3JM65PCcx1xZRLfL5p6RkRERGSD1KESERER6UkdKhEREZGe1KESERER6endPpTORv6d5DyclzoC\n55k5ApIkezeseLDXHKO0riP8mIIHWIPx/rQnFN2QoKVnFO605EFAFjpPHOF3BMdIxZ7gOtHkI0eb\neDgSAKqMLwckFL0YxAPcAJA7wrInw8u0TRnigdqCvA4AZcOLJeZVfN8ta34ME0eY1lNokqfx65Xd\nwwBgMnDcFxyzH2zl8QIFtt8AoA6OgoqE3zuCxZdTp+v5ez5p4vfu4fKQLsNzXw5reP7gubcUAz6a\nvWukdLKqhjUA0Hg+I8A/rwZN/LxMHYUonu01xywj7Jr2FAVcRE+oRERERHpSh0pERESkJ3WoRERE\nRHpSh0pERESkp42G0us1DFTsGtXXET59sgyWx7RNSPlhsbr/qLFZFQ8KerGwuCdkn5R8W1iI3iq+\nT0LiSPY6wo8g4VLPe04X/Fxgo8MDQJ3Fg8aLnIdcPXcCTyj0oIoH4D3B6pvzCW1zOI+Hckc53/+e\n288o84SV429qkPJlDFN+7uZJ/23xjI6dO0bh9oxmzwoqPMUqDQm2A0Ag6/FcQ6njXugp4mHXvZWO\nSiwPR3CdzoThuRU6eIoY2HH0FH8knsIBxw1mXB1FX1coXURERGSD1KESERER6UkdKhEREZGe1KES\nERER6UkdKhEREZGeNlrl51HV8dS+Z1oZD1YdA/iqDNbCMT0Kq9DzVLZ4KutYBR8AWBFfTsgdVROO\nKRnoe2ocFZ+1Y+qZlE/rYGTf2fyEL8NT/eiYEiYn09wMHdPXlCmfkiRxTOswSuPni2damYGjsi7P\n4udL4pjupWn4Ne+5L7Bq5XnDj+H2gF9nWzmf2ioh1VKe6V7GyZy3IZVSgOP8dlRkee65JTu/HUW7\nrvtl4PeXhFUar6niMCGVvQAwqOPHsUz4MjxTDHk+g2vS1Wgcz3ZS8P0/KQ5oGzYl0jIZ02VcRE+o\nRERERHpSh0pERESkJ3WoRERERHpSh0pERESkp42G0pcFD47WIR5c9IRGPUHYYbqkbVhAsnYEiF1B\nzIZP/UCX4QicJ0sePjXH9CgoydQzjWPqH1dwnew7z9QzAx7QTg9u8G2p48coFDxkjNQRxOdLwXDv\ngejrCdlWACjGl2ibKuXHaJTEw/ieKUvGo8u0zTCJT3FTNnzfziu+LZ5pY1IytZVn6qtRxs+Xy/XD\ntE1CguAVm44EwGjOA+eD5SFtw4LeNSmmAIDGsb05CXF7pozxBM49wXW6Hsd92fMZkQ6mtE1FCk08\n+8UTFk8ckzh5PqeZ1FF0xALnALDM4lNbLRp+Xl5ET6hEREREelKHSkRERKQndahEREREelKHSkRE\nRKSnjYbSL287Atrk9SbwPqEnFGpkhGGAh/gc0WtUjlGrB4VjFGIygrk5gsh2vE/bhBkf8TvMyQjO\njtF2PSHuZBIPYobK8Z6HfP97jiPIuhpPKN3BPEUMo/jIvtmMjx6cFrxAoRpt0TYNGWU+dYy8n2zz\n8K8N4kdp7giWXhny82WY8GIVJgNfT17z9UxPHqJtaAGCI4icnezx9XgKN7L4x0u9e40uonEE1wO5\nRqx2jHDuuF96RjlngXLX7AiegiLPdZTF7wuebfFkyT2Bc9YmC3z/p47CAXYuAMAC8f2yX/D73EX0\nhEpERESkJ3WoRERERHpSh0pERESkJ3WoRERERHraaCj96g4PmaVJPHzaOAJxqSNmXAW+K3KyLjaS\nOgA0jtHUG8do0jkJLlqxnhF5Wfh6bRzb0pDwezPjwep6wUebznbjo3ADQCjj567ljuPs2N5kyEcn\nt5P4aPbmGinaEVB1YCFiT+B2G/GR3wEgncbPy13HdTYoSDEFgKzgRRksaO8aHdsTVl7wbaHXPZnV\nAADqh3n4vTjh+y4ZxM/d9DIvlkh2+aj5YRK/Xq3uP8I5AAQ2UwMAY/uXFG0AQD2Jj+TdrohvC5u5\no0hufUTwJ8ozmjrjCb8XaTxwDgB75W709etHfBkX0RMqERERkZ7UoRIRERHpSR0qERERkZ7UoRIR\nERHpSR0qERERkZ42WuV3acyrX/IkXqExTvkyPNPTzBue7M/TeGWRZ2j8xlLaZrDkU888aUilDsCn\njfFMn2I5r34pb9yMv34Yr3YDgJMH+JQZw10+9UAgVVmDLV6pk23Hp9IBgFA5KpSW5BpwVDk1BZ/6\nhJ+5QNqQilpHpVRi/Bhtkcq5asj3rWsanCWvrEvm8evVPNMQOaY1CUeHjsXE70FhyY9z8Uj8OgOA\n5R6/RyVZ/L6bOtYzupNPT5OMyRQrU1616zkvLXfcC1l1qaeaNuFXWp3ybWE8n4ueyrqB8XNqXVXE\nzFHYoW0OlvHqxkVx68+Z9IRKREREpCd1qERERER6UodKREREpCd1qERERER62mgoPTU+Jcw4jQfe\nho5A3CLwIfY9Ab2axHJrR+A8Bw+ohtQxbQmd4sOxnjEP7nqmLUmH8W0JMx7sDSWf4oaF25uCL6M4\n5kUM85s83M5s332FtvFM/JDv8IB8s4i/p2S8pr+bKl50EQbkXHCcc82AF4jUpI05QrCN4zoDuc5c\n62JBfQBWOraXTL0E8AIReK7nCd//2dIxhc0i3qY64VMvFTf2aJvBVTIlWMrvyzbiRSTs3HZxTIkU\nHD/QmS0AABT2SURBVEU8Vca3hQXKzfH5GwLfluB4LtOQxYwq/hlRJkPaZl7zNjeOeAHUrdITKhER\nEZGe1KESERER6UkdKhEREZGe1KESERER6WmjofSy4WFBFhafVHz04NoRSgyOkXJZQC83R1DTHIFz\nR7g9ZPGRchvHqL5IePg0cYQo7Xifr4sJPCCZX7saX4RjRPDLAx5InF3nQdh8Eg8/ZlMeGs2mjv0/\n4stJtuIjQRspGmjb8DBndekO2oYFymdTPvL1POcjW7Pg7rjkhQWDwlF8MHAUbox3o6/nQ36PSue8\nTTLnwd3mOP6emhkPgnuuo3TI7y8ZCbdn27zgInEE5JNr8fPSEyanI5wDqEeOc6GJF240meM6c5xz\nVcLvYzVpY+D33MR4sUQV+L5jn42eEdkPcYm2OSocx5q87Tzj+wUXbK+eUImIiIj0pA6ViIiISE/q\nUImIiIj0pA6ViIiISE8bDaXXjlFYl008WFc6Roz1BOsy8CBmifi2jBo+knHtCT+mPHBIR3ke8cCn\nOYLgcIw4nWyRsKAjIG9HPNjOwtWDAV9P+sgjtM34KXfxbcnjx6g+4oFnV+B2e4dvyzR+rIPjXCh3\n4oF/ADjYeQptU6Tx97R0zFpwXDlG6k7i52WT88KOZcZHx66MX4ssUDsZ8cD5cMoD59nO7bRNfhIv\nqMiPbtJlhMMD2sZzX7Dt+H2h2eLndjPgx6gmBTqVY+T9dUkrMjp8zrdlNuazLFSJ414X4gH5dQXO\nPctJSVh/nvFClJOC77vjgl+vZAB/XBQ499ATKhEREZGe1KESERER6UkdKhEREZGe1KESERER6Ukd\nKhEREZGeNlrllzmqA9j0NHPwYfoXNR/u3zP0PRuqf0kqnDzLAIAy5ZVQAzaFTeoZPp8LCa+WKqeX\n45uy5NWPmWt6oHgbc1QTpju8ggaObam2b+PLYcvI+XlpDa8+rfP4+XIy4dO9LFNeTTUP/Pwu6vgx\nSMCv+QVZBgCURfxvwSWpwgR81+Ks4tsySuMVTHkan5oGAJKcb8t4tKBthrvxNlnDp8caVo6Kw5ov\nhylyfs557st0GcafG3jeT17xaXvKPP555KlKLxz3/9rx0c2mZ/Ls2wb8Xph6KuST+L3uqHZU+ZX8\nWry+x7f3ZE4+xwtV+YmIiIhsjDpUIiIiIj2pQyUiIiLSkzpUIiIiIj1tNJS+M+BhZRZQPa55sHFW\n8vCvZ/j8PImH7wx8W8aJI9iY8u1lUxgMinhQFgAaFmwHABJsbLcl/r6XQz7FxMgR0E7KJXmdh3aX\n23z6jqQpaZvFOB7EPxnEXwd80zoUgQcxG/J30VHpmO5iztfjmanocE6m5OGXmWs9yzJ+Xg4d51Pd\n8HN774hvS04O4za/LSBzFJHsjPk1zS5Xdg8DgEHK2wwzfo2wdbGCIwBIzRHWT+PXfQq+3zJSWAAA\nY0eBDpt6yTOVkee+4MFC6U3gz1PKNW1LFeL77rDgF8m+4x51Y88xnU4VP6d2d/hxvoieUImIiIj0\npA6ViIiISE/qUImIiIj0pA6ViIiISE8bDaV7Rioep/Eg8nHJw2ypI4i5qHhYkIX4zBGg9ITfS/Bt\nGeTxIGZe8tGOzTFqtWeU4aSKjzJcD/hpNpvysHidxJfjGfnXFfh37H/GE/hcBr4tBwWfCaCo4yHK\nG8c8zPnQHt93iWMA4b2D+LXGAqEAkKZ8RUUZP3c925pl/BjVtWNmA7Itec7X47jMsD3l1xHbd+YI\nRW85QvS5I7c7IKO/e4L4w4zfo6bD+Mji45QH6AeOUPrcMRMGkzgqLhrHfawmIW8ACKTowvN55fmM\nXjT8PnZSxdscF/y8fNcj/CKpKv5Zzwo3POf/RfSESkRERKQndahEREREelKHSkRERKQndahERERE\netpoKN0zImxq8ZCZJ+R9uORhwsQR0DtckHBvPBvpNkg8Acmt6Ov5gI/IPiiOaZuUBM4BPmp7mfH9\nz94PABzV29HXM+P7bX/B1+M5p5ZV/NwdZ46R6mkLHjgHgEeO4uelJ3B+4yYP7noC5Qf78WKJxYyf\nT7mjiGFrJx5y9YTJG8ew7Z7gelHG71HBcaDHE08hiidEH19Z3fD9UjtGMB8PHQUgNRvNni9jUfD3\nfLyIb+90yIsyxgN+vQ5SfoMfZ/HzO3fcozyWDT9fijp+HQ0dYX0PNpsJAMzK+Pbun/Br/sZNxzEa\n8HOqIdcjez1GT6hEREREelKHSkRERKQndahEREREelKHSkRERKQndahEREREetpolV8IjiqPJl5B\n4JnioyLVJgCwrHhly2wRX1eS8MqLcRafSgfwTaHCpi2pU155UWfrKUtk09NUCd+W/WqXtplX8eUs\nSOUdAGQJL+EYpbwNq+JbVwWN5xrZHrNzl5/bg5yfu0teoIfpNL6uouDzOkwmjqla2PwRDosFP86p\nY4qVoohXzlXVeqoJh54KJnK+OGY+wSDj68kc+4VNT+OprPYcZvaeKjIFCwDszxxT8oz4McpIhXDt\nmcrLUWU8I/dCAKib+Lo898KKLAPwVSKzz+CjGV0EneKpbcOXs1zE7913Xrv1uWf0hEpERESkJ3Wo\nRERERHpSh0pERESkJ3WoRERERHraaCjdE74zRyiXmQ55Uq2s4yFvACjIyPeL0jE1ROABPkdWEwUJ\n6xcpn+7FExafYJ9vzBokcLxptgzHjhtn/Fy4bbDH10UmjkkQn44EAJaBH6NBwpPggzR+Ym4PeeB2\n1zH1iQcLEXuukXHOp5hgYVlPEHm+XE9BS0UO9WjAz8ss9QS0eRsW0E4df0InjrBylvTfFo/UsR52\n3XuKfE6WjpS9w5JM25M5UvaOGYbo1FcepWOKIU9RTO241tj16Cl48WBTLwHA7qX4Z32fehc9oRIR\nERHpSR0qERERkZ7UoRIRERHpSR0qERERkZ42Gkr3hOJSEjjk8VVfsK5xBCgnw3gjT7DUM/JslvBA\nc01GiK+Mh4wb40H8QcqHsLUQDwJmzZoSh0TqCNNOszltMwh8NHvGE4Q1Emxv8WtkJzuJb4tj5OvL\nA35e5tZ/9HdPIUoGvp7jZjv6etnw87/achSROO5RcxIQzh0j77MRtgFvKD1+rLOE3zE9s094tsVI\nocm84vefeg1FSesI8wPANO9/H2OfZwAwr/m56wmCs7C+Z996Pjs9n2mLIt5mxE8FjOmMEMBiwZez\nuxNfjqOG50J6QiUiIiLSkzpUIiIiIj2pQyUiIiLSkzpUIiIiIj1tNJTuwQKFs4onyJaVI/zuGJHX\nyBCqnt7p4ZKn7zLXSMXx4Hrj2BpP4PB4cIW2yZv+IW7PQOksRDl0hPk9oWhfoJwUKDiC+CHl6xkY\n37cJKQrwFCiU4KPme0LpSYgfg7z2vB9+HAcWT5/WCb+1NeaYtcBxYpbD+L7znE+pY2T9k2ZK23gC\n5U8W+r4zfi549h0rHPAUP00co/N7AuUpuQd5ihxqR8i7cYTS8zx+X/CsJ3d8FnkC/csyvr2eEfx3\ntvm+G434ggbkdrg15tfiRV2nd5+rT0REROQ9lDpUIiIiIj2pQyUiIiLSkzpUIiIiIj2pQyUiIiLS\n00ar/KqGr35OKvSOl3wZRzNeHbA94cn+YR4vZzicO6oQBrxqoh45qr9I9VEVeGVX5qjamjUT2sYw\njr4+TY7pMsakagsAKlLBxKZgAXxVcxUcUz+E+LHeDvz9sOo8r9LiVWauqUQc0+DUjmlwKnJL8VQ2\nevZ/QrbXU3nK9ptnPQDfv0Xg66kCv495qtXYtniqXD08FW8NqdAjRdNtG0eVZSDvyVNB5nk/A8e0\nPanFP0fmjmuxcVRfZ47pjFKyXxJHZbvnbKkcFYfsGJDbKQBenQcAmWOarTEptC+rW3/OpCdUIiIi\nIj2pQyUiIiLSkzpUIiIiIj2pQyUiIiLS00ZD6UcFD2uy0PnRjPcJRwMevsscAb0FGT5/7piBZcTf\nMnLHFCpsSp7KkfIbOoLgnhBr2cTTgqUjlOsxTuM7ODUeGh3Uc9qmTPn0QIswir+ebdFleILgnoA2\nCz3Pqvi2Ar4pPtZhWfP3M0x5sQSbNoldHwBgNW/jKZxhR3HhmB6rrNcTVmaGGb+3pJ6prxz3hUkW\nn36JhdYB33tmx3rguC94QumZI5Tumc6LyVN+jILj/p6T4LpnWxeOadtqRyg9S+P7N3f0RKp6Pfeo\njLylyjPzzAX0hEpERESkJ3WoRERERHpSh0pERESkJ3WoRERERHraaCjdM8r58Tze5zua8fXkjtFT\nl47RUVmwziNx5OrWEWxkI3kDvpGvh46RxRuL77tyDSOPA45RoB0h72HJR1NfpFPahgVh5yE+ejzg\nO86esPi8jofoT0oesj9Z8mPkGRGZXa+1Y+hlTxEJG2U7OC5VT8g1dRSrsFBun5DrY7eFt2H3qEHO\nF7I15OFrzycHG9ndU3wzcBQosHuHZ7R1j4FjZomUBNc99znPiPgDR3EBKxyY1/wg7p04ikjIDCIe\nBSn4AniYHPBda4Msvr2egpaL6AmViIiISE/qUImIiIj0pA6ViIiISE/qUImIiIj0tNFQuieIxkJm\nR8c8hbZY8n7jPXfwbUlIPm93ysNsu+P46MFAv1DcKc8I52yEbQAYOUZTzyx+DMrATzNPWJOFzj3h\n0yKf0DZZ4OHTEv1Hf68dgfNFzddTkHBp1fDz3zFoOA5O+HKWZNfNFnxFqadyYw1YsB0AEkcjdo/K\nea7XFTj3tGEjiw8cAWJPIUTjKFAIaf/R7HPHKOesTU2KWQDfe/a0Yfcgz+jwnnv30DGaOivi8YTf\nPYUb0yHf3sOSbIunDsIRSm/WUH9QVrd+/9ETKhEREZGe1KESERER6UkdKhEREZGe1KESERER6Ukd\nKhEREZGeNlrl99Ceo5qEzCGxXPIKg5s3+PQp21Ne/XV1N74tkyGvvLg2OqBtKkdVXOWoimNSUp3n\n3RZWuVI0jqlnHJVoaRI/1p6pdDzTyniq/FI4ylLYehzTmjSOv3kysl881VSJOaaYyPi1Nivix2A+\n4u+ncOzahmxKsqY/FT2VdetYxjqmuAH4NCADx/RZieN88VS8MZ77T26OqmhSWee5L/iq/NZTLciM\nHdPteCoBD4v4Z5rnfNqeOKa4Sfm21KSi0FOd52mzjuvVU014ET2hEhEREelJHSoRERGRntShEhER\nEelJHSoRERGRnjYaSj884oG3mzfjU58c7M3pMoZD/jaXJMAHAKM8Hr67Mubb4gkIj40vZ7/cib6+\ndITJs5ynf9OEH6N5PY6+njimhOFr4eZNfDsAYGA88OnJleaIh2Ur8JB3Br4t2wlvY6RwYzoY0mUU\nOZ/ixlWgMIn/jTar+HqOC95mUcaTo57Av+da9ExPwwLlueMaWlR835LDDIBv7zDj2zLJHOecY99t\nZbPo6+OE3+fS0L/4w1NAkgS+X04sfs9t1xVfTuoIk/vC+vw91SFegOM5nzxTz4wd0xlNhvE2i8Ix\nrY/jWmRTX3nW5Zme6SJ6QiUiIiLSkzpUIiIiIj2pQyUiIiLSkzpUIiIiIj1tNJT+8MPx0CIA3Hjw\nMP76AzfoMq495Rptc3OPj6B99VI8aJynPPw7yeIhewC4Wr2Ltjmw7ejrjkwuZtWItmkcQ89mJCA5\na/h6BikPWbL1DByjKg/B9/8yOLaXBEeHDQ/cDmq+LeYIyyZNvM3EkeasHOeuR53Er5FqxMP6xZBv\ny0nNr1cmS/g51wTHyO5N/DY6Svl5WZFlAEAd+HGsyQwKnsDzOOUzS2zZEW0zqOPXQF7w839Q8PUw\ntePcno8u0TajhH9e1eQjdZTwfctGfgeAReN4T2V8WxYlP7dZIRbgG1l/OowvZ0FmWACAOd91rtHU\na/KWyurWR7vXEyoRERGRntShEhEREelJHSoRERGRntShEhEREelpo6H0/RsntM1ywQOdzOFNHmy8\n/gAPIm9txYOLT73Ch2kdGk/WNQk/LNtpPCB5Y8lH9WUBVgAY8Sau0X8ZFjgHeOi8DDzwPDQehB3B\nMYJzHT/Wec2P86A45uupHMF1EkpnI6kDQPAMQ2z8768m7X9LKXMeON/J46Pi1+YYedzx96RnvzQZ\nCYI7RvuuHfvNE1ZuHMeIGVX8vjxc8ntqSq4Bdt4CQDY7oG2QkP2f8ZH3LfB72HLrKbRNFuL3Bc/s\nCIdhl7aZVzyUXjXxczc4ihxOlvwDwFMssT2Mv+93PMLXQy4zAEDp6C6wLoVnPRfREyoRERGRntSh\nEhEREelJHSoRERGRntShEhEREelJHSoRERGRnjZa5VcseMVDMY9H8pOUR/JTR5vGMWb9II9XM5QN\nX88y8OqMw/QKbZMZqSZJeNXKvOJVcWXgp0jTxPvlnmqSee2Y+oTs3swxrYZH1vBSkYxUMI3me3QZ\nackr+JKCVxyyCiWreJUZHFVOniq/kNz6tA2nBqRqCwDqUXzqJU+1YZVPaJvg2BZareaoFPRUvHmm\nIWIaMjWQd1syR/UpO3ebnF/zRqppAfBzN+Xv2XOcPVhVaAXH/ndU5Xoq6xyLoRaFo8qV3P9b8fe9\nwy9FHPNbIcaOjxH2Ub/sMbCAnlCJiIiI9KQOlYiIiEhP6lCJiIiI9KQOlYiIiEhPGw2lN1X/kGWW\nr+ctlAUP7h4exbf34SOeiLs85NM6zIIjLEtCiZ6AfGqOIH7CQ6H7y63o654A5aVhfCodAFjU8Skk\ndjI+lcugdoS8HVN8DIr4cfQEzj08U2IYm2/BE+ytHaFoTxsWSncUf3gC8laQ/euYvimZ8OmZPIHy\npOo/PZaLIyzOpmHxqId86h9zvGd27nr2Gz23ATTkOJZjPpVLmcWnMgKAZA1FAZ5QeuKYyqsK/FlI\nVcfP3dmyfwEJADSO+/vRjEwPlPD7gnmmx3Jg3Y4+szfpCZWIiIhIT+pQiYiIiPSkDpWIiIhIT+pQ\niYiIiPRkYR3DqYqIiIj8DaYnVCIiIiI9qUMlIiIi0pM6VCIiIiI9qUMlIiIi0pM6VCIiIiI9qUMl\nIiIi0pM6VCIiIiI9qUMlIiIi0pM6VCIiIiI9qUMlIiIi0pM6VCIiIiI9qUMlIiIi0pM6VCIiIiI9\nqUMlIiIi0pM6VCLy/7dbxwIAAAAAg/ytB7G3KAJgEioAgEmoAAAmoQIAmIQKAGASKgCASagAACah\nAgCYhAoAYBIqAIBJqAAApgBIViYFwlfu6QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e306ccc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CCCE6IodKCCGEEKIjZ5spfZ+L4sJKPMtz5cheO5puUptp4cjaS4Swk+EF2sJB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e3046e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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FqJpLwrEoy+m0KV+KMC54lZNStXLhyt20TTnPV2XFglfqtNsXaJuOVHw29Rbd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\nRJUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e30a74a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EUZD+Ui55RZyyxEq0vIKJVgIK+0lCNcn+re9D21zZzre55fKf0m0g8SUblIor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\nzzcr3W9P5KlZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e3186e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "principal_vectors = wlra.H\n",
    "\n",
    "for i in range(9):\n",
    "    cvec = principal_vectors[i]\n",
    "    max_mag = np.max(np.abs(cvec))\n",
    "    view_as_image(cvec, cmap=\"coolwarm\", vmin=-max_mag, vmax=max_mag)\n",
    "    plt.title(\"occlusion weigted principal vector {}\".format(i+1))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unfortunately this method is slower than the sklearn version and is not guaranteed to find the local optimum in a reasonable amount of time. However when missing data is an issue and simply dropping rows or columns with missing data is not an option accounting for the missing data in some way is essential. The principal vectors which we obtain from this procedure are clearly much more informative than those that we obtained directly from the SVD based sklearn implementation. \n",
    "\n",
    "If you recall the principal vectors that we obtained in part 1 you will note that these principal vectors are slightly different from those we originally found. These differences are partly due to the fact that the apparent covariance structure of our data has been significantly altered by masking out some of the pixels with the natural result that the apparent correlations between pixels are different. Some of the differences are also due to the fact that we have stopped somewhere shy of the true global optimum least squares solution. Also you might notice that some of the principal components as we originally calculated them. This is not a problem since the linear subspace spanned by the vectors is the same regardless of their sign.\n",
    "\n",
    "## Imputation\n",
    "\n",
    "Now that we have a decent learned representation of the face data we can use it to repair the parts of the image that we have masked out. The imputed data in this case is simply $W~H$ plus the mean face image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "imputation_model = np.dot(solra.W, solra.H_t.transpose()) + solra.mean\n",
    "\n",
    "pca_imputed_faces = np.where(occlusion_mask, occluded_faces, imputation_model)\n",
    "mean_imputed_faces = np.where(occlusion_mask, occluded_faces, wlra.mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets look at an example image and see how the imputation looks. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'PCA Imputed')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904adf048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(10, 10))\n",
    "axes = axes.ravel()\n",
    "\n",
    "view_as_image(faces[0], ax=axes[0])\n",
    "axes[0].set_title(\"Original\")\n",
    "view_as_image(occluded_faces[0], ax=axes[1])\n",
    "axes[1].set_title(\"Masked\")\n",
    "view_as_image(mean_imputed_faces[0], ax=axes[2])\n",
    "axes[2].set_title(\"Mean Imputed\")\n",
    "view_as_image(pca_imputed_faces[0], ax=axes[3])\n",
    "axes[3].set_title(\"PCA Imputed\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While clearly imperfect the imputed image looks pretty decent. You might not even notice that the original image had been changed at all if you weren't paying close attention. The imputed parts of the image have lost some of their fine detail and look a little blurrier than the rest of the image.\n",
    "\n",
    "The imputed data looks OK but lets try and quantify just how much better the PCA imputation does than simply using the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6140862687869026"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(pca_imputation_residuals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8402113235250431"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(mean_imputation_residuals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Probability Density')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6904ab84a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "left_out_mask = np.logical_not(occlusion_mask)\n",
    "pca_imputation_residuals = (faces-pca_imputed_faces)[left_out_mask]\n",
    "mean_imputation_residuals = (faces-wlra.mean)[left_out_mask]\n",
    "\n",
    "hist_kwargs = {\n",
    "    \"bins\":71,\n",
    "    \"range\":(-6,6),\n",
    "    \"histtype\":\"step\",\n",
    "    \"normed\":True,\n",
    "    \"lw\":3,\n",
    "}\n",
    "\n",
    "plt.hist(\n",
    "    pca_imputation_residuals,\n",
    "    label=\"PCA Imputation RMS={:4.2f}\".format(np.std(pca_imputation_residuals)), \n",
    "    **hist_kwargs\n",
    ")\n",
    "plt.hist(\n",
    "    mean_imputation_residuals, \n",
    "    label=\"Mean Imputation RMS={:4.2f}\".format(np.std(mean_imputation_residuals)),\n",
    "    linestyle=\"--\",\n",
    "    **hist_kwargs\n",
    ")\n",
    "\n",
    "plt.legend(loc=\"best\", fontsize=14)\n",
    "plt.xlabel(\"Residual\")\n",
    "plt.ylabel(\"Probability Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8f9ac11ba8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xYqZS/vQffnGCZrxEpMqp6DNeUvFoxkuKU1YzXlrHS0REqr3zzz+/yCcKRcpK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\nXhERERE1+T8OUi6gdnatYAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f96b32be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "left_out_mask = np.logical_not(occlusion_mask)\n",
    "pca_imputation_residuals = (faces-imputed_faces)[left_out_mask]\n",
    "mean_imputation_residuals = (faces-wlra.mean)[left_out_mask]\n",
    "\n",
    "hist_kwargs = {\n",
    "    \"bins\":71,\n",
    "    \"range\":(-6,6),\n",
    "    \"histtype\":\"step\",\n",
    "    \"normed\":True,\n",
    "    \"lw\":3,\n",
    "}\n",
    "\n",
    "plt.hist(\n",
    "    pca_imputation_residuals,\n",
    "    label=\"PCA Imputation Residuals\", \n",
    "    **hist_kwargs\n",
    ")\n",
    "plt.hist(\n",
    "    mean_imputation_residuals, \n",
    "    label=\"Mean Imputation Residuals\",\n",
    "    linestyle=\"--\",\n",
    "    **hist_kwargs\n",
    ")\n",
    "\n",
    "plt.legend(loc=\"best\", fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.58565197966178517"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(pca_imputation_residuals)/np.std(mean_imputation_residuals)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The PCA imputation reduces the typical magnitude of residuals relative to mean imputation by almost a factor of two. We knew already that the pixels in these images are strongly correlated with each other and so it is no surprise that PCA should be able to do some amount of repair.  \n",
    "\n",
    "Although the PCA imputed values look good this might represent a slight overestimate of the quality of reconstruction we can expect from pictures of new people. \n",
    "Although we were careful to not use any pixels to both train our PCA expansions and estimate imputation errors we have not done anything to handle the fact that there are multiple images of the same person in our dataset. If we really want to get a good picture for what our imputation errors would look like we should make training and validation folds with all pictures of an individual confined to the same fold.\n",
    "\n",
    "\n",
    "Before you go out and use PCA to impute all your missing values in all your datasets consider a few pitfalls of this appraoch. Firstly PCA should only be used to impute values on datasets where there exist strong correlations between the input features. If the features are not strongly correlated then the imputed values will be poor predictions at best and you would effectively just be injecting cleverly disguised noise into your input data. Secondly using PCA to impute values comes at the steep cost of making it unclear which data originally had values and which did not which can be dangerous (for example over-inflating the confidence of predictions made on mostly missing data).\n",
    "\n",
    "Data imputation is a good tool to have in your toolbox since it is sometimes the easiest thing to do but it is seldom the \"right\" thing to do. For example suppose you are using a machine learning model that has been trained on a cleaned dataset with no missing values but when you deploy this model you find that you must frequently make predictions on data with several values missing. The easy thing to do is to simply fill in the missing values somehow. But since your model has no way of knowing the difference between imputed values and valuable information your predictions will be less good than they could be. A much better idea is to go back to that same clean input dataset and then randomly censor pieces of information in a way that mimics what will be seen at prediction time. In this way your model can learn to deal with missing values in a productive way and your predictions will be better as a result.\n",
    "\n",
    "\n",
    "## De-noising\n",
    "\n",
    "Now we turn to the closely related problem of noise reduction. Here we don't have any missing values but instead our features are degraded by some amount of additive noise. We can use our learned PCA representation to project our input data ont the PCA expansion and then reconstruct it from there. The idea is that noise fluctuations will not correlate with the principal vectors and so will be attenuated wheras common input data variations will be captured and so the signal to noise of the resulting reconstruction will be higher than originally. Note however that this technique cannot add information it can only reject it and necessarily we will always reject some legitimate variation along with the noise. While it is true that it is possible to increase the signal to noise of our observations by rejecting more noise than signal this is harder than it sounds. Just as in the case of data imputation it is usually better to teach our models to deal with realistic amounts of noise than it is to try to reduce the noise in our inputs.\n",
    "\n",
    "\n",
    "Lets apply pca as a noise reduction technique to one of our faces."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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c3L8vxN89OQbiKv/2SLX7K2XxZTiA7qB7nk0AvEI6mwrKpWFcnpY0pxXPrTBn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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e29d5518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+Djr95Zdw+T9uwuVP98bt9X8FNRuhedbvM9uj/nI0ajYaspF6ChrFrUxp1J3O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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e294fe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/7fVGzE7Mz7OSAY2DDTHz86hRXk941msahgtB4+I2GIRnz/GaRniYQKtnvOl0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e32e94e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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25yLJC/DjFguHO/uc31m5vmZm/538P/1fx28r307ikuvVRFG0weLfqi5Nvh68SIgzG8wz\ns22RHJyvdv7d4j89fMhisTlZYfEzkvmqlHxVrjaz35zuxaIoOhFF0aNRFH3UYjdphZ1axLlj4dxZ\np136bhJF0WMWf02fEnxGgScsfjHO7PTALCstrpc5nWx7bRfH7DWzYSEE9w4K8XqH/EVqncXP+Izk\nq1QpliRlOd16W2lmA1J6ujRdlb1bJDq+x8zs+uTraQfdbeMnLL63vKwE6yzWh00PIZR3sr2j/67s\nZFu3iaJoTfLV7M1J+a5PbW5P/l/yS1EJ9ppZRiMd4qVCOFFaZnG/vTzkW/1fSrlWJP/v7KvyPOzz\nO0ETtFcBybotF3ex+f0Wv1jWRqlFLEvwUYs7N9cTOx2+YWZbLV57Ju9PQUeiKLqts/8sHoDMYkHr\nn0JcPTKEMIETMYsncv0sqw/5iMV/asj9s6s4u0nEu5+w+DfzD1n2N/ufWPwb8ruTpVvM7MU/x38m\n2f/2UtcI8RpWnQn7a5P/H0nKssTiF/jbQwiZpTtCCL0D1r16iXzS4nL/bcdLLRHX32nx+nD/X2cH\nBZ+65x6LJ1DvCak1tpLJ1Ees8y8kT1is16Ko+jOGP9smJoz/snjS/Hm+fEO83lfHu+wbFjsd/yH1\nNTK9b/8QQlrK8R2LJxWfSp83hHC5dV9/Vor/l1znxcWwX0Ib326xnu1DnU0oQwi1yXmPWTzxHm6x\nxji9zzst1lL9Kup87ctcQry+X2fjt+vDCXssvu+RL+VaFveThkSP3HH9cosNH46k3/7YYg3eR7g9\nxEvcdLDX4n7ZnXLdbvG9fDz5RaLjvLUW6zuP2+94IWJp0F4dXGtmXwkhrLM45dN2i19CMy12kRw2\nOIy6IoqiDSFeePO2Ert1+ttLFEXHQwifsfhLxcfM7D2nfQenz7ct/g1nnnkx52ct/s3ur5KvHcss\n1txdbbGI83MmRKzL+kuLhfBuYhFF0YEQwnst7mNPhBDS66BNMrN7oyj6Ts7532HxROZhM9tk8cRm\nssX98FmLV5zv4A8tXjfpxyGERRZ/nTth8RIBr7XY1djZl5/TJoqip0MIP7JYh/pHFk9YzOJ1ByeY\n2b+EEP7YzB63ZLFVi8eNYRZ/DbcoivaHEP7M4knUshDC9y0eU260WEzeWRn/zcz+2Mz+O8R5Kncm\n9zTA4i87XAz3Yxabm95jsQHg5xb/mXSCxV/zh1u8xMXOEMIfWbwA8ZMhhPssli6cY/E6XfMsXoKi\nY7z7psVrUb3J4jb9hcV/InuLxeL3606vJksTRdHPQwhLLM6kcmnKtXnabZyYWW61uP8tCyHcbbF+\nbpjFY97PzOzPk/P+lcVSkE+HeB3J5RabI26wuK5Pa7zvgikWa+oet9id36G9vMHiv3z8a2rfX1n8\nHP1DCKHJ4j8p74uiiH/u7YqOZaHuDyF8z+IJ6pUWP3eduTLfZ/GfXP8uxIvdLrB4rbILzOxiS/6c\nHUXRCyGEJ8xsbgjhdov7yEkzuz2Koq3Judx7LIqiX4cQ/tNireqTIXbodjhmh5rZh6LurUuY726O\nTmN9F/33yv7P4j8Z/KXFC3FusriTH7L44foPMxvXyTHPWOxu6ux8I5Lj2y27nk6n66Cltvex+Cva\nEUutGdPN+/mVxYNYZh201LbMujsWf0H7vMWLDB5J/v85M+vX022k/87cfxa//NrN7CddbH9Tsr3d\nUuugpbbPNbP7Lf460GZxCrO/NLOyLq7z36mfXWKxS3RVcvxBM3vKYv1bTSfXGmSxc3q1mb1gsc7m\nKYsnQ687zfvt8nlJtjcl29eaWUj9vNLi5UOWJeU8YPHX6++a2Zs6Oc9NFk8E2pJn/LMW/9k2M04k\n+19m8S+MbRYLxb9hZjUd5e1k/wqLU7atTOpib3K9j3dS940Wa+ueTZ71HRYvFfRpS61hl+xblYwL\nzyXnXWbxZCOzFlZOPXc5Zibbr+2sLrrbxhb/Uv1DiydGh+3UxH4W9qsxsy/ZqfFuW1LHo7so+6ZS\n/ScVn2uxbnKxxXKTNovfK7ebWVMnx7/d4j/9tSX3v/l0rpva58bk+MNJG/1z0madHmvxJP/TSX8+\nbPGEdLGZfQD7jbXYVb3b4v7/4nptpdre4iVfnrD4HXjA4klgZ89Dl2vAnW7fCsnOQgghhBCiIEiD\nJoQQQghRMDRBE0IIIYQoGJqgCSGEEEIUDE3QhBBCCCEKRs8us/GzS7xDoS+WrtqMDBxjkad7LtaL\nW4t0Xn0qfDwOy+LsRIaJPVgGrLbWxxs3+rg3qu/kSR9f/AYfG5fmegHxccSDETNdH+bXR5Gpo+Jy\nH+++x8dDpuL49T4+hpy3rcgcUouFqquQdYb12StV3urqrrd1du1zJvjYmG0D196NvjBkoo+54PN+\n3NuRwz5esMDHk7BywBGU95LpPr7/Zz7m/ffHotirn/TxFGThWvyoj9kW1Tk5tA+gr9TUlD7+ENYC\nXrrUx5ejr21BSr9tcMS/p+W3SqBdFPb+n+DGsEEzMcZwjDqXqfq47uoJxMzkxDGEv2OfzNneFzFf\nAX0Qcx3Pii7+bZZd2B3jZ2Z8Y1l5r6wLlpXH45nNLOqel8Ob+3P96zxDHctDWJcsb17bMeYqEzwf\n75fvk87WsE3D9kpfDylR29FWZewbHI+42H8DYuZhR274nVgPlu+LE+0+Xow0sQOxxu005IJva/Nx\nc7OPL5t/RsYvfUETQgghhCgYmqAJIYQQQhQMTdCEEEIIIQpGz2rQqFOZCk3UvHmlj+ffhXm+a97i\n453Yfyg0bUPxd/OdT/m4Hjlbh89AgaAP2fkwzn8B9uf8GH/Hb4fmrQx/N4+gmeDfzSt2+ngIc86i\n+amp6wM9yjimLaOGAX/3HwhNRWtKwzCEGVSW4dTUS4xATH0ENAjUGGyFZopQ/3gCbVEz1Mdr1/l4\n2jQfPwUNWR3qvg36w23QFzZd6ONjuF9erxV6FN5/b+hfqCHjszQbaR7ZNwg1ZtR/HqC+5+xg0CT0\ny7HI801daia7C7Q8GR0SNWF4xjLPIHVbeXAMwhhSUlfFa/dHTM0sdJKZ46mhyrvXPP0dNVh5Gq28\n61OTlvd9g8fnaeq4PU+jRh0u7ofvh8C+xvaivvFYzvXTm7CtjHrCKsStiNnvqM2Ehm0o9I3HoVnb\nh7rheE7NMPevRvmPsS7ODPqCJoQQQghRMDRBE0IIIYQoGJqgCSGEEEIUDE3QhBBCCCEKhiZoQggh\nhBAFo2ddnHTGHYBLZsrFPq6As+8wXIqD6fyDs4Orwx9FJoGKBh9zdWI61Xbg+Avf5OP+dMnQ2ZLj\nbNuF+xsOF1SAY2zQXpxggw8PwzlYOcTHZcNwfL0Pj8P5Vz4K+8NpUw7nzsjU6vqHf+m3HULZ+sIF\n2A+uRduN+HU+PHk/rj3LxweRaWA96op9pQoOp+nIEpG38v4ulJdZKUahLuuw0jYdtQ/g/mrhJqSr\nky6lScysAFZgpe7+uL9JcCSzfuhybWQmiLOEUXA285lnhoyMc5Db6Xajc5BjCMlzcSK7R2Z/ukbp\nnDx6mtvMspkGeC1uz3sd5a18z5X+6bzLc3EypgszL3NBjrM8Ux62JWNmmqHTEe8POhkPwbVZhetX\nsLzMMgHaS7yvMu8C9mteC5lMMnXDfs++wrLi3uk6HzPGx7t2WUnoQmddniH0BU0IIYQQomBogiaE\nEEIIUTA0QRNCCCGEKBiaoAkhhBBCFIyeNQm0tPh4JlInVSCdw/3f9TFTQ7VBtDloko+ZqSiCaHXr\n49h/tI/PhbD6IFOZQOB7kiJT7g9R6DOrfXzebOwPYeRxCN0pbG993scUomfSzECUuh3pikbg/qNt\nPg5M5QJh+uGUEL+SBhEIUGnIGPOgj8vH41pIy8W6ePArPqaY+wTaqpqpRgBTI+2BQYMif4pMKZpn\n36XonmnMGhpKl2/JEh/PQeqmKvQ9Gl4yqaIwVLB+d6CvsX5b2PfPEpgypm+O0Doj9KaRiGMGheZ5\n6Xi4P8XZFLrnmQr4ikgL9SnKp2iedQHTkyH9WObeaZjIS42UV/cU3Xc31RShkD0vtRPbnuVlzPET\n1+OYQVMbt++BQaSmxsdVqG+eLw1F9GV8l1DUnyeyZ92wrZnWCv26HHXXG/c+FmkdmXqPqZzyTAZn\nCH1BE0IIIYQoGJqgCSGEEEIUDE3QhBBCCCEKhiZoQgghhBAFo2dNAnPm+HjRIh9PhdBvJlaDp7CZ\nq50fxGrmXNWbwnCKJrc+6+ORF/qYq8cbrlcJIfZRiDyPQDR7AqLSvWt83AaRK1e/n/YaH7M+5mP1\n/mve4uP77/FxU5OPn4MQn0LRoRAwr4PJwAk1UTfDIZofiLZdvNjHlyFrxMM/83GmbpCJoA8Ewlu2\n+pgCWRpaKMCthUFi/nwfT7nIx2xr9s277/bxzW/1MetjDdpm3jwfM7PAoWYf90Xb0QTwtrf7+EGY\nNpipgCaBxkY7K2E/YkyzRTvEyNTJ54r8KWSnUB8rqpda/d0s28+P4XoUT59IbaeRhn2onFkJcjIL\nHMe9Uagd8r4n0FTA69NQkbc9ZzX84xzPUf42CN9pKKEon5zA9fiMMfsK25LXI9tg3Ok/wMe9go9P\npvoazTBVGF/YF6ox3vPd2I6+UIZ+S0NfqX5pln03ncRzwrrju/8kzDR5bfUyoS9oQgghhBAFQxM0\nIYQQQoiCoQmaEEIIIUTB0ARNCCGEEKJg9KxJgCvtT7rAxxQWrobofDZWR3/oIR/XjfAxhYukL4SF\nFIJvx8r9FACvWe5jrq7O1fEppOb9LkFmAwp4KUolFI5TiP6tf/dxw3k+3gETQz1WX87cHzILUGi5\nOpUpoQZ1cS5Wet4Ikf+qlT5mW3GVbLbNPT/x8WBvMmhZscvF23Erl8zzbbN1rReZjmz0x2dWrsZK\n+s8/5Pvy8JkNfn8KfO/8oY9r0bdpOqBgmG3PzAQ04LB+V63C9ZHlgyYKGnA2b/bxZXZ2MAzmEGZo\nyIiV8UyUcTV7rrZPaBqAy+AwhOS70C8pliYH9uP43T5O9zOK+NnHKKzm+NYb9543nrEumW2jD0T/\nvcpKb6fQneVnWx2BAYNjDg0ifH/QNJAHTQF5bcP6OwATQyazDWB70JSWbm/2c44XNcgUw/F42DAf\ns6+wbfPqku9SvisPoS4y73rcK58T9p0zhL6gCSGEEEIUDE3QhBBCCCEKhiZoQgghhBAFQxM0IYQQ\nQoiCoQmaEEIIIUTB6FkXJ105dKnQZUMnSHOzj99wo4+3wwnYCtch0/PQ+bELjio6S+gapTOFzrex\n43wMZ9vxfd5JQhPRcRj1qod5J826r/7axTTalaG1yxFXtLbiAkjlwnQYY84vvZ31NTzl0t251m/b\nut7HdOXQgQtXpK1Hmi24iJ7d7CtzyAHvbtsLQ9YBZBp59CHfNjR87djht/de7F2nQ1A1Q5Cpau/y\nZhez6x875l2vAybDpcn6oWuSLqjpM3xMlxMdvHhWDz3wsIurB/rO1H7Ed9ay991mZyVwA2fcYGzI\nCrjfCFPeHDrkYzoFK/GcMIUNnYB0B9MNx/Kz36Q7PlMB8Vx0BRI+ZHQiD0TqoYGDfJz3fugNFydT\n83F844BLJzTJpBvKSd/G8/N9R+czUxnSNQ8XZ7TPn4+mU3YFFpeZtCIUN71///5+/KxAU1TXwqVf\nM8THfLfWYYWAwWhruir57mdb8t3O8Yxtk4nRtzl3GG1nBH1BE0IIIYQoGJqgCSGEEEIUDE3QhBBC\nCCEKhiZoQgghhBAFo2dNAhdP9fGv5vuY6XKYnqauzsfrkGqJKnmmwqCwkDAdxBqkespJZ7N3m1dp\nDjrphew//r4XmfL2VkPUObPexwMHekEv9crU2VMHOXyUT1+xv9WXt63NxzU1XhhaPnmyPyGF5g0N\nPraU6pSK1YULfUxBLFOBUDyNlDvHN291MfXDvDyz1jCmf2Iqui4z6uRpWNfCI3HxDVCdwmDRco8/\noNfqZ13crw4C6F0QOFOgPGokCojj2RkXwRRQ7yt0f7Ov0AFj4YqgaQGZql6xcEzJpPuBcL4CD6nh\neArT2W5MX3Qcx/O5oTia59/inxMef/yIv3551akH43ibV5mXMxtOXjogDkg0JJxgWitA0wBV7xwz\nCOuWqZAAr6BRAAAgAElEQVTyhOSZVFEQltOQwevtw3jJ/Zk+DW2zf4d/f9BTwK5HTwZNBByjMpmz\nUrfPY1kV0Ul/b/34XNCQx7ZjXbFwNIBwvGLf4QBNAwsHfL48ewh9QRNCCCGEKBiaoAkhhBBCFAxN\n0IQQQgghCoYmaEIIIYQQBaNnTQK7IdyjUJDCv21YPZ6rXlPESWEyeezx0sdv3OjC41v86sjlTeP9\n/lBpDrr19/12KCl//zYuL/9BFHAxYggXn7vXSsL7efBBHzc2unAAVsYeMGWK37/fxT4+DqX7RmRu\neOB+H6eU+cdX+8wBFOHXwxDx3GZfNq5yvWuXX0WbHgL6RTIL7UNQm13J38eL0TT0Q+QJdC+e7S/w\n6Pe96L+pye9fCb1zRv/MZ4EK31qo8ml4gQj36BbflyvGw8QA0W1GU8vMBnuQquFsgUYhukNGod4G\noWNwDKR7hdk5KPKn2Jr1TOMOH4w9fjX6na3+weLl0+LtjCmgHsYTPsQUvfNeaCJgH+JDyD7Oe6Mz\niMJzbudDy7agCSCTeSAnCwTbBnVPk8TRjd7AwTGSYwqLz+picdm2Q5EIpx90+enXCccfnpu3niks\nyWS4YEYO9A2OZ+wrNMsw8wxNBJmODniDZwh9QRNCCCGEKBiaoAkhhBBCFAxN0IQQQgghCoYmaEII\nIYQQBaNnTQJLINKn8I8C12mX+PiOH/i4FcJACgspVLzujT6ej0wGs2e5sLzWr1Zvq1b5eKbfPyN0\nXO+F8faWP/Lx7i9aSShUPPdCHz8OUf7qp0qW58nPPuBianoHUUh+8js+ZuoC3h8zDaRMFOV1XpQ5\nsr9XlT6+wC9VvWBB6UtTLzx3ro8psB01ysf0p3Bh6W3bfDxmjI/px5j1NuywC4JgXHDWDVDoQnXf\nj88Gnx2c79AuX3/VDRDRbvHP1urHfDwSfaGCLgBkOlh9hzeMXNjHG2qs7mxJHQC2eHOH9cGYwxXU\nj2IJdna0vHQgHFNI/wE+pnia558+w4VDKZ7m9c9tOPXvZ2AK4viEPpJx0tAExvGZxzPTAKFynSYE\nrkbP8tIZxLajkJ0q/DyTAZ1JqOujLd4wQr8JT09dO8dveiBIqEamB7Y1B9X0oId3M9b1t0F0CbCu\naK5hvz6EmPsTnp9ZLJAlYvsqX9cjGtHvmbGDffEMoS9oQgghhBAFQxM0IYQQQoiCoQmaEEIIIUTB\n0ARNCCGEEKJgaIImhBBCCFEwQhRFPXf1+2e4ix9duMRtrmhs8PvTCVczxMd15/p4PFIx9YYzgy6i\n3nDt0DbT/IyPm+CipKtz8CAfjx3r48WPuvB4s09HQRfPERjAmL5oaIN3ruxt8U4YmnRoWuX16ISc\ncOul/gf9+/k4zxqZdtYwDRRtkStWuPDnt/vUQ3QwHUbdnFvnYxqoeG/rYECd6LNgWVkf/C5TjXu/\n5a0+ZloX7k+HMt1/dNPRocz6WrrUx0h1sn+9rz+6TmkmrOzvf7BogW/LOTf7Z23DAt93Wbyy/nBV\nfegQ8ua8QvnuOD+A0ql46TwcABdlhHbNS810ANvZkOw3LE8lc3LRHcccYrQCXpD6N8qSORfGa9uB\nmLmi4Hp8Dg5ZOlJZNxwg6QqlrTFjBcf4z2eSrlC6OjPWb6QXQupApr46uNk7C5FNLWMyHTEGP+AL\ngY5epqoaBuc4xyy+MNL1x7rM5J2C45aOVu5/BPszhRm307HLtuR4i3s79NiTLi5H01U04V3Nvvfm\nVWdk/NIXNCGEEEKIgqEJmhBCCCFEwdAETQghhBCiYGiCJoQQQghRMHo01dP2u70pYEQjRI0UFs6B\nSJ3pHSjCp4hzFVIfURXf1ORjikbf+Sc+3on8QVSuj369j48jdRLSV5QP8yaEcddD9In0F9vveNhv\nRzqLQZNHujjastXFjRDCM1XIhKkQdlNpf8stPmZ7MQ1OWkTL1EU5ItIpU/zm4XN8Wx9a4QW4FH0S\nXq7pz6/C9SGAXr/Ox+//mI/bIbAd8VofP/drH1O8Tc4Z7ePq36B8ENlOnepjpoKCQLvfGPRViM0P\nbfb7Xzrb777yPi+AvmiqP/7xxT6Nzox5OalaXqlQPDx+Qs4BEM4z3dCOnT5uRcosiq9p1KGwncLv\nOpQ3YH9jShuUz9JjKO6lnel6IOLPYwCE50zXQzg+U1W/BuP9tGk+5iDAAZCGCwrXmQopD5oI8H6i\np2ooNPzn0L9BU1bNUB/nmSh4PzSc8P2ZPh/bhu8GivRpsKCon8/BLjwHLf7dlSlrXox3c/VYppVk\nXTGtF+rqDKEvaEIIIYQQBUMTNCGEEEKIgqEJmhBCCCFEwdAETQghhBCiYPSoSYCazhEUEs6Z4+MZ\n15Q+4b3f8jGFhyeRNYGZA7h91jtwAQgb237oY668bDhf+ad8PPkTPqbQkhUEYeaIy6HypwgUQskX\nkBhh5BXItID6fvTdX3fxrI/O8PvfdZcL2zd7U0BZHVSu6dWnsap2yxbfVgehgZ84mat0e/F0JRbV\nLqvyAt5Rvb2hpKzBGyio0D26wGd5qPjge/3+dgMuCDH3C75usmkh0NcpYF72oI9pKqBodflyK8WA\nq6b7HyzxBp3n4Xehnrn6am96GNziDSpsvxlzeILqkuV7xVIHsTEr7pkNPj4PJoIy7M8xkGMKheAU\nW1dB5H8O+rlBWG4YAw3iboMRy5kGYBJYCxMUDQqEzwDHay6dTxU9Y2aG4flgysqYuiqQfqQC994b\n4zGNOjwf4xZkFoAJYVBNTrYS3i9NDjCRZaCJLmOKwPn3oH2HDT/1bxo0aJapHe5jmlfyjue9sd/T\nNEDYNuwLfG5pEmDmlvHjSl/vZUJf0IQQQgghCoYmaEIIIYQQBUMTNCGEEEKIgqEJmhBCCCFEwehR\nkwA1ijYdInQKC63Mhwchql8PQe5VV5beTuH1bCyXbuf68IWf+XjwIB9nVhuGMJuCWwjlDy5a6WLq\nGtes8fGFk32cWR0ZAmIK6TMmCZgKZl2B1aJZfxAkl/3dx/123J/d9aMX//nwAn9zr70cXbEOdT8M\nIlH0jTKIQttXPOm3j8L5WLkQ8VfUQXxNQXNmhXVvKqCJISM67Y2+vHSpjyminT/fxxSPT5roY644\nv3Chjwf6Vdt77fCi3Iym/5DPrDASWvNNaOr9u7zguG2LF1ijp75yYb+gUJ3taHimDiLbBkE7ZYxM\nfTFGcgV1g1jaIL42COONgzL7fbpfoQ9nRP7MSgB4bxzvKdymaaoNrieurE+hOKni0vw0eaGueL0d\nfKYxhvH8R/BMDh6COGd1fWY24PnZ9jQFTES2EWZ+4BhB00e6fHXoN5ksPrhXjt/MRMB7pdmF5+O9\nZtqCBkCcn22J53j/lv0uHlCTY3h5mdAXNCGEEEKIgqEJmhBCCCFEwdAETQghhBCiYGiCJoQQQghR\nMDRBE0IIIYQoGD3q4qSJJ+P6o8vSkD5i+Y98TKcHXUCEzrdyOEe2f8/HO3b6eOz5Ph4yCxf4hQ/3\nehfk81/4rouHjx/g94fzZdYof306TY42e+dgBZwuZWNG+/MzrQxdSLfd5mO4qI5+7dv+en8AF9Ti\nR1z4rS+fSkXFTB6vvRoOrnnzXLj7Cz6NVx+fycn6Tfdpr5hBJ+PogiuRaWXaD/m0WWVIjWSjH/fx\nykU+xr0/evcOF8962xi/P+u+FS5QujKnl07dlOG663x8p09TNvRan2pq613eVTqyEc/Knr0u7LPF\nuxGPwbBcW1u6eK9Y6E5jPdFdxt+J2S9r4W/lIMl+SzdcxsVJ6OKEc9BWIUZ6ot3rTv2b6cs4njD1\nUBtiljWTtgr3xmeCqZDG4Jli3dJ5yO1DUD46bFes8DHvvwHvB76/WF4OYnShclUAWqtZf6wf1t/z\nzT5ev97Hq/wqAplBOn19upU5Pp1EWi26nelCZ1owujhZF3RlDsSKCjyedUVHMNJc8faq9/gVI857\nu50R9AVNCCGEEKJgaIImhBBCCFEwNEETQgghhCgYmqAJIYQQQhSMEEVR/l4vF8uu9xenMm/9Oh//\ntRel/+LSt7j4yk9d5vd/3X/6+NEP+pipSC6e6+Of3+njaoguKVykoHf5ch9DMLxovldSj4CQGrrF\njIa0clSNi59d6oWPo8dDhDppko/zRLUUfj6GdEYUNMOUsXW1NzGkdaHUu25v9fFRr9G31at9fNVV\nPq6cB9E8BbBsK4jy1y3xZaW+t2LmFBfvne8FwxTFU5P6eI6G/8ImHzMTycTLUdeTL/RxC8TcaMuj\nG7e6uGIw+vLNN7vw8H98w8WVY0pff9nfP+jPj7Riv/Cb7c/2R8HOCj6NARRmj3UQXk+4yMf7YSIY\nMA7nR4oyQ782iLENY1peKik+F5uRPg9jVrTklHmEwzU1/v0mjfQ/YNormriYuqgex1NIXs90cDCR\n0XhDkwBNYazLR73RxxYscOGG1f6h5/0PafTjs01FqiUK3add4uM9u33M8ZgGlFU+vV0m/RLro8WP\nCWzQ3zzm7y89fvPdxKYbNszHFfWoC74AaEjgAJxJg4XHjuejYYX9nCYB1OXj93hTF7veNY+fmfFL\nX9CEEEIIIQqGJmhCCCGEEAVDEzQhhBBCiIKhCZoQQgghRMHo0UwCtuYpFz6/2AtUh18BIfRev1r7\nKix6feWcObgARJ+zbvXxDz/p4wfu9/HV1/iYmQogRN+6xK/kTB3iY4/5eDeEh0Ogg/zDP/TxnfAs\nDBrsL3A+NP+H9niRZzVXlq6BcBMrZT/xfd8el0CHb3NhqoAwc+TYZr89LfSEgaJsh68M6mdnz/Zx\nZTV+t+AK7hSVQvwcrfVtRwPGmjU+vrhmk4upt6Vgmm2PhfltBgwhEe6Xfo4NC33fGocCZEwAo7xK\nt2IuGg+ZGqzSt2XlP97i4n8d8gYXv//7vrO95nov2P7z27xpoQetSC8v6/wYlnGHcLV5ZKzIZAYY\ncD0ugEwFBiMPMwMsgxvjRI44mtlbsNr9zuW+X6UP3+F11BmheL9MZgF/r9EeX/YwyWcDsfp6H/dF\nthGOZ5nrwYRAIfkQrOzP9wWF6+AojEHc/dgqX9cjRqHuSQXux2AS4Psnc0Hc/9qnfUwTBQctkBmD\nNna+n1l2vGSShJre/t7L+uDlx8wC27b5+ATNMIB9gyYx3isNbujMrNp+KN6ZQl/QhBBCCCEKhiZo\nQgghhBAFQxM0IYQQQoiCoQmaEEIIIUTB6FmTwKQLXLjvPpgEqrDSM4TlXL3dyhvwAyi/DUrslhYf\nU+XKTACtXqi9cqlfTpl6W662fASr4//Nh33M1Yp5f9dd5+MlWJ2eqzdXNzX4H1B5T2EmClCJ6rD+\nA3zMlaynz/Ax2tdVEFYJH1HnRebf+bBfFXsk9MKXXTcNZcO9UOWJrAkBYu5KVPa4k1hRHaaDfr3L\nXHzRJC84PrjGi6vHj/enY9IJasnPb/Ji8oM7fOc5vN6fn9rz/eu96HVAL19euw+GmDe/y8fmTRFb\n0DczDp1hXsy+F7vDE3H2cMcPfDwN/ZKifD6kbS/ghDC3GJ45Q8eJMOhQGM9BiM8JV5vH8UPH+H5d\nU3NK6D9xMl4fdNpQlI5nLjA9CIXdU1/j40th2trd7OPMAAqDBK83E6YBGjw4nuF+mqqRaQDpP47u\nw4C/Y6ePOQgYTAsUsrN8fSCMx/0fXuX7RiWP5/URV+B9eG7bKRNZOUwANLgNr0ffQNaevVu8YaSq\nzY/XFWORRQLji+2CgYLAVPD0av/uG3/Mm5jYdXbiseWr80yhL2hCCCGEEAVDEzQhhBBCiIKhCZoQ\nQgghRMHQBE0IIYQQomBogiaEEEIIUTB61sX503tdyOwOE+DEO7rKu3yamnC+vXDpDJrp43Wf8fHU\nqT5+7FEfwwny7EbviIIx0C66AqmTYA3Z2eqtIGVV3goztH6Ii7cv965Rps9gKg4atGwPvHSjRvsY\nTrwff93XN12jmVQpU6b4mDZVWmP2pJw3M+GQWuPTkjBtFV2KGYvrood9TDdbJs2Jd0Ee3ePddOV4\nMto3P+tiOnYnoKuxvCMv92657Qv9CS68Dm2D1CVVh3zfpyHrKaRaIceO+b409A/hsDX0/ad/7sLZ\nk/3m5zd6F9Zw2JyugmuVj9rZwuFD/r77Puat1aEvHtqZs3xM57gxHRD6rcH1GdAR4C7OPJNMgUbW\nrvMxBpWQdmoyjRQdo3lwAIML0g4grdVOOKuZqo6pjpiP7cB+H1dwUMGgMwRpuHg+jm+wYlecgMud\nab3Gj8P10ZYBzsU9SN1EhzBcmJXj4YRk3+AgxRcInN+DpjacCtCPqtlWh9BP0VeOHUNdgAq2JV9+\n0+DwRZpCrrjAtIrbW318Dh7Do3hsMu+fM4S+oAkhhBBCFAxN0IQQQgghCoYmaEIIIYQQBUMTNCGE\nEEKIgtGjJoEI6RO+vdDHjY1eGD1iqk99UV3thYAZoXgT0v1Un+PjbT7dA5WAj97nj6cmvvLqy/wP\nKJKFcHroWog8YUKwXT4VCDWzFDpeAI1tGAuRK0W00y/x8Ze/4sJxEHYzW9JQ5itiqqx65GNiGpt0\n/VBgu96Lk2fN86LQb33VmwKmLPei0HDTjf58VNFT1c+0JugbTy/wqZJ4axPm+pQ9Bzf6/TOi0lYv\nGB4xHQLeujqUd4MLy6ZeZKVoGtjsf9Ar+BipVjIC43v/3cdI60XPRcaQ0uRNB1OmeLH8hHlIW3OW\nUFnj+82hHb7Pn2O+3wbm9GLFTngcV4A42iCefgFia44pJxlj0GU6oauu9DHF3+nnthUDBJ93CrsH\nexOU9UdqI7quCAekvPRueOasBte3csTcjgGYMG3Xli2l92ddth328cFnfNxvkI95v0z1VIX3G8lL\nA8YxmddrOO/Uv2k+oYGC/Q73nkkFxbKwrtau9THHM9zb3h3+fDQB9IPfjZfn60OpnoQQQgghhJlp\ngiaEEEIIUTg0QRNCCCGEKBiaoAkhhBBCFIweNQlQt30phNg7vO7aRkA4SA287drtY4pWj0EUeqT0\nasWz3o3V1imyXP2kj9OrbJtlRaNU/YPjbV6peH4jmoergGOl58xq+RRasjxz57pw5z0/c3HTtVjd\nnithX/ZhH++8x8dLl/o4nSpiGgwLjHdA4Gv+XLyV0ffg2jfc4OOTkY/7oC/AJDDxai9CZSYB9p1+\nTagrugpgqDi+0Z+vnKpULr1/DKu2w+TAlbOtcWLp7cwqsWCBleLtt8H1QFUtBNr0k9j06SXP/0rl\n+D4/xmxHNhRqqS8cA2MSRf3bm308guYKtCPVy+x3bCcK29nvclanz+zvroV7YZYEmgIyWRRyqMX4\nRmE6TQIksx3lMTxj/H7BumbdUlSPlfujzc0uDvuQ6YWDWgOuz7bojTGM1+f+mdX+MZ5zjGTmhXRn\npgmAhoXxE3zMdzHfhXkqfN4L90e/ZNca6xO5WD9U1VZUPY8v1e1fTvQFTQghhBCiYGiCJoQQQghR\nMDRBE0IIIYQoGJqgCSGEEEIUjB41CTwPE8A9WJh+zhwcABHkhXMhkpw82cf1WK2dq6vf8lYfb4MA\nl6JSrrTcCCHkxk0+njfPxyv86ve2w2cOKJ/Z5LdTNMpVv6uxHDJXKZ82zccUmt/nTQH0QNgkCM33\nQTS64XYfU4DM+r/88lP/Xr7cb6PoE/fyztu8geM7X/crtI9ugGCXHMGq3RTE5giWy+pR91SNUoTP\nvoa2KucC8cf8/diiR3zMvt2y1ccUDNOwwvrdvNnHTeh7e2C4gXj8+dU+PrbZZ/2orfWHl9HgcpZQ\n3t+bJ+rrvSuARqfM6vrHIJ7OiKVhlolgbCLMlkIjEceMYzgfhfgcA9NibWYGoGif5+a9cTziM8qV\n8VkWjo8HIHqnEL2OhgsIzw11ZXB4ZMaQHGE7xpgwGNdrgWGEQns+M2y7Chh3hvrsHzYYfYvlp0nu\nBNrjEI6vwur97liMv8ySwLagaaC6X+ntNAmwrmCQq0BmlQruD4NE//6+LWfOxOU4Xp8h9AVNCCGE\nEKJgaIImhBBCCFEwNEETQgghhCgYmqAJIYQQQhQMTdCEEEIIIQpGj7o4yzA9bMD2RYt8POE6unqQ\nKmPjBh+PGeNjpNrIbKcT79J5Pn5kgY+XPOHj2bN8/NBDPqYrp+lCH9OlVHeuj5l6g05Bujb7wrky\n0V9v2Ud/XPLwjMuH6YfoxKRri/e7enVqXziGaJNhYVpbXTi0xjtin17jd59IhxddRuPH+ZgOXbo0\nmVeMjqjrr/cx85jRkTYJacToUmLb0RU157U+pkN4KfpmJgUQ6p9tB1fnhr+/08U0lLH5WP31X/6G\niyv+4et2NtB+yDv9Kmu9k+5kK55ZtiP7GfvhYMR5Tki6ebk/3XRIR2R94dQbXCLdEfclTC2U54I8\nhO08nvvDBZ9x/pFajF8GF6Th/bEbTme6LvPGDD7DJ71Tsb3ZO7F3PLDSxSPoOmX6pN1Iy5VJBYjy\nMBVXnguV5ecYloYpwtjPmFYqL3cSr8UBpz8cq2z7ujof89453sGxy+F4K1aYoB/45UJf0IQQQggh\nCoYmaEIIIYQQBUMTNCGEEEKIgqEJmhBCCCFEwehRk0B7jkZxeyt+QOE100MwNQWFi8OG+njNUz5u\ngRLQIMq0BT6kaL4VaVmue6OP777bxxT0UkTLdDxTpviYwvctz/qYotFve6E2dZdHkNkkIyynsJIm\ni3qYGmgiSN1v+ypf92XTUZdsS6SRaWz0m6knztQd02StRtszTQ3zjDGNFgW8vN4upEo6gr6VSdsF\nUSzF330haP7pvT5mKpPpM3xM1f6kST5mmrO160penqmc1vtMTzZhLtJ+UVB9llDWF/0GD1WvXjQJ\noF/zGd0D4xPrLc8kkJfqiWMM4RjG5yI95tBEROF3xgSAXHIcv3g+lpUGi0x6NVwf6X8y6c8Mg0Y7\n6prlZXlotKHh4gjuH+NpGdK1ZVLtrfCmARs4yMeZvoPyc7zubnsxTu+flwbqCN5tdBGxX/JaNCiw\nrKxrwuv1Ln1vnCoMx/hW3kMzJX1BE0IIIYQoGJqgCSGEEEIUDE3QhBBCCCEKhiZoQgghhBAFo0dN\nAnPe1uDiTRubXfwlH9qHIGKvaIQonUJpCrdHjSxdoLlzffzUD3xMoSLPTyE2RazTXlP6+hBm25xL\nfXwAqzHvgRCdwnAIfH/43vkuvu66krtny8/MBxS6l0EoypWvU5keym6+0W+jyp/HLljgwtG3+KwN\n+x941O9P8TQNIlzZetRoH9MUwEwCXLmfotUmZAqgCjWdVcHMrA9EtRTt0xWRWfEdguFtWPW8qsrH\na5B6YSayYKx+0oVcWZtJL1at8vGE2RCAM9PC2cLkyT6G+LiqCu1AJTj7FU0EFMZT/ExTAIXgJJNZ\nANfjiut0h6THQIrQeW52Ej6TFJZzAOJq8pksC+jzNDhMmujjgDHAumlcyaxen5MVguVj22F7ba0v\nT3uLHwPKNm/yx7Nt6PqikJ9jLNsvk5UCY1ralEeDB2FfoCGuf38f52VhIKx7lp0mBOx/aM8xf7gP\nM1XJqj5T6AuaEEIIIUTB0ARNCCGEEKJgaIImhBBCCFEwNEETQgghhCgYPWoSoGCWQmTIb+2zn/Xx\nH9+61sX102kagDDxDW/y8VNLfTwix0RAISKF32PP9zEzHVCkmTl+rI/XPu3jHTt8PPkiHy9+xMcQ\nXs6b5zczcwB1m3YpMiE8C2E8qYIwdCiWYx46/tS/f/CfftsVV/qYWQgIBLMD5vq6+MXn/Srcs7Z5\ng0T1TBgeKKqnwJkGEwqWuZ0iWaxqvm6F73sTBsIUMAwr8dcM8fGY83xMgTXLT0MLO0OOwabfQN+X\nohP+/ph0IiOGf+iXPkb1v2KhcBwPUf/+eGYorqY6mQ9hZjX34GOKr09AGJ5Znh5wdfw8oX9aOM7x\nMO/cNLaw7BzfaFhgdg6O71R2X8BOBtOBRT7shbriC4mieRqNCNuSbYHMBv0olOf7gsYlmhCYKYFj\nAtuWhpIDyHrB9irV3iwr74VtQ4MCx59M5gC0NWHdsm/g3naiq7F4bPs+ffAcnCH0BU0IIYQQomBo\ngiaEEEIIUTA0QRNCCCGEKBiaoAkhhBBCFAxN0IQQQgghCkaPuji/9XnvYnznl6a6+M7rvZPvMEwo\n//I1H3/uvf74jItm51Yf06VzcK+Pmc6HqY2m4notLT6mM7ChwcdMTULn4pgxpfenSwpOmk2P+fo9\n/wbvajq+3KfzKbv2Kn8+g8NsNH21cMo884SPz5uG/VMONNYFXYZXoixPP+XjJUt8DMfrlR/wqZF2\nLvSO3+ML/b0Puu0mf76MOw4OJqb4aWvzMV2ecOxOeBdSKw2EG5DHs2/QgTWbqZqQSorlpYOYjq0c\nV1Wo98/CyFHo67zeGjiSzxboymz0KcoqxsLdS/faHow5dXCi015GV2XG7ZYzpPN4WrnZj+n8S6dn\nYp9hXWSscYDjI12C2H58l3filQ+EK3Mmxye4yI3lYbogjHd0NWZSIaGuef+sH6au4hjD/fehbzD9\nG8dMPrN8v/F9yLamI5ljULo96ZrMS81E9zGfg8FwqRNej3XNfnwyKhnT8Mqm5woMvXvLxSmEEEII\nIUwTNCGEEEKIwqEJmhBCCCFEwdAETQghhBCiYPSoSWD6dPyg3gtq3zDWC6N/udHvDkmltd99r4vL\nPvkp7IH56GEI/yjCZCoNChMXLcL+EDpSlEmR6fhxPqZgmMLKqiofj/XHty/2wnl6DGyHNxmU33Kj\n306R6f5t2J4jaq1CvNML852JgXW5IyfV0apVPubNUVy9xpsKqJddiixfvf/qThdf8oU/8DvQMEKa\nkFaGAl6m/WrF/TJVCg0oVLFORVqwNgiemcpp7TofU9R7we9hf4j6//R9Ltz09o+5+Gk0df3bcL+Z\nPGJnCaxHmi+mTPExhfFMZ8R6Ytynj4/ZL3phjOnbt/T5aAKgeLs37i8tFGefZiokCrW3POtjitR5\nL6wP+2YAACAASURBVBB+Z0wBMGRkUuUZ7t1wb4a6pxGI4zVNWRzD+P6gkYf50Gp9+rdMX2JbcPyn\naYymDJ6vF9pn8CAfs714fHqMyaTBwlSCfSFjQsK7hMez7lnX7Ds0WZ1E26K8ZShfJa+PvlW5FgbD\nM4S+oAkhhBBCFAxN0IQQQgghCoYmaEIIIYQQBUMTNCGEEEKIgtGjJoGJ777UxU989CcufttHG1z8\ne8ubXXz33f58ZQ1YtXsrhNrMBNDsz5dZ3Z4iTYo+6+p8zFW9KaJd8CsfX/8mH3OlaQrHJ0104fNf\n+K6LqavfscPHw+f54zOiWtbH+vU+hvDerrjCSrIF9Z8WqlMkPwyC2bt/7GOKQnlzvPmZM11YfugF\nF88aCAPKPX77ox/4notHYuXp+mnoSzQFUERLMTaXsqYA+afe8JLpmwsW+LgRbUsoMKZAed2D2I77\nM79KO2/vultR/xTDs/3OFjLiZ4j461CPHCO4WjufQRqJBqDiXzjo40MQR2dE/xBv09iTidFv0uXP\ny7YBU1JG+E1TErMc1Az1MUX2fCbYFoa6pUkgwjPH1erb/JiQMXRgTMmM12zbQ2irUaN9zL7Bh4zn\np4h/x04fc8xhpgCa4Ng3aHrrlTKx0dDButmHe+2DumY/4/E0BRCK+gfS8IB7Z19jW/D9gbZg18zJ\nkfE7Q1/QhBBCCCEKhiZoQgghhBAFQxM0IYQQQoiCoQmaEEIIIUTB6FGTAIXV1KxHm5tdPOhdXlR/\nS19vKji+2a/2W04hIUWrFKZThEnRZVOTj4dAWLjMr+RvF73Gx4895mO6HCDI3bTIC+mpy2xs9PFz\nWPi//mqsbj97to9bW32ct3I296eoNU+Ymc6MQEEvReUQAEd7vEozUKXJtqSAd9q0kmV9fe/VLr73\nO/tdvGaNP3zMet82Q4f5uGmuF+CunO8Fwxdhgfn9EKEOqMUq6LW1VhIKqLnKOA0eEDC3L3rUxWWT\nxvv9Wz7uwiEz8bBS1Euxe57o95UK75MMg9Cdq99TSL5rt4+pTqbZgkJ6Gpm4OjzhM0pTAYXz6eeG\n1yIUYnN85faaGh8jU0pmO7MicLzajmwYrEuurL8np+5pimBdIT602RuZIowZ/UY1++M5Jo6C6Q2Z\ndphpIWPSWL/Bx1y9n2Mmjyfp8tFgQPLqigaMgTAJsKzMlEKDRMYQkZO5pBqGPI5Pq/14WQHvz5lC\nX9CEEEIIIQqGJmhCCCGEEAVDEzQhhBBCiIKhCZoQQgghRMHQBE0IIYQQomD0qItz/1rvahlUD2cF\nU10gvU/lnKl+O11Fi70zLeMCImPP9/Fl83z8DNL5MB0Py7voYR/DUfX4g94pWFvrYxqo6Pyjk6aS\njjCmYqKLdNcuH+P4n37VOyvLMJ2/4sBXXVx+xWUuPvzAr12cNrz1hUnxvMk+LdbKu3xds6ibN/uy\nXnWVv9boSehLdJxeeaOP68914RurfNttXeL7Kk1DNLhuWuLLR9PT03CFTpyOtGBIu7L68w9YKS6Y\ntMLFAfeTcT0hJVFZPVIS0dV01VU+/trXfMwKAc9u9ttHd7HfKw660fJckEznxvgknON0r9FpXQ07\nM1PocDvLyzGTMZ2WaWcjXY6Ij7f5PlTeHw89XYR16LNMR0YXI9OrbdniY46H3D/HBZp1jue8n9BW\nfMZp+B1R588/st7Htc1+zKmYBlf+mDE+ZlouukLXwtWKVQ3aW/0gy0e6vCaVKoo3w2tzBQWOPxwQ\n6drkeE24ndeji5TPAdMwtvgVIHjzQ+t6ZqqkL2hCCCGEEAVDEzQhhBBCiIKhCZoQQgghRMHQBE0I\nIYQQomD0qEmAmSoGzJ7lf7BwoY9nzvDx8uU+ZpoUqhyZyoLpgBY/4mPmVqr1Quq9a7yIk6mWmqZ6\nIfbjC/35LkDmqE0bfUwNqE2FKQL5h4bMQe6n1U/6mPcDQfNvfupNAV9Y6neHXDkjjP/jWn+9ykYv\nBV/7wLMv/ptpqpgCZ9h6f/ElyKL1ZdT109/08cQ637bv+QhSHVEwO8YbRHav9m07chJEpRC11m7z\nguQK6KEpcG5v9qLU7eu9GHsb7m8C6qu6HgLl/gN8fP31Pqaol6JZCr757Kxd52OmCMqIdH08empp\nE8FZA8XJhPVKoXnNEB9vfqb0+WhK4PWZXokxhfRMl0SzSGqMPbrL91kOL/1G4d44oFH0TwPDCaT/\nYVmZHm7VShceavF9eis8BP36++vxETiIqho2zO/f0OBjFq+lBcWDaYCehuMY3kn9Cj++llF4j/R4\nmbRiGVODL39Zbz8mlrX6MdD1BT7vJ9FWJ/Hth+MF4buY8Hocv3hv3L8tx7QA05TV+Xf98S2+LnKe\n8t8Z+oImhBBCCFEwNEETQgghhCgYmqAJIYQQQhQMTdCEEEIIIQpGj5oEhk/HeuI7sIp2zVAfL13m\n4+mX+JhCwY2bfEzRJFfpPg8mhJW/8DGWs6+GcLDpKqyEDcHtjHdjO0T/F93zE7/9ujf6mKLY2lof\nT5rkY5oomEkBqt7v3+M3Y91sYyKDK7G4fEbUC4FxWoSLpBDWsNCbAqhlnjnTx4vu8jFa2lohsq/8\nom+7efP89nNbfYGGjPcrXT+5wCuAL3z3dBdXzMFK/FQMjx3rwjI4ZEZs3OBjrgJOBfMwPBs0CdAE\nwZW7J0CRvG+vj9lAbBAaVlav9jFTPzB1xNkCjUlsd4qnOaaRkef5mKvt05nDFdwpdu4Pc8u+HHE1\n+xkzCaTGEMq+K7g6e16Wg0xWBdxLjqg9L5NBBD8GdePbMUZkPGXwR9D409bmYyaN4PEYve0I9ufi\n+Dw/EyGMOOLHzOomPHM0ZbB9RuH9ywpiX0rXL9uWx3J8yrQ1+gKzOtDswsrh8RwvmZmA1+f4xPGu\n1WdZoKFRJgEhhBBCiFcpmqAJIYQQQhQMTdCEEEIIIQqGJmhCCCGEEAWjR00C2aWX/erqGZEjBbPH\nkBmAqxVTZMrr1UG0bxCdNmGpf4hQy8eP89tpOqBAl9fnasbveKeP12P1dggX7Sqo9DMmC5gCsHT1\n6vleGImFwO026MCvvtrH5Q2oP6hsoxYvi52SchlQo8m4rs7HXKX8vbh1CnKZeWAvqv6XD/mY/orq\nan8Au0JGdD9/vo9vfouP10C0D9NARiSLrBU2d66PuUw5oYCaItlnIOpnpgGKZikwHuszL2QaAKaA\nqM2rbIOdJVBET2U3xc1cqZ/KcoqvKyCcH416P47zlUPJXo0HZzj6FR8Mjkm9ynycFo6zzXkvNJb0\nxrnYp1iXzJJAMN4fhZC7X63v820wGfD1MLQBzwjbjm2zxxtEjhzxdU1fDCT5mdPzkWX5GFePwhjE\n9yGzf4wf72O6IijMp9B/8KDUxfuV3pfv4jyTEOuWMQ0LLDvfreybrGzG6KvHm/27i6c7U+gLmhBC\nCCFEwdAETQghhBCiYGiCJoQQQghRMDRBE0IIIYQoGJqgCSGEEEIUjJ51cdbBUURnRZ5LaNgwHyNd\njh2AK4j5fehco5OOqZVORj4eTWsfnCcH4aIZAVfqvXf4mKmS6ut9fOONPqaTbwzSxDQ/42M4XSph\nrLkVp7/w1mn+B40Tcf5mH8N1yuZKX55ZqOiSpKvzvEm+sLNumYNr+7afMuVZF/N6NP00NvqYZrzw\n7lv9D1as8HE9HK284MBBPoaj1hoafMy+RwsXU5nQ1XTZtT7etMrHTM1ClxUdePUjfUzLGR1iS30a\nmqfWeIsdn5xXKnt3+XofxHahK5L1Sjcct7PdA85fju1M0FaGMY2/kw/CmJPx1/J3+FS79/Kp7jJ9\ncjD6PMdPwj5FVyLrEvD1Qaf1cLru6WzmM0jg2rQtftWBoSe8U7ux0fcNPnJ0pnO45yPZj03JZz7T\nt/A+4vuNrlkO2Kz/9PuYN0OYhpDX5rudjt0KJhrE9cqwP8tDtzTvhXV3xJ+vfKC/fvkxpBk7Q+gL\nmhBCCCFEwdAETQghhBCiYGiCJoQQQghRMDRBE0IIIYQoGD1qEji6ar2LK6pRHApkKSKlyYDCw+nT\nfbx2rY97QRBL4TZFlEyFYRAicr7bD6mWIuz/RqjyH1mA66E+WiHKHX0Jrg8h47W/52MIN89v2Oi3\nUySbJwSdilxQ07ypoN+X/sXFFX1PCTOZ6YiZhagp3d/qReYDNqLsSAvWD2172Qcv9/s/+AsfQ1Dc\nj6lLmMZr/AQfr4IIvwGGDSp+T0C0WjPEx3Qx0LXAvsm0XtthmGF9vQF5u9i3eL71NODs93HfSh/j\n/obidGcLmUeEwvOM8YmifB6P1E6BF2CMMdAqc2KIo43lgbC81P5lOPYc9IlMGiqk69kOI0wmFR77\nFFJFQQhePuUCv50mMtYt3y9sTJoeWqHq5zOCQW1cfz+oNTT49xdfV5Wj/PmOtnin1HGmG6LBhOnn\nOIhmxjS8L+haYGqudMx3J/s9jw0oSzn7Rl6/hYFhN1xkNBnQIMi2paEix0BR3b9nvmXpC5oQQggh\nRMHQBE0IIYQQomBogiaEEEIIUTA0QRNCCCGEKBg9ahKg5v/kHq+CHHHVDL/Djud9DNF+dN8DLg79\nB5QuAFfGp6C3DNVDYaJh9fidfvX0jGiTq8ufhMh2G4TaFOH34UraENWyPCd2+njSJB8PG24lOY/r\nvUPovhfCc4pMr77GhVMO/OzFfz+z2e964RUQ9FKEz5X763CvFPxSILwZWRUacX6KSPdB8ExR6XT0\nTboe2NYUoc6e5eNFi3w8eXLp87Ev0MRAwwvv9wff8/EVV/p48SM+5qrkEAG3LPQNOgRdf9s2H+f0\nvFcMXHy9H1coZ0whPI05FXjGDGLrjIifYmpuJxT9c3l6Hg8zi6WzA1C1jricq8FjfB0IkTpNAXwm\n9+z1MY04hMacvEwBbEzGLB8zG1AYj/3LR432MU0IGMMq6v37poJjGE1yY873Md8/Q3My9/D+OOal\n9+e5WZbKUT7OfAuCYSSvLx3Hu4WZAg6hL2XSSgA+lzQZEI7vZwh9QRNCCCGEKBiaoAkhhBBCFAxN\n0IQQQgghCoYmaEIIIYQQBaNHTQLDx3sR//a1EGY/cL+Pr7rKxxD6hZtv8ttrIVwcgpWfKTxcsMDH\nl2P1+SEQzR/1mRAyolaaGigq5UrQ9fU+pvD9HJR/N1biHoLrV+L+n37Ux70gasVq/Laz2cd9IOwc\nxNXrt/p4lzcpVE9rfPHfFzZC1EnR/FIYLm5+i483bvIxV7anYYEid4pc77nHxxTcjh+P80NUSsfL\nJBhQuGz4woU+njfPxy1oW67UTdMBy3PDDT5m32ZWDJowmpt9TAExrhdRew4unkPB+NkBEzxkTADs\nZxwD2E+NRqC8FdaZzYTia6yoblhNPnM+Hk/S/YbHMtMKgSmqEmWjkWUHTE7s4xTlH8H2ehiJKij0\nxjNUge8VQzB+Vz3lY7YlTQw0MrEvMBsIy8/9mbmAQvj+eJ9wf2adGAETHd83u2CK4/ifJpNlh99+\naEZh34FBjllxaApgXR3xmWYy4y2Pp0mAJgMYOjLj7RlCX9CEEEIIIQqGJmhCCCGEEAVDEzQhhBBC\niIKhCZoQQgghRMHQBE0IIYQQomD0qIuzfY933jEzRyYV0cBBPh410sd33OHjOa/1MZ0cdGa83qcm\nyriS9q7x8SC4jirg5NuKVEhM5VSF/adN8zGdKBue9DFTl6xb6WM6D2vg4KJLaDPyLzF9xwm4sJ6H\n03AEXKB0Gd2XcuXyXunYuuUPfEyH7GOP+5gOr0kX+Hgj2oL3Pu0SH9Plw7ppRtqV696I7c0+bmnx\ncRMcwQfg6KIDi46qE0jBw/OvfdrHbIs8V2uOa5MOter1vnyVA+H4YnnPEphRzLbhmeAYlUnXRlhP\nTPWE9EMZNxzT0fF6dNPy/FVdFy1D3rmZvgepg/j6oVO5L/Znn+V4xGfmHDipjemHmN4np22GMrUe\nyt8Prs1MWi04Dfn+YWolpoLKuEBzUmXx/VHO1/0QH1bi/TqSzsp034RjNHOv7JeE++fUPV3ydEtz\nfKLLsw11xfGdDlj2tbzUUS8T+oImhBBCCFEwNEETQgghhCgYmqAJIYQQQhQMTdCEEEIIIQpGj5oE\nykZ5UeUgCokp/Fu1ysdU6N7w+z5essTHPP81EHZvb/bxCJgM+iD1x951PqawkKLPxkYfU7hYCRHr\n4S0+pgiW9cFUHTz/UIj+H1+E8kFUewiCZIpaByA11TMoD69/05tP/XsNDBeX3ejjCGJn1uVbbsG1\nYQKgSJ6Gil27fZwnOqWA+Rj6EuuK1NaW3n8Nysu0N0yz0gbDCw01NClQYEzDDE0QVZWlY5yfXWPl\nEp/C6KKr0ffOEvqNwTNJcXIVRPdM78Z+9gJSlp1DET+E8UbhOtL3ZFJBYQzLiLMpnMczbOncVnmv\nDzyz7XhG+UxTiM1njmSE3rx3pibCM28YrzMGDQjTM8J4utpoEmBb7fBhGc7PbEJIlZd5yNi3OKYx\nFVY5Rf9se9YHhf7p9mGKMhaeqZ9YF6xbxC8gZl9hzHcNoTnnJMrDnG00pbEuzxD6giaEEEIIUTA0\nQRNCCCGEKBiaoAkhhBBCFAxN0IQQQgghCkaPmgRsjxc17tziV1oeOhnCYq7KPWiqjyMInSmqvxj7\nb1jrY4pOj833cT1E8RSK434yonuuZj/xUh/vzFn9felSHzNTQN5qye0QAPN+uFr9+WOtJLubfXwe\n9t/Z6uO0qYEi96PbfMx7HzDbxyv/x8cU0M6b5+NFj/iYovt6CHwpumfd0uTAtqmGwJni8V7Bx3Nh\nSFn8qI/Hj/MxVw2n6YCGlQd/7mNmPljzlI9hAoiO+VXJw1ifNaLXPi9uv2g2TRUUn58lIKOCHUJG\niIyZBNspXqaJICOuZszV+SPEFLIj44TBWJQRb5NS7Yhj22FgaIVInSvhczV39nFmQqngvdUhhjGH\nK/mXvBez7OsRbZcRxtOQwe8fGI8jPLNc+T8vMwDHFG7fjGwnw3A9np8ms4C+eTD1fuCx5bxXGgyY\nVYL9DG3DzDK8V77bmFWCon6mKTqC63G8ZBYHnv8MoS9oQgghhBAFQxM0IYQQQoiCoQmaEEIIIUTB\n0ARNCCGEEKJg9KxJoLcX4g0dC1Eihc8Ulv/yaz4e44XLGeGfNeD6MBVswcr9l13p4whCRQqfDxws\nHdNEsHIBygNh4zaIamfP8vHq1TgewsaTEAyXwRQwDELLcmQ62L/cxzuwEjYzM7C9hkHUOzVl0qDI\nlCtDD2jw8f2f8zHvleJrno+ZBJhpgIaSfRCx7sAK7E1Npcu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GFwXBjNGiKaA/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\nM0sORschQUcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e2d01fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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wLh1BO/T02KTgbvW9EH+ny0MhNudzmgY4CHg+xyjhHEDhNudX1h1NC9zJvyL4\nmMYbzlEU2TPbB99HfD/QGETyTAFsG74veD7nY8L6YV9Im/BocGDbcFxwPmvjuMH12FdYFr7r+Hm+\nW1kXLG/G0JFnxjkz6Bs0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgY\nU+vipBOMTgw6L+jKrECqjoNwNS47x8djcOXQRcRURnTx0BVE1yVdN3Tt7IMrEo6u6IR34dAZWDXP\nO+F2bfROFpp0Fi/zzpdd2/0FOw/68oZGpIqi84YuV8Z0AjI+nipvXtortgVdOXRcwTE71Ovrhl1t\nFE25H6ZSFn3HDh/TADaMtmrOyRzCrtfe7gs0p4IuU7iK6ILaAtflvBYfs/7ogKMjmI5ntg/o7/V9\nvY7Xo6trusCUXEwZRqcexwxT2HBc0L3G6zXlpBA7DCc5nX7sV5yz6ERMOzcrcj6blwaLdUWHa2Y+\nafYxnXh5qfLynIK8P+uGgzgvVSHLl0nFhLrl9ejSpGsU78Ohg74+8zYByMt+x+Kkr9fY6CdUGljn\ntGP+5jjpxXzAHQXmoa3Jjsd9TMdwe7uPuSMB1w6ZtQEcwUyNd3b54j1b6Bs0IYQQQoiCoQWaEEII\nIUTB0AJNCCGEEKJgaIEmhBBCCFEwptYksHq1jynKp+iT59NEQJEnhYEU2FK0z7QsFOhSad7tRfX9\nW3a7eDRHE3rnnT7+yXYfQ8Zt82Z6AfAll1jZ+FCvL8CiRf54mOmV7k9t99efO9fHVQ1QgrK+bnwJ\njuMJ0vXHtCJbt/m4BwJZKlgphobqngJZQlMA/Sf0f1RipAxBD0zBLQW57MqMt2zx8VVX+wsOHvXx\nSI9PhUXTQW0b6o9QAbx0qY8p+KZgG+1zAPVXxwrNS+P2fIWi/pOYY9hP51D8fAzXyxGmk+P4PMdN\nLzo651iIn0d7/Rw3WCZlGcdADaaH3FRMmVR/qEuSSS2FPjkW+ZiGDN4/z8Qwo7J8nCkfnoeTUN4c\nRiMP2xLvM87vzOrFIZfJbpeTjo6PU+7aNAmMjPj5ozmT5jDHrML5Ka8tu7pYAB+zLtmWHBetMFnl\npcl6jtA3aEIIIYQQBUMLNCGEEEKIgqEFmhBCCCFEwdACTQghhBCiYEytSaC11cc7vfA5IxSkypHC\nPQoBuds6Rf80EWyHSp/lw/0Gt3pTQN2yBf78ZctcOAe7Kf/3z13qY7vKf94gnDTsJG0o/16Uf+cu\nH1O4DeHVciX7AAAgAElEQVT3/BshxKQpo3IN7g+h59AGH6+738dpISdMAvvveNjF9GNQsEpNaEOD\nF4Vu3eqP5wliF8JAwa5FUSw1rm1tPmZXq0HmgRZsrM3MA4M59+PQOIKhUTvgBcgUe3cs9QUaXv+Q\ni6tWLfcfoIgWsHyDO/xO4rVr2HemCRR2cw6j+WIYQvh9+3zMjs8d1WlKyGRb2V/+OMTYUZ+/H4vD\nKTBK9buMbpq7wfPZuRs7heF1uCBNSCdxPnfqZyekkJw0YxAeg2if5WP2ElYAhemcdNgWdBKhbaM9\nvr7gScuMec4ZQzkeBc5ZLWjr2aj+9JxDQ0iUMx+N9vlnrWxgZhOaa3ABtmUb3rU0APLdTtdXngmB\nlZXXl54j9A2aEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgYU2sSoKCWInaK3Lc8Uv56\n/PzWR31MQS+FgSvPL/95UDsXSsnGOT6miJVb+Q9ht/YTt/uYQkaKZqmc507a/X6X8eENXojP6q+G\nkH3Jyh/4H1BZT6FmL0wa3H0+LZrt9iLyjH8Du2JTT7thI4qGqrnwQhQVglhW5Tb4K2rRtO3tPobf\nI9OVmCkgLPeGkUxfnNvkY6iza9kX7r7bhRU9XpCc3dnbx/0HvYKYmRWs21fIktVoW1RgLeqT7VW7\n9j7/g4ttekDhOwcRM2bQbcIdzWkK4BjiQCHsiNzNHwMBsndbyGwsvN7CU+aRql3l58fMIIBpKuP0\n4c76dfU+pkGCQu46PCvHDK/H7yd4nHXNTAe8PsuH+TfzvAR9iacfR9eh0YhNVduIvkg4CTbg/UVT\nROeSU/9/+JA/hndPfY4BImPo4Pl8GE5grPu8tsazPL7Bt83Zy9BWfLdyfj5D6Bs0IYQQQoiCoQWa\nEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgYU+vi3LHDx3TldMHFSecH088w1UhrS/nz\n6bJhuokrkXqJzpIdj/mYqaaYtmXdOh9v3uzCwV5fHmYKaWqDK4f1ARfOYI93RY3C6LIBmZnodFyy\nGg40Pv+qVT6eiXQ+dH2m2xc3X7LcO1qXbPd1u3uzr5tK9NyzkVWGJpwFcGE+BZfoZSg6H5V1V9cJ\nC9XN/83HdLDRxcS+QbceXUsZh5UfK3Pgghq80/e1+R3lh/rsWf5+TyDlz5Nb4bAzHzMtDB/P+uFY\nni4wJU1np4+Z7ihgTprp3cwZd9w+pKw5eMDHM5CChh1/1QU+noN+ZujYhoY0zIl2xan/XXKplQdl\nbUIaqsVX43y4Jg/AZs75mX2KY4yuS75f6LJnXc6Fo3YWJmSOUV6PbcfyIHfT6EnfFlWY7hdgTmpe\njrbk+y8vfRGt6L2wcrO+09dbusQf60Nbc1zw2nkuT+7gwON8tzAnGdsOL7e5c/39j6A4c1qZUg1u\n6zOEvkETQgghhCgYWqAJIYQQQhQMLdCEEEIIIQqGFmhCCCGEEAVjak0Ce/b4mOkaWuf7+IYbfExh\nNUX4THPCNCY0CUC0aW/4JR8bhIkdEGVu3ebjS1+Kz8OkcLUXQtaiPmp5PQovwdD23f7zSEV1BOmA\nbrrJf57C8F0bvRB8ya9f4U8Yw/PQtMD6TCvHKVhFPHzQt80+lO1lt3iBa3+XT/P1OPwnTGVE/WzL\nlRBzM2UP04j95id9bHh2gyB6N9qyY6GP58BUwN+ddkMwTYPGRp/7qnYRBMCsbwiWN6339X3RNeXT\n7Dy8wQukWV3MIhNB0M0UQ89bOMcwx1iA8NxgAmC7sJ9RaM45gGYUCtUzwm80TBVyghnTA2HOtHtT\n/4/5k6nr8tJa8dlno89SpM73Az9/EHXL1IBrLsP1UNcck5zPeH8aMlgekhmDvr54u2a83mrr8Hma\nAij65/stzzQxwPajCWPo1P/z2VnXnGD5rmjDu53AdHBss38XzTjsXUi1LA9TrME00LQcdcW6oQEk\n5937XKFv0IQQQgghCoYWaEIIIYQQBUMLNCGEEEKIgqEFmhBCCCFEwZhSk8CDa70Qb/Vqf7yyAULl\ns6/1cQQR+ooV5W+4fr2PKVrlLuDG60HoOBvCwkWLcP7LEXf4sP4TPl77jfLlYwxlds3Vl/jjvV6o\nPmcEgmMIK5veerOLb//lb7l4CbeHp8kDKtf+TV7Ynt78eRiCWGo8N23y8VXXUbzsqZvnxc4XNfgb\nHDvsBb71a5b7C8yEIHknRPkUf9svIEZWCft3H+7DjvHde8vfnwLdRYt9TIHvyvNxP7gqKBaHmLy9\n3QuKmdWido2//oxNXhRM/TQ1ttS+Yz/95y/MFFCHOWv34z5efC4ugN3pT0KUTxMAxdU8TtNCM4Tk\nnIMMYmqDuNsg9E9nHogwSDloOV/MhCGBqVIITQLMBENVfVdX+evRtMDd55nloQbz+8khH1M4TtE+\n24bz5Ql/vYwJgHMC7885pIfzOwwqi2CCoJCfu/P3weiUNuXlGTbaFviYbcl+yuNH/fxT34F+y7ok\nNEgQvqv7kcWC11/OcXtm0DdoQgghhBAFQws0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgTKlJgDq9\nypdha3sKtQ0iyYDib91a/oYUXlPgewVMCHaYF/Dhk10+pki1hUJFKKV3b/YxhOTRiBdiUlNbuwyi\n1LydovMyNUAo+bLXQ8jJXc15/V/5AxfWPfGQiw98+ItP/z/1xJdd7uNLb8JOzxQcM4sEBbWoy/pO\nnE/VOgTET+70lb3gatQF+6JBVLoLpgGK9BubfIyd+m0s8jH7FjsDt/KnSJd9AwLmWmRiOIyuXwsR\n73nX+vZ5cpP/PDW3bL5pYxKgG4LtxJ37jWJomEdoBGI/5xhmv2e2lGPod/U0BdA0QFMB+k3a1MD5\nl7vF0xTAZ6NInyJ1ivBptOFxGijYCWkqYPmMYxzPQ5MBTFiZ3espfOf7h8/LFyLbkuXnmOf9l5/j\n41UX+JimgrvucuHwJv8+rWpL9UVmXWBmExggMgYKPjvfJTQw0CBBV1nvUzgOg0QFcpew78Ccs3+P\nn19b5mECO0PoGzQhhBBCiIKhBZoQQgghRMHQAk0IIYQQomBogSaEEEIIUTC0QBNCCCGEKBhT6uJs\nacft6Tzb7NPJmF3hw797nY/psrkWrkymb6CL0+CasQM+fPAeHzM31YLz8PkfIEbqj7X3+RhOljE4\ntuis23eXdzUxswhjUjmv2f+AzpcbbvAxnTQZl60n+vwXXfyxv5r4XDYV0251b/QuwY5GuDDpdoPL\nZ7jHu3CqYIDaD7MbTUUZh9TQx3xMW+qGDT6Gw210/UYXV65E6ik6bFmgw4d8TJdoH/ouUjvRfchU\nWY/vgIuVDt7rr3fhwNqvu7itzZ/ejaxs0wY6B8+HU44di78T56X0ynM2VmPMMh1SpiPj80w1ZRsR\nw6n41LZT/78HqYYIHa5Hj/iYE9o8OLf57BnXJJ6dzkLWLV2jrMsWOFaP7fbxpod9TMcuneHLMaaZ\nBqzdh5lUg0z7xTHM+bqnB+fnpK/bgvfr9u0upAm2KT2ncr4hdBvT4UsX+0HMV3Rx0oXOvsXr1dGR\nCzhOcD02bU+P7+sX/Er5yz9b6Bs0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwptQk\nYGsu83E/UiNR+I3US3f/fZeLr/mNi/zp57/Px0d/z8cUYe6CiJKmAqYq6YNotd+Xx+64w8cQxf7n\nbV7ESk0shdbMTEIRZyZ1VjtEsRReMv0GU39s3ebCoT7fPtQfj7zr7f7jyLx1bSqdEw0MO3agqL3r\n/b2pZabAlwJbxFUU+UPQe3SHf3bqlW27r4vBr/+bizcjaxf9Kuv942Su//M3eIFuRyf64jwkR6Lg\nmapWtvVcGEK2Purjd73bhRf9qR87Qzu9IaVmle/LZ6/0rou9O3xamq96D4F96Gs2PTh/DX7AVE7o\n2C0QrnOOm02jEY430TgFsbMhtdT+Lh9nxNZIn9SNmHPcxlMmgv3dvo35KBnjC0XrhyEM55jm/MTU\nSTSVMf0PC0RT1Gy+X1Ce7UjXtu5+F27e6IXljY2+7jpWoa2ufoGPOYEuP9fHrHvWD9MbbYaJgSaJ\nzByI50X9bd/u27f18CljAD0A1dV+/mxC1da1413KFGh81mXLfJxnmmqAAYMw9RQNbwe96YrvVvor\nYAV6ztA3aEIIIYQQBUMLNCGEEEKIgqEFmhBCCCFEwdACTQghhBCiYEytSYBCP4rqudP//ltduA0i\n9Gt+4Q24AbZqvupVPr7nWz7ugeiS96dScK0Xje7d4kX0D2Fz+XshFMc+0NYOUwATFVAjys2UaTI4\nuwM3yBNabvHC8bu/70WmV1zuQqta6YWcVRDmX/xW3C+tpIfhov8uv/P+PXf7j7Zz120KhGn44HFU\nVoRdwQdhQjiBuGGrF/HTBMDzD/rEBbYDotPDiMe+7+NXv9qX91iXF+E2NvqYmQAyjKB+Mlk0zvHh\n+/7ShV8567dd/KuvRu9FZ/3d96xzMeTK04fHIMzmbu+cMzjmTnohtp2LOcrmIOYO7pgUfvIfPh6L\nfMyO2Y1sAHDvPHWvL3+6n3MzeWr0m2hI4Ac4oa2C9JqDnnXFTAIncD+enzFk0AmEMUIRPqBx6Rge\nZ9cGb6RZsgjpNKi0r4HQfQSZAfoxiijy5wsBJi+b63fbH97hMyVUNfg55MIL/cfT2UBYdJq8zl/l\n49mzfBaJsYM+rqzD/MUsFWxLdrZqvOxg8IhwvTDX9/PBHl8emgQyprEzhL5BE0IIIYQoGFqgCSGE\nEEIUDC3QhBBCCCEKhhZoQgghhBAFY2pNAhBh/uibXsD6olsgmsRu6RRqm1H4XI0YOzXPmu1jilax\n/Xv/dr9T9JP7/OncTZ5Cw2aI+FdBSLkcG28zM8CjMEVQlMrN4zO7J1NYCVHprs1ehDobmz2zepq5\n8/VK7oIO0g0GlWndXF95Y2NeFEoDhO3DjudUtFIMDQFxaPM78Z874gXMSDSQ0ag2t/u+tXzEn8DE\nBoSiU+68zfuz6Z6A3rhtxCuW51TnOEq4U3dm7Pyciw4e9CaBTGeHYBt+GLvJpilfR0qEa3y9ZXZI\nZwYIdixmDjCYDgxz4uDjPuaYJ63ISMGUHsh2Mr8T4u2US2DxcsyvHRBq06hDgwR2vh9a95CLa5bD\nuPLil/t4rzfusOwZJftm7OzP7Bos3+VX+Bgmq0urYWrDHNN/FPenSaIO7x+2LduKz8MJH3Pek+u8\nMH7BUt83qhpx/zb/fLXL/PF5J061VxWanokBWjC/Bez0f7jLG+pq4LKqW4px0rHQx8x6Q5ApIJUA\nw8zMOjt9X2HX6YE/QyYBIYQQQghhZlqgCSGEEEIUDi3QhBBCCCEKhhZoQgghhBAFQws0IYQQQoiC\nMbUuTlgntsKl+KI9PhXF6E4f09lmu7/n48VwARlSX8D1wuvT2cH4nNVwuczzLsiZExugSkJDF007\ni+HqZBYZ3i+TCoXOx5d5V9SJE//uYmZGaV4E1w9dRLPhCBuEkzBdQFpc4ZCqb/AOJBh4bcly/G6x\nw6f2yKS1YloUtD1NjvV4NLYFmY80XXQIt7f7vlE5CzYoFOBQn78hq5r1kcko1OVTl1y0BmliFsEV\nZY8i9mnM6NK6/TN+rFx3nT/+f2AKpVlwujA84Nutau19/oRquDCvucbHI6O4IlyfTMFlcGny+tXo\nVwNo9waMC05qW9EPaJ9OW8s5aPIcpJywV1/swhpalzlHPIlO3n6Wj+nCpEt/oMvHNZwwz/ZhM+Yv\nQtc6BuXskZznyTipffo7q8UYPYo5jk51TNgLLkTqqxl4H8BZmWlrTHpNK1OuXNga61gWPitS+/Fd\nl0lbmJfW6+oX+HidTy0X9ZR35XM+m41H57s6s4vAGULfoAkhhBBCFAwt0IQQQgghCoYWaEIIIYQQ\nBUMLNCGEEEKIgjG1JgEIC6HrswMQ9lH/yqwptmGDjxfDNPAIjkMQW1nN9aoXSZ69EgWA8rmJolEI\ncGt7vQA4OuyF3BSi79jhYz4/U0VVzkRzUiS7FMptKCc3bfKHr77ax7YCqZ3aoIwfhih1jxf6W3cq\nPxHTnODaCzv8Z//tdn/6NddAnN0PMXQbBcO1Poa4uhYi/Cf3+Osz1ceRXi9ipYg/zPTXH+z15atr\nwwcgqm260jtCBjf6tDZnr/YC32P7fOoUanQzKn3m7TqAsYE0Z2vW+MPUe9fN9Z3z4kt8/bCvTheq\n5s1x8ehBP6YrKS7eniP0XkJTAIF4mu1IUwCF+znmHHvZy3xME0HabEPT0QDGP9NcUdRPpfbq1T7m\nhHjU9/FMqibWJebbrFMF9zekVjI8D00ITGW1Z4+VI0L5A9IR2TFM+PVNPp6LmMp1TkIQ5mfansp8\ntnUdTARpUwPSWmVE/BXBhVGfbxu+uzMmLJZ1Kwx+MzGfozw0BbCq2BV4f3bNqULfoAkhhBBCFAwt\n0IQQQgghCoYWaEIIIYQQBUMLNCGEEEKIgjGlJoHdO70yrwvHuVv6pTf6nZJvvBGiUAoVhyGY7ez0\n8XKI3nufcmEzNPUZUeXJYR9TuDgTIlAoD3u3e0ExhYuMKawMy1DADuw8TSHnPIhg1/nd4klGKMkC\n8PrI/JCpj7QxgOLlw4dcuHilNxGM3urb8nvf9x9/2e/CdMC2YlkuuaTs+Qs6ITCGCWEOBb4Q2Pbv\n8X2zbjkE0hRzU6yN8tRef5WVo77dZ0qoZ/22t/uYKn86RAYGXNjR4Q9Tj0yV7XwaeDK7pk8Phvv8\nGE77YMzMTmBL8vNaISTnGNqL3fIXol8M4/Psh2wozlFtuB7HBdXVnDPT/YbzLe/FCYQxjDSZMUto\nSqJon4YJXo8mAmMmARgwYBLLzv+oewyKACPS8E5vfKpieWkyQOaYzAuBYzjvBcL79cN0MRbhfN+3\nM8+bhmlsVp7vwgDRfyXuXcm2ZEyV/wj6GuYfFmfFCh/nZWbJJJmYIvQNmhBCCCFEwdACTQghhBCi\nYGiBJoQQQghRMLRAE0IIIYQoGFNqEtiyxcfYxzi7GzoIXF5y52NegAJYCsUp0uT2whRlEopmKcKE\nyHI2dI8183z553dAREuhJJ+XMJNAgz//8e/43ekXQZTavBJKb5oMWD+ZnbpBuv4puGVZV3mR6apV\n61y83Rc9u4s5BcjcJZvi7IyhAXWd1/Yjo/7j7VCh5hlMWB6K+hvYt2EyoOq10xtqMruw83nYd9G2\nrI7Mzt8Q9Q5Rb81d3acJVQ1eTbxokTcFcMrJ1DPbnUJt6yl/PuE4qmNGDRwnFOJTWJ/uCBzvFdi5\nnqJyjBEaUTLGIWYbYWVyTFMEz7JzgjM6XQJivD/4PuEY5qDAmK+aizHMTCusv7kYwzAdZNqyFu3B\nz7PvsL45R/F5OQmkYVtzfmJb0yTF+Yttyb7GukBWh3q6dTC/M6sDL3/VlT7Om/6fK/QNmhBCCCFE\nwdACTQghhBCiYGiBJoQQQghRMLRAE0IIIYQoGFqgCSGEEEIUjCl1cTJzELMrbN3q4xfCCVLLD9AZ\nQpdPXqqiZWf7uN47Q2w3bKd07ZyEdY33g0OrjmlUdiLNC50tdOXQ6TKG8/l881e58K67/OGbb/Zx\nJv0QrSx0PrI+kDrLuY664WCiIxWuzJ9/mW/sJ7/o3XI/vc1f7+L/DccWy06HF208SNGTcYlmUuag\nM9INt+9J3G+Oj/McXL29Pm7A51n3mbQ24CR+N6NrFI45Xr65Fa7No77vz86kCYMDeJow2u/7SWWH\nnzPGetHu7Ecz4Opku3EOoFuOTjz2czYcneUcw7MQZ+6fame6LJme5yBcjiM5Zef8mZnf8Cx9cAbn\nXY/zmaHubbMP98IqznxAeWOsutrHqMuhnU+4uHvTIy4+uwPp4ZiakM9Plz3J1E+Z1E1mWccxnfFp\n+K5F6r5Mv2dfyUubyPcD+yUdp+2oOxAybmjvYOXrgK/mxWWv/uyhb9CEEEIIIQqGFmhCCCGEEAVD\nCzQhhBBCiIKhBZoQQgghRMGYUpPAuSvwg9t9+F1kOfk1CAMrKbBlqgoKEZkqJC/dD4WLFE1S+Ehh\neV5aFQobly3zccaEgPLw+SjiRLok+/YXXEhdeCZTE4XwTPWRZ8rICKJTQngKdile5r3RVldducPF\nGzb40y+moPfyy33ctcvHFKGyL1SjrZhqJE+kz7prgAGFqZhYdyTTNyD4zRhUyqehybRdngAanaVr\niz8/k1WHgu9pQuVMTKEQznOI2gjGMAddnkmAcxbnBJ6fJ8Zm+qV9+3w8A+aVNOwznI8J0/1k0p9R\nxI6ycr7pgQmJ0JhC0b2hro/j/cA+y7pnW9KgQVE+7j9jjzcJZIbIOp/ezuY2I4aRiH2H5c0T6pNM\nPrcULCzfdZwfM2YW9CvWJeffCqThyis7r5+Tq4lLA3q8lOpJCCGEEEKYmRZoQgghhBCFQws0IYQQ\nQoiCoQWaEEIIIUTBmFKTQN31Xrhd+TEvisQ+zlklH0WSFDVS1E9VPM/f8ZiPD+I4z+duydxumLsZ\nz8L26hS9UsRJ4SR3ij4BISSFmNid/v7PP+TiG27wp1c2QOi5dKmP80Sw8+b5mPWRFn5SYMzPsi5Q\n9ywaq3Zwhxfg1jaiN1GQnLcDOwXNFORyB3aWvxqfp6GD98/b8Z1QNMsKoSEls6s6QN8dG+vyx/H8\n3d34OIZarunh+cqay8oenjXLm1myYxTtlpkTEPP8vEwDebA87OczKNaumPhcmqTyTFm5xhyMEc4Z\nNFj0IGvDSpikZrPPY/7mmM+r65w5KlM+zMeVc302kEWLjrj4SJd/3jl8P114IcqH7CKco/i+ysu8\nUO75+W5iX2BdULSfqRsa3pilxmfhyZpl8saVP/9Iny8vuy6bWiYBIYQQQghhZlqgCSGEEEIUDi3Q\nhBBCCCEKhhZoQgghhBAFY0pNArbDC2ivgG7wIWhCP/4RLzx8xSu8CPWc13f4D1AoSJFpC3ZbzxPw\n7oMIleSZFEieEjEj8kT5+XmaJr75DRdSWE+Ramb3fl6fItu8ncCveo2PLZUa4tFH/CHWPbeih6g0\noGwLsCP6Y9962H++29/vnDdfhfsz6wHaIm9H97yds6mi5y7pFDjTNMHrs+5ZPkJTAPsmdwLfvNmF\nQ9APD0FUO4i4vh0CcGZSmC40Ygw1NrmwvvH+8p9nO1I8TXH0DMxJbEf2S+74zt3+80wF/Hx6TswT\nledlaqFwvLfXxxSic4zwfhwjK871sdFogywKeaYAiPytHwaOMVyPbZnJLODfV83YLT86iPl+O0wC\nHNOs35kzrSxUxtNEQKNRuq/kZU5hP0OGjcz8R9NUpm1xPd6fbcG+AMNKD7IUsalCg5+/qqth2jpD\n6Bs0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgYU+rifM9veefHh267\nxMV/+4oNLt6IbDUj3/Lxu95Y7X+Q5wwchgups9PHdA21ItUSXZ15Tru8dBfVKD+vR6cLXZubvVPx\n0Tu9K4pGukNdPrVI0+rV/gQ6+0hzJ35Apx6cfJZ6vqP3+UN0JPHZ9uzxMR2tKOs5a7y77uG7/bPu\n+kd//yWvX2NlyaSCgruObXMQLqWMYxd9YcV5PqbriWll+Hm2FeO8XEx0jaK8HReiPQYGXNg8F44w\nOoLZftMFjvFzV/qY1mmez3589Qt8TPda3wEf0w1H9xxjuu3o4kS7ZtxyaWcfXYO8Vt78wT5JVyGs\ndod6/Hydcd6t8e8Pm70AN4Tj1lB3rEs6WPNc/nRxsn44AWec1P78wL7B+toCJzzfH/OafQyHcWZO\n4fHep3ycnhNYN5lUdDmueLjubQbuDUdr1jGLfknHMMH9+KofxrBkW1VUyMUphBBCCCFMCzQhhBBC\niMKhBZoQQgghRMHQAk0IIYQQomBMqUnghVfiBxAefuIaf/iDd/t4BjSlGaHiAISFFMgylQhFoBQi\nUrRJUWw7RKn8PIWRcyGMpACYQnkKw9evd+Fj393p4vMuRPNS1LpqlY+pnNz6qI8pcl0IYTtFt0NI\nt0Rhabl7de/1MQW8nUtwHIYPtM0Fl/v4gbt856n4pq/LxW+70V/vKESirIu8lDpzIdhl34RA2A57\nU0NWsAxRbBv6HstHwXAr0pxlUkfB4PH297nwyDt+28UrVvjTrQcCY7bPdIHi5wNIV0TjDY1FnIMy\nxiGK/nG/POE6heOcUzJzIuYokhb+08hCUxPnv52P+5jCb/ZBmAaa5uHZli/3MY02mdRO7IO4X+b+\nNFCwvGi7PZiz+HnOrx0LfVyHMcf6o9GI+Yq6dvmYqZ7Yd2h64xzLOSltKmC/4nzH4zRR8V2dMdih\nH+a9q9mvx3xqJ9ZdDd6lNawbTGh1G3LSPD5H6Bs0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEm\nhBBCCFEwptQk8JLf8UK8//jEVhe/9PfPd/GqVX7n5L/4LC646SEfX/5WH1O4zN3OKczeAVFrehdt\ns+zu65ldvbnbO4SR3I2emQ4oSv3+D1y4bb0XrvPjR/q86HXONRf4EyhgZvlZX4Y4I0iG0JM7Ue/Y\ncer/KQLlTvPcSZo7nM+DwHWV7yvWDwHzDS924WUzf+LiH9/qDSD33vJ9F193nb/cgssh8KUIn7Au\nKJKlILhvv49Z19ylnaL+jrN8TJNBnoGGu4yb/zyL27QCpoOMQQZ9a7pAcTTbieYNjjEaj3Z6o09G\nWE6zCdu1H+lWaCZheSkk5xxVLhsADQx8NvZ5ivBpMuiFwaIdfZgmLNYthemGPh1RaI664RzDMcI+\nTZMD655tQ1PZ0rN9TCE9DSPsK5xDejFnEGYK4JzF+/N9dzBlYssz1HE+yVybmU9wr7z5gu8aGijY\n11hXbHu+y/H5PngOmKPiuULfoAkhhBBCFAwt0IQQQgghCoYWaEIIIYQQBUMLNCGEEEKIghGiKMo/\n6/i8LHMAACAASURBVLnibxb5m/f43XqHB7xQr+oVN7l4/1e+6+KWNqw33/Y2H3N3dYpam2AaeHSj\njzs6fMyd/ykqpcgzI4RHeTd6k8Putb4+KFRcutTH1KguvH6Z/8HVL/AxhZtpEb+Z2dr7fTwGYf/y\nc31MEe/atT5O1zfFyBCd9vdg535QtxwCYvSdjKp/0WKUBbuK3+3TVPz1H+52MTWn1G5Tn3wWukoz\nNrpesBJ9gzthZ7JIQJBNgTUF09wZe/t2HzNzA8cCTQa8PnZ5z+wSnzE9oPO+L4IL5HnK187zcxjH\nBHdrz9vJn0Jvzll5u8Hzevv2WVnYTuwHGbNHaiBkDAgoG0X0FM0z5vyx7Bwfsy5ocOCYzoj6MUGy\nvBThs8/SFEGhPOb3p3aUn8PmL8UY5pjmJEOhO5+XwvotGOMsf1ubj1lfJC3M57uN0BCRKSveJRT5\nc0LlfJPJkkBDHuqS72aaDFjeDRtc+NhaP67O+YczM3/pGzQhhBBCiIKhBZoQQgghRMHQAk0IIYQQ\nomBogSaEEEIIUTC0QBNCCCGEKBhTmuop4xqBw6mqHa4VpEFpWQFHFJ0h997nY+ZCoouHTkCm4jh8\nyMf7nvAxXTNguMufvxEmURqwyPLl5c8/+0I4V5jKia5NukpR/n/5ine+PNnjT7/lFu86rbsWTho4\nwh5df+p6M2f6ay9Z4V07e1G0O+804Otyhc8aZqv77nBx06tf5E9YhrZ94xtdeMvWD7p4q89CljEx\nPQGz3Chcn6zqri7vGJsxg7Hv6zRc0RRFExTjymr8LkY3YSbFD1Kv0EFHhxtsrse6fOcMuD2u9vyF\nTkW6wegM5JxDZx7twkw/xBRobOg6pPxiO9J5mInhlqPTMv08mdRGPlXeIIpe2whnHp3BjOlQ5XE6\nkTnI2Ed5nIMYdTHY59u2tgFtx3RzcFHSON3V5eP2dn/9RYt83LbDp76qvxyTHF2u7AvsW1t8qkTb\n5993/ft8+0V4Pde3ppyTfHezn9GFSdck5x/uaEC4gwDvPwPX57uO18/ssOBd+7z+gvbyxXuu0Ddo\nQgghhBAFQws0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgTK1JgEK+oxCsUhBLQStzHQ0g9QhFor1e\ndPnkBi+SpBCbUGNKPS11iNQHU9RPzwJ1le0QJrasai1/AaZpYQFYQJgCvvEpXx+3bcHpPrThz/v4\nHcv853dv8aLXx1O699nQlC6B/pV1zUf5FkTyy3zT2uUwYLxx5EcubrkSotB581xYu8jHnSd8X2pa\n4/veEgpyWWAaUCBC3d3lD1diZFJTW9M6x/+AaXIoqJ7b5GOmKaM4nWlj2HkpHof4nX2Z2vhpA8dU\nRWXp88ahuJnCbjY0hfCEY54VDeF+pt3Yrrwe+8XBU/3mWJ8fhDSuNC9FH6Uxpx3pxFi2zHyONFg9\nT/l482YXHunxEzRF+o2N/tk5ZI/BA7GgzddFZ2f5VHzd3T7+qff92G7McazqjJ9kk3cqVdG4Q6PP\nqvN9jDmOfaNu0yYXD+7BA6VfeCzcGFJG8mFYVsJUTBxXNBlQ5M+YawuuHWhq4PN0LHTh8E50jjOE\nvkETQgghhCgYWqAJIYQQQhQMLdCEEEIIIQqGFmhCCCGEEAVjaqW7VGXOwk74qy7wMYV8MyDIpQC3\nF6LSCy904YLXYn3KXcAXeBHr4nt+4o//8Ifly0fhIgW4nZ0+prCyAyJaimarq3xMgTEzK+zZ68LB\nrV4ofztcANCw2kWIV67ED7Cz+OIrvVD94c2nRLXHscv4oR6vMJ4NTemNN/r4J7f7GJez70BvvP8z\nPn5Tn1fsnne1FwyP9nFnf9yAbcsTmMWhF4JmiF4Xc6dstjX7dh3GytFjOE4BMc6vQ1+nQBu7jGf6\nGscu+m5G740GWmzTBCrDKWSnCYD9hu3KOYFjutuP4Uy7UhxNMTTPZ3nyhPopoXn9CqaHQJ9rQFYD\nGmlYtsxu7zAZZLIe+LKN9sO1BWhc6UFmFDYFd9JncQdxOyZWGMXn0TMy2UZYPprQkEjH2k+sd3E9\n+yJNdA2oT/Y1UFvhTRfOUMK25vxHk1KeoSFvPqX5hvMf+xbHQR0agyYpGAiZJYgGmDOFvkETQggh\nhCgYWqAJIYQQQhQMLdCEEEIIIQqGFmhCCCGEEAWjUCaB0V4v1K6kkJC7CXP39Nb5Pm7D+hOi0ozo\nlDvzU8VJ0wJ2G84IHfMyIWR2/YZAl6pVCoQXQWrd2uLje+/zMQTMW/3G1Bl+Fzr3m2/2cVUbBMxU\nyfb63aHT1VOJpqEAlsepd/01lI27hFNv/CQ2TH9wg48bG31fpAa+FUkcMm1DEStTIRD2NbY9j7Pv\ndHT4mAVm36KAmGOLJgZWIA0nbRhrKF8LDDdH+jCWpgucU/LMHTQKsd0pfqYyffm5PuaYY7vW4X40\nHrFf1EHYn9nRPWUWoamJZaFxhX2Sz0p4fRpVWFYwZ6mfn06e9JMA/Rfzl6I8eaYv1N0gdsNntpRO\nlK8aVUvjFE0GTARQvxzvP/atrdt8zEmUyvc8oX/6+Wl+4buXjoeZM33MfpVnGqAJgOOK5pzM/MyM\nH+XT/hzZ6fsKL3em0DdoQgghhBAFQws0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEw\nptbFCWtE5aoV/jgdTHSZ0OXTg/Q0dILQZcT0E0y3UwmX0JxliOGAMjjtuP6th8vm/nt83Njk4y3I\nvURnH5+P9cFUHps2uZBGwLde7+OfeyNcoje/1Md0CR0+5MKhtRtdnHZmoii2Ak3PR6EJ6JVvg60S\nLsru9b4v7IWpkl2BaV9acPnm6+DgpQWM0HXEvtsD1yQtWmQJHFgH0PeYpqylrfzxHbj/Qdhc6dLi\n2GKatX449gCH2nThQK+fw5ovgdOc/YD1TPca3biZFDhwMjbTXoyKrkU7cspfSHdt3ishVf5BpgPD\nszdi/qMVjjEdrQeRjofzIz5PU2It6r7lBiSrYzqgpWf7OM9lD+t5y8DDLuacRuMgWYj5uAZGyFq8\nDjNjmk5rvj85pjkJcgzz+un6Zj/ku5Mub96bEzwdqExJFnC/CpzPvkd3Na/PvodcdHMw7KYKfYMm\nhBBCCFEwtEATQgghhCgYWqAJIYQQQhQMLdCEEEIIIQrGlJoEMpr93l7/A6aaqM5J30BhIYWMEAJm\n0vMwTUstRKMGYfjoDh9XIg2LQeT68DofU6gIkb2tRj4jnk8RaBVUpRQcr1zpwpZlSM/zWpgiVp7n\nYwo7V5xb9ngNG3jDqfpi0dugaWdWkqplMCwQiKk7VntRaMd1UH1SNErxNtOIXXihj9n3mCpp3xM+\nbpjjY4rDKWplWq99EGRnRLd4nrNy+goruN+nqcn0RY4lCqaRC2vbvb4+6YFotukBh0Qm/RDHLNuJ\n0E3BeucYt3bEEEtb+XRIWahEZ46bVFyLYzPRJ9hH6PTZt8/HeQaKEyd8jPmtdgXmiLkwFdCwwU7J\ntuH9kcopk1pv+XIXnjfXG3k6O/3zse/Ud/r3y7Euf/4QHr+Ownim3qORicL9nXgfZlIRVk0cZ9J2\n5fRbmlUi1HXgd0V4tlHUPVM7sTLZ91hXPJ4xFPr7NYzh/mcIfYMmhBBCCFEwtEATQgghhCgYWqAJ\nIYQQQhQMLdCEEEIIIQrGlJoEHsVG+ZfM9KLISgiPbQZEm33YTX0mhHzcSR8i+YzQO7PVM1SZttuH\nldzFG7spH4fQmyYGxhQ6UrjYdA7uB1HnEOqDItFV55c/TkHzbAjbB7HTNEWljCHMTDdHO7TNi6+F\nwJcCXRpGjh7xMUX4rLt5kKXTQFENQwS3JaeolHVH0T5FqVsewXGIvdlXu7t93H6Wj5chqwXHwk83\nlC8f4zr0RY4FCrQr0D7bt7vwLOyKzkwO08UkwG4xn2OIUAjP3es5J2TmJKZkoCmAW6BHiDOuBsQ0\nFfD8uRMfCxj/cyCi5/cBc9GnOOY5hmi8oeidY7IaQnUaY1i3HPMZ0TxelzTejKGuYUqo5RhmNg4Y\nTOpbIYTfAVMa34/Lzi5/fD4GJWFmhaOY79P1RYMF56/ZeFa2fWC/IjARMKsB24ZZENi2HJd5bY+2\nDssx354h9A2aEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgYU2oSuOQSH3Nj6YUrIezj\nLt0UWXJ3eAqfxyDir4GolByAKJPC80qITg0iVu6mTNEqRaXcHZlCcJoQCHfu587YLD+h8LICwkvW\nL+ufwn2IeBesTj3fPAiImbWAu353dfmYotQe7ORPATGPU3Sat7M+65aCWrb1LPzuw87O5zmMultz\nmY8PIitFRcD9MZRpimDb9iAzAU0TjNlXWX8Q4Vbi8ZkpYrpAk0CmXjnm2E9Yj5UU/TPGuKCYOhOz\ngBTu83q8H8a4pbMB8LMw8mR+/4cwvAHZM1bCxERTAE0DhDv9L0P2jwWYY5gZJvPsMHTsh9GHcwDf\nT3RCsS/QMMI5hkaeRmRGyMukM5dWHLTPQpQ3Uz5kE6EpIg3n69yMFrwWXv6GuuD8xbZmFiC++2jA\n43zJ6y9a5GNmSjhD6Bs0IYQQQoiCoQWaEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgY\nU+rirJzl0900NiLdws6dhhN83IHUFRnnGVygdFAxVRLXq81MV0FHE+43BNcjnSJ5zhE6RSqRDoj3\nO4KY9XMCzha6oAYGEMMZw/pfs8bHTD1CFxFdSWmXFl2YdB3ugxuOaao2PoTPI/VIxhEFF9FMpEFB\nqqKM7ZAOJrqW2Nfy6papq5jmJuMaxXG6UvNSDNHBPII48zxwmNGxxixoSF1VO9OPpdq88j1PoVEv\n48695hofcw4gEdxngSfQyU13XC9ijMnM+XmppNCPnUuUTj3ei+l80KcD5mP2Mc5XPE5XeSuc2wvp\n2uy08vB5UL4WjAm+PuuZ+g/PP4z5mM+TST+H+Z+prPKc5XQIV7GtUV/1jJGq0PUVujYJ+xnfnWRm\n+cN0vDLmu5TPzlROmduj7jgfTxH6Bk0IIYQQomBogSaEEEIIUTC0QBNCCCGEKBhaoAkhhBBCFIwp\nNQlQ2JzJJEETAIXGDXPKX5+pMCiqrIAAlulzmLqDovtaHK9BeY73+Zii14yJAak9KKwchdAxYyqA\nSPcohOSsD6YSocif6Y+Y16YDJgqaClZApLsllSqFz862YaoNpjrivSkazZgGINKfCVEqRfPdSDPT\nihQ5vB8FvEwtQlNEd7ePj0LwTBMB79eLtqX4vA99j+Xj87FvU3TbCNFsBfoiBu/+7V7wTL1zzsh9\n3rBgJYw57MecQzhmKXSnULyJ6YiQcsvQzsY5hKmeKPymsJ8mBKQgc8Yqmpj4+z6eZfBRFA1lq8B8\nR6E2+3AmtR8NDhSeU+SPOcJoZMEYy02LtRAxxkgVrleFVEqkF6n/aAJj/XCO4PtmNuacTP0wFSCP\np5+HKcX4Wb7MMb+wb+QZ4GiyykvFR9g3mAqKsC/y3XmG0DdoQgghhBAFQws0IYQQQoiCoQWaEEII\nIUTB0AJNCCGEEKJgTK1JAMLmigruPA0oCqUQe/m5Pt75uI8HIFSsg0B2QaePhyFEpPB6IQTANAWw\nvBRyU+jYip2od23zcWYn6ZzMBfMgbN+3D+ezPiCkrKGAmAJlCCkpbOduzuWElhRl1mAn/wXMBACB\nbN+B8sfZFhQot6Ps/Hw3xNWdeVkbIKDe/hiOY5fyjGkCbZsRVMPQ0tPj4w4IlikgZt/vgyA5z8Rx\n9EjZ4yeQaYB+lGnDosU+psif/YJzFvsJhd/DOTugz8D1AudQCr1hDjGaEGgqYCqD9DiiqB6fHcZ8\nyOwXrCt2Eu7uzkwBHEP1zPwCk1kmswGF68w0g/tHKH/g9TGf5zEEk1omu0dOZoDM+xCf34E5h2OY\nfY3vi0rc/0hqjqWjL5OlgCYBmk9oEsCz8V1L0xLhfMW+QVNYP+qOBjm+S1n3Zwh9gyaEEEIIUTC0\nQBNCCCGEKBhaoAkhhBBCFAwt0IQQQgghCsbUmgSQKaDv3h0ubsFG9jYDQnKKHimCp9CbInXGxyGk\nngGhIYWEFMnyehRScvf3w9hJmrvjZ3bOhmCYIlHu5L/qAlyvCeXD81RChEth57a1Pm6DkJ/CTtZH\nOjsADQUUDFNwu9f3jYwpgKr0fRBDZ9oGzz4wUP44DSjMbMC+QlE/xeJ9iGkQ4fXY91nXLC/HBgXH\nvSgfdyk/CpMC+x6e79hhPxaoya1ppFh9mpDZvR6wHjmmabZgO9C8wTHPdq1g9hKaECjuZjYAthOP\np8cpXh80Bay738ccE5wDaBLgmM2YAmDQMLYFhep8tj2IaRp40oecX2dijsnLJjIGkxWNOxzjGWMQ\n6oPvN8LrE2Ya4BinKSN9nM/WzLLQFUSzC+p6mHUPuPM/+zXrhnXNvsPy0zRFMu/+M4O+QRNCCCGE\nKBhaoAkhhBBCFAwt0IQQQgghCoYWaEIIIYQQBUMLNCGEEEKIgjG1Lk4492hgyqSuoNMvzzXDVBaE\nN+T1z0K6HKZ7iJgOB85DupIyTjucz/vTmTK32cdMR0FHF+9fLnWHmVk/XEu33YbjKC/Lx/vRubji\nvImvBbfa0O2fdjENujTPzZvn49AJh9eqVT7u7fVxGxxLbCu6QnmcbccCMXUT644PRAcXHVt0KbHt\nOXboJmRbbd7s485OH+e4Yk+c8GOBxW+hQ2y6wDEIZ3qmnVkxdO6xnujEoxuNKb/y7sc5rw5zWA1T\nPzFOg8/SaUfHKdO5sWz8PMdEuVRxZmaGScLgmreW8scHUZ6uLlwe8yPHPMtL135eqr8GpLPj+4yu\nSs4xPSgfYXtwDuCcUgMX7Myhic/NLCXoys9xbeY5VjMuc5xPwyrHCZ894/LE/ElXJ9vqDKFv0IQQ\nQgghCoYWaEIIIYQQBUMLNCGEEEKIgqEFmhBCCCFEwZhakwBE/lUDEA5SlE/hXia9A0SrFG3WQYRJ\noThTLR1DGhYKCSkSbUHqkl2P+Ziiz2XLcBzC7rkUceI4hZBMRcLysn5uvdWFT673QnBmT9q0yceV\n6D2VFV6Izuq9+up7nv7/gwfvccceQyanJ7p9PBtNWUV/BLK4rF6928Vnb/Fx3VKkVqKhhCYAilSZ\nSoltwRQ+eaLUPAMM709BcEa0C5hKautWH9MUwPIz9RT6MvXGzETFVFAYic9fWiE85xhmaqWMkB6m\nAKYc4xzI63EOzNyf5hIam9CPeb96lGc4Vd7MtSCkbm/3MUXwND0xrVUvYo6Row/4mHXB+XAe7kfh\neCYVH+6HMbBtg3/enh5/+vbtPk5nujPLn9M4JM38JDm/Ax/gIOT7jnFeOrnjmAPq57BAKfBui6Da\n34O0WjS30ATFstBgwncpz+f8ypfZAPoq52/Cvn6G0DdoQgghhBAFQws0IYQQQoiCoQWaEEIIIUTB\n0AJNCCGEEKJgTK1JgKLGaqjKKYxugwj/BAStEIpnRKY0IVB0z/N5fwp4m7CTs0HoSAEwlezc/b2x\nycfceZoi2sMQcdJ0cMcdLtx7+0MuvvNOfzr1x9xcHrJyg+zcVrb5mPrjr3391P8/Bo0nf1PAYauH\nxhM1l+nI67tQNhR2xQrf1xq+80MXX3o9BLHMNECBM8Xf7GuZrBLoK9wZmyaA7r0+pmg1b+fsbmQC\nyDPM0JAzcMjKweJkEimgL0wbkwDnILYrzR4Hkb2DUDydB8XQszASaJRidg/OMRRfD08iA0QLBlnL\nUh8fQx+swfkVqJtuOIXgPDl278Mu5nTLR6mu9kahplb/7Ht3+g9UV/vPnzjhb7CfRhj0cWY/oU6d\n5eUYWrfOx00Z35Av7+JFXpi/YoWPqzgHZYTy6Es0jCw/99T/cz5kxgsaLJiFgaYl9lPCsrDf5pm6\nmBWCsPJ3wLXG8p4h9A2aEEIIIUTB0AJNCCGEEKJgaIEmhBBCCFEwtEATQgghhCgYU2sSSIsOzbKq\ndApwKUSksPAk1pvzsMt3niCWAl3eb8l5Pj4OlegJCK2plOZO1RR2cytq7uZOISRVp3/1aRf+6Pv+\n+Vi9O/B49/ow47lgZ3nbtT6mzpL66PTO2hF22b4W19qwwcc0MHShqu5H2bjn9QiaZhNiyGdt505f\n96tX+/icq9G2FOWzbSmazWQegEmgY6GPWQEUo3OssG+3w2BD0SwbiwJiMISuR0E1h87atT5+S9mr\nP4+gmYNGJrYr2zEj4kc7UknOiqYwP8IgDBi1Vfi8cQd12m9gKhhK9Qs+2wnMb9wdnp1i0/f8pTc8\n4mLOJ5y+2YUpymfVLYFnoWmevwGbommef59EI/58au7ps5mD4xySzLbBzfbZVQbhUXuqp/xxvh5W\njXhTRS2unxHWMztJT6p9mRaBcL6jOSWTuYWFAZxfj/qsNRlTU54piwY99OWhLj+ua2gCO0PoGzQh\nhBBCiIKhBZoQQgghRMHQAk0IIYQQomBogSaEEEIIUTC0QBNCCCGEKBhT6+KETWfwoLed1C6C04JO\ns507fbxqlY/pMspz0uWlltq9zceLO31MBxahq4nOlH44U7bifou8s+/Y17/r4ltv9affjeqhK/Mx\nxBsRX4i4A/GLboIjrBXpP2ZUurBzQ9fT/9/e7k/9uRv8tVav9hYsOpLoCtyBwtODyDRVrAv4c239\nFh9vRnwTLFgLYWraD0fXxZfgBrSksW/Q4tVxlo/Zl9lXaXGj25BuQKY9o4MLFrQK/GrHmO1Fh920\ngW6xPKc45yTOaZnrw4+MMZX5HTswZQ6skBk4EphqiinMUlbB7Zif+Ox06TN10xbv2rztNn94CC7M\n40ilRFNoF86nL/ASDJn5rb5u6BrlfNa/3Y8hpoqqqPBtzdcJuwpT7XVggmV52HUIj2+DU55TCsds\na6uvILpaa2edcrLXrPdps1o64aKkq3IG3rUjmG/oksxMKIPlj/Pdk0mFh7UEc89hLcHptbXaV94k\nE7I9Y/QNmhBCCCFEwdACTQghhBCiYGiBJoQQQghRMLRAE0IIIYQoGFNrEvjmN1x4AKLPDubqoMqx\njaJ0PA7TRzC9A3NrULDL1Eznr/bxcSgJ+Xlen9djKqq77nLhcLdXmh+9y4tq70VupkdhCuiEDpzV\n+bgPrQ0xOwc0p/aFv/IXfOnNe13MdEBpXedGOhLMX4siTWqtZ0LbfAMKT4HudhS+CU3VjHgDzqeh\nYs/3fbwSXY2CX2paL1qNB2pFX2CasAqIw2fliF5ZAftgm+BYyvRdLwK2Vp9SaKjXX69qlu8tfX3+\n+e5F35s2UJlN8TOV4QMQO1ejXQaQr2fpEh+zIxlNAzQJEJTPYE4xDLxRlK87Ncbr6v2xrY/6eJNP\nLUShN400nL5pNBnOmQNmoY9x/uL11q/3MUXxjY3eFHAETR1gCuCQIiz/UqSeymRHQnlprMp0BZCX\nCoufZ9fjFNSWmmM5tzcexnzAfs/5iFDE37e//PlMXcfCMk0iO1e3f1ft3ulNBawbGlKay5fuWUPf\noAkhhBBCFAwt0IQQQgghCoYWaEIIIYQQBUMLNCGEEEKIgjGlJoFPf8KrJjs7/fGOV0C4TFEqhYBU\nklMVSZMAd1/nzv4UNj4J0f8C7JS914v4M5kKKISkiQAq0S3YvT5PhHoOdrO/+WYfU0f5Noh0ubP1\nJgjloSG1n6J6N3/Rx6hNJz/ehWPfucPHr8ezvOpVVpaVK33cjGd9PUT8odp3/eEB33dWIfUAuxI3\n4qeAl5y7xvfdQ3t81oimRRBv90OczZ25GzA2KMpd/4CPqQDO7KyN+9E0gJ25K/mrHa7X3e3rEyNh\n+sAxzHqdBRE+zBYZ9THPZ0djxomM6J8Nw/NhUrCR8jHNJ2k4IdEAgd3hR3vxrGARxnzedM75rAVN\nUQ/RP7s0PWSDEL5TtD+IIRRxs3o01cKleL3ShUBDCZTp0WH/fguNPqvE6EF/nE3F+qxEcWpQ3kzm\ngEZ/QnTilAuD92JbVTEzCecn3uzggfIX5LuYn5+DCZiNu87Ph8M9vi9mErPAdEaD3ZlC36AJIYQQ\nQhQMLdCEEEIIIQqGFmhCCCGEEAVDCzQhhBBCiIIxpSaBb0Mz2on45VQicjdgivq5+zBNABA6Z4SG\n3BWccQeU6EMQyVLAi52zrReqfAi3h/u9EvGiqyEMp8oVysbRw154XjnXi0r5/AvqfP29vtWrZG/O\nEYJS38ydr3k8rRNdtswfq2/Ds5KV5/l46zYXzuz1z86doLOZCfzDUODL8l2wGhdcvtzHFEjzhjCo\nNK1AX6EKlZ/ntuOsXJoAKODOM8Cwr/f7+swTRA/2eZPBzi5/nPvdTxd2rfVjmkN0Ds0dGRMBxMzs\nuOwXPH8Yg64KDWVoV+M4gzkk73f2tMnh4CF/bNUqXMpfqxKmgRZsdd+yz+/cn+mDI/7Zurv96TTq\ncHqfvwqughNDZe83ymQf8HeEuRhDDZhv85TlqA/WV5iFVAnz/P71ldhNfw7eL3PYGS+80MecA/i+\nxZwRUnNKPdMU8N3Lfs5xwGdvRVYgzn90ENYjwwb7Md+9uN4dMKUxy8MxVAUzzWBl8Zyhb9CEEEII\nIQqGFmhCCCGEEAVDCzQhhBBCiIKhBZoQQgghRMHQAk0IIYQQomBMqYsTiZqsC/Gjt/pcQ+e9/gJ/\nAtNJ0KUJV05eKpKM84QunN6nfEzHFW2OvXC2bH3Ux8gnUdUKV03HQh9fd52P4byrpDWF5aGzBek3\nKht8fcyZ1+LPR3030ybF560IPk47DekwamzyMfNc0bWItqWDtKnN2wxrZvq2PAKTENOg0KVoq1f7\nmK6inTt9zLph3TPNC9uKKX/YtxkP0I2XA6/PvDl0aSHtDLs+DcqoDUNPnjbQ/PoIuu1LZvmcYVWz\n0NHopFsBtzLnLJ7PfmBMzZSX+omponC9OZgD6lLlWQlvLufjud51aD1waXLMc0zBiRzgkl/YKtJd\nFgAAE75JREFUvdfFozu6XFy5HM5nWrOZpgvzfWVmPkNd0rXJ1H58f9DpSNd/3hhnzL6y5jIft8EZ\nORvvT0P72FD5+Nj6U//P+WMPXJoV6Bvst6xLwjxV9bDQZsqOCbtrnQsf/o7vK4SO3eMYRguQ+ulM\noW/QhBBCCCEKhhZoQgghhBAFQws0IYQQQoiCoQWaEEIIIUTBmFKTAJLRGHR6tnGjj8/7HxSlUiAL\nmMpjJlJnUMi47wkfM1UUhY2MmfqEx+vqfdzTU/44U3NQeE7R7fJzfMwKpJKeIlWm12BaGaYC4fUo\nVJ8B0Wxa8AyPQOZZkBppcLOXnR+AZ6ASVc20WRkNPh6tai7qngLbWRDBjkU+zqT5Qt3QFEADC9Xm\n7WeVP860Z5ugTmf5KVhm36TJAYQZ/vz+o37sbdjgz0fWHYOHYNrAIUbWr/fxJZf4jlgzxpRdGEMU\nlnegXzDF1wy6X2gKwJjMzLoE/TZ9vRYop5l2Kid1EE1SmfRpNGVt96YxW7TYF80AjUg0XHD+xxgb\nRPq4TNatPm+cqWqkUN6PmaF+tH0F3k8U0tOkhdROtuxsH8+GacEaEON6mUmYfaHLh+k5h3M74zxT\nAOfLjAGDZce7zzBf09yy9n4Xchzydh0d5Y9v3uxj1Pxzhr5BE0IIIYQoGFqgCSGEEEIUDC3QhBBC\nCCEKhhZoQgghhBAFY0pNApT4QzL//9u7n14/qvuO479rYy52Ltd/MMYFxxCglKZpRdMoQlXUdpNN\nF1W32fQZ9DFUald9AnkE2bSquoq6yKIiasKmqGVBDTgOMcZ1bGM74DoYY/DtolL5ndfAHVUq9mC9\n36t7PPObOXP+fOd49Pmc7+qf0IR+z93l3an6AAJadzt+mp2lFa0quGUn68n1FDpeJzfCRUSu7jSt\n0Pvb7ASNUH6S+eBZTQH/znF2znZ3eHe3N5OC57Nz9u3T43E3+3/sOUSra6LdW6+OO6zrl3jyuXFn\naKviTv/6J+zKg8dnDCIKilWJfoSgV8XwtqJVuI4pQNOBY/EB6qeIf1Jfsja4S7q7tCuY9vkQ/b5/\nbZytB9EA/5r21hRwTwPNF4gZFJzSmln0ehzaM7brvvPnxxM07mhcUjiucWov42qFkUk+YVxb4cPr\n444xqqFB4bhzyroaj8w0YLaLN94cy056nStmZtGoo6kM7Ap9QIfujAYPq3P4GINj0pdYayZBbibG\nrIgBK7OL0B4T0wAx0t+vvw+3iF++G50IxlvP17W1aV18dsbp6upQunlmNPwZn/ZzeaedTe/xu0Vf\n0CIiIiIWRgu0iIiIiIXRAi0iIiJiYbRAi4iIiFgY91S7683RYE4yDfz4R6Mw8I//AiXfBXajd/t4\nVZ6KTj1fLiOCPXlyLCuC1ZQws1v7ZLd5RauKblWpKgSfKOdv7n5ckwFC9FsXRsWzt39j1P2vHjs5\n3u+/Xnv/c89VlPnOP499vcnxY8fGsl2590GzOPCsiuwVLGuYmBO5nkZFqmMCE8HOqbEBNhR7uwv7\nMTIDaGDRZGD9HdsKpDn//fPj8YNPja6Af/3ROJd+ema8nHJr7DL3DU7599DUX8L8otj4UcbxpF8d\nlxqHNCptMM5vMQ41GmlWMUZ6/q21Se+k1QhjgNDIoinA+ORu9DcQrR/FJOac0xQgxNsdrw9q+J2i\nMjEFOIftW9t6IsRHSH9lFMZPYoDt6/tjm+dVmH+VsbjeP8YX+2qSaYC28PcTA4TfjhhLK/r6Z2Oq\nAD1Sj/J+sDp6vvTGmGngbtEXtIiIiIiF0QItIiIiYmG0QIuIiIhYGC3QIiIiIhZGC7SIiIiIhXFP\nXZx4gFbblF+m/C8/Gcsvvvj2UN58/iluwB10juga0ulm+hude1pFtnmCM1jbdEhpAbOs03CSjwKn\njM+jk+YEqbB0ib7w+2P5zM/G0zHS6HSxOX74j6M1Zv3xb5J64zdwSP0ah5RZqzQNTTLc6Aqy7e0r\nz7/wnxzHHXfhwljWXedYwSG2cZS+tTGtnw/o2NQB5vFruFB1fN3ZPZWT7WdqLpKcrd6mjOfqvuHn\njFOSm63OMGWd0rrD9h+gn6+PTrotJ5kT4SvEEGOg48JxN8d6ENjkabU1mp/NOaL1Wi7j/TU+a8XT\nNT+Jt7hIGfMbpFfbg2t934HxfoePMMeN38Zn46/4frL+c3j/uRjn+ca0i+yKsP4+sS8nLvgHdz8u\nG3PfisipdpXySy8NRZvuNkNHR+5rr43ls1z+NvHue59dyf93+oIWERERsTBaoEVEREQsjBZoERER\nEQujBVpERETEwrinJgHlqa4WNQ38LUK/P0eD/41vIYI89fpYNhWSqZo+QLlu+h1TayjCNLWGIlgF\nuv7+HNJqFcRzuUXMVyGmQlFgrAvg2d8cige5/7Vr4/lf//r4c/XHe9c6+BB6Xm/9BCLOfWhOPV+2\n3xtl6xsPMtRN26Vo3rZRdappQAGzKXg+IG2Kab28nwJpx6b3t/4Inh07Ox9+tNvh1cOPj3Ppl6fH\nND5mLaM1J4lZZpKofWmh1Vdvzpz/FOLjn2B8cg4ZoiapoBzHpo5SeO44EQeCQvd1sffNa59/bLWa\nxsPdROer1WeYujh+nHh86j/GsmmrxID0AamOmGPGmM1DxBCf1zlnfebSH4l9ZSrDiTFp5n7GHE0c\nvh98vnWTw50d6kK8sy00JEzSKpLGyhRljkvrSry0797BW/MY88ShZ1JGpu1doy9oEREREQujBVpE\nRETEwmiBFhEREbEwWqBFRERELIxFZRJwr2H1sa4m/+YfxvLffeed8R8UKsodRJPHHh3L59lNXtGr\nIn9FnQq9Fbmep77HUC6+8spYPvlVro9AWNHrRCCMiUAThcJLRKy/ODUqL9VtHjiwe3n99jadO6y7\nYbp4b8t7Gdlbx8cb7FwcZZ8btt0J2tqsC2IWB6+3za7rCnyv0JdzAmKv7/UEU8H1y2NfP/TQePqN\ni6MpwP75MZ4Ju2vGrnLf4F7vzPiVvfIuGn93OH+UEPBbGp8chwrvzWCxrTibGKW4e2J+4fz1GKhx\nxkloXb2XY957z2UGEK/n+cS3WzfGxrcv9BR8iPJcD9jebUT6zlFNYirTPd/3je1jTBH7Q2G+D+j7\n0hfyev9p4LAsjlMNCNu8exx39qUuJcbWkSNj/BKT/OjRMn5h0bpr9AUtIiIiYmG0QIuIiIhYGC3Q\nIiIiIhZGC7SIiIiIhbEok4BlV49mHvh7yt/561FI+Jfff54LcIWPHxvLmgJURvt7Rf6HDo9lldfy\n1NfGstsfe78b7nytEB3l/ZyoVtHoFiJXdi13M2hNADep/pO4PE6f/vRvH03Uz3r+w+hl3XF9g7re\nOjeaAtyYf8+eUbR68Aht61hQcHxtPH9zS5cCFYbbN0ZZ6r6tsQF2zIzg5NBUwFjYuTLW9+DxcWxe\nOjt2no+rpteRNSeq3f3pv7yg+V+dpswUWT3ClPtDGu6mDaewfG5HdbOleNyJdIwY6CSXdeOR8UWh\nuPHE+OWcUHXvbvXez7q6c74BivtvHh/vv4nJa2t7FOn/6so4CfY+yP016pCJZRLUrJ/tZ3uZKcD7\naQJjzk/ay7F1iLEg66YF62rby0XsMxrqfBazHviu0xCCqeAw8esDmuZlUgP8EdPKnBQzr6svjL6g\nRURERCyMFmgRERERC6MFWkRERMTCaIEWERERsTBaoEVEREQsjHvq4tTjqIEJD8rqccqmgvo+P/jT\nH74xlJ/5NtaOC6Sf0CGls8R0FddJJ6GT7pvfHMtnfj6W92yMZV0+5p94g9RMcy4m8flMdWW6Iqx7\nmq40IWmyunBh9/N3O2ZT2hS7XWu1Wq3exaVj0x4+zj/oaJ1JE2OFNk+So8c0NxMH8eg62vfcU+Px\ns2eH4oaOONPAmEYMl9WGY4WxYJYxDcX7T4xz53VmJyNrRXdNssbcL/jcJygbYBmWk2GBcXp149po\nP9s6MLp5J85txs1kTjuOdNM9+8xYPoyzcr0nraxW3yOPjGVd7aYqctLfIL6axkq2SIt1h3hvEDH1\n1Ex6tcPGf9vOAGlbOwe1kv9fn9cY4+91PuqMPI5r0/oeJfXh+vV8duOjZeOpbeW7yesbn4UdFK5e\n+eXnnPg/XKR8na7gye8ZfUGLiIiIWBgt0CIiIiIWRgu0iIiIiIXRAi0iIiJiYdxTk8B5yshdJwJc\nU0GZXsbyD34wlv/qRdajF0jtpFJaBa9CbJXqimRVyStSfeutsWyqE/PtTFI7IbK9joBYUaipQiap\nnhBuPjemKnlEkwNC9f1b4/WOfji2x5C+6MHRgHHpzChwPYHaeuPEE+M/XCZ1CILfRx1Mth3n37gw\ntt3WCS6gaFXBr2NFga3HTQs2SZtDqifSvkzaQxiLN8+Ngm67/u1zY/kbLyK4pn6K/vEUTFKj3K+p\nnjQy6V2xXf6E8huUDxAUNw16zmlT7pw5wwVNWgOmB1Lc/RXGwa/X5qkmo4nonzlnfJukHqIuBzBp\nGW8x2kzmqG2zh/itScD4bVnRviYxUyf5fKY7emDvWNY0IJNce9TH5/H94aQ3zZemOA0o68c12Dlu\nfFd4LQ0ZE8MJab4mLrHd32VzWQ6NR2cpM+pXv7P75b4w+oIWERERsTBaoEVEREQsjBZoEREREQuj\nBVpERETEwrinJoHjlBXYKpm0snOC3Lcp3zo/ChE3t1HgTkShCBE1FSB0n90N+SS5D154YSzPmQAm\nmQCorztpK0x3J2zr/+zXuB8i2G/9wVhWsIzId5LXYF34jiD1sd/j2RXc2he2pVkWbAsFtZfHPd23\nnsYg4g7sCmgV2CqSdad/RbITQfIoir19g7bcYqxqklB0y/3UF29QfsI0HYzFSxfG+jrX/J+eHo2Z\nfcC/tKhFNkap8df4pMng3wh6L700lr/7Z8QUY4JlO/4Kv3e3f+fNLzAyraMo3bIifVG0rhBc0bxj\nfGJSYNTNiejndqd3DpupxftbP9ve+nn9OdPZnr27HzcTgO1p/czsMJf5YN0YcPrN8ZgGCN8djoVJ\nfKdvjL8+y4yBzkfTtIRdZGIwfIeypoG7RV/QIiIiIhZGC7SIiIiIhdECLSIiImJhtECLiIiIWBj3\n1CSg0Bhd32S3cnf/VeLp9ZBxuzn76tb1URq4yW7tE+G3QnVF/e7E707XCng9PieydXt9MxEotNxC\nCjm3c7Wi2RNfHcuKUkVhqM+zLjrVcKE42bax7hevjmXr6u+vKMilL+07DRTHyAxw9izHGW0KiDUZ\nXH53LJMFYt82s2Gm7y+dHUf/oUNj+TZdu4+Zv9/J9/iYqeCjs6NsVlEttZvM5cur+xNF/0iZJ0Yo\njUtYUyaZBUwM8F3HmcJzt1BXvH0UU4Dnu6P7NebZxYuf/n2cp3v6mbFsPJnbad85u2djLDuHxPhn\n2yg8VxRv/FdU7wvEvpirjyaDjxXlE+M0eWkqMEbNGIUmmRy8nvHdGPfyT//3z51r47ixqgedCNbV\ne9k2hzj/Q97uTIydc2N80kNwlKF2jttbXdcSjMy7Rl/QIiIiIhZGC7SIiIiIhdECLSIiImJhtECL\niIiIWBgt0CIiIiIWxqJSPZ2jbOV0TOnq1HlxkfJcpqSPTo+pkB7W5fg4rkgvMOfKPE8CCZ2Hum50\nvshxXEQf4pKauKJYj+taOopTUWejVh0xHYesO8aO4V+z7j67jloxjZWuoKef/vy6fBYTxy5j4Thj\nwbY5gCvVsYIr9ObF0cW5B9fS5gOjG+/WB+P1zBKja3NnxoC796Fxtt06M47V93k8M0M51zx+TwPN\nXcRRaqonEpStmHGrlym/g/31k7dGH+jeGWfjjYujs3pLp7Xp5LwezsBPXnn103s//+x4rnNWK53M\npVLaZg7OxUN/b7yblHFNGi9N1Tdx6TPJ3vsV9TG9G/F2kmqKsu1j/XWVkmpv4pq1703V564ExNTb\nlz+NmYZjw6Ovsg0dpI4N32WiA5e28d1uV71F/DMVna5z5/FM+PzC6AtaRERExMJogRYRERGxMFqg\nRURERCyMFmgRERERC+OeaneVnCvEm5Gkr9AlTs5X+CcHj46Pf+n8KNI8cG0Ubu819cjJJ8eyJgDS\n5UxMA6YCUUiu8HySHoPu+xil5BHSuqjcNL2SKKRXpDqH9dvNRKBg1rb23hoaFJEqkDWFjQLZx5G1\nT0T/qPDPnx/LCpitj6JY6rP/yDhab14bTQKKvTfRB5sJZU6frZ54Yoq4MY7910+Nhy/wc+eahh5v\nd7/gcztD5lJeMapWdhsy9smUfGRiDBrn0S3GxVWmwbFjYz/vv/HqeALj4vTpT//+7YfOjudO4htP\n55y8s0OZOWl6N3/v/SbXn4mXprHSFGBjm3pPU8J1RPiTmDQj4hfr4/NoIpgzic0Zo4yRpHry8Do2\n7cYDzIS5gKTpyjRTQt/btKeIV5qYtGf8LmXPJ+PaXaMvaBERERELowVaRERExMJogRYRERGxMFqg\nRURERCyMjZ2dnfmzIiIiIuKu0Re0iIiIiIXRAi0iIiJiYbRAi4iIiFgYLdAiIiIiFkYLtIiIiIiF\n0QItIiIiYmG0QIuIiIhYGC3QIiIiIhZGC7SIiIiIhdECLSIiImJhtECLiIiIWBgt0CIiIiIWRgu0\niIiIiIXRAi0iIiJiYbRAi4iIiFgYLdAiIiIiFkYLtIiIiIiF0QItIiIiYmG0QIuIiIhYGC3QIiIi\nIhZGC7SIiIiIhdECLSIiImJhtECLiIiIWBgt0CIiIiIWRgu0iIiIiIXx32HTr4q1iNXUAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e28f2b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "face_index = 10\n",
    "\n",
    "for snr in [0.5, 1.0, 2.0, 4.0, 10.0]:\n",
    "    fig, axes = plt.subplots(1, 2)\n",
    "    noisy_image = snr*faces[face_index] + np.random.normal(size=faces[face_index].shape)\n",
    "    \n",
    "    pca_coeffs = np.dot(wlra.H, noisy_image-wlra.mean)\n",
    "    reconstruction = np.dot(pca_coeffs, wlra.H) + wlra.mean\n",
    "    \n",
    "    axes[0].set_title(\"SNR {}\".format(snr))\n",
    "    axes[1].set_title(\"Noise Reduced Reconstruction\")\n",
    "    view_as_image(noisy_image, ax=axes[0])\n",
    "    view_as_image(reconstruction, ax=axes[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the noisier data in the example above it certainly looks like the reconstruction is doing an excellent job of picking out the signal. In fact again because we are taining on data which includes several images of this very same person the PCA reconstruction is probably doing a much better job at reconstruction than we could really expect in the wild on images of people it has never seen before. \n",
    "\n",
    "Note also that once the signal to noise of our input data is high enough the PCA reconstruction starts to do a worse job than simply using the input data. This is because the degrees of freedom in the input data are much higher than the number of principal components we are using to represent them. We can improve the PCA reconstruction quality by increasing the number of components we use for reconstruction but at the price of capturing more noise along with more signal and so consequently we get poorer de-noising performance. There are many things we can do to try and get around this for example we can attenuate the pca coefficients prior to reconstruction by various schemes which will often give us better performance. The idea is that the coefficients will in general have their magnitudes inflated slightly by the extra variance added to the data by the noise. By shrinking the coefficents towards 0 we can remove some of this extra noise based variance and get better reconstruction. However again there is no magic way to tell noise from signal and so attenuating our coefficients inevitably reduces the amount of signal in our output as well as reducing the noise so proceed with caution.\n",
    "\n",
    "To give you a visual representation of my cautions that an apparent increase in data quality can be misleading consider what happens when we present this same \"de-noising\" technique with data that is 100% noise and 0% signal. Because our PCA expansion is trained to find faces any correlations of the input data with face like structures will be interpreted as \"signal\" and so our de-noising algorithm will quite happily hallucinate faces for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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muvaUld9+3Ynz7rcyqO75ZrlHrfx2pX+Den9ggzqvmdkfVexNrwVW/knt/Vb+uWypWdYv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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f967c0be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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E0xQyU4TO9CVcgDJR+qRUVxGNIH/9ZF2+2b2Y0xRK02GAz+ea0DiCJCJ0wr5D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\nSpkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f96c08fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YuIzTPwVHKZvHruf8StffHpzvXovk+Q2ViIiISE9cUImIiIj0xAWViIiISE9c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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f96ada668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/+d+n+7/a+hyc8/ejzAM1qt/55mg3FOcGfu2j0X77dTfOe2W0SXVPDa57KNpvV2bWaPfb\n1mjzSkS8q2Pfsi+I9k9qb432z2XLg2v9wq3ct3ONH4t2M3Q5Wh/+Nwb+dNXPRuv/fynaX3KvRLuZ\n/K2I+Gqc91XRJuhcHFzreufYqn452s3u34kXpBynovXrr1ilHX/YvSaO3bLf36j/pUFHiIiIiMiL\nRA2ViIiISE/cUImIiIj0xA2ViIiISE/cUImIiIj0ZF3TJvzp16VMET8xkR+fnc3t7duH22kWlT+m\nJnN7U2X/eP368ONs4DZk5J9HbrR9yN22F/YOJqjFA8U4bNTtzEpoRcSxZ3L76Y/n9qFDmXnxUF5X\n8/Dh/PQjR3L7mWO5fQq3ZzEoHI4znX+z2uhZ2EzNuwT7agwHI/Wpmjk3YU/P97R3Ymrt2Jnbc5gq\nnDq0Ofd5nHN/Hg0a240G7ENqmn37cvvAgdzeBTtoM9UNk13j/jEFe/OLSYr4Occz/23uwzjus3uQ\n2mgnxwXjcOVybtNncaD3oN9f8jq0kP3O2r9FLeDK57srdzk/dAYrns9yBefPTOf2uXO5vQn5KW+g\nNN4M/P2NG7ld8+fXr+X2EtrL63Esivvherw/r0+uon/YX2fhJc+eye2r8Iqb8XqfQn/zeTZhSd4Y\nErC2GWNzAR6b996Mdxkd2ASOs295vfsfyG36L86lP85TaX30d49k9hNP4PLIoPbJo7n9te9rVvVf\nfkMlIiIi0hM3VCIiIiI9cUMlIiIi0pN11VBRJ0KJ0gyEL1P4c36a4N9pYdc0U/w7Lf9mzONU7lzF\n38xrfwPn8QZ2gh3QDBT3r7SHf8OnBqECu28S4zPOP9HjdhjerPVoabCnOXKcqBV1RHE+20INFYt4\nbasc5/U4l7dU5i7tQnJQmcq1qV1QzHXMBeo/ihHi3ORxqtqozaHkYGNUvSq0b48cwAkoi0ldJ3VE\ndILF+ZhYbEDhMzhRaNfq6HJcO+evYBVyDlGzM4Fn4fnU1dB/0b+xb2rweotYExwLns9FyTV1BX1L\n3RA/T5YqTqBYo4CaNWrMqDFeRB1p3o/X62rAzl3Mj9UcUk1/VujXMI85N3ic178PIij03QPQfC0u\n5vq0PXsyM85T1LsGfkMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0pN1DbWhkn4M\nrZlGJNTYTCUMkBEytUy7RRQJIpmKTLiM4kCDFxF1wuyx5xAKxiiYuUoETsPMvsgfvoSoDT4PogJr\niYCLgCOMx1Y8ToPHTUx2271WfqiImmPsEjOlM8qPUYLMlF67PvN6F3bPTOicqtO00SHjeIBiatd+\nFaplca5FiBYRqMzyjCifIhc9G8goQUQc3abMHUD00e7duX3wZblNn8GMzlyzRSg0fAwzVlejLwmr\nMRB+vjMRx+C/2FZGuS0uDj/OOVoLdeUcZlTbsCi1iDKqj1HZfH8UUXfwQjMMxcXnObZ8HjoNvj+4\nptnfXMNFlDpg5FzxAsD4dJ+H7xr0RXM1txPHilnZ+S4ko0YR0h9xHd6fVxX5oqUPZnazVKsgsEYz\nXtSnRERERORTuKESERER6YkbKhEREZGeuKESERER6cm6itLn7p3Pf0BhWS11fyHIBNchQqcwjqVm\nIKxbuTK8wMlYVdUNASlFfjWRI8/n81DQStEnRZj4PJuf0HyK0IsqF4Dnz0JJfqljX2IVCFwLksei\nkEmlCEMhtaUIHgVBilI0OyE6p36TNvWhtbJJDMBgWZ9aQACP83oFhUgdc+kKengRovOtrL1AUTl7\nnCNE0endRRNvS/bdA3tfbjPyhhODwuiTp3K7EKFjoGdZFIlCZAYT1IIBuBJZMqjrc9F2+msGAXGR\n8DhF4ZyDFJ1XAy9gc9GQ2vulKJ9SEfQXpXLohUDtfcL+5fPw/UHhON93PM5SNLx/t38pIkcAQNpc\n+a6Gn2cZIb7LLmAunDuf26dP5/YOrMPJg7n9eozNwfx4+pP3Zvb264fjVvAbKhEREZGeuKESERER\n6YkbKhEREZGeuKESERER6cm6itLjkVeMdn4hQoQIr8iMC1U0Pw+b2V0vQ6e7Qs04RO7T1yGMI7Vs\nr2w/hXtsf024R9Ehrs/LjWM2UD9LqLG8hv65xmTcHZsaaNocuiKxdyUBNAX2zEROfSwF9xSdb8Vx\nZkZnX9CuJX0u9KfUx8Iu9K21G3Cw2YHscM6tGQRAjFHgSzE0wwh4/itjQ3D/fbnNNcuM0OMIxNkO\ncSwDTThuDFRJFPvTx9DmwmHwQEW4PSzzOkXSXITnmRWeQUIQqbMvOceL9wHaQ8E/4ftjlv4W7eH9\n2J4iczvnQiWTOqFQu/Y+4PMUovLrw22GAhVBYR17UyXrO6kFJJB5BqxV+opZ6IPXR99teSi378P9\n4A/HGWCwBn5DJSIiItITN1QiIiIiPXFDJSIiItITN1QiIiIiPVlfUfqrXpXbhXAWQjNm0qXo+gKy\nOZ89m9sV0R5vvwxdbU3He/VqfoG5gEidwrrieZlZF6JEwkzoRaZ0NLAQIeZQUzo9M/z4qHQfl01Z\nRt/W+r7Qs1aSDDOT+BY8W02kvgXH+flRReijUmRCL1TqEF0ywzZhVmkGRDBr8gQExTvxQKkicK2K\nnW9TmFKfa5LjEhiXaWT/po+gsHl+F67HYACMU6B9QXFvJdt3MW7dhcc5wEkKQX7Nv3ORFP4e/owC\n/ZpovOjbyhq5wkzrlaz1DAraDGE0M68zc3ktAIFOrwg8oaif2cexRndjLnEu830625mrnOd8F5Ni\nHfB4pW95P8Jgjkt4925hEAwrBqAvv+DR3D72zPD7r34VERERERkVN1QiIiIiPXFDJSIiItITN1Qi\nIiIiPXFDJSIiItKT9Y3ym0OUX1E7AFEdgSiKy1D2nzyV24zqYJQEIwMAgy5YHqWayR8ROHObTvGE\n4TeslS5gFMzixaHHWQqGMLBiKyLbeHtG/dHm9ViJYljbalF9tbEgtbazzE4tqi9N8WFZpmHEpcWx\nJ0XZCkRQjToYtQhTRozWnmcWAzTJ2ji1aLLblD135fbxZ3ObpWbYD6xntXt3bjMybHIO12O0En0a\nFwZtjiuPYx5E16cgqux5RFYxcpRz7ORJHB+xnMkMnn3+Dny+Uq6kVpqFUXtTaD/HhpFq19E/XJP0\n37x/rTTPdsyF0+j/otQaPs/7MyqedCPtGNW3757cZt8WfYNnrUX1Meyaz8YIxS1bc7tYF1i3gVpj\n5BbL5PkNlYiIiEhP3FCJiIiI9MQNlYiIiEhP3FCJiIiI9GR9RenxAOxa+Qqkwp9+Lrf3VkoRUGg7\nmwvVxiYoyss/z8tRV0ehdFEdBKn/JyfwPPwAy4NQ+EwRJ0szQBRaK89S0zHzOMu1pBkIkan0HlYO\nhYLJmgodNkvVXKuI1Mcrz1aIztl2loXg8b61ZmoUZTUqIvWaQLeYzBCFXmCZi0oZEZaaoICXmtHb\nlTEIo2f5YJwHWCNjleiIybvxeYpnsW4Ci5Ki8gbCZZaLuQwhNgN3usLy4hjXLOYQRc+FA8IaWjiB\n4+irvegbrsmakJlwDtP/LlZK0dD/FlFNlfJO9IG1MkTH0T+830m8Hzlehw/jfhSS436d9p8/mY/1\nHN+tLJFE0Ti5gICtYiwhImdf8PoM9hijKB1jHVh3gbn6kgNxK/gNlYiIiEhP3FCJiIiI9MQNlYiI\niEhP3FCJiIiI9GSdRen7YUP0V4jSKRpH85mMeTeEZxcgAqdID4LSqanzmU3NYS079wo0ghRKT1L0\nSFEkhbxFavaV4cdvDBfV10TpU9DPTs/iAxR9bodglgLdbrZcCuxronR2PjLpTiJz72SRhZhzC9QE\nshyLQhTOTOY1GyLyWntqNvuzdj4pROkjZq0usjyjv/m8G0WUzozLO5i5HNESQWH0ntycpEveV7k/\nxbUN7OE+IU4+k9tHj+Y2s293fSj9J0XWWHMrS/maHpuHv6B/rmXnLzKBMwgJ7aGQmQ6Pc7aWOZxr\ngvfn89Cn0N8Xmc4xlsxOjv5fRtDTsWPDL3/8eG6Pozu2b8/Hq+k8Hofm6ofyrPf79+f2Sx/ExXff\nmduzWDfHMC85Nsy8XgQNwd6BsQ9WLeFeBMcLkXusit9QiYiIiPTEDZWIiIhIT9xQiYiIiPTEDZWI\niIhIT9ZZlE5lKlXelezORZZgZKLdAlHgTogMz0IUCZH11m25KJ06aWoSE+xpiLonocsrhcSV562l\naq+INGs65TFmdkf7C5E5RejMVsvjMx3hIVWNtczbS8wyjIzOF5i1GOczSzFFjjWBayUAoYBjWYjI\n8fw10TvnSi1TetGeyuAzKKAYD05+Pl/l/jWB8W0Lfye9AzYzNPM4YWQNxbQUnSNYg4E7Zx7PbSqV\nP/TBzFx+6khmMwF2V2ddVIKAv6A7GJvKP/D84bxvOCWvYs5RQz529unMnl1AZvD9EBrfe29uV6sH\nYE1wjdaE0tXM7Pg874dM54tn8/5gdQjG7Rw5ktvU2FMzz+Zew5LvzgW+61h5gq+mAwfyiyUGCPDm\nzILPdwn9OQX7DJgq1ineH7EXNkTxfCBF6SIiIiKfGdxQiYiIiPTEDZWIiIhIT9xQiYiIiPTEDZWI\niIhIT9Y59IZlGRi1x4gWUouIQVTatjnYldIpiCTbeSOPSplkFBxbg+Njs/gB0+0X6fQR1lJEnrG/\nhlMNNIOdpliLBu1j1B9t9vfs7No3I4wqm0C4Ua3sQ1EKhSU6AEvT1CJ0Ri0FM0EbfRno61qpl1p7\nRj1Oas8vAzBPg+NKWJqG64DhpIhcK8pv8XhlnFl/5CRLcOTMzOR21+c1tcovXLJL+bNdgfun/dL7\n0Tdd/7HaB4pSXVjT/Dx90DwiMLlmCaP0eP8iMq1SzgnvG0b1nUCpGLo4VgLi64NRfXSx9yAo8s7d\nub3cOZ8RgLwWX60n80o0cee2E/kPiohwTDyOHc+fwru/8Hf0/xxbrgMcP/d8bqNyzqduu/qPRURE\nRORWcUMlIiIi0hM3VCIiIiI9cUMlIiIi0pN1FqUfqxynMBYiwEJoxvNRDoMiQwrdqKRD7YQEodts\nTWTI+81AkMr0+xTWkUJojf6oCKU3bcr7h5rMcZbGoXCa7ePzUbTOWhTd44UoG1DgWStNQwVmVfSe\nf765kqsqKbIcVaM+MZELZtME63SgLzkXWMqleJ7K840qUmcZjqK0TSWioZgrGHuO54aBInGWgiEU\npfPzENsGSmpcOpLbFJWzJMeTH8ntBYiBERgzyfIsw+C9Dh/OzItnc3/FKbNnT25TxF6sEQqRGfRS\nKz9CH7FjHjfE9bfmpcfiMlTdDDzhA7B9VI2zvXyfgN0QiVPoTR33M3i9zuNx2Z2veU1uT2/DgHXf\nh3gW+k++qsjKuVyAP1YR6BcBT/v25TY7hw2gin6cJaH4PkLdpEJVH6viN1QiIiIiPXFDJSIiItIT\nN1QiIiIiPXFDJSIiItKTdRalPwEbQtyieRS2MlM4RJKFaJ2Xx/UpDKaokcI5Ct94nKLKIhM6bLaH\n11+C4JVC36ooffjppdAYokver2g/zx+Sir0mGr+BsS2uhXtRVE0KQX8uUryErr0MuyayLEXpuT01\nlV9g+jpEl8UFKyJxPj/XRk10XpsMRcABRfTMZMys/5UAho3CmaO5TWEys29vgbiVn2egDLN9Q/hd\nCJl5/n6kv/6qN6M9EE4zQ/R5ZGI/+snOv9F2BPFsnWVkBypf7NyRn89U3kUQD2z6o7135zZV1y95\nJLcDfV1wV25OV6ob7Lgfx5/JzQsQuaO/YlsuvJ7dnq95ivwpMmfieC5R+qSX3AufshtKa/qE7vjg\n4glRO+PbMVZ8l3KsCQX8JzEP+S5F3xX+Zxz2+Sdze+4gGoD2cu6tgd9QiYiIiPTEDZWIiIhIT9xQ\niYiIiPTEDZWIiIhIT9ZXlP78+3ObIsOasKxoPtJZr0CkTgEn019T+MvsrDzOz1OkTRVgIfKuXI/t\nZXbwGhAVps2V/XNNJM/nqarcP4eAIHYFIvNlCDqp/69lTq+J0mvxC5MTFBdjLEZN1V6I9muZzisi\ndIqlKUIvjmPtpHWOf/lMwczjVApTuD2FzObFmofPopiXwm5miGb27T0QVm+h+BbjFAiWWPiz3H7P\nez71zzP1IkHwAAAgAElEQVRP5gL7Y8jMzTXANbR/fy7S3gGNdtGXnMPsu6LyBNbQJYzVltfihujL\novIGxiIglC7Ox/0XcD6F1ksYezzfVt5+83DR+rCYoIiIxXP5+Uc+9Gx+PejGu/EWLIRADfmrXpWP\n7cxMbt+BoX2mEpux41jetnJd8F2OvcSlc8OPF1Vb0IBbfPd+Dr8BRURERG4P3FCJiIiI9MQNlYiI\niEhP3FCJiIiI9MQNlYiIiEhP1jf05k/em9u1yCIq+xnVwbCSWtQcI2pqoVtsX61cRy3qjzAMhqVz\n2L6aTWpReUXk14ilZWpRft321dra91kq8PKVyjRFWYfaVCEc+mu43+TIUXyVMkBFmSM0gGPJ81lq\nobYWJxktRrsy929XTiJqj+PE6KS9iLq7jhJL9CEMN92D8iAcR5Rzia2MXEN740xu/tkHcvtP/iQz\nP/LuFyL73o8g7dOnc5uRYK95TW53AgYjolyDX/M1hzKba4aRuXc8jGdl37wJ9n0sJ4IyQYzSY1me\nQJmfOJKbH/9Ibv/BuzJz+Vz+AJPz+Zq5dgXlXKaGlz6jz2J1F0bisTTNR5/K7SdQGe5I598sEsei\nbx/6UG6/7nW5fZDBpoClwHbwXV2U3gKMhmUE5taX4/h9sD82/Ppr4DdUIiIiIj1xQyUiIiLSEzdU\nIiIiIj1xQyUiIiLSk/UVpVO5RtH39u2j2RSpU7hG4S/TyV+FyJAqSVITRtdKJVTbU1FGs720a0Jn\n9k8hqq/YFEaPIkq/jrZuYimAEakJ7NHWUYeOjCpKJ2M8vxYQwLVRiMa3DD9eKy1DUXq1lAzWXlGW\ng4JfCnw3Bit/8O8ze+z1X5yfQBE6xfxUDhNOtLsO5HbDkkXwWR//89xmuRP4jDNv/8PMPnw4P72r\nUf/nZ/Njr8rN2IlHOwjR+vHjuc0l8O535/b99+c23ePE03kpHE7hVJQP+VPYlFZzjvPzlVIzUIFf\nPJn7b4r2l0/nZX8Kn4I1e+LpvMwQgwQYz7ATpX26pWQiytJBT/P2nX8fwjHaT7Mq0OO5zVf3q1+f\nB60883Q+uJcX8wuyCF0souQS19nWOXyA/umVsOHvzv2fvOOq+A2ViIiISE/cUImIiIj0xA2ViIiI\nSE/cUImIiIj0ZF1F6RSeTU3l9vbt5zN7fCdUkFTZUYVIoW1NJM6sxWQT8sPWMrNTIMr7835LENZR\naFfYUBWOmvm9yPReya5dO14TqQ9Tbt+o9X0tU3gtS31uj03lU39i4jrs/OMcyoTmjGMlUXDKrMTT\nsIsTKDIvMpVDNFlUEaBIHdevZUYfo+yTonMKdin6RHuLLNMbgzF6UM7Tfffk9sKJ3GYgCas5bMa6\nOIPPcxwfe19uP5mL0p8/lCvDxzHPH4d4mKL0X+u4YGjKYx42c+XTHXHKHoKymWuOa/JVUMGfzDXp\nsXU7xuI4+u5eZMeexPFgwMAu2Hj/kIcfyttz73/KjyMQ5/xT+f3nuMSQJf/kH+eD8+ST+emMYXrw\nweH2G96Q20++M7ff3vn3I2ga4gUCly7Gmm37yIfyd//evflxxm5Mn0bG/1d9QW5Tkb8VwSJFCwnS\nxu9kFv3V8RsqERERkZ64oRIRERHpiRsqERERkZ64oRIRERHpybqK0hcWcptC3iLT65U8k+xWirCp\nfGM2aKbiJbXM4lVhNEXaFSEu78fnoeiconSI2K8hczCbO4bmVbOLF8pqZteu2EVm9Y5dCxAg1Uzo\nzDTOzODDM4/PzORzq5Ykn83l0FMDzqkZ2yDirlYF4Pk7cD1IgClir4rOmTmYovLiAWDXMhFz8m0Q\n9iAT+vshCmfgDOcl5zV9AIXUXwJx7RLOR/WJd/1aHtiD5N2FsJvCZPJQJ5s2Z8BB2PswhV7zmtw+\njczpXHMvxQWnK4EedJfFoiRHjuT2A7hBIatntn8eh3+exhqmCB5OZI5Z7PfvH3o+n59CbmaSZyZ0\nnk+R+pfdm9vHO6nTqZdnz33HV+b2PXiUjyMNO+flQ6/M/fncI5DBn4Qo/SwC1ug/iwADnM+xiyO5\nWQuaGuA3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9WdcoP6afZ+QUy3sUZR4i\nDwuZvZor99MUojyGlT5ZrQE1isgzRrUhCrC4X5PbiPBpruRhGuwvRnEQ9tfsZpaiYSkdRsYhEqxW\nzqQWBTisP9gXfLiirA0jLIeXmikiFhH1Nz6T9/0MQo5qAaIMKCpKy1Sj+GAzLJB2rTTNLCKQEqP2\nalF+tag+RjjVjm/M0jOxe3duX0cpGa4plpbhOO7Oy4sUpWu2IvTt6d/PzI+9f3hUH5fsQVwuvfIV\nmf3Kcx/O7CeeeOHfexE49QDqj9TWzL2IIptH7Rq6APq/ydflIYr3LCBKjn2LUjBFPZNTqF2za09u\nBzqzeH0yEgw+iHOFg7P37txm2CI6iEGAjOK7hCh5uojjqB3EqMo3IuKzW16LZX5OI2iOY7cV9+a8\nK6Kg51Hm535MrkfyeVo8PDsnEBVYFEpiWSGMxcnfzm1MpZv4DZWIiIhIT9xQiYiIiPTEDZWIiIhI\nT9xQiYiIiPRkXUXpNVZQimAZosTFSvWSsaVcGTeG81dwPu/H69Wro1yBPfx8wtILFPbVyqFQxL8F\nAtSmEP2PWHqG5VtqwmgKw7v3Y2dSzHtj8/DjbGu1NA3EwYVoPRdpT9/ISxFMXc/by74uVOnsC6ou\nCxE6SrdQVF4t84PnSRSBc6nzOG2W7WBxCYrYaVOVv0FLzzBYYtTgA9bX4rwhl47kNsqnUOxLe2wK\n84DiX5TwuOPBXLz7JV/yQr0YVm6h5prVQnYcwByHQv6OPVjjhUPEcfYdG7AXZYFqDpki8F2c8xSp\nU0lNoNSevyO3WWaIc4nPC1X+5HzuI/buzctnUTjO9wF55mhu06V1py6n8X68m/fty+25vbl/mHsl\nROGsg8Oxo/9mANTDD+c2x3ILS2M9CxvBIJH3ZRHNsQZ+QyUiIiLSEzdUIiIiIj1xQyUiIiLSEzdU\nIiIiIj1ZV1E6dV7UDDLTN3XMtUzhvF6hgx5RBH4NNkXstfsXQuYKFJETXm8aGspx6rrR3iJ3dSHc\nphCQmdIr9hiFyN3M7MgqXBus2vFRs9xTtM5nvZGLHtMNtLcmkqyJ0ilC52IoMsNXnv8qMnDz+RiR\nUSx9CnDZnyP2b0Gqn3I7wuABZutm9uuxA7m9ldm3EVxw8XBun0TG5925qHzsK96YH6fwmfOQ8+oC\nxLgQ937R17/Qvi86jbbwWgxqoX/gnKWDuo41R6Ey+5aVHx5EOuulPNAkTp/ObSr4i8CK7ZXjuD49\n7N3Ies/s3rz/ZqjEi8CUvH8fmMqfZ9vjuU2ROru79n7tuigO7V3QlO/bj7mwc2duY97GHgj+OZc4\nV67i3XIX+pY0eNjCHdG/QdROkfsa+A2ViIiISE/cUImIiIj0xA2ViIiISE/cUImIiIj0ZF1F6dTt\n1hLZ1nS5SCRb1S0vQ3THTOyXYV8bMXM5Yftryb0pOqeumJlseZwi+qpuu2gQRJUUSlPIPQZBLQW2\nGRAZ1ga/NpjMpF5TXNZE70UmdjwrBaKFKB1iZQpy2Xe1yU1BLZ/vCq53Bf3L9m1BfxWiTI4Hxr4Y\nW4raef0N+rvb/v25fRgico7T2KO4AITJVMtuRT9yXjEl9UmI4pcgSuc8uNHk9gSE2ttwv26K7Ede\nnh/js56D4P7ChRhKERQDB0cROp+dz0Z/VRHcF1njAy+AgtqaQXsYxbR9R25TmE0fxLFkfyOw5S5m\nWo/zmcX3JW1WEum+/9g0BlBdu5L/YJz+rahUAf/B85mafRez1jNggGVBGPzByg4fy80/f29usyzA\nGmxQLyciIiLy2cMNlYiIiEhP3FCJiIiI9MQNlYiIiEhP3FCJiIiI9GRdo/wo3GdgE6MMGElQVCqo\n2EylX4tyoM3P064FjtUCyWo2g154PT5vrXTNyBQNZPEa7s+H7dcre3mWnWDESlGKgIOLiBieX4v6\nY4QQn32KUSosC4HjHDxSPM/y6ufdpDbZiiga2CxBshMRUFsqdZ2KwkW1ucCQWEblbBBmET00uRsn\n1H6HfR42ypsk2JOIwruH90Nk3WVEizLyjpFyw6JvOce4RmsOkOVIauWWOGfn53Ob5ZvGMRZLiOS6\n/wHcv/Y6ZKQY+5pRdSz/hDl/7725zbF43Rfn9hMfzu3TZ3Kb/XXvyzLzrgmUskHU4LVz+dzg+69L\n7V00vhPzkv6H64RRfkwBUISo06a/wtwq/A/BwzJCdRH+cQ38hkpERESkJ26oRERERHrihkpERESk\nJ26oRERERHqyrqJ0ahJrovKaaLwmauf1WJqldpy651p1E1LTPLLUzKiDw8/T7k1NyF0IBWmvrPHv\nKEXYtYiCQqQ+os1SNTWKMjyMGOBx2EWpHFz/Op6fonqWkqmJ7KkSpWieESHzEGHuxfXvwHgV1CYb\nS9XcvepZtx27Ua6E5VACIvCguJXBClwzc7BZMoMlgRjMgHk4zfMrcN51xbpck1wDLLfEOVgL9KAP\n4AuDc34cwuam4lO4BgpQBigglC48NBc1xwLPN4b+2U4HjvMPHsztk6fQnEpUUxGIkvfn+LZ8bo4v\nLeXnd0X/HCv2JceeAQRcNwxw4PWKIB08S9H39EccK4rYK2WIHnwobgW/oRIRERHpiRsqERERkZ64\noRIRERHpiRsqERERkZ6sqyh9fD4XXI4XKvRcmDuxlIsQqbstNIp4ums4f6ySyJfHa6LyUTOlj0OP\nOgmb2WhrNp+39nylUJoq/Yqwm1EB7KCxhjd84Z/XmNm8IsqmKLEQbVfOHzWCYNQ097XJWOtbZC0u\nsiZfOJ/bi7mIcuXK8EzAY1NoLwW+e+7KbY4Hn2cXxc0U8LJ/kcV6o0DhLrNbr6AfxyAkLjLGU9TO\n8wmDBeikmDEa83SaGa0hHGeG6O48XoLgfgrPwr6pBbUUgR14FgqZt6DtFOh/4LHcrmWBH8Pxoi9p\nM9Ci9jplQAHWfOJYoX9qQu/jzw6/fa20BrOXb0dARDfQhpnM+Vm2lYL4WoAC28Z5WojQGdxRqdSw\nfDi3J9Fe+sdtvP/q+A2ViIiISE/cUImIiIj0xA2ViIiISE/cUImIiIj0ZF1F6bHnztxm5l2IGich\n1N20CaJoUIiwK9R0yBSB13TOo15vDKNRE6lPTQ23eX61P25A4EphMkWoFJESHu92EAXuvHYhUmem\ncGY+H1F0XqM2eKQQoV8bfpyC3XMQnZ/OxcjnT+fPdw6JzS8i0W+D201N5Z+fnz+Z2TsogqeovzZ5\n5+hKGJDALNMbBM67sf25fe0Ijp/GBZjxmf2IYIHg5zGPCjhvKaTGmk9Ys8W4d49TZA02QyS+CBH2\n3r25XZTOQNu2UMAPkfrzT+Y2A1X2Y2w4dis4fwxrMvi+YRZ8wr5mtu8amAsJ78sDB4Z//OzZ3KYQ\nvAjkgc+iULwr6ufLZhai7cLfVfqKAQNFwAL8TaIIne+ik7CxTiYZJIN5vutRHB8e9LPGVURERERk\nVNxQiYiIiPTEDZWIiIhIT9xQiYiIiPTEDZWIiIhIT9Y5yg8RLIzyQ3kNRimMT+ShTndM5FEZEwhc\nqkXJsZIKm0O7VkmBMGiiqNQCm6VkilIzldI1k3i+sYlK5Fql9E8xHsXnEZXDKJ9h51YiPOulZBhV\nBmpRe0VpGZbBwLNsgs37M2KG7b+Akh6I6juzkD/fiYX89FMIYmGQXlGGCXODAUB3L+WTf18cyU8o\nQkoRwcT+2cLFUItGu02Z3zX8+PiBygWwxgLlPorIMpZHYeRYrRwK74dxZTTTFqzT7rplOSSuaUJ/\nT3ucbaHNyC4sgpOwdyMqjpOeDpXlU6bhk+Io7IOwGbHJOQ//GSdg8/sNXg9jO3cgt/dgbBlZxyhH\n+qSF53J7WHksRl2zFA39A6G/LSIM4X/5LprCWCauC0ZwYizHULaniOJ7APb74lbwGyoRERGRnrih\nEhEREemJGyoRERGRnrihEhEREenJ+orSWXqAIjmKoJmensI32FtnclHe7GJuU4Q+qih91Gonhe65\nIlIf1abGknbxAcIHWoIQcDOE1LXzWXqm2wFFqRaK1GsidNb5SWvfK6IUTd+olM2p9RXL9FDTOEzQ\nGVHUjrl4Nr8A9bUnjuf2AkTqLEXD7qIo/RKWFrtzeipfDHfMHstPmIGAl2Ut9uRmbEFpio3CJHxY\noHxKUXLnDGyKxEctT0LxL50QJybnda2kxpDfubnGZjDJ5u/IbZYnKeCa3J2by0/lNgI5quWhzqLv\nGVAwzdI2tNnXLAPE52N7YDcY+8Sx5/0rY7tt23CbPohrlqL1kxCpd4Xj9Ken0Re1IBaOFdtSODT4\n023oiy2Y19fwMi8CHij4RwAD+34ZDnkNzb3fUImIiIj0xA2ViIiISE/cUImIiIj0xA2ViIiISE/W\nOVM6lKu1TOkUwtJmtlakj04QpU8jG/c0srE2V/L2sHnXmIy1pu8EzIw+NqJoPW2uZfvmBSpCbGar\nZabd4nyIKCcoYuf9O0LGmoC0JlqvwWetRQww03lN5F60D4PPvlzMBf0rF/K+pQbzDBIBU/NJ0fo5\nLBXmeGZ8Aucqh4pLadu2vAHjtczI7J9ZpHJHkuzbluefzu0dL8MJD8NGNEF8HDZdMiZGIUxmhmj4\nxOL8mRgOM7NDzDvXEe/OUTTNNY3PNpikqZJN+9qh3D5yJLfpf1hdgWuSPmSe2bIr/rEYC/Y9n5+Z\n1SHy5qKHj4h7eL0duXkNToLlEvh+LLKRjw0/zkzzvH4XBiAxAIECeTocHufYzmDe8tmYCZ0UmdL5\nLPfBfnb49dbAb6hEREREeuKGSkRERKQnbqhEREREeuKGSkRERKQn6ytKn0Mm3QaiOGZGL2wI1Qol\n7VxuU/THzLEQwSeI1Cdx/uSo2bzJqCJynl/YEFLX7ke7yO5dEYYvQdTI1Oxsf1e4yGfdhGtVReto\nS7VvKnYh3gUc2+I42nNl+NyivvM87Iuwef4F6HspsaS0mKL0TdDDcilRBE/7ru3IUk2RKKFIdaOI\n0guYCZ1CZmT/LlwwRxLZvAMZ6wthNKEInTbnNVPcsz1d4TefDbOuEKHDH1xD0AtF5xSZXzif2wwk\nYRANs2/vRBZ7BlIEA18Ow4aPiodgoz+u4fOHYbM0B30Mg7IOHMDn8f5h1NRZiNZr2crZn/x813/z\n3UpROv0B3030B3yX8ln4rHSI2xkgAYpKDfT3CBgIvAv5bjRTuoiIiMhnBjdUIiIiIj1xQyUiIiLS\nEzdUIiIiIj1xQyUiIiLSk/WN8gtECiREOWyBlJ5RG7QZBbiIqL8lpLdn1N8Ffh5RFlOI3GJUCVP3\njxzlhyiSUUvHkKI8SqV9tUg2Rq7V2seov24kyMTk2sdWu3at9Eutr0nx+aZyvGJXymAsL+Z9ewkB\nTJcw1RjgxIAgFlqo2YRRgLwfpz6rZMyfy+f+OCOCOH6M0tko7GD5EvYswiOL6CLa8FlxAjYiowsX\nzt+RGZlWK02DiVBE8nVnFj/L2lhY04ziXsCznUWE5ALK9NCfMNKLkcKM+qaP4ee5prkI7nwgt4uI\nS0Sa1UrlHP1kbu+7Z3h7eD2G3nLNMYqd/rsWOcfx2dmZeyzbw9IxtXcFo/L47uD1tiFKj2PLqMLE\ndcR1wncpIzpRNolzYY2gZr+hEhEREemJGyoRERGRnrihEhEREemJGyoRERGRnqyzKB3CL6Z7535v\nDEKyOYgUp3A9CtUoQmcq/mrpF5ZHQTp9ivwoAi/Kn9RE6KOWY6mUimG5ForQKapn+0khqh9SaiYi\nDyIYVURefXaIytl2Piv7ZtQyQpVSM9eW8s9T00gReiE6h6q81l0sOlSTKtd+kyqmBtpDEfscBa0U\nELN/NwrL6IhJirgpSme4AEcK5VGKGhcskcHzWT6FJTkuVWwKrXG/lc48r01KippJUcoKQuYF3JvC\nZN5/Fv6f/piRFZyzFHmzVA399a67c7sQ8IPTEN0zkGMvrkdh9hNP5PbRZ4bfj2sO97uGqXgMQ8/A\nmTt2vjCe8/P52I7vpsi8EpTCMjp8V/BdxWfhu4YOaQpjO8d1gr5lca4Gc+HYs7l9Z6yK31CJiIiI\n9MQNlYiIiEhP3FCJiIiI9MQNlYiIiEhP1lmUzv0cs5cyyy9tNH+ykqm7JvKuZcMuMo1T9A1hNIV5\nZNRM6TUKIXVFmE0ROoR/zdX8fHYHm58mKkLu7gcKgX5lb8++qI0NVd4URTKTb6Uv2HcUdC7DvlzJ\nPE6bzV2p6H0xs4vwDq4knj+D7mY8xzg+UFsqZf+jfxnAsVGgDygypdPmmsZEKDKV8/OnYEN8W4w8\nRfC8H4TRK7Ap3B4luKDmvyhCPwkROu/NOUbROO83i6AkTuKnnsrto0dzm++P+V2wkS2cInNmNqfq\nm5EefH4uMojmLx/OheF8nFFfH9Ts00edOrn2tefn8w8Xen50/a6rH81/wKon7EtekPDdy0zsFL1P\nU5SOzOrnkDmdVVjWwG+oRERERHrihkpERESkJ26oRERERHrihkpERESkJ+ssSie1/R0Flzwfj5Mg\n8oburBCyUZhMIfMERJQTtWzcsAmVfaMKtWvZv4ts4cOzz65cya9XSxbO5k1E/oHEE653xq9oey1g\nYMQs7xRFUwC7lGeIXl7KH4560VFtisxHFqXj8dgdU1SZU3sMeD41m9R88vjMDK5HFXytqsBGZRrC\n50BHBX0A1fyo3lAAkXoD5TDmcWyheJeidayT5fO5zYlJKB7uwjVJITBVz5z0nENcw/RnrIRxGkJi\nCpvh/5577JOZTf9216M78h+w/U99ZPhxiszRnjNH8rG/g5nlKXpH39Mn0AfVNPZc03x++oDucNWG\nklOBSd9PHMkbe9cjeDnz3ch5N4EKAsyUXjhozJ1prkt8np370CvjVvAbKhEREZGeuKESERER6Ykb\nKhEREZGeuKESERER6YkbKhEREZGefI5F+RHu92o2I4sQtpAQGcAolKo9Mfz4dVy/FqVXRPVVIqOK\nqD1GujHUDFGKiAhiVN/lSqQZGasEKY4X5WE6UTZF1B5LeFTC1qpRfXnUxrUL+cMxmOkSgjyW0Rfs\nG5aeGTXqj0EptDm0RUQlp2LFnkUQDSN4GFB05+7hx6e34wYM42HZD0blbBgOwOa8pQ+olW45N/ww\no/oKuI4uDz/OiVfzWd3781zOAa5/Rm7VQsH278/tkyi7w6i4YpFgzp3OP8/bcc3EIy/P7QcfyG1G\nnh0/jvvlpWLi6acz8+TJGGrv2ZN/nt23dT5v8MGD+dzbgjXPNU2fVIvc65aj2oFgUvrLIoATbee7\noygzxMFhySOW8WFpmCmMPR0y18XzCIksIvS3xq3gN1QiIiIiPXFDJSIiItITN1QiIiIiPXFDJSIi\nItKT20yUXjtOIRlF3hCRs9QBRYy0a0I3ijCvjrhf5ef7lluBTRF6LVt/rdQMucHZxAsMO1arc0NB\nfkVwf/lCfj1qHmmPKlIftRTNMuyaqP1aJSCAAlqWgplGWYk7ICJlqZndEKzu2YPrzUNkXq1VUykV\nsWF4FewjsCF2jV2wKXaFkJn1siiE5ppfwUQaw0RpKBSHj2Q5Lq7L7jiz7A4nNdt2AWV2uKYpQj94\nMLd/+7cy8/KxfM1zjjbHc9F6gv+aPoBJ/zBE6IXIHn1DLqCMD/3zLMc674+Fhfwo1zSHYuvOfCx3\nHcyvv2sPAhgK1T04lDs5+qTu+4L+kqJzVv2hO+ezXVvKH26cAn++fFh2iDfceQduCP9zCgENVORz\n7hUlpVbHb6hEREREeuKGSkRERKQnbqhEREREeuKGSkRERKQn6yxK/3TffsTM6lTS0S7ST1OkXsnm\nTSFdITqn8Bqfp2hzxOzgK0tXhx0ustkWyWEBu2dkus9bE6EXAn88O0ToFElSY0j7YkWkzr6iSH1U\nUTmzztcen7DvRxWhM9M5Ree0x/dULkDRJzOjUzRK8fOGAROnWMQJNvotzsCGuL/IdA7okyhCZyDO\ndSx6jhMzUm9C+7vVHC5D9FxbdFxkRRQMgnC2YQ7en2cqv/Dke/PjkbeH7pf+bm4v+mYGi2jfPbnN\n56GK/OzzuX34cG6jQXy9MFM6fUKhk6ZonmuUQQDbIIqHkHvbtryDmOi9W22B/ov+kl1Ff8VrM8Zl\n4no+N6Y3P5efwCAYPhtvyPcHO58PwM4fqzjoAX5DJSIiItITN1QiIiIiPXFDJSIiItITN1QiIiIi\nPVlnUXotezKFYLSZuXbE/SFT51I4OwHRIrOt1lKJU0lcpNOGAPQGhHNFZnRmB+8nQmf2bjJW6U4+\nbi2TeiY6vc6TmRU+74tmKW/8qCL0mn0eetnL6LtaVnn2ZSFCj9HgwqTGkvYkNJazSLBdy4xeiND3\n3DX8A4UoFAJZrhVWJdgw8LngE5pTuZ0ewvl3V65/JDfHIGLfhJnV0Gdg4nLhMPClFhzSrVBAkXlR\nqQH+itmsOUmPHMntBQiR9+V9dee9uRD5xKFchE2NNv3fpqeezeytDKygSL4Q0eP9w77i9fD89CnF\nmsSa5utg5WR+vbEiqAprkE4PF+Rw8PRu/3EaETaFU4WacI5NkdSdc2sRN6CDq/kjzkW+64sILAQc\nrIHfUImIiIj0xA2ViIiISE/cUImIiIj0xA2ViIiISE/cUImIiIj0ZJ2j/BBWUETtMaqPYWmIUKnG\nUo1YioZREizTUFyeYW+VshFFhA2jSlhqJo+aYeQbo0ZosxxKU8mmv6lSmadmDw37K8ruIKrvSj7W\njCphVF7NrkX1sRQN++4yIyQrUXyIb6rObPYUgvhibMSyQIwCZATP5DaE0TBKpig1s2P4+Yyq4VoZ\nW2dX8xmDpWR25WbCRAqUI4lXwWbpGX4e5UQSfMw1RC9x4TC6qVZPqihv1bF5rYUTuc05gHJRMTOd\n2wYGUdMAACAASURBVB/6UG6zvBEX8Xx+fOtC3jdPPTX841wjr952KP/BItrLOc9FRXg+assMi6KL\nqAeNF4Fqi/n153ZjjSNKcRn3I2x+NwizFuA+ib5lxDjPp79lEPHlxfyG05swNrwgx4YR8rxB0SBc\nf8utfffkN1QiIiIiPXFDJSIiItITN1QiIiIiPXFDJSIiItKTdVaKzsGuidBr+z+K1MdWPesFUm6y\nPEZRagai8RqF8LqiLC7KPFAQmgvlKGKkXVRKGLFSDtP/18qfpImKqD9rDEvN5H3DtvPZWBqG9iVo\ncQuReaUsD0XoFPTXwiNoc+ZQpM6FyJnCAIK+YxczMzgBAmEKhme3Dre3ci3j+uvtaj5jIJohDsK+\nDzZK0RSic4rS0c/xAOyjubkJSmcuek4UHqdSuih31RWlowwOoWqaQITOQJTEe9MfYg7O7swn/dWn\nhge28NE/+IHcPnA2L02zYx/65k1vyu1jx3L76vD7c01yzW6Brpo6a9q8/dGj+f2pw6bPq2nsu1On\n9iqjCJ3+dwV9z2ene2LbCwe4G8Eg7OwdOP4cOmuJpW0YQIGxX6NilN9QiYiIiPTEDZWIiIhIT9xQ\niYiIiPTEDZWIiIhIT9ZZKYrsyoUUt5JpvDi/tj+sZEofhzKOqsUblBKDmgj9SqV9VGIjU/rKlfx6\nFBUu9xShUyRJYeDkDC5AIfMERP3DMqUzC3yhcswbX+taPjtF5LR5vVHhkzH8YcTwheJ6XJijZqln\nYvJiKIqs/pW5WUwePjFtPgHmxoaF6lkGZrAfCrVt5XzOLFx/DGuS1RgYbECfw/NrGaRHgSJzUAS1\nMNP66dO4HkM/cpi8n49K/0af8thjub33WP7sr7jxrqEXOLOQ22w+hdj059c4NGgfEq8XovRLjHcA\n/Dxh/3V9DEXitWuROVyb7x4K8ie34wRm0Z+H6LzwT6xCgs7lvL7OoCnMNUXpIiIiIp8Z3FCJiIiI\n9MQNlYiIiEhP3FCJiIiI9GSdRelMzTpctFjmn2bzkfm8ul+k4LOSvrUGVYNUClPgWSitKZzL+6PQ\nrMMeNZs2RZnMlDs2W1Gp10TppCvqZ9Zj9MXmzXlf1jTUzMxLe3xEUfc0Hn0Mfb2ZmdOZkDo3ixoA\nhBLKabS/CBCoZFnm8yYuhZrKn3YlYCJmYKdRA0ZuV6j8fQ42M6lT1M3AG/pEBu7QJ0GMG8jozDXK\ncee48nwen59/4d8LeFZmlz6eZxovsuvfiyzyCydyGz7i4pE88zpF3hR1U6Q9jTVUC9xgVz39dG4v\nLuY35BpktYVl2DUhN4XaTGLP5yXPI1E9q0fUKmns3JnbOzo2Rem0OTa8Nv3R7t25XWRtpwPcB1X4\nLAIYCuBhGfBwFBUH+C6+UUkjP2CjejkRERGRzxpuqERERER64oZKREREpCduqERERER64oZKRERE\npCfrHOVXi4Vi1F/f/V+l9Azbw6BBBtjcQCTABMpAbK5FvVUirRCGwcO18ikjR/VtRxQOaw8wkoIR\nQUW6f9CNnFga3jdjSPU/tZT3BSNgajYjWliKhhE+tfNXKkFxRdWiEceKUXws1cCoGo4ln59Rf0UZ\nJZZWuIK1t4RotsWLuc0Izy1cW8PLhNy+IJypiNLDRCqiAhGKVUTtEfYr1mBgDe/A9U4hkm7bXG5z\n3OkDuguFoVwIQzuFKLZNp/M5c8fin+cnINTrk4/lFyjcEbqaa/jgwdzmGqut2X37Rvs8I9eOH89t\nRrIVlckQtUcfxO4e1eeRWike9seWznFGUfOzjHjkvbbgfI4tI9YTo/LufyC36RC33JnbXDe1Ulss\nRXOLtcr8hkpERESkJ26oRERERHrihkpERESkJ26oRERERHqyzqJ0lqegcJXHKQy7NaHY2nA/WRGR\nFyJ11huBoLNaegbCYIrcIYSjLo6XoxCQdlWEzloDO3fgAjh/hqJ09B+fpyt4nYKAnw8DxebslVy8\nSwFnTdBJAShvx8/z/BX0PUXppKZhLErnYKpQtMmxq5V+oMiTIvfYhMnMB6YocxHjRRF6MX4M2MD5\n1FLfrlz8o9zeSpE5S2KwlAz6qQjEQb8XLpulbDBx2NGcKONoX1GCaEgwQcUfTEzkIvSFhfx0Vvs4\ncCAXob/kQH6cpWQuQ99P98VHpU/gmv7E4dymqPzlj+T2M2j/44/nNkXiXJP0ERdRGuYa2nsBVYz4\nvPv353Yt0Iaf3wXRPH1Qtz/ZFk4bPjvbwr4Yn8nn9bWl/ILjvAADpLZgLhYOhu8ilHziA5EL54cf\nH+A3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0pN1FqVTCEalL7MKU4AJYVkhaq9lZ67tJylS\nr6jCmSm8lo2VwuDi+CaY+f2pea9lRh/bBiEfVYm7dw0/TiUhs9cWonv0V1fofIECdpwLBWVCBufZ\nK/lcoKicmc15efYVBfw8nwLWUWFmYd6/lvWYovStGApmUufxQkDMLPc1UTkzaC9yLYLPF1H6Bz6Y\n2w/CZ22CT9j1jbgAfcQZ2HthU6ROH8VM7VjD4/w8AmO2w6dSvNtd85VM6XNQKi8tnYWdf/xZiMDp\nv5jtfxxznMLos4gPmMb1atUO6P7wePHgg7nN7qBNkTt9Fs9fRP+cys3YjvbUnp+Z2unOXwJRexGf\n0LErMUSFP6U/m5+PoYxvx7uF71ZWJSnWEYNB4K+OHMltPgAdNCfrGvgNlYiIiEhP3FCJiIiI9MQN\nlYiIiEhP3FCJiIiI9GSdRelQ4RUicmYNpgi9dpxZiEdVFlcyqSdcn0o9is4pUC1E7bg+hHETExBq\n4+OTEAKOz+IHTB08fwdsKAXnIVLn50fMdp5l266du0QxbJ5GeGrqEuz89CIrciVT+ji6alQomB01\niz0FuLSLzOezuCFV6wwY4FixAcXcw1zl+FCsTGoiz7uGf/y2gcripz6a2wcO4ANIrx0vh30RNn0c\nXTajD+hTeZw+DYFBtcCSrr337vwY1yz8y13b8lTkdyFV+uKF4ZUh7txf8WfMdr1vX27fe29uY45+\n4cJz+fGr6HsuQqyZB0+/N7OZ2b3WtQcP5jYzpz8PkTmvT5/HqVdMxQrDCn2w6ynYX0ZbpuGf53ai\nM2pBMrxhAYMx8PlrJ3KbDSb0X4wYWAO/oRIRERHpiRsqERERkZ64oRIRERHpiRsqERERkZ64oRIR\nERHpyTpH+S3AZhQeQgWqpWX4edq1/SOP16ICGcXHKL9KvZHacUSRMMqPp49N4QeMStmG8iOMnNiJ\nqD/WXuD5qVY/BOPTfd6rODaBCB2WKqmU8al1/Vil1MtEZahr12OEZa30AqP4GKSXOFa1seQFalEz\nhCFHNYrSNIjwusEIWEQNbhSe+khuM1TryT/P7b0oJTOOyLPCBzEaiaVmeD5L1SA0rIiEho9l6DCj\nRbvlo5ZQzoP+grVPeBzlkGYZVcfPM6qQPoJtZSktrglGcu27Z/j1uYbgL+/DnL+P5U1Yvon3n8nb\nt3wsjyxjOa2PPpXbrI5SK0XG4zUX0H18BlSya7ZUopaLsWJfs3Gsm8Mo5OANwGkU7uFYcO5hbJrT\n+Vxcq2ic31CJiIiI9MQNlYiIiEhP3FCJiIiI9MQNlYiIiEhP1lmU/izsmqh8VPh4FLLVHp/7zcr+\ns1ZaplpqBp+HUC9N5UrnMaoIKbqk8I/C5VkKm3E+hdCJZSxQzqQAQr+JTpmOQlQIKHpGXQWWWajZ\nTWUqUQNZK+vzaRedFwEClYAA2rwBG0iKDsNYjSjajBvN8M9vUJ55PBeN33P9Y/kJnOdU8/5lltTA\nuMdDsKE8LnwSS3BgnIKBJJwnWOOFy+yM6+kzaAqkunzWw3npmQLOeZayOVQp6/P447ldKeVVBFLc\ne19uUyjNMkMPP5zbbD9Ld1GkvojaMvC3N47movTZfflceWRzPvdYigaVfYrjdBnUfZPu64ufpTuh\n/+SrpFgXe1CLCgL9oozQVjYWDpglnFhqZrFyHAr/tPnWvnvyGyoRERGRnrihEhEREemJGyoRERGR\nnrihEhEREenJ+orSzz832vkUPVJkOAGRdKF7rmVrHjWT+oj7Uba/mim98nwUpVNEWdiTox0fo+ic\nNgWuVH4zk32HItM2RMwUDULgSg1hRVNYdFWt66cqInSKzqcpQt+GG9RE5xSwzs/nNrM+8/NbIHIv\nMmqjA1bQ3xQQF/b53GYH17JAj5qJ/TbhAx/I7StX8nl7LxKh3zidT9Sxfb+Xn/ClX407MFN6bU0S\nzKM4uupZL8CM05j4mztC6eMIKirmTN4Xi8fyZ1mGxnvTpvw4L/eSA2ja0Wcy88SRXBl94UJuc81z\nim56PM9qzzXO83e9P09VPg1dNKf8Mgt/gHH4oEOHcnv7ybx/GAgzCZs6bvowCsnpUsZx/lin/3hv\n+t8iXoqacQ4GFfF79sCGaD0QQFW8i+GPGBDBgAqo7JeP55nRmaWeoR9rtUJERERERsQNlYiIiEhP\n3FCJiIiI9MQNlYiIiEhP1leUvrCQ2zWlMEXUzAxOpivZoquZ1AmFtZVM6DVGzaS+CSLv2udrVIXC\nTcWuZbaHkq+bbbsQnUP0DNHgmZP5tU+ezE+nKJJJjdk1NZE5GaNoHSJLZg4uUgNTlE4ROkWYe/fm\n9i4cD2YKpiidYmXMnbFLub0jF2HG1KncZkAFM6NT4cq5dX1IgMJtzIefyG3OK7qwXRi22fe/P//B\no4/m9jTFuMysznFmZnSK2u+onI/s3VzT3WAEjvHpPLM3M4HP7snn6Cz9OTprB/37PNuec9dELjye\nOpw/+yXEUdyFJXX8eG5ThM4pfgaPy/NP4PV2B0Tf9Bk1l8Hj9FkUpReVMpgZnhe8mq/R5bO5j8iu\nD4e6Y08+ds2VvLPSDBpXq/Sw7+7cHoPCvvB/mOcrzIyOec3OO537O2aVf897cvvbfzpWxW+oRERE\nRHrihkpERESkJ26oRERERHrihkpERESkJ26oRERERHryuRXltxlRdozymKlE9TFqpICPyyjAUbuj\nUkuAMDKKUTKjlueofZ5hJ4zyYLmQJUR+zSIsZrJSzqSw8fluLQmG5SGq7/LJPAqQETOcOrwcH70W\n1cdoLHblWCUAtQj7Y4QNI2qK0jOIYCqi+hjlcifsWvQXo+wQZcnzudS24fNLmEucOyz9wAHZIJzH\nYzE6iMGbrCjUnM0nbkI5lXjgAO7IgWEJDvYzJ+ocbIxT4RMR/dldGJwDjNxiZNVeRCzS/0xhDtZC\nb1kq6+DBzNzxSN43O87iWWbz4/cwjO/s87ldKYdFp7FtW26ze8Zn876+tpjfvygts51hfKBwevDX\nN1Dui+/X2TwKcxLvi2tXXnie8VnMK/R9QtmhwqHSH7KtW+Afq6VmECXIskiMQMWzs2zRH/9xfvqR\nI3FL+A2ViIiISE/cUImIiIj0xA2ViIiISE/cUImIiIj0ZH1F6awfQqUv09FfR3kNihJnWRoF5TKC\nomqK/GqlZwhElbXSLzURea1cB0WHPM7Pb4IolMpsKrlrdTO2V0SNvH8hPO8IA0+itMnCidyE6PwE\nykKwTMRFPGqDptT0rRSArrAra6J0zkUGUEDwSUFsoViNHbChZi5E6TzOuY6xK0qSEMztWQhw2WHs\noL4BF7cJ7EXqnqlb5pLYuhMTiUJuisIDQnCKcQvxLkXnaFABfSaCDbpCZQZWMOiFY07RN/07r1eU\ntoHPWHwut7dhjTEwhOVMCIXUm9FXjCigqB5s3573XfF6wPPRp9ElXFnI62nRp43PYC7x+enfaRO0\nLzNZFo2N4dhyLNmX9z+Am6M0VwGDYODfUEaHC/HyUYjUwRLiqYaP9Av4DZWIiIhIT9xQiYiIiPTE\nDZWIiIhIT9xQiYiIiPRkfUXpzGZKkVwh1AUUwl3n+dwvMnt0zaaQlqL3Svf1Fp3DvlrJPk3RJ68/\nKrw+MyMzszGfj4rchY6IFCL05xfytlOUTpvxDBQRUgBay5zOxL0UtZNSlA6RJkXqPE7BKO2AwDbQ\nwCIzOm0GXNTmAkWeaM8YnodVDTZVAjpYJWCDwFoJh3PdcDyMJXAFx4uJSZ93EaL0rRSpI8N+4fMY\nnEB5LYTexTwZEvjCwApmy+ecpmidgRu06W+o+KfCn/B8LnIG1ZzMRe7LR3MnQ/dGH0QdNn0SX1fH\njuVjPwafwqlBn8O5NL8J1+N48AMVUf0yTr/WufxkMVZ42O0IqqFD3ofKD5PMjL4bNv1TpUoHBwvr\n6viT+eBRI092VIKabuI3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0pN1FaVfPJqLCinaG6No\njsI2iiKrImw+7qiidF6fwtwRM6UXIvTh2V6bq/n51Bgyu/fYplwyO30V2WGZTZb9TVEjReY1Ufoi\nPt9JBdws5KLAmuic+tLnoYGk1nccTdmMEwr9Poailtg7cag59rXU6hR1J4qHKfLmcWY5rh1ngyla\n59zn9dD+6lzHXN6gmdIxDYte5rym5pz2LgaeMLghkB28GoxAKKPnOPP6WBhdITfbxjlO/1JUcqjM\nIfYFPr+8mLdt8noe5HQG7u7yldypjOH2NZ/DsSyy3kPzvsKuw9AcO5bbu6HD3gGdNufKFrwv6dN2\nXMkbeLFIkp87RX6e7d3SFd1zbAsHivXPLPi7WemBQTecGxDBBzov0BlFAER+nH352GMxFI7NWvgN\nlYiIiEhP3FCJiIiI9MQNlYiIiEhP3FCJiIiI9MQNlYiIiEhP1jXK78iR3Gbq/l1XzufHWb6D6e1Z\nqiAQaVDAx2fECyOTeLxCtdQM2ldE/eXnMwqDUX48TlgdYHIR/bt4MT/hQn48ZlEOpRblx/HolHZ4\n9nh+6DQichhBc3ExtxnVV4m/LCIgR6UWkNT/A7XSLJVSCyPb7LHrleOV0g61qL4NGuVX8xiMDLv3\n3tymz4tjKMf10KM4gTUyGJXHqEBGAbKkEaOl+ETwCd3IOy7SBbSF/oxrglHALFVT+M98jl3D5c+h\nr+kfn8GjXoJPeeqp3D6Lx2PRH/qgTYgSZLwl50atmgkfn+1lJR0+7yLOr70/GKTJ6jDT3QfalGIo\nLEXFsLqidhfnJXuL/okePi9lVoRQPvzyvDlPH8lsjn0RsI6+XAu/oRIRERHpiRsqERERkZ64oRIR\nERHpiRsqERERkZ6sqyj9k0dzeysEmtQ03juTK5fTPASaFFVfg+punMK2T7NQtiKirNY3KUTr+fk1\nUSFt3o5QF3jxQt6emRmWBsrtcVY3ActoT7eUwykIOM+jLAKfpWFZneG3LosMoa1FJZhKZZVCYz6y\n6BxwbjQYrERROG1KYlGmo4CfZwAHi6jgeg1slp6o1fKploW6PWEoQSFEprAY3UzR+ksp9C7GlTMf\nIvYCBuZw3laufwpi3+64szYLg1io5KUwmbC0FUFnck0H3h9cotMYnBMIjCncMy5fC2GCxJ5y/iJc\noAiZqgif+bqridJp01+z1BsDJIYJs+dmK4r2GZSKmai8LAo4TxGwQH/23OO5zbmEzhqbyK+/b1/+\nsJwLtal5E7+hEhEREemJGyoRERGRnrihEhEREemJGyoRERGRnqyrKJ2iwEsQ2Y2hddQ07qIokiJI\npgafo5CXqcVreY8p4BxRdH4DEtYRs0vzMLN/10TrNZE6RZwUMVIEWtMZsj3d4aH29jI10YD3oiaS\nTEGASgEnBZg8n3ZVlM7MwEXAAUXasNlZk5yblLyyw6ia5FymKJziZ34eNlWZDAC5UhGt1ybfbQp1\nxBSls5fPoCIAq0W8lDe4jHGfppSZQm9mTqfPYkZqXg825/lSpz377s6PHXsmtycgw96MOck5xHsV\n2bRzxnfmzzKO643hcjt35janJH0MfdRRBFFdxRKfQ/s4N7iCOXJcsZMVH0ZROd+XdCl8fsL3K++X\nUfNv9Bc8f4wX5zx9ADb9Hd79rDBAB/700/ndlvL28HTOBW411sJvqERERER64oZKREREpCduqERE\nRER64oZKREREpCfrKkqn0Iu6tS0QDlPntos/uACRI0WPc8xdO0x1txoUzkEZfZXCXNgV0XkNajaZ\nPZyXG1Wkzs/XsoVTBEkRKEXz1zrtYVsIRYIUTNbaWhOl1wSY0xB88nrV1Oo1alnyJ9lBzGxOySvv\nz4zanLunh9sNbCp0C5E6A0IgwaVofYNArSodKqX4nCYMjigmYiHm5x0PwD4D+1TFplQaonRmvB6W\nKZ2LqghMgM0gHQYBMdBjArJtrqHZXKQ+jb596bZ8DW3fnvftnj35+YcO5TZF4McRVEV/eAlLouaT\n+DjsTs6VIlAHx9lezj3ef25+8/ATumuYadvpD/fvH27HXbCZR54RT/R/z+cmAyJOYp7jXUz3tW9f\nbvP9xL3IWvgNlYiIiEhP3FCJiIiI9MQNlYiIiEhP3FCJiIiI9MQNlYiIiEhP1jXKj1FotK/BvszA\nJ0rxGWlEKf9uRLSMszBErTwG09/DZiRTLYyOVEovpE3XYQ+/HGFz2H3s/1GbS5vtYxRgl2pUHeC1\nxzGT+XlGvDAiZisCWrZWStMUZTVqnUGqEZ+ci4yS41xMw+9XRMkwGgxRfadhM6KriPo7DxtrjxFf\nGwQWCKqNyvlKcGScROmY4ydy+wFEVxXRUeBSpRzMFcyLKUT1LaA9mzpPNLMlP0Z7M6OesUjZFkaG\nEkaS1RzW7Jahx3fM5/b167nNQDb6Swau0ccsLOQ2K6Ht2p3bLO1Vi0Rm5Bk/XyunNb4d/VPzWd3+\nLGp3YSw5F8YY1cfCO6yLw4h8+BtGIRcvs3zunX86P58ln9i3dHfPW3pGRERE5LODGyoRERGRnrih\nEhEREemJGyoRERGRnqyrKJ0iuVGreaxAtzvGUi9LEFxSKHsHlcY1UTqudwnCOQo8i9ILletXhM0U\ndVOIPaoOuiZSv4bjLHVDOH4c37GptY9VBZQQXFKAyTIMo9rF/aZYywZiXYowWRZjM8pmjCpaZxkO\nlgQp5NC8Hj+Puc8SJpdRqoGqzJpI/SxKQUBg3FxFQEVsDNir9CiQ5sYy1lgR7HD4cG7vvjO390Lc\ny2iKmg+rBL4UwQbHn13785zjLFNTlC6BfywU+YBtrQX50IHVyh3h2TdvztcURea7ISLn7YvXC0Tt\nu/E4vD5F7jVRfKELx1xKExhbCsVr41Otk9Q9lpf9KeZVYG4E/GXhvyhiR9ue+khu812PufXhJ3D3\nyrS/iKnJYJK18BsqERERkZ64oRIRERHpiRsqERERkZ64oRIRERHpybqK0pkJltmyqYGjELnQ9VK0\nSJE6RZBFdteKoJOiPQrhikzpEKXfoLAYbBouZKbOb1Sb/VVL1s1M9ezeqq4adIXg1ENyLtAu5sIM\nbk6V+WaIHgtReEUWXRPvUqRe3H/EwRi1M6uZ1JmZnAJgqCypyjx7pmLnovTmXJ4p/RKyQnMu7YiN\nwVHYHEXmgyYc9osYlq1UOh/+RG7vh0/hBefQAg4EA2cWkJmd87zr0/jZPRASM1CDqcKZrnoTrsc1\nug3CZwqFZ+DAamsex69fz/uGIu+a/yzOR1fTRezdm9sUoTPeoBb0U0AnWwjHx4bbwx6Y7zb6j51c\n4VwJrCmAzglk+A+oyllBAKws5gp+itAJ+5bBI7WArJv4DZWIiIhIT9xQiYiIiPTEDZWIiIhIT9xQ\niYiIiPRkXUXpFOExcyw1dRStF5lgKaKjaJKpZilSv14RjV+FypAiS4rWa5l9a0BYvXnzFdgx1K7p\nnkfNrF5rfmImd+gMu8LynTvzY7uQhXh2N7L68gOzOD6BAAMKUG80uc2xociyltW+phBleyiSLzKr\nM3Mwl2btdx88XyFax9xdYWbhPLN5XLg43IYIldppZhpmVYONIkqHRyny01OKy2nDNcU1FIc/ntt7\nkDmdInKuEzpVLnpmQi/WCdZFNxCHQT27d8VQTiIbP9fYhTywocjszc7jGmIQUq1SBXzItm35HGdX\ncY7zcisYy21wCVsQWFMVmRfZxlFtgHOFovPCB0F0TpU8J+POO3L72LEX/s1KEpx3BZcqx9HWeDw3\nzx/JbVRi4Lv3xEJ+uHh9YCyegOadY82uWgu/oRIRERHpiRsqERERkZ64oRIRERHpiRsqERERkZ64\noRIRERHpybpG+VF5zygHRvlthTK/jOyq1AZgxAqj9mrwfEYNFlEliBqshclVwu4Y1TFqFN/I1U0q\n8HpjsFkqqBtwVFRFmMfgM5qJIaG8AEtkEEYAsUwQIzR5nGNXK03T1y6WJkvl1AaTEauMeOXzsqwS\nIlgREXsZhxnVx+PLIy612wWO0syqZ70A+4nRRJ84nNsvRRzh7JMfyU949NHcZvgS5/1RFMvhvKaP\nq0W7dtk2l9unT+M41iznHMoZleVN8Cxcgyx/UoQ9I8qtEqnKIHDadP+0dyNyuVb+hI9/50Te9xwa\nPt44ox5rpc449iyltun5tT+7f39uM0q4gNfiyxzRrIzq41w5jVJYuD/9D/cWRakZ9C2X0a0uA7+h\nEhEREemJGyoRERGRnrihEhEREemJGyoRERGRnqyrKJ1VESgc4/Ei/Xut1gqhSLwoNVNRzhafh2hy\n1FotNUZUkVO0Pqo9anNG1WV3x49jW6gAKWDdvn34cQYoEIpzN19e/bw1P4+5UTw8BKEsfcOyD9WI\ngZoIfdTfhVBSpAjY4NxmaZ7hAtlrsCny5PGNArWqdKj3wOY0phCZx7dwnRTiXJRzYfAG5xWFxywX\nQ2X2cZS26a67eZQmYTkQziG2hW3lvbhmKXKHg1levI7Duc3m1CqR8XZnMFYUPvPxeD2+v1iKhkvy\nedyPLu/kydzeejX/wOxO3JDC8RkE8vABpjC+3Q5kYzkvF55D4xCwcOmTuc3rLaB2zJ49uU1/ivuz\nTB3X1TLGvuHj4LiidBEREZHPEm6oRERERHrihkpERESkJ26oRERERHqSmqapnyUiIiIia+I3plLa\nZAAAAMFJREFUVCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIi\nIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3\nVCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9cUMlIiIi\n0hM3VCIiIiI9cUMlIiIi0hM3VCIiIiI9+f8Bxu2MZQuhwtAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f96a552b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    fig, axes = plt.subplots(1, 2)\n",
    "    noise = np.random.normal(size=faces[face_index].shape)\n",
    "    #smooth the noise to reduce the number of degrees of freedom\n",
    "    noise = scipy.ndimage.filters.gaussian_filter(noise.reshape(im_shape), 4).reshape((-1,))\n",
    "    noise /= np.std(noise)\n",
    "    \n",
    "    pca_coeffs = np.dot(wlra.H, noise)\n",
    "    reconstruction = np.dot(pca_coeffs, wlra.H) + wlra.mean\n",
    "    \n",
    "    axes[0].set_title(\"Seed Noise\")\n",
    "    axes[1].set_title(\"Reconstruction\")\n",
    "    view_as_image(noise, ax=axes[0])\n",
    "    view_as_image(reconstruction, ax=axes[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since our principal vectors encode structure that is face like whatever random fluctuations happen to connect to those vectors is what we pick up. I would not reccomend using this noise reduction technique prior to feeding data into a machine learning algorithm. However, if you are considering using PCA as a dimensionality reduction technique as part of a larger pipeline it is often a good idea to first look at what the pca based reconstruction of your data would look like. You might be able to capture 95% of the data variance with just 10 components but the information in that last 5% might be really important. Comparing each observation to its reconstruction will help to give you an idea of what structure the lower dimensional space is capturing and what it is leaving out.\n",
    "\n",
    "If you are using the sklearn PCA class you can do reconstruction simply by chaining the transform and inverse_transform methods of the PCA object. This is exactly equivalent to the \"de-noising\" technique that we were using above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f25e272ad68>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h25y/Fn0VaS7q8PxLatWlWZT6ZREdmijAEhbo4Ydc+A+/5V1/553n4wvfeaX/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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f25e2761390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "validation_subject = 3\n",
    "subject_mask = subject_ids != validation_subject\n",
    "\n",
    "train_faces = faces[subject_mask]\n",
    "validation_faces = faces[np.logical_not(subject_mask)]\n",
    "\n",
    "pca = sklearn.decomposition.PCA(n_components=50)\n",
    "pca.fit(train_faces)\n",
    "\n",
    "faces_pca_reconstruction = pca.inverse_transform(pca.transform(validation_faces))\n",
    "\n",
    "fig, axes = plt.subplots(1, 2)\n",
    "view_as_image(validation_faces[0], ax=axes[0])\n",
    "view_as_image(faces_pca_reconstruction[0], ax=axes[1])\n",
    "\n",
    "axes[0].set_title(\"Original\")\n",
    "axes[1].set_title(\"PCA Reconstruction\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  },
  "nikola": {
   "category": "",
   "date": "2017-09-07",
   "description": "PCA for missing data imputation and/or denoising",
   "link": "",
   "slug": "other_use_for_PCA_part2",
   "tags": "PCA, dimensionality reduction, imputation, mathjax",
   "title": "Imputing Missing Values With PCA",
   "type": "text"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}