From 1f409f9872a0c7c5da333eb3a5a8b545e778fecc Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 6 Apr 2022 05:06:45 -0600 Subject: [PATCH 01/67] Add Tutorial Notebook for VALMOD --- docs/Tutorial_VALMOD.ipynb | 647 +++++++++++++++++++++++++++++++++++++ 1 file changed, 647 insertions(+) create mode 100644 docs/Tutorial_VALMOD.ipynb diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb new file mode 100644 index 000000000..0757670fa --- /dev/null +++ b/docs/Tutorial_VALMOD.ipynb @@ -0,0 +1,647 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "482a2e9b", + "metadata": {}, + "source": [ + "In this tutorial, we would like to implement [VALMOD](https://arxiv.org/pdf/2008.13447.pdf) paper and reproduce its results as closely as possible.\n", + "\n", + "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "40bf9a66", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import stumpy\n", + "from stumpy import core, config\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" + ] + }, + { + "cell_type": "markdown", + "id": "1bc907ef", + "metadata": {}, + "source": [ + "# 1- Introduction" + ] + }, + { + "cell_type": "markdown", + "id": "aa1d847c", + "metadata": {}, + "source": [ + "Some important notations that we may use later:\n", + "* subsequence $T_{i,m}$ --> a subsequence of `T` that starts at index `i` and has length `m` \n", + "* Motif set $S^{m}_{r}$ (for a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$) --> is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set." + ] + }, + { + "cell_type": "markdown", + "id": "8c36e21f", + "metadata": {}, + "source": [ + "### Motif discovery" + ] + }, + { + "cell_type": "markdown", + "id": "fd1568ab", + "metadata": {}, + "source": [ + "We would like to find set $S^{*} = \\bigcup\\limits_{m=min_m}^{max_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "\n", + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index in two different motif sets. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty. \n", + "\n", + "**The authors provided a solution to get top-k motifs from set $S^{*}$. So, this is what can be understood from the statement:**
\n", + "Let us assume we only want to find top-k motifs from all subsequnce with either length `m` or length `m+1`. We try to find motif set for each length...then we should sort the distances (maybe after normalizing them) and then get top-k.\n", + " \n", + "---\n", + "\n", + "**NOTE (from NOTEBOOK producer)**:
\n", + " (1) It is not clear whether the value of `r` can be calculated based on `r`or it should be provided by the user again.
\n", + " (2) It is also not clear whether one should consider trivial matches in $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. Since `m` is changing from one set to another, it may not be easy to understand if two sequences with different length are trivial neighbors of each other or not." + ] + }, + { + "cell_type": "markdown", + "id": "c0455171", + "metadata": {}, + "source": [ + "### Discord discovery" + ] + }, + { + "cell_type": "markdown", + "id": "71cfdcf0", + "metadata": {}, + "source": [ + "First, we need to provide a few definitions..." + ] + }, + { + "cell_type": "markdown", + "id": "3826e0a5", + "metadata": {}, + "source": [ + "**$n^{th}$ best match**: Given a subsequence $T_{i,m}$, the $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", + "\n", + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?!) best match.
\n", + "\n", + "**Top-k $n^{th}$ discord**: This is k-th value of $P^{n_{th}}$, sorted in ascending order. $P^{n_{th}}$ is the matrix profile that is constructed based on $n^{th}$ best match rather than 1NN.\n" + ] + }, + { + "cell_type": "markdown", + "id": "5167292f", + "metadata": {}, + "source": [ + "**NOTE**:
\n", + "Why should I care about $n^{th}$ discord (n>1)? We provide a simple example below:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "3d9db678", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "T = np.random.uniform(-100,100,size=3000)\n", + "m = 200\n", + "i, j = 100, 1500\n", + "\n", + "T[i:i+m] = 0\n", + "T[j:j+m] = 0\n", + "\n", + "plt.plot(T)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "a8e87bc0", + "metadata": {}, + "source": [ + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0. Therefore, we may need to investigate other neighbors. \n", + "\n", + "For further details, see Fig. 2 of the paper (Notice that `Top-1 2nd discord` has a close 1NN...but it is far from its 2nd closest neighbor.)" + ] + }, + { + "cell_type": "markdown", + "id": "1be2fecb", + "metadata": {}, + "source": [ + "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", + "Given a time series `T`, a subsequence length-range `[min_m, max_m]`, and `K` and `N`, we want to find top-k discords $n^{th}$ discord for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + ] + }, + { + "cell_type": "markdown", + "id": "27b8effd", + "metadata": {}, + "source": [ + "# 2- Lower-Bound Distance Profile (for z-normalize case)" + ] + }, + { + "cell_type": "markdown", + "id": "5f999789", + "metadata": {}, + "source": [ + "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can I find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` but is longer by `k` elements ?" + ] + }, + { + "cell_type": "markdown", + "id": "03836054", + "metadata": {}, + "source": [ + "In other words, can I find lower bound for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$?" + ] + }, + { + "cell_type": "markdown", + "id": "be9e2963", + "metadata": {}, + "source": [ + "(Note: It is more common to consider `i` as the main index and `j` as the neighbor. Here, however, we choose `j` as the start index of subsequene of interest so to be consistent with the paper.)" + ] + }, + { + "cell_type": "markdown", + "id": "4fc93b47", + "metadata": {}, + "source": [ + "$d^{(m+k)}_{j,i} \\ge \\min{(d)}$, where $d$ is:\n", + "\n", + "$d = \\sqrt{\n", + "\\sum\\limits_{t=1}^{m}{\n", + "(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}})^{2}\n", + "}\n", + "}$, where ($\\mu_{i,m+k}$, $\\sigma_{i,m+k}$), and ($\\mu_{j,m+k}$, $\\sigma_{j,m+k}$) are (mean, standard deviation) of subsequences $T_{i,m+k}$ and $T_{j,m+k}$, respectively." + ] + }, + { + "cell_type": "markdown", + "id": "ff38394a", + "metadata": {}, + "source": [ + "**Note:** The values $\\mu_{j,m+k}$ and $\\sigma_{j,m+k}$ are known. The goal is to find its lower-bound distane to its neighbor `i` (i.e. $T_{i,m+k}$) without using its last `k` elements! The value $d$ shown above is the z-normalized distance between $T_{j,m+k}$ and $T_{i,m+k}$ considering only the `m` first elements. We know that it is already less than $d^{(m+k)}_{j,i}$. So, by minimizing the Right Hand Side of inequation, we can get the Lower Bound (LB)." + ] + }, + { + "cell_type": "markdown", + "id": "49b2a8fc", + "metadata": {}, + "source": [ + "Factoring out $\\frac{1}{\\sigma_{j,m+k}}$ --> Therefore: $d = \\frac{1}{\\sigma_{j,m+k}}\\sqrt{\n", + "\\sum\\limits_{t=1}^{m}{\n", + "(\\frac{T[i+t-1] - \\mu_{i,m+l}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1})^{2}\n", + "}\n", + "}$ " + ] + }, + { + "cell_type": "markdown", + "id": "4fa6a3a9", + "metadata": {}, + "source": [ + "mulitply by $\\frac{\\sigma_{j,m}}{\\sigma_{j,m}}$ --> Therefore: $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\n", + "\\sum\\limits_{t=1}^{m}{\n", + "(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", + "}\n", + "}$\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "1634ef47", + "metadata": {}, + "source": [ + "Now, we replace $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$, so we have:" + ] + }, + { + "cell_type": "markdown", + "id": "a86bc201", + "metadata": {}, + "source": [ + "$d = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\n", + "\\sum\\limits_{t=1}^{m}{\n", + "(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", + "}\n", + "}$\n", + "\n" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "5b0f6217", + "metadata": {}, + "source": [ + "**Important Note:**
\n", + "Note the typo in eq(1) of the paper...\n", + "![image.png](attachment:image.png)" + ] + }, + { + "cell_type": "markdown", + "id": "9682721a", + "metadata": {}, + "source": [ + "Somehow, the authors change $\\mu_{j,m+k}$ to $\\mu_{j,k}$...However, these two values can be different. It seems the LB provided in eq(2) of paper is derived considering such typo. (In fact, the author of this notebook took the derivatives as explained in the paper and achieved one of the term in eq(2). " + ] + }, + { + "cell_type": "markdown", + "id": "4e1ac4d6", + "metadata": {}, + "source": [ + "**>>> In this notebook:
\n", + "we try to calculate LB after correcting such typo. The problem becomes...**" + ] + }, + { + "cell_type": "markdown", + "id": "51f452b1", + "metadata": {}, + "source": [ + "**To find the minimum value of d, we need to minimize the following function:**" + ] + }, + { + "cell_type": "markdown", + "id": "4c09667d", + "metadata": {}, + "source": [ + "$f(\\mu^{'}, \\sigma^{'}) = \\sum\\limits_{t=1}^{m}{\n", + "(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", + "}$
\n", + "\n", + "**Let's take its partial derivatives and put them equal to 0...**
\n", + "$\\frac{\\partial f}{\\partial \\mu^{'}} = 0$
\n", + "$\\frac{\\partial f}{\\partial \\sigma^{'}} = 0$" + ] + }, + { + "cell_type": "markdown", + "id": "37330b9c", + "metadata": {}, + "source": [ + "**First, let us first provide some guidelines:**
\n", + "\n", + "(1) We use $T_{i}$ to represent $T[i+t-1]$, and $T_{j}$ to represent $T[j+t-1]$. Since we use them inside $\\sum$, the notation should suffice.
\n", + "(2) We use $\\sum$ without limits. It is alway from $t=1$ to $m$.
\n", + "(3) We define: $X = \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}$
\n", + "(4) Similar to paper, We define: $q = \\frac{\\sum{T_{i}T_{j}} - m\\mu_{i,m}\\mu_{j,m}}{m\\sigma_{i,m}\\sigma_{j,m}}$ (note: $q=1$ for $i=j$)
\n", + "(5) Note that: $\\sum{T_{i}} = m\\mu_{i,m}$, and $T_{j} = m\\mu_{j,m}$.\n", + "(6) We use $\\mu_{j}$ and $\\sigma_{j}$ to represent $\\mu_{j,m}$ and $\\sigma_{j,m}$, respectively. If we want to show $\\mu$ for length `m+k`, we use $\\mu_{j,m+k}$" + ] + }, + { + "cell_type": "markdown", + "id": "0df0e59b", + "metadata": {}, + "source": [ + "**Let us solve it...**" + ] + }, + { + "cell_type": "markdown", + "id": "e330f0c1", + "metadata": {}, + "source": [ + "(1) $\\frac{\\partial f}{\\partial \\mu^{'}} = 0$
\n", + "\n", + "Therefore: $\\sum{\\frac{-2}{\\sigma^{'}}X} = 0$
\n", + "Therefore: $\\sum{X} = 0$ (eq: I)" + ] + }, + { + "cell_type": "markdown", + "id": "30f65c15", + "metadata": {}, + "source": [ + "(2) $\\frac{\\partial f}{\\partial \\sigma^{'}} = 0$
\n", + " \n", + "Therefore: $\\sum{\\frac{-2}{\\sigma^{'2}}(T_{i} - \\mu^{'})X} = 0$
\n", + "Therefore: $\\sum{(T_{i} - \\mu^{'})X} = 0$
\n", + "Therefore (using eq I): $\\sum{T_{i}X} = 0$ (eq II)
" + ] + }, + { + "cell_type": "markdown", + "id": "abe3ee87", + "metadata": {}, + "source": [ + "Also, let us find out the value we are trying to minimize:" + ] + }, + { + "cell_type": "markdown", + "id": "91096e9d", + "metadata": {}, + "source": [ + "$f(\\mu^{'}, \\sigma^{i}) = \\sum{\n", + "(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})^{2}\n", + "} \n", + "= \n", + "\\sum{\n", + "[(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})X]\n", + "} \n", + "= \n", + "{\n", + "\\frac{\\sum{T_{i}X} - \\sum{\\mu^{'}X}}{\\sigma^{'}} - \\frac{\\sum{T_{j}X} - \\sum{\\mu_{j,m+k}X}}{\\sigma_{j}}\n", + "} $" + ] + }, + { + "cell_type": "markdown", + "id": "7d6213b9", + "metadata": {}, + "source": [ + "And, with help of eq I and II, we can see:
\n", + "$f_{optim} = - \\frac{\\sum{(T_{j}X)}}{\\sigma^{'}} $" + ] + }, + { + "cell_type": "markdown", + "id": "c63a0492", + "metadata": {}, + "source": [ + "Therefore:
\n", + "$f_{optim} = - \\frac{1}{\\sigma^{'}}F$, where:
\n", + "\n", + "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$" + ] + }, + { + "cell_type": "markdown", + "id": "0fe24576", + "metadata": {}, + "source": [ + "**We need to find $\\mu^{'}$ and $\\sigma^{'}$:**" + ] + }, + { + "cell_type": "markdown", + "id": "b028fd7f", + "metadata": {}, + "source": [ + "eq I: $\\sum{X} = 0$,
\n", + "\n", + "Therefore: $\\sum{\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}}} = 0$
" + ] + }, + { + "cell_type": "markdown", + "id": "e6e9ce06", + "metadata": {}, + "source": [ + "Therefore: ${\\frac{\\sum{T_{i}} - \\sum{\\mu^{'}}}{\\sigma^{'}} - \\frac{\\sum{T_{j}} - \\sum{\\mu_{j,m+k}}}{\\sigma_{j}}} = 0$
" + ] + }, + { + "cell_type": "markdown", + "id": "89ac2637", + "metadata": {}, + "source": [ + "Therefore: ${\\frac{m\\mu_{i} - m{\\mu^{'}}}{\\sigma^{'}} - \\frac{m{\\mu_{j}} - {\\mu_{j,m+k}}}{\\sigma_{j}}} = 0$" + ] + }, + { + "cell_type": "markdown", + "id": "dd128a9f", + "metadata": {}, + "source": [ + "Therefore (given $m \\neq 0$): $\\sigma_{j}(\\mu_{i}-\\mu^{'}) - \\sigma^{'}(\\mu_{j}-\\mu_{j,m+k}) = 0$ (eq III)" + ] + }, + { + "cell_type": "markdown", + "id": "6784d89e", + "metadata": {}, + "source": [ + "---\n", + "\n", + "And, with eq II:
\n", + "$\\sum{T_{i}X} = 0$," + ] + }, + { + "cell_type": "markdown", + "id": "cc05e3e1", + "metadata": {}, + "source": [ + "Therefore: $\\frac{\\sum{T_{i}T_{i}} - \\sum\\mu^{'}T_{i}}{\\sigma^{'}} - \\frac{\\sum{T_{i}T_{j}} - \\sum{\\mu_{j,m+k}T_{i}}}{\\sigma_{j}} = 0$" + ] + }, + { + "cell_type": "markdown", + "id": "b6f83405", + "metadata": {}, + "source": [ + "Therefore: $\\sigma_{j}(m\\mu_{i}^{2} + m\\sigma_{i}^{2} - m\\mu_{i}\\mu^{'}) - \\sigma^{'}(m\\mu_{i}\\mu_{j} + mq\\sigma_{i}\\sigma_{j} - m\\mu_{i}\\mu_{j,m+k}) = 0$ (eq IV)" + ] + }, + { + "cell_type": "markdown", + "id": "71dbe617", + "metadata": {}, + "source": [ + "**solving eq (III) and eq (IV) give us $\\mu^{'}$ and $\\sigma^{'}$ as follows:**" + ] + }, + { + "cell_type": "markdown", + "id": "32537233", + "metadata": {}, + "source": [ + "$\\sigma^{'} = \\frac{\\sigma_{i}}{q}$ (thus, q must be positive.)
\n", + "$\\mu^{'} = \\mu_{i} - \\frac{\\sigma^{'}}{\\sigma_{j}}(\\mu_{j}-\\mu_{j,m+k})$\n", + "\n", + "**If q becomes negative, then:**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2c0d1430", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "b0b16d69", + "metadata": {}, + "source": [ + "To make sure our answers are correct, we plugged them back in eq I and II. To check this, we define functions (just for internal use):" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "a90ed8e8", + "metadata": {}, + "outputs": [], + "source": [ + "def _check_derivatives(T,idx,m,k):\n", + " \"\"\"\n", + " This function checks the first (eq I) and second derivatives (eq II) using the optimal values \n", + " provided above.\n", + " \n", + " T: numpy.ndarray\n", + " A time series of interest\n", + " \n", + " idx: int\n", + " start index of subsequence of interest\n", + " \n", + " m: int\n", + " the original window size\n", + " \n", + " k: int\n", + " the additional length (in other words, new window size is m+k.)\n", + " \"\"\"\n", + " M = m + k #larger length (compared to original length m)\n", + " excl_zone = int(np.ceil(M / config.STUMPY_EXCL_ZONE_DENOM)) #unncessary for now! we just need to check \n", + " # that our values are correct...\n", + " \n", + " \n", + " M_T_m, Σ_T_m = core.compute_mean_std(T, m)\n", + " mu_idx, std_idx = M_T_m[idx], Σ_T_m[idx]\n", + " \n", + " M_T_M, Σ_T_M = core.compute_mean_std(T, M)\n", + " mu_IDX, std_IDX = M_T_M[idx], Σ_T_M[idx]\n", + " \n", + " neighbors = np.full(T.shape[0] - M + 1, 1, dtype=bool)\n", + " core.apply_exclusion_zone(neighbors, idx, excl_zone, val = False)\n", + " for i in np.flatnonzero(neighbors):\n", + " mu_i = M_T_m[i]\n", + " std_i = Σ_T_m[i] \n", + " \n", + " q = (1/(m*std_idx*std_i)) * (np.dot(T[i:i+m],T[idx:idx+m]) - m * mu_i * mu_idx)\n", + " \n", + " #finding optimal values to find LB\n", + " std = std_i / q\n", + " mu = mu_i - (std/std_idx) * (mu_idx - mu_IDX)\n", + " \n", + " #calculate first derivative using optimal mu and std\n", + " X = (T[i:i+m] - mu)/std - (T[idx:idx+m] - mu_IDX)/std_idx\n", + " deriv_I = sum(X) #eq I\n", + " deriv_II = sum(X*T[i:i+m]) #eq II\n", + " \n", + " np.testing.assert_almost_equal(deriv_I, 0)\n", + " np.testing.assert_almost_equal(deriv_II, 0)\n", + " \n", + " return " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "90fc9b10", + "metadata": {}, + "outputs": [], + "source": [ + "T = np.random.uniform(-100, 100, size=1000)\n", + "m = 50\n", + "k = 10\n", + "\n", + "idx = 500\n", + "_check_derivatives(T,idx,m,k)" + ] + }, + { + "cell_type": "markdown", + "id": "bd4a023d", + "metadata": {}, + "source": [ + "Now, we plugged back in the values to find LB:\n", + "\n", + "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{f_{optim}}$, where:
\n", + "\n", + "$f_{optim} = - \\frac{1}{\\sigma^{'}}F$, where:
\n", + "\n", + "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$ in which we should use the optimal value for $\\mu^{'}$ and $\\sigma^{'}$." + ] + }, + { + "cell_type": "markdown", + "id": "bec46a29", + "metadata": {}, + "source": [ + "* If $q \\gt 0$: $LB = \\frac{\\sigma_{j}\\sqrt{\\sigma_{j}}}{\\sigma_{j,m+k}\\sqrt{\\sigma_{i}}} \\sqrt{mq(1-q^{2})}$\n", + "* If $q \\le 0$: $LB = ?$" + ] + }, + { + "cell_type": "markdown", + "id": "3a99be48", + "metadata": {}, + "source": [ + "Note that our formula for LB of distance profile is different than what provided in the paper." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6b4e19c1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 53774a58525ae5b621c24a0d166b9386400571df Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 6 Apr 2022 17:49:25 -0600 Subject: [PATCH 02/67] Fix calculation and implement Lower-Bound distance profile --- docs/Tutorial_VALMOD.ipynb | 249 +++++++++++++++++++++---------------- 1 file changed, 145 insertions(+), 104 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 0757670fa..e3e266d0e 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -5,15 +5,15 @@ "id": "482a2e9b", "metadata": {}, "source": [ - "In this tutorial, we would like to implement [VALMOD](https://arxiv.org/pdf/2008.13447.pdf) paper and reproduce its results as closely as possible.\n", + "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", "\n", "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." ] }, { "cell_type": "code", - "execution_count": 9, - "id": "40bf9a66", + "execution_count": 96, + "id": "6534d116", "metadata": {}, "outputs": [], "source": [ @@ -59,18 +59,9 @@ "id": "fd1568ab", "metadata": {}, "source": [ - "We would like to find set $S^{*} = \\bigcup\\limits_{m=min_m}^{max_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index in two different motif sets. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty. \n", - "\n", - "**The authors provided a solution to get top-k motifs from set $S^{*}$. So, this is what can be understood from the statement:**
\n", - "Let us assume we only want to find top-k motifs from all subsequnce with either length `m` or length `m+1`. We try to find motif set for each length...then we should sort the distances (maybe after normalizing them) and then get top-k.\n", - " \n", - "---\n", - "\n", - "**NOTE (from NOTEBOOK producer)**:
\n", - " (1) It is not clear whether the value of `r` can be calculated based on `r`or it should be provided by the user again.
\n", - " (2) It is also not clear whether one should consider trivial matches in $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. Since `m` is changing from one set to another, it may not be easy to understand if two sequences with different length are trivial neighbors of each other or not." + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index in two different motif sets. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty. " ] }, { @@ -96,7 +87,7 @@ "source": [ "**$n^{th}$ best match**: Given a subsequence $T_{i,m}$, the $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?!) best match.
\n", + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", "\n", "**Top-k $n^{th}$ discord**: This is k-th value of $P^{n_{th}}$, sorted in ascending order. $P^{n_{th}}$ is the matrix profile that is constructed based on $n^{th}$ best match rather than 1NN.\n" ] @@ -112,13 +103,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 97, "id": "3d9db678", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -146,9 +137,9 @@ "id": "a8e87bc0", "metadata": {}, "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0. Therefore, we may need to investigate other neighbors. \n", + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors (maybe the second, third, ...or n-th neighbor as well.) \n", "\n", - "For further details, see Fig. 2 of the paper (Notice that `Top-1 2nd discord` has a close 1NN...but it is far from its 2nd closest neighbor.)" + "For further details, see Fig. 2 of the paper (Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" ] }, { @@ -157,7 +148,7 @@ "metadata": {}, "source": [ "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series `T`, a subsequence length-range `[min_m, max_m]`, and `K` and `N`, we want to find top-k discords $n^{th}$ discord for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + "Given a time series `T`, a subsequence length-range `[min_m, max_m]`, and `K` and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." ] }, { @@ -280,7 +271,7 @@ "id": "9682721a", "metadata": {}, "source": [ - "Somehow, the authors change $\\mu_{j,m+k}$ to $\\mu_{j,k}$...However, these two values can be different. It seems the LB provided in eq(2) of paper is derived considering such typo. (In fact, the author of this notebook took the derivatives as explained in the paper and achieved one of the term in eq(2). " + "Somehow, the authors change $\\mu_{j,m+k}$ to $\\mu_{j,k}$...However, these two values can be different." ] }, { @@ -323,7 +314,7 @@ "\n", "(1) We use $T_{i}$ to represent $T[i+t-1]$, and $T_{j}$ to represent $T[j+t-1]$. Since we use them inside $\\sum$, the notation should suffice.
\n", "(2) We use $\\sum$ without limits. It is alway from $t=1$ to $m$.
\n", - "(3) We define: $X = \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}$
\n", + "(3) We define: $X_{t} = \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}$
\n", "(4) Similar to paper, We define: $q = \\frac{\\sum{T_{i}T_{j}} - m\\mu_{i,m}\\mu_{j,m}}{m\\sigma_{i,m}\\sigma_{j,m}}$ (note: $q=1$ for $i=j$)
\n", "(5) Note that: $\\sum{T_{i}} = m\\mu_{i,m}$, and $T_{j} = m\\mu_{j,m}$.\n", "(6) We use $\\mu_{j}$ and $\\sigma_{j}$ to represent $\\mu_{j,m}$ and $\\sigma_{j,m}$, respectively. If we want to show $\\mu$ for length `m+k`, we use $\\mu_{j,m+k}$" @@ -344,8 +335,8 @@ "source": [ "(1) $\\frac{\\partial f}{\\partial \\mu^{'}} = 0$
\n", "\n", - "Therefore: $\\sum{\\frac{-2}{\\sigma^{'}}X} = 0$
\n", - "Therefore: $\\sum{X} = 0$ (eq: I)" + "Therefore: $\\sum{\\frac{-2}{\\sigma^{'}}X_{t}} = 0$
\n", + "Therefore: $\\sum{X_{t}} = 0$ (eq: I)" ] }, { @@ -355,9 +346,9 @@ "source": [ "(2) $\\frac{\\partial f}{\\partial \\sigma^{'}} = 0$
\n", " \n", - "Therefore: $\\sum{\\frac{-2}{\\sigma^{'2}}(T_{i} - \\mu^{'})X} = 0$
\n", - "Therefore: $\\sum{(T_{i} - \\mu^{'})X} = 0$
\n", - "Therefore (using eq I): $\\sum{T_{i}X} = 0$ (eq II)
" + "Therefore: $\\sum{\\frac{-2}{\\sigma^{'2}}(T_{i} - \\mu^{'})X_{t}} = 0$
\n", + "Therefore: $\\sum{(T_{i} - \\mu^{'})X_{t}} = 0$
\n", + "Therefore (using eq I): $\\sum{T_{i}X_{t}} = 0$ (eq II)
" ] }, { @@ -378,11 +369,11 @@ "} \n", "= \n", "\\sum{\n", - "[(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})X]\n", + "[(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})X_{t}]\n", "} \n", "= \n", "{\n", - "\\frac{\\sum{T_{i}X} - \\sum{\\mu^{'}X}}{\\sigma^{'}} - \\frac{\\sum{T_{j}X} - \\sum{\\mu_{j,m+k}X}}{\\sigma_{j}}\n", + "\\frac{\\sum{T_{i}X_{t}} - \\sum{\\mu^{'}X_{t}}}{\\sigma^{'}} - \\frac{\\sum{T_{j}X_{t}} - \\sum{\\mu_{j,m+k}X_{t}}}{\\sigma_{j}}\n", "} $" ] }, @@ -392,7 +383,7 @@ "metadata": {}, "source": [ "And, with help of eq I and II, we can see:
\n", - "$f_{optim} = - \\frac{\\sum{(T_{j}X)}}{\\sigma^{'}} $" + "$f_{optim} = - \\frac{\\sum{(T_{j}X)}}{\\sigma_{j}} $" ] }, { @@ -401,7 +392,7 @@ "metadata": {}, "source": [ "Therefore:
\n", - "$f_{optim} = - \\frac{1}{\\sigma^{'}}F$, where:
\n", + "$f_{optim} = - \\frac{1}{\\sigma_{j}}F$, where:
\n", "\n", "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$" ] @@ -445,7 +436,7 @@ "id": "dd128a9f", "metadata": {}, "source": [ - "Therefore (given $m \\neq 0$): $\\sigma_{j}(\\mu_{i}-\\mu^{'}) - \\sigma^{'}(\\mu_{j}-\\mu_{j,m+k}) = 0$ (eq III)" + "Therefore: $\\sigma_{j}(\\mu_{i}-\\mu^{'}) - \\sigma^{'}(\\mu_{j}-\\mu_{j,m+k}) = 0$ (eq III)" ] }, { @@ -480,7 +471,7 @@ "id": "71dbe617", "metadata": {}, "source": [ - "**solving eq (III) and eq (IV) give us $\\mu^{'}$ and $\\sigma^{'}$ as follows:**" + "**solving eq (III) and eq (IV) give us optimal values for $\\mu^{'}$ and $\\sigma^{'}$ as follows:**" ] }, { @@ -489,135 +480,185 @@ "metadata": {}, "source": [ "$\\sigma^{'} = \\frac{\\sigma_{i}}{q}$ (thus, q must be positive.)
\n", - "$\\mu^{'} = \\mu_{i} - \\frac{\\sigma^{'}}{\\sigma_{j}}(\\mu_{j}-\\mu_{j,m+k})$\n", + "$\\mu^{'} = \\mu_{i} - \\frac{\\sigma^{'}}{\\sigma_{j}}(\\mu_{j}-\\mu_{j,m+k})$" + ] + }, + { + "cell_type": "markdown", + "id": "bd4a023d", + "metadata": {}, + "source": [ + "Now, we plugged back in the values to find LB:\n", + "\n", + "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{f_{optim}}$, where:
\n", "\n", - "**If q becomes negative, then:**" + "$f_{optim} = - \\frac{1}{\\sigma_{j}}F$, where:
\n", + "\n", + "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$ in which we should use the optimal value for $\\mu^{'}$ and $\\sigma^{'}$." ] }, { - "cell_type": "code", - "execution_count": null, - "id": "2c0d1430", + "cell_type": "markdown", + "id": "bec46a29", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "* If $q \\gt 0$: $LB = \\frac{\\sigma_{j}}{\\sigma_{j,m+k}} \\sqrt{m(1-q^{2})}$\n", + "* If $q \\le 0$: $LB = \\frac{\\sigma_{j}}{\\sigma_{j,m+k}} \\sqrt{m}$ (proof not provided in this notebook)" + ] }, { "cell_type": "markdown", - "id": "b0b16d69", + "id": "3bcf8519", "metadata": {}, "source": [ - "To make sure our answers are correct, we plugged them back in eq I and II. To check this, we define functions (just for internal use):" + "### LB dist profile function" ] }, { "cell_type": "code", - "execution_count": 29, - "id": "a90ed8e8", + "execution_count": 87, + "id": "928fc18c", "metadata": {}, "outputs": [], "source": [ - "def _check_derivatives(T,idx,m,k):\n", + "def _calc_LB_dist_profile(T, D, m, σ, m_target, σ_target):\n", " \"\"\"\n", - " This function checks the first (eq I) and second derivatives (eq II) using the optimal values \n", - " provided above.\n", + " This function finds the lower-bound of a distance profile for a subsequence with window size `m_target` based\n", + " on the distance profile of a subsequence with window size `m` starting from the same index `idx`.\n", + " (note: this is for z-normalize case)\n", " \n", + " Parameters\n", + " ----------\n", " T: numpy.ndarray\n", - " A time series of interest\n", - " \n", - " idx: int\n", - " start index of subsequence of interest\n", + " a time series of interest\n", + " \n", + " D: numpy.ndarray\n", + " Distance profile for a subsequence with length `m` located at an index `idx` in time series `T`\n", " \n", " m: int\n", - " the original window size\n", + " length of subsequence for which the the distance profile D is provided. \n", + " \n", + " σ: float\n", + " standard deviation of subsequence `T[idx : idx + m]`\n", + " \n", + " m_target: int\n", + " new length of subsequence whose lower-bound distance profile will be returned.\n", " \n", - " k: int\n", - " the additional length (in other words, new window size is m+k.)\n", + " σ_target: float\n", + " standard deviation of subsequence `T[idx : idx + m_target]`\n", + " \n", + " Return\n", + " --------\n", + " LB : numpy.ndarray\n", + " Lower_Bound of distance profile for subsequence with length `m_target`, starting at index `idx`.\n", + " \n", " \"\"\"\n", - " M = m + k #larger length (compared to original length m)\n", - " excl_zone = int(np.ceil(M / config.STUMPY_EXCL_ZONE_DENOM)) #unncessary for now! we just need to check \n", - " # that our values are correct...\n", + " if m_target <= m:\n", + " raise ValueError(f\"m_target, {m_target} should be larget than m, {m}\")\n", " \n", + " if len(D) != T.shape[0] - m + 1:\n", + " raise ValueError(f\"length of distance profile D, {len(D)}, should be T.shape[0]-m+1, {T.shape[0]-m+1}\")\n", " \n", - " M_T_m, Σ_T_m = core.compute_mean_std(T, m)\n", - " mu_idx, std_idx = M_T_m[idx], Σ_T_m[idx]\n", + " excl_zone = int(np.ceil(m_target / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", - " M_T_M, Σ_T_M = core.compute_mean_std(T, M)\n", - " mu_IDX, std_IDX = M_T_M[idx], Σ_T_M[idx]\n", + " k = T.shape[0] - m_target + 1\n", + " T_is_finite = core.rolling_isfinite(T, m_target)\n", " \n", - " neighbors = np.full(T.shape[0] - M + 1, 1, dtype=bool)\n", - " core.apply_exclusion_zone(neighbors, idx, excl_zone, val = False)\n", - " for i in np.flatnonzero(neighbors):\n", - " mu_i = M_T_m[i]\n", - " std_i = Σ_T_m[i] \n", - " \n", - " q = (1/(m*std_idx*std_i)) * (np.dot(T[i:i+m],T[idx:idx+m]) - m * mu_i * mu_idx)\n", - " \n", - " #finding optimal values to find LB\n", - " std = std_i / q\n", - " mu = mu_i - (std/std_idx) * (mu_idx - mu_IDX)\n", - " \n", - " #calculate first derivative using optimal mu and std\n", - " X = (T[i:i+m] - mu)/std - (T[idx:idx+m] - mu_IDX)/std_idx\n", - " deriv_I = sum(X) #eq I\n", - " deriv_II = sum(X*T[i:i+m]) #eq II\n", - " \n", - " np.testing.assert_almost_equal(deriv_I, 0)\n", - " np.testing.assert_almost_equal(deriv_II, 0)\n", + " R = 1 - np.square(D[:k])/(2 * m)\n", " \n", - " return " + " LB = (σ/σ_target) * np.sqrt(m) * np.sqrt(1 - np.square(np.maximum(R,0)))\n", + " core.apply_exclusion_zone(LB, idx, excl_zone, np.inf)\n", + " LB[~T_is_finite] = np.inf\n", + " \n", + " return LB" + ] + }, + { + "cell_type": "markdown", + "id": "52a327c7", + "metadata": {}, + "source": [ + "**Example:**" ] }, { "cell_type": "code", - "execution_count": 30, - "id": "90fc9b10", + "execution_count": 92, + "id": "df09cc41", "metadata": {}, "outputs": [], "source": [ - "T = np.random.uniform(-100, 100, size=1000)\n", - "m = 50\n", - "k = 10\n", - "\n", - "idx = 500\n", - "_check_derivatives(T,idx,m,k)" + "T = np.random.uniform(-100,100, size=1000)\n", + "idx = 500 #start index of subsequence" ] }, { - "cell_type": "markdown", - "id": "bd4a023d", + "cell_type": "code", + "execution_count": 93, + "id": "2f0a21d3", "metadata": {}, + "outputs": [], "source": [ - "Now, we plugged back in the values to find LB:\n", + "m = 10\n", + "_, Σ_T = core.compute_mean_std(T, m)\n", + "Q = T[idx:idx+m]\n", + "excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", "\n", - "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{f_{optim}}$, where:
\n", + "#################################################\n", "\n", - "$f_{optim} = - \\frac{1}{\\sigma^{'}}F$, where:
\n", - "\n", - "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$ in which we should use the optimal value for $\\mu^{'}$ and $\\sigma^{'}$." + "m_target = 11\n", + "_, Σ_T_target = core.compute_mean_std(T, m_target)\n", + "Q_target = T[idx:idx+m_target]\n", + "excl_zone_target = int(np.ceil(m_target / config.STUMPY_EXCL_ZONE_DENOM))" ] }, { - "cell_type": "markdown", - "id": "bec46a29", + "cell_type": "code", + "execution_count": 94, + "id": "35649122", "metadata": {}, + "outputs": [], "source": [ - "* If $q \\gt 0$: $LB = \\frac{\\sigma_{j}\\sqrt{\\sigma_{j}}}{\\sigma_{j,m+k}\\sqrt{\\sigma_{i}}} \\sqrt{mq(1-q^{2})}$\n", - "* If $q \\le 0$: $LB = ?$" + "D = core.mass(Q, T)\n", + "core.apply_exclusion_zone(D, idx, excl_zone, np.inf)\n", + "\n", + "D_target = core.mass(Q_target, T) #true distance profile for length m_target\n", + "core.apply_exclusion_zone(D_target, idx, excl_zone, np.inf) " ] }, { - "cell_type": "markdown", - "id": "3a99be48", + "cell_type": "code", + "execution_count": 95, + "id": "09669a7a", "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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w8PDw8PDw8PDwGMKoSMwdDw8PDw8PDw8PDw8PDw+PgUVPTw/mz5+Pzs7Ogc6KR0I0NDRgwoQJqK2tdbrekzseHh4eHh4eHh4eHh4eHusg5s+fjxEjRmCLLbZAEAQDnR0PR4RhiBUrVmD+/PnYcsstne7xblkeHh4eHh4eHh4eHh4eHusgOjs7MW7cOE/sDDEEQYBx48YlUlx5csfDw8PDw8PDw8PDw8PDYx2FJ3aGJpK+N++W5eHh4eHh4eHh4eHh4eHhkTlWrFiBr371qwCAxYsXo7q6GhtssAEA4LXXXkNdXV3Zz9h///2xaNEi1NfXo7u7G1/72tdw0UUXYfTo0WWnPZTglTseHh4eHh4eHh4eHh4eHh6ZY9y4cZg2bRqmTZuGH//4x/j5z38efa6rq0Nvb28mz7nzzjsxY8YMzJgxA/X19Tj00EMzSXcowSt3PDw8PDw8PDw8PDw8PDw8+gXHH388xo4di6lTp2KPPfbAiBEj0NTUhNNPPx0AsPPOO+Nf//oXtthiC9xxxx249tpr0d3djc9//vO48cYbUV1dbUy7rq4Ol112GSZOnIjp06fjM5/5TH8Va8DhyR0PDw8PDw8PDw8PDw8Pj3Ucp556KqZNm5ZpmrvtthuuvvrqxPe99957ePLJJ1FdXY0LLrhAvWbmzJm455578OKLL6K2thY/+clPcOedd+LYY4+1pl1dXY3PfOYzmDVrlid3PDwGEh0dHVi8eLHzkW8eHh4eHh4eHh4eHh4eQwff/e53rQocAHjqqacwZcoU7LXXXgAK68QNN9zQKf0wDMvO41CDJ3c8Bh1uvvlmnH/++WhpafGR3T08PDw8PDw8PDw8PDJAGoVNpTB8+PDo/zU1Ncjn89FnOv47DEMcd9xx+N///d9EaedyObz11lvYYYcdssnsEIEPqOwx6LBy5Uq0traul2yrh4eHh4eHh4eHh4fH+oQtttgCb775JgDgzTffxEcffQQA+OpXv4p7770XS5cuBQA0Nzfj448/tqbV09ODX/3qV9hss82w6667Vjbjgwye3PEYdCDW1pM7Hh4eHh4eHh4eHh4e6zaOOOIINDc3Y7fddsNNN92EbbfdFgCw44474qKLLsKBBx6IXXfdFf/v//0/LFq0SE3j6KOPxq677oqdd94ZbW1tePDBB/uzCIMC3i3LY9CByJ18Ph/rh+nh4eHh4eHh4eHh4eEx+GEKnNzY2IjHH39c/e3II4/EkUceaU332WefLTNn6wa8csdj0IEUO1654+Hh4eHh4eHh4eHh4eERD0/ueAw6eLcsDw8PDw8PDw8PDw8PDw93OJE7QRCMDoLg3iAIZgVBMDMIgi9WOmMe6y+8csfDw8PDw8PDw8PDw8PDwx2uMXeuAfBoGIbfCYKgDsCwCubJYz2HV+54eHh4eHh4eHh4eHh4eLgjVrkTBMFIAPsB+BMAhGHYHYZhS4Xz5eGIDz/8cJ0jQXhA5UrjhRdewL333lvx53h4eHh4eHh4eHh4eHh4VAoubllbAVgG4C9BEEwNguCPQRAMr3C+PBwwf/58TJw4EU8++eRAZyVT9Kdb1nXXXYfzzjuv4s/x8PDw8PDw8PDw8PDw8KgUXMidGgB7ALgpDMPdAbQB+KW8KAiCk4IgeCMIgjeWLVuWcTY9NLS0tCAMQzQ3Nye6p7W1tYK5Kh/96ZaVy+X6RSHk4eHh4eHh4eHh4eGxPqKpqWlAn3/88cdjyy23xG677Ybtt98ev/71ryv+zAsuuABXXHGF+v2mm26K3XbbDdtssw0OP/xwvPvuu5k804XcmQ9gfhiGr/Z9vhcFsqcIYRj+PgzDPcMw3HODDTbIJHMedqRxXzrmmGPw4x//uFJZygT9qdwJw9CTOx4eHh4eHh4eHh4eHusIent7S767/PLLMW3aNEybNg233norPvroowHIWQE///nPMW3aNLz//vs48sgj8ZWvfAVZCGRiyZ0wDBcDmBcEwXZ9X30VQDbUkkdZSEPuLFu2rKjhPP3007jtttsyz1s56E/lTj6fX+diFnl4eHh4rF9oa2vD9ttvj5deemmgs+Lh4cHwhS98AX/+858HOhseHoMS06ZNwxe+8AXsuuuuOOyww7By5UosXboUn/3sZwEA06dPRxAE+OSTTwAAW2+9Ndrb27Fs2TIcccQR2GuvvbDXXnvhxRdfBFBQxJx00kk48MADceyxxxqf29nZCQAYPrwQaeapp57C7rvvjl122QUnnngiurq6AABbbLEFli9fDgB44403sP/++0fPOfHEE7H//vtjq622wrXXXhulffHFF2O77bbD1772NcyePdupHo488kgceOCBuOuuu1yrzgjX07L+G8CdfSdlfQjghLKf7FE20pA7YRgil8tFn3//+9/jzTfftHaA/kZ/BlT25I6Hh4eHx1DHsmXLMHv2bMycORN77733QGfHw8OjD9OmTcPMmTMHOhvrBZYuXYoNNtgAQRAMdFYGN049FZg2Lds0d9sNuPrqxLcde+yxuO666/DlL38Z5513Hn7961/j6quvRmdnJ1pbW/H8889jzz33xPPPP4999tkHG264IYYNG4Yf/OAH+PnPf4599tkHn3zyCb7+9a9H/WzKlCl44YUX0NjYWPK8M844AxdddBHmzJmDn/3sZ9hwww3R2dmJ448/Hk899RS23XZbHHvssbjppptw6qmnWvM+a9YsPPPMM1i9ejW22247/Nd//RdmzJiBv/71r5g6dSp6e3uxxx57RERVHPbYYw/MmjUrcR1KOJE7YRhOA7Bn2U/zyBRpSJB8Pl9E7gxGcqO/3bIGW/k9PDw8PDySgOYx72bs4TG44GM79g+WLVuGCRMm4J///Ce+8Y1vDHR2ysLy5cuxaNEi7LLLLgOdlYpi1apVaGlpwZe//GUAwHHHHYfvfve7AIC9994bL774IiZPnoyzzjoLjz76KMIwxL777gsAePLJJ4ti1LS2tmL16tUAgEMOOUQldoCCW9Z3vvMdrFmzBl/96lfx0ksvYfjw4dhyyy2x7bbbRvm44YYbYsmdf/u3f0N9fT3q6+ux4YYbYsmSJXj++edx2GGHYdiwYVFeXJHVetRVueMxCJHGmJMxZiTZMxjg3bI8PDw8PDzc4ckdD4/BCW9n9g9aWlrQ09ODpUuXDnRWysYVV1yB22+/HQsWLKjMA1IobPob++67L55//nl8/PHHOPTQQ3HppZciCAIcfPDBAAr96uWXX1ZJHHK1euCBB6KgyX/84x+LrmlqasL++++PF154AQceeKAxHzU1NdG8Sq5chPr6+uj/1dXVUYyftMqxqVOnYs89y9fSuARU9hikyMItK5/PDzpj0Ct3PDw8PDw8kmOwzeceHus7BqOdPVTw/PPP48QTT3Sy02ltsy7Y9GvWrEFbW9tAZ6PiGDVqFMaMGYPnn38eAHD77bdHKp799tsPd9xxB7bZZhtUVVVh7NixePjhh/GlL30JAHDggQfi+uuvj9KapriZHXbYYVHwZEma9Pb24tVXX8XWW2+N7bffHnPnzsWcOXNK8rHFFltgypQpAID77rsvtkz77bcfHnjgAXR0dGD16tV46KGHnOrivvvuw+OPP47/+I//cLreBk/uDGGkdcuSyp3BNul45Q5w//33Y+eddx50qioPDw8Pj8GH/twU8fDwcEPW/fK5555DEARRgNd1HU899RT+8pe/ONnC/Rmvs9IYjGuzLNDe3o4JEyZE/6688krceuutOOOMM7Drrrti2rRpOO+88wAUSBWgQJYAwD777IPRo0djzJgxAIBrr70Wb7zxBnbddVfsuOOO+N3vfueUhzPOOAO77bYbdt11V+yyyy44/PDD0dDQgL/85S/47ne/i1122QVVVVXRydLnn38+TjnlFOy7776orq6OTX+PPfbAkUceid122w1HHHFE5Eam4aqrroqOQr/jjjvw9NNPI4sTx71b1hBGGhJkKCh3+nOAHqzKnZkzZ+Kdd95BT0+P02Di4eHh4bH+wrtleXgMPmRtz1566aUAgNdeew0HHXRQJmkOZtC4lsvlUFNjX7L258ZwpZHL5daJckiY+sErr7yifk8nZAHAWWedhbPOOiv6PH78eNxzzz0l91xwwQXG599yyy3G37761a9i6tSpJd/vu+++eO+992Kf8/bbb0f/P/vss3H22Wcbn0X32/JaDrxyZwgjC7csGYNnMKA/dyAHq3LHG+oeHh4eHq7wc4aHx+BD1oQDpbe+nAZF5U2i3BmMNn1SDNa1icfQgCd3hjCyCqg82IxB75blJfYeHh4eHu7w5M7gxGBVB3v0D4iUyKpfUluqqlo/lm9cuROHdY3c8WO5R1qsH6PDOoqsjkJPM4D09PQkvscVPqDyuuU77OHhsX5h7ty56O7uHuhsrFfw5M7gxLbbboubb755oLPhMUDI2pYbzMqd6dOnZz7+eOWOh0dyeHJnCCGXy+Gf//xniRHX38qdDz74AMOGDcO7776b6D5XeOWON9Q9PPobP/nJT7DhhhsOdDaGPLq7u7Hzzjtbfds9soefMwYn5s6di7lz5w50NjwGCFnbs4NVufPxxx9jt912w2OPPZZpummUO+vCGFiptclgXO94xCPpextco4OHFU8//TQOPfRQzJgxA8DAHYU+f/589Pb2Yt68eYnuc4UPqOzdsjzsePXVVxEEQXR8pEf5uOmmm7Bs2bKBzsaQR3d3N9ra2rBy5cqBzsp6BT9nDE4MxriGHv2H9UW509raCgBYtWpVpunSeNbb2xt77bqk3MnlcpmPGw0NDVixYsU6UT/rE8IwxIoVK9DQ0OB8jz8tawihs7Oz6O9AHYWeRCaZBv0dUHkwGl7r0g6ER/Z4/PHHAQCPPfaY9ZhFD4/+Rpqxa9q0aVi6dCkOPPDASmVrnYdX7gxODFYbw6N/sL4od7Iq53vvvYcFCxbggAMOKErXu2WVjwkTJmD+/Pl+E2sIoqGhARMmTHC+3pM7QwjSaM4ioHKaXSUaZF2Y9DTozwF6sCt3vFHooYHaxWAz8Dw80oxdl112Gd58803MmjWrUtla5+HnjMEJr9xZv5F1QOXBqtzJqpyXXXYZnn76aXz44YcA1u+AylmXo7a2FltuuWWmaXoMTviVwRCCHOTSDGRZuGXR9ZUidwbzUegdHR245JJLKhpQGvASew87qA9WV1cPcE48PIqRhmTo6emp2HyyvsCTO4MP/p14DHblzg9/+EOceOKJZaeTldq8u7u7KBh/GuWOlodnn30WCxYsKCtv/Qmv+PMoB57cGUIwBVLu74DKlXbLGswBlSdPnoyzzz4bU6ZMqWCuvFuWhx1eueMxWJFmQZvL5So2n6wv8ETC4IN/Jx6DLebO7NmzsWTJkujz+++/j/fffz+zfJVbTrkBnZVy54gjjsC1115bVt76E7lczm/ueqSGXxkMIWRB7mRxFHp/uWUNxoDKVOZKL0S8Uehhgyd3PAYr0ozfntwpH37OGHzw78RjsCl3DjvsMFxwwQXR56zcf7Jyy9LWKDz9uHsBva67urrQ1dVVVt76E+uSi5lH/8OvDIYQpKGQNuZOVm5ZQzGgcmdnZ9EAn3Ri668B17tlDU7MmTMHu+yyy4AHpKO+58kdj8GGNGOXJ3fKhycSBh+8AtejUsqdtHN/a2sr1qxZU5ReFnnLqpwyP1kpd4aam5MndzzKgV8ZJER7ezvOPPNMdHR09PuzTYodH1DZHd/73vfwk5/8JPqcVLnTXwOuNwqzw/HHH4/bbrstk7TeeustvP3225g7d24m6aWFV+54DFakIRmGmuE9mOEXA4MH69MmzSOPPOLjZinIOqAytaW0blnyiO2slDuVcstKEuPTZp8PtcDmntzxKAd+ZZAQr7zyCi6//HK89tpr/f5sU0Dlct2yku6YDmXlzsKFC7Fw4cLo82BX7gylyWiw4uGHH8aLL76YSVoUSHugVQae3PEYrKi0W1YYhnjjjTdS5W1dxvo0Z4RhiDlz5gx0NmLh+k6mTJmCZ555pj+yVBHMnj0bBx10EB599NGBzsqgQ6Xcssohd+QaIEu3rHLTkmuSNModrb9J0miww2/wepQDvzJIiKxZ+CSoVEBlnrYLhrJyR5N8pim7d8saOshyx4bInYGecD254zFYUemAys8++yz22msvzJ49O1X+1lWsT+TOyy+/jG222WbQtwFXG+2SSy7B//zP//RHliqC9vZ2ABgQRftgx2ALqNzb21v2oSq2fA3WmDuDUR36zjvvGEnq/lpreKyb8CuDhBhINjUrckcbOJOqf4DKn5ZViTqWA7xX7qz7yHJS98qdAjo7O3H22Wd7Y96jBJV2y1q1ahUAYPXq1ckztw5jfZozmpubAQArV64c4JzY4fpOenp6orllKKLSNuFQRqWUO2nTG+xuWZWKuTMY3bJ+9KMf4fTTT1d/825ZHuXAkzsJMZjInTSDfJbkTqWUO5VUrUilTlpyp9Lv30sys0MlyJ2Bfi/0/Orq6gF5/quvvopLLrkEL7/88oA832PwIq0a1HVh6MdGHUOR3GlubsaKFSsS3zdUyATXdzIYF55J4PukGZVS7qS1j3t7eyvillXpmDvrIrnT3t4eqd4kfJ/yKAee3EmIgexwJsVOOTukaeMj8L9ZYzC7ZXnlztBDJdyy+mNRMWfOHFx66aXqbwOt3PGGh4cJlXbLWhd3NJ988kncfvvtZaUxFOeMH/7whzj++OMT3zdUyB3XcVK6ogxGTJ48GTvuuKOq1hzIcAWDHVm711RCuZPFe6vUUehZxdwZjG5Z+XzeuEm+Ls5zHv0HT+4kxEB2uCwCKktW3NUg7O7uxj/+8Y+ia4eicqdct6z1PeZOS0sLfvazn6Gzs3Ogs4Kenh6cf/75se4ZQ1W5c++99+KXv/wl2traSn4bLOTOYGufHgMPT+4kx80334xLLrmkrDQG65xhw/Lly1Mpd4YKkTUYlDtZKTPeeecdzJw5U3WF82S/GYNRuTMU3LJk31kXlTue3PGoFDy5kxCDyS0rLbmTRrnzyCOP4LDDDsN77723XgdU7q8Bd7AaSy+88AKuu+46TJs2baCzghkzZuDCCy+MPWWkEuROf+yy2p5F3w00uTPY2qfHwCMLRWnW6Q92ZLHAGiqEB4d0EXHFUFHuuL4TF+XOa6+9hr333jvxxsrEiRPx+9//PtE9GmxlqbSaeygj6/FqXY+5I8tHf8s9Cj2LvGWNXC5nLJdXw3mUA0/uJMRQJ3ekEeGaBvmFdnZ2VtywqmQdazF3ktYfpVNJZGmoT5o0CTNnziw7HaCg4AIGhxFHk2J/7opmodx54403MGPGDOdnaZP/YFPuhGGISy+9FEuXLh2Q/HgMHnjlTjxeeeUVTJ8+PfqcBQE9FMmdJO+dY6iU1dWWcZmjpk6dipdffhnLli1LlIe5c+fi448/TnSPBludD1XC9frrr8fNN98MAFi6dGkm9SSR9XhVTnqa7Z61W1YWR6Hz9LJQ7iRx7epP5PN5YyD1dWGe8xg4eHInIQZyEpPPTmPgSDbctTx8oB0sblmmQGQ2ZKXcqfT7z1Jif/DBB2PHHXcsOx1g8JwWBSSLZzCYlDunnHIKzjrrrLKelZbcOe6443DBBRckukeDHD/mzZuHX/7yl3jooYfKTttjaCMtueO6g7wuGL2nnHIKzj333Ojz+krueOUOot/jypJmJ5/smyz6iotyZyi1PQC46667cM899wAAzjzzTHzve9/L/BmDyS1L2xAbbMod2bezOC1rsJKPNuXOujDPeQwcPLmTEAM5iWXllgUkj9tDAxCP2TOQAZXnzp2LUaNGYerUqYnTLmdi66+YO4N1MhpMyh3XvlgJcqec9Do7O6N6tIH6XJbkzuuvv564z2iQfdTL8j0IaYzSJPPqUF1IcnR1dRXt2GahLhyK5A4pd9577z1MmTLF+b6hUtYslTtpCC2tL7a1taGrq8s5DZ5Hnqb2HFsZqqqq8N///d8l369YsSKxGqlcnH/++fjTn/5UZM+uXLlSjSfkiscff9zqQj0YAiprY2dW9lHWblkmGyNNHgbreJHPx8fcseU5n8/jX//6lyeAPErgyZ2EGMhFd1YBldOkMdiUO0uWLEFvby8WLFiQKO1yyZ2h6JaVJbJW7rz66qt45JFHUt3rusgbbKdl9fb2OrWfSih30u6Um57vyR0PiTRjV5K5bF3Y0azEiTWDdc6wgcajc889Fz/84Q+d70tCdNx///346KOPUuexHPB3cvPNN+OVV15Rr3NR7qSx97S+8o1vfAO//OUvndMg2Owyl/cRhiGuv/76ku/Hjx+PDTfcMHF+ysHf//53PPzww0X13tvbm9qmnTlzJr7+9a/jiSeeKPltMCp3KnEUehrSvbOzs4RolG0pSV831c1gHRtdYu7Y3s3kyZPxrW99K5MNO491C57cSYiBNCxNyp1y3IpcBz0+0CZdyL3wwgv44IMPEufRVq60E6aUKA/WgMqD9eSTrJU7l112GX7xi1+kuneoKnfkws4EF+VOUpRjwGrP1wyx5uZmT/Ksx0jrlsX/2uDJHR2Ddc6wgZQ7HR0d6hHbJiRZ8B1xxBHYY489UuexHPB3cu655+KWW24xXldJ5Q5Pe+HChVi4cKFzGjyPMi3CUFPTUX1ze7anp8cY/yQOdKKlFiog6/GqEsqdgXLLamxsxCabbKKmsz64Zbkod2zvhsdC9fDg8OROQiQdJJ599tnMdo0Gg1tWGuXOcccdh9/+9rfOeXSVI8ZdY7rPK3fSI2vlTjkGVVrJ+5QpU/DWW2+leqZW/qRkiTyKNMmzCGnbYdbkjmynHR0d2HLLLXHXXXeV/QyPoYk0Y3MacmewjY1J4JU7BZByJ2lg5aRlbWlpSZO9ssHbqq2MLsqdNOpIbfc/bRBrW7+L65ODjXAkuy8r5Y5tPh5Myp3B6JbV3Nxc9Nm0RnFpsya1y2AdG13InUqsgwYCixcv9iRUP8KTOwmRtDMdc8wxuPzyyyvy7HICKicliPigmXQHqauryynGiMyji3In6QQnJ7Kkyp3+2qEarIN21sodF6PWhLTKnT333BO77rprqmdK5c6SJUvQ1NRklNtryOVyTm2OJn3baVlJ20ellTtr1qxBa2srlixZUvYzBgqDbSEy1DCU3LKee+45PP7442WnkxTSPTJL19HBNmfYwImdNIqUuHsGui/zvmCb65Iod9L0qyzInaTKndbW1sQbgf0Feh+S3Em70WSzRbK25cpR7gylgMqy7SY5Cl3mYbCSO+UGVO6vGKBZYOONN8Yhhxwy0NnAypUrUx3GM9TgyZ2ESDqAdXZ2ZtaQslDuSKMojXKHT4au+c5aHZN2sB5qyp3BNmhn4ZbEkdbQpHvj8pL1pC7VNEuWLEFXVxc++eQT5zRMyp2f/exnGDFihPFZHOUod7Ig5mT7pPxQnstptw8++CCOOuqoMnOYHoOtzw01pBm7Bsot66KLLsL5559fVhr5fB7XXHNN5JrhAk25U255BusCxgZO7CQhAJK6kw8UJLljW8i5xtwpN6ByJcgdmbeuri5svvnmkYIzTQDnSsLkllWucsdWN4PJLauSMXfKTcu0RsnCLWugxwMJF+VOJTa5BwpaTKr+xg477ICf//znA52NisOTOwmRlFDJ5XKJVCs2VNIty1USzMkR14kwqewziXInqSE71GLuDDZDXSp3Vq1ahR122AHTp09Pld5QJXdMu0suMJE71113HdasWVPyLBu5M9iUO1mQf88//zzuu+++MnOYHkPFUBqs6K+YO1n06a6urrL7w6RJk3DqqafizDPPdL6nv9yyuru7M6mn5uZm3HnnnWWnI0HjUVLS2dVuGWjFCG+rtrnORbmTRjWcpVtWEuVOZ2cnWlpasGjRIgDIzAbOCtTfwnDtaVmVUu5krfYux6YxKXeyyFtW47Jco2QRc2ew2tMuAZVtec5aFVYpuNpUra2tWL58eUXzks/nUV1dXdFnDAZ4cichki7mcrlc6glDIm28HC2NpARROQGVk04elWSsNeVO0vvTPDcpspa4ZgVJOCxYsACzZs3CO++8kyq9csgdlzrKevIzkTtJDW6X610CKg+WmDuS3Cmnf5TTJrKAJ3fKQ9o+wf+6pJ/Fe+rq6iq7rVGbp4WsC/qL3Jk4cSL+8Ic/lJUuABx99NE45phj8P7775edFke5bllDTblTTsydrJQ7Ls/S4KLcMakukih37r77bpx88smJ85cEWQdUtqlWsrYZy0lPIwySbnDG5SsrmzVL5U6W5E4ul0sds1FifVHuuNb75ptvjg022KCiecnlcolPmR2KWPdLmDGSsvC9vb2DWrnjOuiVE1CZdkhcUclFu4ncSULWadd3dnZi6623zkx2mJVbVtY7l1K5U+6EXmnlTqXIHfnspModl+ttyp20u4GS3Jk/f36qBZtpDNLIncMOOwx//vOfE6U9kDtRg91QGuwYSjF3uru7yyYA6uvrASQ7sUSSO1nE3JH1HoYh5s2bh3nz5pWVLlAg8QH9NKByUG5A5e7ubtx4441GG2uglTuViLmTpJ74PHH//ffj3XffrahblmlhnsQGfuyxx/C3v/0tcf6SgN4HfydZBFR2qZtykUXMnUq6ZWVF7pg2kFzuNbllZfEOHnzwQey2225YvHhx2WlJcueaa67BT3/60+g3/lfDUIm549qv+iPwfS6X88odj1IkHSS4W9Y+++yD7373u5k9OwsjOukOGDdCXA2EpIZrJd2y5MIx6URpmjxWrVqFDz/8ELNnz06UHxOy2mnIeufSRG6Uo74Zym5ZaSbXgVbu8PQ222wzbLvttonS0J5vc8t69tln8cYbbzinncvlMttNTIOBJJbWBVTaLStLN4csyZ0k6oRKKndM8bDKARnDWc8naWPuUJleeeUVnHzyyZg8ebIxfY6TTjoJN998c/oMJwS3U2ykiss8mKbd83H6iCOOwE477VRRtyz5l+6hvlFXVxf7nPb29uj6JUuW4LHHHkuc1zho5E5PT0+Rm1YS2N7NYFfuZLWZkhWBkjZ0hC0PWY6Fzc3NyOfzaG1tLTstOe49++yzePLJJwEkU+70t80yY8YMfOYzn3Gug4Em2Tk8ueOhohxy58UXX8S9996b+tkm5U6SQT6ta5fmllWpmDtJBrWkE5xcNCZNx1RfWQ+yWaXHJ8Ssdrp5uuWSO+uKcidJ+nFHodN7omcNxtOy5ALS5pblevQ7IanbZ1q89957mDlzJoDi/IZhiCeffBLHH398RZ+/riJN2xzKbllkKCYhd2SfKGeB1dLSgr333htz5syJ0gKyJcGojGnTuvHGG/H666+XfE9kc9KYO/TuSS1lcqeRaT788MN4+umnnZ9TLgZauaP1lXLJHZvrkantUd+ora2NfQ4nd37/+9/j4IMPTpzXOGhuWbbTKeNgG5MqZRtmSe4MZreswRZzx2aXJYVU7vAYcJVcB5WLt956CzNmzMD8+fOdrvfkTv/DkzsJkWQAo12AweyW5ZqG5pblaiAknTxc1DRpB2uTcsc1nSwmj9bWVqxevdp6TSXcsrJoh1krd8ohd1zabqXInXIIVlKmxD0j69OyqB9WIqAy/dXIHVelEr+e/60UTj311Ci2gxwTnnzySdx6662DXu48GJFm7ErST7M0aLu7u8vuD3T/QCl3/vGPf+Dll1/GhRdeGKXF/2bRjyhGQdq0zjrrLNx2220l33PlThrSQm42SNC7ofx3dXU5nWrW0tKCa665BjfccINznmz5dCF34tSKad6npix1UQmZ8sjz8cwzzyAIAkydOtVoT8r35KLc6ejoQHd3N8IwREdHh7MbcxLQXCiVO/xvEtiI1CxJViD5+NrW1lZCYFWC3KmUWxb9TXIU+lAhd4jY5mS1tH9c7Nv+tlOkvRcHT+70Pzy5E4Pe3l7MmjUr+pykMyXtAHFIS8xoeUpKEA2EcqcSi3aZl6SDo8kNJ0l+jj32WPzgBz+wXlMJt6yOjo6y0gIqG3Pnsssuw5577pno3rhnV8otyyQ/d0GckkUaDzZyJ6liiP8tB7Lf2Nyy0p6Ek9U7M2HNmjXRQo/XST6fjxQBlc6DCS+++CLOOOOMAXl2uai0W1aW7SMLtyxq8+WQO+XE3Imbi7Kop3LdskyENo+5k8Yti+YjUxkpv0nJnUsvvRSnnnpqFP8iLeT4aHPL4n/TXmO6R5LtaeYA2a9Jhf7CCy8YCUXpluWq3AGKidesx2GyA7kbVhbKHS2fcTbmVVddhcsvvzzxs1xsjjAMMXHiRPzxj38EoLfDcohloPBuzznnnOikz3KJBtlnsoy5kwXRnbVyh//lSlKX95w1ceiKJIQbvy4IgorlyRX5vD8tywOFXbGdd945Op4tyQRLHU8qJtIOCoNBuZMk5s7ixYvR0dGROH6Gy6CWlrGWExndf9999+G0005Lnbck72LZsmVYtmyZ03PKHbR5W8uC3KmkcueDDz7A3LlzE93L86DBVo9pjJAsTstyJXeyVu7YyKKkMJV/KCl3+NG3vJ+EYRiROwO147TPPvvgiiuuGJBnl4s0fWIou2UNtHKH7iPDWY7JWfSjct2yTGNAWuWOdF3NWrlDytpyT1WhfMaNvS4LWPk+29racOaZZ1oDeZvInTRtQvZrem5jY6OxzfFFK5CM3NFcVLKC5pZVKeVO3Hj44IMP4sEHHwQA/OY3v8Ghhx4am3f+N+7axYsXR+4zlVDuvP7667j44oujuFflvivZlpLYmKa67i/lzpo1a/CFL3zB+TQtSSwOFbcs2WfiIMfhgUQu50/L8kAheFYul4sm+yzInRUrVqTKi3x2mgFL3uOaRhrlzuc//3n83//9X2LD1WXySkt+mGLuHHXUUbjyyitj78+C3HGpj6zcsvpLuVOOaxU3CNPsStrusbXvrq4u3HTTTTj33HOdn1nuaVm0U+jilmVbEKTZsZE7k+W0rTjlDm+//B27oL/IHX70LX/WYCB3Ko05c+YkIlKToL+UO1m5ZQ0G5U4lyJ0slTvlumVphDaNhaQkKccty0W5E4Yhuru7nciduHSBAglxzjnnWN+73OHOUrnzwgsv4PLLL7cGq9fmCY3cOf/88/H973/fmA5Q2q9pjGxoaDDaA/I9pSV3KuGWJcmdSsfcMZWhp6cnysO7774bSwwkGf/i3gv9v5z6tal200DmdSjF3FmwYAFeffVVTJ8+PfruhRdewMqVK6355eROko33gSJ3ZL7jQNcNtGKG1n8DnY/+gCd3YmDaiSiH3IlTbZhQrnJH7t4kSYNf79qxly1bhhUrViQ2XJMw1kkHa5mXNPdr9yWZPJKQO+VORnxCTHJUrwlyAi83n9zQTKvwSGIQc3R2duKRRx7B/fff7/zMcmPuuLTbJMqdcsidcsg++XyTgZeGhOpP5Y5m0A8mcqdSRtsPf/hDnHrqqZmkFYYhbr311qg9pRkTkpLjSdM3IQtyJ6lyh0iNfD6P2bNn49133y2L3IlbyKRJ97777is62TMLtyyZD54/IryT2jJJlDt0bRJyhz9L4sUXX8TFF1+MV199NTafWSh35JjqMkaZ5if5nClTpsSeaCjbFfX3hoYGo00q3bJsMXfoWlflThiGePbZZ1ONkZpyh57V38odTmy6qKqSbPzJNpPWLau7uxuffPKJ+ptc55Q7LpvGryzcsipN7si89vb24itf+UrkFsfBN5oprc7OzpKxohLroHJBz0uq3HElVSpl+1G6ntzxKIvcoQY90OTOj3/8Y/zxj38si9xJE1CZDLqkblkuk1daZYucyJLebxpwk7QLl/rIitzJ2i2rkqdl9Te5Q7skSQJNm2LuuObb5XpJ7tiMiDRuWfS3nKM8Zf+Tk73rokZDJcidF198sUSpYlLu5PNrY+5UmmCKQ6WMtra2tihGQrmYPXs2jj/+eDzyyCMA0hmcaZU7YRji7rvvTrUgy+fziRUjGrhh7vpc+nvaaafh5JNPTjxHaull6Zb14osv4qGHHoo+pyV3HnjgASxYsEBdQPK04kgaCUorLqAyV+4QwZAVueMytslx0ETEuPQZ+T4pjzZyx2SvyDwnIRUoj9Teq6qqMlHuUDlcyZ3nn38eBxxwAGbMmGHNtwZqj5zcSeKWlcvl8NxzzxV9NuUzbpHe09NTQnTG5d2W3urVq0velSSw5AZn3Nhz2223YYcddlDHOPmOy52zZJ6HknJHq/eenh7V9uZ5sSl3BqNbFj03qXLH1R0qqzi1Ep7c8YhgYrxdBgk5aRDKJXeSEjOTJk3Cc889p7ojuabBnyknCts9fBJ1hUue0jLWcncw6f1xOwOuE1Dcc7MatHl+BmvMHVrYuBiY3Lhw6Yu2Sb2zsxP5fD4VuWPaoYyDi8y80gGVKb1Vq1Y53xv3fDnWyUVN1v0/KfbZZx9sueWWRd/ZYu5QXxlo5U6lyB2XvuYK6j+0eE5KvPMxOakBP3XqVBx11FF46qmnUue73HpI6pbFbYn29nZ0dHQkniM54jYa0qTLXUWAdOROGIb4zne+g9///vdqPrSTHJOSO3GuIHxRQc9wIXe4zWZK24U8k/mMU+4ksXmovWWh3CGi0wYTucNd7kx2skvMHakojSN3iJx2eZ8SGrmTxC3riSeewP7774/Zs2cX5c/mlmVro0k2uGzj64oVK7DhhhviiSeeKHqmbf3iMvY0Nzejvb09qvNFixbhuOOOi8YuYHC5Zck89Be5Y8q79lwTuSPbvAvh21/kzqpVq/DAAw+UvPM40HWupEpWJ0xLeHLHI4JpUEzi75qVcse0oIzLSz6fR09PTybKnSSGeFpyx6VcaQ1XuUuRRvkj83j33XdHBgbPz2OPPYZ58+apabhO4OVORv2l3EmbT96/4gINv/zyyxg1ahQWLVpU9EwX49pE7pSr3ElL7tjKWemAylkod+Tz5WQvDbKBVu5oGApuWbwOnn/+eQwfPhzNzc1lp1sOmSAh31fSsUvbdHB5Xj6fjxYbtNufBFmRO0ndsnj++T9X9c7KlStxxhlnlCymaFc0K3KHt31KO8mOKs3/0l2P/06gunN9F9LdJ4lyhy9ITeBzQhy547K54Bpzx2Uuo2tc6syV3Emj3KH3yolA0+LWxS2LSA66No7cKad9kx1Lm0r0l8oTB5o7KRanrS3E5ZPXn8t7sM39zc3N6OzsxMKFC4uuLVe5Iwm9M888E7fddhvuu+++knpL8z74PaZNbJe52FQ3WW4YuZA7LmMwf89c/ZlGuVOpTSCJY445Bocffjg++OADAJULqOzJnfLhyZ0YmMidJEaolKQuXbo0VV7SumWRNFAO6EnToOtclDs8XZfJQ7s3jRzxjjvuwOLFi633afWQNm+TJ0/GUUcdhf/5n/8pSe8b3/gGdt9995I0+tMtaygod+hv3K7V/Pnz0d3djSVLlqh50FApcsdEtMaB5/mSSy7B6aefbnxGpY9Cz5LcMRl4aZQ7/UXuZBlQ+cEHH7Qu7g8++GBce+21ifPI6+3DDz9Ee3t7dHJjOUir3Fm4cCFOOOGEIgWd6V27vnOej6TKHeq7aWTcWSt3kpZXkjuA2zjyzDPP4IorrogCr9K9WbplyTKRMZyE7JQkhKyfLJQ7ca4gfFHB+2ccGehC7vDx+aOPPlLfXdKYO7Y2JOe7JG5ZMt1yyB36S2OAdCvS/rq6ZXEbRXNR4ShnYUs2KdmzvA5d2riJLLHl0+bex/ts0veg5UvmR44F/BlpyB0i6Uj9DKx9x2lUJLzOTbYVJwxNc62prgdKuWN79zwvXP1Z6dOy8vl86vibs2bNivIJJHfLqqmpcbq+UuSOnM/WZXhyJwblkDtZxNyZM2cOfvjDH6K3t7cscqe7u1tV7rgOetIg5d/FXS9doeJA1z722GPYYYcd1IFcK3tzczP+8z//E9/85jetaWu7BK6Q7YB20emoSVlO7WQ0mQdTPrX0koK/oywCKlfitCy6P47ckQZVkp1T7Zr+jLnz0ksv4cMPPyxSwJ199tn4v//7v+gamviGknJHvv9KKnd6e3uj41azgMktixs/LsbLBx98gG9/+9tFMUok3njjDefYECYli2tbcwEn6ZPgmWeewS233BIZeTw/aZU75ZA7NDfE9eEvfvGLJUfLJ1WLmJBU3SU3SvjiKoldIeubkNQ+IFx88cXRMcxy7CFjOKlyBzATMLzeXYgKDipznLsTfR8EQVEbiXPlcYm5Q2m/99572GqrrfDiiy+WXENljsunyzwqr8nSLSuNcsdG7sixytUti5NursqdNGQC2aTUB3m7do25w68th4TibllJbMM05I6JOIh7piT06uvrARQTcOUodzQ3SJON+cwzz2DMmDFG25rnV+Y/iw2jrJQ7/Dta3/H6TLJ5maQPHHDAAWhsbMT555/vfA+B+rG0VeOQNKByd3c3Fi1ahNdeey1xHm2gOvVHoXukInfIWJPGDTXwJOTOCSecgD/+8Y945ZVXUpM7+bzulsUVJHFpaAGVk+wYJRnwKU/vvPMOZs2aFUlfOWzpzpkzx5ouv0fe77qDIXfkpCQ+zkhznUzL9aXN2i3LZMykXXAmUe7Qb6tXr8bZZ58dGYIu92jXkHInyRHGaZU7//mf/4nf/va31glbLqAqGXMnDMOyYu7I9ikXMUli7nR0dBQRTaY+NGnSJHz5y1/Gxx9/nDrfHNz1pBzlDrVDvmC85ZZbIsKX0ndduGqqGJ7HgSR3yA2K95m05M6VV16JK6+8MjW5k8/no3zEGZnvvvsu3n///aLvslbuuOSDP4/mAT4fuLxb00KNYFocxeGcc87BP//5z6K0pTHsasxfd911UT81kTu8P5QbUNm2cKb88zabhNwxpU15JSW2pqjLUrkTR+588sknRqLPJeZOUnJHc8uSf5O4ZfX09BjJnTgi4/7770/Uj2Xf4+26HOWOLZ8mGyGpW5aLcke+q7h1TFLlTkNDA4DCO5Jzf5r5SbpFa2Whzx9//DE6OjrU/mYqj218nT9/ftFcHYdyY+6QUou/Z77RxIlHrSwccW1Lw8yZM4v+JoGMq1fJgMo777wzPv/5z1uv+/jjj7HHHntEav44yM2KdRme3IlBUnInDENUV1fjjDPOKLqHkystLS3Oz+fyR5MvatxgSjsTckdYU/IQ5s2bh5tvvrnkdz4ouSh3XALISrgYp3yCe//994vKYyIx+D1XXHEFLrzwQutuoi1v8l1IcsdmBFNeFy1aZFyoDla3rEqclkV/42Lu0G/PPfccLrnkErz00ktF39vusZE7sm/YkDbmTkdHR9Exl1p+TModmxGRRrlD9xOh4jLR3XrrrQiCIHJ5NO0Mmo5Ct7WPnXbaCaNGjYo+m/p9OfFVNNgCKichd6RCs7W1FSeccAIOPPDA6BppzC1atMjonstJt3LJnfb2drXu44hUE+gdaARU0j5x++23489//rOVbNfA03cld/hCkZBULWICv98luCsfA+g9lEPuxLkgpBmbZb9IotxZuXIlfvazn+Huu+8G4KbcsX2nIalypxLkjuz3tt35LGLumNQwvb29mDp1KjbffHPcdNNN6j2VVO7weds0FqR1y3JR7kyZMgVHHHEEnn322ej7U045pYTMlffyfsfft0sblyrYcpU7vN6SvgcO09ogjuRJS+7wGDHlnJalKXfi8u6inCHY6myzzTbDZpttljivWjtx2YCvra3F17/+9RLCRx4W4vJukswbEkmU/BdddBGCIIjm/7g6+O1vf1skYkij3HGJLXjttddi6tSpuO2225zS9eSOR4SkgyF1mOuuu864sE7SERsbG6N0TWy7K7kjFwo2o/qvf/0rfvzjH0dGEDcSpMFieib/m6TMLi4dlN7bb7+NbbfdFpdccknsQpLX36OPPopHHnkk1ugxpRGn3LG5CVAdbrLJJthiiy1i81oO+ku5kwW5E7cLQc+ixb2LMWHrI9wwSRr134WA5JC7NVoZ5QLKxS3LpX088MADmDlzZklcASJ3mpqaYtO48cYbASA6Ttw0BqVR7nz00UdFn039OEu/ecpbFm5Zcied/nLjRpI7m2yyCTbaaCM1PU7+SwMQSEbo7bDDDrj++uuj+3gdlqPcscXccX1Pixcvxty5c1Mrd1zJHbpOXsNjwZSjkDSROwsXLlTngUopd2TMnXLmkHLcsuTpaS4xd2zfaZDz7ECQO3JRq+Whksod/twPP/wQAKJTkuQ9WZA7sj1xt6w4UoHq3raoSuuWRXYN5WfJkiW49tpr8eijjxqfJdURfDxLMuablLxaPl2UOy7jsi0903swjRmuY4TNLUv2xTTjjRZzx6TcsdlsprrJ0nZIE3NHPvfJJ58sUe7w8Ymvz1zGhCTzFz03Cblz5ZVXAlhre0tyk+P111/Hr371Kxx77LHRd5UKqEybgq4qdE/ueERIqtyhxt/Q0FDU8PmklcSo5gx5lm5ZfGLT0pADmNxtjCtHpZU79B3JKZ999tlExolpEo2b2E0TjjSsbYOTrHsNUno7a9YsfPnLX44WV67gZcwy5k4WCwhAJ3dMaUlDzLRo0O7RruH+za6TSVq3LDLgNGNVBptzccuKI8I4Dj/8cOy4444l5A5NiC4TLrW74cOHF+Vf9tVKxtxJY8jYQIS3HAvCMNlR6HIHn+qABw/M5+OPGiZwQ2XSpEn49Kc/jRUrViQmynt7e/HJJ5/gk08+AQB8+ctfjvzsXRZzGjS3LPm+XAzpXC6HZcuWoa2trUhSnYTcyefd3LJMxrjLAt4F/NlUP7lcDjvuuCP++Mc/llwvF3KcXHLJh5yT6d5KBFROQ+7QNVS/lVDuSDLZVG98UZE25k4cuWMj4V3JHZdNEhNh0tvbW+Qmo+XRxS0rbnyyuWWZ5gO6xyXYblpyRz6L7olTT/N+x+stiWtlXPwrnk9bG+V9NaltqOWr0m5ZAxlzx0W5M9Dkjot9LG1A3gZ5m3BR7qRZXyVZD9D4QrApdwjcbS6NcseEv/zlL5GKfPTo0QA8uaPBkzsxkIN3nIFNRkN9fX3RBMonrSQDDB9E05I7pNyRblg2ckeWV+42Am7KHZedewmToaBdQwuo7u7uWMOQ15/JmEm6a8J3BvnvNhkyNypc8goAZ5xxBiZPnoynn37aep/EYFfu8Pv7m9zRTnqwIQxDoww77n3SZK31B4oplUS5k6ZfmZQ7LmnQolUuIGU/qORpWZVQ7tDfctyyJEFIdcD7fhIyhRsq9957L+bNm4ff/OY3ickdmosoXx988EG0w+9CMGtI4pZlS5+TVXSsKk/DBt72XMgdU+BZ3uf5c1966aWiQOdx4Oly2fqqVavUuBBZK3fi4ktoaba0tKix7AhyAZMk5o6J3JH5TDP/9vb24sUXXywhDSqp3DGN7Vm6ZZUbc4fbido9ccSabXyaNGkSPve5zxW12zAsPqnOZi/yfNnKVy65I+vaZYNNW+imUe64bESays7JsSQKqiyVO+W4ZbkSrTbwccUUc0fmPYlyJ8n46prXtDF3CFK5Y2qDLjF30thX5ZA7NuUOhRKRZBWgbyQuXbq0ZJ40zc1AgdwBgNmzZydW7lA9eXLHI7Vyx0bu9Ldyh8gdfl0ulytR8nDIgZR/rjS5Y4otxJGG3OEDP19oc8RN7KZJ06Tc0Y7+465t9Fm7RntO0kGJ18lAxdy54IILMGnSJGv+kpA7VI4s3bJcgipr0mHXPijdsuLIHU4A2sidOKOMT5I8/7lcLpbcyeVyUd5o0Ron6y5HuRMXKyTNLpXpek7U8cUJUOyu5ZJvuZjQTobh7z4O3C2L3Davvfba6B2kJXd4AOkk+eFwIXdcFqpcrcPJHZeyaeSObSFnInc09REAfOlLX8Lpp58emw8CX2RQndvmPU25k6Rtm+bWJG5Z48aNw4QJE2LLJOede++9F0EQYMGCBbH3xrllpVHu/OpXv8I+++yDqVOnAhgcAZWTuGWZ7AuXeVSOpbxdawsqnm4csWYjFY4++mi8/vrr0QIqn88X2bNJTsuytW9bQOU05E6cqybvd0mVO5qi3ZTPOAUGV2m4jMsuyh1ZN3HkW9y4K92yaG7rj6PQTWXJKuZOUqRV7tx9992YPXt2ybWUFm+DrqrSNDZREpuXQOQxwabc0Yhmm3Jno402wgYbbFD0nS0GFq2pcrkchg0bBsArdzR4cicGSQdDMhoaGhqMC+skA4xG7iRVDeTzyd2yTJMBESP8Ow3afa5w2e2i9LgrS1y98ndnmkTTKndM5I5JucPzqgWIlc9JyziXS+709PQUTUhpTsu68cYb8Y9//MOaP5OqhUPuHrmQO7b8JXXL4pNM0vYtlTv8eo3c0Z7F4bpjwxcxSZU7t99+O7bcckv09vaWkDvSwJQ7mUli7hCofZrKltZAc9k1Mync0ih3OLkzb948tLe3I59P55bF63vlypXG8migd88NMd5/05A71Fa107Jk20hD7iRR7uTzbm5Zpmtsu4NJoCl3XMkd/s90ven+OOWObZ7O5wsB1U3llnMvjU0vvPACAGDGjBnG/Nli7vz1r3/FK6+8YsxXXB+he4kAjSNFuHIniVuW5iZiStuF3InLZxLljrQxcrlcZH+kdcuyjQcaechVX7Rxwa+Vz62EW5aJ5HRR7lD8MWlTAOW5ZdlIKBsBaVpnaLDZ/SaCPWvlDicITJswSWBzy8oy5o5tnE8ad1Ebq2xrtB/96Ef4wx/+UJJXSstEMGbtlpWlcsdl3uXXu65feLqyH/M1H5Xb9ZAiPh+s61j3S1gm0ip3KhFzxzQg2wZTmsAGyi3LdRF6ww034OCDD1bLZZswqZMmUe5QGbJ0y0qi3JHkjsY6m+og6aBUrlvWPffcg1122SUaPNMod7gSQiKJckdOSlkqdyZPnow77rjDmA5gP9HBNrmSSoQTijw/ZCjzSSvuaFZX5Y6N3Imrv/nz52PFihXo6uoqOVnI1A/SBpwG1o6RpkVpGkNGPluSTpTncsgdukYuZmtra7HXXnvhmmuuMZLJGrihwtsBtfvp06ejvr4+iqUDAG+99VZJHUvlDu+HSfLDkUS5Y3tPdOoaAMyZMyf6v0ue+HMq4ZaVFBq5Y2v3UgWbz6eLuSOfQXNQ3PzJ38v06dPVZ0gSX8472rwm75Wqqnw+j7POOisKzp5m/qUxgg6aiLuvHOWOdLU2pe3ilhWXT5d5VF7D27VpN96Urja2xhFP/FpO7iQJqBxH7sjTsmybJ6ZxJ27hKd3zef74/TaY5jtbPk1kDCeZksyXadyyTL+XQ+7IvKYhdzQ3JJONmYbccSHPbW6qHEmUO7yt8X7Ky0FplaPcSVLnGqEZhyRuWbY+lSagsnzPtGHOSWWv3CmFJ3diYBoUTYMhJ3d4500bc6dctyz6rVzljibnd1HuuO7cv/rqq3jxxReLro3beeS/SdcKDS4xd+ImdpMhIQ1BzTWD54O/CxdyJ+2gxOskiQyTsHz5cvT09EQqjzQxd7hixZQ/F3KHvicDMG3MHVqYcHLn6quvxi9+8QtjOoCu3EnSB3k9aOQOV+5IFyqJLJQ7cXnXJvCkbllxsSa0vMaRO0mNR56OJieWY0dWyp2amho0NzejubnZON5o4OOBtoP1u9/9Dt3d3XjwwQcBFI4C3nXXXXHppZcWpRPnlpXGCNfInSQbIDNmzMAnn3wSKXcmTpxYlluWjHOkIalbVlLwZ8vTRLTyyDGPvwuX8pvmVlNAZZkmD8r//PPP44477sB1112nlomeQWkTbEda2wIq83HHNq6ZQG1aPj9uQ0CSO3EHE3R3d0e2l8nWS6LckfeYrrO9f9nPkpA7cSSTi3KHk7aS3IkjEQZTzB1eJ9pCtD+VO/J+F9uakITccSV5TJC2F6830zxtwtKlS0v6XxrlTm9vL8IwxDPPPGOM00Nw6V9Zkjta/XISX+alt7fXqB4bDMqdJG5Z2liUVLnD+67sx5SGJ3fs8ORODFwGw0ceeSTqKC4BlZMYkrQQ7ejoKJvc4deRUSmvI5gmHT4hJlHuxA0+q1evjurIZRdDm8jj6pUPhCbCQUtj2bJluOSSS4p2WOLInXKVO/I52qC0ZMkSTJgwAW+//TbCMMRNN91U5O7A88fTTAK+C6sRey5t0Kbc4e/aldwp1y2L6pCTOy0tLbGuWWmVOxoxGoZh1GbilDtam3QlTcmIqqqqKiGM4t6dZmjGKXfivrchTrlDaba3t+Piiy92llHzdLRAydIti4/VSZQ7mlsWtWvb4kmCG768jJSuXMTTiYHksiLT4QRIuW5Z2mlZJmNce+dHH300zjvvPCxevBgNDQ2YOHEili5dGv3ukifebuOUO4ceeijuueee6JrXX389IpMqodyRroVxxCz/x8tmg1xYxu1SyzwsW7Ys+v+LL76Iu+66KwpSSZAkvnyGi3JH9gcqp8y/VjYTyL6KIysIfH5OeloWkTtx46PLaVlx+XTZJJHv1YXcMbVD7bNcfMoy8OfHKXdku+mP07KkTRhnc/DyJg2oLJ9h6782G6GcAyrKccuia1zJAVlPnCCQZY4bwzbaaCPsuuuuRd/ZbCsTMdXT04OXXnoJX/nKVzBlypSia9OQO7SBGYe0MXek3S/tKpNyx/Zu+PteuXIlDjvssCJFr4TJFTEOptOybHWgxXssR7kzY8YM/PSnP/XkjiM8uRODuMXsvHnzcNBBB+H+++8H4BZQOZ/PY968edHJJS7Pb29vT0Xu8IEwjVuWNoG6TECm3UUT1qxZg+7u7oiN52loz5F5MCl3zjvvPDz66KNF91AZXJU7P/rRj3D22WfjueeeM044SU/Lyufz0QCTRLnDB8f77rsPCxYswPXXX4/JkyfjJz/5Cc4888yidHidlEPudHZ2WpUrtrYgF88EKUeuBLmjTer0Hd91WrVqVayyKW3MHU6U8v5Ax4qnUe4kdcuqr6/vF+UOQRraLsaqXLiZdgQvvvhinHPOOfjzn/8cm6ZMhx/fS5BjR1JyR+7gc3JHI0TjYFpomBZu1G5k+ly5I8c8nq8ksLllyTaptau2trbo+PONNtoItbW1iRU03ICPI3f++c9/4te//nWUv+OOOw4XXnghgOzInZ6eHowcORLA2vblotyhd5CU3JH9ku5xDajMyZ0VK1aobSHuFKC0bllx9kNcf5MBqwlxBAxX7gRBYCV3SBEWR+6YFvi2fJnaWZKYO3K8SaPckd8lsbU0csdkF0kiyjZfUUDlIAjQ2NiYqXJnzJgx0Ql43L7ktgDPRxykfcvz0NbWhnHjxuHhhx8uypdWBlm+JJsh5bhl0W+u5I60vXh7M83TNnz00UdFn21uWTblDrVD+htnj/QXuaO9B0me8rxk4ZZ11VVX4R//+Af++Mc/xl4PVC7mjuzz/LpylDuPPvoobrjhhqINuqTkDl3vyZ0+BEEwNwiCt4IgmBYEwRuVztRgQhy5I0+T4QGVTXEccrkcTj31VJx44onOz29ra7MOHHH3a25ZpoGG36ftEtp23uT9ruQO1SMFH+VpvP322zjwwAPVoNQm5Q4NJr/5zW/wzW9+s+geG7mjGTf0XJ43OeHYlDtXXHEFnnjiiSg9cssaMWIEgPRuWXTf6NGjo117WmTI8gRBkGoBww11bTHkEqjOpNyRxmUcEUDXl+uWxQ0VPjkkIXe0BdRDDz2kyv15H7CRO0mUO65GII1HdXV1ickdrZ/LBbzp/SdR7lCblsodeQ+lSXUc51ohywGULr6B7GLuaG5Z/HdXt6w4ckcu4uPIHd6e+KI9Ddlb7lHoVNeLFy+OyB05N8ZBI3c01Z18fm9vL9ra2krGD9fnmtDb2xuN5UnJHWn0u7wTk3LH1S2LyJ2GhgbjXCgXMEnqx0TuEJkv526tbCZI1824+/iOMeVn9OjRVnKHFv3kihA3PmbhlmUjvOS9cvHEN0bkgs02/s6ZMydS/dmer811cmfd1PelPeSi3Bk2bBjq6+udyR3ZD+TCc/Xq1WhpaYlOwNPKWu5R6HxMWrp0KZqbmzFr1qyia7Wyl+OW9cEHH2D77bfHokWLSvJlInekkjstucPboIlISQKbW5Z8z9qGblzso/5yy5LPkaEgNDuU0irXLevVV18FAGy99dbG66m+amtro00fF6RR7mh2Yxypwk8/Nj2L5jmNVI6Dto5aV5FEuXNAGIa7hWG4Z8VyMwhhGnTlBEt/42LuVFdXRzsfLkwxJ3dsA4cJ9FtStyxbuZMYIi7KBqCY3JELw5/+9Kd44okn8Pzzz0fXaxM5L4NmvEnlkqtxyY/2M5EattOyrrrqKtx9991RelSHNnLH9I41cmfUqFGRLHWrrbYqSofKWFdXl2jSfffdd4tcX+KUO6a0qaw231z6fxwRIMmdtG5Z3FDhRk93d3fszqLMO6W1ZMkSHHLIIbj33ntL7uNGCW8/NuWOq1tWXL+ixXhDQ0NJkGZO0NgMTz5OacqdO++8syRYty3mzsKFC4vUAxQc1TXmDhGp/PfFixcb64K/e025I5VlaWPuyLmA8mlz29BgMvIkuUPpSRKJwJU7msqgHOWOi1uWqU319vaipaUFY8eOjdRNMi0beNuzKXdk+Yhkloty7dok6OnpwbBhw1BVVRV74pv8jebhJEaqaePEpNyRZaO+t9FGG0XP1+rKVg5bfdli7sTZD3HvQQZ2J8QRMJzcGTNmjJXcoWfQvF9OzB3Xekuj3CknoDIAbLfddthss82KfrcRVLLdEvhGgcnuSxJQubGxMRG5YyIB6L3MmzcPAKLjlrXFZ9bKHaBUiWoiu7UyuIxHN954I2bPnl10EISsd9N7of/zPNnejcktSyN3ksR/Ibi4vMsy8HYv28lAu2Vp75Mr1fk1lFYatyyN3HG5no4Qd43DmUa5o13vSu709PQUkTj8L9lVfNwB3NqdJ3c8IphIHTnYUWeMi7lTV1cXLfKSLBw0csfFIOTMtlTqJCF3NDm/i3InbsFO0JQ7cjFnY/elckfb1ZcDq23RzMHJHdOEYzstSxpDVPekskmi3OHQyB3Te5SLqDjst99+OOecc6KTe6RyJ24BIZ8fR6QlIXfk7pGtXNqkrpE7BJthZ2t/XA0wa9YsdSeQ9/l8Po+6ujoAunJH2/XgcFXEmdyyXAw7un7FihXG577zzjs45phjIgm6TE97p0cddRR++tOfRp/JcHA9LUuSG++//z423nhjXHPNNWodaDu0UrnDr8lKuWMid+IMd9MuMqUvxxoXckcapGnInZ6enqhstoDKNkOayJ3e3l7U1taWuK265ImPwUnIHSJNNXLHtgsbBypLY2Ojk3KH/yYJj3LIHUKcfcDJHXq2SblTDrmjHYXOy2ob1+Igr4ubfyjmTk1NTYltJkHtwtUty7bJUImYO7L9cnJaKthc25ULucPT4tclccuy5YOUda7KHZONKReeRO5ssskmReXhbShtzB2N3KF5zIXcMblluYyDZD/y0xVNm25aunIN4EIKSHKno6PDOE8ngc0ty1SGNModrV6J6IhT7rS3t+Pll19OFXNH24zj9ZTWLYvKs3Llymg9YIsdSddTmV1dsyQZYlMj29ZVSZQ7UsXDVZj0HF43ce/v5JNPxuOPP16UxroM1xKGAB4PgmBKEAQnVTJDgw2mCUROWlK5U1VVpZI79fX10eSYFbnjEnAracwdk1xU7rzF7WolVRhoblk8gJbML5/Ik5A7cgEt881B5A6XMSZR7khjiJQSNMAmOQqdl4Huq66ujuI3mXZgiVSUuOWWW/Cb3/ym5HuawGix0tnZqe50xxmlrgx/GnJHS8d0j9ZXNH9x206GS8yh1tZW7LDDDjj22GOja7UFdT6/1hUjjXJHLqRNcIm5w8uhPYOTO9KIovYhd8Jl/+RlWLp0KZYvXx59lsodU5uS7if0Oy1W77zzzpIyyHRc3LKyCqjM36d2nQmmXeRyYu5oblm5XA5nn302fvKTn8SWkacH2GPuxC1m6F9NTU1FyR357kidR9/HuWW5LlKoLI2NjbGuhfw3cnFOSu5IwzpuIaOROw0NDRg5cqTRFimH3JGKnSyVO6br4uYfUu7U1dWV2Gam/PdnQOUkyh1pe3IFg6lebOlqNpftuXweq6urswZUlvZQnHJn1apVGDVqVAm5o90nnyVJG3omBZglckcrqzbmPvPMMzjttNPUvNpIBZNyRyuDifh3GQe0zcE4csfklhX3TBu5YyKXk8C2ceai3IkLbG0bX5uamgAUbLfFixdjzpw5ah6PPvpo7L333tGhJUmUOxpJydtfucqd2bNnR9/ZNijpmaQadyV3TJugSZU7caQKJ3Sk/UR/NbcsoEBwmRCGIW688Uacd955ALxyh+NLYRjuAeCbAE4OgmA/eUEQBCcFQfBGEARvcMn9UEccuSOVO/zEJ23BQItsueCPe35a5Q6fWGw79ybjTRtoJftvy7eLwiAMQ6tbFpfhyefyXawk5I50xeDfS5DCgit35KBtU+5odcYX9zZyx2ao0338hCyTcWdyy3rwwQeLXMYI/JQ2KnsatyxXhj8JuSNdgNKSO5pyR1t4T5kyBV/5yleK2pSpD9IE/dhjj0XXasodLtGlts+VHrKvSpSr3HEhd1yUO3IXmSANbZ5+e3t7kSFD5E5a5Q6Rr4sXLy4pg0zH5JalXaPlwZa+XMzKcUsaoia4umVRfZiUO9RetZg7NAa98cYbeO2110ry0N3dXUTA8fR4Xng+pDFualPUDzRyx2VhwPtcJd2yXBcpPT09RuVOHIFB/dDmytbZ2Ym33nqr5H7Zt5K4ZW2wwQaRi7hmi2hKL1MZJFzdslw3VzTIe+PsECJ36uvro3LH5b+cmDu5XA7f/OY38dRTTxXdI10zZP5t5ZfjokbupEl3zpw5xjGX8sx/4+2F3H1N82FSt6zm5maMHTu2Im5ZG220kVoeQB9zJ02ahOuvv17Nq+yDPA8058rTX3kZyM1d2rS29yChkTuSDJN1JNsoz1MStyy6r7293ThPJ4HNtjeRO3wsl+0kiVsWd48/66yz8L3vfU/N46RJkwAU9zsJU/vXNuPkeqScmDv8ehflzkCRO5JUkelq5I5U7tA8J21YG7kjN8Y8udOHMAwX9v1dCuABAJ9Trvl9GIZ7hmG4J/m2rguII3ekcofHjdAWDCQJlrtla9aswYIFC4zPLzegMlAq9TMNNFq5pZScYNrZTrITwSdxbReJd2aZXzlZEeJi7pjIHW1SJXKHE0hy8SoHcZtyRxq5tpg7pokOWCvH1YiAJ598EkuXLi0id0wLDa0eJLlTCeWOfHdxhAVdn0S5YyJEKR2Zb02589prr+GZZ54p6p+uO5WAWbkjyR3Ka5xyx7QYvOeee0r8xmlBXlNTk1q5wxf5JnJH1pvJIAMKbUojd2TMHZknqdyRhk0ScqcSyh1TzB25AIhT7sSROwQb+Q3Y3bL4HKS9+6OPPhpyHufkji2gsqtbVlrlDn9OUuVOJcgdrtyxuWU9/fTTeP/991Vyh49P7777bnR8OwDcdttt2HPPPUv6h5x7kgRU3mCDDVBVVRU9O0vljnTLkqSAbc5wJXdMmxgSfMe4u7sb9fX1UblNyMItq729HY8++mgUByMur+Uod6Stqd1jq9f33nvPiVTgz6eyE7kj7zfNh3Ex7SS5Y7MfNeLiyiuvjDYjpFuW7B+8zfOxlY+RXPG+evXqyK1DEvW8bqRblma7NTY2Yvfddy9RrLi8L4Km/I6zS7JW7nB73SUdDl4fGplhsoH5+Gd6D0nIHZo/W1tbsXr1auNBDXKOqaRyR1MyadDai23ziK4vl9yxbdrayJ2qqirMnTs3WrvIvFIf1ZQ7kiCStovtxCxu0/E01mXEkjtBEAwPgmAE/R/AgQDernTGBgviyB2TckdOuFy5Q0YO7xj/+7//i/3339/4/HIDKvM8UrqmgUYrt7Yo1e6T39tktQTuK2lT7mgTgEb4AOlj7mjfucTckYO3jLkj88l38NK6ZdFCXhIBYRjioIMOwu9+97vouSbljqkeiNwhAyXtUeiyfrTfZD5M7Tnp9/y3csgdTjzKdLXdJEAndySBJckdTlbYlDuSKASAGTNm4N///d9x0knFXrNcGp5EucfzrSl3ZPs3BfI0KXe4UZE05g73uX766aetO2kyHXoub8vlkjuSLIhzy3JR7miEtinmjimegM0ti+YgU/+nwOA8r3HkjnzXlSJ3eLmTxtzhpH5Wblmk3Bk2bJg1oPLxxx+PK664osQQl+TOzTffjB//+MfRNa2treju7i5ZWJnmVtOiiMDJHRoHKknu8HzxsroqZzWUo9xJSu7EuZ5ryh2bq5atrbmQK/K5NuVO3JwKFJM7tvrn/Y6uNyl35HNdY+6sXLkytXLnySefxGmnnRbNgVK5I9PiZdUIdbLTKP3TTjsNX//61/H222+XLG55eV0DKr/zzjslc7ILyUbQlN88H0899VS0iNbSpfLJ9DSYyJ22tjbjPB0H0yaGabNAs7VcyR3bnMTtMBtRKqH1FZPdro3VPC+S3EnqlmVa5xGIhKOyJY25o82l/K+WJw5O7nz961+PQkGYYoRpMXdkQGV52pdt00xu9ntyp4CNALwQBMF0AK8BmBSG4aOVzdbgQVJyx6Tc4TF36Dc+OKxYsQLNzc3G53PSw7ZgNd0PlErpbYs7jSWn6yTjrMG2uJPgi4akAZVNi2AXtywN2vflkjvSLYuIHUnuPPXUU5FPaBK3LFkvtJjjE29tba3R0LQpd6jdmo5Cj2uDckF79tln49JLLy1Kg/5fCXLHptzRJnJtgqAycHcdkzGrtXf+HZ/kJbnjqtzh74vuIaKPjrYl0HgklWpJlDtc7mpS7pjcsuQ4EoZhiVsWTbRxp2VRmjQevPnmm/jqV7+KJ554oiTvHLxsmnJHLo6yCqgsT3sw1ZVEZ2dnZHxpu8uu7jfaaVm9vb1FfcKk3KE65kQXjalBEKjEiDTGtd3TLMkdGuuojBLy3Unipb+UO21tbZHxLuN8Uf3Ld6L1fznGyPHS1C5kOVpbWzF69Ogi5Y5pjDH1RRdyRxsT+LNciQ+ZJ/l/2318UZE25s7TTz+NAw44wPhMjdyx7Wxrz3bZqJP1ZnLL0sb1OHInCbnE32FDQ0PR800L8yRuWWPGjElF7kiil/5SzB2ZJw5NuSNtObLP33rrLeN8nzTmjonccRl76BotoHJraysOPPBA3HbbbdH39913H959992i+/lz0rhlSVLCNe+UR4K2SSvrQo5JvN1p70HLv60dtba2ltSJrUzlKneyIHe0sVQSLp2dnRg+fDjOO++86DpS7rieliXLn1a5E4YhVq1aFdmUJnKnp6fHuDnG1T38WbZNM6/cURCG4YdhGH6m799OYRhe3B8ZGywwkTty0pIBleWiOS6gMh/YW1tbo9OPOENeLrljU+6YOq9WfrlAtj3XZbKKU+7YAipLgoCQltyhNP7whz9EixhbQGWToe3iliV3Xv7+97/jsssuK1r4m4wlfp9sR5zpdlHu2MidcpU7chK45JJL8Mtf/rLoXrq/EuSOra9oC1ttsqNy8wnCVH6be4gsI90rjUC5uJPvR+sHkggl8LgrSckdul47SUQaLSa3LM1QzufzRdfTtTJGgWlHkCZ3MhB4jDftOFONuOF1Iesm7VHoktyRbcLWRjg6OzsjVzVbzB2TAUkwKXf42Ez/XnvtNfzjH/+I7qUxj+94UVsaO3ZsKrcsboj39vaiurq6rJg7SZU7lSJ3enp6Ssgd/m4+85nP4Oqrr44WI1o/lAtnrY9ri5vm5mbjLrVpPJUKFk460/W2RQlP21Qf9ByZL552UnKHz+mmscGUXjluWT/96U/x7LPPlhDncuNCsy9cy0j3Pvfcc/jTn/6k5kuO9SZyR4sZZivvJ598YiXctLQ4uWOLuSPzGqfg7ujocFbuyIU9jYuE7u5uhGEYvTdbWppLjByvJ06cCKA4RpGmcKN5zBZzRz6Lfnch2Qh0jabc6ezsjIhl+v473/lO0amWcWsADvpNKneA0lOKbO+Yg9+nqfLlfCLbqE25I8tSLrmzaNGiku9sxIZpncDrRhIyfE51PS1Lm/slYfLss88CAB544IEScqdctyxpp1544YVFZKNmB/Lxw0QM2pQ7lGY55I4/LcvDSFLIwU4LqMw7hBZQWRpUdP3NN9+ML33pS0WDV7kBlYFSGbptYJfl5gOttkMlod1nAh/k+WKC7rXF3Emi3JExdzTQ96Qu+eijj6JBhu+6cpUFf7Ykd0xHoXMCh/JKsUg6OjoSuWWZyB0eIygtueOq3JGD/1tvvYXVq1erkwBQ2o54PvqT3JH5trllkdHMFwey/FpdckNfTnJA6aSVxC3L5MJIKEe540LuaAtl7Xf6y2M4yWuTBlSmNPiYQRJ8Dm3hI92yTIujcpQ7csdJXmcCV+7ExdxpaWlRXVQBc0Bl3napHVx99dU488wzo3uJ3NGUO+PGjbMGVDbNS7weslDuaOROe3s7giDAnXfeaSR3NEIyCbnT0tKC008/Hddee23UV21HoS9YsAALFiyIxhutXfM602wDnibdP336dIwfPz4Ktkz9Qs4d2hhXV1cXBRaWebKR+Lb6kvdrY4JGHLmmy+2EpModvlETF1CZ8k19gMAXLfyZNuWOK7lD7+zmm2+O1LsS/H3yti/nMT4eutiIWswcDS7kjmYvk4qYl1MDkfRp3bLk3NfT04OWlharqyTBNsfR+6UAxh988EHJmM7r2dUti99P+XN5DwRKTyN3pN1lGt94nu6++25cddVV1mdp5I60tW1tjb//OOWOycbiZTSROybCW8sffba5ZX300Ucl3/X09GDu3LlqWqaNF1M+pHInaUBlG8lBgaA/+9nPRtdlFVCZv7fbbrsN559/Pi688MLoOxkMmdY9JluI9zmTcofP37Zy9/T04LOf/SyefPJJ75blUQoTySF3JJIEVKbJUQ7slOaKFSvQ1dVV5FbDO38ScofnQbLBLuSONjjxa3O5HNrb27HzzjvjxRdfLLk/bsEOFE8O2u5cf7plURoTJkwAUFgs8nct61wOPNIgqK6ujnXLorZBf/lurMktyxSMLpfLFS14OLljMjS17yW5E6fckW3pC1/4Am644QajfHPhwoUlhFfcLmMacscUp4ryJMtuc++QrpVAaT3YlDuS5DMZJppbVldXF1544YWi9Pg99FdOWiZyhxYIMh0OvguolUUrA8Gk3OFkobzWNaAyjQeUL97XSYKvlYPfI4kuTWUprzOB70L96U9/wsKFCwGUugeY6kqCZNTyWqnceeaZZzBmzBj885//LCknYA6oLBfyNBfx7zXlDv3fpNyRu5OVJnfy+dLTsiio9nnnnVfy7myEZBJyZ/Lkyfi///s/nHLKKXjjjTeispjIHV6/2pgjyR0ak0071pT2J598gjAMo/bmuvnDlTtkd0glm6yXNOSOtsDiZdXSsPU3Tu7YCG/teyJD0ih3RowYAaA0Nl6W5A5fPJtcJSS5wtuHafyy1TXPqwupIElhoBAYmNsZ8nlhGBaRYrZ6X7p0KQCd3NEWuHHkTnd3d9Q3ZJ4keJw003hNf3lQdHmt5pZle67sa3E2kDZna25ZcqxwJXdMqjHplpWW3OG/8f5UrnJH2hkmtywtf1IJouVfI3fuuecebLnllnj55ZdL0pZ/tfcgx4skblktLS245JJL1HSlDUtqLd6+KhFzhzbWuA2qzYeu5I5U7kjCMk6509raijfffBPTp0/3blkepTAt4iSTnSSgMv0mOzp95pODNojKQc/FJxMo3am0DXg2UkuSJEuWLME777yDt99+u+R+F3InTrljOwpd+w5AkfpF+z2O3Nlss80AAB9//HHRIldOHnHkjmSq6RobubNixQrjroVcJPM80HVcuUPPTarcoUUXvQ+u3CFXMy1/VE/t7e1YuXJl0YDMnzN79mxj+8+K3DnrrLMwefLkoutskwGVU4Kuo/fT0NBgLH+cW5ZGRsqTRDTlzlVXXYV9990XTz31VAlRyPNhcsvKWrkjDS4JEympkTvyN9NCg64jckMS6oAun9ZIdqnc4XXT2dkZtf8kyp358+fjBz/4QXTSkWn31IXc0WLuSEOIXHeff/55Na8mtyz+rslAkvORptyhdjBmzJhUblmyH5R7FLqm3KGTDWVsG45yyR05J/f0rD0KXWvDNP7blDu8zlwXCPQseVqTac4gSPckG7ljmr9t/cKkTOPz3qc//WmccMIJJdfYyAW+iDQRdxI8/0lj7lAfMJE7trEwrXKnq6vLuODi71XGiNFsTf6sOHInbjznz+ebFC4BlXksSduim8gdirmjkVRafuhZ0i2rp6eniNyx2aJU542NjUZbjvqFFoCal1eelmUiWfn99HscGWdy65HfuSh3aGzin039Wq53+H3SLcs2hvN8aOSOVj5ZJxq5E6fcsa11ePomcoe3I4k5c+aUPEfOhdomp1yPJHHLevTRR3H22WdHMZRMdkJ3dzc+/PBDAMXryUqclkXKu3HjxkXfSXInDMMo9p7MKy+rptyRf+MCKvO24ckdjxLEkTs25Y62m2JS7vBBhfvsauRO3M4ch6nxy0Hs448/xksvvRR9lpOW3DXi18kYE9p9crB9/fXXI6UPnxxclTuaMSINHBNDz8snQd9vvPHGAIC5c+cWGdMmcke2D0nu8LyRMS8nTE25Y1o4cYNJEgGacqempsY4wWt1YVPuNDY2Gidefg/feevp6SmS4fYHuXPFFVfgwQcfLLqOX6sROS6nZXHljiy/Vpcm5Y40wCgtk3IHAB588EHVQJB9hZBFQGVbsMk4Y1COI9TGu7q6Sshp14DK0i2LjxnawlKSvjLf0i0rl8tFC7skyh05xqVxywrD0OiWZVrEaDHJgOJ3z3e/5JxAfY9/L08wA9bW3ejRo53csmR9ZK3c0cgdPqbGEfiaW5ZtEaDFDaHnuCh3bOSOtnA2zcGS3DHFmzAtFLWYOybS2zQmL1q0CIcffniJq5K8n4OnpblPannlKFe5kzbmTlNTEwCzcocgF2v8b1xe+XhpUu6kIXdcbMQ4klP+xttofX29VbnDyZ2qqirrhptU7mjuZdq9pnGRK3fGjh1rHKeBtX2blEg8XbmoXL58eZRXre9RvmXMnSTKnbj2zNPVfpdjiNYOZb/Xxib5LE25I11eXMkdzS1Ls0lsCkYTuUOE9V577YWHH37Yauvwe0zkji3wMG0oyLT4X+29yvEiiXJHxjXTxu+pU6eWuFVnRe5oyh0id8aMGRN9Z1LuUHou5I5U7tDfOLcs3k68W5ZHCUzkjpQpplHuyEW5NNqkcse0E+A6mNoCKl922WX47ne/ayy37Jz8Ohu5Y9otOffcc3H66acDMJM7dA8/+k7+JheshI6ODuMgDpjVTnIQ++ijj4oWptJAkAOPJHeIyOHpErFDaZDKyOaWJd81P8EoTrlTXV1tjDNA7bCzs7PIeOVxhugvN4BMZCeVh+7hA7Ikd0yGhak92wyP1tZWlQyQk2kcuePilsWVO9pukul+2eflYp8ThvKd0u7xc889V5SGNHxMbllSnSIX+Vrd2pQ7poWjKV+SuA7DsMQgcw2oLN2y+MStvVOejotbVi6XQ1VVFaqrqxMpdyTSuGVRW9CUOybIAMsEXi/cyOLXkYEk+4bmlsXJHd4mTES+7MdpyZ0XXngBX/nKV1QDnt63dI2xKXc0ki1uZ/W+++5DQ0MD3nnnnZKxjit3ZHwPuRDRFlCSUJJzWxxRatpg0MbmfL4QA4XHnjG9Jy1NwsUXX4wHHnhAdeMwtW+bckJ7toQt5k7cnEFtJU3MHYq1Yoq5o32OU0xIyI2nK6+8ErvuumvRNVq7p+tN5E7cnAro5L0GjYCk07JsBC+RO+PGjSsq5+zZs4vcXTi509DQUDa509PTgwULFgAoKLGzUu4ABXU1oCt3uPKeb+JpzzWtAeJIFvl/SbrIuUabFzVb3vT+bW5ZpgV6XP415Y5mk9hsLdM6IwxDtLa24o033sCbb77prNwxEVy2DRmN3JF515R8/P9kg9OYExdzx6bM6u7uRktLC/baay/cdddd0fdtbW1RfioRUJnIHZ5fOUfFxdzh75bWIK7KHTnv0G9eueOhwkTu0F+TcodPgECpcod+l3LsMAyN5I6L8WbKP2AndwD9lAXNcJeDUhrlTnt7e1ROfgoLn9DlIkHbLZaEDk/ftktkghyE586dG93HCaOkblkaycDfX0/P2mj5zc3NxndMf7mhKQ0EGVA5jtzJ5XL49a9/jf322w8dHR1YtGhRNLASeCyA4cOHGydeqifArtzhfuu8HnmaEqbvly1bhnHjxqGmpgavvPJK0fU83ffff7/IbcdVuUNpuCh34mLuaAsnTblD19XV1aG3tzeq0xkzZhSptmS7kJOWyS1L9n+b4dnV1VWiDnEld2R/4pOsVELExdwxkTtxyh2tbUq3LDmmVVVVoaamBq+99hpOOOEE5zGWw2SA2QxFqhNO7kg1lnwe/S6/X7NmTcmpd/wZlBfNqNWUO52dnaiurkZTU1PZMXdyuZwzufP666/jmWeeicYPPgabglfzsUeCvweqH+3d8PyTyvSXv/xlifFqU+5wQ5SeY2ov9EzTgkUSUGncsuhack/SyB05Zl5//fUleaYFDZ9ztfs5XMgdW92UE1A5Scwdyr9U7vBxNy4P2mLOlFdt8TZt2jTMmjVLvY/P8fSZp5k0oLKrcoenReVL4pY1bty4onxsv/322GabbaLPfOe/oaEh1jXFtnCmci1cuBCjR4/GiBEjrESXptyxkTs8mDW/ltvvpMKUNqPWTiiNJBtc/P+02SfHjiTkjrQR5LVAYQ6Qa4Ak5A6/j5M7cu7g15psCZtyh2+WyhAN+Xwe//Zv/4af/vSnRelLu5yDVH8a+BxmstddyJ2Ojo6ISJb28KRJk/DFL36x5P1q8b56enoilQ7fBObKnXJj7mjrL+q/vD1oblk2cof3OZNyh7dpG7nD24YndzxKEEfucOVOb2+vasTV1dVFjZwrd7T0eUA26ZaVhtzhv0lyxGR8a8+Syh2+oEij3Ons7IzqbvXq1aitrcWYMWPUQMjUaW1xHoC1Rk1VVVWscscEmW+u3OFuWXwhzu+TBgHVl5zE+Y4OUBgEXdyy6DMnSkwuPEQSVFdXR3EGVq1aVeL61tvbi4ULF2LhwoU46KCDsMkmm5SQOzwWgCu5w0/r6u3tjSbz6upqLFu2zEo8arCRO1S/b775ZtH1vN6POOKI6Bh2KpOEy2lZRNDyPMl2o90vjXAX5Q4RSXwRxXc7ZT4q4ZZFMWhqamqMC04JU7vl5ZCS4izcsuKUOy5HoedyuYjceeKJJ3DLLbeUuGRwxCl35KLcptyhMnG3LL4zqD1Pi0lGbYgk0nzBx/saLcwk2WdS7jQ2NqKhoaHIrc70rk3zC+241dTUlJTNtoiTz4k7vtg0jvBraAEfR+7Qdf/617+ioM1UJ6TcGTZsWNTP5DvnijGbOoIvnOSCQP6lNGW8ClN9AWvrjAdUlvXE2+ftt9+O//7v/y4hcah99Ce5o6nF4u7jbbK7uztRzB165zTe0EJp8eLFOOmkk0rKLhfK/K8trxq5s3LlyhIFJ3+fSd2yXMobdx1fONN1Sdyyxo8fb40P2dbWhurqaowcOTKqe/lsDlO/IFDMnU033bRIhanlobOzE0EQROXh6WkuKLLv8fLKIPSybuTGAi9PXOwj05xNm31y7OBkt4Qc88kWtD2XNsw0wpjgGgM0S+WORu7QO5Ibvfl8Hg8//DBuuOGGkvTjyB2alzlmzJiBIAgwefLkkryaiCmeZ/q9vb09UmhLt6w333wTr7zySklMN5NyR2uzWZI7WhmI3NE23OX60YXckcodbcPEhdzp7S11y/JHoXvEkjtcFi4nSWqMjY2NRVJf2+5cLpcrUu5og50cOFyNpTjljkbuyOuoc5JRTnJC+SxTvRG4m8/q1asxYsQIDBs2rKQTAvrug7a4pHpramqKjbljgnwvixYtitK1KXdM5A4FENPemYncWbFiRWzMHdNJA7lcqXKnpqYmUu6MHj0am2yySUl56X08++yzAKAqd2zkDi9LXMydLbfcEitWrDC2TVN7Nn0vJ0mgdFIFCgYzrzdNQeHqlmUyPGzkjiSb5GTFjT++MyrJHU2yS8+Xk5ZpUelC7nDDsKamRiV3TJO+i3KH8saDiVJ/0dKWbY2uS6Lc0YweWTf5fB5BEBTt7lC6K1aswCmnnOK0IEqj3OF9jO6NI3e0mDs0jmrkDh9HyX2Jz0mAOaByQ0MDGhoaVLe6uHlJjuOuyh3TXMINU2kAyv9z8IUP1W0cucOVklxBIpU79J00vvkcGbeA1jZU+Gd5v1TumFwigVJyR1vM8DqQcX0IA6Hcsb1bU5pplDuS3KE0iNw57bTT8Ic//AGPPPKIMe825Y5L3qm9meLnZBlQWYs9pYG3p1yuoAiura21KnfILSsIAowZMybWBhszZgyCIHAid+LmXlLubLLJJqiurjbaosDaOa62traknWrKHW3RSn8lucOfx8dNmWdpx/FyysNU5P+XL19e9J0cf7JyywIKY5nJdqN0TeD3aRuUmk3iEnNHew9cuaOtoygP/B7T+EzzsEbuUKzSBx54wEiwa+OBdAvu6OhQyR0i1IBSt3KTckfbSOJEY1JyJ5/P44ADDsBrr71W9L2m3LH1E7keMsUW6u7uLgnHIed4V3LHK3c8VMSRO9Q5pESMDxJk9AHxyp18Pm90y5LPNu2QavkHSgcMU8BL/n852NEAyI1iF+WOfBYnC1auXImRI0di2LBhJZH3AX2C0hbvnNxJq9zRBmHKkxZzJ84ti+rZRO7QAGZS7pgmCy0YHeVbBlTmyh1eHl7Ozs7OovZhU+4MGzaspDy8vkwxd4hY2XLLLdHc3FxRckcj//ikV1NTU5ZblrZDKfMi8yT7kjSWNeVOHLkj2wWftDiZ1Nvbi56eniKVB29/tp3Rzs7OEnInbocxLuYOUKrc4RJ2LW3TM6lugiCIDagsJb5Aqcojl1ur3JH3Pfvss7j22mujUypkWhxybJAGtwZNuSMJEJNyh5dBkjtavVO5qP3xetLIHVLu0G/y5JQ4ckeqWFzJHdN8R+loxxeb0uLf53JrA2cnIXd4ujKgMrCW8AHSkTsm28BEGMiFkWmhzctnI3d4+9DcGIHyyB1XAsf2mzYG/OAHP4hirMjraIFUW1ubOOYOlYcUKDK2i5YnW1n5e+XjPgcRSdrpoXwDh56lEdiAm43oSu7IRTAnd2x2cnNzM0aPHo3q6upYcmfs2LEAUELuaPfJ9q2RnkTu8AMltLrg6tRylDvcLQsoPdhDkjv8/6YNgz//+c/YcsstrRsyzz33XNF9mspBIgm5w6+T5I7s767rEVe3LNN7dlXuaG5ZhNdee60ofW08BBCp/jRyh77jRJ7MuzYeSILWptxxJXdqa2tV5U5jY2ORcqe2thZ1dXWJlDu1tbUYP3580fdcNarZ3EmUO9JOM62xvFuWGzy5EwMbCQMUK3c0EgRY67MNoOQUFptyJ4lbVhiG+OUvf4n33nuvKP/arh2lZTK+ZXn599SJuXJHi9guJ1rNgKT73n//fUycOBHDhg1T3bJoALCd0AKsXYiMGDEiM7cs/lzbaVkmcsdm9IRhGO3QS3LHZKDTZ21ipOtkQOWamhrjbiVfwPP6zTrmDrDWYN1yyy3R0tJSNLBr71bChdyRk7xcxNPvUg2h5YNAafCj0E3ljyN3bEQAJ4hsblnabgfdy5U7/H3RZ74bnc/no/es1S1fjGel3NHcsrhyx7Y4j3tmU1NTrFuWidyRxLaJ3NGMtDhyh7fJMAydlDs85k45yp3Ro0cDMJM7tDDk8xWwNo6AyS2Lp2Mi8k2bB1QfSZU7JnKnqakpkXKH59dG7pgWInKsI9LARu7wuopbQMuxS7Z7Wa44ckezAWwBlbWYCbLN0nvTyB1T+66kcufRRx/Fn/70J/zXf/2Xeg/ZLbTR4ULumJQ7poUBT1PadxxUxu9973v40Y9+pOZFI3f4+5R9mD9HWzC5lJfnTYPcjKD+a1PuELkzduxYBEHgpNwBSskdLf9x5E4+n8eCBQuw8cYbx7pluSh3eB3LRTYvf1tbW3QctFTuEMlIMCl38vk8brrpJuy22274+OOPsXz5cjz88MNFQbYp3Y033hj//Oc/i+pAU25IyDWAbWyS5I62YaJdqz2TEKfcMW0g8jLayB1bzB3CK6+8UvTubOQOud5KUFvl71r+TarckepsE7kjyUVyK5S/jxw5MpqrgIKd2NDQYCV3XnnlFVx77bVR+hS7k4OeYwoTQXaHHIddyB1uD2t/uWeCtrHH24k/LcujBKbFuYweb1PucHKHDHXTrm4ulyuKtq8tIuTAEYYhli5diksvvRT333+/mn8g3i0rDEM88sgjOOGEE0p2lwg0sbsqd/h9HKQECcMQs2bNwvbbbx/rlmUL4gmsNYRMblku5I5tEE4TUFm2H77wyefz0WThGnOHvm9tbY0GKJNbFlfu2AIqA6XyTJNyh+JkpCF36ISJLbfcsugzry+epoQLuWNT7vAdDbmo1PIh06SJqra21mjMasY8z5NJdSF3Kug6Tbmj1RU9n5M7fPFLn3mMkThyh7cNE7kTt9Mn24nmlsUX63Ks4bCphWpqalBfX5/aLUuOXUnIHZNBrBnYuVwukXIHQEkgR/m8pG5Zsq/TmC4XIYDZLYunY3rX9Pejjz7C6tWrS9qKRu7Y2qFMn7dvTZ5uei88vTRuWXKs05Q7cjxIo9wx9TV5f1ysHfr8b//2b7jssssAFMfccSF3ZJulzwPlliWvozYplb+8DvL5glIxacwdunbFihV4//33jQsDbZyxkZUff/wx5s6dq5INpBIyxc/hJJ1sUxpZYyovxc/SyiDB21dvbyGWH80JJnuA3LLGjh0bkWrvvfdeUdwqDpNyx4Xc0eaifD6P8ePHOyl3aI4zudHydi0DKvO029rasMEGGwAozy3rJz/5CaZPnx6NHZMnT8b8+fOLrgGAb3/723j99dexcOHCkvdtm2skkWHbfMrKLUsjQHk+tTnIROJx5Y4cWzi5I9cCvL1Pnz69aPw0jc9SucNtA/puzZo1Rnu9HOVOPp+PPpuUO/RcsoGknUOBmmnzvLq6Opbcuf3223HuuedG+SZinIPSX7JkScl3QLKAyvwdccJY2l78XhrTiWTm4OSQV+54lMBkWNJfrtzRBsrq6upo5xwolfpqhI2rWxYflKjTkt+jzD/lkaelDcJPPPEEbrvttpJdGnmfptyxGdaaW1ZXVxcWLlyI1atXR+ROJZU7aWLu8OfLgMoLFy4sMQRM5I42+eRyuahtrFmzpkj+TXm99dZbEQRBiTpq1apV0a68NAp4m+TKHZuhGUfukBsdXxTw/PC61mLuAAXjuKqqCpttthmA4raaFbnT2dmJnXbaCQ888AAAs0IjiXKHL2RI1i/HBZsxxSd2+Q74eMAnI+6WRbs6WnmTKHc4udPb24swDJ2UO11dXcaAyqbFgDRq8vnikwB5/jRSS0vb9sy6ujrU19dblTt1dXVOyh0buaMt2lyVO3Sfra3zI3l52Tjk87Sj0PkJhIA5oDLdJ9sm/V9T7iR1y9p3331x+eWXO5E72rs17YZSn2hqaormJVv7IXAjsVy3LE25097eXkLscaM8bgFtInNM5I7Mr2lR9OKLL0bxIWynZWnKQDmu8TlRohxyZ/78+Zg+fbr1fg30HiW5IxcVRO7Y8mBS7syaNQvbbrutMbi6NibY5lxS3JjIBqBwXPjdd99ddB+f4ymIt83O438l+DjD820rH9mEmluWRixK5c52222HjTfeWH1G1uQOULAHXZQ7tbW1qnJHG8cJmv3X3t5eRO5I+5m/Hxe3LBqDTbb9gQceCKCgtJB1YXufsu9LBZi8lkDkDs07aZU7chzlG1z897TKHZNblpwLeTuiOnnsscfwm9/8pug6Tu7wfkM2Fyd35F8XcieNckf2ATq9zkTu8ENNiNidO3cuPvnkE0h0d3cXre00cofysXTp0ug7G7lDdqA238q6kf1PU8PayB3eTjy541GCOHKHK3fkwEUdQtuFNe0E53LxbllaXkwTAB9o45Q7wFp1Cp+0+IBPEzsZ5dzQsJE78lkUPPWtt94CACflTpzrDt07fPhwNUK+bdIhaJMiV+5wQ3nTTTfFjBkziq43kTvarhEnd/iRhStWrIiumzdvXlH+6PvW1laMGjUKVVVVJQsaGVDZRbkjd2DloovInYaGhqK0tAW3SbmzfPlyjBw5MpIs8wnBhdwxLWr4oL506VK8++67OOGEEwAUv8cwDK3kTlVVldUtq729vSRmgyy/titnU+6QEZuVcodPWppyh7uF5vNubll0XRLljqay4btpQGnMHUAPBjpnzhyccsop1l1o8iG3KXf48brSlU/2oSAIMlPu8LR7e3vVmBgETbnjeloWh2tAZcqDtosL6DF3uEri+uuvj96pidxpbm7GihUrUpM7cXMvtW/NvU4DN/qSKHfI8JZjnVTufPjhhyXtjM+RcQsu04ZA3CLWtLAgg3rNmjWRIoTH3JF1rvUhaThTebJW7lx//fU4/PDD1d9spBilLTeHeNuhhQCN3zLAPkHG3JH1bdrtlgtl7V6eJxoLbJtORx55JI466qgie40TBJzcob4kyWSZNw5J7sQRj/SXkzv8mVpfXbFiRUXcsrTFvoaRI0c6B1R2Ve4QtD7a0dGBDTfcEEB8zB2TcoffQ23UZNtPnDgRQEEJJuvCptx56623MGfOnOizbWzSyB25ltGulTBtitxxxx349re/rc5BJvULJxU111STWxYfI/i8x+fBb3zjGzjvvPOi63p6CgGVyV7n7ZOezVVabW1t2HTTTTFp0iQ178Daequuro7CVCSNuSPrkpQ78v2byJ3Ozk5sueWW2HzzzSFB5A6RMZpbFqVvOuBFKtyk3WgiOvl4J/sfd8uiMb2uri76PgxD/O///m+kJlpflTs18Zes34gjd2zKHUnu8AWDtvCjdKgxS9bflAcbuWNiik1kBw0eJhk53ZdUuSMnOLqHdumI3NF2AimtOHLHFlD59NNPVw1R07O0euPkzuzZs9XyyXYRR+5Q2yByp66uDi0tLdhoo43U/NH9q1atwsiRI1FVVWVU7nC3rHKVO+SWReSOaaeO6onu4ZNQc3MzRo0aFZE7vK3yd3vbbbfh9NNPx+uvv66WXUKbTGhXyTQJygVzXV0dampqrG5ZHR0daGpqUpVLmoFJBmMa5U53d3fRjkSccoeeYVPudHR0JIq5w/NaU1NTZGSYguYSNPKHE9dA6WlZgE7uHHrooXj33Xdx0EEHleSLUFdX50TuyF2gurq6kp3vXC6ZW1accsdEvtJn/hx5WhZQSrSalDsctoDKsq9Tu9TGb3nf+PHjMWrUKADACSecgBkzZmC77bYrypdGfHKDk+DqlqWpAXg5OLnjQrrxMTmJcmf8+PFYvXp1dG1NTU1Uz1y5893vfjc6kZCr3+g5cQto2Xdsu7/yXkAPZk4LMlIguQZUJvQXuQMUx2/Q7tdA+ZHkjk25QyoRSTh0d3dHalftuaZjdLUxQXtXl156KY466iirckdLm/cDPqbR+NXY2BjNHQRtfuaQJEpackcS9XxhTsqdZcuWpQ6o7DIumPI+YsSIWLcsIsfilDtSHSqJIGp/JrcsvnHK75f/52WhPksnYslrxo0bhxEjRhS5+Lkod0444YRofqBreT/hkG5ZtAaQB3HIayVs4/PkyZNV5aVp/OfztnxnXLkjCTYZx0rrVxI25Q69tzVr1kRlb25uxsKFC/H+++8X5U9bV9TX10eKw7jTsrS1Fi+3yS2L5mwaW2ldqm2m8zJT3vk6goPS58pW/g4lGSX/upA7JuWOyS1r7ty5OOuss3DyySdH1/uj0D1KIDulafdQkjs0AdbU1BT5aUrGUE5MXFachtwxTQCUR/69Nghr5I5UP6Qhd/izuEEzbdo0NDU1YZNNNimZ0E15k+kRuFuWHNCvuuoq/O53v7Omz/OtKXc4ccLjKHFItlm+Xyk7pUUc7aiOGDHC+G7onueeew6rVq1SlTt8Vy9pQGUOU0BlE7nD07bF3Bk5cmRkwJmUO2+99RbefPPNkryajGDe1qgcJnKHJgBJ7jQ2NqKurs66sCEDUFPuyImI5yWNcoeO7aW67ujoiN6JZrzTc+Ni7vDFbBy5w/NabkBlusd2WhZQvFiUY6KMgcFRW1trdMui9DXlDi2IpFGZRcwdE7mTtXJHe3euAZXpfm5M8TJJt6yGhgbss88+GDFiRKRapPYlxzjeBmQdA5VX7vBy8jrkBqYLudPd3Y329vZo3KJr+emOfJ4HgIULF0Z54nl1IXfkHGT6rN2r/c3lctGik5/45xJQ2fRdJckdrQ/z+233ZBVzh9zWtOcmOS1Ly/P999+Pe+65JyJ3XN3FJbkCFN4jLb7IvkzilpWW3CG7gvqvLf4WqYyDIIh999THpKLIRu7EERmk3OFEnwap3NGUAzKgrmzT1M9IuZMkoLK0z6md0cLZpNypqqrCFltsgblz55bYmzblDlDcX2R9zpw5E3fddVfRb8Ba5Q6NqVkod4BCXREZwtMxuWXZlDu2gMqS3JEn2GqQAZVN5I7c3JU2gLYe08gdV7csAh8PbG5ZRO5UVVWhqanJidwhrxSbW5ZJuSPzK+cyGVSawN+FtNn4holG7sgNld5e75bloUAOKHLA4Z1YGvG9vcUxd/huEEFODnywJbcs7gLFr+V/TTF3+GDFO9Lzzz+PJ598sqS8LsodPrCnUe5w4+3DDz/Epz/96RI3CA0kEZw2bZo6CEvljs1QMUEbhPlgRYMhDcISceQOz3dvb280WRC5M3z4cOskc8stt2D//ffH5MmTS4yWIAiKlAFcuSPdsuSEKckdacCScocTDrw8vL5sMXdMyh3eNiVRSnDZ4aS2ZTLM6V3KRSXFErG5ZdF9nCizGVPaxCbbpE25U1dXV0Tu0DgiyVb+HZ+0JBHZ2dkZLVrSKHfKdcuicsj82XbVgLXtSTvym+Ci3CEih/JdXV0dyXnlrpEkd5YtW4Zbb701VrnDx3etbnp7e41+5kA6ckd7DtWjFnNHtnFaOHJDl/KluWU1Njbi29/+dsnzJblDaRLhLBcaktzh44rMH6XHP1N6tECVyh2uAOFKKN5nXcgdMlxpl5uTO/QM7pYFrN0pTUPumHaq4xQKGqlDn6WixTWgsum7NOROHNFgez5gJ3cIWcTcIRcMPod86lOfwh133AHATO7IuR0wvysiduLcsnja/P1T+jygMo1nSQIqJ3HL4v2bnhen3KG8ke1byaPQTe3DRbkDIFLuSDUOXyhLckdeS+MlHRkdF1DZptyhuk1D7kiVgwmaUob+7rLLLjj66KOjZ9F8KMkdCVdyR2trU6dOLfndNP5x5Y58D64xd/j4p42Fr7zyCn79619blTvc00La/5J45GWmPlNXVxfNI2SrSbcsU0BlWVfSLYvuk+ROdXU1mpqa1BinBBnbJo1blonc0ebbcpU73d3d+Otf/1pywuP66pblyZ0YmBbncvdQ/p9PuDbljmz0vLORcocGVRPBxJU7rm5Z06dPLwoYJsvA4yhIciefzxcZxUmVO7yempubowEtrsN1dXXh1ltvxe67744HH3yw5HdJvGguXnHQDAVeb/R+TBObHLT44P7mm28W7UzkcqXKHSJ3TEYQXQcgUu5wNQp/H7aAypJ8kka6pihI45bFvyflDrmTmcgd6fpjypMGqdyRxg29j3LIHVv5tXaTRrnT3d1dotzRyB1JssQpd2gMciF3pHJHk6zHLTQ15Q71HR5Qmfq+5pYlj9PUnmlT7nByh/dLTljJsTsIgqLx6K677sLxxx+PuXPnFpVP5ofccUzI5ezKHR4olUBHfWrP0z4Da8cpLeaOJqOXxAzVdVtbG2bOnImf/OQnaGtri4za4447LrpfGl+awsDFLau2tlYti02RAhQTpPwZceQOV+5oO4n0HFpc2ZQ7FPOJIE+Z4mOBbQHN34Vpt9O0iLVt/kjSwzWgMsHklpUkoDLBhdzR5j8Xckfex+vERO7I96Epd+g+wE25IxebWlnon8u8JhehvO1TOnSSpTa+ZK3cIduW5g+TGzr9raqqqvhR6DZyh2+Cmeoi7ih0F+UOXUs2aFrlTj6fLyF3pMqCyh0EgVG549JnZF60cSefX3uyaznkjkaAcmjkjotyR5t7TKdl8TVWLpcrWkfJ9n/nnXfiwgsvdCJ3NOWOjdzRlDtEwpjcsuLInSQBlZuamkrmBQ6p3OFjIH9uGIZFblm2mDvyfSWJuRNH7vztb3/Df/zHf+DCCy8suc8fhe5RAtNkJTsxsNagowWZRu6YlDuUrotyRzPiqPG2t7erCyTAvCPGIY1SuSDNWrmzYsWKImWTDV1dXdHgL0ksoPgodP45CTQDWrLoQPyiVlPunHjiiTjnnHOKnpWU3Nl0002j/8uYO7Q4clHuUBuh/GlxODjiYu7wtE1uWatWrcKIESNQVVWFsWPHGt2ypMSW4GIE07NNBjjlhxsmP/3pT3HhhRcalR980pHKHZOaANB3LeSkrCl3KJAdxQHq7e2NVe5oblnaaVmc0KDdGF4ODt4GslLutLe3RwY8l/Lzk4bk8+WJC1rfc425w/sG36mV5I5U7lBMLDIMeR54HcSRO7RbL/NG0JQ7fBGl3aPVB419pCCxKXeA0j7HibWjjjoKN910ExYvXhwtur761a/iiSeeAFA61nG3LG7EuZA7tnZoIlR5YE9eF3w3kccwI4O0t9ctoLJJuTN8+PAit6ytttoKp556alE60oiVmyUSfIFhIlLj5p4wDCOlCl1vUu64kjvyGnrHmnInzs6wlZ/SNqnekoK3SVoIyLmQb5gAa8kd7tqblNyJy2tS5Q5f7PA2wt2yNOVOHLmTVUBlqdyRbba6utqJ3KlEzJ2RI0cWKXdMeaATISUx50LuyPm/trYWDQ0NJYeiJDkKncYmvnDWyk/kTmtrK1asWFGUHxebiT9T5gkozB1hGBaRO3yD15Qv2zPk/wFgu+22w7Rp00p+l+SYRu6kccuSG568jxFWrVpVtCllc8uiegFKx39tM4yTO/SOTcqdJG5ZtoDKUrljOvmP58HmlkV5WbVqVTQ/8g3ULNyyJFFF13G3LB5SQbpEe+WOhwoboQIUx7GgwYQW2blcccwdvkNNkJ1fi7lDE6hpBzMMwyLjncfd4YOVC7ljCrZJICOJL0o5uROGIQ499FA88sgjRemYyJ2WlhZnckcL3sYh3VDSkDuaoWBbMErYyJ329vYStxON3OGGuQRvPzLmDrU7rtzhgzLPszzhRu628mvpFKlyAyoDaxet48aNMwZUNu16Vorc+cpXvoJjjjkmc+UO9SWuRHJR7lBQ9TjlDo9hQN/Z3LIobg8ZukmVO+XG3Jk8eTKmTp0aGQFcuWMjd+Rn7Zkup2VJtywiF4jc4W5fktwho0j2G/l/irVgAidfgbX1eO211+IHP/iBSu7QgpQg25C2kCSVDbUvW0BloLTPcXKHL7S4UUvHGWuSeJmuS8wdUh5KUB3NnDkThxxySImSK06589hjj+GXv/xlSZq5nJtblqtyp7q6GldddVXRokcbV20Lf27UmojUuLkHKFYAacqdpKdlmZCFckcztLU8pCF3eB2alDt0qgp/tqbcoXzGuWWtXr3ayR0mqXKH900TuUPuCfw+njeJJEehS3LHJeYO33RIEnNnIJQ7DQ0NsQGVTW5Zso9WVVVh+PDhZQVUJhvFpECncpNbFgB88MEHRflIAlM9kiKF2kpWblnyOdtttx0++uijknRknEqeTxu5Y3LLIqJ7+PDhRkKBQORHa2trbMwdnlepWNHKT9eMGzcumquGDRuG6urqfom5M2LECHWTnMBjd/JNYgkid6jv0jOHDRtWYgPbyB26hosj+DWyzFK5Q6A88pApsg/5gMoeTuQOdRxO7pDihcfc6enpcVbujBw5MtYtiw9kfGeOd9g4kkJCi8egDYBczs7Jne7ubvzzn//Ec889V5SOyS0rDMNEyh2b0STdUMohd0zKHYJpArORO9oCp6GhAUEQFJE7/D4JXn6KuWNS7tgCKkvljgT/nuqztbXVidzhMXfk+6LJcezYsUXtICvlDj3bZIBzFzYCTQaVjrkDlLYlTblDx2LGxdyhE6z4dy5uWVy540ru0K4mfed6WhZvF4cccggWLVpUVE661oXciVPuJA2ozOuiq6sryoNG7tC4zGOn8HzRe9xxxx3V+uBl0twmXnjhBTzzzDNOyh1Xcmf48OHqAiGJcqetra0ovhg3aqnfSMONtwkuoU5L7tB3L730Eh566CHMnz+/6Hsec0cqBYHCSYwU54unyd+bC7kTF3OHwMkdzQiPU0fIOcj0WbuX/5/bCZpyh8YW2YdNAY01yMUrUDlyx1Zvpns54cjJHZ6WK7njotxZuHAhRo4ciSuuuMKaR2qrWSh3qE3ZlDumukvilsX7N9m2cTF3+KZDOTF3tHlGzr0mQkPGCTTlobGxsWzlDi+vRu7YlDuy3UrXcQmu3JkwYQIARG7D5RChfLMQWEvuZOGWpW2KHH/88XjuueeK4h3x33l6ktCR9a4pd/j/gbXrguHDhxflRyO6ObkTp9zhzzcREhq5Q/GZKF0tKDpX0djSNZ2WZXLLso3Vrsqdnp4etLS0RPOjRu7IfpLL5dDc3Bwpzfh9tI4xKXcIRI5LcofyaIq5sz4QO4And2JhIndoFz6fz5eQO2SkUoegAaG7u9tZubPBBhuUuGXJa/mgx3fmTOSOi9EWp9yhAVBzy8rn80W78Rwm5Q6wltBwibmTRLljCxZmgpzggPKUOzw9jdypqqpCQ0NDCbljmpz59zLmjiR3KBAbMe48z5oCwVQ+qs+WlhZjQGX+fvlEKmX71BfkaWP95ZZlI3eSuGWZyK2k5I6m3CGyluqaYvDItsHdC5K4ZbnG3OFtwKTcMYGUA5rxQOnyo9DJWNICKsv7tDbrotzh5E5vb2+JWxa1TY3ciVPu0L0bbbQRwjAsCjjM0durB1Qmco/eEW+fMi82cofaUFtbG5qamqJ04tyyNDIaKJBCnNzhiy7qN3Ks05Q7WbhlmdSFnCDl74VL0OXGAc1rcW5Z7777Lo488kgAaxeelMdhw4ZFdSlJKll++VwTbMqduEWsXERyW0UeL07KHa7wIZjmWNOYKufZtOQOJ8VMJHvcghfQj+XN5Qqq4rTKHb6wsZE77733HgAUKRA0pFHu8HZA76yurq7ELUtbIGdN7tDzpG1qIlwqGXMnjvSkwzpyuRzuueceTJkyRb1u2LBhscodqXSSRBBXH5Sj3Mnn80byRJY/CIJo/tHchl0h3xm9AzriW7plmfLnehQ6PWe//fbDfvvtV6Su4teGYaiO8a7KHaB4c4OHbzDFeSEQGbJ69WrU1dVhww03RHV1ddER8ny8lAoRF3KHq32HDRtWRDBSWZIqd+h3uo/mcOmWZQPd6+qWNWrUqKLNZo3c4X/HjRuHW2+9tSgdoJTcMRFlVB9x5M766JIFeHInFiZyhwxxYC0rSp+5WxYndzTljkyfkztxbll8EDWRO3ywShJzh+dPkjtcuSPdskzP4HmVhhuPSWRDnHKnq6sLVVVV6kLRFfx9SHmfdp2ETblDxhwH5ZdiesQpd/j3ZKBLckfGgSpXuUMTw6pVq9DQ0GAlN+iZBPkO6F1L482F3HExWOKUO5SmJuNM4pYl+6K28Eqr3AHWGhPV1dVFO008vZqamhIDV1PI0SROZA6RNGEYlu2WZQKlfc899xR9v91220XB0PtLuUPXx7llceWOPL3PRu709q6NnUVzgWl3SBJefAGRy+Ui10d+v3TLMgWNpbwABYPcpNyxEZiyPUtyhy9uqH5sbllSRciRNKCyzDelF+eWRW1X3iuVO5dffjlOOumkouf+/e9/Rz6fx4QJEyIjnPLIgzTz9G3kDl+QaNCUO66LWF7vchdakjucvHAld77zne/ggQceKFrYAKUnVGVB7pjcsuIWvEAxuSPtKx5zh8phIndkzB0XtyzXQxw4ueOq3OFl4Ys5Se4MRMwd0/P4RkQcudPU1BSll6VbFj2/t7cXP//5z3HDDTeo15Sj3JFEENn9MpivJHd4niXREEdk8jZN/ULWexLIvsLJHT5Hk3Inq5g71J+kOxJvS5QXfkgHJ3rk/JXP5412KLenqJ7IZdBE7hCZdeSRR2Lq1KlFhAzPs4yPZCN3qF1tsMEG0Xeackcjd2Q/leMBb7PA2tMck5A7mnJHI0Z6enqwatUqjB49umg9YlPuaO2T55W/C26zSWjkjly3EeFJ7dWTOx4A7OQONR7NLYsmYB5zByhtWDbljsktS+aF7qPOmqVyhyS4/DMnd7hyx0buAGuNT/mMJG5ZlL7WQbu6uorItHKVOzxQp4SN3OGDMX9nJuVOY2NjNInQO3RR7qxcubIo5g4pxnh+Ozo61IDK5Idsmog1coe7ZZnIDUqbII1dejfSMOB5pv8nVe7U19fHKncI5bplyb6oqQs0Ca2Lcgco1DUpd2hM4O6dlG/plqUp5OQi1DXmDn+nSckd0+9f/epXsdNOOxXVtSnmTltbG2bPnh19ti1ukyp3pFsWkSp0vVTLUF5NblkTJ07EFVdcgcMOOwyAndyxKXfIHY/frylPOLQFArllaQsEm1uWbM981xRI7pbF67tctyx5Pz3HpNzhEnRNucPJglwuh5dffrkk/VWrVqGpqQmffPJJEfkHlJ5oxstByEK5I8sft7Eg0wFQEjiTNgbkfcDadybb8IgRI/Dtb3+7ZO7tT3LHRblDGyV0D1C8EKaNDprXeGB/ejaN85QGd8uyzZmuG0pE7EhS3wS+k82Ju0qSO5MmTcKxxx5b8hsnd2S/MhEuLjF3SBkHpDsKneddtl2a82wbhI2NjYlj7pj6KI+5w/PFbcMgCIryUo5bliQ905A7ctyR5A65Zmd9WhYndzTyh9sHnNzhRLl8Z1K5E0fuUPuQYysfN+vq6lBbW4tddtmlqN0nIXc0W5CTOxRzR/bhJModYK0dxRXdPMBxVVVVKnJHs6uJ3CHlDle2piF3NOVOLpdTx4COjo5Y5Q6tA11PZV5X4MmdGNjIHancMcXckcExOWSjp4aouWVpeSC0trZGJ4LwxXW55I4c8OQgIpU7tmdQfk1uWXHkDrB2YDZ10CyVO5zAMimuJCQZxicobfea5xeIV+7w+w844ABrQGWgWLkjCRjXHRaafMIwdDotS5PAEkzKHZ7ntOQOnU4BxJM72mTg6palkVvSEATSKXeoLZCPd01NTVEAQJ6eptzhdSSVO3RPmpg7aZQ7GvjOLA/CqQX+vfXWW7H99ttHnzUjnkDKnbiAyrQwkW5ZcTF3CCa3rJqaGpx22mlRbBcTuUMLOoJU7pCiyKbc0dIkSHJHM8BtAZW1nV9eVptbVpxyRy6qkip34tyy5PjKlTtyoUSxTrhyh5MC9NyWlhaMGjUKQRBEY4pG7pjcsiRcyB2TzRGnUHAld0iVZmqj9M7kGE3Xl0vuyPJTeloweA5X5Q5/j9qim+ZCqp84tyxy55JkplYu1w0l3t9dlDv8fdJ9QOEd0SKX2rkp5pAGG7nzzDPP4O677y7KA/3lykeZT54OV+7ExdyhuDFAsRqFp+vyLAAlJAwpdzQbjN/DlTtSMWhyy+KbZLy8cW5Z0g0prVuWrCvATeVsgskti0IIZBFzh9uj1M80Ah5Ya3cC7sodGWeH2xXcnqL7pVqEwMdNOVcR+HuTJLqLW5Ykd8p1y+Ll5ZvhtbW10TOTKHd4QGU+D/Iy0jzJ55S4mDsSJnLn7bffxte//nU1j6TckW7sPD2pfPfkjkd0pCiQXrnDAyoDyZQ75C7gQu6sXr0ao0ePBlDojDfccAPefvttdRfVhjhyh6tE6LOrcofyYlLuuHQ6qh/TBM3JtHIDKvOdRFffdBO5A+inR6Uld95//33sscceRUSDjLkDrFXuaG5ZNgOA/8YlqKaYO5I44s/hcFHupI25w5UZ/aXcsRmYaWLucHKH6pog2wZX7mh1JmNQUf658SBVgQSp6pLkTtyCxNS2aCyrr6/Htddei//+7/82Knck4tyy+HGYHFQOHniXlDtazJ18Pp+I3KGFDodpLDMpd8iAyufzJb7tccodnhdK20buJFHuUFoETbnD1Y5Aupg7RDjYFGSaixOQTrlD9cSVO3LXlZQ7NK9KNyYX5Y5WFtuuejnKHZtbFl901NfXIwgCYxulupELWRO5IwmNODtDlp/S09qxvC8puWNT7nByp6enJ+rbPT09Jeo5rtwxvT+tDZnACQPTvGaKs8VtMgqoTBuJJuWOCTa7Rqrt+MKZbFtJ7sjxQyp3TPPG1Vdfjb/97W/GvNnIHWmjA6XkDikzbOQOKXeobfCxGVjbLmT759fGxdzhC3UbuWMjT/g1QHbKHXkvjauk3AmCICJ3bOSTC7nDiXyu3JHX0rtNo9wx2aFtbW2oqamJVG/A2sMp5NjKP/Py8r7J+5vcIHBxy4oLqEwbw0D5yh1O7nB3aw1cuUM2Ed3L0dnZiba2NowePbrot3KUO5Joe+qpp9Q8dnZ2loxD1J64LQR4cseDQVOsaOQOdRITuePilkXpE3lBEtU1a9bEnpZF11EAze7ubpxyyim4/fbbYw0mibjTsqgDmtyybModeUwgIYlyh+rHNIFUV1eXpdzR3LIANx9w+t7mUy0HtSAIioxoaitxblk00HIDNM4ti6fZ0dHhTO7wnQXulqWRn5Q2DbZpYu4Q0pA7hDTkjokckOROnFsaIQvljpwseXquyh0+/tCxsJQPk3JHliepcseF3AGA66+/vqjctj5r2/VxdcsC1hIN/AQwHnMHgHHxK4/8pfTltWli7tAiQSp1TESTLB+lA6wNqMyNHr77KSHfaxJyR+aD140ruaOdYiTTNSl3TKdlUb61mDtUB1zVqCl3SG4OwKrcIdUskJ1yR76T5cuX48Ybb3Talbcpd6jvmdoo1Y0k4E3GvWxPccodF3LHFDvLhdzRlMt83qTxm35rbW3F5z73uaKDL9KQO/l8PjoYwTWPNuUOP+FNEjaU97q6uiKVuAyoHDdO25Q78j3yOY/GPPk+5LzoSu5suOGG2HTTTYu+iyN3ZD/g70WWizZCNAUhv4fGCVK2AsVuWaT25OAEnXTLssXckTFmynHLkn3V1Ebvv/9+PPHEE9Z0TW5ZtBFJtqNpTnIld6Qtq5FmcmMmScwdOpwAKJ7D1qxZg8bGxqL4MDJ+nAYTucPvkSrGpModaoNp3bKkApq3NX4aWdqYO0DpvEEnXrkod2ykIyd3NKJNgy2gsim2qyd3PFRyh0sFqaESOaGdliVj7pjcsmhQam9vj4JfAWsnFP5suWMBFAYV2qmlwZd2gwGUyHWT1IGm3EkaUJnnuxxyxyR7poE3K+VOLlccMM418KAkd2wGCLD2tCygUKc2Nxl+vzbQxrll8faSVrlD5A7lUSMaOzo6omCV8h1QPdqUO4Sk5A5PM+64Q5NyJ+lpWTbCoRzlDrU/Tbkjd5v4d1K5Q4oWQlNTk6rckXUr26k8Cj3uXZgmcXoejwuWlXLHJaAysJYEkModvpgoV7ljc8syxdzhGwJZuWXxwNB88WpCnHKH15FNRk+IC6hMi2YioOVzZ8+eXbLIks8zBVSmtqQpDPgOJu3qa8odkpsDKFncc0Uudx+0ERB8t1mD5uJBn++9916cfPLJRcfH2tIxKXcofza3LGkwA7r7FFCqxO3p6bGS6/I90rs3LXQJrsodfq9NucPb+rRp04ru5wGVeR61/BM0gtAEflKgaazkO/rSppBtn+INSoI7boEk7RrbXMXtTxqnTJteklQjlw7TvKG1RVfljpZ3Gus04sDmlkVtnhMHXLnDyR0ecFsr77Bhw6zKHZpPpRsJkIzcSeKWtfvuu2PjjTe2puvqlmUKsCvLO3z4cJx//vlF+Uqr3KFnUz5N5A4pd2iTXMbcIYUMlZW/dxNcyB2TupSXiSDJHdrMswVUdjkKHTArdwgauXPNNdfg3HPPLSmLidyhz2TLUcwdQmNjo1G5o4GTO/yzDT09PSVl4zYHB83XcWuDdQXrRylTIk65IxcN/LQsvptiU+5IY7q7u7vkKFx5Wpa2Q9ra2hqRO0SAdHd3R9c0NjY6xdzR6oAPJJLcSaLc+etf/4onn3yyxBh0PS0LMJM7PBI6vY+sAioD2ZE7csDiblm0m+CSP025Y3PLku0uiXKH70pzcieXy5W0SaAwsZArw2BV7mjR9RsaGkpOiwOyVe7I/iGVO7wMUrlji7ljcsvihCGwltwZaOUO1Q0Z/C7kjotyR1NGyHGadm+JRJengQDJyJ0slTtp3LK0BRmdlgWsNUq5tN0E3p6pLSZR7lx00UVYsGBBSX5MAZWBtX1KkjuHH344tt9++6Kdc63cJrcsHm/AptwhY1rGS5BuWTblDpe4Z63coc9J5jOp3OGnZcUpdyigsKlNu5A7cnznkOXXFjRZkTvaolvG3OHtsrW1NVa5YyN3XJU7vM5MZCtX7sgxw0TuyE08bZzW1Hy8DNozeVqc3JGbNKTmlYtuqj+TcidrcofGKUrD5OLGQW5ZdA0fm4mE4+SO6aRLoNgti9dpPp8vGpd6enqK0uHXxdkwVJdBEJQQQbbNlTjlAidCAbNblmleImJl0003xf3334/29nZceOGFRWm7KHd4H9Xcsvh4r7lldXZ2RpuM0i2LbG1uS9nqjfJMMLllyfuTkDt8HSRdbJPG3KE5Wyp3CFpA5YcffhgPPfRQSbkkucOV7gCiMY+7ZZFHgiSjbHZjkndBSELu+IDKHhHiyB1qfNQpuVsWUGh4MuZOnHKHyB0+aVJ61OE1tQSdllVXVxdJA7lyx+SyEAduSPD81tbWIgiCEnLH9ozf/OY3uP76643KHZdOJw1wAjdYK6HckUaQTZqdVLlD5R4zZkwsuSMnXl5ntLjl9UvqMZluEnJnzJgxReoWjdwhNy1KO47cke3bFivF9FmCp5nGLWv8+PFobm62vrO4mDscVPY0yh0qj43c4TF3TG5ZDQ0NRRMfkTt8cSvvk3mm67Ikdwg777xzUcDEcpU7QLz7DnfLampqwvLlywGgRGGpGa6m07LKjbnDlTt8IUl5sY2NPC+dnZ045JBDsGrVqqi9kFEjNyFsaeVyOdVVzkbuAMC5556Lm266Kfoc55YFrCV3ZFywxx9/vCiNJMod3v+1dynJHW1RLt2yZMwdqt/NNtus6D4bASHnU9vvsq9pxLMtHemWRWNy3JGwruQOlZO3J9ptl5shNtDYwueAcgIqa/0rTrlDmDdvXlluWUmVOzK/HC7KHaqP7u5uZ+UOr8Mk5A6f82jM00g8rQ2TcsdE7mjzdVJyh+ddkju8LZvIOQpmS9fwDVdu98rj2jU1HrlldXR0FLUX6ZbFNxHle4tTXRGCICgZ40zzsy2QOkG60HC3LFflzpw5c7Bw4UL87Gc/i76fNWtWlC9SS1L+6TsOTbnDyR1eR83Nzdhhhx0wf/58AG7KHW7HuRAKLsqdJOQOKSSHDRuG+vr6qIyyTl2OQqd6Kke5097eHuVXi/MjlTtUB6R4HTlyZNGmM7UVmzqRoxzlDn83ccodT+54OCt34sidJDF3uLyWYDpukg/gtFMrlTuaDDIJ5CTD2XZy7+ADjm1XmIzvctyyTIYQd8uiBXga5Q43SmzKHdPkyUk/nh5BI3foKNbf/va3mSl3pKRcphvnlsXLV1dXFy0MTModYK3EvLe3NxG5ExcrRfscZwymIXc23nhj5PP5kqNxpVuWptzRjFYiIm3kjinmDuWR94mkp2Vpyh2KuSN3Sfh9zz//PH71q18V5ZOTOxRgzwZXcofKQG5fackdUu4ApQtD6bfPAyo3NTVFbi4uyh0tD0mUO729+mlZNFZTWmmVOwsXLox236g+SIbv4pbFyUq6no+j2mlZNsS5ZQFrCVOp3JFpmAxlvsCVxAstKk0BlWmBQgTf5z//eUycODFKn7tlSeUO1cUWW2xRlHYcARFX/7JP0/NsfUNLh9flqlWrIvdaV+WOydWQ3jstDjhRQW07CbmjLRJNyh2Xo9C1xRZ3YZExd3p7e6N3+fHHHxvJHRe3rCyVO5tssol6DY0TXLHB7ca4mDu8DsuNuWMid+S8GBdzJ065YzsKXftM9+65554AylPu8Dg9ruQO39Tl46cWUFnblJC2lQ1Udy7EZ1pyx+SWpc1L+Xy+KN4Z4YEHHkik3OHtSIu5Q58Js2bNiv5Pyp04ckfaQTZk7ZZF5E4QBBg7dqwxJoxLQGWCidyRyp3q6tKAym1tbdH1nFijda0kd/jYQ5+5uoervGw44IADivLK83nkkUfipJNOMt6ruRB7cqcAT+5Y4EruaG5ZQKHR8/g5gLtyJym5AyAid7hyh67hg2kS5HJ6QGXqUEmUO7QbQvVEZXQhd4gs0MA7Nxnz0offFUndsn7xi19gjz32iL5PqtwJggA33ngj7rjjDnzve9/LjNyRx1+X45ZVW1sbyVtt5A5/t7QgcnHLMsWDcjHeOGyuABImcgcAFi1aVHStptyxKXYItKMx0Mod6ZalGTX8vv32269IfUHX1dTUYN68eWhoaMBbb71lLDcQT+4sWLAAn/vc5yLFFwWFTOuWxWMLdXd346OPPioal4DiuqZ4RMOHDy8xIAGohICpfJpyx+aWZVLu8EUTf+8mook/n0CE4uc+9zmceOKJAErJHRsBzxe8aZQ7EtzQkuMxlYnHGtDeLeXXxS2LvqN8cgJJS5PGRiL4zjrrrOj45/b2dvT09BhPy6KFfFJyJ84tTrZzl7FGS0e6ZZF7bRy5Q+7kccodGo94eegdJRmLbeTOU089hWOPPTbaOLDVLeXPplzhyh1OolEw308++USNuePqluWq3OEw2Uy/+MUvcNZZZ5U8k48T1L5NMXe0hRXVoRaI11W5E0fuaGRHOeSOi3KHY8MNN8RTTz2Fv//979HzCTZyR1Pu0GYAUEzuxLllaeQ4tw8poK+J3OF1aAt+S+00a3KH8qO5ZZHC1KTc4ScVEpYvX65uNqc9LQswq1Dz+XyRckcehS4DKruQxpWIuUNlHjduXMmcxcsS55ZFMLllSRtCig7oHkqXjyE8dh3/K4NQ8zGSiEDthGCOK664Av/zP/9TVCaez6233hr//u//XnIftRnNLYvmI0/ueBhhI3e4XzF1Sh5QGVgrleWNKU65Y4u5QzCpBTRyR2PKk4BPMnzHnwwLTu7k8/lY5Q6pe4IgiCasLMgdupcPQGnLS39djkI/9thjixY8fCDWJltNubPXXnvh6KOPjj7bYCN36OSMrq6uIlfANModG7lDackFBCd3Ro4cCaA85Q6lvXz5cvztb3/LlNzRYu7QTiknd2RgUq7ckceFc4wZMyYy9CW5wxcN1EZMyh0buUOql7lz5yaKucOJT0numMgVeeKQzbUHMC9EKY1NNtkEm266adSGqqqqYsmdOOUOP7p1l112iQgqjdyhgMPcaHZxy9LKl0S5k8vl0NraGj2X6p3GRqoLqdyxGSS8fRGheMYZZ+DTn/40gLXkTtKYOzJ22SabbFIUf8vFSOLtUj5Xi7mj9Scet4dDvleqQ1qE8DzKd8ml5ly5w11jqf9K5Q7lkUj94447rijtrJU7rjv4pnSAwjhMyp24gMq9vb3qwi1r5c7BBx+Mp59+Wm3f1Fa+9rWv4fbbb48WCbZFGI2XthgYJrcsinvByR3ZB7N0y+KQ7YGIpU033RT77bcfgNKFPxHK1K7pZCC5UWIiwoHinXbtetnfeFiApOQOr3cNadyybPZLTU0NvvKVr0R2iAu5wwMql6vcIbcsoPgEJa7ckYSl6UQ0YO3puRqSkjtx47aLW1Y+b465k8/nI7KcP4sTM9rpRtraiPIglTuc1NQgY+5wO5Q20eR6Jg5ZkDscpDoBCuSOiXzQ3LLKVe5Qf+TrBNrMkOWQ5I5U7vBn8Gu0mH0SfAzSiDYeZoOD280mckf2yfWN3InXoq3HiFPuyJ1DGpypoRG5w2FS7nByJ41bFlAwturr66PgiSa3rD322ANvvvmmSxUUkTtSSkluWa7KHRqsSVFAnd+l0yVR7tDfNOROUuWOXIhJckfWh2ZscrhOvJJFB8zKHc14roRyhy/gOLlDBgGgK3eklJynt3Tp0mhByWNbaEZlkpg7mnFBi+CFCxdGv8n3RcodAFZyZ9y4capyhxQj/LQeMsg15Q4Z1LW1tRH5xNvAlClTsOWWW0b3uCh3bG5ZTz/9tFoe7gLmAlPfk/XOlTsNDQ1Oyh3TbjSNmcuXL0dbWxvmzJkT3cf9snt6elRyx8UtS+aFyprktKzm5maMHz8ea9asMSp3pEuIa15ox5QbRNRuTG5rHBq509HRgf322w/PPfdcSRltu/FULoKMGcPJHTLStDEpacyd6uq1gV7pGSa3LFrsELkzevToEmWOKebOXnvtFbkwcbiQO/xYWg7pLsSfx8HjX2nQFtgUoDdOuWPalZexFmje1lyMXIj2b37zmzjggAPURaKcN8mWIeWByd0oCAIn5Q6wtj319q49jpzIHT7O031xblm9vb2ZkDtNTU3o7OyMYqnIZ2oKvyTKnZqamsilS4tzQjCVk54vY0PyNAZauSPLxT+b8iCVO5x455shktyxBVQGiskdbh9SPfJ5iSBtq7Fjx+KTTz4pybO2UWRD1m5ZJuUOjacu5I6m3Kmursb06dOjsVeSO/X19dFaQgPZwXS/vM4Uc8cGnmfTesREiGqgzTcAuOiii0o23LQ0k5I7BC3mDlAYa4h8IVsdsCt3TOSOptwB7AcB8A1ME7nDCSh+X1dXlzWgssT6Ru545Y4Frm5ZUlbJJwjZkEzKHZtbljQeTYucYcOGGU/LIlUHAPzud7/Ddddd51IFRSQWJ3doUZrELYt2OGhQk+SObYAlckGDRu5wyWUSmJQ7JvlyHLkjEUfuZOGW1dXVVeKWJdNNS+6YAirTZ2oLNKl2dHQUGWkm5Y6GfD6PO++8syjPhDjlTpqYO5/61KcAFCt3NHKHl99UhzZyRx7ZTgs9m3Jnq622ivLMDRJpPGjKHRlQmfcNSe5QEFsJbSFgQ5xbFrCW3ClHuUPvnCt3aFG+ePHi6HpOmJuUOyZyR9s5ilPumAyI3t5etLS0RMFS+QKCdnJpIcTzklS5w/NMpGVLSwtqamoSB1QGzH00zlDSjERC0pg7pvFcnpbF50/KX5xbFi3KuXKHnwIClMbckUYlwZXc0eCq3NEW1Rwa8UyEe1xAZVI/mYKE8zqtq6tTlTtan5HgO/aacufjjz+OPlPMJtvilN57nHKHnsWJTLrOFnMnzi2rpaXFOqea8i1tppEjR5bE39BcdjgpxjcF42LuUH1rY7rNhZinSeOUtglpUu4kJXekIlrLhwmuAe7l87hyh2+4lhNzh4OrMKiv881ggrQtTMqdSpA7klw2uWWZlDsAInKH5y+JckemK92yONmjgeYaqXYmDBs2rMg9Palb1je/+U28+eabxs16F1AfAoB99tknij1jUjHy/5ueYzqYQip3pPqS7qG2ydsi2d3yPcUpd6SLmAZOoidR7vBn8407mXcOfxS6RwSN3OHECv1fyir5DmmcckemqwVUNrll5fP5okGwoaHB6pbF8+AymFG+eBrSh1NGr3d1y6qvr486v8tR6K7KHT4AleOWJZU7Jvky310Diskwl8k2S3KHTsvSlDtZumW5kDu0kKB75P+lckdDPp9Xj1WW9xPKPS2rrq4O48aNiyV3TG5pHGPHjlXJnTAMi55NExOVzRRzZ+utty5xCzDtmhE6OzuNAZVN5M4bb7yhlke6ZWngdZ6U3KH4D2QIaGXT+jM/7lsezWkid0i509TUVNRPeJvi5A5vy1r5kih3mpubEYZhRO7wBQTlTe6Q2YxomRcbubN8+XLU1NQ4B1SWcbE0ZEXukGFYLrljUu6YDGZJLPDjXKVbllTumMaYcskdubhKQ+5oC+z6+vroZBYgvXKHu7rV19cXzfnaOGYCJ4vks7q7uzF58uSiz67kji3mndyMAYrdPxYuXBipKUwxd0x2BbmimGBqF7I/nnLKKdHmmyu5Y1LuaP2J6lsb012UO+SqTCS0PG5cmxeJ3DHNC1mclsVhU+6YIE/L0pQ7Wswd7sJFkOQOd+k0kTuaOouw9dZbo6mpqSQIrrT/4mBS23C4uGXFjRHLli2L7iXwgxj4+9BOy5LjI49rGoZhVPemjQoiJBoaGtR2x8MLyGebIO223Xff3bhZ7wptLLOpGLNW7tDcBqAoPo5G7ki7RIu5w8d0qdzRyso3MLWYO+W4ZUl45Y5HBFfljpRVciaeGurrr7+O999/P5VyRxt4aGdOI3eoY3NyRw6mrrvwfFdLc8virGwatyxtl1UDV/pI8IVYucodk1uW5gdLzzEpd+IMcKDUqMlCueMSULkS5E4+ny+JuQOsnZgbGxuj8sqj0DXk8/logQ7YyZ0gCIr6TBpyByi4sHByR7YhTu7I8nOYlDtAKQlVW7v2KHgT6TVx4sSoTNokSJDKnTi3LL6L3dvbi2nTphXFVSG4kDv8PZqMDzlxk1sWGY4ybtkmm2wSKaq09koTNj8ti8gdeo9kmFL+Ojs70d7ebo25Q0HZAZ3c4fXMd+B42TSQ0aspd+iv7Ntp3LL4woLcspYvX17U1kxp0dzCF+hpyR1XtywioJPE3CFIckebU+Q4LZU79P/hw4eXKHdMp2WlJXe6uroSKXe0dh/n9qQtsGtrazMnd7jLLZCM3LGRl93d3Zg5c2bR5zhyh8YAl5g7HFx5QWN2mtOy4mBqFzK9z372s1EQUXomlSkIgiK3LBO5w+PjSFBZksbcIfDnA8XqSf47B/Vv07xQabespModHlCZn/SnKXf4tbw8fD7hxBePucNteJtb1kknnYT33nuvaDEOJFPukDteFm5ZFHPHpFileY76E5DMLcuk3KG1DdW9idzhNhJ3v+Lp8eclVe4QZF0mHRu0dmnbiDAdhU4wkTtSuUP5vvrqq6OAxjz/adyy+CYyd8uiNaJWx2lj7kjljnfLKoUndyzgRpxG7kiFhnTH4TF39txzT0ycONEo4+MTSZxbFj0/DMOiQbC+vr5Enka74uWQO5zEkm5ZnJmPU+7QpM+VO3wRYstTdXXp0X0EzS2rXOWOdMsyDQi0I8Xvt7llaffbPpvyl8Qt61Of+lRJum1tbYnIHZIFc3LnySefLKrjOOUOH6RdVAH5fL6IaLGRO3LyiosPYyJ3Nt54Y2e3rDjlDh0taSN3SLlD9SaVO/PnzweAorHDRu5w2bum3LG5Zc2ePRsdHR340pe+VJIujzVgAn9OWrcsed1+++2He++9t6jcHFy5o7ll8V1meucUk8zVLStOuUOuQBymfkxyda7c4e2IK3dsygYTtJg7pNxZtWoVamtrrW5ZPC88DdO7j5tHtMCM8l7uljVjxgzsvvvuRe04jtzhmynyXcvdYLpWU+6MHj26aPFDyh3ttCwbeRxH6lPcLQ1ZKnfkfXQ6nCu5Y2rTScgd25gR55bFx3taYGsqVL7zT/HLeFnkMzX1NNU19R+bW1acXWFTFmmQixFth50vfDTlDi22a2triw4BsCl3NLesrq6uiIRNS+5o7spkJ5nmyzhyx+UodI40yh0ec8cloDI/fTBOuUN1Jd2ySCVGzyHIOmxqasLGG29cMm4kJXcA9w3EuNOyNFKWPi9dujS6l75P4pYl61OSFvTZtN7g6xSNVKyvr0+s3NHGsnKJAu1daCpGoKC6zkq5Q8/dd9998fnPfz76XlPumE7L0mLucALIhdzh46yJ3NE2CmyeKJ7cKcCTOxZwUkOSO3wCTRJQOU65Q8a9C7lDEzqBlDsEbuxKQyWtW1Y5yh26hhQFDQ0NicgdbZEly5OFcod2VOQiXBuINbesJMqdpOQOH0iBteUlpUFvby96enqKFq2bbbZZSbtLSu5oMXdOPPFETJo0qegeGXMHWDuA88WiC3FG5A53gyJo5A5vP3EGuI3c4QGV45Q7pjokMmzVqlUleZHyXr4g4e4AdXV1UVBgjdzR6k1T7siYO9XVulvWlClTAMBI7sQZQLxcruQOJ9A1wo8bYUmVO+3t7fjLX/4SKSYpTVq0x5E7lJ7cLZV50ZQ7pjatKXfkaRtyhyxOucOhuWWR8glYa2SbwBe6/Rlzhy/wp02bho8++qgkDVOfpvmSK3e0uDI1NTUlJ4Zx5Q6NcS7KHRu5U45bFo+VY1PupHHLqq2txeWXX46f/exnAMxzTW+v22lZLuSOrS5M5GVVVRW6u7tVckdT7lBdypg7Wtwhk3JH1rXttCzeX7X2b9qEMvWVpOQOJ1d4mtxupDSTxty5+eabsf/++5eUk4M2NulefvoW/a4pd5K6Ze28887YfffdjeXIWrnDT8viahyTWxa9Zy1+oSR3NOWOzS1L2hY0N8r+xNto1uQO/e3o6Chxy6I5T9YrlYXmOcKoUaMSKXdoA4ZA7dVVucM3QbWN3nLdsghxdRkH7X6NcAUK7Y027ONi7khw+0e+M81uTntaVjnKHZNbluk+0zWmccuTOx4RbOSOzS1LBrnjMJE7fCB3Ue7Qjm+cckeTWCdR7vCBhJM7tJhOotyh8pKiIIlyp6qqqt+UO5K0o/S0/EljkU/elVDuUPuTAy1NtDTZSXJHkntJyJ2amhoceOCB+P73v4+JEydayRh6/9ItrKamxqjcsaW3ePFiTJgwoeQ36ecvlTtx714zoAFggw02KIqdkFa5QyfTtLS0qIYFQSp3uIKlvr4ee++9NwBgt912c1LuSHJHKnco/zKN3t5e3HvvvRg2bBh22223knSTumUlJXekcof6DjfCtHdK7Ywrd/j7+/73v49JkyYVLXxM5I58L8ceeyxuv/32TJU7ktzhSj/A7JblapAQIaERqVtvvXWsWxaf17Jwy+IL17a2thJik9LmYxeAkngrgNloo/FfC6jM3wuREUAxuUPX0HHYlC9aYFAb4SSjbZzOKuaOtDk44sidH/3oR5g6dWpJvr773e9GO7W2cZe7JRIkuVNdXYhtNHfuXIwfPx4zZsyI3hW1P1tdmJQ79fX1JeQOJ+5k3fN3zckdbbzQ+pIWENfVLUt7D6ZNKFdyh7dZV+UOXStt0ThyR8vThx9+WJSGhFTuyL6WJuaO1p9+8IMfRBsOWjls9ku5blkuyh2yRzVbqqqqSrVttYDKmluWrEMTuZNGuRNXF5LcIVddvmCneSpOuUMYNWpUpPgB3I5C5yD7gIgGmptMAbq5XcHtDEJW5I5UsySFdp+mYgTWtjceG0eC2zMc/F2ZCDlg7bt2ccuyxdzhbYXWiCbljjbG8Xxr0OJW2sA3Dz254+FM7nClDl0PFBprnNFPShE+SEnljjbwPProoyWLCknukFxUKncozodrHfBy8o5cW1ubWrlTX1+PzTffvOgYZ1uni1PuyF0JTYrpAr5znZbcqWRAZXmdXABS++SD/Kc//emidEeOHBlL7nDDora2Fpttthn++Mc/Fg3GErlcLlqg1dfXRxMwyeWTKnfa29uxcuXKoiPQCVIKLskHW9n4ffL5w4YNQ0dHR9Qf6V2SEeUac4eUO0Tu8Odpp2Vxcocbcueddx4WLlyIjTfeOLFyh2JbyTalKXcuu+wyPPTQQzj//PNVA6FSMXe4ckcjd7hyRzPkbAGVOfiYSuqWuJg7EyZMwDHHHKP24zjljqkfS7esfD5folDQiFtXMp5iVEk/9XfffRevvPJK5LZhAh/vs465097eXkTK8j5VXV2NN998M7qWH7uehNyRAZWlckce9cqJhQ033DBKj64hxQHQP8odV7esuJg7zzzzDGbNmmXNl6mNJnXLevnll7FixQpcf/31qZU7/FlEdstAzWTvmJQ7pN6jdmLaCZaKHD7n8zy4BFTWymfbhNLgotzhqnDKr6w3TmrS9Uncsqi8tBhzJXd4/fPf5TNtto3pNx6IWMuHCWncsnh8uiTKnfb29li3LFPMHVe3rCzJnTgbU44/9H+prtWUO/QMOQePHDkyVrlje0dkH0hyx4SkblnlxtxxsfU1uCh3qF2QgrStrc1oX9lUg1RG+Uz5vN7eXmtAZdnvy1XuSEWkC7ljU+5o4KfGenLHo4Tc4UaxJHeCIFAbZ5xyR1sgclm5TI9w2GGHYc2aNUXpNTQ0FN1nc8tKE3NHU+5IcidOuUMEUG1tLa677jr84x//KCq3CdXVyWPupHXLMpE72qAg3bL4zkwlAirL60y7+3zRuummmxb9NmrUKJXcMZ12JNufjdyh919fXx+5OaQld+ikLE7uUBuR5E5S5Y7JLYufygCsnXB4DAkX5Y4kd/jztF0HqjdOctTV1aGmpiaKmZJWuSPBjR1KY+bMmdhiiy1wxhlnqAtHTcKvXaPlw3QNzwc3BgCd3NGguWWRMoeDtw9XtyyZFw5O9svYZ/J+DlLukLJLumVp5E5S5Q53nSTssMMOGD9+fOw7NCl3snDL6ujoKCJ8CWTgUX//8pe/XBHlTm1trarcMZE7cnMmK+WOLaAytzPKccvSIJ9pKkNStyxCY2NjCbljy2cS5Y7NLStOuSPHHNm3+ZzPvzcpd/i12nu07Z5rcFHu8PGa+qgk3PkYZ3PLorLIMZ3qkdxukip36Nm2mDsmxP1G4yQPsp21Wxa3I12UO7TZqB1OUV1dHYUe4PmxHYXu4pb1H//xHyV5JlTKLYv+X1VVHP9E23QwjWujR482npaVRrnDbUmt3PQc6u+aepo/z/ZsmwpREh1J4aLcob686aabAijYECb7lhOKMk0TuSHz3tPTU7Zyh9o/4K7cMZHxGrTQBjZwcsd1jTXUsX6UMiUkucMnE67QIOPEhdzRlDsauRPnlqWlXwm3LL6rxRVM1KGo4w4bNqxkF1oDSaBpMcYniyzJnXKUO/y9k9FhWmBJYxFYu3CopHJH+ilLAo8bmHKBPHLkSKxZs6bEIOETZi6Xw8iRI/GDH/ygJOaIKY/cLauhoSEiOMgISOqWRbFvuFsWLRY0cidtzB1eHsoj7VbI+CNSuWNSCEm3LL7IiVPucLcsjrTKHYnq6lK3LHpeEARqn9QWVRLluGVJ5Q5dpymPOLbZZhtstdVW2HHHHVW3LP4sqexpamoqMobSkDvkwhBH4hOWLVtW5I7q4pblotzh46N2uoStLBxJlTtx+ZJGojyiHCjEBNpggw1w/vnnY5tttsHee++Njz/+uCSNcpU7o0ePjlyviLzlCiKTcoeQlXLHFlBZLqgAfRErF9QuSKrcMbVpE7nT0NCQyi1r4403xsYbb4wjjzwSY8eOjcjurMgdOdZr5E4ulyshMyW5o9VXpZU7clebbDDXmDs25Y4kh3hZ2trajLYcJ5d4frk6xRRzh3DQQQfhyCOPLCmnhqqqQuD9e+65B7vuums0fmet3OHXuRyFTuROW1tbiRqSyCxSaPINIRe3LLneoHfz85//HK2trVG6/eGWRf+XGzB8jIgjaJLG3NEUSiZyJ45Arq6uLnk/SQIqk/2rjbWURlpyR2v3sg7JNiQ7eOnSpap9SyfGmjwMXGLuAMXKnaampqjOpV2iKXd4e5DKHS1ffLO00sod1/a/rsCTOxZIcodPWDygMjVqGVCZfuOQnzV/bz5JA/aBh/+mBVSupFsWV+4MGzbMWbnDg/GZyiJRXZ0soHIWyh0+WJkWWDZyJ01AZdcdJvl/m3JHpjty5EiEYVikugKKWf9cLoc99tgDf/jDH5zzKJU7RO6Uq9zh5M6ECRNQVVUV7WLwATstuaMpd2hC08idJMqdlStXlih3bKdlcemzaTHmotwhtwZtocH7hlQ28LLyvEqVnoY05I5JucOfbzP8N954Y3zwwQfYaaedisib2traIlKSj6ncLYurXJKSO2+99Ra22WYbAKXvwpTn9vZ2jB07VjX2Af20LBelZVVVVaSUK4fc+fvf/46TTz4ZgNuJdnHjlc0ti3DNNdfgvvvuwwUXXID33nsPY8aMUduPyZ2Mxn9OAFA5ef7+9a9/4Te/+Q2AYrcsOiGpv5Q7+Xze6FagkTtaXWgnEMahXHJHU+7wsayxsbFE6WibAymdm266Cffccw/++te/YsWKFRFB43paFicXqB0ApaeXUhnkhhj1QT5WchKf8qrVl1a+SgRUlm5ZlYi5I8mduIDKJuWOLeYO4Wtf+xr23HPPot9NIHKHFAs0fmet3OFl4HZ5XMwdHndSPo/IZK7ckQG/pdqKypbL5bDzzjvjrLPOiuonCAKMGDGiaNOREDfuuCoXKFQE35Tq6elR3bKoXCalJMFG7mjE0KRJk3DeeecVXdPQ0ODslsXzqJVXbhrZ1kN0WqJNuVMJtyx6x2Qbks27ZMkSdU6gtDT1TlrlTlNTU9luWdQ/tDrKKuZO3HqWk16e3PGIVe5wcqempkZtnC4xd8pR7thi7nC3rCyUO5pbFpWZyB2XmDsmcidOlmnbEZMdl6sTxo8f7yxj52QWl+zbyB25i1tp5Q6vJxO5Iyc/qdwBSk8kkOSOaXfaRu7wmDukXqEdQp4nF+WO5pb1+c9/HkuXLo0W1WndskwErFTuaG5ZfJHnGlC5v5U7S5YsAVB8UhJPR5NHx5E7mhHLoY1Tp556Kh577DH1Gqnc4eQt5S+O3OF9jNpUc3MzRowYgZaWFuy1114AzG5ZQRBERKjcldSeQcjlctFJZpQ+hy3PY8aMKWpDLqdlxRkkVVVVkRFqkmabysLxyCOP4J577gEA1U1OIgm5w5VkvN2NGDEiIqaAtca0K4ggJbcsvsjlz9l6660jAoe7ZZHSq7+UO4B5ccLry6bcoX6ZhNxJ4l6r2QgauZOFW1ZjY2OJ0pTIHcqDi3KH1MBJlTuUPrcvtJg7Wn1p77oSblmcjOduUXKTRCp3kpyWxcuyZs0aI7lDG5tykRen3JEbjPKzCVVVVQjDMJqTaYFfCXKHtzf+mZ7NyR2aP2zkDilstJg7UgGluWV98YtfxMUXX1ySvowDBmTrlkXvj5M7cgOGrytk3CVgrZ1ZW1uLxsbGRMqdYcOGRcQYXWNS7tg2lE2KuyTKHZqb+tsti89DgJtyB9Dn/6TKHWqLXLkj8yXJHankcnXLkupEF7csr9yJhyd3LHAld4gE0HaK0ih3pFy2XHJHDnAunYEgyykDKhNclTukjKmUcocviGgAfPzxx/GrX/3Kmi/CrFmz8Ic//CF6pkkZQpBGClAaWNsGV3LHNOBxg1vbhdt8881L7iFFA+1YEyS5Y8qL6XvuliWVO8cccwwOOeSQ6FoX5Q6RT5QOPXvcuHGqJJzXkc3wA7JT7pgUKiNHjkRVVVV0FHramDscScgdCqyrkTv8Pv5/qj9uwJVL7nzuc5/DRhttVPIMKg9X7nClDZUjzi2LP3Ps2LERYURtmZ+QoCl3gIIBI409bjRrC9R8Ph8RaLJcVB4TxowZU9SGpEJByp9NYw9HEAQRKVKOcofnhW8ypFXuyIWrRu5IcKLHBTT+xx2Fzj9Tf6uuro7aQ38pdwBzQGRXtywqn+sOtpavcpU71dXVJWNFErcsU9vhbllElGjkDv2VblkyoHJczB2g0B64fTFY3LK0XW1O7nAiSSN3kgRUdiV34gIqu8Tc0WxSE2gzgjaOaG42zb1AercsKgN3LweKg8Jym2PYsGFYvXp1STom5Y7mlkXElzwRjX7TUGlyR8ad1NyyNHKH1zPN5xQLNIlyR57WR5temnLHtqFs6rdZKXcoDdf2Zbqfg7+nqqqqqC1+6lOfQlVVFZYsWWI8CRCIV+6YlI8ErtwZMWJEpJiV5I4kJaVyh9qO61HoJqWlBtl+4tq+J3c8isB3fjo6OnDAAQdEv2kxdzS3LGnEuSh3qqurI/9JIL1bFu0Kl6vc4Tt5vKPzNLJQ7sSRO2mPQnfZ+eY455xzovzw9LQ0tMkja+XOEUccgXfffTda9PBr+IAr5eavvvoq3njjjaLrALNyh2SfgH13WgtYS/dwo4jUK9XV1bjkkkuKggFq5Iqc0LXA1HJiMSl34mAid5LG3DGRSDS50bGVmsKEruPKHS59til3NMUYUKizPffcEzfffDOAeHKn0sod2T9syh1O7tA4E6fckSpJWqBLNY5JuUPXNjQ0lCw+CCbljo3csY03REJROlkpd7Jwy+LjN18s9ie5k0a5Q+SOLaAyzy9X7hAkucOvB/pfudPS0oK3337bGlC5HOVOueSOVO5wlxOX07JMz+fKHZrzNXKHylNOzB2+eJXKnYEidzTljrQtaZzgCzk+xsUFVCYXNv4s7vZoI3e4Wxigu2W5kDuaAlmDJHdobq6kckeSO0QqcHKnurraSO5QeWTMHR5QmdyyqC74piDVoale0rhluZI7XK1vc8uidsSfHUfu0DvTlDuSSJdjb5LTskzpEOShAy7zkTYHxq0P4qDdQ/N4EAQIgiBqFw0NDRg/fnwqciepcoeTOzKvktAzBVSmNsFVbxL95Za1PpI76ejG9QRcuQMAr732WvSbdMviyh0bueOq3KHn2o5NlelJ5Q5QkMJLw8SV3Kmuri4iY6Sx09/kTpKYO2QQAKWkgSu4GsQ0SdjInaxOy6qrq8M222yjTuimBWBdXR0+97nPqenSgC3JnfPOOw+HHHIITj75ZOsChi9qOTi5U1dXFylutDbB0+YTQhAEUX+wMfl8gUGfk+yemCYQWiyREZHmtCy+o0yLFE0NQ9dy5Q7f8dCCCgJryR2traxatQpvv/02pkyZAgCRauaqq67CTjvtVFJezYVUW/xIV1ENJnKHt0tbzB1NuZOE3AEKMXgWL14ckTv03igfVVVVKrlDwaR53ggmcmfp0qXRZ9NCWMO4ceOK2lAcuaO1bT6+0ecslDtceelC7lC+ampqVINTLhC1gMoS5Sh3wjBEdbUeUJl/diV3KqXccYm588gjj+CRRx4pck8g7L777pg5cyY233xzvP3227HP0/JlKgONLy5uWbx++aIgSUBlLZ80blI/pl1/bofU1NQUBaeWblmmxYKmcAVQotxJ65ZViZg7sizkMsiVO3yMThNzh8gToGAbmMgTGfNNc8sybVgSaOHKP5tAYx3VUxq3LNt4c80110QbUUmUOzZyh+qVyB3KqxzvOZEqlTucQJMoR7kTB025QySUSbmjzRPUnzTljkbsye9syh0+xx1zzDFYvnw5Fi1ahOnTpxeVhatJOKRyx4XcsSl3qC5sajINWt5IbU9uqdQWa2trsdFGG2HRokVqWja3LG5DyDYVp9zhafA8SxdGqdyh32lcMSl3iFSutFuWa8ypdQXrRylTQpI7HBq5o8mA45Q7moTVNmBKyJ13mdeOjo4SVtmlM1B6fJKRxk7Wblk2AiaNcof/npZV5+m5umVlrdzRdvLl9fIdy2e7KHdGjRoV+fXaFjDcvYqDdtfIMCaDST7HVD45EVdSuVNTUxO9O96uadHlotw59thj1ZOZ+M4GnbRhOlY6jXKHDC3NIJYLbFqwnnrqqfh//+//FeWP6oGg1R9fjF966aWRqk1DGuUOTexSuZPGLQtAdGy85pYFFOqeCAB6D6Tc0foV3QMUv4845Y4tzxtttFFi5Y5Mf5999sETTzwRlZeTO+XE3DEpd+Ji7pj6niR3iDAfKOWO3JnnfYHI6IFU7mgEmfbdFltsgZdffjl6/y7I2i1LKnf4oiBJQGUtn+SWRW2Zn25mmgNIjZIm5g4QT+5kodxZvXo17rvvvqLvsyJ3eH+Nc8v6+c9/ju9///tF/YPnw6TO5XlJqtyxKaFs4yUdhe4ac6eurq7IFZjnVcORRx6Jo48+GkDp+EDtuFy3LHL95ModYG0sm6qq/nPLioNG7gBQyR2bckeSO2EYoqurq8TO02LuyA1Zm3Jn/PjxeOSRR/DpT3+6pCymfpsk5o5LQGXTc0yQdgkHkTuULid3Ntxww+gUWYlKKHfk+MKfExdzh363kTtcuWNyo+Wg9ijHyK233hoTJkwwjr3ro3LHkzsWmMgdWpRogXeB4oYnjThNuaMFVObPdVXuyOOEgULH0gZTl4GeYg1pp1RIsqM/lDt77703Dj744JLBiy9+5ABE/0+r3Ikjd2zKnf4kd2QZTcQAsHbSlTF3pMuRaQGzzTbbqIQNkXv0bFosyeeYyifVYbYYVhq5k0S5Q21Gtgup3LGRO6+88opVHst3oDVXJ7pWKljiYu7w+yS44Th27Fh1cZWG3KmtLZw+ddZZZ5VcQzDtbJmeJ8uThXJnk002AaC7ZfHrm5qaovatuWVpRjM3dCS5E6fc4elttNFGRuUOEXc8TUnc0ndf+9rXou+DIMjELSupcieO3NFcTuLInaTKHTr9kZ+oRPlOotzR5o6BVO4QtA0TbRNDA2938h2Z7jWRO/KZNnLHdOIfh6kOuVsW9TkajzVyJwu3LAAlblk8jyYFgNY/bOROU1NTif1C+ZXloucCOrlD9c8Xx5zc+eCDDyJChKO6uhonnngivvWtbxU9i7czOm5cgyR3XGLuaJuDmnpDAyl3ZMwdjdxpbGzEBx98gG9961tF39vGG23zweaWxW3NYcOGqe7KlCYpd/gJXzJoOo3v2nH3pnopxy0rDjygLu8f2mlZsg3Y3LKAQj26kDtyQ8Om3LHNQSY7yTXmTn19Pb75zW/iRz/6kTpemjZX46BtJBA4ucPdski5QweNSMQpd5LE3KH3n8Qti9cBr3dOzEtoMXeSkjtVVYXTc+fNm4cddtih5Bl0nyd3PCKYyJ2amho15g7BVbkTBEGsWxb/rEH+pil35ABnIndkR+K+v65uWV1dXdaJOm1A5aqqKkyYMAEPPfRQyc4uZ4nlwoi+S6vc4QOCaXCX5dViL5ngQu5IdxnNKJJltBEDNOlKgobULEBhhynJohpYS+5Qm3dV7nCChj9Tcw/Qdo/pbxLlDvUB+U5lQGWacKhMUsquge9suLhlVVevVf1xgtZG0FVVmWPuELR4OzIdXrda/5NuNLY+mka5Q+ABgYHylTsmcof6BTeADjjgAHzta18zumWNHj0aVVVVRYG9k8bc4Z833HDDIqJAEiAuyh1J9FZVZeOWxeNuJCF3TOmmIXdM7rcayL2DAunKgMqm98Kl5BJyE4M/C+i/mDsEjdxx6Y9A8XtLotxJc1oWJ3eoDWrGOMFFuSPJHT5HaModLaByWuUOL7PJhtCUbXExd2S9cncEjQTh18iYO0EQRHXNF3Dvv/8+Jk6ciA8//NCYD5kX7paVRLmjuWXFxdxJelqWK7kTBAEmTJhQ0rZtc7YLuWNyyxo+fLiTcofyHoZhERlENo603WTQaq2c/C/dZ0PWyh0+L7nE3AEK9SjtPBebnYglmp/4+Gmbg0x2e0NDQ9H3pnoeN24c9tlnH/zud79T26htA8YGLX4mQZI7UrljCotAaSVV7sixmSt3+Jjootzh4yVturgqd2xuWVQm2d74NVrZCJ7c8SiCidyprq5W3bIIpuCpdC2hvr7eGFCZp+Oq3NHyqrllUaeTkAZnfX19kVuW7ERSoUQLFdNRoEB5yh3t//j/7H15mB1F1f7bd5t9zcxkX8nGkhAghEAIhB3ZRXZBRAUEFERERHHFDfXDHRARFTdAP7cfioqAgIALn8qi7FsCIRIIhOyZmdu/P6pP9+m6VdXVffvO3Jn0+zzzzMy9vVRXV5069dZ7TkFtuOTBo1rlju4acuw4IBwDmQzTwYbc4avz8jG6wUUmBvh3urAsrkrh91NBpfhIqtyZP3++Xx5+f1UycJ1jn1S5I9e3LqEyfS7XkQq8/9J1dNtKU7viA6Ru1Vt+76py8JV/WZoulw+IF5YlnytDdb4sr9aRO7JyJ0lCZaCS3CGbZiJ3LrroInzzm99UOpwAcPLJJ+P+++/3Q9yAypw7Mkz92qTc4WU1TSxV5E5c5Y5NO6b6TRqWlYTcKRQK2gmyDO5oqrZCl+tNDrsoFAp4+umn8fDDD1dcUz6fE3I25I7pmDjkji60hspvgql/m8gdU5vjYw4fZ4jcURHUpnwVMlQ5d2yUO9Xm3DEpd3QKABV5pXu3unfGt93WkZG6sCx+P97uf/zjHyvLwK/J/87lciFiNwm5Q+frtkKvZrcs13WtEirrrmNL7sj2wZRQ2SYsi5Q7hMHBwZAqSrWbbZywLB1RyaFS1ZgQJyxLHldVYVkNDQ2xlTu63bIIKnInjnLHJizr/e9/P+66666Kz+XrUxmSKHdU5/Aca7lcrkK5E1WWKOWObkwkcJKeq2hln4PO0yl36JionDt0rCks67777sNll13mP1tG7kQjI3cMoAFKniiTckdH7piUOypyJ0q5Y5tzh59DUIVlqVaCVWVNEpa1ZcuWxOSOqdPFJXdMqwA6XHrppbj++uv9/7mzpSMPVIPHli1brEgAoHICoCqnarLH70+/dU6rfI6O3OHKHVXZdOXksfabN2/2+wspd1TOD8e+++6rLCc5sComX0XuxFHuUB+Q6zvOVuima9OxtOKXhnJHdo6jcu7olDs6csdkE7h6TNeuq1XuxAnLmjhxIi688EIsXrw49DmFZck5d+TVJpUDpFPuNDY2YtGiRaGyb9y4MURaypOhKHKHEwXyhF7u5yrbIx/DlU+2OXei+gspIUzHRil3dDl3ovqQbWiWTO7YKne4VHzGjBnYaaedKq4pn8+VOybbrsrRJCNOWJYKqnFOhaTKHT6e6FSxOuUOX401tR/d/XlYFrVlmtDXMiyrqanJ/86W3FGRn7r3LpebwMkdXeicTrkDhNWJVI6//vWvyjLwa/Iyye3IhtyR65/8WFVCZRWZoyqHCrlcTplzR0V66q5TbVgWqW1KpVLI5+DkDn93ZCvkZOjr1q3DwMCA7xtRzh3Zn7INy7JR7tjMIzh05I4qLMuk3JFz7gBqckfVL+Q6kVNOcBtjGoN0/dYmLKurqwszZ86s+JwjavFXByJ3dOoz/jdP8yCTharzdL5NXOVOPp+PvVuWbE+4ckf1frgvYArLmj9/Pi6//HIlkWdD7pRKpYzcyRAgKiyLvlcZZ4IpLCtKuWOzs4htWFYS5Q6P/ZUn/nwFg56TdjQwrbrSSnXa5I7ccU2OhA5NTU2hpGyctEtC7pjIEX6+6X+6N/8uCbljUu7wlR3b1TS+skL1Iit3bCdou+66q/Ke5MCawrJqlXOHHElVWFYUaccnCOQUcjsgS5vz+bxvA/gKlWlCpHNaqgnLslHuAPp+qitvEuVOVFhWa2srrrzyygqVii4sS560xSF3CLwOaMeKiRMnAkBFYm1Tv+7r64ut3Ek7LMtmB0E+WdRNDKLCg+TdHokcjeqrtkmV6Z3ZKnfo/yRhWfR5uVy2Uu6YJlOyX0DQbT8tw1a5YyJ3dO9fDhWR+5ANuWOzQGVyxCksq6mpCfl8XknuyLleiBzZunUrXNeNHZZVLBZDCk0grJBQlVcVlhVF7sh1YUPuyKHeUcodE2RfUDUOJkmoTP4wqU74s8jKnVqFZenGZlvlDh0n73hK4zjfdYfIHfqOk6D0PDSJp/GIxgm+i5a8OMz97ijljg25E1e5o9oKnZ4rKucOf+cqckeXJoKux+9lIndUNl7us3IZOWyUOzaLs3x+kITciVr4lMOyTHMrKq/s2+hIeoJOuVMqlULXUqly6Hj6Xj7GFJZFcySZ3FH5+/L/OuWOro3L/XZbQEbuGKAjd4rFou880KCVVLmjSj5Xa+WOLueOvEuPPMjInYiXs1AoWCl3APgZ82XYKkXiKndsJjJ0HCe4uNOjM96q3bIo2aHN4BCH3FFJcbnDLbct3XWbm5uRz+d95QEnE2wdLqBSPbPffvvhzjvv9K/H1S4m6Cb8ppw7CxYswGmnnYY99tgDQHrKnWJRJEw0KXei6oU7vTbKHbnOe3t7MWbMGOV9+GQ+KucOV0Spyif/bUvu6AZQG+WOjiSSCeco5Y7uHejIHXqPpOzhIQiqa6quz8tHO1ZQSKGcVFNlowg9PT3+/2+88UYFMSQ7SCrbQ99xmxAnLMuG8OYOdFRYlm4L2P7+/lDb7+3tjQzLAqpX7ujy1cmTtyinXqXckY+RoQtFsgndiavciUPuxA3LomtTWeOQO9Uod4jcoW3OS6VSrITKQFh9YKvcock6P4c/s6q8NEnjE8uovpJ2WBZX7owZMwYdHR047bTTsMMOOxjLQZDHwcbGRj8BsAq6sCyyAbpJWjVhWdWSO7bKHfKNZeXOunXr/LYnkzv8/dHn/L4PPfQQfv7znwMIyB1S7tD9ZRWJastwjjhhWVEEvAyeUFnuO7LvIvuA/B485w4Pb5P7kmxX6Pnk9iP3VfpftjV8bNctgtkod2zmDKYx2gSyG7p8lORX5HK5ULiSKR+dTrkjk8oqn5eDlDtR5I5JucNtNBHz8n1kG2uTUDmucoer4FWL46MZ28ZTJoSNckdFJpicONmxqHa3LBvljmx4VCvB/FwqMyV2I4dZNoZ0jYaGBuTzeT/nDrHLunLrlDsmmDqwSnJoWgXQQSZ3+Aqzrs5Ug0fayh1eBvkYbnBNyh35nJaWFn9g4c6x7QSGl4u/5zVr1oQc/p/+9Kd46KGHjNcBgPvvvx8/+MEPQvc05dxpa2vDDTfc4K+A2UwYOXTkDiDav5xzZ8GCBZg5cyYmTJiAVatWRV4bCIdlmbZCl5/vggsu0MrqeRtQvR8aIH/0ox/h6KOPVl5Ddj5VfxPSJHfk1VuTc89361A9p65tTpw4EWeddRYOPfRQAEG983o5//zzccEFFxivqbq+3M4B4MILL8R73vOeii3idU4J/U3/f/CDH8Q555yjPJf3bZ0ykf+mEACe+FkGX+1MQ7lD19CRErKt33fffa36qq1yRyZ3SGUqO/4Euq9qK3T5mvL3tsS3jhDT5YzgsFXu0ASmGuWOyb7TmMpDMVTkDn8mPimoRrnT3NyMTZs2+dfSkTvz5s3D0qVL/ZC6YrHo3492TpPvLdtNXieFQkFL7sjkxD777IMHHnjAvzcfQ2sZlkXnqsidQkHkqlqzZg1uuOEGrR1Q2Sb+2fjx4xPl3CF/+cQTT6x4ThW5o+tbMhzHCZE7aefckfsyJ3eon65fv75CUcvbC/2vute8efN8okNH7sjjA58wm8pcC+WOKSyLkyx8DKkmLCupckdH7nDo/CSasxDiRhLIx+juo0MUufOXv/wFr7zySkW0RDXKHV37VCl3+vv7USqVlLuSyf2+v7/fzz0aV7nDr2ezFbrKhprmhlywoFMpjlZk5I4BfKtzjjjkjkm5UyqVlDl3TAYzKkeLLixLNqYqZ0teqTMpd3hYFhlKSnpHq+ZxSKko2Cp3VASILbmTy+UqBuso5Y6J3LEx9jbkjmolXz5efkZTQmWZ3KlWuSO/S37v4447DnPnzlWeP2/ePN/JWbx4MU499VQluWMj0zQpd1TPQQOR6p02NzdX7Ja155574sknn0R7e3tkvVCZdGFZqpw7vFytra3YbrvtjNeOIndM7T2Jcod/F5fcUa220HcEuU5poNeFZen6Vi6Xw7e+9S0sWLDAPx8IJlCTJk3CV7/6VZxwwgkV58YJy+K7SXz9618POeuq8236OUFF4MhjgmznHMfBuHHj8Kc//QknnXSS9to8LCvKPsUhd3SkBKkYCUuXLq2JcodyrchboQ+HckdH7vD/q1Xu2PRzIFx+E7kj979cLoczzjgDP/jBDyp8HP47SrlDNjZO2APZ3/7+fjQ0NITIHe6HTJgwAXfffbcffsqVO3w7XxOZHpfc4ePNbrvtVtEv+aRT97xJyB3bsCx+H90qv3wPecLT3d1t3ApdVqrQ9ajt0uKHHJYltzdbXyOXG7qwLCq3KueObAvJjyLIi3Ac9Hwqcof7IfS3KWyU36PW5I4cQs4/iyJ3bLdC1/m18v+2YVkcJnJHZ+flcpnAyx6HNKDxTVb8EpqamirU27JyR+dP6VKB6JQ78rMPDAxg48aNaGxstFLu0JirOqZQKFTYC4L8/uIod3gbMpE7cv7KjNzJACAgd2ilgEBEhqpRA9Xn3DGteskNU0fu0H0pLEueQKqMmY7cUSVUVil3AFFXUcodfi9bRJE7MittGih0UIVl8euqyqyaJMVR7qicahm61Xr+t/yObZQ7PPQFSEe5w68XhYceegivvPKKtpwqckf17ulzXZvSDdw2yh3VwPT2t78dP/nJT7R5M7izYZtQWX4eHXQryQR6p7bOLHd+ah2WZSJ35OfmK4cmZzkKVO82ioiotq96Pp1DHUXm2JBvqratI7Hp97777qslDnh5TTux8HLYkjuLFy/G7NmzK76XyZ3Ozs5hVe7YkDt8B0Rd36xWudPY2BiZEN0EOi6tsCzVeDF9+nS89a1v1S4u2IRl5fMidEUVqq2zdS0tLb4yyaTcUZVHpdyxzblDZeU2WQ5/0d2bT6Dj5NyhHEF0rvw+6RxVQmU6lk+2OXgOM8IVV1yB973vfaHP5HGwtbU1Uc4d2Y+VJ2lJlTtE7sgJlWsRlkXHqsKy5IUOai/yPXSLgEBlzh36Tvbjosjb4dotCwjn4KJrkr3m5IMtuUPPIi/iyXOWJMod20XZapU7cckdk7qWQy4jV+7I/ifVo25hV5dzR05b0d/fj1WrVmHcuHFWOXcofQL/TkW46cKyZHLHZjGXtw8TuSOnGsnIHQUcx8k7jvNPx3FuqWWB6glE7sjsKm/UKoOetnKHX0+Xn4fOoUZMzpSKmIlS7vDVK1NCZe5c8A6aBrljUiipJvgyKy1PHG3JHVmGaDLeKmksIAi1Wih3TDl35GfUrQDS39zZJsmibtDVoVpyRwV5kOEOBJBMuaMb3HWGnit3Vq1ahWKxGBqM8/k8TjrpJO0kmqsJVOSOaSU5qs55GzC1LxvyQL5OrcKy+ORL/o4gP3fSsCwZsnLHhDg5dwhR+TUINv1c/o7/tiV3osCTn8Yhd6LyOXR0dODxxx/H9ttvH/qeyJ0lS5bgQx/6kH/dKPt/+umn46KLLop8HpnckZU7Kpudy+WMYVn8ukmUO+3t7Tj++OMrcl5xu6hr13GVO9WEZcVZDOCfmcgdkvNzv+S3v/0tzj///Iqy6eqej8Emckcm4Lia+KMf/SiefPLJimczkTuFQgFNTU3KZJ1Rv3l7s825Q0odsk0HHXSQMpQ2l8tVhCzwvIWycoegIneOPPJIzJs3r6JcMrlDKhkV5HwwclgWQV6UMSVUjrKHfCv0JLtl2S52AHrlDvXfpUuX4oQTTsD06dOtyR2TckeeqHJyR/c8QxWWxa9J91Ipd3bccUfcc889OOCAA/zjaR6QRLkjEw65XK5i56ZqlDv8vrpzbeYMOv87CrbkDrdxjuOEyDNdXk2dLdcpd/h3gHj/K1euxPjx45Xkjqq+5e9U46cuLIuOjROWxdueiaSTlTv7778/Fi5cWPH8oxFx5BMXAHgUgD6j0yhDFLnDt6PkE3DeeaKUOxs2bIhU7vAGKycClY+l321tbb4qQjZwOoNXbVgWIQ1yJ5/PhxzduOSOPDDYGmpTQmXd5FSuS5rQDFfOHRWxJJ/DjTZ3xqMmuKpyyfWiU7TYgJeTJmqmFT5u7Guh3Fm+fDkmTZqkfC9Rqg2acNI1CaaEylGTdN4GbBOQm77j96+Fcoc78UmUO42Njb4zL1/XBlTvNuRO1HtQPbetciefz+Of//yn79TbvB+VI6Mjd2zrg6+yR7U1HiYSRZyqHC0gSKj85z//2f+sp6enIoxNxoIFCzBhwgT8z//8j/E4FbnD1RO6FdkohVsul6sgwGyJ73w+j5tvvhnf/e53cd111/mfq8gdeYIapTBraWnBhg0bQnlWTLBRPQLJyZ1p06ahqakJW7duRX9/P1zXRbFYDLWLvffeW7krjK79yWNTlHKHTyToOa699lr/GqacO/ydUFiWidyR27u8EMcVBYR8Ph/a1lpH7px99tnYZZddKuqDT/bpvXPlnY7cUYVlqdptoSDSDHzhC1/Aww8/bGUr+f14EmsO/s7l8Up+D7UOy4qj3NGRO5SMf9q0abjpppsAhIlInTKCf/bqq6+iUCiE3g333cjPjgrLUpE7ukW1uOSOabcsIEzucN907733xi9+8Qv/eKobebeszs5O5buXba1MrI8dO9b/n/czuR1y8HbmOE5FsmV+PRk2cwbT4q8JcZU7VBc2yh0diW8id3hd9/f3Y+XKldhrr71Ctlhlb3XfqXw+nXKHjo0TlsXbh+k9trW14aMf/SiOOeYYAMCvfvWrimcfrbBa7nMcZxKAwwFcF3XsaAIZWHlyYSJ35E5uE5YVtVuWvOrBIXdcOocrM+Qy6a6VRlgWv3c15I6uU8t/07FpKXd0YVnyYMPvIZe11jl3dKseUYMc/5sbbb5NYByioRbKHX5P6l+cINDVlynUIy65w5U7zz//PKZMmaK8btTEnn8ftRU6wTafj+y0/PjHP/YHMMB+pZJfp9bKnTg5dyh0gE/mdOeaUE9hWQsWLMDkyZO11yeoCJMZM2agvb3dJ0V0zlQU5DAUE/jqaBS5oyuHKnn+zTffjK985SuRZY2zcsrDslSruqrrmvIOqfpEnJBV1TFpKHeuuuoqXH/99Vi2bBmA6DoyjcHyeK77zkTuTJ06FRs3bsSCBQtCYVkNDQ0YM2YMJk6cWHE9+boyVOSOait0eVLIyR0Ok1JStVuWitzRtXPZthUKBfT29uKSSy7BYYcdpjyXkzuFQpCTQtem8vkgB4u84QOgX0xRKXd05E4+n8fFF1+MG264IXK3U/n+RxxxBAChtuPgyWJVag3Tog0HkaDDkVBZF05NUJE7qntx5U5XV1dF/5L9OFtyR0XQqnIq8d9R4LtlRZE7JnKfjpPJHVVbkJ9V1T6iyB2d+kZ1ffl/nY8YBZX/bQPbPibbOG6bdMod3ee2yp0NGzbglVdewYQJE6zCsvh3pmN0yh0ah2sRlpXP5/GpT30KO+64Y8Uzj3bYeYTAVwB8EEClNfXgOM5ZjuM84DjOA6tXr06jbMOOlStXolQq+TsiEEzkjmyU5NANHs/f1taG9evXVwxSqtWgqBUJmdyRJYymidT06dND1+JhWZQ4Wp5kmcgdWpUwDSY2yh0OUwdWsbjyhFm3sswhO/vy4CWXWTXAAtXtlmWajJjIHd7uVE6ITI7J5E41yp1akTs8p5WKpef/5/PxwrIo75SqPXByZ/ny5bHJHZWzUcucO/l8HieffHIFoauDfD+6Di/vJz/5SQBq9aDcD2bOnIkzzzwT+++/v7K8qlUc/iz871//+tf4wAc+gCuvvBKDg4PaCfhIz7ljQ+7wtn3QQQdh7dq1fm4DeYKblNwx2WFOkkS1dZ0DLefcAYCxY8daJUxOQu5EbYXOr2uzmq/rm3FsOx8nCTpyJ6qddnZ24owzzlDmqVDBluSV3y9/Pt3YKjvunNwpFAp47rnn/Al/HIJWDssqFouxlTscccKyZHJH7l+69i4vxH3+85/HnDlzQvUURe6YFvBk5Q6/N/mYciiVSrmjqnN5kcM23xU9x3bbbQfXdbFo0aLQ97NmzQrdt5qwrC1btvh+ctrKHbneVcodQG0Dk+Tc6e7u1hJd5HNWE5alm0SbiF4O025ZgDrnjso3bWtrw1577YXddtutgkRV2VKdz07/y+SOTODrFjV1vr+J3JbLo4NuUT8KtuO1yc7bhmXJ/qiqnPz6K1asACAS1pt2y+LvUffbRrlDx6vCsnSEHK/vKHJnW0VkC3Mc5wgAL7uu+3+m41zXvdZ13YWu6y6kLVlHOlasWIFJkybh05/+NH7961/7kyfqCNxxVTV4QL2qQseOHz8eq1evrkq5owvL4hO9qAnkgw8+iJUrV1Y4C0nDslpbW5HL5YyDSVynVCYnOPi9VB1eHjx1kOuFq0FUxls1oAHxlDtxEiqbknzyZ4xS7qjInWqUO/K7VMXC20JHdtmQO2mGZf31r3/FvHnzsGLFCkydOlV53TjKHd1W6ConxgT+vuXJgmmQ45DbDznJvL9+7GMfg+u6yncs12dDQwOuvfZaJQnG26VO+QYEz33kkUfii1/8Ysj5V9WJrXOUNOeObhIkw5ZQtCFx5WOjyFzdMSbI5I6uDcvfJ1XuqMgdW9icx/ua67rYsmVLKCzL5MjakDtpKHeoDrkzXiqVlOONjtzRkWxRdaSaAMvlU11XZUtkQoPXrUzuAIEfAMTrw3HDsvjkpVpy59BDD8Vxxx1XUUbdPeUxV7XqLB/LVT48dFdXH3yyr5ps8c0zOGyVO7JvYxsyYvLR1q9fjwsuuCD0nSksK4rc4er5jRs3VqQniLqOzt7q7HwS5Y7OR+GflcvlCuWOTEDkcoGKQVduk3JHtglJlDu2YVly2+bvOJ/P495778Whhx5qJHd0RLr8fxLlDm9nJl/btAhggvzebGG7OKUahwhye6Rrzpw5E0Bl2JMpbJDX3fLlywEgUrmjmlfJx9god+g8m7As1b1N7zEjd8xYAuAox3GeA3AjgP0dx/lhTUtVJ1i+fDkmT56MxsZGHHnkkRUhCjbKHRMjPH78eLzxxhsVYV+q1aCoFYlqlDttbW0YP368MSyrUNAnVJZXIRsbG/H1r38db3vb25Rl5uXWoVpyRzdQmDq7KomziZlPg9wxrSYQTKsjfGDUMff0Pf+bk3/V5tyR27gqv4ItdPVRjXInSVgWADzyyCMAoFXuRO2KogvLqoVyRz7XlsR0HMcn41T1tPPOO2O33XYLTRR0JI2OWFWt4qiOsykvL7cNkubcqTahclS/Nj2viTDRTTbj5tyhc6sld0y2CbDblct0/yjIbYt2h7RR7tj0EV3ftKlveRyPUu7k83ltWFYtyB3+bPvss09IeaGyJfJvmfAdGBgIkTscqvauq38TucPHOduwLNucO/l8Hqeeeiq++tWvVpQ7iuRR5TXR2eckyh2bsCwb5Y4uLIvXCc+HZVqgMxHYLS0tFXZLJndsFzUcx6kgd3TtOg1yR6fcUY33fIdAk3KHP193d7eW6CI/M0nOHZ2NoLrW2Qq57uOQO1H2n2Cj3JGJUbl9yMSmjXJHZS/k5wH0xFAU5Pdmi1wuhxtvvBF33HGH8TjVgi5Bl/Jj2rRp+O9//4tLLrkkdK6pffK65+SOat7F33UU6W2r3OHkjiksSzXPNvm9GbljgOu6l7quO8l13WkATgJwh+u6p9a8ZHWAFStWhCZ2Mrmj2grdZtCixkhM9KpVq0Lfq5Q7dM6pp56KP/7xj3jLW96iPDaNnDtkRBsaGrTKHW7YZeVOY2Mjzj333IpdGVT30qFW5E4ceS6f/OdyuYpJvi4kIu2EyqbJnqrdqZwQ+Rwb5Y4tuSNPnNMkd+T3ZiJ3dO9WZeCpvlTfyYOQjtyJUjPYhmXFqXPVwBqX3JH7BpE7quc54IAD8MADD4S+05E7qtUaW3InKqGmzWcqUL3bqMlqGZYlvw8enitDfp8q262bbEYhqXInKizLRJgkVe4kIXdslDs2Y4GqLcchvuVr5HI5Jbkj96so5Y5um1sdbJU7F198Ma666irld7r2aArLMt3L9Bmg3i2LniMqLCuqj8o2X1bu6Mqos7Uyka8iA03kDk+obCImVIn5ZXKHctEQ4ubcIXDljm5HSH5/gsmXUY1zcch9IndaWlqwadMmbbvW9UtdeK/qszjKnRkzZuBd73pX6Hudv0FQ5dyRFxGThGVNnDgREyZM8MMB+b3b2tpCC7433HADbrnlFv95OWzDsuRym8qbJCwrapIv1/eMGTMqrqMiIFTXrFa5w+vCJvzNcRyceOKJ2G+//SKP05VPp9wBgL6+vgqf2TbnzvPPPw8AfgJxgmmuq7OLJnJHJt3JR1PlPJP/tyV3bP2i0Yht98kjMDg4iBdeeMFPgAlUkjtcuWMK35FBx/T19QGwI3e4ATzggAP8ssidSKXckQdWXYOn+44fPx7t7e0oFovKhMqUT0YXlsVjcnWIcvhNkyMbckd+3jgOPS8jf6+f+MQn8KMf/QgHHnhg6HjZoahVQmUVmaQydknCslTKnajy0zmUP4MSSPJEinGhe++6yWOUY8/LyUHOg6qv/uc//wn9n3ZCZVOCz6g65+87qXJHvh9J3G0n4XHJHSIyhkO5E2fnNtuwLP7+dG3Opl/rYCJudN/VmtyJG5alytkSF6bz5PvKEm+Tcse0gklQEWu27VU+hvq4itxRqV9UqHVYlslHqBW5o6t/eWySCRi5jfHyVBuWpSu3rp3LY25ccqdQKPjvyCbnjrzhA//MJixLZ9d05A4n2lTnqa5N95XbUBphWd3d3di4caOWrDddJ4p0IcRR7gDANddcgz/84Q/+NuCq+/Bnb2tr0/qn9HeShMpjxozBiy++iN133z10bD6fxx133IHzzz/f/+y0007DwQcfrLyH7W5Z3H5FjUM2O4TqFmT58/JnksmdpUuX4q9//Ss++MEPKq+jugYhKbmj8r/jhBPbHqeyK7qcOwTZZ44id8juLl++HMVisWJHS5UN1NlDlS8YpdxRHafzo/g82+T32rzD0YpY5I7run9yXfeIWhWmnrBq1SoMDg4alTt8JxDe0GwmaPl8HpSbSCZ36FrceMkODXUMGvTllb1qlDvnnnsuHn74Yd/xkBMqyxJkHbljmoBFGUCd40DPI38nDzK6gcL0bqLCskqlEk455RTt6jmhv78/cUJl/r9u8q4bGOV2Iz8L/5s70IsXL8bSpUu199eB6nzatGlYtWoVPvvZzwKoDbljo9zp7u7G2WefXZHYUW4vRDZ0d3crk0fSc59wwgkAoM25ExWWxQcp7pSnvVtWXHJH51TbJlzU9c2mpibkcrmKfF9UnuFU7tjAVrnD7bKunm1WkHR5I0yEpjwOqMgUE2Qn20Tu8MlyXHInynG2gc1ETdXXeLlV7ycO0Z+Gciefz4fURIBaucMn8bJdSkru6NoYLx/9rXu+WpE7uverCssimJQ7SXLuyIoCGbqxXjdxUqkNdP2ZLx7x42XoyB26DvmRssrGNixLtmO25I7OxtH5sj1NGpbFyZ0xY8Zg69at2jBbk80wkXfycUTuyHmyVMjnRcJ7OceJ7j6NjY1aYpV8fducOza5rHK5HHbZZZeKJPa6BbMku2VFkTucQOTzGf4MJnJH5ReqbPyiRYsqztONkfyaQ63csfVfVModvsW86lj5HvIYqWvzZHcHBwcxduxYrS+uIrR07YDviCXXpy5xcjVhWfJ7zMidDBWgjOEm5c7WrVuVjTuqQZFxI+XOSy+9FPreFJZFHZg6Bg16fKXyk5/8JE466ST/erJDE0XutLa2YsqUKcjn86GwLPnetVTumBhY1eBlq9yRnQwOVViWapVXHlh1E0EbA24id+QJhonF588YR7mTz+dx4YUX4oYbbgg9k+65OHi5xo4d6xOhxx57rPE8E3T1YUPu5HI5XHPNNdh5550rjlFNXL7xjW/4z81x00034eabb8ZPfvITvPzyy1oHN2rCq1PuyCsTprYtg7/vtJQ7qnKZoHPqOzs7cffdd+OUU07xv+N9xETYxiFddZ+pYAorMN3LlHOHxgETMWLq11GwIXN1v6MQV7lD7TbublkymZwUUaGWKnKHVnVPP/10pew9Drmj6ytxbDu1/SjlTj4f5Nz56U9/invuucf/Lim5YwpHNJE7Kod5qMgdVVgWL4uOaNEpd0w5d6oNyzKtiuvGLlKNympTnU3L5YKdZFTkzmmnnYYvf/nL+PCHPxw6L42cO3HInfXr14fOl8cjeQy27U+c3CHiaMOGDdpjbcurO54rd7gPGLULqMpmqO7T0NCgJbqIJEgSliV/p7q3/LlqXOZhWaqd45KEZQHqxWp+juxjq3xuav9k4+Xz5DKo5k6q49LMuWOzmGHrv6jIHaqDtJU7vK+rdrNUkdRR9pGrFOVnrka5oyN3TPPGbQ3JltS2AVBSKRW5Qw1GlVDZtJpLoIapC8uSJ4d8YJSVOzTIyTvd0DFEQMUhdzihwRMqy450lHIn7kDLoTNUqnNV5I5uoKABbXBwELlcLiRbV91TZUCilDtAELoWBdOAQ/VvmuypSMU4CZVNA6OtcofO6erqwuuvvx4KCYwL3Xu3IXd01+DvnH9P/U/GtGnTMG3aNADBqqgKUWFZqpw7MuknkztJlDuquklC7iQNy+JlXrJkCW699daK6+fzyZU7pLTiKgRbMiOOcofu5bqu8vqykx+H3InjZJiIm7TJnaiEqaeeeirGjh0bUmNx6GT5upW4uOCEh+m+8iTdcRx873vf015TLqMMuW8B8ZU7/D6c3KGxVCYaCoWCP4ltbGwM2Sddm4tqV7YJleWy6MYY+bkItQrLMpE7tmFZJjI9Lrmja+dxwrLoXnGUOwQVuZPP5/G+972v4rw45A6/R1LlDtnavffeG0Cl3Yr6XwdO7tCkMwm5owvPVh3HlTPFYhEDAwOR5I5KgaK6j5xMXSZJbIhx08KizkdSQRWazskdWWXMPyO7xr8z3au1tRUbN27UzkfkvqPqS2PGjMEL/DpWSwAAu0JJREFUL7wAQN3n+PXoPF3ZovwlmzFbnlcAtQ/L0il3onzjqK3QSVFWLpeVPrzKBurIPdU9TeSOjmjT+VEZuRMNuxa2DYKUOzwsS47jt0morAIZ8NbWVjQ0NGhz7nR1daFQKPjhDnR9XhYa5ExyZHnA0BkWui/vkKqEymmQO9Uod2zIHd0EOpfLKdlwwJxQWVV/pgFNXg3TwWbAod+mnDv8HcdJqGwaGOOSO4CIt7cduFSoBbkTZ5UwDpLslqUid+KUjbeB4VLumBQ4vIz8O95HVedFPbfpHnHKGoUoNR4QvHdTfSUlXwC9o6S6nqm8KsgOlYmEzufzGD9+vHHXwyjnDqie3DF9Lo9JpnPk8gylcufzn/98ReLVXE6fc0f+Ts6pJz+LDrZhWbLzbUPu1Eq5k8/nQ2RWnLAslY0xkVi61WO5jLrfkyZNQrFY9BcDVGSNSv1LvoWNcieK3NGhoaEB999/Py6++GLjPeQJPifX4pA7O++8M+6880584QtfqLgXH6/of9tFDU7ukCpIF/pt6pcf+tCH/FBr0/Hy5FKXzFx376i2bgrLkttnFLlTjXIHqHz3juNY75almtybykWhpjK5oyJFdO2D8hrlcjmtckfXzmqZc4f730Ol3JFtne755DFS9VwU0kr3UZE78vV4W9X5AXys5e/8iCOOwLJlyyquLT+ryd+3WdRMy9cfidh2nzwCxx13HH75y1+GktKRMaFOpMq5IxMpKpDBcRwHfX19WnLnlFNOwd///ne0t7dXOPM04MydOxcA8IEPfKDiPuPHj/fvxxt5lBPBO5Drur5CSTYS9ZRQWfUe+PfcwKsGE/pOLmM1YVlJcu6onlNlVOXz+TOanGtSQejInTgTGB3hUg109aEiMPj/UQMCdy7TKm9UqAoffEmKXQvljo7QjLqG/HdS5Y7unfC/5YlMnPJG3SNNmBz0JMqdJH3E1N91qkFbZ1G1c5Bpkh23rCoHtxpyR3euXK+m3dxkqMYIGSq7Uk3OnbPOOgu77747HMcJkTtyP5YVA4SZM2eis7OzQi4/FGFZcn1FkTsq0lOX60UHIhVkcoe3V5VyR1YqRZHpfPJqUnboJjEzZszApk2bsNNOO1Vcw2Sf01TumLB48eJQm1HdQ/ZZ+bsyhbWq6mvZsmUVuT1UNirOggtXbY4bNw4AsGbNGuWxputccskloQml7niZ3JFJfR3k980hK3dMYVk2bSJN5Q6/X6lUQn9/v3G3LB4apVPuqGyAjtxRKXcodFF+hm9961u4++67MXXqVCvljsle8DIkDctSzfvSVO6o6oZsI+Wd0vkYsq2KyrlTKpX8Y0zkDq8/3fivIpT4e7n66qtx1llnVVybn2N6JtW96TlUx2+LyMgdDaZOnYqjjz469BkZOnLAdDl3ojouNwR9fX145ZVXKr4HBEmyYMEC/7pAZc6dtrY2uK6Lww8/vOI+O+64Y8X9+DVkkKGXDQqRWHKHraVyx9RJVZMfnUNBf6vej2mySfdRTQR0EyzZQNkYcNNALA8WtuSOKaEyHV8r5U610BnzNMKyTAkPkyDOblnFYtGfsJlWMG1JDj4ZU61MmQY13f1qrdwxnWdLaun+N2HatGn41Kc+ZXVsHOVOVL4afo6pvN/4xjdw++23V5xratu631FQkTu6tpKE3FGVuRoHS3duNeSOnDtPBdVz6MiPqGvINl1W1HIiSafcOfLII7FmzZqK8LioZ026W5bKlkQReAMDA6kod4BgfLJR7nBVk7zDi5zrQX7OanfLou90i0q6c8jXqqVyR3Vd1T3e+ta3atV5cZQ7MuS6M70HU1vg39H2zK+++mrksTZl1k10+fG6fFcyTGFZMqEot5+VK1cCEGNVlJqMX0/1PuOSO/wera2t2LRpkzLnDl3HJueOqi8Ryah797oFWf6cDQ0N/uYftsod3v/uuusuPPPMM6H76sobZ/zjdWG7FboNVPU5a9YsAJVhaTrFlopokdHV1eVHigDJlTvyPXXKHV0blXMt6Y7TkTvys2XkTgYrkFEjckeVc0c2SirwTqHK6WFaQZKVO1QWFXbYYQcAInzMZiCVnQ06jkgsmViKIndMBixuWFYU6RE3547qHnGVO/IAK69k2ky2bcidKMeSftPfJueajrHJuRPlKNlMXONCVx+q98C/Nw0ItEpI9WI7sEYhTs6dUqnkt1O5jm2IV/napoGVf6aC7n5xyR0dEaKaBBOxpXoW1TVkmO4RhWeffRYf/ehHrY41ycqTJFS26SPTpk3zHTZ+rOq9pknuEIGgOzctcqfewrJogmhD7ujUnXGVO4RCoaBV7nDlST5fuYKvuueCBQvwnve8B/PmzQvdkxAn5069hGUBduQOlXf+/Pm46qqrcPDBB6OnpwebN2/G/vvvX3E83VNH7pgm5bb9TUfuyPctFotDotwBosmdM844A+eee67yXFPOsqj76xbB6G/bcY+fR2p0eUFUdaypzKaFqWqVO6pr8udThWWdfvrpOP744/GjH/3IitypVVhWe3s71q1bZ7VbFo0f/DsTuRNHuWPTPrgd1T0vv47jONhnn338VBtyf5Rh079UZEMtlDv8mt/+9rdxww03+Fve2yp3dD40AFx11VW4/vrrrZQ7JoJFNy7LJLsphMyGBNIR6hm5EyAjd2JAVu4kTajMj5FXmvi1OGSHhjqNbktIIFDuPP3001YDaWdnZygMjc6RkzLXS1gWNwi6nDuy0aGwJHmAoe/ke6omWLqwLNnZlQcPG7m6idzRDYL020TuyNeqV+WOzjinodzROQNJERWWxckkaktE8vCymcoug79veeC3JXd0g2fcsKyodyKXN2lC5ah7pAmTcqeasCzT+2hsbFTaN1Pbln8nCctaunQp9t57b23ZbNqD3AZUDlctwrJM5E7U/WiTBJs+oiOTbdqf6th8Pm8kd/hxJnk6oampCV//+tf9iZNM5sRR7tiSO6o2XSwWsWnTJgDRuzXK11VBF5alUu7kcjmcc845vt/R0NAQUmeZlJJRYVk6P0J+Hgp/U5E1tLgg9wmZ3LFR7nBbYduv4thZGVEJ123uq7JRccKyVOROUuVO1HsE9MqdNHfLkp/94osvxs0334yuri4loSIjrbAseb7S0dFhTe6oJtgqe0wg5Y7se+vGuSi/KGlYluqa9arcUfn8bW1tOO2007R1T1DZSbleCRMmTMCkSZP870wJlfl9df1Jbge6d07g55veu+o4k9+bkTsZrECGjggVVc4dXefh4MfwlRh50iSfw3+TYbMhdx577DGrAf6iiy7CnXfe6f/PyZ2hDssysc0qo9bV1YXddtsN8+fPr/hO/l92qgn0/913341zzjkn9J5U5Jj8TmSZOq9nvmKruqfqf53x1k2e6TjTfaLInTiO4FCGZUUNYDbkznCFZZVKJd+ZVYVlJSE5+Hk2gxyHrq7iKndk0pGgIgijyB1bp1x1jzRhmrzPmTMHY8eOxcSJEwGkp9xRyfR1ZdGRO7Ztmpf5M5/5DD73uc9pz43r3PJypEXuyGXQEYtxlDu0cmsaO1U2HYin3NGtLHJyR+Ug03fyJNMEXXniJFTW9Ue5rpcuXYp3vetd2H777f1j+PbRaSt3ZOLOps1TGaLsbdycO7oJPIWxqPwEWlCS61SnlJYh+1a6cBQd4izYyDCNCaaQLaCyrtIIy6qW3NEtmHFUm1DZhtwxhXjy++jesckOxSF3ZOVOR0cHyuWyv629KueOzW5Z1Sp35PAck3LHRO7wdqbzLXXltRlT+TuPQ7rajtem+pTHQp0aRibhTXaDSD1O7lx++eWh66vmHCriRy6jqc3L8zPdcaZ78/vpzt+WsO0+eQLYKneiBlBuCDi5I5MmHLqwLJODOmfOHADA+vXrIw0lIIwvJWjmz7Rly5aQQVaRO6pJYjXkjmzUVOQOH1gaGhrwwAMPYJmXME8evFXkjm6QWbp0Ka666irt/XUTK9mI8mt/8pOfxDnnnKN9TtX/queUj1ENLjZhWTbKnSjDWA85d1SyVdUxw0HuyAo3Wo2X31/UCpXq2qZVE/6ZCrr7xVXu6Ag3VRtqa2ur2Jo3Caml+z8tmFZE99hjD6xatQo9PT0A7Fa1bWyhrNwxETe6yWYSckcuq+3nqmNMtrCa1TP5XNmhl4lUm/uRckfeyIBDN1GLU9+qY2VyhzuzSZQ7BLn/zJgxA0C6CZXps76+Pnz7298OhezIIaime8nXVYHGJ3kizH0Nk83gO5vKz8n/Tyssi+pZ14/l+8ZR7vC2WCwWqyJ3bO3E+eefD8dxjGOCnP9Jd1/V+5LHPduwrDFjxqBQKFSt3KH2rjpeJoptw7JMY4cpLEtn41TfyddLIyyLv2Mao1977bUK4oeuc+ihh+KSSy7BjBkztPbfRO5s2bJF6cPy95HL5Yw+HRB/K/RaKndUdtx0fjXKHfneUQuf8tzM1B5Ifcl9tcsuuyy0SCDbNVUZZB9YnhdHlVX3TCoRhaovxbWRoxEZuRMDl112GQ444ACccsopAPQ5d6IQRe6YnAzqIJQ3gHYPUKGxsRHvf//78atf/crKIVKVExDGmDtJZLx0YVmmQY4QNZGUWWnVZMFU5yZjIf/I5eZQsd82yh15xfDtb3879ttvP205Vf/rVplUAyM3dqaEylHkTpwJ91CQO3Ld6r43EST0noeK3JFJNn7fNHPuqIhLuQyma8h/J1XumNow/f3rX/+6Iu+NrhxRZQZqp9yxsV0mEpUgOzem60Upd0zEj015OWwn3vJ9ddCVVVYxJoV8ruy0yWHKAEL5i1Qgcke34w6gJ3fiKHdU15Bz7qhIWvouiXJnu+22w/e+9z384he/ABAoSkzlo79tyR0VkpA7puvxsKy+vj4AwKWXXoru7m4twcJhCsvSkTum1fson4Pq2RSWpSJ34ih3eNgZ/zwKSZQ7X/3qV1Eul41jQhS5Y5qoJQ3LKpVK6Orqqlq5o/L/CJy05H5DVEJlnc2Qy6UKy+JQJTGWEScsy9ROVDl3gIDcUZVz7Nix+PznP498Pl/hC6jsMYHCst544w2tn6mavMvHEHT9QOdfmcidanPu8Dkd1YmNf2B7/bSUO729vcpUIITNmzcDUIdlyddVESzy/7yMprmFjhwy+fsmv1dH/G1LSO51bYOYNGkS/vjHP+KHP/whgGhyR9eBeaewVe7Izvyb3/xm3HzzzTjmmGOMZf6f//kfAMB3vvOd0PmA2Cbz3//+t/ZcKg89pzyZpEGwubk5ckCTETcsS9WBTeSCzujIOXfy+bzvmKkGENU9kuTckQcr/rnuf13b0jnepkmnXA8kdzdNmqMGoHpQ7tiQO8Ot3OEDTZq7ZZmcZ9OgprtfXHInSk3Fv+MhHKp715tyx1SeJOSO6X1E5dxRjSk6kicKJieWkuLK9zJBV1aZ0EgKud5ozDGFZS1ZssR4TQrLMkHnVMepb1VdxFHuxCE/ebs9/fTT8fLLLwMwkzuyHYiacJnacBS5YxM+wkGLD8ViEe985zux//77+0pkm3dgUu7w54ibc0c36bAhd/h929ra0NLSEivnDrX9uBOXWoRl5XI5Y7JlOob/Tjrucb8zn89XRe7wMumUOzzcjMZsIN2t0Hm/lMsw3GFZAPD6669XfGda/JTftWkr9Chyp7+/vyIsS/UMNmFZ3I7a+Nq673XgtpGPo4Dop6SEkRFXuWNSFun8MJVfeM899/jvQQVS6JjIHZMPKt/TVrmjmq/19/cbj8vIHTNq4yGPclBjUuXcod/f/e53tcQJNzic3DE1SNmYO46D448/3npCpmKv77//frzxxhvac+RBRnZC586di+uvvx6HH364scwqI5l2WJbufNUEmH64QdZdR+XY2ih3VHHVquubVhNsyB0Vk22TUBkQDrRp1aMelDtpkDtU90O9WxbP+0Cf09+8DUU5UKprk3MKxE+orKurWoZlqRBn8mq6R5rQOYIcccgdmz6iC8tS9VnbyWZU2VVllccSmzrWhYwmaVcqyOXdZZddsMsuu1TseBJFLnBQziQTdBO1OEopVV2YyB35PTuOY70joewf8IWZqPLx+6m+0/VzDl7/qkm/qv+a2ldLS4tPhJdKJZ/Y4dcylcc2505UriZdu9bZV1UC2lwuh+bm5pCv993vfhdXXHFF3Sp3CLq+29LSEnkteTHQ9B5swrLouU3kTlSZeFl0Phl/T9xvsA3LiiIKGhsbjWNkHHInrk8pQw7LInLHFJbFofNRVe2GlDvr1q3Tjv2yn657JiDdsCxVPdv0LxXZwNNV6GA7XqcRlsXPnThxok+cm2BD7vA5h85O6pQ7urKq5mu641S+layaysidDLFAHY52kQIqG+Pb3/72UP4aDm4I4ip3kk6kk5wvr2rJHc9xHJxxxhloamoyDmiq72yVO6qV7yijpvpORe7YTKxtyB2VAW5vb68YnGxWB1QDjmzEdJM9+twmoTKgJnfiOIJZQmVzWJZOucPLIDsxtpM41aTQltzR3a+WYVlR5ag35U615I7cBkzXG8qEyqayJiFh5P6pulY1DpZcpp122gn/+Mc//NVHeeL3tre9LfKaUZM0ft1qlDuqsSOfz4fsEC2ayCoCuR6j6lAuF6kPTjrppMhz6Po2Ey4deD2pVobjttexY8eiu7vbWO6oPkXlkp9L99w2CZV1dXHkkUfi/PPPx9e+9rWKcjqOg9/85jd4//vf73+3ww47YNq0abGUO+QrxiV34owvMnRjQlQyZX4vVZ+R23tccqfardC5DyhDJnfS3gpdZ+8JccKy0lbuUFjWK6+8glKpFEnuyD4gKT9MOXdswrKI/DXV6aJFi3DYYYdVzLNsyR352WQS0qZ/qYgOm7AsW5LVZJvmzJmDcePG+WHGUaFOcWAbliXbRfl3UuWO7r2biCV+nSznThaWlQjckNkQDTLy+by/RWnSsKy4UK2eREGn3LFlufnx8gpiGsodU52bmGD5h2AKy1INcqawLFXyWFM5Vf/Lz6maeKrIHZuwLCBauRPVlocj546uvMORUJnyXsmg68ux+vLEbnBwMPTeqKwm8PctOyG25I7OYcuUO8OTc2cow7JMZY1SvKigKyt/njSVO7r7zZw5E7fffjuWLl1qfW1TvjoVMQPUTrkjjw+yXYu6nzzZa2howJo1a9DW1oaZM2di33331Z5D19f1W5sycBKAVug5+PPwRTEdPvCBD2iJOps2z8OyTIqRfD7vl6masKxisYivfvWr2nN33313ZTmjksZSGYHhUe4sWbIERx99NH71q1+FPo9D7qjGCXkyHZfc0SnObccRk3JHDssa6pw79RCW9cILL2Du3LmR/jGVleqGws1MYVkm5Y7cX6lvqu49ceJE/OY3v6n4XCaLdHMfuQzkkxWLRSsbRdeX79PX14c5c+ZgxowZeOGFF5Tn2fqgJqJpp512wksvvYQTTjhBeU1Te4yCbVhWUuVOFBGl8y355ya/N21ffyRi233yKmCagNuyvfJqDBAvoXLSMg8HuWNKBhZV3qRhWTpjwVcEuEGOuo5qAi4bMj6gtbW1KQcP3XOqPtORWLr219HRgQ9/+MM46qijIq8JpKfcSXOirTPm9ZhQ+bjjjsONN95YsQua3B7khMpA2DmLaoOqa/P2VA25w99dLbZCtyV36k25YypPHHLHRnmhc/ZVbVtne6qpD3mVLcm5tSJ3opQz/Ln3339/62dYu3YtnnrqKe33urErzjiqqovzzjvP35CBxiAiVlT91yZnEy8PL1dXVxcKhQI+8IEPaMkF/t7SCsuKIneirgWI8XO77baLLLMOtjl3iNyhv6PuFWcRz6at8HqLUu4MR86dQw89FL/85S8rPrcJ7dApnOlv276kIncIcn+Pei/yIp/q3knDsmzJHXm3rGrIHdXzxgnLmjlzZqifEblTLpfR29sb6ZssXboU119/PfbYYw8A6txTBHpv5XJZO/bzeQb9H/UMMnR+t8mH4HYhzqIlf+d0fltbGx577DHss88+2vNs+yEdZxpDdT5LrZQ7Jh9UvicXLMRR7ujKbiKW+HlZWFZG7iSCzDQD8ZU7JnLHJA8eSuUOj53nndOU3IvDNNgNlXJHpW7gTnXUBNOUUFnHUgNCuSM7M1GDvvyZDbkjO+ef+cxnMHv27IprEqnFy9Da2lr3yp20yJ0FCxZg5513TrW8juPgxBNPrJjkywOMvBU6lUH1ToZTuRM3f5dNQmWbFVnVNUzHRl23GthMHG3IENm5iZqIVqvcqaZNy2X9/ve/jwcffNDq3OFS7sRR0KjQ3t5unKDqxq5qlTsXXXQRjj76aP9z+YcQd6KR1D+Qx0X5evIxOqRN7phgQwrQBDkq545qUqe6l27yUW05q1Hu2Parasgd3XlJlDu692Br+1Xkjsl/MV1L1ecI3CfnY3ZaW6HL+RjlZ1DlbdJdr1rlzo9//GN8+9vf9v/nivO+vr5IcqdQKOCMM87wjyOFvqptEnEkX0u2eyo7GKfd2oZlyfbONOfQQWU/5d8270gH1dxCd4yNb2yLuLtl6fyApFuh654pSrkj5zvKyJ0MsaAyPnGVO3SNoVbuxHGq0gzLsjmeQyaS4jq+JiaY/0RNrE3KHXkw58fIOXd0joTJ8Mcld6IgD5zd3d0VExydg6/CSCF3HMfBr3/9a1x66aWpl5euryqTbit0+tum7DJk5xSIn1BZ51ilFZZlS9rEaWtxHNZqkFZYlkwAma6nU22Y2kea5I7cx/r6+jB//nyrc3X5wHiZVZP9uGWT/0/juU3QOdVxxuEo59pE7sQlQ5KSO/x5hlK5U43TbfPuTcod+ZlNZapGKWdzrI1yR/YVhzIsSy4DodqcO7rJmek6KnJH1z914GSBDbmTy6Wv3ImzFXqUcqdacke+honcsWk7RO6oFj50ycNloisusSyD141JISa/A3nMjkPg8gV7ud2b7Irts5jKovNZqlHutLa2ar9T+aCqeRZgn1A5rnJHVd/8vEy5k+XcSQQTuWM7yabEY0OVUDkJAx6VUFl1fQ6dg6z7jEMmd1Qr22nslhU1ETWRO/I9+DOlGZYlhz+pymw7EPHjrrzySmzZsiV0jG1IDS/XUJA7NsZedw35mLRVH7r7yWFZLS0t/ooIdzqSkBy5XKVyx7QayFGtcmdbz7lD36WVc4fu6zhOZB433YSpmvrg9hCIp7SxcWj32muvxGWLE5aVJnR2tVrljvw9jUHy+BB3olENuaObfMtlMZXBdresoVbuyOEA3O7y9i4TrPK9oiYdScs51Dl3ktZ7EuWOzk+i72zqh5+XhnKHvz/dO6/1VuhDFZZVKBQwMDAQa2xtaGhAQ0MDtmzZgr6+vlhjNAD09PQAAHbbbTfl96eccgoOPfRQ7XXTVO5E9VnZD5LH7DjKHRXZwO0Lhavx+8V5lmrCspIQHDb+D39mnc+iU+7IZeV56FTXIUQpd+izTLmTkTuJoJpExR306fihCsuyHUg5qlXumFhnnbFauHAhHnjgAStyx1TnOkPL2XyZ7DCFZdmsng9VWJaqLuK2OwCYMWOGsTz1oNyJmhSo6l53TNRkKyl0g6oclvWjH/0otMuPDTElgz+DaSBMQu4MZ0LlelHu2LQRG+VOXHKHrsudcVP7SLNNk22vhtzRrdgB0OZ7iXN9cpBlZ7/W7SDt3bLk76kfyxPNuGRINeSOiUTk5TeVIYoYpnLFmTjpYNPmVcod3biaz+e1bV7Xz+Ks6pveSZKcO9XsllVtWFY+n8fg4OCQhmXRefTcfBe1uMod/k5kQpWgU+5EJVQ22SSZQLEld3TPY6PcsSV35PfS2trqkztxfBMAmDdvHu6//34tufOjH/0IAHD77bcr768jd+LYeV2fjVLuxLW58j10Y5NpPmd7fVNf1/WjWvm78kK56l6yLxGl3Onr66u4tuo4VX2r2kuWUDkjdxJB1ZjisKRLlizxmdyRFJZlImtU5TMZJp0zdfvtt2PlypW44IILAIgM+/l8vmI1hf+OQ+7IBinK8eGx+/Jx8m+Z3NENHhxJyB2VkbSdPNquAMt/qzCSwrL4MbUmd+SJPQ008+bNCx2jKns1yh3eB03X0Q2ycZU7Ue9E9V2S46LukSZsJslJyJ04k0FTf68mTITw61//OrRdNdkFkzOqg87O8udVKTniXr9UKimJr1qTO7VU7rznPe9BoVDAJZdcUjE+yHYvjt2OA37ftMKydPcB0lXu2JA7POeOru0UCoXY5I5N+W3aShLlzlAmVJbPS0Lu6NqX7XhM35MvNmbMGP+7apQ7NuROLZQ7sppMPt4mLMs0H4jb1+T30tbWhldffRW9vb2R/rEKixcvjjxGN/bLJECSTTt0/d1E7vDF17SUO7btweZZhlq5Y4KKYKlWuUPkjs4Hku+tqm9+XqbcycidRFAZnzhOy2c/+1n/73reCl1OqGxy/mXDCJiZa52xam9vDxEjJ554Ir70pS8pB/RqwrLkv3XXOe6449DS0uIbH0A/eMgTGp1yhxykqLLLBjPtsCzdMaq/VRgp5E6tJ4S6+5lW/DgBk7ZyJ+od6+43knbLGs6wLBtyx8ZG6c6JQ+YmGReOPPLI0P9kF6pR7uhsIe2ikhRUFtnhHgnKnaj+eNJJJwEALr30UuRy6t2q4oT12ZaLg5N6un5r04ajjon7PCbYvAMelqXrM7y9696RbKPjLBDYlJO3ryjlTj3k3KF7xgnLUo0TScKyyN5yXzCpcofGT9W9+bPlcunn3JH/l79LKyzLtq/JZaHQ8b6+Pv89yTtcVQvd2C+TAEkW5Gz7rPzcKkIiCjbkjtxGkxBVNuROlN9rg3/+859Ys2aN8RiVD6r7rVLuqBYfaX61adMmAPp3xj9XjTn0WZZzJyN3EkHFFCZVBXByh0uJZYyUsCw+4TEdb5tzp6GhAbvuuqvyXnGUOzwci37TQOI4IteFqm66urr8rWvlspmMuMp54fVB5I5p5UU3QTRN9kwYDcod3UpdPSl3ZKJTRQKoyBnVtVTn0W/dcyUld+KGZdnslmVL7sRxQG2OT4q0yJ0kk1mblb8oZyoJyLbrnFETdLapUCjgoYce0m5nHads/D5DTe7UUrnDj+P1z+87FGFZqnLGnWBRO9cl4pTbVjVOt029cl8qajEmn48flpUWuaNLMsshK3eGM+cOKc6TKHd0k2lb25+mcidJWNZwkDu657ENy9KVR3UtOpf6MA+VGUpyR2UHa6HckcfVJAsy/J3r7EtcAlJ3/ahj0lDuLFiwIPIYPh4kUe6o3iW1tVdeeSV0vomwMil3MnInI3cSwUTuxG1MccOykhrYJBPbJOSOylkxHa+DyYmOo9xRrQrkcjm4rhtyqgcHB2NLJeUy6hh6m8ma6vmSrOSbwA2i6RhT2ThqQe7wZ+UOha79brfddnjLW96CPffcU1tu+Rppqz50cl855458jOl96sDPkdudLbmju5+t7aqH3bJqpdyx6U8qW6e7ThxyRzXplM+tBblDdsHmuWToiEXHcUJhiEkhlynN5zZBZ9NtJuzysTb9kS8GqO5vO15WQ+6kEZZlS+5U217l8sow5dxRTb5qmXPH9KxxlDtpkDvVhmXRbkhp5Nyx9UllcieNnDvc95NR663Q5WNM5E4S5U6SsYefy5U7/Pw0x1wTIRHX9uiuHUXuyP5HXJsrl89mcUZVDhOGWrljA5UPqvvNFwJNbZbaGi162yh3TOROFpaVkTuJoFrVSkO5U8uwrCTny7tl0Q5f1ZI7svRSBRtyJ45yhz4jg0TkDpcI2r47G9KGf66SJ8vkheo83XPy+8QhFW3InXpR7hSLRWzZsiWSyGtqasLPfvYz5TXk/2s12Omchlood3jbS0O5k8TxNynJ4lwzCalle3xS2EySkyh34jiKpvdZC3KnGuWOrsxpTQSGOyyrGuVOnMmrPNHUkVo6VEPu6CbfhL6+PrS0tBhzJ9WbcofnytON1/wd68qjG+Nt3r9NX7BR7tDncs4d236aJrlDaGlpsT5HVQ9JwrJU+Q/jkjtJlDvd3d1oamqKzB1mGn/lZ1TNIQjVboUeNyyLjiF/tK2tDYVCwc/LlnRuE3U/1TXluUE1yp2oMYl/7jiOPw7G9anpWFtyJ049ys9iOkZHhKRNcKieOUq5oyLZOXjaC9V1TPdWjZtZQmVg233yKsAbjOysVKPcMTk+1YZlJTGS8gqCzKqqoEo8LA/ANk6J6XnlujZJU3XkDhkHPkm2rZsollp+BtXxNisvuudUTYptJxtxVB3DTe4Adiot3TUI/P3KK+RpIGp1QZdzJwm5w9+3bsIRh9xJUhe1CMuqF+VOWmFZNu127dq1eP311/3/bYgb+bNqxwW6FrcNaeTcSauP6UiOoSJ3hkq5oyN3hlK5oyNbTz31VDzxxBPGyS2VbyiVO6ZrmJQ79Hc1yp0445DpWBvljrz5xnDsliU/w1DuliWTOxxJyR1VnyPIm3eceeaZeOCBB6yThschBVRlTjssy6atcnva29uLyZMna0mSNKCzo7VIqBxFFPDjVX6VCdxHl9u5bjyN8yy6ccj0HHLZ0h4jZ86ciZ6eHnR3d2uJLHnc5qSdDbmjewdRyp0s506AjNxJAJUTlrQjqYx8vSh3+KoXbauoKx/JdU0JlWlybTN5MA38NhMnHavLJ/hEssR1jOXjoyYCqkHG9Hzy8Wnl3OEGMerZbK45UsgduQ2kPdiZ5L7FYjEyLCsO2cLfd1LljsmxtEEtwrJsn9v2+KRIi9zh70JHKLa3t6Ojo6PiujrCRFW+NMgUTnQD6eyWVWvlTtokkgxdX4ozVsSZvMoTTXlhJOoaSckd/t51tr9QKGDChAnG62zevBmAntyJ+zwm2Pgyppw79LcNuVNNf7Mpp81W6Fu3bgVQH2FZhDRy7tj6zHRvG3InzuKIzi7LeSObm5uxww47GK/L7x3XRzGRO1HKHdW9kip36NxPfvKT+O1vf1tRhjQXVEyEhGp+Fcde6Pqszk/jtj7KN9c9h6o9R80L4jxLNWFZaRMcy5Ytw+rVq9He3h7ps+gSKsuIq9zR2Q/6LAvLysKyEiFNcofDtHJarTOb1Eg2NDRg8+bNkcodkukuW7asosxyHcVR7iQld1T1xY23TPDormNTNp0B1pFA3KmwIXdME5o4BnwkK3fitF9+jf7+/or6Gkpy5+ijj8bee++tLKPq3Q21cieJwxZF7thOJuK0NdM90oSNnaXvbMgd1cRdB11bV5F/aZI7chnTSKic1vtRrQDy69ea3Iki7G2uYWNzdUq+uDveVKPcqYYEoF1OKJRDV744YYo62LwD025Z9Devb115dGNxHHWGqS5tlAlpkTvV9Mkk5I7OT6K/bctF56uU5HIdRPUTbj90dpmXJ047jeOLmcidasOy5L5mY6v4u+rr6wtNttMYY3RllK/JFR70Py+fDXSLXlHKFmoPcfq4SrmjIo1U5bOBKRWGfL2hUu5w6J5VZe9NY7asCs3IneqRkTsJYCJ30nBaVNeo1mlOer4tuTN27Fg89NBDmD17dsU9ed3YKndMg5fNhF/X8Tmhw5U8unuZyhZlxE0TMZvBedGiRXj99df9BHc6wkr+TAebSWYc5U4a29rK0DkmSZQ7hUIB/f39Fc5C2oMdfy9yHqUbb7xReY6O4LOdxKkm43HJnaT1oNu5iGA78U7y3LbHJ0UtlDu2bU5uD2PGjAmtjqmOScPxpjLGId/5uWmXR3X94QrLGg7lDj++HsKybHDAAQfgve99Lz784Q9r7wOkM+Gw8WWilDtyex/usCzTs5AqWs65M5TkjvwMaYRl0W9b28/Jna6uLrzyyis12Qo9zvVUx9q8FxOBZKPktfEfk4ZlyagFSWAiXJL6t/K1o/qs6nt+/zgknYrcUS1Cx911rFwuh66hwlArdziSKHeqsZ0mMo1/n4VlIQvLSgKT81Wtk82vyVHtAF0NuUNlisq5M2/ePGW8MK+jfF6/7ShHrZU7MtHD7xm3bKrnVB3H24jJ0NFn++67L+64444KB1DlhNu0u5Gk3JGNc5xEnDqCiP5OW/UhK7dsy6gafOPKyvn5Q03u6N5/nEktoV6UOza2wIbckft63FVAADjzzDPxyCOPWJE71U7cuFNbTULlJCutJshtTedEpg1dXcS1t/y36V65nMh1IV+7HhIq26BYLOJrX/saxo0bp70P/bbtDzrYvAO+U6GOvBoqcscmLMt0PSJ3kubcqYVyh4eT6mCyUXyssm1rMrlD56vuqYNsl+OMUVFI0jaijo9S7qjOrSYsy+Rv1yIsSzV5V03Wkyh3ZH9Ip7DmflSUby7D5NPr5gVx2pRNnlMbIqRWkOs4qXJHRhzlDn8+qusxY8agq6sL06dPT/BUowOZcicBuCNgoyKxhakzVuvEJy0fdyTI0Ng6/6qOH1e5YyI/bJQ78goJKXX44B53FVh+F7JxpRA13XFctWFaedEZNtVkz5ZQsF0B1pWNo95z7qjOqYVyh5M7W7dutS6j6X2aztOdb9sWqp0YR9k82/6U5Lltj0+KOModm63QZeLEBPn9NTQ0YPLkydrrqn4nAZUviXJH3sEmDbJJLpvp+rUmd4ZSuTNz5kwAwJYtW/zvaq3c4W3TdsKZBLLdSsNPMl2DL0rpFkVUq8AyTAs0UbDpC0mUO8NJ7lxwwQUYP348li1bFnmOqc54vUaVi3I9qsgd3T114H5h2uSOvNhie91qyJ3RqNzhnyXxMXV+uY7ckW1THFLEpCSR279KSR6FOMqdqOerBWyemX5H2aF3v/vd/gYTujbHP9f594DIZ7hmzZoqnmzkIyN3EmDMmDH+37qVyySggc5EaAyXciefz/uDbFyngnfIuMqdWoVlUVnSDMuiujrxxBOVx/Ey0X1Ng7ONsY5jwG3InTgOfq3IHdUAWw25M1RhWXGdKdUEcjQod5KEZdWLcsemP9kod/i7sJ3M2owhOttTTZuWCag45M7OO++Ma6+9FgcccECoHLUid2TSvtbkzlDm3Nluu+0qvqt1QmXeNqtR7tjch35Xa4Nt2pjNbln8HcdV7tj4QDZt1EZdkVbOnWrqnK7R09ODSy65JNF9kyp3iNzi9pbInTfeeCN0rO2YY0syxulPcdqGakIadZyqXKa5QtKcO7rr1YLcka8p75ZVjXInSuWp6tO8PcZ5j5zcke9fjQCgmrCselPuRLWjq6++2v87Sm2lItNU5diWkZE7CTB27Fj/77SVO7a7NiS5Nr+OLcih4GFZtmWQHWTqkHGMpom4qSYsK5fLYf78+RgzZgyefvppANWTO+3t7XjhhRf89qFzDKMcC927UrWBOO3Opu7rQbmjGgiSrJjqwrLSnrgkDcuiZHlxCDW5DfH72a4cynX5zne+E//3f/8XWWaC7W5ZcQibOESQzfFJEUe5Y5tQube31w+5McGmjetsSjVkiqzcidryVy7PmWeeGboWL1e12BZ2y6L6J+UOx1CEZanaUNrkKe9XvK0lgU29xsm509zcjI0bNxrvlaTd2fTNOModCsvad9998fa3vz2U37DactTiGrrxiX9nMx7T83PlDoX/USLvXM4un0lc5U4cJCH++HkqJFHujKSwLJVyJ6l/K187aoxU9WneJmx9avqtsxHyYlgS5Y4NARj1fLWAbmFR9exx5rC6vikLBeTrkY2UEzRvi8jInQTg233KE51qnRbd+dUO0EnPV4Vl2T6jitWNq9xJSu7YKHc+85nPAAB+/vOfa69jKpuK5Jk4cWLkceRY6N6FbnBRfR7HoTj88MMjY1DjrN4mGayiIJM7SZQ78jm1Vu7oVopM4OROEuUOqc6A+AmVZVtw3XXXRZaXY9GiRTj55JOx44474uabb6543pGs3LGZJMdV7vzlL3/RbhGtOyfqGJ1tSQK5z8VR7kSVr1rIhJPu+dOG7l0kmdzb9MdcLocpU6ZUfDdSEipHgVSq8gQqCWzaGA8X1D0f1ekXvvCFUCic6l66yYtNOU3H2oxrcljWhAkT8N3vfjfy/oQ0+kqSa5gm19xuRV1TRe58+ctfRm9vLwYGBvCVr3wF+XzeitzRTeTTQNzJq+pvGUnIHbpeY2MjOjs7Q4vROtj427UgwuRrcr+G3zuJcsdELqrKwBc5bJ+VX8OW3IlTj/WeUFlnF+k3jdtxEyrr3oGpvgFg5syZuOmmm3D44Ycnep7RhIzcSQDHcdDY2OjvIgWkYwBbW1u1k4Bqneak5eOx6zYsMoeK3DFJoDmqDctSGRIaOBzHUU6okyp3ooyrygDysBxd2dMOy/rSl74UecxwK3fa29vR3t5eFbkjD6pyfaU9ITTdz3SOityJ65zy820H82pt1ZgxY/DjH/8Y3/jGNwDYKcxUiDOZ1PWttGFT9jlz5mDatGmYMWOG8TrXXHMN9t9/fyvVDmC3QCD39zj933RfvvJYj+ROVLL6tKEjupIod2zIHcdxlIqpuGFZccGd5FqGZdH1yW7VWrnDyR2VopHbzzlz5hjLrLpnnHHI9G7onZuOkcOy4mK4yB3Tooc8oTaBnl/OufPFL34RH/rQh/zr9Pf3R15L9sFqoUaJo0yX/zYdx2ETRlUqlfDUU09ZJb+28bdrQe7UQrmja3c6f5rXpaxijYKNcse02BgFmwV1XVuoB+WOKqGyzfPr7MLYsWPR3NyMlpYW5fM5joMTTjgh6eOMKtTurY9y9PT0AEg3LOvCCy/E73//e+V31Q7QSZ3uNBIq00CatnLHVOcm5U5jY2PIUYpbN7YTLJNjyJ1L3fXTJndsYVsftSB3LrzwQtx11101I3dqqdyJE5bFyb04yh3ViudQkzuqsth8LkMelG2Ptbl2Utj0p1mzZuHZZ5/F+PHjjdc6++yzMWvWrFTvXQty5y1veQtOO+20SNLZBmk7lNSnSCWV5nOboOtLce5rWxemsUAOR9MhqX/A7WGtyR0+earm+jbjU3NzM6677jq89a1v1Y6bcSbhcnuIc66pnDbj2kgld+S6U7Uvm7agUu7I14nT16gs1bbDqLLI+NjHPoY//OEPFeU0taUkyh0+/o4ZM8bK3zbZtSTqmaT3k/2zJISILSGr6tvUJpIsYOv8sGp2y7JR7kTNF4ZTuVPNVuiq497ylrfgueeeQ1tb25CQVyMZmXInIXp6evDCCy9UDPZJOlIuJ+KFe3p6fNJIdQxQvXKnGnInbkJlmdwhozmUW6Hz5y2VSigUCvjqV7+qnFjaGgldSETUygB/B0nIHd0KpPxZtbCtj1qQO52dnejs7EyF3FGtig4FuROnjFQm1eem83j7iUvupDUxtnWaos6PeyxQ+7Cs4XAYqlHuVFMfp512GgDhOFWj2kmrPBxyWNZoVe7Qsaeeeip+/etf+9+NloTK/F5pkTtR13jnO98JAHjssccqjueTsTj3ijtBiTrWRrmjSigcB2n0lST92mSjeJmiyqXaLUu+jm0/4WPlm9/8ZnR3d0c+hy2i3vcnP/lJ/2/bvhbXR7Qphwo2SqBaEGFy+adPn47XXnvN/78a5Y5sf6MWSzmxY3s/Xj75mVQEh6ocJqSRULmWvozO91SN23HskO4d5PN5XwmdkTtmZOROQtCOWdWwsoTly5dj9erVxmOqNbBJz1clVI5L7sjETpyVhKRhWarvvvzlL6Orqws77bRT6Nhqw7J0dVutcsdm0lwryezg4GBkfbS3twOAVT6RJGXgvw844ACcd955xlAY+VxdWFbag4HpflHnyH/bKlhyudGl3IlL7tRqQK93cqeaMJEo5HK5uiN3ZMd4qMgd3btIe3JP39MxP/jBD0LfDSW5Q+e7rltzcqfWYVlRx9uWIQ1yp1rlDpE7cRKdc9RLWJaK0OCTPh3SVO7wsnz0ox+NfIY4UC2+6RBn7DPdKy0yxmYxtRbkjnzNz3/+88p7JyEVo8KyVGqTuPaJ38tGvcI/t4FNKgxd37T1B6uBrq7lZ0+L3JGPsb3etoiM3EkIWWFTTUObOHFiKBGvCtU6zUnPryahsrw6k3ZYVtzdsvbff3/jvdImd0yOoePo471170rnpKruXQ1sjfDcuXNx9913Y8mSJandmyAPGhMmTPBzvNieq9otot7DsmxJDj4pGy5yx5bUjDqfn2NzrM3xSZE2OZHk3qZ6q2ayGQVb2xx1jbTKw68n9+Va2D0O2TklxBkrbCd7nKiVUeuwLB25U4v2zydP1by3uH1UZY9syyDb1Djt26acNsqd9vZ2vPTSS0pywwZp2LQkZKqpr8ZR7pjIHd0Ch22ZdPjd736He+65x3iM7tpDSe5EhWXZwlQvtQzL0vm48r2rIaqi/HPehsg/tJ3jcLsQpWJJUo82qTB0zzccyp1JkyZh3rx5/gJ6U1MTPvOZz+DYY4/1k9bbql4zcqc6ZOROFDZtAu66Czj0UPF/uQzceit6POVOzx13ABs3YtyKFWgBsNOKFcC11wJvfjPQ2wvccw/wyCPAmDHA1q3AunXAsmVAsQhs2QLsuKO47qpVwIsvApMnA7/4hbjPlCnAPvsAN92EvV96CbcCmP7oo4DrAtRBbr0VOPBA4C9/AZ57TtzjzW8GHnsMmDVLlOH++9Fxxx2YDmDu1q3A1VeLc/fcE+jqAl57DejrA154AZgxA3j8cWDePOAf/0BDQwMaAPT98Y94a7GIqwHsOn8+cMMNoownnyyuddttwAEHAE1Nor7mzUPu8cfRB2DG2rWYBGDOwAAG8nlsLhSABx4QddvUBPz970F9b789sPPOmL16NVoBdD/0ELDXXsBNN4myHn44+v7yFzgAdnj+eeQAzPrXv4DvfAc48URx7+XLMfHpp9ELYOd164Dnnxd1O26cqPNSSdThwADQ1IQdBgfxNIC2Rx8V9wKANWuAn/0MGD8e2H9/cf+WFuD447HDs88iB2CfF14Arr4a45YvRxOA6c89B2zYII677Tb03XEHxgKY198PvPgi8qtXYyqAGf392FwuY6PrBu+CYdH69XgaQMs//wlMnSra0L77YsdnnkERwLx//tM/r2f1ajQAmPHPfwLXXQeccAKQzwO/+x2wZAnQ3w/cfTfwxhuiDa9bBzz1FLDffqI+n3tOfNfZCaxYAcyYgX0A/B3A5MceE+3y//0/oKEB2Hln4G9/Azo6gLe8BSiXsXTp0qAN0srib38LLF8u2sOsWcD//Z9oXytXAv/4R/CgS5YAzc3i/rvuCrz0kjhv5kzM37gRfwVQGhgAfv5zoK0N4Pe6+27xPLfeChxyCPCrXwGvvw6ccAJ6/vMfdACYv3EjngEw9ZVXxLVXr8akwUFst369qL+99xbPdfvtQZnGjgUOOwzg+Q02bhTtatky4Cc/EeecfDLgDSrTHn8cBQBLNm/GswBmPvGEsAHHHCOeGwDuvx+YOFHU/333YcbWraINXn01CrvuCgCYCKDlBz8Adt8d2GknYQc6OkS9//WvwJYtWPTss/g+gF0feQQT+/tRADDl+eeBchl9Dz2EZkjO5e9/Dzz7LHDkkaL+H3gAjutiDoDeclnUwx57iPoHgGeeEbZk3Djx2b/+JX7ffDPQ0yPq/PbbgcMOw5RHHgEAzH3mGdGXbr8d2Gcf9D36KNoBLB0YEPd8/nlhV559FvjnP/2itb7+OnYCsBFA2w9/KN7H0qXAyy8DTz4JzJ0r3m97OxatXo3bAOwH4A4AO9A9b71VnHfrrcKeHHecqLO//AXYbjth/wDg3nuBhx4SbWXGDODBB4H77hPf7buvOOfXv8bOGzbgJQATb7kF+O9/xTVeeUUc86c/AQcfLGzdm94U1LHrCvvA5OTI50Ufeeopcb/nnhPvf8IEUY777hPX3H57cfzy5Zi7eTNeBND0/e+L9jdrFrDbbsIO9fYChx2GGU88gSKACQ88ABx+OOY8/jjyAHZ87jnRfydPFn1h5UqEsGiReI5p04A5c4BHHwUKBTGObN0KtLZi6tq1gRP53/8Cv/ylsD977inevxceEUJLi+gLt90GHHQQJj/xBJoBzP3vf0W/bm8XbX/GDNG3/vEPYXfWrhWfA6J9tbUBq1cL+7t5s/j/tdcw3RtXd/TsXO+//gUceCBmP/UUcgAWPfmkaMONjaIcjY3Ar38t7NZxxwnb89RT4jkPPFDUwcSJop4efhj4859F+995Z/H3f/4j2vR//wsAaHj6aeA3vxHvGMCBa9fi3wD2ovuqUCgIO/zgg5jR2Ykd160Tz7Z8uaiDSZNEPXR2AuUypmzcCGdgQJRn3jxR9uXLgUWLUCgU0AageO+9wmbffbf4/dvfir74u98BRx6J+StXIg9g99dfF2McTYTvvVf0oyefFO1uxgzxXrznm7F5MzYMDAD//jfQ3o5dHQcrAex4zz3AzJnAwoWiz5IN6O8Xvswxxwhb6DjAKaeIZybcdptoi8ceK/rZTjsBTz2FcQCmr12Lp1wXczZuDOpvt92EH7B2raiftWvFfbdsAe64Q7zT/fYD1q8HbroJsx58EHkAvX/7mxibf/MbYbN/9jNxzEkniXYJAGvXovX229ELYLdNm/x7ThscxHT6f++9xf3vv1+0v4YG4JZbANfFDitXohNA509/CowZg3lPPYUSgPH/+hdw9NHi3kccId7DIYeI9vbEE8DRR6PzwQfRAWDOmjWi3T3xhGh3L70kbOnmzWjy+ul01xXvv61NjDUtLWKs2LwZf7r0Uty8di16mpr8foYtW4AbbxRj0AknCJ/mppvE8598cvD8ALoffxxjAMwfHBT3fuEFoLtb2Mt77hE2t6lJjHOkanYc0WafegrYYQfssWULXgEw5amnxPdbtoj3v2mTGMPf+lYx1hx8sO8HNP/tb2gHsPPq1cDVV2Psc89hAoAxAPJPPAGUy5hWLmNMf7+6L40ZA0yYgHlr1uAvUJA75TJmP/00AOCggQH8BMAOzz4rynTHHaIPERwHOPpoFJ94AhMAzNy0Sdjk9evFd6US8Mc/imN32QWHHHIIDtl1V/HZ/vuLel67VvSBri7gqKOA//1fYP584cO7Lrr/8hcUAMx++GHxPLmcGCemTBH9cNYs3x8oPfIIpgFoAtDywx+KtjNvnijzmjUAgHEA8Ic/iM//+EdRz64L7L035v/3v/gFgCVPPx3UXWMjcMop6HvwQTQC2OHll8Xz/fOf4r0++KCw+4CwHRs2iGsODGDm4CCaARQee0zYe0DYofvuQ5frohNA369+JezG4YcH779UEu3tt78Vz/qHPwi/L58X7WHffUUbe/55YTPGjgXuvx9tf/oTpgOYPjAQfvd77CGO8XyGKRs2YAyAwne/K8auI44Q7/c3vxFzo+5u8fchh4g+ePjhGPvgg2gAsP3mzcD112P2ffehA8AO69YJ32LDBuDee5FbuxYzAUwZHASuvhozN25EeXAQ09etwxOA8CFmzxZzqR13BH76U2H/GKasWIE8gPG3347GV15BEcDUxx4Dtm5F94MPogXADq+9hjsB7NLfj9cA7NbfL55v6lTxbv7yl3C7XrhQ+ID//S/mb9iAxwE0bt4sxrVDDxV1vnWr8LcOOQRzn3kGDoA9nnkG+Pa3RZ3Pno3G++5DC4BZ1EZyOWGznn5ajAXUxwYHgQULxHU3bw7mpC++KHy2vfcGXn1VtPfBQTEnOvhg4KabsNsTT6AAYJdHHgGuvhrtTU146O9/F/bz738HjjsOH/7wh4HbbsMLd9+NPgDz+/uFf/Lii2IeCIgy77CDsDe33Ya5a9ficQC45hrR5qdPF7b5b38DFi8GbroJM//5TxQBjP3d78R48+Y3i/Z3yCHChu6zTzC+33uveJZjjhG+7bYA13VT/9ltt93cUYMrr3RdwHUfecR1BwZc949/dF3Ave6MM9zZotn5P+fy/z/6Ude9+WbXdZzQMS7gugcdFPxNOP981x03znUvuyx87Kc+5f99OX32xS+67pFHuu5tt4n/r7gifM6ll7puqeS6F10krj1xousC7g8A94GmpuC4hQtd98QTxX3f+lbXHTPGdT/4QdctFsU1cjn3/Le9zT2RXXv13Xe77ne+E1zjJz9x3UmTxN/f+Y7rrl7turmc615wgesC7t8A96XWVve6fN59uLHR/X1np/ud6dMr64R+2ttdd9ddXRdwb6LPPv3p8PeA+x7v/7P4uZ/7XOhan5CvfdhhrrvnnqLu3vQm1917b/+7P9ExK1a47muvue7llwfnURsAXPeYY1wXcC+Vrn024JYdx3W/9S3X3brVdQsF1wXczyqe8b6mJveOxkb3lmJRWQfrczn3NtWze/eRjw+1u69+1X/f7vTprsvf99veJt454LoHHCDaxnHHue7MmeJ/dp0P0t+5nPo9LV0avHPAdd/7XnG9V18N2nwu57pf+5rrNjeLtpXPh68xa5br7rWX63Z0iPPo8x12cF3A7QTcl3lb+cY3wufvtZf4/fGPB59dconfdtbn8+6n6POWFtedO9f9VXu7++/OTvHZokWue+ihlc+2yy6uWy4HffOznxWfv/WtwTG/+Y347ve/d13A/a73+c38Ottv77qvvOK699wT9PsFC1wXcO9ub3fv9tpyubXVnQq4X6PzikW/nal+zmR/n09/L17suoD7GcDdb8kSUf5zzw3OmzpV2ATv/18D7h8bGsT/u+7qutde67pjxwbHF4uiDzuOX6cuELzDq65yXcB9H32+//7i94c+5LoQtiZU7tNPd91p0yqe5U+A+yP+2Re/6Lpnny3uf955oWPf5f2+gLcfKit9tmCB6/7976LcY8e6bne3615zjev29orv993XdQcHw2Xp6hLvCnBXlkrKPut2dIjfp5wift95p+tu2OC6n/+86/7v/6rf1RVXiHZ36aXBZw8/LPoDtQeC9/1X+PmlkqgP+n/JEtcF3PdL9wnZhK98Rdtu/Lq68UZhB3mfP+00d0VHh7uou9t1f/e7oMy5nOt+7GPma37pS6H3cSV9vt9+oh1SHW/c6LqdnaLPzZ5dWS5AfF8ouO4557judtu5LuC+F3AHHce9ho497DDXBdyPyuW46SbXXbUq+P/DH/btsF+fgOsecYSoc7L/vb0V/W1dQ4P7Ns3znqn5PPRz1lmuC7jrjzxS/D9hguv29bnuO97huv/zP+KzpUtd9+CD3Ye6u93fdna67k47iXLNnSu+HxhwP/axjwX946MfFb+pX5CdPfts1wXcb9JxJ50k7MFvfiPq9bLLRD9QlPMvZAvZj//+CgVRZiAoM2/b/P13dYm2/dJLwefnny/sxemnuy7g/i2fd1e2tbk/bmpyH/Nsn/8c9J6KRdFn1q0Lj8EbNoix1fv/w/T5jBni98UXB8d++9uiHstl4dsA7qcAdxVrC79qbXUfojIsW+a6b3lLcL3TTvOP25rPBzbO+/HbHdkQ6ivf/GZw3DnnuC7gfo/+nzkzXH8LF7ruokXuxiVLXADuBvr8iCPU7WnrVt/mug8/7Lq33BJ8t//+wRgDuO5nPhPYlU2bXBdw7+bXGjPGdadMcd22NvH/kiXCH5o61XU/8AExLrqu8AUbG/1x9od0/mOPVdq8Cy8Uv3/yE3HuM8/4z7+V+RBXAu5/2Xl3NTa697S2RvYnB3Af+uUvRfkGBkK+OfnF74q4hvve97ou4L4IuE+0tAjfd8wY8V1PT3Dc1KnB89M7cV3Xfc97Kt6vC7juP/4hfH3AvUK+Z6nkul//evg6Xh95GHDvpOMWLxbfnXii606d6gJsLOA+HPtRPq9Xrq9A2Ex/PJgzJ3yd444TNpjsE/8heO/0v8ViuA9861tiDKH/aXzwfBv3i1903QMPFH+/732BD3nhheK6kye7LoSP8Ffmk/jXOPVU//9Bxwn6OuC6zz3nutddF/zP5yKA677zna4LuF8C3AH2ue/P9vYKv9j7/2bA/bPnBz3c2en+qq3Nfb6jw72bxqM99hD2yZuTqH7uZX7hh+jzww93XQjfpj+Xcz8IuK/n82HfYvVq3+8I/RSLrnvHHf7/ANwnjzpK/D97tuuuWeO6P/iB+P8d73BdwP04P5+9929RO6Dv3v9+3yaGfvbZR4zLCxcG7//444Vdfuyx0DzUBcQ8w/v7LPla3E9fvFjYcq8NfIYf543vLhCejwDui21t7jXkn9IzKe59Dr8e9WGar33ta+L3jjsGbfBd73JHGwA84LqVPEymZ4rCnXeK3xdeKFanvFX+8cUiOumYb35TfMbPW74cOOccsWK6YoVYAf/PfwTz6q2aAQj+fvVV8bNmjVgZ+PGPxee//KV/aDP9cfHFQk3x/e+L/3/+c/H7Jz8RK80//algdh99VPz2VodaADSXy4J1Pe00wR4/95xg6H/5S3H/Bx4Q7PQPfwiUyxjb3x88J4CefB740pfEChQgVsxfeEH8/fLLgqUvl4WyB8A0AM1bt6IDQFu5jI7BQey5Zo1YrbvuOuBrXxP1s2oV8OEPi1VFT92xI92UWOaFC8X3AD5/3nkAgMm8zu+4Q/z+7ncx2NCAFkjYtCmoZ/rx4NIfkyeL1U1aoeL3Z+/DT2345S8DACYAcFxXrHatWuWvcjejEm3lMtrKZbQCgqFftSr4ufBCNJbL8LMCvfhi6Nyx9Mdtt/kr31P4Af/4hzjn5JPFKt0OO4jVgcmTRdt6+WVx3N13i5XBF18Uz8oUFaFyv+Ut4pr/939CjfL448Dxx4v3DPgr3fjd74L/XVesICxcCFxwgVgR3LpV9IXnnxfP+T//I1aT77tPrIhdfHFwc++apwPoffZZsUoGCFUJIFYZx44NlBd8he5HPwIgVr1aBgfRTQq3DRuAFSvQWS6jhRQIDz8snvvEE4P6/8hHxGcvvRRc8//9v+Da8+YJNcJVV4k+dPfdAIDp3qH70DlHHSXq6utfB848U3y2fr3/PlsHB9E2OOiv5H0FCNprf79oZ6ecIq7/9a+LOrn+egBAH3tP/t/e6k8jgN/dd59YUbzqKlH/v/ud6KPjxol3vXgxWh0HLa7X6l99VbSngQHgyivFakl/v+ifrit+T50q7IYnE8bjjwMAOuj+1Pe8fu+3U8Lzz4v3dOGFfl1vXboUTRBtbbCvT6iLPvIRseLX3y/UeAsXAu96V+hZ/Xp68kmhLjjoILGq9KtfCQXCQQeJcs+aFSjwVq8W6pe77hK27bnnxGrWPfcIxdejjwItLWgaHAyuf++9wPe+J1aq1q4Vn914o/i9YQPw1a8CH/qQaAcdHYEdW7VKrIK99JI4jtkZvPWtov3svrsok4Q2AO748cAnPiH6zHPPBV/eey8AhOwxAIQChN//frFC95//BGVZvhz41rfEuDBxonj+l14K27hXXkHr1q24a80aMUaR3SmXxXnjxoXt1KpVoi7p3dL7AJMD3323eH5AqJp+9jNR17ffLlQMn/60aJcXXCDs1cc/Lu597LHi3Xir8ifsuSdyrovt6bq//S0AoQAA4Lc5vPBCuL5++lPRpq+7Tqy+kh3xrosXXhCqltWrRX/74AfFc59/Ppr6+zEXgFsoiBW/Vav8cb6Lrn/nnZV1smqVsHPXXQcAaPGk6Fi5UtjeF14Q/dmrc6xciTGOg3ENDUF78BIA46yz8KEvfMG3LfjNb8Tvb39b/Kb+67XJNjruxhuFPbjxRtGPHntM9INLLxV1d8894v0vW4ZW6s8MTfTHwEAwXnj9HbfcIn7fdltwwgc+IN7vz38etsXXXivshfd+elxX+AKui+aBAbGKumIF8J73AG97myjf/vuLNvOLXwTvid4Ve7f+s9KY8Oc/B8c+8YT4vWGDeB8AWgE0ua6wJfPno8110ULP/uqr4l3Q9W65RSgELrkExcHB4H17780fG6k8t94qflN/oGfn5eR9DRDv47nnUPSu4V/zt78FTj9d+BzPPivaJD2L17/whz/46g68//3C9n72s+L/KVOA735X+Do/+IE/Lkzl93711eA9HXywqK/HHxf9+Oqrxer48uWi/jdv9sdZf8P4l14K3s1jjwn1x1VXif///W/x2zunF0CxXAY+9CH0d3WhCWKMIrS6LlrKZaEOkPvRvfcKO+md03vnncL3JJ/DU6FQ/wj537vvLspJ19plF3+sngDhG+DVV0U9AeI5//53UZ8rVoi2T3V8yy2iPq67TrQLxxH21Ms5iLvu8q/dS/e/9lpRN3PnAu99r/iMbMHHPw4AcCDaJYDg3T72GPD88/64CEDYk3vvFX7Y//6v7zP49u8PfxB2q7HRV8H0Asi5btBGH39cPOvVVwuFw5/+JN47+e4c5B95baSvvz9ox/vvD5x/vvAHCfQ+/vUv8fuRRwIV1LXXijEEEP6W6/p9shlAs+uKNrhqlfArX3tNjBEecq4b+BiAeBekPgICv4Pwne8AEGNiHgA+9zm4jhPU8+rVQb+aPh1tgO8HtQ4MoKNcRsvWrcEY9te/ivf9j38An/lMuH3+7/8CAPZiu2b6/phnq3cEUCiX0QWgg/sWAHD22eJZPvzh4JrPPivUQscdF3qs8RTd8NRTov2QjfPmfn67IxWr18Yme3WIyy8X1338cXGfD31I9I8HHxTt6/HHxQ/5vRs3imcYGBB19fTTwg/y7Bp/B74OhmzAs8+K38ceK+zP1Vf7bSA0H3rmGeH3H3ZYcF/PV2rx5oyYNEn0DZ7Xk64PNvfZZZfAhlObpzr697/F/adPF7aaxs1RjozcMWFwMJjEkjPjOTcH7r47TjriCPHZzJkAmNMHiAb16qtCMjtpkpB9b7+9kOVTIwQCp2TdOuGIvfpq4PwDoTCWDXL5aHL7t7+J3/vsIyZ15Eg8+aRwKr3GXAJQBMT1Z84MDB0QOOF0zRUrAAB9W7cGzh4gjPajjwpjUSyGJYVr1/qDHIUoPAygNDiIRgANrovxHR1CXjxlCvDOd4qBb9IkMVmfNi30eFvoj2efFVLpH/9YyAcBtKxbB0Cqcyr7/PlwSyU0AOh3HOCSS0TdlMuintevF789oggAlvPrvPZacC1AGL2GhmAw55gwIVyON94IETKqFIgl76fBdYXRGjs2+OnqQp4/+4oVwlh7Dr1v4saPF3UIZtiBYIA98URhkO+9V9TZ9OnimTduFGEZ/f1igCfnfc0aMdgccQQGIAxD2XGEDHmXXYQs/8wzxQBxzTXAqaeK82hC8uSTwBVXiIk5ICbYl10WTLJfekn0pSlTxHO+9a1BaOGyZT5xweE7L+94h/jtOQVYsUJMCAnUhtvbfWeFpgUtPL53wwY0ui4ayanftEmQqwsXBvV/8MHiuwcfDJ7vL38RMmNAON6HHy4Gvh/+UEjhARAV1En3OvZYIXl96aVgArJ5sz94NbiueP+77w4ceSR2hGgTg9OmifoGgLPOEpL597xH2I6xgjLhDkKo/UPYiJLrCgdr5kzgC18QMtW77xY/220HtLaiEUAjDXLUF2bOFOTLSSeJd0M24dVXhQPwwx+K5wf8Nl5BoHpEsj+V+fSnxSTuX/8S/W/OHL+u3ZYWFCH6SHncOOFYc0Jj82Yx2d9779C9+OQAn/qUeBfHHism7+99r3AOly0T7e1Nbwps0sc+Jp7r3HPFhOTUU8W1L7lEnP+OdyDvlae/s1PIgE8/PZg4AYGj+sYbwBe/KIiUjRuFY0p2bOxYEV5BdoCTOw89BHzuc8Lpf+01YVuoz3rP5ra0CBIGEBOuMWP8dw8wQu3AAwEwm7DHHqJ8++0XtJexYwWxe9ZZwmGcNUv0+Vde8W08AGDdOjR6dhqAsB1dXut69FEh1eZ2auxYYVOA8HUgwuwAiPGT7AsAnHGG6EckbT/qKPGcX/mKWKj4xCfEAsXXvx70NwB7z54dvq6HTfTHzJnCPr/0UlCWqVODCdOee4p299OfionJihXBJOOIIwSxsHSpcN4nTAB6epAvl9EOiHYybZp4Xm9nHT84pK+vsk7GjhX2gdoJe28AxD0pZG7jRuCVVzChowO7zJoVEIi0cHL99WjavBlNkyaJ/4mA37pVyOtvuknUk3fe81L9+BMwOm/OHNEf9t5bkHVdXWikcjIUAGzs7BRthfD008K+7rab+P+++0Td8PDE7u6gze+3n+i/gO9/PJTPo8EL/2gsl8XxkyaJBZ7vfEf0s1tvFe3q+98PE+wvvBBqZ22QQD7Q+PEB8eD5CIDo00XXFaFwHR1oct3g2detEz8UQvvaayJMwMur2AXALZV8OX/IHwKC/kshBvvt55Pgz8rHnniisKXr1wMvv4z8ypUoAniK2nu5LI6ZN0+0u+22E59v2BCMc3/4Q+C7XHih8MN+/3ux6PGJTwj/b+JE0a7POgsA8CQvQ2OjINxuuUWE0KxeHdhcsvm3317RrzfTH+vXi+M7O0WbWrIkIC4ee0y0jT/9CQBrk729cItFFAC8AWDwjDOAgw9GDp4f1NFR2Y/22ksQ5xCTwkZqD0QmeO2LWrDfJubNE77iuHHBtXbc0R/T1wMolcviOXp7xfh/773i99y54h2sXCn6J+Hqq8X9vvAFMWaXy2LxZcoU4R94hOxWOn7cOFE3n/tccI3eXnENL2n6c2D+4auvin7std3t4I1zM2aIutxrL+EXHHusTzL7C4x9fcJuzZ/v38rvOdLiIPbdV1yL5iB8oZlAxB/rf60AXMcBLrpIvGvy84Dw4icQkP0zZog6LJXEPOg//xHPSLu/wfNV2trEO+rtFe9kyxZhsy+/HIC34EH26JZbxKSddo6jPnfjjUE4EQA/KLm3F+V8vtIP3203YOJENDiOaH8AGsplNLkuGgYHsZb646xZYnHv3e8WRARvn2SXWR2WpNvQGEVjdhHA65Qjhhbl99svuOa0aWKcWr/ev8ZcAC0vvSTIk7POEu//r38VX3pEmD+T2X57EbbkjQmtNKcaN06MiXTenDnis/nzxTj83/+K9/bqq8Je//734t0tWiSe//HHhV2e6tHEjGDx+x3di/x08tvJ/4U0H3Jd0aYnTQrmEV65S4ODws62tYnx/UMfCs5jIef+wtb11wu/DgjaPF9o6OoSiwcvvihIxm0AGbljwiOPiM7TxIZzb2WitHkzLvQGTnR1wXWc8ESLBvwpIV2FcBheeSWIUSfyiDrzypWiQU+bFuQw8VjLRkigTuO6IsZ6/PiQgcMzz4Q6Vgmeg1MqBZMH7nwDgUPmYczmzZVsKyCMwoQJATvqOKKu7r475JivcRyUBgfRAGHIp3R3o7epKRQTHqobXhT64+mnxQRn1iyx+gv4BrWbjikUAsdk6lSf3Cm6rnBm2tpEHROxI5E7BQBbxo8PVuaffDJwbp94QpSNJt1g78J7N530/xtvhIyPityhiX0DEORGIHiDlp/d4vnnhWHyjGorP86rw5mcdKKVs3HjxPuh67e1ibKtWycmzE1Nwknk73/ZMmDXXVHw6sPVJSrr7hYraEBgyAFhgD/3OVEnU6aISc4RR4jPW1pC7QJjxwrHcsECMZDQ6haD/6ydneF7tbWJQY6IBiIzly3zz6Wh0W8fHnqamtCSywU5ZgDhDBLIQSJyx8u9gM99Tky6Tj5ZqJkI3r1p+u6/zebmYLKz1XP5nnzSn/Q10uSiuRlOQ4NP+LnFIvDRjwpnaOnScOE9e8B7jvx8oUnP9dcHTtBeewUDc0MDGsEckTfeEIMqtaOOjqAeiBxbtEg4X5ddJv4nBRLU8KdVxaKoN1qNY/bQKRRQhKf0KBbFJKHDc4PavCfZd1//GSrInRtuEEQUx0c+Ioj0971P/D9rVlD/y5aJyX1HhyDMaDXoc58Tq3ClEgquiyI8xQbh7W8X1+D94Y9/FJPAq64SNpccC0JbW2AHuIPd2yvK3N0tzp87t8KuOI2NQT08/7xo/6xtd9IfntrNbw/nnCPu6ymdlKDcauvXBwQEAKxbhwau4njwQeFgU/vZYYfKa1F7kVZ/Q5ad25fBQaHYy+VEOaRdC0NlPOSQimtskg7z20GxKMY+Tu4Q6VAshkmK7bYTz/7UU2KsGz9eqLP+9KdgTPbG+24ALh/7PfvVIP1fgcMOC/6WJ09PPBG0pdWrhS+wYYP42bxZTGwkn2HB4sXiD77iePjhwkbM8fUUwcSSQAogIjvYCjMAoLkZjYODWC3twpQHUM7nA+ccEON+V5d4Nw0NwvGfOlWQ+ITXXw/a/CmniN+s3ZQgcqg1ui5Kg4Nhv4rgOIIM/vOfRbui8194IeSs+3avVBLj++Cg8BF23VW82298I7S6XIKnICmVgObmMLlD4+LSpcJuA6Lte3nXugC4DQ3+/5100XnzAj+K6ggQCxceKrycd7xDkLJem3ZcF1PBJnyNjaG+7tuo9euDCdVddwX9qrdX2OpyWdTViScK4o/av0dwPg3WPt70JkGa7LNPQB5RXTiOsDe33x6eHIH1PyJ3aDLHy3vbbcKOk3KNPm9ogJvP+76Fk88DjY1ogLfIoGoLgP8+mgE0kB2VyB2yWv7Y96Uv+QuuPlg/eQ4euUMLfYsWBeMdEasrVoQm2HjkEWEf5s4N+vdhh4mJ9P33+33Nb5fUjt70JkEaA+J+d93lq4VoYcOlMfavf/XvOdN7Zv86HJ7dKUn/+8QrmEKCjz3NzWJxjh0X8t8I5E8xcqcNHsFJ9frQQ6L9O05AohPIByU/aeFCcc+VK0PH+ovNNMa0tgb+eWtryA6jqUkoe++4Q8ytqM09/rjo9yeeGOQKQnhsKOfzkLxsMSZ4+USpHhsHBwW5MzAgFEWLFwt7fdhhgtyTd6ujvslsvGqxzX8GiLZfcN1w3hdayCdsv72wXx6O8P84QjxnuRzOEwmmli0U/MUwAFhK9rOlRbRtIvWonQNhG7B5s7DtN98sfJT3eAkw/v53Ye9pwYfNK/1+5+Wh9eujs1O8N9aOKuZDc+YIG/bqq+L+jNxpAYL2f+mlwdxPRe5MmCBU54Ca3DnwQDFmAoHScpQjI3dMIHaaO8s0CK5dG5AJLS1wGxqCjj1+fCBtVJE7W7cG39OqskzuFApBp/M6qGb4E5g1Sxha7jAz5VG5tzdgyjm5Q9Bss9m9cWOY3OETbLpGY6Mo66pVwvAef7x/eAdEI2t0HDGgbtggnlVF7lDyUw++emXNmoD4IYPqOTf+YEqDd0sL0N0Nt1gMEyGtrcKJo8GDfnvIw3PgyJEGgkHw1VcjyR2Vcqfc0FBhzLZCvAOazOvIHX+a9fzzYqLnfR56Js/w7UNJWXt6gnYlO/Lt7cKwb9ki6nmvvcSEhtUB5s3zHYUiDOQOe+4K52BwUAxOjiMmMP/v/4UnCRw33ywIplJJrN5+73vhWwAYLBSCif5LL4l2WiqJgeR73xODJE0umZNJrStMFwIzxo4NwuEIvM90dopB7Ic/FE7i1VcLh+iii8RgMWGCWD27667Qu6tY/25pEQMhDYIdHUEfLxTQUC6LyUVTE1AqhR2dN79ZrMrL9S+RHICB3Ln++kpyiNDYGFqxwsCAGJA5SUgOAg2IVF/0LlTkzs47B7egPwqFsCPB//ZWcot0XLEonOGmJuC880Qb23PPIEGnfO099gjIJ0J3t7BBRx8t/vdUHwDESuJXviLKfsUVFdWCYjEgd2R7WCz6Kj0AgeOw997C8We2AUCY3KH22dMjVn4bG0XbYOQyoQkQz0+E5vLlou0wssNX7njvwm8P06YJWyUTXhy9vZXJlgHgjTfgcHJn/XrxvGRXVeQO2QAiVLywFSW5c9JJYkXygguEk37yyZXvjuMznxHEHrtGQTrEH5dkcqe5OWi/c+aExzYaU70QN4wbF9gq/8LiymPY36IAogQl6f8K7LqrIBkdp5LcocWTefOEEz0wIOqafIm1a8OkGxCEhwBiTGpuDtrDjBn+VxUjuHwdOZFkczOaAJRZ/awHI/Y/+MHAP1m+XLTZXC4giadNE/2MJvmvvy76VqEgbGRjoyARvvc9oLMTnRC+QBPgE9tKzJolxqnHHhMTQ0C81xUr/Pfnj7cvvRRMtrfbTvw89JBYLKBwWAibUQCEDW1qQlO5HJCZb7whfsaMERP9YlHUMyNz3IYG3977/Y+SonM0NQlyyuubFQqjCRMqfK8Z8NpULifCvDnRIZM7Y8aINvSvf4lnaWgI/JSddhJ1+stfihBitmCyBd4YdcQR4QS2nAQ58kixYHLooWJclsZ2n9zZsEH4JfTeqS3uskugPvPg11VjI+CRO3lA1HFTkyD6yuXwBgYcjNwpkh0l8sAjSSqUO6pdxRi58zKYcmfdumBMA/TkDi3wOY5YWLr4YqHyXbxY9A2vbL7amN6h44iwm6VLxb1uvRVoaMDArrv6Y75LYxQLdbzmoouw94IF6j7i2Z0KkpktWPlPxMmd+fPFsXxhi9mI5+iPp54SE/qXXvLfSxu8MXHatMBWzpghxhMiK668Usx3SIVB5M7SpcH4wUIXfTUdkTttbaLfv/aa+Fsmd444QsydVqwQbZ7eG/m6bAzmY4NbKFSmR5g5E/AWgEueH9RYLqMtn0exXMbU7m69fSLQHIbZeNkf2yR97i9mHX64qMe5c4OFHI4zz/R9lMkAyuRHeZELkMJpfYshkTv+u2hpCZRGQPhvGhMJzzwjbMhJJwW+8eBgmNxRhch2dor2TnajtVX8MDtSMUbNni3aULksxjnPJ8q7LtpdN3gHjhMoK1XkTnOz6PelUiW509cnokQmTBDkWLf8lkYnMnJHB9cVsct77SXk/J/+dGiAwBtvBLJNmdzhnUVF7hAmTxaD9CuvBJNsIneAYGLiqXFC5I58XTqWOiN978WklqdPD5Q7DQ3hzv2pTwW7QfEylkro3LAhfF9iYdvagsnOpEmiY3s7IOCAA8QPAieskcJQaJUyjnKHf0fneQ6/X+dz5wbP7ThwS6XwYN/aKgyd6wbKHYYCvNX6SZOCwYavcIwZE/rfd0UaG+HmcpXKnUIBA729FcbsZccR5I5OueM52r5yh3ayUpE7xaL4IQPOHP2KcIC2tvC7mzkzWAGj682eHXIcXNN2kM3NYUMOBO+Iq8dM6OoKE3ptYVe4Fd6gxsmd1hCdEDbUjMygo3rkCeSGDaLf9vWJ+urqCk/aAfH/v/8tHLi//12sXvDJn+OIVU/WBytcUyJ3aLWVkwxTpqCxXBb9gZE7JUBLsoJ9pyR3HnsM5Vwu3D508FasQi3vxRfD5M6llwrZ8DveIZ6T2j4d4w2w/v0uvzxYOYHkbHBbxcmdUslfvfSf+0tfEhOLT3xCtM+WlornDhFHUSDVxvjx0c5asYiiSrlDoEktEBA2KscMEPVETgb1u299S6iAgMBJktAKSbmzdq3o/6efLsgRMOWA9y789kA2wQSJQPehkuePHRs45SpyJ58XfZPOPeOMcH4DICB3rrgiyCPwy18Kks2EBQvEpIiVrVM6REvuTJ4cjIOyLaKxmcKhVTtnsEmFk0S5k8sJf2HhQnW9AqEQCmzcGEwk164NTyqBsPrpnHPEMdSnTOSODJnwb2lBV6mEXjYW98Nb6MjnxXMQETE4GLRZ6gdTpwa74I0fHyh3xo8Xdvk//xGhlqefDuy2G8Z4E0kKfdCqNegdDQ6Kv8eMCSbQnh317V5TU3A8kTsKhPqIp9xpGBwUtnxgQJCibW3C5n/602JSy5U6TLkTIiy4XQfE2DFmDLByJfq7uqzJnQbXFaTQu98tFdwr+YoVwhcgO/z884EtJgJMVsIxJUMe3qRy/vywb8Dr69prhc+7997KfGA+ubNuXVi5s9tuQe4kQJD811wDt1AI+mxjI9x83i+HUygAjY1oLJfNyh3v8zYAebK5knKHxgPj2Ef+IRipsGaNv1OgDxqfli8XvgJNKJ95JvBvxo8XJH1DQ1ilB0buyGNNW5uot9tuA5Ytg9veHih3aIz6wx/Eb8fB2LVrMbatTe0ny3aIxqo99vAP8Z+IE/nUdkiZSwsIHvzg4aeeEjZm82b/HfvKnVIpsD1TpgT2c/JkESJIobqAIFt+8QuxMEZ22AvXK3d2BgtaUoSC7+fJ5M7eewfj4uzZQT8i/436AVh/95Q7obcxbpx4H6TcIXJncBBTvXc8taUl2l+QFpqBSuUOtcQQueO6og+efnqQ3kAFb27QDqBMbbqzM1zHHkIq1r33FguEvGwyucNtkGwzKQTx9NPD9o2TO2zXMN/GNTaK+3Byh887IIWtTZokjiGfZPVq0e68Z53a1BR+BzQPYG16CtkN+t3eHtyPFkXuuy8goG+8MUT6j2Zk5I4OFEf7jncIo/6Rj4Qbukm5Q52loSEYHAicwDj5ZEE23H574NBt2hRN7jz6aLCiTsaOBgja/vyMM8T/d98tjunuDsKUZOXO4YcLY0CD9eWXi+fdcUd0rFuHZggVCgC1cmfyZGF0SM7Z1+dvIUl10kz3Xr9eOLMW5E5oWk6SP+rssnKHBm/P8XSLxcDolEqivBQasmVLBfNdAIQzm88H72/HHQNHoadHKJK8UAg+wSzzd792re/gUmgYxyaIVSMieCKVO4BauUPnNTcHjhiVu7u78rrt7YGqp71dvGtatdl/fzHIFIshx8Go3HGcgDADRD/5+c/F+bKKwRYKcsctFIJB9PXX9eROZ6dwWLx+Qa1runRNP6a4uVkce/jhlQqC448Xn11wgbgmhX/JYINlBbnT3CwGQlqpl8gdX7nT3OyTHCXATMqYyJ2WlnCbV61esu98p4ZWTLduDRMVEycKm/DmN4uJBNW7twJLbcl/G8ccI9Q9nqOlVO60t4fuURGWRfelLerpPEm5EyKOokD1Lsv0VeAroqqJOyd3SK2iI3fa2oJwMLI1nDzTrB51AqKO+XU7OoRt8hR6nfweCDuykdCROzy/BGHs2EB6ryJ3gOCZ8nmguRnlQkGt3NHd1wRpZVR2nI3kzpw5wiawCS4A4Rg7jhW5M4aXAbAndwitrWFihqsTeCio6wZ5mdaurVh4CBFEM2eG2z1zzI1vv1AIxlBCczOcjRuR27hRkDDvf38QkkvPxklIarOc3CF0dgbKHZpsTZ8e2LPmZvR61+yk/qCbPPFFivHjxfv8xz/EhMLrz36pGhqC42fMCE9U2AREVryObWoKh0cMDIi2fNhhQRJjrx10wQvPY+SOm8uJOqUFP7KP9OytreEFJiprV1fI93JzuUC5o7LZdN1HHhG/VeTOsmXiXFmpyVTIPrkjt9nWVlEHLS0B6SP3GQ/+Ytvzzwvfl7//SZMCH+zII4Gzz8bgpEkhcgc8LMtT7jSQciciLGs2IJSF48aJ0J6tW/2xlXpoyN+TMXOmP863QigD/H7GfQQao0i5Q0TGwIDahs2ZI/y9H/0IbqFQqdwhELmzfDmwww5wikWf3HH6+kTfeughUUYKLaStymXowrLmzQPuvx+u4wR1QX3gq18NQqoBMeegRPQefPvx5JPBBNmbE7SDqVlpLOXkDv2mOurqEu/hmGPEZ1OnimfxIgncCRPUyh1AkJgSueM0NQk7f+ih4pjZs4O+RqT17rv7oTuycic0JtFcSQrLcsplODRHeOUV9RyFgy80e21LHqNoxKd2EfJ3rr9ezLN0YOSOy9u0wr8O+UTNzcIX33FHNbnT2Rn2o7u7w0TfT34i3vvuu4fPmzo17Jd49sL3amgRnUK/iNxhC8ChXkG2k+bIL7wg+rX3Psd6PoUPah+bN/vtbEpTk7gv9YG2tmCeQ9D5aKMcGbmjw/33i4ZywgnBZ9zpkMmdxsagY5Pxmzy5MrSCExiHHio61W23hVfrqBEfeKAYMD1H0O8YY8YEg85BB4kOTVLLUkmspH3sY2FlDYV+kDGleEggcDaI3Hnzm8Xq1eTJaPfIHZfKvXq1eKampuA8Uu7QZIYMfFMTujxWvJ1CQOg5VYazqys00Q4dQfene3uDVkVYFjkcKuWOAb5yBwje37RpgUM8Zoy4ztveJi7pn1iA29AQVu68+CIwcSLcQqEilI4INq1yR865A+jDsgBRj+SkkGMrr9ACYQeGcjoRLr/c32WAT3DLJnIHEHVK7/Xaa4Vz+fDDIjFzEkhETAu8kAH+7mSyhiYc3d2iTm65BZsp9ApAUQ59obpqaRGhYF5ywxDe9z4xgHzlKyL3iCqRNmAmd0i5Q5BWQBrL5SDvBA/LMk3QTWFZTU0oF4vBQBul3CFykTusuufkcJzQcRUE6osvor+lJexsEEnDVTsAnFIpCMuK8dz+tW3IjMmTRR+zIXe86zXBQrmzYYOwRTq7IrdT+TONcqcLCIdlAYFzwsNEcjnf8QmpEqLA37cpLAoQDvt73iMmAhLxXlG29nbAcSrJnVWrQhL7WKAxwrP1keTO66+LicmkSaKunn5ahPdxkGqVdn+KIHdCyh3bsCxefiLQly0TK9gETu4AQUJaUu6ce26wUyc5y8WiT/D50Cl35En8uHGVvkhzs3CESUnLJt8+sd/REbQTarM0dvAxhMidlSsrQ769e3V5pE4n1YmO3JkyJSjrhAnifVHiVEbulEslcZxOueOt8JabmyvInRKNA/z9y/ZPVu6wsCx/JX3pUjHZIj+Rq0B5aDh95zhB/TQ0ALNnC3JHtdADBPaFkoCSn/f660F5Z80S4xpTbgAQ7+djHxNFoc9UhOSsWUFYPyAWNOjdMJuylf6gsChpAwwsXCjGThr/GxvDyp1CwW9f8JQ7Da6LBouwrPdSyPXhh4s2++STenJHVY9NTYLALBRQMdWTbfiUKYKE4eQOoLeB48cDp5yCwebmsKKMo61NKAnWrxe+ikfu+As6NLZMniyI9Gee0S+C6sgdAFi8GOWGhspceEcdFW7rPT0VY6LfRp56KiB3vHL5yh0g6GMmckde1KbFCc8fcydM0Ct3AHVYFiCUr1OnCpWarNxxHBEOivDYUJbDsmihgi9ykb0hcuf116OVO0QqDA4C7e0oF4sVYxS1NWoXsVTHKnsDBDaAjQXKBa+WlmA3OMq5A1T4YQDEO6V+8/rroo7IHvCFc66k9955yAfk77ClRfzvzQtdxwm/B8pNRm2GxAE0f3ntNTW5AwRE9GuvhfuIyofNyJ0MIbz//cLA8wbF5XBvvCGcIscRAxcnd7jxk8FXz8aNEzHbf/6zmtw55BCh0vEabMgw0LUXLxYrKSTDA0Rjz+UCx3bNGjiNjSL0g5IKOo5wmorFoHPNni3uTYZ50iR0bdyIg5YsQb69XQzAtMMTd1JIuUOg6zU2+sbNJ3d4GWXk86H6CQ1QvN6YAfHvKit3OLkjGx0F8kBgGGkiPmVKmNxhx/B34ZZKlWFZEyYAiljfEuCrdkzKndC0SxeWBYTrkRx9FbnDjR4pdwh8ILZV7gBBnTY3Bw7G9tubVSMm6MKy+DPqlDtMCRFaqVHsBuOXWQfHsZsoM3KnYuoqkzs8pHPyZBRcVzi5nnKnBFHnjoVyh5e80y9AUzjPlK1yJy65A4Tek8qhdvP5ymS3uVylU+E5uCHljgq6nDs2DlI+L1aiLrkk+lh2n4qcO0ClPecTXxmquuSf8bbxxS/6IUhdQKVyh2wrm2yWSSKPKpQ7ciJHGWPHinLst5/+GHom73c5nw+TO089Veno20IaIzqlryvIHUBMoKiddXer2wgpEwoFNcnm2YZ2IDxJS6LcIXz1q4Gatr09TBRyvP56kFCUznddsYjz+OOVdblkif8eQ2+f8l/RhFRFYnEb2NwMFArIg4VlAaLfUvuzIXe4cke+l0fuUBiElvArlYJ3OH58OJzAW3XvAlMT77WXmPS96U3Czl5xhTjPu5/b3V2Zq061m5lMyHJyRwrT8idbEycKVdFee4n/2bNXKHfou74+0XYmToQzYQLGwgvLUtls6gOUHJrlNQvZE1Xfdxzgk5/Epr6+yhAejq9/PdjimI4h28Du59+ByB25DZdKImcQvS++6CUpd5DPi5w7PDxZBa+NLqZ3Q4r1//zHn7hSK44MSf7Sl4Djjqskd+T3PnlyoNwZNy6oMx25Q2hqCmySKiyLSFpP1eIrd4pFkZtq2TLg858XvuZrr+mVO7qcOx7KhUIluaNabGA2YaPjBGTR888HoS8sLMuvVxvljsrmU2hWayuctrbwYrP3uQ+m3OkAgvZx6KEiJLC9vVK5A4gFBh6GJefcee97RRoKAKCNLFzXOA5o4ThB/2xpCSv4PfjzH+93rIUpnXLnlFNE3ifa2VV3XT5+cgUOt6eEyy4Tmx0QuJCBfFfyf6iuPNupXURvbg61u3JnZ+AbfPnLwXioI3d4zh0g3IapvcnHyH4XKb62QWTkjglSTKof09zbGyh3KPdIY2Mw+JnIHT5AkAJnxYqQhLjCEHvGPMTOcqafVoRk0A4uixb5O+QUgMCYTpwozqVJ/Ic/LBKe0bUmTYKzZg3GF4viOclYUPlk5Q6BKXdo2GmzIXeAUP20aj7n5/oNeIcdhHHylDWQyR3V4MYQkqKff76IzWxpCe5Lv1XkTkNDYLS4cqdYDAYVz5lp8cocRe6Eakel3CGDxQ0bkY8qR15W7nDHjE/42KqQNbkTQZxZQxWWVSyK9knv3IbcKRYrdymRESW5tQEjKypcUwrLIhBh2N4e7ive4JOja5jIHaltDHKHuLHRPiyrsVEox5KSO+w4lUPtFgphAqZQEKvbPIcVEJamx8g1FIvcAQTxzcm1iPs066593HHAxz8eOD6mFSGVvdGRO/Pn+6uJLUAwkaR3KCl3/JU82VbYEJLkdDsO8Nvfil3CdJDzdqlAZfN+V0jgH300Obkj9XW5xyrJHSBapXXUUeL3wIB63OT9itvXuOSO7FxTfY4fr58ovvqqUPHI+Tba25W5FtDVJXIYQSJ3aLckWuVVEf4yucMn39z2U1ul38ceK8iARYuCYzo7xbi3dq1auaOavJsmT9THJkwIxqpCwe8nebAJT0uLyBVDybE/+MFQGKHb1aXciABAuI1rlDuhPgkvLEvua1S/PORKR+7k8+L4iRMFIUATa5NyZ/ly8WycULO0124up1Z5EHbeuZLoPeEEsfDI2px/DZr4q/xbft+GhlB+Itoty19IY/5hlHLH31572TJRD//+dzzlDrtPp/yZ7FNMmiTa8vr1oh+SbxFB7hS4zZfbuxQG4xSLvnLFKZVEvpo77xSpGjo6gk0/DGFZOsKuot0B6vGILRo6YO9306Zge3OVcudNbxJRBfPm6ckd1dhBfbKvzye3CqqwLPpbZ4cJ1J8kMjlE5sjkzq67BuORNycquq46TNrGR2Q+cLmhoSLpv9xDY4WUM+WOy9v09Okifx/z4ZU+ES9/c7NoV7qFhWOOCSvuuQLyvPMEAUzPSuOASblDAgNO7nR0qBeiqF8RucPnL/wZKCUAINoZjd06AgjYZlU7QEbuxMP++4vY5yVLAuWO1/hCW6b29opjvaTCIXR2Bo5Td7do2HK+A7mBsnAB//899xSJr8hRVaGzU7DcN9wAhxMQZCjOPFPkFSFIO0L5ne7FF0UHoo5L5Zs3Txy/zz5BJyoWA6eD1UlFQ9MRAmwAVYZlAWqjS7Jbcq5KpbCKwSIsyzeMU6aIrOqAnXKHG17K+D5hAsDJna99DTj3XJ/kykMkltSRO6HSSsqdwXw+MGxUF01NgYNpo9wZOzbILs+/s02oDATtIII4s4Yu5w6gJ5I05E4k3RS1KmODqLAsKlM+H0xWenvDTosXlgV47T0GyVH26qvsEWBujLCsRnhONp942w6E7D0pyZ1crtKJ+ctfghUzD6GwLJOzU03OnTiIUu709IhEz0TOVUPucGeytzc8uaG/JeKEH1NmyZMTKXe6uoRNU0m0CTbkjqzckfvec8+lptyRoSV3TLuFAQHxoYPcPwnyinlU+5NXoltbxTNNmFARguyDknBz5Q5grgu2wyEAsdPf+98v/qbdVVRjguz8FwrIedcJ2X5y5qnNNjUJ34ETQJ2dQW4FTVhWBUyhetttJ56rt1fc63vfE84/c/zLOkKAygOIzRU6O8OLIrwsFmFZ/t/eWF2AFCYBqPMQyX2Bk44nnyxIsqYmNMEiLGvtWvEeisXg2WzHXb4VdNSYTjj3XJH8lrWb0BM3NETvOiPXX6GAEjxf0AvL8hGRUBmrVgXPPmOGUO7EybnDylFRA3I99vYGO4u2tlqTO1q7Id9DUu5U2G1qh3LICcEUlgXhM1XkelLVieP4Np52ifT7w/33i37iPXOI3NlxR5FKoqUlmXKntxdOqRQsNqvCsphyB4C6ffAFbgajcofXdUMDWmnROYlyBwgpdyoIX6DCD1WWQwe+O5/KNjA7qw3L4n87jti9ljYqkFEoBLaFkzvbbx8kSweUyp2y44jz5UVY9k7LHR3q5y+VhI8jK3eA8DtwnPCcg74zKXe2YXInZe94lMNxhIHq6AiUO15jduSB7Pbb1dfI5YRTPTAgOoNqwNAod0LsbC5XubOCCp4BdDjZQUbolFPM51LHWLVKsMUyudPdLSTJQJAfoK8vcFpNzpvOWWVKgtARPCxLOnewUEBeVpk0NIQH+4j8EkVA7fholDuhnDv83dNgMXUqkM+Hja5koHNeOUNQkTtMudMGIbv1S0qGraVFGPvW1sq8DEAluUNb2m7cGK6bJGFZNVLutIFNsltbRWJRU84dgqweUCEN5c68eeL9bdlSSe40NQWDYGenqHMKgZRXzL18G62AedWRkUCu46DY2Qm8/DIcIphjhGX5GArlDv/NQMqdkJpQBe+7CnInbbktJ5FM16Y2KCs7Vcdw8DbHncm+vvCuJpzcefnl4D489K1UAvJ5lB0HLWRzbJQ7HR3i2cie6SaITU12jpFE7rhyWBaQKrmzacECNN16KzB+fNhR3HFHQWice250PXR3CwWAyk4CkcodowpCV376e84c8UMhYXybcyDYhU1W7pjslWen/Rbb0yOe8eqrRWj31q1BOAsHf7aWljCxz/sr2VZNnigA4b4g7yAl38v0GeG888QqO4Vqs6T25XweucHB8KKKDGq73q44VsodTVgWANEm2P8V995xR7HbEQthdLkP8v3v+/lAAIjdlgDg//7PTO40NIj3Wy4HPlBXVzjnTgTcfN6+zcp405tESCEUO91E5ezi9eflJwkRo1GTdyB4V6tXi+cnHzxJWBaVQ4bsv/T0BGF7ScgdemccvG15yh0/54481nC7myAsq2Jxy0QCTp0KrFiBIl1v1izh799/f+DfQPhim1X1utNOIUWdkdzhxzQ0BPbbRrmjah+HHy52kJRUZyEyp1TSkzve4hIA9Vhu4yMyMiNENu+1F9y//x0Oj8hATN/Fq5d2QN1ujzxSLDZ94hPRYVnUjvbZx3zPnh5hW3hYlgyJ3GkBMOAtDFTMCeidFgpwW1r05FZvr8iRB+jJHbre668H5I4cupiROz4y5U4StLcHW6Fz5QQhKnlkT08lacARFZYVd4AG4Hh5NgDYTQKAoKOsWxcOy1JN5sk48smiaWWtmrAs6f451QDIn7GhIXKVqwSo69VGuaN6zilTwsqdYlHvvCnKHaqdzk7/uEZ4eWgIVI+krHrmmSA0jUMeOAGRp0iWVsdR7qRN7kireX5YFhCUOWlY1nveE952Mg1yZ9o0YP16DHIyAwhCNXk4g+OIvhGh3LHJudMCMcGh61DSV7dYDGyErYPL+1UCckdlU0I5dyIUOf7qpYVyJ3FYli24csd0bWqLJsdBrsu2trDDzyeZPT1q5Y6sECoU/CTntEoYyq9gY9cdJzz+qOziBz8oVviiJm+8bN7vsqrv6fLLRCGfr7SPLLFtyLYWiyIsV7MVdgXuvBO46ir1d3w8SSvnDl3ztttE7g9APfYTuZNAuVOQ/se73y0WZb78ZRFGIUMRlgV4z2cKy1KBT45oNxrdvQgmP2nBArHtuwKUaydnqhOubimVKrZC92FS7sh2mpM7qr5Gm1sQvHBbAKJOVONkUxNaoVnoAYJdKYFKki1GWJa12kzGIYeICTQU5E4UJJsWIv3zebXNk0HvynWD591hB+CJJ/zNEeht+r0xIiyrArINlH1NW3KHyqpq1xK5Q+pZAHrlDmC3Fbqcc8cbV5XXk3HDDf4icTMQqMsGB0UYNa9LVZufN09MsCnnpYncmTbND09VLjbHVe4UCiJUWhqnKsgcg3LHR1LlDg9D8q7X39gI3HsvNkth6ECysKwmKMhkQNSJp6hR+kRUfh7OFAWa58QgdwBPPQ5Uzgn4b3k+xNHXF2wqwG2yityh35lyx4iM3EmCjg5B7qxf7xvfULytidQAROOlBmxD7rCwrDIPyYkDbphtyR3eMZqaKtlYDhW5k0S5w1ZTQ+bIEJblqO4jD0oRBEQjNBM6uq9tWBZh6tRwzh0duSO3Fe9dhzomU+4AGnKHfvf2qg05N3pUF9/6lkg2yxFHuaMjXKoBa1tFMCc6ZlhWRU1//OPhne/SCMsC/Al36C3Su5DDGS66SCSRkydVMcOymhEmd+i3KxOaOshODbWXBGFZctkAQe7YrFA5pZLIP4WEOXcSkNxGxFXuxAnLUjnY3d3i84YGu7AsAINeuWiCW7as6xBmzAhyd6je5Zw56pBiFWTljqrvnXWW3bVUkGy929hYmVg8bQVXWmFZnHjnodj0+ZQplcQXV+6USsE9TPZKVu5E2W2CIqEyoCD2VepIGZzcUR0XV7ljQMEbA0qmSatE7viIQ+6wPuk0NoYJbBsfysbnampCBynvdDZbJnfoty0Zz8mdJDZTVqwBVuROhZq9UIiv3OGf0/PuuKPIUempIio8yYiwrAqkRe5QWVXtWgrLcjgJLpc3Srkjvw9Fzh3tvWVMn+4T4g2AmGTT8bvuatfm+edz54rcLYcdVnlcLieIwksugVMqBW1BXsCjv+MsmDMYc+7ofCRbmyWD+d+Nnr+X9/qral6QJCwLgH5OqcrHqiibNXp6RNiwqb6ZXzvojTVlsis65U5rq55kA8Ihq1HKHfqtIneynDs+srCsJGhvF7LNl1/2J/0h9UjUbkHf/GYg+4wZllXO5ZIxclEMvAryICMnVOZIi9w5/3yRT8jb0WTLjBloOO+8sBMsn6u6j2zEIwiIBkDtrB97rIi/psmQKkROft+UMLEK5U4InZ3hybOKnY8aiOideVveAlAnXuaOw1CHZQGinKtX+/+6uhUBgmrioRo4m5srwxBSQojMoHsBlSvelAfjj38MjmXZ/PPQrNAQvLaRA7A1n0dRJnfkOGYdZLl8e7uI70+g3AGAwVwuFBbpFgp2K1TcMbFQLNERvh1MQnKbwEiDzSbni57fJizLccKrzhxdXcG7MCl32H3KxSKwZYvfTkJEr61d/9//Va+WEuL0Z0VC5RAuvTQ8JsRFS0s4dEkid8q5HHK2ZIYt0grLirKP3/++SJRLu3cB4Zw79Pv11+OFZdlO4BU5dwDFQkcc5Y7OmY6r3DFBsnvG8qjIHb65Q09PEPZkCMtympoAx8FAoYDCwIBarSshZMt1dr2pKXhvtuROXOVONWFZ7JyQdVHlVZIh2zRZ0Wmj3Mnl/NDnkHKHocJSm2y3bVgW/y5t5U5nJ5xSSU/K8/dqQ+4owrK091ZB9humThW5RXfdNVxfNrugFovANdfov6d8Zyrikz+rjXJHgwpyR6cYiVLuxEyo7Hjl9+eCijYdayGGlc/R1b0qHyshCbnznveEQ8RVYONBuVBAfutWf9FJS+60tJiVOwsWCBUZkI5yp6dHzNsycidDLFCDeemlIJkXd9KjJh081p8PGDong02CIkNldEii3JEHmaFQ7uTzoclM//jxaKBJse5cxX1Cq0Y65Q5t3wqP3FHV7dSpwGc+E/yviHfOy+WZNElcy9sRAUB15E5Hh8ivkcshVy4HEkjA3oBLK+xaDGdYFqBVrWnb3rx5Ij/DIYf4HylXmBob1THIKaAskzuyckd2HDRhWQCslDuA925kcsfWEZNXhOKSO9I7KBeLIZVdnLAsQEzSjcod6X2SgjF12alXhlCSRxXihGWNHStyGKhs5vjxIh8KoHZkVcodry5cptyRyx8JnmeEdqLbsCH4LI4zKCt3+Pt+5hn1Dk9xIJUlx8jQHID+pIsdJugmFXI4RBSpFGWbvaT7PtraRC4/+pvOjSJ35ITKSZQ7jPSvCMsaP16fH5BAY7Yuv1KKyh0lIaorj4rc4X2mpSWo9yhyBx65OjCQnnJHJtpVoHdfT+SOTViWtJtjBbljO3mnvHRkB+fODUhzCYOFAvIm/1tuM45T2Q5lcmfsWFEHaSh3PF8u1O9NOXdU/d4i504IUe1EbqdTp4qcRvPnhyf6tvMGG6j6Bh+LqiF3uG/ghWWF/iekEZbFbbxslxT1lSQsK3RNGarFZlXZbHHoodHHML92sFBAcetW/cYnUliWDxW5QzAp12zJncmTt3lyJwvLSgJqQC+/XJlzJ+5qFE8UTI5RVFhWEtiGbHDIYVmmnDt0bLU5d4Doya58fxvlDh9cHSecVBSecbQxuF79c2PaIBsQvnUroVrlDrxdsoAwucMTKptgu7MVD8uqA3LHd6J1IWClEvCNb4TZfvk9NjUJx6GGyh1lWBaFXMmOgyYsCzCs0ABAPg/Xc1wHuXNMv22VOzIJRPbM9j3Kyh25ndiSO953BdiFZRGaAD/3TKrg96k25w4dQyvcKgf7W98Crr9e/G0ZlkV9n8gdcqrKuZz9pF6G/N6rIXeSjDMmSGVp9HabLHv9IPF4aII3IQAQ7qtsUjVoU9c29pF/x7f0lc+No9xJIyyLt/93vAO4917zJJHuORTkTrXKHfm529tDz+9DQe74K9Q2bdumL/BniFLukK8YNyxLTmQcFymGZSUmd4DgeZubtaRxxVgkQ/ZJW1srF2Nlcufd7xY5uqLaq6ld8k1IAHtyx2YrdPmZ4yp35P5xzDEigXlzczLFvw10z8/9VL4RSkzlDr+2q7tXmjl3OBnFE2tL8EsWV7kzVGFZNjj0UDEmbLedrxzW5tzhfrupze+8c/C3bJ85yAbwDQf489H9yD5l5E6GWFAx69T54pI7nHigWEONciePIVbu0PZ5QLRyZ/x44C1vAQ4+OPgsiXJHLp/KCMrnKgyfVrnT1ib+bmsLOUfW5I6KKZefk5IUy8+hMtAGcsctFsWg4zkbviHVJVSOKndTU7rKnRrn3AFQqdyxuZfcvlUEWIrKndDW3/zajgN87WtiK18Ok3LH1Dcdx59UugpyJ1HOHbI/bW32q7qyckeO+bcNyzIN9rrjINpmzcmdtHLumMidadOCSYqK3Jk0SbRZdh9KIkv5Rsqc3EkKSvZME+I4zqApLCuNXDgaIp9InZqQO+w+KuVOCfBJViNsnGuu9OWhLly5E3UNWbljWyemhMqyumXRIvO1aJvjSy9Vf6/yBYYiLKu9PZykXkXukP2TkcsF9lgid2zCsqwmxnHInYTKnZrk3LEIy8pRX83lxDjAc+7YJlQGKskdoCI0iyCPRRWQ61i3qyGVp7VVtKWlS83X5eVUtUt6h/TuTGONZULlEoAyUEHmVqjKotqJXJZ3vStYdEibrCfofB7u53FVVQxbUZafRzcmpRGWZVLumOrLZq7B60X3/N5CRwHemCTbbSBVXxeAyNn3ne8AxWLgf+hyY9qSOzytQi4X1KH8DuIod4CM3DHBcZxGx3H+5jjOg47j/NtxnE8ORcHqGtwQyModm0FfBq0U0MqdboKLlJQ7tuROLhd0Fq7cUQ2IhQLws5+FtyU0GCSbLZ8BTYiNTc4deQLrbcXpO3KtrZW7/iRU7vjvnFbWSLkjG7OYyp0tJ5wgQv+kCU1oJSIOO69zYjmGcyt0oLJ8UQmVFahoMzK5wxOVpoCKPsnfxdlnA7vsoi4P/W0blgVpUpsWudPebj9RACqOrSB3bEOF2HdxlDsV90gLcckdm5w7Y8eG7agOqonOu98N/OtfofbR7I09jbQ7lVf3g9W0Z7KHSRMwst/WeZ9soSHyh5PcsSYXbWyW4wTPyCeQCZQ7Ben/SGhy7mhDlE0YP16Eyai2XKfry0hK7sQNy5JJFnk3NJP9k+5FE0ejwpLfS/U3hw25I4dlxVTupB6WNW9esDuSAaR2ylEdJkmozL/jz0tkooRIO6hS7sigHQV13+tgE5Zlo9xpaQn6cETOHZWPFiuhMmBupzZ5X5JA5/O0talJnVood3gZSNHPUa1yx1TmtJQ7CMaiijHJVtVfBXyyu9qwLECkK6E5sC6XKLVlUlvKx5CN2GknsYHJUUfFfKLRAxsvYAuA/V3X3RnAAgCHOo6zuKalqnfMnh38Xa1yBxADiePow7KYsRpS5Q4QlsKalDsq6OqCK4JUsFXuGCSbOVm54zjBJIaUO2zb3EbAzvHxmPI8+z+00v6ud4kkzHLZk4RllUqh78lxCQ1WtgmVAbtJfD0kVGaoCMuyaXtym5HrKOXBrqJPRl0/qXIHgexcpdyxDiuSY7lnzgzvVhAFUmlQaIx8L/6/RVgWALOzo6iTmit3TO8hTs6djg7hsPCQGxVU5E5TU+V7kSabflhWNSQHkb5JyJ0FC4BbbglyXo02ckcTlmXV/mzrk74/+ujgM9lWmex7UuUOb3MtLeGEymnXq1z+QiG5sitmWJZWuVMsip/eXn3Sb6m/tXgLOK1R+VcgTYbTCMsiYmDBAuEr2uaz4uROlWFZ63t6gIcesiOWZBJODg+Lq9zh9lZD7kQqd/h9cjm9P1ENuWNS7tiQO44T1G9Ezh2lgrDanDsccRMq20I3TtAiA9nXJOkuZL/CJiyroaHST4ybc0cqq5EMi0nu5AzPT2NgRahwrcKyGNw4yp0oJeNDD4kNBoBocken3KF+29cHfOlL1ef8G8GItPSu67oA1nv/Fr2fykxm2xK6u4VK49VX01PutLaKBtnZWemccXIn6aQmaexsRwewYoXoQJTAzpbc0dVF1IAZNdnlEtc1a+yUO3ReW5tIWl0sil3LFi4EzjlHfG/p0JZzOeQGB8UuQY4TPGdzM/Dtb/vHOfIkNwm5w+9L5E7SuNrPfjacTFUF5jj0RzlKtQjL6u0VZRgYAIDAMU8jLCvOoB0DFRMh29h8+jvGhNif1KrIHe/c/nweRdukkg0NwJVXAoOD5jJzHHAAcOWVWPvtb6Pz0UeVYVk+bMOybEkgDzXLteLBqCSaPl044PI21hxNTSKUZeFC4L3vNW8jDdglT+THSbtlVVUf7e3hrWfj9GfHCas1bNVPtiC7ls+LNjpU5I4qHCCOqhGwt1ktLeJ98qSSdH0b5Y7X12Pn3MnlxPNt2RJKNFwEkik8TKD6LJVEEvFqbLDNhI/U1Z2dcHiycE7u0O+vfS1IbC5DIijy3jmmlXQfNj6XTUJlmRhYuBD473+j7+/B5aRKlcqdWP6nTO7I40LSnDsAcPzxwNatWHfppWhju2vGInfGjNH3TZokxpkYm/yLXC6881aUj9vRIRKpR+TcUZHMtCC2pVRCwxlnqLcl5zCVJemicBR015XV5Skod2KROxs2CB/0+edj75ZV0d5NNiJmQmXH8Pzkf1a0hSEgd7TKHTnKo7UVzpYtwYkq38BmF2BK7j9mjPqYWbOA3/8e2G+/BE8zumBlqR3HyTuO8y8ALwO4zXXdvyqOOctxnAccx3lgNTO2oxbECFabUBkQE+7OTiEj+8MfKr9nA3Lk4KVD0thZWi1paoqv1NDF2UcZm6jJLp1PA7DCiFYod4BAubL//sCyZeFksvJ9DagwpjpjXqVyR2b+fXInqXLn+OOBffYxHzPcYVkXXwz8+c/B/2mSO4WC+K6elTtRYVmc4NMk8ItMKik7Nbp8UKbzL7wQg1Kogg9+/zSUOyzXEGFYw7IWLRI7YM2Zoz/GcYC//hU48USRgyuq3fIdVEzvohbKnYsvFsRvCso2sk1lIB2CQA5JkcidmrQDQK3ciRuWFUe5Q2pWOVGt5TXKjhNfuQOI52tuFve2JWWTgOqRxuykIVmA3eSptRX4+c9F4k+dcod+T5sWVmOb7kW208JehsZvnT2JE5bFN9+IgxRz7tSM3Imbc6exEXjnOyv84Vg5d3bYQb+y39MTjI22iJoDXH01cO654u+osYb87oiwLKUd8tr7YKEgtiXnqRJUMJUln8egRx5bEZq20N1z3LjwAmQScke+ti25Q4ohIoarVe6Y6sumXTG7ZVTuUB5GnR9aS+UOkTtUVnnTnThhWRy6ec0pp4hQ9c5O/TEHH5zOwtIIh9UI7rruIIAFjuN0AviF4zg7ua77iHTMtQCuBYCFCxeOfmXPtGnAAw9UKnaSGMCPflQ4ITp5sDe5yZfLwxuWRfeuJiyruzva2PABOorceeIJ5X0c1YrY174mDPeuu6rvZenQVsS4akLyHHnSXi5XXkx26AzElpLcSduA8zqIamszZ4rQtvnz07k3INrHwoXB/1Q/Rx4JfOITdrH+urAsIJhIpYjY5E4+H4QK8qSdQCrKnci8AylJrX1iIQ3lTsRgTPbPv8dwJlQG9LsCVYPGRqC/Pxm5U81knAjfa66JzocWAXLyBvN55GySDkeBT2xXr073uU1QTSq8e+VQA+UOPee//y1W7OVr2JA7pKyN0zfYFuhDQu6MGSO2V661cgcA3vxmABLJUioFSVZtyqBbjY+h3BnI51HQ9YU4YVmqpK82KBRSy7ljtUscwUTuyAmVbXLuKMJgZVI7lnLnllv07XzWrCApqy2i2uWppwZ/R401prAs9j42RZE7NojwPwbzeeQHBoZGuXPFFUI9Q6hCuVMGkDNtO69S7jQ3x0tEbEioXDTZfRvyIZfDVoj3bFLu+D7hMCh3/N076Xn6+oRfS7vXtreLedqMGcB//hOcmJTcKZWCkMwaKfFHC2KN4K7rvu44zp8AHArgkYjDRzemTRO/X31V/K5GuTNjhvgxoDxc5A5X7syZI1Y6dKtcMuS6KJXCuR10cBzhEA0Omgc+mmCpyB1uuGmQO+CAymux+nRihGXx39qQPHlQUTl4ccgd2ZAC6eeRYXUQ2db6+oCnnkrnvlIZyo6DnOsGddDTA3z843bn65Q79Pdwh2XRMdQeEiRUVip32MTaCNsQoAj4qzayE5kgoXLUZHIwn/dD9YAhCMtK05G1RVMTsG6deQypBblD4AqShCBiNbX3o1FpDkvOHW4bbeqoVBLJ1Hm4lQqc3JHzolk66C5X7sSZgPNFG16XtQrLIvXJUJA7HirIHbq/TRnke9nshEP3ZfZY2zttyJ0TThC/o0I7NQiNT1Xm3NlYK+WOqT5Vyh0PFcqdqEkjlaVYNJOuH/kIcOGF5mvJiDPZrEa5w565rLBDRLBb28aIucFAPo/SwEBVvoL1PXt6wlvRV5FzZzCXE6EpOv/KRO7QBixRmDFDHDd1akBeeGXNm8ps2Q+3wCN3DHVPCw3ajT2GUrkzdapQ1uy0k/i/WASeew5oaoLzkY8EJ9qSOzbhmhm5o0RkC3McpxdAv0fsNAE4EMAVNS9ZvWPPPcVvMsLVKHcsMJjLiWRHw6ncmTsXeOYZ+3OpLjo6gLVrxf+WO/MMErmjKuuSJcA3viEM5C9/aSR3IvOPJFit9I0pXVf37uVBRfXuZKfGk8HmXVcflsWvm/Z2h7yMtVBHWGIgl0NpcDDRJLsikV29KXcA0WZV5E6UcscmLGuolDs0kZcH6rQTKqPScal5WNZwkDs2Y4hm955USI4U+oZrSzDa4pBDgKefDlZz5bCsWil3DDl3+P0j8Y9/RB+z664il4AKXV3ivhHqHzeXQ5HyZsUNyxoK5Q7fWrqhofZhWRwq+2pL7lQTluUdM8Bz3uiuz68tY/Zs4LLLosuqAx/Hq1TubKiG3JFJpkIhUK6afDQDuSP3/0hyx/b90Q6rcRCHiLBR7ugIhqgFOO961sqdiLIMFgrAli3p7pZlq5KtIizLt9E2u2VRuCb/scHOOwOvvSYWre+8U3ymUvlt3hw+zzJsyM8EZtotS6fcoZ3HargduHLBWVby811qCTbkThTBlpE7Rtj0/vEAvu84Th5CkXyz67q31LZYIwDHHgvcdluQuKka5Y4FtHGVtqhWuZOkA1FddHYKcqehAfj6160GTX9yoDq2UADOOw/48Y/F/yrDRxNdjxTTIklYlmXOHcdmAFM8n04GqyR3Jk8WRtyU/yMOePLuWk2cLDDoJVBN5FB4dT2QywkDJydcMyXCTYBQn9xhBzHgR4GTOwkSKpuUO7Gk6SmQO3I7qVVYFkdNFBusrM5wtP0E5I7vyKZR3ne/W+QjqwY0sUjr/eyxh/h529vE/15b9/Oe1Vq5owjLAiyVO7b4whf03515JrDbbpGTUddx4m+FDmiVO6mTp7SrZFNT9erJuL6WalKRlNyJQyzZEJ226pVqUK0iK+mCT5Ryx3Eqc86pYCJ3ZNLfduyrRV2nqdzp6dFPyjnJbFCDW48JFmFZQA23Qje9/yrCsshn0Prhqpw7/McWlKZCs9iGzk6Ro4/D8t209fQAr7xibK9aFWt7O/Db3wKLF1vdKwl8H9BGyRg3505UPxoCZdJIRmQLc133IQC7DEFZRh4OPDD4u8bKnarJnaS7ZdGAmoS0onO6ukT2+cZGkYzUAv5kLqnh984biDKiMdQDBG3OHZnckZ1KlWOkMIoDuZyIkZee3XdceDl7eoA33rAqtxXqRLnjOxQJ+hM5IYP5PAo8ETgA/OpXVYWdqEBOVH8+j+K//213UtKwLJ53SbP15ohR7sQIy8qUO+pjUg3LWrJE/FQBsnmpky6yYkm1c2CaiAjLskqonAa6u8N+hgZu0oTKJ58c7BRVS+UOEDjsTU3VLYIlJHcGHQd5qpuWlurIHZvJjHes0R4PAbkT6iNVkjux7K60s5+jsveNjdG21pRzJ2lYVi389DSVO5dcIvqmCpxkNviUqeXc8a4zUsgdSOSOdc6dt71N5HXbc0/g6KPt76crK12/o6OS3LGca5RaWwW5YwrLMm0ucOihVvdJCl+xY/E8FfMhE6ZMic55NXmysE061es2juFbmh9tqLVyhydSTYI0dsuKC07uALEGVH9yn9TwM+WOEQly7tCA6kaQOxWDCr07xwm2ldcodwDFblkqCWTaqCflDpDM4SViL5dDw49/DGy/ffBdLUgB75qRKjGOhGFZ/kBuCMuKtWNICslzK9pJDcKy5NXvWpM7xq3Qa4XhVu6kgbTDsggyuWNyaNOAamyppbKlSpST5tyh3XuA2ivXTjlFkIf33jssYVkDuRz8t/b5z9uFK6SwW1ZdKXeqyLkDpLhbFl3TRrkzcaJYZFS8r9hhWfVC7kSN+RMnih8Vot5H3FDdCKKJrjMku2XJqCIsSzmHMJE7J50U/M839bCFzlZ0dlYea+tfSASpCq682DyEyHsEecFGPRNHufPJTwKXXmo+Zp99RHL+WmxuMQpQJx7hKMAQKXcST06ThmUddRSwfLlgUuOCYqoTkDtlDcERgoVyx7SFoF9GgqXBrQgJ0JSjYqWKnqW5Gdi0SeyeZSJ3dMqdWqoKaplUMwaoDnIJHF6eyBKHH55quVTw20OcwZWHhqWs3Imc6NP9CoWq3rFPLOjaKZBaQuWhVu4MS0LlBOQO1VvdkA1DpNyhNlbTnDuFQriNJp3kDgWSKnc4am37v/518XvjRv3E1QZJlTv8mQ47zO7cKsKycqTcqSdyp1rlTpphWYAdufPOdwolheI4Y0iwChaT5cTo7Q3vFGRCnImuDPYOlD5HymFZ7X19wOrV5gTBcTEEyh1lzh1eJ9QGHCcdpaIpLEtTxkhYkMk1X+gwYKynrum1sOexlDuNjdE21nEyYseAjNxJC6M1587UqcAXv5jsnhRT3dYWxNxbYtCGyDA5Wp5RbKPdOXRIsFppG5ZVMYBzx6JcFgSPIcbZKudO2qhWwp0Sqonz9kmOIZqAJSJ3vv/94O+kCZVpJdP7XfJivwtRWy87TrAlcDXQKXdsV4rrOKHysJE79G5Mx7Df2tC4YcJQhWX5fa5W5M473ynyZ3HkcmJ7XaSccycFlHO5IGlvUrtX67AswjveUd35CcmdgST1opuwxQjLajRtIJFS/jMj6jXnDn0XZWuLRW3ohdz/i5T/xLZMaWLKFODRR0VevyhUQ+4A/qYbKrLNepGHEOF/NFCd1iosy/T8vb2CHIljj2hMpJw7rP8XuN3mfTkNe64jgNvagM5OlJuakHvppVAZI2Gj3Kl1/jkDfDVXjN0DAVTve2aIRJ0tP41g1Fq5U+3uIOR0A0M7aR8zRuQNaGhIPyxr/HjhbEyaVPkdnRflOFSh3IkKywoRExSWlcsFOzFodonwByXJYNJErqYTz3pT7iTJuVOr0BAN/LwncROZUs6HGLleXL4atWCB2C3Oy8lBTpjNKgoaG6t21vxkenK/sVXkxHBwtwlyp6kpIHh0kJy9mitY4oL6Xq12WxqqnDvbb68kISiB6XA40ia4jhOEHNU7uVMt4u4QWc14UIVyh8bvjt5e/UG0i2Za6gEV0lTuxDlfqitH1b6qzL8kjz1jVb4gB/lgNfLTMWeOXf+rktzxF3sV9yp6/cOxrdeostBYWKvdskxj7QUXAPffH+vSfkJlaQ5RkaIhbRWXjghubAT+7//Q/973BsfavnOqmzpV7sRqGxm5M6So4xF8hKG7W2wVLm8DlxLSSqhcLhSQG8pVx1tvFdK5730vlhG1CsuaMgV44QW1DNbWcFeRc8d38G13y3KcgNgplwHaulaCLoGda0tYVYM6ySth9f41sMp1kCaSKHc4cjl/JS6S5OCEiuOEE/957cKqzhoaqh5gSRXXKqvjbNVfccKyZPn9aCR3bKTIsq2x3SFtqDBawrI0KOdywOBg3YVlhcqTRlhWvbQnFd70JuCb3wTmzbM7fpjIHWsfpKkJGBhIPdG/j3rJuaOy90uWVDUOyeNAZF4Y8sFqRe7YokpyxzXYoRYvDcIE211Bo5TD1H7THBNt1cptbWJeFQdSziEtuZPPCyIureeaMwc44giRkBkI9/8ZM+BwBV/csKw6Ve7EaRu+gspxwgqqDDVBHY/gIwylkpBk1ghpKXcK1WxBmgQkbbeZuDDoQpMqoMuUnkS5YxuWJU/mKQxGCocJTRB5guAockdDbEycPh0AMDZJ/iNb1Mnq7Ugid3zlThX3G8jlkB8cjFbu8Jw7MuKQfymQO+09PQCAMTK5SvUBIGeaDFQRllUTMiOXQ9lxkHPd4SN3otp7nZAcOlCOrNQdTWlVtObKHQ38rYfrjdzhznIKyp2aJFROC83N4UTQUdBN7mzQ1RUmA+Ks9tva46amYMeyWqBOwrIcFel/5ZXxy8NQ0f9t7HYKqtWqUa1yx+vvSrKN8k3GTDhe8bf8Wa2UO2mrOOSE0qb+T/54GmhtBf7f/wtfm/1OFJZkkXPHuFtWrREnTJW9hzoeXUYNsjoeIXCrVe4MherDhJjkTjWTewD2Roc7tEnDsiZNAm68sSJJozLWtwpyh+S2SUKVrJHUkUsZpF6qJixrqFYyEuXckTCQy6EhBrmjdA7iTDxSIHe0NsUr40AuB+PTxHDwKuxejd7tgOOgNFzkzjvfGb0VuUa5Uy/kTs3Cst7yFmDzZj8Rr98ehvi53ToOy/Ix2pU7cRFH0Sjj7LOB/fYL54jhvy3ua0Xu1HAle9i2QrfJuVMl/NBgx4HjuvbkzmhQ7kBD7sQNN4oqSw2VO4MA8mnbUlm5I+XgCSFNckd1bfY75FPUQLkzrGFZNm2DdjGrs4WR0YpRNIKPbqSl3Bk2cuecc4AZM6wPp5XZxOROLXPuqAbWE0+sOC4kQ6QPOblTLiuv39LZCbz4YmXZh+Id1slW6C2dncDzzydSmvnKnaEqf5KcOxL8ZJ9RJIeJ3ImzwpYGuaNzPGzrI4azPyQ5d+A5HuXy8JA7S5eKHxMOPhj4yEeAnXYS/9Pkpk4m4zUjVvv6gAsv9P8dLsXSoGlSNYwIlWe0K3fiwusjPRMmxD+3owPYfffg/zjJnG0n2Y2NgOvGL5sthmu3rIYG4LrrgAMOAKDJuVMl/PwqjY0obNpkN/a1tVWorIccSTc48WDKuRPbT8znBcmiO6cWyh228Jn2SO5K5I5x17pakjsmctO2H9rslpWCcjwx4hCJGbkzpBhFI/joRrnalUqayA0XuXPxxbEOHztlCvDkk0Gm/rioZc4dW6ZcZcwsyJ0x48cD//738JA7CeqjFuiZMAF48MFE5B4N5kO9W1Y1Ez6/jVQTlhVnha2xsXoHO0K5Mxi1Gh0noXLcLW8Tgt7DsJA7NujsBD79af9fysOlbA/DAMp5UescQMZ+UMv7UjjEaFTuJFjoGBGgMJU0JnFHHQV85SvAzJnW97VS7mh8gTTgVKvIqkbN+853BuWIkWPNGt41B4jcsbHb3/++2IVpOJFSWJZyQp/ATxzI5ZAvl4cu504tJ/oS2aHNuQMMrXLH+93vOCjaKvVihGUNywYomXKnbpGROyMEVYdlOY7oXPU6aZHQTNs8J3UyEyh3bMOy/Jw7NSJ3tGUfYnJnOHfLquZZffXAEE1Q0si5468qRSl36Ps0lDu1IndMMmjFcRV/KzAkCZXB+upImdzqdiwbJhQ9pV0qE2kDfHJvOBIqY5Qqd+qE2E8daY6bnZ1iBx8bxE2oXCukmXOnmnZRbXiYAr5yp6kJeO01u3e8eHEq964KtQzLStDey55itepwb1sw5U7qoAUPidwZ9rAsW7/IcA0V6iKhcqbcqTtk5M4Iga8OqMaZpe23RwKqVRrVMueOrYNPk37O0k+bJkIMnn9ef95wkjt1klC5mmcl5c54290iqkUKYVmN7e3A+vXV5dyJU2cXXFC9g12tcidGW5PtXq2VOyOO3KmTMBoi5adst11N7zOsu2UBoz6h8mjMuTPkvk+9JFROM+dONe2+BsodIrUH5YTX9Q4qN4B8gnxLrimxewIypqG9HVizRv1eatF/vGslVuabQP4YpXYg5c5Qh2V1dABnnAEceKAoRxJyw2LBLpW5YVJkyp26xSgawUc3qg7LAkQHHCmDX7UDSg13yyJnJ1FY1s9+JlRUDzwA9Perz6MyyxPMTLkT69ymWjgOCqSh3Gnr7gZWrowmd0z1EsepU+SIio0IcidN5c5QJVQeaeQOEZi0k96ww2sLtd6V0Uhy1hDlbSQsy3ahY0Sg3smdffYB1q6tXTmqHdPTUIUByNWC3OHKHWDELV4mzTlDY2taYVk5WvhVEU21UO54z9/gbRKSKmjBg3LuUA7GoVbu5HLA9df7//okUxwyr7FRPI+h3w1rWFam3KlbZOTOCEEqGdFLpZEz+FXrkBUKYqCKo9yxvFc5LrnDj6Py7LVX5HnDrdwZVjVANcqtoc4vlULOHS2hJ6HRSwTphy2qrjFUzx0RlhU5iMdw9uUQu0y5I0BhUMr2MBwYojY4bDl3tpWwrEy5Uz1sJz6f+ERty5Fizp2q/M9aKMMo1GWkkjuOgyTUQqoJlak8Oltai/6Ty4l2VYv3RWFYtOOq1/+URNgnPwnUeCHCRxJy4/TTIzeiGdawrATKnaHKhbmtYxSN4KMbqWz9ui2RO45j97xDnVDZBnWSc2dY8y6koNwZqraehnLHtsyTvXCXXm9LaOU1hkqdp0m06Ngqd2IkcB0q5U55hJE7wzZx1cGUEypF+FsgZzl3AKQflpUpd0bwfWWkmXOninZf092yiNwZKcr0KlUMvv1Ji9wx+cq1qttSqTbjhKTcMSZUPvzw9O+vA7XVOO983jzxY4C/wDEchHx7u/hto5JXLXZnqBkycmeEoJzGSuW2RO4AwFvf6m/DqUWSnDvVJFS2ge7Za7FrgQxe1pFK7gzRBJNATutQKHcc03FD0T44dGSS7QpNLhdswRr1rlhfypfLtVPuWCa2rhsMcVuPxBArd4YtLKvOlC1ke8oAcglyeACon5DctDGcyp1cbuiUARqE/Jok79VxRLtClcqdasuhAIWlto8fLz4YKf4tC8tKAiPJnCSMyjQ3eNvbgClT0re1NdrghXwk10a5M5QgvyipfdYglaiOpFi2DPjVr4Bdd40+1pT7KEPqqC8PJYMWvhHfVsKy0pi0fOc70cdUQe5ErmLVSrlTy9Upx8Gg4yDvuiM2ofKQK3fSkMUWi6Jv24YyqdpqXx9w+eXAm9+cvBxxUG3OHcC6rU2bPRv44x8xUCohv3lzzdrmSAvLqht1AGGUkzvGFfPhBJFO1UwcRqtyJ58PlLxDfd9f/hLYffehva+qHKq/Y6DsOMi5bt3l3Gnp7AQANC5eDHR3A/vum8p1a458HoMQYVlJYNw9l8jEOKSiKSxr6lQRHpQ2ajUfIRJFSqg87OFANco5M6zkTj4PHHWU3bFZzp0hRUbujBCksjvIUUcBtMJR7xiqScsQJFSOPajont1zZFDj/BplmnCPVOXOUE9401Lu2JTX9GyOA1x2WfIyxMV224mf7bcPFyPGID7gOCi5buQkvcmT/w6WSsDmzVnOHUK9KXeGqjzDpdwxTaqGEb5yx3ESJWgFMHrJHdsQ7VrgyCOH/p4yqs25A09tUKVPULWCSAW6ZmsrcPXV6VxziOAWCmimsJa455rsUF8f8ItfRKvWOYajf5gIpWqvi8oFgGFX7iQJy4px3aHOPxcbwxk+tg0iq+URglRy7nzuc+kUZigwVBP0BKtasXPuxB1UdKE3Bx0E3HsvMGdOvOvFxKDjoAiMXOXOUE94pZWiRLCNP6+nyfy4ccBTT1V+HoPUHMzlgHLZOixrgNpDjdqmT9CNFAdkG1XuFL1dVkq12G3FALded8uiyV41yp3RmlAZECoGyh2yraHardCR0i5xNLkFkE9rgmsZzlyPKDQ2orWrK9G5xq3QAeCYY+JdcDjInRrdk+q0fcwY8YHXNrr6+lK/VyzUKKHwsCp34sB7/skRCaIzpINRNoKPXqRC7owkNDfb7XZVLRKsalkb0xjhKSHMny+k3PL1cznzLlspgRy5YXXwd9pJJJLLlDuVx/HfdYg4OYj8bUGj2hoRpbUmd+qJPLNBvZV3iNrn9FmzAAy9o1ivYVk02asqnwMnd+qlPaWFm24CZs8e7lIMD1Ikd6pq9969B6tRl8kY6p0x00QVyhXrHVuHoCyJUSNyh1S+U7zNJ+i5xk6alPq9YqFWYVnUv+t9bug9f4O342uG2qK+PJQMWpSHSYY+bHj724W0tNarbV6OGQDxyR3LCWnsd3bSScDf/hbvnBThO3LDuRJw/PHAQw8lcyaHKedOVY6WraNTb5N5BeKEZdUbueOTBXVcvyHUG9k3RO2T8ig4Q/zc9R6WVZVyh42Fo065c9BBInfINojQrpdJd2dKwyegxa40E8qOgPFQiyoIFb+/p6mAGuo6rHFYVsXv4R4jky72Wl633sakCozkvjoCMcpG8FGMkSK9Swu9vcDRRw/JreImEI4bljVt5syqyjfU8B38kWqECwXgxBOBffYZkttRPVUV07399sDLL0cfNxIGSIp5t8m5k8thAEAhyuGnnRZoJ4wa2cFGWlWq5/rlqLf20NMDnHMOcPDBtb3PMD13Khsb1AIUNlPlxIF2rxuxtj9DBYioG3Qc5BMSK+U02j0rR2qoN/sXB9WQO2mHh15wAbBhQzrXssUBBwATJ6Z/XR2pM9xtpEZbgY+YqI6R3FdHIOq8NWQgjJgOPAIRW6lCx1mSO0OdF6Ja1IVypxo4DnDjjUN2OzeNlZOPfET8RKHelBoKxCG7yo6DAceJHogo5w6FadbKDo40B2TePOAd7wD23nu4SyKQywFXXVX7+wzTe6p75U6V16HEuRm5M4rAFDNJW22qOXfSJHdGwHioRRVhSamTzIcdls514uBrX6vNdXXKneG2aTVKqOz7n8P9fFGol/ewjSBjCkYIhmvr120BicOyLMmdkfbOyiMtqexww5bsSwMLFwpVRI2TalcDn9yxVe7YOPtyWFat+tRI67NNTcB3vjPcpRh6DLdyp95y7qQRloVgLMyNlPafIRreuFSu4hKp5NypRVjKSLPXHCnk3Kk3O1QXqFdyJ4aiORbIT6+zBYcK5HLiZ7jfwzaCbPY2QjBikmaNQMQmd2yVGiOUkKuLhMojCJT3Y0i22pw8Gfj972t/n2pATryNcieXs1vJbWwEAAwOhXKHnJAM9YthJnci860NNSihcpXttpzLAYODmXJnFMFJQTGTipqXJVRODbNmiTHRS7A+opBGzp16n9APB+qc3EldZTaS5obDkbh7G0XmwY4UZGFZNUNccsdaqeE44pojzJiN+LCsocZISWg3RHBirFD1Tpjg725hxNFHA9/4BtaPGyf+ryW5M8L66zaJ4Vbu1FlfT125MxLDXDKoQcqdKoi/uk2oPHUqsHw5MG1aetccKrS0iJ8EqFc7VBeQx4Z6WWT1yrFdyqprf7F5JMwNM/9qyDACWkMGIAvLqiXikhmx8h+NQGNGTmC2emuJjNwJIY6Sqbm9HVi/PvqiXV3AeefBvesu8X9G7mzbGKYkmfUaDkGTvWonzhmxP/rgh8lWo9xJMaFyquTOSMa11ybeDTb13bJGE4gwo80RHEck+u/tHb4yAUEOzubmdK87kpQ7hx4K7LnncJdim8AIaA0ZAIysDjzCEDfHTKytr0fgZDFz8GNiJK2cDAF85Y5N+ykU4tm0Wis2WlsTr6ZmGEIsXQpcdhmwaNGQ3rZew7Iy5U4GHZwUSJVUEypnhITAzjsnPtWN6bNuUxg7FvjDH4AlS4LP/vEPQfAMJ/J5QTSl7buMpLnhT3863CXYZjACWkMGYARlRB+BiB2WFceYTp4MTJqUrGDDBD/nTtbW7JApd8KIkzgzJvlZ810DL7oIOO642lw7Q3pobgYuv3zIb1u34RA0+U5JuZMlVB5FSCHXTZphWanm3NlGkSl3InDQQeH/J08ennLIiLuYZYEsqiODChm5M0Iwc/vtAQBTpk8f5pKMPpRrSe78/e8jzuj6YVkjYSWgHkBKlay+AASr/jVR7njH1ox4nDhR/GTIoEC9kju+mrRacicLyR11oHG8mrbht4sUEiqnulvWNop6tUMZIlADJX/v+PGh3xkyABm5M2LQ2tEBACh4u8ZkSA9x48l9R9pmUpowpno4kW2FHg+xwpC2Afg5HmoQtlhz5U6GDAbU7aSKlDtVTpxjq1gz1D9SCMuq24TK2yj8cbDe7FAGMzJyJ8MQIRvBRwrqZTu/UYikW6GP1oE12wo9JkZ5e4iNOGFqXV3Axo3Wlx7rhTj20K5ZGTIMIep1UpVWQuVUJvEZ6gpOnDBZDVJNqJwpd6pGthX6CMW4ceInTWRzwwwKZLO3kYKRlDRrhCG2UmWUK1vcjNyJhbauLgBAa2fn8BakTlD0doPo7uuLPvjKK4GtW62vPd6Lne8Y7uSIGbZJ1G0i07QSKtfr82VIjjrLuZMpd6pH3SoIM5hx330iX1yayOaGGRTIWsNIQdaBa4aaJlQegcjyLsRDp0c0zN5hh2EuSX2Acu5sN2dO9MFxpcSjvO9lqG/Uu3Kn2rCs2PnnMtQ9/BxodbIVerZbVvWoVzuUIQLd3elfM/OJMiiQWdmRAtqaNNuiNHXEXpUa5WE4qThy2xJqneR3pKGWzkbmyGQYRtTtinlKyp3M9o9CpJDIOBXlTpZQOTXUrR3KMPTIwrIyKJBZ2ZGCQw4BrrgC2HHH4S7JqMNg3IFylE8wM+VOTGSDaxgZuZNhlKJeE3q7aZE7mXJn1MFJIRwqTeVOtW00Qx2Hh2YYesyfDxx8sPidIYOHzDKMFLS1AR/84HCXYlSi7DgYBJC3XFGqVwc/LWQ5d2IiIxzCqGV9tLWJ362t6V87Q4YI1O2KOe2WlSl3MkhIg9xJU7mThWVVD3/H1qyfZujpAX7/++EuRYY6Q2ZlM2zzKOdyGIhzwiifzNMEJiN3LEGEQ3v78JajXtDQIHbBqsXWnAcdBNx6K7D99ulfO0OGKNRprgt/spfl3MkggRS4w75bluNgoMpyZPBAdZjVZYYMGRTIRvAM2zzKjhNrVWvy9Omh36MNflhWlt/JDhMnAvffD+y223CXpD6QzwNPPgl0dKR/7UIBOPTQ9K+bIYMF6jYcIm3lTr09X4bkIOKvGuVOSoqujNxJB6NdPZ4hQ4bqkFmGDNs84ip3OsaMARDskjTa4Ct36mx1uq6xePFwl6C+4PWRDBlGFepduZOFZWWQkEtBuZNWqHbZcbKcOymgbsNDM2TIUBfIKPQM2zwGc7lgO3QbjPKwrCyhcoYMGTJUolyn5I6v3EkhLGuQXS/DyEcqOXfSIhMKBX9xLENyZOROhgwZTMjInQzbPCZOmYJSc7P9CaOc3CHHIZeROxkyZMgQoF6J7xS3Qo+Vfy5D3aNucu4AaG5rw8y5c6u6Rgb47yHLi5ghQwYVMnInwzaPcRMnojnO7juzZwNz54rfoxCZND9DhgwZFKhT5Q6FZVWbz6ScywnlToZRAyeFLchTyzVVKIzaRbGhRLZbVoYMGUzIrGyGDHEdjokTgUcfrV15hhm+cidLqJwhQ4YMPtw6XTF3aPKdgnInVohyhvpHCjup+Tl3UgjLqjdidCQiC8vKkCGDCfXloWTIMBzo7KzNzj4jFNlW6BkyZMhQCX/FvM5so5tSWFbv2LHIvfhiGkXKUC/w2uxgNeROWmTChz8M7LhjddfIULckc4YMGeoDmWXIkOFTnwLWrh3uUtQNsoTKGTJkyKAATarqbcWcyJ0qw7Kmz5oFPPVUGiXKUC9IMyyr2nZ/3nnVnZ9BoE7DQzNkyFAfyMidDBl6esRPBgDBqlCWUDlDhgwZAvg5LupsxTytrdCznCijECnkY8rUvHUGskOZj5YhQwYFMkudIUOGEPz4+syRy5AhQ4YA9RoOkZJyB3vsAWzalEKBMtQNUsi5k22yUF/wybbsfWTIkEGBbLesDBkyhFCvq9MZMmTIMKyoVwWDR8hXTe6cfTbwk5+kUKAMdQOvrWbKnVGELCwrQ4YMBmTkToYMGUIoNDaKPzLHIUOGDBkC0OS23ia5KagzMoxSpBGylyl36grZAlyGDBlMyDyBDBkyhLBg4ULxR+bIZciQIYOPulUwpLRbVoZRiHraCj1DOsjInQwZMhiQkTsZ/n979xZqaVnGAfz/4B5HHU+JJjkjzTRpOSbOlIVlVKTQkewmKOhABUFlaQhR3XTbRUQFFkh2IilChSSolAoiCM08kOMUSsepKSekki6qsaeL9U3tmdmzD+Psvdbn/v1gsb/1rvXt/QzMs/fLf73f+8EhNm7aNJk8+BQY4H+esWVLkuTsc8+dciWH+t8n+cIdDjf8HT8el2X5wGc22HMHWIzYFzjUu96VXHTRtKsAmCnP3L49SXL6WWdNuZLDHK89d3jqqcqBPMmVO7O6Ym29mtWN3YGZ4DcDcKht2yYPAP5vx47k2c9Ozjtv2pUc6njdLYunpCeSJ3UJT9vAd6ZsOuOMJMmpZ5453UKAmSTcAQBYys6dycMPT7uKI9lQmUXMbdyYSy699JjPt3Jntuy45JIk/79MFGA+MwEAgLE6GOrYc4cFnLB1a06/+OJjPt+eO7Oldu5MXvjCZOvWaZcCzCAxPADAWB2P213z1PXAA0/usiwrd2bLhRcmd9897SqAGbXkyp2qOr+qflhVe6pqd1VduxaFAQCwBHvusJiNG5/cqhvhDsBoLOc39YEk13f3vVV1WpKfVdWd3f3QKtcGAMBi7LnDKrJyB2A8lpwJdPe+7r53OH48yZ4km1e7MAAAlmDlDquo3XobYDRWNBOoqq1JdiW5a1WqAQBg+WyozGqyoTLAaCw73KmqU5PcmuS67v77Aq+/p6ruqap79u/ffzxrBABgIS7LYhW5LAtgPJY1E6iqDZkEOzd3920Lvae7b+zuy7r7snPOOed41ggAwEIOhjrCHVbBSZs2JUlOPPnkKVcCwFKWjOGrqpLclGRPd39q9UsCAGBZrNxhFe285po8/thjOW2z7TYBZt1yZgJXJHlbkldW1f3D47WrXBcAAEuxcodVdOJLX5rT7rjDnjsAI7Dkyp3u/nESu/QBAMyYOrhyx4bKALCu+ZgHAGCsDoY7VlYAwLom3AEAGCu3QgcAItwBABgvK3cAgAh3AADGy8odACDCHQCA0aq54d4Y7pYFAOuamQAAwFgNoU4LdwBgXTMTAAAYK+EOABDhDgDAaLksCwBIhDsAAON1MNQR7gDAumYmAAAwVgdvhS7cAYB1zUwAAGCsrNwBACLcAQAYrRpW7gh3AGB9MxMAABgrl2UBABHuAACMlpU7AEAi3AEAGK+DK3cOhjwAwLok3AEAGCsbKgMAEe4AAIxWzc1NDoQ7ALCumQkAAIxUn3JKkuSJk06aciUAwDQJdwAARuqJLVvy8iR/3LVr2qUAAFMk3AEAGKnt27fnee97X15+1VXTLgUAmKK5aRcAAMCx2bBhQ2644YZplwEATJmVOwAAAAAjJtwBAAAAGDHhDgAAAMCICXcAAAAARky4AwAAADBiwh0AAACAERPuAAAAAIyYcAcAAABgxIQ7AAAAACMm3AEAAAAYMeEOAAAAwIgJdwAAAABGTLgDAAAAMGLV3cf/m1btT/Lb4/6N197ZSf4y7SJghPQOrJy+gWOjd2Dl9A2s3Kz0zTO7+5zDB1cl3HmqqKp7uvuyadcBY6N3YOX0DRwbvQMrp29g5Wa9b1yWBQAAADBiwh0AAACAERPuLO7GaRcAI6V3YOX0DRwbvQMrp29g5Wa6b+y5AwAAADBiVu4AAAAAjJhw5yiq6tVV9cuqeqSqPjLtemBWVNX5VfXDqtpTVbur6tph/KyqurOqHh6+Pm3eOR8deumXVfWq6VUP01VVJ1TVfVX17eG5voElVNWZVXVLVf1i+NvzYr0Di6uqDw3ztAer6utVdZK+gSNV1Rer6tGqenDe2Ip7papeUFU/H177bFXVWv9bhDsLqKoTktyQ5DVJdiR5S1XtmG5VMDMOJLm+uy9KcnmS9w/98ZEk3+/uC5J8f3ie4bU3J7k4yauTfG7oMViPrk2yZ95zfQNL+0yS73b3c5NcmkkP6R04iqranOSDSS7r7uclOSGTvtA3cKQvZ/L/fr5j6ZXPJ3lPkguGx+Hfc9UJdxb2oiSPdPevuvtfSb6R5Oop1wQzobv3dfe9w/HjmUyyN2fSI18Z3vaVJG8cjq9O8o3u/md3/zrJI5n0GKwrVbUlyeuSfGHesL6BRVTV6UleluSmJOnuf3X3X6N3YClzSU6uqrkkpyT5Y/QNHKG7f5TkscOGV9QrVfWMJKd39096sqnxV+eds2aEOwvbnOT3857vHcaAeapqa5JdSe5Kcm5370smAVCSpw9v008w8ekkH07yn3lj+gYW96wk+5N8abik8QtVtSl6B46qu/+Q5JNJfpdkX5K/dfcd0TewXCvtlc3D8eHja0q4s7CFro9zWzGYp6pOTXJrkuu6+++LvXWBMf3EulJVr0/yaHf/bLmnLDCmb1iP5pI8P8nnu3tXkn9kWB5/FHqHdW/YH+TqJNuSnJdkU1W9dbFTFhjTN3Cko/XKTPSQcGdhe5OcP+/5lkyWMgJJqmpDJsHOzd192zD852FJYoavjw7j+gmSK5K8oap+k8mlvq+sqq9F38BS9ibZ2913Dc9vySTs0TtwdFcl+XV37+/ufye5LclLom9guVbaK3uH48PH15RwZ2E/TXJBVW2rqhMz2TTp9inXBDNh2Pn9piR7uvtT8166Pck7huN3JPnWvPE3V9XGqtqWyQZjd69VvTALuvuj3b2lu7dm8jflB9391ugbWFR3/ynJ76vqOcPQlUkeit6BxfwuyeVVdcowb7sykz0S9Q0sz4p6Zbh06/GqunzoubfPO2fNzK31DxyD7j5QVdck+V4mu8t/sbt3T7ksmBVXJHlbkp9X1f3D2MeSfCLJN6vq3ZlMKt6UJN29u6q+mclk/ECS93f3E2teNcwmfQNL+0CSm4cP3H6V5J2ZfECpd2AB3X1XVd2S5N5M+uC+JDcmOTX6Bg5RVV9P8ookZ1fV3iQfz7HNz96byZ23Tk7yneGxpmqymTMAAAAAY+SyLAAAAIARE+4AAAAAjJhwBwAAAGDEhDsAAAAAIybcAQAAABgx4Q4AAADAiAl3AAAAAEZMuAMAAAAwYv8FlP1bkvw4LI0AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "Note that our formula for LB of distance profile is different than what provided in the paper." + "LB = _calc_LB_dist_profile(T, D, m, Σ_T[idx], m_target, Σ_T_target[idx])\n", + "\n", + "plt.title(f'distance profile of subseq at {idx} with length {m_target}')\n", + "plt.plot(D[np.isfinite(D)], 'k', label='True D')\n", + "plt.plot(LB[np.isfinite(LB)], 'r', label='Lower-Bound D')\n", + "plt.legend()\n", + "plt.show()" ] }, { "cell_type": "code", "execution_count": null, - "id": "6b4e19c1", + "id": "11e07596", "metadata": {}, "outputs": [], "source": [] From ca04fae03f5a9e4c803c7a69a6921dcef9b8e264 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 10 Apr 2022 17:21:46 -0600 Subject: [PATCH 03/67] improve markdowns --- docs/Tutorial_VALMOD.ipynb | 26 ++++++++------------------ 1 file changed, 8 insertions(+), 18 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index e3e266d0e..e84e7ad1f 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -61,7 +61,7 @@ "source": [ "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index in two different motif sets. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty. " + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." ] }, { @@ -85,11 +85,9 @@ "id": "3826e0a5", "metadata": {}, "source": [ - "**$n^{th}$ best match**: Given a subsequence $T_{i,m}$, the $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", + "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", - "\n", - "**Top-k $n^{th}$ discord**: This is k-th value of $P^{n_{th}}$, sorted in ascending order. $P^{n_{th}}$ is the matrix profile that is constructed based on $n^{th}$ best match rather than 1NN.\n" + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
" ] }, { @@ -137,9 +135,9 @@ "id": "a8e87bc0", "metadata": {}, "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors (maybe the second, third, ...or n-th neighbor as well.) \n", + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. \n", "\n", - "For further details, see Fig. 2 of the paper (Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" + "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" ] }, { @@ -148,7 +146,7 @@ "metadata": {}, "source": [ "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series `T`, a subsequence length-range `[min_m, max_m]`, and `K` and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." ] }, { @@ -164,7 +162,7 @@ "id": "5f999789", "metadata": {}, "source": [ - "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can I find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` but is longer by `k` elements ?" + "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can I find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" ] }, { @@ -172,15 +170,7 @@ "id": "03836054", "metadata": {}, "source": [ - "In other words, can I find lower bound for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$?" - ] - }, - { - "cell_type": "markdown", - "id": "be9e2963", - "metadata": {}, - "source": [ - "(Note: It is more common to consider `i` as the main index and `j` as the neighbor. Here, however, we choose `j` as the start index of subsequene of interest so to be consistent with the paper.)" + "In other words, can I find lower bound for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? If I can find that, it means I can find the lower-bound for the distance profile of the query $T_{j,m+k}$." ] }, { From c6b0868cee07b4332918e3ce24a75d4902b55754 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 10 Apr 2022 22:33:06 -0600 Subject: [PATCH 04/67] Major Revise of Notebook --- docs/Tutorial_VALMOD.ipynb | 498 ++++++++++++++----------------------- 1 file changed, 186 insertions(+), 312 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index e84e7ad1f..079fc4831 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -41,9 +41,7 @@ "id": "aa1d847c", "metadata": {}, "source": [ - "Some important notations that we may use later:\n", - "* subsequence $T_{i,m}$ --> a subsequence of `T` that starts at index `i` and has length `m` \n", - "* Motif set $S^{m}_{r}$ (for a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$) --> is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set." + "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m` " ] }, { @@ -59,6 +57,8 @@ "id": "fd1568ab", "metadata": {}, "source": [ + "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", + "\n", "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", "\n", "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." @@ -162,7 +162,7 @@ "id": "5f999789", "metadata": {}, "source": [ - "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can I find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" + "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" ] }, { @@ -170,485 +170,359 @@ "id": "03836054", "metadata": {}, "source": [ - "In other words, can I find lower bound for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? If I can find that, it means I can find the lower-bound for the distance profile of the query $T_{j,m+k}$." + "In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" ] }, { "cell_type": "markdown", - "id": "4fc93b47", + "id": "a1429322", "metadata": {}, "source": [ - "$d^{(m+k)}_{j,i} \\ge \\min{(d)}$, where $d$ is:\n", - "\n", - "$d = \\sqrt{\n", - "\\sum\\limits_{t=1}^{m}{\n", - "(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}})^{2}\n", - "}\n", - "}$, where ($\\mu_{i,m+k}$, $\\sigma_{i,m+k}$), and ($\\mu_{j,m+k}$, $\\sigma_{j,m+k}$) are (mean, standard deviation) of subsequences $T_{i,m+k}$ and $T_{j,m+k}$, respectively." + "### Derving Equation (2)" ] }, { "cell_type": "markdown", - "id": "ff38394a", + "id": "982235e5", "metadata": {}, "source": [ - "**Note:** The values $\\mu_{j,m+k}$ and $\\sigma_{j,m+k}$ are known. The goal is to find its lower-bound distane to its neighbor `i` (i.e. $T_{i,m+k}$) without using its last `k` elements! The value $d$ shown above is the z-normalized distance between $T_{j,m+k}$ and $T_{i,m+k}$ considering only the `m` first elements. We know that it is already less than $d^{(m+k)}_{j,i}$. So, by minimizing the Right Hand Side of inequation, we can get the Lower Bound (LB)." + "\\begin{align}\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt{\\sum\\limits_{t=1}^{m+k}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}} \n", + " \\\\\n", + " \\geq{}&\n", + " \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}}\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "49b2a8fc", + "id": "a86c6f4d", "metadata": {}, "source": [ - "Factoring out $\\frac{1}{\\sigma_{j,m+k}}$ --> Therefore: $d = \\frac{1}{\\sigma_{j,m+k}}\\sqrt{\n", - "\\sum\\limits_{t=1}^{m}{\n", - "(\\frac{T[i+t-1] - \\mu_{i,m+l}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1})^{2}\n", - "}\n", - "}$ " + "\\begin{align}\n", + " LB ={}& \n", + " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}} \n", + " \\\\\n", + " ={}&\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "4fa6a3a9", + "id": "31a8cf32", "metadata": {}, "source": [ - "mulitply by $\\frac{\\sigma_{j,m}}{\\sigma_{j,m}}$ --> Therefore: $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\n", - "\\sum\\limits_{t=1}^{m}{\n", - "(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", - "}\n", - "}$\n", - "\n" + "Note that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." ] }, { "cell_type": "markdown", - "id": "1634ef47", + "id": "4595f60b", "metadata": {}, "source": [ - "Now, we replace $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$, so we have:" + "\\begin{align}\n", + " f(\\mu^{'}, \\sigma^{'}) ={}& \n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", + " }^{2}} \n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "a86bc201", + "id": "0be3b76a", "metadata": {}, "source": [ - "$d = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\n", - "\\sum\\limits_{t=1}^{m}{\n", - "(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", - "}\n", - "}$\n", - "\n" + "\\begin{align}\n", + " X_{t} \\triangleq{}& \n", + " {\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " } \n", + " \\\\\n", + "\\end{align}" ] }, { - "attachments": { - "image.png": { - "image/png": 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Nn0vnzapWOmc+gG+gBPyaVmhtysOba8ux+a0LFv5s/G2ww8XAyycMXJV+aNfyc4bHxeHMouk4EJrV851L8EdSnBCuLlGo9vUtR4TmY7ZgfpeqyAg7hPGj9yJdJIaEVx327bNquIUmxjDiA0/TU5HKyT+/fFnnV1XSYMD/HVCtPrKNHwDET4Brz4AqA4Amcn7Tho0B/ePAn4eAVo0Lc0HgynVApgG88QUspgN2esW+DQBAiifwiAN+/twfNO4mMGEO8FoMhCUBLRXvrVOuVKQst5z4PNgiLRKt8xts8T0S1EUvZwcs9nTHtm2B6D+32ac+NJJncBs3Frs/dMe6f2eimZwPjV/dAu2s60AdQtS1sVe8L6fsBS67PwHMp2LTTlfI6QVQvgjNMXHbcly1m4CLb2WIPjETk93a4tiwYnQt4FeH48J9+CugDX479xESSfEHPGQ+8EWghI+aVq1hynuDa8s3463LQvxs/OWLy4D/LS8k8uthaKdszfWsgFaYNNj3cwHdKEcBfRHXnslQZUCrHAW0BgwsbVDn7HYsPxCDjjaFqX8uwZe5FE94PuJg8POn/qCyuJtYPWEOjr8WIyEsCY1UsHSWRQXjaYIMPFMxQraPwbytyRh/8X+5a9tSveD5SAr11u3g8DXvUUMNE3NYCLKGhXER4bgerAFTCwsYfX3GhTDWEQHgkP5WgB/WrMOrGS1xpHI3tLfPelGXxsYigeNBzbgBPvWuyH1++b6cX3UlBwLhMoAfDSRwgOE74M4pYNdOwD8TsKwHPFgHxAwCBhllHVfdArCuA0AI2NgrXgsqewF8Li6w07V4UzLldP8ukK4FOLYCvNYCi/yBpRcB26J2pi4nWAxU6hQbbPF9EqDhxJ3Y9cIFE5d0gPXtXnDQe4v7N/0hthqJg7cW4Kf6eTXbcYjx8kEYVwX92uVurpe3/7vAY9i2cSPW+gIW8wd/W1tUjgnq/4bNf12F3ehTiJPF4vTsKdjreBwjijPKSmCCX+aPxPpLG5CRUdwgVIao4KdIkPFgKg7B9jHzsDV5PC7+L1v6ZGG4dTccVHMYOlpl/zZZAa2o5MBAhMsI/OjXnwvoUNw59R927XSDf6YAlvVq4sG6pYgZNB+DjPgABNA3b42awjRwQku0b6+veBBZgi9zkvt34ZeuBRvHVkjzWovxi/xhv/Qi/Gyrq3CLBR8CAQ/S54ew4tBIrD6xH0NNc//+JA888SBVAIt2jtD7cjP8anAY9Qccsu93MQp7vKtg+HxXuf0KddsMRL+kfejrnwFRi/Zo/3WknwwRV6/jiawqOg/4EQZ8AMh9/vLqrgcgJoBzB1oYAyIZ0HEWsGomcGUgELwF2LsR2GaU40AO8PIBuCpAu5YKXIgDAo8BGzcCvgDmD84jAOWAM4uAA6HZNiUASXGAqwuyvSQDzccA87t8/ocUuOMDkDZwfgjwxgpw24fP31fFxoJQRXBxuPvfHlwOeo24xAw0GfM3pjkA4df2YudxL7wS2uC3hRPgqM9HRvQt7N5yEHfCNdH5fyswsnnWo5rvYIv0QBzfehJ+r6IR/64yOs5dg+EN38J7/1bsvhyMdKM+mLd8KJqUj175RSeshwGb7qHX/MfwDQjHe341TFrZEk1rFVSqpcLL8xGk6q3RzqHgElAWdhFHQ0xhUzMNKYJm6DugInWLEMBk2D9Yd9kXQ49GQxZ/FnMm70GHU6MhpxxUmJr1LxjYfBO8JBJ8OxlKEfAFEPCkeH5oBQ6NXI0T+4d+kzbujQduP5ZBu0dH2GUftMIKaAWl4a6HH8RE4NynooXxcohk1dFx1hasmhmFKwMPIHjLBOzdeArbsvfVyPDHLa9E8OsNRSf5Q7pzUPRljkPcmUWYfiA0a3o1LgH+SXEQurogKlvpLGo+Blvmd/k8X6wUoXd8EEfaSDo/BN3fWGGF2z50UfHSWWA2CUf9bBFGpmjRtFYeNWYyhHvfRzTqoJdjg2LnPx+8bsEnTYhGju2zZjxIu4NN//pA1HoBXIfVUU7QLpNBBgLHETiU4TyPGcCte5/mAT22GdCpDNhYAVp8ABzgcRPgWQLm8qbeSAU8HwHqrQEFiguEXQRCTIGaaYCgGTCgad771jABLLLnZRHA9WDA1ALZXpIB42xTo3EJwL0QwLALoJMMnDsHPJoFGJTAbPWcJBXpVAnaGqoxIKXilLsliV8FptatUOnIX9hzvRJG9o/CyUljsCrcDE0/euDQzaN4ZfYjTrY+gFF/PEQNvVe4dOIhLmS0wYDjQ75OOpvvYAsNQ1ja1MW57X9iX2RzmI6+haVzl8CzakMI/S/i4vF70Ow8EDt7VPQo9BMNw6ZwNMznl56T5AE8H6RCYNEOjnoFZ4sCsx8xpvZtTF0QAljMQe/yMu+LovhGGLThb1zxGYR9EVK8uTAXE3d2xNmxxZgCRtAATl0a4K5EUszCRwCzSUfhZxsGMm0h9wUj/c4t+EnU0LJDByijwfv7K6Af4Na9ZAgsp+LY5u7QqWwBG6s6nwvoxvC4OQY8S3uY5xgZKQu7hbvhhJrDOsJKgalOC/Myp1bDBOYWgqy5R7kIhF8PhoapBSyylc5CY52s6dW4BNy9FwLOsAta6iTjv3PncP7RLHQpidJZqdRQ09IBNfPd5z18fEPA6fZGB+viziubgYBbnkiAFto1/RzQcvG4NG8y/pP0xoa989BKSUVH6osXiJMReNHR4FCI2nIlk4UDvq8AjV5AV8cck7vzAQvHvI+VPAAepAIW7QAFiguY/QjUvg18Li7yniaMDziMQo6XZGCPNzB8ft6j4z94AQ8zAadfgfUGwI0OwPy/gc6LlBekvQ/YjQWuRxDG04JaYjAC05vi1yVrMK+ncdkGgsQoRhZBGzqoE69SS+o1sC9NORpGEiJKc+tLlXkiMu87igaO3EaP04lkrzZSRzUeafbcRYk5TpN+9leqyRdR62XBJM15jY/naKQhn/h6NtS5Wz9afS+JZCSmq2Nrk0DYgKbelpTOvZZD0pA/yUYkoHqTbpGin1JmoCtZiwRkPP46ib+eKIJO7DpPsbISSmhhia/S2Nrq1GpJUBEOltHb879RfRGPABC/mhNtCs311BVK+smR9NPal7mfXXkkkXTrZlDWZ6swMd2cVI8EwgY08fhFWjJkFO18nvcVxRdGUe1G0+hOnl+8hDxnNCQhX5cGHn73aZMsji5OakpVjfvRrqeZhU5hXpIODyI9voiaLXhIyjtr4UmfriBbEY+0nd0oReGjZBSztRtp8nWon1uS4hcTe9CU+kISNV9ADwtz0+ILNKp2I5qW9xdHlHqchlQXUPUhxylVfJdmNBKSurUrBZTlh6ss4ss0praIDIedoncF7VrQMy4NoT/biIhfxZTMW9hT/1EjqHdrc7L6aSGdC1dOuSGLPkVznTtQI10h8QDiVTYh+76z6VhE8fKU/CHPvze7Qdo8UEtXUGY++8n7C/kTJBKAJt1S/JhA10/HjL+etU0aAdp1HiTL5zjxBVDtRqA7krz3uT0VJNQAbY4BkRS0zAYkMAKdSlIgbVLQnWuP8/2dS8N3009GljTTM/3TBlkMufU3IIGWA60KKtsfk2q3aaiS93fg4Z8ByNKgP3gz1g2oBzVIERz0DBKSIf5dQ8z+ZywsKwHSV5GI5oRobN0KVb45SdZgi/adcs+NmPHoLrwTOICrjK5//odZtrrgSx/jlmc8oN8OXYr9tlxxvffxRQinC7sO1ln9QdM8sNCxNrSrmqHXGl+k5TyI48CBBzW1z/UuXCLubnPDR9uuFaQvDh/Ve67G1nGNoMYDuCR3/DFhM54WY/1LDYcR+M22SoHTEHFvbmLpSFf4axoVYdqjDwgPjwPHReH4ikOoMXMDRinUNJwH2UvcuhsOTksHj1f2wIDRI9HHtiPmv+4Lt1sHMbJR8esBuJjTmNevI+x+P4G3XCYer3dGe+f/4XhkUdYcKr4kLy8ES4Vo0KwZNBU+Kh13bvlBotYSHTooXv8sfXYTdyMJtRw6wuLLRymLxMndFxBXzO7DGf534fdehJYO9qikbosRQ1uCAv7F+vPlZe3OvEmfesEvoRb6DO1WYG2/eo+deP0078UYuAQP3H4shabDXNz0PoeVk6dh3YWHeHhqMX40UU65wa/VC64HryAoQQKOCNL3z3Hz0FL0NS6bZt27N4F0PmBlU/jaQh9fgNMFOlhnbUvzABxrA1XNgDW+uY/hOAA8IFtxgW1ugG3XYrZ4yIC79wCeOeCgB0AA/Po7oBsHrNgEpIcBy3cCeU5KIgD043fgtymH8ULuThyiTu3FxXgxMqWfPym+Ifr8ZAfNdD9cvBpdnNQXX5mGwOXIx0u/kZFARJaz71H6l43SMFrTTo34Oj1pR+SXqrNMCnRtSSKhBf3PJ8cbqPQJLbMRkcBoFF34mPMKUgpb047UeJXJaWs0fTmb9PkqshfxSMd5PxWibuI7I6bLY2qTyHAYncpWpSCL3kW9dfmfagF1h9DxnJ+5NIz+G1SPKmk3oh6jxtLvk11pv39BdRKlrFg1oZ+leNDMZhrEAwh8Heq4LrhEa+lk8ZdoescfaJl3apHPkfkmlIIiUhSrcS0oPbHbyKkSjyr/sIPixIn04lEgvXiT6wdYTFKSiCWUKf30y5VJM0kiligl/YWXSieH6hNfYESjLhbiPsU3aVI9AQkbTKTjF5fQkFE76bmUiFJv0R/tjEirSj368S8fyvmtZgYsJCuRkBpMvf2p1lv2lu5sWkZuwQXUwBVYEyqlkOVtSCSyooWfqz5lUXvopxoC0rRZQv5pL+jgn/9SQLlsIJJSyAo7qtJ8AfkqIf0pR3+manwRtVkeUkbPXEnJo/YvGTTUAMQ3AJ1OLVwtKIlBY2qDDIeB3mXbHr0LpMsHASDdIaCPOY6ThoEG1QNpNwKNGgua7Aryf1fw9QqsCX0H6qsFMpkAEn/Zlgna8RNIJASZdARdfZPX+b/IpLC9LuT48256Kud5yoxwp+1bz9PzbNlB6v6+VJmnTt22xRf521EGFoQqJJP85jUlkcCUJt7M1rj4dg/11uZTJadtWc230hBabisiYcPcTSeymK3UTZNPOv3c5ASUSbSvbxXiiexo5dcmUxnF/9uDKvM0qNPfr0hVWohVTmYALbRSJ+Nx7lkvCJ9JU6IoxHMpdbTMqynrI8U/9aeAsCSFm/FLlTKCUCJK81pA1pU+N8tXbU9/PS6hu5UE0d/dG1L3zc9VpjCsuAV0HpJP0FADPvENhtPpwrwHJO2mHyvxiK9pQNZDt9DDz8eW2MtcgUHoO9rXV4uEJhPo+tdsN5NCd/xERiIh6Zh0pDlX35SffDEzmPZMGEZzjr0gcexJGmHRgqZdS1bCicV0bbwxCYQNafpdlczFikF+8CW5D5q5EHQjrJABKIEyA0BW6qBx7rn/LyUK5LkUZDkNJJF3/EfQU39QmCLN5IX4i3kCikrL3cwe/hSUJjfolEOWSOd/syTrGTcUqLBKo8tj65JQpzttjSjbXxALQhUhC6d17dWIX+1nOpqt40X62V/JIEfhJn25lhzVBWQ64QaJP0bS0/C0r/unHBlEunwN6vRPVO6M8+MlGm0kIGHDGeT5NR9JpeNDahBfZE2ugRWhE1TJkIasILsqzWmBvCoFaRSdnuxM0y/El5/CKjslBaFEH+n+ElvS4oEAHlVpu4IeKb28yqSgv9pT9WbzlFK7oxwVuYCWT3J/G81cuJNuhBW2JjqT3oQGUURK7lC9rF7mPsY8oaCotBxbpZQc/pRe5dys6qQRdGxqZ2ra0Iocew6jxRcjldIiIXt7icY1EBKvSk/aHl3RygnlBntEoJAVoCrNQb5yaialUaDJzqAL8cq/btH+Ckf2agf1rNGIJlzN/+VG/Gg5tdWpQ867X5Rp33UiFoQqJnEf9a3KJ81uWyjmayQjobvTG5JQ2Ihmen3JdmUUv/NH0uJp0A9rr9HfP3ejade+1AjkPzSF8xkAACAASURBVNgi03cuWYr4pD/sFH3NW8XuNK6ugPg1h5Pb3S00Zvga8i38KI8KKJOC90ygYXOO0QtxLJ0cYUEtpl2j3D+7dLr3z0xafS2m/NaAKS0IJSJJIK12rEp8gMDTJrtl/kUYNJQ3Wcx/1Le6JrVbE6Yyn3fFLqBLUXl/maugUm6toZE/D6BBQ1zIZchgGuSygE5HV6RvSAmBXCZozwTQnGMgcSxohAVo2jU5+6WD/pkJuhZTPgJO+VLo5NCapGG9iPzzyO6kkcdplGUD6rslMFfLYVlgQagCxO6/U12BJrX7KzSrcJWG0V8OIhLUHUtXvzZPSejeLHMSgkdqetY0avfjrICSkmj3j5WIx9ckA+uhtOVh9loKGUX/04nU+brkvP9t1tbYLdRVnUc8DX1qPnANeSZWpMylOKQUcWwqdW7akKwce9KwxRcpsqLGF8oMQoko88lG6lLtU9Mqr3IbWnxfWX0jMylgUUtSE7WmpcGqEYJW/AK6tFSAlzmmnFJCcCcFHZsKatoQ5NgTtPhi4UfTq2bAKV/ygX6kI6xFv57O3SVGGnGMRrWwpJ93hyi1AqI4eEREZToyqjyQJuLFk2ToWtRH9WzD8NJePUakwAxNjLLNc/ghGk/CxNBrYAY9jRynSXiG0A+GaGysnXuuxg8xCH6RgbqWJtD+OtQuA29Cn+GDgTlMqqrGxLJMKZO4Y1z9Xngw5gH8/lDG+tgyhO3oA7vfLyCB46FSqz9w02Nx8VeLkt7Hgpb2WPF2GM6+3ImeGgUfwjAMk7+C5uFQdaUfXslClsO++R8IH3AEzw/0/zrzAhd3HpN6/A9J085i71CzT7PISOLwKlkHdQ3KLsMu/Nwk3Bt4urnh3hvF594Qmjphar9CTDyuaoTVUb9Z7gVcteo2Ra6woJIRLPK4VaFew9z7fz2uFpo0y7lRDfqNLAuVVIbJnwBmozbjr8sPMepULD48+Au/L/8Bt5fZonLBB+dJFuaOa08zIWhpBjPVXs2SYZhyg9WRFZbA2AwmmoQHHlfgJemPH9QBSJ9iy/CxuNv5EDy/BKAA3l+Yh4mhs3B2rnmZpbcIQWgcbm5fjjXBik82qNZZr3wHoQxTkQiMMXTTOlzx+wWHoz7Cf93vWPbDXaxwKHoY+jEgAKFSHvjV9VGTVdozDMOUDYE+9KrzIYt6jIAIGX5oJEDSycVYcrMa+gxMxLXTpwEAJHmNCyuvQPN/f5dpcgsfhAqbYYHnWywogcQwDFM6+LUGYv3fV3Bv4F5EfHyEDeMXo4fnarQr0pLwMiRExSKdAI1KlYswOT3DMAyjFLxK0NLkAVwsXkdJgUZSeF+9jaTMGOwc7Yyd2fcVtcLSZoovZ1ESKtiC2YyqcHd3x5QpU8o6GWXm8uXLqFu3blknIx981OyzGmt+dscgtxgI1dTBL3LLFyElJRUAD0I1UYGrhzRp0gSsKzpTEkaMGIFZs2YVsJcUj5a0RYfVQchU9MRq3fDPi5MYUa3gXdevX49///1X0TMzTKFdu3YNtWrVkv+ffHWoiXgApSHlPQHQQPdt4RBvF0IoyJ47c5BlcOCplW3TFQtCmRJhaGiI3r17l3UyykzlysXpYVk6ZK8u4/DNeJD+D1i9fxEctIt6Jh40NNQBEDiZDAX1Fu/duzcLQpkS0aSJIoP3+DDsOgmLqyQU+Kx+JTBBawV/0ubm5t913seUPE3N/GovMyGVAeBpQEPz08AuvlBNTuUAHwK1sl+fumh9Qnf8C484xddEFjbohQUu1gXvyFQYlpaWWLlyZVkng8nLhwdYNXQyTr4xwYijuzC2cXHeRwXQq6kHEQ/IkEgKHEqwYsWKYlyLYYqLD307F0y2K5mzd+/eHd27dy+ZkzNMQTgJxBkE8KvDQF/1O+gXIQhNgM/RbdhamIFJneoXKgjNuP8fFrkFwWz4Soy2+pzEDz7YvfQwHmh1xub5PxY21eWAGDH33eHu+wxR8UlIz+CyFeZ8VGk9HHOdG5Zh+pgKg3uDCzNcsNhLhlYL9mHDTwYFNqEXpEqzZqgnPI9nyYlI5IDKZf+CzTAM8/3hkpCUzIGv1QTNG6l+Y3cRBiY1xZwb0ZhTAon5RIaI6zuwdntlbJidVZJJwy5jy9pNSJ3UX3mXkrxDorgSqldVK3jfnKn8kIio8OcICYpGlfZ9YW9Q1FKXQ5zHesycuhxHH6VAqFMdmpJEZFY1hoEWH+AJoGXaEwvG1Svi+bMp8v3K8CExCuHPQxAUXQXt+9qjyLfLlDEpXuz6DaP/fQHdnluw/w87FGksUg5CC0fYG6zC07goREmBuoX/STEMwzDFxL2PRkwKQbO9I+yLO/9zKVDBMDkV9/1CAPPJaKufFemIQ0IQxtVA3w5WuY6QJoYhTGKIRrUU/MS5eFxxHYY/7taCnVk6uPZrsPGXuoWoDZIh/MomzJ67HGfie2P/y36wV/jYbxKCmNO/o6vLHrxrMxW7faZjYGt9vD00BG0XibDY/T8MNs5dnV7q9ysLx5VNszF3+RnE996Pl/2KdrdM2Uu7txQuM84jyWw0TuwcjYbKygEqtUf/HkbYtS8ET94D9npKOm+pqKCtEOIY3Hd3h++zKMQnpSODy9ZRgl8FrYfPhnND1W+uYxhGcZnBQXguq4y2fXvDsDxUFpXtgk1yfLxIo4xEVGece7ZlpT6tuy7U7k173ubYPzOQFluLiK8/lE6lkQKkFPFvL9I3Hklnkoikz9fRpD8fUaFXfZTF0TYnTdLq8S/FFXElQFnsQRpoKKSqjivIP/siruKbNKmeiEwn3sy9tFYZ3a8sbhs5aWpRj3/j2NrRpUmJy3bKYk7Qr2Yi4lexo8U+Cj08hZIZ4ErWGvr0y8nUgndWCTKKvbWGXFpUIxFPSJq6NalaJSFpG5pRgwYNqEHDxmTlNINORJSzNWFlsXRrjQu1qCYinlCTdGtWo0pCbTI0a0ANGjSgho2tyGnGCVLKbYmT6e07iRJOxDBM8WVSwMIWpGY0nE4ll3VaFKNyQajEcwY1ElUlZ7dsn2DmI1rUUkRqbddQmJzFizOTwul5jIJrYItv09SGatRohieJ04Pov3kr6eqbnGGVmG6vm0cHX+SzUnLqcRpSQ5ParwsvYlAmpZCVdqQubEBTPHKkPfMxLbYWkVrHvylKzsnL4n5Tjw+hGprtaV04C0GV5WPENdq84TRF5Lcgt7KCUEkw/d2tBvEFhtRn54vCv3QpQhZPx36pQ4aDj1JiSZxfqWQUfWoMWVQSUa2Os2i/byxJSEbRBweRaYNf6GC+X0oRFCNYk6a/pYige3Tp8HHyjC3g9yeLplNjLKiSqBZ1nLWffGMlRLJoOjjIlBr8cjDvZ036jsJDIihF0Z+3LI4u/9GNWnf8lSaPHkAT90eyl1OGKWsSP5rXTIfargoqmTy+BKhYZa0ML2544CWvBdo6VPm6lYu5hdtPgIbtHFE3W+uROPQKdv+zBqv+3oc7kRKFriC+fQAnIxrgR/tk7NnsjXqTZqGrXs6PQYrwO5fx6G3eMwBIvK/hbmoTdO5W51OztvgVbu/5E/MXH0SgWJGUvIPn7QBI9R3h1CbHuq3iUDyL5KBdywg6/Oyby+p+JfC+dhepTTqjW51Px4pf3caeP+dj8cFAKHS7zFcZ0XewbVIXmFt0xcQ563AiUvGZJormHW4tcMGca6loOGYn/h1hVux+OOLk5Nwb+fpw/nMpbL03YnuQ4gMXywIXdwTTxu9GdKsluHB+NX5pbQA18FHLeRx+lB3B/DV3IO8XJk0MQ2jMh0JcKB5XFjrB5odpWDLzF0xye6X4tEAAvnT9mdavPXqOO4wI9fyybA5xR6Zh/O5otFpyAedX/4LWBmoAvxacx/0I2ZH5WHNH3l1xeL29P5o0aYqfd8cplKbI3b9h2L7aWHBiD9b9zw68V+8KeV8MwygXh7iTa3FEYzLWTm6iin0t5VKtIJSLwY2bQaDazWCVrTPD+zse8Jfqw9ax6TcfrFotSzTPcMeqpf/gWpQit5IB3/PXEKdngspcLQycMQrtijTCJgOPrt9BfL1O6NaAEHPjL4wdPg977wQiJCoNHE+BU3BpSEmXASI1fDuGg0P82SO4+r42nF06f7Oed5ndb8YjXL8Tj3qduqEBxeDGX2MxfN5e3AkMQVQaB0VulwGk8d7YPaMHmlr1wdydNxDxgUASX5w5HYmSC0M5vDo0HsPXB0Jk9wf2r+mBXO8ghT7la/w7cqrc/+LXHYqtGy1xesYGPFbZtxMZnu39B2cSTPHr0qlokb1rtaAGaugC0cGP8TZnVCV9jOVO5rCwGofT6Ypdp/jBmgD1+4yDk4kAleyd0Llqfpd7hr3/nEGC6a9YOrUFvr2tGtBFNIIfv5VzfT7qjDuJp6HBODLSoOAkSbyw4a8r0O0/Ck7qwXDbk4Fev1mWm0KPYSoiLuYE/rc2FdP2zIeNRsH7qwrVyjc++uLeowzwDLWhJQAAKeK9tmPasst4L3REa/MQXL5ZHd07flqJhq+th4/RERBX7YgfOxc003YGYu5uxrpTMWg54TwW9m+Mb7rkiyPheycESbJP+4a8TUXkfXdcThYA4EGzTiu0a1L9U9QuC8f1Wy9QvWlNBLuOxA7tYVhyYBaMcnyaaR4L0cNlPR6pd8Afhw5hpk22cch8Q9i1MQPf8zrOeKWic8dP6Ze+Oo5ZC69C/zc3LHP6tsQpq/uVhV/HrRfV0bRmMFxH7oD2sCU4MMtIxR4e1cYlnMH88Sch6DoRp54eROjUxui/Px4cSeB75jQip0xHvRIYIyIOWIPh448guuZP2LV/DlopY7Sk2B/+4aI8/pOPmr02Ym/iWEyfcgSbNw+Cqco9KF9aIYbk3Qrh9G0rBABA2BTz3J9hiNgA9RWZuPxrsHYzK1ibmjNYk+DO+iWI6r0Eg83yeAA+3MXtB4D1vC75v0C888TtACn0hzgh9209QySnDScjnW9rHsShuHLQHY9j3yKtZldMqVenwNv60roywD4ZezaHoMmkWWhX7DcbhmGKikv0wOLfD6D++v343aJ8TU2iUsWD9MkDPErhIE3eApfO3tBLl8Co73TYNBDi8PNH2LXgIpasnpt1QIY/zl0OR+X2f6Cbbn5nFuPp5WMIeOKDh0mtMXVQA+TM7rkPz+Fx8gSeSQGAw8vod3h3/RROBPAA8KHbzggOn4MyLv46bgYKoavjjnWH09FvZ0sY5vokOaSEPUJQbBpSuItYvvEKJh7oh6yyQQ22c3dh+bPhWDbAEfHDe8E09RE8/JLRaMJZXJ/iCP2c+XqZ3C+H+Os3ESjUhY77OhxO74edLQ1V68EpB/h6fbDqRJ+v/67j7AT9A/sQxxEkvmdwOnIKpis5CuUSr2CWyyJ4fGyMCYd3YKipcs6f8fAWvD7kF82qo/GvO7Hd8C+s3+qDFZPaqNZ68kVohRCHXsHBq48Rm/QBtZymoL5hwVUNigVrn7rCPLFflGcQ+qXrz+jsXX8O7ceVV6YY9L8haKbx5bZS8Om2chRCXDzOHrmK97Wd4dI5R/SsZoDG5mn4a8pSPPihMaaNLuiuvrSuNP7cutIT1Vj8yTBlRxaOw2svov6fbhhqqYwJ90pZWXdKzSKjV/90Ig1hPRp7xI+8AyIp5XMnelnSc3oYFEs5h+Jk3p9PTUVVqc+eeAU6xb+jY4NrkEbbv+jr+Jv0NEqTe2Aa7e3bkv7nLX8gQZKbM+lodqK/I1Po2vh6pNFkFnnKHSckpZSoEPJc2pEsp90h+WeTUeqrQPLyuE3egZH0Lp/xEGVzv0nk5qxDmp3+psiUazS+ngY1meWZ67tgCin1NA034BMAAk+DHNeGkdyvvqgDk6RhtLtvLRLwdchxxUMlfl8S8v6fBak3mau0M5Y+Cd2bbU4iYUOadCPl69bMyCM01KwqNRl/juJz/E5kKVF0f0030hbUoCHHUqhgEvKYbEZqRj1p4bGHlJjnDzb/vIZIQj5zmpC6+WzylmRS9PXVNGagC40cMZD6jt5O/tmnz5Dco9nmIhI2nERZt5VJkUeGklnVJjT+nPx8Qxa1kTqqV6bu22MLyFckFH1nHfWpo0m2y0PkP68MwzCFoEIVWqnwvO2PDDU7tOrYCm2yzTPI160Pq1w1fzI8u3QFT4Vt8Lt9DE6ffIWuzi0hCziGnefj0HjgWPzYMFtthTQSj5+mQr9NC9QWAJCG48Khx2gwvDcaFupN/gPuXr+Hj5YT0MVIGw0njoeN2zK47hqLS6P5eBKuiyaNvzR5CVAJoTjib4VVW+0hv5KcD606TWFXYCtYGd3vh7u4fu8jLCd0gZF2Q0wcbwO3Za7YNfYSRvOfIFy3CRrnarfMmzQhCB4eD/H8dTTepEjAfbPGIw9aVoMxrU/DXDW3FY5WZ/R1qon9e2M/NcmfPYPIKdOU1CSfDt8/f8HUM29g0G8P9s2ygtK6CKVdx65DoeBqloNZkPNU+FYIVe/68+m2bDF313I8G74MAxzjMbyXKVIfecAvuREmnL2OKY76cgcBvPe4DX+eNf7oqpfPIIGCW1eY750UCUEe8Hj4HK+j3yBFwn27hC9PC1aDp6EPm5uWya6so+CvPl6k0UYCElktpACF5hZIpQP9tImvbkptf1lAJ16IiSiNjg+pTnzwSN1+FT395lU9jTwX2VINYyeavnwd/b3tBD1Mzuu9P5/aCckdmtZAgyzn+n6eAkFCQX/3JCM9c+oyeA4dfZkt8en36J+Zq+lajDLqDMrmfiV3plEDDUua6/v5viRB9HdPI9Iz70KD5xyllwrOA5EZdZ1WDrammuq8T7V/uf54JDJwonXfTJhasaWeHUG1BJ/un6fRntbJm3+s0DWhMoo7M5oaqvFIw3IqXUtS5sQ5mfR4hT1p8UBq7dcr8bxlRfFWCJJ402xzEen03U85pyr+1kcKubSPDq0dRHUqO9JaOd+pLNGdVo8bTaNHj6bRo0dSp3p61LLvqM//HkOz9j7+Or2KLHozda1UmZp0705NTNvRwuuJBbeCyFLpVaAXedz2psDIdwXUWKbR6eE1Sa3VEgoqMJsqTOsK8/3IpKjrK2mwdU1S58nL20HgicjAaR19R9k7oyCVCULTLv1GdQUiajrfT+H5rTKTIin8TY7p3DOTKeKuK/UZsp9yT6knpdSYlxSZVJzJlTMpKTKC3uY4hTjx7dfuAyWlTO43M4kiI97m6EogpsS3KQo3x318vIV6G4mIp1aL2rjMp38OnKYLO36lhtWa07g9HuTt7U0+voEU8U7ZpZmMkp7epKO7d9Kh2+FU3PzvXeAZ2rZmEU0f5Uzdpx6npOImL+0cjawl+Nok337dy9yfaSGDUEnIFuqhzye+bkdaHaDcThPJHnOplfanlwj1H3Yo9dyqTvW7/hSR+AZNMFEji//5fP2Ny5L96fBfS2nDudBvu3FkPqKFVupU98tCIpkv6fzOMxRaXiYkZErAR3q8pTcZiXikVqsNucz/hw6cvkA7fm1I1ZqPoz0e3uTt7UO+gRGk/Ow9iZ7ePEq7dx6i2+Esui2vVCQIzaQnh5bRKrc7FFHMhVwyw87Qn7PXkHtBkzpXECp/vyk3aKq5GvGr2tL/3GOygizZGzowQI8qWbvSw3wKMWniU/ILis29clSBUslnTQ8yNmxNI5ZtoKUDHenXo2+LMaG2jJIDz9Gm4U1IxBNRi4X+SpgMOI3OjzIiweeaYI326+hlzii0MEHou9s017oy8YR16OcDyps8XJr8hC785UKWVfhfa60rOx9Q0tnLAykFL21FIs1utCXUn06c8KMUklGy/2H6a+kGOheac7GJwgRr+QWh6XR2hCGpt15GT6RE0idryLGKDnXd9IKk4pcUGJJc7O9Y4j2bLDSa0YL7WYlLOz6EqvNBPHV7WvVN80phWleY70HKjalkrsanqrb/I/dsLX6yNwdogF4lsnZ9mE8+KaXEp34UFFv43J1SfWhND2MybD2Clm1YSgMdf6Wjb9mzWB6pSBCqRGmp31fzkErfr5SCltuSBl+HnLbkHnjzdkd3Uhc1oTk+eWRTmYG0pLU68YQmNOF64TKq5ItjyUxNn/rtjyEZEX08M5qc8xr8ozAZxW7pQuqCujTOvQgZpxxp50eRUfYm+ZxRqKJBqCyKjvxiQiIeiCesRLr6+qSvjL/q2qTGz9mFgk96w04r5f7Lh3LQ9adIMunRwpak02UTfbsQWiYlR9wl1z5DaH+ul1tltCYxFYI0iJbbahBfx4m25Op28pZ2dFcnUZM5lHf2voRaq/NIaDKBCpe9J9PFsWakpt+P9sfIiOgjnRntLLfrC6P6Kl4QyqgOiQ/NaSIkgfE4cpfTWpK2vy9V4lcjlxN5tS+mkf+uqTR83Hq6XZi33MzHtMxGg4SmE+j6RyKShtOukaNoT2Qe50iPo5cRbxQYQZ5OZ0cYkECnPx18p3hy8j/lBRptlE+TvEJBqJgC13aiavw8+mMp/U9AdX93V9IHUD5UnK4/MkoK9aMnbzKJUq7TxGYtafbt1ByXDaMzf86mNe4FjZZnvmcSnznURCgg43Hucro6pdH+vpWIX82F8s7e/WnX1OE0bv1tKlz2voxsNIRkOuE6fcred9HIUXsor+ydUW0qNDqeqWi4WC/ce85Bd2A32OcaTC3Fy7BXyORXQ408J7qujBYj1+O/kYW7bobPHux7KIXx+AFwUIvDlcXLEO68FIvryr+O5NZ8OE6vgkOB69A2v3l+Mx7D0ycRQqt2cChogLSiKnWAcw9D7Pk3CjKSwOfsGbyaPBWFmdKTS7iLS6G10dNlqJISVRABDNrWLaVrqQahbl2Y5NgmfXUbB85qYeLaIci9EJkAWoamKN6sfULo1jXOtVW9WvVizLv6Af77Z2Li5aqwbaqHustOYkG7HKkU1kSnKSvQuzKbAJTJC4dYr3t4zuliYDd75M7eXyLsVSb41WrkvcBC5RYYuf4/FC57z4DPnn14KDXG+AEOUIu7gsXLwuG8dDHyyN4ZFceCUKbESOPj8Zbjo5qeXu4HTRaBK9eCwdV0QdeWOSM/MYJObsZxn0hEx7+HrtNCrBhspuCUMBnwO3keL2GKCU5qcJu/DpJeq7DYvnqx16jlYjxx7wXQuJ8jan05WWoITm/ZhKMPga4LN2JEk8L+pCqhvXMP1Nq9A69lBIn3GZx5NQlTCxGF8vU6Y/b2zoW8LlNcwpqdMGVFb5SvWE0LnZbewpOl+e1TGVqKrAjFfMekiI9/C45fDXp6ufM8WcQVXAvmUNOlK3Jn70E4ufk4fCKjEf9eF04LV+S9WlhOGX44ef4lYDoBTmpumL9Ogl6rFsO+ern6ETLZsCCUKTECvRqoxpchMCIC6Wj7zTypqbc2YIePEDauk+GUq8BTg2HjFtA/vgV/HnqNVo3nK35RaTCuXA+HTMMSb3xDYDF9JeyUtKRgiqcnHnEG+LmdOYSQIe7makyYcxyvxQkIS2qElplFO2+lDv3Rw2gXtr+SgSTeOHPmFSZNNWXzMJYAiUSCx48fl3UyKiwdHR3Ur1+/rJPBlDgB9GpUA18WiIiIdHzbhJSKWxt2wEdoA9fJTsidvRuicQt9HN/yJw69boXCZe9XcD1cBg3LN/ANscD0lXb5L2XLqL6y7g/AVGDSUFrfUZv4Wg60/FFWxyBx6H4aYqZJRr22UlCeXeYk5D3bnIRCM5rsoXi/OmnIcrIVichilqfCUzKJL4yi2o2m0Z18LyMm93F1SKjTjw4kvSXPNQOpi8sGuqeUEZkf6eq4ulmj5Dusp/Avff6KumISI1doaGgp9Zv9Pv969uxZ1l8xU0qkoeupozaftByWU1b2LqbQ/UPITNOIem0NymOVQPo8766QhGaTSfHsXUohy21JJLKgWZ5sSqaKgtWEMiVH0BATd+7CC5eJWNLBGrd7OUDv7X3c9BfDauRB3FrwE+rn1QeTi4GXTxi4Kv3QLld7jrz93yHw2DZs3LgWvrDA/ME2ufspAQAXhzOLpuNAqDRrU4I/kuKEcHWJQjXel60iNB+zBfO7VP30T2ko7vjEgbSTcH5Id7yxWgG3fV3k9AUsCg2069cTtf/dikgZQeJzFmdeT8YUE/aKr2wmJiYIDg4u62RUWNrayuoszag6QcOJ2LnrBVwmLkEH69vo5aCHt/dvwl9shZEHb2HBT/XzWCUQ4GK84BPGoUq/drmb6+Xt/y4Qx7ZtxMa1voDFfAy2Kc8rtjHZsSCUKVHCegOw6V4vzH/si4Dw9+BXm4SVLZuiVkF5SKoXPB9Jod66HRwKzG9kCLt4FCGmNqiZlgJBs74Y0DSvR1sNNUzMYSGQfd3CRYTjerAGTC0sYPQ1CBXCWEeUtU/CXdwL4WDYpSV0kv/DuXPn8WhWFxjkWk62aDTa9kPPOjuwJUIGEn9ukp9iUux+rMolwasbW+G6yAvWBw5jQjkcCaCmpgYLC4uyTgbDVABC1BuwCfd6zcdj3wCEv+ej2qSVaNm0lvwKgGxSvTzxSKqO1u0cCtwXsjBcPBoCU5uaSEsRoFnfAcgze2fKn7KuimUYecTXx5OJQETWS4IUnhRe7DGF6gtF1HxBfhMkyzlOgeb41ONDqLqgOg05nkriuzOokVCdrF0DlDBh/Rcf6foE069N8podN3yau1ElmuPTKezqBvq9Uz3S4vMIal1os6oujsAwjIoT0/XxJiQQWdOSIIVzd/KYUp+Eoua0IL/VTZhyp/xVZTDfARnCve8jGnVg79hAwep6KZ7dvItIqgWHjhZfj5FFnsTuC3HgipWeDPjf9cN7UUs42FeCuu0IDG1JCPh3Pc4nF+vE2WjAoV9P1BUAAEHsfQZnXhUy1VwcLvwxEM4zj+N18W44x3k/4k1aHQz/zw8nxxpDwONDIGBZB8MwRSALh/f9aKCOPRwbKFilKX2Gm3cjQbUc0NHia+6OyJO7cSFOmZkdSUt6tQAAIABJREFUU9pYScKooPfw8Q0Bp2uHDtZZHYbSPBbCsbY2qpr1whrftFxHcRwH8NSg9rkVnUu8i21uH2Hb1aB4D7rsJe7eiwDP3A4OenxAYI5ff+8B3bijWLEpAOlhh7B85yNkFOcaANTt++FH409j4r80yRcme+USzmHzuuO45O2Ny+tnYtRAZzj/MgmrL7yEpDgJ41eHbV9ntKlTBXo1qoIPHngFH8UwDJPbex/4hnDQteuArOw9DR4LHVFbuyrMeq1B7uydw6fsXQ2iz/9OvLsNbh9t0VU5HfOZMsJ6VjCqR+IHrwdi6Pfoj85f59HmkBL2CEGxaUjhLmL5xiuYeKAfNL4eJITl8ClwdhuPXb85I7WDMSob2mPE1F9goUDH93yl+cEvmGA0vD0aCwGAD6NfVmH5GT9MWNIRljfHYceRQXl2wleYuh369TTB1n/CICUxvM+cxevfzBU+/IOnB/zEPGikRiNKux/69BZh/bTVmHPsBt7eeIjVDurg4s5g0fQDyDYuSz5Rc4zZMh9fxmV9xWPhp3xixNx3h7vvM0TFJyE9gwN9/T8+qrQejrnODcswfQyjGiR+Xngg1keP/p2zFnPgUhD2KAixaSngLi7HxisTcaBfVu4OoSWGT3GG2/hd+M05FR2MK8PQfgSm/mJR/HyXKVMsCGVUjvSpF/wSaqHP0G7IioH4qDXyJCKdnuPxnvEYm1QzV+2moN5wHA7+AaFPYyEyNkc9XcWyJ/UeO/G6Rz47VB2Azb4twdVtkrVSjbAhfjsehK4vUqHXqE7uufCKRB22/X+EydaNeCEliL1P40yUIoELh0TPDRg79xQS+WaYunkvFrdVA/ATDJ+ch8OKUFy7+hRwaA6o1YCJuQWyjcuST2iMbOOymDxxiPNYj5lTl+PooxQIdapDU5KIzKrGMNDiAzwBtEx7YsG4emWdUIZRAVI89fJDQq0+GNot2xsuvxZGnoyE0/PH2DN+LJJq5srdUW/4YQT/EIqnsSIYm9eDgtk7o+JYEMqoGBleXHJHWOOh2O6Yc9ykAJUQiiP+Vli11V7+G7CGPhq10FdymjRgaN4k92aBDkwa6Sj1Supt+uFH083Y8FwKEnvj9Nk45D/1dwbCDo3H6L3pEIn/z959x9d4/QEc/9yRIfYKofaOvUMIqhqjaINqq63WqFmjVTVau6hZrV2z+Glrq71niCCxV0iESGLESEJucu9zfn/YJJLIzeL7fr384eZ5znPuveee5/ucaUKXszb1Kj/+ZIwULpQfPWeJDA8HQJ/DlY4/u1o1z28vjWuru9Go3Xzu1OzDPK/v+Li6IzeXfkadoTYM37qATwtZc8sBE3duReGQM2viW38s97l11Z8LZ04SlKUeH9VO4hAVIV6HxY+NWy9S+otZvFy9O8C5f/Cp/Cszasdewu0dS2H16l2kKqmHROozn2ZBz/YMXH4RU8haxi16QMeJ31P9xXro/kFm/HaeFlPH0dTxDS26djVp9UHRh0+HKoqDazdwXb3ieC2Sm4YmTJhUg+hQjYw16lH7SbOsmeDgG2g6WwqVkJY4a9NC/qFv93kEVRvB+nXj+Lx6XmzRk8+jKx9Y/mHwhL1xjMW1cDfgLJfDEzriVyN08xDcazSh74h+fP7tYhI7Z83iv5mpfVtRr1lX/g6wk4pfpBjz6QX0bD+Q5RdNhKwdx6IHHZn4ffWXHqTuH5zBb+dbMHVcU97U6l28TFpCRerTZSSTTRDrB7fBs0R5Gk5Yw6CGsbQwOrjQc7xLyucvRdlSo9UHFP1jEufNiqiDm9lloygR1+H67NT8uBVhf32ET7QNlerVI8fjv1kC2LL9NJasDWnzQV4AtJD/GN5/KRfiHRNagY5TB9BQ1h6Pg4XzC/9gzY0idP27D5WebdUx5CJXdgg6dYKbWn3yv3BD1a7MonXZb/GqP4vz/3WKd8MDy+V5dP7yL97504e5zW4xue+/3NEgMcu0Goq3pKv7LH7dWgz3hi8O9BUi+egyZsImaD2D23hSonxDJqwZROzVe0/e+OpdvESCUJH6DIVoPXkbrSendkbSBtvqrWhe9HcmnjejYu5xNya+wZn38dzlRYSxFG71Cj7Zcz5i71T+9LKh+k/D+LLAo4jFNjvvFCmGFl9LmsGJLLEEORaLBZSGpjTe7o6UO+zf44vZ8TPca9o//6eoc5y/rJHZPT/ZYvmI9AW6svLs+9zJXjQBO26Z8PxtPJuzt2anux2nFs8nunkfyr1Qc5v2TmbE1RaM+LQYsQ8AuM++PUeg6iDek822RQoyFGrN5G2tkepdxEaCUCHSGttqeLQoxpQJ54ivwRKAaF927b8BmepS/tG6e1roRgb1WoCpxW8sHFTtyYQqfY46dB5e5zUzFo6fXwgWpSMoSOOt7jPTIrgXaQEb2xe6FTVC1/7Dlrvv4NGu4QsT1qI4t/l/bD0RzM2IPDTqXZQC8V0nag9LVgZQok1tbs+fxpmy3/JD3dwvhf9m/71sOl2boXEFoaaDbNsXTtlO7/PweSSKwD1LWbQ5kCJtf+SzCvaxnSWEEMnqLb6LCJFW2VLNowXFE/iIaLm0i33+GpmynWBs0zZ06tASlwaDufLRYnb9rwOlkvyoqXFt9SBaNahFtxU30WJOMNmjHh4/LudyfLPs31R6J2rVLIY+aDtrPMOfvGwOXM4PQ7bg2Hkqo9xf7Pa2JW/pMkRsGsvIKVu4oo+/+o0+tI5tIbkpnFEj38ff07Hu600oij62nb2hRXn3/RKoazsY36U9gxbu5fiZq0RosuyWECJ1SEuoEGmQbVUPWpSYzNkz8bWFatzYvYcT5gzUG7iTVa0iOBcETiWKkdtqjVt68jUfxv+ajsBoNGLQa1jMZsyaATtrTv5OV2xxGTiX0efbM6qNG6Htm1Mk/Bi7vW9Tqsdatvd2i6WhWE/WAgVx0GLI4PIe9eMZbxt9bR/TJq3iWpUerBvSmtLPfdZRXD60lzNhD58Cos/cJPzyYbZuuo0B0GUoQLW6ZcmpB7Dgv30XfjnLk+fUMDrMzsyXI5bwQ36p/oUQqUtqISHSItsqeLQoyaQzp+Ppko9k7y5voozlqFs3F3Y58lAhxytPeD0G22cCTj0Go20cYw/fItlq0W/VWbpeOcUJ/zvos3dioHNBsr7qg7m7mz0+Oqr+3IhXDc2MOruJZb6n8ToaRvU+bSnxYprafS7sXsmK8w9Lh3YpiDt3trNqhS86QJ+9LvldHwWhWijbdx7HmD0bWyf9TWSrOVRxkqpfCJH6pCYSIk2ypbJHC0pNPM2pV0WhpkPsOnAXfRFX3Iq+9WFhKtCTqUB5asU7uPOhyD1b2He/HD3cC74yiLcv3ZgWJ//iuxuV+bFloUfH3icy0p6MGfWgz8F7P8zgvcfp/uWB7+kfmT625striN7dyXZvRc0Rs/jX+VcqfdCLse6HGVdbxoEKIVKXjAkVIo2yreJBi9KvmhmvcWvncrYGaTiUKEUR+TWncSYObd3N7eINcX/UtKnd8eWfCaOYsu48Uc8da+byibOEO5aj0jsGwIz/+qVsD0rkAqHA/X3bOfCgHO++l5/M9XvSvcYV/hw2l4sWE/4nznIn8UkKIYRVyG1LiLTKWBmPFqWIPQwNZ/fEzvScd5vqbT/jgyw76D98DdckoEi7on3ZtDOE0h5tqPKoufLB9vH0+PFn+rb+mt/PPTvLy0gx9xZUvr+RCYPGMPmPufjka8UHJRPbeRXN0Z37uF3iPd4vYQBDGb6dPgrX08Np3vhrZp+1I5PcBYQQqUSnlHrVfixCiFRkPvITVWqNw+5nH7x/jmXrUJFumI8PpWY9Tzr4bKZH4ceRn5k7l72Y0ns6xWYu4vMXFg61RAQTGGZP/oLZE79V5+Mr3A4kSMtLoZzPpGAK41Z0VnJmliEcQojUI8/AQqRhxoqtaFlGhm6nV9rt8xw+cwMz4ez5czV8M4T2hZ+pds2B7Fmylkw9J/JZLCvXGzI5USQJASiAMXvB5wNQALscEoAKIVKd3N2ESMuM5WnV0pltqZ0P8Vru+yyiX89NZHUpT+6Co1j5U10yPXuAMQ/v9h5Di4zSHiCEePtId7wQaZzZdyTdNnrw50DpjhdCCPHmkJZQIdI4Y7lWeATLT1UIIcSbRVpChUgHzGYzRqMEokIIId4cEoQKIYQQQogUJ6PhhRBCCCFEipMgVAghhBBCpDgJQoUQQgghRIqTIFQIIYQQQqQ4CUKFEEIIIUSKkyBUCCGEEEKkOAlChRBCCCFEipMgVAghhBBCpDgJQoUQQgghRIqTIFQIIYQQQqQ4CUKFEEIIIUSKkyBUCCGEEEKkOAlChRBCCCFEipMgVAghhBBCpDgJQoUQQgghRIqTIFQIIYQQQqQ4CUKFEEIIIUSKkyBUCCGEEEKkOAlChRBCCCFEipMgVAghhBBCpDgJQoUQQgghRIqTIFQIIYQQQqQ4CUKFEEIIIUSKkyBUCCGEEEKkOAlChRBCCCFEipMgVAghhBBCpDgJQoUQQgghRIqTIFQIIYQQQqQ4CUKFEEIIIUSKkyBUCCGEEEKkOAlChRBCCCFEipMgVAghhBBCpDhjamdACJEAliD2/7uJM5Eq1j97eXlx84E95Uo5YpvCWRNCiDdB//79sbOzS+1svFV0SqnY72pCiLTDtJWuxZsw66ol7mPsspHPMQtGXcplSwgh3hQnTpwgS5YsqZ2Nt4q0hAqRbhipNuIYB38uiyG1syKEEEIkkYwJFUIIIYQQKU6CUCGEEEIIkeIkCBVCCCGEEClOglAh0gPtHrdNGhFh91M7J0IIIYRVSBAqRHoQc5HTt2O4ejI4tXMihBBCWIXMjhciPbCrjGteO+zdisnMeCGEEG8EaQkVQgghhBApToJQIYQQQgiR4qQ7XgjxiMbtc3vY5nkRS/GGtKhbGIfUzpIQQog3lrSECiGACA5NbE7lBv3ZeC0Cv6nt6bHsFlpqZ0sIIcQbS1pChUgPknmJpjsb+/HZoMNUm+vLnM+diF57knZ+d1HkTJbrCSGEENISKkR6oM+Ag1GHfSY766dtPsm0YQu5nL8N3Vs7obcE8L81iuatC8tMfCGEEMlGglAh0gUb7Aw6jLbWDwujvebz11EzhZq3wdU2hM0jRuHvMZIvC0r1IIQQIvlId7wQb7VovFeu4xJF6OFuy+LBkzA1/5XhtXPKE6oQQohkJUGoEG8z8yk2b/fHYl+O64fO4PzdWGrllvBTCCFE8pMgVIi3mMVvE1tPQ5k+U5kzrLYsySReEM21w/u54liTmgWldAghrEuaPIR4G2l3OP7PWL7pMJFDONPq0xoSgIqXRO0bTCPXhtQq24SJZy2pnR0hxBtGglAh0gOrLtFk4eKGfzlTpAZ5Iu5hqPARbcpLp4h4USTbFyzlXLQCTY/eJrXzI4R400gQKkR6YNUlmgwU++AbPoxay7Iz4NykBWVSPQa9y94J7Wn7/T9ckga3tCFiO8s3BGPR2VD8q0F0KJZWF+ySsmNdunTwT7wpJAgVIl2w9hJNZs7v3MdllQ/XBs5PBodbLq9k3vqQlN8pKWIrM8YsZtX2U9xTKX1xEZvwbcvZGKowFvyc8cMakjW1MxQXKTtCpFsShArxltI0DXS22D7qZtVu7WPm4ge4NMqb4hVDtK8nR+7pcKxWi9Kp3ior4C5blm/mhi4fbX4dTfM0vGKClB0h0i/5yYp0wXzjJLt3H+XClSCu3zOhPdfioSNT5U/p27Kk7PCTYEbKte+Nx+LuzO3sQXj9QmR0qs3XfT7H2TblcmEO2MHCVd747/mPS2Yd7wRvY8wwLwy5avF1N3cKyBdqJWbOrpzAX7uv4vTJRL6t9XRYR8TB+YxfdZSYCj0Z2a7Uw9/QnS0s3xxG7hZzGNsm5R9KEkLKTgoyw8oJsPsqfDIRnik+HJwPq45ChZ7QrlTqZVGkTxKEijTNHLSDiT/0Z/LKo4SaYutr02GT931+3fiDBKCJZCjanr9PNeHc2WBsCpWhaPYUjD4B0Lhx6QyBYaH4HA/AbMxP6eIZ0CwahszZySJfqBU9wHvRSMaur8iYHs9W+2bOrpvMmAmhfLpy7JPf0O1Ny9lGI0ZO+Jy0uXFWIsuOJYxzPsFkLV+WvMmw8+0b7wEsGgnrK8ILxYd1k2FCKKwcm2q5E+mYBKEizYo6OYO2jXvz343c1GgziJ+aVqdo5Gr6DvDh3Ym/81UZO3R6B/KULEuhrNa9U2q3z7FnmycXLcVp2KIuhd/U9YvsHSlVyTGVLq7H6d0eDHfdTJcFv2PI04je40bROLYgwRTCqRN3capcihwSnCae+SIX/GMwFKyOS+FnP8C7HPe9hCXTe7xbJ+Oj16LYs+UUNUesoFPRtPphJ6LsYObE6MZUH+qDU/fNnJ36Lmk7DjURuGMGw4Z6UnXJ3/RIA08B5ovgHwMFq8MLxQffS5DpPXhSfKxJg3N7wPMiFG8IdQsnwzVEqkr90i1EbMJ3MvDjPqyLqEr/9YfZv3gUPT9rSdOO4xja8Bp/Td2JbdWa1KhePvYA1BLGucOnCDEl/tIRhybSvHID+m+8RoTfVNr3WMatFJ+p8/YwX/DiSKiGfaVaVI01OjCx4/taVKpRkcajT2BO6Qy+BlPgDn7rUJePpwWm/CSv2Nw+wlE/C5kquVDp2QbvqEMc8I3CUK42rtkev2jPBzOOsKZbqTTfShF/2QEwUrR5V7p92YnebSsS10pT90P9uXwjKplymhD3ubR1Ct0bOlO20XfMP3QbXUp3TsTh9hHws0AlF3ih+OAbBeVqQ7Y4zg07B6dCXuOiETCxOTToD9ciYGp7WHbrNdIRaZoEoSINsnBq6iBmnnOg0Zgl/PKe09Oudn1u3BtVxXJ8Gf8ejSscedjyUbFGJWp9v4NExaF3NtLvs0EcrjaONXMG07tfO0reu8JdmXWbbG57HeKs2UiZmjXJEesRNlRs25tOX3aja/OicQdG90Pxv3yDVA0jLm1lSveGOJdtxHfzD3E7MVGE+RgjXLKTKVOmBP/L4TE/QUlHHTqAT5SRci41yfTsJc8d5Mh1HYVr1KLgMy1cBju7dDG8Jf6y81DGSh2YvGAGfermjOOmZ2LXYDfcxxwmOr6LaiGs//ljPPot54o1nzC0B1yPKED7Bd6s7FIIg06PwZDwW7T52Ahcsie87GTKlAOP+WEJSvvQAYgygkvN518/dxCu66BGLWItL+YT0LgiVKoFOxLZILCxHww6DOPWwODe0K4kXLmbuDRE2pfWH3TF2yj6CIuXHCamQCf6tS/6UuVmnyEDBkswV66aoUZsRfhRy8dFbwq9ouXjZWZOThvGwsv56Ti7NU56CwH/W4NqPvT5Lqg0LurwCOo3GIZXRDJGzoaCdNt0nunvJbVjM4rDB32J0uelqkvxOAIfPTnr9mFG3VenZNo1GLfvsrD0+CTqvDL20whZP5Recx/w8ZRxtC5grWdxjQfXIyjQfgHeH42hapN56A2GhD/p651o9O1wstxIeGRjKFw9AUeZOXPwMDd0hWjr8s4zn7HGzYNenLVkoWXtyqSRRrdEiL/sRJ1cybTlXlwOCuVudneGjPmUpC53qt34j2mTlrOzckGaTD7IQa9L3LbNj8unfendrOjrd/Xrc+LykQdgxjdXVvToErUipt6pEd8Oz0LCi4+BwtUT0IduhoOHQVcIXN555nUNDnqBJQvUrhz7qcai0LUbeBeCionY7MB8EoYthPwdobUTWAJgjYKh0h3/xpEgVABgCjnFibtOVC6VI9VbQLRgTw5c0Mj+8fvUfmkspplLFwOJ0ecg1yuWjXnY8tEhcReO9mL+X0cxF+pOG1dbQjYPZ5S/ByOHF0xXXQb21QYw++dtuA3cy10NdA5V6D51GI1zv94iz5rpHtf9j7Fj+SJWHAomWgEqBlOsE8USyXyeg0euo2VoSq1Y+lMjjy9j+gpvAoNvEJG3JaOGfUj+pH4Z2g3+mzaJ5TsrU7DJZA4e9OLSbVvyu3xK397NKPr6UQQ5XT7CAzD75iKrHnSJiiIcqdWuF7Ve9/Jx0a5z4OA5LJlaULPic52pHDrgi8mmIrVd0uGg53jKDoCtU2kqOS5n+i9LuVKtNIOtcNn7+3fjHaXDPjyIq5lb0bKFDZP7jmPAsh3c3HGUca5WGHGaqILzkN6xFu16Wb30oF2Hg+cgUwt4ofhwwBdsKkKcxScjdJgMiayJ8ZoPR83QvQ3YhsDwUeAxkjQ6SU4khQShAkw7+L6WO9ODKzPc25OfU3kLR3NoKDc1PTly5365gFoC2LztFFqedjSq8nLbTVJaPqK9V7LuEhTp4Y7t4sFMMjXn1+G1yZnuKj5bKnw3i+FbXPlu+220+8dYvSmcgUs/S0IA9xmdvuvPnuEf8dGovYRhwhRvv2X8tFsHOXTOjLFcDWrGshq6fd5y1Ciwllmjl3CtQQ1GJ/2ScH8/u72j0NmHE3Q1M61atsBmcl/GDVjGjps7ODrO1QoTVxLXipWsHnhxwDcaQ/ka1Hg2WDCf4uCRMAwlXHBxSneFPN6yA6DP6UzdqgWww0jBGrWT2KOhcWv/b3QZuIpb+mL0mbaQ4XVsgQ9xOr0O1zHn2LblLLhWTMpF0pwHXuAbDeVrwAvFhyNhUMIFXio+UbByGnhdhtC74D4EPi2WwAtGw8p1QBFwt4XBk6D5r1A7p3Xej0hbJAgVYFORtr07EXG5Os2Lpn6RMOTORQ69heMBAURS57luwvBdvzHby0iNYb1wj6Un6fVbPsyc2rwdf4s95a4f4ozzd4ytlTtdtYA+x1iGnjNHs6VWDzbctBC0oh+9Ftdh2ZdJaNXV58RtyF+M961J5/8eYDIlfUBczJFDHDfpyVO5OkV019k2eho32w3hk0IPowWDYxmq5zESoRkpV68ejkn8QrRb+/mty0BW3dJTrM80Fg5/WL4+dDrNOtcxnNu2hbNmVyqm/s/AasynDuFzB3IUL4XTM0FY1OkNbDtvIUubapRNh+83vrLzkMY1Ty8ualloVbfKk7pEC1nD0O+WcM789LgbPmGEGIfR7mqOpw8QNhX5Zvpg3ssazcWl3em0MBKbKBO6nLWpV/lxakYKF8qPnrNEhofHkX4cnqRvhQ8kmZw6BHeA4qWeH/d5egOct0CbarEEErZQuhIsnw5Lr0DpRDRBm0/Bdn+wLweHzsB3YyEN75UgkigdVj3C6vQ5qdtnBvEMuUsxhoLN8XAdzv6tM5l5vDUDK9gDYDq/mK5d5nG/8ST+7Fch1sL72i0fFj82bT0NZfowdc6wWIYBpD+G4p2ZNn4LtTqtIsQSzOr+vVnotpyvk9IcZCjM54M7MHnjb0RHJzUItXD11FluWHQUiTrDrG8GMeN2dzb8+Gz+ovHZ5cktfVG+ePeZcX9aCGuGfseSZ+7y2g0fwkKMDGt3lRxPowgqfjOdwe9lJfriUrp3WkikTRQmXU5q13s6DtJYuBD59XA2MpxwLfb0Y/c0/bTq9vHj+FsU+qAr3NDA6c459q5awNw5i/GJMVCuaB6OTBrJtbaDaZvksQ4pJSFlByAcz/3HMNtVp67rMz9q21wULuOM4cle8xoB/ts5ZV8EZ+f8T4NQYyGy2QBaJDcNTZgwKZDvq/xDxvfrUfvJQ7CZ4OAbaDpbCpUoGkf6cXicfhp2/DhYFARdAQ24cw5WLYA5iyHGAEXzwKSR0HYwT3ta9OBcFwrYgbEg1E7EWE6/TXAa6DMVhtVOhjck0hQJQtMljZB9C5i/6SRXQm4RXfYbfu/rCv7bWDhnOZ6BRmp0HkIPN0f00UHsmjed/+31J0PDHxnToeIzXSqRHF82nRXegQTfiCBvy1EM+zD/k5ayyOPLmbHSm8CgUO5kbMDACe0pefMgi2bMY9OpSPK3HMToL8paf809Q0l6zpmLX7uejKhflT3NXcl98zA7faKo3OF/7PrpQ4rHOYsi9paPuGncOb6MmVOmMPEQOA/+9Pkuy3TNQOEv/2DSpkN88W8QltC1DOg1n/qrOlEkCXGobdXP+bjiVDxNJnhurvVr0Bsw6MxcWDqGpR3GsWLRF8/nzXKRXfv8UXm+pEHlZ79NW3IVLoPzM3d5LcCf7afsKeLsTP6nUQSFHkYRRN400GTCJAK/r8I/Gd+n3tMoAnNwMDc0HbaFSvCwM+Dl9GP3OP20KoJ9u72JUgptax8qFRqNjSUnDX6Yzq/9rrL54yWcmt6DhVNWMTPdBKCPxFd2AExH2H8kHINzXdyeaU7T53Cl48+uzx7IhqvzOZilPYOH1Yml3shOzY9bEfbXR/hE21CpXr2ns/EtAWzZfhpL1oa0+SBvHOmnUxGw2xuUgq19oNBosOSEH6ZDv6vw8RKY3gOmrOKloT7aNfC6CFlaQSwjp16i3YFlM2HKRMAZPq2RLO8IzRROpHIgs31qz34QACiRLkVe9VVbfnlfZdcbVP5Oa9W5FT1VvRrNVIeO76oCBp2ydZukLt3cq0a2rK8+6thGVc2uV7qsrdSSe8+mYlahp3epPz8vpoy6DKrR9GvK8uxfr59Ru+d+qYobUTZVh6ndW0eolnXd1Zcdm6mSGXTKkK+jWh+VnO/ygbp2fLfasGat2rT3uAqKTMg5d9SSVtmUPkMjNf2aJd6jzX7/qVl/e6ntA8srG5uqatjxmCTnOllEbVFd3rFT1UacTPSpluAVqn1ho9KBQp9LNZ3pp8xJyoxJeQ2orN7/I0jF/wnHl1SIOrFvvzoex5druTZDvZ9Br7K1WqzC4kkqan1H9U6pvmqv6RUH3VqoPsyiU7Z1J6iLTz4Es7owvo6y12dTzWYHJv09KaVifIaoSjZ2yn3WdSuklgSmXapXMaOyKddHrdi9SW0/HKjCH79Byy11avcedfpW0kpDqomn7CillPnML6qGjUEV/XaXelWxUCpKre/4jirVd+8rjotU/33tpPQ25dVg76fGkN4MAAAgAElEQVT1RPjO3qqkTWZVc7i3sk51GKMODy6vbGwbqRmh1iiNicWTf6ZdqGJGVLk+qN2bUIcDUZZHf7PcQu3eg7pl5rlzHv+7swSVTY9qNP3pOXH+M6P+m4Xy2o4qb4OqOgwV88pzEu+Oz1zVs+X7qsmHHqpl3VKqSJXWavi6AJVGa/y3Rjp79BWPOeQvT8mM0dxXduQJXcyAPW7M27uOuVM6UM0e1I29/NJ9PrlHrWfl7Il8WckI0VFExTybigHHMtXJY4xAM5ajXj3H58YLGnKXpoajkUhNTzbDXn6Zac+ANRtYOK03DXLq0WXMTOZknX1hj1N5N5q0aI57nfLkS0gLZRwtH3ExFPuAbz6MYu2yM+DchBZl3rzOAX3eD5k49WuK2ehAu8mmQT2YeT6+Fr5XsaVcjco4RJtI0Pz46EB27zoV+3qttnko51qb8nF8uZF7d+FtsqVK/fpYo8P7vucuvCKMlHKr93RdzIi9TP3TC5vqfRn2ZQHrjAO2WLCg0DSVqovVW/wPcCjQgn3JajRyc+fdqgXI9KTLNAfObnUpk163oIqn7ADc9TrEGS07tepXTfoSVNG+7Np/AzKVoXyJh/WEFrqRQb0WYGrxGwsHVbNSr1A4fn4hWFQoQUGpu9WB/wEItEDJauDmDlULPF1cXJ8D3OoS5w5mR/ZDuAHquiVgQXIDfPANRK2FM0CTFonoprVcZt/2k4S/6pCA+Xz1wWTs+69iw6oVrN61k5FF9zHik3ZMOpUetr9IKo3bgYHcSWRx0m75E5DYkxJJgtB06y57d/sQjYUIx0+ZNqkNRW3BfOok500KS+gdSvb/gy7lHMAcyOUgDWPpqlTL8kIy0T7s8ryFvmg93i3+Ym0SzbF9B7mhgZaxEb8s+AGX7HrMJ3axPxQc675H1TS2uKDF/yCHg6BAbTdKJLAWM5/fyb7LinyuDXB+fI7lMivnrSckTWx3k1R6cjYbx4yupbDVgRa2lZ97TONsEupee9ev6eySJd4Z4Nr1nYzsMAyfDPlf4wZt4sg+b+7pC+DsdJxf2nVirl9SgudofHft5waZKFO+xMObnBbKxkG9WGBqwW8LB1HNSmNLwv38CLEoQoOCUjUIDfP05JTZSIkKFciQivlIHSa8PY8Q5diU1g2TOGwEsFzaxT5/jUzZTjC2aRs6dWiJS4PBXPloMbv+14FSSX5+1bi2ehCtGtSi24qbaDEnmOxRD48fl3M5KcU+CTw9wWyEChUSeaLl4dqiFAC3Egk8xww794HKBw2cn758eSWsf9WOS4a8OIbOpnPvv/GLdcUOjaurFrIhNIoY86MvSe9Eyw9rkSHSmw1bghKYwfRKI2TDD3z09TzOJXJFk8jTf/J1ywFsvp6MtVhqN8WK1/Rgo+qc36BsyvVXB570RpnVxQl1la0+m2o2+/KTbsWY48NUFRujcv7R66WuJvPpUaqGjUHl77hePXjxGuaLakJdW6XL6K5mBD1Ozawu/Fpb2eiyKY9F8XWQprxbC1qqzIZcqt2K8Cevhe/6WdXNn0llKfqBGu8V/tI5Mb5DVGUboyrRZ8/D7jTLTbV36ii1+NSrO/BSVBK645+4t1v1q2D/qFs+m2ow6VSydkVZQjeq7xo0UaMOvvyZJ0yYmveBg9LpM6i8Vb9Q04++Op14u+PNZ9QvNW2UPksRVaZSbdW649eqRfUyqvKHQ9R//tb5ri1Bq9RAj/qqVPaHwx90GQur2h/1V8sCUqPLO1yt/MJR6Q35VccNL/2633wxvmpIZTtVqOtWlaCRPK9kUcEz3ZWDLqNqMjtERd3yU8eO+6nr1v5YzSYVZYpRZsvDa5pjTCrKlNJl51GXdzjqC0eUIT9qw4N4utNf/HcL1TIzKlc7VPgz6f1cF5UpC+qD8c+8/vhfDGpIZZSxBGpP1MPXbu5FjVqMMsXbHR+jLi5sp9w+mafOxvJTjgnYqmbNWKcuPPN9hS/6SGXU2an3Z4Za5VNLqyIO/aLqFWqgJpx8nTouSvmMrK3eqT9GHU76jyhWEoSmUzHeg1R5G4Mq0nPnM+OQbqr5LTIrvYO7mhn8NGg8M9pF2RhLqr4v3Z0t6tqM91UGfTbVanEsAWXYX+qjLDplU2usOve4HrSEqj+bZlQ6+3fV74GpMV7pVaLUpm/eUTZOX6pVdx6/ZlFBc1uo7HoU6FX2z5bHGmwvaFtUOWQupZp27KK69RqmFvncefGo1GWNIFQpFeH5k6rqoFOA0metp8afSKZA23RS/d64pGo87UKSxp/GXD+nTgbcS+IY1ocswTOVu4NOZWwyW4VE3VJ+x44rP+tHEcoUZVIxD6MIZTHHKFOUySr5T7TbK9QXefVKn7e9Wv26zwHpmPnMGFUrS0X10yFrlPF76t9Pcii9TU01+kw6HUObYA8DvdsrUHn1qLztYwkY4/kXtQn1jg3qy1VPX7MEoVpk52Hdkx21PJbA9uICVFEHVKmmqC7dUMMWoe4kdEyo5ZZa17mcqvr9jnjHjysVoTZ1KaiM2RqrGQFp7T5mRbe3q97OWVXVoUdfMdY5RgXvm656DvifCorto3jgqfqXy6TK9tmukuOuKEFoumRR/pPqKVt9DvXJv8/MNIpcq77Kq1c2NUerJ/Wk+ZKa6GanDEV6qB1RD9Tls/7PpHNP/dM2u9Lbv6v+uPpy6XuwsZPKbzCqkt/vf1qAw5erz3LplU3VYSrNzeGJs+XDrO5dPaP2j2ygysU58eCBCj3ro3wvhsUzgSGVWCkIVeqBOjzCRWXSoUCnstQZo45Z/Q3HqJPj66mcFQYpq9z/reTev5+oHHobVXP0mdQJClOY6fBM1W/IHLXj4tsSgcaoU/N7qC8HLFN+UcFq5dfOqlLfbeq2NZKO2qa6FzIoY8nv1L40VKaTx8NA7/BM1JA5qIvhiWwFVSjfISi7Qqitkc+/br6HOrMf1aAcaq8p9nMfhKJ8fFFhcfz9VWGLJXC2aparlOqx5dXfetSx0apOtgLKY57fGzwxKVLt7VdW2eX9VP17M7a/x6jgA/PVjy3LqKwGnbJt8LuKJQxQSllU8PyWKrtdOdV/n/WbQ2VMaLp0h717fTHbVcOtztNlZqJ9duF5U0/RuvUp+mh4p3ZrBzuPRmNTuija7K/pPOvi02RMR9jnfQ99AWecjv9Cu05zeTrkzsyJPQe5rnLgUqfik0H9poPb2HcbcpQrzr0/u/DVRO/YJ5ykAovfRrZeLM0XHdx4fqqCAQfO8Y9PZX4dUDuOCQr2OJaqRMWi2dPhHtqJYU/VH2czpG5W9Cju7R9N1/G+Vv0OteAl/Dz2EM5fdkzQ0iwpw8ShXQe4qy+Cq1vRVN+aNiXYVu3C+OEdaVA06eMh0wcdGTPZELR+MG3e78TqwhNYM64h2ZKcrsatncvZGqThUKIURd6Su2bVLjC8IyS6+Fhg41Yo/QW4vTBnzOAA5/6Byr9C7TjqBntHqFQRsr9G3aEv8Akdm9xh7sDf8I1jzLslcAU92s0n9+j1LPq62Bu7TqXl4hyGzj7HO6070/yF3aa0sO0Ma1KFet3/4sjlW0RoCvT6OCYJ6cnbqiMf5TrLrBELCbD2+GSrh7Ui+UVtVd0KGlSGuuOfdpMrs7o43lXZGAqqLluedjGaDvygyhhROtvcqmrHeepExDPphM1THzjolD5DXlX1i+nquSF3liD1x7t2Sp/dQy168hRlUcHTGyk7nU7ZO1ZUH0/Yr26lak9GAls+Ig+oP/qNU9uupeP2L6u1hD4Uc3qKei+HXgFKl7GmGn7YWt3SMcp3aBVla1NdjTyVdj5vy82NqmsJo9JlaaZmBb25bR/C2u6pXRM6qE/atFWftWunPvu0rWr30+rYuy3fYjGn5qseXw5Qy/yiVPDKr5Vzpb5q28sVsTrwRz81btu1ZO2JuL2klcpmzKe+Wv1y57E5YJnqWKmc+mTeGSstp5VWmdTBH52VjaGI6rkjlndqCVOXA8KUWSkVtbWrKmhA2b43XYXEWa4j1Jqv8iq9TVU19Jh1608JQtOlGHXzwjF14eYLhSH8sjp+8uoLXdGR6uqpuMa+xajr506qgHuxVwmRQSfVMf97z6+baApVZ0/4qztpIr4wq4BlfVTD8iVVZbdm6svhG9TlNzW+sHIQqpRZ+c1qpnLrH3bLO1Qborys0dMS460Gl7dReqeOal0amQtzb9cE1eGTNqrtZ+1Uu88+VW3b/aRWSxQhhNWYA5apPg3Lq5KV3VSzL4erDalYEZtP/6Jq2OhV7s+WPTeG0RL8n+pe2Vl98pff0yFXUcHqcnAaqaisybRb9SpmVHrHL9WqiHgOPfCDKm1E2TZ6VRCqVNiij1RWnVGVHeBl1SEMb2pLdOrQrrN/8WIOJGI5A2MRd/q0Kp/ICxnJWbwCOV98OVNBypd98UUH8jvHlb6R3CVfOuHpmfnK8tLKHLaOlCqXmLwmJwOFWk9mW+vJqZ2RdMhAsY7TGL/pKB1XBXP/yHi6jW7CnlEuZIz/5DhZLm5l29kYDFWKUSyNbCSUud73zK2X2rkQ4s1lKNSaydtakxZqYkOhYhTOoDiyezOeptY0sQPMZ5nevgv7Gi5l/xfFngy5urt+ED3P/cDagWVSM8tWZz62iR2BZgwuFahoH//xCVnuO3PFChQzruLEzu1ctNSglJXGNEkQak1aCDtnjWZCIha/tW2Y+zWCUCGswFCIL6ZOYrP35/x99QE+k7oxqsk+xri+fhj6wNeXc2Yd+pyO5HkbBl4KIdIWgyO5c+qxXD2Bb4CFJqUMhK0czoidOWj58S22rV4NgDJdYf3YzWT48fdUzrD1hfn6cNGsJ2eJUjhZK1gsWpqiGXT4nD7MkftQKrOV0rVOMgIAYwV+2n+Tn1I7HwDadZZ3cKHroWYs8PyDD5I+Oj+uC3F9eQdcuh6i2QJP/ki+C4lkoM/3MZN/38yBjxcS8OAYv3UfTtP946j7WnNZLNy4GkykAnuHjFbaPUYIIRJB50CmDDrQgrly1QylzBzcsoewmGvM6eTBnGePtanGyApv2jYO0fj7XSZG6cmaI4f1diQyZidHFj0q9DIXA81Q1jrhowShbygt8G+m/xvAnZxRGJKzW1QL5O/p/xJwJydRsVzI19eX1Y+ePN9G/fv3x8EhIfuNphY9eVqOY8InW2m7+BpGWzv0CdqLMzaKe/fCAR1GW5tXVn4mk4kxY8a87oVEKvrhhx/ImDGe1nLzMUbUqc+4kzGvPu4Ztu//QdjKrxN07IgRI9C0N2I7M/EaXlkG9XbY2uhARXDvrgLsaTzTn6hZRoyGZ2slDUu0hs72TeuyUdy7G45CR6bMWawXhOqykCWjDlQ4t29b77cnQegbyULAqpUcMOWkyZBBvJ+UQX7xXSlgFSsPmMjZZAiDYrmQn58ff/31V/JlII3r1atXGg9CwRK4ib93hqIcmzBu0VBcX7ubRYe9vR2g0CyWV25XGR0d/VaXi/Ts22+/jT8I1TvR6NvhZLmR8JuVoXD1BB+7aNEiLJZU2stSpLpXl8EYzBZAZ499hoejHfVG21iCMT0G2zd1va2H79tiScLezC8xP/pcbbG3s97nJkGoNWkh7Jz9J7tDEl45Gks056d2Va2bD4s/K1Z6Yf/uOCZ2KJKMayJa8F+xEi/7dxk3sQNFYrlQ69atad26dbLlQCTR/SP8+kUvVl4vzNf/zqVL6aRUCQZy58mNjQ6iTSZe1aCaOXNmLl26lIRriTRN70itdr2olUzJX7hwIZlSFumeZiIqWoE+J3kd37RWzoQwkDtPTvQEE3kv/JWNAYmi3eNepAZkI2euhExlShgJQq1Ju4HXvzOZkZiJSe8Wt3oQarmwnNVnqzNoZzdKJudv0HKB5avPUn3QTrol64VEstCus/77dgz3tFDtp7/47cO8Se66yVKhAkWN6zh/+xa3NMj4pjY0CCHSJi2MsNsa+kxlqVjqbQxxjBQrVYwMumPcCA4hBqyzAcv9EELvKPS5SlLaWrOdkCDUuozlGbAjiAGpmgkLfmu2Yeg1hV7lkvfrtfitYZuhF1N6lZOClO6Y8ZvbmU5/+pG92XQW/VwLa+yrY3R2o3beXzkbcpWrZiiYZnZMEkK8DbS7QVy7p8hQz43aaXskVLJxqFWbSjYrOeB3mktmKP+KG7SKCCdCgYp6wINXpBl95jQXYsChkgtVrVivS+yQzkQfXsDQxScp1n4snSo/+vruezFv5N8cydSQaYObkqvl7/xT3Dlps5OjrnF461YOnb9KaFgk0doznav6LFRv358Pc7Xk93+K4yzToNOdiAMjaff9OsKKdWLFnE6UtFZN4FCP1k3zM/evM5y+C7VzWyldIYRIgJhTJ7lgyUidj1rg9Jb2xBgKNub9SgPZe+YIh29D+Tjr4QiObPUkRAPLhcMcuqVROHdsH5rGNe+jXLZkoE5Tdxyt+Lm+pV9RemUhYPtsJs46RnSep1+d+eImpk+cyraw7ICenKWdcXrdoEILYffEz6mcvzA1PLrx0/hJTBg3lYXLVrBixQpWrt6Mj6kUVYsa0OcsjfNrX0ikFi14Jd9+MYbDupoMXjSJD6xZo2BPg24dqKQOs3tfhBXTFUKI+Jg5u9uTa3la0fWT/G9vgGMoxWefuZIh0pMtu+7GckA0e4c3olKxwrw7/jgxCrSQv/miTEmqtBj/8uHaDbZtPUxMdnfat3nHqp/rW/sdpU/hHPY+A2VqU+eZwCHqzBkuarlwrV85aclr11jdrSFNB+4ke8d5eF25Q9i1E8xplYtMtYaz9cx5zp05yqYJHhSS2NNqoi5vZ/qUNVxOicm+0aeZ9lUX/grIRfNJixhUw/pLJxjLd2NAazu2L9tImNVTfwNEX+PwTi8C76d2RoR4w0T78u/qAGr0+iEZ18ZODwwU+eJbWjvdZcvf//HyJo621B6wmv0nrnIv2oxFKSzmaMKDjrN3aa+XUtMCl/H3HhOlvupLqzzWDRslCE1Pog6w42AkeWvW5el4axOH93kT4VADtyQNgNEI+acv3ecFUW3EetaN+5zqeW1Bnw+Prh9g+WcwE/aarPAmxGPRQXuZ+e17lHFuRM8Bk1iR7FHoHXb91I4B28Ip+c0c/vy6WJLH40Tdvv3yi3pHPH4ZicvBKcw6ac0lQt4EUewb3AjXhrUo22QiZ2WVISGsRCNk5UT+se/FxF5lZaxhjhYMGdwQtsxi4fmXKxqDXUYyOthjazSgB/QGI7Z2DmTM+OL4OhNH/vyT/Vk/Znh/V6w9zFaC0HQk+uh29l13oHqdak/He5rPsWv/FfQV3XBLypOf5TwL/1jDjSJfMbJPpecKmiFXLrITxKkTN6233MNbzBx6kHnfN6V85ZYMnLODgPsKZTrEmtWXSb6YRCNwaXfaTz6OTa2fWTShKbEO/UlUklf4s0OfWP+kL/gFM6aUY/X3v3EiKonXeZNEbmfB0nNEK9D0epJzHwkh3ibatRX8ODGcvvMHUyMB+6W/+QwU++Z3Rtfz449Rq2JpDU0YS8BChs8J5+MpE6zeCgoShKYjFvx27OaSrhJ1XLM8eVW7tos9p6FkXTcKJmXVhDv72eNrxtHNnZov/ICjzp3nspaZfPmzSYFJIu3GGgZ3n4FfiZ6sOnuJeW0cH36mysShNauTrUs+yncC7bv/Q1CeD5myaADVrPE4G+WDj39cYZSePM2nsPDTk/zY+x/8pUEUgIjty9kQbEFnU5yvBnWgmKxsJkSSabd2M7zbEopPXkQ3Z1mS4wlDSTrPnUOLk0MZsDY08Y1Ilkss6DOBsK6LmNoq6Uv4xUZiivRCu8aOnSdR71Sg8jNT/u7u3Y2P2REXt/JJ6n7QIu4RaQEb2xd+wFooa//Zwt13PGjXMBm3XnpL6HO35NcVCxndtSnOObLxnsfjmYYK06E1rE6GKFS7tZkf2g1l94PSdJs7my9i21XgNUQf3YXn/VdFs3aU/moOszwu8ccML2QwRzjblm8kVBkp+Pl4hjXMmtoZEiL9s/jz98QNFP9lMT/XyS5BzQv0eZrx2+ph2C38jT2JHId+e90U1pf5g1VDXXntjfTiId9XevHgEAeORaNzyEwmA4CZUM9p9Bi1ibvG8lQvc4ZNOwPjPj9iN0Pc3iFz1mI0n3CIF+ct651qUbOYnqDta/AMf/yqmcDlPzBkiyOdp47CXe6ZVpf5PQ/cH00yS5YuecslFnbuwIyz9tQdtpjx7jmt9KOPxmfdZgJs41td1EgB94FM+rZm0pYMexPc3cLyzTfQ5WvDr6ObJ304hBACDEX4bPSvfFHOGisdv5mMhdswY9UY6ieyByx7yymsHONOMvTCP/HWj91NL8ynj3Dsnob59nTaNTxI7kgT+T/6jholjPx94Rhzf9rAiHED4zxfu3eRYyeDibinsWH0FDb3XEKrZ7vdbV0YOHc059uPoo1bKO2bFyH82G68b5eix9rt9HZztOoTi/nGSXbvPsqFK0Fcv2dCe26PRx2ZKn9K35Ylk3HL0TQiU0M+cs/DooXBaMrEobVruNy7L0Wt8sYjOfTL5/RZc528rebz1w+VsdpQqYjtzF16Di3PW7oaNABmbpzcze6jF7gSdJ17Ju35rUp1maj8aV9aPtpN7M6W5WwOy02LOWNpk1ciUCH1oBAokQ5YVOAf7yp7Y1HV5R9vddD3srpnfvSXsAvq6Mlg9SABqZjvXVVn9o9UDcr1VXtNcV0qXAUe91S79xxUxy/fUWZrvYVHYq5uV2M/rary2OkUEMs/nbLJ664m+URa+cppV/jar1U+w8P3r7OvpyZdjOVTj9qiurxjp6qNOJnAVC0qZE0nVdJWp+zL9VHbwixWzHGMOjGmtsqkQ9nWm2zFdNOLGHV1+1j1adU8yk4XWxlGobNRed0nqafFOEwt/TiXytVkhort6xVvF6kHhXhIWkLThXD27/Eh2rYW1RpUo+Yzux/osxencvaEpWJwgHP/+FD51xnUjmvstj4TBcrXokCS8/yyqJMzaNu4N//dyE2NNoP4qWl1ikaupu8AH96d+DtflbFDp3cgT8myFMr69rQUZXrXg8Z5/mLeNQvK5MWaNYH06lskSa0f0Wdn0aHzPPwy1mfs4jE0zG69z/POniF8PfoAEQrsHN62ccJRnJzRlsa9/+NG7hq0GfQTTasXJXJ1Xwb4vMvE37+ijJ0OvUMeSpYtxJNiHLWHLadqMmJFJyu1cov0KvXqQY3b5/awzfMiluINaVG3sNWX2xEi0VI7ChYJ8GCD6pTfoGwqD1G+Ma+bSKQ68Ec/NW7bNau3bibIvR2qTxlbpc/qon7c+kweLNfVkja5lUPVYeroa7+3+FhU2Nmd6t95c9TSPf4qqW0Ld46vUTMnDFXfdfRQjfssV2FJzl+EWtcxvzI8agGxrzdJXXrxS0pMS+idPWpg1YxKZyygPllyWVmrDdR8+7RaP76dKpdF/6S1JqPHEiulnj7c29FHlbHVq6wuP6qt155+SZbrS1Sb3A6q6rCjKvZibFZRUdIE+tZLYj1ovnVWeZ8MVlGJvnC48prQVBVyqq6+HvWbGvmxm/rq35tWqxuEeF0ShKYDERs7q4IGG1V+sHccN7i0zqxOjnZR9vpsyn36xZeC4JuzGys7m7JqgFfc7y7tVL4Wdfv4f2pq+7LKRmejKg3xscp3ErGuo8r/bJf8i1FoQoNQy1X1z+eFlY0OpTM6qOyOjsrRGv9yZla2+he7DvUq95errfDu0wnzSTXaxV7ps7mr6S/1qd9UsxvbKZuyA9QrirF4qyWxHow5rkZUt1M6Y2HVY3viasLbG7qoYraOqtWia8qilHqwppPymPhyHoRIadIdn+aZCbxTiB4Ld9D2w2rpcyZZ9BEWLzlMTIFO9Gtf9KVuZvsMGTBYgrly1Qw1YnmH5hOMblydoT5OdN98lqnvJnye9Z2N/fhs0GGqzfVlzudORK89STu/uyhyvuab0ZOtfFNa1ZzC94vDcalbxirfScYGHjTJu4A5QY+65Fe/Tpe8iRO/fUm3/wUQowDzfW5fT869IXVkyPj2dMdHH1nMksMxFOjUj/Yv9anbkyGDAUvwFeIqxuItl9R60FiU5l27cdG7EG0rJmKbA/NJpg1byOX8HZnd2gm9JYD/rVE0H1pYJjyJVCdVZZpnpMwngymT2tlIAi3YkwMXNLJ//D4v7yxq5tLFQGL0OcgV15o1KVX53g/F/4Yep0K545lFHoW390nMmevgVt1KCw851MejqRPz/7yKRZnwWruGwF59SMySntqNfWw89w7N2n1hnTzFy0DeOgVT6FqpTSPY8wAXtOx8/H7tl8fSmS9xMTAGfY5csvSSiFWS60EyUqnDZBZ0SNx1o73m89dRM4W6t8HVNoTNw0fh7zGS4QWloIrUJ0GoSHbm0FBuanpy5M79coGzBLB52ym0PO1oVCWu2VIpU/madg3G7bssLD0+iTqv2nQj+gT7vW5hrFwXV6ut4OtAPY+m5Js3mysWhengGtYEfkufRESh+twN6T+robUyJJ5jJjT0Jpo+B7lzv1xtWgI2s+2URp52jYizGIu32uvXg1GcXDmN5V6XCQq9S3b3IYz5tFgCWzGj8V65jksUoYe7LYsHT8LU/FeG17bWesFCJI2UQ5HsDLlzkUNvITQggMgX/ha+6zdmexmp0b0X7i/17EZxcuVEhv3Yi85ftaf/0ouJWMj9aeX7waPK96L7rwxv5pTkQq9d288BPyhdx418jxMLP8PqX3vwWdsezD/1entUOtRvTdP8D28tynSQNWsCk3EveZE4BnLnyoHeEkpAwEulmF2/zcbLWIPuvdx5ewYoiMR4/XrQFqfSlXC8sp4FC5eyNzG7qplPsXm7Pxb7TFw/dAbn78bSXQJQkYZIWRTJzlCwOR6umQjfOpOZx6OevG46v5iuXeZxv/F4/uxXIZZm+bRZ+d7bv59jWt5H40EthNdigi4AAAnRSURBVOwcQ6v3Pmf0//5js+d5bsW8ZsL2dWnVNP/DFg5l4uCaNVyRKDSNMFCwuQeumcLZOnMmT4uxifOLu9Jl3n0aj/+TfhWkc0nE7vXrQT05netStYAdGAtSo3bCx3Ja/Dax9TSU6TaVOcM6UEvGiog0RmpMkfwMJek5Zy5+7Xoyon5V9jR3JffNw+z0iaJyh/+x66cPKR5rF6YVKt8+U5kzLJYxfK/NxOF93kRmqoFbtQg8J3ZnqE9tRm7wxiVnUit4e+q2asY7f87gskVh8lrLmiu96F1YbhxpgaFkT+bM9aNdzxHUr7qH5q65uXl4Jz5Rlenwv1389GFxpCdexOm160FAu4an10W0LK2om5DxHtodji+byZQpEzmEM4M/rSFrgoo0SYJQkSKMRdsw9UBzBp84hK//XfQ5vmVslfLki69mTK7KVwthzdDvWHLuade5dsOHsBAjw9pdJYfu8as2VPxmOoPfy/rwv+Zz7PUKQWUOY91njbleeQyL/3oPa+3CaF+nFc0KzGZ6gAUV9bBL/tvehdNWl4UpkB0zhjHUsypL/u7B2zO/wUjRNlM50HwwJw754n9XT45vx1KlfD65wYsEee16MNyT/cfM2FWvi2u8hc3CxQ3/cqZIDfJE3MNQ4SPalJdbvUibpGSKFGSPU3k3nMon4pRkq3xtyVW4DM6Gp/3dWoA/20/ZU8TZmfxPglAjhbI9nZGv3djHgTMaTu9VIdvtBfz33zqO/fAeeRO4a1W87F1p1awgs6b5Y1FRHFyzhsBve1PYSsknyf1LbP1zAmN/X8Qu/wiMDau9nS1/9k6Ud3MiMcVYiKcSXw+ajuznSLgB57puCVh9wUCxD77hnT19+OkMOA9oQRm504s0SoqmSNOSrfLV58C148+4PnutDVeZfzAL7QcPi3N2/H3P/RyNyYb7V8OYnBd21J/K4N+/puHQilb6Mdnj2qoZBWdOxd+iiHo0S763UyKS0EJYP7QXcx98zJRxrSlgpZZK7cF1Igq0Z4H3R4yp2oR5egOGt6YVVIjUYsH/4GGCKEBztxIJrGfMnN+5j8sqH50bOD85x3J5JQtP1uarZnnTVu+KeGtJORRp2NPKt/ZrVL6uL1S+89aHoCUpP9H47PPmrk0VXGs7YOfyNV9UUfj+OZl1t5OU8HPsarfig0KPZsk/6pJPTL61G/8xbdJyNh48yKbJ/ej4sQcen3/LuPWXMCUhX/qcLnzkUZMCWXKTK6sedLr4TxJCJNFdvA6dQctei/pVHz8dR7B7iBvvZM5KseYTOBTx8lmapoHOFttHHTnarX3MXPwAl0YSgIq0Q1pCRRr2uPJt8ULl25R2k49hV/9nli7tR41Mz58VV+Xb4IckVr6WS+w7EICuzKe45taDoQxfdWvKb53+ZczUPjT67AxTdjrTr1PFpHVT29WiVbPCzPjjImYVxcE1a7nSOeHbFdzfvxvvKB324UFczdyKli1smNx3HAOW7eDmjqOMc7VDC1nD0O+WcC6+1aRsKvLN9ME8HhL7mMSfQqQQkzeeR6JwbNqaho/rOu0eF4+dJDjiHtqG0UzZ3JMlrZ7dYsNIufa98VjcnbmdPQivX4iMTrX5us/nOL+VY2hEWiVBqEi70lrlG+GN9ylF/vb1KG0E0JP/818ZvcabHiMaUG5nV2b/09YK4yTtcGn9AYVnTMHPrIg6uJo1V0sm4DyNW/t/o8vAVdzSF6PPtIUMr2MLfIjT6XW4jjnHti1nwbUi2OaicBlnDPEtAWUsRLZEbFIlhLAu81lPvG/ko+UX7/PkWVCfjw4rL+N+4QTzu3chLM/Lj9eGou35+1QTzp0NxqZQGYpml+hTpD0ShIo0K6UrX7umc7jS9BUHZG3DtENV0AqW5clmncaSdF5+kv+3d3exUVRhGMf/3Z3OIiBClUZEhbasC9ICRco3rKTxQlK2YZdqYqImfFxoGmNiglDAFK8EgSLWEGNiQAzEpEaoUaKoLKJYJAZjE6RQ/IgpLYIabIttmZ3xoraGYnebstjZ5vnd7szmzMW85zln5px5qL6Z0YF7krZRuW9WhKKs19h+1sJpq2F/dRMT4p7Rwbl9T7Nydyvpbe2k3T6XYH7XdRuMHzcWD6dpbW4GwJMxjxUb5vX+dyLiAjHqDx7i3MTHeX1hj5WZ3qFQ9w4n8zexc24vNW5IJoFpmTe/mSL9pFdDxKX+Lb7L4xTfNXGL79Qkj/6HMGbSZMb2TJrekYxPYgAFwDeLSFF25yjRaaOm+kN+deIcb7dyyfswW7bNpOOCzbCZQeZ2N8iisfEidprJOH92MlspIslmnWJX6ZOsrTpHe1M1m/f8xYqtz1HQo5RdqdnJ9jMhKjcvJlM9uaQozYSKe1in2PXsJuoefIHy+d91Ft8d8Ypv4SAuviYzI0Vkv7qNM5ZDW81HRNMd/L0d7hnFrEci/P7WUk52pDMtGCSj67fYT3z86SlitxVSUnQnAHbT+2xcvY+zCd8JncKKyjUU3pqcqxKRBNKGMTy9gQ/WlXDMn0fhlgOUFY687rChs0t5efYAtE8kiRRCxT1UfK9hFkRYkr2DrWcsnKt/cvlqopczr3AsepwWI8DC4L3dX5dqOVrJG8fTKVhfzhNd+zWZo7g7Kwc70bJ77xhGXBf0Y8Ri4Ng2jo2ep4gkk3ccyyo+YVnFQDdE5OZTCBX3UPG9ljmDcCiHV7bUkWjCEoCOb4l+eRGGLyDP33lr2xcOUvbMLtpD29ldNqP7XVZPxnxWbZzfv3Y111PfFMNJa6DBZhDPRouIyM2k7kPEtUxmhENM6ONQMfZDlC9+tBk+spaXFpewcnkxsxet45elbxPdu5zAjQ457fPsL4uwaM5TvHvJ5mptBeFgmOerfibRInsREZGeNBMq4mLmA2FC/gpOf59oLtTm4pHPqbVuIbj2MO9FWqhrgDH+HEYPSXBqX3nuYkn5Xha/aGAYXjx2DMuysL2+7kf/IiIifaWZUBE3M6cTDt3Xh9FiK0ejJ2gzclmw4A58GTlMyUtiAP2H1/RhGt7OwuHxYpg+TCVQERHpB4VQEVczyQ+HEj9Kb/+a6FeX8WTNY2G2UqGIiLifQqiIy5nTw4QmxlsZb/Pb4SoONdgM9QfI0l0tIiIpQN2ViNsZ+YRDAf47hjZzZOsqSt/8g4JHH6NoxGes3niA84m2XhIRERlgaY7jxPsOi4i4gPXNeqbP2Yxvw0lObJg80M0RERG5YZoJFUkBxtQIxZO0mYWIiAweCqEiqcDII1J8v/ZUExGRQUMhVCQlGOSGi8lVChURkUFCXZpIijByI4QbdcuKiMjgoIVJIinEsiwMQ0FURERSn0KoiIiIiPzv/gaFViXoRmESyAAAAABJRU5ErkJggg==" - } - }, "cell_type": "markdown", - "id": "5b0f6217", + "id": "c42a67de", "metadata": {}, "source": [ - "**Important Note:**
\n", - "Note the typo in eq(1) of the paper...\n", - "![image.png](attachment:image.png)" + "To find critical point(s):" ] }, { "cell_type": "markdown", - "id": "9682721a", + "id": "9ee22e69", "metadata": {}, "source": [ - "Somehow, the authors change $\\mu_{j,m+k}$ to $\\mu_{j,k}$...However, these two values can be different." + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad \\text{(1)}\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad \\text{(2)}\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "4e1ac4d6", + "id": "97afedeb", "metadata": {}, "source": [ - "**>>> In this notebook:
\n", - "we try to calculate LB after correcting such typo. The problem becomes...**" + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m} {\\frac{-2}{\\sigma^{'}}X_{t}} \\Rightarrow \\text{with (1):}\n", + " \\sum \\limits_{t=1}^{m} X_{t} = 0 \\quad (3)\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "51f452b1", + "id": "94efd415", "metadata": {}, "source": [ - "**To find the minimum value of d, we need to minimize the following function:**" + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", + " \\sum{\\frac{-2}{\\sigma^{'2}}\\left(T[i+t-1] - \\mu^{'}\\right)X_{t}} \\Rightarrow {\\text{with (2) and (3)}}:\n", + " \\sum \\limits_{t=1}^{m} T[i+t-1]X_{t} = 0 \\quad (4)\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "4c09667d", + "id": "0a5b427d", "metadata": {}, "source": [ - "$f(\\mu^{'}, \\sigma^{'}) = \\sum\\limits_{t=1}^{m}{\n", - "(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}})^{2}\n", - "}$
\n", - "\n", - "**Let's take its partial derivatives and put them equal to 0...**
\n", - "$\\frac{\\partial f}{\\partial \\mu^{'}} = 0$
\n", - "$\\frac{\\partial f}{\\partial \\sigma^{'}} = 0$" + "Exapanding (3):" ] }, { "cell_type": "markdown", - "id": "37330b9c", + "id": "870b5eb8", "metadata": {}, "source": [ - "**First, let us first provide some guidelines:**
\n", - "\n", - "(1) We use $T_{i}$ to represent $T[i+t-1]$, and $T_{j}$ to represent $T[j+t-1]$. Since we use them inside $\\sum$, the notation should suffice.
\n", - "(2) We use $\\sum$ without limits. It is alway from $t=1$ to $m$.
\n", - "(3) We define: $X_{t} = \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}$
\n", - "(4) Similar to paper, We define: $q = \\frac{\\sum{T_{i}T_{j}} - m\\mu_{i,m}\\mu_{j,m}}{m\\sigma_{i,m}\\sigma_{j,m}}$ (note: $q=1$ for $i=j$)
\n", - "(5) Note that: $\\sum{T_{i}} = m\\mu_{i,m}$, and $T_{j} = m\\mu_{j,m}$.\n", - "(6) We use $\\mu_{j}$ and $\\sigma_{j}$ to represent $\\mu_{j,m}$ and $\\sigma_{j,m}$, respectively. If we want to show $\\mu$ for length `m+k`, we use $\\mu_{j,m+k}$" + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m} X_{t} = 0\n", + " \\\\\n", + " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} = 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) = 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) = 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", + " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) = 0\n", + " \\\\\n", + " \\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} = 0 \\quad (5)\n", + "\\end{align} " ] }, { "cell_type": "markdown", - "id": "0df0e59b", + "id": "ebdb4516", "metadata": {}, "source": [ - "**Let us solve it...**" + "Expanding (4):" ] }, { "cell_type": "markdown", - "id": "e330f0c1", + "id": "5c3fd3cb", "metadata": {}, "source": [ - "(1) $\\frac{\\partial f}{\\partial \\mu^{'}} = 0$
\n", - "\n", - "Therefore: $\\sum{\\frac{-2}{\\sigma^{'}}X_{t}} = 0$
\n", - "Therefore: $\\sum{X_{t}} = 0$ (eq: I)" + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m} T[i+t-1] \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "30f65c15", + "id": "5864dd2f", "metadata": {}, "source": [ - "(2) $\\frac{\\partial f}{\\partial \\sigma^{'}} = 0$
\n", - " \n", - "Therefore: $\\sum{\\frac{-2}{\\sigma^{'2}}(T_{i} - \\mu^{'})X_{t}} = 0$
\n", - "Therefore: $\\sum{(T_{i} - \\mu^{'})X_{t}} = 0$
\n", - "Therefore (using eq I): $\\sum{T_{i}X_{t}} = 0$ (eq II)
" + "\\begin{align}\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\sum \\limits_{t=1}^{m} T[i+t-1] \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}}\\right) = 0\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "abe3ee87", + "id": "c311fdc2", "metadata": {}, "source": [ - "Also, let us find out the value we are trying to minimize:" + "\\begin{align}\n", + " r \\triangleq \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (6)\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "91096e9d", + "id": "4ea25765", "metadata": {}, "source": [ - "$f(\\mu^{'}, \\sigma^{i}) = \\sum{\n", - "(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})^{2}\n", - "} \n", - "= \n", - "\\sum{\n", - "[(\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}})X_{t}]\n", - "} \n", - "= \n", - "{\n", - "\\frac{\\sum{T_{i}X_{t}} - \\sum{\\mu^{'}X_{t}}}{\\sigma^{'}} - \\frac{\\sum{T_{j}X_{t}} - \\sum{\\mu_{j,m+k}X_{t}}}{\\sigma_{j}}\n", - "} $" + "\\begin{align}\n", + " \\frac{1}{\\sigma^{'}}\\left(m(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) - m \\mu_{i,m} \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}) - m\\mu_{i,m}\\mu_{j,m+k}}\\right) = 0\n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "7d6213b9", + "id": "1bdc9010", "metadata": {}, "source": [ - "And, with help of eq I and II, we can see:
\n", - "$f_{optim} = - \\frac{\\sum{(T_{j}X)}}{\\sigma_{j}} $" + "\\begin{align}\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\left(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\left(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}\\right) = 0 \\quad (7)\n", + " \\\\ \n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "c63a0492", + "id": "30a6adeb", "metadata": {}, "source": [ - "Therefore:
\n", - "$f_{optim} = - \\frac{1}{\\sigma_{j}}F$, where:
\n", - "\n", - "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$" + "Solving (5) and (7) gives:" ] }, { "cell_type": "markdown", - "id": "0fe24576", + "id": "fae1014d", "metadata": {}, "source": [ - "**We need to find $\\mu^{'}$ and $\\sigma^{'}$:**" - ] - }, - { - "cell_type": "markdown", - "id": "b028fd7f", - "metadata": {}, - "source": [ - "eq I: $\\sum{X} = 0$,
\n", + "\\begin{align}\n", + " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{'}}{\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (8)\n", + "\\end{align}\n", "\n", - "Therefore: $\\sum{\\frac{T_{i} - \\mu^{'}}{\\sigma^{'}} - \\frac{T_{j} - \\mu_{j,m+k}}{\\sigma_{j}}} = 0$
" - ] - }, - { - "cell_type": "markdown", - "id": "e6e9ce06", - "metadata": {}, - "source": [ - "Therefore: ${\\frac{\\sum{T_{i}} - \\sum{\\mu^{'}}}{\\sigma^{'}} - \\frac{\\sum{T_{j}} - \\sum{\\mu_{j,m+k}}}{\\sigma_{j}}} = 0$
" - ] - }, - { - "cell_type": "markdown", - "id": "89ac2637", - "metadata": {}, - "source": [ - "Therefore: ${\\frac{m\\mu_{i} - m{\\mu^{'}}}{\\sigma^{'}} - \\frac{m{\\mu_{j}} - {\\mu_{j,m+k}}}{\\sigma_{j}}} = 0$" - ] - }, - { - "cell_type": "markdown", - "id": "dd128a9f", - "metadata": {}, - "source": [ - "Therefore: $\\sigma_{j}(\\mu_{i}-\\mu^{'}) - \\sigma^{'}(\\mu_{j}-\\mu_{j,m+k}) = 0$ (eq III)" - ] - }, - { - "cell_type": "markdown", - "id": "6784d89e", - "metadata": {}, - "source": [ - "---\n", "\n", - "And, with eq II:
\n", - "$\\sum{T_{i}X} = 0$," + "\\begin{align}\n", + " \\sigma^{'} = \\frac{\\sigma_{i,m}}{r} \\quad (9)\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "cc05e3e1", + "id": "4d83a448", "metadata": {}, "source": [ - "Therefore: $\\frac{\\sum{T_{i}T_{i}} - \\sum\\mu^{'}T_{i}}{\\sigma^{'}} - \\frac{\\sum{T_{i}T_{j}} - \\sum{\\mu_{j,m+k}T_{i}}}{\\sigma_{j}} = 0$" + "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (4) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." ] }, { "cell_type": "markdown", - "id": "b6f83405", + "id": "14904456", "metadata": {}, "source": [ - "Therefore: $\\sigma_{j}(m\\mu_{i}^{2} + m\\sigma_{i}^{2} - m\\mu_{i}\\mu^{'}) - \\sigma^{'}(m\\mu_{i}\\mu_{j} + mq\\sigma_{i}\\sigma_{j} - m\\mu_{i}\\mu_{j,m+k}) = 0$ (eq IV)" + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", + " }^{2}} \n", + " \\\\\n", + " ={}&\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", + " }X_{t}}\n", + " \\\\\n", + " ={}&\n", + " {\n", + " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]X_{t} - \\sum\\limits_{t=1}^{m}\\mu^{'}X_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]X_{t} - \\sum\\limits_{t=1}^{m}\\mu_{j,m+k}X_{t}}{\\sigma_{j,m}}\n", + " } \n", + " \\\\ \n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]X_{t}\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}{T[j+t-1]\\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)}\n", + " } \n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "71dbe617", + "id": "32e63873", "metadata": {}, "source": [ - "**solving eq (III) and eq (IV) give us optimal values for $\\mu^{'}$ and $\\sigma^{'}$ as follows:**" + "with (6), (8), and (9), we can get:" ] }, { "cell_type": "markdown", - "id": "32537233", + "id": "d717fbad", "metadata": {}, "source": [ - "$\\sigma^{'} = \\frac{\\sigma_{i}}{q}$ (thus, q must be positive.)
\n", - "$\\mu^{'} = \\mu_{i} - \\frac{\\sigma^{'}}{\\sigma_{j}}(\\mu_{j}-\\mu_{j,m+k})$" - ] - }, - { - "cell_type": "markdown", - "id": "bd4a023d", - "metadata": {}, - "source": [ - "Now, we plugged back in the values to find LB:\n", - "\n", - "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{f_{optim}}$, where:
\n", - "\n", - "$f_{optim} = - \\frac{1}{\\sigma_{j}}F$, where:
\n", - "\n", - "$F = \\sum{T_{j}X} = \\frac{\\sum{T_{i}T_{j}} - \\sum\\mu^{'}T_{j}}{\\sigma^{'}} - \\frac{\\sum{T_{j}T_{j}} - \\sum{\\mu_{j,m+k}T_{j}}}{\\sigma_{j}}$ in which we should use the optimal value for $\\mu^{'}$ and $\\sigma^{'}$." + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", + " m (1 - r^{2}) \n", + " \\\\\n", + "\\end{align}" ] }, { "cell_type": "markdown", - "id": "bec46a29", + "id": "4d0f0609", "metadata": {}, "source": [ - "* If $q \\gt 0$: $LB = \\frac{\\sigma_{j}}{\\sigma_{j,m+k}} \\sqrt{m(1-q^{2})}$\n", - "* If $q \\le 0$: $LB = \\frac{\\sigma_{j}}{\\sigma_{j,m+k}} \\sqrt{m}$ (proof not provided in this notebook)" + "**Therefore, the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" ] }, { "cell_type": "markdown", - "id": "3bcf8519", - "metadata": {}, - "source": [ - "### LB dist profile function" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "928fc18c", + "id": "8c3c9bbd", "metadata": {}, - "outputs": [], "source": [ - "def _calc_LB_dist_profile(T, D, m, σ, m_target, σ_target):\n", - " \"\"\"\n", - " This function finds the lower-bound of a distance profile for a subsequence with window size `m_target` based\n", - " on the distance profile of a subsequence with window size `m` starting from the same index `idx`.\n", - " (note: this is for z-normalize case)\n", - " \n", - " Parameters\n", - " ----------\n", - " T: numpy.ndarray\n", - " a time series of interest\n", - " \n", - " D: numpy.ndarray\n", - " Distance profile for a subsequence with length `m` located at an index `idx` in time series `T`\n", - " \n", - " m: int\n", - " length of subsequence for which the the distance profile D is provided. \n", - " \n", - " σ: float\n", - " standard deviation of subsequence `T[idx : idx + m]`\n", - " \n", - " m_target: int\n", - " new length of subsequence whose lower-bound distance profile will be returned.\n", - " \n", - " σ_target: float\n", - " standard deviation of subsequence `T[idx : idx + m_target]`\n", - " \n", - " Return\n", - " --------\n", - " LB : numpy.ndarray\n", - " Lower_Bound of distance profile for subsequence with length `m_target`, starting at index `idx`.\n", - " \n", - " \"\"\"\n", - " if m_target <= m:\n", - " raise ValueError(f\"m_target, {m_target} should be larget than m, {m}\")\n", - " \n", - " if len(D) != T.shape[0] - m + 1:\n", - " raise ValueError(f\"length of distance profile D, {len(D)}, should be T.shape[0]-m+1, {T.shape[0]-m+1}\")\n", - " \n", - " excl_zone = int(np.ceil(m_target / config.STUMPY_EXCL_ZONE_DENOM))\n", - " \n", - " k = T.shape[0] - m_target + 1\n", - " T_is_finite = core.rolling_isfinite(T, m_target)\n", - " \n", - " R = 1 - np.square(D[:k])/(2 * m)\n", - " \n", - " LB = (σ/σ_target) * np.sqrt(m) * np.sqrt(1 - np.square(np.maximum(R,0)))\n", - " core.apply_exclusion_zone(LB, idx, excl_zone, np.inf)\n", - " LB[~T_is_finite] = np.inf\n", - " \n", - " return LB" - ] - }, - { - "cell_type": "markdown", - "id": "52a327c7", - "metadata": {}, - "source": [ - "**Example:**" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "id": "df09cc41", - "metadata": {}, - "outputs": [], - "source": [ - "T = np.random.uniform(-100,100, size=1000)\n", - "idx = 500 #start index of subsequence" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "id": "2f0a21d3", - "metadata": {}, - "outputs": [], - "source": [ - "m = 10\n", - "_, Σ_T = core.compute_mean_std(T, m)\n", - "Q = T[idx:idx+m]\n", - "excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", - "\n", - "#################################################\n", + "\\begin{align}\n", + " LB ={}& \n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m (1 - r^{2})} \\quad \\text{if} \\, r > 0\n", + " \\\\\n", + "\\end{align}\n", "\n", - "m_target = 11\n", - "_, Σ_T_target = core.compute_mean_std(T, m_target)\n", - "Q_target = T[idx:idx+m_target]\n", - "excl_zone_target = int(np.ceil(m_target / config.STUMPY_EXCL_ZONE_DENOM))" + "\\begin{align}\n", + " r ={}& \n", + " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", + " \\\\\n", + "\\end{align}" ] }, { - "cell_type": "code", - "execution_count": 94, - "id": "35649122", + "cell_type": "markdown", + "id": "1112e11c", "metadata": {}, - "outputs": [], "source": [ - "D = core.mass(Q, T)\n", - "core.apply_exclusion_zone(D, idx, excl_zone, np.inf)\n", + "**Note:**
\n", + "* Note that eq(9) is valid only for $r > 0$. Therefore, we can use the formula above to calculate $LB$ only if $r > 0$. \n", + "* The pearson correlation, `r`, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", - "D_target = core.mass(Q_target, T) #true distance profile for length m_target\n", - "core.apply_exclusion_zone(D_target, idx, excl_zone, np.inf) " - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "id": "09669a7a", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "LB = _calc_LB_dist_profile(T, D, m, Σ_T[idx], m_target, Σ_T_target[idx])\n", + "**Pending...**
\n", + "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", "\n", - "plt.title(f'distance profile of subseq at {idx} with length {m_target}')\n", - "plt.plot(D[np.isfinite(D)], 'k', label='True D')\n", - "plt.plot(LB[np.isfinite(LB)], 'r', label='Lower-Bound D')\n", - "plt.legend()\n", - "plt.show()" + "* For $r \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$." ] }, { "cell_type": "code", "execution_count": null, - "id": "11e07596", + "id": "7c1c6e20", "metadata": {}, "outputs": [], "source": [] From d21061aee318130a3d7560029093883296e74aa0 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 11 Apr 2022 00:37:11 -0600 Subject: [PATCH 05/67] Use 2662 to enclose math equations written in latex to resolve rendering issue --- docs/Tutorial_VALMOD.ipynb | 148 +++++++++++++++++++++++++------------ 1 file changed, 101 insertions(+), 47 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 079fc4831..1933799ec 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 14, "id": "6534d116", "metadata": {}, "outputs": [], @@ -175,7 +175,7 @@ }, { "cell_type": "markdown", - "id": "a1429322", + "id": "746512bd", "metadata": {}, "source": [ "### Derving Equation (2)" @@ -183,9 +183,11 @@ }, { "cell_type": "markdown", - "id": "982235e5", + "id": "38b7f91c", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " d^{(m+k)}_{j,i} ={}& \n", " \\sqrt{\\sum\\limits_{t=1}^{m+k}{{\n", @@ -197,14 +199,17 @@ " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}}\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "a86c6f4d", + "id": "ec4e090c", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " LB ={}& \n", " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", @@ -214,12 +219,13 @@ " ={}&\n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "31a8cf32", + "id": "57e5b64c", "metadata": {}, "source": [ "Note that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." @@ -227,35 +233,41 @@ }, { "cell_type": "markdown", - "id": "4595f60b", + "id": "3773968e", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " f(\\mu^{'}, \\sigma^{'}) ={}& \n", " \\sum\\limits_{t=1}^{m}{{\n", " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", " }^{2}} \n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "0be3b76a", + "id": "37918e15", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " X_{t} \\triangleq{}& \n", " {\n", " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " } \n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "c42a67de", + "id": "d1f33f26", "metadata": {}, "source": [ "To find critical point(s):" @@ -263,44 +275,53 @@ }, { "cell_type": "markdown", - "id": "9ee22e69", + "id": "caebf383", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad \\text{(1)}\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad \\text{(2)}\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "97afedeb", + "id": "c8749eee", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", " \\sum \\limits_{t=1}^{m} {\\frac{-2}{\\sigma^{'}}X_{t}} \\Rightarrow \\text{with (1):}\n", " \\sum \\limits_{t=1}^{m} X_{t} = 0 \\quad (3)\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "94efd415", + "id": "22345d05", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", " \\sum{\\frac{-2}{\\sigma^{'2}}\\left(T[i+t-1] - \\mu^{'}\\right)X_{t}} \\Rightarrow {\\text{with (2) and (3)}}:\n", " \\sum \\limits_{t=1}^{m} T[i+t-1]X_{t} = 0 \\quad (4)\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "0a5b427d", + "id": "6e390cf4", "metadata": {}, "source": [ "Exapanding (3):" @@ -308,9 +329,11 @@ }, { "cell_type": "markdown", - "id": "870b5eb8", + "id": "4915e55a", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\sum \\limits_{t=1}^{m} X_{t} = 0\n", " \\\\\n", @@ -327,12 +350,13 @@ " \\\\\n", " \\sigma_{j,m} \\mu^{'} + \n", " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} = 0 \\quad (5)\n", - "\\end{align} " + "\\end{align} \n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "ebdb4516", + "id": "194a1fc1", "metadata": {}, "source": [ "Expanding (4):" @@ -340,62 +364,77 @@ }, { "cell_type": "markdown", - "id": "5c3fd3cb", + "id": "f230b5a7", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\sum \\limits_{t=1}^{m} T[i+t-1] \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "5864dd2f", + "id": "1ed1ca80", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\sum \\limits_{t=1}^{m} T[i+t-1] \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}}\\right) = 0\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "c311fdc2", + "id": "041a0e1e", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " r \\triangleq \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (6)\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "4ea25765", + "id": "7db261d9", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\frac{1}{\\sigma^{'}}\\left(m(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) - m \\mu_{i,m} \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}) - m\\mu_{i,m}\\mu_{j,m+k}}\\right) = 0\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "1bdc9010", + "id": "9117f549", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\left(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\left(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}\\right) = 0 \\quad (7)\n", " \\\\ \n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "30a6adeb", + "id": "f43f2aba", "metadata": {}, "source": [ "Solving (5) and (7) gives:" @@ -403,22 +442,26 @@ }, { "cell_type": "markdown", - "id": "fae1014d", + "id": "f795e3f1", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{'}}{\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (8)\n", "\\end{align}\n", + "$$\n", "\n", - "\n", + "$$\n", "\\begin{align}\n", " \\sigma^{'} = \\frac{\\sigma_{i,m}}{r} \\quad (9)\n", - "\\end{align}" + "\\end{align}\n", + "$$" ] }, { "cell_type": "markdown", - "id": "4d83a448", + "id": "91ee02c3", "metadata": {}, "source": [ "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (4) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." @@ -426,9 +469,11 @@ }, { "cell_type": "markdown", - "id": "14904456", + "id": "2879d93c", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", " \\sum\\limits_{t=1}^{m}{{\n", @@ -455,12 +500,13 @@ " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}{T[j+t-1]\\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)}\n", " } \n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "32e63873", + "id": "bc4bbf39", "metadata": {}, "source": [ "with (6), (8), and (9), we can get:" @@ -468,19 +514,22 @@ }, { "cell_type": "markdown", - "id": "d717fbad", + "id": "afa56247", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", " m (1 - r^{2}) \n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "4d0f0609", + "id": "5b734817", "metadata": {}, "source": [ "**Therefore, the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" @@ -488,25 +537,30 @@ }, { "cell_type": "markdown", - "id": "8c3c9bbd", + "id": "a6b23cfe", "metadata": {}, "source": [ + "\n", + "$$\n", "\\begin{align}\n", " LB ={}& \n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m (1 - r^{2})} \\quad \\text{if} \\, r > 0\n", " \\\\\n", "\\end{align}\n", + "$$\n", "\n", + "$$\n", "\\begin{align}\n", " r ={}& \n", " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", - "\\end{align}" + "\\end{align}\n", + "$$\n" ] }, { "cell_type": "markdown", - "id": "1112e11c", + "id": "b3bfd88c", "metadata": {}, "source": [ "**Note:**
\n", @@ -522,7 +576,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7c1c6e20", + "id": "8b78d721", "metadata": {}, "outputs": [], "source": [] From 88503ed043eaeedff1fd23cc66f7bcec38e0eb17 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 11 Apr 2022 01:06:44 -0600 Subject: [PATCH 06/67] modify math eq latex in markdown --- docs/Tutorial_VALMOD.ipynb | 60 +++++++++++++++++++------------------- 1 file changed, 30 insertions(+), 30 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 1933799ec..888ed3cca 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -175,7 +175,7 @@ }, { "cell_type": "markdown", - "id": "746512bd", + "id": "d60acabc", "metadata": {}, "source": [ "### Derving Equation (2)" @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "38b7f91c", + "id": "1d3734ed", "metadata": {}, "source": [ "\n", @@ -205,7 +205,7 @@ }, { "cell_type": "markdown", - "id": "ec4e090c", + "id": "ade9e7e4", "metadata": {}, "source": [ "\n", @@ -225,7 +225,7 @@ }, { "cell_type": "markdown", - "id": "57e5b64c", + "id": "d410ec5a", "metadata": {}, "source": [ "Note that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." @@ -233,7 +233,7 @@ }, { "cell_type": "markdown", - "id": "3773968e", + "id": "a293197c", "metadata": {}, "source": [ "\n", @@ -250,7 +250,7 @@ }, { "cell_type": "markdown", - "id": "37918e15", + "id": "6722cf8a", "metadata": {}, "source": [ "\n", @@ -267,7 +267,7 @@ }, { "cell_type": "markdown", - "id": "d1f33f26", + "id": "e7564257", "metadata": {}, "source": [ "To find critical point(s):" @@ -275,7 +275,7 @@ }, { "cell_type": "markdown", - "id": "caebf383", + "id": "c2de39a8", "metadata": {}, "source": [ "\n", @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "c8749eee", + "id": "8b7c8a81", "metadata": {}, "source": [ "\n", @@ -306,7 +306,7 @@ }, { "cell_type": "markdown", - "id": "22345d05", + "id": "4eae27d8", "metadata": {}, "source": [ "\n", @@ -321,7 +321,7 @@ }, { "cell_type": "markdown", - "id": "6e390cf4", + "id": "2dd7d048", "metadata": {}, "source": [ "Exapanding (3):" @@ -329,7 +329,7 @@ }, { "cell_type": "markdown", - "id": "4915e55a", + "id": "848e6f89", "metadata": {}, "source": [ "\n", @@ -356,7 +356,7 @@ }, { "cell_type": "markdown", - "id": "194a1fc1", + "id": "4a34e737", "metadata": {}, "source": [ "Expanding (4):" @@ -364,7 +364,7 @@ }, { "cell_type": "markdown", - "id": "f230b5a7", + "id": "de3f6023", "metadata": {}, "source": [ "\n", @@ -378,7 +378,7 @@ }, { "cell_type": "markdown", - "id": "1ed1ca80", + "id": "1ce7c9be", "metadata": {}, "source": [ "\n", @@ -392,7 +392,7 @@ }, { "cell_type": "markdown", - "id": "041a0e1e", + "id": "3a87f16d", "metadata": {}, "source": [ "\n", @@ -406,7 +406,7 @@ }, { "cell_type": "markdown", - "id": "7db261d9", + "id": "1543b1f4", "metadata": {}, "source": [ "\n", @@ -420,21 +420,21 @@ }, { "cell_type": "markdown", - "id": "9117f549", + "id": "1d37830b", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\left(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\left(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}\\right) = 0 \\quad (7)\n", - " \\\\ \n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (7)\n", + " \\\\\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "f43f2aba", + "id": "6adaea06", "metadata": {}, "source": [ "Solving (5) and (7) gives:" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "f795e3f1", + "id": "631d7d57", "metadata": {}, "source": [ "\n", @@ -461,7 +461,7 @@ }, { "cell_type": "markdown", - "id": "91ee02c3", + "id": "a0e36dfc", "metadata": {}, "source": [ "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (4) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." @@ -469,7 +469,7 @@ }, { "cell_type": "markdown", - "id": "2879d93c", + "id": "b51d32b2", "metadata": {}, "source": [ "\n", @@ -506,7 +506,7 @@ }, { "cell_type": "markdown", - "id": "bc4bbf39", + "id": "cfd5a617", "metadata": {}, "source": [ "with (6), (8), and (9), we can get:" @@ -514,7 +514,7 @@ }, { "cell_type": "markdown", - "id": "afa56247", + "id": "a5c3b9e8", "metadata": {}, "source": [ "\n", @@ -529,7 +529,7 @@ }, { "cell_type": "markdown", - "id": "5b734817", + "id": "64dc1027", "metadata": {}, "source": [ "**Therefore, the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" @@ -537,7 +537,7 @@ }, { "cell_type": "markdown", - "id": "a6b23cfe", + "id": "98db40a5", "metadata": {}, "source": [ "\n", @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "b3bfd88c", + "id": "8cbad624", "metadata": {}, "source": [ "**Note:**
\n", @@ -576,7 +576,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8b78d721", + "id": "448cd8ce", "metadata": {}, "outputs": [], "source": [] From 1a87295637d91d5eb8a7cfce30497c477042aea1 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 11 Apr 2022 22:49:52 -0600 Subject: [PATCH 07/67] add twin_freak explanation --- docs/Tutorial_VALMOD.ipynb | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 888ed3cca..4e1c902e5 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 1, "id": "6534d116", "metadata": {}, "outputs": [], @@ -101,13 +101,13 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 2, "id": "3d9db678", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -135,7 +135,7 @@ "id": "a8e87bc0", "metadata": {}, "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. \n", + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", "\n", "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" ] From 00377bda6cd0c62dc18f4d912e47c1eb7bb9cc03 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 11 Apr 2022 23:15:57 -0600 Subject: [PATCH 08/67] add lower-bound calculation for non-normalized p-norm distance --- docs/Tutorial_VALMOD.ipynb | 93 +++++++++++++++++++++++++++++++++++++- 1 file changed, 92 insertions(+), 1 deletion(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 4e1c902e5..7b32f6b96 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -154,7 +154,7 @@ "id": "27b8effd", "metadata": {}, "source": [ - "# 2- Lower-Bound Distance Profile (for z-normalize case)" + "# 2- Lower-Bound Distance Profile" ] }, { @@ -173,6 +173,97 @@ "In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" ] }, + { + "cell_type": "markdown", + "id": "e8ac29f2", + "metadata": {}, + "source": [ + "## 2-1 Non-normalized distance" + ] + }, + { + "cell_type": "markdown", + "id": "f4719164", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m+k}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " +\n", + " \\sum\\limits_{t=m+1}^{m+k}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + " \\geq{}&\n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "6e1b4c8a", + "metadata": {}, + "source": [ + "Therefore:" + ] + }, + { + "cell_type": "markdown", + "id": "f3e5e6de", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " d^{(m+k)}_{j,i} \\geq{}&\n", + " d^{(m)}_{j,i}\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "22bb5bd4", + "metadata": {}, + "source": [ + "In other words, we can simply use the p-norm distance between $T_{i,m}$ and $T_{j,m}$ as the lower-bound value for the distance between $T_{i,m+k}$ and $T_{j,m+k}$." + ] + }, + { + "cell_type": "markdown", + "id": "99f37c41", + "metadata": {}, + "source": [ + "## 2-2 Normalized distance" + ] + }, { "cell_type": "markdown", "id": "d60acabc", From f38e2e56c47eca62e87066b08ebcb0d10556603e Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 12 Apr 2022 02:48:27 -0600 Subject: [PATCH 09/67] major improvement in derivation of lower-bound --- docs/Tutorial_VALMOD.ipynb | 504 ++++++++++++++++++++++++++++++++++--- 1 file changed, 464 insertions(+), 40 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 7b32f6b96..81c8af1fa 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -175,7 +175,7 @@ }, { "cell_type": "markdown", - "id": "e8ac29f2", + "id": "c3b87441", "metadata": {}, "source": [ "## 2-1 Non-normalized distance" @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "f4719164", + "id": "9ecaf914", "metadata": {}, "source": [ "\n", @@ -228,7 +228,7 @@ }, { "cell_type": "markdown", - "id": "6e1b4c8a", + "id": "0fcfe4a4", "metadata": {}, "source": [ "Therefore:" @@ -236,7 +236,7 @@ }, { "cell_type": "markdown", - "id": "f3e5e6de", + "id": "7e435c6b", "metadata": {}, "source": [ "\n", @@ -250,7 +250,7 @@ }, { "cell_type": "markdown", - "id": "22bb5bd4", + "id": "cac0c884", "metadata": {}, "source": [ "In other words, we can simply use the p-norm distance between $T_{i,m}$ and $T_{j,m}$ as the lower-bound value for the distance between $T_{i,m+k}$ and $T_{j,m+k}$." @@ -258,12 +258,20 @@ }, { "cell_type": "markdown", - "id": "99f37c41", + "id": "ce92bccd", "metadata": {}, "source": [ "## 2-2 Normalized distance" ] }, + { + "cell_type": "markdown", + "id": "d0773bc3", + "metadata": {}, + "source": [ + "In z-normalized distance, one should note that $d^{(m+k)}_{j,i} \\geq d^{(m)}_{j,i}$ is not necessarily correct. In other words, the distance between two subsequences does not necessarily increase by making them longer. However, it seems there is a very nice relationship between $d_{j,i}^{(m)}$ and the lower-bound value of $d_{j,i}^{(m+k)}$." + ] + }, { "cell_type": "markdown", "id": "d60acabc", @@ -285,6 +293,17 @@ " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}} \n", " \\\\\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}\n", + " +\n", + " \\sum\\limits_{t=m+1}^{m+k}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}\n", + " } \n", + " \\\\\n", " \\geq{}&\n", " \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", @@ -294,6 +313,14 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "id": "6447a1c8", + "metadata": {}, + "source": [ + "So, the Lower-Bound (LB) value for $d_{j,i}^{(m+k)}$ can be obtained by minimizing the right-hand side:" + ] + }, { "cell_type": "markdown", "id": "ade9e7e4", @@ -308,6 +335,46 @@ " }^{2}}} \n", " \\\\\n", " ={}&\n", + " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left[\\frac{1}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\right)\n", + " \\right]\n", + " }^{2}}}\n", + " \\\\\n", + " ={}&\n", + " \\min \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left[\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m}}\n", + " \\frac{1}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " - \n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\right)\n", + " \\right]\n", + " }^{2}\n", + " }\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\min \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left[\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{j,m}\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " - \n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " \\right]\n", + " }^{2}\n", + " }\n", + " }\n", + " \\\\\n", + " ={}&\n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", " \\\\\n", "\\end{align}\n", @@ -319,7 +386,9 @@ "id": "d410ec5a", "metadata": {}, "source": [ - "Note that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." + "**Note:** that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", + "\n", + "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." ] }, { @@ -347,7 +416,7 @@ "\n", "$$\n", "\\begin{align}\n", - " X_{t} \\triangleq{}& \n", + " \\alpha_{t} \\triangleq{}& \n", " {\n", " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " } \n", @@ -361,7 +430,8 @@ "id": "e7564257", "metadata": {}, "source": [ - "To find critical point(s):" + "Please note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", + "**To find critical point(s):**" ] }, { @@ -380,6 +450,14 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "id": "ec55a584", + "metadata": {}, + "source": [ + "**Deriving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}}$:**" + ] + }, { "cell_type": "markdown", "id": "8b7c8a81", @@ -389,12 +467,59 @@ "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m} {\\frac{-2}{\\sigma^{'}}X_{t}} \\Rightarrow \\text{with (1):}\n", - " \\sum \\limits_{t=1}^{m} X_{t} = 0 \\quad (3)\n", + " \\sum \\limits_{t=1}^{m}{\n", + " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\mu^{'}}}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\mu^{'}}}\\alpha_{t}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}&\n", + " \\sum \\limits_{t=1}^{m} {\n", + " 2\\left(\n", + " \\frac{-1}{\\sigma^{'}}\n", + " \\right)\n", + " \\alpha_{t}} \n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'}}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\\\\n", "\\end{align}\n", "$$\n" ] }, + { + "cell_type": "markdown", + "id": "4e757a6e", + "metadata": {}, + "source": [ + "Please note that $\\sigma^{'}$ is constant and thus it was factered out of the summation.
\n", + "This gives us:" + ] + }, + { + "cell_type": "markdown", + "id": "ced6809c", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (3)\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "14e92a2e", + "metadata": {}, + "source": [ + "**Deriving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}}$:**" + ] + }, { "cell_type": "markdown", "id": "4eae27d8", @@ -404,8 +529,82 @@ "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", - " \\sum{\\frac{-2}{\\sigma^{'2}}\\left(T[i+t-1] - \\mu^{'}\\right)X_{t}} \\Rightarrow {\\text{with (2) and (3)}}:\n", - " \\sum \\limits_{t=1}^{m} T[i+t-1]X_{t} = 0 \\quad (4)\n", + " \\sum \\limits_{t=1}^{m}{\n", + " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\sigma^{'}}}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\sigma^{'}}}\\alpha_{t}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\sum \\limits_{t=1}^{m} {\n", + " 2 \\left(\n", + " \\frac{-\\left({T[i+t-1] - \\mu^{'}}\\right)}{\\sigma^{'2}}\n", + " \\right)\n", + " \\alpha_{t}} \n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1] - \\mu^{'}}\\right) \\alpha_{t}}\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1]\\alpha_{t} - \\mu^{'}\\alpha_{t}}\\right)}\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\sum \\limits_{t=1}^{m}{\\mu^{'}\\alpha_{t}}\n", + " \\right)\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\mu^{'}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\right)\n", + " }\n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\mu^{'} (0)\n", + " \\right)\n", + " }\n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " }\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "00f650c2", + "metadata": {}, + "source": [ + "And, this gives:" + ] + }, + { + "cell_type": "markdown", + "id": "b8578a82", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", + " 0 \\quad (4)\n", "\\end{align}\n", "$$\n" ] @@ -415,7 +614,7 @@ "id": "2dd7d048", "metadata": {}, "source": [ - "Exapanding (3):" + "**Exapanding (3):**" ] }, { @@ -426,21 +625,27 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} X_{t} = 0\n", + " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", + " 0\n", " \\\\\n", - " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} = 0\n", + " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", + " 0\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) = 0\n", + " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) = 0\n", + " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) ={}& \n", + " 0\n", " \\\\\n", " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", - " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) = 0\n", + " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", " \\\\\n", " \\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} = 0 \\quad (5)\n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", + " 0 \\quad (5)\n", "\\end{align} \n", "$$\n" ] @@ -450,7 +655,7 @@ "id": "4a34e737", "metadata": {}, "source": [ - "Expanding (4):" + "**Expanding (4):**" ] }, { @@ -475,26 +680,54 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\sum \\limits_{t=1}^{m} T[i+t-1] \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}}\\right) = 0\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\sum \\limits_{t=1}^{m} T[i+t-1] \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}}\\right) \n", + " ={}& 0\n", " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\mu^{'}\\sum \\limits_{t=1}^{m} T[i+t-1]\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]}\\right) \n", + " ={}& 0\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "3a87f16d", + "id": "817b3066", + "metadata": {}, + "source": [ + "Now, recall the pearson correlation $\\rho$:" + ] + }, + { + "cell_type": "markdown", + "id": "c1337680", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", - " r \\triangleq \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (6)\n", + " \\rho = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (6)\n", " \\\\\n", "\\end{align}\n", "$$\n" ] }, + { + "cell_type": "markdown", + "id": "62a33c70", + "metadata": {}, + "source": [ + "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$.
\n", + "**Note:** Also: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$" + ] + }, + { + "cell_type": "markdown", + "id": "2ff6215e", + "metadata": {}, + "source": [ + "Therefore:" + ] + }, { "cell_type": "markdown", "id": "1543b1f4", @@ -503,7 +736,42 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\\left(m(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) - m \\mu_{i,m} \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m(r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}) - m\\mu_{i,m}\\mu_{j,m+k}}\\right) = 0\n", + " \\frac{1}{\\sigma^{'}}\\left(m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2} - \\mu^{'}(m \\mu_{i,m})\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu_{j,m+k}(m\\mu_{i,m})}\\right) ={}& 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\n", + " m\\sigma_{i,m}^{2} \n", + " + \n", + " m\\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'}(m \\mu_{i,m})\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {m\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " m\\mu_{i,m}\\mu_{j,m}) \n", + " -\n", + " \\mu_{j,m+k}(m\\mu_{i,m})}\n", + " \\right) ={}& 0\n", + " \\\\\n", + " m\\left[\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'}(\\mu_{i,m})\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}) \n", + " -\n", + " \\mu_{j,m+k}(\\mu_{i,m})}\n", + " \\right)\n", + " \\right]\n", + " ={}& 0\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -517,7 +785,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (r\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (7)\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (7)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -528,7 +796,7 @@ "id": "6adaea06", "metadata": {}, "source": [ - "Solving (5) and (7) gives:" + "**Solving (5) and (7) gives:**" ] }, { @@ -539,13 +807,13 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{'}}{\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (8)\n", + " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (8)\n", "\\end{align}\n", "$$\n", "\n", "$$\n", "\\begin{align}\n", - " \\sigma^{'} = \\frac{\\sigma_{i,m}}{r} \\quad (9)\n", + " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho} \\quad (9)\n", "\\end{align}\n", "$$" ] @@ -574,21 +842,91 @@ " ={}&\n", " \\sum\\limits_{t=1}^{m}{{\n", " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", - " }X_{t}}\n", + " }\\alpha_{t}}\n", " \\\\\n", " ={}&\n", " {\n", - " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]X_{t} - \\sum\\limits_{t=1}^{m}\\mu^{'}X_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]X_{t} - \\sum\\limits_{t=1}^{m}\\mu_{j,m+k}X_{t}}{\\sigma_{j,m}}\n", + " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]\\alpha_{t} - \\sum\\limits_{t=1}^{m}\\mu^{'}\\alpha_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\sum\\limits_{t=1}^{m}\\mu_{j,m+k}\\alpha_{t}}{\\sigma_{j,m}}\n", + " } \n", + " \\\\ \n", + " ={}&\n", + " {\n", + " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]\\alpha_{t} - \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}}{\\sigma_{j,m}}\n", + " } \n", + " \\\\ \n", + " ={}&\n", + " {\n", + " \\frac{0 - \\mu^{'}(0)}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}(0)}{\\sigma_{j,m}}\n", " } \n", " \\\\ \n", " ={}&\n", " {\n", - " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]X_{t}\n", + " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t}\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \n", + " \\sum\\limits_{t=1}^{m}{\\left[\n", + " T[j+t-1]\\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " \\right]\n", + " }\n", " } \n", " \\\\\n", " ={}&\n", " {\n", - " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}{T[j+t-1]\\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)}\n", + " - \\frac{1}{\\sigma_{j,m}} \n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\left(\n", + " \\frac{T[i+t-1]T[j+t-1] - \\mu^{'}T[j+t-1]}{\\sigma^{'}} - \\frac{T[j+t-1]T[j+t-1] - \\mu_{j,m+k}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left(\n", + " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu^{'}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma^{'}} \n", + " - \n", + " \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left(\n", + " \\frac{(m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - m\\mu_{j,m}\\mu^{'}}{\\sigma^{'}} \n", + " - \n", + " \\frac{(m\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - m\\mu_{j,m}\\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", + " {\n", + " \\left(\n", + " {\\sigma_{j,m}(\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{j,m}\\mu^{'})} \n", + " - \n", + " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", + " {\n", + " \\left(\n", + " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} + \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \\mu_{j,m}\\sigma_{j,m}\\mu^{'}} \n", + " - \n", + " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right)\n", + " }\n", " } \n", " \\\\\n", "\\end{align}\n", @@ -600,7 +938,93 @@ "id": "cfd5a617", "metadata": {}, "source": [ - "with (6), (8), and (9), we can get:" + "with (8), and (9), we can get:" + ] + }, + { + "cell_type": "markdown", + "id": "7a2c7400", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", + " {- \\frac{m\\rho}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho\\sigma_{(i,m)}\\sigma_{j,m}^{2} + \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \n", + " \\mu_{j,m}\\sigma_{j,m}\\left({\n", + " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " \\right)} \n", + " - \n", + " {(\\frac{\\sigma_{i,m}}{\\rho})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m\\rho}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\mu_{j,m}\\sigma_{j,m}\\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " } \n", + " - \n", + " {(\\frac{\\sigma_{i,m}}{\\rho})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\rho\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\rho\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\mu_{j,m}\\sigma_{i,m}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " } \n", + " - \n", + " {(\\sigma_{i,m})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", + " \\left( \n", + " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " - \n", + " \\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " }\n", + " \\right)\n", + " } \n", + " \\\\\n", + "\\end{align} \n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "f1cd8f37", + "metadata": {}, + "source": [ + "Therefore:" ] }, { @@ -612,7 +1036,7 @@ "$$\n", "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " m (1 - r^{2}) \n", + " m (1 - \\rho^{2}) \n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -635,14 +1059,14 @@ "$$\n", "\\begin{align}\n", " LB ={}& \n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m (1 - r^{2})} \\quad \\text{if} \\, r > 0\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m (1 - \\rho^{2})} \\quad \\text{if} \\, \\rho > 0\n", " \\\\\n", "\\end{align}\n", "$$\n", "\n", "$$\n", "\\begin{align}\n", - " r ={}& \n", + " \\rho ={}& \n", " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", @@ -655,13 +1079,13 @@ "metadata": {}, "source": [ "**Note:**
\n", - "* Note that eq(9) is valid only for $r > 0$. Therefore, we can use the formula above to calculate $LB$ only if $r > 0$. \n", - "* The pearson correlation, `r`, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", + "* Note that eq(9) is valid only for $\\rho > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho > 0$. \n", + "* The pearson correlation, $\\rho$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", "**Pending...**
\n", "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", "\n", - "* For $r \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$." + "* For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$." ] }, { From 9c1e9fd05c4d85d54eda9b1abc4d37e12c077316 Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 12 Apr 2022 02:59:22 -0600 Subject: [PATCH 10/67] minor changes to improve clarity --- docs/Tutorial_VALMOD.ipynb | 62 ++++++++++++++++++++++++-------------- 1 file changed, 39 insertions(+), 23 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 81c8af1fa..662b182b8 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -175,7 +175,7 @@ }, { "cell_type": "markdown", - "id": "c3b87441", + "id": "3b5c8c5a", "metadata": {}, "source": [ "## 2-1 Non-normalized distance" @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "9ecaf914", + "id": "1f7e294e", "metadata": {}, "source": [ "\n", @@ -228,7 +228,7 @@ }, { "cell_type": "markdown", - "id": "0fcfe4a4", + "id": "5a4d2b3a", "metadata": {}, "source": [ "Therefore:" @@ -236,7 +236,7 @@ }, { "cell_type": "markdown", - "id": "7e435c6b", + "id": "dc578dbd", "metadata": {}, "source": [ "\n", @@ -250,7 +250,7 @@ }, { "cell_type": "markdown", - "id": "cac0c884", + "id": "b51f7143", "metadata": {}, "source": [ "In other words, we can simply use the p-norm distance between $T_{i,m}$ and $T_{j,m}$ as the lower-bound value for the distance between $T_{i,m+k}$ and $T_{j,m+k}$." @@ -258,7 +258,7 @@ }, { "cell_type": "markdown", - "id": "ce92bccd", + "id": "0b539ca8", "metadata": {}, "source": [ "## 2-2 Normalized distance" @@ -266,7 +266,7 @@ }, { "cell_type": "markdown", - "id": "d0773bc3", + "id": "91ab346f", "metadata": {}, "source": [ "In z-normalized distance, one should note that $d^{(m+k)}_{j,i} \\geq d^{(m)}_{j,i}$ is not necessarily correct. In other words, the distance between two subsequences does not necessarily increase by making them longer. However, it seems there is a very nice relationship between $d_{j,i}^{(m)}$ and the lower-bound value of $d_{j,i}^{(m+k)}$." @@ -315,7 +315,7 @@ }, { "cell_type": "markdown", - "id": "6447a1c8", + "id": "72a47d5c", "metadata": {}, "source": [ "So, the Lower-Bound (LB) value for $d_{j,i}^{(m+k)}$ can be obtained by minimizing the right-hand side:" @@ -452,7 +452,7 @@ }, { "cell_type": "markdown", - "id": "ec55a584", + "id": "a3656f16", "metadata": {}, "source": [ "**Deriving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}}$:**" @@ -492,7 +492,7 @@ }, { "cell_type": "markdown", - "id": "4e757a6e", + "id": "6ef98f3f", "metadata": {}, "source": [ "Please note that $\\sigma^{'}$ is constant and thus it was factered out of the summation.
\n", @@ -501,7 +501,7 @@ }, { "cell_type": "markdown", - "id": "ced6809c", + "id": "cdc74b21", "metadata": {}, "source": [ "\n", @@ -514,7 +514,7 @@ }, { "cell_type": "markdown", - "id": "14e92a2e", + "id": "393ddb8f", "metadata": {}, "source": [ "**Deriving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}}$:**" @@ -589,7 +589,7 @@ }, { "cell_type": "markdown", - "id": "00f650c2", + "id": "c3b80336", "metadata": {}, "source": [ "And, this gives:" @@ -597,7 +597,7 @@ }, { "cell_type": "markdown", - "id": "b8578a82", + "id": "c398718a", "metadata": {}, "source": [ "\n", @@ -691,15 +691,15 @@ }, { "cell_type": "markdown", - "id": "817b3066", + "id": "0c839937", "metadata": {}, "source": [ - "Now, recall the pearson correlation $\\rho$:" + "**Now, recall the pearson correlation $\\rho$:**" ] }, { "cell_type": "markdown", - "id": "c1337680", + "id": "82bc9b8e", "metadata": {}, "source": [ "\n", @@ -713,7 +713,7 @@ }, { "cell_type": "markdown", - "id": "62a33c70", + "id": "4880c751", "metadata": {}, "source": [ "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$.
\n", @@ -722,10 +722,10 @@ }, { "cell_type": "markdown", - "id": "2ff6215e", + "id": "a01fd0cc", "metadata": {}, "source": [ - "Therefore:" + "**Therefore:**" ] }, { @@ -818,6 +818,14 @@ "$$" ] }, + { + "cell_type": "markdown", + "id": "b266cfb2", + "metadata": {}, + "source": [ + "**Note:** eq(9) is valid if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" + ] + }, { "cell_type": "markdown", "id": "a0e36dfc", @@ -938,12 +946,12 @@ "id": "cfd5a617", "metadata": {}, "source": [ - "with (8), and (9), we can get:" + "plugging in (8) and (9):" ] }, { "cell_type": "markdown", - "id": "7a2c7400", + "id": "f3e25620", "metadata": {}, "source": [ "\n", @@ -1015,13 +1023,19 @@ " \\right)\n", " } \n", " \\\\\n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", + " (\\rho^{2} - 1)\n", + " \\sigma_{i,m}\\sigma_{j,m}^{2}\n", + " } \n", "\\end{align} \n", "$$\n" ] }, { "cell_type": "markdown", - "id": "f1cd8f37", + "id": "d836a69d", "metadata": {}, "source": [ "Therefore:" @@ -1082,6 +1096,8 @@ "* Note that eq(9) is valid only for $\\rho > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho > 0$. \n", "* The pearson correlation, $\\rho$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", + "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho)}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", + "\n", "**Pending...**
\n", "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", "\n", From ffee3db4ae63bbc1e5d4680012a3672c25ae248f Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 09:36:32 -0600 Subject: [PATCH 11/67] explain system of equations in finding critical points --- docs/Tutorial_VALMOD.ipynb | 28 ++++++++++++++++++++++++++-- 1 file changed, 26 insertions(+), 2 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 662b182b8..366f0128c 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -107,7 +107,7 @@ "outputs": [ { "data": { - "image/png": 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Lt8GvH1wZmKuEXofrWM2yr9q2T2sRbIvzL50K52vizNlizfYDcPEtiwrWylXMXq/57jR490+K7my8AkmFFB+nvRnHgo1hFDqcAQtWDhhqzf+hbv20wSu+fS/8889mOtPZdWAENnm0Kh8da8A5X7kDLrohbFwiG2Si3oAmhlG/wGVtG7cf+bsfPwA/uW9F4dmelhVnJ9y+1o1WpiokhVFCggfI5g3ZhPKFPy2Av/vxA7Bmu52gqbJwyfDc/70dzvnKHVb0VcGOfaOKcEC+i1ApoKpcRPYOjcLnbpoP+4f1PuGUUvjOHUtgw64D3HN9OWyaH9y9FAAA+gWrh++25HnzEctIRaHRoPChX82C5/7v7UY0F6zbBa/+zlT4SaCbdmQ8D46MweSLpsCP710apFwf6Cc4C6NMYXnv4i3w+T89FpwvHWat3A7z1u6sm42exd2LNkkPPHzA1cIom+df/q174WXfuscHS5Ui+/69Q2ZudphbuUzRRSEBKwFrYYTpxTa3pPlWgo4faAoMVQVBrhIvueRueMHX7/JGL1OW/OVRsWX8j+5ZCtOX+ncJVaPY03Q32GYKJZk7pGyuyQ6WDhrXD2MNCv/261kwe1U4j4sEPJLCKCHBA2SnXjIl+YJ1TaGLvXWlSQcHQ4tk48WFtSypKsBzCDVLKN2Naf2HwpVTl8FvZqyGn09fqU27cMNu+P5dT8BHr5kjTiD4prbisFyRVejF+HEVuivuHxmD2xduKmyiMMgsnxas97+ZApALV7tbwfZ/dv/KIOX6ANbCyMeYopRqXYVWbN0Hz/jcLbBq2z5lunde8SC85YfTxeVYc5iAwa79I/DBX8xyitXHYuf+4dLmy/UAuwMOwI2B+aQ3fO8+7+Umi3kzGLukjbZbFnPYCADwj1fNMCqDhWi5yhVGNblZvfo7U+H62Wu16WxCCewJFMRZNh6/ddtieM/V/oPOK3mRuaRJZBOdy5rMgmj/cFthtHXvENz22Cb48G8esWUb9g6NwnxPl530OpLCqGZc89DqSk4xfzNjlZHZb4IZZJtn3dW7Yw0Kr/vuNLj9sY2F57o13VSJ87uH1xilZ29JC28xEy7CdqZw8KFoYNlTCV1V3qCW9S9MG2XrtolJePYtorWdfcZ/sy+3Af6zfNSsa38W5c+sZyYOhFlSZRy3N1r23xTSigOAiWE0orEw8tC4v56xCk77zM2weY/cPeD62WthaLQBf57rN65Zgj9km8qVGqUeFh+9Zg587No5BYted5e0Yv5Gw+6yg7f9aDp8+S8L9QkrAD+1vejiu+CqaXHF4rKdvqct2YKO3xM7ChZGiAoZHmuv+Tpdk1/lXZu3ui2Mlm7eC5/4w6PadFVeZtFJyMM7tPpHf8stUmdhJNMPyqzFD7QOliaN78/lbJe5+sO/ng1v/uH92gMrAHPZsMc80pLCqG585sb50lNMEVZv229lKvq5mxaU/MYT/EE2n+lOu3cPjsDiTXvgU9fPAwD8hNVvuLviU+tKyS2MusYlLcx17yLE6tcsU+Jkt1kob34T5GWfkfzf7j8pFp2MZfEZJoyrdkn1MU7/9y9h3b9yCyOBovK+J7bklh/Yk28VbpyzDgCa8VlkyDb6fbGYCSaU4DtOzfqWGy6rLHcNWs3n/8HdS+G8r98Fa3eYyWdz1+yEn01foU9YAfh6X79rEL5+c/gbgUyGvm2rve9nM+G1351mmTsumN6SNsxYGNXl/je+5cNu4x6XEA+y/qOLYdSntTASPz/QCq9w0Ph+YRwkLL535xMw+aIpMHvVDjSNbrQa9YmBuhlIMEPmK3/e5KNq5iSBhdwlzW4G0i3qMnmBUrwL2ebdg7Bp9xCcddLh5fIzehU6X3TSXN1NW83M8kMdl6n8TLLeS9PbgCcTWtjFKPtEAlJ2KjZxoN87TwDy+nS3LwofXDJTBA0KLIz+6afNgKNvfu6TPAWm16fx8bmR6oQTJMj6INtu7jGMin9PXbIZAAA27R6Ek46c5ES7LqR+HRfmrtkJDy7bBv/+itMKz02V3ezm3Idi3gbjWgojXSy7EIj1EE+LiNjmqzDrR7J5NFcoSRZcnYXRQeP6832OjXL/u3c2b6nOD4gQ/d7YwsiYq85GsjDqcPRah60SJstqeTJt/iub51zXbNnkJwswJ0r+im/fC2/+ocT8VmS5EEjQUFEdGh2DP85ea73gs9kopcJrSl/xrXvgF60T3m17h6SmqyytKt3OMHCRh1QCXPaVYpe08KeW5Xb3oFSwfJeBjcHwywdWwgu+fmeudJs4LpDCSMMZdnxcdP280vXVpqfVtpCdNGbguXCxAFFaAHp0U00IAx+WinsGR+BFF98Fs1dtF85jvl3S+hTuuzEipu5fcmmmFP7y6PqobtSqA2/70XT4xq1lCy/TObuuPskOEaxLGqXUKo5QJ+L+J7bC2388XSiX2iCkYoxfN7M+ODzagJVby67DOpc1VpHE8n1guFkXB43vV4ZEQPNtkLdDpu7akBRGHYLzL723bhYSFOAn6lz7bjjTYVPLNjuygIIllzTaDi4nTk+M+PEB0WL3nduXwP/9w6Nw5+ObnWgT0ozj9LTP3lK6JWzltv3wpVYMied99U74xysfRNELiaHRMXjVpffCtCVb1HxYiP18HpUA13Z5EriksQq07Fmrx/jqN6EtjHbsG4ad+9sxfDDCBSvcffHPj8Gm3UO5u9WEQDGMZMgtJ5DpRbHMQrtmsafbQ6Nj8Pyv3Sm82plXggdzXWhVVi+4T3YqfFi2zl+7C9bvGoRv3baYGSdtuioLo+37hrUxLxqUFpROWfdtNCjcu3gz3NRyj+wkxGKIcd8TW+Fj186Bb926uPSuY61FPMI06DVbZ3VZGGVro+xQM8PPp6+EN/3gfnhw2bYq2KoV/3PdXJizeids3Rs2jqALvn3bYph80ZR20OsshlF/899v3LIIXvHte0s3Pg9oblGTuaRlinhWiWzrqQFgtpa4lNMLSAqjDsGyLX6CPyaIcdmdS2DyRVOsNf0yc02dcCN3NVEv6rJNnmzCM7WIcZUp5qzeAb99aBWyLHlhm/cMAQDAbu42OSzY6sgE+JVb1TEmHkXcqMALXdltVQB+rI/W7xyE5Vv2wRf+tKD0bvPuQfiP386GfZ5u5sCc4gpd0goWRp2z+Wa/5Zyv3AFnf/kO5h3CJU0gAA0aWBjtHRqFq6YtM7JwkM4THmIY2VoYffkvC1GBJNkbejbuGoQte4bgK38tB/nl2eCV31+/+fHCOBMBUw1ZGhc9WZWuugl26MvjX7DKnPZ71WHO33zlDniX5paoBi1aZxJGefv+nz8MH//9XCu+q0bBCremfs0PxR0tJf4GiyDiLvjIbx/pCOuWgULQa316n4biK7fu0946pbwlTWNh9FjrptE1hrHATPmJCTGLTz+8ZykAMH2IszDKbojbsneokK/fwCWtaL1fTutibWyS17Sf9JryOimMOhURTzCdiCunLgcA+ys/ZZYQroE1ZTANem2KnDq1sxZ5+48fgM/eWFZ2qCAqx/UrWQE4+2VbdSwtfrP5kd+2r/30sYioaHz79sVw8/yN8Nd57VueXErMTvzE1VI+mc8gUk76Xj9lithQwAxXkeVLpjiZiAh6/bUpj8PXb14Edz5etrKxhUufMz2tzvCz6Svg2pmrtemyk0TdxpRXgvMxDq6athy+fVvZ4kAE1RdlijpVX+KvYE/oPLA37LTdxdp9SuMhCXPX7FS+b1Cax9sAYN133SbBuxdtQiliQ6Cu/Q8/FOviY8r8DfDfHaDoy9x90GDq03UNVYYykBebB71mb2zrdeQyqS96AccNf8Cl60cD/ToLI7ym0+W7OsVFuBOQFEadijQIvMIluBqAfGNrSg47McosOnTBcdvp1AURgYAdClXoPgkhjCuKGCabbt4CbNnmvZacSXjJyvGoIJF9XqYAURUl6seFU0tkWeYoEvJRG6pTdEx/FwVrzOYNjCC/p2UlM2gQ/FPHlv69PIHLBkI0Xz7z87fAB3/xcP63bVBtkWJO586gw/SlW/Mbs1Sf/bFr5xjR7bWTxuogb6RH1+yEyRdNgTmrdwjft/anMEZp3tZb9g7BlVOXAaXUeW1rcDHx8v7kQPbRNTvhg7+YBV+dUrbAqwKx9OI6LfhC3nQ5NDoGky+aAldNW+ZEx1THX7jRtKbD5jzoteDyg1Cg3L+xIZ+CJG0SkyUrv47r5Aa9hVG7HwhTMPOz6wUFWCSXNDWSwighAYrm6zYoB8AUP8fC9pY0X8hdXcIWUyxLUZgtHyKrhoJvNNPgOuuyYgDw4rtQpxhVyHbZgv5PP51ZcvlRtQ27STbtL7fM3wBLLZRs4W9J06cR+d6b8JW7rnixRNOn+dQfH4VTPn2z9L1L0GuRQnNwpAF3L2rHHJPdhsKDF0B1rgtCaCrkPVc/BDfP3wgAbspYvpgkZ4aCvGLvWby59a84zhsbMDVr6o//bi5cfMsiWLBut/MmhJ8GTOOJibCz5Xq9aps/dxwZRN2/LsWndCRqDiqwMPmuCYFuugQA2DPYdN+5omXRbgvTqcv2wg6f/SGzOMHKSt3iRPGz+1fAqyqKQRti9PbnsYhaB4uysrnCMy8I2WUXMkWSKByHD08NlOum6QG/HSsdi6QwihTaibpbZtNIwJqve6GnCfgm22BjSze2CrBMXlAKmJEwKEvu9uSrUAJtQYXdH7ObBpMNKr/HFvHuc0Mqgw8Fygjz3XyQbVE/yFDs2iUbI2WZ//7bR+DV35mq5Y0vNnSgYoyArLJykZ0Ibt075HQTivaWNMW762atBQB5/zZ2bzBEZilEQd1+/JhyCXqNGXs+e1I6mYwP/cyanq2XmUJ8tNHwcksaS0Hk9maKusW6unpx+ZY0RWILJk2aJOTFBe3AwR5ptipk+75huKJlPScr17RsflNvfO24UOFXXS8LNZ4GR8a0F5Jk+PJfF8JyaQza1iFm7SNfjkxhlIcuQAqdJjGMAAB27R+BvUxcTgrVW1ilVVyNpDBKSABGi259fbvYXBMrPJouF9I529OMxyq0qtoLKS2MHJkgpE2DrbuGpcKIX+B1FjjmCCBZtsD3nRHmBEimiBR9ieiGIN8n1GWFatiTJsweMhN0RJY5Itp7Bkfg3K/emQd6tmlSGc+5yb3S5az578Zd4gCy/YGlAGyL8V3PxpXNJIdPK80UJyEU7BuJXYPbiu/Wv2B2ai1SLpWU2blVsSGjESEWvWdeh57GqIkSz5fCaM7qHfD4ht3Cd6o9976hUfj8TQuUl1qI1ulP/fFRuOSWRfCIwEVTpNjEgJeJ3PpHfUoR33LJ//5lIbzvZzOl7YtFrkCUuaSZWrwEGMBtS6FMuYWDLoYRK3dSSuG5X74dnveVO2oNAG6q7I9lvqwKSWGUkACMC5mltMdna9NzYMojSgoORA6AaiZE1QLhevJSdElrU83Ato9JwHPeKMN3NYU4iZSBPekxie8kjGvkuSKqdv3BKKQyQUd0U6Eod3ZqdttjxSDXPr9FReq4QycCAMBGyY1DoS2MsHOqF5e0FjDjRnbTpA2ShZEZrp+9Fl757XuDlsEqcESn4iaHQ6L2lbV5Va6mQWBYrssYZVEOeh324EEF1U2X+4dH0Zaib//xA/CG793H8SHn5PlfuxMuv3cZ/PT+FfDrGavg6vtWSNOy1ZVV1e6Wu5vIApatT5Npj7fyxNajy8GOS96te4fguofXWOfHYtmWpjv9LsvbezPIvjSm5STrL/oDnOL7TK6Q5RMpkoa8KiiLwPSrmOo9RiSFUaTAdtzUwf0g26yMCqwmMOAnI6yFES8YhYohYOzBVmEMowxBYhjlcYvaCg62Luxd0vQWRlVeNe/SbVR9XhW8nQpVcO78qIAh+63bFsGLL7nbij5Gt9FQnLSpFGtZ3bbHFr6SspSDI2Pw2PpdQCmFH9z1BKzbcaBVRpnW/U9shZ9PX8HEIBCXJ4thtHTzXvj338zWjouxBoVrHlotdSHLeDPtE7Y3VmKBHZ2LNupPkdM6jMOX/7IQJl80BT7xh0dhxVaZm4YfZP2+0aAChYTZYY5IuTRGaaHdfcQwwi4Zc9fsdN6simC6Wb/g+/fpEyFg4tBsU7++XNLO+MJt8NFr5lhwkDGS/Sg39JY9Q/CNWxfZuy4j5SeRhdH7fz4TvvrXcqB103nt8Q274Q+z2gobUbBt14tdVPiP3z4Cn7p+HqzeHj4GmA/kVu++6Hmiw6KPj2GEZFZ3CD+iCXot6yeX37sMFq53s+ySIq3jSiSFUUICtBdRdlNlsljyc2K22GVBDmUgEiHTVtkgE/iMXd5ygsUFf6xB4aPXPKK9ctgXfOlcCJD8W1iS7EabP91Q82UWs8cUuUW+z1vSEGlk5YkUEsVAmpZMacD3Z4xC9Uf3LIN1Ow9Yleca10TlmpjNMXYuaU0a/3PdXLjg+/fDo2t3waV3LIH/86tZ0nLf+9OH4H//slCrtJZZ2nz6hnlwy4KNyrFOAOC6WWvgMzfOh5/cJw7kihUG+Y2MTVsYbXCQnfb1l90Hm/eIrbMyJAsjHH42vWg1ETLIctvCiAo3yRgLo7/78XQAwLkc+3TLVSluKKXwth9Nh/f9bKZzOXxZpqw/4fl20DYj7Z9Do2Ow2jEIuIkibLzGJe3WxzY68NEE5kZSlSWQqVxQ6JOCrPcu3gJX31+2aOJrTde33/C9++CTf5wnfJe7hSop4LBp9yBMvmgK3LmwabV7x8JNMH3pVti6ZwgAyvFxYp+dqzxcNEUphpEknaxrmFgYsfRlY/Ybty6CC37gR1HNQ7SOP7xyO/xkmky2ib1n+UVSGEUC241KxPNMRyFbnG2j8cviGbz5h/eb0bEszxTamOoSRdam3YPw13kb4N9/M9uNgUJZiESW3ytySWNJ5dYiRG9hpJK5QrliVT28S5ZTrdoSfR67uIYK2lhySQtAE/sOw4Mq4Gjbwsjc3TNL+siqnQAAsLeliD4wMqblKbfwkaQaGhmDl37z7lLsCyx/u1uWDjv2DYvLR1ptlqxAcMWjaAnTGNDjFf983SSFkR1CVltGe4yJYcQC02aPrN7ZpCGQCxq0OKb6LMY1D3YelVlgZQcbjzoe2ojm7Np6sTSIC8An/zAPXvate2D/sPrwTQWTNgkZgBizrmf9UqTIv/zeZTD5oimFvov5NJElHAZB5jUPNNfuaCoQv3PHEgAA+D+/mgXvufohZ7pVQ1YTtoqIEM1VimFkuOmU7W1ZpZ7o8JFSvy57trLd31/xIHzt5sfNC+xCJIVRJPjp/Svgk394NP+7KsVBQhPZJMieOvLz4tLNexQUig2h8xPPbwaTmKT6Fll8XaoWsruJNtuu9cCe6GXk2QWsfZpHDC2MxOXwv11RtUKY77e58Cz4qIZkkQ+JGGIYtdOWIZKNMqE7Vxhl+S2+JaPx3p8+1KKhJ6LTgc9ftwvWbD8A375tceE55jScfU9pkZ+te4dgy54hJtCwxtIJYWHkczyYbJx09dzJgY7rRNj1pP1vua2p0SGdMIYRlz93wfD0Uf/261nC5+dfOtVPAQKEtPhSgW+dT13ftlKZ9kTzNqqhkdZtixY8mlmLh6mDBet2wWBLwc92x6lLtsBvZqxiypfTuOzOpoJEdVOnCGxq3azH8uZ6YDM40siVO+gwB4hCJo0fAACApVvEFm7lUA96mnWgPUeJGYyB7T7NbWe2kLmw12ltVdf81ykYqJuBhCYuu3MJ7BseKzxLnbc66OJ8AAC8+ycPwczPvlr4jm8q42vvc0K4ZKa3KpiemskUAKY+15fcsgguesMzlWlwmn+3sUAAoNGiwTZx1t59CAsjFuUYRn7HakhTV1XblWMYNf8Vu6TJefTFfdVToJFMxKRtK0UEyRilpCS7vigdDaXVlLqkzAVDJhDq+kvG077hUfj33zySv3vfT2fCwg274SBFEFkW/Im6TdObjBuT4K+6fpHWas/wUJ1ZXxgTxDDKnmMhindUzl48BHKBioStuy0GdSk+Q+8RTeYF25tyVdi8ZxDe9IP74QWnHFV698+cayHvwszSyA61ikodPb8FCyONmUDRKtutLv5v6xB85SUXCOnr8r7kacfACYdPlPJYGsOe+hGltNoYlKXyKytaiyzGYRZbC3uYrPsGtu0eXrldTLPiijCd/2JqpyqQLIxqBHslo0hYt3WPSjAHxiVNpWEvuaRZ8sEGafYJU3ePTMEkO23DLqZXTF2GSifjydVyhV1wcgsj5llu/QFEO96UQZ6Z3z6arm26rqbm3xKNCP/O6mn3YDvQqtCM2Hssp5IYEoBmG5jTZZXFjDjoNadktQpipH6t4jvv1pIk4/qbYgBvMYEV1rI+cu3MNYX4Hgtb65toXIlI89XSoNRaYMQoyE3mWL5+y7G12N9p3cYiZF2xm0ph0GuDsmW3pInnQHuwfGbjsgpMXbIFpszbEF9MDlKeK6wUySYWRgHk7n1DzcPgLB6can7K+hrf/Od97S5UWSLKRdnFYOKzlrv4v2nJqh6DexZvtmOgIriHhoj/oLEU39XwsFqGEWacidwJxYdv+kJ27BuGOZx7vYxeOU1k819kSAqjGsFeuVkSSClVajtT6CK/6ENYGGXYPzwKYw0KDyzdCr9umRLz7YdVqMhKYxf1WxdsQNFSwfaWNFPMXbMTtu0dssss4sNXTyckH09Fl7S2gs7kZJFv31D7nupd0sQFUtrsh5fd8UT+TBTDyHc9lAVPv/TL5eELwCZl3R6ty5IpkhWWTe3ycRZGsv6flTky1rByG8XeklbqexR3Svn5mxbAGotbcUxOkHV8FGKKJJkTDbaqRsYa8K6rHoRZK7d7FXAolQS9drwljR9X2aHTXs1FF1hUpTCitGnl8pFrHqnNByZk3CAAs8/ivb32DY3Czv3i+Gy2fOCCXssTmVhHAogPd2QoWC8p6GDLy/5uB6HH0QCQj4FioHbEIY9hx65qDs/PcjTlzV613atcbYLMIi07MMeOVV0VjplcU2mA13x3Grz9xw/YZU5rtxJBVyRCyDMIIXOZ/3YTQj5OCPkSIWQd8/yNIfnoBIiDKqbeWxWyxRnjp3vGF26D/3f9PHj31Q/B529aAADlecbnRv/DjJtHhsoWNApgMou+7UfT4S0/nO5QVhM79g0Xb6yzosjTb1IRuaT19xGjBYwX2LyfFAVoXwyPMkGUQrMfsrccqYZKKMsBP/3A7l0preCZynWvHcOISPPrIHdFVVgYtRpKlmKCxMKIx+mfvQW+8KfHivyAfvOCXcf4b2sgrEDmrtkJv56xCv7zd3MAwKz9TKZoHR9s1aV12w7rdx6AGcu3wzuveNCPS1p2QEDF48bkgEBsYVT8OxvXn2BiUdqCUoDxFVoY5eVWXmITJsHwbWBkTcY17Mu/dS+c/eU7nMrP52e1kUaz/Hy9kKcyVbCxX6RTlBetJY2KycGPLSr5rYPsxjrK1KMo9mTHzMACRkfHGrBoYzFe6jsufxDecbleCYJtr0dW74AF63bBP1zxIOxhrMZF4INe+4IuDheldgrLrQ6KteTUo0bQGEaU0sUAcDYAACGkHwDWAcCNAPABAPgupfTbIcvvJIg6apI7q4PppPjH2WsLf/NtZRvDyNnEVfrGLoZR2fJNn9c0xgJPc/rSrfCeqx+Cr7z1TGdhUcQuK8xkOiIC+hNn1Sld0e/fHcYnYhalsoHA82eSfqJytWplbPERFjbj419+8TD89P3PR6XFDH/VTWgi/vgT46zvPLxiOwz0Efi7vzkJUWbzX759KPevKq8M2SmuSsjP8GsmOGsG0W0+LLBCWEkJa9CrS/0YMW/I5uiZK8rxFHR1WHB91Red0AJbrweNb8e62ia5cc8E2fzUYNxh8nLBzPVIHMOo2D91sWEwYLkc6K/ejjy0zPnEJtXFIWL4sDI1cknjErtsQG1A8/UCmT7/V/6R7PxkFruNXxPEZSxcvxuOP2xC/jd/8Np0SSvzosN4xBjYN9S26MtS7+fiwZqi6jmcAoVV2/bB1fetgEkT+uHKqc1r3Nm6WrnN3IpWhJGxBvwdY4Fz96LN8NaznyxN3w56XZwEXd23Rg0Dt7uiHAidws79I3DkwePbz9LqrUSVRxjnA8AySmlZ4kwogUI6qawSGJc02dLVaNjH2pCWVbPPYWgTcRGyyTpzL5m/blf7nWX1sidR2e+F69uxw/IrbImZhZFs4+4bIQMv9gtomwRTF+iL2u/s2VKWa7Og37VIHwfhx/cuBQCzObeoJJBb8WTvcoVR6/kfZq+F/7kOZ42Q0TUNdg9g4JIm7f5EOb+5ut+2SynSadCwG1jZBv8frnyw9EynOGeXjbRs41EYz8xPH6fZGYUGFQe9do1hxI8Jn2smBZpfxBEKojoJvWF6zXeniXmRZfC2kOCThowd2nYt1scw8umSxkIbF1HhkibDG79/H7zx++0QG7wsZVKjbFqZhRELVjkkK8fXnPyRax6BD/96dv63twNN2qT96xmr4NcPht0i8/37v343F7556yJp+nbQ66zvitNRSuGx9bvg1d+ZCrsHR7R7Ipm8jb1M5Ru3LoIZy7cpy1Dh8qnL4Jyv3AHrmQNu037Sa2t9lQqjdwHAtczfHyWEzCOE/IwQcqQoAyHkQ4SQWYSQWVu2bKmGy4jgojD6xq2L4L4nynW2de+Q1gSxF4EJeg0gnsz2j4yVFipboSPUBFS2iLGwSIFArlJ8ANnWv32EoBfks798O/zrLx+WviekXc43mMUxs6ogBGFhxPzmN5tsffoQ8325TakgsgxpWh3Rwt8A+FvSQgdx9EFeROKbtzavlEcFvVbQEVoYZVZspPivDWziIGVTkSxpJpSXg16Lf7MgxN82WTRHma6BZi5pgWIYpVNKNEIK3NnYaAa9LsecM1mjRWnHGtz48zEQMktN6nDTKgPM/LB2h/2GyRdMPtVmfJnkCemWgqlfNq6iDESg1VHNZ2y5P7pnKQyN4ixwsv5z64INMPmiKbBtb9vyb3SsAYMjY7CjZQ24aXfbEouXpSht82zSxzBxvDBrxHpjq3cxzSnzNhQudnD2CKhhwInmsh/fK7+chg/XIetlFAC+c/sSWLp5Lzy0XHzrGQutSxrQUv2y9XX5vcvgXVfN0JYjwy3zm+24eU+73yYjDTUqURgRQsYDwFsA4A+tR5cDwGnQdFfbAACXivJRSq+ilJ5LKT332GOPrYLVaECpeuFapTFPvPzeZfBPP51Zen7uV++El3/rXkfuug/9BkGveewbGi1N/Do6+Xov24gZc9Ei53vDzp3yZwqWdTsPwPy1uyS57MsCEAtMOoFv5/4RuPNxkSUJs5ETkMivsO0jZkGvFRZGKiqUUvjLo+vzK0r15egS2G8qRDmlQa8Fz9guXlUQ8NDruQl9sfuZQImGOFXWl6UW1lTQCUGZ68sYpXDrgg3w9M/dAgeGx/IbfXTwsbEV0cG0haroA8NjysMRE7Z1c0MKeu2OwhzqUTHcoGKLDDNrQn1+X+Mgw4AHCyPjE3PJ8wXr/K71AADTlmwxdl+3hYtLmgxjDQq/nrEKRkyip6PKb/5rul4oXdKYdws37Iaf3r8CR7OV7RcPrAQAgMWMS+Hbf/wAPPPzt8I5XynHdypbGLXLNxl3sjhemMMMFq+6dCq6zDogm/tMp0FMXWDitLLg90a+4o3J9kjBZEfu72zcsn1s/c7BMIV3CaqyMHoDADxCKd0EAEAp3UQpHaOUNgDgJwBwXkV8dBRUm/+Nu5sd2+a0ZbuH+ADdhmxxZjcGQpNtprqziXTv0GipFUwn5dCwFT35xZ39+80/vN+BozbKpwjZLwIux7art+1vm9GCePHNZD2MSxqlFH770CrYMzgijGG0f3hUGxfjT3PXw8eunQNXawQ2zCmjK0TTi+qWNB7FW9Ja6TzwpSrX1nqDbRelyXOAYZvRzPZ/NjY5hSEheo4oX4bMNbHRoPCt2xbD8GgDHl7ZPiFsWufJYbuv/fQN85Xv+WvLTfHSb94NZ33pdnsCDErxD0rvxb8T7ODjpDc/gGhQ4YhzvSWN7xO+Pch8uKSZbzjFOd70A/e1nqf9vp/NhNe3XNSkc6KnOnV1PxThmpmr4fM3LUArXwDa7aFa17N6ErmM24L/pEHGjeuah1YbEGr/nK9QIpZjGLW/2aRPDmBuSWOe+6qxqqZwUTmhLVSxh5UZ+vMYRn75GpG5pBV+q9ddFwxnCqOBdq8RuaOr0GvWxFUpjC4Exh2NEHIi8+7tALCgIj46CpHpHLoaWWw9ldJg275heHxjO/7NpFaQzqaFUTEtHyBOhgc5H9xQE5Cp7CHjI6QJLU+5YGFkWOya7fvhZd+6By69fUmLFhEKgtkpRx/CJW3Wqh3w2RsXwGdvXFBSrAyOjsEZX7gNvjJloZJGFkBz8251IM2gm87MNFzQxnwgbN7qi4XYTc0Pizk9T/Sxwg7KJa1gWVV8pgoO7iL/Z2RdLIx0c8sYpTB+oDmn8TfPqMa9SMko/FZajCVz7Uz1RqVpZVssV/f9bOqte9UHIyYWIcklLQxk9Wo7ZlZu3QeTL5oCdy/aBFlvGKNU6Mrp45Y0/x5pbSo+FEYhXTpNIaK9JwtYjPhUfq41Kpv7+4ZH1sK0JeIwF1gr890HmtaLuw7gQzzwN2aK0MgPseRp2P5sdWjA5P/MjXLFvWldk1yOtj+UEbnEY9P7wvSlW73TFKEtN9j16217h+BRxhIYs/aYelHkLmktAVl+MQr7W1+GNui14LXPph5uyTgYt8eEJoLXFCFkEgC8BgBuYB5/kxAynxAyDwBeCQD/HZqPTgMF8/gNCfbIJkWd0uBCxmc2E+hE1z9jJ+Wrpi0XPtctlFKFjiS9baSRwukNIUanshl27sdZtGVVuHFX03qOgP0me/OeJo2ZjKWEqHLYK2x1FkbZqdy2fUPlG51atG94ZF3+TMW67rtMN0xWQrTQwohPgxP8fMTIConihl4OU6755hG7PTb/5W9Js4GNW5tuHcnejjVoHs+IdbPQ9mNBAptP5Lnkb6HiMTgypoitpC8va4/dgyPw3qsfUrrH6KZz9n066MGjYCnAbjgEzzDI5vsp8zYWlN2icWN2S5peYe7zggIK+tsHUXQi6ouurLCba9u8Gf7nukfhfT8rh2ywpY/mo/Xvmu0H4JmfvyWP/8MCE/QaHd+IKzdPo2M0z8dbeKgrpz9XLpQtjGQ0Gg0KG3bZ36zrcz3P8P6fy+NhsvA15GXzoA5v/dF0eOuPphuVZeuSNqIJet1EdhhZ/I77n9gKV0wtxkmS8RHMJY2jm8k4Lq7EMc2vVSC4wohSup9SejSldBfz7J8opWdRSp9DKX0LpXRDaD46EUlhVB3at6SplQYiIY4KNjYhb9qoEiqXNCzO/vIdcOsC+RBnKe4fHoUf3tO8scqnO5bMJa0tnOmVhewJp2xz4IvnPI5BLbfVlX8LFSFMSrPzTgNePM2BPi2M1PnlNLM6sukjeRwk/jmCXexU1GhQmNA6bRvmLYwU+UL10KbQKS55zfb98MzP3wq/f3h1ntYUWTtMmbcB7l+6FX5w1xPStOVb0uTzYmzK0k6ErgqXbdkrfD400lTqTxzX145h1BAotMFsjRYl5fN7sTBiiEzwcPJtau1WV9eV1h2Sn4Xrd8MDy4pWIRff8jhDBv9hVclugyMNmDK/LBe1Yxjh6GDmm9KNfhLatzEBnVlesOjLD1HLiqZMluHZvXzqMnjhxXfDiq37SvRkn5Y95i2iq8a3b1vsNN+L+mVB/tKQZgPWY9IDmPfvTAmY7Y1sYhi996cPwSW3FG9i+75ivQVo1QPln/lrbF7GwWD+2l1wuSJAeLcj2WJFDGv3C89B+HoB7VvS1OkGZHcxc22lNbfkYHODhBl9s/Q6VwFTzFyxA1MqDI2wlg3+1BD87V8ZsrWzj5gGvTZ7bg7/HYGnKCqBrwKlSxozVkpBr83ZE6LEM/fgH698EJ72mZu1dMaQ4xElfLOKstJ3ywVAJwsEw02EkAR7KltQcDT/bbqkNee3j/9+rjQvD+wJnWmfECniM2QKg1sXFDc4JsK7iQGHbt47/9Kp8EQrIGxSF+EhszxQue789qFVcP6lU2HWyvKakrlSThjoL1gFuQa9Fm2y+Ow+LYwAAJ5xwqEA0HZ9t4Hpch3SnVI1NjF1p0ryxu/fB+/+yUOFZ1dOZay3DT4rxEGtjCK/iQZo15PSwshT+Tz+MGutkJf23+r82ThTxjDiiGTuX+t22AZAl6/HoY/bZq3aUVLamMDFas4WphZG2ZbHJB+l9nNJls/7wUvJwigrB0/izT+8v3DLcq8hKYwihSh+AxbvvvohfaKEAtpXR6o1RuP6xUsQ31ZHHTw+/71rf9nHXbaQ3b5wkyZFE8976pHC5xkbdz2+SfieT6cFLc6zyNBMJag2ZzKfdUJcbovDpWvHMCIwhlS0qiyMdLEFsHxla7MqsKQrRAsyb9WRLd61xTDSnDA9tGI7SpBhx7WKR9MT1ay1s2xil7Ssj/G5zFG+nc+9wjMaYw3IFUaFMjUbF5kOXVmmsO+UNxlUMiSzpFJLP0Edl8s0UNIj0sxYsR1PLwEA5NWqqsI/zVkPAAAHRspXgw8KLIyAiPuD0S1pAo7Kt6ShycHSzXtg8kVTCvFHuAJznHD4RDxhR1ThjiWC74192QIQnzekZX9JyShIc8Ocplu7r0O+5ku+XBlxqvhL3z/a1ihlOvlaWVK0ZmmEEpOYS4ZI3cb8PoJBsxRCW6jKvChmseEbGGQybXtcSGIYAfVyxKtyN/RZNTYWRjx+dM9S+J0mFmM3ISmMIobtPDRzhXjgJ8iR3wSgsUQQBUhrbrKLz15y+jH57/O+fieKhy171IGQWRx/WFOIfPHTjha+/5dfzir8ba144f62FaZwwQuLG8DCCZvjSkGAiONYMCfZbNPPXrVd4KLSzi/7HmzsKV11sKfjMvcLV2DmlyyNqPr3DI7mv3nFSaiD6lXb9sMn//Co8VXGWOsx227WPikUbSyb/2b9z84lLaNhwRxHA4D7ztbvBqVShbhKMWXiNmlihdFQnFLm48igPvimMdng8/1HyBUNdDLaxRBZugGo4wut3r4fAAAOnjBQejfYslCdOK6/rVSEslKTUrNb0kRNWgp6bdCf7np8MwAA/HXe+sJzloRrL/r6zY/D9Y+s1Sf0WGZImAwrNpYggJliXdb1qh7XLrFVePDfHyo2Yl+fRGFUOIQqQuaqpuSrQNuEQz8ojFMnl7QyRgy9E3T0eMgUXO+8Qn1DWNam0r5D/YaRCN2u2S1pLoduP753GVykue21m1BecROigUlQxgQ3DORXR6qlyAGkhRH7J3/jkAiUUnj+19qKJa3iQbGRF8HWXF4Vq0OXloVK+GFz8cm8LUBETKvBWhg1siB4AO+4vLl4fuz800t5KFDFZpMIfpmDrZN9Q6PSdDZlqPI0TYmLf/P8ZPjyX5kb4Yw27ibzWjHtJ/7wKAyPNuCdzzsJXnCqWFkqQkGAVRSPUogKkuRm1KLkrYdZn7FpM5lFjU+hqhn0uuz+QjTliMYVEQSX0PFaOk0EKo9hkdcpvjZ5UiZ5TZbipC9yh6oK81v/BBVdtDBqv3e1MFLxoSpDhqzvhewrsgs1MqisIUPAdA5pvtDT/c4dS0rPFrfcQzFl86g0/qTi+1RBzwX6fiXsm9UsY3bgKqpD2S13rjJe3bdSOpWuOGiyxf7hUViz/UDu0srDPFxG8992XE09KLXvc5T71xfkNz/jaYzv78sVTb2IZGEUMZLgWR0GsmCvmsl0PGNhtLPlaiYUvAynO19NjS1Xlm7Vtn1cujYI6BRG8vIwN76UTp6I/J0pLQDxBjGzHGCDXuuuM6ZUvtn0cLENABTrGbMR+d5dT+SbJReUBRec1YTJKaHRSSKXtq3YLRO5btYaWMJtFDJghSTTTWTeDRQK3HbQa/vOIQ16bU2v/LvRoIX5DQufJ+EsRLdPsu8AFLHEECyZKKdNBPq0bOMhqytb2YeNYZQRF93kR4E6Kwb4PmHimtl2w5HQrqkXhSxVaaWIsUCWPBcFz3WZJ2VzTtXyuK0sIarLkmyFpFV2CVcjcxPlD14ptA87pPUrKEN3YKBKUxVcyvc9ziml8LFr5sDrLpsGB4bF8qDpvJfLLYhsuRxoVIIYIqVT3W0tctnvJfT210cO29PuBHNkrhgjo+KgyxlkFkalZjBsl7onwgwv/9a9hb95vlRrjeoTdFYtzX+LFgWk9T8fICAJfNpq7j5CtNfZ8vGVdGmU/CAtyExo/vT+FbiEIN8AUxALYzoZQ3QLUVbOtr1Dwnc2yK/tFTD0qT/Og9d+d5ow30u/eQ9Tvp3Ss51f/kwY9JrduAK+PXk0GhQWbthtlxmKbX4aEyg8e84GvTaBjcJIWM0l4VDeUu2gyJJja0UeFr+ZsQoeWrENAJquTtJxgRBc2T6fgIMsXoWqDlW1K4xhBJLDAkeF0ViDH+8W44BjgbUgDN2NVHOVT6zdsR+GRxt2tGm5L6DGF9cUJtb6ssOFEM2h6jFKq2yFwkRsOcaVKyFtIu+pwBvqi8b54o17YGh0jEljV5gqm0ub4ecg+1IwngKm7vdZSBKZJYxpzKW2hREt/M2Dcu+s55LMglQ0PzmOwndd9SB84OczOZp4yFz2ewVJYRQxQgbfSygiu/1MNzmLYhgB0LJQ48iP7QmQlJ7tJpV3SVMsNrYuaXn+/P+akC0+37vzCTj/0nu19DA8sItgJihqLYyaOYTvdAoubHvZDP0hjYURS/NDv56NKlfl/iHMz/X83zy0Gp731Tullj96ekX0txbsUDdBmtZ71t5ZPYmGB3/rjY0SlFKAhyVBKV2RffNYg8IEYdBrRb0Q4vX6Z54vWZb27YblPFJ6Avqfu2kB/GluM47M9KXb4DczVknKw/OePMkNIKkr2yocZCyMckWtZMQZBb0WJHUJep3fisp8KavAqk/0cyt479AozFi+rfDsJd+4By66fp4yH2ZOpPlGUg83a844oDxkM7ZgL6bHhijg82Hn8FJoB1bxRyls2TMEr7tsGnz2xgXMWBCVL+dMxqMNrphqf1V66LGaxTvDgAJoNw+2ivLMGh83Vq2KaOb1QENIlwLMWL4d7lm8xZqGeP/XO+jtr48Y6MHS2wpPb8gsh7QKI4ndefmUR9OApVgknmZHX2Q0GzXTotXCtHjxJyBWdH33ziWwbMu+8guWIrIexpjNfHtB1IDKv8fVO2dkrAEfueYRWLSxbUmC3pAblHPHQvUteqa0Sy4ArbqctqS5OK/Yuq/0DlUulxSr2LWFsZKeM3ARbyxbSR36BgVJMEwP4z0j0ZBYGKmq5PM3LXBnQIIGLSvifVnwyTB71Q4JL3gadcfU6FQUbz6yq0P2QIMNjL6Sc7UG6m5hVHJJs7G0Y0hcMXVZwVUtdD/CWKKYYO6anfC6706Dd101A7ZyVqX3LlFv0lRVp1IoYGHyXXIrw2rHta1SR4TZK4vz2sL1u2HT7kE9bctP5ocWLch4TcUiQPMQxCmmHxB1bCwkvUtuKV+VjqXr1C89psJm08Vp5ZG7EiLmS9/e6WWFpV/6TZp4osklLSFaoLpxkk29IIuNoothJHJJo1QQ9Nofa0K0T9twJZWu40YyuHbHAVjJbPbtb0nDnUrIXLGy77W9CpMQsUDPWn/IrhsVQR7DyG3FXLh+N0yZtwG+OuXx/JkvtzwMpi7ZUhAkMxkB65ImM4+3FbD4xTw74HG5ylbVhTH9W2VtoDKjzi2MLJsTe9ObDLrcow0qHiOgnmf86brLwqHuhLnPYDPpdOrJzD+TL5oCV99XDihMKcBvH1oF/8rdUJkgh6xfKQ8mFMrZdrgNmtPYPzwG89buMioDw6fLLWl56DOGwNLNYW7DNIHLUH7bj6bDup0HAEC8TtuOPxtFTdlFuvME5T6B/NP+24zWDXOKt8ZNmb8BXvKNu0vpKPA3gJXf24CV7Shz4FZYbz00UR3n56q2eGx9ed4p5qU5DRkdM2UnM7dIKtQ8hlErH+eSpnOFdOkrzX+rGbMmpdjEeOwm9PbXR4y/PLpenwiJFFNBj6yK7FzS/CuIbG81k9Ozz/vJP7bNya2DXmP98bnnbK6pS7bA0z93i4JTNi9nmQBEGJQ0a25C8NcsU6Dq+lRtdjJ+EHGSVM9E73y4J14xdRm8/cfT87+xLmnyoNcCBYpI4dKg8IvpK7SBuzMLI9ObPrDQ1eHHfzcHbprbFr7bG7/sRzvt6FgDPvLbR2DBuqa1WB7DyIKvF19yN8wWuKT52AixgrwwYCqV31YGIJ4zRd9oymlDUa7UJU2pYrJX6mflZSfjP7xnqTDdZ29cIFROJIhRmPuZ3z7c8XUxSHy7pJmMa/7mIWyZPiEi76vMksLGS3sW/7XJi4EuKLNPqOS8T2nc+OQ0celGxmge74ZFQQbLHfBl6zsObLYGbR9MNBpsAHicrFDiESFvhYRqzbng+/dr8vqHbu9ge0uaiVG3F7kE/CmhXPNmSBZGCVECu1h847bFhb+nCkx/k75Ij6yKRjQWLCKFkXBiq6jOsROqiTDbDDZrcfKrmJIx8R0o54LCU5umMWvXQWSpk522ECbota4OeUVWIQ3WZQaXzIimCmMNCrsPjKDSbt07bExfHvQ6e0+Yd+UavnnBBvjSXxbCpbcX5zM+JdZ1VAXV0NQJOjfNXQ9/nL02/5sXdtnNxspt+2DK/A3wjVsXtdKSwr+m+P7dYiUFFiskbpy6b9ZNZTv3l/uLLg/GHUa1qRf1Kxa2VnkyvrN5KeOnX1BuOpjxB9e6VFunNeEe9JoLeW0wrrOUxdsw648w4MsSR2ypKKctrTvLCuGzuSoHVc9doOoy2S28Orjw9Q9XPoii7dov2AsMKLRvzW1QWjp0wXxP8ZBRdYhpzzc2p49+oTqENCIvUcCzMA563fo3c0mTdVkKtLDuWgcxb33Ehl2D8L07izcghlhjTUgmhVFCtMB05EfX7Cz8/c8/m1lKk8RYPbAWRthJ3bTO+fQ6Ocm1TZWbZslLQnRBr+U0L71jCfyfX6ldNSjHF2955LJWECI7wWptAPv8WK3oXNJ03yDa6Mo2v9OWbIUrp7ZdY1SC09emPA4f+MXD6sJFMKwSmRWHrj/vH2paFvFCMl9fWUDy0QaF3YM4gdoEhu79pXw/uW8FLN4oDvAdYjNoMia+/NeFWhpCyyDN5nunQBHpIw6I6pY03Y0tYnr2vGTm+Nn85+p6mtCEXEGHyatZizQ0TBRGopQ8j0YuafkV4+xDlnY9UpsvtzHZPGJOmP2JJyA7wDAsMhqYzF1XTSu7y5ogyDrF/qZFlzSVohUzDurW05uWXzgUZZRkvhSVunnIJPRCIV++5uLCS9giy3vHwk3w+1lr7AkFQAp6nRAtTE5Fnti0B/a1zOV5pJNPPTJhRBfDCLuYxlbnRhsrxTsXVwFZoGXppgHUwoQKJQWcJIYRe/ND2/0KR1MEtghfe0oZnSnzN8ABjQtXhj9burjq6iRD2QUh+7e1we4rvxNBV8dZrLHRsQZ8+S9iBYgOqrFp2r9zU32G86/f/LgwrczK7iYuvkSdEPe1cvBpFqKTcPFtceqyS0p3qlA8tf6V9TvfyL6Hj+OQ4AZZ++aB4pV5NbQ1CiVXt7fyLWkGFkZ5HBAqfF4FRHVvWyX7hovrkGjdVpE2soBGrMS2MRubaWVzTjwynVCB2frX9EKLAg1OSV8eI5ZWI4xChC2BXSds26hgpcd1pNEGhbncobpNGcp0hnXyjssfMOPDgD4fXFwEYwsjg6DXc1bvKJV91yL8LW8AANc/slb6zmUEytsTT1VkWdxLSAqjiIE9AaOUwmu+Ow3+5ZcWFgQJTbSqWmdhhDlplKVj4TrttBdfPS+mwMQOUfFkDe6URfbbFgePHwAAgMMPGpc/Y2Oh6MZbO5igPg2AHc/CGEbmZASwFPTyf3E9WuYiqXURklruFQn257ekUdgTwsLI8jQPk4/fVGX4+O/nmhVaMXT9eDjYjXWqU9eWIpK/bbL1r2+5LhOWszmiX6D9i2c72TmQ1Vm2CRwZa8D0pVuFuVRtTEHfb40sjATEGpxC08jNOKcRV6+xVYrwczHfNjs07lWo8epUVfjMow0KSzfvhZ37h+EHdz2hz4ApPWAzr91xALbvM3cjx+AtP5wO+4fFB9EmoNAOczA2RnN+KaX5QYpJFeVpiTrft25dDG/70XRFCneYtu0jq3eWaXik33bxE2d0DXotw4HhMVi/q31him2X37R7SPouxDiKbAqOGklhFDHwCqPmvzOWlwPYASRBFgNWQAVoWjA4wbTSAzcSf+KntPJQvFP1SVthE+uP7gICJKd95CRGYcTEMMoWRNQJJuKWtP9VWcAY7C4WaG7ayGDbprY0bfMb8cn9nVsY2fqOAcAiicuYsEANSkGvFZi5Yjus3bHfqzLDx2gpbnrLzM1dszMP9izOb1IWPq1KcZ09N4vNxv2NSMPyAtB2Pez1k8YQEB0Q7Ng/Au+5+iGhlYCordjNktqSkXq3MDLqEiKXNAZNhZc5f1PmbZC6xIrKKD2zrJKR0WJGkbXVkk1yvkxijmF45Is32SOv2rYfXv2dqfBPP50Jl96xxKhcU6At1vm/uQf/ee0cH+wAQJmntTsOOAe9Zj/g6vtX5MGgm+2S0aZ8Uu36NjzagD2D8rVJd0uZClXum3QB+m3wzVsXF+iONSh84OczYcbybUZ02kGv1Yr6z9y4IP8dm4cFBp3Ic9VICqOIgRVodJrfNA70yKpoZKwB2/YOwdM+ewvMX4fdqNPSIutb8fH4ht0w+aIp8DB/U1KAtlXfhCZ/9z3H0zia/1+5LAqGprlcUkLEVlnZIjh3zU6YuhgXVFu5sDAdYeve8kmJTb/4798/apynXG4bJvsa7Bykje3Vev/nR9fDxbeUXbba1lvF8vjSM8uOkTH1hlCF91z9kPDaZwBzC6MMWGGDFb5jQaFvCFj76pTH4d9+PRtJwT6VSKEjGy/Z82xjiql+zNiTpcjmieSS5hc6C7IM2/cJ5lJNc+pa20TnLLryvsEFvTZySctolD7CbWP+kWsegdddNs0us0O5mLG1kbE+sCvDIa9ErlBh5VbxJQExgK/vzXvc6rZNNwyaCtDy8wYn46HpMYlFcVttaNoi9P7KLO5f+/fvZ60puItv3zcM9yzeAtfONI0LVJyTZPJLSd4NUS8ONGVZ0/YYj6QwihhYCyPdpi4m3+tYkVXh8ChVmkSa0kOn1/x93xNNZcZtCza23qs3UjxM9zcy9lVdkg3AbFaWWGho0OLGzNfCzNJhx866nQeU5WDiKWHrOTalgQxZVejq/kDL3aq06c822K2///PaOfCrB1eV8mNjVbVjGPm1DtA9lyHj2yQX5lPHGhSunLoMla4KqK6Kx268xxoN2GCwaaSUSuebrEyX67ttLKMyy1OhS1paZo2BvY2zePtO65nWJU3dILKDNlG+T/6xfGttiUerGEbyNOE3ooJnFrLih389G9ZsP2BVXgZM1ZnUh+oAD22571A+FtYxGjleQgbhL7jZW9KQ1d1YQ347mJJeRHsaX1fIY/DpG+ZrY1SxfWocc6vX8i1lpTcGvIVRXXC9JVkHX4dO3YykMIoY2M2L9qStt/s4Cu2NMYVx/fIVLFPciPIWnpkqjLgMMmHXZnG95qHVRhojWb8jQLTWbC7g3QgKiiTDcoU3ogne2bglqHLYCoDt/E7ZpbA2t0Vmu3HOuoLbEl//6HopKZyKf/d5cElTFm9YTTaxSDA18ZdH18PFtywyY8YSLOs2/RcrRH395kXKa5xL1mW03G+xilZTV0gdsnlvVBHDKMECkvm+NJ4E1a1sT6qPt4cJ4tpMi1MuG92SBplLGi09qxM2Y+TWxzbCV6cU3a9N1xuzoNcYgnIXfOy+l29f9u8te9wPFU1Qkg8rLd0d0gNOKv4te7Zx1yCc+YVb8W6XLhYp6H5iQ5vCj+9daszHtTNXK28b5llhR8E/XjUDz6CAhonsH2Kb8J+/m+OksNG5tyfokRRGEQMbRqduzW83gPWfVm0GBkdwjWI6sZlu1NruVfpyPnPjfG8xAkL4+cqVRP6EaFn9isaY7gtVVaDbR4ZcnDT7J0uarXGBILB3cFS46QfQbwhk73l6A4xLWgjYxjXBZnvXVTPgRsStaNjb73yArWOb0WYlMCN6ZIPKU2XPTU7W5SpkPbJ+McbEPEsIB8w4FPWOtsUfBV37yi2M9Pw10xUPODA94rH1u2Db3iFhsHxCOItaHBsOcBkRXL4KTucpUJi+dCtKWVOyMCoojOwOYtl8f5q7TprOBL5mkarmI+tzJ0m+BmXDOeiJ37FwI+wbHoNfzyhbKdcFG5l41qod8M1bFzM0FPRN9xLM71taHgk+kFuLY6wBgTqP93L54eTnv85bD6d+5uYwxLsISWEUMby5pCV9khZsFY3rNxsWNqfZOleKkIJbk748oao/+bjVZf3OA3CD4OpMCrzyyDMyJZuF8AiAE+6wCi7ZohvDKbPIDRBTSyr3QUsDoxKdTJk71mgU0vpSZBqTyTd++IzbAt1oUxdCuIpmf+usO0rzqCDt8GgD/vzoeqc+ki3FmYWRSDGclllzFMewPJ3ILUY3V+qa2/RSER58dozy8oLv3w9v+N59bctEjshvWhvhuvqSt3lUSFueHrs+vOfqh6z4Yedn7FxdtjBq/x5rUPjVgyutePGBsktaGLq+0JTtysQblCrdM2UxDfHBwh0sUpB5bUoot5ecikmb8HX8f//gHv/S5CbYTgQFCn+eux6XtkvrAIukMIoY+IVN/b7X/S5RyJUJ1MrdALNxAQDYsW8YpszboGcHfcqJS2dyACVb3AHMAoXKcOFPZsD/XPcoDI6U497wG4iiEsJk5Sz+SUBsLSMcY9rxJEedhgdqyzA8HXbjY6ogLG36W7Wl29xZxTEIMK0ZxzASPXPoA0s340ztfaLokmaRP9D6orolLStStklnebrsziXwn9fOgbsXbdaWKZ1jMpe0LIZRsjDyApXlAQuRBYWq31Gqt7gUjfXJF02BxzfuVuRsg7dQwnaJzXuG8puKeB5ueKRluVLTzsT6oAqRU51CX3kmVaJqC9sYRvcubs8fv3pwVR7rsoqpoMyxXd+zQdHqza6HUIm1aIOWZQPljWERbmWKbnU4BieO67eij4FLXxDxz7vP5oeImnYK0VYuJDFukQlqJIVRTdg/LL8KMgPawqhbVb8VIlcmOOQtPJMQ+vBvZsNHrnkENtV4YwiAepGjMqUQMfNjlmFzS9DiheUyaX/9WraIisaOViiidoEaMYghhhGrLzWZWkRWALlLGtbCCGlpJ7JG8QFbOj4s7wAAXv2d5g1HVaojWM5tLNxsPh1vCSlG28KIdUESIwtmv/vASOG5jf45tzBKMYy8QHrhAbcGiWpb7cZhb2HEnzar+2D7rUmPuKlVhvpGUgOCFrCxjHajbalscOSlWXb7N/rQiyv4v343N//NzyW28LXeEyBBwgX4glQx3BCPfzkdndrR37yMr07mG5B5eIURpQALN+AU1XpO7OtANCXmFkbcyzp6m68+vm+ouP+Od+TEhaQwqglnfOE2bRrs5jy5pLmjrTX3NXmIqWSbl+Ex3eSrU6aI88l4NwsqqRJi3WuHN3GVBbcuKrWcixXS8B0Kp87YJsp2M6AjPM3HNAAR9EdkwblZeuvvsQaFr9/8OGzajVOs+mpGUzpZXQWKwV0JXMeWL2UZT6VBqZR29hRj2W8Sd0inoBzLXdIsx0gCCqqA0thYGrp1TKYMX7NjfymtmAb3wGLuj++sz1KpwyvwTeOuoOKiGNDjrVaY3OgYRqoSa9YXB3NJMyzXiLYgr84ljWcon/eRY62KKVlmIa8Cv35sVMg5vtZXDERl8e1Tl8fKrgMjsAgZ7FyE8752V/77zC+2999p2cZjoG4GEuTAWg7pXdISdGhPhnEL/vmJuiGL/Po6xATV5Wk1FEqzUQ8SbsZK2ZqElpREIqsVDFRp2XKFFkYO40knxrDXzE++aAqcd8pRcN2/vbCdP5QgalB5tsKn6JQzd0nT0OQF/AeXbYOrpi0v8VKMXSNWNLrA+HafXNEV75yhB2MlYdH2oTa9DapQlLeey/gVuZ3yrsZG80nmkqaIYZRgDuxBiEne7J12HpckyCxgdWg0zINeq3jg17rQc4pwf17TNOZ7OJVjRLZ/Yw9iq6kLO8WHD2UlHiZhqcWQu56araExiuYsS83xjHGvLH7InkG5x4nZOuXqklZ+JrrRUZaWfReiqWxjmPlChN2vUiQLo4jhL+h1r3dzPdrxbSzqSpDFlIxOIHBtQX5D/v275Vd6qupgh4eAvTKrDNUppavw3IxhVIZR0GvmpEVm+txnOKPOXLHdLIMH6E7nTG6ekiJTwGYbe0PBeLTVOWRToO/x4UonPksBPFyXB2/ri0AglW80MsWNuF+xa+fUxVsAoBx3yMolrRXDKLmk+UF5s1X+DSCeP0TNlx9GIFYMXd9SldNMpykAAf6WNF9Yy1lJ8Rgda8BGgVu8tUKA+5s9zc/TVDjP8FVpE/RalcrLGukRcXFThurWrLI1mPi36O8YEMr6vQ4Ix4Yk6HVnH5K1wR9UK9PG0lA1ISmMIobtbQ48eruL4+Dq/sQv2DyJpZv3wJrtbSGuHCQbJ6TyZz0liw4L5k0WZcyVtjpk356d9Mnqnj194t/ZIKsblozotNGlGFcfev3NP1R+Qqo68THgQexuo89HRC5pzDtdXja9zrLEhj8UDOnkn9Ulk6ydlYR3NgCgFfRaUrHXzVoDAPLLBlie9g2PSdKKNP1iXtqKTLWiKsEP+M2J6Lp5VQs0lY3yjknBfciq3OZsabAwP3RqZ/jtQ6uVab928+Pwvp/NdC7TBKpvRbmLOvDGZsW6D6v5tefFB/i5K6T+2sv5EaLtcGmaiWQsYXi974ktzeD2HmIGsTwB4OcUo65sdLBBnSRQhb7I6HCVSmjFiE7hMwYkl7SIMYZe2NTv04DQw6WKRHl5YTULZnvSkQdZlbFs816rfBlMFn3V7URb9npQGLX+5S3omkI8e8oMwt/tZ1QqaPLp2XSuykHVyQq2nm2FsItvWdS+SccARqezXgyMaPajSdMwvzR2jWPb6WAee0Nsrt1JKLjVWLS9r5NG8TwqTjtv7S4AkLvoitqDd0nDWvCyvGV5MLek1b2p7ATINluY8aRLoSShUCjxTx9ds1OYrqnQbMPmsMCnZaIJrTsWbhI+tw5MjWkvRZJOc0mre2iL5JsqrB9sy/jmbYvkL7nDIp8Q0bz9sWbff3il2robbXVikccEIeKBmZTFr7H8v0I6HSwPJciRFEYRAx30OgUxcgZmEjSBqyDI8/GH2WvF6dyKaZXFUVEQ3eXhdhDVJrugEICiQqhkhUUNFDQg/izRplHmGqEMzsiUw+Kx9bvgzCcdztDT8Kn5nqumLZe+k5G+ac663MoCA1vrCQLl78MIO5MvmtJO3yKQNQsh5T6RvV+5bZ9ROQW+NJYkpujkKZatO5ug7cEsjBplxTXPnoxbEUt8vxbxPWX+BjG9VuLMwghTTXVvKjsBcrew4t/CulRtWEA9J2Bc1jK884oHhc99KIlVAbVNqZvwI1OWdvI8pkb7y3zfKoyrdnEi9O2hmpYhABDzvQs3z98ofSeLadl8pv5bl74KiOQTYxqquarCb1INjU4+FPOFXq+B4C5phJCVhJD5hJC5hJBZrWdHEULuIIQ80fr3yNB8dCLwQa/V6brF1zQk2u5KeH/Wdl7BM+Py+fwSChqlhey5yeZF1e18rBnZQX9JaOWFZFr8idFrPeNztwBVuLI087XfmVgZYEAIKdC/4Pv3i9NZbid5KwkMPv77uYW/Z6/aoUwvKgIzh7zrqhnt9JwCFn2rCTTjb2xtWbKVXD1b9H42fQUs27Kv9NwVIjKq0zIbc20dDhgo92KAzbdjcug2/QAiSwJ5ej7ukA3feQwjhNtmnTcmdiIK9efuf6w5AXdXGqvc5rBg+yC7JlB+8UPAZC2TXV4RUmFepRTKjz32c6vY+Ia2sOCp+3KRFfEdehYzmSeLl17wdHxx1AR23ySzilfmMVCEGfUk6hYWQXhLmuSdii/M2p3QeagqhtErKaVnU0rPbf19EQDcRSk9HQDuav2dwAEf9DowIz2ArAq9bTxj08YrVlOeU6qI8ODjs3gLo1y5ALTkoqCOU1FmZmi0IRwPrKVK0a1JcKpVKEP8WwZXocXN/7zJ4PWz1zoF07aNYfTE5r3A95vsL5N6eck37oFP3zBfyIuvUSUTZsSuj3I6GKszU1w5bVml7kwe9uZB+GhQ+dXnGWQbJdG45t3ITNbNjFyWBxPcPqmL7FFqG0EsO9WGZKxBlfKTjQVPmYb7LWnYeDoqHtq/TcqVzH8BN3muMpFLdjavD3mZVXKIpiCsQsB2jijR8zjZqBQ4f5q73l9BCMhie4qUIgQEbSE8zPXcxwOL+lVuJURlZXWajZv8cF2nMeoQxLZVixl1Bb1+KwD8svX7lwDwtpr4iBpYlzSdYikNCD3YSdDYvQXksXTs+cG9x7atDwujpluXe2fKTyx0t6RpTjTMOCFilzStdR5DgVEOyJqbgPqEx7X2MO34iT88Cv9wpdiNAlWGQ1+WtaEtRYwAKCrXFqL+rT6Rzvz7/U2yw6PVOhe4ch7qwKJpBaImLutXIp54yzmTNuNv0cRs9JOBkR5yl7Tii6WGMfy+9JeF8Mk/zpOXC/L2x/YKV2UPgGZuya2eccDKi8q0tmMZkc9mf2krb6gsD31YFeuGtu8pUWeB7jPotdDKqEX/7kWb/RWU0c7LzX7I0/rcy3zhT49Z5xUF4TdDMdfHrp2jSGmyTjnGMEJYmGG5qWrfeftjGys7oO/1vXQVCiMKALcTQmYTQj7UenY8pXQDAEDr3+Mq4KPjgF3YdIOlx/s4ClXXUUx7CZ2ihsdTjrIL3J2hdEsaa9LL8lHgqUwHIWuL3zG/RYHlXRaFPs4lTYbH1u8SPtct9kqh21Mn9hP0uvgvmib3DeUrd/2cjJu4o2Ao82l8x8kICfd+4+dbRTc+6ihnFkZtqxM5eEWoyXffsmAjTL5oCuwZHNWWk5cX1SwfJ6hkxufb5gt/egzmrd2ppYeOCeNhshzjXJ+tAsYzbLjOu6zySfd5Y2NuyjIrOBJ3OawqyhIeFEa6dRrpvuNLqUwCzjbNgNqBiAN7Q6q+EPWFIwLLaEF6bE1h5UtTK3RTVKmkEFvnm0QKzN5Ux/SHfj0bbpprfhFMhuQ6h0cVQa9fTCldTwg5DgDuIIQowuUX0VIwfQgA4OSTTw7FX7TA+lrrb0lLA0KHoluUXV7dMyUNzd/YfDKYCCa6hRJzQ5Cal2Z+4S1p/OKrKEruViQ5IROY0mqVrRqXNR5ai6XW63sWb1Gm43H5vctg0+5Bozy22LKnfBOebX9sVwc2hlFJY1QpRN+JuV6ZTbN17xCc+pmb4f0vmuyXuUAoxmAwXytCLS8NirAwkvaPcj7+FN4klsmc1TsBoB1oXTwv1Nt3OxFYCyMAgHU7DsBzTjoC5xKhK1eRX3YrGg+ex+37zC+EUN0GmSvdFR9acLWqMYaRC17w9TvhP17xNOG7QlwnA95KBw1sPXn5RvXgDl6N/FRD/JUpUhCYWK8Zl6d4J3PtE8YwQpZ30xx75YIIxQNPXD2ZVKdJzbs2k8lth7p9QpVTyabd9rc3N7+jyO1xh05wY6hLEdzCiFK6vvXvZgC4EQDOA4BNhJATAQBa/wrtHCmlV1FKz6WUnnvssceGZjU6YAUArUuaD2a6HG3hzLy+3vezmbCNu27eVWuttxrz16qi28dUxbsGWOSD6BXLooJfYkWemQApbldb83RZDYQKWPyNWxfBLx5YqUwT0zhvB5F3gyzodbk8x4IUhFS0S+b0ALB6234AALjhEfHNhloWrHI5wLFAX0Fky0pzCnPXiC3xMsimIoylmM0mSBcwnkXSF5lBd1Lv08Wvuc67rtHFv382fUUpzcW3PJ4HShfBZwBmdi3T1ZX8ljQ7fjC5ZLQ37R6yniux8H1oqrcwUv9tij/MWlOkx733FfRahD2DI04xEbFwrSNsFewZGkWlU7HDlrV933A7D/IbVrVkBBwjZhXj0hNE00LZWi4mSbOJZBNRDYIqjAghBxNCDs1+A8BrAWABAPwZAP65leyfAeBPIfnoVOCDXuOsGhLkcN3gPrq2uLEJVeclc9qSGwcynwKq/kQB4LCDxqFpidAnszCiRaVQg1IrQ2sKunZsv9Va54meKernwEjYG67q2oRiBe5SMkxgAkV+bNBr0+FmQgezqWP7kevQ77T52kbnivnGBgVYvW2fMk2pf2Snn8Iyi09t+H5s/e5WXn3moYpjUXUiZLUY/iYrc0tiHg2qp3Hl1OVw+8JNChrt3+W4O2b8qBSgvHWdLG3Iav/NjNXSdziFEx6luiz8dv9IlryozrD9FyvffF4TbydkvLSHV+KV5DbILJpYK38Z1DeW2l3W4Yr/+t1c4zz/+qtZ6LQmnxD6oLqZpvhvp0MoK1TORWcgtIXR8QBwPyHkUQCYCQBTKKW3AsAlAPAaQsgTAPCa1t8JHCRu5iXoBm6MGuFoQf2cRhmTMEzP0j/u0Akwvt9+KJdOwzTpJ47rg3889ylw/GF2Zpu8G09RmBP/ITIbNdlUyG5J870x+ZuTj1S+D3sLTTDSaK6/eWvR49h4GHAZQsYkef1l07TlA6gVC+1A6MzpvjEnAroVqgYL48+iD4Xa3IusPflaMbIwkiozzYGin6CFbNyKx1xrY5nllabAlOveXliFo/q2Nr3iRlUMduwePKEYfUJuYWQHzPw7f53aWlBOvPmP0XrPkyjJEtXC97ofKsyEiOya7QbWMBbIrXQF7zxO2cawcs8OwodZepdLS4QWRhZ0muJ6dY3l21pUXk5vI2gMI0rpcgB4ruD5NgA4P2TZ3YAx5DUcWtP6Xu/lCGBON4zoGdIRuYWJIF0LNGuEyRrSoGLuCQGgjWZZLida0lvSgBeUqbIcSgFGxxowzJn8U4HST7YBN7lhELOouJqGd8qm82Ovehr84O6lpeezWi47+abO8TSqLPj72ehQSmHRxj2otMoYRlA8HQVgTkwNecp5q3jCjiXGXdmNg2o3ibLxJvomfqjbxJzJ6VvnTGAhOywQBqv16ZImKcMEJjGDVmzdB6ccc3CZhoSEDX/sWsZ3/0Mm4ET9uuYCWbGbdg/mLkSj2BNUEFkYyevGBix9Ub/EuqTZ9ukqWyl4nzCJr+mJjitmLBe76IWoK6PbPB2LxwUex6etCi7fLYxHGM+nRYUqbklLsARWHglvvt39kN3UZU1PQ8SX8Fs6gZFwb1KcincKVLhJNkEe9FrgTqcS7ESWUB///Vw44wu3lXgUIb8am3lmMnZY5YfUsgEoLGy5rZhgdKwBO/cP6xNGgqMPHm+U3nZM8adloS8fEwoPCL198Yai5u9OiWEj27Sj8wdqEwrm7S0a4/y7DN+9c4kdY4CbN178tKOt6fc6RNXrczz5sDDadWAEHli2TZvu9w+vgVd++154aHk5LSbsgHI9Zl6q+iRvYSSlh0rlL187v5jCLCZm2CjyAFWEosuw+4SlswCtejNtG4sRg6q+RLxxFx+kiqxoiOR5lQhiYRSApgziGEbiv9XzUuccqvg5guwNJIVRxMAuAvoAyQk6sJOgjw2QucUDn9+sTXXLpNktaXrubW/lGB1rwLqdBwCg3b9pYbMNhd+qWAGUUvjrvA2ocosuaTghG0DcDsq2oQArTQIatvD5Pz0GZ3/5Dqe4J0GFVI50Hx8Ug0+e1bWjpR3eJc2oGEX5ZWBuSfNa8xVP2O6uOX4Y5qk0GvZxZoQ3/fmsV5Fgzf190LgqLqHtbMgsOJXWO4J53LhcD7Pl/Uu3wlf+ulCbbm7r1rXlW8vxuIpjx22zq9KnTBhAivoRC4smSpHyLWl+P8xX0OsNu+xuPuXpjY7J50ojCxWRZZ8JYxboM7DI1crFvILJlinLvLcu2FirxS4Ft8No0byLeVI3fNe5lFyPG2ckhVHEwN+Spn7f430chfYG1xdBX4SKEPnmO5/uCSx35MJHtiDZrUr3MtfJmyhrTK63N6kTEyEUk9I2AP1fH10PAABDo2GDZtuCZxvremfqksanK/V3aUYcfV1yEZ9qlzR9mm6H3acjLCtALwjK3P8+du2cUlqfbdS7re0b4poUTcs+rQcolRbtHSbXhoveYVVbPq4+t1WjGd36JCoXUeyogxUNm9OLS5pBeSHA0+etr2JxM8Ygr0sEy7mFkYhOBCa9n/rjPLhDEeTeBqGtqk2xbMs+WLN9v7K5qnerrydvryEpjGrA+paFhQ5YAcDGSiKhiNyVwZMkKXWLyhc8nIWGCMu37IU/zi5eQ9sOvivOoxK2eV5l/SnjWVeWCizt3MKI5YU7cdbFMDKBSCmovSWtwA/Nn8nq0yDMQrEcu2xFGhUO836NhREAwD2LNue3SnkTYCV0/MUeKyPrI5fcskjwVpHRhYcKhV/XzZQPRUzzhsQinbGGPoaRKrhtuQxL5oS00prqG+wYDq2ApeBvznAB+53skoK+lZL5zR5+2G6edYePoYBSGDnEMPLd1DrlJd9/Q/e1yVx8rEfX7oKpS7ZIUseJtgzOPuPTyOH7ogjbKWiH59ACpmuNk4URwi1w5ort8NJv3qN3Sat/erVGxnpa54tINtM14EWX3I1Kh7V+sLVqSGgjq2pfVeVa56r8c1bvLD3zuVgqF4KsPKa46Uu3wnuufghFm7VMEZu/Uua3BgZ1XBTG279NApdiilWNxU/fMA+unbnGuDwThLs9pUi3HyGVfOAXD5uXw/3Nu75l7/tIUdlnevq8bodYaa+Ko3DF1GWld9nGoRDDiHvX7Qi5vOi6s5GrrUdOt+0rbwrKvKaFVwepJavgGX+bEuWeA+DHXFNBiUrqDNv1or1pQZYjce02oVGXpSSmVLcYRvK6CYHQZfylZZEMAHCoID7V2340HQAAVl5ygbss6pZdC6NlEmlx2k5efX+u8oZTHq7fG5s1ExZubJclg6wef/dwWHm905AsjCIGdvHWraMdOgdUi0xh5EkzLiPRjnnCn0DZluMu+PL5G4LTfhaEEd0PDI/BNTNXo8vqY2acBlPnIl743+U6Q2i2GJ7F1iP4ysOkVNWbSlmEXeh1wlXI4JcsdDGMeGC54quBd33L3o/rLy5d5371TiN+3vC9+9BpMVXayXOss1DtY76U0NDVvUkvdNhvlrBncNQfsR6GrHnN4q74Lds3bF3STOHFJS3i00UX1rwHvTb0SQtZrRPG9QWlH1r9obxEha/HLI+AKeFtdS6MWWau+5zIRWFlFPpBUUFUQisUXBTdoqzZI94bKN7ZsRokC6OIgTUP1lsY9Xo318P/LWliKmiXNMPydIuUWdBr1bvmSwJNq45nfeFWPGEongDpBFxKmRvZBHxlLmvY09S2SxmFkbEG3P/EVi2/IgWWajzZbkp9jVAfmwYMDPVF3oFxibOBqPowwojX+DgVz9e08Nu8bC8uabLnxifK5mUk1AfZAYGoT/nciDUPhurvEUoLI4yimq0zDwrR+lzS/M6x/Lwgsg51gcxiOX9W8Wxz45x10neunPzywVWOFNQwuThC1QVisefFxnfEwmSaymRiFsOjDRiPDHrv7bwxgrnVBRn7JdfSzv4sZyQLoy5AcklzR64MqJeNHCoBqrDBk5zAGJVVKludnpDmf2MWAXvYtaztDsYo6wongep4SRQABrCKA1bAA4DL7lwCH/jFwzAdcS2yqFxZqXUGP6aUerWiKNDm/jZV2OCrpZiwHIqCCp/7gkjQR92SJkhiKzdW3oXqNzCSugLqaLNKYB3Cx8VJwqUvmChLbIaZj1vSfIDdoMluBPXhTob91piD97tsZmev2pH/7gaXNBbbBe6xtqij+TO3n/aBnDxtvv4LLYziUBn1ed5Vu85UX5uiv8kxL0tlboN9XgNc+u3yrfvg7kWbvdPtRiSFUcTAThQxL/KdgrwGPcU2MCXh5pJEvW6gdaambWbMabOnL1ffvxwmXzQFBkfaWg7+ZrSCEM3RalAqPM2hgu0An2pl61YXnbBVpIPZlGqTqMtzzB/KwsjdawlHgC/HxILEB4TykupU0yEAfCxwFUh9rT8i5TdPm+8PRorLDm6jbkVxvm8/F9+SJqPBpMGWW2VfUDAlC3oNgBuXvgOFxyxL+rIIKx+Q2Rx8tRuLb7dfPrASzvnKHVwZxkXgedEoSmKwpLOFiRKegNklCKZlY1GnhRFAuQ7mrtmJL8ugHFVaakirTvzvnx8rPcsPoqpmJnIkhVHMwJ4s1WRG3E3wPUGEDAvyVcGJgU5oUMXc4AWKBlW5iLTKA2JVWexiOn1p07pn14GRQtl5WWy5gsIoFVsYaeu+cHqL/wjcqbddw/uwcKNQYQyjik7zSpsoD/WkgoiuahO1ZnvTx11sIeOLq7CwsWZgYdPlsJaRMtrZuDdRGMW8Ge5V6NyHVe+c5koax/j0yYNq7kffuhZBncjgize+Lmzoqpa/r938uDnBBJSCJuvidQaWrhrO3d5AVhPekmbBQdXziO/iMnpF2SgWu9T6kBRGEQPbNZNLmjvYCcLHpCCjgDkl1WHn/raC5bH1u2Hr3raVjEwwvPxevA8/Jm4IsdMXCWPfsMWt2b6/+JypsPImk0qDL4ssVWyUDbyLXP5D0o6uFj6uY9Xm1jcbGOuLkGzxyQLfjlwu39DCKIPPaq9zumZdN7DwcYItmnebm3oxbRvLrjr6ToIaxflVbS0j2yTauaTFcXrsU4nZyRZGuDk2jIWRDVR9jn931hdvg6lLxC4vrvjq257t17q8xkGBWXuVsrlnHZJtXdQfw6hYvsvFENfPXgszV4hlAt26X2lf8l1YtldIi3oBSWEUMbCdVaswikI0ihttZYKn63YlRHILHcNbNjL4FJplRak2vwWrHxtTbs2HT2CC8xXLEvRjmYWRgO6ewRFYvGkPKq0MVSgOXBeoYC5pJRe/UEGnuXJKFkYt64JAU5ppDCNVPhe5scrzU/bz7l+qDwSvyu8bPO1fPLASLr7lcWflbxVIq649hPOoh8OWPE+VJkaq9VRmYQUUtWlhX/kIWB3ztdomvBnd1G7MiVqO4RUGe4ZG4du3L7EoRY/3/u1TtetMxE1awNLNe2HO6h3q/YpCfva9Zv7vX8quShj4Nr523b8ZXXjDlfWJPzwKW/cOSdJWwxMGofp4skouIimMIga2r+oW0tTn9RCZIPqgZ5/fkEJrAn7VpVNh6pIt7qULis8m+cxX3Ea4FFoYsXEs2OdUHZuJAkA/MsLgvYvbdeJ6ZbMqt6vCx0VgpzReCyMZV3x97WTcEwHKwjer2A0BUfNhqrSQxllp6JbfuDxHhv1YZJZpUKBCge3Kqcul87XyBsOKK/buRZthiUBJndCGrO8I1588jyIRutwKN9LIGEYs7FxDO9jCCNEa3mIYGcwZMqiWv6pvEO0W96xfPLAS3v7jB5RpdC3lUxFx09z1VvlqtTCCssxswk8ot8/QcItVJX/Gu+v3+l46KYwqxM79wzBntdi8TwRs39RbGCVowdShj0nBlAY2PWbuv9jQh74sQOkTE0KsNoq2ARqFk7rMwoiqrcR4yyUscD72dp0no60rQyccjgZSGJVc/Bzzy57PWb1TTSerpwonNYzw41NA6jSLUJsYevwXyoQxeb/JRTp8mTVIe9fOXF15mbFCF+eL/W10hboVM3EI/1hrXhmGRtuDT3lLGvJb63LBwCnlffFGFX8hoeh0ld/WpbMwiqCf20Km3Ju3dlcpLRt2oE5UrTDUwcglzeQwVWeoYFCuK3zLTFk/i9nisg4khVGFeHDZNq0GPQSSH6Ye/i2MHE/t7QyMvEA3SbrcDKVbTBvcBkIle1Ggxte7Z3TxacuKRKUVg6VbgMX+t0wDaLCg1yWFkSehWMctfzoWegEXtS2mTBNlR2xw5TPUZ1KqsMBg0qDpubNkjE7pA1XAZG4SjUPZnGNTxaKbNOsA6+4hOwxQcXnB9+/Lf6vWHgoUrnt4Dewbkl9+ARD3BskXb2zXemx9WfHgisj0RUaIYUyooJpPq653GXwrDF0vZjFySfO2/1EjkqYSgo3PGvt4qBpJYRQx8KdCmvfurHQ92JgYXlwsJCRCLWpOi5TgFEfqKlBIZ16UiE/ZyXJpsyiwhBIpjEL3dxV911NQXW5d36zKpcDcJU3Mlym/dVx3itnodrKvuyvnwa67BvkmURbDSMVJBzdRV8DE+hHTjsI0yHmpSvcC7FQpi9emwtodB/Lfqjloyaa98Knr58GXBFdIF8vUFhkEOCtOPD3s+vTDu5e6K8y5/FXdIJpBH8Ooeya+TviSOl3SAKA04Zi4LBpZGOneK2j5V6r5o8VylmSGIgbqZqCX4GuTZYrU6fVou7r4CXqNdcGR81Md+H4mk+vZGEaifBiIYxiJyy7UlaDiXnTJ3dJylBsOEzcWJM0M9i5prX9dLIyo2Sm+C3wt9z+5b7m6HH4T5alcGYSWQpj4GgF4qQq+N0x+afhTkIZW6oldrjq5Z/iF8MpmSfWIb0kTw/qWtIibxuZgBnPhgSyAbYaYFd++eGPr4KDx/Xau9ap3MZtPdBhKBwIqCyOIo//6bv4d+0f0iVQwYMhEfMQG4+80FG5UZj0MFHkopdW7otaApDCqFGYdKkblQrfC9wTnapJp7JLmYmBUMuTRLwSE2Aa9xscwagbwI8zfOGgt7izbunBDl3SjY0c7LwMVw0iepjoLI7MO16AATwgCAH/z1sWacrgHlPvXM0RkMVUqCjZuqyyoXthytYpzZ1h0O2XTJU2Tz0jANefLFWltbkNkYSS3PMTTtaljSuNuG5u5w8eFB3XVScjDGB4f/s0j+e+DxvU7W0rza1TlFkYeVRQxbPRVPKjWmh37R9yVKx6AvIcFjZ9NX4FOS6G8tzCL2oDvAH+dt8Gaiu8R4rPbNiVsKqQrP+AA6O9+fVFySasSodYRvXARwSoQOTJZy5sPb8Ur7/6hMeu8wklRZiEFTU06AWL1jaIxwNJhhUKWPAWzOg11o0qTl3AKG6db0sDP1cpC2tx3mU5lv3pgJbzmu9OMyy3dkpb/G2Z8WSsT/bJhhWlLtsDki6YY53MdKjZ9Fjs+TS90UCWv4/Q5hg1YLNApNArzvTCGUetdbg1sz0tTQRl347Rd77BjxUeZ8daJkUsaMt2k8f1WvKg24VXvG7UuafE2qRZ8f+yEb6nb0oQv30ShWJmbrucq8rm2E8LMvUiys1Zu91Z+zEgKo4gRctObUERsgpJMSJSa5TMvTD+F//Z7Fm1Wpi9db2wA3eLFBu7k6aOvOdVZJeCoWCR2F9pdF77KXNIMF/z56+yCi5YMjKj7ZlEF4fXuiLJ882MjdP5mxiq/TCDhQ1gTk8C7B8cwfYt4iMFFIhaI5iYT123Z2kEQabDldjLCjcMKgJljA6jlJ43372RRtcKgBwwbOgp1todK0Y7KH5CPTgG7hhQPsOXf9KsH65G9qkZSGFUI46uoPZXbuUO3eohcI3wCO3lX6pLG/X31/XITWNYlLUQ9FYTewokznsYV05bBzgMK02RbKxLEqYP1Qkm5f21I0HAbVJ6qaX+z7Z+88B1SHyaLX4aKYSSKz+LAR5VwLc1LDCMo1zOmP7veIBMaae1tQ6gwKvwWW5fqYFPH1LCMKlAItgrMklCh0jRmBaftDaQqTBpv6ZKmkOarvla9ahe4OjBn9Q745QMrYdHG3XWzokXd7cGXbsKOD7fWDOp4U57ryOe0xdySxleHrJjTjjvEIwPxIsUwqhCmJw/Yhez2xzZ5odPLYJUBIW9JC9UWLhOwjXLK61WuEsWQ7dXHl9+7DMZ5ciiWWZzIuLIPek2l5RWg+axYYxjZ9s9yCKOsnvxD1q6oGEbCjK4cVQNXBZUPBZeMhmk8spDuojZIa28boqDM0nYXtGPukkaLaW54ZC08umYn/PKD5+GZoXZrS8zg4//ZoCID1RIwxYYYv9ZBr1UuaRXrC7DlveIZx8K9i7eEZcYDqOD323/8QB2sWKFOhZGoJ5vwU9nwj0hfxE8rfYRVTuMoHzVpnAMHnYNkYVQhQk0jU+bLg48BhDHl7Vb4s+py3ITJXkgmf99rlKj8ZtwiV7qiU+b2s0wo7OMsmEzrc2RMnt62bTD5XE9B3cKR0coEftPuZn3qWrpqOvvX/4dStgD+uTYvu1lzh0111SWnepszeeUPQnkvskqSIfTYkKk+EprQucvKDg50WLvjAExdYrYRjtLCiI/XZsgflf5hQKOmSsEog0KwNnGcXQwjFjxf3q0nNOjTLK4Zfy845WgtrciGREeiagszHrwcMDgyho5t6GuMVT2NTPWoCCVAcrlCFSKDhehCh25EUhhFDF+KntgEoxjRDqTpxyVNR8O3nzt7irB+1wGjvNh+1k5HrDenunrJ5t0+QoACwGV3PmFXkAMPsrQ4SxNLZRQt/muLYC5pvFBsamHkqb+HnMsoFY8ESims2LpPmdenvFD1dO1anpfYKTLaGgWsSWDgOg5O0trbhs4lTffct1VrpzQNlk/MOCSEKN1OYu6vJvMMdr0h4P+bY3VJ6xTPtYJrZsT9UYoa61lUX5t2D+Hze5wVq1xvFwtu4LVFIR4s8huGQ902ExmSwqhCmE7Ynart7WT4szByJSCmgOlCewZHDcsKkhRPkyGaWxj1EemNaXWBtW6RncS6bp5dPzPUCTG/cNYlE+VBr0PQBnE/owDwW11AaZ8Ko4r7urPVoEV+/vpjWewofQwjfJm1xDCKYN6KBa5Br7NJh6rSIKGaw6MAwrqulKVgkSvHN25bpCg23joJcYhPwW7qZhVSV0xdJn1XBbyWFkHzR8CCE+qPYcTdkmbCTqQW6lWCVSKXYhhJ1oxRhUdDNyEpjCqEscIoDBsJAmCFLTw9icKHqN/75AELsVVF+Vm2EBFiLxTpviurF94lzSdMyFLJbxlcbynTKpwU1U5pdRtU0+bv87TShA16Ld4w2VqWVT1/27pCuCspHQko6GrnC94lTUkvbIvIlF4JTYjnRir4Ja43vn+71LetosAFtvs2bLf97p1LmDzyTH9W3DZaWwwjyzlWTg+ZltrNC6q29LXWYaFai1908V1pDqoY9SqMaKk/1KEvCn15UEiQlncDAN7DYDRZGCX4hqlA783CKC0YeFgKEAIy4uetF1WfQqkg+lyZcJbVTaig17xLWp7Ga3nhrIBcu86//Xq2U/6qBH5TochXXIe266gXciXaYrr6wmK+XSg0vChipJYmycKoWyAKei2FRb1RSuGGR9Yh09qVYYNsrQ9d3PItarfZDKqZOGuiow4e786QAXAupSb0cDgwMgaPbzB3Z+GXP3aeqjqGkapF1+8aRKTiqMUjmkI6NjfD7sFRWLSx2J9N9hpVebXE1ceKaFoYteRMZP8b6ZEYRumWtB5AElr1oNy/3gjKXnvcCLlCHIhaDpe5Xvfd7aDXJAqXgaWb9+a/C7fQSFizvyXNHZRWGMPIML8vAcHEH98UMosWTJWK89n2hWr7fUgFKp5G2UWIgl4BalJ2HTJd/TNYPNC5pBVv+Sojn0MklXqb5rZYFl/+60J0WgwOnThg7gquQbs6zHuR7ZDO1o83nnUC/GbGajsigWAyT2GTfvHPj1lyU8TQaCMPoB3bLWkmfWHmyu1uzHjAHQvx4zihiA/+4uHSM5P+WNktuzE7pRWCaOGyjIwmCyNnEEKeQgi5hxDyOCHkMULIf7Wef4kQso4QMrf13xtD8hENjMeI++AdHm3A7sERfcIEAABp4FtjOh74MIHv6VdVPiF+C2RLyvYUhECwGEYmpP7hygdL+TYwp3Y86j5oqMzSxdQlLeYjJQayGEY2+XzyEDO8BL22tDDKGody/4qTVl+xndaWIWES9Bp1axb3d51yTsj1d+veYfj0DfPM8kueo61MKt7QoVzSDBbX0MNOdBNVhqrXOmyQbUIAbvyPF4VlxjM6cf6s86Bz5/7yHFiPS1rnHpYQaPNe2IMo3Ox65Za00BZGowDwCUrpI4SQQwFgNiHkjta771JKvx24/Khguoz4mHfe//OZ8MCybe6Euhy+g+nGYB2DhXCTLHhGmLhCoeKlsC5vrlfUy8twpyE7TbaNYeTHDTKc3zhP1rT9O0Fd5BLDyCdsZY9QNxeGzi+j07SY0+QxmLFDt6PYUrNz1oHQELWlLHagOIZevFC5fWSvfjJtuYaG/N21M9fYsCUpR15QppSpWr+Pi2EUng8seKXQ4EhbWKncwkgzMthqe9IRB4VlJiE6yMb7197+bPjsjQsKzzpp3+IL/Brd10ekQa9lGEkxjNxBKd1AKX2k9XsPADwOAE8OWWbMMI1b42PsJmWRGXwFDpae8BH1e2x+nxAH7FVYGHkW3UWuXqVb0mLYeDEsyOJx2Lsh+YFPC6MjJ43Lf5dc0gy7QCcYGFGgwoYwbVMfQleVAojr2AplkSlyUyulab1+gnEdladNPml1wmRuumXBBuk7WX+tc7ODmd+Wb8XFGALwYaFsma/1b4zTdZCg15bg64e1MKo8ghHWwihuR6CEQJC1+UlHTio9Y0fNe66eYV2mbh8Vszxo4ZGWbknzDULIZAA4BwAeaj36KCFkHiHkZ4SQI6vio5MQxSa5R0AVf1nRk7pYqPN99o3Pci7bB6T8g9sJpM7lpxjDSJKoJrDjsV9SAesV7mqh4UvZmUFlWm8ew8i2w9hlsyqqpS8qBTQ1pOMe5JbCRTfMt85tXFoEFkYyV2ATxfrGXYPKHCmGUb0QW7KKa2hEIIDzcwift04LFB9uSOVb4Kr/oGz9jelSjk7A4Gh9LmndDAoAH7t2Tt1sGCG2OV/WHYWPKcCdCzfB0s17YfpSe2MD3d415hGSy2+UlsJiyL5rJJQ7RGSoRGFECDkEAK4HgI9TSncDwOUAcBoAnA0AGwDgUkm+DxFCZhFCZm3ZsqUKVoMi5kGS0IQvJZ0tndwCqeKNMg+V8E1IuL7cviWteKIY2y1UVV+diwEFv/XUpwiOoHongm1/qbLds5J4gb/qrmdb3i0LNvplBI1wfpC69mc31UPMpk1MLmxDXnbnE6Vnsc1b9UJkycr8dqyqOus6NtlOVhcPLt8GQ4oArXVVIUY5ZmZh5MINAgqXtOpjGGlc0tjKiK2jIvCXR9fXzUJHQ2ZXJuo2FCj8669mwau/MzUwV/GAHbsA3BBBu6T1xjoffNtDCBkHTWXRbymlNwAAUEo3UUrHKKUNAPgJAJwnykspvYpSei6l9Nxjjz02NKvBYbqOJFmzQrTq2ptLmuupveR5VUbFMgHOvW7UJkashdFYQWHkWq6eDW0WKv7tA1h6uiuR/VoYFaij+RDTil9SpbTpAsXrwkwVDZ0WByAGdmUs6A7u2Hy6ubEWC6MI6jYW+Kp/WZ3GFOOGhU0fyKwdfWP/8Bhs3Su/abJtYRSgcEeYtG9o5bDMJW3P4Ags3rSnnCECxNim3YjY5ny5hVH5hc94hMqwFhF3RvbQHqukHk0xjNxBmr3ipwDwOKX0O8zzE5lkbweABXzeboTpZj+yeacnECqAK/a99UTqMP/q3MT454T4dkljzT6bv8f19xX8gmNYhH2ehvvgofSOM6F1hdIlraIYRlVWM4Vmu5bm6Q6xMLIuzzWGkScFeynoNSBc0vg8igwphFG9UF2uMDgyBos27vZfQEWIeQNkAttLG1yBKTUqCyMOmdWW6Frz0NB1PROlemyIQe7rJcSqdK8SbEgBbP/rFQuj0LekvRgA/gkA5hNC5raefQYALiSEnA3NNlkJAP8WmI+ORJosqwOV/PYN3eKeva7SSsH0ZqiQQke2YE0Y6IP9w2PMc7/1YbNJLt7oE5/GqOmS5q8oVmFUrn5DlzTLDVWlLmnZqb6jvihLbx94trMmfh/ciucgRNBrxzJCo9OszUJCVBdZm/zfPzwKf50nD3Qty8+izs2OanrrJF1SZtVbtWIBM0x+MX0lmt61M1fbM2OBbJ16eOWOSssF6Kz+1Uv45QMr62YBAOSyl9AlzeN61alLH7sHw8oMoz0SwyiowohSej+IdxY3hyw3Vhi7pHXYxqEb0Nyk+KEjfq7Op1UoBRAOTIKRUkeBUkSVLSoTvMYP9MGO/cNWZaD4sHETiGA8qhQomA22Cdg4TTzVqoTUSoWOlpXLQB8Btud1u+LHPei1n+/87p1LSs+0CsOIrQ4AkoURC6FCp/VsxnJ8gFVZnXZ6DCN2Tm3eEOiBqCEajXhd0jbvkbvS8Vi5bX9ATuKCThYrhDCKsF1V6JQ1lEXG8xf//FjNnDQhCzcpelxVbcfcDQvzMNKCuVcssyIM3dq9MB4kpc7aI72yBviuW1tqsUykSv4dXNJ0YC2MhpngnLEFj43RJa1BQ1oYUek7DB7fYOduUmnw99b/+gmBVzzj2MLzKlG9S1q9+QHkbrFafZEBL7Wsn3FNW7VCNY4wJv2ltuYexGphhKbhTiKH7XqZheKIRQ6JFaXa7YC+1y1ukwlmMGl2fyE5dCfjfsoJgUwBy1vsq93de2OhTwqjKmFsYcT97bFP1uWrHjuamxT3urEl0b7S0ZkFNHRWP7q0RmVJNobt920Lo6GACiPbQKT5b3+sGEFpYQTlvrt5z6B1WcoYRpq8nSib5nF0CMDEgf7Cc1M6Tny4Za+8QB9Dc1hyc5P+lrT2b20sj1r0RWmdzaGY+30EDa1TaPftwqULGhsKdQW9ju1AyBR1jnOTpurAZRmNaGSOyLqydG4SPo6M+RrABr3GrimdPn9hkRRGESOkAPTmH9wfjHYnIqtpbxp2zcQre1/HoifqZ6IJMFNmEfAreBQUMa3f4wf6YJRRavrWb1rFMGJ/12VhpCi3QWmpni68aoaSHjb2Rn0uadVVdFYS/2mPrtkJV9+/woBOk5K1K1vlFkZuBfpoo2GBwkAUCJuHiaCWbkmrF6L6z+pnBNE4Hr0TvUM5j1bHRg7buhjLXdIqjmFUaWkeENHA1rZVPKwaw6SaY9EXxQa5S1rYW9JUiLmt8hhGAslI9lm9YoCRFEYVwvWWNJ9dcqGli0i3Ax/mLAzYycomnw2EFka6xJYCpSrwKUB7AziBsfCQ5asTUVoO0PIGetmWfcosqlZUBb2uKihqlbWcxYDiBfA/zF5rSMcnV+ERA78jIoUR6Nu/HGNAnqOOU8AY6jYWCAObt57ZWBjx9Do9hhEPl8+xXZ/aQa8TVAhp/W8KXVt9+a8L83SxuaX5ZCeWb4tuyjcJeu2pSF+eGnWA7UfsmqKaU3tEX5QURlXCdT7r1AHYCciqFnOqbULPFDqXtKoEU1Vf870wF4NeN/8d398nTeO7TKtMEQ7FkbEGXDVtuTd67MkU3x+6Meh1pqDgv8108+XKcpTKSAV8cGvtkuah7JDotLYMCbV1JCJ/brknTlxvDKNwa2KVyIJeV60x6nTRtlb+NW11/SNmBx5VQhcLscO7RdQQ1XxVSvdOaFeTvWCv7M2TwqhCmK7BpdNTb5wkyOBTw26Deg5JBCe/kg+Que3Yl8S7erUsjMYVpybvMYwc88Q4Fm9fuAnmr9tllCfb6Jx3ylGldwULIzfWrFGl1UAmIPB925gFd41RpXAuzgO/IoURpRQRw8jEJS1ZGNUJUf37rJ9a48iEuL3UJa+rS1rFGqOte/E3oCUUgb2AgpD4LMf8hjZIk60IMpc0EapySQOIKOYUB/Z2YKzMkFzSEmoH3wV/+cDKOtjoCbDCpg/B0zXeQt3Tj6wOKKUt02afhYlc0sJaGLmiW4QTwv3Lok8RxCjWxd4F2S1pvLWAcdDrzBLCF2OB4dqXvVgYSVySzOte8a6GBukRORIF3WGBKYGyO6IhQx7hYz6MoavkLmldOL/7REyHuZ3cVD77Wd3j5+DxzTAKsYmGsioWWUX6ZL1T4xjlt6QJ1pcYrVurRFIYVQhTs2W+c/5l3gaf7CQwYF3SPFFUvpV1hT6dS1qIk0yhS5o8vQsPwrKY37lL2gBvYWRfJpYPkzzdsj5kbSlq0z7F6oA91XRFpfUssTAyJuPIdKf1LS9Br0UWRtCsy5eefoyibHwZ9VigdFprBoRwnTGxEJOSMablGyqLHCxXfq2t7NDILYw6D6cec3BtZdfa95CN5f2gzwN0lmwm9RqqCWat3A7z1+ottw+ZOBCGgUAQxjDyVImYtTaWmFM8WLawFkbdcoCsQ1IYVQjT8cF3wTiHV7eBepHxbS2MarlRRfBMpqBpu6RZBr3WuL/FHPQ6Bh58I2tHkQJI5ZLWrbekURDEMKq43Ssvr+b8AABDohhGtDkfqARLEyVQuiWtXri6BL73pw/B0s178795avXGMFK8Q9Lg+7JT0Gtbl7RWvkj3ckpUyXOKTdY7eOcVD8Kbf6i/VTq3TImsb9ShmKF+tlG1oHBLGvIjxnpkoU8KowphPGx7wA0kFhSCXvugZ5kva2PjW9IcOodx0GvrkmTlM+6AUgsj3xOyoxtOl6wPKhcE2W0RAHqFoa8+snXvsCdKcpz5pMPy383P5FzSDOnR0o+44WwR5eE7RRZGU+ZvgA27BpUxGApWf1TNSx0K3w7pApVAZ12Kwby1O6XvOv2WtJ9PX5n/rutwolFTDCMfqMrqFSA2lzT8d8fWrrEpV1zQafszEbuVTTseLLlDgb14iPcqkFVPw/ySz45EUhh1EGIdYN0EX/OlrcCn3YgHWJXE1x1L0rqeQAoIsyfDmdA/jr8lzbI4KRs2LmmS352MLFjf4o17S+/6C7ekFd91mnCkQq6kpQAAVGBhZEfXVhiuum+5Wxi5czyiuFZdtREsjkk1H3XswbvRKtEWwpowrJ7RhvzUt1NvSXvtGcfDgFAr6vJBdnmz9cAkUG4sqFVhVGPf++cXTUali9EFqJumx/hqtwnZGiR0SfMkfWCoRNgdAYC1MBIcQkjXni7qyAokhVGFMHdJ4071Yx1hXQRK8WaISjq27wub12ogLEvwLA+QTPyeUxU2fa0/eAHaewwjmzwFa4buWiB27jez5Ommmai/Fawpm29Lt6QZ9hbnINLd1bVQEFkYZVBbGLUrSzdH1KIwqr7IaCG8Jc2whhpMI5fGWaQWRjq5bdxAH0wa369MYwp7l7TO9UmrkuWYNojvfsHJcMwh43GJI2vWeGrRHyLqGgCgquNyZ/BmKeNpH1UL5He9SBHTfBASSWFUKUyDXgdiIyE4bNsulvVcNgG6nkCIcu9ilBVZuf3cLjEGBY0LB43Ir1HgXQB5dLPyOlNOylyafN7UFSUiUHDJbkkDUPe1orKZKueJOoS6CKataOCjLkYV82itcSQcpsM+Qso3M0I9fSf2dUqFetekuutN/+0xLtk6ua6T5s9YZSKTC3SqrO7Y3CMz5BZGnDyhli0CMxUJksKoQhhbGHGdsBPNhDsF2WTQ9FN1H/3WLmk1BagrPVOk933bxvfvXpr/vmnOOgAAGNfPK4z8ldekZ06wsHgY5lVtdGKASGEksvzKEKlsZIV+Nrg3FQS9NqTXabekubukuUNlYaTsalT4U4hagl5XX2TEEFgYGVZQQzEH1+qS5pC3j/ifT10tjDpxeu+vcDfDK5/rVmygb0qLrGF11TZr1fZK+MDgnkWbUelim/NN+PF5MKvdR0XWFzPkN1UL3sm+KFkYJdSOWx/bWPg7Vo1sN0EXOBVNxzIfq92uCrqby0TPbRVbus/aNzwGAAADfWGDXjtTMyQwGnlUPD5mFA/+c7tpJsqs2TJlMT/PVi0LVH8rmysBdx7UFka4onXfsWJrOU5XaMRgGRkLRAod0+oZHZNnqNXAyGEn3idw8fYlh5gii2EUm2IBgzpjGNUNzJd3YJPCb2asrpuFHF+dslD5vtPGjO+oaSwiPx9VohjTEodOtsw0QVIYVYgOm096Ctlw9ybgW8bTyCar3z28xqg4l8VKxItIQUNIK20FHXmAszCKTYNvaoU2otjoxIDxuuPZkoVR98xmWV/L4peVPy3utnOFu5upe/0MjVgGvS7MC2pOHlm9E8WLzj3TBJFNW7XCR12o1oE6lXOu1t++51PbMZnVbyceTla5JvG1W/cwR1sYhWXDGJ00P+r6V1vRENlHSYNeh/NJw1xJH1tfzCCb+1Sf0yP6oqQwqhLOC1qsI6yLQMHPnGltYdRq47U7Dnjgwh5qlzT7jogVZHkLI/8uaW55Nu0eMso7qrCgUN0QZQvTqYZX0AEUv7cUw8iGqUhRiGEE5W+zFQbsb1frLPgYm9+76wnpO18WRlj4Dejfaa0ZDia3ccpQcO3lMtdZ0y5rIgH/86m1S1oHWxhVyTKvFKhbR4Dtf9100FM1dDXXiUpWHt5uSUOQibUr5nyZWBjVPQFUhKQwqhCu4yPS8dUVyMd7hyz8PFzmK/EtaWqCtpM9ls+yhZFdeVI+HPPPXrXDKP2Y4gMGR8YcuXGHaXNWaf4fGmyA9aaFkR/rNus+VrkLnGN+P2xIoQx6LdcfOJTniRDUv5GMCWKXNLMKUs2jv3pwpSFH8YK2/mef3w6Z53Qnzu78RRkhEdu4Rs1ZXbRm1wFd9cVavbKuKnRJ89Svu8HixmT+TS5pCdEh1gmp2+DDpNQ+6LXde999QzX/VdEPB0rCX/0TsosAP6JUGAWwMPJMzzTodSedZLIbjesfWQvrdtZr3Vc1nBVGgXdPqp6068AIwwd4mSZ8KkNj21jWCVE/Ma0elWAeYh7FQtVlOmkvnwe9joQfE1R5KUzZJa3egY799A5s1miAPcylEJdbmsktab70HiNjDeVBaNOSO87emAe95uLINf8WV1CP6ItgoG4GegnuHmlxDrBuQLbg1+2SpqUbgLA46LW4oOy5tSUUMt1APx/02qo4OR9Wt6TZl6dySQthYeRDYcN+rsrK5r1/e3JUwSlNkbk/7tg/LHxfedDrijcfCzfsdspfp4VRQWHkiZPkkhYvWJe0mGrWab4l+f/lcA167e6S1nmyZpU8x3dLmv7bO69F44L2kIz5XXd/YCFbg0QyvK/16qf3r9CmiXWKseEruaQleIerwifWAdZN8HUyoCcjTlCHq4/QVUCRvgoOeQujTp+QVUGvDwRQGI01qNJ9g4dp7bLd9MTDDzLMHRcyCyPZ2LOdE+zzWWXraKisA7DzjbcYRiTrD+60erEtZRDN4ab1E+s64BxuwPOi6hr0uhNRqYVRh1ZT2kOEQ660o3Eps00sjDq1X4eASVV08rxpgqQwqhDOFkZpsg+GbLzT/P8c6VkSiaWNRboGAu2qsY9hhKsXPh5BDCafLiyolDcHhsPEMPr5dP0pDxY89514Ai1D1tdkn1R11+s02cPP7Vfyd9iNIPUkqPu1MErIIO4nZjU0GsNCIECI+0zq+NJODnpd5WEbL9/V3Ss7sb06Ddpb0pjfneCSJkwbjo0SYu2ybZc0rjYU8kWky5J3JIVRByG5pIWHr3nelo6ujUMsRMLYEop4E4TYT/bv//nDqHTjuKDXMSzALiyobkILFfR6zfb9yvfPOP5QNQHmg/lvZzfxIjnKxLqpbmiDpXbOp3QlsMpJb+5fSWMUBKL503ROHRltz6MxrAkZ/FsI1UMgVxhZDoI3PedEu4I9IKTC6EmHTyz8XdpL1twXMZ/elNvSHsIW2ppjEsQzM5VlaSUq7MexHjoyhmJoJAujhOgQ6fjqCtD8X7fbSXh6ptC1cYh9uAnJqubF8f39Qcuten5XnYyHcEkDADhkojpEna6fq90SifB3JyJzf5T1icotjKISN+sHdt3z5pLmhwwApLZk4UOoHlYo3uuEag7EfHUssl3WRrb8POvEw7zx8qLTjjZKH7IOn8YdroSUH2y+o9PX4E4ANoYRBRqVlfDRh0wQPhe6pAXmpROQtyOyMgjprANSFySFUYWIRShIUMPLZK+hYVtGkKDXyJPfpksaBQIkeF/mT0V8a/BtNnIum7+xRvUWRgdPwN9pYFq9bPt3+rzWp1EY2fY9294Sk7AZA7CWA6pbTEzg8+SzR+RIFERVYVo9w6ORKowCXGjiFPTaMl/bwqh+fPVtzzZKX6VLWsibNG2+QvXpEwb6WnTDy23dDJObYWM6KDCRX6qUPaLtirJYlpI27SekZ2S2pDCqEO5Br6MdYh2PPIaRL5c02xhGlnTdekaZpmqRqcK0edwAf0ta/TOyLQuzV+1QBr1+aMV2S47UOAShMLr4786yok0kvzsR/ZnPumRsRdD1ehrooNe+bknz2KHrdlWJCh5c0liFUUw1q+oymD7A9znXbmPb7zIFp+0Y8Dl2tK7CHKoMes3D5zC3kfOV/c+elQQLuN5w6BvSoNeCXlOpnB2p4MhairGYu2YnrNtRVhT39ZEo9idVICmMOgiRjq+uAgU/k72OhtLdR9HQlVkYVVi+COP7eYWRX/pVzu/vuPwB5YLy8+krg5R78Hi9wujISePtiDtORk89epIbAY/o17qkVSsM9IbogUdnu6QlZBDekmZYQ0NjbAwjZ5a8wfUwTxz02v4D3S2M7L7H50GSqcVQSAujKmVvOwsjldCYpbFixxinHXtwNQVFhmLQ69rYKEHGSp23pMV8kNLX1hgV8P6fPywMLdFPSHJJS/AP1wlbF8Q2wQW08A+PMwx983XTh6wr6PpIVROtqhhCwgsf4ziFke+dl001OtV9DevJhHHq6V1noq76XFY4t+kLVboP6JApjLy7PUbkdtrJwG5CKfgZZj77ZmrLNkRVYSpnb949mP+OaAqBDbvkLkp6WYAINvz1dBzXW9J8tokprTot8H0eKtjMP2oLo2r70qETx1VaXlXQrUN5sGQal0uaTG6tO4ZRRNN3Adk8gpUn+vuSS1pwEEJeTwhZTAhZSgi5qC4+qoTrerZ86z4/jCRI4SfktV65oLQwUryrKui1aPNMCKlsQRkf2CUtWY1k8ajav01QdEnzK+BWjdzCSPK+V4SBWNGHlFJ8KdNtbkmRIXWdNkTNo4rtJsLDK3co6ZnifS98qjsRAKXLsS2fewdHLbkBmL50q1U+13XW57xuqgDqFpc0OxMj+SuWtyp0anW2Q51Ysmlv/jsmmcHEJa1Ky59YQ6yYctVH4giZUQVqURgRQvoB4EcA8AYAOAMALiSEnFEHL1Ui3WQQL9gYRj4mTRcKqok0hKLD/HPD92M+6LXvr7azMPLMRGBg+LVdtImjhVFMUyF7Msg/459Xgw7raMFhYGHkpeq8BjHyR6vDIRKqRxWKFh18rIXWLrkcfE9nW/cOw+0LNznlt0Hbwsh2XbDKJoSp4iEmq1UX+F5OKSKNT3RLO7ggplk/JmunToBIHlShv4/AWI+s83VZGJ0HAEsppcsppcMA8DsAeGtNvCQkaGE6HdjPH+rFNkwMI0FsCUlB2ePQpwPlGEb1T8guHETAvld0k0iYCbjSPl+1NVqX9RVXmMQw8tFWXoNe+yPV8RDVhUvsBx8HcL7a2rWdY9ljZ+usLTu1xjAKuJvRhwqorixxHsUhI8NcFYfWfV1qYoRehyCuGD0yI846YxjJyo8B2RjByhKZS1pMbR4K+HuX/eLJALCG+XstALygJl4qQ2wD5Kwv3VY3C1Fg4rh+2LaveSLnKw6GDqrJxcYlzUWBYxZbglbSj8suaX7pVz2113HKgynRNvZBbHOZC9q3pInRA3JA1MB3NU8uacy/rhTnrd2V1tkW9ghcrEYcJnYvykFPG2jft6TVhZhuSeusGEb+4NvF27VNTdFN+qIDw2NW+WISGUxuVq5KTqWS8mOAqYVR+8Axnnk8FOpSGIn7Kp+IkA8BwIcAAE4++eTQPAVHbH3pnc87qW4WaseOfcNw09z1+d91a4m1J1kVuaQpg15D+L7MB7323i4Vu6TV0a027JQHYs1gujjm+ZgeEKsvOhbZiWhDsnkV3YwREr5LG9/fB8NjZrFiYgLW0sDXdcY+u/MLTz0annniof4Idihmr9oB89buKj0fc+iXa7br5zcdqpi6cIr7OOZQVwsjnzCtk25xhbJRuGA/vYoq6u8ijdGzvnCrcR5KaVSHTPJDZnzaEIhVbjRlK+vvY5RCXxQzZzjUpTBaCwBPYf4+CQDW84kopVcBwFUAAOeee25EQ9AOMY2Pt539JPjim8+sm43asXjjnqLCCOq3KLC9uconZIopWtFpVVlhFLY8DDrNF/ziWxZp01i3IxH+7Ehk8m0sretbORrTumMDI1cAH+V57NFfePMZ8CzDGza7EZfduUSoMKpaGcsjlqERyxhtOMcw8vchpqTqDXrtrx/b1CFmzqpKKdktijsnxCJMABjxEoOcHQuwVZH19xjCZoRGXTGMHgaA0wkhpxBCxgPAuwDgzzXxkpCQoznm8TF9fKNpvYPzR/cFkSJEVEzuqlGBPDCun8CRk9rXs3b6ZNyJ3KuqnBXOO10+7GdMirsRnS7Am1gY+UCdbjXdiknj+4XPXWIY+YCv9lHS6aB5xfVAqM7uXuc859clzSIP1sLIgrYpOn298QFWpn7acYfUyIlKdi63U5WHorH2El1MSx75LbsdNM/bohaFEaV0FAA+CgC3AcDjAHAdpfSxOnipFu5DxNcpSqzmgFVDVA2rt+8PXq7t3BJkUhK6pMkCADcRuvcQQuDZTz6c4ccvfZuF0c0lLc7VxPbUsXBLmi9makJfn5mAEBq+ueh0DwF80GvqpfI6vLqixEHjxcbstVsYVSAHucaSqxJxuaQZpg/IdKX1EUPlO6DT1xsZsJ/Feyk884R6XZKl6qIU9FoI0zANB41rHoasQ4SA6HTUZWEElNKbKaVPp5SeRin9Wl18VAkfA2TA01UQsWyO6oaoSb5+s96VJxQIIcqVKYR8LSKpKoYAqUTQZsvwbWFkQ67bRgxlIg+K6kNmFQBQ7KKdrnzOT4iYZ3VOj77L7sT2Ya0LsUrNBvV1S1rn1VfsyIRqHqNj3Tar2iGWPpfLF5b81KksmCjpY5XAYze2szBC5CLV9LNuimFkg5vnbyh0h7rHdtrrmYGVNzB19+KnHQMAzTh93Y7aFEa9CB/TRq9Pxr0AtXU7/sYDLEyCXle5+LDfFMWa58BEDOyLoOo3//KSU+T5umga6jM8Ueo0dGJbHXfoxPw3PoaRp1vSPMa0iiWYcd2Qu6R1bjB2LHRrpuaMqFK4Whj5jWFkRutlpx/rrWxT+HTlsbmWXpajju1C3QqSuvGnuevhL4+WQvLWBmnQa8GzapVLcfYT0+57yMSm9WwvKOaSwqjDcGDE7prHBDHqWtt27h+Rvqs66LVI2FFZ9BBSfb15tzDySi3GAvXQteH4Adzy0OnyYe6zzjRSnd/k3yWtsxsIzX2Et6QlNHGQRGFUv0tarcW3EQkfzjGMfMb/Mkh73KETusYVymcMowHm8hBiSdsU/dEMKs8w+K5te4fa2ULwYgC5S5oghlFVl+rQiOZeCbB1EflneEVSGFWIXte8x4lqA6rqUEfQa2E5hs9Dw3e5NvXowsOWPUP6RDVANSep+iH7znZW+8OHX2iZ0y9OOnISALRP4t77tyfXyI3/Md6JGylWeYc9cY/xlrS05Dchc0mrPei1t7ZWrNmeSqgCbQsjy9h2PpkxAIWw8rWOts8p2+d3jKth8vcUNaNrUPsaIOmcIrZqno6jgOgAUQXTmEedjDS0K0Td80ZC5yNIzGukSxohrZMBqL4vx3BLmgsLn7p+nj9GPMLe9UD2Bx6yTWSVuPC8kxmXtGYDP+ME3DXorzvz+FBseUWnH1RguX/P1Q95UUB0eHVFiXH9YlGzGy2MXvZ0c9eoWLqc8zrr1SXNG6ngiPWWtNOYG7oIIZXUaaevNzqYhgWpuzZMgl5XKWfXXS8ymHbfXnI7TwqjCtHl82hHIrY20bl7hZjQhUGvlS5pNfikeb8lzRw/vGepXyZqhtYsGNnEXpROEcC0T3SKq1dHWhgxjVH1BsRnaR1Y9UEga8LRsXpjGMXSPrFssjP9nbVLmj9WjDdicdSgO2z6gqiunnH8oYWbZqtCp6yLpsi+qtNi1ZjsGSqNYBR5N0G7pHmMeRg7ksIooaeBnbN8BjXUQRn0OkQMIwFRqUtaTYvlWAS3pCWIYb+5iENiyAR0mrtjYPOF4cd/34yjnk1QvGWm2rJj2bx3E2Q12o0WRjxJzIat7h53xomHFQKTd+IhQK1x57y6pPnJ85SjJpXasYq5LeYDiref82RnGqZNXZVllwwmfbPTlGEh0HZJw6Zv/tsLVZcURhUilg1SQrxoGu/4i4dw6rEHwydf9wxlmqvvW1EuR3eziyEfrojBJa0bUeecFEOsA/aGItMuFqLu+oh/5XTMArwM7PxTNfterSQ6sO5DQLamdUsMI/bzbL4ohn7iwcvY75wYQZ1kqJIVK5c02XOiT+MbMVsYnXrMwc40zOWEeutEfktamacqxWzZXHHP/30FHHfohOoY4cBakmGqo5cOmCIQ2XsHPdSvOgadNthlihzVZ+gWq/uXbi09ky0y2eNqfOGZciNwSetGtAP2lWtE6a1WEETtOkMsCnQ+aCG2bwexTiDEe1+PWYDHoHL+O7u6okQvWRjx0I3nZkzA+jsdO86s5/SaPqPuW5d8KvmtvkOQqa76qL8nh8HKbfus89Z5aGNiNVRpDCNJnRw2cSC/qr4OGMcwyl3Sun9XkRRGCT2N2BY3ohHVZPO5ap63ERx807MBW4z3dSxZLAGAn/5v2x9isHwp9DHDvCEUGQT8d80Y6tkFvqv5wvPUt+B1eHVFCVkb1m1hlNAEBeBMjOzo1GmdJ5KcvvzWMyvhxatLmkUtSi2M2NtMq5LbIj6gcGFt5/4Ry0LrrRNZ3xQHvQ7LS2fAzCUtG2O9sKVICqOEBAQqnQwUa4vJ5J/BZsMo1ZZnVhgVb6t8+1b3wNzuDJWQUxBEA9CvEhkbpldKh1DE9BFSOuV77lOOcKIZSz1jMfnoSUHH5/te+FTle7/11Vl1HwqyMTVSd9DrCsYGzq0hOBtaFC2M7ODzO3yQet8LJ3ugUi1s1hVRvRPJ89Do9AMKL+Cs9Wq1MDJYTauMYRRrN+EtzrHpewFJYVQheqljdQrYNnnPC06Gw2o0hQSA5mmE4rWNyaiNckdcDMnpVd2X08lHINieJBPxb1sadaEZwyg7IaL5M1zeED5p5Q3mz9//fDeSEdSzCe795CsLleCbfZ1lWIdVV0dAZWE0PIpXGr3c4sp6FUK0daf2n+Kc3oFuxrVuyv3B7pY0DF1zXmwQ83pTx+EJIXHGMBKnrdIlLc6O0lbu4eoiD3odhJu4kBRGFSLWAdLLYAWcg8b1w9OPP7RGbppQ9RMbxYmdS5q4oLomRd8LWS+Yj2KQK0uE78xomCKa2DqGJ0pcNitMGOiD0487REyT4+PgCf2ldCaIpZpNEHJ46urDZ7/sxLqvEmt3HICnf+4WdPrL/vFsr+WHaJ9S30V05hhkQx8WRl5jXkdQJ2h4FCjsbkkrZ2IvdKgSVa3rAxZmO3XdAlanrGPyzVVVT8zxfkxdzGKIP1cVksKoQvROt+pMNG8oE7+LZXqzmWhtBC9ZKZTSWgQR3xZGMS9YVcL+NhzZH5Y0IkAe0B2Z3mVDc9D4fnj3C8qxdEQuaa4CSTSKOVt45l+3z+j06ooRsjpdtmWvEZ0+B9+ON551QulZLE1dNx+UUti+bzj/28u64AgMrbMZd11M+peefowtO5XBSmEkpVWHRU01ZZ581CTjPJXVB3fLZ60B2Y0sjMLx0SmwDXrdC6fQSWGU0NPgJ4e6tcXaxUU6J8kzWcUwUgW9NifnAX4n40a9oTOigaot0a5ZlmXHoMhgg8wbWxg5si8SzojAJc01/kEM9RwXqquPVPNNyNZV0zHnMhZEPPjaQKqXbP1HxjZE7d2Mq/2QC897ilHZofijADBj+bYgtDEQxzAiyr+r5CVMQRWV44i6XdJks4+IpSoPUmOb8zK0bz0zQ/eri5LCqFLEOkASmlAJE7EEgzPmgtqtqzIXsNwKo+K+7Pvko0pf7W6ED8E7lvkw+5aGaQwjlzJBPKeInrvWdRX1fNTB4+GdzzvJGz3KndD6hN7CKJKO2UXwVaX9bhqj8qMImjoGHnjYKhe8WhghiJnyGaqqKQV411UzvNCyUS7UfdDJoqoAz/F8sR6qOjnn5COClh2jS5oKda+/pi5pvXQglxRGFcLHpP7ev1VfCZzgiJrHPiFEE8PIfEa3MeP/7UOrpe/YQMEhwdaD91vSIlgY6waFdh2L6kPVxuwb6wCpEayzrHulaZdwFRSEdU5ISTnqWk1VCDTb9w3Dt//+ud7ohRyeVQa9rlv4jQW+qsGlL4vyVtE6urWG0jjmQhax8SNDIVC3YXrDkmwzVlOSRBnq43IKU1S1ge6UjXrzljSVTB+2/JXb9qPTVhv0WvGuMi4EZecWRhS1T8iDXvfAniIpjCqEj/ntS28+051IQg5TgaMKKC2MJJNSFZMvIdVOiizfycIoDHzMSZ3sksYivyUN+UV9DqsnIURo/k2grCxxraa6atnlpDnk8NTVZ2TdsisgdUkzVA26WBgJc1bQ2KOIxSsmCxGAOA4BMHXC8omzSHLD9y88Bw4/aFzpuc8DLTsLI9nz6vtVZR5pcQ0ZKZqKOwWzNcmiIp6qkospjW/Oy2A69/XSoVBSGHUYfHXOtF1ugq/Puoe+rnx5MGoVUb9fRWqIeu17IRtLCiMAsG9GHyeXPhRGn3jN051p5CdKhlGvXediWQwjfjB3gkuaCK965vH1FKyB1sKo7kWgCyHT85hOw/0OjSOO8+IHLquJ6rKNuuBjXXDmAUHL9Apsk7n00294poRG+ZlXacKiDncdGCmTqalPVbWBtlKs1VAnzRhG8vcxSaK/mSH3LPCJpnV7JUVZQ7Q2feDFk0vP2hZGMbVkGCSFUYWIfHwkKAS3KqcC1UQqU5yo8vj0Kc9OhGUkn3LUQf4KY8v1fUta98/tzgi9oHuxbvJgfZP7rBuOctdwKliXNFfUZcnlq9iq2fd58pnW/CZ8rasufUGUlRCASeP77Yl6Qrf0E93YOWJS2TrHqbyChTjCIsmA9tv/5snC/KHbyob+yJj4Fo86pv6q1ptOsuxQu6TJZ8HPXfCsEOzUD8vYqlVA5WJ2yISB0rM8rENIpiJBUhhViRrdP0LR6XTEVg/NucfvcYRv008VtaccaX7VKY8nH1FWOvnW3ieXtCZ83IZjT8MuXyhkXQLLlou1A4BYQUWI/5tK6hKsnVzSmDrwPX/pYrrF1i+7A340Ri59WZSXAIEHLzofZnz6fGu6AJ1/AMHz3ylzep/hOuTju0T9yGf72/RxcXyuepx+quoDnTNNE7WFkaLvOAX518CE8vcvPMdr2RSosp8/7bhDAABg/ED1KoqMK1nIgNKzzumIzkgKowrhY/r21Tk7XL7xBv6EKga/WqW7s2HLUfBnYcRaRcgmex/987oPv7D0LMUwCgW5dQ22Ke1v1IlhrJGyS5pBXheIyusjxPvms6pba3i4tG/I4Ym9Jc0HD70kTKogtzCqN8gqIQCHTxoHJxw+sTI+hKi5o/DtEGpuNrE+CVMlBuUL0sq88X32YpvPxtRrda5ilRRj1T989OuPvPI0REHtcvqIuu5V60wsy8fJR7kfBLOgGgujS//hbPjlB8+DkwSHx6GhaivRuz6P8kLsSAqjDkMnmWF2IqTVW1OwZx4NseWxmp5HJSMFUDLoRSkqLNuzhZFFPXYj6nQL8yFY+pgPMwqZEhFL0ykALxFbzRHwrxyNLbg4BkGDXmvmqM6rrfjB1unX335W/rvaSxREVhi+YP8hcRxTFeHD8lT43o6sFAULI0R66+/yQANdlo0iRJKnm13S6oph9NozTjAuU3VBRl16hjrFAtU+gkDT9evlTz+2Qo6K5QPIQgaUn+UubME4igdJYVQhOlBu73qwopqufb7wpjMCc6PfzEhjGKlo+g56reDSpwKCpeV7E90LAeqcEXi+ikaRYbnguyq8ZEGvfffNuqrZ5Ra5kNBbGPkrKz5VQD1g16B3v+Bk+OUHz4Nx/aT2a5xjmIKa7hl1c1GELTs+PwMzdgqn+4jCTfgTB0kXU/A5Z9vMGcK1lLNsqayLRWxhVAcIEKWso+o7sRgI+OaCUiqlWaiNOj7f8EC8l9b4SEW67kTvdKvOAT8fq+bn15xRza0/apc0s+cA/vodYQoKuY6JFlffm+h0S1oTdc5JkchCbRjGMHJTeMlcz/xXSl1CZ7SClE5hVA0XPQW+Tl/+9GPhzCcdbkXrvk+90gsPzWdxtHbdXFQVw8j3VGRKz0/5dbdWGTEp57s96DWqWGZA9RF1nShd0iLpar75aFB5+x3pOTC+KbK2uv6RtYJ35fTtkAbdv6eIaJrpfsSiLU4Qg4BagKyi+Zo+8uaLi4o1Xws4BYDhsYbyGmCfLkLsL/8xjPzS61So4rVgN1O2bR7LfJh9Z9slDZdPFzxZB5F1RR/xH1/LV0yJcf2muzM/5fqGbj702S8j6eK1Q2bdY9PTJ4yzE1uFbeGpfVyGLAESzVzYhuWcrnP39BzDiJ3bcLekGZQv4SlKlzSJuyX7tKouVlkMo2qKcQYbJ9E4r19WONpu1A+dMAAvPf0Yh/LLeO0Zx9c+F+4fHgUAgJ9PX1lan0QyX938VomkMEroaWCHepX6BfX8Y86Jr/nsjoWbAABg+95h6aYr1AGeb+19L5wGYOCjvazdFyJYZ9kNQJUuabLNcpig134qely/mbjgUmrI8anjK4Ju2XWQbWi7JYZRt60m4wdsDwE0701oeUyVpzZILr5VT1xitOJEDZNZVVZ7NuuvH3nHvM8pLYxUs0cMQhLIv9lFtojk00pYu+OA9J0qhlEvICmMKkQP9avOAXtCpTk9qkKTLBNIMthYxvg2Ed62b0j6zksMI0ENJAujeGEf9Lqd8d0vOLnSsgs0Wv+2bwDE5XMdV8Kg11FbGBkqjBzqJ+Tw1AbmJcV/E9whtjAKY8Uig8htJ5bT4bq54Mfb+P5+KzpVf0cfJ7/pEKq5fV7K4atPElJPOPXqbkkzL6iO4d6MYSR/r5JFsew+9WjzW8zMlKfi506HZiiLwOpx6jEHAwDAacceXHon4jndkpYQBJHIJgkdDNOTd0pDBNSUm9B7OcGpYJxUGWw1ZqgVpEgaths4Jtu/vuQU+N+3nGlFxwUs76ZCv7vCSMSPf2WJr02DqcLI18ZB1C4uVa+3MEoLdRWovpabJb709GNgwkBfTTyIEZts6NXtz+B9MS1iQ2kY1NmHS1roGD2hqFc2r1UVw6iSUgTlGhastTBSBr3GlVHXBSK+LYxikMpf/+wTAQDgBaceXXoX68UJVSGYwogQ8i1CyCJCyDxCyI2EkCNazycTQg4QQua2/rsiFA+xIQmi8aFwS5oydpA8qr9nhpSCkmxCrdIyqhlnKVxZVdRzI5kYtfp063TEgY69f34c82HWZ7MugeXLSVgCsdKS2AZ2UcBXQNQBQw1QyNZ1oa2NQxJHt+wqxCBUZzxMGt8Prz3zhMIzV7i6UMYyF2YYb6gcbkNjveeosOFhrJS2Xas0lkwxnj8RCDfuVHSrsjCK5pZVDfoMZfpCX0PHkbRgzAM6pAmMQAjACYdNhLExcYzJcvpMho5wEvCMkBZGdwDAsymlzwGAJQDwaebdMkrp2a3/PhyQh4QEI8Rioi6DTM+hvGnBMw8E5Iu1Hwuj8G0Qo4BXB5SKRsnzj77yaah0JmXbBob0sdHKyzXsFK6Csaw039ZvA540Rqbf6+SSpqkCt5PNdt4zn3RY+T2SB1xZ7jS6AcJ4MB4270b5Wv+yfcebwsiVQGT9xNSaMEPV/Z1fQ7TpLWlnkM0JPmdsn3XIkgpFl0d1t6RZ5KlooLH9gRC1S5qPEEY2de46FprP/azDLml8gwBAfx+BUcFmS+yS1vy3F/YUwRRGlNLbKaWjrT9nAMBJocrqGEQmFCSUT45kTUSZtPanbwh+QL1xjiFYc59ic+8zpkzItWLP0Kg+UaT4wYXn1Fr++c86rvC3jxhGBOqZHtkxn1sY6SxQWnC5JY0QsYDR1+ffLNv1NrcMGOHt2U9uK2BcStWd1hEC8I6/sRMp2DY/ZMJA6X2nnFx3EkQ1WrVVTX9rHDQDy9NaeJChbi54uWL8gKXCSPfe4ENxMYnMlH/YDSifrGiJXsYltywS0nnWiYfBoRPLc4xJ2bYIOY2p6rGqvmzzfVVZgbDDSeeSxh8QEclvFULXuXCeJK4xjOrHBc85Ufi8v49ILMDLaWNZQ6pAVTGMPggAtzB/n0IImUMImUoIeWlFPNSOJIfGByMte0UTg1phZJaHKt7ZQqVY87EMhBwn500+KhzxitAvWKX/4Vz/+niZUOhrQ60z868apspY5xhGotg84P+WtH5PdYsxVPrdh14IJx/VCsDpUK6uDgghcOk/PNeKtu7U3etJfAwdOwIIq6HiqsnHa2TzTgw88JhgqzDSfIzvTzWl50PeMxnTt/zXS+Gck480KNVOzsQc4Pmse6WFUUU+aXZWNW68YQ+TWGWDLuh12SXNTAkKUNMhBw0Qw6ji83AZ9wMyCyMB07mFkUe+YoWTwogQcichZIHgv7cyaT4LAKMA8NvWow0AcDKl9BwA+B8AuIYQUrYLb+b9ECFkFiFk1pYtW1xYjQIRygUJDAjEKbyxsDkh8a3oUi2afiyMSOtfvzj20AnwhTef4ZlqHDjXUhGWtZfJQl1uY7uWKgkbNgKgYydhx7zpyHIxNJQphgjx75LW78klDTOPHDJhIL9dJKQQ60K5GCi3TCn2NaATIeoLttVsm4+1MPINlyFLaXx9LpyFEf5DMWnzG4oQZTdpIsvO/88dxkotj+WGOuRUurJX1JetXNIq4o3VNbAxjEzLDxrDyCCPjL7LXCrOK7e2CgHhukQI9PURGGs0BOnLNGKbu0PCSZKklL6aUvpswX9/AgAghPwzALwJAN5DW8e3lNIhSum21u/ZALAMAJ4uoX8VpfRcSum5xx57rAurCQlC8EKJauxXMTE0rXfkBQnmMBRNGf79FaeZ04Owt6SFWiWOOGgcDPgyt6gRoi+wXbhVfU2qFOTyuMYU0fERHs2y2y5pOCsf91vSRBZG/k/ZfB34Gscw8lOsEG6CqlqA99kXO3+28QOhgVHAQ4cMrItkpjAi0N6W+LIAS0Gvm6h682RqperKXqdZEYRqD6XcUJUlPusmqCnyxMMnBilXBnY+aLqkydMqD4gisTCSWYi6FBuDokXGw0AfgbEGLQljMgUTQIph5ARCyOsB4P8BwFsopfuZ58cSQvpbv08FgNMBYHkoPmJCMk+PD4UWUbRPlZOB0iXNs8ji+5TXi4VRKCGHdEd8EtEnBAyrhSrflY7azTEs2lZWZmPLdT4XxjAK0D99KUlNeXP5FF1LuMVOUG80umCKiA8Gijlf1X/RG54JLzu9fdCY9V+278TQ1Fg3l5Dgx5u1hZHkO975vJOU721hPidhLTZIaX0S/cbRMkxvllxRrp+DHTFx+SvfHmlHThonZoEpp1/zcc856XCfLGlRdknD7y2I5LcKNkbEfi4MsacRxdwred6fKYz49IIMbSvH7tcYmUVjM8MPAWACANzR6lQzWjeivQwAvkwIGQWAMQD4MKV0e0A+okEMAyRBjbqD+RFNOTa3wfu2mqJAFRZGHhYhZwpyVHXla9WwtjBSZMNStFY6ehBoXZtTbGGCg4sepul6Jnrh3yUtRMwpVHqH1sHEMLJFncrJXoWJ6x8hRNkBzNya2r8zpbqOfh2oW2HEw94lTa0E9P2dRPGXPr1duuAKII+VFKpbqej6PvTAxFJs/g4/pgngmoedXvqYg0oRlyWFkZUcFNjCSESfOsrTiA/F1IUs3hCOBcG6pKApYieyqTsogimMKKVPkzy/HgCuD1VuzIhNKEjgTo4gjsGvFIhtFEZKpYD5FzcaoS2MwrSCypWus1D+BneFEb5jdUUVMsg+x3QP6RrcUxz02v9eVhQk3QbYPtZ293EpTX9Lmg+IFRkeN2xdNlZsYWLJ5c3Cgvs737QhrEVMdUpxqZ/cMWA7ZyjqMwSMAwQb8CGVcQx7qOl84rX/F8quZl6ras5jy+nrg6b5QSQo6Bo4azUTYPtO6INQGRtOQa8Fz2xkn4F+F4WR+HmfxMJIlCGz7orsDCIIKnRkSFBhzudfUzcLPQns4k+BVqJN0i0QpmaPzUnML+MUqNQE1ovCyCOtAl3SzS5plgoji77h5TRLcKrm83YYLLbvG8nHXGbZg6Xpao4tc0nzbdos6xuZmwgWVbqkaWm75NUoDDp/hogP4pNZiTWKxwbIymCHAKYfV71O1B7DqDQf264nsuek8C8WN33kxcr3+Q1FyN2aaxDhKgKUd4KIoo596NnCCPFc55JmgmMOGa/mB1EUayXMWhiJwPfdgsu0vig8U+5ZOAJuNHw12TiHeAzimERMDCP+nYBG7XN3hUgKowqh6liHTAzpHVhGL2hDTaGLJaCbGJ4/+Uj444df6M6H4p1MkW47aVm5pFGFsO/FL9qZhBQ+BYuYEOKESXX6XvzbT+F1NA0F2rYwyvhA9mHXOqcCBZXUVc0Bvvq8OZlwDepi3dWnOfENobDodQhN/6UWRuo6w9ZowQKBtKkS0B+8GLeaw5jVyR114dXPOs44j9RVnRT/RdMzKA9lYNRKhJk+ZNZLpk1VW9OSYtmh+thzn3IE/J+XnpL/7VsWwVi36NYDk3n4WScKL+02QimGkWKnrVrvsbGJglsYScv1a2FkAxeFkYyHfplLmuiAKcK5OxSSwqhC9FLH6hgUBAECLtPY4QeNg6cdd4gbOxoWZPFNVAKwWglmjobqDlsPfTzkJqsbxqDoE3QL9/tfNFlMy6I+vNRhIKWTC9ihhWHHSVgipH0rG/sccDe0mUBmYWS88cG6pOW3zRkWIKDB/855sSfNbaLKlP721KPh7ec8GS7+u7McSklgYdRePhV2mYKAGQN9BSWDWsFRBeI9vLOwWpA9J+r3trDdKA9oNpnEoxTiW0kWsmxsXl6BduTB4wt/VwGWB52FdSYfu8oZhOB6hszCSFR+SXYv7Un0OOEw81vgTGpCrrQzLpahqc+M+X43HsTPZUGvRTJfHvQ63oncG5LCKBJUvV2KYH8WBUzqAZM2dNBn2ZykvuZUVZgNv1QuGFpQK9HIhUu/nZQQ4hx3JgYQQuDEwyfCk484KH+mUl688awT4ILnnCim1fpX3K9kigYPdSiQkWyouvLSjGvV/G3qkuZsYdSqhMIGljTf+ISsz59mqNw2/V6X+tHfkuamrGu7yJQxrr8PvvuPZ8PJR02yLqNdljOJroDROuurTIZSH2kzgVrHDRvOdcTGoDD3AflnyDfMdvTK7zG0szlpnG5yUipLwrZVJ/SFotId4F9fcmr+t07GYuUW89LEz7FWtKY1e97kowxzNMEfPqnaVHVLGhb/8QphyODgcJG/RDktIxE58FDOSwhAf18f3iUt/uHqDUlh1KPoAWWoMVSm4bj6IkAcR1RTrpXPQDY3KPm++a1B5TRjFnYIdM8taQ9++nz44EtOyf9WnbDJugwFu8WOL8pO5cjRUIy9kCDEXuhxjXPSEFjisJZHviALYPuhl54qfC6DcQwjB0FOd1rndHKuodMlU0RUMAkurutnNsqnolJWb8VXZR9ozkH1QnhhowVTOostDMljDpkAv/jA83HlGbqkZf1AZ2HUpC15jmHMIYdPhalVPBxEer7e2Vv1VDLgs598GPz2X19gyIkYhbhkHgU7dm7I5KrDDxqXP8OMi0ZBYURyXk2VJJiyDpkwAAMuV7aiIJmrHfY7vuQ9l6aX8d9PAJZv2Vt6LuK5bWFkz0enICmMKoTaxLNukaE3wde6rBUoMua1Lo0w8r4BfF+5bQNKqXSS9tGLQw0FQrok6HXrX3ZTrffhtyhH1sYeqjCGfgyQKWibv/OYQsi8rn2p7bpVFL5VypK/fPQl6M1UBllgR1Mh21QwCznUnAKOE8gbWbkpsi7BL42ugIFizle/KbisECaGERGnceGhG90RvK4ZBkSPO3QCvOIZx7WS+13XsnlDF/dEKgdaXH6yc/+wUXqf86abS5rdQaP6nfmNYXJ3KHtlGLa8TBHjMh/o5M6ShVFFc4/JGiqfJx3WYU+t5jZexJmnPbEVdg+OwqNrd3GpxbIUQPfdlClCUhhViBQAMz6YnlDpwC4Mk8b3l95v3D2o50nxrtHA8XENc4qjPinC0SvwoAp67aES64xh9PKnHxusbF8Qn3LI06vlCattgUWeInjFKX8aiubEkRU2v6nc5Xpd/euffQIANIPls/yo2Dhi0jg4jDntxEDEp42MiY5hlKU3LwIN19gJo2PNiVQZ2DIt194gtOSyPHQwmidahYxRamTlUrWs1gXnGAAgr1sT5Tp3I7kSZXdeXfrmv+MQFhlF6xx7OXHL3iHDHH7AW64Zu1mqFomC0rVIV30wbsQCX5SUlm4tth3PGd38cEfBD4tS0GtlJsUtaVhXu5rmDycRSJDXRvnl5BYnPMgQxy9qvfRafqchKYwqRLcIBd0MjBWYLMA0f5LwymccBxf/3Vlw/jPxt43oXHNklhl8nqMPmSB9V8hnMdmpXJm8nMqT4r++gLEwet8Ln+q30Iqg8+HXnaQLXRKQtGzayfVUzRfY/s+6iJ1yzMH6vE5Ki6ZycuUlF8Dpxx2aP+8jBBoKK0Qb9xVXxVYGLJn27W+4DCK6OrHRVUjLqvi+J7Y60dEirfkAIK4G+fzir9JWbt0HAAD7h8cY+nqFqemQefKRpnFZioixm1g1g2ad8f2dBWsxBPUsvc6FRyWHGcdhMkodzwYUa2Fkwm1T4eLn+1j2sApJ0z49YOlzxS7hfaRdl6LyVU4HWHZD9xkfimAszUIaRCInOcxD+myt6EIj0xKSwigSxLFE9B6KJzDqidd4giMAF553MkwcV7Y0UvMkL0kaj0Yap4YqJ1Td9cLishRBry1nbzYQYqixQIBYK1Zigvi03pxx7GmZKJ8rhIrPGuqe3Ri0eSLw8Vc/HX71wfOUeUO4N+osjGza2ZfCyHfA2gyTxg+Unvne0JuA5P92wGTQIRD1HWkcPI/lbt/XdgdqBzpnTvAl+Uz7+qV/f7Ypa1HBl0ud1PI4+1fiHmuLPH6IYXqdIsBVDhSViYanAUCAV6j5Q8Ey30hj5M8lje2yLrF0VMji/2HcWFnwQa/VFuB2NxzbpCvkMUkbYK72JT65yGHCvApyJutYNyIpjCpE73SrzoHPsc4v0LZUVDTGkBZGpidvpvC9gLALfqgJGGNh1AmTv6g9lUGvJeJ001LMQtHkoY7KLmnFviO71S0EsvpkORrX3wcv07gnqupcV0VKCz3NiaNp/WNvkNHBOIYRcjYQue6qrKwAOmOcJrQhai1pC+qaFr2JEq+lqFNrXBE5Dp1YVnp2EsQWpjZrg+x5pqwTlcPxYh2TRZ+mfb25VRGWrryG6c2LUJQdxgJEJV8iPdmcsXtwJP+NtjAyLKOfs0TDVictuaSVldV5Wu5vG9m9rtUwhhhGLvAxNnMLox6IYpQURhUiCblxQyZgtt8jaIhOLz02u+9gwVYuaVRRF5bfGiqAIQ/dLXadGhRbv5n3Z5nCP7WpspI+oKZqLwyn3JUKl1dV57b9qHlLmvuJY4GXyC2MDp5Q3mzr5rmQw1TlPmBMKwKhOAbIAq+LEKrGWLconXDvo+0PMrQs7gZodX1CBZ7isENraWg3J/G5tC7IhhYmxTLDzJuh6ShlYQe6piKsbA7dtrdtPRhKbuNvGCVIu+xCDCPNQWXJPZ/9jVaO49LZ5pEldbLuEcjiVatcZNy/9ewnCZ+LeM5DlXS/vigpjKoEVmOfUB18CvQ601MRzjvlqBINFbCTEpH+4Y6GyiXNsjDRIul7TBBAWBj5LTIMBEyqlAKYEz/Rqa6srny0i0ghUJe1U0bCdL1XlW1r1aN1SbMYYbzQawtzCyMchBZGumvPO2KgJmQQt5e4Eb0pOKW8MIcTGosYdFmC5Je84yxsbqOyQsDXZkdqeWypfPCt2MvdErmMpx1bVBixrspFfsxlnJDusyYwrSul3GDp69Zc3/x0tq2MwgivWDGrhOzQzLQJ2fVLdxCtPCBClxi2k8n4d7p8whPPLu6IQhczAPjeu86B4w6dIHiHP/joRiSFUUJPQ+XKxaIZt0c/M/gIiKiiYWNh5Hs+a1oY+VUmFG87af7+x+efDAAAJxw20Y4oD6K7raIzLIxEHKr4ftNzn6TYGCnKkVoAuNcR349LipCKTmvYGF8ZT9ivUymFtC5pilgfakG9/Oxpxx0C//GK06R5vMUwQtZM5m7Im/PLIFYYqTtAyHEqs0JwoZVQhq2FkUmdyixXdcuoS7uZBn2P5ULmy/7x7MLfPq0WlDGBuFds2+gUx7a3pJl8muv0abpeegsKrQlvoM2PVPLxydQHHv6Uk9ntok89ehJMGAhjzSc6bMHUKbt+sUGvRU37Js793u7gzDiLGf0Ayn1vlnQO40XFg0huElpItv6NYxYPi6QwqhBJeIwfros1O8eECEQsvSWN/9uRDxUalEqFKNuSRCxmt0g96Qg/CiMC+o3ms598mDeLjNBgu4JMefGCU46CtzxXbF4LoBHkZUoNXslq0ep8jJq65kZK2/yPjJkt+aqTLVuFRp/OJQ1EGyx1YHtfyhXsSV6mMMKOI13Qa1FtVKHYTS7k/qAStEOWKXaB0nPho3+ZUIihr5127CHONGRfoVY++NnwmdySplJSNWm16fF9wdwlLWx6AFxfs7XG0tEycm0ixMKSV/z8O/9wNkz95Ctg6idfGWwu6bc0XykEvQZ5+9z+3y+Df/rbyYVnBWUc4sOohP45Jx+hzOe61xHJIr6BmRedlKJCiyHxuJeX30rXAz5pSWFUIZTXVEYgMPQ6VE1AAbSrcvNEx4OgqSDRaIify6aqEHNYM1iy+J3t51fV/3WLwMETBuDoQ8ZXwostRHUlk2tcqjUEzQz8ybGt8OGz11w1bXmTJpIRVV/SWfWoxo9yyFp8cL+nVR4rQLUVRriC2Vgvrz/zhCYNXQwjFGU7+KSdVvUmTEz5fSoDRZsvzEbJJcC7+VoWRy/BWlub0MifG+RhXZZ0AbBN20kWfLgceJjkfPQRwvUjs0LrjGEULoaaHV0C5kHN33iW+AKMg8b3w1OP1sSe4stHsM2217iWlWzOMcF9ecHCqE9u6TVxoF/Dk6HSgsGN//FiVF4cfclzJ2VvOa9VUHlrDjRxKBXxivjye2X7nhRGCT2N0kBXnYQhJwUTl4b3vXAyjmgLWAsj9onvuay54Iup+ohhVHrnaTaWnTjzfGA3LMcdOgGec9Lh7owZIuOOFaxlPGfdRXfya2LF4aM9fAdvd0HZYgoHVT+xVpyCWmNEys572rgavjbg2HYfNbQwylzXzjjxMLjin54HAPUGvebL6BVhMCTEFkay+UVDy6Bc4e1fOqWspJTXnXm8Qcmd1W9EcWXs1nJ1m5rGANHHMmtt6FUXcQjSY5Dx+uwnH8Y9N4N5evN6l1WTqQUWx4j8lYqu57X96ccfAisvucArTSzsYxixt6S186PoMImwClEro3hFnlc+Q31DrFO5+uLN6DhMtEqXNIlySEYjHok2HJLCKCGhBZuAsoX8BoqiDBc850QYz5gA6ALkjeokKAVfvqASzmzLqsTFBPRtQwhB82LRFEYwqRJfcWpYoN0OLYouxTDS9PuQsC1W1U9sg6sTogmCacHsq59lttGVAdvFMv6xMYyyumK/Wx9jJmBn8Wnh0klag4AwtLHwVuYYM0mLrnY3Wcd+cOHfwFfe9mx0+k6Dj2+Q16dCua5sb7+WhnkMIwLwxrNOaJdSiqkHMH6gD/744RfCzz9wnmEpHI91rWvEcSQhLsvIysECp6zly9IXgKVpWh/iGEZ6KgXZkLQ9DzBWfMW6xXHs25LstWeeAM884VBtOhe5HaXg9URHnleuFMLe7Om6b+wkJIVRQk8DO9TPOPEwY8sD7ETGn+6peBpDaCn++rGXuJ0saUDB/w1aqny+uB/o7/N6S5qpabUviD5BtpnPOBQKHppTWd+BzVnwrpVNZZ45YVdeZBYIGKg8rmQ0Xnjq0UqaOoGaiGhrFLiTdVdGI2HukoZLj9QrcbyY5zGF0alwghJCwdzzoYMI4tsY9flEScYP9MExB+vdlfOg15H0nAueI3bp4VHi14J9qSKc+X39v7+o8I4fy4X4ZZ6DXrNpvssE+ZYVc+7ko+Dwg8ZJaWBguqmORvmolA3Ev/UkSa2hXkyLto9hxAe9lqctu2SaI0SfKcRhktCPwsIoUF5RQG+VhWRERvPBkBRGCT0NfuETCbZ//PAL4XsXnmNFE8BsQtOlHR2TBDFiMH4g7LBuUKrgMxZpp4xx/XorFkLaigDd5r6u9SFbtNgFSiqUOjApVQp6aONYXNKwrgwi8PVz3uSj4FSNckbvbkOUikih37+Cns9qxgqH+S1pSGE7E8xM+kTIzThPOVkJuUNUg1KFkY4W9tSdEGHMP0L0m9aQ1jbCtO7FCfHI518D5zzlCBwPXr5ZdsjQfv68px6JygOgX75MD8bah3kauwDZcqq5YEBcpll6f+DkHUM+VMlVdaePwWe4KCH4xh7emTZFdujBWidiaBSDXrf7GkZ5yAfMDgWTQ1rMuDYv30yWMaHjI6/IJU1qdU+I0K2325AURgkJDETzwbmTj4JDJgwYCapOPCiyYyyM+EXNt/BbtUuar/3auP4+bduwgqSu3NBKD5PPlsYw0tiVszEgsOXLFKInHo6/zY4Pakw0p3BhUSwYbWEkqggioigoUXIy3nRJU5VZfkaVClyfwJWSzVHjDF3STIZTFX3Fy7zpTqIrIDPlx6bVQSbIs/MMEYxN6RznwFtMCsZ+xh1GBdGarsv1n696WukZds1Q5WGnAd9LrEwuEt2SVvjbze/FMLm//hNKsc6yyK+DqjYjmvexwdbVv8FZGGUQKs65pw3BnKWD7ynHWgYyKUPwzMZq3+XThesS0b/jn8Uz44dFUhgl9DQcDmBKyCb6jA6WHm/6qcpnGsOoeW24O9iFoblBlQjUSHol4bSCGXcc8roodKyW0EGMJBDVlfZWLsPnACoLIzGOO3SCkgcWZQHdrgO4dhsK5ifGGVTdydadD2OBVBfMLYywCqPmvyajKWTMMxcL0QQxhONBduhgUeOyeBPCORpBXtZ3Q212Q3Xnvj6DNbmkOFfnnDRhoExD2qbKggtgN426DWTxdjpl0lYakhfJJjdp1tBzsC/qrvOYqj5N5t8b/+NF8N1/fK6WppQP8ywKYnpqbApxDCN9MQ1OpjfROx06sT2uMGU1lb319MnQelRMGt9KqwziNUDQHwQW/92KpDBK6GnwE63JSRiPbMIwncBK84wk/+nHHYKzMCLcd3lYS9i5k4J/C6N/f8Vp0ne+BLTxaIVRS6jUFFvXApGxxcVVFMLF9UL6rqTs664tNba/qQIm6ijI3mvnDiJpF8M2eMbx+oCWPNAxjKhhDKO+TOAycEmrpMvh5gElhe4aGl5huwkRvZb1zbGC8iHLT0AbTNlDu5kcnoRaS/oIQW9Wfbha+bQaMwWmCHZtt123OmlMu/CqtBQyoHvOyUfCcYc2rY8JEPOg114trswwwMmMWFaKVkLyUAgyy+qnHj2p+R4ri+DYQucpK48FaQzmFnMOxPjRu/8Gnj/5SI4PBw4Ucxg66LVMJutCJIVRj6IHlKHG0Fn36F2UiulEQdO0PEiWiP86/3Q4ZOKA1MIo/AlDm35D4cdvo9w568mHw5ue8yRb1tAYwEbXJdk/6vShx5BJm0pPxHNaipcSyPpvkBNWSwHeud+LLPCQJG3cKF3rTkTXtB++5GnHwJ8++mLjsrHxP0fHMoWRmYLWZNMc1MLIg6IoQQ+pFZ4VLTEdkYVR0QVUXJrppQ5F9yaqTFsl+vsMXNK4Z3qlN25DxaYVvVeNZZMYRhiwt6SxWUu3pKnmdrMijbWBofqN6VqJtTDi6apj8Kmr42VPx13nXhWEFkaIHrB/eIxJz/Z/QwVQIGWvL/i+0v7C805W5rngOSfCB158inWZPJQ33QrbvoyMRC/sqZPCqMfwQY+DrRvgc57NFspsEvK9qcHTKy5pqgXOgGSOpnDpdpJoVDOeqhHvkobbMDYorcfKSMCXKEAfjpRiwURsjnxBp6wNCVuhh68fUqCloSmtW3U+VvjMYOp2eujEAZg4rt8gB463DNnpKlZBm1sYGfFikNgRLkq+WG7KihGymtHHmSs/w1kYFV3GVag6UHE4JYHBmszPZ7opzIBnE0tWdh7AxgnEBqPO0hAQW3184x1nCXkq/FmT+0/VdGxkAxkKN98pZvqvvPVMAR9m9H0iW5tM63L2qh35b9bCSKhwED0jZuXa3TCrGpR6+oT4dQdbeckF8Mazijc6iud6no9yIqw3gYp7kfgitipv/i+5pCV0HU468iAAqG9zFhuKnlvq0zisxUmWymYTrxLwbNtMxQZ2kmMn6YYq6DWerXaeijojVmGEZaeum75EPtOu5vWiU0FZf+eFBJOSp37yFQap1fCl/Ob5x36PlYWRnR6JyV9OYXo7h+14w2Yzj2HUTGd0S1pICyNeuE+LZRDYjhF0HlK8JS13SSNm17XjyifC33Wjn5hsJd35tpELlKUaTW16/vONOJFv/pTs0PDKRJ/9J6SrYwaM63G2RunGnm2QaZ83VLHVLzr0YN+zFztc928vFNLrU8n0GitLbF8I3ycFzxzLtVc26eXPRV95vZJCrghUuJ0JXdJE3BDJiy5EUhj1GHrJfM4GLuO+wZmiY104sDyIJrAvvOmMcn5ugfIxl7GClOo0L8RNcr7m4vGGtzbp4HIlu2/Ig7Rmp+pqwUQEqYWRCWMcjj9MfJMaAfO6/MKbz3Cuf5/zIGslZcuWTgCT1ZPRab8ld8YWRr4URkJlZnVwKiuS+SFGyKrGZkzL5my2T1FNWlce8nJyOaD+xu8zMDFSWtUI05tMOirlOveOCn8aY8JAWQCT3ibKnfap10WzdjWO2WOYXkqHFBUpXnsjQwyj5DnvlKPgtWccD19567OVCiNs3BhT2NIoH47JCZ167MGKsuUdy8DQx0NCv3CyMLI9uOLnKQt5CHOTq9AlTaI4A/CrtIwVSWHUY6hfhIkLsuutxWnV79snmHLttTgf0n9e8PhJRxykpa+0mkJ2CH7uzBaKEw6bKD1ZwaKqPskHMJQhtzDQVA6lYQNfm2yoZDKbC3u2N32pIBMu69xclQUQuw0W9h2AmVJYR9dXH5z/pdcq32NPE0dzCyPceMuGpVkMI3xaU5ie7ibYQX66rhkDEveIDCcflQWMLd4q2g56rUfIGFlihCmvrw+vHjblQHjabnEwwYOdBkwubeCb7FcfPK+UPo9hVCozXndFF7isDVhFhmrTnWHCQD9c9b5z4dRjD4FjDh0vTRd63JmSb1uiSOghekwfUQS9lmXKZVAt+eZNrzYuaY5pVcG8UTQReUXfxfcRsZIRx5hIRslyisa5TKFJAHrCCiMpjBISWDhMgNlpZjbR2MeVwT+Xabx9x85gJ8oGpYVJ9bxTjspPV7CfbLRYefoUtEuaoSVFKJgIGbIA1VoWFZ8qtzDiTt0M2kc2Jvg+W9VpDaV2whaAeuMaKnaNKPbGB198ill5tid7yHRjWdBrQ4u+WIJeJ1QDE4W4DsUgvO3nRQsjvKWaqWuMWHkSBzD1OfmYSWVrCgvltdzyuPg3q2RQVbXJOsCTUbmbyBiVHfYVFVNxKTWkdKB4I5lPttk64C830LXYcYdOhIc/+2r4+KtPL70T3rxX40Di54ESL0T4swSiTMOVwazmmHU9iKU734iyfYaLhZG13MX97fDtqi2BcA0QluWmOOskJIVRjyGdmqqBnaBVz7M6bt/IoaaJFYmwmySVsFMqG1n4BCZIrmiBesXTjwMAg2BzNXRDvEsajh6FeoUZVpiWmtq3/tWdkIm6AUvzlc9gbi9x+GbVzYE2dakU0kgzkKKWBkcEy4YVv4INCTvn3LVos1GZKy+5AD74klPMeJA8199IhPvgMVOXNJvbJAOOu7bSz72stNwqYKAQ14HtQmy7NQQWRrE1SmhudDLN9y88B3787ucZz4PZ+nDkpHHtPMhDhqKcIC9Jb2Fktp7kF1pIypFZIOXpgFofBOIRR//EKEAADG6fZXDsoRPE9Sh8ZC+T8+9NlRTZGsZaJ5o2v40ljsk+jYJdj/HRjbFL97+97FQBA3Zl2sprIihvSRMpnBX89ICBUTiFESHkS4SQdYSQua3/3si8+zQhZCkhZDEh5HWheEhI8AmtSxoULYzsrgnHn9Lp6OS/jbko4ofvPgcOmziQ/y0y3s7KsxEedPBlrYF1SZMJlTzquiVN1K+kQqyGQaxb1SnHHILKY4sQNDFtI0qCtpIrCS7ts8GgCg2NS442vySxbiOELSJzA+JPnmXIyo0l6HW7jNa/kWzgegWut6Sx+Qu3pGXvQS/c+7BgQ7ukO5ek40P9/vxnHgeHTxpn3M9ZuodMaMoHsnrjH49n4gth1yA9P/ZtxgZE18E2NiUW3iyMSDiXeZbHcZYVohvHJsB+JoZ8luT1Z56gtbojincZ+gh7865YbpbxgFHINGOK+l2jeMs+11vSPv3GZ5XzI/Kh+ojDtwsPtYikHMkzAr0jI4S2MPoupfTs1n83AwAQQs4AgHcBwJkA8HoA+DEhxPyO3wQhXnjq0cr3kR2uRQVXn9z2jSxNIrY3PmBvpzrxcHkA4cLfjgLZM084rECUUpovZDR/1vwXu0k0urvFU5/Fu6Th6NV1jaaJK4BL5cnie5X6l4fFktS05DrFeFBwLG0OzXttmYEq6ZOvewYcPGFAmQbtqml8S1rzX5O2CNlXGh7HdVpu5ZDGu7GotG37hoX0szX5yn96Xt7Biu5FYnrGLmnyfUft0PGRK0YNGc6Ss8NFVm3884LCiEvLxnR84alHw/tfNBku4K7bluXVvWtv3GV59O+Dx9nxSKsY9NofZZbWuAGfdAXPTPuliXyEpFP8bTg3sC5mpodRKIVR+LlGzDdxiudlreTisrnw0N/aE4hYEa0BqnhJopuGuw11uKS9FQB+RykdopSuAIClAFCOTpdghfOfdVzdLHQ01AKIembiLYzQrk3s9ehApEywc9WfP/piuPsTr8AV4Ah+jmy6pJH8N0D728cLbiaJBZjgjABmC1mdCli238g2OJhbt2QQuXkAlOvHV7whq7r0YgnA/Y0Uv1TxFkJZwPQ7KrUBxG3+kqcdo8+HLDez6sBuuvO5xKAfhdy0ZTeoVGEt1suQ1evQSEP8AkuX+Z215VlPPpyxMNI3aJVtTgKV97TjmlahOtrWigTkCTxA2e1UJSews8BAfx986S1nSm/XLLCjZ08f9FpTFRSocu6Jaa4g4Br0Gved2ENCE/qmCL9Zt1du9xH5txKJvaPJmGwobi1WQVUGtjqxF1uwOO7QCfCtdz7H/tBM87cJVFbVwqDXgs/N5u8e0BcFVxh9lBAyjxDyM0LIka1nTwaANUyata1nJRBCPkQImUUImbVly5bArPYGIlrPooNr3WQn09kcZLupkeViF50jDhoPB40XG+aVi/Xb6iKf6WyyRJ/MGrBkewLK44hJ8ts5CuVx5apQi0ua4JkqmLSSVpZP8B1s/2UFfilNgwY6dGLRmiWEoH34QeP0icBecHU9tbSB9JY5Rx5MTPV1yMYEVkGbfZOJZY9tPb7/RZO1aXjXOJcmSzED5ZDVzLqdB7wQJqSovGQvpdBtMG2sCGLDs048DAD0vEnXV4PDhuy3THnAy0JsDCMfV3OL4wkKFFr5rVfcoUepOxDpXyoZR/QtpjKC3eY/DF0MeLeeUEoqNA1nCgyt0mES3+/1cpGLnICZVxo0/Pwjok4IwFEH42QsFpe84yz4+3OfYt0fy2599t+eTUOiNkW7pJHe2Vc7KYwIIXcSQhYI/nsrAFwOAKcBwNkAsAEALs2yCUgJpxhK6VWU0nMppecee+yxoiQJpkgCrBJO1ZMHTmxNOB6DufKTUntB0dPxbZHwzXc+hxHUikPXyjwUyaCrVcHRh+AURrFcm2visiHvN0T9XlF+IS6IoixTYeWaf30B3P7fLzPkxhy3/NdLrfLhu5k8oY6GtTKZuIuGQuEPQdWUZ2z6bANmckpsW3+vfKbeAjdzqQttLdbrqKJa3/LcJwFAU0E9mt/ep4+f4yMUX93dxuTgo5mOV5LgFE0sZAYH/IEGq3QRWTBjygJQ8yhcJ7l/TfICNHlTyQc+ZAdfm39XS2lsbj425DuedxK8uTXuTCHcHMZkuWGl/CFSeV1r/YcduxY7eRVtCpw7o0hRAgBHHTzBvGAmv00afoy5jJbMQkoYFxTrktbiIKZuGgpOCiNK6asppc8W/PcnSukmSukYpbQBAD+BttvZWgB4CkPmJABY78JHQhtJuLVHUyljX3+5WXPrb1vhQaU0yqC67rNwPTmlXsSPjMZrzzgenj/5qNJV2NlmD1t/Jjy1Nf4GmQQ49hDc4taJV3bLTZ5daIqfu9bPi552DJx4+EFONDLIODl04gA86Qh9GSJrOezXlRRnCCWtaBOnqs43PUccu0PHizqt+JTMVxk/uPAc+JuTjzDgp/mvUQyjgEN0LMUwqgSyteIfz32K8Dmebvvfz7zxWTDvS6+FSeMHYKTVsBjLN36Ou/w9f+PEky2eP/lI67zYyzd0h0/SfIIcUgtIxSEDn8PWxZnnRxVvpKSkMilH6aqlrsUlX30Dgr4BMxqwSnifcxH7nfx4Onh8P/zgwnM8lqYHOui1h7Iw8jlfZtu9GSkfG1s4hoWMPvYQtkjLrC5k+TO4yKOTWl4aL3962yClHVpEpDAS8EOa3xKVYjMQQt6Sxkq6bweABa3ffwaAdxFCJhBCTgGA0wFgZig+eg3ak5NKuOhM2J46ZWi7pDUT2ly/qlJaFVyEKlRqyIIfs3C5sRi9QXfsvUcejHRJMxCggzaDlDa+0PaNb+U8YjN+phT2XeDu1lx0/dHDLt7U0v8fQGKpo6hvUbomD/J0X3v7WYK8KPbkZdvmQ2Z883OfBDf8x4vR6bN50temTZkPkabhM+p1ghSyJjz12IOt8rXftxP09xE4bGLTbWK0FQF7oI8Y35J2xpMOM+bJx3z20tPtLevbc5EmXb6B4/Or84mC1ctkHt5tqagw11eULIVK8a6KMVcC1yFUHJnGPWEVYJgYj3Wsg6ZFst/JuyG6HFqLsqIUiGwcUKVCz5Qfrt9a0DO9TKe5BzCD91vSBFXOz8uEAByJDPMggjc5REJo5mfPh5c9XT1/HjxhAO771Cvh0r9/bumdyENE5jXSK/vqkDGMvkkImU8ImQcArwSA/wYAoJQ+BgDXAcBCALgVAD5CKR0LyEdCAhou8252mpOtn74ncZaaKtZcWfBTLKCGPPC3jPC3pGEVWaYLaPMHPo8I49G3pOELqiWGkUk96DZXCnPaokuaXGnoo5tjbkkz2ZQZXdHOl4z8HhvBFLuJM4XrXIMVfEOgba0objNx37QrC/MJYx5jGCXIIWsL29tFc7oS+qPZ7X2sSxrS7beOGCEAbnUhq4dSuvyARL05luUrWLFIClN9R6hDF1UMEnm7658rZa/IZgsn8QR5mDRg6b8Zqt1dyWot8mR9R3rQq1B4mjCm5MkdqqmGEIC7P/EK+PdXnMaUSeza3lGex/ab4w6dCIdNVN/8OtBH4ClHTRIqcoVBrxXW2b4uf4kZwRRGlNJ/opSeRSl9DqX0LZTSDcy7r1FKT6OUPoNSeksoHnoRWOEgoQzdSUA2WcjiYPAH0/ZxSmTPGaFFa2bObvblwExxhKGXC5dc+WxA0VBwJR0gHnetwMR80X4Lor8DcCe5AWoIM1RMxhPawghNsQwRN1gOVSfjsnTmpciIih7paRqfeiJzZKd2RkGvDXlp59PnLCkbHao7rbcqyDZYYSptdKxpYTQOsRDwPGjlKuEzf99x2MSBkpWODrr4dXm6PL0ZT6Lvk7GYjfFsaKmsls1iGCn4E7zMrYP4MlsrQe5aLyHM3hArgtCqybAf+IthxNWlcp2x5xF7uYEpXRPgXdLw9EWWPjqLIykdcbcDAHV/V8kx/+/1zyyldwE75/HKD1lYCBsvCp6maz6XT+cPwAEg70yibxNbLSo0gl2GeO/ATshx83/ig7f2SL+tBf19BO7/f6+U+mfzczvSoKUAAnKlFfvcZKL2KX9nCyZvjk6591o6Fj3V9TuwG5H2IoLYRNegIDMpsq3gU78XgV0c2WTl03c/0NW3yX7J5LTH1ppAZWmla7s642SJvg9nYRSAGWDnEsZ1QzN5hqw/3iUtralhYGthhL71i0vHBr3WKZQtbwrnGEEmQyjtn/fUI+GFpx1tVrykHsrpWuudAV/CDCBvu0zZxcd5xPDH8igFLfMrnCMUiqBiMnl5ape08jtjywMC8L13nW2WRwJs2WKFpyI987LkkoYqEb/O+rxlzjo+FiNHFQ97cH1Xms5CLsvALpE+lIxsmbI6Z/s+IXYWkFkO1BLOJLrmX18gzKeSBUT1/osPPD//LbKQyj5d6JImsjDK8nW/gVFSGHUCnowI3opFbCazMaE5F6jr56QjJ8HEceLr7HmLD19B3drP28AqNXRzmOGczViT5tOkNC2WJhaum0S0wshgVqzHJY2gy3a7srgoHOS/rSkqykLQFd/UIc5lFEBZ8e4pR8nnXvUNPbhNrQ5CQd6xAYT7KIzCyLLldUIlH0AfAGDqp14Br1LcaGZbB5h8LUMUL0jrrRyymnG1UpXV+UhDEPRaUpaphVEo5MpUMF9r2kGv1elI6QcO4rlJTERVnxgLIyMmWhDNO4T7t/Qe0dA61x1XEAB469lP9kCnGIjX51zEUvJpYRR6urS3akE8V+iEjJQk0OZTpeCSWYBjoTooK5WazyXFTC7ypbVbOfe3qdLqFc9oyxVZXqy1pMwlrVdW+aQw6jLYXOWe4Ae8K4PNZMqfYMjo8UoNXgBjSXg5fchpZ4qq4vvc1Ny5JEHZkhNQYzrI2a6bNnlaC6PWvzr3tmIMI7P6eeYJh2rTYGiKTnZlAhV60yG4Jo0t5raPv0yaVSRwqUzP2Ty+e5hJkwg3egiOTJeWjCddvv7cJa3daCcefhA896Qj8r8//urTOdp+BX8WpRhGNVqDdTOk65wvGYYjk7mkDfT16Q9SSgoOrNZF+cgYImUqFqaWkmVXj+LfX3zzGVy+bFML2o/tL7mkseUgeMSkKW1m5WlK8otB+ar+6aPv+pxvXM6zPv3GZ8lfMjy+83l2txpiPxPT94u3wak0enpaBdm5tMabj+u+gkBuNiarhKrM9lrOyIFgaWGUy/N2H8mPMZe6EsqUmUuaMOh1mUZT7usNGSEpjDoBPhX4vdGvrUDArn6Oat2+xS9sNi5pKrC8mSij1Ca6iPxMB8xPLXk6ue9/uA7mSts0IHesQ8WEL5PbutTpFOX72t9p6AhvoJF0YJOg1yU+mN+TxquDJvIYyAa9bn/pYvllnTMrG/esnMZSwNPkyzeTsnIB4OOvfnrpWSiUXNIcCkvrrRyyuUnnbq3V3Ujej4yVLYxkpPi5JnQzShX6rec281n7sAC3BpQ2x7xSxSG0Fz/Gi9YRLnOhvC3FFqnlfAAi63BxeRTU8xlGxrjwvKfAeaccpU3nG6bVrOIxI/XFN58BB40vWtx383zJ96nnPuUI5p0sj7xfEFDf2Ii1YrayMOIVxAgahTAFhDhZg+KsmvXPbOaPLMh1bmGkUC6zUAa97gGftKQw6jJEPt9GD5v6+/rbnw0AfoJeq3Kw9NS3jvjtBSJlAe8WZXxLmoS+Kq3rV6GDXkciteg2EShlny9ljgNNzDrKK2tFecTxISRlojhrWij5OukCADhoXHNJVYzO5v977ouuVnEherzoVFIE0fXcLHQ3+JkxpU/iomxMcIev+FQ8ldFGK+g14iQnHpc0B2WKoWWuaUn5aTs7XCRDp1SfpuVaVINqc2cMJp86hlH5GT+dXPx3z4Gf/vO5mKKcQIigcM9w6p/IZxiE+krhuso8+vF7/wZFw/S72tZ78i9jafqYMwtcSm4KLVv3uMxPfvLZeERmMRLFMYxat2kKFUYCfgQ8dSuSwqgDYNQZdadJrX97QRtqDFs3h1x5InZlsF0syi/YNKVHomT6stA8Nf/lbxXIvjgPZhlSKeM4KeODXruVEyOc3ew8nQgjyCsSCZ7JrmI3mN/KJ+vmSs8MmUWS/mpee7jWv23Qa1uhVBvEWCIcv+m5JwIAwFue+yRBHitWUOOg5JJmV1SCBjqFuDSfZXntoNdEOz+ULYx04zlML2GVqaYBe7ExjDKU3fA06Q2+OQ96beuTJuNBIBNlMIk1xNdsKSuTQBXj0Mfa6HN59X0LaP5O0bd8yweYb8DeBmeKkmzAvT8YYYHcR+T1pRX1FR/vaQjlUI8Xs4MuFYjgl1H+0jxlTie3MBIdQqpc0oQdvpXPmIvOQ1IY9Rh6RRNqC5v6kcUZsNF8E9KeRk8/7hBhOU3aeOJe21yiqPrYq06H508+Et747BNtScrfK5RjRuUgCQiv2qwB8uDneMawm3yX4Og6fvA3tajpiBZwGWXsFe2U2vcrkfB3UCsgvowm1urGlRfztHoCtixrYxi1CPNtdtqxh8DKSy6A048vx8CyjRWC+YayS1paNENAVqu+Ljfg222EiWGU8yBzFYnEwsil7+X1gJzhTEsyYa2Pc0ljs/JkRMo81E1qXBr17Ul8mc1/D53YVAC8UhlwX0FXw6NPGtoyoCiTBhADvatJQ8+1JtQx8le2DH3iNU+X0yZhFMqubp18luMPn5j/lolProG2VeWLUIh/KdkHKBVdkueZhZHaU6P8THxLGimNtW5FUhj1KJIQXAYBu4k9m3MyV4bcPctxU6M63VAJQwULcep3sZL5/j/lqEnwhw+/CA6fNA5Jh6GBLNs1oKSNu1yMyK27MK5eipNAABMBF5lQAByf+gIGRAqjAIs0+kReUHvZDYra03l0GbhnJhCfCovTstfbG28oWzlYoUxUTv7eoC0xCvMPv/w0PEEGqlvSHv7sq+HFT8Nfb56WWTlkY94mkGqRrvj5qOiWNAlMYxjJLC0e/PSrtGWp45Q0/7W5Dlw398vSs5xhgOFsgBvjRcsgTqZAldrKq3qn3EiKXx5+0Dh44KJXwZfecqa0ILVLmvuA7wTZnJh2LiENXDpTb4iM7Lf//rlmDClo5X+XDokIrLzkAvjY+aeDDH1EfRmG6PMwdePbwuh9f/tUOEIiv2f0fVjfmxwAf+ktZ7a/M587eGW+OVOZhZEqr9glTaAwIp0xZn0gKYw6ACZd8dAJahPJ/LrGXlCHVoTcwkjy3BdYcibKE58nAW0z9+omSF+nWfig1+G+bf6XXhuMtgj+TivtKaFnGkUR//Oap8PJR00q03acxyi1b29RtklcAFAe7aDx4jIvf48+JoKQF8fUovzHHDIBTmBOHW0VtnqXtOa/JptiHStHHTweLjyvfHsP5gv4GEZsnmMPnQDHHzYREsJBr2zF9Sce+S1piBhGpT5rOf2ZBs3nka1ZjYa5crxtYYSDsUuawbxZin0i+S0vyzyNkYUR8/tJRxwkjXNFKVXOPbG5s7Nzquk6p+pu+SUnNkwp4JNeoY8ZEFYfqBApLam1IsOL6hBYlF4dEFvEHx58lr4+Am9+TtP9uxTgvpW4agujieP64QVc8HV+jNmMuezQILM6FVoTCQgL+0brXxulfqchKYy6CF9/+1nw6jOOr5uNjkVTU2yXD6C90XBzO2lvJflJO6OnmyCxN37YcKUStAwJin6qszi7Kpim8y/9HToRZ4EF4KndPCm/lKe1nqpJReY/JSd4Ppbo0imiZT4AyG+MkSmEdO6OLz79GH25AQQ1UT855pDx0lPMzHUDU07hNhdBumxzjnUjBNDPrTJFImY88JaipSzdLxcGw/GHTch/y5rC1cIop1960HzCWirKSiopTyzXAhdrRTZ/FZsRHa+qOD+6z+Q3wKobnkwUY+34Z2WYBL3O5guMzMZuJH/zLy8Q8qODKpUvqYNCeDcZl7XIp+V7UTEmeC+xTtHBmwxmXK4+fXEM+ZfzxJZP7NxpOSdmewnH/Bls9lnZoY/oG0U3OeZlCZVIySUtISJgJ4N3v+Bk/RCM7AQkNthdX5tLdc1/8hvDzMtnzRuLcfza06RIoLa5IhPPU5sYf2ppO0masGcbPFxGR4Yzn3RYK51jQYFhwl/boqUMdlOta0eXKglpzWiiZJChbGaOzVh+lLmkiXDfp14pVBixZHgzaKyizlmJJHhWiu/E/DH/S69D0+7XCLbtGEYmO0VMErtKKfNhX7mhgiF3Ih646FVw+3+/PP9bVjcTB9RWejrI6P7wwnPgQy87Fc448TAtDdNb0mTzq2vry+IjYmA6J/DJJynmMlP67e8oW6bg4hPpn/NpRMGp9cHL9WDns5dwCn5RmaZtt27nAbMMEjQDpbfhU65px6LyO78JlT2IfFi3Lltu2QNTTF9k0cfkKcvpEkUxhifPSwtLrnTo3Hrr04LOln8XS8IMP7jwHPjim8+Apx/fjBPLtkv27SIjQ5GbGlGU021ICqMuQ6903BAgQGDMYgcqC8Fh48Kh8o9v31RgeFrhcVFvWw240bHZ52PKfOvZT4LTjj3YgjrAP79wMgD4dyUMBdyps0ZARn6qTZU876lHGqXXu5qU3zu7pAG1jzUmqNss6PWwIBDOU46axPjvi8vEWFe0hTdbvgXPAipg+jUWHcRhUywDIWLXAcx3ymIYxeZu0ml40hEHweEHtS0sZW0xYZxaLNU1g2yNespRk+Azb3wW9PURbV/jwxxZbzQ9WcXaDI1zn3qUPhEDntf/fs3TpZadAEUl0N+e2ozrNW5AsgFWKOVRcw9qBy3mT0yv+E5/YMIcmikmArzbu/zdQyu2o2joQIHGbWEUaD4VWcOblVVWQ+a3ANvwQyyUtwHX43YZYuWHih8fLmljAqWxC2z4OPqQCfCBF5+inJ+FFkYKmeL/t/fecZYU5f7/p86ZvJN3J2yYtDs7m/NsznlZQIKCS1hyDgsuQZIBQeHnvV6v16uIXvM1XBUzCggqev0iiH5NJEVARJH4VZa07M7U749zuk+Hqu6q7upz+sx53ryWmemurqrurq7w1BMqQMGIBEaVBs15g4kmMGKua0WdqyrZjNMkTWxaphMhzXldVNwSdDMtSCeX4OWmOexJgSGhWFzkO1nqFdMNrSytS0AGlt+ezqZa13G7HauWEXI+qnDo2OEpgef932m0ST9jzN6VkmnLWMITWWhmX54BdXFOXnTahHjnVXy989noCkys5GFtT9UE6T1HOBzRJqjZ6I+Slvup2p87/QiWug9JM7JHI/MfY5JD5+eieU6VbC74fO5EeJGMsdhCRq/2sg7WPSqX5fl7XG0V9m4dCk3PAXxo1yLc8bZ1Up9NXj+PQf2Vjvld0GsJFBhJygx7zRzA6kG52bCJzSYVp+wq5DSMwp/lEzceGilvwPyMTNguSrgSF2866M6/mXa7KPialadJcgNDHiWt8LtK8TcePQ8Pvsetjbzv9QO56yN+K37tz/gPwplFkEmaWMjGUCkraxIYlQF6i+vg1JXizT0KjAVHyJFR8MHhiZIW4VFnMoWdcb8Po9xPYbQoRxfvvI4jvlq8qA4mnafvXtkXeN56rsXa4U/7N6JTvbC0dVVZTGypww1Hz4tcnxndTfjAMQt8UUnsshOc8KmYMd149HzpOc6jtyvRZWEmJLqhroXl2kLAaHmIyhabArht0qJ+FmFR0lSfv4mvUknDSPLyvKHBZVTCTqMJZO8idpS0kPwBYNfSHjxy/Q5MafM70gcEpqFhZUpNS8zcSxq0RYJ8I9bXZDHU1QQZhU0wzwGoafuoma250wSG25acC/MlBQDrhzpw6541+PSpSwXX+9F9bY0hgWuEyG7IUXgSsxrjZlER83O2mTAt3igotT9pm5L3SQwSoZ5C1ZOYpkbR8g6iOpvxCZFfeu2gdr1yhVt1cB82vi6w12/+jIVlSdZrYxESGBGEg5HRnMRosLNR+RpbYOTZmVad+DrT5Saq4oWJbYoSsgDTQVcd3P49+sanj6MWBWuA/OiR5wAAz+7bH5qXiU67bEzSJPfq1PQJu5dMhuGeKzfjyEWTA9NZ2ZyxZsB/DgxvXjIFLfXVGHaYoelO2GRV7R+fW9SJblflfQeZEHDo+ysppJPvQMl2dsO016JojwXlZ5LIJmlONXZBHtbz7w6LPlYkzUpb8O8xQ1CdmDqFmOXRk5QG2eIj7DmHvleFF88YQ22AryTv2B21Lan3JcH1MOGrLbQO2q1VZ+dC/mecb8RZZ5HGpy+9TK6i+XznTGrBxhmdyvn70gXctUoUPxV0NvNuOnGJXt75n2nfXLNoqs2ZwoaZu7pg/rbJBMfCcJlxaV4bhClhtAi1KGnRyi9oGEW6XCAwiv9URTkIfRhJIqflqjD2JUYkMCoDTGoUEHIYgJH8N3/yqn7l66xOxLszXfA5FHy9UwU5kwlYTDJ3eU6C5gZB5UcN1RuXNE40vGrWxa5h3MWFxfcvWitIG3dykbs+62yrgiy/du4qXL5jhqvsuMPojy7dID1nYoiO2hRF92/7HAnTMFIsNKrJhW6eQbujhfIiFefOW7JD99ETFuPr560Kzke73IDtwABkJmmW4CtsIVYJO40mkL2JuGNDof+Ono+uXzNRas659oaMzjkvzgh0UQgryxc5TqNuBZM0v+mXNx/R56Or/ZQrU57ee0oaETHP0YtzGyreEN8A8PMrN2PDjI58mfFnDd7+Jyoc6k6vt87uCjQ/9Gdu1g9NYFGao7z9/Tsqd81hs3DlITOxZVa8KNJBfUqQdpqsPwkbd4PuPekptKhkXZM0EQt7WvPXR8tBZ4MvziOSRUSzsPxVspjllBMkMKowKqVhR8UarEVmXzKshYTX/5FqFtUOhybO3Xi/Cnh+0a4gMHJ3xmaEBcKcUrY4MjGIlsq5rWqxYQOtUwXYlFq2yLzMMkGQTWq8kXFCy5BOuOT3EHdxnjNJ80xAFK/1RTyBikmav4ygxVMQJp1eq12od6UlQBf1V58+ZSmmTij4j9k5byImtdYr5x31tauZpImPqz5vd4hnGnGlKAgpS4XfJC3qtxZPMKzahx63rAe37lkrPGdqiPZHTlLHHj7sTRnHnMIrMNKpcMACVsfpdRirpk3AEzceir7xfp9X3S11aKqrDi1TFZlJrC6c62kZ6dTchIaRyb4x7D6b6qpx9vppSv3/hMYaAEBve8FcNeoYDXjbevjcXbWM2IL1gI0jDvczjRtow8nyvIN87Xm2xG+WEQ0jofmZ6JizOpbwO3jON5YggVGFQfNXOYwVhD46nZmtYeQ1SVN82FUOrQ2X02tB/XTy9V5nAqtzbKqtwoqp7fjw8YvMZW4AkQBAF1XNsLh8aNdCYbmyv70ojU+WgCLmvViXO81tPn/6cnx89xKpaYeuhlGUOuruPoqI7ERRkKygYRTs9NpZhMv/gkqxMd9pkCmdlzjq9IW+1J9Hd0sdetrF/mNkaGnaQlxflSx8GkYCU+DA6ytg4pgkYf13uJ8N988o+ISczPdLKLJIfSJkiw3rXp1tqkng42bBlFZMaExWw8ifXn2h5H1nTqf/av6JIpQRJDDy/B33k7XyM6ElrBp45Z4rNwWe9/u9Cq5cNoKzbdNTJNFzKfZCfOW08fjUKcPYu3Uollad85o4QqZi4vRNKvQL5drpillW5PmL+++gYXmoW+5XTYY1pxSts4SOsAV1GquQwKgMiBsBh1DH6ix0hA6WwMc70KsuPJ026ypOr+M6BXWiqjLvFaJkMgxfPmslNgjs+FUw4SxbRnyBkaGKhHDEQrffIKtYy3m0rBrhpgOF34c69QdM1TI7mmqxbU6373jB6bvZBylqMmZ8VkW7znt7TtVz2Zzf/o6iFenC7Uw6ZpuXHXec0H2feXdwQqfXuQg+ejjHwVCzMET/jk9c0ZcvI1+u1ecJ8jtvwzR/2ZWw1WiAh5/eJzweu/+OdXUOuQ8jvXcb915sATTMCMeD0PY5p5HWa6rrClMf4xEFmqNonLO+2biLWBNaMyoCo4ktdZjYEqyRqdvH1nictgR1Y2EmfCokNc0qzFVFi3u1UjfN7EJ1NiPZdBDnIXsWjAVcE5JX8DtItj9wmTPmf+puIAW1jwMyVV5pZuKSg9ZD56ybhqt2ztQqJqhtO8vypquEYZ8ERhUGCZTkjIwWFno6QhlLEu0d51XzcA7UWcYKUn7PcG/7kdGoG+fBHbtuJ1eqnQ8ddP1P+K4v0UdilTuxJdj5r079Ltg0qF2Pfz1mAU7x+PBSCfPqRXcgdd6V6jXxJ03cv4uoeKUonddXh/+8Ox3g7pNVFhxWmqR9GMkcX6piaaO5BEaCp1bMry3s+T5+w06snDZeeM66D+djWdTb5kunqzFWqbyyXxwtJw1zFJ/AKCS9LFqjcl8iW2xC0IkaeD5rp/tDw+s+d0tLSEWQJRKuywuOZqPjTSF2UGsd01vAq5ZtYi9PVcMojJxZkXr62ir95aDpbzVt80vvHCZK7TIOTcPWhmqFMtU1E3X5t2MXuMrxl134XdSnZQKayAffukB+EsA1h87C/5y1wv779QMjgell+L8x+cPKZBg2zQz3WyXKQebg2n9t7r+kBfppgARGZYCeKn66OtxyYmR01F6A6izGvCZpBQ0Ltet9JmmS60QaRoUBLcg5nrkd21L599Ehah1tu3z7Z5Fvlrl+SMl6t2sV0qrcyVBXLjLgW5ZMwbvfNMddNcdOd2JEeNyl3NUR273nfjrrdebaAZywvDd/3tr9VC1Dfs6EA8rC9eELKN3vasTetTfzHekI1hiiCadE+Y5q3sfYnzaaQRaxyJRJcbw8ZHmK85Yt8qNU5boj59q/OzWMFvbkhJMdTX7Ts6A2J6rC509f7jum+9z1NN/laeO8rSC5k8x8JAmChPi6mxoy4aMTlXfl94EZnN5rWh6UvhBBMvoTVTbX1EwT/KVGw6VBppmx85JV3s0IJvFhpFBIlHFmvKLZas7/laM+gvbt/aZF0Y6da5Uz1k61/RcBwKtvRBMY+U1PI2UjxbpvkcBI2KewdGxyFAMSGFUYJFCSMzLKI6naegVG1s8axR0bZ8fk7JD8O/zMl16FoNTattVl0HzimuyVSsPIJqR4XR9WMrwTju9euBYPX7cj+BotDSOWLye5JbROzsN9bf7rIzqcBMSvqXDPBa4+dDbee9Q8AM62JRPQqJcbZWE8Z1IzTl8z4M9TkpXLJE3zu7IWLE7XGFWZQpvQXUg5S1e51tRnbGudqgqMnM5Cy6C/LBUHDkq08CTDpkgrRkSc78PCG/TCMSoL08scFUepw4ahDt/1nAOXbhvCbRevxWBHo3aeKmgPm1obmTm4QPjqNw+LVZRNYJQ0SZmRTdIUyvyXt8xXysuaP95w9LxolcmTM0lT72O989XAyLvQ2/hQRUXTVYTqOK5SX7EpW3ScGkacq81PlTboIkyrwop2nnYKLgvtW/1JTO0Yh0PnTZSejyww8v4ddk9K71x0LFhg5H38lWCS5veeR5Q1NEGNzsHRwvAaScMo32MctCOtqQmMXCZpAT6M7DSiXSzn76Y7LmZmEl4skogeoXpdnGfvK1ZSj7BmpTr4eQkScEYR/uguQKIIs1Wf9+M37AQADFz5Pe0yZPi0EBAeJc26RvZsZK/p06csRVOde7h2aRgpPjpZJCWVy3UFqSOj/us+euJi/PDhZzGruxndzTnTy0aBE19hHbXbU3ge2+d04fYHngnMZ1QzEAI5vVZjv9VA8hy9eDLqqrPSdnbz7iVK+ZoYonxR0hIW4nujhlljSUHDiKMqm8HM7uZY5QTWQVvDKEcUp9dM8jsgXgfLBdqO5wbvO5Pfj+xM3LYTVOZUh6AvqBxT/YdPSyQkvY5JmolvTDUL7Q0ng1PUqEInV3oU2maphwbVOZbfYXoOHR9Gl22b4fLP6uXPL7yiVJegOgDmNlAtrNsWO70WX8NQ+ndbDEjDqMIog/V+yRjl3JaqxzFJs/KoqVLLw2mSlmHyTt2qk+5Ov8l3Xg7tJ0KwDwDOXcZkds/CsNWeQ4biKBpUcX396CwOol4T9rxF2ahOJnN+ARgu3zEjNE/lUNiCdIVXI65XVqFt/el9O31lbJzZieH+dlfORjXhFBZkuhMzO0qao732tY/Duw6fg0yG4doj5uCDb11g35cOUVuz95ndvHs49BprI8C6jyhadoSfAwfdAqN/O3Yh3nfUPOmkvKFGb38zzpP3CzjsLRNh+s7mgt+5RT2tAICu5mhRyxhzlCYQQDfUiKNSFhudtu00rctdK8/nxVfeiFmzcHwaRnGXeyEbAaIyYxWnkJfuPalqxAPJbSBGzc15r9cfORcLprRgsNOviRe3tkG3G6SlK9sEZgwYmDBO5kbpnQAAPl1JREFUmmfQvC1Kmw3VMArZyIqySSVj3uQWpXTVeaGTTKtNxTw9DMYYlnnmIaJn5SpLYLI31iGB0RijMpptMhwc5fbujs6a3LuAtxZK1QHSdSdOTSSnjbTMBt2rLi/CNSGL2Spcu59l0MJMRabRJfZkRDEHa+Eumy6I8om7+xHlkRZjENWVgy2Y0hqaRtkkTZDO6gtGeW4iON0zabWEDvLoKCxUIDgaEK4+KkqhrTULKZikiS9sqKkS+j2Qli+oY1WGyZ3EB7wfHUTPm4jPAY+GkUV8n3vx35PPJC1AEOx1ZHvRlpzpmKo2kLe2GVZ4BiKfaNe+aS7etmVIKe8k0XnK3qAJzHVO/XpTFfLmJ4repoN1XVAf4b7n8HICTcJUBEbcPYcMm4/qCIysCpjuEU3MGYb72/GtC9b4fDIp18H1u2AulX+k4xQFt9ZmFSAW8tTXZNE3vsF1TGWOH2kPUPHxettOUOS5qLzv6Hn4P1dsCk33gWMW4Oz1U7F8QLyxZGpcbq73aHArzhXCLELGEiQwKgNonlocRkYKfjV0tHi8pmdegVFYTtUelRhbM8N5jDkiLAnqFndyEUaYKU2aiBslzcTzunPvehy9eHKkcsPKj6LpENcvRGdTblHeHRLBzYmGb27t+ljojtFJD+oFjQCOH126AT/Yu95zPvfT2WXoTsJMhDT2It1ZdPyuK2wpaOaEl6OE4NqHrtuBn16+UZLcf4HO5NJqKjX5hUdve4PrOGAiSl/l8oZEYBR3AWAtyuL4stMZQ7wpsxmmZTrWVOcWODFHyy1EXSzQ0lCNi7ZMV84/KWSvyRth05nWdpbsFHZ78tESXMDKV61vCRtj45ijh11vcrGt6hTZ2W7CBEY6AhZv+4yCchCBFHSxTq1zq1/ZPqfbnUa2CQTHnN6rYSQp78Y3z8fuFX1YM6jmt02VsPflfCci00h3oI147bmuOotJrfWh6Tqb63DlIbPsPtnbN5teH6sGPrLWbWlon8WCBEZjjFD1vBDthErmoMPptZZJmidtQWCk9qxVNZGsjjIb0mmbdjLsVh83lWdykqfoUdLcA4W2rbrjgsHORoyLaUIhKz7MNEh82t8mdFrJznnduHn3Epy5dmpoWq9j00QX1Zp5e78N3bo5/ah4+wjGmM/0wovdtlTN3gTJopjNhpajUL6+DyOz9RTlUp3NBPpJ8KKR1GZSax0+esJifOT4xQBISGQKr0maRdxNCd0opSK8wqZCE/ZnGnUsG1eTxTWHzsIFmwZdx3MaRu7i0tDmvFUQCbMA+CJsAv5+TLbw/Ob5q3GXR8guur5wrR6yfje2Bq71M0Jb2OERPCiVp1CM14dRmCBOyyRNcXNLl6jZiXw1ifLSfj+C76+xtgp3X7YBN75ZzYm5yvjnTdHVXIfrjpwbOLYlqGCUz99fgjtKWtj1yeAtNqyfV6+Huz8Lmyvcct4qXLxlOuqqs/nrSt9HJw0JjErIF87whzYlSsco5w6hgfp1WY+GkK5JmjdqkchvAVAQFIicaTs7K6cTWdNdmCmTtKQmwBzlGyXN3sUKSRdFgyru42aMYfucbq1nqz2Zdzz3jTM7/AkEN6HrIDTuc3DuKoqaidV2RiUVywTNZhUpCIwKx+I7ehcJnj0CI812t2LqeGyc0SFcQMZFzdGu/1jUb3vnvIlo8ZgeEfFwahhZwjggfv9rQqDqc3ot1PtFvpxoZdRUZXDG2qm5BYfnW1YxcSo1ds1UvkV45zQuiZHNwp5W9LS7zXO066OS1pPY3uSIVLKaBrbzlLP8+T1iXy5BC1BfMYIO0Xu9V5PdS42GNN3AMBYqcLBMkIq9DGfippn/O3ekb/w4n4AtSGvNahejESYgM7ubhMejzGVUx3AOiYaRoIncfdkG/PASv5A3KRm3T/isaMKvnW9IA53Z3YyL86bBjKEitDASi5LGGPsfAJaH0VYA/+CcL2SM9QN4CMAj+XM/55yfk1Q90oxqZ6uzSFfPk/BiTMOI6wmMNs/qcv1dmJoWeqCqLEPmYH4SGZBtTVUG4xtr8cxLrxfyi/myGdQmRGkhzZPsILy7lLLxxxLayCaUDMCde9ehsbawwC3FWFYwQwD2bJ6OB//2T6X0AHDscA/efsvvQsvQ3dXxphZdrezDSPB3mIaR1VeotlFRKtvPmsGPUaph5DijW1xddRafPnVZ9Ep5WNzXppVeVN0ofUN59ibp5w2HhtH6GQUBsWrUPBnW92HSJC242UQrR1Y/xvzjbdhCsxgKSL5noHHb1pzFqmbQolxYtkoahW/bNomT+pBTKEh0nYoPI8mpxN4dd4+PYRpEtdU6Gkb5zS3DnaMzv8HORtz7+Iu+NO88bLbPUbTXfYOsbtEFgtHvl4FJ26ZKm509sRkP/32ffsHCuqifF7oxENS3b7zcaXcS+KIhhtzVQYfAaNPMztD8o6wBy3TJoU1iGkac87dyzhdyzhcCuAXA1x2n/2Sdq1RhUampAGGoNqOjhShpOh1AXKfXXuyFtuMlnbZ6oGCSFuDDaKog4oJR868y6BnjCoys56vmJ8DhGDBWqYUMwnY7VaJVDXY2ufwNFdOiQTTg7t06hP86eakv7c27l+Ctwz2uYzVVmcT8G5jUbBPV0T4mKUakRXaywOdHEKL2EVsorHC9ifC1cbKY1tGID+1aCCB8/JKVE1f7kDCHU8PI+VbaxtXgzr3rIucbxQ+hF68yBhP8Zh+JWIysLWYYcwiM8psDKZiw+f2v6Gxkehd5jt+L+Ena9+ApM7ZJmud9CdMEtiLd8lTmJu53VpsN9lGkE33PxJ0oX+lpeKetGcBGz8Jf7KPRxHhlZswTzenjErRZdvdlGyR1cd/Pdy9cg8MXTPLnzcVzJeccoFSRwbzdZlg3b63H5kxqxqdO8c9BLbzZ6M4VUtBFJ05iGkYWLNeqjgUQ7g6dEKKzi14G6/nUMuKIkqbTWcgiGlgqwHFfyRWHzERddbYQklshRyb5PQqMMSN+IXbO68b3fvf3mLUJJ+6aMOqi0oQmFxA+8Hg1zLZ4NdSE5kXFG84sDTtbEyqg6O1zum0zL7vWGlXVNknz/h1joilKZX2jMo0Akd+PyQqOH50UIjma1DAK33E3qdFUDETfgXUPt5y7Cr//6z8j5VsJE8Ni8LnTluPYm+8B4O87BzvFZhgqWO8nlkmaT8MoSBAQsQxJnhlW+B5D5M9KeK9tqjMz7dd5vEELZhMRGjlXew/S5ygyldMgSKtFFKSAu87rv12le+XuUb+6KvgqHc2+qH4eZbz/zfPR0lAd6AxdlaD2pJJn4PWB18nLtM555wVxHl9Qs/Fq/SzoacVv/vIP3/3PndyCZmd/IGmjFjp9akdTrXJaLTxVCJuvWxpGKpHncui7JWFgqfAzlzTF8GG0FsAznPM/Oo4NMMb+L2PsbsbYWtmFjLGzGGP3M8buf+6555KvabFRbJDednjLuatwyNyCL43WhmrbzrVUUt+xwMFRbveSOh2jbCEVWcMo/9Pb/VjZCScl1rX5k435QeCYJcFhq1XaC4Nj0hNjiPv3ty6KfK0OUQU+1j3q+ekxuGj37CaHmTVZLJT4QCgVo9oDdI4oXZc1Jb5s+wyfLzDJBUF/atVD6CPHY3rhO695j0HCP6dDzNitUJKB87AJAVUxxydRSdbzX9LXpq3ZJWLsTxGTY5kkTHJcrEVZHI04n0laQNrIGkYONSaXM1mINIzMtbT7rtpiJB+d2y48Tr9/KaVFvMo8RSGfMO3dqO9S9/VYbfNdh89OLDy6N9swH0X+IB0BFWOuH9FwPOyV08b7oo7FJYmhJsr4lXGoGMmeaGC+klM6zWZaR06A1FwX4IfPUQcOLtz0cvrbCnoSXzpzRWL9u09bMeSdjIzmNFnDNry8Qm0ySfMTS2DEGLuTMfZ7wb8jHMmOA/Alx99PA+jlnC8CsBfAFxljwhiknPOPc86HOefDHR0CJ6hjlLPWFSIRHTp/Imo9tsdL+tpw04lLsG4o90z+/a0LcdvFfhXuBT2tidZzrDES0SRNRnSTNLFmhrDDk9SzoaYKD1+3A5dtnxF4L6oTUZHvAV2ihMuNQtxFqb3QUJqUOU3SvLvCejNBb7VlxYcJtERni7n5UQinbk2SzBQuzMUxuEdbwETH285y80Lxt2uXa2tdRX8mQ51NOH3NAD524uLwxIpIPxnHiYjdWckQ3VOQEOHxG3a6/pa+I5ISGcek4N2ydAvy9ReGz+l14HouWt2dwSuc2h0sU1isyCKRxaFew/QoiIKvPZXayZ9nKRZb3r7b1PMN1ERznMpkGJ648VCcutq9ybG0vw3f25PbQw8aInyliDYWuDuPsGiSOhqkVspibADozVDNonN3cj9Fjk1gr1lnTBWjaw6dhc+fHu4n8L1HzsPnT1+Gwc7GwPyczulF7a+5rhrfvXANgOC6r5w2PrROUfE206X9bYHpD45E28AkkzQ/saaAnPMtnPO5gn/fAgDGWBWAowH8j+Oa/ZzzF/K//xLAnwAMxanHWGNpf0Ey+5HjF0s7orBFx4ahyhGymeDgaGHqY2I3PSwqhQynnN9J0GJH1BTqqrNwRlyJCmMOvxAJzg/OWDOAE1f0xs4nbh3tiVNCI4AsjK49qcgXHLYbpSNziBKdIyrWgk13gI6yXykTZB63rMeXFgDWTJ+AE5b34oaj58lrEaP9ZEIWUSZ8GWQyDO84bLZb7TxmfyUWMnLjGkalJmhRJF38JGCOROQIMuWJCk9Cwyggr6jjjfM6p5mYU/htbbKMH1cTrRDEb6NL+9tw3ZFzfcczGn2ZN61LYKRQw+df3h+aJk5wmLhR0oIIc7TtfHzHLOnB7EnC/XMXKoKa3JifkCDFgIaR89oDDn9mhfPquR+3rDBvDBTuek5ecchMQRr/73E2eJw+yUy+Dw7gjLVTsXZ6+DqvviYrTScT3qbVxMp6h9kMw5/etxPzJgdr2I/YGu964g4tDSOtnMuXpH0YbQHwMOf8KesAY6wDwIuc8xHG2FQA0wE8lnA9Uom3Q8xmGEZGeaKNr1IadhScTq9Lan7hnVzlDwdLvOUTHp0BNLRqCS4arzlstpF8Ipuk5X9agg4VIYvrG1acRP3n8YtcDl/tyz2CINW7EGm6qJDUfMBesOUH6CTnHaKJ/tU7Z+FMh5amk+psBu89ah5+/MizidQnbBGlu4gtVn+t8l0b6RNj55BDZTIrWnCYcNztqofR3CqP6kxG2BfGwTYpiOX0WmOxELFNSTWM7P8Bve0NuPHoedgy2+2nrph89ZxVAIBP/MQ9TdfzYeTWlHI5gFbI588vvKpQRng+IoGVO4+IcweFMVuWdZTNHG9W7zxsFs7971/h2X0Fwdr+g6MYaEzGj4xXmzouBwOcEao8nr1bh/DhHz7qOqZSt67m4Odj3eeo5pzMnUdB4NvRVBecWANT8ypnPs77k2Uf9g0lTUFbiyObkUegs7C0qnZJNhEL+br7KN3xI6XyNaMkrWS+C25zNABYB+C3jLHfAPgagHM45/7YiRWIHZ0pwQ+xAtp0ZA66nF7nBqG3bdFXfnvPEXPQN77Bd/wsySI2DK9/omL7qco5dCtqkbGIbZKW/w5HdD0qh3Dptlxbqspm0ODzFyBXW5ahU7uimqTZUQLdA3AYYa/t8u3+3cAo9ubu6/21i6ORFxbVKEwDKSpxewTZ9c45Uxo0jLS+bUFSnXuY2pGbaJ67Plq/TYSzfKp5PxcjBjZ9ihFNz7kgkWkYMQC7lvViQkILfx38fVaMHXjNxysTqui+Yi7ZWIvbG9v5CuqjM544n3FQnbzlLOlrx+0etxT/fO0ALtw0XblsIOcCw1GK/dvk1nos7m21/84E+NOMwhsHRRto6te7nGVrlKs+1wqXGElPsVxwjw/tWogLNw260tmCN7VqJIvThxHn0mcTpjGXND7XDSHV6GyuwxM3HoojFk7Wyte7aRBkMcIYq4i1daIaRpzzUwTHbgFwS5LllgsynyW6Ex1ydG2GUYfhLmMMezbrDbYWJ63sx0kr+33HVV+TV9JtYfVX7gEnh5a9ewRMal4lTVwtAuseVXb+3D6M4rFm+gR869d/Q111XjMnYj6q/UFSr/KgRwVYdVIWVp010yfYv1sC2ai+tXT6zLPWTcXHHbvrezYN4gv3PinKNbTt6JqkmXxHPe3yaGyicjjcz8mEDyNT9xP129DRSm+pr8YTNx4qKLsSpobF4WMnLsFjz72CumozfnUAh9PrGEIfLX8uEYtxmuy6NIyY/pyuFG1Sp4pe592uOYxCRrLNG8uR89mKQl3pIjiGBklomQHCJG+d1MfK8Jq+9NoBbb+RHzl+MW797a1WbezjN+9egrmTW9B/xa2u8uOsPZyXek3SthrQqFOpmzhqnzxdlLvNmaQxW2Bh6ks1bjLGudAk7RMnDXuTlRSvtqLpNUlBQ9V9vK5KPkalf1VkhqRN0ggNrImO18m1SSqlYUfBqWGk2wl99ITFmB7kUE4jTyvZqGdypTIBFhZh8KWnUV40vbMRf3z2ZfvvuJvDVRE1jMKeTdgE5v1vmY+LNk83bqIBFHeQL5ikJVfG3ZdtzJflKFfj+qA34X1NV+2c5RIY7d02A3u3zRBeG+b+KimBa1i2P718I5rr5RFS1EJbp/DjD0BU3WJojhDqjKutwrwpwT4odLGjXcbRMNIySYtYhqMtbprZKcwzarf9udPCHeHGxd6sCkjz7QtW442Do777cfYlcT7JqmzGFuq+fmDEPn7dEXOE6ZdPzTnj3bXM7SuxtaEaT74YP8Jq4Lgi82EUxSRNoZr/fO0AAOCLZyzHn55/RbsMEVceMhN//cdreOy5XH5xelPn8+hpL2jk/+LqLWiur8J7b30IQITno1GpsJz1tJwkxwPLjz4xS3JKx3nBDM+KwO0tt2QmaZ5NN1PV8N6P1+dRmPA1rT6fTFJmcU/GHkNdBSGDtUAVNczv7VmLO/f6I6GpcOTCSdEqV2GMjI7aHbjuvGHnvImY3tUUmCYoT2f0Apm6tLXrqR2a20CXWpDmx84qFnu3DuFLZ65wHesbPw4f2rXQ/jtsd3hiS7AduXX9iEL/L3q2tumg51zYgFJblbXNYFTQGZ+KuQM9YguMrH5MrWy9qDs5ClEN4030XfWIlFNuwhEWBU3HUaxJetob0BIkMFKY7Jrw/1M8NXZxSeWgIUnEw9ZiifGqdYTdUduUUzgxvrHWNnlgzK+Ro8u6IgQ8Uelz509pxXB/e+AiTyU4gpI/QUc2uwUa3l8/bxUmt9bjiRsPxYqp7ihOnzhpGNe+aY5LcFHuvJQXGK0anIDdK/qM5Hn2+ml4zxFzHc7qo39k1sb4ppmdLpPLjqZa1FZlEzOzdqL6fdk+jCLcb1D/IJx/lHCIco6aYZpxpaqmt1zjGkYQa6gGKnJUyLSCNIxKCAPwjfNW4+X9BwEUOqVagepbUOSEsE6v1xlNh5DS2z4OTzyfc66YxMIiaLF020VrfZJ772u1FmyiuiW9/ixoOxW/Z6zOMhzIS28sM8GFPa0YGeX43V//6Zrcc86RYcGz/e9ftBYL3/MDADnNiw/e+Qd8/Vd/tR+4Zfo3qqBhFCTcSJPpiqiLSEpoETVKWrzdSs30CTXjMA0jaxKi6uhU2bywCN9lnDDlppiRF8qvV4gMI4IERmOfgsA6+ruWtZPFfa2+Y1FL8davIEwpfM2G3egZRee+gwIzqLwnFW3fsD5wcW+b9FxXcx1OXtUfWkZoHfI31je+Abecu0rpGi75XaWcID5/xnLF3PRhMQWaQC5yFyCOkOZEtwQdh9xhAhun+MT9t+g68dm4Q45cMy1evv6C3Hcrs7YotSaNtz6mhnTbFYiloeoVGIWYTae4qzZGCqaAlc242ip0Nbs1HnTtjgkzXLJtyKGxYC7fgrNqeZqqbAbVnm1Nr72/pb0gGpiCdlWN3Iu9w2IgL03uuXKz79g3z1+Nc9ZPA+Dv2MPmn04NpJ72BjTUuAeCbP49aJukhUxYS2nSU8zBzBK0ZTPuATgJ4moTiIR6cV6TN9Kd7HzakFXLOTkzEzky3vUzupvw63duxTHDU4Tnb7t4raMsf2EmTNKi+Bwhisdofv0Z513Lru1syjlQdYa5jx4lzX3dJ04exrqhDlRnC2G407Tp4EVHCypIK0Al3PVBj7rvx05cjJ9dsSm8kiEct6wXF24ajJ2PvdmX/zmxpc7Wmgl7PNLNg4ALVVpckIAsiG+ctwq37lkTmMYqP+jern3THHz6lKXS85avRu+7tcsowlgZ9n1V5eeC9TXRfayZuo//783z8Mf3HmL/bbxn8PgwgkRgZFOiuUxixXry9fbPgU6vgYqQGJGGUZH59gWr8ab//BkAeUeiKzAK65CcZ62oJKet7tcqoxJwCmyS2LF3O5Bl+MHbxCaGcqfXloaRZrl6yYUZiHwPBJHNMGNRxqyJ11GL3FEORNFwGGO+Ae5dh892TUrC7sB6ziNKE2Hz7aS5Lmc6tLCnFT/94/PSdGEqw6XCem7WgKu+a5r7qWdqlyMtmiNWPWSTi0KUNLMktYvpPJyWZ9zaUCM91+44J6ptqU1qieThgnFBl2I4vfYKpTbO6MTGGZ35PENUFVOAKafXi3pbcevvng683quF0t1Sj8mtbif+Ud7DDUfP079IAbGpeiJFGWdRXtD06LP7pGlUBJphGluWE+EwDSNdbHM5hblZ2FxjaX8bLtk6hCX9bTj+E/fGqk9cMoz5NpWTIufDSOyeo9Rdkve9JjUv8W9EBwiMyuXjjgkJjIrM/CmtaKmvth3SiTDt9Nr5gVs7ZIQYmYd8Ezj7n/7xDVJ/NVbfc9baqfjlk/8Pb13a46qTV0ACBHfiJjoz0URPxn1Xb0ZTbTXqa7J2VI24PHL9DlR7XoqlyeJ8Hpxz32T/1NUDrr9lz8N6htaYrLJz6oqSZk9U4jGptR7fvXANGmursOFffxyaXm1iVLxh3tYwCtiRERFF+GabcTjVyE1ISCNeZTU92cSuVD6MTGBCOyepaVVzXZW9G2yXJdS2NKthRKSPgilF9DzC/HU5m0BYMZNb6/HXf7zmOx64AMn/TJNJmjzMdjg++Zfj1jfN7MT1eQfHMvZ7wq6Lnlwpl2zecUinm4kUJS0k/6TXryoaRmFYJj4HQhp51DKUTNLEVzryYLhw83Q8/PeXlPOU5+b/2/s9DHU14v1vWaBUV+NzOsaEdfOOmUlGFFTB+w6Sauve+U5VyHw2zdqgpiDbpxRCJmmlI0lfPeNqnKFzg6TVuZ/tjTX4zKnL7B11a4LplJtMacvtsq2elgs5npQvk4ImR3jazqa6WCq8Imqrsj5BkCx8clgd/QO4eCdB3yTNHHMntxjtB4q58PBpGCW4wra1rDSv89qrm6KgYSQTGNlTbaPlxm17Ko4tM4xhYEI6/eH96h1bcd9Vm0u7aiRSgWxc0EHnWmssf/+b5wujc/1AEqwkqIwt+bDiDbXxx9Gkel+dhZq323OOuSrP2hs5NL0b+voVk43NosOWX6RS33+Y6bUKNVnLJM2whpFGWv0AbPoPXkcD5qMnLMHCnlbtMmR898I1+N6eteEJPXBwqYaRRanaoLdc806vc3j7paBNBIbK2EgiDaMSImt/JDAqHQWpuvm8m+vVPjcrUkeHI3IE4PSFVKjctI5G3HPlJjz70n6pWreJWynsoMXLbd1QB6Z3NuKr9/8ldp0sgY63SnGjOVk7CU6B0W/etQ0Lrr3Dl7akqucaA1RvEaO/jNg+jHRNa/XLGo34wQYlj/P+rMmLrA+PYnZXDITfDHc/iwzLOYw3bUJgAlu7yPFcS+Ggnyg9MmetOuhca6U8Nq8J7KWhRjzuBwlKrn3THOzZNN02T04jOt+X18ze+XiVBEYeDSPR+0mTWUhSVbE2YUL9JRooSxR8xyIsuIMK1VW5TEw7vbZQeQaqWiFxxuugtqBjTeLNRqVOcye3KOcP7h7w5XP+0k5evG3f1KdW0Jpzb3ja5xU2+cc6JJkoAWGNy7RJGqFOmFQ9Ds4OJyj7s9dNw6dOGcbW/C6jhcw3w8SW+sQWwHbZhvzlfO60ZXjHYbPjVwiOaAaMuZ9tmE+vkHuwnq9z56+lvloY9cttklaaUUOl2I6mWjx+w87kK4PCN2T58UlyehFXPVoYJSVybQrafzUSDaOspl8nVeI2PZnPFu/krK46i6Y4i9gifiJJfY7Ob37DjOTDlxO6Jj7xNYzCzA+cRG1nQVEkq7MZdLfUSc87qanKYNPMTun5pOaTOsJvnxmJ43cVp9crp44PLyO8GonhFTzoCNOc14YJMIL2R0z3dz2Bm0zWHCn6SGa99wNSp9fR8tWZh4m0u0zPpX1RxvI/H7l+h5ZPIp9JWoIzK+dr9fkwGqMmacsHcv59p07IuQrxvrewqL9p2wRMApJMlICwhiVbbOhSKVJPk5jSpIlDNsOwaWaX1HZY1G8FtSkTO+1W5Jm0OL4F3E6vnWZPYR17WJhSa6Fhyml3XLqaa7F36xCAeILMYrXpkSJGSUNEQWaUJ6HiN0LZ6XWZzC6c95ySzyE1fOzExagLCbVLFJ9RycaKDmFjiJOo46uOY+0g/nD9IZjYUi89v3FGJy7fMcNIWU6sYBQq2qs+p9dOzUWF6e71R811/Z2iaYgLkQ+jsG4zQpA0YYtrbaixI76ZGutnT2wWl28ge2udE0foFIiSilHyGkYyxP2GekHeOv3i6i0xKySukbcttecjRM6f0hqvvIh4+3VTbf3EFX3437dvxLwpOa0s76ZBUH9dKdrMZJJWQmRNTPcDqIymWhx0nDsDwCX5hbwKzjyjmd+ET4SFpww0EMuHQJrMJS3BhLcjrw6pY9gOhbVY8E5kQgUGwacjw8DsSXmaBHYyLA1zXR9G3lub0dWEzuZaceI8hd0uFmlSJ9qlE/W/Hz5uEeZMEk+eRfWR7Rz6nL8aohgTFhM7msWaWCX5mZSJrK9isU3SYgxVzu/3kycPB6ZNQsPIJJkMw3kbBvH+2x4xmm9HUy0+c+pSdDQF99GAf2x09gMqGkZe8yixSVpoNsmhoHVhonphY+nZ66fhwz981EBJasTpC6e01eO01QM4bpnYlLNQRrRClIKBKOalO/Ydt6wHX7ov53YhSLsu6JguKt+hiIl5Tcbx42rw/L79ANzPxdtNTe1oxHcuWIMZ3U2RyotLYvNsxjClrSD81vFhBFSG02sSGKWIL565HD96+NlE8v7OBWtw7+MvJJL3WKLg3FmtW7pw83St/L92zkq85WP3RFo4yXz2mGRmdxMW9bbhS/c96Tpu2Zmb0n4zQcG5qXuRX53v6I9cOAl7t+rvrMqcXufeWfigYHpRzFjhnTs1GqIMTx1NteA89z6v2jkzNH37uBq8+MobWmUU3ku8tnL728TOYp0Ead0FomFOAQCHL5ikkCWzvxNvxC6LgqPP8phcuHbKy6DK1kK/py3YTNcM6RfeViJ2/xNHw8ixu7x5VldASv0NvhldTXjkmX2xfe0VG9Hnv2GG3BTOiVdQ7vJhFOE5iE2ySvc843SNToFIWB9beH5hWtTJUhhvo995JsPwzsPl7gks588zu8M3apzo3Lu202vFNnbD0fNtgVHcTT7Z5aaG43PWT8PAhEYcMrcbywbacc9jL2D3ij78x11/BCCuv6WFUwqK9Zl7BdlBJs6Mlcf8KC4kMCoh3oa/atoErMpHuzLNvCktJf3Iy4VRgcq0KRhjGFcb/ZMrLI79lQvqq3Tu5baLc4t0n8DoYDwNoy+ftSLSdUH0j89FbJo7yd2urUXjlLYG9I73q8uHPQ/bJE0yAnQ01eK5/E5MsRA5U9bVhgP01ZbveNs6PPPS61rXWIK2Kk1/PV7HqCok8b3GyaogWBXnUlude3/eqD+xSWgSde2b5mLLv90NwMyEKOnJXtu4GnzsxCVYNtBeMjXxDTM68ONHnitJ2WOJX1y9Ba/sP4gN//pjreu8psVRCPdX4fBdp5n3iC1QLy+BURy8UbVcAiMNf1F2fikV1hZM0tTrp9Ovip6fq3z1rGJhPf8kzZSPWDgZi3vbQnwpybGeUdBnJtJeMq0lJrckUbv++OW9+Novn8LqQffa0JSAoiqbwaHzJwLImZl+5eyVrvM6Aq9ZE5vx8N9fMlMxCcUSDHsF2aZMiMsZEhiVgDLbWKoogoQyURHbBevno+KQO46662PvkztFthwT6jjpc7JCwWmlLuuGOnDbxWsxo6sJ3/ltIUKcpd0hi74h92HknsiPemdD+ct+evlGzHzHbfKKJfB9j8uHV07M3l/ChMZa21eFKnY71Rxgo3wT9o5rShYQYd+JZVqRxkhjXjiAwc5GrBmcgP999Hlf21swpQVHLZqMd3/nwdJUUMKOud0A/JGVisV/nTSMwau/X5KyxxIdTbVoqstNUXW+7oIQOXqfoKMdqVuMLVCPIChx8vHdS/Dki6/GyqNY+J+R0yRN/zmkbe0WZHYUZlKlN6JHM+82jY7D8zhEERb5XQ7IH4Zq9Wd1N+OklX04bfWAdn3iriUW97bhiRsP9R0XmUDdePS8yKZpMnSq/709a4yWXUq8guyw7roCFIxIYEQQ3c11mJ/XvgrbwYlLnAFW11zOQnXiHLTAP5D3ei1z5lsqROrKVh1lWhxhNuUyDaOwO79i50xc/Y3fh6SKhhWa2SfESiFeDSPVkdR6bzrOxnlBYqRFkIApzrc/2JmLsHHmuqnC85aGmGmBkazKNx49L37ektf4rQtyk0MdgVExe4/koqQFIzNHJJLjv09fjhM/eS8Ap0lschpGTnTb2cH8WBp3IbltTnes60Us7GnFA3/7Z2CammwGnzwl2K/TbRevdf1tO70WBCmI8hxML4rjYmkjRBlXnNMM7jru72lUI1QlvYFSGBPSOx9ReQKqU41MhuE9R8wNTyiqRxEHvV3Leo3nqfN9ltIs1DTeMSBoE4GxaD40yw0SGJWUsfNxlTM/v2qz/buJ3UkZDPEG2KC6JR11yco+TT6MZFSHaBiFYU3+RiWXix71dy5Yg+ldjYkJjBrzpoyuyWXCws2oRF2w9baP0y7L+p6iLr6sx7ln83TbZj/qZJuxnM8n0W6ghRXiuljaL7oTyN+8axueeP4VHPGRn9nHrP6m2NptcUn6s0jbd1epLB9ox5rpBXMNq9+O4yNIp+/S7S9GRjwC9RTxzfNXh6Y5dXU/1k7vCEzj3cix7lQk8FB9DtvndKGhpgo3vnmezwl2EGesGcB//e/jyumjYGmLHQzwMymNhhZhTiibnxarT7LNx1M4JFh1Y7YQT441bz5heS/uffxFPPrsy8bn/r5ox4H1Uc+3WM8+hd1UIJZWaly8c8qgpU+ZPaLIkMAopRw2fyKmdTSWuhoVh+oOTlyiDEp29BfBpZYGyuQ2f3jduPfirGpYBLI0UB3iWDjseViaVj6n15q7aiYHdMv3lcyvUprwLthUa1xTlcHqwfFYPqBhvhjxe7XbdP76vVuHbIFRkhQ0jMy+R1OT3Jb6at+EK+N5VnEYCzuQZfAJjjlk7eaBa7f7/OoVTGKjl5ekhtGIXb/y/xZUCYpMqvocbt4drNUk45rDZuOaw+TOlU1gCRgt7TGdN6slJMj/DM2/WCZpyRZjBJXvs646a4eLJ9ykMTLveRumYfMsv8P9uy5Zj9b6aiNl+DWMwp5DOXwN8SCBUUr5z+MXx87juGW9uP2BZ3B8AmqKYxVVjYXWhmr849UD+vnH6FMscyRR3WZ0N+E/j1+E9UP+nb84/f3sic0YV1PoJqL6MCoWHComaeIHYr2aKnvy5zVJC7KF5/Z1Ry4Mj6ilA+el82EUBWvSHMWZ6RfO0HOOLoq6o0JQ8iTnR9bOeKn860Th+iPn4l9ufwSrBs37IUuSpIVT6ZtGVx6iIBJRTbedaGkYaZbjM9ktEh8+bhFaDC2mdMl4Ng/SuAiNgxVRqRDJ1n9/SrfsjJgmOD0aEim3WL78Ck7MUzgfYa4fvmfy8ys3Y8UNdwEo3gaxk3Jr+Wn8VC/fIY7wa1LJwivIDuqz0viMkoAERiUkbiOT9dW97Q3YvaIPXc11+P5Fa8WJCCFBWjxO7r5sI14/MKKVN0fBtGhqh775zXB/GwBg62xxmN/D5osFFUGTiI68Q+Pu5jrh+W+ev9o1eU6bDyMR1o6zTMPIup3D8pEhvJM7Syg2IrFJk313VdkMfvPObbZwxySW0M4pw+rLR4Cb1OrXKislV+6chUu/+hvMmZQzS0hyUhk3SlqxfTBYbdN0lLQkv8opbQ340K5FCZaQLIwBd1+6ES+8UtzIhkR8dL7rCY01WD04AT979AU8//L+WEIJb0jlIHRLsTYidBxrm+DwBfE2Mox04/k85k5uMZBZerDmSJYZvJ6GUQSTtJASEteQz/9Mo7zIghUkRi66WwpzXdH8Ielnt3tlHz79sydc/RPzCFRVKJawbixoBZsgbBMhzd+CKUhgNAb5yeUbS12FsqWptgrP7dsfqibdUl8dabeuf8I4fObUpVja36597ZxJLYH+UaLwliVTUF+Txc55E4XnvWNF2n0YMRQm+9IoaYzh/mu2SN+fFfp8v0cLJEgN25rAtTSY38FlDGioyWK4r83lTPmE5X0YmNCI1SnT/Fja3467L9uIV/YfBJBs6N0z107Fjx5+Fmund2D+lFZ8/f8+JW3LThLxUaaQZW1CTq+TIIkJaTGnnhmW07I9atFk9I5vQO94ecSdTTP96u1EelBpN/dfsxUA8OQLr+Lnj70Qy+m1qiynoSaLKw4R73Y7+crZK/HFe/+Mb/76b9gw1IFv/vpv2D5HvPEzFvGacx+zZAou/9pvS1gjs9haySN+AURYLxp2/uSVffjsPX9WSlss0uz0utGjdRjow8hKU0ShyDsPm42rds6K1T8BlSGgSBNBPvEYS8+3mSQkMCohJLdNH589bRnuePAZ7VDiKljve8OM4i5OnP3cppmd+OHDz9p/ZzJMa+exnEzSgvzEiN6v17G312zoP3Ytwod/9Cgaqv0aRElOnDjPTWi+du4q1/FMhrmcvaaNYszB5k5uwW/fvR1A7p3++p3btK4v9qTLFhgZNkmL+qzfffhsTEhZxCFTMMZwg0KUOH0hfCVMDcuXMOGgCqoaRv/79k1Kvk+WDbTjBw/+HQAwa2Iz/j0hjb2bTliMnz76fCJ5x8GrETPWtBZsDaPA3RGJKbw0Slr+KsezUg10EXT+tovX4oG/voRLvvqb4EyC8vfUJ01Y78Jqc0Gahi6TtCIFEWGMGdHUT+Gjj8RNJyzG+ATWW6YJUiIoliloqSGBEUE46GlvwOlrBhLJOw0d/KdOWQoA6L/i1kjXl5PT66haHLV5gZDXh9GW2V3YIjEHJOSYFKZNaKxN3LQo6oRRZdKQlNPrqJyyOpm+TsZYWicGLXo3z+zEXQ7BPBGNUk3E4+7+l4pD5k3EIQoalrGI8WiKIWAohZ+mKjtQhjXnUH9IzvFxqKtJKa2s61EZa2d2N2Nmd3M8gZHtwyhyFkUjaMwpPE+G1w/mXEzUCTYE00jUZ3/Luauw73V9/6tJkXh/ZYiwqJup9OdlGBIYEUTCFAai0ghboizSGMtrtniOp90kDXBESZP4IPKybU4XPvN/nsCKqTnTrtoIQrGoC5sPHLMgdOJWrovsJBZ791y5KfFJan2CE8aabAZTJ4zDns3TEysjLtaObFUZfOulQKX93bx7iXE/VUTxCHNIPfaXBn5mdueEGXMm6fsfqs4yLB9oxxlrp4YnjsFNJywuiX8kyx+VyCQtrLFY/ck566fZcxB5YrX6JC1ondCY06pLwl+jjDPXDuATP31c/QKFR+DU2Np/INdfl2qerkvUjbglfW2GazJ22b2iD0+++Cru/sNzwRpGZTpH14UERiXElFpupTTWcuWl13K+XJrrShOhJAoZxjDCC0PSeRum4au/fMoXcjstOD+BgbxD8S2z1LSBVk2b4DJL8YZpViHq4P3mJVNi7fSVAyYFPKZMIoP8UYkiL5mCMYYfXrohgXzN5dU3vgHnb5yGY4d7zGWaZyypbgfdSVU2QwK3MiaJkPflboa1cWYnfnjJekyNEImIMYb/OXtlArVyUypthSrbDF7u9FquFZRjcps7eIVl6tjhMBm2fe4omLclySXbZqB/wjhsn9NdnAIBXH3obFx96Gzp+W+ct8o1P7Cet8pXx4CSahjp9AzHLevBl+77S+LrieuOnIsv/PzPiZZhkokt4sA9cbjuyLn43D1P4O4/PEebCCCBUUkwFU61pz03wDSVkSCiEnkpr/7ZXKKQtlEWaQ01Wex7/aAdReLyHTNx2fYZxie964c6jOTj7Kwnt9bj99dux7iaaAN/FA0jwo9lp3/cst4S18TPlPzkfIdgwluO77+uytwklzGGy7aHO/IlcjTVVmFf3sE7kQyiYactgQADXvpj+kJyctSiyfj4Tx7DtiIusk0TRVgk42vnrMSfnnvZWH6lxNLK9JqxO5EJc2Sh3Y9YmPMtedj8ifiX2x9xnQsTPqlM0245dxU6I/qvq6vO4oTlfa5jxy/vxRfvfTJSfiZY1CvWnAmas46OFjTCXnujdAKjk1b24R3fegBdkmjFTq47Yi5mTWzG8QnPq3av6MPuFX3hCVPAXZesx3gFX3JRGLGjWgb5MCoP88y4kMCoBExorMXzL78R2+bxXYfPwYYZnVjY02qmYkQivPRaXmBUIu0c2Xj5liVTpNd847xVuPOhZ1HrWIgmsUP6Hwk5//RGytBBxezuzr3rkc0wXPilXwEIFso11VVh3+vyBeX73zLfVvEeS1RlM3jk+h2oLnL4aBUmtsiFilHbeVxHu3HwOo0c6mrEqUX2T6REeStZCPnJ5Rvx8v6DWPv+H5W6KhXDLeeuRE9bst/bz67YZHTMnjWx2XiU03JmuL8dwxGixaaRoChp4X2e2C8RYwxHLprsThnimLmhOouhrka8bctQaJ1VTJNmTmzCg0+/pKTN8r6j5uF9R4UHGSgWKg7CLY35lvpqvH6gdAKj3Sv7sXtlv1LaqmwGJymmrRSmGRRke7EERpZQeM+mQduKwabMtUdVIYFRCehuqcPDf9+HF15+I1Y+ddXZoqqEEtF4KS8sKJ2GkZ+wietgZxMGO4MdMKYJk921isBgsNPcAJWE6U9aqDWo+WKaOEJFL586ZRhrp5vRlgOA7164Bj9/7AXl9M5ITeNqsrjjbeuN1SWMT5w0jIEJiov3MbAL572FtnE1aEtod7PSkZn6LulLXtAwubU+PBFBoKB9sG5oAl59YwRv3+HQ0FT0YRS06XTrnjVorqvG48+/Epg2k2FG+/73HTUPu5b2lnQzJDISzS0nJ67oA2MMxy/vxQfu+AMAoC6GhvGezdOxLsWRawl9ChpGub/3bpshTDcGpjahpG/rtwKwFhaNKfUHQ5jl8u0zkGFAa4kERgRBJEd9dRabZnbF8q9kOZS1mDu5RctBrFMd+4H37Ihcjyhsnd0VKly+c+86nLFmAM31Y2fMq5BNxVSQNt9XlrC5TIOppY6GiObjacHyYZTNMHxo1yJMcggbT17VDwDoahabf6lowsyZ1IKe9oLQplh9T111FssGylMLLMiv5AUbBzF3cjOqshmcvKof1dkM9h/M+Z+qj9EW924dGjNac0QOS7MoyLdpW0N1ySxIikmsO2SMHQPg3QBmAVjGOb/fce5KAKcDGAGwh3N+e/74EgCfAVAP4HsALuKVEI/OwWmr+7G0vw3zp7SWuipEEdi1rBe7SujHJY3ONpdPHY8fPPgMqqvM1G3LrC5sn9OFq3bOMpKfxZrBCZg/JV7UlYktddj3+suR/QWosn1OF25/4JlEyxjL7JjTjede3q91zU8v32jESfbXz1uFV/aPRL6+pb4aqwfH46hFcjPTUjLY2YRrDpM7LC0nKmy6UlKq8uasp69Nl3nlF89YgTse/DtaG0izzAR3XbIeT77waqmrERlLw0gUGPHkVf220EiEtXGsEp2Teh51CoI4/xzz0u0zcOl2saaISX+ARPmze2Ufnv7n6zhvw6A0zWdOXVbEGpWOuDPd3wM4GsDNzoOMsdkAdgGYA2ASgDsZY0Oc8xEANwE4C8DPkRMY7QDw/Zj1KCsYYyQsIopG+sRFOd9Ff/l/r6KhxoxUvr4mi5t3DxvJCwCW9bdj7fQJuDBG+PPT1gzgx488h/8+fTl+9eQ/sH2OWtQ2i5a8RtoxAb6mnHz0hCV2lBZCn4/tXqJ9jXPXNw4NNVWxvoVMhuELZ6wwUhdCjRTK4ccc2Qwrmt+fczdMw00//pNS2t7xDYmHiK8kJrbUY2JL+ZoAWn5E1w/pmyNdsm0IHU21OHzBpNC0JKxWR8cBOJDzMfrS6weNRUg8YXkvvlBCJ+CEGeqqs3jn4WNjsysusVZrnPOHAKEE9wgAX+ac7wfwOGPsUQDLGGNPAGjmnN+Tv+5zAI5EhQmMCKKYWJ9nkJf/JFnc2+o7Vl+TxVBXen0kfeUctRDAHXlnwyJ11WkdjfjZFZsAADvm6vsaG1dbhUeu36HkhBvIvd9shnbHCCJJrto5C/teP4jlA+N959IYEZBQ4+07ZuKuh57BH54ZG5G7iOIxZ1ILHr5uRySHyQ01VThn/TSltNY8o4XcGyijair+3QvX4sGnXzJW7nuPmof3psgJOEHEJSmju8nIaRBZPJU/diD/u/e4EMbYWchpI6G3lyZiBBEFxhj2bBosSTjfB67dHsu3S9r54FsX4o4HnsGM7mSEX2l2Gk0Qlcj0riZ87dxVvuMUAav8+db5a+xoSWOdT548XBGhoItFMaJrrZw6HlfvnIVjl47dQBmmaGuoxgUbB3HkonDNLSCnNViWzr0JokiECowYY3cCEK00r+acf0t2meAYDzguhHP+cQAfB4Dh4WEa2ggiIjLP/kljwr9LmmltqKHJG0EQxBigviYby+ltObF5lp6JNFF6GGM4cx2ZQqrAGJP6KSIIQp/Q1RznfEuEfJ8C4FxFTQHwt/zxKYLjBEEQBEEQBEEQBEEQREpIylbk2wB2McZqGWMDAKYDuI9z/jSAfYyxFSzn+OgkADItJYIgCIIgCIIgCIIgCKIExBIYMcaOYow9BWAlgFsZY7cDAOf8AQBfAfAggNsAnJ+PkAYA5wL4LwCPAvgTyOE1QRAEQRAEQRAEQRBEqmDlEqZxeHiY33///aWuBkEQBEEQBEEQBEEQxJiBMfZLzvmw9/jYDV9EEARBEARBEARBEARBRIIERgRBEARBEARBEARBEIQLEhgRBEEQBEEQBEEQBEEQLkhgRBAEQRAEQRAEQRAEQbgggRFBEARBEARBEARBEAThggRGBEEQBEEQBEEQBEEQhAsSGBEEQRAEQRAEQRAEQRAuSGBEEARBEARBEARBEARBuCCBEUEQBEEQBEEQBEEQBOGCcc5LXQclGGPPAfhzqethgAkAni91JQgiBGqnRNqhNkqkHWqjRNqhNkqkHWqjRNoZS220j3Pe4T1YNgKjsQJj7H7O+XCp60EQQVA7JdIOtVEi7VAbJdIOtVEi7VAbJdJOJbRRMkkjCIIgCIIgCIIgCIIgXJDAiCAIgiAIgiAIgiAIgnBBAqPi8/FSV4AgFKB2SqQdaqNE2qE2SqQdaqNE2qE2SqSdMd9GyYcRQRAEQRAEQRAEQRAE4YI0jAiCIAiCIAiCIAiCIAgXJDAqIoyxHYyxRxhjjzLGrih1fYjKhTH2BGPsd4yxXzPG7s8fa2eM/YAx9sf8zzZH+ivz7fYRxtj20tWcGKswxj7FGHuWMfZ7xzHtNskYW5Jv248yxv6DMcaKfS/E2ETSRt/NGPtrvi/9NWNsp+MctVGiqDDGehhjP2KMPcQYe4AxdlH+OPWlRCoIaKPUlxKpgDFWxxi7jzH2m3wbvTZ/vGL7URIYFQnGWBbARwAcAmA2gOMYY7NLWyuiwtnIOV/oCAV5BYC7OOfTAdyV/xv5droLwBwAOwB8NN+eCcIkn0GufTmJ0iZvAnAWgOn5f948CSIqn4G4PX0w35cu5Jx/D6A2SpSMgwAu4ZzPArACwPn5tkh9KZEWZG0UoL6USAf7AWzinC8AsBDADsbYClRwP0oCo+KxDMCjnPPHOOdvAPgygCNKXCeCcHIEgM/mf/8sgCMdx7/MOd/POX8cwKPItWeCMAbn/CcAXvQc1mqTjLGJAJo55/fwnIO+zzmuIYhYSNqoDGqjRNHhnD/NOf9V/vd9AB4CMBnUlxIpIaCNyqA2ShQVnuPl/J/V+X8cFdyPksCoeEwG8BfH308huIMkiCThAO5gjP2SMXZW/lgX5/xpIDegA+jMH6e2S5QK3TY5Of+79zhBJMkFjLHf5k3WLBV1aqNESWGM9QNYBOBeUF9KpBBPGwWoLyVSAmMsyxj7NYBnAfyAc17R/SgJjIqHyGaRQtQRpWI153wxciaS5zPG1gWkpbZLpA1Zm6S2ShSbmwBMQ05t/WkAH8gfpzZKlAzGWCOAWwBczDl/KSip4Bi1UyJxBG2U+lIiNXDORzjnCwFMQU5baG5A8jHfRklgVDyeAtDj+HsKgL+VqC5EhcM5/1v+57MAvoGcidkzefVJ5H8+m09ObZcoFbpt8qn8797jBJEInPNn8hPLUQCfQMFcl9ooURIYY9XILcS/wDn/ev4w9aVEahC1UepLiTTCOf8HgB8j53uoYvtREhgVj18AmM4YG2CM1SDnHOvbJa4TUYEwxsYxxpqs3wFsA/B75NrjyflkJwP4Vv73bwPYxRirZYwNIOe07b7i1pqoULTaZF5FeB9jbEU+EsVJjmsIwjjW5DHPUcj1pQC1UaIE5NvUJwE8xDn/N8cp6kuJVCBro9SXEmmBMdbBGGvN/14PYAuAh1HB/WhVqStQKXDODzLGLgBwO4AsgE9xzh8ocbWIyqQLwDfykR2rAHyRc34bY+wXAL7CGDsdwJMAjgEAzvkDjLGvAHgQuegW53POR0pTdWKswhj7EoANACYwxp4C8C4AN0K/TZ6LXDSregDfz/8jiNhI2ugGxthC5NTMnwBwNkBtlCgZqwHsBvC7vP8NALgK1JcS6UHWRo+jvpRICRMBfDYf6SwD4Cuc8+8yxu5BhfajLOe0myAIgiAIgiAIgiAIgiBykEkaQRAEQRAEQRAEQRAE4YIERgRBEARBEARBEARBEIQLEhgRBEEQBEEQBEEQBEEQLkhgRBAEQRAEQRAEQRAEQbgggRFBEARBEARBEARBEAThggRGBEEQBEEQBEEQBEEQhAsSGBEEQRAEQRAEQRAEQRAuSGBEEARBEARBEARBEARBuPj/Ad1IPAM+0sHNAAAAAElFTkSuQmCC\n", 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\n", "text/plain": [ "
" ] @@ -425,13 +425,37 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "id": "5b946c7f", + "metadata": {}, + "source": [ + "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" + ] + }, + { + "cell_type": "markdown", + "id": "6a6a8e13", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f(\\mu^{'}, \\sigma^{'}) ={}& \n", + " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, { "cell_type": "markdown", "id": "e7564257", "metadata": {}, "source": [ "Please note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", - "**To find critical point(s):**" + "**To find extrema points, we first need to find the critical point(s) by solving the single system of equations below.** In other words, we are looking for $\\mu^{'}$ and $\\sigma^{'}$ that satisfies both equations below.\n", + "\n" ] }, { From 7554bff7810263b5efb6735cc77af3bece569bc8 Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 09:46:46 -0600 Subject: [PATCH 12/67] use cdot in latex math to improve readability --- docs/Tutorial_VALMOD.ipynb | 23 +++++++++++++---------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 366f0128c..8f3258acb 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -427,7 +427,7 @@ }, { "cell_type": "markdown", - "id": "5b946c7f", + "id": "0a4166f2", "metadata": {}, "source": [ "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" @@ -435,7 +435,7 @@ }, { "cell_type": "markdown", - "id": "6a6a8e13", + "id": "f0cc2aa1", "metadata": {}, "source": [ "\n", @@ -598,7 +598,7 @@ " {\\left(\n", " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", " - \n", - " \\mu^{'} (0)\n", + " \\mu^{'}\\cdot 0\n", " \\right)\n", " }\n", " \\\\\n", @@ -760,14 +760,15 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\\left(m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2} - \\mu^{'}(m \\mu_{i,m})\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu_{j,m+k}(m\\mu_{i,m})}\\right) ={}& 0\n", + " \\frac{1}{\\sigma^{'}}\\left(m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2} - \\mu^{'} \\cdot m\\mu_{i,m}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\\right) ={}& 0\n", " \\\\\n", + " \\frac{\n", " \\sigma_{j,m}\\left(\n", " m\\sigma_{i,m}^{2} \n", " + \n", " m\\mu_{i,m}^{2} \n", " - \n", - " \\mu^{'}(m \\mu_{i,m})\n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", @@ -775,8 +776,10 @@ " +\n", " m\\mu_{i,m}\\mu_{j,m}) \n", " -\n", - " \\mu_{j,m+k}(m\\mu_{i,m})}\n", - " \\right) ={}& 0\n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\n", + " \\right)\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}} ={}& 0\n", " \\\\\n", " m\\left[\n", " \\sigma_{j,m}\\left(\n", @@ -784,7 +787,7 @@ " + \n", " \\mu_{i,m}^{2} \n", " - \n", - " \\mu^{'}(\\mu_{i,m})\n", + " \\mu^{'} \\mu_{i,m}\n", " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", @@ -792,7 +795,7 @@ " +\n", " \\mu_{i,m}\\mu_{j,m}) \n", " -\n", - " \\mu_{j,m+k}(\\mu_{i,m})}\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", " \\right)\n", " \\right]\n", " ={}& 0\n", @@ -888,7 +891,7 @@ " \\\\ \n", " ={}&\n", " {\n", - " \\frac{0 - \\mu^{'}(0)}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}(0)}{\\sigma_{j,m}}\n", + " \\frac{0 - \\mu^{'} \\cdot 0}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0}{\\sigma_{j,m}}\n", " } \n", " \\\\ \n", " ={}&\n", From b8ea16cf41054fff51dc3d57f239bbebb756f71d Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 09:52:03 -0600 Subject: [PATCH 13/67] restructure the notebook to keep the flow --- docs/Tutorial_VALMOD.ipynb | 92 +++++++++++++++++++------------------- 1 file changed, 46 insertions(+), 46 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 8f3258acb..4c5eb56a2 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -427,7 +427,7 @@ }, { "cell_type": "markdown", - "id": "0a4166f2", + "id": "27796250", "metadata": {}, "source": [ "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" @@ -435,7 +435,7 @@ }, { "cell_type": "markdown", - "id": "f0cc2aa1", + "id": "e7b2a98e", "metadata": {}, "source": [ "\n", @@ -536,6 +536,47 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "id": "5c39469f", + "metadata": {}, + "source": [ + "**Exapanding (3):**" + ] + }, + { + "cell_type": "markdown", + "id": "25a3cf35", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", + " 0\n", + " \\\\\n", + " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", + " 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", + " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", + " 0 \\quad (4)\n", + "\\end{align} \n", + "$$\n" + ] + }, { "cell_type": "markdown", "id": "393ddb8f", @@ -628,49 +669,8 @@ "$$\n", "\\begin{align}\n", " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", - " 0 \\quad (4)\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "2dd7d048", - "metadata": {}, - "source": [ - "**Exapanding (3):**" - ] - }, - { - "cell_type": "markdown", - "id": "848e6f89", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", - " 0\n", - " \\\\\n", - " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", - " 0\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", - " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", " 0 \\quad (5)\n", - "\\end{align} \n", + "\\end{align}\n", "$$\n" ] }, @@ -823,7 +823,7 @@ "id": "6adaea06", "metadata": {}, "source": [ - "**Solving (5) and (7) gives:**" + "**Solving (4) and (7) gives:**" ] }, { @@ -858,7 +858,7 @@ "id": "a0e36dfc", "metadata": {}, "source": [ - "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (4) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." + "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (5) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." ] }, { From d3f9617b926585ab5ef97ab65382d5da9272bc54 Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 10:06:45 -0600 Subject: [PATCH 14/67] minor changes --- docs/Tutorial_VALMOD.ipynb | 65 ++++++++++++++++++++++++++++++-------- 1 file changed, 52 insertions(+), 13 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 4c5eb56a2..fe12d0fe0 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -427,7 +427,7 @@ }, { "cell_type": "markdown", - "id": "27796250", + "id": "a8f1ad87", "metadata": {}, "source": [ "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" @@ -435,7 +435,7 @@ }, { "cell_type": "markdown", - "id": "e7b2a98e", + "id": "3b2d48d7", "metadata": {}, "source": [ "\n", @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "5c39469f", + "id": "4f30398f", "metadata": {}, "source": [ "**Exapanding (3):**" @@ -546,7 +546,7 @@ }, { "cell_type": "markdown", - "id": "25a3cf35", + "id": "49cf48c5", "metadata": {}, "source": [ "\n", @@ -708,8 +708,8 @@ " ={}& 0\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\mu^{'}\\sum \\limits_{t=1}^{m} T[i+t-1]\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]}\\right) \n", - " ={}& 0\n", - "\\end{align}\n", + " ={}& 0 \\quad (*)\n", + "\\end{align} \n", "$$\n" ] }, @@ -740,8 +740,8 @@ "id": "4880c751", "metadata": {}, "source": [ - "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$.
\n", - "**Note:** Also: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$" + "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$. Becauses, the correlation of any subsequence with itself is 1.
\n", + "**Note:** we can rewrite (6) as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$" ] }, { @@ -749,7 +749,7 @@ "id": "a01fd0cc", "metadata": {}, "source": [ - "**Therefore:**" + "**Therefore, continue from eq(*)...**" ] }, { @@ -760,7 +760,26 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\\left(m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2} - \\mu^{'} \\cdot m\\mu_{i,m}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\\right) ={}& 0\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left[\n", + " \\left(\n", + " m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}\n", + " \\right)\n", + " - \n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", + " \\right] \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left[\n", + " \\left(\n", + " m\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " + \n", + " m\\mu_{i,m}\\mu_{j,m}\n", + " \\right)\n", + " - \n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", + " \\right]\n", + " ={}& 0\n", " \\\\\n", " \\frac{\n", " \\sigma_{j,m}\\left(\n", @@ -774,14 +793,17 @@ " \\sigma^{'}\\left(\n", " {m\\rho\\sigma_{i,m}\\sigma_{j,m} \n", " +\n", - " m\\mu_{i,m}\\mu_{j,m}) \n", + " m\\mu_{i,m}\\mu_{j,m} \n", " -\n", " \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\n", " \\right)\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}} ={}& 0\n", " \\\\\n", - " m\\left[\n", + " \\frac{m}{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\left[\n", " \\sigma_{j,m}\\left(\n", " \\sigma_{i,m}^{2} \n", " + \n", @@ -793,13 +815,30 @@ " \\sigma^{'}\\left(\n", " {\\rho\\sigma_{i,m}\\sigma_{j,m} \n", " +\n", - " \\mu_{i,m}\\mu_{j,m}) \n", + " \\mu_{i,m}\\mu_{j,m}\n", " -\n", " \\mu_{j,m+k} \\mu_{i,m}}\n", " \\right)\n", " \\right]\n", " ={}& 0\n", " \\\\\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", "\\end{align}\n", "$$\n" ] From 7d26c9721a800ecac2cff241a2e45c8f8f308681 Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 11:24:51 -0600 Subject: [PATCH 15/67] improve readibility of equations --- docs/Tutorial_VALMOD.ipynb | 227 +++++++++++++++++++++++++++++-------- 1 file changed, 180 insertions(+), 47 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index fe12d0fe0..82657ab11 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -375,7 +375,7 @@ " }\n", " \\\\\n", " ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad (1)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -402,7 +402,7 @@ " f(\\mu^{'}, \\sigma^{'}) ={}& \n", " \\sum\\limits_{t=1}^{m}{{\n", " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", - " }^{2}} \n", + " }^{2}} \\quad (2)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -418,7 +418,7 @@ "\\begin{align}\n", " \\alpha_{t} \\triangleq{}& \n", " {\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}} \\quad (3)\n", " } \n", " \\\\\n", "\\end{align}\n", @@ -427,7 +427,7 @@ }, { "cell_type": "markdown", - "id": "a8f1ad87", + "id": "c5e7e16d", "metadata": {}, "source": [ "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" @@ -435,14 +435,14 @@ }, { "cell_type": "markdown", - "id": "3b2d48d7", + "id": "a55134cb", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", " f(\\mu^{'}, \\sigma^{'}) ={}& \n", - " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \n", + " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (4)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -466,9 +466,9 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad \\text{(1)}\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad (5)\n", " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad \\text{(2)}\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad (6)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -531,22 +531,22 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (3)\n", + " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (7)\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "4f30398f", + "id": "0a3dd808", "metadata": {}, "source": [ - "**Exapanding (3):**" + "**Exapanding (7):**" ] }, { "cell_type": "markdown", - "id": "49cf48c5", + "id": "91c2bf00", "metadata": {}, "source": [ "\n", @@ -572,7 +572,7 @@ " \\\\\n", " \\sigma_{j,m} \\mu^{'} + \n", " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", - " 0 \\quad (4)\n", + " 0 \\quad (8)\n", "\\end{align} \n", "$$\n" ] @@ -669,7 +669,7 @@ "$$\n", "\\begin{align}\n", " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", - " 0 \\quad (5)\n", + " 0 \\quad (9)\n", "\\end{align}\n", "$$\n" ] @@ -679,7 +679,7 @@ "id": "4a34e737", "metadata": {}, "source": [ - "**Expanding (4):**" + "**Expanding (9):**" ] }, { @@ -729,7 +729,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\rho = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (6)\n", + " \\rho = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -741,7 +741,7 @@ "metadata": {}, "source": [ "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$. Becauses, the correlation of any subsequence with itself is 1.
\n", - "**Note:** we can rewrite (6) as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$" + "**Note:** we can rewrite (6) as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (**)" ] }, { @@ -749,7 +749,7 @@ "id": "a01fd0cc", "metadata": {}, "source": [ - "**Therefore, continue from eq(*)...**" + "Therefore, with help of (\\*\\*), we continue eq(*):" ] }, { @@ -851,7 +851,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (7)\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (10)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -862,7 +862,7 @@ "id": "6adaea06", "metadata": {}, "source": [ - "**Solving (4) and (7) gives:**" + "**Solving (8) and (10) gives the values of critical point:**" ] }, { @@ -873,13 +873,13 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (8)\n", + " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (11)\n", "\\end{align}\n", "$$\n", "\n", "$$\n", "\\begin{align}\n", - " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho} \\quad (9)\n", + " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho} \\quad (12)\n", "\\end{align}\n", "$$" ] @@ -889,7 +889,7 @@ "id": "b266cfb2", "metadata": {}, "source": [ - "**Note:** eq(9) is valid if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" + "**Note:** Eq(12) is valid if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" ] }, { @@ -897,7 +897,17 @@ "id": "a0e36dfc", "metadata": {}, "source": [ - "We can try to simply $f_{min}(\\mu^{'}, \\sigma^{'})$ first with help of (3) and (5) before plugging in the values $\\mu^{'}$ (8) and $\\sigma^{'}$ (9)." + "---\n", + "\n", + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we solved the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all discovered equations (5), (6), (7), (8), (9), and (10) throughout the solution.
" + ] + }, + { + "cell_type": "markdown", + "id": "2b12d914", + "metadata": {}, + "source": [ + "**Start with equation (4):**" ] }, { @@ -908,29 +918,109 @@ "\n", "$$\n", "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", - " }^{2}} \n", + " f(\\mu^{'}_{c},\\sigma^{'}_{c}) ={}&\n", + " \\sum \\limits_{t=1}^{m}\\alpha_{t}^{2}\n", " \\\\\n", " ={}&\n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", - " }\\alpha_{t}}\n", + " \\sum \\limits_{t=1}^{m}\\alpha_{t} \\cdot \\alpha_{t}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4324a2d7", + "metadata": {}, + "source": [ + "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(3)..." + ] + }, + { + "cell_type": "markdown", + "id": "b07d7917", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", + " \\sum\\limits_{t=1}^{m}{\n", + " {\\alpha_{t}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " }}\n", " \\\\\n", " ={}&\n", " {\n", - " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]\\alpha_{t} - \\sum\\limits_{t=1}^{m}\\mu^{'}\\alpha_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\sum\\limits_{t=1}^{m}\\mu_{j,m+k}\\alpha_{t}}{\\sigma_{j,m}}\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]\\alpha_{t} \n", + " - \n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu^{'}\\alpha_{t}\n", + " \\right)\n", + " - \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[j+t-1]\\alpha_{t} \n", + " - \n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu_{j,m+k}\\alpha_{t}\n", + " \\right)\n", " } \n", " \\\\ \n", " ={}&\n", " {\n", - " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]\\alpha_{t} - \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}}{\\sigma_{j,m}}\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]\\alpha_{t} \n", + " - \n", + " \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\right)\n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} \n", + " - \n", + " \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\right)\n", " } \n", - " \\\\ \n", - " ={}&\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "fe63f99b", + "metadata": {}, + "source": [ + "And, now with help of eq(7), $\\sum\\limits_{t=1}^{m}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}}=0$, we will have:" + ] + }, + { + "cell_type": "markdown", + "id": "6b89c8a5", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", " {\n", - " \\frac{0 - \\mu^{'} \\cdot 0}{\\sigma^{'}} - \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0}{\\sigma_{j,m}}\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " 0 - \\mu^{'} \\cdot 0\n", + " \\right) \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0\n", + " \\right)\n", " } \n", " \\\\ \n", " ={}&\n", @@ -970,13 +1060,33 @@ " }\n", " } \n", " \\\\\n", - " ={}&\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "0e8a53c1", + "metadata": {}, + "source": [ + "And, now with help of Pearon Correlation eq(\\*\\*)..." + ] + }, + { + "cell_type": "markdown", + "id": "eed98832", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", " {- \\frac{1}{\\sigma_{j,m}} \n", " {\n", " \\left(\n", - " \\frac{(m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - m\\mu_{j,m}\\mu^{'}}{\\sigma^{'}} \n", + " \\frac{(m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu^{'} \\cdot m\\mu_{j,m}}{\\sigma^{'}} \n", " - \n", - " \\frac{(m\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - m\\mu_{j,m}\\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{(m\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - \\mu_{j,m+k} \\cdot m\\mu_{j,m}}{\\sigma_{j,m}}\n", " \\right)\n", " }\n", " } \n", @@ -1012,7 +1122,7 @@ "id": "cfd5a617", "metadata": {}, "source": [ - "plugging in (8) and (9):" + "And, finally, we plug in the values $\\mu^{'}$(11) and $\\sigma^{'}$(12):" ] }, { @@ -1024,10 +1134,12 @@ "$$\n", "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " {- \\frac{m\\rho}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\n", + " (\\frac{\\sigma_{i,m}}{\\rho})\n", + " } \n", " {\n", " \\left[\n", - " {\\rho\\sigma_{(i,m)}\\sigma_{j,m}^{2} + \n", + " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} + \n", " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \n", " \\mu_{j,m}\\sigma_{j,m}\\left({\n", " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", @@ -1050,11 +1162,11 @@ " {\n", " \\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", " + \n", - " \\mu_{j,m}\\sigma_{j,m}\\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " \\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}{\\mu_{j,m}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", " }\n", " } \n", " - \n", - " {(\\frac{\\sigma_{i,m}}{\\rho})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " {\\frac{\\sigma_{i,m}}{\\rho}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right]\n", " }\n", " } \n", @@ -1074,11 +1186,32 @@ " }\n", " } \n", " - \n", - " {(\\sigma_{i,m})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " {\\sigma_{i,m}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right]\n", " }\n", " } \n", " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\rho\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\rho\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k})\n", + " }\n", + " } \\\\\n", + " - \n", + " {\\sigma_{i,m}\\sigma_{j,m}^{2} - \\sigma_{i,m}\\mu_{j,m}^{2} + \\sigma_{i,m}\\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " \\\\\n", " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", " \\left( \n", @@ -1159,7 +1292,7 @@ "metadata": {}, "source": [ "**Note:**
\n", - "* Note that eq(9) is valid only for $\\rho > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho > 0$. \n", + "* Note that eq(12) is valid only for $\\rho > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho > 0$. \n", "* The pearson correlation, $\\rho$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho)}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", @@ -1167,7 +1300,7 @@ "**Pending...**
\n", "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", "\n", - "* For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$." + "* **For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$.**" ] }, { From 32f12a11503485ddfaebed092c51f2df74803412 Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 12:14:54 -0600 Subject: [PATCH 16/67] Polish math equations --- docs/Tutorial_VALMOD.ipynb | 84 +++++++++++++++----------------------- 1 file changed, 33 insertions(+), 51 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 82657ab11..e5751d9d3 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -375,7 +375,7 @@ " }\n", " \\\\\n", " ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad (1)\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -399,6 +399,10 @@ "\n", "$$\n", "\\begin{align}\n", + " LB ={}& \n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\sqrt{f(\\mu^{'},\\sigma^{'})} \\quad (1)\n", + " \\\\\n", " f(\\mu^{'}, \\sigma^{'}) ={}& \n", " \\sum\\limits_{t=1}^{m}{{\n", " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", @@ -427,7 +431,7 @@ }, { "cell_type": "markdown", - "id": "c5e7e16d", + "id": "d4ad4a6b", "metadata": {}, "source": [ "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" @@ -435,7 +439,7 @@ }, { "cell_type": "markdown", - "id": "a55134cb", + "id": "07223500", "metadata": {}, "source": [ "\n", @@ -538,7 +542,7 @@ }, { "cell_type": "markdown", - "id": "0a3dd808", + "id": "0aad71e0", "metadata": {}, "source": [ "**Exapanding (7):**" @@ -546,7 +550,7 @@ }, { "cell_type": "markdown", - "id": "91c2bf00", + "id": "0d3f4dfa", "metadata": {}, "source": [ "\n", @@ -718,7 +722,7 @@ "id": "0c839937", "metadata": {}, "source": [ - "**Now, recall the pearson correlation $\\rho$:**" + "Now, recall the pearson correlation $\\rho$:" ] }, { @@ -740,8 +744,8 @@ "id": "4880c751", "metadata": {}, "source": [ - "**Note:** The pearson correlation, $\\rho$, is 1 when $i=j$. Becauses, the correlation of any subsequence with itself is 1.
\n", - "**Note:** we can rewrite (6) as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (**)" + "Note: The pearson correlation, $\\rho$, is 1 when $i=j$. Becauses, the correlation of any subsequence with itself is 1.
\n", + "Note: we can rewrite pearson correlation equation as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" ] }, { @@ -749,7 +753,7 @@ "id": "a01fd0cc", "metadata": {}, "source": [ - "Therefore, with help of (\\*\\*), we continue eq(*):" + "**Therefore, with help of (\\*\\*), we continue our calculation from eq(\\*):**" ] }, { @@ -889,7 +893,7 @@ "id": "b266cfb2", "metadata": {}, "source": [ - "**Note:** Eq(12) is valid if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" + "**Note:** Since standard deviation is positive, eq(12) is valid only if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" ] }, { @@ -899,12 +903,12 @@ "source": [ "---\n", "\n", - "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we solved the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all discovered equations (5), (6), (7), (8), (9), and (10) throughout the solution.
" + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" ] }, { "cell_type": "markdown", - "id": "2b12d914", + "id": "92abd2a2", "metadata": {}, "source": [ "**Start with equation (4):**" @@ -930,7 +934,7 @@ }, { "cell_type": "markdown", - "id": "4324a2d7", + "id": "7afe0a3d", "metadata": {}, "source": [ "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(3)..." @@ -938,7 +942,7 @@ }, { "cell_type": "markdown", - "id": "b07d7917", + "id": "bfb10bce", "metadata": {}, "source": [ "\n", @@ -996,7 +1000,7 @@ }, { "cell_type": "markdown", - "id": "fe63f99b", + "id": "4a9e3f03", "metadata": {}, "source": [ "And, now with help of eq(7), $\\sum\\limits_{t=1}^{m}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}}=0$, we will have:" @@ -1004,7 +1008,7 @@ }, { "cell_type": "markdown", - "id": "6b89c8a5", + "id": "650cae87", "metadata": {}, "source": [ "\n", @@ -1066,7 +1070,7 @@ }, { "cell_type": "markdown", - "id": "0e8a53c1", + "id": "9f2ca2da", "metadata": {}, "source": [ "And, now with help of Pearon Correlation eq(\\*\\*)..." @@ -1074,7 +1078,7 @@ }, { "cell_type": "markdown", - "id": "eed98832", + "id": "35db152a", "metadata": {}, "source": [ "\n", @@ -1122,7 +1126,7 @@ "id": "cfd5a617", "metadata": {}, "source": [ - "And, finally, we plug in the values $\\mu^{'}$(11) and $\\sigma^{'}$(12):" + "And, now we are at a good position to plug in the values $\\mu^{'}$(11) and $\\sigma^{'}$(12):" ] }, { @@ -1194,7 +1198,7 @@ " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", " {\n", - " \\left[\n", + " \\left(\n", " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", " + \n", " \\rho\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", @@ -1202,16 +1206,15 @@ " {\n", " \\rho\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", " + \n", - " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k})\n", + " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k}\n", + " }\n", " }\n", - " } \\\\\n", " - \n", - " {\\sigma_{i,m}\\sigma_{j,m}^{2} - \\sigma_{i,m}\\mu_{j,m}^{2} + \\sigma_{i,m}\\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right]\n", + " {\\sigma_{i,m}\\sigma_{j,m}^{2} - \\sigma_{i,m}\\mu_{j,m}^{2} + \\sigma_{i,m}\\mu_{j,m}\\mu_{j,m+k}}\n", + " \\right)\n", " }\n", " } \n", " \\\\\n", - " \\\\\n", " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", " \\left( \n", @@ -1222,36 +1225,15 @@ " \\right)\n", " } \n", " \\\\\n", - " \\\\\n", " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", " (\\rho^{2} - 1)\n", " \\sigma_{i,m}\\sigma_{j,m}^{2}\n", - " } \n", - "\\end{align} \n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "d836a69d", - "metadata": {}, - "source": [ - "Therefore:" - ] - }, - { - "cell_type": "markdown", - "id": "a5c3b9e8", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " m (1 - \\rho^{2}) \n", + " }\n", " \\\\\n", - "\\end{align}\n", + " ={}&\n", + " m(1-\\rho^{2})\n", + "\\end{align} \n", "$$\n" ] }, @@ -1260,7 +1242,7 @@ "id": "64dc1027", "metadata": {}, "source": [ - "**Therefore, the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" + "**Finally, with eq(1), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" ] }, { From 5405d476493846d2e9eaf566c3d6fd13c747cd1a Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 13:30:51 -0600 Subject: [PATCH 17/67] imporve readability --- docs/Tutorial_VALMOD.ipynb | 38 +++++++++++++++++++++++++++++++------- 1 file changed, 31 insertions(+), 7 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index e5751d9d3..338f043c0 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -708,10 +708,34 @@ "\n", "$$\n", "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\sum \\limits_{t=1}^{m} T[i+t-1] \\mu^{'}\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}}\\right) \n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " -\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]\\mu^{'}\n", + " \\right) \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " {\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", + " -\\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}\n", + " }\n", + " \\right) \n", " ={}& 0\n", " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m} T[i+t-1]T[i+t-1] - \\mu^{'}\\sum \\limits_{t=1}^{m} T[i+t-1]\\right) - \\frac{1}{\\sigma_{j,m}}\\left({\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]}\\right) \n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum \\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " -\n", + " \\mu^{'}\\sum\\limits_{t=1}^{m} T[i+t-1]\n", + " \\right) \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1]\n", + " -\n", + " \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " \\right) \n", " ={}& 0 \\quad (*)\n", "\\end{align} \n", "$$\n" @@ -785,7 +809,8 @@ " \\right]\n", " ={}& 0\n", " \\\\\n", - " \\frac{\n", + " \\frac{1}{\\sigma^{'}\\sigma_{j,m}}\n", + " \\left[\n", " \\sigma_{j,m}\\left(\n", " m\\sigma_{i,m}^{2} \n", " + \n", @@ -801,8 +826,7 @@ " -\n", " \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\n", " \\right)\n", - " }{\n", - " \\sigma^{'}\\sigma_{j,m}} ={}& 0\n", + " \\right] ={}& 0\n", " \\\\\n", " \\frac{m}{\n", " \\sigma^{'}\\sigma_{j,m}\n", @@ -903,7 +927,7 @@ "source": [ "---\n", "\n", - "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" ] }, { @@ -1073,7 +1097,7 @@ "id": "9f2ca2da", "metadata": {}, "source": [ - "And, now with help of Pearon Correlation eq(\\*\\*)..." + "And, now with help of the fact that $\\sum{T} = m\\mu$ and also the Pearon Correlation equation (\\*\\*)..." ] }, { From cd6be19decc37fb2a9af6484d83b6ba508fb90ef Mon Sep 17 00:00:00 2001 From: ninimama Date: Wed, 13 Apr 2022 13:37:06 -0600 Subject: [PATCH 18/67] minor change --- docs/Tutorial_VALMOD.ipynb | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 338f043c0..3e3b453e9 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -714,14 +714,15 @@ " -\n", " \\sum\\limits_{t=1}^{m}T[i+t-1]\\mu^{'}\n", " \\right) \n", - " - \n", + " - \\\\\n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", " {\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", " -\\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}\n", " }\n", " \\right) \n", - " ={}& 0\n", + " ={}& \n", + " 0\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", @@ -729,14 +730,15 @@ " -\n", " \\mu^{'}\\sum\\limits_{t=1}^{m} T[i+t-1]\n", " \\right) \n", - " - \n", + " - \\\\\n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", " \\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1]\n", " -\n", " \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", " \\right) \n", - " ={}& 0 \\quad (*)\n", + " ={}& \n", + " 0 \\quad (*)\n", "\\end{align} \n", "$$\n" ] From 06480c1fdd25b9df0b934b16678abfb8194e8abc Mon Sep 17 00:00:00 2001 From: ninimama Date: Fri, 15 Apr 2022 20:18:52 -0600 Subject: [PATCH 19/67] minor changes to improve readability --- docs/Tutorial_VALMOD.ipynb | 73 ++++++++++++++++++++------------------ 1 file changed, 39 insertions(+), 34 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 3e3b453e9..d38012c3e 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -107,7 +107,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -386,35 +386,16 @@ "id": "d410ec5a", "metadata": {}, "source": [ - "**Note:** that the variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", + "**Note:** that the unknown variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", "\n", - "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$." - ] - }, - { - "cell_type": "markdown", - "id": "a293197c", - "metadata": {}, - "source": [ + "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$. Note that the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$.
\n", "\n", - "$$\n", - "\\begin{align}\n", - " LB ={}& \n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{f(\\mu^{'},\\sigma^{'})} \\quad (1)\n", - " \\\\\n", - " f(\\mu^{'}, \\sigma^{'}) ={}& \n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)\n", - " }^{2}} \\quad (2)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" + "Also, we define $\\alpha_{t}$ as:" ] }, { "cell_type": "markdown", - "id": "6722cf8a", + "id": "caffa72c", "metadata": {}, "source": [ "\n", @@ -422,7 +403,7 @@ "\\begin{align}\n", " \\alpha_{t} \\triangleq{}& \n", " {\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}} \\quad (3)\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " } \n", " \\\\\n", "\\end{align}\n", @@ -431,22 +412,39 @@ }, { "cell_type": "markdown", - "id": "d4ad4a6b", + "id": "91be5280", "metadata": {}, "source": [ - "Therefore, we can write $f(\\mu_{'},\\sigma_{'})$ as follows:" + "Therefore, we have:" ] }, { "cell_type": "markdown", - "id": "07223500", + "id": "a293197c", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", - " f(\\mu^{'}, \\sigma^{'}) ={}& \n", - " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (4)\n", + " LB ={}& \n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\sqrt{\\min f(\\mu^{'},\\sigma^{'})} \\quad (2)\n", + " \\\\\n", + " f(\\mu^{'}, \\sigma^{'}) ={}&\n", + " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (3)\n", + " \\\\\n", + " \\alpha_{t} ={}& \n", + " \\frac{\n", + " T[i+t-1] - \\mu^{'}\n", + " }{\n", + " \\sigma^{'}\n", + " } \n", + " - \n", + " \\frac{\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " } \\quad (4)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -457,8 +455,7 @@ "id": "e7564257", "metadata": {}, "source": [ - "Please note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", - "**To find extrema points, we first need to find the critical point(s) by solving the single system of equations below.** In other words, we are looking for $\\mu^{'}$ and $\\sigma^{'}$ that satisfies both equations below.\n", + "**To find extrema points, we first need to find the critical point(s) by solving the single system of equations below.** In other words, we are looking for $\\mu^{'}$ and $\\sigma^{'}$ that satisfies both equations below:\n", "\n" ] }, @@ -483,7 +480,7 @@ "id": "a3656f16", "metadata": {}, "source": [ - "**Deriving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}}$:**" + "**Solving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0$:**" ] }, { @@ -586,7 +583,7 @@ "id": "393ddb8f", "metadata": {}, "source": [ - "**Deriving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}}$:**" + "**Solving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0$:**" ] }, { @@ -656,6 +653,14 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "id": "f9c281a2", + "metadata": {}, + "source": [ + "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." + ] + }, { "cell_type": "markdown", "id": "c3b80336", From 0ccf8d5e8e28b8955cd1424a007792c5f4351d14 Mon Sep 17 00:00:00 2001 From: ninimama Date: Fri, 15 Apr 2022 20:30:39 -0600 Subject: [PATCH 20/67] improve readibility of expansion of eq 9 --- docs/Tutorial_VALMOD.ipynb | 35 +++++++++++++++++++++++++++++++---- 1 file changed, 31 insertions(+), 4 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index d38012c3e..694a23205 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -375,7 +375,7 @@ " }\n", " \\\\\n", " ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}}\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad(1)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "caffa72c", + "id": "ce5f5ca3", "metadata": {}, "source": [ "\n", @@ -412,7 +412,7 @@ }, { "cell_type": "markdown", - "id": "91be5280", + "id": "dc3e9f2a", "metadata": {}, "source": [ "Therefore, we have:" @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "f9c281a2", + "id": "a1cb6776", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -713,6 +713,32 @@ "\n", "$$\n", "\\begin{align}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}}\n", + " \\right)\n", + " - \n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " T[i+t-1] - \\mu^{'}\n", + " \\right)\n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", " \\sum\\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", @@ -729,6 +755,7 @@ " ={}& \n", " 0\n", " \\\\\n", + " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", " \\sum \\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", From 9d61b8fc0f85ed8e68ebcbd500cbe859750265fe Mon Sep 17 00:00:00 2001 From: ninimama Date: Fri, 15 Apr 2022 21:02:18 -0600 Subject: [PATCH 21/67] Elaborated calculations --- docs/Tutorial_VALMOD.ipynb | 103 ++++++++++++++++++++++++++++++++----- 1 file changed, 90 insertions(+), 13 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 694a23205..0d9d1faa0 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "ce5f5ca3", + "id": "0405ac3d", "metadata": {}, "source": [ "\n", @@ -412,7 +412,7 @@ }, { "cell_type": "markdown", - "id": "dc3e9f2a", + "id": "e16169fc", "metadata": {}, "source": [ "Therefore, we have:" @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "a1cb6776", + "id": "bd343f99", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -780,7 +780,7 @@ "id": "0c839937", "metadata": {}, "source": [ - "Now, recall the pearson correlation $\\rho$:" + "Now, recall that the pearson correlation $\\rho_{ij}$ between two subsequenes of lenght $m$ is defined as follows:" ] }, { @@ -791,7 +791,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\rho = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", + " \\rho_{ij} = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -802,8 +802,8 @@ "id": "4880c751", "metadata": {}, "source": [ - "Note: The pearson correlation, $\\rho$, is 1 when $i=j$. Becauses, the correlation of any subsequence with itself is 1.
\n", - "Note: we can rewrite pearson correlation equation as: $\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" + "Note: we can rearrange the pearson correlation equation as:
\n", + "$\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" ] }, { @@ -825,7 +825,7 @@ " \\frac{1}{\\sigma^{'}}\n", " \\left[\n", " \\left(\n", - " m\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}\n", + " m\\rho_{ii}\\sigma_{i,m}\\sigma_{i,m} + m\\mu_{i,m}\\mu_{i,m}\n", " \\right)\n", " - \n", " \\mu^{'} \\cdot m\\mu_{i,m}\n", @@ -834,7 +834,7 @@ " \\frac{1}{\\sigma_{j,m}}\n", " \\left[\n", " \\left(\n", - " m\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", " + \n", " m\\mu_{i,m}\\mu_{j,m}\n", " \\right)\n", @@ -843,6 +843,38 @@ " \\right]\n", " ={}& 0\n", " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left[\n", + " \\left(\n", + " m\\cdot1\\cdot\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}\n", + " \\right)\n", + " - \n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", + " \\right] \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left[\n", + " \\left(\n", + " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " + \n", + " m\\mu_{i,m}\\mu_{j,m}\n", + " \\right)\n", + " - \n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", + " \\right]\n", + " ={}& 0\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "5c9c05b6", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", " \\frac{1}{\\sigma^{'}\\sigma_{j,m}}\n", " \\left[\n", " \\sigma_{j,m}\\left(\n", @@ -854,7 +886,7 @@ " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", - " {m\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " {m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", " +\n", " m\\mu_{i,m}\\mu_{j,m} \n", " -\n", @@ -875,7 +907,7 @@ " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", - " {\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", " +\n", " \\mu_{i,m}\\mu_{j,m}\n", " -\n", @@ -893,7 +925,26 @@ " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", - " {\\rho\\sigma_{i,m}\\sigma_{j,m} \n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2}\n", + " \\right)\n", + " - \n", + " \\sigma_{j,m}\\left(\n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", " +\n", " \\mu_{i,m}\\mu_{j,m}\n", " -\n", @@ -901,6 +952,24 @@ " \\right)\n", " ={}& 0\n", " \\\\\n", + " - \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2}\n", + " \\right)\n", + " + \n", + " \\sigma_{j,m}\\left(\n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " + \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", "\\end{align}\n", "$$\n" ] @@ -913,12 +982,20 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (10)\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (10)\n", " \\\\\n", "\\end{align}\n", "$$\n" ] }, + { + "cell_type": "markdown", + "id": "922bb7a8", + "metadata": {}, + "source": [ + "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." + ] + }, { "cell_type": "markdown", "id": "6adaea06", From 52204e0f3605418a6ad2ed383b042f4ff4338dea Mon Sep 17 00:00:00 2001 From: ninimama Date: Fri, 15 Apr 2022 21:52:10 -0600 Subject: [PATCH 22/67] show calculations for two equations with two unknowns --- docs/Tutorial_VALMOD.ipynb | 197 +++++++++++++++++++++++++++++++++++-- 1 file changed, 187 insertions(+), 10 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 0d9d1faa0..8b8514630 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "0405ac3d", + "id": "c6ac3737", "metadata": {}, "source": [ "\n", @@ -412,7 +412,7 @@ }, { "cell_type": "markdown", - "id": "e16169fc", + "id": "7df0ca7f", "metadata": {}, "source": [ "Therefore, we have:" @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "bd343f99", + "id": "b1eafd1e", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -869,7 +869,7 @@ }, { "cell_type": "markdown", - "id": "5c9c05b6", + "id": "6f947d20", "metadata": {}, "source": [ "\n", @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "922bb7a8", + "id": "f386eb7a", "metadata": {}, "source": [ "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." @@ -1001,7 +1001,131 @@ "id": "6adaea06", "metadata": {}, "source": [ - "**Solving (8) and (10) gives the values of critical point:**" + "**Now, it is time to solve equations (8) and (10), provided below:**" + ] + }, + { + "cell_type": "markdown", + "id": "bedf9fb0", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} \n", + " ={}& 0 \\quad(8)\n", + " \\\\\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", + " ={}& 0 \\quad(10)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "b808d61d", + "metadata": {}, + "source": [ + "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." + ] + }, + { + "cell_type": "markdown", + "id": "c777af36", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "-\\mu_{i,m}\\left[\n", + " \\sigma_{j,m} \\mu^{'} \n", + " + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} \n", + " - \n", + " \\sigma_{j,m}\\mu_{i,m} \n", + " \\right]\n", + " ={}& 0 \\quad(8')\n", + " \\\\\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", + " ={}& 0 \\quad(10)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "62a5b4d2", + "metadata": {}, + "source": [ + "$(8')+(10)$ gives:" + ] + }, + { + "cell_type": "markdown", + "id": "4ff2f712", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "-\\mu_{i,m}\\sigma_{j,m} \\mu^{'} - \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} \n", + " + \\sigma_{j,m}\\mu_{i,m}^{2} +\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m}\\sigma^{'} - \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m}^{2} - \\sigma_{j,m}\\sigma_{i,m}^{2}\n", + " ={}& 0\n", + " \\\\\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} - \\sigma_{j,m}\\sigma_{i,m}^{2} \n", + " ={}& 0\n", + " \\\\\n", + " \\sigma_{i,m}\\sigma_{j,m}\n", + " \\left(\n", + " \\rho_{ij}\\sigma^{'} - \\sigma_{i,m}\n", + " \\right)\n", + " ={}&\n", + " 0\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "2d2810c3", + "metadata": {}, + "source": [ + "Hence:" + ] + }, + { + "cell_type": "markdown", + "id": "0b83e765", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "f0811a01", + "metadata": {}, + "source": [ + "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." + ] + }, + { + "cell_type": "markdown", + "id": "f031e59c", + "metadata": {}, + "source": [ + "And, subsituting eq(11) in eq(8):" ] }, { @@ -1012,15 +1136,68 @@ "\n", "$$\n", "\\begin{align}\n", - " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma^{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k}) \\quad (11)\n", + "\\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", + " ={}& 0 \n", + " \\\\\n", + " \\frac{1}{\\sigma_{j,m}}\\left[\n", + " \\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", + " \\right]\n", + " ={}& 0 \n", + " \\\\\n", + " \\mu^{'} + \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}) - \\mu_{i,m} \n", + " ={}& 0 \n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "00754de4", + "metadata": {}, + "source": [ + "Hence:" + ] + }, + { + "cell_type": "markdown", + "id": "f7840fd6", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", "\\end{align}\n", "$$\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "679375e8", + "metadata": {}, + "source": [ + "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" + ] + }, + { + "cell_type": "markdown", + "id": "d6807479", + "metadata": {}, + "source": [ "\n", "$$\n", "\\begin{align}\n", - " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho} \\quad (12)\n", + " \\sigma^{'} ={}& \n", + " \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", + " \\\\\n", + " \\mu^{'} ={}& \n", + " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", + " \\\\\n", "\\end{align}\n", - "$$" + "$$\n" ] }, { @@ -1028,7 +1205,7 @@ "id": "b266cfb2", "metadata": {}, "source": [ - "**Note:** Since standard deviation is positive, eq(12) is valid only if $\\rho \\gt 0$. Therefore, the rest of this calculation is based on the assumption that $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" + "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" ] }, { From ad1e79dd96876f416658831d7eaa53babfb28010 Mon Sep 17 00:00:00 2001 From: ninimama Date: Fri, 15 Apr 2022 22:52:13 -0600 Subject: [PATCH 23/67] Discussed the advantage of discovered solution --- docs/Tutorial_VALMOD.ipynb | 44 +++++++++++++++++++------------------- 1 file changed, 22 insertions(+), 22 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 8b8514630..ae5739a65 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "c6ac3737", + "id": "be1e17a8", "metadata": {}, "source": [ "\n", @@ -412,7 +412,7 @@ }, { "cell_type": "markdown", - "id": "7df0ca7f", + "id": "876440a6", "metadata": {}, "source": [ "Therefore, we have:" @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "b1eafd1e", + "id": "ec9d15db", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -869,7 +869,7 @@ }, { "cell_type": "markdown", - "id": "6f947d20", + "id": "e4c3d081", "metadata": {}, "source": [ "\n", @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "f386eb7a", + "id": "7559b895", "metadata": {}, "source": [ "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." @@ -1006,7 +1006,7 @@ }, { "cell_type": "markdown", - "id": "bedf9fb0", + "id": "db952d92", "metadata": {}, "source": [ "\n", @@ -1025,7 +1025,7 @@ }, { "cell_type": "markdown", - "id": "b808d61d", + "id": "8074e1d6", "metadata": {}, "source": [ "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." @@ -1033,7 +1033,7 @@ }, { "cell_type": "markdown", - "id": "c777af36", + "id": "16abecf4", "metadata": {}, "source": [ "\n", @@ -1057,7 +1057,7 @@ }, { "cell_type": "markdown", - "id": "62a5b4d2", + "id": "d0cf405e", "metadata": {}, "source": [ "$(8')+(10)$ gives:" @@ -1065,7 +1065,7 @@ }, { "cell_type": "markdown", - "id": "4ff2f712", + "id": "b2242352", "metadata": {}, "source": [ "\n", @@ -1093,7 +1093,7 @@ }, { "cell_type": "markdown", - "id": "2d2810c3", + "id": "18eecb94", "metadata": {}, "source": [ "Hence:" @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "0b83e765", + "id": "923ba0e2", "metadata": {}, "source": [ "\n", @@ -1114,7 +1114,7 @@ }, { "cell_type": "markdown", - "id": "f0811a01", + "id": "8a5e0e53", "metadata": {}, "source": [ "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "f031e59c", + "id": "cc154e80", "metadata": {}, "source": [ "And, subsituting eq(11) in eq(8):" @@ -1154,7 +1154,7 @@ }, { "cell_type": "markdown", - "id": "00754de4", + "id": "2ca19873", "metadata": {}, "source": [ "Hence:" @@ -1162,7 +1162,7 @@ }, { "cell_type": "markdown", - "id": "f7840fd6", + "id": "d1d78325", "metadata": {}, "source": [ "\n", @@ -1176,7 +1176,7 @@ }, { "cell_type": "markdown", - "id": "679375e8", + "id": "c296d6f7", "metadata": {}, "source": [ "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" @@ -1184,7 +1184,7 @@ }, { "cell_type": "markdown", - "id": "d6807479", + "id": "916c22b8", "metadata": {}, "source": [ "\n", @@ -1205,6 +1205,8 @@ "id": "b266cfb2", "metadata": {}, "source": [ + "**NOTE:** It is important to note that eq(11) and eq(12) are favorable to us as it gives the $\\mu^{'}$ and $\\sigma^{'}$ of the critical point of `f` as a function of known parameters $\\mu_{i,m}$, $\\sigma_{i,m}$, $\\mu_{j,m}$, $\\sigma_{j,m}$, $\\rho_{i,j}$, and $\\mu_{j,m+k}$. Therefore, we can calculate the lower-bound LB as a function of the aforementioned parameter. \n", + "\n", "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" ] }, @@ -1213,8 +1215,6 @@ "id": "a0e36dfc", "metadata": {}, "source": [ - "---\n", - "\n", "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" ] }, @@ -1223,7 +1223,7 @@ "id": "92abd2a2", "metadata": {}, "source": [ - "**Start with equation (4):**" + "**Start with equation (3):**" ] }, { @@ -1234,7 +1234,7 @@ "\n", "$$\n", "\\begin{align}\n", - " f(\\mu^{'}_{c},\\sigma^{'}_{c}) ={}&\n", + " f(\\mu^{'},\\sigma^{'}) ={}&\n", " \\sum \\limits_{t=1}^{m}\\alpha_{t}^{2}\n", " \\\\\n", " ={}&\n", From e5c3d381c905af7abc12190d0036666f9b319edb Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 00:48:03 -0600 Subject: [PATCH 24/67] add subscript ij to correlation rho --- docs/Tutorial_VALMOD.ipynb | 128 ++++++++++++++++++++++--------------- 1 file changed, 78 insertions(+), 50 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index ae5739a65..bbe2edc09 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "id": "6534d116", "metadata": {}, "outputs": [], @@ -388,14 +388,14 @@ "source": [ "**Note:** that the unknown variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", "\n", - "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$. Note that the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$.
\n", + "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$. Note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", "\n", "Also, we define $\\alpha_{t}$ as:" ] }, { "cell_type": "markdown", - "id": "be1e17a8", + "id": "327fbe20", "metadata": {}, "source": [ "\n", @@ -412,7 +412,7 @@ }, { "cell_type": "markdown", - "id": "876440a6", + "id": "6a8b3359", "metadata": {}, "source": [ "Therefore, we have:" @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "ec9d15db", + "id": "c0924610", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -869,7 +869,7 @@ }, { "cell_type": "markdown", - "id": "e4c3d081", + "id": "041482b8", "metadata": {}, "source": [ "\n", @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "7559b895", + "id": "53f8c4b4", "metadata": {}, "source": [ "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." @@ -1006,7 +1006,7 @@ }, { "cell_type": "markdown", - "id": "db952d92", + "id": "9d89eca8", "metadata": {}, "source": [ "\n", @@ -1025,7 +1025,7 @@ }, { "cell_type": "markdown", - "id": "8074e1d6", + "id": "44d1afe8", "metadata": {}, "source": [ "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." @@ -1033,7 +1033,7 @@ }, { "cell_type": "markdown", - "id": "16abecf4", + "id": "35c4e371", "metadata": {}, "source": [ "\n", @@ -1057,7 +1057,7 @@ }, { "cell_type": "markdown", - "id": "d0cf405e", + "id": "5cb0edfe", "metadata": {}, "source": [ "$(8')+(10)$ gives:" @@ -1065,7 +1065,7 @@ }, { "cell_type": "markdown", - "id": "b2242352", + "id": "0e192a68", "metadata": {}, "source": [ "\n", @@ -1093,7 +1093,7 @@ }, { "cell_type": "markdown", - "id": "18eecb94", + "id": "02003455", "metadata": {}, "source": [ "Hence:" @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "923ba0e2", + "id": "70c325aa", "metadata": {}, "source": [ "\n", @@ -1114,7 +1114,7 @@ }, { "cell_type": "markdown", - "id": "8a5e0e53", + "id": "e087b39f", "metadata": {}, "source": [ "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "cc154e80", + "id": "024639e5", "metadata": {}, "source": [ "And, subsituting eq(11) in eq(8):" @@ -1154,7 +1154,7 @@ }, { "cell_type": "markdown", - "id": "2ca19873", + "id": "a745e0a1", "metadata": {}, "source": [ "Hence:" @@ -1162,7 +1162,7 @@ }, { "cell_type": "markdown", - "id": "d1d78325", + "id": "853400dd", "metadata": {}, "source": [ "\n", @@ -1176,7 +1176,7 @@ }, { "cell_type": "markdown", - "id": "c296d6f7", + "id": "15f7a1e4", "metadata": {}, "source": [ "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" @@ -1184,7 +1184,7 @@ }, { "cell_type": "markdown", - "id": "916c22b8", + "id": "a7ff8c57", "metadata": {}, "source": [ "\n", @@ -1205,9 +1205,9 @@ "id": "b266cfb2", "metadata": {}, "source": [ - "**NOTE:** It is important to note that eq(11) and eq(12) are favorable to us as it gives the $\\mu^{'}$ and $\\sigma^{'}$ of the critical point of `f` as a function of known parameters $\\mu_{i,m}$, $\\sigma_{i,m}$, $\\mu_{j,m}$, $\\sigma_{j,m}$, $\\rho_{i,j}$, and $\\mu_{j,m+k}$. Therefore, we can calculate the lower-bound LB as a function of the aforementioned parameter. \n", + "**NOTE:** It is important to note that eq(11) and eq(12) are favorable to us as it gives the $\\mu^{'}$ and $\\sigma^{'}$ of the critical point of `f` as a function of known parameters $\\mu_{i,m}$, $\\sigma_{i,m}$, $\\mu_{j,m}$, $\\sigma_{j,m}$, $\\rho_{ij}$, and $\\mu_{j,m+k}$. Therefore, we can calculate the lower-bound LB as a function of the aforementioned parameter. \n", "\n", - "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho \\gt 0$. (We will discuss $\\rho \\leq 0$ later...)" + "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho_{ij} \\gt 0$. (We will discuss $\\rho_{ij} \\leq 0$ later...)" ] }, { @@ -1215,7 +1215,9 @@ "id": "a0e36dfc", "metadata": {}, "source": [ - "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. Note that we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. \n", + "\n", + "**NOTE:** we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" ] }, { @@ -1249,7 +1251,7 @@ "id": "7afe0a3d", "metadata": {}, "source": [ - "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(3)..." + "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(4)..." ] }, { @@ -1400,18 +1402,41 @@ " {- \\frac{1}{\\sigma_{j,m}} \n", " {\n", " \\left(\n", - " \\frac{(m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu^{'} \\cdot m\\mu_{j,m}}{\\sigma^{'}} \n", + " \\frac{(m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu^{'} \\cdot m\\mu_{j,m}}{\\sigma^{'}} \n", " - \n", - " \\frac{(m\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - \\mu_{j,m+k} \\cdot m\\mu_{j,m}}{\\sigma_{j,m}}\n", + " \\frac{(m\\rho_{jj}\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - \\mu_{j,m+k} \\cdot m\\mu_{j,m}}{\\sigma_{j,m}}\n", " \\right)\n", " }\n", " } \n", " \\\\\n", " ={}&\n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left[\n", + " \\frac{\n", + " m\\left(\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu^{'} \\cdot \\mu_{j,m}\n", + " \\right)\n", + " }{\n", + " \\sigma^{'}\n", + " } \n", + " - \n", + " \\frac{\n", + " m\\left(\n", + " 1\\cdot\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m+k} \\cdot \\mu_{j,m}\n", + " \\right)\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", " {\n", " \\left(\n", - " {\\sigma_{j,m}(\\rho\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{j,m}\\mu^{'})} \n", + " {\\sigma_{j,m}(\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{j,m}\\mu^{'})} \n", " - \n", " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right)\n", @@ -1422,7 +1447,7 @@ " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", " {\n", " \\left(\n", - " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} + \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \\mu_{j,m}\\sigma_{j,m}\\mu^{'}} \n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \\mu_{j,m}\\sigma_{j,m}\\mu^{'}} \n", " - \n", " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right)\n", @@ -1451,38 +1476,38 @@ "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", " {- \\frac{m}{\\sigma_{j,m}^{2}\n", - " (\\frac{\\sigma_{i,m}}{\\rho})\n", + " (\\frac{\\sigma_{i,m}}{\\rho_{ij}})\n", " } \n", " {\n", " \\left[\n", - " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} + \n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \n", " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \n", " \\mu_{j,m}\\sigma_{j,m}\\left({\n", - " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", " }\n", " \\right)} \n", " - \n", - " {(\\frac{\\sigma_{i,m}}{\\rho})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " {(\\frac{\\sigma_{i,m}}{\\rho_{ij}})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right]\n", " }\n", " } \n", " \\\\\n", " ={}&\n", - " {- \\frac{m\\rho}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {- \\frac{m\\rho_{ij}}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", " {\n", " \\left[\n", - " {\\rho\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", " + \n", " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", " - \n", " {\n", " \\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", " + \n", - " \\frac{\\sigma_{i,m}}{\\rho\\sigma_{j,m}}{\\mu_{j,m}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}{\\mu_{j,m}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", " }\n", " } \n", " - \n", - " {\\frac{\\sigma_{i,m}}{\\rho}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " {\\frac{\\sigma_{i,m}}{\\rho_{ij}}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", " \\right]\n", " }\n", " } \n", @@ -1491,12 +1516,12 @@ " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", " {\n", " \\left[\n", - " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", " + \n", - " \\rho\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", " - \n", " {\n", - " \\rho\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", " + \n", " \\mu_{j,m}\\sigma_{i,m}(\\mu_{j,m}-\\mu_{j,m+k})\n", " }\n", @@ -1511,12 +1536,12 @@ " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", " {\n", " \\left(\n", - " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", " + \n", - " \\rho\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", " - \n", " {\n", - " \\rho\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", " + \n", " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k}\n", " }\n", @@ -1530,7 +1555,7 @@ " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", " \\left( \n", - " {\\rho^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", " - \n", " \\sigma_{i,m}\\sigma_{j,m}^{2} \n", " }\n", @@ -1539,12 +1564,12 @@ " \\\\\n", " ={}&\n", " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", - " (\\rho^{2} - 1)\n", + " (\\rho_{ij}^{2} - 1)\n", " \\sigma_{i,m}\\sigma_{j,m}^{2}\n", " }\n", " \\\\\n", " ={}&\n", - " m(1-\\rho^{2})\n", + " m(1-\\rho_{ij}^{2})\n", "\\end{align} \n", "$$\n" ] @@ -1554,7 +1579,7 @@ "id": "64dc1027", "metadata": {}, "source": [ - "**Finally, with eq(1), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" + "**Finally, with eq(2), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" ] }, { @@ -1566,14 +1591,17 @@ "$$\n", "\\begin{align}\n", " LB ={}& \n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m (1 - \\rho^{2})} \\quad \\text{if} \\, \\rho > 0\n", + " \\frac{\n", + " \\sigma_{j,m}\n", + " }{\\sigma_{j,m+k}\n", + " } \\sqrt{m (1 - \\rho_{ij}^{2})} \\quad \\text{if} \\, \\rho > 0\n", " \\\\\n", "\\end{align}\n", "$$\n", "\n", "$$\n", "\\begin{align}\n", - " \\rho ={}& \n", + " \\rho_{ij} ={}& \n", " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", @@ -1586,10 +1614,10 @@ "metadata": {}, "source": [ "**Note:**
\n", - "* Note that eq(12) is valid only for $\\rho > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho > 0$. \n", + "* Note that eq(12) is valid only for $\\rho_{ij} > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho_{ij} > 0$. \n", "* The pearson correlation, $\\rho$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", - "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho)}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", + "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", "\n", "**Pending...**
\n", "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", From 1e2b64c1f67d9c7f83d073ba3d747bfab718a62d Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 01:00:13 -0600 Subject: [PATCH 25/67] Create Tutorial Notebook for VALMOD --- docs/Tutorial_VALMOD_notebook.ipynb | 178 ++++++++++++++++++++++++++++ 1 file changed, 178 insertions(+) create mode 100644 docs/Tutorial_VALMOD_notebook.ipynb diff --git a/docs/Tutorial_VALMOD_notebook.ipynb b/docs/Tutorial_VALMOD_notebook.ipynb new file mode 100644 index 000000000..86e244817 --- /dev/null +++ b/docs/Tutorial_VALMOD_notebook.ipynb @@ -0,0 +1,178 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c7a27406", + "metadata": {}, + "source": [ + "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", + "\n", + "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "0adbe18a", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import stumpy\n", + "from stumpy import core, config\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" + ] + }, + { + "cell_type": "markdown", + "id": "e9d48c97", + "metadata": {}, + "source": [ + "# 1- Introduction" + ] + }, + { + "cell_type": "markdown", + "id": "b0423978", + "metadata": {}, + "source": [ + "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m`. " + ] + }, + { + "cell_type": "markdown", + "id": "4a4af7fd", + "metadata": {}, + "source": [ + "## Motif discovery" + ] + }, + { + "cell_type": "markdown", + "id": "78ac5b0f", + "metadata": {}, + "source": [ + "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", + "\n", + "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "\n", + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." + ] + }, + { + "cell_type": "markdown", + "id": "7fc09927", + "metadata": {}, + "source": [ + "## Discord Discovery" + ] + }, + { + "cell_type": "markdown", + "id": "0f4ee615", + "metadata": {}, + "source": [ + "First, we need to provide a few definitions...\n", + "\n", + "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", + "\n", + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", + "\n", + "**NOTE**:
\n", + "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "37fdbb26", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "T = np.random.uniform(-100,100,size=3000)\n", + "m = 200\n", + "i, j = 100, 1500\n", + "\n", + "T[i:i+m] = 0\n", + "T[j:j+m] = 0\n", + "\n", + "plt.plot(T)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "cb3a3940", + "metadata": {}, + "source": [ + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", + "\n", + "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" + ] + }, + { + "cell_type": "markdown", + "id": "45eeecf5", + "metadata": {}, + "source": [ + "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", + "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + ] + }, + { + "cell_type": "markdown", + "id": "e503fb0a", + "metadata": {}, + "source": [ + "# 2-Lower Bound of Distance Profile" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "71517d38", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 3ed76c332f58d1acbe9275026f8706b7165e24a5 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 01:11:57 -0600 Subject: [PATCH 26/67] Removed old notebook --- docs/Tutorial_VALMOD.ipynb | 1658 ------------------------------------ 1 file changed, 1658 deletions(-) delete mode 100644 docs/Tutorial_VALMOD.ipynb diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb deleted file mode 100644 index bbe2edc09..000000000 --- a/docs/Tutorial_VALMOD.ipynb +++ /dev/null @@ -1,1658 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "482a2e9b", - "metadata": {}, - "source": [ - "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", - "\n", - "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "6534d116", - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "\n", - "import stumpy\n", - "from stumpy import core, config\n", - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" - ] - }, - { - "cell_type": "markdown", - "id": "1bc907ef", - "metadata": {}, - "source": [ - "# 1- Introduction" - ] - }, - { - "cell_type": "markdown", - "id": "aa1d847c", - "metadata": {}, - "source": [ - "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m` " - ] - }, - { - "cell_type": "markdown", - "id": "8c36e21f", - "metadata": {}, - "source": [ - "### Motif discovery" - ] - }, - { - "cell_type": "markdown", - "id": "fd1568ab", - "metadata": {}, - "source": [ - "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", - "\n", - "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", - "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." - ] - }, - { - "cell_type": "markdown", - "id": "c0455171", - "metadata": {}, - "source": [ - "### Discord discovery" - ] - }, - { - "cell_type": "markdown", - "id": "71cfdcf0", - "metadata": {}, - "source": [ - "First, we need to provide a few definitions..." - ] - }, - { - "cell_type": "markdown", - "id": "3826e0a5", - "metadata": {}, - "source": [ - "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", - "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
" - ] - }, - { - "cell_type": "markdown", - "id": "5167292f", - "metadata": {}, - "source": [ - "**NOTE**:
\n", - "Why should I care about $n^{th}$ discord (n>1)? We provide a simple example below:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "3d9db678", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "T = np.random.uniform(-100,100,size=3000)\n", - "m = 200\n", - "i, j = 100, 1500\n", - "\n", - "T[i:i+m] = 0\n", - "T[j:j+m] = 0\n", - "\n", - "plt.plot(T)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "a8e87bc0", - "metadata": {}, - "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", - "\n", - "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" - ] - }, - { - "cell_type": "markdown", - "id": "1be2fecb", - "metadata": {}, - "source": [ - "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." - ] - }, - { - "cell_type": "markdown", - "id": "27b8effd", - "metadata": {}, - "source": [ - "# 2- Lower-Bound Distance Profile" - ] - }, - { - "cell_type": "markdown", - "id": "5f999789", - "metadata": {}, - "source": [ - "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" - ] - }, - { - "cell_type": "markdown", - "id": "03836054", - "metadata": {}, - "source": [ - "In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" - ] - }, - { - "cell_type": "markdown", - "id": "3b5c8c5a", - "metadata": {}, - "source": [ - "## 2-1 Non-normalized distance" - ] - }, - { - "cell_type": "markdown", - "id": "1f7e294e", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " d^{(m+k)}_{j,i} ={}& \n", - " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m+k}{\n", - " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", - " }\\bigg\\rvert\n", - " }^{p}\n", - " }\n", - " \\\\\n", - " ={}&\n", - " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m}{\n", - " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", - " }\\bigg\\rvert\n", - " }^{p}\n", - " +\n", - " \\sum\\limits_{t=m+1}^{m+k}{\n", - " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", - " }\\bigg\\rvert\n", - " }^{p}\n", - " }\n", - " \\\\\n", - " \\geq{}&\n", - " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m}{\n", - " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", - " }\\bigg\\rvert\n", - " }^{p}\n", - " }\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "5a4d2b3a", - "metadata": {}, - "source": [ - "Therefore:" - ] - }, - { - "cell_type": "markdown", - "id": "dc578dbd", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " d^{(m+k)}_{j,i} \\geq{}&\n", - " d^{(m)}_{j,i}\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "b51f7143", - "metadata": {}, - "source": [ - "In other words, we can simply use the p-norm distance between $T_{i,m}$ and $T_{j,m}$ as the lower-bound value for the distance between $T_{i,m+k}$ and $T_{j,m+k}$." - ] - }, - { - "cell_type": "markdown", - "id": "0b539ca8", - "metadata": {}, - "source": [ - "## 2-2 Normalized distance" - ] - }, - { - "cell_type": "markdown", - "id": "91ab346f", - "metadata": {}, - "source": [ - "In z-normalized distance, one should note that $d^{(m+k)}_{j,i} \\geq d^{(m)}_{j,i}$ is not necessarily correct. In other words, the distance between two subsequences does not necessarily increase by making them longer. However, it seems there is a very nice relationship between $d_{j,i}^{(m)}$ and the lower-bound value of $d_{j,i}^{(m+k)}$." - ] - }, - { - "cell_type": "markdown", - "id": "d60acabc", - "metadata": {}, - "source": [ - "### Derving Equation (2)" - ] - }, - { - "cell_type": "markdown", - "id": "1d3734ed", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " d^{(m+k)}_{j,i} ={}& \n", - " \\sqrt{\\sum\\limits_{t=1}^{m+k}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", - " }^{2}}} \n", - " \\\\\n", - " d^{(m+k)}_{j,i} ={}& \n", - " \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", - " }^{2}}\n", - " +\n", - " \\sum\\limits_{t=m+1}^{m+k}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", - " }^{2}}\n", - " } \n", - " \\\\\n", - " \\geq{}&\n", - " \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", - " }^{2}}}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "72a47d5c", - "metadata": {}, - "source": [ - "So, the Lower-Bound (LB) value for $d_{j,i}^{(m+k)}$ can be obtained by minimizing the right-hand side:" - ] - }, - { - "cell_type": "markdown", - "id": "ade9e7e4", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " LB ={}& \n", - " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", - " }^{2}}} \n", - " \\\\\n", - " ={}&\n", - " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", - " \\left[\\frac{1}{\\sigma_{j,m+k}}\n", - " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", - " \\right)\n", - " \\right]\n", - " }^{2}}}\n", - " \\\\\n", - " ={}&\n", - " \\min \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left[\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m}}\n", - " \\frac{1}{\\sigma_{j,m+k}}\n", - " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", - " - \n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", - " \\right)\n", - " \\right]\n", - " }^{2}\n", - " }\n", - " }\n", - " \\\\\n", - " ={}&\n", - " \\min \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left[\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{j,m}\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", - " - \n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", - " \\right)\n", - " \\right]\n", - " }^{2}\n", - " }\n", - " }\n", - " \\\\\n", - " ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad(1)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "d410ec5a", - "metadata": {}, - "source": [ - "**Note:** that the unknown variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", - "\n", - "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$. Note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", - "\n", - "Also, we define $\\alpha_{t}$ as:" - ] - }, - { - "cell_type": "markdown", - "id": "327fbe20", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\alpha_{t} \\triangleq{}& \n", - " {\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", - " } \n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "6a8b3359", - "metadata": {}, - "source": [ - "Therefore, we have:" - ] - }, - { - "cell_type": "markdown", - "id": "a293197c", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " LB ={}& \n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{\\min f(\\mu^{'},\\sigma^{'})} \\quad (2)\n", - " \\\\\n", - " f(\\mu^{'}, \\sigma^{'}) ={}&\n", - " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (3)\n", - " \\\\\n", - " \\alpha_{t} ={}& \n", - " \\frac{\n", - " T[i+t-1] - \\mu^{'}\n", - " }{\n", - " \\sigma^{'}\n", - " } \n", - " - \n", - " \\frac{\n", - " T[j+t-1] - \\mu_{j,m+k}\n", - " }{\n", - " \\sigma_{j,m}\n", - " } \\quad (4)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "e7564257", - "metadata": {}, - "source": [ - "**To find extrema points, we first need to find the critical point(s) by solving the single system of equations below.** In other words, we are looking for $\\mu^{'}$ and $\\sigma^{'}$ that satisfies both equations below:\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "c2de39a8", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad (5)\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad (6)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "a3656f16", - "metadata": {}, - "source": [ - "**Solving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0$:**" - ] - }, - { - "cell_type": "markdown", - "id": "8b7c8a81", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", - " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\mu^{'}}}\n", - " }\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", - " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\mu^{'}}}\\alpha_{t}\n", - " }\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}&\n", - " \\sum \\limits_{t=1}^{m} {\n", - " 2\\left(\n", - " \\frac{-1}{\\sigma^{'}}\n", - " \\right)\n", - " \\alpha_{t}} \n", - " \\\\\n", - " 0 ={}&\n", - " \\frac{-2}{\\sigma^{'}}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "6ef98f3f", - "metadata": {}, - "source": [ - "Please note that $\\sigma^{'}$ is constant and thus it was factered out of the summation.
\n", - "This gives us:" - ] - }, - { - "cell_type": "markdown", - "id": "cdc74b21", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (7)\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "0aad71e0", - "metadata": {}, - "source": [ - "**Exapanding (7):**" - ] - }, - { - "cell_type": "markdown", - "id": "0d3f4dfa", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", - " 0\n", - " \\\\\n", - " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", - " 0\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", - " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) ={}& \n", - " 0\n", - " \\\\\n", - " \\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", - " 0 \\quad (8)\n", - "\\end{align} \n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "393ddb8f", - "metadata": {}, - "source": [ - "**Solving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0$:**" - ] - }, - { - "cell_type": "markdown", - "id": "4eae27d8", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", - " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\sigma^{'}}}\n", - " }\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", - " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\sigma^{'}}}\\alpha_{t}\n", - " }\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\sum \\limits_{t=1}^{m} {\n", - " 2 \\left(\n", - " \\frac{-\\left({T[i+t-1] - \\mu^{'}}\\right)}{\\sigma^{'2}}\n", - " \\right)\n", - " \\alpha_{t}} \n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1] - \\mu^{'}}\\right) \\alpha_{t}}\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1]\\alpha_{t} - \\mu^{'}\\alpha_{t}}\\right)}\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\n", - " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", - " - \n", - " \\sum \\limits_{t=1}^{m}{\\mu^{'}\\alpha_{t}}\n", - " \\right)\n", - " }\n", - " \\\\\n", - " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\n", - " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", - " - \n", - " \\mu^{'}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", - " \\right)\n", - " }\n", - " \\\\\n", - " 0 ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\n", - " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", - " - \n", - " \\mu^{'}\\cdot 0\n", - " \\right)\n", - " }\n", - " \\\\\n", - " 0 ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\n", - " {\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", - " }\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "c0924610", - "metadata": {}, - "source": [ - "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." - ] - }, - { - "cell_type": "markdown", - "id": "c3b80336", - "metadata": {}, - "source": [ - "And, this gives:" - ] - }, - { - "cell_type": "markdown", - "id": "c398718a", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", - " 0 \\quad (9)\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "4a34e737", - "metadata": {}, - "source": [ - "**Expanding (9):**" - ] - }, - { - "cell_type": "markdown", - "id": "de3f6023", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} T[i+t-1] \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "1ce7c9be", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", - " \\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}}\n", - " \\right)\n", - " - \n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", - " \\left(\n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", - " \\right)\n", - " ={}& 0\n", - " \\\\\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", - " \\left(\n", - " T[i+t-1] - \\mu^{'}\n", - " \\right)\n", - " - \n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", - " \\left(\n", - " T[j+t-1] - \\mu_{j,m+k}\n", - " \\right)\n", - " ={}& 0\n", - " \\\\\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", - " -\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]\\mu^{'}\n", - " \\right) \n", - " - \\\\\n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left(\n", - " {\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", - " -\\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}\n", - " }\n", - " \\right) \n", - " ={}& \n", - " 0\n", - " \\\\\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left(\n", - " \\sum \\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", - " -\n", - " \\mu^{'}\\sum\\limits_{t=1}^{m} T[i+t-1]\n", - " \\right) \n", - " - \\\\\n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1]\n", - " -\n", - " \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", - " \\right) \n", - " ={}& \n", - " 0 \\quad (*)\n", - "\\end{align} \n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "0c839937", - "metadata": {}, - "source": [ - "Now, recall that the pearson correlation $\\rho_{ij}$ between two subsequenes of lenght $m$ is defined as follows:" - ] - }, - { - "cell_type": "markdown", - "id": "82bc9b8e", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\rho_{ij} = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "4880c751", - "metadata": {}, - "source": [ - "Note: we can rearrange the pearson correlation equation as:
\n", - "$\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" - ] - }, - { - "cell_type": "markdown", - "id": "a01fd0cc", - "metadata": {}, - "source": [ - "**Therefore, with help of (\\*\\*), we continue our calculation from eq(\\*):**" - ] - }, - { - "cell_type": "markdown", - "id": "1543b1f4", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left[\n", - " \\left(\n", - " m\\rho_{ii}\\sigma_{i,m}\\sigma_{i,m} + m\\mu_{i,m}\\mu_{i,m}\n", - " \\right)\n", - " - \n", - " \\mu^{'} \\cdot m\\mu_{i,m}\n", - " \\right] \n", - " - \n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left[\n", - " \\left(\n", - " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " + \n", - " m\\mu_{i,m}\\mu_{j,m}\n", - " \\right)\n", - " - \n", - " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", - " \\right]\n", - " ={}& 0\n", - " \\\\\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left[\n", - " \\left(\n", - " m\\cdot1\\cdot\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}\n", - " \\right)\n", - " - \n", - " \\mu^{'} \\cdot m\\mu_{i,m}\n", - " \\right] \n", - " - \n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left[\n", - " \\left(\n", - " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " + \n", - " m\\mu_{i,m}\\mu_{j,m}\n", - " \\right)\n", - " - \n", - " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", - " \\right]\n", - " ={}& 0\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "041482b8", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\frac{1}{\\sigma^{'}\\sigma_{j,m}}\n", - " \\left[\n", - " \\sigma_{j,m}\\left(\n", - " m\\sigma_{i,m}^{2} \n", - " + \n", - " m\\mu_{i,m}^{2} \n", - " - \n", - " \\mu^{'} \\cdot m\\mu_{i,m}\n", - " \\right) \n", - " - \n", - " \\sigma^{'}\\left(\n", - " {m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " +\n", - " m\\mu_{i,m}\\mu_{j,m} \n", - " -\n", - " \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\n", - " \\right)\n", - " \\right] ={}& 0\n", - " \\\\\n", - " \\frac{m}{\n", - " \\sigma^{'}\\sigma_{j,m}\n", - " }\n", - " \\left[\n", - " \\sigma_{j,m}\\left(\n", - " \\sigma_{i,m}^{2} \n", - " + \n", - " \\mu_{i,m}^{2} \n", - " - \n", - " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", - " - \n", - " \\sigma^{'}\\left(\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " +\n", - " \\mu_{i,m}\\mu_{j,m}\n", - " -\n", - " \\mu_{j,m+k} \\mu_{i,m}}\n", - " \\right)\n", - " \\right]\n", - " ={}& 0\n", - " \\\\\n", - " \\sigma_{j,m}\\left(\n", - " \\sigma_{i,m}^{2} \n", - " + \n", - " \\mu_{i,m}^{2} \n", - " - \n", - " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", - " - \n", - " \\sigma^{'}\\left(\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " +\n", - " \\mu_{i,m}\\mu_{j,m}\n", - " -\n", - " \\mu_{j,m+k} \\mu_{i,m}}\n", - " \\right)\n", - " ={}& 0\n", - " \\\\\n", - " \\sigma_{j,m}\\left(\n", - " \\sigma_{i,m}^{2} \n", - " + \n", - " \\mu_{i,m}^{2}\n", - " \\right)\n", - " - \n", - " \\sigma_{j,m}\\left(\n", - " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", - " - \n", - " \\sigma^{'}\\left(\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " +\n", - " \\mu_{i,m}\\mu_{j,m}\n", - " -\n", - " \\mu_{j,m+k} \\mu_{i,m}}\n", - " \\right)\n", - " ={}& 0\n", - " \\\\\n", - " - \\sigma_{j,m}\\left(\n", - " \\sigma_{i,m}^{2} \n", - " + \n", - " \\mu_{i,m}^{2}\n", - " \\right)\n", - " + \n", - " \\sigma_{j,m}\\left(\n", - " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", - " + \n", - " \\sigma^{'}\\left(\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", - " +\n", - " \\mu_{i,m}\\mu_{j,m}\n", - " -\n", - " \\mu_{j,m+k} \\mu_{i,m}}\n", - " \\right)\n", - " ={}& 0\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "1d37830b", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (10)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "53f8c4b4", - "metadata": {}, - "source": [ - "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." - ] - }, - { - "cell_type": "markdown", - "id": "6adaea06", - "metadata": {}, - "source": [ - "**Now, it is time to solve equations (8) and (10), provided below:**" - ] - }, - { - "cell_type": "markdown", - "id": "9d89eca8", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "\\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} \n", - " ={}& 0 \\quad(8)\n", - " \\\\\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", - " ={}& 0 \\quad(10)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "44d1afe8", - "metadata": {}, - "source": [ - "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." - ] - }, - { - "cell_type": "markdown", - "id": "35c4e371", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "-\\mu_{i,m}\\left[\n", - " \\sigma_{j,m} \\mu^{'} \n", - " + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} \n", - " - \n", - " \\sigma_{j,m}\\mu_{i,m} \n", - " \\right]\n", - " ={}& 0 \\quad(8')\n", - " \\\\\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", - " ={}& 0 \\quad(10)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "5cb0edfe", - "metadata": {}, - "source": [ - "$(8')+(10)$ gives:" - ] - }, - { - "cell_type": "markdown", - "id": "0e192a68", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "-\\mu_{i,m}\\sigma_{j,m} \\mu^{'} - \n", - " \\mu_{i,m}\\mu_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} \n", - " + \\sigma_{j,m}\\mu_{i,m}^{2} +\n", - " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m}\\sigma^{'} - \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m}^{2} - \\sigma_{j,m}\\sigma_{i,m}^{2}\n", - " ={}& 0\n", - " \\\\\n", - " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} - \\sigma_{j,m}\\sigma_{i,m}^{2} \n", - " ={}& 0\n", - " \\\\\n", - " \\sigma_{i,m}\\sigma_{j,m}\n", - " \\left(\n", - " \\rho_{ij}\\sigma^{'} - \\sigma_{i,m}\n", - " \\right)\n", - " ={}&\n", - " 0\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "02003455", - "metadata": {}, - "source": [ - "Hence:" - ] - }, - { - "cell_type": "markdown", - "id": "70c325aa", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "e087b39f", - "metadata": {}, - "source": [ - "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." - ] - }, - { - "cell_type": "markdown", - "id": "024639e5", - "metadata": {}, - "source": [ - "And, subsituting eq(11) in eq(8):" - ] - }, - { - "cell_type": "markdown", - "id": "631d7d57", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "\\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", - " ={}& 0 \n", - " \\\\\n", - " \\frac{1}{\\sigma_{j,m}}\\left[\n", - " \\sigma_{j,m} \\mu^{'} + \n", - " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", - " \\right]\n", - " ={}& 0 \n", - " \\\\\n", - " \\mu^{'} + \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}) - \\mu_{i,m} \n", - " ={}& 0 \n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "a745e0a1", - "metadata": {}, - "source": [ - "Hence:" - ] - }, - { - "cell_type": "markdown", - "id": "853400dd", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", - "\\end{align}\n", - "$$\n", - " " - ] - }, - { - "cell_type": "markdown", - "id": "15f7a1e4", - "metadata": {}, - "source": [ - "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" - ] - }, - { - "cell_type": "markdown", - "id": "a7ff8c57", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\sigma^{'} ={}& \n", - " \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", - " \\\\\n", - " \\mu^{'} ={}& \n", - " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "b266cfb2", - "metadata": {}, - "source": [ - "**NOTE:** It is important to note that eq(11) and eq(12) are favorable to us as it gives the $\\mu^{'}$ and $\\sigma^{'}$ of the critical point of `f` as a function of known parameters $\\mu_{i,m}$, $\\sigma_{i,m}$, $\\mu_{j,m}$, $\\sigma_{j,m}$, $\\rho_{ij}$, and $\\mu_{j,m+k}$. Therefore, we can calculate the lower-bound LB as a function of the aforementioned parameter. \n", - "\n", - "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho_{ij} \\gt 0$. (We will discuss $\\rho_{ij} \\leq 0$ later...)" - ] - }, - { - "cell_type": "markdown", - "id": "a0e36dfc", - "metadata": {}, - "source": [ - "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. \n", - "\n", - "**NOTE:** we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" - ] - }, - { - "cell_type": "markdown", - "id": "92abd2a2", - "metadata": {}, - "source": [ - "**Start with equation (3):**" - ] - }, - { - "cell_type": "markdown", - "id": "b51d32b2", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f(\\mu^{'},\\sigma^{'}) ={}&\n", - " \\sum \\limits_{t=1}^{m}\\alpha_{t}^{2}\n", - " \\\\\n", - " ={}&\n", - " \\sum \\limits_{t=1}^{m}\\alpha_{t} \\cdot \\alpha_{t}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "7afe0a3d", - "metadata": {}, - "source": [ - "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(4)..." - ] - }, - { - "cell_type": "markdown", - "id": "bfb10bce", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", - " \\sum\\limits_{t=1}^{m}{\n", - " {\\alpha_{t}\n", - " \\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", - " \\right)\n", - " }}\n", - " \\\\\n", - " ={}&\n", - " {\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]\\alpha_{t} \n", - " - \n", - " \\sum\\limits_{t=1}^{m}\n", - " \\mu^{'}\\alpha_{t}\n", - " \\right)\n", - " - \\frac{1}{\\sigma_{j,m}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[j+t-1]\\alpha_{t} \n", - " - \n", - " \\sum\\limits_{t=1}^{m}\n", - " \\mu_{j,m+k}\\alpha_{t}\n", - " \\right)\n", - " } \n", - " \\\\ \n", - " ={}&\n", - " {\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]\\alpha_{t} \n", - " - \n", - " \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", - " \\right)\n", - " - \n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} \n", - " - \n", - " \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", - " \\right)\n", - " } \n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "4a9e3f03", - "metadata": {}, - "source": [ - "And, now with help of eq(7), $\\sum\\limits_{t=1}^{m}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}}=0$, we will have:" - ] - }, - { - "cell_type": "markdown", - "id": "650cae87", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", - " {\n", - " \\frac{1}{\\sigma^{'}}\n", - " \\left(\n", - " 0 - \\mu^{'} \\cdot 0\n", - " \\right) \n", - " - \n", - " \\frac{1}{\\sigma_{j,m}}\n", - " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0\n", - " \\right)\n", - " } \n", - " \\\\ \n", - " ={}&\n", - " {\n", - " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t}\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {\n", - " - \\frac{1}{\\sigma_{j,m}} \n", - " \\sum\\limits_{t=1}^{m}{\\left[\n", - " T[j+t-1]\\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", - " \\right)\n", - " \\right]\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {\n", - " - \\frac{1}{\\sigma_{j,m}} \n", - " \\sum\\limits_{t=1}^{m}{\n", - " \\left(\n", - " \\frac{T[i+t-1]T[j+t-1] - \\mu^{'}T[j+t-1]}{\\sigma^{'}} - \\frac{T[j+t-1]T[j+t-1] - \\mu_{j,m+k}T[j+t-1]}{\\sigma_{j,m}}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{1}{\\sigma_{j,m}} \n", - " {\n", - " \\left(\n", - " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu^{'}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma^{'}} \n", - " - \n", - " \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma_{j,m}}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "9f2ca2da", - "metadata": {}, - "source": [ - "And, now with help of the fact that $\\sum{T} = m\\mu$ and also the Pearon Correlation equation (\\*\\*)..." - ] - }, - { - "cell_type": "markdown", - "id": "35db152a", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " {- \\frac{1}{\\sigma_{j,m}} \n", - " {\n", - " \\left(\n", - " \\frac{(m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu^{'} \\cdot m\\mu_{j,m}}{\\sigma^{'}} \n", - " - \n", - " \\frac{(m\\rho_{jj}\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - \\mu_{j,m+k} \\cdot m\\mu_{j,m}}{\\sigma_{j,m}}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{1}{\\sigma_{j,m}} \n", - " {\n", - " \\left[\n", - " \\frac{\n", - " m\\left(\n", - " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu^{'} \\cdot \\mu_{j,m}\n", - " \\right)\n", - " }{\n", - " \\sigma^{'}\n", - " } \n", - " - \n", - " \\frac{\n", - " m\\left(\n", - " 1\\cdot\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m+k} \\cdot \\mu_{j,m}\n", - " \\right)\n", - " }{\n", - " \\sigma_{j,m}\n", - " }\n", - " \\right]\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", - " {\n", - " \\left(\n", - " {\\sigma_{j,m}(\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{j,m}\\mu^{'})} \n", - " - \n", - " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", - " {\n", - " \\left(\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \\mu_{j,m}\\sigma_{j,m}\\mu^{'}} \n", - " - \n", - " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "cfd5a617", - "metadata": {}, - "source": [ - "And, now we are at a good position to plug in the values $\\mu^{'}$(11) and $\\sigma^{'}$(12):" - ] - }, - { - "cell_type": "markdown", - "id": "f3e25620", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\n", - " (\\frac{\\sigma_{i,m}}{\\rho_{ij}})\n", - " } \n", - " {\n", - " \\left[\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \n", - " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \n", - " \\mu_{j,m}\\sigma_{j,m}\\left({\n", - " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", - " }\n", - " \\right)} \n", - " - \n", - " {(\\frac{\\sigma_{i,m}}{\\rho_{ij}})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right]\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m\\rho_{ij}}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", - " {\n", - " \\left[\n", - " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", - " + \n", - " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", - " - \n", - " {\n", - " \\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", - " + \n", - " \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}{\\mu_{j,m}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", - " }\n", - " } \n", - " - \n", - " {\\frac{\\sigma_{i,m}}{\\rho_{ij}}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right]\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", - " {\n", - " \\left[\n", - " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", - " + \n", - " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", - " - \n", - " {\n", - " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", - " + \n", - " \\mu_{j,m}\\sigma_{i,m}(\\mu_{j,m}-\\mu_{j,m+k})\n", - " }\n", - " } \n", - " - \n", - " {\\sigma_{i,m}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", - " \\right]\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", - " {\n", - " \\left(\n", - " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", - " + \n", - " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", - " - \n", - " {\n", - " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", - " + \n", - " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k}\n", - " }\n", - " }\n", - " - \n", - " {\\sigma_{i,m}\\sigma_{j,m}^{2} - \\sigma_{i,m}\\mu_{j,m}^{2} + \\sigma_{i,m}\\mu_{j,m}\\mu_{j,m+k}}\n", - " \\right)\n", - " }\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", - " \\left( \n", - " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", - " - \n", - " \\sigma_{i,m}\\sigma_{j,m}^{2} \n", - " }\n", - " \\right)\n", - " } \n", - " \\\\\n", - " ={}&\n", - " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", - " (\\rho_{ij}^{2} - 1)\n", - " \\sigma_{i,m}\\sigma_{j,m}^{2}\n", - " }\n", - " \\\\\n", - " ={}&\n", - " m(1-\\rho_{ij}^{2})\n", - "\\end{align} \n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "64dc1027", - "metadata": {}, - "source": [ - "**Finally, with eq(2), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" - ] - }, - { - "cell_type": "markdown", - "id": "98db40a5", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " LB ={}& \n", - " \\frac{\n", - " \\sigma_{j,m}\n", - " }{\\sigma_{j,m+k}\n", - " } \\sqrt{m (1 - \\rho_{ij}^{2})} \\quad \\text{if} \\, \\rho > 0\n", - " \\\\\n", - "\\end{align}\n", - "$$\n", - "\n", - "$$\n", - "\\begin{align}\n", - " \\rho_{ij} ={}& \n", - " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "8cbad624", - "metadata": {}, - "source": [ - "**Note:**
\n", - "* Note that eq(12) is valid only for $\\rho_{ij} > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho_{ij} > 0$. \n", - "* The pearson correlation, $\\rho$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", - "\n", - "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", - "\n", - "**Pending...**
\n", - "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", - "\n", - "* **For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$.**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "448cd8ce", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 9d8753810d6d1ab2f3e77612ad8a706b92765383 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 01:12:29 -0600 Subject: [PATCH 27/67] ADD new notebook for deriving equation in VALMOD --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 1507 +++++++++++++++++ 1 file changed, 1507 insertions(+) create mode 100644 docs/LowerBound_Dist_Profile_Derivation.ipynb diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb new file mode 100644 index 000000000..09d5202ca --- /dev/null +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -0,0 +1,1507 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3b23610b", + "metadata": {}, + "source": [ + "In this notebook, we would like to derive the eq(2) of the paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf)." + ] + }, + { + "cell_type": "markdown", + "id": "5f999789", + "metadata": {}, + "source": [ + "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" + ] + }, + { + "cell_type": "markdown", + "id": "03836054", + "metadata": {}, + "source": [ + "In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" + ] + }, + { + "cell_type": "markdown", + "id": "3b5c8c5a", + "metadata": {}, + "source": [ + "## 2-1 Non-normalized distance" + ] + }, + { + "cell_type": "markdown", + "id": "1f7e294e", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m+k}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " +\n", + " \\sum\\limits_{t=m+1}^{m+k}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + " \\geq{}&\n", + " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\bigg\\lvert{\n", + " T[i+t-1] - T[j+t-1]\n", + " }\\bigg\\rvert\n", + " }^{p}\n", + " }\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "5a4d2b3a", + "metadata": {}, + "source": [ + "Therefore:" + ] + }, + { + "cell_type": "markdown", + "id": "dc578dbd", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " d^{(m+k)}_{j,i} \\geq{}&\n", + " d^{(m)}_{j,i}\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "b51f7143", + "metadata": {}, + "source": [ + "In other words, we can simply use the p-norm distance between $T_{i,m}$ and $T_{j,m}$ as the lower-bound value for the distance between $T_{i,m+k}$ and $T_{j,m+k}$." + ] + }, + { + "cell_type": "markdown", + "id": "0b539ca8", + "metadata": {}, + "source": [ + "## 2-2 Normalized distance" + ] + }, + { + "cell_type": "markdown", + "id": "91ab346f", + "metadata": {}, + "source": [ + "In z-normalized distance, one should note that $d^{(m+k)}_{j,i} \\geq d^{(m)}_{j,i}$ is not necessarily correct. In other words, the distance between two subsequences does not necessarily increase by making them longer. However, it seems there is a very nice relationship between $d_{j,i}^{(m)}$ and the lower-bound value of $d_{j,i}^{(m+k)}$." + ] + }, + { + "cell_type": "markdown", + "id": "d60acabc", + "metadata": {}, + "source": [ + "### Derving Equation (2)" + ] + }, + { + "cell_type": "markdown", + "id": "1d3734ed", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt{\\sum\\limits_{t=1}^{m+k}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}} \n", + " \\\\\n", + " d^{(m+k)}_{j,i} ={}& \n", + " \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}\n", + " +\n", + " \\sum\\limits_{t=m+1}^{m+k}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}\n", + " } \n", + " \\\\\n", + " \\geq{}&\n", + " \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "72a47d5c", + "metadata": {}, + "source": [ + "So, the Lower-Bound (LB) value for $d_{j,i}^{(m+k)}$ can be obtained by minimizing the right-hand side:" + ] + }, + { + "cell_type": "markdown", + "id": "ade9e7e4", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " LB ={}& \n", + " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " }^{2}}} \n", + " \\\\\n", + " ={}&\n", + " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\left[\\frac{1}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\right)\n", + " \\right]\n", + " }^{2}}}\n", + " \\\\\n", + " ={}&\n", + " \\min \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left[\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m}}\n", + " \\frac{1}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " - \n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\right)\n", + " \\right]\n", + " }^{2}\n", + " }\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\min \\sqrt{\n", + " \\sum\\limits_{t=1}^{m}{{\n", + " \\left[\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{j,m}\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " - \n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " \\right]\n", + " }^{2}\n", + " }\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad(1)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "d410ec5a", + "metadata": {}, + "source": [ + "**Note:** that the unknown variables are $\\mu_{i,m+k}$ and $\\sigma_{i,m+k}$. Also, note that all $\\mu$ and $\\sigma$ values are **constant** regardless of them being known or unknown.
\n", + "\n", + "We subtitute $\\mu_{i,m+k}$ with $\\mu^{'}$, and $\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}$ with $\\sigma^{'}$. Note that the unknown variables are now $\\mu^{'}$ and $\\sigma^{'}$.
\n", + "\n", + "Also, we define $\\alpha_{t}$ as:" + ] + }, + { + "cell_type": "markdown", + "id": "8a778de1", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\alpha_{t} \\triangleq{}& \n", + " {\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " } \n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "18656992", + "metadata": {}, + "source": [ + "Therefore, we have:" + ] + }, + { + "cell_type": "markdown", + "id": "a293197c", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " LB ={}& \n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\sqrt{\\min f(\\mu^{'},\\sigma^{'})} \\quad (2)\n", + " \\\\\n", + " f(\\mu^{'}, \\sigma^{'}) ={}&\n", + " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (3)\n", + " \\\\\n", + " \\alpha_{t} ={}& \n", + " \\frac{\n", + " T[i+t-1] - \\mu^{'}\n", + " }{\n", + " \\sigma^{'}\n", + " } \n", + " - \n", + " \\frac{\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " } \\quad (4)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "e7564257", + "metadata": {}, + "source": [ + "**To find extrema points, we first need to find the critical point(s) by solving the single system of equations below.** In other words, we are looking for $\\mu^{'}$ and $\\sigma^{'}$ that satisfies both equations below:\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "c2de39a8", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0 \\quad (5)\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0 \\quad (6)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "a3656f16", + "metadata": {}, + "source": [ + "**Solving $\\frac{\\partial{f}}{\\partial{\\mu^{'}}} = 0$:**" + ] + }, + { + "cell_type": "markdown", + "id": "8b7c8a81", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\mu^{'}}}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\mu^{'}}}\\alpha_{t}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}&\n", + " \\sum \\limits_{t=1}^{m} {\n", + " 2\\left(\n", + " \\frac{-1}{\\sigma^{'}}\n", + " \\right)\n", + " \\alpha_{t}} \n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'}}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "6ef98f3f", + "metadata": {}, + "source": [ + "Please note that $\\sigma^{'}$ is constant and thus it was factered out of the summation.
\n", + "This gives us:" + ] + }, + { + "cell_type": "markdown", + "id": "cdc74b21", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (7)\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "0aad71e0", + "metadata": {}, + "source": [ + "**Exapanding (7):**" + ] + }, + { + "cell_type": "markdown", + "id": "0d3f4dfa", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", + " 0\n", + " \\\\\n", + " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", + " 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(m\\mu_{j,m} - m\\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\\mu_{i,m} - \\mu^{'}\\right) - \n", + " \\sigma^{'}\\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) ={}& \n", + " 0\n", + " \\\\\n", + " \\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} ={}& \n", + " 0 \\quad (8)\n", + "\\end{align} \n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "393ddb8f", + "metadata": {}, + "source": [ + "**Solving $\\frac{\\partial{f}}{\\partial{\\sigma^{'}}} = 0$:**" + ] + }, + { + "cell_type": "markdown", + "id": "4eae27d8", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\sigma^{'}}}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", + " \\sum \\limits_{t=1}^{m}{\n", + " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\sigma^{'}}}\\alpha_{t}\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\sum \\limits_{t=1}^{m} {\n", + " 2 \\left(\n", + " \\frac{-\\left({T[i+t-1] - \\mu^{'}}\\right)}{\\sigma^{'2}}\n", + " \\right)\n", + " \\alpha_{t}} \n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1] - \\mu^{'}}\\right) \\alpha_{t}}\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1]\\alpha_{t} - \\mu^{'}\\alpha_{t}}\\right)}\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\sum \\limits_{t=1}^{m}{\\mu^{'}\\alpha_{t}}\n", + " \\right)\n", + " }\n", + " \\\\\n", + " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\mu^{'}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\right)\n", + " }\n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\\left(\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " - \n", + " \\mu^{'}\\cdot 0\n", + " \\right)\n", + " }\n", + " \\\\\n", + " 0 ={}&\n", + " \\frac{-2}{\\sigma^{'2}}\n", + " {\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " }\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "c6084fa1", + "metadata": {}, + "source": [ + "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." + ] + }, + { + "cell_type": "markdown", + "id": "c3b80336", + "metadata": {}, + "source": [ + "And, this gives:" + ] + }, + { + "cell_type": "markdown", + "id": "c398718a", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", + " 0 \\quad (9)\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4a34e737", + "metadata": {}, + "source": [ + "**Expanding (9):**" + ] + }, + { + "cell_type": "markdown", + "id": "de3f6023", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum \\limits_{t=1}^{m} T[i+t-1] \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "1ce7c9be", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}}\n", + " \\right)\n", + " - \n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " T[i+t-1] - \\mu^{'}\n", + " \\right)\n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\left(\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " -\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]\\mu^{'}\n", + " \\right) \n", + " - \\\\\n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " {\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", + " -\\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}\n", + " }\n", + " \\right) \n", + " ={}& \n", + " 0\n", + " \\\\\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum \\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " -\n", + " \\mu^{'}\\sum\\limits_{t=1}^{m} T[i+t-1]\n", + " \\right) \n", + " - \\\\\n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1]\n", + " -\n", + " \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " \\right) \n", + " ={}& \n", + " 0 \\quad (*)\n", + "\\end{align} \n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "0c839937", + "metadata": {}, + "source": [ + "Now, recall that the pearson correlation $\\rho_{ij}$ between two subsequenes of lenght $m$ is defined as follows:" + ] + }, + { + "cell_type": "markdown", + "id": "82bc9b8e", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\rho_{ij} = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4880c751", + "metadata": {}, + "source": [ + "Note: we can rearrange the pearson correlation equation as:
\n", + "$\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" + ] + }, + { + "cell_type": "markdown", + "id": "a01fd0cc", + "metadata": {}, + "source": [ + "**Therefore, with help of (\\*\\*), we continue our calculation from eq(\\*):**" + ] + }, + { + "cell_type": "markdown", + "id": "1543b1f4", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left[\n", + " \\left(\n", + " m\\rho_{ii}\\sigma_{i,m}\\sigma_{i,m} + m\\mu_{i,m}\\mu_{i,m}\n", + " \\right)\n", + " - \n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", + " \\right] \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left[\n", + " \\left(\n", + " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " + \n", + " m\\mu_{i,m}\\mu_{j,m}\n", + " \\right)\n", + " - \n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", + " \\right]\n", + " ={}& 0\n", + " \\\\\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left[\n", + " \\left(\n", + " m\\cdot1\\cdot\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}\n", + " \\right)\n", + " - \n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", + " \\right] \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left[\n", + " \\left(\n", + " m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " + \n", + " m\\mu_{i,m}\\mu_{j,m}\n", + " \\right)\n", + " - \n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", + " \\right]\n", + " ={}& 0\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4c6d53dd", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{1}{\\sigma^{'}\\sigma_{j,m}}\n", + " \\left[\n", + " \\sigma_{j,m}\\left(\n", + " m\\sigma_{i,m}^{2} \n", + " + \n", + " m\\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'} \\cdot m\\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " m\\mu_{i,m}\\mu_{j,m} \n", + " -\n", + " \\mu_{j,m+k} \\cdot m\\mu_{i,m}}\n", + " \\right)\n", + " \\right] ={}& 0\n", + " \\\\\n", + " \\frac{m}{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\left[\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " \\right]\n", + " ={}& 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2} \n", + " - \n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2}\n", + " \\right)\n", + " - \n", + " \\sigma_{j,m}\\left(\n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " - \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", + " \\\\\n", + " - \\sigma_{j,m}\\left(\n", + " \\sigma_{i,m}^{2} \n", + " + \n", + " \\mu_{i,m}^{2}\n", + " \\right)\n", + " + \n", + " \\sigma_{j,m}\\left(\n", + " \\mu^{'} \\mu_{i,m}\n", + " \\right) \n", + " + \n", + " \\sigma^{'}\\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", + " +\n", + " \\mu_{i,m}\\mu_{j,m}\n", + " -\n", + " \\mu_{j,m+k} \\mu_{i,m}}\n", + " \\right)\n", + " ={}& 0\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "1d37830b", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) = 0 \\quad (10)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "f9a99369", + "metadata": {}, + "source": [ + "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." + ] + }, + { + "cell_type": "markdown", + "id": "6adaea06", + "metadata": {}, + "source": [ + "**Now, it is time to solve equations (8) and (10), provided below:**" + ] + }, + { + "cell_type": "markdown", + "id": "7878d61c", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m} \n", + " ={}& 0 \\quad(8)\n", + " \\\\\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", + " ={}& 0 \\quad(10)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "ff88e0e5", + "metadata": {}, + "source": [ + "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." + ] + }, + { + "cell_type": "markdown", + "id": "5fd91d3d", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "-\\mu_{i,m}\\left[\n", + " \\sigma_{j,m} \\mu^{'} \n", + " + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)\\sigma^{'} \n", + " - \n", + " \\sigma_{j,m}\\mu_{i,m} \n", + " \\right]\n", + " ={}& 0 \\quad(8')\n", + " \\\\\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + (\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{i,m}\\mu_{j,m+k})\\sigma^{'} - \\sigma_{j,m}(\\mu_{i,m}^{2} + \\sigma_{i,m}^{2}) \n", + " ={}& 0 \\quad(10)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "5b103a95", + "metadata": {}, + "source": [ + "$(8')+(10)$ gives:" + ] + }, + { + "cell_type": "markdown", + "id": "99e96a66", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "-\\mu_{i,m}\\sigma_{j,m} \\mu^{'} - \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} \n", + " + \\sigma_{j,m}\\mu_{i,m}^{2} +\n", + " \\mu_{i,m}\\sigma_{j,m}\\mu^{'} + \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} + \\mu_{i,m}\\mu_{j,m}\\sigma^{'} - \\mu_{i,m}\\mu_{j,m+k}\\sigma^{'} - \\sigma_{j,m}\\mu_{i,m}^{2} - \\sigma_{j,m}\\sigma_{i,m}^{2}\n", + " ={}& 0\n", + " \\\\\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}\\sigma^{'} - \\sigma_{j,m}\\sigma_{i,m}^{2} \n", + " ={}& 0\n", + " \\\\\n", + " \\sigma_{i,m}\\sigma_{j,m}\n", + " \\left(\n", + " \\rho_{ij}\\sigma^{'} - \\sigma_{i,m}\n", + " \\right)\n", + " ={}&\n", + " 0\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "bb19c9d4", + "metadata": {}, + "source": [ + "Hence:" + ] + }, + { + "cell_type": "markdown", + "id": "3675507e", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sigma^{'} = \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "11ce066e", + "metadata": {}, + "source": [ + "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." + ] + }, + { + "cell_type": "markdown", + "id": "21f83530", + "metadata": {}, + "source": [ + "And, subsituting eq(11) in eq(8):" + ] + }, + { + "cell_type": "markdown", + "id": "631d7d57", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", + " ={}& 0 \n", + " \\\\\n", + " \\frac{1}{\\sigma_{j,m}}\\left[\n", + " \\sigma_{j,m} \\mu^{'} + \n", + " \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}}) - \\sigma_{j,m}\\mu_{i,m} \n", + " \\right]\n", + " ={}& 0 \n", + " \\\\\n", + " \\mu^{'} + \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right)(\\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}) - \\mu_{i,m} \n", + " ={}& 0 \n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "c6c67de5", + "metadata": {}, + "source": [ + "Hence:" + ] + }, + { + "cell_type": "markdown", + "id": "2aa3b77a", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\mu^{'} = \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", + "\\end{align}\n", + "$$\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "cb7cdb37", + "metadata": {}, + "source": [ + "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" + ] + }, + { + "cell_type": "markdown", + "id": "e87fc766", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\sigma^{'} ={}& \n", + " \\frac{\\sigma_{i,m}}{\\rho_{ij}} \\quad (11)\n", + " \\\\\n", + " \\mu^{'} ={}& \n", + " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}} \\left(\\mu_{j,m} - \\mu_{j,m+k}\\right) \\quad(12)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "b266cfb2", + "metadata": {}, + "source": [ + "**NOTE:** It is important to note that eq(11) and eq(12) are favorable to us as they give the $\\mu^{'}$ and $\\sigma^{'}$ of the critical point of `f` as a function of known parameters $\\mu_{i,m}$, $\\sigma_{i,m}$, $\\mu_{j,m}$, $\\sigma_{j,m}$, $\\rho_{ij}$, and $\\mu_{j,m+k}$. Therefore, we can calculate the lower-bound LB as a function of the aforementioned parameters. \n", + "\n", + "**NOTE:** It is worthwhile to reiterate the fact that the solution is valid when $\\rho_{ij} \\gt 0$. (We will discuss $\\rho_{ij} \\leq 0$ later...)" + ] + }, + { + "cell_type": "markdown", + "id": "a0e36dfc", + "metadata": {}, + "source": [ + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. \n", + "\n", + "**NOTE:** we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" + ] + }, + { + "cell_type": "markdown", + "id": "92abd2a2", + "metadata": {}, + "source": [ + "**Start with equation (3):**" + ] + }, + { + "cell_type": "markdown", + "id": "b51d32b2", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f(\\mu^{'},\\sigma^{'}) ={}&\n", + " \\sum \\limits_{t=1}^{m}\\alpha_{t}^{2}\n", + " \\\\\n", + " ={}&\n", + " \\sum \\limits_{t=1}^{m}\\alpha_{t} \\cdot \\alpha_{t}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "7afe0a3d", + "metadata": {}, + "source": [ + "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(4)..." + ] + }, + { + "cell_type": "markdown", + "id": "bfb10bce", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", + " \\sum\\limits_{t=1}^{m}{\n", + " {\\alpha_{t}\n", + " \\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " }}\n", + " \\\\\n", + " ={}&\n", + " {\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]\\alpha_{t} \n", + " - \n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu^{'}\\alpha_{t}\n", + " \\right)\n", + " - \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[j+t-1]\\alpha_{t} \n", + " - \n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu_{j,m+k}\\alpha_{t}\n", + " \\right)\n", + " } \n", + " \\\\ \n", + " ={}&\n", + " {\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]\\alpha_{t} \n", + " - \n", + " \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\right)\n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} \n", + " - \n", + " \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\right)\n", + " } \n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4a9e3f03", + "metadata": {}, + "source": [ + "And, now with help of eq(7), $\\sum\\limits_{t=1}^{m}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}}=0$, we will have:" + ] + }, + { + "cell_type": "markdown", + "id": "650cae87", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", + " {\n", + " \\frac{1}{\\sigma^{'}}\n", + " \\left(\n", + " 0 - \\mu^{'} \\cdot 0\n", + " \\right) \n", + " - \n", + " \\frac{1}{\\sigma_{j,m}}\n", + " \\left(\n", + " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0\n", + " \\right)\n", + " } \n", + " \\\\ \n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t}\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \n", + " \\sum\\limits_{t=1}^{m}{\\left[\n", + " T[j+t-1]\\left(\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\right)\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {\n", + " - \\frac{1}{\\sigma_{j,m}} \n", + " \\sum\\limits_{t=1}^{m}{\n", + " \\left(\n", + " \\frac{T[i+t-1]T[j+t-1] - \\mu^{'}T[j+t-1]}{\\sigma^{'}} - \\frac{T[j+t-1]T[j+t-1] - \\mu_{j,m+k}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left(\n", + " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu^{'}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma^{'}} \n", + " - \n", + " \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "9f2ca2da", + "metadata": {}, + "source": [ + "And, now with help of the fact that $\\sum{T} = m\\mu$ and also the Pearon Correlation equation (\\*\\*)..." + ] + }, + { + "cell_type": "markdown", + "id": "35db152a", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left(\n", + " \\frac{(m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) - \\mu^{'} \\cdot m\\mu_{j,m}}{\\sigma^{'}} \n", + " - \n", + " \\frac{(m\\rho_{jj}\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) - \\mu_{j,m+k} \\cdot m\\mu_{j,m}}{\\sigma_{j,m}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{1}{\\sigma_{j,m}} \n", + " {\n", + " \\left[\n", + " \\frac{\n", + " m\\left(\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu^{'} \\cdot \\mu_{j,m}\n", + " \\right)\n", + " }{\n", + " \\sigma^{'}\n", + " } \n", + " - \n", + " \\frac{\n", + " m\\left(\n", + " 1\\cdot\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m+k} \\cdot \\mu_{j,m}\n", + " \\right)\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", + " {\n", + " \\left(\n", + " {\\sigma_{j,m}(\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m} - \\mu_{j,m}\\mu^{'})} \n", + " - \n", + " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma^{'}} \n", + " {\n", + " \\left(\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \\mu_{j,m}\\sigma_{j,m}\\mu^{'}} \n", + " - \n", + " {\\sigma^{'}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "cfd5a617", + "metadata": {}, + "source": [ + "And, now we are at a good position to plug in the values $\\mu^{'}$(11) and $\\sigma^{'}$(12):" + ] + }, + { + "cell_type": "markdown", + "id": "f3e25620", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f_{min}(\\mu^{'},\\sigma^{'}) ={}& \n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\n", + " (\\frac{\\sigma_{i,m}}{\\rho_{ij}})\n", + " } \n", + " {\n", + " \\left[\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} + \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} - \n", + " \\mu_{j,m}\\sigma_{j,m}\\left({\n", + " \\mu_{i,m} - \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " \\right)} \n", + " - \n", + " {(\\frac{\\sigma_{i,m}}{\\rho_{ij}})(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m\\rho_{ij}}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\frac{\\sigma_{i,m}}{\\rho_{ij}\\sigma_{j,m}}{\\mu_{j,m}\\sigma_{j,m}}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " } \n", + " - \n", + " {\\frac{\\sigma_{i,m}}{\\rho_{ij}}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left[\n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\mu_{j,m}\\sigma_{i,m}(\\mu_{j,m}-\\mu_{j,m+k})\n", + " }\n", + " } \n", + " - \n", + " {\\sigma_{i,m}(\\sigma_{j,m}^{2} + \\mu_{j,m}^{2} - \\mu_{j,m}\\mu_{j,m+k})}\n", + " \\right]\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}} \n", + " {\n", + " \\left(\n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " + \n", + " \\rho_{ij}\\mu_{i,m}\\mu_{j,m}\\sigma_{j,m} \n", + " - \n", + " {\n", + " \\rho_{ij}\\mu_{j,m}\\sigma_{j,m}\\mu_{i,m} \n", + " + \n", + " \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m} - \\mu_{j,m}\\sigma_{i,m}\\mu_{j,m+k}\n", + " }\n", + " }\n", + " - \n", + " {\\sigma_{i,m}\\sigma_{j,m}^{2} - \\sigma_{i,m}\\mu_{j,m}^{2} + \\sigma_{i,m}\\mu_{j,m}\\mu_{j,m+k}}\n", + " \\right)\n", + " }\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", + " \\left( \n", + " {\\rho_{ij}^{2}\\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " - \n", + " \\sigma_{i,m}\\sigma_{j,m}^{2} \n", + " }\n", + " \\right)\n", + " } \n", + " \\\\\n", + " ={}&\n", + " {- \\frac{m}{\\sigma_{j,m}^{2}\\sigma_{i,m}}\n", + " (\\rho_{ij}^{2} - 1)\n", + " \\sigma_{i,m}\\sigma_{j,m}^{2}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " m(1-\\rho_{ij}^{2})\n", + "\\end{align} \n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "64dc1027", + "metadata": {}, + "source": [ + "**Finally, with eq(2), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" + ] + }, + { + "cell_type": "markdown", + "id": "98db40a5", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " LB ={}& \n", + " \\frac{\n", + " \\sigma_{j,m}\n", + " }{\\sigma_{j,m+k}\n", + " } \\sqrt{m (1 - \\rho_{ij}^{2})} \\quad \\text{if} \\, \\rho > 0\n", + " \\\\\n", + "\\end{align}\n", + "$$\n", + "\n", + "$$\n", + "\\begin{align}\n", + " \\rho_{ij} ={}& \n", + " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "8cbad624", + "metadata": {}, + "source": [ + "**Note:**
\n", + "* Note that eq(12) is valid only for $\\rho_{ij} > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho_{ij} > 0$. \n", + "* The pearson correlation, $\\rho_{ij}$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", + "\n", + "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", + "\n", + "**Pending...**
\n", + "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", + "\n", + "* **For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$.**" + ] + }, + { + "cell_type": "markdown", + "id": "e0dcda60", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From b4ef7db6b0218cdc58214a54e97cc43c8467ecd2 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 03:32:46 -0600 Subject: [PATCH 28/67] ADD calculation for LowerBound when corr is negative --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 690 +++++++++++++++++- 1 file changed, 668 insertions(+), 22 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 09d5202ca..6d202afac 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "3b23610b", + "id": "78a48e7c", "metadata": {}, "source": [ "In this notebook, we would like to derive the eq(2) of the paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf)." @@ -13,7 +13,8 @@ "id": "5f999789", "metadata": {}, "source": [ - "The idea goes as follows: \"given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" + "**The idea goes as follows:**
\n", + "\"Given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" ] }, { @@ -246,7 +247,7 @@ }, { "cell_type": "markdown", - "id": "8a778de1", + "id": "3cbc6e7f", "metadata": {}, "source": [ "\n", @@ -263,7 +264,7 @@ }, { "cell_type": "markdown", - "id": "18656992", + "id": "7f3eea94", "metadata": {}, "source": [ "Therefore, we have:" @@ -506,7 +507,7 @@ }, { "cell_type": "markdown", - "id": "c6084fa1", + "id": "71ea26a2", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -720,7 +721,7 @@ }, { "cell_type": "markdown", - "id": "4c6d53dd", + "id": "ad80f924", "metadata": {}, "source": [ "\n", @@ -841,7 +842,7 @@ }, { "cell_type": "markdown", - "id": "f9a99369", + "id": "4ebe4a56", "metadata": {}, "source": [ "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." @@ -857,7 +858,7 @@ }, { "cell_type": "markdown", - "id": "7878d61c", + "id": "715c3679", "metadata": {}, "source": [ "\n", @@ -876,7 +877,7 @@ }, { "cell_type": "markdown", - "id": "ff88e0e5", + "id": "00d6276a", "metadata": {}, "source": [ "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." @@ -884,7 +885,7 @@ }, { "cell_type": "markdown", - "id": "5fd91d3d", + "id": "2561aacf", "metadata": {}, "source": [ "\n", @@ -908,7 +909,7 @@ }, { "cell_type": "markdown", - "id": "5b103a95", + "id": "3341901c", "metadata": {}, "source": [ "$(8')+(10)$ gives:" @@ -916,7 +917,7 @@ }, { "cell_type": "markdown", - "id": "99e96a66", + "id": "f54ab003", "metadata": {}, "source": [ "\n", @@ -944,7 +945,7 @@ }, { "cell_type": "markdown", - "id": "bb19c9d4", + "id": "0b72b310", "metadata": {}, "source": [ "Hence:" @@ -952,7 +953,7 @@ }, { "cell_type": "markdown", - "id": "3675507e", + "id": "626898d8", "metadata": {}, "source": [ "\n", @@ -965,7 +966,7 @@ }, { "cell_type": "markdown", - "id": "11ce066e", + "id": "54616fb6", "metadata": {}, "source": [ "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." @@ -973,7 +974,7 @@ }, { "cell_type": "markdown", - "id": "21f83530", + "id": "89cd4a74", "metadata": {}, "source": [ "And, subsituting eq(11) in eq(8):" @@ -1005,7 +1006,7 @@ }, { "cell_type": "markdown", - "id": "c6c67de5", + "id": "46693f92", "metadata": {}, "source": [ "Hence:" @@ -1013,7 +1014,7 @@ }, { "cell_type": "markdown", - "id": "2aa3b77a", + "id": "693ab21d", "metadata": {}, "source": [ "\n", @@ -1027,7 +1028,7 @@ }, { "cell_type": "markdown", - "id": "cb7cdb37", + "id": "707daf5b", "metadata": {}, "source": [ "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" @@ -1035,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "e87fc766", + "id": "9532e72b", "metadata": {}, "source": [ "\n", @@ -1066,7 +1067,7 @@ "id": "a0e36dfc", "metadata": {}, "source": [ - "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. \n", + "Now that we calculated the values $\\mu^{'}$ and $\\sigma^{'}$ of the crtical point, we need to plug them in the function $f(.)$ to find the extremum value. However, using these values directly in function $f(.)$ might make the calculation difficult. Therefore, we prefer to use higher-level equations (7) and (9) to first simplify $f_{min}(.)$. \n", "\n", "**NOTE:** we have been solving the single system of equations (5) and (6). Therefore, the calculated values $\\mu^{'}$(11) and $\\sigma^{'}$(12) should satisfy all equations (5), (6), (7), (8), (9), and (10) discovered throughout the solution.
" ] @@ -1478,8 +1479,653 @@ }, { "cell_type": "markdown", - "id": "e0dcda60", + "id": "d34924d4", "metadata": {}, + "source": [ + "So far, we derived the first sub-function (i.e. LB for $\\rho_{ij} \\gt 0$) of the piecewise function provided in the eq(2) of the paper VALMOD.
\n", + "Now, we would like to derive the second sub-function, where LB is defined for $\\rho_{ij} \\leq 0$." + ] + }, + { + "cell_type": "markdown", + "id": "27d5a98b", + "metadata": {}, + "source": [ + "Let us first visit the equation stated by the authors again:" + ] + }, + { + "cell_type": "markdown", + "id": "a3bdfcbb", + "metadata": {}, + "source": [ + "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$, if $\\rho_{ij} \\leq 0$" + ] + }, + { + "cell_type": "markdown", + "id": "bded35a6", + "metadata": {}, + "source": [ + "Comparing the equation above with eq(2) of notebook, i.e. $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, shows that we need to prove:" + ] + }, + { + "cell_type": "markdown", + "id": "392ab830", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "f(\\mu^{'}, \\sigma^{'}) \\geq{}& \n", + "m\n", + "\\\\\n", + "\\frac{\n", + "f(\\mu^{'}, \\sigma^{'})\n", + "}{\n", + "m} \\geq{}& 1\n", + "\\\\\n", + "\\frac{\n", + "f(\\mu^{'}, \\sigma^{'})\n", + "}{\n", + "m}\n", + "-\n", + "1 \\geq{}& 0 \\quad (13)\n", + "\\end{align} \n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2abe5321", + "metadata": {}, + "source": [ + "Therefore, we need to show (13) is correct when $\\rho_{ij} \\leq 0$.\n", + "\n", + "$F \\triangleq \\frac{f(\\mu^{'}, \\sigma^{'})}{m} - 1$ (14)" + ] + }, + { + "cell_type": "markdown", + "id": "debdb6a8", + "metadata": {}, + "source": [ + "We start with eq(3), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(4). Therefore:" + ] + }, + { + "cell_type": "markdown", + "id": "5139c4a9", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "f(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\sum \\limits_{t=1}^{m}\n", + " \\left(\n", + " \\frac{\n", + " T[i+t-1] - \\mu^{'}\n", + " }{\n", + " \\sigma^{'}\n", + " } \n", + " - \n", + " \\frac{\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\n", + " \\right)^{2}\n", + " \\quad (15)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "18136d35", + "metadata": {}, + "source": [ + "Inside the summation, we use the formula: $(A+B)^{2} = A^{2} + B^{2} - 2AB$" + ] + }, + { + "cell_type": "markdown", + "id": "672654f3", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "f(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\sum \\limits_{t=1}^{m}\n", + " \\left[\n", + " \\left(\n", + " \\frac{\n", + " T[i+t-1] - \\mu^{'}\n", + " }{\n", + " \\sigma^{'}\n", + " }\\right)^{2}\n", + " +\n", + " \\left(\n", + " \\frac{\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\n", + " \\right)^{2}\n", + " -\n", + " 2\n", + " \\left(\\frac{\n", + " T[i+t-1] - \\mu^{'}\n", + " }{\n", + " \\sigma^{'}\n", + " }\\right)\n", + " \\left(\\frac{\n", + " T[j+t-1] - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\n", + " \\right)\n", + " \\right]\n", + " \\\\\n", + " \\\\\n", + " ={}&\n", + " \\sum \\limits_{t=1}^{m}\n", + " \\left[\n", + " \\left(\n", + " \\frac{\n", + " T[i+t-1]^{2} + \\mu^{'2} - 2T[i+t-1]\\mu^{'}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\\right)\n", + " +\n", + " \\left(\n", + " \\frac{\n", + " T[j+t-1]^{2} + \\mu_{j,m+k}^{2} - 2 T[j+t-1]\\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " \\right)\n", + " -\n", + " 2\n", + " \\left(\\frac{\n", + " T[i+t-1]T[j+t-1] \n", + " - T[i+t-1]\\mu_{j,m+k}\n", + " - T[j+t-1]\\mu^{'}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\right)\n", + " \\right]\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "5c6c90c2", + "metadata": {}, + "source": [ + "Now, we distribute summation into all terms..." + ] + }, + { + "cell_type": "markdown", + "id": "b68a1419", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "f(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\frac{\n", + " \\sum \\limits_{t=1}^{m}T[i+t-1]^{2} + \\sum \\limits_{t=1}^{m}\\mu^{'2} - 2\\mu^{'}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " \\sum \\limits_{t=1}^{m}T[j+t-1]^{2} + \\sum \\limits_{t=1}^{m}\\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[j+t-1]\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\frac{\n", + " \\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", + " - \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " - \\mu^{'}\\sum \\limits_{t=1}^{m}T[j+t-1]\n", + " + \\sum \\limits_{t=1}^{m}\\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "f9b131ae", + "metadata": {}, + "source": [ + "With help of Pearson Correlation equation (\\*\\*), we have:" + ] + }, + { + "cell_type": "markdown", + "id": "7cf643c5", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "f(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\frac{\n", + " (m\\rho_{ii}\\sigma_{i,m}^{2} + m\\mu_{i,m}^{2}) + m\\mu^{'2} - 2\\mu^{'}\\cdot m\\mu_{i,m}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " (m\\rho_{jj}\\sigma_{j,m}^{2} + m\\mu_{j,m}^{2}) + m\\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\cdot m\\mu_{j,m}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\frac{\n", + " (m\\rho_{ij}\\sigma_{i}\\sigma_{j} + m\\mu_{i}\\mu_{j}) \n", + " - \\mu_{j,m+k}\\cdot m\\mu_{i,m}\n", + " - \\mu^{'} \\cdot m\\mu_{j,m}\n", + " + m\\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "2190c5b2", + "metadata": {}, + "source": [ + "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. After subsituting them in the formula above, and factoring out m, we can write it down as:" + ] + }, + { + "cell_type": "markdown", + "id": "2975a04b", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\frac{f(\\mu^{'},\\sigma^{'})}{m} ={}& \n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " \\sigma_{j,m}^{2} + \\mu_{j,m}^{2} + \\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\mu_{j,m}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\frac{\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\left(1\n", + " +\n", + " \\frac{\n", + " \\mu_{j,m}^{2} + \\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\mu_{j,m}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " \\right)\n", + " -\n", + " 2\n", + " \\frac{\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "aa314371", + "metadata": {}, + "source": [ + "Therefore, we can now see:" + ] + }, + { + "cell_type": "markdown", + "id": "9812ba37", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 ={}& \n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " \\mu_{j,m}^{2} + \\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\mu_{j,m}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\frac{\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "223936b7", + "metadata": {}, + "source": [ + "Recall eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always positive. " + ] + }, + { + "cell_type": "markdown", + "id": "bec5c521", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " F ={}& \n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " \\mu_{j,m}^{2} + \\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\mu_{j,m}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\frac{\n", + " \\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + \\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + (\\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m})\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " (\\mu_{j,m}^{2} + \\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\mu_{j,m})\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\n", + " \\left(\n", + " \\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " \\frac{\\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\right)\n", + " \\\\\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + (\\mu_{i,m}-\\mu^{'})^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " (\\mu_{j,m} - \\mu_{j,m+k})^{2}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " 2\\frac{\\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + " \\geq{}&\n", + " \\frac{\\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " } \\quad (16)\n", + " \\\\ \n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "0074dd7e", + "metadata": {}, + "source": [ + "Note that the first two terms are non-negative (i.e. $\\geq 0$).The third term is also non-negative because $\\rho_{ij}\\leq 0$. Therefore, we just need to prove the last term is non-negative. Hence, we need to show:" + ] + }, + { + "cell_type": "markdown", + "id": "fdbf21bd", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "G \\triangleq{}& \\frac{\\mu_{i,m}\\mu_{j,m}\n", + " - \\mu_{j,m+k}\\mu_{i,m}\n", + " - \\mu^{'} \\mu_{j,m}\n", + " + \\mu^{'}\\mu_{j,m+k}\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\geq 0\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "8a8220bd", + "metadata": {}, + "source": [ + "Let us factorize G as follows:" + ] + }, + { + "cell_type": "markdown", + "id": "9e49a113", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "G = {}& \\frac{\\mu_{i,m}(\\mu_{j,m}\n", + " - \\mu_{j,m+k})\n", + " - \\mu^{'} (\\mu_{j,m}-\\mu_{j,m+k})\n", + " }{\n", + " \\sigma^{'}\\sigma_{j,m}\n", + " }\n", + " \\\\\n", + " = {}&\n", + " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", + " {\\sigma^{'}\\sigma_{j,m}} \\quad (17)\n", + " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "4cef4acd", + "metadata": {}, + "source": [ + "**NOTE:**
\n", + "We **cannot** prove eq(17) to be always positive! In fact, it is possible that eq(17) to be negative! For instance, consider a case where subsequence $T_{j,m+k}$ has lower mean compared to $T_{j,m}$. But, its neighbor, at index `i`, has higher mean in $T_{i,m+k}$ compared to $T_{i,m}$. We will investigate this matter shortly with help of `np.random.uniform` time series data." + ] + }, + { + "cell_type": "markdown", + "id": "952091ef", + "metadata": {}, + "source": [ + "**NOTE:**
\n", + "Let us take a better look at eq(2) of paper VALMOD. It seems there has been a typo and the authors replace $\\mu_{j,m+k}$ with $\\mu_{j,m}$. (In the paper, the authors used $l$, instead of $m$ as the subsequence length.). Having considered that typo, we can see the the term $\\mu_{j,m}-\\mu_{j,m+k}$ in the numerator of eq(15) becomes 0, and thus we can get to the equation provided in the paper." + ] + }, + { + "cell_type": "markdown", + "id": "096b25c4", + "metadata": {}, + "source": [ + "**The correct formula can be achieved as follows:**
\n", + "Based on eq(14),(16), and eq(17):" + ] + }, + { + "cell_type": "markdown", + "id": "7915ff7e", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\frac{f(\\mu^{'}, \\sigma^{'})}{m} - 1 \\geq{}&\n", + "\\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", + " {\\sigma^{'}\\sigma_{j,m}}\n", + " \\\\\n", + " f(\\mu^{'}, \\sigma^{'}) \\geq{}&\n", + " m \\left[\n", + " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", + " {\\sigma^{'}\\sigma_{j,m}} \n", + " \\right]\n", + " + 1\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "74bbbd59", + "metadata": {}, + "source": [ + "And, with help of eq(2), i.e. $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can claim:" + ] + }, + { + "cell_type": "markdown", + "id": "88052b40", + "metadata": {}, + "source": [ + "$$\n", + "\\begin{align}\n", + " LB^{*} ={}&\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\sqrt{\n", + " m \\left[\n", + " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", + " {\\sigma^{'}\\sigma_{j,m}} \n", + " \\right]\n", + " + 1\n", + " } \\quad (\\rho_{ij} \\leq 0)\n", + " \\\\\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "02822e09", + "metadata": {}, + "source": [ + "We used superscript * to distinguish the LB proposed by the paper and the LB achieved by the calculaton of this notebook." + ] + }, + { + "cell_type": "markdown", + "id": "88edf049", + "metadata": {}, + "source": [ + "## Validating LB with a test case" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58062d43", + "metadata": {}, + "outputs": [], "source": [] } ], From 9629b8ec786301292a2989bf5088ae4cbc0c144b Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 05:21:14 -0600 Subject: [PATCH 29/67] FIXed Calculation for deriving eq(2) when q is neg --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 316 +++++++++--------- 1 file changed, 156 insertions(+), 160 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 6d202afac..7d025a180 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "78a48e7c", + "id": "d8ebe111", "metadata": {}, "source": [ "In this notebook, we would like to derive the eq(2) of the paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf)." @@ -247,7 +247,7 @@ }, { "cell_type": "markdown", - "id": "3cbc6e7f", + "id": "2ade7583", "metadata": {}, "source": [ "\n", @@ -264,7 +264,7 @@ }, { "cell_type": "markdown", - "id": "7f3eea94", + "id": "5fe5c9e3", "metadata": {}, "source": [ "Therefore, we have:" @@ -507,7 +507,7 @@ }, { "cell_type": "markdown", - "id": "71ea26a2", + "id": "1340817b", "metadata": {}, "source": [ "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." @@ -721,7 +721,7 @@ }, { "cell_type": "markdown", - "id": "ad80f924", + "id": "182b8064", "metadata": {}, "source": [ "\n", @@ -842,7 +842,7 @@ }, { "cell_type": "markdown", - "id": "4ebe4a56", + "id": "978473a2", "metadata": {}, "source": [ "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." @@ -858,7 +858,7 @@ }, { "cell_type": "markdown", - "id": "715c3679", + "id": "6ac05b5f", "metadata": {}, "source": [ "\n", @@ -877,7 +877,7 @@ }, { "cell_type": "markdown", - "id": "00d6276a", + "id": "b2322ecc", "metadata": {}, "source": [ "Note that in the system of equations above, the unknown variables are $\\mu^{'}$ and $\\sigma^{'}$, and the remaining ones are known." @@ -885,7 +885,7 @@ }, { "cell_type": "markdown", - "id": "2561aacf", + "id": "e40d711e", "metadata": {}, "source": [ "\n", @@ -909,7 +909,7 @@ }, { "cell_type": "markdown", - "id": "3341901c", + "id": "4dfc6b45", "metadata": {}, "source": [ "$(8')+(10)$ gives:" @@ -917,7 +917,7 @@ }, { "cell_type": "markdown", - "id": "f54ab003", + "id": "c798dc6b", "metadata": {}, "source": [ "\n", @@ -945,7 +945,7 @@ }, { "cell_type": "markdown", - "id": "0b72b310", + "id": "3627a49a", "metadata": {}, "source": [ "Hence:" @@ -953,7 +953,7 @@ }, { "cell_type": "markdown", - "id": "626898d8", + "id": "de0702cf", "metadata": {}, "source": [ "\n", @@ -966,7 +966,7 @@ }, { "cell_type": "markdown", - "id": "54616fb6", + "id": "ed3f7802", "metadata": {}, "source": [ "Note that we assumed $\\sigma_{i,m}$ and $\\sigma_{j,m}$ cannot be zero. Also, since standard deviations are positive, eq(11) is valid only if $\\rho_{ij} \\gt 0$." @@ -974,7 +974,7 @@ }, { "cell_type": "markdown", - "id": "89cd4a74", + "id": "91752bef", "metadata": {}, "source": [ "And, subsituting eq(11) in eq(8):" @@ -1006,7 +1006,7 @@ }, { "cell_type": "markdown", - "id": "46693f92", + "id": "335173da", "metadata": {}, "source": [ "Hence:" @@ -1014,7 +1014,7 @@ }, { "cell_type": "markdown", - "id": "693ab21d", + "id": "8efc2627", "metadata": {}, "source": [ "\n", @@ -1028,7 +1028,7 @@ }, { "cell_type": "markdown", - "id": "707daf5b", + "id": "4278ff7e", "metadata": {}, "source": [ "**Therefore, the critical point of function $f(\\mu^{'},\\sigma^{'})$ is:**" @@ -1036,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "9532e72b", + "id": "e0104b24", "metadata": {}, "source": [ "\n", @@ -1479,7 +1479,7 @@ }, { "cell_type": "markdown", - "id": "d34924d4", + "id": "fc19b2dd", "metadata": {}, "source": [ "So far, we derived the first sub-function (i.e. LB for $\\rho_{ij} \\gt 0$) of the piecewise function provided in the eq(2) of the paper VALMOD.
\n", @@ -1488,7 +1488,7 @@ }, { "cell_type": "markdown", - "id": "27d5a98b", + "id": "7e523470", "metadata": {}, "source": [ "Let us first visit the equation stated by the authors again:" @@ -1496,7 +1496,7 @@ }, { "cell_type": "markdown", - "id": "a3bdfcbb", + "id": "326d2300", "metadata": {}, "source": [ "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$, if $\\rho_{ij} \\leq 0$" @@ -1504,7 +1504,7 @@ }, { "cell_type": "markdown", - "id": "bded35a6", + "id": "86dd8eb5", "metadata": {}, "source": [ "Comparing the equation above with eq(2) of notebook, i.e. $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, shows that we need to prove:" @@ -1512,7 +1512,7 @@ }, { "cell_type": "markdown", - "id": "392ab830", + "id": "8670ed3e", "metadata": {}, "source": [ "\n", @@ -1538,7 +1538,7 @@ }, { "cell_type": "markdown", - "id": "2abe5321", + "id": "b6b9eff9", "metadata": {}, "source": [ "Therefore, we need to show (13) is correct when $\\rho_{ij} \\leq 0$.\n", @@ -1548,7 +1548,7 @@ }, { "cell_type": "markdown", - "id": "debdb6a8", + "id": "a4f11acc", "metadata": {}, "source": [ "We start with eq(3), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(4). Therefore:" @@ -1556,7 +1556,7 @@ }, { "cell_type": "markdown", - "id": "5139c4a9", + "id": "1aac6ab8", "metadata": {}, "source": [ "\n", @@ -1585,7 +1585,7 @@ }, { "cell_type": "markdown", - "id": "18136d35", + "id": "bf007040", "metadata": {}, "source": [ "Inside the summation, we use the formula: $(A+B)^{2} = A^{2} + B^{2} - 2AB$" @@ -1593,7 +1593,7 @@ }, { "cell_type": "markdown", - "id": "672654f3", + "id": "f8d24612", "metadata": {}, "source": [ "\n", @@ -1668,7 +1668,7 @@ }, { "cell_type": "markdown", - "id": "5c6c90c2", + "id": "edc051ab", "metadata": {}, "source": [ "Now, we distribute summation into all terms..." @@ -1676,7 +1676,7 @@ }, { "cell_type": "markdown", - "id": "b68a1419", + "id": "9f44f100", "metadata": {}, "source": [ "\n", @@ -1711,7 +1711,7 @@ }, { "cell_type": "markdown", - "id": "f9b131ae", + "id": "c1cbd849", "metadata": {}, "source": [ "With help of Pearson Correlation equation (\\*\\*), we have:" @@ -1719,7 +1719,7 @@ }, { "cell_type": "markdown", - "id": "7cf643c5", + "id": "bb5a2896", "metadata": {}, "source": [ "\n", @@ -1754,7 +1754,7 @@ }, { "cell_type": "markdown", - "id": "2190c5b2", + "id": "f54b458f", "metadata": {}, "source": [ "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. After subsituting them in the formula above, and factoring out m, we can write it down as:" @@ -1762,7 +1762,7 @@ }, { "cell_type": "markdown", - "id": "2975a04b", + "id": "755955af", "metadata": {}, "source": [ "\n", @@ -1823,7 +1823,7 @@ }, { "cell_type": "markdown", - "id": "aa314371", + "id": "96db6201", "metadata": {}, "source": [ "Therefore, we can now see:" @@ -1831,7 +1831,7 @@ }, { "cell_type": "markdown", - "id": "9812ba37", + "id": "4359532f", "metadata": {}, "source": [ "\n", @@ -1865,7 +1865,7 @@ }, { "cell_type": "markdown", - "id": "223936b7", + "id": "317e1594", "metadata": {}, "source": [ "Recall eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always positive. " @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "bec5c521", + "id": "d73539ec", "metadata": {}, "source": [ "\n", @@ -1944,186 +1944,182 @@ " }\n", " -\n", " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", - " +\n", + " -\n", " 2\\frac{\\mu_{i,m}\\mu_{j,m}\n", " - \\mu_{j,m+k}\\mu_{i,m}\n", " - \\mu^{'} \\mu_{j,m}\n", " + \\mu^{'}\\mu_{j,m+k}\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", - " }\n", + " } \n", " \\\\\n", - " \\geq{}&\n", - " \\frac{\\mu_{i,m}\\mu_{j,m}\n", - " - \\mu_{j,m+k}\\mu_{i,m}\n", - " - \\mu^{'} \\mu_{j,m}\n", - " + \\mu^{'}\\mu_{j,m+k}\n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + (\\mu_{i,m}-\\mu^{'})^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " (\\mu_{j,m} - \\mu_{j,m+k})^{2}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " -\n", + " 2\\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}\n", + " - \\mu_{j,m+k})\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", " } \\quad (16)\n", - " \\\\ \n", + " \\\\\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "0074dd7e", + "id": "e0b43f1e", "metadata": {}, "source": [ - "Note that the first two terms are non-negative (i.e. $\\geq 0$).The third term is also non-negative because $\\rho_{ij}\\leq 0$. Therefore, we just need to prove the last term is non-negative. Hence, we need to show:" + "**Now, we define two new intermediate variables as follows:**" ] }, { "cell_type": "markdown", - "id": "fdbf21bd", + "id": "ed9912e4", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", - "G \\triangleq{}& \\frac{\\mu_{i,m}\\mu_{j,m}\n", - " - \\mu_{j,m+k}\\mu_{i,m}\n", - " - \\mu^{'} \\mu_{j,m}\n", - " + \\mu^{'}\\mu_{j,m+k}\n", - " }{\n", - " \\sigma^{'}\\sigma_{j,m}\n", - " }\n", - " \\geq 0\n", - " \\\\\n", + " \\beta \\triangleq{}& \\mu_{i,m} - \\mu^{'}\n", + " \\\\\n", + " \\gamma \\triangleq{}& \\mu_{j,m} - \\mu_{j,m+k}\n", + " \\\\\n", "\\end{align}\n", - "$$\n" + "$$" ] }, { "cell_type": "markdown", - "id": "8a8220bd", + "id": "961562f1", "metadata": {}, "source": [ - "Let us factorize G as follows:" + "By subsituting $\\beta$ and $\\gamma$ for their corresponding terms in eq(16), we get:" ] }, { "cell_type": "markdown", - "id": "9e49a113", + "id": "ecd9622b", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", - "G = {}& \\frac{\\mu_{i,m}(\\mu_{j,m}\n", - " - \\mu_{j,m+k})\n", - " - \\mu^{'} (\\mu_{j,m}-\\mu_{j,m+k})\n", + " F ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2} + \\beta^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " \\frac{\n", + " \\gamma^{2}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " -\n", + " 2\\frac{\\beta\\gamma\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", + " } \n", + " \\\\\n", + " ={}&\n", + " \\left(\n", + " \\frac{\n", + " \\sigma_{i,m}^{2}\n", + " }{\n", + " \\sigma^{'2}\n", " }\n", - " \\\\\n", - " = {}&\n", - " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", - " {\\sigma^{'}\\sigma_{j,m}} \\quad (17)\n", - " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "4cef4acd", - "metadata": {}, - "source": [ - "**NOTE:**
\n", - "We **cannot** prove eq(17) to be always positive! In fact, it is possible that eq(17) to be negative! For instance, consider a case where subsequence $T_{j,m+k}$ has lower mean compared to $T_{j,m}$. But, its neighbor, at index `i`, has higher mean in $T_{i,m+k}$ compared to $T_{i,m}$. We will investigate this matter shortly with help of `np.random.uniform` time series data." - ] - }, - { - "cell_type": "markdown", - "id": "952091ef", - "metadata": {}, - "source": [ - "**NOTE:**
\n", - "Let us take a better look at eq(2) of paper VALMOD. It seems there has been a typo and the authors replace $\\mu_{j,m+k}$ with $\\mu_{j,m}$. (In the paper, the authors used $l$, instead of $m$ as the subsequence length.). Having considered that typo, we can see the the term $\\mu_{j,m}-\\mu_{j,m+k}$ in the numerator of eq(15) becomes 0, and thus we can get to the equation provided in the paper." - ] - }, - { - "cell_type": "markdown", - "id": "096b25c4", - "metadata": {}, - "source": [ - "**The correct formula can be achieved as follows:**
\n", - "Based on eq(14),(16), and eq(17):" - ] - }, - { - "cell_type": "markdown", - "id": "7915ff7e", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "\\frac{f(\\mu^{'}, \\sigma^{'})}{m} - 1 \\geq{}&\n", - "\\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", - " {\\sigma^{'}\\sigma_{j,m}}\n", - " \\\\\n", - " f(\\mu^{'}, \\sigma^{'}) \\geq{}&\n", - " m \\left[\n", - " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", - " {\\sigma^{'}\\sigma_{j,m}} \n", - " \\right]\n", - " + 1\n", + " +\n", + " \\frac{\n", + " \\beta^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " \\right)\n", + " +\n", + " \\frac{\n", + " \\gamma^{2}\n", + " }{\n", + " \\sigma_{j,m}^{2}\n", + " }\n", + " -\n", + " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " -\n", + " 2(\\frac{\\beta}{\\sigma^{'}})(\\frac{\\gamma}{\\sigma_{j,m}})\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " (\\frac{\n", + " \\beta\n", + " }{\n", + " \\sigma^{'}\n", + " })^{2}\n", + " +\n", + " (\\frac{\n", + " \\gamma\n", + " }{\n", + " \\sigma_{j,m}\n", + " })^{2}\n", + " +\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " -\n", + " 2(\\frac{\\beta}{\\sigma^{'}})(\\frac{\\gamma}{\\sigma_{j,m}})\n", + " \\\\ \n", + " ={}&\n", + " \\frac{\n", + " \\sigma_{i,m}^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " \\left(\n", + " \\frac{\\beta\n", + " }{\\sigma^{'}\n", + " }\n", + " -\n", + " \\frac{\\gamma\n", + " }{\\sigma_{j,m}\n", + " }\\right)^{2}\n", + " \\\\\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "74bbbd59", - "metadata": {}, - "source": [ - "And, with help of eq(2), i.e. $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can claim:" - ] - }, - { - "cell_type": "markdown", - "id": "88052b40", - "metadata": {}, - "source": [ - "$$\n", - "\\begin{align}\n", - " LB^{*} ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{\n", - " m \\left[\n", - " \\frac{(\\mu_{i,m}-\\mu^{'})(\\mu_{j,m}-\\mu_{j,m+k})}\n", - " {\\sigma^{'}\\sigma_{j,m}} \n", - " \\right]\n", - " + 1\n", - " } \\quad (\\rho_{ij} \\leq 0)\n", - " \\\\\n", - "\\end{align}\n", - "$$" - ] - }, - { - "cell_type": "markdown", - "id": "02822e09", - "metadata": {}, - "source": [ - "We used superscript * to distinguish the LB proposed by the paper and the LB achieved by the calculaton of this notebook." - ] - }, - { - "cell_type": "markdown", - "id": "88edf049", + "id": "1f8c0fb5", "metadata": {}, "source": [ - "## Validating LB with a test case" + "NOTE: Since $\\rho_{i,j} \\leq 0$, the second term becoms non-negative. Therefore $F \\geq 0$ which, according to eq(14), satisfies equations (13). Therefore, LB proposed by the authors are acceptable." ] }, { "cell_type": "code", "execution_count": null, - "id": "58062d43", + "id": "665164cc", "metadata": {}, "outputs": [], "source": [] From 8b249e42d132ceeabad7dd7e0b269704a99246cc Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 05:38:41 -0600 Subject: [PATCH 30/67] Removed unnecessary variables in calculating LB --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 138 ++++++------------ 1 file changed, 47 insertions(+), 91 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 7d025a180..60123374c 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -1868,7 +1868,7 @@ "id": "317e1594", "metadata": {}, "source": [ - "Recall eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always positive. " + "Recall eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always non-negative. " ] }, { @@ -1972,138 +1972,94 @@ " - \\mu_{j,m+k})\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", - " } \\quad (16)\n", + " } \n", " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "e0b43f1e", - "metadata": {}, - "source": [ - "**Now, we define two new intermediate variables as follows:**" - ] - }, - { - "cell_type": "markdown", - "id": "ed9912e4", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\beta \\triangleq{}& \\mu_{i,m} - \\mu^{'}\n", - " \\\\\n", - " \\gamma \\triangleq{}& \\mu_{j,m} - \\mu_{j,m+k}\n", - " \\\\\n", - "\\end{align}\n", - "$$" - ] - }, - { - "cell_type": "markdown", - "id": "961562f1", - "metadata": {}, - "source": [ - "By subsituting $\\beta$ and $\\gamma$ for their corresponding terms in eq(16), we get:" - ] - }, - { - "cell_type": "markdown", - "id": "ecd9622b", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " F ={}&\n", + " ={}&\n", " \\frac{\n", - " \\sigma_{i,m}^{2} + \\beta^{2}\n", + " \\sigma_{i,m}^{2}\n", " }{\n", " \\sigma^{'2}\n", " }\n", + " +\n", + " \\frac{(\\mu_{i,m}-\\mu^{'})^{2}}{\\sigma^{'2}}\n", " +\n", " \\frac{\n", - " \\gamma^{2}\n", + " (\\mu_{j,m} - \\mu_{j,m+k})^{2}\n", " }{\n", " \\sigma_{j,m}^{2}\n", " }\n", + " +\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", " -\n", - " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", - " -\n", - " 2\\frac{\\beta\\gamma\n", - " }{\n", - " \\sigma^{'}\\sigma_{j,m}\n", - " } \n", + " 2(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}})(\n", + " \\frac{\\mu_{j,m}\n", + " - \\mu_{j,m+k}}{\\sigma_{j,m}})\n", " \\\\\n", " ={}&\n", - " \\left(\n", - " \\frac{\n", + " \\frac{\n", " \\sigma_{i,m}^{2}\n", " }{\n", " \\sigma^{'2}\n", " }\n", " +\n", - " \\frac{\n", - " \\beta^{2}\n", - " }{\n", - " \\sigma^{'2}\n", - " }\n", - " \\right)\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " \\left[\n", + " \\frac{(\\mu_{i,m}-\\mu^{'})^{2}}{\\sigma^{'2}}\n", " +\n", " \\frac{\n", - " \\gamma^{2}\n", + " (\\mu_{j,m} - \\mu_{j,m+k})^{2}\n", " }{\n", " \\sigma_{j,m}^{2}\n", " }\n", " -\n", - " 2\\frac{\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", - " -\n", - " 2(\\frac{\\beta}{\\sigma^{'}})(\\frac{\\gamma}{\\sigma_{j,m}})\n", + " 2(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}})(\n", + " \\frac{\\mu_{j,m}\n", + " - \\mu_{j,m+k}}{\\sigma_{j,m}})\n", + " \\right]\n", " \\\\\n", " ={}&\n", - " \\frac{\n", + " \\frac{\n", " \\sigma_{i,m}^{2}\n", " }{\n", " \\sigma^{'2}\n", " }\n", " +\n", - " (\\frac{\n", - " \\beta\n", - " }{\n", - " \\sigma^{'}\n", - " })^{2}\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " \\left[\n", + " (\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}})^{2}\n", " +\n", " (\\frac{\n", - " \\gamma\n", + " \\mu_{j,m} - \\mu_{j,m+k}\n", " }{\n", " \\sigma_{j,m}\n", " })^{2}\n", - " +\n", - " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", " -\n", - " 2(\\frac{\\beta}{\\sigma^{'}})(\\frac{\\gamma}{\\sigma_{j,m}})\n", - " \\\\ \n", - " ={}&\n", - " \\frac{\n", + " 2(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}})(\n", + " \\frac{\\mu_{j,m}\n", + " - \\mu_{j,m+k}}{\\sigma_{j,m}})\n", + " \\right]\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", " \\sigma_{i,m}^{2}\n", " }{\n", " \\sigma^{'2}\n", " }\n", " +\n", - " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", - " +\n", - " \\left(\n", - " \\frac{\\beta\n", - " }{\\sigma^{'}\n", - " }\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " +\n", + " \\left[\n", + " \\left(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}}\\right)\n", " -\n", - " \\frac{\\gamma\n", - " }{\\sigma_{j,m}\n", - " }\\right)^{2}\n", - " \\\\\n", + " \\left(\\frac{\n", + " \\mu_{j,m} - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\\right)\n", + " \\right]^{2}\n", + " \\\\\n", "\\end{align}\n", "$$\n" ] @@ -2113,7 +2069,7 @@ "id": "1f8c0fb5", "metadata": {}, "source": [ - "NOTE: Since $\\rho_{i,j} \\leq 0$, the second term becoms non-negative. Therefore $F \\geq 0$ which, according to eq(14), satisfies equations (13). Therefore, LB proposed by the authors are acceptable." + "NOTE: Since $\\rho_{i,j} \\leq 0$, the second term becoms non-negative. Therefore $F \\geq 0$ which, according to eq(14), satisfies equations (13). Therefore, the LB proposed by the authors is correct." ] }, { From e3874833ab4b09bf93db8deca82b971fcaac8f10 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 06:39:39 -0600 Subject: [PATCH 31/67] ADDed proof for pearson correlation --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 99 ++++++++++++++++++- 1 file changed, 97 insertions(+), 2 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 60123374c..ff96212a6 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -646,7 +646,94 @@ " \\rho_{ij} = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", - "$$\n" + "$$\n", + "\n", + "**Proof:**\n", + "\n", + "$$\n", + "\\begin{align}\n", + "\\rho_{ij} ={}&\n", + " \\frac{\n", + " COV(T_{i}T_{j})}{\n", + " \\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " E\\left[\n", + " (T_{i} - \\mu_{i})(T_{j} - \\mu_{j})\n", + " \\right]}\n", + " {\n", + " \\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\frac{1}{m}\\sum\\limits_{t=1}^{m}\n", + " (T[i+t-1] - \\mu_{i})(T[j+t-1] - \\mu_{j})\n", + " }\n", + " {\n", + " \\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]T[j+t-1] \n", + " -\n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu_{i}T[j+t-1]\n", + " -\n", + " \\sum\\limits_{t=1}^{m}\n", + " \\mu_{j}T[i+t-1]\n", + " +\n", + " \\sum\\limits_{t=1}^{m}\\mu_{i}\\mu_{j}\n", + " }{\n", + " m\\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]T[j+t-1] \n", + " -\n", + " \\mu_{i}\\sum\\limits_{t=1}^{m}\n", + " T[j+t-1]\n", + " -\n", + " \\mu_{j}\\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]\n", + " +\n", + " \\sum\\limits_{t=1}^{m}\\mu_{i}\\mu_{j}\n", + " }{\n", + " m\\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]T[j+t-1] \n", + " -\n", + " \\mu_{i}\\cdot m\\mu_{j}\n", + " -\n", + " \\mu_{j}\\cdot m\\mu_{j}\n", + " +\n", + " m\\mu_{i}\\mu_{j}\n", + " }{\n", + " m\\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + " ={}&\n", + " \\frac{\n", + " \\sum\\limits_{t=1}^{m}\n", + " T[i+t-1]T[j+t-1] \n", + " -\n", + " m\\mu_{i}m\\mu_{j}\n", + " }{\n", + " m\\sigma_{i}\\sigma_{j}\n", + " }\n", + " \\\\\n", + "\\end{align}\n", + "$$" ] }, { @@ -654,7 +741,7 @@ "id": "4880c751", "metadata": {}, "source": [ - "Note: we can rearrange the pearson correlation equation as:
\n", + "Note: we can rearrange the pearson correlation equation as below:
\n", "$\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" ] }, @@ -1477,6 +1564,14 @@ "* **For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$.**" ] }, + { + "cell_type": "markdown", + "id": "b35090c6", + "metadata": {}, + "source": [ + "### Derving Equation (2): Continued" + ] + }, { "cell_type": "markdown", "id": "fc19b2dd", From b6b0151156beb75a5c6fab9a477324647c3e3e0e Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 07:06:03 -0600 Subject: [PATCH 32/67] proof read the notebook --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 90 ++++++------------- 1 file changed, 29 insertions(+), 61 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index ff96212a6..a24785032 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -640,40 +640,30 @@ "id": "82bc9b8e", "metadata": {}, "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " \\rho_{ij} = \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", - " \\\\\n", - "\\end{align}\n", - "$$\n", - "\n", - "**Proof:**\n", - "\n", "$$\n", "\\begin{align}\n", "\\rho_{ij} ={}&\n", " \\frac{\n", - " COV(T_{i}T_{j})}{\n", - " \\sigma_{i}\\sigma_{j}\n", + " COV(T_{i,m}T_{j,m})}{\n", + " \\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", " \\frac{\n", " E\\left[\n", - " (T_{i} - \\mu_{i})(T_{j} - \\mu_{j})\n", + " (T_{i,m} - \\mu_{i,m})(T_{j,m} - \\mu_{j,m})\n", " \\right]}\n", " {\n", - " \\sigma_{i}\\sigma_{j}\n", + " \\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", " \\frac{\n", " \\frac{1}{m}\\sum\\limits_{t=1}^{m}\n", - " (T[i+t-1] - \\mu_{i})(T[j+t-1] - \\mu_{j})\n", + " (T[i+t-1] - \\mu_{i,m})(T[j+t-1] - \\mu_{j,m})\n", " }\n", " {\n", - " \\sigma_{i}\\sigma_{j}\n", + " \\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", @@ -682,14 +672,14 @@ " T[i+t-1]T[j+t-1] \n", " -\n", " \\sum\\limits_{t=1}^{m}\n", - " \\mu_{i}T[j+t-1]\n", + " \\mu_{i,m}T[j+t-1]\n", " -\n", " \\sum\\limits_{t=1}^{m}\n", - " \\mu_{j}T[i+t-1]\n", + " \\mu_{j,m}T[i+t-1]\n", " +\n", - " \\sum\\limits_{t=1}^{m}\\mu_{i}\\mu_{j}\n", + " \\sum\\limits_{t=1}^{m}\\mu_{i,m}\\mu_{j,m}\n", " }{\n", - " m\\sigma_{i}\\sigma_{j}\n", + " m\\sigma_{i,m}\\sigma_{j,,m}\n", " }\n", " \\\\\n", " ={}&\n", @@ -697,15 +687,15 @@ " \\sum\\limits_{t=1}^{m}\n", " T[i+t-1]T[j+t-1] \n", " -\n", - " \\mu_{i}\\sum\\limits_{t=1}^{m}\n", + " \\mu_{i,m}\\sum\\limits_{t=1}^{m}\n", " T[j+t-1]\n", " -\n", - " \\mu_{j}\\sum\\limits_{t=1}^{m}\n", + " \\mu_{j,m}\\sum\\limits_{t=1}^{m}\n", " T[i+t-1]\n", " +\n", - " \\sum\\limits_{t=1}^{m}\\mu_{i}\\mu_{j}\n", + " \\sum\\limits_{t=1}^{m}\\mu_{i,m}\\mu_{j,m}\n", " }{\n", - " m\\sigma_{i}\\sigma_{j}\n", + " m\\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", @@ -713,13 +703,13 @@ " \\sum\\limits_{t=1}^{m}\n", " T[i+t-1]T[j+t-1] \n", " -\n", - " \\mu_{i}\\cdot m\\mu_{j}\n", + " \\mu_{i,m}\\cdot m\\mu_{j,m}\n", " -\n", - " \\mu_{j}\\cdot m\\mu_{j}\n", + " \\mu_{j,m}\\cdot m\\mu_{i,m}\n", " +\n", - " m\\mu_{i}\\mu_{j}\n", + " m\\mu_{i,m}\\mu_{j,m}\n", " }{\n", - " m\\sigma_{i}\\sigma_{j}\n", + " m\\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", @@ -727,9 +717,9 @@ " \\sum\\limits_{t=1}^{m}\n", " T[i+t-1]T[j+t-1] \n", " -\n", - " m\\mu_{i}m\\mu_{j}\n", + " m\\mu_{i,m}\\mu_{j,m}\n", " }{\n", - " m\\sigma_{i}\\sigma_{j}\n", + " m\\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", "\\end{align}\n", @@ -932,7 +922,7 @@ "id": "978473a2", "metadata": {}, "source": [ - "In the calculations above, we subsitute 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." + "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." ] }, { @@ -1559,14 +1549,12 @@ "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", "\n", "**Pending...**
\n", - "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function.\n", - "\n", - "* **For $\\rho \\leq 0$, the authors claimed that: $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$.**" + "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function." ] }, { "cell_type": "markdown", - "id": "b35090c6", + "id": "2c878b7b", "metadata": {}, "source": [ "### Derving Equation (2): Continued" @@ -1757,28 +1745,8 @@ " \\right)\n", " \\right]\n", " \\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "edc051ab", - "metadata": {}, - "source": [ - "Now, we distribute summation into all terms..." - ] - }, - { - "cell_type": "markdown", - "id": "9f44f100", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "f(\\mu^{'},\\sigma^{'}) ={}& \n", - " \\frac{\n", + " ={}&\n", + " \\frac{\n", " \\sum \\limits_{t=1}^{m}T[i+t-1]^{2} + \\sum \\limits_{t=1}^{m}\\mu^{'2} - 2\\mu^{'}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", " }{\n", " \\sigma^{'2}\n", @@ -1835,7 +1803,7 @@ " -\n", " 2\n", " \\frac{\n", - " (m\\rho_{ij}\\sigma_{i}\\sigma_{j} + m\\mu_{i}\\mu_{j}) \n", + " (m\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}) \n", " - \\mu_{j,m+k}\\cdot m\\mu_{i,m}\n", " - \\mu^{'} \\cdot m\\mu_{j,m}\n", " + m\\mu^{'}\\mu_{j,m+k}\n", @@ -1852,7 +1820,7 @@ "id": "f54b458f", "metadata": {}, "source": [ - "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. After subsituting them in the formula above, and factoring out m, we can write it down as:" + "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. After subsituting them in the formula above, and multiply it by $\\frac{1}{m}$ :" ] }, { @@ -1921,7 +1889,7 @@ "id": "96db6201", "metadata": {}, "source": [ - "Therefore, we can now see:" + "Therefore:" ] }, { @@ -1963,7 +1931,7 @@ "id": "317e1594", "metadata": {}, "source": [ - "Recall eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always non-negative. " + "eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always non-negative. " ] }, { From 1c4d7fa96d199b68e5c7373555c1cc365c6d8f67 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 07:09:32 -0600 Subject: [PATCH 33/67] check equations and flow --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index a24785032..814324401 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -1554,7 +1554,7 @@ }, { "cell_type": "markdown", - "id": "2c878b7b", + "id": "a5370108", "metadata": {}, "source": [ "### Derving Equation (2): Continued" From 4335cbdce0a265ff7820e091d5acb3e411f8f717 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 07:23:34 -0600 Subject: [PATCH 34/67] comments are adressed --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 814324401..5ab017a8d 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -510,7 +510,7 @@ "id": "1340817b", "metadata": {}, "source": [ - "Note: In the calculations above, we substitute 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." + "Note: In the calculations above, we substituted 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." ] }, { @@ -868,9 +868,8 @@ " \\mu_{i,m}^{2}\n", " \\right)\n", " - \n", - " \\sigma_{j,m}\\left(\n", + " \\sigma_{j,m} \\cdot\n", " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", " - \n", " \\sigma^{'}\\left(\n", " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", @@ -887,9 +886,8 @@ " \\mu_{i,m}^{2}\n", " \\right)\n", " + \n", - " \\sigma_{j,m}\\left(\n", + " \\sigma_{j,m} \\cdot\n", " \\mu^{'} \\mu_{i,m}\n", - " \\right) \n", " + \n", " \\sigma^{'}\\left(\n", " {\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m} \n", From 58c88f5d35c919e7e287fb6c133b5d2cb329e6f7 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 12:19:31 -0600 Subject: [PATCH 35/67] Improve readabilty of calculations --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 158 ++++++++---------- 1 file changed, 72 insertions(+), 86 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 5ab017a8d..5420a285d 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -5,7 +5,9 @@ "id": "d8ebe111", "metadata": {}, "source": [ - "In this notebook, we would like to derive the eq(2) of the paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf)." + "In this notebook, we would like to derive the eq(2) of the paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf).\n", + "\n", + "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m`. " ] }, { @@ -14,15 +16,7 @@ "metadata": {}, "source": [ "**The idea goes as follows:**
\n", - "\"Given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`?" - ] - }, - { - "cell_type": "markdown", - "id": "03836054", - "metadata": {}, - "source": [ - "In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" + "\"Given the distance profile of $T_{j,m}$, how can we find a lower bound for distance profile of $T_{j,m+k}$\", where $T_{j,m+k}$ represents a sequence that starts from the same index `j` with length `m+k`? In other words, can we find **Lower Bound (LB)** for $d(T_{j,m+k}, T_{i,m+k})$ only by help of $T_{j,m}$, $T_{i,m}$, and $T_{j,m+k}$? (So, the last `k` elements of $T_{i,m+k}$ are unknown)" ] }, { @@ -1567,66 +1561,6 @@ "Now, we would like to derive the second sub-function, where LB is defined for $\\rho_{ij} \\leq 0$." ] }, - { - "cell_type": "markdown", - "id": "7e523470", - "metadata": {}, - "source": [ - "Let us first visit the equation stated by the authors again:" - ] - }, - { - "cell_type": "markdown", - "id": "326d2300", - "metadata": {}, - "source": [ - "$LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\sqrt{m}$, if $\\rho_{ij} \\leq 0$" - ] - }, - { - "cell_type": "markdown", - "id": "86dd8eb5", - "metadata": {}, - "source": [ - "Comparing the equation above with eq(2) of notebook, i.e. $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, shows that we need to prove:" - ] - }, - { - "cell_type": "markdown", - "id": "8670ed3e", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "f(\\mu^{'}, \\sigma^{'}) \\geq{}& \n", - "m\n", - "\\\\\n", - "\\frac{\n", - "f(\\mu^{'}, \\sigma^{'})\n", - "}{\n", - "m} \\geq{}& 1\n", - "\\\\\n", - "\\frac{\n", - "f(\\mu^{'}, \\sigma^{'})\n", - "}{\n", - "m}\n", - "-\n", - "1 \\geq{}& 0 \\quad (13)\n", - "\\end{align} \n", - "$$" - ] - }, - { - "cell_type": "markdown", - "id": "b6b9eff9", - "metadata": {}, - "source": [ - "Therefore, we need to show (13) is correct when $\\rho_{ij} \\leq 0$.\n", - "\n", - "$F \\triangleq \\frac{f(\\mu^{'}, \\sigma^{'})}{m} - 1$ (14)" - ] - }, { "cell_type": "markdown", "id": "a4f11acc", @@ -1818,7 +1752,7 @@ "id": "f54b458f", "metadata": {}, "source": [ - "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. After subsituting them in the formula above, and multiply it by $\\frac{1}{m}$ :" + "Recall that $\\rho_{ii}=1$ and $\\rho_{jj}=1$. Therefore:" ] }, { @@ -1829,7 +1763,8 @@ "\n", "$$\n", "\\begin{align}\n", - "\\frac{f(\\mu^{'},\\sigma^{'})}{m} ={}& \n", + "f(\\mu^{'},\\sigma^{'}) ={}& \n", + " m\\left[\n", " \\frac{\n", " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", " }{\n", @@ -1851,9 +1786,11 @@ " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", " }\n", + " \\right]\n", " \\\\\n", " \\\\\n", " ={}&\n", + " m\\left[\n", " \\frac{\n", " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", " }{\n", @@ -1878,6 +1815,7 @@ " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", " }\n", + " \\right]\n", "\\end{align}\n", "$$\n" ] @@ -1887,7 +1825,7 @@ "id": "96db6201", "metadata": {}, "source": [ - "Therefore:" + "Hence:" ] }, { @@ -1898,7 +1836,10 @@ "\n", "$$\n", "\\begin{align}\n", - "\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 ={}& \n", + " f(\\mu^{'},\\sigma^{'}) ={}& \n", + " m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right] \\quad (16) \n", + " \\\\\n", + " g(\\mu^{'},\\sigma^{'}) ={}& \n", " \\frac{\n", " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", " }{\n", @@ -1919,19 +1860,11 @@ " + \\mu^{'}\\mu_{j,m+k}\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", - " }\n", + " } \\quad(17)\n", "\\end{align}\n", "$$\n" ] }, - { - "cell_type": "markdown", - "id": "317e1594", - "metadata": {}, - "source": [ - "eq(13), $i.e. F=\\frac{f(\\mu^{'},\\sigma^{'})}{m} - 1 \\geq 0$, is equivalent to what claimed in the paper for $\\rho_{ij} \\leq 0$. So, we just need to prove that the right hand side, F, is always non-negative. " - ] - }, { "cell_type": "markdown", "id": "d73539ec", @@ -1940,7 +1873,7 @@ "\n", "$$\n", "\\begin{align}\n", - " F ={}& \n", + " g(\\mu^{'},\\sigma^{'}) ={}& \n", " \\frac{\n", " \\sigma_{i,m}^{2} + \\mu_{i,m}^{2} + \\mu^{'2} - 2\\mu^{'}\\mu_{i,m}\n", " }{\n", @@ -2121,6 +2054,11 @@ " }\\right)\n", " \\right]^{2}\n", " \\\\\n", + " \\geq{}&\n", + " 2\\frac{(-\\rho_{ij})\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}} \\quad (18)\n", + " \\\\\n", + " \\geq{}&\n", + " 0\n", "\\end{align}\n", "$$\n" ] @@ -2130,13 +2068,61 @@ "id": "1f8c0fb5", "metadata": {}, "source": [ - "NOTE: Since $\\rho_{i,j} \\leq 0$, the second term becoms non-negative. Therefore $F \\geq 0$ which, according to eq(14), satisfies equations (13). Therefore, the LB proposed by the authors is correct." + "NOTE: Since $\\rho_{i,j} \\leq 0$, the second term becoms non-negative. Therefore:" + ] + }, + { + "cell_type": "markdown", + "id": "c26f0a33", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " g(\\mu^{'},\\sigma^{'}) \\geq{}& 0\n", + " \\\\\n", + " 1 + g(\\mu^{'},\\sigma^{'}) \\geq{}& 1\n", + " \\\\\n", + " m\\left[1 + g(\\mu^{'},\\sigma^{'})\\right] \\geq{}& m\n", + " \\\\\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d7ae9e69", + "metadata": {}, + "source": [ + "Therefore, according to eq(16), $f(\\mu^{'},\\sigma^{'}) = m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right]$, we have: $f(\\mu^{'},\\sigma^{'}) \\geq m$, and according to eq(2), $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can see that:" + ] + }, + { + "cell_type": "markdown", + "id": "b661f3d9", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " LB ={}& \n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{m} \\quad \\text{ if } \\rho_{ij} \\leq 0\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "1365fad2", + "metadata": {}, + "source": [ + "**NOTE:** Please note that a stronger LB for $\\rho_{ij} \\leq 0$ is $2\\frac{(-\\rho_{ij})\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}$ (see eq(18) above). However, this has $\\sigma^{'}$ which is unknown. we would like to find LB that is only based on known parameters. Therefore, we are okay with the LB proposed in the paper." ] }, { "cell_type": "code", "execution_count": null, - "id": "665164cc", + "id": "52c83826", "metadata": {}, "outputs": [], "source": [] From 9c921c25980fe07224e682e3f1a39778a0f8c9cd Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 12:20:20 -0600 Subject: [PATCH 36/67] DELETED file with old name --- docs/Tutorial_VALMOD_notebook.ipynb | 178 ---------------------------- 1 file changed, 178 deletions(-) delete mode 100644 docs/Tutorial_VALMOD_notebook.ipynb diff --git a/docs/Tutorial_VALMOD_notebook.ipynb b/docs/Tutorial_VALMOD_notebook.ipynb deleted file mode 100644 index 86e244817..000000000 --- a/docs/Tutorial_VALMOD_notebook.ipynb +++ /dev/null @@ -1,178 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "c7a27406", - "metadata": {}, - "source": [ - "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", - "\n", - "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "0adbe18a", - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "\n", - "import stumpy\n", - "from stumpy import core, config\n", - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" - ] - }, - { - "cell_type": "markdown", - "id": "e9d48c97", - "metadata": {}, - "source": [ - "# 1- Introduction" - ] - }, - { - "cell_type": "markdown", - "id": "b0423978", - "metadata": {}, - "source": [ - "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m`. " - ] - }, - { - "cell_type": "markdown", - "id": "4a4af7fd", - "metadata": {}, - "source": [ - "## Motif discovery" - ] - }, - { - "cell_type": "markdown", - "id": "78ac5b0f", - "metadata": {}, - "source": [ - "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", - "\n", - "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", - "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." - ] - }, - { - "cell_type": "markdown", - "id": "7fc09927", - "metadata": {}, - "source": [ - "## Discord Discovery" - ] - }, - { - "cell_type": "markdown", - "id": "0f4ee615", - "metadata": {}, - "source": [ - "First, we need to provide a few definitions...\n", - "\n", - "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", - "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", - "\n", - "**NOTE**:
\n", - "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "37fdbb26", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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LOK7fumjdkmZNyitCdcH52vXPwBVMDCUf3cTGwiiEZr3gFrzLYOv2r/y7RY3LG9Zts/c++I/fPQIf/OMUazoAxbqkJXNvazxEYBGWFByBwpt/9TAqIJevGCudiB/eOgcufWCBNM3kmSuhf6gGf5/m171q5eb6ScDzq+XBAcsWYF72w3vg7RwzV0opXDNlSfMGotCsC4qWa9972ePFFhgQ3vrrh5uWVf96Uh28EgtXp742J5NFIPt5ibykcrkZasRVkbmkfeOGZ+D2Z1fBUw4VeVkkgjzGRYjSuou1zpXnP79rLsxavgUemrfOmMcUD06oROjg/rlr0C7LTWuAgBpqhBPDiDctBcRyCipFD4bvsmURHv7r0sfgR7fPsb5mvubAmpWHzX1DWjeGKRFiIwD+pjMbtBRG5nVQpsLzD8ib7ZZu6IPN28WHI4lF8TDHTVYXTy7ZBA89n19XTbpZUUGvH35+XfOAOsS1InSEKQV3KFxPSO3islQVNE+aymUjqAnwBc6NF1MXboBv/msmfOfGWQAQDr+u5Km1vQOweL3Z7VVYvPzCe+CPDy+EvsHhQgQuXWCbdObyzbB+m1l8IGn5jU5lIh+y/dHmdhVdDI/UhLFXsEgUZJw9aqas5JY0cQUlJ3H3zpXfKJXnAZ8Ws+ZtHxyBoZEa3Dd3DXzumifhF3fjY0MkymhXzZewG5q1RDvjI1c+gXZZVp0aF9lsyVjkWhhVIOg19gQey3c2XdmWLrZzbQJfMYze8btH4GwmsPcn/jwNfuTg9lTX/ez3D8xXWkfLoOJnzqot0jiAmGoftLEwkljslI3sp//n7x9r/uYdwvQ0BCKeEtsVTOqJNxc8tWSjdr/K34DWovvCmq3wgT9OgSWZwNw289C6rQMw8ZzJcLumO2VVERVGAcG1pQWPXq1GtaPnR2iiJI3Rpr7B5ulCyEg0/OsaioKRQFbiZINsK8i+9Ad3w+k/ud8BR2mwXK3c3A/fv+U5OOY7d8Anr56uR4fSwpRMrpp22cY++Okdc9Eb9aRP2d6SNjScuG75H9SfvHo6HP2d21FpRbWAjbcwhLklrfHq0gcWoFygW9n060om9B/9ndvhfZc9Dhu21ee2lRqu1kk378oI/Xh3m/TfJ3zvTnTZEeUhBIVeM4YRL+g1J33ZCpQsXGyUqeB3SLDtK75iGC1clz50uuu51VYudL5WsItum+M0/mJ2HLzhFw9ZxwFsWgr3tMeWN6mjbM/dwBy+8bp1T1f9+3mB+MsEj9d3/u5R7X4lE2t7+93vjeatqlsAXvXoIue0Q0R7jJ42gWsXMt5G/Jv/mglHfRu3KYnQg2+Bb+I5k+GjV04Vvj/x/LsquaEJxSWtqiaq987RswD548ML4bBv3Qbrt4r92C+8bTY8zDE3Lguf+cuT8Jv7XoB5jBvmTTOWwwpBoEZXp77NGEYFCJq67VhH+vuS71W6pCUWRsgT1019eGFLy8IImW6a4Ql2cpKqc3tKhH9MXbih0Kvts7j8oYWwTjL/ucQQMuh1VYGRewiAtetXqGjdyFkuHxu2DaJkqfvmroHzb8bHxGkH2FgYlQEXykd2XA6P1KBWo00Lo2FLCyOZW3jRno/zVvc2LXyyco9cDHJgOYYMAdAuqMbo6RC47nS8xeO6J5Y6LSOihZZLmr8Z8765reCwIZyispi3urcZXFaG1sklTf0bUQxuaMQKkllqXPrAAviAo4CGLpAIfIkQNDhcgy9dNwPec9lj3PS0eeprp5BMyi3y9g0Uv4IkXU2lZyvBxHMm505ohxEWRqZfbJLP15yZHKSqFEab+gZh6sINOcs70WY4zlh2+K9LH4PXMe42ZWA+x13aKRpdjmfNybN8DHUZtHFJY9+9/MJ7uO/Kvl3MtvzkE127pImwbusAbM4o8LcODMNLvn8XfF8SHDlh75llm1NBplkMDI/A0ozLjgi9/UOlusPrjJdEwXHvnDVBuvDrArVeMvXziovuhf931RNNCyPTGEbrtw7A5u1DsEXiyWDkkmYx95198YPw6b9Mb9DBE3Jx+13LK6EzEBVGAcG5hVEglhudhrJjC7po9b7BYW3XxbMvfhD++3J1AOds9YTSTXmb7ZDgii8bKtsHR7zemoVFspFfvZlvJZDMfd/61yw49Ju3GpeTCJpF9gidWwOzc00iwGTHVDYGRLLWJAKkirbO95c9/7GoNWMYyd1NTzz/LvivSx+DL/1tBopuoFNEx0PHSrSoJuRZerseIo/NX9+8DMMVXI5jQgD6HMUM0sHA8Aj8/K55UlnGlUuaiYWRTgD/BJMuuBtOOD9tSZ6428hiqWCUDF//5zNw2o/vg75BtTXYcefdCV+6boYynS58zK0szduf1Ys3IxsHc1f1wpt/9ZBzdydVS2Gs+hIZYHPfEKzpHYD7565txiw03WuefMHd8JLv3xXshUpZtjBc2oz/5pgPszqcIyqMAoLrINWdYibnCusdBTArar/k82TumO/cAWf+7AHuu9tmroSJ50xO+UsnmLVcfp03i6R7hqLYJC5MVNscR3/ndnjbbx5WJyy5Dk271KrN/amgiCqB/g2/eBAWrXMb4BwjrIuQ6H9UfTj5LpnljanVj8685HusNYNeI3m6E7mZ2D40EqxiOcLcPdxHm3JjGCGCXj+7YjNaOf++yx+Hs3/ux2Kryv386scWw6/ueR4ue1B+w20Wt89aBf9E3syXrDUm8phOAH8MD7ZucffPq1uwDwzh+t3kmSvtCiwIafcs07kh/+wnd8yFZ1dsgcfmrzdljV8WMp2suZNvZt3Pmi5pFlZWIzUqXbeNbklzJDDq7HmbB8QW5TW9JcoWeAtCVBiVhKUb+mDaog2pZ9HCqFzMbcRU+NOjfHNdFXiC1dSFG+B///G0F6GLUgprtvTnaLtSIy0XxIdJzJl5N6BhkF1QQlNshsWNe9j2jzmr/MQeGa5RpUtj65YqOS3TPnXqhfekbqZJYv2Ixu+cVb1wqeZmRIQdR3cDAEDfgPokXvR1BBnDqFmPyN6uZeqNTsl8hyfdd7IGYoOfZ5Vkss92vUmIsIdK6c8+5qVxKTIlvPBvScunZ8fionXb4M2/ehh+eOtsdHm9jmMEYRXGST0OjdTQLp3pcvwhuU5dx2oTAODTf5kO/4u8ma8V9FqPNwCApRvcWIW1XLAlBwAeYstVBTYiZst1KZxaEY5N1iq4uca3kFgYsUGvD95zRwAAeOVhezjhrWiXNBY683ezDl30jXC6hldEhVFJOO3H98G7f5+Ov+HawqgNXHULRXIKbRoPjncDz/sufxz+OX0ZV3m3fuuAlVLvhbVb4ZQf3gN/ykTox1B8+28fgSsFfuxFIVmAQ1EYdcrkH+rnXTt1CRx/npug7a7acKBA97txo3sAQM91Iys2Ni2kVQqj5JYVQbJ1WwcKEZCbGx1P9BN3oKwllXBjlb2WV0K7yL4RgYOeS1o+kcuDnYQXXoBZVbyb9dvqrrY6txPK8MyyTbBgrZ+YTUk9HnnubcLbQX3FKOsfGoHbDK1cnFloN617cPSmLtwA9xldcMBH/9CIs5uPy/Amzo5DH6uOlRWJVAntZ4104ZKWpGDl6yToNzsnHbbXeAAA2GunsWj+UIrgxkfMXrlFabnrqhaz8zdmPpd9yznXPwPbJIr4pJ1C2cP4RlQYlYyf3TkXBobrk717CyOxQFtlM2NfSDYVpte8J7lY4SjZp2SbdvP2ITj5gru1ThCzWLy+7jrzkOA2K5n88vTSTfA9w5sybLtOdgEOzRAupJMkFq65spGXB4ZHYBUnaPaGbYPpq13Ni5DCl4URCwKkKVg9vmCDIrU9xo2uL8fbh9SWAqL5u3l9vDK/+N3mviGYdMHdqW/Wqk2DfuXLvXY4E8PIKQKK1RSRhunod2thVMfQcJ4orzuyYzI57HPVb9/2m0fgtQIXcxGwyjd2HRdZJfvC925+Fj7z1yfhySUbue9l3+BKBtaNYfRflz4GH/3TE7C5bwjW9qpv6vv30yukrtHHnXcHnNVwR5SEpGuL6Wr1lv5cvCDM0uHCwkiehp9ow7ZB2F5A7C5p/2be9TQVRpRJV/9XR2bCJJ2yYD2s2zoAb/zlQ/DJq6cr6Ok3EO/WRRO5T5bluieWwp8fWyx87yJwdpUQFUYl49f3vgBXNzqkaxcymatu1Bflkbgt2LYDu3aIXESSWwbu0AzAlyqn8W9Zyj/TPV7OJS0QjRFm0/roC+uaCt5Oxlf+9jSceuE9ubHyku/fBS/5/l3Oy8s2jUqp52IupdDy1f/R7XOs6akwtqfuktaPjB8BkO+zTQW14vtlrn267hs5ngLamtQyMYxUU2U4nEd4B2+T5UH0/9u0/M20vDHClpwoqou6eYuHVjxXlbWi5J3npX3ZxrqCqrefr2RvHU6JGblxxgru5hOLZgwjzdnjpT+8Gx5boHZr/eK1T8Fv73tB+J51L0p4uPu51fDXKemNrpZLWqAbhJf9MO0yjgXbh43jmxnkecn374L/uORR7XyqtsL0Nd6BbDPodWpzSHPpXOCqxxbDu5HfPmv5FlioEQvy9lkr4cXfvSNngZm1kZB9ElohLqeCotEuiAqjAJBoe10rjELZiFcFXQLlDha8bMkGzkc8KXazWOQCzyvJpHyTkw2faCng+O9nLd8M//2HKXDhrf6VB6EjUXQWFSct2ybNYgVyU5FdihXubp+1ytg9wIVLZEtBLU8nE4K4Vg0aPIV0S9qIwMJIxKIO7wF9ZkQGovWIfXzzM/XLG5Zt7OO+t4WsL3FjGDGFJz+7CIH75qyBI8+9zUqpYQIX47g5TUu+1+d8IaJ913OrYagxN3z7xlnwjRtmGpdhGsNI57bR1VvUlkgsDx//8zT41r9mAaUUPvfXJ+HeOauR+cuf1VSy5EqOZbOapik3isDSCLqzV+IvgtGhi6XBrvW8oNdGFkbIdIvW96kTQT10xxk/vR9dfuJV8fTSTannOt4hLnq6i8DZVUJUGAWA5PTTtUsaz3c+Qad0cB0k7WC6CU4mZnYiSpRQpm5uuHLTp0xlnA7pBZurI6mvbH2v2aIvELD41r9mwsV36d0+8vzqXrhvrjyuwPqGq9V8T7EgVCiqWddtVQunKrnSt1ufqo+7cknTGUvTF2+ET/9lOpx/i5mrpw5EXGFNpGtNYZJD27LuTAQxbzGMNOfyfNBrcf4QNlcRaei4CNzwZP0WrDkrW0H8i5pjubekMb+TftvTTeBnd82FgeEaKgbR1IXuXWfVLmnhS5Msh4/OXwef+PO0lMJmtYXMwSr3ykaWh5nLN8PkmSvh/JufK2W+uurRRXDXczhllS5MZYz/+dvTzm6nS1B0zeJiGOUth0bxXNKSfyswjhMkB0DZ5T0fw0hNSykr1aiwbpq3pFWo7mwQFUYBoKvZ+R27pGXN8zqkU5si8f821ds1q7cxifxg8nPNALY+rL1Yi4RBjo+7L9eQhOr2wRG4acbyBg8GGqMGslVzyg/vEWYdHK4pN4F/nbIEfnnP83h+AOB1Fz/YPLUQfUvrJLF8wdAnJl1wtzNaruacvEtaC+/83SPNfpigDKu15Ia35RvzcTx06kFHEM72xC6kACN7zRteWjxpuT7g02bx9t88DJ/765MAUI/zccszK3JpdBX10cKoTSBodrZ9ucrSgo7SlDGMmnFxiPLmNxZPCWL5mAC7ztnWWN/gCJx7o7mFjww8t/2N2+Q3ceqCNtvKKVkjZJsssUzab9dxWnRcjYLv/vtZ+MSfpzmiZo7seviLu/Py4TdumAnXTl2CpuETTqz7kkMhhu9E0cIzThDZFyxevy13iFj2XrJLcLivdXCNlJV+euc8YQwmlVdCuyEqjAJAw0ow41dqj+ymif2z7AEfIpouaQbKnaeXboI1vfVTqhWbtsPdz62Gyx9a2Hy/eH0fXPHwQlF2I7QsdfTMm22R1M73b3kOvnTdDJiyYD1qov7l3c+nNva8BU2FI869DT77V3kAPVuIuAlJMCwbzU1MSbaKzS5DAZ5asgm+dN2M1HtXN0Rivg7THTDjQ2djKEqT8KJWmNEGHY7gaG1hhB8gTatMgzH19LL66TlAPc7H5695Kpcmmcuzn4S8JE2KNtcbVxKqeYkbHJb5bXqus3DdtlxgYtk4UPWdpN8+MG+tlpWcDysX5UwiSYC5BfFPjy6Cvzwu3qhj8JM75sDMZZtzz4u4+TRpnq4ABIMsB7pyfnJhRZFWZVhSNmVihtC1U5dwXRObigXj0t2jObdIxnvLcqj1LIlhNJRySUsskfhfePpP7nd6iOgCyWdnec7teTVuk5NBZCXXumQkpN7hD1FhFABkFkaPza8HxZu/ditceNtsrUkzK2h0Rpc2B+aWtP/7x9Pwjt8+knv+9t8+AtdOrQe3/Of0ZfDxzKnKey97HM6/5TnY1DeYy+sCRSqMEqxqmHFvHRhGTZgX3z0PvnTdDEaor0PXCuCOZ/2YOCcQsZOcwHQ7FMq//s9n0GldLUomgtfQSC0dQ6MAQZyHzY1g8aqqEH3jHc+u0nPbcPR9vmI9ZbtispaoBf7Gv5x3PF4xm0IZbpqxHA7+xmRhfKcvXTfD2dXQLGxdgWW5QwruHdGAzrzEUx4Z9Jc1vf1wxk/vh+/d/GyaFVkMI17fYS2MmDG4tBFjCaW8dtglXfbuFZK4My6UD7OWb4G3/fbh3POsrKGL++bI3dQBwrI8zvJAm8/VfUPHOq2M82bxIYnfepfGMPJasqzc5mlr6jnLa9Ivr2+43gK0FEYjHJc0HRGlbHuDliV1+rkLMUsc/47C9MUbUsq2IhTSISEqjAKAyLwOoB4MDADgo1c+AZc+sEB5bSl7pbVsk9Ih/VsLGAujf0xfBjMygdYwSG4eEk0sj81fb6VM4ikT3vSrh+D2Wea3sKnALk5aHmmZFbiowMlYiBQzpsEtZeDdoJPjh1Ivm2kdfPrq6fDi796Re+5joZRtIN57WX0+FLXRP6cvg6/982nhadmnrp4O/3XpY/ZMSsAr2UdASR5aJ2/5d1sHhmHpBvXmU7dNMdY7P759LlDaio9104zlsG7rQDPvhm2D8MgL6xTl8Bm7TuJGkFjtJv0lS6NWoyl3mNyGK6ypKcIzTJaizX11JXZyuIcBNwg0MyrZ+ULH4tmLhRHOWFGfbuNfmaJl+uINMGeVftDgBNgNnYiDL16Xt1rMonVLWvnIGjnpzF9bBDfNhQIby1eXQaSLQashTRWqlFJYuG5byv2OGzuNttJXBaLDfZ1v0FX2zFu9Fd51yWPw5Yw1uw6NqiMqjAIA91YaBhfeOhtWKBRFAAA3PrUcXvL9u5qR43MWRp3Sqy3hM0A1D/1DI/C+yx+Hj1z5hFY+1gdXxPKUhXgh1gZGVcY/JHGOKQvWw5k/ux+tdBHxgxFwfeDaqUvhqG/f3rxCuAzcIzhptblyWZgHkUl0S9r//uNp+Pu0Zc6uiNUhI3MHwHxTS4DBmFHz0ySnrTzh+j2XPgan/fi+dBkcMry88phH4lNOHtZtHYAvXTcDPnZV2gpz1x1GK3LWMThcg+dWtDaR50huOBJtMhIeZ6/aknKHiS5p7QGcgRHPxMi8LJ11QbZxA0i71DYD1NN68NX1kksJnHpFNQOIq+Z4ycEkZt6TvHvXJY/BG37xkBV9gDSPrmOstVzV7SpfPu/jPnRt70DONTKByhJHL86eP6jkLxNYuVk3qy2c/RPKJY2KPQ9S4Uka/4ZyWzEGohuts8p12ScRQbuK8lz9+CIASLuniVzj2hVRYRQAVFfzXfrgAtQNao/Or5/QJicyOe0r+7sz+rcRFq/vg75Bv6ctaeGw/se81b2C1GnwTyf5YIPgrjK4jpQHnmBhE6jX92T7vZufg/lrt8ELa3C3m4m4KTqGEaUUBoZH4NZGnJaFa7c5pW9jyq0K9pc8X+2oz+Xpy/uMkz7FqZ5Vm/vRpvtps28/fTz7mbK++SyjZJFxo1t3udSKjVNi9bNq8/YU/+PH9EjzJZvsW55ZCW/6lXgTyWIkE8No8Yb0Nb9DFnEDRV8ZD2bKh2kcMJt5I9sfZMOAN05Z1xFWdkt+UwC48pFFcLIknojq8BGD4ZEaDA7X0DHVTKssyefzdrHWoZpZftFYfnLJRph4zmR4asnGZp+xrXoX08bGviH4ZkqB7mvdKX6Ok8Vk9QlMsxZ9eJCVJ/46ZUnuQLRGcX2yFcNIo/ySl7jku7IKIpODQuy3JAdL7AVD77rkUf0CK4yoMAoAOgumzilW3sKI+R2QtjwctOrkm5JTa4B63d43Z432wslrvqarE5JGUmSSL8vCnFUtxVMysV4zdQmceuE9MGt5PjCkKVhhzOh2gkZ9h+aSJkKtAAGXxRWPLIIjz7296cbjWrHmYg5QUZBZf6hoXvXoIph4zmQYGM5bhqnKdVJXNC8Yn/HT++Gdv8MJCVhLxVRsKEBaRwgSYQP3twyM8un4t6TV8egL6+DvGTfKnEuatGRzmGxSsv3g/rlr5TQ1mB8YrsHfpy3N0ShbmO5kNBXZhnObSS5xe4s7E28NuWDy7OZvdvyyvx+Yl+6/uRIt16YrH1kIh33rNjji3NsK2wS7OoChFOCS++en5Alb0qKmfaAxj5x/y3PO5AJX6/vds1sWEAlJAkTPssqD5XAW7/jtI/CGXzyITm9TPb4UXCZ0120daMViRJWBS3fxXfNSf9co1WrzIqxk5q7qbSpabdCyMEo/1/kG0YGpTi30D9WVR52y5keFUQBwcSrEQ1U24qGAHfRLMifRWfz+gfnw0T89AXfPVgdFxEJX2GuengMVLlzJxPr4gnqg3/lrcVY2urDxHfa9UOnKcSJ2WieJxUjSNz5Vv1FupScrHRfwIYglNH95T933fisntkKzWFFbeYoBv10jlhTLg6ia7nx2Fbz4u3fAk6wApXPSl/m7efKmsgqQvZO06X//YQp8LROoPbu5CMlVqzVHpiGaawnUv/+aKUugt3+Ik7OFn945F772z2fg3oy7Zlx1y4fYrSX/gu3vJmuRyU1/qqSs7CY6GOLBdm363s3PaecJqb//6PY5cPPTK5p/285FQpfWBt2nlmyCf05f5qQsV/XIzm2+2sbFsj9j6abU4WaC6Yv5ygReWixc1IMrUWfSBXfDqT+8xw0xBhszMVDr/KY7ZVP25h4U4T/QVCF//9z6WnmbZWxV0UVRWgojgWePiUzbKQYYUWEUAFi3IRV01iTZFYOdohH1hWWNm0vW9Npv5nWbIpnoUi4vAiKJ8KByIbKFjW4yPL0mnyFR3Bx/XCQKquRvfdz41HJ4UHAqbeWSZsGTC6gWaCdxyIipxUE91zBCa/VwI9DzM0wgfR3hI28hI45hxMvHS8arO9nalDfSUcTKYNchwW8eTKwnTA5Npi/eCN/810w498ZZ0vkyuWBiSz/+tDjCL3SuwObpnO1CnfA3Z9y0gpfJOBtJKbGab5U8uDx7xFs84+cGbjmONczseGzJPaq5hf9cNH3wFHO2yrrljmIUirgISI+fQraKr358MUxZkI+9ybudGABQH2Y1rj2cgKgOntgiTVmvUYp0SWukL+CiZVfyItYlTRrDqJnHnqvw9jB+4FVhRAg5khAyg/lvCyHky4SQ8wghy5nnb/LJR+joKsjCKCqJ5KCC33zY+canym2aDeshiWsl4yHpWqkFSIPpWcs3wzdueIbr4pJaRw3qIcmCnbBFAfzQ5SF5FMflKdbCqNkvLMr78t9mwIeumOqIozx8zCnNjZyMOE3+4acpMsaCcLPBWhih6ODbWeyShi8PoB7z4ohzb4OpCzc0n9kKjq6DyrbS6rdpK4YRhe2DatdGQkhTmF8nCS4MwLr/2fMZoYftgyPS4M+YjpW006eung4L19Xjw5mcFJs0t2iMtDZvPKWtmq4PWVLVn217u+vllHe5hTGPooM43jPL78DGZVMhLevxnyuhqDDfFhWrtri1qvbtfh+SVW0CSnEyRVI3WhZGJvK+w3WxO7lZ3MLCSASbQ8J2h1eFEaV0LqX0RErpiQBwMgD0AcC/Gq8vTt5RSm/1yUfo6CYE+odGYP1W82vVI8wxMDwCX/3701quP04tLAwtVzDX7WaVG3X3NXmeY79ze/P3J/48Da6duhRWMgt4ll0Kemb52VM/7LXB/2l4Hbp7lzQjNrSRVSSGtCa1AqKWw1Tr5iD5e1vYfJ6plZOWEiXzN9ZaNXn95JKNMDhcg9/d/0LzHfeWNAQteXkCxZ4mHV0kJP/78ilwNDOvieYEnblCeLWvDoMRUoist97+24elwZ8xYNspuXXPbCNU/1en74gOHZLiTecOl4cZ2GunTcdty4LWnGeeIiCJKwLQUqClFCca9EUbUJ5iznb+6uMotE2QdknzMxv5XvYJIbB0Q59WjCMZ7CwH7WkUhbRlEs0H4ufkSb7LRu7AAGPtewMT+F+Glkta+rnON9gGxE+Va0+iEijSJe1MAJhPKV1cYJnBoX9oBK6ZsiT1rLsL4EN/nAof//M0QS4+sBvtBFWY8MrAfXPWwPVPLoPz/v0sOk9z4jWo1KUb+mD5prr58bKN2+GuRpBCXbGpeXsKVVscsIteNunSDX2pYJrbGMFlh9Hd9WcD8lvjkq6I+Yassg3bjZ9m3HZ8QiRkJZYERVkYJQjx9Aq7mTABSgFhsETbxnTTVY6x6dUuEYyQzyTd0j/EtYwR0mn8q3RJSxS8nDJ5WeXGXumXvrqrjaUdNvZUtgRZLXY3N6MZhVFcZ51gYHgEjj/vTu67eav5sfjYQwwVdPs5i43bBmHiOZPhHibAsIgX3XcAAgsjBF9uXdJwxDY06oIHzDzt08Ko1R8MlfcO+CkaKcNvRplp44JeBq58ZJFV3CIWNu1YtvxleihXvyUNYWGUWDV6XrjYKU3E1Vf+/jSKlug6++y8yY77rPwgWiuMqqGKE4UBilQYvRcArmX+/jwh5BlCyBWEkN0K5KNUXHzXPPjmv9I3BxFCYOqiDYIcabB9Xh2nwuxdp4HnEqaqHxsLo9N+fB+87/LHm38n/UF3Q9Q8GZBw0YxhxGjTswvQWT9/AD4scFsa11AYZW9yyvOSWBihVEapv0ILzi50SWv8K/tElxY3zFKXe+ICLgShj131hD2RDL5+/TPw2/taFi+8PtXq+3gMjej7WtnEfdNtLV5zHH/enXDWzx8Ql5EphHeijsnHQldwFIRRyjxrPTTduLi2Zjv+vDvg2zfOSj0jhKD5EwUY75QAmL4xYOGCnO0q81b3osY/r+8v3dAHdz2XVgzNXlW3SLr8oQXC9pbHMOI/b8YwMnRJ83GBiqpY24Mc1xzz+o3p1KEKep0qw6yIwpDleZKlhV4W/8jcnhkS3FiRmClxywL2ljQzlzT9L3epkOoWWAfJthJCK+eS3NiqiEIURoSQ0QDwNgD4R+PRJQBwKACcCAArAeBngnyfJIRMI4RMW7tWfp1oVbB+W97trNtw56ZrthwFWT5MaqVLMGHZwGYDL2rbhM+0+1gaMsF8h9E9AMC3MGI3gToWRgkWrN0GSzf0FXKdJ0C9ju6dsxomnjMZ1vaK41+IuMHckva23wgCMxogWci6u5LynZFu0Len8eSSTXzaFjT/9dRy+Mkdc6VpTOgPG1QgW0eq+VamLNUpOZs2sUaUpV6/dQBWbt7OnLzJy8hfiCB+x+dK/Iav4FNoYUHdH+9XXCmuAwIAW/qH4dmGKxL7HItuwU0t8TDGDbJtMWPpJrjjWfntOi3Lx1YjLNvYB2df/CBccMtzakUq59kbf/kQfEJi/Z3QnL92KwwMs9Yt+gt6Uv6IYR9yGaAXa0UqW78xY8F1UOFUDCONIOg8iC23w7XWYb9f9t3ZGG1U8JsHXr38X+b2TN/Q3f2YouV+r04jwuHfuhXmrNoiTZOm14Lrvpt917IwyqebtXxz8zcvELkrfnSRjD9WsT5r+Wb465S0A5O0TJHS3qDGi9rDlI2iLIzeCABPUkpXAwBQSldTSkcopTUAuBwATuFlopReRimdRCmdNGHChIJY9QteHzU9FdI+8WYniag8aoJrmq7Ik43DUyYwLmnACNI6LI8fI1YYtcqnqRhGA8MjKHfJzduH4LQf3+d9smUX8ysfWQQAAM+tFC/ewr1tYkUlKWsms8C6Qoim5CxHE8+ZDNdPx/me60DWK9QxevLvhyyDptta3uDzqTNm05x8wd3w8gvvRceWyr62uVp81WY3t/uoMPmZldp5bEaOqhqaQa/LXwI6Au/47SPwqauno9KyTbJxWz0O0vQlG5X52HWrb3AYvn3jLKV1bYKhEQrfuGGmOiHI1pg8H6136o6GFSU39w3B5u3y2/2w7lzSU31JPp5lty54VcLGMPIVf4YfCyZdSK1G4Ye3zoaVBc2PCbb0t/qrL/m0iP2DyzKsYhg5EL+GRih8+8ZZisMfPJJ1XsYa5VkYyQ61OJX0ll8/3PzNXp6STZlSNgrqekRz7yFDYknNKoze8uuHYY3kIFjokubC+qxDZICiFEbvA8YdjRCyL/PunQAwK5ejTeHyYELkykMpwJ8fW5TbFHdIn9ZGc2HS8EnTub5XWT7CckWaX/KOG5xRg+uWSxpzaiWpLgIEjjz3dvj8tU+iyyhywzU80lL66LgoHffdO+Dr19c3A9h2mrZoA0w8ZzIsWMuPt6FSqrHxB9i/XcHlXPS3gs3RTepiyOD6L4wghMH0xfzNKkvTpD1yLmlIV1nZe163lH37WT9PBybNfsdIjcI6xrI25eYX2KqU5V323U0Lo3gbqReYWJ7INgGU6o2xPz26CK5+fDH/paCNpy2qj/PtgyNw41PLpfRHajRlkVQnWyfsO+j1CeffCSd8jx8fqgkkLbmFkfo79C+lkNNMWXk1aSvkOU21FYbnJ5dshMseXABfRcZlKRs6NSBqAt4NdWpi+lkA3PBbJJ5YtBFeedG92vn4B9rqD0LHMGLS+4Rbl7T6vzo3OGKVpyZshibH+IJ3hREhZAcAeB0A3MA8/jEhZCYh5BkAOAMA/sc3H+2I7ABkF73v3CQP4BzCBBoKbOpCNy9PMMGctImUDnUCmi4vTOLnV8uDCiY8YZUbSYZbZ8pcB9K0MDGMXMU5SgTxD10xFQ7/1m3cNLzJv5c5Ze5Czpo3NDYMj8znm/LyNgWDjBVM9haZkBalbY5udDFFM4aRxgAcMvXzaEDUB0WbDba9PnplPtbT/XPXNDek6dtNAO58dhV88dqnhLyIvqR11bviWyWvdS9TyCJbH395fHGqX6fYYIoqtH8LBen0c1n/ErqkBTRO2x1retU3m4quGeeBbcut/WrLIgKE24d/cOtzqTUjCwoAX7zuKTjy3NvTzxu0uDGMlNyU4yplYsXCzge6ikHV9JS2MMrT5scf0vsGXj1nKSQu0Cau0D6gqmedwxHR66O+fbvgjR4wPUJL5nUwJ2fr5KYZy+H+uWGFSmH7O9fCSOJOoVLo6MyjPFA7A+8URLekmcBH32hXeFcYUUr7KKV7UEo3M88+SCk9jlJ6PKX0bZRSfVvzioKrMNDosGx+3QPz1K09elnbGslEKVqkeAKRTdDrHH1Emtf+7AFJfqoU2pquKpnnr7tYfm1pc2Ou4FKnD2dZxWxQ//DQAjR9EUZqFKYuRASXV7DjKuYCb1NwxLktJVbebchJsZUDgXydJ/1Np0qMXNKYAnQCoGLwEUaJlI0p8Mmrp8O/n16hw16KF7W+SGwVw7UwUnIixrMrxG6aIXZpbHs2lelxnJaG1wvWL9MmYNsOc7MeBcpd+1ZtFrtGJJC5WPJd0pQknd6Shi1XdpgjenPEubc13+nyrL7spfXen3WumulWzEO3ZesgZcGqk6/AmRl74Y8NnLgdZerkS9fNsCfqEVhlSivotQ51sfwg5sewM3KQjD+VJWZ6Lsi4pDmMQ9spa36Rt6RFCGDa2bRjapgV0zEQCQHXPZF3t2kFvdZtA54g2FBYISfRm2akN5IY4aWZhMr7W1b4k/UxVmmWZDM5bcSY36/aoj5JzuKDf5yS2qxiY1GouHElAKqsppoCdVf6bxs8vmC9s6tqi4To6nJhLBDOM9lJL6UUfn3P81IetE+zNNO7cEkjSGu0JN+djduf0rfBWVoYZb5j3KhuVL4QhC6tNhCsAQF8RsdgY186Dg+RrMu6mxoT9xrbeHOf+PM0OO/fzxqfnLu0MGJEBinkNxOpy9HlWUfubSl1cQdqunRTECiOywyQnb5W3CFdz5M1IW7XAycHuxIifYMjsJFzoZEp0hbHZtzL2ohnTYY9dDaFj1ilOv0wm/aFNVsbz4vlo8qICqOCwTWH1ehrbH7tW9JSp9id0cEx4MbkYX7f8GQ+oK+fYIq4CTlrBttF1AsiG8BStgBl4/rITePT5q/1/OoKyabAuJuZCF0PPb8Ozr1xVnPMYIPLq8aGLi+i1NjTEWwgYwy++S9cUFZbuJxfPn/tkzkll6EIJXyzfNN2+Nld81LPCLhVpMiQ7lKIMSRI0oxhpLQwEtPTjWGURYkH6tbIxmWTfXZS167cZSPSKLIf8SyG+xButyKXNBVEc8lDz6+DPz26iJ8H1NdkY92lMcAuc9kvedDhbYbc8gzlZZdAXVeeyJWBWBjp4IG5a+GRF9aJ6Rry4wMo9zULhjEHsp+75kk46ft3mRfiAbxPlj3TUejkrN8RPWKEyvceOkjmT8za+87fPQJfvu4pDdoG/OhnqSSiwqhguFw8tDW2ndKrNcG3+jHPK03P24w1/iUE4Ct/mwEPPa8ncGWFVm4aZiMptMqgNGeF0bIcktPX6YrZtBgff9ObBE2gtjDCKp7k75VxoZrloYprOyT198gL+RhQ2pZ9VH5DB8+awESxKcuPzqczljKlYE/UZfVnGnA3wZSFG1J1JaJWn7d8n1T7GzyiW9LiYUx5sD3ISbmkIeO08Yry1e3U63zxPmnZdexDV0yFfz+9Ajb1DQJmFtSPYcQq8RW0EVeim4AfwygrO1Fh2tBxzg0z4f1/mCJ8X7UpzkZRoTOnuJr707GIzGjUFDJPiz5tpDcrBwunFmMNWphQjU8t2QQ3zlghnGdyh2cGfaVq48EUUWEUAEz7msGlP9ZltiNMBvsfHl5onFdUPoF6oOQP/nGqNH0WslPFnJUKiNu+RvNxXrjxmzJ/z1vVC49lAjuP6hYLSVmamI24E5mrpE5/7o2z4FNXT8s9xwbDdLoJUCr+wp8ZBoZH4FFBIHFTsIFSWagsb1jYtBIBucl31txdJNQkwSDtLIw4CnSNwXPvnDVw6YPzpfTKhsh9QOeWNJFyLryvDQeUUvg78kZFm3p04caRjWF03HfvgI9fNa1B3w5sfuz0fuvMlbBB4fbi1iWNH/cwC974/uK1T8EXrn1KOn54lt0YaCnuHcaaTJFFMN2MjVmmSxrz4U658DzJESBula4u5HQEkfWO3NJcWOLoKoC0LIw0edGlryy/ua+RY8n6vlweES0rfjpk1Y8Ko8LBOZkw7LDa1i0d0ql1YWM6rFujsvSmCyRpOM9I06RuOOCnrVGau3o8sTZgc7AWUQAAP7trHnzt+mdS+UZ146cWXy5pWWDbSjUcTXi549nVuWfYm6ywJ1xDIzX41T3PC0/GN/cNwYJ12xSc+sf2wRH4yR1zcldKY3HhrXPg3BtnaeVR1d3gSF5hlG1lfasmreStfJxn593Mv/VSFMNIbWGULZM9tbdfJxasxfWzslakn2fcDxMQjUgNzQDjmXEcoH4sGNz13Gr42j+fUSc0heUywTZd1uqwd2AY7p6dn8eLUrL/5fElMHN5OoD8NmRcPhNgA0aLlrFVm3FxB3WXUxNLiPQ32MsSPAr5ObWOUoNeN/4lhJSquNJF/SIXRRqNcWejrNAJnL5mizrYfVHAxnFLHqnkUWn3QdSNSwsmLK3//P1jyjSywzPX/FQdUWFUMGzn7HQcouLytjOsTjIDr8csfzVKYdqijdy0NUpzMYhMJ0KZwihLEqMw6hYMnKseXQQPPy/2tU+Vi/wWVTK8ACinpHL9aQo5yPL+OX0Z/PyuefBLQfDmLyD8uIvoz5c8MB9+e998+MvjS6TpRALM/LVbjcqVfZro2vcUP9j+Y1mHvPwiJWA2bdI3Zbz+4aEF0oC+PMtVm28KfY5kobM+E4FLWjyXEaNf46ZCG0WMbGMkA7uxlM0JoniHvPcq2IiEH2VuWkywYtN2eFQSfwYLLF+yzTimzp9dsQVZEo5oynqr+cxiM8xNr86Q9F8nh12mhw9MRreGyp0zyenUmysrGtsA0wAgjcHH2wvqyPpGShWHWhUsJdZKVDhmXVifdchw6CmbgQi9/po6CfZYTiehaTrM+g03amvG0k1CdxU2HRYyIdh0kcD6KgPUFSzzVvM33JQCDI/wXdJ0J0SpwihDC2dhxH/+3X/zLS9YYIXGBMqg1+jg2fL3w4gA4QB4/pMNjujUefnGvtTfPk2+ZZwmyopsgPUsegXf4SMmxIBgc8h+h/YlAxpzwxWPLIIdRncL82GvbscESL9g8uzcM5VLmi+EdoiRVgTIg3SKXdIC+JBAMbZHfkbZNzgM40Z1W1tDpJQGGqRcHSrolGOzj8peSU4phbMvfhC2DgzDoovebE4YdCxyJQojKRH/46TZj5BF9Q+NwDHfuV2Zjh/DKI1E8V4dux48fM/VLhQmLFywW4VZne2W2HW8aWGk0aiTZ67U4KpFv3UGajm/N9099fPknkN2/TbiyChX1RAtjAoGxpQVC5PAr60/zMpsSySTWMptC2BNbz+847eP5MzAU1mpO5N0UxlZdpKQpf38GrF1Rt3CSH1LWpOmpLzRshhGGW4xG3GskiYLNtdVjy5G5cHWpQqqBVjpNtT4NxFOla5yXXJ3pNE96uvNi5wWTEUGTAB0nnuArP4GEFdoi07IstzMWbWleWUrFgvXbZOetC/ZsI1vYp5pMewtaXk6LXBvSdMjB9ilJrRliBDSbNDHF2yQpu0SuP+FoPgKFeNGi+eg9VsH4Jjv3AGXPFCPf2VSjbZBjjGbppWbt8ONTy2vl0f8tLeNvmyrIze15LtUClCZwsuH8lSHZuuwBYd1WwdQCjzVbcf9QyPw8T9Pa6Ql0D80Ai/74d1wD8el0Se0al/HwkSXEU1MX7wRbpqxHJUWo1x2YdxCKYXhkRosKsCtP7sXyeKaKUtyh7tZcK0s+Q+F6UX4VcaKHZPVtg0GhkealtYu51wXtKJLWoQXlOmSlqITnKheHkR10Teg3kRqK+0k7/jKRIq4TUtywpehLmO3RvOBmLkCNEK7P1pxksxiBGFp48KqhBd/gguVYsbRLWmqoNfZ2Foyepv7hpTuSDpt4hO2ClYfMSGEFkYMr1i2120dhLN+/oDFQUD+2bzVW+GyBxe00gjyipQYOnBtYYS32nBX7uL122Duql5rOlu2izffyWUDMeg1HmNHiRVGq7bUY97c/LT+6XUW/JtPqXLuwSg6//vyKfCP6ctAnVJaEpoPJSV2jjLgREgXcBtJ3dsjXcK1qxkWKrLTF29s/u4iACs398PqLQPw/Vue88OQCEz1VMnS6YpHFsLGvqGy2QCAdPD3C2+bA6/56f2wYtN2J7RvmrEc7nx2lXa+ZRu3w9WPyw9Aa4j5DgBvYWTbf2zlijN+cj8c3bD+M5EVsFarqDrLHRJ1xqofxg6i42FoBGdxihzRgtC9AzG/1C2M3PDBm9A+efV0OOSbt1rzgL3VIxfzqLGP1p2gpUGvM6Qwt4VhrEqE0JQalUIoko7qs7CKQMxtNW/9zcMtZYGA7hhEIPIiFr6sIkwXJspD1XeJFEYsbK+bx0JUytSFeYuXHEuIGEaqQrm3pGl+O7qJPNXp6T+5H17/iwet6cjcJpNxmXcXjCutCBhXZV0rOUop3D5rJQyP1LjKdYz7w9WPLYZv/msmqkxMMOcKxRcWQqf+eVBZX7lUqIvQ6g9uFUtcCyM2XARTHLteuZ4Z7n5OfgjWkiHcompznA2/7JyS3M4quq1Qt5gvXTcDPnn1dGkakTy6efsQ/O0J8Y2Tchkg31d9N6ltDKMVzLybkHIS68maQufsraPCqGDwOrjWaVLqt6Z1iyPrpHaDqCowkxGV5Oem16z3uxQCQYsHPuGWz7AatJbnz3STrBP0GnPyUKQArnT9wp5UKHqGqm7zFkbi9Es29DUDg4td0sKa7k0Xe1PlIdseE8+ZnBpbvBvbCEn3Vd0TMp9TrIoVmxs03Zjvp6mXBd2ekh3aMs6bt6RFCyMnSOpRVyF89eOL4dN/eRL+9RTOhYWHxxash2umLDE6uS7bJS1VviYvH79qGsxYuolPF0lS6pJW8mAQKXWz0OVTJ8aWT9nlotvnSN+nvsshI1Wb49z0Q4y1TrE1IwuXweNXxp0N75j6dWmI6NMlDUM6l6dqA8IQYe0gOgD8kwkz6FsYdUiv1kRrY05Sz/AWRiXXK6J4rIWR6BnvE2Ub/h5JDKMsMBZGpi5pJsFT1QojN3R036tqKflUkSJqDEJh5Em+FJZhAtN4Vllc+cjC5u8hjoVRXijgc/7YgvVctwzTecHFfKK9NqQOE/iZb356hVdeyp5GAeqm/jc82VI8SC8pEFj0hfAdoUJWn0k1Nsc3sh4fmLsWAOTublgYXdluUI6vPqKr1L579mr4suj2zAYt21h8rqFTWpEuaWl3xtYfPi5pSNCjsxY6bKeqzXE2e59mHKyCvvnGp5bDbbPUbmqqA7caxfFc1L6QnSesQ7M45NkFrdL3gAUhKowqhpnLNjV/23TRzujeOCQTxrqtA8wzpMJIc7rxMTnLbknTKa9G819jeiogswLJu72pC+m2WGFci2usEurh58XXF+vEy0BBkT6pcxHdIi2MMK4IhbqkqXgSPWdeiLrpvNVb4ZL7X3C2OVm/lW/uzkPumwzHK8aS6naNWAuyoJ2YODFl4p+p+DRiJJ+Yc0kL8qvCgKxmWhZGejQ39NXHy/ixPczmjl+SWkmv13aiMV9kXB+2pI9dNc05Xd76vLa3JSsVHfQ6RR+rjFa813dJ07Mw8qUyUq2FFsZnCrrVmuNU/WRQ5pKeXDqSf6RdDgZf/tsMJzTRt6RRXDmYPj9So0I5waVi2VaG5NES/c3No/i7XREVRgVDdTKhwv/94xkmn7aJUQQHicDDCkEAuAmSIrX4PiFTGCXAuP9wb0dKLIzYZwlNCUmZgid3SxpCuC7SJU21sLFC2gf+OEVCxxlLKCR8ieozqzBK+sQdzAKfjv3hB7bCJsZ4TbcEHslsn5P10/lr8zenmM4L5wsCo6b5kRPXbTt2LeGF7aEUlLeyZNM3fyNbI8TlSbYGiFzSIsTIVtUR594Gb/rlQ4139Zetm630NjyqZyhaJnkymf72xBK4e/Ya5+UUDVkdshdIyORQPzGM8BmbVoBI6wYsaZ5SMyUjseuoR+GlS7GDS9YsX7f5VQWqb//YVU+4KccJFTfAzotNhZFNWY3cvf3iQOU1vPigLk/i+aBNS/nAhEh7IiqMAoDOBsrmxCC9oHVID8eAUxeUUlzcH45VjjwDPmnRJClH8ZTdDE1+ZiU8s6zuNy2rH5nbULYM70GvJeCNA1mgWwC88kq1kVT1m9xNDIr0SZ0LYxhx4kr1D43ApwRBF30Kujb0TVzSXEx3svYsS2kgjF1mQVP0LUOI2wx1EfoyJFsnEwWtKyuvTsTgcA2eW7kFABiXNN1LCpgdTzPeG/NeLx6QfuNl81z/pHksJZewlfFk6w27Rrqe+5Krs3nYsG0QbQEIUJ5lTzqtJyZAbXnNbqxV/UGrHQOb49ZvHYCJ50yG6wV9QyU7PSSxFG/SQNShD+iUyPYGWXvyrHzdyEiyd+4tjMpCXjbvDESFUcGw3YSZXPNsmr5TIKoWnEuau3o17Ro1Ktk4Ujxt3mTflAsbhD53zZMonnRcyEYQRw82cQBkWXnfrLoxq7AYRprpE750gl5nk05ZuL7525uFkeV4MXVPtC3Xx2m5KVy4oKbzsbQ5CnSgKMVuAplLWpYui+2DI7CpD++SVyZaLmmdKTyaQaJ0bfQvoSJOg6J4fChoOZgjBobECg8fMHW/UyEZ7jw6rAuPaFowvdTgLb9+SPjuc399Ei68TR7omQvHg5K7BLGyOfM4dUuasVWViA91HBssdNwZQ5rjCAAsXFe38L1m6hJuGpuxwHNzFfXtkA7i0fNnQTy7VBg1b0lzIaRqHszy+Qmn3X0iKowCgLliX6+Tpq791MrZ3hAuxphb0nSVdnrJkUQxLmlqcINeG/pVyYJeZynigl4bsaH8bt439ysEfqyFi63rVc63WpG+eUuaQN/FU7plH33wj1OF71zDtE1NrM1cxFyQuaSVZmHkoVjRZ5q6pOHzUHjTrx6CE8+/Sz+zCLbBNSXfkWzWsv2iQ2RHI8jqxnQTkHajTeKNcJSeiHZhm9JUYdU/pB4nRfQR2zlJlp1ds2Xzoo6yOAHPvTfBmt5+4TseWhZn/iv82zc9y+fBY5mqoNdJH8je+GmLqs1xLtjF0KgfIIdROdw5UJFDBllPw82trMLNDm6DXpvlsTHeqCqiwigA6PQ1dtAVHSOlXSGa4LFBr8uGPOhkHRjLNp6Ayd649a5LHuXS5kFmEZStb4xg6+pmrCx4wq5K4MeenFqfVmv2reYGllPwlv4h2DY4bMeQI2RjlejCtC9k69OlshcbL8A1XBXB8sobj5QCDBu6pOnUW3JSXAW0Yhiln4ewJlQRlNncAuD7dlLfonrHWruxPOggm2VguGALI8FzW/lQ6pLGWBhJYxg5Hgu6FvpNBaLyQE3XDVL1ntkcOzh5EZFQrYUmCtAqw4e1XXM+Kqn+TBVQtZqmMUKF+ofLvW/uYBZtmdX6vX1oxPhwvUqICqOCYX2doMUCYJO3nSE2qVaj7teML0t+Yo2nwwKjcMEsOrxvSWhTAJi+eCOaJ+ktaZm/MUGvfV1Ny6s7lcDvyiVNN7+KXuuWtHzC48+7M3VdOBbTF29ECyyXP7gAlc526rG5Mc8XilESMK4NIj4M2WCziYbjkGHUyixPATafEUQ3csW1VQxZ1SSKbv0YRrhnGOjK/DxFg8qlGUA9X7joQ9ZWjzT1TwrpGEZm5P8+DR+LSARV0b42+zrzvc8YRira7CbWqYVRAEpxvTY15zep4hueXAZzVvXKS/FYLS7XTd5esPwW1UCyLylNiZevr1/c83wpvBSJqDAqGDwBQ0eDTFO/9UaLTd52Bq8mKAWUxohC+XWJUVphhDqRZYEJWKF/xtJNcMn984VpMQojGyWBLCevaKWFkaug16pTysa/iZCiDHrd4MvVlc5DIxTedcmj8O+nVyjTPr+mF35w62wU3eS7TU9eecrIHCnOJt5WcSGbp3m6FPfzAm98eph7nFsYiRUqqd9G1P0C04YxhhEesu6azFsyxTcPvFg73DUd1BdU6MtUeZoql2bXEFWTI30RF4PMXIANrusC2ItIsunZNvIQ9iT/nvnt67ALQO2ezbaNy7WiakpxF/z+AxVsXR0eQhem5Pj7Gs7a7mDFwlBwWS+0+a8D3g3X7+y89+gL6sDpVUdP2QxEaEIgbKOyVm2WLwhClzRkDCMtCyMP2wmpYqLxDnPayAue3bQw0jzFZX3r3/HbRzIZ03+iLIwKdElTWRhhzddln3XjU8thoyK4b7Z+l23cLk3fuiUNxR4ai9f3KdNklQkYFkzlaJ8CuCkoUOMgr0blOZdK1SfROkGv07TNslUF2dBOcZ0VQ1Y3yRyiq0jm0jRsA6NsmTyYGEZqkvZ9yD6GkXjtx1oYlT0SvFkYadDr6sLFUtpvl7HafKjWwqQ01ytT2e2ahWrKsOHX922xWBDQ/w7MPNK0MFL7bQYD2b5En5Z+HupBMVgFRIVRweDNPaYKB+HJEo5QhAK4yVZPtHv5hfcK35luOOes6oVN2+XKB5zCKJ/G1FpF7pKWpunytu6tA+k4PUSxyvL8jgcaAv/SDX0wa/lmeONx++ZpIiBbgL/8txk4IgxkVloALeHRdQBm1KmuBj3bzVC3B7tYjFAo45o3TNwLFBzrVEeUVbEuKOgFvZaBin4HuCZJdfEGeSLESBSSXc3NtT5a8YwE71WWIZqF8tbsfkQMI7en7XxituuAbOln5wJpDKPSB0MIu9zyLIxcWRtnUX67toCKNepaJhKUyXNVclcm0Zo4sN9MM/8Ky0eXLC7HVTv4dKND11smWTgjwh+iS1rBsB10KcE+00WVWvZO6NEG4G+Q8JOtr8XzN/fifWK/+a+Z3OcJZ5jwI5Tmtebo04cMZBZBJtWFLf8Hk5/Tosu9Ja0h8L/hFw/CZ/76ZO79kEsNlxR65XRrKowenLcWNm8f0uaKBy232kZS46DXgZz4sShLgC5SaBkyVBjJeApp48GD3HgzUU60Ev39iaXw+Wvyc0ZEHbLWTja3uqO7tUbln9Xp4QIfA5gpWbI5XHTpsk7OWciUDaxLmihdSNO061lGh57fGEYKC6OUS5o/PkKBUFFcKBdugW03AsTIGkpmSYjBLc+sKHwdbyq5VEZRyLAi2uVTjuzVAQMsKowCgM6Ju6sFoP27Nh68+p+3eivcMWuVOq+mhZEM2cntp3fOQ+ft7ZffgIV1ScvC2MJIZ91C8IblQlUPWfBuFEsUQtsG+SfFP7p9Doq2bb/QDsCa3NqE3Nf/4NbZ8Jm/TEfTdQ5Dwhj3xKLnN5FVjrfynNNj15U89W0Dw7B+q9yKUUibjSlCSNsIVs3PYD7na9c/A08v21wKP1WArOmHGxNXsgnGdhMt+cnyPTePyQGIQz7EMYzsxhlPIZqAVR6LSpmzqhdumqGOf6fDiy5aLmlu5xwlPeY19oDDhEMVZdkBsw3Cm8JVijNflDPlmBejhIqPuptUmgOxF4o7Ti++C7dPcdlnWi5p9kRdxTDqBESFUcGwd0kzRwf2bxRE9fLtm55F5a1CvWKDXmeTSQNaSnqj7KTDyCoCe8qSKZdSPV54MHXFKXpBSb6SpwQTYREiPhEGWhscy7J4AdCVwhT3REieJ+tuIktfnvDAL5dqClQp6wzO++/++1noHdBTxsr4AuCthe7r0IUZvQjsDZIROMjWjKaFkaYiuRn0GlhXheJapexLL0SwtjCSzB3pGEbidH96dJEdEw00rVJzlxvg8qmgfQGCRloXt6qK3qnGSjroNY9umH0XA5eKYhl4VSx1SXNdp4K+z91LCn43n0kOtlR8i/qayedaH0LS1D/icjCkDPg/9rt3BDrr+0VUGFUMIrNrVF5E/KNOhI1gFXo16riU8SxTasiJOV+uOMd3/51WxMlYm7uqF15x4T2wfhvOukF3HcJYUB32rds0qdZhK7DrCh7YhZ9Fj097eQGsXdJK4FkFfgwjf7OD2KrAH21jep7p+4RcYR7hEknQ61YMI6yys57uzmdXMc9a71ObE0XnS1lwl9nCGoPkp3fMFZCw41+2frHveHEAXcM+gHfrt2jje8XDC+HKRxYhCapes4px4u1CBNXGO2ka14GbTZpj+abtsKa33ykfWFRBMdY/NAITz5ksfI85wJJ9prALGMr4CWqcUBa+gbUwwsWmzFgYIb5lpEY70sIoBr0uGLwObNrvQj3Zqhps6pFScLZz8LkNNg16bXpLmqy05ZvSt33J6v/SB+fDis39cO+c1RKKLfBOYWR8+goKCeDAJcAwn843YRRGqEVXSyuQWBIoyXLBszBSwc1cWa7yQMc6Vf+mKQOGDFA1lzQZr63r3KvzPaVDUlVJ0GtVIF8RyX9MXwbvPnl/VTHOYeSS5rDP/OHhhdznrg4seKyyLVSAvqil+DCUkjAsnn8LPv6haj0RKiyRNAeHcVbNqqHCKvOwFicYmKynr7yofuHLoovebFYoAj6mYp0+ZzOu1/YO8Gk2TYwEz0XPaLrNFfoi40kTa9HOi5FqipYlqXugDyqyt6N64CU0RAujgsEbtOaaXb30abeDTujeONhMYrTxPxfwcX1nwhumr/DMaTc0LHt0A95quVlK0o7qqk9RgxaBpmW1yhWGHTWD7eKobUHYSK8zL3RrBZuSlG0wBkyFf1MDoyyPjy1YD5/9az2Gk22bU0pzNIqYYUVl2ASydM132ipWfJoXot5F7ibSqOOCeGkHyOpqpGHi2hxH2IpFHmY4PNtpghBfmxYHNDQG1NBILWfdIDt4YOe6sE/acZYI2lQ1yJlc0vCXxxej0qnWUJVLWqfA6ts1ms9mjlFZTmff6t7MSgjhK5ks1zFszEyXSHhVhxVA0IoGG2h4tzAihCwCgF4AGAGAYUrpJELI7gDwNwCYCACLAOC/KKUbffPSbjB1WanndctLp4IXGyVEmFoYJRjgnHipbUhwkLGWKDSwcYR0g2zqxPvRhe2CYirk6gjwPV3FnxkI41GUgFtnqgPbY1D0HCDqG6Z9Lr02uP0YUX9cubkfdh47ymlZroFVtEfYI7Ew0lUk8+QaF+PABMs2blcnwvDhoE/pHBzwLouQ5U95+eGL0QLPPdD01iPnSnDJuyseXpiyVsJ6RLLvePIWD6r6mLJwQ4u+w1qo2pwnk4lmLQ/jkgJtcUjlXou1lEEXx0+JlTdddhmv8QORRLPzY9XGhAmK2i2cQSk9kVI6qfH3OQBwD6X0cAC4p/F3Z4DrVmAv3DyxaANc98RSefpO6NEGKMt1yCUwQX9V4AW9ToA1kW6V56ZWEpepYU9X2ft0SbM9edHlrGVNpqMwcmRhpMFswp9LfZHKOs+FYleWn1fnRUy37lzSypnF5q7ubfFQCgdyyITuuJzqA7NhTuocW73s2EuslIrsTKHKVTrrAM+CWJafnV98xTByUa3NPsXQWrRumz1hCbK3qPqMuaeyXpq+uH4OT0BsdWcCTL6ixgUBseIMswy+5dcPK+ljYfPJorYUHbBxLYxyeVtPRIrL1hhRKaD48G1heOvMlbB+a9pdD8vzsE/5Pmst7a2kcFCWS9rbAeCqxu+rAOAdJfFROHinZ8aTNpMRa8JqW2Y7wsoljeavsgwJLTcljIWR+J2uJY6WhZHkXRLPQtcljoVMaPDZdtYLqWF2narSjRfiEiFYGCWwbaoi3TI29Q0q+Q3JXSprAVLkdGnr5isP/BtOHVcFmFPvROfzz+nLUDS3bB9q/uZtEJoebpgYGgaN6aP9XViD6MxJvAMhmSIoHcPIk8KI/S0ogldPsrAPTy7ZCD+4dbY2L7++5/mUJYqQH0pzhzD4GEYGKGkNxchNZYjFoiJd8yKygqxfbW9GUyWKZctUjbvsa1U8TyXbggQ1z2v6Z//6JHziz9N0WNJCTsmGzPf+y6c4KL1aKEJhRAHgTkLIdELIJxvP9qaUrgQAaPy7VwF8hAvjXq/WHjspps1hUy816q5eyw56LROotRcEjfQy4SMRvoYMzXVU7g1PL9ssvZnCBrLTHi/lIU9dWGAURiZuADIOQhIkXdHgf5P7D121uR9OPP+u5hX3sphAOgg9llBpkFSGyXjrdGA2LBQobNw2CD8R3P6VxcY+RmE04k6JJ7be80fbJXTK4CnaRpD92+IsRwqX4yqhZWpd9LO75qUsUWQKvZ7u9LaKAPF2OGJ9O7lXl/wWfnvfC97KwSDsOFt1CK+tF6TXNZ4R02/MmcayAy4jZfZKum7H2Ytymu1ZYrOy1tEA0BGCUxG3pL2SUrqCELIXANxFCJmjzNFAQ8H0SQCAAw880Bd/hcLlwqHbP9Obgvbv3FjYLCY2JwouoVpscC5pAKIYyPxgeWJarvzlE+HLl0vatVOX5J5RCjkTWBPwNvM649/0i13fkuYapkKDDFlKLs3vMShiDiAAuWuJRcUm8wFamPNZOzT7J7+sEObRLKKFUfGoUfMDguFGPtcxvqTwQdIBTZ8uaeyE60uW9KHk932hBaX5QxjsEmtSjToWlE4VcJrl/c6Dwqio9UKrz1jwpCond6kGwoWMTbHTmJ7UuxYdFHvCT/MZ1kEEHc8JLC3R3xEteFcYUUpXNP5dQwj5FwCcAgCrCSH7UkpXEkL2BYA1gryXAcBlAACTJk1qi2bkm8uafRqbi104xPTaogqdw84lzaEQaiHMmPofs6hRCt3mLKTL07IwEr+75P75AGDpkiapWFG9vfZnDxiX16Kd+Vs7v16OJLVWDKNutZEpSrFjMgSCcknLf4COoDh75RZYtrEvQ9OWqzywLoS6fWfe6q0wUqPQ3cW/ScUGVb5NRDaWqvtV5UFupUdT/5pgKLEwYkgk43j+2m3KWHwmfdVHHhd9S2cfx1tfZe3Argm+xoGxxYPknatDClkZ2TmapJRrOKrYPqVz3uPqEOWKhxfCPXNWa+XxPVcqY3ha0c5Tl4Y5MCxNt2fqKktG93RxOWsZ6yjmJEF5NeQeyGnQdUurKBFumrEc9t1lnFuibQSvCiNCyI4A0EUp7W38PhsAzgeAfwPAhwHgosa/N/nkI3S4cCPQTR+1qC3YVEVVqhEjhNcXIKGJkWZ5GmkRxIc8WRiJsJmJi6FCrUa5gS1zQfFk9cuB6Rfr1H23oyNXHWGgFJc0qh9rTOfkqXdgGL5+/UwDzvSQvdXOVinJom9wGHYaO8p7+8jif4QGKUs082+EEr5jnzQtjATvL39ooTnxikHPwiifNrEc4FFhlztfFgbsmpJ8StaiRvWJLbdRgJWbt7uz8BdasPmx2hWtr6qg1wlWbu6HEw7IP0+CYuuAvQFOhhCmRQINSxuLSaUIq/B6OaKg13Wq2be6ww47VoTvBc9NrHzq8ZTMayv5dteHUV+6boZx3hD6u2/4tjDaGwD+1RgIPQBwDaX0dkLIEwDwd0LIxwBgCQD8p2c+goFbl7RWF8Ve3RnBgY1LGoUgZgrxYpP+VwZKJZs5jaf1N24VCMOmFkaJxCAq24xqCiOUQhcimL2+hZFuev2v6RH5IDJwHX+heUWyW7LBwce0oBukXIcH7OYDV25+s5f9XQXILYwq9jEBAFNjNrXKszDyDR9luaCpsx7wXdLE6dmpwlvQa4dkpy7cAC+/8F547VFuwqWKWKOUStc16Xxi8L3YGfu5lVtg1x1G5Z6/97LH9QtFojiXMQKfv+apIHiRydDqvPKMWRkfE/QaJ/eLFcMYoL/Xog1Eh3cudNVxHcfDq8KIUroAAE7gPF8PAGf6LDtUuLwlTVvDbFhOu8OuXtxNNzbbNVcuaab08+k10iLSDJXgJ43FSI3CKI4vny3LLlxVVSj3ljSzsnnfl/Pvz6RS6XVRNAPQdmRPr10KO4nCyPVXYq+fxd6KFQqyp5xre+3jnnUy2LgUs1f2yhMLwD9Y0Inzol9mUXl04colzdYywRQpRbPlIcNg4/umLdrAfa+7Fsm+WXaVt2vl2p47jUGnnb1yi9OyVWDXpr7BEae0n12xGZZvbAVCbgZFllh+maLs21wT3lVxGgkQxeEoP94qWt8jSFijuDiu/cMj8PO75inp4Xgp/mBAhZB48YUigl5HKGDuq81kZP2kHZfT7rCOYRRwvSZ9BCOoyG5842Vft3VQUi4emI24sYURgHdTFmHd5lzSGumRkry2hZFecgBwZz6v475lq5EIebyxcM0nIRwFn8Mytg+NwJxVW0qr338EqDCSzZu1jND62p/eXwBHFQeib23YNggfvmKqEfnhphsVW1BFJgwGLhTBrlzSeEjHMPJkYeSALpaGq8MACvl6w1pYmnCw2w6j0WmLHgU+15E3/+phdSIGRR322PRZZU6FqJY/JHMrQIroYV1Sr3p0sU5xcl6SwxoH7VoVeTIEqCOeRjiFU221pmZI5CbQ6bCa5GkYJo3s1cI8YNrbZYBXnf4lO5FL4MvAyMU4EC2Y2cc6yrt6ev/o7lIvAY/OX++0TNGJGT5/OeOt7FFOKWL9ECgpMfjy32bAO3/3KGzsEyuCTZC1FCjSUst2vZXNO9nP6B0YtiusAyAbu8m7rf3m9WjrkqYbK48QYjQvKPlzMES01mDOgcz2IbFVCDuuvMUw4ihayrb2SGA6h5nWlItg3Z0o8xNPVrMiFOmeipEjn166CQAAxo/pESoum8oXRS3Z8AHQii/nAs2g184o2iOEfaBvRIVRAJi60GxDJtQXofK2f+fGwkbeEZl5msDURQcDzKROJaal+t+Iz7B4fZ86kSe4aDrROpit80fnrwdKqTflV/Zjnlm2SZkFY2H04Ly1yjQ6p9nNII6G3d3UBUR6uutD0PMwx+YsuQDg9lmrnNBOhMt+yUYxwZb+IVi5ebsyXdUh7zN2yomINFiXNFPwFB865D79l+la5ZkE0y8KehZG+Xp7fEHdfYs3j6ViGLnbB6ZQZK1qu6SJnlO5m7esr8jebenHX8Ihgsm4sunbIQ0LG164t6RZ8CKCisd80GuaeZ8PCP/Vfzydyssby7Y3jsk8E1hkYyS6CHrtK35aBB9RYVQweBPNjTNWGNFixwo7WYhcXuLY4sPaJc0dK+6hwZxLwS+UvkZAsbg7YHSEUtg+OAL/+ftHpaQ/euUTcMOTy/GLnLZFcTrDO377iDKPKx1lkc0dSNdSwodLWhYb+wa1N7kqYPh+w8UPwssvvBcAAE49ZHcAAHjoa2ek0sxYugleWLO1Mu3Fg9wiRp0mIg2cpas5/aZLGqWwbWAY3vCLB+GZZZvNCXLgOh4LDy56lM78M6h9Cykjb3pa7NkNpenhqAvWeBtbGV3eIUzLhUZSjoSH2wSHAr5vJw1FjrOFzWcUdUuaCvmg19myFRZCoueWTGPHP8u/4i4aJVqHCxZEHKNdxooMMYZR0fB0E0361gpBeoFJYqfD1u841BNGFliXNNG36NZR+DVSh4sFp0YpfPlvT8ETizamnvNIL9u4HT32jINea1n7GBVhBesiOUzzTtfyhdqVrB1TqoC6HRxOa3nzn21wqozIs2Jzf/P3XjuNhYP33BEO2H2HVJpEYXnW0Xu3aIeuYM8AY5VWgek/GGA2zDYKiMRShkJdYTlnVS9ceNscI1oYNoxd0gzy6EKnHnVjBLLypq9v8UHXlRW3WIFFoVty82iZU4WJnFqj/BtgUeUV9LUy7prvHE/SA8P88SKz0jeFqB65ikw27Aj7QnIpCM38K+ZD8Bz5vS7vV2lZRbmp7KeXboKP/3maFY1OkAOihVGFoetTGk9CBbCoFuwNARh4MXNt/IsNei2ko71ZrkZfm7nc/vSZUoAt2/NxN3h1QIhGDCNLBUWoLdC8XcqQQUw27brjPLMdj8J52KGZv8thVnRcDhle85P74Lf3veCBsh5kAerjeqoPWY25UMANM5YybFhmn/ATt8SeqM5hiCwOkYoVfxZG7O/6Hxh9TyqfY56y/PDK7pHEBZTfRGvCh0ZaffJ24RoCOoxyzcr5Nz/nmKJ6Pcn2/axHgCzOFQEQuuW35l1FLUn3B+oazrukKbNIyrOn0aJF4ed3zYu3nCIQFUYFo4iY18L0BSykVYRVXVSkIjETK6XutkAVqRYnEJ8A5Z916SiMNHgwjgfkqKV0Fu61vf2Nsv2XZQNbax0Rnz75zwbtNdlQmPAn7376PC1a3wc/uWOuPiOOIdswJQJ7J811RcAmiHISWJVSaHbKkNwWEqg2WC7mCJ/xPdjxjr31UxuBtJtuNfIsKUJQLpv0B5s+VP4Xt2AVw4gjXC1Yt5VfjnkxYjSIqmIYyfqY3LKOssV4g1MLI5rw7IZrWYB/LELq774QFUYFw2VcY1boIKnn7sroBFid+DvkwycwE6vcwsjNZrktofGthBB0rCidOk9OkNL5MWWgi3CGZjBVY4sWdT6eskfuXuS+IkY80MxfnZvG929xf/Kpgs7mt+juZrvcomIYddJcZwlp0N9GjVoFvU5iGAFtnmj7t3YNswO4vCo+C0wIBPtyKfPbL3TnCWPr2ILXIGzZLvO08oYzLtwr7GRuh6adQ1GiIoZRnh6zPyTqAnw3V87CyKJNmkGvNTxpZWN8ewFx6doBUWFUYbDDLb2AIzZUAU3mZcN2UXTmkubBJy1pZ4xQJ3Ov07Zm00zvC4SUdxWvaEH0Y2FUlAMGDiZKHTRtpLWcLWy7jchSwpQzF1crS2FTZRLW8mRD6KE44DZ41fmesoGpKRsFxNBwy8Io6ZK+LYyMNuKW7zHQ+W7d8ojnoNfrtw5w+dedA7PrgMm64EL2Qbv9ZNK7hAnNKlgYsTxm2U3EIisLI53EBS4F2b6kckkT00GWhzg8kSF7e6BNmyRtrhX0XfD8p3fOc3ILYScgKowKhkuhX7T4LN7Av6Y86oj4sPLThjDMjZVAKoyE2TU/sZMUkqIv5bukES8Ctu2tE6XA5UEcAfj4VU+I81Bxcc8s22RRsBjFxDByq5Qyyas+6KTc3yjaJc8j8muwC2SkA5DUp838OMgEvW7RNaNX9eb15ioG/i2MXn7RvZl5g59Ot23dBb0Wze28tPzfsnQ+YHYBgkV5BQ2gYUQHdM2LqBvZXqAje54tMpteZX1MBR0Ry7FtHWYtjET499PqW8Nba4UNRy0sXs/fM0ekERVGBcOtSxr/+TVTlvDTF2jiWyVYTfLU3WLkw4JARwivb6pFG9Bq9pgihBYdq6x60Gs7ujywi/H2wRFYKlAa58rAF+EE6auSDTdygmx3z15jRO9tv3kEVm/pVyfUhM8NWwKXJTTtZQyI6sxcVVK0SN10k9gPFfqesuGirlZu3i58l8TwohSgq3Gi7bN5fCnq3cQw0ilQ8opr6cO+d18Dg8M1pSucCVzJ3+I1n38ygaohg2r0fSOq1eFWQfPiEOKGP9esuLDY0S4zG/Rao6Cuxm2O3JvVLA50tMDyLxmI10xZrCTV/HYNdn07GpR9uFUEosKowmD7J0bZkIol0f59uxBQqIbyDcOjWwsjvfRVhs61pwNDNTjv38+6Z4K0ylvTOwCn/fg+92U4AHsaaBwHAuPupkl760D+lrt8uXoQxTAqwvrHRDjSuYkondHqtTxvyfOI61uNIuwr7eUX3qtMM2Xhepizqrdeoud2MqKvHDP2TBe1gbEJUi6DyCKiaPCvLzclZsWKFUyUPyMj+nmK3jgPI3i04Ym3HgotjDx8eoum3KWLABHu8WRremqYSQ9IMDyK4fKWtKQv6/TpuFzbIyqMCoavW9LKitPSDrCduKqgWcbwWHOo/aqqRZIJdCyM/j5tKUyeudI5D1UZ/qxw51Lozptr08zfxW/wdQIyGkPR93S+2crCCLkAVUXBnkDGayuOQgQWmJhQLtbTBWu3wbdvnOWMngyhrnX//YcpaHdbuwC0nhRGgdYrgLgff+TKJ2DBum2c9Oq5wvfXmuj1Nm83j+1SVPsNST7MhdU+j4KIrpVBliKvjYURABG7ryPJyObRh55fq8zf7VBITZo83BmiPREVRgXD1y1pGKQHdRxqTsC3QA4GCW/YoNcqOuhyA6kUQgoIFqwBX6exhJj1w6LbaZjRophbGFUDQgsjww8gJD/nSwNRUgrTFm8wKMltDdv0sWeWb3bHiAEwc2IVDgyqAF/V6Lt1TPhWbaZd1cW1U5c6oFJnZqRG4ZopS3IuQN7ql7WWELrKi7Fw3TbYYqHwkJUh4mfqQvl863KuWL5pu/f1e03vgHaeprdQQdPi4LD6hisdXmwDIGOLwpajEy8r/b6VQBb8Ox0mQMaHGN+7WX07q8tb0lqX+eBonHTgrsZlYdEJYkBUGFUYuv3zp3fO88JHJ0N1XbcOfFqJYVikVDyFR5c0MepWE7yVOP/IVxuHpBQDELd/2sLIrJOs3Kwfb4gqLAEx/VW3TwuDXjuO3cQDAYC/TFkCH/zjVC/0U/lUm18zsgAA8I7fPmKR2wGkFjHKJBEZlFFXvixgEoTc/pj4LgC4sX/dE0vgm/+aCVc8vBDtxmIDHlmdVe6Mn94P374J5/6tuy5ry0MomnpEX3mR2jXTFmsNFEYJihoX7CGcixicp/3ovtTfOoHSdb75u5m+qeIxy4XuvOajD+qgqwtphYw63E7/q8Ko7q54sOMAUWFUMFzd0gCQHli+F7wIPkKvxyZ/WJc0MSW9coMWo91C56YqX2qdLmLaF4ttpyEHFkY3c27RyM5/IYxLH0GvsxRl7pDz12w1K8OAbXkQUEagp37bJrtBtl1v5TGMAuhkFQMmRobrWjVtpnmre5H0w+0HWIWRDMnnrd86CAAAvf3peG9FxDD68BV4xXfIcN63HdPLYmPfoHaeQ755KzyxaEMY46Ix/et00awbHtclTRjDCB+iQtf6DeOSRgW/ZTesiX7naFs2Z1Zf5CKGURB9rIFO2PNEhVGlIZsSIopAfb4Kf6LAuqQJN6AVtjDyHd9LXGf5Fy4Vxi7oFt1O6dNAf9CljbIw0qQqGnM2Lmk+YXrrV0hj/YJb1KbxOkApOAL6/tDhI2C9L3q+FCEAeu4kNsAEBAbAzZfJhQXdXengukXEMHp6WcM11XISNLsMwKpINC2XtXjMvjs7oWPK0+2zVhUmFZcx/7pYirPjRlf21pmeSONAkZuloPrLu6SZoxnDCEskrtFOEBVGFYZVgDV3bHQ0XLqk+QRGUJdeIe3BBLvdUWQd+L9A2g1SG5gCBw4FxemZh7rzseHMVpmshCKtTnXK8nkS9/AL65zSw8yJ4Y+6asDXdODdJS3gDuDCwijBSMM6dFQmeq03l7QC63XlJj03Z93r7FtzRTEf1eVqZ2fRCEW1H6aYoixRdErR5SgbdoAXz1C0DMtCFqQsjDxWEysj2F7E2goirzEONcuMyKOnbAY6DS5PiT0egEUgIdTaF4SdxvRAr+RK8GRCxdzYVI9hxP8abUEnkL4ZWmwfbzB2SSsW7AbGq4VRAJXhe6MaCtTWEqm/fLLi3IJP1oad0r4uIbew8GWp4hcmfKtyuOLZRQyj5F2i7O/u6kp9s69xwKPrazWfK3E//MHkvNWiziezdYWpZx2I8mStOUzRLjOcSd1OXbgB/jplMfedaJ3R2Q9g929JMozbvUj5k70wQ/jbY4tn68xGRkvmhkJuokWiE8SBaGFUYdwze3Xzd4xhVA5q1F1dGm12kFkwLLqMuRKSP295LmnF86KLoltpuIYTnnWRO33LvFfFzuG3ld1JusjCyO67cWbsAPrKUtr8V5/BXFmsIZkGz1VC02qgXT6oAJRhDeDTteyBeWuD7s9DSJc0DJK5O2th5M0lzZCsa26ueiyvNHCvIjSbdy++m3+RjTOFkWkb0HJlwOWbtsPSDX0tfgxofPiKqXDTjBWwfUh9C5sJ8hZCcmRbdDAbr0+y3idvdJRMrtHt0iWtpkcjpP1IlREtjAqGS4uHG55aDj9/z4kNuhHlQGyVowu2DV0JzTqbGplc/fdpy4zK7QTotL8vhdHwiFkvLHqzy7qkne843kwKDj7Ltm58bKTyLmniMopSTrazMCa/Wa99v7sMVLU6Ta4eV8FVXaAtjBBjeLhBKx/DyIi1SkOrfSj3p1cgL6RSwmqOK+hjs5cqAORvkDP5jmRM6Cnf8OXYjvGBofTYzh3MZMvzxEcRYG/rm7uq1yjote/vrEA1WiMqjApGKBYG7SzkFwmV5YIWLTdk+LQRxGVBr7XLc0OmEhBaGHFqwZeLnMtYFT4xzNgQ+zz550E256EsHzTLEymMTOde72uHRXPkeGP+ZqvB5XyJgW2VybpoNvBmF+nMzbMOpAq4zL/tDKUbp6NacHJLWoOXxMKopzvtmOBLcRryRlY3dgpFdG6X31u2S5q7Y1Q3sOGFV5WyG86w7Zi3vBVZJNMGH2lGdCyffF22ogNXlsav/8WDTSvHkOeIdkR0SetQxIHmBilhwCVdJE3sMlD07TQhnb6XFceoSJe04ZqZss9XK4l4cekiIS0/97d+ubY+96K9mstDW6djFpJTO3yeD/5xCtzx7Or8i5KGv+vhJbMSy/apblfH+p2OcJYOFAJa6nLAzreYb0isQ3u6SKqJfClJuQcuDq/mtoG5u1wxDJftkmabV6scTBrHvIjihmrFtsIqlgTp+jMKIwJEGJuo/oDf/7AxtmyRjalkg2Rew1pxF9EXQ9rz+EJUGBUMXyJlAArkjoQsUHRIQFsYuSrPER1bFDEudEx9O32YFm1V5BK6LmYuY4IVCR2uH3pefSvZ4LDcdD5k4G5J458AR+QhHUKJm0ExrJQK1RhwtfeYuXyzNY1m0OvEwiijGPU1p/vYf5UxRilSrnL5ua4+09jCSKCcKAu6vMxjgqDrHATolGLrst4/nFYYPbdyi3C9kvWHlAWwxzbLUXZQlF4d+u2P4fR2f4gKo4IhGri2E7x2gNNO6N0FwJuFhmN6mInVpdzXSf2Larjy+RRYjW7rKbidhh27zolkOd7pmq07gC7rYpc0c/A+SwTtq2tp+l8rMIVPW7yxVYYD0sVCZmGURjaoZ9QfpTFz2Wa48pGFynSdcFIbGjA1PlITxTDypDDK/D08UgvmwEVrm8okLsrC1pnCyKJtC7MwQpSjy8vZFz/YzJOd19WF4ZJl5W1haIPG8ywb/ZkYRjLlMCFptrK/y1irxDcy4/tdXCqKRYxhFBFhAacxjAwIqRQQCU0M5XoMIzcf00nzuOhbl2/annsWisDrG6I6GXJ8Gt1FCHfDolsKRtmmuzEaKcYO2gNJBzRLnAAenLfWGS1ZVTTn1mRjEV3SpHjrbx6WvqeZfzsZIdZBYmGU7ee+prnsPORC2eJMGalJB5XcYT26cklrF9g0e5eOhZEHg5eWBWv6ef+gRgwjyMf8+fHtc+qWVLQul1LwN5azZTuj6TidFUKctB0jKowKhsgSKBmwRSEkc9GyYXWK4pCPFF20ht2dJt7pyW5Aqn/fslPd/Lp8hBTDSATXp9F1wZii2ti2ZF0XM1Fyu/nGv8m4SQlYyznfQa8JAfjQFVOd0ZPGMMpYZGWrIG7Z9ODUwq1A+LDsLDyeICIYeeJ6Nqq7C9hZoigLIwB7C11X5xUe9AJO53ZXymuX8faKgI+uqFOVesHQ9WT37N5RFEdJTCdd3u/unw8AAKO6CXR3EagZ3rRrWr78MMaMpjwtOmmEANElrWD42rzGA4VyoOOO5ANb+nGLBmZirTlUfIQyN4c2Lnzxs+f4MX4Iu4bjjiGqTx3XLVwCfYshkYLJtAp4hw0yWrp9LdkQOlEcBzbuTCG/JS2x3uRbXkSYIR5muYUrJUli4ZPt574URlc/tjj1t4t+4cyCWoNMGfKhK9d30zqnDq3VVZixdJMyjQkvA43Ye7rWWtg68x3iUBZkOu1S2vpGn22W4geItJawXFQ0TGRl4VVhRAg5gBByHyFkNiHkWULIlxrPzyOELCeEzGj89yaffFQBthO8abyKCDv4Cu7nWnGDoedS8Ous/oXXtPmKYXTqIbsb9RlfAsLAMN5c2gaiTbrumOSeZmf+1g3uahMM9m0n7Jd7RqEY5bSRhZELIg7g+kZE+S1paWQ3FjEIth5MbumrKtSf6K4SMPMQprRmDCOSjWFkyJgCf3p0Ue5ZdkTxipatac480rTXF0QbOKxHV7prKwujgMaxDSs6CiM9RSLO4iZ5bLOcNF3OBHw0FUYSGgfuvoM5A+Brn4S10gqoM1YYvi2MhgHgq5TSowHgVAD4HCHkmMa7iymlJzb+u9UzH8EjipbVhK9NnGua6KDXJQlUVYZOW3XKOF+wdhv3uet+kQg6qno1cYXKJte+JU0U9BpB5k3H7YMqQ0bLVGHhNY5BwfOCtc4GYTbfchnIlG1ZdKehWZ/lstF2sD0ISrIPiywmC9qMhRRaTUsxUEKPdhXDqF3GotUY0HJJ03CnwtJsENQ2CmBKyMoCbNl1CyM1vf12HavJQYafrNW3VLGLtNLSuIjEd19ul7Eig9cYRpTSlQCwsvG7lxAyGwBe5LPMiIgi4TJ+zZxVvepEmtCJC+FS8OskhX5dz4b7YF9GB3VBpYMqvQGsS5oK/UNqiygd4QRAIqSieMt/GAGiJXSZwsjCSEeo9thNXY8vqdl85kKBaFDkCBWbxkI/MFJZGFEAWL91UElneKTV31n+bCwpi0YZl3pc+cgiWLYxfwGGjKYtn2VbGOkoTkKHrwDi2GHTWl/M+SDQaA9Bo7Rc0iR8WLZnNrt0bbUrqhR0gvxdWAwjQshEADgJAKY0Hn2eEPIMIeQKQshuRfFRNkSD3nZO0p1MOqBvo2FTFXXLhfJMLdH0EORqlDorN/YvPly7zNiiyHba3DcE377xWac0RcIc77tkffu2Watyz7KUN/apN1UsRjQVTC5BqbmFSycIPlhggl63ulXWJc0LS22LVnV2QP9TjDGnCiMFscXr++CX9zwv5qXRHqIYZ0Xpi3SKEc1hLljtHxrRvgDhrudWo2lv3j5kwlYG5cYwss3rGjbjSSvotVYQ5nRa4TXzAgtWNX3mD5Kmny27eROcTGGkWb4NsNWItRwLpydWG4UojAgh4wHgegD4MqV0CwBcAgCHAsCJULdA+pkg3ycJIdMIIdPWrnV3VW6ZiDJke8GdisUvsEGvnZXnjpS4jEA2tjruTp28ifzJnXNg+Sb1SasOEjlHpTB3MUovmDxbK73QJQ3BC/dzSD6vjxHgc1T5ivnmC7I5Mfsqf0taBw92CwQyraOhqzwoGtb80bqyiJ3PyhjDvPX+aU7AY0LylpgJXMRpPOrbt8OlDy6wppMFpRTed/njcML37rSmVbqFkYZM5BKiIm2GgL4rGDIdmif7ilR9QxILUjqubaeRnHW0HT0A/Hje1DcE//n7x+wLlCDsVcANvCuMCCGjoK4s+iul9AYAAErpakrpCKW0BgCXA8ApvLyU0ssopZMopZMmTJjgm9WOQpWE9pDha1F0HZwRQ65G3cVjCkWZUwSCGEvGpuPF8e7D4ibkm6lsXDW4X1VUUxmU066KUJlAmr0lrU2roDBUNYaRCb+qPC7nZVuXsRueWg6HfrMVZrTM9sHMM5SKay9ksYQCwFNLNjmhFfK66BM+5E5flxfkDn8ErDefa7KRMjBqKFGfW7kl9w4Ap2C0nZO0rK+QZWGntoXr+DE1I/Tg+5Y0AgB/BIDZlNKfM8/3ZZK9EwBm+eQjJIjmnngaWU1QCFsISYDRxFfhOxJs3j4En/jzNFRa37cVuYxjZYMqtZ8riNqWdwNJ0fUj2qhh+BB/lwYtw27v65rsBJXqp7IDV5r+t12VZkWhdUtalTqI//FiC5VLGhYslZCsR7hpPbqkVQHOgl5TCn2Dw/r5wjhGY2DhWqflZoani42JaKgvSoEAwMBwDe6evSZNNHlfSgwjMUF04PCAOllIvPiC16DXAPBKAPggAMwkhMxoPPsmALyPEHIi1PvQIgD4lGc+goFo0NtOr7rrQyd07kJAm/8XJHSCXtdqLi2M3NAR4bqpS1qLX8nQiWPl87QqNBGtCIhOxkKoCZtNC/ezOA99bFZNSGIPPHzPC0OOzdhwFkZ1xEMfNwhh7Oog9KDXusH6VShTdkTPM9ovygdbr7ZehC7FjG/eMNMoX7L+vfqICfDgvHJDitjUp25WrCyYV6CI6GkyYJAPEcLIeuiw9UKIA4KAr+sIN/B9S9rDwJd9b+U862gMjcSOX0W4dOMyBSHqxQHnkuaEnUZ5sT/zENqWsuy+a4vkJBVTr0V/quxk/45n80G2WZRprVLlset6HZWeuKoyhzbYQ4fG4UZIMNm0uFivsXBlYcSijCbSst6wiB8XAgaG1bd2yuDOwghg0fq+5t+bkBc/sFbXVfeO0+l3Ov0Lr1iqp7O6JS2TNctnd9PCSGb1E97YCYmjqswtNijslrSIOkSDfr9dxtrR1ZRO279rFwMKfupSZ25GbZZRQa/dTXmhrC2kgHN/HdueLo8zrqrOuwjAx151sFae0IEVjMv4TJGxC6VUqTASwUfgSFUZGOjIsj7bwrXQJt1sNxUciUCffl3xfVKhkMWdCR2h873S8UUDpX4xclAp48EEju2DdmZhzoJeZ/4+8fy78HkTV103rFjBRtmh5wrpPq2LelRJwRhllLWFkQY9fN2EM6ADYsUbosKoYLAd/JSDd2/+PmD3HcpgJwLsBjr1ZGGkIz7LJvuECoZHl5Ov77kzpHghOtU2a/mW0nh43TF7w+lHtNflAaJ+wKsP3f5t24dl7kxqAc6ycEQZIvi89Mm3WsD1XCy7YSp7oUBAU1LlUGVh+7H567XzqOYil/Xxbg+3A5XSXsgyZy7fDBsFljChx5tK0B+QhZFFbqe82MDKJc2T3MAeRtT3EQKruERhpB30OuMCxqGZIDnIdKHEweaXn8XgCgv8gsq2Q1QYlQh2DNv2e/0YRnGkuQCFatQlRlCqUXff4rtOQqvyEPhR8cBTIFT3XL8O0W0w+RtIiv9OkbKBgnq+Fil7st+1dGMfNx0gyhBDv650ivLZFq5JD0sk0uRVMm+u2Nyfeh/APqkyqMo6ysO0xRvLZqFQhN5Mm/qG4B2/fYT7LnDWm+gfslMYuYqVaCof1MezW15sUNTcYuo22T9Ug9f+7AEPHOHQjQl6bVkGOr+WlVZVRnR7wHfQ64iItgbrq+2aLhay5bgZ9BpBx+XpW0jTuG95pSprVldX+21iQzi9FEHkzjTpgrvVmTmf9cLqrblnf35ssS5bSlSlP+Ng1z8wQa+BUvjbE0utyul0RME/jZAV+RTK4U+nzNVbBvg0wq3WFAaGAnFJc1BfISzRNp+h5ZKmk5ZJvHyT+OCnGcNIN+wIQz+rtMtZGCUKI9kXWHaGVNBrRVm67noRxSBaGBUMYf+27Pi6c3IcZ27AnqSEDAyPNZfKL891EoIQwqLMLtBF/CkuQ0ezHyhMrgH068d2E7t4vVgIVIHXveeu7oV+5Ebi30+vML9dxSwbikbV+umIzCWNUcbPWdWbex9vTcOjbqVVNhfFQfmpAdfFlAXrYdG6baWU3SkjajtjYSSyopXBmUsamHXF4IJeF6UxAvw8ll5bJGElDF3SdIChXZiFkUbakFxMA2LFG6KFUYlwOQHou6S5K7uj4akiXdr6vLBmK2zePqRO2YYWRkUolso+DcaafBOSDwFe9XlAJBhnP4tSgBufWu6fIQb3zlnjnKbOtfGTZ64wKsNoHghEg7ulXz3P6UCmMEpAKV9wDaRKKgGdiwMiysVVHqwaMaj6WqUD1hXWZBpxdrmGTbDoRtYQrIDt9EX43DprJ7tm+K6iLPnsNzXbyJ+BUa5upO5vyMJiDKNiES2MCobw9oYoLlUSZZln6+Bnd85FpRupuQvg3UkuBjQQMzOj65098CGCD6EIS/KBeWvhphl6CpQyW1SkBNRp4u2DZnEwXHw3xk3WB3r7h53SwyiMapQGddJZRXRa9am+t8OqA40AdA+FgFoqE9zFMDLPmcjFRSuMeEHorW5J07UwQtZaymUMkc6mTVVBrxMrNhnnrvc5LqjFdbdYRIVRICheUxoHmgtQU5tdJV08UdU6MqobN8xdfkZIvcu3uFL2t3YR/GKe6ytlM28J7C1pri1PfEPUZ4sQkEzWojbrVk3Igl4nqFsY5Z93yN7WCVweVkS0Jzq1e5i4toYQw6gIVyoe3nf543leCipbp5y0hZHspmMz7nWUjkn5cqsfIzaM8mOThjQndMIheVQYlQh2IbDtbCHcRFBV2GjOs6b0h+013p4hXR4Uk/zoHtwwrznUfnXA3JlCqdYooD4dEiF06zgVxMK0/XeV2YdF0/mHrphaLCNeUJ0+h1HQ1Q0Mq/NNIWKERqc0FiH2pxB46sS4YCaivbsYRqbKCjeWMSbl6jy3ocnDgrXb4GU/vAeVlrVefWLhBmX5NrWYC0WQeZ+cKbsIRI3JT4h8PsGWJbqJNsIPosKoYIi6t0m3n7DTmOZv7aDXcZw5QTZ+xcsO3t0NXSdU6sAqjFwW2knC/22zVpbLgMbgz1mCtEkz+fiuMvuwi42RcdBrg4zZPYFQjVdwla7fxr8tCQtcDCMKNbtLjToetMPqT9Wr2mRadooQFFZloFSFkY2ipemS5oQVK9geCmPx58cW4W/4Yn5/7fpnlOlsmlSVF9NfbEdfth5dDGfRTbRlIBxO/CEqjAKBSb+3GSuX3D/fPHNEE7WMO0IZhl6yMikFGI10SatRlzGM3NARIaSTxksfWFCuNQqYu0ZWfZHDjreQ+kvocKNsCwO232IX9Dr2OSxGHK49EX4Q+3NxSMe30a93V01Fs8wYIIReU5SFkY94TaaKUh33MpxLml0/0MqOVbrFNaNQRIVRiWDnFsMpwbjsezzc4NOJoJmAp642pi4nwlHdOJ5cWnf6nsg7yYJJBS0ZJRf8sNr1KAwOnUvnnxeXKJNfk7Glw26VuhxKYQQ03tZiCUw9txNU826IYyTLc9FzVIBVUggqa2FE3fJig6L6jo9PdWJhpHifbBF81pOevqhTR3vYiAqjgiESFIxuOGKzlD8ndyxsb7TgE3VEB/SCXrfjNF3EyWjZ7kvUkIci92nXTFninGbSstk2dqEIK9tqTIbPvOZQb2X7/O6qCYIYk3ehhZEPhtoUVVdcdyLK6N8B6B4KATtPmnyys6DXFjGMEgRhmWblWoeHHwuj+r+6h9EpvhW3nXQ1LYyKiWEkTQfVtDatIs+6iAqjQGDkksb8ji4X5YBSSMWvcNUKgyNugjpQoJpBr93A9wYgtP5eZgyTRBbAVHlo9WYLrHx20W1z/DLiGorvetGu45QkTEegf+vA6gBnYSSYO9trqHlF3SWtSj3DL6pQE0VbjoTQPYrqo7YKF2dtYxoHj9n0Vz6GkUZWnWpf24uNr0e1aWeRzbpqS3/q72LGsvsYRhHFIiqMSkTaJc3EOiCOOBewDeyHvR5TB2/7zcPotColANrCyKXCyBklOxR1urV1YLiQcnhAfyGnUUJpJ9dw8V1l1o1qTPvs1kYuaSGcInsAOuh1uw6kgtBpLmkqlK08w2zyQ4vXWASKapZ0DCN9uJqPbazOW0GvC7wlTcCtXbvhM4e0CmZvJWMxa/mW1N+YQ0db6+CsElR6I5tVSeWgatbTJogKo0BQdNDriBZsqrHujtD629XauHJzvzpRwoPiKkx00Ouauz4VUt8sYhHvGxwpoBQ+CCH1a2xRadN/l70xsYVIGHXyWQFXDepWEw/BMrH411PLhbSr1OUw1/ZGlzR7YOeviGKAOWQq2lo1hA1ZGRyYxTByU7bNGtK0MApgl1lUu/l1STOHMoZRAWZgWjGMqiQkdBACGMoRAKYKIw+xcyK0QCHTDgFuE7BBr1mB7IfvPM6qzBCEO4AiF54yYxiZo+rrcrvOe6rv8vnZJn2iTZsBF8MI+PNMu1pd+cBIrZpxK0yh+tayqwJllVyGhVHbzjRppGIYleiSZmd9X0cI86CNN4YvlzR0+YbEdfpQojDSuVlNF9k1UkYPs+6GhgqyrI2oMCoR7OJn0tfSMYwiTGEz0GsBuCMoXdLQMYxai4ztwtcJkyeLUr9XK4ZRGqEo9kzRCnqdfl71EyrV8MOMT1tXAl+oUtuIXKVS7uSUlhrDrB1QxQ2CSxyy545ls5AC5pCp8Ng0AXSRMmIYmdSzKM+Bu++gx4d+0c18SV1lWVm5ebsh1XKgUwc+lGOmXe4Xdz/f/K2WJ4q3MJJ9VnRRDhNRYVQwRIPfaCGKY6p8ZNwRQgjwx4ICQDdyMUhbStmX6xMBHFqlUL6+qDz3o1IhcklzQLrUm+8UHdznSbuRhRGSnap1N5Hgmj3Bj/EE7UAprbzy2goE4IwjJ7T+LrkqegJ0SQsB5bik6dezKM9uO47WouNiWsuy8j9/m4HK99FXTrQvvIGipmcf8r9I8aYDVRdK+PYZV0inDYZHqrcWVI9jfUSFUYXRCR20GFiYqwJkgl47YMcxEu5Ufso1xu88dAuj0PZnZW4YE+FQteGiQHOCZNUPcoTd1MF3ldnHlAcIGAsjQ/59f3aVutywyMKI+V1fAwphp23h6FLQyoA3V7Nzc9nKM2zcwyIRwhArLOg189tEFBO5pOnSMr3inI1JluUFaz1ywG561lBJua6hc5jvJYZR41+fe4uEb5/9O2dhJCmsihZGoe1JfCC8VaHNkfYrbT032XDGGEZuYOWnTdMLagj+2izY4IM8zl528O5MWpexmPQqdQzSbc4ERTRJmYuFzfdVyT2Ih8CGmzOoBCa/MYz0+0S7WhuIgl6nXdIEQa/bs0q8oNNiGIWOnhBd0gJA2Yo8LNwFvbbPW+QtaT6gUwU+g17bQLU+NxVGqXKzMYfsGNHJLzqoYVHxblVJRIVRIIgeadVEzsKoPFaEkMUlSist3Z1m6PZn3fJCWyzKVLwQSCsGpWkDqzdbkMy/Cao+N6oEJp+KaZ91VzUFpSi2TtYaJN6SZocarcpW3A2UQa9LrgzULWkFLyaUlr9+VeUOjS6BxqjY+uPLndjDhbLbOkHZY7Epv9sQQbqkFQnbGEbYUBsR7hAVRoHAZE5ihdSyJ7Uqw/YUJTW3BTiHtdzM8syxi3fatc7uQzqtO5Yaw8iirao+b/jctJTpZqgKAuxzmvFtDV6lPicKZp0VsCtoQR8UYgwof2PaJKB2D2cHmW0hl/zuv9s4h9SqD1v1qatl0UbB35EWRj521BL5HQtVzpZLWnExjGRdaxhxi0TV+1UVERVGBcNl0Gs2SxS3ykH2dLkU1wxJkWwoUV4y0e1Stl+xefuQJQWXKMInzX8RInSRevEYFtr1lrR2g8gVKgHqljTjIEYG+do06LVIcGWF1bp1nzwmTYQcbPy8ToDqU13VxfgxPbDzuFHa+UZjXMQL7t5VX6t0YNv+7mIYmdU7K3eaWq+YZPPRQ4KJYWRBQ8VWEt807ZJmUSAHOv0IY2HkRTlnhfafn4Kr8k6FSVfj5dl5bI8tKx0HG0GkVqtALKkGf7zFjH3mMni3btC6qsdAKXep6GQLI/7zqrk+ZaGMYYRRGBmW7bvmqrTxEzVDKui1KIaRH5baEvX+Xp1+4QOpuFiO6qLurqxPC+OS1okn/GUsKyZFipQ0ukps4+9lFMC5ftLG3cbHp7m4iEYlXye0pe1t2ffztMUEMTGMesLTGLU9Yo2HAkON0UiNwsRzJsMl988HAIBbvnCaW74ilGDntuDWQpY3VQwj5jC9CGFwz/Fjmr91BeQbnlzumh0rBOFSgeAh26xl8b2H5vW+IogEIRdfVWaLqtrF5/j0aGDUNshuvKp4q0tICGL+bEcQs3mM55KWI120hREt32qvKGW3bSmu1gcn39tuAQYl8NE/hxqCuc2hKtbCiG2cbDMV5ZJGKdLCKDChoxOWsKgwKhipcDepwJkmtGhqYI3u6YID99C/irLTYXtLmkvLHB/Afl7R3/H4N15rnHfl5u2odEUFyixzsegiuFNkXpKy2D5yn53cEApwvLkA5oRNCVOPNI+9grapIQmvuUJcC0JFrcNuSSsq6HUXIUa0ooURH1XpoyLFhbZLmvEawoY3MOsnJsqXF9ZsNSpLBp068DEkvvbPZ6xpqPgqYizryBXDI+q03YFpjCoyNVgh+i8FApMTtuxmOKzhUx3YDPQazVoYhdcKsuCDWaVlkQKRVRC/wITVMt1sCAG4b+5auG/uWkzq1F9DI+rggj7gqvkSMtkNu4t+XObmQO2SFpiFUVjD0TvSLmm08i6QZUMV5D3CDPX4diYuaQgLIxOGLBBCDymKB3Y+MZlbXO6lbZRGABxeKrZW6IwfH4qXtb0D9R8e643nkpbtd7ZrXM7CSJIWdUtaYAqjTkBpFkaEkDcQQuYSQl4ghJxTFh9lY99dxgKA2aSc3eB3mtAeAmqUpgLUhtYG6ZOePLIbn+bz0D4kg9A2aIGxg8bSDThLLddwpVhNumlW4V6lODk8lOni5LsvV7tlGkjFmxHFOgp7Dg0J9ViAZXNRHFTzk6uqIIQIb/qToQdhYeRSRAhc3KgchEGvNevZOIQRpdKDSgxC6RM685JPHYZV0GtF7uYtaRZlqJD2rpGnxdySFprCKLQ9iQ+UojAihHQDwG8B4I0AcAwAvI8QckwZvBSNlIIHAP7fKw+uPzcYqjVKU/lCtG6pAmzGeS3nkhZeGzS5U8Uwoq1+WMRXZAPHVhllsq8jkIXSPd1ZGCVHY27ohQKVwgjlgmhYtom1K37taY+GQgW9DmSsVQFZWabT4Wo9JGA24kYjFEZFK0QppaVLuNhN4YG724WGoILfWLjaS1uFa2hwHti+3iv6h8qx2FZBGcMoURixFkaZNNZTkoYVOMrCKC6whaMsC6NTAOAFSukCSukgAFwHAG8viZdSgYpOL0D9Ol+3/EToYaRGSw96LStTddLDPgk9FhMLHcVcIZ9S4jgMvKm8ggj0RVWeF0f3dDkJAhzqiVegbGkh7cpLuRZGa3sHoH9opECuqouOd0nz9PmEEKN5oAfhkla0IiCELoJl4cQDdrUrx/JbefLRBe94scGhspXGiMsLloNQ5Bqdtliyoc8bHz5lcvbCsTW9/XD2xQ/AUsffkj0QkB0QYGI4dgWmiQxgevKOsmIYvQgAljJ/LwOAl5XESxBwsRjqTihv+MWD9oW2Aeas6jXOO1xLx68IUdGScMe/JY3Z+DAKyHYJaFnUqXUVbvmhNBwhzJUlntglrZrYcXQ33PPV18AOY7rh69fPFKbz2d0q0JVLR+62QYGAe9S3b4ejXAV4b2PEoNe5FE7KIcRsPPOCXmfpyKbwXXcYBZv6hvQLVqBssaSoPmpbDE9++8CpB8G/Z6zQ48PiULoVwygUqcMMoVg+2t2SJs+bvKdA4eanV8K81Vvhjw8vTKWx7fvp+EjytDGGUZgoS2HEa+lcDyGEfBIAPgkAcOCBB/rmqRCkXMgc9Pesi5sODoo3qkFv/7BV/qw7QohugYlCS2VhlFJ8+WYK7Pq/adafvPt4+M5Nz8J2xyf/ZYoUIbpBFoVkvOUEkDBkPG0ct/8usE8jrt0he+4IC9Zt46bzqaA0EZCxXbBdlAIYlzQAgHGjuuM6C+pDmbo7dAeDM35G93TB4LCdi0vdJU2/ZnFBr8VpTpm4O8xfuxXmr+XPX5UFsipd9mWTOVO4l9aNYWSpLALIrw1ocSUQuaYd1ixVTbIuaTuNqasFtg7Y7Y2y0LECx1gYRZe04lGWwmgZABzA/L0/AORU35TSywDgMgCASZMmtcGwFcPUfSCtgMIPoBMP2BUu/eAkozLbCXNX9cLrLSytsi5poSG1cHPe52IY0fzzqoP9lv+cdAB899/POi+jTPcfnbYKRbnkiguRhVFVgVU4Y+Yc0xrxH/S6PdoqAQVxe1z6wZPh1UdMKJSfEHH+zc/BFY8sFL4vM8h7gq++7gj42V3zymYDAOpj8PC9xsOS9X3Qa7Fx6yLEmYVRFrKlxNcyU/bqVdjcZTkJu7Lq4X3v/ruNg2Ub5ZdlsJZJZbdZu8CrSxoTGmX82IbCKHOYbtv387euidOOIIJeB+eSVv4S5h1lxTB6AgAOJ4QcTAgZDQDvBYB/l8RLocib9dY7vam8ZJovkH1j6bCth7rCqNUIgc1hACBXArEKhPSm2/+HpOOAVBvlWhiVWLghXPOcNzCqeo+Sw6eC0oRyFfugDfKuvPxaq7o7hiuoqqFGy3dJ23WHUYWVJXJhTEDBzZjqImbjuadLvTVQ9W29OIPqtKf9+D4YGqnGvG7bdOxXmsz1oqrXjmDEKXqXcbhx0gx6bSgUhzJzhtLjbOYDVROwY3XHhoVRVlFtMj+PH9OySdHJPoIwrIwWRsWjFIURpXQYAD4PAHcAwGwA+Dul1P2xf+Ag0JoUTTc4aXcoPKIgW4dtLYxkBN3QqpXSVt/iCXBZ1wpZvKMicMy+O6PS2bjA+Pi0Mjc7Om6QoXRPdxZG/KjXvtrjsg+e7IewJjAWAKbw6+7WHidx2f4rqrPQ1oOyoKqGdrEQdAkCxHqiJIQY1S3GJU1arifn/A3bBj1QxQNblWX3Zlfy/dKNffDcyi2pZxhrQHaer/wcWHZjNuAzhlHSXyhQGNNTly1yFkYG9XDoXuO5+ankVkwKVbUwCqSjeERZLmlAKb0VAG4tq/zQYNrXaoZXdIU11MqDCwsjdgENxeWHBdY02FT56BIHT9gxJ6DwEV49l4UAu5wSzoJeN/4tasN5NFKhaYpUtUiqaP/dxilpGVeJQb4QY7f5RLr7UuEmqrNqRQzVcB+piTcQhaHAiVT1pU43HyW4pGHem6DsLVlR5ds2v8hATLdNHl+wIfdMV2lmqrwKRa4pfV5qwGd9JMOdbdveAfug9akDaY18mBhGPYEpjDoBZbmkRTQguhYaC9Mr3UOZjMuHfUVgJjefULWlzGqIXcxZ14qyLNCKCbbdXp2/iuPedQyjvEtae4MQgBP238ULbZ91x1oxVhvpeXNQZEMfyHgLHbUAOkaRTZVTcPMsYe0NjKCry9AlDRP0uoQYRmWjDCsCkxJ9ym8YBQqllJElvbFSCNrBcETVBKy1TvK92YD71n1fI4bRMML1NDgLo7IZKABRYVQisnEQTGA6iDvtRNgnhpnNQmiCEmsazL0ljbBpKfd5IZDwaIO+wRHuKVk7AasAC+WkDMBd/2q69OaEET/fGtr4lkHV3l9/w1H8fA5jZrQr0vMmwMAQX2EU11kcEB4I3lFEHz7njfUxpxpirmavetBrE5c0BzGM2rDvF2ZhZFmSSCZw0SbYAPUiCyMsD6H0n3CkJnOo5rbUwXHji7PThsm5eHadbP5W0OpH3GKM9Zo9cPeCbilth46iQFQYlQhKKXtOaUQjZWGkE2QwjLm4dLiohyFWYRTIIseiGcOI8y53SxrneZFwXe6MpZtg8/a0aW14LWQHLQujYL7ekUua5aUBuvBteYcnb8+H6Lp331XZjr7+IgE3rrN1qGSTr/7jabjhqeUFcVMePv6qgwEA45LmZoYkiLJ4wLh7yFIQ4qfvlz2cipq6rF3SPFYUmrdmDKM0M0s29LllqENgZxmvimFU/zcVZyiTxv6WNHzavkGEwigwC6NOQGkxjDoVImHZhYWR3vXaZuW1G1xUA3tzR2j1Spmg3Pyg161n6RhG5XwIdkPuce2sHir4Pa4tjLLwJdeHNr5lUK0pwrrzuClqF2VRKjYDpTAwLLIwiqgKCl3zMOOAEGv3aUKI8kY2HnAxjNzVV5Xm1SpAJEe5qGdMvMCpCzfA3FW99TIz75Zv2g6b+9TxcULpE6GsWVYiL9LCiELr1Dhvta1fbloBRZnfcnooCyOkwqiofhRGL/GLaGFUMlon5A4sjDTyxVvS6nAh9KQtjMIF91NZk1EKjIlRAQxxgC025HouGjGGUR6+ZLwiN5WqE3xr+gIivgOIZ6l//ozDvJbnAzmXNJHCKJQBVzKqUAtFNpXSwshROYSYjWfMLWnS+akSLa6Poty6U01mUKRP44ve/mE448gJ8JIDdxWmWdM7AM+v2QoA/HG1pd8+oHJRaAdFgDKGUaIwYrwMXLikydzQZGNpu0uFESqVPZLb5doZ7f+FAYNCazLdJjHBO/mg3YTvTIX7KMfW4aIahgO2MGLB4y17Us57XgSabnPoeDzmCLiJjFDFTak7lov9dt9VXeRGKxSL7gp231Q7yZbgKn5bp6KIpiLMxiyL7LXTzlzSjGKPIBRGiiRVXJeUKMolzTK/MIaRgyZZv21QWkYWvMNpbBykiBZ8DqeWhVEL+RayNDFSP24C45IWmtHD5R+eVDYL3hEVRgVDNFCyEelZyDSXKTcijQEU2mArCy6q4W/TlrboBaaOqJt+JjGMOC5pTAXUYxjpKW5cIenGCEt4AGg/pY8NOrkuip7GQpk2MWyoxDvRGPfqkgYAk59ZmebDX3HegO0HVfy2TkWxFkbpQSYq25Yn03Uck01Ku007Pjp8j8NJ1IRSSNXPO5jA3CwcyjcE4pFmBbVLWut38r1ZYwQjlzRJfhk9jIURPnxFKD2p+ogKo5KBEvwlA4t9F4eFPlwreMqYm1Tf0IphxMvbArtAFG19ILpRQwSbem63BaSKn+Nq3BX96UEphBUNr9q0iMa4z5gNm/qG4J/Tl3mjXxRElpm5dAF1l4jykXSHbJfJrns1Sp30nS5iPp4XXfRmePGLdha+V7Hno+uXvXcvLui1XUHCGEaOL5swTevb7dklQuHUpuVU7Z5cUc/2u2zsM5N6EAXRVrl29jsMel3UEtwJS31UGFUAfRJta9rCqAhu2guu6yw4ZQR78xnndSoWR0r5WLSFUXGWTaE1kS2wbUVpON/uLOh1m1kYoS1XCFHuXlQyuWhT4VNA5m6EQumUGmDnKVl9BbcelIUKVEORa162z2S7Sa1WrzJbjroIMbsOm1PyjKWb0mkUBkbt2PWxMYzKHvddBezssF9o6pIWTP8JRLll06fU7qP1f2+btaq5p8x+tYmSLxXoOmuxJMpDqVuXtFD6URsgKowKRm6QIDp9ryRAXHrejS5pvrHHjqOl70Os1WSe5rU5+yx9o1oRnLXQsjAqttwq4bTD9+Q+F7XVPjuPhX9++uUeOTKHu1vSiu0wZXTPD738ICM+lAKe0MIIQdwQIxzilR/yshhGxXERYQvPjfW797+k+Ts7DLLzmMvgyjbWHLL5VSVDat3ai09aCTh1STOgJWo337eT8sCT6WIMI31YWRgpXdLqCS57cAH8PQmxoeFCJkI6Llv2nZggpn9gw1dEuEOs8hKBHYBbtg8L38Wg13bQqYcJO42BC97xYmf0ikJT+FS6pPGfF4FWDCOsmanFaYtxznKBrZsEhABMmrh7+lllvz6Pyz54cuHjrQxF+8Q9duS/UPCikrlEuX3eBMTjKcQ50xXKtjQIBVWYd3xz+Kbj9m329TmrtqTLzhRetwa154gQYhYDx7JoEe+fec2hdoRLxkevfKKQcqz1TQENN15XwOxbQpkzQlFtWYVhUNQl+3b2yvrclI9hZGBhlHJJa/3x6Pz18P1bnuPzQghKBgnOJa0D1vqoMCoY+ZMlNWRXUKbciDT6a7QwqkN3kCtNOy148QEKVGphxDJco8w0XdKHxH6pD+GNKAXzoQPbxfXIvXeCs4/dp+1c0rBlEgLWuwqhS5q7y1A46XgWRiH3VD5SrryydN45iXCFIgX+++eulZZNBc910aX2XJVC6namsjDi9P5uy+8pezzNWdVbSDkpVx6D/EXIUVru0xlggl6HgkA80ryC7S/z124DgNbhzk5jegDAMIYR+5v5Y+rCDfDkkk3ifIjCsHNjJyhyikJUGJUMTF/ecXS38J3pVehxCNWhXw8qM2y/NXvsfuIglCJIYxgxT9f0DjRPFcraxOGFEJsy2qv3a437QD7dlUBbdFtWUbkhgqjqfMrHvJPlUPqkDtKx32LQ6wgcsMp9SqmTmaY+z5q4NNmlIcDv+yKjAOw8/tzKLepEEcK2cbVe2robolzSApk7Zy7fXDYLDViZGMlfc94nSsuxyf7T6CDJTJrA5MIqnwuzMCqonDIRFUYVwCUfOBk+zIljAZBxI9KZxKMkCwDuBXqf1fr9tx8LO43t0cpDKUjV9Vl+r35sMQCUF0tIpkg4Yf9dmr874dQnC7EQKHrevmM8EWYK/8IyLIy4z+wZEVsYeXRJq+WfVbGXsvUvtzCq4te5RxWmojJZzNbPSM3NLWmI2PjGMAms3M5rkkvIYr9gUEQ1Y+c206DXEWnYuaSpaOdTNOOZJn+bF6+Vvx5L1aFLWpxynCEqjApG1tQUM+nuu8tYeO8pB3LfmU68cRDVoSvQl+2SxuNXxROVpMk+XrFpe4NmOR1Eugi4Oh1zQiUc6FjrhDLuA2FDG74Vqey48z0GhRZGHmX5drQwcpEuonyU2VbZOXxEHHZQC2b2Ra26kFsRid8SAvDMsrxlRnQ5LwbCoNcOS8CCp1jMXtluV0KECmr30TyyoSyMbklLKT7x+TEpQ5tKQuPHB6LCqAKQLcy1lEuaxsbRiqPOhbLefM4ahrQpFZuIZ5/tMLrHpihrFOOSZp43RGC/p53O9Fq3+RXskhZI53FifSCYzcxiFeBy8RVGYdSpDliObW6higgHZXbDvIVRzYl1GiHEW/80UZ7HW1BxsG2xkOqZa2EU50xt2DSpKi+vvzStuBvvjGIbGsbiwpSFd0kLaDBUHFFhVDIwfV6WxjTodQVldC9w7pLmlpw1KAXY0DcovDEpO5mOa/grl/UdshNIIvgdgUcoi6ercXfQ7jsAQHECchm150uhIqozry5pbbhP4LnZJYjrbHVQ5tyYHePDI+nNmilMg16j6gK5Vqf4CUmTETBs52BhrCyX1Y8+3MsnxAS9ruJBgk/4PCTljcu8S5qthZFGPkQarLVi7EbuEBVGBcPYRE+QlB3EOuMilI1j2dCtBaVpZ2DVOlyrwTVTlgjfZ/kdN6qb+7wo2N6igkNgjWSJQoRDx7BlLZn1vnTW4QAAcNrhEywp4uC7TotsMlG/8anUMXWh/s+T93fMiR3YupOdlsd1to5YCy1wLX0zfw/XqJNKI4SYKR+Ssg2UQjJ0okvanuPHWOU/8+i9tPO4qGZX0QF4STEuaRFp+FxLuDGMMu9CMwoziaHmE52w1gdW5Z0HTBeTTc6m825og600aI5xVXKvk7pBnoHh1vE3Jv7RuOaNfOVMfvEAUh9aiuJA6tfV6eGo7i444YBdC3O3K2PD46vIMiyMeLQxdRpKv02AdUkLje+yUIV6CMslzc0taQQMYxhh0kgVCvyXwlvSEOVVFS/abZx2HrbNdt9xNFz4H8dp5RfVp56s4KZVTINet3OfKBqqNZb3NttGZi5pbH4dEyN12k5UPpeNqDYoGTiXNCI0BzT1T99rp7FG+doNrhU8ocxho7vrQ1vdPdIMJ/nKUtzIhBRXdRtKG/lGyN9ZgmV85SD7Ljc3KPGJ+FS+8fYJqDUwtFZm2JHNsSGPwYhwkN38DDf9HO06UBchVpYB0jnIgF6nbPLKNsZwoexRtT22BJ4sGeO+6cPnLWnSUBCNV2YuaYYxjBBp8LekFTPndMLUFhVGBcP1aQ87IHv7h1H0dtthFJzzxqMMOGk/6A7yom9J+/X7TtIqP8G8H7wRjtpnp9QpASbodbKQ+5hk995ZbZqdXbh+8M4Xw/+efUQuXfRvb0FHuRdKrdm2n08rGBm8u6Qh3FV8lgUARosUtjna5Tpl/GYplBEXoUJhGwvBM3ZkjIxQN3MNMZsrMXUhPdwRPI8xjJDINJlurQktuTQ6lau5SzeG0SETdmzkc1J828BnfWDcD+0tjDTyIdKiYxjhi41QICqMSgbm5BTrktY7gFMY/cdL9oexo7rVCTsArieTMi5JkxU5LIvIysmbDXTnCq85cgLss4vaNLs7MyON6elu3tzmCu22gAhjGGW+NKRDPZblj7xiojW9ohRIoVi6OLlBSfDcr4UR55Y0RL7QNg/YjVdgbEdIUGZb5S2M3IxCU5c0X4j6Ihxs28yNBao9DREd2cHB4XuNd1Nwm8FqzVcddEveJ3OTkVUYG7NXo1dj0sbDmOIRFUYVgGyiMAkeF4dZCzonLpQiLIwcT2KE2C3cKsEzO+m2LIzMy+SBAKA0Fianltq8tNkA0ItL4I0NY+yzi517bJHfVMqGx9staQKXNAPBEJuFl872ptCQUVW+XSMURWsI4K5xmUfDNQoEiINb0sxc0pJipXGKZO8Fz+MmryiIDpHwULkpYZvSNIZRRAZW+iJ5ZozcbdJiPi2MsofLIphMOZ8+/VD9TB2AqDAqGtmRYCksx3nXDrpziXLiNWfFC03VwpwLtpkojDx8ielVmS0f6vyzToLubWgh11HArEnh220FS93nCbLPJYV3o1gVlQl4jqv3be2Kb75J7oZfatDrzN/DIzU3N111+Y0X48pVKiINW4tZF/XsajzweMFY0IUsv1QNNqE0bG5JS8Uwwh4qIdOiXdIM+lEM2cJHVBhVAATEA8jMP92On3aCc0sa1xZGzFSuu7EihMDwiEJhlPk7Wcd91AtuEeDk5dKz4KXNNnGi77E/YywGJhyVpScvxcDIE12xhZGnAkHgkhZel1QCy3MVv61dceohe0jfl7ku8G5JA7Af+wQId65E91/ZO4J3h27lEZ1u4PiJwIGt57987GXw6DmvbTzH05BaGDX+Z0pn++AInpEIALAbIqq88rYW42OvOlhK11SUQB0uY4NeFzS5dMJaHxVGBSNroofqY44tjGLA4Ba0JxMLTb0pbNpLbWGUpk09uaQB2Psls29CisdTOio4nNlmto7XYJlfq6xA6tqvhZG/wdUu4xa7bgTSXSIQKGpscw9AMk+Ha26CXhMC3AlWRdpXXWBvNmormLj4Mr9Naoyt5l3GjYL9dlXHj8zCZwyj5Zu2q/Mhvvx/zspfiILBIXvuaJTPBHvtpL7sBQObfYAqa5dEE6ByS5WB7fqu40x2e7QwiuAjKowqAGkMo3aRwMuCW32RB8scO9pDTNBrzIJT8+mShuiqWRYJeLDaarMFRPQ5vHoL5dtdx7Ioahr07pKGbDM3Qa/5NEwOIbBKJl7MPVydBtJxG8BbGIXFd1mI1SBHdsPmKsYLIURg1edm/hCvPfznnagvcgHd5kpZppP0GyxcrdE8OovXbxOm11nbqtCfbvzcK8tmQQl5vCrzSmblAp0ZDaNcwrZ9UV2k3TwXeIgKo5KBGUSy8WoiVrR/t8bDp4LHGU2LfLqC50hDv+TFwgilMEJumGMnbqKKdWHNM9OX2nVT7vuzhKeKXl3S8s9wn1nNg5H27Jn6CKEeyog/yC2HKei1R+3VKJtjYcQEvd5pjNlNoV2EP3JUm62kXNXcqq3IaNO5OgfL6cr2AMSnBWryzibo9VbmRufddhjFvRkNQx/rlpQnbpbNBLvvONoJHTuXNAvrJNk7Bdm0hZExC4Ky0ac2bgvuYESFUcHIDRrMJlrybu6qLfpMxPHThG5VKAUox5Vbt7BRpJEkYGMYYTjz6ZKGgWz9dyVstlv3x8cwom337Z0KJwFxRTGMLHY7v/nvk+Dlklgx7WIRi52LoqxaHZTRVrL1ln02Yecx8PkzDtOmT4B/Wo+VU6Qn/URn7akD60bS6bB1C3ZxEYbM6uT5NVvxdDi7zCkLNjA8mfeJTrp1zypup8olTWphZF5uSmGk0adxt6R1TtuHAm8KI0LITwghcwghzxBC/kUI2bXxfCIhZDshZEbjv9/74iF0YAeQbEL94a1ztMvtBNM5LHQXK1cuaWN6cEOPMEKZbqvVKEX5imfzAPhwGcL19my59e/Pw+rEpM2EDNXnHDKhOH99PBz3r4paoGSh09d9xX4yuw2l/u9bjt8PrvnEy4TpzINeV3PMxrW2Sii+rVqXTIgULyLXIhzqLmm854p8jXKVU4EmT7JYKW0Fy65kbWFk2W8A5Id3Szb0adDJE8Lckoaj7YSME7zyMP5BibNYUDZ5FUyYyvs6srROn8bFO8XRKsNytF3hc/q+CwBeTCk9HgDmAcA3mHfzKaUnNv77tEceggdmYHRAP+w4nP/2Y/GJkR3gio9MSv09MFwTpBSjKcBq51TD1i+ZfdUJk7M1GnX0tdcf2XoUSMW5ZCOMLzLHaKTymIWLbxb1BWtFlKRxuQojFE0LhjwAy05ofHcy1Ja6BfHB9J7WAY18fTRlTbSeYr9VYWAkfid4KdqYtt0wKfn8IhX7klUe6VERvunpIug+hLEEMVdqhdNzxH3bjMfR3e6251gXVF2osrFzml4MI3Ua9C1pDrrIxxW3wXUKvCmMKKV3UkoTR9XHAWB/X2VVCSYn4YSoB9B+u4yFMxv+8Bh6EXXou6Sp3uMovuLQPbElohUlE/dIW5LkAkgrzN4BWkFpXfcRbK/n1h/nWZt4tniFqZhYBFiOjCxanHESPoTuBZ7our7NhMW/nlzO4QOxofDBjAVi+ARNFFwRZx+zd6HlmYJqHNAY2gAInsqpJc2lmgn05ac4IDBwGcPIh4VRj4Zpj3GYIcy64EnRYURTpDByZWHk0XXP16hku/Ha3oF6WYjCMN2/SPfW/XdT3zLYCVNbUQai/w8AbmP+PpgQ8hQh5AFCyGmiTISQTxJCphFCpq1du9Y/lwWDUmQgYCAwdpS8qb7+xqPgjx95KarcDujXaOgNcuoscKaZebnqvX3LtiwA3PcSk1vS/HDSXhDHKyC596HUpXOFZGAaJJ3vM7GcI8SfS5ojbwEuVmzuz/PhSIAsEvh2CmXEdRYu+9AkdaIMCmsppqDmraScfkJIy4rDtB9Zx7KRWT0RmTKb/yIkF6J2htDaRaP+ZUqGUd1daMsZVd+1iWsX0vza7fpgJ3vga0oHPO4dFNl4TYspCeeNgOx/qFQRGFgpjAghdxNCZnH+ezuT5lsAMAwAf208WgkAB1JKTwKArwDANYSQnXn0KaWXUUonUUonTZgwwYbVYIGaKgnA4XvvBO875QDf7HQcXMeYcG0iKxPKfKAVU8Gcho3ShxfDSPVbF2XIGF868/DiC80gNKWKDViBIiCZ0QjqeCLhw6ZrVeH7skBvljzzEeEOZWw+mwojzrucFYcBf6IcWDlFpTzWlZ9E5fpUUpeNMj7N5BAiC6mFkUg7wqWjUBjV+AexrhQLRUHkeheCUkvVBkUqclX1gW1SvEtaMR/XCfEKrRRGlNKzKKUv5vx3EwAAIeTDAPAWAHg/bYxsSukApXR94/d0AJgPAEfYfUZ1YDK/Jf39nSeJvfp0BkUA81cw0K0LV3EQTCYxbeumTF/jK3LSD2UCLBa8vBTMA9mVbXX04hdx9dla2HncKAec8KG6qcaF8OgaIcUe8AEXXycf7/biSQiCLACgOmUgnDYRXdL0UIVqKINHKjmgcXEL0OAIP44h2sBIsmbLZiBCAMaP6ck9F837QwI+2x2i2ChZRYjubM/O7ekYRjr7BHHaHo3o5SrXoayysKpzpjhwvasCLLIq8hoHvVYwxZs/UIpARBoNnaU1wlFLlguft6S9AQC+DgBvo5T2Mc8nEEK6G78PAYDDAWCBLz5CBt4lrfGvZIDojJ1O0IT6gquaw9IhYKAoskDSH2029KKFE3OKyDXNd9xfdT/t4D3Hw5uO28euTKvcejhojx0KLM0MtvWR7UoBHTTC9Z95hVb6TJSy/HsCcNkHT4aPvGJi6nlAn2wF32Njz/GjPZcgRlxr6yhjE4iJ4afz3hXYYloKo3zho7pbvYeA2TjpGxhRM8F73eBHNa/K6ow3D4p0YMMj7TKb6cFXn3NhjS3LN6obH/RalW5EIBhi6Nu4s7mGbYB5FaxuBkbGLHMNrkuaI40R2sIIlSoCA58xjH4DADsBwF2EkBmEkN83nr8aAJ4hhDwNAP8EgE9TSjd45KPy8Bn8rdPhut58NIPpwpydc9lF41OvPoRLoxVTAcsdhw/OM+y67temwpxOCHIJluuvvK5usMmLfxHKBtaldQsBYnSZgC8csNs45xafZx+7D5x6yO5aeZTl2pNwAt9rl4+xi1b4h1LJbYQdR3eXzYIzyCx6ux3cQb9tcJj7HHsgJL0ljYjHASH8DbSoXFfXrFcNonWCF+tNi66wPDwNWR/BbtYB1JZyNUqN58kQ5LIEYbukqd774ZHXPCoZdMbSTbB9SKDoZoCOYeTg00zjr7Yb8jajjkApPUzw/HoAuN5XuSGjt38I5q3uTT3DbHRI5l9bdELHxkJ7A+3olNLIdU1VdiaByL97l3GjYMJOY7jvbE5sJu6xAyxa3yd8bxrIruz+SsDtrSWuoRt4tB0R1H7D7ZTipB0PnbAjzF+7LU3XqWmiedZK9tMYcLM0oG/c1EgLUJybLFtMwh+v7PrV5aSZx4S9gWG+q9fm7UNyHjP8CdNlmBrVTWCoYS3EUyqINtXDtc50SfPV5dj+lLJf1VIYueeFB5HMiVkXTJcdF0qclxy4Kzy5ZJNTmjLYkFcp+IwVdooW4DYtoqyVCIUpPuh1XIVdoahb0iIA4KHn18Hds9eknrnSkGv5Jrspsi2gHcMIsb1zQ6cFn4JslnQSSsDOJY3/HNPVs4eqxMN0b/JpthYsRY65rOBiKjAWBZO6ZefN6Us2wtSFYRmp6lQzXtDkbwLcllE8AmZNCDTLFfy2dkF+HpQ3houYQbpI3HF4Y0Dn6nJfkB3y8Hh+98nJxSyEG7tGNNbbzSUNu6b52sy6cUlzw1u3YpeZdUnTKbZMC6P/ed0RcNPnXtn827fC2Ya6ctfijXezGEYYoKfHgqbR8mdr/4gKowLB6+CY+a7lWqJOg0IVJXRPCL0mCLhzf8D0Ixe3TgiFIIxfMjJQV5FyAiEuLIyK72khD3OXvIliIJQFm02Ar9vfeKRCOXnDcGFTFz56B9pCNJA6bifYzMXXfuJU4buiFDRsn0jGO9fCKBPV1cyV2qyy8P07DVY5wFPAiV3SooWRU7qCuHh6Qa8d8aIZ9FoHZbqidxMCx+y3M/O33/KswkQoMvua+oxjGCFQZAyjsCTM8hAVRoUi3XVdTnZRLDWD7kbe3SKqn66uPPLb0i5iGFnoi/jkHH+ytnUG2C8YRSpvREWFtOi1+0Zap73ZpNw24ih6dectU1fPvXfmu65mYbOWhazYFMGVEr9T4HK827hNv/zQPYTvyrAwam6WuRZGLfHctP5s53xpDCMgOb6TeUbkQidUGLWZhREWvrqcEwsj2UuN5jK1vMGsKbUyD4sy3d+/hZE5fVU/k954aHMA5pgei9Bu2g2MHS+ICqMCYbo4pO/KEKQx3KB0OkyUB4XDsFDRUkpALAgm66+NRQwvJ3ZZ525sHde6ybdZWxjZZW87dMLiigZrOYfsaNrzlmF9v++UA80yOkZoCkbsHBIW1+0BnRhGqb8VjZG16CkCNYmFUXcXgeWbtgNAPf6l0Rg2XLeS8aZSzmVZYr+Db2HEp9POQa+VSjcPEPYVnX2CosNh50DMvsdU3jTtNi5qPdt2OoHAjcqzIK9SrvizMOK4pDkqS+Xq6LI8F54X7YCoMCoQ3ElRoyMWbd3SCXBfF24nFpRVgciih6KSpSC7tQULYQwjw6DXTbopWppMWYAQIuR9p7He7g0whjPXVY+wZSOkW9GyIMR8I8ATgNXHBf5QhJtOaMoglwjtFLQtgL1xU7PqXdxKhkEq6HVyQMNJN4pRYK3cYnZrlrWFkeJ9ViZpWhgBCGIYxfHAwiB8HQqioNc6cNVSPudAG2tDF2D7s+ul0iU5pYWRpI1sZC3DmNcoxKDXxSMqjAqEbQwjRSpNbiIATFzS3NQzpQD//TLc6b2yxKZVEK5s6eKgSYtLX8AxKuh1Jish4Lxrm1iVCXlHH3cXPz5DFs4DZq1wsFWBFYB168/UJc20D+nF1DMqolSg93kV/DYfCKEelBZGJbikyUY7q8Ci1GyY2MYw0g16rTrgKsPtL2Rg5lc2zbtP3h8O3nNHRB5+fq1pWaVkQNJxYXlz+hETuM/LdEnL1k/foPoqeB1kv8wuTERZFkY8VtwUFt5hTGj8uEdUGBWIbP+mVM9SQtYd9VzS2r9j+4KqnrHtSYHCD995HLz4RTtL0xEg6Ak2my53MsC8T95lKScBhL3ckoaom53GjsrTM+bEHUSCs6l7hE9I/dEDWWRD4cMHSPP/HNFrxgVxPyZVwG7wssNDZ/7w3RN8mJPHoNd6cFkLvm6gKkqZkbaUTdbbfLpRDlzkfFsYZdG0hiR6LmmdCl/VwfZ90zJkc7hOv+BZmmWhSvHHD0/iPh8p28KI+Y25Ct5daXqwsTCSQlH9Pl25sPN1G4uahSMqjAqE6aDECN8uTw4izKEvYDnYWGm2pyg5IY5c0jjPKKUoQX/sqC5YdNGb4a0n7Mflr0nPRhQ2MDESlRaCb7OIBVZ4Dw22LAVQ7VLozcet1DILI5L6rVeDfAsjNQ3TDZ5OPtwpuxkfvoCu/8D4bgf4Mioow8KodckEya0x2Q2RyRgwmSfH9HTBqxOLDkX+LE/s39ElzT3qh8zqRhVGL3BmIY/vWLrDije39ggC1hjHMHJQDSRDZ99dxtoTzdB3hdJiGHGeuSoK7ZJW0JTTCVNbVBgVCNFGWobff+BkGN1TbybZZB8X4mKgqmXZ+0fPeS3ss3N9UUG7fhGd02w7EGAETAtior6IkTH4Zu7l920R7yF6pEljGBXHRtvgy2cdrpXe5uZF3u3SLtqMO64Q+UwtDXXqoJJ9EjsnV/LjwgZ6s5pVZigarQx3qcSil9dPRmGjukpgcrByw2dfAePH9DTyK+gLDysI8EJCRZe0NHy51aRd0kxp5DMm/UKHrs9g0EW7pOUVpAQO32s8AAC86+T9Cy1bB64tjA7fazz84j0nqhOKnRysge1WLg4XQz+gLApRYVQg8i5DasiugU3R1uFDI21EC5QiXNIk7whH+YM6XVezxudFEPRaJEx0EcJYGJn3ElFO3KQrUYoy72wmcH0Do/zpry4fZbim5F1gA1r1WGuxgNji4YDddpC+P3a/neGNL94n9czcwhsXM0SXvmnvwwqSNk1YRaUKluUKflrw8OUG3FNY0Ov8OsZbH/IWRvq9iaeAVqErxZ9sPpJbEPGUIZ2oL8LO6S6Rdkljf9vS1QfKQ8KQsaKDXqeCiTddxfPvfMCGuvrGOz1673npAfCOk16kTMdtHUfVhFU++3cV7BxEhVGBMFksU5sER3xUUUBvN2ANeepmr+mFSZjWsl27CGn6hJv0VRdLN69c193VxAJEHMPIT5BiGxqyZKGM/SrEdhndnVh2ytNN/uJpcOQ+OxmXw5LnB4k0Js3Q4G3u1PmKuGk8lD6JxVPffh06bQjWkRE4dBfR2TNIhjtv3SvDRQ4gozAypME7HMvSbmcYGsGh0ulelGNsYSR5qNMvTLsxpg6NXdIcyB9JvSa0Qu7Zyr2Dp3KzcrPLcrBzyYgDKzSMnB9y+7tCVBgVCN4k5Uo/rhX0ukMWbT+wsbxp9QBZsEvdEvUtegQ5COsqZ9FHbLI2ymUXmpC7q2vB0IgHwSwScr3Z8lbEwWJTIETwyrqPEODP9R971cGCcnCWc67bEyM0Y90JfAqGtnDdVXbbcXRhbsLtApd913Tsq3goSkHDltKKYeSHn2Rc/vCdx6HzsMWqYqrJ6lTnZsY//79TkNy1F3y5a4k20zrjkGdwl7KwQdLxud9woQzQAe9LqhAjRx3DyIx4mcbhIcu37YqoMCoQubUBcUsam0UamyQOnkKgdElTbPiyi6dqok5diao8JcCbnfL4ZPsntju9/2UHcvjgA2M+nM0r+v5iXdLEvIfuTgWQtVIMY6IIgws5WlaAfG5ffsgezfhGmBuNvvK6I7jP06fHYXUo8xhG/ssoE9hxVMFPaxvo1n0Z8XWSvs8L6tvtJIZRg5YGKawCm/eeMP/qWBi9+ogJMHEPuetvleBz3KNiQToohzfHmXwX6lDUkOGiXdJkHh++53ob2U3VBrprMP426DQIcSeBhhYPrRMMMaLCqEhw+pPOdCe9LrsSW7D2h+6GD2Mq6sK8GFNml4ZyKsFXzz6SQ9/CCouTtex5+LC9xkuCXhfnkoZF1lRaF0UsxGW3KQZUcvoPAHDtJ0+FL59VVwKlLIxIK89RjKsa5pt5B6a89izKxdG0L7T7eoS3MGrveggZunVfhgvY207YDz76yonw9dcflXs3yuEtaTobQuzBjIokP4aROFNYqnI7oC2PPXU5kczosjisnNdOFkY8NENGeJ7rfVoY+WqirELPZTG8Wxh5cHEIV4WD4SIQFUYFwuQkFT3ZapAOKvhtxaCqZqmAxUmHa1+z02xdN5G0uTGyTAQfdV5wk27CA5u0zE3XsfvtDJ847RCxwiiAoNfCm2oCVL4lsK2P0OYw0bW/RHNM+ToxNW130z20axfpQLptE+hlOTTGS0IIp68qDgo7sWaKGdVN4LtvPRZ22WFULpmuuxLPyjHZLOl8mwuLP0IIl47M0imwKd0ZZN/l7Za01OGCWRm8LtOUzzTayueoEumLPvzyg+Atx+/rvDzeoU1ST/4tjDzS1iSOTc+99dVRRYWwprAIixs/iAqjAsHrUDobH1fjo10X5iKgmqSkVcvJetpheyrKY7MrTgmkb/np0htaA2IafITmboPBpIN2g64uIuQd/UWFribhL12BrfVc6Ch1R2c2a8lfKTdPARnViX5z3KdoOdjUYdIU0FC++fCx3kXLofCh22WKuiUNi6wyQdXnJu6xY+5Z0vd1FEbpgy3NGEbM37wi+4cMrm1rY+jOIrTxPx3CInlPTSOfNnmiI8thiiQchjElyPqnl31OiYdwNmugrxhGKgxnNEYui5HR+uJrD3NXELSX9aMNwloh2xwmAe5MlAAqxM7vDyoF4J47jQGAlgD3uTPUE1sZQfWwXTWdp2GaK2AY5XuPXJBtLExsTPtN+Shje5ktkyL5CM16pyxgbzIESG82Ra5j4n7XepEO9s5XQjkDgmAV4wsVAWy1xPqrDoqyMDKV6ZTu65z3iQWGsUsaOhePTrrM8WN64IDdxXGKqnigZIsiXNKMaSjo4vuxv3ElckkjhMgDtptaznL+qsItaa5jGCVQyYoyF3tbiMgcvtd4+AonVEaEPXrKZqCTkN/AuVsgdbTPcT9oDpu5jgCByz90Mtwzew3st+s4AFArEYnOcqsUKBOFDl8QZHkxOc1oxVrhA3UdLGdJdt1dTfq/KAuWVJHms9miojWEGVQxjFiM6kmfvfDiGmDagdefuEpUNUtOgA2Wa7extMgcONr520KHrsKljBhG7FqUXZd0DZ7480udqM63sXTkMYx4FijicmZ97/XScjtRLsWsCacfMQHWbR3QpMv8NlDyZPOZUbApB4cRSaexce/ec/xoWLd1MPecdwDUfOa4atxa46gsjNyVJeUDCGzqG3JDK7DFNTB2vCBaGBUIXgdX3pKGtfQw4CdCH6r2UAWJ3GunsfC+U/I3i9mULbTowdBs/HvW0XuZXZnKpOxmFFKmkAnJZUzINPcj8z5kIddQ01DEJ5k25Y/fdTwAFMOj6pY0FimXNIFVkalLWitdmoBt38N8VxEWMr4VmmVazMV1uXh89JUTAUB/Q+HrinNT8A5PdNEMeq2jMEpZGJmNHZdWvDKcceQE4bs9x4/RJ+gZucMcRD2dcdReqb6sW0+m86vKwghNR5Fn3KhuY6WWrC7s4mHzueDeHGdTjAas5GoD68TQUUWeq46oMCoQth1cll+Hdiea/hYF13VLiI7SELehJEBS7xZe+Cb4w4dfKjyVwqK1ueQoRoEir4MlSQaGF7crg0kL2barz7VNdLVx0DBs01MO3t0xI2K0Yhip0776iPTGhTcSRMoX9in2VNSJy4GExjH77gwANqbqbvgIFSHcEBTBx5fOPFzwJoy2SG3+U8+z6fTo8pRCCX3sjUJZyDbdIdTmm44TBza+56unF8gJDkW5qKZiU6YEOzwN/i139X8pdTdvjxvVbZxXdktaragb1DjWxKFBvQ4VZmIUIikltPYubYyoMCoQvAlYtRHthE5YJdi0h2lOV31ARKXlqsZaGOmXmTPRzUE962KNYopWeYoWjBMP2BWVv4x9I/eEEOMWFbA+OZR6zGKH0T38GCgIqz32m7AbNALEa/yLiXvWY41gNzg2faaKKxzeAjMCoNhxWyWZSceiUBnDiPMsUUB3c25QE5fb+q1tzZLIAAZtYGIJWDWFbHaJCDnGGV8Wqz90eSCQWATq4oi9x8MXBMGNCbFzScNYAzefKfK4gs28pg56bUa3KJ1c2YhGFnVEhVGByI5Jl6alOpNJyBvC0GHnkmaghEGU2aKf4UUwyYnoYW50yhNj85PsozQ/iH4nW7iwsRVU0BFMk6S8HONGdcN333qMOSMe0EWqIUQfJAl+KoPJtb620K1OQqA5CHSt9nh90yaIvAxCBRa0Tm6L8NKpQHfNwXROjigAjTr//QdOhtMOl99CWgZ8hRnguXM3b0nT6Ijp+cZ94OAj9h5vlpEDqbxQ4tgTWndrKgHzhLHWDqLfGv3A2UGlmM6rDtsTPnfGYUYl3fk/p8Phe+8kfG+jzNDhp4uz1ocG10Gvkz4os/DiwWUdYVkuSlbshLU+KowKBNfCSCOGkTuXtAhf8KFxtz3NPn7/XeATpx3M7yOC/mXkktYlz2tyn5iOS55LvOTAXQGgXncA/NOqI/fZCUb34KZQ2Tdc9sGTrVytWMXgWMa8m3sa5rEuX3XYnnDKRNx3/MdLXtSs4/BhpugFyI4pPeuubGrb8ZmFiJ/6DTP139jYJ9nRoXciVz1JCz0nd4IUiUCRVj9Jlb/q8D3h6o+9LPc8JLDjJOdanOFXVYd8+bJhYaQV9JrNj86Wyiur65ccuBv3uYnoJNvohtLcbB1mm4H98+Gvn+GHAdOK4ORL848jrNq3+JgjCchvSTOny3lWmJuhv7zaCqPGaNW1CnQcsMMptQSfec2h0vc/fvfxXsqtAqLCqEDwxqSrARTK4tjpkE2gRm2kueFM81L/96OvnAjfenPLEkZEJR30Wl8YaFkY8RWjmMXFlVLUFqcesgc88H+vgXefvD8AyONBYSBLd/ax+8AolMuAOs3YUd3c+DkJxiAVXCboGxxGpyWEwKmH7AEAekJHKS5puhZGzG+MIJaynNNYEbQOCXRcCKAV/8GFy4Qq+GyIG3kVrC0FIryhXZpCd+xxL1UxoMWmVQVMMMH+u43jPjfZ34c67sRW3OkXtjfTYspP3dSpUYQr5Ygsh6zNbS4rIMTSTVrANP9mQPE7l7ChruJNKndzSh6p1f8t0yXNV3WfceRe0vf77cKfvzoBUWFUIPIuQ+b5dxrbk3mpQSj6pBlD6ZJmkZebB4h1gFWsUiOlMDKxMGrGQuK/17m1jd048/i3OT3C5jxojx2bdSrK48o1xdWQHMsohHi3ao0f05PNUimUYbGBtiZhfyvcM1P5mES8ftBSAJLUM28uaYSJfWIpIVzy/pc4OTm3aXYfq929c9ak/h5lW1FtjkJjGIWqRdCEzMKQB+6ZQ+KSZnpLmuEkIyvt06cfCpd/aFLuuUmckJ3HjhLzUGI/EFVbVmFEBL9tIVISYfvUO096Eey981h5GWjZR5yw2eYe2qo4CyPnxfDLtijHdayspG6169hhkxQ5uuOWuY4o5RQIkeWFCX73/pcY8xH7vkeUULn4mAiJQodwhTOZYCGm2YLMlxvLY16g4gf3tapmo2vSwh01LGtjM1fUAoCVlVrZmLhHOtZR85aWAgeaTZ3pZvUh5Ir4EJ6iAoGRphxv1192HNOTcpPkl6dG6IGMx0SFUTAQKkIL5QIHlzEPZRZGOt2TpaJ7AIZhuae7C153zN6557pT3w/e+WI43GE8pCKQX5tD7JUAF7/nRK6S0TW7vsQqApZBr0WzBa/PNx7aWERhYLMWq/TFPNIfOPVAAODLWsMjicLImCVriF3q03+bBu43fd/OiFJOgeAFJVSBZ1p6yIQdYbcdRqfTBSkOtRcoqOtZtpG1uXmsnl+RNsdLnga6LINZsWVhxDPbJbhgjchirYJeO8zjavFwZmHExjByQ9IbMHX3w3cel85TwlfplkhIS8mpG7eIa2FE0v8aMaUDwsQ+sRyQmOxVU2LygI1lFhGBdfnSHRa8TWErhpGZxki1Lm3qG+KTMBjSukvgqw+fIJ07QpxVci5pKZlLnE9/DeLnzZYho+vKmkaWhb/euWk56Y2jLtccoi7PBYYSPzADqJUg+QQ8q6Tk0UhiYaT50S4P+kSfVNbNg20gxihRbf+EiiG72aGUOhtAvuJZRDiE4YRS1ESUjmGEA7vQSANQEtwJDE8hwKPq+zQnXx7nGeAVGCoBxdU8MHYU65LmhKQW2vH6URu3Q0zWVOBbGX0cG2iI+i57Opuz+CN66wdGeCviJjbfiAqjcBC64I7d0Oh+Bo9usp/TuiWNKVlmpRF4NQfZD/IKG30mdWUfqVJNNqErrGnwMqL4XbL2OV/bCMBLJ+4GUxduMM7PfS555lr2IUDg5s+/Cuau7oXZK7fAUfuIb4RTQTXnyL6L7aM9XQSGRmhTUeTLIhoD0SfZKoxU+40Ap5XC4E3KIYScRwhZTgiZ0fjvTcy7bxBCXiCEzCWEvN4XD6GB61qjuiVN4Iss84VWoR03dUWhqFg0zfIQZYqQ8NIUGDgnh2z/so1hZBPfKUsjdVsUb9ygueLkNWgk2zHjc5FhORvTw3FJy+AdJ+7nkRszfOrVh2ilL1JO0R0LBBhhSzMvTwDjK1Ed9CgJiZFm0Gsz0q25B8FGG0hgMYZROBAqQgPpaKmuIpnI8spaOf/cW9Iaq4OWgRFLRtedg3F714Vr1xFTHLLnjtY09t65Feif/SyeAr7525OUkDZMxe8buOuOJMN7Jh3ApyOLYeRxHf/K646Ee796OozmzM0ua7rZph6+5bj9d4F3n7w/fPstx6APJd7/sgNzz4yClXPyJG6KiYXRSJkKIyAwjuPubuLJ4wKhrC8+4btqL6aUntj471YAAELIMQDwXgA4FgDeAAC/I4TIgxy0CVydpPKUCJ3QWUOAqprlZrCGZTaFMHm6fNH80xvM6YmNSxpPIVM/yVLTkJpls6b8AVgYAdhZn8jo/9/rj4QPnnoQjjiDHibyac6isfHv5197uDZdn6AUYN9d5AE2E5QxzdnchIfJy7a99MSuoG8npDWPdWUWLRELIq7LMg9PoYCpIloYyVFkLwihy8nQg9zRaLukccgm0wm2TIB0W7m+xEMO/YGqq/DA4IDdd1AnkuDi95wA33jT0dx32T1AWuZS08bWkAu5xNRiVge+pmZCCHR3EThkgv8YV0k9lRnPh8UPMm78AOp2w/aXxFIxsTDSjnntMug1AdhhNEdhZGthpKwsK/KVRhlSztsB4DpK6QCldCEAvAAAp5TARwkw0fLmc1OwW6yjS5o/yGMY6YONh5L8rU8DV76tf3py+mCzcPK/j+TKKroLi74JW2Xq2FdpfO6Mw+Dzrz0MSV2vLEw7n3mU/GrRwhDC4mxkbYdT8gKk214Ww0j1TMoP75lQcUyaAqEP825eeVUH7xQ7ooXQlThFAntjmU68mfp7noVRUiaqyEa55gczWFmDB30LozA71TtP2l8Y6F9mYYSFruyTlh818nFpkSYP+UNrTcYSQqZ5PUJn3WsZGNFg3avVLmn597w8ydw1HIBLGgBwx1mgTdAW8C3lfJ4Q8gwh5ApCyG6NZy8CgKVMmmWNZzkQQj5JCJlGCJm2du1az6z6h+1kIjNf1YphZMdGR+COL7+a+1y58fdYubobK57bGYBYgHClmee71SBd0hr/si4tA8MjAACw09hWyLXCg177XhgdkSfpScIYf/zIS2HRRW+WpnnL8fuaF8AgNGExC91xoSugi4Je68a7kCn5dLpX3cIoCZabfadXF1kLJX6BWiSDQPb2vmhhFA504o+Y4Jw3HmWVn1UYyS14zOedJn1BLDIpHTa/NJ3bget6hQ1xXeHdAtv67Q5pumaUdS2MzJRffuSqdB/2K7ux9fv4N870V45Fhza5JY13I21PQyAYaSqM5HT32DF9OZPrlhjHsTCyVyRzFO8Y7wjLUqsAKymHEHI3IWQW57+3A8AlAHAoAJwIACsB4GdJNg4pbnNQSi+jlE6ilE6aMGGCDatBINuRKag3oiJ7C93Tp1S5UWOkxO47juZuAmzi9JhaB9laSGKLNVEY8RROvDpgN6G6PGzZXr+JZZdxo5rPXCpwbNaX0IRS0vy/zDMPOPNoN1ZIlOLHRlOh6KRkHEzqL8mDG1NM0GuBshX1zIHVUfJ8JBv/TBPJV4SgL/LRV37ynyek/o4Ko86BbX9FWxhl/1Zk49FNphNsmdlyjJdZE+WBrjUThLf+qjBhpzGpv3Vdx4zkHskBxqsPF++rZDGMKOW9128MrkWtNpXi8FrOoQxbJ3vtjHOtLxpG3gNcJVL9YSLLq2T6e7/6Gnjoa2foF45AdxfhuqTpzHVYsF/ZDhbRprCSciilZ1FKX8z57yZK6WpK6QiltAYAl0PL7WwZALDR0fYHgBU2fFQF/GtP8flTp8+Zd1VbOEMHRlHDhYdbRVyZXrfMxfn0bIvpkgg1WNI8Hrb0DwMAwM4phZEudy1k86K29Jk8++82Ds55w1HI3Aj6iG2tsH0EVikyhYALFLFw5spghDMd2FhD6Sti9DKkLIys+BAn4CuYRPMAgUMbgV93HjuKmyYLcXuo6wIzv4W2vmUVgaO6A2MwMBQpZOusby85cFfn5b/i0D2k79kby2RjX9uaj5OeSt6JwNaf1MVe0wJFhU44x7zoXcfBCfvv0vzblUVwFhgr153H9sCZR+8tpMELaCy/cQ3NXj6v4PlfP/4y+JYgHpQRweS1wfup3zoTvvK6I4V5ynbPkkP+wTL5IHtLGgBjYaQwMdplh1Gw/27jmn+7POgd1U24LmkuPXmKyFcl+LwljZXQ3wkAsxq//w0A7yWEjCGEHAwAhwPAVF98hASZj7kwj1Coz1PHIt6SpgZvXjtkzx0L1y2z5elOSMknZLOJJlSduCvNPAz11ukDn7aJWScBgM08CyM8i+oyER+cHTMPf/218HLFxkAHOuvor953Esz6nvhySaFeybFAk602G+q+F1veSRQW6M0uR0jH9C1W0MQKnTy6ruqQAMAF73wx/Pn/nQKH7TU+904HRVgYvfWE4m/968l8mE5Q4U7EiQ3FzFtP2I97i49LYMfBLV94Ffz+gyc7p3/NJ06Vvu9KuaSJrQtlAZK5dLkHkolrqYbCiOnKpkuG2XXxZmUJeQhwA7fz2FHwnpe2+n9KvkPWmV09tcoYN1p+o2pi2e0Tsk+hFOCVh+0Jn9C8QRUgo/R01K/22mmsIJ5g/aHvXRWmd/zpoy/l51VlRip/W3FKy49h1NPVxb0lzXdssxDnlaLgU8r5MSFkJiHkGQA4AwD+BwCAUvosAPwdAJ4DgNsB4HOU0hGPfAQDtx3NgljUF6GQba8/fHiSpUuaGQ+23SYfnJBP0V4z31g4hTGMMFY0eSaO2mcnAAA46YBdm8+yZYiudOXBRGFqekua7P31n3kF3Pe/r9HmZUxPF4wf0wN3/s+r4cqPpAUEGwWjLmwXZjurA133hXJWeZT1GvObr2zN09L9Gq6bqCgxAdhhdA+8+gh7N3CMZQOmG8mSvPwQd4pbLLIb8KwCKSKNl07cHZ7+7tnw6/edBCcftJvXsrAt8eIX7QLjx/SoEzqGqK9kN1+6cxZvPm4FvdaxMGLyS6ZZ1+uLSYBtH/O6T/E4+4m+9MzYtUL2jlcPbFwbm7AYCcK2ysGh+d0BKDxP2H9XPi1VWUiNUXfGwmikpsEcuK2iUT18hZH1PsYue1vDm8KIUvpBSulxlNLjKaVvo5SuZN79gFJ6KKX0SErpbb54CA25E3mq1n6LTAVzp0+xlztHdhLddYfRgpQtyG/FNrV1xCXLClytv9OmpSJyvI2pDpI+KbJSRVkYMQJJgnee9CJ46GtnwMuYjSFLatyobvjSWX6vihexbnBw08TJB+0GBzdcf3j0VfV1xN47wRlH7ZWqq/qtenKunLk4cp6Zn0j7hc0n6wog9bL0rfUA7E5DdT/RJDiwtnseShlkqXgsYe3LbsB5wb3ZIP0RaQtRHl5+yB5w3It2kabBQGiV7cp92HLXkwp6zbqkZZUJyIMeUXqWpl4MI74FFDIz+48WnAe9Nmxv19MJK5dlFS2p4NQOC2bbMP0bT4MfX0hMwC4WpNtaV5E7ZMJ46XsddnjBoUODWibMP2vFJGWDXtefJbekYZS82bKP2XdnNA8yjOoi3KDX9pf3cBTvknAwreftvwmPdtQFwrYjs8h2ahXlj7xiYtO9INxprQqQ17RsAjVbUAjnlyYFiXKRfeUq6DX3ljSC63dZDgip9/UDdk/fSsQWcfXHToH9dh0HpmBjCohg6s6FFYR06MuVkuxvvwuYixNG7TJNNwE2zCHzpuq+8QdmTKU3jTT3PKFhKvjrQhqnQlAZubktw7tPlCGmZTfg3Znv/OxrDoWZ54ndRiP8wUd/YK3tbOUnkfImN69rfohsrGX7pwxoCyMg8NFXTkTTdQ1f65tPq5dc/ETs2sKk05UjRUXUL5vQIqUoR58YVynluFl5tfW+Uw5w1neT9bJWS/52QpZTjnkaE5Z4ebqb32ruknb1x07hPtflsae7SxDDKE3J+w3HHYSoMCoQpi5J3Oe5dHLi573tWPivSfsDQBxAMti4GAGor5k0gen6k41hpIqrQjgbUx10t45aeNRRNLBlswuVLr/Z7n/E3jup8wieY099izp9cuHCiC7L1Ym9rIxMEYnVxodfPlGzFHNebb4TkzN9At1C0sdbCiNjNviWqgLu3J5055/d+T+vdlqe0k3Yw3qXUxhFlzRtnH7EBLjm4y9zTlenP2HH9mUfPBneedKLAMCBhZGAwewakeVN9V3JPHHeW4/JvzO9JU2Rds/xmVu/Mv9qIQCXHt+QrnVYGgaxIHXLaJSUz0/4v03hSypKKz15IRIIvHTi7pL8+gpW19/ictlS7ms4z3gK6KZLWoO3EU0eKRUrtnUPl3q6Cey7S/5WOmt5gvPM6lKaNkJUGBWInOYTzDeSZZzudwJs65F37aYNEgub5m9uGvmJJdYazdXtAiILI0xXx/LAkipkohbFMFJkQwey1GCF59oqS+crCGCOD8v8GIwd1Q2LLnozfOFMPRfEbouVzsStLKuklaZP5c3XIi/Ohe4FCtwYRsjDiMe/cSZ8+vRDJdTF4PGZVdBiqldWj2WYgmc3/VFhpI/ddhgFrzhsz8LKs5kGx47qhr12ritHbJX/KZc05nn2sMnMFZYPnRhb6YDBcnNWl0uLyfohnxfCBMuXyHXMaXmieZ7I586kP77ysFYogFacSnw5UjQIldFWsjK1lM7JoWAJB/FjetLCgbkFdj4frw4Sl7SahktaFiLFkG7/Gd3dBZ8+/VA4Yu+0e6Fvq2bfQbVDRlQYFQiu5lIy3q7/zCu8++NHiMGrelWtT9xzR1h00Zvd8uE4PyHiwNQA5oqjls8znweUlh4dsClNWwcm67qtmbrqu3TIy9OyAqgqhR24MTNMiXlehP/3bPF1uK7A/wQ9jVEt9bshTCcK41QWf8Jpds3ZZ5excNAeaZfQ7MmeqE+igrq6nuAKgCrodQfLlGhk+5lJn/6fs46A585Pu/7pCPQm1ki2+8Jk05WllV2TdcMOSF3SfFgYSawFTBCK5btfl7SsFZlmfmS6dNgBtUzALavBKxtIWWZNY6QvMsiDga2ngGZpAJC36LemmjMKyFP+0MsPQtFSjVPsQXR3Y0EfbvjfmYwVIpAJdBUxPV0ERvd0wQdOTdeBbuy3PB/pv/fZeSy8++T91fm0SqkmosKoQMhuseBBdpuIkXubI4GnU6BjzSOCKtAnhgdVkT959/Fw1D47KcvixVVhafNipSj5S+Wv/zvMsVOtK6kwBHHlsguVfZA7dRqxS5qKeJK/QJe0wlau6iyRmID1ItjE9tLtW2y/zsYwSuXR7E46X8Cd9zI/9to5bwrOIunvqFvSLPtREXGSsoguaX6gO0/2dBPYYXQxwcVddTNRfzWNb9Oiq1+mCrJ5hgLlHkaZQtvCSPVeg5mdPQSo333H0XDsfukAvxT4MhcAfo4uwpKXhUhezLtM6hdUxF7EpAit9bJpYaSfRweouVFE12i/mEei605uR6tp3pIGIHNJ06OTrLn5ywLcrsWPf/NM2H+31oFZJx8GRYVRgch1NErhxAN2QeeXTRcYTW9zYkOX2HlwbW54z1dPz/n56yA9+fF5O/PoveH2L78aegR+N9hPSsqytTAaaqwi2VN3lL4IufjyXNJec6TpNeDqDxa6fSny+hICMeVhNuKvsnAJ6ZSFM/ud9/3va+DyD03C5RXQYJE6deb8TIYRS6NGKSfmiR5krgq6GCWaeyz4CBlRYdR5aFpXWO5ye1Iuafz4ZQDpdfiUibsrB4oPCyMZZPFIjDbEBtXqatTN+M7ZcNF/HGfMBw9Pfvt1MPmLp6We2SoFscB4JlAK0gpsrj9M33HNb9L/eXRtDtmK9MBgR7NP2MRHVStX8894Y7unYWGU7DeNLIyEz3UtgURzT2bfoclj9N4RIyqMCgRvAL72qL3hI6+YqE/LYDPeTBs1Rihw/Xp1aQDA3z91KnzrTUcbnYSO7ukynsCSibJp7QAtCyKZD7pewD9WmGjQb/w9mvGvJkBQE3d+jIhOY/MWRl94rV5cGx3YxhpTfjpG4YssU0WKreKTDtwVSZVDxzinGHvtxA+iWiayPBy8547wumP2FqZn+wrmtIvnhsb+5tHwEVy/Bc68R0Rv6hjVjRPecKXpQZXfR1VlN+A6QYUj6rBRvLBxVYqCiSUBD6K+kq+PVrq/f/rlSrrN+DK8MjW6JzruHi1X2au8KlyDVlcXEVos+ETqgEfCsKtNbN7NSYyWhauAD5JNH87GQumSpkijigvKohmKgcrzZsvXBe4Ke9Fz1VgRr/ksmkGvLW5Jc6lkBsjXi++lWEi+A0SAqDAqEKL+9NYT9rWmpRUDJdoYCaGy52EntUs/eLKaHiFwyITx8IlXH2LEz+ieLvOJNOEh8yUiAaDlsmZWXtbIgLU6IARpYYQsy++GOQ9VYGkRbIJeZ8ep6JN51lbZ3yJ8+awj4MDdd1An5MClNV5C6axj9obRNhGqPQD7mTKhSyqYC6wM8i5p7Okwtd5EmNySxr577BuvhUve/xIAEFsYYeYSlIAtSVPGpjUb9FonqHCEPQ7Zc7w6UQa2/aTp0m9HRnhLWnZN09ncA8jHmq+4TtnNn82cpH1dvOMh11K46fGx6w6j4D2TDkCmpsA7ZAPQU9TpQOgCpyiuZeGaT8jjwUQmK8QlzbPlWlI9vmVSr3XF+eCW1NF6mSiMWhZGesWMHSXezxi7zTqik6CKFs9FISzJvM0h6sgnH7Q7PP+DN6Lp8LTjOO1zHAkq8KroV+87Cf79+Vfmnk/YydzVDIvRGaWLEbKCp2LCNp1wc8KjpvKCTaezDjU35cgyTE7CTBfrot1ACRCtsrq7CBy1z07qhNyy3CCgg0krXPKBl8ArD9sDxvZ0N5+1+qa4ttKBb1u/WxZGnDxgr/g3GebNMU4p7LvLOBg7uv6tWXdYWfwlEz5kY7aUGEYZi6roklYsXFW3nnKk/q/tfJXqK6mxnz0p1/vIrKUDQP1QS9dVG1suBdqsk5dO3A3u/erpWuVkobv57CJEugjpTgum7TvjO2fDj959PCptUS5pqTI4h4Ktv9UMsN11+9CIMJ1sPfqDwIU7afMUj0qO1FDRcHrY1ZTxfLukmVuhm8yXvO86dMKOAABw9rH7AEDL0giLMT3dYgsjfRa5yF604bpVhFZcHWBiVEy0wIg6JP1JdEIrJpUmpjNu22WD5h2NKj5qn52aV0GLFrYT9t8Fnl62WUTCGNlrM7XQXIzrWLWlHwAA+gb5i35zItdgOq0UaimcapQ2r96sk+S7wQl50EDIJwpY0pi6wdDifUv2kauFjXcDlmuz9BCU3FgeXnPkXvCaI/fSzsvWGDfodUPaY0nZBtOXgcdx0mcS64iRBnNJgPvRQpc0s/LydMwtjGy75EdfORGufGRR6lnWSkRkNRKRh6iq9ILGllDfhhYoWXSlYhgB9zcAZ95WfDLP1e31x+4Dr29s7rDQWbOSdjhqn53hkAnjCz2dd60UKOJwhwKIGfdUdykZLVOIrMhkLWf71db+YWFe2R5kzKgQbRNk2kZ87uxlQuj1THNhQsmIQmWMnCuu3Mh5+KLdxsHs898AYxvtqSvvje7pEiqvzF3SsnTiWuwLIY7itkXOKsglLYcxUCLq4G6cBJX4t0+9HKafexY6PRbpOEBm9JIJ9IU1WwEAYMHabfxrURu0zS2M0n+nBAifShlNPZfJuBONL1drE7sJ4QVJf+OLxUI/y1tdDjGbWXQtjbCKpyP2xruPhKjMtmlikvmXC4GFUeumsTSNw/YaD2NHdWsp/rjjXZBW1qe7mjEM6n8PjSQB7kUuaXxif/9UKyaLK6WSL/DqORf0WqAwi/ADm3XQuMzGv7ZzFMvFDqNb1ohZCwLdddjVWoS21IXW3JTl3ehQwsTCyCE6wULAxNKEredtA4nCKN9YMrlD9Mpb3KMClAYJ599889Hw+mP3hrOOFsc1zMKEO77M7uY7sXsdAgTGje5ulqtrFTimpwsdrBoL1y5pEWJEhVGBcNmRdbT7zTxxHBkBU21jR3XDHha3oYkwOjPB+txQtyyE0s/v/sqrxXmY328+rh6L6+WH1gOSGt2gkJzy0fTfMhSxQIjGlzKYYNNNAFcX13ziZfDYN16berb3zmPgkg+o42UBZM3P07ypWPjyWUegymAKswKbPeS5yUSQGWpY3jQDwUtIpKyKGPEnubI2Wz7hpHUJ7sap8agZw6AxIJoKI00Lo1MO3h1etOs4O0abZfjtPAfunuczpzAKuQO3IVzN+VoXPDiyQEno7LfLWPj06Yc2n6vclVS8djnjD1cnrIWRSfyWb7/lmDQ9Xc6JWyUPaU2s3pBrY175yvyasZ6Y31krtJ0Rlqpslt6BYWE6XfekFCyaMZmLJ+6Bj8WoqmvRa14ffdGu4+DSD06CcYzy17Z8Hmxc0pTfy0nQvCRH0ji6bS6zMHLlZmxLR902GXmsg5b+qDAqEE77Vc5aCT+ZhHSbQWiQbbhzaTHxOSxbfXR3lzGFpJWx+ZOJNiuMH7bXTilLJxFecdiesOiiNzctVdjFBCvgm9QXNsdDXzsDnT9vDWg2ZvBxler/ju7uyrmnatUJUYuTKp4+iQzQjuVKr00zJ9UBLMYmLGzYNggAAJv6Bhs0xFTSLmn5911NpZN5ZfD7uJ6SByAf9HKo6ZLGnx9wPLux/PCF4/bfJfcsG+Q6Br3WB2+ewoomotq+4bOvMGUHUWbmNMOYTh2ffs2hMHZUa5Npffta4ZMlZcpsKMg1cn/sVQenqWlbGOmlV8E06LUOKNCiPdLSgbUzhZx19F7w43cfz4+Tx4kvJKIL4D7oNbY/JHMvq8RHrToVm7Jt9m0mn8p3U0v/fXjDenxHpLJsTE+3RO7AcTlxjx3g1i+e1vzbNvZbBB5RYVQg3FoY6VkPRIjx9Tcc1fpDqYnXJG7Z5D3drVsFCCGGpvi4d62NKSedMH/+TUKHPRHRVVrpgK0fGQ5o3AZmMlaEt6Qp8mE/R8eiCnvCaNL1Fl30Zvjmm47G0ceeRKOU2e25yG9NTmQln8cKPDXO7+yYcOZ6ovE8eZZ1QRluWBiZ3JLWGrdyPgHkPd63gDi6Oy8ME0Lgnq+eDv/9sgPrPGQ+tF37cygQNflLDtxNnMdRma5ErSw/Kpc0ZQyjgjdKlLbGt5V1SUJP8PxVh+3Jfe7astA2qPlV/++U1EaWh4l77GhG3AJsLbF9JLEQ+69JB8AtXzgNvnjm4al8TZdoZm476+i9mnmzMLEo58kGuu2qG9QdA99Wq5j1IZsCF8PIlJ88MLL4Rf9xPFzziZc1ZWsVZAfPWIXY/rvtAMfst7PwvW3TmcR76hREhVGByHY03QmWTZ6PF5OndVnm2vfWCUoEi8+85lDpe9EEUdS8YR4MLjn1w1r3JOXl0+vw8IFTD4KD9tgB3nnSi/CZBGXjTor8t4TpmGm5pKFzGJbE5M4on3xVD1a5pzPNUepHALSBTf1hsrJ7Ld6NaU1FrjkbWpCNp8T1KuFZ5JKWfIZs04v5rsRt7bgX5a18eDR5sLUYEN2AduiE8U3LqmhhpA+bGnPmkqZBpmlLYxvDCDkx635iy527GAmvHsMoPR9Y0RPw/dkz+PJZF3G7tiVyElYuf/Nx+6bc6k4/YoJ0I3vLF16VsigDSMsV2MD+Ns3LTlODSSA6ADhmv53hK69Lu6S31p/6v3uOHwNfYw9XM5DxJfo0nUDRIvzyvSfBvV89HUZzbicV8qOgudsO5pdK+DKqtRljKtdDUbwiFcaN7oZXHLonej62usSngbIU52ODDNxeLGINFIicm4uNyy8iPsmJB+7KLT9aI4nB1irfJFNvMnIxd9meVvN44PUBUQwjXR4O2H0HeOD/zoB9dmnF/sDWgyrZpR/Mx/IhmX9VyG4g8bED9IF2SdNKz9+c1/OTpsDrewuL7RMqAZwCTX33r953ElOGf6iFS3suTCgk/VQ3lgkWWpvlZG4QuKSJLIyyRbDCHMYy8NVH7AkPfe0MeOsJ+4l5k3KOw/gxPXDwnvzTf1YZllVcJZYV3YKg3xF4aE2xJejnWhZGblzSVBZG+XEfFiilOZnSh2gpmu8wG8OTMjKwtBzNCj7pwF1zbnU8ZK2Hi77FiS2Orcu+Af5tuVkk9TyGiT9DQd1/WQiDXqM4kGPsqG44ZMJ4bUWpqBW+//Zj4SuvO9KeMcewsdTeeewoePLbr9PKx5vvTNzYWbhQGGWRbXZfMYzu+p/T4bIPnpyrqdDmZZ+IUk6ByA5KF2a8CXiUoi+nKxDOL92cLrlApkec4LPvWrcxyUvqQfqKk8zv/5q0v5QuADtZ88fGGZlrywGK6ud+taxUS8kj5iWt8LSlJodufCYssqewvlFE/zEpIlkeZK6iLHbbYbQmT/rCXzL2RzJBr0cJg16nn2fnhOwzDgWluXuPQFmlg1nfe73wlsBkujt0wo5w8xdelXo3QhOFkTULERowinXHPQjRyV9PbX3gprC2SFAF+U33UgcZRBRsquHaT5wq3SizcBU0XATuplzw22m5TAWKLIx4yFoYNagJ05vsZ0xuVsPA5lDl/S87SOg6xcomNu1ldIDEO+TVyL/7jnrywaET6vGJjtlXbDXX5APJiOhgicVBiuDlwyPpisgq0nzNmwfsvgOcfaz4tuJOQBRzCkRW8+nSaoGn3RdpQn0G9as60qcx+LQ+Ye2XjLXuaaTjaejZZz9/z4koetledtF/HA9zvv8GABCbd+Y2mIiP13W9chnDSEVKd8y5uBGvKAtCVXUf2zDPD3228TnObYSXrEuaip/vvPUY/gvQO9WWJRXdkpYVBJONQHYuSVsYqRVhsncnHbgr/PHDk2DnsT3iRAb4xGkHw2dfI769ikXrO8Pf3IcGm3mhzOrG7Iu/fNbhwnfN24cy35C/mj6TT/HNRcfNIoTkYprZQDdOYBdRf/HYUd0aG2VHCkFUKZzniOajYDtu8H2kZeGKO1gwkqsEtEzAls/S413IoFpzRIqsvXceq+QDFZ/I4HsxSlnjvQIn3ysO2wNu//Jp8P5TD2qlE+VHzj0Y659z3yyWYwDUiknd24Hz+XXTd87aHxVGBSJ/q4D51J+bPDikckKsqxOyNsbXXl/30d5l3CjrWD719OaTybwL3linYZi/qUhBT+aJIMv7bv4pFfbzugiBri4CY0d1w9RvnQmPf+NMXMYcH5xnBQjKRcUwsj15kik8RUor49rjCIxsCV3NbxftBPIllzE3FbHem/TRrNJFRWPHMWLFiY4FgOwkPFEYJZY1JzWCDL/skD34tCTKLsz8JBMwd99hNJx59N7OBbaj9tlZGquDRSK8xhhGbhCybIJxSfvZf54AAABfPusIYRpRv89S1Zc19NKb4BOnHQyvOLQ11kUxjFzyYusGgy/HLb2i6WOgo9jmHVi0XBDzY8BoP+NwvIvGpcgNSnZbl4ytEw7YVZMzN3DokIICAQJH7bMzSnJBh5zAHAAr3g/V0pZxrl3SVDCJs9ouiAqjApHtyCMOpSOuhVEn9WRHeM9LD4BFF705ZZIq8gE3uelAB1mzWEL06GVv7mHBW1yxri9YoYMI/thrp7Gwq6b7DJdm8syyn2PaUbThVlqncJ5d98lT4f7/fU2GfiO9obUFW15u45HhIncyqCYrKEvOUFIORtCxOXW1RREnREYnis28RVsOiN9lN4ivPGxPePo7Z8PpR/ADlctueCOcZ6LyZChzo/fZ1xwGx+63M7zhxfv6ZSLCGvw4HfjO08wvmc+sYubklC7ZjUn5At0333Q0vOm4el8nwCrR+Hjoa2dYlylqItdWfQk1by5pJP1v/beePGkLk810F2fO5kGmMBI11f+93l2sIFbOYIsbY+Di7t/KzPwAyQe4B7Ec+U3UjtivwfQ/1bAeyrhSZmvFdl7oifEIhXBryx0hha2pnAyH75WPv5DbKCbluiu2rVG+eFaH6YYRsyFLl1P/lzfhsk+6BAJPWdC1pDLp/0meH7/reNh/93HStCxaJ3KtZ6dyrDGa5t+Sb8Bdq5o/DVTxZgrVde8JL0fvuxMs2dBnV5hHqISY8lzSMhZGBQ01mVI2sTBihdddJDfKZOcHnkuaLi9ZqNrPp/A/cc8dYfIXT4P+IVwA2YgwFB8mUClH6mnwfTqbUuWSFgIIISnFR0uBzK8V7HXbMojGNwG38gfhLdYeYLuhtVEc6BSdlCKas7OkZCGReCyffcze8Mam8hF3MIBxD86Cb2EkL89KOeNAKcKDTwsjWf2jLMeQHyTr+9jPy8YwypeRpatXcTwXRhbZLwhgC1QYoiqtRLjw+05wICdQGMm0bkHrYaXBc5kQvdelZ4pkk2bqDofNJrsljSXCm/R5QQJFllk24AmIPuKH7L9bejwlMVvOOmZveMWhezafI7zKtcq1t5bCCzu2taYS1pN+9InTDpGmK3s+KmIDa1JCNuh1UZC1a9MlTSG9tjYb6eddkg2HLi9MKkQaPFxUdycJkc6gmAfOPmZvK/J8d2aN/I1/bU/6RX1DeVKOZLY46wiidjt2VCL3qeMx5utAFXsra9HWtJd/aJI8McLqOZVc95YyTWuVUQrLD7Z0lvYYg+vQMcoZV/0kcWNVAbNfdOoK2vg3FfJAkVZJ04EybTjTONlqsVUi9wgu8BChbPm1SESFUYlwpTCSncBE2IMIfg/X5LdM1NPbt0K34QTYskyQ5GfeydKnLYzS77/5pqPg5s+nbw+SFIOCztDgmXrr0M7mu/pjp8B7X3pAOk/jX12TblOeeDT0984iQduV8k6DFSTyp0F6VLLtBgDwv2eL44kAAOykCJrsYgyb1LkooLIOrT3Hj4GTD9oN/mtSvl5E4OqLGw8TXrA34khvScvQ5OdHFRPRAdAV5F3D1YHb/2/vzOP0KOr8/6nnmftMZiaTTDKTzCSTZJLJPbnvhCQkhMvEcJ+CkRhu5FAEorIruurP3UURd1mPxQvFgwVBxFU8FkFOUUEBjdyHnOHKWb8/nq5+uvup7q7qru7neWa+79crr3nSR1V1d3XVt7/1PcR44i2mwMJId66J0SYdnBaPdtDrcFEoMv4KlmQUxUl9AIrnrqs0N4mo+7CZo7E2RAEr5mJZezkK77/u94zuQkjo++9TfU1FoUsaY8H3PunEQM66m2v9LXTTQr44LsYpc4oqNQvM4GP2FbikuduXjRnEKKyfFVrSx6qurCCFURHRnWSdL4ZKKuGCDw1ySguF+aqHComSRjQK0V1qc+1XHdCCYhi5gl5ngF98aCVuP285AGDr8gmY7JOS2t0SdYZbmU1qPf7nsnJMW2AsmziicGITq226FkPu033Jx6vJbxNp0k/3WOgExbtnCA7Y6GpbzPvmPdsvLXRYexgD5nYPBwDbRD0qV22eUbDtzNX+GYvuOH+FNB19l8PtsK0xWrwtIJ7gqRLXKoz2xmrcuG0xWhuqoxfiQAR3Vh36gtwWleITKboqBKH7BKLc76EkNCZJ0LMqdiY6P0WP+xiFcnwUEwULGT4hBYqNa46y5unRw3LjpSllS6Xjoy2t6867HKbnkqZaU3drPQBgdtewWK3L2H1PvRQhf3LOXX3X+z7qisNh1vxewhILuC2M8sdGsTCKc5NN9VelECbe+TVi7YHKM1cMI/mRqmOz0nEhh+wNcUl770CnUlv8CLNk81KuLtZRoBhGRSSOhVFzbSUu2dCHq2591PcYX9Nn0hcpIb1/jm1hA5dvGZrYLmkR3ZtUzxLHSWMYuSZ3hu62+khtUWXH4f2Y0dmMJb3ueD9x3Qpy6MeKsBU6mrKH/ipx/oTaqix2XrVRrwCNur27TbhbyjK2hY03nAO97Y2xrjUqve0N0u0HDuSULS/u2o32xvBUun7YSp8I54r5wbtiplOW3W91Kg44OGMrjNQmERXrqKAPNKUgmUotIUqFnFtvKy5YqxfwNu7KsXQ61yjSmIWRolxWuJKt1tjErSMcru4Lx7fiSycMYFWfPOh9VGoqs9i7f5+rPmlbDNYp5t5qiUWKSXw9AgIuZmbXMPz8QyvR3VqHf/3ZYzHqtpSeKi5XkkUy5+/CWDH+hC1CSuv3/F8W9sB1vFYMo2DivEGycyeNbEBVRQZ/eOaNgn2qY1CsrNohVxTkVaDkCqfYDhPzudezw9k8EzJkZYT+MlSgO1NE4rqkhfn0Fwrrub+kMNLDL5OFikuaCbIRTYxES8M+7O3jHYKgX1mATpY0+X1ToaG6Aict6lYTklP4YhTCiG5V9qp0yEtnl69yuQHHMBb+fvudrjsuhD0b1WsvRQ5wjlvOXoY7L1wZuxwAkfqoLOhoVEQR3ZJYdwXHSrfltgr32KjWlbKA+UHdIyjTY77MdFRGwZYlpLZSpaG6At98/0Jp3MUgorpmm4aD4+rjZuOSDX2xy3H9P8QlTTc4/4hGM1aFBfV46ls/bZRxJYvTsji1p25VVF9dgR+fvSzUlTkqzjFN59p62urjWwVbp6t8e8isnp14FbgHAuYEqbwZ2gI3Ydmr/Kof2VS44MMQLEcpxXn2Pbfw5NvPW4Edh/Xb/293tEk5bIHCMaKsb75/gVqhCmXJFgH9jg0tM16TAIQHvY5LmCVbwVxfGtNSKpDCqIhE9WgqTJOt+gFPhOGypAk5dt8BjmPnj8WwgCxBJhDW2borh/kPKbUVOjFOyi2M8tuKKbinFfTaS9SPd11hQOX4AnnEscF5ureosBVsXcIslPLCabx6TLFsYlv4QRYHOMeIxmqMa9WzpPMSycLH0QYgPBtdYP0aish8+f4H57OkqZXlfV+0g16rHGP49S9U/tDMWQqoKA+TxKngPHTGaCyfWGhVo9YX5e9QQfQ2T2E6Fla/vngV7jh/hfLxOtiu64pyRRRqqxwKo5Qeu7OaqaObjCnB/Fy1C+tP/kJVlPQCmeLD5VLsVRglnL0tLLaMUz52lveJI6dptyfOtfjJO842feP0vEJH9bnrtGmUR0kWVkfQXiVFleI1BMnPPZbXQphicG9QOj4DVCqEexmq0J0pIvGzbfhbhOT2+9RLMYwi47yn+/ZzfHLTdDx4+Tql46OSz0ykd56ufB0YwyhCubo+6lHxrniGESWrgl88GdPWM3GFxlz71IKnFiqedesKEULsFSr5PUpbGXDtiQP43wvyH1E3n+UfqN2UTJLvN/oX4j03XqZfqwylYyXbhDJZjEWhFnPW8QHKrnxsjIC2KNw3Ux9a/u1Ix/V4qBMml8ReqJDNaxplmnrE+Vg5brwfhEEZBoPgPJflM6lgumn0dWeg4kDFlIG2/Gj7EqssMc7mnkNYf4w6HkdxSTOFHcMo5jcA57zgOnQSKwAB757P5rAPeb/n0VSj/x7EuTsqip3Rw2q1F5pjWT1JrsipgA5yGXRej1/5R0mSjUjbF9DJrzt5Hq47eS6aauWRcoTlT2GWNLMyeJhivmBh1GjtpU1iCiPG2HcYYw9a/3Yyxh60tnczxt5x7PtSUm0odXTN+ie2N+KouZ24+rjZAMI7KrmkmcHPamN/SlnSdDMT2XUHKICk8fOY+zzZPr/94W3RPkWZdCyMhEuapoWRfX5oBbnjY38TsdBgyaZuV5gFk2rQ67SGo7qqCowfkY9ZNMH6LXfZNNMqv1I+unEKjg4RsFWULso4xv5vb12I05f2+B8aUL5Y5I2aJc3Za8S7dIBzXHP8HCyfFM1iI/QYbVdLveOJdMiGWBhM6WiKXPbsscNCj/EqwOULKyoKToiCXNu9r5S3rLB5jimOt3HJywnJ1VHjCFSc9Ps4s2tYrh7P9qQsY11WlimPNaJunbTxTNJejkIFblIukILQoNdO16kwixrGpPdeWObEmf/9T9VTkBWWq94mPxm90mcMDZLpXfX6HKcaaDroEbbUV+GgKf5hVoTCMGmXNMKfxIJec86PFr8ZY58F8Lpj9xOc81lJ1V0u6E5I2QzDp9870/5/2GRTKKqTJKxD2P1VCXptAqHx1jWTtQU75eNzR8oH9fzGaMFHk+t7+etUXIGNUMcBHyVMuJWNz3KyT5uCStNXVmkOEJqEjj/W/rix2pJG1jxjbfb5uBSZ775z71NY0NOCu//2SuGpnrTGBeljdSzjHNsWjm/FwvGt0uNzxxaWK+6Hqrn21I4m/Om5NwpKcscwstqIXHa8O//ykqQt4UwY0WAHKNfl6Lld2DRnjKs9hWgoAYhYBH0UBfX3h3esCw2K68fNZy0NjKc0ztqnrPwPwW9KCHMZLhVPiSBLZFMkHXhahndBNWwO0LfIDT5Ptbg4yoyM5xqD6/GcA6/ySP0GhFmty+Yc73WGZYae39OCHzzwjHKbvHQOr8WvL16dqztyKep84ohp+MTNf0JTjdpnuDwOlNcowHo3fcq4/7K1eGnXbqz+7J1gAIbXVeLVt/dq1xuVOIu7lVmGd/YCmwfGuLaXuHg5qEh8CmK5HnwUgG8lXVe5EfejJOyD0O/lpPfLH5cljeT+OidJlaDXJoSqjMMUM8okrXpOcAyjwuN0MClcFpqExiu8qyX3QbCktxU3nblEfpDPS2PMEkUh1oyKGTlj6u933EeiOv7Ec6XKUVuZxe3nLY9ekCZRgzp7CVME3vXh1fjqqfPl59oCu0cotEq7+rg5yu3IWx9Ec696c/d+AFB2c/nG6Qvw7a0LC+JcuMfXHEHvkMq4UVuVxT2XrinYvmZKe+i57U3VWGApz0jwLC7LJDGBnAQtVDTWVIYqGfzGq2ljmn3dVu75yEG45exlufM941nUOS2fDMC7J9iVOG7AY9MkuQBZrWhhpNuGi9f7ByrPu+1aLmlhizyRXdLi3bdpY5ojn+t1uwsiP3fJ2xsne2euLfLffvhZxwg+uWm6baUa91VJIlGHt02HzRyNey5do5zUxoRI0lhTiWF1VQByz/fOi1bhnksPCjzHbbkVD3EP7vto4Xydr0NeSybD8IePHYwrj5zubl/MNsWlxIblREljzWIZgBc4585ckD2MsQcYY3cyxpb5ncgY28oYu5cxdu9LLxWuPpY7QVkFVFBd4c9vyP0hwVgPv/u8YVpHKvWLlVXd/iIG3kCrFZciyH/l0LUaFMUlTfsMfwpWYjVHMa8wcOribnz11Hm4/rQFmNE5TH4OwhU6MvKrycmpcZwlBwlhxoNeK57vpxjXqX/SqEZMGtmofoICQSu+hg2MfN+ZjuZaV4BXJ+K++fXvrpY69I0Kvid5V0p3e3R5891ciusmRYXR8PoqqRWT2x1DfKD5E+fjaotmTA2TDCEZ0hhnruoN3J9WNjwn7U01aKjOWQCojOVxmlgwPnt6UZhFYVp3xx7LZOOmoc+3Koc1iUnF1LaVE0KPsS2MEvJJ83NJU5Wrrj1xIHLdigbP1kGFMo/9k0e1NI9OmEtaTWUWk0c2BB4jYAjuV0Hz5Kc2T8dBfe3oHx1dcedti8p2pcUe8TdQyZqnqaYS7Y2FWeScqBo2fOmEOfj05hnB7bMa1trg777o1/bj5o9FQ3WFdr+j711zxFIYMcbuYIz9QfLvCMdhx8JtXfQcgLGc89kAzgfwTcaY1Pmcc/5lzvlczvncESOCV5/KEVPzkX+skngrAEMRVyr4EMVJTWW42bSJe54Pep3vMJ3Da0PPE+OqtH8EZMAIE1yUg16rHRYblUkySNjIZBhWTm4PvO7xbTlBJCjrk7RtijchHy8goCylO8pCJ8i8IjHeEwq7tqmjc8N6m49woDWRpzzrqwZxDCPOB5Q4M46lVhRrCNl78NZuS2EUIYCoE9nHUrCFkX/DdV2yZZjqVqVm/VGOhGVBi+uSFVtBbv3Nu3lGK9Cv34cFvU77A72YqFoYmcTrkmZqxvGW4xv0WrG8xppKjG4O/sj3Iz+XqFsYOd3YdK2C7LKk7lRy/N6rMJc0lbKDcLYx6Nusb1QTrjtlnrYLbNxurPO9qBVLLQS/BUkv66d1hMpNUcfw3+9YhwsPnizdl7ZCyLSHQzkRK4YR59zfrgwAY6wCwCYAtkqcc74bwG7r932MsScATAJwb5y2lCNpx/bQcUsYamRYQDrMECVSECY+JGyFkaO/XLS+D2d/6wGlunVTXsoEGueHXhTBNUmhT2XlOa6w/Y33L8DDz7xeEMOlI0RwU46rJIk143tsUH0aAp1XQNZFGnfA8fvCdZOxbuooIyb0SeDXbxqqK3DpIVOM1CG8VuMIsHGCXkd5tLLi37QURg2K8Ra8VGZZQcw3FUVYMUQxUv6UJmEKpcRRsIhTwS8ZQEHQa++CX8Dlf2rzdPz1pbdy5aYk3iX5NFwWRkEVKTYim2Ghbsa2QtB6MmHyeVQ5upjji3iFlIJe28c45F9nLMuUryPMwqhcUV5UVHixVcrSfWy67nk3bluEzdfcJd2nIquPGVa4GF6Vzfi+N/Q9mx5Ju6StAfAo5/xpsYExNoIxlrV+jwcwEcBfE25HSRJ3Ytd98Q+d0YGj53bhI4Y+hgYT0rg9RWiHDDEx62dJc/9VPT48hlEEhVEKQa+D3iensBHltWtrqMaqyYUxURhjOHa+/6qKrlImTvp1INdnvROo/0qePvd9dA02zRmDi9f3hfarimwGA+OG++4v9ne5nwBaXZEx9nGqYjkWRlC2OdX+4h83xxwuJwAALoRJREFURVZm4TahMGqsjqYw+tn5KwEAznAN+Q80f+K4IakskAQVf8mGPnz8iH61urRaRkSh2B+MXgujuHjL8X6Yea82dNEjxu3RsxaJOIho4IxHZUJ2uOP8Ffji8cEx37wxqpJSvDmfo0ICKqPIUqVHxTs2B4mnUmt9zQs2aWHHGALflyRiGMVFp0km+9IBl3wZXnCQq55Ks4bXV2HnVRtdmSvjyAGmn+Tufe7YtcWWY9MksSxpFsegMNj1cgAfZ4ztA7AfwBmc88IUMUOA2EGvNXtqTWUWn3pvsI/pUKV/TDMeeuo11zZpenlN4cXEWJKRuKSplKt2TOHqUdh5UQbIJAdVZ3puL9eftgAnXHd3oub8QbHPVT6Kc/vdsWaCUL0Sv75aYFKrcWtaG6rxuaNmAQAeff4N9RMtvnTCQKTzkiANiwUTgmehCXT8MnSP7Wmrz/0dUY+PbpwSmGVNhng35S5pem1RRclaL6DuM1bk4p08/uKb1sHR20LEJ65FQ9y3Pd93o8Wz8+LtToWuS+4KVK8/yop7hjGXBXNg+bblY3Ljp9Pdx0Q1PW319hjmhze+T2iWtIg9qph6T51nJovb6LxH3vlT1n/+86S52m3M1+8mTZfM4fVVxsv0+15Tz+6rYmEUXpZuvzWpO9P5Zt22YgK2/vd9AIKfvan2ffyIfjQqWFC/u2e/6//D66rw9p53ivpep0WiCiPO+SmSbTcCuDHJessF7wD74Q19+K/f/A0vvKGWHngI9M/U+Nqp8/Do87ukfsmuMU7zppsQdoR19gHOtarXFegCs6Q5fossC2FIgyUmgKhHJuBNsoIg+q3qmSBI0FadIHVizYS5pPk1p8DySLN/eAMsR/lgWD9tFNZPG6V9XvkT/Q3QiTvhxc6+p3GOTKA8Y8UELJ7Qitljh2Ned4t2Ow5I2hGk6BWMlpinqxJ17E1aIUdEo9guaXFdeAvL8ZoYeQ/0nhd8/XEscUqtz6vGh0mkDdZzSNslTWc+jtoFMwGyUkEdHsUgR17+5JwXKDD3S1bO1kwd6Vu+ay5QuHYdC8O4/WJedwsuWj8Zn77tz/EKUkC1rTILLr9z93kOjjNmOft5XJc3HZlxdV/eoj/o0ZsS5xdPaENve3jQ9Hf2uhVGXz9tPu564uXAQN6DhTSypBE+eF/iD6yYgLs/EhgWygUJqeYYVifP6lMKOF3SdAZHXZc0IZAHmQ9fc/wcqY9xeFuS66yi6CCXPdXUpVEIEr7yApZaWbEDUTvPDylKt6Yfbl8Sfn6cyMxBhygUU4pBYeOm4AYkQpbTSiesfs+BKkqnBT2FCqFshmH22OGh54a1w3UtIR/gXzl1HjbPGRO5Tr8P/M8fPStymUTxSDtmihfvWC5rjdIHlc9b651HvGUlOb5FsTxJEqfCSNcVPyp5+7FcfaYXlkT5xZymdJSe0n7u+I/3Ovbt9y/UxL00adGmImetnFQYgiBenfHQckkz2BCTr59O33eOdyrfDzM7o8fK1MGrMBrdXIsTFo5Lpe5iQwqjQcBQitKeJnLFiW4Z8Z+NUHa4XNI0BNOw4MTeMoPK1glg7Lz2EY3Jad+FICGb2MRKS5LxLwIncsVqdRQL3kO8K0Bh83vB+YoCgTcroLetSYj1rZZp+Nxx4VYtPzl3WaQ6EnVXjGDh48XOUhOl/gOifrFKHMx3ti7EJRv6ItQUjG3pJNFn+n2ArgrJXBiVI2ePwQVrJ/nuj+KySYGykyeuhVHcZ5R3x0lGgVEQ9NqzP3CVnct/KxPh1iTZ451Br1NTGHliGCVVbZKufKp162Qc8y3L0yG1Q2xo3gbT83RYaWknJQpDttizZEKb9NjutnpcvF4+j+t2v1mdw/Ln6p0aq27l8dq6L6v65Ao+1SpVq1s5uR3zI1hZDwZIYVTGkKIofYpxx6O6pOmaj4r+FBT0OsocOmZYLT6wfLz+iYqI1someCFsul3SzAoCaQm0AlX9VOjjj92Zk38bulrqcMf5y/HhQ8KVGL3tjaHHyPAGQzX5NPdLFCW6FGRLcu0LPveAhiISyMUoMvEx4d8O56qh9SOh10c7VoNPQ6J9gNPcbJpiWxB6A8dHfcR+bkGi/wllidfDJ0mXPJ2ig94HU1OrqoWRyTtSuACSzMBkQmEUObOpVXdWoQmiCpmMCBReh9cNyl2vZJsrfmY4Ou9/2P2RtSfpQNdxH7t3vHj0E+uxdKJcYQQA8yWWwlEY21qHjTM6lI+XzbtLe3PtTEJZavdTn15k+qk2VFfghjMW2eP0UJrqSWFUxgyljlpMir3QkA96HU1Dr7pSIqxwAhVGEYbfw2eNTuQjVGBbGEkEFpnCyDRKLmmK983EO60q+JheLdItT/WDvre9EZUJ9p9xrcHBUONQ7LFjv21hlKNY7cnHw8hvC8r+FofO4ZbLrKZl1h4r+0lVgn2NCCaofxbbJU2lPykFnfU5RExf56/LWb/VVrktOpO8fh3lal5hllx7nO9gkCLCJF79tblseMGuhmkixl8VeUhqFep4B7zDpMrC2fyeFtvyRXYfPrhyAsa21AEA2hrcsTLTVhgnNVdGtXb33l6vxbcqUWoXc3XUvru4t9U63/wznGFZQE3vbDJeNuEm6SxpRASmjWnCgEK8CNIXJUtQLJ80yccwOpAfuBWeftARsskwGxTDyLO6WkrYMYwkjRPKnJrKvHRj+hKCyssHLA4pw9CNdVtwWL+9z9OnY8g2n7tmIj5/x2PKx+uQRiyMYrPf4xKmw5op7bjjkRft/8u6SLiFkRD6hXKmOPc875pXaGEk9lUrBroNQ2eIdt6Pt3bnYhM01lRGLo9IjkyG4ai5nfjVY/+IdH5sBbn1N/8exiux4H22/n/K4m47Q5+TsNX5eFaM6sfmV/STw6kcSMs1yBuMXLYAZYJiuqSJ8VdH+eJnCeS9DhWFUVU2g8qskGELmdfdgmUT2zBtTBNWTXa7GJlWmIbJ8s65wURIA797r+l5ZQytxeeYdckWjEyxdupI/OaS1ZFiqzoRC0aEP6QwKkFuPksxFgfz/CUSwRUjpgj1Zx0WRhVZ9Q+/jMOVTace2fHOlaVSwxt7YGxLHZ585W0AuXS621ZOwLHzxiZWf5BgqSwM2Mf7n+C3y+/xisPndbdg0+wxOGfNRE957gJlxZy7ZpKvwqiYgq+Tr5wyD0+9+naxmyHlgGSVVpUvHD8Hu97dV7Bdp6x9toWdaI9+O0wgc+PxKlM/dPBk1FVX4JpfPGGkTt1bvmt37l6rpNYl0ifLgE+/dyYA4FO3PZp6/fl5Jt5LlFfeuhFzut+4mmDehmhjeYLDf6XDZ2rv/rQ+5NzPRTZWLuhpwaPP78Lr7+yN/AFfTNdK0ccqdDqTrUhzb9ZRGDnPlck4zk0V2QwOmlKYXc3kfWusqcDLb+1xt9FzjPNybosYH1GGXwbAxpoKbJ7Tia/+307pft3FHr9XOsqid37tMZoFpZCRk5IZ4yqLgMJg1kQhZHtNED6UilWNGGT3c57/rfDlFxQMWoaYkGXXu2WgEwDQUl9VuLNEEB/nwqQZyE2OF6/vw9jW/DbTAluwS5qa201Q5h3vMUEwVvhxXpnN4HNHzypwvYo7d3vvI4eeQtFUDLZVfe04aVG3kbL8aK6txHlr/AMl+3HA4xIWxuSR+ThM1RVZtLlSteoPRAdshVHG9f+0Ee+IU2Cc3TUMANDelLvGxppK30CdcuR3Vdavbty2KPTYN3fvBZCLUUCUHtkiuwp6XZaCjlEpx8sXjpuDgXHDXcoSJ0kqGrQsjAImoowhpZozq2nQx6BJi++8xaP4W3gN3/nAIhw9rytWPSYeY1RLUSE3qsTDkskkzsU5b39UjeVor3Nr3geT/b9NIQW66MMzO5sjx0d0Iq7X60om+vf5aydhx+H9eOiKddLzj18wLnYbopLJa4wioRtL0SSqQ9E7e6IpjEpk3TQVSGFUxuSzYBFJIHdJS78d1ZY7FUOwFZCXvAm9WtDICtuSqfD47at68ZcrN6C5trJgXxhpKdxs95+QZ2R6lcPkN3jcpjEwW5j0K8pv3NCtuiIgcuZntsxULqcUrda8PHTFugILLRXyQa/V7u73P7jYd59UgA95amKcEO92WvFAvAglzMSRDfa2c9ZMwm3nLkPfqKixB4KvxXnPBxSy7L1pWXM1kIVRSeJ0Selpyym/xzkWAsKIPbZ6XJYil+djsbGufxRu3LbYd6wImrc4wuf7UxZ3hzVJibxLWuFZYk6Ikwhi51UbXXPLuNZ63H/Z2nxssoRQvQemLMxyZcUqSpt9+93zQRC2HOF0c3fs9xYhCwlgn+c4Ni/D+tcpw6TCqL66IvR55z1PzcqLzvAIADCsrgo7r9qIU5f0BJ7X294QuF+V/Dihf05UZH2pGHz+6FnS7S31VVoZoJ0U26AgTUhhVMYMJc1mMXGOB8XITHfq4h6csrgbW5ePd8QzUjhRM6hskIURY8zXlDak+tQQ7Q4TLIwrjIy4pCkoABXKcloYhR8b7z4EmbWbEm7KHd3vpvoA6xYVt0Uv3qDv3g+5tLwjutvqcf1pC3DVphn2tmyGxVAW+RO1W7/p45LWallV6mSKIaIxr2e47z6ngdGWgU7cuG0RNk5P75mYcssWMoRubJ64MYxWTB7hKc95ro6JkX99OhbQQQiFxpGzRgNIx7KZ5TWCAMzHThLFO++7eCZByjxdjp7rbwG1X2Lp6Yfcwij/22ulpPrMM5JFTxUFllbcpQhzgPdxJxV3p7oiWrBqP/wsYp3Ndn3DRLmeeAZGthxU5ESXWNWXj4vV6Lhv91+2NtJi+FCDltLKGNIXJUup3N/aqix2HN4PwLE6o+SSlvurKvfYCqOysPkoZL+in7RpzwYlwTLkmLxwpi7IhRUd9hEQt397hTyGdAKiJsnYljp8eIOOW1QwSbiA+QnwMsQ74Wc9mGEstaCyQSmAoxG/fzvHuq+cMh/fuPvvBQL9sLoqPLxjHeqrSFxKmssP7cfJi7rxb//7OP7noWdd+5zjOmNMyWrMSdzFHq+Luqw0VaW+Kp87aqZ9vGmXtNrKLN6y3DB0ig6yYDVlyTiyqQYAMDokNonJO2JbXlh//cbFuAstoh+PGVaLymwGO6/aGKs8L5967wzffQc880EQC8a34LEX38SwusIPaQ5eEIRaWC+FUSFZmPzn90xH5/AnsHziCJ+z9Bb6gqa03126RrEMPXfyMGQJWAJRrPjWc5Zh2ad/rt0enW4snrWOZ4MTrqGoNI+8zQ9/7GB0X3JL7NKHkuEGSUBFJG6shGKb9w0VnCbIqre8pjKDd/eaD9YoTLVVBLIgE3WZUijIJa0cEO4JS3vb8L+Pvuh7nOlsG0G3S/cdje+SpmNhlPsr0jcHuZjJCDpepQmlOHz98qJVRsuLE/TaSxS9jlhR9rMw6m1vwKPP74rdtmLQN0otroSqC8nSiW2+Si1v5jQiGaoqMpg4shH/fuzsAoVRMYMFA+YsjHTYNKfT/m368mscCqM4gXCd+I0zuizpbcN1J8/F8kl5BUJa84UYLpISg0zEeYp66j6NGEaXH9qPUxb32BaXObfH/Hnej3/d5CrO629vqrEXRf2Ik6nMmQhlRGMufpFob1VFRpohK4pFbxDie8C0hVFXS7hbrmuRKYIKrMJaZd2rqBT00tFca/2tKdj378fOtp9J4pTnp03JQAqjIvGVU+a54jlEoQS/twYVftlMVLj1nOV44MlXzTYITpPvcGWUbvvzpsKRmuZLWhZLE0c24u6PHIT2xmp8/OY/+R6nIizpEBz0OkfYHdC5Q0Hyi3Of32He5/GJI/rR01aPlZPafc6QU+kx1aK5uBDvu/Sri1bh7YjBFQU68quoX7gP7vOMG9efvgDX/OIJXPfrv8VqU9rcuG0RZnYOk+4Tt6cUFZKEPofNHI3/eejZoiuMBPkYRtHaE7SQE4Tq6rxqsc7gu1oWRgHlm4hhJJBlykqSvEIw1/aw56N6hd7jiplx1mtxGkRVRQa97Q148Y138xsdVutR5Sh7YVLzBmQ1F7Sc3HH+Ckz66K2ubUJJVG0pjLxykWmXtHetLFzKFkYGUb3VjTUV0sysIhD/vogZC4+Z14VRzdVYNblQxjxkekdqY3u5ek+UChTDKGVuO3cZrj9tAVb1taNzuHrAxiBIME6GOLe1p63etTqoi98AqrOCJ4pQdYuxTYWVjg5nakcuPsn0iMHkojCyqSZUkE81S5qiW6BKljTvsfb/XfWx8OeXj+YIIOdyc/7aSdoCYJDQSUNSDuFSIfpBV0sdJitaxniRfcCE3Wc7S1pWrgxua6jGysn+bgClysC4FnvV0w+xkjrTysbm2pdwB6X+bw5jKZljni4swmUuOvkqwiuJehlB4zPn4XV797qDSEewMJKcI55REsH15bEVzZXvdTlMylM3I3HJisut56ilfd/niWmngjh2REO1O4aR9Xvh+BactrQHJywcp1Werit0HMtwWfxNYS3jZ/FjWwcbGs13WwqqGsMWRn74ycF+t/E7Wxfip+etkO4Ti4NKng2SCjIZhtV9I6X7aK4sH8jCKGX6RjUBo8yURYqidHDOa0nc82++fwGO+4+77f9feeQ0LOiRx2fIaqzOiMFZmo1CKCgc12M69fbKye345YWrXCntSwHzQa/992lXZeCbqMkyIR/RFGzmG/c2lMqKfynzHycNYOmnfo5DppkLzqsjwO7TWFEeLIhxL8OAH25fYmfUcjKUMpuUO1NHN+GWh59Tcr1QYUFPC155a4/2eav72vHxI/rx3oHcQlDUN8qrmFDF+8E8sqkar769V+pOo8I1Jwzg63ftxOfveEwzhlEO2fyRd2vXb9NNZy7BPX97Rfs8U3gXd8IUGlGfvx1b0qC1w5QOteQBByIojFobqvGZLTOx3OOuK8qorcziskOnKpdXEVHONC1v7Nmfs/ip9knmIpOR45C3MEpHYaTLgvGtvvuE5WBUl7Qg0vyO1RlzLz90Kn79+D+Sa0wZQgqjMqYYGbuGFPbtdcQwSuCeL57gnoiDVmryWdLkAtk9lx5k/867Q6n6luf+mgyCW2rKIsD8BBWUTlYdM/e8taEKa6eOxGe3zMShM+VKiig11UqEHIqhFk7n8Do8cNlaNCWVgUPxGagK24NhTnFewSyJdRFRXmxbMQGrJrdj6uh4GfXEq/KdDyyKeD7DSYu6lepQOUZ3XcablHLR+FbUVmXxrXuecm1XLbalvgpHz+vC5+94TNPN1T8umxhnnJYId314tZJSa0bnMMzwcTNV4ei5Xbj/yVfx2ItvRi4DcAa9VjtOHaHIVnP9XzV5BC72ScDgPFVHjyJkFd0FBKEk3fXuXrt+1evwElXONK4wcrikATLLbXPxB4H8XHTUPP8sdlbFoYxTkKtN3q1K4dIe0SWtmEQVz9+3tAfvW9rju39YXSVe3LU7YqvKE1IYlTM+I0LfqMayDWRKBJO1YwTI97c35oPKsbzGSK3sjHziLGVUTbGdOFdq2w0E2xOuQl89dR6+/Mu/4v+eeNnepxrgUiVLWpjgcuiMDrxvSQ8YY9g84O8OqeP+BgA3n7VU+T6VU99Ji+GGUkLHubWqHwhtDcmnr06KyixTXgElXWf5kMmw2MoiID1XkDB0F3IEYZaxcVKJR1MUF54jLBGc1iMi4G1c6qokixaONojsYFEzH3nvn2/20UilF9YTNleu7mvPeSRIqHK441Z4NYkB7NcIei3DuUiUVxjp9WPGgmVYP0wnKxEuYnXVWas9cl9/U4soXS11xjLi3XTm0tBjJo2Uu75HuY15CyOF2KmaZSe18PjZLTPxxV88jlff3mtv4wC+efoCI9q0752xGL96/CXjQcxLGYphVMb4vWc/3L4ED12+Lt3GDBGK/aERZmHkZHVfLsDcmOH+AptzsK6I6FteTFRNsZ2IlartqybgB9uXxG5D/+hcjKaulrqCzIeq3SXIzN8+JuSxbB7oDI3r4kS1L08b04z2psLsFqaQXdcnjujH1cfNTqzOUuSUxd2B+0XfcsYeUe1fKquzS3vbytpqzDb1V7iElVbwzbQD6xLqtDWYzZxTGSNorozIr0rEE70fzCbtWk0FvU4yhtF1J8/Dh9ZNMl6uIO8qmGt7UnKQtx4/gu7hf58237b60bG8mdGZk1XmjhuufI4TZ02RLYUiZolTUXLpuJEJC6P6qty86lWGHNAoK22aFSyWa6uy6DZk4S9iGO0towzKmwc68bMLVhZsX9zbVuDVEYWxrXU4foFa3K7BAlkYlTF+41hNZbZk/WTLCXslkBduKxb5oNfhx75/2XhsmtOpLHgLYU8WIHAwIa5zw7QOjBkWf/XzI4dMwaY5YzBhRAM2zRmD2//0Qn6nZqa6KP1LV/Aqh0wRJ4a4fgTR1VKLp155x1xjUkBl5XHamGZ88fg5WDFJP0i1zip0KRAlzW5dVRa73t2nFBtj2phmY6u9RDL85pJVRi0W01CG6tSge22BQa8dY7pOuR1NNThh4Vgcv2AcNvzrr7TaI49hlBtnTGRJ89LVUoczV0/EZ27/i/GyAf0YRlH7pmqWtKB7OH5EA85bOwnfu+9pLfeyZRNH4HeXrjGSxty2MNK0FBJTka4rv8p1CiWbN4OrjD2WEF1fLRRG7vaId8p0zMtyRNz78nRJ49LfADCqqQbPO7MAEoGQwmgQEGQy+Z2tC+1MPYQepbjang96rZatQGeVVkwKgz1Ark6mORWqKjJ27IX10zqw86qNtlm8TOkoQ0XpE9YdVZ+auOwkBaFivjo3n7UMr7+9F8v/5efFa0RCHDI9WvDsCsPWFUly47ZFkQIcizhb71jBRYnyptRN/aO6qmh6itt4p+XcPJbfGObq5pe96Mojp2u1QwSR75e4CcpiGCWJ0SxptiIn13bvlDzTss6JXY/1N2zOVw26rZtuPo6yyBnmIJ85S0+JEDX20bjWfPKCVh83b6EEUrG03r03d2xDtdzCyHTQ6yS5/bzlaKoptDo6a/VEXPDdhzBSkgBFZ/yq0MiSVsp4F85+dbHZRYnBDimMyhghAAQNaEGR7wk1nONJsZVIcbKQOJGNkULw0HFrKkcyGkq3uHi7y4Zp8hSJeZc0//4l4hb4PR7dvllsOSip+ptrK5VMtgcDqo/cdPyHJBkYJ88QGcbSiW3Y+fKT0gDtBFFMTnMET81/dMcL+ttYXYE9BrMWff+Di/Hmu/tCj1vS24bbzl2GyZIYKbZbewl/WH73jEX40YPP4PrfPuna7s1e51XYeAPgKg+pnlvBFK2OVY050hzb7XsEbsfme1kz42DeMkmvj6yfNgo3fGARxrbU2XGHvAgLmCoFJdqiCa341589htV97bjpoWcLlCHF7sE6T9UvXtHmgc7AeJYyWuqrCrJICnfefQrjTamJGqLFn9w0Hc11brlQxRKNyEMKozKmxN7LQUcpuqRlElzBs13SBvkgKmQJXVeuuKi4wAT1rysO68eo5lqsiRl3Je3rDiNJF7lRkthLG6d3oF2y4jaYiRrktJSYNLIBf3nBPwPSFYf148SF3dhx0x+x8+W3U2xZIaUmNBPmkT1jmVWUd9zPf3Tr4VUYNdRUoNGyKhjZWIMXXo/nWjFnrH9cm63Lx2ORY/HRLxhz2hZGUZjX3YJ53S2FCiPP8wy7gsguaYrnq8YGMp09LAjnPRKWSv9wZIr6+BH9+P79z+DBp15znSf66ZhhtZGDZQPA/J7gxQThVqbigr1wfCse+6cNeNVH4SXk4OF1eokg7rxwJZ57/V0c8+Xfap1XKvzk3OV47nW3S7+4nypBr0sN0c3W98sXawl1SGFEED6UotCfjbg6o4JYnTEdHDSIH21fgoosw8Z/+7XRch+4bK3vR7IQWNKY+zKKq4kqstPw+ipc4pNmF9AIsG2bWht+zpyXVHykX120SprO/gvHzylCa5Ih6Amev3YSlvSGW5jO72nBxukduPDgyeYalgC3n7cCN/zuKXQMkwdgr8xmMHmUfKU1TZb2tuHEhUMrGOZg4azVvbjzLy/h90+/rnxOhuXda6orwz9UVbNkefEu5DRUV+L9y8ZjakcTlk1ssz/y/Nx1ovDT85bj6dfewSorSHwYpt2908TrKigWVoSi2s5AG3PaVM2cGnYPhcKlWCEEREbNNxxWaSct6sZJi7oLMtXN6hqGa46fg5WT2/HAU68CSCaouFBoVCrG4azMZnytTBaOb8GOw6Zik6aFzrjWepf7nC61VjbAM1ZOiFyGCn5j1YjG6gK3xXyWtPJ7rwWl+D1XbpDCiCBCcH4EF3vQ0Ql6rYu9OpOihdHMrmGJlBuUyjyTolCrrsTJtSVO/ypm3zx+wVhsXT4e2795v/a5ptLWeokSB2cwcfZBE5WOq67Ilo0S7ah5XaHHFFtpef3pC4paPxGdC9ZNxgXrJmulZq/MZuwU3dUKH6pRRzuvgr+hpgLZDMNyKwj+cQvGobGmEofPHG2s3okjGzHRx91Fhh0cN6bLfDHIK/KsLGnWJZy1eiJGNFZjoWVhJRR3qooasWghjmdWF6kKidHVVBP8eSbkF90YRqaorshi4fgWHDt/rNLxG6z4e1GDZatgK4w0lGh+yiXGGE5Z0iPdp8pBfWqKVidVFZlEEzJUV2Rx8fo+rJmi3jbbJU3hoRU7bIeXUrOoL2dIYVTG0GuQLF6fdiD5wfDhHesC92dNxTCSdB4xGaRpYVQMsjFMonXxCqGhx0cQ6+NmazHBP71HL3Cqk2J/4A8mNs7owC2/f67YzSgNBvcwRpQIVQ6FkYp8INxh42aqaqx2i+/ZDMORs8fEKjMu2Yy+MkBFyZYmYjYS8kFlltnKIgDYtnICdu87gBMXqVkRXnviAH788HPotoKFN9VU4oK1k2wFioyrNk3He0MsW8QCX2WKGTC91nHf3rpIuwy7jyQgf9lKNB2FUULy7l+u3JCqu6AO2zStl4RLmkoMI1WyGZaqJWJSC5NDCVIYDQLoNUiGYijKGyWZDpxUGA7Y7LxGe3VmsMcwStHCqMYKwFsVIhSbaInqhGhSTrtx22JpkGGanNPh+AXjcP+Tr9n//8Jxc7DjsN14a3d48FqCKAV+fPYyJVeuqHz3jEWJzmm6GQi3DHShvroCh0yLlvEQyClZlvS2RT4/KbKaFkbXn7YA3W2lYQkq4k+NsDLLCvHAqwSsq6rARw6ZolzuyKYanOqxVDkrwPpzYNxwHKNgtRNFORIX1Xm9tb4KKyzLNy+iuUkkHbGVaBJ5q29UIx59flfB9qQUbmEyXznRbbnYTRtjJlMgANx6zjLc/deXjZVHJA8pjAgiBNm8VqxMPHHcqX64fQmO/MJvcP7aSXh7T2HqaWEqXG+tXP5w+xLUV5VexqEn/vkQHH71r3FwxCB2aWRJE3EtzlzVixmdzThmXogAaKdJS6xJjqriu78JBsa5A6UKobvErJIHLZsHOnHBdx9ybZPFICCAUxZ3xw4YT5hnqiQ9u0nmdUfLuheGGON0lVGZDMOhM+RuY6r8+coNsc5PCt3FmKUT9ZVeN5+11LZOEc/AxHzT1VKHz26ZiZWThaIjV0cmxcnsnksPkqZHl1EMhZEq91221ndfPui1+XrzLmmF7+TNZy2VynyDISFE0kzvbMbt5y1H74gGY2VOGtnom91NcOWR0/Du3sJvFR3Ift0cpDAqY4Qv9WE+PutEPETwOe/c87HD+4u2urdpdifu+/uruGDdZHzrnqe0zp3VNcz2jf7krY8U7D9kegcefX6Xba46K6H4QnHJZhhuOXtZ9PMt+SDJ1L8ZxnCAc9RVVeDCg/0DVQuqKzPYtTudGEZt1grq+5eNj16ZD1cfNxvfuvtJ9Ct8BJJSKV3mjhuO1RpxCwYbOw7vL3YTiEGE+Pb0Uxh9ZstMPPvaO9J9g5XO4TlroY0zoltPhSGzcnAqdWZ0NisFLd88pxOjPQH0nSnIhXiQpj7BDqytgAg6vXZqekpw2yUtRhn5GEZJJG7JuxF6qchm6IM3BmHKnSQ4wUTyiBQXYwc79P6UMVUVGTxw2Vo0hgTHI6LxxePn4IbfPY3JnoHy5MXdxuv6zSWr8Y7E6sdLbVUWnztqlvH6gZzge/H6cOVGuTOqOSeUJWkllhOKuLJS5NtbF+HWh59TXl100mC9/6oGU/XVFYkFVexorsX569SybQnLgmmjzZk5lwq/umhVya38fm/b4mI3gSAGDXtDsoqGxaAZjIxorMYjH1+PmgRdDGU4n8D3zlis5BL32aNmBu4/c3UvHnjy1QIr2lKhvakGv7t0jZ0Vz5mtLyr/d8nqQBdLEzNaJsEYknusdzLNxC1EeUALlPGJpWlgjG0BsAPAFADzOef3OvZ9GMBpAPYDOJtz/hNr+wCArwKoBfBjAOdwCmMemaBsUEQ8Opprcc4atUxDcRkzrDbSeVM6kjXnT4vKLEstZedlh07F7K7hWDQhPOV4VHQnp972hsC4BkEIBdjLb+2OdH4a3HL2UvzjzT2ubav7RuKXF67C2NbSiGFhkqGeoY0gBjvFyCpqioP7k7NKqU3RjZ3bVkD5CbeqIoMqxH8mc8YOxwOXBychKTZO1+OHrlgXW2E0OqIcqoN4VEkYeA+VxC2lzraVEyKHjDANKRfMEdc05Q8ANgG41rmRMTYVwDEA+gGMBnAHY2wS53w/gGsAbAXwW+QURusB3BqzHQQx5Hjinw+JveJTKsGJH95xcGp11VVVKKXnjkNFhiEt9Y1QNnoVMqVEv48V0WBUFhHFpaetHr/96yuRrPUIAsiN3/tCvmiLkSTiE0dOw2tvRRvnxYf60t42XHviXIOtKh62wqj8dHbGCUuYYpI4a/xTOpqwZaATW5ebd4kXLmkVmh1ifncLVkyWB+kuJT61eTru/tsrxW5GKKXkqSD6aml86ZQ3sRRGnPNHAGkq0SMAfJtzvhvA3xhjjwOYzxjbCaCJc36Xdd7XARwJUhgRhDZxXF5md+XMrFVizaRBTZGCiCfFCYvG4do7/5rKx8SZq3vx+tt7cdTcoecCYYrpY5rx9p7yzCz20BXrEo3HVW5ccVg/1vWPMprRhRha3HnRKjzzanD8IRF0uKYyg2tPHIj1Ea3KiTFieky1rJHft7TbUGuKj3Cf2jKQ7AJQOXL5oVPx2ItvGi1TyJzerG+6ZfzLlmB3wKjUWdZtulkXbzhjURLNMc7R88bi6LAEKoSLRRPacMcjLwz67M9pwExMcoyxXwD4kHBJY4xdDeC3nPPrrf9fh5xSaCeAqzjna6ztywBczDk/1KfcrchZI2Hs2LEDf//732O3lSCIHM+9/g46mpM3QR6KcM7xp+fe8LWsIQhicPHFXzyO+d0tmJtQVi6itDhwgOPKWx7B+5Z228GeifR5a/c+1FRmSy5m3GDFttgowaAwz7/+Lm7+/bM4bWlPSbaPSJ939uzHM6+9jd729IN2lyuMsfs45wVmqKEWRoyxOwDInBEv5Zz/yO80yTYesF0K5/zLAL4MAHPnzqUlVIIwCCmLkoMxRsoighhCfHBlb7GbQKRIJsNw+WFTi92MIU99NSV9SZNSVsSMaq7B6QlkfyXKl9qqLCmLDBE60gprIE2eBuC0Ee0E8Ky1vVOynSAIgiAIgiAIgiAIgigRknLquwnAMYyxasZYD4CJAO7hnD8HYBdjbCHLqalPAuBnpUQQBEEQBEEQBEEQBEEUgVgKI8bYexhjTwNYBOAWxthPAIBz/kcANwD4E4DbAGy3MqQBwDYA/wngcQBPgAJeEwRBEARBEARBEARBlBRGgl6nwdy5c/m9995b7GYQBEEQBEEQBEEQBEEMGvyCXlOeOYIgCIIgCIIgCIIgCMIFKYwIgiAIgiAIgiAIgiAIF6QwIgiCIAiCIAiCIAiCIFyQwoggCIIgCIIgCIIgCIJwQQojgiAIgiAIgiAIgiAIwgUpjAiCIAiCIAiCIAiCIAgXpDAiCIIgCIIgCIIgCIIgXJDCiCAIgiAIgiAIgiAIgnBBCiOCIAiCIAiCIAiCIAjCBeOcF7sNSjDGXgLw92K3wwBtAP5R7EYQRAjUT4lSh/ooUepQHyVKHeqjRKlDfZQodQZTHx3HOR/h3Vg2CqPBAmPsXs753GK3gyCCoH5KlDrUR4lSh/ooUepQHyVKHeqjRKkzFPoouaQRBEEQBEEQBEEQBEEQLkhhRBAEQRAEQRAEQRAEQbgghVH6fLnYDSAIBaifEqUO9VGi1KE+SpQ61EeJUof6KFHqDPo+SjGMCIIgCIIgCIIgCIIgCBdkYUQQBEEQBEEQBEEQBEG4IIVRijDG1jPG/swYe5wxdkmx20MMXRhjOxljDzPGHmSM3Wtta2GM/ZQx9pj1d7jj+A9b/fbPjLGDi9dyYrDCGPsvxtiLjLE/OLZp90nG2IDVtx9njP0bY4ylfS3E4MSnj+5gjD1jjaUPMsYOceyjPkqkCmOsizH2c8bYI4yxPzLGzrG201hKlAQBfZTGUqIkYIzVMMbuYYw9ZPXRj1nbh+w4SgqjlGCMZQF8AcAGAFMBHMsYm1rcVhFDnFWc81mOVJCXAPgZ53wigJ9Z/4fVT48B0A9gPYAvWv2ZIEzyVeT6l5MoffIaAFsBTLT+ecskiKh8FfL+9P+ssXQW5/zHAPVRomjsA3AB53wKgIUAtlt9kcZSolTw66MAjaVEabAbwGrO+UwAswCsZ4wtxBAeR0lhlB7zATzOOf8r53wPgG8DOKLIbSIIJ0cA+Jr1+2sAjnRs/zbnfDfn/G8AHkeuPxOEMTjnvwTwimezVp9kjHUAaOKc38VzAfq+7jiHIGLh00f9oD5KpA7n/DnO+f3W710AHgEwBjSWEiVCQB/1g/ookSo8x5vWfyutfxxDeBwlhVF6jAHwlOP/TyN4gCSIJOEAbmeM3ccY22ptG8k5fw7ITegA2q3t1HeJYqHbJ8dYv73bCSJJzmSM/d5yWRMm6tRHiaLCGOsGMBvA3aCxlChBPH0UoLGUKBEYY1nG2IMAXgTwU875kB5HSWGUHjKfRUpRRxSLJZzzOci5SG5njC0POJb6LlFq+PVJ6qtE2lwDYAJyZuvPAfistZ36KFE0GGMNAG4EcC7n/I2gQyXbqJ8SiSPpozSWEiUD53w/53wWgE7krIWmBRw+6PsoKYzS42kAXY7/dwJ4tkhtIYY4nPNnrb8vAvgBci5mL1jmk7D+vmgdTn2XKBa6ffJp67d3O0EkAuf8BUuwPADgP5B316U+ShQFxlglch/i3+Ccf9/aTGMpUTLI+iiNpUQpwjl/DcAvkIs9NGTHUVIYpcfvAExkjPUwxqqQC451U5HbRAxBGGP1jLFG8RvAOgB/QK4/nmwddjKAH1m/bwJwDGOsmjHWg1zQtnvSbTUxRNHqk5aJ8C7G2EIrE8VJjnMIwjhCeLR4D3JjKUB9lCgCVp+6DsAjnPPPOXbRWEqUBH59lMZSolRgjI1gjA2zftcCWAPgUQzhcbSi2A0YKnDO9zHGzgTwEwBZAP/FOf9jkZtFDE1GAviBldmxAsA3Oee3McZ+B+AGxthpAJ4EsAUAOOd/ZIzdAOBPyGW32M4531+cphODFcbYtwCsBNDGGHsawBUAroJ+n9yGXDarWgC3Wv8IIjY+fXQlY2wWcmbmOwF8AKA+ShSNJQBOBPCwFX8DAD4CGkuJ0sGvjx5LYylRInQA+JqV6SwD4AbO+c2MsbswRMdRlgvaTRAEQRAEQRAEQRAEQRA5yCWNIAiCIAiCIAiCIAiCcEEKI4IgCIIgCIIgCIIgCMIFKYwIgiAIgiAIgiAIgiAIF6QwIgiCIAiCIAiCIAiCIFyQwoggCIIgCIIgCIIgCIJwQQojgiAIgiAIgiAIgiAIwgUpjAiCIAiCIAiCIAiCIAgXpDAiCIIgCIIgCIIgCIIgXPx/bMWOFvUH+CEAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "T = np.random.uniform(-100,100,size=3000)\n", - "m = 200\n", - "i, j = 100, 1500\n", - "\n", - "T[i:i+m] = 0\n", - "T[j:j+m] = 0\n", - "\n", - "plt.plot(T)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "cb3a3940", - "metadata": {}, - "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", - "\n", - "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" - ] - }, - { - "cell_type": "markdown", - "id": "45eeecf5", - "metadata": {}, - "source": [ - "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." - ] - }, - { - "cell_type": "markdown", - "id": "e503fb0a", - "metadata": {}, - "source": [ - "# 2-Lower Bound of Distance Profile" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "71517d38", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 4c1e2be79448d5483b6bf0cb56f8bffcbd1575a2 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 12:28:11 -0600 Subject: [PATCH 37/67] Reviewed notebook --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 5420a285d..2b91a91e2 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -2073,7 +2073,7 @@ }, { "cell_type": "markdown", - "id": "c26f0a33", + "id": "d435f4fc", "metadata": {}, "source": [ "\n", @@ -2091,7 +2091,7 @@ }, { "cell_type": "markdown", - "id": "d7ae9e69", + "id": "125c27bc", "metadata": {}, "source": [ "Therefore, according to eq(16), $f(\\mu^{'},\\sigma^{'}) = m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right]$, we have: $f(\\mu^{'},\\sigma^{'}) \\geq m$, and according to eq(2), $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can see that:" @@ -2099,7 +2099,7 @@ }, { "cell_type": "markdown", - "id": "b661f3d9", + "id": "06f789ce", "metadata": {}, "source": [ "\n", @@ -2113,7 +2113,7 @@ }, { "cell_type": "markdown", - "id": "1365fad2", + "id": "810ab4ae", "metadata": {}, "source": [ "**NOTE:** Please note that a stronger LB for $\\rho_{ij} \\leq 0$ is $2\\frac{(-\\rho_{ij})\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}$ (see eq(18) above). However, this has $\\sigma^{'}$ which is unknown. we would like to find LB that is only based on known parameters. Therefore, we are okay with the LB proposed in the paper." @@ -2122,7 +2122,7 @@ { "cell_type": "code", "execution_count": null, - "id": "52c83826", + "id": "826bb9c8", "metadata": {}, "outputs": [], "source": [] From 2b6c9dc4296f375e139db07316d54f91e9d5e759 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 12:40:04 -0600 Subject: [PATCH 38/67] ADD heading and revise subheadings --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 2b91a91e2..d45ddb85d 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "4db65758", + "metadata": {}, + "source": [ + "# Intro" + ] + }, { "cell_type": "markdown", "id": "d8ebe111", @@ -24,7 +32,7 @@ "id": "3b5c8c5a", "metadata": {}, "source": [ - "## 2-1 Non-normalized distance" + "## Non-normalized distance" ] }, { @@ -107,7 +115,7 @@ "id": "0b539ca8", "metadata": {}, "source": [ - "## 2-2 Normalized distance" + "## Normalized distance" ] }, { From b2a86e407045bbfaa70af178d8f5d469cc0fed4d Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 14:20:56 -0600 Subject: [PATCH 39/67] ADD proof for global minimum --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 175 +++++++++++++++++- 1 file changed, 167 insertions(+), 8 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index d45ddb85d..ed53f146a 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "4db65758", + "id": "760a9022", "metadata": {}, "source": [ "# Intro" @@ -1557,7 +1557,8 @@ "id": "a5370108", "metadata": {}, "source": [ - "### Derving Equation (2): Continued" + "### Derving Equation (2): Continued\n", + "**How about LB for the case $\\rho_{ij} \\leq 0$?**" ] }, { @@ -2027,7 +2028,7 @@ " \\sigma^{'2}\n", " }\n", " +\n", - " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}}{\\sigma^{'}}\n", " +\n", " \\left[\n", " (\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}})^{2}\n", @@ -2050,7 +2051,7 @@ " \\sigma^{'2}\n", " }\n", " +\n", - " 2\\frac{-\\rho_{ij}\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}}{\\sigma^{'}}\n", " +\n", " \\left[\n", " \\left(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}}\\right)\n", @@ -2060,10 +2061,10 @@ " }{\n", " \\sigma_{j,m}\n", " }\\right)\n", - " \\right]^{2}\n", + " \\right]^{2} \\quad (18)\n", " \\\\\n", " \\geq{}&\n", - " 2\\frac{(-\\rho_{ij})\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}} \\quad (18)\n", + " 2\\frac{(-\\rho_{ij})\\sigma_{i,m}}{\\sigma^{'}} \\quad (19)\n", " \\\\\n", " \\geq{}&\n", " 0\n", @@ -2124,13 +2125,171 @@ "id": "810ab4ae", "metadata": {}, "source": [ - "**NOTE:** Please note that a stronger LB for $\\rho_{ij} \\leq 0$ is $2\\frac{(-\\rho_{ij})\\sigma_{i,m}\\sigma_{j,m}}{\\sigma^{'}\\sigma_{j,m}}$ (see eq(18) above). However, this has $\\sigma^{'}$ which is unknown. we would like to find LB that is only based on known parameters. Therefore, we are okay with the LB proposed in the paper." + "**NOTE:** Please note that a stronger LB for $\\rho_{ij} \\leq 0$ is $2\\frac{(-\\rho_{ij})\\sigma_{i,m}}{\\sigma^{'}}$; see eq(19) above. **However,** this has $\\sigma^{'}$ which is unknown. we would like to find LB that is only based on known parameters. Therefore, we are okay with the LB proposed in the paper." + ] + }, + { + "cell_type": "markdown", + "id": "d7846918", + "metadata": {}, + "source": [ + "### Derving Equation (2): Continued\n", + "**Is the LB calculated for the case $\\rho_{ij} \\gt 0$ a global minimum?**" + ] + }, + { + "cell_type": "markdown", + "id": "70ddffdd", + "metadata": {}, + "source": [ + "There is still one thing left to be done. We need to show that the LB discovered for $\\rho_{ij} \\gt 0$ is actually a global minimum. In other words, we need to show that the inequation below holds true for all $\\rho_{ij} \\gt 0$:" + ] + }, + { + "cell_type": "markdown", + "id": "b59c489a", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " f(\\mu^{'},\\sigma^{'}) \\geq{}&\n", + " f(\\mu_{c}^{'},\\sigma_{c}^{'})\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "26564b7a", + "metadata": {}, + "source": [ + "where, $\\mu_{c}^{'}$ (eq(11)) and $\\sigma_{c}^{'}$ (eq(12)) are the values of the critical point." + ] + }, + { + "cell_type": "markdown", + "id": "2a694b0b", + "metadata": {}, + "source": [ + "We replace left-hand side $f(\\mu^{'},\\sigma^{'})$ with its equivalent term (16), and we replace $f(\\mu_{c}^{'},\\sigma_{c}^{'})$ with $m(1 - \\rho_{ij}^{2})$ as calculated before. Therefore:" + ] + }, + { + "cell_type": "markdown", + "id": "1a1f44e4", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right] \\geq{}& m(1 - \\rho_{ij}^{2})\n", + " \\\\\n", + " 1 + g(\\mu^{'},\\sigma^{'}) \\geq{}& 1 - \\rho_{ij}^{2}\n", + " \\\\\n", + " g(\\mu^{'},\\sigma^{'}) + \\rho_{ij}^{2} \\geq{}& 0 \\quad (20)\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2d2fc60e", + "metadata": {}, + "source": [ + "Therefore, we need to show inequation (20) is satisfied for all $\\rho_{i,j} \\geq 0$.
\n", + "We now subtitute eq(18) for $g(.)$. Thus:" + ] + }, + { + "cell_type": "markdown", + "id": "9054a4f6", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " \\frac{\n", + " \\sigma_{i,m}^{2}\n", + " }{\n", + " \\sigma^{'2}\n", + " }\n", + " +\n", + " 2\\frac{-\\rho_{ij}\\sigma_{i,m}}{\\sigma^{'}}\n", + " +\n", + " \\left[\n", + " \\left(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}}\\right)\n", + " -\n", + " \\left(\\frac{\n", + " \\mu_{j,m} - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\\right)\n", + " \\right]^{2}\n", + " + \n", + " \\rho_{ij}^{2} \n", + " \\geq{}& 0\n", + " \\\\\n", + " \\left[\n", + " \\left(\\frac{\n", + " \\sigma_{i,m}\n", + " }{\n", + " \\sigma^{'}\n", + " }\\right)^{2}\n", + " +\n", + " \\rho_{ij}^{2} \n", + " -\n", + " 2\\left(\\frac{\\sigma_{i,m}}{\\sigma^{'}}\\right)\\rho_{ij}\n", + " \\right]\n", + " + \n", + " \\left[\n", + " \\left(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}}\\right)\n", + " -\n", + " \\left(\\frac{\n", + " \\mu_{j,m} - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\\right)\n", + " \\right]^{2}\n", + " \\geq{}& \n", + " 0\n", + " \\\\\n", + " \\left(\\frac{\n", + " \\sigma_{i,m}\n", + " }{\n", + " \\sigma^{'}\n", + " }\n", + " -\n", + " \\rho_{ij}\n", + " \\right)^{2} \n", + " + \n", + " \\left[\n", + " \\left(\\frac{\\mu_{i,m}-\\mu^{'}}{\\sigma^{'}}\\right)\n", + " -\n", + " \\left(\\frac{\n", + " \\mu_{j,m} - \\mu_{j,m+k}\n", + " }{\n", + " \\sigma_{j,m}\n", + " }\\right)\n", + " \\right]^{2}\n", + " \\geq{}& \n", + " 0\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b2d7da6e", + "metadata": {}, + "source": [ + "The above inequation is always satisfied. Therefore, the critical point gives global minimum." ] }, { "cell_type": "code", "execution_count": null, - "id": "826bb9c8", + "id": "10851222", "metadata": {}, "outputs": [], "source": [] From 53e740b8c2a500acf413b38757c92878e5a35e3e Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 14:25:34 -0600 Subject: [PATCH 40/67] Correct some notes --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 28 +++++++++---------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index ed53f146a..952819e1e 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "760a9022", + "id": "0e440d53", "metadata": {}, "source": [ "# Intro" @@ -1549,7 +1549,7 @@ "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", "\n", "**Pending...**
\n", - "* The proof is not complete. We need to take the second derivatives and make sure the discovered values give local minimum and not maximum or saddle point. Also, we need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function." + "* We need to analyze the behavior of function `f` to verify that this local minimum is actually the global minimum for this function (more on this later after we derive LB for case $\\rho_{ij} \\leq 0$.)" ] }, { @@ -1566,7 +1566,7 @@ "id": "fc19b2dd", "metadata": {}, "source": [ - "So far, we derived the first sub-function (i.e. LB for $\\rho_{ij} \\gt 0$) of the piecewise function provided in the eq(2) of the paper VALMOD.
\n", + "So far, we have derived the first sub-function of the piecewise function provided in the eq(2) of the paper VALMOD, that is LB for $\\rho_{ij} \\gt 0$.
\n", "Now, we would like to derive the second sub-function, where LB is defined for $\\rho_{ij} \\leq 0$." ] }, @@ -1612,7 +1612,7 @@ "id": "bf007040", "metadata": {}, "source": [ - "Inside the summation, we use the formula: $(A+B)^{2} = A^{2} + B^{2} - 2AB$" + "Inside the summation, we use the formula: $(A \\pm B)^{2} = A^{2} + B^{2} \\pm 2AB$" ] }, { @@ -2130,7 +2130,7 @@ }, { "cell_type": "markdown", - "id": "d7846918", + "id": "a8b816ff", "metadata": {}, "source": [ "### Derving Equation (2): Continued\n", @@ -2139,7 +2139,7 @@ }, { "cell_type": "markdown", - "id": "70ddffdd", + "id": "fc7711bb", "metadata": {}, "source": [ "There is still one thing left to be done. We need to show that the LB discovered for $\\rho_{ij} \\gt 0$ is actually a global minimum. In other words, we need to show that the inequation below holds true for all $\\rho_{ij} \\gt 0$:" @@ -2147,7 +2147,7 @@ }, { "cell_type": "markdown", - "id": "b59c489a", + "id": "cc4dc1b6", "metadata": {}, "source": [ "\n", @@ -2161,7 +2161,7 @@ }, { "cell_type": "markdown", - "id": "26564b7a", + "id": "81e012b9", "metadata": {}, "source": [ "where, $\\mu_{c}^{'}$ (eq(11)) and $\\sigma_{c}^{'}$ (eq(12)) are the values of the critical point." @@ -2169,7 +2169,7 @@ }, { "cell_type": "markdown", - "id": "2a694b0b", + "id": "372a014e", "metadata": {}, "source": [ "We replace left-hand side $f(\\mu^{'},\\sigma^{'})$ with its equivalent term (16), and we replace $f(\\mu_{c}^{'},\\sigma_{c}^{'})$ with $m(1 - \\rho_{ij}^{2})$ as calculated before. Therefore:" @@ -2177,7 +2177,7 @@ }, { "cell_type": "markdown", - "id": "1a1f44e4", + "id": "e10ed8a8", "metadata": {}, "source": [ "\n", @@ -2194,7 +2194,7 @@ }, { "cell_type": "markdown", - "id": "2d2fc60e", + "id": "7988c834", "metadata": {}, "source": [ "Therefore, we need to show inequation (20) is satisfied for all $\\rho_{i,j} \\geq 0$.
\n", @@ -2203,7 +2203,7 @@ }, { "cell_type": "markdown", - "id": "9054a4f6", + "id": "ea2a5a7e", "metadata": {}, "source": [ "\n", @@ -2280,7 +2280,7 @@ }, { "cell_type": "markdown", - "id": "b2d7da6e", + "id": "fe8f12ec", "metadata": {}, "source": [ "The above inequation is always satisfied. Therefore, the critical point gives global minimum." @@ -2289,7 +2289,7 @@ { "cell_type": "code", "execution_count": null, - "id": "10851222", + "id": "ebf2b75e", "metadata": {}, "outputs": [], "source": [] From a39e98b097a2bda928d50e65dbdb3030b4f70526 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sat, 16 Apr 2022 14:35:02 -0600 Subject: [PATCH 41/67] Rename the notebook --- docs/Tutorial_VALMOD.ipynb | 178 +++++++++++++++++++++++++++++++++++++ 1 file changed, 178 insertions(+) create mode 100644 docs/Tutorial_VALMOD.ipynb diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb new file mode 100644 index 000000000..86e244817 --- /dev/null +++ b/docs/Tutorial_VALMOD.ipynb @@ -0,0 +1,178 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c7a27406", + "metadata": {}, + "source": [ + "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", + "\n", + "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "0adbe18a", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import stumpy\n", + "from stumpy import core, config\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" + ] + }, + { + "cell_type": "markdown", + "id": "e9d48c97", + "metadata": {}, + "source": [ + "# 1- Introduction" + ] + }, + { + "cell_type": "markdown", + "id": "b0423978", + "metadata": {}, + "source": [ + "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m`. " + ] + }, + { + "cell_type": "markdown", + "id": "4a4af7fd", + "metadata": {}, + "source": [ + "## Motif discovery" + ] + }, + { + "cell_type": "markdown", + "id": "78ac5b0f", + "metadata": {}, + "source": [ + "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", + "\n", + "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "\n", + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." + ] + }, + { + "cell_type": "markdown", + "id": "7fc09927", + "metadata": {}, + "source": [ + "## Discord Discovery" + ] + }, + { + "cell_type": "markdown", + "id": "0f4ee615", + "metadata": {}, + "source": [ + "First, we need to provide a few definitions...\n", + "\n", + "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", + "\n", + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", + "\n", + "**NOTE**:
\n", + "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "37fdbb26", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "T = np.random.uniform(-100,100,size=3000)\n", + "m = 200\n", + "i, j = 100, 1500\n", + "\n", + "T[i:i+m] = 0\n", + "T[j:j+m] = 0\n", + "\n", + "plt.plot(T)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "cb3a3940", + "metadata": {}, + "source": [ + "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", + "\n", + "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" + ] + }, + { + "cell_type": "markdown", + "id": "45eeecf5", + "metadata": {}, + "source": [ + "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", + "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + ] + }, + { + "cell_type": "markdown", + "id": "e503fb0a", + "metadata": {}, + "source": [ + "# 2-Lower Bound of Distance Profile" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "71517d38", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 46ed1f654f90df73abd37ab0a3e9c0724b8b9950 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 13:43:09 -0600 Subject: [PATCH 42/67] Removed redundant equation --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 19 +++---------------- 1 file changed, 3 insertions(+), 16 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 952819e1e..aecfbb8d4 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -257,7 +257,7 @@ "\\begin{align}\n", " \\alpha_{t} \\triangleq{}& \n", " {\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}} \\quad (2)\n", " } \n", " \\\\\n", "\\end{align}\n", @@ -282,23 +282,10 @@ "\\begin{align}\n", " LB ={}& \n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{\\min f(\\mu^{'},\\sigma^{'})} \\quad (2)\n", + " \\sqrt{\\min \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}} \\quad (3)\n", " \\\\\n", " f(\\mu^{'}, \\sigma^{'}) ={}&\n", - " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (3)\n", - " \\\\\n", - " \\alpha_{t} ={}& \n", - " \\frac{\n", - " T[i+t-1] - \\mu^{'}\n", - " }{\n", - " \\sigma^{'}\n", - " } \n", - " - \n", - " \\frac{\n", - " T[j+t-1] - \\mu_{j,m+k}\n", - " }{\n", - " \\sigma_{j,m}\n", - " } \\quad (4)\n", + " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (4)\n", " \\\\\n", "\\end{align}\n", "$$\n" From a2754b56e5e8dd05c740e466ed2e2a9b4fe4b2fe Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 13:52:33 -0600 Subject: [PATCH 43/67] FIXED spelling errors --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index aecfbb8d4..7eb2d8304 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -621,7 +621,7 @@ "id": "0c839937", "metadata": {}, "source": [ - "Now, recall that the pearson correlation $\\rho_{ij}$ between two subsequenes of lenght $m$ is defined as follows:" + "Now, recall that the pearson correlation $\\rho_{ij}$ between two subsequences starting at locations $i$ and $j$, respectively, and both of length $m$ is defined as follows:" ] }, { @@ -909,7 +909,7 @@ "id": "978473a2", "metadata": {}, "source": [ - "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequenec with itself is 1." + "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequence with itself is 1." ] }, { From 87c53321425d8696ca975f65b62501fbe5212d0e Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 14:59:01 -0600 Subject: [PATCH 44/67] minor changes --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 61 +++++++++---------- 1 file changed, 29 insertions(+), 32 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 7eb2d8304..4afba90a6 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -761,6 +761,26 @@ " \\right]\n", " ={}& 0\n", " \\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "51235736", + "metadata": {}, + "source": [ + "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequence with itself is 1." + ] + }, + { + "cell_type": "markdown", + "id": "182b8064", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", " \\frac{1}{\\sigma^{'}}\n", " \\left[\n", " \\left(\n", @@ -781,18 +801,7 @@ " \\mu_{j,m+k} \\cdot m\\mu_{i,m}\n", " \\right]\n", " ={}& 0\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "182b8064", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", + " \\\\\n", " \\frac{1}{\\sigma^{'}\\sigma_{j,m}}\n", " \\left[\n", " \\sigma_{j,m}\\left(\n", @@ -904,14 +913,6 @@ "$$\n" ] }, - { - "cell_type": "markdown", - "id": "978473a2", - "metadata": {}, - "source": [ - "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequence with itself is 1." - ] - }, { "cell_type": "markdown", "id": "6adaea06", @@ -1141,7 +1142,7 @@ "id": "92abd2a2", "metadata": {}, "source": [ - "**Start with equation (3):**" + "**Start with equation (4):**" ] }, { @@ -1167,7 +1168,7 @@ "id": "7afe0a3d", "metadata": {}, "source": [ - "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(4)..." + "And, we replace one of $\\alpha_{t}$ with its equivalent term provided in eq(2)..." ] }, { @@ -1485,7 +1486,7 @@ " }\n", " \\\\\n", " ={}&\n", - " m(1-\\rho_{ij}^{2})\n", + " m(1-\\rho_{ij}^{2}) \\quad (13)\n", "\\end{align} \n", "$$\n" ] @@ -1495,7 +1496,7 @@ "id": "64dc1027", "metadata": {}, "source": [ - "**Finally, with eq(2), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" + "**Finally, with eq(3), the lower-bound `LB` for distance profile of `T[j:j+m+k]` is as follows:**" ] }, { @@ -1510,13 +1511,9 @@ " \\frac{\n", " \\sigma_{j,m}\n", " }{\\sigma_{j,m+k}\n", - " } \\sqrt{m (1 - \\rho_{ij}^{2})} \\quad \\text{if} \\, \\rho > 0\n", + " } \\sqrt{m (1 - \\rho_{ij}^{2})} \\quad \\text{if} \\, \\rho > 0 \\quad (14)\n", + " \\\\\n", " \\\\\n", - "\\end{align}\n", - "$$\n", - "\n", - "$$\n", - "\\begin{align}\n", " \\rho_{ij} ={}& \n", " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", @@ -1562,7 +1559,7 @@ "id": "a4f11acc", "metadata": {}, "source": [ - "We start with eq(3), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(4). Therefore:" + "We start with eq(4), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(2). Therefore:" ] }, { @@ -2159,7 +2156,7 @@ "id": "372a014e", "metadata": {}, "source": [ - "We replace left-hand side $f(\\mu^{'},\\sigma^{'})$ with its equivalent term (16), and we replace $f(\\mu_{c}^{'},\\sigma_{c}^{'})$ with $m(1 - \\rho_{ij}^{2})$ as calculated before. Therefore:" + "We replace left-hand side $f(\\mu^{'},\\sigma^{'})$ with its equivalent term (16), and we replace $f(\\mu_{c}^{'},\\sigma_{c}^{'})$ with eq(13), i.e. $m(1 - \\rho_{ij}^{2})$. Therefore:" ] }, { From 8a3501051b186eb47dc3baed6d557e3d5919d275 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 15:42:11 -0600 Subject: [PATCH 45/67] convert equations to base-zero indexing --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 284 +++++++++--------- 1 file changed, 141 insertions(+), 143 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 4afba90a6..b6591b9cb 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -45,33 +45,33 @@ "\\begin{align}\n", " d^{(m+k)}_{j,i} ={}& \n", " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m+k}{\n", + " \\sum\\limits_{t=0}^{m+k-1}{\n", " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", + " T[i+t] - T[j+t]\n", " }\\bigg\\rvert\n", " }^{p}\n", " }\n", " \\\\\n", " ={}&\n", " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m}{\n", + " \\sum\\limits_{t=0}^{m-1}{\n", " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", + " T[i+t] - T[j+t]\n", " }\\bigg\\rvert\n", " }^{p}\n", " +\n", - " \\sum\\limits_{t=m+1}^{m+k}{\n", + " \\sum\\limits_{t=m}^{m+k-1}{\n", " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", + " T[i+t] - T[j+t]\n", " }\\bigg\\rvert\n", " }^{p}\n", " }\n", " \\\\\n", " \\geq{}&\n", " \\sqrt[\\leftroot{5}\\uproot{5}p]{\n", - " \\sum\\limits_{t=1}^{m}{\n", + " \\sum\\limits_{t=0}^{m-1}{\n", " \\bigg\\lvert{\n", - " T[i+t-1] - T[j+t-1]\n", + " T[i+t] - T[j+t]\n", " }\\bigg\\rvert\n", " }^{p}\n", " }\n", @@ -143,24 +143,24 @@ "$$\n", "\\begin{align}\n", " d^{(m+k)}_{j,i} ={}& \n", - " \\sqrt{\\sum\\limits_{t=1}^{m+k}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " \\sqrt{\\sum\\limits_{t=0}^{m+k-1}{{\n", + " \\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}} \n", " \\\\\n", " d^{(m+k)}_{j,i} ={}& \n", " \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " \\sum\\limits_{t=0}^{m-1}{{\n", + " \\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}\n", " +\n", - " \\sum\\limits_{t=m+1}^{m+k}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " \\sum\\limits_{t=m}^{m+k-1}{{\n", + " \\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}\n", " } \n", " \\\\\n", " \\geq{}&\n", - " \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " \\sqrt{\\sum\\limits_{t=0}^{m-1}{{\n", + " \\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}}\n", " \\\\\n", "\\end{align}\n", @@ -184,29 +184,29 @@ "$$\n", "\\begin{align}\n", " LB ={}& \n", - " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", - " \\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", + " \\min \\sqrt{\\sum\\limits_{t=0}^{m-1}{{\n", + " \\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{i,m+k}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m+k}}\\right)\n", " }^{2}}} \n", " \\\\\n", " ={}&\n", - " \\min \\sqrt{\\sum\\limits_{t=1}^{m}{{\n", + " \\min \\sqrt{\\sum\\limits_{t=0}^{m-1}{{\n", " \\left[\\frac{1}{\\sigma_{j,m+k}}\n", " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\frac{T[i+t] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t] - \\mu_{j,m+k}}{1}\n", " \\right)\n", " \\right]\n", " }^{2}}}\n", " \\\\\n", " ={}&\n", " \\min \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", + " \\sum\\limits_{t=0}^{m-1}{{\n", " \\left[\n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m}}\n", " \\frac{1}{\\sigma_{j,m+k}}\n", " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " \\frac{T[i+t] - \\mu_{i,m+k}}{\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", " - \n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{1}\n", + " \\frac{T[j+t] - \\mu_{j,m+k}}{1}\n", " \\right)\n", " \\right]\n", " }^{2}\n", @@ -215,13 +215,13 @@ " \\\\\n", " ={}&\n", " \\min \\sqrt{\n", - " \\sum\\limits_{t=1}^{m}{{\n", + " \\sum\\limits_{t=0}^{m-1}{{\n", " \\left[\n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", " \\left(\n", - " \\frac{T[i+t-1] - \\mu_{i,m+k}}{\\sigma_{j,m}\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", + " \\frac{T[i+t] - \\mu_{i,m+k}}{\\sigma_{j,m}\\frac{\\sigma_{i,m+k}}{\\sigma_{j,m+k}}} \n", " - \n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " \\right)\n", " \\right]\n", " }^{2}\n", @@ -229,7 +229,7 @@ " }\n", " \\\\\n", " ={}&\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=1}^{m}{\\left(\\frac{T[i+t-1] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad(1)\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}} \\times \\min \\sqrt{\\sum\\limits_{t=0}^{m-1}{\\left(\\frac{T[i+t] - \\mu_{i,m+k}}{\\frac{\\sigma_{j,m} \\sigma_{i,m+k}}{\\sigma_{j,m+k}}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right)^{2}}} \\quad(1)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -257,7 +257,7 @@ "\\begin{align}\n", " \\alpha_{t} \\triangleq{}& \n", " {\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}} \\quad (2)\n", + " \\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}} \\quad (2)\n", " } \n", " \\\\\n", "\\end{align}\n", @@ -282,10 +282,10 @@ "\\begin{align}\n", " LB ={}& \n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{\\min \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}} \\quad (3)\n", + " \\sqrt{\\min \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}}} \\quad (3)\n", " \\\\\n", " f(\\mu^{'}, \\sigma^{'}) ={}&\n", - " \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}} \\quad (4)\n", + " \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}} \\quad (4)\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -333,24 +333,24 @@ "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", + " \\sum \\limits_{t=0}^{m-1}{\n", " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\mu^{'}}}\n", " }\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", + " \\sum \\limits_{t=0}^{m-1}{\n", " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\mu^{'}}}\\alpha_{t}\n", " }\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\mu^{'}}} ={}&\n", - " \\sum \\limits_{t=1}^{m} {\n", + " \\sum \\limits_{t=0}^{m-1} {\n", " 2\\left(\n", " \\frac{-1}{\\sigma^{'}}\n", " \\right)\n", " \\alpha_{t}} \n", " \\\\\n", " 0 ={}&\n", - " \\frac{-2}{\\sigma^{'}}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\frac{-2}{\\sigma^{'}}\\sum \\limits_{t=0}^{m-1}{\\alpha_{t}}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -373,7 +373,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m}{\\alpha_{t}} = 0 \\quad (7)\n", + " \\sum \\limits_{t=0}^{m-1}{\\alpha_{t}} = 0 \\quad (7)\n", "\\end{align}\n", "$$\n" ] @@ -394,14 +394,14 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} \\alpha_{t} ={}& \n", + " \\sum \\limits_{t=0}^{m-1} \\alpha_{t} ={}& \n", " 0\n", " \\\\\n", - " \\sum \\limits_{t=1}^{m} {\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", + " \\sum \\limits_{t=0}^{m-1} {\\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}} ={}& \n", " 0\n", " \\\\\n", - " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=1}^{m}T[i+t-1] - \\sum \\limits_{t=1}^{m} \\mu^{'}\\right) - \n", - " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=1}^{m}T[j+t-1] - \\sum \\limits_{t=1}^{m} \\mu_{j,m+k}\\right) ={}& \n", + " \\frac{1}{\\sigma^{'}}\\left(\\sum \\limits_{t=0}^{m-1}T[i+t] - \\sum \\limits_{t=0}^{m-1} \\mu^{'}\\right) - \n", + " \\frac{1}{\\sigma_{j,m}}\\left(\\sum \\limits_{t=0}^{m-1}T[j+t] - \\sum \\limits_{t=0}^{m-1} \\mu_{j,m+k}\\right) ={}& \n", " 0\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\\left(m\\mu_{i,m} - m\\mu^{'}\\right) - \n", @@ -436,50 +436,50 @@ "$$\n", "\\begin{align}\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", + " \\sum \\limits_{t=0}^{m-1}{\n", " \\frac{\\partial{(\\alpha_{t}^{2})}}{\\partial{\\sigma^{'}}}\n", " }\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}& \n", - " \\sum \\limits_{t=1}^{m}{\n", + " \\sum \\limits_{t=0}^{m-1}{\n", " 2\\frac{\\partial{(\\alpha_{t})}}{\\partial{\\sigma^{'}}}\\alpha_{t}\n", " }\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\sum \\limits_{t=1}^{m} {\n", + " \\sum \\limits_{t=0}^{m-1} {\n", " 2 \\left(\n", - " \\frac{-\\left({T[i+t-1] - \\mu^{'}}\\right)}{\\sigma^{'2}}\n", + " \\frac{-\\left({T[i+t] - \\mu^{'}}\\right)}{\\sigma^{'2}}\n", " \\right)\n", " \\alpha_{t}} \n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1] - \\mu^{'}}\\right) \\alpha_{t}}\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=0}^{m-1}{\\left({T[i+t] - \\mu^{'}}\\right) \\alpha_{t}}\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", - " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=1}^{m}{\\left({T[i+t-1]\\alpha_{t} - \\mu^{'}\\alpha_{t}}\\right)}\n", + " \\frac{-2}{\\sigma^{'2}}\\sum \\limits_{t=0}^{m-1}{\\left({T[i+t]\\alpha_{t} - \\mu^{'}\\alpha_{t}}\\right)}\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", " \\frac{-2}{\\sigma^{'2}}\n", " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " \\sum \\limits_{t=0}^{m-1}{T[i+t]\\alpha_{t}} \n", " - \n", - " \\sum \\limits_{t=1}^{m}{\\mu^{'}\\alpha_{t}}\n", + " \\sum \\limits_{t=0}^{m-1}{\\mu^{'}\\alpha_{t}}\n", " \\right)\n", " }\n", " \\\\\n", " \\frac{\\partial{f}}{\\partial{\\sigma^{'}}} ={}&\n", " \\frac{-2}{\\sigma^{'2}}\n", " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " \\sum \\limits_{t=0}^{m-1}{T[i+t]\\alpha_{t}} \n", " - \n", - " \\mu^{'}\\sum \\limits_{t=1}^{m}{\\alpha_{t}}\n", + " \\mu^{'}\\sum \\limits_{t=0}^{m-1}{\\alpha_{t}}\n", " \\right)\n", " }\n", " \\\\\n", " 0 ={}&\n", " \\frac{-2}{\\sigma^{'2}}\n", " {\\left(\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " \\sum \\limits_{t=0}^{m-1}{T[i+t]\\alpha_{t}} \n", " - \n", " \\mu^{'}\\cdot 0\n", " \\right)\n", @@ -488,7 +488,7 @@ " 0 ={}&\n", " \\frac{-2}{\\sigma^{'2}}\n", " {\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} \n", + " \\sum \\limits_{t=0}^{m}{T[i+t]\\alpha_{t}} \n", " }\n", "\\end{align}\n", "$$\n" @@ -499,7 +499,7 @@ "id": "1340817b", "metadata": {}, "source": [ - "Note: In the calculations above, we substituted 0 for $\\sum \\limits_{t=1}^{m}{\\alpha_{t}}$ according to eq(7)." + "Note: In the calculations above, we substituted 0 for $\\sum \\limits_{t=0}^{m-1}{\\alpha_{t}}$ according to eq(7)." ] }, { @@ -518,7 +518,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}} ={}&\n", + " \\sum \\limits_{t=0}^{m-1}{T[i+t]\\alpha_{t}} ={}&\n", " 0 \\quad (9)\n", "\\end{align}\n", "$$\n" @@ -540,7 +540,7 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum \\limits_{t=1}^{m} T[i+t-1] \\left(\\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", + " \\sum \\limits_{t=0}^{m-1} T[i+t] \\left(\\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\\right) = 0\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -554,43 +554,43 @@ "\n", "$$\n", "\\begin{align}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}T[i+t-1] \n", " \\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}}\n", + " \\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}}\n", " \\right)\n", " - \n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}T[i+t-1] \n", " \\left(\n", - " \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " \\right)\n", " ={}& 0\n", " \\\\\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}T[i+t] \n", " \\left(\n", - " T[i+t-1] - \\mu^{'}\n", + " T[i+t] - \\mu^{'}\n", " \\right)\n", " - \n", " \\frac{1}{\\sigma_{j,m}}\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}T[i+t-1] \n", " \\left(\n", - " T[j+t-1] - \\mu_{j,m+k}\n", + " T[j+t] - \\mu_{j,m+k}\n", " \\right)\n", " ={}& 0\n", " \\\\\n", " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " \\sum\\limits_{t=0}^{m-1}T[i+t]T[i+t]\n", " -\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]\\mu^{'}\n", + " \\sum\\limits_{t=0}^{m-1}T[i+t]\\mu^{'}\n", " \\right) \n", " - \\\\\n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", - " {\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", - " -\\sum \\limits_{t=1}^{m}T[i+t-1]\\mu_{j,m+k}\n", + " {\\sum\\limits_{t=0}^{m-1}T[i+t]T[j+t] \n", + " -\\sum \\limits_{t=0}^{m-1}T[i+t]\\mu_{j,m+k}\n", " }\n", " \\right) \n", " ={}& \n", @@ -599,16 +599,16 @@ " \\\\\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", - " \\sum \\limits_{t=1}^{m}T[i+t-1]T[i+t-1]\n", + " \\sum \\limits_{t=0}^{m-1}T[i+t]T[i+t]\n", " -\n", - " \\mu^{'}\\sum\\limits_{t=1}^{m} T[i+t-1]\n", + " \\mu^{'}\\sum\\limits_{t=0}^{m-1} T[i+t]\n", " \\right) \n", " - \\\\\n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1]\n", + " \\sum\\limits_{t=0}^{m-1}T[i+t]T[j+t]\n", " -\n", - " \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " \\mu_{j,m+k}\\sum \\limits_{t=0}^{m-1}T[i+t]\n", " \\right) \n", " ={}& \n", " 0 \\quad (*)\n", @@ -648,8 +648,8 @@ " \\\\\n", " ={}&\n", " \\frac{\n", - " \\frac{1}{m}\\sum\\limits_{t=1}^{m}\n", - " (T[i+t-1] - \\mu_{i,m})(T[j+t-1] - \\mu_{j,m})\n", + " \\frac{1}{m}\\sum\\limits_{t=0}^{m-1}\n", + " (T[i+t] - \\mu_{i,m})(T[j+t] - \\mu_{j,m})\n", " }\n", " {\n", " \\sigma_{i,m}\\sigma_{j,m}\n", @@ -657,40 +657,40 @@ " \\\\\n", " ={}&\n", " \\frac{\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]T[j+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]T[j+t] \n", " -\n", - " \\sum\\limits_{t=1}^{m}\n", - " \\mu_{i,m}T[j+t-1]\n", + " \\sum\\limits_{t=0}^{m-1}\n", + " \\mu_{i,m}T[j+t]\n", " -\n", - " \\sum\\limits_{t=1}^{m}\n", - " \\mu_{j,m}T[i+t-1]\n", + " \\sum\\limits_{t=0}^{m-1}\n", + " \\mu_{j,m}T[i+t]\n", " +\n", - " \\sum\\limits_{t=1}^{m}\\mu_{i,m}\\mu_{j,m}\n", + " \\sum\\limits_{t=0}^{m-1}\\mu_{i,m}\\mu_{j,m}\n", " }{\n", " m\\sigma_{i,m}\\sigma_{j,,m}\n", " }\n", " \\\\\n", " ={}&\n", " \\frac{\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]T[j+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]T[j+t] \n", " -\n", - " \\mu_{i,m}\\sum\\limits_{t=1}^{m}\n", - " T[j+t-1]\n", + " \\mu_{i,m}\\sum\\limits_{t=0}^{m-1}\n", + " T[j+t]\n", " -\n", - " \\mu_{j,m}\\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]\n", + " \\mu_{j,m}\\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]\n", " +\n", - " \\sum\\limits_{t=1}^{m}\\mu_{i,m}\\mu_{j,m}\n", + " \\sum\\limits_{t=0}^{m-1}\\mu_{i,m}\\mu_{j,m}\n", " }{\n", " m\\sigma_{i,m}\\sigma_{j,m}\n", " }\n", " \\\\\n", " ={}&\n", " \\frac{\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]T[j+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]T[j+t] \n", " -\n", " \\mu_{i,m}\\cdot m\\mu_{j,m}\n", " -\n", @@ -703,8 +703,8 @@ " \\\\\n", " ={}&\n", " \\frac{\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]T[j+t-1] \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]T[j+t] \n", " -\n", " m\\mu_{i,m}\\mu_{j,m}\n", " }{\n", @@ -721,7 +721,7 @@ "metadata": {}, "source": [ "Note: we can rearrange the pearson correlation equation as below:
\n", - "$\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" + "$\\sum \\limits_{t=0}^{m-1}T[i+t]T[j+t] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" ] }, { @@ -767,7 +767,7 @@ }, { "cell_type": "markdown", - "id": "51235736", + "id": "538ba69e", "metadata": {}, "source": [ "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequence with itself is 1." @@ -1154,10 +1154,10 @@ "$$\n", "\\begin{align}\n", " f(\\mu^{'},\\sigma^{'}) ={}&\n", - " \\sum \\limits_{t=1}^{m}\\alpha_{t}^{2}\n", + " \\sum \\limits_{t=0}^{m-1}\\alpha_{t}^{2}\n", " \\\\\n", " ={}&\n", - " \\sum \\limits_{t=1}^{m}\\alpha_{t} \\cdot \\alpha_{t}\n", + " \\sum \\limits_{t=0}^{m-1}\\alpha_{t} \\cdot \\alpha_{t}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -1180,10 +1180,10 @@ "$$\n", "\\begin{align}\n", " f_{min}(\\mu^{'},\\sigma^{'}) ={}&\n", - " \\sum\\limits_{t=1}^{m}{\n", + " \\sum\\limits_{t=0}^{m-1}{\n", " {\\alpha_{t}\n", " \\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " \\right)\n", " }}\n", " \\\\\n", @@ -1191,18 +1191,18 @@ " {\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]\\alpha_{t} \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]\\alpha_{t} \n", " - \n", - " \\sum\\limits_{t=1}^{m}\n", + " \\sum\\limits_{t=0}^{m-1}\n", " \\mu^{'}\\alpha_{t}\n", " \\right)\n", " - \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[j+t-1]\\alpha_{t} \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[j+t]\\alpha_{t} \n", " - \n", - " \\sum\\limits_{t=1}^{m}\n", + " \\sum\\limits_{t=0}^{m-1}\n", " \\mu_{j,m+k}\\alpha_{t}\n", " \\right)\n", " } \n", @@ -1211,17 +1211,17 @@ " {\n", " \\frac{1}{\\sigma^{'}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}\n", - " T[i+t-1]\\alpha_{t} \n", + " \\sum\\limits_{t=0}^{m-1}\n", + " T[i+t]\\alpha_{t} \n", " - \n", - " \\mu^{'}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\mu^{'}\\sum\\limits_{t=0}^{m-1}\\alpha_{t}\n", " \\right)\n", " - \n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} \n", + " \\sum\\limits_{t=0}^{m-1}T[j+t]\\alpha_{t} \n", " - \n", - " \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}\\alpha_{t}\n", + " \\mu_{j,m+k}\\sum\\limits_{t=0}^{m-1}\\alpha_{t}\n", " \\right)\n", " } \n", " \\\\\n", @@ -1234,7 +1234,7 @@ "id": "4a9e3f03", "metadata": {}, "source": [ - "And, now with help of eq(7), $\\sum\\limits_{t=1}^{m}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=1}^{m}{T[i+t-1]\\alpha_{t}}=0$, we will have:" + "And, now with help of eq(7), $\\sum\\limits_{t=0}^{m-1}{\\alpha_{t}}=0$, and the eq(9), $\\sum\\limits_{t=0}^{m-1}{T[i+t]\\alpha_{t}}=0$, we will have:" ] }, { @@ -1254,21 +1254,21 @@ " - \n", " \\frac{1}{\\sigma_{j,m}}\n", " \\left(\n", - " \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0\n", + " \\sum\\limits_{t=0}^{m-1}T[j+t]\\alpha_{t} - \\mu_{j,m+k}\\cdot 0\n", " \\right)\n", " } \n", " \\\\ \n", " ={}&\n", " {\n", - " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=1}^{m}T[j+t-1]\\alpha_{t}\n", + " - \\frac{1}{\\sigma_{j,m}} \\sum\\limits_{t=0}^{m-1}T[j+t]\\alpha_{t}\n", " } \n", " \\\\\n", " ={}&\n", " {\n", " - \\frac{1}{\\sigma_{j,m}} \n", - " \\sum\\limits_{t=1}^{m}{\\left[\n", - " T[j+t-1]\\left(\n", - " \\frac{T[i+t-1] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t-1] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", + " \\sum\\limits_{t=0}^{m-1}{\\left[\n", + " T[j+t]\\left(\n", + " \\frac{T[i+t] - \\mu^{'}}{\\sigma^{'}} - \\frac{T[j+t] - \\mu_{j,m+k}}{\\sigma_{j,m}}\n", " \\right)\n", " \\right]\n", " }\n", @@ -1277,9 +1277,9 @@ " ={}&\n", " {\n", " - \\frac{1}{\\sigma_{j,m}} \n", - " \\sum\\limits_{t=1}^{m}{\n", + " \\sum\\limits_{t=0}^{m-1}{\n", " \\left(\n", - " \\frac{T[i+t-1]T[j+t-1] - \\mu^{'}T[j+t-1]}{\\sigma^{'}} - \\frac{T[j+t-1]T[j+t-1] - \\mu_{j,m+k}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\frac{T[i+t]T[j+t] - \\mu^{'}T[j+t]}{\\sigma^{'}} - \\frac{T[j+t]T[j+t] - \\mu_{j,m+k}T[j+t]}{\\sigma_{j,m}}\n", " \\right)\n", " }\n", " } \n", @@ -1288,9 +1288,9 @@ " {- \\frac{1}{\\sigma_{j,m}} \n", " {\n", " \\left(\n", - " \\frac{\\sum\\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - \\mu^{'}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma^{'}} \n", + " \\frac{\\sum\\limits_{t=0}^{m-1}T[i+t]T[j+t] - \\mu^{'}\\sum\\limits_{t=0}^{m-1}T[j+t]}{\\sigma^{'}} \n", " - \n", - " \\frac{\\sum\\limits_{t=1}^{m}T[j+t-1]T[j+t-1] - \\mu_{j,m+k}\\sum\\limits_{t=1}^{m}T[j+t-1]}{\\sigma_{j,m}}\n", + " \\frac{\\sum\\limits_{t=0}^{m-1}T[j+t]T[j+t] - \\mu_{j,m+k}\\sum\\limits_{t=0}^{m-1}T[j+t]}{\\sigma_{j,m}}\n", " \\right)\n", " }\n", " } \n", @@ -1515,7 +1515,7 @@ " \\\\\n", " \\\\\n", " \\rho_{ij} ={}& \n", - " \\frac{\\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", + " \\frac{\\sum \\limits_{t=0}^{m-1}T[i+t]T[j+t] - m\\mu_{i,m}\\mu_{j,m} }{m\\sigma_{i,m}\\sigma_{j,m}}\n", " \\\\\n", "\\end{align}\n", "$$\n" @@ -1559,7 +1559,7 @@ "id": "a4f11acc", "metadata": {}, "source": [ - "We start with eq(4), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=1}^{m} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(2). Therefore:" + "We start with eq(4), $f(\\mu^{'}, \\sigma^{'}) = \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}}$, and we replace $\\alpha_{t}$ with its equivalent term, see eq(2). Therefore:" ] }, { @@ -1571,16 +1571,16 @@ "$$\n", "\\begin{align}\n", "f(\\mu^{'},\\sigma^{'}) ={}& \n", - " \\sum \\limits_{t=1}^{m}\n", + " \\sum \\limits_{t=0}^{m-1}\n", " \\left(\n", " \\frac{\n", - " T[i+t-1] - \\mu^{'}\n", + " T[i+t] - \\mu^{'}\n", " }{\n", " \\sigma^{'}\n", " } \n", " - \n", " \\frac{\n", - " T[j+t-1] - \\mu_{j,m+k}\n", + " T[j+t] - \\mu_{j,m+k}\n", " }{\n", " \\sigma_{j,m}\n", " }\n", @@ -1607,19 +1607,19 @@ "\n", "$$\n", "\\begin{align}\n", - "f(\\mu^{'},\\sigma^{'}) ={}& \n", - " \\sum \\limits_{t=1}^{m}\n", + " f(\\mu^{'},\\sigma^{'}) ={}& \n", + " \\sum \\limits_{t=0}^{m-1}\n", " \\left[\n", " \\left(\n", " \\frac{\n", - " T[i+t-1] - \\mu^{'}\n", + " T[i+t] - \\mu^{'}\n", " }{\n", " \\sigma^{'}\n", " }\\right)^{2}\n", " +\n", " \\left(\n", " \\frac{\n", - " T[j+t-1] - \\mu_{j,m+k}\n", + " T[j+t] - \\mu_{j,m+k}\n", " }{\n", " \\sigma_{j,m}\n", " }\n", @@ -1627,12 +1627,12 @@ " -\n", " 2\n", " \\left(\\frac{\n", - " T[i+t-1] - \\mu^{'}\n", + " T[i+t] - \\mu^{'}\n", " }{\n", " \\sigma^{'}\n", " }\\right)\n", " \\left(\\frac{\n", - " T[j+t-1] - \\mu_{j,m+k}\n", + " T[j+t] - \\mu_{j,m+k}\n", " }{\n", " \\sigma_{j,m}\n", " }\n", @@ -1641,18 +1641,18 @@ " \\\\\n", " \\\\\n", " ={}&\n", - " \\sum \\limits_{t=1}^{m}\n", + " \\sum \\limits_{t=0}^{m-1}\n", " \\left[\n", " \\left(\n", " \\frac{\n", - " T[i+t-1]^{2} + \\mu^{'2} - 2T[i+t-1]\\mu^{'}\n", + " T[i+t]^{2} + \\mu^{'2} - 2T[i+t]\\mu^{'}\n", " }{\n", " \\sigma^{'2}\n", " }\\right)\n", " +\n", " \\left(\n", " \\frac{\n", - " T[j+t-1]^{2} + \\mu_{j,m+k}^{2} - 2 T[j+t-1]\\mu_{j,m+k}\n", + " T[j+t]^{2} + \\mu_{j,m+k}^{2} - 2 T[j+t]\\mu_{j,m+k}\n", " }{\n", " \\sigma_{j,m}^{2}\n", " }\n", @@ -1660,9 +1660,9 @@ " -\n", " 2\n", " \\left(\\frac{\n", - " T[i+t-1]T[j+t-1] \n", - " - T[i+t-1]\\mu_{j,m+k}\n", - " - T[j+t-1]\\mu^{'}\n", + " T[i+t]T[j+t] \n", + " - T[i+t]\\mu_{j,m+k}\n", + " - T[j+t]\\mu^{'}\n", " + \\mu^{'}\\mu_{j,m+k}\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", @@ -1670,25 +1670,23 @@ " \\right)\n", " \\right]\n", " \\\\\n", + " \\\\\n", " ={}&\n", " \\frac{\n", - " \\sum \\limits_{t=1}^{m}T[i+t-1]^{2} + \\sum \\limits_{t=1}^{m}\\mu^{'2} - 2\\mu^{'}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", + " \\sum \\limits_{t=0}^{m-1}T[i+t]^{2} + \\sum \\limits_{t=0}^{m-1}\\mu^{'2} - 2\\mu^{'}\\sum \\limits_{t=0}^{m-1}T[i+t]\n", " }{\n", " \\sigma^{'2}\n", " }\n", " +\n", " \\frac{\n", - " \\sum \\limits_{t=1}^{m}T[j+t-1]^{2} + \\sum \\limits_{t=1}^{m}\\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[j+t-1]\n", - " }{\n", - " \\sigma_{j,m}^{2}\n", - " }\n", + " \\sum \\limits_{t=0}^{m-1}T[j+t]^{2} + \\sum \\limits_{t=0}^{m-1}\\mu_{j,m+k}^{2} - 2\\mu_{j,m+k}\\sum \\limits_{t=0}^{m-1}T[j+t]}{\\sigma_{j,m}^{2}}\n", " -\n", " 2\n", " \\frac{\n", - " \\sum \\limits_{t=1}^{m}T[i+t-1]T[j+t-1] \n", - " - \\mu_{j,m+k}\\sum \\limits_{t=1}^{m}T[i+t-1]\n", - " - \\mu^{'}\\sum \\limits_{t=1}^{m}T[j+t-1]\n", - " + \\sum \\limits_{t=1}^{m}\\mu^{'}\\mu_{j,m+k}\n", + " \\sum \\limits_{t=0}^{m-1}T[i+t]T[j+t] \n", + " - \\mu_{j,m+k}\\sum \\limits_{t=0}^{m-1}T[i+t]\n", + " - \\mu^{'}\\sum \\limits_{t=0}^{m-1}T[j+t]\n", + " + \\sum \\limits_{t=0}^{m-1}\\mu^{'}\\mu_{j,m+k}\n", " }{\n", " \\sigma^{'}\\sigma_{j,m}\n", " }\n", From 94dd218713d2efc91bd2407239b3cefee5d43f22 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 16:21:40 -0600 Subject: [PATCH 46/67] minor changes --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index b6591b9cb..3436c5288 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -720,7 +720,7 @@ "id": "4880c751", "metadata": {}, "source": [ - "Note: we can rearrange the pearson correlation equation as below:
\n", + "We can rearrange the pearson correlation equation as follows:
\n", "$\\sum \\limits_{t=0}^{m-1}T[i+t]T[j+t] = m\\rho\\sigma_{i,m}\\sigma_{j,m} + m\\mu_{i,m}\\mu_{j,m}$ (\\*\\*)" ] }, @@ -767,7 +767,7 @@ }, { "cell_type": "markdown", - "id": "538ba69e", + "id": "3ab1a478", "metadata": {}, "source": [ "In the calculations above, we subsituted 1 for $\\rho_{ii}$ as the Pearson Correlation of a subsequence with itself is 1." @@ -1527,7 +1527,7 @@ "metadata": {}, "source": [ "**Note:**
\n", - "* Note that eq(12) is valid only for $\\rho_{ij} > 0$. Therefore, we can use the formula above to calculate $LB$ only if $\\rho_{ij} > 0$. \n", + "* Note that eq(12) is valid only for $\\rho_{ij} > 0$. Therefore, we can use the formula (14) to calculate $LB$ only if $\\rho_{ij} > 0$. \n", "* The pearson correlation, $\\rho_{ij}$, can be also obtained with help of $ED_{z-norm}$ between subsequences `T[i:i+m]` and `T[j:j+m]`.\n", "\n", "In fact: $d_{i,j}^{(m)} = \\sqrt{2m(1-\\rho_{ij})}$, where $d_{i,j}^{(m)}$ is the z-norm euclidean distance between two sequences of length `m` that start at index `i` and `j`.\n", @@ -2085,7 +2085,7 @@ "id": "125c27bc", "metadata": {}, "source": [ - "Therefore, according to eq(16), $f(\\mu^{'},\\sigma^{'}) = m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right]$, we have: $f(\\mu^{'},\\sigma^{'}) \\geq m$, and according to eq(2), $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can see that:" + "Therefore, according to eq(16), $f(\\mu^{'},\\sigma^{'}) = m \\left[1 + g(\\mu^{'},\\sigma^{'})\\right]$, we have: $f(\\mu^{'},\\sigma^{'}) \\geq m$, and according to eq(3), $LB = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{\\min f(\\mu^{'},\\sigma^{'})}$, we can see that:" ] }, { @@ -2179,7 +2179,7 @@ "id": "7988c834", "metadata": {}, "source": [ - "Therefore, we need to show inequation (20) is satisfied for all $\\rho_{i,j} \\geq 0$.
\n", + "Therefore, we need to show that inequation (20) is satisfied for all $\\mu^{'}$ and $\\sigma^{'}$ when $\\rho_{i,j} \\geq 0$.
\n", "We now subtitute eq(18) for $g(.)$. Thus:" ] }, From 86e0a33d24a87b8d7203bca025dfbf27bd30e3cc Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 18:43:43 -0600 Subject: [PATCH 47/67] proof read --- docs/LowerBound_Dist_Profile_Derivation.ipynb | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/docs/LowerBound_Dist_Profile_Derivation.ipynb b/docs/LowerBound_Dist_Profile_Derivation.ipynb index 3436c5288..e93c9cccf 100644 --- a/docs/LowerBound_Dist_Profile_Derivation.ipynb +++ b/docs/LowerBound_Dist_Profile_Derivation.ipynb @@ -282,7 +282,11 @@ "\\begin{align}\n", " LB ={}& \n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - " \\sqrt{\\min \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}}} \\quad (3)\n", + " \\sqrt{\\min \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}}} \n", + " \\\\\n", + " ={}&\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + " \\sqrt{\\min f(\\mu^{'}, \\sigma^{'})} \\quad (3)\n", " \\\\\n", " f(\\mu^{'}, \\sigma^{'}) ={}&\n", " \\sum \\limits_{t=0}^{m-1} {\\alpha_t^{2}} \\quad (4)\n", @@ -2124,7 +2128,7 @@ "id": "fc7711bb", "metadata": {}, "source": [ - "There is still one thing left to be done. We need to show that the LB discovered for $\\rho_{ij} \\gt 0$ is actually a global minimum. In other words, we need to show that the inequation below holds true for all $\\rho_{ij} \\gt 0$:" + "We need to show that the LB discovered for $\\rho_{ij} \\gt 0$ is actually a global minimum. In other words, we need to show that the inequation below holds true for all $\\rho_{ij} \\gt 0$:" ] }, { From 92e7840579f13c67673e30efc6231201189bca5b Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 17 Apr 2022 19:07:10 -0600 Subject: [PATCH 48/67] ADD LowerBound formula --- docs/Tutorial_VALMOD.ipynb | 61 ++++++++++++++++++++++++++++++++++---- 1 file changed, 56 insertions(+), 5 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 86e244817..366206b60 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -146,12 +146,63 @@ ] }, { - "cell_type": "code", - "execution_count": null, - "id": "71517d38", + "cell_type": "markdown", + "id": "8538f0e3", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "Lower Bound (LB) for $d(T_{j,m+k}, T_{i,m+k})$ can be calculated as follows:" + ] + }, + { + "cell_type": "markdown", + "id": "a7f08024", + "metadata": {}, + "source": [ + "**Non-normalized distance (p-norm):**" + ] + }, + { + "cell_type": "markdown", + "id": "297e8f9e", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "LB_{j,i}^{(m)} ={}& \n", + "d_{j,i}^{(m)}\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "7ff2e666", + "metadata": {}, + "source": [ + "**Normalized distance:**" + ] + }, + { + "cell_type": "markdown", + "id": "0f192dfa", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "LB_{j,i}^{(m)} ={}& \n", + "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\sqrt{\n", + "m\\left(\n", + "1 - \\max(\\rho_{j,i},0)^{2}\n", + "\\right)\n", + "}\n", + "\\\\\n", + "\\rho_{j,i} ={}& 1 - \\frac{d_{j,i}^{2}}{2m}\n", + "\\end{align}\n", + "$$\n" + ] } ], "metadata": { From bd5c133813809c85ec5b0c228b44d1722bf4ec5d Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 24 Apr 2022 09:03:16 -0600 Subject: [PATCH 49/67] Add intro on VALMOD algorithm --- docs/Tutorial_VALMOD.ipynb | 41 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 366206b60..216f5605a 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -24,6 +24,7 @@ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", + "import heapq\n", "\n", "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" ] @@ -203,6 +204,46 @@ "\\end{align}\n", "$$\n" ] + }, + { + "cell_type": "markdown", + "id": "3b82e805", + "metadata": {}, + "source": [ + "**NOTE:** A better notation might be $LB_{j,i}^{m+k, m}$ as it shows the lower bound is for subsequence of length `m+k`, and it is calculated based on $\\rho_{j,i}$ of subsequences with length `m`. However, to simplify the notaton, we avoided using `m+k`. We expect the reader to remember that the calculated lower bound LB is for subsequences of length `m+k`, as shown in the $\\sigma_{j,m+k}$." + ] + }, + { + "cell_type": "markdown", + "id": "833c4f6b", + "metadata": {}, + "source": [ + "# 3-VALMOD algorithm\n", + "The valmod algorithm discovers motifs / discords for subsequence length range `(min_m, max_m)`. The algorithm starts with performing complete scan for length `min_m`, and as we see shortly, it extracts more infomation than just Matrix Profile values and their corresponding indices. Then, it uses those information to accelerate constructing matrix profile for length `(min_m+1, max_m)`. \n", + "\n", + "The main algorithm `VALMOD`, shown as Algorithm1 of the paper (see page 13). However, before implementing this function, we first implement the functions that are being called inside this algorithm. To be consistent with the paper, we use the paper's proposed name of function as title of each section. However, we may use a different name for the function in the notebook." + ] + }, + { + "cell_type": "markdown", + "id": "f6cbecbd", + "metadata": {}, + "source": [ + "## 3-1- ComputeMatrixProfile (see page 15)\n", + "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest values of each distance profile and their indices. More precisely, it just need those indices, the first smallest value and the p-th smallest value. (The parameter `p` should be set by the user.) \n", + "\n", + "In the paper, the authors used the formula LB to convert distances to LB on the go. So, as they scan pairs of subsequences, they keep track of the matrix profile and its index for each subsequence. They also convert distances to lb using LB formula to calculate the LB values for subsequences with length `m+1`, then, they use heap structure to discover `top-p` LB values for each distance profile. However, in this notebook, we simply return the `top-p` distances as their corresponding LB values can be calculated without losing the order. This can help us avoid performing such conversion on all elements of each distance profile, and instead, just calculate `LB` for the `top-p` smallest distances.\n", + "\n", + "**NOTE:** In STUMPY, parameter `p` is used to calculate the p-norm distance. To this end, we use a different name for the parameter. Let us call it `n_LB`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a6144a1", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 34441e092dafe2ddd9ad07be61aab2cb8f811b47 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 24 Apr 2022 18:57:00 -0600 Subject: [PATCH 50/67] Add section 3 (core idea) and section 4 (implementation) --- docs/Tutorial_VALMOD.ipynb | 287 +++++++++++++++++++++++++++++++++++-- 1 file changed, 272 insertions(+), 15 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 216f5605a..e71274dcb 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 280, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -24,6 +24,7 @@ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", + "import time\n", "import heapq\n", "\n", "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" @@ -170,8 +171,8 @@ "\n", "$$\n", "\\begin{align}\n", - "LB_{j,i}^{(m)} ={}& \n", - "d_{j,i}^{(m)}\n", + "LB_{j,i}^{(m+k)} ={}& \n", + "d_{j,i}^{(m)} \\quad (1)\n", "\\end{align}\n", "$$\n" ] @@ -192,25 +193,157 @@ "\n", "$$\n", "\\begin{align}\n", - "LB_{j,i}^{(m)} ={}& \n", + "LB_{j,i}^{(m+k)} ={}& \n", "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", "\\sqrt{\n", "m\\left(\n", - "1 - \\max(\\rho_{j,i},0)^{2}\n", + "1 - \\max(\\rho^{(m)}_{j,i},0)^{2}\n", "\\right)\n", - "}\n", + "} \\quad (2)\n", "\\\\\n", - "\\rho_{j,i} ={}& 1 - \\frac{d_{j,i}^{2}}{2m}\n", "\\end{align}\n", "$$\n" ] }, { "cell_type": "markdown", - "id": "3b82e805", + "id": "f3c414f7", "metadata": {}, "source": [ - "**NOTE:** A better notation might be $LB_{j,i}^{m+k, m}$ as it shows the lower bound is for subsequence of length `m+k`, and it is calculated based on $\\rho_{j,i}$ of subsequences with length `m`. However, to simplify the notaton, we avoided using `m+k`. We expect the reader to remember that the calculated lower bound LB is for subsequences of length `m+k`, as shown in the $\\sigma_{j,m+k}$." + "And, the pearson correlation $\\rho^{(m)}_{j,i}$ can be calculated as follows: " + ] + }, + { + "cell_type": "markdown", + "id": "117f52c8", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "\\rho^{(m)}_{j,i} ={}& \n", + "\\frac{\\sum \\limits_{t=0}^{m-1}{T[i+t]T[j+t]} - m\\mu_{i,m}\\mu_{j,m}}{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (2a)\n", + "\\end{align} \n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "9d25f29d", + "metadata": {}, + "source": [ + "Alternatively, $\\rho^{(m)}{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" + ] + }, + { + "cell_type": "markdown", + "id": "ce0de3e3", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "d^{(m)}_{j,i} ={}& \n", + "\\sqrt{\n", + "2m \\left(\n", + "1-\\rho^{(m)}_{j,i}\n", + "\\right)\n", + "} \\quad {(2b)}\n", + "\\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "eb030645", + "metadata": {}, + "source": [ + "# 3- Core Idea" + ] + }, + { + "cell_type": "markdown", + "id": "7e44c53b", + "metadata": {}, + "source": [ + "The core idea of VALMOD can be explained as follows:" + ] + }, + { + "cell_type": "markdown", + "id": "419329a4", + "metadata": {}, + "source": [ + "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", + "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the distance profile for subsquence with length `min_m`.\n", + "\n", + "In other words...
\n", + "IF:" + ] + }, + { + "cell_type": "markdown", + "id": "33011ed1", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "LB^{(m+k_{1})}_{j,i} \\leq{}& \n", + "LB^{(m+k_{1})}_{j,i^{'}}\n", + "\\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "6f9db92c", + "metadata": {}, + "source": [ + "THEN:" + ] + }, + { + "cell_type": "markdown", + "id": "49a09cf9", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + "LB^{(m+k_{2})}_{j,i} \\leq{}& \n", + "LB^{(m+k_{2})}_{j,i^{'}}\n", + "\\\\\n", + "\\end{align}\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "id": "61ab5384", + "metadata": {}, + "source": [ + "where, the lower-boundns are calculated based on the distances for length `m`. " + ] + }, + { + "cell_type": "markdown", + "id": "f46bf2bc", + "metadata": {}, + "source": [ + "**Also:**
\n", + "$LB^{(m+k)}_{j}$ denotes the distance profile of subsequence `T[j:j+m+k]`, calculated based on the distance profile of `T[j,j+m]`." + ] + }, + { + "cell_type": "markdown", + "id": "f623aa60", + "metadata": {}, + "source": [ + "## 3-2: Accelerating Matrix Profile calculation\n", + "Storing all \"ranked LB\" for all indices needs a significant ampunt of memory. Instead, we can just store the `p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." ] }, { @@ -218,10 +351,10 @@ "id": "833c4f6b", "metadata": {}, "source": [ - "# 3-VALMOD algorithm\n", - "The valmod algorithm discovers motifs / discords for subsequence length range `(min_m, max_m)`. The algorithm starts with performing complete scan for length `min_m`, and as we see shortly, it extracts more infomation than just Matrix Profile values and their corresponding indices. Then, it uses those information to accelerate constructing matrix profile for length `(min_m+1, max_m)`. \n", + "# 4-VALMOD algorithm\n", + "The VALMOP algorithm (see Algorithm1 of the paper (see page 13)) discovers the matrix profile and the matrix profile indices for subsequence length range `(min_m, max_m)`.\n", "\n", - "The main algorithm `VALMOD`, shown as Algorithm1 of the paper (see page 13). However, before implementing this function, we first implement the functions that are being called inside this algorithm. To be consistent with the paper, we use the paper's proposed name of function as title of each section. However, we may use a different name for the function in the notebook." + "In this section, we implement the functions that are being called by VALMOD algorithm, followed by the implementation of VALMOD algorithm." ] }, { @@ -229,18 +362,142 @@ "id": "f6cbecbd", "metadata": {}, "source": [ - "## 3-1- ComputeMatrixProfile (see page 15)\n", + "## 4-1- ComputeMatrixProfile (see page 15)\n", "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest values of each distance profile and their indices. More precisely, it just need those indices, the first smallest value and the p-th smallest value. (The parameter `p` should be set by the user.) \n", "\n", "In the paper, the authors used the formula LB to convert distances to LB on the go. So, as they scan pairs of subsequences, they keep track of the matrix profile and its index for each subsequence. They also convert distances to lb using LB formula to calculate the LB values for subsequences with length `m+1`, then, they use heap structure to discover `top-p` LB values for each distance profile. However, in this notebook, we simply return the `top-p` distances as their corresponding LB values can be calculated without losing the order. This can help us avoid performing such conversion on all elements of each distance profile, and instead, just calculate `LB` for the `top-p` smallest distances.\n", "\n", - "**NOTE:** In STUMPY, parameter `p` is used to calculate the p-norm distance. To this end, we use a different name for the parameter. Let us call it `n_LB`." + "**NOTE:** In STUMPY, parameter `p` is used to calculate the p-norm distance. To this end, we use a different name for the parameter. Let us call it `h`." + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "id": "279e54e3", + "metadata": {}, + "outputs": [], + "source": [ + "def naive_VALMODstump(T, m, h = 5):\n", + " \"\"\"\n", + " Explain\n", + " \"\"\"\n", + " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", + " \n", + " distance_matrix = np.array(\n", + " [core.mass(Q, T) for Q in core.rolling_window(T, m)]\n", + " )\n", + " \n", + " n_T = T.shape[0]\n", + " l = n_T - m + 1\n", + " \n", + " P = np.full(l, np.NINF, dtype=np.float64)\n", + " I = np.full(l, -1, dtype=np.int64)\n", + " \n", + " DP = [] #distance profile\n", + " for i in range(l):\n", + " tmp = [(np.NINF,-1)] * h #to use max_heap, I flipped the sign.\n", + " heapq.heapify(tmp)\n", + " DP.append(tmp)\n", + " \n", + " diags = np.arange(excl_zone + 1, l)\n", + " for k in diags:\n", + " for i in range(0, n_T - m + 1 - k):\n", + " D = -1 * distance_matrix[i, i + k]\n", + " \n", + " if D > DP[i][0][0]: \n", + " heapq.heapreplace(DP[i], (D, i+k))\n", + " if D > P[i]:\n", + " P[i] = D\n", + " I[i] = i+k\n", + " \n", + " if D > DP[i+k][0][0]:\n", + " heapq.heapreplace(DP[i+k], (D, i))\n", + " if D > P[i+k]:\n", + " P[i+k] = D\n", + " I[i+k] = i\n", + " \n", + " \n", + " # post-processing\n", + " P = -1 * P \n", + " DP_larget_dist = np.asarray([-1 * item[0][0] for item in DP], dtype=np.float64)\n", + " DP_all_indices = np.asarray([[pair[1] for pair in item] for item in DP], dtype=np.int64)\n", + " \n", + " return P, I, DP_larget_dist, DP_all_indices" ] }, + { + "cell_type": "code", + "execution_count": 284, + "id": "915eeabb", + "metadata": {}, + "outputs": [], + "source": [ + "seed = 0\n", + "np.random.seed(seed)\n", + "T = np.random.uniform(low=-100, high=100, size=1000)\n", + "m = 50" + ] + }, + { + "cell_type": "code", + "execution_count": 285, + "id": "a025035b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "running time: 1.074126958847046\n" + ] + } + ], + "source": [ + "tic = time.time()\n", + "P, I, DP_larget_dist, DP_all_indices = naive_METAstump(T, m, h=5)\n", + "toc = time.time()\n", + "print('running time: ', toc-tic)" + ] + }, + { + "cell_type": "code", + "execution_count": 286, + "id": "f3e1d82d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[557, 281, 279, 157, 667],\n", + " [827, 282, 280, 158, 668],\n", + " [828, 283, 669, 281, 159],\n", + " ...,\n", + " [687, 316, 410, 218, 886],\n", + " [587, 887, 219, 244, 411],\n", + " [530, 588, 193, 412, 220]], dtype=int64)" + ] + }, + "execution_count": 286, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "DP_all_indices" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f9739437", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, - "id": "9a6144a1", + "id": "10b4684a", "metadata": {}, "outputs": [], "source": [] From ab36c8aa3e34c639949bd51faeed31e272c21e57 Mon Sep 17 00:00:00 2001 From: ninimama Date: Sun, 24 Apr 2022 22:02:04 -0600 Subject: [PATCH 51/67] Elaborate sections 2,3,4 --- docs/Tutorial_VALMOD.ipynb | 190 +++++++++++++++++++++++++++++-------- 1 file changed, 153 insertions(+), 37 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index e71274dcb..e281850e8 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -207,7 +207,7 @@ }, { "cell_type": "markdown", - "id": "f3c414f7", + "id": "530e86c4", "metadata": {}, "source": [ "And, the pearson correlation $\\rho^{(m)}_{j,i}$ can be calculated as follows: " @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "117f52c8", + "id": "6d015362", "metadata": {}, "source": [ "\n", @@ -229,7 +229,7 @@ }, { "cell_type": "markdown", - "id": "9d25f29d", + "id": "b792cb2b", "metadata": {}, "source": [ "Alternatively, $\\rho^{(m)}{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" @@ -237,7 +237,7 @@ }, { "cell_type": "markdown", - "id": "ce0de3e3", + "id": "4a905185", "metadata": {}, "source": [ "\n", @@ -256,7 +256,7 @@ }, { "cell_type": "markdown", - "id": "eb030645", + "id": "40da3ca9", "metadata": {}, "source": [ "# 3- Core Idea" @@ -264,7 +264,7 @@ }, { "cell_type": "markdown", - "id": "7e44c53b", + "id": "f83325aa", "metadata": {}, "source": [ "The core idea of VALMOD can be explained as follows:" @@ -272,7 +272,7 @@ }, { "cell_type": "markdown", - "id": "419329a4", + "id": "77748a27", "metadata": {}, "source": [ "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", @@ -284,7 +284,7 @@ }, { "cell_type": "markdown", - "id": "33011ed1", + "id": "c2e1782a", "metadata": {}, "source": [ "\n", @@ -299,7 +299,7 @@ }, { "cell_type": "markdown", - "id": "6f9db92c", + "id": "a49074ff", "metadata": {}, "source": [ "THEN:" @@ -307,7 +307,7 @@ }, { "cell_type": "markdown", - "id": "49a09cf9", + "id": "ce9d6f16", "metadata": {}, "source": [ "\n", @@ -322,7 +322,7 @@ }, { "cell_type": "markdown", - "id": "61ab5384", + "id": "01c13220", "metadata": {}, "source": [ "where, the lower-boundns are calculated based on the distances for length `m`. " @@ -330,7 +330,7 @@ }, { "cell_type": "markdown", - "id": "f46bf2bc", + "id": "a3edd469", "metadata": {}, "source": [ "**Also:**
\n", @@ -339,7 +339,7 @@ }, { "cell_type": "markdown", - "id": "f623aa60", + "id": "ee30da36", "metadata": {}, "source": [ "## 3-2: Accelerating Matrix Profile calculation\n", @@ -363,23 +363,140 @@ "metadata": {}, "source": [ "## 4-1- ComputeMatrixProfile (see page 15)\n", - "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest values of each distance profile and their indices. More precisely, it just need those indices, the first smallest value and the p-th smallest value. (The parameter `p` should be set by the user.) \n", + "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `p-th` smallest value of each distance profile and all the indices of `top-p` smallest values. \n", "\n", - "In the paper, the authors used the formula LB to convert distances to LB on the go. So, as they scan pairs of subsequences, they keep track of the matrix profile and its index for each subsequence. They also convert distances to lb using LB formula to calculate the LB values for subsequences with length `m+1`, then, they use heap structure to discover `top-p` LB values for each distance profile. However, in this notebook, we simply return the `top-p` distances as their corresponding LB values can be calculated without losing the order. This can help us avoid performing such conversion on all elements of each distance profile, and instead, just calculate `LB` for the `top-p` smallest distances.\n", + "In the paper, the authors used the LB formula to convert distances to LB on the go. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used heap data structure to store `top-p` smallest LB values for each distance profile. " + ] + }, + { + "cell_type": "markdown", + "id": "15cce626", + "metadata": {}, + "source": [ + "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", + "
\n", + "In addition to matrix profile (P) and matrix profile indices (I), we just return the p-th smallest value of each \"distance profile\" and the indices for all top-p smallest valus of each \"distance profile\". \n", + "* In addition to storing the \"indices\" of the top-p smallest distances for each distance profile, we just need to store the p-th (not all top-p) smallest distance of each distance profile (see line 8 of the algorithm 4 provided in the paper). Therefore, at the end of algorith3, we return p-th smallest value of each distance profile rather than all top-p smallest values of each distance profile.\n", + "* We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As proved below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the p-th smallest value of distance profile and then calculate LB with help of eq(2)." + ] + }, + { + "cell_type": "markdown", + "id": "2064289b", + "metadata": {}, + "source": [ + "IF: \n", "\n", - "**NOTE:** In STUMPY, parameter `p` is used to calculate the p-norm distance. To this end, we use a different name for the parameter. Let us call it `h`." + "$$\n", + "\\begin{align}\n", + "d^{(m)}_{j,i} \n", + "\\geq{}&{}\n", + "d^{(m)}_{j,i'}\n", + "\\\\\n", + "\\end{align}\n", + "$$\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "da181848", + "metadata": {}, + "source": [ + "THEN:\n", + "\n", + "$$\n", + "\\begin{align}\n", + "\\rho^{(m)}_{j,i} \n", + "\\leq&{}\n", + "\\rho^{(m)}_{j,i'}\n", + "\\\\\n", + "\\max(\\rho^{(m)}_{j,i}, 0) \n", + "\\leq&{}\n", + "\\max(\\rho^{(m)}_{j,i'},0)\n", + "\\\\\n", + "\\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", + "\\leq&{}\n", + "\\left(\\max(\\rho^{(m)}_{j,i'},0)\\right)^{2}\n", + "\\\\\n", + "1 - \\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", + "\\geq&{}\n", + "1 - \\left(\\max(\\rho^{(m)}_{j,i'},0)\\right)^{2}\n", + "\\\\\n", + "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\sqrt{m\n", + "\\left[\n", + "1 - \\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", + "\\right]\n", + "}\n", + "\\geq&{}\n", + "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\sqrt{m\n", + "\\left[\n", + "1 - \\left(\\max(\\rho^{(m)}_{j,i'}, 0)\\right)^{2}\n", + "\\right]\n", + "}\n", + "\\\\\n", + "LB^{(m)}_{j,i} \\geq{}& \n", + "LB^{(m)}_{j,i'}\n", + "\\\\\n", + "\\end{align}\n", + "$$\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "7e10dc4a", + "metadata": {}, + "source": [ + "Therefore, if the ranked distance profile and its ranked lower bound have the same order. we can skip line19 of Algorithm3 and calculate LB once we discover p-th smallest value of distance profile at the end of algorithm 3. In our implementation, we simply return the p-th smallest value as it can be easily calculated outside of the function." + ] + }, + { + "cell_type": "markdown", + "id": "57fbdf38", + "metadata": {}, + "source": [ + "**NOTE (2):** \n", + "
\n", + "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, we use the name `h` to denote the number of smallest LB values that should be considered for each distance profile." ] }, { "cell_type": "code", - "execution_count": 263, - "id": "279e54e3", + "execution_count": 304, + "id": "7313cb44", "metadata": {}, "outputs": [], "source": [ - "def naive_VALMODstump(T, m, h = 5):\n", + "def VALMODstump(T, m, h = 5):\n", " \"\"\"\n", - " Explain\n", + " This function takes the input time series `T`, window size `m`, and, \n", + " in addition to matrix profile and matrix profile indicecs, it returns the indices of top-h smallest value \n", + " and the h-th smallest value for each distance profile.\n", + " \n", + " This is a naive implementation in a sense that it calculate the whole distance_matrix right in the beginning \n", + " of the algorithm. The structure of this code is based on the stump function available in stumpy/test/naive.py.\n", + " \n", + " Parameters\n", + " ----------\n", + " T : numpy.ndarray\n", + " \n", + " m : int\n", + " \n", + " h : int\n", + " \n", + " Returns\n", + " ---------\n", + " P :\n", + " \n", + " I :\n", + " \n", + " DP_larget_dist : \n", + " \n", + " DP_all_indices : \n", + " \n", " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", @@ -390,12 +507,12 @@ " n_T = T.shape[0]\n", " l = n_T - m + 1\n", " \n", - " P = np.full(l, np.NINF, dtype=np.float64)\n", + " P = np.full(l, np.NINF, dtype=np.float64) \n", " I = np.full(l, -1, dtype=np.int64)\n", " \n", - " DP = [] #distance profile\n", + " DP = []\n", " for i in range(l):\n", - " tmp = [(np.NINF,-1)] * h #to use max_heap, I flipped the sign.\n", + " tmp = [(np.NINF,-1)] * h\n", " heapq.heapify(tmp)\n", " DP.append(tmp)\n", " \n", @@ -405,18 +522,17 @@ " D = -1 * distance_matrix[i, i + k]\n", " \n", " if D > DP[i][0][0]: \n", - " heapq.heapreplace(DP[i], (D, i+k))\n", + " heapq.heappushpop(DP[i], item=(D, i+k))\n", " if D > P[i]:\n", " P[i] = D\n", " I[i] = i+k\n", " \n", " if D > DP[i+k][0][0]:\n", - " heapq.heapreplace(DP[i+k], (D, i))\n", + " heapq.heappushpop(DP[i+k], item=(D, i))\n", " if D > P[i+k]:\n", " P[i+k] = D\n", " I[i+k] = i\n", - " \n", - " \n", + " \n", " # post-processing\n", " P = -1 * P \n", " DP_larget_dist = np.asarray([-1 * item[0][0] for item in DP], dtype=np.float64)\n", @@ -427,8 +543,8 @@ }, { "cell_type": "code", - "execution_count": 284, - "id": "915eeabb", + "execution_count": 305, + "id": "46815234", "metadata": {}, "outputs": [], "source": [ @@ -440,15 +556,15 @@ }, { "cell_type": "code", - "execution_count": 285, - "id": "a025035b", + "execution_count": 306, + "id": "63e9acea", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "running time: 1.074126958847046\n" + "running time: 1.078115463256836\n" ] } ], @@ -461,8 +577,8 @@ }, { "cell_type": "code", - "execution_count": 286, - "id": "f3e1d82d", + "execution_count": 307, + "id": "d0953028", "metadata": {}, "outputs": [ { @@ -477,7 +593,7 @@ " [530, 588, 193, 412, 220]], dtype=int64)" ] }, - "execution_count": 286, + "execution_count": 307, "metadata": {}, "output_type": "execute_result" } @@ -489,7 +605,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f9739437", + "id": "e0f83c16", "metadata": {}, "outputs": [], "source": [] @@ -497,7 +613,7 @@ { "cell_type": "code", "execution_count": null, - "id": "10b4684a", + "id": "7b4a04dd", "metadata": {}, "outputs": [], "source": [] From 4ae4d26ea7edbf4a68e57d2a44c0d1c7c8f05857 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 25 Apr 2022 00:24:33 -0600 Subject: [PATCH 52/67] Improve readability --- docs/Tutorial_VALMOD.ipynb | 227 ++++++++++++++++++++++--------------- 1 file changed, 135 insertions(+), 92 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index e281850e8..a6b897202 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -207,7 +207,7 @@ }, { "cell_type": "markdown", - "id": "530e86c4", + "id": "6fc1437c", "metadata": {}, "source": [ "And, the pearson correlation $\\rho^{(m)}_{j,i}$ can be calculated as follows: " @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "6d015362", + "id": "be0504c8", "metadata": {}, "source": [ "\n", @@ -229,7 +229,7 @@ }, { "cell_type": "markdown", - "id": "b792cb2b", + "id": "de7efb95", "metadata": {}, "source": [ "Alternatively, $\\rho^{(m)}{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" @@ -237,7 +237,7 @@ }, { "cell_type": "markdown", - "id": "4a905185", + "id": "30baf843", "metadata": {}, "source": [ "\n", @@ -256,7 +256,7 @@ }, { "cell_type": "markdown", - "id": "40da3ca9", + "id": "58f786c0", "metadata": {}, "source": [ "# 3- Core Idea" @@ -264,7 +264,7 @@ }, { "cell_type": "markdown", - "id": "f83325aa", + "id": "1ac2547c", "metadata": {}, "source": [ "The core idea of VALMOD can be explained as follows:" @@ -272,11 +272,11 @@ }, { "cell_type": "markdown", - "id": "77748a27", + "id": "91b69e91", "metadata": {}, "source": [ "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", - "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the distance profile for subsquence with length `min_m`.\n", + "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in the ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the distance profile for subsquence with length `min_m`.\n", "\n", "In other words...
\n", "IF:" @@ -284,7 +284,7 @@ }, { "cell_type": "markdown", - "id": "c2e1782a", + "id": "3f4fcb84", "metadata": {}, "source": [ "\n", @@ -299,7 +299,7 @@ }, { "cell_type": "markdown", - "id": "a49074ff", + "id": "573a90f3", "metadata": {}, "source": [ "THEN:" @@ -307,14 +307,52 @@ }, { "cell_type": "markdown", - "id": "ce9d6f16", + "id": "c0a4e7df", "metadata": {}, "source": [ "\n", "$$\n", "\\begin{align}\n", + "\\frac{\n", + "\\sigma_{j,m+k_{1}}}\n", + "{\\sigma_{j,m+k_{2}}\n", + "}\n", + "LB^{(m+k_{1})}_{j,i} \n", + "\\leq{}&\n", + "\\frac{\n", + "\\sigma_{j,m+k_{1}}}\n", + "{\\sigma_{j,m+k_{2}}\n", + "}\n", + "LB^{(m+k_{1})}_{j,i'}\n", + "\\\\\n", + "\\frac{\n", + "\\sigma_{j,m+k_{1}}}\n", + "{\\sigma_{j,m+k_{2}}\n", + "}\n", + "\\left[\n", + "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k_{1}}}\n", + "\\sqrt{\n", + "m\\left(\n", + "1 - \\max(\\rho^{(m)}_{j,i},0)^{2}\n", + "\\right)\n", + "}\n", + "\\right]\n", + "\\leq{}&\n", + "\\frac{\n", + "\\sigma_{j,m+k_{1}}}\n", + "{\\sigma_{j,m+k_{2}}\n", + "}\n", + "\\left[\n", + "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k_{1}}}\n", + "\\sqrt{\n", + "m\\left(\n", + "1 - \\max(\\rho^{(m)}_{j,i'},0)^{2}\n", + "\\right)\n", + "}\n", + "\\right]\n", + "\\\\\n", "LB^{(m+k_{2})}_{j,i} \\leq{}& \n", - "LB^{(m+k_{2})}_{j,i^{'}}\n", + "LB^{(m+k_{2})}_{j,i'}\n", "\\\\\n", "\\end{align}\n", "$$\n" @@ -322,7 +360,7 @@ }, { "cell_type": "markdown", - "id": "01c13220", + "id": "5328138d", "metadata": {}, "source": [ "where, the lower-boundns are calculated based on the distances for length `m`. " @@ -330,20 +368,11 @@ }, { "cell_type": "markdown", - "id": "a3edd469", - "metadata": {}, - "source": [ - "**Also:**
\n", - "$LB^{(m+k)}_{j}$ denotes the distance profile of subsequence `T[j:j+m+k]`, calculated based on the distance profile of `T[j,j+m]`." - ] - }, - { - "cell_type": "markdown", - "id": "ee30da36", + "id": "ad925832", "metadata": {}, "source": [ "## 3-2: Accelerating Matrix Profile calculation\n", - "Storing all \"ranked LB\" for all indices needs a significant ampunt of memory. Instead, we can just store the `p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." + "Storing all \"ranked LB\" for all indices needs a significant ampunt of memory. Instead, we can just store the `top-p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." ] }, { @@ -352,9 +381,7 @@ "metadata": {}, "source": [ "# 4-VALMOD algorithm\n", - "The VALMOP algorithm (see Algorithm1 of the paper (see page 13)) discovers the matrix profile and the matrix profile indices for subsequence length range `(min_m, max_m)`.\n", - "\n", - "In this section, we implement the functions that are being called by VALMOD algorithm, followed by the implementation of VALMOD algorithm." + "The VALMOP algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions that are being called by VALMOD algorithm, followed by the implementation of VALMOD algorithm itself." ] }, { @@ -362,27 +389,24 @@ "id": "f6cbecbd", "metadata": {}, "source": [ - "## 4-1- ComputeMatrixProfile (see page 15)\n", - "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `p-th` smallest value of each distance profile and all the indices of `top-p` smallest values. \n", + "## 4-1- ComputeMatrixProfile (Algorith3 on page 15)\n", + "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their indices as well.\n", "\n", - "In the paper, the authors used the LB formula to convert distances to LB on the go. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used heap data structure to store `top-p` smallest LB values for each distance profile. " + "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used heap data structure to store `top-p` smallest LB values for each distance profile. " ] }, { "cell_type": "markdown", - "id": "15cce626", + "id": "cb41990b", "metadata": {}, "source": [ "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", - "
\n", - "In addition to matrix profile (P) and matrix profile indices (I), we just return the p-th smallest value of each \"distance profile\" and the indices for all top-p smallest valus of each \"distance profile\". \n", - "* In addition to storing the \"indices\" of the top-p smallest distances for each distance profile, we just need to store the p-th (not all top-p) smallest distance of each distance profile (see line 8 of the algorithm 4 provided in the paper). Therefore, at the end of algorith3, we return p-th smallest value of each distance profile rather than all top-p smallest values of each distance profile.\n", - "* We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As proved below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the p-th smallest value of distance profile and then calculate LB with help of eq(2)." + "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As proved below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the top-p smallest value of distance profile and then calculate their corresponding LB value." ] }, { "cell_type": "markdown", - "id": "2064289b", + "id": "6b1327a0", "metadata": {}, "source": [ "IF: \n", @@ -400,7 +424,7 @@ }, { "cell_type": "markdown", - "id": "da181848", + "id": "41714628", "metadata": {}, "source": [ "THEN:\n", @@ -447,104 +471,123 @@ }, { "cell_type": "markdown", - "id": "7e10dc4a", + "id": "06f3b5d2", "metadata": {}, "source": [ - "Therefore, if the ranked distance profile and its ranked lower bound have the same order. we can skip line19 of Algorithm3 and calculate LB once we discover p-th smallest value of distance profile at the end of algorithm 3. In our implementation, we simply return the p-th smallest value as it can be easily calculated outside of the function." + "This proves that the ranked distance profile and its ranked lower bound have the same order." ] }, { "cell_type": "markdown", - "id": "57fbdf38", + "id": "29f02f99", "metadata": {}, "source": [ "**NOTE (2):** \n", "
\n", - "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, we use the name `h` to denote the number of smallest LB values that should be considered for each distance profile." + "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, we use the name `n` to denote the number of smallest LB values that should be considered for each distance profile." ] }, { "cell_type": "code", - "execution_count": 304, - "id": "7313cb44", + "execution_count": 396, + "id": "12c7d922", "metadata": {}, "outputs": [], "source": [ - "def VALMODstump(T, m, h = 5):\n", + "def _VALMOD_stump(T, m, n = 5):\n", " \"\"\"\n", - " This function takes the input time series `T`, window size `m`, and, \n", - " in addition to matrix profile and matrix profile indicecs, it returns the indices of top-h smallest value \n", - " and the h-th smallest value for each distance profile.\n", - " \n", - " This is a naive implementation in a sense that it calculate the whole distance_matrix right in the beginning \n", - " of the algorithm. The structure of this code is based on the stump function available in stumpy/test/naive.py.\n", + " This function takes the input time series `T`, window size `m`, and, the number of elements `n` that \n", + " should be stored for each distance profie. In addition to the matrix profile and the matrix profile indicecs, \n", + " this function returns the indices of top-n smallest value and their corresponding indices for each distance profile.\n", " \n", " Parameters\n", " ----------\n", " T : numpy.ndarray\n", - " \n", + " The time series or sequence for which to compute the matrix profile\n", + " \n", " m : int\n", - " \n", - " h : int\n", + " Window size\n", + " \n", + " n : int\n", + " The number of elements stored for each distance profile\n", " \n", " Returns\n", " ---------\n", - " P :\n", + " P : numpy.ndarray\n", + " The matrix profile\n", + " \n", + " I : numpy.ndarray\n", + " The matrix profile indices\n", + " \n", + " Partial_DP : numpy.ndarray\n", + " The partial distance profiles that contain their `n` smallest values \n", + " \n", + " Partial_DP_indices : numpy.ndarray\n", + " The indices corresponding to Partial_DP\n", + " \n", + " Notes\n", + " -----\n", + " https://doi.org/10.48550/arXiv.2008.13447\n", " \n", - " I :\n", + " see Algorithm 3\n", " \n", - " DP_larget_dist : \n", " \n", - " DP_all_indices : \n", + " This is a naive implementation in a sense that it calculates the whole distance_matrix right in the beginning \n", + " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", + " available in stumpy/test/naive.py.\n", " \n", + " In contrast to the original paper, we simply return the `h` smallest values for each distance profile as their order \n", + " is the same as their corresponding LB values. This can help us to compute the P and I in a clean way.\n", " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", + " #naive calculaton of distance_matrix\n", " distance_matrix = np.array(\n", " [core.mass(Q, T) for Q in core.rolling_window(T, m)]\n", " )\n", " \n", - " n_T = T.shape[0]\n", - " l = n_T - m + 1\n", + " k = T.shape[0] - m + 1\n", " \n", - " P = np.full(l, np.NINF, dtype=np.float64) \n", - " I = np.full(l, -1, dtype=np.int64)\n", + " P = np.full(k, np.NINF, dtype=np.float64) \n", + " I = np.full(k, -1, dtype=np.int64)\n", " \n", " DP = []\n", - " for i in range(l):\n", - " tmp = [(np.NINF,-1)] * h\n", + " for _ in range(k):\n", + " tmp = [(np.NINF,-1)] * n\n", " heapq.heapify(tmp)\n", " DP.append(tmp)\n", " \n", - " diags = np.arange(excl_zone + 1, l)\n", - " for k in diags:\n", - " for i in range(0, n_T - m + 1 - k):\n", - " D = -1 * distance_matrix[i, i + k]\n", + " diags = np.arange(excl_zone + 1, k)\n", + " for i in diags: \n", + " for j in range(0, k - i): \n", + " D = -1 * distance_matrix[j, j + i] \n", " \n", - " if D > DP[i][0][0]: \n", - " heapq.heappushpop(DP[i], item=(D, i+k))\n", - " if D > P[i]:\n", - " P[i] = D\n", - " I[i] = i+k\n", + " if D > DP[j][0][0]: \n", + " heapq.heappushpop(DP[j], (D, j+i)) \n", + " if D > P[j]:\n", + " P[j] = D\n", + " I[j] = j+i \n", " \n", - " if D > DP[i+k][0][0]:\n", - " heapq.heappushpop(DP[i+k], item=(D, i))\n", - " if D > P[i+k]:\n", - " P[i+k] = D\n", - " I[i+k] = i\n", + " if D > DP[j+i][0][0]:\n", + " heapq.heappushpop(DP[j+i], (D, j)) \n", + " if D > P[j+i]: \n", + " P[j+i] = D \n", + " I[j+i] = j \n", " \n", " # post-processing\n", " P = -1 * P \n", - " DP_larget_dist = np.asarray([-1 * item[0][0] for item in DP], dtype=np.float64)\n", - " DP_all_indices = np.asarray([[pair[1] for pair in item] for item in DP], dtype=np.int64)\n", " \n", - " return P, I, DP_larget_dist, DP_all_indices" + " DP = np.array(DP)\n", + " Partial_DP = -1 * DP[:,:,0].astype(np.float64)\n", + " Partial_DP_indices = DP[:,:,1].astype(np.int64)\n", + " \n", + " return P, I, Partial_DP, Partial_DP_indices" ] }, { "cell_type": "code", - "execution_count": 305, - "id": "46815234", + "execution_count": 397, + "id": "82fe0538", "metadata": {}, "outputs": [], "source": [ @@ -556,29 +599,29 @@ }, { "cell_type": "code", - "execution_count": 306, - "id": "63e9acea", + "execution_count": 398, + "id": "b758fbac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "running time: 1.078115463256836\n" + "running time: 1.08510160446167\n" ] } ], "source": [ "tic = time.time()\n", - "P, I, DP_larget_dist, DP_all_indices = naive_METAstump(T, m, h=5)\n", + "P, I, Partial_DP, Partial_DP_indices = _VALMOD_stump(T, m, n=5)\n", "toc = time.time()\n", "print('running time: ', toc-tic)" ] }, { "cell_type": "code", - "execution_count": 307, - "id": "d0953028", + "execution_count": 399, + "id": "52e54a1f", "metadata": {}, "outputs": [ { @@ -593,19 +636,19 @@ " [530, 588, 193, 412, 220]], dtype=int64)" ] }, - "execution_count": 307, + "execution_count": 399, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "DP_all_indices" + "Partial_DP_indices" ] }, { "cell_type": "code", "execution_count": null, - "id": "e0f83c16", + "id": "f237c078", "metadata": {}, "outputs": [], "source": [] @@ -613,7 +656,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7b4a04dd", + "id": "72365af4", "metadata": {}, "outputs": [], "source": [] From 450ddc6cb757cb13bab1555934dc50390b1e31b6 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 25 Apr 2022 00:44:37 -0600 Subject: [PATCH 53/67] Correct grammer and typo --- docs/Tutorial_VALMOD.ipynb | 144 ++++++++++++++++++------------------- 1 file changed, 71 insertions(+), 73 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index a6b897202..75827d222 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -182,7 +182,32 @@ "id": "7ff2e666", "metadata": {}, "source": [ - "**Normalized distance:**" + "**Normalized distance (see eq(2) of the paper):**" + ] + }, + { + "cell_type": "markdown", + "id": "8b8cc26a", + "metadata": {}, + "source": [ + "\n", + "$$\n", + "\\begin{align}\n", + " LB={}& \n", + " \\begin{cases}\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\sqrt{\n", + "m\\left(\n", + "1 - \\rho^{(m)^{2}}_{j,i}\n", + "\\right)\n", + "}, & \\text{if $\\rho^{m}_{j,i}>0$}\\\\\n", + " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\sqrt{\n", + "m\n", + "}, & \\text{otherwise}\n", + " \\end{cases}\n", + "\\end{align}\n", + "$$\n" ] }, { @@ -190,6 +215,7 @@ "id": "0f192dfa", "metadata": {}, "source": [ + "Or, equivalently:\n", "\n", "$$\n", "\\begin{align}\n", @@ -207,7 +233,7 @@ }, { "cell_type": "markdown", - "id": "6fc1437c", + "id": "a6b6a92f", "metadata": {}, "source": [ "And, the pearson correlation $\\rho^{(m)}_{j,i}$ can be calculated as follows: " @@ -215,7 +241,7 @@ }, { "cell_type": "markdown", - "id": "be0504c8", + "id": "06f74a00", "metadata": {}, "source": [ "\n", @@ -229,15 +255,15 @@ }, { "cell_type": "markdown", - "id": "de7efb95", + "id": "1e23d962", "metadata": {}, "source": [ - "Alternatively, $\\rho^{(m)}{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" + "Alternatively, $\\rho^{(m)}_{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" ] }, { "cell_type": "markdown", - "id": "30baf843", + "id": "bd2e70a1", "metadata": {}, "source": [ "\n", @@ -256,7 +282,7 @@ }, { "cell_type": "markdown", - "id": "58f786c0", + "id": "1dd3b3a4", "metadata": {}, "source": [ "# 3- Core Idea" @@ -264,7 +290,7 @@ }, { "cell_type": "markdown", - "id": "1ac2547c", + "id": "9b0ebd60", "metadata": {}, "source": [ "The core idea of VALMOD can be explained as follows:" @@ -272,19 +298,19 @@ }, { "cell_type": "markdown", - "id": "91b69e91", + "id": "d3c23204", "metadata": {}, "source": [ "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in the ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the distance profile for subsquence with length `min_m`.\n", "\n", - "In other words...
\n", - "IF:" + "In other words,
\n", + "**IF:**" ] }, { "cell_type": "markdown", - "id": "3f4fcb84", + "id": "33bc22e8", "metadata": {}, "source": [ "\n", @@ -299,15 +325,15 @@ }, { "cell_type": "markdown", - "id": "573a90f3", + "id": "02b333a3", "metadata": {}, "source": [ - "THEN:" + "**THEN:**" ] }, { "cell_type": "markdown", - "id": "c0a4e7df", + "id": "3fc03958", "metadata": {}, "source": [ "\n", @@ -360,19 +386,11 @@ }, { "cell_type": "markdown", - "id": "5328138d", - "metadata": {}, - "source": [ - "where, the lower-boundns are calculated based on the distances for length `m`. " - ] - }, - { - "cell_type": "markdown", - "id": "ad925832", + "id": "8f1df704", "metadata": {}, "source": [ "## 3-2: Accelerating Matrix Profile calculation\n", - "Storing all \"ranked LB\" for all indices needs a significant ampunt of memory. Instead, we can just store the `top-p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." + "Storing all \"ranked LB\" for all indices requires a significant amount of memory. Instead, we can just store the `top-p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." ] }, { @@ -381,7 +399,7 @@ "metadata": {}, "source": [ "# 4-VALMOD algorithm\n", - "The VALMOP algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions that are being called by VALMOD algorithm, followed by the implementation of VALMOD algorithm itself." + "The VALMOP algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions by taking a bottom-top approach. So, we first implement the functions that are being called by VALMOD algorithm, and then we implement VALMOD algorithm." ] }, { @@ -389,7 +407,7 @@ "id": "f6cbecbd", "metadata": {}, "source": [ - "## 4-1- ComputeMatrixProfile (Algorith3 on page 15)\n", + "## 4-1- ComputeMatrixProfile (see Algorith3 on page 15)\n", "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their indices as well.\n", "\n", "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used heap data structure to store `top-p` smallest LB values for each distance profile. " @@ -397,19 +415,19 @@ }, { "cell_type": "markdown", - "id": "cb41990b", + "id": "eb51f0f6", "metadata": {}, "source": [ "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", - "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As proved below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the top-p smallest value of distance profile and then calculate their corresponding LB value." + "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value." ] }, { "cell_type": "markdown", - "id": "6b1327a0", + "id": "3a1ba5e4", "metadata": {}, "source": [ - "IF: \n", + "**IF:**\n", "\n", "$$\n", "\\begin{align}\n", @@ -424,10 +442,10 @@ }, { "cell_type": "markdown", - "id": "41714628", + "id": "f7f22edc", "metadata": {}, "source": [ - "THEN:\n", + "**THEN:**\n", "\n", "$$\n", "\\begin{align}\n", @@ -471,7 +489,7 @@ }, { "cell_type": "markdown", - "id": "06f3b5d2", + "id": "ec7b8819", "metadata": {}, "source": [ "This proves that the ranked distance profile and its ranked lower bound have the same order." @@ -479,18 +497,18 @@ }, { "cell_type": "markdown", - "id": "29f02f99", + "id": "3db70f03", "metadata": {}, "source": [ "**NOTE (2):** \n", "
\n", - "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, we use the name `n` to denote the number of smallest LB values that should be considered for each distance profile." + "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, from this point onwards, we use `n` to denote the number of elements that should be stored for each distance profile." ] }, { "cell_type": "code", - "execution_count": 396, - "id": "12c7d922", + "execution_count": 402, + "id": "be7b439d", "metadata": {}, "outputs": [], "source": [ @@ -498,7 +516,7 @@ " \"\"\"\n", " This function takes the input time series `T`, window size `m`, and, the number of elements `n` that \n", " should be stored for each distance profie. In addition to the matrix profile and the matrix profile indicecs, \n", - " this function returns the indices of top-n smallest value and their corresponding indices for each distance profile.\n", + " this function returns the top-n smallest values and their corresponding indices for each distance profile.\n", " \n", " Parameters\n", " ----------\n", @@ -531,13 +549,12 @@ " \n", " see Algorithm 3\n", " \n", - " \n", - " This is a naive implementation in a sense that it calculates the whole distance_matrix right in the beginning \n", + " This is a naive implementation. It calculates the whole distance_matrix right in the beginning \n", " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", " available in stumpy/test/naive.py.\n", " \n", - " In contrast to the original paper, we simply return the `h` smallest values for each distance profile as their order \n", - " is the same as their corresponding LB values. This can help us to compute the P and I in a clean way.\n", + " In contrast to the original paper, we simply return the `n` smallest values for each distance profile as their order \n", + " is the same as their corresponding LB values. \n", " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", @@ -586,8 +603,8 @@ }, { "cell_type": "code", - "execution_count": 397, - "id": "82fe0538", + "execution_count": 403, + "id": "f431a4fb", "metadata": {}, "outputs": [], "source": [ @@ -599,15 +616,15 @@ }, { "cell_type": "code", - "execution_count": 398, - "id": "b758fbac", + "execution_count": 404, + "id": "0b3c14c2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "running time: 1.08510160446167\n" + "running time: 1.1100335121154785\n" ] } ], @@ -620,35 +637,16 @@ }, { "cell_type": "code", - "execution_count": 399, - "id": "52e54a1f", + "execution_count": null, + "id": "b5e0fe7e", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[557, 281, 279, 157, 667],\n", - " [827, 282, 280, 158, 668],\n", - " [828, 283, 669, 281, 159],\n", - " ...,\n", - " [687, 316, 410, 218, 886],\n", - " [587, 887, 219, 244, 411],\n", - " [530, 588, 193, 412, 220]], dtype=int64)" - ] - }, - "execution_count": 399, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Partial_DP_indices" - ] + "outputs": [], + "source": [] }, { "cell_type": "code", "execution_count": null, - "id": "f237c078", + "id": "6df35afc", "metadata": {}, "outputs": [], "source": [] @@ -656,7 +654,7 @@ { "cell_type": "code", "execution_count": null, - "id": "72365af4", + "id": "154664aa", "metadata": {}, "outputs": [], "source": [] From 15e5a1432def2d5fbc016a8b8677cca781c27d26 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 25 Apr 2022 01:01:09 -0600 Subject: [PATCH 54/67] proof read --- docs/Tutorial_VALMOD.ipynb | 31 ++++++++++++++++--------------- 1 file changed, 16 insertions(+), 15 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 75827d222..7eb2a79ea 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 280, + "execution_count": 1, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -97,7 +97,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -182,7 +182,7 @@ "id": "7ff2e666", "metadata": {}, "source": [ - "**Normalized distance (see eq(2) of the paper):**" + "**Normalized distance(see eq(2) of the paper):**" ] }, { @@ -193,7 +193,7 @@ "\n", "$$\n", "\\begin{align}\n", - " LB={}& \n", + " LB^{(m+k)}_{j,i}={}& \n", " \\begin{cases}\n", " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", "\\sqrt{\n", @@ -223,7 +223,7 @@ "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", "\\sqrt{\n", "m\\left(\n", - "1 - \\max(\\rho^{(m)}_{j,i},0)^{2}\n", + "1 - \\left(\\max(\\rho^{(m)}_{j,i},0)\\right)^{2}\n", "\\right)\n", "} \\quad (2)\n", "\\\\\n", @@ -236,7 +236,7 @@ "id": "a6b6a92f", "metadata": {}, "source": [ - "And, the pearson correlation $\\rho^{(m)}_{j,i}$ can be calculated as follows: " + "And, the pearson correlation, $\\rho^{(m)}_{j,i}$, can be calculated as follows: " ] }, { @@ -302,7 +302,7 @@ "metadata": {}, "source": [ "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", - "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in the ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the distance profile for subsquence with length `min_m`.\n", + "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in the ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the $\\rho_{j,i}$ values for length `min_m`.\n", "\n", "In other words,
\n", "**IF:**" @@ -407,10 +407,10 @@ "id": "f6cbecbd", "metadata": {}, "source": [ - "## 4-1- ComputeMatrixProfile (see Algorith3 on page 15)\n", + "## 4-1- ComputeMatrixProfile (see algorith3 on page 15)\n", "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their indices as well.\n", "\n", - "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used heap data structure to store `top-p` smallest LB values for each distance profile. " + "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used max_heap data structure to store `top-p` smallest LB values for each distance profile. " ] }, { @@ -507,7 +507,7 @@ }, { "cell_type": "code", - "execution_count": 402, + "execution_count": 4, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -538,7 +538,7 @@ " The matrix profile indices\n", " \n", " Partial_DP : numpy.ndarray\n", - " The partial distance profiles that contain their `n` smallest values \n", + " The partial distance profiles that contain the `n` smallest values of each distance profile\n", " \n", " Partial_DP_indices : numpy.ndarray\n", " The indices corresponding to Partial_DP\n", @@ -558,7 +558,7 @@ " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", - " #naive calculaton of distance_matrix\n", + " # naive calculaton of distance_matrix\n", " distance_matrix = np.array(\n", " [core.mass(Q, T) for Q in core.rolling_window(T, m)]\n", " )\n", @@ -568,6 +568,7 @@ " P = np.full(k, np.NINF, dtype=np.float64) \n", " I = np.full(k, -1, dtype=np.int64)\n", " \n", + " #create nest list of heapified lists\n", " DP = []\n", " for _ in range(k):\n", " tmp = [(np.NINF,-1)] * n\n", @@ -603,7 +604,7 @@ }, { "cell_type": "code", - "execution_count": 403, + "execution_count": 5, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -616,7 +617,7 @@ }, { "cell_type": "code", - "execution_count": 404, + "execution_count": 6, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -624,7 +625,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 1.1100335121154785\n" + "running time: 2.506328582763672\n" ] } ], From c8653e2f6c9ac0c41d54cf52bdfded77b8f194a3 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 25 Apr 2022 01:12:37 -0600 Subject: [PATCH 55/67] Removed unrecognized latex code --- docs/Tutorial_VALMOD.ipynb | 26 -------------------------- 1 file changed, 26 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 7eb2a79ea..57cb9047c 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -185,37 +185,11 @@ "**Normalized distance(see eq(2) of the paper):**" ] }, - { - "cell_type": "markdown", - "id": "8b8cc26a", - "metadata": {}, - "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - " LB^{(m+k)}_{j,i}={}& \n", - " \\begin{cases}\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - "\\sqrt{\n", - "m\\left(\n", - "1 - \\rho^{(m)^{2}}_{j,i}\n", - "\\right)\n", - "}, & \\text{if $\\rho^{m}_{j,i}>0$}\\\\\n", - " \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - "\\sqrt{\n", - "m\n", - "}, & \\text{otherwise}\n", - " \\end{cases}\n", - "\\end{align}\n", - "$$\n" - ] - }, { "cell_type": "markdown", "id": "0f192dfa", "metadata": {}, "source": [ - "Or, equivalently:\n", "\n", "$$\n", "\\begin{align}\n", From d924fc1847c58322f64391cb0441fd3cff5f8494 Mon Sep 17 00:00:00 2001 From: ninimama Date: Mon, 25 Apr 2022 01:22:00 -0600 Subject: [PATCH 56/67] minor changes --- docs/Tutorial_VALMOD.ipynb | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 57cb9047c..d11c2eebe 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -393,7 +393,7 @@ "metadata": {}, "source": [ "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", - "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ corresponding to each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value." + "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ for each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value." ] }, { @@ -481,7 +481,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -490,7 +490,7 @@ " \"\"\"\n", " This function takes the input time series `T`, window size `m`, and, the number of elements `n` that \n", " should be stored for each distance profie. In addition to the matrix profile and the matrix profile indicecs, \n", - " this function returns the top-n smallest values and their corresponding indices for each distance profile.\n", + " this function returns the top-n smallest values and their corresponding indices for each distance profile as well.\n", " \n", " Parameters\n", " ----------\n", @@ -501,7 +501,7 @@ " Window size\n", " \n", " n : int\n", - " The number of elements stored for each distance profile\n", + " The number of elements stored for each distance profile.\n", " \n", " Returns\n", " ---------\n", @@ -523,9 +523,9 @@ " \n", " see Algorithm 3\n", " \n", - " This is a naive implementation. It calculates the whole distance_matrix right in the beginning \n", + " This is a naive implementation of stump. It calculates the whole distance_matrix right in the beginning \n", " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", - " available in stumpy/test/naive.py.\n", + " available in stumpy/test/naive.py. \n", " \n", " In contrast to the original paper, we simply return the `n` smallest values for each distance profile as their order \n", " is the same as their corresponding LB values. \n", @@ -578,7 +578,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -591,7 +591,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -599,7 +599,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 2.506328582763672\n" + "running time: 2.5790293216705322\n" ] } ], From df84ded6a17ce9b679fbd41b56d2427bcf9b9b91 Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 26 Apr 2022 17:03:55 -0600 Subject: [PATCH 57/67] minor changes - Fix typos - replace variable name n with k --- docs/Tutorial_VALMOD.ipynb | 45 +++++++++++++++++++------------------- 1 file changed, 23 insertions(+), 22 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index d11c2eebe..9b501a521 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -373,7 +373,7 @@ "metadata": {}, "source": [ "# 4-VALMOD algorithm\n", - "The VALMOP algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions by taking a bottom-top approach. So, we first implement the functions that are being called by VALMOD algorithm, and then we implement VALMOD algorithm." + "The VALMOD algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions by taking a bottom-up approach. So, we first implement the functions that are being called by VALMOD algorithm, and then we implement VALMOD algorithm." ] }, { @@ -476,21 +476,21 @@ "source": [ "**NOTE (2):** \n", "
\n", - "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, from this point onwards, we use `n` to denote the number of elements that should be stored for each distance profile." + "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, from this point onwards, we use `k` to denote the number of elements that should be stored for each distance profile." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 6, "id": "be7b439d", "metadata": {}, "outputs": [], "source": [ - "def _VALMOD_stump(T, m, n = 5):\n", + "def _VALMOD_stump(T, m, k = 5):\n", " \"\"\"\n", - " This function takes the input time series `T`, window size `m`, and, the number of elements `n` that \n", + " This function takes the input time series `T`, window size `m`, and, the number of elements `k` that \n", " should be stored for each distance profie. In addition to the matrix profile and the matrix profile indicecs, \n", - " this function returns the top-n smallest values and their corresponding indices for each distance profile as well.\n", + " this function returns the top-k smallest values and their corresponding indices for each distance profile as well.\n", " \n", " Parameters\n", " ----------\n", @@ -500,7 +500,7 @@ " m : int\n", " Window size\n", " \n", - " n : int\n", + " k : int\n", " The number of elements stored for each distance profile.\n", " \n", " Returns\n", @@ -512,7 +512,7 @@ " The matrix profile indices\n", " \n", " Partial_DP : numpy.ndarray\n", - " The partial distance profiles that contain the `n` smallest values of each distance profile\n", + " The partial distance profiles that contain the `k` smallest values of each distance profile\n", " \n", " Partial_DP_indices : numpy.ndarray\n", " The indices corresponding to Partial_DP\n", @@ -527,7 +527,7 @@ " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", " available in stumpy/test/naive.py. \n", " \n", - " In contrast to the original paper, we simply return the `n` smallest values for each distance profile as their order \n", + " In contrast to the original paper, we simply return the `k` smallest values for each distance profile as their order \n", " is the same as their corresponding LB values. \n", " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", @@ -537,21 +537,21 @@ " [core.mass(Q, T) for Q in core.rolling_window(T, m)]\n", " )\n", " \n", - " k = T.shape[0] - m + 1\n", + " l = T.shape[0] - m + 1\n", " \n", - " P = np.full(k, np.NINF, dtype=np.float64) \n", - " I = np.full(k, -1, dtype=np.int64)\n", + " P = np.full(l, np.NINF, dtype=np.float64) \n", + " I = np.full(l, -1, dtype=np.int64)\n", " \n", " #create nest list of heapified lists\n", " DP = []\n", - " for _ in range(k):\n", - " tmp = [(np.NINF,-1)] * n\n", + " for _ in range(l):\n", + " tmp = [(np.NINF,-1)] * k\n", " heapq.heapify(tmp)\n", " DP.append(tmp)\n", " \n", - " diags = np.arange(excl_zone + 1, k)\n", + " diags = np.arange(excl_zone + 1, l)\n", " for i in diags: \n", - " for j in range(0, k - i): \n", + " for j in range(0, l - i): \n", " D = -1 * distance_matrix[j, j + i] \n", " \n", " if D > DP[j][0][0]: \n", @@ -578,7 +578,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -586,12 +586,13 @@ "seed = 0\n", "np.random.seed(seed)\n", "T = np.random.uniform(low=-100, high=100, size=1000)\n", - "m = 50" + "m = 50\n", + "k = 5" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 8, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -599,13 +600,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 2.5790293216705322\n" + "running time: 2.5206298828125\n" ] } ], "source": [ "tic = time.time()\n", - "P, I, Partial_DP, Partial_DP_indices = _VALMOD_stump(T, m, n=5)\n", + "P, I, Partial_DP, Partial_DP_indices = _VALMOD_stump(T, m, k)\n", "toc = time.time()\n", "print('running time: ', toc-tic)" ] From 7d38e39c0b01c5d25589971e6e9c487cc644f1f5 Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 26 Apr 2022 17:59:21 -0600 Subject: [PATCH 58/67] replace heapq with np.searchsorted --- docs/Tutorial_VALMOD.ipynb | 73 ++++++++++++++------------------------ 1 file changed, 26 insertions(+), 47 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 9b501a521..965824fbb 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -481,16 +481,16 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 50, "id": "be7b439d", "metadata": {}, "outputs": [], "source": [ "def _VALMOD_stump(T, m, k = 5):\n", " \"\"\"\n", - " This function takes the input time series `T`, window size `m`, and, the number of elements `k` that \n", - " should be stored for each distance profie. In addition to the matrix profile and the matrix profile indicecs, \n", - " this function returns the top-k smallest values and their corresponding indices for each distance profile as well.\n", + " An extended version of stump. While stump returns the smallest valus of each distance profile \n", + " and its corresponding index, this function returns top-k smallest values of each distance profile \n", + " and their corresponding indices.\n", " \n", " Parameters\n", " ----------\n", @@ -505,18 +505,12 @@ " \n", " Returns\n", " ---------\n", - " P : numpy.ndarray\n", - " The matrix profile\n", + " P_topk : numpy.ndarray\n", + " The i-th row contains the top-k smallest values of the distance profile corresponding to `T[i:i+m]`.\n", " \n", - " I : numpy.ndarray\n", - " The matrix profile indices\n", + " I_topk : numpy.ndarray\n", + " The indices that correspond to P_topk\n", " \n", - " Partial_DP : numpy.ndarray\n", - " The partial distance profiles that contain the `k` smallest values of each distance profile\n", - " \n", - " Partial_DP_indices : numpy.ndarray\n", - " The indices corresponding to Partial_DP\n", - " \n", " Notes\n", " -----\n", " https://doi.org/10.48550/arXiv.2008.13447\n", @@ -539,46 +533,31 @@ " \n", " l = T.shape[0] - m + 1\n", " \n", - " P = np.full(l, np.NINF, dtype=np.float64) \n", - " I = np.full(l, -1, dtype=np.int64)\n", - " \n", - " #create nest list of heapified lists\n", - " DP = []\n", - " for _ in range(l):\n", - " tmp = [(np.NINF,-1)] * k\n", - " heapq.heapify(tmp)\n", - " DP.append(tmp)\n", + " P_topk = np.full((l,k), np.inf, dtype=np.float64)\n", + " I_topk = np.full((l,k), -1, dtype=np.int64)\n", " \n", " diags = np.arange(excl_zone + 1, l)\n", " for i in diags: \n", " for j in range(0, l - i): \n", - " D = -1 * distance_matrix[j, j + i] \n", + " D = distance_matrix[j, j + i] \n", " \n", - " if D > DP[j][0][0]: \n", - " heapq.heappushpop(DP[j], (D, j+i)) \n", - " if D > P[j]:\n", - " P[j] = D\n", - " I[j] = j+i \n", + " if D < P_topk[j,-1]:\n", + " idx = np.searchsorted(P_topk[j], D, side='right') \n", + " P_topk[j] = np.insert(P_topk[j], idx, D)[:-1]\n", + " I_topk[j] = np.insert(I_topk[j], idx, j+i)[:-1]\n", " \n", - " if D > DP[j+i][0][0]:\n", - " heapq.heappushpop(DP[j+i], (D, j)) \n", - " if D > P[j+i]: \n", - " P[j+i] = D \n", - " I[j+i] = j \n", - " \n", - " # post-processing\n", - " P = -1 * P \n", - " \n", - " DP = np.array(DP)\n", - " Partial_DP = -1 * DP[:,:,0].astype(np.float64)\n", - " Partial_DP_indices = DP[:,:,1].astype(np.int64)\n", + " if D < P_topk[j+1,-1]:\n", + " idx = np.searchsorted(P_topk[j+i], D, side='right') \n", + " P_topk[j+i] = np.insert(P_topk[j+i], idx, D)[:-1]\n", + " I_topk[j+i] = np.insert(I_topk[j+i], idx, j)[:-1]\n", + " \n", " \n", - " return P, I, Partial_DP, Partial_DP_indices" + " return P_topk, I_topk" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 51, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -592,7 +571,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 52, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -600,13 +579,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 2.5206298828125\n" + "running time: 2.5092923641204834\n" ] } ], "source": [ "tic = time.time()\n", - "P, I, Partial_DP, Partial_DP_indices = _VALMOD_stump(T, m, k)\n", + "P_topk, I_topk = _VALMOD_stump(T, m, k)\n", "toc = time.time()\n", "print('running time: ', toc-tic)" ] @@ -630,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "154664aa", + "id": "c7a09d91", "metadata": {}, "outputs": [], "source": [] From cbe649f5092962ccccca9179f519cc5f0884b71b Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 26 Apr 2022 18:19:17 -0600 Subject: [PATCH 59/67] Fix typo --- docs/Tutorial_VALMOD.ipynb | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 965824fbb..0dd91dd99 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -481,7 +481,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 64, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -506,7 +506,8 @@ " Returns\n", " ---------\n", " P_topk : numpy.ndarray\n", - " The i-th row contains the top-k smallest values of the distance profile corresponding to `T[i:i+m]`.\n", + " The i-th row contains the top-k smallest values of the distance profile corresponding to `T[i:i+m]` sorted \n", + " in ascending order.\n", " \n", " I_topk : numpy.ndarray\n", " The indices that correspond to P_topk\n", @@ -546,7 +547,7 @@ " P_topk[j] = np.insert(P_topk[j], idx, D)[:-1]\n", " I_topk[j] = np.insert(I_topk[j], idx, j+i)[:-1]\n", " \n", - " if D < P_topk[j+1,-1]:\n", + " if D < P_topk[j+i,-1]:\n", " idx = np.searchsorted(P_topk[j+i], D, side='right') \n", " P_topk[j+i] = np.insert(P_topk[j+i], idx, D)[:-1]\n", " I_topk[j+i] = np.insert(I_topk[j+i], idx, j)[:-1]\n", @@ -557,7 +558,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 65, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -571,7 +572,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 66, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -579,7 +580,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 2.5092923641204834\n" + "running time: 2.3726773262023926\n" ] } ], From 34edea87f7aa90f6a4f38aeb89e77a47f6d99d3d Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 26 Apr 2022 18:38:53 -0600 Subject: [PATCH 60/67] Test P and I of _VALMOD_stump --- docs/Tutorial_VALMOD.ipynb | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 0dd91dd99..dd6f377f6 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -593,11 +593,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 76, "id": "b5e0fe7e", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "P = P_topk[:,0]\n", + "I = I_topk[:,0]\n", + "#just test the P and I\n", + "mp = stumpy.stump(T, m)\n", + "np.testing.assert_allclose(mp[:,0].astype(np.float64), P)\n", + "np.testing.assert_allclose(mp[:,1].astype(np.int64), I)" + ] }, { "cell_type": "code", From b4b9f691a7f598d0b197af802d64b59a25cff515 Mon Sep 17 00:00:00 2001 From: ninimama Date: Tue, 26 Apr 2022 18:50:34 -0600 Subject: [PATCH 61/67] minor changes --- docs/Tutorial_VALMOD.ipynb | 42 +++++++++++++++++++------------------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index dd6f377f6..50c4e7c05 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -382,7 +382,7 @@ "metadata": {}, "source": [ "## 4-1- ComputeMatrixProfile (see algorith3 on page 15)\n", - "This algorithm scans all pairs of subsequences. However, instead of just returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their indices as well.\n", + "This algorithm scans all pairs of subsequences. However, instead of returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their corresponding indices.\n", "\n", "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used max_heap data structure to store `top-p` smallest LB values for each distance profile. " ] @@ -481,7 +481,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 77, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -522,8 +522,8 @@ " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", " available in stumpy/test/naive.py. \n", " \n", - " In contrast to the original paper, we simply return the `k` smallest values for each distance profile as their order \n", - " is the same as their corresponding LB values. \n", + " Unlike the original paper that returns matrix profile and indices and the LB values for the next length (i.e. m+1), \n", + " we return the `k` smallest values and their indices for each distance profile.\n", " \"\"\"\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " \n", @@ -534,23 +534,23 @@ " \n", " l = T.shape[0] - m + 1\n", " \n", - " P_topk = np.full((l,k), np.inf, dtype=np.float64)\n", - " I_topk = np.full((l,k), -1, dtype=np.int64)\n", + " P_topk = np.full((l, k), np.inf, dtype=np.float64)\n", + " I_topk = np.full((l, k), -1, dtype=np.int64)\n", " \n", " diags = np.arange(excl_zone + 1, l)\n", " for i in diags: \n", " for j in range(0, l - i): \n", " D = distance_matrix[j, j + i] \n", " \n", - " if D < P_topk[j,-1]:\n", + " if D < P_topk[j, -1]:\n", " idx = np.searchsorted(P_topk[j], D, side='right') \n", " P_topk[j] = np.insert(P_topk[j], idx, D)[:-1]\n", - " I_topk[j] = np.insert(I_topk[j], idx, j+i)[:-1]\n", + " I_topk[j] = np.insert(I_topk[j], idx, j + i)[:-1]\n", " \n", - " if D < P_topk[j+i,-1]:\n", - " idx = np.searchsorted(P_topk[j+i], D, side='right') \n", - " P_topk[j+i] = np.insert(P_topk[j+i], idx, D)[:-1]\n", - " I_topk[j+i] = np.insert(I_topk[j+i], idx, j)[:-1]\n", + " if D < P_topk[j + i, -1]:\n", + " idx = np.searchsorted(P_topk[j + i], D, side='right') \n", + " P_topk[j + i] = np.insert(P_topk[j + i], idx, D)[:-1]\n", + " I_topk[j + i] = np.insert(I_topk[j + i], idx, j)[:-1]\n", " \n", " \n", " return P_topk, I_topk" @@ -558,7 +558,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 78, "id": "f431a4fb", "metadata": {}, "outputs": [], @@ -572,7 +572,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 79, "id": "0b3c14c2", "metadata": {}, "outputs": [ @@ -580,7 +580,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "running time: 2.3726773262023926\n" + "running time: 2.096430778503418\n" ] } ], @@ -588,22 +588,22 @@ "tic = time.time()\n", "P_topk, I_topk = _VALMOD_stump(T, m, k)\n", "toc = time.time()\n", - "print('running time: ', toc-tic)" + "print('running time: ', toc - tic)" ] }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 80, "id": "b5e0fe7e", "metadata": {}, "outputs": [], "source": [ - "P = P_topk[:,0]\n", - "I = I_topk[:,0]\n", + "P = P_topk[:, 0]\n", + "I = I_topk[:, 0]\n", "#just test the P and I\n", "mp = stumpy.stump(T, m)\n", - "np.testing.assert_allclose(mp[:,0].astype(np.float64), P)\n", - "np.testing.assert_allclose(mp[:,1].astype(np.int64), I)" + "np.testing.assert_allclose(mp[:, 0].astype(np.float64), P)\n", + "np.testing.assert_allclose(mp[:, 1].astype(np.int64), I)" ] }, { From c6dd58d68be3033f7ca4caa360fee81b7fcea2ce Mon Sep 17 00:00:00 2001 From: nimasarajpoor Date: Mon, 27 Feb 2023 08:34:14 -0500 Subject: [PATCH 62/67] Implement VALMOD-draft version --- docs/Tutorial_VALMOD.ipynb | 399 +++++++++++++++++++++++++++++-------- 1 file changed, 311 insertions(+), 88 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 50c4e7c05..f67df115a 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 175, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -20,12 +20,12 @@ "%matplotlib inline\n", "\n", "import stumpy\n", - "from stumpy import core, config\n", + "from stumpy import stump, core, config\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", + "import math\n", "import time\n", - "import heapq\n", "\n", "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" ] @@ -43,7 +43,7 @@ "id": "b0423978", "metadata": {}, "source": [ - "**Notation:** $T_{i,m} = T[i:i+m]$, a subsequence of `T` that starts at index `i` and has length `m`. " + "**Notation:** $T_{i,m} = T[i:i+m]$ is a subsequence of `T` that starts at index `i` and has length `m`. " ] }, { @@ -63,7 +63,7 @@ "\n", "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both these two subsequences start from the same index." + "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both of these two subsequences start from the same index." ] }, { @@ -83,7 +83,7 @@ "\n", "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequence and its ($n^{th}$ ?) best match.
\n", + "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequences and their ($n^{th}$) best match.
\n", "\n", "**NOTE**:
\n", "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" @@ -127,7 +127,7 @@ "source": [ "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", "\n", - "For further details, see Fig. 2 of the paper. Notice that `Top-1 2nd discord` subsequence has a close 1-NN; however, it is far from its 2nd closest neighbor.)" + "For further details, see Fig. 2 of the paper." ] }, { @@ -152,7 +152,7 @@ "id": "8538f0e3", "metadata": {}, "source": [ - "Lower Bound (LB) for $d(T_{j,m+k}, T_{i,m+k})$ can be calculated as follows:" + "Lower Bound (LB) for $d_{j,i}^{(m+k)} = d(T_{j,m+k}, T_{i,m+k})$ can be calculated as follows:" ] }, { @@ -393,7 +393,7 @@ "metadata": {}, "source": [ "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", - "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ for each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value." + "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ for each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value all at once." ] }, { @@ -481,135 +481,358 @@ }, { "cell_type": "code", - "execution_count": 77, - "id": "be7b439d", + "execution_count": 164, + "id": "a010e37e", "metadata": {}, "outputs": [], "source": [ - "def _VALMOD_stump(T, m, k = 5):\n", + "def _VALMOD_stump(T, m, k):\n", " \"\"\"\n", - " An extended version of stump. While stump returns the smallest valus of each distance profile \n", - " and its corresponding index, this function returns top-k smallest values of each distance profile \n", - " and their corresponding indices.\n", + " Computes the top-1 matrix profile and matrix profile indice, and also computes the lower bound component\n", + " and their coresponding indices.\n", " \n", " Parameters\n", " ----------\n", " T : numpy.ndarray\n", " The time series or sequence for which to compute the matrix profile\n", - " \n", + " \n", " m : int\n", " Window size\n", - " \n", + " \n", " k : int\n", - " The number of elements stored for each distance profile.\n", + " Number of nearest neighbors to consider in constructing the profiles and lower bounds.\n", " \n", " Returns\n", - " ---------\n", - " P_topk : numpy.ndarray\n", - " The i-th row contains the top-k smallest values of the distance profile corresponding to `T[i:i+m]` sorted \n", - " in ascending order.\n", + " -------\n", + " out 1: np.ndarray\n", + " A 1D array containing the exact matix profile values\n", + " \n", + " out 2: np.ndarray\n", + " A 1D array containing the exact matix profile indices\n", " \n", - " I_topk : numpy.ndarray\n", - " The indices that correspond to P_topk\n", + " out 3: np.ndarray\n", + " A 2D array, with k columns, containing the core component of lowerbound values,\n", + " \n", + " out 4 : np.ndarray\n", + " A 2D array, with k columns, containing the indices that correspond to the lowerbound values\n", + " \"\"\"\n", + " mp = stump(T, m, k=k)\n", + " P_TopK = mp[:, :k].astype(np.float64)\n", + " I_TopK = mp[:, k:2*k].astype(np.int64)\n", + " \n", + " # In VALMOD paper, LB has the following component:\n", + " # np.sqrt(m * (1 - np.square(ρ_clip))). Here, we\n", + " # show it by `LB_σr`\n", + "\n", + " ρ = 1.0 - np.square(P_TopK) / (2 * m)\n", + " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", + " r = np.sqrt(m * (1.0 - np.square(ρ_clipped))) \n", + " _, σ = core.compute_mean_std(T, m)\n", + " LB_σr = σ.reshape(-1,1) * r\n", " \n", - " Notes\n", - " -----\n", - " https://doi.org/10.48550/arXiv.2008.13447\n", + " return P_TopK[:, 0], I_TopK[:, 0], LB_σr, I_TopK\n", " \n", - " see Algorithm 3\n", " \n", - " This is a naive implementation of stump. It calculates the whole distance_matrix right in the beginning \n", - " of the algorithm. The structure of this code is based on the naive implemention of function stump, \n", - " available in stumpy/test/naive.py. \n", " \n", - " Unlike the original paper that returns matrix profile and indices and the LB values for the next length (i.e. m+1), \n", - " we return the `k` smallest values and their indices for each distance profile.\n", + "def _VALMOD_stump_partial(T, m, k, LB_σr, LB_I):\n", " \"\"\"\n", - " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", + " Compute partial matrix profile for subsequence length `m`, \n", + " with help of lowerbound. \n", + " \n", + " Parameters\n", + " ----------\n", + " T : numpy.ndarray\n", + " The time series or sequence for which to compute the matrix profile\n", + " \n", + " m : int\n", + " Window size\n", + " \n", + " k : int\n", + " The number of nearest neighbor to consider for constructing lowerbound \n", + " profiles\n", + " \n", + " LB_ar : np.ndarray\n", + " The array that contains the main component of lowerbound values\n", + " \n", + " I_TopK : np.ndarray\n", + " The array that corresponds to the indices of lower bound values\n", + " \n", + " Returns\n", + " -------\n", + " P : np.ndarray\n", + " A 1D array containing the exact matix profile values\n", " \n", - " # naive calculaton of distance_matrix\n", - " distance_matrix = np.array(\n", - " [core.mass(Q, T) for Q in core.rolling_window(T, m)]\n", - " )\n", + " I : np.ndarray\n", + " A 1D array containing the exact matix profile indices\n", + " \n", + " LB_σr : np.ndarray\n", + " A 2D array, with k columns, containing the core component of lowerbound values,\n", " \n", - " l = T.shape[0] - m + 1\n", + " LB_I : np.ndarray\n", + " A 2D array, with k columns, containing the indices that correspond to the lowerbound values\n", + " \"\"\"\n", + " n = len(T) - m + 1\n", + " P = np.full(n, np.inf,dtype=np.float64)\n", + " I = np.full(n, -1,dtype=np.int64)\n", + " is_mp_valid = np.full(n, 0, dtype=bool)\n", " \n", - " P_topk = np.full((l, k), np.inf, dtype=np.float64)\n", - " I_topk = np.full((l, k), -1, dtype=np.int64)\n", + " # may add support for `T_B` (AB-join)\n", + " Q, μ_Q, σ_Q, Q_subseq_isconstant = core.preprocess(T, m)\n", + " T, M_T, Σ_T, T_subseq_isconstant = core.preprocess(T, m)\n", " \n", - " diags = np.arange(excl_zone + 1, l)\n", - " for i in diags: \n", - " for j in range(0, l - i): \n", - " D = distance_matrix[j, j + i] \n", + " σ_Q_inv = 1.0 / σ_Q\n", + " LB = σ_Q_inv.reshape(-1, 1) * LB_σr[:len(σ_Q_inv)]\n", + " \n", + " maxLB_profile = np.full(n, np.NINF, dtype=np.float64)\n", + " isin_excl_zone = np.full(LB.shape[1], 0, dtype=bool)\n", + " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", + " for i in range(n):\n", + " isin_excl_zone[:] = False\n", + " \n", + " excl_zone_start = max(i - excl_zone, 0)\n", + " excl_zone_stop = min(i + excl_zone + 1, n)\n", + " excl_zone_range = range(excl_zone_start, excl_zone_stop)\n", + " \n", + " min_dist = np.inf\n", + " idx = -1\n", + " for enum, j in enumerate(LB_I[i]):\n", + " if j >= n:\n", + " isin_excl_zone[enum] = True # just to exclude...\n", + " \n", + " elif j in excl_zone_range:\n", + " isin_excl_zone[enum] = True\n", " \n", - " if D < P_topk[j, -1]:\n", - " idx = np.searchsorted(P_topk[j], D, side='right') \n", - " P_topk[j] = np.insert(P_topk[j], idx, D)[:-1]\n", - " I_topk[j] = np.insert(I_topk[j], idx, j + i)[:-1]\n", - " \n", - " if D < P_topk[j + i, -1]:\n", - " idx = np.searchsorted(P_topk[j + i], D, side='right') \n", - " P_topk[j + i] = np.insert(P_topk[j + i], idx, D)[:-1]\n", - " I_topk[j + i] = np.insert(I_topk[j + i], idx, j)[:-1]\n", + " else:\n", + " QT = np.dot(T[i:i+m], T[j:j+m])\n", + " d_square = core._calculate_squared_distance(\n", + " m,\n", + " QT,\n", + " μ_Q[i],\n", + " σ_Q[i],\n", + " M_T[j],\n", + " Σ_T[j],\n", + " Q_subseq_isconstant[i],\n", + " T_subseq_isconstant[j],\n", + " )\n", + " d = np.sqrt(d_square)\n", + " if d < min_dist:\n", + " min_dist = d\n", + " idx = j\n", + " \n", + " eligible_LB = LB[i, ~isin_excl_zone]\n", + " if len(eligible_LB) > 0:\n", + " maxLB = eligible_LB[-1]\n", + " else:\n", + " maxLB = np.NINF\n", + " \n", + " if min_dist < maxLB:\n", + " P[i] = min_dist\n", + " I[i] = idx\n", + " is_mp_valid[i] = True\n", + " else:\n", + " maxLB_profile[i] = maxLB\n", + " is_mp_valid[i] = False\n", " \n", + " n_invalid = np.sum(~is_mp_valid)\n", + " time_complexity_threshold = (n * np.log2(k) / np.log2(n))\n", " \n", - " return P_topk, I_topk" + " global_min_dist = np.min(P)\n", + " global_min_maxLB = np.min(maxLB_profile[~is_mp_valid])\n", + " if global_min_dist > global_min_maxLB:\n", + " if n_invalid < time_complexity_threshold:\n", + " for idx in np.flatnonzero(~is_mp_valid):\n", + " if global_min_dist <= maxLB_profile[idx]:\n", + " continue # Q: so, are we considering approx. best match?\n", + "\n", + " QT = core.sliding_dot_product(T[idx:idx+m], T)\n", + " D = core._mass(\n", + " T[idx:idx+m], \n", + " T, \n", + " QT, \n", + " μ_Q[idx], \n", + " σ_Q[idx], \n", + " M_T, \n", + " Σ_T, \n", + " Q_subseq_isconstant[idx], \n", + " T_subseq_isconstant\n", + " )\n", + " core.apply_exclusion_zone(D, idx, m, np.inf)\n", + "\n", + " arg = np.argmin(D)\n", + " if D[arg] < np.inf:\n", + " P[idx] = D[arg]\n", + " I[idx] = arg\n", + "\n", + " args_topk = np.argsort(D)[:k]\n", + " LB_I[idx] = args_topk\n", + "\n", + " ρ = 1.0 - np.square(D[args_topk]) / (2 * m)\n", + " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", + " r = np.sqrt(m * (1 - np.square(ρ_clipped)))\n", + " LB_σr[idx] = σ_Q[idx] * r\n", + "\n", + " else:\n", + " mp = stump(T, m, k=k)\n", + " P_TopK = mp[:, :k].astype(np.float64)\n", + " I_TopK = mp[:, k:2*k].astype(np.int64)\n", + "\n", + " ρ = 1.0 - np.square(P_TopK) / (2 * m)\n", + " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", + " r = np.sqrt(m * (1 - np.square(ρ_clipped)))\n", + " _, σ = core.compute_mean_std(T, m)\n", + " LB_σr = σ.reshape(-1,1) * r\n", + " LB_I = I_TopK\n", + " \n", + " return P, I, LB_σr, LB_I" ] }, { "cell_type": "code", - "execution_count": 78, - "id": "f431a4fb", + "execution_count": 165, + "id": "be7b439d", "metadata": {}, "outputs": [], "source": [ - "seed = 0\n", - "np.random.seed(seed)\n", - "T = np.random.uniform(low=-100, high=100, size=1000)\n", - "m = 50\n", - "k = 5" + "def _update_PIM(P, P_new, I, I_new, M, m_new):\n", + " \"\"\"\n", + " Update P (profile values), I (profile indices), M (length of subsequences), in place, \n", + " by using the new values `P_new`, `I_new`, `m_new`\n", + " \n", + " Parameters\n", + " ----------\n", + " P : np.ndarray\n", + " The matrix profile value containing the scaled distance between a subsequence to the nearest neighbor\n", + " \n", + " P_new : np.ndarray\n", + " The matrix profile value containing the scaled distance between a subsequence to the nearest neighbor, \n", + " computed for a subsequence length that is longer than the one used for `P`\n", + " \n", + " I : np.ndarray\n", + " The matrix profile indices containing the nearest neighbor index of each subsequence\n", + " \n", + " I_new : np.ndarray\n", + " The matrix profile indices containing the nearest neighbor index of each subsequence, computed \n", + " for a subsequence length that is longer than the one used for `I`. These indices correspond to \n", + " the matrix profile `P_new`\n", + " \n", + " M : np.ndarray\n", + " For a subequence at index `i`, `M[i]` is the lenght of subsequence for which the lowest distance \n", + " between `i` and its nearest neighbor is discovered.\n", + " \n", + " m_new : int\n", + " The new subsequence length that is used for computing P_new, I_new\n", + " \n", + " Returns \n", + " -------\n", + " None\n", + " \"\"\"\n", + " n = len(P_new)\n", + " mask = P_new < P[:n]\n", + " P[:n][mask] = P_new[mask]\n", + " I[:n][mask] = I_new[mask]\n", + " M[:n][mask] = m_new" ] }, { "cell_type": "code", - "execution_count": 79, - "id": "0b3c14c2", + "execution_count": 166, + "id": "94eceff1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "running time: 2.096430778503418\n" - ] - } - ], + "outputs": [], "source": [ - "tic = time.time()\n", - "P_topk, I_topk = _VALMOD_stump(T, m, k)\n", - "toc = time.time()\n", - "print('running time: ', toc - tic)" + "def VALMOD(T, m_min, m_max, k):\n", + " \"\"\"\n", + " This function finds the matrix profile of T_A while considering different length of subsequences in \n", + " range `[m_min, m_max]` inclusive. To be able to compare distances across different subsequence length, \n", + " each distance is scaled by a factor of `1 / sqrt(m)`. \n", + " \n", + " Parameters\n", + " T : np.ndarray\n", + " The timeseries of interest\n", + " \n", + " m_min : int\n", + " The smallest window size\n", + " \n", + " m_max : int\n", + " The largest window size\n", + " \n", + " k : int\n", + " The number of nearest neighbors to capture for speeding up the computaion.\n", + " \n", + " Return\n", + " ------\n", + " PIM : np.ndarray\n", + " A 2D array, with exactly three columns, representing the ensembled matrix profile. The first column \n", + " contains the ensembled matrix profile value. The second column contains their corresponding nearest\n", + " neighbor index, and the third (last) column contains the corresponding subsequence length. Hence, \n", + " for instance, when `dist = PIM[i, 0]`, `j = PIM[i, 1]`, and `m = PIM[i, 2]`, then `dist` is a (scaled) \n", + " distance between subsequence `S_i` and subsequence `S_j`, each with length `m`. `dist` is the lowest \n", + " scaled distance between `S_i` and all of its neighbors considering all values of `m`.\n", + " \"\"\"\n", + " n = len(T) - m_min + 1\n", + " out_P = np.full(n, np.inf, dtype=np.float64)\n", + " out_I = np.full(n, -1, dtype=np.int64)\n", + " out_M = np.full(n, -1, dtype=np.int64)\n", + " \n", + " # out_P, out_I, out_M = _update_PIM(out_P, P_TopK[:,0] / np.sqrt(m), out_I, I_TopK[:, 0], out_M, m)\n", + " LB_σr = None\n", + " for m in range(m_min, m_max + 1):\n", + " if LB_σr is None: # only runs for the first iteration, i,e, lowest `m` \n", + " P, I, LB_σr, LB_I = _VALMOD_stump(T, m, k)\n", + " else:\n", + " P, I, LB_σr, LB_I = _VALMOD_stump_partial(T, m, k, LB_σr, LB_I)\n", + " \n", + " _update_PIM(out_P, P/np.sqrt(m), out_I, I, out_M, m)\n", + " \n", + " out = np.empty((n, 3), dtype=object)\n", + " out[:, 0] = out_P\n", + " out[:, 1] = out_I\n", + " out[:, 2] = out_M\n", + " \n", + " return out" ] }, { "cell_type": "code", - "execution_count": 80, - "id": "b5e0fe7e", + "execution_count": 172, + "id": "9557a1ad", "metadata": {}, "outputs": [], "source": [ - "P = P_topk[:, 0]\n", - "I = I_topk[:, 0]\n", - "#just test the P and I\n", - "mp = stumpy.stump(T, m)\n", - "np.testing.assert_allclose(mp[:, 0].astype(np.float64), P)\n", - "np.testing.assert_allclose(mp[:, 1].astype(np.int64), I)" + "import time\n", + "\n", + "seed = 0\n", + "np.random.seed(seed)\n", + "T = np.random.rand(1000)\n", + "m_min=5\n", + "m_max=10\n", + "k=10\n", + "\n", + "T1 = time.time()\n", + "valmod_mp = VALMOD(T, m_min, m_max, k)\n", + "T2 = time.time()" ] }, { "cell_type": "code", "execution_count": null, - "id": "6df35afc", + "id": "f80bf53e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cff941a8", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb7e87da", "metadata": {}, "outputs": [], "source": [] @@ -617,7 +840,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c7a09d91", + "id": "0b9d7321", "metadata": {}, "outputs": [], "source": [] @@ -639,7 +862,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.10.9" } }, "nbformat": 4, From ada4fdf3c620792c270bacba933cab24998c4a74 Mon Sep 17 00:00:00 2001 From: nimasarajpoor Date: Mon, 27 Feb 2023 22:52:09 -0500 Subject: [PATCH 63/67] implement naive valmod and minor changes --- docs/Tutorial_VALMOD.ipynb | 255 ++++++++++++++++++++++++++++--------- 1 file changed, 193 insertions(+), 62 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index f67df115a..886237e0b 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 175, + "execution_count": 1, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -30,6 +30,34 @@ "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" ] }, + { + "cell_type": "code", + "execution_count": 4, + "id": "44d283f8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0.8774290881094438, 3, -1, 3],\n", + " [0.22840038810292498, 4, -1, 4],\n", + " [0.012465907727357997, 5, 0, 5],\n", + " [0.8774290881094438, 0, 0, 6],\n", + " [0.1871064481158026, 6, 1, 6],\n", + " [0.012465907727357997, 2, 2, 7],\n", + " [0.1871064481158026, 4, 4, -1],\n", + " [0.23027056533433626, 5, 5, -1]], dtype=object)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stump(np.random.rand(10), 3)" + ] + }, { "cell_type": "markdown", "id": "e9d48c97", @@ -97,14 +125,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -479,9 +505,81 @@ "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, from this point onwards, we use `k` to denote the number of elements that should be stored for each distance profile." ] }, + { + "cell_type": "markdown", + "id": "4711a892", + "metadata": {}, + "source": [ + "First, let us implement the naive version of VALMOD, that is we do not take advantage of previously-calculated top-k profiles, and we just iteratively call `stump`." + ] + }, { "cell_type": "code", - "execution_count": 164, + "execution_count": 15, + "id": "4a17e969", + "metadata": {}, + "outputs": [], + "source": [ + "def naive_VALMOD(T, m_min, m_max):\n", + " # out_P is the scaled version of matrix profile value. \n", + " n = len(T) - m_min + 1\n", + " out_P = np.full(n, np.inf, dtype=np.float64)\n", + " out_I = np.full(n, -1, dtype=np.int64)\n", + " out_M = np.full(n, -1, dtype=np.int64)\n", + " \n", + " for m in range(m_min, m_max + 1):\n", + " mp = stump(T, m)\n", + " P = mp[:,0].astype(np.float64)\n", + " I = mp[:,1].astype(np.int64)\n", + " \n", + " P[:] = P / np.sqrt(m)\n", + " \n", + " l = len(P)\n", + " mask = P < out_P[:l]\n", + " out_P[:l][mask] = P[mask]\n", + " out_I[:l][mask] = I[mask]\n", + " out_M[:l][mask] = m\n", + " \n", + " out = np.empty((n, 3), dtype=object)\n", + " out[:, 0] = out_P\n", + " out[:, 1] = out_I\n", + " out[:, 2] = out_M\n", + " \n", + " return out" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "62a300d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The computing time: 6.5180253982543945\n" + ] + } + ], + "source": [ + "# Example\n", + "seed = 0\n", + "np.random.seed(seed)\n", + "T = np.random.rand(5000)\n", + "m_min = 50\n", + "m_max = 100\n", + "\n", + "t_start = time.time()\n", + "naive_VALMOD(T, m_min, m_max)\n", + "t_stop = time.time()\n", + "\n", + "print(\"The computing time: \", t_stop - t_start)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, "id": "a010e37e", "metadata": {}, "outputs": [], @@ -583,61 +681,48 @@ " σ_Q_inv = 1.0 / σ_Q\n", " LB = σ_Q_inv.reshape(-1, 1) * LB_σr[:len(σ_Q_inv)]\n", " \n", - " maxLB_profile = np.full(n, np.NINF, dtype=np.float64)\n", - " isin_excl_zone = np.full(LB.shape[1], 0, dtype=bool)\n", + " global_min_maxLB = np.inf\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", " for i in range(n):\n", - " isin_excl_zone[:] = False\n", - " \n", " excl_zone_start = max(i - excl_zone, 0)\n", " excl_zone_stop = min(i + excl_zone + 1, n)\n", " excl_zone_range = range(excl_zone_start, excl_zone_stop)\n", " \n", " min_dist = np.inf\n", " idx = -1\n", + " maxLB = LB[i, -1]\n", " for enum, j in enumerate(LB_I[i]):\n", - " if j >= n:\n", - " isin_excl_zone[enum] = True # just to exclude...\n", - " \n", - " elif j in excl_zone_range:\n", - " isin_excl_zone[enum] = True\n", + " if j >= n or j in excl_zone_range:\n", + " continue\n", " \n", - " else:\n", - " QT = np.dot(T[i:i+m], T[j:j+m])\n", - " d_square = core._calculate_squared_distance(\n", - " m,\n", - " QT,\n", - " μ_Q[i],\n", - " σ_Q[i],\n", - " M_T[j],\n", - " Σ_T[j],\n", - " Q_subseq_isconstant[i],\n", - " T_subseq_isconstant[j],\n", - " )\n", - " d = np.sqrt(d_square)\n", - " if d < min_dist:\n", - " min_dist = d\n", - " idx = j\n", - " \n", - " eligible_LB = LB[i, ~isin_excl_zone]\n", - " if len(eligible_LB) > 0:\n", - " maxLB = eligible_LB[-1]\n", - " else:\n", - " maxLB = np.NINF\n", + " QT = np.dot(T[i:i+m], T[j:j+m])\n", + " d_square = core._calculate_squared_distance(\n", + " m,\n", + " QT,\n", + " μ_Q[i],\n", + " σ_Q[i],\n", + " M_T[j],\n", + " Σ_T[j],\n", + " Q_subseq_isconstant[i],\n", + " T_subseq_isconstant[j],\n", + " )\n", + " d = np.sqrt(d_square)\n", + " if d < min_dist:\n", + " min_dist = d\n", + " idx = j\n", " \n", " if min_dist < maxLB:\n", " P[i] = min_dist\n", " I[i] = idx\n", " is_mp_valid[i] = True\n", " else:\n", - " maxLB_profile[i] = maxLB\n", + " global_min_maxLB = min(global_min_maxLB, maxLB)\n", " is_mp_valid[i] = False\n", " \n", " n_invalid = np.sum(~is_mp_valid)\n", " time_complexity_threshold = (n * np.log2(k) / np.log2(n))\n", " \n", " global_min_dist = np.min(P)\n", - " global_min_maxLB = np.min(maxLB_profile[~is_mp_valid])\n", " if global_min_dist > global_min_maxLB:\n", " if n_invalid < time_complexity_threshold:\n", " for idx in np.flatnonzero(~is_mp_valid):\n", @@ -688,7 +773,7 @@ }, { "cell_type": "code", - "execution_count": 165, + "execution_count": 7, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -735,7 +820,7 @@ }, { "cell_type": "code", - "execution_count": 166, + "execution_count": 8, "id": "94eceff1", "metadata": {}, "outputs": [], @@ -794,48 +879,94 @@ }, { "cell_type": "code", - "execution_count": 172, + "execution_count": 9, "id": "9557a1ad", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing time: 98.4311773777008\n" + ] + } + ], "source": [ - "import time\n", + "k=20\n", "\n", - "seed = 0\n", - "np.random.seed(seed)\n", - "T = np.random.rand(1000)\n", - "m_min=5\n", - "m_max=10\n", - "k=10\n", - "\n", - "T1 = time.time()\n", + "t_start = time.time()\n", "valmod_mp = VALMOD(T, m_min, m_max, k)\n", - "T2 = time.time()" + "t_stop = time.time()\n", + "\n", + "print(\"Computing time: \", t_stop - t_start)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, + "id": "a6ff78e0", + "metadata": {}, + "outputs": [], + "source": [ + "ref = naive_VALMOD(T, m_min, m_max)\n", + "comp = VALMOD(T, m_min, m_max, k=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, "id": "f80bf53e", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "# np.testing.assert_almost_equal(ref, comp)\n", + "# results in error as the paper's proposed method is approx. \n", + "# However, the global min is exact. " + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "cff941a8", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.8414941313430254, 2031, 51], dtype=object)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "idx=np.argmin(ref[:,0])\n", + "ref[idx]" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "bb7e87da", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.841494131343025, 2031, 51], dtype=object)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "idx=np.argmin(comp[:,0])\n", + "comp[idx]" + ] }, { "cell_type": "code", From f6126ca76c6fe4ded11df8b222d8a51a7f767098 Mon Sep 17 00:00:00 2001 From: nimasarajpoor Date: Tue, 7 Mar 2023 04:36:40 -0500 Subject: [PATCH 64/67] minor changes --- docs/Tutorial_VALMOD.ipynb | 299 ++++++++++++++++++------------------- 1 file changed, 145 insertions(+), 154 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 886237e0b..f5c58265d 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 43, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -23,6 +23,8 @@ "from stumpy import stump, core, config\n", "import pandas as pd\n", "import numpy as np\n", + "import numba\n", + "from numba import njit, prange\n", "import matplotlib.pyplot as plt\n", "import math\n", "import time\n", @@ -32,24 +34,24 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 44, "id": "44d283f8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[0.8774290881094438, 3, -1, 3],\n", - " [0.22840038810292498, 4, -1, 4],\n", - " [0.012465907727357997, 5, 0, 5],\n", - " [0.8774290881094438, 0, 0, 6],\n", - " [0.1871064481158026, 6, 1, 6],\n", - " [0.012465907727357997, 2, 2, 7],\n", - " [0.1871064481158026, 4, 4, -1],\n", - " [0.23027056533433626, 5, 5, -1]], dtype=object)" + "array([[0.7444217828807693, 2, -1, 2],\n", + " [1.5382980393045818, 4, -1, 4],\n", + " [0.19836142937718138, 5, 0, 5],\n", + " [0.44958674269840077, 7, 0, 7],\n", + " [1.5382980393045818, 1, 1, 7],\n", + " [0.19836142937718138, 2, 2, 7],\n", + " [0.9901822253111079, 2, 2, -1],\n", + " [0.44958674269840077, 3, 3, -1]], dtype=object)" ] }, - "execution_count": 4, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -119,13 +121,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 45, "id": "37fdbb26", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -515,7 +517,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 46, "id": "4a17e969", "metadata": {}, "outputs": [], @@ -550,36 +552,15 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "62a300d8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The computing time: 6.5180253982543945\n" - ] - } - ], - "source": [ - "# Example\n", - "seed = 0\n", - "np.random.seed(seed)\n", - "T = np.random.rand(5000)\n", - "m_min = 50\n", - "m_max = 100\n", - "\n", - "t_start = time.time()\n", - "naive_VALMOD(T, m_min, m_max)\n", - "t_stop = time.time()\n", - "\n", - "print(\"The computing time: \", t_stop - t_start)" - ] + "outputs": [], + "source": [] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 48, "id": "a010e37e", "metadata": {}, "outputs": [], @@ -615,23 +596,24 @@ " A 2D array, with k columns, containing the indices that correspond to the lowerbound values\n", " \"\"\"\n", " mp = stump(T, m, k=k)\n", - " P_TopK = mp[:, :k].astype(np.float64)\n", - " I_TopK = mp[:, k:2*k].astype(np.int64)\n", + " P = mp[:, :k].astype(np.float64)\n", + " I = mp[:, k:2*k].astype(np.int64)\n", + " is_mp_valid = np.full(len(T) - m + 1, 0, dtype=bool)\n", " \n", " # In VALMOD paper, LB has the following component:\n", " # np.sqrt(m * (1 - np.square(ρ_clip))). Here, we\n", " # show it by `LB_σr`\n", "\n", - " ρ = 1.0 - np.square(P_TopK) / (2 * m)\n", - " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " r = np.sqrt(m * (1.0 - np.square(ρ_clipped))) \n", + " ρ = 1.0 - np.square(P) / (2 * m)\n", + " # clipping ρ\n", + " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", " _, σ = core.compute_mean_std(T, m)\n", - " LB_σr = σ.reshape(-1,1) * r\n", - " \n", - " return P_TopK[:, 0], I_TopK[:, 0], LB_σr, I_TopK\n", - " \n", + " LB_σr = σ.reshape(-1,1) * np.sqrt(m * (1.0 - np.square(ρ))) \n", + " is_mp_valid[:] = True\n", " \n", + " return P[:, 0], I[:, 0], LB_σr, I, is_mp_valid\n", " \n", + "\n", "def _VALMOD_stump_partial(T, m, k, LB_σr, LB_I):\n", " \"\"\"\n", " Compute partial matrix profile for subsequence length `m`, \n", @@ -652,7 +634,7 @@ " LB_ar : np.ndarray\n", " The array that contains the main component of lowerbound values\n", " \n", - " I_TopK : np.ndarray\n", + " LB_I : np.ndarray\n", " The array that corresponds to the indices of lower bound values\n", " \n", " Returns\n", @@ -678,7 +660,7 @@ " Q, μ_Q, σ_Q, Q_subseq_isconstant = core.preprocess(T, m)\n", " T, M_T, Σ_T, T_subseq_isconstant = core.preprocess(T, m)\n", " \n", - " σ_Q_inv = 1.0 / σ_Q\n", + " σ_Q_inv = 1.0 / σ_Q # add code to handle `σ_Q==0` cases\n", " LB = σ_Q_inv.reshape(-1, 1) * LB_σr[:len(σ_Q_inv)]\n", " \n", " global_min_maxLB = np.inf\n", @@ -690,7 +672,6 @@ " \n", " min_dist = np.inf\n", " idx = -1\n", - " maxLB = LB[i, -1]\n", " for enum, j in enumerate(LB_I[i]):\n", " if j >= n or j in excl_zone_range:\n", " continue\n", @@ -710,7 +691,8 @@ " if d < min_dist:\n", " min_dist = d\n", " idx = j\n", - " \n", + " \n", + " maxLB = LB[i, -1]\n", " if min_dist < maxLB:\n", " P[i] = min_dist\n", " I[i] = idx\n", @@ -719,61 +701,61 @@ " global_min_maxLB = min(global_min_maxLB, maxLB)\n", " is_mp_valid[i] = False\n", " \n", - " n_invalid = np.sum(~is_mp_valid)\n", - " time_complexity_threshold = (n * np.log2(k) / np.log2(n))\n", - " \n", " global_min_dist = np.min(P)\n", - " if global_min_dist > global_min_maxLB:\n", - " if n_invalid < time_complexity_threshold:\n", - " for idx in np.flatnonzero(~is_mp_valid):\n", - " if global_min_dist <= maxLB_profile[idx]:\n", - " continue # Q: so, are we considering approx. best match?\n", - "\n", - " QT = core.sliding_dot_product(T[idx:idx+m], T)\n", - " D = core._mass(\n", - " T[idx:idx+m], \n", - " T, \n", - " QT, \n", - " μ_Q[idx], \n", - " σ_Q[idx], \n", - " M_T, \n", - " Σ_T, \n", - " Q_subseq_isconstant[idx], \n", - " T_subseq_isconstant\n", - " )\n", - " core.apply_exclusion_zone(D, idx, m, np.inf)\n", - "\n", - " arg = np.argmin(D)\n", - " if D[arg] < np.inf:\n", - " P[idx] = D[arg]\n", - " I[idx] = arg\n", - "\n", - " args_topk = np.argsort(D)[:k]\n", - " LB_I[idx] = args_topk\n", - "\n", - " ρ = 1.0 - np.square(D[args_topk]) / (2 * m)\n", - " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " r = np.sqrt(m * (1 - np.square(ρ_clipped)))\n", - " LB_σr[idx] = σ_Q[idx] * r\n", - "\n", - " else:\n", - " mp = stump(T, m, k=k)\n", - " P_TopK = mp[:, :k].astype(np.float64)\n", - " I_TopK = mp[:, k:2*k].astype(np.int64)\n", - "\n", - " ρ = 1.0 - np.square(P_TopK) / (2 * m)\n", - " ρ_clipped = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " r = np.sqrt(m * (1 - np.square(ρ_clipped)))\n", - " _, σ = core.compute_mean_std(T, m)\n", - " LB_σr = σ.reshape(-1,1) * r\n", - " LB_I = I_TopK\n", + " if global_min_dist <= global_min_maxLB:\n", + " return P, I, LB_σr, LB_I, is_mp_valid\n", " \n", - " return P, I, LB_σr, LB_I" + " if np.sum(~is_mp_valid) < (n * np.log2(k) / np.log2(n)):\n", + " for idx in np.flatnonzero(~is_mp_valid):\n", + " if global_min_dist <= maxLB_profile[idx]:\n", + " continue \n", + " \n", + " QT = core.sliding_dot_product(T[idx:idx+m], T)\n", + " D = core._mass(\n", + " T[idx:idx+m], \n", + " T, \n", + " QT, \n", + " μ_Q[idx], \n", + " σ_Q[idx], \n", + " M_T, \n", + " Σ_T, \n", + " Q_subseq_isconstant[idx], \n", + " T_subseq_isconstant\n", + " )\n", + " core.apply_exclusion_zone(D, idx, m, np.inf)\n", + "\n", + " arg = np.argmin(D)\n", + " if D[arg] < np.inf:\n", + " P[idx] = D[arg]\n", + " I[idx] = arg\n", + " global_min_dist = min(global_min_dist, P[idx])\n", + " \n", + " args_topk = np.argsort(D, kind='mergesort')[:k]\n", + " LB_I[idx] = args_topk\n", + "\n", + " ρ = 1.0 - np.square(D[args_topk]) / (2 * m)\n", + " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", + " LB_σr[idx] = σ_Q[idx] * np.sqrt(m * (1 - np.square(ρ)))\n", + " is_mp_valid[idx] = True\n", + "\n", + " else:\n", + " mp = stump(T, m, k=k)\n", + " P = mp[:, :k].astype(np.float64)\n", + " I = mp[:, k:2*k].astype(np.int64)\n", + "\n", + " ρ = 1.0 - np.square(P) / (2 * m)\n", + " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", + " _, σ = core.compute_mean_std(T, m)\n", + " LB_σr = σ.reshape(-1,1) * np.sqrt(m * (1 - np.square(ρ)))\n", + " LB_I = I\n", + " is_mp_valid[:] = True\n", + "\n", + " return P[:,0], I[:,0], LB_σr, LB_I, is_mp_valid" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 49, "id": "be7b439d", "metadata": {}, "outputs": [], @@ -820,11 +802,16 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 50, "id": "94eceff1", "metadata": {}, "outputs": [], "source": [ + "def print_verbose(msg, verbose=False):\n", + " if verbose:\n", + " print(msg)\n", + "\n", + "\n", "def VALMOD(T, m_min, m_max, k):\n", " \"\"\"\n", " This function finds the matrix profile of T_A while considering different length of subsequences in \n", @@ -861,12 +848,17 @@ " \n", " # out_P, out_I, out_M = _update_PIM(out_P, P_TopK[:,0] / np.sqrt(m), out_I, I_TopK[:, 0], out_M, m)\n", " LB_σr = None\n", + " is_exact = np.full(n, 1, dtype=bool)\n", " for m in range(m_min, m_max + 1):\n", " if LB_σr is None: # only runs for the first iteration, i,e, lowest `m` \n", - " P, I, LB_σr, LB_I = _VALMOD_stump(T, m, k)\n", + " idx = 1232\n", + " P, I, LB_σr, LB_I, is_mp_valid = _VALMOD_stump(T, m, k)\n", " else:\n", - " P, I, LB_σr, LB_I = _VALMOD_stump_partial(T, m, k, LB_σr, LB_I)\n", - " \n", + " P, I, LB_σr, LB_I, is_mp_valid = _VALMOD_stump_partial(T, m, k, LB_σr, LB_I)\n", + " \n", + " l = len(is_mp_valid) # which is: len(T) - m + 1 \n", + " is_exact[:l] = is_exact[:l] & is_mp_valid\n", + " \n", " _update_PIM(out_P, P/np.sqrt(m), out_I, I, out_M, m)\n", " \n", " out = np.empty((n, 3), dtype=object)\n", @@ -874,107 +866,106 @@ " out[:, 1] = out_I\n", " out[:, 2] = out_M\n", " \n", - " return out" + " return out, is_exact" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "9557a1ad", + "execution_count": 51, + "id": "d0800ab7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Computing time: 98.4311773777008\n" + "The computing time: 5.127043724060059\n", + "Computing time: 34.47108221054077\n" ] } ], "source": [ - "k=20\n", + "# Input\n", + "seed = 0\n", + "np.random.seed(seed)\n", + "T = np.random.rand(10000)\n", + "m_min = 50\n", + "m_max = 60\n", "\n", + "#####################\n", + "\n", + "# naive valmod: a simple for-loop, computing full mp for each `m`\n", "t_start = time.time()\n", - "valmod_mp = VALMOD(T, m_min, m_max, k)\n", + "mp_ref = naive_VALMOD(T, m_min, m_max)\n", "t_stop = time.time()\n", + "print(\"The computing time: \", t_stop - t_start)\n", + "\n", + "#####################\n", "\n", + "# valmod\n", + "t_start = time.time()\n", + "mp_comp, is_exact = VALMOD(T, m_min, m_max, k=20) # k=20 is provided by user\n", + "t_stop = time.time()\n", "print(\"Computing time: \", t_stop - t_start)" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "a6ff78e0", + "execution_count": 52, + "id": "b3f9d40b", "metadata": {}, "outputs": [], "source": [ - "ref = naive_VALMOD(T, m_min, m_max)\n", - "comp = VALMOD(T, m_min, m_max, k=10)" + "np.testing.assert_almost_equal(mp_ref[is_exact, 0], mp_comp[is_exact,0])" ] }, { "cell_type": "code", - "execution_count": 25, - "id": "f80bf53e", - "metadata": {}, - "outputs": [], - "source": [ - "# np.testing.assert_almost_equal(ref, comp)\n", - "# results in error as the paper's proposed method is approx. \n", - "# However, the global min is exact. " - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "cff941a8", + "execution_count": 53, + "id": "8aabf529", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "array([0.8414941313430254, 2031, 51], dtype=object)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" + "ename": "AssertionError", + "evalue": "\nArrays are not almost equal to 7 decimals\n\nMismatched elements: 5771 / 9915 (58.2%)\nMax absolute difference: 0.0592546542833442\nMax relative difference: 0.06382009396320394\n x: array([0.9452865772913406, 0.9344991685815902, 0.9092612749994912, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9439425333188787],\n dtype=object)\n y: array([0.9678644071613989, 0.9574466161924685, 0.9319605844727593, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9478057237030245],\n dtype=object)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[53], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtesting\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massert_almost_equal\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmp_ref\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m~\u001b[39;49m\u001b[43mis_exact\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmp_comp\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m~\u001b[39;49m\u001b[43mis_exact\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[0;31m[... skipping hidden 2 frame]\u001b[0m\n", + "File \u001b[0;32m~/miniconda3/envs/stumpypy39/lib/python3.10/site-packages/numpy/testing/_private/utils.py:844\u001b[0m, in \u001b[0;36massert_array_compare\u001b[0;34m(comparison, x, y, err_msg, verbose, header, precision, equal_nan, equal_inf)\u001b[0m\n\u001b[1;32m 840\u001b[0m err_msg \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(remarks)\n\u001b[1;32m 841\u001b[0m msg \u001b[38;5;241m=\u001b[39m build_err_msg([ox, oy], err_msg,\n\u001b[1;32m 842\u001b[0m verbose\u001b[38;5;241m=\u001b[39mverbose, header\u001b[38;5;241m=\u001b[39mheader,\n\u001b[1;32m 843\u001b[0m names\u001b[38;5;241m=\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m'\u001b[39m), precision\u001b[38;5;241m=\u001b[39mprecision)\n\u001b[0;32m--> 844\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(msg)\n\u001b[1;32m 845\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m:\n\u001b[1;32m 846\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtraceback\u001b[39;00m\n", + "\u001b[0;31mAssertionError\u001b[0m: \nArrays are not almost equal to 7 decimals\n\nMismatched elements: 5771 / 9915 (58.2%)\nMax absolute difference: 0.0592546542833442\nMax relative difference: 0.06382009396320394\n x: array([0.9452865772913406, 0.9344991685815902, 0.9092612749994912, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9439425333188787],\n dtype=object)\n y: array([0.9678644071613989, 0.9574466161924685, 0.9319605844727593, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9478057237030245],\n dtype=object)" + ] } ], "source": [ - "idx=np.argmin(ref[:,0])\n", - "ref[idx]" + "np.testing.assert_almost_equal(mp_ref[~is_exact, 0], mp_comp[~is_exact,0])" ] }, { "cell_type": "code", - "execution_count": 24, - "id": "bb7e87da", + "execution_count": 54, + "id": "9557a1ad", "metadata": {}, "outputs": [ { "data": { + "image/png": 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"text/plain": [ - "array([0.841494131343025, 2031, 51], dtype=object)" + "
" ] }, - "execution_count": 24, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "idx=np.argmin(comp[:,0])\n", - "comp[idx]" + "plt.figure(figsize=(30,3))\n", + "plt.plot(mp_ref[:,0], c='k', label='naive')\n", + "plt.plot(mp_comp[:,0], c='r', label='valmod')\n", + "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0b9d7321", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From 764ec9d32976bc3bd48f9700653b2034ef52148b Mon Sep 17 00:00:00 2001 From: NimaSarajpoor Date: Sat, 3 Jan 2026 00:14:17 -0500 Subject: [PATCH 65/67] Enhance Tutorial for VALMOD --- docs/Tutorial_VALMOD.ipynb | 152 ++++++++++++++++++++++++++----------- 1 file changed, 108 insertions(+), 44 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index f5c58265d..19ab48d6b 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 1, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -32,34 +32,6 @@ "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')" ] }, - { - "cell_type": "code", - "execution_count": 44, - "id": "44d283f8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.7444217828807693, 2, -1, 2],\n", - " [1.5382980393045818, 4, -1, 4],\n", - " [0.19836142937718138, 5, 0, 5],\n", - " [0.44958674269840077, 7, 0, 7],\n", - " [1.5382980393045818, 1, 1, 7],\n", - " [0.19836142937718138, 2, 2, 7],\n", - " [0.9901822253111079, 2, 2, -1],\n", - " [0.44958674269840077, 3, 3, -1]], dtype=object)" - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stump(np.random.rand(10), 3)" - ] - }, { "cell_type": "markdown", "id": "e9d48c97", @@ -73,7 +45,7 @@ "id": "b0423978", "metadata": {}, "source": [ - "**Notation:** $T_{i,m} = T[i:i+m]$ is a subsequence of `T` that starts at index `i` and has length `m`. " + "**Notation:** $T_{i,m} = T[i:i+m]$ is a subsequence of $T$ that starts at index `i` and has length `m`. " ] }, { @@ -89,9 +61,7 @@ "id": "78ac5b0f", "metadata": {}, "source": [ - "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set.\n", - "\n", - "We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set. We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", "\n", "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both of these two subsequences start from the same index." ] @@ -109,11 +79,11 @@ "id": "0f4ee615", "metadata": {}, "source": [ - "First, we need to provide a few definitions...\n", + "First, we need to provide a couple of definitions:\n", "\n", - "**$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", + "* **$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", "\n", - "**$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequences and their ($n^{th}$) best match.
\n", + "* **$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequences and their ($n^{th}$) best match.
\n", "\n", "**NOTE**:
\n", "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" @@ -164,7 +134,7 @@ "metadata": {}, "source": [ "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series `T`, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each `k` in $\\{1,...,K\\}$, for each `n` in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + "Given a time series $T$, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each $k$ in $\\{1,...,K\\}$, for each $n$ in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." ] }, { @@ -175,12 +145,106 @@ "# 2-Lower Bound of Distance Profile" ] }, + { + "cell_type": "markdown", + "id": "b014af81-30c0-4ab9-9081-3db57f173054", + "metadata": {}, + "source": [ + "Suppose we know the distance between $T_{j,m}$ and $T_{i,m}$. Let $d_{j,i}^{(m)}$ denote that distance. What can we say about $d_{j,i}^{(m+1)}$? In other words, if I know the distance between `T[j:j+m]`and `T[i:i+m]`, what can I say about the distance between `T[j:j+(m+1)]` and `T[i:i+(m+1)]`? If it is a non-normalized (p-norm) distance, there is an easy answer: $d_{j,i}^{(m+1)} \\ge d_{j,i}^{(m)}$\n", + "\n", + "But... \n", + "\n", + "What about normalized euclidean distance? Although the above relationship is not guaranteed to be true in this case, the authors discovered another relationship:\n", + "\n", + "$d_{j,i}^{(m+1)} \\ge LB$. The LowerBound is $LB$: $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+1}}\\sqrt{m(1-r^{2})}$, where $r=max(\\rho_{j,i}^{m}, 0)$. If we follow the notation in the paper, this lower bound can be shown as $LB_{j,i}^{(m+1)}$. However, this does not show the \"reference\" (i.e. the subsequence length) based on which the lower bound was calculated. I think it is better to use the following notation instead: $LB_{j,i,m}^{(m+1)}$\n", + "\n", + "\n", + "
\n", + "It can be shown that the formula can be extended to compute the lower bound for $LB_{j,i,m}^{m+k}$. The formula is as follows:\n", + "\n", + "$LB_{j,i,m}^{(m+k)} = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{m(1-r^{2})}$, where $r=max(\\rho_{j,i}^{m}, 0)$. \n", + "\n", + "\n", + "---\n", + "\n", + "As a side, the following relationship exists between $\\rho_{j,i}^{m}$ and $d_{j,i}^{m}$. \n", + "\n", + "$$\n", + "\\begin{align}\n", + "d^{(m)}_{j,i} ={}& \n", + "\\sqrt{\n", + "2m \\left(\n", + "1-\\rho^{(m)}_{j,i}\n", + "\\right)\n", + "}\n", + "\\\\\n", + "\\end{align}\n", + "$$" + ] + }, { "cell_type": "markdown", "id": "8538f0e3", "metadata": {}, "source": [ - "Lower Bound (LB) for $d_{j,i}^{(m+k)} = d(T_{j,m+k}, T_{i,m+k})$ can be calculated as follows:" + "## Example:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f8d60146-0150-4c8e-b5f2-da0a1a29f2de", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "T = np.random.rand(100)\n", + "m = 5\n", + "\n", + "Q = T[0:0+m]\n", + "D = core.mass(Q, T)\n", + "\n", + "m_new = m + 1\n", + "Q_new = T[0:0+m_new]\n", + "D_new = core.mass(Q_new, T)\n", + "\n", + "# Now, we calculate LB using `D` and see if it is <= D_new...\n", + "_, Σ_T = core.compute_mean_std(T, m)\n", + "_, Σ_T_new = core.compute_mean_std(T, m_new)\n", + "\n", + "# compute \\rho based on distance\n", + "R = 1.0 - np.square(D) / (2 * m)\n", + "r = np.maximum(R, 0.0) # r is between 0 and 1\n", + "\n", + "# LB formula\n", + "l_new = len(T) - m_new + 1\n", + "LB = (Σ_T[:l_new] / Σ_T_new[:l_new]) * np.sqrt(m * (1 - np.square(r[:l_new]))) \n", + "\n", + "# note that we do not need to slice `Σ_T_new` as its full length is l_new. This was added to just be consistent\n", + "\n", + "plt.figure(figsize=(15, 5))\n", + "plt.plot(D_new, color='b', label='actual distance profile')\n", + "plt.plot(LB, color='r', label='lower bound for distance profile')\n", + "plt.legend(title='profile for m_new')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "832fc0d9-b8e4-4bf0-8fb7-e76540597640", + "metadata": {}, + "source": [ + "As observed, the plot for LB is below the actual distance profile!" ] }, { @@ -188,7 +252,7 @@ "id": "a7f08024", "metadata": {}, "source": [ - "**Non-normalized distance (p-norm):**" + "## 2-1: Non-normalized distance (p-norm):" ] }, { @@ -210,7 +274,7 @@ "id": "7ff2e666", "metadata": {}, "source": [ - "**Normalized distance(see eq(2) of the paper):**" + "## 2-2: Normalized distance(see eq(2) of the paper):" ] }, { @@ -260,7 +324,7 @@ "id": "1e23d962", "metadata": {}, "source": [ - "Alternatively, $\\rho^{(m)}_{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" + "As a side: $\\rho^{(m)}_{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" ] }, { @@ -517,7 +581,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 2, "id": "4a17e969", "metadata": {}, "outputs": [], @@ -534,7 +598,7 @@ " P = mp[:,0].astype(np.float64)\n", " I = mp[:,1].astype(np.int64)\n", " \n", - " P[:] = P / np.sqrt(m)\n", + " P[:] = P / np.sqrt(m) # scale by 1/sqrt(m) to allow us compare distances of a pair of subsequence with another pair when their lengths are different.\n", " \n", " l = len(P)\n", " mask = P < out_P[:l]\n", @@ -984,7 +1048,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.14.2" } }, "nbformat": 4, From bab59616a518a1216ec865fe3ef54fe694d022c5 Mon Sep 17 00:00:00 2001 From: NimaSarajpoor Date: Sun, 18 Jan 2026 23:20:26 -0500 Subject: [PATCH 66/67] Update VALMOD Tutorial --- docs/Tutorial_VALMOD.ipynb | 1294 ++++++++++++++++++------------------ 1 file changed, 639 insertions(+), 655 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index 19ab48d6b..a6b88c03c 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -5,14 +5,12 @@ "id": "c7a27406", "metadata": {}, "source": [ - "In this tutorial, we would like to implement VALMOD algorithm proposed in paper [VALMOD](https://arxiv.org/pdf/2008.13447.pdf), and reproduce its results as closely as possible.\n", - "\n", - "The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and a range of subsequence length `[min_m, max_m]`, and find motifs and discords." + "In this tutorial, we would like to implement [VALMOD](https://arxiv.org/pdf/2008.13447.pdf) algorithm. The **VAriable Length MOtif Discovery (VALMOD)** algorithm takes time series `T` and the range of subsequence length `[min_m, max_m]`, and find motifs and discords." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -45,160 +43,170 @@ "id": "b0423978", "metadata": {}, "source": [ - "**Notation:** $T_{i,m} = T[i:i+m]$ is a subsequence of $T$ that starts at index `i` and has length `m`. " + "Matrix profile provides an efficient algorithm for finding the exact motif pair of a time series for a given window size. However, searching for motifs with different lengths can result in different motif pairs that might be of interest. Given a data series\n", + "`T` and a subsequence length-range `[m_min,...,m_max]`, we want to find the motif pairs of all lengths in `[m_min,...,m_max]`. One approach is to compute matrix profile for each subsequence length in `[m_min, ..., m_max]`. However, [VALMOD](https://arxiv.org/pdf/2008.13447.pdf) provides an alternative approach that should speed up this data mining task for real-world data. VALMOD takes advantage of the previously-computed distances to compute the lower bounds of distances for subsequences with longer window sizes. Then, it uses those lower bound values to find an approximate matrix profile." ] }, { "cell_type": "markdown", - "id": "4a4af7fd", + "id": "d2950b0f-1329-4d8e-98cb-5c001035383e", "metadata": {}, "source": [ - "## Motif discovery" + "## 2. The Lower Bound (LB) of Distance" ] }, { "cell_type": "markdown", - "id": "78ac5b0f", + "id": "b014af81-30c0-4ab9-9081-3db57f173054", "metadata": {}, "source": [ - "For a given motif pair $\\{T_{idx,m},T_{nn\\_idx,n}\\}$, Motif set $S^{m}_{r}$ is a set of subsequences of length `m` that has `distance < r` to either $T_{idx,m}$ or $T_{nn\\_idx,n}$. And, the cardinality of set is called the frequency of the motif set. We would like to find set $S^{*} = \\bigcup\\limits_{m=min\\_m}^{max\\_m}{S^{m}_{r}}$, and $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$. In other words, we want to find motif sets for different length `m` and we want to make sure there is no \"common\" (see note below) subsequence between any two motif sets. \n", + "Suppose the z-normalized distance between $T_{i,m}=T[i:i+m]$ and $T_{j,m}=T[j:j+m]$ was already calculated. Let $d_{i,j}^{(m)}$ denote that distance. VALMOD shows that $d_{i,j}^{(m+1)} \\ge LB_{i,j,m}^{(m+1)}$, where $LB_{i,j,m}^{(m+1)}$ is calculated as follows:\n", + "\n", + "$$LB_{i,j,m}^{(m+1)} = \\frac{\\sigma_{i,m}}{\\sigma_{i,m+1}}\\sqrt{m(1-r^{2})}$$ \n", + "\n", + "where: $$r=max(\\rho_{i,j}^{(m)}, 0)$$ \n", "\n", - "**NOTE:** The subsequences in motif set of length m and m' are indeed different because they have different length. However, by the constraint $S^{m}_{r} \\cap S^{m'}_{r'} = \\emptyset$, the authors meant to avoid considering two subsequences (of different length) that start from the same index. For instance, if $T_{200,m}$ is in one set and $T_{200,m'}$ in another set, the authors consider the intersection of their corresponding set to be non-empty because both of these two subsequences start from the same index." + "\n", + "$\\rho_{i,j,m}$ is the pearson correlation between the two subsequences $T_{i,m}=T[i:i+m]$ and $T_{j,m}=T[j:j+m]$, and has the following relationship with its corresponding distance: \n", + "\n", + "$$\n", + "\\begin{align}\n", + "d^{(m)}_{j,i} ={}& \n", + "\\sqrt{\n", + "2m \\left(\n", + "1-\\rho^{(m)}_{j,i}\n", + "\\right)\n", + "}\n", + "\\\\\n", + "\\end{align}\n", + "$$" ] }, { "cell_type": "markdown", - "id": "7fc09927", + "id": "43e87eda-3d09-4dcd-b4b6-b14985b69a98", "metadata": {}, "source": [ - "## Discord Discovery" + "**Note:** We can use $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+1}}$ instead when computing $LB_{i,j,m}^{(m+1)}$, which can give a different value." ] }, { "cell_type": "markdown", - "id": "0f4ee615", + "id": "8538f0e3", "metadata": {}, "source": [ - "First, we need to provide a couple of definitions:\n", - "\n", - "* **$n^{th}$ best match**: For the subsequence $T_{i,m}$, its $n^{th}$ best match is simply the $n^{th}$ smallest distance in the distance profile.
\n", - "\n", - "* **$n^{th}$ discord**: a subsequence $T_{i,m}$ is the $n^{th}$ discord if it has the largest value to its $n^{th}$ best match compared to the distances between any other subsequences and their ($n^{th}$) best match.
\n", - "\n", - "**NOTE**:
\n", - "Why should we care about $n^{th}$ discord (n>1)? We provide a simple example below:" + "### Example" ] }, { - "cell_type": "code", - "execution_count": 45, - "id": "37fdbb26", + "cell_type": "markdown", + "id": "13568235-41d1-42ca-a45e-e83af7cce79a", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ - "T = np.random.uniform(-100,100,size=3000)\n", - "m = 200\n", - "i, j = 100, 1500\n", - "\n", - "T[i:i+m] = 0\n", - "T[j:j+m] = 0\n", - "\n", - "plt.plot(T)\n", - "plt.show()" + "The following example computes the actual distance and its LB" ] }, { - "cell_type": "markdown", - "id": "cb3a3940", + "cell_type": "code", + "execution_count": 4, + "id": "1b34e09e-118e-4749-8bce-56aac05e6314", "metadata": {}, + "outputs": [], "source": [ - "Here, the subsequences at index `i` and `j` can be considered an anomaly. However, the 1NN distance is 0 for them. Therefore, we may need to investigate other neighbors rather than just 1NN. In discord discovery, it is called twin-freak problem (see [Tutorial](https://cci.drexel.edu/bigdata/bigdata2017/files/Tutorial4.pdf)). It happens when the (same) anomally occurs more than once. In our example above, the anomaly occurs twice. Therefore, we should be able to detect it if we consider 2nd nearest neighbor. \n", + "T = np.random.rand(100)\n", + "m = 5\n", + "\n", + "# Compute distance profile between the query Q and T\n", + "Q = np.random.rand(m)\n", + "D = core.mass(Q, T)\n", "\n", - "For further details, see Fig. 2 of the paper." + "# Add one new element to the existing Q\n", + "Q_new = np.append(Q, np.random.rand())\n", + "D_new = core.mass(Q_new, T)" ] }, { "cell_type": "markdown", - "id": "45eeecf5", + "id": "cfaeca12-d9f0-4702-8b06-58f32dbdfdce", "metadata": {}, "source": [ - "**Variable-length Top-k $n^{th}$ Discord Discovery:**
\n", - "Given a time series $T$, a subsequence length-range `[min_m, max_m]`,`K`, and `N`, we want to find **top-k $n^{th}$ discord** for each $k$ in $\\{1,...,K\\}$, for each $n$ in $\\{1,...,N\\}$, and for all `m` in $\\{min\\_m,...,max\\_m\\}$." + "Let's compute the LowerBound (LB) for D_new. `D[i]` represents the distance between `Q` and `T[i:i+m]`. \n", + "`D_new[i]` represents the distance between `Q_new` and `T[i:i+(m+1)]`. Recall that $LB = \\frac{\\sigma_{i,m}}{\\sigma_{i,m+1}}\\sqrt{m(1-r^{2})}$, where $r=max(\\rho_{i,j}^{m}, 0)$. The factor $\\frac{\\sigma_{m}}{\\sigma_{m+1}}$ can be computed based on `Q` or based on subsequence in `T`! Let's try both and check out the results." ] }, { "cell_type": "markdown", - "id": "e503fb0a", + "id": "9534d4b0-327b-4f9b-84e4-98fae862603f", "metadata": {}, "source": [ - "# 2-Lower Bound of Distance Profile" + "#### Option 1\n", + "Compute LB by considering the change of standard deviation in Q:" ] }, { - "cell_type": "markdown", - "id": "b014af81-30c0-4ab9-9081-3db57f173054", + "cell_type": "code", + "execution_count": 5, + "id": "640f06fd-be97-40e1-a0e3-21d9681acbe1", "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Suppose we know the distance between $T_{j,m}$ and $T_{i,m}$. Let $d_{j,i}^{(m)}$ denote that distance. What can we say about $d_{j,i}^{(m+1)}$? In other words, if I know the distance between `T[j:j+m]`and `T[i:i+m]`, what can I say about the distance between `T[j:j+(m+1)]` and `T[i:i+(m+1)]`? If it is a non-normalized (p-norm) distance, there is an easy answer: $d_{j,i}^{(m+1)} \\ge d_{j,i}^{(m)}$\n", - "\n", - "But... \n", - "\n", - "What about normalized euclidean distance? Although the above relationship is not guaranteed to be true in this case, the authors discovered another relationship:\n", - "\n", - "$d_{j,i}^{(m+1)} \\ge LB$. The LowerBound is $LB$: $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+1}}\\sqrt{m(1-r^{2})}$, where $r=max(\\rho_{j,i}^{m}, 0)$. If we follow the notation in the paper, this lower bound can be shown as $LB_{j,i}^{(m+1)}$. However, this does not show the \"reference\" (i.e. the subsequence length) based on which the lower bound was calculated. I think it is better to use the following notation instead: $LB_{j,i,m}^{(m+1)}$\n", - "\n", - "\n", - "
\n", - "It can be shown that the formula can be extended to compute the lower bound for $LB_{j,i,m}^{m+k}$. The formula is as follows:\n", + "σ_Q = np.std(Q)\n", + "σ_Q_new = np.std(Q_new)\n", "\n", - "$LB_{j,i,m}^{(m+k)} = \\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\\sqrt{m(1-r^{2})}$, where $r=max(\\rho_{j,i}^{m}, 0)$. \n", + "l_new = len(T) - len(Q_new) + 1\n", + "ρ = 1.0 - np.square(D) / (2 * m)\n", + "ρ[:l_new] = np.clip(ρ[:l_new], a_min=0, a_max=1.0)\n", "\n", + "LB_option_1 = (σ_Q / σ_Q_new) * np.sqrt(m * (1 - np.square(ρ[:l_new])))\n", "\n", - "---\n", + "# assertion\n", + "assert np.all(LB_option_1 <= D_new)\n", "\n", - "As a side, the following relationship exists between $\\rho_{j,i}^{m}$ and $d_{j,i}^{m}$. \n", - "\n", - "$$\n", - "\\begin{align}\n", - "d^{(m)}_{j,i} ={}& \n", - "\\sqrt{\n", - "2m \\left(\n", - "1-\\rho^{(m)}_{j,i}\n", - "\\right)\n", - "}\n", - "\\\\\n", - "\\end{align}\n", - "$$" + "# plot\n", + "plt.figure(figsize=(15, 5))\n", + "plt.title('Plotting distance profile and its lower bound (Option 1)')\n", + "plt.plot(D_new, color='k', label='The actual distance profile')\n", + "plt.plot(LB_option_1, color='b', label='The LowerBound of distance profile')\n", + "plt.legend(title='distance profile for Q_new')\n", + "plt.show()" ] }, { "cell_type": "markdown", - "id": "8538f0e3", + "id": "11315c2d-deb8-4c5f-87fa-e70911750d3c", + "metadata": {}, + "source": [ + "#### Option 2" + ] + }, + { + "cell_type": "markdown", + "id": "e60198ad-ebf3-492c-a09a-bd7666286f33", "metadata": {}, "source": [ - "## Example:" + "Compute LB by considering the change of standard deviation in the subsequences of T:" ] }, { "cell_type": "code", "execution_count": 6, - "id": "f8d60146-0150-4c8e-b5f2-da0a1a29f2de", + "id": "10ef76a0-aba9-4742-9d51-1f4630e43e51", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -208,302 +216,278 @@ } ], "source": [ - "T = np.random.rand(100)\n", - "m = 5\n", - "\n", - "Q = T[0:0+m]\n", - "D = core.mass(Q, T)\n", - "\n", - "m_new = m + 1\n", - "Q_new = T[0:0+m_new]\n", - "D_new = core.mass(Q_new, T)\n", - "\n", - "# Now, we calculate LB using `D` and see if it is <= D_new...\n", "_, Σ_T = core.compute_mean_std(T, m)\n", - "_, Σ_T_new = core.compute_mean_std(T, m_new)\n", + "_, Σ_T_new = core.compute_mean_std(T, len(Q_new))\n", "\n", - "# compute \\rho based on distance\n", - "R = 1.0 - np.square(D) / (2 * m)\n", - "r = np.maximum(R, 0.0) # r is between 0 and 1\n", + "l_new = len(T) - len(Q_new) + 1\n", + "ρ = 1.0 - np.square(D) / (2 * m)\n", + "ρ[:l_new] = np.clip(ρ[:l_new], a_min=0, a_max=1.0)\n", "\n", - "# LB formula\n", - "l_new = len(T) - m_new + 1\n", - "LB = (Σ_T[:l_new] / Σ_T_new[:l_new]) * np.sqrt(m * (1 - np.square(r[:l_new]))) \n", + "LB_option_2 = (Σ_T[:l_new] / Σ_T_new[:l_new]) * np.sqrt(m * (1 - np.square(ρ[:l_new]))) \n", "\n", - "# note that we do not need to slice `Σ_T_new` as its full length is l_new. This was added to just be consistent\n", + "# assertion\n", + "assert np.all(LB_option_2 <= D_new)\n", "\n", + "# plot\n", "plt.figure(figsize=(15, 5))\n", - "plt.plot(D_new, color='b', label='actual distance profile')\n", - "plt.plot(LB, color='r', label='lower bound for distance profile')\n", - "plt.legend(title='profile for m_new')\n", + "plt.title('Plotting distance profile and its lower bound (Option 2)')\n", + "plt.plot(D_new, color='k', label='The actual distance profile')\n", + "plt.plot(LB_option_2, color='r', label='The LowerBound of distance profile')\n", + "plt.legend(title='distance profile for Q_new')\n", "plt.show()" ] }, { "cell_type": "markdown", - "id": "832fc0d9-b8e4-4bf0-8fb7-e76540597640", + "id": "dda51563-f24f-4889-a0fb-9eea936aa6a3", "metadata": {}, "source": [ - "As observed, the plot for LB is below the actual distance profile!" + "#### Plot both Option 1 and Option 2" ] }, { - "cell_type": "markdown", - "id": "a7f08024", + "cell_type": "code", + "execution_count": 7, + "id": "78e4d806-2c56-40d0-8636-9a385e4e592b", "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "## 2-1: Non-normalized distance (p-norm):" + "plt.figure(figsize=(15, 5))\n", + "plt.title('Plotting distance profile and its lower bound')\n", + "plt.plot(D_new, color='k', label='The actual distance profile')\n", + "plt.plot(LB_option_1, color='b', label='The LowerBound of distance profile (Option 1)')\n", + "plt.plot(LB_option_2, color='r', label='The LowerBound of distance profile (Option 2)')\n", + "plt.legend(title='distance profile for Q_new')\n", + "plt.show()" ] }, { "cell_type": "markdown", - "id": "297e8f9e", + "id": "a478eba2-e372-4861-b872-32e7ea8db784", "metadata": {}, "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "LB_{j,i}^{(m+k)} ={}& \n", - "d_{j,i}^{(m)} \\quad (1)\n", - "\\end{align}\n", - "$$\n" + "At some indices, `Option 1` gives a tighter LB, and at other indices `Option 2` gives a tigher LB. Recall that $LB = \\frac{\\sigma_{i,m}}{\\sigma_{i,m+1}}\\sqrt{m(1-r^{2})}$. The second part, i.e. $\\sqrt{m(1-r^{2})}$, is the same in both Option 1 and Option 2. The first part, however, is different between the two options. The larger the std-based factor, the tigher the LowerBound (LB)." ] }, { "cell_type": "markdown", - "id": "7ff2e666", + "id": "37413954-2756-49fa-baca-25efbc9cdcf3", "metadata": {}, "source": [ - "## 2-2: Normalized distance(see eq(2) of the paper):" + "#### Option 3 (Best of Option 1 & 2)" ] }, { - "cell_type": "markdown", - "id": "0f192dfa", + "cell_type": "code", + "execution_count": 8, + "id": "824fe60a-8df1-4db4-a7b6-a6283f671138", "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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YYyqPfeC/80Pr1q1haWmJc+fOwdXVFSkpKejcuTMeP36MdevWISsrC+fOnYOHhwd/zJVkfyzufFUUVX3OxV3c+Y0T7UqCJucvdTGmpKSUeN0EQRAEoQ4SvgiCIIgKjbe3t1Y3v9zNW1pamsJnT58+hVAohJ2dXanFpw2VK1dGQUEBMjIy5MSvZ8+eaTy/sraazh8cHIzg4GDk5eXh6tWrWLZsGQYNGgR3d3e0atVK5Xxv377F8ePHsXDhQsyZM4efnpeXh4yMDI3WXRSuRtvjx4/h6uqqtE2VKlUAAOvWrVM5MqImoqGqPit6o19U3AIK+/zff/8FY0zu8xcvXqCgoICP8WPglhESEsLXDSuKl5eXyvn37t0LExMTHD9+HObm5vz0I0eOlDimj93XtMHY2BgzZszAjBkz8ObNG5w7dw7ffvstAgMD8ejRI41Fajs7OwiFQpXHPvBfX5uamqJt27Y4d+4cqlevDicnJzRo0AAeHh4ACgdGCAsLQ48ePfhllGR/VLZPqUNVn3t6egIo/vwmuz+am5srDK4BqBdR1cGtW1f7BUEQBEFwUKojQRAEQcjg5eWFatWqYffu3XIjsWVnZ+PgwYP8SI+AoqNBlqIOmNLA398fAPgi2xx79+7VaP727dsjPj5ewam0e/dureIwMzODv78/fvzxRwDgRzhU1R8CgQCMMf5zjs2bN0MikWi1bo4uXbrAyMgI69evV9mmTZs2sLW1RUJCApo2bar0ZWpqWuy69uzZI7cvPHz4EFeuXFE64l1ROnbsiKysLAURiRvJjhv58WPw8vJC7dq1ERsbq3I7ra2tVc4vEAhgbGwsl6aWk5ODnTt3ljim9u3bIywsjHc5AYBEIlHYd7VBk2PK1tYWffv2xcSJE5GRkaGVi8jKygotWrTAoUOH5NYjlUrxxx9/oHr16qhTpw4/vVOnToiKisLBgwf5dEYrKyu0bNkS69atw9OnT/npQOntj+rYtWuX3PsrV67g4cOH/L7aqlUrWFhY4I8//pBr9/jxY5w/f15uf3R3d8fdu3f50UeBQtcWl96pLV5eXnB2dlZ5PBEEQRBEWUGOL4IgCIKQQSgUYvny5Rg8eDB69OiBr776Cnl5eVixYgXevHmDH374gW/boEEDAMCaNWswfPhwmJiYwMvLC9bW1mjQoAH27t2Lffv2wcPDA+bm5nz7ktK1a1e0adMGM2fORGZmJpo0aYLIyEheRJGtSaaMadOmYevWrejevTu+++47ODo6YteuXbh9+3ax616wYAEeP36Mjh07onr16njz5g3WrFkDExMTXpCrVasWLCwssGvXLnh7e0MkEsHFxQUuLi5o164dVqxYgSpVqsDd3R3h4eHYsmULbG1tS9QX7u7u+Pbbb7FkyRLk5ORg4MCBsLGxQUJCAl69eoXFixdDJBJh3bp1GD58ODIyMtC3b184ODjg5cuXiI2NxcuXL9UKZxwvXrxA7969MXbsWLx9+xYLFy6Eubk5QkJCip132LBh+PXXXzF8+HCkpKSgQYMGiIiIwNKlSxEUFCQnjHwMGzduRLdu3RAYGIgRI0agWrVqyMjIQGJiIqKjo3HgwAGV83bv3h0///wzBg0ahHHjxiE9PR0//fSTglCpDfPmzcNff/2FDh06YMGCBbC0tMSvv/6qUU01Vag6pnr27In69eujadOmqFq1Kh4+fIjVq1fDzc0NtWvX1mody5YtQ+fOndG+fXvMmjULpqam+O2333Dr1i3s2bNHzoHVsWNHSCQShIWFYfv27fz0Tp06YeHChRAIBOjQoQM/vbT2R3Vcv34dY8aMQb9+/fDo0SPMnTsX1apVw4QJEwAUCoPz58/Ht99+i2HDhmHgwIFIT0/H4sWLYW5ujoULF/LLGjp0KDZu3IghQ4Zg7NixSE9Px/LlyxXSeTVFKBRiyZIlGDNmDH88vXnzBosWLSqTFFiCIAiC4NFnZX2CIAiCKCu4Uc7EYrHadspGyGOMsSNHjrAWLVowc3NzZmVlxTp27MguX76sMH9ISAhzcXFhQqFQbjkpKSmsS5cuzNramgHgRyxTN6rjy5cvlW6D7Ah4GRkZbOTIkczW1pZZWlqyzp07s6tXrzIAcqMjqiIhIYF17tyZmZubM3t7ezZ69Gh29OjRYkd1PH78OOvWrRurVq0aMzU1ZQ4ODiwoKIhdunRJbvl79uxhdevWZSYmJnKjET5+/Jj16dOH2dnZMWtra9a1a1d269Yt5ubmxoYPH66wzUW/N1Xf044dO1izZs2Yubk5E4lErFGjRgqjSoaHh7Pu3bsze3t7ZmJiwqpVq8a6d+/ODhw4oLavuHXu3LmTTZkyhVWtWpWZmZmxzz77jF2/fl2u7fDhw5mVlZXS5aSnp7Px48czZ2dnZmxszNzc3FhISAg/IiDHx4zqyBhjsbGxrH///szBwYGZmJgwJycn1qFDB7Zhwwa128kYY1u3bmVeXl7MzMyMeXh4sGXLlrEtW7Yo7H9ubm6se/fuCvMrGwHw8uXLrGXLlszMzIw5OTmxr7/+mv3+++8lHtVR1TG1cuVK1rp1a1alShVmamrKatSowUaPHs1SUlLUrkPZscgYY5cuXWIdOnRgVlZWzMLCgrVs2ZIdO3ZMYX6pVMqqVKnCALAnT57IbTf+/2igytBkf1R1TlAFd9ycOXOGDR06lNna2vKjN967d0+h/ebNm5mvry8zNTVlNjY2LDg4mMXHxyu02759O/P29mbm5ubMx8eH7du3T+WojitWrFCYv+i+y627du3azNTUlNWpU4dt3bpVYZkEQRAEUZoIGJPxGhMEQRAEUe7YvXs3Bg8ejMuXL9PoaKXIxYsX0b59exw4cEBtQXKCIAiCIAjCcKFUR4IgCIIoR+zZswdPnjxBgwYNIBQKcfXqVaxYsQLt2rUj0YsgCIIgCIIgikDCF0EQBEGUI6ytrbF371589913yM7OhrOzM0aMGIHvvvtO36ERBEEQBEEQhMFBqY4EQRAEQRAEQRAEQRBEhUT98E9FWLRoEQQCgdyruFFYwsPD0aRJE5ibm8PDwwMbNmz4qIAJgiAIgiAIgiAIgiAIQhO0TnWsV68ezp07x783MjJS2TY5ORlBQUEYO3Ys/vjjD1y+fBkTJkxA1apV0adPn5JFTBAEQRAEQRAEQRAEQRAaoLXwZWxsXKzLi2PDhg2oUaMGVq9eDQDw9vbG9evX8dNPP5HwRRAEQRAEQRAEQRAEQZQpWgtf9+7dg4uLC8zMzNCiRQssXboUHh4eSttGRkaiS5cuctMCAwOxZcsW5Ofnw8TERKN1SqVSPH36FNbW1hAIBNqGTBAEQRAEQRAEQRAEQVQQGGN49+4dXFxcIBSqr+KllfDVokUL7NixA3Xq1MHz58/x3XffoXXr1oiPj0flypUV2j979gyOjo5y0xwdHVFQUIBXr17B2dlZ6Xry8vKQl5fHv3/y5Al8fHy0CZUgCIIgCIIgCIIgCIKowDx69AjVq1dX20Yr4atbt278/w0aNECrVq1Qq1YtbN++HTNmzFA6T1GHFjeIpDrn1rJly7B48WKF6Y8ePUKlSpW0CZkgCIIgCIIgCIIgCIKoQGRmZsLV1RXW1tbFttU61VEWKysrNGjQAPfu3VP6uZOTE549eyY37cWLFzA2NlbqEOMICQmRE9K4DapUqRIJXwRBEARBEARBEARBEIRG5bA+SvjKy8tDYmIiPvvsM6Wft2rVCseOHZObdubMGTRt2lRtfS8zMzOYmZl9TGgEQRAEQRAEQRAEQRDEJ476CmBFmDVrFsLDw5GcnIx///0Xffv2RWZmJoYPHw6g0Kk1bNgwvv348ePx8OFDzJgxA4mJidi6dSu2bNmCWbNmle5WEARBEARBEARBEARBEEQRtHJ8PX78GAMHDsSrV69QtWpVtGzZElevXoWbmxsAIC0tDampqXz7mjVr4uTJk5g+fTp+/fVXuLi4YO3atejTp0/pbgVBEARBEARBEARBEARBFEHAuGrzBkxmZiZsbGzw9u1btTW+JBIJ8vPzdRgZQRAE8bGYmJjAyMhI32EQBEEQBEEQBFFO0FQnAj6yxpehwBjDs2fP8ObNG32HQhAEQZQAW1tbODk5aVSckiAIgiAIgiAIQlMqhPDFiV4ODg6wtLSkGyeCIIhyAmMM79+/x4sXLwAAzs7Oeo6IIAiCIAiCIIiKRLkXviQSCS96Va5cWd/hEARBEFpiYWEBAHjx4gUcHBwo7ZEgCIIgCIIgiFJDq1EdDRGuppelpaWeIyEIgiBKCncOpzqNBEEQBEEQBEGUJuVe+OKg9EaCIIjyC53DCYIgCIIgCIIoCyqM8EUQBEEQBEEQBEEQBEEQspDwRZQ6AQEBmDZtGv/e3d0dq1ev1ls85ZVFixbB0dERAoEAR44cwYgRI9CrVy/+86L9XBKePXuGzp07w8rKCra2th+1LIIgCIIgCIIgCIIwNMp9cXvC8BGLxbCystKorbu7O6ZNm/bRgk55JzExEYsXL8bhw4fRsmVL2NnZoX379mCMlep6Vq1ahbS0NMTExMDGxqZUlw0UDj6xdu1abNu2DXfv3oW5uTlatWqFefPmoU2bNqW+PoIgCIIgCIIgCIKQhRxfRJlTtWpVGnzg//PhwweN2iUlJQEAgoOD4eTkBDMzM9jY2JS6KyspKQlNmjRB7dq14eDgUKJlqCpGzhjDl19+if/973+YMmUKEhMTER4eDldXVwQEBODIkSMfETlBEARBEARBEARBFA8JXxUMiUSCvLw8na0vOzsbw4YNg0gkgrOzM1auXKnQpmiq46JFi1CjRg2YmZnBxcUFU6ZMAVCYuvfw4UNMnz4dAoGAL3adnp6OgQMHonr16rC0tESDBg2wZ88euXUEBARgypQpmD17Nuzt7eHk5IRFixbJtXnz5g3GjRsHR0dHmJubo379+jh+/Dj/+ZUrV9CuXTtYWFjA1dUVU6ZMQXZ2tsptX7RoERo2bIiNGzfC1dUVlpaW6NevH968ecO34dITly1bBhcXF9SpUwcAEBcXhw4dOsDCwgKVK1fGuHHjkJWVxS+3Z8+eAAChUMj3Q9FUx6J8+PABs2fPRrVq1WBlZYUWLVrg4sWLKtu7u7vj4MGD2LFjBwQCAUaMGAEASE1NRXBwMEQiESpVqoT+/fvj+fPnCtu9detWeHh4wMzMTKkTbf/+/fjzzz+xY8cOjBkzBjVr1oSfnx9+//13fP755xgzZoza/i26vp07d8Ld3R02Njb48ssv8e7dO74NYwzLly+Hh4cHLCws4Ofnhz///JP/vEmTJnL7Zq9evWBsbIzMzEwAhSmfAoEAd+7cKTYegiAIgiAIgiAIovxAwlcF4/79+4iLi9OZ+PX111/jwoULOHz4MM6cOYOLFy8iKipKZfs///wTq1atwsaNG3Hv3j0cOXIEDRo0AAAcOnQI1atXx//+9z+kpaUhLS0NAJCbm4smTZrg+PHjuHXrFsaNG4ehQ4fi33//lVv29u3bYWVlhX///RfLly/H//73P5w9exYAIJVK0a1bN1y5cgV//PEHEhIS8MMPP8DIyAhAoRAVGBiIL774Ajdv3sS+ffsQERGBSZMmqd3++/fvY//+/Th27BhOnTqFmJgYTJw4Ua5NWFgYEhMTcfbsWRw/fhzv379H165dYWdnB7FYjAMHDuDcuXP8umbNmoVt27YBgFw/FMfIkSNx+fJl7N27Fzdv3kS/fv3QtWtX3Lt3T2l7sViMrl27on///khLS8OaNWvAGEOvXr2QkZGB8PBwnD17FklJSRgwYIDS7T548CBiYmKULn/37t2oU6cOL+LJMnPmTKSnp/PfT3EkJSXhyJEjOH78OI4fP47w8HD88MMP/Ofz5s3Dtm3bsH79esTHx2P69OkYMmQIwsPDARQKo5wIyBjDpUuXYGdnh4iICADAhQsX4OTkBC8vL43iIQiCIAiCIAiCIMoHVOOrgpGTkwOgUCwyMzMr03VlZWVhy5Yt2LFjBzp37gygUHyqXr26ynlSU1Ph5OSETp06wcTEBDVq1EDz5s0BAPb29jAyMoK1tTWcnJz4eapVq4ZZs2bx7ydPnoxTp07hwIEDaNGiBT/d19cXCxcuBADUrl0bv/zyC8LCwtC5c2ecO3cO165dQ2JiIu+68vDw4OddsWIFBg0axNcWq127NtauXQt/f3+sX78e5ubmSrcnNzdXbpvXrVuH7t27Y+XKlfw2WFlZYfPmzTA1NQUAbNq0CTk5OdixYwdf++yXX35Bz5498eOPP8LR0ZFPaZTtB3UkJSVhz549ePz4MVxcXAAUCminTp3Ctm3bsHTpUoV5qlatCjMzM1hYWPDrOXv2LG7evInk5GS4uroCAHbu3Il69epBLBajWbNmAArdZTt37kTVqlVVxnT37l14e3sr/YybfvfuXY22TyqVIjQ0FNbW1gCAoUOHIiwsDN9//z2ys7Px888/4/z582jVqhWAwu82IiICGzduhL+/PwICArBlyxZIpVLExcXByMgIQ4YMwcWLFxEUFISLFy/C399fo1gIgiAIgiAIgiCI8gM5vioQjDFIJBIAQEFBQZmvLykpCR8+fODFBqBQvFLnmunXrx9ycnLg4eGBsWPH4vDhw8XGKpFI8P3338PX1xeVK1eGSCTCmTNnkJqaKtfO19dX7r2zszNevHgBAIiJiUH16tV50asoUVFRCA0NhUgk4l+BgYGQSqVITk5WGVuNGjXkhL5WrVpBKpXKpcw1aNCAF72AwsL1fn5+cgX/27RpozCfNkRHR4Mxhjp16shtQ3h4OF8vTBMSExPh6urKi14A4OPjA1tbWyQmJvLT3Nzc1IpemiLbL+pwd3fnRS9A/rtNSEhAbm4uOnfuLLftO3bs4Le9Xbt2ePfuHW7cuIHw8HD4+/ujffv2vCOMhC+CIAiCIAiC0D0fPnzA6dOnNSqBQhAlhRxfFQipVMrXWtKF8FWSEQZdXV1x584dnD17FufOncOECROwYsUKhIeHw8TEROk8K1euxKpVq7B69Wo0aNAAVlZWmDZtmkKh+KLzCwQCSKVSAICFhYXauKRSKb766iu+3pgsNWrU0Hj7uHpc3F8ACiNaMsbkPlc2v7ZIpVIYGRkhKiqKT9/kEIlEGi9HVWxFp2sySmft2rWRkJCg9DNORFMlRBZF3XfL/T1x4gSqVasm145zPdrY2KBhw4a4ePEirly5gg4dOuCzzz5DTEwM7t27h7t37yIgIECjWAiCIAiCIAiCKB22bduG8ePHIyQkRGmWCkGUBuT4qkBwbi9A9Uh7pYmnpydMTExw9epVftrr16+LTV+zsLDA559/jrVr1+LixYuIjIxEXFwcgEIHkOx2AMClS5cQHByMIUOGwM/PDx4eHirrVqnC19cXjx8/Vhlb48aNER8fD09PT4WXOldSamoqnj59yr+PjIyEUChUK+j4+PggJiZG7qnG5cuXi51PHY0aNYJEIsGLFy8U4tc0XZKLLTU1FY8ePeKnJSQk4O3btyrTFlUxcOBA3Lt3D8eOHVP4bOXKlXBxceFTZD8GHx8fmJmZITU1VWHbZZ1rAQEBuHDhAv755x8EBATA1tYWPj4++O677+Dg4KD19hEEQRAEQRAE8XHcunULAJCSkqLfQIgKDQlfFQhZwUgXji+RSITRo0fj66+/RlhYGG7duoURI0ZAKFS9W4WGhmLLli24desWHjx4gJ07d8LCwgJubm4AClPa/vnnHzx58gSvXr0CUCiwnT17FleuXEFiYiK++uorPHv2TKtY/f390a5dO/Tp0wdnz55FcnIy/v77b5w6dQoA8M033yAyMhITJ07kXUB//fUXJk+erHa55ubmGD58OGJjY3Hp0iVMmTIF/fv3Vys2DR48mJ/v1q1buHDhAiZPnoyhQ4fC0dFRq+3iqFOnDgYPHoxhw4bh0KFDSE5Ohlgsxo8//oiTJ09qvJxOnTrB19cXgwcPRnR0NK5du4Zhw4bB398fTZs21SqmL7/8Er169cLw4cOxZcsWpKSk4ObNm/jqq69w/Phx/PHHHypdftpgbW2NWbNmYfr06di+fTuSkpJw48YN/Prrr9i+fTvfLiAgAKdOnYJAIICPjw8/bdeuXZTmSBAEQRAEQRgkCQkJWLJkSYVNBXzy5AkA8CPcE0RZQMJXBULXwhdQWBS+Xbt2+Pzzz9GpUye0bdsWTZo0Udne1tYWmzZtQps2beDr64uwsDAcO3YMlStXBgD873//Q0pKCmrVqsXXkJo/fz4aN26MwMBABAQEwMnJCb169dI61oMHD6JZs2YYOHAgfHx8MHv2bL7PfH19ER4ejnv37uGzzz5Do0aNMH/+fDg7O6tdpqenJ7744gsEBQWhS5cuqF+/Pn777Te181haWuL06dPIyMhAs2bN0LdvX3Ts2BG//PKL1tsky7Zt2zBs2DDMnDkTXl5e+Pzzz/Hvv//KuZ6KQyAQ4MiRI7Czs0O7du3QqVMneHh4YN++fVrHIxAIcODAAXz77bdYtWoVvLy84Ofnhz///BM3btxA+/bttV6mKpYsWYIFCxZg2bJl8Pb2RmBgII4dO4aaNWvybdq1awegUATl0jb9/f0hkUhI+CIIgiAIgiAMkoULF2LBggUluh4vDzx+/BgA8O7dOz1HQlRkBKwkhZp0TGZmJmxsbPD27VtUqlRJ7rPc3FwkJyejZs2aKkfe+1R4+/YtnwIoEolQt25dPUdUsVm0aBGOHDmCmJgYfYdSboiOjkanTp0wevRorFixQt/hEAYEncsJgiAIgiAUadeuHS5duoQ5c+Zg2bJl+g6n1KlWrRqePn2Kpk2bQiwW6zscohyhTicqCjm+KhC6rvFFENrSuHFjhIWFwcrKSqvRJgmCIAiCIAjiU+Tt27cAKmYNrIKCAr6EDTm+iLKERnWsQMimN+oq1ZEgtKVRo0Zo1KgR/75evXp4+PCh0rYbN27E4MGDdRUaQRAEQRAEQRgUb968AQCV18vlmefPn/MjtJPwRZQlJHxVIGQdXxKJBFKpVG2heeLjWLRoERYtWqTvMMo9J0+eVOlQLGmxf4L4lHj8+DH279+PMWPGFGvzJgiCIAiifFGRHV9cYXuAitsTZQsJXxUIWeELKHR9mZqa6ikagtAMbkRPgiBKxg8//IBff/0VEokEX3/9tb7DIQiCIAiilJBKpcjMzAQApKWlITc3t0LVQi0qfDHG+EGoCKI0ITtQBUKZ8EUQBEFUbLjaGDdv3tRzJARBEARBlCbv3r2D7Fh0qampeoym9JEVvqRSKXJycvQYDVGRIeGrAkHCF0EQxKcH9yT49u3beo6EIAiCIIjShKvvxVHR6nzJCl8A1fkiyg4SvioQRYUvGtmRIAii4sMJX3fu3JF7KkwQBEEQRPmGq+/FUdHqfBUVvqjOF1FWkPBVgeCELy4vmhxfBEEQFR/u6ei7d++Qlpam52gIgiAIgigtijq+KrrwRY4voqwg4asCwQldZmZmcu8/ZbjhcQmCICoqnOMLoHRHgiAIgqhIFHV8VbRUx8ePH8u9J8cXUVaQ8GWgpKSkQCAQICYmRuN5OMdXeRW+QkNDYWtrq9U8Rfvp4sWLEAgEePPmDbKysnDjxg1yQGjAs2fP0LlzZ1hZWfHfgUAgwJEjRwCUbH8kCEI3kPBFEARBEBWTiuz4Yozxji+RSASAHF9E2UHClx4QCARqXyNGjCjRcjnhixvitixqfMkKS4ZI69atkZaWBhsbG35IXFVPDgx9W3TJqlWrkJaWhpiYGNy9exdA4ZDJ3bp103NkBEGogzEmd5FIwhdBEARBVBw4x5ebmxuAiiV8ZWZmIjs7GwDg5eUFgIQvouww1ncAnyKyDqR9+/ZhwYIFuHPnDj/NwsICr1+/1mqZUqmUT+srr46v0sDU1BROTk4A/tv+okX/PyXy8/NhYmJSbLukpCQ0adIEtWvX5qdx/UgQhOGSnZ0tV9CehC+CIAiCqDhwwpefnx8ePnyIp0+f4sOHDzA1NdVzZB8P5/aysbGBo6MjAEp1JMoOcnzpAScnJ/5lY2MDgUCgMI3jwYMHaN++PSwtLeHn54fIyEi5ZV25cgXt2rWDlZUVunfvjp9++okXepQJX0lJSQgODoajoyNEIhGaNWuGc+fOybXJy8vD7Nmz4erqCjMzM9SuXRtbtmxBSkoK2rdvDwCws7OTc6e5u7tj9erVcstp2LAhFi1axL//+eef0aBBA1hZWcHV1RUTJkzQ+uR27do1NGrUCObm5mjatClu3Lgh97msi6ugoABpaWkYP3487OzsYGVlhXr16uHkyZNqt+XUqVNo27YtbG1tUblyZfTo0QNJSUn8Ori0v0OHDqn9bi5fvgx/f39YWlrCzs4OgYGBvKDJGMPy5cvh4eEBCwsL+Pn54c8//1S77e7u7liyZAkGDRoEkUgEFxcXrFu3Tq6NQCDAhg0bEBwcDCsrK3z33XcAgPXr16NWrVowNTWFl5cXdu7cKbfcgwcPYseOHXL9IJvqqIyEhAQEBQVBJBLB0dERQ4cOxatXr9RuA0EQpYtsmiNAwhdBEARBVCS4zJTatWvDwsICjDE8evRIv0GVEpzwVa1aNVhbWwMgxxdRdlQ44YsxhuzsbL28ymIY+blz52LWrFmIiYlBnTp1MHDgQF7QiouLQ2BgIL744guIxWIsXboUMTExmD17NgDlwldWVhaCgoJw7tw53LhxA4GBgejZsydSU1P5NsOGDcPevXuxdu1aJCYmYsOGDRCJRHB1dcXBgwcBAHfu3EFaWhrWrFmj8bYIhUKsXbsWt27dwvbt23H+/Hk+Vk3Izs5Gjx494OXlhaioKCxatAizZs1S2V4ikWD58uXIy8vDP//8g7i4OPz444/Fbkt2djZmzJgBsViMsLAwCIVC9O7dW6FQvrrvJiYmBh07dkS9evUQGRmJiIgI9OzZkxcl582bh23btmH9+vWIj4/H9OnTMWTIEISHh6vtgxUrVsDX1xfR0dEICQnB9OnTcfbsWbk2CxcuRHBwMOLi4jBq1CgcPnwYU6dOxcyZM3Hr1i189dVXGDlyJC5cuAAAEIvF6Nq1K/r376/xd5qWlgZ/f380bNgQ169fx6lTp/D8+XP079+/2HkJgig9OOGLc3Y+evSInpYSBEEQRAWBc3zZ2tpWuHRHZcIXXcMQZQb7CJYuXcoAsKlTp6psc+HCBQZA4ZWYmKjxet6+fcsAsLdv3yp8lpOTwxISElhOTg5jjLGsrCyl69PFKysrS+s+3LZtG7OxsVGYnpyczACwzZs389Pi4+Pl+m7o0KFs3Lhx/HaLxWK2bds2JhQKWUREBBOLxUwqlRYbg4+PD1u3bh1jjLE7d+4wAOzs2bNK23Lf5+vXr+Wmu7m5sVWrVslN8/PzYwsXLlS53v3797PKlSvz71X1BcfGjRuZvb09y87O5qetX7+eAWA3btxQiO/27dvM09OTjR8/XqttKcqLFy8YABYXF8cY0+y7GThwIGvTpo3S5WVlZTFzc3N25coVuemjR49mAwcOVBmHm5sb69q1q9y0AQMGsG7duvHvAbBp06bJtWndujUbO3as3LR+/fqxoKAg/n1wcDAbPny4XBsA7PDhw3LbzPXz/PnzWZcuXeTaP3r0iAFgd+7cUbkNBKGKoudyQjP+/fdfBoDVqFGDVa1alQFgUVFR+g6LIAiCIIhSoF+/fgwAW7duHevatavCPUh55rvvvmMA2MiRI9m0adMYAPbNN9/oOyyiHKFOJypKiR1fYrEYv//+O3x9fTVqz7lquJdsLSFCNbL96+zsDAB48eIFACAqKgqhoaF8qlm7du0wYcIESKVSPH36FICi6ys7OxuzZ8+Gj48PbG1tIRKJcPv2bd7xFRMTAyMjI/j7+5f6tly4cAGdO3fmVf1hw4YhPT2dL2pYHImJifDz84OlpSU/rVWrVirbFxQUYMCAAdi0aRPatGmDhQsX4ubNm8WuJykpCYMGDYKHhwcqVaqEmjVrAoCcKw5Q/91wji9lJCQkIDc3F507d4ZIJOJfO3bskEupVEbR7W3VqhUSExPlpjVt2lTufWJiItq0aSM3rU2bNgrzaUNUVBQuXLggF3/dunUBoNhtIAii9OBSAipVqsQfg5TuSBAEQRAVA87xZWNjA3d3dwDAw4cP9RhR6UGOL0KXlKi4fVZWFgYPHoxNmzbxNYSKw8HBAba2tiVZnVZYWlrq7YCRFWRKC9nC5AKBAAD4lDupVIqvvvoKU6ZMwdu3b5GamgpLS0vUqlWLryVVUFAgt4yvv/4ap0+fxk8//QRPT09YWFigb9+++PDhA4DCwvolQSgUKqR6yo4q+fDhQwQFBWH8+PFYsmQJ7O3tERERgdGjR2s8+mTR5ReHRCJBr1690LJlS6SmpuLcuXNYtmwZVq5cicmTJ6ucr2fPnnB1dcWmTZvg4uICqVSK+vXr833Eoe67UdePXJsTJ06gWrVqcp9xAxNoA7duDisrq2LbMMYUpmmDVCpFz5498eOPPyp8xomABEGUPVyqo7W1NerWrYtLly7JDZZCEARBEET5havxVdFTHbnrGarxRZQVJRK+Jk6ciO7du6NTp04aC1+NGjVCbm4ufHx8MG/ePL6wuDLy8vKQl5fHvy9avFcdAoFA6Y1/RaRx48aIj4+Hp6cnXr16BcYYbGxs4OnpiVu3biE3N1fB8XXp0iWMGDECvXv3BlAoYsqePBs0aACpVIrw8HB06tRJYZ3cCCJFR0qsWrWq3GiVmZmZSE5O5t9fv34dBQUFWLlyJYTCQqPh/v37tdpeHx8f7Ny5Ezk5ObywdPXqVZXtuW13cnJCYGAgJkyYgJCQEGzatAmTJ09Wui3p6elITEzExo0b8dlnnwEAIiIitIoTKHSDhYWFYfHixUq3w8zMDKmpqVo764pu79WrV3mXhyq8vb0RERGBYcOG8dOuXLkCb29vrdYtS+PGjXHw4EG4u7vD2JgGhyUIfcH9PpLjiyAIgiAqHsocXxVR+OIMDuT4IsoKrVMd9+7di+joaCxbtkyj9s7Ozvj9999x8OBBHDp0CF5eXujYsSP++ecflfMsW7YMNjY2/MvV1VXbMD8JvvnmG0RGRmLixImIjY1FamoqLly4gMmTJ/NiRFE3laenJw4dOoSYmBjExsZi0KBBckXb3d3dMXz4cIwaNQpHjhxBcnIyLl68yItUbm5uEAgEOH78OF6+fMmfnDp06ICdO3fi0qVLuHXrFoYPHw4jIyN+ubVq1UJBQQHWrVuHBw8eYOfOndiwYYNW2zto0CAIhUKMHj0aCQkJOHnyJH766SelbaVSKaRSKVauXInIyEgkJSUhOjoa58+f5wUfZdtiZ2eHypUr4/fff8f9+/dx/vx5zJgxQ6s4ASAkJARisRgTJkzAzZs3cfv2baxfvx6vXr2CtbU1Zs2ahenTp2P79u1ISkrCjRs38Ouvv2L79u1ql3v58mUsX74cd+/exa+//ooDBw5g6tSpauf5+uuvERoaig0bNuDevXv4+eefcejQIbUDAxTHxIkTkZGRgYEDB+LatWt48OABzpw5g1GjRimIogRBlB2ywpeXlxcAEr4IgiAIoqLAOb4qovD1+PFjAIXCl0gkAkCOL6Ls0Er4evToEaZOnYo//vgD5ubmGs3j5eWFsWPHonHjxmjVqhV+++03dO/eXaVgARSKBm/fvuVfFWXI1tLG19cX4eHhuHfvHoKDgzFkyBCsWrUKzs7OvPBV1PG1atUq2NnZoXXr1ujZsycCAwPRuHFjuTbr169H3759MWHCBNStWxdjx47l63BVq1YNixcvxpw5c+Do6IhJkyYBKPzO2rVrhx49eiAoKAi9evVCrVq1+GU2bNgQP//8M3788UfUr18fu3bt0lg85RCJRDh27BgSEhLQqFEjzJ07V2mqnex2S6VSLF++HA0bNkTXrl3h5eWF3377TeW2CIVC7N27F1FRUahfvz6mT5+OFStWaBUnANSpUwdnzpxBbGwsmjdvjlatWuHo0aP897JkyRIsWLAAy5Ytg7e3NwIDA3Hs2DG+npgqZs6ciaioKDRq1AhLlizBypUrERgYqHaeXr16Yc2aNVixYgXq1auHjRs3Ytu2bQgICNB6uzhcXFxw+fJlSCQSBAYGon79+pg6dSpsbGx4Rx9BEGWPshpfd+/eJQGaIAiCICoAsqM6csLXkydPNC4VY6jk5+fztZFla3yR8EWUFQKmReGkI0eOoHfv3nJOHolEAoFAAKFQiLy8PLnPVPH999/jjz/+0Li4dmZmJmxsbPD27VtUqlRJ7rPc3FwkJyejZs2aGotxFZHU1FS8ePECTk5OqF69Oh4+fIiXL1/CxcUFLi4uOo2FMYanT5/CzMwMVapU0em6Od6/f4+EhAT+fZ06dRT2nfKGu7s7pk2bhmnTpuk7FILQiNzcXDx79gzOzs7F1q+jc3nJmDNnDn788UdMmzYNP/30EywtLfHhwwc8ePCgWCGdIAiCIAjDJS8vj78mev36NSpVqgRLS0vk5eWV+9/51NRUuLm5wcTEBLm5uTh//jw6d+6M+vXrIy4uTt/hEeUEdTpRUbSyZnTs2BFxcXGIiYnhX02bNsXgwYP50QA14caNG1QAu5Thnu5z34Eqx5cuyMvLQ1paml6dekXdDuR+IAjd8+LFC7x69QrPnz/XdygVFtlURyMjI9SpUwcApTsSBFF6SKVS3Lx5k66lCELHcG4vgUCASpUqQSgUVpgC91x9L2dnZwiFQnJ8EWWOVsKXtbU16tevL/eysrJC5cqVUb9+fQCFKW+yRbRXr16NI0eO4N69e4iPj0dISAgOHjzIp8gRpYMq4UsfNlhObJNIJHL1w/QRAwddrBGE7uGOQy5Vmih9ZIUvAFTgniCIUmfdunXw8/PDunXr9B0KQXxScPW9rK2t+VIiFaXOl2xhewC88EXF7YmyotSHY0tLS0Nqair//sOHD5g1axaePHkCCwsL1KtXDydOnEBQUFBpr/qThhN2OMFLn44vWZFJIpHopeZT0e3WlwBXmnzsD1xGRgYKCgrg4OBQOgERRDFwx+H79+8hlUqp/lsZIFvjCyDhiyCI0ufu3bsAgJMnT1K5BYLQIbL1vTg4x9fDhw/1EVKpUVT4ouL2RFnz0cLXxYsX5d6HhobKvZ89ezZmz579sashiqGo48vExASAfoQv2XUWFBTwsegSSnWUh6v5AxT+eJqamuo5IuJTgDsXMMaQk5MDKysrPUdU8eAcX9yTUhK+CIIobTgHxtWrVyGRSDQubUIQxMfBCV82Njb8tIru+Prw4QM+fPhA9ypEqUOP3ysIhpjqKBuXPmPQZxyGQnp6Ov+/PsRQ4tNEdl97//69HiOpuFCqI0EQZQ0nfL179w7x8fF6joYgPh24VEdZx1dFE76qV68O4D/HF0DpjkTZQMJXBYG7wVRW3F6LgTtLBVmRSV8iC7degUCgENOnBmMMr1694t9/yn1B6BbZ45/qfJUNRYUvLy8vAIUDC7x+/VpvcRXHv//+ixEjRuDp06f6DoUgiGKQvQmNjIzUYyQE8WmhzvFV0VIdTUxM+BHASfgiygISvioAjDGVji9A90KHITm+OJvspyz2ZGVlIS8vj3//KfcFoTuKDm5Bjq+yoWiNL5FIxD89vXPnjt7iKo5vv/0W27dvx/79+/UdCkEQxSB7E3rlyhU9RkIQnxbKHF9cja9Hjx6V6yyOosIXQHW+iLKFhK8KgOzNJSd8CYVC/n9dpzsaguOLi4GEL8i5vYBPuy8I3VF0P+MK3BOlS9EaX8B/ri9DTXfMzMzEpUuXAPx3UU8QhOFCwhdB6Adlji9nZ2eYmJhAIpHw4lF5gzGmVPjirmVI+CLKAhK+KgDcDaZAIJAbNU1fIzsakuOLs8x+qmJPQUEBn+5EIiChS7hj0MTEhB/gglxfpUt+fj5ycnIA/Of4Agy/zldYWBj/QIYT7giCMFxkha/79+/jxYsXeoyGID4duIdDssKXUCjkXV/ltc7X69ev+esXFxcXfjrn+KJUR6IsIOHLQElJSYFAIEBMTEyxbWXTHLmaVoD+hC9DcHwVFb5K22ly8eJFCASCj3Yr/P7773B1dYVQKMTq1as1mqfovqEultevX0MqlcLc3Jy/MSbhq5Bnz56hc+fOsLKy4i3kAoEAR44cAaDdMVgcQ4cOxdKlSz96OdowYsQI9OrVS6frlIU7Bh88eIDAwEDk5ORQna9SRvaJqKzjy9CFr5MnT/L/k/BFEIYPdxPKXVNRnS+C0A2c40s21RH4L92xvNb54txe9vb2sLCw4KeT44soS0j44pBKgOcXgZQ9hX+lZScOCAQCta8RI0Zotbyi9b04OJeFrPgUGhqqcPIsbWTXV1LhKyAggO8PoVAIR0dH9OvXT+MTfHlIdczMzMSkSZPwzTff4MmTJxg3blyJltO6dWukpaXJPQ3i4NIcq1SpAiMjI0RFRcHFxYXSiwCsWrUKaWlpiImJwd27dwEAaWlp6NatW6mu5+bNmzhx4gQmT54sNz0+Ph79+/dH1apVYWZmhtq1a2P+/Plau6JUCXRr1qxBaGjoR0ZfPJ9//jlq1KgBc3NzODs7Y+jQoXj69Cl/7Pv4+KBx48bYvXs3Ob5KGe7C0NzcXG7Yb0MWvhhjcsIXXdwShOHDCV+fffYZAEp3JAhdoczxBZT/kR2VpTkC/wlf5PgiygISvgDg0SHgL3cgrD1wZVDh37/cC6eXAWlpafxr9erVqFSpkty0NWvWaLW8oiM6cnCOL33W+NJWcPrw4QP//9ixY5GWloYnT57g6NGjePToEYYMGVLsMqRSKe/wMuRUx9TUVOTn56N79+5wdnaGpaVliZZjamoKJycnObcfUJhWlp2dDYFAgMqVKyvsHxUVTff3pKQkNGnSBLVr14aDgwMAwMnJid9nSotffvkF/fr1k3PkXL16FS1atMCHDx9w4sQJ3L17F0uXLsX27dvRuXNnueOgpNjY2JS5yA0A7du3x/79+3Hnzh0cPHgQSUlJ6Nu3L39eMjY2xrBhw3Dw4EFy95QyRUd05OCEr6SkJJ2f/4sjNjZWbiRH2icIwrCRSCT8Q4vOnTsDIMcXQegKVY6viip8UXF7oiwh4evRIeBSX+D9Y/np758UTi8D8cvJyYl/2djYQCAQKEzjePDgAdq3bw9LS0v4+fkpXGxcuXIF3bp1Q9u2bdGxY0dMmTKFTycqSapjamoqgoODIRKJUKlSJfTv3x/Pnz8HUHjy5VxDQOGTe3t7ezRr1oyff8+ePejYsSP//unTpxgwYADs7OxQuXJlBAcHy52kuXSsZcuWwcXFBXXq1OE/s7S0hJOTE5ydndGyZUtMnDgR0dHRcvGGh4ejefPmMDMzg7OzM+bMmYPc3Fz+83r16mH37t2QSCRgjAEAGjZsiEWLFvFtBAIBNm/ejN69e8PS0hK1a9fGX3/9JbeekydPok6dOrCwsED79u01+qFR15ehoaFo0KABAMDDwwMCgUDlMq9du4ZGjRrB3NwcTZs2xY0bN+Q+L5rq+PDhQ/Ts2RPOzs747LPP8OWXX+Ls2bN48uQJxo8fDwCws7OTcxeeOnUKbdu2ha2tLSpXrowePXogKSmJXwfnKjp06JDa/fHy5cvw9/eHpaUl7OzsEBgYyNcYY4xh+fLl8PDwgIWFBfz8/PDnn3+q7UN3d3csWbIEgwYNgkgkgouLC9atWyfXRiAQYMOGDQgODoaVlRW+++47AMD69etRq1YtmJqawsvLCzt37pRb7sGDB7Fjxw65fpBNdVRGQkICgoKCIBKJ4OjoiKFDhyoMHiCLVCrFgQMH8Pnnn/PTGGMYPXo0vL29cejQITRv3hxubm7o168fjh07hsjISKxatUpu+9avX49u3brBwsICNWvWxIEDB/jPa9asCQBo1KgRBAIBAgICACimOubl5WHKlClwcHCAubk52rZtC7FYzH/O7UdhYWFo2rQpLC0t0bp162JHBpw+fTpatmwJNzc3tG7dGnPmzMHVq1f52g3Gxsbo2bMn3r59iytXrhikCF1eUVbYHii8kLSyskJBQYHccWwIcG4vc3NzAHRxSxCGjqxTt0uXLgAAsVhcKg9oCIJQT3GOr/Ke6kiOL0KXVDzhizGgIFuz14dM4PoUAEzZggr/XJ9a2E6T5TFly/k45s6di1mzZiEmJgZ16tTBwIEDeSErLi4OgYGBCAoKwu7du7FmzRpERERg0qRJALQXvhhj6NWrFzIyMhAeHo6zZ88iKSkJAwYMAFB40m3YsCEuXrwIoDCFi/vL3YBduHABjRs3BgDk5uZi+PDhEIlE+OeffxAREQGRSISuXbvKXTCFhYUhMTERZ8+exfHjx5XGlpGRgQMHDqBFixb8tCdPniAoKAjNmjVDbGws1q9fjy1btuD777/nt59zQTHGeOFLGYsXL0b//v1x8+ZNBAUFYfDgwcjIyABQOFzwF198gaCgIMTExGDMmDGYM2fOR/XlgAEDcO7cOQCFwlZaWhpcXV0VlpOdnY0ePXrAy8sLUVFRWLRoEWbNmqV23RMnTkRubi42b96MPXv2YMmSJRCJRKhRowZ+/PFHAMCdO3fk3IXZ2dmYMWMGxGIxwsLCIBQK0bt3b4XaaOr2x5iYGHTs2BH16tVDZGQkIiIi0LNnT17omDdvHrZt24b169cjPj4e06dPx5AhQxAeHq52e1asWAFfX19ER0cjJCQE06dPx9mzZ+XaLFy4EMHBwYiLi8OoUaNw+PBhTJ06FTNnzsStW7fw1VdfYeTIkbhw4QKAwov2rl27on///hq7LNPS0uDv74+GDRvi+vXrOHXqFJ4/f47+/furnOfmzZt48+YNmjZtyk+LiYlBQkICZsyYITcYBQD4+fmhU6dO2LNnj9z0+fPno0+fPoiNjcWQIUMwcOBAJCYmAijcfwDg3LlzSEtLw6FDysX62bNn4+DBg9i+fTuio6Ph6emJwMBAfj/nmDt3LlauXInr16/D2NgYo0aNKrZvODIyMrBr1y60bt2aP/aMjY1hZWWFOnXqICYmhtIdSxFVji+BQGCw6Y6c8NW9e3cA5PgiCEOHe5gqFArh6+sLe3t75Obmlkr9S4Ig1FNcjS9yfBGEFrBywNu3bxkA9vbtW4XPcnJyWEJCAsvJySmckJ/F2C7o55WfpfW2bdu2jdnY2ChMT05OZgDY5s2b+Wnx8fEMAEtMTGSMMTZ06FA2btw49vTpUyYWi1lycjK7dOkSEwqFLCcnh7169YqJxWJ2586dYtfHGGNnzpxhRkZGLDU1VWGd165dY4wxNmPGDNajRw/GGGOrV69mffv2ZY0bN2YnTpxgjDFWu3ZtNmfOHCYWi9n8+fOZu7s7k0ql/PLy8vKYhYUFO336NGOMseHDhzNHR0eWl5cnF4u/vz8zMTFhVlZWzNLSkgFgderUYcnJyXybb7/9lnl5eckt/9dff2UikYj9+++/LC4ujrm5ubHp06czsVjMPnz4wBhjzM/Pjy1cuJCfBwCbN28e/z4rK4sJBAL2999/M8YYCwkJYd7e3nLr+eabbxgA9vr16xL35Y0bNxgAuW0qysaNG5m9vT3Lzs7mp61fv54BYDdu3GCMMXbhwgW5WBo0aMC++eYbJhaLWUxMDB93eno627Bhg9q4OV68eMEAsLi4OMaYZvvjwIEDWZs2bZQuLysri5mbm7MrV67ITR89ejQbOHCgyjjc3NxY165d5aYNGDCAdevWjX8PgE2bNk2uTevWrdnYsWPlpvXr148FBQXx74ODg9nw4cPl2gBghw8flttmrp/nz5/PunTpItf+0aNHDIDcMSbL4cOHmZGRkdy+s3fvXrnlFmXKlCnMwsJCLqbx48fLtWnRogX7v//7P6VxcgwfPpwFBwczxgr738TEhO3atYv//MOHD8zFxYUtX76cMfbffnTu3Dm+zYkTJxiA/86vKpg9ezZ/nLZs2ZK9evWKJSUlMbFYzJ49e8YYY6xz586sR48eLC0tTekyFM7lRLHs27ePAWD+/v4Knw0ePJgBYMuWLdN9YCpIT09nQqGQAWD79+9nAJibm5u+wyIIQg337t1jAFilSpUYY4z16NGDAWCrVq3Sb2AE8QlgZ2cnd63NkZqaygAwY2NjVlBQoKfoSk737t0ZALZx40a56XPmzFF6XU8QqlCnExWl4jm+Khi+vr78/87OzgDADyMdFRWF0NBQeHp6ol27dqhXrx4CAwMhlUqRnJysdY2vxMREuLq6yjmPfHx8YGtry7tLAgICcOnSJUilUoSHhyMgIAABAQEIDw/Hs2fPcO/ePd7xlZiYiEePHsHa2hoikQgikYh/UiibftOgQQO5wswcgwcPRkxMDGJjYxEREQFPT0906dKFfwqQmJiIVq1aydW2atOmDbKysvDixQt++zlXjboUK9l+trKygrW1Nd/PiYmJaNmypdx6WrVq9dF9qQmJiYnw8/OTq/9V3LqnTJmClStXYvTo0QgNDUVcXByA/xyAykhKSsKgQYPg4eGBSpUq8elzqampcu3U7Y+c40sZCQkJyM3NRefOnfl9QSQSYceOHcWmYhXd3latWin0oayjCijstzZt2shNa9OmjVZ9X5SoqChcuHBBLn7ZWkrKyMnJgZmZmUL9NXUwxhTaa9IH6uBqPcn2iYmJCZo3b66wHHXfsSq+/vpr3LhxA2fOnIGRkRGGDRvGn3e4/U4kEiE3N5dGdixFVDm+gP/qfBWXqqpLzpw5A6lUivr166N+/foA6KluSWCMGVztNqJsyMrKQr9+/bBjxw69xgD858Ro3bo1ACpwTxBlDWNMpePLxcUFxsbGKCgokKubWV7gHF/Vq1eXm06OL6IsUX0nXF4xsgT6a5gX/OIf4GJQ8e0CTgIO7TRbdynDjcwIgL8Z5tLPpFIpvvrqK/Tp0wcZGRlwcHCAo6MjAKBGjRr8hbE2qY7KbtBlp7dr1w7v3r1DdHQ0Ll26hCVLlsDV1RVLly5Fw4YNUbVqVdSsWRMmJiZgjKFu3bo4ePCgQmH1qlWr8v9bWVkpjcfGxgaenp4AAE9PT2zZsgXOzs7Yt28fxowZozReJpPOaGRkJJdKxglfym4YZPsZKOxrrp9ZCVJYNelLTZejLUOHDoWTkxMuX76MxMRENG3aFCtXrsTIkSNVztOzZ0+4urpi06ZNcHFx4W9Oi9bwULc/yg5HXBSuzYkTJxRszSUpJl+0D5XtQ8r2DW36vihSqRQ9e/bk00Vl4QSiolSpUgXv37/Hhw8feHGXq2OXkJCAhg0bKsxz+/Zt1K5du9h4SrIfadIn6r5jVVSpUgVVqlRBnTp14O3tDVdXVwwePBh16tThha93797Bzs6OUh1LEVU1vgDDHNmRS3MMCgriY87MzPzoY/NTo3v37oiPj8fly5cVbhqIisWBAwfw559/Ijo6GsOGDdNLDCR8KRIVFQULCwv4+PjoOxSiApOVlcVffxWt8WVkZARXV1ckJyfj4cOHSsulGDLF1fgi4YsoCyqe40sgAIytNHs5dQEsqwNQdcEtACxdC9tpsjwdX7g3btwY8fHxqF69OlxdXeHp6cm/TE1N5Wp8aSKg+Pj4IDU1FY8ePeKnJSQk4O3bt/D29gbwX52vX375BQKBAD4+Pvjss89w48YNHD9+nHeUmJqaom7dunj06BEqV64sF5unp6fCCVwTOPGMK5rt4+ODK1euyG3blStXIBKJ4ODgAGNjY1StWpWvYSSRSJCZmYnk5GSt1uvj44OrV6/KTSv6Xtk8xfWlpuuOjY3lt1mTdaenp8PJyQkjRozAkSNHMHPmTGzatAlGRkb8PiHrfktPT0diYiLmzZuHjh07wtvbmy9Irw2+vr4ICwtTuR1mZmZITU1V2BeK+7FW1vfcTb0qvL29ERERITftypUrWvV9Ubjjzd3dXWEbVIm3nLCVkJAgN61u3bpYtWqVgqAUGxuLc+fOYeDAgXLT1fUBJ6ipczRy5wTZPsnPz8f169c/qk+UwR2PssXtgUIBxsvLC3l5eVoNuEGoRp3jy8vLC0Bhv5dEQC9tpFIp/v77bwCFwhcXc0FBAfLy8vQZWrkjLCwMqampmDhxokF8t0TZwdVUTUlJ0Vsx+aLCV9OmTWFkZIQnT57IXeN8KmRkZKBt27bw9/cv9qEQQXwMXGF7U1NTfkAYWcrryI55eXl4+fIlANU1vqi4PVEWVDzhSxuERkATrqh1UdHq/79vsrqwnQHyzTffIDIyEgsWLMCdO3eQkpKCv/76C5MnTwbwn3ODMSZ3UyyRSBATEyP3SkhIQKdOneDr64vBgwcjOjoa165dw7Bhw+Dv7y+XShYQEIA//vgD/v7+EAgEsLOzg4+PD/bt28enZBkZGaF79+6wtbVFnz59cOnSJSQnJyM8PBxTp07F48dFRtFUwvv37/Hs2TM8e/YMsbGxmDBhAszNzflRhSZMmIBHjx5h8uTJuH37No4ePYqFCxdi7NixEAqFMDY2RocOHXDs2DHcuHEDt27dwvDhwxXcZ8Uxfvx4JCUlYcaMGbhz5w52796N0NBQtfNo2pfFMWjQIAiFQowePRoJCQk4efIkfvrpJ5XtGWOYPXs2IiMjkZ2djejoaJw/fx7e3t4wMjKCs7MzBAIBjh07hpcvXyIrK4sfcfP333/H/fv3cf78ecyYMUPjGDlCQkIgFosxYcIE3Lx5E7dv38b69evx6tUrWFtbY9asWZg+fTq2b9+OpKQk3LhxA7/++iu2b9+udrmXL1/G8uXLcffuXfz66684cOAApk6dqnaer7/+GqGhodiwYQPu3buHn3/+GYcOHSp2YAB1TJw4ERkZGRg4cCCuXbuGBw8e4MyZMxg1apRK0alq1apo3LixnODEjSKakJCAPn364Nq1a0hNTcWBAwfQs2dPtGrVCtOmTZNbzoEDB7B161bcvXsXCxcuxLVr1/hBLBwcHGBhYcEX2+ds8bJYWVnh//7v//D111/j1KlTSEhIwNixY/H+/XuMHj26xH1y7do1/PLLL4iJicHDhw9x4cIFDBo0CLVq1UK9evUAFApfKSkpePLkCdq2bQsAlO5YSnBPRJUJX7Vr1+ZHey0uVVUXXL9+Ha9evUKlSpXQunVr/uIWoAL32lBQUMALIH/99RcOHjyo54iIsoIxxgtfUqkUDx480EscRYUvKysr/qHOp+j6io2NRW5uLl69eoX09HR9h0NUYLjrORsbG6Wu6PIqfHGpmWZmZqhcubLcZ+T4IsqST1v4AgDXL4DP/gQs5RVnWFYvnO76hX7i0gBfX1+Eh4cjJSUF48aNQ8eOHTF//nw+7UooFPKpfrIOi6ysLDRq1EjuFRQUBIFAgCNHjsDOzg7t2rVDp06d4OHhgX379smtt3379pBIJAgICOCn+fv7QyKR8KMuGhsbw9raGhs3bkS1atXwxRdfwNvbG6NGjUJOTo7SG7WibNq0Cc7OznB2dkb79u3x8uVLnDx5kncyVKtWDSdPnsS1a9fg5+eH8ePHY/To0ZgwYQKAQvEtJCQEzZo1w/Tp09G/f3/06tULtWrV0qqfa9SogYMHD+LYsWPw8/PDhg0bsHTpUrXzyPblZ599hg4dOsDNzU2hL4tDJBLh2LFjSEhIQKNGjTB37lylqXYc7969Q35+PpYvX47WrVuja9eu8PLywm+//QYjIyM4ODhg3LhxCAkJgaOjIyZNmgShUIi9e/ciKioK9evXx/Tp07FixQqt4gQKU/jOnDmD2NhYNG/eHK1atcLRo0d5x8+SJUuwYMECLFu2DN7e3ggMDMSxY8f4emKqmDlzJqKiotCoUSMsWbIEK1euRGBgoNp5evXqhTVr1mDFihWoV68eNm7ciG3btsnts9ri4uKCy5cvQyKRIDAwEPXr18fUqVNhY2OjMDqjLOPGjcOuXbvkprVp0wZXr16FkZERgoKC4OnpiZCQEAwfPhxnz55VSP9cvHgx9u7dC19fX2zfvh27du3iUyyMjY2xdu1abNy4ES4uLggODlYaxw8//IA+ffpg6NChaNy4Me7fv4/Tp0/Dzs6uxH1iYWGBQ4cOoWPHjvDy8sKoUaNQv359nD9/nv/ejYyMsGfPHnTp0oVP4aR0x9JBnePL3NycP7YMId2RS3Ps0qULTExMIBQKqZZHCZB1/wLApEmTSuTQJQyflJQUuTqbd+/e1UscRYUv4NNOd7x16xb/f3msrUSUHzjHl6osmfIqfHFpji4uLgqCHid8keOLKBNKsah+maHVqI4lRVLA2LMLjCXvLvwrKT8jZMTFxTGxWMwyMzMVPouNjWVisZi9e/dOJ7E8fvyYicVi9vDhQ5aQkMDEYjHLyMjQybo57t27x8RiMXv+/DljjLH79+/Lvdc1iYmJcqPblSXctqakpCh8JpVKmVgsZmKxWGEUTV2Snp7O3r9/r1FbNze3cj9yVE5ODqtRo4bCiJaagv8/0uSzZ8+YWCxWOSqiIZGXl8fEYjG7fv06y8nJYa6uriwiIoLfhnv37inMQ6M6ak///v0ZALZmzRqlnwcFBTEAbMOGDTqOTJFmzZoxAGzr1q38NGdnZwaARUdH6zGy8sWzZ88YAAaAeXt7MwBs1KhR+g6LKAO2bt3Kf9cA2IoVK/QSx7p16xgA1r9/f37anj17GADWtGlTvcSkT8aNG8d/JydPntR3OEQF5vjx42qPs9DQUAaAderUSceRfRzc6OZt27ZV+OzSpUsMAPP09NRDZER5hEZ1LAlCI8AxAHAfWPjXQNMblcGlWSlL4ePSHXVVU0c2FmX1pHQZg6zjRB9xcHD1a8p6/QUFBfzToSpVqih8LhAI9N4X2dnZePDggdZ11soz5ubm2LFjB169evVRy+FcUuXBLcWdb4yNjZGamoq5c+eiTZs2/OiklOpYOqhzfAGGU+D++fPnEIvFAICuXbvy07m4KdVRc7jj39LSEps3b4ZAIMDWrVtV1lckyi9cmiM3cIwhOr5u3LjxyZ3PZR1fnHOF0D979+7Ft99+W6HqHlZ0x1fR+l4AOb6IsoWErwoAd5OpTPjixB9dDX0uGwsXj64LWcvedHOxAPoReyQSCd/3Zb3+9PR0MMZgaWmpsti6voUv7odMV/ujoeDv74+ePXt+1DK4PisPfSd7DNapUwdfffUVAPDCV35+vt4KNVck1NX4AgxH+Dp9+jSAwgEiZEdA5eKmVEfNkRW+Wrduzaf2f/XVV+VCFCc0hxO++vfvD8CwhC9XV1dUq1YNEokE169f10tc+oAxRqmOBsrUqVOxbNky3LhxQ9+hlBpcjS9bW1uln3PCV2pqarkaaEGd8EUlEIiyhISvco5UKuWfbqgTvnQlPsne8OrL8VVUCOTqL+lD7JEdraws188Y4x1FytxeHPoWvrgnw5r+QKekpCgUev/UYIyhV69evFBUHgSjouIzh5GREe9eMNSb9MePH2PevHnlomhxeXF8cfW9unfvLjede7JLji/NkRW+AGDp0qWoXr06kpKSsHjxYn2GRpQiXH0vY2NjjBgxAoBhCV8CgYAfzCgyMlIvcemDR48eyZ2vSPgyDAoKCvhRAvU1CERZUJzjq1q1ajAyMsKHDx/w7NkzHUb2cWji+MrOzi5XYh5RPiDhq5wjK2AYUqqjsbExOb4gL3yVZT+8f/8eOTk5EAgEsLe3V9lO38IXd9MmkUgqlB1dF8gKX4bed6qELwAGn+44evRofP/991i7dq2+QykW7gaMu1AsCid8PXz4UKEouq4oKCjgHV9BQUFyn5HjS3uKCl+VKlXC+vXrAQArV65EdHS03mIjSg/O7dW8eXN+BMW0tDS9HCvKhC/g0yxwL+v2Akj4MhQyMjL466KHDx/qOZrSozjHl7GxMapXrw6gfKU7auL4Agz3OpEov5DwVc6RramlbKhbXac66rvGl6wDztCEr7JcP+f2srOzUyo2cOg77TM3N5d/b+jijSEhkUj4J1+MMb0Jl5qiTvji0nAN0fEVFxeHM2fO8P8bOsU5vqpUqQJ7e3swxnDv3j1dhsYTGRmJN2/eoHLlymjWrJncZ+T40p6iwhcA9OjRA19++SUkEgnGjBmj84dNROnDCV8BAQGwtbWFg4MDAOjlONZE+PpUfs854Ytz4JQn4WvLli04evSovsMoE2RrqFZE4UuV4wson3W+1AlfFhYWfKYOPRQjShsSvso56grbA/pNddSH40t2XdyJk4tDH5ZZXQhfUqkUGRkZANSnOQL6Fb6KCh1kYdacoumNhp7uqInwlZ2dbXA3Sz///DP/f2Jioh4jKR7GWLE1vgQCAby8vADoL92RS3Ps2rWrwu8UFbfXHmXCFwCsWbMG9vb2uHHjhtx+TJRPOOHL398fAFCnTh0A+kl3VCV8NWrUCGZmZkhPT9ebsK5ruAciHTt2BFB+hK8nT55gzJgx6Nu370cPtGOIcGmOQMUSvrhUR1WOL6D8CV+MMf644dxqsggEAv5cQwXuidKGhK9yjiEJX4wxufpa+nB8yd5wcw44fYo9sg6nslr/69evIZFIYGZmpjLliUOfImBR4cvQXUuGRFHHpqEXuFcnfFlYWEAgEKCgoMCgBLy0tDTs2rWLf3///n2D7ufc3Fy+n1UJX4D+63xxwlfRNEeg/KU6/vbbb3B0dERsbKzeYlAlfDk4OPCC18KFC3H//n2dx0aUDikpKXj48CGMjY15V5UhCl+mpqa8i/NTSXfkHF9dunQBUDhibXlwWKalpQEo/G0+cOCAnqMpfWSFr/IiAGmCJo4vNzc3AOVH8EtPT+dNAS4uLkrbcPcy5eXagCg/kPBVzlE3oiOg2xpfsmKKvkZ1lK0xJhuL7Ge6RBeOL+7pXeXKlZWmu8qiz74omqtPji/NqUiOL6FQyBe4N6T6Db/88gvy8/PRqlUriEQiFBQUGLR4IOuSUjWKK6Bf4evx48e4efMmBAIBAgMDFT4vT6mOjDH89NNPePHiBfbs2aO3OFQJXwAwbNgwdOrUCbm5uRg3bpzBOSoJzeDcXs2aNePFJkMUvoBPq85XQUEB7wRu3749jIyMIJVK8eLFCz1HVjyyg7Xs3r1bj5GUDRU11bEiOr4eP34MAKhatSpMTU2VtuGuDcjxRZQ2JHyVczR1fOXn55f5RTB3sysQCCAUCvXu+OLQl9gjlUrlBIqCgoJS/w5yc3P5JyLFpTkClOpYXikqdBmyEwlQL3wBhlfnKzs7my8QPmvWLL27pDRBtrA9l9atDH1uy99//w0AaNmyJSpXrqzweXlyfCUkJCA5ORkAcP36db3FoU74EggE2LhxIywtLXHhwgVs27ZN1+ERpYBsfS8OQxW+PqWRHZOSkpCXlwcLCwt4enrCyckJQPlId+TKYQBAREREhRKHAHnH19u3b3nBqLxTEWt8qavvxcGda8rDtQFRviDhy0BJSUmBQCBATEyM2naaCl+MsTIXGmTdVgKBQM7xpasnz8occNxNYWmKPRcvXoRAIFD748q5vWRdWEW/g99//x2urq4QCoVYvXq1RuuW3TfS09MRFRWFZs2aaSQi6Ev4ki1sz+2T+ha+nj17hs6dO8PKyop/miYQCHDkyBEAmh+DmjB06FAsXbq0xPNzQhe3L2ni+BoxYgR69epV4nV+DLLCV1xcHKpXry7n7jK0kR1DQ0Px+vVr1KpVC8HBwbxYZMh1voqr78XBbcudO3d0fsypS3MEypfj6/jx4/z/169f19v5S53wBQAeHh5YsmQJAGDmzJl8ihNRflAnfN27d0/nTj5NhK/4+PgKIzaogktzrFevHoRCIX/jXt6ELwB6da2WBUXrllUUYY87pjRJdUxNTS0XLl9NhC99Or6uXr2KkJAQvY2ETZQtJHzpAYFAoPY1YsQIjZelLLVPFqFQyN8sFxQUIDQ0VK1l9mMoKjrJxqSt0BIQEMD3h1AohKOjI/r161fsj5k6x5cuxD9ZOOGLq2kEyPdDZmYmJk2ahG+++QZPnjzBuHHjtFo+YwyvXr2Cr68vEhIS1P4wckRGRqJZs2Z4/fq1Vuv6WLibNRMTE97arO8aX6tWrUJaWhpiYmL4p+hpaWno1q1bqa7n5s2bOHHiBCZPniw3PT4+Hv3790fVqlVhZmaG2rVrY/78+UoFTE7o4m52ZYUvVQLdmjVrEBoaWqrboozvv/8erVu3hqWlJX9ukT0OGzRogObNm2PVqlX8PLKOL31fqEkkEj62adOmwcjICN7e3gAMW/gqbkRHjpo1a8LExATv37/nUwx0QV5eHs6dOwdAtfBVnhxfx44d4/9/+/YtkpKS9BIHJxarEr4AYMqUKWjatCnevHmDKVOm6Co0ohRQVt8LAGrVqsU/bNN1cXJ1wpejoyNq1aoFxhj+/fdfncala7jC9g0aNADwX32i8iB8camO3Dm3oqU7yjq+gIojfHGOL3X3bdWrV4dQKERubi6eP3+uo8hKjqE7vubMmYMffviBf3BHVCxI+NIDaWlp/Gv16tWoVKmS3LQ1a9ZovKziHF8CgUBndb6KinCyopumIofsDf3YsWORlpaGJ0+e4OjRo3j06BGGDBmiVQyAfN/oUmzhHE5mZmZKnVapqanIz89H9+7d4ezsrPZGRtXy8/PzYW5uDi8vr2LrewH6c3xxYo6VlVWZF9jXNA0wKSkJTZo0Qe3atfmh4p2cnGBmZlaq8fzyyy/o16+f3MADV69eRYsWLfDhwwecOHECd+/exdKlS7F9+3Z07txZZU0vTjDSZBttbGzKTOSW5cOHD+jXrx/+7//+D0DhvsV9t9x3PXLkSKxfv57f78zNzSEQCCCRSOTq4OmDv/76C0lJSbCzs8PIkSMBoFwJX8UNaGFiYgJPT08Auk13jIiIQFZWFpycnNCwYUOlbcqL4+vVq1d8Khf3dF1f6Y7FOb6Awt+/zZs3w8jICH/++SfvYiUMn/DwcADy9b2AwnNmjRo1AOg23ZExplb4Aj6dOl+c46t+/foAypfwxTm+Bg4cCFNTU8TFxfFCXkWAE7646+CKIHzl5+fz53t1D7ZNTU15Eak8pDtq4/jSh/DFlTTQt4h49uxZvlwEUXqQ8KUHnJyc+JeNjQ0EAoHCNI4HDx6gffv2sLS0hJ+fn0IdhWvXrmHcuHHw9PSEq6srpkyZopA+JFvnqzhSU1MRHBwMkUiESpUqoX///vzB//btWxgZGSEqKgpA4QWRvb09P6pPQUEBTp8+jXbt2vHLS09PR0hICJycnFC5cmUEBwfLnZi5dKxly5bBxcWFt/MDhRf2Tk5OcHZ2RsuWLTFx4kRER0fLxRseHo7mzZvDzMwMzs7O+P7771FQUMDfcLu7u2PNmjVy6Y4NGzbEokWL+GUIBAJs3rwZvXv3hqWlJWrXro2//vpLbj0nT55EnTp1YGFhgfbt22v04/LgwQPMnDkTvr6+aNu2LUJCQvgLpNDQUP6poYeHBwQCgcplXrt2DY0aNYK5uTmaNm2KGzdu8P0NADExMTAyMuIt0Q8fPkTPnj1hZ2cHKysr1KtXDydPnkRKSgp69uwJoLDmjqy78NSpU2jbti1sbW1RuXJl9OjRQ87RwLmKDh06pHZ/vHz5Mvz9/WFpaQk7OzsEBgbi9evXyM7OBmMMoaGh6NSpE9q2bYt27drhzz//VNuH7u7uWLJkCQYNGgSRSAQXFxesW7dOro1AIMCGDRsQHBwMKysrfPfddwCA9evXo1atWjA1NYWXlxd27twpt9yDBw9ix44dcv0gm+qojISEBAQFBUEkEsHR0RFDhw5V+/RdKpXiwIED+Pzzz/lpjDGMHj0a3t7eOHToEJo3bw43Nzf069cPx44dQ2RkpJw7SiAQYNeuXZgyZQq8vLwQHBws9ySqZs2aAAqHlhcIBHx6TNFUx7y8PEyZMgUODg4wNzdH27ZtIRaL+c+59N2wsDA0bdoUlpaWaN26Ne7cuaNy+wBg8eLFmD59Or8/c+KWbLpzYGAg0tPT+Zs6oVBoMOmOK1euBACMHz+eFxY54ev27dt6d6SpQtNUR0A/db64fbRbt24qa5BxsRu68PX3339DKpXC19eXP4fqW/hSN6ABAPj5+WH27NkAgIkTJ/LOAcKwUZbmyKGPOl95eXn8OZ2Er/IrfHGOL09PT96BW5FcX9x1mJeXF4CKIXzJnrOL+50vT3W+tHF86TrVUSKR8PEVTQ/WJUlJSejatSt69epFv92lTIUTvhgDsrP18yqL+6O5c+di1qxZiImJQZ06dTBw4EBe8IiLi8OIESMQEBCAixcvYt++fYiIiMCkSZPklsEJX8U5vhhj6NWrFzIyMhAeHo6zZ88iKSkJAwYMAFD4xKFhw4b8hdnNmzf5v5mZmZBIJIiKikKLFi0AFF6gjxs3DpaWljh58iQiIiIgEonQtWtXOUdLWFgYEhMTcfbsWbk6KrJkZGTgwIED/LKBwpNnUFAQmjVrhtjYWKxfvx779u3D1q1bFVI/i3MZLV68GP3798fNmzcRFBSEwYMH8ye9R48e4YsvvkBQUBBiYmIwZswYzJkzp9i+HDt2LDIzM/HXX39h8+bNePz4MYYPHw4AGDBgAJ8GdO3aNaSlpcHV1VVhOdnZ2ejRowe8vLwQFRWFRYsWYdasWXLbUtTtN3HiROTl5eGff/5BXFwcfvzxR4hEIri6uvIXOkePHpVzF2ZnZ2PGjBkQi8UICwuDUChE7969FfpL3f4YExODjh07ol69eoiMjERERAR69uwJiUSC9+/fY/369Thw4AD+97//Ye/evRg7diyGDBnCiyGqWLFiBXx9fREdHY2QkBBMnz4dZ8+elWuzcOFCBAcHIy4uDqNGjcLhw4cxdepUzJw5E7du3cJXX32FkSNH4sKFCwAAsViMrl27on///hq7LNPS0uDv74+GDRvi+vXrOHXqFJ4/f47+/furnOfmzZt48+YNmjZtyk+LiYlBQkICZsyYoSAI+Pn5oVOnTgr1N3777Td06NCBjzskJATx8fEACvcfADh37hzS0tJw6NAhpbHMnj0bBw8exPbt2xEdHQ1PT08EBgYq/LjPnTsXK1euxPXr12FsbIxRo0YV2zeyyKY5ck9fTU1N4efnh0uXLvHtDKHA/b///ovLly/DxMRE7rxZq1YtGBsbIzs7W6fpgdqgaaojoF/hS1WaI1B+Uh25NMeePXvyx7KsaKxLNHF8cSxYsAC1a9fG06dPsWvXrrIOjSgFDE34kr3xVLXPccLX1atX9V7CoKzIzc3FvXv3ACgKX9yNsiHD/c7b29tj0KBBAAqFL33XWi0tOMcXd34uDwJQcXAPs0UikcpyNhycE7k8CH6G7Ph69uwZfw7Tp/C1evVqfoC0R48e6S2OCgkrB7x9+5YBYG/fvlX4LCcnhyUkJLCcnBzGGGNZWYwVSlC6f2Vlab9t27ZtYzY2NgrTk5OTGQC2efNmflp8fDwDwBITExljjA0dOpT179+ficVilp6ezhhj7NKlS0woFPL9wRhjSUlJTCwWs7S0NJXrY4yxM2fOMCMjI5aamqqwzmvXrjHGGJsxYwbr0aMHY4yx1atXs759+7LGjRuzEydOsEePHrEaNWqw77//njHG2JYtW1jNmjXZtWvX+Pjy8vKYhYUFO336NGOMseHDhzNHR0eWl5cnF4u/vz8zMTFhVlZWzNLSkgFgderUYcnJyXybb7/9lnl5eTGpVMpPW7BgAbO0tGQvX75kjDHm5ubGVq1axeLi4phYLGaZmZnMz8+PLVy4kJ8HAJs3bx7/PisriwkEAvb3338zxhgLCQlh3t7ecuv55ptvGAD2+vVrtX157NgxlpmZye7cucP27dsn15c3btxgAOS2qSgbN25k9vb2LDs7m5+2fv16BoCFhYUxsVjM/vjjD7lYGjRowBYtWqR0eadPn2YA2MWLF1WukzHGXrx4wQCwuLg4xphm++PAgQNZmzZtFJZVUFDA/vnnH2ZmZsb++ecflpyczMRiMXv69CkbPXo0GzhwoMo43NzcWNeuXeWmDRgwgHXr1o1/D4BNmzZNrk3r1q3Z2LFj5ab169ePBQUF8e+Dg4PZ8OHD5doAYIcPH5bb5hs3bjDGGJs/fz7r0qWLXPtHjx4xAOzOnTtK4z98+DAzMjKS23f27t0rt9yiTJkyhVlYWMjF1KdPHxYVFcWkUimLiopi9evXZ+PGjVMaJ8fw4cNZcHAwY6xwnzYxMWG7du3iP//w4QNzcXFhy5cvZ4wxduHCBQaAnTt3jm9z4sQJBkDufKIK7tzy9u1bJhaL2a1bt+Q+7927NxsxYgT//tWrV0wsFvP7T9FzuS7o168fA8CGDRum8FndunUZAP5cZWj88MMPDIBcn6pi+/btDADr0KGDDiIr/M0BwIyMjNibN29Utnvy5AkDwIRCodwxYkjk5eWxSpUqMQDs6tWr7NatWwwAs7KyYgUFBTqPp3fv3gwAW79+vUbt//e//zEA7MsvvyzjyIiPhTuXGxsbs3fv3il8vmbNGgaAffHFFzqPSfY3qSgFBQXM2tqaAWCxsbE6i02XREdHMwDM3t6eP1edOnWKAWC+vr56jq54WrRowQCwI0eOsPfv3/Pf16VLl/Qd2kcjlUqZmZkZA8AfI02bNtV3WB/N9evXGQBWvXr1YtvOmzePAWDjx4/XQWQfh729PQPAbt68qbLNwoUL9bI9V69eZQAYAIX7A12Rnp7O3/ca8jWoIaFOJyrKRzm+li1bBoFAgGnTpqltFx4ejiZNmsDc3BweHh7YsGHDx6z2k8LX15f/39nZGQDw4sULAEBUVBQOHz6Mdu3aoUaNGhCJRAgMDIRUKuVzlAFoXOMrMTERrq6ucs4jHx8f2Nra8rVuAgICcOnSJUilUoSHhyMgIAABAQEIDw9HWloaUlNT0aZNGz6+1NRU+Pv7w9XVFSKRCPb29sjNzZVLo2vQoAFf8FyWwYMHIyYmBrGxsYiIiICnpye6dOnCPwFITExEq1at5Gpb+fr64v379wq52cXVtpLtZysrK1hbW/P9nJiYyKcGcnAjGakiISEBjo6OfM0oIyMjeHh4wMbGRqu6QYmJifDz85N70sqtW1V9tylTpuC7775DmzZtsHDhQt6ZJ9tWKpXKpXAlJSVh0KBB8PDwQKVKlfj0udTUVLllq9sfOcdXUd6/f48HDx4gLy8P3bp1Q7169dCuXTt4enpix44dxRaJLtrXrVq1UuhDWUcVUNhv3H7I0aZNm4+q2RQVFYULFy5AJBLxL85Jo2obcnJyYGZmplH9NQ7GmEL7Bg0awMTEBAKBAKampmjQoIFW25KUlIT8/Hy5PjExMUHz5s0VlqPuO9YEZQNMAIWDPMi6u7h9Wl8F7lNSUnDw4EEAwIwZMxQ+N/Q6X5rW+AL+S//QleOLq0vRtm1btbVJOMeXVCo12BGULl26hMzMTDg4OKBZs2aoW7curKyskJ2dXWwacFmgjeMLKPwOgMLt0MdxRmgO535u2rSp0rRCfTq+VKU5AoXXFZwbv6KmO8qmOXK/z+Up1VHW8WVhYYEvvvgCQMVId8zKyuJrhTZp0gRA+XA+FYcmIzpylJdUx5ycHH5frF69usp2+nJ8ybqr9OX42rBhg9y1cnlwlJYnSix8icVi/P7773I3ScpITk5GUFAQPvvsM9y4cQPffvstpkyZwt9wlDaWlkBWln5eWtYm1whOtAL+K9rIWZOlUin69u2LXbt24cqVK7xIdO/ePdSqVYufT9MaX8puuItOb9euHd69e4fo6GhcunQJAQEB8Pf3R3h4OC5fvgx7e3teDJBKpahfvz527dqFs2fPIiYmhh9Bj7NaA6prldjY2MDT0xOenp5o06YNtmzZgnv37mHfvn0q4y160y0UCsEYkxO+lPWDbD8DhX3N9XNJbha4dQiFQpiYmMiNLKmtCKIKLr6i6XJjxozBgwcPMHToUMTFxaFp06Z8XSzZdcuKgD179kR6ejo2bdqEf//9lx+dqWiRdXX7o4WFhdI4ZYWNEydO4NSpU9i1axdOnTqFhISEYut8KaNoHyrbh4q20bbviyKVStGzZ09+P+Ze9+7dk6trJ0uVKlXw/v17uX7kbl4SEhKUznP79m3Url1bYTonDnPfgTb7JddWkz5R9x1rgirhKyMjA1WrVuXfm5ubQygU6k30WLNmDaRSKTp16gQ/Pz+Fz2XrfBki2tT44oSvp0+f6qSeliZpjkDhccvtY4Za54tLc+zevTuEQiGMjIzQuHFjAPqp86Wt8NW8eXMYGxvjyZMnCg8yCMNCXZoj8N9vx71793SWoqaJ8AVU/DpfRet7Af8JX69evdL7IC3FwdX4qly5MgDw1+D79+/XeEAgQ4VLczQ3N4ePjw8/TZ9lFEoDTUZ05OBSHQ1d+OJEYgsLC7XbxQlfuq7xJVvaQh/CV15eHn+/VqVKFQDlQ1gvT5RI+MrKysLgwYOxadMm2NnZqW27YcMG1KhRA6tXr4a3tzfGjBmDUaNG4aeffipRwMUhEABWVvp5fcQ9dYlo3Lgx7t+/D1dXV9SpU4cXiTw9PeUcVJrW+PLx8UFqaqqc4p2QkIC3b9/yN4Fcna9ffvkFAoEAPj4+vKgZFhaGxo0b8+tr3LgxUlJSYGdnhxo1asjFp8kTjKJw4hF3k+zj44MrV67ICQA3btyAlZUVP/pR1apVkZaWxotDb968kXPDaYKPjw+uXr0qN63o+6J4enri+fPnyMjIgEAggLGxMR48eIDMzEy+LzVdd2xsrJwwwK1b3Yierq6uGD9+PA4dOoSZM2di06ZNAAovDLh5ufnT09ORmJiIefPmoWPHjvD29sbr1681jpHD19cXYWFhCtOzs7NRs2ZNmJmZITU1FbVq1eKdhdygDOpQ1vecuKoKb29vREREyE27cuWKVn1flMaNGyM+Ph7u7u5y+7Knp6dK8ZYbzU5W5GrYsCHq1q2LVatWKdy8xMbG4ty5cxg4cKDc9Li4ODnh69atW7y4zU1XV1uFOyfI9kl+fj6uX7/+UX2iDFXC161bt9CoUSP+vUAg0Fudrzdv3mDz5s0AgJkzZyptU14cX5oIX7a2tnBycgKAMncp5eTk4Pz58wCKF74EAoFBj+zIGOOFrx49evDT9VnnS1vhy8rKihfqip4TCfVkZGRo5Xb9WIoTvtzc3GBiYoK8vDyd1X0h4asQZcKXvb09//v77NkzvcSlCVKplL+ms7e3BwB06NABjo6OSE9Px5kzZ/QZ3kfDFbavWrUqbG1t+d/E8u764oQvbRxfDx8+NGhnLycsVatWTe2DaO5886k5vnbv3o1nz56hWrVqGD16NAByfJU2JRK+Jk6ciO7du6NTp07Fto2MjESXLl3kpgUGBuL69esqnzLk5eUhMzNT7kUoMnv2bNy8eRM//vgj4uLicO/ePfz111+YPHmyXLuiqY4SiUTBtZKQkIBOnTrB19cXgwcPRnR0NK5du4Zhw4bB399fLpUsICAAf/zxB/z9/SEQCGBnZwcfHx/8/fffaNy4MS/EDB48GPb29pg1axauXLmC5ORkhIeHY+rUqRoVjH7//j2ePXuGZ8+eITY2FhMmTIC5uTm/P02YMAGPHj3C5MmTcfv2bRw+fBgbN27EoEGD+IuRDh06YOfOnYiKisL9+/cxadIkpUKROsaPH4+kpCTMmDEDd+7cwe7duxEaGqp2npYtW8LT0xPffvstoqOjcfPmTSxatAgtWrRQSMtTx6BBgyAUCjF69GgkJCTg5MmTvGjMfZ9FHV/Tpk3D6dOnkZycjOjoaJw/f56/iXdzc4NAIEBERASePXuGrKws2NnZoXLlyvj9999x//59nD9/XmnqV3GEhIRALBZjwoQJuHnzJm7fvo3169fjyZMnsLKywqRJkzB9+nT8+eefePz4MeLi4vDrr79i+/btapd7+fJlLF++HHfv3sWvv/6KAwcOYOrUqWrn+frrrxEaGooNGzbg3r17+Pnnn3Ho0CF+YICSMHHiRGRkZGDgwIG4du0aHjx4gDNnzmDUqFEqRaeqVauicePGcjec3CiiCQkJ6NOnD65du4bU1FQcOHAAPXv2RKtWrRTSx8PCwnDw4EHcvXsX69atQ3x8PIYMGQIAcHBwgIWFBV9sX9kIMFZWVvi///s/fP3117zTbuzYsXj//j3/41pSUlNTERMTg9TUVEgkEsTGxuLOnTtyT8BTUlLw5MkThd8MfY3suGnTJmRlZaFevXoIDAxU2oYTVyuC8AXorsD9hQsXkJubixo1aqBevXrFtjfkAve3b9/GgwcPYGpqKncdw53Dy4PjC/gv3ZGEL81gjGHz5s2oUaMGvL29kZubW+brfPjwIVJSUmBkZKSQps9hZGQET09PALpLd9RU+GrRogUEAgGSkpIUSk1UBOLi4gCAH70YKPwtLw/pjm/evOHFEE74MjY25geuKu8DX3COrypVqkAgEJSrQu/q0CbV0dXVFQKBADk5OXx/GCKaFLYHDMPxxbkkdQVjjB9lfOrUqfx+bMjnlvKI1sLX3r17ER0djWXLlmnU/tmzZ3B0dJSb5ujoiIKCAl6lL8qyZctgY2PDv4pzhHyq1KtXDxs3bsSjR4/QoUMHNGrUCPPnz+fr8nAUdXxlZWWhUaNGcq+goCAIBAIcOXIEdnZ2aNeuHTp16gQPDw8+tZCjffv2kEgkck8l/f39IZFI5BxflpaW+Ouvv+Dk5ITx48fD29sbo0aNQk5OjkY3a5s2bYKzszOcnZ3Rvn17vHz5EidPnuTTdqpVq4aTJ0/i2rVr8PPzw4QJE/D5559j9OjRvBgUEhKCdu3aYezYsZg2bRq6dOkilwaqCTVq1MDBgwdx7Ngx+Pn5YcOGDVi6dKnaeT58+ICffvoJtra2aNeuHQYMGIBq1appNHqgLCKRCMeOHUNCQgIaNWqEuXPn4scffwSgOtVRIpFg4sSJ8Pb2RteuXeHl5YXffvsNQGGfTZgwAb/88gtq1qyJSZMmQSgUYu/evYiKikL9+vUxffp0rFixQqs4gcI0jDNnziA2NhbNmzdHq1atcOTIEX6/W7p0KRYsWIB169ahX79+GDFiBI4dO8bXE1PFzJkzERUVhUaNGmHJkiVYuXKlSrGCo1evXlizZg1WrFjBHyfbtm1T+SRdE1xcXHD58mVIJBIEBgaifv36mDp1KmxsbBS+A1nGjRuncGHZpk0bXL16FUZGRggKCoKnpydCQkIwfPhwnD17FmZmZgrLOH78OHx9fXHw4EEsWbKEf8JnbGyMtWvXYuPGjXBxcUFwcLDSOH744Qf06dMHQ4cO5d2ip0+fLta1WxwLFixAo0aNsHDhQmRlZSEoKAhDhgzhn5ADwJ49e9ClSxf+h5yDc3zpUvjKz8/H2rVrARTW9lL11JETil68eKHX0X1UoU2NL0B3wpdsmqMmqcWG7PjiRhlu37693I1/s2bNABTWNdR1mhAJX2XLy5cv0bt3b4wdOxbZ2dnIyMjQyY0kV9+rWbNmakUmXdf50lT4srW15YXuyMjIMo9Ll7x9+5Z3ghQV88uD8MX9folEIrlsEC7d8ejRozoXGEoTWccXUL5GOFSHNqmOZmZm/L5oyOmOmgpfhuL40qV77vTp04iPj4dIJMLYsWP5PiLHVymjTdX81NRU5uDgwGJiYvhp/v7+bOrUqSrnqV27Nlu6dKnctIiICAaApaWlKZ0nNzeXvX37ln9xI6dpMqrjp0Rubi4Ti8Xs+vXratvl5OQwsVjMoqKiyjSe6OhoJhaL2fv37/lp3Mhtt2/fLtN1M8ZYdnY2E4vFSkfLe/z4MROLxezhw4dlHgdjjN29e5eJxWL24sULxljZ9EN8fDwTi8VqR01TRkJCAhOLxSpHpCxNMjMzmVgsljtnaNMX3Kic5ZmcnBxWo0YNduXKlRLND4CtWLGC/74yMjKYWCxmCQkJpRhl6XHnzh0mFov5kVVzc3OZq6sri4iIUGgrew7Lzs7WybmcGwXV0dGR5ebmqm3r6urKALDLly+XaUwloXnz5gwA++uvvzRqv3r16jIfEU4qlTJ3d3et4uJGGzt69GiZxVVSPvvsMwaArVu3Tm66RCJhNjY2DIDcuU0XVK1aVW7EXU3gRukFwI+wTChy8uRJ5ujoyAAwExMTZmxszACw+Pj4Ml/3yJEjGQA2Z84cte2+/vprBoBNmTKlzGNi7L9RpHv37l1s27FjxzIAbPbs2TqITHdcvnyZAWDVqlVT+Kxv374MAFu7dq0eItMMbqS6GjVqyE2XSqWsVq1aDIDciM/ljRUrVjAAbPDgwYwxxiZOnMgAsJCQED1H9nFMnTpVo3MCR+vWrRkAtn///jKOrORw2/T111+rbScWizUe0bI0qV69Ov9bCYBlZmbqbN0dO3ZkANj06dMZY//1gYuLi85iKK+U2aiOUVFRePHiBZo0aQJjY2MYGxsjPDwca9euhbGxsdJ0HycnJ4Xc9xcvXsDY2JgvslgUMzMzVKpUSe5FKML1d9FaOkXhPpdKpWVWEJUxpjQe7n919YdKC3X9UdyojqUNlxrB1dQqi/VzTiptUzc5d5Iu+oJzJ8jWwJIdWfJTwNzcHDt27FDpcNUULmWZe2JbdOABQ4HbL7l4Hz58iLlz5ypN3zE1NYWxsTEYYzpJJ2IyVvJJkyYpOOuKYsh1vgwx1fHOnTtISUmBqakpOnTooNE8hur4Sk9Px+XLlwEUDv4hi1Ao5EcP03Wdr5I4vqpWrco7pStqDaaP4f3795g0aRKCgoLw/Plz1KtXD9euXeNHHdOF66C4+l4chur4AipunS9l9b04ypPjq+g9l0Ag4F1f5TndUTbVESg/IxwWhzaOL6B8bLe2ji9dOhELCgqQlpYmN01Xbv+YmBiEhYXByMiIL+XC9dGzZ8+KrdFNaI5WwlfHjh0RFxcnVxuqadOmGDx4MGJiYpTegLdq1Qpnz56Vm3bmzBk0bdpUYSQ9QjvUFTeXxcjIiE85Kau0DFkRRTYe7n9dHLSqimrLxqELsYcxxosS3I11WQiAmgqfRdFlX3ApbLI3aZzw9qkIX0BhKnDRm2dNkO2joqM65ufnG2QR06LHYZ06dfDVV18pbSsQCPh9QxcjO168eBE3btyAhYUF/u///q/Y9oZc56ukwte9e/fK7HzMpTkGBASoHPChKIZa4+vUqVOQSqVo0KCBQoouoJ86X4yxEglfAKU7qiI6OhpNmjTBr7/+CqCwtopYLEbDhg11dvP18OFDJCcnq63vxVEehC+xWGywD2ZKQnkXvrhaRVx9L1k44ev06dMGXRtKHRU11VGbGl9AxRK+uAdi796909l17rNnzyCRSGBsbAwHBwcAuhO+uAey/fr14/dfBwcHGBkZQSqV6nSQlYqOVsKXtbU16tevL/eysrJC5cqV+R+EkJAQDBs2jJ9n/PjxePjwIWbMmIHExERs3boVW7Zs+agi00Qhmgpf3KiCQNkJULKF1mXrHenS8aXOAaVLsefDhw9gjEEgEPAiRWmvX9Zhp63jS5d9oewmTRvhKyUlRaHQ+6dEfn4+xGIx2rdvzx9Lsg8MDHEYcnUCtDI4gUQXji/u4mLEiBEqHceylAfHl6Y1vlxdXWFhYYH8/HytR7bVFNn6XppiqI4vZaM5ysLV+dKl8JWbm8vfBJDw9XFIJBIsW7YMLVq0wO3bt+Hs7IzTp09j9erVsLCwACB/81WWaFrfC/hP+EpJSZEbQKSs0Eb4ql27NipXroy8vDzcuHGjrEPTGcoK23NwN/CGLHypcnwBhQ9EGjduDIlEgj///FPXoZUKnGBXVsLX+/fvsXbtWp0Lado6vrjtrgjCF3e+kUgkOjnPAfIjTnL7ki6Er8ePH2Pv3r0A5EcZNzIy4kfjpjpfpUeJRnVUR1paGlJTU/n3NWvWxMmTJ3Hx4kU0bNgQS5Yswdq1a9GnT5/SXvUnhzbCR1kLX6rcR7IiS1mr9obi+JJNc+ScdrLOt9LoB1UOO03QVV9IJBK+L2TdH7pMtSzvcMKWiYkJvy8JBALe/WVowpdEIuEFTU33S+4GnhNJy4rExEScOHECAoEA06dP12geQxW+pFIpf0OqqeNLKBTy6W537twpk7hu3rwJAGjXrp3G83DxG5LwlZ+fj1OnTgFQTHPk4BxfN2/e1NmFuewxUlLhSywW60RkNmRSUlIQEBCAb7/9FgUFBejTpw/i4uIURiDXlfClaZojUDg4lEgkglQqxYMHD8o0LkA74UsgEFS4dEfGGC98lVfHF3fzrszxBaDcpztyji8u1VF2NLzScB5u374dU6dOxdy5cz96WdpQUseXoTrdpFIpf5xoKnwBunODc4Xtq1evzh8ruhC+1q5di4KCAvj7+/PXFRzl4fxS3vho4evixYtYvXo1/z40NJT/Eefw9/dHdHQ08vLykJycjPHjx3/sagloV+OJc4mUtfBVNBZZEaqs0x3Vpf7pUmzhboJk6wfJ9ktppPipcthpgq6EL+4mzcTERM6l9KnV+PoYuIs22ZGYgP+OZ0NLJ+H2KYFAoLHwxYmieXl5ZbpPrFq1CgDw+eefo3bt2hrNwwlfKSkpOknF1BTZ1CttamBywldZ1PmSSqV8Sg33lFITDDHVMSIiAm/fvkWVKlXQvHlzpW3c3NxQuXJl5Ofn84JfWcOdU7naeNpQq1YtODo64sOHDzp1qRkau3btgq+vLyIiIiASiRAaGooDBw4odcPoWvjy9/cvtq1AIOBdX/fu3SvLsAD8V65AE+EL+C/dsaKM7PjixQukp6dDIBDwvweylIcbU+68rMrl/OWXX0IgEODy5csG7RZSRVHHl4ODA8zNzcEYkxulr6TExMQAKLsHRqr4mBpfhlgG4+XLlygoKIBAIICzs7PatkZGRrzzVld1vjjHl6urq86Er8zMTGzcuBEAlGbC0ciOpU+pO74I3VESx1dZOURUua0EAoHORCdDcXwpE76EQiHv2CmNGEpa3wvQvfBVtNaPbKqjIf44GxKyji9ZDLXAvewxyO3vxSErjJbV+enFixfYsWMHAHkreXFUrVoV9vb2YIzprKaOJnDuKBMTk2IL9MtSlgXu37x5wwuXmqSRchhiqiOX5ti9e3eVv68CgUDndb5KWt8LKIz3s88+A/DppjsmJCRg6NChePfuHVq3bo3Y2FgMHz5c5blKFzW+tKnvxaHLOl/aOL6Awrq+AHD58uUK8fvO1feqVauW0uOOE77evHlT5q7lklKc46tatWq823DPnj26CqvUKFrcXiAQlGq6Y0JCQqktSxu0dXzVqFEDQKFYzYmdhgQn3jg6OmpU41tXDx44lDm+yroft2zZgszMTHh5eSktEVEehPXyBglf5RhDSnVU5z4r63VrEoM+Uh1lb0hlHTClEUNJR3SUnaes+0JZYXsAcg41cn2ppzjHl6GlOmpb3wuQL3BfViljv/32G/Ly8tC0aVM+5UvT2AyxwL1sfS9NBUagbIUv7gLR2tpaYX9VhyE6vo4fPw5AdZojh67rfH2M8AX8l+546dKlUoupPCEWi8EYQ4sWLRAeHg4PDw+17XVx48XV92ratKnG9foMWfhq1qwZjIyM8PTp01Jx2+gbdfW9gMJ9hHu4Z6g3p8U5vgBg8ODBAIDdu3frJKbSIj8/n3dGcY4voPTqfDHGeOHr5cuXOhM3GWNaO77Mzc15t7UhpjvK1tDSBO58WFEdXwUFBXzG3MyZM5Vm75Djq/Qh4asco43rR181vmSnGYLjizFW5mILd/Nubm6uNIZPzfFFwlfJUSV8lQfHlzZwNw5ltT2HDx8GUDhimzZCEWCYdb64G3Ft0hyBshW+uDor2ri9AMNzfN25cwf37t2DiYkJOnfurLYt5/gSi8W6CK3UhK/Lly9/kudeLjWwYcOGGp2jdCl8aVLfi8OQhS9LS0s0atQIQMWo86VuREeg8OGIobsyinN8AUCfPn1gamqKW7du8WJfeYD73REKhbCzs+Onl9YIhy9fvpQTP2RrWJcl79+/56/RNXV8AYY9sqOmhe05uHNORa3x9eeffyI1NRVVq1bF0KFDlbYx9HNLeYSEr3KMNo6vsq7xpYnbSp81vmTjKkvBhzGmNNVRNobS6IfScHyV5Y2PqsL2gHz666d486UNqlIdK5LjCyh74YtLGeBqXGkDJ3yVhVhUUjiRSFvhi7thTk9P528YSgvOVcClm2iKoRW359IcAwICiu1fTviKj4/XiRPgY4UvPz8/WFlZ4e3bt4iPjy/N0MoFnPClaY0/XaQ6alPYnsOQhS8AFarAfXHCF2D4N6eaOL5sbW3RvXt3AOWryD33O2Zvby93PVxaji/O7cWhKycVd81iZGSk1fm+Iglf+kp1dHV15Y+VshK+GGP46aefAACTJk1SMEpwkOOr9CHhy0BJSUmBQCDgiyoqw5BqfBmS40tZf5S22HLx4kUIBAL+x4njw4cPYIzJjbzHoawffv/9d7i6ukIoFMoNEqGOlJQUODo64s6dOzA2NlYZiyp04fhSVdiewxBGdnz27Bk6d+4MKysr3kouEAhw5MgRAJodg5oydOhQLF26VOv5PsbxNWLECPTq1UvrdX4MyoSvuLg4VK9enU99VQZ3YZefn18mFzkluXnjMETHV0mFL0tLS/6GoLSFvJI6vgwt1VHTNEeg8IbXyckJUqm0VM4TxfGxwpexsTFfg+lTrPN1//59AJoLX2V945WamooHDx5oVd8L+C/+tLS0Mj9uSnLubNmyJQDdpQCXFVKplBeIy7PwpYnjC/hvdMc9e/aUm4eSRQvbc5R34Us2zVEblzq33RVB+NLFgweOgoICpKWlAdCN4+uff/5BVFQUzM3NMWHCBJXtDP3cUh4h4UsPCAQCta8RI0ZotJySCF8HDx7UOF9cG0rb8RUQEMD3h1AohKOjI/r166fyR4cxVqzbRBeCj6zbq+iPVdH1Z2ZmYtKkSfjmm2/w5MkTjBs3Tuv1GRkZoXXr1khLS9PIDn3x4kVYW1vj3bt3OhG+irq9OAxhZMdVq1YhLS0NMTEx/JPztLQ0dOvWrVTXc/PmTZw4cQKTJ0+Wmx4fH4/+/fujatWqMDMzQ+3atTF//ny+7xhjvFCtrsZXcnKyUoFuzZo1CA0NLdVtKUpKSgpGjx6NmjVrwsLCAq1atcLGjRvlvtcGDRqgefPm/KiKypAVSIteaJYGHyN8cemBd+/e1atQK4tsjS9tKat0x5I6vgwp1fH169e8INSjR49i2wsEAp3W+fpY4Qv4L93xUxO+GGO848vT01Ojecpa+CpJfS+g8GbYwcEBQNmP7FiSc2fNmjUBlH+XQmpqKrKysmBqaqpWLDXkm9OCggL+oWhxDyW6d+8Oa2trpKam4vLlyzqI7uMpWtieo7SEr6IPvHTt+NImzRH4z/FliDW+DNnxlZaWBqlUChMTEzg6Opa58MW5vUaMGKH2monrq9evXxvUyOLlGRK+9EBaWhr/Wr16NSpVqiQ3bc2aNRotR5t0t7J2XZWW40vWwTJ27FikpaXhyZMnOHr0KB49eoQhQ4YonU92hEBDEb6KW39qairy8/PRvXt3ODs7l+hmxtjYGKampnByctK6dpFEIimzUZeKu0Ery1RHTV2NSUlJaNKkCWrXrs3fRDg5OWk1Sp4m/PLLL+jXr5/cjc3Vq1fRokULfPjwASdOnMDdu3exdOlSbN++HZ07d8aHDx9QUFCgcp/mhDCpVKpyf7axsSkTkVuW27dvQyqVYuPGjYiPj8fcuXNx6NAhLF++XK7dyJEjsX79erXHHjd0dWnXF/nw4QN/XimJ8OXm5gZzc3Pk5eUhOTm5VGMrKSWt8QWUnfBVERxfp06dgkQiQb169fib9+LQZZ2v0hC+PtWRHV+8eIF3795BIBAUW9Seo6xvvEqS5sihq3THkghfzs7OAApd1eV5ZEfut6hu3bpqR6EzZOFLNhNAtgaWMiwsLNCnTx8A5afIPfe7U9TxxQlAjx49+qhrfu5BnI+PDwD9OL60oSKlOurS8SVbeF8oFJap8JWYmIjjx49DIBBg+vTpatva2Njw18aGeH4pj5DwpQecnJz4l42NDQQCgcI0jgcPHqB9+/awtLSEn58fIiMj+c8kEgliY2PRrVs3WFhYwNXVFVOmTFGaUsT9aBcnNKSmpiI4OBgikQiVKlVC//798fz5cwCFJ2IjIyNERUUBKHyCam9vj2bNmvEi3OHDh/mLHqDwRDdhwgR06NABvr6+CA4Oljshc+lYy5Ytg4uLC38xBxRe3Ds5OcHZ2RktW7bExIkTER0dLRdveHg4mjdvDktLS3Tt2hW//PKL3Da6u7vzKYSc8NS6dWssWrSIbyMQCLB582b07t0blpaWqF27Nv766y+59Zw8eRJ16tSBhYUF2rdvr/JHhatrZW5urtCXkyZNQnp6OgoKChAaGsqPEuTh4QGBQKBymdeuXUOjRo1gbm6Opk2b4saNG/xnRkZGCqmODx8+RM+ePWFnZwcrKyvUq1cPJ0+eREpKCtq3bw8A6NChA5o2bcq7C0+dOoW2bdvC1tYWlStXRo8ePZCUlMSvh0v7O3TokMr9ESgsmuzv7w8fHx906NABQ4cOxevXrwEU7i/Lly+Hh4cHmjRpgkGDBvFFx1Xh7u6OJUuWYNCgQRCJRHBxccG6devk2ggEAmzYsAHBwcGwsrLCd999BwBYv349atWqBVNTU3h5eWHnzp1yyz148CB27Ngh57KUTXVURkJCAoKCgiASieDo6IihQ4eqrZUklUpx4MABfP755/w0xhhGjx4Nb29vHDp0CM2bN4ebmxv69euHY8eOITIyEqtWreLFmmbNmmHjxo38cV6zZk0cPHiQF8O4J9GNGjWCQCDgb6KKpjrm5eVhypQpcHBwgLm5Odq2bSt3s87tR2FhYWjatCksLS3RunVr3LlzR+X2de3aFdu2bUOXLl3g4eGBgIAADBkyBH///bdcu8DAQKSnp/MOB2VwNQ5KW/iSPR+qciCqw8jIiK8NZih1vkqa6gj8V+estG+YP9bx9e7dO73fJHP1vTRxe3Fwwld5cXy1aNECRkZGSE1N1VmhZkOAS3N0dXVVWU+lKGV942XowldBQQF/TaON8MWNLPfhw4cyLQ5d1mhS3wswbOGLOy/b2NhoVHuTS3fcv3+/wQ2eowxVqY7Ozs4wNjZGQUHBR30vnPDFZQKUF8dXSkqK3n9Pi2LIji/ZwvYA5ISv0u5HLvvh888/l7vnVYZAIKA6X6VMxRO+GAOys/XzKoOTzNy5czFr1izExMSgTp06GDhwIO8EuXPnDqZMmYJevXrh5s2b2LdvHyIiIjBp0iSF5WjiCmOMoVevXsjIyEB4eDjOnj2LpKQkDBgwAEDhCbhhw4b8xdrNmzf5v9zTCU74AAov0tu3bw9ra2v8/vvv2LNnD0QiEbp27Sr3gxoWFobExEScPXuWr69SlIyMDBw4cAAtWrTgpz158gRBQUFo1qwZrl69ijlz5uDo0aP4/vvvlS5D2VCxHIsXL0b//v1x8+ZNBAUFYfDgwfwF26NHj/DFF18gKCgIMTExGDNmDObMmaN0OZzjy9TUVKEvU1NT8e2330IikWDAgAE4d+4cgEJhKy0tDa6urgrLy87ORo8ePeD1/9g77zA3qrOL/0baXtx778Y2uGEMhrhg00MnhBBCCSFfMB0CJEASSEiA0HsJndBSMC10U00xbrhgG/e+67be4u1aab4/Zu/sSKsy5Y402tV5Hj+71s6MRqOZe9977jnnjhzJ4sWLueWWW7j22mv1v0crZC699FIaGhr44osvWLFiBX//+98pKiqif//+vPbaa4C2msh7773HPffco7/PNddcw8KFC/n444/x+XycdtpprYjSWPcjwNKlS5k1axajR4/m6aef5sknn+Tkk0/WZ9v+8Ic/8Oyzz/LYY4/xv//9j7PPPpvf/OY3cckQgLvuuouxY8eyZMkSbrjhBq6++mo++uijsG1uvvlmTjnlFFasWMGFF17I66+/zpVXXslvf/tbvv/+e37zm9/wy1/+kk8//RTQ1BnHHXccP/3pT02rLEtLS5k+fTrjx49n0aJFvP/+++zatYuf/vSnMfdZvnw5FRUV+uBYXKdVq1ZxzTXXtLonx40bx1FHHcUrr7wS9oz88Y9/5IwzzmDZsmX84he/4Oyzz9YHrZ988gkAc+fOpbS0lDlz5kQ9l+uvv57XXnuN559/niVLljBs2DCOPfbYVgOTm266iXvuuYdFixaRlZXFhRdemPDaCDQ1NVFdXd1qZjknJ4dx48Yxb968mPuKwajszl0MWnNyclpZRs3CazlfTogvMUgTExqy4FTxpapq3Bw4txEIBHTC1ky+l4B4ttesWeO6XVMG8VVYWMjEiROB9qX6shpsD+4OvOzmewkkg/gyPo9WiK/c3Fy9HRC5OemItkB8mc33Epg5cyY9e/Zk3759fPjhh26emhSIfidywsXv9+s1tV2yat++fezcuRPQJvmcHMsq7Cq+BgwYAGhtlph09gJqamr0z+RlxZe4Z8Tz0tDQIHXhml27dvHCCy8AhI3l4sHL7Us6ou0RX7W1UFSUmn8urOp07bXX8uMf/5gRI0bw5z//mS1btrB+/XpUVeWFF17g2GOP5eqrr2b48OEcfvjhPPjgg7zwwgv6LJ2AoigJZ3vmzp3L8uXLefnllzn44IM59NBD+ec//8nnn3+uK0NmzJihE1+fffYZs2bN4sADD9Rnu7/88kt99vLVV1/F5/Px4IMPMmzYMAYNGsSzzz7L1q1b9WOAVog/9dRTjBkzJqzAePTRRykqKqKwsJCuXbuyZs0annnmmbC/9+/fn4cffpihQ4cyY8YMLr30Uu65556oyjZB/kVj7y+44ALOPvtshg0bxm233UZNTQ0LFiwANOXQkCFDuO+++xg5ciTnnHNOzBw2QXx98803ra7lI488wpIlS/juu+/Iz8/XC8Pu3bvTq1evqOTkSy+9RDAY5JlnnmHMmDGceOKJXHfdda0+kxFbt27liCOO4KCDDmLIkCGceOKJTJs2Db/frzfm3bt3p1u3bnrHcsYZZ3D66aczfPhwxo8fz9NPP82KFSta5S3Fuh8B7rzzTiZNmsSdd97JiBEjOOCAA7jyyivp1q0bNTU13HvvvTzzzDMce+yxDBo0iJNOOomf/OQnPPHEE1GvpcARRxzB73//e0aMGMHll1/OT37yk1Z5UT//+c+58MILGTJkCAMHDuTuu+/mggsu4JJLLmHEiBFcc801nH766bqvXuRq5efnt1JZxsJjjz3GxIkTue222zjggAOYMGECzzzzDJ9++mnMwcfmzZvx+/26lRJaBiqCTInEqFGjWLt2bZhl88wzz+Siiy5ixIgR3HrrrUyaNIl//etfQAtx0LVrV3r16hW1wK2pqeGxxx7jrrvu4vjjj2f06NE8+eST5Ofn8/TTT4dt+7e//U1X7f3+97/n66+/btWexMKmTZv417/+xUUXXdTqb3379o0rvxf3suwcAyf5XgLCHug14stOxpeYGRcz5bJgV/GVn5+vE8CpzPn6+uuvqaiooGvXrno4txn06NGDAQMGoKpqmBrXDcggvqB95nx5jfgSEz4HH3ywrec4GcSXaDuzs7MtTxoI5X86D9bsEF9eU9mIdtks8eX3+/nZz34GpIfdMZbiC5znfIn+vn///vo9sGPHjqSspm1X8VVQUKDXm17K+RITmoWFhaYn7FKp+CoqKtLHzDJVq48++igNDQ1MnjzZ9IRHRvElF22P+GpjGDt2rP67KCR2795NMBjUfcIdO3akqKiIoqIijj32WEKhUNQsmngZBaA18v379w9THo0ePZpOnTrpHcCMGTOYN28eoVCIzz//nBkzZjB9+nQWL17M3r17Wbduna74Wrx4MevXr2fgwIFMmzaNiRMn0qVLF+rr68NsdAcddFDUouqcc85h6dKlLFu2jC+//JJhw4ZxzDHH6I3g6tWrmTJlCoqi6KqiSZMmUV1drbP3RsQjvozXubCwkOLiYnbv3q2/z2GHHRaWoSVWxjJCVVWd+NqwYUPUa1lcXGwpjHb16tWMGzcubKBjfO9oZOYVV1zBX//6V4444ghuvvlmXZlnROSqihs2bODnP/85Q4YMoUOHDnq+TaQVJtb9CC2Kr2iDs1WrVlFfX8/RRx9NUVER48aNY9q0afz73/8OuxeiIfJaT5kypRUBYVRUgXbdIjuVI444whFxsXjxYj799FP9WSsqKtIJkVifoa6uLupCB/EgVgU1Kr6iXYONGzcC5haN2LBhA4FAIOyaZGdnM3ny5FbXJN53HA8lJSXMnj2bo446il/96let/p6fnx935kxcI5mza9AyeLNjcxTwmuLLScaXW8SXXcWXoij650gl8SVsjieccIIphbQRycr5yhBf9iEmaMwG24O7igNBfNmxOUILgbd27VrXyBYnkwai70hXxVcgENDbexFLEQuC+KqpqfFEVqERYtBupV0Wdsc333wzKWobJ4gVbg/O867E9z9q1Ch69OhBbm4uoVAo6vhCNuwqvsCbOV9Gm6PZelgQX8m4BwXxJcZsiqJIz/mqra3lkUceATQRgdnrkFF8yUViw3e6oaAAUtVQOyxGo8FIVomHJBQK6XbHM844g1tvvbXVfkLuaoQgSWIVSWLAHe/1adOmsX//fpYsWcK8efO49dZb6d27NzfffDMjRoygR48e+iAxFApx8MEH8+STT7JhwwaysrL0vxlnZ2INSDt27KgXqcOGDePpp5+md+/euqLEeF5i8C/+L376fD7988ZbXTKSFFQURVeNmS0qA4EAoVAIRVHw+/1RV3VUVdVSoHui9442QLvooos49thjeeedd/jwww+5/fbbueeee8JWFYwM2j/ppJPo378/Tz75JH369CEUCnHggQe2yniIdT9CSzh5tBUdxTbvvPMOffv2Zfv27ZSXl+tqCauIvLbR7qHIbWLd32YRCoU46aST+Pvf/97qb8ZcOyO6detGbW0tjY2NOrkrZupXrVrF+PHjW+3zww8/MHz48IT5GoK8NDP7KO4jM9ck3nccCyUlJRx55JEcdNBB3HjjjVEJ2X379jF06NCYxxCfR7bdTYbiS7RbP/zwg+P7SAacWB3FAKG6upr6+nrTeUeJYFfxBdrnqKioSOmgURBfVmyOApMmTWLOnDmu53yJZ8Mp8SUI8O+//57y8vKEoddtAU4UX7W1tQSDQcuEaDw4yfcCGDp0KIqiUFlZyZ49e8JUxbLgpO0Ug7V0Jb7WrVtHIBCgqKgoYY1SUFBAp06dqKiooKSkxFa77BasKr5AyxUdMWIEa9eu5dlnn221IrWXECvcHpwrvozB9j6fjwEDBrBu3Tq2bNlievETu7Cr+ALtcy9YsMCTxJdQVJmBaHeSURcIMtN4fl27dmX37t3SiK+vvvqKsrIy+vbty2mnnWZ6v4ziSy7anuJLUaCwMDX/kjgYCgaDjBw5ko0bNzJs2LBW/6IpqBJZHUePHs3WrVt15hu0hr+yslIf+Imcr4cffhhFURg9ejRTpkxhzZo1YfleABMnTmTdunX07t2b/v3707dvX/387DTmkVao0aNH8/XXX6Oqqk5mLVu2jOLiYr2h6N69u154+f1+qqurLQf6jh49mvnz54e9Fvl/CM/3GjNmTKtruW7dOqqrq/XZGLPvvWzZsjD7lzFQPlYh3r9/fy6++GLmzJnDb3/7W5588kn93IwIBoOUlZWxevVq/vCHPzBr1ixGjRplKxtg7NixfPzxx1EHZ6NHjyY3N5etW7cybNgwhg4dSv/+/Rk4cGDUbDMjol17obSKhVGjRrVSM3z99dcx7YVmMHHiRFauXMmgQYNaPW+xyFtBbBkto+PHj+eAAw7gvvvua0UoLVu2jLlz53L22WeHEVrRrkFkKGa8lYtEm2C8JoFAgEWLFjm6JqB1xjNmzGD8+PH86U9/wu/3R70vv//+eyZMmBDzOIL4qq2tlapgkEF8jRgxAp/PR0VFhfRsLDtwQnx16tRJ7wviLcxgBaqq6gMsq4ovaCEYUqX4Wrt2LWvXriUrK4tjjjnG8v6HHHII4H7AfbRJBTvo2bMnI0aMQFXVVguUtEWoquqI+AK5qoNt27axYcMG2/leoE00CULGLbtje1Z8CZvjmDFj4ubDCnhVlWFH8WVcbe7uu+9OirXPLty0Okau6Oj0eFYgQ/HlJaujcdVEs0iF1dE4HpGt+BJ5caNGjTK10ISAV9uWdEXbI77aCYLBIOeffz7Lly/n0ksvZenSpaxbt4633nor5uyMUHIEg0GWLl0a9m/VqlUcddRRjB07lnPOOYclS5awYMECzjvvPKZPnx5mJZsxYwYvvvgi06dPR1EUiouLGTx4MB9++GHY7OU555xDt27dOPPMM/nuu+/Ytm0bn376KVdeeaUpqXBtbS07d+5k586dLFu2jEsuuYS8vDx9YHLJJZewbds2Lr/8ctasWcPnn3/OAw88EBYaPnPmTP75z38yb9481q1bx5///GfLs7YXX3wxGzZs4JprrmHNmjW8/PLLPPfcc622EzlIubm5Ua/lb37zGyZOnJiQtDHi5z//OT6fj1/96lesWrWKd999Vw+kh+hk5lVXXcUHH3zApk2bWLJkCZ988olObgwcOBBFUfjiiy8oLy+nsrKSzp0707VrV/7xj3+wfv16PvnkE6655hpL1wjghhtuYOHChdxyyy2sW7eObdu28dhjj7F3716Ki4u59tprufrqq3n++efZunUra9as4dlnn+X555+Pe9yvvvqKO++8k7Vr1/LII4/wn//8hyuvvDLuPtdddx3PPfccjz/+OOvWrePee+9lzpw5psMko+HSSy9l3759nH322SxYsICNGzfy4YcfcuGFF8Yknbp3787EiRPDCCexiuiqVas444wzWLBgAVu3buU///kPJ510ElOmTOGqq64KU3z95z//4ZlnnmHt2rXcfPPNLFiwgIsvvhjQioP8/Hw9bF8UTEYUFhYye/ZsrrvuOt5//31WrVrFr3/9a2pra6PaEs2ipKSEGTNm0L9/f/72t79RXl4elRzavHkzO3bs4Kijjop5LPHMNjU1SV1NSgbxlZuby5AhQwBv2B2dZHwpiqKrsmTZHauqqvTJBzvElyDwUqX4EouqTJ8+3dakzMEHHwxolmI3V7GTZXWE9mV33L17N9XV1SiKYkmpkZubq9dNMu9NY76XE3WQ2zlfMoivdB2smc33EhCDU6+pMqyG2wtccMEF9OzZk61bt/Lqq6+6cWqOoapqzHB7aBvEl53+yOtWR7NIVrh9IBDQCXqj4ks28SUiQ6yqczOKL7nIEF9pimAwyPDhw/nnP//JunXrmDp1KhMmTOCPf/xjTNuVIElqamqYMGFC2L8TTjgBRVF444036Ny5M9OmTeOoo45iyJAheoi2wJFHHkkwGNRJrmAwyMSJEwkGg2GKr4KCAr744gsGDhzI9ddfz09/+lN+9atfUVdXZ6rYe/LJJ+nduze9e/fmyCOPZM+ePbz77ruMHDkS0BqDd999lwULFnDsscdy++23c/bZZ/OHP/xBP8YNN9zAtGnTOPHEE/nFL37B9OnTEyqMIjFgwABee+013n77bcaNG8fjjz/Obbfd1mo7ofjKy8uLeS1vu+02gsGgaUVLUVERb7/9NqtWrWLChAncdNNNurXV5/NFtVwFg0EuvfRSRo0axXHHHcfIkSN59NFH9Wv25z//mXvuuYdjjz2W3/3ud/h8Pl599VUWL17MgQceyNVXX81dd91l6RqBVoS/8cYbrFu3jgsuuIBp06bx5ptv6vfdrbfeyp/+9Cduv/12jjzySC6//HLmzp2bcCDy29/+lsWLFzNhwgRuvfVW/dzj4dRTT+WBBx7grrvuYsyYMTzxxBM8++yztm0loBW2X331FcFgkGOPPZYDDzyQK6+8ko4dO8adEf6///s/XnrppbDXjjjiCObPn4/f7+eEE05g2LBh3HDDDZx//vl89NFH5OTkhJE/f/7zn3n11VcZO3Yszz//PC+99JKexaWqKg8++CBPPPEEffr04ZRTTol6HnfccQdnnHEG5557LhMnTmT9+vV88MEHjmxOH374oU6WDh8+nOOPP56jjjqqVRv0yiuvcMwxx+iFYzQYCWmZhY4M4gu8FXDvJOML5Od8icFHQUGBbnm2glQrvgTxZcfmCNC5c2fdxrt48WJp5xWJDPFlD0LtNWDAAMvWXjcGX4JUMa5SbQeC+LKSG2oF7VnxtWLFCiBxvpeAV1UZdpW4eXl5+gTj3//+d0sRHclCZWWlPuESL+Nry5YtllXk+/fv11VAxoljcTy34cTq2FaIr2QpvkpLS1FVlezs7DBSyivEl5cXz0hLqGmAyspKFVArKytb/a2urk5dtWqVWldXl4IzSx12796tLly4UF23bp3pfXbt2mV5HzPYu3evunDhQvWHH36Iuc13332nLly4UK2trZX63gLr1q1TFy5cqO7atSvmNmbO0wnWr1+vLly4UN25c2fUvzc1NakLFy5UFy5cqDY1Ndl+n+rqanXhwoXqsmXLbB9j8+bN6sKFC9UdO3bYPkY07Ny5U124cKG6du1aU9utX78+7nYDBw5U77vvPolnmHzU1dWpAwYMUL/++mvT+wQCAf1eAdTXX3897jbBYFDiGdtDWVlZ1Oervr5e7d+/v/rll1/G3b+urk59//331YEDB6qbNm2Sdl733nuvCqhnn322o+Ncd911KqBedtllks7MPrp3764C6ooVK2ztP3PmTBVQX3zxRSnn8+2336qAOmDAAFv7/+QnP1EB9eGHH5ZyPlZQXl6uZmVlqUDC9igezjrrLBVQb7vtNolnF44jjzxSBdRXXnnF8bHWrl2rAmpubq5aX18v4ey8i2effVYF1KOOOsryvgMGDFABdcGCBdLO5+KLL1YB9ZZbbnF0nAceeEAF1NNPP13SmYXjqaeeUgH1pJNOsrzvvHnzVEAdMmSIC2fmPoYNG6YC6ty5c01t//vf/14F1CuuuMLlM7OGo48+WgXUF154wfK+5eXlanFxsQqob7/9tgtn5wyiDSssLIz694aGBlVRFBWIWZfHwoIFC1RA7dmzp/7a888/rwLqrFmzHJ23GYwZM0YF1I8//tjyvt9//70KqB07dpR/YjYxefJkFVDnzJljep/ly5ergNq9e3cXz0xVv/rqKxVQBw8eHPb61VdfrQLq9ddfL+V9LrjgAls1Ql1dnQqogFpWViblXNoa4vFEkcgovtIUwlplxbYnlDdmVoGzcy7xPMvxguVlQBzXzDnEy0JyAqPVMRqMqiAn5yA+q5OgXbeuhdkMGvH+XpxFlI28vDxeeOEFS3lKQu2V6H4W95RMa6BdxHoGt2zZwk033WQqy0YoGL2o+DIG3KcaTjK+wD3Flx2bI5DSVR3ff/99mpqaGDVqVNzFFxIhGTlfMhVfw4YNo0ePHjQ0NLieTZZqCEWUlRUdBdxQHTh9fgW8bHU0hturaaZSqK2t1Vdqtmp1bCuKL9DypWbPng1oinGvIV6wPWiZtuJ7sarSirQ5QvoovsR5VlZW6sdJNbys+BLKvsjgfa8ovvLy8vRz8Vr7ko7IEF9pCjvEl8iqkE0+mSFixGDYLdLJCvnmxjmoqhpmdYwGRVGkXAczJF8iuHUtzK46Jgib9kB8gZYdZMVGJcJkoy1SIaAoiv5MeyF8NtZ9OWLECH7zm9+YOoa4L7xMfKXa6tjY2Ki3NXYyvkA+8eVkRUdIrdXRqc1RQORgLly40PE5xYJM4ktRlHZjd7QTbC/ghtVRNvG1bt06V/pSGVbHurq6lFmY7WL16tWoqkq3bt1MD1K9SnzZzfgSuOqqq8jJyeGrr77yXDsRL9hewC5ZFY34EhbCrVu3ul67Ogm3Lyoq0vtiLwTcB4NBPdjdTsZXfX29a6IJiB5sDy3PjKhvnMLM/RoLmZwvecgQX2kKO6qfjOLLPZVRU1OTftx4ZIUMwskO6RkJQTDIJL6CwaCuekuk+DL7/ps3b+aqq66Scn7pBKHgys7ORlVVTj311KjbiXvNy4ovK/Cy4ktkfO3YsSOlAznj7Kdd4ksUxbJWdZSl+EpFuP0nn3wCwAknnODoOBMmTEBRFLZt2+bayp8yiS+AqVOnAvaIry1btnDggQfaWggl2Vi/fj1gj/jysuJr4MCBZGdn09DQELaCtCyIttPOKqL5+fm6WkU2GeQ26SAy2A466KCoOarR4FXiy4niCzQC8/zzzwe0rC8vIV6wvYDdvKtoxFffvn3x+/00Nja6urpzU1OT/uzZUXxBC+HnhZyvXbt2EQwG8fl89OzZ0/R+bq2qGwmx2JpXFV/g3fYlHZEhvtIUTq2OMqXnZkg4t9VWqT4Ho80xXtC5TOLLa4ovMSjLzs7WlUiJ3r+9KL6sQhBZ8UhUIC0UX1bgZcVXp06d6NWrF5Bau6MYNBcUFNi+1m5ZHdNN8WWciRaLpthFhw4d9GO4FXAvm/gSiq+vvvrKUlscCoU4//zzWblyJS+88IKUc3ELqqq2Wauj3+/XP5MbdkenbacbAfdXXXUVvXv3djU0XwTbm7U5gjcDqAOBgH7f2lV8gbZKtqIo/O9//9OvjRfgpuJLKLuF0hu02kYob9xUUhn7QbvElzHYP9UQKqVevXpZqlmMq+q6SXzFUnwJslgG8aWqqiPiK6P4koc2Q3x5paNJFuyQH8ZtZSqvzJyLW2oz0Ipw8f2bVXzJJlyE9ShWvlfkOTi5DjIyvtywnloZlHnB6tjY2OjZdkMQWYkIRC8qvuzel6qqoigKqqpKHWTKIr7AGzlfMgbNXrM6pkrxVVZWpt93ds/dCLdzvmQTX+PHj6ewsJDy8nJLFt777ruPzz//HNCuYV1dnZTzcQO7du2iuroaRVEYMmSI5f29THyBuzlfTttOY86XLLz22mvs3r3bVdudUHxZIb7EpEhjY6M0hYhTiPNQFMWWZU5g+PDh/OQnPwHgzjvvlHFqUiD6r3httx3iq66ujo0bNwLhii+7x7MKkctVUFCQsAaMBS+t7Ggn30tAtD1u1gbJUHzV1NTo/WRG8ZVapD3xJRoFURC2F9hRfBkzpmQSUKnO+BLHVBQlrtrK+LdUEV8yroMMxZcbVkezwfbG908V8VVWVsby5ctdlas7gVnFlxeJL7uFWm1tLcFgkL1790qd3RO5czKJr1TmfIlBs12bI3gv3D5Vii8xA9u1a1dH7amA2zlfsomvrKwsDjvsMMC83fH777/nxhtvDHtNDBy8CGFzHDBgQML+ORq8nPEF3ia+ZCu+mpqa9IGfmwN6O8RXbm6uTsB4ZXAqBuydOnVyNFEK8Lvf/Q6AV155xRNkCiQOtwd7lr81a9agqipdunRpRVIkw0LoJN9LQJD8a9askXFKjuCE+EpGwH2ijC8ZxJeoNfLz821ZxzOKL3lwXumlGH6/n06dOuk3VUFBgWlPfjpDKEKMuUpmIAiHmpoaaddJnEsoFIp5LoLgaGhosHS+ZiBYdL/frxNQsSAUJbW1tQlJBSsQg2ufz2fq89XX19u+DuIzxrveiSBIiqamJmnfh+iYsrKyEh7T7v0rC6K92L17t6Piwi0Yr0m86yMUa248V1Zh9zsVz+Pu3btZvXo1tbW1nrQ6gjeIL/GctUXFV6qILzszsNEgiK9FixbpSjJZCAQC+jMmi/gCze748ccfM2/evISLUDQ2NnLuuefS2NjIj3/8Y9avX8+aNWvYvn27rfysZMBJsD14X/ElPld7IL5KS0v1WtItxU15ebk+uBwzZoylffv06cPevXspKSnhoIMOcuP0LMFpvpcRBx98MEcddRRz587l3nvv5cEHH3R8TKcwY3U0Wv7MtsnGfK/I7ZOp+LJrcwQYO3YsAMuWLZNxSo4QS1FlBm5MPBgRCAT0uINYxFddXR11dXXk5+fbfh9jrWGnLsgovuQh7YkvaJEYixurPWDnzp0Eg0GysrIszWKWlZXpxIkd1jneuWRnZ8ckk6qrqykrK6Ompka63bG+vp69e/eSnZ3Npk2b4m5bVlZGKBSKe652UFpaSmNjI4qixG2gy8vLqaqqorGxUSfLrGLXrl06sWB3oBgIBNi7dy+KotiaBY9EKBTSG+S8vLyEq6AIZQ/Axo0bk0pWq6rKtm3bwmyOdlVKbkEsAZ+TkxP33BoaGti7dy9+vz+u2jEZ2Llzp6lzjoVOnTrphJJXiS8RcO8FxZcM4mvfvn00NTU5Vjula7i9bOJr/Pjx+P1+du7cSUlJia0Z7lgw2gllE19gTvH15z//maVLl9K1a1eeeuopzj33XNasWeNKsLoseI34amho0BW67UXxJWuwZrzP3CIehNprwIABlomHPn36sHz5cs8MTp2u6BiJ3//+98ydO5ennnqKP/7xj7ZWp5MJM9mSAwYMALTnt6Kigs6dOyc8brRge4FkEF8yFF+C+NqxYwdlZWVSyE+78LLiS2Ty5eTktLqPOnTogN/vJxgMUl5e7oj4crKiI2QUXzLRJogvRVHo3bs3PXr08ETIczLwk5/8hJqaGj744AO9ITaD++67jw8//JA//vGPnHPOOVLO5dRTT6WhoYGPP/44ZsP20UcfcfnllzN+/HheffVVKe8r8MEHH3DllVcyceJEXn755bjbzp49m82bN/Piiy/qs/NOoaoqZ555JtXV1fzvf/9j8ODBMbd9//33eeCBB/jpT3/KX/7yF1vvd9VVV7FmzRqeeuopS1J8I/bt28fJJ58MwMqVKx3L4BcvXszFF19Mjx49+OKLLxJu39DQwIknnghotiAnti2r+Pbbb8OUDb/97W/59a9/nbT3T4SamhqOP/54QLuu8Qjq3bt3c+qpp+L3+1m+fLnj79Eu6urq9HO2831mZ2fj9/tdyXNwQ/G1YcMGGhsbpZLnZiGD+OrSpYuufi0rK7O00lI0OFV8pdrqKIv4KigoYMyYMSxfvpxFixZJJb7ERImsyQqBww47DL/fz5YtW9i2bVurWW+Br7/+mjvuuAOAJ554gl69eukz+OlgdbQTbA/yFQfGe1xGmySIr82bN9PQ0CD13vCa4mvr1q36724TX3ZqK6+pMkS7LIv4mjlzJpMmTWLRokU89NBDtmtYWTBDJhQUFNC9e3f27NnDli1bTBFf0YLtBdJF8dWhQwcGDx7Mpk2bWL58OUceeaSks7MOGRlfbim+BJner1+/VpPHiqLQuXNn9u7dy759+/Tn2w6c1hrivXft2iVlsrI9o01dOb/fn7KBXzLR1NSkz0h07dqVvLw80/v6fD69wLWyXyzU19frM43dunWLecwOHTqwZcsW8vLypLyvEbt27WLLli2MGzcu4bGrq6vZsmULlZWV0s5jz549rFy5EkVRGDZsWNzjZmdns2XLFjZv3mz7/VevXs22bdvo2LGj7WN07dpV77gDgYBj9d+iRYvYsmULY8eONXVOubm5bN++nWAwSCAQkH5PxMMHH3zAli1bKCoqorq6mldeeYXLL788ae+fCJs3b2bLli106NAh4Sxd37599etYWVnpqGN2AlFUZmVl0a1bN9sKPjeKHJnEV58+fSguLmb//v2sX78+6oyw25CR8ZWVlUXnzp3Zt28fe/fudUR8qaqaUXwZMGnSJJYvX87ChQs55ZRTpB3XmKEoUyFbVFTEhAkTWLRoEV999RU/+9nPWm1TXV3NeeedRygU4txzz+WMM84AWqwhGcWXeYjnt6ioSEq92qtXL70v27hxY9TBul14LdzeeJ9t3rxZup0YnBFfYmDvFeJLKL5kqX0UReF3v/sdZ555Jg8//DDXX3+9lH7VLsyE24NGVu3Zs4fNmzczfvz4hMc1q/hy4/6DFsWXE+ILYNy4cWzatIlly5alLfHltuIrkQ2zS5cu7N27N6GLJRGc1ho9evTQ1We7du2SOqnW3pD24fbtEU6WupWd7VJeXg5ohFq8gZiYZRHby4QVObcbWTJiRrlfv34JCRwhXRYzOnYgrqGZmatYyM3N1WeGRSfrBIsXLwa0HAgzUBRFJ9vcXKY4Gj766CMAbrrpJgDmz5/v6tLoVmElD8Hv9+uz6qlUXRizRJwUgqIN8SrxpShKynO+ZGR8gby+oLq6WldaO1V8VVdXJ3XBC7eIL5C/sqPsYHsjEtkdr732WjZs2ED//v156KGH9Ne9Tnypqqr3z14jvmTYHEFrk9yyO3pN8WW8z4R1TTZkKL68YkeSbXUEOO200xg+fDjl5eU8+eST0o5rFfX19fr9mcg+Zsz5SoTGxkadLI9GfAnrZHV1tSvjGZBjdQTv5Hylg+IrltJZVsC901rD7/frsU5eIdbTFRniKw0hGkU7S93KJr5EY9C5c+e4GUOCpNm3b19YtpIMWJFzC6LQDeLLjJXCKfEVCAT0DsAJ8QVyr4VV4gtaMubsZp3ZQVlZmX6u5513HpMnT0ZVVd5+++2knUMiWA0C9YL330zWhhnILnJCoZDUVR0h9TlfsgbOsvoC8d3n5eXZJmWMnyWZRLjbxJfMvi5VxNe7777LE088AcBzzz0XNtnmdavjrl27qK6uxufzxY0giAevE1/gXs6XLOJr//79Up7rSIJVtt1MVVVWrFgBYCucXpbVUVa7ITPcXsDv93P99dcDcM8996RsRWnR74gFzuLBij1x3bp1BINBiouLoxI1+fn5en/hlt1RhtURNMUXpJb4qqqq0p/9dFR8iWcn1cQXeKPWbwvIEF9pCCeNoluKr0QkjCClmpqapBMdVuTcbiq+kkF8GfdzOhskroVTxVd1dTU//PAD4H3i65NPPkFVVcaMGUOfPn049dRTAXjjjTeSdg6JIDpis0WCFwafsokvWUWOIAuMx3YKofgS93yy4TXiy2m+F2gKVJFZkcycLzeIr7Fjx5KdnU1ZWZnUJe/dJL6OOOIIAJYvXx7WH+zdu5df/epXgJYtOXPmzLD9vK74EsqNAQMG2M6+civjy+vEl4xJg+LiYr2fl6H6cpv4Ki0tpby8HJ/Pp09wWIEM4uv555+nc+fOfPLJJ7aPIeCG4gvg3HPPpXfv3uzYsYOXXnpJ6rHNwlhzJFKZWyG+xIRWtBUdBawoyOxAluJLEF8rV66UvqiYWQiSpkOHDrbaETdcAEYkS/El6iwntYbXMgTTFRniKw0hyA87jWKqiC+jOs1pAxIJO1ZHGfY+gWQSX+J6i9VGnECW4mvp0qWEQiH69Omjz/CagegEk0l8CZvj0UcfDaATXx9//HHSg7VjIR0VXzLID5A/yBTHURTF0Yo8RqTa6igj4wvkK76cqAoURXFlUiIR3CC+cnNzdYuJTLujm8RXr169GDZsGKqq8vXXXwOa6mT27Nns3LmTUaNGcdttt7XaT7RR+/btCyOZvQKnNkdIL8WXIPpkoK6uTlceOZk0kGl3FINUUWvJJJahxeY4fPhwW7mjYmAqVjq3gxdeeIHKyko++OADW/sb4YbiC7Q27uqrrwbgzjvvtGRP37BhA48++mjYQgV2YGWVPEF8mblfRL5XvKw8twPuZSm+Bg8eTFFREY2NjaxZs0bCmVmHE5sjyJ8MjYSZjC+Qp/hyshKqF2r9toAM8ZWGcDIb4JbVMRHpJFbHAPk5X1asjl5SfNmRs8vI9xKQRQJ+9913gDW1F5D0jC9VVVsRXwcccAAjRoygsbGR999/PynnkQiiUzNLfIntvGB1dFpgy57dE8eRGQhuVHwlM49KwGsZX7JIz1QE3LtBfIE7OV9uEl8AU6dOBVrsji+99BL//e9/ycrK4sUXX4xKHHfs2FEfmHjR7iiIILsrOkJ6EV8yFV+yJg1kBdzX19frz6uw5somHpzke4HWjvh8PoLBoK12NRgMsnDhQkBOf+6W4gvgN7/5DR07duSHH37grbfeirttKBTi/fff58QTT2T48OFceumlXHvttY7e34rK3IpCK16wvYDbxJcsxZfP50t5zpdT4sttq2O6ZHxBRvElCxniKw0hw+pYVlYmZdBmhYgRDYhs4iudrI7iOwsEAtTV1Vl+L5nElyzFV+QsrFkk2+q4YcMGNm/eTHZ2NtOnTwe0ot5rdke7iq+2ZHWUTXzJXHlqyJAhZGdnU1tbmxKLl9esjrJJz2Qpvurq6vRiOkN8hed8bdu2jcsuuwyAm2++mYkTJ0bdR1EUT1itY8Hpio4QrkyWUTO5QXyJz1daWiptgGicNIiX35oIshRf4v7Kz89nwoQJgPeIr6ysLH2FXDuD09WrV+vfnwziyy3FF2j376WXXgrA7bffHnUit6qqigcffJBRo0Zx/PHH88477+jbrVy50tH721F8lZWVJaw3vUB8yVJ8QeoD7mUpvtyYIG9sbGTXrl2Au8RXKBSSYnXMKL7kwFJv9thjjzF27Fg6dOhAhw4dmDJlCu+9917M7T/77DMURWn1L1XZKG0FTmYDxMA0GAxKIaCsEDHGgHuZSOWqjvv27dPff+jQoQm3Lyoq0otIO3ZH42ICTiFL8bVz504AveAzi2RbHYXa6/DDD9dJN2ixO7777rspC2o1ImN19DbxlZWVpQ80U2F3lDVwFt+VIK7sIl0VX6IQzcnJkUpCABxyyCGARnzJUgUmi/j69ttvOe+886isrOTQQw/l97//fdz9vJzzZWVSKhaMlmIZfZXob2Xec506ddIHVLLsjrIWBRHEl1OVglGZ4VbGkpNgewEnqoxvv/1W/93rii+AK664gry8PBYsWMDnn3+uv/7DDz9w2WWX0bdvX6688krWrl1Lhw4duPLKK/Ux48aNGx2F+Fshvjp27KiTSPHumaamJt0SaIb4km21FZCl+ILUB9xbrWcj4abiq6SkBFVVyc3NjVm/yCC+Kioq9Iw1J1bHjOJLDiwRX/369eOOO+5g0aJFLFq0iJkzZ3LKKackZO7XrFlDaWmp/s/J7FsGzmYDcnJy9MZUht3RSsfqhuJLVdWUruq4YcMGQGuQjGRKLCiK4ijnyw3Fl1PiS8yYiKV2zSLZVsdIm6PAoYceSs+ePamsrAwr3lKB+vp6nYiwE24ve8VUs5Cl+jHmOcj4LG4QX5DagPu2mPEFyVd8Ga0HsmywAqNHjyYvL4+qqiqdfHEKt4mv4cOH0717dxoaGvjss8/Iz8/nhRde0BcdiAWvKr5UVZWi+MrLy9PzNGUMvsT9LUPNYYRsu6OstlOW4ksQXwMGDHCFeAiFQvpYxq7iC+QRX07784aGBp28dEPxBdpk5y9/+UtAU329/fbbHHPMMYwaNYpHHnmE6upq/fft27dz//33M2vWLHw+H/X19fqkqR1YVZkLsjTePbNp0yYaGxvJz8/X77FoSCfFlyC+li9f7vhYdiCeWy8qvsS59evXL2YNIMaVYpxpB6LW6Nixo+1FVsAbk9xtAZaIr5NOOokTTjiBESNGMGLECP72t79RVFTE/Pnz4+7Xo0cPevXqpf9zGsrd3uEk3B7k5nzZUXzJJL5qa2t1lU4qrI52ZpRlEF8yZvBkkYCC+LKq+Eqm1bGpqUlfJSmS+PL5fJx88slA6u2OokPLy8sz/R2LQruurs72oglOIcvqKMiPYDBIQ0OD4/Nym/hKheKrrWd8pYL4ko3s7GzGjx8PyLM7uk18KYqiq74A7r77bp1MiQevKr527txJTU0NPp+PwYMH2z6OoihSVQduWB2hhdzzGvElK+PLqPiyYl0zi02bNlFXV0dubq4p9X4sOCG+jGMpp/25mJT2+XzS7zUjrr32Wnw+Hx9++CEnn3wyH330ET6fj1NOOYW5c+eycuVKLrnkEv0Zys7OZsCAAYCm+rILK4ovMEdWCZvjAQccENfe68b9J6Cqqj4ZLYP4Ouigg1AUhdLSUmnZzmYRCoX45ptv9POwAzcVX2bUaDIUXzJsjtDStlRUVHhyMZl0gW3jfjAY5NVXX6WmpoYpU6bE3XbChAn07t2bWbNm8emnnyY8dkNDA1VVVWH/MmiBUxlsqokvmVZHcazs7GxTiqu2Qnx50epoV/GVDOJr0aJFVFZW0rlz56gh/MLu+Oabb6YksFzAGGxvVoWSn5+vk76pmgmSRX4Yn2EZM3xtjfhSVVV6xtfevXsdKQtkKb6SbXV0k/iClpwvEVbtFG4TXwDHHXec/nP27Nmm9vGq4kv0zQMGDHA0yw5yVQduEV/tRfHVv39/OnXqZMq6ZgUi32vUqFEJVY7xYJf4qq6u1hVnOTk5gLP+3OiEcJLRlghDhgzhF7/4hf5e119/PRs2bOCNN95g1qxZUeuYIUOGAM6IL9HvuEF8xbM5gnnrpB3U1dURCAQAOVbHoqIinchNtt3xu+++o6ysjOLiYg499FBbx0iG4itWvhfIIb5krOgI2n0n+v+M3dE+LLeGK1asoKioiNzcXC6++GJef/31mI1E7969+cc//sFrr73GnDlzGDlyJLNmzeKLL76I+x6333673rB07Ngx7k3ZHuFUBisePvEwOkGqrY7G9zdDFMgiewTsrBolOjM75+C1cHvj6kVezvgSNseZM2dGVZzOnDmToqIiduzYweLFi10/n1iwm4eQ6oB7WeSH3+/XVxDzMvF1wAEHAMknvmpra3ViVhbx1dTU5EhZIIv0TKXV0Q2Ie2Tr1q1SjpcM4utXv/oVH330Ea+//rpp4t2rii8ZNkeBdFB8tXXiSzxH4n6TbTcT2U5iUsMu7BJfIg+wX79+jBw5EnBGfLmd72XEE088wSeffMK2bdv4+9//rtsKY0EG8SXqTrP9jkziy+zx7ECMC3w+n7S6JVU5X6LunjFjBtnZ2baOkWrFl6hpa2pqbLsQZNUaiqJkcr4kwDLxNXLkSJYuXcr8+fOZPXs2559/vt5YRNv217/+NRMnTmTKlCk8+uij/PjHP+buu++O+x433HADlZWV+j+vFVSpRkbx1QKrq9ZkFF8tkEEC7t27l1AohKIolmczkpnxFSvfSyAvL4/jjz8eSK3d0S7xJbZPheKrrq5OH5Q7JT8gPOfLKdwivsTAZO/evY7D4a1AtFs+n88xAZKbm6sXlU76goziKzpkf55kEF9+v5+jjjqKvLw80/t4VfHVnokvL+UjCuKrvLzc1krWApHqDNk5X7LuF7sDU2FzPOyww6Rk+bi5omMk8vLyOPLII023TTKJL7N1p5mMLy8RXx07dpSWPZmqlR0T1d1mINre6upq6Rm2ZhRfxu/BrmhDZq2RyflyDsvEV05ODsOGDWPSpEncfvvtjBs3jgceeMD0/ocddljCVWdyc3P1lSPFvwxaIEvx1RYyvqzOaol7qba2Vl9lwwnSmfiSofgS+V7dunWzbA9IltVx//79es5AvA5Y2B29QHxZDQJNpeJLFNhZWVlS2mpjoeMUbhFfhYWFeuGbzIB7MfAuLi6WUhQ77QuMi4tkFF/hkD1TLdpJM5b+ZEIMGvbt2+ep3BEZKzoKpIPVcejQoSiKQmVlpZTaTlbb2alTJ91q6iTMPBbxJYt4EEo5M7l28SD6YqvElwi2P/TQQ6UMbpOp+LIKp8RXKBSy3O8kul9CoZDel5shvtxaWVRmsL1AKgLua2tr+fLLLwFnxJdof1RVld6/GMPtY8Hn8zkWbcisNTKKL+dwbPxWVdWS/O+7777TZ4AysAevhNurquopq6MZGItNpwMSY4FpJQzVK8SXDMWX3WB7SJ7V8fPPP6epqYkhQ4boBVc0nHDCCWRlZbFq1SppS8JbhVOrYypmgYyKHxlkjMxBplvEF6Qm50v2oFkMGuyq1mpra6mvrwfST/El2i63iS9ZRF4yFF920KFDB/358pLqq70pvvLz8/XQcBl2R1ltp9GeY9fuuH//fr1OEcSXbOJBFvElPuvu3bv1rKZEUFVVOvFlZbXzZMMp8VVeXq5b/q0SX6WlpVHHrFu3bqW2tpacnJy4dWLk8dxSfMnI9xIQxNeqVav0xcDcxrx582hsbAyz7tpBQUGBXlfKrg1Ef5UoTslpzldG8eUtWCK+brzxRubNm8fmzZtZsWIFN910E5999hnnnHMOoFkUzzvvPH37+++/nzfeeIN169axcuVKbrjhBl577TUuu+wyuZ+incErVseamhpdNZUuVsecnBzdxuF0QLJhwwZAa8ysFLFeIb7EjJIT4kvM4NohvpJldTQrt+7UqRMzZswAtJD7VMAYbm8FqbQ6ylrRUUAm8SVIVTeIr1TkfMkeNDvtC0T7m5OT4/gaZxRf8eFV4ktRFM/lfKmqqiu+2gvxBXJzvmROGjjN+RL3VadOnfTvQibxsH//fr2WcXq/dO3alezsbFRVNa1w2759O6Wlpfj9fg4++GCpiq9kWB2tQkwUl5SU2LK/ipqjY8eO+kIAidCtWzc9PzRa7qKwOY4YMcKUe8Et4ssNxdfAgQPp2LEjgUAgaQp1Y93tZELU5/O5MlZoaGjQJ7/cJr5kreoIGcWXDFgivnbt2sW5556rh9R/++23vP/++/qAsrS0NKxBaWxs5Nprr2Xs2LFMnTqVL7/8knfeeYfTTz9d7qdoR1BV1TNWR0HCZGdnmyrGvaD4Ank5X3atFE6IL/F5vWZ1tLqiIyTP6mglZyDVdsd0DLd3i/jycsYXtCi+kml1FM+qGPw5hdO+QKbaT3b+YiJkiC95EO2VV4ivnTt3UlNTg8/nY/DgwY6PJ+u7DAQC+kC/PRJfdgdr0bJ4ZBIPQh3YvXt3x0obn89n+fOKfK+xY8dSUFAgZSLLy1bHzp076/WnnYw2q8H2oBH08VSCVvK9IL0UX4qiJD3nS0a+l4AbAffi2czLy0tIDotnSEz0WYWsVR0ho/iSAUvE19NPP83mzZtpaGhg9+7dzJ07N+ymfu655/jss8/0/19//fWsX7+euro69u3bx7x58zjhhBOknXx7RG1tLcFgEEi94svqioqCrKmoqNBlyk7hhPhyurJjsomvQCCgk0QyrY6NjY26XckqnFgdk0F8bd++ndWrV+Pz+Zg5c2bC7U8++WQAvv76a/2zJQuBQECfEU8nxZfsEN2M1TE2ROHnNcWXDNIzmVZHVVWTGm4vI5TXy8SXICS8YnUURMbAgQNNK0LiQVabZLy3ZZHXRnid+LKr+Ipc0RFaiIeSkhLbq60JyLI5ClhVZRhtjiBncJvMcHurUBTFkd3RarC9QDyySvTjVomvkpISqfZBNxRfkNyA+127dul5YrNmzXJ8PJk1oYAx3yvR+NVLVseM4ss5HGd8ZZBciEbR7/fbLoBFZ7F3715HBblV253YTlVVx6STgJ0cg3RVfBmVcjJmg4yFt91rIaT8dhRfycj4mjt3LgCTJk0ydZ/279+fSZMmoaoqb7/9tmvnFQ07d+5EVVWysrIsd5CiUC4rK3O0cpYdyFZ8pUO4PbQQX1u2bElaqLfXrI4yv/tkWh0rKip0m76MWdhoEJ8nGAzanlgwwsvEl9cUXzJtjiBPcSDu7fz8fLKzsx2fVyS8Snw5zfiKpvjq3r27bl1zet8JojTVxNdhhx0GtPTnu3fvtk2qeFnxBc5yvuz2O/GIL6H4Ev16Ioj7T1VVqe2eG4ovSG7Avai7x48fL4XscUPxZcVd4YT4ampq0sepsjO+ZK9y2V6QIb7SDMZG0a61RBT6gUDAEQFllfjKzc3Vi3ZZdkc7OQbpTnx17NgRv99vad9o8Pl8eodi9z6QofhyM+PLjtw6VXZH0RH36dMHn89a09ypUyd9EJDsmSAvZ3y5SXx169aNrl27oqoqa9askX78aPAa8SVTVZBMxZeYge3QoYOe+SgbxntOxmfyMvHlVcWXjBUdQT7x5dZK5YK4Wb9+ve4MsAsvKb6iEV+KokizmwmiUBZRaoX4CgQCLFq0CGhRfHXt2lVfCdNuf+5lxRc4I76cKr4i7ZWqqlq2OiqKoi8mIdPu6JbiSxBfyVB8ybQ5gruKr0T5XtDyDNkhvkR9rCiKlGdRtKUNDQ1SY4PaEzLEV5pBRqOYl5enNyRO7I52ZpRkB9y3p4wvmcH2Ak5zvmSE29fU1LgycxEKhfSZJzvE19y5c211tKFQyNbnsRtsD1qnKvZL9uCzvVodIfl2R9kZX4Ks9JLiq7a2VldjuQW3bY4QHsrbXogvryi+ZK7oCPLaJLeJLzEQb2hosJ1HI+B14gvk5Syl0uq4YsUK6uvr6dixo/7+xpUw7dod24PiyyrxFSvjq6SkhKqqKvx+v6U2w42cLzEJLZv4OvDAA/H5fOzevdv0ogt2oKqqdOLLDcWX0eqYCE4UX6LW6NatmxTBgjGTLGN3tIcM8ZVmEGSJUxmsjJwvO0SM2FYWU23H6igj1L2mpkYv4pwQX1YIEjeIL6d5Z07C7UVBHQwGXVliecWKFezevZvCwkKmTJlier/Ro0czbNgwGhoa+OCDDyy957Zt25gwYQLjxo2znDtiN9heIFWhl+013B6SH3DvVsaX+A6tQibpaSTz3FZ9JYP4ArkFu5eJr1SR7rFgd1IqFtJF8ZWVlaXXF14kvpyG2wtiTyCWgscKVFVNKfElbI6TJ08OU3o77c/TRfElVke3Ajvh9hCbqBJqr2HDhulKOyfHcwJZY7xIFBQU6KSem6qv1atXU1JSQm5uLj/60Y+kHFNm/IWA6KvMKL6cEF8yV3QUcEqKt3dkiK80gyz/d6qIL5krO6qqmjKro+isu3btapmIEt+d1VB5NxVfdoivYDCoD5idKL7AHbujmHWaPn26pYBjRVFs2R03bdrEtGnTWL58OStWrOB///ufldN1THylKuC+vWZ8QQvxtXTpUleOHwmvWR1lfve5ubn6oCNDfIUjFArp2X1eJL7E4KG8vNz1VXoTQVVVz2d8uUV8QUstJIv4MvbTdiGIr71791qe5DJmKEUOUuOt0mcWZWVlOtkwdOhQ28cxwg7xJfK9BJwQX3V1dXptmQ6KL6sKeadWx+3bt4epiq0G20ceLx0UX5CcgHtRd0+bNk2P33AKmZOhAlasjjIUXzKzREXbYHci4ZVXXmHq1Kk8+eST0s4pnZAhvtIMsvzfMogv0QjYUXzJsDrW1tbqRVSyrY5OZpSLior0mT0rdkevWR337NlDKBTC5/PZatSzsrJ0QsqNwZITufUpp5wCwP/+9z8CgUDC7detW8f06dPZvHmzLmd+/vnnLb2nLMVXqqyOXsv4UlVV6uAtGqZPnw5o98nChQtdeQ8j3CK+6urqbD2DslUFyQq4F8WoHcLeCmR9HuMEiReJrw4dOuifNdWqr9LSUmpqavD5fAwePFjKMdsz8SVj0qBr1656mL/V1ZKNC7ZE9o0yiAeh9urfv7+0Z8sK8TV//nygJd9LwAnxJb77rKwsV1YPlYEBAwbg8/moq6uzfE/YnXDp3bs32dnZBIPBsOtqNdheIJ0UX5CcgHvZNkdI73B7NybZnCq+Pv74Y7788ktbasu2gAzxlWbwouLLCukkU/ElOvfs7GxLA1un9j5wFp6rKIpOOFkhvuwQjYng5FqIYsWJd92Y8yUT9fX1fPHFF4C9DnjKlCl0796diooK/TixsGrVKqZPn862bdsYNWqU3vG/++67lgo60RGLgtcqUm119FrGV2Njoz6r65bia+LEiZx77rmoqsoll1ziOFA6EWRnfBUVFekqKzt9gWy1X7IC7tNN8WVcNVTWLLpseCXnS0xKDRw40JLSNx7SJeMLWtphu/ZlAZnEl8/n0+MQrOZ8ifupR48erWxoMogH2Ss6QsvAdN++fXFV/eXl5frCKJMnTw77m5P+3JjvZXcRLLeRk5OjtxlWc77sKr58Pl/UQHqrwfYCMhSHkXBT8eV2wH1jYyOfffYZIJf4kh1u39DQoNcAyVJ8yaw1nCq+xJhm2rRp0s4pnZAhvtIMXlJ8pTrjy2hztNK5p1rxBfYC7r2m+HISbC8gOjTZxNdXX31FfX09vXv3tlzMAPj9fk4++WQgvt1x+fLlzJgxg9LSUg466CA+++wzjjzySCZPnkwwGOTll182/Z5Owu2N+yVTcVFXV6cPyr2W8WUsktxSfAHcdddddOjQgUWLFrkuHZed8aUoiqO+IN0VX+lGfOXm5koJyHUDXsn5kh1sD+ml+BLtsBPFV2Njo650ljVpYDfgPp4lSRBf27Zts70ghuwVHUGr78RqsfE+r1AJDx06tBWJI0Px5dV8LwG7Afd2w+0hOllql/gy3n+hUMjyuUSDLHFDNAji64cffrCcQWsG33zzDTU1NXTv3l23VcqAbMWXeKby8vJMCTfENlVVVaYcIEZ4TfG1c+dO1q1bh6IoHH744dLOKZ2QIb7SDF4Kt0+11dHuqjXpTnzJzGyQofiyE2wvIAgJ2RlfQnV11FFH2Z7xNOZ8RcugWLx4MUceeSR79uzh4IMP5tNPP9U7t/PPPx8wb3cMhUKOia9UKL6MlgpZgzlZGV9i/9zcXN1m4wZ69uzJX//6VwBuvPFGR21qIrgxcHbSF2QUX/Eh6/OIiQE3CVyn8Jriyw3iq7q62tEKxOlidXRj0sBuwH084stoXbOrfpAdbA/hqzLGO69YNkeQp/jyMuwQX7W1tY4m2yKJrz179lBWVoaiKIwcOdLSsfr06UNWVhaBQMD2iqVGBINBvY1wQ/HVr18/OnfuTFNTk072yYSx7jYu1OAUshVfxjbFzPjAON62KtpwI9zeieJr3rx5gEaCukGupgMyxFeaQdZsgHgI24LVsb0RX15RfAniy4niyy2ro4ycgVmzZlFYWMj27dtZsmRJ2N+++eYbZs2axb59+zjssMOYO3du2Ozqz372M3Jycli2bJkpWfmePXsIBAIoiqIPEKxCEGalpaWWLHdNTU0ce+yx/PjHP7Y8a2m0OcqyVMgqctwOtjdi9uzZjB8/nvLycn73u9+59j5uDJzF4MFqX2BU+2UUX9EhW/HlxXwvAa8pvmSt6AgtbYiqqmG2U6tIN+JL5qSBIILsKr4iV3QETZktCDG7djM3rI5gjrgSwfaJiC+rZGtbVnyJfionJ8eW5T9yJVBBAA0ePNhy++r3+/V2T4bd0dhPuEF8KYriqt3RjXwvkK/4Em2K2Ulm42q5VkUbXlN8CeJr6tSp0s4n3ZAhvlKAN998k0MPPZQrrrjC8r5txeooU/FltXN3QvaAZgMQDY7d8FyvEF9OFF9etTru3buX7777DtBmnuwiPz+f4447DtCeWYEvvviCY445hsrKSqZOncqHH37Yioju0qULJ510EmBO9SUGi7169bI90OjZsyd+v59gMGgpW+z111/nww8/5N1332XlypWW3lO24gfSk/jKysri0UcfBeDZZ5/l66+/duV9ZGd8QUtfYDUTyA21n4xJCTPIEF/y4RXFlxtWx4KCAl3B4OS7TDfiS2bb6YbVEZzlfIVCIVfuF0gccK+qaswVHY37NzQ0WK6X27Liy1hz2Jlsi8zlshtsLyAz4F6MB/Ly8lrl2cmCsCDKDrgvLy9n0aJFgHziS7biS9TbZvK9BOzmfLm5quOuXbssW7xFvleG+MogqWhqamLBggV89dVXlvf1Srh9KBTyTMZXshVf27ZtQ1VV8vLybA+cxPdnhXByU/HVlqyOH3/8MaqqcuCBB9pWTwkY7Y4Ac+fO5bjjjqO6uppZs2bx3nvvxSQhhN3xpZdeSpgL4DTYHrTZR/F5rcwE3X///frviYL8IyF7RUcIz/hyYitKJvEF2oIIv/rVrwC45JJLbGfOxEIwGNQJEC9YHd1Q+yXD6hgIBPS+I0N8yYMXFF+qqrpidVQURUr2oOhnM8SXeWzduhVITHwJBY8VlJSUUFtbi9/vl7YCqEAi4mvDhg2UlZWRk5Ojq3CMyM3N1dtmq8oOu26IZMOJ4ssukRBJVNnN94o8np37LxJu5nsJuKX4+uSTTwiFQhxwwAG24zpiIdWKL3BOfMmsNbp3747f7ycUClma5K6oqNAJzwzxlUFSccghhwAa4x5vxZdocEPxZWdwWVVVpe9nhYhpC1ZH0WEOHDjQ9oDPK4qvtmh1lCm3PuGEE/D7/axYsYKHH36YE088kbq6Ok444QTefvvtuPknxx13HN27d2f37t188MEHcd/Hab6XgCDOzA4+FyxYEKZOskp8yV7REVoGW6FQyHL7aESyiS+A22+/nc6dO7Ns2TJdASYLxqLPDcWXVeLLDdIzGVZHcc/6fD7XB4btifjyguKrtLSU2tpafD6fruyQBRnfpZv5PQIyVnV0k/iSmfEFzlbWE2qvIUOGSM+BTER8CbXXhAkTYqp7rPbnAnbdEMmGIL527Nhhuq93EmwPLUTV1q1bCYVC0ogvmYovN9sHI/HlZGIxEm7ZHCF9FV91dXV6fyGT+DJOcltpT7/66itUVWX48OGOBAvpjgzxlQL079+f7t2709TUZFluKjvcvr6+3lZjIkiY/Px8ffUaM/CC1VEQX9XV1ZaykASMxJddeIX4kmF1lKH4kkV8qaoqtQPu0qUL06dPB+Dyyy+noaGBU089lTlz5pCfnx933+zsbM455xwgsd1RdMSyiC+zM8QPPPAA0CLz/+KLLywVQ25YHY1kopNCJxXEV/fu3bn99tsB+OMf/6g/IzIgBs25ublSbRAyFF+ykAzFl9F6IDOANxraE/El2q6Kigrpi5WYhSAyBg0aRE5OjtRjyxh8pcuqjl5RfAWDQb0vc8Pq6MaKjgJmia9oNkcBuwH36WJ17Nq1q95GmlVMiX7Kbs3Rr18/fD4fDQ0N7Nq1i9WrVwPeIL5EHe4m8TVmzBj8fj9lZWW2F4SIBjeJL7cUX24TX+Jezc7Olv6d2sn5EhPb06ZNk3ou6YYM8ZUCKIrCpEmTAHRPtFnIksIWFhbqA3c7dkc7KzpCS+NRXV1teVnYWOdgV/EF9hrSVBBfjY2NOjnUlhRfsjO+1q1bx9atW8nJyZHWuAu7I8BPf/pT/v3vf5smHoTd8a233orbYcoivsT+ZjrDHTt28O9//xuAp59+mpycHHbu3KlbhczADdWP3+/XB/jpRnwBXHTRRRxyyCFUVVVx3XXXSTuuG/le0P4UX8nK9wJ5nycdiK8OHTrofWuq7I5u2BwFZCq+kmF13Ldvn21Fhxttpxio7d692/SEo8iw8fl8MWMLZBBfsoPtwTzxFS3YXsAu8ZUu4faKoli2Ozq1OmZnZ+vXddmyZToR66WMLzetjnl5efrqlbLsjhs3bmTjxo1kZWUxY8YMKcc0QjbxZafedkJ89ejRQ1ochICdlR0zwfYaMsRXimCH+AoEAnoBLIM9dpLzZWdFRwhv0K2onaLBrtUxNzdXnw22MyBJBfFltIbKnDmwq/hqamrSFR8yrI6yFAJi1unwww+Xtgz72WefzaRJk7jssst46aWXLFkixo8fz9ixY2lsbORf//pXzO1kK77MDDwfffRRmpqamDZtGlOmTNELcCt2RzdUPyBHXZEq4svv9/Poo4+iKAovvvgin3/+uZTjiqJP9qDZi4qvtkZ8tQfFF7S0X6myO7qxoqNAuhFfTU1Ntp8jN9pOobAMhUL6M5gI4j7q27cvWVlZUbcxEg9WVyV2a0VHiE981dfX6wvwuEF8pYviC6znfMlQmYt75r333gO0dsvuhJLx/nNqHUyG4gvkB9yLuvuwww6TPjEHLe1QIBCgsbHR0bHq6+v1WseO4suKktbNWsOq4qu2tpaFCxcCGcVXhvhKEewQX0ZyQkbhJIP4sqo+8vv9+rk7tTs6yTFwonRKJfHVsWNH/H6/7feNhLgO+/fvt1Q0imw4n8/nqACRbXV0Q27drVs3Fi5cyEMPPRSz+I4HofqKZ3eUEW4P5hVftbW1PP744wBcddVVQEtnaIf4kqn6AaQESYt7KtnEF2jt+29+8xsALr30UsfqVnBv0Cy+Oy8ovpJpdcwQX/IhBhKpUny5tUIfOCfjg8Ggvq+bxFd+fr6u5rdrd3SD+PL7/fokmVm7oxlLktG6ZpZQE3BT8SUUavv372/1/C9dupRAIED37t3jhuq3dcUXWCe+nCq+oKV2f/fddwH7NkeAAQMGAFob7cReDMlRfIH8gHs3bY4Q3g457UvFs5Sfn28rn9rKuNWNFR0FrCq+vv32W5qamujbt6/0/Mt0Q4b4ShEE8bVy5UrTg37RKBYVFdkagEfCCfFl1+oI8gLuncxqOVEWiCyCVBBfsmfwxHVQVdVSQS9sjmJ1EbuQaXVsamri008/BdzrgO3gnHPOwe/38+2337JmzZpWf1dVNenh9i+++CL79u1j8ODBnHzyyYC3iC9BGKSj4kvgb3/7G926dWPlypU8+OCDjo/nFvEl+oGqqipLs6luKL7amtVRFpGXLsRXqhVfwuroRcWXsS1zk/gC5ys7utV2Wg1kTrSiI0BOTo6ufrBiN2tqamLDhg2Ae9ZYcc9EEn1Gm2M8C5Qd4ktV1bRSfA0dOhSwrviSQXyJ9sIJ8ZWbm6vf107tjslSfMkkvoLBIJ988gngXt2dnZ2tx4s4dYcYyXQr9kOjhdwsvKT4MuZ7ybZdphsyxFeK0KdPH/r06UMoFGLp0qWm9pE9GyBm36zOJoEzIkZGwL3Tzt0u8RUMBvWGMxXEl8x8L9D8/sK6Z8XuKEK7ndgcQa7VccGCBVRVVdG5c2cmTpzo+Hiy0LNnT44//ngguuqroqJCH9g6VXwZC+VYsntVVbn//vsBuOKKK3TicsqUKfj9fjZv3mx64OrWzHI6Wx0FunTpwp133gnALbfcYqudNcKtjK/OnTvr94CVleAyiq/EyCi+kgdVVT2d8SWe35ycHKmLU0SD05Ud3Wo7xWBNpuIL7OUsbd68maamJvLy8hxPOMVCLLvj/Pnzgfg2R7BHfNXU1OgTGG1Z8eWk34lUvDghvkBezpesDOdEEMTXmjVrqKurc3SsxYsXU15eTseOHTnkkENknF5UyOpLRZti9Zl3ovhyo9awqvjK5Hu1IEN8pRBW7Y6yG8UDDzwQsMf6OyFiZCi+nHbudrOtSktLaWpqIisrSy9q7MArxJeiKLZsn0Lx5XRJXJlWRyG3njVrllQ7qAwIu+MLL7zQKthXDBK7du2acKXIRBCdYW1tbcx7+6OPPmL16tUUFxdz4YUX6q8XFxfrhKHoJBPBbatjOhNfoH3vhx9+ONXV1VxzzTWOjuVWxpfP59PbUCvq34ziKzHE56mtrbW1grBAuhBfqVR8lZSUUFtbi9/vd8XK4dR+nYx8LwGnKzu6rfhyi/gyuzIghNti3VrdNRbxZSbYHlr687KyMurr6029pxiY5+TkeL69gHDiy0xGlkyro4BXiC8xHnBb8dW7d2+6detGKBRi5cqVjo4l6u6ZM2dKcSLFgoyaEFrqbSv5XuA94suK4isQCPDNN98AmXwvyBBfKYVV4kt2ozhhwgQAlixZYnlfJ1ZHsY8T4stp525X8SU6tn79+jlq5AXx1dDQYKqgcYv4AnskoGzFlwzi66uvvgI04strOOmkk+jcuTM7duzQZeECsoLtQcstEB10LNWFUHtdeOGFrQZhVuyOdXV1+oDcixlfXiC+fD4fjzzyCD6fj3//+9/MnTvX9rHcHDjbsb1nFF+JYVTnOSnY04X4SqXiS6i9Bg4cqC9eIxNO7dfJJL68bnWUTXwJotMK8SDyvdxQBwpEI752797Npk2bUBSFyZMnx92/c+fO5OXltTpGPBhV2OlgaRo4cCCKolBTU5Ow/2lqatJrYRnh9gJ2V3SMPF66KL4URdFVX04D7t3O9xJIR8WXcVVH2RCkuNExEgtLliyhtraWLl26OL7X2wIyxFcKIYgvsdJCIshuFAXxtXHjRssrLKba6mi0Odrp3J0SX05sjqAVlGKW0cy1d5P4SqXiS2bGl+hkvBjcmJuby89+9jOgtd1RVrC9QLyA+x9++IH33nsPRVG4/PLLW/3dCvElCuysrCzpg7m2kPElMH78eC677DJAC7pvaGiwdRyvEV9uqP3E915fX+949aZYSCbxlZubq0+QOCnYRWEra6VatyAICqeKr+XLl3PbbbdZev7dDLYHeVbHDPFlnfgSAeKxYId4cDPYXiAa8SXUXgcccEDCSWxFUSzbHdMp3wu0yWvRbojMtVjYt2+frgpzojQ23k89e/Z0fK3STfEFLSs7Osn5qq6u5uuvvwbcJ768oviqqKgwrd52M9y+Q4cO+kRYIlJc1PNTp051Td2aTshcgRRCEF9r1qwxRTrIbhS7dOmikwRmc8YEUm11FAWd3Q4r1cSXz+fTv8dUE192FF+C+PJSxpfXCz5hd5wzZ07YfScr2F4gXsC9CFk/+eST9VBZI4444ggAVq9enXCFLKPVTfbMcluxOgr85S9/oVevXqxdu5Z7773X1jHcyvgC68RXQ0ODfn3dsDqCe6qvZBJfiqJImakWEwNeV3yJNqyystLR57388su56aab+MUvfmF6tWE3870gQ3zJgJVw+8bGRl1Z7kbGlyBKU0V8JbI5CphdqVkgnVZ0FDCb8yVqji5dujhyXOTn5+u1q1ObI9iz2kZDshRfICfg/osvviAQCDBo0KCo9aRMyFZ8WSW+jGMvs0IRN2sNIymeqD3N5HuFI0N8pRDdu3fXG0wzdkM3lroVmT5W7Y4yrI4yFF92O3c7KieQR3yBtZwvJ9c7EexcCy9aHd0kB2Vg8uTJjBw5krq6Ov773//qr8u0OkLsQNx9+/bparOrrroq6r5du3bVs/++/PLLuO/jVr4XtD3iq2PHjtx9990A3HHHHaYH80a4lfEFLd+hWeJLDK78fr/U2ens7Gw9584N4qu6ulpXTyWD+AI5uWXpYnUsLi7W7we7dsempiZdBf/mm29yyy23mNpPEBlurOgIztukdCK+RH+cynB7sUBLbm5uQsWEkXgwkxMFybE6RuuLBfF12GGHWTqG2efJ6xOA0WCW+JIRbC8g7hmZxFc6Kb6MxJfZZyYSH374IaCpvdy21coivuzW29nZ2fo5mGlXVVV1fZLNTM5XKBTSa/lMvpeGDPGVYljJ+XJjNsBuzpcMq6OMjK9kK77EjE6yiS+vKr68YnUMBAJ6h+hV4ktRFF31ZbQ7yia+xHEiC+WnnnqK2tpaxo0bx/Tp02Pub9bu6EbGk4DMjC+v2MPOOusssrOzqaqqskUKJMPqaHYVOKPiVrZ03s2Ae1GI5ufnJ+2+kFGwpwvxBbHbH7NYtWoVdXV1+gIlt956a9hEQSxkrI4t8Lria+fOnQnJf2MWT6JBtajHqqurTdWV9fX1bN26FUiu4isUCrFgwQLAvOLLqtWxLSu+ZATbC4wZMwZAygrg4v4rLy931M6LGjwZxNeoUaPIysqioqLCtjU9WfleIGcytK6uTq9xrCq+wFrO1/79+/VYCzesjmBuZceVK1dSXl5OYWGhPt5v78gQXymGFeLLjdkA0eh/9913lvZr71ZHGTlSXrE6ivNIpdWxpqbGlgpGwHgNkyETt4tzzz0XRVH44osv2LRpE5AcxVcgEOChhx4CNLVXvIGEWeLLjVX9BNqa4gu0LDRR4ItBuhV4KePLTbWfmwH3xhnYZAU/tzfiy2nOl1B7TZs2jauvvhrQbOLxLDmqqmasjgaI59IskR0Jt9rOnj17oigKTU1NCUk5K5ak/Px8XVVhRnWzYcMGVFWlY8eOrg1KIZz4UlWVH374gaqqKgoKCnRldSK09YwvsG51lNHv3HHHHbz88sv84he/cHys4uJivTa3q/qqr6/XiZJk1LC5ubl60LmdgPsdO3awatUqFEVh5syZsk+vFWT0o6LWLigosHWNRa1rhvgStUZhYaFrk2xmFF+ijj/88MNdXXUznZAhvlKMQw45BDAXcO+G4ksQXz/88INp1U1TU5NexKWr1dGOyklV1ZRZHZ0o7BLBqtUxEAjoBYhTxZexQ6irq7N9HHF9OnTo4OnGvV+/fvqqky+88AKQnHD7119/ne3bt9OjRw89ZD8WRA7AsmXL4j4fbpIfbSnc3ggxKHdCfHkh48tNVUEyFF/JsjmCHCIvnYgvp4ovUQtNmjSJO++8k6OPPpra2lpOOeWUmEROSUmJrhJza3ETpyrUjOJLswuJ/iJRLo3VLB4rdjOjzdFNAlwo3Orr66moqNBtjpMmTTJdp9hVfLVF4kum4qtHjx6cffbZ0laAdWp3FLWWMRfSbTgJuBcrVB988MFJURfKmAw1Btvbee6tKL7cXNFRwIziK5Pv1RoZ4ivFEMTTxo0bEz5Mbii+evXqRa9evQiFQqZZfyNRkyrFVyqsjnv37tXJGTsy2Uikq9VRNOh+v99xh2ccyDmxO3o938sIYXd84YUX2L9/v37d3Qy3v//++wGYPXu2vjx6LPTp04dhw4YRCoX0FXuiIRlWR7tFTjAY1J9VLxFfIn/IDvHlZsaXFxVfbYX4yii+rEEQX4cccghZWVm8+uqrDB06lC1btnDmmWcSCARa7SOep0GDBpGdnW3zzOPDKRmfIb40mF3Z0eyKjgJWAsaTsaIjQF5enl6jlpSUWA62B/uKr3S0Ou7YsYP6+vqY24l+x02Vnl0Iwt0u8SXGAR06dEjayntOAu6TaXMEOf2o0T5tB1aILzdXdBRIpPhSVVVXfGXyvVqQIb5SjM6dO+uDocWLF8fd1o1we7AecC9IhuLiYlvqGhkZX6mwOooOrXfv3uTm5tp6XyPE92iGcEqG1dHstRDB9t27d3fcQft8Pn0w54T4Sid5/2mnnUZRUREbN27kX//6F6A9S7IGRKJTLysro76+nm+//ZZvvvmGnJwcLr74YlPHMGN39LLV0XgveYn4EoovYcuyAi9ZHd1UfCXL6pgstDfiy4niq76+Xp+AE2r4Ll268NZbb1FUVMRnn32m2x+NEM+TW8H2EP492gmDTgXxVVtbG5dIiIZgMKjfb260nWYD7q0qvqwQD8lY0VHAaHecP38+YI/4KikpMRUHkU61kEC3bt0oKioKc1VEg8xwe9mQpfhKRr6XgF3iS1VVXfGVLOJLtuLLDuwQX6lUfG3cuJHS0lKys7OZPHmya+eRbsgQXx6A2Zwvt5a6tZrz5XSFQbFffX29bXtbKlZ1lGlzBPOKr8bGRr0Q9YLiS1awvYCwOzrp0NJJ8VVYWMiZZ54JaDkTIE/tBdp9JVbG27FjBw888AAAZ599tunvzArx5cVwe3Ev+Xy+hAq3ZMKu1VFV1aQQX2VlZQSDwYTbJ8PmmlF8aVBVNa2ILyeKr+XLl9PU1ES3bt3C+tnRo0fz0ksvoSgKjzzyCE8++WTYfm4H20PL9xgKhWzVLckkvjp27KgvDmBV9SXuNUit4kuEz7ttdXQbgvhat24dK1asAMyv6Aja9VIUJSxiIh7SMdxeURRTdkeZVkfZkEV8JTOjVhBf69atszTxvGLFCnbt2kVBQQGHH364W6cXBpmKr7ZCfBkVX9EmY0T9PnnyZH1MkEGG+PIEBPGVKOfLraVu7Sq+nKitRFFmV/WVCqtjqogvcY0URXFlNshquL2sYHsBY8C9XaQT8QUtdscNGzYAcokvRVH0maAFCxbwn//8B4Arr7zS9DEE8bVw4cKwgZARblodndqKjFadZIWYm4EYaG3YsMEUwSTQ0NCgW7zcyP8QgyRVVU0VdRnFl3k4LdgDgYB+r6QD8SXaMjvEl9HmGPncnnzyydx6660AXHrppfoS7ZAc4st47e20S8kkvhRF0Wsjq8SX+Gx+v1+Ksj0SVq2ObhJfyVR8vf3224RCIfr27WspzzM7O1tvr8zYHdNR8QXmcr68bHV0Sny5Nb6Lh549e9KzZ09UVWXlypWm9xM2x2nTprnSRkSDTMVXMq2OySC+Ghoaoo6lM/le0ZEhvjwAIemPp/gKhUJ64SR7RkAscfr999/rq4rEg1OSQVEU/TPYDbiXZXXcv3+/6dUERXZEsokvcY06duzoivffKgkorI6yiC/RobUXqyNoHdHgwYP1/8sKthcQHfuf/vQnmpqamD59uqWljAcNGkTfvn0JBAJ6LkkkvGx19GKwPWiDuJycHBobGy0RA0bSxI3PlJ2drbdHZlQFGcWXeTglvozEczoRX1VVVZa/Q2OwfTTceOONes7XGWecoauCkmF19Pl8jpSoySS+wP7Kjm5PGgjiK14gc21trd6nyya+qqqq9Mm7ZCq+Pv74Y8CazVHAbM6XceIinRRfYI74ag9Wx2SvSm4n4P6DDz4A4JhjjnHlnKLBS4ovM5MJyQi3z83N1Z/zaG1DJt8rOiyNoh977DHGjh1Lhw4d6NChA1OmTOG9996Lu8/nn3/OwQcfTF5eHkOGDOHxxx93dMJtERMmTEBRFLZt26Z3yJGorq7WCRrZMwIDBw6kc+fOBAIBU6y/U6ujcV87ii8Znbux+DTbkIoOTdaqUVYVX26pmewqvjJWR/vw+Xycd955+v9lKr6gpVAWA8KrrrrK0v6KoiS0OybD6lhdXW0rT8erxJff79cLfCt2RzFoLioq0tWysmEl5yuj+DIPp0SeIL78fr9rwe0yUVxcrPcpVnO+jIqvaFAUhWeffZZx48axe/duTjvtNGpqavR2zm0iw8ngK9nEl92Ae7fbTjMZX2KAWlRUZLreFcRDWVlZ3FpCtLs9evRIirpGfF6h2HWT+Nq/fz9NTU1A+kwCCiQivlRVTQvFV2lpqSkBQSRSofgCazlfO3bs4LTTTtMVX+lKfLUVxRfEzvkqKSlhw4YNKIqSNDtqusAS8dWvXz/uuOMOFi1axKJFi5g5cyannHJKTLJk06ZNnHDCCUydOpXvvvuOG2+8kSuuuILXXntNysm3FRQXF3PAAQcAsQPuBSmRk5MjPbNGURRLOV9OrY7Gfe0QXzU1NXoRYfcccnNz9UGE2QFJqq2ObhNfqVJ8tUerI+Aq8WU83uDBgznppJMsHyMe8VVXV6cPyN0kvuzm6XiV+AJ7AffJGDRbIb7SXfElq+0yA1mKr4KCAk/ZduNBzKhbIb7279/P6tWrgdjEF2j9xZtvvkm3bt1YsmQJp556KnV1dfj9fmmTUrHgRPElarj2TnyZsToaV3Q0e8937NhRr6niqW6SaXOEFuJLwEq+l4DozxMRX+K7zs/PT7tMn0TEV3V1tU4oeVHx1bVrV12RK5SoVpAqxZcZ4isUCvHYY48xevRo3njjDbKysrjtttsYM2ZMsk7TsQvAjoo0EqJN9cqqjhB7ZUdhcxw/fnzSyVSvwxLxddJJJ3HCCScwYsQIRowYwd/+9jeKior0lUoi8fjjjzNgwADuv/9+Ro0axUUXXcSFF17I3XffLeXk2xIS5XwZV3R0o/i1kvMlg2QQ+9qxOorOPScnx7b1Q1EUyxa/VBNfbs3gietQX19PY2Njwu3dUny1J6sjaIXe8ccfD8DBBx8s9dhG6+QVV1xhSyUkiK9vvvmm1X0hnsGsrCxXBnLingB7hU46EF92FF9u5HsJeE3xJZv4CoVCSbEfREIW8WV8JrwOOzlfS5YsQVVV+vXrl7BvGThwIP/973/JysrSVxcbNGiQ64o4u9mDxsUpkjUIcUp8uXW/GYmvWGpeu5YkM3azZK7oCOHEl9/vt9XXi/48EZGcjnWQgJH4inZfiLY7Pz/fk22hoiiO7I6pVnwtX7486nVftWoVU6dO5ZJLLqGqqopDDz2UJUuWcMMNNyT1PJ32o+LZKSwstH2N00nxlcn3ig3bgUHBYJBXX32VmpoapkyZEnWbb775ppUU8thjj2XRokW6YicaGhoa9HwIOzkR6YhEOV9uN4oi/8cM8SXD6uhE8WW0OTohAa0MsKqqqvTvoK0pvozEhZlrITvcXkbGVzoqvgD+9a9/sWLFipiZNnYhBgzFxcVceOGFto4xatQounXrRl1dXat2wZjv5QYR7/P5HFlgxb3UVogvUex5QfEVCAT02Wk3Zt7dsjru27dPjwtIpmLA6edJpxUdBewovkTtE0/tZcT06dN58MEH9f8nI6/J7uCrpqZGH1S2d8WXIDUbGhpi1j5WV3QUEIo/ryq+DjzwQFukjVmrYzqu6CgwaNAgFEWhuro6ai6dl22OAk6IL9GnJpv4OuCAA8jJyaGqqirsvBsaGrj55psZP348X3/9NUVFRTz00EN89dVXHHTQQUk9R2hpj2pray0tDCQg+qL+/fvbrlmN49Z42dDJnGSLpfgSTo0M8dUalomvFStWUFRURG5uLhdffDGvv/46o0ePjrrtzp07Ww2Oe/bsSVNTU9zAzdtvv52OHTvq/+zKEtMJYuC7aNGiqKy72zJYofhatmxZwkZFhgLJScaXrFktKxY/0SF06dJFWkEovsv6+nrq6+tjbuc2qeP3+/VizEzOl1tWx/aU8SVQXFzMgQceKP24xx13HOeccw7/+Mc/bA+0FEXRO81Iu6ObVjcBJ9J2Lyu+RAC3HcWXF4gv0f4aFymRCbesjmIGtkuXLknNynI6Uy1I3HQivuwovhLle0XD7NmzufjiiwF7FjKrsPtdinvZ7/cnzYLmVeIrLy9P76djBdw7VXyJhYiiQRBfySBKQSP6xEDb7j1qlvhKZ8VXbm6u3m5Eszt6OdheQIbiK9lWx+zsbH0ML+yO8+bNY/z48fzlL38hEAhw0kknsWrVKi677DLXMkYTwah2tzNJ7jTfC1rGF6qqxh0rJXOSLZria9++fXz//fdAhviKBsvE18iRI1m6dCnz589n9uzZnH/++axatSrm9pHMqiB14jGuN9xwA5WVlfo/O8tipxvGjRuH3+9n586dUYsBtxVfw4cPp6ioiLq6OtasWRN3W69YHZ127lYUX7JXdAStIRfPQbxGNBmkjtmA+0AgoH9nGaujd5GXl8eLL77Iz372M0fHiZXzJZ7BZBBfdggDLxNfYsC1ceNGPYg4EZJBfInvMhHxJUjPLl26uFIEu6X4SkWwPcjN+EoX2FF8JVrRMRYeffRRFi1alBTrjV0y3vj8JiunTcaqjm4hUcC9W1ZHVVWTbnXMzs7W2xw7wfbQPhRfED/nK6P4cg9iZccvvviC3/zmN0ybNo0ffviBnj178u9//5s333wz5QKUvLw8fVV7O5OhRsWXXeTm5urjlXhjV1FDde7cmZycHNvvZwbRFF9fffUVqqoyYsSIpOaZpgssE185OTkMGzaMSZMmcfvttzNu3DgeeOCBqNv26tVLV4cI7N69m6ysrLgNc25urr5ypPjX1lFQUKAHBUazO7qt+PL5fIwfPx5IbHf0ktXRCawQX7LzvUC75qKTi2d3TAbxZfZaiMGj3++XRjK1Z6uj1yGIry+//DJMCWq0OrqFtqr46t+/P7m5uQQCAdOTOsnM+Eo0UHZ7cOW24iuVxJedFUrTkfiyqvgqKyvTB7tWiS9FUTj44INdH2CAc8VXMmtZryq+IHHAvVvE1969e6moqEBRFIYOHWrp2E5w7LHH0rlzZ4499lhb+wviq6KiQm8PoiHdJwDjEV/poPgyY7WNhVQpvqAl5+vee+/lH//4BwAXXXQRq1ev5swzz/TEoiqKojiaRLLbpkTCTM5XMmuNaIovke8l6vcMwmE740tAVdWYS7dOmTJFX/ZU4MMPP2TSpElpsSx3shEv4D4ZjaLZnC+ZVkc7ii9ZnbsoQs3Y+0RHJnvVKDM5XzKIxkQwq/gy2hzF7ItTOLU61tfX6yv/ZYgvuRg3bhzFxcVUVlayYsUK/fVkWB3tBkkb9/Ei8eXz+fRBl1m7o5cyvtz+7t0Kt0818dXU1GRrmft0JL6sKr7EZN+wYcM83YZniC85iEd8qaoatqqjFSQiHoTNsX///kld9fC5555j165drVZ4NIsOHTrodVI81VdbUXxt2LCh1d9Ev5RRfMmHED2ApoT87LPPePLJJz3XFjuZDJVhdQRrxFcy7lXRpuzatUt3EGTyveLD0sj1xhtvZN68eWzevJkVK1Zw00038dlnn3HOOecAmkXxvPPO07e/+OKL2bJlC9dccw2rV6/mmWee4emnn+baa6+V+ynaCOIF3CdjxQ+zKzvKtDraUXylwurohuILzBFfybQ6JroWsoPtwbnVUVwfn8/XLtShyYTf7+eII44Awu2OybQ6tjXiC6wH3Hsp48tttZ/4jIFAwBZRFAupIr6M96Cdmep0JL7E4MLs4kRWg+1TBRlWx2QhHYivaLEelZWV+jlYHaSK+qy0tDRqbmqybY4CiqI4muxXFMWU3bEtK77Syeq4fft2ywHsqVR8TZs2jf/7v//j1ltvZdmyZUyfPj3p52AGThRfMqyO0PJsxWtXk1lr9OjRA7/fTygUYteuXdTU1LB48WIgo/iKBUvE165duzj33HMZOXIks2bN4ttvv+X999/n6KOPBrTORqzGAjB48GDeffddPvvsM8aPH8+tt97Kgw8+yBlnnCH3U7QRxAu4d9vqCC3E13fffRdzxYqGhga9EM9YHZ3DK8SXWfWb7GB7kEd8derUSZoKLYMWRMv5ylgdncFqwH2yia94ljy3SU/jdyZT9ZUq4svv9+uklZ3Pk47EV1FRkd63mVF92Qm2TwXSUfFVUVFhaRCe6owvMYbo2rWr5XveuE80m22yV3SUCTPEl6xJ4VQh3a2OvXv3Jjs7m6amppgLN0RDKBTS24hUKL6ysrJ44okn+MMf/kBeXl7S398sZFgdnSq+RLvqFaujz+fTJxJ27NjB/PnzaWpqol+/ftLHq20FWVY2fvrpp+P+/bnnnmv12vTp0xMqiDLQcNBBB7WoTz4AAQAASURBVJGdnU1ZWRlbtmwJs9UlQ/E1atQocnNzqaqqYtOmTVEzEATJoCiKo3PxgtXRzqqObZX4sqr4khVsD84zvjL5Xu7CSHypqoqiKEld1bGthduDfcVXMjK+AoEAVVVVMdt3t0lPscpsTU0N+/fvlzbDnyriC7Tvrba2tt0ovkCbWa+oqGDbtm0xV/4WsBtsn2ykE/El6iNVVSkvLzfdVqfa6ugki0dRFAYOHMjq1avZsmVLq5Ubk72io0xYUXylu9Vx+/btNDQ0kJubq/8tHRRfPp+P/v37s3HjRrZs2WL6Hq6urtYnm1Kh+EoX2J0Mraio0McJVu3TkfBaxhdobcP27dspKSlh6dKlgFa3eyGbzYvIyCM8hNzcXH11jcicr2QovrKzsznooIOA2HZHWeoao+LLauCv7IyvRGRPXV2dTvikkvhycxbPrOLLTauj3YyvdJf3ex2TJk0iLy+PPXv26AOHZFgdZWR8iXvLaxADr/Xr15vaPhkZX/n5+fr1imd3TOZ33xYUX+BspjpdiS8xs55I8VVSUkJJSQk+n09XnXsV6UR8ZWdn6+S1lZUd05n4gvg5X21d8ZXutVD37t0pLCxEVdVW3186KL7AXs6XqP9zcnI8rbhKNey2vz/88AOgKU2dtsFmiC9xryar1jCu7JjJ90qMDPHlMcTK+UqW/ztRzpesoHWxfzAYtDywTXbGl5DeFxYWSi8oEq3q2NDQkJTgdjvh9rIgy+qYUXy5g9zcXA477DCgxe6YsTo6gyC+Nm7cqAeSxkOyBs5iUBGP+EqG2k98TjtEUSykkvhy8nnSlfgSxEWilR3FJN/o0aM9S1QLpFPGF9jL+Uo28RU58emU+BLEw+bNm8NeD4VC+kRDOhNf8YjkdA+3VxQlpt0xHcLtIfb9Fw+pDLZPJ9htfwXxNWrUKMfn4FXFF2j33Pz584FMvlc8ZIgvj8GY82VEMqyOEJ7zFQ2y1Ef5+fn68uNW7Y7JzvgyrugoWzoqiMxYhJPRWupm0Wz2WmSsju0TkTlfybQ6tkXiq2/fvuTl5dHU1GRqZjhZA2cxqIinEEnG4Cqj+GpBuhJfZhVf6ZLvBeml+ALvE1/CzmyE3RUdBWIpbnbs2EFdXR1ZWVnSV+dOBsTzFEvxFQqFkuIOcBvRiK9AIKDXyOlCfNlRfGVsjvHhVPF1wAEHOD4Hr63qCC2Kr7fffpu6ujq6du0qheRrq8gQXx6DIL4WL14cFjCfDKsjwIQJEwBN8RXNgiiLZFAUxVbAvaqq0q2OiVRObuV7QWKrY7KC272g+MpYHb0LI/FVV1enD8YzGV/24PP59AxFMzlfycj4AnMrOyZT8SWL+GpoaNDbtgzxlRyYVXyly4qOkCG+ZKGwsFC/FpF2R1mKr0jiQdgchwwZQlaWpXhjTyCR1bGyslIfM6RzLRSN+BJ9js/n8/wEpx3iK6P4Mgeniq9kE1/JVnytWbMG0GyOmXyv2MgQXx7D6NGjycvLo7Kykg0bNuivJ0vxddBBB+H3+9mzZ0/UDlaW1dF4DCuKr+rqagKBAJA8q6MXiC+3O/tUhttnrI7ex2GHHUZWVhZbt27VbdBZWVmuDuRkZHx5lfgCawH3ycj4AnPEVzIUX7KtjuLzZGVlpWRWvT0SX0KhEo/4UlU1bYLtIWN1lIlYOV8iWkJ2xpdoZ9PR5ggtg9vS0tKoq3SKOrqwsDAsFD7dEI/46tq1q+dX7hbjhE2bNpneJ6P4Mod0UHw1NjbqY5JkZ3wJZPK94sPbLUg7RHZ2NuPHjwdaLAD19fU0NDQA7jeM+fn5+gpM0XK+ZEqpBVFhRfElGpvc3FzHA4F0IL5kEo3xYEb91tDQoH9Xbii+GhoaLC27LpAhvtxHYWGhPjCdM2cOoBWhbs4q2R1kqqqaVsRXooD7UCjkGeKrqalJf97SKdzeOAObiplQGcSX1/OvIiGIi3hWx02bNrFv3z6ys7P1hX28DOP3aGVRngzx1RrRiK9QKKTfL04VX9u3bw/LT0znFR1Bq7l8Ph/BYFBvz4xI93wvgWjEV7oE2wMceOCBZGVlsW7dupiRMZHIKL7MwU5NGAgEdBGJTOIrVptqVCcmS3kpSHGBTL5XfGSILw8iMuBeNIqKorhudYH4OV8ySQY7Vkejrc3pAEZ0Mvv37w+zlUYio/jSIIqtrKwsqedjLLDtqL4yVsfkQMwivf7664D7Rahd4qu+vl5/ntOB+Eqk+KqpqdEH2akmvoxttZttkmzFVyrzvcAZ8SXaxHRVfO3fvz/mhIqY3Bs3blxaqFTE99jU1KRPRppBqogv0UabJb6SOWkQjfjas2cPjY2NKIrSajBnFr169SInJ4dgMBjmWkjnFR1Bq7uE0j6eGyPd6yAj8SX6vXQJtgetjznzzDMBuP/++03tk1F8mYOdfnTDhg00NTVRWFhou00xwqj4ijZuNN6ryVInGhVfRUVFungmg+jIEF8eRGTAvWgUO3TokJQHyZjzFYlUWx1lregILUWoqqpxCZf2QHyZUXwJm6OYeZSF3Nxc/Xh2bG0ZxVdyIGaRhITf7ZlluxlfxnvIyyoZs8SXGDT7/X7XlzpPRHyJ2czOnTu7mpPjpuIrFXDyedLV6lhYWKi3ybFUX+kUbA/h7YmVdinViq94i1UYkcxJAzFYKykp0V8TtthevXqRnZ1t67g+n09XixntjuludYT4OV9tRfElrKr79+/XP5O4f9OB+AK46qqrAHjllVf0XNx4yCi+zMEO8WW0OcpQe4uxp1GJb0Qqao0OHTrofdPhhx+elhmGyUSG+PIgBPG1ZMkSgsFg0oLtBYTiy22roxPFl4zOPS8vT28gYg1IAoGAXrS3ZeLLqPiKZeEwEl8yoSiKo5yvDPGVHBxxxBFhhYPbii+7GV9i+/z8fPx+v/TzkoVhw4YBGpEocgujwWhzdNumJ77TWMRXsgZXshVfou1KNfHVnjK+IHHOVzoF24NGPovvwUq7lGriy6ziy/iZ3L7foim+nAbbC0TmfAUCAd0611aJr7ai+MrLy9M/p/jO0snqCDB58mQOP/xwAoEAjz76aMLtM4ovc7DjApCZ7wVaXZmfnw9EF20ke0VH0MZQYiIhk++VGBniy4MYOXIkhYWF1NTU8MMPPyQt2F5AyCS3b9/eagAkk2RwkvElo3NXFCWh0mnHjh2EQiFycnKkBroLiI6urq4uqnUiWctTi+sQCoVikk9i5sqN6yA6tIzV0bvo3LlzWA6PV62O6ZDvBZriIT8/n2AwyObNm2Nul8xBsyjWYilEkrGiI7RdxVd7I77i5XwFg0EWL14MpA/xBda/S1VV0474KigocH3SIBrxJYLtBwwY4OjYYpJStKubN2+mqamJ/Pz8VkHQ6YT2oPiC1jlf6ab4ghbV12OPPUZ9fX3cbTOKL3Ow04+uXr0akEd8QfyA+1TVGkcddRT5+fmcfvrpSX3fdESG+PIg/H6/rrpatGhR0hVfxcXF+qxYZM5XW7I6QuKAezFjOGDAAFdspkYVRzTyLVlqJmOhG4sEdEvxBS0WEjtB5hnFV/JgDM1MJvFlJUhakKdeJ758Pp+u+ooXcJ8K4ssriq+2Qnw5UbClM/EVT/G1Zs0aqqurKSgokDoocRtWB18NDQ26ojNdiK9ktJ1uKr4E8SXqN2FzHD58uOdXBYyH9qD4gtbEV7opvgBOO+00BgwYwN69e3n55ZfjbpvsMV66wonia9SoUdLOw4vE18MPP8yePXv0xekyiI307QHaOIwB98lWfEHsnK+2ZHUE88SXGzZH0Aa/4hyi2R2TReooipIw4F4ovtwkvqwqvmpra/VBRYb4ch9G4itZGV+qqlJXV2d6v3RRfIG5nK9UEF81NTVRr3myFF+ZcPsWpDPxFU/xJfK9Jk6cmFaZJFYHX8aJpGS3SUbiy8zkQSqIr2gZX7KJr3QPthdor4qvdAq3F8jKyuLyyy8HtJD7eM9fKsZ46Qg7alvZVkeIT3yJezXZtYbP5/N0pq2XkCG+PApjwH0q/N/Rcr5kq2vsKL6E6kjWrFYissdt4gvi53wlU82UyPYprr0bVke7xJe4d7KzszONfhJgzA9wm/wwDvStEAbpRHwJxVc84kt89mSs6NuhQwc9VDqa6itZg6uM1VFDMBjULfDpSHzFU3ylW7C9gNXvUtzDxcXFSVcbiTY6EAiYIuqS2XYKy2FVVZVO7rqV8SWILzHRkK4QxFc0IrktKb6GDh0KpLfVEeCiiy6isLCQFStW8Mknn8TcLmN1NAerLoCdO3dSVVUVpq6XAS8qvjIwjwzx5VEI4mvp0qV6o58K4stodaytraWxsRGQQ8RYVXxt376dOXPmANry5zKQasUXxCe+ZFpLEyERCeim1dFunpORGHQ7+DsD7bsXknExY+8WfD6frfsinYgvrym+FEWJa3fMKL7swS7xZVTdpSPxZUbx1V6Ir1QMagsKCvSVYM2s7JhMm3hxcbF+Twu7oxuKr1Ao1CZWdIT2Z3XcsGEDkJ5WR9Bq+1/+8pcA3HfffTG3y4Tbm4Noe4PBYMLcNGixOQ4ZMoTc3Fxp5yGesWgW8lTXGhkkRob48iiGDh1Kx44dqa+v5+uvvwZSY3Vcv369PhshSIasrCwphZHVcPsbb7yRuro6pk6dynHHHef4/cH7xJeXFF9etDpm8r2Sj6eeeoq//vWvHHnkka6/V4b4Sv6KcPGIr3RUfKmqmvJi1C7xJZQwgE5gpBMEgbFt27awGfrGxkaWLVsGtB/iK9n5XgJWcr6S2XYqihKW89XU1KTbHp0SX3379sXn89HY2MiuXbvanNVx//79re6/tmh13LZtGw0NDWmr+AK44oorUBSFd955R78PI5FRfJmD0dVhpiZ0w+YI5hRf6XivthdkiC+Pwufz6aqv+fPnA8mdDejatau+ss7SpUsB+eoaQVZUVFQQDAbjbrto0SL++c9/AnDvvfdKU/ckIr7EqkBCOu8GvEJ8iU43Ha2ObWGWM11w+OGHc9NNNyUll6e9EF+bN2/W1bSRSPbAWcyqe0HxVVVVZWlhg2ioqqrSr22qilFBltTU1CTs64wQxFd+fn5ahnILq2N1dXVYH/v999/T0NBAp06ddFtTusBqm5QhvmLDSHyVlJQQCoXIzs52XGNkZ2frJNGaNWv01SLT3epYXFys30eRqq+2VAv16NGDgoICVFVl+fLlNDU1Aemn+ALtnjvxxBMBeOCBB1r9vbGxUVf2ZhRf8eH3+3WVqJmJB7eIL9GmZqyO6Yn0q6TaEQTxJRr9ZM8GROZ8ybbdGY8Ti2wBbcb+6quvBuDcc8/Vr4sMxFM5hUIhvWBKheKrvr5el/MmU/EVjQSsr6/Xz89Nq2NG8ZWBEeK+aKsZX71796agoIBQKKST7JFIZsYXtJBD0axRyV7V0aylIR5EIVpUVJQyu6Dxu7NC4qZzsD1o5y0G4sacL2FznDRpUtpZ1DOKL3kQOV8lJSX6/SHUWk4hJis//vhjQKuz0pE4iUQ0u2MwGNTrs7ag+FIURVd9ffvtt4B2T6aj6hXgqquuAuC5555r5XAxjj1S1UakE6y0v8lWfNXW1upjmAzx5V1kiC8PI5LgSfZsQGTOl8wVHQFycnJ0pU88u+OcOXP48ssvyc/P57bbbpPy3gLxyJ5du3bR2NiIz+fTiw03EIv4EtdEUZSkdIjxFF9i8Jidne0KySTuAycZXxm0PYgip60qvhRFSRhw7yWrY7IUX0ZLg1O7oxdmYPPy8vD7/YA1EjfdiS9oUX0Zc77SNd8LMsSXTBgVX7LyvQTEZOVHH30EaDbHdCNZoyEa8VVRUaErY9tKLSSIrwULFgDpbR078sgjGTt2LLW1tTz55JNhfxN1f3Fxsd5HZBAbVhS3ySa+RM2Um5ubtInKDKwjQ3x5GKkmvkTOl1B8uUEyJFrZsaGhgeuvvx6A6667Ti+iZSEe8SXyvfr27auvdOYGEhFfnTt3TorNJV64vTHY3o3iMWN1zCAa2rrVERLnfHmF+AoGg3qb5LaqwOfz2c7FioQgvtxQqpqFoii2Po8gvtJ5xVpjzpdAOhNf6WZ1FCR1eyW+xL2W7jZHgWjEl/hujavypjsiFV/prNZTFEVXfT300EMEAgH9b5l8L2sw24/W1NTojp1kEV/GSba2QLK3VWSILw9j4MCBYQOMVFkdV69eTW1trSsrDCZa2fGhhx5i48aN9O7dm+uuu07a+wrEI3uSEWxvPIdIpVWy1UzxbJ9uBttDxuqYQXQ4Ib7ShSxIF+KroqKCUCgEJMdOIyvg3guKL7C3UmVbUnwJYqO2tpaVK1cC6Ul8paviy8yqjm2R+BJtVroH2wtEI77a4gSgIL5EIHw6K74Azj77bHr06BG2Oj1kVnS0CrM14Zo1awDtvpFdr5ghvjLwLjLEl4ehKEpYYZjshrF379707NmTUCjE8uXLpVsdIb7ia8+ePdx6660A3Hbbba4UY2YUX24TX2YUX8mAGcWXG8H2YN/q6AYZm4F30NYzvqCF+Fq/fn3Uv6cq4yuS+Eq2qsAOURQNXilG7Si+xERAOhNfgsgQVselS5cSDAbp2bOnqxECbiFdia/2pviKXJCoLRNfbWlFRwFBfAmks+ILNLv77NmzAbj//vv11zOKL2sw2/66ZXOEcOLLuPhOZkXH9ECG+PI4jHbHZDeMiqKE5Xy5QcTEU3zdcsstVFVVMWHCBM477zxp72lEPOJLhE2nivhKNqkTT/FltDq6AbtWRzfI2Ay8g7ae8QXpo/hKVr6XQFtTfDmxOqYz8RWp+DLaHNPRDtIeiK9kqWWN4fbCliRWE3eKyLqtLVsd27LiS6AtkAmzZ88mJyeH+fPnM3/+fCCj+LIKs4qvZBBfgUAg7Dy8UmtkEB8Z4svjSCXxBeE5X24QMeJYkcTXqlWreOKJJwC49957Xcu4MqP4ipw5lA2vKb7iWR3dVnxlrI4ZGNEeMr5EuP2WLVtobGxs9fdkD5wFsRVL8ZUsVUG8ttkKvFKMtlfiK1Lxlc75XpB+GV/poPjat28fGzZsAOQpviIJtLZMfLVFxVdk3d0WiK+ePXvy85//HGhRfWUUX9bgBcVXQUEBOTk5QLhbySu1RgbxkSG+PI7DDjuMnJwcevfuTW5ubtLfXyi+lixZklSr47XXXkswGOTUU09lxowZ0t4vEvFUTu3N6phohUvwXsZXxurYttEeiK9evXpRVFREKBRi48aNrf6eKsVXRUVFWAhvshVfGatj2yC+jIovVVXTnvhqD4qvZLWdnTt31utaUYPJIr7y8vL0eqVXr14pu/6yIYivnTt30tTUBLRNxVd+fr6uCIT0tzoKXHnllQD897//Zdu2bRniyyK8oPhSFEVvV41jVzFZmOpaI4P4yBBfHkfPnj2ZN28ec+fOTcn7C+JrxYoVOvnhttXxgw8+4L333iM7O5s777xT2ntFg5HsMXq1VVVtd8SXGcWX21ZHqxlfGatj20Z7IL4URdFVX5F2x0AgQH19PZC8jK8uXbroFjTjYFn8nrE62kN7J75qamrYsmWLHladIb6SAy+v6qgoSpiKPD8/X2pfLlRDbSXfC7R2zO/3EwqF9LqsLSq+INzu2BYUXwDjx49nxowZBINBHn744YzV0SLMtL/BYFDvZ9wgviB6wL1Xao0M4iNDfKUBJk+ezOjRo1Py3oMGDaJTp04EAgGWL18OuGN1FI1HU1MTv/3tbwG47LLLXJenC7JHVdUwtVF5ebleBMrKnIgF0eHV1taGWZ3aY7i9FcVXKBTSi4aM4qttoj2E20PsgHvj504W8eX3+/UBlNHuKBRfybY6tjXFlxUiry0QXwUFBfog4c033wS0uiJdFRzpanWsrq6moaEh7rapaDuF3RE0tZfM3DcxadlWbI6gtc/imgm7Y1tUfEHbJL4Arr76agD+8Y9/UFJSAmQUX2ZhpibcsmULDQ0N5ObmuiZcyBBf6YsM8ZVBXCiKoud8iWWh3bA6CpLn6aefZuXKlXTp0oU//vGP0t4nFvLz8/H7/UD4gESovXr06EF+fr6r52AsiI1qq2SrmcR51NbWhlmcwJtWx6qqKv2ezBBfbRPtIdweYgfcizYpPz8/KSspCkQLuE9HxVdTU5N+3qkuRtur4gta7Guvv/46EJ5dmm4Q32NjY2PUTL5IpJr46tixo56Rmkj1lYq202hnk2VzFJg+fToAM2fOlHrcVEOoKAXx1R4UX+lKlEfDj3/8Y4YOHUpFRQVvvPEGkFF8mYWZmlDYHEeMGKGP72QjHvHVlkjatogM8ZVBQgi7o4BbVseqqiqd7LrllluSQmYoihI12ypZNkfQZvDEORjtjqnK+ILwwVl9fb1OyCXD6mi0nMaDuD75+fnk5eW5cl4ZpBZW1RWBQEBXNaQT8RXL6piqQXM04itVii8nxFdZWRmqqoZlcqQK7Zn4EgP1efPmAelrc4TwdsXMd5lq4svn8+l1lheJL6PiS7a6/pJLLqGsrEwPFG8riAy4zyi+0gt+v1/P+hI5bRnFlzmY6UfdzPcSiCS+VFXNKL7SBBniK4OEcJP4Mlodb7/9dvbs2cPIkSO5+OKLpb1HIkQbYG3evBlIDvEF0XO+kk18ZWdn6+o2o/JMqL1ycnJcm5USxFcwGDQ1iw6ZFR3bA6wSX0bFYDoRX7EUX6K4S5bNUSAe8ZVO4faiEO3WrZtrM79mYefztBXiSyh5hEI3nYmvrKwsvZ9M9F02NjbqGX2pDFc3E3CfqkmDSKujbLQ1MgjaH/GVlZXV5oihCy64IKxNyCi+zMFMTSiIr1GjRrl2HpHEV2Vlpe6UaUskbVtEhvjKICGMxFdeXp5U659oPHbt2sV9990HwN13351UW0+0lR2F4itySWW3EI34SsWKhdEC7o3B9jLzN4wQxBeYtzu21WIvgxZYzfgS905WVpa+3HQ6QBBfW7du1QfKkDq1iCC3olkdk6WckmF19NIMbEbxpUFRFA4++OAUno1zmCXkU5HRFw1miK9UTRq4TXy1RUQSX23V6jhu3Dj69+/P0Ucf7VrtmSoUFxfz61//Wv9/WyP23IKZfnT16tVAchVfolYqLi52PR4nA2fIEF8ZJMTw4cP1wls2CSOOJ2YbZ82axY9//GOp75EIqbY6gjcUXxD9WrgdbA+a2kwQFWaJr4ziq+3DasaX0aqTToVyjx49KC4uRlVVNm3apL+eaqujUHkZf09HxVeG+EotjITGyJEjU6p+kgGz36V4fgsKCsjKynL9vGLBzMqOou009sXJgJsZX20VRuIrEAjo91lbmwQsKipi48aNvPPOO6k+FVdw2WWX6fl7bSnDzE1YUXwlg/gSbaqXao0M4iNDfGWQEH6/n/HjxwPySQbjLIeiKNx7771JH7B6kfiqq6vTbQepVny5HWwvYMz5MoMM8dX2YVz0QNik4iEdg+1Ba/ui5XylmvgSs5ihUEif2cwovuzBCfFlVMSmI4yKr3QOthewSnylmugzo/hKVduZUXxZh5H4EnUQtM1aKCsrK60msaxg0KBBPP300/z5z39uUyuPuolEbe/evXv1SboRI0a4dh6iTRV1USbYPn1gifi6/fbbOeSQQyguLqZHjx6ceuqprFmzJu4+n332GYqitPonGNkM0gPC7ih7Rsnv9+ukz69+9SvGjh0r9fhmIMgeLxFfopjx+XxJtUhEuxZGq6ObEIO7jNUxAwExCFNVlbq6uoTbpyvxBdFzvryS8VVZWUkwGASSH26fUXy1LcVXOud7CZi1OnqN+DIqOCORqrZTkDiKomSIL5MwEl+CzOzUqVPKcwwzsI4LLriAP/3pT6k+jbRBorZXcBIDBgxwdcIo0uropVojg/iwRHx9/vnnXHrppcyfP5+PPvqIpqYmjjnmGFMD1TVr1lBaWqr/y7Db6YUjjjgCcCfz6qyzzmLMmDHceuut0o9tBpGKr5qaGr2YSDXx1alTJ10KnQxEyztLhtURwtU9ZpBRfLV9FBQU6LO9ZpSAbY348oriS7SHRUVF5ObmJuUcMoqvlrYw3Ykvo+KrLRBfZr9L0Y96hfjyouKrW7du/PWvf+Wuu+5KaQ5aOkEQXzU1Nbo1vq3le2WQQTSINqK+vl5fEdOIZNgcIUN8pTMshQ68//77Yf9/9tln6dGjB4sXL2batGlx9+3Ro0dm1Yo0xplnnkl2djZTp06VfuzHH39c+jGtIJL4Emqvjh07Ji1wMhbxlWxSJ5riK2N1zCBVUBSFoqIi9u/fz/79+xPegxniSw4iia9k53tBuOJLVVVbdhcvFaNGIs/s52kriq/8/HzOOusstm3blvbB9pCxOsrGTTfdlPT3TGcUFBTQqVMnKioqWL58OZBRvmfQPmBsn/bv39+q/k8F8aWqql4reaHWyCA+HElJxGyWmQZ3woQJ9O7dm1mzZvHpp5/G3bahoYGqqqqwfxmkFn6/nzPOOKNNPtSRxNfmzZuB5K3oCLGJr2QXM9EUX8Lq6LbiK2N1zCAazNqKjNukM/G1fv16/bVUE19lZWWEQqGUrBomPnMoFNIJIKsQpL0X+i1BljQ1Nen5jYnQVogvgFdffZWvvvoqrVZbjQWrxFeqV2zzOvGVgXUI1deKFSuAjOIrg/aB3NxcsrOzgeg1YbKJr4aGBurq6jw1yZZBfNgmvlRV5ZprruFHP/oRBx54YMztevfuzT/+8Q9ee+015syZw8iRI5k1axZffPFFzH1uv/12XW3TsWPHjO8/A1cRSfYkO98LvKf4SmW4fcbq2E4RCsKuz2DzK9rPkJYplVTiK8Y5JAMi3H7btm3U19cDqcv4EoOoYDBIeXl5ShRfBQUFus3b7uSXl4rRyJlqM2hLxFdbQrplfFlZ1dHTxFcK22evQRBfGcVXBu0N8SYeBPE1atQoV8+hqKhIX6l337598muNTFvnGmyvr3zZZZexfPlyvvzyy7jbjRw5kpEjR+r/nzJlCtu2bePuu++OaY+84YYbuOaaa/T/V1VVZcivDKwjFIQ986CuFPJ7Q/ep4Gsd/hnL6pgK4ksQTqkidaKtcJmscPtMxlc7xrY5sPhKqN3e8lpBPzj4geQRX3HOgf6nWz+eRXTv3p0OHTpQVVXFhg0bGDNmTMoGzrm5ufq57N27NyWKL0VRKC4uprKykv3794et/mYWXiK+srKyKCgooLa2lv379ydc/UlV1ejEl8l+LQP3kLE6pgBut89p9lyJ3Dwx0E/YNqfZ58sgg1goKipi3759rWrChoYGNm7cCLiv+FIUhS5durB79+4w4kvKqo4prkXbOmwRX5dffjlvvfUWX3zxRVhoqVkcdthhvPjiizH/npubm7QA3QzaKCw0HJG5VqkgvsQ5CMWXsPGlWvFVV1enF/fJsjqazfhKmtUxUzC6i21zYN5PADX89dodMO8nnHDQAXz3nTmVjLh3wlbzMfP9JTgHpv7X9YJDURSGDx/O4sWLWbduXUqJL9AKuKqqKvbs2ZMSxRegE192FF81NTU6ie4F4gu0zyOIr0RoaGhAVbX7USe+MgWxJ5CuxNe+ffsIBoNRV//zNPHldvuchs+VUHyJgO+4dVAafr4MMoiFWO3vunXrCIVCdOzY0fWJekAnvsrKyuRNsnmgFm3rsGR1VFWVyy67jDlz5vDJJ58wePBgW2/63Xff2Zq9zSADUxANh7GTh5aGY9ucsJe9pPjyitVRXAthcxQKEDfhSavjtjnw1iD4+Ej4+ufaz7cGtbqHMrCJUFAryEUnvwbQeU/ttSt/tAmfYlPxZeb7M55DENgKLAdCLefA4quSIjWPzPlKNfEFWsB9KhRfEF2BahYibDY3N9czq8VZWdnRmGuWn59vuV8DMnYJl5BuVkdBiqiqqtcYkZBKfMm87yL7iDBIaJ/tPFcegCC+BGK2zWn6+TLIIBZitb/GfC87i+FYhXjmjJODjoivyLZuO7BT/DG5tWhbhiXF16WXXsrLL7/Mm2++SXFxsW6B6tixo1aYodkUd+zYwQsvvADA/fffz6BBgxgzZgyNjY28+OKLvPbaa7z22muSP0oGGWCiSFK0hqPvKbrqwzLx5YICyCvEV2TemdHm6HZHYsXq2NTUpH9fnTt3dkeVlZl5cR975rUU5KuBvwIHA7rTXaV7YT1TD7BBfCX6/ia/CCV++PhZ+Ho7bEIjvQLN250BnK6dA7XbtHPtOcPBh02MyJUdU5XxBeHEV6oUX8aVHa3COAObjCLYDOwQX9nZ2WT7fa37tebuLFa/llF5uId0U3zl5ORQXFzM/v37KSsri0qSSCO+ZN93xj4CYAOwFjiW5ql7B+2zjXrRK4gkvqIqviI/n5jQGQco3v58nkJG9e8pxGp/kxVsLyCeufXr1+vqbEc10p55ULMdlgH/Q6uJc4G7gK6QzFq0LcMS8fXYY48BMGPGjLDXn332WS644AIASktL2bp1q/63xsZGrr32Wnbs2EF+fj5jxozhnXfe4YQTTnB25hlkEA3GImk38ChwIjBJbNC64TASXw0NDZSWlgIxiC+XBhOC+KqpqSEQCKRc8SWIL6H4kmZzjFNAWLE6Gmetu9R8Bl9dI/c7SeOCOK1QV9ryu1jMsLT1Zr07WSO+iosKwr+/ELAFjdzarGo/t53TQnIZkQM0Ah8AJwB5Uc7VJYiAe0F8tXfFlyhw7Si+vJTvJWCH+CooKGg9+H8AWAoMBIYAQ1UYug12fQ69Z2ZIe5eRbsQXaM+uIL6iQQrx5cZ9F9nuPgHsAAYAY+JsZwbG56oReBU4BNBzsb070DSl+DJ+vh3AnWhfzVDgbGCUdz+fZ5CZQPAczCi+kgFBfBlz9kTgfVTEI1DrquGRP8OzaEovgQbgLeCXhteSUIu2ZVgivgSjGQ/PPfdc2P+vv/56rr/+eksnlUEGtmFsED4A1gEfYiC+Wm9nJL62bduGqqrk5+e3Dil0cTBhLIwrKytTrvgSBbvUYPsEBYQVq6O4Pj+fmof/67OQ/p0YC0YV+BwY1PxPvJgpGJ0j32B5F7dFFI6jtAIGW8j4GlpcEn6fPQ58FWWHAmBYEfSvhsFo/7oD1wG70L73Y6Ocq0swKr5UVfUM8ZXuii+vwDbxZezXQsCi5p/rmv8J/GkWHNAVBu6HwapGinUyHjVD2stAOhJf3bp1Y/Pmze4RX8bJohDwBTAM6AeO7jtju1uLRuAAlBBOfNlpn43P1UK0mnEBcD/hoyMPDjRNKb6M5/0NLWXSBjR19XjgLDz5+TyBzASCJ+E1xZd437i1Rqzxz+A/wD/fgmffh30h7fU84Ei0evRR4DPgJECUX0moRdsyLGV8ZZCB52FsEJY1/yyJv50oSoPBIKtXrwY0tVeYPcblnImsrCy9Ma+oqPCE4ktVVXmKLxM5E1aJL58Cd/0sgH79g4DeDzr8ToyF4GLgyeZ/8bbLwDq6T4X8PtrvYkBTQ3O+FoBCRaAD836wpvjqnFcf/ocfmn8OR1OAXg7cC6x4Eb6rgIv6wRQFegF+NKUXwHto91VBf+1cXYYgvrZv364HUUNqBs6C5MoovuTByucJI74iB//i+bgYOA7tvs5Ge3YWl8GcRrgHuBS4Aq14NmbnCdI+A1tIt4wvSLyyo2PiyzhZ9Blaf/kP4wY277vuU7UBIgpsNry+S/yi2G+fjc+V6MrLgW/jbOcRdOvWjezsbP3/UYkvcd4qML/5tXOAo9D6uaXAjcCvfwsrv2zZL5MN6H62XAa2IdooI/GlqmrKia+YKzpGG/+UAU9th8Muhnve1Uivzj74eR48CPwCOAIYDTQBb4Kjti4DHRniK4O2BVEk7SK8kNFzgls3HIWFhfh82qOwfPlyIIrNMdJqshB4G8MA3flgwpjzJYgv11csjICRBKyrq9OJL0eKL5MFRHGRtnKZGeJr3759TD0A+nQyFB0vog30dAWEg+/EWOguaP65k9YfwYMFcVrB54fOE7XnSBDUKs0EpkY8f1JxEiHVGvGlFPRpeVGlRUV2CZrF4zCgJ1DYVzuHgx9o3qCZ7J4GFAN70L7/g+9Pijqma9euejuwdOlS7YwUJXyVSqcwOajJKL7kw47iq7CwMHzwL3bNB6YC5wK3KPBiX/j4BbjucJiOprRR0Arsr4DIZjBD2tuGY8VXCogFQXyJZzkSjokvcT+pwPvNr21GsxBG284sjO3zJsPruw2/222f9ecKA5GGdv4qeHmg6fP56NOnpZ+LOikhPt8WtHo4B5iJZpu6EzgU7XPOLYXxU+Gcg2HhQ5kFfSC85q8DXqNlcg7ITCCkDqL9NdaEO3bsoKamhqysLIYOHZqU8xDjM9EPRK01ogXWPw5cDbwD1AN9gdsvgO3lcMdLUKig16JnNB/nc2CPmrRatC0jQ3xl0LYgiqRlEa+Xgt6QRDQciqLohemKFSuAKMRXpNXkcbQ8iM+IvZ1FiAFveXl5yhRfRUVFOglYWVkpx+oYWUDcglZE6NAKiAF52qICZgiO8vJyeneKeHE1mjrn04jX7Xwn3adCfj9tpuW75tfqiUugZmAD+zfAzg9gL1qWgf46WsE+9b+U+A8DrBFfjZ0ObSEK6mnJ8tLHnxHfX//TNdtCQbN9JAc4unnT93Kg76n2Pp9FKIqiq74WL14MaEWetHB2C6uUCuJr48aNNDU1ARnFl1PYtjoaB//iUujrHTTfG1MehJnnwm//Bv8H/B1NdXN882ZrIt4gQ9rbhiPiK0UrBbuu+BL30/e0EARBNNIl2nZWINrnTYYBnyC+Bl9g327m88MB12m/G4mvjWgB+uDpgaawO/p8Pl2tHwbRbnzT/P8JtGRW9lLgCgVevQzGd9JqnZeXwPQr4JXtWr8p0B5XgDTWja8Cc4DbgYo423kJbVi1F639FaqrYcOGhSkh3USkMCFqrWEc/5QAf0SbhAoCBwDXAncAvzwfCjq0rkUPQLN0B4EP+2astRKQIb4yaHvofzqsiphhLQHy+8b05CckvozFWhktRcG/MNjrcDSYEMRXaWkpDQ0aC5Bs4stIAlZVVcmxOhoLg+/RFFmftN6sY4420DNrdSytiHyx+edCtCJOwM534vND/1NgJQayC+27F/BwQZw2WHYjhAJQMyH89V6XwsmboP/ppm1Fxm2Kiju2EAXi+cxBWyEnBgFO/9Ph5M0w61M4/GX40wvaPhsa4fX77H0+GxAB94L4kmaTsrisvSC+Nm3SZBYFBQX66s3JQmTmoBUI4ktKPqEkWFGwhRFf0FIQ1zczXoL4aiaI9X7NqA7LpyXfch2eV7G4DkmDQdEmNTQ0EAhEWyFDU02Lvkx/hi0+gzKRiPgS52qb+Oo+FbI7tai9BDaIXxzed/1Ph02GCYC92dr9XPoONCWuGWJizxfaT0GkDWn++R4w9CJPDzQF8dW5c2d9wrL1RqfC/Oa/TTG8LtqNsx7S7NEv/kVbLKMO+DfwWzSViQppYe2TTfSIurGElnq1HM2G5rS+dBspIteThWg1YbJtjmCS+IrMEWxEW5jjL2gk2AQ0Jsa4XWQtetNV2usf7IDvv5D3AdopMsRXBm0P+/fB0uaB0iRNPUEJMPnxmEWMKEzXrNGmxVsRX8bBhFHuXI02GyRhMCGILzHQ9Pv9+sxGMiGuRWVlpRyro7EwELO/lYQXD4CvUCvizFod5/0A++oLAUXrTEQfWItGsIH976RuF2x+Weuowt64+WfvYz1dEKcF9n4LW/8NKNA0PfxvNbk6KWVFJROmWhBEQV0zeVysvVUrosAIn19brGDQ2TDuXDj5QO31O++w/vlsQii+lixZAkgivoxy+wCa9U0f/0Yf1AjiKxTS/NzJtjlC+7Y6inZQJ75Au2c7nab93qWDVhg3E8Q6Iq27Q9CCuitoGdy3R9Je4mDQ2C/HIuSN33FxcXH4M6ii1STGqARwlVhwXfFVXwrbarXcKAXNhguaeirWZIMV7NoEO5uLBkWBugA0DYD63bD2UXvHLFsI217Tagbxdd11i/ZzEbDoX1Af3RrqBQjiK24kxvtPwd6QRoJf9qY2kI5sN3w+OGqqFnh/CdoCLxVoGW3bxIE8bO1zg+gRNf+/0J7TEWjXcA1arIZXJxBSSK4nC/EUX8kkviIV8FFrDeP4Z0Xzz5loK6vG2g7Ca9Gz74ODu2iqrxt/7eykM8gQXxm0Qbz1qDa46+qHcy7RXisBSiOnIltgzLaCKMSXcTAhiC/RTn0GrHPuvY4kvjp16iTP4mQBxoB7KVZHY46GIL5UDJJxrYAIdj0cMG91DKnwv9Kjml+I2ECE047+vb3vZMlVUF8OS5qXdurcTD7kNxeKpR/Anq+tHzcDDaoK312r/T7kfNgU8QXublmRwqziS1XV1qqF/qdD7+Y2oFNOdKIgHv7wgDZmW7AXvnot4eYyIIiv9evXA8ghv4XcvgrNrvEoCYOnI4Nak21zhIzVESKIL4A9zexV9+5aYRytfTPaJXLQVocCzb414a72R9pLHgxmZ2eTm5sLxP4uxT2bm5urbWu0vHyKtnLsu8Y93CUWBHHtCvGlqrDwUni/OdDr4Dw4vPlvG4g/2WAWn/9H+9krC/r3137PP1f7ufrvELBOjrP0Bu1n1onaz+7d4fSb4aijtBrlnSpYdoP9c3YZgviK2za/0EwKTh8CQ0/WBtLR2o26Um1EeARwF5r6C1qyco3beQluET0+P1QeqxGgCnARGikI8BHwuQfzlozkejmaUk3vOtNAtWcS0WpCsTCZ5xRfYvxTT4t9+iDjBiYJ1L/crv18Zy2s+MzW+WagIUN8ZdD28HZzgfSj4TB6tPZ7CbDjHa1Ai4JIVcWgQYNab9T/dBh9gxZOCFphJ9qq54BAZIqrNUQSX8m2OQqIa1FaWqp3LI6sjkbS0Jj3UQ7GmeDCIu19zVodAXb4DtUK6urmfAvRoi1GU5Rtfsl6J7/jXdjyKqxVoLIJOneGM3+m/a3pABhyAaDCgl9DsCHekeSiLWU2bH8T9nwJ/nwYeyusXKm93qk5gGR3S+CKWeKrrq4Otfn5Dhu87Wxmqrt2jE0UxMK4mTCjmbT92/Xm93MAQXwJSFF81ZVq7dafaMl6WklrwtgwqCksLAyzNqaT4isUCrFnzx6gLRJf2ueiS6f4BzDaJWb8WHttLVD1Q7y92h4iw4VVDIuU2B8MRltZzIhW+V5GwmB988/lUXZ0iViIp/gKhULOrI7bXoO1b4Fw4dz+Fpzzovb7TmDyXOdk6zfNfrPRvUGEV9cOheLh0FAGax+2drydc2HXx+DLhqzmIDxx3Kuv1n5+Bnz/lKZO9iDGjx8PwKhRo6JvEGiED5plJmefF/9gRsVJNtriGBC+iEDkdqlG5LO9D9gq/uiQ6AmF4I5Xtd9nZmkB5BNpCRt/Blhdaeu0XcOeebB3u2ZVvQZ4mmZ1moCHVXsW4BXFVyTxFXVVRzH++QFNsdUNbWElwJIS9oT/g8ndNPXhDf/n5LTbPTLEV3tFWxpER+ILjfnnxFNBFAS7gMpNUBWZ8KvBOLjMysqid+8YnXv9zhbF18wr4dE5UJSrrV70t19Czdbo+5mAV4gvofhat05bHjEvL8+56qTDaM1KYKy59xE2EyxWrqutrdUJjFjYt0/zHHbp0kUrqDuco/1hVD706AI1wOp82Ps1rL7T/HkGqmHhbO33deO1n6ecAoObJRPbtsGEuyG3O1SuglV/N39sJ2hLmQ2hACz9nfb7AVdDXh9onq1j0iDtp2HlMbPEl/HvYWTBbk21SFeb9/ANf9V+frgR1kV6X+XDFeLrw7naohJ7gB5ogxrjEvcCEYMaI9mVToqviooKPZA/5hLjViGhz5RCfO2r0H6aISKFXeKEi7T/r0WbDGisMHW+bQJGpVUVcCXwBOHkl43BYLSVxYxoRXwZn61m7pKNGOyOtN5OIuKt6hhz0sAMGsth0eUaSdQAHHggzDoKDjoHejeHTH8uQS37XXN+wcSxLQTV5i1w4M3a76vvgkaTRISqtqi9hs2GHc3PozjuccfByJFa3tXnwKJLPVkjz5o1i8WLF/PwwzFIv7cehoqQtkrcmb+NfzBjnAdo/QQYiC8PWvsiV1u/C7iBlgWJnBA9T1wLP9RouaD/WNCSt/TgR3BEL21i9eyLYPP3iY6UHNRVwx3Xa4TXm7SsprqC1quRe021ZxGRNWFVVRUlJZpLYOTIkUk7jw4dOuD3txBWMSfZ+p8O65rrkAPRHzHLSthbm8cy762DpR/bOucMMsRX+0RbGkRH4ruPoDQAfuD0y6FvXygs1Jj23UDJO1F3M66I079//7DGTEeoSVOqCOJrxv/BgafB7c2N0av18M5PbRdIgvjasUN7g1Qrvtau1XS5vXr1cm65XPdo69Wd/D8Ks52JzkxVVerq6uIertWql9ubD96nB/z059rvaydqP1fcDOVLzZ3n8j9A7VbIHwhfNld8p5/eYq3Ytg1yu7Yo2Fb+DSpXmzu2XXgps0EGYb7hKdi/ViMPR/8Otm6FmhrIzoaJI7Rt9lbomydSVgiIIqiwsDA86FcoZLrafJ6OPh/GdtTakFsvSbi5U3Tp0iXs2XdMfN38U5j9jDaIG4kWqtrsEEZ360Yf1BhJo1QqvqwSX8Lm2KlTJ3JycpyfiKQ+Uw7x1bxvDwsq3MObfWfbgco62Pic+X1jIV0mz4yDvJVoky/zaJ3faHEwmOi7bEV8GYkFQXzVoSmiBJwSC3G+E6PiK3JiSbSdiqJYX8Diu99BzU74qDkW4KqrtAwugAP7aD+/ljBIW9V8oabMaiGoNmyAgT+DDqM0Am7NA7H3N2LbHNi3CLIK4cCbtONAy3F9PrjySu33D32wd7HWb3kMiqIwceLE1m2EwItPaj9njYD8BIRmZDagaPqNii+vWfuMz2yAljyyx2nJY43cztRxq+EvD2m//3I6DJnQkrfU5yh4cyH0zYF9ITj5R9BQG/dwUhDr2Q42wUNXwJDOcP9CbYK5N3AFGmlXRYtLRcBLqj0biGx7RTZzr1699HFUMqAoSlitFpP4ClTD4uYJh9NnR8/ZM4NjfgmHdtcmS27MqL7sIkN8tTd4aRDtBv77mPZzbGfo0kcrYMQMQAkxiS/j4LJVvpfAni+htEzzamdlQfPqa8y+FMaN1gJSH/4WVtkLwhYNtgiTjhtY6iIECSiIL8erogX2awOtSOJrb31YEWUs3hKpe1oRXzuaM6F694Azz9R+//h76HGypjD6+lwI1kc5kvF8FsCaB7Xfc66B7TugqAiOPjqc+AKt2O59PIQaYcH/gRo5bS8JkVL+MCQ5s0HG4D+wH1bcov1+0M2Q3QFWrdL+P3Ik9G72V5S3fP+iyKmpqdGfjWiImVGzt9nP58Ty9turtJ//XQR77Ks6zcKo+rKttmysh7PGwl/+oxVKR/fUZsOLFTgUrfffSEuGS5RBjZH4SoXiy67VUWq+l8Q+04qCLSbxVd5sBe/Rx/T70qMHjGgmldehTUQ4abPSafLMOMgrMbz+AhrxFG07E7BMfAliIaiGD8o3GH4fcJZ9YiHBdyKe38bGxlZxAsZJA0uTXLs+hw1PatECe5o0FeLPf97y90nNk09LHKpitq2GPc193LSfwJDmpRc3bNCu10G3aP//4V6NAIuHUJM2wQVwwDWQ1wOa8xR14gvgvPO0mINdIViClvXl4aD7VmiohbnNDodf/MrcPsZsQNF07gH8Bc4z2txA5GrrokyqRsuxDEXZzgz+er62kEInH9z2auu/d+0Hr7+uhd2vqITzp7TeRiZiPdtPng+jOsIVD7Wc7/8VwN/R+nghflopDiRBteeBCY/IydBU2BwFxDgtKysrNum27F+wTdWUXmf/JXbOnhncepf28/2NsOQDO6fc7pEhvtoTvDSIdgsfNYdMzDqi5TXRGJYCu+dFlcObIr62zWlRew0fDkJJ4PfD409rv88D/vMnW5kQkY2mV6yOjomvzS9C034oaR7Ad9YsjZTuCdvM5/Pps82Jcr7CrI4AO5uP1bcvHHEE9O4NlZWw/yzI6wmV38PyP8Y+YCgACy4CVBj0C5jXPEL68Y8hLw8GDND+v327ZpNQFJj8mDZjvOdLWP+kqUthGULKX42W23AjECYwS1Jmg6zB/6o7tVW4iofDsOYZK5HvNXo09BLEV8uI1EhkCTIgGmISX/uaSQYrCplInPMHGJCrDZTvuNj+cUzCSHwlVHxFK0T3bIUf9YN/N+e7XH0cvF8CM1/TBjUdaAlY/TY35qAm1YovI7kQj/SMhDTiS3KfKUXxVdmcK9izv6n31HFEc5+4Pgf2r4OdNlU46TR5pqpQYkiQNxJf5cB/m3/P62l5MJjIgt2K+ALtGRtwm6YeFdiA1o8ArH0Qdn1q6TwAU99JYWGhrn6MzPmyFWwfrNcmfQA+a25bL74YjIqxHx2n/Vy1R8tMsosvmq2SfbOhW/9wxRfAgJ9Ap4MgUAmr741/rE0vaDl3uV3hgN+GH0dMZoLmFPi/5s83t1Aj1JbdaP8zJBv/uRuqVY0MOfVK8/uJbMDT/qX9fy+gFEK/U104SYcwqiiFMq0TkIdWJ72OdaJnz1Z46HXt92t+Bp1j1A2HnAAPN98P/1oOd7m02l60Z3srcPN2+L8XYF1t84qds2BzKfzhn+BXAAWaI45ZBVJWVvXIhEfkZKgXiK/u3buHOw2MePt57ecBPcxFFMTD0efDlB5a+XHjbGfHaqfIEF/tCZF++LnAZbQEraZ78GHVXljaXND9xNAJicZwTwdQm2DnR612TUh8qaFw4kuE5gscdhj8qnlW7bkQzDvb8ipDrhJfFmZpxLUQ5JOjYHtVbQmd3d5c3M9ongXe2XpmVhTeiYivVoqvXc1kZv8hGhH5k59o/3/jA5jcTEqtvkeboY6G1XdBxQqtGJ5wD7zWXGif3kwG9O2rkV0NDS3WucKBMPZv2u9Lr9cGGbKxfRn8By2X5k001dy/omznZmZD5OB/DwabkIXBf+0O+OEe7ffxd2ihwtCi+BozBno3Z6lVtCwUkZ+fr6sQ4ikBYw7eypvJMkGq2YE/Cy5pVjI894FmhXARpomvaIXoE73g4KGwsExb0e+J6+De9zT1qzHw/LSZ2jG+DkHfU6Me3iuKLzC36IWANOIrss/8HPg9BpWOtT7TrHoR4hFfWnYZfYaYek8dgvja0lx4r3vU2v7Qui1YioFM8tjkWSgA8y/Q2nYBca7HNv/8AC2fs7E8al0QD5YVXwL7IhcrOABO36c9m6FG+PwU2PcdpmGSnFXUUMyVHW0RX9//VbOs7+gKy3ZqKvjZEQOxqT/RYicqQrDWQUD8/M+0n2O0VQx14mv3bqiuBsUHB/1Ze23N/VrYfTQE67XoA4DRN0JOR61PF0puo+IL4LLLtHpiRY12n2x4SlOGpwNebh5sHzMGsi3avX1+GHeGFj8QRJukrIi2EkOKYbRninnUwcAvm39/HSg/yhrR87uzYL8K/XLgd0/H3/bCv8HF07Xfb3oKPnkx/vZWEflsl6PZOG9EWxjDDxyXDT+sgIfmQsce4aq9Mc3HWQ3k9nGm2vPQhIdoe1VVpba2Vie+Yi7y4CIE8RWz1ggF4bPmNmPWLDlv+tfmOvrDTbD4PTnHbEfIEF9eh0xZqXFwvA54Hq0hXRRnu3TCGw9rPv/ufjjkxJbXBfG1u5l4iWJ3NBanUVd0LFsEdTugpDnHIpL4ArjjDujSWZuNeX2TFvhqAa4RXxZnaYx5Z+BQ8bX7cy0EPlQAG5un5I5vbvz3tlbviID7eARHQ0ODPijUr9Ge5mMNbNZ2C7vjG29A92Ng6K8AFeafD4EIm1HVWljxF+33iffB+l2a9SE3F45vXu0pOxsEAbjVYHUbcRl0nawd0+L3HffZ3r1FK6imXgVvoNlrB6C12OtIbmaDcfBfD9wK3I9BPm9y8L/8TxCsg+5HQL/TWl43Kr76Ng889od0hYCiKKZyvmITX80KGUGq2cXl90Nnn5br8dBVzo6VAMMMyoOYxFe0QnQN8Lu9sK0JOivw3j/h/yIWdxCB55f/U1u9a0cAPn8l6lukWvGVl5en5y1ayfmSRnwZ+8JytD5zG3AfUBFjuzgwfpeJ7NxRia/aqhZ7Xu9hrXeKB0F8rS7Tgpl3vGV9MRZjW7AOLUz67xgC2j0yeRaohs9P1tQ9ih8OexYO/3dLntaxwBS08eTz+dDUCJ+fBBtfMP0WiYivykptMqbV87u+2fbXp1kZtXKDZn88/CXoMUNTR392HOxfjylEkrPvA2ElTst3EmtlR8vEV/nyloVdvmkeXZ91FvSJsN8Wd4HBzZ/z0/9iG0ub+4iJ47SfnTqBUHtv3Kj97HcqdJ4ATdWw+u7ox1n3mHatCvrBiOa8xs2btQm6wsLWdvh+/VpqiXlDANWzQfdhqKmAz5qvy7k2VSF+P4haeA9Q4tEBtiB6ypon0roDPwKm+7Xn+9rnYXv0Ra1aYc238GLzii9/vhZy8hLv8/BcTYETAM66ALZ+L2/MZny2NwB/QHOVqMBhaO3vuQHIjbDgigmuCz6AArQYlo5/tU96RRJw9WgLSAGpmPAoKCgImwxNpeJLtKkxF9HZ+y0sb65BT7lAzpvO/IW2wIIK3JBRfVlFhvhKBcySWVZlpfGO21SjLd8MWiP4CC3F6k7C4XQQnSoP+NvNKp2pIzV1g4BoDLdUaQ1Fybut8k0SKr62N0ufdzeTQtGIr27d4PbmfK//Akueb7kGJq6FZeLLzHW2MUsTWag7UnwJtVfTcRqR0aMHTDlSe62sqZX9QRBf8dQdQu2lKIpG0gWbYF/zZx9yoPZT2B2rquCjjzRCq3Aw1Gxp6aB3fQabXoYvfwqhBuh1tGZznNN8TY49Foz5SpE5X6CRCJOfBCVLu0e2/tfZs73sCbjkSBg8CJ74Qhvk9geuAv6Gtpw2aCtoaVfB/cyGXZ+0/P4aLStz/hBxnOqNsY+74RnY+Iz2+vi7WsKPVTVc8dWnmbgMAntaQuESraBm/FvY4C0Ugsrmz9NnaJS9LKCgA/yyWSryyIvW2zUL7WLCjK9oKo95wG1o4baDgDt7wIyzY59Plz4wtfmefua+qJu4pvgyeS0URbGV82Wa+IrbZ9aFK0T/hbZqHWgk2INoBBLA/g3avZzg2EYiL9HniUp8lTaTIT6gRwxLfiyMHAldu0J9A1RO1PrA9f+wdgwjwSdUn3vRSLBY21mF1fohcvu6nfDxTCh9X8smmvYWDLkAQgdrK53lZsPJL8Lj/4UOHWBtHSybrKnB55+v2bFVNeF5JCLjYyq+NjV/hwf312qGQACWLQN/Hkx/EzqP1+zgnx6rXcdE18OoNC4H/gm8jGFg2oy6UvvEl/EcSj+Gby/Srlf+8fC/b7Rtrroq+r5jmycc5jsgQ1c1T5pNOarlNWPOF2h9iq76elC7hkYEqrTFaEDLBPPnhe8/dGhLv2TE1VdrPz/eBjVFWij+hifdqXFl1c4v36HVDt38cLwDC55YzXo32vMkA26MD/qfDlXNbf0BkzRF85wtLQH0Z04zZ7X97S80AuvADnDBrebe25/VHHafDXuDcPxY+FCSFVC0o9+gTThWoK3I/BfgcqBnxHZG+PzQ7xiY0Fy/v/dve+cA4QRcCG2F6GsJJ79kTHhYqAtEW1VeXq7HskghvizenwkVX/Oe0b63HD/8aJrz8xP4a7Ole+4WWPA/ecdtB8hK9Qm0O2ybow1YjEREQT9Nrmtk4wVhESlfF4RFpGQ11nEn3AuBci1Quq5UO9wzNAdWog0wd4kdFG0fJ4Nos59PNkIh+KJ5JH5ixPsMH64RYVU1UFMIym7Ytxi6HqJvEpf4UlXY9pp27bY2B6RHI74ALroInn4aFiyAV4DO5xD2Hca5FpFKq7jEl5nrnNACoWgkUN9TwqTg0hRftdth+xva7xUHAnNg/HgYMl57LQCUrIN+LcsPWyG+OnXqpHnqt67W7mMFGNQ8I+zzaTO1Dz4I//43nHgiTHke5k6Hjc/C9regMcIO0e80rfCNtDkK9O+vfa9G4gug81gYdR2suh2+PIuw9enNPtu1wJzt8N7F2u8AA3Phd5fB8ZPh659pr81QNYXmPOAsNMWO08yGaPfRxPshtwus+LOm2gPNZmmsfTcQDnGckVdoZFnkcQG6ToHuhiBY44qOw4ZpP/PRivYda6GnVngnytMx/k3cQwBU7tbuM4C+I+JcCJP4/ePw2EDY2gAv3grn3WJuP4vtYkKrY6TKYx6aBQJgEjAbyNulbddzRuzz+vkv4JPb4d3vINDYyhJjVHlJU3xZvBbFxcWUl5fLV3zF7TMrm/vMZlJhA9o1BrgYeA5NXfcKcC6w4o9Q8j/NwttzRsxjKwc/QHFxMRUVFaaJr7D7ubSZXC5WtAGXFSiKNiHw1luw60DoukQbwB/4R/DnmjuGcVJsieH1+bQEKUduZwVW64do2ytZGimT2xWmvwPdDtVeX90cjjjiABh6jvb730rh8svhyTXwn9mw5zFY+jvY/QWUL4O62OeRiIwX92tkf8rW5mMOGgDBYfDuu1q/MnmyttjHjPfhoyOgegN8MAXUANQZwsnEefQ8UptQWH1Py9+M+Y/lgOHWIb+3Tnzt3RuuEIlLfEW7xgD+fFgwEgLvaffVpElRrwOHHApzVsGySHbUJDYt18gLBc06KTB0KCxa1EJcAfQ9EbocAvsWagTmRIPya/U9mgWyw0gYfH7L65ErOkZi8mSYMgW++Qa+OxJ+9CEsvASzdZ1pyKydX31Z+3n8BOvthBGCXNwD7Play8fN6Rh3l7hwc3ywozk646BjWvq8V/4Js86C+bvhxtPhjjdi7z/v3/BuMyl9z/3hk+eJ0H0APP5bOPMOWKVqxPO5zX+LNWYzg5zu2iR687w7E4FL0GokI+K1t9OmwFevwzwHFl0jsbaBltUzV6Apz6JtZxUW742ioiL279/PihUrCAQCFBQU0K+fgzgLG+cAMLp5LHjQQQdFP+YHzfLbQ0drecGyMONs+NFv4ctSuPFSmHti4n0yADKKr+TCrPomkrAooUVlEU1WGvO42+Grn8KC32gNUuFgWHe0NnvgA8RCL7tbDut4EJ0qD/ji92F3k0blnh5hOcvLa5m5qj9Y+7kj3O4oilNFUegvlD0Clau0MOCqbI088/laVsiKhM8HjzyiDTK+AlbHIC6jXAvTxJeZ66yqsO2/LdvsQrOn3U+LSiHGLE3kQNs28bXuCVCD0GM6rG0OYJgwQVPOdGieWd20LGwXMxlfrfK9NjZnT3T0QZ6h0hcWhTff1HI8ekzVSD5oTXqBZmH44mFYsULLKznppPC/R1N8CXQSnV7ErGKiZ7serai5Ck1NVYs2o/fIVbChGmbfDYN+2pLZMBbojBZ2v6zIpcyG7fDlTzTVxO7PtYGkUqAR5qHm8wOtABK3t5KlWUxW3Ayv94V5Z7Q+LkDZ/PB7X6i9RozQSC+Ajs2FekmLgswK8RU2eNveTIbnoOVfOEX3AXBGcxty7/3m9rHRLnbu3FkfpEYlviILzGYxL0eh5cHlxdguEmf/HgoVbWD5duvMJ+mKLwcKVKnEV8I+89ca6VUwAIZfqq0ACDC1+Z9wF7wP/HCIpiwq+1ab4X93QtzPeOZhThRfm7SfHS1m9ggIu+PKSsjvo6lirPTL3adCVrGmEjfeWgtobvocKFCt3huxtlebO7gDb24hvQCa7TAYc2Bmz4aDD9YWQnmuEiY2z6KXvBNOekU5D9sZX9ua+8KhIzRSBWDhwpa/5/eEmR9Cdkeo3RJOeunncQbM6QXfXQv1pejB1Ubiq0L80vKdWFZ8xbrGAHV18I9mFe+VV7b+u8C0k7Wfayo0ct0q5jV/7/1zw4PGBVG1saWfQFFgbHNswbpHWtq/+t3aio8AY/8KPgMZlIj4ghbV17++0VSDsSak7da4Mmvnil3wZXONckGc78UMBPFVXqw9V0b1t1W4PT7Y2ewBHzmx5bWpP4UbztJ+v/tNmBvHyvzbS7SvdWZ/OOaXsbeLhlAQml7UJkVA6xfm0nyb2LQCVu6Gn5/fQnqdCFxNBOllor39cTPJv7zMfjapkVhbbHh9xf+zd97hUVVdF//NpBMIoYfee5UqCAIiIKCi2LFhb9h7770XBBUVlSJFrIj03qv0HiBAAgmppCezvz/2vdNnMpME1PdjPU+emdw2t5x7yjprr+1nu2BQirJh1r/rjLqzZcuWvs3lT9M5ANx+++1s2rSJxx57zHPlqXhYZ4RUDb3Sc31Z8cZH+rnwMMx+7R/NtPlfwlni60zBbcB7NLUOhUVm4yv6t2oULL0CZrVxvHyHUTPdR1EzQ3P7nARYNBA2Pamyc6+qHhNWVXA0/xXeW6mLRsZAL7S/lAcU1CrbIPqfzhj50xf62bGq9wGuKYHNMNRcbj5fDRs2JDQ0lHbt2tkzH9lhVng5xoC3aVP/zH3nc2CwMViZgBPRBP7uRWhoqEvH0yvxVeJ9FlhxHUyPhRXX6m//CjyJhqasA7a57eY2OHYn4EoV6licD/uNMJoWo2HTJv3eqZN+VjfuX/wOl90C8fjyyOh4yOjtV3dTLfTqpZ4jmZkwd67eu9R1+MXXz+ln//4ODxETvogvW7Ga23uF8UxW3wbrRqvizLlhHYfO6GUDddBkE28CVwx3nak1PRsGLYJLDNJ1afhpel+d0PxeuPQAHLxRk2BEonVRKEq+nQCwQK8pcN6PENMGin1nXgRcy76zv5eJWKNsJDn8h0pNfB0zBjWVQ4KbwfWH58aoWvbvDJj3nf9ty1AvPvroo/Tv359u3bp5rHPpYGbhUN9dimurXlJHtEIMDDDK0/dfeKyuXVv3j46O9jRZd0dJIQKlvBflHuoYUNm3apKLS3bDnp5G2beoyhJUVXeFEYL63jZo/Lu+K4RA+mYfx9ZlL1+agdVSSuLruFF3VC7lzLFJfK1cBU2NjHV7xwS+f/JS9aAy1V6tUFVROo7Q59JMngVbNkp8hhY1tXcuS6biyzkcJiQEvvhC64bJk+FwGwh3q/d9nEepia9Eow5r1sFBfK11U2NUaOgIxfN1HrYCqNwOun+p/mBYXMPPM8A9k1tQxFdJ93glmjG3fn24/HLv24Bmv4tA+5nrS+ETtdpQHJvG9ibcMzuaqD0YqvdUI/v192t9tO5enZip2gXqX+G6fSDE1+WXa2bn1Cy9bg+UoY9b3n3n719Tcq52GPQbGdy5uMOcME41M3GXMtzxdI8PUhMg0zhOm16u616cDOfX0aiAG2+Dk15I3B/f0mQwIcAHE4L/fVOB3Q24zFj2LWpCvwaweZ9k9om966BrI1hyTM/pTuA6i9uI3fXd9olzh+tEcz7+iT9/cM6e6Ux8bcPxSEs74VHKsmHWVSbxVaYwxzKUT6vVSqdOnQgN9aKsjP/ZMRkxZHjpz88X+lwN51XRU3z5+X800+Z/CWXQwJ5FUHAKTflz8xBuHPsDd13wBW9c86xjm6IsOOJUWAWYhFbYxcD7wAOAwb9wfJFL6msReOrHt/h26S2IuHoVhIdGMjuzLx2Ks1kadgFXzZ6D7U8bmyxNqCdHocbzZZMaO11fQVEYF739FxXCc3jnuidoU28nLuoif6E3pcW85fo50BFDvXMnXH01PPYY3NyqFcyaBccjoCnq05CbBFFK6sTFxbF582bvqgbzmWQ2AVb7DnM0kbyMlAsjqLSkkIgjBYx57B4+D7+PGQ9eSeu6u/B3L2JjY+2dUK/El9N9zsiJYfBbc9h/wnuHrXvRGt7Lf5zWNu0NZxBDZTIp3mAlpJOTMsltcFwuoY4JP+ksa1QdqH0xbNHQgsNVO3FNT/iuoCUt2AyHXQ18gwl1tN+fw9pxlRoxbNsKKSmQlgZpaVY6NbmKLsc+Zs2j0/jw6x6kHfiatOwqpGVXITM3hrCQQiLD84gMyyMqPJfvjt1MGzIYkzSCxVdpZvbISP3rsKcBtwO7FyTw9AjIy9NJ77ysU+Sl/EZeYSR5hZHkFkTRs/kqvr/7JipFGYOcwnTvA0xzsvoG1HDZ7Nh4Uer8+nsITz3Vjy8e+oHzv+8BG1Jh21JoVwrfAKdyVGyzctXH0yksDmPK6OuoGOl07xtcBafC4R0jleT1laFmBjTEkLxXhSu/ctQdETVg4QD77jPWXMETU94hK6+S6++HFYM1hI+zdjASeOePNrxbQ8ehq6Ia05itcNzhXVPSIBN8DN6S1Ccs0VaHTrUCs/kAqFBBRQwPPqjn5IKWPWBgE/jrALz5HHRoqM8rqrZ2/Jw7oU73ef2BLjwy8QOa1DzAhLvNGWXfdcHTTz/N008/7f0EzY5ozlHYJiCwK6QlfZ516lhbrD4H8aGh8NJLcNddwI13wG+PwfzdkJsFUY5n1aRJE15++WUaNGhgN5P1ikBCBIx7sTepGX/9fRF/bbmIQykNmXr/NbStt8PnvTCffbkpvtzCRO/55nNmrPUyGxtWmWhLAavSnqA28Jr1NT5+4TFU2mTFarHyY9gw+ufOJb7nHQyMXU8G77tk840IzeejGx/iyh5G+DRC7cpF9GlVMvFl1oEuxFey1gubU9sx0IeXrjfUqAGffQYX9OoC4eGaDc9yIVheg+QVGtZXpaP/g+SnwkojfmdbFSCNz9Lu47wayzkn+29YGwp3TS1dP8LtmYydfzev/PwCRcXuXdQ0He8JuMZa+oBRzwDMSt9Jd+COD1vzi4u4sQtvhN/HHXmfsn/IaPpW2Ey+xUE69Wq+kp8fvhyr1ZjEMMpoSWS8V+KrIA9O6uCpx11DSM+twG6AXbtoUi2DLKvR9tqKodBdTuHt+iqDVSfqqhf1Zmd6A/sqSQdLhXo6MDaeSVBZHd2eyeIdfRn1xQSy86NBhMU5/WjLTl5KuYcxtT2HEiEh8MQT8Mgj4dCyMmzJgKW/Qs8gB4CbjcmxzucAmkPo22/h2rgmvAzkbt8PudpWA6r6ihsEKau0H5Lwk+NYdYa5+HgVFUHR9n1EAh/82pTJ4zXy3mZz/wvljvS7eY5n2Pl1K/r9uAgbIQxqP5eJ995gHLKUfVy3+zxr01Ce+vEtvrnzVro1XR/8cacbSQQu7uEy2ZOfD0OHwpYtPvbzgiG1mqjYNckwNzw2Wwca/toCb3C6xt3HWnDD2Ik8fNGHjDxvirFBGccHO5WNzAmrwJARtZk61ZGLCKsVpi2H9s0hqQiuOU+z4Zn3prgInjG84a7uBB0v8Dj88uXqYtKkCQwbpvfR5AQB1/7aFWgdNRsVLnyCTmpeBnQ75PDlAn3Pk5e59h/mfw/X3K6ZUGMsMPEz6BQHGx7ki9+H8tLMl7RetFghtCJYfYeph4fDBx+Eck3XerAwAf6aAZfcG/BttcPMnjntCjgGYgWxWLCmiEaTxKEK29JECzmVjd82XMJTP77Fa1c/x4huptTNf79gwwZl4spEfLm9g5/OGc13y25m2gNX06RmvM9zKBHzJinhWK0itG9PYqLmyzoaRAL4evXUdeWqq1znbADtd12cptFFa9Dy1oCyhdf+f4D8B5CRkSGAZGRk/NOnUnrETxaZhMgkZNoDV4q2HiJ/PTnIvlwmIbLyJpGtr+n3x4yNQhHpYHwPQeQBY9s1d4sscOz/+S1324/r/vc+D4uAJFNNanPUvnweA/TLO7eX2/WteaWb/fihIQXy8JD3Jf2rGF0fP7l87qczUhP1HoHI+j/ti2+5RRdFR4ukvfuV/jN4sMjsLnou+78t+dhZB3TbySEid4zSYzzzjMsmRUUiW7aIjBsnctNNIs0aZQqIjOIbEZBMKkodjsiNvb9zfdZe7kW7du2M3jWSmZnpeT5O9/mjGx/w+qxjSZWx3GVfcJwaMpKJMoRZIiB5lcJFJiIyySLyc32R4iKXnzhx4oT9HKKiosRmswX0GFwwp5ee55aXRXbuFAEpjqogjRsUCYhMiDAezl3nu+x2++23CyCvvfaaz0N//PHHAsjVV1+tC+7sIwKypPGlHveiJytEQDKoJBHk+nw/QKQeh/U8sUgtEj3Wd2e1CMgh6vs9jvl3SedfpegHq+N5L75UZP1Djv8nIGIxNv4c17KRtMjlmteuFYmM1E3btxexdamq/9zZJ/hnI+JSjmY+dJn9nId2+kMKvw9xLaM33KArO3cWyc/Tc7t5sC574AGfx5339AAJDSnwe49W0UME5Eqm2Zf9HHOVceyB9sNec801AsjHH3/s85LuuOMOAeSVV15xLHxLy9mi8P4BPTP3v27dRP7+28uPLZuuG1gQ+dDpuf1cT+TwT7pN4SmRtffKqa8ryKND3xWrpch+3MQxtUqsC0rE4Z/0He6jB32bx4O6trg4kcJCESnIF6li1YXfPFv683C+nklG/TLJIqe2/yh/fLdW7hv+izSttdfjPO4b+Knfe3HVVVcJIJ9++mlAp5Ofn2+vv1JSUjw3cCqjq17q4fcevcJzIiD7aey1/qhKihygkQjIHwwVC8Ue21za+RePe3NtT+T777/3ex2VK1cWQHbv3u1YeHdfEZAvLHcGXZbDw0WmTxeR887TBd9+K7LsaqMvcaf/m2qziSy90mgLm4otJEQEpDH75eKwP/R4MRaR/NyAnpG/Z2KbiDSsHl+q99X3n01OUkUEpAObPdbHkC5HqS0C8gIveazf+35TjzI6Y8YMAaR3795eL6lNmzYCyMKFCx0Lty0TASmwhtrLyj6aiIBcwPwyXeMVTHdZcGp4e4+2fcKECQLI4MGDXZY/9NBDAshTTz3l9ZnIJOTuAZ/bD9+PhfobVJBYUv3WMTabiNzUTReMaBNcuSguFok16qZZX0hRkUjlyvqv2V4XECoRIYXSubPIvfeKfP/hWtn9XguxTXR952wTkX0fNJXJn66Rhx7S16BCZLHkEmEvy/7ub2XSJItoEZABzLMv3/R6x7LV5W73uXOj9QIigzvMDv64xw86+sIrf3FZ9cMPwZepWFId/3wbrueRvj2463O7xut6ThIQ6d1yqWebUdrxwddPioBs4BwBkXPPFcl1r4pmfSFiNa7ljZu0HxM/WeSVYbqsAiJH93gcev9+kWrVPO9N69Yijz0msnChSEHCYs9rGYfI5cZx7S9EiMibo0RysrTd/Lme6z4PRYuEGds2jND6wsCJpCKpGF0Y9DNs00bE9vJI/adD5dLdXxP3dhYBWRx6vizmfD3mLUYfd8FAEVtx8Mc0ysYvD19q7y+2qL3L4/11LxvDhg0Ts50HZOrUqaW/LqfymfZlZYmOyBIQubbn5NKXz/x0kcsseo+uukRERO65p2ztWLt2Ii+/LLJjh2jdbpafHsYG3Zzvmffx3f8qguGJziq+zhScVDVX9ZjBPRd+ztj593Lj2B/Y/EYn6lQxZgya3KKs/66xMNmghQejIRbjUJn1p4ClKlz7mTLQSXPZfLAjD0/8EIBXr3yOEd0cyrGKu07R4FsNz8r57Fvm968DqLJ/3+vNuJAFsNc9RVvpr2/3MXW5jQzLJa8wig9nP8LklSN5+9onubFfrfKPr/35Uw3piwuFczTrWk4OTJ+uq7OzYcyCVjwLKgOrM0rN7Y/O0mxP/pDws37W7Au7DXlOmzbs3w8//AArV8Lq1eA6eW/Entfpyr5TTWiWeYD3eZRRaybw0Y0PUbVimm7mJQzJzOwYEhLi3WjW2EcEvlhwFwCvXfUsl3f9GUSI+TuTuN+PE3pKZ5XTLhpMWvd4no1+g6cnvk721gpEZ+XAQaAxXmXSzjPUcXFx/pUe3pC6CVJWgjUMmt0Jvy4G4G/pQPxh/a19+cZ02VFXZVOpQh2PaQz93xnq3dK4sSZ0rFIFqsaeS/ovdYnNPsq0kd+RHrOCKtFpVIlOIyYqk2JbCLkFUeQVRlJrTRIsgJSm5/D603EORZfxWSW3PnwI9SxHGfdpERHRoaoIy9tK5M7H7KqxpPQ4rv50Gr9vvJRnpr7B29c9pefZ6mF9txNm6IxMsmiTHQHYb7lngomjR2H4cD0PUAuyLffdT8cNL8OMFfBpPoQHaE5twqnsfTD7Efv3PzcP4+5vxvHV7XfopO76YzBxos7wjhunv1OrH1x4BL6b4xmiYxx388GOjPhwJkXFYVzbcwrPX/aq63bnToBq3WjZYwdkw1u/tuG6IrjiCjhaqPUTyQ4D5lKHOh7X8nWkSI85dy7UreuxqweWL1e1wrp1agH05JPw3HNOEc4Nreq3tgX4ExhlLDf9d2r1h5PrWLC5O3eM30p8snqlRITlkV8YyZp9PRje9TeP+xYU6o+AXj8i916DBfiLi/j54cto0TgL2jwFtQd63c1m00jepCSYPx8uuigchnSCyRth0g9wy2uBn4OXEAER2Hm0NX9tuYjZfw9h6a7zKShylM+wkAL6tFpG/aoJfLdsFPO2uZ2n270IVvGVnKweSiEhId5Vs07Hf+0XDW0e2WsSzw5/3WWzsIZv0PSmd6EAwj56j40DvYWeVUN2zsR2fS+G5f/J8VF3kdx6BQALtg/gge8/5USmp+osMb2UoY4nte47ISr3+vtvVe/5g4iq+2bMUAX0hgvP4xxWwIoVMOReODwN4idCp7chPNb7QeK/03rLEsr2dffQtvgxttOGeJqQUFifgqhwwjML4JdP4GpfYd9+4PRM9iS24FBKI8JD81nzcg/CQ518oTq+rn6K6Vvh72e9HMgN506A6t0JOZlM1fPTEIuFH9e3QDweZWVsf30Ej17DiyEvc+MjP1BQPZwRH81kd2Ir9p9oSrM4p5C6qNpUqqTnFVSo4y4NyzkeVhvJt/Laa1B9RXeYfYDJD63l5B2GWjZlLaweFfD1AcS9vgQmQx4RRJJPwQkb0W5te1Chjm7vYVKGSmheuPxlHtv9HuyA/HPDWfH2Xvs5mCgq0ijOpCTYtw+an9sHvl8HW+JLviZnHNioyhcr0HsEW7eqHVvFijD6mboUPBdBuC2f2sUJbNzYmI0b4XO6AbupWvEk3ZuspVWdXew81pp1B7qRespV0V+Po0SST5EllJFPNKBzd020abU6/iwW43vaPnJfjKLi6mxmthzBdVFT+HPzMKasuo5OjZy8SoOty13KfnM2HtSQjjlbLmL/8SY0rXUg8ONOeFX7wg0jPJR1Y8fq52OPwS0BWFj9+Sc8/ngVMqyxVLalg60rsBKO/QWVS4h6cIdx7olpcUxfq96rexK9+OSW1iNqv8aTxaP9ytWrVaH1ww9O4rShd8IDM+GjOfDS9xDyPdQEPjbW33wO1GnuctjMTLV6PXlSczdcdZUGjqxYoUOJnTvhvfcgJuZ8BrX9naHtZzKk45/ExR7XYcCVwFBgHtpPSCqGpyfA+9/DxTboi/qP2oCZwM+G2r5HZfhzh2ZeNvDGWyGcyobOnfW6SkJenuZk2LEDdre8g1ZMhh0ZkJUKlXyFc5eAxZqgYlrR1VQhjb4sZd/awTQbvBiS5qmPXmsvXlf+EFWbX9dfylWfTKeoWH1e9yS2ZOH2CxjQbqHLds5wz3ZdJsWX07G/WnQH2flaD05dfQ3PDn+ddvW3ez0Hv0icA1uNftHQERw6BOPH67/TpmkS85Igol3s6dM1Of22bfr34ovQtmUeV7W9lat6TKfNiJ3qs7kOOArUBU53lNV/GWeAiCsz/icUX3Z2VmfGc7+NkI4NNgmI9G29SAq/D3VlZ1+5TRncSoh8ZTC4PyDS12B2LRaRL78UKS6SzMktpXncbgFVmbgw5WMQiTFmzO6/3+WUZs8WeZR3dd2ABuV2fc8Of1VA5K4LxsrsJwZLi9q77Ix1z9ZbZMPCHa77mTMvSYtKx05f3tpg1dvbF02erIvMmZqqpDho84PG7My0GJHiAv/HnnuebrvrU5Hq1UVAjs/ZKLGxrkx8xYoiAwaIPP+8yJ9/FEnqD231Wb+O2AxVTx+WyAc3POSXib/44osFkOrVq/u9z0ue6yMgEh2RJRlfVVLVSQenE2rVSmTxYt3HmFl6b+QjMpPLjHsV4VCmeEFERIQAcu6555Z4+z2w+ja9Z8uvFRGRnAd0Nm4M90jDhqpcMtVw0q2ay67PPPOMAHK/W1l1xgMPPCCAPP3007qgmz7keyK+FFCBmQseekh/a+RIl3fQ46+1ce/ef8/7DxcViYSG6jaHDzuWu73bMgmZfN+1jonSO0e5Pm9TIfO4sUF9pxmaSRaX55KdrUIrc+Zu1Cj9fvGFOSKVjNmk714M4KG4wThnU50ZFpIv4269065KemnEiyJT64k0b66/MXq06/579ujyiAiR/HyX4x78oofUjlVVaf82CyRvQrj3WajDOmMvoaEi+fly5Ij++7jlHf0yqJH9sA8++KDrM/eCSy65RAD58ssvHQtv6CIC8i6PCoicOhX4LTp6VOTyy11fqWXLHPdOnjZWhKOzu05lKfXLWLml79f2fetXOySzHh8it/fTMvrkJW+Wz6zc4ikiIFlES2xklhQeWRzQsUaPdrwSIiIy7zvHtaQmBv77SYtcrvv7u2+QBtUOesxUNqxxWO6+fLH8+sT1kjm+ksgkJP2rGAmx6gz2wY8a+LwXphrlySefDOiUPvjgAwGkZcuW3jcwnt+G11QdYLUUuSl6jPO48ko9+f79DdmKH3z/veNin6kmMskiy1/oJSDSpOY+l2OnjK8gVgvy1ltv+TxcQUGBfSb75MmTjhUX1BcBeYCPJDY2oNshIlp13WWIgC/hVxEQW+vWel1/tDXaOB9qysy9IlOjRSYh0z+YKVOs14mATKr/pFxliDNXNh2iX4a3CvyknOFUh35y02jtkrSd53v22kud66E2dN5+8WI9v8aNfZ+DzSYyaJAxtY7IRGR4l58FRD67+V6P465YsUIAadKkidfDxcTECCB79jipSAwF6tKIvgIiixaJyAcf6G9edpnX+xHQ9YmoFBhkQcWhIiApTT37dCtXrhRAGjVq5LL82muvFUA++ugjn+dwbrOVAiJzRl3oUCp/GuezvjnfEIR89ZWI7Fyp/4QgknnS6/ZeMf5p47lFiojIRx/pvxddZKxv1UoEJGnSPJk2TeSRuw7LeS2WSWRYjkcdBCIRYbnSo+kquf+2BPn+e5FD3y3SFc2alXwuxUUiY2rZr332jYMERBpUOyjFP1hKX5c73eeXRrzgcr6PD3tbn/fMeoEd1+gLyf0XuizevNnR1CYGWL3n5Gj/eQPn6M6f3+ZQ9gQL4xpfHPGiy/WlfVm5fNrB6zrY2/kqVUQMQaq88YbbdvFTRdobP14PkRHG92qIfItL36uoSGSovkpSp472B0ykpYlMnaoRHjVqeJazLo3XybQHrnTt123/WuSJSx0KRhCJReR6VKljLrsYkRl1Xe7FoUOq2AWRv/4K/LaY/ZcnHy8WqWbclGnvlO4ex2+1l/16HJbLamsERBqV5Y2HVui1TgkTObk+qMP+On6lhIXkC6jC6s4LxgmIjOg2w2/ZMBX+gFgsFsn1kPgFAaN8Fn4fIvWrHRIQiYs95nQepSifs6901JNHjshtxpD+wgtL3tUbUlNVpD10qEhYmGt5a1N3m+yv0Vj/uc2trTgdUVb/QgTDE501tz9TMGOkAbAQGZ7PtAeupmJkFkt29uOVn19wqG/S0uDjX3TTkbFgTvhagQfqwU0XaXm/805kzFjumjqPvUktqF/tMBPuGuWY4bABY4FMG3ToAO+843JKLVvCPpoBIIe9ZLkr5fXtTlTFV8s6u7mo4xy2vtWBt699guiIU6za2Z6uA1py1+VLSVk3RU34FvQvvSmfzQbL9+j3ix2mpeaMyH33wc03QyrVSAtVfwtOVoTImlCYCcnLfR87N0lTOANE9oGUFMRi4Z4PW5KerlZfn3+uvu1paaqeeOUVGDIshCp9jcxCjSxY+unXuxnHFwvuQgSfhpSm4stnRkfjPn+xUNVeN577AzELstS8fgvq2vfINbB5M/Ttq/sYxug9r7ue39AMS7LR6jf22/T5CtrYPj8VDk7S7y1Gk5EBmydsAiC+cicWLICGDeEohuzmhKuCJxCPL1PxZb9HxjH25TcEHB70dlx9tX7+/ju0fddY6KZiy8BhDDzCzfzWREiIQy7kbHDv9m4DXNfrR56/XMvAnV9/wfLiHxzPu/4Ijb1Pi9X/Tc+HCvVcYvJtNi27GzfqLPTvv8Pzz+vs8x/zo0jpYxhVf/Wl9/P1B2sInPMu78961DjfKdw14EvGjLoPgJdmvsTGr4fB3r1qlvGamwqoWTOV1OXnqwTNQFpGCEPenUtieh3a1dvKzIdGEBFmKjbczFhNY/vmzSE8HNOO6bgYX1IdSopSe3ydTAMgmRpUrAjR0d729I46dWDmTFXK1KqlSeH69IH7bksiMyUD2gKNUCPhl/VPXoHkJ6qz/Z62jFwymbkMZEedPhyo3YSh82bz/IFXuZcxrN53ruf9KA1+/haAhVxAxx4VCa3bN6Bj3WhYNf38s6FWveAGqBOm1zLhlcB/38nbJDmzOrePH8/hkw2JCMtjUPs5fHjDQ+x8txXxq5cxdmZfLh09wvC9s1C5QiY9mq4BcKi+/ChQAzG3z87O5q233gLwnmUJ7O+rqfa6rtcUJzWP8UwK79AHb7XCRx+V7Glz440werR+/ywXkoRaldVn7HiG+YLrMX4+3Beb+L+e3Nxc+3cXxVealvEUqhOM9WJIiCo+XngBVqLmz5adOylOTjVM+YG9n2u/whm2Qlh5PRRlM3bN+4x8ZBiDbWpQfsWES7jSsEb7usA4xoLdkF9CcgtvcKpD52xR1fag9nONlV7eEy91rgNetveW0dEdFos26BFhatq8CprVUg9K9dF0Pa5ZJ3lTodpsNvvzdVF8xWs521WgapdmzfBucB/s9Z08aa+H19YfDkBImudzCErx5XYOpuKr/c5tOtzsCAwf47O+Od+wnly6FGjRA2Kt6lW7bIbX7b1ijeFZ2La+41hOxzazDtbK2s9VV8H7Ty1n+Yt9yBhfmXWvduWzm+/jgcEf8/kt97D+tS5kjo9h9Ss9+eS5Zdx4IzQoDMDY3oQ1BC75HNRqjAuPLqBSZCaHTzZk1d6eurA0dblxn0VgyqrruJyZHImsyw38wDdLbiWvIAIqBKA0SdgJG4zneutTLqtMtdeIEU7eVyUgKkpVUwcwMjtmGhXOiSVQ5Lt/5hXWEArafmjvt5rYm9SccmkHD6vqP57G9O2rfoYAzzyjbRxgJCF6VDPyVgaOoCorgKuAcIuLgfkTT6jqLSpKE4PXcYiviI3VbuV336mqcc0aVeF07aD9jQ3xXRk5ZjJbD7dz9Ova3Apv/wrrf4abgWpoUpBJqFInBMPEHsg/6mKE//LLUFCgXfpBgwK/LSON3AY/TrMi3RrpP3N+CfwAzpjyHghs5ByOUJ8XfutKbmQssWTwy0chPP3nT0hxoSbXKgwse+Tv367lyru6UFgczrU9p/DDPTdx/6BPAfh1w3COnDRSiHspG851VePGjYn0l3CsJFhDoN1L/LT2ChJONqBmzHH+fHwoFouNmeuuYNPBTsGVT1sRzJ+t9WSLhuzLrcuECbrq1Vf97egbVarAqFGGVfVxmPDxToZ1+oOwkAJ2HG3Lz8maYOTEDjfzz9KqKP+XcQaIuDLjf0LxZcItrnvSvdcJiFgsNpk/39jmkUeUuW3b1uGp46yIstlEHn3UTvc+xjsSElIsK94c7sr03lRZt4mKMoKCXVFUJNI5TKeCiqJCyu36OjT4W0Dkj8eG6nn8XF/k8E9yZO8xGTlwuZ2lrhJ9UsaMusfVB8mL6sUvVv6iBwtDJCNZRHRGy2pMquzZI3LsmCqyltJbF06eLLLyZv29DY/6PvaecbrNXz3sM8aZNZsI6OzL1q0l3wv5uZ7Ia3rBOURKZdJk0dcTfO4yevRoAaR79+4+t0lOSJHw0DypwCk5VbeCg/ZvFyGy6BOf++XmitQNS5JiDKXQnrU+t23WrJkActddd5VwkW7Y8Z7es1kd5VSWTXqfZ5Pj6JTY/h/19y68UKQN2/Qcoi0uu5v+Xddcc43PnzBj+8ePH68LovV62rBNqlb1skNxsUi9evp7v/zi3Vvh3irGVF0X/9fX2yhDP/7ouc7tuMU/WOTKnn8IqFjwwAG37R94QI91+zCvasfnnzeKdpjI0qWO5Vdcocufu1j9y8SKyAFvRlT+ET//a7vCa/MbHezn/cwVn0gz9ti9T7xeq4j65YHImDEiouWrj9qtSd24HEn4qqvrPTbqATvef183vvJK+6Jq1cTuRSdNo+zL33rrLQFk1KhRPq+nW7duAshvv/3mWNhdVZqj+EaaNg36FtmRmipy662OV61e1cNavz3oNtUbwF8xFmkavkcKf6wReD3nC+0ri4DczecSoCBKRLQJadlST+nbb42Fhn+U9KgR+IGcFF/vXPeYgEjnRusl+5so12fv7Fnn9J6YCoereszweS/effddAeSGG24o8XTefvttAVXhFBT4VvNuWb7baHeLZcc7rVzLaPw0kY4d9V7cc0/g9yI/X6RXL92vZQPJGN/c/thPfV3BXv6ffvppAeQBd388JyQmJtpnsl08Fhur0d8g/pI+pbT3+/RTkR2oUuat3r9JXlamyNSKev2J81033vyc2CYiL175poBIXxapWqx6dZGiIjl5UsXnIRRKUSVDDTvJtz9jScibPUwqRJxyrZPc6w1neKvLvW3/4IN6bo88UvJJvPqqocawyviRtwgYPm1ux42PjxdQH0x3ZGZm2tUIOTk5jhVD1M/rKd6QiAhtmiQ72yFROXKkdNf388+6f+vW8vRQVVflhHueV0pKiv288p2Uuv369RNAfvTRrtl+qieRYTlSiQwpjjD6Dz885/c2zpunmzUwhWe9aumCpy/3u58LjPpbXrxGbDa76F5WrDDW33+/IY16XP93U6D6/DPro6cNRdm99wZ+Tj++ZMjHkLt7jBEQuW/wuDLX5RtnfCdgk620tbcV7/GI/HDXjSX3VUVEXlYlpjSv4LI4I0N9bsFQGAaBgwdF3uUxVRDe8IDILw31XI7MCu5AIjLpI+371449Kj2brxAQmXjvSP/vd6BorHKoIcySJ57QRaaquUIFkU2bxLVsPI1DjdMAjaZxKhvjxzua7GnTgjuVpGNFMuzCFAGRnl3TpbjQTSVk+kl9h8jtiNRClV8vuJVRQ6mzc6djPLNyZXDnkpMjUqmS7rv7XvV5llYVgzuICeP9fY5X1DfMJiIjRoiAPItG+Ywe+o2qH1f57qeZ+O2bNXal1zUXrJDCfdNFptQRGYlc1uwnAZEXrnzTZ9l44YUX7HXZ0KFDS3dNzlh2tfRoukqrmxEvikxCrj/vBwGRi7svCe5Yx5eIXGAUoPtHy4036tfyOE07DJVa2pex8t3dN8pLVV8QAdlepXX5qCj/YwiGJ+IMnE+Z8T9FfIl4hPfdfpuanNaqJXJi5V6HjtGfptVmk+N3PmevnZcNfFmkqNBx3NljHWFZX33l8zBdW2c6avhj+8rh0oolKjxbQGTvX994HdAv/WWDnRwDkY4NNsnyF3r5l/H7wmOGMWV3R2igGTngHKX35psiX3K7CEj+Uy+IHJqmv/W7n9AMM3HA9rdFPv9cBGR26MUCIq+/HvANEUlcKNJSQ1Tu4Au5dsAKn5s/99xzAp7ms85497FFAiJv1jCef0wFkY+e1OdfAs49V2QFPXW/l6/zuV2XLl0EkBdeeKHEY9phKxb5tYnIJCR329cycKBIbY7qQMlq1VZYlECIId1R7gzCUkRk/PjxAsiwYcN8/kyvXr0EkJ9++knDJozjVCZNOnXysdPDRqNvxna5h9iaJE5JD/Y6o3P57rve17sdNzurSLp0cfDYLlXYxRfris8/9zjMpEmO22MnJgysMPiu8HCR/Oax+s/DF3kcwy8KsuThi8cKiFzYK8HlnG2FhbK19oUiIPNCBsm6tT7CvExm7uabpbhY7GFPMTGa7KHEMGaTSXIqY23aiHRlrS6v5iDjP/vsMwHkSieSzB1ezaSbKzE8jN+lV6/gbpE3zJ8v0qShI4zmup6TJPXRWJkz4EK5Ifx7uYLpco11skztdpXkf/y8yMSJGgY3YYLI11+LrU1TEZCH+EA2jX+4bCdz4pCGDqHGzD//HNzur72m13DBBcaC9X86iNTDnhMlXmF0vop/sNiN68ffcWvJdblRNlZMnCggUrViihTl5Xj9iS+++EIAGT58uN9TyczMlGrVqgkgEyZM8LvttQN04HVV/xWeZfSLLwziI1YkOdnvcTxw9Kg6eoPYrr5aIkO1LTyweKb9HrzxxhsCyC233OLzMPv37xdAoqOjXVdU1RHQOWwQP69CidjXX+Mu3uRJufBCkcxFD+vzWnyZ437s/FiKfghxMTVfca4xKXfTTfZjde+ui3Z0uUC/DGteupMqyJSFzw8REKlbLU2Kl34cmP1BIHYJZgijn76QHXl5dlb4UP+LBETa1NvpcVxnEqmw0LXtPXLkiAASGhrqSly2jxEBuYYp0rq10w6dOun5zZxZuuszw/nvvlteujfB0Xhku/aZi4qKxGqkp0x0innr2rWrAPLHH394vSXpiZrs5UE+tBNsJYX/njrl6IIePCgio41ESgMb+t3Pcd3FmjABROZ+K9u369eoKKfoejP28YorjH2CDBG9+mrd//33AzsnEb3uDhpat2v4FQIiNSufkML8kvtf/vD4TYukC+v0fEIc4XCrK/UT+dI4/z3jfB+gQ2Xd5zHXvtOYMQE/Mq8Y11H7vpsbXiqy5i49j3WjS97RDee22qLdznsWyh3DZmvTf8vPZR+YFxfZDeRbsUPM+dDCQpGBA/Xa69cXSVw707UsXItIjCfhtHjKPPsQ7KWXSndKCQk62Q6a9MoF7uTsRFyJNzdy1oy4v/TS0p3LTTfp/s+N3O5o31MSgjtI+nG76X57/nZ0k41x0dHm54vFeFVHnf+tihnip/g83O8THKTX1RescLw7j6mgY3+X3gIicbFJUpDnfQLrnXfesde/jwQyoeEPR2fLypfONfrVxZK0dblI/GTZM/9nux3D6r9KUjo4YeNjIjX1fh3+/Hc7cbk+uCjQkmFPLGSRtTfqQOOIpY7kfxcWnIDkfwBnia//GLKzNVsDiCytYQRlX+R/IJuVpfYGz/Cao5Pz1FPasmVkiDTVAZZcdZXf1m7ECJEj1NFt53xT5ms5uP2w9m2sf0nh2nXeN0paJIXfh8hnN98rsRU0I1BYSL5se7uNb5WAL3QyBv7PXuFY1MmTT8jNFXm96nsiIFtaX60ZNyaH6u9k7fc8bn6qY33GHrHdp9NHb/GEdOliZEMLBu/pb6+gp4SF5MvxQye8bvbJJ58IIDc5DSycUVxULM1qxwvYJCXOeMbOvhwl4JFHRJ7kTYMs9K3suOCCCwSQMYaaJyAcmSUyCSmYXF0uvUQbi8sjDPVOG0c2pxdfFAGb5IYYiqKNc+3rpkyZIoD069fP58+0atXKQXBsmi8CUhAaKmDz3TlYtUp/q2JFOwFnR1qag2z2MAhzw5PqV+aRzdAPjhwRqV3bMeNTZPbzWhvedHPmuGy/erVaZ4FjItsd555rjJP6v6hfaocZ8oHAkL7qfakUmSEg8ucfboXZMMjLt0ZIE/ZJzZqa2cgDfxjZ3Fq1so+7wsM1y1FAMC/CKRvPBReINCRel4dhvyYzG9lFfurFBg0aCCBr1zopGWuokqI7q2XEiADPqwRkZxXJo8PH2dVyZgcORLo1WSNb3mzvm7j/7DMdzNBdxt7+gEhRGXwpvnhcB1+0EFBlazCIj9dztlicLOuaRRk9/msDP9DGJ2TuUxcKiMREpau6KUD1bmGBTWIqaDlcO8v7dPbkyZMFkP79+/s9jddff10AadGihQcR4Yxd6/eLxaKTTZuX7nZdmZbmkJUEUa+6YNky+4j/lYqqaFs1a6N99aeffiolkbhbt24VQGrUcKqji4vtRGd9Dsl995Xu9ERE5Bv1WFxh1QFGt87ZcmJsdZf2N/fbCLmi23R7GRkzRhyef9On2w9l8t8v9/5Zv0RbNGtZsNgzTp68RJVlaxoYo73ly8twkU5o0CC44y3UrIU2i0W6sUYiw3KkuMD1Xc3Ly7MPvNLT013W7dixQwCp6i5Brq71UQ9WySWXOC2/805HH640OMfwYZoyRT54r1jyMdszz3fKJIe3bdtmX2a2qYtNX1A37FqzQ6wUSbyloY/RvHeYVfx334nI5DccbVUg2LHcIIEQyU43x9gOol5E5PffdaHzjJfTYNCD9HKvj8xZqV9+CeycTHz7rZaPuvWkViUlBedMLv2otrioWOpXPyKfca99gi71y2lyCp24yatdU+QdNLv4US8T4nvXORRMTs/cZnOMLfwkRPaLzW//JQKyzdJOUrf8offy1wA80Zywdu52e1uZdOC4/HD9GKnAKb+TwAEjYYt9DBRFtos6PjVVpEULXd2jc4bkfhvhVwm4/8PGUq2qZha85prSEYUmTE42NtbNVy0Icnb9ekcbXWKEiQ/Mnq3HqFFDxBZn1AvB+sJ++YQIyAEaCdgkPt5Yvnev0VcLkylfZdmFq1f3+FHyJ1dTf0g30v73CWskPDRPh6f9VzpIL6fIDFvz5lIr9riAyLTPvfcLxo4da69/XXxdg0VhtsgvjeWqHlMFRNzno24ZtlRAZFBXH+NZb/iykd6I0BC5eUSmgKuFY7nCUAUXjbPY34M/Rw8VOTTjNP3gvxNnia//IHbsEBkUsVgEpNgaIrLdf8pgk8WvU0ck6+X3HeTXgw+K3HCDfm/YUDvyfvDUU+JIS/tREHJvH5g7ZZ3U55AUEqI1fna250ZOqWNPjK0u/VovFBC5sfd3XqW+PpGSYB8IyCYN0di61V4Pi3sm+5XP6kD9b0sHDTub109/Z5eX8MAD3+u6P9qJiEhiG53NvjVkgqpZgkVioj2coQW75O1HFnm/pJQUeeKJJ2S7j+c/f9oG7fxFGHEEkZHaugeI6dNFWrPdQSz4MLL++uuvpW3btnLAIz7PC8wZ6VkdpegHq1w7aIP91PbfahCz11/vdGxdlBChKjiZ4Zht/f333wWQbt26+fy5WrVqCSCbN28Wmam9i+SKNQU8PdjtsNl02g/EQxozcaIHOecTBnERbCu2bp3eDzCibYqLHezWPofS8vBhVX6CyCWXOJFkbpg2TbdpUDVTbJFGgzczwIF6fpq8d+OzesnN01w7d2lp9hPIfe5VO4ncvLkX8cvx4/Z6J4Z0c9wVGGw2lYaBS4/uuutEKnDKUZ+dVEfZGTNmCCDnnXeez0NWrVpVANlhhnUXF9tnKRtxIKiotRJx+CdZ+0o36dBgs4BIVHi2fHDDQ1L0Q4h/sicpSYotOv33WNe3RY7+WfpzGK7hah/yoDRsWLpD9O2rt/nNN40FjxsqxHYxgR0gJ0lkRnUZ0W2Gvn+DPvEfkuUFl/XdKCDy+r2/e13/xx9/CCBdu3b1eYz09HSpUqWKADJp0iS/v3fTkGUCIpeet9pzpakMbdVKxE+oZIn49FMRkEJCpDdL5dfxjrT0JonrT9W7Zs0aAaSh84NNcSh5osiWl18u/enJ7t3a1wiPkNpVdRDSovYuI8mAJh4w2+Xw0DyZ9vlqkV27HI2rU19sucFP1KhaKDbTuDnYgZXNJjKro5zTaIP0YYnj/X/mmTJcpIGsLMfx3DsF/mDEp2ykk4BNjmzf5bFJWFiYAJKQ4KqgWL16tYCbiXxOlp2cqEWiPPSQ0w5ffeWF1QkQ6elil1scOyaTJ4scwmjr/hrvsXmLFi0EkCVLHOE79erVE0DW+5AkLJ6xWi7lFz1mlSre+3Ve8ISOl+W220QjCsznEEh0wVgNsZNmGrJ57bUGJ/+S0zY7dujCSpVcWYpAQkRtNpHKlT3aoICQl2d3Nf/iXA3zGjVsacn7+cCy3/6WCHIlFeN85s0TEZHHBm6SgxikbYUwkUcRmVpJJM3tfJ+6TLdpW8n1uMuMXSuUOBTwCdsurStOUUHefzvHMSGcuTfgY9x4kda5NwxepiQjyFfcJuc0DVBZ7A9zvxQBSaSWgEhSkuvqPXu0yILI9ef/JLaJ3gmnjK9ipE19DYHv2tVzfjRYFBU5eNXr3IMrAiRnTaFqAFH+PlFQ4DDgP9zTCMW/vgRLD3cMbWrva/Tu7bTcZhNpZJA8f/whM2eKhIXZBEQuPuc3yf2uksv1/fHUdd5JLxGRJU71PsjrN/4qINKv40aP0xER+eGHH+zE19KlpX/3ZNPTEv9RQ7FadSLTfXx3YOthCQ1RMnTZbwFYimTsFrlVr+FUp572S/o7eDeSwGGMwdKj9EE/2+4VkZPe79v/Ks4SX/9FFBdLSkNN3/Y594iPiTcRsU82idWqdYWIOPTM5p/VGtDs5rffiozHCDm61/+MeiD49LnFMpyfHecx2Qt55Sb1XfdqFwGR0JACOfRx/cAVX8YshNRxzCCaHS1vvIRtr3a8comQq0YUiWx/R39noZcByJLLdN3fL0hiokiiRcNXxt/l2xerRBihba/ztDSJOyjFRYErdExc2U8zK61qaITm3XxzUPsfPSoCNtmHeo3Il08EfQ4ucOpgFv9gkVv7jjfGRsUya5Y4dNpOoYGm98eqSKMR/uBu+7qFCxcKIK1d4kAcsNlsEh4eLoAcOnRIyVqQ7bEdBUTe8ZewxvTOc++FmKlvnvPvWSIiIr9qRrQSvcC8YOpUx2sx6W1jEBsSYh9gZ2U5rIXatxfJzPR9rMJCR39je8f++mWwn4xlzvtueMmeuearL9zK4L3GjHPLliJ5eXL0qEMsce65nuOdrBp6EgOY5zP60ysSnK7fyWvG5B3yrcbM5JZFIiIyZ84cAaRjx44+D2mWi8OmfCk10X7Do8kqG1HgDYd/koLpjeSnhy63EwaBkD0nztH4iw8qPSSy5m6/2/pEcbFdPTKY2eLHEs8vTC8Tu2fHnrVOyoESZuNtNpHFl8jRz2rbwwG2LlobdIbez19T4qtvuzVe1y9ZskRMJZcvvPTSSwJImzZtpMgXWywi+7ccsp/runlukws7dzpis4JJneUNNpuGVYNM4Rr58pUF9lU//fSTANLLT+ztokWLPOvBLYtEQPIs4QIBi258n58xGjo4cak0qJGgTWmVIzL/6QukU0N9JpUiM2TBMxdouX7nbb03A12zuhUUODjspAvP0y8Xec906BPJqyXp85oCNlnJuY6K0u23SgVTNuGsngsEx4/bJyeaslcWT/P0efEg2w3MnTtXAOnQoYNjocvzs8mnnzrt8PffDgInCOWuiDiUt801xHThQpHVGPGn4z2z4Pbs2VPsVgEGYmNjBZBduzzJPRGRHz9eIJ9ynx4zCLXzLEPwbU+aWNuo1ye7p9vzgluMcnBZK7HZHKppF5+qnBxHWTnhpqIvKUQ0JcWxb4BEngueeUYEJK29ZkaOiUqX3FOlU/Dee+ViuQbN0CsNGtjLwMKFItU5IcusxuS0BZGrEZlZXyQn0XGNLYxJtOeucDmuUQUp8Vha5OWJzSBWuzU8LkV/XaBt3e7PAtr9+KETdrJjzZxtIo8pobmNNhIdkSW24jLIqkRExmi5XMm5EhPjXaW1YIFTpsern/YgnIp+CJEhHWdpHeiWwbEsWL/e4c/lJuwvkZxdtEj3Cw31obgPAvcZr+5n3T/RL008/f98Ij/XnkG8Hwtl7Fi39Xfcocc0mPzZs0UiI7SNvaDtfMn6WjMCz3p8iL0cXNl7gWcIo5l22Pg78dVEu6p++2pPkvWXX36xE18n3N/9QJG2TWRyqDwy5D0BkQEDvG921+WL/ZJwLtjxnkh3vYbJrV8W0IjqM4H0bhpOfkfIOMla8eKZ+dF/Cc4SX/9FTJggApIdFiPVOSF16ni24yIqBKtg+Jm/5u4h+/XXjpm/V14J6GdXrhR5ijdK11n1gtFXLXYNvxwyxHMjL1LfC9rOFxB58KIPdVkg6ZsvNdyZr+skIjrDUseI2vRmlSFFRVIcrh2ExuyXhb/F629NiRApPOXYrvCUyI9qzmw7uVmuH+LwkSo46YeNKAkzZoiAHKGOWCmSuVOCk8YnHjguoSEFEkuq/TqCdrsU7Vd9wEO6/7DgJOsusM9aIbaJyP2DPhYQsVqKZMaDV+j6Zs30d+yZGxzCgUkhRq/MyZ/KVDo0sDviuuLUqVP2xi4zM1PkUc03PSf2EgHfPuwiojGEoE6v5nTeqVNqGgIiGwNo1DZu1G1r1gzkDnng5Zd1934hxuxWE33niouVrDUPffBgycey25vUXapfwhBJKkGhl5ssUx4YpePAarnikgF6zRpH/eEUr7hjh2PGdPhwhwpt0SKRqdZrREB+O/f14MIC/tLwCWnl6rH31lu6ODnCCDczFAsrVqwQQJr6cKjPz8+3l4tUUwG5dYnLQLNMRIEvBOK/44asj1XyuIV2cvK7NuqNFyxW/Wq/tkhySh2Vl57uUCJu2GAs7BirCx7xUnc7Y983IpOQV656UUBcZ4KDwN7tGuoYFpIvWYnxHus3bdokgMTFxXnd/+TJkxITEyOATCvBifiO4Uu0qevuZQLDzF1/8cWluQxPTJ8uArKM8+S1+xzh3CYp0q5dO5+7zpo1SzxUbnM0PPFYaJzvNi4YmBXO83dJwid1pU3dbc7jDqkZkyQbXjvHMSg7V32N5BNPhbQ5dzDhBr1miULkVFrg57JqlPxwz/WOSTOzHoqNLVu8kYhD0Xv++cHva8xEXMxv8vWrnupMM7x6zRpX0tZUqPZ2fimmvSsCsj9UE+TMnu20Q2Gho2PnJRGRXzyuIc9y++0iorv/wqVGP3Ckx+YXX3yxOIcH2Ww2CQ0NFUCOuJvrG/joyb/kZ4brMb14UvpCerpj4H/0qIgMbKT/jPYxwnRG56q67avX2yOqwsO9KHHq1tWVq70oOP1hzRqxMx2lwaFD9ovrX3mRgMhPX6wK+jAFeQVSPSZZ/sKQ9zz/vH2dzaZNZBj5srX33Y6Xsyci05qIzKwr8iEOUmx8TTtxcuKE3i8ou7dQcV0NQevBKvl9zHStDxYFVk++OlrvTfeWhkrN8FPNJ0xCKJSj+7xHHQSMR9SPdBLXiR9RsD1UFkRmPnm7C+H08CVfarUVper88oSZV6NpUy9l10f/wWZzhAkHk3fBF0xVbuMKxxw34eiewHb+Rcmyk1SRiJACT9GsGX7Qtq39mha/eqVUjNQQv57NV8jk+661k15XdJsuBdMbufaV8vNFqhrvuzmj+9JLcllvNZsfffVij9OaP3++mOHkttK0EbZikbm9JXN8RYmJ1oQqPiwO5fCuo/bzXzC9hHHCX+eLROs9PpeVYrEEX6WXFqYlz9s8Lj88/EjZ287/EILhiaw+kj2exZlEdrbm3QVCX3yOmm1qcOyYZki32Ryb5eRoCt2cHBg4EJ5+2u04t94K8+fDmDH245WEli1hH80AKI5PKfOl7ImPph3bHAvmztXcq87wkqr7yYvfBuCrRXdwMqsqxLQEi5/iabPB8r36/WLNqb5oERw7pmlfhw71sk9ICNaWmka8Fbt46LmGFEc2AVs+JC1wbJc4B4pzoWITfvyrAwdn7wCgoHYDwqpWCug+eMXFF0PVqtTlGBcyny/GFQS1+7cf76CoOIwXa72FtSAfOnSAc88N+jR69YLfuFT/WbYfCoM7D0BTPm94EOUa4Nlpr/Pp3AcAmHDXKK7oPhOWPQD7NB08nTrZd62vmck5VNxAvxw9al8XHR0NQHa293TZaWlpAISGhmo642PHADhQ2AiABg38nHP37rpBdjb89ZcumzMHcnOhcWOXc/QJ8+RPnID8/JK3d8Pzz8O110KjYk2jnlNb06g/9xz88guEh2v67YYNSz7WrbdC5crw09HeZNSqBoXAZ0/43Ud2vMP7f9wLwH2jw7FngC4qgrvu0i7RTTdB//72fVq3ht9+g4gITet9//2wbRtcdhmstnUH4OIaa7BYgrgRO/Sdom1bl8W1jIzpqSHV9EvSIcCRuvrUKe9psp3Li1mGOLrXOFZVwGI/drnCGgK1+kGj6/QzgHTXFW8aQQFhtGcb2xdVgdSNwf/uzK8AWBHShzyiSlMNAFp+hg/X799/byy86hL9/HmR7x1PHYQND1JUHMKXyx4B4J57SncOTVvH0DjuGIXF4Sz5bYfH+piYGACysrK87v/BBx+QmZlJhw4duOKKK3z+zuFdR5nwh96o556PcF3555/6FxYG779fugtxR21NI16bRI6fcLRllSppG+LregBycnIAqFChgmOh8S6koOnKy1yezztPP1evp161oyx7oQ89m68EoEnN/ax48Tw6N96k25wC1hnt+iWXeBxq8GD9/Obg5VDVCrnAj+8Edh4FaXDoR+ZvGcAbGP2Wxx7TCic93dGGlBY7d+pnq1bB79umjX6wg/37bB6rzWfpXi9lZmYCjrILwD69f/uKtb/VtKnTDqGh0KWLfl+7NrhzXLJEP/v2BSAuDpKIA6DocKLH5tWqad168uRJAAoKCigqKgIc9aw7kpKgLkY7XbduwKdWubKjWV26FOh6jv6zcZuvXRQ2G+zWtp7zhtgvsXt3iIpy29a8kfv3B3xeLtu7PIgg0KABXKr9qFfjtD+rFqXBYcGMv4nMzGUg83TBqFH2dRaL1quFhHNd+ljk87FaVlYBTxyAhKOw2ti4DRCVDMuuhISZfPMNFBRAt26OolVaWJs2AaAx8Xw6w3jZjy+EYv99oML8QsZObgnA/Xdl6MJt+uzDKaQp+9nzd1LZTu7gYQDiaUyLFr43u+ceGD1av9/w6ZdsrrUOek3m6+M7+fD3OwCYMAG6di3b6bjj1Vf1ldm/H15/3W2lj/7D77/D6tVa1p97ruzn0LOn9injc2qTUd3oW/32ZWA7T/8OgD+4mMHDwjCqDwcuuEAL6vbt2h9PXkbfJjNY8MwAqkSnsmpvL0aOmUJBUQRXdJvBlNHXEVZwEJKXOY4xbx6kpmqj9tBDumzNGu69LwyA73/vxKk01zq2W7dudOzYkbvvvhtLUJ1PAwe+heTlfLPsHjKzo2nZEoYM8b5p/ZZ1uHOEvmjPvxiC2Hy85/mpsG45ZMOp0MqsoxsjR2of+kzA0tbRXk1eOADSNp+ZH/6P4Szx9W/Au+9qhdG4MeGPPcC0aVrhzZkD7zj1He+/X+uWuDj44Qewent6F1wA994LISUPwACqVoWUmEYA2I7klvlSdh+qRVu26z8REVBcDFOmeG5YfwT0mQEVtBM1sP08zmm0kZz8aMbMGw3HF8Dujz33M7FyJqTaIBwYfh+g9wTgmmv0p73C6Px2jtrFli0Wxq97TZcf+9OxTcJMAI5XuInR91togw7Gwju2KfH6/SIiAkaOBGAUE/hlWTcSDxwvYSeFrdjGl1OaAsIomaoL776b4NgGRc+esJzenAqJhkyBud8GfQySl0HOEQCmr7mSN3/TAcvYW+7mxj4TAYHdRke5fn2cW8sKFaB6dThCPV2Q6CBczY53ScRXlSpVtLFLTAZgV452Xv0SXxYLXHWVfp82TT9/+kk/R4wI7F5Wq4adLTpypOTtvZzCN99An9ra6f5te1M++wzefFPXjx+vxGQgqFQJ7rwTwMJ3EQ/qwkl/uLLlzshNZPlvG1l/oBuREcXce59TBfLZZ7B5s7LG777rsWvv3jBpkp7/2LFahjIyILd9D72utWuUNAsU2406oo3rOxWn4zVOiDGqT9J7XBLxZS4PDw8nPDzc2FeJgmRquhz7H0dsLNvqaQ/LtsoKR38L/hgLlKD4tegSwsMD42x94cYb9XPKFCgsBG59EUKA+DxY9avnDmKD1TdDURZ/xj/GkaQYqlcHP5yTX1gsMLCP1oPz5hV7rDfJhezsbIqLXdenpKTw8cfaTrz88stYvTaKinde2EdhcTj9O23ivIs7OFYUFMAjSt7xwAP4HT0FA4P4qsMxTiSH2heXmvg6rvXpcZu+GzVrlvH8TOJrwz4QqFoxjQXPDGD6A1ey9pXuNItzIhL+Bopt0K4dNGrkcahBg/Rz5eoQ8gcYo+ypkwM7j/gfsBXmU2VjJm3YSWFMVXj2WUehXreuNFfngEl8lWb04UR87Tvozrj4fpZeia94vZ/7pQlWq5fJje46iRAU8ZWVBRs26PfzzwcgNhZOWLWM5Cake+xSvXp1wEF8Odep9kkDNyQdDy0V8eV0Wkp89b5I/9mR7LudAti6GLIFQoFzh+u+TsdywT9FfIGdSTn38FwqkckfKzqReTIzqENMmZTHTXyPFVHyskkTl/U33aR9pm3bYEX7u2HeXIixwEHgeWChsWFPMCcii9c+wrhx+r20ExIuaNwYgKYcYO6iSuxK6Q3FOa7khRf8PH4dx1JrU7NyMlfd1RXS0lwmOluzkz07grtfHjhyAoCDNKJlS/+bfvihigZycixcektXpq29jnue1DHBSy+psKC8UakSfPqpfn/nHcecny8UF2v1B/Dgg/ZmpEywWuG66/T78gijsl7wV8k72mzIgi0A/Mpwrr/eyzbVqkHnzvp9/nzIVbK9e9N1LH6uHzVjtG0f0e0nJb1ClWQ3twMcY8RrrnF0gNesYcCVnWheJ57M3MpM/sx1gjAmJobNmzfzugebGADykmHTExTbrHy8QMcuDz7oY0xt4Jk3WxEZlsvKHR2YM2WD942OzYatWq/NK+oPIaG8+GLwp1dqOLVXc7cOInnznyXs8P8TZ4mvfxpHjjjYrXfegYgI2rZ1VJTPPQfLl8PEiTpgtlhg8uRymO11QmhLbfjDsgvhZPCDeRO5WTkcTa5FS3brAnN6xWSk3FF/BFx6EAYswnLeZJ54SgmFTxc+SU5+FGx6VCsSb5j5tX52rgnRsWRnOzgMcyDnFQbxdd05uwB49osrSMuOhWOzdOBeXABHf0cE7vlwNKmp0Le60VK1KSPxBXDLLQCMsMykou0U33y0M6Dd5v64kYMn6jM08k9iTxyC6Gi8t0Ilo1cvKCKMvyzG9MaMUhBfTo3WpBV6Ho8MeZ+7L/zCsc1B49PLqLx+fTiK0YE+4ej4mB3vvLw8j0EuQGpqKqDEFwDHdRYxQeoRGhoAuWH2bH7/XdUEf/yh/48YUcKOBiwWh+orISGwfdwQFQXXdddO94b0Jtx/vy5/+ukSyq4X3H+/TgC/dPg+bKEWJSsWTvS+8fY3+WCWksQ33WSlRg1j+aRJ8NRT+v3tt32OqK+4QjuOAKdOqVr0tVnnKMl+/HhwRGAJiq/EYqO3d0Jng53JD5uXAZM5eHNRLBikWWJxnMux/w04OUh7oc3j90HCL8HtnHECtuh78BcX0bmzH6I/AAwaBDVqqIhx7lygdlPoYdysbzxJUHZ9BCeWQmg041a8AGi1VqZzGFoZgLmrmmsd7ARn8sCd+Hz33Xc5deoUnTt3ZrgpXfOCxAPHGf+LkrTPu8+gjxkDu3frTXj++dJfhDuMEUsUeZxKdpTZkhRs4IP4StZ3Ickgvspcns2Ck5oB6bUAC1HheVzZ4yeqVUp12tACWwzSx4vaC3Rc3Ly5CkfXtH5UFy47BFmpXre3QwT2jmPbgbY8kvue/tozz6hUqFs33aasxNcubevLSnztP+IudQiS+DqsA/6DNKJBA1X3uqA0xNfKlTpSbtTIPutjsUBupaoAFCV6kgruii/znYqMjCQ0NNRje4DkE+HEYShz6tUL/PywC9FUtdXnSiXV022wZ43vnZYZhHuTaIiq6C5qc4VJFP0TxNcFF0CrVoTk5vBo5Q/JK4zi1++2BLx7blYuPy9qzygm6AKjf+iM2FgHaTF2LNDaAq8INAAygWT0nnYz9xDmrGnDwYMWYmOVSygzjHvct0E8AJ8tfUmXH/NPnnw6Tvtzd1+7nYgKEXa1l4k27GDPbj8EaCA4puW3JMUXaF9p6lSd20hI0HtTWKjdwhdeKNtp+MNll2nVWVio89X+ON8pU/Q2xcbCE/4F/EHBLEMTjmuEDKv3lLzT6l+xJBWSRwQrKw7yVf0rmwiq3IpyMHUdGmxl4+udmf7Alfw4+loH6QWO7XJyNNzBPMmOHY12KRVr/AHuuVEnMMd8W8u30ipYbHoMClL5bdcDxB+JpWpVJZj9oXaTWtx7tdZZz79cwfu5HP0dturXeQzkppu0XTxjMNq4Rhwk3FbAtKmFwU1I/z/BWeLrn8azz2qoVe/eLlPmt96qvEZxsVbOd9+ty194wSUKqVxQv11VThjhE2z1P4PjD3v/TqApB4igAKlQQWvt0FDYuNH3NIeT1PfK29rQuDGkpFXgm+1fqbJgxbWQ4WXf+av0c5DejJ9/1gi2pk1VjeITBvHVxrqLtm3hZFo4r/z8iqqX0reqfLswk2kb7+TnP6sRGgqXNCtH4uucc6B9eyKkgGuYypc/NqO40JPgcce4cbrNy7U+0gUjR4JzpzoIdOyo5MuMIqO8Ldwc/EGMRiu/MJz52y4E4IbeboTLIePznHM8dm/QwIn4SnYoDZ1nnL2pvkzFV9Wq2rEnRfc9Sl3q1g1A6Nitm061Z2fD449DZqYOUIOJFTNlZaUkvgCijmmn+0i4drovvxxeey3449Svr522NKqyqro+Bz5/y3PD7MPsXbaAXzcoOfDwIxatXB5/HG64QcM2L7sMbrvN7+89+KAKwi66SKNFq9WvoCG3AGv8DGScIeKoD9zeKXMwf6TQ6BQlq6LPmdDyVi68El8GaZYk/z7iq+Ztl5BNBeoUJGLbsFVDBwPFL59BEaREVWcPLUod5mgiLMwuRHXMUVxrEsRrXHvp6dvhb50hja8xnr/mKTGjysPS44JLG2G1FrPzaCuObFnvsi4iIoKwMA15MAkFgOPHj/PZZ58B8Morr/gNd3jvhZ3kF0bSq80W+l3eybEiN9fx4r3xhhIu5YWoKAorKDFiOZlnX2ySJYWFheT7CJc2y7gr8aXvQgrViYwEH1FpgSMiwkEu5Zp9D/d7aIEigS3Gcp8jH0e444/Hr4IaIZAHTPFSFzkjeRlk7uTkL7WozxFORNYn9EEl50tFBLmjqAj2GpYIZQh1bM1O9h+rD4WuBJcvJapX4uuIEk3xNKZZMy+/ZV7v339DXp6XDbzAByNUWNXoz530rCt9EV++whwBipLzsSLYQsJwzJgEht699XPHDkjOqwqNDRJ10QzfO61VRSvtG3HoEBw6pG27177dP6n4slg0wgK41/otIEyZGvgMwJ+TNtMxbwvN2YdUrAhXXul1O1O1NWMGJB9JhRrAi0APY4POgNPjGztfdxg1StViZYah+OpS9QAA3/11Ppk5lSDRN/G1eckulm/rSGhIIXc9brx7W7e6bNOanew54KmkDBiFOXBCyZRAiC9QUfsff+gnaGjjt9+WKngiYFgsKqqPjoZlyzSk0hsKChwE3BNPOM6xPNC+vc4zzi/qr7rAIwWwvwSbhR8/B2ABAxh8RSXPMGMTJvE1fz5U7w0V6mG2JXWrHuPKHj85kV4WqFAfavTRf3//XfvjjRtDjx46I2AqyNasYdTDnYgKz2FLfEtWzXYtPwHDVgzHF8PBKbDrQ4j/HrDw4YKXAXX58CF2dcGTb7QlOuIU6/e24fcJbu1ScQHE/4ltt173opCB5TqPFhBq1IBq1bAitGQ3kxcNPBvu6AVBEV9vvvkm3bp1o1KlStSsWZPLLruM3bt3l7jfkiVL6NKlC5GRkTRp0oRx48aV+oT/p7B+vcNY5YMPXGpeM6SoRQuNgszOVsLrdLxILVo4fL7YWfrZ1T1bT9rDHC1t2qhyxAya9qX6ckJoqFp7ALz/00iKqvWHwkxYcgnkOfmPnTgE2w2/gKvudTn8jTeW0IAZnV/Lrp189JEu+mzuPew82kpVX0d+5kRGDe77Wn1enn0WYhLKkfiyWOweDrdbx3M4uR5zpvhvfI7sTeSPlV2oTjKdjxkd3bvuKvUphIXpeOcvLsJmscDhfNi8oOQdnVGjD0TVY8nOvmTnV6ROlaN0arjZaQMLJOhg1Zviq0EDp1DHNBsUaEc/MjLSHq7kj/iqUqUKFBdBqhKCR6nrP8zRflpO4Y7jx+vn5Zf71zi7w1R8HT4c+D7uMDrdz3zdlDff9BO6HADMKK0XTzypX/7aqaogZ2x7lY/+vBcRK8OGQataaWqE956qLHjmGe1VB3ASjz0Gs2c7RTwFO0A9dkzjJENCPMLKatTQR3TcDHU8qc/buVx4C3f0TnzpPUimBpUqldMAoJzQtns0f4YoiZA2v4rOFAaKWb8AsCjiIsBSZuILHErDX3/VR8NNz0EEcLwI5hmK0OICWHWjeiLWGcZXc69BRPu8XgfyQaBKVSvdWqmaYN6vRz3We1NJvf322+Tk5NC9e3eGejV1VCQnpDBuhhI8zz9TgMXq1EBMmaLeIo0aeVVblBXFNZV0DU3Ps8+8OpdRX6ovr4ov411IoTq1apXTQM1kJXbmuVgP2FGhHoS/BJk5+nKa77oXmOGOc+ZZ4SJjsmPqj/5/f+84yIEuBtm5ZcTLjlByk5TbtEkJrNJg/36VWVSo4Ki3g0HTpkhoKBXJplLuKVIPx7usDkrxlah11EEaeedaGjbUe1xYqORXIPAlhaqlqt3QjByPXUziKyVF+1QlEl9iIzRNJ5gKa9QKuqGqXl0jZEEH/XRQEoXVfiZZtxi+bl272cMcu3TRsDEPmDfzwIGgzqtciC9QqUh0NDXSDtGfRczb0IkUg+QsCVN+hFvQ+tVyzTU+R99duujrUFAA3/zcURdGAvcDLwBOEw+Hkhswa/MwwDFhXmYYiq8qaQdo3RpOZYcxYdktkLEdsr1PAH76nhL1V/ZbR52mhhTfVHwZMYmt2cmeQ8ERqS6IXw8FUIyVwzQIWF3TvLlyNE8+qbzLmegbNGgALyvPwuOP2+cxXDB+PMTH6yTdAw+U7+9bLCqoSqcKe6MMIvK38X73sf2lAoNfGc4NN/jZ8LzzdDY9KQl27vLwcHY6C/3o8pHDD9UMc7zuOkej1sNgdFevpkqtWK4bpKGFn39SirDYhJnwWyNY0B9WjoSN2mHekHUvy1bHEBoK990X2KFqNqjB/SO1rXrhtVhsxU6TgsnLkK1ZWG3CQRrS97ZmJl985mCx2MepbdnGyr3nEb9q/hk+iX8/gmrBlixZwn333cfq1auZN28eRUVFDBo0yKcfD0B8fDxDhw6lT58+bNq0iWeeeYYHHniAn8y4tP+vEHGMWG+80dHJc0KlSjB9us7s1qmjEUkBWncFBWeDe3ZvL/Vxdu/Id/h7mSFM5ohq0iT/+l4Dt9yifb+DBy1MS/wVohvDqQOw/EoozFXW/tt7wQbUC4d253PsmDZigP/KGewNLikpXNgpheHDoag4lIcnfogcmAiHfuS+CWM4mVGRjh3hmfsyHJ4E5eVQeP31EBJCN9t6WrKLcV/4vy9ff7ibYlsor8S9gbWwUKeoyuhW2rMnZBDL7qrtdcGPnwZ3AGsINLqOPzZdDMDQjn86DcQMlcARQ2LrI9TxBDUpxqq2FIe1Q2SxWOyqL28Eh0uoY8IuKNbdk4gLjPgCTyOHQMMcnU8eSq/4Sk/XwTbQfngTnnoqsNkmX+jSRcc9C239SYmuocbSXzglt8jaR+qWX/h2qQ7snx+xXeubuXO1xzd1qrqulrZyMQfDgSq+TLVXs2Ye8XFhYWoZkWwqUFN1QGmxWPz6fJnLXDxqDKIgmRr/KrUXKMm/qaXGHkRuzIcEL15avrBMw6MnZ6pKpzyIr86dtXrLy1P+k8o1oW8jXfnVmzpTuuY2SNsEEdUoOGc8X3+jL3x5Da4GXqDk97zFni+DSTCYhMKxY8cYO3YsULLa68OXtpKTH03X5jsYfJ1TvSni8BQIwhczGFjrKZFUIS+Hwpx0QBNzRBlT50ERX2l67cnUKLu/lwnT52vFChfrAXpN1s9L42GNnjfDhvm9R/376/t74AAcudAId1yR4EnCm8g7AQkzKPgllJjiDLbThvrPOsWbtGihqubcXIcnYLAwwxxbtSrdzEJYGBaDnG/DDvZtc/XkDJj4ysnUCR78EF8WS3CTCDk5jjBQN+IrtH4dAKJysj36XcEqvopzTlLhlBJflrqlIA9x8/nqbgxqN/sItSougj3p+r33MDvx5TXMERzE1bFjWlYCQU6OPTFOmYmvypXtcVLPRr9FUXEYM74pubxmnsxk0YrmXI3hN1oC8W6qvr6Y3ARbZH3AojxCS8Cpmvhy0V2IWBkwQEr0vAoYBvFlSUjggXsKAfhswaPYbBZNBuWGlCMnmTRHxzT3P+zEVpqKL6MP1pqdHEisS1FBKYntXVr+j1CPGrXDvBOjPtC5M7z11pn1/nzwQY24SE11TPKbyM5WI3xQgUNZ+oS+YIY7/pqr/XYW+iFF9m/EujcbGxbW1BjmP9IoIsLxks+b5+HhbEeFerq8vtHnTkvTpDLOJweOTo3Rp7z3YfUlnL6wGycOe2EMfSFhpiZ7yPG04fjwB/2Na64Jzrbwsdc6UCkqk7/jWzLzS6c+79HfSVis9eMC60Cefe40Sgj9wSC+LqqngoopP1rPhju6IaiewF9//cWoUaNo27YtHTt25Ntvv+Xw4cNsMM01vWDcuHE0aNCAjz76iNatW3P77bdz66238p6pNPj/ipkzdforKkpDLHygQwedAdizp3xMDr3BmfiS/fElbO0bu/eFOjI6mlN8l1yiHYOEBOw9GD+IinLMdLzzUSXk/N8htBKcWAIzayhrP9uoKDsKJMxk8mTt2513XgB9mOhoR6ja7t289x6EhxUzZ8tF/Lm0EdOWDWbG2qsIDSlkwlsLCN9veHDVqaNB9+WBWrXsaSdv5jtmrepKwu5jXjctKihi/LQWWLBxQ5ERGlAGtZcJM2TgV4tBAs1ZEtwBRJDE+faZxYvP+cOxrkI9iHsfCor02XsxQ27QAGyEkBJqEBz7HTPc/jI7uoQ6xus+mRGVKSIscOKra1fHOVWt6qdH7QNlJb7MmeaaNX1MYQePRx8FwcpnhYZh2HfTHCu3vsy4+XeQW1CBhxr9QvcHz9VzaNhQPWLK6uhqzs6tXx+YMmO7Gznuhlq1nIivNEcZ8GcK7nXwdlK3+zcSXwCWIReRTmWis3Ng6WIoSC95p03zIakIm9XCfNsAatcuIaFDoOdicXhc2MW5FxuD8Pn7YdlIOGiEMje+hV/mxHHihLZJfqLfgsKg4aoAnbexG7ZTrvWhSSCYhMKbb75JXl4e5513HoNMqZEXpCam8dkUJbueezLLVe21apUmdIiMVG+B04DQBtqjrsMxUo44VMslGdx7Jb5S9V0wFV/lAtNIePdulSC4ZxmzWFUSASU+6IoVHTzab5lXQ1wo5AMT3/S+w4EJcLKQkLn670c13qBFaydizWp1pFgrrc9XWTI6mnD2+drtSrqb9Y37c8zIUEW6nfjasw4E8iwRJFPDt0IyGOJr9WpVh9Wrh7u0IKppIwBCbcVw3LVPFyzxlXIkmdqop2doo+D8vUy4+Hydb3jx7c7wnlF68zydvAkDul9sF7V5NbYHbcPN+xyo6svcrnJl3b+sMCQj/XMWUI8Epswo2Ybil2+3cGnR71QkG2nRosSsNtdco13Q+HgLc06ZCaNcB9cFReGMX6R2BffcU44D77g4rSdtNm7se5iYGNh7tAFztw6CRE8f3vHvbyW/MJLOzXbSc4gxFhBxKL6GD0fCwogmh9q2JOK3l9JbeK8SaQdpVG45SU4nQkPhiy+0vf3+e1i40LHu009VMNW4Mdxxx+n5/SZNlFNawABdsM7PeG+SjtHX0IMBN9QteV7oQsNqY56RndTXREp9p4nmmTO1Dmvf3jFmBEef0gj77nJBa7q33EZBUQTffFhCRlgTbpnnnXE0tQ5TV6v53cMPerGasdl8CjWq1anKwzcpqfTiWzXUqkYESfiNwr81ysU6aGCpBMblAkOg0buG1nGTFl2EpG7+h07m34kyeXyZjXtVPw3HqlWrPDqmgwcPZv369RQWFnrdJz8/n8zMTJe//ynk5ztcCx9/vESz0OrVTw/7b6JpUzhg0Rmdgv0lmNH6wZ74WE/FV2SkI7QsgHBH0Mn36Git8+asaQstjMF8cbbWYSZH0qEQll3J919rOQzYGNzsBO/aRbOImTx8kVbwD/7wMfdNGAPAM5e+SafUgbDcOOfyCHN0hhnuGPo1CIz/0Pvs558TN3DkZB0ur/AzlVKOaAfv2mvL/PMm8fVlijHLsiXdo4PsF4l/sXtHDgdONCU8XBgw+jHXxi3RMALu1MlrTI45WD9qhjsecoRMB0J8ValSBQ7qbH5yaC2XY5YIU/MN6qvnw9DXJ8qL+CrrTLMThg1TgcQXBbdr+OqOLJjzBux4l/y90/hszn28wMt8ePByLKdOqTxj/XqdfiwrWrXSUW9OTskpi8Cnv5eJuDgn4ivd4YEUiOLLZfBmkGYnqPnvyejohG69I5iJ0QlcVVyiUTAAP6lNwJG45pyiEueeW37eJNdfr8dasgQOrZoNlaepb0wG4PxYd73PuI9VxXP77aryKQ+c2zeWilHZpGTV4O+FrgN/51DHhIQEvvxSU7GXpPb65JW/ycqNoUPj3Vx6i1uYnuEPxsiReOZoLx9Y6+hsVW0SOX4kw77cXcHmDq/EV4Yq4sqV+Kpa1aFkXrnSc/2uXVpfhYc7Yhn9wCXccYhBWk2b5rmh2GDfF/AzhBQWsZKeWIZf6lmWTSV8aX2+ypLR0YQz8bXPdZBkPscSPb52a3jMIUsjwOK76g+G+HIOc3S7cTUaRJOKYRB00HWgaGZ1TE1NxWazlUh8JR1Opx5KTFgblI74Mkmrv/+G9GZDNEwvH1g3y3PjpQbR2qwiiScj2btXL8+MyvWAxRK8z5e5XbNm5VOBtm0LfftiFRt38QXLtnXgyN5Ev7tMmR7hCHMcNarE86hQwd5t5PPp53lV1Py85XZOZNaidm249NLSXowXWCx2cjX6RLxdnPbJnAcgaT7YHGO5ooIiPp+oMYf333HSMdlw9Kiq3UNCoF07LEZcYmt2smdrECoeZ8RrSGyg/l7/BvTo4VDv3XOPDgfT0jSvEGg4pEfii3LEdddpVvciQtTKYJt3QULRr2p/UmKYownT52vJEr0o8JxIsbqxZ85hjs5o2FAnhgsLNdQduPe2dADGTQrMF9k58zwAE4HHgUcg6slc4osbkxJSjS6DqyoBHh2tN95q1TJao4bDisgND79yDrHR6ew43IypY1bBgQksmtuQpgUHsGFhyLsXlHx+pwtGe1X/1G7CwwrZcbQtWxeU3rv7fxGlJr5EhEceeYTevXvTzpmpdUNSUhK13HpptWrVoqioyO4x4I4333yTypUr2//q/2PU6WnCp5/qjFPt2uWbtqOUiIiA7Dgjt/YR32Gr/iA24UBCLVpgEDjOag6TkZoxIyApetWqDrPkt98WOOhU+RwC0lH/mZbw96EObN1VmfBwCVy4YhJfO3fAhgd5dvhrxMUmsv94M1KyatC+/haevcwwPD5dxNfFF0O1atQoSuZC5jN+ekuvcu8vvtRX9IXqRkjOjTeWg6uxtilNm0I8TciqWUVDR38MUIUpAtteY9YmVXv162ehYpM+ro3b5s26rRdje3BwR/FFRrk77JipNTvg3ogv11BHwyAeZbyCUr688IIaKrzrJWtdSfgXEl9WKzz8MCRRm/nhxujz42dh8xPMWHIFYzJG8zIv6fL774c5c5RRLw+EhAQ3QA1G8ZXheCeCJr4M0uzfqvjq0QN+REls22rg0C8l7zRfO6mLo1U1UR5hjibq14d+/fT7xM+2QihgHt+JE9l1rCWLVtbEahVuv738fj8sDPp313dq7mzXd9+ZKHr99dcpKCigX79+XHCBlw6mYWSbufkHPv5Bid3nHk91VXslJqqPAARu8FEa1HYQXyeOOsptqRRfxrtQrqGO4GAUVqzwXGeqvfr3D6jdMQ3uFy6Ewhse0n9WHYNUN0Vz0nzYdwAW6b9P8RaDL/Iy8C9rZseyZHQ04WRwvy/e1d054FDHfVrn7bNpnW8mIvSAeb179uho2B/8SKHi4iARI0TgiOukmqn4stlsZGRk2NtZn8TXkSzqYtg9BBMT5HY+LVpo12H5mnBoGasrlv7mufG61frZoYk9SKBjxxIE98H6fJ2GNtjMYn5vyFjCpJCpX/n2P05OSOHAukqczzLEai05pZwBM6x81iw4ZPNU1Ixdr2T+HXeU34SEHaaq8MABRo8Gi0WY/fdQ9ibUhJTV9s1+m7CehJS6VI9J4dr7ujr2N9VeLVrooMPpvdqzo3TjDg4qsfFfIr5Ag3zi4vQ1f+st7Yamp2uXyEw0c7pw9dWQa63IarNx/8NLVveTR7Bs1vH51oZDfHXjXdG+vQ4scnJUjVoSEhMdkjf3yXyLxcXnC+Dqu7tQtWIqh5LrM3uSawIcr3DKPE8yMBs4BhyHqjlp1OMo1YpT1UIgM1PPu9ApC2JqKtx8sw5G3ZKNxNaszGO3bgbgpbdrUrjiThbP6AfAscr1iatccnTTaYPxXoUc2MfwftqfmjQ14my4oxNKTXyNHj2aLVu2MMVkbP3AfUZWjAfga6b26aefJiMjw/6XUIbsaf9KXHqp/r3xxumVcgWBsFY6+xKRlefbk8MPkhOSqZGTTBhFSKVKrkayvXsrg5+ZCb956eh4wcMPqxBn8WILa7c6xXhuNj7bAmHww3KdirhkYErgGVBM4mvLKsg5QqWoU7xxtXoihViLmHDXKMJDCwGBg0aHtryJr/Bwewt3V+gXHEutzawfXEOGD+08wuy1XahFEh2OGYOScghzNGEq6zfVuUi//P6H742dcWIJpKxk1mYNfRk2zMs2xiyNN38v0PFgSAgkYJSTI4533J/Hl0uoo7HPgYJGQJDEV2SkZjAsTRY3s2ynp4OXcywRp6PTjfadq1XJ55N87YCzHOQI9Ji4lsv5hSJrCLx3H3zySfn3igNVKvjJ6GjCRfGVB2SnA0ESXzYbZOisYDI1/pWKr9q1YX+DCzhBDayngLm/u8yceyA7HTbpzPj36dpRLE/iC5zCHRddqv0kM4vaeuwRA18u1DiMYReeLJcwS2cMHKyeb/NW1AWbg/Q0CYStW7fy9ddfA6r28oCTke2YN3eQnl2FVnV2MmKwm2H+V19pWG6vXo4MUqcDddRrqTaJHE90qBeDJr4K8uCUPoByVXyBq8+XOwIMczTRqZNOlJ86BausV0GdMCgEfnjddcO942AaYINZDGWF9XwGDPByQLNe2bo1cP8mEyLlE+pokGZt2MH+BNdORknEV2WzfYnXOv8gjYiL88MhVqvmaBfW+xnc5eU5BpdeQvXj4tT3EoAjrkru8PBwez158uTJkhVfiQV2xVdJ0Qn+4OLz1clgKdZ5aS+2Gu1j1x4l+3uZKK3iqzzb4OHDoU4dqhancgU/MeUX3+z0jG92cKNo6Lhl0KCACcWWLeGCC7Rof/klLoqaHSf7sWSJhZCQ0xQqZ7K18fE0awZDhuj4bcy8+1yyO376udbhd161jcjoSMf+pr9Xe8NX1um92rO3lENRp0yp/yXiq3Jl+Njwf3/jDeyJtspitRoo4uK0DC3EmDRatNhzox/fJ8RmYw/N6Xlr+8BEkVarZ7ijP0ybpgW5Z0+PUG3Aw+crqlIUt16+BYDPxwZQXqKcxo1mlFBj+GXocLqzhkur/ELx6xZYOkEZyAMHdDI7MVETI73yihJwX32l5+hWtzxwx3GqVUxhb1ILrv98Es2SdX3VHsnqK5Yws+RzPB2oU0ctVIqLuX2QjpemLBmC7eTmf+Z8/oUoVW1z//3389tvv7Fo0SLqldAQxsXFkZSU5LLsxIkThIaG2mee3BEREUFMTIzL3/8UWrTQ9Fk33/xPn4kddTvGOaTx24KXRe7efMw1o6NzTWm1OlznAwx3rF9fQ28A3v7dyFZ3CjB9NLtAUXEIk1bqRjdeujPwkzU7wXscs4M39/mO90Y+yvQHrqJz402Obc3xkg91Splg6NYvsf1BZdIZ96Xr6/jVB/sQsfJ67dewmIM0s9NQDjDDHX9Cz4NVhyE3ACJn22tk5MSwbLemI/YgvkRKVHyFhGgf+ihGhy/RQbYGHOp4TI2G9xVqo1neg3CfiIlxEGalIeVPE/FVIbKYey4cx19cRHJIdcgCedpCs8L9JBJHzhMVoOlvqogpb5izcyUZ3CcmKmFoteLLebdWLcgkhiKL0QM8ojPnvvx0wAvxlXECDPuYE9T8Vyq+ALr1DGU6Rij4shw44Wem8PexUABFsWEsSD6HkJAy57jwwBVXQFRkEbsTW7H+QFdohvYScoA0yC2IZMLSUQDcfW2AXhtBYOBwfYmX7exJToJj4G8SDGPGjKGoqIiBAwfSp08f152djGyz8yrwwWxNHvPs8NcJWX21oyNaWAhmZmlDpXHa4Kz4Ou4g8oImvpIcne5Uqpav4sskvtavd53ZPnnSEf548cUBHcpqdUS8zJlnhWFGvTDDaRCQcxSW/QprQCwWnuZNevTwoeipV08rhOJix2RKoDh2DLKytLEJNN2bN7RogVitVCGdrMQoyHfYQfgi4z0UX4e1I+HT2N4ZgUwirF2r4US1anlkxgVX4kuOeWYfdvb58poYxAlJx4rLrPgCN5+vHsa7u8XNXqGwAPYa4b+9A/D3MmGSMv8k8RUWZp+YHM1nbNjbhr2bDnrddOr0itzMd/pPkNlkzTC58eM1y6MJI9cHl1xSJn7SN5wUX6DCcYBvl9zCqf36oLau2MPiv88hxFrEPU+6te+m4suMEDKIr9bsZE98KaIYRJAk7SPG07j8jPzPEK66SpPeFxQop3/uueUcnuoHI0c6iC9Zd9jDzypnmoYg/8JljLwhCJrArPwDIb4mT3acjDd46VPe/aiWwb/WdWH/34d8H1sEUpz6ogbxZesCT216i3V0Z8DFiwhpUw/Ou0Hbh8aN9cWJi9PZm+efd0RGbN6sna1ffjEOVEyl/Y/x5CUanzp9zVVciCYKqNDFmKDZ8NDp6WuXBKfMjn1rHyAmOpuEkw1Y8Vsp7QL+BxEU8SUijB49mpkzZ7Jw4UIaB5Crs2fPnsxzewnmzp1L165dCSt3Le5/DOVlzlIOaNHCKbPjzgBkpG7YsyPD09/LGWa4419/KZseAMwo0J/XX87uYy1gKpAJ1AV6w4LtA0hKr021iikMGRKEjNMkvhKS7YNjq1V4dNgHXN7tF8d2eYAZjVteGR2dcc450L49YbZCrmEqc9Z1IX6bEimF+YV8PaM1Voq5Nt/IgFqOai9wKL6+23cBUtmqg9s/xvrfKWU1HF/A3K1DKCoOoWVLL33HgwchI0NVbX5m2uvXdyK+jqfblwcc6nhcvx+lLpUrO/xtzwhM1ddhz0FFiTDDMcqZ+CJ5Gff1e5OQ0GK+KNayYrUJq+nBmPPvJaZ9FuQkqPdBecMcrG3bpumJfMFPRkcTSlJZSA81iPhj6uPhy0/HeZmd+Dqq4T15lgiyif7XEl/nnusId2Q9sN/PLOHvmtzicNNugIUOHcpfMFypElw2RGfRv19+k4Y7mvfuGExbfTVp2VVpWP2gPaytPNGydQj1a6ZQUBTBsj8dIVomgVBgjPReNvPCm3Azsh234G5SsmrQtNY+ru35o25jdkR//lkJ2Fq1lOk7nTCIrzoc4/gJR3fL2bPMGzyIr0QdqKdbKlNMaPmW56ZNNUSloMBVZfTnnzog6tBBFdsBwiwXc+cCNz+k/6xOgmSjrtz/NfyoA61l9a9nKx18lyWLpfThjmaYY9OmZTPNiYzE1ljr6mqZqWQ7kZDeCEwR8SS+jmhbFRTx5e96/fh7gRZtM9Sx4LCnpYhJfKWkpJSs+DpudRBf5aD42rABsrtfqf/E50KWk6/sxr/U+ysCUhpeZI+Kd+e4PfBvUHyBhkWFhdGLVXRiE1PGH/TYJGH3McK3p1CfIxTHVlGlWBAYPlyrlRMntCoDVViadkQmMVbucFJ8gfr5NW9WRGZuZb7/vQPsGcdnb+l9vfz8ddRr7paNy5/i61ApKrTcZEjR+j7B2tCraOjfDIsFxozRhF6gyq8zNSQcMQI2hfcgl0gsaTbY4OQvmp+DdZXW1QdaXeg7LNsbTMXX+vX+Q7X371fy3mp1eEC7o1s3vSEHD8JxneRu2rEhF3Vfh4iVLz7w4UlclAMrr4e/n9L/C8Ecmq6s0Ivdia2Iicrg1r7fQJePPH3HnDFwoE649OqlY5rLL9d0nMcWQc4R7hs4hlqVk2jDDuqQiIQBLQDk9PW1A4FBfEXs28GIITrenjy94tlwRwNBEV/33XcfEydOZPLkyVSqVImkpCSSkpLIdZKgP/3009zkFK9+9913c+jQIR555BF27tzJN998w9dff81j7rlcz+IfRcuWsB+jE7B7a9D7795lcxBf3jzfWrbUiqy4GH78MaBjtmkDl1wsiFiZOXkEmBlQbgFC4YflSqZd2+cPwuv6cj71grg4VezYbJBRC/fMOHaYtiS1ap0e82OLxa76ejB6DCJWvvpQOw6/fbuepPRaXBs9lejUJKhSxXcDUUq0a6chFxmnQknr2EEX/jzZ/07bNGRl1j5VSngVAphqr7Zt/Q44GjTQNNQAnHCQJQGHOp7Q9Uepe+YzqJTW5ys/37FPeXe6cxOJiz3O9edN4nPuZU94cz7nHvqzkFsum+CyXbmjbl39s9l0ZOMLJfh7gSO9eIrF8CBLPAgEGep4TN+jk5ZqgOVfGeoISnyt4DyOWutqJrM/pvvunCzTGfNlsZqNyFRsljduul3v+4+rrqWwKBTqGCuOKqEEcNdFUwmJK2k0GjwsFhjYVwfCc+c7OqTOqu8hQ4bQ0/3inYxsc/KjeO9P7V88fembhIYU49IRNU3t77rr9LoIg534qsQpMpIcYayBKr7sKhzjHUgxQoDLVfFlsXgPdwwyzNGEOem/YQOkNL8c6odDEfDDGxq+OvNT2AYSFsL9aRqu6tc3PxAiyBvKI8zRQEg7h8H9gR2OCAZvzzE3N5fiYp3pt5dbJ2WKz4yOJszrXbPGd11QQgxghQqQHq7vcb5TUgUT3hRfvoivnGP5RGKE6dap43WbQNCggSZTLi6GFcndIdYKxcCyGY6Nlhl2C81jWLZa3802bVSA4RdmW3rwoP6APxQV6XbO+5UX4uLsZPp9jGHKb/URm+sznDp+j93UPuSG631OAPlCWBh2b0VT5TVlijqJNG3q4B7KHW6KL6sVRt+g7fmnc+/n5KJn+WGulsf7b97rum9xsWPSyxwftGyJWCxUJY2C1FCyM4L0+dq7BksxFBBGROO6p70qPx1o3BgWLdIAoP79z9zvVq4MA4ZFsQKj3v/DyUf518+ILMznBDXoeG+QJ1Wvnta3Nptrykp3mGPAAQPwOYsTE+Oww3BSfd17t75PX8/sQO7+eXBwChxfrJNa2Ydg3nlwaApYQqHb5xD2gpLpsfDKhhcAuH3gVCoNmuCaYdLfNS1erKnTAd5/Hy6/D1KhQkQub1z9DANRcY+lFeBcDk9HXzsQmPdt505G3qqd32nLL6Lg+N9+dvr/g6CIr7Fjx5KRkUG/fv2oXbu2/W/q1Kn2bRITEznspIJo3Lgxf/75J4sXL6ZTp068+uqrfPLJJ1xxumdazyIotGzpUHwV7w0iu5+B3fuiaIchZfY1qDVVXwGGOwI8+ZSFEIoYuulPXXA+0Bqycisyc51WWjfe3dA/a+8Oi8XRGY4wU0G6k18WR5hjeft7OeP66yEkhDbZW2nFTr6Z2YaCQ/P54kut3J+rplkmuflmx9RQOSEkxKEmXtfAIKsXbvOZxpe0zXDsD2wSwux1Gn/v1d+rhDBHEw0aOCm+Thbaf9dXqKPNZnMNdUzRzvhR6p65MEcTpSW+Dh7UwUx0dDmPXrF7Gjwy5AMSqUPLgj3cx+cM7TabprUOeGxX7ggkRKcEfy9w9IOO28wvSmgERXwlah2WJHEux/y34ZxzICzcyhSbofpalAzpXiYedq6AhAKwwuRMDQ0ob38vExcOCqFWjTxSsmrw15YhduIreXc1Vu/rSWhIIbc+3C64OtcbTpzQtsDNOHbQJTrKnbeuPeTpbKVJMIAPby+nDuZrvzxHUnptGlY/yI293dqaDath2TI1kCxnBa1XVKpEYbjW20VJOU6Lgw111HrmuGidUe7l2d3gvqBA1dkQNPFVu7aKxERg3gIrDDNIyqlTYeOT8J0qkJKG382WrMbExjpEXV5R2syO5ZHR0YSTEff+3Y5n5i382lR7WSwWbcuy0yFN27aAFF/nnKONc1KSZsJzR2GhIwTVj/lVXmUlvopPeBIKZmbHQIiv4hNaFvMqVS0zUWz3+VpuhTYGm7XcSW2y3hjgtm8auL8XaHscGqrl1ts9c8bhw0p+RUSUKXTTJ4xkGSOZzPEjVfh7uWtygT9+iuRyDKlWkGGOJu64Q4mnJUu0STUJsLvv1uWnBSbxdfKksmwJMxlV93wqRmax61hrbhr3PbkFFejQ4G/6hI1y9Tjat08n/aKiHMqxqCgsxjFbs5N9W44QFHbpBNshGtKs5Wk2xjqN6NHjzIU4OsMl3HHxcvvy1G/1uc2yDOOq60oRlWXOfMyf7329SMlhjia8hDsOvaELDaonkHqqKtPf+wFWjoQF/eHn2jCrvY5TImrAgAXQ/B7YoPVb6rkXM2/7YKxW4f4PbwuM9DIRFgbvvQc//aSE3Po98CywDW7t9y3vtntct3N3ojldfe2SYLZ5O3ZwwaAoalVNI/VUNeZOO0t8QSlCHb39jTJz7AITJkxg8eLFLvv17duXjRs3kp+fT3x8PHebqUnO4l+DOnUgIbwRAHl7Ssgm5AXxh2JohoYk+SS+rr1WO3Tr1zvCEErAeefBB40+pSNbyA6LBiPr7cx1I8gtqEDzxll0v6QUUyUm8ZVS2WtaaCrUA8tl+v10El+1asHQoQDcG/E5x9Nr8sGT85m3qRf1OUSrBKODe5oGaXafr6JbIAxNb7z6V+8bb38DgPU5T3MiOZSYGB8pxkswtjdRvz4cM0fVBUCyxuz7Ir6ysrKwGeRYFWuhhmbyHyO+zBCLJk3KX9deow9UqEe7+jsY1H6OffEjQz4wvlmgQn3d7nTAWangCwEovsxBfWKRIdM6rqSGP+LLIzNZknaiT5wuoqCcEBGh3upTzIptE7B3uueGMz4HwNYqhiVbdNB6uoiv0FAYeYOaEn+/8k478ZW6R1UiI4Ycp1Znb4x3kHj6aXXTN1P4GhgwpAoWi42tCR1I/FtDBdoYdfCVV15J165dPQ5ldjB3Hm3Fe7NU7fXRjQ8ZSUqcMNno4F9xRZnUK8GgoIqWQctJhzI+aOIrWeXHydTAatXMx+UKZ8WXzaaKoqwsfXH8slLe4RLueLERU78hHcZ+APFAJEyspsrFCy/UMucT5vPeu1f9AQNFeWR0NOEUlrVvr2NiyFv4tXOYo8Vigd1aH2ZTgZNUK5n4iopS5hC8k33r12sGsmrV/F5bsUFuWdNyPNYFrPgSITRNy21hzbKTRC4+X50N5c/6jY4NthgTNN3ODdzfC7Rf2aiRfi8p3NFc37jx6WGJzjsPOnSgArncwrdM/tpByu/ecIDW8ZuIJJ+i1m1LnBz0hfr1HWTJXXdplysiotQ8WmCIiXFkgt6/DzY8SEyFTEadPwGAPzdrm/DA4E+0a+PscbTNaVLc+Z47+3xtcwp5DQRGptT/mrH9vwXDhsGaKH25itadgOIisNmwLlFP1SMd+pUu8XdJPl9btypbGxGhoYP+4JbZESAk6VfuvkD7Q5/Pu9exbX4yFGVBxSZw0QaoeT4iUPT7bAC+SlaRw4gRFho1KSVROmKESpk7dVLbnbeAnyBsr+HfaQ92Os197ZJgjll37yZEirh2uCZFmvxTlbPhjpQhq+NZ/G/BYoHCesoeWI5574z7QlF+AWGJuYRSjK1SjO8BRY0acJGRQTBQ1deRI9x7XOWpT4V8SMaApdBrMt9v/wiAm26tVDr+wCS+du1S5t8tLTSXxsMRo9E+ncQX2MMdb7Z8h5VinpmmBNMbNZ/BIkBrIHrHaflp0+dr8YZY6GzMwE4b57lhxk44rCEJs/apq+mgQT6SAwah+MojinRrrC7Ypx1gXx5fptorMjKSqGM6qMkNiSSLmP8e8VXeIRagCpwumiro6UvfwmKx0bf1Ynq1WIld0ViSp0FZYHZSfCkzAsjoCFpNWCxqSg9AsqvqJyBz+xMajpRMDWJiyl0sWa4491zYSGdOVGqgBPBPXsKN5y4C4Fi7AeTnK/FRYshUGWC6Ffy+cRhZF34BQOV0HdDf/Ug5OSeboWs//ODSHlSvDp1bKdEzf5Z22AYPHsyGDRuYNGmS92PV6INE1uXebz+nsDici8/5neFdnAl8CxTXgZlG+MXpNrV3gi1OSbmwrFwQJU2CJr5OqMdJCtWpUeM0ZP465xzNdJuaCrt3O8Ichw0rFTlghi7OnZ2LpL8F9dGwNsPPm6Hw88IQl219onp1h0rEX6ZDd5RjqKNZX7VhB/sPOjLVmc8xOzvbPinj4e+1W5Up8TQGLIFV/f7Us86MkJ9nY62jEwcRWZ6Kr4CJr4JUorIMwrZu2f0ETBJr7VrI72rE5G0zPCUK8mCfnkvWOcPt3YiAiC8I3OfLXH+6KlCLxV6/3MNYps5qiq1Yy8aU8Ye5lW8ACL3z9jJNfpleXssNLv+aa06PI4cLTNXX5ln20PLRAz+zr65a8SQje03Gw+PI3d/LhJOScveOfILCQSVJzxJfpUNUFDQY0Z1MKhGWWwgrfkKWTCU2N50comj1QCllaP36aQO1f7/dD84Fptpr2LCSs6qbs3vr1mm4rOHleVu/rwkLKWDN/nPZEN+ZnPwo/j7UgWmrr+K1H+/mxrvq0r07dKh8iNC9OynGylsblJB7+OHSXZYdzZqp4vbaC9VSdCYaShmDtnNnoq9dEho21AdcUAAHDjDydu2z/bpmAKcStvwz5/Qvwlni6yzsiGirrUdUxinIyQx4v/jtCbSwqZzb0q6d/8bcDHecONF3SJ0zHnqI0NxTbIrqxZi82xg3sw9HQq9j0Qo1vjaTRQYNszNsdo6d0kJTq5/+H8AgvVwwdAhUshKTl8Ug5iBiJYQirsg2pOIDOG0ZQsx2Ze9eONVPlWfMWem54Y63AIF6lzFrgRISXsMcT550kEHmrLUPmGTVETPc8aA+C18eXy5hjvE625ccWtPlWGcM5g/+m4gvUBK3zwz6dd3H9rfb8tsjl+rrWKGeKhuDkXcHiy5d9N0/fFjDdNyRlKSGp34yOoKqP6pXV9IKgBSdCQ4q1DFZCZN/c0ZHE/oOWvg92khjO/8A5BxzbJB7CjaoamBZjdvs+5xOI9yOHdWKJT/fwk/HNAwzTpLo0jSdfv3K4QcKC11Vv/fco5WQgYEXatswb0lVEBsWi4XOnTsT7ivUyhrCpPUPsHhnf6LCc/j05vud7o/xZc9ATZ/VsaND4XQGEGKQ5BVycpA8LcsmYWKSJO4wSX878XVSEw6kUP30lOfwcAfZsmJFqf29TPTuDVFRwrHjUWxLaAsGJ04xEAPp/WJYs08XDrowgHYt2HDHjAxNYADlQ3wZx6hJMikHrfZZc+cQXLMO8iC+nJQplSsHSE4EQnyVEAMY3kjbqMiCPI/+XKDEV356ElUKtN0Na1L2RrZpU50XLSiAddFGeHdioSZvWPuHGlFHwdLMAYjoGDNgYabZpprJY3zhdLfBACNHIpUr04z9tDm5jZV/bkNswvqZeXRjPTZriCNteSlx4YWul3DaTO2dYc+eudu+qGWdPQzuoOGqd/T/iqhwp9B1MwTdVHy5E1/OBvf7/Mk+veCQHvsgjc4SX6XEtTeGswxVJRX/NoWEj6cAsMB6IcOurVK6g1aq5BhYuKu+RBz+XtddV/Kx2rZVW5CsLO0vGF6eNSsnc2V3nYjv++oSom/NodMzf3PNp9N4fsrjTJxkZd06OC9L1V6bInpy7kVV+OCDcvJGjYqCKfPg/dEQbvQv2qGMypnoa5cEq9VljNutZwWa1U0kJz+aXycGFm31v4yzxNdZ2BHXqT5ZVNRhwvblJW1ux56tyXZje0s73yFMgOqzY2J0cLyshIwXf/6pMdUhISQ8MxbBykcfwddfa/3Zp49D3R40nBVf3gi43FxHB+p0E18Za6CnnsNTsW8BcFP0d0Rl5+ksQldOW4aQKlUc0RKrGhsJJ3afgoPbHBudOgAHVWmRWO0lu3f5kCFeDmhO0zZrVmKaRXtiRJvRoT6kA19foY4uGR0P67ZHRA/yjyq+gpEOn4lOt6FgbH3TWGIu/MKhYDzdDbGzGam3AZtJJDdtquoSP6hVy4n4SlVz5qCIL4MsS6bGf4T4go+TDRb/b2C7UwKQv8ar8X1lC3+cvMhln9MFi8UxR/H19BiOhyk5/eiwXeVDuO3dq+RXxYo6gM/O1lD4fJ31H3SpqqTmbemDnNzo70gApO1ayqNjbgbg+Ss/oFENp1TnFepBr6kw2ag/R48+oxmVwxvpvaslJ0g/roSsP8WXzWazJwxyEF/pgBJf5W0NaIcZt/7VVzpTHxHhCFsJEpGR0K+nkaRg6yBwLq+XwYL9F2KTEFrW3kXDCgG0a8FmdjRJ1Tp1SlYVBILoaPLiNLNlyLF8yFMFXkREBCGG/M4n8RWv/QjT3yugomcSX+vXu5q1FxU5JD4lEF8xjePIN52WD7n6Bgaa1fH44ZP2jI4RTcoe6mixOBRcC3c0gjqGZHzRj7B8ln5vEcvSFUqCBOTvZSJYxdfpbIOjo7EYcYej+Ywp3xxh04xv6H9CiYDiIUMDcOz3D6vVQXZ16uQQXJ9WmIqvY659s2/vvIWPbnyQF0e4Zds1PY5MxZd74ivnUMeDsUGdiu1IOnBW8VUWDBgAa6O03j/5xxYsC9UDKqnTeZhNT6ngK9xx1So4dEjJMa8z524ICXGEuq9Z4+LlqSG1NrLztd6qWvEkPZuvZNT53/LG43/z00/wTn8lvrq+MJTZs1XtVa5N/yOfwtqNcNvl8Nr7Z66vHQjMvviOHVgsMPIKnTybPLPm//twx7PE11nY0aKV1W5wz47V/jd2wu7tuY6Mjn68ewBlyq80Uln7C3fMyXGEozz8MBc90YF69VQ08tprutgpeWjwaNpUpSU5Od7NUHfv1sqhWrUyd1BKRG6imvYDfU4tp03lbbxS9UVdcD7qvWVudxpgzoAsOtQOmldQ+e6P7zs22PE2SDHUHsyfqzsC2i/3SiiYxFcJ/l4AsbE67rVndjyiSTFKCnWsWrUqJBwE4EBhI+AfIL7MtO45ORoeFCjORKcbvCsYzwT8KRWCUFDGxTkTX67+XQERXyeVUEimxr82o6OJBg30ercWtyG7fj1VxUyb4NjgN4ME69mYVWv0OZ6ujI7OuP567SQuXw5bC3Wi4JJmO8vn4M5ebxMnauzmxo3wzDMA9OoTRoXIPJLSa7NtqZ8soQCFWTz78CFOZNaidaNEHv36ac+w9e0VdCIjNrZkQ91yRmh9HfzVJpHjCemAf+Irz8ns3058pTrK82kjck0VnPnuXnCBzraXEoPOU/JxzpbBUBsYgiq/BhhkGDC4w5zA2rVgMzuWZ5ijiTbat6makUphqvqZWiwWj2fpQXwdVvVmQMb2Jlq3digddjvUNWzaBKdOaTl2V8+4Ia6OlSSMyu+w6yx/oIqvpCNZduLLUq98jOBdfL7aGcdcuRDWG8+2Q7Pg/L1M/JuIL4B71X9oCLNZO786k75O4wYmAhA2ooR+coB44AH4+GPNG3FGuHxT8ZWUrxMKhpq2dpUkHrzoEye1l5PHUW6umtuDT8VXXY6ReLiSRwZMn7AVU3xM/RsTIxqelhwF/x8QGgpR5zcCIHbPEepnHaYYK80uWOOanCBYmMTXwoWuxL0Z5nj55YH7Tzj7fDmZxZ/bfA3rX+3Kihd7kTKuGie/qM7Kl87j27tu5elH0xgxLJ+YtQt0Y6+z9OWEjp1g/Ezo/8iZ7WuXBCfiC2DkHUpaz9nUh+S9XhIo/T/CWeLrLOxwzuzI7m3+N3bC7r1WR0ZH9xkdbzClBNOne2T0suP113XWuX59ePFFwsPhkUd0lZmQx+TPSoWwMIfHgzejfedB+unuUUTVhkZAfbAWCdv7tKfeEYOMu8Btu9MA0+dr5UpgoNHIzDIyLeUcgQMT9Hvb55hlTMr6nKwJ0Nge9La6ZHY8puFxAYU6HtPBRILUx2o9Yz7VDkRGOgjRQMMdbTaHivB0d7r/KXjJwmNHAMb2JlwUX+laRwTl8ZWmZNl/IdTRYnEQWRtbGnXjX9ug0Cj/S3QWNqPXpcTH6/al8BsPGnXr6owwwE50gFIxoZyIr21O7UW9evDtt/r/Bx/A7NlEREDf7urtNndOoY+DKNZOHMO4ORo29PlXlQmP9EL6fmb40Nx2G2Wbyi4FajuIrxPH9Jn6K8umvxdAlDk4SNdlp1Xx5c6mljLM0cTggWr4u3T3+eTkR8ENwAMgIQYZhkF8BdKude6sEpejR+11v1+UZ0ZHAxHn6ECipezh0C4HWVci8XVUJ0YO0ihwWylnpYPzJILJCPXpU6LRW1wcDuLriCsZFGhWx6SjOdTDyLZnTvaUESaZtWoVFJ3TRf/ZuA22HgQgr2Mfu6o8KMWXPQzPD/ElcuaIr8it2NpbsCJcfWo6B+c3ohYnyKsQAWFvlY1YMBAWpuTXGVM8mYqv+Hi7n6jXjOjg8DjauVP7PtWqec6WVq6Mzagf43KSOHkswEnE9P2EZmj9Ym3a5PRlsvxfR8JM+nT/jFSqEC7azq4N6UafDr/DsitLX0a7d9cIgNRUx5igqAimTdPvgYQ5mjDl7WvW2BM4mWWsc+NN9GqximqVzHLjRLguW6ZK8ri4gMYj/3Mw2z6jLWzZLpouLfdTbAtl+gQv3mv/j3C2ujgLO1q0gP1oZyB/58GA94vfF05TjM5EAINazj9fGY/MTIeXiDN27oR339Xvn3yisiA0hXMVI+z80kt10rNMcA53dMeZ8vcCraSj69lVX/yBqq7aAbXgdGcIMcc769ZB4RVG9sh1SbDjK8NbrABqnk9+5d525bJP4itAY3sT9es7Kb4SVYobUKhjYgqgpFmdOj5M9k83gjW4P3ZMQ7lCQv4BidoZgrMywz2EuLSKL6OD60vxZbPZPLM6pmvI3H9B8QWOvt2UEPXwYrvAlqmwfyPE54EFVtVRBWybNuUTvRUIzDkKk/iyEwplxTa3iZJLL4X7NWkGN98MiYkMHKrPct7q5lDgPdNw8ZF53PPKQESs3HBlEv0u9EJq7d0Lf/2ljOEZMcJxg8HK1yaR48eUxDVJEX/El3MYHRkFwGn0+AJtXJ3b74svLtPhWvXqQv3qR8kvjGTZbkfbtSexBYdSGhEemk/fzvsDa9eiox31RiCqr9NAfFnaOPyI9u92eGaZdY5P4itJn2c8jYPjWrypZ5cu1c8AGCEX4uvoQZd1ASu+jhXbFV/lJatp3Vo9HHNzYUdNI6vb9mQ4oHX4+ugrKSrSJrJhwyAObBJf6enqJekNJ07oYNhiKYNPRgAwTLitg1TBdBtfc6ftKwBC+xZBiOW0+baeVpj3OD4e6l7mOyO6s8eRs7G9l0lkq1PiiD1/B0BqA+xZiwXNlFqjzemaCfgfh1FGe7ZYxZpwR5zsiWa1CA0xshSWtoyGhkL//vrdHDQsWKDeqzVqOGbUAoE5mbptG+TkBk64ztYwRy666IxaG/xrYLaXJvEMjLxK26bJv9T9fx3ueJb4Ogs7KlWClEo6mM/dE0T41qFTWBGKKlX2Ef/mBqvVYezpHu4oooOTwkLteA8fbl9VsSK89ZZOoD/+eOCn5xP+iC9TnXImiC8zG995uL6RF8KZyBDSqpWSiDk5sCWnGlRDs5R8eyck/KQb1ezHsmUaZREX54PXys113MsAZ1hcFF/JOnDwRXy5hDqeUN+no9S1809nHMESX+ZMc8OG/xBTdwbQrp2q4TIyYM8ex3KR0iu+sgXyc3wSX84KGfvgLUM7a/8Fjy9wEF+/bWsK7eKU+J70JcwwlErNo1m6v6nLtmcCV1yh/c6a5xsEgre6sjRwJ74A3nlHjeeTk+HGGxk0NBaAJTvPJ+/gIs9jFGYy9pWlbDzYhdhKObz3mQ+G83NNfc7Qof+M0tJZ8XVcy2Ugiq8Kzso0p/J82hRf4Ah37NSJslaslpAQBl2oKoI5Wy6yLzfDHHu3XE70eW8G3q4FE+5oltNyDXV0DND37XWQ+uaz9OrxlZUK6bptUKGO4GnoX1zs8EUNIAYwLg4S0bJnO+pKKJjEV15ent1PzhvxdfJIHlVI13/KSfHl7PM1J+tSCAEyBYqAaJhzWAe6Qam9QMlRc5bDl+rLDLmrX1/DBk4XDBNuOkFebARVSWMwcwEI7V+MR9bD/wrq19f+e36++o74yoju7HHkra53hrPP1/aMwM5jt6qIDtKIFi3/H5Ia5QGjjFqtQkELR3+0yRDz3SljGb3QyNpqEl9T1Difq64Krv9bp47WPTabeh4aCZxKJFxN4ut0hjn+m9G0qd7nnBz11Aauua0FFouNFTu7cnDxFDg4BY4v/u8R8GXEWeLrLFxQ1ECn2KzHAmuAMlPSqJmlRq+0bRs4s25KCWbPtmdgA5QIW7JE478//dTjeHfeqcKZcgn1cc/s6IwzqfgCrawv/gm6GKbfscA5nJEMIVarYzC9asav+rsAzp7S217ljynaaRw61EcW9W3btHNes6Z9sFcSXIivFFXplOTxVaVKFUhW5cRR6v5z4qnSEl//q2GOoA1tFyN8xVmpcOKEyt5LyOhoolYtSKUqxWYTdXSPT+LL/N9isWhoWMYJKDB+9j8Q6gh6y0JCNJIrffA1uvDPDfDnr/q9X2dWrdKvZ5L4io5Wa42XfjTqygMHfIenBwpnzxfnwVBkpGZ8qlABFiygze9vU6dGBnmFUayY45mpLXHuqzw7URNyvPGG1ftzPnXKEUZpekaeaRh1YVXSOHlM6zhnssTmpoz0IL4yU+zl+bQqvgBuv12VPU88US6HGzyiEQBztg21LzPDHAddUiu4di1Qg/v8fEddW46KL2c/oqN7iuyL/YY67lKv1EwqkUaVwEMdwUH0/f23vnNbt6qaqVKlgBTVNWrAcZWMk5fgqoCqWLEiYW6DT69ZHRO0bs0Pq1BisppgYJJaCxdngzO/2hiW/LoeCNLfy0RJPl9nqg02feusED443744o04M1PWy3X8FYWEOtbpp21CSn6iz4ssbjD52a3ayZ3eR923csU/77GeN7csAp7LX5pIdnCKaDZHn0K7rdp/bBQXT52vFCu37zTTCJkvjsekc7gglE66HDum4zmotdYKW/zxCQx19bWM8W7dRNP076sBuyritsHIkLOgPvzUql9Dr/wrOEl9n4YLI9s0BiM7IhPycEraGPZuP2I3tQzt1CPyHWrfW0V5RkTpzglaOjxmZBV944fRK0cG34is/3zEwO1PEF2il/cFcqFoZHr8NBp+5DCE9z9XB18o9PcHgLdgEOI3JZs3WDk1A/l4BEqAuoY5ZAlmpPj2+zFDHapUrQZrOUPyjxJf5w4ESX//r/l4mzAGbs8+XqfZq0iQgU9O4OBCsZFhjdcGxffaBWU5ODsVOhqnOoToWiwUS9H3OI4Jsov8ToY7R0dDBqD6XV+uvQs/dxbBGy3xR/R2sW6uDgjNJfNkRF6fxlTabhg6WBWYm3apVPRXCrVrphAdgeeF57u6gnkZzF0a5SvOPzeHR188hM7cy3Tplcuc9PrKETpqk6sNmzWDQoLKdd2kRG0tRiGbXyzuqZL5JloAnwe9BfB3T+11AGFlUOr2Kr27d4MiR4DxY/GDAAB177EhoyZHWK8nv8iOLdusM/OBrAvADdT83UOLLX5jG3r1avmJiAp6ACQiVK3Oqsh6vaP8pEG0c/RJfe3SQcZBGRERYgvOibNBAJ5GKitRCwPT3Ou88HdSUgNBQyIpWL6/CRFdlocVisau+AEJCQojwooCyHdeymBNbvpWoSWqtWF0BWxNHX6GoQQhr9nQCoG+LOcEfuCSfrzNFfDn51ln7gy1Ur7HyRZk+t/vPwDncMRAEqPhqww727A9QhXdQE2ecJb7KAKey17zdfk6+UpUm7x7w7LqXtoy2aKEd/IICePppTdTRoEHpMvN48471R7iaaq9evRz+OP8f4ebzRcJMRnYbC8DklU4EZM7Rsnm6/cdwlvg6CxfU6tKUXCIJEZt9ttIf9mxLDzyjoztM1ZcZ7vj006r+atPG4WR/OmESX4mJOjgysWePdpwrVy7fjnMg6N1HU9c/M/6MZgjp1UZn5Vbt6wmtgUggDcycBXsSm7EvsTFhYTbfEyhB+nuBtoPpxJJrMQauBzaXGOrYKCQHbFCMlePU+ucVX4aMuET8f1B8gaOT4qz4ClJBafIhJ8xwx8R4n2SBSXyZ5YZj+532tfwnFF/gILQWL98HZoRWPhAN2y11yc4JpVLFwnIVsQQMi8WzE1VamCRou3beCfJbboFrr4XiYh7++wEqk868zT0hw6iMCjKY/9UEpqwaidVqY9zXMd59vkUcpvb33edDpnoGYLGQE6Pl2HZCy21UVBRW43zcwx09iK9EJcyT/2PlGZTbNPmquZt6svLYNeTkhlCzpoPoDRjt22t4WlqafwNz5zDHcvZ2yWuifZzw43kayoan96AL8bVPy3o8jWnSJMgiaLG4+nyZxFcQMYCFVZTckhTPSUxn4ss+aeAMEUJT9ZoKa5Zv2rz2bYuJjU4nKy+GQ5UdDfjuqBYUFEUQF5tIs5N3BB+CY7at5iSTO8xyE5T0rhRwNuGuBNZRAn2A3uYGp9e39bTCNLj3dY+dkZbmyJpeAvHVmHgOHvBUHXpD0UGNEjlLfJUBbkbxDZsmUKWqc6RPGcuoxeJQW335pX5ee23p2mHnzI6BeFP9+ad+/n8NczThnNnR8HS7ottPhIfms+1Ie7YeNt9J457+F30HS4GzxNdZuKBF61C7wT3bV5W4/e6dhaUnvq67TuN71q6F775zVI5jx0J4eHDHKg2ciS3nlOFnMqPjvwTdW+3BYrFxMLkxiafiwAwl/QBYAbM2q8yrb/cTOPEPrjCJryAyqChpZeGoGB3rg9vtA4mioiIKCgrs25rEV718VcGcDKlGMaH/PPF1NtTRFe4hOhCUvxc4iK8km/klwcXs21kN6GHOnKSzwcnUdDnWvx09e6iCZPW+HuA8KdoeVh9QVqxH09WEWP6hjolJfJXV56skBYDFAuPGQePGVEw5xBfcxaaD53Bi1fdwcAr5i27kvi9eAuC+e4rp3NnH7yxdqr9VoQKMGlW2cy4jCqppIbSmKgFhsVjsRK5JlJgwiS87kWuU5xRUvWMmk/2vYLBGNjJnjv6Biu+CHv+EhzvaFn/hjqfB2N5EaAcdSFTPPIktQ5V4fhVf8UoOBJXR0RlmXbp6dVDG9iakppa70HRP4svM7AjewxwpTCfylFF/1yvfRjYkdRm9W6h30NICR0zjghw1ve7bagmW3FL4C/1bQh1N31YALNAfuBuIMP6H0+rbeloRjOLLrOsbNPAdKluzJsUxlbEiWBJzsRXbvG/nhPzDGj6aUrEBVasGctJn4QH3MuqCciqj7rPkpQlzBIcXRGKiKpL9IT8fFi7U72eJL/3cscPu6RYbncGwTrMAmLTyeqeN/6O+g6XAWeLrLFzQsiXsQ3totp1bStz+4G4bTTFmfnwNZHyhZk1Hr/jWW/Vz1KhSmjuUEt7CHc+0v9e/ADE1a9C+vpPqaxTQGSgEPoeafx3Hgo1hg095P0BxsRIdEJTiy/TLTTCNPg7ucgz4cCU47KGO2Trbd9QIkfzHia+jRz0zGHqD2ek2O47/q2jUSEfnhYUOMjTId6pGDR0Ym+QVx49hsVi8+nx5EF+JqsA7QU0qV1brqP8Czm2hg/kN8V0o6Byqps8AHWD1PiW+zm28+J/rmPjzRAwGJRFfoJMSP/4IoaFcwzRu42sWzDoCK0fy7vgO7ElsSVz1LF593Y9Jrqn2uummckgBXEbU1hi3iKwc+4yqL4N7D8VXknb0U6j+nyrPJswI03nzHBEoZrMfNNwN373hNBJflbpr/dXCtofE/WoY75f4SlB/nKCN7U2YxNdvv8HJk0ridu0a8O4h9bXcReVke7RR7oovd0j2MWJy9VrCmgSTXjEA5CbSt7Uq2H4+djn0As6H3w5dCsD5rZbatwsK/xbiCwI34f6vIRjFV0n+XgAWC9Z2OiHWtOgACXtKyOxYlE1IshJf1sblXC7/v+F0l9ELLnB8b926FDJf83wqOPZ1Dnf0hmXLNHNrXFxQk/D/k3BW6ec43quRvSbTus4OGlU/6LnPf813sBQ4S3ydhQsaNYIDFh2Yn9paspKlaJ+qcPIrVSndVPQNN+inzaax2O+8E/wxyoKzxJeiRh96tlKic9Xenhrq+DBwia6+PmUKM7iSiy/2YTCzb59mD6lQIagwgogIVeTYDe4TDhIWFmY33nUOaTMVXzHpKQAcLNZOzz9GfNWpo+xMYSEcP+5/2/R09bCD/33iyz1EJ8iMjqCTe9WrO2V2TD4BeIYVOX+3D95OJOku/5GMjiaaxR2gasWT5BVG8XdqJ333WgLdnIivZqv/uY5JeYU6BkJ8gZahx9Vr6hMeYOuadhw40ZjXf30W4P/au/Mguer77vfv7p6enunZt+6eVaMdCSG08QhkBLKJibGD7QLH8UpcuZXHxBAbU44Ndkxy7RiuHYcQmwKCHyfO5rJzbZlQFed54AYMwgaDBGKRhEYSkmZfNfs+033/+PXpZfal9/m8qlSaOX1GHKRezvmc7/f748E/+CxFA/PMpGhqgl/8wnx9xx2rO94YyAq+SeWNDMNED7CM4KsrPZ/Plv37TY7Z2wtvBO+lrXje8FJWdozHio5BjisiVnY8ZUKhme9J/cGxCYWFhdBi3vNXHHxZQZ/1OXjgwLJWRMtdb553Dr8f2qPDoMWCr8HuTrx+87nm3hzbVkdyK0Ph1vMN1+P/ExsT/5eT35w1q4paodiy5wtZn63NzabyI9LgYHghpURVXS9l1cN0Y/0dLyX4WuJ7vS1ixdSG1xc5l+o4Sc6o+bd179i8+DHIwuL5HPV4wuHTJz6xug6aueZ8zcW6u/K+962Zjp15bdlirlH6+2Eg3EV1y1WHOfGdy7n9d/5+9s+k49zBZVLwJVGysmCwzJzkjJ3pXnDfwPQ0eR0mjJjeusKTzA99KFwC/Z3vJL6PQ8GXYXdw4H3mwvY3DQeC24CPwSs37mOcbG7hF2z6o+vnbu2zBtvv3MncA3fmF7WyY6u5KzFzztf09HTogiKnxzwvW6gmLy+JsyuzssKtsou1O1p3mj0e5u8VzSCRJyldXaZawWZb0oqOFq83Ivjqnj8smBV8BS9u0i0osLkrTbBFMOj6feA+uOQv4e1W89rcv+m3yTsxsYKv06dNhedKDAyYFZdg8RDUPw37nqGnvhQ3o3zqtX/jnv/1AFOTWdyw/Wk+ds1P5p9J8fd/b47x0KHlVyLHQc4G8/5WNt3DSI+5sFt68GVC327K4zvYPk6yssyQe8uuXatoP7aCoFdfNUPfZ/L7w5/l8RiGFzwnqOciF09GL1QwZ8VXm/m3PM/6lbU6lpZG30haZjV8RV0ePQR7wS6ejHpsseCrvbGPasx8JteGGAdfFQfZs72TPNcQvcOlvNW8g2Pn9zI64aYsv5ttVW+vbL6Qx2NWCgkEZrfiWZ/B5eUxXaFyUYutephurIqv1tbFV/hdSsUXhF6r2zhFw6l5ugosb5tqz16Kqb2ieJGDlSWJ53P07/4Obr8d/vRPV/fnRM75WogVfL3//Qvvtxa4XOHPj46C0Ew3uz0wRyaYxnMHl0nBl8ziX2fuEma19i24X8vZVjZNmdUPXfuW3t4Wxe02d+YfeSTc7phIM9t3JifNcHtYW8EXcM3vmRaKYxf2Mj4Zvjvw6NSXeDfPMuj2mNa1q66a/eGzgsH2lqiVHVtNaDHzLnpfX19of2eXCUGsFR2TelNnqXO+1sp8L0tkxVfkio7WxfwS+HwRwVePCT2XVPHVY8L4TjxpsaJjSMVBrt5m3oesCi+Al8+Zv8tN3jOUe93JOzFZv97MWRobW/qCDjNZNxUqK1l0OEvXERhrwX3XMB142D59in8/8TEmyeb/O3kjts8E4ONNUF5q/rx168xJ3vbt8OCD5s+4886VHWeMuepNWFlJG50tfUAwGGEJwVePqRrqpjytgtxIkQtqrmpxzS1bTGgxOhp+X4nU2GgeczrjU1lbVsZAjpmNNXjCvM/MF3wV2yZgwAwNXnHFF4TfS2FZ873AvIe2E3wTbG6IemzR4KtlhBqC83SsmQSxYneQ9T8e5F1bfg3A829fx/Nvm1Dvusuex24PrGy+kM02/4B7a6XutfIZHC8VFeFw0bqJMZdAIFzxtZzg6/TCu3LGjNTQYPs0cd11Zm5zUdHq/hxr9Z9jx8x12lwuXDDXcg7HKsqKM4x1Hfv26fjPdEsTCr5kltyd5tOkoL8XJifm3e/08fbQYHvHzlXcVX/Pe+BP/iQ5q25ZwdfZs+bN9OxZcyc5Pz8caqwRmzaZm6Hjkzm8VvEiHPgx/nc/yy9PfJQXOcAbP3jZVHR1dJhKin/7t/APWxVfK+ipj6r46jABx8yKL6vNMT8/H1tHH2B+Jun/RFafpYKvaFZlxtmzZuYCLDtIjqr4uhQdbi0YfHWbC890q/jC7uDqD5iTu8jgK6rNMZknJg4HoSuNlbY7Rq7ouJhgS2duxTh/U383XZRHPz4FjAG9A9DebkKPc+fMsY2OmuDjQx9a2XHGmK0qIvhqNQHJfBVf1nteKPi6FH4+p2PFF0TP9FrxfC8w5wjWjKu52h2taq/Nm02pWRz0VwarVs8PgH8q6t9xfHw8tCBLcbu5gu+jiEF7MetWOo7ICr5crugQbAmig6/oIGix4KujcQQfps2W6hhXfAHU3sL1N5lA7blT1/PcKRPqXb/zjdXNF5pvztda+wyOF5stXPW10ID7lhYz4sHhWLzSO3husIUGzr6z8MJWgXfMohIKvtaYLVtMeDY6Gg5UZ7Kqva65JvlzPVNF5IiKTJ07uEwKvmQW7/5tTODEGZiCc8fm3a/h1NDKV3RMFTU15u7V1JS5Q7gGV3S02Gzm8wLgxdN7oP7jvNpyiI4OGwUFcNVH1sGvf20uJsfHzXy2r33NtJdYwdcKKr6igq/uUWD+4KukpAS6TNBhVXwllZW8LVYBs9ZOuktLzcUnmBVbYdnvEVEVX33mebGk4KvXPGe6qEivii/gf/zetdhsAd7p3Ehnv/l/t4Kva266IvknJqud87XU+V4Q1dLpPdCJj3Z2VLzB6MMueAT4HvC3wJF/MgtrvPKKeX969ll46il48cW4hR/LVmWGjFfSRkeraQ9acqtjMPRN54qv+nr44z+Gm2+Gg6stWLRC9bmCrzgOtrdMbTXVK+7uYRi+GPWeFLlCZ26zCeEuUE9d3SoWqn7/+82KBrfeuuyVDXw+aCP4OmqNvjmz2KqOg+cHsBNgypZFvBLX6242nwnPnfsQL5wzFRrXfe7rq3ufsyr9FHzFz1LmfFnv9Vu3mtB2IbW1TLtyyGaS8fOjC+46dtqEsSteKVXSk90evcrtXKzga62v5hgpcmVHyMy5g8uk4Etm2Xx5NucJ3tF56zfz7nfhrWHqWeK8llRlt4fvRr399tqc7xXhQHC812+C/+z/aVa95b3vDZ645+fD4cNwzz3mgfvvN0Mku7rMnb0VzNOJanW8NA2TE6ETcSv4slZ0LCkpgW5zRz2lgi9VfM1mnaRYJ8erqfjqN6XtS5rx1WcG33biSbugoKgItm83gftv8/8b/9U/5rcXzYCkq2/alcQjC0pk8FVxMDST4k9+51G+fss3+X//7KPkloxDEVBmg/paOPBJU4m6b595Azt0yLxhpVJ5VHAWoIcuulqWGXz1m/3TdcaX5fHHzeKEy5jNPrckB1+u3eZcxzvUCYMNUf+OVvCVn5+P4x0TfK14vpdl82ZT0fiP/7jsH42s+Jpqjh4avljF13ij+X8ZcHviVo1/1VUmy+vqyWZwyElREezctcqK1sUqvpSWrJ4VfC1U8WXN91rKe73djn+zKd8q7O5jfGR83l1H3jHnhP1F1eTmLuloJVNY7Y5zDbgfH4dnnjFfK/gKmxl8QebNHVwmBV8yy9atcBZzcjDx5uvz7jd+0gzdHckvg4iTqLQTOeB+jQdfVsXXb35jRjRYwdcHPhCxk90ODzwA//zPJg17+mmz/bLLWMmZSF0ddOBlGjv4gaaToYovK9SwKr42lOZB8Iaggq8UZw0jtSwzHI8KvgYDUYFoZMWXFY6GLt76zbDztGt1DLLO7V56+woaJj5OX7+T3NzFx6QkxFyLgSyHFXwt5blgd4RmUrhdY/zlrf8326qt/26azaQoKzOVM8DwhT5gOcGXCfrT9fkcc1ag/sYbpu0lUhxXdLSUXmvODTZPn+FSU+OcwVdhYSGcN4H/quZ7WYqKVlQyVlwMXXbzpBlvjn6eLRZ8+dvNe+xIcfzKZl2u8PsdwLXXLnttnNnmm/G1Fj+D48VqdVxKxdcSP7iyrtwJwFZOc26+FeUDgdCCEdN19Uv6cyWDLLSy45EjZvXbysoVjVzJWFZhR3d3eFXbNU7Bl8xSXg7N2WYgRd9rzfPu52oxQ8bHN6T5HTQFXyH79pkTz9ZWOHo0fFN9zgVSPv1p01ZklSHs3bui/2ZdHUyTFZ5F8s4bs1odrYqv3cHFmIZseQxRkB7B1/i4WV4d1tZJd+Q8Gptt2RejPh/0ELw4CwDt5xZvdezvhOBYwnRsdYTwheCLL5pfYF6Xq66UiYXIiq9AYHk/29NjKldg6e+vmTKTwm5nyG2eyxMt5vlqBSaR7XEwI/ianjKhL+lf8RUzNTUmFZ+eDi+qYklAxVfOHvPc3cA7nHujZ85Wx8LCQmgyM+piEnytkM0GY4XmeTfVEb1a3oLBVyBAVq95Hk56YjzYfobIef3LnN0/t8jgy+83X09MhD+j19JncLzEuuILsG03r9ntnKThzZ65dxrvwt1vzglztm9e0p8rGcQ6p3z7bQjeDA+x2hzf9741N6ZmQXl5ZtYArLxSP8Mo+JJZbDYYKjcXGhNn506Ix4eH8Q60AuDae2XCji0urAvyt96C08ElZdZo8JWXF75Z8vWvm9/37WP+AOHAAZOO/fmfw333rei/6fGYi/pQu+OFU/PO+NqaY6p5mgNm35QJvtraFl5pJhAwf7lr6cp1165wWrN+/bJWdARzbTuFk16KzYa2JQRfwZXLRslhiPy0rJCxgq+XXzYjqyK3Jd3WreYD4tKl5d89tAbb19dDMPRZkgyZSTFWZF77ga7o4GvBiq/Oi6YKFhMCp+PzOeZstrnbHbu7zS9YfJj2ani9DDiKceCn++X20L/j0NAQ/f1mcZbCwkJoMZ9ZyZ5FNBWc5WUPBlmWkpISbMELxFnB12Q/OYPB/WtXOpV/aa67bu6vV6yuzty9Gxszn8tgPoP9fvMZrBfR6lkVX+fOzX0DZHo6fBN5qaXKkSs7nppnzlfLG+ROmdbv0r0KMNeciopw6Dqz1V3zveY3V7vjGqbgS+a23iQKzvZLcz589vUmtmPS49z9K6v0SRlW8HXsmKnOyc1l5UswpT+r3fH//B/ze1Sb41zq6uCb31zxnVS73eRHoQH3TbMDDiv4qvObkx4rJIv1KuvLZqV2gYApk5tLZIvFWroT5XKFU9QVBMnW9UknwbCw7XzoeTHvjK8Ws+KTaZG0pWXOuG2byYWGh+Hf/91sS5ngKzd35XcPlzPfa6YMmEkxWWHuHjj6TKCwpOCr7SwAAxQwgSstn89xYd35f/nl8DarzbGuzgQc8WKz0VFiqk1GT14K/TsGAgHagkFLYWEhtJuL9/OsT2qRkc1n5ss5B6ODL4fDQXFw5bNZwddoG4WjpnrNuSG+50LXXGP+yTZuhD17YvAHOp3hO2LWZ6/1+4YNa+szOF6s4GtgYHblDZjVnMfHzc0ua9/FBIOvy3ibMw3z/Bu9bcKODjxs2LG8G2mSIeaa83XhgjkfcTjMfE+JZlVAK/gCFHzJPNxXmkGTxf094XLxCKff7A6t6GjbkaaD7S2bN5v0xbpztW1b3Ia5pgNrwL1l0eArBurqIiq+mpvnbXX0TJiLiRaq8fkWXywo7qzUDuZvd1zLs0WsW/j79i37R8vLzV9vaM5XW2NUdYUlKvhqN4ttdFFBcfGyF0FLCQ5HeJSFlYmkTPAFK5/ztZrgKwPYqsz7W87gMPinlhZ8tZpWoi4qcLmgsDCBB5zK5qr4SkCbo2Wo1gT5juZBcrPt2IPnCy0tLQDU5WeHWlQvsi5UpJAMzvrg8258HIb7oh6zVnacGXxND7VSNmnazdxbZrQZx1hurhnX9uqrMWznnjnnay1/BseD2x2+MzVXu2PkLMelnktv3Mi0I4t8hulrGJlzF3+D+XPPsz6uRZ2Swuaa82VVe11zjRlsKNGsG89qdQQUfMk8vNfuYBo7Lv84XHhj1uMXj/dQS3BuUbqu6GjJyYm+K7VG2xwtVsUXmHObFY7uWpaoiq/WjnlbHYuGzQlRSgy2t1jBV2Pj3I9H3m1ea/7iL+Dv/x6+9KVl/6jDYSrbQ8FXZ8virY7t5j0pHVd0jBQZdNXVQVVV8o5llpWu7LjGgy9nvXnDyh8bgvEuUxXE/MFXXl4edJj3lG7K8XpVrBJiBekNDdDXZ75OYPAVuNwM4i661I9tOFyJ2hqs+r0yx9yguUQJbl8Rc8yOT5jCei/jBAfjN56Iemxb8O9qw4zPpp7WS1RjQrzCy+IbfIGZ3R/TUHfmyo5nz0Zvl9WznjNzDbhf5nwvAJxOJmpMdWFWS/+cu/S9YV5fF231a7kpY22zgq+XXgoXK1jB15zDiEWtjtEUfMmcNu/I4yLmkyXw5guzHh953VxgDuRVZEbCHjl4e40HX+vWmYVRwLTLJ6L4ra4uIvjq6A1dSMwMvvKCg01bqA7lTUmniq/5FRTA//yfK249ilrZsbNj8eCrw5wYp/sKeJHBV0pVe8HKgq9AYHkrOmag3I3m/a1k8hJTQx1LnPFlns8abD9DeXn4wvvoUfN7AlZ0tORdZZ7DVSOtMNgQ+re0Kr62YD6nkjnY3uKrsocXjrkYXaX5T//0Txw9epQ9M3oM25sGQ8FXVn2y5wmswMzgay1/BseLdbN4oYqvZS5FnLXTvK58w230d80Ov4ZOm239xVWrX/1T0tOuXWaF254eE7qOj8Mzz5jHNN9rbtY5W2sr9M8dKq8lCr5kTps2wVnMScLg0TdnPe443wnASF2GVLEo+Aqx2eDDHzZff+pTiflvRrU6dg6HKr6sUMNqdXT2mRlfKVnxpeAr5nw+c9EPQHf34sFXcOB6uq7oaLFuakKGBF9tbWYWjN2ekGAiFeVtMncTKmmnu+XSEoOvDiD9g9y4mNnumMCKL++7zTnCev95hlvOzQq+asbMfKxkz/cC8x4aCr6az0Y9VlxczN45Srp7zlwih3HzTUqVmy6RFYrODL6SucpApol1xRfg3GUWytrGKc683jLrcX9wRdzJqlS56ykJ53LB7t3m69/+Fo4cMQNRKyvhyjRfaC1eiorC7+Nqd1TwJXPLzYUOt/lw6XttxgV9IEBxjzkhd1yRISGRgq8of/u3Zl7kDTck5r8X1erYPUGeOxeYXfHluDQBpFHw5feHTwyTfQWUhqIqvrr7ZoUFgUAgOvjqMc+TdA8KysvNjU2bDd797mQfzQzWe2VTE0QEkAuyVnTcvDk9B6/FgKPGCr7a6GwdWlrw1WNWKVTF1xwig6+REbho5vslIvgq3lHDIPk4maLluXdmtTqWD5l/02Sv6Agm+GojWMLdenFJPzN01sz36ssqS4FBmisQOeNLn8HxYQVfMyu+RkfDraXLrPiyXrvbOUnDiRlD8/2TuHrM6yp7i/4d17TIdkerzfF979MsgIWo3TFEwZfMa8RjEuKps51R23taOtg4ae6gFV73PxJ+XHFhXcxlZy99FZoM5nIldmHLqFbHcSjDVHZFBl9ZAH1moYW0Cb5aW00ptsNB6hxw+ogKvi4Nzqr4mpiYYGpqCgjOROoxlRbpPuML4Be/gOeeCy+MmTLKyszwNYDTp5f2M2t8vhcQuuPqpYOO5uFQ8DUxMcH4+Hhot+jgy1z8WTO+JELkyo4NDaadtrTUpMbxZrPRmGtWduw71h76t+zpMYFRQa95f0qJVseIiq9Ay+wqmrmMN5n30f68NH3SWX/p3d2mBXZ8HLKy9BkcS9Z58syKr1OnTNhYXs6y37SCwdc2TnH65ET0Y8ONlIwEZ73uXZtVwxIUOeDeCr7U5rgwBV8hCr5kXraN5iTB2dETtf308dbQio6uvbsSfVjxsX8/fOhD8LWvmRMkSajaWhjFzSVKAPCNtAMm4JiYmGB4eJgdhWDzwxQOOvCmzjmsdSBzBV9Wi8W6dTFcsmrt8Pkigq++0VnBV2TLY15eHlwyQWm6tzoC1NfDwYPJPop5LLfdUcEXeDxMY8eBn/6z4VZHCFd9RQa5JvgyAUQXFar4mmnPHtM629ISnvGybVvC7vp3V5iVrycbov8tAVw9Zrh9KgRfXm+44muy5dKSfsbfZt5Xh0sq43ZccVVQEA7nn37a/L5unc7tYsmq+Lp4Eaanw9sj2xyX+1rcupUANsq4RPupGSs7XniNnMA4fmxUXl2/4sOWDGDNfzh2zJyDOBzw3vcm95hSnXXOpuBLwZfML3+3WS+4ZLDL3MEJOv9yM1W0mW8ypS3Q6YQnnoD77kv2kaxJhYWmDd2q+irpMy0jw8PDoTbHncFri3Z8+HGkTvBlVXx1d5sy/0ia77UqURVffROh4Gt0dJTp6elQ8OVyuXA6ndBnKmfSvdUx5VknUW+/vfB+ljU+2B4Ah4MBVykAYxd7ycrKIifY9mkFX1a1FwSDrz7zvSq+5pCXFz7/+Jd/Mb8noM3RMrrBtHFltw1SXpwb9Zi9axIwM76S3erodkO/y1TBTbQOLrI3EAjgCN5AmPSk4WB7ixXMPPWU+V2fwbFVXW3OmycnTfhsWeFgewBycxmpMJWxgXPdUQ9NvPkqYGbBbr48e0WHLBli/XpTUWgFrgcOZMYia/FkfVZqxpeCL5mf77rd+LGRPz0MrWdC24eOmtLmS25vjNeglrUsst2x4JKp+IoMvq4sMic7LVTjcoVv6CZdcXF41cKZVV8KvlYlquJrwE9BxOqQQ0ND0fO9AAbMiVAnnrSv+EppVmv4Uk6i/P7wjK+1XPEFDOWZ5/Jkm6nkmjnnywq+HA6HCXL7TZCrGV/zsNodjx83vydw4QTHTjNIubT/EvXl4YqX6hywDwcA6Cuso7Q0YYc0r/FiE3z5u0cW2ROYGiRnyOxnq0ngvINYsz5zf/Wr6O8lNhyO8DyMyHbHFQ62t/i3mEpKd+clAv5AaHvf3hUQAAAtNElEQVTnK2Yl+Ub7Ot0EWOtstugVgNTmuDgr+LpwwSwGsIYp+JJ5bbqyMLTS3tTxF0LbA2fM3Z2BSs3CktiJXNkxt8eszjc8PBxa0XFrrmkVtOZ7pcwcS5tt/jlfCr5WJariaxqyBzrICrarzAq++juxFiJTxVecLafVsbHRnGhlZ6/5VdXGS4LpVbd53s4XfLndbmw2G/Sbtkc9n+dhDbi3JLDiq+hq89+qGWtmffFYaPv+IvN7N2V4NxWmxOeUv8I87xx9o4vsCYy0Ujhqglnnxvo4HlWcWZ+5VhWlPoNjz5rzFTngfjUVX0Duvl0AbJg6T/uF8Hzh/pOmAqyvsDIlXlOSZJHLXSv4Wlx5ebhaYKmV+hlq2cHX888/z80330xVVRU2m40nnnhiwf1/9atfYbPZZv16e43/xaeDmho4bzMfbF2/fiu0vaDdVOMEtm1JynFJZopc2dHZOTv4qgme7LRQHcqZUsZ8wZdWk1oVrxfGyWEQU9Flaz0TNecrKvhqbgBgDBdD5KtCJp6sgOHMGdPqshDrQuiyy9b8nLvp4IIxWX3mjmthsGJ6ruCLkUEI5hSq+JpHEoOvmmvrGSUHFxOsG+sLbd8dLEpNhfleFkeNed7lDI9Eja2Y01gbZRPmM9e9uTrehxY/M//yU+UfI5NY7aTWeU5vb7jtcYVt7VlXmsBsG6doeL0ttH3qYj8A4940fk5K7LzrXeb36mq48srkHku6WO5s1gy17OBreHiYK6+8kocffnhZP3f69Gna2tpCvzZv3rzc/7QkmN0OPQXmhGnweCMA0xMTVA2bi/uCa/Yk7dgk80S2Ojq6+gAIBAKhJeIrJlNwRUeLKr7ioqzMdFSEqr5a35k/+Go1f9edeCgpseFyJeWQ14aaGtPeOzU1e1WvmTTYPsRWbSpac4aGwT+5YMUXbWa8wBQOBmxFCVmsMO1ccQWhF3pOTkJX7auscdBgM3NQcxunQtu3BccPpcJ8L0vOBvO8c/j90H5uwX3H+zqoDJjAoejyDJjxZdFncOzNrPiy3uvXrVv5GJTgxfl2TtJwciC02dllgi/HRnWaCHDoEDz2GPzsZynU/pHitLIjAMte4uSmm27iphWUFXo8Hoo1fC7tjHqrYACm3jFVXhdPNbI9YNLi0vdck8xDkwxTVwdHgq2Ots7wan1NwTCpYMRcXLRQzYZ0CL76+iBYrTbrJFyWxOEw1dld7RVs4Dy0X4wKC6KCrzZz8q22sASw22HrVnj1VXP3cOvW+ffVYPuQ7A1mJk7h2CCMdS4SfJlAsYcyyiocOBxJOOBUl50Nu3aZZe23biWRf0k2GzTlb+HKwdfJujgR2l4f/D2VKr4qavLooZQyLsGFE1A1/43nzrNd1NIHQNH2NK6umfmXr8/g2JtZ8bXK+V5AKPiqppXGN4PB1+QghYN9AOTvStwcP0lhNht89rPJPor0ouALSOCMr927d1NZWckNN9zAs88+u+C+4+PjDAwMRP2S5LBvMglDTofprz//QgNeTN+9fUeGrOgoKSGy1dHWPUZurlkpq7nZDDXNHTQDhFOy4ss6oMjgy6r28njAGr4uyxY156ujZf6Kr3bzPFHwlSBLLZtXxVeIe2Nw1drJXgKj7YsEXxcAtTkuyhpwn8A2R0ufz4x7yG4Nz/iqChZ/pVLw5fNBG5Xmm2BL+HwunQguLGPLw1aUxosXVVZC8ByCysrwAjQSO1bwNbPia4XzvQAoKmI4vwyAsVMdZlv/WTyT5rrDcyDxr3ORjGB9Rir4iq/Kykoef/xxfv7zn3P48GG2bt3KDTfcwPPPPz/vzzzwwAMUFRWFftWm3ECftaNgrzmxKx0yHzq9vzYXOR05lbqYl5iKHG7PQABvgTlptSq+HH1p0OrY2BjepjbHmIha2bGzff7gq9O052hFxwRZSvA1NRV+XMEXhVtN+OCjnf6OnnmDr7y8POgw73vdlCvIXcjnPw/vex988YsJ/09PbjWzZfK7Bylym21Fw6bt5gL1KdPq6PNBO8E3xZbzC+47dLYHgK5sX3q3ENls4WBGn8HxYbU6trebRQRiUfEFjNWbfy9no3kuDrz+OtlMMoGT+gNVq/qzRdYsq+Lr3DkYH0/usSRR3IOvrVu38sd//Mfs2bOHa665hkceeYQPfOADfPe73533Z+699176+/tDv5pmzs2RhKk8tBeA4uk+6LzI1ElzYd9boT57ia3qauilhDHMzJZ9ZaYTu7m5GZ8LbMGb6ikdfM1V8aWT7lWJqvjq6o4KvoaDyzKb4MuE86r4ShAr+FpooZpz52BiAtxuqK9PyGGlspwN5qLNRzudLQOh4Muqao+q+OoyQW4XFar4WsimTfBf/xWu/Eog125T2VIx2MWW4HuOq9eERS3OdVSlyDV6dPDVuOC+441mllK/OwPuHij4iq+SEigKLmN6/nxsKr6A7CvNBXppfwdTE1O0vGDOpVrsNRSWqOdbZEUqK83r1e+HhoUrfzNZwlodI1199dWcOXNm3sddLheFhYVRvyQ5Nu3z0BY8YRr67QvkNpsVWyY36URCYsvphMoqe6jdcWeBeXtqampiV/AtoJ9ChslP3VUdBweh31w4KPiKjajgq6d3/oqvnl5AwVfCXBactfL22xAIzL1P5Hwve1JON1JL8ImZzSQ9DYvM+AoGuar4Sl0VV29kAie5/jGuLoG6XHCMmcpkx4Z1KfOUj2x19Ld1LLhvoN28pw6XVMb9uOLOWvVz5uqfEhs2W7jq68gRM9fU4Vh45uMS5F29D4CtgQYunGyh93XznO3JS5EkWSQd2Wya80WSgq/XXnuNysoM+FBdA4qK4GJWPQAdz5/E22+Cr9y9aluR2Itsd9zsNBfTIyMjXB5sI2mhmvJyU0CSUvLyzN1PCFd9KfiKiahWx0sD8w+37zFVM2p1TJBNm8xFzuBgeAn7mTTYPlp2Nr2OUgCGznQvHHz1mIUxNOMrdW3Y6qQBMw7iKhdcXWy2d1JB9ZaC5B3YDBUV0IFJTyea+xfc13HJVNFOedJ4RUfLV74CL76oIdjxZFXVPfmk+X3rVla7pLL9cnNxvo1TNLzRyfg50/I4UqHgS2RVljqbNYMtO/gaGhri+PHjHD9+HIDz589z/PhxGoOzbe69915uu+220P4PPfQQTzzxBGfOnOHEiRPce++9/PznP+fOO++Mzf+BxF1voQkpe14+x6YpU6lXceOBZB6SZKi6uvCA+zpbeIn4LcHzqJRsc7TMbHdU8BUTURVfvSPzV3z1mtBAFV8Jkp1NaIjRfCdRGmw/S3+ueS6PNfUuEnz1Aar4SmV1dXDKZi4k6icL2RW8IZNKg+0BsrJgOL8cgKmO4fl3nBwkZ9A8B6lZl4Aji7PsbLj6avMXIPFhVXw984z5fZVtjkCoKmUD73DujV7sHcGwdl2qlfqLpBlVfC0/+Dp69Ci7d+9m9+7dANx9993s3r2b++67D4C2trZQCAYwMTHBl770JXbu3MnBgwd54YUX+M///E9uueWWGP0vSLyN+0zwZX/9POX04MdG0bv2JPmoJBNFruzomZwMbV8XfKdqoTr12hwtkcHX+DgEV6NMqSugNBRV8dU3sUDwZYbAdVGhiq9EWWzOl4KvWYbzzXN5qm0wNMZhzuCr1zy3NeMrdTmd0FqwGYDygVwuc5rt51mfcm/7U2Um+OLS6Pw7jbZROGoqZ50bNcdVlsCq+LKGZcfivd7jYSS7ADsBBo43kd9vxhjk7UixF5VIulHwxbJvgxw6dIjAfPM8gB/96EdR33/5y1/my1/+8rIPTFKHY3MtnIQr+o8D0JpdQ03K9ZpJJqirg3PBVsfi0XDwZRW4p3TFl3VgTU1m0GsgYFogddW6KlEVX/3T5OeZ956ZwVdgYBobqvhKKGvO11wVX+PjYM3yVPAVMlHqhXaw9QzNqviyFmtwu93QZwIKVXyltuHaLXACinv91JeZbReo58oUWdExxOeDi+AcGJl/n9E2SidNi617c3WCDkzS2voZAWksKr5sNoYq1+G++BaBM614xsy8w7Jrdq7+zxZZy6yblQ0NZtXtNVgNmyKjNyWVFe01MyxcTADQVVKfxKORTBbZ6pg3FG51LA9mYCkdfFkVX42N0W2O6bwkfAqICr4moSLbfBk546vUMYUteMO5E4+yxkRZaF7E6dMwPQ3FxaTM8nYpwO8zfxfO/uEFWx0D/ebzVsFXavNvuxKA4t5B1pm59inX6giQVWduKLnGJ2C4b859AgNNVPi7ACjekQEzviT+rIovS4xucgQuM9cdOS19VGNmSFZduzkmf7bImlVXZ4YkT06Gr1PWGAVfsqiq9+yN+n6sxgP+6SQdjWSyyFbH7P5w8FVoutjSI/hqaoJ33jFfp9rVTxoqK4Mxu5tRcgCo9JtWnMiKr4oJ0woxhovskjyys5NzrGvOQsFX5GB7hb8h9uD7hHt4iMI8M7xwVvCVmwP9JkVRq2Nqy9+3nWns5E6NUdRqTqkbbetYl2IjsgrXeRgjOCzzwltz7jN0+jwO/EySRfl2PelkCdatC7+/u92zK8BWKH+/GafznulnsRNgxJZLdo2ekyKrYreHz9vWaLujgi9Z1LrKV+mmLPS903MBnqyHpsNJOybJTJGrOtr7AqE3qByTb6RP8KXB9jFjt4PHaw9VfZVPzA6+SkZNe04XFXh9+lhLGGvZ+o4O6O2NfkzzveaUs8EkIoXjAxTnmKqumcFXuX0SW/De0kRBGTk5iT9OWZr1l7k4i+lrdAyZsHKisjrlwndflZ12gsMPm+aeydf7VhsA7TYfeQV6H5UlyMkJV/Refrn5wI6BvKvNDfc9vAZAV06lbqCIxIKCL5EFNB3G+dKtNDvDZe+lW3tgpAWOfEThl8RUeTn0ubz4sWGbhm35kG0Du8k60iP4am6Gs2fN1wq+YiKy3bF4zKzwFBl8FQyZ5c478agtLJEKC6E6OAto5oB7BV9zygvOTiqb6qEg2wRdg4OD+P3+UPDlmTZveCPkUuDNS86BypJs3Agn2R61LXtL6r3v+3yEg6/muVtchs4GbyBkVybqsCQTWO2OsZjvZbEuzoOGisvVaSISC9aA+5aW5B5Hkij4kvn5p+HYF4AAffnFAExjp+byZiC4wMGxu/RhJDFjs0FlXTYdmPRiZwHsLAJbAKZw0JuVwiv2WQHA2Bi8/LL5eub8C1mRyJUdC4LzaSKDr9x+E3xpRcckmK/dUcHXnIq3mVDBG+gga3I4tH14eDgUfJWO9QFaqCEdbNgApwhfpLfjpXZL6i3+ExV8tVyYc5/xJnNTod+tN1FZhp3BofP798fuz7QdZdzuCn3rLxpRp4lILNx+u6nQf+SRZB9JUij4kvl1HYGRZgAmykzd/kXHOrLd1uylAIw0mf1EYiSy3fGyXLgiWPDQRiVVtVmxqqSPPZeL0FVqlxkQrIqv2Iis+MoZ6AOgr6+P0VGz8p2rP6LVUUFBYs0VfA0Pm5VNwbS/SEjBFhN85TLGwPle7ME3tMHBwVDwVTjaB5jB9prvldrcPYdpc4cXb7hAPRvH7k+5C3Sv13yGAtDWOuc+/nZzI2GkWBVfsgx/9Vfwi1/AZz4Tmz+v6TD8+qNcKiwJbXJVjanTRCQWSkrMokNrVKpeQkoqGG0LfenYbMKu88VzDK6M2E9ktSJXdtzshK3B+TYp3eZoiTxAh4PUP+D0EBl8uQZMG1hvxEyprODXanVMgssuM79HtjpasyM8HqioSPwxpTCbO5c+WxEA/afbyc/PB6KDr4JhU3mjFR1TXNNhOPIRRivCQ9guUM+m0ldT7gI9suJrurVrzn0cl0wF4qS3OmHHJRmguBg+/GFiMtguotNkwhv+80rqe1GniYisloIvmV9u+K7ftR99gZ994BY2/tnZBfcTWa3IlR1r7bDBaba3UB0ao5WyIg9w3TpwOpN3LBkkstXR0T8Y9Zjdbsd+qQ9Qq2NSzFXxpTbHBV1ymjKuobPdFBYWAtHBV86gCb60omMKi7hAd9RM4ccM3j7PejZ6g+dJKXSBXlICnQ6Too63Ds3eYWqY3MFg621Nii1JKWtHRKdJTv1YaHPZ+p7gV+o0EZGVU/Al86s4CO4awIYre5KPfOIw9bWNETvYwF1r9hOJkchWR+80WMsqpEXFV2TwpTbHmPF6TfULgKM3+qItPz8fW4+pAlOrYxJYwdf582a+HSj4WsSA24S4E819FBQUANHBl1XVqIqvFBZxgV5b2cwF6gFT8bXB8w6pdoFus8FEkVmd2981MnuH0TYKRs1NBeeGOSr7RRIhooPEc1ln6Gv7zPdBdZqIyAoo+JL52R2w9++C38xcRjj4/d6HzH4iMRLZ6lg6AV6zQryCrzUssuLL1jeMM6KSLj8/H3rNhVwnHlV8JZrXa1pd/H5oaDDbFHwtaKTAPJen2wfnDL6yIoIvVXylqIgL702+szzJBxklh1MF28jPGZ5zv2SbLg9WzfaOzn5wpIXSSTMr0b2lZvbjIokQ0UFiqw9+UQzMXNxWnSYisgIKvmRhtbfAwZ+Be8bMB3eN2V57S3KOSzJWbW244it/BErGzXYFX2tX5Iwv+sZDc5HABF+BPvMkUcVXEthss+d8Kfha0GSZeZLaLw2Fgq/+/n7GghVz9j4TnOj5nMIiLrw3es7xRR6ihF78lfZ590s2e3Dl4ezhMZiein6w7Qw5AfM+Wry9auaPiiRGRKcJHuCu4K8QdZqIyMop+JLF1d4CH7wANzwLB35sfv/geYVeEheRM76cA5AX7MpQ8LV2RQZfgb6pWcEXfWaOjmYiJUnknK/eXmgNrhq3fXvyjimFBSqDAcRAOPjq7Ixo6+k3FTlqdUxhERfoG73nABgnJ/R1Kl6gu+rNDSWH3w9t56Iem37HVGt2UY53Xc6snxVJiJmdJlcBmwl/D+o0EZEVU/AlS2N3gPcQ1H/c/K4PHYmTvDwYKzV3nO1j4DTdF+k33F7BV8yUlkKvw8z4so2BpyB8YVZVkI1twqz2NF1arvUEkiEy+DpxwnxdWwtFRck7phTmWGcS/LyRIUqLcgFob28PPW5VMKrVMYVFXKCX5vdRkmc+qDZ5z5KqF+gVNbl0Y+Z80Xgy6rHBt1sA8zmrhVglqdRpIiJxouBLRFJOaV0BfZiLZltwUazhoiqCC6ClrspKqKoyS2ht3rz4/rIkdjtke4qZJAuAHcXhdGtLnrnIHMNFnrcgKce35kUGX2pzXFTuxnoAiib6qSo1wUhHR4d5LDeXQL950+tzlik7TGURF+hbfKZiarPvTMpeoPt80E5wCGLzmajHhs6a4K7TWambB5J86jQRkTjISvYBiIjMVFcHLcerKaYfgF6KKV+Xv8hPpQCHA159FaamIDc32UeTUbw+O91t5VTSziZ3ePuGbDOrposKvD7dy0kKa8ZXQwO8/rr5WsHXvPK2mIrW8qlufEUmuLUqvorzcnB0m1ZHW1kZtpnrykhqqb0Fqj/EA9NvcvjJBj549+dg3b+lVKWXxQq+dnACmt+Jemy80Syo0O9Wb62kCKvTREQkRhR8iUjKsVZ2vBzTjpEW870sGsoTF9bKjpW0U+f0h7ZXOyYB85hWdEyS9evB5YKxMfjlL802BV/zKt1uBp7nM4zPOQGEK762FmdDt9nPVVWelOOTZbI7ePetu3j3rQBbkn008/L54BzBYfutTVGP+TuGABgp1mB7ERHJTLo9LiIpJ3JlR0iT+V4SV5ED7itt4RXJPH4TfHXiUeaYLA4HbAle8Dc2mt8vvzx5x5PiyuoLGMRUsOaZotZw8FVgKoUuUUKZVz1nEjuRrY6BtvaoxxyXzEqikx4FXyIikpkUfIlIyrEqviwtVFNX61/gJyTTRQZf5f5w8FU6OQYEWx0VfCWPNecLwGaL/l6iZGVBp908WbN7gq26XV0AbMgxvY16Pkuseb3QFqz4mmrtCz8wNULugAm+ArX1iT8wERGRBFDwJSIpp871q9nBV9cXoOlwEo9KkslqdQQonpwIbS8cMyvgqdUxyaw5X2BWNHW7599XuJRtlmvM6jYVi36/CfarnWaFUq3oKLGWlwf9LtM+O9kxHH5gtI2CsUEAsjfUJ+HIRERE4k/Bl4iklqbD1DbfNqvVsa7gOBz5iMKvNSqy4is/GHYBuEdNxZdaHZMsssJL870WNeg2AYTj0njUdp/dBGDdlOv5LDE3WRqcGxdcQAGAnvPkT5kgzL2lZo6fEhERSX8KvkQkdfin4dgXqCxupd0WvuproZq6sovmm2N3mf1kTYms+ModCVd8uYZU8ZUSFHwty1iRKedyXBqL2l4+bd7buqhQxZfEXMBj3iSzBiKedxdOADBEHmUbipJxWCIiInGn4EtEUkfXERhpJssxjb84/PbUho+qklYgACNNZj9ZUyIrvrKHJkPbswZNCKaZSEm2ZYuZ7QUKvpZgstw8WZ39I1Hbi6bMzC9VfEk8ZNWZEQLZ4xMweMlsbDwDmBtMvkpbsg5NREQkrhR8iUjqGG0LfZlXPkwX5YyTzXhJDlmO6Tn3k7UhMviyD4aH29NvWsM68VBRkYwjEwByc2HPHrPC4/79yT6a1FdlWspyhoajNueNm1BXwZfEQ0FdBWO4zDeNJwGYfMesxNpMjapmRUQkYyn4EpHUkVsZ+rK2vJn38AyH+BVFFf3z7idrQ0kJ9GWZ+TS2gfAKn/ZBE4hOF5fidCbl0MTyv/83vPkm1Ncn+0hSnnP9OgAKRgdxu8Lbc0aCqzyq1VHiwFdlp51gutX0NgDD50zlV5utipKSZB2ZiIhIfCn4EpHUUXEQ3DWAjbryRt7iCl7iGurKGoM72MBda/aTNcVuh0BZGQCOET85dih1gmPChGB2r8q9kq68PHrWl8wrd6MJvoon+/AWhrc7hszvPZRRXp6EA5OM5vMREXyZFsfxpgEA+t3eULeyiIhIplHwJSKpw+6AvX8HQG1pc2hzbVkTEDwj3/uQ2U/WHFdVOf7g82BTHmzNN9vHcJFfpaHMkj4KtlYBUOgfZFNZVmi7fdAEuZOFJWRlzfmjIivm80EbwYrpVnNDyd9u0tbhYvU5iohI5lLwJSKppfYWOPgz6qrDs2/qyhpNJdjBn5nHZU3yVGbRg6n62uyGjblmexcV+Cr1cSbpo3xTcWjW0hXFOaHtzmHT6mirKEvKcUlmi6r4am0BwNFrFliY9FQn67BERETiTlcKIpJ6am+h9tb/Ffq27obb4YPnFXqtcZED7tfnwPrgbCSt6CjpxuO10Yqp+lqfXQAEW3enTMVXVqUGfEnsRVZ8+du7YGqUnIHgyqK165J4ZCIiIvGl4EtEUlJdfbidsW7nFWpvlOjgK9fBRreZZt+JR8GXpBW3Gzrt5knr8Zue3c155rEJnBRUFyfpyCSTVVRAB+Z5N9k2CEPN5I+ZVkfn+vokHpmIiEh8aYKEiKSkkhLYuhW6u2HTpmQfjaQCny8cfH3s3deRNTkJJ14wrY4aTyNpptdVAaNQPG5KFzfmAn3BFR29ui8psed0wkhBOQzCdMcoXHwLOwGmcFCwSXcPREQkcyn4EpGUZLPBsWMwMQF5eck+GkkFkRVf5f5pmBgHzLbtumaTNDOUZ4KvvBETctUFW3e7KVcFo8TNVLkHBsHeNwYX3gaglSq8VaqqFhGRzKVbiiKSsvLyTOWXCERXfNHdAz29gGl1VMWXpJvxEvNcdg9PA1BjOncVfElc2SvNm2X20ChcaACghWq9h4qISEZbdvD1/PPPc/PNN1NVVYXNZuOJJ55Y9Geee+459u7dS05ODhs2bOCxxx5bybGKiMgaFlnxRU8fge4BQMPtJT1NVZgh4+7hCQCshUm7qMCj2fYSJ9nragCw+wMEXn8dgGZqFHyJiEhGW3bwNTw8zJVXXsnDDz+8pP3Pnz/P+9//fg4ePMhrr73GV7/6VT7/+c/z85//fNkHKyIia5fXa6phAPw9w0x1jQFmW0VFMo9MZPns1dUAuEfNqnoVNrNdFV8STxU1uXRTBsD06xcAU/Gl55yIiGSyZc/4uummm7jpppuWvP9jjz1GXV0dDz30EADbtm3j6NGjfPe73+XWW29d7n9eRETWqJIS6HWUwTRM90wSGPMDMFlUSpYmVkqasVbRKxwbID8HSs3TmW7KVfElcePzQRuVlNMDDaZqtjvbq1maIiKS0eI+4+vFF1/kxhtvjNr2u7/7uxw9epTJyck5f2Z8fJyBgYGoXyIisrbZbOAvLTXf9E9gHzQtYoGKsiQelcjKuLesA6BoapDaQsifMumtgi+JJ58P2jF9jVlDZr7ccLH6HEVEJLPFPfhqb2/HO6N+2uv1MjU1RXd395w/88ADD1BUVBT6VVtbG+/DFBGRNGD3mlbHrOFJsibNRZuzShdtkn6KN5QxGSy8vywPckbN14OuEtzuZB6ZZLLI4MsyVVGVpKMRERFJjISs6miz2aK+DwQCc2633HvvvfT394d+NTU1xf0YRUQk9eXUmAs269NjnGwKa4qTdjwiK+WttIcCiC254Bozz2p/cXESj0oyndXqGClQU5ekoxEREUmMuE9F8fl8tLe3R23r7OwkKyuLsrK521NcLhculyvehyYiImmmrCqHPoooph+ATjx4fQm5hyMSUx4PnKGKWpqpc2ThCs6ss5WrdVfiZ66Kr+zgvDkREZFMFferhWuuuYann346attTTz3Fvn37cDqd8f7Pi4hIBvF6oYvwEo5dVGg1MklLJSXhAKLSn49rzMysy6rSEqUSPyUl0OUIv2l2U0Z5bW4Sj0hERCT+lh18DQ0Ncfz4cY4fPw7A+fPnOX78OI2NjYBpU7zttttC+99+++1cvHiRu+++m1OnTvEP//AP/PCHP+RLX/pSbP4PRERkzfD5ZgdfPo34kjRks0F/rplZVzfuxB4cA5FbW7nQj4msis0GE8Xloe+bqcHn8SfxiEREROJv2cHX0aNH2b17N7t37wbg7rvvZvfu3dx3330AtLW1hUIwgPXr1/PLX/6SX/3qV+zatYtvfvObfO973+PWW2+N0f+CiIisFTMrvjrxqOJL0tZwvgkgakfN9wMUUFatyfYSR02HCeQNhb5toRrfxc9A0+HkHZOIiEicLXvG16FDh0LD6efyox/9aNa266+/nldffXW5/ykREZEoXi+cnVHxdYWCL0lTEyUe6IKibjOzTq27EldNh+HIR3AU/ysE71E3U8NVOUfhyL/CwZ9B7S3JPUYREZE40ERgERFJG2p1lEwy7TFtja5xM9+rm3I8nmQekWQs/zQc+wIQoKB0kDHMIlItVOMrbjP7HLvL7CciIpJhFHyJiEjamD3cvpzyUl2oSXpy1FZHfd9NuSq+JD66jsBIMwC+kg7aMKFrK5VUFHQBARhpMvuJiIhkGAVfIiKSNooHD9NrLw59P5HrIuuX9ZpPI2kpe0N91PddVKjiS+JjtC30pa+onRNcDkBjXh3OrKk59xMREckUCr5ERCQ9NB3G9sJHmMoLj6f0F9hgpAWOfEThl6Sdgs01TEeciqniS+ImN7xaqK+4ndv4Z/bzEu2llfPuJyIikikUfImISOqLmE9DYXizvchvtoHm00jaqfA56CRc4tVrL6W4OHnHIxms4iC4awAbvqJ2einlZfbjK2oP7mADd63ZT0REJMMo+BIRkdQXMZ/GWRxuy3GVjge/0nwaST9eL6FZSwDj+cXYbEk8IMlcdgfs/TsAfMUdoc2+4nYg+KTb+5DZT0REJMMo+BIRkdQXMXfGUT7Fy1zFM7ybotL+efcTSXUeD7RSFfp+WuVeEk+1t8DBn+H1hcMtX1G7qQQ7+DPzuIiISAZS8CUiIqkvYu6Mp7iL/fyWG/hvvMWd8+4nkuoqKqIrvuzFLrXrSnzV3kLeR09RkG8qZ31X3QIfPK/QS0REMpqCLxERSX0z5tOY1hyb5tNIWnO2H6bPWRz63uE8C0/Wa6EGiS+7A1+lWSTEt3mT2htFRCTjKfgSEZHUFzGfxlsUrvLyFnWg+TSSlpoOw5GPMOLODW3KLR3VKqWSENddB9nZcNVVyT4SERGR+FPwJSIi6cGaT+PxhzZ5izo0n0bST8QqpZMFTgCmcFBYPoBWKZVE+MEPoLsbNm9O9pGIiIjEn4IvERFJH7W34Lv1J6FvfTc/ovk0kn4iVimdKjYtZ5148BR1BXfQKqUSXzYbFBQk+yhEREQSQ8GXiIiklZo6B3l5UFYG5dvepfZGST8Rq4+OVLr5Nl/mbh4Mtu7OvZ+IiIiIrExWsg9ARERkOfLy4KWXwOkEhzIvSUeRq5QWdXEP3wbgnsL/Z979RERERGRlFHyJiEja2bEj2UcgsgrWKqUjLVFVXuGvbeZxrVIqIiIismpqdRQRERFJpIhVSj2FXaHN5QXdaJVSERERkdhS8CUiIiKSaMFVSn0+s3JjWX43zqwprVIqIiIiEmNqdRQRERFJhtpb2HvXh/iD33Sy/4pmuOFZ096oSi8RERGRmFHwJSIiIpIkWdkOfvKEB/Ak+1BEREREMpJaHUVEREREREREJCMp+BIRERERERERkYyk4EtERERERERERDKSgi8REREREREREclICr5ERERERERERCQjKfgSEREREREREZGMpOBLREREREREREQykoIvERERERERERHJSAq+REREREREREQkIyn4EhERERERERGRjKTgS0REREREREREMpKCLxERERERERERyUgKvkREREREREREJCMp+BIRERERERERkYyUlewDWIpAIADAwMBAko9ERERERERERESSycqHrLxoIWkRfA0ODgJQW1ub5CMREREREREREZFUMDg4SFFR0YL72AJLiceSzO/309raSkFBATabLdmHExMDAwPU1tbS1NREYWFhsg9HZM3Ra1AkefT6E0kuvQZFkkuvQZHVCwQCDA4OUlVVhd2+8BSvtKj4stvt1NTUJPsw4qKwsFBvdiJJpNegSPLo9SeSXHoNiiSXXoMiq7NYpZdFw+1FRERERERERCQjKfgSEREREREREZGMpOArSVwuF3/xF3+By+VK9qGIrEl6DYokj15/Isml16BIcuk1KJJYaTHcXkREREREREREZLlU8SUiIiIiIiIiIhlJwZeIiIiIiIiIiGQkBV8iIiIiIiIiIpKRFHyJiIiIiIiIiEhGUvCVBI888gjr168nJyeHvXv3cuTIkWQfkkhGeuCBB7jqqqsoKCjA4/Hw4Q9/mNOnT0ftEwgE+Mu//EuqqqrIzc3l0KFDnDhxIklHLJK5HnjgAWw2G3fddVdom15/IvHV0tLCpz71KcrKynC73ezatYtjx46FHtdrUCR+pqam+PM//3PWr19Pbm4uGzZs4Bvf+AZ+vz+0j16DIomh4CvBfvrTn3LXXXfxta99jddee42DBw9y00030djYmOxDE8k4zz33HHfccQcvvfQSTz/9NFNTU9x4440MDw+H9vnOd77Dgw8+yMMPP8wrr7yCz+fjve99L4ODg0k8cpHM8sorr/D444+zc+fOqO16/YnET29vL+9617twOp3813/9FydPnuRv/uZvKC4uDu2j16BI/Hz729/mscce4+GHH+bUqVN85zvf4a//+q/5/ve/H9pHr0GRxLAFAoFAsg9iLdm/fz979uzh0UcfDW3btm0bH/7wh3nggQeSeGQima+rqwuPx8Nzzz3HddddRyAQoKqqirvuuouvfOUrAIyPj+P1evn2t7/NZz/72SQfsUj6GxoaYs+ePTzyyCP81V/9Fbt27eKhhx7S608kzu655x5+/etfz9tZoNegSHz93u/9Hl6vlx/+8Iehbbfeeitut5t/+Zd/0WtQJIFU8ZVAExMTHDt2jBtvvDFq+4033shvfvObJB2VyNrR398PQGlpKQDnz5+nvb096jXpcrm4/vrr9ZoUiZE77riDD3zgA/zO7/xO1Ha9/kTi68knn2Tfvn38/u//Ph6Ph927d/ODH/wg9LhegyLxde211/Lf//3fNDQ0APD666/zwgsv8P73vx/Qa1AkkbKSfQBrSXd3N9PT03i93qjtXq+X9vb2JB2VyNoQCAS4++67ufbaa9mxYwdA6HU312vy4sWLCT9GkUzzk5/8hFdffZVXXnll1mN6/YnE1zvvvMOjjz7K3XffzVe/+lVefvllPv/5z+Nyubjtttv0GhSJs6985Sv09/dz2WWX4XA4mJ6e5lvf+hYf//jHAX0OiiSSgq8ksNlsUd8HAoFZ20Qktu68807eeOMNXnjhhVmP6TUpEntNTU184Qtf4KmnniInJ2fe/fT6E4kPv9/Pvn37uP/++wHYvXs3J06c4NFHH+W2224L7afXoEh8/PSnP+Vf//Vf+fGPf8zll1/O8ePHueuuu6iqquIP//APQ/vpNSgSf2p1TKDy8nIcDses6q7Ozs5ZSb+IxM6f/umf8uSTT/Lss89SU1MT2u7z+QD0mhSJg2PHjtHZ2cnevXvJysoiKyuL5557ju9973tkZWWFXmN6/YnER2VlJdu3b4/atm3bttCCSvoMFImvP/uzP+Oee+7hYx/7GFdccQWf/vSn+eIXvxia66zXoEjiKPhKoOzsbPbu3cvTTz8dtf3pp5/mwIEDSToqkcwVCAS48847OXz4MM888wzr16+Penz9+vX4fL6o1+TExATPPfecXpMiq3TDDTfw5ptvcvz48dCvffv28clPfpLjx4+zYcMGvf5E4uhd73oXp0+fjtrW0NDAunXrAH0GisTbyMgIdnv05bbD4cDv9wN6DYokklodE+zuu+/m05/+NPv27eOaa67h8ccfp7Gxkdtvvz3ZhyaSce644w5+/OMf8x//8R8UFBSE7qgVFRWRm5uLzWbjrrvu4v7772fz5s1s3ryZ+++/H7fbzSc+8YkkH71IeisoKAjN07Pk5eVRVlYW2q7Xn0j8fPGLX+TAgQPcf//9fPSjH+Xll1/m8ccf5/HHHwfQZ6BInN18881861vfoq6ujssvv5zXXnuNBx98kD/6oz8C9BoUSSQFXwn2B3/wB/T09PCNb3yDtrY2duzYwS9/+cvQ3TcRiZ1HH30UgEOHDkVt/8d//Ec+85nPAPDlL3+Z0dFRPve5z9Hb28v+/ft56qmnKCgoSPDRiqw9ev2JxM9VV13FL37xC+69916+8Y1vsH79eh566CE++clPhvbRa1Akfr7//e/z9a9/nc997nN0dnZSVVXFZz/7We67777QPnoNiiSGLRAIBJJ9ECIiIiIiIiIiIrGmGV8iIiIiIiIiIpKRFHyJiIiIiIiIiEhGUvAlIiIiIiIiIiIZScGXiIiIiIiIiIhkJAVfIiIiIiIiIiKSkRR8iYiIiIiIiIhIRlLwJSIiIiIiIiIiGUnBl4iIiIiIiIiIZCQFXyIiIiIiIiIikpEUfImIiIiIiIiISEZS8CUiIiIiIiIiIhlJwZeIiIiIiIiIiGSk/x8FPCbD8AsxXwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ + "factor_option_1 = σ_Q / σ_Q_new\n", + "factor_option_2 = Σ_T[:l_new] / Σ_T_new[:l_new]\n", "\n", - "$$\n", - "\\begin{align}\n", - "LB_{j,i}^{(m+k)} ={}& \n", - "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", - "\\sqrt{\n", - "m\\left(\n", - "1 - \\left(\\max(\\rho^{(m)}_{j,i},0)\\right)^{2}\n", - "\\right)\n", - "} \\quad (2)\n", - "\\\\\n", - "\\end{align}\n", - "$$\n" - ] - }, - { - "cell_type": "markdown", - "id": "a6b6a92f", - "metadata": {}, - "source": [ - "And, the pearson correlation, $\\rho^{(m)}_{j,i}$, can be calculated as follows: " - ] - }, - { - "cell_type": "markdown", - "id": "06f74a00", - "metadata": {}, - "source": [ + "factor = np.maximum(factor_option_1, factor_option_2)\n", + "LB_option_3 = factor * np.sqrt(m * (1 - np.square(ρ[:l_new]))) \n", "\n", - "$$\n", - "\\begin{align}\n", - "\\rho^{(m)}_{j,i} ={}& \n", - "\\frac{\\sum \\limits_{t=0}^{m-1}{T[i+t]T[j+t]} - m\\mu_{i,m}\\mu_{j,m}}{m\\sigma_{i,m}\\sigma_{j,m}} \\quad (2a)\n", - "\\end{align} \n", - "$$\n" + "# assetion\n", + "assert np.all(LB_option_3 <= D_new)\n", + "\n", + "# plot\n", + "plt.figure(figsize=(15, 5))\n", + "plt.title('Plotting distance profile and its lower bound')\n", + "plt.plot(D_new, color='k', label='The actual distance profile')\n", + "plt.plot(LB_option_3, color='orange', marker='o', label='The LowerBound of distance profile (Option 3)')\n", + "plt.plot(LB_option_1, color='b', label='The LowerBound of distance profile (Option 1)')\n", + "plt.plot(LB_option_2, color='r', label='The LowerBound of distance profile (Option 2)')\n", + "plt.legend(title='distance profile for Q_new')\n", + "plt.show()" ] }, { "cell_type": "markdown", - "id": "1e23d962", + "id": "1dd3b3a4", "metadata": {}, "source": [ - "As a side: $\\rho^{(m)}_{j,i}$ and $d^{(m)}_{j,i}$ are related to each other according to the following formula:" + "## 3. Ranked Lower Bound (LB) Profile is preserved!" ] }, { "cell_type": "markdown", - "id": "bd2e70a1", + "id": "08e84eef-92a1-4d6f-a1b6-45ffe8b2693f", "metadata": {}, "source": [ + "For the sequence `T[i:i+m]`, we can calculate its distance with all subsequences (of length `m`) in `T`. For `T[i:i+(m+1)]`, we can compute the LB of its distance to all subsequences (of length `m+1`) in `T` based on the distances computed before for length `m`. Let's consider two subsequences `T[j:j+(m+1)]` and `T[j':j'+(m+1)]`, and let's assume $LB_{i,j} \\le LB_{i,j'}$, i.e.:\n", "\n", - "$$\n", - "\\begin{align}\n", - "d^{(m)}_{j,i} ={}& \n", - "\\sqrt{\n", - "2m \\left(\n", - "1-\\rho^{(m)}_{j,i}\n", - "\\right)\n", - "} \\quad {(2b)}\n", - "\\\\\n", - "\\end{align}\n", - "$$\n" + "$$LB^{(m+1)}_{i,j,m} \\leq LB^{(m+1)}_{i,j^{'},m}$$" ] }, { "cell_type": "markdown", - "id": "1dd3b3a4", + "id": "c88e8f3f-b189-4ab5-ad48-549943f6bfc8", "metadata": {}, "source": [ - "# 3- Core Idea" + "and if we expand this:" ] }, { "cell_type": "markdown", - "id": "9b0ebd60", + "id": "09cf47d3-0f80-4146-b040-1d165dceb890", "metadata": {}, "source": [ - "The core idea of VALMOD can be explained as follows:" + "$$\\frac{\n", + "\\sigma_{i,m}}\n", + "{\\sigma_{i,m+1}\n", + "}\n", + "\\sqrt{m(1-r_{i,j,m}^{2})} \\leq \\frac{\n", + "\\sigma_{i,m}}\n", + "{\\sigma_{i,m+1}\n", + "}\n", + "\\sqrt{m(1-r_{i,j',m}^{2})}$$" ] }, { "cell_type": "markdown", - "id": "d3c23204", + "id": "2b2f44e0-fdfe-434e-afac-6e0e1e649ffe", "metadata": {}, "source": [ - "## 3-1: Ranked Lower Bound (LB) of Distance Profile \n", - "Ranked LB of distance profile refers to the values of the LB of a distance profile sorted in the ascending order. It is important to note that such ranking is preserved for all subsequence length range `(min_m+1, max_m)` having assumed that they are all being calculated based on the $\\rho_{j,i}$ values for length `min_m`.\n", + "As shown in previous section, we could have computed different LB by using $\\frac{\\sigma_{j,m}}{\\sigma_{j,m+1}}$ or $\\frac{\\sigma_{j',m}}{\\sigma_{j',m+1}}$, respectively, for the left or right terms of the above inequation. However, using the common factor $\\frac{\\sigma_{i,m}}{\\sigma_{i,m+1}}$ allows us to preserve this rank as we increase the length of subsequences! To better see this, let's multiply both sides by the positive factor $\\frac{\\sigma_{i,m+1}}{\\sigma_{i,m+2}}$, and that gives:\n", + "\n", "\n", - "In other words,
\n", - "**IF:**" + "$$\\frac{\n", + "\\sigma_{i,m}}\n", + "{\\sigma_{i,m+2}\n", + "}\n", + "\\sqrt{m(1-r_{i,j}^{2})} \\leq \\frac{\n", + "\\sigma_{i,m}}\n", + "{\\sigma_{i,m+2}\n", + "}\n", + "\\sqrt{m(1-r_{i,j'}^{2})}$$" ] }, { "cell_type": "markdown", - "id": "33bc22e8", + "id": "da6ab407-e79a-427b-8617-6971621ca67f", "metadata": {}, "source": [ - "\n", - "$$\n", - "\\begin{align}\n", - "LB^{(m+k_{1})}_{j,i} \\leq{}& \n", - "LB^{(m+k_{1})}_{j,i^{'}}\n", - "\\\\\n", - "\\end{align}\n", - "$$\n" + "which is $LB^{(m+2)}_{i,j,m} \\leq LB^{(m+2)}_{i,j^{'},m}$, and those are the LB values for the distance between `T[i:i+(m+2)]` and `T[j:j+(m+2)]` (left) and the distance between `T[i:i+(m+2)]` and `T[j':j'+(m+2)]` (right). Note that the LB values for subsequences of length `m+2` are computed based on the distances computed for subsequences of length `m`!" ] }, { "cell_type": "markdown", - "id": "02b333a3", + "id": "293d02f6-af1f-413f-ab55-1fd0b5c7c25a", "metadata": {}, "source": [ - "**THEN:**" + "**Note:**\n", + "\n", + "(1) It was shown that the ranked LB is preserved. In fact, the order of subsequences in ranked LB for subseqence $m'$ is the same as the order of subsequences in ranked distances for subsequence $m$ (where $m < m'$). In other words: \n", + "\n", + "$$d_{i,j}^{(m)} <= d_{i,j'}^{(m)} \\implies \\rho_{i,j}^{(m)} >= \\rho_{i,j'}^{(m)} \\implies r_{i,j}^{(m)} >= r_{i,j'}^{(m)} \\implies LB_{i,j,m}^{(m')}<=LB_{i,j',m}^{(m')}$$" ] }, { "cell_type": "markdown", - "id": "3fc03958", + "id": "63474717-ad3d-4c29-a3d5-03a7b7ca2229", "metadata": {}, "source": [ + "(2) Note that: $LB_{i,j,m}^{(m')} \\le LB_{i,j',m}^{(m')}$ does NOT mean $d_{i,j}^{(m')} \\le d_{i,j'}^{(m')}$. Suppose we compute the LB values between subsequence $T[i:i+m']$ and all of its neighbours, and they are ranked as follows:\n", "\n", - "$$\n", - "\\begin{align}\n", - "\\frac{\n", - "\\sigma_{j,m+k_{1}}}\n", - "{\\sigma_{j,m+k_{2}}\n", - "}\n", - "LB^{(m+k_{1})}_{j,i} \n", - "\\leq{}&\n", - "\\frac{\n", - "\\sigma_{j,m+k_{1}}}\n", - "{\\sigma_{j,m+k_{2}}\n", - "}\n", - "LB^{(m+k_{1})}_{j,i'}\n", - "\\\\\n", - "\\frac{\n", - "\\sigma_{j,m+k_{1}}}\n", - "{\\sigma_{j,m+k_{2}}\n", - "}\n", - "\\left[\n", - "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k_{1}}}\n", - "\\sqrt{\n", - "m\\left(\n", - "1 - \\max(\\rho^{(m)}_{j,i},0)^{2}\n", - "\\right)\n", - "}\n", - "\\right]\n", - "\\leq{}&\n", - "\\frac{\n", - "\\sigma_{j,m+k_{1}}}\n", - "{\\sigma_{j,m+k_{2}}\n", - "}\n", - "\\left[\n", - "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k_{1}}}\n", - "\\sqrt{\n", - "m\\left(\n", - "1 - \\max(\\rho^{(m)}_{j,i'},0)^{2}\n", - "\\right)\n", - "}\n", - "\\right]\n", - "\\\\\n", - "LB^{(m+k_{2})}_{j,i} \\leq{}& \n", - "LB^{(m+k_{2})}_{j,i'}\n", - "\\\\\n", - "\\end{align}\n", - "$$\n" + "$LB_{i,j_{1}} \\le LB_{i,j_{2}} \\le LB_{i,j_{3}} \\le LB_{i,j_{4}} \\le .....$\n", + "\n", + "We can start computing the actual distance for pair $(i, j_{1})$. If we are lucky and the actual distance is $\\le LB_{i,j_{2}}$, then it means it will be less than the actual distances that will be computed for other neighbours! No need to continue futher! We already found the nearest neighbour. If not, we can try the second pair, i.e. $(i, j_{2})$, and so on. " ] }, { "cell_type": "markdown", - "id": "8f1df704", + "id": "833c4f6b", "metadata": {}, "source": [ - "## 3-2: Accelerating Matrix Profile calculation\n", - "Storing all \"ranked LB\" for all indices requires a significant amount of memory. Instead, we can just store the `top-p` smallest values of the ranked $LB^{(m+k)}_{j}$ and their corresponding indices. The parameter `p` is set by the user (e.g. see Table 2 on page 28). As we will see in the next section, we can use this meta information to skip some unnecessary calculation of distances for length larger than `min_m`." + "# 4-VALMOD algorithm\n", + "The [VALMOD paper](https://arxiv.org/pdf/2008.13447.pdf) proposes different algorithms to address different problems. Let's start with the first problem as described in the paper:\n", + "\n", + "> **Problem 1 (Variable-Length Motif Pair Discovery)** Given a data series T and a subsequence length-range [m_min,...,m_max], we want to find the data series motif pairs of all lengths in [m_min,...,m_max], occurring in T." ] }, { "cell_type": "markdown", - "id": "833c4f6b", + "id": "a55f578e-4051-4d12-808d-69cd65a825e2", "metadata": {}, "source": [ - "# 4-VALMOD algorithm\n", - "The VALMOD algorithm (see Algorithm1 and Algorithm2 on page 13) discovers variable-length matrix profile and the matrix profile indices. In this section, we implement the functions by taking a bottom-up approach. So, we first implement the functions that are being called by VALMOD algorithm, and then we implement VALMOD algorithm." + "## 4-1- Naive Approach" ] }, { "cell_type": "markdown", - "id": "f6cbecbd", + "id": "8aa66202-f114-44d8-9686-8c37e023fd58", "metadata": {}, "source": [ - "## 4-1- ComputeMatrixProfile (see algorith3 on page 15)\n", - "This algorithm scans all pairs of subsequences. However, instead of returning the matrix profile and its indices, the algorithm returns the `top-p` smallest value of each distance profile and their corresponding indices.\n", - "\n", - "In the paper, the authors used the LB formula to convert distances to LB. So, as they scan pairs of subsequences, they calculate LB for each pair of subsequences. The authors used max_heap data structure to store `top-p` smallest LB values for each distance profile. " + "A naive approach is to compute exact matrix profile for each window size." ] }, { - "cell_type": "markdown", - "id": "eb51f0f6", + "cell_type": "code", + "execution_count": 9, + "id": "ee52892a-6042-4889-b405-16db44d5412b", "metadata": {}, + "outputs": [], "source": [ - "**NOTE (1): Our implementation is slightly different than what proposed in the Algorithm3 of the paper**\n", - "We can skip line19 of Algorithm 3 provided in the paper. We do NOT need to calculate $LB^{(m+k)}_{j,i}$ for each $d^{(m)}_{j,i}$. As we prove below, the ranked distance profile, $DP^{(m)}_{j}$, is in the same order as its corresponding ranked Lower Bound, $LB^{(m+k)}_{j}$. Therefore, we can simply return the `top-p` smallest value of distance profile and then calculate their corresponding LB value all at once." + "def naive_find_motif(T, m_values):\n", + " m_values_sorted = np.sort(m_values)\n", + " \n", + " num_m = len(m_values_sorted)\n", + " motif_distance = np.full(num_m, np.inf, dtype=np.float64)\n", + " motif_index = np.full(num_m, -1, dtype=np.int64)\n", + " motif_index_nn = np.full(num_m, -1, dtype=np.int64)\n", + " \n", + " for i, m in enumerate(m_values_sorted):\n", + " mp = stump(T, m, k=1)\n", + " \n", + " idx = np.argmin(mp[:, 0]) # motif index \n", + " \n", + " motif_distance[i] = mp[idx, 0]\n", + " motif_index[i] = idx\n", + " motif_index_nn[i] = mp[idx, 1]\n", + " \n", + " out = np.empty((num_m, 4), dtype=object)\n", + " out[:, 0] = motif_distance\n", + " out[:, 1] = motif_index\n", + " out[:, 2] = motif_index_nn\n", + " out[:, 3] = m_values_sorted\n", + " \n", + " return out" ] }, { "cell_type": "markdown", - "id": "3a1ba5e4", + "id": "f6cbecbd", "metadata": {}, "source": [ - "**IF:**\n", + "## 4-2- VALMOD Approach\n", + "[See Algorith3 on page 15](https://arxiv.org/pdf/2008.13447.pdf). This algorithm scans all pairs of subsequences of length `m`. However, instead of returning just the matrix profile and its indices, the algorithm also computes the lower bound values of `m+1`, and return `top-k` smallest lower bound values from each lower bound profiles. Here, we are going to return top-k matrix profile for length `m` as that allows us to calculate those `top-k` lower bound values later for `m+1`! Below, we've shown that top-k matrix profile (for length `m`) corresponds to top-k lower bound values for length `m + k`. In other words, we would like to show:\n", "\n", - "$$\n", - "\\begin{align}\n", - "d^{(m)}_{j,i} \n", - "\\geq{}&{}\n", - "d^{(m)}_{j,i'}\n", - "\\\\\n", - "\\end{align}\n", - "$$\n", - "\n" + "$$d_{i,j}^{(m)} \\le d_{i,j'}^{(m)} \\implies LB^{(m+k)}_{i,j,m} \\le LB^{(m+k)}_{i,j',m}$$: " ] }, { @@ -511,42 +495,42 @@ "id": "f7f22edc", "metadata": {}, "source": [ - "**THEN:**\n", - "\n", "$$\n", "\\begin{align}\n", - "\\rho^{(m)}_{j,i} \n", - "\\leq&{}\n", - "\\rho^{(m)}_{j,i'}\n", + "d_{i,j}^{(m)} \\le&{} d_{i,j'}^{(m)}\n", "\\\\\n", - "\\max(\\rho^{(m)}_{j,i}, 0) \n", - "\\leq&{}\n", - "\\max(\\rho^{(m)}_{j,i'},0)\n", + "\\rho^{(m)}_{i,j} \n", + "\\geq&{}\n", + "\\rho^{(m)}_{i,j'}\n", "\\\\\n", - "\\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", - "\\leq&{}\n", - "\\left(\\max(\\rho^{(m)}_{j,i'},0)\\right)^{2}\n", + "\\max(\\rho^{(m)}_{i,j}, 0) \n", + "\\geq&{}\n", + "\\max(\\rho^{(m)}_{i,j'},0)\n", "\\\\\n", - "1 - \\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", + "\\left(\\max(\\rho^{(m)}_{i,j}, 0)\\right)^{2}\n", "\\geq&{}\n", - "1 - \\left(\\max(\\rho^{(m)}_{j,i'},0)\\right)^{2}\n", + "\\left(\\max(\\rho^{(m)}_{i,j'},0)\\right)^{2}\n", + "\\\\\n", + "1 - \\left(\\max(\\rho^{(m)}_{i,j}, 0)\\right)^{2}\n", + "\\leq&{}\n", + "1 - \\left(\\max(\\rho^{(m)}_{i,j'},0)\\right)^{2}\n", "\\\\\n", - "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\frac{\\sigma_{i,m}}{\\sigma_{i,m+k}}\n", "\\sqrt{m\n", "\\left[\n", - "1 - \\left(\\max(\\rho^{(m)}_{j,i}, 0)\\right)^{2}\n", + "1 - \\left(\\max(\\rho^{(m)}_{i,j}, 0)\\right)^{2}\n", "\\right]\n", "}\n", - "\\geq&{}\n", - "\\frac{\\sigma_{j,m}}{\\sigma_{j,m+k}}\n", + "\\leq&{}\n", + "\\frac{\\sigma_{i,m}}{\\sigma_{i,m+k}}\n", "\\sqrt{m\n", "\\left[\n", - "1 - \\left(\\max(\\rho^{(m)}_{j,i'}, 0)\\right)^{2}\n", + "1 - \\left(\\max(\\rho^{(m)}_{i,j'}, 0)\\right)^{2}\n", "\\right]\n", "}\n", "\\\\\n", - "LB^{(m)}_{j,i} \\geq{}& \n", - "LB^{(m)}_{j,i'}\n", + "LB^{(m+k)}_{i,j,m} \\leq{}& \n", + "LB^{(m+k)}_{i,j',m}\n", "\\\\\n", "\\end{align}\n", "$$\n", @@ -558,478 +542,478 @@ "id": "ec7b8819", "metadata": {}, "source": [ - "This proves that the ranked distance profile and its ranked lower bound have the same order." - ] - }, - { - "cell_type": "markdown", - "id": "3db70f03", - "metadata": {}, - "source": [ - "**NOTE (2):** \n", - "
\n", - "In STUMPY, parameter `p` is used to denote the kind of p-norm distance. To this end, from this point onwards, we use `k` to denote the number of elements that should be stored for each distance profile." - ] - }, - { - "cell_type": "markdown", - "id": "4711a892", - "metadata": {}, - "source": [ - "First, let us implement the naive version of VALMOD, that is we do not take advantage of previously-calculated top-k profiles, and we just iteratively call `stump`." + "This proves that the ranked distance profile (for subsequence length `m`) and its ranked lower bound (for subsequence length `m+k`) have the same order. The good news is that stumpy currently provides support for returning top-k (k>1) matrix profile values and their corresponding indices! Therefore, for each subsequence `T[i:i+m]`, we have its `top-k` smallest distances from its distance profile, and we can calculate their corresponding LB values for subsequence length `m+k` as follows:
\n", + "\n", + "(1) Compute top-k $\\rho$ based on the top-k distances
\n", + "(2) Compute $r = max(\\rho, 0)$
\n", + "(3) Compute $LB = \\frac{\\sigma_{i,m}}{\\sigma_{i,m+k}}{\\sqrt{m(1-r^{2})}}$" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "4a17e969", + "execution_count": 34, + "id": "56587835-14d5-4bf4-9ec6-5438299845d7", "metadata": {}, "outputs": [], "source": [ - "def naive_VALMOD(T, m_min, m_max):\n", - " # out_P is the scaled version of matrix profile value. \n", - " n = len(T) - m_min + 1\n", - " out_P = np.full(n, np.inf, dtype=np.float64)\n", - " out_I = np.full(n, -1, dtype=np.int64)\n", - " out_M = np.full(n, -1, dtype=np.int64)\n", - " \n", - " for m in range(m_min, m_max + 1):\n", - " mp = stump(T, m)\n", - " P = mp[:,0].astype(np.float64)\n", - " I = mp[:,1].astype(np.int64)\n", - " \n", - " P[:] = P / np.sqrt(m) # scale by 1/sqrt(m) to allow us compare distances of a pair of subsequence with another pair when their lengths are different.\n", - " \n", - " l = len(P)\n", - " mask = P < out_P[:l]\n", - " out_P[:l][mask] = P[mask]\n", - " out_I[:l][mask] = I[mask]\n", - " out_M[:l][mask] = m\n", - " \n", - " out = np.empty((n, 3), dtype=object)\n", - " out[:, 0] = out_P\n", - " out[:, 1] = out_I\n", - " out[:, 2] = out_M\n", + "@njit(fastmath=True, parallel=True)\n", + "def _compute_LB(T, m, Σ_T, Σ_T_prev, M_prev, P_prev):\n", + " \"\"\"\n", + " Compute LB top-k profile for subsequences of length `m` in `T`\n", + " based on top-k distances discovered previously for subsequences\n", + " with length recorded in M_prev. \n", + "\n", + " The LB between two subsequnece Si'=T[i:i+m'] and Sj'=T[j:j+m'] can be computed based\n", + " on the the distance between Si=T[i:i+m] and Sj=T[j:j+m], where m < m'. The formula is:\n", + " LB = (std_of_Si / std_of_Si') * ((m * (1 - r ** 2))**0.5), where r = max(rho(Si,Sj), 0.0).\n", + "\n", + " For a given 2D array P_prev, P_prev[i] contains top-k smallest distances between T[i,i+M] \n", + " and its neighbours, where M==M_prev[i]. The standard deviation of `T[i:i+M]` is stored in\n", + " Σ_T_prev[i]. Σ_T[i] represents the standard deviation of subsequence T[i:i+m]`, where m > M.\n", + "\n", + " Parameters\n", + " ----------\n", + " T : np.ndarray\n", + " Time series\n", + "\n", + " m : int\n", + " Window size\n", + "\n", + " Σ_T : np.ndarray\n", + " A 1D array containing the sliding standard deviation of subsequences with length `m`\n", + "\n", + " Σ_T_prev : np.ndarray\n", + " A 1D array containing the standard deviation of subsequences. Σ_T_prev[i] represents \n", + " the standard deviation of T[i:i+w], where w==M_prev[i]\n", + "\n", + " M_prev : np.ndarray\n", + " A 1D array containing the length of subsequences used for obtaining top-k smallest distance\n", + " for a subsequence.\n", + "\n", + " P_prev : np.ndarray\n", + " A 2D array where P_prev[i] contains the top-k smallest distance between `T[i:i+w]`\n", + " and its neighbours. Note that `w==M_prev[i]`\n", + "\n", + " Returns\n", + " -------\n", + " LB : np.ndarray\n", + " A 2D array where LB[i] contains the lower bounds when subsequence length is `m`. It corresponds\n", + " to the distances P_prev[i] previously computed for the subsequence length `M_prev[i]`\n", + " \"\"\"\n", + " l = len(T) - m + 1\n", + " k = P_prev.shape[1]\n", + "\n", + " LB = np.empty((l, k), dtype=np.float64)\n", + " for i in prange(l):\n", + " ρ_prev = 1.0 - np.square(P_prev[i]) / (2 * M_prev[i])\n", + " ρ_prev = np.clip(ρ_prev, a_min=0.0, a_max=1.0)\n", + " LB[i] = (Σ_T_prev[i] / Σ_T[i]) * np.sqrt(M_prev[i] * (1 - np.square(ρ_prev)))\n", " \n", - " return out" + " return LB" ] }, { "cell_type": "code", - "execution_count": null, - "id": "62a300d8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "a010e37e", + "execution_count": 29, + "id": "635b584f-47ab-45e1-843a-796d0f3bf923", "metadata": {}, "outputs": [], "source": [ - "def _VALMOD_stump(T, m, k):\n", + "@njit(fastmath=True, parallel=True)\n", + "def _approx_stump(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I):\n", " \"\"\"\n", - " Computes the top-1 matrix profile and matrix profile indice, and also computes the lower bound component\n", - " and their coresponding indices.\n", - " \n", + " Compute approx matrix profile for time series T and window size m. For\n", + " the i-th susbequence, this function only computes its distance to those \n", + " neighbours whose start indices are in `LB_I[i]`. In addition to P and I,\n", + " this funciton also returns a boolean-valued 1D array is_exact, which \n", + " reflects whether `P[i]` is [guaranteed to be] exact or not.\n", + "\n", " Parameters\n", " ----------\n", - " T : numpy.ndarray\n", - " The time series or sequence for which to compute the matrix profile\n", - " \n", + " T : np.ndarray\n", + " Time series\n", + "\n", " m : int\n", " Window size\n", - " \n", - " k : int\n", - " Number of nearest neighbors to consider in constructing the profiles and lower bounds.\n", - " \n", - " Returns\n", - " -------\n", - " out 1: np.ndarray\n", - " A 1D array containing the exact matix profile values\n", - " \n", - " out 2: np.ndarray\n", - " A 1D array containing the exact matix profile indices\n", - " \n", - " out 3: np.ndarray\n", - " A 2D array, with k columns, containing the core component of lowerbound values,\n", + "\n", + " M_T : np.ndarray\n", + " Rolling mean\n", " \n", - " out 4 : np.ndarray\n", - " A 2D array, with k columns, containing the indices that correspond to the lowerbound values\n", - " \"\"\"\n", - " mp = stump(T, m, k=k)\n", - " P = mp[:, :k].astype(np.float64)\n", - " I = mp[:, k:2*k].astype(np.int64)\n", - " is_mp_valid = np.full(len(T) - m + 1, 0, dtype=bool)\n", - " \n", - " # In VALMOD paper, LB has the following component:\n", - " # np.sqrt(m * (1 - np.square(ρ_clip))). Here, we\n", - " # show it by `LB_σr`\n", - "\n", - " ρ = 1.0 - np.square(P) / (2 * m)\n", - " # clipping ρ\n", - " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " _, σ = core.compute_mean_std(T, m)\n", - " LB_σr = σ.reshape(-1,1) * np.sqrt(m * (1.0 - np.square(ρ))) \n", - " is_mp_valid[:] = True\n", - " \n", - " return P[:, 0], I[:, 0], LB_σr, I, is_mp_valid\n", + " Σ_T : np.ndarray\n", + " Rolling standard deviation\n", " \n", + " T_subseq_isconstant : np.ndarray\n", + " A boolean array that indicates whether a subsequence in `T` is constant\n", + " (True)\n", + "\n", + " LB : np.ndarray\n", + " The lower bound values. LB[i] represents top-k smallest lower bound values for the distances\n", + " between T and the neighbours whose start indices are stored in LB_I[i]\n", "\n", - "def _VALMOD_stump_partial(T, m, k, LB_σr, LB_I):\n", - " \"\"\"\n", - " Compute partial matrix profile for subsequence length `m`, \n", - " with help of lowerbound. \n", - " \n", - " Parameters\n", - " ----------\n", - " T : numpy.ndarray\n", - " The time series or sequence for which to compute the matrix profile\n", - " \n", - " m : int\n", - " Window size\n", - " \n", - " k : int\n", - " The number of nearest neighbor to consider for constructing lowerbound \n", - " profiles\n", - " \n", - " LB_ar : np.ndarray\n", - " The array that contains the main component of lowerbound values\n", - " \n", " LB_I : np.ndarray\n", - " The array that corresponds to the indices of lower bound values\n", - " \n", + " A 2D array. LB_I[i] contains the start index of top-k neighbours discovered previously \n", + " based on a smaller window size.\n", + "\n", " Returns\n", " -------\n", " P : np.ndarray\n", - " A 1D array containing the exact matix profile values\n", - " \n", + " A 1D approximate matrix profile\n", + "\n", " I : np.ndarray\n", - " A 1D array containing the exact matix profile indices\n", - " \n", - " LB_σr : np.ndarray\n", - " A 2D array, with k columns, containing the core component of lowerbound values,\n", - " \n", - " LB_I : np.ndarray\n", - " A 2D array, with k columns, containing the indices that correspond to the lowerbound values\n", + " A 1D matrix profile index. I[i] is the start index of the neighbour of i-th subsequence \n", + " and their distance is stored in P[i]\n", + "\n", + " is_exact : np.ndarray\n", + " A 1D array of boolean values. is_exact[i]==True means `P[i]` is exact,\n", + " and `I[i]` represnts the correct nearest neighbour.\n", " \"\"\"\n", - " n = len(T) - m + 1\n", - " P = np.full(n, np.inf,dtype=np.float64)\n", - " I = np.full(n, -1,dtype=np.int64)\n", - " is_mp_valid = np.full(n, 0, dtype=bool)\n", - " \n", - " # may add support for `T_B` (AB-join)\n", - " Q, μ_Q, σ_Q, Q_subseq_isconstant = core.preprocess(T, m)\n", - " T, M_T, Σ_T, T_subseq_isconstant = core.preprocess(T, m)\n", - " \n", - " σ_Q_inv = 1.0 / σ_Q # add code to handle `σ_Q==0` cases\n", - " LB = σ_Q_inv.reshape(-1, 1) * LB_σr[:len(σ_Q_inv)]\n", - " \n", - " global_min_maxLB = np.inf\n", + " l = len(T) - m + 1\n", + " P = np.full(l, np.inf,dtype=np.float64)\n", + " I = np.full(l, -1,dtype=np.int64)\n", + " is_exact = np.full(l, 0,dtype=bool)\n", + "\n", " excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))\n", - " for i in range(n):\n", + " for i in prange(l):\n", " excl_zone_start = max(i - excl_zone, 0)\n", - " excl_zone_stop = min(i + excl_zone + 1, n)\n", + " excl_zone_stop = min(i + excl_zone + 1, l)\n", " excl_zone_range = range(excl_zone_start, excl_zone_stop)\n", - " \n", - " min_dist = np.inf\n", - " idx = -1\n", + "\n", + " nn_dist = np.inf\n", + " nn_i = -1\n", + " \n", " for enum, j in enumerate(LB_I[i]):\n", - " if j >= n or j in excl_zone_range:\n", + " # ToDo: Add if-block to early abondon\n", + " if nn_dist <= LB[i, enum]:\n", + " break # nn was found!\n", + "\n", + " # skip if neighbour j is trivial or infeasible \n", + " if (j >= excl_zone_start and j < excl_zone_stop) or j >= l or j == -1:\n", " continue\n", - " \n", - " QT = np.dot(T[i:i+m], T[j:j+m])\n", + "\n", " d_square = core._calculate_squared_distance(\n", " m,\n", - " QT,\n", - " μ_Q[i],\n", - " σ_Q[i],\n", + " np.dot(T[i:i+m], T[j:j+m]),\n", + " M_T[i],\n", + " Σ_T[i],\n", " M_T[j],\n", " Σ_T[j],\n", - " Q_subseq_isconstant[i],\n", + " T_subseq_isconstant[i],\n", " T_subseq_isconstant[j],\n", " )\n", " d = np.sqrt(d_square)\n", - " if d < min_dist:\n", - " min_dist = d\n", - " idx = j\n", - " \n", - " maxLB = LB[i, -1]\n", - " if min_dist < maxLB:\n", - " P[i] = min_dist\n", - " I[i] = idx\n", - " is_mp_valid[i] = True\n", - " else:\n", - " global_min_maxLB = min(global_min_maxLB, maxLB)\n", - " is_mp_valid[i] = False\n", - " \n", - " global_min_dist = np.min(P)\n", - " if global_min_dist <= global_min_maxLB:\n", - " return P, I, LB_σr, LB_I, is_mp_valid\n", - " \n", - " if np.sum(~is_mp_valid) < (n * np.log2(k) / np.log2(n)):\n", - " for idx in np.flatnonzero(~is_mp_valid):\n", - " if global_min_dist <= maxLB_profile[idx]:\n", - " continue \n", - " \n", - " QT = core.sliding_dot_product(T[idx:idx+m], T)\n", - " D = core._mass(\n", - " T[idx:idx+m], \n", - " T, \n", - " QT, \n", - " μ_Q[idx], \n", - " σ_Q[idx], \n", - " M_T, \n", - " Σ_T, \n", - " Q_subseq_isconstant[idx], \n", - " T_subseq_isconstant\n", - " )\n", - " core.apply_exclusion_zone(D, idx, m, np.inf)\n", - "\n", - " arg = np.argmin(D)\n", - " if D[arg] < np.inf:\n", - " P[idx] = D[arg]\n", - " I[idx] = arg\n", - " global_min_dist = min(global_min_dist, P[idx])\n", - " \n", - " args_topk = np.argsort(D, kind='mergesort')[:k]\n", - " LB_I[idx] = args_topk\n", - "\n", - " ρ = 1.0 - np.square(D[args_topk]) / (2 * m)\n", - " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " LB_σr[idx] = σ_Q[idx] * np.sqrt(m * (1 - np.square(ρ)))\n", - " is_mp_valid[idx] = True\n", - "\n", - " else:\n", - " mp = stump(T, m, k=k)\n", - " P = mp[:, :k].astype(np.float64)\n", - " I = mp[:, k:2*k].astype(np.int64)\n", + " if d < nn_dist:\n", + " nn_dist = d\n", + " nn_i = j\n", "\n", - " ρ = 1.0 - np.square(P) / (2 * m)\n", - " ρ[:] = np.clip(ρ, a_min=0.0, a_max=1.0)\n", - " _, σ = core.compute_mean_std(T, m)\n", - " LB_σr = σ.reshape(-1,1) * np.sqrt(m * (1 - np.square(ρ)))\n", - " LB_I = I\n", - " is_mp_valid[:] = True\n", + " P[i] = nn_dist\n", + " I[i] = nn_i\n", + " if nn_dist <= LB[i, -1]: \n", + " is_exact[i] = True\n", "\n", - " return P[:,0], I[:,0], LB_σr, LB_I, is_mp_valid" + " return P, I, is_exact" ] }, { "cell_type": "code", - "execution_count": 49, - "id": "be7b439d", + "execution_count": 40, + "id": "aba52bf3-8f15-4e7a-a0c3-f68efb3460e6", "metadata": {}, "outputs": [], "source": [ - "def _update_PIM(P, P_new, I, I_new, M, m_new):\n", + "def _stump_valmod(T, m, P_prev, I_prev, M_prev, Σ_T_prev):\n", " \"\"\"\n", - " Update P (profile values), I (profile indices), M (length of subsequences), in place, \n", - " by using the new values `P_new`, `I_new`, `m_new`\n", - " \n", + " Given T and m, returns approximate matrix profile such that its global minimum is exact.\n", + "\n", " Parameters\n", " ----------\n", - " P : np.ndarray\n", - " The matrix profile value containing the scaled distance between a subsequence to the nearest neighbor\n", - " \n", - " P_new : np.ndarray\n", - " The matrix profile value containing the scaled distance between a subsequence to the nearest neighbor, \n", - " computed for a subsequence length that is longer than the one used for `P`\n", - " \n", - " I : np.ndarray\n", - " The matrix profile indices containing the nearest neighbor index of each subsequence\n", - " \n", - " I_new : np.ndarray\n", - " The matrix profile indices containing the nearest neighbor index of each subsequence, computed \n", - " for a subsequence length that is longer than the one used for `I`. These indices correspond to \n", - " the matrix profile `P_new`\n", + " T : np.ndarray\n", + " Time series\n", " \n", - " M : np.ndarray\n", - " For a subequence at index `i`, `M[i]` is the lenght of subsequence for which the lowest distance \n", - " between `i` and its nearest neighbor is discovered.\n", + " m : int\n", + " Window size\n", + "\n", + " P_prev : np.ndarray\n", + " A 2D array where P_prev[i] contains the top-k smallest distance for \n", + " subsequence length M_prev[i]\n", " \n", - " m_new : int\n", - " The new subsequence length that is used for computing P_new, I_new\n", + " I_prev : np.ndarray\n", + " A 2D array where I_prev[i] contains the start index of\n", + " top-k nearest neighbours for subsequence length M_prev[i]\n", + "\n", + " M_prev : np.ndarray\n", + " A 1D array containing the length of subsequences used for obtaining top-k smallest distance\n", + " for a subsequence.\n", + "\n", + " Σ_T_prev : np.ndarray\n", + " A 1D array containing the standard deviation of subsequences. Σ_T_prev[i] represents \n", + " the standard deviation of T[i:i+w], where w==M_prev[i]\n", " \n", - " Returns \n", - " -------\n", - " None\n", " \"\"\"\n", - " n = len(P_new)\n", - " mask = P_new < P[:n]\n", - " P[:n][mask] = P_new[mask]\n", - " I[:n][mask] = I_new[mask]\n", - " M[:n][mask] = m_new" + " # preprocess\n", + " T, M_T, Σ_T, T_subseq_isconstant = core.preprocess(T, m)\n", + "\n", + " # compute LB\n", + " LB = _compute_LB(T, m, Σ_T, Σ_T_prev, M_prev, P_prev)\n", + " LB_I = I_prev\n", + "\n", + " # compute approx matrix profile\n", + " P, I, is_exact = _approx_stump(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I)\n", + "\n", + " if np.min(P) <= np.min(LB[is_exact == False, -1]):\n", + " # global min is exact\n", + " skip_full_compute = True\n", + " else:\n", + " skip_full_compute = False\n", + " k = P_prev.shape[1]\n", + " mp = stump(T, m, k=k)\n", + " l = len(T) - m + 1\n", + " P_prev[:l] = mp[:, :k].astype(np.float64)\n", + " I_prev[:l] = mp[:, k:2*k].astype(np.int64)\n", + " M_prev[:l] = m\n", + " Σ_T_prev[:l] = Σ_T\n", + "\n", + " # overwrite P and I\n", + " P[:] = mp[:, 0].astype(np.float64)\n", + " I[:] = mp[:, k].astype(np.int64)\n", + " \n", + " return P, I, skip_full_compute\n", + "\n", + "\n", + "def find_motif(T, m_values, k=None):\n", + " if k is None:\n", + " k = max(5, int(0.005/100 * len(T)))\n", + " \n", + " m_values_sorted = np.sort(m_values)\n", + " \n", + " # to save outputs\n", + " num_m = len(m_values_sorted)\n", + " motif_distance = np.full(num_m, np.inf, dtype=np.float64)\n", + " motif_index = np.full(num_m, -1, dtype=np.int64)\n", + " motif_index_nn = np.full(num_m, -1, dtype=np.int64)\n", + " motif_skip_full_compute = np.full(num_m, 0, dtype=bool)\n", + "\n", + " # mp for smallest m\n", + " m_min = m_values_sorted[0]\n", + " mp = stump(T, m_min, k=k)\n", + " l = len(T) - m_min + 1\n", + " P_prev = mp[:, :k].astype(np.float64)\n", + " I_prev = mp[:, k:2*k].astype(np.int64)\n", + " M_prev = np.full(l, m_min, dtype=np.int64)\n", + " _, Σ_T_prev = core.compute_mean_std(T, m_min)\n", + "\n", + " idx = np.argmin(mp[:, 0])\n", + " motif_index[0] = idx\n", + " motif_distance[0] = mp[idx, 0]\n", + " motif_index_nn[0] = mp[idx, k]\n", + " motif_skip_full_compute[0] = False\n", + "\n", + " for i in range(1, len(m_values_sorted)):\n", + " m = m_values_sorted[i]\n", + " P, I, skip_full_compute = _stump_valmod(T, m, P_prev, I_prev, M_prev, Σ_T_prev)\n", + " idx = np.argmin(P)\n", + " motif_index[i] = idx\n", + " motif_distance[i] = P[idx]\n", + " motif_index_nn[i] = I[idx]\n", + " motif_skip_full_compute[i] = skip_full_compute \n", + "\n", + " # construct output\n", + " out = np.empty((num_m, 5), dtype=object)\n", + " out[:, 0] = motif_distance\n", + " out[:, 1] = motif_index\n", + " out[:, 2] = motif_index_nn\n", + " out[:, 3] = m_values_sorted\n", + " out[:, 4] = motif_skip_full_compute\n", + "\n", + " return out\n", + " " ] }, { - "cell_type": "code", - "execution_count": 50, - "id": "94eceff1", + "cell_type": "markdown", + "id": "1f24fc53-ad5a-4d97-9d1e-48bc5b0d63ca", "metadata": {}, - "outputs": [], "source": [ - "def print_verbose(msg, verbose=False):\n", - " if verbose:\n", - " print(msg)\n", - "\n", - "\n", - "def VALMOD(T, m_min, m_max, k):\n", - " \"\"\"\n", - " This function finds the matrix profile of T_A while considering different length of subsequences in \n", - " range `[m_min, m_max]` inclusive. To be able to compare distances across different subsequence length, \n", - " each distance is scaled by a factor of `1 / sqrt(m)`. \n", - " \n", - " Parameters\n", - " T : np.ndarray\n", - " The timeseries of interest\n", - " \n", - " m_min : int\n", - " The smallest window size\n", - " \n", - " m_max : int\n", - " The largest window size\n", - " \n", - " k : int\n", - " The number of nearest neighbors to capture for speeding up the computaion.\n", - " \n", - " Return\n", - " ------\n", - " PIM : np.ndarray\n", - " A 2D array, with exactly three columns, representing the ensembled matrix profile. The first column \n", - " contains the ensembled matrix profile value. The second column contains their corresponding nearest\n", - " neighbor index, and the third (last) column contains the corresponding subsequence length. Hence, \n", - " for instance, when `dist = PIM[i, 0]`, `j = PIM[i, 1]`, and `m = PIM[i, 2]`, then `dist` is a (scaled) \n", - " distance between subsequence `S_i` and subsequence `S_j`, each with length `m`. `dist` is the lowest \n", - " scaled distance between `S_i` and all of its neighbors considering all values of `m`.\n", - " \"\"\"\n", - " n = len(T) - m_min + 1\n", - " out_P = np.full(n, np.inf, dtype=np.float64)\n", - " out_I = np.full(n, -1, dtype=np.int64)\n", - " out_M = np.full(n, -1, dtype=np.int64)\n", - " \n", - " # out_P, out_I, out_M = _update_PIM(out_P, P_TopK[:,0] / np.sqrt(m), out_I, I_TopK[:, 0], out_M, m)\n", - " LB_σr = None\n", - " is_exact = np.full(n, 1, dtype=bool)\n", - " for m in range(m_min, m_max + 1):\n", - " if LB_σr is None: # only runs for the first iteration, i,e, lowest `m` \n", - " idx = 1232\n", - " P, I, LB_σr, LB_I, is_mp_valid = _VALMOD_stump(T, m, k)\n", - " else:\n", - " P, I, LB_σr, LB_I, is_mp_valid = _VALMOD_stump_partial(T, m, k, LB_σr, LB_I)\n", - " \n", - " l = len(is_mp_valid) # which is: len(T) - m + 1 \n", - " is_exact[:l] = is_exact[:l] & is_mp_valid\n", - " \n", - " _update_PIM(out_P, P/np.sqrt(m), out_I, I, out_M, m)\n", - " \n", - " out = np.empty((n, 3), dtype=object)\n", - " out[:, 0] = out_P\n", - " out[:, 1] = out_I\n", - " out[:, 2] = out_M\n", - " \n", - " return out, is_exact" + "### Example" ] }, { "cell_type": "code", - "execution_count": 51, - "id": "d0800ab7", + "execution_count": null, + "id": "87b6b3c6-0d9f-47cc-b8cd-732fd3a9b995", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The computing time: 5.127043724060059\n", - "Computing time: 34.47108221054077\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "seed = 0\n", "np.random.seed(seed)\n", + "\n", "T = np.random.rand(10000)\n", "m_min = 50\n", - "m_max = 60\n", - "\n", - "#####################\n", + "m_max = 100\n", + "m_values = np.arange(m_min, m_max + 1)\n", "\n", - "# naive valmod: a simple for-loop, computing full mp for each `m`\n", - "t_start = time.time()\n", - "mp_ref = naive_VALMOD(T, m_min, m_max)\n", - "t_stop = time.time()\n", - "print(\"The computing time: \", t_stop - t_start)\n", + "start = time.time()\n", + "out_ref = naive_find_motif(T, m_values)\n", + "stop = time.time()\n", + "print(f'naive took: {stop - start} seconds')\n", + "print('-' * 50)\n", "\n", - "#####################\n", "\n", - "# valmod\n", - "t_start = time.time()\n", - "mp_comp, is_exact = VALMOD(T, m_min, m_max, k=20) # k=20 is provided by user\n", - "t_stop = time.time()\n", - "print(\"Computing time: \", t_stop - t_start)" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "b3f9d40b", - "metadata": {}, - "outputs": [], - "source": [ - "np.testing.assert_almost_equal(mp_ref[is_exact, 0], mp_comp[is_exact,0])" + "start = time.time()\n", + "out_comp = find_motif(T, m_values, k=5)\n", + "stop = time.time()\n", + "print(f'valmod took: {stop - start} seconds')" ] }, { "cell_type": "code", - "execution_count": 53, - "id": "8aabf529", + "execution_count": 45, + "id": "d8ee07eb-765f-4a48-93c5-3af38ed0fc08", "metadata": {}, "outputs": [ { - "ename": "AssertionError", - "evalue": "\nArrays are not almost equal to 7 decimals\n\nMismatched elements: 5771 / 9915 (58.2%)\nMax absolute difference: 0.0592546542833442\nMax relative difference: 0.06382009396320394\n x: array([0.9452865772913406, 0.9344991685815902, 0.9092612749994912, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9439425333188787],\n dtype=object)\n y: array([0.9678644071613989, 0.9574466161924685, 0.9319605844727593, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9478057237030245],\n dtype=object)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[53], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtesting\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massert_almost_equal\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmp_ref\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m~\u001b[39;49m\u001b[43mis_exact\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmp_comp\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m~\u001b[39;49m\u001b[43mis_exact\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[0;31m[... skipping hidden 2 frame]\u001b[0m\n", - "File \u001b[0;32m~/miniconda3/envs/stumpypy39/lib/python3.10/site-packages/numpy/testing/_private/utils.py:844\u001b[0m, in \u001b[0;36massert_array_compare\u001b[0;34m(comparison, x, y, err_msg, verbose, header, precision, equal_nan, equal_inf)\u001b[0m\n\u001b[1;32m 840\u001b[0m err_msg \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(remarks)\n\u001b[1;32m 841\u001b[0m msg \u001b[38;5;241m=\u001b[39m build_err_msg([ox, oy], err_msg,\n\u001b[1;32m 842\u001b[0m verbose\u001b[38;5;241m=\u001b[39mverbose, header\u001b[38;5;241m=\u001b[39mheader,\n\u001b[1;32m 843\u001b[0m names\u001b[38;5;241m=\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m'\u001b[39m), precision\u001b[38;5;241m=\u001b[39mprecision)\n\u001b[0;32m--> 844\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(msg)\n\u001b[1;32m 845\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m:\n\u001b[1;32m 846\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtraceback\u001b[39;00m\n", - "\u001b[0;31mAssertionError\u001b[0m: \nArrays are not almost equal to 7 decimals\n\nMismatched elements: 5771 / 9915 (58.2%)\nMax absolute difference: 0.0592546542833442\nMax relative difference: 0.06382009396320394\n x: array([0.9452865772913406, 0.9344991685815902, 0.9092612749994912, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9439425333188787],\n dtype=object)\n y: array([0.9678644071613989, 0.9574466161924685, 0.9319605844727593, ...,\n 0.9612889703718848, 0.9425392112609088, 0.9478057237030245],\n dtype=object)" - ] + "data": { + "text/plain": [ + "array([[10.04110674205363, 5487, 7014, 100],\n", + " [10.235396091248132, 7337, 8268, 101],\n", + " [10.235713184882687, 7336, 8267, 102],\n", + " [10.315601362114847, 7335, 8266, 103],\n", + " [10.345260896090974, 7334, 8265, 104],\n", + " [10.341158051197167, 7333, 8264, 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7298, 8229, 148],\n", + " [12.8083480918068, 7297, 8228, 149],\n", + " [12.885026286543928, 7298, 8229, 150]], dtype=object)" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "np.testing.assert_almost_equal(mp_ref[~is_exact, 0], mp_comp[~is_exact,0])" + "out_ref" ] }, { "cell_type": "code", - "execution_count": 54, - "id": "9557a1ad", + "execution_count": 46, + "id": "f218cd24-7bf0-453e-9038-2a2a858b4e38", "metadata": {}, "outputs": [ { "data": { - "image/png": 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[11.065676145204215, 7328, 8259, 118, False],\n", + " [11.058210043828147, 7327, 8258, 119, False],\n", + " [11.138328008988738, 7326, 8257, 120, False],\n", + " [11.207987492874635, 7327, 8258, 121, False],\n", + " [11.286060644275912, 7326, 8257, 122, False],\n", + " [11.361874941080497, 7327, 8258, 123, False],\n", + " [11.359403520203283, 7327, 8258, 124, False],\n", + " [11.436930785107815, 7326, 8257, 125, False],\n", + " [11.536472885222906, 7327, 8258, 126, False],\n", + " [11.614494160884242, 7326, 8257, 127, False],\n", + " [11.69615368445294, 7327, 8258, 128, False],\n", + " [11.742709765477846, 7327, 8258, 129, False],\n", + " [11.81540618863074, 7321, 8252, 130, False],\n", + " [11.945921991266609, 7321, 8252, 131, False],\n", + " [11.9704839989172, 7306, 8237, 132, False],\n", + " [12.013113551512077, 7305, 8236, 133, False],\n", + " [12.075077588959394, 7304, 8235, 134, False],\n", + " [12.12042994619002, 7303, 8234, 135, False],\n", + " [12.211134183100658, 7302, 8233, 136, False],\n", + " [12.283942458747582, 7301, 8232, 137, False],\n", + " [12.274083235112094, 7298, 8229, 138, False],\n", + " [12.33091545398737, 7297, 8228, 139, False],\n", + " [12.279765348110109, 7298, 8229, 140, False],\n", + " [12.335892236114566, 7297, 8228, 141, False],\n", + " [12.500598332271148, 7297, 8228, 142, False],\n", + " [12.593294312523177, 7297, 8228, 143, False],\n", + " [12.64958808664091, 7298, 8229, 144, False],\n", + " [12.705249712588992, 7297, 8228, 145, False],\n", + " [12.738211768227922, 7298, 8229, 146, False],\n", + " [12.793338287857067, 7297, 8228, 147, False],\n", + " [12.754039217230453, 7298, 8229, 148, False],\n", + " [12.8083480918068, 7297, 8228, 149, False],\n", + " [12.885026286543928, 7298, 8229, 150, False]], dtype=object)" ] }, + "execution_count": 46, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "plt.figure(figsize=(30,3))\n", - "plt.plot(mp_ref[:,0], c='k', label='naive')\n", - "plt.plot(mp_comp[:,0], c='r', label='valmod')\n", - "plt.show()" + "out_comp" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5305af0b-af89-452d-8403-2d33b87c2735", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -1048,7 +1032,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.14.2" + "version": "3.12.12" } }, "nbformat": 4, From 95c4cb8dd7960faa32b4b5486fe43d889fffca64 Mon Sep 17 00:00:00 2001 From: NimaSarajpoor Date: Sun, 18 Jan 2026 23:48:24 -0500 Subject: [PATCH 67/67] rename function --- docs/Tutorial_VALMOD.ipynb | 188 ++++++++++++------------------------- 1 file changed, 61 insertions(+), 127 deletions(-) diff --git a/docs/Tutorial_VALMOD.ipynb b/docs/Tutorial_VALMOD.ipynb index a6b88c03c..23686cced 100644 --- a/docs/Tutorial_VALMOD.ipynb +++ b/docs/Tutorial_VALMOD.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "0adbe18a", "metadata": {}, "outputs": [], @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "1b34e09e-118e-4749-8bce-56aac05e6314", "metadata": {}, "outputs": [], @@ -145,13 +145,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "640f06fd-be97-40e1-a0e3-21d9681acbe1", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -200,13 +200,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "10ef76a0-aba9-4742-9d51-1f4630e43e51", "metadata": {}, "outputs": [ { "data": { - "image/png": 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Oh8MBh8OB1NRUVFdXtyixAgJ/F0BTier3338Pr9eLm2++Oeh7Ll26FKWlpZg6dSo8Hg//5/P5cOaZZ2LFihWqNjm47LLL/MruOnfujJNPPhmLFy9u8dwLLrjA7+cff/wRKSkpuPDCC/0ev+qqqwBAtessFDt27MDWrVt5Npjys06cOBFFRUXYtm1byGP8+OOPOP3005GRkQG73c4DsUtKSvj1xxg0aBA6derEf05MTETPnj39nHaLFy/GuHHj/O4zu92Oiy++2PDnbc6JJ56IdevW4aabbsL//vc/VFRU6DpOdXU1fv/9d1x44YVITU3lj9vtdlxxxRUoLCzk3+O4ceNQW1uLpUuXAmh0do0fPx6nn346vv/+e/4YAJx++ukA9F2Pza+ncDTPhzv55JPRuXNnfq0uW7YMtbW1/PpjdOzYEWPHjjV0PU6aNAl2u53/3PyeZW1rsPtJDQcPHgxY4qcG+f+X+DXfLbT5d3bRRRfB4XAEvL/DoeUaYoRr69QgyzKuvfZa/PLLL3jvvffQsWPHFs9h35vWtpsgCIKIDhRuTxAEQajmvffeQ58+feBwONCuXTvk5+eHfD7b9SrQ8woKCuDz+VBWVmZKyHROTo7fzy6XCwBQW1vLz83hcCA7O9vvecFEvOaUlJTguOOOa/F4Xl5e2Neeeuqp+Oyzz/DSSy/hyiuvhNvtRt++fXH//ferEt4uu+wy/PDDD3jwwQcxbNgwpKenQ5IkTJw4kX8+JeG+C5bBEyoA/dChQwDQQnRSUlpa6heSHYhA309eXh7WrVvn91hycjLS09P9HispKUFeXl6LyXZubi4cDoeQXdbY57znnntwzz33BHxOoHJSxh9//IEzzjgDY8aMwX/+8x906NABCQkJ+Oyzz/Dkk0+2+Ps0/9sAjX8f5fPY526OmmtNK9OmTUNKSgrmzJmDmTNnwm6349RTT8XTTz/NN7ZQQ1lZGWRZDnrvA03tw8knn4zk5GQsWrQIHTt2xJ49ezB+/HgUFhbi5ZdfRlVVFRYtWoSuXbvye07P9RiuvWpOsO+cnXe49o2JdnpQ036FOsc9e/aEfY/a2lokJib6PdamTRskJydj9+7dIV+7Z88eJCcnt2g/m5+Pw+FATk6OrntTyzXECPe9hUOWZVx33XWYM2cO3n33XZx77rkBn8e+N7XHJQiCIKILCV8EQRCEavr06aNp8ssmIUVFRS1+d/DgQdhsNmRlZQk7Py3k5OTA4/GgtLTUb/JWXFys+vWBnqv29eeeey7OPfdcuN1uLF++HNOnT8dll12GLl26YMSIEUFfV15ejq+++goPP/ww/vnPf/LH3W43SktLVb13c1hGW2FhYUB3A9A4IQaAl19+OejOa2pEw2DfWfMJa3NxC2j8zn///XfIsuz3+8OHD8Pj8fBzNAI7xrRp03huWHN69eoV9PVz586F0+nEV1995ScqfPbZZ7rPyei1pgWHw4G77roLd911F44dO4ZFixbhvvvuw4QJE7B//37VInVWVhZsNlvQex9o+q4TEhJwyimnYNGiRejQoQPy8vLQv39/dO3aFUDjxgg//PADJk+ezI+h53oMdE2FIth33r17dwDh2zfl9ZiYmNhicw0gtIgaCvbeRq6LNm3atGgz7HY7TjvtNCxcuBCFhYUBxfDCwkKsWrUKZ511lp8rjb13+/bt+c8ejwclJSUBBd5waLmGRMBEr3feeQdvv/12yGww9r2JfH+CIAjCPKjUkSAIgjCNXr16oX379vjggw/8dr+qrq7GvHnz+E6PQOiV+eYOGBGMHj0aAFoEJM+dO1fV60877TRs2rSphVPpgw8+0HQeLpcLo0ePxtNPPw0AfIfDYN+HJEmQZZn/nvHWW2+1CJpWyxlnnAG73Y7XX3896HNGjhyJzMxMbN68GUOHDg34LyEhIex7ffjhh37Xwt69e7F06dKAO941Z9y4caiqqmohIrGd7NjOj0bo1asXevTogXXr1gX9nGlpaUFfL0kSHA6HnyBQW1uL//73v7rP6bTTTsMPP/zAXU5AYwh5oHBvtai5pzIzM3HhhRfi5ptvRmlpqSoXESMlJQUnnXQS5s+f7/c+Pp8Pc+bMQYcOHdCzZ0/++Omnn45Vq1Zh3rx5vJwxJSUFw4cPx8svv4yDBw/yxwFx12Mo3n//fb+fly5dir179/JrdcSIEUhKSsKcOXP8nldYWIgff/zR73rs0qUL/vzzT777KNDoVmLlnVrp1asX8vPzg95Paujduzd27tzZ4vFp06ZBlmXcdNNNLdoUr9eLG2+8EbIsY9q0aS1e2/w7+/jjj+HxePzub7XtudZryAiyLOP666/HO++8gzfeeANXX311yOezzTiUGwMQBEEQ1oUcXwRBEIRp2Gw2PPPMM5gyZQomT56Mv/3tb3C73Xj22Wdx7NgxPPXUU/y5/fv3BwC8+OKLmDp1KpxOJ3r16oW0tDT0798fc+fOxUcffYSuXbsiMTGRP18vZ555JkaOHIm7774bFRUVOOGEE7Bs2TIuoigzyQJxxx13YNasWZg0aRKeeOIJtGvXDu+//z62bt0a9r0feughFBYWYty4cejQoQOOHTuGF198EU6nkwty3bp1Q1JSEt5//3306dMHqampKCgoQEFBAU499VQ8++yzaNOmDbp06YKffvoJb7/9NjIzM3V9F126dMF9992Hxx9/HLW1tbj00kuRkZGBzZs34+jRo3j00UeRmpqKl19+GVOnTkVpaSkuvPBC5Obm4siRI1i3bh2OHDkSUjhjHD58GOeddx6uv/56lJeX4+GHH0ZiYmLASXRzrrzySrz66quYOnUq9uzZg/79++PXX3/Fv/71L0ycONFPGDHCG2+8gbPOOgsTJkzAVVddhfbt26O0tBRbtmzB6tWr8cknnwR97aRJk/D888/jsssuw1//+leUlJTgueeeayFUauGBBx7AF198gbFjx+Khhx5CcnIyXn31VVWZasEIdk+dffbZ6NevH4YOHYq2bdti7969mDFjBjp37owePXpoeo/p06dj/PjxOO2003DPPfcgISEBr732GjZu3IgPP/zQz4E1btw4eL1e/PDDD3j33Xf546effjoefvhhSJKEsWPH8sdFXY+hWLlyJa677jr83//9H/bv34/7778f7du3x0033QSgURh88MEHcd999+HKK6/EpZdeipKSEjz66KNITEzEww8/zI91xRVX4I033sDll1+O66+/HiUlJXjmmWdalPOqxWaz4fHHH8d1113H76djx47hkUceUV0CO2bMGDz22GOoqanxc/KNHDkSM2bMwB133IFTTjkFt9xyCzp16oR9+/bh1Vdfxe+//44ZM2YEzBKbP38+HA4Hxo8fj02bNuHBBx/EwIED/bIUtbTnWq4hI9x22214++23cc0116B///5Yvnw5/53L5cLgwYP9nr98+XJeBkwQBEHEANFI1CcIgiBiC7Zj1ooVK0I+L9AOebIsy5999pl80kknyYmJiXJKSoo8btw4+bfffmvx+mnTpskFBQWyzWbzO86ePXvkM844Q05LS5MB8B3LQu3qeOTIkYCfQbkDXmlpqXz11VfLmZmZcnJysjx+/Hh5+fLlMgC/3RGDsXnzZnn8+PFyYmKinJ2dLV977bXy559/HnZXx6+++ko+66yz5Pbt28sJCQlybm6uPHHiRPmXX37xO/6HH34o9+7dW3Y6nX67ERYWFsoXXHCBnJWVJaelpclnnnmmvHHjRrlz587y1KlTW3zm5n+3YH+n9957Tx42bJicmJgop6amyoMHD26xq+RPP/0kT5o0Sc7OzpadTqfcvn17edKkSfInn3wS8rti7/nf//5Xvu222+S2bdvKLpdLHjVqlLxy5Uq/506dOlVOSUkJeJySkhL5hhtukPPz82WHwyF37txZnjZtGt8RkGFkV0dZluV169bJF110kZybmys7nU45Ly9PHjt2rDxz5syQn1OWZXnWrFlyr169ZJfLJXft2lWePn26/Pbbb7e4/jp37ixPmjSpxesD7QD422+/ycOHD5ddLpecl5cn//3vf5fffPNN3bs6Brun/v3vf8snn3yy3KZNGzkhIUHu1KmTfO2118p79uwJ+R6B7kVZluVffvlFHjt2rJySkiInJSXJw4cPl7/88ssWr/f5fHKbNm1kAPKBAwf8Pjf+/26ggVBzPQZrE4LB7pvvvvtOvuKKK+TMzEy+e+P27dtbPP+tt96SBwwYICckJMgZGRnyueeeK2/atKnF89599125T58+cmJionz88cfLH330UdBdHZ999tkWr29+7bL37tGjh5yQkCD37NlTnjVrVotjBmPHjh2yJEktdkllLFu2TL7wwgvldu3ayQ6HQ87NzZXPP/98eenSpS2ey77jVatWyWeffbacmpoqp6WlyZdeeinf+ZGhpT2XZXXXkNa2rjmdO3eWAQT8F+i7HDVqVIsdRQmCIAjrIsmywh9NEARBEK2cDz74AFOmTMFvv/2menc0IjxLlizBaaedhk8++SRkIDlBEJHj7LPPhsfjwbfffmvoOI888ggeffRRHDlyJO5zr3bu3IkePXrgf//7H8aPHx/t0yEIgiBUQKWOBEEQRKvlww8/xIEDB9C/f3/YbDYsX74czz77LE499VQSvQiCiHumT5+OwYMHY8WKFRg2bFi0TycmeOKJJzBu3DgSvQiCIGIIEr4IgiCIVktaWhrmzp2LJ554AtXV1cjPz8dVV12FJ554ItqnRhAEYTr9+vXDO++8Y8oOofGIx+NBt27dVGUSEgRBENaBSh0JgiAIgiAIgiAIgiCIuCT0llUEQRAEQRAEQRAEQRAEEaOQ8EUQBEEQBEEQBEEQBEHEJSR8EQRBEARBEARBEARBEHFJTITb+3w+HDx4EGlpaZAkKdqnQxAEQRAEQRAEQRAEQUQJWZZRWVmJgoIC2GyhPV0xIXwdPHgQHTt2jPZpEARBEARBEARBEARBEBZh//796NChQ8jnxITwlZaWBqDxA6Wnp0f5bAiCIAiCIAiCIAiCIIhoUVFRgY4dO3K9KBQxIXyx8sb09HQSvgiCIAiCIAiCIAiCIAhVcVgUbk8QBEEQBEEQBEEQBEHEJSR8EQRBEARBEARBEARBEHEJCV8EQRAEQRAEQRAEQRBEXELCF0EQBEEQBEEQBEEQBBGXkPBFEARBEARBEARBEARBxCUkfBEEQRAEQRAEQRAEQRBxCQlfBEEQBEEQBEEQBEEQRFxCwhdBEARBEARBEARBEAQRl5DwRRAEQRAEQRAEQRAEQcQlJHwRBEEQBEEQBEEQBEEQcQkJXwRBEARBEARBEARBEERcQsIXQRAEQRAEQRAEQRAEEZeQ8EUQBEEQBEEQBEEQBEHEJSR8EYQOysrKsG/fvmifBkEQBEEQBEEQBEEQISDhiyB0MGbMGPTs2RMlJSXRPhWCIAiCIAiCIAiCIIJAwhdBaKSiogLr16+H2+3G3r17o306BEEQBEEQBEEQBEEEgYQvgtDI9u3b+f9XVlZG8UwIgiAIgiAIgiAIgggFCV8EoZFt27bx/yfhiyAIgiAIgiAIgiCsCwlfBKGRP//8k/8/CV8EQRAEQRAEQRAEYV1I+CIIjZDjiyAIgiAIgiAIgiBiAxK+CEIj5PgiCIIgCIIgCIIgiNiAhC+C0IAsyyR8EQRBEEQcI8syJk+ejJEjR8Ln80X7dAiCIAiCMIgj2idAELFEUVERqqqq+M8kfBEEQRBEfFFSUoKvv/4aAFBcXIyCgoIonxFhJWbNmoWMjAxccMEF0T4VgiAIQiWGHF/Tp0+HJEm44447gj5nyZIlkCSpxb+tW7caeWuCiArKfC+AhC+CIAiCiDd27NjB/7+6ujqKZ0JYjcOHD+Paa6/F5ZdfDo/HE+3TIQiCIFSi2/G1YsUKvPnmmxgwYICq52/btg3p6en857Zt2+p9a4KIGsoyR4CEL4IgCIKIN3bu3Mn/n4QvQsmBAwcAAHV1dTh69Cjy8vKifEYEQRCEGnQ5vqqqqjBlyhT85z//QVZWlqrX5ObmIi8vj/+z2+163pogogpzfGVkZAAg4YsgCIIg4g1yfBHBOHz4MP//4uLiKJ4JoaS+vh7Hjh2L9mkQBGFhdAlfN998MyZNmoTTTz9d9WsGDx6M/Px8jBs3DosXLw75XLfbjYqKCr9/BGEFmPB1wgknACDhiyAIwmwOHDiAc889F9999120T4VoJZDjiwiGUvg6dOhQFM+EUHLmmWeiY8eOKCkpifapEARhUTQLX3PnzsXq1asxffp0Vc/Pz8/Hm2++iXnz5mH+/Pno1asXxo0bh59//jnoa6ZPn46MjAz+r2PHjlpPkyBMgZU6Dh06FAAJX2YjyzLtqEUQrZzPPvsMX3zxBf79739H+1SIVgI5vohgKMUucnxZh7Vr16KqqgpbtmyJ9qkQBGFRNGV87d+/H7fffju+++47JCYmqnpNr1690KtXL/7ziBEjsH//fjz33HM49dRTA75m2rRpuOuuu/jPFRUVJH4RUae+vh67d+8GQI6vSHHGGWeguLgYq1evhtPpjPbpEAQRBY4ePQoA2LNnT3RPhGg1kOOLCAaVOlqT2tpaAMCRI0eifCYEQVgVTcLXqlWrcPjwYT7pBwCv14uff/4Zr7zyCtxut6rsruHDh2POnDlBf+9yueByubScGkGYzq5du+D1epGamoqePXsCIOHLTEpKSrBo0SIAwO7du/l3ThBE66K0tBQAsG/fPsiyDEmSonxGRDxTWVnpJ25UVVVF8WwIq0GOL+shyzLq6uoAkPBFEERwNAlf48aNw4YNG/weu/rqq9G7d2/ce++9qgPr16xZg/z8fC1vTRBRh+V79ezZk+9QSsKXeWzfvp3/f3FxMQlfBNFKYZktdXV1OHToEO2iRpiK0u0FkOOL8IcyvqwHE72AJocwQRBEczQJX2lpaejXr5/fYykpKcjJyeGPT5s2DQcOHMB7770HAJgxYwa6dOmCvn37or6+HnPmzMG8efMwb948QR+BICIDy/fq2bMn0tLSAAA1NTXwer20S6kJsO8bAIqKiqJ4JgRBRBPm+AIayx1J+CLMRJnvBZDwRfhDji/rUVNTw/+fHF8EQQRDk/ClhqKiIuzbt4//XF9fj3vuuQcHDhxAUlIS+vbti6+//hoTJ04U/dYEYSrM8dWrVy8ufAGNZRAZGRnROq24pbnjiyCI1olyl669e/di+PDhUTwbIt4hxxcRCsr4sh4s3wsg4YsgiOAYFr6WLFni9/Ps2bP9fv7HP/6Bf/zjH0bfhiCijtLx5XK54HA44PF4UFlZScKXCSgdXzS4JIjWS3PHF0GYCXN8sT6ehC+CIcsyCV8WhIQvgiDUYIv2CRBErKB0fEmSxF1flPNlDiR8EQQBWEf4Wr16NW6//Xa/8yHiD+b46t27NwByfBFNHDt2DA0NDfznsrIyuN3uKJ4RAZDwRRCEOkj4IggVHDt2jK/y9ejRAwBI+DIRWZb9Sh0p40s7O3fu9BsMEkQs4vV6UVZWxn+OpvD12GOP4aWXXsKHH34YtXMgzIc5vgYOHAiAhC+iCZbvlZaWBqfTCcC/9JGIDiR8EQShBhK+CEIFzH2Un5/Pd3Qk4cs8ioqK/CYb5PjSxsaNG9G9e3dMmTIl2qdCEIYoLy+HLMv8571790btXJgYv3v37qidA2EudXV1KCwsBAAMGDAAAAlfRBNM5MrLy0O7du0A0PjECiiFr6NHj/r1GQRBEAwSvghCBcp8LwYJX+bBvm+brbGJooGlNtatW+f3X4KIVZqXFe7ZsycqkxpZlrngpdzAh4gvdu/eDVmWkZaWhi5dugBo3MCGIIAmx1e7du347rI0Pok+SuGrrq6OxGqCIAJCwhdBqECZ78VgwhcNisXDhK/BgwcDaFxl9Xg80TylmIINzpXbrhNELMJ2dMzLy4MkSaitrY1KKcuhQ4f45IqEr/iF5Xt1794dKSkpAMjxRTTBHF+5ublc+KJ+Nvo0j3WgckeCIAJBwhdBqIAJMYGEL3J8iYd93yeffDJsNhtkWaaBjAbYQLy6upombURMwxxf+fn5KCgoABCdckdleSMJX/ELy/fq1q0bCV9EC5SOLyp1tA41NTV+P9N4kSCIQJDwRRAqYI4vKnWMDCxLp3fv3sjNzQVAg0stKFegaTWaiGWY8JWdnY3OnTsDiE7A/a5du/j/FxUV0U5ucYrS8ZWamgqAhC+iiUCOLxqbRB9yfBEEoQYSvoiwlJWV4bXXXsMFF1yAxYsXR/t0Io7P5yPHV4RRZqrR4FI7yl2m4lH4kmUZ5513Hq688koKsY1zWKljTk4Oz1yKtvAFAAcOHIj4ORDmQ44vIhSsb6WML2vRXPg6evRolM6EIAgrQ8IXERCfz4cffvgBl112GfLz83HzzTdj/vz5ePrpp6N9ahHnwIEDqK2thcPh4BMvgIQvs/B4PHzVvWfPnsjPzwfQ6LIg1BHvjq+ioiJ89tln+O9//xvVXf5ikaNHj2LKlCn4/vvvo30qqlA6vqIpfDXfyZGuu/iEMr6IULD+lDK+rAU5vgiCUIMj2idAWIt9+/Zh9uzZeOedd/wmF+3atcOhQ4daZQfPyhy7desGp9PJHyfhyxz27t2LhoYGJCYmokOHDrSqqgPlfap0f8ULytXc3377zU+QJkLzxRdf4IMPPsDu3bsxfvz4aJ9OWJjjSyl8RUN0au74opyv+MPj8XCBs1u3bkhOTgYAuN1ueDweOBw0ZG7tKB1fzG1MY5PoQ8IXQRBqIMcXAbfbjY8//hgTJkxAly5d8PDDD2PPnj1IT0/HDTfcgD/++ANfffUVgPicRIdDWXanhIQvc2D5Xt27d4fNZiPhSyOyLMd9qaNS+Pr111+jeCaxB7s21q5dGxM7pTLHV05OTlQzvpggcvzxxwMg4Sse2b9/PzweD1wuF9q3b88dXwC5vohGAjm+aGwSfUj4IghCDbR81Yo5cuQInnjiCcyZM4dPLgDgtNNOwzXXXIPzzz+fr3ju378fQOOkSZZlSJIUlXOOBszxpcz3AsCDb0n4EktzoZEGl9ooKytDQ0MD/zneha/ffvstimcSezAHVW1tLbZs2YL+/ftH+YxCE6zUMZL9UH19Pe8DR48ejc2bN5PwFYewfK+uXbvCZrPB5XLBZrPB5/OhuroaGRkZUT5DIprU1tby8V5ubi7sdjsAoKqqCtXV1X5CKRFZmPCVm5uLw4cPk/BFEERAyPHVinn44Yfx0ksvobS0FO3bt8cDDzyAHTt24Mcff8Tll1/ORS8AfGc9j8eDY8eORemMowM5viJL8++bMr600dyVGe/C18aNG1tdm2QEJnwBwKpVq6J4JupQljp26tQJQKP7Rvk5zGbfvn2QZRlJSUkYNmwYf4yIL5T5XgAgSRLlfBEc1rcmJCQgIyMDqampfJwcjX5206ZNyM7OxmOPPRbx97YaNTU1AMD7CBK+CIIIBAlfrRi2gv3AAw9g7969ePzxx9GtW7eAz3W5XHy1s7WVOwZzfJHwZQ7k+DJG8wF4vAtfsixj2bJlUTyb2EL53cWC8KUsdUxMTOTtQSRzvli+13HHHcfLLUn4ij+UOzoymLObhC+CjX1zc3MhSRIkSUK7du0ARGd88v7776OsrAxPPfUUysrKIv7+VoI5vpjwRbs6EpFAlmVs3rw5JmIjiEZI+GrFsBXzIUOGcMt2KJjrqzUJX263m+fJkOMrMrCMrx49egAg4UsrTOhiQczxLnwBlPOlBaVTauXKlVE8E3UoSx0BRGVnR5bv1bVrVz6xYi4wIn5o7vgCQI4vgsP6UiZ2AdEdn/z0008AGkWfd955J+LvbyWY8MUWJsjxRUSCp59+Gn379sWMGTOifSqESkj4asWwCVBOTo6q57dG4WvHjh2QZRnp6el+gx2AhC8zqKur406O5o6vqqoqVFVVRe3cYgU2OGcOxXgWvvr27QuAcr60oBS+1q1bZ+mVSq/Xy8tYoyl8KR1fHTp0ANBYWqPMxiRin0COLxK+CIbS8cWIlvBVXV2NP/74g//86quvwufzRfQcrERzx1dFRQXcbnc0T4kwmX379kV1TnDkyBE8+eSTAJpEaML6kPDViiHhKzzKsrvmQcokfIln586dkGUZGRkZaNu2LYDG75lNPsj1FR52fw4YMAAAUF5eHncDQCZ8nXvuuQCA33//HfX19dE8pZhB6ZZjAfdW5dixY9xV1Vz4imSpo9LxlZiYyBdBqNwxfpBlmRxfREgCOb7Y/0d6gWnp0qXweDzIz89HZmYmdu3ahYULF0b0HKwEE77y8/N5BQuVO8Yva9euRc+ePXHRRRdF7RyeeuopLryxuSJhfUj4aqV4vV6/7BQ1tEbhK1i+F9AkfLndbr9d9Aj9BBMaqdxRPUrHl9PpBBB/9ywb0I4cORI5OTmoq6vDmjVronxW1sfn8/EsGNamWTnni/VRaWlp/FpmpSzRcnwB8Ct3JOKDoqIi1NbWwm6382sMaBK+yG1MWMnxxRwmp59+Oq655hoAwCuvvBLRc7ASTPhKTk5GmzZtAFC5Yzzz4osvwu12Y/Xq1VF5//379+PVV1/lP+/atYvmgTECCV+tlEAr6eFojcIXE2JCCV8Aub5E0Tzfi0HCl3qY8JWXl8fv2Xgrd2TCV9u2bTFy5EgAlPOlhmPHjvFymPHjxwOwds5XIFdytDO+ABK+4hHm9urcuTMXWQFyfBFNWCnja8mSJQCA0aNH48Ybb4QkSfj22295uW5rgwlfSUlJXPgix1d8Ulpairlz5wJoHCNEI2vz8ccfh9vtxqhRo5CcnAyPx8PHCYS1IeGrlcImFOnp6UhISFD1mnidRIeCOb6aB9sDgNPphMvlAkDClyia7+jIyM/PB9C4Kk+ERjk4j1YZhtmwAW2bNm248EU5X+Fh31t6ejpGjBgBIDYcX8rFGaXwFYkBb3l5OT+P5o6vSJZbEuYSKN8LIOGLaMIqjq+amhqe7zVmzBh0794dZ511FgDg9ddfj9h5WAml8MViMsjxFZ/Mnj0bdXV1AACPxxPx+deff/6JWbNmAQCmT5/O5ytsvkhYGxK+Wila870AcnwFgnK+xBJM+CLHl3qYyJWbmxuXwldNTQ0f5CqFr19//ZV22QuDst0/4YQTADRmZVg14J6dr1L4YmVolZWVPPjeTNgqbtu2bZGamup3DuT4ih8C5XsB4H9zEr4Iq2R8LVu2DA0NDejQoQN3od5yyy0AgFmzZrXKa7WmpgYACV/xjs/nayHuKjfsiQQPPfQQvF4vJk2ahJEjR/L5IeV8xQYkfLVSSPgKT2lpKXdINC+9Y5DwJRYSvozD7s94dXyxezIhIQGpqakYOnQoXC4Xjhw50mrLPNSibPd79OiBtLQ01NXVYfPmzVE+s8AEyqFMSkrifVEkyh2b53sBVOoYj5DjiwhHOMdXpBZeWL7X6NGjeRbqhAkT0K1bNxw7dgwffPBBRM7DSigzvkj4il8WLVqEHTt2ID09nZe0RlL4Wrt2LT766CMAwBNPPAEA5PiKMUj4aqWQ8BUe1oh16NCBD36bQ8KXOCoqKrhAQxlf+qiqquIrn+3atYvL8mRlmaMkSXC5XBg6dCgAyvkKB2v327RpA5vNhiFDhgCwbrljoFJHILI5X83zvQASvuKRYI4vEr4IoHFDKNb3BHJ8ud1ulJeXR+RcWL7XmDFj+GM2mw0333wzgMaQ+9bmfqZSx9bBa6+9BgCYOnUqCgoKAERW+Lr//vsBAJdccgkGDRoEAOT4ijFI+GqlsA5cj/BVVlaG+vp6U87LSgRzHykh4UscLNi+Xbt2SE9P9/sdZXypgwlcycnJSE1N5YPyeBKrleIN45RTTgFAOV/haN7us3JHqwpfgUodgSbhKxIZW6EcX0VFRXC73aafQyBa28TWbMjxRYSipKQEPp8PkiT59T1JSUnIyMgAEJkFptraWvz+++8AGh1fSq666iokJydj/fr1rWoRSJZlnvmkDLcn4Su+2L9/P7788ksAwI033sjHMZESvn799Vd88803sNvteOyxx/jj5PiKLUj4aqXocXxlZ2fDZmu8ZFrDbimsEQuW7wWQ8CWSUEIjOb7U0TyDJJ5LHZWTDwq4V0fzdt/qwlegUkcg+o6vNm3aIDExEQBw4MAB089BSXFxMU499VT069cvaqJbvFFaWsrz4pR/Z6BJ+Kqqqor0aREWgi0e5eTkwOFw+P2O9bORGJ8sX74c9fX1KCgoaOFOzMrKwuWXXw6g0fXVWmCiF+Dv+GoN85TWxJtvvgmfz4fTTjsNffr0iajwJcsy7rvvPgDANddc41eVwuYsxcXFqKioMP1cCGOQ8NVK0SN82Ww23qHEk4MkGOT4iixqhK/Dhw/D6/VG9LxiCWWwPdB6hK+TTz4ZALB161Ya7IaguVuOlYhaNeA+WKkjC5ePZMaXUhCRJCkq5Y7btm3DiBEj8Msvv2Dz5s3cJUsYg7m9CgoKkJyc7Pc7cnwRQMu+VUkkF+ZYmaMy30sJK3ecP39+xEX5aMHKHAEqdYxX6uvr8Z///AdAo9sLQESFr//973/45Zdf4HK58NBDD/n9LiMjg4+1qdzR+pDw1UoJVC6khtaU80WOr8jCJnGBNhLIzc2FJEnwer0R38ElllAG2yv/G+/CV05ODvr06QMAWLp0aVTOKxZoXurYvXt3SwfcB1ugiZTjy+fzcceXstQRiHzO12+//YaTTz7Z7zNHYlfL1kCwfC+AhC+ikeZ9q5JICl8s2F6Z76VkwIABGDVqFDweD958803Tz8cKMOHL4XDA4XCQ8BWHLFiwAIcOHUJeXh7+8pe/AIic8OXz+bjb6+abb0aHDh1aPIfNE6nc0fqQ8NVK0eP4AlqP8OXz+bgQQ46vyBDK8aUczFDOV3CClTqWlJRY0tGjh0DCF9CU89Wask200rzdt3rAfbhwe7MzvoqKilBfXw+73Y6OHTv6/S6SwteCBQtw+umno7S0FCeeeCJvI0n4EkOwfC8ASE1NBUDCV2tHjePL7AWmuro6LF++HEBw4QsAbrnlFgDAG2+80SryeJXB9gD4WLGkpIQqBOKE119/HQDw17/+FU6nE0DkhK9PP/0Ua9asQVpaGqZNmxbwORRwHzuQ8NVKIeErNPv27YPb7YbT6eSTrECQ8CUGWZbDlpZSzld4mgtfOTk5sNlskGU5blY/g23MQTlf4Qnk9GXljitXrozKOYUiXKnjsWPHTBV/WJljp06dWuT6REr4euWVV3DBBRegrq4OZ599NhYvXszfm4QvMZDjiwgHG/MGEr4ilfG1fPlyuN1u5OXlBXTGM8477zzk5+fj0KFDmDdvnqnnZAXYTtZM+GJjA1mWeR9CxC6bNm3CTz/9BLvdjuuvv54/Hgnhy+Px4MEHHwQA3H333UGrpCjgPnYg4auVomdXR6D1CF9MhOnevTvsdnvQ55HwJYYjR46gvLwckiQFXHUHSPhSQ3Phy2638446Xsodwzm+Vq5c6Rd2SzQRqN23asC9x+Phwk7zfiolJYX//c10fQUKtmeYLXz5fD7ce++9uPXWWyHLMv72t79h/vz5SE5ORlZWFoDGHZYJ44RyfJHwpY9423W0ed+qJFJjE2WZY6B8L4bT6cQNN9wAoHWE3DPHF8vnczqdyMzMBEDljvEAc3udc845fmWGbFxgZq7ru+++iz///BM5OTm48847gz6PHF+xAwlfrRBZlnU7vlinH+/Cl5p8L4CEL1GwstJOnTrx3dKawwaXVOoYnECr0vF2zwYTvrp27Yp27dqhvr7eku6laBOs3WfC17p16yxVDqt0MzGhR0kkcr6Y46t5vhfQJHyZIby53W5cfvnleOaZZwAATz75JF5//XXuOmOTOnJ8iYEcX2LZtGkT8vPz8c9//jPapyKMUI6vSAlfymD7cLCSsKVLl2L16tWmnle0aV7qCIB2dowTqqqq8N577wEAbrrpJr/fme34qqurw6OPPgoAuO+++5Cenh70uczx9eeff8ad6B9vkPDVCqmuruZ1/+T4CgxT7Un4igxqdtDMz88HQI6vUARalY63gPtgwpckSZTzFYKqqio0NDQA8G/3rRpwzwaz6enpLcoMgcjkfIVyfLFyy3379gkd6B47dgxnnXUWPvzwQzgcDrz77ru47777/BweJHyJo6qqivcpoRxfVVVVET2vWOb+++/HoUOHMHv27LiZBIZyfEWij1Wb78XIy8vDhRdeCAB49dVXTTsvKxBK+CLHV2zz/vvvo7KyEj179sTYsWP9fme28DVz5kzs378f7du35ztJBqNr166w2+2orq7GwYMHTTkfQgwkfLVCWCPhcrn4oE4trUX4Yo6vUEIMQMKXKNQIX1TqGJ54F75kWQ4qfAGU8xUK9r0lJSXxkhCgMeCeub6s5JRj2SzBFmeY8BQtxxcruaipqRGWI1NYWIhRo0Zh8eLFSE1Nxddff40rr7yyxfNI+BIH+xvn5OTw71UJGyPV19dbyhFpVVatWoXPP/8cQGOfU1hYGOUzEoMax9ehQ4fg8/lMef8//vgDdXV1aNeuXdgFWQYLuf/ggw/iejdsEr7iE1mW8dprrwEAbrzxRths/pIFGxtUVVUJ38ShsrIS//rXvwAADz/8sN+1FQin08kXyCjny9oYEr6mT58OSZJwxx13hHzeTz/9hBNOOAGJiYno2rUrZs6caeRtCYMoy11C5QQEorUIX9FyfB06dAg33ngj1q5dK+R4sQIJX8apq6tDeXk5gPgVvpQDnHDCl1kTkFglVHm7FXO+ggXbMyJR6hjK8ZWYmMjvLRE5Xxs3bsSIESOwceNG5OXl4eeff8YZZ5wR8LmU8SWOUPleAPwWB6ncMTyPPPKI388rVqyIzokIRJblkI4vNi72er2mCUws32v06NGqx+0jRozA4MGDUVdXh1mzZplyXlaAhK/4ZOnSpVi/fj2SkpIwderUFr/PzMzk94Lo+27GjBk4cuQIevTogauuukrVayjnKzbQLXytWLECb775JgYMGBDyebt378bEiRMxatQorFmzBvfddx9uu+22VrHTiFXRm+8F+Atf8WJhb05tbS2fyETa8fXhhx9i5syZvK68tcAyvkLtVMRKHSnjKzBMjFYGuwLxJXwFcy0xBg8ejKSkJJSVlWHr1q2RPj1LE2hHR4YVhS92vuGEL7NKHevq6nDgwAEAgR1fgLiA+9LSUowePRqFhYXo3bs3li1bhsGDBwd9Pjm+xBEq3wtodMYzpwEJX6FZsWIFvvrqK9hsNpx22mn8sVinqqqKb5gSyPHldDp5u2rWwhzL91JT5siQJIm7vl577TV4vV4Tziz6BBK+2N+DhK/Yhbm9Lr300oA5n3a7nY8PRApfJSUleO655wAAjz32GJxOp6rX0c6OsYEu4auqqgpTpkzBf/7zn4AXo5KZM2eiU6dOmDFjBvr06YPrrrsO11xzDb+oiMgjQviqra2N20Hgjh07IMsysrKygm5dyxAtfDHxwkolR2bj8/m48EWOL/0oSzGUK8LxKHwFuy+dTidOOukkAJTz1ZxQO/kOHToUALB27VqeAxZtwpU6mu34YoJaampq0OtNlPD166+/orS0FJ07d8Zvv/3GP1swSPgSRzjHlyRJSE1NBUDCVziY2+vyyy/HpZdeCiA+hC/Wd6akpASNBzGzn3W73Vi6dCkAdcH2Si699FJkZ2djz549+Oabb4SfmxWgcPv44/Dhw/j0008BtAy1V2JGztdzzz2HiooKDBw4EBdddJHq1zHHFwlf1kaX8HXzzTdj0qRJOP3008M+d9myZS3s+hMmTMDKlSstM8BubYSaAIUjJSWFOy3iYSIdCGW+VzhLuVL4EuGAY6UrhYWFcV9OyigsLERdXR2cTifP7QkEE74qKipQU1MTqdOLGYKVYjCxOh7u11CuJQYLuKecL39CLXh069YN6enpcLvdlgm4D1fqyNqK0tJSVFRUCH9/Zb5XsH5AlPC1fv16AMCoUaOCfl4lVOoojnCOL4B2dlTD8uXL8c0338But+PBBx/EsGHDADQu4sV62XmofC+GmQtzK1asQF1dHdq2bYs+ffpoem1SUhKuvfZaAMArr7wi/NwAoKGhgbeX0YCNB6nUMX6YNWsW6uvrceKJJ3JHeiDMEL5+/PFHAMA999zTIlcsFMqdHQnroln4mjt3LlavXo3p06eren5xcXGLiVi7du3g8XiCKvFutxsVFRV+/whxGHF8AfGf88WELzUBokz48nq93ApvBOVExkplR2bCOolu3boF3L2NkZ6ejsTERADxIeKIJpjwxX6Oh/s1nOMLaMr5IseXP6HafZvNhiFDhgCwTrsTrp9KS0vjIpEZ5Y6h8r0YooWvcNERDHJ8iSOc4wsg4UsNzO115ZVXonv37ujbty8SExNRXl7OxcVYJVS+F8NM4YuVOWrJ91Jy4403QpIkfPfdd6a4UZ566il069YNc+fOFX5sNTDHlzL+gISv2MXr9fIs8HC7KZohfLGxcqg+IRBszrh792643W5h50OIRZPwtX//ftx+++2YM2cOn4CqoXlDzZwxwRrw6dOnIyMjg//r2LGjltMkwqDGNRGKeBe+1AStM1gJBCCm3FEpfK1evdrw8WIBNfleQGN7QTlfwVEjfMX6yrsa4WvEiBGQJAm7du2islgF4b47q+V8hXN8AebmfIXa0ZEhSvhat24dAGDgwIGqns+Er/Ly8pi/p6OJ2+3G/v37AZDjywhLly7F//73PzgcDjzwwAMAGsvOBw0aBCD2yx2j7fhiwfZa8r2UHHfccZg8eTKAptwkkfzxxx8AgDfffFP4sdVA4fbxxbfffou9e/ciKysLF198ccjnmil8hbrfA5GXl4fU1FT4fL6oOiCJ0GgSvlatWoXDhw/jhBNOgMPhgMPhwE8//YSXXnoJDocjYHBiXl5ei47g8OHDcDgcQVdyp02bhvLycv6PDUwIMZDjKzRaHF82m40PikULX1aZgJqNFqGRcr6Cw4Sv5p21cscpJibEKmqEr4yMDPTv3x8AlTsqCdfus5wvq+QLhgu3B8zN+YqU46umpoaL/1odX7IsC8uXbI3s2bMHPp8PKSkpISc5rI+vqqqK1KnFFA8//DAAYOrUqX73Cyt3jBfhK5Tjy6yMr/r6et6P6RW+gMaIGgCYM2eOiNPyg4lLP/30U1TGZuGEr3jdiCteef311wEA11xzjd/fNBCiha/q6mpeOqtV+JIkiXK+YgBNwte4ceOwYcMGrF27lv8bOnQopkyZgrVr18Jut7d4zYgRI/D999/7Pfbdd99h6NChQXdKcLlcSE9P9/tHiIOEr+DIsuyX8aUGkQH3JHyFhoSv4AQbnDudTi4exHqJqBrhC2jK+aJyxybCtfvM8bVu3TpL5G+GC7cHmnK+zBC+tDi+ioqKUF9fr+t9Nm3aBFmW0bZt25ATayWJiYncdU85X/pR5nuFKiEjx1dwfv31VyxatMjP7cWIF+Er2KKSErPGJitXrkRtbS3atGmD448/XvdxRowYAaCxXRWdkcqEL5/Ph/nz5ws9thpC7erY0NBAcTkxxK5du/Dtt98CAG644YawzxctfLFrOTEx0a+iRy1M+KKcL+uiSfhKS0tDv379/P6lpKQgJycH/fr1A9Do1rryyiv5a2644Qbs3bsXd911F7Zs2YJZs2bh7bffxj333CP2kxCqIeErOEePHsWxY8cgSVLY0juGWcLXvn37WsWONCR8iSFUDkm87OyodmMOlvNFjq8mwpW4Wy3gXkupo2jhS5ZlLnyFcny1bdsWiYmJkGUZhYWFut5LWeaoJb+Hcr6MoybfCyDhKxTM7XXNNde02I2UCV+rV6+Gx+OJ9KkJQ43jy6yxidF8L0ZaWhoSEhIAiC//Ux7v448/FnpsNQQSvpKTk3nmV2sYRxuhrq4OZ599Nr+Xo8kbb7wBWZZxxhlnhCw/Z4gWvti93rZtW133G5vHkOPLuuja1TEURUVFfrb/4447Dt988w2WLFmCQYMG4fHHH8dLL72ECy64QPRbEyoxsqsjEN/CFxNhOnXqFNZiyxAlfPl8Pi58ZWRkAIj/nK+GhgZeUqRGaKSMr+C0JuFLreNr9erVNFn9/4Rr9202G3d9WaHcUUupo+iMr7KyMu4SaD6ZVyJJkuFyR63B9oxYE7527NiBtWvXRvs0/FCzoyPQlOVJbYk/P/30E3788Uc4nU7cf//9LX7fs2dPpKeno7a21hJiul7UOL5YH2um8GUESZJMyb1yu91+Y9+ff/454uOzQMIXQDlfavnhhx/w1Vdf4bHHHuNuq2hQV1eHt99+GwBw0003qXqNWcKX1jJHBjm+rI9h4WvJkiWYMWMG/3n27Nm8oWaMHj0aq1evhtvtxu7du1XZFwnzIMdXcLSWOQLihK/KykoeVMyyHOK93HH37t3wer1ITk5GQUFB2OeT4ys4oYQvds+2FuGrU6dO6NChA7xeLw/ebe2oafetEnCvLE8Jdb5mOb6YGJ+Xl+e3U1ggjApfWoPtGVlZWQBiQ/jy+XwYNWoUhg8fLjSE2Cjk+DIGc4hcd911/D5QohTTY7ncUUu4fUlJibBS8YaGBiH5Xgwzxu5MVHI4HDjppJMgyzLmzZsn7PhqIOHLGMr+/sYbb4xaluFnn32GkpISdOzYEZMmTVL1GqsJX+T4sj7CHV+Etamvr+cCDe3q2BKm0qsJtmeIEr6Y2ysxMZGXasW740tZ5qjGVkzCV2A8Hg/v+AN12MqdHWMZtcIX0FTuSDlfjRMDlusS6ruzivClFHOYsykQLOPr6NGjQkUJNfleDCPClyzLhh1fsZDxtXv3bhQXF8PtdmPjxo3RPh2OWscXCV8tWbx4MX766SckJCTgvvvuC/q8eMj5CrWoxMjJyYHdbocsy8KElpUrV6KmpgbZ2dno27ev4eOZIQSxY7Vp04bvwBfpckfWt5HwpQ9lf7937148+OCDUTmPrVu3AgDOOussOBwOVa+xqvB15MiRmOibWyMkfLUyWG6KzWYLOaEIRTwLX9F0fLFGMisryzITULNhu5mp/b6Z8EWljv4cPXoUsizDZrMFFDbiodRRlmVNwhcrd6Scr6ZBocPh4O1VIKwScM/ONyMjI+QAOCMjg/djIssd1ezoyDAifBUWFuLYsWNwOBzo06ePptfGUqnjhg0b+P+zyU208Xq9XOAkx5c2ZFnmbq/rr78eHTp0CPrcWBe+6uvr+dgs1GTYbrfz34tamPvpp58ANFbN2GzGp2tmCl9t27bFhRdeCKBxsenAgQPC3iMczPHV3J3LxgnxInwtWLAAp556qvDSfhZtwDanePHFF6PilGfta6gxSnOY8FVaWipk9052regVvlJTU3n1CpU7WhMSvloZbEKRlZWluyNlDcLRo0fh9XqFnZsVsILjKysrC0OGDAHQOAFjYmU8wr5vtRsJsIyvQ4cO8bJQoknQatOmTcDddeNB+CovL+ftjZoybeb4Wrp0ady1U1pRljmGclZ269YNGRkZcLvd2LRpU6ROrwVqdnRkmFHuGCnHFytz7N27N1wul6bXxqrwZZUSkMLCQjQ0NCAhISGkcAM0CV/RKgGyGj/88AN++eUXuFwuTJs2LeRzmfC1fv161NXVReL0hMImwna7PWTeICA+54vFxogocwSaxu5mCV8dO3bEySefHPFyx3CljvESbv/mm2/il19+wZw5c4Qds7i4GAcPHoQkSbj33ntx+eWXQ5ZlXHfddRFf/GLOPdbeqoGNEbxeL8rLyw2fg1HHF9A0f7RKX0f4Q8JXK8NovhfQtIri8/niSpTxer0880OP48vooFgpfGVmZvJV6Hgud9SyoyPQ1Bl5PJ64uvaMEq4UIx6ELzZ4TU1NRWJiYtjn9+/fH2lpaaisrLRUeVU0CLejI8Nms3HRPZpuUzU7OjJYuaMZwpfZji+9ZY5AU8ZXLJRTWFH4Yn39cccdF3CxQAk5vppQur3+9re/oX379iGf36lTJ7Rt2xYej4cLvbGEcpe3cIvFzJEuop9V5nsZDbZnMCHIjIwvduyLLroIQGTLHVtLxhfrF3///Xdhx2T9fO/evZGamooXXngBbdq0wYYNG/Dss88Kex81MOErXK6mksTERP58EeWOyvtdL2w+Q44va0LCVxRYuHAhxo8fj3vvvTfi7210R0cAcDqd/PXxVO64d+9e1NfXw+VyBQxqDYYZji8AfAJKwlcTCQkJ/NqjnK8mWpPwpTab0OFwYPjw4QAo50tLu2+FMmstCzRmOL5YqaNWx5fWUgsjwlesOr6sUuqoNt8LIOFLyffff4+lS5ciMTER//znP8M+X5IkDB06FEBsljuqyfdiiMwgXb16NaqqqpCVlYX+/fsbPh5gfqkjAF7u+Ntvv6GwsFDY+4SiNQpfIsr6gKZ+nvX7bdq0wQsvvAAAeOyxxyIq3ugRvgCxOV/k+Ip/SPiKAuXl5Vi0aFFUsmdEOL6A+Mz5Yo1Ujx49NJWBmiV8WWECaiY1NTV8YKTFYUc5Xy0J11krhS9RA6ZIo9a1pIRyvhrR0u6zSSrL/YgGWhxfTPgSlXvi9Xr5sdQ4vliZXHV1tWb3ld4dHYHYEb7q6up4liPQKFBaoeRN7Y6OQKPLFCDhS5ZlPPTQQwAad39j0QPhYOWO0WxT9KJlIixS+GJljqeeeqqQfC8gMsJX+/bteb/76aefCnufULQ24evw4cPC+js2v2D9PgBMmTIFEyZMgNvtxl//+teIxYqw9lVLqSNgPeGLHF/WhoSvKMAGWmzFMZLomTwGIh6FLz35XgAJX3phE4/s7GxVE1wGG2yT46uJcKvS7H6tr68XkoMQDbQ6vgDa2ZGhpd1n7c769eujFnDPzleL8CXK8XXgwAE0NDTA6XSGLeMCGidb7P7SUu5YW1vL+5x4dnxt2bIFXq8X2dnZyMjIgM/n421/NCHHl3YWLlyI33//HUlJSZoqFmI54F6L40tkxhcLtheV7wWYM25vLnwBkS93bA3Cl8/n81tYEVXu2NzxBTS6NGfOnInk5GT89NNPePvtt4W8Vzii7fhS7sgqwvG1fft2yiK2ICR8RQEmfBUXF/MbPVKQ4ys4enZ0BMQJX2w1hwlfgwcPBtA4QLf65Mbtdmt+jdYyR4bIVdV4IdzgPCkpiV+nsXrP6hG+TjrpJNjtduzfv19XBlO8oKXU0QoB91rC7UVnfLF8r86dO4fNfmLoyfnavHkzfD4f2rRpo9o5oyRWMr5YmWP//v0tVQKixfFFwpd/ttdNN92kSghiMOFry5YthsdJkUaP48topIDH48Evv/wCQFy+FxAZxxcAXHDBBZAkCcuWLTO935VlOajwFU+7OpaXl/u59ZcvX274mMXFxThw4AAkScKgQYP8ftelSxc88cQTAIC///3vEamwiLbwVV5ezhf7jGR8denSBU6nE7W1tbrLfWVZxi233IIbbrghZqs0rAoJX1EgKyuLD1rZIDtSkPAVHDYY1+r4YmUQohxfzOWQk5PD3Qxr1qwxdGwz+d///ofk5GRMnz5d0+tI+BKHmlXpWM/50iN8paam8gFday531NLuS5LE8wWjVZqkp9Tx8OHDfAJkBC35XgwmfGkpP2FljgMGDAi502YwYsXxZUXhS5Zlcnxp5Ntvv8WKFSuQnJyMf/zjH5pe265dO3Ts2BGyLMdcZmk0Mr7WrFmDqqoqZGZm6nKDBoNN5qurq4W0lUBg4augoACjRo0CYH65o7JsOpjjS+TnjRbNN3MS4fhqHmzfnNtuuw3Dhg1DeXk5br31VsPvFw7WvkZL+GLz2fT0dFUbKAXD4XDwBRW9fd2mTZvw6quv4o033oibXUmtAglfUYJlh0S63FG08BWrk+hA6BVizCp1BGKj3PHLL7+Ez+fDQw89hM2bN6t+Hct90fp9M3cEZXw1we7DUKvS8SJ8aW27KOdLe7vP8j6i1e5oKXXMzMxEeno6ADE5X1p2dGQw15kWd4ORYHsgNoWv3r17A4h+wP2hQ4dQXV0Nm83GhdNQMOHL6M7NDI/Hg6VLl1oi60wtTMC4/vrrdZUBxWq5YzQyvpT5Xmpdp2pIT09HQkICAHEuqEDCFxC5ckeloNVc+MrIyIDT6QSAmBcPmPDFPs/q1atRX19v6JiByhyV2O12/Oc//4Hdbse8efOwYMECQ+8XDub4ilbGl4gdHRlskUdvztcXX3zB/7+iosLw+RBNkPAVJaKV8yViV0cg/hxf1dXV3JJqlYwvIDZ2dtyyZQuAxsH8jTfeqNqWyzqEHj16aHo/cny1hN2H5PhqCcv5as3Cl9bvLtqCu5ZSR0mShOZ8MceXFuFLT6kjE770BNsDTf1EVVUVPB6PrmNEAis6vti4q1OnTlwICIVox9frr7+OkSNH4qSTToqZAGTm/hw3bpyu18e68KUl46u8vNyQqMnyvUSWOQKNbSWb1IsYuzc0NPBxa3OxgJU7/v7770J33G0OE74cDgcXhRiSJMVNuSP7nvv06YPs7Gy43W7eh+glnPAFNPZPzOF58803m5oRG+1SRxHB9gy2oK+3r/vyyy/5/8daebjVIeErSkRL+KJSx8CwjjkrK0tT0DpAji8mfAHAzz//jPfee0/V66jUUQw+n4+ErxAw4Wv9+vWtduVMa7uvDLg3uqqsBy2ljoDYnC/m+NJT6qhW+JJl2a/UUQ8ZGRn8/63q+iotLcXBgwcBAP369fNzfEUzt4Tle6kpcwSahK/6+nohIiNzO69fvx4nnHAC5s6da/iYZlJTU8Pz/kJNkkMRq8KXGjc1IzMzkwupevtZZb6XyGB7hsicL9avSJLUoq3Oy8vjwp2Z5Y7B8r0Y8RJwr1wMOvHEEwEYL3dUI3wBwIMPPogePXqgqKgI//znPw29ZyjiSfgysshz+PBhv79tax23mgUJX1GCCV/RyviiXR39YasYWkUvoEn4qqqqMjSYD+X4+vPPPy3Z+JWXl/OSw2nTpgEA7rnnnhZ5BM0pKyvjQobayQeDhC9/ysrK+GSsNZQ6am27CgoK0LVrV/h8PnzzzTdmnJrl0Sp8RTvgXuv5MseXiFLHSDi+Dh48iNLSUtjtdhx//PHaTxKNDgeWy2JV4Yu5vbp06YK0tDR0794dNpsNFRUVUW2H2IKjmmB7wL/0RoTri403UlNTUVVVhUsvvRQ33nijZUsf165dC5/Ph4KCAhQUFOg6Bptc7969O2bKzmRZ1uT4kiTJ8Phk7dq1qKioQEZGhm43aChECkHsGDk5OQFLMiNR7tjahK+srCycdNJJAIwJX4cOHeLB9mwjrWAkJSXhzTffBADMnDmTC7MikWWZt63RKnUUsaMjgy3o63H0fv31135zSXJ8iYWErygRjYwvn8+nqYQkFNEUvszYHpaJSkzE0gJ7jbLh1orP5+OTF6Xw1bZtW3Ts2BFA44DIarCslvz8fDzyyCM4/vjjcfToUS6CBYOteLdv3z5gqGYoWMZXWVmZoYlCcXFxXOyWwiaQWVlZIct2Yj2XT6/wBQBXXHEFAOD555+Pi7+5FhoaGvhEW+13J0lS1NymDQ0NfKCndiFCVKljTU0Nn7DqcXwVFRWpcsgxt1evXr0MhehaPedLWeYIAC6Xi/+tolnuqNXx5XK5+MRepPD19NNP4/777wfQOKEcMWIEPzcrwcoc9bq9gMZrlU0Go7VphlaUi0pqc3+YQKZX+GJljqNGjRKa78UQOXYPlu/FOP/882Gz2bBixQq+oCCacMIX6/NiRWwNhtIFLUL4Chds35wxY8bguuuuA9CY8ydapG9oaIDX6wUQX46vvXv3at5YQZnvBZDjSzQkfEUJttK4Z88efrObTXl5OReNRAlflZWVEdstZd26dTjrrLOQnp6OpUuXCj02m2jpEb6Sk5Nhs9n8jqPn/dnfRil8AdYud2Rljn369EFCQgJef/11AMCbb74ZcrtlvflegJhygjlz5iA/Px8vvfSSrteLYufOnXj33XcNiTFqO2s2II9Fl6bX6+UDPz3C10033QSXy4UVK1a0uqwv9r1JksSFEjVEq91hzlct5ytK+GKvz8jIaNEOh6Jt27ZwuVyQZRkHDhwI+3yjwfYMdo7sO7MazYUvAJYIuNfq+JIkSWjOl9Jh/sQTT2DhwoVo06YN1q5diyFDhuCTTz4x/B4iYUIV2/RCL+z1sVLuyPrKzMxMuFwuVa9hji+9Y5Nff/0VQGOwvRmY4fgKJny1a9eOl2uadU23NsdXdnY2L3X8888/dbf9assclTzzzDPIy8vDtm3b8K9//UvX+waDlTkC8SF8tW3bFhkZGX47CKuhrq4O3333HYCmBTUSvsRCwleUaN++PRISEtDQ0ID9+/dH5D1Zo5Camqoq0DUUyt1SzO5Q9uzZgyuuuAKDBw/GwoULUV1dbSnhS5IkvmKiV/hinVpiYmILB0CsCF9A42Bt6tSpAIAbbrghaB6K3nwvQEw5wVdffQUAIcU5s/F4PJgwYQKuuuoqLFy4UPdx1G63HsuljseOHTMk2ufm5vq5vloTrN3PysrS5CBg7U6k3RnsfDMzM1Wfr6iML2W+lyRJql8nSZKmckejwfaMWHN8AcayT0Sh1fEFiA24Z8IXy2mbMGEC1qxZg1NOOQWVlZW46KKLcMstt1im9FGU8BVrOV9a8r0YRsYmsixzF8/w4cM1v14NkRS+APPLHa0mfPl8PvzrX/8SvgOiUvjKycnhbdcff/yh63h6XJxZWVl4+eWXAQBPPfWU0H6Htat2u73FJgXhYGPC6upquN1u3ecgUviSJElXX7d48WLU1NSgffv2GDVqFAAqdRQNCV9Rwm6381KKSJU7itrREWi8qc0udzx69CjuvPNO9OrVC3PmzIEsy7wTE62As+Olp6frer3RgPtA+V6MWBK+AODZZ59FVlYW1q1bh1deeSXg64wIX0DT4JLli2mFdfoseDkazJkzh9/7RnbtbA3CF2u7lIK7Vu68804AwGeffWbJciKz0JvryCa5kQ641xpsDzQ5voqLiw2JBXryvRhahC+jwfYMKwtfsixj48aNAKzl+CorK+PXmJa/MxO+qqqqDJ9Dc+ELADp06IDFixfz8OhXX30VI0eOjPgGSM2prKzkfysjpY5Ak/AVK6WOeibCRoSvwsJCFBUVwW63G/6ug8E+S6SEL1buuGrVKlOuZeYUsorwtXDhQtx///246aabhB63eb9otNxRj+MLaNytMyMjAw0NDUJzdtnfMSUlRdOiE9DYjrKqGyOuL3a/qy1rDoeenC+2m+PkyZN5/0COL7GQ8BVFIh1wL2pHR4ZZwld1dTWefPJJdOvWDTNmzEB9fT1OP/10rFq1Ctdeey0A8Qq4EceX8nVGha9Akz0WcL9t2zYhg26RBBK+2rZti6eeegpA424wgUp/WMaXXuGL5Xzp6XhLS0v5AEyvcGYUj8eDJ554gv+8efNm3cfSKnxVV1cLcS1EEiP5Xozjjz8eZ511FmRZxosvvijq1CyP3gWPrl27IjMzE/X19RENuGf9lBbhKzs7m7tu1QbMB0LPjo4MtcJXXV0dXwEWVepoReFr7969qKyshNPp9Gvno+34Ym1/fn6+phBlMx1fDIfDgenTp+Obb75BTk4OVq9ejSFDhmDevHmG31Mva9asgSzL6Nixo6qA91AMHjwYdrsdRUVFqkqCo43avlWJkYwv5t7p37+/5nIvtbBJfSQyvtjvxo4dC8Ccckfm+Ar2fUVa+GI7tB4+fFhoHrFI4UtLsH1zlGXfyvJEo+jd0REAbDYb/16MZLmJdHwB2vs6WZa58HXOOedwIwY5vsRCwlcUiXTAvagdHRmihS+Px4M33ngD3bt3xwMPPICKigoMHjwY3333Hb7//nsMGTKENwSiFXCrCF+BHF/t2rVD+/btIcuypQLu6+rq+ERRKXwBwHXXXYfhw4ejqqoKd9xxh9/vZFk2lPEFGFtVVTrnDh48GJWw8/fff9/vvmcCoh7UDs5TU1P5qmisub5EtV133303AGDWrFlhdx6NF/QueEiSxEX3SLpN9WzAIkmSkHLHSDi+tmzZAq/Xi+zsbLRv3177SSpgji8rZnyxMsc+ffr4uTTZZGDPnj1RKeXTmu/FECV8ybIcVPhinHXWWVizZg1OPvlkVFRU4MILL4xaibaoMkegcVLbt29fALFR7mjE8aWnj2UiBhM1zCDSpY6AueWOasPtIyF81dbW4rPPPgPgv2GVCJovjiuFL61jWNaf9+rVS/PmUoDYRQCGEeELaPo763V8eb1e/lpRwpdWx9fatWtRWFiI5ORkjB07ls8ryfElFhK+oggbeEVa+LKa40uWZcyfPx99+/bFDTfcgOLiYhx33HH44IMPsHLlSowfP54/16yGgAlWVix1BKxZ7rh9+3b4fD5kZGTwwR7DZrNh5syZsNvt+PTTT/0yrIqLi1FVVQWbzaZrggkYE76UA+7q6uqIr6Yo3V5sl5ytW7fqXh1UOziXJClmyx1FOL4AYOzYsRgwYABqamrwxhtviDg1y2NENGST3UiWJukpdQSayh337t2r+71FOL7Cvb+yzFFrSUdzRJc6HjhwAH/961+FLLAEyvcCGgX6jIwM+Hy+qJQc68n3AsRN9mpra3n2ZTDhCwA6duyIJUuW4PbbbwcAvPDCC4beVy8ihS8gtnK+9Di+jIxN4lX4Ou+882C327FmzRru9heF2oyvSOzq+O233/qNJ0W+J+sX2Rxh4MCBSEhIQElJieaqITaP0HtPmyF8sWNpceEqMRpwX1JSAlmWIUmSsDmyVscXc3uNHz8eiYmJ5PgyCRK+oggJX43ceOONuOCCC/Dnn3+iTZs2eOmll7B161ZceumlvG6bYVZDwIQ0Kzq+gKZyRyNZUKJRljkGmsANHDgQt912GwDg5ptv5gMUtvpx3HHH6d5kwUjGV/NJfKRzvj788EPs2LEDOTk5eO6555CQkIDa2lrdE3Ytg3N2z7ZW4UuSJO76evnllyOaXRUtjGQ7RkNw11PqCBjf2VGWZUOOL+Y4C+f4ErWjIyBe+JozZw7+85//4MEHHzR8rGDCl97QX1HodXwxZ4TRyR5ze9lstrBuC6fTicceewxAY/5TJCbvzWnNwpfRjC8tThyPx8O/azOFL/ZZqqqqDO/Irlb4atOmDcaNGwdAfLmjWuGrtLQ06GZLomBljgyjuwwyZFlusSDkcrl4maLWcke9+V4MKzq+jApf7F7PycmBw+HQdYzmsIqW0tJSVefFhK+zzz4bgHlGj9YOCV9RRCl8RaLcyorCl9frxezZswEA//znP7Fz507ceuutQQURsx1fVhW+rOj4CpTv1ZxHH30U7du3x65duzB9+nQAxvO9AGMZX2zAzcS6SOZ8eTwePP744wCAv//978jIyOCTQL3ljlqEL/YcszakMAtRwhcAXHLJJcjPz0dRUVGLgWo8YqTdZ4L7hg0bhOaVhEJPqSNgXPg6evQoz1BkIpYWlKWOofpzUTs6AuIzvlhb+NNPPxmeJAYTvoDoBtxH2/HFhK/09HRVjr/09HR+rmvWrDH03lo5duwY769Fha0rA+6jETOgBSMZXzU1NZoyWTdt2oSamhqkpaXxMYEZpKenC9uRXa3wBZhX7hhO+MrJyeH3mSghKhCVlZV8t3C2QC9KqK6pqeGLdMoFIb05XyR8tUR0vhfQ+Fk6duwIIPwiz8GDB7Fy5UpIkoTJkycDgGnRPq0dEr6iCCunqKioiEjejGjhS8Qkeu/evXC73XC5XHjiiSfClhqa5fiKlVLHLVu2WCaYnE1a2CQmEGlpaZgxYwYA4Omnn8aff/5pON8L0F9OUFxcjMLCQkiSxAfgkXR8zZ07F9u3b0dOTg5uvvlmAE3CoZ6Ae1mWdQlfser4EtF2JSQk4NZbbwUAPP/885affBnFSKljly5dYLfb4Xa7I3af6C11NJrxxcpF2rdvj8TERM2v79ChA4DGyUCwzC1ZloXt6AiIz/hiE9nKykpD5a319fV8oB9I+IpFx5do4StUmWNzmLMj0hmfzGF+3HHHCRs39u/fHy6XC2VlZVHfsTIceibDqamp/FrR0s8y8WLYsGGw2+0azlIbkiQJKXf0+Xy8b1EjfP3lL3+Bw+HAunXrhN734YQvu93O+xIzc76+/PJL1NbWokePHjj55JMBiBO+WJ/odDr9SgGHDx8OQJvwdejQIT4G1hpsz4hn4UvUjo4MtX0dE01PPPFEPk43Oq8kAkPCVxRJSkpCQUEBgMiUO4qcPAJiHF9MPOnevbuqzt4sx5fVSx3z8/ORl5cHn8/HHQPRRo3jC2jc/vjMM89EfX09brrpJt4BGHF86S0nYJO5Pn368PeP1ITe6/Vyt9c999zDy1zY96fH8VVZWckDotUMzmNd+BK1Mcff/vY3JCcnY926dfjxxx+FHNOqGGn3HQ4HF5Ssvvuw0YwvVuaoJ98LaOzP2T0YrNyxuLgYR48ehc1m4yHfRhBd6qicGBq5L7Zu3QqPx4OMjAwuCCqJlvBVU1PD23u9ji+jOysbEb4i7fgSXeYINE7eBw0aBMD65Y56HF+AvoW5SOR7MVg7ZUQIKisr4y5gNf1yTk4OTj/9dABiyx3DCV9AZHZ2ZO7xiy++2HDQenOUi0FKlyi7VtasWQO3263qWEaD7YH4zPgyw/EFqA+4b17mCJDjyyxI+Ioykcz5suKujmzgq9babbbjK1rCV/PgykBYqdzR6/Xyv1044UuSJLzyyitITEzEDz/8gG+//RaAGOGrvr5ek9uBDbSHDh3KRedICV9z587Fn3/+iezsbO72AoDjjz8egD7hi917KSkpqgYMJHw1kp2djauvvhoAorZbWjgqKyuF9AtGnb6RzqI0Gm5/8OBB1ZMAJUzY07vhBhB+Z0e2aNGzZ8+QEzW1mCl8/fDDD7qPoyxzDFTOpyx1jKTjkv2Ns7KyQva1gbCC4ysehC/l8awsfClLFbVOhq0ufDEhyMjYnbUVmZmZfru2hsKMckfmFArVnpq9s2NZWRnfwOmSSy7h7yfa8dW8TzzuuOPQpk0b1NfXq3aDGi1zBOLT8cWuDdHCl5pFnpqaGixatAhAYOGLHF9iIeErykRD+DLD8aV38KpV+FI6vkQOmKMtfIVzfAHWEr727t2Luro6uFwuVQ6Jbt264f777wcANDQ0ADAmfLlcLv5daRlcsoH8sGHDuPAViYyv5m4v5XWmLHXUek1rXZEm4auJO+64A5Ik4ZtvvtGdr2Ym55xzDnr16mXYaWW03WdCUKQcX3qFrzZt2iA5ORmyLGP//v2a39eo4wsIL3yJLHMEmvoL0aWOAPDbb79xN6lWQuV7AY1uK5vNhoqKioi2RQcOHADQ9HfSQjSFL+aQ2rZtW0SjDswSvmIh4J7dCy6XS3MEButn1Y5NKisredRBJIUvI0KQlnwvxl/+8hc4nU5s2LBBWJ/LHF+hBBOzd3b87LPP0NDQgH79+qFv376GRZjmBOsTJUnSnPNFwldgoun4+uGHH1BXV4fOnTv79ZlmzXdbOyR8RZlYFr5YZ9LQ0KB7xVmv48vr9eoelAeCWUmjnfEVarLHgqatIHyxQUvPnj1V51H8/e9/539nl8vFQx/1onVVVZZlPtAeNmwYD8iPhOPro48+wrZt25CdnY1bbrnF73c9e/aEzWZDeXm55syyaAhfzz33HE488cSI7jBmhvDVvXt3nHvuuQCAF154QdhxRbF+/Xp4vV5DO7n6fD4+aNb73UVa+NLbT0mSZCjnK5KOLxHB9kCT48vtdhvuD2VZ9pvsu91uLF26VNexwglfygWTSAbcGxkDRVP4ysvLQ15eHmRZjljUQUlJCReD2dhDFEz4Wr16tek77emF9ZG5ubmqNiFQwsYmavtZFvTfqVMn/loziZbwlZWVhfHjxwMQ5/qyQqkjK3O85JJLACBiji9Ae8A9mz8YEbNZW8jEKhHEa6kjm/Ps2LEDXq834HO++OILAI1uL2Vbo5zvGt2BlWiChK8oE6lJRU1NDR8YixK+EhMT+Y2p1zLNhK9QAelKUlJSeMMgqu7Z6/XyBjwWHF+bN2+OeiOoNt9LicvlwmuvvQa73Y4RI0bAZjPW/GgVvvbt24cjR47A4XBg4MCBESt19Hq9fEv6u+++u8U15nK5uACuNeBeq/DFOnUjwte///1vrFixAp9//rnuY2jB4/Hw+0Ok8AU0/j0A4L333rPUTpcej4cPdvWGtQONJXAsh0Wrg4oRycWZ+vp6Xl6k53yN5HzFouMrLS2N94dGyx2rqqr4zmGTJk0CoD/ni4kzwYQvIDo5X0aEL5aHEw3hC4h8wD2bIPfo0YMLrKJg+UI1NTWWdNsCTWNarflegPaxSSTLHAExMSV6hC+gqW0R5faLtvB1+PBhXhZ+8cUXAxAvfIWaH2gRvg4fPmw42B5ocmWR4ys8nTp14gtJgcYFPp+PB9sryxwBfxGQyh3FQcJXlInUpII1Bk6nU3egYSCMdKAVFRW8zEyt48tms/HzF9UQKMNqoyF8+Xw+PmkJJXy1b98eubm58Hq9UQ+41yN8AcDYsWOxZcsWLFiwwPA5MMeW2lJFVrbRv39/JCYm+glfZtqIP/74Y2zbtg1ZWVkt3F4MvQH3ylVpNbBBfHl5ua4cpKKiIj6Yj1SZChOAJEnSnMsTjpEjR+LEE0+E2+3G66+/LvTYRlAO3pggY+Q4aWlpSEhI0HWMSDq+lH9rrcIA0CR8aRULPR4PH5Sa5fhyu93c3SRK+LLZbMJyvtikMCkpiQ/A9eR8lZWVobCwEADQr1+/oM+LhvDFrq9Yc3wBkc/5MqvMEWjcaY8t5BnZPdRMtPatSrSWOkZa+IqW4wtoEoWMbhLBiLbwNW/ePHi9XgwdOpRvmBGpUkegcRdAoHEOGU5oExFsD1i71FG56YIWzNrV0W638+siUF+3atUqFBcXIzU1FaNHj/b7nc1mM21Dt9YMCV9RhglfBw4cMNXFo9zZS6ttOxRGhC9W85ybm6tpRVH0ThfsOE6nEy6XS9cxjAhfyvrtUBN7SZIsk/OlV/gCxK0ga11VVQbbA03CWW1trWmdSnO3V7BSWr0B91pXpbOysngQrZ57Vll2Fynhi7VdWVlZcDgcQo8tSRLuuusuAMCrr74adSclQzlAN+L4ElEiyoSgI0eOmL7qqNzkQ20JtRK9wtf+/fvh9Xrhcrl4u6CHUMIX2+kwMzPTcJm3EtaWGs35Uk5kx44dC6DxHtfaNm7cuBEA0LFjx5DtvDLgPlKwiageNyEJX2Kxes5XpBxfsixz4YuJGGYTTeGLCS6RFL7MDLdvXuaofL9IlDpmZmbyRYQ//vgj5HHYPW0k3wuwtvClNBJowSzHFxA654vt5njmmWcGnH8arSYiWkLCV5TJycnhk2EjK/vhEL2jI8OI8KU134shuiFQBtvrFQWNnBObsCQlJYUV3ljWhpHcH6PIsmxI+BKFVuFLGWwPNH7fbGJmVrnjJ598gq1btyIrKwu33npr0OcpA+61oLXUUZIkQ+WOyutuw4YNQnP2gmFGvpeSCy64AJ06dcKRI0fw/vvvm/IeWlEO0EU4voyUt2dkZPDXm+360htsz2AZX1pLHdnn6tKli6ESbCZ8HTx4kJcNMpRljiIXn0Q7vtq2bYtOnTqhe/fu8Hq9+PnnnzUdJ1y+FyPWSh2jLXyxgPsNGzbwDWLMpLULX0YcX1oyvgoLC1FUVOTngjMb9plai/BlVrh9YWEhfvnlFwBNO1YCTe1LaWmpLvdRc8L1i2rLHUUE2wPmCF9GM74SEhL4taXVaed2u/kCjxnCV6i+TpnvFQjRRg+ChK+oI0lSRModRQfbM6IhfIluCIzu6Kh8rRHhS00ZlxUcX4cOHcKxY8cgSRJ69OgRtfNgg0s1pY4+n6+F8AXA1JwvpdvrrrvuCrlxgtFSRy2r0kYC7pXCV0NDQ0RKbs0S7RkOhwO33347AOD5558XMlA1irI93bNnj+5SXFHtfqTKHY04cgD9ji8R+V5AY3/ocrkgyzLfQZAhOtieYYbwBYC7vrTmfKkVvpjja/fu3RER0AExpY5GJ+x6ha+uXbsiLS3Nr2TWLA4dOoT9+/cbzgIKBeuH161bp6vs3myMOECUi3Lh2m4mVvTv31+320Ur7B6PRsaX6KiSaJY6fvLJJ5BlGaeccoqfi5e1L16vl9/vRmgNwpdRxxegv8SUXRcOh0N4niEQ3PG1b98+rFu3DjabDRMnTgz4WjZvIMeXOEj4sgCRmFTEk/BlluNL746OynOqra3VvEuRsrwnHKzD2rhxY8QmC81hg+7jjjsu5GDDbFhJkhrH186dO1FeXo7ExET07duXP26m8PXpp59iy5YtyMzMDOn2ApomgYcOHeLXgxqiJXyxazUSq/VmO74A4LrrrkNaWhq2bNmChQsXmvY+alEO0Gtra3VPUER9d5ESvowIE0CT8HXgwIEWjqtQiNjREWhcyApW7siEL1H5Xgx2L4oqdWTXyrhx4wBoz/lSK3zl5uYiIyMDsixjx44dWk9XF7Fc6miz2bjry+xyRzZB7t27t6EFwVB06dIFOTk5EVtA0YqevpXBxsUNDQ1h70tWnhapfC+gSQiqqqrSPY7UK3yx60mU44sJJmodXyLzXAOVOQKNGxaxzynCZaZW+Prjjz+Cfj5RwfZA/AlfSpFbpBubEczxxULtR4wYEXSMRhlf4iHhywKQ4yu6ji92HBGOL0B7h67F8dWxY0fk5OTA4/HwLJVIY4UyR0BbqSMTaAYNGsQzroAm4UttQL5afD6fn9sr3CQnLS2NrxhqcX3pWZXWW+pYUlLCJ/NXXnklgMgEE0dC+EpPT8f1118PoNH1FW2ar0zrzfkS1e5HahMWo6WOubm5SExMhM/n4wHrahDl+AKC53yJ3tGRYZbj67TTTgPQKNipdUrIssz7pXDClyRJES93jOVSRyByOzuaXeYINP79rVzuaMTxlZiYyO/LcOOTSAfbA43XHhsH6XVBiSh1FCFCMcdXKMGEnaPH4zHcTjJ27dqFP/74AzabDRdeeGGL34sMuA/XLw4YMACJiYkoKyvD9u3bAz5HGWxvVMy2YqkjIEb4MgPWz+3fv9/vO2P5Xuecc07Q11Kpo3g0CV+vv/46BgwYgPT0dKSnp2PEiBH49ttvgz5/yZIlkCSpxb9IhpnGAq1R+PL5fNz2aRXHl5HOwOVy8YGE1vPSInxZIeDeasJXSUlJWHdH82B7BnONiXZ8ffrpp9i8eTMyMzNx2223qXqN1oD7uro63hlGwvHFXAbdu3fnbpB4cXwBwG233Qa73Y4ffvjB9IllOJpPRvTmfMVqqaPe85UkSVfOlyjHFxBY+Dp06BAOHz4MSZJC7nSoB7OEr7Zt23KRbvHixaqOsX//fpSXl8PhcHAXaygiHXBvRFhlE7L6+nrNrm4lIoSvSDm+zBS+lMe3ovBlxPEFqMv58ng8XGSMpPAlSZKhckdZlg0LXz6fT0jVgppSR6UDS1S540cffQSgsSQ80DUiMuA+XLvldDp5/m+wckdRZY5A/Dq+RO/oyMjJyeF/O+Zurqys5DECwfK9AAq3NwNNwleHDh3w1FNPYeXKlVi5ciXGjh2Lc889F5s2bQr5um3btqGoqIj/i2YukBWJhPCl3NVRJHqFr8LCQtTW1sLhcGheZbdixpfy9XqFL7WDcRK+GsnOzua7/IUTcQLlewHmlDoq3V533nmn6gmO1oB79pkTEhI0TaLYIE3rPcvKHIcMGcInLFu2bBFWshAMs9qu5nTu3Jmv3L7wwgumvlc4RDu+Yq3UUa/jC9CX82W244uVcvXo0UN4jg9bMBEtfAHac75YmWOvXr2QkJAQ9vmRdHwp3R562hI2YQf0T/hkWRbm+BJZstWcSDi+AOsG3Hu9Xt7v6HWBqHGkb9q0CTU1NUhPT1clFIvESO5VRUUF32BBq1igbP+Mjh1kWVYlfAHid3YMVubIEOX4qq+v5+1NqMXxcDlfJHwFx2zHF9Cyr/v+++9RX1+Pbt26hbz3yfElHk3C19lnn42JEyeiZ8+e6NmzJ5588kmkpqZi+fLlIV+Xm5uLvLw8/k/PNuXxDBO+du/eDa/Xa8p7WM3xxW7+bt26+ZWeqUG0As4aFCMZX4Bx4UuN4wuI/s6OVhG+bDabqsGlx+Ph31XzgbwZwte8efOwadMmTW4vQHvAvXJFWksugV7Hl1L4ys/PR/v27eHz+Ux3H0TK8QUAd999NwDgww8/NG2nTzWwwTlbJNLr+BIlGrI+as+ePab1UUB0hK+qqir+fZvl+DKrzBFocnyJyvhSTmS15nypzfdiRNLxpfx+1Pa1ShISEvjYVe+Er66ujgsGeoSvPn36wOl04tixY7rF8HAcPHgQBw8e9MsUMwsmfEViAUULLAtKkiTd/Q7rZ0ONTZhIMWzYMEO7yerBiPDFXpOamorExERNr7Xb7VzcMPo3V26KEE74Ermz4+bNm7F+/Xo4nU6cd955AZ8jyvHF2i1JkkK2GeGELyZmixS+6urqhG0GZIVwezOFr+YB96zM8eyzzw45fqdwe/Hobmm9Xi/mzp2L6upqjBgxIuRzBw8ejPz8fIwbN06VZZ5tLar8F8906NABDocD9fX1pk22zNoZjTUUpaWlmrbY1pvvBcSv40vtYJx1XBs2bNAU4CyCiooKvltZtIUvQN2q6tatW1FTU4PU1NQW15vojC9ZlvH4448DAO644w5NO8RoLXXUW4phVPhiroNIrdZHUvgaNmwYRo0ahYaGBrz88sumv18w2EDsxBNPBBD9jK/27dvD6XSioaFBU3aWVkScr9ZSRyYqZmVl6RIjmhPK8SV6R0fAvFJHADj11FNht9uxY8eOFpllgdAqfClXwc10MAFNompGRgZ3CmtBkiTDTgfm9pIkyc9BppaEhAReKmvWggNzhvTt29f0XQaVCyjRWsgLBFvIzcnJ0XWtAOrGJkykYO18JGFjdyPCl97SMGXOlxGY2wtQL3yJcHyxMscJEyYEXaQRJXyxdiszMzOkaYQJX2vXrvX7XgCxwfaAvzjFBCsjyLIc1xlfgH9f5/V68fXXXwMIne8FULi9GWgWvjZs2IDU1FS4XC7ccMMNWLBgAZ+wNSc/Px9vvvkm5s2bh/nz56NXr14YN24cfv7555DvMX36dGRkZPB/ym1i4xGHw8FXqc0qdzTL8ZWdnc1XqrQ08EaEL9ENQawJX126dEFWVhbq6+sjHnDPVubz8vJM2fZXK2oGl0yYOeGEE1oMHJQZXyImXqWlpXzyp8XtBTQJiXv37lU1INTbWesRvioqKnhoanPhy+yA+0gKX0CT62vmzJlRcyE0F76MZnwZ/e7sdjvvo8wsd4yG40tkvhfgL3yxNiUSji8zhK/09HR+n6spd9QqfHXv3h02mw0VFRW6dpnVgogxEJuU6W0XmPCVnp6u2+FjdsB9pMocGVYsdzSa7wWoy/iKRrA9w0jGl1HhS1TVBhN47HZ72MoRUcKXLMthyxwBcaWOavvEzp07Izc3Fx6Pp4UozsTsnj17CtmlVSkyiih3rK+v586xeC11VDq+fv/9dxw5cgQZGRk45ZRTQr6OHF/i0dzz9urVC2vXrsXy5ctx4403YurUqUEzaXr16oXrr78eQ4YMwYgRI/Daa69h0qRJeO6550K+x7Rp01BeXs7/7d+/X+tpxhxm53yZJXzZ7XY+qdLSgYpwfLXWUsdoBtxbpcyRwQaXoRxbwYLtgSbhq66uTshuP2yynZeXp7mcJicnhw/O1GTeGHV8lZSUqA5pZpOsjh078nOMVDBxpIWvs88+Gz169MCxY8cwa9asiLynEq/Xy9trJnzt3btXc0mBLMtC89EiuQmLCOFr2bJluOiii/Duu++G7JuYqChK+GILdVVVVTh27Bjq6+t5u2mG40tExldtbS2fwDSfzLKcr3Dljg0NDXxhRK3w5XK5eK6a2eWOIoUvo44vI85CswPuoyV8RWKHYLWImAiHK3WsqKjgc6doCl/x4PgK5/YCxAlfa9euxZ9//onExMSQbh3Rjq9wfaIkSUHLHUVvVmGz2bhAJUL4UrrG4lX4Ujq+WJnjWWedFVawJceXeDQLXwkJCejevTuGDh2K6dOnY+DAgXjxxRdVv3748OFBt1tluFwuvnMk+xfvmDmpaGho4AMuMwKi9YRlk+OrCa3CFxC9nC+rCV9MuArl+AoWbA80bjvOBhQiyh2NhmQz96yagHu9wldOTg5sNpvfzkzhUOZ7MdggaseOHYbzhYJRX1/P7/NICV82m427vl544QVDO7jpobS0lItcAwcOhN1uR319vebrs6qqipefi2j3IxFwzwb5Rs534MCB6NGjB+rr6/HJJ5/gqquuQl5eHk488UQ8+uijWLlypZ+IyD6PiGB7oHESxiZZ+/btw7Zt29DQ0ID09HTuBhOJiIwv1g44nc4WogzL+frxxx9DumLZ50xLS+PlpmqIVMC9CDdhvAtfsiwLzQJSgxUdX2wsK8LxFWxssmrVKsiyjE6dOvHnRpJ4EL6YYKJG+BIVbs/cXpMnTw45Z4i04wsInvMlMtieITLgnh3D6XRqznxWYtVdHYHGOb4kSSgvL8d7770HIPRujgwKtxeP4TRFWZb9AgbDsWbNGj5ZJZowU/hiDackSbpCXcOhNeC+pqaG54VYwfEVbeGL/X20/G2i5fhiq/KR3oEoGOEGl/X19bzMKNhql8iAe+b4Yq4TrWgJuNcrfCldmmrLiwIJX9nZ2bzdMus6ZAMYm80W0dLaK6+8Em3atMGePXswf/78iL0v0DQwz8zMRFJSEncQac35Yt9dUlKSkKwesx1fbrebD4CNiBPJycnYsmULli1bhgceeABDhgyBLMtYsWIFHnnkEQwbNgwFBQW4+uqr8emnn/JdqUU5vgD/ckdlmaOWTSjUoix11FuurXRVNj/HESNGwOVy4eDBgyHFKVbm2K9fP02fk40ByPGlDnYdHThwQNgOdYzCwkIcPnwYDofDlLLcQLA+ZefOnUJ3iTMC6xeNOEDClTpGs8wR0L8xFWAd4Ys5vtT0byLC7dWWOQKRd3wBsSt8iQi2B/QJX7IsR8TxlZSUxBeEDh48CLvdjrPOOivs60Rv5kZoFL7uu+8+/PLLL9izZw82bNiA+++/H0uWLMGUKVMANJYoXnnllfz5M2bMwGeffYbt27dj06ZNmDZtGubNm4dbbrlF7KeIA8xcTWeNQLhwRL1o7UCZ4y8rK0uXi8Msx1eslDoCTR3Y+vXrNW0qYBSrOb7CCV9sA4Ds7OygE1tlzpdRjDq+IiF8KV+j9p4NJHwB5pc7Kkv1IrnrVVJSEu+nnnvuOdODt5U0n1Swa0lrzpfIMkfAfMcXG+DbbDbDIfN2ux3Dhw/H448/jlWrVuHAgQN46623cN555yE1NRWHDh3C7Nmz8X//9388u0qU4wvwD9g3M9geaBK+vF6v7klIqIlsUlISRo4cCSB0zpfWfC8GW0SJlOPLyP3AJuzRFL7S0tLQvXt3AOJdX8zt1a9fP1UuGhFkZ2fzSXQ0d9JVItLxdfjw4YA74UZb+IoHx1ekSx2XL1+Offv2ITU1FRMnTgz53GgIX8OGDYMkSdizZw+/hg8fPoz9+/cLC7ZnWFn4qq2tbRHwH4zq6mrU1dUBMFf4AppyvgBg1KhRquZ85PgSj6aZxKFDh3DFFVfwkPrff/8dCxcuxPjx4wE0lgopd/6pr6/HPffcgwEDBmDUqFH49ddf8fXXX+P8888X+yniADNX083a0ZHBGgu17hFlmaOeFXCzMr6i4fjy+Xx8MKxF+OratSsyMjLgdrtVlcWJoL6+nl+fVhG+mGgVrAxMme8V7FqzkuNLS6mjkVUqLQH3NTU1XIhrLnyZXaYS6XwvJTfddBMSExOxYsUK/PLLLxF73+aTCq1h7QzRuY6REr6ysrKEi5wFBQW49tprMX/+fJSUlGDRokW48847udsoOTlZqDCldHwx4cssB01ycjIvD9Fb7hhuIqsm50uv8BWpUkcR+XFWcHwB5gXcRzrfC2isRGjfvj0A8B2jo40Ix1fbtm0hSRJ8Pl8L8UOWZRK+EHvCF3N7/eUvfwn7nkr3kZGFMy0L4xkZGXxszq4v0cH2DCsKX+np6XwXVrWuLzaOTk5ONrSjpBqUFU5qyhwBCrc3A02jy7fffht79uyB2+3G4cOHsWjRIi56AcDs2bOxZMkS/vM//vEP7NixA7W1tSgtLcUvv/wSViVvrbBJRVlZmfC8HLOC7RlaHV9G8r0Af8eXCCdGNEsdy8vL+WfQInxJksRFiEiVO27fvh1erxdpaWlcLIo2SsdXoGtBzUCefRYrZHyxQcvOnTtRX18f8rkiHF9qhK/169fD5/OhXbt2LcrUzQ4mNlu0D0Xbtm1x1VVXAUDYDVlEIsrxZZbwVVpaKmQjiOaIyGBSQ0JCAsaNG4fnn38eW7duxc6dO7F161ZD7o7mBCt1NANJkgzv7BhuIstyvhYvXhx0kwWjjq/du3fzlXcziJdSR8C8nK9oCF8AuPBVWFgY0fcNhgjHl8Ph4P1Wc0d6YWEhioqKYLfbWywmRQo2bq+srNR837VG4cvr9eLjjz8GEL7MEWhqZ7xeL7/v9aC1X2xe7mhGmSNgTsaXUeFJkiT+PWkVvsx2ewH6hC/lvDKSlQfxTORqR4iQpKSk8Em8aNeXVYUvvTlRTAH3+Xyq7ayhiKbwxUTO5ORkuFwuTe8X6ZwvZZmjGVk1emAD07q6uoBWYOZEChRszxBV6ijLsmHHV0FBAdLT0+H1ekNuAtLQ0MDva7OFL2WZY/O/++DBgyFJEvbv36/a8amFaDq+AODOO++EJEn48ssvTc8gYohyfIn+7lJTU3lbb2ZJvln9VDC6du3Kc9REwYSvlStXori4GJIkoV+/fkLfQ4nZwtfQoUORlpaGsrKygC6jiooK7N27F4B24Ss3NxcZGRmQZRk7duzQduIaEFHqyCZmeifsVha+lMH2kRa+OnToACC+HF9A8JwvJkr0799fSP6iHjIyMrhTVKsYZFT4EpVbpEf4Uu5gq4Wff/4ZxcXFyMrK8jN8BCMxMZG3F0YC7luD8CXK8QVoz/mKpPDFRO7+/fujR48eql6jnO8qd78k9EPCl4Uwq5TEqsKXXsdXSkoKn4AbrXuWZVl4xpeWQbGefC9GpB1fVsv3Aho7SvZ3a+7Yqqmp4cHVahxfRoWvw4cPo7a2FpIk6d69TZIk/v2GKndkA0+bzabrvtYrfDUnLS2Nn68Z5Y7RFr569uyJc889FwDw/PPPR+Q9rer4Aswtd4yU4ysSsPufLWJ169aNuxzMgPUfRoWvYPeZw+HA6NGjAQTO+dq4cSOAxrZU699PkqSIBNzHU6njoEGDAAB//vmnYdcMY8+ePSgtLUVCQoKpIm0grFTqqAy7NuoCDZZBGu0yR6DxvtO702EsOr5SU1ORkJAAQJ/ri5U5XnDBBfw44RCR86VX+Prjjz/g8/n4/EC0mM3aQhFijEjhi33nWoUvM3d0ZIwYMQJffPEFFixYoPo1ycnJPPqBcr7EQMKXhTAr58tKwpcsy4aFL0mShK0YVVdXc/toNB1feoQv1pGtXbs2bFmcCKwofAFNjq3mg8u1a9fC6/UiLy+PD6wDIUr4Yo6c9u3bqx4YBUJNwL2ys9aTh6Qlly+U8AU0XYdmlDuKDmjXwz333AMAeO+990xxtTWHDcrZ34g5vvbv3w+Px6P6OGa0+5HYfTiehC+GWcH2DOb4MivjCwid86W3zJERiYD7eCp1ZGXnsizzDDmjsPZ7wIABmt3nRrGS8KUs/TM6GWbCmRWFL0Bf+V91dTUXnKItfDHBRI3wJUmS7p0dGxoa8OmnnwIALr74YtWvi4bw1a9fPyQnJ6OiogK//vqrKcH2QJNIZaVSR8Daji+gscSRjaPUoJzvkvAlBhK+LIRZkwqzJ49K4StcDXJxcTEqKyths9k03fzNEbXTBROpbDab4dWGSAtf3bt3R3Z2Ntxut7DBbyisKnwFW1VVE2wP+Gd8GamhN5rvxVATcG8k30v5unBCjtvt5m6OYMKXmQH30XZ8AcDJJ5+M4cOHw+1249VXXzX9/ZqLEAUFBXA6nfB4PJomhmZ8d5HYfTiaIqco2rZt6ycemJXvxTC71BFoyvn65ZdfWiy0MOFL7+eMRMC9CGHVKsIXIL7cMVpljoC1hC82EU5JSTE8EQ80NvF4PNyFE23hS2u1BtDUVihL+bQSDccXoD/n64cffkBpaSlyc3MxZswY1a/TKsIEQmu75XA4eFnja6+9BkB8sD0QP6WOzRcarYgoowfRCAlfFsJsx5fZuzqqqZ1nA9vjjjvO0KqiqIZAuaOj0dwq1plHSviSJIkPnJYvX6759Vrw+Xz8bxcrwhcbyIfK91K+3u12G9pYwmi+F0ON40uU8BVuwLtp0yY0NDQgKysLnTt3DvgcpfAlOnzTCsKXJEnc9fXqq6+anrPQ3Hpvs9n4d68l54tKHaOHzWbzyw2LB+GrX79+aNOmDaqrq/HHH3/4/U6U48usUke3283HJkbuB9bHW0n4ErWzIwlfjRjtW5UEyvjatGkTampqkJ6erjvnVhR6hCBlW6F3zCxa+FIrmOgVvj777DMAwPnnn893DVSDUceX1+vlbbqWfpHNC+bNmwdAfL4XYH3hS+13HmnHlx5EGT0YCxcuxLRp0/Dtt98KOV6sQcKXhYjVUseUlBS+4hJuIm20zJEh2vElYjVEjxjHJnt6hC8AGD58OADzha+9e/eitrYWCQkJhh1NomGDy+YZX2qC7QHA5XLxe8NIuaMoxxcTvrZt2wav1xvwOSKFr2C7tAGhg+0ZAwcOhMPhwJEjR7B//35d5xMMKwhfQOP25V27dkVpaSlmz55t6nsFEiH05HzFWqmjiAwmK6EsdzS71FFUxlco4ctms/FyR2XOlyzLhoUvpePLjJ2r2LVlt9sNiU7x6vgyMwtIDUz4KioqCtrnRQqRE+FAi3KszHHYsGG6YgpEYlT40kssOb5kWcbXX38NADjnnHM0nZ9Rx5feXd+Z8MWiEVqj8GXVUkc9sPmuKMfXjz/+iKeeegqLFi0ScrxYg4QvC8FW0wsLC+F2u4Ud12zhS5Ik1ZZpUcKXKMdXtIUvI44voEn4YoMps2Ar8T169NC04hUJAmV8VVRU8GtNzUBeRM6XKMdXly5dkJiYCLfbHVToMCp8sfvV6/Vy8TUQ4fK9gMaSBzbhFV3uaBXhy26346677gLQGHJv1uTM5/Pxz6ycWOjZ2dHMUsd9+/ahoaFB2HEBMbvuWQkmfKWlpQV1S4rCSMZXQ0MDF8zCTWYD5XwdPHgQZWVlsNvtut3A3bt3h81mQ0VFRQvnrgiUC0xGnN1WFL42bNhg+F7cuXMnysvLkZiYyEvtI0leXh7sdju8Xm9EchRDIdLxFSjjyyr5XkDTOKC1CF96wvzXr1+PwsJCJCUlaSpzVL6fXscXa89TUlI05cY2v7asLny1powvPYjO+DI674x1SPiyELm5uUhJSYEsy5q3rg9FJLJTIi18iXJ8sdcb3dERaGqc6uvrVYfNG22ATjzxRADAjh07DAVohsOq+V5A4FVVtnrduXNnVQM0Zc6XXkQ5vux2O78/gpU7Gu2snU4nd9aEmmioEb4A83K+rCJ8AcBVV12F7Oxs7Ny5E59//rkp73Hs2DEuqlnR8ZWfnw+XywWv1yvc3RdPpY5Ak/DVv39/050dRkod2T0mSVLY757lfC1btoyv0jO3V8+ePXXHF7hcLn6Nm5HzJepeYBMzvRN2kcJXly5dkJ6ejvr6+pBl8WpgZY6DBg2C0+k0fG5asdvtvB+PdrljpBxfVhC+WB+jJ+PLiPAlauFar+NLy1j5q6++AgCcfvrpqt+HYVT40tsndujQgS8IAxAebA/En+MrErs66kV0qSMJX4RlkCRJeCmJLMtxKXxZ2fGlPG44WAOkd7KXmZnJcyLMdH3FmvClDLZXAxsk6HV8+Xw+7N27F4BxxxcQPuBexKp0uIB7j8fDN00IJ3yZsbOjMjPQCsJXSkoKbrrpJgDAc889Z8p7sElFWlqan4ig1fFVW1vLB5Mi232bzcZdX7FWkh9pxo0bB5fLhQsuuMD09zJS6siuuZycHNjt9pDP7datGzp27IiGhgb8+uuvAIznezHMDLgXLXzpmezV1dXxBTERwpfNZsOgQYMAGC93jGa+F8MqOV9mZHyVlpaivr4eFRUVvE9ni5bRhEodw8PKHCdPnqzx7IyXOuoVvpT5v7169RKysN+ceBC+fD5fqwy3J+GLsBSiha/y8nLuIIi28KUs3bKK40uk8OVwOJCYmOh33HCIaIAiUe4YC8KX0q2lNtieYbTUsaioCPX19bDb7ejQoYOuYygJF3AvYnDO7tlgwte2bdtQW1uL1NRUdO/ePeSx2Pe8cuXKkJlhWmADF4fDYcrATQ+33HILEhISsGzZMixdulT48YNNKrQ6vsz87swKuI83x9epp56KiooKXiJrJkZKHbVMZCVJ4q4vlvMlSvgyM+Be1LVlZLLH3F7K7emNIirgnoSvJkQ6vrKzs7mYfPjwYaxcuRKyLKNTp0583BJNrCB8Gcn0M1v4OnLkCM/PnTRpkubzi5bjCwBGjx4NABg5cqSu9w5HPJQ6BnPYWw1yfImFhC+LIVr4Yjd/SkoKF2XMQI3wtXPnTvh8PqSlpRnu9EU7vkRNDrWel4gGyOydHWVZtrTwxdxaR48e5VknaoPtGUaFL+bE6dixo5AMtEgIX+EcX6zMcfDgwWFLtfr27YvExESUl5djx44dus9JibLM0eiOq6Jo164drrzySgDmuL6CrT4yx9eBAwdUlVErHS6ivzszhK+6ujq+6hsvwhcATbksRhBR6qh24N8854scX+pgwldaWpqw0lcRAfder5e39SR8NY1hRTi+bDabX84X2w3VCmWOgPpKDSUihS+v12soz5j1GWYJX99++y1kWcagQYP49amFaDm+AODmm2/G22+/jaeeekrXe4fD6o4vpagVDHbdZ2ZmRqyv1gM5vsRCwpfFED2piFT5iJoOlK3k9urVy/BkTHTGl6gV2GgIX0rHlyi3jZIjR46gtLQUkiQZduqZASvRkWUZR44cwdGjR7kQFa5Ej2E040tUvheDlTpu2bKlxYqo0p4tQvgKds8qha9wOJ1OXnYjqtzRSvleSpiD57PPPsP27duFHjvYpKJdu3ZITEyEz+dTla1lZrtvxs6ObIBvdNe91ooR4UvrRJYJX6tXr8bRo0e5OC9K+DLD8SXqfmATdiPCl8jrW+n40uuc+fPPP1FVVYXk5GTuuosGTFgoLCyM2jkATQtBokqflFEMVsr3Apru+crKStUClAjhS+nsMVLuaLbji+V76SlzBPwdX3ruTyPCl9PpxDXXXGOak4mJVEy0MoJI4Yt9V7Ish3VAx0KwPUCOL9GQ8GUxzHJ8WUH4EpXvBYjb5UJkqaPyOJEUvvr164fk5GS/nQxFwiY2Xbp00RzuGQnsdju//oqLi7nw0rNnTz4hDIfRjC9ROzoyunfvDrvdjsrKyhYr4KWlpULs2WodX2rFQ9EB96ztsprw1adPH0yePBmyLOOFF14QeuxgkwpJkjTlfJn53Znh+BK1615rhfUfFRUVmhc/tE5k27dvj169esHn8+Gtt96C2+1GSkqK4baPiS579uxBXV2doWM1R3SpY319PTwej6bXmiF89enTBwkJCSgvL9e08YUS1l8OGTIkbMabmcSj4wuwtvCVmZnJHepayv8AY2MPu93Ox5IihC+1ggnrD8vLy8M6pxsaGvC///0PgH7hi827PB6PrrmKlcv/rer4cjqdXCgK57SLNeFLhOPL6/XyvoiEL8ISMOFr165dQtw78Sp8iWoIoil8eb1evkJvpAFyOBy8RMGMckcrlzkymHBVVFSkOdge8C911LMyJ9rxlZCQwHO1mpc7MqEqOzvb0A5coYQvn8/Hy2eiJXxZ1fEFAPfccw8A4J133tGUjxKOUDsMacn5Yt+dGe2+MtzeSD6LEtZPWXGAHwswMUWWZT6oVYueiSzL+XrllVcANC6+GC3fy83NRUZGBmRZFlYuzRBd6ghon/CZIXw5nU7069cPgP5yRyvkewHg2ZjRFL7q6+v5YqSoyTDrZ1euXImioiLY7XbVfarZSJKkK/cKMJ6JJCLgXqvjKzs7m7dT4USRX3/9FRUVFWjbtq3qyIzmJCUlcTFHT7mjckHIalg14wtQX2IaCzs6AuKMHgD8xgdWvK4iAQlfFqNTp06w2+2oq6vTXXalJFLCV7iyKcCaji/2+mhkfIlsgFi5Y2sVvpSrqlqD7ZWvb2ho0DVAEe34AoLv7Chq16lQwtfOnTtRWVmJxMRE1X93NnFas2aNZjdEIKwsfJ166qkYOnQo6urq8Prrrws7bqhJhR7HlxntPhPgKioq+MDcKOw48bKjY6RxuVx88qe13FHPRJaVOzKRwmiZI9A4CTcr4F7U/ZCQkMBdUVon7GYIX4DxnC+rCF9WcHyxe8HhcAibFLKxxRdffAEAGDBggBBniyjYfa8m58vtdvOxrVGxQERukVbhy2az8TYgnNDHyhwnTpxoSNQ3EnBvdNd3M1EKX0YXwEQ6vgDtwlesOL5ECF/smkpJSTG0cB7LkPBlMZxOJzp16gRATLmjmSv/SljDceTIkYCBgrIsk+OrGawBSk5ONhysyKzzZuzsyCYh0cz/CIdS+NIabA80TmjYQE6P4Cza8QUED7iPhPDFyhwHDBigOqy/V69eSEtLQ01NTdBQfi1Equ3SgyRJ3PX1yiuv8AG4UUKJEFocX2YKX8nJydxhKarc0colHbGC3pwvPcLXmDFj/EpSRQhfgHkB96KuL0mSdDsdzBa+9Ozs6PF4uGBmFeGrqqpKWJaNVlhf2LZtW2EbEDTfddoqZY4MLY4v9hyn02n4Oo6G4wtQ/3m//vprAPrLHBlGAu6t3C+ydtDr9aracCcU0RK+gm0mZDVEhtu39nwvgIQvS6IsdzRKpHJy2PF9Pl9AF8DRo0f5DdejRw/D7xcPGV8iGyDm+NqwYYOhgUQgYsnxtWrVKhQVFcFms/GwdbXozfnyeDw8cDwSji9RGSSssz906FCLFTut+V5A42rqCSecAEBMwL2VHV8AcMEFF6Bz5844cuQI3nvvPSHHFOX4Mvu7M2sTFisO8GMF1o/oFb60XCs5OTl+7ato4cuqji9Af4mPFR1fW7ZsQW1tLdLS0oSMy4yQkpLCv5toub5E53sBaLGDeTwIXyJ2Wray8LV9+3Zs27YNDocDZ5xxhu7zA4w5vmJB+AKMlztGu9TR6sKXGY4vEr4ISyEy4D5SpY5Op5M3zoEs02wFt1OnTkJUfVGOr2iWOoq0MRcUFKBjx47w+XzCdtUDGgclTNSxsvDFRKvvvvsOANC3b1/Nnagy50sLBw4cgMfjgdPp5McQQTjHl9HOmg3u6+vrW+QC6RG+gCbXgIicL6sLXw6HA7fddhsA4KOPPhJyzFhwfAHiN2GhUkfjMMdXuJ2smqM3s4flfAHihC/mKhbp+JJlOa6FrwEDBkCSJBw8eFBVuZoSNlY44YQThDmcjBDtckfROzoCLUW0E088UdixRaAmn5chKt8LsLbwxdxep556quG5ARu/xJvjy+l08lI5I8KXLMtU6hgGkeH2JHyR8GVJYlH4AkJ3oGwgK6pcTikwGakvjxfHF2BOuSNbec/NzbVk58tgq6qsA9ZTtqFX+GIOnM6dOwudPDD3w9GjR/0GaaJKHZOSkvj1qrxnZVnWLXyJDLi3uvAFNE1i9u7da/hYsiyrcnwVFRWF3fXO7HZftOPLygP8WEFPqaPP5+PXil7hq3379sLuUWWpo6iNE6qrq9HQ0ABAzPVlNeErNTWVu7W0ur6sku/FYMJXYWFhVN7fbMdXenq65SIj9Di+rCB8KQUTLcIXa6tCfV6W72W0zBFo6oO1Or5kWbZ8vygi4N7tdvO2noSvwCjnlUY3vSPhi4QvSxLPwpeIfC+gSQH3+Xy889NDPAlfZgTcx0KZI9CynEDPLjxM+NKa8WVGvhfQOKhgYofS9SVK+FIeQ5nztW/fPpSWlsLhcPAdw9TCJlDr1q2D2+02dG6xIHx17NgRQONEzeiApKKigk/QA00scnJy+GQhnNAWq6WO5PjSj55Sx9LSUn7dar1WJkyYgKeeegqzZs3S9LpQdO/eHTabDRUVFSguLhZyTHZtuVwuIRMrdg9aRfgC9JU7Hjx4EPPnzwdgHeEr2js7muH4Uo5Nhg0bZglnnZJYFb6U4wst9zU792BCVEVFBX7++WcAYoQvvaWOogV7MxAhfCnnb9ESvqy+q6PSdWi0rJSELxK+LIlyu3ijxKvwlZyczAcQeuueZVnmAlU0Sx3NEL5ErZbHqvClZyCvN+PLjB0dGYHKHc0Wvpjbq1+/fnC5XJqOd9xxxyEnJwcNDQ3YsGGD7vOSZTkmhK+CggJIkoT6+nrV28EHg70+JSUl4ABQkiTVOV+xWupo1QF+LKCn1JFdcxkZGZo3WJEkCffee6/hDBwlLpeLLyCIKndU5scZzSUCrOf4ArQH3NfW1uIvf/kLiouL0adPHyETfBFEu9TRDAdIeno670etlu8F+G9MFQ4rCV/KDWVEljp+//33aGhoQM+ePYXk3ukNt2d9YkJCgqV2AVUiQvhir01ISFC9kVI41HznDQ0N/Du2uuMrMTGR7yZsNOeLhC8SviwJm1SUlJS0yN7RSiR3Rouk8CVJkuGdLurq6uDxeADEh+NryJAhcDgcKC4u5rlcRolF4cvpdGLAgAGaj6G31NEsxxfQ9L0rA+5FDs5DCV9ayxyBxvtSRM5XTU0NL+ezsvDldDr5tWf0nlMzqVCT89XQ0MD7DbNLHffv3294RyeAhC8R6Cl1FDmRFYXogHvR+XFssqd1wm4Vx5csy7jmmmuwYsUKZGdn48svvxQWKm2UaAtfIheVGJIk8bGFFYUvdu9HOuPL6PidCV92u51nTakhnPDFyhwnTZqk67yao9fxxdqtrKwsIYK9GTBBzkjVjeh8L0Cd8MV+Z7PZLD/ukCRJWMA9CV8kfFmStLQ03jgbKSWpra3lnUMkJo/BhK+GhgbuDBAlfAHGd7pQdrhs9ckoWjpzZccmgqSkJAwcOBCAuHLHWBG+UlNT+d9w4MCBmp1KgPGMLzMcX2xnR/Z3kGU5Yo4vPcIX0OS2M7LJAhskulwuy0zKgsHKHY0KX2ps9+waCyV8sXZFkiTTBjft2rVDcnIyZFkWkm9GpY7GiRfhS3TAvehry4qOL7bD5vbt28MKck8++STmzp0Lh8OBefPm8YVWKxBt4cuszJ/HH38c1157Lc4880yhxxVBrJY66gm2B0J/Xp/Ph2+++QaAmDJHQH+4vcjNr8xCZKljpIUvdq+3adOGu6msjFGhmEHCFwlflkVEKQm76R0OhzBHUyiCCV+7d++Gx+NBcnIyH9iIwGhDwF6XkpIiLHchmo4vQGzOV319PXbs2AHA+sIX0OT60ptXwoSv4uJiTXlNkXB8MeGroqKCZ1uIEL7YPStS+BIRcK8sc7TqaidDlPClxfEVqtSRtftZWVmmDegkSRJakk+OL+PoyfiyovClDLgXgehry4rCV25uLgoKCiDLMtatWxf0efPmzcODDz4IAHjttdcwZswY4edihGgLX2Y4vgBgypQpeOuttzSXE0cCdu8rxxbBiAfhK1S4/cqVK3H48GGkp6fjlFNO0XVezdEbbh8LfaLIUkeRC5xK4StY7EusBNszyPElDhK+LIpI4SsnJycik8dgwhcbwPbs2VNosKfRhoC9TlS+FxB94Uvkzo47duyA1+tFamqqUMHSLJgAoXe78Hbt2kGSJDQ0NKhenauvr+eDdDMzvgoLC1FRUcEH5mlpaZoHfIFo7vgqKipCcXExbDabrnJRoEn42rRpk+4BUSzkezGUAfdGUDOpUOP4ipR7SlTAvdKZbOVBvtUxkvFlJeGLOb5ElTq2BscXEL7ccc2aNbjyyisBALfffjuuv/56U87DCGyccejQIR7sHSl8Ph+/H2JlMiyCzMxMnq0UzvUVD8IXO/eSkpIWC5yszHHChAnCREplqaOW7N3WInyZ6fhyu91ByzBjVfgS5fhi44XWCAlfFkXEanqky0fCCV8iyxwBcY4vkW64aAtfzPG1atUqw9k7bOLRu3dvy7tugMYSjnvuuQeXXHKJrtc7nU4+KFJb7rh//374fD4kJiYKXyUGGq8N5mTbunWr8BVpdhx2zzK3V+/evXWvwBUUFCA/Px8+n0912HJzWNsVS8KXVRxfkRIN2eKMUeGLDfDtdrvQRYjWhp5SR3atWEn4YuOEPXv28Jw/I1hB+HK73dxNEw3hq6ioCOeccw5qamowYcIEPPfcc6acg1Hatm0Lp9MJWZY1765slLKyMp75GiuTYRHYbLaQLigl8SB8sc/q8/laLBKIzvcCmtqdhoYGTZ+VhC/9pKam8ty3YIvYsbKjI4PNLcnxZRwSviyKiElFvAtfojK+zBK+wq3umFHD3717d2RnZ8PtdmP9+vWGjhUr+V6MESNG4NlnnzXkhNKa86XM9zJLHFSWO4pepWru+DJa5sgwWu4Yi46vSAhfzPF15MiRoIPoSDu+jJY6Kgf4sSCwW5V4KXXMzc1FRkYGZFnG9u3bDR9P9ASSTdi1TPaUmxSZFTsRbGfHuro6nHfeeSgsLETv3r3x0UcfCds9TTQ2m433wZEud2R9a2ZmpiVLEs1ETc5XQ0MDH7NaQfhigonW8V5CQgIXn5Wf98CBA1izZg0kScJZZ52l65wCkZyczM9RS7kjCV/6kSQpbM5XrLk7RTu+SPgiLIeIUsdI7ugINDUgFRUVfiu1VnV8mVnq6PP5/LZbDoQZDZAkSbzc0WjOV6wJXyLIz88HANWrzWbmezFYwP3mzZtNc3yR8KUf0cJXqIFYZmYmd/YEC5WPtVJHCrYXQ7yE20uSxMsd//zzT8PHs4LjiwlfaWlppuXuMeFr48aNvExQlmVce+21+P3335GVlYUvv/zSNMeZKKKV88WELzOc21aH9TmhhC/Ru+CJcnzpEUwCCX0s1P6kk04SLoboCbhvLcKXGRlfQPiA+1grdRTh+PL5fLwvIuGLsBxM+Nq3b5/ukrVIlwsFywpoTY4vZeMdSpDzer2mNUCiAu5bo/BlxPFlFkrHl1nCV3V1Naqrq3mZjFHhy+jOjpEW7Y3AhK8DBw7A6/XqPo5aESJczlc0Sh21ZJc0JxYG+LEAE76qq6tV5yNZUfgCgM6dOwMwLiYD1hK+zBSdunTpgoyMDNTX12Pz5s0AgOnTp+ODDz6Aw+HAp59+iu7du5v2/qKIlvDFFn3Y4ldrgt3/zas1lLC2IicnR0hWr9GFa72ljkBg4cuMMkeGnoD7WOgXrer4AuJP+BIRbl9eXs7HaiR8EZYjLy8PSUlJ8Pl8ureLj/RKuiRJLcodjx07xv+/Z8+eQt/PihlfNpuNr2SFOi9l6YPoBkhEwL3P5+MZXyR8BScSji/2/Zvh+EpNTeUDx82bN/O2ZtCgQYaOy4SvP//8U5MDhRFLjq+8vDzY7XZ4vV4UFxfrPo5aESJczlek2v3OnTtDkiRUVVWFzYYJRSwM8GMBpaii9p6zqvAlUvwwa1dHLU6VSAhfkiTxdnvNmjVYsGAB7r//fgDAyy+/jLFjx5r23iKJhvBVX1+PF154AQBw8cUXR+x9rYKaUkfRbUW0Mr6Aljs71tXVYdGiRQCAyZMn6zofNe+nR/iyskBhZeErnMsu1oQvo/NdoKnKKCkpCS6XS8h5xSIkfFkUEdvFR6OEpLnwxdxeBQUFwrMtrLirI6CugWKdWkpKCg9hFAXb1XDHjh2at1Bm7N+/HzU1NXA6ndzZ0RqwouOLlTru3r0b+/btAyBO+FKK1QsXLgTQ6OQxOkFr06YNF2hWrVql+fWxJHzZ7XZ+3eh1qMiyrFn4Cub4ilS7n5iYyCepsZRFGa8oNwdQI3wprzmr3WcixY/W4vgCmsodP/jgA1x++eUAgFtuuQU33HCDqe8rEva3N7pLrhbef/997N+/H/n5+bjqqqsi9r5WIdrClx7HsAjHFxtnLFmyBDU1NWjfvj0GDhyo+XjhCOc+CoQZGcCisbLwRY6vllC+VyMkfFkYowH3VhK+RJc5AsZrns1wfCmPF0r4MrMBysrK4hkpel1frMyxR48elg3CNQMrZny1a9cOmZmZ8Pl8WLp0KQCxnTUT0b799lsAxsscGUbKHWNJ+AKM53xVVVXxXES1pY7RdnwBYjZhIceXOFi5Y/PdygJRUVHBSyLj1fGl3LmtNQlf33//PWpqajB+/HjuZIoVIu348nq9mD59OgDg7rvvRmJiYkTe10oE25hKiVnCl8fj0RXnIrLUkZU5Tp482ZQNVow4vqzcLzKxiolXeoh2xpfV+r5giAi3J+GrERK+LIzRgPtoCF/Nw7LNFL6MNgTxKnwBxssdW2O+F6DN8VVXV8cFMjMdX5IkcdcXm0CJDOBlx2LXiijhy0jAfWsTvtgAPDExMewAMJzjK5LfnYidHWNhgB8raAm4Z9dccnKy8NV2o4gSP8rLy+Hz+QCIL3W0svAFNEZLWHkHx2B06NABQOSEr3nz5mH79u3IysrC3/72t4i8p9WIhuNL2c/pKXcUJXzJsmxqvhdA4fahiIbjq7a2ll9zseL4EhFuT8JXI5qEr9dffx0DBgxAeno60tPTMWLECO4SCMZPP/2EE044AYmJiejatStmzpxp6IRbE7EofJHjyxrCl9GA+9YufBUVFfEJUzBYHlZqaqrp91jzv4MZwhf7vNEWvmRZjlnhS295jnJSEW7F2UqOLxE7O1Kpozj0CF9WXPFWCl9GNk5g11ZqaioSEhKEnBtzqlhR+Orduzc6d+6MNm3a4Msvv4zJCY6ov70aZFnGv/71LwDA7bffzv+2rY1oCF8Oh4O766IpfLFs08TERIwbN07zsdSgNdze7Xbz9oWEL32EEr7YtZyQkCA86sYsqNRRHJqErw4dOuCpp57CypUrsXLlSowdOxbnnnsuNm3aFPD5u3fvxsSJEzFq1CisWbMG9913H2677TbMmzdPyMnHO0ZX06MxeYyk8GXU8RXNjK9ICV+///57WAGnOWVlZZg/fz4A4yHnsUa7du0gSRK8Xm/YwG5lvpcZ9nglkRC+GErXgBGGDBkCSZKwb9++kCUUzamsrOQlWLEihohyfKmZVDDhq6yszG+TDKBRvGQrxZEsdSTHlzVg/UmsC19sAaKurk5V2WYw2KRH5LVlZceX0+nExo0bsWPHDuGbCUUKUX97NXzzzTdYt24dUlNTceutt5r6XlaGjdsjKXwBxgLumWBiNNyeub3Gjh1rmvNVa6kju+4lSTK9zTCCCOErGqWOynwvs8fuohAZbk/ClwbOPvtsTJw4ET179kTPnj3x5JNPIjU1NairZObMmejUqRNmzJiBPn364LrrrsM111yD5557TsjJxztGtov3eDx88Bstx5fX68X27dsBkOOrOWYHV/br1w/JycmoqKjg4qNaHn30UZSUlKBv374499xzTTk/q+JwOPg1HC7nKxL5XgxW6gg0lsOJvGaVwlfHjh2FDWzT09P5fa8l54sNDq1YghWMSApfqampfCDd3PV17NgxLnTHmuOLhC/jaMn4srLwlZiYyK9fIyVvZojAbIJWX1/PBfpwREr4AhrbBytPlsMh6m8fDlmW8eSTTwIAbrzxxlbd/rA2oLy8HG63O+BzzGgvjEzmmeNLzxhBGW5vdpkjoD3cXrmjo81m3USiWHV8xVqwPUCOL5HovqO8Xi/mzp2L6upqjBgxIuBzli1bhjPOOMPvsQkTJmDlypWqBwytmS5dusBms6GmpoZnZqlFOfCN5EWuFL727dsHt9sNl8uFzp07C38vyvgKjsPh4OHiWsodt2zZgldffRUA8MILL8RcPogI1OZ8RWJHR4bS8SV6lUopfIkqc2Swa/CXX35R/ZpYK3MExAlfagdiwXK+2CAvLS1NWGlXKJjwdeDAAR7Or5VIOtTinXgpdQTE5HyZUUardCaonfBFUviKByIRcP/zzz9j2bJlcLlcuPPOO017n1ggMzMTdrsdQHBXktUcXyJKHYuLi/mGQWYKX1odX7Higo4F4SvQdx7LwpcRxxcbF5DwpZENGzYgNTUVLpcLN9xwAxYsWODnRlBSXFzcooymXbt28Hg8IRsAt9uNiooKv3+tkYSEBD6h0lpKwgZ8mZmZERUvlMIXcxr16NGDd6oiUQpMerIg4rnUEdCX83XXXXfB4/HgnHPOwfjx4806NUujVviKpOOrU6dOfGAgsswR8O/8RQtfZ599NgDgnXfeUb1zUywLX0VFRboWdbROKoLlfEU6L6tNmza8vQsWth+OWBnkxwLxUuoIiBW+RF5bCQkJfDxDwpc5sL+93sxENTC31zXXXMN3c26t2Gw2v/K/QMSj8OXxeODz+dC/f39TFucZynB7NXMVpePLysSC8FVeXg6Px+P3u1gUvtg4q7q6Gl6vV9cxyPHViGbhq1evXli7di2WL1+OG2+8EVOnTsXmzZuDPr+5M4Hd9KEcC9OnT0dGRgb/xyYVrRG9GSrRCgxWCl9bt24FYE6ZI9AkWMmyrKvhjWfHF6B9Z8dvvvkGCxcuhNPpbNXlyFZ0fNlsNvTu3RuAeOHLTMfXX/7yF+Tl5eHQoUM8Ny4csSh8tW3bFk6nE7Isq9oRtDlaJxXBHF+R/u4kSTJU7lhTU8OdYuT4Mg45vvwxw00oSZLmCR8JX9owe2fHFStW4Pvvv4fdbsc//vEPU94j1miez6vE5/PxOUU8CF8pKSl+r5s8ebLmY2iBtT/K0PpQmB2FIgrWDtbV1ekWY8zK+FLOrVg/wLB63xcIpUFDz/0CkPDF0Cx8JSQkoHv37hg6dCimT5+OgQMH4sUXXwz43Ly8PBQXF/s9dvjwYTgcjpADkWnTpqG8vJz/01s+Eg/oDbiPlvDFGpKGhgb88ccfAMwTvpKSknj9ux5XYDSFr0is6DDH14YNG8I2lA0NDbjrrrsANO5u1KNHD9POy+qw1V8rZXwBTeWOooWvvLw8/v+igu0ZCQkJfIt4VkIbDtZ2xZLwZbPZ+GRNT38Vq44vwFjOF2sHHQ5Hq91RTSRaMr6YSGrVwb9VSx0B7U4HEr60YXap4/Tp0wEAU6ZMicjCVSwQamfH0tJSU7IjoyV8Af7tnplljkCjm4ntYKmm3DFWXNBKsYo5t7RiluPL4XDw/rB5zlcsOr5cLhecTicA/TlfJHw1Yjg1T5bloGGII0aMwPfff+/32HfffYehQ4fyP2AgXC4X0tPT/f61VvQ6vljjGmnhKykpiQs/LNfHLOFLkiTddc/19fX8uo3XUseCggJ07NgRPp8vbLj4q6++im3btqFt27Z44IEHTDunWECN46u6upoPECM1cJ44cSJsNhtOPfVUocfNysrCww8/jEcffZRPOETy17/+FQ6HA7/++ivWr18f9vnRaruMYiTniw3EjDq+oiF8GdnZUTnAj5XdlawMOb78MWvjBBK+zMVM4WvTpk1YsGABJEnCP//5T+HHj1VCCV/ssczMzJBzN61EU/hiC2vZ2dl8kdgsJEnSFHAfK8KX8rvXW+5olvAFBA+4j0XhCzAecE/CVyOahK/77rsPv/zyC/bs2YMNGzbg/vvvx5IlSzBlyhQAjU6tK6+8kj//hhtuwN69e3HXXXdhy5YtmDVrFt5++23cc889Yj9FHKPc2VEL0XRNsMaE5TOYJXwB+nd2VIpS8VrqCKgrdzx69CgeffRRAI25F619cK5G+GJOm8zMTD7ZNJvLLrsMFRUVfm2sKB555BE89NBDwo8LNH6f5513HgB1rq9YLHUEjAlfRhxfysyQaHx3Rhxf0XImxyuU8eWPWRsnsAk7CV/mYKbw9dRTTwEAzj//fL9NY1o7bNweSvgS3VZYwfE1ceJEUzKIm6Ml4D5WhC9JkrhgpdfxZVapIxB/wpeRXVABEr4YmoSvQ4cO4YorrkCvXr0wbtw4/P7771i4cCEPwS4qKsK+ffv484877jh88803WLJkCQYNGoTHH38cL730Ei644AKxnyKOYcLX9u3bNQW4R3NC0bwxMVP40uv4Ys9PTEwUHv5vJeFLTcD9Qw89hGPHjmHQoEG45pprTD2fWECL8BXpMgkzBgeR4OabbwYAzJkzJ+yknISv8LAg3srKSr/8ilgtdbT6AD9W0FLq2BqELyuUOtbX1/McOxK+1GGW8LVr1y58+OGHABoX6okmWDsQKOPLrLbCyESeCS16ha/x48fD6XTi+uuv1/V6rSgD7sMRS/2ikYB7WZbJ8aUBI44vn89Huzr+fzTN+N9+++2Qv589e3aLx0aPHo3Vq1drOimiid69eyMpKQlHjx7FihUrcOKJJ6p6nVWEr9zcXFMdMXobArPyvZTHDNaZe71efr6RcnwtX74csiy3KCdav3493njjDQDAiy++GJGVL6vDMr4OHToEr9cb8DuJdL5XrHPqqaeib9++2LRpE2bPno077rgj6HNjXfjSuhNZTU0NH/ypnVgkJSXxDM09e/a0GOBFo9Rx165dAduYUMTSAD8WUJY6hvpb6LnmIg0TP44cOQK32w2Xy6X5GGaXOqpxqjC3FyA+ViFeYX/7o0ePoq6ujucjGeXZZ5+F1+vFhAkTcMIJJwg5ZrygptTRio4vvYLJ3Xffjdtuu01o6WYoWJ8cT44voLEtPHLkiC7hiy0IAJETvmRZjnnhS49QXFlZyXP6WrvwZTjjizCX5ORkXib03nvvqX6dVYQvM91egP4VIyY8mTEQZecUrDNXOl7MboCGDBkCh8OB4uLiFk4UWZZx5513wufz4cILLxSeHRWr5Obmwmazwev1Bt3aO1qOr1hFkiTu+nrttdd4BxyIWBe+tDq+2DWWkJCgqT0KlPMVje+uU6dOsNlsqK2tbbGZTTio1FEsrD9RuowCwa45p9NpyuKPCHJycrjYFW6jkWCYVeqoxeXAhK/U1FRaWFJJdnY2F7v07JIbiIMHD2LWrFkAGmNbCH9iVfjS6/gCEDHRC9BX6hgLAoURx5eyPDJSwldlZSXq6+sBWHfRJxh6o32AJhd4YmKisIWEWIWErxiAZfrMnTuX37DhaC3ClxUdX6wzDybGsQYoNTXV9I43OTkZAwcOBNCy3PHzzz/Hjz/+CJfLhWeffdbU84glHA4H3zkx2KCbHF/aueKKK5Ceno7t27dj0aJFQZ/XWoWvtm3banJLBdrZMRrtfkJCAv/sWssdY2llOxZITU3lOx2HKinWe81FEkmSeNm5npK3hoYGPi6wgvBFZY7qkSRJeLnj888/j/r6epxyyim0yBcANm6PZKljtIWvSBKP4faAMeGLvcblcpmyKBDoO2fXd2pqasxcOwwjji/K92qChK8YYNy4ccjPz0dJSQm+/fZbVa+J5s5oseD4ikSpY1VVVUBnS6QboEAB9263m28ycffdd5NzqRnhcr7I8aWd1NRUTJ06FUDwkHufzxfVjTmMwMSfw4cPB93pOBB6JxWBHF/RWvDQu7OjWaVorRVJklTlfFk934thRPxgk0fldyIKEr7MR6TwVVJSgpkzZwIgt1cwYsnxJctyzAlfWhxfrO2OhX5RhOPLDLcXEFr4irUyR0CM44uELxK+YgKHw4HLLrsMAPDf//5X1WussKsjYF3HVyRKHYHAnUGkG6BAAfcvvvgidu7cifz8fAp5DQDL+QpWYkOOL33cdNNNAICvvvrKz6nEKC8vh9frBRB75W/K8hwtOV96JxXNHV+yLEfNLac34N6sUrTWjDLnKxitSfjKzMwU7iYg4ct8RApfL730EqqrqzF48GCceeaZho8Xj7C2oLy8vEVlidWEr/r6er7ZV6wJX+EcX16vl7fdJHwZI96ELyPh9iR8NUHCV4zAyh2//PJLv128AiHLcqspdbSi4yspKYmXmwQ6r0jX7zPha9WqVaivr0dxcTEef/xxAI1be7PBB9FEKMdXeXk570TI8aWN3r17Y9y4/8feecc3VbZv/DpJ96QtUFbZQ0A2KDgYIqAogluc/NyvDBURX14XrpdXEcUJDgTR1wm4eRGUochesvcolEJZpdDdJr8/7jw5J2nGOcnJOMn9/Xz6SZqmyWmTnOd5rue6r7s/LBaLfQdeiRBuUlNTfQqzDiWSJPlU7qiX4+v8+fOorKwEEPzzvr/ClxEm+EZBjCvRLnwFcg4kxkwWvgKHXsLXuXPn8PbbbwMgt1e4lvaGmoyMDLtA7OxKCnRXR63Cl3B7AcYRvtSG2589e9Yu6hlBpNCj1DFQ3cojTfjypwsqC18yLHwZhI4dO6Jjx46oqKjAN9984/G+586dQ1VVFYDQCF8iHykmJibgjphwzPiSJMnjCSrYJ6CWLVsiMzMT5eXl2Lx5M55++mmcP38eF110Ee68886gHIPR8CR8CYdN7dq1WTT0ARFy//HHH9cI4DZqvpfAF+FLTMT8cXwpNzsSEhICtoPqDn9LHdnxpR/s+CICKaqy4yvwiNdea5dcZ6ZPn47CwkK0adPG3iiKqYnJZLKPu845X4F2fGldyAvhy2QyBTWg3h/UljqK81ZKSgri4uICflz+wo6v4MGOL31g4ctACNeXt3JH8SFPTEwMyW5I27Ztcc899+DFF18M+KDka81zIEsdAc/KfLBPQJIk2XO+3n//fcycORMAMHXqVLszjXFElDp6Er7Y7eUbQ4YMQU5ODk6dOlVDxI9G4cvXRUXjxo0hSRJKS0tRUFAQUhGJHV/hA2d8EYH8PIjFnhqnCgtfvtGoUSMA/jm+SktLMWXKFADAP//5T+6q6QVXOV/KEvpwKXUUgkliYqJhHHxKEUY4ulxhtDFRnAuVHRrVEkzhS/zPjTL2uYLD7fWBV70G4vbbb4fJZMKKFSuwd+9et/cL9S66yWTCrFmzgpId5euJIJCOL+XjhoPwBcjljjNnzoTVasXtt9+OXr16Be35jYZwfLnK+OJ8L/+IiYnBww8/DKBmyD0LX+qJi4uzCwMHDx4M6f9OCF/Hjh1TPQG2Wq2Gm+QbAXZ8EYFsnMCOr8CjR6nj7Nmzcfz4cTRu3Bh33HGHXocWsbgSvs6ePWsvoQ8X4Us4voLtbPYHMS6XlZV5HCONNiaK1yCcHV+VlZX295iRHV8cbq8PLHwZiPr162PAgAEAgM8//9zt/ULZ0THY+HoiiDbhSzi+ABpkXn311aA9txFRU+rIji/fuf/++xEXF4c1a9Zg7dq19tuN2tFR4I/w5ctETJnzFcoNj8zMTLvgotb1VVJSYu9+GQ1jVbCI1IwvTy4JVwSycQILX4FHvPZHjx512R1bDT///DMAKq83SklcKBFjkLLUUZwrUlJS7M1b9EIIX5WVlTUC9T1htI6OAJ0zRG6pp4D7YGcA+0s4Z3wlJSXV+J8bWfhix5c+sPBlMO666y4AVO7obiJo9MWjFnw9EYRDqWMwd3Quuugi+/WnnnrKXkbAuEYIX8ePH7fn5QnY8eU/devWxc033wzA0fVldNFeCF/B6OoIOOZ8hdrpq7XcUUzwY2NjAzbxjUbUlDoGqnRJb8R5uLy83GtTH2eCUerIwlfgqF+/PiRJQmVlpddcJFdYrVZ7J+s+ffrofXgRiSvHVyBFcuV5X4vry4jClyRJqgLujeb4CueML+X/PBKEL3Z86QMLXwZj2LBhSElJwf79+7FixQqX9wn1AiiYsONLHRkZGXjsscdw7bXXYty4cUF7XqNSp04dmEwmWCyWGkGv7PjSBxFy/9VXX9knglzqqA2l4yvU/ztfha/MzEzD5LQYgUgqdYyPj7e/n7WWvHGpo7GJjY21L059KXfcu3cvTp48ifj4eHTp0kXvw4tIgi18xcbG2h05kS58AeoC7kOxMe4P4Sx8ATUD7o0sfOkRbi/mB9EMC18GIzk5GTfeeCMAyi9wRTQJX5zxpZ4333wTP/30k6FyEUKF2WxGvXr1ADjmfFmtVnZ86UTPnj3RtWtXlJeX45NPPgEQOcLX6dOnVWVdlZeX288RRnd8ae3sGOrjjVS8lTpWVFTYxZhwF74A37OeAlnqKEq0WPgKLP7kfImN4W7duhmiO1444KnUMVDnCjFXjgbhy1WXQWeiyfEV6FJHwPF/brFY7HNMIwpfntaV3mDHlwwLXwZEdHf85ptvUFZWVuPn0bSgUJ4ItORAhFL4MloNf7TiKufrzJkz9te0SZMmITmuSEGSJLvra9q0aaiurja88JWWlmZfFKtxfYlFRUxMjE87ceGS8QX45/hi9MOb40t8xsxmsyHGIF/FDy51ND7itddSOi5YuXIlAHATHw0E2/EFyCKylsW8UYUvNY4vo42LRnJ8nT592r5ONOL6WBg9SktLa0SweIOFLxkWvgxI3759kZOTg8LCQnt4p5JQL4CCiTKjS8uJNxwyvvgEFN64Er6E26tevXqGm3SFI7fddhsyMjJw8OBB/O9//zO88CVJkqZyR7GoqF27tk/lfsLxdejQIfsufaj+d8LxpVb4iqZxKph4y/gS77msrCyYTOE/BfRX+ApkqaMalwoLX74jskh9cXwJ4euSSy7R9ZgimVAKX9Hg+BJjMzu+iGALX2KOlJmZachmF0qjhhah2Gq12jfCeN3JwpchMZlM9tbMn332WY2fGz0gWgsJCQkwm80AtNU9h8rxVVVVZb+NT0DhTf369QE4ljpyvpe+JCUl4d577wUAvPvuu4YXvgBtOV9iIubroqJRo0Ywm82oqKjA1q1bAYTe8XXgwAFV7lujTfCNgjfHl1JsNQLK7n5aCEZXx8rKSlRWVnq8LwtfvuOr6FlUVGQ/H7LjSz1GEb6EYGI04YvD7R0JhvClFBuNnO8FAHFxcfZMPK3r3erqagC87gSAmFAfAOMbd911F/7zn/9g/vz5OHHihMOgFE1dHSVJQlpamkMJmjeqq6vtJ9xgC1/KxQiHDIY3nhxfnO+lH//4xz/wxhtv4Ndff7XfZuRzly+OL18XFTExMcjJycHBgwftk7pQCV85OTmIiYlBeXk5+vTpg9q1ayMjI8Pt1549ewAYZ4JvFJQZX1artYaT0CjB9gJfxI/S0lK7KySQwhdACz53Y3llZaX9OFj40o6vwteaNWtgsVjQpEkT+wYW4x0hCBQWFqKiogJxcXFhKXyJz5TR8mq51NGRYGd8GV34AqhK6cSJE5qEL+H+jouLM5xYHAhY+DIo7dq1Q7du3bB+/Xp8/fXXGDVqlP1n0VZCkpqaijNnzqg+ESjFqGCXOooTUEpKiiGtttGEK+GLHV/606JFC1x99dWYP3++/TajTPpcEUzhCyARVrwvgdCJhjExMejevTtWrVqF5cuXq/69aBmngoUQYSwWC86fP19jcycahC8xB4qJiQnI5lZcXBzMZjOqq6s9Cl/C7QUEbq4RyfgqfHG+l29kZGTY39cnT55EgwYNwlr4MtoiXku4vVGcOUK0UtPMx5lQlToaWfhKTU3FiRMnNJU6KuN1uIM2C1+G5u6778b69esxe/bsqBa+tHZ2FPdTtlLWG2/Cl1EGtWiGHV/BY+TIkXbhq1atWoYWhX0RvvyZiDmLsKE87//6669YuXIlzpw54/BVWFhY47YzZ84gLi4OAwcODNnxRiIJCQmIi4tDRUUFzpw5Y3jhS5yHtYgfStdEICb6kiQhOTkZRUVFHp0OQvhKTk5GTAxPt7Xir/DF+V7aMJlMyMrKQkFBAU6cOMHCl854c3xZrVbDOb6EaFVcXOzSYewJFr60I9a7vji+eN1J8EhsYG677TaMHTsWa9euxc6dO3HBBRegvLzcPhGLNuFLq+MrUGWOysd2J3wZZVCLZjjjK3hcddVVaN68Ofbv32/oMkcgNI4vQUxMTEidJWlpaRg0aFDInp8hUSYjIwPHjx9HYWEhGjdu7PBzowlfQvw4ceIEysvLVW1WBWPzT4vwxWWOviFe+8LCQhQXF6sqibJYLFi1ahUAdnz5Qt26dVFQUICCggJYrdaAny/EXDmahC93jq/i4mJ7tz6jrBHEZ7K6uhoVFRWazATBLnU02tjnCq1GD4CFL2c43N7A1K1bF1dffTUAOeRenFDNZnPUTLY8dVB0RaA7Ono6Jj4BGQfhNDh+/DiqqqpgtVrtwhc7vvTFZDLhH//4BwAYPpNFCF9Hjhzxel89JmJKETYrK4ut7IzHgHujTf6zsrLsiynlJoQnAtnRUSCcKix8BY60tDT7/1mt62vXrl04c+YMEhMT0alTp0AeXkSiDLgvLi5GWVmZw+16I15fLQt5owpf3sLthdsrLi7OMPllznmHWmDHl3bE2pIdX77DwpfBueuuuwAAn3/+OSwWi8OEL1oWQEZ0fPEJKPypU6cOzGYzrFYrjh8/jhMnTqCkpASSJNnFDUY/Ro8ejeeffx6vvvpqqA/FL8R7o6ioyOs5SW/HV7S4fBnPCOFLjDdKjCZ8SZKkudwxkB0dBWpCnVn48g9JkjSXO4oyx+7duxu6ZD5UKIUvca5ISEgImCsnGksdS0tLXWZiBbpEOxDExsbaP2fhLHwVFRXZzyFGFr7Y8eU/LHwZnCFDhiA9PR25ubn4448/7DsJRi8X0oJWx1cohS+jBVdGMyaTye4+Onr0qD3fq2HDhgHLhotm4uPjMXHiRMOXpyQnJ9s/397KHQPh+GKYSHJ8AdqznoLh+BJCgKcFOwtf/uOr8MX5Xr7hSviqU6dOwISYaBK+lE2tXJU7Gi3fS+BrZ8dgCF+1atWyv3d37twJwNjCFzu+/IeFL4OTmJiIm2++GQAwe/bsqAu2B8Lb8VVWVmav2Qf4BGQ0lDlfnO/FqKVRo0YAgiN8NWjQwD6ZjqbzPuMeMb5Eu/DFji/j46vwZfQNlFAhRAERcA8E9lzhi/AlBBOjCV+SJHkMuI824SsYGV9ms9k+HorzsZGFLw639x8WviKAu+++GwAwZ84ce65MNC2AwjnjC3A8Lj4BGQtlZ0fu6MioRU3AfUVFhV2Y8GdhYTKZ0KRJEwDR5fRl3OPO8VVdXW1fXEWy8MWljpGDlte+sLAQ27ZtA8DCl6+4c3wFCn8cX0bJwVLiKeA+moQvi8UStNfReRwwsvCldb0L8LrTGRa+IoBLL70UzZo1w7lz5/DJJ58AiC7hKxwdX3FxcYiLi3N4PoBPQEZDKXyx44tRixrhS+z4mkwmvye6QoyNpvM+4x53GV+nT5+G1WoFYKz3SjiXOrLwFVi0vParV68GADRv3tzQi9tQYiThy2iOL8BzwL1Ro1B8Eb5E0wQguMKX2Wy2j49GhB1f/sPCVwRgMplw5513AgC2bNkCwFiTWn/RWvMcDOFL+fgsfBkXdnwxvqBG+BKLitq1a8Nk8m8o7tKlCwCgdevWfj0OExm4c3yJ91xGRoahgr+51DF6EWXjarrkcpmj/wS71FHMk6NF+GLHF2rcN5jCV506dfyeb4USDrf3H+O++owDorujIJqEL60ngmCUOgIsfEUCnPHF+IIW4UuPRcXzzz+PJUuW2MvemejGXcaXEfO9gPAsdRROFRa+AouW156D7f0nVI4vLQt5IwtfnhxfYn1gNOFLCFeuOlW6Q9w3ISEh4EKUchwwuhPUl3B7MQ/gdSfBwleE0KpVK/Ts2dP+fTRlvRjR8WW0gS1aEY6vI0eO2IUvdnwx3gi28JWUlIS+ffsiJibG78dijI83x5eRhS9RqukJLnWMHMRrf+zYMVRXV7u9n8ViwapVqwCw48sfxLmhsLAQR48edbgtEERbqSOH2xPB6OgoiCThix1f/sPCVwSh3O1nx5d7wkH44hOQMRDC1/bt21FRUQGz2WwvvWAYdwjh68iRI24X6kYVIZjwx13Gl1Hfc+I8XF5ebl8cusNqtQY13N7Tgp2FL//Jzs6G2WxGdXU1jh8/7vZ+27dvR1FREZKTk9GhQ4cgHmFkkZmZaXfg7NixAwALX3oizknRXurIwpdvaDV6WK1WXnc6wcJXBHHLLbfYczvY8eWeUJU6VlZW2q/zCcgYiAVXVVUVABI02FXDeEOIoyUlJTXEB4FRRQgm/PFW6mi0+UF8fLz9mL2VvJ07d85+vuaML+NjNptRr149AJ5fe1Hm2KNHDx6j/cBkMtk/a8KxHAzhq6KiAhUVFap+x8jCFzu+4HBf8buBJJKEL63h9sXFxfbxkNedBAtfEURWVhZef/11DB8+HBdffHGoDydoGMXxpVyEGLmrSDSRlZXlMInmfC9GDQkJCfbFgrtyRxa+mEARaaWOgPqsJ+GkSEhICOjCmIWv4KHmted8L/1wPj8E8nyhFD7UCCdWq9XuFjKy8MWOr9A4vow49ilxVUnkCbHxGhsbG5T/tRFg4SvCGDNmDL744gtDdWzyF2VXGIvF4vX+oRK+xAkoNTWVdyQNgslksgfcA5zvxahHuL5Y+GKCjRC+ioqKHHKRjPyeUyt8BaPMEWDhK5io6ezIHR31I5jCV1xcHOLi4gCoK3esqKiwxwcYcSHvKdyeha/AEImOr/LyclUOSWWZoyRJAT02o8DCF2N4lCWLagbOUAtfbDc1FqLcEWDHF6MebwH3BQUFAIwpQjDhjdJRLMQXIDqEL+GkCLXwVVlZaV/csfDlH95e+9OnT2Pnzp0A4NDkifENpTgQGxsb8PevcvPaG6LMETC248tZ+CorK7OfL4y2RuBSx+ChXLeqcX3xurMmLHwxhic+Pt7uoFJT9xyqjC8+ARkTdnwxvuBN+DKyCMGEN7GxsfYFhbLc0cjvOa3CV6BdEyKbyN1iTzkXCfRcI9Lx9tqLbo6tWrUyXH5dOKI8P9SuXTvgThHxWVKzkBfCl8lkMmRlixBhSkpKHEQ8sT6QJMlwQjk7voJHTEyMXfBVs97ldWdNNAlfkyZNQo8ePZCamoq6deti2LBh2LVrl8ffWbp0KSRJqvEldmcYxl8kSVKd82W1Wu27Suz4YtTAji/GF9QKX0afiDHhiaucr2gQvsKl1FE47ZKSkgy5QA8nvL32nO+lL8rzQzDOFVo6OyqD7Y1YupWWlmbfqFfmfCnXB6KrplFg4Su4aMm15nVnTTR9upYtW4aRI0di1apVWLRoEaqqqjBw4EBVb/Zdu3YhPz/f/tWqVSufD5phnFHb2bG4uNieD8DCF6MGpfDFji9GLZ6Er6qqKvsC3YgiBBP+COFLjDtWq9VeXmPE91y4ljq6W6xzvpd+qBW+ON9LH4wifBkRSZJcBtwbNd8LCH/hKzExEYMGDUKXLl3QuHHjgD9foFG73gV43ekKTQnbCxYscPh+5syZqFu3LtavX4/evXt7/N26detyJzsmYKhVwMWJwmQyBfyE6074MuLAFs0I4Ss2Ntah7JFhPOFJ+BITXkmSAr5AZ6ITMdEVjq/CwkJ7W/NoEL4CPc6qdXyx8OU/4rU/cuQIrFarg9Onuroaq1evBsDCl14oXTEsfOlPVlYWjh075pDzZWThS6ylhJilhmBmfAHA//73PwAwpEvQGbHeZeHLN/zyU4qBXc0HtUuXLqhfvz769++PJUuWeLxveXk5ioqKHL4YxhNqFXBlsH2gT4Ds+IoMREeppk2bwmw2h/hoGKMghK8jR47U6DYrSs4yMzP5PcUEBOdSR7HISklJQUJCQoiOyneE+HHy5EmUl5e7vV+wSx0rKytRWVlZ4+csfOmHeO2Li4trzPG2bt2K8+fPIzU1Fe3btw/F4UUc7PgKLK4C7o0sfIW74wuAPWYpEuBSR//wWfiyWq0YO3YsLrvsMlx44YVu71e/fn18+OGHmDt3LubNm4c2bdqgf//++OOPP9z+zqRJk5Cenm7/EgsIhnGH2hNBsDo6Kp9DPKcY2PgEZCz69u2LUaNGYfLkyaE+FMZANGzYEJIkoaKiokYHJyNnLTHGwLnU0ejvuczMTMTHxwMAjh496vZ+wXZ8Aa4XfCx86UdycrL9/ezs+BNljhdddBFvIuhEOAtfQjAxsvAlRHkudQye8BVJcKmjf2gqdVQyatQobN68GcuXL/d4vzZt2qBNmzb273v16oXDhw/j9ddfd1seOWHCBIwdO9b+fVFREYtfjEfUWj+D1dERYMdXpBAbG4t33nkn1IfBGIzY2FjUq1cP+fn5OHz4sEP5iNFFCCb8cXZ8Gf09J0kSGjZsiP379yMvL89t3mKwMr7i4uJgNptRXV2N4uLiGlEeLHzpS8OGDVFYWIi8vDy0a9fOfjsH2+tPsEsdxVxZi+PLyIKJJ8eXEdcH/ghfwSp1jCTY8eUfPjm+Ro8ejR9//BFLliyxlwFpoWfPntizZ4/bn8fHxyMtLc3hi2E84SwyuSOUji8+ATFMdCHGR+ecL6OLEEz445zxFQnvOTU5X8EqdZQkye5UYcdX4HH32q9YsQIA53vpSWZmpr2zYDAdX2oW8pFU6hjNji9xXyMLmKHCF8cXZ6zLaBK+rFYrRo0ahXnz5mHx4sU+dzjbuHEjh0QzuqLW8RUq4ctqtbLwxTChoqICsAkAwcRdwH1BQQEAY4sQTHgTaY4vQJ3wFaxSR8Dzgo+FL31x9dqfOHECe/fuBUAb6ow+mEwmu3AcbqWOkSB8if9tpGV8lZWVobq6WtXvcKmj7/gdbl9VBVitATk2I6BJ+Bo5ciQ+//xzfPHFF0hNTcWxY8dw7Ngx+4kIoDLFu+++2/791KlT8f3332PPnj3Ytm0bJkyYgLlz52LUqFH6/RVM1KPW8SVOFMEUvqqqqlBRUcHCV7Tw8svA0KHAM88A334L7N4NqJwMMAHizjuBhg2BffuC+rTuhC8hQihLShhGTyIt4wvwLnxVV1fbhb5gdEsVCz5XC3YWvvTF1Wu/atUqAMAFF1wQvfOqsrKAPOxDDz2EXr16oXv37gF5fCXRJny5KnU0ctd3Zbmi2s6OLHypYNo04L33atysdr0LuBG+Xn0VSE0FJkzQ5zgNhqaMr2nTpgGgsGclM2fOxIgRIwAA+fn5yM3Ntf+soqIC48aNQ15eHhITE9G+fXv88ssvGDx4sH9HzjAKtDq+glE+qxwMzp07x8JXNHDkCPDss3T9xx/l25OSgA4dgE6d6KtzZ/o+CAJs1FNVBfz0Ey0Q5s8HRo8O2lN7E75CIkIUFwPvvgsMGAB07Rr852eCgjvHl1h0GRFvwldhYSGstp1sdnxFFq5e+6jP9/r9d2DIEODxx4FXXtH1oV966SW89NJLuj6mO6JN+Iq0cPvExERIkgSr1Yri4mJVxgJxzuSMLzds3Ag88ghdv/VWQDFuq13vuq00OnKE5oGxsfoes0HQJHxZVVjjZs2a5fD9+PHjMX78eE0HxTBaUVvzHMxSx5iYGCQmJqK0tBRnzpyxD+osfEUwixfTZYsWwBVXAH//DWzZApSUAKtX05eSFi2ASy+lXR3b5I/RmZ075V3xlStZ+HriCeCDD4AXXgB+/pnep4yx+OwzIC8P+Oc/3d4lGjO+xEIyNTUVsUGY1LPwFTxEXuKRI0fst0V1vld5OfDww0BpKbBoke7CVzCJNuHLU7i9EYUvSZKQlJSE4uJi1Tlf7Pjywptvytdzc10KX94cXyUlJaisrATgtO4U89EobRroU7g9w4Qbak8EwRS+lM+jXPhGdchgcTHQq1fkWmyF8HXzzcCHH5LQde4csGMH8NVX9HdffTXQoAHdb98+YPZs4PPPQ3fMkc6GDfJ1m0MgWISd8LVqFYleAC2YrrmGFk2McTh6FPi//6NziYcmQdGY8RWsjo4CNcJXVI/3OuL82ldVVWHt2rUAolT4mjIFsOWbQSEGGhEtwpcQTMJW+MrLo6iLSZPc3iXSwu0B7QH3LHx5IC8P+PJL+Xun+aNao4dwe5nNZvtnzOHxfGhOGAmw8MVEBGpPBOLnweoUKo7r0KFD9ueNidFktIwsVq6kxferrwIHDoT6aPTFapWFr/795dvNZuCCC8iu/O9/U7ldXh5w4gTw6KN0n19+Cf7xRgvr18vXDx4Ejh0L2lML4SsvL88h9DUkIkRVFTkEAOD224FrryUn3JAhwIIFwTuOYFBVFbm5ep9+Kv9t+flu7xbJGV9Hjx51WYEQrI6OAnZ8BQ/x2hcUFKCyshKbN29GSUkJ0tPT0bZt2xAfXZDJzaUsUcGxY4DN2WFExDzZ8I6vrVuBnj0p5uKVV9wGiIvz0/nz5+2B8GKDwqjClxCwtGZ8camjC957j+YwAifhS63RQ1nmKEmS/AMhlLPji2GMS7g7vkTuXdSXOdq62cFqBd5/P7THojd799IAFRcHqMkcqV0buPdeuv7bb1QOqSerV8v/72hG6fgCgur6ql+/PsxmM6qrq3HMJrhZLBb7Tm9QRYh33qHS24wMYOpUYM4c2pkuL6fL+fODdyyBpKAAaNwY6Ncv8sQviwX4+GP5e5uY5Qox1pSWlqK8vDwihK8GNqdseXm5g1tCEMyOjoAfwtfevcDw4cDmzQE9vkiidu3aiI2NhdVqRX5+vj3f6+KLL4bJFGVLmbFjybF72WU037BaPYrg4Y5wo6gJ6xbCV9g5hZYsoddDiArFxYCilFFJeno6zGYzADpnFSo6Tht1jaDV8SXuF3avY6gpLpZd+S1b0qWfji+H91RJCWDbIGLhi2EMjC4ZX6dP0yIwAMelWvjatQvo0YPCuCMR5UJtxgz9xZ5QItxevXpRmL0aOnSgwaesjCZOerF0Ke083n67fo9pRCwWCgkFKEsNCKrwZTab7Yt1kU1z+vRpWCwWAEEMGj9yBHjuObr+6qtAnTpAfDzwzTfA9dcDFRV0GQnnnWnTaBH455+UhRVJLF0K7N8vf+9B2E5LS7Pv8ubl5aHMlnNnZOErLi7Ofvyuyh2DXeooFuyaha/33qPS97vuijxxNkCYTCb7uTQvLy96g+0XLQLmziUn+XvvUbdiwNDljobP+PriC2DQIODsWZpniHPswYMu7y5JkkPAvXCqpqSkBCWbMBBoEb4sFot9PGLhy4nZs2kt2qIF8MADdJvTZ1ttuL1L4UuIaCkpQJAqn8INFr6YiECt48ttqePp00CTJoBTx1J/0Sx8ffABsG6dY7BhJKFcqJ05QxOGSEEIX1rCwiWJSs4AChrXC5EZtmwZ7SBFK3v20N+fmAjYOg8HO+dLhDKLnC/hvKlVq1bwJrmPPQacP0+i7H33ybfHxQFffw3cdBOJXzfeCHz/fXCOKRCUl5PwJXjmmcgS15VuL8Cj8GUymezj3B5bFlh8fLxj1ocB8ZTzFapSR+cFe1VVlX0B6FL4EtlsmzdH1hjoKydOAC4cfM4oX/uoDLavqJCbs4wcCXTsKOf0sPAVfKxW2ki64w4qNb3pJnLvt25NP/cQ56EMuDd6vhegTfgSryHAwpcDFou89nv0UVqTAm4dX+fOnfPYdNBtR0eANtyV5Y9RBAtfTEQgTgTFxcUOWTrOuHV87dpFC8NVq4Djx3U/LtXCl20yh3XrInMnWDi+6tWjy3fecZuDEFCOHweefZayMvTAYpEdW1q75CmFLz3+F1VVsnhRVVWzk2Q0IcocO3emMgSAPlsVFUE7BOeA+wKbWBE05838+bJDYPp0wLksKDaWglRvu40m7zffTPc3Il9/TZ/thg1p0piXB7z1VqiPSh9OnZJfl6uvpksPpY6AnPO1e/duAPSekww+2VXmfDkTLqWOyp14l3miyqYEzzwjd52NRlavJndDx45eHfdiE2H9+vU4cOAAJEnCxRdfHIyjDA/eeovmqnXrUldeIKKEr/LycnsXOneEjfBVXU3io+is+/jjNP4kJADNmtFtKoQvpeMrWoQv5X1C/jqGE7/8QmNDejo1sBGliG4yviorK1Hu4Zzp0fEVpWWOAAtfTISgnFx62jVyK3wpdxv/+ku349IkfJWWygv1c+doghMKDh+mBfLLL+svEIiF2pgx5MLZvBlYvlzf5/CG1Uo7dC+/DDz1lD6PuW0b/W3JycBFF2n73X796H9x5Ig+mS/Lljm+n4P9/w0nxOepa1fahc3IoEXm338H7RCchS/h+Kpbt27gn7ykBBg1iq4/9hgtLl0RE0NlgbffTmLprbdSGaSRsFplkWvkSAoXBqi7lheByBB8/jmdj7t0Aa66im7zkuEnxhvh+DJymaPAk+MrXLo6ijLHpKSkmq7Oqip5QZyeTpsvkZZ3qZbNm0nEPXeOupV6KfcXr/2cOXMAAO3atYue5gF5ebLY9eqrgOgWGkHCF+BdOAkL4aukBLjhBnIXSxK5dN54Q95UatqULt2UOgLyOerkyZN2gSJahC9lZ07D5/OdP0/rJZGb5Q9vvEGXDz1EpYhCnMrLo811G8rPi6cqJ4/CV5R2dARY+GIihPj4ePsE01Pds/hZDeFLGUIZAOFL1LN7FL7WrXPszBMsp051NZV/Pf000KkTBUP/4x/kiLJNMHVDLNTatCHxCSDXVzD59FPg99/p+i+/6JPrJsocL7+cyse0kJgIXHklXdej3FG4QoQY/Oef/j+mUVEKXyYT5Z4BQS13dCd8BUWEeOUVWmQ3agRMnOj5vjExlC8hcoduv92xpXa489df9HonJAAPPkjh4V270qL6pZdCfXT+YbXKZY7330+OD8Cr8CUcX3v37gUQ+cJXuHR19JjvdfgwjfPx8cDkyXTbK68AioDrqGD3bmDgQIo8sAV944cfPP6KeO3F+zmq8r3GjaOy/V69gLvvlm+PAOErLi4OcbZ5k7dyx5ALXydOkKv/xx/lnMzHHnO8jwbHVzSWOgrhKyLKHP/xD/oaNsy/Kp0NGyjDMyZGLmeuX5/mrZWVDmO92Wy2/789rXfZ8eUaFr6YiMFbzpfVarX/rEb5QYAdXwKPwpfz865Zo9tx1ODsWeDbb4F77qGyw0suAf79b9qBNZlk0USvUkCBcF7UqSOf3OfNox2NYFBQADzxhPz9uXOyCOYP4jG0ljkK9Mr5qq6m/ydAJTQAiTzK1sjRgtXqKHwBtGgAokP42rFDXli//TbtIHrDbAZmziSbfXU1cOedcl5cuDN1Kl3edReQlUXnMfH3T5tGnfSMypo1wNatJOrdfrssfKksdYw2x1eoSx09Cl+izLFFC/qctWtHboFXXw3osYYVubm02XP8OJWhiyYUP/7osdxfvPaCqMn3WrqUmiFIEvDuu47l6hEgfAHqc76UbiG/+N//KO/ymWdojFu3juaDnti7l+YQq1cDmZmU53XTTTXvp0L4chVuH23Cl/gdw7JypTw/+vNP4PXXfX8ske11yy3yZzomhsQvwG25o2bHlzLjK0ph4YuJGLx1diwrK7Pnf3l0fG3YoFsgsvPzeBzYRL6X2MXUW/g6epSstP37A7Vr0wl29mz629PTqbzps89oMvrQQ/Q7XhwFmhGPV6cOlV317k0L7OnT9X0edzz2GC0yOnWS/0YhFPlKVRWVFwK+C1/XXEOXq1f79z9fsYJev/R0EhZr1aJd4k2bfH9Mo3LgALko4uJocQlEj/BltdIuZGUliarDhqn/XbOZ3EX330/2+rvvDv/uiIcOAd99R9fHjJFvv+IKKqWqqgImTAjNsemBcHvdfDN9psV7R2Wp4wHbAizShS9DOL6EANuyJS1sJk2i76dONbx4oYrjx0n0OnyYnN+//kplYykpNEdZv97tr0al8FVZKZerP/ywvIkjMJrwlZtLwd3r1jncLIQvbw2q/HZ8nT1LgvPgwcAnn5Db8q67qJt6WhrlQ15xBfDII7Rh9OuvNL6sXEnzh337qJTxr7/k3FBnRKnjoUMOJWpKotnxJe5jaMeXxULvYwC44AK6fPZZuYu4FvLySNgGKCtOiZucL2/rXYBLHd3BwhcTMXhTwJW31+hspXR8VVYCa9fqckyqHV9Wqyx8Cdv05s2U+6UHVisJak88QWV5VVV0sh43jnI1TpygE++dd5Iolp1Nv6dj0D8qKmjSAciOBTGh+/BDfUoOPTF/PpVumUy0kLzlFrr9hx/8tygXFdGCtHNn3x6jYUOa0FqttBPpK6LMcehQcodceil9H405X8Lt1aGDXH560UW0a37oEJCfH5TDEMJXfn4+KisrgyN8ffYZibGJiVRKrDXQ3GSiDrMPPUTvyYcf9r4bHkree48mov37Axde6Piz116jv2fOHGpeYjTOnZNLTkV7c3H+PHXKo5tTOL7Ehk+kC1/BdnyJeYRPjq9WrehyyBBaQJeVeS9HNjqnTwMDBtD/oEkTYNEiei/Hx8u5dR7KHZXCV0ZGBlqL7nmRzLvvUoZoVhblkjojFrBHj4Z/Q6SVK2kMfvvtGuXnah1fQvjySTRZuJDGh1mzaEy8/34a4/r0kee8Imtu2jQSNq66ioSsSy6hTeJu3ejvEGKHK3JyaAOpvBw4dszlXVyF23ttfhXGRF2p4+zZtE5MTaX3y7BhtHa8807t67b33qNx/PLLge7dHX8mPt9uHF9c6qgdFr6YiMGbAi5uT0lJqRmoKBxfYoGoU7mjauFr925axCQkkGiRnU0nQr2cOjt20GI/IYF2lvfskUuh+valzm5KVGbIaEL8j81mOZh12DASfQoKqPQyUJw/Tw4YgITF7t3JbZaZScfljzAk8r369ZOzSnzB33JHi0UWvm68kS7FjmQ05nwJ4atbN/m2tDRZGAmS66tu3bqIjY2F1WrF0aNHAy98nT5NgjYAPPecvPusFZOJJv+tW5MDVnQKDTeKi4GPPqLrzlkrAL3eI0bQ9XHjQtNF1h++/pr+xtat5c9zVhaNVVar46aNE0L4EhhC+Dp7lhbG48a57HYoxI+TJ086dLSqqKiwL5oN4/gC6HUUZY4zZwLbtwfkWP2ioIAcxNnZJIL7EoFw7hy5bLZsoXiF335zXHxddx1d/vij24do0KCB/XqvXr2MH4ztjWPHgOefp+uTJtF8xZnsbJp3VFe7FVnCgs8+o7mm2Ex1Eq61Cl+aHF/nztH7dtAgcsa1bElzoo8+omqDpUvpf3fmDG2OzJpFDuHrrwfatpXnx0OG0H1FV3J3xMTI72035Y7KcPtIcHwJEatERbWM4YWvoiK5m+dzz9H74cMP6bO4fbs2d3lxsVzxMnZszZ+L95GTo9OnUsdz52TzAQtfDGMQrFYanFyg1vFVo8wRkBcPosww2MKXeL4ePcidIjoD6lXu+McfdHnJJbSLJSbd7giE8KUscxQT1thYmpAAgQ25f+YZmqw3bQq8+CLdFhMjT7ZFmZQvCOHL1zJHgRC+fv3Vt26aa9fS4JiSQqHBAO0gASTsGW3B7y/O+V6CIJc7mkwmNLLt2h0+fDjwwteECeTgbNfO9URKC5JEmVIA8MUX/h9bIJg9m0paW7akhbUrXnyR3G9//eU1QFs3Nm2irJdp0/x7HGWovdiYiYmRF8Eecr6chS/hMghLtm2j8qKGDWmMmjKFRD8nMjIykJCQAAA4evSo/XaxeJQkqcbfHSiE8OW8WNfk+AJoXL7+etq8CKeS3JISKgVr2ZKcRwUF5ARt2ZJeKycXglvKymhDT2QjLVpUcw5yzTUk4Gze7FYsSEhIsL+Ho6LMcfx4Wqz26EF5VK4wmwEhCIZjuaN4T999N81rxHjsJNIFTPhatoyiLT74gL4fNYrOzcINr6RWLeDiiyn79t//phiM7dvpc1BQQKKsmqxMQN5wcvNe5lJHA2d8vfIKCbitWsnRCnXqUOksQN2lFy1S91iffkpr2hYtSFh1Rs9SR3F+SE8np1qUwsIXYyxeeIF2u12cVLxZPz0KX8KNJISQFSvc1uZrQbXw5ZzvJYQvvTo7CuGrd2919w9EqaMy2F7Jgw+S2LdmTWAC/desIQcBQDsrysH2+uvp8rvvfBOGystlt5i/wle3bvR/P3fON4eW6MB57bXk7API2RYfT5M2seCKBlwF2wtCkPMlhK8jR44EVvhauZJ2HgESXLR2GHWFEL4WLdI/889fLBb5sz16tGPos5KGDWUR8KmnHLvnBooPP6R29mPG1MizUc2WLTQGxMQ4dnIDVG1OOI83Yef4qqqic68oUZ02jXbAxft2584avyJJkstyR1HmmJGRETQnkGbHV3U1sH8/XXcWfv79bxIxfvwx9KXp1dXAjBm0sHvmGRqTunWjhV2/fvT5mTaN/oaRIz0LLpWVlE23ZAmJBgsW1CxHBkgQE45GD66vtm3bAgCu8He8DXeWLyeXlCRRKZSn93S45nydP0/5bf/5D30/YYK8yVhQ4DDHViN8Wa1W9cJXSQk5gPv2JfGpSRNqQvTOO45zQDXExNSct3pDBNwfPOjyxwEPt9+wgaoc/v5bv8f0QNSUOu7ZIwfRv/GG4xxr8GC5smTECHLfe8JikR/rscdcV4y4Eb7UNHOrIXxxvhcAFr4Yo/HDD7SodSGQCJHJ3YlACGI1OjoCsuPriiuApCRyEOzY4ffhanZ8iV0oPR1fVqt24UvZNUwHARCAo+PL+blE3ta77+rzXILKSnJKWK3AHXeQ1V3JgAE0CcrNlYUSLaxaRfX82dlkifcHk0kOudda7mi11ixzBEj0Eu+lUC+mgkleHr13zWbK+FIihK9163xz1vmAyPnKzc21C191xWdML6qqZPfkiBHqP+veaNWKHAfV1dS6PZxYuJDEkdRUuZzRHePH07ln927ZRRVIfv2VLquq6NyjYkFQgxkz6PK66+TNCIEK4StsSx1PnqTFcIsWtDBevJjOf9dfT9dfe43ut3u3y1/3JHwFq8wR8EH4OnyYxqS4uJqLjwsukF0948eHxqFrtQK//EIOmfvvp7yjpk3J7blmDYWCL15M5V59+9L58/336XUcNapmd+bqahJsf/6ZNmN+/pnOJe4YOpQuPQhfn3/+Of73v//hErFJGIlUVcn5p/fd5/l/Brgthwophw7RfPaHH2ge8tlnJO6KMsHKSofqDTFX9iR8VVZWwmKbj3oUvlaupLzVt96i7x94gJyEwRRLvXR2FI6vc+fO4ZjN/aaL8FVSAjz5JL1npk+nOBGdmnV5ImqEr3Hj6L171VXyfF3J669T046jR0kE83Qe//lnKn2vVcv9/MVNxpc3x1dpaSkqbPPbGo6vKC5zBFj4YoxEaSntgAMuyzt8dnwpc1Lq1SOrM6BLuaPzc7kswTh1St7ZFotyMdHZt89jhosqDhygCWlsrPy3eUMskCwW/59fIF4zVwv+0aPp8uuv9XWVTJ5M75msLHlnRUliInV9A3zr7qgsc9QaIO4KUe7400/aFj6bNtHrrPx7BKLcMZpyvoSI2b697H4TtG5N7oLy8qB1uxTC15YtW+xB47qXnb39Nk3uMzJk4UAv7riDLv/7X30f11/Ewua++yi/zRNpaXJezsSJgQ3r37uXnD2xsVSGtHs3LUa0UFYmd9MUofZKxDlaQ6ljyIWv9etpgt+oEbk/cnOpmcqECXT+mjePHEUitNyNS9WV8BXsjo6AvNirrKxEpcJF6Fb4En9Pixaud/eff57O4StXBq8kV7BuHY1j115LZacZGeRo2LkTGD7c0XHUpw85uJYsIYG9ooJcSS1akMPx6FG5s+xXX5FjZu5c+j1PCMf9smVuIy0aN26Mq0QQvjdKSug9JXLVjML06eTUyciQu356ItwcXytW0Ibb5s0k2C9dSqHfAIm+QuBRlDuqcXyVKkLDXQpfZWXk6L3sMvqsNWxIzYI+/ND7+KA3Xkod09PTYbadA8T5wm/ha9EiclO+/jrN3RMTyXEm4j0CSECEr+pqOpesWUNOwXfeoWytu+6icaJ9e9fz+kCxcCGJ8jExdG50NedPSgI+/5zu8803nudMb7xBlw895L6EVohUTs0rvDm+CgsLAQBms1leh3KwPQAWvkLHwYP0RmbUs2mT/MF3Mdn35vhyK3wVFcmdsbKyZNeVzsJXWlqafaBzQHQaa9OGFgEATXjE5N/fDpPC7dWjB52U1RAbK09O9BKi3JU6AjRJuugimkCLoGp/2b1bHvDffNO9Vf2GG+jSl5wvvfK9BFdeSRPDffvcuh1cIsocr766po0/GgPu3ZU5AjRZ6dmTrgep3FEIXxtsx5WWlob4+Hj9nuDwYQpZBUj00lvguPVWWviuWiWXaoWanTupbEqSZOHcGw8+SA62ggISxQOFcHtdeilleABUGvbLL+of47vvqFQiJ4ecqc5odHyZzeagZV+55NZbqfT6009JdO7WjUKkDx8mJ0jjxvJ9lcKXC8exJ8dXMHNylBk1ygWfW+HLOdjemQYN5JLcCRM8duzUjQMHqJy5Rw8SKOLjSaTdtw94/HH63h19+9LvLF5MGyzl5bQ4bd6cFqYffUTnjS++cJ+/p6RFC1rMVldTF2Z/GTuWHNCtWtF76rHHaPHqomlCyCgvp83FgweBrVtJ9Hv2WfrZyy/Lc0JPhJPwNXs2vfYFBeQcXLNGHm8FwvWliNIQwpensG4hmEiShDhXZfx33knjn8VCTsMtW+RuocHGS6mjyWSqca7y+dx16hRtKAwcSJ/nnBxyE331Ff18yhTZNBAgdMn4ysuj161nT/ob4uNJvLz4YpqnjxlDjUA+/5zOO9u3B0/4qqyUm+eMGuW5wqN7d3mTbeRIcj86s2EDfdZjYmR3pyvq1aP7ODWv8Ob4EmWOtWrVgiQEOi51BMDCV2h4/30ahMVChVGHMifFB8eX21JH4WhKSqIdEiEU6Cx8eS1zdLbu61XuqLXMUaB3zpe7UkeBOPlPm+b/hN9ioUVueTktGsVuoysGDyahb8cObeWtxcWyaNm/v3/HK0hNpcUEoL7c0WqVhS9lmaPgkktIHNi3D8jP1+Uwwx5PwhcQ9JwvIXzttDk7dXfe/Otf9H7s1Qu49159HxugyZd4j4dLyL1ohjFkCC201RAbKzsopkwJ3OaTEL4GDSIx+/HH6ft771W/kSDKMe+917U7SGPGV+3atUPXBe/4cblM9o476HO3di2FSDs7MgHK44mJIYHCuXwO4VPqGBcXh5iYGAAqhS9XwfbOPPkkbcDt3EldHgPJm2/ShtuXX9IYcdddwK5dJB64m684I0kkdCxbRp0aL72Uxt1ly+jnH31EGV9qUVHuqIoTJ0hYBejzs2cPOUQHDaL/73XXkbPK1aJUb77+muYhF19Mwl7jxrSxGBdH7//atUko6dCBxv/CQqBLF3KCqCEchK/qanJb3XMPbWBefz3FKygFbYGYW/ro+EpMTJQX8wJRpguQy+bTT9W/hwOBEL5yc93OZ5Wu7/j4eG2dKgH6m7/6ikSYTz+VN4G2baMyvOuuo9ehqoreS3rFlrhAF8fXrFnkcl69mt7L1dX02W3UiMSwG28k8eu11+Rsz+PHg1MWPm0arQ9q15ZFLU/88580Hysqos+Ewq0FQBbsbrnFsxClbF6hKHf0tt6tke8FcKmjDRa+QkHXrqQez5oVuYHT27b51vLaE0rnkwijV+BNAXfr+BKPJQahnj1locDP9tDJycn2Adrtbo4ItnfuMqOX8CWcPlqFL707O3oqdQRoAKhThxY633/v33N98glNvJOSqJuPpzLE9HRanALaXF/Ll9OEomlTeZKjB6LcUa3wtW0bucPi4uTfVZKeDnTsSNejJedr/Xq6DDPhS+ST6Cp87d4ti1Fvv+05BNkfRMj9f/8b+g6hZ87Ii9pHH9X2uzfcQK9/SYm6CaxWKiqoBAyQMwX//W8qQSkokDMHPbFvH7loJIlylVyhzGF0g9LhFdIyR/E5a9+eduvFGOuOmBhy/wAu50jhUuooSZLLBZ/Pji/6Jdnx8/zzvmXDqeGbb8gRVVlJ49/69eTWadLEt8eTJBLH//yTSq5uvJE+o1qFeCF8/e9/JKD5yocf0u93707OyXnz6LPXoAF99n/6iUoxmzal9+WTT9Ln1nmB6i9WKzlFfvuN5nLbt9MC9swZxyYbCQk0/2nWjNx3M2a4FrxdEWrhS4TYixL7p5+mzTh35VseHF9qhC+XJXJnz8pOPtG0KJTUr09zsupqt6+L8lyVkZFRU8zzRG4ubfoMH05jQPv2tJZ4+23Hjn1vv02vw8qV+lVTuEAX4UtszN5+O31W8vLoM3z4MB3/nDkkXj/5JH2WARpvPXQ21IUTJ+S5wiuvUCaXN2JiSMRLSaG1yJQp8s/y8mQ3ntgU84SLnC9vpY4uhS8udQTAwldo6NmTFqjV1ZQ1EmkcPUqTjb599d1hUApfHhxfmksdheNLDELp6XIgtp+uL0mS7AO6S8dXZaUsbLlzfK1e7ftC8+hRmmybTDUf3xvBdnzFx5NLC5DdHL5w7Jicp/Pii+pEKWV3R7X8/jtd6h2YKgIz//yTdn69IULtBw50n2Mhcr6iQfg6doze95JEpRauuOgi+kzk5gal5DzHaaKhqwjx8st0nh0yhM67geKGG+gzunNn0LLR3DJjBi1eO3Qgt4kWJIkyUAASyLdt0/fYVqyghWDduvL7LyGBBMO4OFpwe1uAiFD7gQPdCxHiPeRhYyI5OdleXh8WwpeWMUi4olyUfIdLqSMgL/iUC3avji9PwhdATSqaNqWFoMix0xORtQbQwmvhQnIY6YEkkZA2Zw45HbTSvTuJBufOUTmTL4jMMYBEp7Q0GuM/+ohEiE2bSIy+7DIaB7Zvp3PCFVfIDUL04sgRGpPMZppfLF5Mc9kdO2ghWlhI88DSUvos799Pc0Itr4dYGOflBdTV45ZnniGHXnw8nedeftnzBowOjq8aiMdKT6fKjVBjMsnnbjfljkrHl+rzVnU1zY/btyeHW1wczXM3bKhZUgrQe+Pll+n6P//p92a+O5TCl9XLesVtqaMYy3r1IvG3QQP34m9ioizw6dl93hXPPUef006d5AYkamjRApg6la4/84w8b3r3Xdo0791b3ZzNRfMKtaWOLoUvLnVkQsJLL9Hll19SXX8k8ddftPNy4ADZ5vWgqMjxsU6cqCEGeTsRiNu9Or6AgOR8uRS+Nm2iCU9mJpUcKOncmUpzTp50O3B6Rbi9OnemCYEWgu34AmjSaTZTeebmzb49z5gxNEh166beDTJ0KE3Y161T71TUO99L0Lw50K4dTXBEyZQnXHVzdCaacr42bqTLCy5wv+OcmkoOHCAorq+srCwkKEq6dBMhdu+Ww1MD4V5SkpZG4hoQ2nLHqiq5++ujj/rWVOKSS0jIs1hoMaAnCxfS5cCBjou/jh3lMsvHH3ef4VdVJZe4uQq1F6g4P0uSZB93wkL4Ek5LNQjhy4Xjq4Gt9OPo0aP2RVYoSh0B104Hl8JXdbWcj+ep1BEgAeGVV+j6q6+6dLj7TH4+jXelpZR/NHmyPo1Z9MJkks8zvpY7fvst/Z3169cssxQbIhMm0Hh48iSVIor7aW0s4w0R0XHhhdRhr18/WuxecAEtQNPTyR3iD/Xq0f+tstKjAzRgiDy2WbNkZ7An/HR8uRS+hFuofn3vzx8sVHZ2BFQKX4cO0VxuzBjaXLnsMlpDPPssCWDuGDWK5sOFhXKGoM6I86DFYkG5F6emW8eXGMvUdrzWe3PeFX//Te5RgNxzal2Ygnvvpc99ZSVFrpw6RSXWgPrXQghf/ji+iorkhj7s+GJCQufONNBarZGX9aV0ZukgHAGgHUqrVd7lLi+vUQKg1vHlNuNLOWEOlvAlHr9Xr5o7ZPHx9D4BfC939DXfC9B/UPEUbi9o1Eh2X4nFrRZ+/JEmvWYz7e6qnVDWrSuLQ2rKLM+ckXOktDpO1KC23HH3bgotjYmRO2K5Qvxtf/8deFt4qPGW7yUIYrmjJEkOri/dRIhXXiHx5tpraWIbaER3xy+/1L8kSC0//EALgKwsdYssd0yaROeJn3/23VniCiFWDxxY82ePPUZCeUkJTYKVpU6C+fNpV75OHVkAcIWKUkdALncMmfBVUSHPCbQIXyLg3oVAKISv8vJyu+AVilJHoKbwVV1dbV+8OwhfR47Q/yIuTt3C47bbyPVTVCSLYP5SVkbja14eCS9ffaV9IRcMxFj244/aRSirVXZZPPKIZ0EAoByoW26hjCSzmeY7epYMivd+IN24sbGymBTscsdjx0icliT1QfIuHF9inhxNwpfyXKVK+HryScqVTU2lzKllyzyHrAvMZor8MJlo7BabMzqiFLGEsOUOwwhfVittrlksdI7wZR0lSSScZWeTu/zSS0mAbNnSdTSJK1wIX5odX+J3MzJqNsCKMlj4CiUvvEAnou++cwxuNzrKv0Wv0ioxeejTRw7DdZrw65bxBcjC14YNtEjxA4/Cl7t8L4G/OV/+CF96Or7KyymDAfDecU50aPv8c7ctzV1SVEQTXQB44gntpRuiu+O8ed7vu2wZDYpt28rBk3oiBsT58z0LDMLtdcUVchdOVzRsSJMwiyVouVYhIwyFLwD6C1979tBnBAi820tw9dWUb5GX5797sLKSXiutjSxE6dfDD/tX0tK6tRwePW6cPiVCBQXy+8+V8GUy0QK7Vi0a04TzW4kItb/nHs+LdvEeKiwkQcUNIRe+/v6bBBdlp2I1eHB8xcXF2f8eUe4Y6lJHIXwp5x8Owpf4O5o3Vyc2mUzk9gKobM/N4lk1VitFCaxeTa/Fjz9qd4EHi/79aXF25Ij8eVLLypU0B42PVx8OD9C5RGRh+purqkTMh3v00O8xXRGqnC8xDnTsqC77CIgex1fTpnSpV6mjyC6dO5fGPy15nt26yXPrf/yDHJ86Ehsbi9jYWADec74MI3zNnUtz/YQEOb/OF+rUoVgFQK5cevRR7Rl+/oTbc5mjHRa+QknbtnK3ORFmanQsFvnkDOjn+BLCV48e8oTfSfjSLeMLoNr8Bg1oUaZ0sPmAW+HLanXf0VHgj/B16pRcRiscP1rQU/gS4mJMjPfJ0eWXU3ZPaak8WHhi924alHr3pgV58+a+CQHDhtHln396LxcIVJmjoFcvWpycPi13jnSFEL5uusn7Y0ZLzpdW4Wv9eo/CgV40Ukw46qqd2HlCuL2uuSawbgIl8fHye02UWPrKiBE0GW/VisQsD23s7WzYQJ/PmBhZ5PaH55+nctj16/VxfS1aRJedO8uTcmcaNaLdd4BeQ7H5AdD5S3Qm85YlkpEhT5xVBNyHTPhSljlqWagJkWzfPpfiqHPOV7iUOooyx8TERPtCEIC6YHtnBgygvKzKSm0dQV0xeTKFLZvN5Ir2Vm4ZShIS5MYQWssdhdvrzju9b7I5o1dDIYHVKgtfgT5Hh0r48mVzVQhfLjK+3M3fAQMKX3o6vkpK5MfxNY/vpZdoE3T/fjn3S0fUBty7zPiqqpLXYmo/t4EUvkpLaUMMAMaP973ph2DwYBIcAVoDiYxFNXjI+Dp37pzLTLUawhd3dLTDwleoee45msQvWBAZC9Ldu8l5Ex9PFs+9e/U5KSmFL7FL4sbxVVJSgioXE2WhjNcodRSijHLCLEm6lTuKRW595wFZBGvHxLjfDRQTsfXrXZfFeEK8n9q21T4BBPQdVMSEvXZt74sf0ZIZAN5/v6bjSUwmn3mGAj7btKE22n//TRPmjz+mbo5aadqUJhQWi/fJdqCFr5gYctcA7ssdDxyg94XJJIt2noiGnK/Tp+XdVVEm7I5WregzX14u54IFEF0dX3v3Bt/tJRDlhXPm+N51beFCOSfs4EEqAczJoQmmp4WbcHvdfLM+Tsu6deW/59NP/X88UeYoFu3uuOUW4K676Fxz552y6DdrFt122WVUiuYJk0lVwP3//d//oVu3bhg8eLC6v0FvfMn3AmiBlpBAC6JDh1z8WBa+rFarvdQx1I4vr8H2WgWnyZNpPrV0KeVE/fCD9oP8+Wc5y+6tt8hRFe6Ickctf29uruzY1trtFdBf+Nq/n1zrcXFyw6RAYSThS8wtCwrs8zs1ji/hFIoU4UuT42vnTjnuRVmdooXUVDlC5LXXdG/solb4cun4Euswk8lz9YISsYEYCOHr9ddp3GnUiNYXej3m+PE0d3OXP+sKMXfMz7dvAol1bHV1tV0QVuLW8cXCFwtfIadFC7nd89NPh75NvL8o8wzat6fryh1tXzhxgk5AkkQOATHZdwp8VTq5XA2eXh1fzoOJEAr8FCRfeOEFvPLKK7jZOWRVCGpdurgXalq3pnKE0lLtg5Q/ZY6Avo4vNcH2Su64g3ZF9u+ntuaVlSQ2jR4NNG5MQuErr1A3ppgY2hl//31yB/iTuSXKHT11dzx2jF4LSaLS20DhLedLTPB791YnbArH1+rVQXE4hQQhYLVo4d1ZKElyF6QglDvqKny9/DItGAYPDnwJjTO9e5MoUVhIn02tlJdT2C5A5RrTp9N57uxZWuQ3a0aff+cSp+PH5Rbgvixq3SE6z82dS4HBvmKxyNkp3oQvgDpzNWlCiyKRIyK6OXoKtVfixv2s5Pbbb8e6devQVJTdBBsx/msVvkwm1Z0dS0pK7IHKwXZ8iQW7V+HLF8cXQAL+qlUkep04QZsc996rPqtx2zZg+HCaWz70kD5OyWBwzTX0Hvj7b/XNfd57j86LV1zhm9AkhK916/TJMBRur06dvGeN+UsohK8zZyhjFJDnF2qoU4fGX4vFPv+O6FLHo0ddbhJpEr7E/F+sq3xl2DASlauqaPzVWuK/ejW5UPv1q+HE9Uv4Um6Oqy0BDJTj6/BhuRHN5Mm+baS7IimJytdF53a11K1LOX4Wi70LeXJyMiRbUxJXLkkhfAnHN5c6yrDwFQ48+yzt6P3xB/Dbb6E+Gv9Q2rqFY8pfJ5sQ09q0oc5ibib78fHxiLNNLlzVPWsqdQTk41+50q/8lzZt2uBf//pXzda93vK9AJr4iYWt1l1If4UvMaiUlPi3IATUBdsrSUqSS30eeYSOpX9/2q06coR+fuONtHNSUEALzn/8w38XiAjWX7TI/cJiyRK67Ny55ntGTwYNognA1q2uJ/5z5tClmjJHgD4/tWtT3o6yHDmQWCzBFdnE3+WtzFEQxJwv3YSvULq9AHpP3nYbXfelu+Prr5P7pV494D//ocX4jh3UTa1vX5pMf/EFbXL060e3WywkkFVUkFh58cX6/T29epHAUlwslw77wpYtNAFPTnZfuq4kPZ1KzySJujiOGUMiWFqa+s+03p139eboUXLhmEyyqKAFDzlfSuFLlDnGxsbaF9DBQozrYsHu1fGlVfgCaKxZt47CrcX7pWNHyp/xxMmTtMg9f54+W++8E14dHD1Ru7a8+fjTT97vX1wsd1977DHfnrNtW/r8nj9PDht/UVYqBJpQCF9//UWCaps27ku7XRETI28028odxee2rKzMZcUGIAtfNbKhgPAUvurUobmq1eqyW7hSpHeZAaxk+3a6bNfO/+N65x16ny9fri5OBKA56PDhNP7+/js5UJ02JPwqddSa7wU4Ogf15MUXyWxw2WXArbfq+9i+YDLRZiNgF7BMJpP9M+Nqvculju5h4SscaNSIlHeAyreM7PpSDvR6dUZ0njy4KXUEPOd8eS11dHZ8depEg0NhoTzo6Im3fC+BL/b7c+dkx4SWnTglyclyeLS/A4v4fS0L/kceoUn64cO0s5iVBfzf/1EZ4smTJPzccQdl3ehFu3bkPqmocO9mEWWOgS4XycyUP0POrq8jR+TsLyHWeUOS9HExHjtGZWFTpwITJwKPP06vy/XXk1DRpQu5djIyaIKbkqKuU6YeqM33EhhR+HrlFXIjXH21b2KCHojujj/9pK1L6MGDcoe611+Xw7VNJnI4LllC4uUdd9B7Z+lSWri3bUuTdUBftxdAnwvh+vKn3FGUOfbtSxtZarj8crkE7b336PKOO9TvMIe78CU+Vx06UJmNVjx0dlQKX8oyRynIwo6qUsfqanIjA75na8XHU3nSsmV0fj10iM6348bRZoYzlZVUErx/P93/22/JNWAktJQ7zp5Nc7UWLbQ7KgRms5zFpUe5Y7DyvYDQCF9ic9WXOaZTwL1SsHYnnKhyfInHDQckyWO5o0+OLz2Er8aN5cYq48d7Hj/OnqVSP9EFVpJk96KT00oXx5cvwpfeji+x5hw3Lnw2ClzkfHla73Kpo3tY+AoXJkygye6aNep2t8KRykq51KhHD3mRvWGDfx1EnIUvN6WOgPvOjhUVFaiwOU8cHF9Wq3vHV0yM7CzQK6RfcO4csHkzXQ+E8LViBbkkmjXz/UQnSfoNLFpLHQEKqf/0UxqYly4lweWTT4AhQ/zr5uYJSZKFJHfdHQOd76XEXbmjKMW85BJtLjd/c74sFnKijRhBgtcLL5AANmsWiVtLlwKbNpHAUVhIn6/KSmqhHQyE8NWtm7r7X3QRiS6HD1OweABp1aoVGjdujIsuusj1xF0N+/aRSwgIjdtL0LkzTYTLyjyXBTvz6KM0FvTtK2drOdO1Kzna9u8nh0t6Ogkfp07RrueNN+rxFzhy11302V+yxGWelCrU5ns5M3Gio1B7//3qf1dFqWNI8TXfS6DR8RXsMkdApfCVl0ebKbGx/i88Lr+cyv/uv5/Or1OmkLDinFM4Zgydj1NSaE7pay5QKBHC17JlNJ64w2KR8//GjNHWRMEZvXK+qqtlB3KwHV/B2jz3p6pAzC1tjtDhBZgAAIWLSURBVK/4+Hh7Mwh35Y5uha/SUrlreDg5vgCPnR1r1aoFk+296lX4Epvv/pY6CkaPpnH8zBnqgu5MZSVtxrRsSYJ7eTnNeTdskM/nPghf1dXV9rL0sBW+hIjauLG+j+sPYtxQdHZ0t94FnIQvq5VLHRWw8BUuZGfTgA1Q6aMerdW9sXgx1WqL7Al/2b6dFkLp6XSybNqUBqHKSt87I1qt7oUvDY4v5fcOwldxsVx772piqJdrzZnVq+k1btJEtrC6Q0zEtm1TX3Lob5mjQC9HgS+OL4AWpK++SllaMTH+HYNaRM7X/Pk1d9IPHqQFeUyMb50ytSKEryVLHF97rWWOArEz+9dfvp1j5s4lwTYlhcrdHn6YHCv/+Q8wbRoJXP/7Hy14d+yQj9NTZ0q9KCqSF8hqux6lpMhZMAF2fSUkJGDPnj34y59zidLtpWe5n1YkSXZ9qe3u+NNP5NaMiaEJtbed1JwcmnAfPkziap8+VOocCNdK48ZyNqAQFrVQXCy7KLUKX3Fx9D/MyqLxWK1bEQh/x5ev+V6CSBG+xPE3b67POJaaCnz0EX2e6talucHFFwP//jeVCr//PpUGSxKdk/VaLAebVq3I7VlV5TlPcOFCYNcuKhP+v//z7zn1Er5276YxOynJe6MKPRAbYGVl8mZuIDl/Xhb2fJlnOjm+AO85X26FL9EdMiFBdhGHCx4cXyaTCe3bt0dCQgKaifu5oqSE5p2APo4vgM5DH35I54jPP5djdqxW2mjt2JGyOE+epFLWH3+k+yg7Fiu6cgLqhC9lELtuwldxMX3pQVWVvLYMJxHVhfAl1rvOwldZWRnKbGuXjIwMEoXF/4eFLxa+woonn6SBe/NmsqUHkupqylb5/Xe5hMRfhEDVrRvtuCk7I/paWnX4MJ0QY2LkLm0ehC93Crj4PiEhATHKiaeYIMTHuy4vCZTwJRYEarJg6tenk5XFoj6bSS/hK5SOr1DRvTuJkefP18zcE26viy7yrXRHKxdcQIuligr5WI4flx1bQqRTi2ikcPo0CVNasFgo+wCgHcIvvySxa9IkssI//DCJYVddRTkQF1wADBxI54HcXHkXLVBs2kSXjRtrczcEsdwxLi7O8fyjhf37qZwHCK3bSzB8OF3+/nuNCXANSkrkjZ2xY7VN3lNTySm2dKm67qW+oix31OqYWLqUPqNNm/pWynbBBeQKEq4xtYSz8FVeLo9XvgpfotTx0KEa4dBC+Dp16hSO2gJ/g93REVApfPkabO+NIUMoA/KGG2iD8emnaYNQfNb+8x9588SoDB1Kl57KHadOpcv77vN/XBbC1+bN+lQqdO0anE27+Hj5fBCMcsdVq0gkaNyYNnC14kI8EcKXq9ItwIPwpcz3CpfSNIGXzo7Lli3Dzp07PYv2oqNj7dr6zqF79JAbzfzjH/SaXnklnVd27qTne/ddyq8cMkT+37oQLQFZyBKljK5QimIOr6MvwldKilz9oZfr6/hx+l8ruyaHA0KwcuH4cv68CLeXJEkkjonfycrSL6jfwLDwFU5kZsqW0+efr9ExQ1e++06ejImwbn9xFeTpr3AkHrNDB9rNAXzK+BLfe8z3cjVg9uxJt+/f731xpwXx//AUbK9Eyy5kWZl8v3BxfGkNtw8lJpNc7uhcxhXMMkeA3nvO5Y7ff08Dc48e2iecsbFyJ0Ot5Y7z5tEiKy1Nfc5Saip1IwPI5RhItOZ7CYIofPmFcHtddVVo3V6CFi3ovWSxAF9/7fm+kyaRW7JRI3I0hyM33EC5hnv3au9ErCxz9HXhFR+vvUQrnEsdN24kMbB2bd8Fn7p16RxisciOBxsZGRlIsM0Jtm7dCsAAji+9hS+A3gNz5pBgm5ZGGwDV1eSWfvJJ/Z8v2Ajh63//c90oZft2+vyZTFS+5S85OSTKVFXJmym+EMx8L0Ewc77E/MHXOaaejq9wDLYXeCh1BOg81sTbPE7PYHtnXn6Z3IJ799JcaPFiciGPH0+3jRxZ02Xth+NLme/lkMfoi/ClZxyLQLyXsrPVd5cMBh4yvpyNHsqOjiYR5QGw28sGC1/hxmOPkSq7a5f6EhKtWK1UQiLYskWfibMr4UuUg4nMKV8fUzl58CHjS3NHR0F6ulwKpZfrq7paLv1S4/gC5IWuGuFrzRqaINavT4tTf9Cra4qvpY6hQghfP/wgC9BWa/CC7ZUMGUKXv/xCnyFRPuhr1pEvAfcWC+V5AXSO0tJQQLx3A13u6K/wtX69y5bjYUG4ub0EIqfLU3fHPXvk8WbqVNqlDUdSUuTSYa0h977me/lLODu+lPlevoqBkuQ24F6SJLvra7MtL9Or8FVcTOdTkQelA2Kxrsrx5WuwvTckCbj7bprL3XQTOW9FGZPRuegimocUFbnuYvn223R53XWyu8YfJEmfcsdgdnQUBFP48ifYHvDo+HInfAnRxFDClxfHlypEsH0gSpbT0uTPEEDnjl27KGLEXdmoEC39FL4c8EX4Ut5fb+Er3N5LHkod3Tm+uKOjazQJX5MmTUKPHj2QmpqKunXrYtiwYdi1a5fX31u2bBm6deuGhIQENG/eHNOnT/f5gCOetDQqGwIo9NbVDpe/LF1Kg3JCgnxS9tYW2xtlZTTpAhxFqk6dyFpZWKi9tApwPXkQ4snZszX+P94cXzWEL3cdHZXo0QlPybZtNIlT5gt5Q8tETFnm6O/EV69BxUiljgD97zIzSRgVr/uuXTQoJiTIrqlgHUtKCk0yFi2SHZq+Cl9ioqrF8fXdd7LbS2urePG/Clfhq2VL+vxXVNQMiA4XRHbPoEHBfe9545ZbaFd0zRqXOUywWqmUoqKCjl1raW6wEeWOX3+tvszp4EESZczm4DlBBeEsfPmb7yVQkfMlHF9eSx1/+YWcsxMmUIMZHRCLPbFYD2qpozONG1NMxpdfyg55o2MyyZs/zuWOp0/LGwJaxyVP+Ct8VVbKbrFIdHyVl8vjOTu+PCPWWAUFvudQBdLxBdBcctEimkN9+aXsUnOHm1JHNcKX+Jm4rx1fha9AOb7C7b0kRKvjx+3rXndGD+7o6BlNwteyZcswcuRIrFq1CosWLUJVVRUGDhzo8U1+4MABDB48GJdffjk2btyIf/3rXxgzZgzmzp3r98FHLCNH0onl4EHqYqc3Yvf93nvlCYVwsvjK33/TwqxOHcdOGLGxsuNDq3Bksch2caXwlZEhl4Q4ub7cWT/F9zVKHb05vgD9c77EguDii9VnP3TrJmcleSu51CvfC9BnYVVeTkIfYBzHV0yM3FFKdHcUn5FLLw3uoiIuTnaSjB5NjsFOnXxfRPXsSYv03Fz68obS7fXoo9rcXuL5APosB6p8u6REFta1Cl+SJB9jOJY7HjggO5DCye0F0KTzyivpuqvOnXPmUPB0fDxlhYS7A6VPHyofLirynCmkZOFCuuzZM/jByuL8XFxMn4Fwwt+OjgI3ji9AFr7Egtir40tkjpWWUlizDngtdbRYqBsrEDjHV6Qjyh1//NExf++jj+i17NxZn/mOwF/ha9s2x0ZPwSJYwte6dfT31alDwee+4MI1pFb4quEWClexAgBq1ZLHBTfljl4JpONLcOWV6psC6VTq6AALX56pXZvmUVarvQO5ascXlzo6oEn4WrBgAUaMGIH27dujU6dOmDlzJnJzc7HeQ+D29OnT0bhxY0ydOhVt27bF/fffj3vvvRevv/663wcfsSQlUUgpALz0kn8Bm85s3gwsWEDC0RNPyJ2s/M35UjqznBc3wjGlVTjas4cWIAkJjid8k0kWqpxKNN2F/fnl+BLC18aN+iwutOZ7AZRzInZ7PHXIrKyUhTVfLehK9BhUxGsUE0OTAKMg3CnffedY5hhsVwcg53wJ14Ovbi+A3GNigqNGjP7uO3Jz+uL2Aii4OzWVFudiAqc3f/9NC8x69XybsIRzzpdwew0c6L+IEAiU3R2Vi9Jz54DHH6frTz0V3AWgr5hMlI0EqC93DFWZI0Cfq7g4uh5OOV+HD9Pk3Gz2v9RLheNL4FX4EhtpAPDVV/4dlw2vwldeHokEMTGOm4KMevr3p3nx4cOyk6qyksR0gDZk9BTVhUtr715ylWlFvM9Eo6dgESzhS5nv5ev/XcwtT560b4iJ+XlEOb4A2fXli/BVWqp/R0d/EaJlQYFDhI3PwpeyK6OvwpdermfxXhJdUsMFSarx+Vbt+OJSRwf8OiOLAd6TvXzlypUYOHCgw22DBg3CunXrUFlZ6c/TRzYPPEBv0qNHqS21XkyeTJc330zd4vr0oQ/Uzp3+dV3zFOTpq2NKCDxdutQMV3ST8+XO8eVzxhdAk9WGDWlw9rfFNaCto6MSsQvpKSR840YaQDIy9Nkd0sPxpQy2D3fHh5IBAyjs+sgRet2FOBwK4evqqx3/d/4IX4AsinoTvpSdHB99lMo/tWI2q3vv+oOvZY6CcBW+Dh4EZs2i6+Hm9hIMG0adlXbvduw6++KLtOhv1gz45z9Ddniauftuuly4kMZfT1RVUVdLIDTClySFZ7mj+Bx16kTnUH9Q4fgSeCx1tFrl8wRAgqUvooYTXoUvIdg1bx6c7n6RSGIiCf+A7MT87jsam+vWpVwiPcnMlAVXTxuN7ghFvhcQPOHL33wvgObcZjN9Lm1zRL9LHYUgE274k/MlOjpmZYVPVIg4jupqeQ0FP4QvsUZISNCeARotji+gRs6Xt3B7LnV0jc/Cl9VqxdixY3HZZZfhQtG1ywXHjh1Dtnhj2sjOzkZVVRVOuggnB4Dy8nIUFRU5fEUd8fHAc8/R9UmTADcDgSYOHZLLUcaPp8uMDNn94Y/ry9NAr+yMqEVcc1XmKHDTzcqdAu621FG8Bz0JX5KkX7njsWP0f1CWV6lFTcC9ckKix06j+OyeOkU7rL5gtGB7QUICMHgwXZ84kRZJqanBzewQZGfL4lHbtv7v/AkXprecr++/J5doaqp/GSqBzvkSC9pu3Xz7/R496PNy5EhwgoHVItxeAwZoF8qDRWqqXBYsQu63baMgewB45x255bgRaNWK/tcWi/cGM6tXU9ZkZqbv7z1/EYuQcHJ86ZXvBcgCxNGjNeZBmhxf+/dT1mhcHJ0/KyvlMnY/8Cp8BSvfK9IR5xghfInzyz/+EZjoAX/KHUPR0RFwFL6U7ls9qa6WN8z8KS81m+U5oa1kTghfzhUbAsM6vkRmli/ClzLfK1w2jmNj5TWTQnDyOeNLWeao9W9k4ctzqaPVysKXEz6vjEeNGoXNmzfjS1e5Hk5ITm9kq+2E7Hy7YNKkSUhPT7d/5UTri3XPPTRZOnHCseuGr7z5Jg1aV17p6Izwt9zx3Dk5X8eVSOVrZ0RPYpooTXSa7GsOtxe7FZ5KHQH9hC+xILjwQu15MGIitnat+w6ZeuZ7AbSgc5OnphqjBdsrEd0dFyygyz59QrdrL5wo99/v/2MJ4WvrVsA2SNbAOdvLF7eXINCdHf11fKWkAB070vVwcX0dPAjMnEnXw9XtJRDdHb/6ioS6Rx6hy6FDgWuuCe2x+YIIuf/0U88LSFHmOGBA6Fqfi8VjODq+9BC+MjLkRZYQkWxoEr6EGNGpE3DnnXRdh3JHsYCrrKxEeXm5fa5Rw/HFwpd/XHstzUU2baLswJUrScR8+OHAPJ+vwldZGW0WAaFzfBUXkyAfCP7+m+b8aWnymOkrTiHpPjm+qqrkOWY4ihWAf6WOwcj38gUXOV8+O758zfdSHkc0CF/i820TslSVOp45I8clOY2X0YpPwtfo0aPx448/YsmSJWjkJSytXr16OOYUgFdQUICYmBi3k5QJEybg7Nmz9q/DivadUUVsLDlNAOA//6kx6dPEqVMUBArIbi+Bv8LXhg20OMjJkU9CzmjN+aqqkjuseXJ8OYkx7k4EfpU6ArLwtWKFe9FJDb7kewkuvJB2NgsLXb8XLBbH7AU9UO7K+TqwKEsdjcY118gZOkBoyhwF//gHlfuI3CR/qFtXLiFy95n84QfZ7eXvcwrha8cOev/qSXk5CXiA78IXEH7ljq+8QufBK6/07XwRTK66igSK/Hwq0//jD3J5vfVWqI/MN265hVzX27Y5lsc5E8p8L0G4lTqWlcljt16ZdOJc5ZTzpanUUZThdusG3HorXV+yxHuzGC+kKEpz8hWO9hqOLw629486dWTX63330eVttwWuvE0pfGlxT23eTOft2rWDn+mWmCjPZQPlXBabq5dd5r/Y7ySe+CR8FRTQ66Ocq4Yb/pQ6Brqjo6+46OxoeOHLYpHHg3AUvoQJyPbZVuX4EvpJnTqR0+nXTzQJX1arFaNGjcK8efOwePFiNBMfZg/06tULixYtcrht4cKF6N69O2Kdc5tsxMfHIy0tzeErarntNhpgzp2jXK6yMt8e5/33KZi9c2e5C5fg8stp0Ni3T12XN2fU2Lq1Oqa2bSOVOi3N9YTRTamjuxOBEMJ8CrcH5KySs2f9C+j2Nd8LICFULOxd7UJu3UqiQnKy+u4savB3YWXUUkeA3n/9+8vfh1L4kiT6LOhld/eU86V0e40Z45/bC6D3UPPmdN2XzBRPbN1KC42sLP+s3L4KXwcP6t+tctEi4OOP6brY/Ahn4uJofALkTLJnn6UOiUakVi3KLgPch9yfPi2/lwcMCMZRuSbchK/166mMMDtbXvD5i5uA+/qKxUlSUhISPE3shfDVvTudiy6+mM5z337r16HFxcUhxuYCPmrLhEtISECc2DDhUkf9EOWOYmPz0UcD91ydO5O7u6BA27zYU6OnYBDonC89N1c1Or6EaOIgfAmxOTs7uI0EtOBPqaOBHF9CzCrx0ATMa6mjr8dx9qzv62PBqVPyXM6diSOUOJU6qnJ8cZljDTSdJUaOHInPP/8cX3zxBVJTU3Hs2DEcO3bMrsID5Na6W5TkAHj44Ydx6NAhjB07Fjt27MAnn3yCGTNmYNy4cfr9FZGM2Ux2/Nq1yeLtS85OaalcKjl+fM3BOC1NFq18cX2pCfJUdkb0sBtQ4zG7d3c9mGnM+BJCWA0RVa3jKyZGzinytdyxrEyefPua1+PJfi924i69VN9yPH93VIxc6gjI3R2zsuSS3UjAU87XDz9QSYMebi9BoModlWWO/iw0hPC1YQO5yLyxbx+V8jVrRsHLejVrOXlSLrV75JHwd3sJRHdHgFrcP/FE6I5FD8Rr8MUXQEVFzZ//9hs5Ddq3D22bcDdjYchQ5nvptfB3E3AfFxeHurZxxWuwvdLxBciB6DqWOwrhy+72sljY8aUnQ4fK13v39s/h642EBNrwBLSVO4Yq30sQSOHLatUn2F6gwfFltVpdO77CuTRNIISvwkJtjvdw7OgoCBfHV61acvMzfzd/xHupdm3HSo9wwZeML3EeCOUcJczQJHxNmzYNZ8+eRd++fVG/fn3719dff22/T35+PnIVuyPNmjXD/PnzsXTpUnTu3BkvvfQS3n77bdzob1eyaKJhQwrZlSTggw+8B+46M2sWLaaaNpV35Z3xp9xRjfCltTOit8fUI+OrtJRccMrH84S/OV/r1sk74cL9ohVP3fH0zvcSRLPjC6D8orvvpoy8cN1R9AUxcV27Vs4AAGq6vbyJwmoRwrHenR39zfcStGhB54GKCs/lbefOARMm0ET0xx/ptiVLgCef9O/5AVpY3H8/TcDatpW78BqByy4jV4skAe+9F54TRy0MGECT+1OngPnza/48HMocgfBzfOmZ7yVw4/gC5HJHj/le+/aRIyA+XnZO3HILvVdXrKDGP37gVvg6epQ2vGJijOt+DCdat5ZzpcaODfzz+ZLzFaqOjoJACl87d9JaIiFBH2HPSTwR83NXwldlZSUstpgRB9HECMJXSoo8/9WS87VrF83HMjPDz4EkXrtQZ3wpOxv7W+4Y7u8l8dk+cQIoK3MwelgV5djs+PKM5lJHV18jRoyw32fWrFlYunSpw+/16dMHGzZsQHl5OQ4cOICHAxVGGckMHEilIwDw0ENymLw3qqqA11+n60884d4JpBS+tOQZnD4t70h46molSdpyvrxNHrxkfJWWlqJKUX7kstRRuL1iYsjZ4g1/hS9lmaOvO+HCNbNpk6MrRbkTF27Cl9EdX0lJVO50112hPhJ9ad6cJi+VlY7lhz/+SG6vlBT93F6AY2dHPTtOCSeHv8KXJHkud7RYgNmzyc30n/+QQDZwoJxj9dZb2jclnPnwQ3LbxcWR00g5OQx3TCYaP9atcywPNioxMfJn3rnc0Wpl4csVVmtghC83ji9ApfAlzhGdOsnugAYNqFkJACg2b33BrfAlhLpmzULXFCXS+O474JdfHN1fgUKr8HX+vDw3j0THl5hj9uqlz8aGBseXsrLIcI4vwLdyx3Ds6CjwEG5fVlaG6upql7+mu/ClPBa9HF/h+l7KzJQ7ZOfl2Y0eVqvVQWxk4cszEWRfiAKee44yhoqLybmlpmRw3jwSprKygP/7P/f3u/RSmhDm5spClhqErbtlSwo39oRa4aisDNiyha57E77clDoCjq4vl6WOynwvNYNKz560uDtwQD5BasGfYHtBs2b0WlZUyJ2DACqnOH6cdrT13mnUq9TRqI6vSEWSZNeXKHe0WgPj9gJo0RkXR4Lzvn36PGZlpfw50KPsxZ3wtXo1/eyee+iz36IFCYQLFtD/6emn6X4PPECitC/s3CkLjZMmUcaM0WjUKLDlR8FGlDv+/LPjWLN9O5CXR84HPUp+/CGcSh0PHaKFUEyMvgt/kY918mSNLrRC+PJY6ijmKc6bczqVO7oVvjjfS3+aNwcGDw7Ocwnha906dTmOGzfSBknDhqFbPAdS+NK7eZKTa0gIX84VG4AsfEmSJOfnAeEvVgh86ewYrvlegMdSR8B9zpfuGV+AfgH34f5ekiSHcsekpCSYbFUo4jNTXl5u/6w4CF9c6miHhS8jYTaTC6BePTohPvKIZ+eE1Qq89hpdHz2aQs/dkZwsu4m0lDtqsXULwWflSsDNbgAAWjhWVdFJ0J1KLSb7p045dFmMi4tDfHw8AMecL5eljmrzvQRpaXLGk1bXl9XqX7C9QJJc70KKnbiLL9a/c0e0lzpGMsKFKQLuf/iBPn8pKfqXksTHy6KIXuWOO3aQ8zEtzffyYSXOwld+PokfPXvS5y0lBXj1VTr/DhkiC+YvvECdDUtLKRPu9Gltz1teTiW1paVUYudLliOjP+3bk1hSVQV8+aV8u3B79ekj78CGCuX5WU8npS+Iz02XLvr+X1JSyKEF1Ch3bG1zgzXxVEronO8luPFGEuk2bqSyIh/x6vhi4cuYtGlD1QAlJbL7xhOhzvcCAid8Wa3AsmV0XW/hS0W4vTLfS1JuVIe7WCHwpbNjuHZ0BFw6vpSvjbtyx4A6viJd+ALkz/fhw5AkqUautXB7SZJE45A4D7Djyw4LX0YjO5t2J00mKrv55BP39128mCZ8iYnAyJHeH9uXnC8tA33Hjuo6I6rpiiPEqurqGmGRrnK+XApfajs6KvG13HHPHno+5eLfVzwJX3qXOQL+DSplZZSJBBi31DGSEW6VFStocS/cXqNH6+v2EijLHfVAme+lR/5ajx60wZCXBzz1FJVYzZ5NPxsxgkqtxo+nz7ESs5nKHJs3p4nt7bd7FvedefZZWnxnZVEmYyRlyRkd4fpSljsuXEiXAwcG/3icERsK5eXyuTZUKIPt9cZNzteDDz6ImTNnYsKECa5/z2KRzxPO85TateWOnH6UO3p1fHGwvTExm+X3jB7ZtMFAsTDWlUOHaBGtbPTkL2Juefo0UFGhWvhyQIgVQkQLV3wpdTSC4+vkSftcR5Iku6ClWviyWPyPQ4km4ctLwL0QvtLT02GSJBa+XMCzayPSpw/w8st0fdQoyuNxhXB73XefOnHniivocvFi9TvHWgb6mBh5QuxJOFLzmPHx5PIAvHZ2rKqqsp9sHUodtTq+AN+FL7Eg6N695qJZK8EWvvxxfInXJjYWEIsBJnzo2JF2tIuKgFdeCZzbSyBcpXo5vvQKthckJ8vhya+9Rpktwu01c6bnCVFmJpWWJyaSI+j559U95++/yyH2M2bIzhYmPBg+nM5fGzYAW7eSK084H0Kd7wXQe1YsIkJd7hiIfC+BEI+ccr5SUlIwYsQI9xlfymB7V84JUe745Zc+O+bEgj0vLw8AlzpGFFpyvsLB8WUr/UVREX3phZhjdu+uX/ZkRoZDRz7xOSotLa2REeVV+ApnsQLQXupYViZHQoSj40tExCiFK3gPuBdrMXupY2GhXEbsa1VINApfNkHLneMrIyODRMmyMro/zyvtsPBlVJ56Crj6anpT33xzzQFu0ybalTab1beV79mTJofHjqmz/efnkzPCZFK/8FQjHKkV09xkmzgr4MrdI90cXxs2qMtYE+iR7yUQE7GdO2nQyM2lwdRsDsyCQxkcqXVhoMz3CrdwTobeM6L09sUX6XL0aG2fCS2IneKNGx07SfqK3sIXIG8A1K9Pbq+//lK/g9+pE/DRR3T9lVeA77/3fP9Tp6hjKEBNS4IR2Mxoo3Zt4Jpr6Pqnn1LOTVkZLTDDZUESDgH3JSXyJpw/5fzuEAH3Ljo7esRVsL2SYcNo3rNzp2NupgbEIk4sPtLT02lByI4v46NW+CoslN+boRS+UlPlTUabEKsLeud7AbR2EOeuY8fswhdQUzgRgomD8GW1yqV24SxWAI6ljmrm0aKjY0ZGeLrZYmLkNZiLnC93wpe43e74EmNWrVq+N0yIRuHLyfHlUvgSbq/sbP8NFxEEC19GxWQCPvuMPgR79gD33+94MhUOgltukS223khIkCesasodhUDVrp3n/DAl3oSvoiJZdPM2eRCLcy+OLyGAxcbG2vO/APjm+GrcmKzk1dXaWlzrke8lqF1bzjNat06ekHTtSm4dvRETk4oK2jnXAgfbhz8i58tiCazbCwCaNKFBuKqKxC9/qK6Wg+T1FL4mTiTBatcu6uqntezwjjuARx+l63ffTQtqV1itFIZ/9Chlybzxhj9HzQQSUe74+efA/Pl0fdCg8BHzw0H4EgHgDRoEpqzCjePLK0L4cjefSEuThU0fQ+6TneY/6enptIgqLaXNBU/5Y0x4I4SvrVs9b3aK95loQBRKApHzFaiqAkXOV3x8PGJs3U+dyx1dOr5On6YGN8rHCVcaN6bL4uIa3ehdEs4dHQUeOjuqLnX0N99L+bv+CF9WqzGEL6dSZrHeFevcQlv0D3d0dA8LX0YmK4tyKWJigG+/Bd5/n24/eFDOq3jySW2PqSXnyxdbt+iMePCg692o9evpBNS4sfcToRBTnAYRZ8eXEMAc3F7K39MySZEk7eWOp0/Lg5heO+HKXchAljkCJIiKElGtAwsH24c/yq50o0YFzu0F0OdHr3LHPXtoEpmUJLtB9CAlhZxXzucLLUyeTJ/Hc+eA6693nb00Ywbw3XfkQvnyS/3KRxj9GTyYxoljx4APPqDbwqHMUSDGylCWOirzvQKxUFM6vrQ4j911dFSi7O7oQ7mjS+FLuH+aNnXtNGOMgejQWF3tebMmHPK9BHoLX8eOkeCsnP/qhUI8kSTJbc6XEL4cQtGFUJGV5btbKFgkJMjlZmrKHcM530vgorOjeH3cdXUMiPClh+OrqEiuQghn4UuL44s7OrqEhS+j06uX7O56/HEafN94gwbpgQOpu5IWRJnPkiUO3RJd4stAn5pKJQeAa+FIy2O6KXV05/hyyPcCZMeX1oW+VuFLBHm3aqWfABRM4Qvw3VHgb2glE3guuogmMLVrqy+L9ge9Au5FmWPnzuSqCCdiY4FvvqFF086dFIyvXFDv2iW7wv79b+3naSa4xMVRwwKAyhwlCbjyytAekxIxroTS8RXIfC+AXM6SRAsUtQKfMtjek/B1zTUkeB886JMg71L44jLHyMBdJ21nwiHfS6C38CWqCjp2pJI0PXHT2fGc02aRS8eXERw6SrR0dgznjo4C8dppcHyJ2+3nTD2Fr1OnZAegVsR7KS0tvDchhfB1+jRQUuI23N6h1JEdXw6w8BUJPPoouQoqKynva8YMun38eO2P1aMHfehPnvTcedFq9X2Hy5NwpIPw5XwicNnREfCt1BFwPP5//hMYNw547DFyyzz8MJWdjhgB3Hkn7SSLblN67pSJidjSpXIplShZCwS+7qiw4yv8SUykksEtWwLr9hLoJXyJ0hI9yxz1JDsbmDuXRJN584BXX6XbKyqoHLKkBOjfP7ClpYx+iHJHgManzMzQHYszepU6VlQAP/ygPRTbapWFr0DkewHkmBAlg2rLHffupb8lIcHzAjIpSc7X86Hc0aPwxcH2xkeN8BXJjq9gdA23iSfeHF9RI3wZwfHlYl0QklLHrCw5kkJNGakrjPJeSk+XI22OHPEcbs+lji6JCfUBMDogScAnn1Cw7P79dFvXrrJ7SwtxcSSgLFxIrq8OHVzf79AhEo5iY+UuaGq59FLg3Xf9F77cZHw5Wz+9ljpqXex37Ei7AkVF8mJWDb68Hu7o0oVcLiJzq0OHwC7E2PEV2YgJTDDo3p3OWbm5NNnwdaIRiGB7vbn4YuCddyi4/umn6VgXLybRLjOTwtK1ZogxoaFrV1qEbNsWXmWOgH7C18yZtHnTowd1rnTuoOaO/fvpXB8XF9jPY6tW5Mras0fdRo+3YHslt90G/Pe/FBMxZYomF6nHUkd2fBkfUZ7vTvgqKKDxTJLCYzwKlOMrEMKXk2soooUvkbfsrdSxvFwWziPI8VVVVYWKigoAOgtfZjNtrh8/Tl++vB+M8l6SJPp879wJHD7s2fElNpe51NEBFr4ihVq1KOerVy/atR0/3vecjX79SPhavBgYM8b1fYRA1bGj9m4Rwvm0aRNw/rysXp84QYIa4LksQeAm48s57M9rqaNWx1dMDJUx/fILXXf+io2teVvt2sANN2h7Hk8kJdH/XmROBLLMEfBf+GLHFyNITQUuvJAcZqtXU1c1rVit8ntfzbkilDz4IJ0vP/6YHLmihOPjj+XW80z4I0nAtGnA9OnU+TSccON+1oz4TK1dS+/b2bPVzSNEvlfXroHtHtW6NbBokXrHl7dgeyUDB1IHtWPHyOEi8k5VkOLUVIYdXxGGeP8cOECfMef5jChzbNNGzkMNJXoKX2fOyN1OlXmgeuHkGopo4Uut40t0dKxVK7z/No3h9qWKTt66ljqKYxHCly8Y6b2Uk2MXvjw6vrjU0SUsfEUSXbtSx6nt22mB5SvCmbRsGWWFudr59MfWnZND4fW5ubTw7d/f8THbtJHbMXvCS6mjc8aXg+OrokJegPpS3jVoUOh3/S+6KHjCF5c6MnrSsycJX6tW+SZ8/foruR1TUoC2bXU/PN155x1y5Ipz3P33U3k6Yywuvzwwiz9/0cvxJVxKAHWw7NSJSvm9Eeh8L4FwTymP0xNqgu0FcXHAjTeSIP3VV5qErxqOr7Q0zviKJNLTgQsuoMXm2rXU7EJJOOV7AfoKX3/9RRtNbdoExhmuh+Mr3Ds6CtQKX0bo6Ai4DLf3JHyJ2yRJQrzYINFT+HI6Fk0YTfgCgCNHkGZbvzoLX7XS0lj4cgPXWEQa/fvTbrQ/5TNdu5Iro7CQFmuu8DfPwFXOl9bH1Bhu7yB8CbeXyaROZAtHRO4EEPjFGJc6Mnrib2fH116jywceMEbHtIQEyvtq3ZpEv6lTQ31ETCShl/AlxBoR5P/UU8CCBd5/L9D5XgIhIqlxfKkNtlciujvOmUObYyqpIXyVlFCGn9ks55IxxsZTzlc45XsBsvBlC8D2C5HvFag5ppN4IubpzsKXyIYytONLWeroqXmYEfK9AM2OL2W+lyQEPRa+tKPo7Oiu1DHbZKIxTJLkbqIMABa+GFfExMgOoiVLav7cYtFWQuAKV8KX2DVTO3kQTi2nUkfnE4EQwBxKHcXvKEMRjUa/frSgvvjiwJ+s2fHF6IkIuF+7llylWli7ls5LMTHUVMIo5OTQTu6KFYDTQplh/EJZ9u+tG7M7ysrkMNw33gDuu48e67bbqPTGHefPy6VQgXZ8tW5Nl3v3ev879+4lV7e3YHslffvSWHf6NPDbb6oPSyl8xcfHIz43l75p0oScZIzxcSd8Wa3h5/hKT5fHmLw8/x4rkPlegDy3PHsWKCuL7FLHnBwSwysqHMSiGhihoyMgi5aKbopqhS87eglf4vejQfgSwraHUsc65eV0n3r1jLE5HEQMuuJnAo4od1y8uObPdu+mCWViou8nZiF8rVxJC19fukSKyX5pKaA4yWpyfGnN9wonmjWjnaFffgn8c/niKCgro0URwMIX40jbtpSFUlzsuXusKyZPpsvhw6lk2kiYzeFdusAYE3F+raoip7YvHDhA43BqKp3v33uPxumzZ6njobvHXbOGRKicnMBn1jVtSoJ3aan3Bb0QIzp3pt9Rg9kM3HILXdfQ3VEpfDnke3GZY+SgFL6sVvn2vDwSMcxmeq+FAyIAG/Cv3LG4WP4cBUr4Sk+XcwGPH7cLX2LeLhDCl4NoYiSxAqDzkHDreCp3NIrjKytLjsKxrQ3UlDraz5cVFZQhB7DjSwsqHF+Z4v/PZY41YOGLcY3It/jzT5pMKxECVdeu6ieUznToQBPsc+co6+fIETphxcSonzykpMgDpqLc0flE4FL48rWjY7jRvHlwxDtfBhXxmsTGGreclAkMJpMscIvOM2rYt49KBgHgySf1Py6GMSLx8fI51tdyR5Gb1bIlLZzj4+mzlpNDjq/hw127M4OV7wXQ/KB5c8fjdYdwpWttfiHKHb/7jgQ2FbgVvjjYPnLo2JHce6dOOYoWQhhq356aDoULeghfq1bR/L9x48CV7EqSQ8mcasfX+fPyhrcRxAqBKHd0J3wZpaMjQPM4J6eVJseXWIeZzdRYxB+iUfg6csTB6FFZWWn/v6edPUv34Y6ONWDhi3FNp050Ijp3Tp5ACvSwdZvN8kT5r79kMe3CC9W3UJckWbhSCF/Oji+XpY6R4PgKJmJwKyoiJ5calGWO7HJhnBHljlqErzfeIHfJVVeReM4wDOFvZ0dXLqXsbOD772lMXrAAmDCh5u8FU/gC1Od8+RrH0LMnLfTPn6dmQSqoIXwJUY4dX5FDfLy8Kassdwy3fC+BHsKXyPcKdPMkRc6XauFLCBUpKXJneCMgAu4PHnT98927aYMhPd0Y2UxOzQmEqFXiIluuhvClXCP4GzkjhC9fNn5KS8nZDBhL+CosRLrNcXfu3Dm72wsAEsUalx1fNWDhi3GNyQT06UPXncsd9RrolTlfvj6mMtvEhibHFwtf6qhVS64TVzuwcLA94wkhfKkNuD9xAvjkE7o+fnxgjolhjIq/AffuXEpduwIzZ9L1yZOp26PAag1esL1A5Hx5cnz5EmwvMJlk15fKcscUxcKbHV8RjKucr3DL9xIoXCE+I/K9At08yRfHl5EcOkq8dXY0SkdHgZPTSo3jy75RoFe+l4vj0IR4LyUkGKM6JTWVokIApCsifU7ZxK60tDSYRBQAC181YOGLcY/I+VIG3FdWAhs30nV/ha/LLqPL5cv9F75cOL7KyspQWVnpOePL6KWOwUKStC+sxGvC+V6MK0Rnx+3b1eUSvfsuuQ27d6cQaoZhZAIlfAHArbcC//oXXb//fnm83r2bguATEoKXbyRcVJ6Erz175BzStm21P4cQvn7+mVzOXnBwfKWlsfAVqTgLX8pg+0hzfFVUyKJ2EB1f7ro6Rozw5a3U0Sj5XgInx5eajC+740vPzXEhfJ04ob3Bi/K9ZASxEbALWqmKufMR22c9IyNDblTDpY41YOGLcY/I+frrL7m197ZttPhMS/N/UnfxxVTyePgwiV+ArsIXQCq4KHVkx5efaLUSc0dHxhN16sh5PWIh7Y7iYhK+AHJ7GWVywjDBQq9SR3fj+ksvAUOGUAbNsGG0WBAL427dgte9UDi+PJU6ijJHLcH2Sjp3pucpKwN+/NHr3ePi4hBje57GcXF0vjKZZHcHExkI4WvDBtoEPnCAhN+4uPArvfdX+Fq3jt7/deoAbdrod1yuiEbHl7tSR6N0dBT44PiqUeqoh/Alxr/qatnYoBYjvpdswldcQYF97Dl06BAAm/AlPvfs+KoBC1+Me9q3p5NJSYm8w6W0dftbk52cLO8Sl5fTrrHWXQ7h2FKUOsbGxiIhIQEA5XsJx5fLjC92fKlHa7tgLnVkvKG23PGTT2iB0bw5cMMNgT8uhjEa/ji+KioA26TZbS6VyURlju3aAUePAtdfDyxdSj8LVr4XIB/f/v01G+8IxDxFa5mjQJIozB9QXe4oFnzNRQOAJk2CJwYywaFVKyqFKi2lTWCxYdOpU/i91kL4Es4PrSjzvQK90aRwDbnr6ihEk4gRvnJzXZ+/Itjx5THjy19iY2Ujg9Zyx6NH6dJI7yWboCUpAu5zc3MBAJm1asldj1n4qgELX4x7JEl2fYmcL72DPEXOF0AimMiRUoubXW5lzpfHUkd2fKlH68KKHV+MN0S5o6eA+6oqCrUHgCeekNtnMwwj44/wdeAAlYckJ8s7+K5ISwN++IEa36xeDXz6Kd0erHwvgBb0CQnkuBFinTO+BtsrufVWuvz1V2DnTq93Fwu+xsIdz8H2kYeyG/GaNeGb7wXIwteJE+obEikJVrA94OAa0uz4EsKLUahfn0TS6uqabryKCrmE22iOLw2ljgHJ+FI+jlbhy4giqkLYFutd4fhqmphI46PJZKy/KUiw8MV4RghfIudLb+FL5Hz5+phuhC8hcp09e9ZzuD07vtSjNTySHV+MN5SdHa1W1/eZM4fKAmrXBkaMCNaRMYyx8Ef4UpY5enN3tGwJfPONowAdTMeXySSXY7rK+fIn2F5J27bUPbaqCrjnHvfuMhtiMVdfLPg43ysyUeZ8hWtHRwDIzCSBGJAdLWopLQ2u8OXC8eVO+LK7hYwoVgB0/mrShK47lzuKjo5paUDDhkE/NJ9Q5LMBjsKX1WlOF9BSR8D3gHsjvpeEk+vw4RqOr2bCQFK/vm+l/hEOC1+MZ4TwtXIlBVBv2ULf67XDpXR86Sh8CQU8X5zQ4KbUkR1f6uFwe0ZvRInIqVNUuuSM1Qq89hpdHz0aEBMmhmEc8SfjS2sY+5VXAlOm0PULLgi+60K4qVzlfO3eDZw/T8H2F1zg3/N8+CGVtq1ZI5+H3CAWfHVE2DA7viITIXytWqWPszBQSJLvOV+LFlFOXePGNEYHGoV4EvEZX4D7zo5G6+gIuHV8WSwWlJeXO9yVhS8dUXRtdXZ85Tjfh3GAhS/GM61b08mgvByYPp12PevUoQFRDxo0oElDYiLQp4/233eR8QXI7q6jtp0uk8kkD5hVVXIXOXZ8qUfroMKljow34uOBrl3puqtyx99/py6ySUnAyJHBPTaGMRL+OL6Ec0qLWDNmDPC//1HpY7ARAfeuHF9CjOjSxf/d7pwc4O236frEicDff7u9a13b/z/rzBm6gR1fkYkQvrZtI4E1Kcm3zqHBwFfha948urzhhuAIMGJuef48UmzPV1JSgmqRl4cIE77cdXY0Wr4XIIuWhYVAeblDh1vnckchfAWs1DEahS+F4+uwLc+vgfjcsPDlEha+GM9IEnDFFXT9rbfoskcPfQfDBQtop8MXMc2L4yvPFvCXmpoKSRzz6dN0KUmUVcKow1fHF5c6Mp7wFHAvXBb33cfuTIbxhDjPnjpF5TJa0Or4Amj8vOoqWYQKJp4cX0L48qfMUclddwFDh1Jmyt13yx2unXjjjTfw1tSpSBWLLha+IpP69WVBCdBHYA0UvghflZVyJ9NgNZJJSbG7udNsAhcgCyWAk/BVXi7P440kVgjcdXYUwpdR8r0AWkOJ0rrjxxETE4M4W6MHZ+FLfB9wx5fWzR8jCl/is33uHLJtYnCVrRy/jnDaKc9TjB0WvhjviHJHm5VVd1t3Vpa8A6IVIXwVFtKAbUMo4EL4cihzFO6wjAwOytaClt2U0lLaDQXY8cV4xl3A/aZNVHJhMgGPPx70w2IYQyGEYatVezt3X4SvUOLJ8eVvR0dnJAn44AP6/27eDLz4osu7tW/fHmNuvRVScTGds8Tilok8hOsLCM98L4EvwtcffwBnztC8LVhNKyTJPr+MO30aZtu8XJQ7VlZW2t1fiYmJ8hw0Lo6yzIyGt1JHIzm+FK+deF2EsKUULpXfJyUlUSmt+HkoHV8VFfKasEEDfY4jGCQn240bTZyMKBlCcGTHl0tY+GK8I4QvQTgN9BkZNMkEHCb7rhxfdjjfyzfE4HTiBAUIe0K4veLiKKiTYdwhHF+bNjl2n5o8mS5vuYUXkQzjjZgYeUzTsuNdWSk7D4wifAnH16FD5P4QWCxUGg3ou0GXnU1RDwAwaZJrdyogC4iNG1MZNxOZKIWvcMz3EvgifIkyx2HDgrsxbCuZkwoK7DlfojFVqcIFlpiY6NjR0ShZWEpclToasaOjQNGcAHDf2dFB+BJjVGIiiTh64IvwJe6rHD+Ngk3YaujURCDt7FmHnzOOsPDFeKdZM7kLCRBeA73ZLO/4KModnR1f3NFRB4Rzy2Lx7ihQBtsbcWLCBI8mTWjCUlkpL1oPHgS+/pquP/lkyA6NYQyFLzlfBw9SaWRionF2vLOzgdRUGouUTTFEsH1Skv/B9s7cdBNw++30nPfcQ65mZ3zJSmOMR6Q6viwW4Lvv6HqwyhwFipB054B7IZhIkoT4+HhjlqYpERt5R4/Kwv2ePZQ/nJpqvBI1J8HJnfAlvk9OTnYsc9RrjeCL8KUUUU0Gk0RswlZ9p47DSaIM2GjvoyBhsFeZCQmSJLu+GjUKfgcnb7jI+WLHVwCIjZVFRm8LKw62Z9QiSTXLHd98kxbjV14ph98zDOMZXzo7KsscjbJJIUmyuKQsdxRljp07B8at8s47tNjetQt45pmaPzdaySjjGz16AA0bkjMnnF9rrcLX6tUkBKSlydm+wULhGnIWvoTjKyEhgbJ6jS581alD4rzVCuTm0m3KfC+jnIcF/ji+9MwAVm78OLmg3GLk95Lt811HUSlhAhAnxn92fLmEhS9GHddfT5eDBoX2OFzhQfgSA6bLjC8WvrSjNjySg+0ZLYhyx1WrSJj++GP6fvz40B0TwxgNXxxfRhVrXAXci2D7QLnSMzPlc9Obb1IekhJ2fEUHKSmUx7R6dXi7RITwdeyYQwauW4Tb69prKaYimCjcOu6EL3soutKlY0QkqWa5oxHzvQQqHV8BF77EcVRUUO6zGowsfNmErUzF/7keAKm6mjZ+jPr5CDBhfMZmworrrgPWrqXJXrghShaFoAUnh5fz98LxxaWO2hGDlDcrMTu+GC0oOzu+/z6FnnbuTI4vhmHUEU3Cl6uAe72D7V0xeDBw//3kKBgxQm7iAhj3f8loJy2NBLBwpk4dcupbrfIC3x1Wq5zvFewyR0CV4yvR1r3O0GKFwLmzoxE7Ogo0Or5qlDrqRUKCnCmsttzRyO8lm/CVbsvCAwB7cWODBty8zQ0sfDHq6d6d6s/DDQ+OLwGXOuqE2oWVMuOLYbzRvTvtgh46BEyZQrc9+aTxLP8ME0p8KXU0qkvJ2fFVXR2YYHtXTJlC2YQHDsgZhFar/L9k4YsJB0wmKskEvJc7btkC7NtH4sFVVwX+2JxRuIbEfD0qhK9Icnx5Eb7E9wFzfCmPJYqErxSFu611QoLDz5iasPDFGB8Xk31nx5fLUkd2fGlH7aDCpY6MFlJTgQsvpOtnz9Ki8uabQ3tMDGM0otnxtXs3UFxMHcLatAnsc6elATNn0vXp04Fff6X/+fnzJNY3bx7Y52cYtajN+RJur0GD9Ouyp4Voc3wpSx0rKmQB38iOr1CXOgLq41gERn4v2T7biYpqp1YsfHlFs/D1xx9/YMiQIWjQoAEkScL333/v8f5Lly6FJEk1vnbu3OnrMTOMI+z4Ch5qF1Zc6shoRZQ7AsDYsVSiwTCMerQKX1VVsuPAaMKXcHzl5ZHgFehge2f69QPGjKHr990nP3/jxkB8fOCfn2HUoFb4ClU3R4FCPEmxCSfnbCVcESl8KR1fe/fSuTglxZiChQrHV2VlJSptOXPs+NIJ22fbXFaGDNtNTcW8mTs6ukWz8FVcXIxOnTrh3Xff1fR7u3btQn5+vv2rldFs9Uz4ojXjix1fvsOOLyZQCOErIwO4997QHgvDGBGx0aBW+MrNpQVXQoJcEmUUMjPlzau9ewMfbO+KSZNIgMvLAx54gG7juS0TTqgRvvbuBTZvBmJiKNg+FIi5ZWkpsmzB+i4dX9XV8vnNiGKFQJnxZeSOjoAsWp47B5SUuBS+hNsLCGDGFxBdwldion0dK2SuxuJnRhRQg0SM1l+4+uqrcfXVV2t+orp166JWrVqaf49hvKLC8eXwPTu+fIcdX0yguO024K+/gKFDwz80mGHCEXF+VpvxJcoEW7QI7+507mjVisbz3btl4SuQwfbOJCUBn34KXHaZvIAymnOOiWzUCF/C7dW3LwnKoSApiSIPzp1Dtk38EcKXEE0SExNp47q6mgQiI2+sCuGroIAahwHGzPcCqPQ7IQEoKwOOH7d331SKXeK6yWRCXFxceAhf1dXy/YwofAEkcJ08iRwAWwDUr6qSb2dcErSZTpcuXVC/fn30798fS5Ys8Xjf8vJyFBUVOXwxjFtUZHzZv6+uBk6fpuvs+NKOVscXC1+MWpKSgBkzqIMswzDaEYuIwkLKjfGGUfO9BCLna+dOYMMGuh5M4QsAevUCxo+Xvzfq/5KJTLQIX6EqcxTY5pd1q6sB1HR8JSUlyQJz3brkUDMqtWoB6el0ff58ujRivhdAIqRibeDJ8ZWUlATJag1cVYjazvOAo4gqjt9o2D7fQuaqU17ucDtTk4ALX/Xr18eHH36IuXPnYt68eWjTpg369++PP/74w+3vTJo0Cenp6favHFYuGU8IceXkSeqsBA/CV2Gh/T4h29kyMmocXyUllLmivD/DMAwTWDIy5HwrNa4vowtfoqzw559p3AlGsL0rJk4EOnak6xddFPznZxh3iAXw4cOuf370KLByJS3+hw0L2mG5xFYyl2XLgnJZ6mjk0jRnhOtLlDoa1fEFODQn8CR8JScnA2fOkOAE6G9A0OL4Eu+lOnWMK6La9JGmJhPMAGrZPivs+HJPwF/pNm3aoI1iItKrVy8cPnwYr7/+Onr37u3ydyZMmICxY8favy8qKmLxi3GPOHFWV5OwlZGBmJgYJCYm2gdMu/Al8r3S0zk82xfEoCLELVfdf8SCKy6OrOsMwzBM4DGZaDw8fpzOw95yuyJF+Fqzhi67dAlOsL0z8fHAH38AW7ZQ2SPDhAtC+MrPpzw/5wW+aFDWs2foxSTb/DLD5laNCuFr0yb5e6M6vgCvji9x3SHYPiOD1gkBOg6vRMJ7SQhfsbGoX14Ok9VKn3GjOtiCQEhCHXr27Ik9IlvCBfHx8UhLS3P4Yhi3xMfLAoubnC/7dc738o/kZApUBNwPLEoLsxGDOhmGYYyKls6OYh5m1EB2UeooCHaZo5L0dBa9mPCjXj0Sg5V5RkrmzaPLUJc5AnbXULpN6PIofAmHkZFp2lS+npJCHWGNikrHV0A7OgKOwpeo7nFHJAhfNmG7sSTZyx3RsKExMzuDREj+Mxs3bkR9I7/RmPDDS85XDccX53v5hrIW3t3CioPtGYZhQoNa4au6Gti/n64b1fHlfNzB7OjIMEbAbAYaNKDrzjlfp08DS5fS9euvD+phucQ2t0yxCSbnzp0DEOGOL0HbtsbeKNaQ8RUU4au0VI5ccUckvJdsjq+GFou9syOXOXpGc6nj+fPnsVfY4wEcOHAAmzZtQmZmJho3bowJEyYgLy8Ps2fPBgBMnToVTZs2Rfv27VFRUYHPP/8cc+fOxdy5c/X7Kximdm2axAthC46OL7vwxY4v/6lbl1owe3N8sfDFMAwTXFxsArnk8GGgspJKTYwahJuaSosWsYAJpeOLYcKVRo3o837kCHDxxfLtP/1EAninTtTZNdTYXENJNsHLpeNLuFSNLFYIlMKXkfO9AK+OL3E9OTk5sMJXSgo1SiopoTWKpw7hESR81a+uRjOTCbBYWPjygmbH17p169ClSxd06dIFADB27Fh06dIFzz33HAAgPz8fubm59vtXVFRg3Lhx6NixIy6//HIsX74cv/zyC24IB1stEzl4cXyliJOfEMZY+PIdb46CQHVrYRiGYTyj1vElNjCbNw9NLpZeiDLN5OSapY8Mw7jv7CjKHMPB7QXY3ToJhYUAZOFLuIUizvGlLHU0cr4XIDutQl3qqDwWbzlfkfBesuV4xlVX46WbbqLbjLqRFSQ0O7769u0Lq4e62VmzZjl8P378eIxXtnpmmEDgQvgSjq+UlBSYRL2zcHxxqaPveBtUuNSRYRgmNKgVvoye7yVo3ZqC5bt2NbaAxzCBwpXwdf48sHAhXQ8XI4LNNRR3+jSAKAi3VwpfkeL4CnWpI0BrlAMHokP4io+n/2NBAeLWraPb2PHlEU4/YyIDIbIoSh2F40vp/OJSRx1gxxfDMEx4orbU0egdHQX9+tHltdeG9jgYJlxxJXwtWACUldHn/8ILQ3NcztjEE7Ntnl5cXAyLxWIXvpISE4Fjx+i+RhYrBCkpwAUXkHjRtWuoj8Y/FKWOSUlJAEIofInHjQbhC5CFLpHZycKXRzQ7vhgmLBEOLheOL4euoBxu7z/eHF+c8cUwDBMatJY6Gl34Gj6cQu3DIaOIYcIRV8KXsswxXELVbecuqaICtQAUggQTIXylWa0k1gHGFysES5cChYXG71Ip1gUlJUi2VYWVl5ejuroaZrPZMeNLCDShLHW0WiNL+Fq/Xv6eSx09wo4vJjLwkPHFji+d8baw4lJHhmGY0BBtwpckUbkjlzkyjGucha/ycuDnn+l6uJQ5AkBCAlCrFgCggU2MO3/+vF34yhCiV61adN9IIDsbaNMm1EfhPykplLMIIMVWogrITq+wy/gqLKTPARAZwpen7xkHWPhiIgMPGV8Owhc7vvxHreOLSx0ZhmGCixgLPQlfFguwbx9dN3rGF8MwnhHCV14effYXLwbOnQMaNAAuuii0x+aMbX7ZNDERAHDu3DnZ8SVK54wuVEQqojnB2bOQbMKlcHqFnfAl3F6RIKIqHV5xcWw68AILX0xk4CLjKz09HYBTqSM7vvyHHV8MwzDhiTg/FxdTS3dXHDlCu92xsbw7zDCRTv365IysrKSNSWWZoynMloG2kr/G8fEAHB1fqcJJZPSywEjF9rpIx4/XyPkSl6nx8eS2AsJD+IoEEVU5hjdqFH6f6TCD/ztMZOAi4+u6665D//798eCDD9INVit3ddQDMaicOgVUVTn+rKREXmyx44thGCa4pKXRri/gPuBelDk2awbEcNQrw0Q0sbGyWHToEPDDD3T9+utDd0zusM0vG9nOS0rhK7moiO4TCWJFJKIQnJw7OwrHV5bFQveJibGXtQbsODy5niNZ+GI8wjMeJjIQ7iIhvCQloUmTJvjtt9/k+5w9C1RX03V2fPlOZibtKFgstLBSDhxioRUfTzX/DMM4UF1djcrKylAfBhPJdO5Mu90FBfIiQMnhw0CTJkDPnnJYNBOVxMbGwsz5aJFPo0a02P/6a5qnZWYCvXuH+qhqYhPoGthcK+fPn7eLJolnz9J9IkGsiEQUnR3dCV+ZYrO8Tp3AOZOi2fHFDm6vsPDFRAapqbTLXVFBg3qTJjXvI8ogU1JImGF8w2ymQUssrJQDh7LMMVw6BTFMGGC1WnHs2DEUCps/wwSKSZNoLDSbgQMHav68VStg+nQaN139nIkqatWqhXr16tlzeZgIpFEjYO1aYMYM+v6668gJFm7YRAsh1ysdXwmnT9ONkSBWRCIqHF/pIlA+kBUh4jiKimhjx1WGVyQJXw0a0HrLamXhSwUsfDGRgSRR+eLRoyRwuRK+ON9LP+rWJeHLeUeFg+0ZxiVC9Kpbty6SkpJ4kckEluJimtRnZNT8mclEG0X16/N4GMVYrVaUlJSgwLZhVT8SFoGMa0QJlHBNhWOZI2B3DdW1lcQpha84MYfn92l44sHxJS6DInylp8tGiOPHXa8HI0n4EqXM+flc6qgCFr6YyKFOHRK+3OWaCMcXT/T9x13APQfbM0wNqqur7aJXFp9/mECTkEDClyS53u0W5SYpKcbvaMX4RaKte15BQQHq1q3LZY+RinJBnJwMDBgQumPxhM2tI0rizpw5g2pbREmMmMNHglgRiSiFL1vUibPjKyUYGcCSRI9/5Eh0CF8A0Lo1/U2tW4f6SMIeDrdnIgchtrgTvjjYXj/c1dCL/z0LXwxjR2R6iU5HDBNQRGC9qyw5q5U6OgJc8s8AkM9LnD0YwSiFr8GDAZvgGXbYxJMM2znqhGI+bxIbq5EiVkQainWBc1dHIXwl274PeFWIt5yvSBO+PvgA+PhjoH//UB9J2MOOLyZyEGKL2BVyhh1f+uHO8cWljgzjFi5vZIKCEL6cu+4CJIZZLLQrzsIXAz4vRQVK4euGG0J3HN6wCV9pZWWQAHsZbiIAicPtwxul4+viiwHIgpe9QcG5c3QfFr70pU0b+mK8wo4vJnIQTi52fAUed4MKlzoyDMOEFhFa7crBI9xecXHcgIRhooXmzWWxe/DgUB+Ne2yCiNliQSZkx1dTIdInJgJpaSE6OMYjYl1QXo7acXEAamZ8xQvxMpTCV3ExIAS4SBG+GNWw8MVEDmpLHdnx5T/s+GIYRiV9+/bFY489Zv++adOmmDp1asiOx6hMnDgR2dnZkCQJ33//PUaMGIFhw4bZf27/P3tyfJWV0aUbt9exY8cwYMAAJCcno1atWroeP8MwIaJRI+CLL4Cffgpv4Sg21j5HrwdZ+GpiE1JQvz4L9uGKQpS0eb9qlDrGiq7WwRK+nNcogOz2SkqizsZMVMGljkzk4E34EqWO7PjyH3eDCju+GIbxwtq1a+1dn7zRtGlTPPbYYw7CWTSyY8cOvPDCC/juu+/Qs2dPZGRkoF+/frBarTXvLBxfroQv4fhyE2r/5ptvIj8/H5s2bUJ6erpORy9TXV2Nt99+GzNnzsTu3buRkJCAXr164ZlnnsGll16q+/MxDGPjtttCfQTqyM4GTp1CNoCDtjllY3FOE+V0THiSnQ0UFaGOrStncXExKisrUWUbi8zCgBBKx5eyzJFF1KiDHV9M5OAt44sdX/ohBi0Ot2cYRiN16tThoH8bFRUVqu63b98+AMDQoUNRr149xMfHIz093bUrSxlu7yyMeQm237dvH7p164ZWrVqhro+LE3ch6VarFbfddhtefPFFjBkzBjt27MCyZcuQk5ODvn374vvvv/fp+RiGiSBs4pbS8dXQZFuucmlaeGN77WrbhK7i4mK76wsATGJ9Fi7CFxN1sPDFRA7eMr7Y8aUfSseXcmHFpY4ME9UUFxfj7rvvRkpKCurXr48pU6bUuI9zqePEiRPRuHFjxMfHo0GDBhgzZgwAKt07dOgQHn/8cUiSZA/hPnXqFIYPH45GjRohKSkJHTp0wJdffunwHH379sWYMWMwfvx4ZGZmol69epg4caLDfQoLC/Hggw8iOzsbCQkJuPDCC/Hzzz/bf75ixQr07t0biYmJyMnJwZgxYxwm8c5MnDgRnTt3xgcffICcnBwkJSXh5ptvRqEo7wDs5YmTJk1CgwYN0NrWfnzLli244oorkJiYiKysLDz44IM4f/68/XGHDBkCADCZTPb/g3Opox2b8FVRUYHxTz6Jhg0bIjk5GRdffDGW/vEH3ceF46tp06aYO3cuZs+eDUmSMGLECABAbm4uhg4dipSUFKSlpeGWW27BccWCQvzdn3zyCZo3b474+HiXTrRvvvkGc+bMwezZs3H//fejWbNm6NSpEz788ENcd911uP/++z3+f52f77PPPkPTpk2Rnp6O2267DedEbgtIZHvttdfQvHlzJCYmolOnTpgzZ4795926dXN4bw4bNgwxMTEoKioCQCWfkiRh165dXo+HYRgdsc0vswH7Z7qBcOawWBHe2F67TNvmR3Fxsb3MMd1kgiRK7QO9Oe5ucx6Qha8GDQJ7DExYwsIXEzlwxlfwEINKRQUgwiqLiwHbAMeOL4aJTp588kksWbIE3333HRYuXIilS5di/fr1bu8/Z84cvPnmm/jggw+wZ88efP/99+jQoQMAYN68eWjUqBFefPFF5OfnI982YS0rK0O3bt3w888/Y+vWrXjwwQdx1113YfXq1Q6P/emnnyI5ORmrV6/Ga6+9hhdffBGLFi0CAFgsFlx99dVYsWIFPv/8c2zfvh3/+c9/YDabAZAQNWjQINxwww3YvHkzvv76ayxfvhyjRo3y+Pfv3bsX33zzDX766ScsWLAAmzZtwsiRIx3u8/vvv2PHjh1YtGgRfv75Z5SUlOCqq65CRkYG1q5di2+//Ra//fab/bnGjRuHmTNnAoDD/8EtZjNgMuH/XngBf/31F7766its3rwZN990E656+GHsyc116fhau3YtrrrqKtxyyy3Iz8/HW2+9BavVimHDhuH06dNYtmwZFi1ahH379uHWW291+XfPnTsXmzZtcnlYX3zxBVq3bm0X8ZQ88cQTOHXqlP318ca+ffvw/fff4+eff8bPP/+MZcuW4T//+Y/958888wxmzpyJadOmYdu2bXj88cdx5513YtmyZQBIGF26dCkAEsn+/PNPZGRkYPny5QCAJUuWoF69emjDnbIYJrgoHF/2m4SQzsJXeGN77WrZBC6l8NUkMZHuk5QEqIw68Bl2fDFu4IwvJnIQYsuZM5RtEqN4e1ut7PjSk4QECrEsKiLXV61asuCYkACkpIT08BiGCT7nz5/HjBkzMHv2bAwYMAAAiU+NGjVy+zu5ubmoV68errzySsTGxqJx48a46KKLAACZmZkwm81ITU1FPUW2S8OGDTFu3Dj796NHj8aCBQvw7bff4mJbG3UA6NixI55//nkAQKtWrfDuu+/i999/x4ABA/Dbb79hzZo12LFjh9111bx5c/vvTp48Gbfffrs9W6xVq1Z4++230adPH0ybNg0JbjKyysrKHP7md955B9dccw2mTJli/xuSk5Px8ccfI84W2PzRRx+htLQUs2fPtmefvfvuuxgyZAheffVVZGdn20sa66nMuNmXn48vFy7EkV270KBVKwDAuEcfxYJvv8XMn37Cv104xerUqYP4+HgkJiban2fRokXYvHkzDhw4gJycHADAZ599hvbt22Pt2rXo0aMHAHKXffbZZ6jjYdNj9+7daNu2rcufidt3796t6u+zWCyYNWsWUm3hxHfddRd+//13vPLKKyguLsYbb7yBxYsXo1evXgDotV2+fDk++OAD9OnTB3379sWMGTNgsViwZcsWmM1m3HnnnVi6dCkGDx6MpUuXok+fPqqOhWEYHVE4vgR1q6vpCosV4Y1t3Ei1iV1K4SsnPp42yINRESKEr9OnqeRfZMQBLHxFOez4YiKHzEw5qFC4uwTnz8ut3dnxpQ/OVmJlsD0HRjJM1LFv3z5UVFTYxQaAxCtPrpmbb74ZpaWlaN68OR544AF899139iBcd1RXV+OVV15Bx44dkZWVhZSUFCxcuBC5ubkO9+vYsaPD9/Xr10eB7Ty1adMmNGrUyC56ObN+/XrMmjULKSkp9q9BgwbBYrHgwIEDbo+tcePGDkJfr169YLFYHErmOnToYBe9AAqu79Spk0Pg/6WXXlrj97SwYfduWK1WtO7SRf4bMjOxbMMG7MvPB0zqpn87duxATk6OXfQCgHbt2qFWrVrYsWOH/bYmTZp4FL3Uovy/eKJp06Z20QtwfG23b9+OsrIyDBgwwOH1mz17tj0rrXfv3jh37hw2btyIZcuWoU+fPujXr5/dEcbCF8OECBeOL5EZxWJFmGMTnFJsZfrKjK+GQnwKhvCVlUXOZ6BmEy4WvqIadnwxkYPZTOLXqVPkPspW7BcJt1diItlsGf+pWxfYu1ceVDjYnmGiGpcdBr2Qk5ODXbt2YdGiRfjtt9/wyCOPYPLkyVi2bBlilbu0CqZMmYI333wTU6dORYcOHZCcnIzHHnusRlC88+9LkgSLrdtUoii7cIPFYsFDDz1kzxtT0rhxY9V/n8jjkhSbAc4dLa1Wq8PPXf2+ViySBLPZjPWLFsEszsmnTwN5eUjRsPBwd2zOt6vp0tmqVSts377d5c+EiOZOiHTG02srLn/55Rc0bNjQ4X7xthLP9PR0dO7cGUuXLsWKFStwxRVX4PLLL8emTZuwZ88e7N69G3379lV1LAzD6IgLx1emOLezWBHe2ETLRFtWYklJid3xVV8IUcEQvkwmWoscO0ab88pxgIWvqIYdX0xk4S7ni/O99Me5hp6D7RkmqmnZsiViY2OxatUq+21nzpzxWr6WmJiI6667Dm+//TaWLl2KlStXYsuWLQDIAVQtylxs/Pnnnxg6dCjuvPNOdOrUCc2bN8eePXs0HWvHjh1x5MgRt8fWtWtXbNu2DS1btqzx5cmVlJubi6NHj9q/X7lyJUwmk0dBp127dti0aZNDsPtff/3l9fc80aVjR1RXV6Pg+HH52Bs0QMucHNTzUHrq6thyc3Nx+PBh+23bt2/H2bNn3ZYtumP48OHYs2cPfvrppxo/mzJlCho0aGAvkfWHdu3aIT4+Hrm5uTVeO6VzrW/fvliyZAn++OMP9O3bF7Vq1UK7du3w8ssvo27dupr/PoZhdMDJ8WUGkCa60bJYEd7Y1gUJtuxfZaljtnAZB2uN4C7ni4WvqIaFLyayEMKXcHgJxPcsfOmHGLyE40tZ6sgwTNSRkpKC++67D08++SR+//13bN26FSNGjIDJQ1ndrFmzMGPGDGzduhX79+/HZ599hsTERDRp0gQAlbT98ccfyMvLw0nbebxly5ZYtGgRVqxYgR07duChhx7CsWPHNB1rnz590Lt3b9x4441YtGgRDhw4gP/9739YsGABAOCpp57CypUrMXLkSLsL6Mcff8To0aM9Pm5CQgLuuece/P333/jzzz8xZswY3HLLLR6zue644w77723duhVLlizB6NGjcddddyFb6VzWQOvWrXHHVVfh7tGjMW/ePBw4cABr167Fq59+ivm2AHc1XHnllejYsSPuuOMObNiwAWvWrMHdd9+NPn36oHv37pqO6bbbbsOwYcNwzz33YMaMGTh48CA2b96Mhx56CD///DM+//xzty4/LaSmpmLcuHF4/PHH8emnn2Lfvn3YuHEj3nvvPXz66af2+/Xt2xcLFiyAJElo166d/bb//ve/XObIMKHCdq6sA1qkZtsuYTZzRm+4Y3vtYk+fBuBY6miXu4ItfClLHSsqZCMEC19RCQtfTGQhBkV3ji8eNPWDHV8MwzgxefJk9O7dG9dddx2uvPJKXHbZZejWrZvb+9eqVQsfffQRLr30UnTs2BG///47fvrpJ2TZNilefPFFHDx4EC1atLBnSD377LPo2rUrBg0ahL59+6JevXoY5iKs3Rtz585Fjx49MHz4cLRr1w7jx4+3u8s6duyIZcuWYc+ePbj88svRpUsXPPvss6jvZbLcsmVL3HDDDRg8eDAGDhyICy+8EO+//77H30lKSsKvv/6K06dPo0ePHrjpppvQv39/vPvuu5r/JjsxMZj5/PO4+/rr8cQTT6BNmza47sEHsXrrVuQ0bar6YSRJwvfff4+MjAz07t0bV155JZo3b46vv/5a8yFJkoRvv/0W//rXv/Dmm2+iTZs26NSpE+bMmYONGzeiX79+mh/THS+99BKee+45TJo0CW3btsWgQYPw008/oVmzZvb79O7dGwCJoKJss0+fPqiurmbhi2FCRe3asEoSzABqA7CfcbOzVWcTMiHCNv83VVUhA46Or9q2EvSQOr7EBllcHEXjMFGHZPUllCPIFBUVIT09HWfPnkVaWlqoD4cJZx56CPjwQ2DiRMDWzQsA8PbbwKOPArfcAvgwYWdc8N57wKhRwA03AHPnAvfcA8yeDfznP8BTT4X66BgmbCgrK8OBAwfQrFkzt90AGeMzceJEfP/999i0aVOoD4U2ew4coO67rVtTZ+ONGwGLBWjfnvIuw4ANGzbgyiuvxH333YfJkyeH+nCiEj4/MWFHdjZQUIBOABoD+AkAunUD1q0L7XEx3snMBM6cQTsAu0wmTJ06FWPGjMHmunXRoaAA+Pxz4I47An8c48YBU6YAY8fSJQCsXg307Ak0bgwcOhT4Y2CCghadiKVzJrJwl/ElSh3Z8aUfzjZiDrdnGIYJD2JsvYtEN+OqKhK9AMAW8B4OdO3aFb///juSk5PtHRcZholyFAH3dscXl6YZA8VrZ7FYcObMGQBAhmhQEErHF+d7RT0sfDGRhbuMLw631x8xeHGpI8MwTHghhK+qKroU4dBxcWFXLtSlSxdMnDgRLVq0AAC0b98eKSkpLr/++9//hvhoGYYJOIqAexa+DIZTc4ITtrWBvUEBC19MCIkJ9QEwjK64y/hix5f+ODu+ONyeYZgoZuLEiZg4cWKoD4MQIfFVVVTmWFZG3xuglG3+/PmoFE41J3wN+2cYxkCw48u42ISvhmYzUF2NgoICSABSxBjEwhcTQlj4YiILd6WO7PjSHzF4nT1LiyoudWQYhgkPhOPLagWqq2XHVxiVObpDdPRkGCZKYceXcbEJTo1iYoDqapw4cQKZAEwiUjxYBgQWvhgXhJffnWH8xV2pIzu+9KdWLdlVcOAAUFpK17nUkWEYJrSYTIDZTNcrK2XHlwGEL4Zhohx2fBkXm2jZwDb+nDhxAvZVQWamvG4INEL4OnmSNn8AFr4YFr6YCEMpfCkblrLjS38kSRa5tm2jy4QEIDk5dMfEMAzDEMqcL+H4MkCpI8MwUY7C8SWyolisMAg2wUmZ8WUXvoK5MV6nDq1TLBZ5DcjCV9TDwhcTWQhHV2UlleAJ2PEVGMQgtnWr/L0khe54GIZhGELsrFdWGqrUkWGYKMcmntQHC1+GwyZa1rWZD06ePBka4SsmRjY7iHJHFr6iHha+mMgiIQFISaHrInOqpEQu82DHl74IK7EQvjjfi2EYJjwQjq+yMrnUg4UvhmHCHZt40gpAnLiNG1sYA9vrVNs25lRXV4dG+FI+3/HjNAYKAYyFr6hFs/D1xx9/YMiQIWjQoAEkScL333/v9XeWLVuGbt26ISEhAc2bN8f06dN9OVaGUYdzzpe4jIuTRTFGH5wdXyx8MQzDhAdC+Dp/ni7j4ij7i2EYJpyxCV9C9KpMT6fzFxP+2F67jMpKiPqPkAlfyoD7Eyeo7NFk4iziKEbzDKi4uBidOnXCu+++q+r+Bw4cwODBg3H55Zdj48aN+Ne//oUxY8Zg7ty5mg+WYVQhyhmF40uZ78VlePoiBpW9e+mSBxOGiSoOHjwISZKwadOmUB9K0Jg1axZq1aql6Xec/09Lly6FJEkoLCzU/fjsiFLH4mK6jAC317FjxzBgwAAkJyfbXwPlJmw0vh8ZJuLIyoJFIdJX86aqcbC9VmarFaLGJiyEL1HmWLeu3PiFiTo0C19XX301Xn75Zdxwww2q7j99+nQ0btwYU6dORdu2bXH//ffj3nvvxeuvv675YBlGFWKAFMKXcHxxmaP+iEFMlNHw5IRhIgZJkjx+jRgxItSH6JagCEt+cMkllyA/Px/p6ele7+vz3yIcX+L8HAHB9m+++Sby8/OxadMm7N69GwCQn5+Pq6++OsRHxjCMbphMKFVUaFi4zNE4xMbaDQginy2shC8uc4xqYgL9BCtXrsTAgQMdbhs0aBBmzJiByspKxAarrSkTPTiXOgrHFwfb64/zZIQdXwwTMeSLiSKAr7/+Gs899xx27dplvy0xMRFnzpwJxaEZnri4ONSrV8/7Hf0hxmmKF8aOL7XzwX379qFbt25o1aqV/baA/x8Zhgk6ZbVqIbmoiL5hscJYZGcDJ08iG8BWsPDFhA8BD3s4duwYsp0Wx9nZ2aiqqsJJIUw4UV5ejqKiIocvhlGNs+NLWerI6IvzIMaOL4aJGOrVq2f/Sk9PhyRJNW4T7N+/H/369UNSUhI6deqElStXOjzWihUr0Lt3byQmJiInJwdjxoxBsSjBc8G+ffswdOhQZGdnIyUlBT169MBvv/3mcJ/y8nKMHz8eOTk5iI+PR6tWrTBjxgwcPHgQ/fr1AwBkZGQ4uNOaNm2KqVOnOjxO586dMXHiRPv3b7zxBjp06IDk5GTk5OTgkUcewXmRk6WSNWvWoEuXLkhISED37t2xceNGh587u7gOHTqEIUOGICMjA8nJyWjfvj3mz5/v8W9ZsGABLrvsMtSqVQtZWVm49tprsW/fPvtzHDx6FFKPHpi3eDH6Pfwwkpo3d/na/PXXX+jTpw+SkpKQkZGBQYMG2QVNq9WK1157Dc2bN0diYiI6deqEOXPmePzbmzZtipdeegm33347UlJS0KBBA7zzzjsO95EkCdOnT8fQoUORnJyMl19+GQAwbdo0tGjRAnFxcWjTpg0+++wzh8edO3cuZs+e7fB/8JY3u337dgwePBgpKSnIzs7GXXfd5Xb+yTBMeFCZmWm/LjVoEMIjYTRj24wIK8fX0aN0nYWvqCYoKaeSU66S1dbi1Pl2waRJk5Cenm7/ysnJCfgxMhGEc8aXmOCy40t/nB1fLHwxjCqsViuKi4uD/iXGX715+umnMW7cOGzatAmtW7fG8OHDUVVVBQDYsmULBg0ahBtuuAGbN2/G119/jeXLl2PUqFFuH+/8+fMYPHgwfvvtN2zcuBGDBg3CkCFDkJuba7/P3Xffja+++gpvv/02duzYgenTpyMlJQU5OTn2HNFdu3YhPz8fb731luq/xWQy4e2338bWrVvx6aefYvHixRg/frzq3y8uLsa1116LNm3aYP369Zg4cSLGjRvn8XdGjhyJ8vJy/PHHH9iyZQteffVVr39LcXExxo4di7Vr1+L333+HyWTC9ddfD4vFQg9qc3w9PW0axt15JzatWlXjtdm0aRP69++P9u3bY+XKlVi+fDmGDBmCalt55DPPPIOZM2di2rRp2LZtGx5//HHceeedWLZsmce/Z/LkyejYsSM2bNiACRMm4PHHH8eiRYsc7vP8889j6NCh2LJlC+6991589913ePTRR/HEE09g69ateOihh/B///d/WLJkCQBg7dq1uOqqq3DLLbeofk3z8/PRp08fdO7cGevWrcOCBQtw/Phx3HLLLV5/l2GY0FGtmLObeR1oLGzCl1ghhIXwxY4vBgCsfgDA+t1333m8z+WXX24dM2aMw23z5s2zxsTEWCsqKlz+TllZmfXs2bP2r8OHD1sBWM+ePevP4TLRwowZVitgtV59NX0/ejR9/69/hfa4IpG8PPrfiq/Vq0N9RAwTdpSWllq3b99uLS0ttd92/vx5K4Cgf50/f96nv2HmzJnW9PT0GrcfOHDACsD68ccf22/btm2bFYB1x44dVqvVar3rrrusDz74oMPv/fnnn1aTyeTwP/FGu3btrO+8847VarVad+3aZQVgXbRokcv7LlmyxArAeubMGYfbmzRpYn3zzTcdbuvUqZP1+eefd/u833zzjTUrK8v+vbv/heCDDz6wZmZmWouLi+23TZs2zQrAunHjRpfH16FDB+vEiRM1/S3OFBQUWAFYt2zZYrVardYDu3fTa/PMM1br2rVWa1VVjddm+PDh1ksvvdTl450/f96akJBgXbFihcPt9913n3X48OFuj6NJkybWq666yuG2W2+91Xq1GJOtNH987LHHHO5zySWXWB944AGH226++Wbr4MGD7d8PHTrUes899zjcRzkXFe9H8X9+9tlnrQMHDnS4v5hT7tq1y+3fEE24Oj8xTKjJveMO+9zS8tVXoT4cRgtjx1qtgPU1wBqnXCOcPh3c41i7lp63YUOrddgwuv7ee8E9BibgnD17VrVOFHDHV69evWrs8i1cuBDdu3d3m+cQHx+PtLQ0hy+GUY1zxhc7vgKHs8OLHV8ME5V07NjRfr2+bUe1oKAAALB+/XrMmjULKSkp9q9BgwbBYrHgwIEDLh+vuLgY48ePR7t27VCrVi2kpKRg586ddsfXpk2bYDab0adPH93/liVLlmDAgAFo2LAhUlNTcffdd+PUqVMeSzOV7NixA506dUJSUpL9tl69enn8nTFjxuDll1/GpZdeiueffx6bN2/2+jz79u3D7bffjubNmyMtLQ3NmjUDANkVZ3N8dWzZkgKHzeYar41wfLli+/btKCsrw4ABAxxeu9mzZzuUVLrC+e/t1asXduzY4XBb9+7dHb7fsWMHLr30UofbLr300hq/p4X169djyZIlDsd/wQUXAIDXv4FhmNBhUmT3camjwVA4vsSqwBoTA2jshuw3wmFWUMCljgwAH8Ltz58/j71799q/P3DgADZt2oTMzEw0btwYEyZMQF5eHmbPng0AePjhh/Huu+9i7NixeOCBB7By5UrMmDEDX375pX5/BcMo4Yyv4BEbC2RmAqdP0/ccbs8wqkhKStKcG6XX8wYC5UaWiDEQJXcWiwUPPfQQxowZU+P3Gjdu7PLxnnzySfz66694/fXX0bJlSyQmJuKmm25CRUUFAArW9wWTyVSj3LOystJ+/dChQxg8eDAefvhhvPTSS8jMzMTy5ctx3333OdzPE86Pr4b7778fgwYNwi+//IKFCxdi0qRJmDJlCkaPHu32d4YMGYKcnBx89NFHaNCgASwWCy688EL7/wi21yE2Jsbe0dH5tfH0fxT3+eWXX9CwYUOHn8X7EJTvHG+RnJzs9T5Wq9VtLIYaLBYLhgwZgldffbXGz+rzAohhwpbU1q3lb/izaixsJYb1IJc5SnXr2sekoCHWJJWVwM6ddJ3fS1GNZuFr3bp19qBVABg7diwA4J577sGsWbOQn5/vkMHRrFkzzJ8/H48//jjee+89NGjQAG+//TZuvPFGHQ6fYVzAGV/BpW5dEr4SEwEXCxmGYWoiSZLLhX8k0rVrV2zbtg0tW7ZU/Tt//vknRowYgeuvvx4AbbodPHjQ/vMOHTrAYrFg2bJluPLKK2v8flxcHADYs6oEderUcehWWVRU5OA6W7duHaqqqjBlyhSYTGSK/+abb1QfNwC0a9cOn332GUpLS+3C0qpVq7z+Xk5ODh5++GE8/PDDmDBhAj766COMHj3a5d9y6tQp7NixAx988AEuv/xyAMDy5cvdP7gboapjx474/fff8cILL7j8O+Lj45Gbm6vZWef8965atcrutHJH27ZtsXz5ctx9993221asWIG2bdtqem4lXbt2xdy5c9G0aVPEOHe5ZBgmbElTjhfcudVYKMLtQ5bvBdCGT3o6cPYswB1CGfgQbt+3b19YrdYaX7NmzQIAzJo1C0uXLnX4nT59+mDDhg0oLy/HgQMH8PDDD+tx7AzjGuH4Ki4GSkvZ8RVoRHgklzkyDOOCp556CitXrsTIkSOxadMm7NmzBz/++KNHN1PLli0xb948bNq0CX///Tduv/12ObQd1OHvnnvuwb333ovvv/8eBw4cwNKlS+0iVZMmTSBJEn7++WecOHHC7q674oor8Nlnn+HPP//E1q1bcc8998BsNtsft0WLFqiqqsI777yD/fv347PPPsP06dM1/b233347TCYT7rvvPmzfvh3z58/H66+/7vF3HnvsMfz66684cOAANmzYgMWLF9sFH1d/S0ZGBrKysvDhhx9i7969WLx4sX0j0iVuhK8JEyZg7dq1eOSRR7B582bs3LkT06ZNw8mTJ5Gamopx48bh8ccfx6effop9+/Zh48aNeO+99/Dpp596/Hv++usvvPbaa9i9ezfee+89fPvtt3j00Uc9/s6TTz6JWbNmYfr06dizZw/eeOMNzJs3z2tjAE+MHDkSp0+fxvDhw7FmzRrs378fCxcuxL333ltDFGUYJowQgfYZGUBKSmiPhdGGbV2QjRALX4pjscMialQTlK6ODBNU0tKoBA8gtxc7vgKLGMy4zJFhGBd07NgRy5Ytw549e3D55ZejS5cuePbZZz2Wmr355pvIyMjAJZdcgiFDhmDQoEHo2rWrw32mTZuGm266CY888gguuOACPPDAA/YcroYNG+KFF17AP//5T2RnZ9s7SE6YMAG9e/fGtddei8GDB2PYsGFo0aKF/TE7d+6MN954A6+++iouvPBC/Pe//8WkSZM0/b0pKSn46aefsH37dnTp0gVPP/20y1I7JdXV1Rg5ciTatm2Lq666Cm3atMH777/v9m8xmUz46quvsH79elx44YV4/PHHMXnyZNcPbjLRuOiC1q1bY+HChfj7779x0UUXoVevXvjhhx/s7qiXXnoJzz33HCZNmoS2bdti0KBB+Omnn+x5Yu544oknsH79enTp0gUvvfQSpkyZgkGDBnn8nWHDhuGtt97C5MmT0b59e3zwwQeYOXMm+vbt6/H3PNGgQQP89ddfqK6uxqBBg3DhhRfi0UcfRXp6ut3RxzBMGNKqFTBlCjBjRqiPhNGKTVyqA8CezhYOwldmpttNICY6kKy+hFEEmaKiIqSnp+Ps2bMcdM+oo0EDal27YgVwySV025kzwQ9WjAZGjwbefRe4+mpg/vxQHw3DhB1lZWU4cOAAmjVrhgRb1hLDBA2rNajZKk2bNsVjjz2Gxx57LGjPyfgOn58YhtGV6mpY4+IgWSyYDeBuABg7loTMYHPzzcCcOXS9fXtg69bgHwMTULToRLzdxUQmouxOhBmazVTnzeiP6LbDdfMMwzDhR7ADhRmGYZjoxWxGdUYGAMDe7zkcHF+8Tol6OOmTiUycha+sLJ78B4oRI4C8POCRR0J9JAzDMAzDMAzDhBBL3brAqVOwtyZh4YsJA1j4YiITV8IXExjq16dSR4ZhGCbqUXbfZBiGYaKQ7Gxgxw7YE7VY+GLCAC51ZCITEWQvhC8OtmcYhmEYhmEYhgkopoYNHW8IlfClfF4WvqIeFr6YyEQ4vvbto0t2fDEMwzAMwzAMwwQUs7PIxI4vJgxg4YuJTITwVV1Nl+z4YhiGYRiGYRiGCSiSs8gk1mXBRil8iWZcTNTCwhcTmTifYNnxxTAMwzAMwzAME1gUglN5bCyQlBTy42DHF8Ph9kxk4uzwYscXwzAMwzAMwzBMYKlXz361OCVFDrkPNsnJwNVXAwUFQNOmoToKJkxg4YuJTNjxxTAMwzAMwzAME1wUTquy1NQQHgiA+fMBqxWQpNAeBxNyuNSRiUychS92fDEMw+jOwYMHIUkSNm3aFOpDYVywdOlSSJKEwsJCvx7nww8/RE5ODkwmE6ZOnarqd5zfG3odS7Rx7NgxDBgwAMnJyahVqxYAQJIkfP/99wD4M8gwTBiicHyVp6eH8EBssOjFgIUvJlLJzHT8nh1fDMMwmpAkyePXiBEjAvbcs2bNsi/yw5m+ffva/x8mkwnZ2dm4+eabcejQoVAfmm4UFRVh1KhReOqpp5CXl4cHH3zQp8e55JJLkJ+fj3QViyAWyWTefPNN5OfnY9OmTdi9ezcAID8/H1dffXWIj4xhGMYNmZmosolNFRkZIT4YhiFY+GIik5gYR/GLHV8MwzCayM/Pt39NnToVaWlpDre99dZboT7EkFFRUWG//sADDyA/Px95eXn44YcfcPjwYdx5550hPDp9yc3NRWVlJa655hrUr18fST6GFMfFxaFevXqQeOcdAFBZWanqfvv27UO3bt3QqlUr1K1bFwBQr149xMeHLDWHYRjGMyYTKmybVw06dQrtsTCMDRa+mMhFWe7Iji+GYRhN1KtXz/6Vnp4OSZJq3CbYv38/+vXrh6SkJHTq1AkrV650eKwVK1agd+/eSExMRE5ODsaMGYPi4mKfjy03NxdDhw5FSkoK0tLScMstt+D48eMAgLNnz8JsNmP9+vUAAKvViszMTPTo0cP++19++SXqKzo85eXl4dZbb0VGRgaysrIwdOhQHDx40P7zESNGYNiwYZg0aRIaNGiA1q1b23+WlJSEevXqoX79+ujZsydGjhyJDRs2OBzvsmXLcNFFFyE+Ph7169fHP//5T1RVVdl/3rRp0xolhJ07d8bEiRPt30uShI8//hjXX389kpKS0KpVK/z4448OvzN//ny0bt0aiYmJ6Nevn8Pf4Mv/ctasWejQoQMAoHnz5pAkye1jrlmzBl26dEFCQgK6d++OjRs3Ovzc2cV16NAhDBkyBBkZGUhOTkb79u0xf/58HDx4EP369QMAZGRkOLgLFyxYgMsuuwy1atVCVlYWrr32Wuzbt8/+HKLsb968eR7fj3/99Rf69OmDpKQkZGRkYNCgQThz5gwAer+89tpraN68ORITE9GpUyfMmTPH4/+wadOmeOmll3D77bcjJSUFDRo0wDvvvONwH0mSMH36dAwdOhTJycl4+eWXAQDTpk1DixYtEBcXhzZt2uCzzz5zeNy5c+di9uzZDv8HZamjK7Zv347BgwcjJSUF2dnZuOuuu3Dy5EmPfwPDMIyeJDVrBgBIbd48xEfCMAQLX0zkIoQvSQIMUDLDMEwUYbUCxcXB/7JaA/LnPP300xg3bhw2bdqE1q1bY/jw4XZhZ8uWLRg0aBBuuOEGbN68GV9//TWWL1+OUaNG+fRcVqsVw4YNw+nTp7Fs2TIsWrQI+/btw6233goASE9PR+fOnbF06f+3d//BNZ75/8df54QgEilaIW2isUoThPixlpTEVkOzDO1uWVLsYpdJ/EjSdklL/WpjsKzdIn6soatrmumo9Xsbi08k1CQbCSopqtlNtlhaJhKCkXN9/2hzf3v8iCjJWSfPx8wZOde57vt+39fc73Pineu+zv9Jko4ePWr9e/nyZUnfFmEiIiIkSVevXlW/fv3k7e2t/fv3KzMzU97e3ho4cKDTzK49e/aooKBAu3fv1vbt2+8Y28WLF/XRRx+pZ8+eVttXX32l6Oho9ejRQ0eOHFFKSorWrl1rFT7ux5w5czRs2DAdPXpU0dHRiomJ0cWLFyVJxcXFevnllxUdHa28vDyNHz9e06dPf6CxHD58uP7xj39I+rawdfbsWQUEBNy2nytXrmjQoEFq3769cnJyNHv2bL3++utVHjsuLk7Xr1/X/v37dezYMS1YsEDe3t4KCAjQpk2bJEknTpxwml145coVJSYmKjs7W3v27JHdbtdLL70kh8PhtO+qrse8vDw9//zz6tChgz799FNlZmZq8ODBqqiokCTNmDFD69atU0pKio4fP66EhAS9+uqrSk9Pr/J8Fi1apNDQUB0+fFhJSUlKSEjQ7t27nfrMmjVLQ4YM0bFjxzR27Fht3rxZU6dO1WuvvabPPvtMEyZM0K9//Wvt27dPkpSdna2BAwdq2LBh1Z5lefbsWUVERKhLly765z//qb///e/673//q2HDht1zWwB4aIKDv/332WddGwdQyTwCSkpKjCRTUlLi6lDwKBk61BjJmObNXR0JgDqsvLzc5Ofnm/Ly8v/fWFb27ftTbT/Kyn7QOaxbt874+vre1l5YWGgkmT//+c9W2/Hjx40kU1BQYIwxZtSoUea3v/2t03YZGRnGbrc7j0k1jmeMMWlpacbDw8MUFRXddsysrCxjjDGJiYlm0KBBxhhjli5dan7xi1+Yrl27mh07dhhjjGnXrp1JSUkxxhizdu1a0759e+NwOKz9Xb9+3TRq1Mh88sknxhhjxowZY/z8/Mz169edYomIiDD169c3jRs3Nl5eXkaSadeunSksLLT6vPnmm7ftf/ny5cbb29tUVFQYY4xp3bq1+cMf/uC0786dO5tZs2ZZzyWZGTNmWM/LysqMzWYzu3btMsYYk5SUZIKDg52OM23aNCPJXLp06QePZW5urpHkdE63WrVqlWnWrJm5cuWK1ZaSkmIkmdzcXGOMMfv27XOKpVOnTmb27Nl33N+tfe/m/PnzRpI5duyYMaZ61+OIESNMeHj4HfdXVlZmGjZsaA4ePOjUPm7cODNixIi7xtG6dWszcOBAp7bhw4ebF1980XouycTHxzv16d27t/nNb37j1PbKK6+Y6Oho6/mQIUPMmDFjnPpIMps3b3Y658pxnjlzpomKinLqX1xcbCSZEydO3Bb7Hd+fAOBBXbxozN69xnz3OQfUhPupEzHjC+6rcsYXtzkCQI0KDQ21fq68hfD8+fOSpJycHK1fv17e3t7WY8CAAXI4HCosLLzvYxUUFCggIMBp5lFISIgee+wxFRQUSPp20fmMjAw5HA6lp6crMjJSkZGRSk9P17lz53Ty5ElrxldOTo6++OIL+fj4WPE1a9ZM165dc7qNrlOnTvL09LwtnpiYGOXl5enIkSPKzMxU27ZtFRUVpdLSUiveXr16Oa1tFR4errKyMv3nP/+5r3P//jg3btxYPj4+1jgXFBToJz/5idNxevXqVeX+qjOW1VFQUKDOnTs7rf91r2NPmTJF77zzjsLDwzVr1ixrZl5VTp8+rZEjR6pNmzZq0qSJgr67laaoqMipX1XXY+WMrzvJz8/XtWvX9MILLzhdr3/5y1+croU7ufV8e/XqddsYdu/e3el5QUGBwsPDndrCw8Pva+xvlZOTo3379jnF/+x3My7udQ4A8NA0bSr16yfZKTfgf0M9VwcA1JjKwhcL2wP4X+PlJZWVuea4NaB+/frWz5WFl8rbzxwOhyZMmKApU6bctl1gYOB9H8sYc8cF0r/f3rdvX5WWlurw4cPKyMjQvHnzFBAQoOTkZHXp0kUtWrRQ8He3YTgcDnXr1k1//etfb9vnE99bK7Jx48Z3jMfX11dt27aVJLVt21Zr165Vq1atlJqaqvHjx98xXvPdLaeV7Xa73WqrdKfFz78/zpXbV47zrdtXR3XGsrr7uV/jx4/XgAEDtGPHDqWlpWn+/PlavHixJk+efNdtBg8erICAAK1Zs0b+/v5yOBzq2LGj0y2pUtXXY6NGje66/8o+O3bs0JNPPun02g9ZTP7WMbzTNXSna+NBvgDA4XBo8ODBWrBgwW2vfX9dOwAA6hIKX3Bf3337EYUvAP9zbDbpLoUUd9O1a1cdP37cKg49qJCQEBUVFam4uNiaqZSfn6+SkhKrmFW5zteyZctks9kUEhIif39/5ebmavv27dZsr8r4UlNT1aJFCzVp0uSB4/Pw8JAklZeXW/Fu2rTJqaBx8OBB+fj4WMWVJ554QmfPnrX2cfny5fueDRcSEnLbgueHDh265zb3GsvqHnvDhg0qLy+3Ckv3OrYkBQQEaOLEiZo4caKSkpK0Zs0aTZ482ZpZV7nuliR98803Kigo0KpVq9SnTx9JUmZmZrVjrBQaGqo9e/Zozpw5dzyPBg0aqKioyOkaqY5bz/fQoUPWTKu7CQ4OVmZmpkaPHm21HTx48L7G/lZdu3bVpk2b9PTTT6tePX7NBwBAYnF7uLOXXpIGDpRiY10dCQDUWdOmTdOnn36quLg45eXl6dSpU9q6dWuVM3ukb4seeXl5To/8/Hz1799foaGhiomJ0eHDh5WVlaXRo0crIiLC6VayyMhIffDBB4qIiJDNZlPTpk0VEhKi1NRURUZGWv1iYmL0+OOPa8iQIcrIyFBhYaHS09M1derUat2KePXqVZ07d07nzp3TkSNHFBsbq4YNGyoqKkqSFBsbq+LiYk2ePFmff/65tmzZolmzZikxMVH2724B+elPf6oNGzYoIyNDn332mcaMGWMV0Kpr4sSJOn36tBITE3XixAlt3LhR69evr3Kb6o7lvYwcOVJ2u13jxo1Tfn6+du7cqd///vdVbhMfH69PPvlEhYWFOnz4sPbu3WsVfFq3bi2bzabt27frwoULKisrs75xc/Xq1friiy+0d+9eJSYmVjvGSklJScrOzlZsbKyOHj2qzz//XCkpKfr666/l4+Oj119/XQkJCXr//fd1+vRp5ebmavny5Xr//fer3O+BAwe0cOFCnTx5UsuXL9dHH32kqVOnVrnNG2+8ofXr12vlypU6deqUlixZoo8//vieXwxQlbi4OF28eFEjRoxQVlaWvvzyS6WlpWns2LFOhUQAAOoSCl9wX4GB0q5d0oABro4EAOqs0NBQpaen69SpU+rTp4/CwsI0c+bMe952VVZWprCwMKdHdHS0bDab/va3v6lp06bq27ev+vfvrzZt2ig1NdVp+379+qmiosKpyBUREaGKigqn2TxeXl7av3+/AgMD9fLLLys4OFhjx45VeXl5tWaArVmzRq1atVKrVq3Ur18/XbhwQTt37lT79u0lSU8++aR27typrKwsde7cWRMnTtS4ceM0Y8YMax9JSUnq27evBg0apOjoaA0dOlQ/+tGPqjO8lsDAQG3atEnbtm1T586dtXLlSiUnJ1e5TXXH8l68vb21bds25efnKywsTG+99dYdb7X7voqKCsXFxSk4OFgDBw5U+/bttWLFCknfjtmcOXM0ffp0+fn5adKkSbLb7frwww+Vk5Ojjh0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" ] @@ -247,13 +247,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "78e4d806-2c56-40d0-8636-9a385e4e592b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -290,13 +290,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "824fe60a-8df1-4db4-a7b6-a6283f671138", "metadata": {}, "outputs": [ { "data": { - "image/png": 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YYyqPfeC/80Pr1q1haWmJc+fOwdXVFSkpKejcuTMeP36MdevWISsrC+fOnYOHhwd/zJVkfyzufFUUVX3OxV3c+Y0T7UqCJucvdTGmpKSUeN0EQRAEoQ4SvgiCIIgKjbe3t1Y3v9zNW1pamsJnT58+hVAohJ2dXanFpw2VK1dGQUEBMjIy5MSvZ8+eaTy/sraazh8cHIzg4GDk5eXh6tWrWLZsGQYNGgR3d3e0atVK5Xxv377F8ePHsXDhQsyZM4efnpeXh4yMDI3WXRSuRtvjx4/h6uqqtE2VKlUAAOvWrVM5MqImoqGqPit6o19U3AIK+/zff/8FY0zu8xcvXqCgoICP8WPglhESEsLXDSuKl5eXyvn37t0LExMTHD9+HObm5vz0I0eOlDimj93XtMHY2BgzZszAjBkz8ObNG5w7dw7ffvstAgMD8ejRI41Fajs7OwiFQpXHPvBfX5uamqJt27Y4d+4cqlevDicnJzRo0AAeHh4ACgdGCAsLQ48ePfhllGR/VLZPqUNVn3t6egIo/vwmuz+am5srDK4BqBdR1cGtW1f7BUEQBEFwUKojQRAEQcjg5eWFatWqYffu3XIjsWVnZ+PgwYP8SI+AoqNBlqIOmNLA398fAPgi2xx79+7VaP727dsjPj5ewam0e/dureIwMzODv78/fvzxRwDgRzhU1R8CgQCMMf5zjs2bN0MikWi1bo4uXbrAyMgI69evV9mmTZs2sLW1RUJCApo2bar0ZWpqWuy69uzZI7cvPHz4EFeuXFE64l1ROnbsiKysLAURiRvJjhv58WPw8vJC7dq1ERsbq3I7ra2tVc4vEAhgbGwsl6aWk5ODnTt3ljim9u3bIywsjHc5AYBEIlHYd7VBk2PK1tYWffv2xcSJE5GRkaGVi8jKygotWrTAoUOH5NYjlUrxxx9/oHr16qhTpw4/vVOnToiKisLBgwf5dEYrKyu0bNkS69atw9OnT/npQOntj+rYtWuX3PsrV67g4cOH/L7aqlUrWFhY4I8//pBr9/jxY5w/f15uf3R3d8fdu3f50UeBQtcWl96pLV5eXnB2dlZ5PBEEQRBEWUGOL4IgCIKQQSgUYvny5Rg8eDB69OiBr776Cnl5eVixYgXevHmDH374gW/boEEDAMCaNWswfPhwmJiYwMvLC9bW1mjQoAH27t2Lffv2wcPDA+bm5nz7ktK1a1e0adMGM2fORGZmJpo0aYLIyEheRJGtSaaMadOmYevWrejevTu+++47ODo6YteuXbh9+3ax616wYAEeP36Mjh07onr16njz5g3WrFkDExMTXpCrVasWLCwssGvXLnh7e0MkEsHFxQUuLi5o164dVqxYgSpVqsDd3R3h4eHYsmULbG1tS9QX7u7u+Pbbb7FkyRLk5ORg4MCBsLGxQUJCAl69eoXFixdDJBJh3bp1GD58ODIyMtC3b184ODjg5cuXiI2NxcuXL9UKZxwvXrxA7969MXbsWLx9+xYLFy6Eubk5QkJCip132LBh+PXXXzF8+HCkpKSgQYMGiIiIwNKlSxEUFCQnjHwMGzduRLdu3RAYGIgRI0agWrVqyMjIQGJiIqKjo3HgwAGV83bv3h0///wzBg0ahHHjxiE9PR0//fSTglCpDfPmzcNff/2FDh06YMGCBbC0tMSvv/6qUU01Vag6pnr27In69eujadOmqFq1Kh4+fIjVq1fDzc0NtWvX1mody5YtQ+fOndG+fXvMmjULpqam+O2333Dr1i3s2bNHzoHVsWNHSCQShIWFYfv27fz0Tp06YeHChRAIBOjQoQM/vbT2R3Vcv34dY8aMQb9+/fDo0SPMnTsX1apVw4QJEwAUCoPz58/Ht99+i2HDhmHgwIFIT0/H4sWLYW5ujoULF/LLGjp0KDZu3IghQ4Zg7NixSE9Px/LlyxXSeTVFKBRiyZIlGDNmDH88vXnzBosWLSqTFFiCIAiC4NFnZX2CIAiCKCu4Uc7EYrHadspGyGOMsSNHjrAWLVowc3NzZmVlxTp27MguX76sMH9ISAhzcXFhQqFQbjkpKSmsS5cuzNramgHgRyxTN6rjy5cvlW6D7Ah4GRkZbOTIkczW1pZZWlqyzp07s6tXrzIAcqMjqiIhIYF17tyZmZubM3t7ezZ69Gh29OjRYkd1PH78OOvWrRurVq0aMzU1ZQ4ODiwoKIhdunRJbvl79uxhdevWZSYmJnKjET5+/Jj16dOH2dnZMWtra9a1a1d269Yt5ubmxoYPH66wzUW/N1Xf044dO1izZs2Yubk5E4lErFGjRgqjSoaHh7Pu3bsze3t7ZmJiwqpVq8a6d+/ODhw4oLavuHXu3LmTTZkyhVWtWpWZmZmxzz77jF2/fl2u7fDhw5mVlZXS5aSnp7Px48czZ2dnZmxszNzc3FhISAg/IiDHx4zqyBhjsbGxrH///szBwYGZmJgwJycn1qFDB7Zhwwa128kYY1u3bmVeXl7MzMyMeXh4sGXLlrEtW7Yo7H9ubm6se/fuCvMrGwHw8uXLrGXLlszMzIw5OTmxr7/+mv3+++8lHtVR1TG1cuVK1rp1a1alShVmamrKatSowUaPHs1SUlLUrkPZscgYY5cuXWIdOnRgVlZWzMLCgrVs2ZIdO3ZMYX6pVMqqVKnCALAnT57IbTf+/2igytBkf1R1TlAFd9ycOXOGDR06lNna2vKjN967d0+h/ebNm5mvry8zNTVlNjY2LDg4mMXHxyu02759O/P29mbm5ubMx8eH7du3T+WojitWrFCYv+i+y627du3azNTUlNWpU4dt3bpVYZkEQRAEUZoIGJPxGhMEQRAEUe7YvXs3Bg8ejMuXL9PoaKXIxYsX0b59exw4cEBtQXKCIAiCIAjCcKFUR4IgCIIoR+zZswdPnjxBgwYNIBQKcfXqVaxYsQLt2rUj0YsgCIIgCIIgikDCF0EQBEGUI6ytrbF371589913yM7OhrOzM0aMGIHvvvtO36ERBEEQBEEQhMFBqY4EQRAEQRAEQRAEQRBEhUT98E9FWLRoEQQCgdyruFFYwsPD0aRJE5ibm8PDwwMbNmz4qIAJgiAIgiAIgiAIgiAIQhO0TnWsV68ezp07x783MjJS2TY5ORlBQUEYO3Ys/vjjD1y+fBkTJkxA1apV0adPn5JFTBAEQRAEQRAEQRAEQRAaoLXwZWxsXKzLi2PDhg2oUaMGVq9eDQDw9vbG9evX8dNPP5HwRRAEQRAEQRAEQRAEQZQpWgtf9+7dg4uLC8zMzNCiRQssXboUHh4eSttGRkaiS5cuctMCAwOxZcsW5Ofnw8TERKN1SqVSPH36FNbW1hAIBNqGTBAEQRAEQRAEQRAEQVQQGGN49+4dXFxcIBSqr+KllfDVokUL7NixA3Xq1MHz58/x3XffoXXr1oiPj0flypUV2j979gyOjo5y0xwdHVFQUIBXr17B2dlZ6Xry8vKQl5fHv3/y5Al8fHy0CZUgCIIgCIIgCIIgCIKowDx69AjVq1dX20Yr4atbt278/w0aNECrVq1Qq1YtbN++HTNmzFA6T1GHFjeIpDrn1rJly7B48WKF6Y8ePUKlSpW0CZkgCIIgCIIgCIIgCIKoQGRmZsLV1RXW1tbFttU61VEWKysrNGjQAPfu3VP6uZOTE549eyY37cWLFzA2NlbqEOMICQmRE9K4DapUqRIJXwRBEARBEARBEARBEIRG5bA+SvjKy8tDYmIiPvvsM6Wft2rVCseOHZObdubMGTRt2lRtfS8zMzOYmZl9TGgEQRAEQRAEQRAEQRDEJ476CmBFmDVrFsLDw5GcnIx///0Xffv2RWZmJoYPHw6g0Kk1bNgwvv348ePx8OFDzJgxA4mJidi6dSu2bNmCWbNmle5WEARBEARBEARBEARBEEQRtHJ8PX78GAMHDsSrV69QtWpVtGzZElevXoWbmxsAIC0tDampqXz7mjVr4uTJk5g+fTp+/fVXuLi4YO3atejTp0/pbgVBEARBEARBEARBEARBFEHAuGrzBkxmZiZsbGzw9u1btTW+JBIJ8vPzdRgZQRAE8bGYmJjAyMhI32EQBEEQBEEQBFFO0FQnAj6yxpehwBjDs2fP8ObNG32HQhAEQZQAW1tbODk5aVSckiAIgiAIgiAIQlMqhPDFiV4ODg6wtLSkGyeCIIhyAmMM79+/x4sXLwAAzs7Oeo6IIAiCIAiCIIiKRLkXviQSCS96Va5cWd/hEARBEFpiYWEBAHjx4gUcHBwo7ZEgCIIgCIIgiFJDq1EdDRGuppelpaWeIyEIgiBKCncOpzqNBEEQBEEQBEGUJuVe+OKg9EaCIIjyC53DCYIgCIIgCIIoCyqM8EUQBEEQBEEQBEEQBEEQspDwRZQ6AQEBmDZtGv/e3d0dq1ev1ls85ZVFixbB0dERAoEAR44cwYgRI9CrVy/+86L9XBKePXuGzp07w8rKCra2th+1LIIgCIIgCIIgCIIwNMp9cXvC8BGLxbCystKorbu7O6ZNm/bRgk55JzExEYsXL8bhw4fRsmVL2NnZoX379mCMlep6Vq1ahbS0NMTExMDGxqZUlw0UDj6xdu1abNu2DXfv3oW5uTlatWqFefPmoU2bNqW+PoIgCIIgCIIgCIKQhRxfRJlTtWpVGnzg//PhwweN2iUlJQEAgoOD4eTkBDMzM9jY2JS6KyspKQlNmjRB7dq14eDgUKJlqCpGzhjDl19+if/973+YMmUKEhMTER4eDldXVwQEBODIkSMfETlBEARBEARBEARBFA8JXxUMiUSCvLw8na0vOzsbw4YNg0gkgrOzM1auXKnQpmiq46JFi1CjRg2YmZnBxcUFU6ZMAVCYuvfw4UNMnz4dAoGAL3adnp6OgQMHonr16rC0tESDBg2wZ88euXUEBARgypQpmD17Nuzt7eHk5IRFixbJtXnz5g3GjRsHR0dHmJubo379+jh+/Dj/+ZUrV9CuXTtYWFjA1dUVU6ZMQXZ2tsptX7RoERo2bIiNGzfC1dUVlpaW6NevH968ecO34dITly1bBhcXF9SpUwcAEBcXhw4dOsDCwgKVK1fGuHHjkJWVxS+3Z8+eAAChUMj3Q9FUx6J8+PABs2fPRrVq1WBlZYUWLVrg4sWLKtu7u7vj4MGD2LFjBwQCAUaMGAEASE1NRXBwMEQiESpVqoT+/fvj+fPnCtu9detWeHh4wMzMTKkTbf/+/fjzzz+xY8cOjBkzBjVr1oSfnx9+//13fP755xgzZoza/i26vp07d8Ld3R02Njb48ssv8e7dO74NYwzLly+Hh4cHLCws4Ofnhz///JP/vEmTJnL7Zq9evWBsbIzMzEwAhSmfAoEAd+7cKTYegiAIgiAIgiAIovxAwlcF4/79+4iLi9OZ+PX111/jwoULOHz4MM6cOYOLFy8iKipKZfs///wTq1atwsaNG3Hv3j0cOXIEDRo0AAAcOnQI1atXx//+9z+kpaUhLS0NAJCbm4smTZrg+PHjuHXrFsaNG4ehQ4fi33//lVv29u3bYWVlhX///RfLly/H//73P5w9exYAIJVK0a1bN1y5cgV//PEHEhIS8MMPP8DIyAhAoRAVGBiIL774Ajdv3sS+ffsQERGBSZMmqd3++/fvY//+/Th27BhOnTqFmJgYTJw4Ua5NWFgYEhMTcfbsWRw/fhzv379H165dYWdnB7FYjAMHDuDcuXP8umbNmoVt27YBgFw/FMfIkSNx+fJl7N27Fzdv3kS/fv3QtWtX3Lt3T2l7sViMrl27on///khLS8OaNWvAGEOvXr2QkZGB8PBwnD17FklJSRgwYIDS7T548CBiYmKULn/37t2oU6cOL+LJMnPmTKSnp/PfT3EkJSXhyJEjOH78OI4fP47w8HD88MMP/Ofz5s3Dtm3bsH79esTHx2P69OkYMmQIwsPDARQKo5wIyBjDpUuXYGdnh4iICADAhQsX4OTkBC8vL43iIQiCIAiCIAiCIMoHVOOrgpGTkwOgUCwyMzMr03VlZWVhy5Yt2LFjBzp37gygUHyqXr26ynlSU1Ph5OSETp06wcTEBDVq1EDz5s0BAPb29jAyMoK1tTWcnJz4eapVq4ZZs2bx7ydPnoxTp07hwIEDaNGiBT/d19cXCxcuBADUrl0bv/zyC8LCwtC5c2ecO3cO165dQ2JiIu+68vDw4OddsWIFBg0axNcWq127NtauXQt/f3+sX78e5ubmSrcnNzdXbpvXrVuH7t27Y+XKlfw2WFlZYfPmzTA1NQUAbNq0CTk5OdixYwdf++yXX35Bz5498eOPP8LR0ZFPaZTtB3UkJSVhz549ePz4MVxcXAAUCminTp3Ctm3bsHTpUoV5qlatCjMzM1hYWPDrOXv2LG7evInk5GS4uroCAHbu3Il69epBLBajWbNmAArdZTt37kTVqlVVxnT37l14e3sr/YybfvfuXY22TyqVIjQ0FNbW1gCAoUOHIiwsDN9//z2ys7Px888/4/z582jVqhWAwu82IiICGzduhL+/PwICArBlyxZIpVLExcXByMgIQ4YMwcWLFxEUFISLFy/C399fo1gIgiAIgiAIgiCI8gM5vioQjDFIJBIAQEFBQZmvLykpCR8+fODFBqBQvFLnmunXrx9ycnLg4eGBsWPH4vDhw8XGKpFI8P3338PX1xeVK1eGSCTCmTNnkJqaKtfO19dX7r2zszNevHgBAIiJiUH16tV50asoUVFRCA0NhUgk4l+BgYGQSqVITk5WGVuNGjXkhL5WrVpBKpXKpcw1aNCAF72AwsL1fn5+cgX/27RpozCfNkRHR4Mxhjp16shtQ3h4OF8vTBMSExPh6urKi14A4OPjA1tbWyQmJvLT3Nzc1IpemiLbL+pwd3fnRS9A/rtNSEhAbm4uOnfuLLftO3bs4Le9Xbt2ePfuHW7cuIHw8HD4+/ujffv2vCOMhC+CIAiCIAiC0D0fPnzA6dOnNSqBQhAlhRxfFQipVMrXWtKF8FWSEQZdXV1x584dnD17FufOncOECROwYsUKhIeHw8TEROk8K1euxKpVq7B69Wo0aNAAVlZWmDZtmkKh+KLzCwQCSKVSAICFhYXauKRSKb766iu+3pgsNWrU0Hj7uHpc3F8ACiNaMsbkPlc2v7ZIpVIYGRkhKiqKT9/kEIlEGi9HVWxFp2sySmft2rWRkJCg9DNORFMlRBZF3XfL/T1x4gSqVasm145zPdrY2KBhw4a4ePEirly5gg4dOuCzzz5DTEwM7t27h7t37yIgIECjWAiCIAiCIAiCKB22bduG8ePHIyQkRGmWCkGUBuT4qkBwbi9A9Uh7pYmnpydMTExw9epVftrr16+LTV+zsLDA559/jrVr1+LixYuIjIxEXFwcgEIHkOx2AMClS5cQHByMIUOGwM/PDx4eHirrVqnC19cXjx8/Vhlb48aNER8fD09PT4WXOldSamoqnj59yr+PjIyEUChUK+j4+PggJiZG7qnG5cuXi51PHY0aNYJEIsGLFy8U4tc0XZKLLTU1FY8ePeKnJSQk4O3btyrTFlUxcOBA3Lt3D8eOHVP4bOXKlXBxceFTZD8GHx8fmJmZITU1VWHbZZ1rAQEBuHDhAv755x8EBATA1tYWPj4++O677+Dg4KD19hEEQRAEQRAE8XHcunULAJCSkqLfQIgKDQlfFQhZwUgXji+RSITRo0fj66+/RlhYGG7duoURI0ZAKFS9W4WGhmLLli24desWHjx4gJ07d8LCwgJubm4AClPa/vnnHzx58gSvXr0CUCiwnT17FleuXEFiYiK++uorPHv2TKtY/f390a5dO/Tp0wdnz55FcnIy/v77b5w6dQoA8M033yAyMhITJ07kXUB//fUXJk+erHa55ubmGD58OGJjY3Hp0iVMmTIF/fv3Vys2DR48mJ/v1q1buHDhAiZPnoyhQ4fC0dFRq+3iqFOnDgYPHoxhw4bh0KFDSE5Ohlgsxo8//oiTJ09qvJxOnTrB19cXgwcPRnR0NK5du4Zhw4bB398fTZs21SqmL7/8Er169cLw4cOxZcsWpKSk4ObNm/jqq69w/Phx/PHHHypdftpgbW2NWbNmYfr06di+fTuSkpJw48YN/Prrr9i+fTvfLiAgAKdOnYJAIICPjw8/bdeuXZTmSBAEQRAEQRgkCQkJWLJkSYVNBXzy5AkA8CPcE0RZQMJXBULXwhdQWBS+Xbt2+Pzzz9GpUye0bdsWTZo0Udne1tYWmzZtQps2beDr64uwsDAcO3YMlStXBgD873//Q0pKCmrVqsXXkJo/fz4aN26MwMBABAQEwMnJCb169dI61oMHD6JZs2YYOHAgfHx8MHv2bL7PfH19ER4ejnv37uGzzz5Do0aNMH/+fDg7O6tdpqenJ7744gsEBQWhS5cuqF+/Pn777Te181haWuL06dPIyMhAs2bN0LdvX3Ts2BG//PKL1tsky7Zt2zBs2DDMnDkTXl5e+Pzzz/Hvv//KuZ6KQyAQ4MiRI7Czs0O7du3QqVMneHh4YN++fVrHIxAIcODAAXz77bdYtWoVvLy84Ofnhz///BM3btxA+/bttV6mKpYsWYIFCxZg2bJl8Pb2RmBgII4dO4aaNWvybdq1awegUATl0jb9/f0hkUhI+CIIgiAIgiAMkoULF2LBggUluh4vDzx+/BgA8O7dOz1HQlRkBKwkhZp0TGZmJmxsbPD27VtUqlRJ7rPc3FwkJyejZs2aKkfe+1R4+/YtnwIoEolQt25dPUdUsVm0aBGOHDmCmJgYfYdSboiOjkanTp0wevRorFixQt/hEAYEncsJgiAIgiAUadeuHS5duoQ5c+Zg2bJl+g6n1KlWrRqePn2Kpk2bQiwW6zscohyhTicqCjm+KhC6rvFFENrSuHFjhIWFwcrKSqvRJgmCIAiCIAjiU+Tt27cAKmYNrIKCAr6EDTm+iLKERnWsQMimN+oq1ZEgtKVRo0Zo1KgR/75evXp4+PCh0rYbN27E4MGDdRUaQRAEQRAEQRgUb968AQCV18vlmefPn/MjtJPwRZQlJHxVIGQdXxKJBFKpVG2heeLjWLRoERYtWqTvMMo9J0+eVOlQLGmxf4L4lHj8+DH279+PMWPGFGvzJgiCIAiifFGRHV9cYXuAitsTZQsJXxUIWeELKHR9mZqa6ikagtAMbkRPgiBKxg8//IBff/0VEokEX3/9tb7DIQiCIAiilJBKpcjMzAQApKWlITc3t0LVQi0qfDHG+EGoCKI0ITtQBUKZ8EUQBEFUbLjaGDdv3tRzJARBEARBlCbv3r2D7Fh0qampeoym9JEVvqRSKXJycvQYDVGRIeGrAkHCF0EQxKcH9yT49u3beo6EIAiCIIjShKvvxVHR6nzJCl8A1fkiyg4SvioQRYUvGtmRIAii4sMJX3fu3JF7KkwQBEEQRPmGq+/FUdHqfBUVvqjOF1FWkPBVgeCELy4vmhxfBEEQFR/u6ei7d++Qlpam52gIgiAIgigtijq+KrrwRY4voqwg4asCwQldZmZmcu8/ZbjhcQmCICoqnOMLoHRHgiAIgqhIFHV8VbRUx8ePH8u9J8cXUVaQ8GWgpKSkQCAQICYmRuN5OMdXeRW+QkNDYWtrq9U8Rfvp4sWLEAgEePPmDbKysnDjxg1yQGjAs2fP0LlzZ1hZWfHfgUAgwJEjRwCUbH8kCEI3kPBFEARBEBWTiuz4Yozxji+RSASAHF9E2UHClx4QCARqXyNGjCjRcjnhixvitixqfMkKS4ZI69atkZaWBhsbG35IXFVPDgx9W3TJqlWrkJaWhpiYGNy9exdA4ZDJ3bp103NkBEGogzEmd5FIwhdBEARBVBw4x5ebmxuAiiV8ZWZmIjs7GwDg5eUFgIQvouww1ncAnyKyDqR9+/ZhwYIFuHPnDj/NwsICr1+/1mqZUqmUT+srr46v0sDU1BROTk4A/tv+okX/PyXy8/NhYmJSbLukpCQ0adIEtWvX5qdx/UgQhOGSnZ0tV9CehC+CIAiCqDhwwpefnx8ePnyIp0+f4sOHDzA1NdVzZB8P5/aysbGBo6MjAEp1JMoOcnzpAScnJ/5lY2MDgUCgMI3jwYMHaN++PSwtLeHn54fIyEi5ZV25cgXt2rWDlZUVunfvjp9++okXepQJX0lJSQgODoajoyNEIhGaNWuGc+fOybXJy8vD7Nmz4erqCjMzM9SuXRtbtmxBSkoK2rdvDwCws7OTc6e5u7tj9erVcstp2LAhFi1axL//+eef0aBBA1hZWcHV1RUTJkzQ+uR27do1NGrUCObm5mjatClu3Lgh97msi6ugoABpaWkYP3487OzsYGVlhXr16uHkyZNqt+XUqVNo27YtbG1tUblyZfTo0QNJSUn8Ori0v0OHDqn9bi5fvgx/f39YWlrCzs4OgYGBvKDJGMPy5cvh4eEBCwsL+Pn54c8//1S77e7u7liyZAkGDRoEkUgEFxcXrFu3Tq6NQCDAhg0bEBwcDCsrK3z33XcAgPXr16NWrVowNTWFl5cXdu7cKbfcgwcPYseOHXL9IJvqqIyEhAQEBQVBJBLB0dERQ4cOxatXr9RuA0EQpYtsmiNAwhdBEARBVCS4zJTatWvDwsICjDE8evRIv0GVEpzwVa1aNVhbWwMgxxdRdlQ44YsxhuzsbL28ymIY+blz52LWrFmIiYlBnTp1MHDgQF7QiouLQ2BgIL744guIxWIsXboUMTExmD17NgDlwldWVhaCgoJw7tw53LhxA4GBgejZsydSU1P5NsOGDcPevXuxdu1aJCYmYsOGDRCJRHB1dcXBgwcBAHfu3EFaWhrWrFmj8bYIhUKsXbsWt27dwvbt23H+/Hk+Vk3Izs5Gjx494OXlhaioKCxatAizZs1S2V4ikWD58uXIy8vDP//8g7i4OPz444/Fbkt2djZmzJgBsViMsLAwCIVC9O7dW6FQvrrvJiYmBh07dkS9evUQGRmJiIgI9OzZkxcl582bh23btmH9+vWIj4/H9OnTMWTIEISHh6vtgxUrVsDX1xfR0dEICQnB9OnTcfbsWbk2CxcuRHBwMOLi4jBq1CgcPnwYU6dOxcyZM3Hr1i189dVXGDlyJC5cuAAAEIvF6Nq1K/r376/xd5qWlgZ/f380bNgQ169fx6lTp/D8+XP079+/2HkJgig9OOGLc3Y+evSInpYSBEEQRAWBc3zZ2tpWuHRHZcIXXcMQZQb7CJYuXcoAsKlTp6psc+HCBQZA4ZWYmKjxet6+fcsAsLdv3yp8lpOTwxISElhOTg5jjLGsrCyl69PFKysrS+s+3LZtG7OxsVGYnpyczACwzZs389Pi4+Pl+m7o0KFs3Lhx/HaLxWK2bds2JhQKWUREBBOLxUwqlRYbg4+PD1u3bh1jjLE7d+4wAOzs2bNK23Lf5+vXr+Wmu7m5sVWrVslN8/PzYwsXLlS53v3797PKlSvz71X1BcfGjRuZvb09y87O5qetX7+eAWA3btxQiO/27dvM09OTjR8/XqttKcqLFy8YABYXF8cY0+y7GThwIGvTpo3S5WVlZTFzc3N25coVuemjR49mAwcOVBmHm5sb69q1q9y0AQMGsG7duvHvAbBp06bJtWndujUbO3as3LR+/fqxoKAg/n1wcDAbPny4XBsA7PDhw3LbzPXz/PnzWZcuXeTaP3r0iAFgd+7cUbkNBKGKoudyQjP+/fdfBoDVqFGDVa1alQFgUVFR+g6LIAiCIIhSoF+/fgwAW7duHevatavCPUh55rvvvmMA2MiRI9m0adMYAPbNN9/oOyyiHKFOJypKiR1fYrEYv//+O3x9fTVqz7lquJdsLSFCNbL96+zsDAB48eIFACAqKgqhoaF8qlm7du0wYcIESKVSPH36FICi6ys7OxuzZ8+Gj48PbG1tIRKJcPv2bd7xFRMTAyMjI/j7+5f6tly4cAGdO3fmVf1hw4YhPT2dL2pYHImJifDz84OlpSU/rVWrVirbFxQUYMCAAdi0aRPatGmDhQsX4ubNm8WuJykpCYMGDYKHhwcqVaqEmjVrAoCcKw5Q/91wji9lJCQkIDc3F507d4ZIJOJfO3bskEupVEbR7W3VqhUSExPlpjVt2lTufWJiItq0aSM3rU2bNgrzaUNUVBQuXLggF3/dunUBoNhtIAii9OBSAipVqsQfg5TuSBAEQRAVA87xZWNjA3d3dwDAw4cP9RhR6UGOL0KXlKi4fVZWFgYPHoxNmzbxNYSKw8HBAba2tiVZnVZYWlrq7YCRFWRKC9nC5AKBAAD4lDupVIqvvvoKU6ZMwdu3b5GamgpLS0vUqlWLryVVUFAgt4yvv/4ap0+fxk8//QRPT09YWFigb9+++PDhA4DCwvolQSgUKqR6yo4q+fDhQwQFBWH8+PFYsmQJ7O3tERERgdGjR2s8+mTR5ReHRCJBr1690LJlS6SmpuLcuXNYtmwZVq5cicmTJ6ucr2fPnnB1dcWmTZvg4uICqVSK+vXr833Eoe67UdePXJsTJ06gWrVqcp9xAxNoA7duDisrq2LbMMYUpmmDVCpFz5498eOPPyp8xomABEGUPVyqo7W1NerWrYtLly7JDZZCEARBEET5havxVdFTHbnrGarxRZQVJRK+Jk6ciO7du6NTp04aC1+NGjVCbm4ufHx8MG/ePL6wuDLy8vKQl5fHvy9avFcdAoFA6Y1/RaRx48aIj4+Hp6cnXr16BcYYbGxs4OnpiVu3biE3N1fB8XXp0iWMGDECvXv3BlAoYsqePBs0aACpVIrw8HB06tRJYZ3cCCJFR0qsWrWq3GiVmZmZSE5O5t9fv34dBQUFWLlyJYTCQqPh/v37tdpeHx8f7Ny5Ezk5ObywdPXqVZXtuW13cnJCYGAgJkyYgJCQEGzatAmTJ09Wui3p6elITEzExo0b8dlnnwEAIiIitIoTKHSDhYWFYfHixUq3w8zMDKmpqVo764pu79WrV3mXhyq8vb0RERGBYcOG8dOuXLkCb29vrdYtS+PGjXHw4EG4u7vD2JgGhyUIfcH9PpLjiyAIgiAqHsocXxVR+OIMDuT4IsoKrVMd9+7di+joaCxbtkyj9s7Ozvj9999x8OBBHDp0CF5eXujYsSP++ecflfMsW7YMNjY2/MvV1VXbMD8JvvnmG0RGRmLixImIjY1FamoqLly4gMmTJ/NiRFE3laenJw4dOoSYmBjExsZi0KBBckXb3d3dMXz4cIwaNQpHjhxBcnIyLl68yItUbm5uEAgEOH78OF6+fMmfnDp06ICdO3fi0qVLuHXrFoYPHw4jIyN+ubVq1UJBQQHWrVuHBw8eYOfOndiwYYNW2zto0CAIhUKMHj0aCQkJOHnyJH766SelbaVSKaRSKVauXInIyEgkJSUhOjoa58+f5wUfZdtiZ2eHypUr4/fff8f9+/dx/vx5zJgxQ6s4ASAkJARisRgTJkzAzZs3cfv2baxfvx6vXr2CtbU1Zs2ahenTp2P79u1ISkrCjRs38Ouvv2L79u1ql3v58mUsX74cd+/exa+//ooDBw5g6tSpauf5+uuvERoaig0bNuDevXv4+eefcejQIbUDAxTHxIkTkZGRgYEDB+LatWt48OABzpw5g1GjRimIogRBlB2ywpeXlxcAEr4IgiAIoqLAOb4qovD1+PFjAIXCl0gkAkCOL6Ls0Er4evToEaZOnYo//vgD5ubmGs3j5eWFsWPHonHjxmjVqhV+++03dO/eXaVgARSKBm/fvuVfFWXI1tLG19cX4eHhuHfvHoKDgzFkyBCsWrUKzs7OvPBV1PG1atUq2NnZoXXr1ujZsycCAwPRuHFjuTbr169H3759MWHCBNStWxdjx47l63BVq1YNixcvxpw5c+Do6IhJkyYBKPzO2rVrhx49eiAoKAi9evVCrVq1+GU2bNgQP//8M3788UfUr18fu3bt0lg85RCJRDh27BgSEhLQqFEjzJ07V2mqnex2S6VSLF++HA0bNkTXrl3h5eWF3377TeW2CIVC7N27F1FRUahfvz6mT5+OFStWaBUnANSpUwdnzpxBbGwsmjdvjlatWuHo0aP897JkyRIsWLAAy5Ytg7e3NwIDA3Hs2DG+npgqZs6ciaioKDRq1AhLlizBypUrERgYqHaeXr16Yc2aNVixYgXq1auHjRs3Ytu2bQgICNB6uzhcXFxw+fJlSCQSBAYGon79+pg6dSpsbGx4Rx9BEGWPshpfd+/eJQGaIAiCICoAsqM6csLXkydPNC4VY6jk5+fztZFla3yR8EWUFQKmReGkI0eOoHfv3nJOHolEAoFAAKFQiLy8PLnPVPH999/jjz/+0Li4dmZmJmxsbPD27VtUqlRJ7rPc3FwkJyejZs2aGotxFZHU1FS8ePECTk5OqF69Oh4+fIiXL1/CxcUFLi4uOo2FMYanT5/CzMwMVapU0em6Od6/f4+EhAT+fZ06dRT2nfKGu7s7pk2bhmnTpuk7FILQiNzcXDx79gzOzs7F1q+jc3nJmDNnDn788UdMmzYNP/30EywtLfHhwwc8ePCgWCGdIAiCIAjDJS8vj78mev36NSpVqgRLS0vk5eWV+9/51NRUuLm5wcTEBLm5uTh//jw6d+6M+vXrIy4uTt/hEeUEdTpRUbSyZnTs2BFxcXGIiYnhX02bNsXgwYP50QA14caNG1QAu5Thnu5z34Eqx5cuyMvLQ1paml6dekXdDuR+IAjd8+LFC7x69QrPnz/XdygVFtlURyMjI9SpUwcApTsSBFF6SKVS3Lx5k66lCELHcG4vgUCASpUqQSgUVpgC91x9L2dnZwiFQnJ8EWWOVsKXtbU16tevL/eysrJC5cqVUb9+fQCFKW+yRbRXr16NI0eO4N69e4iPj0dISAgOHjzIp8gRpYMq4UsfNlhObJNIJHL1w/QRAwddrBGE7uGOQy5Vmih9ZIUvAFTgniCIUmfdunXw8/PDunXr9B0KQXxScPW9rK2t+VIiFaXOl2xhewC88EXF7YmyotSHY0tLS0Nqair//sOHD5g1axaePHkCCwsL1KtXDydOnEBQUFBpr/qThhN2OMFLn44vWZFJIpHopeZT0e3WlwBXmnzsD1xGRgYKCgrg4OBQOgERRDFwx+H79+8hlUqp/lsZIFvjCyDhiyCI0ufu3bsAgJMnT1K5BYLQIbL1vTg4x9fDhw/1EVKpUVT4ouL2RFnz0cLXxYsX5d6HhobKvZ89ezZmz579sashiqGo48vExASAfoQv2XUWFBTwsegSSnWUh6v5AxT+eJqamuo5IuJTgDsXMMaQk5MDKysrPUdU8eAcX9yTUhK+CIIobTgHxtWrVyGRSDQubUIQxMfBCV82Njb8tIru+Prw4QM+fPhA9ypEqUOP3ysIhpjqKBuXPmPQZxyGQnp6Ov+/PsRQ4tNEdl97//69HiOpuFCqI0EQZQ0nfL179w7x8fF6joYgPh24VEdZx1dFE76qV68O4D/HF0DpjkTZQMJXBYG7wVRW3F6LgTtLBVmRSV8iC7degUCgENOnBmMMr1694t9/yn1B6BbZ45/qfJUNRYUvLy8vAIUDC7x+/VpvcRXHv//+ixEjRuDp06f6DoUgiGKQvQmNjIzUYyQE8WmhzvFV0VIdTUxM+BHASfgiygISvioAjDGVji9A90KHITm+OJvspyz2ZGVlIS8vj3//KfcFoTuKDm5Bjq+yoWiNL5FIxD89vXPnjt7iKo5vv/0W27dvx/79+/UdCkEQxSB7E3rlyhU9RkIQnxbKHF9cja9Hjx6V6yyOosIXQHW+iLKFhK8KgOzNJSd8CYVC/n9dpzsaguOLi4GEL8i5vYBPuy8I3VF0P+MK3BOlS9EaX8B/ri9DTXfMzMzEpUuXAPx3UU8QhOFCwhdB6Adlji9nZ2eYmJhAIpHw4lF5gzGmVPjirmVI+CLKAhK+KgDcDaZAIJAbNU1fIzsakuOLs8x+qmJPQUEBn+5EIiChS7hj0MTEhB/gglxfpUt+fj5ycnIA/Of4Agy/zldYWBj/QIYT7giCMFxkha/79+/jxYsXeoyGID4duIdDssKXUCjkXV/ltc7X69ev+esXFxcXfjrn+KJUR6IsIOHLQElJSYFAIEBMTEyxbWXTHLmaVoD+hC9DcHwVFb5K22ly8eJFCASCj3Yr/P7773B1dYVQKMTq1as1mqfovqEultevX0MqlcLc3Jy/MSbhq5Bnz56hc+fOsLKy4i3kAoEAR44cAaDdMVgcQ4cOxdKlSz96OdowYsQI9OrVS6frlIU7Bh88eIDAwEDk5ORQna9SRvaJqKzjy9CFr5MnT/L/k/BFEIYPdxPKXVNRnS+C0A2c40s21RH4L92xvNb54txe9vb2sLCw4KeT44soS0j44pBKgOcXgZQ9hX+lZScOCAQCta8RI0Zotbyi9b04OJeFrPgUGhqqcPIsbWTXV1LhKyAggO8PoVAIR0dH9OvXT+MTfHlIdczMzMSkSZPwzTff4MmTJxg3blyJltO6dWukpaXJPQ3i4NIcq1SpAiMjI0RFRcHFxYXSiwCsWrUKaWlpiImJwd27dwEAaWlp6NatW6mu5+bNmzhx4gQmT54sNz0+Ph79+/dH1apVYWZmhtq1a2P+/Plau6JUCXRr1qxBaGjoR0ZfPJ9//jlq1KgBc3NzODs7Y+jQoXj69Cl/7Pv4+KBx48bYvXs3Ob5KGe7C0NzcXG7Yb0MWvhhjcsIXXdwShOHDCV+fffYZAEp3JAhdoczxBZT/kR2VpTkC/wlf5PgiygISvgDg0SHgL3cgrD1wZVDh37/cC6eXAWlpafxr9erVqFSpkty0NWvWaLW8oiM6cnCOL33W+NJWcPrw4QP//9ixY5GWloYnT57g6NGjePToEYYMGVLsMqRSKe/wMuRUx9TUVOTn56N79+5wdnaGpaVliZZjamoKJycnObcfUJhWlp2dDYFAgMqVKyvsHxUVTff3pKQkNGnSBLVr14aDgwMAwMnJid9nSotffvkF/fr1k3PkXL16FS1atMCHDx9w4sQJ3L17F0uXLsX27dvRuXNnueOgpNjY2JS5yA0A7du3x/79+3Hnzh0cPHgQSUlJ6Nu3L39eMjY2xrBhw3Dw4EFy95QyRUd05OCEr6SkJJ2f/4sjNjZWbiRH2icIwrCRSCT8Q4vOnTsDIMcXQegKVY6viip8UXF7oiwh4evRIeBSX+D9Y/np758UTi8D8cvJyYl/2djYQCAQKEzjePDgAdq3bw9LS0v4+fkpXGxcuXIF3bp1Q9u2bdGxY0dMmTKFTycqSapjamoqgoODIRKJUKlSJfTv3x/Pnz8HUHjy5VxDQOGTe3t7ezRr1oyff8+ePejYsSP//unTpxgwYADs7OxQuXJlBAcHy52kuXSsZcuWwcXFBXXq1OE/s7S0hJOTE5ydndGyZUtMnDgR0dHRcvGGh4ejefPmMDMzg7OzM+bMmYPc3Fz+83r16mH37t2QSCRgjAEAGjZsiEWLFvFtBAIBNm/ejN69e8PS0hK1a9fGX3/9JbeekydPok6dOrCwsED79u01+qFR15ehoaFo0KABAMDDwwMCgUDlMq9du4ZGjRrB3NwcTZs2xY0bN+Q+L5rq+PDhQ/Ts2RPOzs747LPP8OWXX+Ls2bN48uQJxo8fDwCws7OTcxeeOnUKbdu2ha2tLSpXrowePXogKSmJXwfnKjp06JDa/fHy5cvw9/eHpaUl7OzsEBgYyNcYY4xh+fLl8PDwgIWFBfz8/PDnn3+q7UN3d3csWbIEgwYNgkgkgouLC9atWyfXRiAQYMOGDQgODoaVlRW+++47AMD69etRq1YtmJqawsvLCzt37pRb7sGDB7Fjxw65fpBNdVRGQkICgoKCIBKJ4OjoiKFDhyoMHiCLVCrFgQMH8Pnnn/PTGGMYPXo0vL29cejQITRv3hxubm7o168fjh07hsjISKxatUpu+9avX49u3brBwsICNWvWxIEDB/jPa9asCQBo1KgRBAIBAgICACimOubl5WHKlClwcHCAubk52rZtC7FYzH/O7UdhYWFo2rQpLC0t0bp162JHBpw+fTpatmwJNzc3tG7dGnPmzMHVq1f52g3Gxsbo2bMn3r59iytXrhikCF1eUVbYHii8kLSyskJBQYHccWwIcG4vc3NzAHRxSxCGjqxTt0uXLgAAsVhcKg9oCIJQT3GOr/Ke6kiOL0KXVDzhizGgIFuz14dM4PoUAEzZggr/XJ9a2E6T5TFly/k45s6di1mzZiEmJgZ16tTBwIEDeSErLi4OgYGBCAoKwu7du7FmzRpERERg0qRJALQXvhhj6NWrFzIyMhAeHo6zZ88iKSkJAwYMAFB40m3YsCEuXrwIoDCFi/vL3YBduHABjRs3BgDk5uZi+PDhEIlE+OeffxAREQGRSISuXbvKXTCFhYUhMTERZ8+exfHjx5XGlpGRgQMHDqBFixb8tCdPniAoKAjNmjVDbGws1q9fjy1btuD777/nt59zQTHGeOFLGYsXL0b//v1x8+ZNBAUFYfDgwcjIyABQOFzwF198gaCgIMTExGDMmDGYM2fOR/XlgAEDcO7cOQCFwlZaWhpcXV0VlpOdnY0ePXrAy8sLUVFRWLRoEWbNmqV23RMnTkRubi42b96MPXv2YMmSJRCJRKhRowZ+/PFHAMCdO3fk3IXZ2dmYMWMGxGIxwsLCIBQK0bt3b4XaaOr2x5iYGHTs2BH16tVDZGQkIiIi0LNnT17omDdvHrZt24b169cjPj4e06dPx5AhQxAeHq52e1asWAFfX19ER0cjJCQE06dPx9mzZ+XaLFy4EMHBwYiLi8OoUaNw+PBhTJ06FTNnzsStW7fw1VdfYeTIkbhw4QKAwov2rl27on///hq7LNPS0uDv74+GDRvi+vXrOHXqFJ4/f47+/furnOfmzZt48+YNmjZtyk+LiYlBQkICZsyYITcYBQD4+fmhU6dO2LNnj9z0+fPno0+fPoiNjcWQIUMwcOBAJCYmAijcfwDg3LlzSEtLw6FDysX62bNn4+DBg9i+fTuio6Ph6emJwMBAfj/nmDt3LlauXInr16/D2NgYo0aNKrZvODIyMrBr1y60bt2aP/aMjY1hZWWFOnXqICYmhtIdSxFVji+BQGCw6Y6c8NW9e3cA5PgiCEOHe5gqFArh6+sLe3t75Obmlkr9S4Ig1FNcjS9yfBGEFrBywNu3bxkA9vbtW4XPcnJyWEJCAsvJySmckJ/F2C7o55WfpfW2bdu2jdnY2ChMT05OZgDY5s2b+Wnx8fEMAEtMTGSMMTZ06FA2btw49vTpUyYWi1lycjK7dOkSEwqFLCcnh7169YqJxWJ2586dYtfHGGNnzpxhRkZGLDU1VWGd165dY4wxNmPGDNajRw/GGGOrV69mffv2ZY0bN2YnTpxgjDFWu3ZtNmfOHCYWi9n8+fOZu7s7k0ql/PLy8vKYhYUFO336NGOMseHDhzNHR0eWl5cnF4u/vz8zMTFhVlZWzNLSkgFgderUYcnJyXybb7/9lnl5eckt/9dff2UikYj9+++/LC4ujrm5ubHp06czsVjMPnz4wBhjzM/Pjy1cuJCfBwCbN28e/z4rK4sJBAL2999/M8YYCwkJYd7e3nLr+eabbxgA9vr16xL35Y0bNxgAuW0qysaNG5m9vT3Lzs7mp61fv54BYDdu3GCMMXbhwgW5WBo0aMC++eYbJhaLWUxMDB93eno627Bhg9q4OV68eMEAsLi4OMaYZvvjwIEDWZs2bZQuLysri5mbm7MrV67ITR89ejQbOHCgyjjc3NxY165d5aYNGDCAdevWjX8PgE2bNk2uTevWrdnYsWPlpvXr148FBQXx74ODg9nw4cPl2gBghw8flttmrp/nz5/PunTpItf+0aNHDIDcMSbL4cOHmZGRkdy+s3fvXrnlFmXKlCnMwsJCLqbx48fLtWnRogX7v//7P6VxcgwfPpwFBwczxgr738TEhO3atYv//MOHD8zFxYUtX76cMfbffnTu3Dm+zYkTJxiA/86vKpg9ezZ/nLZs2ZK9evWKJSUlMbFYzJ49e8YYY6xz586sR48eLC0tTekyFM7lRLHs27ePAWD+/v4Knw0ePJgBYMuWLdN9YCpIT09nQqGQAWD79+9nAJibm5u+wyIIQg337t1jAFilSpUYY4z16NGDAWCrVq3Sb2AE8QlgZ2cnd63NkZqaygAwY2NjVlBQoKfoSk737t0ZALZx40a56XPmzFF6XU8QqlCnExWl4jm+Khi+vr78/87OzgDADyMdFRWF0NBQeHp6ol27dqhXrx4CAwMhlUqRnJysdY2vxMREuLq6yjmPfHx8YGtry7tLAgICcOnSJUilUoSHhyMgIAABAQEIDw/Hs2fPcO/ePd7xlZiYiEePHsHa2hoikQgikYh/UiibftOgQQO5wswcgwcPRkxMDGJjYxEREQFPT0906dKFfwqQmJiIVq1aydW2atOmDbKysvDixQt++zlXjboUK9l+trKygrW1Nd/PiYmJaNmypdx6WrVq9dF9qQmJiYnw8/OTq/9V3LqnTJmClStXYvTo0QgNDUVcXByA/xyAykhKSsKgQYPg4eGBSpUq8elzqampcu3U7Y+c40sZCQkJyM3NRefOnfl9QSQSYceOHcWmYhXd3latWin0oayjCijstzZt2shNa9OmjVZ9X5SoqChcuHBBLn7ZWkrKyMnJgZmZmUL9NXUwxhTaa9IH6uBqPcn2iYmJCZo3b66wHHXfsSq+/vpr3LhxA2fOnIGRkRGGDRvGn3e4/U4kEiE3N5dGdixFVDm+gP/qfBWXqqpLzpw5A6lUivr166N+/foA6KluSWCMGVztNqJsyMrKQr9+/bBjxw69xgD858Ro3bo1ACpwTxBlDWNMpePLxcUFxsbGKCgokKubWV7gHF/Vq1eXm06OL6IsUX0nXF4xsgT6a5gX/OIf4GJQ8e0CTgIO7TRbdynDjcwIgL8Z5tLPpFIpvvrqK/Tp0wcZGRlwcHCAo6MjAKBGjRr8hbE2qY7KbtBlp7dr1w7v3r1DdHQ0Ll26hCVLlsDV1RVLly5Fw4YNUbVqVdSsWRMmJiZgjKFu3bo4ePCgQmH1qlWr8v9bWVkpjcfGxgaenp4AAE9PT2zZsgXOzs7Yt28fxowZozReJpPOaGRkJJdKxglfym4YZPsZKOxrrp9ZCVJYNelLTZejLUOHDoWTkxMuX76MxMRENG3aFCtXrsTIkSNVztOzZ0+4urpi06ZNcHFx4W9Oi9bwULc/yg5HXBSuzYkTJxRszSUpJl+0D5XtQ8r2DW36vihSqRQ9e/bk00Vl4QSiolSpUgXv37/Hhw8feHGXq2OXkJCAhg0bKsxz+/Zt1K5du9h4SrIfadIn6r5jVVSpUgVVqlRBnTp14O3tDVdXVwwePBh16tThha93797Bzs6OUh1LEVU1vgDDHNmRS3MMCgriY87MzPzoY/NTo3v37oiPj8fly5cVbhqIisWBAwfw559/Ijo6GsOGDdNLDCR8KRIVFQULCwv4+PjoOxSiApOVlcVffxWt8WVkZARXV1ckJyfj4cOHSsulGDLF1fgi4YsoCyqe40sgAIytNHs5dQEsqwNQdcEtACxdC9tpsjwdX7g3btwY8fHxqF69OlxdXeHp6cm/TE1N5Wp8aSKg+Pj4IDU1FY8ePeKnJSQk4O3bt/D29gbwX52vX375BQKBAD4+Pvjss89w48YNHD9+nHeUmJqaom7dunj06BEqV64sF5unp6fCCVwTOPGMK5rt4+ODK1euyG3blStXIBKJ4ODgAGNjY1StWpWvYSSRSJCZmYnk5GSt1uvj44OrV6/KTSv6Xtk8xfWlpuuOjY3lt1mTdaenp8PJyQkjRozAkSNHMHPmTGzatAlGRkb8PiHrfktPT0diYiLmzZuHjh07wtvbmy9Irw2+vr4ICwtTuR1mZmZITU1V2BeK+7FW1vfcTb0qvL29ERERITftypUrWvV9Ubjjzd3dXWEbVIm3nLCVkJAgN61u3bpYtWqVgqAUGxuLc+fOYeDAgXLT1fUBJ6ipczRy5wTZPsnPz8f169c/qk+UwR2PssXtgUIBxsvLC3l5eVoNuEGoRp3jy8vLC0Bhv5dEQC9tpFIp/v77bwCFwhcXc0FBAfLy8vQZWrkjLCwMqampmDhxokF8t0TZwdVUTUlJ0Vsx+aLCV9OmTWFkZIQnT57IXeN8KmRkZKBt27bw9/cv9qEQQXwMXGF7U1NTfkAYWcrryI55eXl4+fIlANU1vqi4PVEWVDzhSxuERkATrqh1UdHq/79vsrqwnQHyzTffIDIyEgsWLMCdO3eQkpKCv/76C5MnTwbwn3ODMSZ3UyyRSBATEyP3SkhIQKdOneDr64vBgwcjOjoa165dw7Bhw+Dv7y+XShYQEIA//vgD/v7+EAgEsLOzg4+PD/bt28enZBkZGaF79+6wtbVFnz59cOnSJSQnJyM8PBxTp07F48dFRtFUwvv37/Hs2TM8e/YMsbGxmDBhAszNzflRhSZMmIBHjx5h8uTJuH37No4ePYqFCxdi7NixEAqFMDY2RocOHXDs2DHcuHEDt27dwvDhwxXcZ8Uxfvx4JCUlYcaMGbhz5w52796N0NBQtfNo2pfFMWjQIAiFQowePRoJCQk4efIkfvrpJ5XtGWOYPXs2IiMjkZ2djejoaJw/fx7e3t4wMjKCs7MzBAIBjh07hpcvXyIrK4sfcfP333/H/fv3cf78ecyYMUPjGDlCQkIgFosxYcIE3Lx5E7dv38b69evx6tUrWFtbY9asWZg+fTq2b9+OpKQk3LhxA7/++iu2b9+udrmXL1/G8uXLcffuXfz66684cOAApk6dqnaer7/+GqGhodiwYQPu3buHn3/+GYcOHSp2YAB1TJw4ERkZGRg4cCCuXbuGBw8e4MyZMxg1apRK0alq1apo3LixnODEjSKakJCAPn364Nq1a0hNTcWBAwfQs2dPtGrVCtOmTZNbzoEDB7B161bcvXsXCxcuxLVr1/hBLBwcHGBhYcEX2+ds8bJYWVnh//7v//D111/j1KlTSEhIwNixY/H+/XuMHj26xH1y7do1/PLLL4iJicHDhw9x4cIFDBo0CLVq1UK9evUAFApfKSkpePLkCdq2bQsAlO5YSnBPRJUJX7Vr1+ZHey0uVVUXXL9+Ha9evUKlSpXQunVr/uIWoAL32lBQUMALIH/99RcOHjyo54iIsoIxxgtfUqkUDx480EscRYUvKysr/qHOp+j6io2NRW5uLl69eoX09HR9h0NUYLjrORsbG6Wu6PIqfHGpmWZmZqhcubLcZ+T4IsqST1v4AgDXL4DP/gQs5RVnWFYvnO76hX7i0gBfX1+Eh4cjJSUF48aNQ8eOHTF//nw+7UooFPKpfrIOi6ysLDRq1EjuFRQUBIFAgCNHjsDOzg7t2rVDp06d4OHhgX379smtt3379pBIJAgICOCn+fv7QyKR8KMuGhsbw9raGhs3bkS1atXwxRdfwNvbG6NGjUJOTo7SG7WibNq0Cc7OznB2dkb79u3x8uVLnDx5kncyVKtWDSdPnsS1a9fg5+eH8ePHY/To0ZgwYQKAQvEtJCQEzZo1w/Tp09G/f3/06tULtWrV0qqfa9SogYMHD+LYsWPw8/PDhg0bsHTpUrXzyPblZ599hg4dOsDNzU2hL4tDJBLh2LFjSEhIQKNGjTB37lylqXYc7969Q35+PpYvX47WrVuja9eu8PLywm+//QYjIyM4ODhg3LhxCAkJgaOjIyZNmgShUIi9e/ciKioK9evXx/Tp07FixQqt4gQKU/jOnDmD2NhYNG/eHK1atcLRo0d5x8+SJUuwYMECLFu2DN7e3ggMDMSxY8f4emKqmDlzJqKiotCoUSMsWbIEK1euRGBgoNp5evXqhTVr1mDFihWoV68eNm7ciG3btsnts9ri4uKCy5cvQyKRIDAwEPXr18fUqVNhY2OjMDqjLOPGjcOuXbvkprVp0wZXr16FkZERgoKC4OnpiZCQEAwfPhxnz55VSP9cvHgx9u7dC19fX2zfvh27du3iUyyMjY2xdu1abNy4ES4uLggODlYaxw8//IA+ffpg6NChaNy4Me7fv4/Tp0/Dzs6uxH1iYWGBQ4cOoWPHjvDy8sKoUaNQv359nD9/nv/ejYyMsGfPHnTp0oVP4aR0x9JBnePL3NycP7YMId2RS3Ps0qULTExMIBQKqZZHCZB1/wLApEmTSuTQJQyflJQUuTqbd+/e1UscRYUv4NNOd7x16xb/f3msrUSUHzjHl6osmfIqfHFpji4uLgqCHid8keOLKBNKsah+maHVqI4lRVLA2LMLjCXvLvwrKT8jZMTFxTGxWMwyMzMVPouNjWVisZi9e/dOJ7E8fvyYicVi9vDhQ5aQkMDEYjHLyMjQybo57t27x8RiMXv+/DljjLH79+/Lvdc1iYmJcqPblSXctqakpCh8JpVKmVgsZmKxWGEUTV2Snp7O3r9/r1FbNze3cj9yVE5ODqtRo4bCiJaagv8/0uSzZ8+YWCxWOSqiIZGXl8fEYjG7fv06y8nJYa6uriwiIoLfhnv37inMQ6M6ak///v0ZALZmzRqlnwcFBTEAbMOGDTqOTJFmzZoxAGzr1q38NGdnZwaARUdH6zGy8sWzZ88YAAaAeXt7MwBs1KhR+g6LKAO2bt3Kf9cA2IoVK/QSx7p16xgA1r9/f37anj17GADWtGlTvcSkT8aNG8d/JydPntR3OEQF5vjx42qPs9DQUAaAderUSceRfRzc6OZt27ZV+OzSpUsMAPP09NRDZER5hEZ1LAlCI8AxAHAfWPjXQNMblcGlWSlL4ePSHXVVU0c2FmX1pHQZg6zjRB9xcHD1a8p6/QUFBfzToSpVqih8LhAI9N4X2dnZePDggdZ11soz5ubm2LFjB169evVRy+FcUuXBLcWdb4yNjZGamoq5c+eiTZs2/OiklOpYOqhzfAGGU+D++fPnEIvFAICuXbvy07m4KdVRc7jj39LSEps3b4ZAIMDWrVtV1lckyi9cmiM3cIwhOr5u3LjxyZ3PZR1fnHOF0D979+7Ft99+W6HqHlZ0x1fR+l4AOb6IsoWErwoAd5OpTPjixB9dDX0uGwsXj64LWcvedHOxAPoReyQSCd/3Zb3+9PR0MMZgaWmpsti6voUv7odMV/ujoeDv74+ePXt+1DK4PisPfSd7DNapUwdfffUVAPDCV35+vt4KNVck1NX4AgxH+Dp9+jSAwgEiZEdA5eKmVEfNkRW+Wrduzaf2f/XVV+VCFCc0hxO++vfvD8CwhC9XV1dUq1YNEokE169f10tc+oAxRqmOBsrUqVOxbNky3LhxQ9+hlBpcjS9bW1uln3PCV2pqarkaaEGd8EUlEIiyhISvco5UKuWfbqgTvnQlPsne8OrL8VVUCOTqL+lD7JEdraws188Y4x1FytxeHPoWvrgnw5r+QKekpCgUev/UYIyhV69evFBUHgSjouIzh5GREe9eMNSb9MePH2PevHnlomhxeXF8cfW9unfvLjede7JLji/NkRW+AGDp0qWoXr06kpKSsHjxYn2GRpQiXH0vY2NjjBgxAoBhCV8CgYAfzCgyMlIvcemDR48eyZ2vSPgyDAoKCvhRAvU1CERZUJzjq1q1ajAyMsKHDx/w7NkzHUb2cWji+MrOzi5XYh5RPiDhq5wjK2AYUqqjsbExOb4gL3yVZT+8f/8eOTk5EAgEsLe3V9lO38IXd9MmkUgqlB1dF8gKX4bed6qELwAGn+44evRofP/991i7dq2+QykW7gaMu1AsCid8PXz4UKEouq4oKCjgHV9BQUFyn5HjS3uKCl+VKlXC+vXrAQArV65EdHS03mIjSg/O7dW8eXN+BMW0tDS9HCvKhC/g0yxwL+v2Akj4MhQyMjL466KHDx/qOZrSozjHl7GxMapXrw6gfKU7auL4Agz3OpEov5DwVc6RramlbKhbXac66rvGl6wDztCEr7JcP+f2srOzUyo2cOg77TM3N5d/b+jijSEhkUj4J1+MMb0Jl5qiTvji0nAN0fEVFxeHM2fO8P8bOsU5vqpUqQJ7e3swxnDv3j1dhsYTGRmJN2/eoHLlymjWrJncZ+T40p6iwhcA9OjRA19++SUkEgnGjBmj84dNROnDCV8BAQGwtbWFg4MDAOjlONZE+PpUfs854Ytz4JQn4WvLli04evSovsMoE2RrqFZE4UuV4wson3W+1AlfFhYWfKYOPRQjShsSvso56grbA/pNddSH40t2XdyJk4tDH5ZZXQhfUqkUGRkZANSnOQL6Fb6KCh1kYdacoumNhp7uqInwlZ2dbXA3Sz///DP/f2Jioh4jKR7GWLE1vgQCAby8vADoL92RS3Ps2rWrwu8UFbfXHmXCFwCsWbMG9vb2uHHjhtx+TJRPOOHL398fAFCnTh0A+kl3VCV8NWrUCGZmZkhPT9ebsK5ruAciHTt2BFB+hK8nT55gzJgx6Nu370cPtGOIcGmOQMUSvrhUR1WOL6D8CV+MMf644dxqsggEAv5cQwXuidKGhK9yjiEJX4wxufpa+nB8yd5wcw44fYo9sg6nslr/69evIZFIYGZmpjLliUOfImBR4cvQXUuGRFHHpqEXuFcnfFlYWEAgEKCgoMCgBLy0tDTs2rWLf3///n2D7ufc3Fy+n1UJX4D+63xxwlfRNEeg/KU6/vbbb3B0dERsbKzeYlAlfDk4OPCC18KFC3H//n2dx0aUDikpKXj48CGMjY15V5UhCl+mpqa8i/NTSXfkHF9dunQBUDhibXlwWKalpQEo/G0+cOCAnqMpfWSFr/IiAGmCJo4vNzc3AOVH8EtPT+dNAS4uLkrbcPcy5eXagCg/kPBVzlE3oiOg2xpfsmKKvkZ1lK0xJhuL7Ge6RBeOL+7pXeXKlZWmu8qiz74omqtPji/NqUiOL6FQyBe4N6T6Db/88gvy8/PRqlUriEQiFBQUGLR4IOuSUjWKK6Bf4evx48e4efMmBAIBAgMDFT4vT6mOjDH89NNPePHiBfbs2aO3OFQJXwAwbNgwdOrUCbm5uRg3bpzBOSoJzeDcXs2aNePFJkMUvoBPq85XQUEB7wRu3749jIyMIJVK8eLFCz1HVjyyg7Xs3r1bj5GUDRU11bEiOr4eP34MAKhatSpMTU2VtuGuDcjxRZQ2JHyVczR1fOXn55f5RTB3sysQCCAUCvXu+OLQl9gjlUrlBIqCgoJS/w5yc3P5JyLFpTkClOpYXikqdBmyEwlQL3wBhlfnKzs7my8QPmvWLL27pDRBtrA9l9atDH1uy99//w0AaNmyJSpXrqzweXlyfCUkJCA5ORkAcP36db3FoU74EggE2LhxIywtLXHhwgVs27ZN1+ERpYBsfS8OQxW+PqWRHZOSkpCXlwcLCwt4enrCyckJQPlId+TKYQBAREREhRKHAHnH19u3b3nBqLxTEWt8qavvxcGda8rDtQFRviDhy0BJSUmBQCBATEyM2naaCl+MsTIXGmTdVgKBQM7xpasnz8occNxNYWmKPRcvXoRAIFD748q5vWRdWEW/g99//x2urq4QCoVYvXq1RuuW3TfS09MRFRWFZs2aaSQi6Ev4ki1sz+2T+ha+nj17hs6dO8PKyop/miYQCHDkyBEAmh+DmjB06FAsXbq0xPNzQhe3L2ni+BoxYgR69epV4nV+DLLCV1xcHKpXry7n7jK0kR1DQ0Px+vVr1KpVC8HBwbxYZMh1voqr78XBbcudO3d0fsypS3MEypfj6/jx4/z/169f19v5S53wBQAeHh5YsmQJAGDmzJl8ihNRflAnfN27d0/nTj5NhK/4+PgKIzaogktzrFevHoRCIX/jXt6ELwB6da2WBUXrllUUYY87pjRJdUxNTS0XLl9NhC99Or6uXr2KkJAQvY2ETZQtJHzpAYFAoPY1YsQIjZelLLVPFqFQyN8sFxQUIDQ0VK1l9mMoKjrJxqSt0BIQEMD3h1AohKOjI/r161fsj5k6x5cuxD9ZOOGLq2kEyPdDZmYmJk2ahG+++QZPnjzBuHHjtFo+YwyvXr2Cr68vEhIS1P4wckRGRqJZs2Z4/fq1Vuv6WLibNRMTE97arO8aX6tWrUJaWhpiYmL4p+hpaWno1q1bqa7n5s2bOHHiBCZPniw3PT4+Hv3790fVqlVhZmaG2rVrY/78+UoFTE7o4m52ZYUvVQLdmjVrEBoaWqrboozvv/8erVu3hqWlJX9ukT0OGzRogObNm2PVqlX8PLKOL31fqEkkEj62adOmwcjICN7e3gAMW/gqbkRHjpo1a8LExATv37/nUwx0QV5eHs6dOwdAtfBVnhxfx44d4/9/+/YtkpKS9BIHJxarEr4AYMqUKWjatCnevHmDKVOm6Co0ohRQVt8LAGrVqsU/bNN1cXJ1wpejoyNq1aoFxhj+/fdfncala7jC9g0aNADwX32i8iB8camO3Dm3oqU7yjq+gIojfHGOL3X3bdWrV4dQKERubi6eP3+uo8hKjqE7vubMmYMffviBf3BHVCxI+NIDaWlp/Gv16tWoVKmS3LQ1a9ZovKziHF8CgUBndb6KinCyopumIofsDf3YsWORlpaGJ0+e4OjRo3j06BGGDBmiVQyAfN/oUmzhHE5mZmZKnVapqanIz89H9+7d4ezsrPZGRtXy8/PzYW5uDi8vr2LrewH6c3xxYo6VlVWZF9jXNA0wKSkJTZo0Qe3atfmh4p2cnGBmZlaq8fzyyy/o16+f3MADV69eRYsWLfDhwwecOHECd+/exdKlS7F9+3Z07txZZU0vTjDSZBttbGzKTOSW5cOHD+jXrx/+7//+D0DhvsV9t9x3PXLkSKxfv57f78zNzSEQCCCRSOTq4OmDv/76C0lJSbCzs8PIkSMBoFwJX8UNaGFiYgJPT08Auk13jIiIQFZWFpycnNCwYUOlbcqL4+vVq1d8Khf3dF1f6Y7FOb6Awt+/zZs3w8jICH/++SfvYiUMn/DwcADy9b2AwnNmjRo1AOg23ZExplb4Aj6dOl+c46t+/foAypfwxTm+Bg4cCFNTU8TFxfFCXkWAE7646+CKIHzl5+fz53t1D7ZNTU15Eak8pDtq4/jSh/DFlTTQt4h49uxZvlwEUXqQ8KUHnJyc+JeNjQ0EAoHCNI4HDx6gffv2sLS0hJ+fn0IdhWvXrmHcuHHw9PSEq6srpkyZopA+JFvnqzhSU1MRHBwMkUiESpUqoX///vzB//btWxgZGSEqKgpA4QWRvb09P6pPQUEBTp8+jXbt2vHLS09PR0hICJycnFC5cmUEBwfLnZi5dKxly5bBxcWFt/MDhRf2Tk5OcHZ2RsuWLTFx4kRER0fLxRseHo7mzZvDzMwMzs7O+P7771FQUMDfcLu7u2PNmjVy6Y4NGzbEokWL+GUIBAJs3rwZvXv3hqWlJWrXro2//vpLbj0nT55EnTp1YGFhgfbt22v04/LgwQPMnDkTvr6+aNu2LUJCQvgLpNDQUP6poYeHBwQCgcplXrt2DY0aNYK5uTmaNm2KGzdu8P0NADExMTAyMuIt0Q8fPkTPnj1hZ2cHKysr1KtXDydPnkRKSgp69uwJoLDmjqy78NSpU2jbti1sbW1RuXJl9OjRQ87RwLmKDh06pHZ/vHz5Mvz9/WFpaQk7OzsEBgbi9evXyM7OBmMMoaGh6NSpE9q2bYt27drhzz//VNuH7u7uWLJkCQYNGgSRSAQXFxesW7dOro1AIMCGDRsQHBwMKysrfPfddwCA9evXo1atWjA1NYWXlxd27twpt9yDBw9ix44dcv0gm+qojISEBAQFBUEkEsHR0RFDhw5V+/RdKpXiwIED+Pzzz/lpjDGMHj0a3t7eOHToEJo3bw43Nzf069cPx44dQ2RkpJw7SiAQYNeuXZgyZQq8vLwQHBws9ySqZs2aAAqHlhcIBHx6TNFUx7y8PEyZMgUODg4wNzdH27ZtIRaL+c+59N2wsDA0bdoUlpaWaN26Ne7cuaNy+wBg8eLFmD59Or8/c+KWbLpzYGAg0tPT+Zs6oVBoMOmOK1euBACMHz+eFxY54ev27dt6d6SpQtNUR0A/db64fbRbt24qa5BxsRu68PX3339DKpXC19eXP4fqW/hSN6ABAPj5+WH27NkAgIkTJ/LOAcKwUZbmyKGPOl95eXn8OZ2Er/IrfHGOL09PT96BW5FcX9x1mJeXF4CKIXzJnrOL+50vT3W+tHF86TrVUSKR8PEVTQ/WJUlJSejatSt69epFv92lTIUTvhgDsrP18yqL+6O5c+di1qxZiImJQZ06dTBw4EBe8IiLi8OIESMQEBCAixcvYt++fYiIiMCkSZPklsEJX8U5vhhj6NWrFzIyMhAeHo6zZ88iKSkJAwYMAFD4xKFhw4b8hdnNmzf5v5mZmZBIJIiKikKLFi0AFF6gjxs3DpaWljh58iQiIiIgEonQtWtXOUdLWFgYEhMTcfbsWbk6KrJkZGTgwIED/LKBwpNnUFAQmjVrhtjYWKxfvx779u3D1q1bFVI/i3MZLV68GP3798fNmzcRFBSEwYMH8ye9R48e4YsvvkBQUBBiYmIwZswYzJkzp9i+HDt2LDIzM/HXX39h8+bNePz4MYYPHw4AGDBgAJ8GdO3aNaSlpcHV1VVhOdnZ2ejRowe8vLwQFRWFRYsWYdasWXLbUtTtN3HiROTl5eGff/5BXFwcfvzxR4hEIri6uvIXOkePHpVzF2ZnZ2PGjBkQi8UICwuDUChE7969FfpL3f4YExODjh07ol69eoiMjERERAR69uwJiUSC9+/fY/369Thw4AD+97//Ye/evRg7diyGDBnCiyGqWLFiBXx9fREdHY2QkBBMnz4dZ8+elWuzcOFCBAcHIy4uDqNGjcLhw4cxdepUzJw5E7du3cJXX32FkSNH4sKFCwAAsViMrl27on///hq7LNPS0uDv74+GDRvi+vXrOHXqFJ4/f47+/furnOfmzZt48+YNmjZtyk+LiYlBQkICZsyYoSAI+Pn5oVOnTgr1N3777Td06NCBjzskJATx8fEACvcfADh37hzS0tJw6NAhpbHMnj0bBw8exPbt2xEdHQ1PT08EBgYq/LjPnTsXK1euxPXr12FsbIxRo0YV2zeyyKY5ck9fTU1N4efnh0uXLvHtDKHA/b///ovLly/DxMRE7rxZq1YtGBsbIzs7W6fpgdqgaaojoF/hS1WaI1B+Uh25NMeePXvyx7KsaKxLNHF8cSxYsAC1a9fG06dPsWvXrrIOjSgFDE34kr3xVLXPccLX1atX9V7CoKzIzc3FvXv3ACgKX9yNsiHD/c7b29tj0KBBAAqFL33XWi0tOMcXd34uDwJQcXAPs0UikcpyNhycE7k8CH6G7Ph69uwZfw7Tp/C1evVqfoC0R48e6S2OCgkrB7x9+5YBYG/fvlX4LCcnhyUkJLCcnBzGGGNZWYwVSlC6f2Vlab9t27ZtYzY2NgrTk5OTGQC2efNmflp8fDwDwBITExljjA0dOpT179+ficVilp6ezhhj7NKlS0woFPL9wRhjSUlJTCwWs7S0NJXrY4yxM2fOMCMjI5aamqqwzmvXrjHGGJsxYwbr0aMHY4yx1atXs759+7LGjRuzEydOsEePHrEaNWqw77//njHG2JYtW1jNmjXZtWvX+Pjy8vKYhYUFO336NGOMseHDhzNHR0eWl5cnF4u/vz8zMTFhVlZWzNLSkgFgderUYcnJyXybb7/9lnl5eTGpVMpPW7BgAbO0tGQvX75kjDHm5ubGVq1axeLi4phYLGaZmZnMz8+PLVy4kJ8HAJs3bx7/PisriwkEAvb3338zxhgLCQlh3t7ecuv55ptvGAD2+vVrtX157NgxlpmZye7cucP27dsn15c3btxgAOS2qSgbN25k9vb2LDs7m5+2fv16BoCFhYUxsVjM/vjjD7lYGjRowBYtWqR0eadPn2YA2MWLF1WukzHGXrx4wQCwuLg4xphm++PAgQNZmzZtFJZVUFDA/vnnH2ZmZsb++ecflpyczMRiMXv69CkbPXo0GzhwoMo43NzcWNeuXeWmDRgwgHXr1o1/D4BNmzZNrk3r1q3Z2LFj5ab169ePBQUF8e+Dg4PZ8OHD5doAYIcPH5bb5hs3bjDGGJs/fz7r0qWLXPtHjx4xAOzOnTtK4z98+DAzMjKS23f27t0rt9yiTJkyhVlYWMjF1KdPHxYVFcWkUimLiopi9evXZ+PGjVMaJ8fw4cNZcHAwY6xwnzYxMWG7du3iP//w4QNzcXFhy5cvZ4wxduHCBQaAnTt3jm9z4sQJBkDufKIK7tzy9u1bJhaL2a1bt+Q+7927NxsxYgT//tWrV0wsFvP7T9FzuS7o168fA8CGDRum8FndunUZAP5cZWj88MMPDIBcn6pi+/btDADr0KGDDiIr/M0BwIyMjNibN29Utnvy5AkDwIRCodwxYkjk5eWxSpUqMQDs6tWr7NatWwwAs7KyYgUFBTqPp3fv3gwAW79+vUbt//e//zEA7MsvvyzjyIiPhTuXGxsbs3fv3il8vmbNGgaAffHFFzqPSfY3qSgFBQXM2tqaAWCxsbE6i02XREdHMwDM3t6eP1edOnWKAWC+vr56jq54WrRowQCwI0eOsPfv3/Pf16VLl/Qd2kcjlUqZmZkZA8AfI02bNtV3WB/N9evXGQBWvXr1YtvOmzePAWDjx4/XQWQfh729PQPAbt68qbLNwoUL9bI9V69eZQAYAIX7A12Rnp7O3/ca8jWoIaFOJyrKRzm+li1bBoFAgGnTpqltFx4ejiZNmsDc3BweHh7YsGHDx6z2k8LX15f/39nZGQDw4sULAEBUVBQOHz6Mdu3aoUaNGhCJRAgMDIRUKuVzlAFoXOMrMTERrq6ucs4jHx8f2Nra8rVuAgICcOnSJUilUoSHhyMgIAABAQEIDw9HWloaUlNT0aZNGz6+1NRU+Pv7w9XVFSKRCPb29sjNzZVLo2vQoAFf8FyWwYMHIyYmBrGxsYiIiICnpye6dOnCPwFITExEq1at5Gpb+fr64v379wq52cXVtpLtZysrK1hbW/P9nJiYyKcGcnAjGakiISEBjo6OfM0oIyMjeHh4wMbGRqu6QYmJifDz85N70sqtW1V9tylTpuC7775DmzZtsHDhQt6ZJ9tWKpXKpXAlJSVh0KBB8PDwQKVKlfj0udTUVLllq9sfOcdXUd6/f48HDx4gLy8P3bp1Q7169dCuXTt4enpix44dxRaJLtrXrVq1UuhDWUcVUNhv3H7I0aZNm4+q2RQVFYULFy5AJBLxL85Jo2obcnJyYGZmplH9NQ7GmEL7Bg0awMTEBAKBAKampmjQoIFW25KUlIT8/Hy5PjExMUHz5s0VlqPuO9YEZQNMAIWDPMi6u7h9Wl8F7lNSUnDw4EEAwIwZMxQ+N/Q6X5rW+AL+S//QleOLq0vRtm1btbVJOMeXVCo12BGULl26hMzMTDg4OKBZs2aoW7curKyskJ2dXWwacFmgjeMLKPwOgMLt0MdxRmgO535u2rSp0rRCfTq+VKU5AoXXFZwbv6KmO8qmOXK/z+Up1VHW8WVhYYEvvvgCQMVId8zKyuJrhTZp0gRA+XA+FYcmIzpylJdUx5ycHH5frF69usp2+nJ8ybqr9OX42rBhg9y1cnlwlJYnSix8icVi/P7773I3ScpITk5GUFAQPvvsM9y4cQPffvstpkyZwt9wlDaWlkBWln5eWtYm1whOtAL+K9rIWZOlUin69u2LXbt24cqVK7xIdO/ePdSqVYufT9MaX8puuItOb9euHd69e4fo6GhcunQJAQEB8Pf3R3h4OC5fvgx7e3teDJBKpahfvz527dqFs2fPIiYmhh9Bj7NaA6prldjY2MDT0xOenp5o06YNtmzZgnv37mHfvn0q4y160y0UCsEYkxO+lPWDbD8DhX3N9XNJbha4dQiFQpiYmMiNLKmtCKIKLr6i6XJjxozBgwcPMHToUMTFxaFp06Z8XSzZdcuKgD179kR6ejo2bdqEf//9lx+dqWiRdXX7o4WFhdI4ZYWNEydO4NSpU9i1axdOnTqFhISEYut8KaNoHyrbh4q20bbviyKVStGzZ09+P+Ze9+7dk6trJ0uVKlXw/v17uX7kbl4SEhKUznP79m3Url1bYTonDnPfgTb7JddWkz5R9x1rgirhKyMjA1WrVuXfm5ubQygU6k30WLNmDaRSKTp16gQ/Pz+Fz2XrfBki2tT44oSvp0+f6qSeliZpjkDhccvtY4Za54tLc+zevTuEQiGMjIzQuHFjAPqp86Wt8NW8eXMYGxvjyZMnCg8yCMNCXZoj8N9vx71793SWoqaJ8AVU/DpfRet7Af8JX69evdL7IC3FwdX4qly5MgDw1+D79+/XeEAgQ4VLczQ3N4ePjw8/TZ9lFEoDTUZ05OBSHQ1d+OJEYgsLC7XbxQlfuq7xJVvaQh/CV15eHn+/VqVKFQDlQ1gvT5RI+MrKysLgwYOxadMm2NnZqW27YcMG1KhRA6tXr4a3tzfGjBmDUaNG4aeffipRwMUhEABWVvp5fcQ9dYlo3Lgx7t+/D1dXV9SpU4cXiTw9PeUcVJrW+PLx8UFqaqqc4p2QkIC3b9/yN4Fcna9ffvkFAoEAPj4+vKgZFhaGxo0b8+tr3LgxUlJSYGdnhxo1asjFp8kTjKJw4hF3k+zj44MrV67ICQA3btyAlZUVP/pR1apVkZaWxotDb968kXPDaYKPjw+uXr0qN63o+6J4enri+fPnyMjIgEAggLGxMR48eIDMzEy+LzVdd2xsrJwwwK1b3Yierq6uGD9+PA4dOoSZM2di06ZNAAovDLh5ufnT09ORmJiIefPmoWPHjvD29sbr1681jpHD19cXYWFhCtOzs7NRs2ZNmJmZITU1FbVq1eKdhdygDOpQ1vecuKoKb29vREREyE27cuWKVn1flMaNGyM+Ph7u7u5y+7Knp6dK8ZYbzU5W5GrYsCHq1q2LVatWKdy8xMbG4ty5cxg4cKDc9Li4ODnh69atW7y4zU1XV1uFOyfI9kl+fj6uX7/+UX2iDFXC161bt9CoUSP+vUAg0Fudrzdv3mDz5s0AgJkzZyptU14cX5oIX7a2tnBycgKAMncp5eTk4Pz58wCKF74EAoFBj+zIGOOFrx49evDT9VnnS1vhy8rKihfqip4TCfVkZGRo5Xb9WIoTvtzc3GBiYoK8vDyd1X0h4asQZcKXvb09//v77NkzvcSlCVKplL+ms7e3BwB06NABjo6OSE9Px5kzZ/QZ3kfDFbavWrUqbG1t+d/E8u764oQvbRxfDx8+NGhnLycsVatWTe2DaO5886k5vnbv3o1nz56hWrVqGD16NAByfJU2JRK+Jk6ciO7du6NTp07Fto2MjESXLl3kpgUGBuL69esqnzLk5eUhMzNT7kUoMnv2bNy8eRM//vgj4uLicO/ePfz111+YPHmyXLuiqY4SiUTBtZKQkIBOnTrB19cXgwcPRnR0NK5du4Zhw4bB399fLpUsICAAf/zxB/z9/SEQCGBnZwcfHx/8/fffaNy4MS/EDB48GPb29pg1axauXLmC5ORkhIeHY+rUqRoVjH7//j2ePXuGZ8+eITY2FhMmTIC5uTm/P02YMAGPHj3C5MmTcfv2bRw+fBgbN27EoEGD+IuRDh06YOfOnYiKisL9+/cxadIkpUKROsaPH4+kpCTMmDEDd+7cwe7duxEaGqp2npYtW8LT0xPffvstoqOjcfPmTSxatAgtWrRQSMtTx6BBgyAUCjF69GgkJCTg5MmTvGjMfZ9FHV/Tpk3D6dOnkZycjOjoaJw/f56/iXdzc4NAIEBERASePXuGrKws2NnZoXLlyvj9999x//59nD9/XmnqV3GEhIRALBZjwoQJuHnzJm7fvo3169fjyZMnsLKywqRJkzB9+nT8+eefePz4MeLi4vDrr79i+/btapd7+fJlLF++HHfv3sWvv/6KAwcOYOrUqWrn+frrrxEaGooNGzbg3r17+Pnnn3Ho0CF+YICSMHHiRGRkZGDgwIG4du0aHjx4gDNnzmDUqFEqRaeqVauicePGcjec3CiiCQkJ6NOnD65du4bU1FQcOHAAPXv2RKtWrRTSx8PCwnDw4EHcvXsX69atQ3x8PIYMGQIAcHBwgIWFBV9sX9kIMFZWVvi///s/fP3117zTbuzYsXj//j3/41pSUlNTERMTg9TUVEgkEsTGxuLOnTtyT8BTUlLw5MkThd8MfY3suGnTJmRlZaFevXoIDAxU2oYTVyuC8AXorsD9hQsXkJubixo1aqBevXrFtjfkAve3b9/GgwcPYGpqKncdw53Dy4PjC/gv3ZGEL81gjGHz5s2oUaMGvL29kZubW+brfPjwIVJSUmBkZKSQps9hZGQET09PALpLd9RU+GrRogUEAgGSkpIUSk1UBOLi4gCAH70YKPwtLw/pjm/evOHFEE74MjY25geuKu8DX3COrypVqkAgEJSrQu/q0CbV0dXVFQKBADk5OXx/GCKaFLYHDMPxxbkkdQVjjB9lfOrUqfx+bMjnlvKI1sLX3r17ER0djWXLlmnU/tmzZ3B0dJSb5ujoiIKCAl6lL8qyZctgY2PDv4pzhHyq1KtXDxs3bsSjR4/QoUMHNGrUCPPnz+fr8nAUdXxlZWWhUaNGcq+goCAIBAIcOXIEdnZ2aNeuHTp16gQPDw8+tZCjffv2kEgkck8l/f39IZFI5BxflpaW+Ouvv+Dk5ITx48fD29sbo0aNQk5OjkY3a5s2bYKzszOcnZ3Rvn17vHz5EidPnuTTdqpVq4aTJ0/i2rVr8PPzw4QJE/D5559j9OjRvBgUEhKCdu3aYezYsZg2bRq6dOkilwaqCTVq1MDBgwdx7Ngx+Pn5YcOGDVi6dKnaeT58+ICffvoJtra2aNeuHQYMGIBq1appNHqgLCKRCMeOHUNCQgIaNWqEuXPn4scffwSgOtVRIpFg4sSJ8Pb2RteuXeHl5YXffvsNQGGfTZgwAb/88gtq1qyJSZMmQSgUYu/evYiKikL9+vUxffp0rFixQqs4gcI0jDNnziA2NhbNmzdHq1atcOTIEX6/W7p0KRYsWIB169ahX79+GDFiBI4dO8bXE1PFzJkzERUVhUaNGmHJkiVYuXKlSrGCo1evXlizZg1WrFjBHyfbtm1T+SRdE1xcXHD58mVIJBIEBgaifv36mDp1KmxsbBS+A1nGjRuncGHZpk0bXL16FUZGRggKCoKnpydCQkIwfPhwnD17FmZmZgrLOH78OHx9fXHw4EEsWbKEf8JnbGyMtWvXYuPGjXBxcUFwcLDSOH744Qf06dMHQ4cO5d2ip0+fLta1WxwLFixAo0aNsHDhQmRlZSEoKAhDhgzhn5ADwJ49e9ClSxf+h5yDc3zpUvjKz8/H2rVrARTW9lL11JETil68eKHX0X1UoU2NL0B3wpdsmqMmqcWG7PjiRhlu37693I1/s2bNABTWNdR1mhAJX2XLy5cv0bt3b4wdOxbZ2dnIyMjQyY0kV9+rWbNmakUmXdf50lT4srW15YXuyMjIMo9Ll7x9+5Z3ghQV88uD8MX9folEIrlsEC7d8ejRozoXGEoTWccXUL5GOFSHNqmOZmZm/L5oyOmOmgpfhuL40qV77vTp04iPj4dIJMLYsWP5PiLHVymjTdX81NRU5uDgwGJiYvhp/v7+bOrUqSrnqV27Nlu6dKnctIiICAaApaWlKZ0nNzeXvX37ln9xI6dpMqrjp0Rubi4Ti8Xs+vXratvl5OQwsVjMoqKiyjSe6OhoJhaL2fv37/lp3Mhtt2/fLtN1M8ZYdnY2E4vFSkfLe/z4MROLxezhw4dlHgdjjN29e5eJxWL24sULxljZ9EN8fDwTi8VqR01TRkJCAhOLxSpHpCxNMjMzmVgsljtnaNMX3Kic5ZmcnBxWo0YNduXKlRLND4CtWLGC/74yMjKYWCxmCQkJpRhl6XHnzh0mFov5kVVzc3OZq6sri4iIUGgrew7Lzs7WybmcGwXV0dGR5ebmqm3r6urKALDLly+XaUwloXnz5gwA++uvvzRqv3r16jIfEU4qlTJ3d3et4uJGGzt69GiZxVVSPvvsMwaArVu3Tm66RCJhNjY2DIDcuU0XVK1aVW7EXU3gRukFwI+wTChy8uRJ5ujoyAAwExMTZmxszACw+Pj4Ml/3yJEjGQA2Z84cte2+/vprBoBNmTKlzGNi7L9RpHv37l1s27FjxzIAbPbs2TqITHdcvnyZAWDVqlVT+Kxv374MAFu7dq0eItMMbqS6GjVqyE2XSqWsVq1aDIDciM/ljRUrVjAAbPDgwYwxxiZOnMgAsJCQED1H9nFMnTpVo3MCR+vWrRkAtn///jKOrORw2/T111+rbScWizUe0bI0qV69Ov9bCYBlZmbqbN0dO3ZkANj06dMZY//1gYuLi85iKK+U2aiOUVFRePHiBZo0aQJjY2MYGxsjPDwca9euhbGxsdJ0HycnJ4Xc9xcvXsDY2JgvslgUMzMzVKpUSe5FKML1d9FaOkXhPpdKpWVWEJUxpjQe7n919YdKC3X9UdyojqUNlxrB1dQqi/VzTiptUzc5d5Iu+oJzJ8jWwJIdWfJTwNzcHDt27FDpcNUULmWZe2JbdOABQ4HbL7l4Hz58iLlz5ypN3zE1NYWxsTEYYzpJJ2IyVvJJkyYpOOuKYsh1vgwx1fHOnTtISUmBqakpOnTooNE8hur4Sk9Px+XLlwEUDv4hi1Ao5EcP03Wdr5I4vqpWrco7pStqDaaP4f3795g0aRKCgoLw/Plz1KtXD9euXeNHHdOF66C4+l4chur4AipunS9l9b04ypPjq+g9l0Ag4F1f5TndUTbVESg/IxwWhzaOL6B8bLe2ji9dOhELCgqQlpYmN01Xbv+YmBiEhYXByMiIL+XC9dGzZ8+KrdFNaI5WwlfHjh0RFxcnVxuqadOmGDx4MGJiYpTegLdq1Qpnz56Vm3bmzBk0bdpUYSQ9QjvUFTeXxcjIiE85Kau0DFkRRTYe7n9dHLSqimrLxqELsYcxxosS3I11WQiAmgqfRdFlX3ApbLI3aZzw9qkIX0BhKnDRm2dNkO2joqM65ufnG2QR06LHYZ06dfDVV18pbSsQCPh9QxcjO168eBE3btyAhYUF/u///q/Y9oZc56ukwte9e/fK7HzMpTkGBASoHPChKIZa4+vUqVOQSqVo0KCBQoouoJ86X4yxEglfAKU7qiI6OhpNmjTBr7/+CqCwtopYLEbDhg11dvP18OFDJCcnq63vxVEehC+xWGywD2ZKQnkXvrhaRVx9L1k44ev06dMGXRtKHRU11VGbGl9AxRK+uAdi796909l17rNnzyCRSGBsbAwHBwcAuhO+uAey/fr14/dfBwcHGBkZQSqV6nSQlYqOVsKXtbU16tevL/eysrJC5cqV+R+EkJAQDBs2jJ9n/PjxePjwIWbMmIHExERs3boVW7Zs+agi00Qhmgpf3KiCQNkJULKF1mXrHenS8aXOAaVLsefDhw9gjEEgEPAiRWmvX9Zhp63jS5d9oewmTRvhKyUlRaHQ+6dEfn4+xGIx2rdvzx9Lsg8MDHEYcnUCtDI4gUQXji/u4mLEiBEqHceylAfHl6Y1vlxdXWFhYYH8/HytR7bVFNn6XppiqI4vZaM5ysLV+dKl8JWbm8vfBJDw9XFIJBIsW7YMLVq0wO3bt+Hs7IzTp09j9erVsLCwACB/81WWaFrfC/hP+EpJSZEbQKSs0Eb4ql27NipXroy8vDzcuHGjrEPTGcoK23NwN/CGLHypcnwBhQ9EGjduDIlEgj///FPXoZUKnGBXVsLX+/fvsXbtWp0Lado6vrjtrgjCF3e+kUgkOjnPAfIjTnL7ki6Er8ePH2Pv3r0A5EcZNzIy4kfjpjpfpUeJRnVUR1paGlJTU/n3NWvWxMmTJ3Hx4kU0bNgQS5Yswdq1a9GnT5/SXvUnhzbCR1kLX6rcR7IiS1mr9obi+JJNc+ScdrLOt9LoB1UOO03QVV9IJBK+L2TdH7pMtSzvcMKWiYkJvy8JBALe/WVowpdEIuEFTU33S+4GnhNJy4rExEScOHECAoEA06dP12geQxW+pFIpf0OqqeNLKBTy6W537twpk7hu3rwJAGjXrp3G83DxG5LwlZ+fj1OnTgFQTHPk4BxfN2/e1NmFuewxUlLhSywW60RkNmRSUlIQEBCAb7/9FgUFBejTpw/i4uIURiDXlfClaZojUDg4lEgkglQqxYMHD8o0LkA74UsgEFS4dEfGGC98lVfHF3fzrszxBaDcpztyji8u1VF2NLzScB5u374dU6dOxdy5cz96WdpQUseXoTrdpFIpf5xoKnwBunODc4Xtq1evzh8ruhC+1q5di4KCAvj7+/PXFRzl4fxS3vho4evixYtYvXo1/z40NJT/Eefw9/dHdHQ08vLykJycjPHjx3/sagloV+OJc4mUtfBVNBZZEaqs0x3Vpf7pUmzhboJk6wfJ9ktppPipcthpgq6EL+4mzcTERM6l9KnV+PoYuIs22ZGYgP+OZ0NLJ+H2KYFAoLHwxYmieXl5ZbpPrFq1CgDw+eefo3bt2hrNwwlfKSkpOknF1BTZ1CttamBywldZ1PmSSqV8Sg33lFITDDHVMSIiAm/fvkWVKlXQvHlzpW3c3NxQuXJl5Ofn84JfWcOdU7naeNpQq1YtODo64sOHDzp1qRkau3btgq+vLyIiIiASiRAaGooDBw4odcPoWvjy9/cvtq1AIOBdX/fu3SvLsAD8V65AE+EL+C/dsaKM7PjixQukp6dDIBDwvweylIcbU+68rMrl/OWXX0IgEODy5csG7RZSRVHHl4ODA8zNzcEYkxulr6TExMQAKLsHRqr4mBpfhlgG4+XLlygoKIBAIICzs7PatkZGRrzzVld1vjjHl6urq86Er8zMTGzcuBEAlGbC0ciOpU+pO74I3VESx1dZOURUua0EAoHORCdDcXwpE76EQiHv2CmNGEpa3wvQvfBVtNaPbKqjIf44GxKyji9ZDLXAvewxyO3vxSErjJbV+enFixfYsWMHAHkreXFUrVoV9vb2YIzprKaOJnDuKBMTk2IL9MtSlgXu37x5wwuXmqSRchhiqiOX5ti9e3eVv68CgUDndb5KWt8LKIz3s88+A/DppjsmJCRg6NChePfuHVq3bo3Y2FgMHz5c5blKFzW+tKnvxaHLOl/aOL6Awrq+AHD58uUK8fvO1feqVauW0uOOE77evHlT5q7lklKc46tatWq823DPnj26CqvUKFrcXiAQlGq6Y0JCQqktSxu0dXzVqFEDQKFYzYmdhgQn3jg6OmpU41tXDx44lDm+yroft2zZgszMTHh5eSktEVEehPXyBglf5RhDSnVU5z4r63VrEoM+Uh1lb0hlHTClEUNJR3SUnaes+0JZYXsAcg41cn2ppzjHl6GlOmpb3wuQL3BfViljv/32G/Ly8tC0aVM+5UvT2AyxwL1sfS9NBUagbIUv7gLR2tpaYX9VhyE6vo4fPw5AdZojh67rfH2M8AX8l+546dKlUoupPCEWi8EYQ4sWLRAeHg4PDw+17XVx48XV92ratKnG9foMWfhq1qwZjIyM8PTp01Jx2+gbdfW9gMJ9hHu4Z6g3p8U5vgBg8ODBAIDdu3frJKbSIj8/n3dGcY4voPTqfDHGeOHr5cuXOhM3GWNaO77Mzc15t7UhpjvK1tDSBO58WFEdXwUFBXzG3MyZM5Vm75Djq/Qh4asco43rR181vmSnGYLjizFW5mILd/Nubm6uNIZPzfFFwlfJUSV8lQfHlzZwNw5ltT2HDx8GUDhimzZCEWCYdb64G3Ft0hyBshW+uDor2ri9AMNzfN25cwf37t2DiYkJOnfurLYt5/gSi8W6CK3UhK/Lly9/kudeLjWwYcOGGp2jdCl8aVLfi8OQhS9LS0s0atQIQMWo86VuREeg8OGIobsyinN8AUCfPn1gamqKW7du8WJfeYD73REKhbCzs+Onl9YIhy9fvpQTP2RrWJcl79+/56/RNXV8AYY9sqOmhe05uHNORa3x9eeffyI1NRVVq1bF0KFDlbYx9HNLeYSEr3KMNo6vsq7xpYnbSp81vmTjKkvBhzGmNNVRNobS6IfScHyV5Y2PqsL2gHz666d486UNqlIdK5LjCyh74YtLGeBqXGkDJ3yVhVhUUjiRSFvhi7thTk9P528YSgvOVcClm2iKoRW359IcAwICiu1fTviKj4/XiRPgY4UvPz8/WFlZ4e3bt4iPjy/N0MoFnPClaY0/XaQ6alPYnsOQhS8AFarAfXHCF2D4N6eaOL5sbW3RvXt3AOWryD33O2Zvby93PVxaji/O7cWhKycVd81iZGSk1fm+Iglf+kp1dHV15Y+VshK+GGP46aefAACTJk1SMEpwkOOr9CHhy0BJSUmBQCDgiyoqw5BqfBmS40tZf5S22HLx4kUIBAL+x4njw4cPYIzJjbzHoawffv/9d7i6ukIoFMoNEqGOlJQUODo64s6dOzA2NlYZiyp04fhSVdiewxBGdnz27Bk6d+4MKysr3kouEAhw5MgRAJodg5oydOhQLF26VOv5PsbxNWLECPTq1UvrdX4MyoSvuLg4VK9enU99VQZ3YZefn18mFzkluXnjMETHV0mFL0tLS/6GoLSFvJI6vgwt1VHTNEeg8IbXyckJUqm0VM4TxfGxwpexsTFfg+lTrPN1//59AJoLX2V945WamooHDx5oVd8L+C/+tLS0Mj9uSnLubNmyJQDdpQCXFVKplBeIy7PwpYnjC/hvdMc9e/aUm4eSRQvbc5R34Us2zVEblzq33RVB+NLFgweOgoICpKWlAdCN4+uff/5BVFQUzM3NMWHCBJXtDP3cUh4h4UsPCAQCta8RI0ZotJySCF8HDx7UOF9cG0rb8RUQEMD3h1AohKOjI/r166fyR4cxVqzbRBeCj6zbq+iPVdH1Z2ZmYtKkSfjmm2/w5MkTjBs3Tuv1GRkZoXXr1khLS9PIDn3x4kVYW1vj3bt3OhG+irq9OAxhZMdVq1YhLS0NMTEx/JPztLQ0dOvWrVTXc/PmTZw4cQKTJ0+Wmx4fH4/+/fujatWqMDMzQ+3atTF//ny+7xhjvFCtrsZXcnKyUoFuzZo1CA0NLdVtKUpKSgpGjx6NmjVrwsLCAq1atcLGjRvlvtcGDRqgefPm/KiKypAVSIteaJYGHyN8cemBd+/e1atQK4tsjS9tKat0x5I6vgwp1fH169e8INSjR49i2wsEAp3W+fpY4Qv4L93xUxO+GGO848vT01Ojecpa+CpJfS+g8GbYwcEBQNmP7FiSc2fNmjUBlH+XQmpqKrKysmBqaqpWLDXkm9OCggL+oWhxDyW6d+8Oa2trpKam4vLlyzqI7uMpWtieo7SEr6IPvHTt+NImzRH4z/FliDW+DNnxlZaWBqlUChMTEzg6Opa58MW5vUaMGKH2monrq9evXxvUyOLlGRK+9EBaWhr/Wr16NSpVqiQ3bc2aNRotR5t0t7J2XZWW40vWwTJ27FikpaXhyZMnOHr0KB49eoQhQ4YonU92hEBDEb6KW39qairy8/PRvXt3ODs7l+hmxtjYGKampnByctK6dpFEIimzUZeKu0Ery1RHTV2NSUlJaNKkCWrXrs3fRDg5OWk1Sp4m/PLLL+jXr5/cjc3Vq1fRokULfPjwASdOnMDdu3exdOlSbN++HZ07d8aHDx9QUFCgcp/mhDCpVKpyf7axsSkTkVuW27dvQyqVYuPGjYiPj8fcuXNx6NAhLF++XK7dyJEjsX79erXHHjd0dWnXF/nw4QN/XimJ8OXm5gZzc3Pk5eUhOTm5VGMrKSWt8QWUnfBVERxfp06dgkQiQb169fib9+LQZZ2v0hC+PtWRHV+8eIF3795BIBAUW9Seo6xvvEqS5sihq3THkghfzs7OAApd1eV5ZEfut6hu3bpqR6EzZOFLNhNAtgaWMiwsLNCnTx8A5afIPfe7U9TxxQlAjx49+qhrfu5BnI+PDwD9OL60oSKlOurS8SVbeF8oFJap8JWYmIjjx49DIBBg+vTpatva2Njw18aGeH4pj5DwpQecnJz4l42NDQQCgcI0jgcPHqB9+/awtLSEn58fIiMj+c8kEgliY2PRrVs3WFhYwNXVFVOmTFGaUsT9aBcnNKSmpiI4OBgikQiVKlVC//798fz5cwCFJ2IjIyNERUUBKHyCam9vj2bNmvEi3OHDh/mLHqDwRDdhwgR06NABvr6+CA4Oljshc+lYy5Ytg4uLC38xBxRe3Ds5OcHZ2RktW7bExIkTER0dLRdveHg4mjdvDktLS3Tt2hW//PKL3Da6u7vzKYSc8NS6dWssWrSIbyMQCLB582b07t0blpaWqF27Nv766y+59Zw8eRJ16tSBhYUF2rdvr/JHhatrZW5urtCXkyZNQnp6OgoKChAaGsqPEuTh4QGBQKBymdeuXUOjRo1gbm6Opk2b4saNG/xnRkZGCqmODx8+RM+ePWFnZwcrKyvUq1cPJ0+eREpKCtq3bw8A6NChA5o2bcq7C0+dOoW2bdvC1tYWlStXRo8ePZCUlMSvh0v7O3TokMr9ESgsmuzv7w8fHx906NABQ4cOxevXrwEU7i/Lly+Hh4cHmjRpgkGDBvFFx1Xh7u6OJUuWYNCgQRCJRHBxccG6devk2ggEAmzYsAHBwcGwsrLCd999BwBYv349atWqBVNTU3h5eWHnzp1yyz148CB27Ngh57KUTXVURkJCAoKCgiASieDo6IihQ4eqrZUklUpx4MABfP755/w0xhhGjx4Nb29vHDp0CM2bN4ebmxv69euHY8eOITIyEqtWreLFmmbNmmHjxo38cV6zZk0cPHiQF8O4J9GNGjWCQCDgb6KKpjrm5eVhypQpcHBwgLm5Odq2bSt3s87tR2FhYWjatCksLS3RunVr3LlzR+X2de3aFdu2bUOXLl3g4eGBgIAADBkyBH///bdcu8DAQKSnp/MOB2VwNQ5KW/iSPR+qciCqw8jIiK8NZih1vkqa6gj8V+estG+YP9bx9e7dO73fJHP1vTRxe3Fwwld5cXy1aNECRkZGSE1N1VmhZkOAS3N0dXVVWU+lKGV942XowldBQQF/TaON8MWNLPfhw4cyLQ5d1mhS3wswbOGLOy/b2NhoVHuTS3fcv3+/wQ2eowxVqY7Ozs4wNjZGQUHBR30vnPDFZQKUF8dXSkqK3n9Pi2LIji/ZwvYA5ISv0u5HLvvh888/l7vnVYZAIKA6X6VMxRO+GAOys/XzKoOTzNy5czFr1izExMSgTp06GDhwIO8EuXPnDqZMmYJevXrh5s2b2LdvHyIiIjBp0iSF5WjiCmOMoVevXsjIyEB4eDjOnj2LpKQkDBgwAEDhCbhhw4b8xdrNmzf5v9zTCU74AAov0tu3bw9ra2v8/vvv2LNnD0QiEbp27Sr3gxoWFobExEScPXuWr69SlIyMDBw4cAAtWrTgpz158gRBQUFo1qwZrl69ijlz5uDo0aP4/vvvlS5D2VCxHIsXL0b//v1x8+ZNBAUFYfDgwfwF26NHj/DFF18gKCgIMTExGDNmDObMmaN0OZzjy9TUVKEvU1NT8e2330IikWDAgAE4d+4cgEJhKy0tDa6urgrLy87ORo8ePeD1/9g77zA3qrOL/0baXtx778Y2uGEMhrhg00MnhBBCCSFfMB0CJEASSEiA0HsJndBSMC10U00xbrhgG/e+67be4u1aab4/Zu/sSKsy5Y402tV5Hj+71s6MRqOZe9977jnnjhzJ4sWLueWWW7j22mv1v0crZC699FIaGhr44osvWLFiBX//+98pKiqif//+vPbaa4C2msh7773HPffco7/PNddcw8KFC/n444/x+XycdtpprYjSWPcjwNKlS5k1axajR4/m6aef5sknn+Tkk0/WZ9v+8Ic/8Oyzz/LYY4/xv//9j7PPPpvf/OY3cckQgLvuuouxY8eyZMkSbrjhBq6++mo++uijsG1uvvlmTjnlFFasWMGFF17I66+/zpVXXslvf/tbvv/+e37zm9/wy1/+kk8//RTQ1BnHHXccP/3pT02rLEtLS5k+fTrjx49n0aJFvP/+++zatYuf/vSnMfdZvnw5FRUV+uBYXKdVq1ZxzTXXtLonx40bx1FHHcUrr7wS9oz88Y9/5IwzzmDZsmX84he/4Oyzz9YHrZ988gkAc+fOpbS0lDlz5kQ9l+uvv57XXnuN559/niVLljBs2DCOPfbYVgOTm266iXvuuYdFixaRlZXFhRdemPDaCDQ1NVFdXd1qZjknJ4dx48Yxb968mPuKwajszl0MWnNyclpZRs3CazlfTogvMUgTExqy4FTxpapq3Bw4txEIBHTC1ky+l4B4ttesWeO6XVMG8VVYWMjEiROB9qX6shpsD+4OvOzmewkkg/gyPo9WiK/c3Fy9HRC5OemItkB8mc33Epg5cyY9e/Zk3759fPjhh26emhSIfidywsXv9+s1tV2yat++fezcuRPQJvmcHMsq7Cq+BgwYAGhtlph09gJqamr0z+RlxZe4Z8Tz0tDQIHXhml27dvHCCy8AhI3l4sHL7Us6ou0RX7W1UFSUmn8urOp07bXX8uMf/5gRI0bw5z//mS1btrB+/XpUVeWFF17g2GOP5eqrr2b48OEcfvjhPPjgg7zwwgv6LJ2AoigJZ3vmzp3L8uXLefnllzn44IM59NBD+ec//8nnn3+uK0NmzJihE1+fffYZs2bN4sADD9Rnu7/88kt99vLVV1/F5/Px4IMPMmzYMAYNGsSzzz7L1q1b9WOAVog/9dRTjBkzJqzAePTRRykqKqKwsJCuXbuyZs0annnmmbC/9+/fn4cffpihQ4cyY8YMLr30Uu65556oyjZB/kVj7y+44ALOPvtshg0bxm233UZNTQ0LFiwANOXQkCFDuO+++xg5ciTnnHNOzBw2QXx98803ra7lI488wpIlS/juu+/Iz8/XC8Pu3bvTq1evqOTkSy+9RDAY5JlnnmHMmDGceOKJXHfdda0+kxFbt27liCOO4KCDDmLIkCGceOKJTJs2Db/frzfm3bt3p1u3bnrHcsYZZ3D66aczfPhwxo8fz9NPP82KFSta5S3Fuh8B7rzzTiZNmsSdd97JiBEjOOCAA7jyyivp1q0bNTU13HvvvTzzzDMce+yxDBo0iJNOOomf/OQnPPHEE1GvpcARRxzB73//e0aMGMHll1/OT37yk1Z5UT//+c+58MILGTJkCAMHDuTuu+/mggsu4JJLLmHEiBFcc801nH766bqvXuRq5efnt1JZxsJjjz3GxIkTue222zjggAOYMGECzzzzDJ9++mnMwcfmzZvx+/26lRJaBiqCTInEqFGjWLt2bZhl88wzz+Siiy5ixIgR3HrrrUyaNIl//etfQAtx0LVrV3r16hW1wK2pqeGxxx7jrrvu4vjjj2f06NE8+eST5Ofn8/TTT4dt+7e//U1X7f3+97/n66+/btWexMKmTZv417/+xUUXXdTqb3379o0rvxf3suwcAyf5XgLCHug14stOxpeYGRcz5bJgV/GVn5+vE8CpzPn6+uuvqaiooGvXrno4txn06NGDAQMGoKpqmBrXDcggvqB95nx5jfgSEz4HH3ywrec4GcSXaDuzs7MtTxoI5X86D9bsEF9eU9mIdtks8eX3+/nZz34GpIfdMZbiC5znfIn+vn///vo9sGPHjqSspm1X8VVQUKDXm17K+RITmoWFhaYn7FKp+CoqKtLHzDJVq48++igNDQ1MnjzZ9IRHRvElF22P+GpjGDt2rP67KCR2795NMBjUfcIdO3akqKiIoqIijj32WEKhUNQsmngZBaA18v379w9THo0ePZpOnTrpHcCMGTOYN28eoVCIzz//nBkzZjB9+nQWL17M3r17Wbduna74Wrx4MevXr2fgwIFMmzaNiRMn0qVLF+rr68NsdAcddFDUouqcc85h6dKlLFu2jC+//JJhw4ZxzDHH6I3g6tWrmTJlCoqi6KqiSZMmUV1drbP3RsQjvozXubCwkOLiYnbv3q2/z2GHHRaWoSVWxjJCVVWd+NqwYUPUa1lcXGwpjHb16tWMGzcubKBjfO9oZOYVV1zBX//6V4444ghuvvlmXZlnROSqihs2bODnP/85Q4YMoUOHDnq+TaQVJtb9CC2Kr2iDs1WrVlFfX8/RRx9NUVER48aNY9q0afz73/8OuxeiIfJaT5kypRUBYVRUgXbdIjuVI444whFxsXjxYj799FP9WSsqKtIJkVifoa6uLupCB/EgVgU1Kr6iXYONGzcC5haN2LBhA4FAIOyaZGdnM3ny5FbXJN53HA8lJSXMnj2bo446il/96let/p6fnx935kxcI5mza9AyeLNjcxTwmuLLScaXW8SXXcWXoij650gl8SVsjieccIIphbQRycr5yhBf9iEmaMwG24O7igNBfNmxOUILgbd27VrXyBYnkwai70hXxVcgENDbexFLEQuC+KqpqfFEVqERYtBupV0Wdsc333wzKWobJ4gVbg/O867E9z9q1Ch69OhBbm4uoVAo6vhCNuwqvsCbOV9Gm6PZelgQX8m4BwXxJcZsiqJIz/mqra3lkUceATQRgdnrkFF8yUViw3e6oaAAUtVQOyxGo8FIVomHJBQK6XbHM844g1tvvbXVfkLuaoQgSWIVSWLAHe/1adOmsX//fpYsWcK8efO49dZb6d27NzfffDMjRoygR48e+iAxFApx8MEH8+STT7JhwwaysrL0vxlnZ2INSDt27KgXqcOGDePpp5+md+/euqLEeF5i8C/+L376fD7988ZbXTKSFFQURVeNmS0qA4EAoVAIRVHw+/1RV3VUVdVSoHui9442QLvooos49thjeeedd/jwww+5/fbbueeee8JWFYwM2j/ppJPo378/Tz75JH369CEUCnHggQe2yniIdT9CSzh5tBUdxTbvvPMOffv2Zfv27ZSXl+tqCauIvLbR7qHIbWLd32YRCoU46aST+Pvf/97qb8ZcOyO6detGbW0tjY2NOrkrZupXrVrF+PHjW+3zww8/MHz48IT5GoK8NDP7KO4jM9ck3nccCyUlJRx55JEcdNBB3HjjjVEJ2X379jF06NCYxxCfR7bdTYbiS7RbP/zwg+P7SAacWB3FAKG6upr6+nrTeUeJYFfxBdrnqKioSOmgURBfVmyOApMmTWLOnDmu53yJZ8Mp8SUI8O+//57y8vKEoddtAU4UX7W1tQSDQcuEaDw4yfcCGDp0KIqiUFlZyZ49e8JUxbLgpO0Ug7V0Jb7WrVtHIBCgqKgoYY1SUFBAp06dqKiooKSkxFa77BasKr5AyxUdMWIEa9eu5dlnn221IrWXECvcHpwrvozB9j6fjwEDBrBu3Tq2bNlievETu7Cr+ALtcy9YsMCTxJdQVJmBaHeSURcIMtN4fl27dmX37t3SiK+vvvqKsrIy+vbty2mnnWZ6v4ziSy7anuJLUaCwMDX/kjgYCgaDjBw5ko0bNzJs2LBW/6IpqBJZHUePHs3WrVt15hu0hr+yslIf+Imcr4cffhhFURg9ejRTpkxhzZo1YfleABMnTmTdunX07t2b/v3707dvX/387DTmkVao0aNH8/XXX6Oqqk5mLVu2jOLiYr2h6N69u154+f1+qqurLQf6jh49mvnz54e9Fvl/CM/3GjNmTKtruW7dOqqrq/XZGLPvvWzZsjD7lzFQPlYh3r9/fy6++GLmzJnDb3/7W5588kn93IwIBoOUlZWxevVq/vCHPzBr1ixGjRplKxtg7NixfPzxx1EHZ6NHjyY3N5etW7cybNgwhg4dSv/+/Rk4cGDUbDMjol17obSKhVGjRrVSM3z99dcx7YVmMHHiRFauXMmgQYNaPW+xyFtBbBkto+PHj+eAAw7gvvvua0UoLVu2jLlz53L22WeHEVrRrkFkKGa8lYtEm2C8JoFAgEWLFjm6JqB1xjNmzGD8+PH86U9/wu/3R70vv//+eyZMmBDzOIL4qq2tlapgkEF8jRgxAp/PR0VFhfRsLDtwQnx16tRJ7wviLcxgBaqq6gMsq4ovaCEYUqX4Wrt2LWvXriUrK4tjjjnG8v6HHHII4H7AfbRJBTvo2bMnI0aMQFXVVguUtEWoquqI+AK5qoNt27axYcMG2/leoE00CULGLbtje1Z8CZvjmDFj4ubDCnhVlWFH8WVcbe7uu+9OirXPLty0Okau6Oj0eFYgQ/HlJaujcdVEs0iF1dE4HpGt+BJ5caNGjTK10ISAV9uWdEXbI77aCYLBIOeffz7Lly/n0ksvZenSpaxbt4633nor5uyMUHIEg0GWLl0a9m/VqlUcddRRjB07lnPOOYclS5awYMECzjvvPKZPnx5mJZsxYwYvvvgi06dPR1EUiouLGTx4MB9++GHY7OU555xDt27dOPPMM/nuu+/Ytm0bn376KVdeeaUpqXBtbS07d+5k586dLFu2jEsuuYS8vDx9YHLJJZewbds2Lr/8ctasWcPnn3/OAw88EBYaPnPmTP75z38yb9481q1bx5///GfLs7YXX3wxGzZs4JprrmHNmjW8/PLLPPfcc622EzlIubm5Ua/lb37zGyZOnJiQtDHi5z//OT6fj1/96lesWrWKd999Vw+kh+hk5lVXXcUHH3zApk2bWLJkCZ988olObgwcOBBFUfjiiy8oLy+nsrKSzp0707VrV/7xj3+wfv16PvnkE6655hpL1wjghhtuYOHChdxyyy2sW7eObdu28dhjj7F3716Ki4u59tprufrqq3n++efZunUra9as4dlnn+X555+Pe9yvvvqKO++8k7Vr1/LII4/wn//8hyuvvDLuPtdddx3PPfccjz/+OOvWrePee+9lzpw5psMko+HSSy9l3759nH322SxYsICNGzfy4YcfcuGFF8Yknbp3787EiRPDCCexiuiqVas444wzWLBgAVu3buU///kPJ510ElOmTOGqq64KU3z95z//4ZlnnmHt2rXcfPPNLFiwgIsvvhjQioP8/Hw9bF8UTEYUFhYye/ZsrrvuOt5//31WrVrFr3/9a2pra6PaEs2ipKSEGTNm0L9/f/72t79RXl4elRzavHkzO3bs4Kijjop5LPHMNjU1SV1NSgbxlZuby5AhQwBv2B2dZHwpiqKrsmTZHauqqvTJBzvElyDwUqX4EouqTJ8+3dakzMEHHwxolmI3V7GTZXWE9mV33L17N9XV1SiKYkmpkZubq9dNMu9NY76XE3WQ2zlfMoivdB2smc33EhCDU6+pMqyG2wtccMEF9OzZk61bt/Lqq6+6cWqOoapqzHB7aBvEl53+yOtWR7NIVrh9IBDQCXqj4ks28SUiQ6yqczOKL7nIEF9pimAwyPDhw/nnP//JunXrmDp1KhMmTOCPf/xjTNuVIElqamqYMGFC2L8TTjgBRVF444036Ny5M9OmTeOoo45iyJAheoi2wJFHHkkwGNRJrmAwyMSJEwkGg2GKr4KCAr744gsGDhzI9ddfz09/+lN+9atfUVdXZ6rYe/LJJ+nduze9e/fmyCOPZM+ePbz77ruMHDkS0BqDd999lwULFnDsscdy++23c/bZZ/OHP/xBP8YNN9zAtGnTOPHEE/nFL37B9OnTEyqMIjFgwABee+013n77bcaNG8fjjz/Obbfd1mo7ofjKy8uLeS1vu+02gsGgaUVLUVERb7/9NqtWrWLChAncdNNNurXV5/NFtVwFg0EuvfRSRo0axXHHHcfIkSN59NFH9Wv25z//mXvuuYdjjz2W3/3ud/h8Pl599VUWL17MgQceyNVXX81dd91l6RqBVoS/8cYbrFu3jgsuuIBp06bx5ptv6vfdrbfeyp/+9Cduv/12jjzySC6//HLmzp2bcCDy29/+lsWLFzNhwgRuvfVW/dzj4dRTT+WBBx7grrvuYsyYMTzxxBM8++yztm0loBW2X331FcFgkGOPPZYDDzyQK6+8ko4dO8adEf6///s/XnrppbDXjjjiCObPn4/f7+eEE05g2LBh3HDDDZx//vl89NFH5OTkhJE/f/7zn3n11VcZO3Yszz//PC+99JKexaWqKg8++CBPPPEEffr04ZRTTol6HnfccQdnnHEG5557LhMnTmT9+vV88MEHjmxOH374oU6WDh8+nOOPP56jjjqqVRv0yiuvcMwxx+iFYzQYCWmZhY4M4gu8FXDvJOML5Od8icFHQUGBbnm2glQrvgTxZcfmCNC5c2fdxrt48WJp5xWJDPFlD0LtNWDAAMvWXjcGX4JUMa5SbQeC+LKSG2oF7VnxtWLFCiBxvpeAV1UZdpW4eXl5+gTj3//+d0sRHclCZWWlPuESL+Nry5YtllXk+/fv11VAxoljcTy34cTq2FaIr2QpvkpLS1FVlezs7DBSyivEl5cXz0hLqGmAyspKFVArKytb/a2urk5dtWqVWldXl4IzSx12796tLly4UF23bp3pfXbt2mV5HzPYu3evunDhQvWHH36Iuc13332nLly4UK2trZX63gLr1q1TFy5cqO7atSvmNmbO0wnWr1+vLly4UN25c2fUvzc1NakLFy5UFy5cqDY1Ndl+n+rqanXhwoXqsmXLbB9j8+bN6sKFC9UdO3bYPkY07Ny5U124cKG6du1aU9utX78+7nYDBw5U77vvPolnmHzU1dWpAwYMUL/++mvT+wQCAf1eAdTXX3897jbBYFDiGdtDWVlZ1Oervr5e7d+/v/rll1/G3b+urk59//331YEDB6qbNm2Sdl733nuvCqhnn322o+Ncd911KqBedtllks7MPrp3764C6ooVK2ztP3PmTBVQX3zxRSnn8+2336qAOmDAAFv7/+QnP1EB9eGHH5ZyPlZQXl6uZmVlqUDC9igezjrrLBVQb7vtNolnF44jjzxSBdRXXnnF8bHWrl2rAmpubq5aX18v4ey8i2effVYF1KOOOsryvgMGDFABdcGCBdLO5+KLL1YB9ZZbbnF0nAceeEAF1NNPP13SmYXjqaeeUgH1pJNOsrzvvHnzVEAdMmSIC2fmPoYNG6YC6ty5c01t//vf/14F1CuuuMLlM7OGo48+WgXUF154wfK+5eXlanFxsQqob7/9tgtn5wyiDSssLIz694aGBlVRFBWIWZfHwoIFC1RA7dmzp/7a888/rwLqrFmzHJ23GYwZM0YF1I8//tjyvt9//70KqB07dpR/YjYxefJkFVDnzJljep/ly5ergNq9e3cXz0xVv/rqKxVQBw8eHPb61VdfrQLq9ddfL+V9LrjgAls1Ql1dnQqogFpWViblXNoa4vFEkcgovtIUwlplxbYnlDdmVoGzcy7xPMvxguVlQBzXzDnEy0JyAqPVMRqMqiAn5yA+q5OgXbeuhdkMGvH+XpxFlI28vDxeeOEFS3lKQu2V6H4W95RMa6BdxHoGt2zZwk033WQqy0YoGL2o+DIG3KcaTjK+wD3Flx2bI5DSVR3ff/99mpqaGDVqVNzFFxIhGTlfMhVfw4YNo0ePHjQ0NLieTZZqCEWUlRUdBdxQHTh9fgW8bHU0hturaaZSqK2t1Vdqtmp1bCuKL9DypWbPng1oinGvIV6wPWiZtuJ7sarSirQ5QvoovsR5VlZW6sdJNbys+BLKvsjgfa8ovvLy8vRz8Vr7ko7IEF9pCjvEl8iqkE0+mSFixGDYLdLJCvnmxjmoqhpmdYwGRVGkXAczJF8iuHUtzK46Jgib9kB8gZYdZMVGJcJkoy1SIaAoiv5MeyF8NtZ9OWLECH7zm9+YOoa4L7xMfKXa6tjY2Ki3NXYyvkA+8eVkRUdIrdXRqc1RQORgLly40PE5xYJM4ktRlHZjd7QTbC/ghtVRNvG1bt06V/pSGVbHurq6lFmY7WL16tWoqkq3bt1MD1K9SnzZzfgSuOqqq8jJyeGrr77yXDsRL9hewC5ZFY34EhbCrVu3ul67Ogm3Lyoq0vtiLwTcB4NBPdjdTsZXfX29a6IJiB5sDy3PjKhvnMLM/RoLmZwvecgQX2kKO6qfjOLLPZVRU1OTftx4ZIUMwskO6RkJQTDIJL6CwaCuekuk+DL7/ps3b+aqq66Scn7pBKHgys7ORlVVTj311KjbiXvNy4ovK/Cy4ktkfO3YsSOlAznj7Kdd4ksUxbJWdZSl+EpFuP0nn3wCwAknnODoOBMmTEBRFLZt2+bayp8yiS+AqVOnAvaIry1btnDggQfaWggl2Vi/fj1gj/jysuJr4MCBZGdn09DQELaCtCyIttPOKqL5+fm6WkU2GeQ26SAy2A466KCoOarR4FXiy4niCzQC8/zzzwe0rC8vIV6wvYDdvKtoxFffvn3x+/00Nja6urpzU1OT/uzZUXxBC+HnhZyvXbt2EQwG8fl89OzZ0/R+bq2qGwmx2JpXFV/g3fYlHZEhvtIUTq2OMqXnZkg4t9VWqT4Ho80xXtC5TOLLa4ovMSjLzs7WlUiJ3r+9KL6sQhBZ8UhUIC0UX1bgZcVXp06d6NWrF5Bau6MYNBcUFNi+1m5ZHdNN8WWciRaLpthFhw4d9GO4FXAvm/gSiq+vvvrKUlscCoU4//zzWblyJS+88IKUc3ELqqq2Wauj3+/XP5MbdkenbacbAfdXXXUVvXv3djU0XwTbm7U5gjcDqAOBgH7f2lV8gbZKtqIo/O9//9OvjRfgpuJLKLuF0hu02kYob9xUUhn7QbvElzHYP9UQKqVevXpZqlmMq+q6SXzFUnwJslgG8aWqqiPiK6P4koc2Q3x5paNJFuyQH8ZtZSqvzJyLW2oz0Ipw8f2bVXzJJlyE9ShWvlfkOTi5DjIyvtywnloZlHnB6tjY2OjZdkMQWYkIRC8qvuzel6qqoigKqqpKHWTKIr7AGzlfMgbNXrM6pkrxVVZWpt93ds/dCLdzvmQTX+PHj6ewsJDy8nJLFt777ruPzz//HNCuYV1dnZTzcQO7du2iuroaRVEYMmSI5f29THyBuzlfTttOY86XLLz22mvs3r3bVdudUHxZIb7EpEhjY6M0hYhTiPNQFMWWZU5g+PDh/OQnPwHgzjvvlHFqUiD6r3httx3iq66ujo0bNwLhii+7x7MKkctVUFCQsAaMBS+t7Ggn30tAtD1u1gbJUHzV1NTo/WRG8ZVapD3xJRoFURC2F9hRfBkzpmQSUKnO+BLHVBQlrtrK+LdUEV8yroMMxZcbVkezwfbG908V8VVWVsby5ctdlas7gVnFlxeJL7uFWm1tLcFgkL1790qd3RO5czKJr1TmfIlBs12bI3gv3D5Vii8xA9u1a1dH7amA2zlfsomvrKwsDjvsMMC83fH777/nxhtvDHtNDBy8CGFzHDBgQML+ORq8nPEF3ia+ZCu+mpqa9IGfmwN6O8RXbm6uTsB4ZXAqBuydOnVyNFEK8Lvf/Q6AV155xRNkCiQOtwd7lr81a9agqipdunRpRVIkw0LoJN9LQJD8a9askXFKjuCE+EpGwH2ijC8ZxJeoNfLz821ZxzOKL3lwXumlGH6/n06dOuk3VUFBgWlPfjpDKEKMuUpmIAiHmpoaaddJnEsoFIp5LoLgaGhosHS+ZiBYdL/frxNQsSAUJbW1tQlJBSsQg2ufz2fq89XX19u+DuIzxrveiSBIiqamJmnfh+iYsrKyEh7T7v0rC6K92L17t6Piwi0Yr0m86yMUa248V1Zh9zsVz+Pu3btZvXo1tbW1nrQ6gjeIL/GctUXFV6qILzszsNEgiK9FixbpSjJZCAQC+jMmi/gCze748ccfM2/evISLUDQ2NnLuuefS2NjIj3/8Y9avX8+aNWvYvn27rfysZMBJsD14X/ElPld7IL5KS0v1WtItxU15ebk+uBwzZoylffv06cPevXspKSnhoIMOcuP0LMFpvpcRBx98MEcddRRz587l3nvv5cEHH3R8TKcwY3U0Wv7MtsnGfK/I7ZOp+LJrcwQYO3YsAMuWLZNxSo4QS1FlBm5MPBgRCAT0uINYxFddXR11dXXk5+fbfh9jrWGnLsgovuQh7YkvaJEYixurPWDnzp0Eg0GysrIszWKWlZXpxIkd1jneuWRnZ8ckk6qrqykrK6Ompka63bG+vp69e/eSnZ3Npk2b4m5bVlZGKBSKe652UFpaSmNjI4qixG2gy8vLqaqqorGxUSfLrGLXrl06sWB3oBgIBNi7dy+KotiaBY9EKBTSG+S8vLyEq6AIZQ/Axo0bk0pWq6rKtm3bwmyOdlVKbkEsAZ+TkxP33BoaGti7dy9+vz+u2jEZ2Llzp6lzjoVOnTrphJJXiS8RcO8FxZcM4mvfvn00NTU5Vjula7i9bOJr/Pjx+P1+du7cSUlJia0Z7lgw2gllE19gTvH15z//maVLl9K1a1eeeuopzj33XNasWeNKsLoseI34amho0BW67UXxJWuwZrzP3CIehNprwIABlomHPn36sHz5cs8MTp2u6BiJ3//+98ydO5ennnqKP/7xj7ZWp5MJM9mSAwYMALTnt6Kigs6dOyc8brRge4FkEF8yFF+C+NqxYwdlZWVSyE+78LLiS2Ty5eTktLqPOnTogN/vJxgMUl5e7oj4crKiI2QUXzLRJogvRVHo3bs3PXr08ETIczLwk5/8hJqaGj744AO9ITaD++67jw8//JA//vGPnHPOOVLO5dRTT6WhoYGPP/44ZsP20UcfcfnllzN+/HheffVVKe8r8MEHH3DllVcyceJEXn755bjbzp49m82bN/Piiy/qs/NOoaoqZ555JtXV1fzvf/9j8ODBMbd9//33eeCBB/jpT3/KX/7yF1vvd9VVV7FmzRqeeuopS1J8I/bt28fJJ58MwMqVKx3L4BcvXszFF19Mjx49+OKLLxJu39DQwIknnghotiAnti2r+Pbbb8OUDb/97W/59a9/nbT3T4SamhqOP/54QLuu8Qjq3bt3c+qpp+L3+1m+fLnj79Eu6urq9HO2831mZ2fj9/tdyXNwQ/G1YcMGGhsbpZLnZiGD+OrSpYuufi0rK7O00lI0OFV8pdrqKIv4KigoYMyYMSxfvpxFixZJJb7ERImsyQqBww47DL/fz5YtW9i2bVurWW+Br7/+mjvuuAOAJ554gl69eukz+OlgdbQTbA/yFQfGe1xGmySIr82bN9PQ0CD13vCa4mvr1q36724TX3ZqK6+pMkS7LIv4mjlzJpMmTWLRokU89NBDtmtYWTBDJhQUFNC9e3f27NnDli1bTBFf0YLtBdJF8dWhQwcGDx7Mpk2bWL58OUceeaSks7MOGRlfbim+BJner1+/VpPHiqLQuXNn9u7dy759+/Tn2w6c1hrivXft2iVlsrI9o01dOb/fn7KBXzLR1NSkz0h07dqVvLw80/v6fD69wLWyXyzU19frM43dunWLecwOHTqwZcsW8vLypLyvEbt27WLLli2MGzcu4bGrq6vZsmULlZWV0s5jz549rFy5EkVRGDZsWNzjZmdns2XLFjZv3mz7/VevXs22bdvo2LGj7WN07dpV77gDgYBj9d+iRYvYsmULY8eONXVOubm5bN++nWAwSCAQkH5PxMMHH3zAli1bKCoqorq6mldeeYXLL788ae+fCJs3b2bLli106NAh4Sxd37599etYWVnpqGN2AlFUZmVl0a1bN9sKPjeKHJnEV58+fSguLmb//v2sX78+6oyw25CR8ZWVlUXnzp3Zt28fe/fudUR8qaqaUXwZMGnSJJYvX87ChQs55ZRTpB3XmKEoUyFbVFTEhAkTWLRoEV999RU/+9nPWm1TXV3NeeedRygU4txzz+WMM84AWqwhGcWXeYjnt6ioSEq92qtXL70v27hxY9TBul14LdzeeJ9t3rxZup0YnBFfYmDvFeJLKL5kqX0UReF3v/sdZ555Jg8//DDXX3+9lH7VLsyE24NGVu3Zs4fNmzczfvz4hMc1q/hy4/6DFsWXE+ILYNy4cWzatIlly5alLfHltuIrkQ2zS5cu7N27N6GLJRGc1ho9evTQ1We7du2SOqnW3pD24fbtEU6WupWd7VJeXg5ohFq8gZiYZRHby4QVObcbWTJiRrlfv34JCRwhXRYzOnYgrqGZmatYyM3N1WeGRSfrBIsXLwa0HAgzUBRFJ9vcXKY4Gj766CMAbrrpJgDmz5/v6tLoVmElD8Hv9+uz6qlUXRizRJwUgqIN8SrxpShKynO+ZGR8gby+oLq6WldaO1V8VVdXJ3XBC7eIL5C/sqPsYHsjEtkdr732WjZs2ED//v156KGH9Ne9Tnypqqr3z14jvmTYHEFrk9yyO3pN8WW8z4R1TTZkKL68YkeSbXUEOO200xg+fDjl5eU8+eST0o5rFfX19fr9mcg+Zsz5SoTGxkadLI9GfAnrZHV1tSvjGZBjdQTv5Hylg+IrltJZVsC901rD7/frsU5eIdbTFRniKw0hGkU7S93KJr5EY9C5c+e4GUOCpNm3b19YtpIMWJFzC6LQDeLLjJXCKfEVCAT0DsAJ8QVyr4VV4gtaMubsZp3ZQVlZmX6u5513HpMnT0ZVVd5+++2knUMiWA0C9YL330zWhhnILnJCoZDUVR0h9TlfsgbOsvoC8d3n5eXZJmWMnyWZRLjbxJfMvi5VxNe7777LE088AcBzzz0XNtnmdavjrl27qK6uxufzxY0giAevE1/gXs6XLOJr//79Up7rSIJVtt1MVVVWrFgBYCucXpbVUVa7ITPcXsDv93P99dcDcM8996RsRWnR74gFzuLBij1x3bp1BINBiouLoxI1+fn5en/hlt1RhtURNMUXpJb4qqqq0p/9dFR8iWcn1cQXeKPWbwvIEF9pCCeNoluKr0QkjCClmpqapBMdVuTcbiq+kkF8GfdzOhskroVTxVd1dTU//PAD4H3i65NPPkFVVcaMGUOfPn049dRTAXjjjTeSdg6JIDpis0WCFwafsokvWUWOIAuMx3YKofgS93yy4TXiy2m+F2gKVJFZkcycLzeIr7Fjx5KdnU1ZWZnUJe/dJL6OOOIIAJYvXx7WH+zdu5df/epXgJYtOXPmzLD9vK74EsqNAQMG2M6+civjy+vEl4xJg+LiYr2fl6H6cpv4Ki0tpby8HJ/Pp09wWIEM4uv555+nc+fOfPLJJ7aPIeCG4gvg3HPPpXfv3uzYsYOXXnpJ6rHNwlhzJFKZWyG+xIRWtBUdBawoyOxAluJLEF8rV66UvqiYWQiSpkOHDrbaETdcAEYkS/El6iwntYbXMgTTFRniKw0hyA87jWKqiC+jOs1pAxIJO1ZHGfY+gWQSX+J6i9VGnECW4mvp0qWEQiH69Omjz/CagegEk0l8CZvj0UcfDaATXx9//HHSg7VjIR0VXzLID5A/yBTHURTF0Yo8RqTa6igj4wvkK76cqAoURXFlUiIR3CC+cnNzdYuJTLujm8RXr169GDZsGKqq8vXXXwOa6mT27Nns3LmTUaNGcdttt7XaT7RR+/btCyOZvQKnNkdIL8WXIPpkoK6uTlceOZk0kGl3FINUUWvJJJahxeY4fPhwW7mjYmAqVjq3gxdeeIHKyko++OADW/sb4YbiC7Q27uqrrwbgzjvvtGRP37BhA48++mjYQgV2YGWVPEF8mblfRL5XvKw8twPuZSm+Bg8eTFFREY2NjaxZs0bCmVmHE5sjyJ8MjYSZjC+Qp/hyshKqF2r9toAM8ZWGcDIb4JbVMRHpJFbHAPk5X1asjl5SfNmRs8vI9xKQRQJ+9913gDW1F5D0jC9VVVsRXwcccAAjRoygsbGR999/PynnkQiiUzNLfIntvGB1dFpgy57dE8eRGQhuVHwlM49KwGsZX7JIz1QE3LtBfIE7OV9uEl8AU6dOBVrsji+99BL//e9/ycrK4sUXX4xKHHfs2FEfmHjR7iiIILsrOkJ6EV8yFV+yJg1kBdzX19frz6uw5somHpzke4HWjvh8PoLBoK12NRgMsnDhQkBOf+6W4gvgN7/5DR07duSHH37grbfeirttKBTi/fff58QTT2T48OFceumlXHvttY7e34rK3IpCK16wvYDbxJcsxZfP50t5zpdT4sttq2O6ZHxBRvElCxniKw0hw+pYVlYmZdBmhYgRDYhs4iudrI7iOwsEAtTV1Vl+L5nElyzFV+QsrFkk2+q4YcMGNm/eTHZ2NtOnTwe0ot5rdke7iq+2ZHWUTXzJXHlqyJAhZGdnU1tbmxKLl9esjrJJz2Qpvurq6vRiOkN8hed8bdu2jcsuuwyAm2++mYkTJ0bdR1EUT1itY8Hpio4QrkyWUTO5QXyJz1daWiptgGicNIiX35oIshRf4v7Kz89nwoQJgPeIr6ysLH2FXDuD09WrV+vfnwziyy3FF2j376WXXgrA7bffHnUit6qqigcffJBRo0Zx/PHH88477+jbrVy50tH721F8lZWVJaw3vUB8yVJ8QeoD7mUpvtyYIG9sbGTXrl2Au8RXKBSSYnXMKL7kwFJv9thjjzF27Fg6dOhAhw4dmDJlCu+9917M7T/77DMURWn1L1XZKG0FTmYDxMA0GAxKIaCsEDHGgHuZSOWqjvv27dPff+jQoQm3Lyoq0otIO3ZH42ICTiFL8bVz504AveAzi2RbHYXa6/DDD9dJN2ixO7777rspC2o1ImN19DbxlZWVpQ80U2F3lDVwFt+VIK7sIl0VX6IQzcnJkUpCABxyyCGARnzJUgUmi/j69ttvOe+886isrOTQQw/l97//fdz9vJzzZWVSKhaMlmIZfZXob2Xec506ddIHVLLsjrIWBRHEl1OVglGZ4VbGkpNgewEnqoxvv/1W/93rii+AK664gry8PBYsWMDnn3+uv/7DDz9w2WWX0bdvX6688krWrl1Lhw4duPLKK/Ux48aNGx2F+Fshvjp27KiTSPHumaamJt0SaIb4km21FZCl+ILUB9xbrWcj4abiq6SkBFVVyc3NjVm/yCC+Kioq9Iw1J1bHjOJLDiwRX/369eOOO+5g0aJFLFq0iJkzZ3LKKackZO7XrFlDaWmp/s/J7FsGzmYDcnJy9MZUht3RSsfqhuJLVdWUruq4YcMGQGuQjGRKLCiK4ijnyw3Fl1PiS8yYiKV2zSLZVsdIm6PAoYceSs+ePamsrAwr3lKB+vp6nYiwE24ve8VUs5Cl+jHmOcj4LG4QX5DagPu2mPEFyVd8Ga0HsmywAqNHjyYvL4+qqiqdfHEKt4mv4cOH0717dxoaGvjss8/Iz8/nhRde0BcdiAWvKr5UVZWi+MrLy9PzNGUMvsT9LUPNYYRsu6OstlOW4ksQXwMGDHCFeAiFQvpYxq7iC+QRX07784aGBp28dEPxBdpk5y9/+UtAU329/fbbHHPMMYwaNYpHHnmE6upq/fft27dz//33M2vWLHw+H/X19fqkqR1YVZkLsjTePbNp0yYaGxvJz8/X77FoSCfFlyC+li9f7vhYdiCeWy8qvsS59evXL2YNIMaVYpxpB6LW6Nixo+1FVsAbk9xtAZaIr5NOOokTTjiBESNGMGLECP72t79RVFTE/Pnz4+7Xo0cPevXqpf9zGsrd3uEk3B7k5nzZUXzJJL5qa2t1lU4qrI52ZpRlEF8yZvBkkYCC+LKq+Eqm1bGpqUlfJSmS+PL5fJx88slA6u2OokPLy8sz/R2LQruurs72oglOIcvqKMiPYDBIQ0OD4/Nym/hKheKrrWd8pYL4ko3s7GzGjx8PyLM7uk18KYqiq74A7r77bp1MiQevKr527txJTU0NPp+PwYMH2z6OoihSVQduWB2hhdzzGvElK+PLqPiyYl0zi02bNlFXV0dubq4p9X4sOCG+jGMpp/25mJT2+XzS7zUjrr32Wnw+Hx9++CEnn3wyH330ET6fj1NOOYW5c+eycuVKLrnkEv0Zys7OZsCAAYCm+rILK4ovMEdWCZvjAQccENfe68b9J6Cqqj4ZLYP4Ouigg1AUhdLSUmnZzmYRCoX45ptv9POwAzcVX2bUaDIUXzJsjtDStlRUVHhyMZl0gW3jfjAY5NVXX6WmpoYpU6bE3XbChAn07t2bWbNm8emnnyY8dkNDA1VVVWH/MmiBUxlsqokvmVZHcazs7GxTiqu2Qnx50epoV/GVDOJr0aJFVFZW0rlz56gh/MLu+Oabb6YksFzAGGxvVoWSn5+vk76pmgmSRX4Yn2EZM3xtjfhSVVV6xtfevXsdKQtkKb6SbXV0k/iClpwvEVbtFG4TXwDHHXec/nP27Nmm9vGq4kv0zQMGDHA0yw5yVQduEV/tRfHVv39/OnXqZMq6ZgUi32vUqFEJVY7xYJf4qq6u1hVnOTk5gLP+3OiEcJLRlghDhgzhF7/4hf5e119/PRs2bOCNN95g1qxZUeuYIUOGAM6IL9HvuEF8xbM5gnnrpB3U1dURCAQAOVbHoqIinchNtt3xu+++o6ysjOLiYg499FBbx0iG4itWvhfIIb5krOgI2n0n+v+M3dE+LLeGK1asoKioiNzcXC6++GJef/31mI1E7969+cc//sFrr73GnDlzGDlyJLNmzeKLL76I+x6333673rB07Ngx7k3ZHuFUBisePvEwOkGqrY7G9zdDFMgiewTsrBolOjM75+C1cHvj6kVezvgSNseZM2dGVZzOnDmToqIiduzYweLFi10/n1iwm4eQ6oB7WeSH3+/XVxDzMvF1wAEHAMknvmpra3ViVhbx1dTU5EhZIIv0TKXV0Q2Ie2Tr1q1SjpcM4utXv/oVH330Ea+//rpp4t2rii8ZNkeBdFB8tXXiSzxH4n6TbTcT2U5iUsMu7BJfIg+wX79+jBw5EnBGfLmd72XEE088wSeffMK2bdv4+9//rtsKY0EG8SXqTrP9jkziy+zx7ECMC3w+n7S6JVU5X6LunjFjBtnZ2baOkWrFl6hpa2pqbLsQZNUaiqJkcr4kwDLxNXLkSJYuXcr8+fOZPXs2559/vt5YRNv217/+NRMnTmTKlCk8+uij/PjHP+buu++O+x433HADlZWV+j+vFVSpRkbx1QKrq9ZkFF8tkEEC7t27l1AohKIolmczkpnxFSvfSyAvL4/jjz8eSK3d0S7xJbZPheKrrq5OH5Q7JT8gPOfLKdwivsTAZO/evY7D4a1AtFs+n88xAZKbm6sXlU76goziKzpkf55kEF9+v5+jjjqKvLw80/t4VfHVnokvL+UjCuKrvLzc1krWApHqDNk5X7LuF7sDU2FzPOyww6Rk+bi5omMk8vLyOPLII023TTKJL7N1p5mMLy8RXx07dpSWPZmqlR0T1d1mINre6upq6Rm2ZhRfxu/BrmhDZq2RyflyDsvEV05ODsOGDWPSpEncfvvtjBs3jgceeMD0/ocddljCVWdyc3P1lSPFvwxaIEvx1RYyvqzOaol7qba2Vl9lwwnSmfiSofgS+V7dunWzbA9IltVx//79es5AvA5Y2B29QHxZDQJNpeJLFNhZWVlS2mpjoeMUbhFfhYWFeuGbzIB7MfAuLi6WUhQ77QuMi4tkFF/hkD1TLdpJM5b+ZEIMGvbt2+ep3BEZKzoKpIPVcejQoSiKQmVlpZTaTlbb2alTJ91q6iTMPBbxJYt4EEo5M7l28SD6YqvElwi2P/TQQ6UMbpOp+LIKp8RXKBSy3O8kul9CoZDel5shvtxaWVRmsL1AKgLua2tr+fLLLwFnxJdof1RVld6/GMPtY8Hn8zkWbcisNTKKL+dwbPxWVdWS/O+7777TZ4AysAevhNurquopq6MZGItNpwMSY4FpJQzVK8SXDMWX3WB7SJ7V8fPPP6epqYkhQ4boBVc0nHDCCWRlZbFq1SppS8JbhVOrYypmgYyKHxlkjMxBplvEF6Qm50v2oFkMGuyq1mpra6mvrwfST/El2i63iS9ZRF4yFF920KFDB/358pLqq70pvvLz8/XQcBl2R1ltp9GeY9fuuH//fr1OEcSXbOJBFvElPuvu3bv1rKZEUFVVOvFlZbXzZMMp8VVeXq5b/q0SX6WlpVHHrFu3bqW2tpacnJy4dWLk8dxSfMnI9xIQxNeqVav0xcDcxrx582hsbAyz7tpBQUGBXlfKrg1Ef5UoTslpzldG8eUtWCK+brzxRubNm8fmzZtZsWIFN910E5999hnnnHMOoFkUzzvvPH37+++/nzfeeIN169axcuVKbrjhBl577TUuu+wyuZ+incErVseamhpdNZUuVsecnBzdxuF0QLJhwwZAa8ysFLFeIb7EjJIT4kvM4NohvpJldTQrt+7UqRMzZswAtJD7VMAYbm8FqbQ6ylrRUUAm8SVIVTeIr1TkfMkeNDvtC0T7m5OT4/gaZxRf8eFV4ktRFM/lfKmqqiu+2gvxBXJzvmROGjjN+RL3VadOnfTvQibxsH//fr2WcXq/dO3alezsbFRVNa1w2759O6Wlpfj9fg4++GCpiq9kWB2tQkwUl5SU2LK/ipqjY8eO+kIAidCtWzc9PzRa7qKwOY4YMcKUe8Et4ssNxdfAgQPp2LEjgUAgaQp1Y93tZELU5/O5MlZoaGjQJ7/cJr5kreoIGcWXDFgivnbt2sW5556rh9R/++23vP/++/qAsrS0NKxBaWxs5Nprr2Xs2LFMnTqVL7/8knfeeYfTTz9d7qdoR1BV1TNWR0HCZGdnmyrGvaD4Ank5X3atFE6IL/F5vWZ1tLqiIyTP6mglZyDVdsd0DLd3i/jycsYXtCi+kml1FM+qGPw5hdO+QKbaT3b+YiJkiC95EO2VV4ivnTt3UlNTg8/nY/DgwY6PJ+u7DAQC+kC/PRJfdgdr0bJ4ZBIPQh3YvXt3x0obn89n+fOKfK+xY8dSUFAgZSLLy1bHzp076/WnnYw2q8H2oBH08VSCVvK9IL0UX4qiJD3nS0a+l4AbAffi2czLy0tIDotnSEz0WYWsVR0ho/iSAUvE19NPP83mzZtpaGhg9+7dzJ07N+ymfu655/jss8/0/19//fWsX7+euro69u3bx7x58zjhhBOknXx7RG1tLcFgEEi94svqioqCrKmoqNBlyk7hhPhyurJjsomvQCCgk0QyrY6NjY26XckqnFgdk0F8bd++ndWrV+Pz+Zg5c2bC7U8++WQAvv76a/2zJQuBQECfEU8nxZfsEN2M1TE2ROHnNcWXDNIzmVZHVVWTGm4vI5TXy8SXICS8YnUURMbAgQNNK0LiQVabZLy3ZZHXRnid+LKr+Ipc0RFaiIeSkhLbq60JyLI5ClhVZRhtjiBncJvMcHurUBTFkd3RarC9QDyySvTjVomvkpISqfZBNxRfkNyA+127dul5YrNmzXJ8PJk1oYAx3yvR+NVLVseM4ss5HGd8ZZBciEbR7/fbLoBFZ7F3715HBblV253YTlVVx6STgJ0cg3RVfBmVcjJmg4yFt91rIaT8dhRfycj4mjt3LgCTJk0ydZ/279+fSZMmoaoqb7/9tmvnFQ07d+5EVVWysrIsd5CiUC4rK3O0cpYdyFZ8pUO4PbQQX1u2bElaqLfXrI4yv/tkWh0rKip0m76MWdhoEJ8nGAzanlgwwsvEl9cUXzJtjiBPcSDu7fz8fLKzsx2fVyS8Snw5zfiKpvjq3r27bl1zet8JojTVxNdhhx0GtPTnu3fvtk2qeFnxBc5yvuz2O/GIL6H4Ev16Ioj7T1VVqe2eG4ovSG7Avai7x48fL4XscUPxZcVd4YT4ampq0sepsjO+ZK9y2V6QIb7SDMZG0a61RBT6gUDAEQFllfjKzc3Vi3ZZdkc7OQbpTnx17NgRv99vad9o8Pl8eodi9z6QofhyM+PLjtw6VXZH0RH36dMHn89a09ypUyd9EJDsmSAvZ3y5SXx169aNrl27oqoqa9askX78aPAa8SVTVZBMxZeYge3QoYOe+SgbxntOxmfyMvHlVcWXjBUdQT7x5dZK5YK4Wb9+ve4MsAsvKb6iEV+KokizmwmiUBZRaoX4CgQCLFq0CGhRfHXt2lVfCdNuf+5lxRc4I76cKr4i7ZWqqlq2OiqKoi8mIdPu6JbiSxBfyVB8ybQ5gruKr0T5XtDyDNkhvkR9rCiKlGdRtKUNDQ1SY4PaEzLEV5pBRqOYl5enNyRO7I52ZpRkB9y3p4wvmcH2Ak5zvmSE29fU1LgycxEKhfSZJzvE19y5c211tKFQyNbnsRtsD1qnKvZL9uCzvVodIfl2R9kZX4Ks9JLiq7a2VldjuQW3bY4QHsrbXogvryi+ZK7oCPLaJLeJLzEQb2hosJ1HI+B14gvk5Syl0uq4YsUK6uvr6dixo/7+xpUw7dod24PiyyrxFSvjq6SkhKqqKvx+v6U2w42cLzEJLZv4OvDAA/H5fOzevdv0ogt2oKqqdOLLDcWX0eqYCE4UX6LW6NatmxTBgjGTLGN3tIcM8ZVmEGSJUxmsjJwvO0SM2FYWU23H6igj1L2mpkYv4pwQX1YIEjeIL6d5Z07C7UVBHQwGXVliecWKFezevZvCwkKmTJlier/Ro0czbNgwGhoa+OCDDyy957Zt25gwYQLjxo2znDtiN9heIFWhl+013B6SH3DvVsaX+A6tQibpaSTz3FZ9JYP4ArkFu5eJr1SR7rFgd1IqFtJF8ZWVlaXXF14kvpyG2wtiTyCWgscKVFVNKfElbI6TJ08OU3o77c/TRfElVke3Ajvh9hCbqBJqr2HDhulKOyfHcwJZY7xIFBQU6KSem6qv1atXU1JSQm5uLj/60Y+kHFNm/IWA6KvMKL6cEF8yV3QUcEqKt3dkiK80gyz/d6qIL5krO6qqmjKro+isu3btapmIEt+d1VB5NxVfdoivYDCoD5idKL7AHbujmHWaPn26pYBjRVFs2R03bdrEtGnTWL58OStWrOB///ufldN1THylKuC+vWZ8QQvxtXTpUleOHwmvWR1lfve5ubn6oCNDfIUjFArp2X1eJL7E4KG8vNz1VXoTQVVVz2d8uUV8QUstJIv4MvbTdiGIr71791qe5DJmKEUOUuOt0mcWZWVlOtkwdOhQ28cxwg7xJfK9BJwQX3V1dXptmQ6KL6sKeadWx+3bt4epiq0G20ceLx0UX5CcgHtRd0+bNk2P33AKmZOhAlasjjIUXzKzREXbYHci4ZVXXmHq1Kk8+eST0s4pnZAhvtIMsvzfMogv0QjYUXzJsDrW1tbqRVSyrY5OZpSLior0mT0rdkevWR337NlDKBTC5/PZatSzsrJ0QsqNwZITufUpp5wCwP/+9z8CgUDC7detW8f06dPZvHmzLmd+/vnnLb2nLMVXqqyOXsv4UlVV6uAtGqZPnw5o98nChQtdeQ8j3CK+6urqbD2DslUFyQq4F8WoHcLeCmR9HuMEiReJrw4dOuifNdWqr9LSUmpqavD5fAwePFjKMdsz8SVj0qBr1656mL/V1ZKNC7ZE9o0yiAeh9urfv7+0Z8sK8TV//nygJd9LwAnxJb77rKwsV1YPlYEBAwbg8/moq6uzfE/YnXDp3bs32dnZBIPBsOtqNdheIJ0UX5CcgHvZNkdI73B7NybZnCq+Pv74Y7788ktbasu2gAzxlWbwouLLCukkU/ElOvfs7GxLA1un9j5wFp6rKIpOOFkhvuwQjYng5FqIYsWJd92Y8yUT9fX1fPHFF4C9DnjKlCl0796diooK/TixsGrVKqZPn862bdsYNWqU3vG/++67lgo60RGLgtcqUm119FrGV2Njoz6r65bia+LEiZx77rmoqsoll1ziOFA6EWRnfBUVFekqKzt9gWy1X7IC7tNN8WVcNVTWLLpseCXnS0xKDRw40JLSNx7SJeMLWtphu/ZlAZnEl8/n0+MQrOZ8ifupR48erWxoMogH2Ss6QsvAdN++fXFV/eXl5frCKJMnTw77m5P+3JjvZXcRLLeRk5OjtxlWc77sKr58Pl/UQHqrwfYCMhSHkXBT8eV2wH1jYyOfffYZIJf4kh1u39DQoNcAyVJ8yaw1nCq+xJhm2rRp0s4pnZAhvtIMXlJ8pTrjy2hztNK5p1rxBfYC7r2m+HISbC8gOjTZxNdXX31FfX09vXv3tlzMAPj9fk4++WQgvt1x+fLlzJgxg9LSUg466CA+++wzjjzySCZPnkwwGOTll182/Z5Owu2N+yVTcVFXV6cPyr2W8WUsktxSfAHcdddddOjQgUWLFrkuHZed8aUoiqO+IN0VX+lGfOXm5koJyHUDXsn5kh1sD+ml+BLtsBPFV2Njo650ljVpYDfgPp4lSRBf27Zts70ghuwVHUGr78RqsfE+r1AJDx06tBWJI0Px5dV8LwG7Afd2w+0hOllql/gy3n+hUMjyuUSDLHFDNAji64cffrCcQWsG33zzDTU1NXTv3l23VcqAbMWXeKby8vJMCTfENlVVVaYcIEZ4TfG1c+dO1q1bh6IoHH744dLOKZ2QIb7SDF4Kt0+11dHuqjXpTnzJzGyQofiyE2wvIAgJ2RlfQnV11FFH2Z7xNOZ8RcugWLx4MUceeSR79uzh4IMP5tNPP9U7t/PPPx8wb3cMhUKOia9UKL6MlgpZgzlZGV9i/9zcXN1m4wZ69uzJX//6VwBuvPFGR21qIrgxcHbSF2QUX/Eh6/OIiQE3CVyn8Jriyw3iq7q62tEKxOlidXRj0sBuwH084stoXbOrfpAdbA/hqzLGO69YNkeQp/jyMuwQX7W1tY4m2yKJrz179lBWVoaiKIwcOdLSsfr06UNWVhaBQMD2iqVGBINBvY1wQ/HVr18/OnfuTFNTk072yYSx7jYu1OAUshVfxjbFzPjAON62KtpwI9zeieJr3rx5gEaCukGupgMyxFeaQdZsgHgI24LVsb0RX15RfAniy4niyy2ro4ycgVmzZlFYWMj27dtZsmRJ2N+++eYbZs2axb59+zjssMOYO3du2Ozqz372M3Jycli2bJkpWfmePXsIBAIoiqIPEKxCEGalpaWWLHdNTU0ce+yx/PjHP7Y8a2m0OcqyVMgqctwOtjdi9uzZjB8/nvLycn73u9+59j5uDJzF4MFqX2BU+2UUX9EhW/HlxXwvAa8pvmSt6AgtbYiqqmG2U6tIN+JL5qSBIILsKr4iV3QETZktCDG7djM3rI5gjrgSwfaJiC+rZGtbVnyJfionJ8eW5T9yJVBBAA0ePNhy++r3+/V2T4bd0dhPuEF8KYriqt3RjXwvkK/4Em2K2Ulm42q5VkUbXlN8CeJr6tSp0s4n3ZAhvlKAN998k0MPPZQrrrjC8r5txeooU/FltXN3QvaAZgMQDY7d8FyvEF9OFF9etTru3buX7777DtBmnuwiPz+f4447DtCeWYEvvviCY445hsrKSqZOncqHH37Yioju0qULJ510EmBO9SUGi7169bI90OjZsyd+v59gMGgpW+z111/nww8/5N1332XlypWW3lO24gfSk/jKysri0UcfBeDZZ5/l66+/duV9ZGd8QUtfYDUTyA21n4xJCTPIEF/y4RXFlxtWx4KCAl3B4OS7TDfiS2bb6YbVEZzlfIVCIVfuF0gccK+qaswVHY37NzQ0WK6X27Liy1hz2Jlsi8zlshtsLyAz4F6MB/Ly8lrl2cmCsCDKDrgvLy9n0aJFgHziS7biS9TbZvK9BOzmfLm5quOuXbssW7xFvleG+MogqWhqamLBggV89dVXlvf1Srh9KBTyTMZXshVf27ZtQ1VV8vLybA+cxPdnhXByU/HVlqyOH3/8MaqqcuCBB9pWTwkY7Y4Ac+fO5bjjjqO6uppZs2bx3nvvxSQhhN3xpZdeSpgL4DTYHrTZR/F5rcwE3X///frviYL8IyF7RUcIz/hyYitKJvEF2oIIv/rVrwC45JJLbGfOxEIwGNQJEC9YHd1Q+yXD6hgIBPS+I0N8yYMXFF+qqrpidVQURUr2oOhnM8SXeWzduhVITHwJBY8VlJSUUFtbi9/vl7YCqEAi4mvDhg2UlZWRk5Ojq3CMyM3N1dtmq8oOu26IZMOJ4ssukRBJVNnN94o8np37LxJu5nsJuKX4+uSTTwiFQhxwwAG24zpiIdWKL3BOfMmsNbp3747f7ycUClma5K6oqNAJzwzxlUFSccghhwAa4x5vxZdocEPxZWdwWVVVpe9nhYhpC1ZH0WEOHDjQ9oDPK4qvtmh1lCm3PuGEE/D7/axYsYKHH36YE088kbq6Ok444QTefvvtuPknxx13HN27d2f37t188MEHcd/Hab6XgCDOzA4+FyxYEKZOskp8yV7REVoGW6FQyHL7aESyiS+A22+/nc6dO7Ns2TJdASYLxqLPDcWXVeLLDdIzGVZHcc/6fD7XB4btifjyguKrtLSU2tpafD6fruyQBRnfpZv5PQIyVnV0k/iSmfEFzlbWE2qvIUOGSM+BTER8CbXXhAkTYqp7rPbnAnbdEMmGIL527Nhhuq93EmwPLUTV1q1bCYVC0ogvmYovN9sHI/HlZGIxEm7ZHCF9FV91dXV6fyGT+DJOcltpT7/66itUVWX48OGOBAvpjgzxlQL079+f7t2709TUZFluKjvcvr6+3lZjIkiY/Px8ffUaM/CC1VEQX9XV1ZaykASMxJddeIX4kmF1lKH4kkV8qaoqtQPu0qUL06dPB+Dyyy+noaGBU089lTlz5pCfnx933+zsbM455xwgsd1RdMSyiC+zM8QPPPAA0CLz/+KLLywVQ25YHY1kopNCJxXEV/fu3bn99tsB+OMf/6g/IzIgBs25ublSbRAyFF+ykAzFl9F6IDOANxraE/El2q6Kigrpi5WYhSAyBg0aRE5OjtRjyxh8pcuqjl5RfAWDQb0vc8Pq6MaKjgJmia9oNkcBuwH36WJ17Nq1q95GmlVMiX7Kbs3Rr18/fD4fDQ0N7Nq1i9WrVwPeIL5EHe4m8TVmzBj8fj9lZWW2F4SIBjeJL7cUX24TX+Jezc7Olv6d2sn5EhPb06ZNk3ou6YYM8ZUCKIrCpEmTAHRPtFnIksIWFhbqA3c7dkc7KzpCS+NRXV1teVnYWOdgV/EF9hrSVBBfjY2NOjnUlhRfsjO+1q1bx9atW8nJyZHWuAu7I8BPf/pT/v3vf5smHoTd8a233orbYcoivsT+ZjrDHTt28O9//xuAp59+mpycHHbu3KlbhczADdWP3+/XB/jpRnwBXHTRRRxyyCFUVVVx3XXXSTuuG/le0P4UX8nK9wJ5nycdiK8OHTrofWuq7I5u2BwFZCq+kmF13Ldvn21Fhxttpxio7d692/SEo8iw8fl8MWMLZBBfsoPtwTzxFS3YXsAu8ZUu4faKoli2Ozq1OmZnZ+vXddmyZToR66WMLzetjnl5efrqlbLsjhs3bmTjxo1kZWUxY8YMKcc0QjbxZafedkJ89ejRQ1ochICdlR0zwfYaMsRXimCH+AoEAnoBLIM9dpLzZWdFRwhv0K2onaLBrtUxNzdXnw22MyBJBfFltIbKnDmwq/hqamrSFR8yrI6yFAJi1unwww+Xtgz72WefzaRJk7jssst46aWXLFkixo8fz9ixY2lsbORf//pXzO1kK77MDDwfffRRmpqamDZtGlOmTNELcCt2RzdUPyBHXZEq4svv9/Poo4+iKAovvvgin3/+uZTjiqJP9qDZi4qvtkZ8tQfFF7S0X6myO7qxoqNAuhFfTU1Ntp8jN9pOobAMhUL6M5gI4j7q27cvWVlZUbcxEg9WVyV2a0VHiE981dfX6wvwuEF8pYviC6znfMlQmYt75r333gO0dsvuhJLx/nNqHUyG4gvkB9yLuvuwww6TPjEHLe1QIBCgsbHR0bHq6+v1WseO4suKktbNWsOq4qu2tpaFCxcCGcVXhvhKEewQX0ZyQkbhJIP4sqo+8vv9+rk7tTs6yTFwonRKJfHVsWNH/H6/7feNhLgO+/fvt1Q0imw4n8/nqACRbXV0Q27drVs3Fi5cyEMPPRSz+I4HofqKZ3eUEW4P5hVftbW1PP744wBcddVVQEtnaIf4kqn6AaQESYt7KtnEF2jt+29+8xsALr30UsfqVnBv0Cy+Oy8ovpJpdcwQX/IhBhKpUny5tUIfOCfjg8Ggvq+bxFd+fr6u5rdrd3SD+PL7/fokmVm7oxlLktG6ZpZQE3BT8SUUavv372/1/C9dupRAIED37t3jhuq3dcUXWCe+nCq+oKV2f/fddwH7NkeAAQMGAFob7cReDMlRfIH8gHs3bY4Q3g457UvFs5Sfn28rn9rKuNWNFR0FrCq+vv32W5qamujbt6/0/Mt0Q4b4ShEE8bVy5UrTg37RKBYVFdkagEfCCfFl1+oI8gLuncxqOVEWiCyCVBBfsmfwxHVQVdVSQS9sjmJ1EbuQaXVsamri008/BdzrgO3gnHPOwe/38+2337JmzZpWf1dVNenh9i+++CL79u1j8ODBnHzyyYC3iC9BGKSj4kvgb3/7G926dWPlypU8+OCDjo/nFvEl+oGqqipLs6luKL7amtVRFpGXLsRXqhVfwuroRcWXsS1zk/gC5ys7utV2Wg1kTrSiI0BOTo6ufrBiN2tqamLDhg2Ae9ZYcc9EEn1Gm2M8C5Qd4ktV1bRSfA0dOhSwrviSQXyJ9sIJ8ZWbm6vf107tjslSfMkkvoLBIJ988gngXt2dnZ2tx4s4dYcYyXQr9kOjhdwsvKT4MuZ7ybZdphsyxFeK0KdPH/r06UMoFGLp0qWm9pE9GyBm36zOJoEzIkZGwL3Tzt0u8RUMBvWGMxXEl8x8L9D8/sK6Z8XuKEK7ndgcQa7VccGCBVRVVdG5c2cmTpzo+Hiy0LNnT44//ngguuqroqJCH9g6VXwZC+VYsntVVbn//vsBuOKKK3TicsqUKfj9fjZv3mx64OrWzHI6Wx0FunTpwp133gnALbfcYqudNcKtjK/OnTvr94CVleAyiq/EyCi+kgdVVT2d8SWe35ycHKmLU0SD05Ud3Wo7xWBNpuIL7OUsbd68maamJvLy8hxPOMVCLLvj/Pnzgfg2R7BHfNXU1OgTGG1Z8eWk34lUvDghvkBezpesDOdEEMTXmjVrqKurc3SsxYsXU15eTseOHTnkkENknF5UyOpLRZti9Zl3ovhyo9awqvjK5Hu1IEN8pRBW7Y6yG8UDDzwQsMf6OyFiZCi+nHbudrOtSktLaWpqIisrSy9q7MArxJeiKLZsn0Lx5XRJXJlWRyG3njVrllQ7qAwIu+MLL7zQKthXDBK7du2acKXIRBCdYW1tbcx7+6OPPmL16tUUFxdz4YUX6q8XFxfrhKHoJBPBbatjOhNfoH3vhx9+ONXV1VxzzTWOjuVWxpfP59PbUCvq34ziKzHE56mtrbW1grBAuhBfqVR8lZSUUFtbi9/vd8XK4dR+nYx8LwGnKzu6rfhyi/gyuzIghNti3VrdNRbxZSbYHlr687KyMurr6029pxiY5+TkeL69gHDiy0xGlkyro4BXiC8xHnBb8dW7d2+6detGKBRi5cqVjo4l6u6ZM2dKcSLFgoyaEFrqbSv5XuA94suK4isQCPDNN98AmXwvyBBfKYVV4kt2ozhhwgQAlixZYnlfJ1ZHsY8T4stp525X8SU6tn79+jlq5AXx1dDQYKqgcYv4AnskoGzFlwzi66uvvgI04strOOmkk+jcuTM7duzQZeECsoLtQcstEB10LNWFUHtdeOGFrQZhVuyOdXV1+oDcixlfXiC+fD4fjzzyCD6fj3//+9/MnTvX9rHcHDjbsb1nFF+JYVTnOSnY04X4SqXiS6i9Bg4cqC9eIxNO7dfJJL68bnWUTXwJotMK8SDyvdxQBwpEI752797Npk2bUBSFyZMnx92/c+fO5OXltTpGPBhV2OlgaRo4cCCKolBTU5Ow/2lqatJrYRnh9gJ2V3SMPF66KL4URdFVX04D7t3O9xJIR8WXcVVH2RCkuNExEgtLliyhtraWLl26OL7X2wIyxFcKIYgvsdJCIshuFAXxtXHjRssrLKba6mi0Odrp3J0SX05sjqAVlGKW0cy1d5P4SqXiS2bGl+hkvBjcmJuby89+9jOgtd1RVrC9QLyA+x9++IH33nsPRVG4/PLLW/3dCvElCuysrCzpg7m2kPElMH78eC677DJAC7pvaGiwdRyvEV9uqP3E915fX+949aZYSCbxlZubq0+QOCnYRWEra6VatyAICqeKr+XLl3PbbbdZev7dDLYHeVbHDPFlnfgSAeKxYId4cDPYXiAa8SXUXgcccEDCSWxFUSzbHdMp3wu0yWvRbojMtVjYt2+frgpzojQ23k89e/Z0fK3STfEFLSs7Osn5qq6u5uuvvwbcJ768oviqqKgwrd52M9y+Q4cO+kRYIlJc1PNTp051Td2aTshcgRRCEF9r1qwxRTrIbhS7dOmikwRmc8YEUm11FAWd3Q4r1cSXz+fTv8dUE192FF+C+PJSxpfXCz5hd5wzZ07YfScr2F4gXsC9CFk/+eST9VBZI4444ggAVq9enXCFLKPVTfbMcluxOgr85S9/oVevXqxdu5Z7773X1jHcyvgC68RXQ0ODfn3dsDqCe6qvZBJfiqJImakWEwNeV3yJNqyystLR57388su56aab+MUvfmF6tWE3870gQ3zJgJVw+8bGRl1Z7kbGlyBKU0V8JbI5CphdqVkgnVZ0FDCb8yVqji5dujhyXOTn5+u1q1ObI9iz2kZDshRfICfg/osvviAQCDBo0KCo9aRMyFZ8WSW+jGMvs0IRN2sNIymeqD3N5HuFI0N8pRDdu3fXG0wzdkM3lroVmT5W7Y4yrI4yFF92O3c7KieQR3yBtZwvJ9c7EexcCy9aHd0kB2Vg8uTJjBw5krq6Ov773//qr8u0OkLsQNx9+/bparOrrroq6r5du3bVs/++/PLLuO/jVr4XtD3iq2PHjtx9990A3HHHHaYH80a4lfEFLd+hWeJLDK78fr/U2ens7Gw9584N4qu6ulpXTyWD+AI5uWXpYnUsLi7W7we7dsempiZdBf/mm29yyy23mNpPEBlurOgIztukdCK+RH+cynB7sUBLbm5uQsWEkXgwkxMFybE6RuuLBfF12GGHWTqG2efJ6xOA0WCW+JIRbC8g7hmZxFc6Kb6MxJfZZyYSH374IaCpvdy21coivuzW29nZ2fo5mGlXVVV1fZLNTM5XKBTSa/lMvpeGDPGVYljJ+XJjNsBuzpcMq6OMjK9kK77EjE6yiS+vKr68YnUMBAJ6h+hV4ktRFF31ZbQ7yia+xHEiC+WnnnqK2tpaxo0bx/Tp02Pub9bu6EbGk4DMjC+v2MPOOusssrOzqaqqskUKJMPqaHYVOKPiVrZ03s2Ae1GI5ufnJ+2+kFGwpwvxBbHbH7NYtWoVdXV1+gIlt956a9hEQSxkrI4t8Lria+fOnQnJf2MWT6JBtajHqqurTdWV9fX1bN26FUiu4isUCrFgwQLAvOLLqtWxLSu+ZATbC4wZMwZAygrg4v4rLy931M6LGjwZxNeoUaPIysqioqLCtjU9WfleIGcytK6uTq9xrCq+wFrO1/79+/VYCzesjmBuZceVK1dSXl5OYWGhPt5v78gQXymGFeLLjdkA0eh/9913lvZr71ZHGTlSXrE6ivNIpdWxpqbGlgpGwHgNkyETt4tzzz0XRVH44osv2LRpE5AcxVcgEOChhx4CNLVXvIGEWeLLjVX9BNqa4gu0LDRR4ItBuhV4KePLTbWfmwH3xhnYZAU/tzfiy2nOl1B7TZs2jauvvhrQbOLxLDmqqmasjgaI59IskR0Jt9rOnj17oigKTU1NCUk5K5ak/Px8XVVhRnWzYcMGVFWlY8eOrg1KIZz4UlWVH374gaqqKgoKCnRldSK09YwvsG51lNHv3HHHHbz88sv84he/cHys4uJivTa3q/qqr6/XiZJk1LC5ubl60LmdgPsdO3awatUqFEVh5syZsk+vFWT0o6LWLigosHWNRa1rhvgStUZhYaFrk2xmFF+ijj/88MNdXXUznZAhvlKMQw45BDAXcO+G4ksQXz/88INp1U1TU5NexKWr1dGOyklV1ZRZHZ0o7BLBqtUxEAjoBYhTxZexQ6irq7N9HHF9OnTo4OnGvV+/fvqqky+88AKQnHD7119/ne3bt9OjRw89ZD8WRA7AsmXL4j4fbpIfbSnc3ggxKHdCfHkh48tNVUEyFF/JsjmCHCIvnYgvp4ovUQtNmjSJO++8k6OPPpra2lpOOeWUmEROSUmJrhJza3ETpyrUjOJLswuJ/iJRLo3VLB4rdjOjzdFNAlwo3Orr66moqNBtjpMmTTJdp9hVfLVF4kum4qtHjx6cffbZ0laAdWp3FLWWMRfSbTgJuBcrVB988MFJURfKmAw1Btvbee6tKL7cXNFRwIziK5Pv1RoZ4ivFEMTTxo0bEz5Mbii+evXqRa9evQiFQqZZfyNRkyrFVyqsjnv37tXJGTsy2Uikq9VRNOh+v99xh2ccyDmxO3o938sIYXd84YUX2L9/v37d3Qy3v//++wGYPXu2vjx6LPTp04dhw4YRCoX0FXuiIRlWR7tFTjAY1J9VLxFfIn/IDvHlZsaXFxVfbYX4yii+rEEQX4cccghZWVm8+uqrDB06lC1btnDmmWcSCARa7SOep0GDBpGdnW3zzOPDKRmfIb40mF3Z0eyKjgJWAsaTsaIjQF5enl6jlpSUWA62B/uKr3S0Ou7YsYP6+vqY24l+x02Vnl0Iwt0u8SXGAR06dEjayntOAu6TaXMEOf2o0T5tB1aILzdXdBRIpPhSVVVXfGXyvVqQIb5SjM6dO+uDocWLF8fd1o1we7AecC9IhuLiYlvqGhkZX6mwOooOrXfv3uTm5tp6XyPE92iGcEqG1dHstRDB9t27d3fcQft8Pn0w54T4Sid5/2mnnUZRUREbN27kX//6F6A9S7IGRKJTLysro76+nm+//ZZvvvmGnJwcLr74YlPHMGN39LLV0XgveYn4EoovYcuyAi9ZHd1UfCXL6pgstDfiy4niq76+Xp+AE2r4Ll268NZbb1FUVMRnn32m2x+NEM+TW8H2EP492gmDTgXxVVtbG5dIiIZgMKjfb260nWYD7q0qvqwQD8lY0VHAaHecP38+YI/4KikpMRUHkU61kEC3bt0oKioKc1VEg8xwe9mQpfhKRr6XgF3iS1VVXfGVLOJLtuLLDuwQX6lUfG3cuJHS0lKys7OZPHmya+eRbsgQXx6A2Zwvt5a6tZrz5XSFQbFffX29bXtbKlZ1lGlzBPOKr8bGRr0Q9YLiS1awvYCwOzrp0NJJ8VVYWMiZZ54JaDkTIE/tBdp9JVbG27FjBw888AAAZ599tunvzArx5cVwe3Ev+Xy+hAq3ZMKu1VFV1aQQX2VlZQSDwYTbJ8PmmlF8aVBVNa2ILyeKr+XLl9PU1ES3bt3C+tnRo0fz0ksvoSgKjzzyCE8++WTYfm4H20PL9xgKhWzVLckkvjp27KgvDmBV9SXuNUit4kuEz7ttdXQbgvhat24dK1asAMyv6Aja9VIUJSxiIh7SMdxeURRTdkeZVkfZkEV8JTOjVhBf69atszTxvGLFCnbt2kVBQQGHH364W6cXBpmKr7ZCfBkVX9EmY0T9PnnyZH1MkEGG+PIEBPGVKOfLraVu7Sq+nKitRFFmV/WVCqtjqogvcY0URXFlNshquL2sYHsBY8C9XaQT8QUtdscNGzYAcokvRVH0maAFCxbwn//8B4Arr7zS9DEE8bVw4cKwgZARblodndqKjFadZIWYm4EYaG3YsMEUwSTQ0NCgW7zcyP8QgyRVVU0VdRnFl3k4LdgDgYB+r6QD8SXaMjvEl9HmGPncnnzyydx6660AXHrppfoS7ZAc4st47e20S8kkvhRF0Wsjq8SX+Gx+v1+Ksj0SVq2ObhJfyVR8vf3224RCIfr27WspzzM7O1tvr8zYHdNR8QXmcr68bHV0Sny5Nb6Lh549e9KzZ09UVWXlypWm9xM2x2nTprnSRkSDTMVXMq2OySC+Ghoaoo6lM/le0ZEhvjwAIemPp/gKhUJ64SR7RkAscfr999/rq4rEg1OSQVEU/TPYDbiXZXXcv3+/6dUERXZEsokvcY06duzoivffKgkorI6yiC/RobUXqyNoHdHgwYP1/8sKthcQHfuf/vQnmpqamD59uqWljAcNGkTfvn0JBAJ6LkkkvGx19GKwPWiDuJycHBobGy0RA0bSxI3PlJ2drbdHZlQFGcWXeTglvozEczoRX1VVVZa/Q2OwfTTceOONes7XGWecoauCkmF19Pl8jpSoySS+wP7Kjm5PGgjiK14gc21trd6nyya+qqqq9Mm7ZCq+Pv74Y8CazVHAbM6XceIinRRfYI74ag9Wx2SvSm4n4P6DDz4A4JhjjnHlnKLBS4ovM5MJyQi3z83N1Z/zaG1DJt8rOiyNoh977DHGjh1Lhw4d6NChA1OmTOG9996Lu8/nn3/OwQcfTF5eHkOGDOHxxx93dMJtERMmTEBRFLZt26Z3yJGorq7WCRrZMwIDBw6kc+fOBAIBU6y/U6ujcV87ii8Znbux+DTbkIoOTdaqUVYVX26pmewqvjJWR/vw+Xycd955+v9lKr6gpVAWA8KrrrrK0v6KoiS0OybD6lhdXW0rT8erxJff79cLfCt2RzFoLioq0tWysmEl5yuj+DIPp0SeIL78fr9rwe0yUVxcrPcpVnO+jIqvaFAUhWeffZZx48axe/duTjvtNGpqavR2zm0iw8ngK9nEl92Ae7fbTjMZX2KAWlRUZLreFcRDWVlZ3FpCtLs9evRIirpGfF6h2HWT+Nq/fz9NTU1A+kwCCiQivlRVTQvFV2lpqSkBQSRSofgCazlfO3bs4LTTTtMVX+lKfLUVxRfEzvkqKSlhw4YNKIqSNDtqusAS8dWvXz/uuOMOFi1axKJFi5g5cyannHJKTLJk06ZNnHDCCUydOpXvvvuOG2+8kSuuuILXXntNysm3FRQXF3PAAQcAsQPuBSmRk5MjPbNGURRLOV9OrY7Gfe0QXzU1NXoRYfcccnNz9UGE2QFJqq2ObhNfqVJ8tUerI+Aq8WU83uDBgznppJMsHyMe8VVXV6cPyN0kvuzm6XiV+AJ7AffJGDRbIb7SXfElq+0yA1mKr4KCAk/ZduNBzKhbIb7279/P6tWrgdjEF2j9xZtvvkm3bt1YsmQJp556KnV1dfj9fmmTUrHgRPElarj2TnyZsToaV3Q0e8937NhRr6niqW6SaXOEFuJLwEq+l4DozxMRX+K7zs/PT7tMn0TEV3V1tU4oeVHx1bVrV12RK5SoVpAqxZcZ4isUCvHYY48xevRo3njjDbKysrjtttsYM2ZMsk7TsQvAjoo0EqJN9cqqjhB7ZUdhcxw/fnzSyVSvwxLxddJJJ3HCCScwYsQIRowYwd/+9jeKior0lUoi8fjjjzNgwADuv/9+Ro0axUUXXcSFF17I3XffLeXk2xIS5XwZV3R0o/i1kvMlg2QQ+9qxOorOPScnx7b1Q1EUyxa/VBNfbs3gietQX19PY2Njwu3dUny1J6sjaIXe8ccfD8DBBx8s9dhG6+QVV1xhSyUkiK9vvvmm1X0hnsGsrCxXBnLingB7hU46EF92FF9u5HsJeE3xJZv4CoVCSbEfREIW8WV8JrwOOzlfS5YsQVVV+vXrl7BvGThwIP/973/JysrSVxcbNGiQ64o4u9mDxsUpkjUIcUp8uXW/GYmvWGpeu5YkM3azZK7oCOHEl9/vt9XXi/48EZGcjnWQgJH4inZfiLY7Pz/fk22hoiiO7I6pVnwtX7486nVftWoVU6dO5ZJLLqGqqopDDz2UJUuWcMMNNyT1PJ32o+LZKSwstH2N00nxlcn3ig3bgUHBYJBXX32VmpoapkyZEnWbb775ppUU8thjj2XRokW6YicaGhoa9HwIOzkR6YhEOV9uN4oi/8cM8SXD6uhE8WW0OTohAa0MsKqqqvTvoK0pvozEhZlrITvcXkbGVzoqvgD+9a9/sWLFipiZNnYhBgzFxcVceOGFto4xatQounXrRl1dXat2wZjv5QYR7/P5HFlgxb3UVogvUex5QfEVCAT02Wk3Zt7dsjru27dPjwtIpmLA6edJpxUdBewovkTtE0/tZcT06dN58MEH9f8nI6/J7uCrpqZGH1S2d8WXIDUbGhpi1j5WV3QUEIo/ryq+DjzwQFukjVmrYzqu6CgwaNAgFEWhuro6ai6dl22OAk6IL9GnJpv4OuCAA8jJyaGqqirsvBsaGrj55psZP348X3/9NUVFRTz00EN89dVXHHTQQUk9R2hpj2pray0tDCQg+qL+/fvbrlmN49Z42dDJnGSLpfgSTo0M8dUalomvFStWUFRURG5uLhdffDGvv/46o0ePjrrtzp07Ww2Oe/bsSVNTU9zAzdtvv52OHTvq/+zKEtMJYuC7aNGiqKy72zJYofhatmxZwkZFhgLJScaXrFktKxY/0SF06dJFWkEovsv6+nrq6+tjbuc2qeP3+/VizEzOl1tWx/aU8SVQXFzMgQceKP24xx13HOeccw7/+Mc/bA+0FEXRO81Iu6ObVjcBJ9J2Lyu+RAC3HcWXF4gv0f4aFymRCbesjmIGtkuXLknNynI6Uy1I3HQivuwovhLle0XD7NmzufjiiwF7FjKrsPtdinvZ7/cnzYLmVeIrLy9P76djBdw7VXyJhYiiQRBfySBKQSP6xEDb7j1qlvhKZ8VXbm6u3m5Eszt6OdheQIbiK9lWx+zsbH0ML+yO8+bNY/z48fzlL38hEAhw0kknsWrVKi677DLXMkYTwah2tzNJ7jTfC1rGF6qqxh0rJXOSLZria9++fXz//fdAhviKBsvE18iRI1m6dCnz589n9uzZnH/++axatSrm9pHMqiB14jGuN9xwA5WVlfo/O8tipxvGjRuH3+9n586dUYsBtxVfw4cPp6ioiLq6OtasWRN3W69YHZ127lYUX7JXdAStIRfPQbxGNBmkjtmA+0AgoH9nGaujd5GXl8eLL77Iz372M0fHiZXzJZ7BZBBfdggDLxNfYsC1ceNGPYg4EZJBfInvMhHxJUjPLl26uFIEu6X4SkWwPcjN+EoX2FF8JVrRMRYeffRRFi1alBTrjV0y3vj8JiunTcaqjm4hUcC9W1ZHVVWTbnXMzs7W2xw7wfbQPhRfED/nK6P4cg9iZccvvviC3/zmN0ybNo0ffviBnj178u9//5s333wz5QKUvLw8fVV7O5OhRsWXXeTm5urjlXhjV1FDde7cmZycHNvvZwbRFF9fffUVqqoyYsSIpOaZpgssE185OTkMGzaMSZMmcfvttzNu3DgeeOCBqNv26tVLV4cI7N69m6ysrLgNc25urr5ypPjX1lFQUKAHBUazO7qt+PL5fIwfPx5IbHf0ktXRCawQX7LzvUC75qKTi2d3TAbxZfZaiMGj3++XRjK1Z6uj1yGIry+//DJMCWq0OrqFtqr46t+/P7m5uQQCAdOTOsnM+Eo0UHZ7cOW24iuVxJedFUrTkfiyqvgqKyvTB7tWiS9FUTj44INdH2CAc8VXMmtZryq+IHHAvVvE1969e6moqEBRFIYOHWrp2E5w7LHH0rlzZ4499lhb+wviq6KiQm8PoiHdJwDjEV/poPgyY7WNhVQpvqAl5+vee+/lH//4BwAXXXQRq1ev5swzz/TEoiqKojiaRLLbpkTCTM5XMmuNaIovke8l6vcMwmE740tAVdWYS7dOmTJFX/ZU4MMPP2TSpElpsSx3shEv4D4ZjaLZnC+ZVkc7ii9ZnbsoQs3Y+0RHJnvVKDM5XzKIxkQwq/gy2hzF7ItTOLU61tfX6yv/ZYgvuRg3bhzFxcVUVlayYsUK/fVkWB3tBkkb9/Ei8eXz+fRBl1m7o5cyvtz+7t0Kt0818dXU1GRrmft0JL6sKr7EZN+wYcM83YZniC85iEd8qaoatqqjFSQiHoTNsX///kld9fC5555j165drVZ4NIsOHTrodVI81VdbUXxt2LCh1d9Ev5RRfMmHED2ApoT87LPPePLJJz3XFjuZDJVhdQRrxFcy7lXRpuzatUt3EGTyveLD0sj1xhtvZN68eWzevJkVK1Zw00038dlnn3HOOecAmkXxvPPO07e/+OKL2bJlC9dccw2rV6/mmWee4emnn+baa6+V+ynaCOIF3CdjxQ+zKzvKtDraUXylwurohuILzBFfybQ6JroWsoPtwbnVUVwfn8/XLtShyYTf7+eII44Awu2OybQ6tjXiC6wH3Hsp48tttZ/4jIFAwBZRFAupIr6M96Cdmep0JL7E4MLs4kRWg+1TBRlWx2QhHYivaLEelZWV+jlYHaSK+qy0tDRqbmqybY4CiqI4muxXFMWU3bEtK77Syeq4fft2ywHsqVR8TZs2jf/7v//j1ltvZdmyZUyfPj3p52AGThRfMqyO0PJsxWtXk1lr9OjRA7/fTygUYteuXdTU1LB48WIgo/iKBUvE165duzj33HMZOXIks2bN4ttvv+X999/n6KOPBrTORqzGAjB48GDeffddPvvsM8aPH8+tt97Kgw8+yBlnnCH3U7QRxAu4d9vqCC3E13fffRdzxYqGhga9EM9YHZ3DK8SXWfWb7GB7kEd8derUSZoKLYMWRMv5ylgdncFqwH2yia94ljy3SU/jdyZT9ZUq4svv9+uklZ3Pk47EV1FRkd63mVF92Qm2TwXSUfFVUVFhaRCe6owvMYbo2rWr5XveuE80m22yV3SUCTPEl6xJ4VQh3a2OvXv3Jjs7m6amppgLN0RDKBTS24hUKL6ysrJ44okn+MMf/kBeXl7S398sZFgdnSq+RLvqFaujz+fTJxJ27NjB/PnzaWpqol+/ftLHq20FWVY2fvrpp+P+/bnnnmv12vTp0xMqiDLQcNBBB7WoTz4AAQAASURBVJGdnU1ZWRlbtmwJs9UlQ/E1atQocnNzqaqqYtOmTVEzEATJoCiKo3PxgtXRzqqObZX4sqr4khVsD84zvjL5Xu7CSHypqoqiKEld1bGthduDfcVXMjK+AoEAVVVVMdt3t0lPscpsTU0N+/fvlzbDnyriC7Tvrba2tt0ovkCbWa+oqGDbtm0xV/4WsBtsn2ykE/El6iNVVSkvLzfdVqfa6ugki0dRFAYOHMjq1avZsmVLq5Ubk72io0xYUXylu9Vx+/btNDQ0kJubq/8tHRRfPp+P/v37s3HjRrZs2WL6Hq6urtYnm1Kh+EoX2J0Mraio0McJVu3TkfBaxhdobcP27dspKSlh6dKlgFa3eyGbzYvIyCM8hNzcXH11jcicr2QovrKzsznooIOA2HZHWeoao+LLauCv7IyvRGRPXV2dTvikkvhycxbPrOLLTauj3YyvdJf3ex2TJk0iLy+PPXv26AOHZFgdZWR8iXvLaxADr/Xr15vaPhkZX/n5+fr1imd3TOZ33xYUX+BspjpdiS8xs55I8VVSUkJJSQk+n09XnXsV6UR8ZWdn6+S1lZUd05n4gvg5X21d8ZXutVD37t0pLCxEVdVW3186KL7AXs6XqP9zcnI8rbhKNey2vz/88AOgKU2dtsFmiC9xryar1jCu7JjJ90qMDPHlMcTK+UqW/ztRzpesoHWxfzAYtDywTXbGl5DeFxYWSi8oEq3q2NDQkJTgdjvh9rIgy+qYUXy5g9zcXA477DCgxe6YsTo6gyC+Nm7cqAeSxkOyBs5iUBGP+EqG2k98TjtEUSykkvhy8nnSlfgSxEWilR3FJN/o0aM9S1QLpFPGF9jL+Uo28RU58emU+BLEw+bNm8NeD4VC+kRDOhNf8YjkdA+3VxQlpt0xHcLtIfb9Fw+pDLZPJ9htfwXxNWrUKMfn4FXFF2j33Pz584FMvlc8ZIgvj8GY82VEMqyOEJ7zFQ2y1Ef5+fn68uNW7Y7JzvgyrugoWzoqiMxYhJPRWupm0Wz2WmSsju0TkTlfybQ6tkXiq2/fvuTl5dHU1GRqZjhZA2cxqIinEEnG4Cqj+GpBuhJfZhVf6ZLvBeml+ALvE1/CzmyE3RUdBWIpbnbs2EFdXR1ZWVnSV+dOBsTzFEvxFQqFkuIOcBvRiK9AIKDXyOlCfNlRfGVsjvHhVPF1wAEHOD4Hr63qCC2Kr7fffpu6ujq6du0qheRrq8gQXx6DIL4WL14cFjCfDKsjwIQJEwBN8RXNgiiLZFAUxVbAvaqq0q2OiVRObuV7QWKrY7KC272g+MpYHb0LI/FVV1enD8YzGV/24PP59AxFMzlfycj4AnMrOyZT8SWL+GpoaNDbtgzxlRyYVXyly4qOkCG+ZKGwsFC/FpF2R1mKr0jiQdgchwwZQlaWpXhjTyCR1bGyslIfM6RzLRSN+BJ9js/n8/wEpx3iK6P4Mgeniq9kE1/JVnytWbMG0GyOmXyv2MgQXx7D6NGjycvLo7Kykg0bNuivJ0vxddBBB+H3+9mzZ0/UDlaW1dF4DCuKr+rqagKBAJA8q6MXiC+3O/tUhttnrI7ex2GHHUZWVhZbt27VbdBZWVmuDuRkZHx5lfgCawH3ycj4AnPEVzIUX7KtjuLzZGVlpWRWvT0SX0KhEo/4UlU1bYLtIWN1lIlYOV8iWkJ2xpdoZ9PR5ggtg9vS0tKoq3SKOrqwsDAsFD7dEI/46tq1q+dX7hbjhE2bNpneJ6P4Mod0UHw1NjbqY5JkZ3wJZPK94sPbLUg7RHZ2NuPHjwdaLAD19fU0NDQA7jeM+fn5+gpM0XK+ZEqpBVFhRfElGpvc3FzHA4F0IL5kEo3xYEb91tDQoH9Xbii+GhoaLC27LpAhvtxHYWGhPjCdM2cOoBWhbs4q2R1kqqqaVsRXooD7UCjkGeKrqalJf97SKdzeOAObiplQGcSX1/OvIiGIi3hWx02bNrFv3z6ys7P1hX28DOP3aGVRngzx1RrRiK9QKKTfL04VX9u3bw/LT0znFR1Bq7l8Ph/BYFBvz4xI93wvgWjEV7oE2wMceOCBZGVlsW7dupiRMZHIKL7MwU5NGAgEdBGJTOIrVptqVCcmS3kpSHGBTL5XfGSILw8iMuBeNIqKorhudYH4OV8ySQY7Vkejrc3pAEZ0Mvv37w+zlUYio/jSIIqtrKwsqedjLLDtqL4yVsfkQMwivf7664D7Rahd4qu+vl5/ntOB+Eqk+KqpqdEH2akmvoxttZttkmzFVyrzvcAZ8SXaxHRVfO3fvz/mhIqY3Bs3blxaqFTE99jU1KRPRppBqogv0UabJb6SOWkQjfjas2cPjY2NKIrSajBnFr169SInJ4dgMBjmWkjnFR1Bq7uE0j6eGyPd6yAj8SX6vXQJtgetjznzzDMBuP/++03tk1F8mYOdfnTDhg00NTVRWFhou00xwqj4ijZuNN6ryVInGhVfRUVFungmg+jIEF8eRGTAvWgUO3TokJQHyZjzFYlUWx1lregILUWoqqpxCZf2QHyZUXwJm6OYeZSF3Nxc/Xh2bG0ZxVdyIGaRhITf7ZlluxlfxnvIyyoZs8SXGDT7/X7XlzpPRHyJ2czOnTu7mpPjpuIrFXDyedLV6lhYWKi3ybFUX+kUbA/h7YmVdinViq94i1UYkcxJAzFYKykp0V8TtthevXqRnZ1t67g+n09XixntjuludYT4OV9tRfElrKr79+/XP5O4f9OB+AK46qqrAHjllVf0XNx4yCi+zMEO8WW0OcpQe4uxp1GJb0Qqao0OHTrofdPhhx+elhmGyUSG+PIgBPG1ZMkSgsFg0oLtBYTiy22roxPFl4zOPS8vT28gYg1IAoGAXrS3ZeLLqPiKZeEwEl8yoSiKo5yvDPGVHBxxxBFhhYPbii+7GV9i+/z8fPx+v/TzkoVhw4YBGpEocgujwWhzdNumJ77TWMRXsgZXshVfou1KNfHVnjK+IHHOVzoF24NGPovvwUq7lGriy6ziy/iZ3L7foim+nAbbC0TmfAUCAd0611aJr7ai+MrLy9M/p/jO0snqCDB58mQOP/xwAoEAjz76aMLtM4ovc7DjApCZ7wVaXZmfnw9EF20ke0VH0MZQYiIhk++VGBniy4MYOXIkhYWF1NTU8MMPPyQt2F5AyCS3b9/eagAkk2RwkvElo3NXFCWh0mnHjh2EQiFycnKkBroLiI6urq4uqnUiWctTi+sQCoVikk9i5sqN6yA6tIzV0bvo3LlzWA6PV62O6ZDvBZriIT8/n2AwyObNm2Nul8xBsyjWYilEkrGiI7RdxVd7I77i5XwFg0EWL14MpA/xBda/S1VV0474KigocH3SIBrxJYLtBwwY4OjYYpJStKubN2+mqamJ/Pz8VkHQ6YT2oPiC1jlf6ab4ghbV12OPPUZ9fX3cbTOKL3Ow04+uXr0akEd8QfyA+1TVGkcddRT5+fmcfvrpSX3fdESG+PIg/H6/rrpatGhR0hVfxcXF+qxYZM5XW7I6QuKAezFjOGDAAFdspkYVRzTyLVlqJmOhG4sEdEvxBS0WEjtB5hnFV/JgDM1MJvFlJUhakKdeJ758Pp+u+ooXcJ8K4ssriq+2Qnw5UbClM/EVT/G1Zs0aqqurKSgokDoocRtWB18NDQ26ojNdiK9ktJ1uKr4E8SXqN2FzHD58uOdXBYyH9qD4gtbEV7opvgBOO+00BgwYwN69e3n55ZfjbpvsMV66wonia9SoUdLOw4vE18MPP8yePXv0xekyiI307QHaOIwB98lWfEHsnK+2ZHUE88SXGzZH0Aa/4hyi2R2TReooipIw4F4ovtwkvqwqvmpra/VBRYb4ch9G4itZGV+qqlJXV2d6v3RRfIG5nK9UEF81NTVRr3myFF+ZcPsWpDPxFU/xJfK9Jk6cmFaZJFYHX8aJpGS3SUbiy8zkQSqIr2gZX7KJr3QPthdor4qvdAq3F8jKyuLyyy8HtJD7eM9fKsZ46Qg7alvZVkeIT3yJezXZtYbP5/N0pq2XkCG+PApjwH0q/N/Rcr5kq2vsKL6E6kjWrFYissdt4gvi53wlU82UyPYprr0bVke7xJe4d7KzszONfhJgzA9wm/wwDvStEAbpRHwJxVc84kt89mSs6NuhQwc9VDqa6itZg6uM1VFDMBjULfDpSHzFU3ylW7C9gNXvUtzDxcXFSVcbiTY6EAiYIuqS2XYKy2FVVZVO7rqV8SWILzHRkK4QxFc0IrktKb6GDh0KpLfVEeCiiy6isLCQFStW8Mknn8TcLmN1NAerLoCdO3dSVVUVpq6XAS8qvjIwjwzx5VEI4mvp0qV6o58K4stodaytraWxsRGQQ8RYVXxt376dOXPmANry5zKQasUXxCe+ZFpLEyERCeim1dFunpORGHQ7+DsD7bsXknExY+8WfD6frfsinYgvrym+FEWJa3fMKL7swS7xZVTdpSPxZUbx1V6Ir1QMagsKCvSVYM2s7JhMm3hxcbF+Twu7oxuKr1Ao1CZWdIT2Z3XcsGEDkJ5WR9Bq+1/+8pcA3HfffTG3y4Tbm4Noe4PBYMLcNGixOQ4ZMoTc3Fxp5yGesWgW8lTXGhkkRob48iiGDh1Kx44dqa+v5+uvvwZSY3Vcv369PhshSIasrCwphZHVcPsbb7yRuro6pk6dynHHHef4/cH7xJeXFF9etDpm8r2Sj6eeeoq//vWvHHnkka6/V4b4Sv6KcPGIr3RUfKmqmvJi1C7xJZQwgE5gpBMEgbFt27awGfrGxkaWLVsGtB/iK9n5XgJWcr6S2XYqihKW89XU1KTbHp0SX3379sXn89HY2MiuXbvanNVx//79re6/tmh13LZtGw0NDWmr+AK44oorUBSFd955R78PI5FRfJmD0dVhpiZ0w+YI5hRf6XivthdkiC+Pwufz6aqv+fPnA8mdDejatau+ss7SpUsB+eoaQVZUVFQQDAbjbrto0SL++c9/AnDvvfdKU/ckIr7EqkBCOu8GvEJ8iU43Ha2ObWGWM11w+OGHc9NNNyUll6e9EF+bN2/W1bSRSPbAWcyqe0HxVVVVZWlhg2ioqqrSr22qilFBltTU1CTs64wQxFd+fn5ahnILq2N1dXVYH/v999/T0NBAp06ddFtTusBqm5QhvmLDSHyVlJQQCoXIzs52XGNkZ2frJNGaNWv01SLT3epYXFys30eRqq+2VAv16NGDgoICVFVl+fLlNDU1Aemn+ALtnjvxxBMBeOCBB1r9vbGxUVf2ZhRf8eH3+3WVqJmJB7eIL9GmZqyO6Yn0q6TaEQTxJRr9ZM8GROZ8ybbdGY8Ti2wBbcb+6quvBuDcc8/Vr4sMxFM5hUIhvWBKheKrvr5el/MmU/EVjQSsr6/Xz89Nq2NG8ZWBEeK+aKsZX71796agoIBQKKST7JFIZsYXtJBD0axRyV7V0aylIR5EIVpUVJQyu6Dxu7NC4qZzsD1o5y0G4sacL2FznDRpUtpZ1DOKL3kQOV8lJSX6/SHUWk4hJis//vhjQKuz0pE4iUQ0u2MwGNTrs7ag+FIURVd9ffvtt4B2T6aj6hXgqquuAuC5555r5XAxjj1S1UakE6y0v8lWfNXW1upjmAzx5V1kiC8PI5LgSfZsQGTOl8wVHQFycnJ0pU88u+OcOXP48ssvyc/P57bbbpPy3gLxyJ5du3bR2NiIz+fTiw03EIv4EtdEUZSkdIjxFF9i8Jidne0KySTuAycZXxm0PYgip60qvhRFSRhw7yWrY7IUX0ZLg1O7oxdmYPPy8vD7/YA1EjfdiS9oUX0Zc77SNd8LMsSXTBgVX7LyvQTEZOVHH30EaDbHdCNZoyEa8VVRUaErY9tKLSSIrwULFgDpbR078sgjGTt2LLW1tTz55JNhfxN1f3Fxsd5HZBAbVhS3ySa+RM2Um5ubtInKDKwjQ3x5GKkmvkTOl1B8uUEyJFrZsaGhgeuvvx6A6667Ti+iZSEe8SXyvfr27auvdOYGEhFfnTt3TorNJV64vTHY3o3iMWN1zCAa2rrVERLnfHmF+AoGg3qb5LaqwOfz2c7FioQgvtxQqpqFoii2Po8gvtJ5xVpjzpdAOhNf6WZ1FCR1eyW+xL2W7jZHgWjEl/hujavypjsiFV/prNZTFEVXfT300EMEAgH9b5l8L2sw24/W1NTojp1kEV/GSba2QLK3VWSILw9j4MCBYQOMVFkdV69eTW1trSsrDCZa2fGhhx5i48aN9O7dm+uuu07a+wrEI3uSEWxvPIdIpVWy1UzxbJ9uBttDxuqYQXQ4Ib7ShSxIF+KroqKCUCgEJMdOIyvg3guKL7C3UmVbUnwJYqO2tpaVK1cC6Ul8paviy8yqjm2R+BJtVroH2wtEI77a4gSgIL5EIHw6K74Azj77bHr06BG2Oj1kVnS0CrM14Zo1awDtvpFdr5ghvjLwLjLEl4ehKEpYYZjshrF379707NmTUCjE8uXLpVsdIb7ia8+ePdx6660A3Hbbba4UY2YUX24TX2YUX8mAGcWXG8H2YN/q6AYZm4F30NYzvqCF+Fq/fn3Uv6cq4yuS+Eq2qsAOURQNXilG7Si+xERAOhNfgsgQVselS5cSDAbp2bOnqxECbiFdia/2pviKXJCoLRNfbWlFRwFBfAmks+ILNLv77NmzAbj//vv11zOKL2sw2/66ZXOEcOLLuPhOZkXH9ECG+PI4jHbHZDeMiqKE5Xy5QcTEU3zdcsstVFVVMWHCBM477zxp72lEPOJLhE2nivhKNqkTT/FltDq6AbtWRzfI2Ay8g7ae8QXpo/hKVr6XQFtTfDmxOqYz8RWp+DLaHNPRDtIeiK9kqWWN4fbCliRWE3eKyLqtLVsd27LiS6AtkAmzZ88mJyeH+fPnM3/+fCCj+LIKs4qvZBBfgUAg7Dy8UmtkEB8Z4svjSCXxBeE5X24QMeJYkcTXqlWreOKJJwC49957Xcu4MqP4ipw5lA2vKb7iWR3dVnxlrI4ZGNEeMr5EuP2WLVtobGxs9fdkD5wFsRVL8ZUsVUG8ttkKvFKMtlfiK1Lxlc75XpB+GV/poPjat28fGzZsAOQpviIJtLZMfLVFxVdk3d0WiK+ePXvy85//HGhRfWUUX9bgBcVXQUEBOTk5QLhbySu1RgbxkSG+PI7DDjuMnJwcevfuTW5ubtLfXyi+lixZklSr47XXXkswGOTUU09lxowZ0t4vEvFUTu3N6phohUvwXsZXxurYttEeiK9evXpRVFREKBRi48aNrf6eKsVXRUVFWAhvshVfGatj2yC+jIovVVXTnvhqD4qvZLWdnTt31utaUYPJIr7y8vL0eqVXr14pu/6yIYivnTt30tTUBLRNxVd+fr6uCIT0tzoKXHnllQD897//Zdu2bRniyyK8oPhSFEVvV41jVzFZmOpaI4P4yBBfHkfPnj2ZN28ec+fOTcn7C+JrxYoVOvnhttXxgw8+4L333iM7O5s777xT2ntFg5HsMXq1VVVtd8SXGcWX21ZHqxlfGatj20Z7IL4URdFVX5F2x0AgQH19PZC8jK8uXbroFjTjYFn8nrE62kN7J75qamrYsmWLHladIb6SAy+v6qgoSpiKPD8/X2pfLlRDbSXfC7R2zO/3EwqF9LqsLSq+INzu2BYUXwDjx49nxowZBINBHn744YzV0SLMtL/BYFDvZ9wgviB6wL1Xao0M4iNDfKUBJk+ezOjRo1Py3oMGDaJTp04EAgGWL18OuGN1FI1HU1MTv/3tbwG47LLLXJenC7JHVdUwtVF5ebleBMrKnIgF0eHV1taGWZ3aY7i9FcVXKBTSi4aM4qttoj2E20PsgHvj504W8eX3+/UBlNHuKBRfybY6tjXFlxUiry0QXwUFBfog4c033wS0uiJdFRzpanWsrq6moaEh7rapaDuF3RE0tZfM3DcxadlWbI6gtc/imgm7Y1tUfEHbJL4Arr76agD+8Y9/UFJSAmQUX2ZhpibcsmULDQ0N5ObmuiZcyBBf6YsM8ZVBXCiKoud8iWWh3bA6CpLn6aefZuXKlXTp0oU//vGP0t4nFvLz8/H7/UD4gESovXr06EF+fr6r52AsiI1qq2SrmcR51NbWhlmcwJtWx6qqKv2ezBBfbRPtIdweYgfcizYpPz8/KSspCkQLuE9HxVdTU5N+3qkuRtur4gta7Guvv/46EJ5dmm4Q32NjY2PUTL5IpJr46tixo56Rmkj1lYq202hnk2VzFJg+fToAM2fOlHrcVEOoKAXx1R4UX+lKlEfDj3/8Y4YOHUpFRQVvvPEGkFF8mYWZmlDYHEeMGKGP72QjHvHVlkjatogM8ZVBQgi7o4BbVseqqiqd7LrllluSQmYoihI12ypZNkfQZvDEORjtjqnK+ILwwVl9fb1OyCXD6mi0nMaDuD75+fnk5eW5cl4ZpBZW1RWBQEBXNaQT8RXL6piqQXM04itVii8nxFdZWRmqqoZlcqQK7Zn4EgP1efPmAelrc4TwdsXMd5lq4svn8+l1lheJL6PiS7a6/pJLLqGsrEwPFG8riAy4zyi+0gt+v1/P+hI5bRnFlzmY6UfdzPcSiCS+VFXNKL7SBBniK4OEcJP4Mlodb7/9dvbs2cPIkSO5+OKLpb1HIkQbYG3evBlIDvEF0XO+kk18ZWdn6+o2o/JMqL1ycnJcm5USxFcwGDQ1iw6ZFR3bA6wSX0bFYDoRX7EUX6K4S5bNUSAe8ZVO4faiEO3WrZtrM79mYefztBXiSyh5hEI3nYmvrKwsvZ9M9F02NjbqGX2pDFc3E3CfqkmDSKujbLQ1MgjaH/GVlZXV5oihCy64IKxNyCi+zMFMTSiIr1GjRrl2HpHEV2Vlpe6UaUskbVtEhvjKICGMxFdeXp5U659oPHbt2sV9990HwN13351UW0+0lR2F4itySWW3EI34SsWKhdEC7o3B9jLzN4wQxBeYtzu21WIvgxZYzfgS905WVpa+3HQ6QBBfW7du1QfKkDq1iCC3olkdk6WckmF19NIMbEbxpUFRFA4++OAUno1zmCXkU5HRFw1miK9UTRq4TXy1RUQSX23V6jhu3Dj69+/P0Ucf7VrtmSoUFxfz61//Wv9/WyP23IKZfnT16tVAchVfolYqLi52PR4nA2fIEF8ZJMTw4cP1wls2CSOOJ2YbZ82axY9//GOp75EIqbY6gjcUXxD9WrgdbA+a2kwQFWaJr4ziq+3DasaX0aqTToVyjx49KC4uRlVVNm3apL+eaqujUHkZf09HxVeG+EotjITGyJEjU6p+kgGz36V4fgsKCsjKynL9vGLBzMqOou009sXJgJsZX20VRuIrEAjo91lbmwQsKipi48aNvPPOO6k+FVdw2WWX6fl7bSnDzE1YUXwlg/gSbaqXao0M4iNDfGWQEH6/n/HjxwPySQbjLIeiKNx7771JH7B6kfiqq6vTbQepVny5HWwvYMz5MoMM8dX2YVz0QNik4iEdg+1Ba/ui5XylmvgSs5ihUEif2cwovuzBCfFlVMSmI4yKr3QOthewSnylmugzo/hKVduZUXxZh5H4EnUQtM1aKCsrK60msaxg0KBBPP300/z5z39uUyuPuolEbe/evXv1SboRI0a4dh6iTRV1USbYPn1gifi6/fbbOeSQQyguLqZHjx6ceuqprFmzJu4+n332GYqitPonGNkM0gPC7ih7Rsnv9+ukz69+9SvGjh0r9fhmIMgeLxFfopjx+XxJtUhEuxZGq6ObEIO7jNUxAwExCFNVlbq6uoTbpyvxBdFzvryS8VVZWUkwGASSH26fUXy1LcVXOud7CZi1OnqN+DIqOCORqrZTkDiKomSIL5MwEl+CzOzUqVPKcwwzsI4LLriAP/3pT6k+jbRBorZXcBIDBgxwdcIo0uropVojg/iwRHx9/vnnXHrppcyfP5+PPvqIpqYmjjnmGFMD1TVr1lBaWqr/y7Db6YUjjjgCcCfz6qyzzmLMmDHceuut0o9tBpGKr5qaGr2YSDXx1alTJ10KnQxEyztLhtURwtU9ZpBRfLV9FBQU6LO9ZpSAbY348oriS7SHRUVF5ObmJuUcMoqvlrYw3Ykvo+KrLRBfZr9L0Y96hfjyouKrW7du/PWvf+Wuu+5KaQ5aOkEQXzU1Nbo1vq3le2WQQTSINqK+vl5fEdOIZNgcIUN8pTMshQ68//77Yf9/9tln6dGjB4sXL2batGlx9+3Ro0dm1Yo0xplnnkl2djZTp06VfuzHH39c+jGtIJL4Emqvjh07Ji1wMhbxlWxSJ5riK2N1zCBVUBSFoqIi9u/fz/79+xPegxniSw4iia9k53tBuOJLVVVbdhcvFaNGIs/s52kriq/8/HzOOusstm3blvbB9pCxOsrGTTfdlPT3TGcUFBTQqVMnKioqWL58OZBRvmfQPmBsn/bv39+q/k8F8aWqql4reaHWyCA+HElJxGyWmQZ3woQJ9O7dm1mzZvHpp5/G3bahoYGqqqqwfxmkFn6/nzPOOKNNPtSRxNfmzZuB5K3oCLGJr2QXM9EUX8Lq6LbiK2N1zCAazNqKjNukM/G1fv16/bVUE19lZWWEQqGUrBomPnMoFNIJIKsQpL0X+i1BljQ1Nen5jYnQVogvgFdffZWvvvoqrVZbjQWrxFeqV2zzOvGVgXUI1deKFSuAjOIrg/aB3NxcsrOzgeg1YbKJr4aGBurq6jw1yZZBfNgmvlRV5ZprruFHP/oRBx54YMztevfuzT/+8Q9ee+015syZw8iRI5k1axZffPFFzH1uv/12XW3TsWPHjO8/A1cRSfYkO98LvKf4SmW4fcbq2E4RCsKuz2DzK9rPkJYplVTiK8Y5JAMi3H7btm3U19cDqcv4EoOoYDBIeXl5ShRfBQUFus3b7uSXl4rRyJlqM2hLxFdbQrplfFlZ1dHTxFcK22evQRBfGcVXBu0N8SYeBPE1atQoV8+hqKhIX6l337598muNTFvnGmyvr3zZZZexfPlyvvzyy7jbjRw5kpEjR+r/nzJlCtu2bePuu++OaY+84YYbuOaaa/T/V1VVZcivDKwjFIQ986CuFPJ7Q/ep4Gsd/hnL6pgK4ksQTqkidaKtcJmscPtMxlc7xrY5sPhKqN3e8lpBPzj4geQRX3HOgf6nWz+eRXTv3p0OHTpQVVXFhg0bGDNmTMoGzrm5ufq57N27NyWKL0VRKC4uprKykv3794et/mYWXiK+srKyKCgooLa2lv379ydc/UlV1ejEl8l+LQP3kLE6pgBut89p9lyJ3Dwx0E/YNqfZ58sgg1goKipi3759rWrChoYGNm7cCLiv+FIUhS5durB79+4w4kvKqo4prkXbOmwRX5dffjlvvfUWX3zxRVhoqVkcdthhvPjiizH/npubm7QA3QzaKCw0HJG5VqkgvsQ5CMWXsPGlWvFVV1enF/fJsjqazfhKmtUxUzC6i21zYN5PADX89dodMO8nnHDQAXz3nTmVjLh3wlbzMfP9JTgHpv7X9YJDURSGDx/O4sWLWbduXUqJL9AKuKqqKvbs2ZMSxRegE192FF81NTU6ie4F4gu0zyOIr0RoaGhAVbX7USe+MgWxJ5CuxNe+ffsIBoNRV//zNPHldvuchs+VUHyJgO+4dVAafr4MMoiFWO3vunXrCIVCdOzY0fWJekAnvsrKyuRNsnmgFm3rsGR1VFWVyy67jDlz5vDJJ58wePBgW2/63Xff2Zq9zSADUxANh7GTh5aGY9ucsJe9pPjyitVRXAthcxQKEDfhSavjtjnw1iD4+Ej4+ufaz7cGtbqHMrCJUFAryEUnvwbQeU/ttSt/tAmfYlPxZeb7M55DENgKLAdCLefA4quSIjWPzPlKNfEFWsB9KhRfEF2BahYibDY3N9czq8VZWdnRmGuWn59vuV8DMnYJl5BuVkdBiqiqqtcYkZBKfMm87yL7iDBIaJ/tPFcegCC+BGK2zWn6+TLIIBZitb/GfC87i+FYhXjmjJODjoivyLZuO7BT/DG5tWhbhiXF16WXXsrLL7/Mm2++SXFxsW6B6tixo1aYodkUd+zYwQsvvADA/fffz6BBgxgzZgyNjY28+OKLvPbaa7z22muSP0oGGWCiSFK0hqPvKbrqwzLx5YICyCvEV2TemdHm6HZHYsXq2NTUpH9fnTt3dkeVlZl5cR975rUU5KuBvwIHA7rTXaV7YT1TD7BBfCX6/ia/CCV++PhZ+Ho7bEIjvQLN250BnK6dA7XbtHPtOcPBh02MyJUdU5XxBeHEV6oUX8aVHa3COAObjCLYDOwQX9nZ2WT7fa37tebuLFa/llF5uId0U3zl5ORQXFzM/v37KSsri0qSSCO+ZN93xj4CYAOwFjiW5ql7B+2zjXrRK4gkvqIqviI/n5jQGQco3v58nkJG9e8pxGp/kxVsLyCeufXr1+vqbEc10p55ULMdlgH/Q6uJc4G7gK6QzFq0LcMS8fXYY48BMGPGjLDXn332WS644AIASktL2bp1q/63xsZGrr32Wnbs2EF+fj5jxozhnXfe4YQTTnB25hlkEA3GImk38ChwIjBJbNC64TASXw0NDZSWlgIxiC+XBhOC+KqpqSEQCKRc8SWIL6H4kmZzjFNAWLE6Gmetu9R8Bl9dI/c7SeOCOK1QV9ryu1jMsLT1Zr07WSO+iosKwr+/ELAFjdzarGo/t53TQnIZkQM0Ah8AJwB5Uc7VJYiAe0F8tXfFlyhw7Si+vJTvJWCH+CooKGg9+H8AWAoMBIYAQ1UYug12fQ69Z2ZIe5eRbsQXaM+uIL6iQQrx5cZ9F9nuPgHsAAYAY+JsZwbG56oReBU4BNBzsb070DSl+DJ+vh3AnWhfzVDgbGCUdz+fZ5CZQPAczCi+kgFBfBlz9kTgfVTEI1DrquGRP8OzaEovgQbgLeCXhteSUIu2ZVgivgSjGQ/PPfdc2P+vv/56rr/+eksnlUEGtmFsED4A1gEfYiC+Wm9nJL62bduGqqrk5+e3Dil0cTBhLIwrKytTrvgSBbvUYPsEBYQVq6O4Pj+fmof/67OQ/p0YC0YV+BwY1PxPvJgpGJ0j32B5F7dFFI6jtAIGW8j4GlpcEn6fPQ58FWWHAmBYEfSvhsFo/7oD1wG70L73Y6Ocq0swKr5UVfUM8ZXuii+vwDbxZezXQsCi5p/rmv8J/GkWHNAVBu6HwapGinUyHjVD2stAOhJf3bp1Y/Pmze4RX8bJohDwBTAM6AeO7jtju1uLRuAAlBBOfNlpn43P1UK0mnEBcD/hoyMPDjRNKb6M5/0NLWXSBjR19XjgLDz5+TyBzASCJ+E1xZd437i1Rqzxz+A/wD/fgmffh30h7fU84Ei0evRR4DPgJECUX0moRdsyLGV8ZZCB52FsEJY1/yyJv50oSoPBIKtXrwY0tVeYPcblnImsrCy9Ma+oqPCE4ktVVXmKLxM5E1aJL58Cd/0sgH79g4DeDzr8ToyF4GLgyeZ/8bbLwDq6T4X8PtrvYkBTQ3O+FoBCRaAD836wpvjqnFcf/ocfmn8OR1OAXg7cC6x4Eb6rgIv6wRQFegF+NKUXwHto91VBf+1cXYYgvrZv364HUUNqBs6C5MoovuTByucJI74iB//i+bgYOA7tvs5Ge3YWl8GcRrgHuBS4Aq14NmbnCdI+A1tIt4wvSLyyo2PiyzhZ9Blaf/kP4wY277vuU7UBIgpsNry+S/yi2G+fjc+V6MrLgW/jbOcRdOvWjezsbP3/UYkvcd4qML/5tXOAo9D6uaXAjcCvfwsrv2zZL5MN6H62XAa2IdooI/GlqmrKia+YKzpGG/+UAU9th8Muhnve1Uivzj74eR48CPwCOAIYDTQBb4Kjti4DHRniK4O2BVEk7SK8kNFzgls3HIWFhfh82qOwfPlyIIrNMdJqshB4G8MA3flgwpjzJYgv11csjICRBKyrq9OJL0eKL5MFRHGRtnKZGeJr3759TD0A+nQyFB0vog30dAWEg+/EWOguaP65k9YfwYMFcVrB54fOE7XnSBDUKs0EpkY8f1JxEiHVGvGlFPRpeVGlRUV2CZrF4zCgJ1DYVzuHgx9o3qCZ7J4GFAN70L7/g+9Pijqma9euejuwdOlS7YwUJXyVSqcwOajJKL7kw47iq7CwMHzwL3bNB6YC5wK3KPBiX/j4BbjucJiOprRR0Arsr4DIZjBD2tuGY8VXCogFQXyJZzkSjokvcT+pwPvNr21GsxBG284sjO3zJsPruw2/222f9ecKA5GGdv4qeHmg6fP56NOnpZ+LOikhPt8WtHo4B5iJZpu6EzgU7XPOLYXxU+Gcg2HhQ5kFfSC85q8DXqNlcg7ITCCkDqL9NdaEO3bsoKamhqysLIYOHZqU8xDjM9EPRK01ogXWPw5cDbwD1AN9gdsvgO3lcMdLUKig16JnNB/nc2CPmrRatC0jQ3xl0LYgiqRlEa+Xgt6QRDQciqLohemKFSuAKMRXpNXkcbQ8iM+IvZ1FiAFveXl5yhRfRUVFOglYWVkpx+oYWUDcglZE6NAKiAF52qICZgiO8vJyeneKeHE1mjrn04jX7Xwn3adCfj9tpuW75tfqiUugZmAD+zfAzg9gL1qWgf46WsE+9b+U+A8DrBFfjZ0ObSEK6mnJ8tLHnxHfX//TNdtCQbN9JAc4unnT93Kg76n2Pp9FKIqiq74WL14MaEWetHB2C6uUCuJr48aNNDU1ARnFl1PYtjoaB//iUujrHTTfG1MehJnnwm//Bv8H/B1NdXN882ZrIt4gQ9rbhiPiK0UrBbuu+BL30/e0EARBNNIl2nZWINrnTYYBnyC+Bl9g327m88MB12m/G4mvjWgB+uDpgaawO/p8Pl2tHwbRbnzT/P8JtGRW9lLgCgVevQzGd9JqnZeXwPQr4JXtWr8p0B5XgDTWja8Cc4DbgYo423kJbVi1F639FaqrYcOGhSkh3USkMCFqrWEc/5QAf0SbhAoCBwDXAncAvzwfCjq0rkUPQLN0B4EP+2astRKQIb4yaHvofzqsiphhLQHy+8b05CckvozFWhktRcG/MNjrcDSYEMRXaWkpDQ0aC5Bs4stIAlZVVcmxOhoLg+/RFFmftN6sY4420DNrdSytiHyx+edCtCJOwM534vND/1NgJQayC+27F/BwQZw2WHYjhAJQMyH89V6XwsmboP/ppm1Fxm2Kiju2EAXi+cxBWyEnBgFO/9Ph5M0w61M4/GX40wvaPhsa4fX77H0+GxAB94L4kmaTsrisvSC+Nm3SZBYFBQX66s3JQmTmoBUI4ktKPqEkWFGwhRFf0FIQ1zczXoL4aiaI9X7NqA7LpyXfch2eV7G4DkmDQdEmNTQ0EAhEWyFDU02Lvkx/hi0+gzKRiPgS52qb+Oo+FbI7tai9BDaIXxzed/1Ph02GCYC92dr9XPoONCWuGWJizxfaT0GkDWn++R4w9CJPDzQF8dW5c2d9wrL1RqfC/Oa/TTG8LtqNsx7S7NEv/kVbLKMO+DfwWzSViQppYe2TTfSIurGElnq1HM2G5rS+dBspIteThWg1YbJtjmCS+IrMEWxEW5jjL2gk2AQ0Jsa4XWQtetNV2usf7IDvv5D3AdopMsRXBm0P+/fB0uaB0iRNPUEJMPnxmEWMKEzXrNGmxVsRX8bBhFHuXI02GyRhMCGILzHQ9Pv9+sxGMiGuRWVlpRyro7EwELO/lYQXD4CvUCvizFod5/0A++oLAUXrTEQfWItGsIH976RuF2x+Weuowt64+WfvYz1dEKcF9n4LW/8NKNA0PfxvNbk6KWVFJROmWhBEQV0zeVysvVUrosAIn19brGDQ2TDuXDj5QO31O++w/vlsQii+lixZAkgivoxy+wCa9U0f/0Yf1AjiKxTS/NzJtjlC+7Y6inZQJ75Au2c7nab93qWDVhg3E8Q6Iq27Q9CCuitoGdy3R9Je4mDQ2C/HIuSN33FxcXH4M6ii1STGqARwlVhwXfFVXwrbarXcKAXNhguaeirWZIMV7NoEO5uLBkWBugA0DYD63bD2UXvHLFsI217Tagbxdd11i/ZzEbDoX1Af3RrqBQjiK24kxvtPwd6QRoJf9qY2kI5sN3w+OGqqFnh/CdoCLxVoGW3bxIE8bO1zg+gRNf+/0J7TEWjXcA1arIZXJxBSSK4nC/EUX8kkviIV8FFrDeP4Z0Xzz5loK6vG2g7Ca9Gz74ODu2iqrxt/7eykM8gQXxm0Qbz1qDa46+qHcy7RXisBSiOnIltgzLaCKMSXcTAhiC/RTn0GrHPuvY4kvjp16iTP4mQBxoB7KVZHY46GIL5UDJJxrYAIdj0cMG91DKnwv9Kjml+I2ECE047+vb3vZMlVUF8OS5qXdurcTD7kNxeKpR/Anq+tHzcDDaoK312r/T7kfNgU8QXublmRwqziS1XV1qqF/qdD7+Y2oFNOdKIgHv7wgDZmW7AXvnot4eYyIIiv9evXA8ghv4XcvgrNrvEoCYOnI4Nak21zhIzVESKIL4A9zexV9+5aYRytfTPaJXLQVocCzb414a72R9pLHgxmZ2eTm5sLxP4uxT2bm5urbWu0vHyKtnLsu8Y93CUWBHHtCvGlqrDwUni/OdDr4Dw4vPlvG4g/2WAWn/9H+9krC/r3137PP1f7ufrvELBOjrP0Bu1n1onaz+7d4fSb4aijtBrlnSpYdoP9c3YZgviK2za/0EwKTh8CQ0/WBtLR2o26Um1EeARwF5r6C1qyco3beQluET0+P1QeqxGgCnARGikI8BHwuQfzlozkejmaUk3vOtNAtWcS0WpCsTCZ5xRfYvxTT4t9+iDjBiYJ1L/crv18Zy2s+MzW+WagIUN8ZdD28HZzgfSj4TB6tPZ7CbDjHa1Ai4JIVcWgQYNab9T/dBh9gxZOCFphJ9qq54BAZIqrNUQSX8m2OQqIa1FaWqp3LI6sjkbS0Jj3UQ7GmeDCIu19zVodAXb4DtUK6urmfAvRoi1GU5Rtfsl6J7/jXdjyKqxVoLIJOneGM3+m/a3pABhyAaDCgl9DsCHekeSiLWU2bH8T9nwJ/nwYeyusXKm93qk5gGR3S+CKWeKrrq4Otfn5Dhu87Wxmqrt2jE0UxMK4mTCjmbT92/Xm93MAQXwJSFF81ZVq7dafaMl6WklrwtgwqCksLAyzNqaT4isUCrFnzx6gLRJf2ueiS6f4BzDaJWb8WHttLVD1Q7y92h4iw4VVDIuU2B8MRltZzIhW+V5GwmB988/lUXZ0iViIp/gKhULOrI7bXoO1b4Fw4dz+Fpzzovb7TmDyXOdk6zfNfrPRvUGEV9cOheLh0FAGax+2drydc2HXx+DLhqzmIDxx3Kuv1n5+Bnz/lKZO9iDGjx8PwKhRo6JvEGiED5plJmefF/9gRsVJNtriGBC+iEDkdqlG5LO9D9gq/uiQ6AmF4I5Xtd9nZmkB5BNpCRt/Blhdaeu0XcOeebB3u2ZVvQZ4mmZ1moCHVXsW4BXFVyTxFXVVRzH++QFNsdUNbWElwJIS9oT/g8ndNPXhDf/n5LTbPTLEV3tFWxpER+ILjfnnxFNBFAS7gMpNUBWZ8KvBOLjMysqid+8YnXv9zhbF18wr4dE5UJSrrV70t19Czdbo+5mAV4gvofhat05bHjEvL8+56qTDaM1KYKy59xE2EyxWrqutrdUJjFjYt0/zHHbp0kUrqDuco/1hVD706AI1wOp82Ps1rL7T/HkGqmHhbO33deO1n6ecAoObJRPbtsGEuyG3O1SuglV/N39sJ2hLmQ2hACz9nfb7AVdDXh9onq1j0iDtp2HlMbPEl/HvYWTBbk21SFeb9/ANf9V+frgR1kV6X+XDFeLrw7naohJ7gB5ogxrjEvcCEYMaI9mVToqviooKPZA/5hLjViGhz5RCfO2r0H6aISKFXeKEi7T/r0WbDGisMHW+bQJGpVUVcCXwBOHkl43BYLSVxYxoRXwZn61m7pKNGOyOtN5OIuKt6hhz0sAMGsth0eUaSdQAHHggzDoKDjoHejeHTH8uQS37XXN+wcSxLQTV5i1w4M3a76vvgkaTRISqtqi9hs2GHc3PozjuccfByJFa3tXnwKJLPVkjz5o1i8WLF/PwwzFIv7cehoqQtkrcmb+NfzBjnAdo/QQYiC8PWvsiV1u/C7iBlgWJnBA9T1wLP9RouaD/WNCSt/TgR3BEL21i9eyLYPP3iY6UHNRVwx3Xa4TXm7SsprqC1quRe021ZxGRNWFVVRUlJZpLYOTIkUk7jw4dOuD3txBWMSfZ+p8O65rrkAPRHzHLSthbm8cy762DpR/bOucMMsRX+0RbGkRH4ruPoDQAfuD0y6FvXygs1Jj23UDJO1F3M66I079//7DGTEeoSVOqCOJrxv/BgafB7c2N0av18M5PbRdIgvjasUN7g1Qrvtau1XS5vXr1cm65XPdo69Wd/D8Ks52JzkxVVerq6uIertWql9ubD96nB/z059rvaydqP1fcDOVLzZ3n8j9A7VbIHwhfNld8p5/eYq3Ytg1yu7Yo2Fb+DSpXmzu2XXgps0EGYb7hKdi/ViMPR/8Otm6FmhrIzoaJI7Rt9lbomydSVgiIIqiwsDA86FcoZLrafJ6OPh/GdtTakFsvSbi5U3Tp0iXs2XdMfN38U5j9jDaIG4kWqtrsEEZ360Yf1BhJo1QqvqwSX8Lm2KlTJ3JycpyfiKQ+Uw7x1bxvDwsq3MObfWfbgco62Pic+X1jIV0mz4yDvJVoky/zaJ3faHEwmOi7bEV8GYkFQXzVoSmiBJwSC3G+E6PiK3JiSbSdiqJYX8Diu99BzU74qDkW4KqrtAwugAP7aD+/ljBIW9V8oabMaiGoNmyAgT+DDqM0Am7NA7H3N2LbHNi3CLIK4cCbtONAy3F9PrjySu33D32wd7HWb3kMiqIwceLE1m2EwItPaj9njYD8BIRmZDagaPqNii+vWfuMz2yAljyyx2nJY43cztRxq+EvD2m//3I6DJnQkrfU5yh4cyH0zYF9ITj5R9BQG/dwUhDr2Q42wUNXwJDOcP9CbYK5N3AFGmlXRYtLRcBLqj0biGx7RTZzr1699HFUMqAoSlitFpP4ClTD4uYJh9NnR8/ZM4NjfgmHdtcmS27MqL7sIkN8tTd4aRDtBv77mPZzbGfo0kcrYMQMQAkxiS/j4LJVvpfAni+htEzzamdlQfPqa8y+FMaN1gJSH/4WVtkLwhYNtgiTjhtY6iIECSiIL8erogX2awOtSOJrb31YEWUs3hKpe1oRXzuaM6F694Azz9R+//h76HGypjD6+lwI1kc5kvF8FsCaB7Xfc66B7TugqAiOPjqc+AKt2O59PIQaYcH/gRo5bS8JkVL+MCQ5s0HG4D+wH1bcov1+0M2Q3QFWrdL+P3Ik9G72V5S3fP+iyKmpqdGfjWiImVGzt9nP58Ty9turtJ//XQR77Ks6zcKo+rKttmysh7PGwl/+oxVKR/fUZsOLFTgUrfffSEuGS5RBjZH4SoXiy67VUWq+l8Q+04qCLSbxVd5sBe/Rx/T70qMHjGgmldehTUQ4abPSafLMOMgrMbz+AhrxFG07E7BMfAliIaiGD8o3GH4fcJZ9YiHBdyKe38bGxlZxAsZJA0uTXLs+hw1PatECe5o0FeLPf97y90nNk09LHKpitq2GPc193LSfwJDmpRc3bNCu10G3aP//4V6NAIuHUJM2wQVwwDWQ1wOa8xR14gvgvPO0mINdIViClvXl4aD7VmiohbnNDodf/MrcPsZsQNF07gH8Bc4z2txA5GrrokyqRsuxDEXZzgz+er62kEInH9z2auu/d+0Hr7+uhd2vqITzp7TeRiZiPdtPng+jOsIVD7Wc7/8VwN/R+nghflopDiRBteeBCY/IydBU2BwFxDgtKysrNum27F+wTdWUXmf/JXbOnhncepf28/2NsOQDO6fc7pEhvtoTvDSIdgsfNYdMzDqi5TXRGJYCu+dFlcObIr62zWlRew0fDkJJ4PfD409rv88D/vMnW5kQkY2mV6yOjomvzS9C034oaR7Ad9YsjZTuCdvM5/Pps82Jcr7CrI4AO5uP1bcvHHEE9O4NlZWw/yzI6wmV38PyP8Y+YCgACy4CVBj0C5jXPEL68Y8hLw8GDND+v327ZpNQFJj8mDZjvOdLWP+kqUthGULKX42W23AjECYwS1Jmg6zB/6o7tVW4iofDsOYZK5HvNXo09BLEV8uI1EhkCTIgGmISX/uaSQYrCplInPMHGJCrDZTvuNj+cUzCSHwlVHxFK0T3bIUf9YN/N+e7XH0cvF8CM1/TBjUdaAlY/TY35qAm1YovI7kQj/SMhDTiS3KfKUXxVdmcK9izv6n31HFEc5+4Pgf2r4OdNlU46TR5pqpQYkiQNxJf5cB/m3/P62l5MJjIgt2K+ALtGRtwm6YeFdiA1o8ArH0Qdn1q6TwAU99JYWGhrn6MzPmyFWwfrNcmfQA+a25bL74YjIqxHx2n/Vy1R8tMsosvmq2SfbOhW/9wxRfAgJ9Ap4MgUAmr741/rE0vaDl3uV3hgN+GH0dMZoLmFPi/5s83t1Aj1JbdaP8zJBv/uRuqVY0MOfVK8/uJbMDT/qX9fy+gFEK/U104SYcwqiiFMq0TkIdWJ72OdaJnz1Z46HXt92t+Bp1j1A2HnAAPN98P/1oOd7m02l60Z3srcPN2+L8XYF1t84qds2BzKfzhn+BXAAWaI45ZBVJWVvXIhEfkZKgXiK/u3buHOw2MePt57ecBPcxFFMTD0efDlB5a+XHjbGfHaqfIEF/tCZF++LnAZbQEraZ78GHVXljaXND9xNAJicZwTwdQm2DnR612TUh8qaFw4kuE5gscdhj8qnlW7bkQzDvb8ipDrhJfFmZpxLUQ5JOjYHtVbQmd3d5c3M9ongXe2XpmVhTeiYivVoqvXc1kZv8hGhH5k59o/3/jA5jcTEqtvkeboY6G1XdBxQqtGJ5wD7zWXGif3kwG9O2rkV0NDS3WucKBMPZv2u9Lr9cGGbKxfRn8By2X5k001dy/omznZmZD5OB/DwabkIXBf+0O+OEe7ffxd2ihwtCi+BozBno3Z6lVtCwUkZ+fr6sQ4ikBYw7eypvJMkGq2YE/Cy5pVjI894FmhXARpomvaIXoE73g4KGwsExb0e+J6+De9zT1qzHw/LSZ2jG+DkHfU6Me3iuKLzC36IWANOIrss/8HPg9BpWOtT7TrHoR4hFfWnYZfYaYek8dgvja0lx4r3vU2v7Qui1YioFM8tjkWSgA8y/Q2nYBca7HNv/8AC2fs7E8al0QD5YVXwL7IhcrOABO36c9m6FG+PwU2PcdpmGSnFXUUMyVHW0RX9//VbOs7+gKy3ZqKvjZEQOxqT/RYicqQrDWQUD8/M+0n2O0VQx14mv3bqiuBsUHB/1Ze23N/VrYfTQE67XoA4DRN0JOR61PF0puo+IL4LLLtHpiRY12n2x4SlOGpwNebh5sHzMGsi3avX1+GHeGFj8QRJukrIi2EkOKYbRninnUwcAvm39/HSg/yhrR87uzYL8K/XLgd0/H3/bCv8HF07Xfb3oKPnkx/vZWEflsl6PZOG9EWxjDDxyXDT+sgIfmQsce4aq9Mc3HWQ3k9nGm2vPQhIdoe1VVpba2Vie+Yi7y4CIE8RWz1ggF4bPmNmPWLDlv+tfmOvrDTbD4PTnHbEfIEF9eh0xZqXFwvA54Hq0hXRRnu3TCGw9rPv/ufjjkxJbXBfG1u5l4iWJ3NBanUVd0LFsEdTugpDnHIpL4ArjjDujSWZuNeX2TFvhqAa4RXxZnaYx5Z+BQ8bX7cy0EPlQAG5un5I5vbvz3tlbviID7eARHQ0ODPijUr9Ge5mMNbNZ2C7vjG29A92Ng6K8AFeafD4EIm1HVWljxF+33iffB+l2a9SE3F45vXu0pOxsEAbjVYHUbcRl0nawd0+L3HffZ3r1FK6imXgVvoNlrB6C12OtIbmaDcfBfD9wK3I9BPm9y8L/8TxCsg+5HQL/TWl43Kr76Ng889od0hYCiKKZyvmITX80KGUGq2cXl90Nnn5br8dBVzo6VAMMMyoOYxFe0QnQN8Lu9sK0JOivw3j/h/yIWdxCB55f/U1u9a0cAPn8l6lukWvGVl5en5y1ayfmSRnwZ+8JytD5zG3AfUBFjuzgwfpeJ7NxRia/aqhZ7Xu9hrXeKB0F8rS7Tgpl3vGV9MRZjW7AOLUz67xgC2j0yeRaohs9P1tQ9ih8OexYO/3dLntaxwBS08eTz+dDUCJ+fBBtfMP0WiYivykptMqbV87u+2fbXp1kZtXKDZn88/CXoMUNTR392HOxfjylEkrPvA2ElTst3EmtlR8vEV/nyloVdvmkeXZ91FvSJsN8Wd4HBzZ/z0/9iG0ub+4iJ47SfnTqBUHtv3Kj97HcqdJ4ATdWw+u7ox1n3mHatCvrBiOa8xs2btQm6wsLWdvh+/VpqiXlDANWzQfdhqKmAz5qvy7k2VSF+P4haeA9Q4tEBtiB6ypon0roDPwKm+7Xn+9rnYXv0Ra1aYc238GLzii9/vhZy8hLv8/BcTYETAM66ALZ+L2/MZny2NwB/QHOVqMBhaO3vuQHIjbDgigmuCz6AArQYlo5/tU96RRJw9WgLSAGpmPAoKCgImwxNpeJLtKkxF9HZ+y0sb65BT7lAzpvO/IW2wIIK3JBRfVlFhvhKBcySWVZlpfGO21SjLd8MWiP4CC3F6k7C4XQQnSoP+NvNKp2pIzV1g4BoDLdUaQ1Fybut8k0SKr62N0ufdzeTQtGIr27d4PbmfK//Akueb7kGJq6FZeLLzHW2MUsTWag7UnwJtVfTcRqR0aMHTDlSe62sqZX9QRBf8dQdQu2lKIpG0gWbYF/zZx9yoPZT2B2rquCjjzRCq3Aw1Gxp6aB3fQabXoYvfwqhBuh1tGZznNN8TY49Foz5SpE5X6CRCJOfBCVLu0e2/tfZs73sCbjkSBg8CJ74Qhvk9geuAv6Gtpw2aCtoaVfB/cyGXZ+0/P4aLStz/hBxnOqNsY+74RnY+Iz2+vi7WsKPVTVc8dWnmbgMAntaQuESraBm/FvY4C0Ugsrmz9NnaJS9LKCgA/yyWSryyIvW2zUL7WLCjK9oKo95wG1o4baDgDt7wIyzY59Plz4wtfmefua+qJu4pvgyeS0URbGV82Wa+IrbZ9aFK0T/hbZqHWgk2INoBBLA/g3avZzg2EYiL9HniUp8lTaTIT6gRwxLfiyMHAldu0J9A1RO1PrA9f+wdgwjwSdUn3vRSLBY21mF1fohcvu6nfDxTCh9X8smmvYWDLkAQgdrK53lZsPJL8Lj/4UOHWBtHSybrKnB55+v2bFVNeF5JCLjYyq+NjV/hwf312qGQACWLQN/Hkx/EzqP1+zgnx6rXcdE18OoNC4H/gm8jGFg2oy6UvvEl/EcSj+Gby/Srlf+8fC/b7Rtrroq+r5jmycc5jsgQ1c1T5pNOarlNWPOF2h9iq76elC7hkYEqrTFaEDLBPPnhe8/dGhLv2TE1VdrPz/eBjVFWij+hifdqXFl1c4v36HVDt38cLwDC55YzXo32vMkA26MD/qfDlXNbf0BkzRF85wtLQH0Z04zZ7X97S80AuvADnDBrebe25/VHHafDXuDcPxY+FCSFVC0o9+gTThWoK3I/BfgcqBnxHZG+PzQ7xiY0Fy/v/dve+cA4QRcCG2F6GsJJ79kTHhYqAtEW1VeXq7HskghvizenwkVX/Oe0b63HD/8aJrz8xP4a7Ole+4WWPA/ecdtB8hK9Qm0O2ybow1YjEREQT9Nrmtk4wVhESlfF4RFpGQ11nEn3AuBci1Quq5UO9wzNAdWog0wd4kdFG0fJ4Nos59PNkIh+KJ5JH5ixPsMH64RYVU1UFMIym7Ytxi6HqJvEpf4UlXY9pp27bY2B6RHI74ALroInn4aFiyAV4DO5xD2Hca5FpFKq7jEl5nrnNACoWgkUN9TwqTg0hRftdth+xva7xUHAnNg/HgYMl57LQCUrIN+LcsPWyG+OnXqpHnqt67W7mMFGNQ8I+zzaTO1Dz4I//43nHgiTHke5k6Hjc/C9regMcIO0e80rfCNtDkK9O+vfa9G4gug81gYdR2suh2+PIuw9enNPtu1wJzt8N7F2u8AA3Phd5fB8ZPh659pr81QNYXmPOAsNMWO08yGaPfRxPshtwus+LOm2gPNZmmsfTcQDnGckVdoZFnkcQG6ToHuhiBY44qOw4ZpP/PRivYda6GnVngnytMx/k3cQwBU7tbuM4C+I+JcCJP4/ePw2EDY2gAv3grn3WJuP4vtYkKrY6TKYx6aBQJgEjAbyNulbddzRuzz+vkv4JPb4d3vINDYyhJjVHlJU3xZvBbFxcWUl5fLV3zF7TMrm/vMZlJhA9o1BrgYeA5NXfcKcC6w4o9Q8j/NwttzRsxjKwc/QHFxMRUVFaaJr7D7ubSZXC5WtAGXFSiKNiHw1luw60DoukQbwB/4R/DnmjuGcVJsieH1+bQEKUduZwVW64do2ytZGimT2xWmvwPdDtVeX90cjjjiABh6jvb730rh8svhyTXwn9mw5zFY+jvY/QWUL4O62OeRiIwX92tkf8rW5mMOGgDBYfDuu1q/MnmyttjHjPfhoyOgegN8MAXUANQZwsnEefQ8UptQWH1Py9+M+Y/lgOHWIb+3Tnzt3RuuEIlLfEW7xgD+fFgwEgLvaffVpElRrwOHHApzVsGySHbUJDYt18gLBc06KTB0KCxa1EJcAfQ9EbocAvsWagTmRIPya/U9mgWyw0gYfH7L65ErOkZi8mSYMgW++Qa+OxJ+9CEsvASzdZ1pyKydX31Z+3n8BOvthBGCXNwD7Play8fN6Rh3l7hwc3ywozk646BjWvq8V/4Js86C+bvhxtPhjjdi7z/v3/BuMyl9z/3hk+eJ0H0APP5bOPMOWKVqxPO5zX+LNWYzg5zu2iR687w7E4FL0GokI+K1t9OmwFevwzwHFl0jsbaBltUzV6Apz6JtZxUW742ioiL279/PihUrCAQCFBQU0K+fgzgLG+cAMLp5LHjQQQdFP+YHzfLbQ0drecGyMONs+NFv4ctSuPFSmHti4n0yADKKr+TCrPomkrAooUVlEU1WGvO42+Grn8KC32gNUuFgWHe0NnvgA8RCL7tbDut4EJ0qD/ji92F3k0blnh5hOcvLa5m5qj9Y+7kj3O4oilNFUegvlD0Clau0MOCqbI088/laVsiKhM8HjzyiDTK+AlbHIC6jXAvTxJeZ66yqsO2/LdvsQrOn3U+LSiHGLE3kQNs28bXuCVCD0GM6rG0OYJgwQVPOdGieWd20LGwXMxlfrfK9NjZnT3T0QZ6h0hcWhTff1HI8ekzVSD5oTXqBZmH44mFYsULLKznppPC/R1N8CXQSnV7ErGKiZ7serai5Ck1NVYs2o/fIVbChGmbfDYN+2pLZMBbojBZ2v6zIpcyG7fDlTzTVxO7PtYGkUqAR5qHm8wOtABK3t5KlWUxW3Ayv94V5Z7Q+LkDZ/PB7X6i9RozQSC+Ajs2FekmLgswK8RU2eNveTIbnoOVfOEX3AXBGcxty7/3m9rHRLnbu3FkfpEYlviILzGYxL0eh5cHlxdguEmf/HgoVbWD5duvMJ+mKLwcKVKnEV8I+89ca6VUwAIZfqq0ACDC1+Z9wF7wP/HCIpiwq+1ab4X93QtzPeOZhThRfm7SfHS1m9ggIu+PKSsjvo6lirPTL3adCVrGmEjfeWgtobvocKFCt3huxtlebO7gDb24hvQCa7TAYc2Bmz4aDD9YWQnmuEiY2z6KXvBNOekU5D9sZX9ua+8KhIzRSBWDhwpa/5/eEmR9Cdkeo3RJOeunncQbM6QXfXQv1pejB1Ubiq0L80vKdWFZ8xbrGAHV18I9mFe+VV7b+u8C0k7Wfayo0ct0q5jV/7/1zw4PGBVG1saWfQFFgbHNswbpHWtq/+t3aio8AY/8KPgMZlIj4ghbV17++0VSDsSak7da4Mmvnil3wZXONckGc78UMBPFVXqw9V0b1t1W4PT7Y2ewBHzmx5bWpP4UbztJ+v/tNmBvHyvzbS7SvdWZ/OOaXsbeLhlAQml7UJkVA6xfm0nyb2LQCVu6Gn5/fQnqdCFxNBOllor39cTPJv7zMfjapkVhbbHh9xf+zd97hUVVdF//NpBMIoYfee5UqCAIiIKCi2LFhb9h7770XBBUVlSJFrIj03qv0HiBAAgmppCezvz/2vdNnMpME1PdjPU+emdw2t5x7yjprr+1nu2BQirJh1r/rjLqzZcuWvs3lT9M5ANx+++1s2rSJxx57zHPlqXhYZ4RUDb3Sc31Z8cZH+rnwMMx+7R/NtPlfwlni60zBbcB7NLUOhUVm4yv6t2oULL0CZrVxvHyHUTPdR1EzQ3P7nARYNBA2Pamyc6+qHhNWVXA0/xXeW6mLRsZAL7S/lAcU1CrbIPqfzhj50xf62bGq9wGuKYHNMNRcbj5fDRs2JDQ0lHbt2tkzH9lhVng5xoC3aVP/zH3nc2CwMViZgBPRBP7uRWhoqEvH0yvxVeJ9FlhxHUyPhRXX6m//CjyJhqasA7a57eY2OHYn4EoV6licD/uNMJoWo2HTJv3eqZN+VjfuX/wOl90C8fjyyOh4yOjtV3dTLfTqpZ4jmZkwd67eu9R1+MXXz+ln//4ODxETvogvW7Ga23uF8UxW3wbrRqvizLlhHYfO6GUDddBkE28CVwx3nak1PRsGLYJLDNJ1afhpel+d0PxeuPQAHLxRk2BEonVRKEq+nQCwQK8pcN6PENMGin1nXgRcy76zv5eJWKNsJDn8h0pNfB0zBjWVQ4KbwfWH58aoWvbvDJj3nf9ty1AvPvroo/Tv359u3bp5rHPpYGbhUN9dimurXlJHtEIMDDDK0/dfeKyuXVv3j46O9jRZd0dJIQKlvBflHuoYUNm3apKLS3bDnp5G2beoyhJUVXeFEYL63jZo/Lu+K4RA+mYfx9ZlL1+agdVSSuLruFF3VC7lzLFJfK1cBU2NjHV7xwS+f/JS9aAy1V6tUFVROo7Q59JMngVbNkp8hhY1tXcuS6biyzkcJiQEvvhC64bJk+FwGwh3q/d9nEepia9Eow5r1sFBfK11U2NUaOgIxfN1HrYCqNwOun+p/mBYXMPPM8A9k1tQxFdJ93glmjG3fn24/HLv24Bmv4tA+5nrS+ETtdpQHJvG9ibcMzuaqD0YqvdUI/v192t9tO5enZip2gXqX+G6fSDE1+WXa2bn1Cy9bg+UoY9b3n3n719Tcq52GPQbGdy5uMOcME41M3GXMtzxdI8PUhMg0zhOm16u616cDOfX0aiAG2+Dk15I3B/f0mQwIcAHE4L/fVOB3Q24zFj2LWpCvwaweZ9k9om966BrI1hyTM/pTuA6i9uI3fXd9olzh+tEcz7+iT9/cM6e6Ux8bcPxSEs74VHKsmHWVSbxVaYwxzKUT6vVSqdOnQgN9aKsjP/ZMRkxZHjpz88X+lwN51XRU3z5+X800+Z/CWXQwJ5FUHAKTflz8xBuHPsDd13wBW9c86xjm6IsOOJUWAWYhFbYxcD7wAOAwb9wfJFL6msReOrHt/h26S2IuHoVhIdGMjuzLx2Ks1kadgFXzZ6D7U8bmyxNqCdHocbzZZMaO11fQVEYF739FxXCc3jnuidoU28nLuoif6E3pcW85fo50BFDvXMnXH01PPYY3NyqFcyaBccjoCnq05CbBFFK6sTFxbF582bvqgbzmWQ2AVb7DnM0kbyMlAsjqLSkkIgjBYx57B4+D7+PGQ9eSeu6u/B3L2JjY+2dUK/El9N9zsiJYfBbc9h/wnuHrXvRGt7Lf5zWNu0NZxBDZTIp3mAlpJOTMsltcFwuoY4JP+ksa1QdqH0xbNHQgsNVO3FNT/iuoCUt2AyHXQ18gwl1tN+fw9pxlRoxbNsKKSmQlgZpaVY6NbmKLsc+Zs2j0/jw6x6kHfiatOwqpGVXITM3hrCQQiLD84gMyyMqPJfvjt1MGzIYkzSCxVdpZvbISP3rsKcBtwO7FyTw9AjIy9NJ77ysU+Sl/EZeYSR5hZHkFkTRs/kqvr/7JipFGYOcwnTvA0xzsvoG1HDZ7Nh4Uer8+nsITz3Vjy8e+oHzv+8BG1Jh21JoVwrfAKdyVGyzctXH0yksDmPK6OuoGOl07xtcBafC4R0jleT1laFmBjTEkLxXhSu/ctQdETVg4QD77jPWXMETU94hK6+S6++HFYM1hI+zdjASeOePNrxbQ8ehq6Ia05itcNzhXVPSIBN8DN6S1Ccs0VaHTrUCs/kAqFBBRQwPPqjn5IKWPWBgE/jrALz5HHRoqM8rqrZ2/Jw7oU73ef2BLjwy8QOa1DzAhLvNGWXfdcHTTz/N008/7f0EzY5ozlHYJiCwK6QlfZ516lhbrD4H8aGh8NJLcNddwI13wG+PwfzdkJsFUY5n1aRJE15++WUaNGhgN5P1ikBCBIx7sTepGX/9fRF/bbmIQykNmXr/NbStt8PnvTCffbkpvtzCRO/55nNmrPUyGxtWmWhLAavSnqA28Jr1NT5+4TFU2mTFarHyY9gw+ufOJb7nHQyMXU8G77tk840IzeejGx/iyh5G+DRC7cpF9GlVMvFl1oEuxFey1gubU9sx0IeXrjfUqAGffQYX9OoC4eGaDc9yIVheg+QVGtZXpaP/g+SnwkojfmdbFSCNz9Lu47wayzkn+29YGwp3TS1dP8LtmYydfzev/PwCRcXuXdQ0He8JuMZa+oBRzwDMSt9Jd+COD1vzi4u4sQtvhN/HHXmfsn/IaPpW2Ey+xUE69Wq+kp8fvhyr1ZjEMMpoSWS8V+KrIA9O6uCpx11DSM+twG6AXbtoUi2DLKvR9tqKodBdTuHt+iqDVSfqqhf1Zmd6A/sqSQdLhXo6MDaeSVBZHd2eyeIdfRn1xQSy86NBhMU5/WjLTl5KuYcxtT2HEiEh8MQT8Mgj4dCyMmzJgKW/Qs8gB4CbjcmxzucAmkPo22/h2rgmvAzkbt8PudpWA6r6ihsEKau0H5Lwk+NYdYa5+HgVFUHR9n1EAh/82pTJ4zXy3mZz/wvljvS7eY5n2Pl1K/r9uAgbIQxqP5eJ995gHLKUfVy3+zxr01Ce+vEtvrnzVro1XR/8cacbSQQu7uEy2ZOfD0OHwpYtPvbzgiG1mqjYNckwNzw2Wwca/toCb3C6xt3HWnDD2Ik8fNGHjDxvirFBGccHO5WNzAmrwJARtZk61ZGLCKsVpi2H9s0hqQiuOU+z4Zn3prgInjG84a7uBB0v8Dj88uXqYtKkCQwbpvfR5AQB1/7aFWgdNRsVLnyCTmpeBnQ75PDlAn3Pk5e59h/mfw/X3K6ZUGMsMPEz6BQHGx7ki9+H8tLMl7RetFghtCJYfYeph4fDBx+Eck3XerAwAf6aAZfcG/BttcPMnjntCjgGYgWxWLCmiEaTxKEK29JECzmVjd82XMJTP77Fa1c/x4huptTNf79gwwZl4spEfLm9g5/OGc13y25m2gNX06RmvM9zKBHzJinhWK0itG9PYqLmyzoaRAL4evXUdeWqq1znbADtd12cptFFa9Dy1oCyhdf+f4D8B5CRkSGAZGRk/NOnUnrETxaZhMgkZNoDV4q2HiJ/PTnIvlwmIbLyJpGtr+n3x4yNQhHpYHwPQeQBY9s1d4sscOz/+S1324/r/vc+D4uAJFNNanPUvnweA/TLO7eX2/WteaWb/fihIQXy8JD3Jf2rGF0fP7l87qczUhP1HoHI+j/ti2+5RRdFR4ukvfuV/jN4sMjsLnou+78t+dhZB3TbySEid4zSYzzzjMsmRUUiW7aIjBsnctNNIs0aZQqIjOIbEZBMKkodjsiNvb9zfdZe7kW7du2M3jWSmZnpeT5O9/mjGx/w+qxjSZWx3GVfcJwaMpKJMoRZIiB5lcJFJiIyySLyc32R4iKXnzhx4oT9HKKiosRmswX0GFwwp5ee55aXRXbuFAEpjqogjRsUCYhMiDAezl3nu+x2++23CyCvvfaaz0N//PHHAsjVV1+tC+7sIwKypPGlHveiJytEQDKoJBHk+nw/QKQeh/U8sUgtEj3Wd2e1CMgh6vs9jvl3SedfpegHq+N5L75UZP1Djv8nIGIxNv4c17KRtMjlmteuFYmM1E3btxexdamq/9zZJ/hnI+JSjmY+dJn9nId2+kMKvw9xLaM33KArO3cWyc/Tc7t5sC574AGfx5339AAJDSnwe49W0UME5Eqm2Zf9HHOVceyB9sNec801AsjHH3/s85LuuOMOAeSVV15xLHxLy9mi8P4BPTP3v27dRP7+28uPLZuuG1gQ+dDpuf1cT+TwT7pN4SmRtffKqa8ryKND3xWrpch+3MQxtUqsC0rE4Z/0He6jB32bx4O6trg4kcJCESnIF6li1YXfPFv683C+nklG/TLJIqe2/yh/fLdW7hv+izSttdfjPO4b+Knfe3HVVVcJIJ9++mlAp5Ofn2+vv1JSUjw3cCqjq17q4fcevcJzIiD7aey1/qhKihygkQjIHwwVC8Ue21za+RePe3NtT+T777/3ex2VK1cWQHbv3u1YeHdfEZAvLHcGXZbDw0WmTxeR887TBd9+K7LsaqMvcaf/m2qziSy90mgLm4otJEQEpDH75eKwP/R4MRaR/NyAnpG/Z2KbiDSsHl+q99X3n01OUkUEpAObPdbHkC5HqS0C8gIveazf+35TjzI6Y8YMAaR3795eL6lNmzYCyMKFCx0Lty0TASmwhtrLyj6aiIBcwPwyXeMVTHdZcGp4e4+2fcKECQLI4MGDXZY/9NBDAshTTz3l9ZnIJOTuAZ/bD9+PhfobVJBYUv3WMTabiNzUTReMaBNcuSguFok16qZZX0hRkUjlyvqv2V4XECoRIYXSubPIvfeKfP/hWtn9XguxTXR952wTkX0fNJXJn66Rhx7S16BCZLHkEmEvy/7ub2XSJItoEZABzLMv3/R6x7LV5W73uXOj9QIigzvMDv64xw86+sIrf3FZ9cMPwZepWFId/3wbrueRvj2463O7xut6ThIQ6d1yqWebUdrxwddPioBs4BwBkXPPFcl1r4pmfSFiNa7ljZu0HxM/WeSVYbqsAiJH93gcev9+kWrVPO9N69Yijz0msnChSEHCYs9rGYfI5cZx7S9EiMibo0RysrTd/Lme6z4PRYuEGds2jND6wsCJpCKpGF0Y9DNs00bE9vJI/adD5dLdXxP3dhYBWRx6vizmfD3mLUYfd8FAEVtx8Mc0ysYvD19q7y+2qL3L4/11LxvDhg0Ts50HZOrUqaW/LqfymfZlZYmOyBIQubbn5NKXz/x0kcsseo+uukRERO65p2ztWLt2Ii+/LLJjh2jdbpafHsYG3Zzvmffx3f8qguGJziq+zhScVDVX9ZjBPRd+ztj593Lj2B/Y/EYn6lQxZgya3KKs/66xMNmghQejIRbjUJn1p4ClKlz7mTLQSXPZfLAjD0/8EIBXr3yOEd0cyrGKu07R4FsNz8r57Fvm968DqLJ/3+vNuJAFsNc9RVvpr2/3MXW5jQzLJa8wig9nP8LklSN5+9onubFfrfKPr/35Uw3piwuFczTrWk4OTJ+uq7OzYcyCVjwLKgOrM0rN7Y/O0mxP/pDws37W7Au7DXlOmzbs3w8//AArV8Lq1eA6eW/Entfpyr5TTWiWeYD3eZRRaybw0Y0PUbVimm7mJQzJzOwYEhLi3WjW2EcEvlhwFwCvXfUsl3f9GUSI+TuTuN+PE3pKZ5XTLhpMWvd4no1+g6cnvk721gpEZ+XAQaAxXmXSzjPUcXFx/pUe3pC6CVJWgjUMmt0Jvy4G4G/pQPxh/a19+cZ02VFXZVOpQh2PaQz93xnq3dK4sSZ0rFIFqsaeS/ovdYnNPsq0kd+RHrOCKtFpVIlOIyYqk2JbCLkFUeQVRlJrTRIsgJSm5/D603EORZfxWSW3PnwI9SxHGfdpERHRoaoIy9tK5M7H7KqxpPQ4rv50Gr9vvJRnpr7B29c9pefZ6mF9txNm6IxMsmiTHQHYb7lngomjR2H4cD0PUAuyLffdT8cNL8OMFfBpPoQHaE5twqnsfTD7Efv3PzcP4+5vxvHV7XfopO76YzBxos7wjhunv1OrH1x4BL6b4xmiYxx388GOjPhwJkXFYVzbcwrPX/aq63bnToBq3WjZYwdkw1u/tuG6IrjiCjhaqPUTyQ4D5lKHOh7X8nWkSI85dy7UreuxqweWL1e1wrp1agH05JPw3HNOEc4Nreq3tgX4ExhlLDf9d2r1h5PrWLC5O3eM30p8snqlRITlkV8YyZp9PRje9TeP+xYU6o+AXj8i916DBfiLi/j54cto0TgL2jwFtQd63c1m00jepCSYPx8uuigchnSCyRth0g9wy2uBn4OXEAER2Hm0NX9tuYjZfw9h6a7zKShylM+wkAL6tFpG/aoJfLdsFPO2uZ2n270IVvGVnKweSiEhId5Vs07Hf+0XDW0e2WsSzw5/3WWzsIZv0PSmd6EAwj56j40DvYWeVUN2zsR2fS+G5f/J8VF3kdx6BQALtg/gge8/5USmp+osMb2UoY4nte47ISr3+vtvVe/5g4iq+2bMUAX0hgvP4xxWwIoVMOReODwN4idCp7chPNb7QeK/03rLEsr2dffQtvgxttOGeJqQUFifgqhwwjML4JdP4GpfYd9+4PRM9iS24FBKI8JD81nzcg/CQ518oTq+rn6K6Vvh72e9HMgN506A6t0JOZlM1fPTEIuFH9e3QDweZWVsf30Ej17DiyEvc+MjP1BQPZwRH81kd2Ir9p9oSrM4p5C6qNpUqqTnFVSo4y4NyzkeVhvJt/Laa1B9RXeYfYDJD63l5B2GWjZlLaweFfD1AcS9vgQmQx4RRJJPwQkb0W5te1Chjm7vYVKGSmheuPxlHtv9HuyA/HPDWfH2Xvs5mCgq0ijOpCTYtw+an9sHvl8HW+JLviZnHNioyhcr0HsEW7eqHVvFijD6mboUPBdBuC2f2sUJbNzYmI0b4XO6AbupWvEk3ZuspVWdXew81pp1B7qRespV0V+Po0SST5EllJFPNKBzd020abU6/iwW43vaPnJfjKLi6mxmthzBdVFT+HPzMKasuo5OjZy8SoOty13KfnM2HtSQjjlbLmL/8SY0rXUg8ONOeFX7wg0jPJR1Y8fq52OPwS0BWFj9+Sc8/ngVMqyxVLalg60rsBKO/QWVS4h6cIdx7olpcUxfq96rexK9+OSW1iNqv8aTxaP9ytWrVaH1ww9O4rShd8IDM+GjOfDS9xDyPdQEPjbW33wO1GnuctjMTLV6PXlSczdcdZUGjqxYoUOJnTvhvfcgJuZ8BrX9naHtZzKk45/ExR7XYcCVwFBgHtpPSCqGpyfA+9/DxTboi/qP2oCZwM+G2r5HZfhzh2ZeNvDGWyGcyobOnfW6SkJenuZk2LEDdre8g1ZMhh0ZkJUKlXyFc5eAxZqgYlrR1VQhjb4sZd/awTQbvBiS5qmPXmsvXlf+EFWbX9dfylWfTKeoWH1e9yS2ZOH2CxjQbqHLds5wz3ZdJsWX07G/WnQH2flaD05dfQ3PDn+ddvW3ez0Hv0icA1uNftHQERw6BOPH67/TpmkS85Igol3s6dM1Of22bfr34ovQtmUeV7W9lat6TKfNiJ3qs7kOOArUBU53lNV/GWeAiCsz/icUX3Z2VmfGc7+NkI4NNgmI9G29SAq/D3VlZ1+5TRncSoh8ZTC4PyDS12B2LRaRL78UKS6SzMktpXncbgFVmbgw5WMQiTFmzO6/3+WUZs8WeZR3dd2ABuV2fc8Of1VA5K4LxsrsJwZLi9q77Ix1z9ZbZMPCHa77mTMvSYtKx05f3tpg1dvbF02erIvMmZqqpDho84PG7My0GJHiAv/HnnuebrvrU5Hq1UVAjs/ZKLGxrkx8xYoiAwaIPP+8yJ9/FEnqD231Wb+O2AxVTx+WyAc3POSXib/44osFkOrVq/u9z0ue6yMgEh2RJRlfVVLVSQenE2rVSmTxYt3HmFl6b+QjMpPLjHsV4VCmeEFERIQAcu6555Z4+z2w+ja9Z8uvFRGRnAd0Nm4M90jDhqpcMtVw0q2ay67PPPOMAHK/W1l1xgMPPCCAPP3007qgmz7keyK+FFCBmQseekh/a+RIl3fQ46+1ce/ef8/7DxcViYSG6jaHDzuWu73bMgmZfN+1jonSO0e5Pm9TIfO4sUF9pxmaSRaX55KdrUIrc+Zu1Cj9fvGFOSKVjNmk714M4KG4wThnU50ZFpIv4269065KemnEiyJT64k0b66/MXq06/579ujyiAiR/HyX4x78oofUjlVVaf82CyRvQrj3WajDOmMvoaEi+fly5Ij++7jlHf0yqJH9sA8++KDrM/eCSy65RAD58ssvHQtv6CIC8i6PCoicOhX4LTp6VOTyy11fqWXLHPdOnjZWhKOzu05lKfXLWLml79f2fetXOySzHh8it/fTMvrkJW+Wz6zc4ikiIFlES2xklhQeWRzQsUaPdrwSIiIy7zvHtaQmBv77SYtcrvv7u2+QBtUOesxUNqxxWO6+fLH8+sT1kjm+ksgkJP2rGAmx6gz2wY8a+LwXphrlySefDOiUPvjgAwGkZcuW3jcwnt+G11QdYLUUuSl6jPO48ko9+f79DdmKH3z/veNin6kmMskiy1/oJSDSpOY+l2OnjK8gVgvy1ltv+TxcQUGBfSb75MmTjhUX1BcBeYCPJDY2oNshIlp13WWIgC/hVxEQW+vWel1/tDXaOB9qysy9IlOjRSYh0z+YKVOs14mATKr/pFxliDNXNh2iX4a3CvyknOFUh35y02jtkrSd53v22kud66E2dN5+8WI9v8aNfZ+DzSYyaJAxtY7IRGR4l58FRD67+V6P465YsUIAadKkidfDxcTECCB79jipSAwF6tKIvgIiixaJyAcf6G9edpnX+xHQ9YmoFBhkQcWhIiApTT37dCtXrhRAGjVq5LL82muvFUA++ugjn+dwbrOVAiJzRl3oUCp/GuezvjnfEIR89ZWI7Fyp/4QgknnS6/ZeMf5p47lFiojIRx/pvxddZKxv1UoEJGnSPJk2TeSRuw7LeS2WSWRYjkcdBCIRYbnSo+kquf+2BPn+e5FD3y3SFc2alXwuxUUiY2rZr332jYMERBpUOyjFP1hKX5c73eeXRrzgcr6PD3tbn/fMeoEd1+gLyf0XuizevNnR1CYGWL3n5Gj/eQPn6M6f3+ZQ9gQL4xpfHPGiy/WlfVm5fNrB6zrY2/kqVUQMQaq88YbbdvFTRdobP14PkRHG92qIfItL36uoSGSovkpSp472B0ykpYlMnaoRHjVqeJazLo3XybQHrnTt123/WuSJSx0KRhCJReR6VKljLrsYkRl1Xe7FoUOq2AWRv/4K/LaY/ZcnHy8WqWbclGnvlO4ex2+1l/16HJbLamsERBqV5Y2HVui1TgkTObk+qMP+On6lhIXkC6jC6s4LxgmIjOg2w2/ZMBX+gFgsFsn1kPgFAaN8Fn4fIvWrHRIQiYs95nQepSifs6901JNHjshtxpD+wgtL3tUbUlNVpD10qEhYmGt5a1N3m+yv0Vj/uc2trTgdUVb/QgTDE501tz9TMGOkAbAQGZ7PtAeupmJkFkt29uOVn19wqG/S0uDjX3TTkbFgTvhagQfqwU0XaXm/805kzFjumjqPvUktqF/tMBPuGuWY4bABY4FMG3ToAO+843JKLVvCPpoBIIe9ZLkr5fXtTlTFV8s6u7mo4xy2vtWBt699guiIU6za2Z6uA1py1+VLSVk3RU34FvQvvSmfzQbL9+j3ix2mpeaMyH33wc03QyrVSAtVfwtOVoTImlCYCcnLfR87N0lTOANE9oGUFMRi4Z4PW5KerlZfn3+uvu1paaqeeOUVGDIshCp9jcxCjSxY+unXuxnHFwvuQgSfhpSm4stnRkfjPn+xUNVeN577AzELstS8fgvq2vfINbB5M/Ttq/sYxug9r7ue39AMS7LR6jf22/T5CtrYPj8VDk7S7y1Gk5EBmydsAiC+cicWLICGDeEohuzmhKuCJxCPL1PxZb9HxjH25TcEHB70dlx9tX7+/ju0fddY6KZiy8BhDDzCzfzWREiIQy7kbHDv9m4DXNfrR56/XMvAnV9/wfLiHxzPu/4Ijb1Pi9X/Tc+HCvVcYvJtNi27GzfqLPTvv8Pzz+vs8x/zo0jpYxhVf/Wl9/P1B2sInPMu78961DjfKdw14EvGjLoPgJdmvsTGr4fB3r1qlvGamwqoWTOV1OXnqwTNQFpGCEPenUtieh3a1dvKzIdGEBFmKjbczFhNY/vmzSE8HNOO6bgYX1IdSopSe3ydTAMgmRpUrAjR0d729I46dWDmTFXK1KqlSeH69IH7bksiMyUD2gKNUCPhl/VPXoHkJ6qz/Z62jFwymbkMZEedPhyo3YSh82bz/IFXuZcxrN53ruf9KA1+/haAhVxAxx4VCa3bN6Bj3WhYNf38s6FWveAGqBOm1zLhlcB/38nbJDmzOrePH8/hkw2JCMtjUPs5fHjDQ+x8txXxq5cxdmZfLh09wvC9s1C5QiY9mq4BcKi+/ChQAzG3z87O5q233gLwnmUJ7O+rqfa6rtcUJzWP8UwK79AHb7XCRx+V7Glz440werR+/ywXkoRaldVn7HiG+YLrMX4+3Beb+L+e3Nxc+3cXxVealvEUqhOM9WJIiCo+XngBVqLmz5adOylOTjVM+YG9n2u/whm2Qlh5PRRlM3bN+4x8ZBiDbWpQfsWES7jSsEb7usA4xoLdkF9CcgtvcKpD52xR1fag9nONlV7eEy91rgNetveW0dEdFos26BFhatq8CprVUg9K9dF0Pa5ZJ3lTodpsNvvzdVF8xWs521WgapdmzfBucB/s9Z08aa+H19YfDkBImudzCErx5XYOpuKr/c5tOtzsCAwf47O+Od+wnly6FGjRA2Kt6lW7bIbX7b1ijeFZ2La+41hOxzazDtbK2s9VV8H7Ty1n+Yt9yBhfmXWvduWzm+/jgcEf8/kt97D+tS5kjo9h9Ss9+eS5Zdx4IzQoDMDY3oQ1BC75HNRqjAuPLqBSZCaHTzZk1d6eurA0dblxn0VgyqrruJyZHImsyw38wDdLbiWvIAIqBKA0SdgJG4zneutTLqtMtdeIEU7eVyUgKkpVUwcwMjtmGhXOiSVQ5Lt/5hXWEArafmjvt5rYm9SccmkHD6vqP57G9O2rfoYAzzyjbRxgJCF6VDPyVgaOoCorgKuAcIuLgfkTT6jqLSpKE4PXcYiviI3VbuV336mqcc0aVeF07aD9jQ3xXRk5ZjJbD7dz9Ova3Apv/wrrf4abgWpoUpBJqFInBMPEHsg/6mKE//LLUFCgXfpBgwK/LSON3AY/TrMi3RrpP3N+CfwAzpjyHghs5ByOUJ8XfutKbmQssWTwy0chPP3nT0hxoSbXKgwse+Tv367lyru6UFgczrU9p/DDPTdx/6BPAfh1w3COnDRSiHspG851VePGjYn0l3CsJFhDoN1L/LT2ChJONqBmzHH+fHwoFouNmeuuYNPBTsGVT1sRzJ+t9WSLhuzLrcuECbrq1Vf97egbVarAqFGGVfVxmPDxToZ1+oOwkAJ2HG3Lz8maYOTEDjfzz9KqKP+XcQaIuDLjf0LxZcItrnvSvdcJiFgsNpk/39jmkUeUuW3b1uGp46yIstlEHn3UTvc+xjsSElIsK94c7sr03lRZt4mKMoKCXVFUJNI5TKeCiqJCyu36OjT4W0Dkj8eG6nn8XF/k8E9yZO8xGTlwuZ2lrhJ9UsaMusfVB8mL6sUvVv6iBwtDJCNZRHRGy2pMquzZI3LsmCqyltJbF06eLLLyZv29DY/6PvaecbrNXz3sM8aZNZsI6OzL1q0l3wv5uZ7Ia3rBOURKZdJk0dcTfO4yevRoAaR79+4+t0lOSJHw0DypwCk5VbeCg/ZvFyGy6BOf++XmitQNS5JiDKXQnrU+t23WrJkActddd5VwkW7Y8Z7es1kd5VSWTXqfZ5Pj6JTY/h/19y68UKQN2/Qcoi0uu5v+Xddcc43PnzBj+8ePH68LovV62rBNqlb1skNxsUi9evp7v/zi3Vvh3irGVF0X/9fX2yhDP/7ouc7tuMU/WOTKnn8IqFjwwAG37R94QI91+zCvasfnnzeKdpjI0qWO5Vdcocufu1j9y8SKyAFvRlT+ET//a7vCa/MbHezn/cwVn0gz9ti9T7xeq4j65YHImDEiouWrj9qtSd24HEn4qqvrPTbqATvef183vvJK+6Jq1cTuRSdNo+zL33rrLQFk1KhRPq+nW7duAshvv/3mWNhdVZqj+EaaNg36FtmRmipy662OV61e1cNavz3oNtUbwF8xFmkavkcKf6wReD3nC+0ri4DczecSoCBKRLQJadlST+nbb42Fhn+U9KgR+IGcFF/vXPeYgEjnRusl+5so12fv7Fnn9J6YCoereszweS/effddAeSGG24o8XTefvttAVXhFBT4VvNuWb7baHeLZcc7rVzLaPw0kY4d9V7cc0/g9yI/X6RXL92vZQPJGN/c/thPfV3BXv6ffvppAeQBd388JyQmJtpnsl08Fhur0d8g/pI+pbT3+/RTkR2oUuat3r9JXlamyNSKev2J81033vyc2CYiL175poBIXxapWqx6dZGiIjl5UsXnIRRKUSVDDTvJtz9jScibPUwqRJxyrZPc6w1neKvLvW3/4IN6bo88UvJJvPqqocawyviRtwgYPm1ux42PjxdQH0x3ZGZm2tUIOTk5jhVD1M/rKd6QiAhtmiQ72yFROXKkdNf388+6f+vW8vRQVVflhHueV0pKiv288p2Uuv369RNAfvTRrtl+qieRYTlSiQwpjjD6Dz885/c2zpunmzUwhWe9aumCpy/3u58LjPpbXrxGbDa76F5WrDDW33+/IY16XP93U6D6/DPro6cNRdm99wZ+Tj++ZMjHkLt7jBEQuW/wuDLX5RtnfCdgk620tbcV7/GI/HDXjSX3VUVEXlYlpjSv4LI4I0N9bsFQGAaBgwdF3uUxVRDe8IDILw31XI7MCu5AIjLpI+371449Kj2brxAQmXjvSP/vd6BorHKoIcySJ57QRaaquUIFkU2bxLVsPI1DjdMAjaZxKhvjxzua7GnTgjuVpGNFMuzCFAGRnl3TpbjQTSVk+kl9h8jtiNRClV8vuJVRQ6mzc6djPLNyZXDnkpMjUqmS7rv7XvV5llYVgzuICeP9fY5X1DfMJiIjRoiAPItG+Ywe+o2qH1f57qeZ+O2bNXal1zUXrJDCfdNFptQRGYlc1uwnAZEXrnzTZ9l44YUX7HXZ0KFDS3dNzlh2tfRoukqrmxEvikxCrj/vBwGRi7svCe5Yx5eIXGAUoPtHy4036tfyOE07DJVa2pex8t3dN8pLVV8QAdlepXX5qCj/YwiGJ+IMnE+Z8T9FfIl4hPfdfpuanNaqJXJi5V6HjtGfptVmk+N3PmevnZcNfFmkqNBx3NljHWFZX33l8zBdW2c6avhj+8rh0oolKjxbQGTvX994HdAv/WWDnRwDkY4NNsnyF3r5l/H7wmOGMWV3R2igGTngHKX35psiX3K7CEj+Uy+IHJqmv/W7n9AMM3HA9rdFPv9cBGR26MUCIq+/HvANEUlcKNJSQ1Tu4Au5dsAKn5s/99xzAp7ms85497FFAiJv1jCef0wFkY+e1OdfAs49V2QFPXW/l6/zuV2XLl0EkBdeeKHEY9phKxb5tYnIJCR329cycKBIbY7qQMlq1VZYlECIId1R7gzCUkRk/PjxAsiwYcN8/kyvXr0EkJ9++knDJozjVCZNOnXysdPDRqNvxna5h9iaJE5JD/Y6o3P57rve17sdNzurSLp0cfDYLlXYxRfris8/9zjMpEmO22MnJgysMPiu8HCR/Oax+s/DF3kcwy8KsuThi8cKiFzYK8HlnG2FhbK19oUiIPNCBsm6tT7CvExm7uabpbhY7GFPMTGa7KHEMGaTSXIqY23aiHRlrS6v5iDjP/vsMwHkSieSzB1ezaSbKzE8jN+lV6/gbpE3zJ8v0qShI4zmup6TJPXRWJkz4EK5Ifx7uYLpco11skztdpXkf/y8yMSJGgY3YYLI11+LrU1TEZCH+EA2jX+4bCdz4pCGDqHGzD//HNzur72m13DBBcaC9X86iNTDnhMlXmF0vop/sNiN68ffcWvJdblRNlZMnCggUrViihTl5Xj9iS+++EIAGT58uN9TyczMlGrVqgkgEyZM8LvttQN04HVV/xWeZfSLLwziI1YkOdnvcTxw9Kg6eoPYrr5aIkO1LTyweKb9HrzxxhsCyC233OLzMPv37xdAoqOjXVdU1RHQOWwQP69CidjXX+Mu3uRJufBCkcxFD+vzWnyZ437s/FiKfghxMTVfca4xKXfTTfZjde+ui3Z0uUC/DGteupMqyJSFzw8REKlbLU2Kl34cmP1BIHYJZgijn76QHXl5dlb4UP+LBETa1NvpcVxnEqmw0LXtPXLkiAASGhrqSly2jxEBuYYp0rq10w6dOun5zZxZuuszw/nvvlteujfB0Xhku/aZi4qKxGqkp0x0innr2rWrAPLHH394vSXpiZrs5UE+tBNsJYX/njrl6IIePCgio41ESgMb+t3Pcd3FmjABROZ+K9u369eoKKfoejP28YorjH2CDBG9+mrd//33AzsnEb3uDhpat2v4FQIiNSufkML8kvtf/vD4TYukC+v0fEIc4XCrK/UT+dI4/z3jfB+gQ2Xd5zHXvtOYMQE/Mq8Y11H7vpsbXiqy5i49j3WjS97RDee22qLdznsWyh3DZmvTf8vPZR+YFxfZDeRbsUPM+dDCQpGBA/Xa69cXSVw707UsXItIjCfhtHjKPPsQ7KWXSndKCQk62Q6a9MoF7uTsRFyJNzdy1oy4v/TS0p3LTTfp/s+N3O5o31MSgjtI+nG76X57/nZ0k41x0dHm54vFeFVHnf+tihnip/g83O8THKTX1RescLw7j6mgY3+X3gIicbFJUpDnfQLrnXfesde/jwQyoeEPR2fLypfONfrVxZK0dblI/GTZM/9nux3D6r9KUjo4YeNjIjX1fh3+/Hc7cbk+uCjQkmFPLGSRtTfqQOOIpY7kfxcWnIDkfwBnia//GLKzNVsDiCytYQRlX+R/IJuVpfYGz/Cao5Pz1FPasmVkiDTVAZZcdZXf1m7ECJEj1NFt53xT5ms5uP2w9m2sf0nh2nXeN0paJIXfh8hnN98rsRU0I1BYSL5se7uNb5WAL3QyBv7PXuFY1MmTT8jNFXm96nsiIFtaX60ZNyaH6u9k7fc8bn6qY33GHrHdp9NHb/GEdOliZEMLBu/pb6+gp4SF5MvxQye8bvbJJ58IIDc5DSycUVxULM1qxwvYJCXOeMbOvhwl4JFHRJ7kTYMs9K3suOCCCwSQMYaaJyAcmSUyCSmYXF0uvUQbi8sjDPVOG0c2pxdfFAGb5IYYiqKNc+3rpkyZIoD069fP58+0atXKQXBsmi8CUhAaKmDz3TlYtUp/q2JFOwFnR1qag2z2MAhzw5PqV+aRzdAPjhwRqV3bMeNTZPbzWhvedHPmuGy/erVaZ4FjItsd555rjJP6v6hfaocZ8oHAkL7qfakUmSEg8ucfboXZMMjLt0ZIE/ZJzZqa2cgDfxjZ3Fq1so+7wsM1y1FAMC/CKRvPBReINCRel4dhvyYzG9lFfurFBg0aCCBr1zopGWuokqI7q2XEiADPqwRkZxXJo8PH2dVyZgcORLo1WSNb3mzvm7j/7DMdzNBdxt7+gEhRGXwpvnhcB1+0EFBlazCIj9dztlicLOuaRRk9/msDP9DGJ2TuUxcKiMREpau6KUD1bmGBTWIqaDlcO8v7dPbkyZMFkP79+/s9jddff10AadGihQcR4Yxd6/eLxaKTTZuX7nZdmZbmkJUEUa+6YNky+4j/lYqqaFs1a6N99aeffiolkbhbt24VQGrUcKqji4vtRGd9Dsl995Xu9ERE5Bv1WFxh1QFGt87ZcmJsdZf2N/fbCLmi23R7GRkzRhyef9On2w9l8t8v9/5Zv0RbNGtZsNgzTp68RJVlaxoYo73ly8twkU5o0CC44y3UrIU2i0W6sUYiw3KkuMD1Xc3Ly7MPvNLT013W7dixQwCp6i5Brq71UQ9WySWXOC2/805HH640OMfwYZoyRT54r1jyMdszz3fKJIe3bdtmX2a2qYtNX1A37FqzQ6wUSbyloY/RvHeYVfx334nI5DccbVUg2LHcIIEQyU43x9gOol5E5PffdaHzjJfTYNCD9HKvj8xZqV9+CeycTHz7rZaPuvWkViUlBedMLv2otrioWOpXPyKfca99gi71y2lyCp24yatdU+QdNLv4US8T4nvXORRMTs/cZnOMLfwkRPaLzW//JQKyzdJOUrf8offy1wA80Zywdu52e1uZdOC4/HD9GKnAKb+TwAEjYYt9DBRFtos6PjVVpEULXd2jc4bkfhvhVwm4/8PGUq2qZha85prSEYUmTE42NtbNVy0Icnb9ekcbXWKEiQ/Mnq3HqFFDxBZn1AvB+sJ++YQIyAEaCdgkPt5Yvnev0VcLkylfZdmFq1f3+FHyJ1dTf0g30v73CWskPDRPh6f9VzpIL6fIDFvz5lIr9riAyLTPvfcLxo4da69/XXxdg0VhtsgvjeWqHlMFRNzno24ZtlRAZFBXH+NZb/iykd6I0BC5eUSmgKuFY7nCUAUXjbPY34M/Rw8VOTTjNP3gvxNnia//IHbsEBkUsVgEpNgaIrLdf8pgk8WvU0ck6+X3HeTXgw+K3HCDfm/YUDvyfvDUU+JIS/tREHJvH5g7ZZ3U55AUEqI1fna250ZOqWNPjK0u/VovFBC5sfd3XqW+PpGSYB8IyCYN0di61V4Pi3sm+5XP6kD9b0sHDTub109/Z5eX8MAD3+u6P9qJiEhiG53NvjVkgqpZgkVioj2coQW75O1HFnm/pJQUeeKJJ2S7j+c/f9oG7fxFGHEEkZHaugeI6dNFWrPdQSz4MLL++uuvpW3btnLAIz7PC8wZ6VkdpegHq1w7aIP91PbfahCz11/vdGxdlBChKjiZ4Zht/f333wWQbt26+fy5WrVqCSCbN28Wmam9i+SKNQU8PdjtsNl02g/EQxozcaIHOecTBnERbCu2bp3eDzCibYqLHezWPofS8vBhVX6CyCWXOJFkbpg2TbdpUDVTbJFGgzczwIF6fpq8d+OzesnN01w7d2lp9hPIfe5VO4ncvLkX8cvx4/Z6J4Z0c9wVGGw2lYaBS4/uuutEKnDKUZ+dVEfZGTNmCCDnnXeez0NWrVpVANlhhnUXF9tnKRtxIKiotRJx+CdZ+0o36dBgs4BIVHi2fHDDQ1L0Q4h/sicpSYotOv33WNe3RY7+WfpzGK7hah/yoDRsWLpD9O2rt/nNN40FjxsqxHYxgR0gJ0lkRnUZ0W2Gvn+DPvEfkuUFl/XdKCDy+r2/e13/xx9/CCBdu3b1eYz09HSpUqWKADJp0iS/v3fTkGUCIpeet9pzpakMbdVKxE+oZIn49FMRkEJCpDdL5dfxjrT0JonrT9W7Zs0aAaSh84NNcSh5osiWl18u/enJ7t3a1wiPkNpVdRDSovYuI8mAJh4w2+Xw0DyZ9vlqkV27HI2rU19sucFP1KhaKDbTuDnYgZXNJjKro5zTaIP0YYnj/X/mmTJcpIGsLMfx3DsF/mDEp2ykk4BNjmzf5bFJWFiYAJKQ4KqgWL16tYCbiXxOlp2cqEWiPPSQ0w5ffeWF1QkQ6elil1scOyaTJ4scwmjr/hrvsXmLFi0EkCVLHOE79erVE0DW+5AkLJ6xWi7lFz1mlSre+3Ve8ISOl+W220QjCsznEEh0wVgNsZNmGrJ57bUGJ/+S0zY7dujCSpVcWYpAQkRtNpHKlT3aoICQl2d3Nf/iXA3zGjVsacn7+cCy3/6WCHIlFeN85s0TEZHHBm6SgxikbYUwkUcRmVpJJM3tfJ+6TLdpW8n1uMuMXSuUOBTwCdsurStOUUHefzvHMSGcuTfgY9x4kda5NwxepiQjyFfcJuc0DVBZ7A9zvxQBSaSWgEhSkuvqPXu0yILI9ef/JLaJ3gmnjK9ipE19DYHv2tVzfjRYFBU5eNXr3IMrAiRnTaFqAFH+PlFQ4DDgP9zTCMW/vgRLD3cMbWrva/Tu7bTcZhNpZJA8f/whM2eKhIXZBEQuPuc3yf2uksv1/fHUdd5JLxGRJU71PsjrN/4qINKv40aP0xER+eGHH+zE19KlpX/3ZNPTEv9RQ7FadSLTfXx3YOthCQ1RMnTZbwFYimTsFrlVr+FUp572S/o7eDeSwGGMwdKj9EE/2+4VkZPe79v/Ks4SX/9FFBdLSkNN3/Y594iPiTcRsU82idWqdYWIOPTM5p/VGtDs5rffiozHCDm61/+MeiD49LnFMpyfHecx2Qt55Sb1XfdqFwGR0JACOfRx/cAVX8YshNRxzCCaHS1vvIRtr3a8comQq0YUiWx/R39noZcByJLLdN3fL0hiokiiRcNXxt/l2xerRBihba/ztDSJOyjFRYErdExc2U8zK61qaITm3XxzUPsfPSoCNtmHeo3Il08EfQ4ucOpgFv9gkVv7jjfGRsUya5Y4dNpOoYGm98eqSKMR/uBu+7qFCxcKIK1d4kAcsNlsEh4eLoAcOnRIyVqQ7bEdBUTe8ZewxvTOc++FmKlvnvPvWSIiIr9qRrQSvcC8YOpUx2sx6W1jEBsSYh9gZ2U5rIXatxfJzPR9rMJCR39je8f++mWwn4xlzvtueMmeuearL9zK4L3GjHPLliJ5eXL0qEMsce65nuOdrBp6EgOY5zP60ysSnK7fyWvG5B3yrcbM5JZFIiIyZ84cAaRjx44+D2mWi8OmfCk10X7Do8kqG1HgDYd/koLpjeSnhy63EwaBkD0nztH4iw8qPSSy5m6/2/pEcbFdPTKY2eLHEs8vTC8Tu2fHnrVOyoESZuNtNpHFl8jRz2rbwwG2LlobdIbez19T4qtvuzVe1y9ZskRMJZcvvPTSSwJImzZtpMgXWywi+7ccsp/runlukws7dzpis4JJneUNNpuGVYNM4Rr58pUF9lU//fSTANLLT+ztokWLPOvBLYtEQPIs4QIBi258n58xGjo4cak0qJGgTWmVIzL/6QukU0N9JpUiM2TBMxdouX7nbb03A12zuhUUODjspAvP0y8Xec906BPJqyXp85oCNlnJuY6K0u23SgVTNuGsngsEx4/bJyeaslcWT/P0efEg2w3MnTtXAOnQoYNjocvzs8mnnzrt8PffDgInCOWuiDiUt801xHThQpHVGPGn4z2z4Pbs2VPsVgEGYmNjBZBduzzJPRGRHz9eIJ9ynx4zCLXzLEPwbU+aWNuo1ye7p9vzgluMcnBZK7HZHKppF5+qnBxHWTnhpqIvKUQ0JcWxb4BEngueeUYEJK29ZkaOiUqX3FOlU/Dee+ViuQbN0CsNGtjLwMKFItU5IcusxuS0BZGrEZlZXyQn0XGNLYxJtOeucDmuUQUp8Vha5OWJzSBWuzU8LkV/XaBt3e7PAtr9+KETdrJjzZxtIo8pobmNNhIdkSW24jLIqkRExmi5XMm5EhPjXaW1YIFTpsern/YgnIp+CJEhHWdpHeiWwbEsWL/e4c/lJuwvkZxdtEj3Cw31obgPAvcZr+5n3T/RL008/f98Ij/XnkG8Hwtl7Fi39Xfcocc0mPzZs0UiI7SNvaDtfMn6WjMCz3p8iL0cXNl7gWcIo5l22Pg78dVEu6p++2pPkvWXX36xE18n3N/9QJG2TWRyqDwy5D0BkQEDvG921+WL/ZJwLtjxnkh3vYbJrV8W0IjqM4H0bhpOfkfIOMla8eKZ+dF/Cc4SX/9FTJggApIdFiPVOSF16ni24yIqBKtg+Jm/5u4h+/XXjpm/V14J6GdXrhR5ijdK11n1gtFXLXYNvxwyxHMjL1LfC9rOFxB58KIPdVkg6ZsvNdyZr+skIjrDUseI2vRmlSFFRVIcrh2ExuyXhb/F629NiRApPOXYrvCUyI9qzmw7uVmuH+LwkSo46YeNKAkzZoiAHKGOWCmSuVOCk8YnHjguoSEFEkuq/TqCdrsU7Vd9wEO6/7DgJOsusM9aIbaJyP2DPhYQsVqKZMaDV+j6Zs30d+yZGxzCgUkhRq/MyZ/KVDo0sDviuuLUqVP2xi4zM1PkUc03PSf2EgHfPuwiojGEoE6v5nTeqVNqGgIiGwNo1DZu1G1r1gzkDnng5Zd1934hxuxWE33niouVrDUPffBgycey25vUXapfwhBJKkGhl5ssUx4YpePAarnikgF6zRpH/eEUr7hjh2PGdPhwhwpt0SKRqdZrREB+O/f14MIC/tLwCWnl6rH31lu6ODnCCDczFAsrVqwQQJr6cKjPz8+3l4tUUwG5dYnLQLNMRIEvBOK/44asj1XyuIV2cvK7NuqNFyxW/Wq/tkhySh2Vl57uUCJu2GAs7BirCx7xUnc7Y983IpOQV656UUBcZ4KDwN7tGuoYFpIvWYnxHus3bdokgMTFxXnd/+TJkxITEyOATCvBifiO4Uu0qevuZQLDzF1/8cWluQxPTJ8uArKM8+S1+xzh3CYp0q5dO5+7zpo1SzxUbnM0PPFYaJzvNi4YmBXO83dJwid1pU3dbc7jDqkZkyQbXjvHMSg7V32N5BNPhbQ5dzDhBr1miULkVFrg57JqlPxwz/WOSTOzHoqNLVu8kYhD0Xv++cHva8xEXMxv8vWrnupMM7x6zRpX0tZUqPZ2fimmvSsCsj9UE+TMnu20Q2Gho2PnJRGRXzyuIc9y++0iorv/wqVGP3Ckx+YXX3yxOIcH2Ww2CQ0NFUCOuJvrG/joyb/kZ4brMb14UvpCerpj4H/0qIgMbKT/jPYxwnRG56q67avX2yOqwsO9KHHq1tWVq70oOP1hzRqxMx2lwaFD9ovrX3mRgMhPX6wK+jAFeQVSPSZZ/sKQ9zz/vH2dzaZNZBj5srX33Y6Xsyci05qIzKwr8iEOUmx8TTtxcuKE3i8ou7dQcV0NQevBKvl9zHStDxYFVk++OlrvTfeWhkrN8FPNJ0xCKJSj+7xHHQSMR9SPdBLXiR9RsD1UFkRmPnm7C+H08CVfarUVper88oSZV6NpUy9l10f/wWZzhAkHk3fBF0xVbuMKxxw34eiewHb+Rcmyk1SRiJACT9GsGX7Qtq39mha/eqVUjNQQv57NV8jk+661k15XdJsuBdMbufaV8vNFqhrvuzmj+9JLcllvNZsfffVij9OaP3++mOHkttK0EbZikbm9JXN8RYmJ1oQqPiwO5fCuo/bzXzC9hHHCX+eLROs9PpeVYrEEX6WXFqYlz9s8Lj88/EjZ287/EILhiaw+kj2exZlEdrbm3QVCX3yOmm1qcOyYZki32Ryb5eRoCt2cHBg4EJ5+2u04t94K8+fDmDH245WEli1hH80AKI5PKfOl7ImPph3bHAvmztXcq87wkqr7yYvfBuCrRXdwMqsqxLQEi5/iabPB8r36/WLNqb5oERw7pmlfhw71sk9ICNaWmka8Fbt46LmGFEc2AVs+JC1wbJc4B4pzoWITfvyrAwdn7wCgoHYDwqpWCug+eMXFF0PVqtTlGBcyny/GFQS1+7cf76CoOIwXa72FtSAfOnSAc88N+jR69YLfuFT/WbYfCoM7D0BTPm94EOUa4Nlpr/Pp3AcAmHDXKK7oPhOWPQD7NB08nTrZd62vmck5VNxAvxw9al8XHR0NQHa293TZaWlpAISGhmo642PHADhQ2AiABg38nHP37rpBdjb89ZcumzMHcnOhcWOXc/QJ8+RPnID8/JK3d8Pzz8O110KjYk2jnlNb06g/9xz88guEh2v67YYNSz7WrbdC5crw09HeZNSqBoXAZ0/43Ud2vMP7f9wLwH2jw7FngC4qgrvu0i7RTTdB//72fVq3ht9+g4gITet9//2wbRtcdhmstnUH4OIaa7BYgrgRO/Sdom1bl8W1jIzpqSHV9EvSIcCRuvrUKe9psp3Li1mGOLrXOFZVwGI/drnCGgK1+kGj6/QzgHTXFW8aQQFhtGcb2xdVgdSNwf/uzK8AWBHShzyiSlMNAFp+hg/X799/byy86hL9/HmR7x1PHYQND1JUHMKXyx4B4J57SncOTVvH0DjuGIXF4Sz5bYfH+piYGACysrK87v/BBx+QmZlJhw4duOKKK3z+zuFdR5nwh96o556PcF3555/6FxYG779fugtxR21NI16bRI6fcLRllSppG+LregBycnIAqFChgmOh8S6koOnKy1yezztPP1evp161oyx7oQ89m68EoEnN/ax48Tw6N96k25wC1hnt+iWXeBxq8GD9/Obg5VDVCrnAj+8Edh4FaXDoR+ZvGcAbGP2Wxx7TCic93dGGlBY7d+pnq1bB79umjX6wg/37bB6rzWfpXi9lZmYCjrILwD69f/uKtb/VtKnTDqGh0KWLfl+7NrhzXLJEP/v2BSAuDpKIA6DocKLH5tWqad168uRJAAoKCigqKgIc9aw7kpKgLkY7XbduwKdWubKjWV26FOh6jv6zcZuvXRQ2G+zWtp7zhtgvsXt3iIpy29a8kfv3B3xeLtu7PIgg0KABXKr9qFfjtD+rFqXBYcGMv4nMzGUg83TBqFH2dRaL1quFhHNd+ljk87FaVlYBTxyAhKOw2ti4DRCVDMuuhISZfPMNFBRAt26OolVaWJs2AaAx8Xw6w3jZjy+EYv99oML8QsZObgnA/Xdl6MJt+uzDKaQp+9nzd1LZTu7gYQDiaUyLFr43u+ceGD1av9/w6ZdsrrUOek3m6+M7+fD3OwCYMAG6di3b6bjj1Vf1ldm/H15/3W2lj/7D77/D6tVa1p97ruzn0LOn9injc2qTUd3oW/32ZWA7T/8OgD+4mMHDwjCqDwcuuEAL6vbt2h9PXkbfJjNY8MwAqkSnsmpvL0aOmUJBUQRXdJvBlNHXEVZwEJKXOY4xbx6kpmqj9tBDumzNGu69LwyA73/vxKk01zq2W7dudOzYkbvvvhtLUJ1PAwe+heTlfLPsHjKzo2nZEoYM8b5p/ZZ1uHOEvmjPvxiC2Hy85/mpsG45ZMOp0MqsoxsjR2of+kzA0tbRXk1eOADSNp+ZH/6P4Szx9W/Au+9qhdG4MeGPPcC0aVrhzZkD7zj1He+/X+uWuDj44Qewent6F1wA994LISUPwACqVoWUmEYA2I7klvlSdh+qRVu26z8REVBcDFOmeG5YfwT0mQEVtBM1sP08zmm0kZz8aMbMGw3HF8Dujz33M7FyJqTaIBwYfh+g9wTgmmv0p73C6Px2jtrFli0Wxq97TZcf+9OxTcJMAI5XuInR91togw7Gwju2KfH6/SIiAkaOBGAUE/hlWTcSDxwvYSeFrdjGl1OaAsIomaoL776b4NgGRc+esJzenAqJhkyBud8GfQySl0HOEQCmr7mSN3/TAcvYW+7mxj4TAYHdRke5fn2cW8sKFaB6dThCPV2Q6CBczY53ScRXlSpVtLFLTAZgV452Xv0SXxYLXHWVfp82TT9/+kk/R4wI7F5Wq4adLTpypOTtvZzCN99An9ra6f5te1M++wzefFPXjx+vxGQgqFQJ7rwTwMJ3EQ/qwkl/uLLlzshNZPlvG1l/oBuREcXce59TBfLZZ7B5s7LG777rsWvv3jBpkp7/2LFahjIyILd9D72utWuUNAsU2406oo3rOxWn4zVOiDGqT9J7XBLxZS4PDw8nPDzc2FeJgmRquhz7H0dsLNvqaQ/LtsoKR38L/hgLlKD4tegSwsMD42x94cYb9XPKFCgsBG59EUKA+DxY9avnDmKD1TdDURZ/xj/GkaQYqlcHP5yTX1gsMLCP1oPz5hV7rDfJhezsbIqLXdenpKTw8cfaTrz88stYvTaKinde2EdhcTj9O23ivIs7OFYUFMAjSt7xwAP4HT0FA4P4qsMxTiSH2heXmvg6rvXpcZu+GzVrlvH8TOJrwz4QqFoxjQXPDGD6A1ey9pXuNItzIhL+Bopt0K4dNGrkcahBg/Rz5eoQ8gcYo+ypkwM7j/gfsBXmU2VjJm3YSWFMVXj2WUehXreuNFfngEl8lWb04UR87Tvozrj4fpZeia94vZ/7pQlWq5fJje46iRAU8ZWVBRs26PfzzwcgNhZOWLWM5Cake+xSvXp1wEF8Odep9kkDNyQdDy0V8eV0Wkp89b5I/9mR7LudAti6GLIFQoFzh+u+TsdywT9FfIGdSTn38FwqkckfKzqReTIzqENMmZTHTXyPFVHyskkTl/U33aR9pm3bYEX7u2HeXIixwEHgeWChsWFPMCcii9c+wrhx+r20ExIuaNwYgKYcYO6iSuxK6Q3FOa7khRf8PH4dx1JrU7NyMlfd1RXS0lwmOluzkz07grtfHjhyAoCDNKJlS/+bfvihigZycixcektXpq29jnue1DHBSy+psKC8UakSfPqpfn/nHcecny8UF2v1B/Dgg/ZmpEywWuG66/T78gijsl7wV8k72mzIgi0A/Mpwrr/eyzbVqkHnzvp9/nzIVbK9e9N1LH6uHzVjtG0f0e0nJb1ClWQ3twMcY8RrrnF0gNesYcCVnWheJ57M3MpM/sx1gjAmJobNmzfzugebGADykmHTExTbrHy8QMcuDz7oY0xt4Jk3WxEZlsvKHR2YM2WD942OzYatWq/NK+oPIaG8+GLwp1dqOLVXc7cOInnznyXs8P8TZ4mvfxpHjjjYrXfegYgI2rZ1VJTPPQfLl8PEiTpgtlhg8uRymO11QmhLbfjDsgvhZPCDeRO5WTkcTa5FS3brAnN6xWSk3FF/BFx6EAYswnLeZJ54SgmFTxc+SU5+FGx6VCsSb5j5tX52rgnRsWRnOzgMcyDnFQbxdd05uwB49osrSMuOhWOzdOBeXABHf0cE7vlwNKmp0Le60VK1KSPxBXDLLQCMsMykou0U33y0M6Dd5v64kYMn6jM08k9iTxyC6Gi8t0Ilo1cvKCKMvyzG9MaMUhBfTo3WpBV6Ho8MeZ+7L/zCsc1B49PLqLx+fTiK0YE+4ej4mB3vvLw8j0EuQGpqKqDEFwDHdRYxQeoRGhoAuWH2bH7/XdUEf/yh/48YUcKOBiwWh+orISGwfdwQFQXXdddO94b0Jtx/vy5/+ukSyq4X3H+/TgC/dPg+bKEWJSsWTvS+8fY3+WCWksQ33WSlRg1j+aRJ8NRT+v3tt32OqK+4QjuOAKdOqVr0tVnnKMl+/HhwRGAJiq/EYqO3d0Jng53JD5uXAZM5eHNRLBikWWJxnMux/w04OUh7oc3j90HCL8HtnHECtuh78BcX0bmzH6I/AAwaBDVqqIhx7lygdlPoYdysbzxJUHZ9BCeWQmg041a8AGi1VqZzGFoZgLmrmmsd7ARn8sCd+Hz33Xc5deoUnTt3ZrgpXfOCxAPHGf+LkrTPu8+gjxkDu3frTXj++dJfhDuMEUsUeZxKdpTZkhRs4IP4StZ3Ickgvspcns2Ck5oB6bUAC1HheVzZ4yeqVUp12tACWwzSx4vaC3Rc3Ly5CkfXtH5UFy47BFmpXre3QwT2jmPbgbY8kvue/tozz6hUqFs33aasxNcubevLSnztP+IudQiS+DqsA/6DNKJBA1X3uqA0xNfKlTpSbtTIPutjsUBupaoAFCV6kgruii/znYqMjCQ0NNRje4DkE+HEYShz6tUL/PywC9FUtdXnSiXV022wZ43vnZYZhHuTaIiq6C5qc4VJFP0TxNcFF0CrVoTk5vBo5Q/JK4zi1++2BLx7blYuPy9qzygm6AKjf+iM2FgHaTF2LNDaAq8INAAygWT0nnYz9xDmrGnDwYMWYmOVSygzjHvct0E8AJ8tfUmXH/NPnnw6Tvtzd1+7nYgKEXa1l4k27GDPbj8EaCA4puW3JMUXaF9p6lSd20hI0HtTWKjdwhdeKNtp+MNll2nVWVio89X+ON8pU/Q2xcbCE/4F/EHBLEMTjmuEDKv3lLzT6l+xJBWSRwQrKw7yVf0rmwiq3IpyMHUdGmxl4+udmf7Alfw4+loH6QWO7XJyNNzBPMmOHY12KRVr/AHuuVEnMMd8W8u30ipYbHoMClL5bdcDxB+JpWpVJZj9oXaTWtx7tdZZz79cwfu5HP0dturXeQzkppu0XTxjMNq4Rhwk3FbAtKmFwU1I/z/BWeLrn8azz2qoVe/eLlPmt96qvEZxsVbOd9+ty194wSUKqVxQv11VThjhE2z1P4PjD3v/TqApB4igAKlQQWvt0FDYuNH3NIeT1PfK29rQuDGkpFXgm+1fqbJgxbWQ4WXf+av0c5DejJ9/1gi2pk1VjeITBvHVxrqLtm3hZFo4r/z8iqqX0reqfLswk2kb7+TnP6sRGgqXNCtH4uucc6B9eyKkgGuYypc/NqO40JPgcce4cbrNy7U+0gUjR4JzpzoIdOyo5MuMIqO8Ldwc/EGMRiu/MJz52y4E4IbeboTLIePznHM8dm/QwIn4SnYoDZ1nnL2pvkzFV9Wq2rEnRfc9Sl3q1g1A6Nitm061Z2fD449DZqYOUIOJFTNlZaUkvgCijmmn+0i4drovvxxeey3449Svr522NKqyqro+Bz5/y3PD7MPsXbaAXzcoOfDwIxatXB5/HG64QcM2L7sMbrvN7+89+KAKwi66SKNFq9WvoCG3AGv8DGScIeKoD9zeKXMwf6TQ6BQlq6LPmdDyVi68El8GaZYk/z7iq+Ztl5BNBeoUJGLbsFVDBwPFL59BEaREVWcPLUod5mgiLMwuRHXMUVxrEsRrXHvp6dvhb50hja8xnr/mKTGjysPS44JLG2G1FrPzaCuObFnvsi4iIoKwMA15MAkFgOPHj/PZZ58B8Morr/gNd3jvhZ3kF0bSq80W+l3eybEiN9fx4r3xhhIu5YWoKAorKDFiOZlnX2ySJYWFheT7CJc2y7gr8aXvQgrViYwEH1FpgSMiwkEu5Zp9D/d7aIEigS3Gcp8jH0e444/Hr4IaIZAHTPFSFzkjeRlk7uTkL7WozxFORNYn9EEl50tFBLmjqAj2GpYIZQh1bM1O9h+rD4WuBJcvJapX4uuIEk3xNKZZMy+/ZV7v339DXp6XDbzAByNUWNXoz530rCt9EV++whwBipLzsSLYQsJwzJgEht699XPHDkjOqwqNDRJ10QzfO61VRSvtG3HoEBw6pG27177dP6n4slg0wgK41/otIEyZGvgMwJ+TNtMxbwvN2YdUrAhXXul1O1O1NWMGJB9JhRrAi0APY4POgNPjGztfdxg1StViZYah+OpS9QAA3/11Ppk5lSDRN/G1eckulm/rSGhIIXc9brx7W7e6bNOanew54KmkDBiFOXBCyZRAiC9QUfsff+gnaGjjt9+WKngiYFgsKqqPjoZlyzSk0hsKChwE3BNPOM6xPNC+vc4zzi/qr7rAIwWwvwSbhR8/B2ABAxh8RSXPMGMTJvE1fz5U7w0V6mG2JXWrHuPKHj85kV4WqFAfavTRf3//XfvjjRtDjx46I2AqyNasYdTDnYgKz2FLfEtWzXYtPwHDVgzHF8PBKbDrQ4j/HrDw4YKXAXX58CF2dcGTb7QlOuIU6/e24fcJbu1ScQHE/4ltt173opCB5TqPFhBq1IBq1bAitGQ3kxcNPBvu6AVBEV9vvvkm3bp1o1KlStSsWZPLLruM3bt3l7jfkiVL6NKlC5GRkTRp0oRx48aV+oT/p7B+vcNY5YMPXGpeM6SoRQuNgszOVsLrdLxILVo4fL7YWfrZ1T1bT9rDHC1t2qhyxAya9qX6ckJoqFp7ALz/00iKqvWHwkxYcgnkOfmPnTgE2w2/gKvudTn8jTeW0IAZnV/Lrp189JEu+mzuPew82kpVX0d+5kRGDe77Wn1enn0WYhLKkfiyWOweDrdbx3M4uR5zpvhvfI7sTeSPlV2oTjKdjxkd3bvuKvUphIXpeOcvLsJmscDhfNi8oOQdnVGjD0TVY8nOvmTnV6ROlaN0arjZaQMLJOhg1Zviq0EDp1DHNBsUaEc/MjLSHq7kj/iqUqUKFBdBqhKCR6nrP8zRflpO4Y7jx+vn5Zf71zi7w1R8HT4c+D7uMDrdz3zdlDff9BO6HADMKK0XTzypX/7aqaogZ2x7lY/+vBcRK8OGQataaWqE956qLHjmGe1VB3ASjz0Gs2c7RTwFO0A9dkzjJENCPMLKatTQR3TcDHU8qc/buVx4C3f0TnzpPUimBpUqldMAoJzQtns0f4YoiZA2v4rOFAaKWb8AsCjiIsBSZuILHErDX3/VR8NNz0EEcLwI5hmK0OICWHWjeiLWGcZXc69BRPu8XgfyQaBKVSvdWqmaYN6vRz3We1NJvf322+Tk5NC9e3eGejV1VCQnpDBuhhI8zz9TgMXq1EBMmaLeIo0aeVVblBXFNZV0DU3Ps8+8OpdRX6ovr4ov411IoTq1apXTQM1kJXbmuVgP2FGhHoS/BJk5+nKa77oXmOGOc+ZZ4SJjsmPqj/5/f+84yIEuBtm5ZcTLjlByk5TbtEkJrNJg/36VWVSo4Ki3g0HTpkhoKBXJplLuKVIPx7usDkrxlah11EEaeedaGjbUe1xYqORXIPAlhaqlqt3QjByPXUziKyVF+1QlEl9iIzRNJ5gKa9QKuqGqXl0jZEEH/XRQEoXVfiZZtxi+bl272cMcu3TRsDEPmDfzwIGgzqtciC9QqUh0NDXSDtGfRczb0IkUg+QsCVN+hFvQ+tVyzTU+R99duujrUFAA3/zcURdGAvcDLwBOEw+Hkhswa/MwwDFhXmYYiq8qaQdo3RpOZYcxYdktkLEdsr1PAH76nhL1V/ZbR52mhhTfVHwZMYmt2cmeQ8ERqS6IXw8FUIyVwzQIWF3TvLlyNE8+qbzLmegbNGgALyvPwuOP2+cxXDB+PMTH6yTdAw+U7+9bLCqoSqcKe6MMIvK38X73sf2lAoNfGc4NN/jZ8LzzdDY9KQl27vLwcHY6C/3o8pHDD9UMc7zuOkej1sNgdFevpkqtWK4bpKGFn39SirDYhJnwWyNY0B9WjoSN2mHekHUvy1bHEBoK990X2KFqNqjB/SO1rXrhtVhsxU6TgsnLkK1ZWG3CQRrS97ZmJl985mCx2MepbdnGyr3nEb9q/hk+iX8/gmrBlixZwn333cfq1auZN28eRUVFDBo0yKcfD0B8fDxDhw6lT58+bNq0iWeeeYYHHniAn8y4tP+vEHGMWG+80dHJc0KlSjB9us7s1qmjEUkBWncFBWeDe3ZvL/Vxdu/Id/h7mSFM5ohq0iT/+l4Dt9yifb+DBy1MS/wVohvDqQOw/EoozFXW/tt7wQbUC4d253PsmDZigP/KGewNLikpXNgpheHDoag4lIcnfogcmAiHfuS+CWM4mVGRjh3hmfsyHJ4E5eVQeP31EBJCN9t6WrKLcV/4vy9ff7ibYlsor8S9gbWwUKeoyuhW2rMnZBDL7qrtdcGPnwZ3AGsINLqOPzZdDMDQjn86DcQMlcARQ2LrI9TxBDUpxqq2FIe1Q2SxWOyqL28Eh0uoY8IuKNbdk4gLjPgCTyOHQMMcnU8eSq/4Sk/XwTbQfngTnnoqsNkmX+jSRcc9C239SYmuocbSXzglt8jaR+qWX/h2qQ7snx+xXeubuXO1xzd1qrqulrZyMQfDgSq+TLVXs2Ye8XFhYWoZkWwqUFN1QGmxWPz6fJnLXDxqDKIgmRr/KrUXKMm/qaXGHkRuzIcEL15avrBMw6MnZ6pKpzyIr86dtXrLy1P+k8o1oW8jXfnVmzpTuuY2SNsEEdUoOGc8X3+jL3x5Da4GXqDk97zFni+DSTCYhMKxY8cYO3YsULLa68OXtpKTH03X5jsYfJ1TvSni8BQIwhczGFjrKZFUIS+Hwpx0QBNzRBlT50ERX2l67cnUKLu/lwnT52vFChfrAXpN1s9L42GNnjfDhvm9R/376/t74AAcudAId1yR4EnCm8g7AQkzKPgllJjiDLbThvrPOsWbtGihqubcXIcnYLAwwxxbtSrdzEJYGBaDnG/DDvZtc/XkDJj4ysnUCR78EF8WS3CTCDk5jjBQN+IrtH4dAKJysj36XcEqvopzTlLhlBJflrqlIA9x8/nqbgxqN/sItSougj3p+r33MDvx5TXMERzE1bFjWlYCQU6OPTFOmYmvypXtcVLPRr9FUXEYM74pubxmnsxk0YrmXI3hN1oC8W6qvr6Y3ARbZH3AojxCS8Cpmvhy0V2IWBkwQEr0vAoYBvFlSUjggXsKAfhswaPYbBZNBuWGlCMnmTRHxzT3P+zEVpqKL6MP1pqdHEisS1FBKYntXVr+j1CPGrXDvBOjPtC5M7z11pn1/nzwQY24SE11TPKbyM5WI3xQgUNZ+oS+YIY7/pqr/XYW+iFF9m/EujcbGxbW1BjmP9IoIsLxks+b5+HhbEeFerq8vtHnTkvTpDLOJweOTo3Rp7z3YfUlnL6wGycOe2EMfSFhpiZ7yPG04fjwB/2Na64Jzrbwsdc6UCkqk7/jWzLzS6c+79HfSVis9eMC60Cefe40Sgj9wSC+LqqngoopP1rPhju6IaiewF9//cWoUaNo27YtHTt25Ntvv+Xw4cNsMM01vWDcuHE0aNCAjz76iNatW3P77bdz66238p6pNPj/ipkzdforKkpDLHygQwedAdizp3xMDr3BmfiS/fElbO0bu/eFOjI6mlN8l1yiHYOEBOw9GD+IinLMdLzzUSXk/N8htBKcWAIzayhrP9uoKDsKJMxk8mTt2513XgB9mOhoR6ja7t289x6EhxUzZ8tF/Lm0EdOWDWbG2qsIDSlkwlsLCN9veHDVqaNB9+WBWrXsaSdv5jtmrepKwu5jXjctKihi/LQWWLBxQ5ERGlAGtZcJM2TgV4tBAs1ZEtwBRJDE+faZxYvP+cOxrkI9iHsfCor02XsxQ27QAGyEkBJqEBz7HTPc/jI7uoQ6xus+mRGVKSIscOKra1fHOVWt6qdH7QNlJb7MmeaaNX1MYQePRx8FwcpnhYZh2HfTHCu3vsy4+XeQW1CBhxr9QvcHz9VzaNhQPWLK6uhqzs6tXx+YMmO7Gznuhlq1nIivNEcZ8GcK7nXwdlK3+zcSXwCWIReRTmWis3Ng6WIoSC95p03zIakIm9XCfNsAatcuIaFDoOdicXhc2MW5FxuD8Pn7YdlIOGiEMje+hV/mxHHihLZJfqLfgsKg4aoAnbexG7ZTrvWhSSCYhMKbb75JXl4e5513HoNMqZEXpCam8dkUJbueezLLVe21apUmdIiMVG+B04DQBtqjrsMxUo44VMslGdx7Jb5S9V0wFV/lAtNIePdulSC4ZxmzWFUSASU+6IoVHTzab5lXQ1wo5AMT3/S+w4EJcLKQkLn670c13qBFaydizWp1pFgrrc9XWTI6mnD2+drtSrqb9Y37c8zIUEW6nfjasw4E8iwRJFPDt0IyGOJr9WpVh9Wrh7u0IKppIwBCbcVw3LVPFyzxlXIkmdqop2doo+D8vUy4+Hydb3jx7c7wnlF68zydvAkDul9sF7V5NbYHbcPN+xyo6svcrnJl3b+sMCQj/XMWUI8Epswo2Ybil2+3cGnR71QkG2nRosSsNtdco13Q+HgLc06ZCaNcB9cFReGMX6R2BffcU44D77g4rSdtNm7se5iYGNh7tAFztw6CRE8f3vHvbyW/MJLOzXbSc4gxFhBxKL6GD0fCwogmh9q2JOK3l9JbeK8SaQdpVG45SU4nQkPhiy+0vf3+e1i40LHu009VMNW4Mdxxx+n5/SZNlFNawABdsM7PeG+SjtHX0IMBN9QteV7oQsNqY56RndTXREp9p4nmmTO1Dmvf3jFmBEef0gj77nJBa7q33EZBUQTffFhCRlgTbpnnnXE0tQ5TV6v53cMPerGasdl8CjWq1anKwzcpqfTiWzXUqkYESfiNwr81ysU6aGCpBMblAkOg0buG1nGTFl2EpG7+h07m34kyeXyZjXtVPw3HqlWrPDqmgwcPZv369RQWFnrdJz8/n8zMTJe//ynk5ztcCx9/vESz0OrVTw/7b6JpUzhg0Rmdgv0lmNH6wZ74WE/FV2SkI7QsgHBH0Mn36Git8+asaQstjMF8cbbWYSZH0qEQll3J919rOQzYGNzsBO/aRbOImTx8kVbwD/7wMfdNGAPAM5e+SafUgbDcOOfyCHN0hhnuGPo1CIz/0Pvs558TN3DkZB0ur/AzlVKOaAfv2mvL/PMm8fVlijHLsiXdo4PsF4l/sXtHDgdONCU8XBgw+jHXxi3RMALu1MlrTI45WD9qhjsecoRMB0J8ValSBQ7qbH5yaC2XY5YIU/MN6qvnw9DXJ8qL+CrrTLMThg1TgcQXBbdr+OqOLJjzBux4l/y90/hszn28wMt8ePByLKdOqTxj/XqdfiwrWrXSUW9OTskpi8Cnv5eJuDgn4ivd4YEUiOLLZfBmkGYnqPnvyejohG69I5iJ0QlcVVyiUTAAP6lNwJG45pyiEueeW37eJNdfr8dasgQOrZoNlaepb0wG4PxYd73PuI9VxXP77aryKQ+c2zeWilHZpGTV4O+FrgN/51DHhIQEvvxSU7GXpPb65JW/ycqNoUPj3Vx6i1uYnuEPxsiReOZoLx9Y6+hsVW0SOX4kw77cXcHmDq/EV4Yq4sqV+Kpa1aFkXrnSc/2uXVpfhYc7Yhn9wCXccYhBWk2b5rmh2GDfF/AzhBQWsZKeWIZf6lmWTSV8aX2+ypLR0YQz8bXPdZBkPscSPb52a3jMIUsjwOK76g+G+HIOc3S7cTUaRJOKYRB00HWgaGZ1TE1NxWazlUh8JR1Opx5KTFgblI74Mkmrv/+G9GZDNEwvH1g3y3PjpQbR2qwiiScj2btXL8+MyvWAxRK8z5e5XbNm5VOBtm0LfftiFRt38QXLtnXgyN5Ev7tMmR7hCHMcNarE86hQwd5t5PPp53lV1Py85XZOZNaidm249NLSXowXWCx2cjX6RLxdnPbJnAcgaT7YHGO5ooIiPp+oMYf333HSMdlw9Kiq3UNCoF07LEZcYmt2smdrECoeZ8RrSGyg/l7/BvTo4VDv3XOPDgfT0jSvEGg4pEfii3LEdddpVvciQtTKYJt3QULRr2p/UmKYownT52vJEr0o8JxIsbqxZ85hjs5o2FAnhgsLNdQduPe2dADGTQrMF9k58zwAE4HHgUcg6slc4osbkxJSjS6DqyoBHh2tN95q1TJao4bDisgND79yDrHR6ew43IypY1bBgQksmtuQpgUHsGFhyLsXlHx+pwtGe1X/1G7CwwrZcbQtWxeU3rv7fxGlJr5EhEceeYTevXvTzpmpdUNSUhK13HpptWrVoqioyO4x4I4333yTypUr2//q/2PU6WnCp5/qjFPt2uWbtqOUiIiA7Dgjt/YR32Gr/iA24UBCLVpgEDjOag6TkZoxIyApetWqDrPkt98WOOhU+RwC0lH/mZbw96EObN1VmfBwCVy4YhJfO3fAhgd5dvhrxMUmsv94M1KyatC+/haevcwwPD5dxNfFF0O1atQoSuZC5jN+ekuvcu8vvtRX9IXqRkjOjTeWg6uxtilNm0I8TciqWUVDR38MUIUpAtteY9YmVXv162ehYpM+ro3b5s26rRdje3BwR/FFRrk77JipNTvg3ogv11BHwyAeZbyCUr688IIaKrzrJWtdSfgXEl9WKzz8MCRRm/nhxujz42dh8xPMWHIFYzJG8zIv6fL774c5c5RRLw+EhAQ3QA1G8ZXheCeCJr4M0uzfqvjq0QN+REls22rg0C8l7zRfO6mLo1U1UR5hjibq14d+/fT7xM+2QihgHt+JE9l1rCWLVtbEahVuv738fj8sDPp313dq7mzXd9+ZKHr99dcpKCigX79+XHCBlw6mYWSbufkHPv5Bid3nHk91VXslJqqPAARu8FEa1HYQXyeOOsptqRRfxrtQrqGO4GAUVqzwXGeqvfr3D6jdMQ3uFy6Ewhse0n9WHYNUN0Vz0nzYdwAW6b9P8RaDL/Iy8C9rZseyZHQ04WRwvy/e1d054FDHfVrn7bNpnW8mIvSAeb179uho2B/8SKHi4iARI0TgiOukmqn4stlsZGRk2NtZn8TXkSzqYtg9BBMT5HY+LVpo12H5mnBoGasrlv7mufG61frZoYk9SKBjxxIE98H6fJ2GNtjMYn5vyFjCpJCpX/n2P05OSOHAukqczzLEai05pZwBM6x81iw4ZPNU1Ixdr2T+HXeU34SEHaaq8MABRo8Gi0WY/fdQ9ibUhJTV9s1+m7CehJS6VI9J4dr7ujr2N9VeLVrooMPpvdqzo3TjDg4qsfFfIr5Ag3zi4vQ1f+st7Yamp2uXyEw0c7pw9dWQa63IarNx/8NLVveTR7Bs1vH51oZDfHXjXdG+vQ4scnJUjVoSEhMdkjf3yXyLxcXnC+Dqu7tQtWIqh5LrM3uSawIcr3DKPE8yMBs4BhyHqjlp1OMo1YpT1UIgM1PPu9ApC2JqKtx8sw5G3ZKNxNaszGO3bgbgpbdrUrjiThbP6AfAscr1iatccnTTaYPxXoUc2MfwftqfmjQ14my4oxNKTXyNHj2aLVu2MMVkbP3AfUZWjAfga6b26aefJiMjw/6XUIbsaf9KXHqp/r3xxumVcgWBsFY6+xKRlefbk8MPkhOSqZGTTBhFSKVKrkayvXsrg5+ZCb956eh4wcMPqxBn8WILa7c6xXhuNj7bAmHww3KdirhkYErgGVBM4mvLKsg5QqWoU7xxtXoihViLmHDXKMJDCwGBg0aHtryJr/Bwewt3V+gXHEutzawfXEOGD+08wuy1XahFEh2OGYOScghzNGEq6zfVuUi//P6H742dcWIJpKxk1mYNfRk2zMs2xiyNN38v0PFgSAgkYJSTI4533J/Hl0uoo7HPgYJGQJDEV2SkZjAsTRY3s2ynp4OXcywRp6PTjfadq1XJ55N87YCzHOQI9Ji4lsv5hSJrCLx3H3zySfn3igNVKvjJ6GjCRfGVB2SnA0ESXzYbZOisYDI1/pWKr9q1YX+DCzhBDayngLm/u8yceyA7HTbpzPj36dpRLE/iC5zCHRddqv0kM4vaeuwRA18u1DiMYReeLJcwS2cMHKyeb/NW1AWbg/Q0CYStW7fy9ddfA6r28oCTke2YN3eQnl2FVnV2MmKwm2H+V19pWG6vXo4MUqcDddRrqTaJHE90qBeDJr4K8uCUPoByVXyBq8+XOwIMczTRqZNOlJ86BausV0GdMCgEfnjddcO942AaYINZDGWF9XwGDPByQLNe2bo1cP8mEyLlE+pokGZt2MH+BNdORknEV2WzfYnXOv8gjYiL88MhVqvmaBfW+xnc5eU5BpdeQvXj4tT3EoAjrkru8PBwez158uTJkhVfiQV2xVdJ0Qn+4OLz1clgKdZ5aS+2Gu1j1x4l+3uZKK3iqzzb4OHDoU4dqhancgU/MeUX3+z0jG92cKNo6Lhl0KCACcWWLeGCC7Rof/klLoqaHSf7sWSJhZCQ0xQqZ7K18fE0awZDhuj4bcy8+1yyO376udbhd161jcjoSMf+pr9Xe8NX1um92rO3lENRp0yp/yXiq3Jl+Njwf3/jDeyJtspitRoo4uK0DC3EmDRatNhzox/fJ8RmYw/N6Xlr+8BEkVarZ7ijP0ybpgW5Z0+PUG3Aw+crqlIUt16+BYDPxwZQXqKcxo1mlFBj+GXocLqzhkur/ELx6xZYOkEZyAMHdDI7MVETI73yihJwX32l5+hWtzxwx3GqVUxhb1ILrv98Es2SdX3VHsnqK5Yws+RzPB2oU0ctVIqLuX2QjpemLBmC7eTmf+Z8/oUoVW1z//3389tvv7Fo0SLqldAQxsXFkZSU5LLsxIkThIaG2mee3BEREUFMTIzL3/8UWrTQ9Fk33/xPn4kddTvGOaTx24KXRe7efMw1o6NzTWm1OlznAwx3rF9fQ28A3v7dyFZ3CjB9NLtAUXEIk1bqRjdeujPwkzU7wXscs4M39/mO90Y+yvQHrqJz402Obc3xkg91Splg6NYvsf1BZdIZ96Xr6/jVB/sQsfJ67dewmIM0s9NQDjDDHX9Cz4NVhyE3ACJn22tk5MSwbLemI/YgvkRKVHyFhGgf+ihGhy/RQbYGHOp4TI2G9xVqo1neg3CfiIlxEGalIeVPE/FVIbKYey4cx19cRHJIdcgCedpCs8L9JBJHzhMVoOlvqogpb5izcyUZ3CcmKmFoteLLebdWLcgkhiKL0QM8ojPnvvx0wAvxlXECDPuYE9T8Vyq+ALr1DGU6Rij4shw44Wem8PexUABFsWEsSD6HkJAy57jwwBVXQFRkEbsTW7H+QFdohvYScoA0yC2IZMLSUQDcfW2AXhtBYOBwfYmX7exJToJj4G8SDGPGjKGoqIiBAwfSp08f152djGyz8yrwwWxNHvPs8NcJWX21oyNaWAhmZmlDpXHa4Kz4Ou4g8oImvpIcne5Uqpav4sskvtavd53ZPnnSEf548cUBHcpqdUS8zJlnhWFGvTDDaRCQcxSW/QprQCwWnuZNevTwoeipV08rhOJix2RKoDh2DLKytLEJNN2bN7RogVitVCGdrMQoyHfYQfgi4z0UX4e1I+HT2N4ZgUwirF2r4US1anlkxgVX4kuOeWYfdvb58poYxAlJx4rLrPgCN5+vHsa7u8XNXqGwAPYa4b+9A/D3MmGSMv8k8RUWZp+YHM1nbNjbhr2bDnrddOr0itzMd/pPkNlkzTC58eM1y6MJI9cHl1xSJn7SN5wUX6DCcYBvl9zCqf36oLau2MPiv88hxFrEPU+6te+m4suMEDKIr9bsZE98KaIYRJAk7SPG07j8jPzPEK66SpPeFxQop3/uueUcnuoHI0c6iC9Zd9jDzypnmoYg/8JljLwhCJrArPwDIb4mT3acjDd46VPe/aiWwb/WdWH/34d8H1sEUpz6ogbxZesCT216i3V0Z8DFiwhpUw/Ou0Hbh8aN9cWJi9PZm+efd0RGbN6sna1ffjEOVEyl/Y/x5CUanzp9zVVciCYKqNDFmKDZ8NDp6WuXBKfMjn1rHyAmOpuEkw1Y8Vsp7QL+BxEU8SUijB49mpkzZ7Jw4UIaB5Crs2fPnsxzewnmzp1L165dCSt3Le5/DOVlzlIOaNHCKbPjzgBkpG7YsyPD09/LGWa4419/KZseAMwo0J/XX87uYy1gKpAJ1AV6w4LtA0hKr021iikMGRKEjNMkvhKS7YNjq1V4dNgHXN7tF8d2eYAZjVteGR2dcc450L49YbZCrmEqc9Z1IX6bEimF+YV8PaM1Voq5Nt/IgFqOai9wKL6+23cBUtmqg9s/xvrfKWU1HF/A3K1DKCoOoWVLL33HgwchI0NVbX5m2uvXdyK+jqfblwcc6nhcvx+lLpUrO/xtzwhM1ddhz0FFiTDDMcqZ+CJ5Gff1e5OQ0GK+KNayYrUJq+nBmPPvJaZ9FuQkqPdBecMcrG3bpumJfMFPRkcTSlJZSA81iPhj6uPhy0/HeZmd+Dqq4T15lgiyif7XEl/nnusId2Q9sN/PLOHvmtzicNNugIUOHcpfMFypElw2RGfRv19+k4Y7mvfuGExbfTVp2VVpWP2gPaytPNGydQj1a6ZQUBTBsj8dIVomgVBgjPReNvPCm3Azsh234G5SsmrQtNY+ru35o25jdkR//lkJ2Fq1lOk7nTCIrzoc4/gJR3fL2bPMGzyIr0QdqKdbKlNMaPmW56ZNNUSloMBVZfTnnzog6tBBFdsBwiwXc+cCNz+k/6xOgmSjrtz/NfyoA61l9a9nKx18lyWLpfThjmaYY9OmZTPNiYzE1ljr6mqZqWQ7kZDeCEwR8SS+jmhbFRTx5e96/fh7gRZtM9Sx4LCnpYhJfKWkpJSs+DpudRBf5aD42rABsrtfqf/E50KWk6/sxr/U+ysCUhpeZI+Kd+e4PfBvUHyBhkWFhdGLVXRiE1PGH/TYJGH3McK3p1CfIxTHVlGlWBAYPlyrlRMntCoDVViadkQmMVbucFJ8gfr5NW9WRGZuZb7/vQPsGcdnb+l9vfz8ddRr7paNy5/i61ApKrTcZEjR+j7B2tCraOjfDIsFxozRhF6gyq8zNSQcMQI2hfcgl0gsaTbY4OQvmp+DdZXW1QdaXeg7LNsbTMXX+vX+Q7X371fy3mp1eEC7o1s3vSEHD8JxneRu2rEhF3Vfh4iVLz7w4UlclAMrr4e/n9L/C8Ecmq6s0Ivdia2Iicrg1r7fQJePPH3HnDFwoE649OqlY5rLL9d0nMcWQc4R7hs4hlqVk2jDDuqQiIQBLQDk9PW1A4FBfEXs28GIITrenjy94tlwRwNBEV/33XcfEydOZPLkyVSqVImkpCSSkpLIdZKgP/3009zkFK9+9913c+jQIR555BF27tzJN998w9dff81j7rlcz+IfRcuWsB+jE7B7a9D7795lcxBf3jzfWrbUiqy4GH78MaBjtmkDl1wsiFiZOXkEmBlQbgFC4YflSqZd2+cPwuv6cj71grg4VezYbJBRC/fMOHaYtiS1ap0e82OLxa76ejB6DCJWvvpQOw6/fbuepPRaXBs9lejUJKhSxXcDUUq0a6chFxmnQknr2EEX/jzZ/07bNGRl1j5VSngVAphqr7Zt/Q44GjTQNNQAnHCQJQGHOp7Q9Uepe+YzqJTW5ys/37FPeXe6cxOJiz3O9edN4nPuZU94cz7nHvqzkFsum+CyXbmjbl39s9l0ZOMLJfh7gSO9eIrF8CBLPAgEGep4TN+jk5ZqgOVfGeoISnyt4DyOWutqJrM/pvvunCzTGfNlsZqNyFRsljduul3v+4+rrqWwKBTqGCuOKqEEcNdFUwmJK2k0GjwsFhjYVwfCc+c7OqTOqu8hQ4bQ0/3inYxsc/KjeO9P7V88fembhIYU49IRNU3t77rr9LoIg534qsQpMpIcYayBKr7sKhzjHUgxQoDLVfFlsXgPdwwyzNGEOem/YQOkNL8c6odDEfDDGxq+OvNT2AYSFsL9aRqu6tc3PxAiyBvKI8zRQEg7h8H9gR2OCAZvzzE3N5fiYp3pt5dbJ2WKz4yOJszrXbPGd11QQgxghQqQHq7vcb5TUgUT3hRfvoivnGP5RGKE6dap43WbQNCggSZTLi6GFcndIdYKxcCyGY6Nlhl2C81jWLZa3802bVSA4RdmW3rwoP6APxQV6XbO+5UX4uLsZPp9jGHKb/URm+sznDp+j93UPuSG631OAPlCWBh2b0VT5TVlijqJNG3q4B7KHW6KL6sVRt+g7fmnc+/n5KJn+WGulsf7b97rum9xsWPSyxwftGyJWCxUJY2C1FCyM4L0+dq7BksxFBBGROO6p70qPx1o3BgWLdIAoP79z9zvVq4MA4ZFsQKj3v/DyUf518+ILMznBDXoeG+QJ1Wvnta3Nptrykp3mGPAAQPwOYsTE+Oww3BSfd17t75PX8/sQO7+eXBwChxfrJNa2Ydg3nlwaApYQqHb5xD2gpLpsfDKhhcAuH3gVCoNmuCaYdLfNS1erKnTAd5/Hy6/D1KhQkQub1z9DANRcY+lFeBcDk9HXzsQmPdt505G3qqd32nLL6Lg+N9+dvr/g6CIr7Fjx5KRkUG/fv2oXbu2/W/q1Kn2bRITEznspIJo3Lgxf/75J4sXL6ZTp068+uqrfPLJJ1xxumdazyIotGzpUHwV7w0iu5+B3fuiaIchZfY1qDVVXwGGOwI8+ZSFEIoYuulPXXA+0Bqycisyc51WWjfe3dA/a+8Oi8XRGY4wU0G6k18WR5hjeft7OeP66yEkhDbZW2nFTr6Z2YaCQ/P54kut3J+rplkmuflmx9RQOSEkxKEmXtfAIKsXbvOZxpe0zXDsD2wSwux1Gn/v1d+rhDBHEw0aOCm+Thbaf9dXqKPNZnMNdUzRzvhR6p65MEcTpSW+Dh7UwUx0dDmPXrF7Gjwy5AMSqUPLgj3cx+cM7TabprUOeGxX7ggkRKcEfy9w9IOO28wvSmgERXwlah2WJHEux/y34ZxzICzcyhSbofpalAzpXiYedq6AhAKwwuRMDQ0ob38vExcOCqFWjTxSsmrw15YhduIreXc1Vu/rSWhIIbc+3C64OtcbTpzQtsDNOHbQJTrKnbeuPeTpbKVJMIAPby+nDuZrvzxHUnptGlY/yI293dqaDath2TI1kCxnBa1XVKpEYbjW20VJOU6Lgw111HrmuGidUe7l2d3gvqBA1dkQNPFVu7aKxERg3gIrDDNIyqlTYeOT8J0qkJKG382WrMbExjpEXV5R2syO5ZHR0YSTEff+3Y5n5i382lR7WSwWbcuy0yFN27aAFF/nnKONc1KSZsJzR2GhIwTVj/lVXmUlvopPeBIKZmbHQIiv4hNaFvMqVS0zUWz3+VpuhTYGm7XcSW2y3hjgtm8auL8XaHscGqrl1ts9c8bhw0p+RUSUKXTTJ4xkGSOZzPEjVfh7uWtygT9+iuRyDKlWkGGOJu64Q4mnJUu0STUJsLvv1uWnBSbxdfKksmwJMxlV93wqRmax61hrbhr3PbkFFejQ4G/6hI1y9Tjat08n/aKiHMqxqCgsxjFbs5N9W44QFHbpBNshGtKs5Wk2xjqN6NHjzIU4OsMl3HHxcvvy1G/1uc2yDOOq60oRlWXOfMyf7329SMlhjia8hDsOvaELDaonkHqqKtPf+wFWjoQF/eHn2jCrvY5TImrAgAXQ/B7YoPVb6rkXM2/7YKxW4f4PbwuM9DIRFgbvvQc//aSE3Po98CywDW7t9y3vtntct3N3ojldfe2SYLZ5O3ZwwaAoalVNI/VUNeZOO0t8QSlCHb39jTJz7AITJkxg8eLFLvv17duXjRs3kp+fT3x8PHebqUnO4l+DOnUgIbwRAHl7Ssgm5AXxh2JohoYk+SS+rr1WO3Tr1zvCEErAeefBB40+pSNbyA6LBiPr7cx1I8gtqEDzxll0v6QUUyUm8ZVS2WtaaCrUA8tl+v10El+1asHQoQDcG/E5x9Nr8sGT85m3qRf1OUSrBKODe5oGaXafr6JbIAxNb7z6V+8bb38DgPU5T3MiOZSYGB8pxkswtjdRvz4cM0fVBUCyxuz7Ir6ysrKwGeRYFWuhhmbyHyO+zBCLJk3KX9deow9UqEe7+jsY1H6OffEjQz4wvlmgQn3d7nTAWangCwEovsxBfWKRIdM6rqSGP+LLIzNZknaiT5wuoqCcEBGh3upTzIptE7B3uueGMz4HwNYqhiVbdNB6uoiv0FAYeYOaEn+/8k478ZW6R1UiI4Ycp1Znb4x3kHj6aXXTN1P4GhgwpAoWi42tCR1I/FtDBdoYdfCVV15J165dPQ5ldjB3Hm3Fe7NU7fXRjQ8ZSUqcMNno4F9xRZnUK8GgoIqWQctJhzI+aOIrWeXHydTAatXMx+UKZ8WXzaaKoqwsfXH8slLe4RLueLERU78hHcZ+APFAJEyspsrFCy/UMucT5vPeu1f9AQNFeWR0NOEUlrVvr2NiyFv4tXOYo8Vigd1aH2ZTgZNUK5n4iopS5hC8k33r12sGsmrV/F5bsUFuWdNyPNYFrPgSITRNy21hzbKTRC4+X50N5c/6jY4NthgTNN3ODdzfC7Rf2aiRfi8p3NFc37jx6WGJzjsPOnSgArncwrdM/tpByu/ecIDW8ZuIJJ+i1m1LnBz0hfr1HWTJXXdplysiotQ8WmCIiXFkgt6/DzY8SEyFTEadPwGAPzdrm/DA4E+0a+PscbTNaVLc+Z47+3xtcwp5DQRGptT/mrH9vwXDhsGaKH25itadgOIisNmwLlFP1SMd+pUu8XdJPl9btypbGxGhoYP+4JbZESAk6VfuvkD7Q5/Pu9exbX4yFGVBxSZw0QaoeT4iUPT7bAC+SlaRw4gRFho1KSVROmKESpk7dVLbnbeAnyBsr+HfaQ92Os197ZJgjll37yZEirh2uCZFmvxTlbPhjpQhq+NZ/G/BYoHCesoeWI5574z7QlF+AWGJuYRSjK1SjO8BRY0acJGRQTBQ1deRI9x7XOWpT4V8SMaApdBrMt9v/wiAm26tVDr+wCS+du1S5t8tLTSXxsMRo9E+ncQX2MMdb7Z8h5VinpmmBNMbNZ/BIkBrIHrHaflp0+dr8YZY6GzMwE4b57lhxk44rCEJs/apq+mgQT6SAwah+MojinRrrC7Ypx1gXx5fptorMjKSqGM6qMkNiSSLmP8e8VXeIRagCpwumiro6UvfwmKx0bf1Ynq1WIld0ViSp0FZYHZSfCkzAsjoCFpNWCxqSg9AsqvqJyBz+xMajpRMDWJiyl0sWa4491zYSGdOVGqgBPBPXsKN5y4C4Fi7AeTnK/FRYshUGWC6Ffy+cRhZF34BQOV0HdDf/Ug5OSeboWs//ODSHlSvDp1bKdEzf5Z22AYPHsyGDRuYNGmS92PV6INE1uXebz+nsDici8/5neFdnAl8CxTXgZlG+MXpNrV3gi1OSbmwrFwQJU2CJr5OqMdJCtWpUeM0ZP465xzNdJuaCrt3O8Ichw0rFTlghi7OnZ2LpL8F9dGwNsPPm6Hw88IQl219onp1h0rEX6ZDd5RjqKNZX7VhB/sPOjLVmc8xOzvbPinj4e+1W5Up8TQGLIFV/f7Us86MkJ9nY62jEwcRWZ6Kr4CJr4JUorIMwrZu2f0ETBJr7VrI72rE5G0zPCUK8mCfnkvWOcPt3YiAiC8I3OfLXH+6KlCLxV6/3MNYps5qiq1Yy8aU8Ye5lW8ACL3z9jJNfpleXssNLv+aa06PI4cLTNXX5ln20PLRAz+zr65a8SQje03Gw+PI3d/LhJOScveOfILCQSVJzxJfpUNUFDQY0Z1MKhGWWwgrfkKWTCU2N50comj1QCllaP36aQO1f7/dD84Fptpr2LCSs6qbs3vr1mm4rOHleVu/rwkLKWDN/nPZEN+ZnPwo/j7UgWmrr+K1H+/mxrvq0r07dKh8iNC9OynGylsblJB7+OHSXZYdzZqp4vbaC9VSdCYaShmDtnNnoq9dEho21AdcUAAHDjDydu2z/bpmAKcStvwz5/Qvwlni6yzsiGirrUdUxinIyQx4v/jtCbSwqZzb0q6d/8bcDHecONF3SJ0zHnqI0NxTbIrqxZi82xg3sw9HQq9j0Qo1vjaTRQYNszNsdo6d0kJTq5/+H8AgvVwwdAhUshKTl8Ug5iBiJYQirsg2pOIDOG0ZQsx2Ze9eONVPlWfMWem54Y63AIF6lzFrgRISXsMcT550kEHmrLUPmGTVETPc8aA+C18eXy5hjvE625ccWtPlWGcM5g/+m4gvUBK3zwz6dd3H9rfb8tsjl+rrWKGeKhuDkXcHiy5d9N0/fFjDdNyRlKSGp34yOoKqP6pXV9IKgBSdCQ4q1DFZCZN/c0ZHE/oOWvg92khjO/8A5BxzbJB7CjaoamBZjdvs+5xOI9yOHdWKJT/fwk/HNAwzTpLo0jSdfv3K4QcKC11Vv/fco5WQgYEXatswb0lVEBsWi4XOnTsT7ivUyhrCpPUPsHhnf6LCc/j05vud7o/xZc9ATZ/VsaND4XQGEGKQ5BVycpA8LcsmYWKSJO4wSX878XVSEw6kUP30lOfwcAfZsmJFqf29TPTuDVFRwrHjUWxLaAsGJ04xEAPp/WJYs08XDrowgHYt2HDHjAxNYADlQ3wZx6hJMikHrfZZc+cQXLMO8iC+nJQplSsHSE4EQnyVEAMY3kjbqMiCPI/+XKDEV356ElUKtN0Na1L2RrZpU50XLSiAddFGeHdioSZvWPuHGlFHwdLMAYjoGDNgYabZpprJY3zhdLfBACNHIpUr04z9tDm5jZV/bkNswvqZeXRjPTZriCNteSlx4YWul3DaTO2dYc+eudu+qGWdPQzuoOGqd/T/iqhwp9B1MwTdVHy5E1/OBvf7/Mk+veCQHvsgjc4SX6XEtTeGswxVJRX/NoWEj6cAsMB6IcOurVK6g1aq5BhYuKu+RBz+XtddV/Kx2rZVW5CsLO0vGF6eNSsnc2V3nYjv++oSom/NodMzf3PNp9N4fsrjTJxkZd06OC9L1V6bInpy7kVV+OCDcvJGjYqCKfPg/dEQbvQv2qGMypnoa5cEq9VljNutZwWa1U0kJz+aXycGFm31v4yzxNdZ2BHXqT5ZVNRhwvblJW1ux56tyXZje0s73yFMgOqzY2J0cLyshIwXf/6pMdUhISQ8MxbBykcfwddfa/3Zp49D3R40nBVf3gi43FxHB+p0E18Za6CnnsNTsW8BcFP0d0Rl5+ksQldOW4aQKlUc0RKrGhsJJ3afgoPbHBudOgAHVWmRWO0lu3f5kCFeDmhO0zZrVmKaRXtiRJvRoT6kA19foY4uGR0P67ZHRA/yjyq+gpEOn4lOt6FgbH3TWGIu/MKhYDzdDbGzGam3AZtJJDdtquoSP6hVy4n4SlVz5qCIL4MsS6bGf4T4go+TDRb/b2C7UwKQv8ar8X1lC3+cvMhln9MFi8UxR/H19BiOhyk5/eiwXeVDuO3dq+RXxYo6gM/O1lD4fJ31H3SpqqTmbemDnNzo70gApO1ayqNjbgbg+Ss/oFENp1TnFepBr6kw2ag/R48+oxmVwxvpvaslJ0g/roSsP8WXzWazJwxyEF/pgBJf5W0NaIcZt/7VVzpTHxHhCFsJEpGR0K+nkaRg6yBwLq+XwYL9F2KTEFrW3kXDCgG0a8FmdjRJ1Tp1SlYVBILoaPLiNLNlyLF8yFMFXkREBCGG/M4n8RWv/QjT3yugomcSX+vXu5q1FxU5JD4lEF8xjePIN52WD7n6Bgaa1fH44ZP2jI4RTcoe6mixOBRcC3c0gjqGZHzRj7B8ln5vEcvSFUqCBOTvZSJYxdfpbIOjo7EYcYej+Ywp3xxh04xv6H9CiYDiIUMDcOz3D6vVQXZ16uQQXJ9WmIqvY659s2/vvIWPbnyQF0e4Zds1PY5MxZd74ivnUMeDsUGdiu1IOnBW8VUWDBgAa6O03j/5xxYsC9UDKqnTeZhNT6ngK9xx1So4dEjJMa8z524ICXGEuq9Z4+LlqSG1NrLztd6qWvEkPZuvZNT53/LG43/z00/wTn8lvrq+MJTZs1XtVa5N/yOfwtqNcNvl8Nr7Z66vHQjMvviOHVgsMPIKnTybPLPm//twx7PE11nY0aKV1W5wz47V/jd2wu7tuY6Mjn68ewBlyq80Uln7C3fMyXGEozz8MBc90YF69VQ08tprutgpeWjwaNpUpSU5Od7NUHfv1sqhWrUyd1BKRG6imvYDfU4tp03lbbxS9UVdcD7qvWVudxpgzoAsOtQOmldQ+e6P7zs22PE2SDHUHsyfqzsC2i/3SiiYxFcJ/l4AsbE67rVndjyiSTFKCnWsWrUqJBwE4EBhI+AfIL7MtO45ORoeFCjORKcbvCsYzwT8KRWCUFDGxTkTX67+XQERXyeVUEimxr82o6OJBg30ercWtyG7fj1VxUyb4NjgN4ME69mYVWv0OZ6ujI7OuP567SQuXw5bC3Wi4JJmO8vn4M5ebxMnauzmxo3wzDMA9OoTRoXIPJLSa7NtqZ8soQCFWTz78CFOZNaidaNEHv36ac+w9e0VdCIjNrZkQ91yRmh9HfzVJpHjCemAf+Irz8ns3058pTrK82kjck0VnPnuXnCBzraXEoPOU/JxzpbBUBsYgiq/BhhkGDC4w5zA2rVgMzuWZ5ijiTbat6makUphqvqZWiwWj2fpQXwdVvVmQMb2Jlq3digddjvUNWzaBKdOaTl2V8+4Ia6OlSSMyu+w6yx/oIqvpCNZduLLUq98jOBdfL7aGcdcuRDWG8+2Q7Pg/L1M/JuIL4B71X9oCLNZO786k75O4wYmAhA2ooR+coB44AH4+GPNG3FGuHxT8ZWUrxMKhpq2dpUkHrzoEye1l5PHUW6umtuDT8VXXY6ReLiSRwZMn7AVU3xM/RsTIxqelhwF/x8QGgpR5zcCIHbPEepnHaYYK80uWOOanCBYmMTXwoWuxL0Z5nj55YH7Tzj7fDmZxZ/bfA3rX+3Kihd7kTKuGie/qM7Kl87j27tu5elH0xgxLJ+YtQt0Y6+z9OWEjp1g/Ezo/8iZ7WuXBCfiC2DkHUpaz9nUh+S9XhIo/T/CWeLrLOxwzuzI7m3+N3bC7r1WR0ZH9xkdbzClBNOne2T0suP113XWuX59ePFFwsPhkUd0lZmQx+TPSoWwMIfHgzejfedB+unuUUTVhkZAfbAWCdv7tKfeEYOMu8Btu9MA0+dr5UpgoNHIzDIyLeUcgQMT9Hvb55hlTMr6nKwJ0Nge9La6ZHY8puFxAYU6HtPBRILUx2o9Yz7VDkRGOgjRQMMdbTaHivB0d7r/KXjJwmNHAMb2JlwUX+laRwTl8ZWmZNl/IdTRYnEQWRtbGnXjX9ug0Cj/S3QWNqPXpcTH6/al8BsPGnXr6owwwE50gFIxoZyIr21O7UW9evDtt/r/Bx/A7NlEREDf7urtNndOoY+DKNZOHMO4ORo29PlXlQmP9EL6fmb40Nx2G2Wbyi4FajuIrxPH9Jn6K8umvxdAlDk4SNdlp1Xx5c6mljLM0cTggWr4u3T3+eTkR8ENwAMgIQYZhkF8BdKude6sEpejR+11v1+UZ0ZHAxHn6ECipezh0C4HWVci8XVUJ0YO0ihwWylnpYPzJILJCPXpU6LRW1wcDuLriCsZFGhWx6SjOdTDyLZnTvaUESaZtWoVFJ3TRf/ZuA22HgQgr2Mfu6o8KMWXPQzPD/ElcuaIr8it2NpbsCJcfWo6B+c3ohYnyKsQAWFvlY1YMBAWpuTXGVM8mYqv+Hi7n6jXjOjg8DjauVP7PtWqec6WVq6Mzagf43KSOHkswEnE9P2EZmj9Ym3a5PRlsvxfR8JM+nT/jFSqEC7azq4N6UafDr/DsitLX0a7d9cIgNRUx5igqAimTdPvgYQ5mjDl7WvW2BM4mWWsc+NN9GqximqVzHLjRLguW6ZK8ri4gMYj/3Mw2z6jLWzZLpouLfdTbAtl+gQv3mv/j3C2ujgLO1q0gP1oZyB/58GA94vfF05TjM5EAINazj9fGY/MTIeXiDN27oR339Xvn3yisiA0hXMVI+z80kt10rNMcA53dMeZ8vcCraSj69lVX/yBqq7aAbXgdGcIMcc769ZB4RVG9sh1SbDjK8NbrABqnk9+5d525bJP4itAY3sT9es7Kb4SVYobUKhjYgqgpFmdOj5M9k83gjW4P3ZMQ7lCQv4BidoZgrMywz2EuLSKL6OD60vxZbPZPLM6pmvI3H9B8QWOvt2UEPXwYrvAlqmwfyPE54EFVtVRBWybNuUTvRUIzDkKk/iyEwplxTa3iZJLL4X7NWkGN98MiYkMHKrPct7q5lDgPdNw8ZF53PPKQESs3HBlEv0u9EJq7d0Lf/2ljOEZMcJxg8HK1yaR48eUxDVJEX/El3MYHRkFwGn0+AJtXJ3b74svLtPhWvXqQv3qR8kvjGTZbkfbtSexBYdSGhEemk/fzvsDa9eiox31RiCqr9NAfFnaOPyI9u92eGaZdY5P4itJn2c8jYPjWrypZ5cu1c8AGCEX4uvoQZd1ASu+jhXbFV/lJatp3Vo9HHNzYUdNI6vb9mQ4oHX4+ugrKSrSJrJhwyAObBJf6enqJekNJ07oYNhiKYNPRgAwTLitg1TBdBtfc6ftKwBC+xZBiOW0+baeVpj3OD4e6l7mOyO6s8eRs7G9l0lkq1PiiD1/B0BqA+xZiwXNlFqjzemaCfgfh1FGe7ZYxZpwR5zsiWa1CA0xshSWtoyGhkL//vrdHDQsWKDeqzVqOGbUAoE5mbptG+TkBk64ztYwRy666IxaG/xrYLaXJvEMjLxK26bJv9T9fx3ueJb4Ogs7KlWClEo6mM/dE0T41qFTWBGKKlX2Ef/mBqvVYezpHu4oooOTwkLteA8fbl9VsSK89ZZOoD/+eOCn5xP+iC9TnXImiC8zG995uL6RF8KZyBDSqpWSiDk5sCWnGlRDs5R8eyck/KQb1ezHsmUaZREX54PXys113MsAZ1hcFF/JOnDwRXy5hDqeUN+no9S1809nHMESX+ZMc8OG/xBTdwbQrp2q4TIyYM8ex3KR0iu+sgXyc3wSX84KGfvgLUM7a/8Fjy9wEF+/bWsK7eKU+J70JcwwlErNo1m6v6nLtmcCV1yh/c6a5xsEgre6sjRwJ74A3nlHjeeTk+HGGxk0NBaAJTvPJ+/gIs9jFGYy9pWlbDzYhdhKObz3mQ+G83NNfc7Qof+M0tJZ8XVcy2Ugiq8Kzso0p/J82hRf4Ah37NSJslaslpAQBl2oKoI5Wy6yLzfDHHu3XE70eW8G3q4FE+5oltNyDXV0DND37XWQ+uaz9OrxlZUK6bptUKGO4GnoX1zs8EUNIAYwLg4S0bJnO+pKKJjEV15ent1PzhvxdfJIHlVI13/KSfHl7PM1J+tSCAEyBYqAaJhzWAe6Qam9QMlRc5bDl+rLDLmrX1/DBk4XDBNuOkFebARVSWMwcwEI7V+MR9bD/wrq19f+e36++o74yoju7HHkra53hrPP1/aMwM5jt6qIDtKIFi3/H5Ia5QGjjFqtQkELR3+0yRDz3SljGb3QyNpqEl9T1Difq64Krv9bp47WPTabeh4aCZxKJFxN4ut0hjn+m9G0qd7nnBz11Aauua0FFouNFTu7cnDxFDg4BY4v/u8R8GXEWeLrLFxQ1ECn2KzHAmuAMlPSqJmlRq+0bRs4s25KCWbPtmdgA5QIW7JE478//dTjeHfeqcKZcgn1cc/s6IwzqfgCrawv/gm6GKbfscA5nJEMIVarYzC9asav+rsAzp7S217ljynaaRw61EcW9W3btHNes6Z9sFcSXIivFFXplOTxVaVKFUhW5cRR6v5z4qnSEl//q2GOoA1tFyN8xVmpcOKEyt5LyOhoolYtSKUqxWYTdXSPT+LL/N9isWhoWMYJKDB+9j8Q6gh6y0JCNJIrffA1uvDPDfDnr/q9X2dWrdKvZ5L4io5Wa42XfjTqygMHfIenBwpnzxfnwVBkpGZ8qlABFiygze9vU6dGBnmFUayY45mpLXHuqzw7URNyvPGG1ftzPnXKEUZpekaeaRh1YVXSOHlM6zhnssTmpoz0IL4yU+zl+bQqvgBuv12VPU88US6HGzyiEQBztg21LzPDHAddUiu4di1Qg/v8fEddW46KL2c/oqN7iuyL/YY67lKv1EwqkUaVwEMdwUH0/f23vnNbt6qaqVKlgBTVNWrAcZWMk5fgqoCqWLEiYW6DT69ZHRO0bs0Pq1BisppgYJJaCxdngzO/2hiW/LoeCNLfy0RJPl9nqg02feusED443744o04M1PWy3X8FYWEOtbpp21CSn6iz4ssbjD52a3ayZ3eR923csU/77GeN7csAp7LX5pIdnCKaDZHn0K7rdp/bBQXT52vFCu37zTTCJkvjsekc7gglE66HDum4zmotdYKW/zxCQx19bWM8W7dRNP076sBuyritsHIkLOgPvzUql9Dr/wrOEl9n4YLI9s0BiM7IhPycEraGPZuP2I3tQzt1CPyHWrfW0V5RkTpzglaOjxmZBV944fRK0cG34is/3zEwO1PEF2il/cFcqFoZHr8NBp+5DCE9z9XB18o9PcHgLdgEOI3JZs3WDk1A/l4BEqAuoY5ZAlmpPj2+zFDHapUrQZrOUPyjxJf5w4ESX//r/l4mzAGbs8+XqfZq0iQgU9O4OBCsZFhjdcGxffaBWU5ODsVOhqnOoToWiwUS9H3OI4Jsov8ToY7R0dDBqD6XV+uvQs/dxbBGy3xR/R2sW6uDgjNJfNkRF6fxlTabhg6WBWYm3apVPRXCrVrphAdgeeF57u6gnkZzF0a5SvOPzeHR188hM7cy3Tplcuc9PrKETpqk6sNmzWDQoLKdd2kRG0tRiGbXyzuqZL5JloAnwe9BfB3T+11AGFlUOr2Kr27d4MiR4DxY/GDAAB177EhoyZHWK8nv8iOLdusM/OBrAvADdT83UOLLX5jG3r1avmJiAp6ACQiVK3Oqsh6vaP8pEG0c/RJfe3SQcZBGRERYgvOibNBAJ5GKitRCwPT3Ou88HdSUgNBQyIpWL6/CRFdlocVisau+AEJCQojwooCyHdeymBNbvpWoSWqtWF0BWxNHX6GoQQhr9nQCoG+LOcEfuCSfrzNFfDn51ln7gy1Ur7HyRZk+t/vPwDncMRAEqPhqww727A9QhXdQE2ecJb7KAKey17zdfk6+UpUm7x7w7LqXtoy2aKEd/IICePppTdTRoEHpMvN48471R7iaaq9evRz+OP8f4ebzRcJMRnYbC8DklU4EZM7Rsnm6/cdwlvg6CxfU6tKUXCIJEZt9ttIf9mxLDzyjoztM1ZcZ7vj006r+atPG4WR/OmESX4mJOjgysWePdpwrVy7fjnMg6N1HU9c/M/6MZgjp1UZn5Vbt6wmtgUggDcycBXsSm7EvsTFhYTbfEyhB+nuBtoPpxJJrMQauBzaXGOrYKCQHbFCMlePU+ucVX4aMuET8f1B8gaOT4qz4ClJBafIhJ8xwx8R4n2SBSXyZ5YZj+532tfwnFF/gILQWL98HZoRWPhAN2y11yc4JpVLFwnIVsQQMi8WzE1VamCRou3beCfJbboFrr4XiYh7++wEqk868zT0hw6iMCjKY/9UEpqwaidVqY9zXMd59vkUcpvb33edDpnoGYLGQE6Pl2HZCy21UVBRW43zcwx09iK9EJcyT/2PlGZTbNPmquZt6svLYNeTkhlCzpoPoDRjt22t4WlqafwNz5zDHcvZ2yWuifZzw43kayoan96AL8bVPy3o8jWnSJMgiaLG4+nyZxFcQMYCFVZTckhTPSUxn4ss+aeAMEUJT9ZoKa5Zv2rz2bYuJjU4nKy+GQ5UdDfjuqBYUFEUQF5tIs5N3BB+CY7at5iSTO8xyE5T0rhRwNuGuBNZRAn2A3uYGp9e39bTCNLj3dY+dkZbmyJpeAvHVmHgOHvBUHXpD0UGNEjlLfJUBbkbxDZsmUKWqc6RPGcuoxeJQW335pX5ee23p2mHnzI6BeFP9+ad+/n8NczThnNnR8HS7ottPhIfms+1Ie7YeNt9J457+F30HS4GzxNdZuKBF61C7wT3bV5W4/e6dhaUnvq67TuN71q6F775zVI5jx0J4eHDHKg2ciS3nlOFnMqPjvwTdW+3BYrFxMLkxiafiwAwl/QBYAbM2q8yrb/cTOPEPrjCJryAyqChpZeGoGB3rg9vtA4mioiIKCgrs25rEV718VcGcDKlGMaH/PPF1NtTRFe4hOhCUvxc4iK8km/klwcXs21kN6GHOnKSzwcnUdDnWvx09e6iCZPW+HuA8KdoeVh9QVqxH09WEWP6hjolJfJXV56skBYDFAuPGQePGVEw5xBfcxaaD53Bi1fdwcAr5i27kvi9eAuC+e4rp3NnH7yxdqr9VoQKMGlW2cy4jCqppIbSmKgFhsVjsRK5JlJgwiS87kWuU5xRUvWMmk/2vYLBGNjJnjv6Biu+CHv+EhzvaFn/hjqfB2N5EaAcdSFTPPIktQ5V4fhVf8UoOBJXR0RlmXbp6dVDG9iakppa70HRP4svM7AjewxwpTCfylFF/1yvfRjYkdRm9W6h30NICR0zjghw1ve7bagmW3FL4C/1bQh1N31YALNAfuBuIMP6H0+rbeloRjOLLrOsbNPAdKluzJsUxlbEiWBJzsRXbvG/nhPzDGj6aUrEBVasGctJn4QH3MuqCciqj7rPkpQlzBIcXRGKiKpL9IT8fFi7U72eJL/3cscPu6RYbncGwTrMAmLTyeqeN/6O+g6XAWeLrLFzQsiXsQ3totp1bStz+4G4bTTFmfnwNZHyhZk1Hr/jWW/Vz1KhSmjuUEt7CHc+0v9e/ADE1a9C+vpPqaxTQGSgEPoeafx3Hgo1hg095P0BxsRIdEJTiy/TLTTCNPg7ucgz4cCU47KGO2Trbd9QIkfzHia+jRz0zGHqD2ek2O47/q2jUSEfnhYUOMjTId6pGDR0Ym+QVx49hsVi8+nx5EF+JqsA7QU0qV1brqP8Czm2hg/kN8V0o6Byqps8AHWD1PiW+zm28+J/rmPjzRAwGJRFfoJMSP/4IoaFcwzRu42sWzDoCK0fy7vgO7ElsSVz1LF593Y9Jrqn2uummckgBXEbU1hi3iKwc+4yqL4N7D8VXknb0U6j+nyrPJswI03nzHBEoZrMfNNwN373hNBJflbpr/dXCtofE/WoY75f4SlB/nKCN7U2YxNdvv8HJk0ridu0a8O4h9bXcReVke7RR7oovd0j2MWJy9VrCmgSTXjEA5CbSt7Uq2H4+djn0As6H3w5dCsD5rZbatwsK/xbiCwI34f6vIRjFV0n+XgAWC9Z2OiHWtOgACXtKyOxYlE1IshJf1sblXC7/v+F0l9ELLnB8b926FDJf83wqOPZ1Dnf0hmXLNHNrXFxQk/D/k3BW6ec43quRvSbTus4OGlU/6LnPf813sBQ4S3ydhQsaNYIDFh2Yn9paspKlaJ+qcPIrVSndVPQNN+inzaax2O+8E/wxyoKzxJeiRh96tlKic9Xenhrq+DBwia6+PmUKM7iSiy/2YTCzb59mD6lQIagwgogIVeTYDe4TDhIWFmY33nUOaTMVXzHpKQAcLNZOzz9GfNWpo+xMYSEcP+5/2/R09bCD/33iyz1EJ8iMjqCTe9WrO2V2TD4BeIYVOX+3D95OJOku/5GMjiaaxR2gasWT5BVG8XdqJ333WgLdnIivZqv/uY5JeYU6BkJ8gZahx9Vr6hMeYOuadhw40ZjXf30W4P/au/Mguer77vfv7p6enunZt+6eVaMdCSG08QhkBLKJibGD7QLH8UpcuZXHxBAbU44Ndkxy7RiuHYcQmwKCHyfO5rJzbZlQFed54AYMwgaDBGKRhEYSkmZfNfs+033/+PXpZfal9/m8qlSaOX1GHKRezvmc7/f748E/+CxFA/PMpGhqgl/8wnx9xx2rO94YyAq+SeWNDMNED7CM4KsrPZ/Plv37TY7Z2wtvBO+lrXje8FJWdozHio5BjisiVnY8ZUKhme9J/cGxCYWFhdBi3vNXHHxZQZ/1OXjgwLJWRMtdb553Dr8f2qPDoMWCr8HuTrx+87nm3hzbVkdyK0Ph1vMN1+P/ExsT/5eT35w1q4paodiy5wtZn63NzabyI9LgYHghpURVXS9l1cN0Y/0dLyX4WuJ7vS1ixdSG1xc5l+o4Sc6o+bd179i8+DHIwuL5HPV4wuHTJz6xug6aueZ8zcW6u/K+962Zjp15bdlirlH6+2Eg3EV1y1WHOfGdy7n9d/5+9s+k49zBZVLwJVGysmCwzJzkjJ3pXnDfwPQ0eR0mjJjeusKTzA99KFwC/Z3vJL6PQ8GXYXdw4H3mwvY3DQeC24CPwSs37mOcbG7hF2z6o+vnbu2zBtvv3MncA3fmF7WyY6u5KzFzztf09HTogiKnxzwvW6gmLy+JsyuzssKtsou1O1p3mj0e5u8VzSCRJyldXaZawWZb0oqOFq83Ivjqnj8smBV8BS9u0i0osLkrTbBFMOj6feA+uOQv4e1W89rcv+m3yTsxsYKv06dNhedKDAyYFZdg8RDUPw37nqGnvhQ3o3zqtX/jnv/1AFOTWdyw/Wk+ds1P5p9J8fd/b47x0KHlVyLHQc4G8/5WNt3DSI+5sFt68GVC327K4zvYPk6yssyQe8uuXatoP7aCoFdfNUPfZ/L7w5/l8RiGFzwnqOciF09GL1QwZ8VXm/m3PM/6lbU6lpZG30haZjV8RV0ePQR7wS6ejHpsseCrvbGPasx8JteGGAdfFQfZs72TPNcQvcOlvNW8g2Pn9zI64aYsv5ttVW+vbL6Qx2NWCgkEZrfiWZ/B5eUxXaFyUYutephurIqv1tbFV/hdSsUXhF6r2zhFw6l5ugosb5tqz16Kqb2ieJGDlSWJ53P07/4Obr8d/vRPV/fnRM75WogVfL3//Qvvtxa4XOHPj46C0Ew3uz0wRyaYxnMHl0nBl8ziX2fuEma19i24X8vZVjZNmdUPXfuW3t4Wxe02d+YfeSTc7phIM9t3JifNcHtYW8EXcM3vmRaKYxf2Mj4Zvjvw6NSXeDfPMuj2mNa1q66a/eGzgsH2lqiVHVtNaDHzLnpfX19of2eXCUGsFR2TelNnqXO+1sp8L0tkxVfkio7WxfwS+HwRwVePCT2XVPHVY8L4TjxpsaJjSMVBrt5m3oesCi+Al8+Zv8tN3jOUe93JOzFZv97MWRobW/qCDjNZNxUqK1l0OEvXERhrwX3XMB142D59in8/8TEmyeb/O3kjts8E4ONNUF5q/rx168xJ3vbt8OCD5s+4886VHWeMuepNWFlJG50tfUAwGGEJwVePqRrqpjytgtxIkQtqrmpxzS1bTGgxOhp+X4nU2GgeczrjU1lbVsZAjpmNNXjCvM/MF3wV2yZgwAwNXnHFF4TfS2FZ873AvIe2E3wTbG6IemzR4KtlhBqC83SsmQSxYneQ9T8e5F1bfg3A829fx/Nvm1Dvusuex24PrGy+kM02/4B7a6XutfIZHC8VFeFw0bqJMZdAIFzxtZzg6/TCu3LGjNTQYPs0cd11Zm5zUdHq/hxr9Z9jx8x12lwuXDDXcg7HKsqKM4x1Hfv26fjPdEsTCr5kltyd5tOkoL8XJifm3e/08fbQYHvHzlXcVX/Pe+BP/iQ5q25ZwdfZs+bN9OxZcyc5Pz8caqwRmzaZm6Hjkzm8VvEiHPgx/nc/yy9PfJQXOcAbP3jZVHR1dJhKin/7t/APWxVfK+ipj6r46jABx8yKL6vNMT8/H1tHH2B+Jun/RFafpYKvaFZlxtmzZuYCLDtIjqr4uhQdbi0YfHWbC890q/jC7uDqD5iTu8jgK6rNMZknJg4HoSuNlbY7Rq7ouJhgS2duxTh/U383XZRHPz4FjAG9A9DebkKPc+fMsY2OmuDjQx9a2XHGmK0qIvhqNQHJfBVf1nteKPi6FH4+p2PFF0TP9FrxfC8w5wjWjKu52h2taq/Nm02pWRz0VwarVs8PgH8q6t9xfHw8tCBLcbu5gu+jiEF7MetWOo7ICr5crugQbAmig6/oIGix4KujcQQfps2W6hhXfAHU3sL1N5lA7blT1/PcKRPqXb/zjdXNF5pvztda+wyOF5stXPW10ID7lhYz4sHhWLzSO3husIUGzr6z8MJWgXfMohIKvtaYLVtMeDY6Gg5UZ7Kqva65JvlzPVNF5IiKTJ07uEwKvmQW7/5tTODEGZiCc8fm3a/h1NDKV3RMFTU15u7V1JS5Q7gGV3S02Gzm8wLgxdN7oP7jvNpyiI4OGwUFcNVH1sGvf20uJsfHzXy2r33NtJdYwdcKKr6igq/uUWD+4KukpAS6TNBhVXwllZW8LVYBs9ZOuktLzcUnmBVbYdnvEVEVX33mebGk4KvXPGe6qEivii/gf/zetdhsAd7p3Ehnv/l/t4Kva266IvknJqud87XU+V4Q1dLpPdCJj3Z2VLzB6MMueAT4HvC3wJF/MgtrvPKKeX969ll46il48cW4hR/LVmWGjFfSRkeraQ9acqtjMPRN54qv+nr44z+Gm2+Gg6stWLRC9bmCrzgOtrdMbTXVK+7uYRi+GPWeFLlCZ26zCeEuUE9d3SoWqn7/+82KBrfeuuyVDXw+aCP4OmqNvjmz2KqOg+cHsBNgypZFvBLX6242nwnPnfsQL5wzFRrXfe7rq3ufsyr9FHzFz1LmfFnv9Vu3mtB2IbW1TLtyyGaS8fOjC+46dtqEsSteKVXSk90evcrtXKzga62v5hgpcmVHyMy5g8uk4Etm2Xx5NucJ3tF56zfz7nfhrWHqWeK8llRlt4fvRr399tqc7xXhQHC812+C/+z/aVa95b3vDZ645+fD4cNwzz3mgfvvN0Mku7rMnb0VzNOJanW8NA2TE6ETcSv4slZ0LCkpgW5zRz2lgi9VfM1mnaRYJ8erqfjqN6XtS5rx1WcG33biSbugoKgItm83gftv8/8b/9U/5rcXzYCkq2/alcQjC0pk8FVxMDST4k9+51G+fss3+X//7KPkloxDEVBmg/paOPBJU4m6b595Azt0yLxhpVJ5VHAWoIcuulqWGXz1m/3TdcaX5fHHzeKEy5jNPrckB1+u3eZcxzvUCYMNUf+OVvCVn5+P4x0TfK14vpdl82ZT0fiP/7jsH42s+Jpqjh4avljF13ij+X8ZcHviVo1/1VUmy+vqyWZwyElREezctcqK1sUqvpSWrJ4VfC1U8WXN91rKe73djn+zKd8q7O5jfGR83l1H3jHnhP1F1eTmLuloJVNY7Y5zDbgfH4dnnjFfK/gKmxl8QebNHVwmBV8yy9atcBZzcjDx5uvz7jd+0gzdHckvg4iTqLQTOeB+jQdfVsXXb35jRjRYwdcHPhCxk90ODzwA//zPJg17+mmz/bLLWMmZSF0ddOBlGjv4gaaToYovK9SwKr42lOZB8Iaggq8UZw0jtSwzHI8KvgYDUYFoZMWXFY6GLt76zbDztGt1DLLO7V56+woaJj5OX7+T3NzFx6QkxFyLgSyHFXwt5blgd4RmUrhdY/zlrf8326qt/26azaQoKzOVM8DwhT5gOcGXCfrT9fkcc1ag/sYbpu0lUhxXdLSUXmvODTZPn+FSU+OcwVdhYSGcN4H/quZ7WYqKVlQyVlwMXXbzpBlvjn6eLRZ8+dvNe+xIcfzKZl2u8PsdwLXXLnttnNnmm/G1Fj+D48VqdVxKxdcSP7iyrtwJwFZOc26+FeUDgdCCEdN19Uv6cyWDLLSy45EjZvXbysoVjVzJWFZhR3d3eFXbNU7Bl8xSXg7N2WYgRd9rzfPu52oxQ8bHN6T5HTQFXyH79pkTz9ZWOHo0fFN9zgVSPv1p01ZklSHs3bui/2ZdHUyTFZ5F8s4bs1odrYqv3cHFmIZseQxRkB7B1/i4WV4d1tZJd+Q8Gptt2RejPh/0ELw4CwDt5xZvdezvhOBYwnRsdYTwheCLL5pfYF6Xq66UiYXIiq9AYHk/29NjKldg6e+vmTKTwm5nyG2eyxMt5vlqBSaR7XEwI/ianjKhL+lf8RUzNTUmFZ+eDi+qYklAxVfOHvPc3cA7nHujZ85Wx8LCQmgyM+piEnytkM0GY4XmeTfVEb1a3oLBVyBAVq95Hk56YjzYfobIef3LnN0/t8jgy+83X09MhD+j19JncLzEuuILsG03r9ntnKThzZ65dxrvwt1vzglztm9e0p8rGcQ6p3z7bQjeDA+x2hzf9741N6ZmQXl5ZtYArLxSP8Mo+JJZbDYYKjcXGhNn506Ix4eH8Q60AuDae2XCji0urAvyt96C08ElZdZo8JWXF75Z8vWvm9/37WP+AOHAAZOO/fmfw333rei/6fGYi/pQu+OFU/PO+NqaY6p5mgNm35QJvtraFl5pJhAwf7lr6cp1165wWrN+/bJWdARzbTuFk16KzYa2JQRfwZXLRslhiPy0rJCxgq+XXzYjqyK3Jd3WreYD4tKl5d89tAbb19dDMPRZkgyZSTFWZF77ga7o4GvBiq/Oi6YKFhMCp+PzOeZstrnbHbu7zS9YfJj2ani9DDiKceCn++X20L/j0NAQ/f1mcZbCwkJoMZ9ZyZ5FNBWc5WUPBlmWkpISbMELxFnB12Q/OYPB/WtXOpV/aa67bu6vV6yuzty9Gxszn8tgPoP9fvMZrBfR6lkVX+fOzX0DZHo6fBN5qaXKkSs7nppnzlfLG+ROmdbv0r0KMNeciopw6Dqz1V3zveY3V7vjGqbgS+a23iQKzvZLcz589vUmtmPS49z9K6v0SRlW8HXsmKnOyc1l5UswpT+r3fH//B/ze1Sb41zq6uCb31zxnVS73eRHoQH3TbMDDiv4qvObkx4rJIv1KuvLZqV2gYApk5tLZIvFWroT5XKFU9QVBMnW9UknwbCw7XzoeTHvjK8Ws+KTaZG0pWXOuG2byYWGh+Hf/91sS5ngKzd35XcPlzPfa6YMmEkxWWHuHjj6TKCwpOCr7SwAAxQwgSstn89xYd35f/nl8DarzbGuzgQc8WKz0VFiqk1GT14K/TsGAgHagkFLYWEhtJuL9/OsT2qRkc1n5ss5B6ODL4fDQXFw5bNZwddoG4WjpnrNuSG+50LXXGP+yTZuhD17YvAHOp3hO2LWZ6/1+4YNa+szOF6s4GtgYHblDZjVnMfHzc0ua9/FBIOvy3ibMw3z/Bu9bcKODjxs2LG8G2mSIeaa83XhgjkfcTjMfE+JZlVAK/gCFHzJPNxXmkGTxf094XLxCKff7A6t6GjbkaaD7S2bN5v0xbpztW1b3Ia5pgNrwL1l0eArBurqIiq+mpvnbXX0TJiLiRaq8fkWXywo7qzUDuZvd1zLs0WsW/j79i37R8vLzV9vaM5XW2NUdYUlKvhqN4ttdFFBcfGyF0FLCQ5HeJSFlYmkTPAFK5/ztZrgKwPYqsz7W87gMPinlhZ8tZpWoi4qcLmgsDCBB5zK5qr4SkCbo2Wo1gT5juZBcrPt2IPnCy0tLQDU5WeHWlQvsi5UpJAMzvrg8258HIb7oh6zVnacGXxND7VSNmnazdxbZrQZx1hurhnX9uqrMWznnjnnay1/BseD2x2+MzVXu2PkLMelnktv3Mi0I4t8hulrGJlzF3+D+XPPsz6uRZ2Swuaa82VVe11zjRlsKNGsG89qdQQUfMk8vNfuYBo7Lv84XHhj1uMXj/dQS3BuUbqu6GjJyYm+K7VG2xwtVsUXmHObFY7uWpaoiq/WjnlbHYuGzQlRSgy2t1jBV2Pj3I9H3m1ea/7iL+Dv/x6+9KVl/6jDYSrbQ8FXZ8virY7t5j0pHVd0jBQZdNXVQVVV8o5llpWu7LjGgy9nvXnDyh8bgvEuUxXE/MFXXl4edJj3lG7K8XpVrBJiBekNDdDXZ75OYPAVuNwM4i661I9tOFyJ2hqs+r0yx9yguUQJbl8Rc8yOT5jCei/jBAfjN56Iemxb8O9qw4zPpp7WS1RjQrzCy+IbfIGZ3R/TUHfmyo5nz0Zvl9WznjNzDbhf5nwvAJxOJmpMdWFWS/+cu/S9YV5fF231a7kpY22zgq+XXgoXK1jB15zDiEWtjtEUfMmcNu/I4yLmkyXw5guzHh953VxgDuRVZEbCHjl4e40HX+vWmYVRwLTLJ6L4ra4uIvjq6A1dSMwMvvKCg01bqA7lTUmniq/5FRTA//yfK249ilrZsbNj8eCrw5wYp/sKeJHBV0pVe8HKgq9AYHkrOmag3I3m/a1k8hJTQx1LnPFlns8abD9DeXn4wvvoUfN7AlZ0tORdZZ7DVSOtMNgQ+re0Kr62YD6nkjnY3uKrsocXjrkYXaX5T//0Txw9epQ9M3oM25sGQ8FXVn2y5wmswMzgay1/BseLdbN4oYqvZS5FnLXTvK58w230d80Ov4ZOm239xVWrX/1T0tOuXWaF254eE7qOj8Mzz5jHNN9rbtY5W2sr9M8dKq8lCr5kTps2wVnMScLg0TdnPe443wnASF2GVLEo+Aqx2eDDHzZff+pTiflvRrU6dg6HKr6sUMNqdXT2mRlfKVnxpeAr5nw+c9EPQHf34sFXcOB6uq7oaLFuakKGBF9tbWYWjN2ekGAiFeVtMncTKmmnu+XSEoOvDiD9g9y4mNnumMCKL++7zTnCev95hlvOzQq+asbMfKxkz/cC8x4aCr6az0Y9VlxczN45Srp7zlwih3HzTUqVmy6RFYrODL6SucpApol1xRfg3GUWytrGKc683jLrcX9wRdzJqlS56ykJ53LB7t3m69/+Fo4cMQNRKyvhyjRfaC1eiorC7+Nqd1TwJXPLzYUOt/lw6XttxgV9IEBxjzkhd1yRISGRgq8of/u3Zl7kDTck5r8X1erYPUGeOxeYXfHluDQBpFHw5feHTwyTfQWUhqIqvrr7ZoUFgUAgOvjqMc+TdA8KysvNjU2bDd797mQfzQzWe2VTE0QEkAuyVnTcvDk9B6/FgKPGCr7a6GwdWlrw1WNWKVTF1xwig6+REbho5vslIvgq3lHDIPk4maLluXdmtTqWD5l/02Sv6Agm+GojWMLdenFJPzN01sz36ssqS4FBmisQOeNLn8HxYQVfMyu+RkfDraXLrPiyXrvbOUnDiRlD8/2TuHrM6yp7i/4d17TIdkerzfF979MsgIWo3TFEwZfMa8RjEuKps51R23taOtg4ae6gFV73PxJ+XHFhXcxlZy99FZoM5nIldmHLqFbHcSjDVHZFBl9ZAH1moYW0Cb5aW00ptsNB6hxw+ogKvi4Nzqr4mpiYYGpqCgjOROoxlRbpPuML4Be/gOeeCy+MmTLKyszwNYDTp5f2M2t8vhcQuuPqpYOO5uFQ8DUxMcH4+Hhot+jgy1z8WTO+JELkyo4NDaadtrTUpMbxZrPRmGtWduw71h76t+zpMYFRQa95f0qJVseIiq9Ay+wqmrmMN5n30f68NH3SWX/p3d2mBXZ8HLKy9BkcS9Z58syKr1OnTNhYXs6y37SCwdc2TnH65ET0Y8ONlIwEZ73uXZtVwxIUOeDeCr7U5rgwBV8hCr5kXraN5iTB2dETtf308dbQio6uvbsSfVjxsX8/fOhD8LWvmRMkSajaWhjFzSVKAPCNtAMm4JiYmGB4eJgdhWDzwxQOOvCmzjmsdSBzBV9Wi8W6dTFcsmrt8Pkigq++0VnBV2TLY15eHlwyQWm6tzoC1NfDwYPJPop5LLfdUcEXeDxMY8eBn/6z4VZHCFd9RQa5JvgyAUQXFar4mmnPHtM629ISnvGybVvC7vp3V5iVrycbov8tAVw9Zrh9KgRfXm+44muy5dKSfsbfZt5Xh0sq43ZccVVQEA7nn37a/L5unc7tYsmq+Lp4Eaanw9sj2xyX+1rcupUANsq4RPupGSs7XniNnMA4fmxUXl2/4sOWDGDNfzh2zJyDOBzw3vcm95hSnXXOpuBLwZfML3+3WS+4ZLDL3MEJOv9yM1W0mW8ypS3Q6YQnnoD77kv2kaxJhYWmDd2q+irpMy0jw8PDoTbHncFri3Z8+HGkTvBlVXx1d5sy/0ia77UqURVffROh4Gt0dJTp6elQ8OVyuXA6ndBnKmfSvdUx5VknUW+/vfB+ljU+2B4Ah4MBVykAYxd7ycrKIifY9mkFX1a1FwSDrz7zvSq+5pCXFz7/+Jd/Mb8noM3RMrrBtHFltw1SXpwb9Zi9axIwM76S3erodkO/y1TBTbQOLrI3EAjgCN5AmPSk4WB7ixXMPPWU+V2fwbFVXW3OmycnTfhsWeFgewBycxmpMJWxgXPdUQ9NvPkqYGbBbr48e0WHLBli/XpTUWgFrgcOZMYia/FkfVZqxpeCL5mf77rd+LGRPz0MrWdC24eOmtLmS25vjNeglrUsst2x4JKp+IoMvq4sMic7LVTjcoVv6CZdcXF41cKZVV8KvlYlquJrwE9BxOqQQ0ND0fO9AAbMiVAnnrSv+EppVmv4Uk6i/P7wjK+1XPEFDOWZ5/Jkm6nkmjnnywq+HA6HCXL7TZCrGV/zsNodjx83vydw4QTHTjNIubT/EvXl4YqX6hywDwcA6Cuso7Q0YYc0r/FiE3z5u0cW2ROYGiRnyOxnq0ngvINYsz5zf/Wr6O8lNhyO8DyMyHbHFQ62t/i3mEpKd+clAv5AaHvf3hUQAAAtNElEQVTnK2Yl+Ub7Ot0EWOtstugVgNTmuDgr+LpwwSwGsIYp+JJ5bbqyMLTS3tTxF0LbA2fM3Z2BSs3CktiJXNkxt8eszjc8PBxa0XFrrmkVtOZ7pcwcS5tt/jlfCr5WJariaxqyBzrICrarzAq++juxFiJTxVecLafVsbHRnGhlZ6/5VdXGS4LpVbd53s4XfLndbmw2G/Sbtkc9n+dhDbi3JLDiq+hq89+qGWtmffFYaPv+IvN7N2V4NxWmxOeUv8I87xx9o4vsCYy0Ujhqglnnxvo4HlWcWZ+5VhWlPoNjz5rzFTngfjUVX0Duvl0AbJg6T/uF8Hzh/pOmAqyvsDIlXlOSZJHLXSv4Wlx5ebhaYKmV+hlq2cHX888/z80330xVVRU2m40nnnhiwf1/9atfYbPZZv16e43/xaeDmho4bzMfbF2/fiu0vaDdVOMEtm1JynFJZopc2dHZOTv4qgme7LRQHcqZUsZ8wZdWk1oVrxfGyWEQU9Flaz0TNecrKvhqbgBgDBdD5KtCJp6sgOHMGdPqshDrQuiyy9b8nLvp4IIxWX3mjmthsGJ6ruCLkUEI5hSq+JpHEoOvmmvrGSUHFxOsG+sLbd8dLEpNhfleFkeNed7lDI9Eja2Y01gbZRPmM9e9uTrehxY/M//yU+UfI5NY7aTWeU5vb7jtcYVt7VlXmsBsG6doeL0ttH3qYj8A4940fk5K7LzrXeb36mq48srkHku6WO5s1gy17OBreHiYK6+8kocffnhZP3f69Gna2tpCvzZv3rzc/7QkmN0OPQXmhGnweCMA0xMTVA2bi/uCa/Yk7dgk80S2Ojq6+gAIBAKhJeIrJlNwRUeLKr7ioqzMdFSEqr5a35k/+Go1f9edeCgpseFyJeWQ14aaGtPeOzU1e1WvmTTYPsRWbSpac4aGwT+5YMUXbWa8wBQOBmxFCVmsMO1ccQWhF3pOTkJX7auscdBgM3NQcxunQtu3BccPpcJ8L0vOBvO8c/j90H5uwX3H+zqoDJjAoejyDJjxZdFncOzNrPiy3uvXrVv5GJTgxfl2TtJwciC02dllgi/HRnWaCHDoEDz2GPzsZynU/pHitLIjAMte4uSmm27iphWUFXo8Hoo1fC7tjHqrYACm3jFVXhdPNbI9YNLi0vdck8xDkwxTVwdHgq2Ots7wan1NwTCpYMRcXLRQzYZ0CL76+iBYrTbrJFyWxOEw1dld7RVs4Dy0X4wKC6KCrzZz8q22sASw22HrVnj1VXP3cOvW+ffVYPuQ7A1mJk7h2CCMdS4SfJlAsYcyyiocOBxJOOBUl50Nu3aZZe23biWRf0k2GzTlb+HKwdfJujgR2l4f/D2VKr4qavLooZQyLsGFE1A1/43nzrNd1NIHQNH2NK6umfmXr8/g2JtZ8bXK+V5AKPiqppXGN4PB1+QghYN9AOTvStwcP0lhNht89rPJPor0ouALSOCMr927d1NZWckNN9zAs88+u+C+4+PjDAwMRP2S5LBvMglDTofprz//QgNeTN+9fUeGrOgoKSGy1dHWPUZurlkpq7nZDDXNHTQDhFOy4ss6oMjgy6r28njAGr4uyxY156ujZf6Kr3bzPFHwlSBLLZtXxVeIe2Nw1drJXgKj7YsEXxcAtTkuyhpwn8A2R0ufz4x7yG4Nz/iqChZ/pVLw5fNBG5Xmm2BL+HwunQguLGPLw1aUxosXVVZC8ByCysrwAjQSO1bwNbPia4XzvQAoKmI4vwyAsVMdZlv/WTyT5rrDcyDxr3ORjGB9Rir4iq/Kykoef/xxfv7zn3P48GG2bt3KDTfcwPPPPz/vzzzwwAMUFRWFftWm3ECftaNgrzmxKx0yHzq9vzYXOR05lbqYl5iKHG7PQABvgTlptSq+HH1p0OrY2BjepjbHmIha2bGzff7gq9O052hFxwRZSvA1NRV+XMEXhVtN+OCjnf6OnnmDr7y8POgw73vdlCvIXcjnPw/vex988YsJ/09PbjWzZfK7Bylym21Fw6bt5gL1KdPq6PNBO8E3xZbzC+47dLYHgK5sX3q3ENls4WBGn8HxYbU6trebRQRiUfEFjNWbfy9no3kuDrz+OtlMMoGT+gNVq/qzRdYsq+Lr3DkYH0/usSRR3IOvrVu38sd//Mfs2bOHa665hkceeYQPfOADfPe73533Z+699176+/tDv5pmzs2RhKk8tBeA4uk+6LzI1ElzYd9boT57ia3qauilhDHMzJZ9ZaYTu7m5GZ8LbMGb6ikdfM1V8aWT7lWJqvjq6o4KvoaDyzKb4MuE86r4ShAr+FpooZpz52BiAtxuqK9PyGGlspwN5qLNRzudLQOh4Muqao+q+OoyQW4XFar4WsimTfBf/xWu/Eog125T2VIx2MWW4HuOq9eERS3OdVSlyDV6dPDVuOC+441mllK/OwPuHij4iq+SEigKLmN6/nxsKr6A7CvNBXppfwdTE1O0vGDOpVrsNRSWqOdbZEUqK83r1e+HhoUrfzNZwlodI1199dWcOXNm3sddLheFhYVRvyQ5Nu3z0BY8YRr67QvkNpsVWyY36URCYsvphMoqe6jdcWeBeXtqampiV/AtoJ9ChslP3VUdBweh31w4KPiKjajgq6d3/oqvnl5AwVfCXBactfL22xAIzL1P5Hwve1JON1JL8ImZzSQ9DYvM+AoGuar4Sl0VV29kAie5/jGuLoG6XHCMmcpkx4Z1KfOUj2x19Ld1LLhvoN28pw6XVMb9uOLOWvVz5uqfEhs2W7jq68gRM9fU4Vh45uMS5F29D4CtgQYunGyh93XznO3JS5EkWSQd2Wya80WSgq/XXnuNysoM+FBdA4qK4GJWPQAdz5/E22+Cr9y9aluR2Itsd9zsNBfTIyMjXB5sI2mhmvJyU0CSUvLyzN1PCFd9KfiKiahWx0sD8w+37zFVM2p1TJBNm8xFzuBgeAn7mTTYPlp2Nr2OUgCGznQvHHz1mIUxNOMrdW3Y6qQBMw7iKhdcXWy2d1JB9ZaC5B3YDBUV0IFJTyea+xfc13HJVNFOedJ4RUfLV74CL76oIdjxZFXVPfmk+X3rVla7pLL9cnNxvo1TNLzRyfg50/I4UqHgS2RVljqbNYMtO/gaGhri+PHjHD9+HIDz589z/PhxGoOzbe69915uu+220P4PPfQQTzzxBGfOnOHEiRPce++9/PznP+fOO++Mzf+BxF1voQkpe14+x6YpU6lXceOBZB6SZKi6uvCA+zpbeIn4LcHzqJRsc7TMbHdU8BUTURVfvSPzV3z1mtBAFV8Jkp1NaIjRfCdRGmw/S3+ueS6PNfUuEnz1Aar4SmV1dXDKZi4k6icL2RW8IZNKg+0BsrJgOL8cgKmO4fl3nBwkZ9A8B6lZl4Aji7PsbLj6avMXIPFhVXw984z5fZVtjkCoKmUD73DujV7sHcGwdl2qlfqLpBlVfC0/+Dp69Ci7d+9m9+7dANx9993s3r2b++67D4C2trZQCAYwMTHBl770JXbu3MnBgwd54YUX+M///E9uueWWGP0vSLyN+0zwZX/9POX04MdG0bv2JPmoJBNFruzomZwMbV8XfKdqoTr12hwtkcHX+DgEV6NMqSugNBRV8dU3sUDwZYbAdVGhiq9EWWzOl4KvWYbzzXN5qm0wNMZhzuCr1zy3NeMrdTmd0FqwGYDygVwuc5rt51mfcm/7U2Um+OLS6Pw7jbZROGoqZ50bNcdVlsCq+LKGZcfivd7jYSS7ADsBBo43kd9vxhjk7UixF5VIulHwxbJvgxw6dIjAfPM8gB/96EdR33/5y1/my1/+8rIPTFKHY3MtnIQr+o8D0JpdQ03K9ZpJJqirg3PBVsfi0XDwZRW4p3TFl3VgTU1m0GsgYFogddW6KlEVX/3T5OeZ956ZwVdgYBobqvhKKGvO11wVX+PjYM3yVPAVMlHqhXaw9QzNqviyFmtwu93QZwIKVXyltuHaLXACinv91JeZbReo58oUWdExxOeDi+AcGJl/n9E2SidNi617c3WCDkzS2voZAWksKr5sNoYq1+G++BaBM614xsy8w7Jrdq7+zxZZy6yblQ0NZtXtNVgNmyKjNyWVFe01MyxcTADQVVKfxKORTBbZ6pg3FG51LA9mYCkdfFkVX42N0W2O6bwkfAqICr4moSLbfBk546vUMYUteMO5E4+yxkRZaF7E6dMwPQ3FxaTM8nYpwO8zfxfO/uEFWx0D/ebzVsFXavNvuxKA4t5B1pm59inX6giQVWduKLnGJ2C4b859AgNNVPi7ACjekQEzviT+rIovS4xucgQuM9cdOS19VGNmSFZduzkmf7bImlVXZ4YkT06Gr1PWGAVfsqiq9+yN+n6sxgP+6SQdjWSyyFbH7P5w8FVoutjSI/hqaoJ33jFfp9rVTxoqK4Mxu5tRcgCo9JtWnMiKr4oJ0woxhovskjyys5NzrGvOQsFX5GB7hb8h9uD7hHt4iMI8M7xwVvCVmwP9JkVRq2Nqy9+3nWns5E6NUdRqTqkbbetYl2IjsgrXeRgjOCzzwltz7jN0+jwO/EySRfl2PelkCdatC7+/u92zK8BWKH+/GafznulnsRNgxJZLdo2ekyKrYreHz9vWaLujgi9Z1LrKV+mmLPS903MBnqyHpsNJOybJTJGrOtr7AqE3qByTb6RP8KXB9jFjt4PHaw9VfZVPzA6+SkZNe04XFXh9+lhLGGvZ+o4O6O2NfkzzveaUs8EkIoXjAxTnmKqumcFXuX0SW/De0kRBGTk5iT9OWZr1l7k4i+lrdAyZsHKisjrlwndflZ12gsMPm+aeydf7VhsA7TYfeQV6H5UlyMkJV/Refrn5wI6BvKvNDfc9vAZAV06lbqCIxIKCL5EFNB3G+dKtNDvDZe+lW3tgpAWOfEThl8RUeTn0ubz4sWGbhm35kG0Du8k60iP4am6Gs2fN1wq+YiKy3bF4zKzwFBl8FQyZ5c478agtLJEKC6E6OAto5oB7BV9zygvOTiqb6qEg2wRdg4OD+P3+UPDlmTZveCPkUuDNS86BypJs3Agn2R61LXtL6r3v+3yEg6/muVtchs4GbyBkVybqsCQTWO2OsZjvZbEuzoOGisvVaSISC9aA+5aW5B5Hkij4kvn5p+HYF4AAffnFAExjp+byZiC4wMGxu/RhJDFjs0FlXTYdmPRiZwHsLAJbAKZw0JuVwiv2WQHA2Bi8/LL5eub8C1mRyJUdC4LzaSKDr9x+E3xpRcckmK/dUcHXnIq3mVDBG+gga3I4tH14eDgUfJWO9QFaqCEdbNgApwhfpLfjpXZL6i3+ExV8tVyYc5/xJnNTod+tN1FZhp3BofP798fuz7QdZdzuCn3rLxpRp4lILNx+u6nQf+SRZB9JUij4kvl1HYGRZgAmykzd/kXHOrLd1uylAIw0mf1EYiSy3fGyXLgiWPDQRiVVtVmxqqSPPZeL0FVqlxkQrIqv2Iis+MoZ6AOgr6+P0VGz8p2rP6LVUUFBYs0VfA0Pm5VNwbS/SEjBFhN85TLGwPle7ME3tMHBwVDwVTjaB5jB9prvldrcPYdpc4cXb7hAPRvH7k+5C3Sv13yGAtDWOuc+/nZzI2GkWBVfsgx/9Vfwi1/AZz4Tmz+v6TD8+qNcKiwJbXJVjanTRCQWSkrMokNrVKpeQkoqGG0LfenYbMKu88VzDK6M2E9ktSJXdtzshK3B+TYp3eZoiTxAh4PUP+D0EBl8uQZMG1hvxEyprODXanVMgssuM79HtjpasyM8HqioSPwxpTCbO5c+WxEA/afbyc/PB6KDr4JhU3mjFR1TXNNhOPIRRivCQ9guUM+m0ldT7gI9suJrurVrzn0cl0wF4qS3OmHHJRmguBg+/GFiMtguotNkwhv+80rqe1GniYisloIvmV9u+K7ftR99gZ994BY2/tnZBfcTWa3IlR1r7bDBaba3UB0ao5WyIg9w3TpwOpN3LBkkstXR0T8Y9Zjdbsd+qQ9Qq2NSzFXxpTbHBV1ymjKuobPdFBYWAtHBV86gCb60omMKi7hAd9RM4ccM3j7PejZ6g+dJKXSBXlICnQ6Too63Ds3eYWqY3MFg621Nii1JKWtHRKdJTv1YaHPZ+p7gV+o0EZGVU/Al86s4CO4awIYre5KPfOIw9bWNETvYwF1r9hOJkchWR+80WMsqpEXFV2TwpTbHmPF6TfULgKM3+qItPz8fW4+pAlOrYxJYwdf582a+HSj4WsSA24S4E819FBQUANHBl1XVqIqvFBZxgV5b2cwF6gFT8bXB8w6pdoFus8FEkVmd2981MnuH0TYKRs1NBeeGOSr7RRIhooPEc1ln6Gv7zPdBdZqIyAoo+JL52R2w9++C38xcRjj4/d6HzH4iMRLZ6lg6AV6zQryCrzUssuLL1jeMM6KSLj8/H3rNhVwnHlV8JZrXa1pd/H5oaDDbFHwtaKTAPJen2wfnDL6yIoIvVXylqIgL702+szzJBxklh1MF28jPGZ5zv2SbLg9WzfaOzn5wpIXSSTMr0b2lZvbjIokQ0UFiqw9+UQzMXNxWnSYisgIKvmRhtbfAwZ+Be8bMB3eN2V57S3KOSzJWbW244it/BErGzXYFX2tX5Iwv+sZDc5HABF+BPvMkUcVXEthss+d8Kfha0GSZeZLaLw2Fgq/+/n7GghVz9j4TnOj5nMIiLrw3es7xRR6ihF78lfZ590s2e3Dl4ezhMZiein6w7Qw5AfM+Wry9auaPiiRGRKcJHuCu4K8QdZqIyMop+JLF1d4CH7wANzwLB35sfv/geYVeEheRM76cA5AX7MpQ8LV2RQZfgb6pWcEXfWaOjmYiJUnknK/eXmgNrhq3fXvyjimFBSqDAcRAOPjq7Ixo6+k3FTlqdUxhERfoG73nABgnJ/R1Kl6gu+rNDSWH3w9t56Iem37HVGt2UY53Xc6snxVJiJmdJlcBmwl/D+o0EZEVU/AlS2N3gPcQ1H/c/K4PHYmTvDwYKzV3nO1j4DTdF+k33F7BV8yUlkKvw8z4so2BpyB8YVZVkI1twqz2NF1arvUEkiEy+DpxwnxdWwtFRck7phTmWGcS/LyRIUqLcgFob28PPW5VMKrVMYVFXKCX5vdRkmc+qDZ5z5KqF+gVNbl0Y+Z80Xgy6rHBt1sA8zmrhVglqdRpIiJxouBLRFJOaV0BfZiLZltwUazhoiqCC6ClrspKqKoyS2ht3rz4/rIkdjtke4qZJAuAHcXhdGtLnrnIHMNFnrcgKce35kUGX2pzXFTuxnoAiib6qSo1wUhHR4d5LDeXQL950+tzlik7TGURF+hbfKZiarPvTMpeoPt80E5wCGLzmajHhs6a4K7TWambB5J86jQRkTjISvYBiIjMVFcHLcerKaYfgF6KKV+Xv8hPpQCHA159FaamIDc32UeTUbw+O91t5VTSziZ3ePuGbDOrposKvD7dy0kKa8ZXQwO8/rr5WsHXvPK2mIrW8qlufEUmuLUqvorzcnB0m1ZHW1kZtpnrykhqqb0Fqj/EA9NvcvjJBj549+dg3b+lVKWXxQq+dnACmt+Jemy80Syo0O9Wb62kCKvTREQkRhR8iUjKsVZ2vBzTjpEW870sGsoTF9bKjpW0U+f0h7ZXOyYB85hWdEyS9evB5YKxMfjlL802BV/zKt1uBp7nM4zPOQGEK762FmdDt9nPVVWelOOTZbI7ePetu3j3rQBbkn008/L54BzBYfutTVGP+TuGABgp1mB7ERHJTLo9LiIpJ3JlR0iT+V4SV5ED7itt4RXJPH4TfHXiUeaYLA4HbAle8Dc2mt8vvzx5x5PiyuoLGMRUsOaZotZw8FVgKoUuUUKZVz1nEjuRrY6BtvaoxxyXzEqikx4FXyIikpkUfIlIyrEqviwtVFNX61/gJyTTRQZf5f5w8FU6OQYEWx0VfCWPNecLwGaL/l6iZGVBp908WbN7gq26XV0AbMgxvY16Pkuseb3QFqz4mmrtCz8wNULugAm+ArX1iT8wERGRBFDwJSIpp871q9nBV9cXoOlwEo9KkslqdQQonpwIbS8cMyvgqdUxyaw5X2BWNHW7599XuJRtlmvM6jYVi36/CfarnWaFUq3oKLGWlwf9LtM+O9kxHH5gtI2CsUEAsjfUJ+HIRERE4k/Bl4iklqbD1DbfNqvVsa7gOBz5iMKvNSqy4is/GHYBuEdNxZdaHZMsssJL870WNeg2AYTj0njUdp/dBGDdlOv5LDE3WRqcGxdcQAGAnvPkT5kgzL2lZo6fEhERSX8KvkQkdfin4dgXqCxupd0WvuproZq6sovmm2N3mf1kTYms+ModCVd8uYZU8ZUSFHwty1iRKedyXBqL2l4+bd7buqhQxZfEXMBj3iSzBiKedxdOADBEHmUbipJxWCIiInGn4EtEUkfXERhpJssxjb84/PbUho+qklYgACNNZj9ZUyIrvrKHJkPbswZNCKaZSEm2ZYuZ7QUKvpZgstw8WZ39I1Hbi6bMzC9VfEk8ZNWZEQLZ4xMweMlsbDwDmBtMvkpbsg5NREQkrhR8iUjqGG0LfZlXPkwX5YyTzXhJDlmO6Tn3k7UhMviyD4aH29NvWsM68VBRkYwjEwByc2HPHrPC4/79yT6a1FdlWspyhoajNueNm1BXwZfEQ0FdBWO4zDeNJwGYfMesxNpMjapmRUQkYyn4EpHUkVsZ+rK2vJn38AyH+BVFFf3z7idrQ0kJ9GWZ+TS2gfAKn/ZBE4hOF5fidCbl0MTyv/83vPkm1Ncn+0hSnnP9OgAKRgdxu8Lbc0aCqzyq1VHiwFdlp51gutX0NgDD50zlV5utipKSZB2ZiIhIfCn4EpHUUXEQ3DWAjbryRt7iCl7iGurKGoM72MBda/aTNcVuh0BZGQCOET85dih1gmPChGB2r8q9kq68PHrWl8wrd6MJvoon+/AWhrc7hszvPZRRXp6EA5OM5vMREXyZFsfxpgEA+t3eULeyiIhIplHwJSKpw+6AvX8HQG1pc2hzbVkTEDwj3/uQ2U/WHFdVOf7g82BTHmzNN9vHcJFfpaHMkj4KtlYBUOgfZFNZVmi7fdAEuZOFJWRlzfmjIivm80EbwYrpVnNDyd9u0tbhYvU5iohI5lLwJSKppfYWOPgz6qrDs2/qyhpNJdjBn5nHZU3yVGbRg6n62uyGjblmexcV+Cr1cSbpo3xTcWjW0hXFOaHtzmHT6mirKEvKcUlmi6r4am0BwNFrFliY9FQn67BERETiTlcKIpJ6am+h9tb/Ffq27obb4YPnFXqtcZED7tfnwPrgbCSt6CjpxuO10Yqp+lqfXQAEW3enTMVXVqUGfEnsRVZ8+du7YGqUnIHgyqK165J4ZCIiIvGl4EtEUlJdfbidsW7nFWpvlOjgK9fBRreZZt+JR8GXpBW3Gzrt5knr8Zue3c155rEJnBRUFyfpyCSTVVRAB+Z5N9k2CEPN5I+ZVkfn+vokHpmIiEh8aYKEiKSkkhLYuhW6u2HTpmQfjaQCny8cfH3s3deRNTkJJ14wrY4aTyNpptdVAaNQPG5KFzfmAn3BFR29ui8psed0wkhBOQzCdMcoXHwLOwGmcFCwSXcPREQkcyn4EpGUZLPBsWMwMQF5eck+GkkFkRVf5f5pmBgHzLbtumaTNDOUZ4KvvBETctUFW3e7KVcFo8TNVLkHBsHeNwYX3gaglSq8VaqqFhGRzKVbiiKSsvLyTOWXCERXfNHdAz29gGl1VMWXpJvxEvNcdg9PA1BjOncVfElc2SvNm2X20ChcaACghWq9h4qISEZbdvD1/PPPc/PNN1NVVYXNZuOJJ55Y9Geee+459u7dS05ODhs2bOCxxx5bybGKiMgaFlnxRU8fge4BQMPtJT1NVZgh4+7hCQCshUm7qMCj2fYSJ9nragCw+wMEXn8dgGZqFHyJiEhGW3bwNTw8zJVXXsnDDz+8pP3Pnz/P+9//fg4ePMhrr73GV7/6VT7/+c/z85//fNkHKyIia5fXa6phAPw9w0x1jQFmW0VFMo9MZPns1dUAuEfNqnoVNrNdFV8STxU1uXRTBsD06xcAU/Gl55yIiGSyZc/4uummm7jpppuWvP9jjz1GXV0dDz30EADbtm3j6NGjfPe73+XWW29d7n9eRETWqJIS6HWUwTRM90wSGPMDMFlUSpYmVkqasVbRKxwbID8HSs3TmW7KVfElcePzQRuVlNMDDaZqtjvbq1maIiKS0eI+4+vFF1/kxhtvjNr2u7/7uxw9epTJyck5f2Z8fJyBgYGoXyIisrbZbOAvLTXf9E9gHzQtYoGKsiQelcjKuLesA6BoapDaQsifMumtgi+JJ58P2jF9jVlDZr7ccLH6HEVEJLPFPfhqb2/HO6N+2uv1MjU1RXd395w/88ADD1BUVBT6VVtbG+/DFBGRNGD3mlbHrOFJsibNRZuzShdtkn6KN5QxGSy8vywPckbN14OuEtzuZB6ZZLLI4MsyVVGVpKMRERFJjISs6miz2aK+DwQCc2633HvvvfT394d+NTU1xf0YRUQk9eXUmAs269NjnGwKa4qTdjwiK+WttIcCiC254Bozz2p/cXESj0oyndXqGClQU5ekoxEREUmMuE9F8fl8tLe3R23r7OwkKyuLsrK521NcLhculyvehyYiImmmrCqHPoooph+ATjx4fQm5hyMSUx4PnKGKWpqpc2ThCs6ss5WrdVfiZ66Kr+zgvDkREZFMFferhWuuuYann346attTTz3Fvn37cDqd8f7Pi4hIBvF6oYvwEo5dVGg1MklLJSXhAKLSn49rzMysy6rSEqUSPyUl0OUIv2l2U0Z5bW4Sj0hERCT+lh18DQ0Ncfz4cY4fPw7A+fPnOX78OI2NjYBpU7zttttC+99+++1cvHiRu+++m1OnTvEP//AP/PCHP+RLX/pSbP4PRERkzfD5ZgdfPo34kjRks0F/rplZVzfuxB4cA5FbW7nQj4msis0GE8Xloe+bqcHn8SfxiEREROJv2cHX0aNH2b17N7t37wbg7rvvZvfu3dx3330AtLW1hUIwgPXr1/PLX/6SX/3qV+zatYtvfvObfO973+PWW2+N0f+CiIisFTMrvjrxqOJL0tZwvgkgakfN9wMUUFatyfYSR02HCeQNhb5toRrfxc9A0+HkHZOIiEicLXvG16FDh0LD6efyox/9aNa266+/nldffXW5/ykREZEoXi+cnVHxdYWCL0lTEyUe6IKibjOzTq27EldNh+HIR3AU/ysE71E3U8NVOUfhyL/CwZ9B7S3JPUYREZE40ERgERFJG2p1lEwy7TFtja5xM9+rm3I8nmQekWQs/zQc+wIQoKB0kDHMIlItVOMrbjP7HLvL7CciIpJhFHyJiEjamD3cvpzyUl2oSXpy1FZHfd9NuSq+JD66jsBIMwC+kg7aMKFrK5VUFHQBARhpMvuJiIhkGAVfIiKSNooHD9NrLw59P5HrIuuX9ZpPI2kpe0N91PddVKjiS+JjtC30pa+onRNcDkBjXh3OrKk59xMREckUCr5ERCQ9NB3G9sJHmMoLj6f0F9hgpAWOfEThl6Sdgs01TEeciqniS+ImN7xaqK+4ndv4Z/bzEu2llfPuJyIikikUfImISOqLmE9DYXizvchvtoHm00jaqfA56CRc4tVrL6W4OHnHIxms4iC4awAbvqJ2einlZfbjK2oP7mADd63ZT0REJMMo+BIRkdQXMZ/GWRxuy3GVjge/0nwaST9eL6FZSwDj+cXYbEk8IMlcdgfs/TsAfMUdoc2+4nYg+KTb+5DZT0REJMMo+BIRkdQXMXfGUT7Fy1zFM7ybotL+efcTSXUeD7RSFfp+WuVeEk+1t8DBn+H1hcMtX1G7qQQ7+DPzuIiISAZS8CUiIqkvYu6Mp7iL/fyWG/hvvMWd8+4nkuoqKqIrvuzFLrXrSnzV3kLeR09RkG8qZ31X3QIfPK/QS0REMpqCLxERSX0z5tOY1hyb5tNIWnO2H6bPWRz63uE8C0/Wa6EGiS+7A1+lWSTEt3mT2htFRCTjKfgSEZHUFzGfxlsUrvLyFnWg+TSSlpoOw5GPMOLODW3KLR3VKqWSENddB9nZcNVVyT4SERGR+FPwJSIi6cGaT+PxhzZ5izo0n0bST8QqpZMFTgCmcFBYPoBWKZVE+MEPoLsbNm9O9pGIiIjEn4IvERFJH7W34Lv1J6FvfTc/ovk0kn4iVimdKjYtZ5148BR1BXfQKqUSXzYbFBQk+yhEREQSQ8GXiIiklZo6B3l5UFYG5dvepfZGST8Rq4+OVLr5Nl/mbh4Mtu7OvZ+IiIiIrExWsg9ARERkOfLy4KWXwOkEhzIvSUeRq5QWdXEP3wbgnsL/Z979RERERGRlFHyJiEja2bEj2UcgsgrWKqUjLVFVXuGvbeZxrVIqIiIismpqdRQRERFJpIhVSj2FXaHN5QXdaJVSERERkdhS8CUiIiKSaMFVSn0+s3JjWX43zqwprVIqIiIiEmNqdRQRERFJhtpb2HvXh/iD33Sy/4pmuOFZ096oSi8RERGRmFHwJSIiIpIkWdkOfvKEB/Ak+1BEREREMpJaHUVEREREREREJCMp+BIRERERERERkYyk4EtERERERERERDKSgi8REREREREREclICr5ERERERERERCQjKfgSEREREREREZGMpOBLREREREREREQykoIvERERERERERHJSAq+REREREREREQkIyn4EhERERERERGRjKTgS0REREREREREMpKCLxERERERERERyUgKvkREREREREREJCMp+BIRERERERERkYyUlewDWIpAIADAwMBAko9ERERERERERESSycqHrLxoIWkRfA0ODgJQW1ub5CMREREREREREZFUMDg4SFFR0YL72AJLiceSzO/309raSkFBATabLdmHExMDAwPU1tbS1NREYWFhsg9HZM3Ra1AkefT6E0kuvQZFkkuvQZHVCwQCDA4OUlVVhd2+8BSvtKj4stvt1NTUJPsw4qKwsFBvdiJJpNegSPLo9SeSXHoNiiSXXoMiq7NYpZdFw+1FRERERERERCQjKfgSEREREREREZGMpOArSVwuF3/xF3+By+VK9qGIrEl6DYokj15/Isml16BIcuk1KJJYaTHcXkREREREREREZLlU8SUiIiIiIiIiIhlJwZeIiIiIiIiIiGQkBV8iIiIiIiIiIpKRFHyJiIiIiIiIiEhGUvCVBI888gjr168nJyeHvXv3cuTIkWQfkkhGeuCBB7jqqqsoKCjA4/Hw4Q9/mNOnT0ftEwgE+Mu//EuqqqrIzc3l0KFDnDhxIklHLJK5HnjgAWw2G3fddVdom15/IvHV0tLCpz71KcrKynC73ezatYtjx46FHtdrUCR+pqam+PM//3PWr19Pbm4uGzZs4Bvf+AZ+vz+0j16DIomh4CvBfvrTn3LXXXfxta99jddee42DBw9y00030djYmOxDE8k4zz33HHfccQcvvfQSTz/9NFNTU9x4440MDw+H9vnOd77Dgw8+yMMPP8wrr7yCz+fjve99L4ODg0k8cpHM8sorr/D444+zc+fOqO16/YnET29vL+9617twOp3813/9FydPnuRv/uZvKC4uDu2j16BI/Hz729/mscce4+GHH+bUqVN85zvf4a//+q/5/ve/H9pHr0GRxLAFAoFAsg9iLdm/fz979uzh0UcfDW3btm0bH/7wh3nggQeSeGQima+rqwuPx8Nzzz3HddddRyAQoKqqirvuuouvfOUrAIyPj+P1evn2t7/NZz/72SQfsUj6GxoaYs+ePTzyyCP81V/9Fbt27eKhhx7S608kzu655x5+/etfz9tZoNegSHz93u/9Hl6vlx/+8Iehbbfeeitut5t/+Zd/0WtQJIFU8ZVAExMTHDt2jBtvvDFq+4033shvfvObJB2VyNrR398PQGlpKQDnz5+nvb096jXpcrm4/vrr9ZoUiZE77riDD3zgA/zO7/xO1Ha9/kTi68knn2Tfvn38/u//Ph6Ph927d/ODH/wg9LhegyLxde211/Lf//3fNDQ0APD666/zwgsv8P73vx/Qa1AkkbKSfQBrSXd3N9PT03i93qjtXq+X9vb2JB2VyNoQCAS4++67ufbaa9mxYwdA6HU312vy4sWLCT9GkUzzk5/8hFdffZVXXnll1mN6/YnE1zvvvMOjjz7K3XffzVe/+lVefvllPv/5z+Nyubjtttv0GhSJs6985Sv09/dz2WWX4XA4mJ6e5lvf+hYf//jHAX0OiiSSgq8ksNlsUd8HAoFZ20Qktu68807eeOMNXnjhhVmP6TUpEntNTU184Qtf4KmnniInJ2fe/fT6E4kPv9/Pvn37uP/++wHYvXs3J06c4NFHH+W2224L7afXoEh8/PSnP+Vf//Vf+fGPf8zll1/O8ePHueuuu6iqquIP//APQ/vpNSgSf2p1TKDy8nIcDses6q7Ozs5ZSb+IxM6f/umf8uSTT/Lss89SU1MT2u7z+QD0mhSJg2PHjtHZ2cnevXvJysoiKyuL5557ju9973tkZWWFXmN6/YnER2VlJdu3b4/atm3bttCCSvoMFImvP/uzP+Oee+7hYx/7GFdccQWf/vSn+eIXvxia66zXoEjiKPhKoOzsbPbu3cvTTz8dtf3pp5/mwIEDSToqkcwVCAS48847OXz4MM888wzr16+Penz9+vX4fL6o1+TExATPPfecXpMiq3TDDTfw5ptvcvz48dCvffv28clPfpLjx4+zYcMGvf5E4uhd73oXp0+fjtrW0NDAunXrAH0GisTbyMgIdnv05bbD4cDv9wN6DYokklodE+zuu+/m05/+NPv27eOaa67h8ccfp7Gxkdtvvz3ZhyaSce644w5+/OMf8x//8R8UFBSE7qgVFRWRm5uLzWbjrrvu4v7772fz5s1s3ryZ+++/H7fbzSc+8YkkH71IeisoKAjN07Pk5eVRVlYW2q7Xn0j8fPGLX+TAgQPcf//9fPSjH+Xll1/m8ccf5/HHHwfQZ6BInN18881861vfoq6ujssvv5zXXnuNBx98kD/6oz8C9BoUSSQFXwn2B3/wB/T09PCNb3yDtrY2duzYwS9/+cvQ3TcRiZ1HH30UgEOHDkVt/8d//Ec+85nPAPDlL3+Z0dFRPve5z9Hb28v+/ft56qmnKCgoSPDRiqw9ev2JxM9VV13FL37xC+69916+8Y1vsH79eh566CE++clPhvbRa1Akfr7//e/z9a9/nc997nN0dnZSVVXFZz/7We67777QPnoNiiSGLRAIBJJ9ECIiIiIiIiIiIrGmGV8iIiIiIiIiIpKRFHyJiIiIiIiIiEhGUvAlIiIiIiIiIiIZScGXiIiIiIiIiIhkJAVfIiIiIiIiIiKSkRR8iYiIiIiIiIhIRlLwJSIiIiIiIiIiGUnBl4iIiIiIiIiIZCQFXyIiIiIiIiIikpEUfImIiIiIiIiISEZS8CUiIiIiIiIiIhlJwZeIiIiIiIiIiGSk/x8FPCbD8AsxXwAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] @@ -448,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "ee52892a-6042-4889-b405-16db44d5412b", "metadata": {}, "outputs": [], @@ -551,7 +551,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 9, "id": "56587835-14d5-4bf4-9ec6-5438299845d7", "metadata": {}, "outputs": [], @@ -614,13 +614,13 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 10, "id": "635b584f-47ab-45e1-843a-796d0f3bf923", "metadata": {}, "outputs": [], "source": [ "@njit(fastmath=True, parallel=True)\n", - "def _approx_stump(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I):\n", + "def _compute_approx_PI(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I):\n", " \"\"\"\n", " Compute approx matrix profile for time series T and window size m. For\n", " the i-th susbequence, this function only computes its distance to those \n", @@ -715,7 +715,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 11, "id": "aba52bf3-8f15-4e7a-a0c3-f68efb3460e6", "metadata": {}, "outputs": [], @@ -757,12 +757,16 @@ " LB_I = I_prev\n", "\n", " # compute approx matrix profile\n", - " P, I, is_exact = _approx_stump(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I)\n", + " P, I, is_exact = _compute_approx_PI(T, m, M_T, Σ_T, T_subseq_isconstant, LB, LB_I)\n", "\n", " if np.min(P) <= np.min(LB[is_exact == False, -1]):\n", " # global min is exact\n", " skip_full_compute = True\n", " else:\n", + " #ToDo: Compare full_mp_time vs remaining_mass_time\n", + " # to decide whether to compute full mp as below or\n", + " # just compute distance profile via MASS for subsequences\n", + " # where is_exact == False\n", " skip_full_compute = False\n", " k = P_prev.shape[1]\n", " mp = stump(T, m, k=k)\n", @@ -838,18 +842,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "87b6b3c6-0d9f-47cc-b8cd-732fd3a9b995", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "naive took: 13.810273885726929 seconds\n", + "--------------------------------------------------\n", + "valmod took: 5.585030794143677 seconds\n" + ] + } + ], "source": [ "# Input\n", "seed = 0\n", "np.random.seed(seed)\n", "\n", - "T = np.random.rand(10000)\n", - "m_min = 50\n", - "m_max = 100\n", + "T = np.random.rand(50000)\n", + "m_min = 10\n", + "m_max = 20\n", "m_values = np.arange(m_min, m_max + 1)\n", "\n", "start = time.time()\n", @@ -867,67 +881,27 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 18, "id": "d8ee07eb-765f-4a48-93c5-3af38ed0fc08", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[10.04110674205363, 5487, 7014, 100],\n", - " [10.235396091248132, 7337, 8268, 101],\n", - " [10.235713184882687, 7336, 8267, 102],\n", - 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"execution_count": 46, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" }