{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lecture 1: Introduction\n", "**References:**\n", "* [Introduction to Symbolic Computation](http://homepages.math.uic.edu/~jan/mcs320/mcs320notes/index.html), Lectures [1](http://homepages.math.uic.edu/~jan/mcs320/mcs320notes/lec01.html),[2](http://homepages.math.uic.edu/~jan/mcs320/mcs320notes/lec02.html),[3](http://homepages.math.uic.edu/~jan/mcs320/mcs320notes/lec03.html)\n", "\n", "**Summary:**
\n", "In today's lecture we'll **motivate** why computer algebra systems are helpful, followed by an overview of **SageMath** (the system we'll use in this course). Then we **get started** with using SageMath, learn some elementary functions and how to get help. In the appendix, there is some advice on how to **install SageMath** on your local computer, and an **exercise for the lecturer**." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Motivation\n", "In practical mathematics, one often has to do concrete computations. As an example, one might need to compute the determinant of the following matrix:\n", "$$\n", "M = \n", "\\begin{pmatrix}\n", "17 & 2 & -4 & 9\\\\\n", "-13 & 2 & 8 & 3\\\\\n", " 6 & 1 & -1 & 4\\\\\n", " 5 & 5 & -2 & 2\n", "\\end{pmatrix}\n", "$$\n", "Doing this by hand can be rather exhausting (and prone to producing errors). For the above $4 \\times 4$-matrix, the typical recipes for computing determinants take a lot of operations:\n", "\n", "| Algorithm | number multiplications | number additions |\n", "| --- | --- | --- |\n", "| Summing over permutations in $S_4$ | 72 | 24 |\n", "| Laplace expansion (\"expand along a row/column\") | 40 | 23 |\n", "\n", " \n", "\n", "Luckily, instead of using our brains (or pen and paper) we can ask a computer to do the calculation for us. \n", "\n", "In the input cell below, we enter the matrix from above, and store it in a **variable** ``M`` in the first line. Then we ask the computer to print out the value of the variable ``M`` in the second line. Click into the grey box below and press ``Shift+Enter`` to execute it." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "M = matrix([[17,2,-4,9],[-13,2,8,3],[6,1,-1,4],[5,5,-2,2]])\n", "M" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Then we can compute the determinant of ``M`` as follows:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "M.determinant()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the calculation above, we used **SageMath**. This is a free, open-source mathematical software system, which allows us to do computations in many different areas of mathematics. In particular, it is an example of a **Computer Algebra System (CAS)** and we can use it for manipulations of symbolic objects, like polynomials:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "P = M.characteristic_polynomial(); P" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "P.is_irreducible()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "factor(P)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the course, we will learn how to\n", "* **use** the functions of SageMath\n", "* **apply** them to concrete problems\n", "* **program new functions and software packages** for SageMath\n", "\n", "On the other hand, we will **not** treat in so much detail\n", "* **theoretical descriptions** of algorithms\n", "* extensive introduction to **Python** (we'll have a **crash course**)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plan of the course\n", "The following is a preliminary plan of the topics covered in the lectures this semester:\n", "\n", "**Part 1 : Introduction to computer algebra** \n", "1. Introduction\n", "2. Linear Algebra\n", "3. Numbers and symbolic expressions\n", "4. Calculus and power series\n", "5. Algebra\n", "6. Combinatorics and graph theory\n", "7. Convex geometry\n", "8. External packages and software\n", "\n", "**Part 2: Mathematical programming** \n", "\n", "9. Classes and algebraic structures\n", "10. Tools for debugging and optimization\n", "11. Python packaging\n", "12. Documentation and testing frameworks\n", "\n", "The total number of lectures in the semester is 13, so we have a bit of wiggle-room in case a topic needs longer than one lecture.\n", "\n", "To get credit for the lecture, you should either\n", "* hand in a **short software project** (from list of topics or chosen yourself)
\n", " Example: PlaneTriangle (with functions for area, circumference, center of mass, $\\ldots$)\n", "* or have an **oral exam**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## SageMath\n", "### History\n", "SageMath (or Sage, \"Software for Algebra and Geometry Experimentation\") was originally developed by a team around William Stein at the University of Washington. The first version was released in 2005 and since then it has been steadily updated and developed. For more information you can have a look at the [SageMath wikipedia page](https://en.wikipedia.org/wiki/SageMath) or watch [this video](https://vimeo.com/13986940?embedded=true&source=video_title&owner=1449175) from 2010 describing the motivation behind and the beginnings of SageMath." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Features, strengths and weaknesses\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ProsCons
SageMath is free and open source software
don't need an expensive licensethere can be bugs or missing features
you can look at the source code and modify it if necessary
has interfaces to many other open-source programs (gap, singular, polymake, ...)
SageMath is based on Python
intuitive, convenient syntax and data structuresnot as fast as programs in C++ or other compiled languages
interactive session
SageMath is primarily developed by volunteers, who are researchers in pure math
lots of cool functions for math research
(elliptic curves over finite fields, hyperbolic 3-manifolds, ...)
code quality can vary ...
active and friendly communityless focused on applied mathematics and numerical computations
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Useful links\n", "* [Official website](https://www.sagemath.org/)\n", "* [Ask.SageMath forum](https://ask.sagemath.org/questions/)" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "## Getting started\n", "In an Appendix below you find a guide how to get access to SageMath. Please tell me if you encounter any problems, and I will do my best to help. For quick access to the present document (only requiring a web browser and internet access) click on [the following link](https://cocalc.com/share/public_paths/1cacfaf59fe6f43145b8344ba4fbb91da50b2ffd) and select\n", "```\n", "Edit -> Use CoCalc Anonymously -> Create Project -> Copy * to ** -> Open your copy of **\n", "```\n", "There are two main ways to use SageMath. One is to run it in a command line (or console/shell/prompt/terminal/...). For this, open the console (on Linux or MacOS) and type ``sage``+``Enter``, or start the program SageMath 9.X (on Windows). You will see something like the following:\n", "\n", "Then you can enter commands one after the other, pressing ``Enter`` to execute them." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Instead of the command line, we are going to use a so-called **Jupyter notebook** running SageMath as a kernel. This is the format you see before you - in particular, it allows mixing text (with formulas and pictures) and cells with code that can be executed.
\n", "To run the notebook of this lecture on your computer, you should type ``sage -n jupyter``+``Enter`` in your console (on Linux or MacOS) or start the program SageMath 9.X Notebook (on Windows). This opens a page in your webbrowser where you see files on your computer. Click your way to the folder where you saved the file ``01_Introduction.ipynb`` and click on it to start." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the rest of the lecture, we are going to play around a bit with SageMath, make some computations and see some of the basic features that help us using it.\n", "\n", "### SageMath as a calculator\n", "One of the most elementary ways to use SageMath is as a calculator: you can type numbers and combine them using ``+`` for addition, ``*`` for multiplication and ``^`` (or ``**``) for raising to a power. To structure the calculation, you can also use parentheses ``(`` and ``)``." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "7*8" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exercise\n", "Calculate the numbers\n", "$$17+3\\cdot(8-9),\\quad 9^{12 \\cdot 12},\\quad \\frac{24}{33}$$\n", "in the three code cells below. Remember that you can execute a cell by clicking into it and pressing ``Shift+Enter``." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A priori, SageMath tries to do exact computations, and thus the division of two integers is in general displayed as a fraction instead of a decimal number. To get the decimal digits, you can use the function ``n``:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "n(24/33)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Or, if we need it to a precision of 30 digits (not that this is very interesting in this case ...):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "n(24/33, digits=30)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It also knows a lot of standard functions, like ``exp``, ``sin`` or ``cos`` and universal constants like ``e``, ``pi`` and ``i``." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exercise\n", "Verify that SageMath is smart enough to know the following identities:\n", "$$\n", "\\sin\\left(\\frac{\\pi}{2}\\right)=1, \\quad e^{\\pi i}=-1.\n", "$$" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But what about the logarithm? Here we could get ourselves into trouble, since there are different conventions: some people write $\\log$ for the natural logarithm, some people use it for the logarithm to base $10$. To find out which convention SageMath uses, we can look at the **documentation** of the function ``log`` by typing ``log?``:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "log?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So this tells us that ``log(x)`` computes the natural logarithm of ``x``, whereas ``log(x,b)`` computes the logarithm to base ``b``.\n", "

\n", "
\n", " SageMath-Tip No. 1
When unsure what a function foo does or which arguments it needs, type foo? to see its documentation.
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exercise\n", "On a big lake, the number of water lilies doubles every three days. Starting with one water lily, how many days does it take before their number exceeds 10000?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)
\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Before moving on to more interesting mathematical objects, let's see another useful feature: **tab completion**. If you start typing the name of a function and press ``Tab``, you can see a list of all functions starting with the letters you already typed:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "arc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " SageMath-Tip No. 2
Instead of learning function names by heart or looking them up online, just guess the first letters and try Tab-completion to try finding them.
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exercise\n", "Mmh, I'm sure that SageMath has some way to compute the binomial coefficient\n", "$$\\binom{n}{k} = \\frac{n!}{k! (n-k)!}$$\n", "but was the corresponding function ``binom`` (like in LaTeX) or maybe ``binomial_coefficient``? Find it out using Tab-completion and compute $\\binom{20}{10}$." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)
\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interlude : getting to know the Jupyter notebook\n", "Since we are going to use SageMath within a notebook like the present one, it's a good idea to learn a bit about how to use it.\n", "\n", "As you have already seen, there are two types of cells in Jupyter:\n", "* **code cells** where you can perform computations with SageMath\n", "* **[Markdown](https://en.wikipedia.org/wiki/Markdown) cells** containing text, formulas, or pictures\n", "\n", "Clicking on a Markdown cell and pressing ``Enter`` allows you to see its source code. You can execute it and see the nicely formatted text again by pressing ``Shift+Enter``." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exercise\n", "Play around with the notebook a bit (in particular with the various options in the menu above). Some things you can try:\n", "* Insert two new code cells below.\n", "* Convert one of them into markdown and write a bit of text.\n", "* Delete the code cell again.\n", "* (if you know LaTeX) Insert an equation between two ``$$``-symbols, e.g. giving the value of the integral of $x^2$ from $0$ to $1$.\n", "* Find a picture of a cat on google and insert it into one of the markdown cells.\n", "* Save the notebook so you don't loose the picture of the cat!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)
\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Some first computations with matrices\n", "As we saw before, SageMath can also handle more complicated mathematical objects, such as matrices. As we saw above, you can create a matrix ``M`` using the function ``matrix``. Then you can compute information about this matrix (such as its determinant) by using the internal functions (or **methods**) of the matrix ``M`` such as ``M.determinant()``. SageMath also supports addition, scalar multiplication and matrix multiplication using ``+,*`` as before.\n", "\n", "#### Exercise\n", "* Enter the matrix ``N`` given by\n", "$$N = \\begin{pmatrix} 1 & 4 & 9\\\\16&25&36\\\\49&64&81 \\end{pmatrix}.$$" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Compute the determinant and trace of ``N``.
\n", "*Hint*: Given a matrix ``N``, you still have access to Tab completion by typing for example ``N.``+``Tab`` or ``N.de``+``Tab``." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Compute the matrix $3 \\cdot (N + N^\\top) - N \\cdot N^\\top$, where $N^\\top$ denotes the transpose of the matrix $N$." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When solving this exercise, you should keep in mind the\n", "
\n", " SageMath-Tip No. 3
Often, the easiest way to program something is to copy and paste related code and just modify it a bit.
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's finish up by seeing a first toy example of how SageMath can be used to solve \"real\" mathematics problems. Consider the following question, which might appear on a Linear Algebra problem sheet:\n", "\n", "**Question** For the matrix\n", "$$\n", "M(n) = \n", "\\begin{pmatrix}\n", "1 & 2 & \\ldots & n\\\\\n", "n+1 & n+2 & \\ldots & 2n\\\\\n", "\\vdots & & & \\vdots\\\\\n", "n^2-n+1 & n^2-n+2 & \\ldots & n^2\n", "\\end{pmatrix} \\in \\mathbb{R}^{n \\times n},\n", "$$\n", "what is the rank of $M(n)$ in dependence of $n \\in \\mathbb{Z}_{>0}$?\n", "\n", "#### Exercise\n", "Let's compute the rank of $M(n)$ in some examples, to see if we spot a pattern. However, instead of entering the matrix by hand, we can write a function ``M(n)`` taking as input the number ``n`` and returning the matrix.\n", "* We will recall the details about how to define a Python functions in a later lecture. Below, I have an almost finished version of the function ``M(n)``. Replace the ``????`` part by a formula for the $(i,j)$-entry of $M(n)$, where $i,j$ run from $0$ to $n-1$.
\n", "Here we use that a different way to create a matrix $M$ is to call ``matrix(n,m,f)`` where ``n`` is the number of rows, ``m`` is the number of columns and ``f`` is a function $(i,j) \\mapsto M_{i,j}$." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def M(n):\n", " def M_entry(i,j):\n", " return ????\n", " return matrix(n, n, M_entry)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Check that for some values of $n$, your function above computes the correct matrix." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Compute the rank of $M(n)$ for several examples of $n$ and guess the pattern." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* (optional) Can you see how to prove the formula that you guessed?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Solution** (uncomment to see)
\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Two take-aways from that last example:\n", "* Knowing the answer of a problem in some examples is often really helpful in finding a general proof, and computers can help us with those examples!\n", "* Learning a bit about programming (such as Python functions above) can help in doing computations, even if one is not primarily interested in pursuing a big programming project." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I hope you enjoyed this little introduction to SageMath. Starting from next week, we'll go into more details for specific areas of mathematics (beginning with Linear Algebra) and also recall more systematically some Python concepts like functions, lists, etc.

\n", "
\n", " See you next week! \n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "image/png": 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fEWXJQvTjj0StW7uvfQLPJi4ujkJDQyk2NpZy5Mjh7uYIPJBbt4gGDiTauJGoSxeiOXOIChR49vmSRDRqFNHXXyufnTlDVLmy+W19nujfn2j1aqLwcKLAQKLy5Ynu3yfy88NnpUu7ri2+rqtKYd06RSBp1oyoVSuiWbOIoqKI5s4VAom7eOklDAKTJuH99OlE48YRjR2LQaBNGwwoCQnubadAIPAuJIlo4UKiChWIjh8n+uMPol9/tS+QbNiASVEWSBYvxoJWCCTGM20akb8/BMBcuYhmzMDnFgvR5MmubYvLNSXp6dCGXLyI98eOERUqRFSmDNGgQViVC9zPo0dELVtiACFCh23alGjfPqJixYhWrCCqW9etTRR4GEJTIsiIy5eJ+vWDJrZfP0x4OXM++/yICKIXXlDev/EG0S+/YAwSmMeSJUR9+xLt2kXUsCF2LiIiiHx9ic6fJypXzjXtcLmm5H//UwSSbt2IatYk+uwzoqxZiT75xNWtETyL3LkhMO7Ygffp6UTbt2OlcuUKUYMGROPHE6WlubedAoHAM0lPhwBStSq2bXbsIPr++2cLJImJ0NbKAom/P9G9e0Rr1giBxBX06UNUvz6UA8zYvieClmviRNe1w+VCycKFyusxY4guXSL66Sd8aXvSs8A9NGuGwULuoCkp+CtJRFOmoBNfuuS+9gkEAs/j1CloUseOJRoyhOjsWYwlGSFJRFOnEmXLRrR3Lz7bvRsLHnvbOwJj8fUlWrAA4/m8eUTvvINdDCJstd286Zp2uHT75tYtqP6JiGrVIjp6lGjoUOULZ8niqpaYAzPRw4dEN25gIk9Px4Ml/5UkosKFiUqWJMqXz/tsZ06dgnpP3tKxZu5cSNi+brFSEngCYvtGkJwMG4QZM2A/smQJUe3azz5/506i5s2V91OmQGPuCWNjaipRbCyOuDjldUoKUXAwUfbsEKTkv3ny4LW306cPfperV4m+/Zboww/x+bffEn3wgfn1u1QomTOHaNgwvF64kOitt4iKFIFgMnWqq1rhPMxE//4Laf70aey7XbuGQ60RaNasEE6sjxIllNf583vGg/kk6en4HT/9lCgpyfZ/9epB1VqkiHvaJnAP8+fPp/nz55PFYqHLly8LoeQ5Zd8+ovfewzj42WdEH38MT46MuHkTHh3y9m/DhkRbtrhnUpckov/+IzpxgujkSeXvgwfayypSBJ4r5crhb/nyEMq8SVg5fhxKg3Xr4I1ZoAAEtJdewpxnNi4VSpo2xZfKmpXo7l2ilSuh2ouIICpe3FWt0Mf160R//w0joF27iO7cgVagXDnsgcrCRKlS+C7ZsxMFBGAvVP5LhOtkAcb6iIiANC6TNSuElHLl4J3Upo1n3aOICHjibN369P9++YWoa1fXt0ngXoSm5PkkLg7bNAsWYDv3hx+gJcmIxESinj3hfSNz+TIcHVxBejpsGmXh48QJaIDj4/H/YsWIqlcnqlED43loqO2RIwc0+omJRI8fYxGakIDX9+9j6+PSJdRx5QrqCwzE5N6mDY4yZTxzwWlNvXpEISFE27YRdegATygfH8zbZm+puUwoiYwkKlgQWobevWFHUrkyfiDrDupJpKYSrV8PV7Tt2/Gj1KwJ4appU0j3oaHG1RcTAwHl+nVFWDl+nOjAAbhmVaqETt26NeoOCDCubj0wE/38M9Hw4di2sqZ7d6L58+FeJng+EELJ88fmzUQDBsBbb9o0bOH6+T19HjPsFKzV/7/9RtS5s7ntu3cPMVGOHYMAcvYstpiIMPfIAkiNGnidN69xdaelQTDZvh33adcubP288AJRjx64VwULGlefkfzvf0S9ekHAOn4c7SUiWrQIMU1MxVVR2hYtUqLx7dih5L3ZutVVLVDPtWuI+583L9rYoAHzjz8yx8S4pz3R0cyrVyPTb4ECaFOOHMhbsGQJ85077mmXTGQkc8+eTyf6K1CAeds297ZN4DpERNfnB+sQ8S1bMkdEPPvc/fttx4XBg81NtBoby7x0KdKY+PriqFSJ+e23mb/5BqHU3dFFHz9m3rABEVOzZUMm5N69mU+dcn1bHJGcjDlm8mTkoAsKUn5rs3GZUCLnWAkKwheeMIE5NNSzsgDHxyMHT5YsCLE+YgTzuXPubpUtFgvyAk2ejGyaPj64r9WrM3/yCQYANQmtzGDLFuaSJZ8WTj74gDkx0T1tErgOIZRkfiSJedUqdSHib95Eoj15HChVyrws5CkpSMr35pvKBNqkCRbDDx+aU6czREczz5ih3J9mzZiPH3d3q2zp2hU5cZiZO3dGO/39mR89Mrdelwgljx7hyxAxN2+Oz2rVYu7SxRW1O8ZigWRdqBA69Kefek9ehago5p9/xqolTx7c49y5kbsmKcn17Xn8GEkVnxRMKlVivnrV9e0RuA4hlGRukpOZ+/TB89yly7MFjIQE5vfes33+Dx40vj0WC/OuXcz9+0NAImKuWpV5+nTk8/IGUlOZf/kF46OvL8ZOT5l7Vq3CPb1xg/mnn5TfcsUKc+t1iVCybZvyhT7/nPnuXbxevtwVtdvn8mXm2rXRnq5d3ZMV0SjS0/Hwy5mWy5Zl3rPHPW05elTZapKPPHmgOhVkToRQknm5c4e5Xj1okZcty/gcScJ2svUzP2cOhAejkCRsd3z8saJlKFGCeexYz9NqayE1FcJU1qzMxYsjOa27iYnBPDJ3LnN4uPKbjhhhbr0uEUrmzlW+0IEDsM/w8YEtgjv56y9sIZUty7x3r3vbYjTnzmF7h4j5/ffdYw+Tmgoh9EmtyeLFrm+LwHyEUJI5OXIEqewLF2Y+fDjjcw4dsn3GO3Uy1m7jzh3mL75grlhRWeAMHMi8b5/jDMPexH//MbdqpYzbaWnubc8rrzC3aYN7LGvizbYrcYlQMmgQvky2bJioundnrlPHFTVnjCQxf/klBKN27dxnwGo2FgvSUWfPjq2ptWvd0w7ZqNn6GDbM/Q+cwFiEUJL5WLEC2pG6dZlv3376/7duwe5Afq6DgrCqNoo7dzBWBAUxBwdj7ti40bNsEY1GkrBw8/eHgOLOx2nCBAgjksTcvj1+4yJFzK3TJUJJs2b4Mi+/jPfly8MC2x0kJWGbhgiGoUaqFj2VGzeUDtWpU8aDi9ncvw9bF2vBpFUrGHwJMgdCKMk8pKczjxqF57R376ft0xISoMa3fp7XrzeufmthJDSUedKk52+s2L4dHjBVqsBo2B1s3ozf9t9/madNU35rMxfyLklzJOdGCQuDj3h4OGJbuBqLBVFkt2xxjY+8DDNC9h4+jL+PHhFFR+OQX8fGIiiPHKQnZ07b1yVLIk5J+fIIcayFYsUQb2XNGkTPrVABYaD79nVdWPj8+REz4L33kGGYCIHX6tQh2rTJdcGTBAKBfWJiME5u3Uo0ezaicMvBvpgR9LJnT+X8ceOQnNOINCF37xJNn454GFmyICjbBx84nxdNkpD+4/x5ogsXkPJEDn72+LHt66Qk1FewIAKFWf8tXBixqkJCnP+ujmjeHDGq2rRBHqFdu1w/TsopAg4fts0Kf+ECAuWZgenB0+LilABjM2bgRtesSXTokO2XNBtmRI9duBDhc9u3N6+uuDiigwfxQx4+THTkiBKyOF8+ZODNnRuBxeQjZ04E1pHzK8TE2L6+exfX+/ggPHPFihBSKlVC0J+wMHVRAqOjiUaNQk6Kxo0RGK5sWfPuRUb8+COEE2u2bSN65RXXtkNgLCJ4mvcTHo4InlFRyEnWooXyvyNHbMfs+vWx0Clc2Pl6rYWRoCCiESP0CyNRURh3L1xQhJCLF5UUICEhiI4dEqLkrrHOYxMUhHHy3j1Eab13D0diIq7380MY9pdfxtGwIa41i3v3EKxTkjBv5s5tXl0Z8eKLRO3aEY0ciSjjRIja++QYbhjmKWHAkSOKymftWrgW+fi43u1p6lRzjSwlCcayb78NC2oiuKm1agX33M2bmR880F9+fDyMzJYsgdq0RQvYicj3tkwZ5tGjcY4aw68dO5hLl0YAnylT4OfvSp40jCOC/YvAexHbN97N5s3YLihfnvnKFeXzW7cQysH6WT1wwJg6rbdpcubUt02TmgqvvnHjmGvWVNoYEgJbmHffZZ45E44N16/rN4yNj2c+f5554UKYAOTPj3oCApgbNmSePRuBxszg339h29GkievH6jfewO+flsbs52e+B47pQsny5UonOX0aX+bFF82u1ZZly1D/xInGlx0VxTxrFh5kIuYXXoCVeHi4a6zCHzyA4dd77ynW0cWKIWDZ7t32A6klJjKPGYOOVqmSObEE7HH3rm1wJSJY1GdmI7bMjBBKvBNJQiAvHx/Ynsk/X2Ii7O6sn89Fi4yxw3tSGJk8WZudwtWrzN99x/zaaxA+iBDQ7a23MN5fu2b++CtJEFLmzUM7/P3xXcaMMcdub+9eLCLfece1HkcffYQFLLMSHLNVK/PqM10ose7Ujx/Dnej1182uVSEiAlbbRv+QCQnofIGBOLp2hWGSOw1n09KYd+5kHjIE7ntEzPnyIazxli3PlrBPnkQwOx8fCDNmSfsZkZKiBGSSjwYNnNMqCdyDEEq8j8REJVz8uHEYvySJeeVK22fy3XeNMTR1Rhi5dAna4LAwtMnPj7lRI4QdOHrU/U4LN24gPUlICLQnffoYHztlxQp897lzjS3XHvPm4fukp0NTQ6REejUD04WSoUPxJfLnx/uqVeEi7AokCRJdsWLGTrSbNkFizJIFWzNRUcaVbRQWCzQfo0ZBe0MEK/aePZn/+ANClTVpacxffw0Brlgx1wfv+f5720HQ35/5wgXXtkHgHEIo8S5u3sRiJGtWRBVlxna7rHGVQ8OfP+98Xenp0MZoFUYeP8aWf6NGypZ4v34wBfDUUA4xMfiuRYqgzcOHIxquUQwYgDAPt24ZV6Y9Nm3C97h5E+YJRMwVKphXn+lCycCBis0DM3PRosyffWZ2rUCWKo2aYG/dUnIAvPIKosF6A3IUxPHjleBDwcHYK1y50tYP/upVJU9Rt25w5XUVTybuIsI+t8A7EEKJ93D2LLSpxYoxnziBse2112yfvXXrjNEu37jB3LQpNLEffuhYmJAkLKj69sXkK4+3q1a5J3WGXlJSsLUfGIjFuBHCHTM0VvnzYy5yBefP4zfYuxeRc2Vh1SxMF0r69cOXqFoV77NmRaZGs4mMhMTfrZsx5f39N9RyBQpgIvfmKIKXLsHnvFYtJajd3LmK+lOSINDlyYPYIj/95Lrve/s2BFjrwfHrr737fj8vCKHEOzh0CBqHatWwvT1pku3zNnGicZP/qlXQjBQtiq1le0RGYhKvUEGxjRs/3n4GYm/g1CnYHAYFMS9YYMxY9vPPuEebNjlfliMePUJda9YofaVQIfPqM10oke0F6tXD/iWR+Ql9mCEM5c5tzEr/t9+wp9amTeYL4HP9OtSBRNgv/O8/5X+RkdjuIYL19b//uqZNycmI3PjknraIAOuZzJs3j8uXL89hYWFCKPFwtm3DIqRhQ3iRWD9jrVsbF6QrJkYZO7p1s59Z9uFDbDMHBUGr0KULbODcle3cDBISlF2Djh2d9z6VJGiPSpY0X3uUkoJ2L1umBFDLmdO8+kwXSnr1wpdo1gwd3hXS3b176Nxfful8Wd9/j+yNb72Vub1CduxAYqvgYFutCTMGiBIloOWaPt01woHF8nTEyNdfd707nEA9QlPi2fz+O8bFfPlswwlky2Zs4s49ezBe5MiBBeizNAMJCRijc+ZEGzzVPs9I1q+Hxv2VV5y3M7l4EVtiS5YY0zZ7BAYyz58PrTURBEizMF0okVe8bdtCjUUE9aGZTJiAydWedK6GL79Ee4cMcb9ltyuIi1PyFL30kq1mJD4eQoKvL3P16szHj5vfHjlHkbVg0qqVd+0rP08IocRzeTJ7r3x8951xGonUVHjw+PrCMPVZ2y5paVjsFS4MDfSQIVhIPi/88w+cJDp3dv7et22LMPRmb2/nyoUF6bx5St8xq07ThZI338QXePNNBNwhgpGVWSQlYSXgbG6dWbPQ1vHjnz97hp07oRYMDmb+9ltbgezIETwEfn7wX3/Si8cMfvjBdiBt1Mg19Qq0IYQSz+Srr54WRgb+TSuJAAAgAElEQVQMwLaJUVy6BBs1f38EqsxospUkaGvKlkUb3nrLdrv4eWLdOghv/fo5N79s24Z7+c8/hjUtQ4oVg4PK4sVKHzJrcWi6UPL66/gC3bsj2igRNCZmsWQJVFrOeMYcOYKHa9Qo49rlbcTHQ7AjYm7c2DbCY2oq9hazZIG78bZt5rfnjz9sB9UqVVwbT0XgGCGUeBaShFhK1s9N9erMZ84YW8fChVjAhIUhXkhG/PMPoqvK2s4TJ4xrg7fy00+4H2PG6C9DkuBR+dprhjUrQ158EfOhHIiUyDz7StOFEjk7bfv2zMeO4bWZqv9q1VCXXuLiEL2udu3MbUOiln/+gfuX7DVlrTW5fBmufkTIJGp2wLNdu2wH2BIlMp/hsTcjhBLPwWJRPB/lY+lSY7W+kZHK+P7++4gp8iSnTjG/+irOqV3bsQfO84askZfjxOhh0SIsxK9dM65dT1K8OPOnn9oKJWbNj6bniJWTxMXFIZEREbL1msH160SnThG9/bb+MoYORRKmlSuJAgKMa5u30rQp0ZkzSL40fDje//sv/lemDNHOnUjOtH49MhivXIkuawZNmhCdPKm8v34dCaIePjSnPoHAG0lNJerSBck2ZdauJerdW13STjVs3kxUuTISj65fj0Sn1knpIiKQSbh6dWRG/+03JMl7+WVj6s8sjBxJ9PrrSEAYF6evjO7dMbdu3mxs26xJSUHW5uhovM+d27z50XShpFAh/HWFULJ1K+rQm2121SqiZcuI5s9HZkQByJ6daO5con/+Ibp9m6hKFaJvvkHWSh8fCCwXL0Jg6dGDqG1bCAxmUK0ahCL5gYiLI8qbF4KkQPC8k5hI9OqrRL//rny2bh0mPqPKHzIEz3iNGkRnzyKrsExkJLL7li2LBcvChUTnzhF17mycQJTZ+OYbZIOfOFHf9SEhyN68c6ehzbIhJYUoMFARSvLlM68u04WSokXxNzZWmUhSU82pa8sWpNPWk+46NpZo0CBInb16Gd+2zICsNenbF5J9kyZEV67gfwULEq1ejVXTmTNEFSsSffutOQJo6dJEN24QFSmifFawIAQmgeB5JSaGqHFjLB5k/vyTqGNHY8o/eZKoVi2iJUuI5s0j2rQJzx0RUXw80aRJeDaXL8frf/8l6t9faJwdUbw40fjxRHPmYOzUQ7Nm+N0lydi2yTypKcmf35x6iFwglMgTR1QUVD5ERI8eGV9PWhrR9u1YJehh4UKsAmbNEhK9PbJlw8OzaxfRnTvQmsyerQgfHToQXbgAVfGIEUQNGmA1ZTQFCxKdP09Us6byWdGi5mloBAJP5v59CAwnTiifbdxI1L6982VbLEQzZmA1niUL0fHjRIMHY5xMTYUWtXRpomnTiAYMIPrvP6KxY4mCg52v+3lhxAiisDAsjPUIFs2bYxv79Gnj28YMoSQoSJm7M4WmJD6eKE8edOSoKOPrOXgQdegRSpKToUJ7+21lu0lgnyZNINX374990SZNiC5fxv9y5MAW2L59+E1q1CD69FPcZyMJDUUd1tt1JUtiUBSYy/nzRKNHQ0DdupXo2jXztmUF9rl7F/Yd1v1+82ZssTjLjRt4vsaMwcR5+DBRhQpKHeXLw9asXTs8/199hXFeoI3AQIyZ+/fDjEAr9eoRZc1KtGOH8W179AiCUt68rtGUmO59IyfzIYJ1dp48zF98YXw9kyYhrLyeIGfffw/r5fBw49v1PLB7NzyWgoJgTW4doyA5Gbk0AgLgMrhrl/H1p6Uxd+1q62lw8aLx9QgQHyYwMONAXETwviGK5bAwRHOeNw9uog8fZq6w4Z5CVBSSs1n/Dlu2GFP2qlXILP5k3prkZOZhw1BXy5bM584ZU58A97NBA33XtmiBVAFGc+4cfut9+5jr18drM5Pqmi6UxMYqD8vZs8zlyiEyqNG89RaCamklPR0+2G+8YXybniceP8ZA5eODh+rSJdv/nz+Pz4ngqmi0K68kKbk25MPIeAwC28BJcuyh9u3hLvikUJKx0ILEZNevu/ubZA5iYmzDxRMZEzPIXt6aixcRdiEwECECnrfAkmazahXuu544W19+iXD9RqfikAO0/fefkix17lxj67DGdKGEWXlg/vgDgbh69jS+jtq1kfxPK7/9hrYdOWJ8m55H9uyBkBcUxDxzpu3q2GJB/oSQEOaCBZF10shBzWJRIgjLhyvC4Wd2YmJs7+kPP2R8nhyn5NGjWH70CIuQJUuY+/dHsDvrMnbscO13yGzExyNwodH31Dpvzf/+pzyfkoTfPTgYEVlPnnS+LsHTJCZCO/XJJ9qv3b4d/cDoxKnLl6PcuDilrzkTV8URLhFK5LDCM2ZAzd60qbHlSxKSOunZFurQASopgXEkJDAPHw6tSf36T2tNbt7EfSdCxsxbt4yrOz1dKVs+Dh40rvznDTkBFxFWxxkFyJJxFDzt/HkIq3J5s2aJlbYekpKYq1a17ePOhhlPSXl23proaGV79L337PcBgfP074+w7lpNEWRTCSOTKzJj3s6RA9obub/t329sHdaYbuhKpBi7/vsvAm7JbqRG8eAB3OHKlNF2XVoa3KjatDG2Pc87wcHwyNmzB0bN1aoRzZypGEIWLYrYCb/9RnToEAznFi40xp3Nzw8xGlq1Uj6rXx8GZAL1JCTAKH3kSLz/5RdY4FsHyNJKhQpEly4RvfAC3n/4IdFbb6EugTpSU4latrT1sti1C+76egkPh5fcjBlEU6agvJIl8b8DB/D8/vUX+sAPPzjXBwSO6d2b6OZNW9duNchOGnfvGtuemzfhRRsernxWubKxdVjjEqGkWDH8/fdfuD3dvk30+LFx5ctCjlah5OhReIe0aGFcWwQKjRph8Bw4kOjjj/H+0iX8z8cHAZUuXiR6802c06QJ3juLvz/Rhg220SMbNUIQJ4FjTp1CwDwiWNknJRF17WpM2SVKKBMdESa6+vWFx5Qa0tMRBG3vXuWzPXvw3OiBmWjRInjHxcfDg3HcOAj2FgvR1KlEL72Eye70aeP6gMA+9etjLlu2TNt1OXPCZdtooeTiRaJy5RSh5MUXEbDNLFwilMgD0IULiuAghyo3gogI/C1dWtt127bhh6xVy7i2CGwJDib6+msMpA8foi989ZWiNcmVC6uvf/5BrIVq1YgmT3Y+wF5AAFZ3DRsqn1WuDBdHQcakpiKqZPXqeC+nXAgKsn/d/PnzqUKFClS7dm1V9RQogNV448Z4f/bs0zE2BLZIEsK2W4cS37dPuYdaiYxEULUBAxAs8sQJZRy8fRtuwJ99BlfgPXsUzYnAfHx8iF57Dc+I1usKFTJHKClfXhFKatQwtvynMG9nSOHQIWUv6vZt/P31V+PKX7gQ9gta96cbNmTu1Mm4dgjsk5DAPHIkfqu6dZ92201MZB47FhmaK1ZkPnDA+TqTkmAEbb3/bmTK9syCxaIkTiNiHjpUexlaE/IlJDC3bavUWaYMDDgFtkjS08n1nHk2DhxgLlCAOW9e5vXrbf+3fj1CKxQuLJLnuZOVK/E7a01y2qAB89tvG9cO2bh1+XLYGhGZE9LDGpdqSogghefJY7s/5SxytDktkVjj4mDPoDdPjkA7wcGImLtvH4LwVKuGfWxZa5I1K9EXXxAdO4bXDRsiz4beRFVE6Be7dhFVrap8VrUqovcKFL79FmkaiGBjNXu2+XUGBxP98QfsSoiwDTtsmPn1ehPMRB99ZJtc7+BBqPj1sHkzon+WKWObtyY5GZqxjh2VbVeRPM99yNrKU6e0XWe0pkTebi9fHuO2ddvMwiVCSZYsyhc5dAh5UYwMh5ucjDq0cOAAJsPmzY1rh0AdDRrgYRsyBOrhhg1tbUmqVkU/mTWL6Kef0F82bNBfX3Awto9kFfStW7AjSk936mtkGs6cUQxaK1RAREk5eabZBAQQrViBvkBE9OOPyKEkAJMmYftT5vBhRO/Uw4oVEEJatiT6+28lb82FC0R16kDwmTcPRuh58zrfdoF+ypTBuGWdFV0NRgsl8ricK5fymdlCib+5xSvIaecPHcIDYOTAIycL0sK1axh4tdqheAKRkUgHfu0a7GmuXVM6oo+Pcvj6YnApUUI5ihcnKlwYxqDuJGtWeOR06kTUpw86+qRJ8Mjw98dvM2IEDPsGDMBg2qULwpoXKKC9vpAQCEIlS8JT68AB7KWvXPl85zpKTlYMGLNlQwK3HDlc2wZfX/yuISHIn9K1K/KslCjh2nZ4GjNn4pmQOXpUv/3brFnQuLz7Loxb/f2hhVm8GGHiS5UiOnIEuaw8kbt3MdZFRsLOKTJSOaKiINyGhipHzpz4W7IkFkHeFvrezw+LM61CSWCgsYutkyfRN6yVCHrGXy24bGqSpfs//8RqaOZMonv3FGndGeTtGy3cvg2p0lUrQmdISsIWxJYtOOQcM0SQYEuWhMuWry8M4uSdZ4sFD/KaNbZJEAMCoP5t0QKrppo13XcfZK3J+PGw/F+7FtoROb9GyZIwWF25EoNn+fLoO336aBcmQkPh5SEPUL/8gonvyy8N/Upexdixiop2wwb3Cek+PkSff47tnEuXIIDu3+9+4dldfPcd0ahRyvvjx/UZGDIjR9FXX+G3njoV9zo6mqhfP7jPv/8+tDGekkDv8WN838OHcRw5Au2mjK8vEsLlz4+jQAFMxDExWKDFxuKIicHcQITxpFEjGAY3auQdhrvVq2t3C05MNPZ33LsX90veumnd2riyn4m5JisKERGKkdbhw/j755/GlP3hh8irooV33mGuV8+Y+s3ixAnm115TAk4VL878/vvMq1cznzqFSJtqiY9HDoPNmxEeumNHRFYlYs6Vi7lzZ+ZFi5ivXjXv+zjiwAEE2gsMZJ42DTltrImKQj4VIuZmzZivXNFXT1SUrdGgmSGTPZmtW5V78N13zpen1dA1I06fVto0aZLzbfJGZCNH+Th0SF85aWkY54iYZ89WPt+7F8G5cuZEVGV3k5KCcen995krV0YANyKETG/alPnjj5l//x3jV1SU+qBiksR87RrzihUou0IF5Z42bMi8bp2+XGmuYvFi3IuEBPXXvP22vnQrGREXh/oXLVKcBcaONaZse7hMKJEkpUOsW4ckUkYl9fnoI1jua6FFC0zEnsilS0q49LAwRL68cMH46JepqUiyNH48Iq/6+aHO0qWZBw5kXrvW+Bw1jkhMZB41Cg9D7doZJ/vasoW5ZEkIa7//rq+ee/dsB/7ffnOu3d5GVBQ8MIiYX37ZmDKNEEqYmUePVn6XffuMaZu3sHevbb/cuFFfOQkJyEvk749w8cyYgCdPVqK2ujMHUVISPH169UJYddn7ql8/hLM/e9acBI4PHmBRJ3uSlC2LhKxJScbX5Sx//YU23ryp/po33kBSPyOQc94cPWo7d5uNy4QSZiX895gxcAU06uZNnQr3Ni2UL49Q6J7E9esI4+znh5XMkiVPawvMJDoagsjAgchfQ4QBrH595LFxpYBy8CCSNwYGwgXtyfvw+DEENz8/rCz1EB5uOwGYkcHYU3nrLeNDRhsllCQkoP8TIQ+Lk8V5DVeu2PbHxYv1lfPoETQBwcGY2JixAOnVC+7448e7dlyRSUiA8N+tG3P27PiOFSsyT5gAIcTVKQcOHGB+/XXckwIFjA1TYQS7d+MePZmmwx6tW0O7bgTjxzPnyYOcSnKfjIszpmx7uFQomTYNX6xRI0w0ISF4WJzlu+8wOWnp1CEhzF995XzdRiBJWMEEBjLny4ftFU+Q3K9ehequUyfmgAAMJMOGuW6LJykJqltfX+ZatTBwWZOWpgy0P/2kr459+2wngtOnnW62x3PxovJ927QxrlyjhBJmqPPlNn7+uQGN83AePlQ0lUTIQ6OHW7eYK1VCrBF520eOBxMQYG4itWfx8CHzxInYJiZCluEpU6D99QTCw6E1J0IcJXcIbBkhayhOnFB/TZMmzD16GFN/s2ZQJEyebKxG1REuFUp27bLNaEkEdaWz/PorylI7Fj5+jPN//tn5up3FYoFmQh6IPDV41J07yFyZOzeEhM6djQlupoZDh6DZCgyEVsx60LBYlMBSeu0i5P4jH9bJyDIjsp0BEfOxY8aVa6RQwqwkgcuWTdu+ureRkgJbCvk36dxZn9YgPByapaJFlQn/0SME1MqWDTZEruTePWzFZc+OrdahQ5HUzRORJCwG/f0xsd+75+4W4TfUuoVZuzbGQ2dJTYWmbcYM5saN0Y6ZM50vVw0uFUpSU2338HPlgorIWf7+W9tkIkepc8eqwZrUVEi1Pj76VbWuJiGBecEC7P8SwVj4t9/MX10kJWHbz9eXuWZNW62JJGHAe9KgTwuyFk8+oqKMabencf268h2NjmZstFBy9arS1m+/NaRIj0OSsJ0hf8/KlfXZUhw9ii3s8uWZb9zAZ7dvQ2uSJ49+Y1k93LiB5zEoCALJxx97xiSvhj17sJVTpIj7s4tfu4Y+8fff6q+pWBHabGc5cgR1//OP0jddpdlyqVDCrHhPvPsuVgT16ztf5rFjKPP4cXXnp6Tg/GXLnK9bL0lJUI0FBHjeXqYaLBZ4TzVpgntZsiRWGmbvOR4+jIE3IABqfXn7T5Iw+OkNgyxJ6JPyA1ioUOZM0S4Lb0RPb4c5i9FCCTNzly5oa+HCeG4zG1OmKL+Hvz8MvbWybRsm/3r1lLDkly8/rTUxmytXmPv2xbOZKxe2bLwxpcPt25iXAgIgpLiLyEj0iz/+UH9N0aLQaDvLrFkQKteuVfqnq2x+XC6UWH9J2RZEi2trRty4oc1SXfYEWrTIuXr1Eh+P/bmsWbF37u0cOwaNj78/c44c8IaSV2tmYK01qVGD+cwZfC5JGAiJoIHT+hClpSEnj9w/X3rJGJsnT+H+fWjliJi7dze+fDOEEnnFRgTD78zEL7/Yauf0TOC//orJs3VrRYg+fhy2aeXKmfscypw7B8NpX19oGWbMcI1BpJmkpOD5L1wYwoE70GpmIJ+v177OmubN4aEqb40PGOB8mWpxuVCSkKA8hPJevrNuRhYLJvivv1Z/TZYszHPmOFevXoYOxX6dO6VwM7h5E9qK0FAImz17YiI0iyNHEHsgIAArTlmA+PJL9KtRo7QLJvHxSlwYIvj9u9orwCzGjVO+V3i48eWbIZQwK9q4sDBz3ETdwYEDtgLJtWvay/juOwiZPXsqfX/nThjx16mjPZmbVo4dg/cKEbyl5s7Vp+nxVG7fhnD36qvuiWcimzuoFTKOH8f5zm7VPXiA8Xv+fKV/GhVTTA0uF0qYlcygEybA9bRvX+fLrFIFAXLUkiOHe7xvTpzAisJVRkPuID4eNgD58mGfW28sETUkJ2Oy9fNjrl5diWvyzTfoY0OHah9Q7tyxnTBmzDC+3a4mJgaaLCLmPn3MqcMsoWTDBuW3WL3a0KLdgrWtDBECIWplyRJcO2yY0r9//x3G4C1bmmswv2cPc6tWqP/FF9GWzLi1xgzjYB8f2Jy5GnkcUisQ/Pwzznd252HpUnznP/5Q+qgrt7LdIpQsXarsE48ejYnLWUPJN99E9D+15MvneldDiwX7vhUrZq5tgWdx/z585olgS2RmnJOjR6E1yZkTGhRm5oULUXe/ftoFk3PnbCeOTZuMb7Mr+eIL872LzBJKLBbYEcnupN6suYqOtu1XWuwFZH79FQubAQOUe/H99/isWzfzBITt27GlQQQD2pUrPcd91kw++QSLHldrtk+exL0+fFjd+Z9+Cls4Z+nQAR5bY8a41hVYxi1CycOHykO5bp3iIuwMWn+QokWNiyirlh9+wHfdvdu19boTSYJBcY4cuOdaLMm1EhODhylHDsVdeelSDNa9emkfQHfutJ1ALl40vs2uIDEREZTNsiWZN28ely9fnsPCwkwRSpiVZ8eIscJdpKbauv7q8TzcuBEar549IaxJEtzkiZiHDDFnmyElRTGQrl3b88OzG01aGoSxUqVcu324ZYu2rb033kBsEWeQt69nzoQHEpE2swgjcItQwgxVu+z7XLw486BBzpW3YgXKU2tgVbasayO6PngA17yePV1Xpydx4wbzK6/gNxo0yDx1YFwcBpDs2ZWVzS+/YKXz5pvaNVSymlz2jnB12H0j+P1351bmajFLU8KMbTpZsOrf3/DiTUeSmHv3Vn6Hl1/WrvHZuRO2cK+/jonSYsH2DRHyBJmhQbp+HcbfAQGwMfBmLZUzyB6e69e7rs7ly1GnWjudChWYBw92rs7ffkOdskBEpC3MvRG4TSiZO1cxkBoxgrlgQeekbzn6nay6d8SrryI3hKsYNAgr+Lt3XVenp2GxMM+bB6PkF180Lrz5kzx+jBVDcLCyql63DgNr9+7a+9nw4coD2qCB9xlb9uiBtmfLZq4hoplCCTM0AUQQ7r1t22DGDFutm9aIzQcP4vdr2RICWmoqFjg+PogbZAabNyNYYokS6sfVzEzdusalRlHDV1/BaFkNaWkY3+bNc67O7t2Zq1ZV4jYZEbJDK24TSm7eVB5QWUBxJrprUhKMvNR61AwdCpc5VxAXh4l48mTX1OfphIfDtsbXF/uWycnG15GYiAEkKEiJZLlmDeocOlTbik+S8HDK/XXECOPbaxYpKRCGiRDzw0zMFkrkXCBEsG/wFqxD5hPBgFELp07BVqpRIwjcjx/DBdisGEfp6dgOJ4JTgjfGGjEDWXNhhudaRnz0ERZvapDzeDmztZmcjLFi4kQs6Iiw/e1q3CaUMCuufoMHw+h1yBDnyqtfH6Gp1TBnDoQYV6x6f/wRKxp3ZuX0NNLSYHwZEADPKT0eCI5ISsKgGhioxLBZtAh9TquAmJRkO7G4M/CeFuRMo67wXDFbKElPVzIba/G0cydyVE750BrW/9IlbFvVrAmbqYcPMc5ly4agaUZz7x60jL6+eD6fJ9sRRyQlwSnDVdv+vXohsaIa5PhfWgVea2ThWXYQ0GIOYSRuFUpWr1a+/LBhUBU6s2r+6CMYU6pB3jNzRXK5pk2dN0DKrJw6BeO/gICn89oYQUoK9uADAhR7is8/x2+vVe1965btBKPWKt6dyMGPgoLMz6tktlDCjG1QImM89swmOVkxFiRi/t//tF0fEYHxrEIFpD24dQuee3nymLOdsmcPnAUKFID9iuBpRo9GHCZXuMi+8or6VBAffICo2s7Y/HTvDlvL995Df1W7wDcatwolcrh3IiXcsjOrOdmvWk0Uw//+Uwx6zOTRI2hJfvjB3Hq8meRkJUJrvXrGq0dTU2Hk6u+P/iVJEIJ9fLSrv/fssRVMPDmnR3o6XN+JIJiZjSuEEutcHJ7uhWOdtkBrRMw7d5hLl8Zx+zaeieLFYYNntBeYJMF+wc8PRuLOrLYzOxERGDe0CphakSRoyNR6iJYv71wivqgoaJQnTXJ/GARfciOBgURjx+L1zp1E9esT/fij/vIaNMDf/fsdn1u8OFFAANGVK/rrU8O+ffiJmzUztx5vJksWomnTiPbuJXrwgKhaNaJ584gkyZjyAwKIVq4k6tKFqFs3olWriL7+mqhHD6KePYm2bVNfVuPGRF99pbxv25bIYjGmnUazfz9RVBRed+7s3rYYRePGRPny4fVvv7m3Lfb4+WdlLCtZkmj+fPXXPnhA1KIFUXIy0fbtRHfuEDVsSJQtG9GBA0TlyhnXzpgYok6diEaNIvroI6IdO4gKFTKu/MxGyZJEpUsTHT9ubj23bhFFRhLVqqXu3IsXiV55RX99y5fjb7ZsymctW+ovzyncIwspWEc3nDwZq2VnXJDKlFFvm1K2LNReZiJvKT2vrnRaefwYNkZEyL9gZO6O9HTmd95BH1u6FBqUNm2wP69lK0aSlCBSRIgo64nI7qIBAcwmKi/+D1doSpihdSCCFsgTPaGeDLynRdUfGwv7kXz5oBE5dOjpZHtGcfw48wsvwIjWla6u3k6nThibzES2Ebl92/G5P/0E7Y3e/iFJmAu7dVNCdbg6hpc1btWUEBGVKkVUty5ep6Vh1SxLbXpo1Ijon3/UnRsWRhQerr8uNezdi9Wdj4+59WQWsmWDluTvv4kuXSKqVIlo2TIM787i50e0ZAnRe+8R9emDcn/7jahqVaI2bbDaUIOPD9HWrcr7L74g2rTJ+fYZCTPR2rV43aoVUY4c7m2Pkbz5Jv5GRRHt2ePetjxJfDz6rMylS7arT3skJhK1a0f033/Q3qWlEbVuDc3h9u1EefIY00ZmosWLoVnOmZPoxAmiDh2MKft5oEoVotOnjRmTnsXRo9BYFS7s+Nxt24hq1NDfP/buxTzYrBnRyZP47P339ZVlBG4XSoiIxozB3ylToGb+8Uf9qvu2bYnOnyeKiHB8bp06RAcPmqd+Z8ZEV7WqOeVnZlq0IDp3jqhjR6J33oGKOTLS+XJ9fYkWLiQaNIioXz8IJhs3YgBo2ZLo5k115QQFEd24obxv147o+nXn22cUx44p3yWzbN3IvPSSMgD//rt722INM8YfmZUricqWVXdtSgrR669DQPjrL6Ls2dEfS5Qg2rBBvWDjiIQEPE/9+0Mw378fC0OBeqpUwRbb/fvm1XHsmLqtG2YIrM5s3Xz/PdGLLypzZps2REWK6C/PadynpFFIS1NUnXLQFr0GqHFxMNj59lvH5+7bh7qOHtVXlyPkcPqZIYmYO/n9d3hb5MsHtaYRyMauRMjhcfs2rNfLlYPRl1q2b1f6btGi5sRc0YOct8LHB8bWrsBV2zfMzJ074/tVqGB6Var5+mulL2gJ55+WBkPkLFlgvHvrFvpiWJixWbYvXYL3TnCw+YaamZkrV/Aby/GPjEaSmHPlUhe24PRp5+L2PHiAfjd5stJ33e155RGaEn9/ok8/xett24iqVyf69lt9ZYWEEL38MtGffzo+t3ZtouBgol279NXliKtX8bd0aXPKf17o1AlakwYN8Prtt2Gg5ww+PkSzZxP17o3j/EPutZMAACAASURBVHlsGT16hNXu48fqymneXDHWvnWLaOhQ59plFPL2UsuWRLlyubctZtCwIf5euED08KF720IEA9SRI5X3S5equ44ZqvING4jWrMEqvGVLaG+3bSPKn9+Y9v36K1beFgu2Bnr0MKbc55EXXsC8ceaMOeVHRBBFR6vTlGzbBq2t/DxoZcUK7Er4+eG9vz9R06b6yjIM98pECtevK5KavMrT6/o2bx7cP9WkcG7RAsaOZiDnERAREY1BkmCgamRyP9nYNXt2BLY6cQKhnVu0UK/1kCTEd5D7788/O98uZ7AO9KY2wvEXX3zBtWrV4uzZs3O+fPm4Y8eOfOnSJU31ulJTIqeVIEIKAXdy/76tYeutW+qvnTlTCcYXG8tcqxY0gka5xVsn0+vWzfxYNc8Ldeogl5EZ/Porfi81WrJWrTBW6UGS4ErcuTPGPDm6urvxCE0JEVx0W7fG62vXiAoUIJo7V19Z7doRpafbGiM+i6ZNYeiTnq6vLnvExeFvaKjxZT+P+PhAq3H2LPbqW7YkGjIE++R6CQggWr2aqGJF9L+QEGjZ9uyBRkaNbZOPj62RbI8eWMG7i9Onldeym7wjdu/eTYMHD6ZDhw7Rtm3bKD09nVq2bEkJztxcE6laFatVIjy/7sJigf2TzNat6vfjN2+GK+6YMTDe7dCB6PJllBEW5nzbbtyA/c3ChXBJXrkStioC58mblyg21pyyDxyALZEjLVl8PMYpva67u3Zh3CpaFGURYcxzO+6Wiqw5fFhZbfTrh71PvfvhVauqy8h74IB50TnnzYN9i8B4LBZoAYxK7hcVBbe4F15A0sS1a2GPoSW9/JEjSv8NCjI3+Z095s1DG3x9tWdFlomMjGQi4t27d6u+xpWaEmZESSbCqtVdjBun/OZaMrSeO4fVaYcO0Mi1a4e+7Ez+L2tEMj1zeeMNc5LzSRLGIDXB9pxNX9KyJVJ8VKmC/jt2rL5yjMZjNCVE8IapVw+vk5KgvfjhB31ldeyIFW9Skv3zatWCZbsZdiWJiURZsxpfrgBeNEOHEp06BU+Mxo1hl6TXaytvXqxQk5Nhfd68OdHUqUSTJ6sP0lW7Ns4nQjnDhulri7McPYq/DRtCE6SH2P+/DMydO/czz0lJSaG4uDibw5XI++jHjzunLdPL5s1wByfCfZ4zR911Dx5AK1KyJPb0330XfW/tWoQ0cAaLheizz9CH69eHN0/t2s6VKXia4GDHc4sezp+HLaIaF+3ly2E/Wby49nqOHYMNXatWim3M8OHayzEFd0tFT7J3r7Ly6NgRYZX1rPYuX0YZq1Y5PrdVK+ZXX9VehyMmT0YeCYG5pKUhn42PD7weUlL0l3XmDHJbNGuGFWy3btDYnTyp7npJwupU7sMbNuhvi14qVkTdH3+s73pJkrh9+/bcqFEju+dNmDCBieipw1Wakq1b3Zc1+PZtWzsStXZjKSlIRJovH0KWDxqkL91BRohkeq6jXz/m2rWNL/fzz2Hf5sieLSLCuSy+nTpBw9yunb40CGbicUIJM9wyiZh79MDfJUv0ldOggTph48svEdUzKUlfPc9i+nRESxS4htWrEb20VSvnEmbt3g03uS5dYBhYowbyjqh1z5RdweXDlblE4uOVeuUEhFoZNGgQlyhRgm86CK2cnJzMsbGx/3fcvHnTpUJJbKzyXSdNckmVzAzBs1YtpW61Wy6ShMksIADXyFs/ixc73yaRTM+19OyJqM5GU7s2DE8dMWUKFkt6DJcvXFCitsp9OCJCezlm4ZFCyY4dys1q2xZJqfRkBF20CKsGR6F65R/J6FDLCxYgyZUIMe86tm3DSqNuXefCcv/+O/rOBx8g1H2BAsyNGqnXwuzfr/ThatVct2q1Thh4967264cMGcJFixblqzrSZ7vapoQZ95YIe/yuQrbZIWLu31/9dd9+i2t++gljExHzjBnOtUUk03MPr7/O3Lq1sWXK2rcVK+yfJ0lIp9Krl756evdG9mo5g7grknVqwSOFEklCsCwi5oED1f1QGREdjRXv9OmOz61YUZ1hrBZWrEDbExKMLVdgn6NH0X/Kl3cud87ChUpAvwMHYLTcr596IXP4cGXyUtMHjUAO4FW0qLbrJEniwYMHc+HChfny5cu66naHUCLnSSpb1jX1XbpkqwVTm3tnyxYIuR9+CMHZzw9bN84sWKKjmV97De0YPVrfwk2gjxYtkHncSBYuRL9wtBUoO2fo2bKMiEAdo0YpffjcOV3NNQ2PFEqYYT0u37Q2bbCloyf5VteuiPro6OGfOBHxL4yMyLluHdrvyentMytGpXqfMAG/4Y8/4iDCSlkNFovtBGZW5GBrundHXZ06abtu4MCBHBoayrt27eK7d+/+35GowYXIHUKJ/JsQGb/9+iSpqdh6ketT6/Vw8SLslNq0YT5/Hq9btnROiLBOpvfnn/rLEeijXj3mPn2MLbN1a+aXX3Z83oABGNf0aF8HD2bOk0cZJ8xOLKgHjxVKJEl5+OXgP3qMwf76S92EcP48zjPyAZdV+KdPG1emQD23bkEDliePfpdvSYKK3s8PRqvDh+P1jh3qro+KshVM4uL0tUMtZcqgnk8+0XZdRgarRMQ//fST6jLcIZTIqSKI1Bsj62X0aKWu5cvVXfPwIQwKK1RARvTSpfFaTWDHjJAk5u+/hwa4Rg2UKXA9RYsyf/qpceXJ6VG++cb+eUlJEET1uO/eu4dQBX36KP34/Hl97TUTjxVKmBVNAxEs1itX1i4dpqczFy4MtbsjKlTQv0+XEXfvOmdwKHCehw+Z69eHIbPeCLDp6dh3zZoVk2CLFogB8e+/6q6XI/vKxttmER2t1OOO3CbuEEqshT61goIeDh5U6qlZU901qalYiebJA23JSy9hW/G///S14fFj5rffVrwlzNYMCTImJQVbcUYYKMusXo3f1ZGQKY8lerS/Y8bA3u6VV1CGGoNad+DRQokkQbKTjXH0akumTEE5jgwfJ0/G5GXUalaSMJF9/bUx5Qn0kZAA1WhAAPMvv+grIymJuWFD5oIFsQf74ovQwqjtK3XrKpOa0QbVMtbJAY8fN6cOe7hDKJGTlznjAu2Ix4/1absGDUK6i3/+gXFhYCCEWj2IZHqew3//oR8YkeZCplUrjBGOaN1aX7DAu3cxt3Xo4JkeN9Z4VPC0J/HxIfrlF7z+4w8EA/rkE6K0NG3lvP8+/i5aZP+83r0R8Gz1au1tzQgfH6QFl1NCC9xDcDDR+vVEXbsSde9OtGCB9jKCgoh+/x2Jq/r2RfK0GzeIevZUF7Btxw7ldceO5iSRs04QVras8eV7Ij4+ync9d86cOuTxg4jo4EGkInDEggXKcfgw0bJlREuW6EuctmaNSKbnSVy/jr8lShhT3tWrCJ43cKD9886dI/rrL6LBg7XXMWECUWAg0e3beN+vH4L3eSTuloocIUnYViFCYCAfH+b587WX07cvtnEcuXS++irU/UbRrp3xrmMCfVgsikfMhAn6PB+OHMF+ft++zBs3oj+qtd+w3gLQm0TLHkOGoOzixY0vWw3u0JQwK1saZnzvjRuV30zNFjAzNFZ+fnAn//13XKvX/mDlSvQxOWaOwP3MnQutqzNBGq0ZPRp2Io5synv10hdM9Px5bDf16uVcuABX4fFCCTPzqVPKzWzalDl/fu1bLOfO4XpHGVzlPTuj3KQ++QQxLkSsEs9AkhDtkgjqdT0eXT/9hOu/+w6uvkTqt4Xee0/py3q3kp5F27Yot1UrY8tVi7uEkqlTlXtqZL6hyEjt7r8REdhOatkSxtVZs0Kg0OMpsW4dhJtevUR0Vk/i3XdhZGwEycmI7jtsmP3zrl/HVuDs2drraNeOuVQp5kqV0I9HjdLXVlfhFUIJs+LCVKkSVqoTJmgvo0ULRGK0JyCkpMAYbcQI3U21QTbWdRAcU+BiFi/G6qFLF31u4EOGKJE5e/TA5KPGkj011XaiM3LFImsUhw83rkwtuEsosTYk1hli5SkkCcHytOy/p6ZCy1qiBPPZs9DM1qmjT1D6+2/YoLzxhog/4mlUr47FhRGsWoX+deGC/fOGDYOwq1Vb9s8/KF+O50OkP8mtq/AaoeTePeWmNmsGox2t8T82bcL1jozNPvwQFvNGWLffuiU8cDyVtWsh4LZsqV0wSU2FN0WBApgIy5eHd5iaCcg6AFfDhsZo0SRJiaGxcKHz5enBXULJmTPK/TQqB451/BO1IezHjoVmY/t2TFzFiukTOvfsgZDburVxWwQCY0hJwXOmNlaRI5o0wWGPBw9g4PzZZ9rKtljgKWadEsGodpuJ1wglzIqaNigIe3CDBmm73mJB5MfXXrN/Xni4EjDLWSQJHhta40YIXMOOHRBMOnXSviK9fx8TT506iIMTFIQIxGr49FNloNCbVMsaa6F982bny9ODu4SSxETlu2sIq/JMrl611WapERr//hu2H9OmQfuWLZu++ERHjzKHhGCb2sitKIExHDmCPnHggPNlyelNVq60f96kSRBSIyO1lf/zzyj/rbeUvuwNWjevEkqSk221JX5+UJNqQV4BOQq01L49toqMWMV26IBBRuCZrF+PvvTuu9p/76NHIdT06QMbEyLmNWscX2cdHJDIuXD4zEroaSL3Betzl1DCrGRmdjYxn8WCSKnyvbx2zfE19+5BY9aihRLm/7fftNd95gzi39SrZ36QPYE+pk+HwGmEBmvYMJgK2NPSJiTgnMGDtZWdlIRn4qWXlL7sLYkavUooYcaAL9/k0qUx2WuZSNLScJ0jbYm8F2eEL/qcOVD5OZO5VmAuy5fj9/7wQ+2CybJlimq0c2eEEVdjg3DjhtKX69Z1TgCWV0VECCjmDtwplDRvju/et69z5cj5jojUJcuzWLD9lz8/PG38/dGHtBIeDsGmWjXP3/N/nmnZUl3meUckJkLb7yi2zty5WDBpjdwrJ2msXx99uVEj/W11NV4nlMgByYiQS0JPQLWlS3HdiRP266le3ZgOKNsQbNrkfFkC85CzuH7xhfZrhw3DhLR+PXPJkljtqnHds97GcSYo1rRpKCNLFvd5erlTKJFV1M54HslZWrVs28jeV8uXw7C1cWPtLpsREQhbXr68dhW9wHWkpGDucTazMzNSBRAxX7ny7HPS0jCWdO+urewHDyDwWBtqe1M6Aq8TSpghTMg3u04dPNBarJLT0pAjpEMH++fJWX6ddQ+WJMRQcOT2JXA/EyfqMxZNTUUyrXz5oLr390dYZ0c8mbRP76Q0ciSuL1VK3/VG4E6h5IMP8P3Ll9dfhrWqW02yvYMHFc1I06bQdNy5o63OO3eguX3hBRjFCzyXPXvQN5yNlpyaCmHDUZh3WfupNafTu+9CWytHQ/d0F+An8UqhhBmuckTYNwsK0p6gSFbX2+tgKSnMhQrhR3aWvn3hsinwbCQJE5yPj/Y4IpGRED5r1lSEm61bHV93+bIyGToSlJ+FHBipYUN91+tFkpi//HIxlyr1Ohcu/B4TEY8cGcs9e8KroFw55gULzG/H5Mn4/tmz69MUyUHOiFCWI6KjMbHUrQuB0M+PefdubXVGRWFMKFrUc0N+CxRGj4Z9h57YRtb88AP62Zkzzz4nNZU5LEx74M1du1D2yy8r/dnbgu55rVBi7W1QvTp8+rXEKEhLw4/evr3982bOxGrIWfWXHEtBbRI3gfuwWJh79sTv/tdf2q49fhxCcq9eiq2BGrdQORM2EfOWLdrb/OqruLZLF+3XquXCBWw39e4NQ/OwMGUrFQc0JcWKxXKjRlA7d+wIAU+N8a8zyEbGRMxaFTXWiQzVbNtIEvObb2I1Ons2rvnqK+11Vq+O/nHpkrZrBa5HkpDvytn4JLKW5I037J83dy6em1On1JednIxFQLVqSl82Muu9q/BaoYRZMTAkQlyR1q21rZL+9z9ce/Tos895/BgDh7MGdI8fw9d82jTnyhG4htRUCKxyZmAtyP1qwgTFK8NRRM60NNuJUevqpmZNXGdU0L8nuX8fWkPZO+TNN6EhmD0bAsfhw8yXLj29fWOxMHfrBkHNCDfKZ2EdQE3N1os1PXpo87ZZtAjnTpvGnCMH3Mm1jDvx8cwNGiAYlrs8pQTakGPhOOtuv2SJYw+5mBjMZ1o19JMnYyHVsCHqMCrqrKvxaqFEkrCHTITBkkibyj09HepTRx48RmlLunSBFCvwDhITsQURGqptxcIMF76gIOZvvlHiVzji9GllchwwQFt9skus1hW7GtLTIZgTwUj8yBFo/B49shW2nmVTkpQEo7u8ee0b9jmD7C2n1SVaVncTqbP5OntW0YRVqQLbNC2amaQkaJlCQnAfBd7BxIkQQPVEf5ZJTYXtkCMtyccfYwF7+7b6ssPDlUCQcn/Wcr0n4dVCCTNWRfKPUKIEDA0fPFB//ebNuNZexFWjtCWyO3N4uHPlCFxHbCxWHAUKaJtQExORar5yZWgv/PzUaQq6dVP6s5ZJK0sWXLNkifpr1PLOO7ZaHOvDxwcr/tKlmWvUgFDyxhuxPGgQtnpmzUJAM+sIqWfOOL8v/yRybisi9bYdSUm238VRmxISsIipVAlbU8HB2uIkpaQgP1HWrNrtTwTupXJleHg5g/wM2BOaIyK0p1GRJNiQFCum9OU5c5xrqzvxeqGEGT+A/GOEhCBrqBZatcJ+ob2AOEZoSxITEXhnyhT9ZQhcT2QkIgGXLKnNQ+L0aQwwgwYpOVEcxaBISVH6sr+/OvfShATlGj1Bu+yxbZtS9t27WAScPIlIuGvWwLXxyy+xunv7bQgljRvHctWqGCSzZ89YmKlf31jXZWsbs/Xr1V0zapQ2AbBfPwgU48fjGi3RY9PTseUVGKjPZkjgPuSEsOvW6S9Djo/VqZP987p3xzaplphWshlD7dr4Gxzs3QkcM4VQYrFgsifCxKHVWPDcOaxkZ8169jmytqRPH+fa+tZbMEYSWYO9ixs3MMlWqKBNEyfHPvnuO8QOUGN/sHOnMlnOnOm4DmttoRpvH7VYx+1Yvdrx+c/avklJgdBw4YIS8ZSIeeNG49pqnehw+XLH51vny1ETbfnXX3Hup59iO69rV/XPsMUCbZOfn8iB5Y0MG4axX2v8GWvkzOL2toEPH8Y5P/ygvtyoKNifVKmi9GejMty7i0whlDDbulWWLo1VqRZjwUGDMNjYixMxZw7U1fZcuRyxfTvauGeP/jIE7uHSJWwP1qmjPgy4JMEAO39+xUNk2TLH1xUvrvRnR9qZs2eVc40yJpUkxXi2dm11E7DaOCVr16r3dNFCzpzqVNeShEBnao2Kr16FPcEbb8A2pnhxeM+oQZJgX+Tjg7gTAu8iJQWT/kcf6S9D1pK8/vqzz5GzUleurG1rs08f7A7IfdnbYpJkRKYRSpixDyf/OFmzagtWFhUFocRekr+UFGzzOBPl1WJBB+3ZU38ZAvdx/DgmqObN1Ru93bsHoaRNG3h65Mzp2AjtwQOlLzuKUiqvsIxcJcnCM5H6LUstwdNkw3StLtf2KFMGZTqKMyIHRSRC6nh7WCyI0lqyJIKk+foy792rvk0zZ6Ke779Xf43Ac5DtAM+f11/G4sUow14QNDlOjhZNp6xRlY3ciTJHVulMJZRYu1WGhWF1omXlOHMmVKz2Bna58ziTE2f6dNgaPHyovwyB+9i9W0nCp3alv2kT+s3EiTCa7dDB8bVTpij9efv2Z59n7UGi1R32WciamqlT1V+jRSiRUy+QgSOQnOdj5Eh7bbS1bXHEggXKffDzgz2JWrZvhxAzerT6awSeRZs2CJCnl+hoaFd79Hj2OXoWuzExeEatNX6Zxb08UwklzLaq7Lx58WOr3caRO8crrzx7wpAk+IFXqaLfg+D+fSTomz1b3/UC9yNHBNZi5f7BBxBmJk3CtY7U+U+GoH/WKuivv5Rz1G4r2MN6K1TLyktrmHk58JpR2UtfeQXl2YvvMHCg8t1u3rRf3vXrMNTt2hWakvr11ad+v3YNav8WLYz3NBK4hitXsLDVYuPxJMOHow/Z04x+8w2EVy2eXD172hqRaxGWPZ1MJ5QwY/9P/rECApjff1/9tfKK1l5ytIMHtVvfP0mXLjB49WYr6ecdObz4jh3qzk9Kwp5xxYqIdJo7N7Z27HHypNKXP/8843OsQ6QbMQF27Yqypk/Xdp1WoeTCBWO1JY6i2lovWAYOtF+WJKG8IkWY27XDvr3abazERERrLVlSm1G0wLMYOhQL28REfdfLDhT2nqNbt7AdrGWOko2uy5Y19rn3FDKlUGLtViknJdJi6d+1q+N4J126QHWmN6/A3r1o14YN+q4XuJ+0NKyE8+RRP2GdPQttSbdu6GOOAikxKxEan7U9I0eQ9fHR1v6MsA65rnVC1ZOQz8cHdR0+rLGhGdC2LcrK6J7KSTHVDuKyJkwW0NQaqUoSQhJkzao9kZrAc4iOhkfnp5/qu16SYHdWpox927NOnbCd6yhUgMzNm4gLZC2QmBWQ0F1kSqGE2VYFHRKCH15tBta7d2GMaM/99+pVCDwff6yvfZIEdXDjxvquF3gGDx8iSmOVKuoF1Llz0S/ffludu21cnNKXM0q4JxvS5cunvf1PMmsWytLTL2Wh5NChWNVGwPv3o77QUO31PUnHjijrtdee/t/Klco9dGRce++eEk4/JESbUbocM0l42ng3s2ZBy64167OMbCC7adOzz/njD5zz66/qyrRYIOjIXmZEcLHPbGRaoYQZIbHlH8/fH4OVWsNEOb+Fvf3uKVNQrl7LbLlTmpkTRGA+585hf7dzZ3X9S5Kwqs+bFzlQ8uVzLDB//73Sl5+00JdjoRQurP87MEN78Kw6HBEdzfzllxBKkJgPofLVJLeT69Syp54Rcubwdu1sP7cW6tRsFXXuDO1XhQrYglGr+Nm9G+PB8OHa2y7wHNLS4NHSq5e+6xMSoJV7sh9aExuLrcG2bdXPSXLyR9mWpHjxzBnvKlMLJcy2KZyJEOpXDRYL/MbLlIEtQEYkJ+P/jnLn2KsjLMy+/7rAO5AFzGfZfTzJ/fvQ3lWrBnVst272z7eevIlsDS6//BKfFS2qv/3MtvFD1No6HTuGyRvX2QolRIhO6aisMWNwrqNol46Qt1qeTPf+wQfK93KUcE+2z5G3zP75R13dN2/C7btpU+eCbAncjxwh9cQJfddPnIjIvfa2VYYOxfaQmgSQzMq2b9GiSl9Wk33cG8n0Qkl8vO1gnj07komp4cIFqPDs7Stu3erYMNYeixdjX12kL/d+Jk5EX1CbLnzLFpxfpw7+Oor2aR2FdN485fOpU/FZsWL6286MLRsix3k3Ll/G5Gv9XBExN2gAoeTixViOibH9nz1jwYsXlfMSEvS3X87226KF8pm1Ma0joefRI+aCBWGIHByMoGdqSE7Gb1isGIRNgfeSmoo4UhltAaohIgLb+mPGPPucQ4cw5qvdeklOxvZwaKh+TaY3kemFEmZbDwYfHyRYU7vnPX48BBN7sUvefBOr3pgY7W1LSsJA+M472q8VeBYWCwazkBBMhmoYMgQTYKVK6EOOYteEhSl9WTaOmzYN70uU0N92a+PwiIiMz4mKeloQqVqVecSINVyuXEUOCwuzMXSVJEXgIrK/GJDTRDgTer537//H3nWHR1V07xMSEmoChF4EpEakKcUOIgioIKBipQiKAooCnyIiiL0r+qGICipYUFEpKkpXQXrvPQIBAoQ00rP3/P54f/PN3N17t2U32STzPs99dvfe2Vvnzrxz5pz3YB/dusl1bdvK43vKJzJ0KJ5d06aYtvHGR8gwmIcPxyh20yb/z10jNDBrFuqKr1nBBe64w30ARG4uIvCuvNL78PKnnkIUj6jHvkTqFEeUClLCzPzqq/KhlimDzsAbZGXB07ljR3uz7IkTaFQff9y/c/vgA5zTvn3+/V8jdJCWhpF2s2beedSnp4NMxMVhJORpHjspSdZjEdYqpm8aN/b/vP/6C/uoUsW+jDhutWrWflB20Tdq4js70iWUTwuSiXX4cOzjhhvwW1Wl/egj9/8VFs927Tz7kqn4+GOUL4g8gEZoICcHZPTOO/37v7B8unNynjIFBGPLFu/2uWKFjFATS0mfHiw1pMQwYJFQH+78+d79d/16VKSpU+3LvPsuKs+aNb6fW3Y2nJbuusv3/2qEHg4fhp9Ir17e6QeIDvG667yzFoweLevwgQPMb76J75de6v85T5qEfdhpKsybJ6c/7eAuJFhEHBFZ+18dO+Z+uzcYMUL6g6hOu572KYhh48YI5XWXakLFP//AiupteY3QxsyZaMP9cbhOToa/x0032de1DRvQj3iaHhU4eRJ+ShUqeO8TVRJQakgJs3mUGRMD0ZojR7z7r2C4dinO8/MRQti8uX9iO8Js6C2D1ghtLF0K65e3IeNDh6I+tm0L8687ZVY1I27HjtLK0LSp/+cr9HzWr3fdpirLupui9KRTIpz0fvjB+v/iGP5Gs40ahf937gyHdrE/T9Ftjz+O67/kEu+nbU6dghPvtdeWjHwjpR3Z2fAJ8uRwbgeRGM8uzUNGBvqGDh28s3Tk5iIyT7yX7t6bkoZSRUqYzXlCwsNRSbzxL8nNRdnmze2d8fbuxdyyP9oleXnYt3PkgEbxhdD88EazQjhZXnEFyMmjj7ov/+23sh737o3P5s39O8/MTPem4f79sc1TgktPpCQxUR7HCkJn5K23fLyA/4eIsmnVSh7Hk3bLmjUYHTdtivLeqPPm5ICM1KlTciMgShs+/ND/KfTFi1F33MnRP/YYCIa3+3/iCZyPqMd9+/p+XsUVpY6UMENHQDXtjhnj3f/27UPFcueP8tprqEz+KFQK+eC//vL9vxqhB8NAREjFiohY8QQ1HDUszLPVzNnptEUL/85zxQr7DvzUKe+nVbxRdBVKlFYRStOnY9tVV/l4Af+PceNc78nJk/blhb9YzyENnQAAIABJREFUrVp4rz1JzwuMGoVpG60vVDKQkQHNEH8ytyclgZz27m3/fixdirrobZ4sMVWqLt4GZpQElEpSkp+PBlh96N6axsTc+O+/W2/Py4NndatWvlckhwOOdp0765w4JQVpaRiFd+jgnZn/jjvgj1KnDhR/3dWD3bvNdbhlS//O8dln8X+rpF5i397odXhDSi5csLeWbN8ut/mTy0N1qCWyz4EjMHEiyEWdOvApSUvzfAwxLfTxx76fn0Zo4vnnoSvirVSEivvvh3O4Hfm9cAGEp3t379r0PXswiClbVtZjT4kjSxpKJSlhNvuXEKEieOPg5HAw33wzGjK7SIKdO1GpJk3y/bxWrcL5zJnj+381QhObNkHp05tpvdOnQUoaNEA9+OIL9+VbtpR1uE4d/84vOhr/X77cvH7hQqyPiPBuP97mvmnWDPt1luBWnVPdheDb4fHHze+0O9+uvXtxXeJcvNF92LQJ07MPPVQylTRLI4SuyMSJvv9XiA26a6vvvRekxRtikZaG91kN/1292vfzKu4otaSE2XWk2aSJd2GcJ0+i4xg40L5xevFFTOOsXev7ed15JzoYb0ZuGsUDb7yBOrZsmeeyIj1CTAy87905lzprh/gKVVzQWcdDrHfndKvCW1KiJv1zxtVX+0/K27eX+502zb6cYTD37InOIjoaHYcnJCaCKHbqVLpM6SUdAwbAkuFrYtVz5/Bu9u1r3wfMneu9T5lhIPpSfZdfesm3cyopKNWkhNksrU3kfRin8P+YOdN6e14eGtjGjb3PnSEQH+9ZFVCjeMHhgAm3Th3PeW5Epykc3TzlUlHrryfxNWcsWSIJkPP5+kp0fMkSLBxLncOfX3oJ6/3R/FHvgztLxi+/oEzNmrhuT86qubnMXbqgfGkzpZdkLFuGevDNN77/d+BA6PXY1Z19+2B9HzzYO6uayGsjlg4dSq81rtSTEmbmsWPNFcJbU97IkTDn2uVIOHIEYWKDB/t+TlOmeM6foFG8cOoUkvD16eO5wYmPl/oE4eHupxbFiMwXp22BiRPxv/Hjzes/+sjez8QOvpAS1cKjQkxfuhNxs8LKlXJ/7kTkcnIwZVO+PMp++KHnfU+ciKmeP//07Zw0Qhe5ucjZdN11vnf+YkD67bfW2zMyoNAcF+dZRZiZ+e+/Ub/UPqgg6RaKOzQpYVRKVb7bW8fXrCyEcDZpYm9inzPHfQW2Q0YGzMWlKRSsNGDRItQHNXeNHYRSK5H7pI9CfE0sx497fz4dO+I/CxaY14t92SWjtIIvpEQ9hpoePiNDrvfW2dswzHoO7kKXhaZLWBiu3ZNVdO1aWKxeecW7c9EoHpg2Dc912zbf/nfqFDJIu8sIPnw4SK83flEJCbCequ+vt9pZJRWalPw/1MbQF8fXw4cxL33HHdaV1DAgyBMT47san2DkCxf69j+N0MZjj8HCtnOn+3I5OTKElgihglZYu9Zcd++4w/tzsWoI1YzEvsBXUiI0g3r1sj4nb5NUCqInlgkTrMslJkqn3jJlPIdcp6djwHHVVd7nKdEIfSQmoj32pAXkjLw8TOPVrm0/BSsGod6kHbh4EZGaat21i+osTdCkRMHx4+YKcumlMDN7gtCXsItDT06GWuT11/sW6mgYiH+vV893vxSN0EVmJsy7rVp5Vv8V895E9g55O3aY6y2R91LZorwqmib8rEaM8P6amH0nJerxVQi5fW8cBFXfF7HYyXg//LB31hSBkSMxheaNxoxG8cHQoQhUOH/et/89+yzIrF1EzN69qC9Dhnjel8MBJ1u13r7+um/nU1KhSYkTVMVXIghZeeNt/+STCAO2E037809UaF/m6JlhXalYUefXKGnYtQtTDt48V9Ur38oKcPiwa8d8zTWe92sXBSMy9noTiaaiIKREnSYSyqwvvOD5/99843rtVo371q0ysVndup5Jvkiu5o3PiUbxgXiun3zi2/9+/RX/e+016+2++pE884y5zt5+u2/nU5KhSYkFRCp4sdx3n2dnqJwciJ41bGgfAfHSS2gYfTXRvf8+zsOfZH8aoYsPP/Rueu74cen0Wras67TGmTOyrr7yivzuaXpi61Y5VanCn6kbZv9IiRAjVH02RCTCgw+6/6+aAyg2FiZ5K38dw4CVUpT1lIgzKQnEpUeP0hsBURKRkoL8S927+/Zc//0XkTa33Wbt52QYsL5460fy+efm/iU21j+xwJIKTUps0KuXueK4yxAsEB8Ps+Ctt1pXMocD+42N9c0ZMT8fhKdlS62RUJJgGBghxca6l0NnNju93nyzuVG9eFFu27RJfo+Lc79PMe3Yp49c99dfWOePg7U/pCQvz5UELViA35df7v6/M2fK/8bHy+/OTuXCN4vIvRy4gC+CVxrFBw8/jCzXvvj2eTPY/OAD1C1vtHVWrzartRJpPSpnaFJig7w86RQnlq++8vy/336DNcQurPjcOUTVXH21b9lFd+9GZfZ1+kcjtHHuHEbl3bq5jzZxdnr9+We5TfWrWLlSEgsi66y/Am+9hTIvvijXNWmCdXbZTq0wffp0jouL4+bNm/tMSphdSYnqI2MHNYngZZeBrIvfqkBdRgb8uYSVyZN/iMg74o0/i0bxgYhQ8zU9wBNPuJ+WX7ECIfvjxnne16FDsLiofYovg9PSAk1K3CAtzVyBIiMRU+4Jb76J8naiPOvWoaJ7EsVyxpQpiGe300XRKJ5YsQJE1lN2XNXptVEjs9VMrBeh7OJ306b2+xsyBGXmznXdjz/wx1LCzNy2LY555gx+q++dHVETob3if2raCPX9eOEFud5Zi8UZCQnoNO66S0/blCSkpoKY+jpt88MPqDd2AQxHj8LK2aOH5+isCxdcZSf8SdpaGqBJiQeo6dbF/J8nQTPDYB40CI6MmzZZlxF+Ip7mt1Xk5EBKOy7Oc9SGRvHC2LGoL57qlur0qkqpixwuH32E32vWyHJ2RFpYEISvkrC4lCvn3zX4S0pEkrs335TrxLknJLiWV8P3b7wR6/79V64TVp7jx6VIWo0a7uX6RaRbrVreRdxpFB+MGIFpm2PHvP/PwYMQvrQjqBcvMrdpgwhNTyrKOTmwhKr9yPff+3QJpQqalHgB5+iGJk08S1NnZSFPRr16ZnEoAZHroHJlhJJ5iz170Gn4qtypEdq4eBHWj27d3I/mVKfX6tVlFIkIo1WnYkR9tVM4de74hePr0KH+XYO/pET4xKhWnchIrPvnH9fy77wjz13k5dmzR64T0Q/33SfXeTLbC/+UxYt9OnWNEIewLs6Y4f1/MjNBOJo1s47SMgyIp1Wq5Nmx1eEw10Mi5nff9e0aShs0KfESW7aYK1br1p5DJhMS4C/QubO1MmZaGubDmzXzLfxSWFmWLvXtGjRCG2Lee9Ys9+VefFHWQ+Fj1L8/fqtkVRVVW7nSvA9VIE1MkUyahN+LFvl3/v6SEmbXaaObb7Z2WlV9SVRnXPVaDcNsKWrTxn10w5EjiEB66CGfT1sjhJGSAmugJ38tZwwfjoHfjh3W219+2dWvywqGgSl6td/wJ6dTaYMmJT5AJC8Ty9VXe45J37gR6p1DhliPgA8fRsROz57eh4U5HJjHrFvX9wRsGqGNwYMR+eHOEnfxIp49ETrTxETmRx7Bb+eMt6KuXnqpef2pU65EoGVL/PZFWl5FIEnJ00/jt7PmiCDkqkWEGdOgRJiucTjMSpnOhExFfj6sTI0a6SiIkgTDQNK86Gj4fniL6dNRZ2bPtt6+aBH8v7yJxnSWlujd2/vzKM3QpMRHqGGIRCAHnsJ0v/4aZd9+23r78uXw4PbkiKfi5EmQGe2UV7Jw/jz8H+66y3054YchRl/PPSfro4p//pHlVJ0bYVmoV0+uK4iTK3PBSInIwSP8OURCwKeekmXUCJt+/cz/F2GZbdqYBdX693d/3DffRCejk+2VLHz8se++G0uWQODSLgBh82YMAgYM8Gx5+ewzcz/RqpVup72FJiV+QIzixHLHHZ69r595BhXeTihLjAC//NL78/j+e+/M/RrFC99+i+fqnCRPRX4+OmAiGclFxNyunWtZtWEUEJYFdfRWlKRECMmJuX9B5NUM24KoOFtJmKF0S8R8ww0yyiEy0n1ys337UOY///H5dDVCGDt2wDo9cqT3/9m1C/59t91mbbGOj0fOm86dPWfwXbAAbb2oqxUr+jZ9VNqhSYmfuO02MzEZNsw9E87PB3kpXx4hwc4wDOwjKsq9toQzREZKT8ndNIoPDAMCfHXruo8YUbMDC0GmmBjXcqq/hYgGE5YWoZrqbxI+FQUhJSdO4Ng334zfQkCte3f8zsmR53fTTa7/HzTI/D4S2SfmY8b13ngjnNZ1JFvJQXo69HzatPF+GvLMGYijtW1rPYWXnAzfv0svxVSpO/z1lzljNZE5r5SGZ2hS4icMA1ENauUbO9Y9McnKwvx19erWIk7Z2chZUqeO96I6wlO8RQs9J16ScPw4vPs9ZTLt2dO1M7aqg2Jb5874PW0afgtT9YED0urnLwpCSsQ5hoXh+/Ll+H3ZZfj9ySfyGqyI2k03me9BjRru89sIS8ySJX6dqkaIYvBgWCa8zTCdmYl3wq7NzckBea1WzfM+d+yQqQ7Eogmv7yhDGn4hLIzowAGismXluvfeI3r5Zfv/lCtHtHAhUfXqRL16ESUmmrdHRRH99BNRZCS2Jyd7Po/y5Yl++IEoIYFoxAi8ChrFHw0aEL3+OtHHHxP9/bd9ubfecl2Xmem67o8/8LlhA9HOnURpafhdsSI+f/oJn3fc4f85BwKi/orzOn2aKD8fdZuIqFMnopgY1/+dOmX+/dxzRNHR1sdISSEaN47ozjvxnmmUDHz5JdGcOXhnWrTwXN4wiIYOxfuwaBHeORXMRA89RLR2LdGCBe73GR+PupSaKtelpKB91vARRc2KijvUvCNisVMAFDh2DPOTHTpYp6Lfvx8ibddd5z3TFvLYvsTja4Q2HA5Yzpo3d2+KHj7cXP8OH7YuJ7Z36wYHUiKZCK9DB3srhLcIhKVEtEg7d8rfX30lv9ulm1evv2FD987njz0GK5TObVNysHcv9Hs8JXFUIZzDf/zRevvkydg+b577/Zw4gakdtQ56mubRsIcmJQGAsxw9kefkTNu2oWG85RZrJ9l16+Ar0q+f96HCo0fDcc9TdliN4oM9e/BMJ02yL5OQYJ7HXrHCupxIwCeICREy8jIX3J+EObCk5MgR13eqWTPr/zkPDNw5i2/eDCfEd97x6xQ1QhAZGUjeGBfnWaJB4MsvUVfeeMN6+6xZ2O4cku6MhASppiwWX5RjNVyhSUmAkJpqrphlyriPnmCG+FlEBESbrPwAFi9GqPAjj3gXTpadDX2Gxo21fklJwgsvoJ7YiTkxQ0RN1D13YbDOHf0nn5jXFwQFJSVxcdIx0Dm9A5G1MjKz2apStao9ic/PR+hx69ba+bCkwDCgzVO+PCJovMGff8Ix3C44YcEC79rdM2ekto9YdMBBwaFJSQDhTEwiI90LNzFLxm4nxiMY+wsveHcOR4/CKat7d89hyhrFAzk5COft2NG+w01PN9c9u3Kff24uJzJfhwIpEQJwGza4Wj8qVLD/3+23y3LuVDZnzEAZVa9Fo3hDCJR5q0ciMvXeeKN1lvaVKxEBeeed7i3UZ8/inVTr6Nq1/l2DhhmalAQYKSnmilqxoudskK+84t4XRcgai1GtJ4h02r5mIdYIXaxbh8gUMd1iBW+mMNTQX7UTDwVSInxH3n1XJgcUi1W0GrMrGbMb2SYmQil32DC/Tk0jBCHUVSdP9q58YiL8s1q0sE7rsWEDptRvvtm9T9L581IjSCy//+7fNWi4QpOSICA52Vxhq1bFXLYdDAMCTkTWQmiGwTxqlHvxNWf897/Y3+ef+3UJGiGIRx9FyOHZs9bbn39e1rkWLexHeupUz/z5KEdkn7jPWxSUlIhpGOGsqL5Ddnj1VVlGhBNbYcgQjJB1BuCSgd27QSD69fNOmCw5GcKCtWtbO4Lv2oX6cc017v1SLlxApnYrYq8RGGhSEiQ4E5PoaPdmY8NApxMW5pqEjBkdx4ABcGj0xkxoGPBViYy0zrSqUfxw9ixIiZ1SpVCCFcsPP1iXy8uTZfr1Q0dNJIXKfMX06dM5Li6OmzdvXiBSkpGB87jmGqitinP84w/r8ikpUOEU5R54wLrcn39i+6ef+nVaGiGG8+cR7dK6tXX0ojMuXkSdqlrV2u/kyBHolLRp4z4xakqKTIcgFq1zE3hoUhJEXLjgOi++fLl9eYcDypQREdaZWrOyIKNdtSpC4DwhJwdhxbVrI1eORvHHu+/CYmbVuKp5bogworObzlDLrV+Pz0ceKdi5FdRSIqaWGjSAiJs4P6u5f2b4YanXMXGia5ncXAiwXXWVlvouCcjNReRYbKx3ifays5EPqlIl62n0U6dAcJo2heOqHdLSkIBVrW+rVvl9GRpuoElJkOFMTKKimH/5xb58Xh4a5Kgo5mXLXLcnJyP8rUED74hGYiLKduig1QVLAnJyEILYvbsr4UhIcI1Y+fVX6/2oZfr2xeebbxbs3ApKSpzPyx0pSUpCxIVazkqj5803QeK2bfP7lDRCCI8/jkGbN4QgLw/W5ago6/JJSWhL69VDbhs7JCe7EhKrVCEagYEmJYWApCRzhY6IsDetM6MR7t0blhWrKZ+TJ0E0Lr/cvblRYOtW7Kt/f+81TzRCF4sWoR45W9OcnUPFVIg72Xl1sROR8hbBIiVW4bvPPuta7rffzGWOH0e91w7fJQMi1YA3ApEOB/yIIiIgreCM5GQM1KpXd291PnsWvihqPdu61e9L0PACmpQUEs6fd21E3Yk8ZWYyd+0KXxQrJ9m9ezGNc/313iWeWrwYI8YnnvD/GjRCA4YBS0mzZq5WhFq1ULd69JD1bPVq131Ydf4FbWyDRUqcQ9vPncPolwjTmaKcc0bgAQOQ1LAAp6MRIli2DNoi3mT+NQxYVMLCmL/5xnW7ICTVqrmv8wkJmPpT6+Lu3f5fg4Z30KSkEGFFTD7+2L58WhrmwqtVsxbOWrsWjq+33OIdMRE6De7CSjWKB3btslYmFZodL70kpa9F5l0V4eGudbGgsuvBIiXO1r0XXpDbpk+3Lrd6NdZZdUoaxQtbtsAnpFcv70TvhDy8VduanAxn1apV3ROS+HhkkFbr4YED/l+DhvfQpKSQ4ayrQATnRTtcuACV1mrVrOXj//gDxKRXL++IyYQJGEHMn+//NWiEBkaOdA0RnjABdWroUCnMR8S8caP5v9WqyboXKpYSVUOlSxf5XXVQzcyU596njxQXVCXoDYO5Uyd0Pt4oIWuELg4fZq5ZE8/Sm0ibt99GfbCSj/eWkBw8iOlxtY32Nmu7RsGhSUkRIDsbL4Za6V980b4BTU5GI1ulimvnwgzTZvnyMNl7cmZ1OJjvucf70GKN0IVViPAXX6A+tW6NaQ9hLenXz/zfpk1lBIGog74kM7NCQUnJ77/Lc1H9sNT3YuZMuX7TJplYcOBAWeaHH7DOk5qyRmgjMRH1tFkze20eFcLn5NlnXbeJNrRqVfe5wXbtklOgYvHm2BqBgyYlRYT8fFdVwAkT7IlJSgo8wKOjrXVHVqwAMbnpJug9uEN2NubiY2O1SbK44513zCHCIrxXdOaffmo9H96pE9b9+qu5DnrjOG2HgpIS1VyuWk0EHA5Jpm65Bev69MHv55/H79xcdGK9e/t/HRpFj/R0+H3Uru1d6O8338ACPHq0axuakuIdIdm8WVrhxJKcXLDr0PAdmpQUIQxDNqpieewxez2FtDQ4tlaqxPz3367bV69GtMGNN3rOlpmUhGRSjRrpFO7FGc4hwmqag1OnQEBr1MDv+++X/+vVC+vmzzfXv7ff9v9cCkJK9uwxn0durispEVFHRCBfzIieIJKCgx99hM7JXfJCjdBGTg78oCpX9m5K8YsvQMyHDHFtOwUhqVLFPSFZswYpQdQ66M10kUbgoUlJCGDUKPPLMGyYfejuxYsgHRUqWMfe//UXXq4uXTwTk+PHmS+5BOREmyiLL5xDhEU9WrECv8U8uxqhcu+9+D13rquPk78iYwUhJUOHunYIzqTkuuvwu2dP/M7OlmW2bcN/atViHjzYv/PXKHo4HFDmLVtW1l93ENN5Dz3kWm/Pn4cPSZUq7tN8LFrk6vitNZ2KDpqUhAhEUj6x3HOPvad5Rgb8R8qXtxZYW7MG1pTrr/fM9g8eREPevj1GFRrFD84hwtdfLyNTmGFhK1cO60aMwLqRI/FbzMOri7Peh7fwl5Skpbmeg5C+F6Rkwwb5+88/sU61rmRkQOE1Kor533/9O3+NosfTT+N5zpvnuez779tbl0+dQhbf6tXdW0ic639EhL2CsEbhQJOSEMLs2eYXpFcve42FrCzMm0dFWXcia9fC/HnttWj03WHHDsy3XnutZ+uKRmhi504ZIiwsb6NHy+0iTJIIDoTjx+P7tGmuhOCyy/w7B39JyYcfup7DiRNmUjJwIL6rETU//oh1FSpAIrxSJSS21CieEBa9adM8l33jDZR96ilXH5KjR+HgXa+evTCaYZgTWBIx16/vqomjUfjQpCTEsHix+UVp08Y+HC07Gz4pZcsyf/ed6/Z16+AYe/XVngWk1q/HtI+ntN0aoYtHHgG5fPll1J0uXeS2s2dlnXr5ZebnnsP3116T6z/8cJtS9xrzzz6mP/WHlKgOrT17yu+HD8vvR4/K72oou7Au9uwJAlalCnylNIofPvgAz9Iqf5EKw5A6NVOmuBKSvXtBRpo0YT52zHofeXnMw4e7DgB1bqTQgCYlIYh168wvTJ069ibI3Fzm++6Dc99HH7lu37ABYaNXXeV5emblSlheBgzQI4biiIQETNMI3wtyersffxzrqlSRxGXKFHXa5jel3k0rFFIiMvgSmTNr796Nz+rVmceMke+B6ms1eDDW33YbzO5W2hQaoQ8h6jh+vHtdGcNgfuYZlH31VdftW7agvrRqhekbK1y8yHzrreb29bnnAnMdGoGBJiUhioMHzS9OZKR15mBmMHzRcL/wguuLvWkTOqJOnTyHuC1ahAZ+8GA9ciiOGDfOXG9UIhof72qVGDcO0x6CwKhqqfPm2VQ4G/hDSrp2NRMo8X3zZnzWratacsz/bdXKbHrXzonFDyJk/YknPBOSJ55AWSuxyb//hlW4Uyc4uFrh7FkZCi+WguZ70gg8NCkJYVjJ0r//vnVZw5Dm7NGjXQnFli0w7Xfo4FmLQsT8jxqlFTGLGxITzaGNInRWQFgXxHLPPdCCIMKzVkNxR4924yFoAV9JyalT8ljCYVv8XrvWte6r+jvqtA8R/LE0ihe++MK7dsbhYH70UTxnK2vwkiVw+u/a1d5/7sgROIKrdUaHjYcmNCkJceTkuEoeP/aY/fTKzJlweLz7blcv8q1bIQ7Uvj0cA91BjGAefVRbTIob1Ay6n3xi3rZrl7kuXXedFC0Tdap9e7ndXWeRnZ3Nqamp/1tOnDjhEymZOtV1mklOJZnPU4ijCaiEpnlznf26uOGrr0BIHn7YffuSn49w8bAwpBRwxty58Km77TZ7S9nmzVLPRixaAiF0oUlJMYBhMA8aZH6pbr3VPtx3/nxM9/To4Vpmxw7MzTdu7FnNddYsNAZWGgAaoYsLF2Q9eeQR1+1qZt1LLmFu29ZsiUhIkNut1IMFnn/+eSYil8UbUqJaZB5+WK4X60ROG7tOZMkSuc0qNb1G6GLePAycHnzQfbuSmws9nfBw5q+/Nm9To2eGDrWXTxApB9RFO/KHNjQpKUb46CPzy9WuHfPJk9ZlV65ESHDHjtB8UBEfzxwXB5l5T/lvvvwSxGToUD0aLU7o0MHVCiGwcKG5Hl17LT7VaT2xzZ1ce0EsJaqSrDrCFeteekl+t0pXr27XU4zFB/Png2QMGuS+PUlNxaCqbFnX5KHZ2VAnJoLDq9XzNwxzHSFivuYaXVeKAzQpKWb4+2/zi1avHtQsrbBlCyTGW7RAiKWKpCSIbJUrx/zTT+6P+dVXGNl4akg0QgeqsJjzNF5+PqKsxHbh9KpO6RH1/d92T1N9Ar74lFxyCfZdrpx5vTimmgfHyqIntg0a5N25aRQ9FiyAE/0997hvRxISMOCKjnZNqnjuHKYco6LsBdayshCRqLaTEyYE7jo0ggtNSoohjh83v3DlyjH/8ot12YMHkcQsNlYqYQpkZTHfdRcsIUL90w7z5mGEc++9Oly4OEB1BLUine++K7f374/P3bsv8rZt23jbtm3/PxWD9ePHe5eVzFtSsnevPLZz1mtnU3tkpPtr27TJq1PTKGJ8/TXaj7vuct9+7NkDwlq/vkwyKXDgAMhqjRr204qnTzN37myuQ99/H7jr0Ag+NCkpplBzg4jFjlicPw/P9LJlXaMUHA7msWPx/6efdj/HO38+Rjp33WU/h6sROmjXzn4KR03cJ6J1Pv54s5N/yPz/lfGGiHpLSh55xP68nOu0VfjnN9/I7VlZns9Lo2gxYwYGPkOGuK9Hq1dDuqBNG9dp6dWrET3YsqXM3+SMbdtgOVbrz/btAbsMjUKCJiXFGPn50klRLE8+aW0azcmBwyoRpJmdy7z7LhqO++5z7wj2888gNwMG6BwRoQ6RR4TIdfqO2ZUAOFvbVOLijZ6DN6REJdOTJnk+J6tdiW2VK3s+J42ixeuv41k9/rj7Ac+8ebCK3XSTq8jjl1+izenWzV5n6eefXeuOVvctntCkpARA5DERS58+1uqthiHJR9++rpE533+Pudobb3QvsrZoERqQnj11rpxQxrx5sk5YReEI0TSxWIVcim1t2ng+njek5OOP3UdBOHcszvjnH7ntwQc9n5NG0UBVX7WSg1fLiZw3DzxgHugYhlQcHjbMehBkGJL4iCU2Vg+YijM0KSkhWLDA/GIYqFsaAAAgAElEQVReeqm9ONAvv6BDatvWNaPqX3/BTHr55fY5d5iZly/HPjp3tldQ1ChaHDki60OZMq7S2yJTsFis5LZ/+UVu37PH/fE8kRLVF6RBA9ftmZmeScltt8ltzgqvGqEBh0PWrXfesS+Xny+VqJ991kxcVGfV116zJjXp6a4OrYMG6Qib4g5NSkoQjh1zbdTnzLEuu3Mnc8OGzLVquap+7t0LZ7N69VDODps2QZQoLs49gdEoGjirnj71lHn7O++Yt3fvbr0fsX3UKPfH80RK1Mgxq+ytzqkVIiLM27dvN29ft879+WgUPnJzEa4bFgYBRjtkZmIKuEwZ+JyoOHcOYepRUdaJRplBkOPizPXhm28Cdx0aRQdNSkoYsrNhJVFf1kcftTaVJyYig3C5cszffmvepoblrVhhf7wDB0Bu6te3TxOuUXTo0QN1oFYtWLZULZLvv/dsmWBmvvNO9z4eAp5Iye23uz/Od9+Zz6VzZ/P2u+9mrlDB/fSPRtEhKwvTwhER9mSCGZbVa66BNLxzPq/9+2WEjR3pnDMHpEetK3YZgTWKHzQpKaFQJbyJIKLmPFXDjIZECBE9/7zZ9KkKGDkrKqo4eRLJ0WJjkZVYI3Qg5uv79gX5fOkluc05G7UdWUhNldvdhY67IyWqSuzbb1v/v3Vr87molpkDB9AR9emDbfXqeXHxGoWGtDT4opUrx/zrr/blDh9GWoAaNVzbilWrMHUcF8d89KjrfzMzof6r1pE6dbT/SEmDJiUlGM6dTnQ08++/u5ZTk/ndfbdZYTM3F6F8REh3bzdfm5SE0U/Fisx//BGUy9HwA6pj6KhRII7COfnECVdScuiQ9X7E9urV7euAO1IiHBaJrMNCnaeaiJjfe09uHzYMiQMnTMC2Z57x8UZoBA2nTjFfcQWioZy1kFQsXQrS0ayZaz0TETY33WTtZH/okDnEnYh58uTAXodGaECTkhKO5GTXxv6FF6zD8+bPh0m1UyezU6SaZ2LgQPuIm4wM5ltuQePiPB2kUTTIzpbPfft2CFhNm4Zt+fmudcMqTJcZZFaUsZvOsyMl6jnYRfGsXy/LXHcdPhcswLZ//8WUwFtvYaqQyP1oXKPwsHu39D+z0wQxDDy7MmWQtkAlHQ4HHKyJmIcPt9Y/mj/frEBM5OoHp1FyoElJKYDDgQR+6kvdu7d1HP/mzcx168JHxFm+fv58WELatrWfw83NRWhfWBjM9NoTvuhRsyae+W+/ITqhfn1p8nYmJUT2ehJie79+1tvtSMmcOZ7n/gcPlmXq18fn7t3YNmYMRthqokF3IesahYOVK5ljYkA0T5ywLpORISNknnnGrI90/jzaobAwhPU6txU5OcxPPOFaP+2yAWuUDGhSUoowd6755W7YECTEGSdPMl95JZwKv/rKvG3nTmQYjo11zUsh4HBIM/sjj2j116LGU0/hWUyciI6eSCr7WpGS5cut96MqsVpFW1mREsNA7iV3PiuqSJtz55OYCOvd1Klma4pG0WLOHFhEe/Swd37+91/m9u3Rjjg7vv7zD8LCY2OR8dkZ8fGw2Kr1Ydy4wF+HRuhBv96lDKp2hVg++cR1lJKRgVE1EfOIEebRyfnzmPsND2f+4AN7a8hnn8Hs3qOHtZibRuFAaNg0bIjfffsyX3YZntuVV7rWBztLSFaW+2keK1Ki+jVZibMxu2a/VonHxImIGkpKwhQAEZwdNYoGhsH84ot4Dg8+aD/g+PNPOLM2bGie1jEM+ApFRMAHzYrc/vILtqt1wTlHkkbJhSYlpRDZ2QgRVV/6oUNdzaKGAa2BcuUwZXPwoNyWlydz5jz4oH145ooVyGdx2WU6bK+ocPasfM7Z2YhyIGJetoz5P//Bd5H/Rix2o9/YWPO+VFiRknvvleXtyGujRtakJD0d0wP/+Q/KXX011mt/paJBbi7edSJEcVk9T8NAhFZEBKJxzp2T21JSoE1CBBVqZ0KTlydVYMVSpoxWjS5t0KSkFMNZnvnyy61zpOzYAY/5ypVdzbBffgkntM6dEfZphX37oJ1Ss6YWvCoqiGe8Zg06jjZtoI76009Y7zwytbNq7NkjywjRq+nTp3NcXBw3b97cREqOHpVl77jDen9Wgn9EiOaYOROdUnw8pgTFNjv/BY3gQZUHmDvXukx2NqKkiOALopKOrVvRBsTEIE+NMxISmK+/3lwHnnlG+6SVRmhSUspx6JBrhzBvnmu5tDTme+7B9tGjzaPkjRvhfV+njj3pUFUarfavEVwMH45n99pr+P3ZZ3AwXLjQ/OyFBa1mTft9ibI1apjrgbOlRNQXIvvR7quvYnv//ubzmDwZxKlvX5RTyZBG4eLwYVg6Y2Ls/cgSEpivugrv9xdfyPWGgXxHUVGYKrTK8Lt8uWsbpPWOSi/0K67BeXlS+VMs99/vGuFgGJj/j4x0bWBOn8YccdmyzP/9r/UIJztbCrW50zzRCDyEemu7dvidmYmpmEcfNT93Neu0ldWMGc9XlFHF1FRSsmGDLFO2rP15qftRz+PJJ/EpNG9EIj87fxeN4GDZMqktYqfYvG4dBiT16pnJhJqbZtQo+CSpcDikf4pYKlXS/melHZqUaPwPv/5qbiCqVbMeGW3ZIk2xP/0k16shfHfdZZ+p+IUXUGbQIB3eV1g4d04+VxHy++yzmJJznsMXHYlVgj5ms9BZnTrwWWGWpCQlJdVkirdLDCkigYiQXE89j7g45qZN5bn27Yv1H38c2PuiYQ3hkFqmDHOvXtYh2Oog5ZprMDAR2L2buWVL+CpZ5aQ5exY+J+oznzhRD1Q0NCnRcIJVeOb48a6jHNVp7cknzVLP8+dDPbZpU1etE4FvvoED7ZVXWsvfawQe4nmKJIsnTiCCyvl5//mnK4Fxxt13yzItW2JfgpR8/XWqaX92EKHKTz5pdogVy7vvup67lflfI7DIzobjOxGekaotIpCcDD8hq+ncOXMQBnz55fAnc4aamFEsa9cG73o0ihc0KdGwxOTJ5kbj8stdR7yGwfz++zDPd+5sJheHD0OjICoKo1urEdDWrQgZrF7dfq5aI3AYNQrP8r//letUcqESEU+dRW6uLFO9Op7j1q0gJUSSlKxaZf1/1dqyaxcE+9RzKF9eJg+Mj9f+JIWFU6ekb4idQ+u6dXjeVaow//ijXJ+ZyfzQQ3hOQ4dCVkBFZia0RtTn3KaNnq7RMEO/5hq22L/ftcN66y3X0fOGDWikqlWDxoBAVhbzyJH43333YY7ZGefOMXfvjhH7O+9o820wsWQJnkXz5nKdmhtH7fgnTpS+AHYQ03AxMSKk2ExKatWy/6/qc8Lseg7Dh8uyn32Gdffe6/+1a3jGxo0gh3XrWuuCOBzMb7yBSK2rrjKH+B88CH+kcuWkMJ+KtWtdiad2eNewgiYlGm6RlwcriNqYdO2K0auKpCSZwfXpp83hgN9+Cwe2Fi3k1IHzMZ5+WnY8ziMsjcDg4kX5DMV0m1UivJwcMyG1I4quuXPMpMR5yk+FmB54/XX8dj6HLVtkWSHwJnLhaAQec+fCOnLVVea8VwKJicw9e+I5TJhgfr+//x6+Sc2bu1pTMzMx/ev8fIUVTEPDGZqUaHgFoWehLnPnmjssw0C+m/BwhP+q6cf370dq+vLlrUdSzNBAqVABJl3tOxAcCJE0NZurGk1DhIgLZvnbnZqmmo9GkJKoqFS3AmcqmTl50nws52kataydoJuG/8jOltN6diKIy5cjQ3ONGuYs41lZzI8/jv8OHOj6fP75B0TF2dKqoeEOmpRoeI3UVFg81EbmzjtdE/utXQuVzkqVzBL2GRlSL2PQIOu55J07mZs0QRiiCAfVCBxEtudnnpHrMjPNz/SJJ7D+7bfxe+RI9/v85x/kSLpwQUbfuMOKFdhvxYr47excPXGiLCvy3YSH+36tGu5x7Bhzhw6Inpkxw9UilpeHdAJhYUgroVpQNm6EdklkJMK51f9mZkqlYHWxssBoaDhDkxINn/H1164NztKl5jJpachRQoSQQjEiZoZ3fuXKSMglRuUqLlyQ2UNfecU+AkTDd6xda+00qj7LJk2w7t9/PU/hqLDLEuwMEd47cyZ+//ij+fiq0JpwuH7+ee+vUcMzFi2Co2rjxtZJOY8fZ77uOoQEv/yyjMDJzgZRCQ/HtNquXeb/rVuHqDs7/yANDU/QpETDL6SkIBRUbXycE/cxQ/ukTh00gF99JTu3+Hjmbt3wv9GjXRU/8/PRIYWFMd98M+a0NQoONWpGzUviLPEtIH7bhXar8IaUqMcX+ibCeuaOLOmEbIGB6r91++3Wvh0LF8JpvX59hO8KbN2KKdiyZZH7RvUrycqS+1UXPQ2r4Ss0KdEoEJwF14hgzleRlCQFuQYMkJ2RwwF/hvLlMTpfs8Z1/0uXQvK8dm0dNhwoXHeda/SDs8+QgIiwGT/e8369ISXLlmF/VavKdc5RGQLqtI6VVoaGbxD5ZcLD4dvhbP3Kzpbih337ymnZ3FzmqVMRddO2rTnrLzOm2Bo2ND/DsWN1JJ2Gf9CkRKPASE/HnLPaKN1/v6vPyA8/QNq8Rg1zUq4DB+D1HxaG0ZZz1MapU7CqhIXBjK87qIJhzhw8o9695To1eZ5KDA4c8H4KxxtSIvLhfPSRXKce98kn5fqff8a6Tp18vEANF6xYAXJft67Z+iGwfTtSEERGQntIPOudO6E3FB4Oy6UqkmhnHTl+vHCuSaNkQpMSjYBBVQIVy/z55s7szBnpUzBokJSvzs9HeGhkJHOrVuaQULH9xRcxx921q31GYg3PUCXnxbNxDg1WnZfFut273e/XEylRj6FOx6nHVZ2bBw7EOruMxRqekZ+PqZYyZTBwcJ4Gzc3F9rJlIZC4dSvW5+UhWWLZsngfnf1ONmzA4EJ9dpMna+uIRsGhSYlGQJGZKadqxHLFFWa1V8Ng/vJLSNHXq2fuiHbuxIgtIgJTB+q8NTPz6tUY7TmHJ2r4BvFs9uxxXUeEqCkBMRqeNMn9Pj2Rkq1bXS0xzmRI9XEQ606c8OMCNfj4ceYuXWBhnDLF1cK4axecVcuUQR4kEQ68dy+sU2XKIEpLDRPOzsY658GHfkYagYImJRpBwcaNrg3XO++YG8bjx6HmSoRstULxNScHo67wcIQsqh0nM3xSevfG/5yFnDS8w5QpuH+vvSbXCZEyZ+KwbZu1E6ozPJGSxx7DPqZNk+tUZVd1/4cOeXdMDWt89x2cyxs0AJFXkZeH5x4ZicSHwok4Px++JlFREDpct878v40bodiqPq/XXtPWEY3AQr/yGkFDdjbzmDHmRqx8efPUjMg0WqECMg//9ZfctmEDInyioqCZoRIah4P5zTdhUbn6au3l7yt27XLt9D/6yJogqNYMZyVfZubp06dzXFwcN2/e3C0pEftQp97U8NGaNeX611+XpFPDe6SlSbXcgQNdo2tUK4jqv3XwIDL9hoXBqVmNosvOlskT1UUn0tQIBjQp0Qg6duxwbdBGjzbnwjl0CCqwolEUjaVI4hUWhsiBw4fN+/7nH2gtVKqEHCl61OYdVKIhOq4jR8zPSE1XLzRnPvzQfp/uLCXHjllbPtTjvfyy63pPfiwaEuvXI4qtYkXmzz83vwv5+SD2UVFQWRURcg4HLFfly4MgOkfALV3q+u7OmaPfM43gQZMSjUKBYcioD3VRE/gJ83FkJBrO5cvlttWrQT4qVnRVn0xLk1oXffrAmVbDM/r3xz0T2WCd/Ts+/VSWFYn71FBeZ7gjJW+9hf8/9ZRa3ny8TZuw/vx5V0dcDXvk54PQhYfDCnLokHn7gQPSCjJunLSCHDnCfMMNuM9jxpi1go4ckVOrYunVS+el0gg+NCnRKFRkZjLffbe5seve3SxBvWePbCzvvVduS0tjfuQRrL/5ZlfnuoUL4QDrHHKsYY3ff8e9bNFCrlOfS0SEXO9wyPVW+VGY3ZOSiAj8V9W4+Pxz8/FEuOmsWfj9wAMFv8aSjvh4WBDDwuCIrPpXqVaQJk1kKLDDgam6ihWRDmLVKvmfixeZn3vOdfCwf3+hXpZGKYYmJRpFAlXCXCwzZkhJecNg/uIL5urVEaXzwQfSp2TJEkTgxMS4mpITE2XI8bBhOombO2Rny3svpsuc1VXV9ABCdE21YKmwIyVqbh31WTVrZu3DIkJN164N0IWWQBgGyFtMDJxZ1QSLzJjmFCq9jz8urSCbN8us36pzuWHAOdb5nXz//cK9Lg0NTUo0ihTff29uBMuUQViwQFISrCNhYQgtFpECFy5AoI0I0xCq/oJosCtVwkhQdZ7VMKN1a/M02qpV5uehZnX94w9pxreCHSkRFpmuXeW6U6dcrWXMmB4Q63TOI2scOSLFCgcNMjuz5uWBSFSoYLaCnD8v36M2bczvxI4d0jIplubNXUUMNTQKA5qUaBQ5HA7m224zN4p33WVWhly3DvolYWHIWisa4vnzYU2pXt2cW4cZKqXXXSeVYu2mHUozfvjBTBguXjQ/h3btZFnV4mEFO1IifBNUXZl33zUf5+uvsX7BAvzu0iVw11hSkJ+PsPry5ZkvuQQWQxUbNkB9Vbwj6en4z8cfI5dNTAwsjnl5KJ+UJMO01cUqQZ+GRmFBkxKNkMHx464N5LhxGOUxozGdNg0ZhmvWlFM3iYkgMUQwWe/YIfeZn8/8xhtSsXLDhqK5tlCFapkQ02POz8BKYM0qHNSOlDhPETG7aqIcPYr1HTvi92+/BfhCizl27oQTa1gYpmPS0uS2CxcwFRMWBhK5fj3Wr18v7/PQodIBXBAV5+f89NOFf10aGs7QpEQj5ODsAEnE/Morcl48IUE6y3btCu0FZiR7a9kSU0CPPWY2a+/YIdUrx43TUQQqLrkE91I4QrZvb773zz4ry06ejHWqAJqAFSlRfYcE9u93fb6GAdLpyZm2tCE7G0J3EREQOlOTXYqItpo1QdTffx/38OxZ+FMR4Vmq//n7b/igqPe+VSs9VaMROtCkRCMkkZ8vfUacnWFFhMEff0BboWxZ5okTQTRycqDHULkypnQ+/VT6JuTlQXCtXDkIta1YUXTXF0oQDo63347fIvpFLI0ayWmx3buxrkIF1/1YkZL33kP5qVNlOaEmK5YqVbBe5E5q1ChIF1rM8M8/ICIRESCDKlHbswdTXEQg6AkJeGemT8f9rFoVETbC+nXyJPMdd7i+T87hwxoaRQ1NSjRCGunpCGdUG9LoaHSkhoER3tSpEIVq1Ih58WL879QpOAESYUpAnbY5eFA26MOHm0XCSiPUKRzDQAfn3HmJ+6dqmQjfBAErUlKpEsqKkFLDcH2er7+ObX364Pe33xbCRYcw0tMxRRMWhrqrOn5nZCD3TEQEopeWLsX6NWukz9XDDyPpIjOIzCuvuD7PH34o/OvS0PAGmpRoFAuoiqCq2VmEpx46xNyzJ9b36yd9HkRjTQSTtojScTgwr165MnOdOlrXJDoa90h0gOp9jo1FRyjQsiXWi0goAWdSohIYYWlZv956tK6WLc1Ta7//ztywIZxZnXNFLVqEbVFRSFaZlcV8+jTz4MHW5HvxYtd7PWqUK5nU0AglaFKiUaywYoVrQ3vjjcinYxgIMa5bF1M0EybAryQ/H6bsqlURgSDm3pkhwCYif+68E418acTXX+Me3HMPfjduLO/vAw8gRFQQi7lzsf6JJ8z7cCYlYqrn0ktlmccfBwl09icRirENGhTCxYYgzp+X5KJbN3Mup/h4qb3TsydIXF4epsaio0EaP/lETlMeOMBcv775HrdsqZWONYoHNCnRKHYwDOmroC4DB6LBTkvDHHyFCiAib72FUeW5c1KroXVrmT3VMDBlUL06ys+aVfo0MpyncGbPNt9XIhmFo8rAq3AmJZMmoczs2dhuGOgsnZM0MkMGnaj0Rd0YBvO8eXBWjYlB3RPkLycHU1sVKjDXq4cpF8NAvb38chn6m5SE8sePg1ir97ZMGZAUDY3iAk1KNIotsrOtnWFHjYLF4/RpNNoREegMZ8+G1WTzZuarrpKWASFXf+4crAJECL8UoZWlBUJJdf165pQU8yi7UiXrhHnqVIAzKRFlhPVJJGZ89VW5bcwYc9RNaZpaOHlSWkAGDDCnWvj9d+bLLkM+m3HjQLQTEpB2gQj1V2TbPnBAEkd1cZ5e09AoDtCkRKPY48wZROE4N8rPPQeZ+YMHZaN92WUQ6HI4IGNfsyZygLz+uoxu+Osv6YcyeLC5syjJEOq6N9+M385WqCuukGW7dZMERkAlJWquHIFXXgG5ueUWue3wYan4evXVhXOdRQ2Hg3nmTEy91K7N/OOPctuOHbj/RNDc2b4dUzmjR8PPpEYNhMw7HNjmbBkpjdYmjZIFTUo0Sgw2b3ZtoImgHpqdjSy0Qp77mmug2ZCSwjx2LEakzZtLlcz8fHQcsbHoSN94o+RrZ6i5cPLyzH4J8+bhMz4eZZcswe+hQ+X/VVKycye2q8n+rr4aFgFnf5KGDfF93bpCvdwiwf79MvJr2DCppZOQgN9hYaiHCxbAEnLPPZiCqV4dzq3JyfC/ufVW13quZnXW0Ciu0KREo0TBMBBJY0VOvvgCZGPpUoz6iRCGumsXnDJvvBHrbr9dKoxeuIAphvBwWGNEjpiSCqGo+vvv0vmVCBoikZFSNC093dUSopKSqVOxbdYsbDt7Fh2u6qsSEQFfH5WglFQkJcExOCICTsTLlmF9ejrz88/DbyQ2FjLwv/3G3KMH7knjxtAeychAve3a1bVeT5pUsu+dRumCJiUaJRbr1lmTk8WLYf7+9ltEhoSFYcT/77/QP6lfH2GXU6bI8NTdu6WVpXfvkpvKXY2CUS0nAwdidH7DDbKs2PbBBx9yXFwcN2/e/H+kJCoK28TU15w5+P333/J/b7+NZ0CENAElETk5IHJVqyL8/LXXkEMoP5/5s88QiRQVBb+RmTMlWW7fHvcmNxckW5BF5yk1NWRYQ6MkQJMSjRKPffusycnateg0pk+Hb0lUFPP48YhiePZZWAYaNsQcfl4eRqM//QSRtogIlHVK81LsoeqFqAn4iBB2WqaMnHLo0AHrt2/Hb9VS4mxFGTgQHauQPxcOsBER+L5vX+FfazBhGMwLF0LgrEwZ5hEjZEjuH3/I7Mz9+iHnzKWX4nf37rCI5OYiwWSrVq71tm1bPBsNjZKIMqShUcLRsiWa86NHiSIi5PprryWKisLnkSNEzz5LNHMmUevWRJUqEW3aRHTllUQPPkjUqhXRt98S9e1LtG8f0dSpRDNmEDVvTvT550SGUWSXF1CEhRENHozv331HdNttcluvXrjO5cvxe+xYfH7/vXkf587hMyYGn3l5RL//jn3Nni3LVahAlJ+P7y1bBvY6ihLbtxPddBPR7bcTNWyI3zNn4r706kXUsyfuY58+RGvXEr39NlHHjkSbNxMtXox62qwZ0QMPEO3ZI/fbujVRSgr2V7580V2fhkZQUdSsSEOjsHHoEDQhnEeg27dD8XXMGOTTqVMHJvWNG6XA2mWXMc+fj+mfEydkiGbHjiUnhDg+Xt6TDRvk9127MHIfNgzlEhOlbwiztJRMmwZLyRtvYP2qVSi3ZYvcV7du8J8gchVhK644dUo6q7ZsCf8jw8D6hx6CxSQqCta3ChUg8DdqFCKQ0tOh4Fq1qmu97NQJDtkaGqUBmpRolFps24ZpG+dOYP16hGHef7+Mhpg/Hz4qIlyzXTvIfhtGyQwhFvciKUl+HzAAU1Z160rHSnWaRpCSRo1ASk6exHrxHzWnjki+p/qdFFdkZDC/9BJCy2NjMR2Ymwvn3ilTsF6tX1WrIlw9MRFTYS+8YD29eMMNEKrT0ChN0KREo9Rj1SpXWW4ijHS3bWPu1UuOWFetAgkRYZ2dOiFSpaSFEIskbpMnm+/JsmX43LED5UTCvcRESUqIUk3+JC1awFIwbpzcj2qNKa5wOOD3Ub8+LGvjx4NkbN/O/OCD/D9nX7E0aAAl4vR0+Jc8/bQ1GRkyROZo0tAobQhjZi7iGSSNEoj8fKKLF12X9HR85uTIZpjI3CwTEZUtC5+D8uXx6bxUrowlLCxw57xzJ9HEiUS//WZe//LLRB06EE2ZQrRxI/wCXn4Z8/uTJxOtWwe/lJdeImrXDv4mH35I1Lgx0bRpRLfeGrhzLCykpxNFR+P7Cy8QPf88vmdnE1Wrht9PP41rnjKF6IsviPr3T6OYmBgiSiWiaGImOnwY/hELFhD16yf337cv0aJFRPPmEd19dyFfXACwdi18ajZtIhowgOi11+D/8f77RH/+aS57+eW4V/fcQ3TqFNFbb6F+OGP6dKIRI1D3AwXDwLO8cIEoOZkoIwM+Prm59p8OB1FkJFG5cvC5iopy/V6xIlH16kRVqxKV0Z6JGgGEJiUaPiMjg+jgQXQ4CQlEZ84QnT4tP0+fJjp/PvjnERlJVLMmUY0a+FS/q5+1axPVr08UHu7dflNSQCzef9+8/ppriIYMIXrnHVz/TTcRjR8PIjVlCtGWLUQ33oiOukoVoieeIFqxgqh3b/wnLi7gtyCoKF8eJGT5cqLu3bHur7+I3nwTdWDlSjgIN22Ka1u/XpKSYcOiadYs3MMJE1AfKlfGPl55hWjSJHzPz/f+uYQCjh3D9fzwA5ygp0xBXZg+nejff81lu3QBGendm+jAAaLXXyf68kvXfa5ZA1LrLZiJkpLgEHv0KJ5BQgJIR3KyJCAXLqAu++KEHREBkpGb61358HCQkxo1zO9crVpEjRoRNWmCpUaNwA4gNEouNCnRsEVqKiICdu5Ew3vwIBrXhARZpnx5ojp10PGrn7VqoWOuVMm8VK6Mz6goNFKioVK/E2HUlpVFlJmJRf2emUmUloZohrNn5af6PTnZfC0REYiEuPRS89K4MT6rVnW9fsPACP+OO1y3TZiATnnTJoyEx4/H6PHll3G/evYEOTl5EgTKAQ0AACAASURBVNvi44nuvRedWIsWBX40hYKVK0G8WrWSUSCdOiE6Z+xYdIyVKsmRcmqqJCVbt0ZT+/ZEPXrg3gtrExHRp58SPfwwti1dWiSX5jNSU4lefRWWr+rVQU4vXCCaOxf1USAsjKh/f5CRzp2Jtm6FNc3Z+nbFFURLlqATt0JeHtHx4yAcKvkQ39PSZNnYWJDuatVQj+0+q1bF8ypbFoTe+VMQEiIQn7w8kNKcHLmI3xcv4l0Ti/runTuHAYo6MKlcGe9Zs2ZEbdrAoti+PVG9epqsaJihSYkGEWFktG0bOtmNG7EcOIBt5cujMWneHB2q+GzWDA1dKDYqeXloFM+dg8n82DE05uLzyBFzw16liiQqrVqhA+3QASSLCKSiWzf8X8W992I/v/5KVLcu0Zgx6CTefRehw336ED33HKwor76Kc7n/fnRUzZoV2u3wC8yyk+rVC2G9RLCQNW1KtHAhpmHE84+PT6NGjUBKHI5oysvDfX31VaKffyb6+2/z/uPjQRRDGfn5RJ99BjKZnk7Uti068TVrzOUiI0FUxo/Hu7FmDULJDx82l3vsMaL33gMBSE62JhxHjoCQCAtHeDjuU5Mmso6q30XodaghPV1ej1gOHkRIsxg0VK8OctKxI1HXrrBGVqxYpKetUcTQpKQU4+hRdDR//IFphowMNK5t22JELJbmzUvevDGzuVNQO4QdO2AFIALREATlyithFfnkE0xBqGjQgOiGG2DWj4oiGjYM1qLZs9Ex3Xkn/FXWrUMnnZgIHYrJk9HBhCqeego6GkOHwm+ECCPlZs1gQXr3XXTE775LNGtWGg0fDlLCHE3//INpiU2b0OkQYZpn3z58D+WW59w5oq++gr6IIOcVK+IdqVABJD4/H343o0aBjNaujXepd2/X/T37LAjEhg2wnhw9arbmxcTIqQ5n4tGggVlfp7iDmejECQyCtm/H57p1sLJERKDN6doVVrrrrw+sj41G6EOTklIEZnQQ33wDc/KhQ2gErr0WI+Fu3UBIoqKK5vwyMmBJSEyEuVwsKSn4dJ7nVi00Vt/LlEFjX60arBdiEb8rVLA+D2aMVDdvhoVj82YsohNp0AAEJTPTevrhnntA9i5eRMddqxasCsePw7IyYQLR6tVwjjx3DtMhzz2HDijUkJnpOnL94APUoz17cH/27oV1iSiNiGKoa9dUWrUqmt54A9M2iYlyH61bE+3aBeG5Rx8t5IvxAIcDz3PWLDjh5uXJbeHhmJbMzoYFrm5dTGGNGIEpkW+/Bcl0Ro0a+E96Ourj5ZeD4DZrZiYfVtOHzLDCnT8Pkiw+k5Kwz/x8nLPDIb9brXM48E5UqIBzrVhRLlWrSn+smjWLzvLJTLR/P94LsZw9i/Pp2xfOxD16aNG40gBNSkoB4uMx6ps7F+bTunXxovfqBcdMEWURbBgGRkh79qAj27cPHXVCAshIaqrrfyIiQCxiYuD1L6DWWrvvDgf2eeECvjujXDlXohIbi8b50ksxRdGkCTojItxHQVAEWbE6Z4GrroLT77//wopSvTpGyqdPS7+MlSvhAJmUBPP/c8/BQTCUULOmVGkV+OwzdMgXLuDZoCMDKfn991Tq2TOabrsNRLJnT6L//Mf8/9zc0BkBHzsGi9YXX8AHSEWVKvB7uHgRz7FlS/iL3HcfSMaLL4J4WaF2bdSBzp3x2aEDSAEz7puYTjx2DHXr7FlXAiIUb1WIqLSICJCl8HDP3w0DBPPiRZD/jAyzL4xARARIdOPG0t9KEKdWrXA/CgPMsKD8/DPRTz+hvahYEeTkkUcwzROK08YaBYcmJSUUzBitv/02Oj7xQg8eDCIS7IiHvDyYqf/+GyNjQUIyMrC9YkWY8hs1QqNfrx7IUr16csQWE4PGt6CNj2FgxClGmUlJ6BTU3+q6M2fMzrwVKkjTetOmkqw0aYLr3LYNBGXjRkSnuEOLFnD6O3oUx+vWDc/k9Gn4Gly4gKmfSZOILrmkYNcdKOzZgxG+ioMHMa33669Et9wCqf1hw0BKUlNTqVKlaIqNJRo3Dv4YKlq3hjNwUSI7G53drFl4PyIi8M4I8tq8Oawcwh/pmmtARlq1wjMePtx6vyNHYuqhbVsQCkE6VJ+mY8dgORGIjgYBqF0bxDU21vzpvE4l5wWBYYBUCydxsZw6BZIkpjTPnJH/adgQ19a2LayF116L8wo29u8n+vFH1LMjR1AfR4zAuxOqPjUa/kGTkhKG/Hz4NbzxBnwjOnWCc13//hilBQuChAjT65o1GJVVrIhO6LLL5NKqFaIFQtlPJSsLncfhw2gEDx+W3+PjZedVtqwcSTZtipF0lSqwiDiHFDujdWsQrp07QcTuvhv3cf58dBbDh8MXoUGDoF+uRzgTw337QKgGDUJdy8ggevHFNHrzTZCS+PhoatuWaNUqkGAV+/cXXQTStm0gIl9/jWnBSy+Fj8yFCyAqXbqAhO7YAWJaoQLWhYcT/fKL9T779cPUzYEDeJY7d+K7cFSNjAT5FtYHYYEQ30PVWVwgMxP1fudO3BexJCZie6tWsAR26UJ0883WU1GBgmHA/23mTEyJVqwI4vvEE5qclBRoUlKC8NtvRE8+CV+Rnj3hu9C1a/AavPx8omXLMDW0aJEkIddfj+N27YrQx1Ax0wcKIlxTJSri+8GDICxlyyL0MS4O98cdoqPh1LdqFTrKa67Bvd2/Hx3lQw/BSbZ+/cK5Piu88QbRM8/I3zfcAMvWsWNE69djXVoaQoJTU1Np7txoGjsW26680ryvwm5xkpPhRzVrFkhJ7dqwhKSno6OtUAHJAg0DSQh9QZUqeGZE6BTbtJFLy5YgH3XrhjYB9xf//gtL6F9/YTlwABanLl2QjPD224Nr7Tt1CpbgGTNgUR0/Hu2fjt4p3tCkpATg6FG8jIsXo3N76y2E2QUDwln2q6+gxnnuHDree++FI9qVV5Y8EuILsrLQ0al+J3v2eC9gdfXVuMfr18OylZmJ/0ZGwlw9cSI6ucKGYbhO+c2YAStcSgrOVSUlI0ZE0/Hj6IzXrpX/mTYNo9rCON/Vq0FEfvoJRLJHDxBAEZbatCmmno4cwTSUirZtYQ2wQ4sWKKOSkEsuCW2LR7CRkIDBycKFmBIT9/yhh0BQguVAf+oU/LJmzsT076efoh3UKKYoTE17jcDCMJg/+gjZRhs0YP7hB5koLRjHWrCAuW1biMHXro1cJlu3Bu+YJQUZGcxr1yIr7uDB1vlOrJZ27ZgrVzavi4hAVt2iSGJ32WXmc9m0CZ+jRy/guLg4bt68ORMRp6Skct261rld8vODe44nTiA53qWX4njNm6OePvoo6iwRkiqOH+/9cxDLf/+La87ICO41lASkpDB//jnzNdfg3lWvjuSEFy4E75gHDzJ37YrjPfggc3Jy8I6lETxoS0kxRUYGQiq/+opo9GiY14NhtmTGtNCUKfAZufFGmPFvuqn4yIPn58Oik5iI5cIFGYUgcvLk5MiIBedFjWYID4ejoXBAFPLasbG+3Y+LF2EN6dHD/+saOxb6GIUVrXP6tNlKM3IkfDMmTIDvi7CUbN+eSu3aRdO8eQiPFrj7bljXAo3cXFgJZ82CTki5ckQDB8JauHkzpmQiIhCefeiQnG7yBlu2YArSGzBLx9G0NEwPOS9pabCmGYZ17iciTEWI3E5CAblyZUwP1auHaLDISN/uUVFi716ijz+GBSMyEpay8eOD4wNiGIik+s9/EEW0eDGm6jSKDzQpKYY4fRo+I0eOIDTz3nuDc5yDByGatW4d0XXXIfzR2WkxVJCdjSgfkZPn0CEsx44hvNKqlqvy95GRUtPBeVH1HhwOHMs5xDgsDGHFNWqYyYrIByIkths3tu5QXnsNHbs/6N4dBKFPn+BPnTlPT3Ttiuv+8UdJSmbMSKWRI6PprrvgdC2QkhLYjmjvXhCRuXNBOjt3Rlh1VBSiNNaswb2/5BKQE2/x2Weo9yrJzMuDD8XhwwgbVnM9qZ/Z2db7DA+XJKNCBUxridQKaqoFIhm6m55uHbYbFoYOt359LJdcAmfTNm0QlRJMh/aC4MwZTC3PmAFfnOnTEREYDBw+jPfhzBk4juvpnOIDTUqKGc6fR0eQkoJRIUSrAo+vv4Ylpk4dNB49eoTWfPnhw8jGKmTxd+2Smg61aplDd0UuHrEI4TR/nQ+Zcf9F3g8hZ68u6rrERFhiiHDMhg1BUJyXRo2Idu/2fmRuhQkTMIfftKn/+3CHJUvghyEwdix8NuLjJSkZNCiVtm2Lpt27Zbm6dc1h1v4iPR2Wj1mzYPGoXh0RQP37E/3zD7Lvnjjh+37btIEmRkaGdFwW0uiHD8OxWRDRsDCQTaucT7Vro45FR0sSEh0N640/74/DgXNKT0edS0gAKTp5Etd58iTu/aFD8vyaNMH1XH01CGvbtqHlaHviBKy7ixfDejV7dnC0klJSYKlbuRL1VhOT4gFNSooR0tJgqThxAt7uLVsG/hhZWXBenD0bOVpmzJDZXYsSeXmITvntN6lGW6YMQow7dsTSoQPuSSDP1zCkhomY6lGnfFTzOxE6nvLlQXrEUq4cnl1yMgiKask5fFgSlvBwWFKaNkXnJmTd/UHXriCV/foF3sFQ7Vzbt0dEy/nzRGXLgpQ0a5ZKXbpE02efyXIFCQNmBuGYNYvo++9hPejZEyHTTZpgamD2bGuhMU+oWxdaG8LKJhySK1Y069E0bQprV+3a6EAzM81TMunpOM+ICPslKgqWm9q1A/9OZWfDciRCkrdvB2nLygIJ79YNZHLAgMITS3QHZljRRozAlNTixcFRNM7Lg8Vk3TpECrVpE/hjaAQWmpQUIzz0EBrlv//G6CfQMAyMXP74AyPOoUOL3jpy6BDM6V98gbn6Bg3QuN5yCwhaIBr3tDTobuzfj8+DBzEiFSZ5VW68oIiIkP4o1atj6oMZnYrIwCpkyY8c8S3tvB3Gj0dW3kBpg4wdiygaFX/8QXTVVSAlYWGpFB0dbVK79aeVSUwkmjMHhGP/fliShg2DYNbOnUTvvANrWUFQtSqsjdWrY2pJZLDOzgb5P34c1q60NBDRQKFiRVcry6WXYvqlVSusK+i7l5ODznjFCqLly6GdU64crEpDhsCKUtQWlP37EY6dlgbiGQwLX3o6SPrZs4iECwVSpmEPTUqKCZYtgzDRzJkYXQQDTz2FxGoLFmB0UZTYuRM+Fr/+ivnnQYOQdbVdu4I31idOwOqyZg0WkSCOCPPzLVqA/NSoASfK48dRTohFFSYiIvyzAFjh2mthPbnjjoLlEHE4zAniKldGqPLo0SAlRKlEJFv+n3+GxcYb5OdDiXjWLIiVhYdjdD98OMLNZ88GySoIRE6kixcDSzi9RcuWmKKrXh3WszNnENZ65Ij0SalZE3o1114LK0f79oGp919/TfTllyADl18OP7F+/Yp28HH+PHzWHA6QqGAoxB4/DumCESOgnKwRutCkpBjAMNCQ1a+PUU8wGpAvv4RlpLB0JOxw/jwUGr/6CmbzyZOJ7rqr4Im4jh9H0rQff4QfChFGpNdei8b/8sth5v7lF6KpU2WWYG9QqxbITNWqcDQtU0Y6MjJjxJqVhSmgM2dc88gUBcaMgfXEWT7eW7RoAYuSAHwDrEmJYXius4cPg3B8+SU66HbtQETuuw/36+673euGBBtC5r1KFZkCITIS1yYcofPyUH9Pn8aSleX9/h96CH4WFSvCr2jLFui7bNiA/dSrh3xVQ4diqrIgbQAz9j11KtqTK65A5mtnkbvCxNGjyA90/fV4R4OBN95A+obt2/2v9xqFgKKIQ9bwDatXI2Dwr7+Cs//8fOaGDZkHDixazZG1a5nr1WOOjWWeMYM5N7fg+9y5k/mBB5jDw5nLl2ceMID566+Zk5KwPSGB+d577bUprrmG+c03mbdvZ87OLvj5eMK5c8x//MH8yis41/r1fdfT8GXp3Jl59mzmixd9O8+TJ837adSIOTU1lYmIiVL/t37yZPt9ZGQwz5nD3KULysbEMI8axbxlC+rk1KnBu+5KlZhvuw33+ddfmf/9lzkrq0CPziMMg/n0aeYff2QeMoS5QgXrc2vZknnNGpTPzWVeuZL5ySehRUQEraB585gdjoKf0+rVzO3bM5cty/z++0X7/n/1Fa5v1arg7D8nh7lOHeYxY4Kzf43AQJOSYoChQyEGFawGY9EiNAYbNwZn/95g8WIIg113HTq8guLiReYRI3BdDRqgwU1Pl9t37rTuEF55pWiEybxFfj6e03PPMbdqFdiOeuRIiOF5C+f/HzvmSkqchcYMAwJkjz7KHB2NMjfeiA4pIwMdcMWKgbme8uVBtOfOZU5MDOxzCCRyckCM2rd3vYavv5bkIz+f+bffmHv1wrYrrkA9Liiys0F6iJgff7zg+/MXDgfuQZ8+wTvGmDEgJoEgdBrBgSYlxQDNmqHRCBb69GHu2DF4+/eE7dvREfXrFxjryKFDGG2WL8/84YfmfWZlMd96q7nh//JLdAzFHSdOQOG3U6eCdeaxscwzZzKnpbk/niCzYvn5ZzMp6d9flj1/HsSwTRuUrVePedIk5sOHmTdvZr777oJZPUaPZl63rvh3NobBvH49Ok5xfRUqMJ89ay7399/Ml18ONefvvgvMsWfMwPE++CAw+/MHr7+O6w2WVXLlSlxjIMicRnCgSUmIwzDQub73XvCOceWVGLkWFW64gbl1a9+nEKxw8SIsCE2bMu/da96WlmaWbf/ll4IfL9SRl8f800/MV1/tX4d/882wzNhZ6dSyI0aYSUlKCvPSpSAckZGwhA0YAKvAli3MEyf6d06vvhra1qxAYetW83Vv2GDenpnJfN99uK8rVwbmmGPGYCqnqCxLf/+Na921Kzj7P3oU+1+6NDj71yg4NCkJcaSm4iX65pvgHaNtW4w0iwI7duD65s8PzP4mTcJIa88e12133CEb+NLQqdkhMZH59tt9JwPPPOOaT2TaNLk9OtpMSho2xPq4OOa334ZP1OTJ8D/x5bjbthXJbQoJOBzMvXvLe+F8//PymK+/HlaTQEzvnj/PHBXF/MYbBd+XP9i8GdfpyzSiL0hLk9NiGqGJENL507BC5crwyD91KnjHYC6a0Egi6AYQQQwrEFixAhlJL7vMvP7MGenVv38/dCFKK2rWRNi36OpOnvTuf6+/jsiTsDDokjCbI7XS0szlu3eH9sQnnyCq6YYbiF56CQqk7vDXX2Za0q6dT5dXolCmDEKqRZisc+6giAjkedm9GxFmBUVsLCLSNm4s+L78gaiLVaoEZ/9nz+IzGGHHGoGBJiUhjrAwJJQ6cCB4x7jqKnTmzME7hh0EGQpUcr/kZOv8Kqr0eKBExEoK6tWTBMAwoK7pCb16ocO8/Xbr7ampRK1bI9z6+uuJVq+239ezz0IPRpzD9df7dRklFlFREDsjQuisM4SAYEZGYI4XFlZ0yTaXLYOIXOPGwdm/GAQFKz2HRsGhSUkxQKdOEJQKlIiWMwYMgHDTqlXB2b87iFHwkiWB2V/37uhU09PN61Vdgl27AnOskoiwMChsCoKQm4t8OnZYtMh6fUwM0ZNPWm9r00YmSWQmeuWV4CcSLM5wOJBhlwgCYM745htYOAKRDTc1FfL0VscJNlJToVit5lYKNJYsgZVUzXatEVrwWzyNmSndueXXCAq2byfq0gVqjLfdFvj9M6Mzz8nBiFZV6ywMdO+OEfrvvxc8Jfvhw5CUvv56CLCpI77Ro7GOCPL1NWsW7FilCcyYipk2jWjpUrtSaUTUgIhOkCqeRoR8RddeG9xzLIkwDKjwfvcdfickmLMAf/sttr/5JtEjjxT8eK+9hky+e/dC6r4wMXEi0kls2RIc0pCaChHKxx/3PyO3hu+oXLkyhfmg9uc3KREZQTU0NDQ0NDQ0rJCailxY3qLAlpK0tDRq0KABnThxwqcDO6Njx460Seh/F+E+QuVcnO/r+vVwBp0yxbfcH76cxyefIP/N668TjRzp/378OZfvvkNeigcewEitQgXf96Fi7VrIqF+8CEfAYcMwwjx7No2aNVtNRH2JCFahP/5AhuFAXk9x3kdeHqZlhg3zdS/2lhIr9O5N9PzzrlMFoXhPCnM///6Lkfwvv6hr29OJE39S5crRtHo1tu/dS/Tcc2gPvEmsZ3cezLDCjhuHnFeffmq/v2Dck40bIaF/ww04D2+n8nw5l127YEEdMwZ1jsi1jfUXJanfCcQ+nO+rr5aSAocEC2np1NTUAu0nLi6uoKcSkH0Eaj8F3YfVfZ0wARoCmzYF7zz+8x/M9E+aZA4xLIx7Mns2NFkuu8xep8CX87hwgfmhh6DjEBvL/NJLzPv2pTER8fLlF11CT6dMQUhkoK6nOOwjPx8aF5UqLfNLM8S8yJBgZ4E6b5emTZlr137uf2kAiuKeBHIf3u4nJwfy88734+WXmZOSUpkoimfNyuCOHbH+6qt9V2C2Oo+UFGidEDEPG+ZZaj/Q92TJEuYqVaDknJnp3z48IS0NOkht2phF2UKp7wrUfkJhHwW9ryFDSqZPn17QUwnIPgK1n4Luw+q+ZmdDrTM2FvoewTgPw0CuFyIIXZ07599+/D2XPXuguRAezjx8OHN8vO/7cEZ8PHKqREUxh4UZTLSa33knkxMTIUhllYOkRw/mP/90rzAbCvXEm30YBpRTP/qIuUOHghIPeX/S0pAzxoqUPPoojjtrVmCOV64c89NPoyPOzw+N+1qQ/RgGtDgEIXBepk8HQf71V+ZBg3KYKIWJmG+6CVLz/miSqOeRkcH81ltoSypX9l4HKVD35IMPpvPUqcxhYcy33OKqvxKoc8nIgDhjdLSrimso9V2B2k8o7KPEkBINM+zua1IS8kNUrx481UNmjNqqVWOuXRt5aQoTWVkQ5apZE5ahkSO9J2HukJzM/NFHmUy0hMPDDSaC+uvIkeiwJ0yw7xTDwpgffJB5xQp0FkWZuMwZeXnMu3cjud3o0cy1agWGCFgts2bheAJmQmcWT1Ml33//PXjnJEjSyy9DEbQwEif6guRkKIg+8QRz48b219C3L+T9X34ZSrpRUVjfuLGDiV7gzZvTPR/MAxITIWRXpw4siI8+ivQEhYldu5i7dsU79eKLwUsNkJHB3L07Ulj884/rdt13BQdFTkqys7P5+eef5+xQawmKOdzd1/PnocJapQrzwoXBO4eEBJn8q2fP4JIgK6SnM7/2GnONGjiH9u2RP0VYb/yBuK8nTmTz3LnMDz/M3KKF7Bhq10aCuM6dfesUW7WCYuxTTyGHyG+/QUr9+HE8r8xMayJjGGiUs7JQbv9+KJ/+8APy9kyejIyyXboEl2x4WpYscT1/IdltR0qssrFu2VJ014AOHnV65EjI1c+di0y5Bw+iw754EZYYh0MuhiGX3FyQjJMnYdX780/m77+HdXHIEKRsEGTCm+XGG0FGWrZkLlMG66Kj8b69+y7zvn3MWVkFa2Nzcph//hnHiYiA5P+QIcxHjvi1O79x4QLqRHg48nktWxa8Yx06hCmbChXwfK2g+67goKD3tcCkRKNokJyMBHZE6AgDkcjOCoYBq0nTpmg0hwwpfHKSmwvy1b8/GtXwcOZrr2V+4QUkYVNH7v7izBkQgcmTMW3VsiWOU5QdaCgs7vwWypaV5Vq0YK5a1TVLsN0o+MgR5ksuKfrrK+qlWjUQzsceY/70U1i8AmE5OHIE1r/bb5f5njp0kNNChYkzZ/BeVauG5IlvvhncBJgLFzLHxID4FHZbpVFw+B19o1H0YCZ67z2IW115JdFHHxFdcUVwjpWbSzRzJvQQTp6EoufYsUQ33VS46o/nzhH99BO0MlasgPZATAw86zt0wPVfcUVgNBZycogOHiQ6dgz6EAkJkPsX38+dQ3RPZmbBj2WHypWJ6tcnKl8ev9PScM3p6XgmhuH9vmrXJurcmWjhQvflypSBVoQ7efeDB83KuLVrE8XFpdGqVTF05ZWptGULohnGjyd6+237/SQmEg0cCGn5QCMyEqJi5cubl8xMHNdbeX1/EBODY8fGElWrJr/XqQO1UqFaWr06BOsKgowMaBlt2UK0dSvRmjUQQ4yIgKLuzTdDeVcVECwM7NuH9mnOHJzLsGFEzzwTPOGys2ex/88/J+rXD5onWrWi+EGTkhKAdesQTrtnDz5feQUNYDCQlwfVxbffRkNYvz7RoEFEgwdDmKgwkZ9PtGkTpKlXrybato0oJQXb6tQhat8eOXAaN5ZLo0ZE5coF9jwcDpCT9HT5mZcnx8NE5u9hYQh5Fh1kSgqWpCQz6UlIQJ4YVaOwfn0824wMHEss/8feeYdHUX19/CSBQAgklNBLQgu9xoBUQZp0FBCkqDQLoIioNBVQFBABQVAQEVRAFBBQQKRL76G3ACG0UBIgCaTvnPeP7zu/O7Ml2STbsrmf55lnd2dnZu/MTvnec0+xRP/+RIGBECJqiu302L0bifoyQvsgnTkTwvjNN+Po++/9aePGWOrSRYRYKkrGD947d4j69SP677/0l6tUiah4cfzvGQmygACikiUh7B49Qop2taxBnjw4F4KC8JBUp9KlISLUmlPJyfiPPDwg1jw99e+1n/PmxbpFitg+AaGi4Hy4dk1MV6/iGrx4EeeWtzey5TZqBCHSujVRNiJds8TduwjvX7kSob6lSiEM9803cWzsgcGAdAYTJuC/mDYN98Hsij2Jc5CixE1IS4Ol5NNPYbkYNw43AnvdlJiJDh9GL2jVKtz069aFBeWFF5C9M7vZWbPSpuvXIU5OnMB0+TLyPmhT9JcuTVShgvmebNGiKAaWLx/ab27y8ICVIiUFDznta0oKUVISrBmPHkFsGL+qAiQqSl8I0dMTN/GyZTGVLo3fUgVIfDxqIEVGYnm1LcnJ+uPQsiVEYnIysthaw7p16E1bcyM/d07f637yBDlgZsyI1TlZnAAAIABJREFUo7Fj/Wn58lgaMECceB9+CAubNVy8SDRoEFKdp0ezZshzcvYsMgGrYtQSZcpAoBYpIiwmefPCYnLnjpiMj6Vq3VDPC39/vBq/9/PDOZMnD7arndR5ioLta6eUFLwmJeH8iI7WTzExsABERmJZlbJlIbLr1IGVNCQE9Vycka4/IgKWy7VrYb308kKq+FdegcUiXz77/K6i4Lz9/HOiU6dgiZk+HaJVknORosTNuH+f6JNPYML09cVD6d137ZtSPTkZiZ7+/hsPiHv38JB6/nkhUuxVYMsaDAb0MiMiIFoiIlCg7+FD3PS1ky3rC3l74yFYuLDpa9GieFCWLYvXPHkwNHP1KhI9hYWhFxwbi20VL05UpQoeXgkJECoPH+J93rwYsmrThqh3bzwcpk61ro0//QRLV2Z69sbCJSoKD+4VK+Kof39/mjs3lho08KOWLcUyBoN1Cb5UDh5E+vTTpzNe9o8/YPE4cgRJ8w4cEMKNCA/FQoUwGQyimq6XF4ag6tQRU7lyOJ5RURAp6qsqJtUpNhavtq60UbgwLDwBARBEAQH474OCxJCPPax9mSE2Fha1rVsxXbmCY9miBaxdPXvazypCBCG/ciUEyMWLOO8//5yoSRP7/abEcWRblEyePJlWrVpFN2/eJG9vbwoJCaEvvviCGjdubKs25jpSU1Pp448/ps2bN9O1a9fI39+f2rZtS9OnT6cyVg7I3rqF8dxFi3AjfvVV9EAbN7avWVNR8CDZsgXT/v140Jcpg+EU1eejQQNYKxxtYv3zzz9p0aJFdPz4cYqJiaGwsDCq///OE8zo9T9+LKwexhYR1Y9DaznJm1f/mi8fHi7584v9Y4ZgDA/HdOWKeL1yRTzcPDwgPurXh4BRBci1axArioIbftOmsBY0bUoUGkqUmAiz/dWr1h2HWbOIhg/P/MPt+HF99tuICByb4GCijRvjqEsXf5o0KZYmT/bT/bf9+iFbZ2ZghtgdNAiCUSVvXr2FSeXDD2EdrFwZ5/+BAzj/9u+HwDMYYN2oVUtYN3x8cMxOnxbWlkKFiKpWhQgwnipU0Fsj0tKEn09KCj6npopJ+9nTE+eGpalwYf229+zZQzNnzqTjx49TVFQUrVu3jnr06JG5g5hNYmMhkFV/lePHYX1kxnFu314MFdnbfyMykujnn4mWLIGw7NYN9XKefTZz25k2bRr9+eefdPHiRfLx8aGmTZvSjBkzqJosH54tvv/+e/r+++/p+vXrRERUq1Yt+vTTT6ljx46Z2k62RcnKlSupRIkSVKlSJUpMTKQ5c+bQ6tWr6cqVK1Rc2tGyRGxsLPXq1YuGDRtG9erVo0ePHtF7771HaWlpdOzYsUxt6+FDogULMOZ66xZ6hq+/jt5x2bL2ab+WuDhUHz5yRAyp3L+P74oWFQIlOBi+D4GBuPHbqyf466+/UkREBJUpU4aGDRumEyXZISEBveq7d/Gq9rCvXRPiQ9urLl8eD74qVfAaFATxERWFY7R/P9YnwrFp1kxMwcHC6nDxYuYqur7/PixphQtnbT+NRSQz2hsSQrR7dxy1auVP77wTS/Pm+dGzz2KITyUhQTjsZgaDAcOE2rT3pUrhNzdtMl0+NBQOttqhgydP4IeiipSDB/HA9fLC+desGc49Pz8IoKtXhe9GZCTaQITjXqGCqVgJCoL/SokSlkskZJZ//vmH9u/fTw0bNqSePXvaTZQYDDjXrl8XlsRz5/C/XrmCZQoUgFBu2BDHvWVL7Le9SUyEY/vSpUQ7d6IdvXvDyb5u3axt84UXXqC+fftSaGgopaWl0cSJE+nMmTN0/vx58vX1te0O5CL+/vtv8vLyoipVqhAR0c8//0wzZ86ksLAwqlWrltXbsfnwjVqob/v27dSmTRtbbjpXc/ToUWrUqBFFRkZShQoVMr2+wQBxsGwZLvLkZNxYunTBFBzsGKsFMx68Wr+PsDD0fLRnYqlSQqSoU0AAemPGk69v5tt+/fp1qlixookoURThPKp1XFUtKKrgUCdVhMTF6bfv7Y0hjUqV9OKjalW0OTwcvfMzZ8SUmIiH6DPPCAHStCn225i1a4l69TK/byVLoq1a/4j27Ynmzs2eM/K+fTDRq3z2GQTOf/8h+un48TgKCfGnIUNi6ccf/Sg+Xu/T1KJF9qJsnjyBE+OXX4p59ephuODTT82v8/77qIFkvN+KggevKlIOHIAAIcK51qwZHr41a0LIM+Nhbexoeu0afEG0FCwIcaKKFO179bVYMZy3BQpg8vVNP4rNw8MjU6IkLc3Un0mdoqMhtNThzBs39JanEiVwP1B9VUJCcAwcFWUXHY2q0hs3wtoaH4971euvQ5BoqyTbggcPHlCJEiXov//+o5baMUdJtilatCjNnDmThgwZYvU6NhUlKSkpNG/ePJo6dSpduXKFAszdTSVZYvv27dS+fXt6/PhxtopHEeEBuno1nMR27ICfQpUqECedOuGGbKvenrWkpMCSExlpOl2/Dh8QcyZ7Itws/fyESFFN4B4eYjL+nJycRMePH6dq1RpQWlqB/4mPjMJ7/fwgNkqXhnBS32unUqUw9JKcjLBIrfg4fRpChgjCpVYt+DLUq4cx8YYNLTsGpqTgIbtggel3Hh7w4VEUiE+VcuWIvv+eqHPn7ItO4/XVqJqNG1HI7dKlOKpWzZ+GDo2lxYv9zK5z9y4ezNnhyhX0lLUF61q1wvDN6NEYXjCmRQuIk969LVvhoqL0Qz6qUCTCg7BmTdMpMBAWl5s34Ut1/376r1pnVWO8vU2FSoECaO/OnbuoZs06VKRIACkKOhnGr2oU2KNHliOyPD1xbqqRR6qPivoaGIjfdSRpabgutm7Ff3rwIPYpNBTn1Suv4P5kL65cuUJVq1alM2fOUG1Hx027KQaDgVavXk2vvfYahYWFUc2aNa1e1yaiZOPGjdS3b19KSEig0qVL0/r16yk0NDS7m5X8P0lJSdS8eXOqXr06LV++3KbbTkiAWXTTJtwQbt2C02NICFHz5riZN23qfI921YIRG2s6qY6H6mQw6FNUEZl+jo9/QmvXrqGXX+5MQUHFqVAhPHgKFqT/vTd+9fc3L9YUBeLJWHyEhwuzvxopUacOzM516sBqYo2DaXg4REV4uOl3fn5Er72Gdi1dKobGiOAI+N57tol+WLhQXzm6aFHh57F6NXKNREbGUWCgXpQcOqR3QAwKQg/dFmzejP3THpe33yb66COiGTPQZmNKlULo6LBhGQ8Rqv/r+fOmk/rQ9/HB8JmxWKlUydSywIwOwb17wklZ9RnSvhrPS0oi+v33lfTccy0oMLA8eXlBXHh5ke69pyfO0yJFLDtYFyqUOYdje/DkCYb19u3DdOgQ5hUoQNSuHYRI5862yTWUEcxM3bt3p0ePHtHevXvt/4NuzpkzZ6hJkyaUlJREBQsWpJUrV1KnTp0yt5HMZFpbvnw5+/r6/m/as2cPMzM/efKEw8PD+eDBgzx48GAOCgrie/fuZT+1Wy7B0nFlZk5JSeHu3btzgwYN7F6jQVGQAfG771AorHx58SgvV465SxdkZly7FhkjrSmM5kzSO64RERFMRBwWFpbhdtLSkC5+716kJf/8cxQLbNsWmW69vcVxKlIEBcBGjkQdkwMHULgusxgMyDBrKRNolSrM8+ahkFqNGvrvXn2V+c6dzP+mJVJTTX//9m3x/YYNmHflCjK6Dh2qP0+N1zUujJYdkpKYZ8zQp3b398exefzYcj2jggWR3TQrmbAVBefDli1IBT90KHPTpvhddfv58qEqbd++qO+yZg32+9GjrNVNIiJet25d5ld0IoqCgo0bN6JcRL9+SP2uZkouUgT3lOnTmffty7hCsT0YPnw4BwYG8k1HFwByU5KTkzk8PJyPHj3K48aN44CAAD537lymtpEpS0l8fDzdu3fvf5/Lli1LPmY816pWrUqDBw+m8ePHZ04h5VIsHdfU1FR6+eWX6dq1a7Rz504qZq+MaOlw4wbMqSdPwvcjLEz0xr29YVYNDkavPzgYFoFy5eBEa+ux38yS3vmq+pScOBFGlSvXp5gYmOBVZ7/r18XQ0Y0b+lDhgABh/g4MxGvlyrCAlCmTvWESNeKkWzfz37drRzRqFHwk3n0X1gKVkBAM7dg68G3AANPIGe1dY+TIDbRgQXeqVKkVXbv2n85SQoRkfh9/bHl9W3DnDhK4aQ2JtWrBj6ZePYRIz51rft3vvoMTbXYtSswYnjK2qpw7p48eKlgQjs7lyuHVeCpVClY5rUUjsz4ljiI11fS6uX4d/jbnzomQ9kKFhKWwQQNYYWvUcK7V5p133qH169fTnj17qKIzcxa4MW3btqXKlSvTokWLrF7HLnlKqlSpQgMGDKDJkyfbetO5BlWQhIeH065du1wqkikqCsMTly+LKTwcNyPt2VS4MMRJuXIw9/v5WZ78/fWffXxgPlcndew8o/dq/o5Hj8Sr9r36eu9eKl2//pi8vALIYNCriBIlhOjQCg97j7lv3w7RYY5Bg4g++ADi5+uv8ZBNSsJ3vr548I8caXtnxHv3TM3omzcjcZmK6gCrRt8YixJm04fP779jyMfW7NuHbJ4XLoh5L76IY+bpCYfYX381v+7330Oc2CPp34MH8IW5edP8pPoZqXh5iTwlAQFEe/aspfbtG9Izz1SkgAAMx/j6Cr8T9b128vYWGWctoSjwm7E0PXxomtAtOhr7oyae02bWLVNGXCu1awsh4ozwf0swM73zzju0bt062r17N1WtWtXZTXJb2rRpQ+XLl6dly5ZZvU62RMnTp0/piy++oG7dulHp0qUpJiaGvvvuO1q+fDkdP348U2FAEkFaWhr17NmTTpw4QRs3bqSSGs/AokWLkrejU6VaSVISkpTduiVe1enxY4ynayfVidCe+PriBq6m/y5YMIXy5IknL69Y+vPPH2nw4JcoODiAgoL8qF69olShguOdfHfvRp4Hc7RpQzR7Nqwwu3Yht8jFi+L7Tp3Q0w8MtE/bypc3rRFjfMdQc5cUKRJHjx750/r1sdS9u94Zu2FDWNm0pKbaPh07ERyMp02DUFMtXPnyIUx4wgSIg/Hjif75x/z6ixYh0sORl1lKCq6ZmzfxwI+OJrp9O5muXo2jx4+9aPPmI1SuXAMyGIpQbGweSkjIvIlB6+itCgRrkgV6euoFUvHi4lUr2CtUsF/2VlsyfPhwWrlyJW3YsEGXm8Tf39+s5V9iHRMmTKCOHTtS+fLlKT4+nlatWkXTp0+nLVu2UDtLvS0zZEuUJCUlUb9+/ejw4cMUHR1NxYoVo9DQUPr444+lo2s2UIcWzLFr1y5q1aqVYxtkJ1JTTYWKOiUk6B34rH1vLEKMHyzLli2jQYMGmbRl0qRJDrfs7dljuc5MtWro3XfujOGyDz7QD02ULEk0bx6iSezVA92/H2Z2LeYK7EVEwLEzJCSOjh/3p9jYWJMIsUePRJbP4sXx4H3vPST4sxfnzsGh9eBBMS8wEBaRjh0h8saORf4ScyxeDCdiZ6RuJyLavXs3tTajVl977TVavHjZ/xxh1cn4c3Ky5frEqnUjXz7TgoXaSU2v72znWFviYeGCWbp0Kb3++uuObYwbMWTIENqxYwdFRUWRv78/1a1bl8aOHZspQUIk08xLJA4nPctI0aJEkycjxbqXFx6M48bpa7sMHYpaMkWK2K+NBoOwYtSvD58iIvSszQ0RnTpFVL58HBUrZl6UEJkXT7Gx9i0apyiIwhk7Vh8m+8orEEQlSiDny4QJ5qObiJwvTiSS3IQb6V+JxLXZvh0PZmNBohZtU8Nb33kHheaaNoU4UQVJcDB694sX21eQEGFIiAgOiqogqVnTss9KvXoZD8UcOCDeq4UC7V2NwtMTQ17nzyMPj8pvv8HRculSJF87dw7ixVwY6rBhsLgtXGg5V45EIrERtgwHkkgkpuzaZd6IXqAAXrt3Z750CcvGxTG/9x6zp6cIc/X0ZB4/3nEhk/fvizb27i3e372b/nqxsQgJTi903dxxuHDBxjtgAUVh/v135pIl8bu+vnht1Yr58mUs8+QJ89SpzIUKWQ7HnjsXIdsSicT2SEuJRGInIiPNW0bUujNVqyKj7vr1sIKsW4dQ30WL4PugKAi53r8fqdUdVRl22DC8duiAxGgq2c3ESgTnU5V16/Bao4btQ4TN4eGBiJ+zZ2EdefoU0SJnzyJC5MsvYbWaOBHp4997z/yQzahRsBj98Yf92yyR5DakKJFIbExCAsRFUJB+fkAAhjjy50el0+PHkRo+NhZVnF96CWnq1aynQ4di6CSzVVCzw5EjRBs24L3WyXXHDttsX5u66O23RfrwGTNss31rCAiA2PrlF/iZeHggd8annyLXy+HDWGbOHKJLl5CnxZw/TJ8+mK8dlpJIJNlDOrpKJDZCUeAQaVwJoFQpRBQpCqJXxo6FrwYRHvaDBkGYNG+OSJH8+Yl++onohRcc337VZ+S77+CLoWLNXUItxmnJ0VXlhReI/v0X769eRe4VIuS/cURqcS2RkRCEe/cStW2L3Btnz0I8ffqpiN46eRIRUDt2wDE3NVUf0p4/P9qf1erLEokESEuJRGIDlizBA10rSNSkcXfvEvXogV731KkQJImJGB5o2xY5IGrXRlKydu1QO8fRgoQIobJE6P1rE8QZhwBnl7VrxftXXiH69lu8r1TJMcM4WgIDUfvpq69Q7Tg1FdWXZ8yAher8eSxXvz7Rtm1Eq1aJqtTaNExJSXA+HjrU8fsgkbgT0lIikWSDa9dET1+lQgVYHW7dQjG6OXP0USbHjhENHIghmk6dUJAsMRHWiVdecWz7VR4+hDgiQrbeunXFd2o14Iyw1lJChFwl0dF4Hx2N4RIiiLvBg7OwAzbg9GkM1Vy8CJ+TkyfxH02bBj8SNVdHbCysKPPnY7itWDGsq2XDBsulAiQSiWWkpUQiyQJpaUitrhUkxYtj3oMHeICtWgUnVVWQpKYSTZmCHriPDxKfbdgAJ9czZ5wnSIjgH0GEoaRTp8T8MWPsk5xNDTMmQlp49TeHDEFmU2dQty4SqY0ahf+udGkcl/ffh0Xrxg0s5++POjpHj6KMgiritPkOu3fHcXPWvkgkORbnBv9IJDmPRYtMw0TbtWOuXh3hu6NHM8fH69e5cIE5NBQVUocPZ27ThtnDg/njj1GF15kcPy72Iz5ev1+ZqWhrTUiwFu3vxMaiiiwRc4MGWauka0v++Ye5WDFUx546FRWz/fyYf/5Z37a0NOaFC5kLF8YUGmp6brRv7/oVtSUSV0GKEonESs6fN33g1KqFh46XF8qyHz6sX8dgQF6L/PmZg4OZZ81iLluWOSCA+d9/nbMfxu1T9+Wvv5h//VV87t8/c9vKrCgJDxe/1acP88OH4vNPP2VhZ2zMjRvMTZsy58nD/MknzAMGoG0vvcT84IF+2Xv3mF97Dd9XrYr1jM+VxYudshsSSY5CihKJJAOePmVu3tz0IdOtG3NQEJKcffEFc0qKfr3bt2ERIWIeMQIPNi8v5hYtmG/dcs6+GDN7NtpXvLheoBBl3oKTWVHCrP+9J0+Yf/hBfL5xI5M7YwdSUpg/+EAkufvxR1hQypZl3rvXdPn//mOuVg3nRI8eEKrG5835847fD4kkpyBFiUSSDuvXmz5UmjZlbtsW71u2ZL540XS9nTuZS5RgLlOG+bffmDt1wvLjxzt/uEbl0SOxT7dv660k7dplfntZESUnTojf7NQJwxxVquBzmzbOH8ZR2bABwzNBQXjfogUE5owZptldExKYP/wQQ3kNG2K4Ts3Oq061a5uKWIlEIkWJRGKWuDg8hLQPkuLFmV9+GWnK/fzgW2L8QFIUPKg8PZmff5550yb4JRQrxrx5s3P2xRyKAsFExDxunKmVJCEh89vMiihh1v/u/fvMBw+KzwsXZr4d9iIiAj4j3t4Ykhs3Dm3s3Jk5Otp0+YMH4Wfk7Y3SAX36mArc335z+G5IJC6NFCUSiRHffWf68Ojdm7ljR7zv0QOWBWMeP8Z3RMwTJjD/8gt8SRo1co2hCC1ffCH2LS0NDpzq5zp1Mret+fPnc40aNTg4ODhLomT3bvHbNWpg3uuvi3nXrmWuPfYkKYl55Ei0a9gwWNKKFoUj7MGDpssnJjJ/9BFE6jPPwGm2RAn9uVWwoOPqGkkkro4UJRLJ/3PvnqkYqV6defJkWDv8/ZmXLzc/pHDqFIYd/P3xoBo/HusPHOh6D5wdO8T+HT+O/dHu86NHWdtuVi0lzPrfv3IFxf88PPC5dWvXK4C3ZAlz3rwYxjl+nLlJEzjEzp5t/vw4dEhYTd5/n7lXL9Nzbe1ax++HROJqSFEikTB8AIwfEuPGwR9AfTBGRppf9+efmX18mOvXZw4LY+7aFQ/UmTNdxydC5cYNsX8jR2Le0qX6Iaqskh1RsnmzaIOPD+Z9842Y9+23WW+Xvdi3D1aPwEDmY8eYx4wRlrSHD02XT0xkHjtWWE2mTEEUlvacK1GCOTnZ4bsikbgMUpRIcjWXLpmKkWbNmFeuZK5ZEw6Ks2eb76knJTG/+SbWGTSI+exZhAj7+cGXxNVISmJu3BjtzZcPfjPGVhJzw1LWkh1Rwqxvx5EjOOYvvCDmhYdnvW32IjISYtTXl3ndOuEQW6kSzgdzHD6MYar8+Zk/+4y5Z0/Tc/Dvvx27HxKJqyAzukpyJcyocVKtmpjn4UE0eTJRx44orJc3L1LCjx4tUoyrREaigN6yZUQ//oi08S1bEiUnI218p06O3BvrGD0aFXCJiFasQA2e+fPF997eRGXKOKdtRERbtoj3jRrh//j1V1Hk7tVXkfLelahQgWjfPpwzL76I7K7Hj6M+TpMmRBs3mq7TqBGWGTQI6eoNBpQYUNP8ExF17YoMsampjtsXicQlcLYqkkgcjTnrSMWKzCtWwEri4YGhm6Qk8+tv2QLnxqAg+BMsWoTw0HbtzJvtXYFly8S+du4MC8mTJ/pjkN3cKdm1lDCbtxbs2yfmzZ6dvTbaC4MBvkdEiLJ58AB5TTw8mKdPtzyMt24dzqWyZZl//535xRdNz82tWx27LxKJM5GiRJJrUBRETBjf9AcORNKuQoUgNPbssbyNb7+FT0CnTswxMcyffir8M1wl/4gxYWEYKlD9NSIiMH/IEHEMypXL/u/YQpRs26b/b9RhsxkzxDxzeWFchdWrcaxbtsT5MXEi2jxggGWH55s3mVu1goCZMAE+SkWK6I9DzZoyVb0kdyBFiSRXcOeOqRgpVAhRFG+/jc+vvIIaLOYwGBA1QQSHxuRk5qFD8XnGDNdzaFV5+BBWIHWfZ8zA/GvXbBNxo8UWooRZ3y41NbvBgLwvRLAquPIDet8+iIo6deCjs3IlhErjxjgPzZGWhjBtLy/mZ59lPnBA70+jTrt3O3ZfJBJHI0WJxO3Rpi4nQo+0SRP0yhs0gNPnwoWWhUVCApwRPT1hKXn6FCnmvbzQq3VVDAaRSZYIWWjVh/kzz4j5jRrZ5vdsJUq0IctEwsIQHS3mTZ1qgwbbkXPnYH0KDIRl58gRJKsrWxaROpY4eBAi0s8Pw4nTp+M80x6PZ55xbVEmkWQHKUokbktamshaqk6enhhyWbUKN/4qVZDq3BL370PA+PggsiImBmnmCxRwrQyt5lB9HIiYK1QQReSMH/pZyd5qDluJEmZ9+yZPFvO12V7Pncv2z9iVGzcw7FKsGPKU3L4NAejjw7xmjeX1Hj+G1Y4IQ2w7dkDgGFtNTp1y3L5IJI5CihKJW3LqlP4G7uWFB/OOHczvvot5vXrhAWCJy5chWkqUQE83MhKhnAEBptWAXY1Nm0TyMW9vtJ8Zfi/a4/Lii7b7TVuKkv37LQ8vabPRuqofj4qxiE1IYO7bF//Nd99ZXk9RUCk5f35YRk6cYO7SxVSYfPaZ4/ZFInEEUpRI3I5PPjG9efftC4fP0FBk4vz22/T9QPbvRw+3WjX4X5w7B6tLxYoQK67M1av6uj0//CC+mztXf1xs+VC3pShh1rezf38xX1GYS5fG/KFDbfJTduXpUyTUy5MHw30GA2rhEMFql955eOIEnK+LFUMUzqxZ2I7quEwEi58czpG4C1KUSNyG1FRYBbQPs4IF8SD46y9R5fXo0fS3s3o1/EzUCIozZ5DptG5d5qgox+xLVklIQDIvdf+HDBHfaX0yiJhHjLDtb9talFy+rG/vlSviu4cPxfyM/k9XIDVVRDt9/z2EyPTp+PzGG+mLiuho5vbtMfQ4bRqGsAIDYX3RHh9XF8sSiTVIUSJxC86d09+gvb3xcL58GU6RRMgbkV4eEUVh/vprmNb79UOeklOnMFxTv775SrCuhKIwv/aaOAYhIfow1H799MfI1hFDthYlzMjhobbX11ff5r17xXc5ITW7ooihw++/x7ylSzG0+OKL6ddISksT4cUvvoihRHM5Tb75xiG7IpHYDSlKJDmeL780vTm//DIcO9Vy8ZMmpV/UTVFE7ZIJE7DsyZMwmzdoAIuJq7Nwodj/okVFPhJm7Iv2+Hz5pe1/3x6i5NEjfbv/+EP/vVpNOLOVjZ2FOWGycSOcX1u0yDg0e/16DNdUqwYhPm+eqXWwUiXXK2AokViLFCWSHEtamj7JVLlysHJ8+SV6kg0bwsS9enX621EU5lGjsA218FtYGB7sISE5Q5AcOgRfGSIcg3//Fd8pCnOpUvoHlz2whyhhRvi1tu1PnojvtLV7jAWLq2JOmBw4gPNNzW2SHpcuIaqnYEGc28eOQYj4+OiPk6UCkhKJKyNFiSRHYpwqvkoVJEP7+284qZYsiWibsLD0t6MozO+8o39AHD8OsRMa6rpp47Xcv68PGTXO4fHHH/pj9c8/9mmHvURJWpq+/Vo/GWZYxHLag9icMDl/Hv9j1aoZp/yPj4c1kAjVhqOjUck6Tx79sfrtN/vvi0RWKrWLAAAgAElEQVRiS6QokeQ4tCXta9SAgKhaFTf1pUthzm7enPnevfS3YzAwDx+O7SxahHknTsAhtlEj22Q5tTepqSLTKRGiPLSm+6dPTYe2bM38+fO5Ro0aHBwcbBdRwiycQtXJOEfJX3+J79LzzXAlzAmTq1chpq0RJorC/PnnWH/gQFiQ3noLn6tXF8fDlmHfEom9kaJEkqNo00bcbHv1QkRChw7oLY8eLcJEM3J8NBiY33wTQx0//oh54eHISRIamn7+Eldi7Fi9tchYSE2Y4LgIDXtZSlS0++HnZ+qoO2iQcHJ21bT/xmiFyZIlmKcKkypVrCuSuHKliBaLjmZesADOsw0b6o9ZThFrktyNFCWSHIFx0q+ePfH64Yd4EL/wAm7EGeUfYYYgGTYMguSnnzDvzh3kIKlWTWQ+dXXWrhXHw8eH+fRp/ffXr+uPWYMG9m2PvUXJli36/fn1V/33iiISxr3+ul2aYBcUBQLZywtOr8zIjaMKk5s3M97Gvn2IEqtaFcJz2zZY/IKD9cfszBn77otEkl2kKJG4PPfu6W+soaFIHrV8OfKGNGyInvO2bRlvy2CAT4KHB/OyZZj3+DFzvXqoS3L9un33xVZcvAgfGvWYrFhhusxzz+mPW1KSfdtkb1HCbDoUZWzRio1N/5i4KmlpCFn38YHTMnPmhcmVKxDVRYui0vXly/hcuLD+XJg/3667IpFkCylKJC7NoUPiZlqnDjJ5li2LhFmXL8O6Ubq0dXVA0tLQg/b0FL3sxETcsAsXzjm9yPh4RF+ox+Xdd02X2bVL//BWqwPbE0eIkitX9PtlziISFia+P37cbk2xOQkJSElfrBgcuZkzL0wePmRu1QpDWL/+Citihw6wwgwYII5Ljx723ReJJKtIUSJxWbR5N9q2xY22aVNYRw4fhrm6enXrrBsGAxKLeXqKHnRaGpwA8+eH+TsnoCgi9woRc7Nmpv4zxkNd9goBNsYRooQZ2Uy1+2auoKI2nX5GIbauREwMnLeDgkT2YFWYBAdbN7SYnCzyt0yejPNBDXnXnjteXjKficT1kKJE4pL07Stunr1743XwYAxBbNyI/CNNm1qXZVVR4ATr4QGnQHXe22/jxvzXX/bdF1syZ444LqVKmX/gzp6tf2g7Kg27o0RJfLx+/woXNn24KoqISvLzQxRSTiEyEnWW6tfHcBQzLEQlSiAqTJunxRKKIgoXvv02js8PPyBkuFUr/fGzZnsSiaOQokTiUiiKvqaHWsJ9yhR8t2QJhET37jB3W4MaTrpggZj33XeYpy1W5+rs2YN9V3u5e/aYLnPxov6BU6KE49rnKFHCjAgr7X6a+x+14qVr15wTkcMMp2V/f+Z27UTRxGPHkDCtUyfmlBTrtvPjj7AO9uuHdXbvxnZDQuCbpR6fnJLfReL+SFEicRkSEvQPmh49cENdvFifk+Gtt6yvivrTT1jn00/FvP/+Q49x5Ej77Ic9uH0bCeHUYzNnjukyaWnwt9Eew7g4x7XRkaJEm8lVne7fN13uzBnx/eTJdm+WTdm5E+Lzww/FvK1bkbn3tdesF1mrV2OdLl1wjYWF4VyqVg3WR/X47N9vl92QSDKFFCUSl+D2bXFzfOYZ1AHx8cHQijbr6uefW38z/vtv3NTffFOsExmJir+tWlnf23Q2yckYqlKPT58+5o/BtGn6h/R77zm2nY4UJcwQl9r97dDB/HKqMCViXrXKIU2zGepQnDaF/ooVmDd+vPXb2bIF19Nzz2FIKDwcfivlyomClURIPiiROBMpSiRO5+hRcVMcOJC5Vi2ENR48KJKcEcHx1VrCwlBV9sUXhVXl6VOEDwcG5pxcJMwiuRYRjk18vOkyp0+bWg4cPVzhaFHCDAdQ7T5bEh3a6smHDzusedlGUeBf5eurjw6bNQv7Mm+e9dvatw9DN888g/P/1i2cTwEBsEY6S8xKJFqkKJE4lVWrxM1wyhQ8ZAIDmS9cgJgYPFif5Mwa7txBDzAkRDjxKQr8U3x8Mq6H40qovWIi5CVRQ0W1pKSYDtts3er4tjpDlCQmmooxNWpFy5MnzJUrC8dXa8JrXYUnTxAOX7WqPmPvBx/g2li3zvpthYXBz6hGDYiSmBjmxo3hq/Lbb+IYNmqUs3xwJO6DFCUSp/HVV+Im+NNPyDcSHIwHRloarCbanCLW8PQpeoJly+ojU9QQ0Zxkvj99Wu/0a+nhM2mSc0KAjXGGKGHW9/KJMERh7oF67pxYpkGDnBV1cuUKooy6dBGRRgYDMhsXLIi6T9Zy6RJz+fIQ/1euwPLWrh1S1Ws7CfnySWEicTxSlEicgnZIYv16+HnUrs189y6iDfr2hT9IZqqcKgrq4RQooE+adfIkcpyMGmX7/bAXjx8jYZZ6jCz5Dxw7ZipIMipEaC+cJUqYTY+Bmq3XmF9+Ecu89FLOytOxeTMsI19+KebFx2MIJjg4c/WabtzAOuXLM0dEINS+d290An76CdeLepxy0jGS5HykKJE4nO7dxQ1v82b0AENCkHMkJQXCIk8eRA1khpkzsc21a8W8p0+RYK1ePfunWbcVBoP+GLVtaz7aKDER+Sy0D+N+/RzfXhVnipK7d02FyY0b5pcdMkQsM3GiY9uZXcaPRyTNyZNiXni4qRXFGm7dwpBWxYo4VmlpzG+8geMyaxaGQNXjZG20m0SSXaQokTiUZs3Eje7ff+En0bQpenlJSXgY580L60lmUHN4fPSRfv4bb8CPJDPmbWfz5ZfiGJUvbz7UlRn76mznVi3OFCXMzCNG6I9Fkybmj0dCAnw01OUWL3Z8W7NKUhJz3bpov1Zkq1YUbei7NURGIgqnShUMdyoKhI8a6Va/vjhOOSVaTZKzkaJE4hAURV+vZft2DLM8/zxM0KmpiJTx9haVUq3l7l34o7RsKRJNMTNv2oTfWrTItvtiT7ZuhQmdCMfiyBHzy+3fbypIdu1yaFNNcLYoMZe75PvvzS978SIiWjJazhU5eRLCfdw4/Xw1g2tmHF+Zkca+XDlYFO/exTw1J9DXXzO3aSOOk7UJCyWSrCJFicTuKIreFLxnDx4IbdrgJqcoiLLJSsr3tDTm1q2RDOrOHTE/Nha/2aFDznHWu34dxdjU42Qp2+yTJxBh2odv0aKObauW+fPnc40aNTg4ONipooQZdXCMhcnVq+aXXbkS3/v44HXuXMe2NTt88QXE64EDYp6iwPG1UCE4sGaGy5dxTtWuLcLlJ0zAcVmwAEOq6vE0F5IukdgKKUokdkVR9OGqBw8iJLNlS1GPRB2G+OWXzG9/4kTcnI2tBG+/DeFjTbE+V+DGDWTYVI/T4MGWxZSaSE47uUIkibMtJSrPPqs/Ng0bWva1eOstRJm0bYtlv/rKsW3NKqmp2M+qVfX/fVwcc6VKGLrSWg2t4cIFhAvXr49QYUVBzhIiJFVT/U2IUI1YIrEHUpRI7Iai6B0xjx2DQ16TJiL9+YwZ+O6bbzK//b17MY7+xRf6+Wqmz2+/zf4+OAI1RLNQIbQ7JAROrObYscNUkPz8s2PbawlXESUpKabHaPZs88smJiKEvEQJWBlUX4qcwKVLqHBt7Ky7bx+EuvF1YQ1nzsBaFxICa6OiIHmhpyci4bR+TFKYSOyBFCUSu2AsSE6dws0uNFSELv74I777+OPMb19NhtW0qT4yIC0NjoDPPpszQhlPnEA4dLVqcF4sWhQhmuaIjdXXvyFClJKr4CqihJl5zRpTYXLhgvllHzzAsS9VCrlx1HMyJwz7TZwIS4+xRXDCBJwbx45lfpthYcj82rYtShwYDDguXl7wV5k4URzTmBjb7IdEoiJFicQuaIdsLl4UZmG1d/Xnn+h9vfVW1m7+I0bAF+DyZf38RYvwmzkhlfjevRjKCglBKK+HByKSLGFcGZdIDIG5Aq4kSpiFw7A61a6Nh6w57t2DI3bZsmKY4sMPXV+YxMdDTPXtq5+fnIxhq+rVs+acumsXHK1ffRXHIDUVeUzy5mX+5x8RoUPk2KKPEvdHihKJzaleXdywbt9GyGGNGsKBbudO3PBefjlr+Q+2bTM/PPP4MawOAwdmfx/szebNokDaoEEZR4CokUTaacUKhzXXKlxNlDx8aHrMhg+3vHxUlEgoNmoUlh81yvWFiVpw0LjK7/nzGN55552sbVd1BFYtmcnJzF27Yps7dzK//744rjklB5DE9ZGiRGJT2rUTN6pHj5C0rGxZkcjq6FGkxW7f3nKvNT1iY/HQaN3adHhmwgSEGd+6lf39sCerVsG03rUr87BhGQuSmBjTh6uvr+Paay2uJkqYRZisdkovL4maUCwoSFgD3nrLtYcCDQakzW/UyLSd8+ZhH/bty9q21VIQalh9YiKucV9fiKABA8RxlQnWJLZAihKJzVCr+arRIK1awbH17Fl8HxmJYZzGjbMeVjhmDISHsd9FTAwcRT/8MFu7YHcWLcIwTf/+iBAiSr/6cXKyiCbRDke40rCNiiuKEmZTUUKkD6U15sYNZDmtVIn5s8/wfw0e7NoPXdW52zgLssEAP6769bPWfkXBUKmXl8gf9PQpouf8/VFPSNsRcXWrksT1kaJEYhO0PdL4eOQ1yJ8ffhPMuJE1aIAiYJYylGbEhQuwMEydavrdpEkYDlGTP7ki06fj+IwYIbKPppfYLS0N4/jGD9TM1ANyJK4qSqKjxbHz98dr8eL6go3GRESgYnXVqrAWeHpCSGY2zNaRtGqFyDZjDh3K2BqXHmlpyLRcoAAsncywWNaqBfF2/z7eq8JZIskOUpRIss2yZXpv/BEjcHNSU8UrCnOfPripaWt2ZAZFQSK0ihVNw2Xj4vCwGT06e/thLxQF2TfV8fmRIzMWJIqid2ytXRuvxYo5rt2ZxVVFCbOoi6SdGjdO3xfi6lWR6XTePFgLevd23XTrGzZgvw4eNP1u0CBEdkVHZ23bT5/CYleihLBSRkTgc/PmOI5qhtyGDbO6BxKJFCWSbLJli7jJR0Yi34jxA1e1oqxZk/Xf+esvbMNcTZyFCyGCLBVgcyZpaWJYa9Ys6ywkzPp8ENrifJbyl7gCrixKmMUxDA4W79NLUscsMp3WqoUMu3nzMvfo4ZqOnQYDati8/LLpd3fvItLrrbeyvv0HD9ApaNBARPQcOICQ5IED9Wn+X301678jyd1IUSLJMmFh4iZ0+jQiSjw9mT/4QCzz119ZKxSmJSUFN9t27UwfIIqCm2TXrlnfvr1IToaFyNOTeckSIUgspY9XmTZNHNeWLcV7Vw9zdnVREhsrjmVoqHg/f3766124gPwwdesiUZ23N3OnTq6Zbn3+fFh0zGUynjMH12JWrZXMWNfHR4gQZgwnEmFYVZu4ztwwq0SSEVKUSLLE/fvi5rNrFxze/PxQPl11qDt3Ds6nL76YveiFn3/G75i7mR49iu8yW8TP3jx9ytyxIx5ga9YgFNUaQbJwoTiupUszBwTg/ZAhjml3dnB1UcIsLG5E8BlR3+/enf56Z8/CD6VBA0RPFSyIhGvXrjmm3dYSH4/rcPJk0+9SUhBZ1Lt39n5j+XLTkPzJkzHvjz8Qmu+qYesS10eKEkmm0faGFi+GWbdSJfg9qImUYmJwA6xdO3s9yrQ0mNu7dTP//UcfYVzblSIjHj7EOLuvL5KhqYIkvVBUZvQ4PTywrJeXsKyQA67StWvXcvv27blYsWJMRBwWFpbpbeQEUcIsrE+lS4vjXbw4hh/T49Qp+GWEhiIctnJlfN6+3THttpY+fZA63xxq9NfFi9n7jVGj4HSuOrIrCvMrr8C5/fBhWGrUc/fEiez9liR3IUWJJFNox43798cQxXPP4aauOsClpiJFddGiliu0WsuqVfitI0fMf1+9OvwCXIVjx5DjomhRjLerYb8ZCZJNm3CT9/PD8tqMmY5I5f3LL7/wlClTePHixW4vSrTncNeu4n3DhhmHWp84gTD3Z5/F+d6uHQTk3LmuEw7766/YH23VbJWkJIix7F4zKSkQd6VKiSimxERE/5QsCYG3f784tll1sJXkPqQokWSKDh1wkylcGJ9HjIDzn9pjYob/iJcXisdlB4MBJvIOHcx/Hx5u2fnV0SgKhl68vdFLvXJFOLj++GP66+7Zgx5mrVqIUHrpJXEzX7nSMe1XiYiIcHtRwoyHpnqM1XNaFdoZiYujR3H+16iBonhjxmDd1193DUfk6Gj4MVkSwl9/jWs2u47hd++ivlXTpiIR4r17EOV168JqqpZ9IHLtBHQS10GKEonVqHk2iDBcsmKFaf4DtULplCnZ/72dO4XPijnUHuGjR9n/rezw5Iko5DZ8OG7WHTpAmC1Zkv66J07AOvLssyjKV7UqojuIIFIcTWZESVJSEsfGxv5vunnzZo4RJcyoHKyez5UqifezZmW87oULcL4uVgz+KL/8giiUxo1dI6Nws2YQt+aIi2MuUgRDMNnl4EEIHG0q+7NncU736QOBp+baKV48+78ncX+kKJFYxd694qb96BGcWH199T3Lx4/RS2ra1DZJpgYOxEPaUs/1/ffxMHEmFy8KC8eKFQghrVYNPelt2zJet3hx+Cj07ImohvnzxXF2Rj6MzIiSSZMmMRGZTDlFlDCLZGrt2kFUEEFUZ/TfMWNYrXVrDLv9+COGGMuWxdCdcWZVRzNiBKyMlhg7Fu3MSqkHY9RU9v/8I+b98YfeSqie066aS0jiOkhRIskQbUbMU6fguFqjBqqqPnkiluvfHz0kW0QkxMbiIf3FF5aXad8eVgVnoCgQIQULwq/l3Dk8yIoUgSgxrl5szI0bqOFTs6awQKk5XixFGtmK5cuXs6+v7/+mPXv2/O+73GQpYUa+DfWYv/WWeG+tP1RKihimGz0awxe9eolcHY8f238fzPHVV7gWLXHqlO2i1gwGXIulS+t9R4YNwzV8/jzEj3psteJFIjFGihJJumidAhcvFl72vr4wYauoYYLLl9vmd5csQZRAeuPeISEoM+9obt8WCc1eeQUibcECDNe0b5/xcNK9exAuQUEIUc2XD/uhZsR87z37tj8uLo7Dw8P/NyVoatvnFp8SLVqHTG2iujp1rIscUxRYCzw9EQb++DHC2AsVQlkFjeZzGKqDuKVzUVHQsRgwwDa/d/s2hFzPnsKy+fQpfqNuXfjaRESIY+sKQ1wS10SKEkm6NG4szNvMwnFNW3/l2jX0yvr1s93vvvAC8/PPp79MlSqOLcCnKBBL/v6IMFizBj1lNcLm3XczHrZ6/Bi5LkqWhLk/KAjiSlvM0JkOgblRlDCLlP6enhCMXl6YevWyPqrm339xbtSoAUfniAiEhnt4YLjEFkMl1rJ7N/ZH23Ew5rPPYOnTaNJssXo1fnPZMjHv9GmI7hEj8HntWucOT0pcHylKJBb58UdxA1EURBoUKKC3TqSmwqkuMNB2puqUFFgNpk9Pf7lnnnFcUjE1/JOI+bXX4E8QEwPhlCdPxmnjmXHzb9kS/iYnTyLRXJEi+uP84IG998Q8MTExHBYWxps2bWIi4lWrVnFYWBhHRUVZvY2cLEq0FsEuXTDsULQoPqc3hGiMsQNsWhoy9ObNC7Gydav99kGL6tORXjj55ctYZt062/3uq6/CQqSt4r1ggf53Bg/GZ29v2/2uxH2QokRilmvX9HkyUlKYGzXCDVdr0v78c/QutSHB2UU1p2eUVn3AAAgie5KUhCgNX19kAFXHw8+f1z98MiIlhblzZ4i6AweYv/wS+6hmqyVCjhNnsXTpUrNOq5MmTbJ6GzlZlDDDP8rYvyQoCJaOzPheaMWq6uh58iRzixZiiCi7+XsyYtYsnGsZWXlKlUKRSFvx+DE6KC1aiISGigLfryJFxHCsepwzI/gkuQMpSiQmpKWJm8bmzZg3eTLM2YcOieXCw2GaHTvWtr8/dSp6WxkNhUydit6sPZJWpaXBDB0YCNE1fLjIVvvPPxiuqlnTuoeLwQDfk7x50VPevh3bnDhRHOfZs22/D44mp4sSZuEASoRQ1vz5EVHj55e5LKgpKULYjB6N80lR4OtRrhysBBMm2K9+ztChGIbKiHbtIJJsyZ49EHJz54p5MTHY75YtcSwSE8Vx1lpVJBIpSiQmqGm41SJ3hw5BkGiL6ikK/D4CAzPOgplZ+vRhbtUq4+XUPCYbNtjutxUFZuaaNbHtnj1hFWGGuJg5E4Kic2dECFmzvbffxjpr1sDBr3hxZLxt3hy/ERJiu/Y7E3cQJcz4j9UHZuPGGMrJlw9RVpnZNUVBfRitAywzLDKffIJtlimDZbRRbNklJgZWkk8+yXjZMWNQ+dfWvPUWhJw2q+yePTgWal0e9fpVh4clEmYpSiRGrFunv1E8fYpcIaGhesc01WHNHtlUmzWzrvS5ojC3aYMeYXad5lJSsE+qY2/btvrU9pcuCRHx4YfW19qZMAHrLFmC32jaFD1GbSVgd8l06S6ihFkkU2vbFsN06n/VtWvm/y/VAbZcOf0wUEQEnMO9vGDx+/hjJN7LLpMnw8Jz717Gyy5bhv1SrYC2IiYGxST799fPnzQJwkT1o+7UCb/fsaNtf1+Sc5GiRPI/4uLEzVf1bxw3Dj06ren6yRPk2Ojc2T49nMBAPMytISwMpuLXX89aFMGlSxAZJUpgv5s00SfOSktDzzl/fhRgs8Z/REXtcX/9NT6/9x78DNRMtBk5IuY03EmUGAziP/rmG1i31M9ai6G1RESIdPZ9++oFQ0QEsqv6+uJaGzYMqeyzcm398AOuB2uj0o4ds85/Kyv89BO2rc3InJICK+Szz+IYax2Md+60fRskOQ8pSiT/Q705/PADPp8+jYfoZ5/plxs7Fg9peznr5c+PB4G1LFuGderWhRNpej3Z5GQMR82aJYapihRBOO+pU/plz52D5cTDA4IiMyZ2NaJm4kR8VqMhZs0SxzkzAicn4E6ihBm5N9T/atMmDImon//8M/PbUxQI0mLFYBn5+We98Hj4EA7QpUrhN8qVQyjttm0ZWwIvXGAeORLrjRhhvTXnxAn7OVkbDLAM1qypb/9//4m8R8z6OkRJSbZvhyRnIUWJhJlRv4YIIoQZN5Rnn0UYoza/wvnzWMYWtW0sERCQea/8U6cwjEOEm36fPhhTHzcO6ehHjMDwS/78WCZ/fjj5rVxpWkQtNRUPB29vbHP//sy1ZfVq4RyrKLAyFSzI/PLL4uY7ZkzmtpkTcDdRwizEJBES3Xl44H3BgqjxkhXu38ewDRGS7RlnQE5JgdXg3XdhNSSCIKpbF/VsPvqIecYMvA4ahAc/Ea6b6dMzZ2FR/TquXMnavmTEyZO4Fr76Sj//1VchzNQQeHU408fHPu2Q5BykKJFwbKy48arOeGpuAW2or6Kg1kflyvathhocnLWHdkoKnOk+/hjhy+XKwTegWjVk5+zVi3nOHJiqLSWyOnUKJew9PWERyux+/vsvomz69YOwu3MHPjnVqyOEWRVE7og7ihJm+JEQwYKxcKG4VipVYr55M+vb3bQJw6AFCiD6ypyfkqJgiHLWLDhMt2sHx1Q/P/x+48YIt125MmtWhj//tH9+nFGjsI/aLK737iFfjzbPkHpcf/nFfm2RuD5SlEj+V5Ts22/x+c4d3PSGDdMv9/ff+jBhe9GiBQSEI0lOhoNg3rwosKd1crWW/ftx8+3cGQIpKgqCqFw55u++EzddWxQrdEXcVZQwi/9u2DB9KHfFitkLaY2Lg0XEwwPO5MZDiPZGHWa0Z3bVx49hFRk+XD9ftc7u24fPjx6J42rriD5JzkGKklyO2lMizZkwZAiGQB4+FPMUBTfNFi3sH743eTKEkiPSUKemImV+rVoYlvrkk6z1OE+dQs+vZUs43N69i6GvsmX1oY+2KFboqrizKElNFf/hsmUYflA/lyuXcQHGjDhwAL4XefJA9NjTEqmlSxeUPbA3albbyEgxLy0N95Q6dYRQnz0bxzQ42P5tkrgmUpTkYrQJjNRom1On0GubN0+/7ObNWM6aku7ZRXW+27LFfr+RmAhTfOXKYmw/C+VemBlJ5EqWxLBPbCxM0zVromrqkSPiGNuqWKGr4s6ihBlCU/0v9+0TZQfUoZ1z57K3/aQkYa0LDIR1zZ7iJCIC17rqcGpP4uPh82JcQPPYMbRBmzxQPaZZsVZKcj5SlORiGjTAxT9+vJjXvj18ILRWCkXB2HWTJo5JcqQoSChWp47trSWxsXC6K1UKN8PevbMXeXDrFh4g1arBgfH+febatbF9rSDJDem03V2UMMPHSv1Pw8KY69eHQ3SxYnjoZlXYajl/HmHDHh5IrjZnjn2GMz76CBZJWyZuS4+ZM2EJMrYWjhgBx+Hbt/E5PNzUeivJPci/PZdy5oxpNsV//sFn4wJdW7divlr3xREcP46kUuPG2UYI3b8Ps3jhwuiJDhmCHCXZ4cEDDNFUqICaHg8eIEKiZEnmgwfF8X399ey3PyeQG0QJM1LFq//t6dP4/8uWhZgvXNh2OT8uXkTxRy8v5EmZMoX5+nXbbHvpUjhzazsk9ubpU1wbgwfr5z96JMLyVVQrlCOrgEtcAylKcinqTVUNazQY0MNv2VIvAhQFGVYbNXJ8Kujp04VzYVYsJqmp8Od4+22EGvr6Ijw4OxETKnFxGA8vXhziJjqauV49JGHbs0cc30aNsv9brs78+fO5Ro0aHBwcnCtECTOsF+p/fPw4xEhICM6JQoVwDtiKa9eY33xT5Elp1QqJybKahVV1un7jDcdnE54zByIrPFw/f8oURKWpw8ja5HWOsuRIXAMpSnIhau6FkiXFvNWrMe/gQf2yO3ZgfmaqpNqSpUvFGPvXX+Phb4nUVCSRWrkS6a2LFEHby5bFWH1662aGxESERvv5wf8lJgZDYQEBKLZXuDB+t3Bhy6HH7khusZSojB4tHpy7dmEYp3t3nBsFCtje/yo+HgnXnn8eQzs+PkjP/sUXSEiWXkbj5GRcF7DNZ1IAABqjSURBVE2aoL3vvuucejMJCRDyWqsIM5zqCxXSW0bUFPhVqji2jRLn4sHMTJJcg8FAlCcP3kdHExUrhttqgwZExYsTbdumX75zZ6KoKKLjx4k8PBzfXiKiM2eIvv6a6LffiFJTicqVI6pTh8jfnyglBdOdO0TnzxMlJWGdunWJunfH1LCh7dqelkbUsyeO09atRLVqEbVrR3T9OtHy5USvvkr04AGWvXuXqGRJ2/xuTiAuLo78/f0pNjaW/Pz8nN0ch9CjB9GGDXj/++9EffoQjRpFdPky0c6dRGvX4hqyNTdu4HrYtYvo4EGiuDiivHmJKlfGNV20KFHhwkT37xNdu4bzMzWV6Pnnid55B9eFs67nCROIFizANevrK+ZPnEg0dy5RZCT2gUi08cIFourVHd9WieORoiSXMWEC0bRpuJmuW4d5GzcSde1KtHs30XPPiWWjoiAAvvuO6M03ndJcHVFRuAmfOUN09ixRQgKRtzemgAAIkbp1IVgCAmz/+4pC9PrreBj89RdRkyZE7dsTXb1KtHQp0ZAhEHpEROfOEdWsafs2uDK5UZQQEdWoQXTxIpGfH9GkSURjxhBNnQohv3EjzpeePe33+wYDrod9+3AuPnxIFBND9OgRroNKlSBWWrWCiHY2kZFEFSsSLVpENGyYmP/gAVFQEI7fZ59hXlgYOhVE6DxJ3B8pSnIRyclE+fPjfUICkY8PLvQmTdDL2rNH33uaOZPok0/Q4y9c2DltdhWY0QOePx8PmRdegCAJD8fN9e238SAgIjpxApan3EZuFSXMRJ6eeB8aivPiiy+Ihg/HObFmDdHPPxP17+/cdroS3boR3byJa0V7zxkzhmjJEggXf3/M8/eHJWj7dqI2bZzTXonj8HR2AySOY+RIvI4ZA0FCRPTff0SHD8N0qr05MONG2qOHFCRERFOmEH37LdHChUQdO0KUXL6MeW+9JQTJwYO5U5DkZjw8MKxHRHT0KNGVKxieWLiQKDGRqHdvooED8bCVgOHDiU6exL1Hy5gxGIKdP1/Mu3ABr23bOq59EifiTIcWieNISjKf5nzAAGRPNHZ6U0ua2zulfE7gm29wLKZPR8RD06bI7/DTT8Kp1R2r/maW3OboakxCgjgXPvgABfwKFECOn9699aUccjsGA3KwjBpl+t3w4cj7Eh8v5lWogOO3Y4fj2ihxDtJSkkt45RW8Tp8uHF1jY2FaHjTI1Olt2TKi0qXhxJmb+flnovfeI/roI6IRI4g6dcL4/fTpRKNHEz1+jOX++UfvjyPJffj4CCfnr7+GxWT3bqKICAxTdOsGJ9OZM53aTJfA05PopZfgCKwo+u8++gj+MMuXi3nHjuFVDt/kApytiiT2R2sl0VpEFi1CAiU1k6JKcjJ6Krk9cdG6dcipMGwYem0tWyJscc4cvKrH1DjZXG4lt1tKVK5eFefGr78iz0i1arim2rbF/MmTnROS60rs2oVjceiQ6XedOyPni5Z8+bD8yZMOaZ7ESUhLSS7giy/w+tFHeovI0qVEHToQlSmjX/7YMfhI9O7tuDa6Gjt2ILyzZ0+iWbMQnXTiBKKXPv6YKD4ey61cCb8biUSlUiXhKzFwIELVDxxAlM6+fXCGnTyZaPz43B1R0qIF0hCsXWv63ZAh8M85c0bMU9/Xr++Y9kmchLNVkcS+KIrotWmTK50/j3mrV5uuM306alFofU9yE4cOIfvrCy8gBfbzz+PzpElIWKUezyVLnN1S10JaSvRs2CDOlR07kHTv5ZeR+KxiRcx/5x3HZ1V1JYYMQakGY5KTkWTtvff089XjGRHhkOZJnIC0lLg5ajK0unVFxA0RrCRFi8ICYMzevQgTVn1PchNnz8JvpH59jGn37k106BD8SaZPRzQFEaJuBg92blslrk23bkSLF+N9mzawQP72G9EHH8DPxMdHRG8Z+1XkFp57DtE1Dx/q53t7I4R61Sr9sdm/H6+hoY5ro8SxSFHi5nTogFc16yQRMjv+8gvRgAFE+fLpl1cUXPgtWjiuja7CtWvIMVG+PByA+/XDsRg6lGjOHOR5ISKaMUOEV0sk6TF0KJyliXBNHTlC9NVXCHlVz6fFi5GUTw0rzk00bYrXQ4dMv3vpJeRIOnLEdPnoaGRylrgfUpS4Mbdvi/dBQeL94cNE9+6ZT+Z09iwiSnKbKImKQqRRwYLI1jpoEJLJ9e+PnBOpqVju00/hmyORWMurrxKtXo33TZrgITtiBDIqq9bLX39FhFxue9BWqkRUogR8boxp2hQ+J+vX6+er2V5nz7Z/+ySOR4oSN0ZNDf/nn/r5e/cSFSpEFBJius7evcju2qiR/dvnKjx8CAtJcjLSgr/9NkI5e/ZEwiuDAcuNGQMHRYkks/TqBbFLRNS4MZw4u3XDeVa8OOavWYNU8LduOauVjsfDA0LNnKXEywvHSC2HoaJ2CsaPt3/7JI5HihI3ZtMmvBpHh+zbh16Il5fpOhcvEgUHExUoYP/2uQKPH6Ng2t27OF5jxiDyplMnohUrIN6IIFRmznReETNJzqdrV6ItW/C+USNYTBo1wgM5OBjz1YzAW7c6r52Opnp1DJ2ao2NHZE7WCjXtkPOjR/Ztm8TxSFHippw7h9datfQPUoMBfhLNm5tfLzoa5tTcwP79RPXqQYitWYNQ361biVq3hnUpMJDoyROi116DD4AUJJLs0qEDargQwWJy4ACGMA4cIGrWDPOjo1HGYMoUYaVzZypUgOgw5+yr3qdUB1eV33/H67vv2rdtEscjRYmbojpifvedfv7Zs8jkmp4oUc3J7kpaGm74LVvihrhuHTJt7t5N9Oyz6M2WLo3S6r16Ef34oyi4JjFlwYIFVLNmTQqVIRFW0aYN0c6deN+sGXyXihWDWFFzAwUE4Bzt1ElUnnZXKlSAz9a9e6bflSwJK9Levfr56nHSZn2VuAfyVuum7N6NV2PxsW9f+j4jDx7ghuiu3LgBS8hnn8FpdeJEePknJqIXu2cPlouKgoVk+fLcGRqdGUaMGEHnz5+no0ePOrspOYbWrYUwee45hO7nz48Q2A8+wHVYpw7R8eMYzjl40LnttSflyuH15k3z3zdrZuoI6+Eh1ouMtF/bJI5HihI3RL1IixQx7eHv3QsHV0s+I+5sKVmzBsM1N26gOnLBgvAnCQ2Fg6GaWdLTE579P/wAASeR2IPWreG/RARH67//xrk3cybyl5w5AytBiRKw6s2d654ZYNVrzNJQVZ06GGI1Ht5ZtAivEyfar20SxyNFiRuycCFezYXMnT9P1LCh5XUfPyby97dPu5zF06dEw4bB5Nu2LXqdCxeiRzpmDFGVKhiiIYJj619/odie9CGR2JvnnxdOrd26EX3/Pd6PHIlhxZMn4ZDevz8KQ778MlFcnPPaaw9UsWHO8Z6IqFo1WDKNo5LatsXrihX2a5vE8UhR4oZMn45Xc7VrHj5Mf3jG319UvnUHTp4keuYZ1KhZvFjUsfnzT9zMHj8WfjdBQTATd+7s1CZLchnt2onhieHDIT6IiLp3J9q1i+j6dXw/cyYEzDPPoA6Tu6BaSCz5bVWrhtdLl/Tzvb3F+9yYeM5dkaLEzdCaOH19Tb9/9AjDOpYoWdK8w1lOg5nom28Q4ZA/P8bmg4NxQ4+JwTDWli0iDXjz5gjRrF3bue2W5E6aNMGwIhGGaZ57Du8bNxb+JF99BUtKwYLwCfvgA1gBczqq5cfSkHLJkng15/CrpjtQCyBKcj5SlLgZERF4rVfP9LvkZKKEBNS8sUSpUjlflNy/T9SlC4Zghg9HHogdOxD1ULs2bvIzZiCLJhFSfG/f7r6+NJKcQfnyQmTs2QMHa0UhqlwZlpKqVZG2fsIEVP5esAAh/2ruk5zKxYuwklSubP57dVjHXMjwuHF4nTXLPm2TOB4pStwMNTNinz6m36mJhtKzlAQG4iaRE2GGM2vdusiYuWkThrJGjMAY/YgRcCbUpv3+6iuin34yrQEkkTiDAgXw8PX1xbCGlxeESkAAhHPnzvAr8fVFeH/Vqkgw1q9fzu1MXLgAQWLpGlRFiTlHWNU/zjjrqyTnIkWJm6FGkLRpY/qdNaKkdWuIEkvhea7K4cOo19O7N6JpTp9GUqoWLRDWu2wZ0bRpyEOiJq/asIHoww+lQ6vEtfDwQNI+1ZGzYEFRVfj332EBfOcdOGtv2YLimtu2EdWoAYGd0yJ0TpwgqlnT8veqr4k5S4mMjnM/pChxM9QeQ/Xqpt8lJuI1f37L67dti5vitm22b5s9uH6dqG9fiI34eLR7/Xo4sdavj0Rxe/ciCVqJEuhdEhGdOoVoB4nEVdm2DX4jRBDYa9bgAT1rFvxOZs1CEb9evWBt6NaNaMgQRPRcvuzctltLVBSuzy5dLC+TnqVES27IfpsbkKLETfHzM50XGIjX69ctr1e0KJzoVIuLqxIbSzR2LMTXnj0onHfiBLJDtmwJC8iIEYi+qVYNvc0nT7Du3bsY4pFIXJ2ZM2HRI4IVcOBAvH/3XUSQbdyIIYzLl2EN3L4dVs66dYk+/xw+ZK7M6tXwnXnpJcvLqJZMc5YSIoT0E+G6luR8pCjJRRQrhqGb8PD0lxsxgmjzZvhluBqpqXDwq1IF9WjGjcMN+fXXkXCqXj04uu7Zg55kYqLIu1KlCj6r3vwSSU6gWzei27fxfvlyPKRTUxF5cuwYzu/mzYlGjUK0zpkzRO+/j6zFFSsSff21a0bppKZiCOqFF9J3vn/4EK/mogmJRNZqKUrcAylKchlVq2YsSvr1w/j0J584pk3WwAwn1Tp1MJ7etSvEyOTJuBm1aoWx9jffxNBM8+YIsSxWDOv37Inl0xu6kkhclTJlMDyhns/e3kRXrsAXY/9+CPDFi3F97NtH9OWXyOvRrRvR+PHIwTN9OoY4XYUFC9DGzz5Lfzk1h8uzz5r/Xh2qVkOqJTkbKUrciOTkjJepWjXj8WYvL5h+//2XaOlS27QtOxw9Csfdbt1Q7+LECTj0lS4Na0m9euhJ7t6N3CQFCmAZdbhqyhSMx0uHVklOxtMTuTo+/BCfq1Yl+vlnXK+jR8NfqlIlpKwfMgRW0cWLIV569UKtp6AghBPHxjp1V+jmTaJJk4jeeAO+X+mxfz9SFVSsaP77UqXwGhVl2zZKnARL3IYHD5iJmPPksbzM5MnMAQHMBkP621IU5jfewLZ27rRtO63hwQPmb75hrlcP+1SjBvPGjWgXM/O1a8ytWuG7ESOY4+PFuuvXYz4R82+/Ob7tuZXY2FgmIo6NjXV2U9yeHTvEOd6xo7ieFYX5hx+Y/fyYS5ViXrdOrHPjBvPIkcz58jEXLox7waNHjm97TAxzzZrMgYHM0dEZL9+yJXPPnpa/X7kSx+Gbb2zWRIkTkaLEjXj6VNyoLHHwIL7fuDHj7aWkMLdrhxvYv//arp2WSE1l/usv5pdeYs6bF9NLLzH//Te+Y8Y+TpvG7OuLm9qOHWJ9RWHu1Ekcg3377N9miUCKEsdy964414mY798X3928ydylC+b37s0cFSW+u32b+b33mPPnh3gZMoR561ZxjdmTW7eYGzViLlaM+eLFjJdPTkY7Z82yvMyqVdjPOXNs106J85CixI1QlIxFiaIwh4ZCbFjD48fMHTpgmx9+iJuErTl3jvmDD5hLlsTv1KuHXs+DB2KZlBTmhQuZS5eG9eadd5jj4sT3ly7pb9A3bti+nZL0kaLE8SQnMwcHi/N+6VLxnaLAihAQABH/ySe4nlWiopg//pi5cmWsGxDA/OabsIympdm2nYqCDkdAAHPZssxHj1q33oYNaNuRI5aX+fVXLDNvnm3aKnEuUpS4GRmJEmbm5cuxzNmz1m3TYGD++mtYLipVYp49O3tmX0WBiPjuO/SaiNBzevdd5rAw09/+/XfmqlWxXL9+zFeuiO9TUpgHDRL73ayZGOKROIb58+dzjRo1ODg4WIoSJ7FihbgGSpTAdaESE4MORf78zEWL4lpOSBDfKwrzsWPMH30E6yMROggjRjD/91/2BEpUFPP06UI4vfCC3qKTHikpzNWqMbdunf41PWoUtu0Ia67E/khR4mZYI0qSk2FxeOONzG371CmIgrx50fPq2xcm0/379Tc5FUXBDfHMGebNm5mnTmXu3BkChIjZywuf16xhTkoyXffff5kbNsSynTqZChZ1KEqdtmzJ3P5IbIu0lDiX2Fj99aAd2mTG0Mkbb+C6K1uWefFi0yEbRWE+dIj5/feZy5XDdvLnZ65bl7lPH/ihrFqFe0FiolgvKQkC5Nw5DJuuWsXcvTt+K18+3Dd27Mhch2HuXGYPD+aTJ9NfrlYttFPbWZHkXKQocTPUG9LDh+kvN20abhhZeZDfuYObU9OmuGGpv6n2xMqVQ48rXz79TdLPj7l9e+ZJk/C7lqwtR44wP/881mnSBL01LU+eYDvqdlu3hq+JxLlIUeIafPyx3mpifG1cvowOBREsGH/8Yd7x3WBgPnAAQ6lvvgmH0xIlxLY9PWFR8fHRX+fq1KAB8/z5Gd+LzBEdzVykCPOwYRkvq/6ePYaWJY7HgzmnVUqQpEf//kQrV6ImRocOlpdLS0Pypf/+Q5rnjMLyLJGailDE06eRAyEhAVNqKpKUlSkjpgoVRB0LY5gR+vvVV8gmW6sWci107aoP5f37b316+L17RfIkiXOJi4sjf39/io2NJT9zKYUlDuPmTVxvKvPmIb+PlrAwookTif75B1lhP/gAmVUzKk758CHS2l+8iFB8f3+EHxcpgiRoRYogn0pWkxSmphINGIB2hYdnvB31/iCfZG6Cs1WRxLasW4dew8CBGS8bH88cEoKhnMhI+7fNHPfuwbNeNcEGBTEvW2Y6jn3/PsII1V5Rnz5687HE+UhLieuxcKHeemHuOv/vPxFeX6wYhm6siYyxB7GxcMLPmxe+ZBmhOriXKWP/tkkcgxQlbkZCgnV+JSpRURACwcGOC6FNTUVI8osvIpLG25v55ZcxpGMsRhQFY9/aG+uxY45ppyRzSFHimiQlMVesKK6f3r3ND9dcuABBovp8PfccHGgdJf5v3ULknb+/9bmRhg1DW3/5xb5tkzgOOXzjhvj4ECUloRhdvXoZL3/5MlLLHz+O4Z8ZM4jKlrV9uy5fRobYn39G9sV69ZB5sl8/kT5by9WrotgWEWryzJ6NFNsS10MO37g2Bw8SNW0qPm/dStSunelySUmoNv7DD8iSXLQo0WuvIStsaChR3ry2bVdKCgrzjRuHoZjNm4lq17ZuXXXoJj4eRTclOR8pStyQEyeIQkIwNpyUZN06igLBMH48fELGjUNV0uDgrKVnT0sjOn+e6PBhoiNH8HrmDFHhwhA+gwcTNWhgfttpafAb+ecffPbwgM+KtTcqiXOQosT1YSYaNAgdAyKigAD4hpjrFBChNs2PP6ICcXQ0iuI1b07UujWmhg1R5Tcr3LlDtGgRpnv3kB7/p5+s7xD99hs6NKGhuMdI3AMpStwU9WF/8SJRtWrWr/f4MYrcLVgAcVCqFIrdtW5N1KwZbkrGfvaKYipCjh2DuPH0RJGwxo2xjR490i+Kt2QJ0dCh4vOmTUSdOmXlCEgcjRQlOYcbN0RtKCJc4//+a9kKmZaGzs6uXZj27UPlYT8/ohYtYIEpVYqoeHFMJUrgtWBBrHvjBlFEBNG1a3g9dw6djnz5YIUZORJFQK1FUVDzhwh1fOTp5j5IUeKmrFgBD3airHmlx8ejENbu3ZiOHUOV0owIDCRq1AgipFEj9KQslRzXsmYNLDMq48ejcJgsopdzkKIkZ8FM9PvvRK+8IuY1b060cSMiatIjNRXRcqpIOXGC6NEj0+Xy5cOyioLPnp5E5cujcGCPHhAkGf2WOWbMgDW3Y0cM90jcBylK3Jg8eSAk3n2XaO7c7G0rPh43ntRUCAV18vQUr1WqiIqd1sBMtGoVTLAqISEI8/XxyV57JY5HipKcy4IFsFao5M2LIdPq1a3fRmoqhngePBDT/fuwjFaqhKl8+ez7pJw9C+srkfQlcUekKHFjkpLEw/2vv5DzwxUwGIjGjiWaNUvMa9gQFplChZzWLEk2kaIk57NhAywYWtavJ+re3TntMUabf+W334j69nVueyS2x0IqK4k7kD8/HNWI4Dj666/Obc/du7CE5MkjBEmbNuhdHT8uBYlE4my6d4cF8+JF4fvVowesoZ98Av8QZxEZKQTJokVSkLgrUpS4OcHB6P0QEb36KlHLlo7NfJiYSDRlCm5qpUtjCIiI6PPPYTHZvt2y579EInEO1arh2o2NJXruOcybOhVDLx06EMXEOLY9v/1GFBSE99OmEb3xhmN/X+I45PBNLuHOHX2o3d9/E3XubB9H0pQUovnzicaM0c/Pl49o2zZ460vcDzl8476kpRFNmEA0c6Z+/ogRiNYLCLDP72r9R4iIfvmFaOBA+/yWxDWQlpJcQpkysEyoY8Ndu8I5dexYori47G37/n3U2wkNhcjJl08vSL78EkIlKUkKEokkJ5InD+pSKQqudZUFCxD66+GBaLu9e62L0ksPZqIdO7BNrSC5cUMKktyAtJTkQi5dgo/J5cv6+c8/D1NtixYQGMZe7U+f4qbz77/IBnn+vOXfmDGDaPhw6Rmfm5CWktyFohD9+SfR22/DL8wcHTti2Lh+fWSGLVxY5EJhRofowQPkPfn+e/NJ0C5cyFwUkCRnI0VJLsZgQAbF7I7P+vkRjR6N7ZQpY5u2SXIOCxYsoAULFpDBYKDLly9LUZJLuXCB6OuvkRk6u0+VFi2QRbZSJZs0TZKDkKJEQkTIMRAVhXLme/diOncO1hEiCI+qVVEro21bkZMkozLnktyDtJRItDAThYcTrV2LaJ6oKEx37hA9fIjonoIFiZ55BveUV16RnRqJFCUSicRGSFEikUiyi3R0lUgkEolE4hJIUSKRSCQSicQlkKJEIpFI/q+9OyABGAaCIJgKiH+hLyA10cBSZlQsPNwDCaIEAEgQJQBAgigBABJECQCQIEoAgATjacAnzjlrZtbeez033k8DvydKAIAE5xsAIEGUAAAJogQASBAlAECCKAEAEkQJAJAgSgCABFECACSIEgAgQZQAAAkvDJCuaumATXMAAAAASUVORK5CYII=\n", "text/plain": [ "Graphics object consisting of 1 graphics primitive" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Butterfly curve by Temple H. Fay\n", "t = var('t')\n", "parametric_plot((sin(t)*(exp(cos(t))-2*cos(4*t)-sin(t/12)**5), cos(t)*(exp(cos(t))-2*cos(4*t)-sin(t/12)**5)),(0,12*pi))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Appendix: Getting your hands on SageMath\n", "Here are three ways of getting access to SageMath:\n", "### SageMathCell\n", "If you have internet access and want to perform a short computation, you can go to [https://sagecell.sagemath.org/](https://sagecell.sagemath.org/), enter the code you want to run and click a button to see the result.\n", "\n", "### Cocalc\n", "For longer computations and projects, you can got to [https://cocalc.com/](https://cocalc.com/) and create a free account. Then you can create a new project, and add a Jupyter notebook (a file ending on ``.ipynb``). Select a SageMath kernel to get an environment like the current file.\n", "\n", "### Local SageMath installation\n", "The most convenient way to work with SageMath is to install it on your computer. On the university computers, it is already installed. For your personal computers, see [https://doc.sagemath.org/html/en/installation/binary.html](https://doc.sagemath.org/html/en/installation/binary.html) for the official installation guide. \n", "Here is the short version for the most important operating systems:\n", "* Linux: follow the [section of the installation guide above](https://doc.sagemath.org/html/en/installation/binary.html#linux)\n", "* Windows: go to [https://github.com/sagemath/sage-windows/releases](https://github.com/sagemath/sage-windows/releases) to download the latest ``SageMath-XX-Installer-YY.exe`` and run it\n", "* MacOS: installing SageMath here can be slightly tricky, but many people had good experiences with this inofficial guide: [https://github.com/3-manifolds/Sage_macOS/releases/](https://github.com/3-manifolds/Sage_macOS/releases/)\n", "\n", "If you still have some older version of SageMath installed on your computer, note that you should use **Version 9.0 or newer** for this course, since the version of Python changed starting from SageMath 9.0 and some of our code will not work on the older versions." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Appendix: Strengths and weaknesses of SageMath and an exercise for the lecturer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As an illustration of some of the points in the tabular overview of Pros and Cons about SageMath: originally I wanted to demonstrate a slightly different computation in the \"Motivation\" section above. There we had the characteristic polynomial ``P`` of the matrix ``M``:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "M = matrix([[17,2,-4,9],[-13,2,8,3],[6,1,-1,4],[5,5,-2,2]])\n", "P = M.characteristic_polynomial()\n", "P" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What we can do in SageMath is to compute the quotient ring $$S = \\mathbb{Z}[x]/(P).$$" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "S = ZZ[x].quotient_ring(P); S" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Then I had planned to demonstrate that SageMath can decide cool properties about this ring, such as whether $S$ is an integral domain.
\n", "**Recall:** A ring $S$ is an **integral domain** if $S \\neq 0$ and for $a,b \\in S$ with $a \\cdot b = 0$ we must have $a=0$ or $b=0$.
However, I was disappointed:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "S.is_integral_domain()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On the other hand, since SageMath is open-source, we can immediately check what goes wrong here, by looking at the code of the function ``is_integral_domain``:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "S.is_integral_domain??" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we have seen that SageMath *knows* that ``P`` is not irreducible:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "P.is_irreducible()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But the quotient $S=\\mathbb{Z}[x]/(P)$ can never be an integral domain if $P$ is not irreducible: for $P=P_1 \\cdot P_2$ with $P_1, P_2$ not units, we have \n", "$$\n", "\\overline{P_1} \\cdot \\overline{P_2} = \\overline{P} = 0 \\in S\n", "$$\n", "but $\\overline{P_1} \\neq 0, \\overline{P_2} \\neq 0 \\in S$.\n", "\n", "**Exercise (for the lecturer):**
\n", "Implement a better function ``is_integral_domain`` for quotient rings like $S$ and get it added to SageMath." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Assignments\n", "**Exercise** (not so relevant for course, but fun anyway)\n", "* Understand where the numbers of multiplications and additions for computing the determinant of $M$ in the first section come from.
\n", "*Fun fact*: I actually used SageMath to compute them!\n", "* For the two algorithms from the table, show that one needs at least $n!$ multiplications to compute the determinant of a $n \\times n$-matrix. \n", "* Can you think of an algorithm where this number grows only polynomially in $n$?" ] } ], "metadata": { "kernelspec": { "display_name": "SageMath 9.1", "language": "sage", "name": "sagemath" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }