{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# The $0$-Rook Monoid and its Representation Theory\n", "\n", "\n", "Joel Gay and Florent Hivert\n", "\n", "$\\newcommand{\\emptyw}{\\varepsilon}\n", "\\DeclareMathOperator{\\code}{code}\n", "\\DeclareMathOperator{\\decode}{decode}\n", "\\newcommand{\\Z}{\\mathbb{Z}}\n", "\\newcommand{\\un}[1]{\\underline{#1}}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Rook vectors\n", "\n", "A *rook vector* of size $n$ is encoded by a tuple whose element belongs to $\\{0, \\dots, n\\}$ and such that each non zero integer appears at most one. The number of rook vector is\n", "$$\n", "\\sum_{r=0}^n \\binom{n}{r}^2 r!\n", "$$\n", "($r$ denotes the number of non zero entries)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# %load -s rook_number rook0.sage\n", "@cached_function\n", "def rook_number(n):\n", " r\"\"\"\n", " The number of rooks\n", "\n", " EXAMPLES::\n", "\n", " sage: [rook_number(i) for i in range(10)]\n", " [1, 2, 7, 34, 209, 1546, 13327, 130922, 1441729, 17572114]\n", " sage: rook_number(10)\n", " 234662231\n", " sage: sum(c(10, k) for k in range(11))\n", " 234662231\n", " \"\"\"\n", " return sum(binomial(n, r)^2 * factorial(r) for r in range(n+1))" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "[1, 2, 7, 34, 209, 1546, 13327, 130922, 1441729, 17572114]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[rook_number(i) for i in range(10)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rook triangle \n", "\n", "Count the rook according to the position of the first zero\n", "\n", "Implementation using Lemma 3.28, page 19\n", "\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# %load -s c rook0.sage\n", "@cached_function\n", "def c(n, k):\n", " \"\"\"\n", " Rook triangle : count the rook according to the position of the first zero\n", "\n", " Alternative implementation using Lemma 3.28, page 19\n", "\n", " EXAMPLES::\n", "\n", " sage: [[c(n, k) for k in range(n+1)] for n in range(8)]\n", " [[1],\n", " [1, 1],\n", " [3, 2, 2],\n", " [13, 9, 6, 6],\n", " [73, 52, 36, 24, 24],\n", " [501, 365, 260, 180, 120, 120],\n", " [4051, 3006, 2190, 1560, 1080, 720, 720],\n", " [37633, 28357, 21042, 15330, 10920, 7560, 5040, 5040]]\n", " \"\"\"\n", " if k < 0 or k > n: return 0\n", " if n == 0: return 1\n", " return (c(n-1, k)*(n-k-1) + c(n-1, k-1)*k +\n", " sum(c(n-1, k1) for k1 in range (k, n+1)))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[1],\n", " [1, 1],\n", " [3, 2, 2],\n", " [13, 9, 6, 6],\n", " [73, 52, 36, 24, 24],\n", " [501, 365, 260, 180, 120, 120],\n", " [4051, 3006, 2190, 1560, 1080, 720, 720],\n", " [37633, 28357, 21042, 15330, 10920, 7560, 5040, 5040],\n", " [394353, 301064, 226856, 168336, 122640, 87360, 60480, 40320, 40320]]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[[c(n, k) for k in range(n+1)] for n in range(9)]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# %load -s is_rook rook0.sage\n", "def is_rook(r):\n", " r\"\"\"\n", " Test for rook\n", "\n", " EXAMPLES::\n", "\n", " sage: is_rook((0, 1, 4, 3, 2))\n", " True\n", " sage: is_rook((0, 1, 5, 3, 2))\n", " True\n", " sage: is_rook((0, 1, 6, 3, 2))\n", " False\n", " sage: is_rook((0, 1, 2, 3, 2))\n", " False\n", " sage: is_rook((0, -1, 2, 3, 0))\n", " False\n", " \"\"\"\n", " n = len(r)\n", " for i in r:\n", " if not (0 <= i <= n):\n", " return False\n", " for i in range(1, n+1):\n", " if r.count(i) > 1:\n", " return False\n", " return True\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_rook((0, 1, 4, 3, 2))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_rook((0, 1, 5, 3, 2))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_rook((0, 1, 6, 3, 2))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_rook((0, 1, 2, 3, 2))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_rook((0, -1, 2, 3, 0))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We enumerate rook vector recursively as follows: from a rook of size $n-1$, we get a rook of size $n$ by\n", "\n", "- either insert $n$ at any place\n", "- either insert a $0$. To get each rook ony once, we choose to always insert before any other $0$.\n", "\n", "Starting from the set of rooks of size $n-1$, one gets each rook of size $n$ exactly once." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# %load -s first_zero rook0.sage\n", "def first_zero(r):\n", " r\"\"\"\n", " The position of the first zero\n", "\n", " EXAMPLES::\n", "\n", " sage: first_zero((1,2,0,2,0))\n", " 2\n", "\n", " TESTS:\n", "\n", " sage: for n in range(7):\n", " ....: l = [first_zero(r) for r in rooks(n)]\n", " ....: for k in range(n+1):\n", " ....: assert(l.count(k) == c(n, k))\n", " \"\"\"\n", " if 0 in r:\n", " return r.index(0)\n", " else:\n", " return len(r)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "first_zero((1,2,0,2,0))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here is a function to generate rooks" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "def rooks_iter(n):\n", " if n == 0: \n", " yield ()\n", " else: \n", " for r in rooks(n-1):\n", " for i in range(n):\n", " yield r[:i]+(n,)+r[i:]\n", " try:\n", " fz = r.index(0)\n", " except ValueError:\n", " fz = n-1\n", " for i in range(fz+1):\n", " yield r[:i]+(0,)+r[i:]\n", "def rooks(n):\n", " return list(rooks_iter(n))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[()]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rooks(0)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(1,), (0,)]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rooks(1)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "[(2, 1), (1, 2), (0, 1), (1, 0), (2, 0), (0, 2), (0, 0)]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rooks(2)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "[(3, 2, 1),\n", " (2, 3, 1),\n", " (2, 1, 3),\n", " (0, 2, 1),\n", " (2, 0, 1),\n", " (2, 1, 0),\n", " (3, 1, 2),\n", " (1, 3, 2),\n", " (1, 2, 3),\n", " (0, 1, 2),\n", " (1, 0, 2),\n", " (1, 2, 0),\n", " (3, 0, 1),\n", " (0, 3, 1),\n", " (0, 1, 3),\n", " (0, 0, 1),\n", " (3, 1, 0),\n", " (1, 3, 0),\n", " (1, 0, 3),\n", " (0, 1, 0),\n", " (1, 0, 0),\n", " (3, 2, 0),\n", " (2, 3, 0),\n", " (2, 0, 3),\n", " (0, 2, 0),\n", " (2, 0, 0),\n", " (3, 0, 2),\n", " (0, 3, 2),\n", " (0, 2, 3),\n", " (0, 0, 2),\n", " (3, 0, 0),\n", " (0, 3, 0),\n", " (0, 0, 3),\n", " (0, 0, 0)]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rooks(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's perform some consistency test" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "for n in range(9):\n", " assert(len(rooks(n)) == rook_number(n))" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " l = [first_zero(r) for r in rooks(n)]\n", " for k in range(n+1):\n", " assert(l.count(k) == c(n, k))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Rooks and $R$-Codes\n", "\n", "In this section, we check the combinatorics of $R$-code and reduced word in $0$- and $1$-rook monoids\n", "The primary goal is to check that Definition 3.37, page 22 is correct." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Function $m$ of Definition 3.16, page 16\n", "\n", "To each word $\\un{w}$ over $\\Z$, we associate a nonnegative number $m(\\un{w})$ defined recursively by: $m(\\emptyw) = 0$ and for any word $\\un{w}$ and any letter $d$,\n", " \\n", " m(\\un{w} d) :=\n", " \\begin{cases}\n", " -d & \\text{if $d\\leq0\\,$;} \\\\\n", " m(\\un{w})+1 & \\text{if $0 m(\\un{w})+1\\,$.}\n", " \\end{cases}\n", " \\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# %load -s mcode_ref rook0.sage\n", "def mcode_ref(c):\n", " r\"\"\"\n", " Fonction m (Definition 3.16, page 16)\n", "\n", " EXAMPLES::\n", "\n", " sage: mcode_ref((1, 2, 8, 3, 6, 4, 2, 7))\n", " 5\n", " sage: mcode_ref((3, 6, 4, -4, 2, 9, 4, -3, 5, 2, 5, 3, 8))\n", " 6\n", " sage: mcode_ref((3, 6, 4, -4, 2, 9, 4, -3))\n", " 3\n", " sage: mcode_ref((0, 2, 1, -1, 1, 2, 5, 4))\n", " 4\n", " \"\"\"\n", " if not c:\n", " return 0\n", " d = c[-1]\n", " if d <= 0:\n", " return -d\n", " mw = mcode_ref(c[:-1])\n", " if d <= mw + 1:\n", " return mw + 1\n", " else:\n", " return mw" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "5" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mcode_ref((1, 2, 8, 3, 6, 4, 2, 7))" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mcode_ref((3, 6, 4, -4, 2, 9, 4, -3, 5, 2, 5, 3, 8))" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mcode_ref((3, 6, 4, -4, 2, 9, 4, -3))" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mcode_ref((0, 2, 1, -1, 1, 2, 5, 4))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here is a faster code. Warning ! it only agrees with the previous definition on rook vectors." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "# %load -s mcode rook0.sage\n", "def mcode(c):\n", " r\"\"\"\n", " Faster Implementation of m, only agree with m on codes\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7):\n", " ....: for c in codes(n):\n", " ....: assert(mcode_ref(c) == mcode(c))\n", " \"\"\"\n", " n = len(c) + 1\n", " k = 0\n", " for i in range(1, n):\n", " if c[-i] <= 0:\n", " k = i\n", " break\n", " if k == 0:\n", " return n-1\n", " else :\n", " k1 = -c[-k]\n", " k2 = 0\n", " for i in range(-k+1, 0):\n", " if c[i] <= k1+k2+1:\n", " k2 += 1\n", " return k1 + k2\n" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mcode((0, 1, 1, -1, 1, 2, 5, 4))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### $R$-Codes\n", "\n", "We now implement Definition 3.16, page 16:\n", "\n", "A word on $\\Z$ is an *$R$-code* if it can be obtained by the following recursive construction: the empty word $\\emptyw$ is a code, and $\\un{w}d$ is a code if $\\un{w}$ is a code and $-m(\\un{w}) \\leq d \\leq n$.\n" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "# %load -s is_code,code_iter,codes rook0.sage\n", "def is_code(c):\n", " r\"\"\"\n", " Test for code (Definition 3.16, page 16)\n", "\n", " EXAMPLES::\n", "\n", " sage: is_code((0,))\n", " True\n", " sage: is_code((1,))\n", " True\n", " sage: is_code((2,))\n", " False\n", " sage: is_code((-1,))\n", " False\n", " sage: is_code((1, -1, -1))\n", " True\n", " sage: is_code((1, -1, -2))\n", " False\n", " \"\"\"\n", " for i in range(0, len(c)):\n", " if not -mcode(c[:i]) <= c[i] <= i+1:\n", " return False\n", " return True\n", "\n", "def code_iter(n):\n", " \"\"\"\n", " Iterate on codes according to Definition 3.16, page 16\n", "\n", " See codes for tests\n", " \"\"\"\n", " if n == 0:\n", " yield ()\n", " else:\n", " for c in code_iter(n-1):\n", " for i in range(n, -mcode(c)-1, -1):\n", " yield c + (i,)\n", "\n", "@cached_function\n", "def codes(n):\n", " \"\"\"\n", " List of codes according to Definition 3.16, page 16\n", "\n", " EXAMPLES::\n", "\n", " sage: codes(1)\n", " [(1,), (0,)]\n", " sage: codes(2)\n", " [(1, 2), (1, 1), (1, 0), (1, -1), (0, 2), (0, 1), (0, 0)]\n", "\n", " TESTS::\n", "\n", " sage: \"|\".join(\"\".join(str(l) for l in w) for w in codes(3))\n", " '123|122|121|120|12-1|12-2|113|112|111|110|11-1|11-2|103|102|101|100|1-13|1-12|1-11|1-10|1-1-1|023|022|021|020|013|012|011|010|01-1|003|002|001|000'\n", " sage: for i in range(7):\n", " ....: for c in codes(i): assert(is_code(c))\n", " sage: for i in range(7): assert(len(codes(i)) == r(i))\n", " \"\"\"\n", " return list(code_iter(n))\n" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((0,))" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((1,))" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((2,))" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((-1,))" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((1, -1, -1))" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_code((1, -1, -2))" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(1,), (0,)]" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "codes(1)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(1, 2), (1, 1), (1, 0), (1, -1), (0, 2), (0, 1), (0, 0)]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "codes(2)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(1, 2, 3),\n", " (1, 2, 2),\n", " (1, 2, 1),\n", " (1, 2, 0),\n", " (1, 2, -1),\n", " (1, 2, -2),\n", " (1, 1, 3),\n", " (1, 1, 2),\n", " (1, 1, 1),\n", " (1, 1, 0),\n", " (1, 1, -1),\n", " (1, 1, -2),\n", " (1, 0, 3),\n", " (1, 0, 2),\n", " (1, 0, 1),\n", " (1, 0, 0),\n", " (1, -1, 3),\n", " (1, -1, 2),\n", " (1, -1, 1),\n", " (1, -1, 0),\n", " (1, -1, -1),\n", " (0, 2, 3),\n", " (0, 2, 2),\n", " (0, 2, 1),\n", " (0, 2, 0),\n", " (0, 1, 3),\n", " (0, 1, 2),\n", " (0, 1, 1),\n", " (0, 1, 0),\n", " (0, 1, -1),\n", " (0, 0, 3),\n", " (0, 0, 2),\n", " (0, 0, 1),\n", " (0, 0, 0)]" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "codes(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's perform some consistency test" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "for i in range(7):\n", " for c in codes(i): assert(is_code(c))" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "for i in range(7): assert(len(codes(i)) == rook_number(i))" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " for c in codes(n):\n", " assert(mcode_ref(c) == mcode(c))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Encoding and decoding rooks\n", "\n", "**Definition 3.12, page 16**:\n", "\n", "For a rook $r$ of length $n$, we call the *$R$-code of $r$* and denote $\\code(r)$ the word of lenght $n$ on $\\Z$ defined recursively by:\n", "\n", "1. If $n=0$ then $\\code(\\emptyw) := \\emptyw$.\n", "2. Otherwise, if $n\\in r$, then $r$ can be written uniquely\n", " $r=\\un{b}n\\un{e}$. Let $r':=\\un{b}\\un{e}$ (the subword of\n", " $r$ where the unique occurrence of $n$ is removed). Then $\\code(r)\n", " := \\code(r')\\cdot (\\ell(\\un{b})+1)$.\n", "3. Otherwise, $n\\notin r$ and $r$ can be written uniquely\n", " $r=\\un{b}0\\un{e}$ with $0\\notin \\un{b}$. Let $r':=\\un{b}\\un{e}$ (the\n", " subword of $r$ where the first $0$ is removed). Then $\\code(r) :=\n", " \\code(r')\\cdot (-\\ell(\\un{b}))$.\n" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "# %load -s encode,decode rook0.sage\n", "def encode(r):\n", " r\"\"\"\n", " Encode a rook (Definition 3.12, page 16)\n", "\n", " EXAMPLES::\n", "\n", " sage: encode((2, 0, 3, 0, 4))\n", " (0, 1, 2, 4, -1)\n", " sage: encode((0, 2, 4, 0, 1))\n", " (1, 1, -1, 2, 0)\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7):\n", " ....: for c in codes(n):\n", " ....: assert(c == encode(decode(c)))\n", " \"\"\"\n", " n = len(r)\n", " r = list(r)\n", " res = []\n", " for i in range(n, 0, -1):\n", " if i in r:\n", " pos = r.index(i)\n", " res.append(pos+1)\n", " del r[pos]\n", " else:\n", " pos = r.index(0)\n", " res.append(-pos)\n", " del r[pos]\n", " return tuple(res[::-1])\n", "\n", "def decode(c):\n", " r\"\"\"\n", " Decode a code (Definition 3.23, page 18)\n", "\n", " EXAMPLE::\n", "\n", " sage: decode((1, 1, -1, 2, 0))\n", " (0, 2, 4, 0, 1)\n", " sage: decode((0, 1, 2, 4, -1))\n", " (2, 0, 3, 0, 4)\n", " \"\"\"\n", " res = []\n", " for i in range(len(c)):\n", " if c[i] > 0:\n", " res.insert(c[i]-1, i+1)\n", " elif c[i] == 0:\n", " res.insert(0, 0)\n", " else:\n", " res.insert(-c[i], 0)\n", " return tuple(res)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 1, 2, 4, -1)" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "encode((2, 0, 3, 0, 4))" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1, 1, -1, 2, 0)" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "encode((0, 2, 4, 0, 1))" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " for c in codes(n):\n", " assert(c == encode(decode(c)))" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 2, 4, 0, 1)" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "decode((1, 1, -1, 2, 0))" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 0, 3, 0, 4)" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "decode((0, 1, 2, 4, -1)) " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Action on rooks" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "# %load -s act_rook,act_rook_w rook0.sage\n", "def act_rook(r, i):\n", " r\"\"\"\n", " Right action on a rook (Definition 3.8, page 15)\n", "\n", " EXAMPLES::\n", "\n", " sage: act_rook((1, 2, 3), 1)\n", " (2, 1, 3)\n", " sage: act_rook((1, 2, 3), 2)\n", " (1, 3, 2)\n", " sage: act_rook((1, 2, 3), 0)\n", " (0, 2, 3)\n", " sage: act_rook((3, 1, 2), 0)\n", " (0, 1, 2)\n", " sage: act_rook((3, 1, 2), 1)\n", " (3, 1, 2)\n", " sage: act_rook((3, 1, 2), 2)\n", " (3, 2, 1)\n", " \"\"\"\n", " if i == 0:\n", " return (0,) + r[1:]\n", " elif r[i-1] >= r[i]:\n", " return r\n", " else:\n", " return r[:i-1]+(r[i], r[i-1])+r[i+1:]\n", "\n", "def act_rook_w(r, w):\n", " r\"\"\"\n", " Right action of a word on a rook (Definition 3.8, page 15)\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7):\n", " ....: for c in codes(n):\n", " ....: assert(act_rook_w(tuple(range(1, n+1)), code2word(c)) ==\n", " ....: decode(c))\n", " \"\"\"\n", " for i in w:\n", " r = act_rook(r, i)\n", " return r" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 1, 3)" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((1, 2, 3), 1)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1, 3, 2)" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((1, 2, 3), 2)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 2, 3)" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((1, 2, 3), 0)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 1, 2)" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((3, 1, 2), 0)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3, 1, 2)" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((3, 1, 2), 1)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3, 2, 1)" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_rook((3, 1, 2), 2)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Action on codes" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "# %load -s act_code,act_code_w rook0.sage\n", "def act_code(c, t, print_rule = False):\n", " r\"\"\"\n", " Right action on a code (Definition 3.37, page 22)\n", "\n", " EXAMPLES::\n", "\n", " sage: act_code((1, 2, 3, 4, -2, 1, 2, 6, -4), 5)\n", " (1, 2, 3, 4, -2, 1, 2, 6, -4)\n", " \"\"\"\n", " n = len(c)\n", " if n == 1:\n", " assert(t == 0)\n", " return (0,)\n", " cn = c[-1]\n", " if cn >= 1: # Pos\n", " if t == cn: # a\n", " if print_rule: print \"Pos.a\",\n", " return c\n", " elif t == cn-1: # b\n", " if print_rule: print \"Pos.b\",\n", " return c[:-1] + (cn-1,)\n", " elif t < cn -1: # c\n", " if print_rule: print \"Pos.c\",\n", " return act_code(c[:-1], t) + (cn,)\n", " else: # d\n", " if print_rule: print \"Pos.d\",\n", " return act_code(c[:-1], t-1) + (cn,)\n", " else: # Neg\n", " i = -cn\n", " if t == i: # a\n", " if print_rule: print \"Neg.a\",\n", " return c\n", " elif 0 < t < i: # b\n", " if print_rule: print \"Neg.b\",\n", " return act_code(c[:-1], t) + (cn,)\n", " elif t > i + 1: # c\n", " if print_rule: print \"Neg.c\",\n", " return act_code(c[:-1], t-1) + (cn,)\n", " elif t == 0: # d\n", " if print_rule: print \"Neg.d\",\n", " return act_code_w(c[:-1], range(i)) + (0,)\n", " else: # e\n", " if mcode(c[:-1]) == i: # alpha\n", " if print_rule: print \"Neg.e.alpha\",\n", " return c\n", " else: # beta\n", " if print_rule: print \"Neg.e.beta\",\n", " return c[:-1]+(-(i+1),)\n", "\n", "def act_code_w(c, w):\n", " r\"\"\"\n", " Right action of a word on a code (Definition 3.37, page 22)\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7):\n", " ....: for c in codes(n):\n", " ....: assert(decode(c) ==\n", " ....: act_rook_w(tuple(range(1, n+1)), code2word(c)))\n", " \"\"\"\n", " for i in w:\n", " c = act_code(c, i)\n", " return c" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1, 2, 3, 4, -2, 1, 2, 6, -4)" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_code((1, 2, 3, 4, -2, 1, 2, 6, -4), 5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Canonical word associated to a code" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [], "source": [ "# %load -s code2word rook0.sage\n", "def code2word(c):\n", " r\"\"\"\n", " Word associated to a code (Definition 3.33, page 21)\n", "\n", " EXAMPLES::\n", "\n", " sage: code2word((1, 1, -1, 2, 0))\n", " [1, 2, 1, 0, 1, 3, 2, 4, 3, 2, 1, 0]\n", " \"\"\"\n", " res = []\n", " for i, ci in enumerate(c):\n", " if ci <= 0:\n", " res.append(range(i, -1, -1)+range(1, -ci+1))\n", " else:\n", " res.append(range(i, ci-1, -1))\n", " return flatten(res)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[1, 2, 1, 0, 1, 3, 2, 4, 3, 2, 1, 0]" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "code2word((1, 1, -1, 2, 0))" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "((0, 2, 4, 0, 1), (0, 2, 4, 0, 1))" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "decode((1, 1, -1, 2, 0)), act_rook_w((1, 2, 3, 4, 5), code2word((1, 1, -1, 2, 0)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Check that acting on the identity and decoding is the same" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " for c in codes(n):\n", " assert(act_rook_w(tuple(range(1, n+1)), code2word(c)) == decode(c))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Check that acting on code and acting on rook commute" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "# %load -s check_act rook0.sage\n", "def check_act(n, print_rule = False):\n", " r\"\"\"\n", " Check for Lemma 3.38, page 22 and Corollary 3.44, page 27\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7): check_act(n)\n", "\n", " sage: check_act(2, True)\n", " Pos.c Code=(1, 2), i=0, w=[], r=(1, 2), r.i=(0, 2), c.i=(0, 2)\n", " Pos.b Code=(1, 2), i=1, w=[], r=(1, 2), r.i=(2, 1), c.i=(1, 1)\n", " Pos.b Code=(1, 1), i=0, w=[1], r=(2, 1), r.i=(0, 1), c.i=(1, 0)\n", " Pos.a Code=(1, 1), i=1, w=[1], r=(2, 1), r.i=(2, 1), c.i=(1, 1)\n", " Neg.a Code=(1, 0), i=0, w=[1, 0], r=(0, 1), r.i=(0, 1), c.i=(1, 0)\n", " Neg.e.beta Code=(1, 0), i=1, w=[1, 0], r=(0, 1), r.i=(1, 0), c.i=(1, -1)\n", " Neg.d Code=(1, -1), i=0, w=[1, 0, 1], r=(1, 0), r.i=(0, 0), c.i=(0, 0)\n", " Neg.a Code=(1, -1), i=1, w=[1, 0, 1], r=(1, 0), r.i=(1, 0), c.i=(1, -1)\n", " Pos.c Code=(0, 2), i=0, w=[0], r=(0, 2), r.i=(0, 2), c.i=(0, 2)\n", " Pos.b Code=(0, 2), i=1, w=[0], r=(0, 2), r.i=(2, 0), c.i=(0, 1)\n", " Pos.b Code=(0, 1), i=0, w=[0, 1], r=(2, 0), r.i=(0, 0), c.i=(0, 0)\n", " Pos.a Code=(0, 1), i=1, w=[0, 1], r=(2, 0), r.i=(2, 0), c.i=(0, 1)\n", " Neg.a Code=(0, 0), i=0, w=[0, 1, 0], r=(0, 0), r.i=(0, 0), c.i=(0, 0)\n", " Neg.e.alpha Code=(0, 0), i=1, w=[0, 1, 0], r=(0, 0), r.i=(0, 0), c.i=(0, 0)\n", "\n", " \"\"\"\n", " for c in codes(n):\n", " for i in range(n):\n", " ac = act_code(c, i)\n", " if print_rule:\n", " print \"Code=%s, i=%s, w=%s, r=%s, r.i=%s, c.i=%s\"%(\n", " c, i, code2word(c), decode(c),\n", " act_rook(decode(c), i), act_code(c, i, True))\n", " assert(is_code(ac))\n", " assert(decode(ac) == act_rook(decode(c), i))" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "for n in range(7): check_act(n)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now check Example 3.50, page 28" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 4, 0, 5, 0, 3)" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "c = (0, 1, 3, 2, 3, -2)\n", "r = decode(c); r" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 0, 3, 1, 3, 0)" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "act_code(c, 0)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 4, 0, 5, 0, 3)" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "decode(act_code(c, 0))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Canonical words" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "# %load -s canonize,canonwords rook0.sage\n", "def canonize(w):\n", " r\"\"\"\n", " Canonize a word\n", "\n", " EXAMPLES::\n", "\n", " sage: canonize([1, 0, 1, 0])\n", " [0, 1, 0]\n", " sage: canonize([1, 0, 1, 0, 2])\n", " [0, 1, 0, 2]\n", " sage: canonize([1, 0, 1, 2])\n", " [1, 0, 1, 2]\n", " sage: canonize([0, 1, 0, 1, 2])\n", " [0, 1, 0, 2]\n", " \"\"\"\n", " n = max(w) + 1\n", " res = act_code_w(tuple(range(1,n+1)), w)\n", " return code2word(res)\n", "\n", "def canonwords(n):\n", " r\"\"\"\n", " List of canonical words\n", "\n", " EXAMPLES::\n", "\n", " sage: canonwords(0)\n", " [[]]\n", " sage: canonwords(1)\n", " [[], [0]]\n", " sage: canonwords(2)\n", " [[], [1], [1, 0], [1, 0, 1], [0], [0, 1], [0, 1, 0]]\n", "\n", " TESTS::\n", "\n", " sage: \"|\".join(\"\".join(str(l) for l in w) for w in canonwords(3))\n", " '|2|21|210|2101|21012|1|12|121|1210|12101|121012|10|102|1021|10210|101|1012|10121|101210|1012101|0|02|021|0210|01|012|0121|01210|012101|010|0102|01021|010210'\n", " \"\"\"\n", " return [code2word(c) for c in codes(n)]" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 1, 0]" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonize([1, 0, 1, 0])" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 1, 0, 2]" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonize([1, 0, 1, 0, 2])" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[1, 0, 1, 2]" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonize([1, 0, 1, 2])" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 1, 0, 2]" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonize([0, 1, 0, 1, 2])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[]]" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonwords(0)" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[], [0]]" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonwords(1)" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[], [1], [1, 0], [1, 0, 1], [0], [0, 1], [0, 1, 0]]" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "canonwords(2)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The 0-Rook monoid\n", "\n", "We can now compute the product in the $0$-Rook monoid" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "# %load -s prod_rook rook0.sage\n", "def prod_rook(r1, r2):\n", " r\"\"\"\n", " Product in the 0-rook monoid\n", "\n", " TESTS::\n", "\n", " sage: for n in range(4):\n", " ....: for r1, r2, r3 in cartesian_product(([rooks(n)]*3)):\n", " ....: assert(prod_rook(r1, prod_rook(r2, r3)) ==\n", " ....: prod_rook(prod_rook(r1, r2), r3))\n", " \"\"\"\n", " return act_rook_w(r1, code2word(encode(r2)))" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 0, 1)" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prod_rook((0,2,1),(3,0,2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's check that it is associative:" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "for n in range(4):\n", " for r1, r2, r3 in cartesian_product(([rooks(n)]*3)):\n", " assert(prod_rook(r1, prod_rook(r2, r3)) == prod_rook(prod_rook(r1, r2), r3))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "# %load -s is_action_reduced rook0.sage\n", "def is_action_reduced(w):\n", " r\"\"\"\n", " Test for action reduced word (Corollary 3.54, page 29)\n", "\n", " EXAMPLES::\n", "\n", " sage: is_action_reduced([1, 0])\n", " True\n", " sage: is_action_reduced([1, 1])\n", " False\n", " sage: is_action_reduced([1, 0, 1])\n", " True\n", " sage: is_action_reduced([0, 1, 0])\n", " True\n", " sage: is_action_reduced([1, 0, 1, 0])\n", " True\n", " sage: is_action_reduced([0, 1, 0, 1])\n", " False\n", "\n", " TESTS::\n", "\n", " sage: for n in range(7):\n", " ....: for c in codes(n):\n", " ....: assert(is_action_reduced(code2word(c)))\n", " \"\"\"\n", " if not w:\n", " return True\n", " n = max(w) + 1\n", " r = tuple(range(1, n+1))\n", " for i in w:\n", " newr = act_rook(r, i)\n", " if newr == r:\n", " return False\n", " r = newr\n", " return True" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([1, 0])" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([1, 1])" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([1, 0, 1])" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([0, 1, 0])" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([1, 0, 1, 0])" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "is_action_reduced([0, 1, 0, 1])" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " for c in codes(n):\n", " assert(is_action_reduced(code2word(c)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# The $0$-rook monoid" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From now on, you need [sage_semigroups](https://github.com/nthiery/sage-semigroups/) to be installed." ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Monkey patching sage.misc.sage_unittest.InstanceTester.__init__\n", "Monkey patching sage.misc.sage_unittest.IsMethod\n", "Monkey patching sage.misc.sage_unittest.ReturnOnError\n", "Monkey patching sage.misc.sage_unittest.TestMethodFromIs\n", "Monkey patching sage.misc.sage_unittest._test_method_from_is\n", "Monkey patching sage.misc.sage_unittest.is_method\n", "Monkey patching sage.categories.aperiodic_semigroups.AperiodicSemigroups.ElementMethods\n", "Monkey patching sage.categories.aperiodic_semigroups.AperiodicSemigroups.ParentMethods\n", "Monkey patching sage.categories.character_ring_functor\n", "Monkey patching sage.categories.examples.finite_h_trivial_monoids\n", "Monkey patching sage.categories.examples.finite_semigroups.LeftRegularBand.__init__\n", "Monkey patching sage.categories.finite_h_trivial_semigroups\n", "Monkey patching sage.categories.finite_j_trivial_semigroups\n", "Monkey patching sage.categories.finite_left_regular_bands\n", "Monkey patching sage.categories.finite_semigroups.CharacterRings.WithRealizations\n", "Monkey patching sage.categories.finite_semigroups.CharacterRings.WithRealizations.ParentMethods\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.CharacterRings\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ElementMethods\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.character_ring\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.green_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.group_of_regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.groups_of_regular_j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.h_le_on_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.h_poset_on_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.index_of_regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_DA\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_DG\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_aperiodic\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_basic\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_l_trivial\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.is_r_trivial\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_class_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_class_index\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_class_representative\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_classes_of_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_lequal\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_poset\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_poset_on_regular_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_transversal\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.j_transversal_of_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.l_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.lr_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.lr_class_of\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.lr_regular_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.lr_regular_class_module\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.r_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.regular_j_class_semigroup_generators\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.regular_j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.ParentMethods.regular_j_classes_keys\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.character_ring\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.green_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.group_of_regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.groups_of_regular_j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.h_le_on_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.h_poset_on_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.index_of_regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_DA\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_DG\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_aperiodic\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_basic\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_l_trivial\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.is_r_trivial\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_class_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_class_index\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_class_representative\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_classes_of_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_lequal\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_poset\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_poset_on_regular_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_transversal\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.j_transversal_of_idempotents\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.l_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.lr_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.lr_class_of\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.lr_regular_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.lr_regular_class_module\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.r_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.regular_j_class\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.regular_j_class_semigroup_generators\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.regular_j_classes\n", "Monkey patching sage.categories.finite_semigroups.FiniteSemigroups.parent_class.regular_j_classes_keys\n", "Monkey patching sage_semigroups.categories.finite_semigroups.FiniteSemigroups.element_class.ideal\n", "Monkey patching sage.categories.finite_semigroups.WithRealizations.ParentMethods\n", "Monkey patching sage.categories.h_trivial_semigroups.HTrivialSemigroups.Finite\n", "Monkey patching sage.categories.h_trivial_semigroups.HTrivialSemigroups.Finite_extra_super_categories\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Monkey patching sage.categories.j_trivial_semigroups.JTrivialSemigroups.Finite\n", "Monkey patching sage.categories.l_trivial_semigroups.Finite.ParentMethods\n", "Monkey patching sage.categories.l_trivial_semigroups.LTrivialSemigroups.Finite\n", "Monkey patching sage.categories.module_functor\n", "Monkey patching sage.categories.monoids.Monoids.ParentMethods.submonoid\n", "Monkey patching sage.categories.monoids.Monoids.parent_class.submonoid\n", "Monkey patching sage.categories.r_trivial_semigroups.Finite.ParentMethods\n", "Monkey patching sage.categories.r_trivial_semigroups.RTrivialSemigroups.Finite\n", "Monkey patching sage.categories.r_trivial_semigroups.RTrivialSemigroups.example\n", "Monkey patching sage.categories.semigroup_modules\n", "Monkey patching sage.categories.semigroups.Semigroups.ParentMethods.cayley_graph_cached\n", "Monkey patching sage.categories.semigroups.Semigroups.parent_class.cayley_graph_cached\n", "Monkey patching sage.categories.set_with_action_functor\n", "Monkey patching sage.categories.transformation_semigroups\n", "Monkey patching sage.monoids.automatic_semigroup.AutomaticSemigroup.__init__\n", "Monkey patching sage.monoids.bi_hecke_monoid\n", "Monkey patching sage.monoids.catalog\n", "Monkey patching sage.monoids.character_ring\n", "Monkey patching sage.monoids.free_left_regular_band\n", "Monkey patching sage.monoids.free_partially_commutative_left_regular_band\n", "Monkey patching sage.monoids.free_semilattice\n", "Monkey patching sage.monoids.j_trivial_monoids\n", "Monkey patching sage.monoids.karnofsky_rhodes_expansion\n", "Monkey patching sage.monoids.rees_matrix_monoid\n", "Monkey patching sage.monoids.representations\n", "Monkey patching sage.monoids.set_compositions_monoid\n", "Monkey patching sage.monoids.set_partitions_monoid\n", "Monkey patching sage.monoids.sign_vectors_monoid\n", "Monkey patching sage.monoids.transition_monoid\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Loading sage-semigroups and patching its features into Sage's library:\n" ] } ], "source": [ "import sage_semigroups" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We finaly check that the monoid defined as function and the one using words are isomorphic" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [], "source": [ "# %load -s Rook0 rook0.sage\n", "def Rook0(n):\n", " r\"\"\"\n", " The 0-rook monoid\n", "\n", " EXAMPLES::\n", "\n", " sage: Mon = Rook0(4)\n", " sage: Mon.fun((3,1,2,4))\n", " 3124\n", "\n", " TESTS::\n", "\n", " sage: TestSuite(Mon).run()\n", " \"\"\"\n", " rk = rooks(n)\n", " fun = FiniteSetMaps(rk, action=\"right\")\n", " gen = { i : fun.from_dict({r : act_rook(r, i) for r in rk}) for i in range(n) }\n", " monoid = fun.submonoid(gen, category = Semigroups().JTrivial().Finite())\n", "\n", " one = tuple(range(1, n+1))\n", "\n", " # print a function by the image of the identity\n", " def print_el(el):\n", " return \"\".join(str(i) for i in el.lift()(one))\n", " monoid.element_class._repr_ = print_el\n", " monoid.element_class._latex_ = print_el\n", " monoid.rename(\"Rook monoid of rank %s as functions\"%n)\n", "\n", " # retrieve an element from the image of the identity\n", " dct = { el.lift()(one) : el for el in monoid }\n", " monoid.fun = dct.get\n", "\n", " return monoid" ] }, { "cell_type": "code", "execution_count": 85, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "running ._test_an_element() . . . pass\n", "running ._test_aperiodic() . . . pass\n", "running ._test_associativity() . . . pass\n", "running ._test_cardinality() . . . pass\n", "running ._test_category() . . . pass\n", "running ._test_elements() . . .\n", " Running the test suite of self.an_element()\n", " running ._test_category() . . . pass\n", " running ._test_eq() . . . pass\n", " running ._test_new() . . . pass\n", " running ._test_not_implemented_methods() . . . pass\n", " running ._test_pickling() . . . pass\n", " pass\n", "running ._test_elements_eq_reflexive() . . . pass\n", "running ._test_elements_eq_symmetric() . . . pass\n", "running ._test_elements_eq_transitive() . . . pass\n", "running ._test_elements_neq() . . . pass\n", "running ._test_enumerated_set_contains() . . . pass\n", "running ._test_enumerated_set_iter_cardinality() . . . pass\n", "running ._test_enumerated_set_iter_list() . . . pass\n", "running ._test_eq() . . . pass\n", "running ._test_j_trivial() . . . pass\n", "running ._test_new() . . . pass\n", "running ._test_not_implemented_methods() . . . pass\n", "running ._test_one() . . . pass\n", "running ._test_pickling() . . . pass\n", "running ._test_prod() . . . pass\n", "running ._test_r_trivial() . . . pass\n", "running ._test_some_elements() . . . pass\n", "running ._test_symbol() . . . pass\n" ] } ], "source": [ "TestSuite(Rook0(4)).run(verbose=True)" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3124" ] }, "execution_count": 86, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Mon = Rook0(4)\n", "Mon.fun((3,1,2,4))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We check that the product of two functions is the same as the product computed previously by the reduced word and code algorithm:" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "# %load -s check_isom rook0.sage\n", "def check_isom(n):\n", " r\"\"\"\n", " Checking for ismorphism\n", "\n", " TESTS::\n", "\n", " sage: for i in range(5): check_isom(i)\n", " \"\"\"\n", " Mon = Rook0(n)\n", " one = tuple(range(1,n+1))\n", " assert len(Mon) == len(rooks(n)), \"Wrong cardinality\"\n", " for m1 in Mon:\n", " m1v = m1.lift()(one)\n", " for m2 in Mon:\n", " m2v = m2.lift()(one)\n", " assert (m1*m2).lift()(one) == prod_rook(m1v, m2v)" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Checking 0\n", "Checking 1\n", "Checking 2\n", "Checking 3\n", "Checking 4\n" ] } ], "source": [ "for i in range(5):\n", " print \"Checking %d\"%(i)\n", " check_isom(i)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the $\\mathcal(J)$-trivial monoid theory to compute the reprensentation theory of the $0$-rooks monoids:" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": [ "n = 3; Mon = Rook0(n); one = tuple(range(1,n+1))" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(\n", " [1 0 0 0 0 0 0 0]\n", " [0 1 1 0 1 0 0 0]\n", " [0 1 3 0 2 1 1 0]\n", " [0 0 0 1 0 1 1 0]\n", " [0 1 2 0 2 0 0 0]\n", " [0 0 1 1 0 2 2 0]\n", " [0 0 1 1 0 2 3 0]\n", "[123, 023, 213, 003, 132, 032, 321, 000], [0 0 0 0 0 0 0 1]\n", ")" ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "idm = sorted(Mon.idempotents(), \n", " key=lambda x : x.lift()(one)[::-1])[::-1]\n", "idm, Mon.cartan_matrix(idempotents=tuple(idm))" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(\\left[123, 023, 213, 003, 132, 032, 321, 000\\right],\n", " \\left(\\begin{array}{rrrrrrrr}\n", " 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\\\\n", " 0 & 1 & 1 & 0 & 1 & 0 & 0 & 0 \\\\\n", " 0 & 1 & 3 & 0 & 2 & 1 & 1 & 0 \\\\\n", " 0 & 0 & 0 & 1 & 0 & 1 & 1 & 0 \\\\\n", " 0 & 1 & 2 & 0 & 2 & 0 & 0 & 0 \\\\\n", " 0 & 0 & 1 & 1 & 0 & 2 & 2 & 0 \\\\\n", " 0 & 0 & 1 & 1 & 0 & 2 & 3 & 0 \\\\\n", " 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1\n", " \\end{array}\\right))" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "latex(idm), latex(Mon.cartan_matrix(idempotents=tuple(idm)))" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "Digraph on 8 vertices" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Mon.quiver()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# $\\mathcal{R}$-Order of the $0$-Rook Monoid" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "Graphics object consisting of 28 graphics primitives" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Rook0(2).cayley_graph(side=\"right\").plot()" ] }, { "cell_type": "code", "execution_count": 113, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "Graphics object consisting of 170 graphics primitives" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Rook0(3).cayley_graph(side=\"right\").plot()" ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [ { "data": { "image/png": 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hZ2fHtTyJwoEDBwSWeTtw4AAmTZoksvrrOj6fDx8fHyxYsECgX2afPn2we/dudOzYUYzREVLz0SNgQki99/fff2PMmDEYOnQol/xJSEjAwcEBcXFxmDFjhkiTvz///BN2dnbcv9etW0fJXzlJSEjA3t4eMTExmDhxIld+48YNdO7cGUuWLEF2drYYIySkZqMWQEJIvZWVlYUNGzZgw4YNyM3N5cp79eoFLy8vdO7cuUL18vl8bjLj/7p37x7Mzc2RlZUFAHBycsL27dvpsWUlXb58GQ4ODnj+/DlX1qZNG+zatatWrZNMSHWhFkBCSL3DGMOpU6egp6cHd3d3Lvlr3LgxDh06xLUilVV4eDicnJzQ1cQEcnJykJSUhJycHLqamMDJyQnh4eEAgLi4OPz4449c8vfTTz9h69atlPyJwKBBg/D48WMsXbqUG5zz8uVLDBkyBFZWVoiPjxdzhITULNQCSAipV2JiYjB79mxcvnyZK5OSksLcuXOxbNkyNGzYsMx1PX/+HPbTp+NaSAiaaWpgYFcjGOm0RUNFBaRnZiEi7gWCH0TgfUIizM3MoNSgAc6fPw8A6NevHy5evFjhVUNI6aKjozFz5kxcv36dK1NWVsb69ethb29faussIfUJJYCEkHohPT0d7u7u2L59OwoKCrjyQYMGYceOHejQoUO56vP394ednR2aqKlik+M0jOzdA1JSwv0ECwoKcf7mHbh67ce7hETk5eeja9euuHz5MlRUVCp9XaRkjDEcPHgQLi4uSE5O5sp79OiBPXv2oFOnTmKMjhDxo69BhJA6jTGGQ4cOQVdXF1u2bOGSv5YtW+LUqVMICgqqUPJnY2MDi349EXHIG2PNepWY/AGAlJQkxpr1QsQhb1gO6Asej4c5c+ZQ8lfFeDweJk+ejJiYGEyePJkrv3PnDoyNjeHm5iYwzc/3vHr1CgcPHizXMYTUZJQAEkLqrIcPH6JPnz745ZdfuD5gcnJyWLFiBZ4+fYqxY8eWuf/d9evXMXLkSGhpaRVNEN3ZEL7L5kNRvugRLmMMK30OodnIiVDoNwrmDq6IevmKO15RXg6pGV8gLysDW1tbaGpqwtbWFh8+fBD5dZN/qaurw9fXF9euXYOuri6AotVXNm3aBH19ffzxxx/frSMpKQk9evTA5MmTMWbMGNCDM1IXUAJICKlzkpOT4eDggK5du+LWrVtc+ZgxY/D06VOsXLkSCgoK5aozMzMTRkZG0NTQAADMGDtcoC/ZRr/j2HrkNDznO+De7zvQuJEaBs9ZjIzMLG4fcxMjnN/sDm0tTWg3b44XL17AwsKikldLysLMzAwRERFwd3fn1g9+/fo1Ro4cifHjx+P9+/elHuvm5oZPnz4BAIKDg3H48OFqiZmQqkR9AAkhdUZhYSH27duHJUuWICUlhStv3bo1du3ahSFDhlSq/rCwMHTt2hUAcGr9cozp1xNAUetfs5ETMcdyLBbY/gwAyM3LQ+MfrbDeYSpmjP1RoJ5TITdhsWg1PDw8MH/+fOTm5lZ6WTlSdnFxcXBwcEBwcDBX1qBBA6xevRqzZs0SmPPx+vXr6Nevn8DxmpqaiImJgaqqarXFTIioUQsgIaROuH37Nn744Qf8+uuvXPJX/Hj377//xvz587Fo0SKEhoaisLCwQuc4cOAAmmtpCpX//SEe8cmpGNzNmCuTlZFBvy6GCH0SLbT/qN6maKLeCN7e3ujZsyclf9VMR0cHly5dgp+fHzQ1i36eGRkZmDNnDrp3746wsDAARcsCzpw5U+j4hIQELFmypFpjJkTUKAEkhNRq8fHxmDRpEnr16oWHDx9y5dbW1tyjPgCIiorC+vXr0bNnTzRt2hTTpk3DmTNnytWpP/T2bQwwER49Gp+cCgDQUhNsEdJUU0X8Vy2RALBg536oDBqHj0nJ+PjxI86ePVvm8xPR4fF4sLa2RkxMDOzt7bnysLAwdOvWDXPmzMGqVasQHS2cwAPA7t27ce/eveoKlxCRowSQEFIr5efnw8PDA+3bt8f//vc/rrxTp064fv06/Pz8Sl0PNiEhAb///jvGjh2LRo0aYcSIEdi7d+93B2RERkXBSKdtqa//dzwJYww8CBa6Wlsg/OBO2I8ZjqysLPzyyy80qECMVFVVsWfPHty8eRMGBgYAilZy2bFjB1avXl3qcYwxzJw5U2BKIUJqE0oACSG1TnBwMIyMjDB//nxkZGQAAFRUVODl5YWwsDD06dMHAKCvr//dunJzcxEYGIgZM2agWbNm6NatG1atWoWIiAiBxIzP5yM3NxcNFYUHjzRuVNTyV9wSWCwxNU2oVVBdRRntWzRHt466YIzhwoULuHPnTvluABG5Xr16ITw8HOvXry/z5NwPHz6Et7d3FUdGSNWgBJAQUmu8fv0aFhYWGDRoEPdojsfjYfr06YiNjcWsWbMgJSXF7V/colMe9+/fx/Lly9G5c2coKiri0qVLAAAJCQnIysoi/atRvcVaN22Mxo1Ucfn+v4+g8/Lz8dfDJzA11CvxPJ+/ZEJGRgYABNYhJuIjLS2NBQsWYP369WU+ZunSpTSVD6mVKAEkhNR4OTk5WLVqFfT09HDy5EmuvHv37rh37x727t0LjX+mZ/laWVoAvyU7Oxvr1q0DAHz58gVtWrfGtbBHAIoGfjyKfYE38QlFkztbjsW6gwE4HXILkS9eYcqqLVCQk8XEweYAgHtRz+B1/Bwexb7A64+fEHTnAWRkZNC2bVuYmppWKk4iOqmpqdzPvCwyMjIwb968KoyIkKoh9f1dCCFEPBhjOH/+PJydnfHy5UuuXFNTExs2bMAvv/xS6rquCQkJSE9Pr9T5paWlsXTpUgDAgwcPEB0Tg+IhAfN37AUATBo+EL7LXOBm8xOyc3Mxa7MXUjO+oHvHDgjathYN/nlkLC8rg9N/3cJKn0PIzMlBQUEh9Dp2xMWLFwUGqxDxWrRoETfnX1kdPXoUU6dOxeDBg6soKkJEj+YBJITUSLGxsZg7dy7+/PNPrkxSUhJOTk5YsWIFt5RaamoqoqKiEBkZKfDfxMTESp1/4MCB8PPzg5aWFlcWHh4OExMTnFy3DGPNelW47uJ5AG/evIlevSpeDxGt0NBQ9OzZs0LHtmvXDk+ePClz/0FCxI0SQEJIjfLlyxesXl00SXJ+fj5X3rdvX8yYMQPZ2dkCiZ6o+19JSUlh7dq1mD9/fomti/3NzfE6LhYRh7y5ZeDKIzM7B4bWM/D2UyI0tbTg5eWFcePGiSJ0Ugn5+fkwMTHBkydPKlzHihUrsHLlynIdw+fzS23FJqQqUQJICKkRGGMICAiAi4uLQFInJycHJSUlJCUllbmuxo0bQ19fHwYGBnjw4IHAcnDf0rp1awQEBKBbt26l7vP8+XN06tQJFv16wndZyUliafh8Pqas2oIjwX8JTB8yduxYeHl5oWnTpmWui4hWSEgIzM3NK1WHpKQkIiIivtn3NDw8HL6+vgi9fRuRUVHIzc2FrKwsDPT1YdqzJ6ZMmQJjY+NSjydEVCgBJISITHlaM/Ly8vDs2TNERUXhypUrOH36NJKTk8t1PjU1NRgYGHDJXvH/N2rUiNtn69atZeqkb2lpiT179kBZWfm7+x45cgTW1tawGdIf3m5OZWoJzMzOgcNGT/gFXYW3tzf++OMPBAYGcq83bNgQGzZsgL29PbUIiUFiYiK6dOnyzTWBy6JNmzZ48eKFUPnz589hP306roWEoJmmBgZ2NYKRTls0VFRAemYWIuJeIPhBBN4nJMLczAx79+1Du3btKhULId9CCSAhpMLK0prRqVMnPH/+XKifXlxcXJkn0W3QoIFAolf8Xy0tLW65t9Jcvnz5m53z5eXl4enpialTp363rq/5+/vDzs4OTdRUsdFxKkb1NoWUlKTQfgUFhTh3MxRuXr/jY0oq9u/fDysrKzDGcOzYMcyePRsJCQnc/r1798a+ffvQoUOHMsdCRCMvLw8vXrzAp0+fEB8fL7B9XZaQkAA+n19iHSoqKkhNFZwP8uvflU2O0zCyd49Sf1fO37wDV6/9Ar8rhFQFSgAJIeVWltaMoLvhiE9OgZSkJArKuPYuj8dD27Zt0atXL4FEr3nz5uVKzr724cMHNGvWrMTXOnXqhICAAOjplTxX3/f89z4MMDGCkU4bKCsp4vOXTETEvcSVsKJWnf7m5tizd69Qq05KSgpcXFzg6+vLlcnIyGDp0qVYsGABN1cgqTkKCwuRlJQkkBQ+fPgQMTExWLZsmcBAEn9/f9jY2FS4tdjPzw8TJ06syssh9RQlgISQcjl8+DCm29mhsZoKNjtN/25rhvO23XiXmAQ+/9+PGh6PJ7DKhqysLBwdHeHu7g4FBeGVNiqDMYZGjRoJtco4ODhg8+bNkJeXr/Q5iltC74SG4klkJNcSamhggB6mpmXq13XlyhXMmDFD4PGhvr4+fHx80KNHj0rHSKqPt7c3Nm3ahA8fPiA/Px+DfuiCC1tXQ0JCAjPWb8eVB4/wITEZSgry6Gmoh/UO09ChlTZ3/Jv4BMza7IWLdx6gsJAPW1tb+Pj40JcBIlKUABJCSsQYw6dPnwQe24aEhOD58+ewHtIfuxfMLnNrxq8bd+Bw0DVYWlrixIkTAo9+f/75Z2zevBna2trfqKVy+vbtixs3bgAoekRXvA5wVanoyM6srCy4u7tj8+bNKPyn1ZTH48HR0RFr1qxBgwYNRB0qEbGjR4/C1tYW3t7e2Ld3L55FP0VBQSGijuxFi8aa2HvmAjq01EaLxhpISc/Abz5+eBT3Ei9PHoCkpCQKCwvR5ZdZ0FBVxir7SbBYvAYpGRmwt7eHp6enuC+P1CGUABJCkJycLDSPXmRkJFJSUoT2Hdm7O05vWMElOLl5eXDx9EHA5RBk5+ZiQNfO2OnqiOaaRStzJH9Oh/WKDbjx6Amyc/O4ejp06ABvb+9Kj7wsi1OnTmHKlCno3r07fHx80KJFiyo/Z2U8fPgQ06dPR1hYGFemra0Nb29vjBgxQoyRke/p3r07jI2NYWdnh65du+LkumVYsvsARvc1xTqHqUL7P37+Ep1tHRB3/He0bd4Uf4bex0iXFXhz5hCaajTi5oyUkZFBYmIiGjZsKIarInURJYCEfENdm6Pr8+fPiIqKEkr0yrLygQSPB1kZaagrK+NpwD6u9e/XjZ744+Zd+C6dh0bKDeHiuQ8p6Rl44OsJSUlJpKZnICD4Lxi0aQWblRvBk5VFfn4B+vbti4CAgKq+ZE5t+1kWFBRg+/btWLZsGbKzs7lyS0tLbN++XWCCalIz5OXlQUFBAcePH8fVq1dx5vgxvDzhi/meexER+xIhuzYJ7J+ZnYOlew7i3I1QRAfsg4y0NJbv/R/O3QjFo0O7ABR1pWg59hd8TErG1atXq+ULE6kfas+nISHVIDw8HE5OTuhqYgI5OTlISkpCTk4OXU1M4OTkhPDwcHGHWCaZmZm4f/8+Dhw4ABcXFwwbNgza2tpQUVFBr169YG9vjx07duDKlSulJn9NmzbF4MGD4ezsjGXLloHPGHa6OOJtQiLCYuIAAJ+/ZOL380HYPHs6BnYzRhfddji0wg1PXrxC8P2HAADVhg3w67gR6NPZAFvn2uPNm7ewtrYu89x8olKbkj+gaELq+fPnIzIyEoMGDeLKjx49Cj09Pfj6+oK+v9csSUlJKCwshJaWFkJv38YAk06QkpKElqoq4r9qTfc+eR4N+o9Bg/5jEHTnAS5tXwsZaWkAQHxKKrTUVLl9paQkMeiHLuDxeIiPj6/2ayJ1F60FTAhKHtVq3WeywKjW08eOwsvLq0bN0ZWTk4Nnz54hMjJSoEXv1atXZU4ONDQ0hKZY0dfXh6rqv3+EnJyc0FxLEz0MikbLqjUs6osWFhOH/IICDO727wCHphqNYNCmJW4/icaQHl0FzjWqtykaN1KDv78/tWSUUZs2bRAUFAQ/Pz84OzsjOTkZqampmDp1Kvz8/LBnz54a8btI/sXj8RAZFQXrPpMBAAwMPPw7it16SH8M6maMj0kp2OJ/ApZL1+LmHg/Iycr8c7xgfUY6bfC/P4MrPBKekJJQAkjqva/n6Dq5blmZ5ujq1KlTtc7RlZ+fj9jYWIFHt1FRUYjTwuAbAAAgAElEQVSLiyt1PrL/UlFREZpHT19fH5qamt89NvT2bfQ3NsSCnT7obaQPg7atAADxyamQkZaGakPBwQlaaqqITxbsPzhx+TqcvX4H2bm5UFZWho+PT9kunoDH48HW1hZDhw6Fs7MzDh8+DAC4evUqDA0NsXLlSsybNw/S/7QiEfFQV1eHpKQkPnz4gNzcXDRULBrRnpCaJtCqp6ykCGUlRehoN0MPgw5QG2yB03/dgtVgczRWU8W9qBiBeqUkiz6PNDQ0qu9iSJ1HCSCp18ozR5eUlCTGmvXC4O4mcNjoCWtrazDGRDpHV2FhIV6+fCnQmhcZGYnY2FiBdXG/RUlJCR07dhRK9Jo2bVrhFoTIqCjIFbTFu4Qk3Niz5bv7M8aEzuUxZwaWT7XBJr/jOHDhMubNmwdvb+8KxVNfaWhowM/PDzY2Npg5cyZev36NnJwcLFy4EAEBAfDx8YGJiYm4w6y3ZGRkYGJigitXrkBWVhbpmVkAgOB7DzGqT+lT+TAG5P7z/jY11MPagwH4mJSMJupFK9rcj44FAPzwww9VfAWkPqFBIKTe+dYcXXvPXMCRS9cQ/uwFMrKykHLpBFQaKAkcP9p1BR7FvcT7xGTw+XyMHj0a3t7e5VrHlc/n482bN0Ijb6Ojo5GTk1OmOuTk5KCnpyeU6LVo0UKk/d34fD4kJSWh2kAJDw54oXXTxtxrVx88wkCnhUgOOi7QCtjZ9leM7tsTv023Farv9/NBsFu7FUDRJM1NmjQRWaz1yZcvX7B8+XJs376dawWWkJDA3Llz4e7uDkVFRTFHWD8VTwPTtEkTdG7VDK2aNIbPuT8ReXgPCvl8HA3+C4O7m0BDRRnvE5Ow0e84bjyKxNMj+6CppsJNA6OlpoKNjnZISc/AaLeVUGrQEJ++WjGGkMqiFkBSrxw9ehRz584VmKPr1uOneJeQhBaNNZGVk4shPbpiSI+uWLzLt8Q6zIyNsGjSBCgrKmLQ7MW4du0aLCwscPv2baF9GWP48OGDUKIXFRWFzMzMMsUsLS0NXV1doUSvTZs2kJQUflQtSowxzJ49GwAwc+wIgeQPAEw66EBaSgqX7z3EzwP7AgA+JiUj8uVrbJg1rcQ6P3/JhLS0NPLz85Gbm1ul8ddlSkpK8PDwgJWVFezs7PD48WPw+Xx4eHjg1KlT2LNnzzeXwCNVw9LSEsnJyVi4cCHOvnmDLu3bInDLKrRsooUPicm4GRGF7UfPIDXjC7TUVNC3syFu7fWAppoKAEBSUhJ/bHHHrE1e6D1jPuRlZcDj8TDewkLMV0bqGmoBJPVKWefoCgmPQP9ZC0psAfxa8RxdPB4Pb9++xbNnz4SmWPn8+XOZYpOQkICOjo5QoqejoyO2vl0ODg7w9/eHlqYmOrdojG3OvwIAlBUVIS8nC6BoGpjAW3fhu3Q+1Bo2gKunD5LT07lpYC7cvodPKWn4Qa89lBTkYLdmG25HxcDExAQ3b94Uy3XVNfn5+diyZQtWrlwpkFTb2trCw8MD6urqYoyufgoPD4eJiQlOrluGsWa9KlxP8WdMWFjYd1eTIaQ8KAEk9UZ55ugqawKYkJKGVuN+QX5BIbdyw/fweDy0bt1aKNHT1dWFnNz3V9aoTqX1Gfx96TxM/rGodSknNw+uXj44cukasnPzuImgtbWKOqxfC4vA0t0H8PTVG+Tm5SO/sBBGRka4cuUKVFRUqu1a6oO4uDjY29sjJCSEK1NXV8e2bdswceJEGkVaxf7b97W/uTlex8Ui4pB3mVbN+a/M7BzoW01H4ucMBF64QCPniUjRI2BSb5R1jq6yWLBzP3aeOIesnFyoqygjJT29xP20tbWFEj09Pb1a0z+r+Pvht1oz5GRl4DnfAZ7zHUqsw9zECLf2FfX5K27N6Ny5MyUjVUBHRwdXr17F77//DhcXF6SlpSEpKQk2NjY4dOgQdu/ejVatWok7zFopKysL79+/x7t37/D27Vu8e/eO216/fo24uDhkZ2ejS5cu3Hyhe/ftQ6dOneCw0RO+y+aXq28un8/Hrxt3cOtoDxgwAG5ubnB3d6c1gYlIUAsgqTc+fPiAZs2a4fbt2zA3N8e6mZMxd8JYrDlwBH5/XkH00X+nJfleC2BS2mekpGfgdXwCZqzfjlcfP6F///4wNDTkkr2OHTtCWVm5Oi9RAGMMUVFRSEtLQ3Z2NrKysr773+L///TpE16+fInWrVvjr7/+grS0tEhaMwxtZuJtfAIK+Xw0btwYW7duhaWlJSWDVSA+Ph6zZ8/G8ePHuTIFBQWsXr0as2fPrvL+o7VRfHw8goKChBK8t2/flrgsYkl4PJ7A1ExHjhyBtbV1mWYaKJaZnQOHjZ7wC7oKPT09PH36lHvNxMQEhw8fhq6ubvkvkJCvUAsgqTfKOkdXmepSUYa6ijLat2gOh/Ej4eblA3d3d/TqVfG+PqJmYWGBU6dOVaqO+Ph4+Pn5YcqUKZVuzXDY6In4lFTIyMoiOzsb8fHxsLKywu+//46dO3dCR0enUrESQY0bN8axY8dw/vx5ODg44N27d8jKysK8efPg7+8PHx8fGBkZiTvMGiMjIwMdO3ZEampqper5etUWALCysgJjDHZ2drj1JBobHadiVG/TUucaPXczFG5ev+NjSioOHz4MS0tLbNmyBUuWLEF+fj7XF3Dbtm2ws7OjL0+kwmrX2kikXmKMwc/PD+7u7jh06BBu3bqF+Pj4ci+D9a05ukwN9SocX3E9ZZ2nr7o8fPiw0nVISkpiyJAhAIB27dph//798Au6iimrtiAzu2zT1WRm52DKqi3wC7qK33/3RUxMDMaMGcO9fvnyZRgaGsLd3Z1GBVeBkSNHIioqCrNmzeKShQcPHsDExASLFi0SWGe4PmOMISMjo1J1qKqqcutb37hxA6dPnwYATJw4EY8fP0ZLnfawWLQarcdPxmT3zdh65BR+Px+ErUdOYbL7ZrQePxkWi1ajVXtdPH78GFZWVpCQkICrqyvu3LnDtfplZWXB3t4e48ePR3JycuUunNRfjJAaLjg4mAEQ2hQUFJiBgQEbNWoUmzt3LvP09GSBgYEsJiaG5eTklFhXQEAAk5aWZi1btGCj+5qyOZZjmaK8HPv71EHGD73IPvzhz8IP7mR7F81hANhfuzaz8IM7WdLF44wfepHd8dnOdsxzYOEHd7K/Tx1kV7w2ME1VFSYrK1vqOcVl/fr1Jd638mwBAQFC9R4+fJjJy8uzNs2ashPrlrK8G4GMH3pRaMu7EchOrFvK2jRryuTl5Zm/v79APWfPnmUtWrQQOF/79u1ZcHBwdd2ieufWrVusY8eOAve8Xbt27OrVq+IOrUZYuHBhpd4v+/btY48ePWJ9+/blytatWydwjrCwMObo6Mi6mpgwWVlZBoDJysqyriYmzNHRkYWFhZUa35cvX9iMGTMEztm0aVN6z5AKoQSQ1Hg3btwo9wcxj8dj2trarG/fvmzIkCHMysqKvX//njHG2M6dO1mDBg0YANalfVsW4r2JS1qWT7Musb7fl85j/NCLLOLQLmZuYsTUGjZgsjLSrFUTLaYoL8cmT54s5rskLCsrizVv3rzCf8wmTZpUat1xcXHM3MyMAWDNNDXYL8MGsi2z7ZnPYme2ZbY9+2XYQNZMU4MBYP3NzVlcXFyJ9Xz58oW5ubkxKSkpgXNPnDiRffz4sYruTP2Wk5PDfvvtNyYjIyNwz6dOncpSUlLEHZ5YZWVlsfbt21fo/aKvr8/Gjx8vVD516tRvnrOwsLDccZ4+fZo1atRI4PPO1dWV5ebmVvTSST1Eg0BIjVdYWIjmzZsjPj6+UvW0b98ez549A1B/5ug6ePAgJk+eXO7jWrZsiYiIiO8OYgkPD4evry/uhIbiSWQkcnNzISsrC0MDA/QwNcWUKVPKdF+ePHmCX3/9Fbdu3eLKlJWVsW7dOtjb29OAhSoQHR2N6dOnC9xzLS0t7NixAz/99FO97Vt2/fp19OvXr9zH8Xi8Erul/Pnnnxg6dKgoQhPw4cMHTJ48GZcvX+bKunTpAn9/f3To0EHk5yN1DyWApFaYM2cOduzYUak6TE1NBVbrEMWoViNbB7TUaY+r165VKraqUlhYCGNjYzx+/LjMx/B4PFy7dq1CfwT5fH6Fl6Hj8/nw9fWFm5ubwIjLbt26Yffu3ejSpUuF6iWl4/P52Lt3L9zc3AT6v40cORI7d+6Etra2GKMTn19//RW7d+8WSV0fP35E48aNv79jBfD5fGzbtg2LFi1CXl4eAEBeXh5bt26Fvb19vU3iSdnQIBBSK0yYMKFSxxsaGiI4OFigbO++ffiYkgqHjZ4C0zaURfGo1o8pqdi7b1+lYqtKkpKSWLBgQbmOmT9/foWSPwCVWoNYQkIC06ZNQ0xMjECr5b1799C1a1c4OztXupM+ESQhIYGZM2ciOjoao0eP5srPnz+Pjh07YufOneV+b9QFNjY2Ill9R11dHVpaWiKIqGQSEhKYN28e7t69Cz29ooFs2dnZmDlzJsaOHYukpKQqOzepA8T6AJqQMuLz+UIDBsq6mZmZsczMzBLr9ff3Zzwej9kOHcAyrp4pcTDDf7eMq2eY7dABjMfjCQ1sqEnS0tLY4sWLmby8fJnvlYGBAcvOzhZ36IwxxkJCQpienp5AfM2aNWMnTpxgfD5f3OHVOXw+n504cYI1btxY4J6bmpqyyMhIcYdXLbKzs9nixYuF+qRWdDMzM6u22DMzM9mvv/4qcP7GjRuzS5cuVVsMpHahBJDUCi9fvhQYWVfWrU+fPuzLly/frFtUo1pritzcXLZjxw6mrq5ernslLS3NHj16JO7wBeTm5rJ169YJJbHDhg1jL168EHd4dVJqaiqbPn260O/G8uXLa9xId1G6ceMG09XVFbhuZWXlSiWATk5O1X4d586dE3rvz5s3r07/7EjFUAJIaqx3796xrVu3su7du1fow7dnz54sPT29TOcS1ahWceLz+ez48eOsXbt2Qn+8nZ2d2c8///zN+7V+/XpxX0KpXr58yYYPHy4Qr5ycHFuzZg2NfKwiISEhQiNiO3TowG7cuCHu0ETq8+fPzMHBQeg9s3LlSvb69WsmISFR4QRw7969YrmmDx8+sMGDBwvEYmRkxKKiosQSD6mZKAEkNcqnT5+Yt7c369u3L+PxeBX+4O3evTv7/Plzuc//9RxdxdNkSEpIMBNj4+/O0SVO169fLzFRtrKyYi9fvmSMMfbq1Stu3rH/br1792YFBQVivopv4/P57OTJk6xZs2YCsevp6bGQkBBxh1cnZWdnsyVLlgg9Ep05cyZLS0sTd3iVFhgYyLS1tYU+O4ofeWdnZzMFBYUKfw6FhoaK7doKCwvZ1q1bBab7kZOTYzt37qQuFIQxRgkgqQFSUlLY/v372aBBg0r9tm1kZMTWrl3LZs2a9d0P3R9++EEkf5w2btzI1fnnn3+K4EpFLzo6mo0ePVroHpiZmbH79+8L7e/q6iq0r5KSEpck1gbp6enM2dlZ6Hdl0qRJLCEhQdzh1UkRERGsW7duAve7adOm7PTp0+IOrUISExOZtbXgnJ8KCgps69atQl+Erl69KjRnYlm3sj6BqEoRERFCk3+PHDmS3iuEEkAiHunp6czPz4+NGDGCSUtLl/jhqaury1asWMGePn3KHRcZGfnND1xjY2ORTWa7a9curl4fHx+R1CkqHz9+ZDNmzGCSkpIC16+vr88CAwNL/YafkpLCVFVVBY7Zv39/NUcvGuHh4UJJiaqqKtu3b1+FJtcl31ZQUMC2bdvGFBUVBe75uHHjuEnWazo+n8/8/f2F+sgNGjTom1+C7t+/L/Re+97WunXraryyb8vKymKOjo4C8WlpabGLFy+KOzQiRpQAkmqTmZnJjh8/zsaPH8/k5ORK/dBcuHAhe/ToUalJjL6+fonHdu7cmSUnJ4ss3tOnT3N1r1q1SmT1VkZGRgZbsWKF0B/hpk2bsv3795fpMe6WLVu440aNGlWrHwcVFBSwXbt2CXXWNzU1ZREREeIOr0569eoVGzZsmMD9VlZWZnv27KnRifebN2/Yjz/+KPSF4cCBA2V6D/zvf/8rV3/AUaNGVcNVlc8ff/zBNDU1BeKcO3dujRn5T6oXJYCkSuXk5LBz586xiRMnCiUtXycvzs7O7O7du2X6IF61apVQHYaGhiwxMVGksd+5c4er38HBQaR1l1d+fj7bvXs309LSErjuBg0asDVr1pQ6zU1J8vLymKurK5s2bZpIE2Zxio+PZzY2NgL3RlJSkrm4uLCMjAxxh1fnFLekaWhoCNzzvn37spiYGHGHJ6CwsJB5e3tzyz8Wbz/99FO5lxvMzs5mhw8fLlP/5MWLF1fRFVVOfHy8UALfqVOnejPVD/kXJYBE5PLz81lQUBCbMmVKqdMoaGhoMAcHB3b9+vVytxrExsYK1NWxY0f26dMnkV/H69evuXOMHTtW5PWXBZ/PZ2fOnBGankJKSoo5OjpWyXXXZleuXBEauaqtrc3OnDkj7tDqpKSkJDZp0iSB+y0rK8tWr15dI0Znx8TEsD59+gjE16RJkwr3XczJyWHGxsZlagE8cuSIiK9GdPh8PtuxY4fAoDA5OTnm6elZq58IkPKhBJCIREFBAQsJCWEzZ84sdf45FRUVNm3aNHb58mWWn59fqfMNGjSIAUXTUsTHx4voKgTl5uYKPFKsbqGhoax3795C99HCwoLFxsZWezy1RU5ODnN3dxca8Txq1Cj26tUrcYdXJ126dIm1bt1a4H4bGBiwO3fuiCWevLw8tnbtWqHfATs7O5aamlrheufMmcPVpaOjw9avX19qH+ba0KL25MkTZmBgIBD38OHD6YtlPUEJIKkwPp/PQkND2Zw5c1iTJk1K/BBUUlJiNjY27I8//hBpi8Dnz5/Zn3/+Wa5HnxXRqFEjBoC1atWqSs/ztdjYWGZhYSF0L3v37i3WaSVqm7i4OKG50BQUFNjGjRtZXl6euMOrczIzM5mrq6tAPzkej8dmz55draNhw8LCWOfOnQV+7m3atGFXrlypVL1nz54VaOV8+PAhY6xogEibNm0EzictLV1rfseys7PZ7NmzBeLX1NRkFy5cEHdopIpRAkjKhc/ns/DwcObm5sZatmxZYtInLy/PfvrpJ3by5EmWlZUl7pArpfjbsaysbJU/GklISGCOjo5Cc67p6uqyM2fO0KOZCuDz+SwgIEBoeTMDAwN28+ZNcYdXJ4WFhbEuXboI3O8WLVqwwMDActXz4cMH9ubNmzLvn5WVxdzc3ARG60pISDAXF5dKf1F8/fq1wOj5nTt3CryelpbGLC0tude7detWqfOJw4ULF4T6GDs5OdX6z3BSOkoASZlERUWxZcuWMR0dnRKTPmlpaTZq1Cjm7+9fpzrdDxw4kLtGUU0v81+ZmZlszZo1Qp3UtbS02O7duyv9uJwU/YF2cnIS6rxvZ2fHkpKSxB1enZOfn882btwotISflZVVmR4v3r17lykqKjIZGRl2+fLl7+5/7do1oRVwOnXqVOJcmOWVl5fHevbsydU7fvz4Er+M8fl89r///Y9NmDCB3bt3r9LnFYdPnz4JjZQ2MDBgjx8/FndopApQAkhKFRcXx1avXs0MDQ1LTPokJSXZkCFDmK+vb6X61dRktra23PWKehmlgoICtn//fta0aVOB+6qoqMhWrFhRpxLpmuL+/fvMxMRE4H6rq6szX19famGtAs+fPxf4EgWAqampfXPqldzcXIF+ae3atSt1Hdu0tDRmb28vUL+MjAxbvXq1yB7BLlq0iKu7VatWdfazrhifz2deXl4CU3XJysqybdu20XukjqEEkAh4/fo127Rpk9Afya/79JiZmbHdu3fXi5nk3dzcuGsPDg4WSZ18Pp8FBgYKzWcoKSnJZsyYwT58+CCS85CSFRQUME9PT6EW1759+9JaqVWAz+ezAwcOMDU1NYH7PXDgQPb8+XOh/Uua5mn16tVC+509e1ZoWcCePXsKTBxfWUFBQVyrsZSUlNgGtYhDZGQk69Spk8D9HTp0aLmnziE1FyWAhH38+JHt2LGD9erVq8SkDygaBbt9+/ZaM+O/qGzdupW7B35+fpWu7/79+8zc3Fzo/o4ePVqkf7jI971//16g31bxH/lFixZV+eCi+ujTp0/MyspKqL/wxo0buW4O0dHRJS67Ji8vz43g/vTpk9DPTUlJiXl6eop0IuqPHz8KTJq8adMmkdVdW2RnZzNnZ2eBe62hocHOnz8v7tCICFACWE8lJiayPXv2MHNz81Jntzc2NmYbN26s11NnBAQEiOQPwMuXL4X++AFFC89fv35dhBGT8rp48SJr27atwM+lVatW7I8//hB3aHVSYGAga9GihcD97tKlC7t//77QnH1fb+PGjWMHDx4UakkcNmwYe/36tUhjLCgoYP379+fOMXz48Bq9yklVCwoKEhpINWvWLBogUstRAliPpKWlsQMHDrChQ4cKjTQt3vT19dmqVatonrl//PXXX9y9mTdvXrmPT0pKYs7OzkKtGm3btmXHjx+nPjU1RFZWFlu2bJnQnG7jxo1jb9++FXd4dU5GRgabM2eOwKCcsqyu8fXWqFEjdujQoSp5D339GLpp06YiX2WoNkpISGCjRo0S+Bl07NiRPXr0SNyhkQqiBLCO+/LlCzty5AgbPXp0iY9WgKJO1kuXLmVPnjwRd7g1zrNnz7j7ZGVlVebjsrKy2IYNG4RWQlFXV2eenp41YpUEIiw6OlroEb2SkhLz8PCg0dhV4M6dO6UOMvvWNmHChCqbrPj69evcUxEJCQkWEhJSJeepjfh8Ptu1a5fA6G4ZGRnm4eFRr1tIaytKAOug7OxsdurUKfbzzz8zBQWFEj9AW7RowVxdXVlYWBi1Qn1Deno6d8/MzMy+u39hYSE7ePAg09bWFrjfcnJybPHixSwtLa0aoiaVwefz2aFDhwT6fwFgRkZG9WoQQHXJy8tjHTt2LHPyZ2trW2WxJCYmCgws+e2336rsXLXZ06dPhSbbHjx4MA1gq2UoAawjcnNzWWBgILO1tRUa3Vi8NWnShM2ePZvdvn2bvq2Vg6KiIgOKJmT+lkuXLjEjIyOBe87j8djUqVPpMWItlJKSwmbOnCn0mHLmzJlVNidkfXTy5Mlytf4pKCiIvM8fY0WJ/9dz4Jmbm7OCggKRn6euyMnJYfPnzxd6wnH27Flxh0bKiBLAKlTVSVZBQQELDg5mdnZ2Qh2jv+4nM2PGDHbt2jX6MKug4glmlZWVS3z90aNHQkuOFXccpwlUa7/Q0FChxF5TU5P5+flR63klpaamlrqM5Lc2CwsLkceyZcsWrn4NDQ1qzSqjy5cvC/0MZ86cSSPpawFKAEUoLCyMOTo6MhNjY24RcllZWWZibMwcHR1ZWFhYpc9RWFjIbty4wWbNmiW0bE/xpqyszCZPnswuXrxYa9ajrMm+Hpn49ai3169fs19++UWo87qxsXGl1x0lNUt+fj7z8PDgWoOLt/79+7OYmBhxh1drzZgxo9zJX/FWlhVCyuru3bsCA4AuXrwosrrrg8TERDZ69GiBn0+HDh1YeHi4uEMj30AJoAjExcUxczMzBoA109Rgk4YPZB5zZjCfxc7MY84MNmn4QNZMU6PosYKZGYuLiytX/Xw+n927d4/Nnz+fNW/evMQPQ0VFRWZlZcXOnj1b6qz5pGJ+/vln7j6/ePGCpaamMjc3Ny7JL95atmzJDh8+TI/X67A3b96wcePGCfzcZWRk2PLly1l2dra4w6tVvh5hX5FNV1e33IOpSnpvpqWlsdatW3P1LliwQFSXWK/w+Xy2Z88egQEi0tLSbNOmTfSZWENRAlhJhw8fZvLy8qxNs6bs5LplLO9GIOOHXhTa8m4EspPrlrE2zZoyeXl55u/v/816+Xw+i4iIYIsXL2Zt2rQp8QNQVlaWjRs3jh07doya26vQ7NmzuXvu5OQk9LhdVVWVbd68mRLveuT8+fOsZcuWAr8Hbdu2ZUFBQeIOrdYYMmRIpRJAoOQVQr5Wlqcyc+bM4eozNTWlpyaVFBMTw4yNjQV+TgMHDqx3iwjUBjzGGAOpEH9/f9jY2MBmSH94uzlBUV7uu8dkZufAYaMn/IKuws/PDxMnThR4/dmzZzh69CgCAgIQHR0tdLy0tDQGDx6MCRMmYNSoUWjYsKHIroeUbN26dVi8eLFQuaysLGbPno1FixZBVVVVDJERccrKysKqVauwefNmFBQUcOWWlpbYunUrmjRpIsboarZTp07B1tYWWVlZlapHQkICz549Q7t27QTKnz9/Dvvp03EtJATNNDUwsKsRjHTaoqGiAtIzsxAR9wLBDyLwPiERmpoaSEhIhIqKCh49eoSWLVtWKiYC5OXlYdmyZdi0aROKUww1NTXs378fY8aMEXN0hCPmBLRWWbt2LevatStTUlJiampqTEJCgo3q3YMV3LrAtfTtXjCb9etiyBr8M/1KyqUTQq2BI3p1Zwpyslxn4zFjxrDFixcLDasv3iQkJNjAgQOZj48PS05OFvdtqFeuXbvGWrVqJfDz4PF4zNbWtl6vkEL+FRkZKbSCRcOGDZmnpycNvPqPDx8+CD1Cl5OTYz/99BNzcXFhEydOZGZmZkxHR6fUKaz+uy1dulTgHOV/KtOEyUhLMw8PDzHdlbrrypUrQus129vbsy9fvog7NMKoBbBchg4digkTJuCHH37AlMmTERX5BI0aNsTTgH1c69+2gNPIycsDACze5YuUSyeg0kBJoJ6tR06hc/u2mLxqCwp4EvgYHy90Lh6Phz59+sDS0hLjx4+HlpZW1V8g4URFRWHBggUIDAwUKG/VqhVOnTqFLl26iCkyUhMxxnDw4EG4uLggOTmZKzcxMcGePXtgYmIixujEjzEGX19fzJ8/H2lpaVz5iBEjsGvXLjRv3rzEYz5//k9elxkAACAASURBVIz3798LbB8+fEBMTAwiIiLQsGFD3L17F5qamgCq5qkMqZzk5GTY29vj1KlTXJmuri78/f1hbGwsxsgItQBWwIMHDxgA9vuSeQwAC/HeJPTt8urODaW2ABZvJ9YtFfo22717d+bh4UHzxonJ+/fv2bRp00pdH3ny5MniDpHUYElJSWzatGlCLfhOTk5lngT83bt3bMSIEWz69Ol1ol/pixcv2MCBAwXuiYaGBjty5Eilp9H566+/2IgRI7hpSGRkZJjt0AHcU5nl06yZbovmTEFOlqk0UGIDunZmoT7bBD6Hk4OOM+sh5kxaSpIBYKNHj2apqakiunrCWFGfdh8fH4FWXWlpabZhwwYaICJGEtWZbNYVBw4cQHMtTfQw0AMAqDVsUKF6RvU2ReNGqlBSUkLLli3x8uVL3LlzB87OziV+IyZVJz09HcuWLUO7du2wf/9+8Pl8AEDz5s3h6enJ7RdfQmstIcUaNWoEHx8f3Lx5EwYGBgAAPp8PT09P6Onp4dixY1yfqJIwxjB16lT88ccf2LdvHzZs2FBdoYtcYWEhPDw8YGhoiODgYK7cxsYGT58+xYQJE8Dj8Sp1jszMTBgZGcHLywsAoNZAEd5uTpCQKPrT1l67OTznO+Cx327c2L0ZLZtoYcicxUhM/bcV0nrFBkTE/Y0/t65BU3V1BAcHw9bWtlJxEUE8Hg/Tpk3Dw4cP0bVrVwBAfn4+FixYgEGDBuHdu3dijrCeEncGWhuZGBuzX4YNYCN7d2e9jfRLbN37Xgugq81PXD9ARUVFlpSUJO7Lqpfy8vKYl5cX09DQEOrDtX79epaVlcUKCwuZlJQUA4qWAyOkLPLy8tjGjRuF+rINGTKEPX/+vMRjAgIChEb6x8bGVnPklff48WPWrVs3gWvR1tZmFy5cqJLzFT+VcbP5qdQnLvzQiywtuGjVkcs71jF+6EUWdWQvA8C1Cn79VIbmd6waubm5bOHChQLzp6qqqrKTJ0+KO7R6h1oAKyAyKgov3n/E4+d/w999YYXqcLW2QPjBnbAfMxxZWVn45ZdfvtkyQESLMYaTJ09CX18fjo6OSExMBFA0ynru3Ll48eIFFixYAHl5eUhISKBx48YAgI8fP4ozbFKLSEtLw9XVFU+fPsXIkSO58qCgIOjr62PVqlXIzc3lyj9//oy5c+cK1JGbmwsHB4da89mQm5uLFStWwNjYGPfu3QNQ1Prj6OiIqKgoDBs2rErOe+DAAQDAD3q6pe6Tl5+PvWf+hLKSIox02gAAQp9EQ1lJEd31OwAoeirTTFMDMjIyuH37dpXEWt/JyMhg3bp1uHr1KvekKzU1FePHj4ednR2+fPki5gjrD0oAy4nP5yM3NxdP/36Dqzs3ormmRoXqUVdRRvsWzdGtoy4YY7hw4QLu3Lkj4mhJSW7duoWePXvCwsICcXFxXPmECRMQExODrVu3Ql1dXeCY4ik9EhMTBab8IOR7WrZsiXPnzuHMmTPQ1tYGUJQoLV++HEZGRrh69SoAYOnSpSV2MQgODsaRI0eqNeaKCA0NRZcuXeDu7s69Rzp06ICbN2/C09MTDRpUrKtMmc79T7ImKSn8J+2Pm3fRoP8YyPcbhW0Bp3Fp+1qoqygDAOKTU6GpqsLtKyUliQEmRuDxeNTdo4qZmZkhIiICFhYWXNn+/fthbGyM+/fvizGy+oMSwHJgjGH27NkAgJljR6B108aVrvPzl0zIyMgAgEBrABG9Z8+eYdy4cejdu7dAst2vXz/cu3cPR44cQZs2bUo8tjgBZIwhISGhWuIldcvo0aPx9OlTuLi4QFJSEkDR7+SAAQMwfPhw7Ny5s9RjnZ2dkZqaWl2hlsuXL18wZ84c9OrVi5u7VEpKCkuXLsXDhw/Rs2fPKo8hMiqq1NfMTYzw8KA3bu31wJAeJrBcuhYJKf/2AfxvN0QjnTbIy8urdP9E8n1qamo4duwYfH19oaioCACIi4tDz549sW7dOhQWFoo5wrqNEsBymDVrFvz8/NBeRwcv3r9HfHIK4pNTkJ3zb+IWn5yCR7Ev8PzdBwDAkxev8Cj2BVI+ZwAA7kU9g9fxc3gU+wKvP35C0J0HkJGRQdu2bWFqaiqW66rrPn36BAcHB+jr6+P06dNcuZ6eHs6fP49r1679n70zj6sp/eP4u0WLIpSiRCK7UtnHUhjbWGeQZB3riB9j33cydhMiGsYky2BmzBjLGMPYl5rshuxSCtnab/f8/mg6ugqV6t5bz/v16uV2zvM893uu7rmf+32+C/Xq1XvvGumL+optYEFOMTU1ZfHixYSEhKi83/ft2/febd6oqKhMi5GrmwMHDlCrVi2+/fZb2f66desSHBzM3LlzMTL6cBmWjyVtV+ZdmBgbUdnWmoa1qhMwdQz6enoE/LofgDLmJXmcTgwCmJmaIEkSpUvnbHdHkD10dHTo378/oaGh1K9fHwCFQsGUKVNo2bIlDx48ULOFBRchALOBn58fL1684MbNm+z48xjWHXph3aEX2/88Ko9Z+9NeXPp5M8RnJQDNvxqHSz9v9hw/BYCxoQE/HT1Bq5GTqNZzEH+eD8XOzo6jR49iaGiolusqqLx+/Zo5c+ZQqVIl/Pz85G+TZcuWZf369Vy8eJEOHTpk6Zu+EICC3MTR0ZHjx4/j7++PsbFxluasW7dOY8JEnj59Sr9+/Wjbti337t0DwNjYmCVLlnDq1CkcHR3zzRZdXd1s3TslSSIxORmARrWr8+J1LGev/Cufvxh2B4AmTZrkrqGC91K5cmWOHz/O1KlT5Xvy0aNHcXR05Mcff1SzdQUTUQg6B4SEhODq6soun+l0dfskx+vsPnKcbpPnERwcLApi5iIKhYLvvvuOmTNnqsTxmJqaMnHiRL7++mt5uyGrrFu3jmHDhgHg7+/P4MGDc9VmQeHk0aNHVK1aNcuB746OjgQHB6Ovr5/HlmWOJEn8+OOPjBw5UiUUwt3dnfXr11OpUqV8tef169eEhYXRy9OTa9evs/R/Q3B3daJU8WKYmxVn/qatdGrakLLmpXj68iVrdv3GlgOHOb/Rl5r2dgC0/3oaj548Ze3E1PCe9mOmI+nqqRSsFuQvf//9N3369OH+/fvysQEDBrBy5co8jSUtbAgPYA5wcXHB3c2N8asCiI1PyNEasfEJTFj1He5ubkL85RKSJLFnzx5q167N0KFDZfGnr6+Pt7c3t27dYtq0adkWfyA8gIK84euvv85W1uPFixdZuXJlHlr0bsLDw+nSpQseHh6y+DMzM2PDhg38+eef+S7+AM6fP4+zszPXrl8HYOy3/rj082bm+s3o6ery770HdJs8j6oeg+g4biZPnr/gb78lsvgDCJw1kdqV7GgzaiptRk0hMSmZHj165Pu1CN7QrFkzLly4gIeHh3xs48aNODs7y9nlgo9HeABzSFhYGI6OjnRr3piN08fKhUezglKpZMDcpew8epKLFy9maGQuyD5nzpxh/PjxHDt2TOX4559/jo+PD1WqVPmo9c+dOyfHpwwbNgw/P7+PWk8g2L9/f47KopiYmHD16lXKly+fB1ZlRKlUsmHDBsaPH8/Lly/l4126dGH16tVYW1vnix3vQ+zKFEwkSeKHH37A29tb/qKkp6fH7NmzmTRpkpxM9SFiY2MpWrSoSOx5C+EBzCFpHSMCDxxmwNylWfYExsYnMGDuUgIPHCYgIECIv48kLCyMHj160LBhQxXx17hxY06cOMGuXbs+WvyB8AAKcpf4+Hi8vb1zNDc2NlauRpAd0rrbZIebN2/SokULhg4dKos/KysrfvzxR3bv3q0R4g/ErkxBRUdHh759+xIaGkrDhg2B1A4z06ZNw93dXWWL+F3873//w9TUlBEjRuS1uVqHEIAfgaenJ4GBgew8ehKnPsPZfeQ4CkXmaesKRQq7jxzHqc9wdh49yZYtW/D09MxniwsO0dHRjBo1iho1aqgECFepUoXdu3dz/PjxXC0/YWVlJX97FPXBBB/L0qVLuX37do7n//LLL/zyyy/vHRMSEsLIkSOp6+qKkZERenp6GBkZUdfVlZEjRxISEvLOuQqFgkWLFuHo6MjRo2+S3Pr378/Vq1fp1q2bxnlT/NevJ+JZDMMX+WZb7CqVSoYv8iXiWQz+69fnkYWCnFKpUiX+/vtvpk+fLu+2HTt2DEdHR7Zv3/7OeVu2bJFbea5Zs0Zjkqg0BbEFnEMkSZJvgGFhYQwZPJi/jhzBxrI0LV2dcHKwx8zUhBevY7lw8zZ/Bl8gPCqaFu7urPP3F56/HBIXF8fKlStZuHChynaUpaUls2bNYtCgQRQpUiRPntvS0pLo6GjKly8vZz4KBDmhQ4cO7N2796PWMDEx4dGjRxQvXlzl+Nv3o1Z1nXByqERxk6K8jI3jws1bHDqfej9yd3PDf/16lftRaGgoAwcOVBGIdnZ2+Pv78+mnn36UzXnN1q1b8fLyonebFqyZMBIT4w+XoYmNT2D4Il8CDxwWX8y1gOPHj9O7d2+Ve3Dfvn3x9fVVeS/cuXMHJycnXr16JR9zc3Pj8OHDGvflRW3kb+c57efvv/+WypcvLwGSl5eXyrng4GBpxIgRUl1XV8nQwEACJF0dHalqFQdpxIgRUnBwsJqs1n4UCoX03XffSTY2Nir9RYsWLSpNnz5devnyZZ7b4OjoKAGSgYGBpFQq8/z5BAWXc+fOSe3atZOqV68ulSpVSuVvOjs/Y8aMUVl3y5YtkrGxsWRvYy3t8pkuJR3bm2lP3KRje6VdPtMlextrydjYWAoKCpLi4+OlKVOmSHp6evL6Ojo60ujRo6XXr1+r6ZXKPulfg50+0977Guz0mabyGgi0g+fPn0u9evVSeS/Y29tLp06dkiRJkpKTk6XGjRtn+p45cOCAmq3XHIQHMIucPHmSmTNncujQIflYiRIl3lmd//Dhw7Rs2RKACRMm8M033+SLnQUNSZLYv38/EyZM4PLly/JxXV1dBg4cyKxZs/ItDqlNmzYcPHgQgCdPnmBubp4vzyso+CQlJREdHc3jx495/PgxUVFR8uO3j0VFRck7EL///jtt27YFICgoiN69e+fY+9WwYUNOnToln6tZsyYbNmyQY6+0CbErUzjYsmULX331lezl09PTY8aMGaSkpDBnzpxM56S1mstO4maBRb36U/M5ffq01KZNm0y/STRt2vSd865duyaPe9tTKMga58+fl1q0aJHhde/YsaN05cqVfLenX79+sg2XLl3K9+cXCCQp1RseGRkpzZw5U6pbt65kamoqlSpVStLV1ZU6NWkoKU78Lnu5BnduJ9nblJWMDAwkixJmUqemDaWrW9ereMJu79ok2ZS2kP+2dXV1pWnTpkmJiYnqvtSPJm1XxsmxtqSroyMBkqGBgVTX1VXsyhQQbt++/U5v37t+tm/frm6zNQIhgd/B2bNnad++PQ0bNuTAgQOZjmnfvv0759vY2MiPw8PDc92+gszdu3fx8vKibt26HD58WD5er149jhw5wp49e6hRo0a+2yUygQWagJ6eHlZWVpw+fRpvb29Onz5NJXt7jAyK8M+NW8QnJsljXas58N3UMVzd5s/+FfOQJIk2o6fIXXFSUlLoNH4WlWzKYl3aAuuyZbGwsOD58+dyj3JtxsXFBV9fX74eMxblf5td3/r6cu78eXx9fUW2bwGgYsWKHD16lFmzZmU5tm/atGkk/9cNpjAjBOBbBAcH06FDBxo0aMC+ffveO7Z27drvPFesWDG5YrkQgFnj2bNnjBs3jqpVqxIUFCQft7e3Z/v27Zw5c4bmzZurzT4hAAWaxP79++nfvz8JCQmcO3+eVWO9eRAVTfD1m/KYIV3a08y5NnZly+BS1YG5Q/vx4HE0dyMeA3DwbAhX794naM4kvh0zjEcREYwePZr169erJFlpO1K6SKeclMMRaDb6+vrMnDmTNm3aZGn8zZs32bhxYx5bpfkIAfgfISEhdOrUibp162Y5O+9D/S7TvIDh4eHvbfRe2ElISGDJkiVUqlSJpUuXkpSU6sEwNzdnxYoVXL16lR49eqg9cyu9ABSlYASawqZNmyhnZUnDWtUBKFU881ZZsfEJbPztDypal8HWqjQApy5do5Z9BaxLm9OpSSNsLEtz+/ZtEhMTCQ4OzrdryGvS3zvEvbhgsnXrVvbv35/l8bNnzyY+Pj4PLdJ8Cr0ADA0NpUuXLri6uvLrr79meZ6ZmRnlypV775g0ARgXF8eLFy8+yk5NJqffqJVKJYGBgVStWpXx48fLvTeNjIyYNGkSYWFhjBo1KluN3vMS4QEUaCKnTp6khUttJq7eQBOnmtSqZKdyfs2uXynWogvFWnThwOnzHFy5AIP/SiVFPovBqlRJAPT19Wjp6kToP/9gYGBQoL7kCAFYsLl7967cqz2rPHr0iFWrVuWRRdpBoRaAfn5+ODs7f7CgamY4Ojp+0CNVUOMAP6bAbBqHDh2ibt26Kg2/dXR06N+/Pzdu3MDHx4cSJUrk9aVkizJlysiPhQAUaAqXr1zhVngEF8PuEDRnUobzXm1aEPL9ao6sWYyDrTUe0xaQkC5OMP1tzMnBnkuXL6vUOS0IpM/4FAKwYKFQKOjdu3eOQhZ8fHxkx0NhpFALwD179uR47oe2f6HgCcCwsDBauLvj6urKTzu2U6tMKXyG9WfDlK/xGdafWmVK8dOO7bi6utLC3Z2wsLAMa1y8eJF27drx6aef8s8//8jH27ZtS2hoKBs3bsTW1jY/LyvLCA+gQNNQKpUkJiZy9c59Dq9eRDnL0hnGmJma4GBrQzPn2vy4YBrX7z3gp6MnAChTqiSRT2NUxiYmJpKcnIyVlVW+XUdek17MihjAgsWiRYs4ceJEjubGxMSwePHiXLZIe9BXtwHqZM6cOQQHBxMdHZ3tue9LAEmjIAnAoKAgBg0aRNlSJdnlM52OTRqir5+xEbdCkcKvx08zflUAjo6OBAQE4OnpyYMHD5gxYwbff/+9yjdwZ2dnFi1aRKtWrfLzcnKEiYkJxYoV49WrV0IACtSOJElyT+BhXTtQ0brMB2akzYPE/zIgG9WuzoLvtxHx5CllLcx58ToWfX199PT0cHV1zTPb8xuxBVxw2bx580fNX7FiBSNGjFD5gv8+lEplgakhWDCuIofUq1eP0NBQ3Nzcsj23MHkA0wrMdmvemAs/rKGr2yeZij9IjSPq6vYJF35YQ7fmjfHy8uLrr7+mSpUqbNq0Sb75li9fnsDAQM6fP68V4i+NtJtEQYqPEmgn3t7eBAYGUsXBgVvh4UQ+fUbk02fEJyQCcDs8Ap/vtxF8/Sb3I6M4dekqHtMWYGxoQPtG9QFoXd+FGnbl6Tt7Mf/8G8b+U+fR0dFh8ODBGVrMaTNCABZcvvrqK4yMPlz0/F3ExcUxYsSId57PjZAnTUV0AgG5avjcuXOzfHN4+fKlXOblXZw7d4769VNvtMOGDcPPz++jbc1P1qxZg4+PDw8fPqRU8WLs8plOcxdHnr14xcwNP/DH2WAePH6CRYnidG7WiLlD+mFmagLA0xcv8Zr5DcdCL6nUJTMzM2PatGmMGDHio9606sLNzY2jR48C8Pr1a0xMTNRskaCw8q4Yve+mjaH/Z615FP2UwT4rCL5+k5hXr7EqVYJmdWoz/cteVK3wJszifmQU3otXcTj4AglJSdSqVYtz585pTPJVbrBt2za5x+/y5csZPXq0mi0S5CYKhYI7d+5w/fp1rl27xvXr1+XHWY3xCw8PV+kq9bE9tbWBQr0FnIaenh6zZ8+mefPmdOjQ4YOp4RUrVvyg+APt9gBu376d0aNHY1+xIrZWpen4SQM6jJvBlSB/XsbGEfHkKYtHDKZGxfLci4ziq0W+RDx5xo8LpgGgq6ND52aNmNrfE6+Z3xATG4ehoSHu7u6MGzdOzVeXc96OA9S2N7yg4JD2ZTUkJARXV1d2+Uynq9sn8nnr0ubsXTb3g+uUL2PJr0vnsPvIcbpNnsemTZsKlPgD4QEs6Ojr6+Pg4ICDgwMdO3aUj0uSRHR0tIogTHt87949+W9BR0eHIv9lxsPHhzxpC0IApiMqKipLdYGysv0LYGVlhZ6eHikpKVonAJctW0anTp3YtWuX/MFyOPgCfrt/w2f4l+z0mS6PrVTOmnlD+9Fn9mIUihT09fUoWbwYX33eAYAVXw+l2+R5fPXVV2zbtk1dl5QrvJ0JLASgQN24uLjg7ubG+FUBtG7gmqUewG8TG5/AhFXf4e7mViC7YwgBWDjR0dHB0tISS0tLmjVrpnIuLi6O69evc/DgQZo3b07p0qkJVNnpqZ0W8tS6gSvDF/ni5eWFJEn06tUrT68rtyjUMYDpCQsLY8iQIfLvXbt2fWegZ1YFoJ6eniwYtEkAJiUlERwcTFxcHOWsLOnYJLUZ/KcNXDh16Vqmc17ExlLcpGim35I6NWlEGfNSBAUFqbWTR24gMoEFmoj/+vVEPIth+CLfbGe5KpVKhi/yJeJZDP7r1+eRhepFCEDB2xQtWhQXFxfMzMwYOnQoxYsXx9TUlN69e+Pu4sjG6WMxMTYiMSmJkUvXULptD0zdO9N5/EweRqkmjj598ZJnr16hq6uDl5cXffv2lRsaaDJCAAKJiYn06NGDV69eAdC7d2927drFkSNHVLZx08hKBnAaafOjoqK0pvfgkydPSElJ4fatW7R0dZRFnVXJkkQ+e5Zh/NMXL5m3cStDurTLcK7XDB/MWn1O5NNnxMbGsmHDhjy3Py8R3UAEmkjlypUJCAgg8MBhBsxdSmx8QpbmxcYnMGDuUgIPHCYgIKDAerSFABS8i3LlyrFw4ULOnz9PrZo1MTM14diFK1y7m1qfdvSKdfx89CRb50zi2NqlvI5PoOO4mSr9tDuMnUFcQiJH1yyhjLk527dvZ+zYseq8rCwhBCAwbtw4uSZd1apV8fPzQ0dHh6ZNmxIaGkq7dqrCJqseQHgjACVJ0jqP0e07d3ByqCT/LiGhg2rg+cvYWDqMnUENu/LMHNg7wxrLRg0leNMqBnzWmpcvXzJmzJg8tzsvER5Agabi6elJYGAgO4+exKnPcHYfOY5CkZLpWIUihd1HjuPUZzg7j55ky5YtWhW7lF2EABS8i44dO9K+fXtevXrFmbNnCZjyNabGRpy+fJ0Xr2P57tcDLPnfYFrVd8G5amV+mDmBS7fucuhcqmZI66f9w8wJNHaswapxX5GUlIS/v7/G99Mu9AJw165dcjsYQ0NDduzYgampqXzewsKC3377jcWLF2NhYUHv3r2pUqVKltfXxkQQCwsL9PT0SE5OprhJUfl4VMxzuW0UwKvYONqNnoapsRG7F86giH7GkNIy5qWoZmfLJ041kSQJPz8/rRZOQgAKNJlevXpx8eJFKjhUodvkeVT8oj/95yxh+dbdfPfrAZZv3U3/OUuo+EV/uk2eh12Vqly8eLFAiz8QAlDwYTZt2oSNZWniEhKJTUikUe3qBF+/SbJCQev6b+JirUubU8u+Aif/C4dK308bUkOeylqYy6FUmkyhTgK5c+cOAwcOlH9fuXJlpt49XV1dxo0bx9ixY7PdHim/BOCzZ8/o0qULt27domLFilSsWBF7e3v5X3t7e6ytrbNUwNLAwABXV1fOnz/Py9g4+fihs//QqWlqPODL2Fjajp6KYZEi/LJ4FkaGBu9d88XrWIoUKUJycjKJiYkfd7FqRAhAgaZTuXJlDv/1FyEhISxatIitu3YReOAwSqUSQ0NDateqRdceHgwYMKBAJnxkhhCAgvdx6dIl1qxZgyRJjFi6mt0Lp1OjYgVCb9zGoEgRShZXrfphVaokkU9Tw6HS99OG1MSQT+s588P+PzU+TKjQCsCkpCQ8PDx48eIFAB4eHipJIJmRk96Y+SUA//77b44dOwakNrnOrDWOgYEBdnZ2mYrDihUrqvTeHTNmDJ6enuw8/DdtGrri//M+7j+OYljXz3gVG0ebUVOJS0jgh5kTeBkbJwvF0iXM0NPT4/eTZ3n87Dn1qlfBtKgRe0+cRU9Pj/r162NnZ5dnr0NeU7JkSQwMDEhKShICUKDRuLi4YGdnR7JCAcDhw4dxd3dXs1XqQQhAwfuoWrUq+vr6eH/eAYMi+vSfu5Qjaxa9c/zbvbLflgZODvZs3ndI4/tpF1oBOGnSJM6dOwdApUqV8Pf3z5P/rPwSgFlp25SUlMSNGze4ceNGpuf19fWZPn06M2bMwMPDAz8/P44fO4Zz3+HUsrdj79K5VChrxZGQC5y5ch0Ah+5fqqxxe/cm7MqWwdjQkA2/7GPMynUkJiWTnJKCk5MTv/3228dfrBrR0dGhTJky3L9/XwhAgcbz8OFD+XFWW10VRIQAFLwPfX19kpKSqGlfgS87tuH8tRus3P4zHq2ak5ScTMzLVypewKiY5zSqXQNI7ad99r/PQ3k9vdTEybTSMppKoYwB/PXXX1m+fDmQ6hXbsWNHnrU9yi8BaGtrS9OmTT9qDYVCodKtZNmyZaQolWydM5nzm1bRzDk1+9nNxQnlqf2Z/tiVTS174+7qxIn1y4n5YxeBsyeQkpLC+vXrVbyM2kraB+mTJ0+0JrNbUDh58OCB/LhcuXJqtES9CAEoeB+6uroYGhrKO1mSBEnJybhWc6CIvj5/nP1HHhvx5CmXb9+jce3qQGo/7cu37xHx5Kk85ty1VCdLvXr18vEqsk+hE4D379+nX79+8u9Lly7N0ziY/EwC6dmz50evkT51PX2B2ayWlXibglhgNr0n5fHjx2q0RCB4P2kewBIlSqgktxU2hAAUvIspU6Zw7NgxHCpX5kjwBaau3cSRfy7Sq00LzExN+LJjG8b5+vPnuX/4598w+sxaTO1KdrSq5wxk7Kf957l/2H3kOJalS2t8P+1CJQCTk5Pp2bMnMTExAHz++ed4e3vn6XOamprKfwR5LQC7d++Onl7GQsxZLg0bfgAAIABJREFUQUdHh82bN2do0yYKzGZEJIIItAGlUikLQFtb2w+MLtgIASh4F48fP6ZPnz5cvXaN306c4czla+xbPo9P/8v8XT5qKJ2bNcZj2gKaDB1LUSND9iyeLX/W6unp8dvSORgZGNBk6Fg8pi1AR0eHL7p1U+dlZYlCFQM4ffp0Tp06BYCdnR0BAQH5EqRpY2PDy5cvCQ8PzxA8mpuULl2aVq1aceDAgWzN09HR4bvvvqNPnz4ZzqUVmPXy8gL4YGucNGLjExi+yJfAA4fZsmVLgSowKwSgQBt48uSJ3I2gMG//ghCAgncTEBAAvOmp7d2tkyz+AIwMDfAdOxzfscPfuUZaP21A7qk9aNCgvDU8Fyg0HsB9+/bxzTffAKkBn9u3b8+3eLS0beD4+HieP3+eJ89x5coVpk+fLhe0zg7r1q2jf//+7zwvCsyqIgSgQBtIH/8nPIBCAAreT2EMeSoUHsDw8HD69u0r//7NN99Qv379fHv+t+MAS5Ys+Z7RWef27dts27aNbdu2cenSpRytsXr1agYPHvzBcb169aJ+/foMGTyYbpPnYWNZmpauTjg52GNmasKL17FcuHmbP4MvEB4VTQt3dw74+xcoz18aQgAKtIH0GcDCAygEoODD+K9fj6OjI8MX+bJx+tgs1c1NI33I0wEtCXkq8AJQoVDg6enJkydPgNS2L19//XW+2vC2AKxVq1aO13r06BE7duxg27ZtnDlzJsN5HR0dzM3N5et9H8uXL2f48He7td8mfYHZmTNnErRvH4H7/0QpSYWqwGyZMmXkx5pe6FNQeBEewDcIASjICoUt5KnAC8DZs2fLBZJtbW3ZtGlTvhdn/NhM4KdPn7Jr1y62bt3K0aNHM72BNWrUiJ49e9K9e3eOHTuGh4fHe9dctGgRo0ePzrYtkOoqr1u3rlzT79dff6VDhw45WksbER5AgTYgSsC8QQhAQVbx9PREkiQGDRrEiUvXWDTiSzo1aYS+fsYES4UihT3HTzFh1XdEPIvRupCnAi0ADx06xPz584HUTJ1t27ZRqlSpfLcjJwLw1atX/PLLL2zdupWDBw+i+K+af3qcnJzw9PTEw8NDpbtGhw4dMDExITY2NtO158+fz/jx47N3EW+R3sNoaWn5UWtpG5aWlujo6CBJUqYCUJIkFAoFRYoUUYN1AkEq6beAhQdQCEBB1sl6yFMo4VFPtDbkqcAKwMjISLy8vOQ3+/z582ncuLFabMmqAIyPj+f3339n27Zt/PbbbyQkZAxEdXBwwNPTk549e1K9evVM1ylatCidO3cmKCgow7mZM2cyZcqUHFyFKukFoIWFxUevpw2kpKQQHR1NREQEZmZmPH/+nH///ZcRI0YQERFBREQEkZGRREREkJyczLhx41i4cKG6zRYUUoQH8A1CAAqyS/qQp40bN3L61Cm2H/6exMREiujro5SUmJiYcuLECbVpi4+lQArAlJQUvLy8iIqKAqBt27Yf7fH6GN4nAJOTkzl06BDbtm3jp59+4tWrVxnmlytXjp49e+Lp6Ymzs3OWtrA9PT0zCMDJkyczc+bMHF6FKukFoLm5ea6sqWncu3ePqVOncvXqVSIjI3n8+HGGWogvX75k9erVmc7fvXu3EIACtZHmASxZsiQmJiZqtka9pA/mFwJQkB1cXFxUYtqVSiWjR4/G19eXly9fyqWWtJECKQDnz5/P4cOHAbC2tmbz5s3ZyubJbSwtLdHT0yMlJYXw8HCUSiXHjh1j69at7Ny5k6dPn2aYU7p0abp3746npyeNGzfOtv2tW7emZMmSctHrsWPHMn/+/FyLf0wTgPr6+hpf7TynLFu2jC1btuR4fqtWrXLRGoEg66QvAl3YvX+g6gHMbkF7gSA9urq6KoLw9OnTuLm5qc+gj6DACcAjR44we/ZsIPU/auvWrWpvyKynp0eZMmUIDw/n+vXr2Nra8ujRowzjzMzM+Pzzz+nZsyctWrRAXz/n/z0GBgYsX76c2bNn069fP2bMmJGryS9pAtDCwiLfk2ryC1dX14+a/+WXX+aSJQJB9oiOjpb7VBf2+D8QW8CC3KVRo0by47TmEtpIgRKAUVFR9OrVS/6GN3v2bJo1a6ZWmy5fvsy2bdtkwRQfH098fLx83tjYmE6dOuHp6Unbtm0xNDTMtefu16+fSt/j3CTNa1mQ4/969+6Nv78/J06cyPZcR0fHjxaQAkFOEfF/qggBKMhNHBwc5B2206dP52mHr7ykwAhApVJJnz595KzMli1bMnnyZLXYcuvWLblA8+XLlzOcL1KkCG3btsXT05OOHTtqXZP2uLg4WcQWZAGoq6vLunXrqFOnTqZZ2O/jyy+/1MobgqBgIDKAVRECUJCb6Orq0qBBA/bv309UVBR3796lYsWK6jYr2xQYAbho0SIOHjwIgJWVFVu2bJGbNecH4eHhcoHms2fPZjifVjYEYM+ePbRt2zbfbMttClMGcM2aNZkwYQILFizI8hwDAwN69+6dh1YJBO9HFIFWRQhAQW7TqFEj9u/fD6RuA2ujACwQvYCPHz/OtGnTgNQ3+pYtW7Cyssrz533y5Anr1q3Dzc0NW1tbxowZk0H8NW7cmG+//Val9Epmmb7aRGHIAE7PtGnTslXfqXPnzoXidRFoLqINnCpCAApym4YNG8qPT58+rUZLco7WewCfPn2Kp6cnKSkpQOqHdcuWLfPs+V6+fCkXaP7jjz8y3RqsU6cOnp6e9OjRQy7QHBgYKJ/PSTcQTaIweQAhNU7Tz8+PTz/9NEvjRfKHQN0ID6AqQgAKcpv69evLj7U1EUSrBaAkSfTr10/+ttu8efNcq3OXnvj4ePbu3cu2bdvYu3dvpgWaq1SpIhdorlatWobzH9sOTpMobAIQUku69O7dW0XIZ0a5cuWyLBQFgrxCeABVEQJQkNuUKFGCGjVqcPXqVUJDQ4mPj8fY2FjdZmULrRaAy5YtY+/evUCqEAkKCsq1uL/k5GT++OMPtm7dys8//8zr168zjLG1tZULNNepU+e9Qf8FSQCmr1tYWAQgpP69/f777zx79uydY/r375+vsacCQWakeQBLlSpF0aJF1WyN+hECUJAXNGzYkKtXr6JQKAgJCeGTTz5Rt0nZQmtjAE+fPs2kSZPk33/44Qesra0/as2UlBSOHDnC0KFDKVOmDJ999hmBgYEq4s/S0hJvb2+OHz/O3bt3WbRoUZa6cxQkAVgYPYCQWpx78eLF7x0zYMCAfLJGIMgcpVIp32OE9y8VIQAFeYG21wPUeA+gUqnM0AUjJiaGnj17yvF3kyZNynFWrSRJnDt3jq1bt7Jjx453Fmj+4osv6NmzJ+7u7jkq0GxiYoKZmRkvXrwQAlCLGTBgAJs3b+bo0aMZzrm7u2Nvb68GqwSCN0RFRYki0G8hBKAgL9D2RBCNE4BpjZdPnTzJ5StXSExMxNDQkFo1a9KocWMGDBjAunXruHfvHgCffPIJc+fOzfbzXLp0Sa7Vd/v27QznixYtKhdobtOmTa4UaLaxsZEFoLYWjoTCLQB1dHRYu3YtTk5OGXpAiuQPgSYgikBnRAhAQV5QvXp1ihUrxqtXr4QA/BjCwsIYMngwfx05go1laVrVdcKraX+KmxTlZWwcF27e4qcd21m1ahUlS5YAUuNbtm7dmmWPXFhYmCz6rly5kuF8kSJFaNeunVygObcbqNvY2HD16lUSEhKIiYmhVKlSubp+flHYysC8TbVq1Zg8ebLcchDA1NSUL774Qo1WCQSpiCLQGRECUJAX6Onp0aBBAw4dOkR4eDgPHjzQqvecRgjAoKAgBg0aRNlSJdnlM52OTRqir58xkF6hSOHX46cZt2oDsa9jmTx58gdf7PDwcLZv3862bds4d+5chvO6urq0bNmSnj170rVrV0qWLJlr1/U2b8cBarsANDAw0LouJrnF5MmTWbNmDdHR0UBqvUdtywATFEyEBzAjQgAK8oqGDRty6NAhIHUbWAjAbBAUFETv3r3p3aYFayaMxMTY6J1j9fX16Or2Ca0buDJ8kS8TJkzA2tqaXr16qYyLjo5m165dbN26lWPHjmX6hv/kk0/w9PSkW7du+VI0GjIKwNq1a+fL8+Y2aQLQwsJCa7exPxZDQ0N8fX3p2bMngNraDgoEbyM8gBkRAlCQV7wdB9i9e3c1WpM98l0A/v333yxevJjg4GAiIiJS22a1acHG6WNJUSqZuDqAfSfPcftRBGamJrSq64zP8C+xLv1mq7HXDB9Cb95GR0cHLy8vduzYwTfffMPp06fZtm0bf/zxh1wYOj3Ozs54enri4eFB+fLl8/OygYKRCSxJklwGprDF/72Nh4cHDRo0AJALfgsE6kZ4ADMiBKAgr0gvALUtEzjfBWBsbCxOTk4MGDCAL774glLFTFgzYSS6urq8iovnn3/DmDagF04OFYl59ZqvV6yj84RZnNvoK6/h5uLE5H49MTMx4dP/TeHAgQPs2bMn0zd21apV5QLNVatWzc9LzUBBEICxsbEkJiYCQgCCEH4CzUMUgc6IEICCvMLc3BwHBwdu3rxJSEiInLiqDeS7AGzXrh3t2rUjODgYgL7tWsnbvmamJhz81kdl/LdjvqLBwFHcj4yifBlLAL72/PzN+bHD6DZ5nsqc8uXLywWanZycNGabsiAIwMKcAfw+MitXJBCogzQPoLm5uSgC/R9CAArykoYNG3Lz5k0SExO5cOGCSps4TUZtn1ibNm0CoF7193vlXryORUdHhxLFMs/IbeJYCyMDA4oUKcKIESM4ceIEd+7c4Ztvvvlgd478pqAJwMKYAZxGSEgII0eOpK6rK0ZGRujp6WFkZERdV1dGjhxJSEiIuk0UFEJEEejMEQJQkJdoa0FotSWBnDp5EgA9vXdr0ITEJCb7baRXazeKv1WSZeLqAFbv3ENcQiIWJcwoV8EOX1/fd6ykGVhaWqKvr49CoSgQArAwegCzU67I3c0N//XrqVy5srrNFhQSHj9+LBfIFwkgbxACUJCXvJ0IMmrUKDVak3XUJgAvZ1KHLz3JCgWeM3xQKpWsHj8iw/nxXt0Y2LEN9yKjGLpwJRcvXdL44sq6urqULVuWBw8eCAGohWS3XNH4VQE4OjoSEBCAp6enGiwWFDZE/F/mCAEoyEtq165N0aJFiYuL06qC0GrZAlYqlXIiQWYkKxR4TF3AnUeRHPzWJ4P3D8CihBlVypfj0/ouDP+iI0qlkpP/eRU1mbRt4Ojo6Pe+BppKWgYwFC4BmFauqFvzxlz4YQ1d3T7JVPzBm3JFF35YQ7fmjfHy8iIoKCifLRYURtJnAAsP4BuEABTkJfr6+tSrVw+Au3fvEhkZqWaLsoZaBKCuru47s2TSxN/Nh+H88a0P5mbFP7jey9i41Ln/9b/UZNLHAUZERKjRkpxR2DyAa9aswdbWFi8vL0oWM+XLjm3kpKWhC1dSudsAijbvhGU7D7pMmMX1u28+gE2MjShRzISSxUzx8vKievXq6roMQSFBlIDJHCEABXmNNvYFzncB+Pr1a0JDQ7GvWBGAO48iCb1xi/uRUSgUKXSfMo/z128QOGsiKUolkU+fEfn0GUn/ibuzV/5l1Y97CL1xi3sRj/kr+AL+P/+OoaGhSiCmpqLtiSCFSQBu376d0aNHY1K0KLZWpenZqjkdxs3gfmQUAK7VHPhu6hiubvNn/4p5SJJEm9FTVGpQSsDU/p6YGhvzMN2Hs0CQF4gi0JkjBKAgr9FGAZjvMYDnz5/H3d1d/n3st/4A9GvfipmDerPnWOoL59x3uMq8w6u/wc3FCWNDA346eoJZG34gNiGBsualiE1IwNPTUytq7wgBqD0sW7aMTp06sWvXLnb5TKer2yccDr6A3+7f8Bn+JUO6tJfH2pUtw9yh/ajTZzh3Ix5TqZw1AN+OSf07Pn3lGj/+eYyQkBBcXFzUcj2Cgo/wAGZO+hJNQgAK8gJtLAid7wLQzc0NSZIICQnB1dVV/mBNQ3lq/3vn165ckT9XfSP/vvvIcbpNnsfIkSPzzObcpCAJwIJcBiYpKYng4GDMzc0pZ2VJxyapb+5PG7hw6tK1DONj4xPY+NsfVLQug61V6Qznq5a3pYi+Hhs3bhQCUJBniCSQzEnvAVQqlWq0RFBQKVOmDHZ2dty9e5dz586hUCjQ11d7t933orY6gC4uLri7uTF+VQCx8Qk5WiM2PoEJq77D3c1Naz5UC4oANDIyKtBFZp88eUJKSgq3b92ipaujnPBhVbIkkc+eyePW7PqVYi26UKxFFw6cPs/BlQswKFIkw3q6ujqYGhtzWku+GQq0k/RFoI2NjdVsjeYgtoAF+UGaFzA+Pp5Lly6p2ZoPo9bWBf7r1xPxLIbhi3yz/a1MqVQyfJEvEc9i8F+/Po8szH3SfyvXZgFoYWGh0SV3covbd+7g5FBJ/l1CQoc31+3VpgUh36/myJrFONha4zFtAQmJSZmuZWxoyKXLl/PcZkHhJCUlhUePHgEi/u9thAAU5AfaVhBarQKwcuXKBAQEEHjgMAPmLs2yJzA2PoEBc5cSeOAwAQEBWlVoV5s9gJIkyWVgCnr8n4WFBXp6eiQnJ1Pc5I2nMyrmOValSsq/m5ma4GBrQzPn2vy4YBrX7z3gp6MnMl1TT1eXxMREsQUlyBPSF4EW27+qCAEoyA+0LRFE7c1LPT09CQwMZOfRkzj1Gc7uI8dRKFIyHatQpLD7yHGc+gxn59GTbNmyResK7BobG1OyZKqA0DYB+OrVK7nUTkEXgAYGBri6uqKrqyuXGQI4dPYfGtV+dzkXSYLEd5QjSlEqMTQ0FD2DBXmCyAB+N0IACvKDOnXqyMmo2iAANSJCsVevXtSvX58hgwfTbfI8bCxL09LVCScHe8xMTXjxOpYLN2/zZ/AFwqOiaeHuzgF/f63y/KXHxsaGmJgYwsPDNb57SXq0IQNYkiT+/fdfXr9+jYWFBebm5piamuboNR4zZgyenp7sPPw3bRq64v/zPu4/jmJY18+4HR7B9kNHad3AldIlzAiPfsKiwB8xNjSgfaM3jcDDHjzidXw8kU9jeB0fTyV7e0JDQ6lRowYGBga5eemCQo4oAv1uhAAU5AdpjoOTJ09y8+ZNnjx5orGflaAhAhBSt4MP//UXISEhfPHFFwQd/IugP46gUCgwNDSkdq1adO3hwYABA7Qm4eNd2NjYcPnyZRITE3n27JnWZNNqQwbwunXr+Oqrr1SOGRgYYG5ujrm5uSwK3/43/WMbGxuMjY3x8PDAz8+P48eO4dx3OLXs7di7dC4VylrxKPopxy9cYeX2n4l59RqrUiVoVqc2J/yXYVmqhPzcg32Wc/SfN8HAV69dw9nZmTt37mBnZ5dfL4ugECAygN+NEICC/KJhw4ZyV7IzZ87w2Wefqdmid6MxAjCN6tWrc/fuXQCaNGnC0aNHC9yW2dtxgJoqpt5GGzyAYWFhGY4lJSURERGRrc4rvr6+jBgxgmXLluHq6sqO+VNVyhVZlzZn77K5H1znrzWLgTfliipXrsysWbMoX758lm0RCLKC8AC+GyEABfnF23GAmiwANU5ZpYk/gPLlyxc48QfamwiiDQKwe/fuubLO7t27gdwrVzTedwN6urqEhYXRu3dvGjVqxIkTmSeLCAQ5QXgA340QgIL8QpsygTVOXd2+fVt+bG9vr0ZL8o70AjD9TVvTScsABs0VgPXr18fZ2fmj1jA0NGT16tXy77lRrigy5gUtW7WSj589e5YmTZrg4eHBnTt3PspegQBEF5D3IQSgIL8oV66c/Bl/9uxZldagmobGCcD0H4aFQQAKD2DuoqOjw7Bhw3I8v2jRopw6dYrq1d9k+uZWuaIDBw5w4MABatasKY/ZsWMH1apVY+LEibx48SLHdgsEaQLQwsICIyMjNVujWQgBKMhP0raBX716xbVrGTtHaQoaJwALmwdQCMDcp1evXhQrVizb8/T09Ni5c2emHsTcKlfUunVrQkNDWbt2LaVLp7aMS0pKYtGiRTg4OLB27Vq5lptAkFVEEej3IwSgID/Rlm1gIQDVgBCAeYupqSnt2rXL9ry1a9e+d16vXr24ePEiFRyq0G3yPCp+0Z/+c5awfOtuvvv1AMu37qb/nCVU/KI/3SbPw65KVS5evJihVqW+vj5Dhw4lLCyMiRMnyuVgoqOj+eqrr6hTpw4HDhzItv2CwktkZKS81SS2fzMiBKAgP9GWgtAaKwCLFCmCtbW1mq3JGywsLCjyX79YbRWAmpi5HB8fz+bNm2ncuDE7duzI1txp06YxaNCgD45LK1cUHBxM1x4eXI2KYcq67xm0YDlT1n3P1agYuvbwIDg4mD8PH35vrcrixYuzcOFCrl+/To8ePeTjV65coW3btrRv356rV69m6zoEhRNRBPr9CAEoyE9cXFzQ108tsqLJAlCjysBIkiQLQDs7O/T09NRsUd6gq6uLtbU19+7d00oBWLRoUY1qNH/z5k3Wrl3Lpk2bePbsWbbn9+nThzlz5mRrjouLi0o9SqVSmeOM9YoVK7J9+3ZGjRrF119/zdmzZwHYt28fBw8eZOjQocyaNUveMhYI3kYkgLwfIQAF+YmxsTHOzs6cO3eOq1ev8vz5c0qUKPHhifmMRnkAo6OjiY2NBQru9m8aadvAT58+JSEhZ+VF8ps0AagJ27/Jycns2rWLTz/9lCpVqrBs2TIV8Ve7dm369+//wXXc3d3ZsGHDR3djyY1yRY0bN+bUqVNs2bJF9uKkpKSwZs0aHBwcWLJkCYmJiR/9PIKCh/AAvh8hAAX5Tfpt4LQv9ZqGRgnAwpABnEb6OMC04G1NRpIkuQyMOgXggwcPmDFjBhUqVKBbt24cOnRIPmdoaEjv3r05ceIEFy5cwM/P771b1TVr1mT37t0a1ZJNV1eXXr16cf36debNm4eJiQkAL168YPz48dSoUYNdu3aJDzGBCsID+H6EABTkN9oQB6hRArAwJICkoW2JIC9evJCDzPNbACqVSvbv30/nzp2xs7Nj7ty5Kl09KlWqxOLFi3n48CE//PADjRs3RkdHByMjI7788stM17S2tmbfvn0a6ZaH1G32qVOncvPmTQYOHCh/gN2+fZtu3brRvHlzzp8/r2YrBZqC8AC+HyEABfmNNmQCa1QMYGEVgFevXsXU1JTw8HD559GjR9ja2jJ16lQ5mFSdqCMDOCoqio0bN7Ju3boMxZL19PTo3Lkzw4YNo2XLlu/cgh0yZAiLFy9WOWZqasrevXu14oOybNmybNiwgREjRjBmzBj++usvAI4dO0a9evXo27cv8+fPF16fQk56D2D6e4sgFSEABfmNnZ0dlpaWREVFcebMmY+KE88r1K8s0pFeAFasWFGNluQeSUlJnDlzhocPH6oIvAsXLshj3le4uFq1anh4eOSHqe8lvzKAJUni2LFjrF27lp07d5KcnKxy3sbGhiFDhjBw4MAsfdBVrlyZ1q1bc/DgQeBNrb86derkif15RZ06dfjzzz/59ddfGTduHDdv3gRg8+bN/Pjjj4wfP54JEybIW8aCwkWaB7B06dKiCHQmCAEoyG90dHRo2LAhe/bsISYmhps3b1K1alV1m6WCxgrAguABVCgUuLi4cOXKlRyvUaZMmVy0KOfktQB88eIFmzdvZu3atZmWPmnTpg3Dhg2jQ4cO2faIjh8/nj/++ANJkli3bh1t2rTJLbPzFR0dHTp16kTbtm3x8/Nj9uzZxMTEEB8fz5w5c1i/fj0LFiygb9++GvdNU5B3iCLQH0YIQIE6aNSoEXv27AFSt4E1TQBq1KdEmgAsVaoUZmZmarbm40lMTOT69es5nl+hQgWaNm2aixblnPQCMDfLkQQHBzNo0CCsra353//+pyL+LCwsmDBhAmFhYezfv58uXbrkaDu8VatWnD17lpCQEAYOHJhrtqsLAwMDRo0aRVhYGKNGjZJfk4iICAYMGEC9evU4evSomq0U5BcRERGiCPQHEAJQoA40PRFEYwRgUlKSHMdSELx/ACYmJnh7e+d4fr9+/TTGk5OWAQwfHwMYFxfHd999R/369albty4BAQHExcXJ55s0acKWLVt4+PAh33zzDZUqVfqo5wOoW7dupi3etJlSpUqxYsUKrly5QqdOneTjISEhuLm58fnnnxMWFqZGCwX5gUgA+TBCAArUQd26deXPcCEA38P9+/flN2ZBEYAA8+bNo3z58jma27dv31y2JufkRhLItWvXGD16NDY2NgwcOJBz587J54oVK4a3tzeXLl3i2LFj9OrVC0NDw4+2uzBQpUoVfvnlF/7880+cnJzk4z/99BM1atRg7NixxMTEqNFCQV4iSsB8GCEABerA1NQUR0dHAC5dusSrV6/UbJEqGiMAC1r8XxrFihVj7dq12Z7XrFmzXPF85RY5FYBJSUls374dd3d3atSowcqVK3n+/Ll83tnZGX9/fx49esSqVauoVatWrtpdmGjRogXBwcEEBATIsaPJycksW7YMBwcHVq1alSGpRqD9CA/ghxECUKAu0raBlUqlxpXuEgIwH2jXrh2enp7ZmpOVLhb5SXYF4N27d5kyZQq2trb07NmTI0eOyOeMjIzo378/Z86cITg4mMGDB2NqapoXZhc69PT0+PLLL7lx4wZTp06VM0KfPn3KyJEjcXR0ZO/eveJDsAAhPIAfRghAgbrQ5DhAjRSABaUETHpWrFhBqVKlsjS2aNGidOvWLY8tyh5ZyQJOSUnht99+47PPPsPe3h4fHx+ioqLk81WrVmX58uU8evSIjRs3Ur9+/Y9uwSbInGLFijFv3jz+/fdfvLy85OPXr1+nQ4cOtG7dmkuXLqnRQkFuITyAH0YIQIG60OSC0BopAAuaBxDA0tKS5cuXZ2lst27dKFasWB5blD3SBKCpqWmG2LzIyEjmz5+Pvb09HTt25Pfff5dvsvr6+vQgJuvNAAAgAElEQVTo0YPDhw/LMYAlS5bMd/sLK+XLlycwMJDTp0/TuHFj+fihQ4eoU6cOQ4YM4fHjx2q0UPCxiCLQH0YIQIG6cHBwkJ0/p0+f1qi/P40TgHp6egX2W2yfPn349NNPPziuX79++WBN9ni7D7AkSRw+fJgePXpga2vLtGnTuH//vjy+fPnyzJs3jwcPHsgxgMLbpz4aNGjA8ePH2b59O3Z2dkBqTMr69eupXLkyPj4+JCQkqNdIQY5I8wBaWlqKxKl3IASgQF3o6OjQoEEDAKKjozN0tVInOpKGvBtKlizJ8+fPqVixooo3sKBx+/ZtatWqRXx8fKbny5cvz507dzSm/AukCoUiRYqgVCqpU6cO/fr1Y+3atfz7778q43R0dGjfvj3Dhg2jXbt26OnpqcliwftISEhg5cqVzJ8/XyUrrUKFCixcuBAPDw8h1rUEhUKBoaEhSqUSFxcXgoOD1W2SWvn9999Zs2YN8fHxSJIk/ygUCk6cOAGAmZkZNWrUUDkvSRKlS5dmyZIlVK9eXc1XIShozJ07lxkzZgAQGBioEpajViQN4NmzZxIgAVLLli3VbU6es2TJEvl63/6ZPn26us3LwJMnT2T7dHV1M9hsaWkpTZkyRbpz5466TRVkg8jISGno0KEZ/k8bNmwonTp1St3mCbLAgwcP5P+3zp07q9sctWNra/vOe2tWfgYPHqzuSxAUQA4ePCj/jY0YMULd5shohJupoMf/vc2oUaNwdXXN9Jwmbf++fv0af39/mjVrJh9TKpXyYzc3N7Zv386DBw+YP3++vLUo0A6srKxYu3YtoaGhKqEJp0+fplGjRvTq1Yt79+6p0ULBhxAZwKrUrl37o+bXrVs3lywRCN6QPuFRkzKBNU4AFsQM4LfR19dn/fr1GbZImzZtqhG1/y5fvoy3tzfW1tYMHTpUpT2boaEho0aN4tq1a/z111/06NEDAwMDNVor+Fhq167NgQMH2Lt3L9WqVZOPb926lWrVqjF16lSNK2AqSEVkAKsyffr0HM8tV66cRn0BFxQc0sIOAEJDQ98ZApbfaJwALAweQEgtgDxu3DiVY+qs/ZeYmMiWLVto0qQJtWvXZs2aNZl+6E+YMIEVK1aoCAWB9pMWv3nx4kVWrVoll/pJSEhgwYIFODg4sGHDBrnnrEAzSO8BFAIwteZau3btcjR30qRJIolGkGek1QNUKBQaE6srBKAamTlzJiYmJkDqB7A6av/dunWLCRMmUK5cOXr37i0HSkNqPcJBgwapfKu2trbOdxsF+UeRIkXw9vYmLCyMsWPHUqRIEQAeP37M4MGDcXZ25tChQ2q2UpBGeg+g2AJOZdasWdmeY21tzcCBA3PfGIHgPzSxILRGCMD0adGFSQAaGxvz22+/4ezszLfffkvx4sXz5XkVCgU///wzbdq0oXLlyixevFil0HONGjXw9fXl0aNHrF+/XqUmYU77AAu0ixIlSrBkyRKuXbvG559/Lh+/dOkSn376KR07duT69etqtFAAwgOYGfXr1+ezzz7L1pyJEyfKXXMEgrxAIwtCqzsLRZIkqVKlShIgFS9eXFIqleo2p8Dy8OFDadasWZKNjU2G7LciRYpInp6e0t9//53h/2DChAnyuL/++ks9xgvUytGjRyVXV1eVvxl9fX1p5MiR0pMnT9RtXqGlQYMG8v9HQkKCus3RGM6fP5/lzN8yZcpIcXFx6jZZUMBJSUmRihcvLgFS2bJlNULrqN0DqFAo5ExDe3v7Ql1/LH2GbW6u+ccff/D5559ToUIFZs2aRXh4uHy+YsWKLFy4kIcPHxIUFETTpk0z/B9ktw+woODRrFkzzp49y/fffy+HASgUCnx9falcuTLLly8nKSlJzVYWPtK2gK2srET8WjpcXV3p1KlTlsZOnDgRY2PjPLZIUNjR1dWlfv36AERERKiEb6gLtQvAhw8folAogMKRAZyekJAQRo4cSV1XV4yMjNDT08PIyIi6rq6MHDmSkJCQHK/95MkTlixZQtWqVWndujU//fSTHMCvq6tL586d2bdvH2FhYUycOBFLS8v3rpXGu/oACwo+urq69O3blxs3bjBr1iyKFi0KwPPnzxkzZgw1a9bk559/Fp0W8gmFQkFERAQg4v8yIyuxgFZWVgwZMiTvjREI0LxtYLULwMKYABIWFkYLd3dcXV35acd2apUphc+w/myY8jU+w/pTq0wpftqxHVdXV1q4uxMWFpaldSVJ4sSJE/Tp04dy5coxfvx4lblly5ZlxowZ3L17l59//pm2bdtmqeOIEICC9JiYmDBz5kxu3LihUjYjLCyMrl270qJFC/755x81Wlg4iIiIkHcNRPxfRpydnenatet7x4wfP17+IiMQ5DWalgiir24DCpsADAoKYtCgQZQtVZJdPtPp2KQh+voZW6YpFCn8evw041cF4OjoSEBAAJ6enpmu+fLlSwIDA1m7di2XLl3KcL5Vq1Z89dVXdOzYUc7qzA5pArB48eKi5p9AxsbGhk2bNjFy5EjGjBnD33//DcCRI0dwdXWlX79+zJ8/X2SO5xGiCPSHmTVrFj/99FOm50qXLs2wYcPy2SJBYSatJzAIDyBQuDKAg4KC6N27N92aN+bCD2vo6vZJpuIPQF9fj65un3DhhzV0a94YLy8vgoKCVMaEhoYydOhQrK2t8fb2VhF/pUqVYuzYsfz7779yDGBOxB/A06dPARH/J8gcV1dXjhw5wu7du+VC5pIksWnTJqpUqcLcuXOJi4tTs5UFD1EE+sM4Ojq+s7zWuHHj5DJcAkF+YG5uTpUqVYDUELDExES12qN2AViQPYA+Pj7Uq1ePYsWKYW5uTp8+fej4SQM2Th+LiXFqyYGhC1dSudsAijbvhGU7D7pMmMX1u2++2ZsYG1GimAkli5ni5eVFtWrV+P7772nUqBHOzs74+/sTGxsrj2/UqBGbN2/m4cOHLFmyRP5jyykpKSk8e/YMEAJQ8G50dHTo2rUrV65cYcmSJZiZmQEQGxvLjBkzqFq1KoGBgXmS6FRYER7ArDFz5swMiW0WFhYMHz5cTRYJCjNp28BJSUmEhoaq1RaNEYA6OjpUqFBBzdbkLkePHsXb25vTp09Tyd4eI4Mi/HPjFvGJb7IlXas58N3UMVzd5s/+FfOQJIk2o6eodFyQgKn9PTE1NiYsLIz+/furxA+YmpoybNgwQkNDOXnyJH369Mm1rLaYmBg5qF8IQMGHMDQ0ZOzYsYSFhTFixAi53eHDhw/p06cPDRs25Pjx42q2smAgPIBZo1atWnTv3l3l2NixYzE1NVWTRYLCTPo4QHVvA2uMALSxsSlwZQz2799P//79SUhI4Nz586wa682DqGiCr9+Uxwzp0p5mzrWxK1sGl6oOzB3ajwePo7kb8Vge8+2Y4Xzt+TntGtdVEYaOjo74+fnx6NEj/Pz8cHJyyvVrECVgBDnBwsICX19fLl26RPv27eXj586do2nTpnTv3l3F+y/IPqIIdNaZOXOm/FhfXx9vb281WiMozKTPBFZ3IohaBeDLly9lgVHQtn/Ts2nTJspZWdKwVnUAShUvlum42PgENv72BxWty2BrVTrD+arlbdHX06Nhw4acPHmS0NBQhg0bptKpI7cRGcCCj6F69ers3buXAwcOUKtWLfn4zp07qV69OhMmTODFixdqtFB7SfMA6ujoiESbD1CjRg26d++OsbEx06ZNy9N7pkDwPmrVqiVnnhdqAVhYEkBOnTxJC5faTFy9gSZONalVyU7l/Jpdv1KsRReKtejCgdPnObhyAQaZJGzo6upQrKgxiuRkGjVqlC9Fs4UHUJAbtG7dmn/++Yd169bJNSeTkpJYvHgxlStXxs/PT64HKsgaaR5AKysrkZ2fBXbs2EFcXJyKN1AgyG/09fWpV68eAPfu3ZNreaoDtQrAgpwAkp7LV65wKzyCi2F3CJozKcN5rzYtCPl+NUfWLMbB1hqPaQtISMy8q4KxoSGXLl/Oa5Nl0jKAQQhAwcehr6/PkCFDuHnzJpMmTZJDPp48ecLw4cNxcnJi//79arZSO0hOThZFoAUCLUVTtoGFBzCPUSqVJCYmcvXOfQ6vXkQ5y4xbu2amJjjY2tDMuTY/LpjG9XsP+OnoiUzX09PVJTExMd+yKYUHUJDbFC9eHB8fH65fv46Hh4d8/OrVq7Rr14527dpx5coVNVqo+URERMjJWSL+L+uILHSBJqApBaGFBzAPkSSJ//3vfwAM69qBitZlsjgPEpOTMz2XolRiaGiYpQ4euYEQgIK8ws7Ojm3btnHy5EmVAqn79+/HycmJ4cOHEx0drUYLNZf0GcDCA/hu8rLdpkCQUzQlE1hjBGBB7APs7e1NYGAgVRwcuBUeTuTTZ0Q+fUZ8Qmrxx9vhEfh8v43g6ze5HxnFqUtX8Zi2AGNDA9o3qi+vE/bgEaE3bhH5NIbX8fFUsrcnNDSUpKTMt4lzEyEABXlNo0aNOHnyJEFBQbI3KyUlBT8/PypXrszixYuzXTBVqVRy8eJFEhIS8sJktSMygN9PXrXbFAhyAysrK1nznD9/nuR3OHzyHEmNVK1aVQIkY2NjSalUqtOUPIHUEn4Zfr6bNkZSntovPdyzRWrXqJ5kWbKEVERfXypnaSH1au0uXdu2XlKe2i//NHeunek6d+7cyTVbX716JcXGxmY43qFDB/n5IiMjc+35BILMiIuLk+bPny+Zmpqq/K1XrFhR+vHHH7N8nxg+fLgESPXq1ZPi4+Pz2Or8Z8mSJfJrExQUpG5zNIotW7ZIxsbGkr2NtbTLZ7qUdGyvyv007Sfp2F5pl890yd7GWjI2NhavoyBf8fT0lN/DwcHBarFBR5L+CyTJZ5RKJcbGxiQlJVGzZk0u52NiQ34TEhKCq6sru3ym09Xtkxyvs/vIcbpNnkdwcDAuLi65Zt+KFSsYO3as/H9iYWEh/4SEhMiJICtXrsTKykrlvIWFRYGr3yhQP5GRkUyfPp2AgADS36KaNGnCsmXL5Cy6zDh79qzKlvLEiRNZuHBhntqb34wePZqVK1cCcOzYMZo0aaJmizSDtHabvdu0YM2EkXLHpfcRG5/A8EW+BB44TGBgIL169coHSwWFnW+//ZZRo0YBsGrV/9k777Aorq+Pf3eXKk1AuoggWIKAskhsUYq9xRYbJXYNohKJvcQWMTb0hy0gtoCKsWA0saCABrEBCmKJAioqoKigsHT2vn/sy4SVurBNuJ/n4WGZmXvvmWF29uy953zPTploU8psCTgjI4NZwmyK8X+Vsbe3h7OTExbuDAavsGFLUrzCIizauR/OTk5idf4AICIiggmOLiwsxMuXL3H37l1EREQIZQHPnz8fEyZMQL9+/dClSxe0bt0aLVu2RGBgoFjtoVAMDQ0RFBSEu3fvwsXFhdkeExMDR0dHeHh4CMXBVUAIwYIFC4S2bd68WeZ6W+KmKcQAPn78uNESGHv27IGtrS00NTWhrq4Od3d3ONvbMuU2A8P/hrPXQmi5jga7xyDk5uVX6aOktBR8wocChw03NzeMHDkSubm5jbKLQqkLeUgEkZkD2BwygCsTGBSEzA858NoUIHImGp/Ph9emAGR+yEFgUJDYbatcqUFUioqKEBYWJkZrKJT/sLOzw+XLl/Hnn38K1bUOCQlB+/btsWrVKuTn//ehfuLECVy/LpxBz+fz8f3336OwsFBqdkuaihhAFosFExMTGVsjOr///js6deoEExMTuLq64uDBg/j06ZPI/bRu3RobN25EXFwcOltbQ0tdDf8kPsCj5+kAgIKiYgzs7oCl34+vsQ+3n39F4tNnOO//C4xbtcLly5fh4eHR4HOjUOpDly5dmNWzZucANvUM4M+xtLREcHAwQi5GYsq6rfWeCeQVFmHKuq0IuRiJ4OBgWFpait02d3d3Rpm8IdCHJUWSsFgsDB8+HMnJydixYwe0tbUBCGar161bh/bt2+PgwYMoKCjAokWLqu3jyZMnWL58uTTNligVDqChoSEUqxGNl3du374NQDBjGxkZiSlTpsDAwAATJkzAuXPn6h0UP3z4cAwZMgR5eXm4dfs2gpf9CHVVFdxMfgwA8JkwCks8x6N7547Vtn/0PB0XbsYhaJkPXBy64H++s8Hj8XDu3Dn8+++/4jlZCqUalJSUwOVyAQiSlmSheEAdQCkyceJEhISE4MTVWNh5eOFUdAzKysqrPbasrBynomNg5+GFE1djERoaiokTJ0rELi0trQbHvfTs2ROenp5itohCqYqioiLmzZuHlJQU/Pjjj1BQUAAg0MSbMmUKrKys8Pz58xrbb9++Hf/884+UrJUcpaWlyMrKAvDlLv9WN2tZsZowfPhwGBsbw9vbGzdv3kR9wtQPHjwIE309FBQVg1dUjB42neplx437j6ClroavrQUO4ojePWCirwclJSXExsaKdlIUiohUXga+deuW1MeXCwewKUrA1MSkSZOQlJQEM6v2GLt0PczHTMbktVvgf/QU9p+9CP+jpzB57RaYj5mMsUvXo237DkhKSpKY81fB7NmzRW7DZrOxa9cuqWkSUigAoKOjg23btuHhw4f49ttvme0ZGRm1tiOEYPLkyeDxeJI2UaJkZGR88SLQZmZmte5/9+4ddu3ahR49eqB9+/ZYs2ZNjVIt9+/fx+7du5GR/Q7eW3fh1MaV+Mq89v4ryHqfA33tlszfCgocuHLtwGKxGCebQpEUsq4IIhcOYNu2bWVlhkywtLREZFQU4uPjYefQDccj/8Hi3fsxfYM/lv12CA/f5mDUuPGIj4/HlchIiSz7fg6Xy601s7I65syZgy5dukjIIgqldqysrBAeHo7IyEjo6urWq01aWhoWL14sYcskS1NIAGnTpk29j01JScHq1athZWWFHj16YNeuXUL6pB06dICCggJ8xo/C7FFDMXndVjx89qLe/X9eUt3OygIlJSVSqbVOad7IWhBa5g6goaEh1NTUZGWGTLG3t0dubi6KiovB4XBQVlaGoqIi3ImLQ0BAgNizfetClFlAfX19rF27VoLWUCj1Q09PDzk5OfU+fteuXbhy5YoELZIsTUEEWhQHsDI3b96Et7c39PT04OvrC0BQY7qkpATWFmbw85oKO0tz7AgLr1d/hrraePNBOONXS10NhBDo6VUt20mhiJPWrVsz4RC3b99GeXn1IWGSQiYOYEFBATO93lzi/2oiNTUVAKCrqwsOhyNTW8aPHw8tLa16Hbtp0ya0bNmy7gMpFAlCCGE0LEVh6tSpDco6lQe+9BnA4uJiFBYWNjp05Pjx4wAEoSjKysr4xCsAICilWVLPJJIeNp3wMZ+H2w/+S/hIShEoVFBtRYo0qFgGzs/Px8OHD6U6toJUR/t/KgdqN2cHkMfj4c2bNwDk4zqoqanB09MTAQEBtR7Xq1cvmvlLkQsuXLiAS5cuidwuPT0dP/30U4M0LPl8vkzjXuV5BpAQgpycHKSnp+PFixdIT0+v8rqx2n8AoKysjC1btmDZsmUYPHgwrCwtER2fiOzcj4i+m4Tz/usB4P/Lb+Yg5ZUgPvR+6nNotFBFGwN96GhpoFPbNhjU3QEzN27H3sWCuu2Hz1+GlpYWOnTo0Gg7KZS66N69O06cOAFAsAxsY2MjtbFl4gA21wSQz5FHLcRZs2bV6gDSxA+KvFBaWsosAzaEoKAgjBkzBgMHDqz1uISEBBw4cAA3YmOR/OABiouLoaysjM7W1ujRsyemTJki1XANWc4AlpWV4fXr17U6eJV1GSXBlClTsHXrVmhra+PSpUvw8PDAy5cv8ZAQ5BcW4rz/evR3FPw/9p7+C2uDQ5m2fX/4CQCwf8UCTB46AAAQsnox5vvvxsD5ywEQlJXz4e4p2aQ7CqWCzwWhZ86ciYyMDNy8eZP5SU9Px6JFi+Dl5SXWsWVSCq5yCZQDBw5g8uTJ0jZBLvjzzz+ZLMbVq1fj559/lrFFAvr06VOjXMa8efOYElQUiiw5ePAgpkyZ0qg+NDU1kZaWVm0SSUpKCmbOmIGo6GiY6Ouhn4Md7KzaQVOtBT7xCpD4NBWX4xLx+m02nJ2cEBgUJJWELUdHR9y5cwcsFgvFxcVi1QHMy8tjnLnqHLzXr1+LvNxeGSMjI5iZmaFNmzZITk4WacnL1NQUgYGBGDRoUJV98l5uk0KpidzcXLRq1Qrl5eXQ0NCAtrY20tPTqxwniZK5Mp8BlJeZL1kgr9fhhx9+qNYBNDAwwJo1a2RgEYVSlRcv6p/pWROfPn3CxIkTqywjHzlyBNOnT4eRjjZO+q3E8N7doaBQNUa3rKwcZ2NuYuHOYNja2iI4OFjikk0VM4CiikDz+XxkZmZWO2tX8boxJdBUVFTQpk0bxsH7/HXr1q2F6oYvX7683g7g7Nmz8euvv0JTU7Pa/ZXLbQ74mluvGsCfI8lymxQKIAiRSE9PF5rdS0hIYJI/8vLykJeXV21bSYQkUAdQhsjrdRg9ejRatWolJLUA0MQPinwxf/58lJeXIyUlhXlw5uXlIT8/X+h1XXweznDkyBG4u7vDfaALdi+aW6szoaDAwSinXhjwNRdemwLg5uYGQkiDhdXroqSkhEmg+zz+r6CggHHoqnPwXr16Ve8KG9Whp6dXq4Onp6cnknRKXVqAgCBEaN++fUL1oGsiMCgItra28NoUgAMrfUUKU6lcbvOiBMptUigZGRkYMmQIEhMTG9TeyclJvAZBRg5gReybkpISjI2NZWGCXCCvsZDKysqYOnUqNm3axGzr3bs3TfygyBUtW7asU4qIz+eDx+NVcQzz8vKQmpoKHo8HTU1N2Nra4vnz5+Dz+SgoKICzvS3jRBSXlOCngH04FhGNwuJiuDp0wa6F3mit/59MyLK9B/Dg2QuwICit6OjoKNblYEIIsrOzhSpjvH//HqNHj2Ycvc+/sImCoqIiWrduzTh0n/82NTVtVLnI6qhNCobFYmHu3LnYsGFDvWXCKspturm5AUCdznsFvMIieG0KQMjFSISGhkplGZ/S/IiOjm6w8wcAzs7OYrRGgNRjAAkhUFdXR0FBATp06IDHjx9Lc3i54quvvsKjR4+goqICHo8nV4kVqampQg/CxMRE2NraytAiCkUynD17FhwOB5aWlvD08MC/jx6CV1iEhEM7YW3RFj9sCsC5mFs4sGIBdLU08VNAED58ykPcgQBGumnett3o0KY1YpMe4mR0DHr16o3IqKh621BcXIyXL1/WOHv38uVLFBXVr354dWhra1c7a1fx2sDAQOoyVA8fPoS1tXWV7e3bt0dwcHCDZVgqL99v8p6KEb171Lh8/2fMDSzauR+ZH3KksnxPab7k5OTA1tZWKImrvrRq1Qpv3rwRu48g9RnAt2/foqBAoNckT7Ne0obP5zMzoebm5nLl/AFAu3bt0KNHD9y4cQNjxoyhzh+lyTJ8+HAAQHx8PG7dvo2TfisxfYM/biY/Rmt9Pew/exGHf16Ifv+fWfr7z4vQZqQHLt+5i4HdHQAA/1sgyM7Lzv0I41a6iIqORkJCAuzt7RlplJqyZl+8eNGosmMcDgcmJiY1OnimpqY1xs7Jks9nANlsNn766SesXr0aqqqqDe530qRJcHR0xMwZMzB26XqY6OvBlWsHOysLaKmr4WM+D4lP03DxVjzefMiBi7MzLgYG0pk/ikTR1tZGeHg4evfuLfKXOScnJ4n4CFJ3AOU17k3aZGVlMTeBvF6H2NhYlJWVQUFBJpECFIpUOXjwIEz09VBQVAxeUTF62HRC/OOnKC0rwwDH/5ICjPV00dnCDLH3HzEOYGU01VrAWK8Vxo8fD0VFRaSnpzeq/rC6ujrj1OXk5DA1Q1evXo0pU6bA2Nj4i3yPqquro0+fPrh27Rqsra2xf/9+ODo6iqXvinKbFRI+N2/cQFjkIUbCB4SguKQEZmZmuBIZKZYxKZS64HK52LdvH9zd3UVqJ4n4P4A6gDLjS7kOX+IHC4UiKvfv38fu3btBCIH31l04tXElvjI3w70naVBSVIS2pobQ8QY62sh6/6HavlgsFvo5dEHopUiUl9cumcJisWBkZFTr8mzLli2Z5Ir58+czDmD//v0bXFJNXrh48SKSkpLQtWtXscrZVGBvby+U0Vsh4t2rVy/ExsYyy+vyJqhNabq4ubnh3r172LJlS73bSCL+D5CBAyiP4sey4EtwAGVd8YBCkRYdOnSAgoIC5oweBiVFBUxetxXRuzfVeDwhpNaMVzsrC4RcuAIVFZUas2bNzMxgYmIiJI1SF5WrgHyJZeA+R0VFRWyzfvWh4nnWv39/xMbGAgAiIiIwdepUqdlAoWzcuBFJSUn1qmKkr6+PTp06ScQOOgMoI+TxOshbxQMKRVooKCigpKQE1hZmmDp8IOIePcGOsHCM79cXJaWlyPmUJzQL+DYnFz1svqqxPy11NfAJQX5+vliTKyoCyNlsNoyMjMTWb3NjwIABjKYpdQAp0obD4eDYsWPo1q0bUlNTaz3WyclJJHklUZD69I68Sp9IG3lyAFNSUuDi7Awul4vTx8PQ2VAHfrMnY9+yH+E3ezI6G+rg9PEwcLlcuDg7IyUlRab2Uijihs1mQ1lZGZ94ggQ1QoCS0lJwO1pBUUEBEbfvMsdmvnuP5LQX6GlT87fyj/k8KCsriz2ztmIGUFQRaIowjo6OTGLM5cuXG1XdhEJpCNra2jhz5gzU1dVrPU5Sy7+ADGcAdXV15TIzTVpUXgqXpSMszxUPKBRpsGzZMgwePBhWlpaIjk9Edu5HRN9Nwnn/9dBSV8PU4QPxU0AgdLU0oKOpgYUB+2DTri36devK9JHyMgP5hYXIep+DwuJiRMUnop2FBUpKSqCkpCQWO0tKSvDmzRsAVUWgKaKhoKAAFxcXhIeH4927d7h37x5d3aBIHWtra/z+++8YNWpUjcdIKgEEkLIDWFxczCxhyHrWSxYhLssAACAASURBVNZUOMIGBgb1FjoVN/Jc8YBCkRZv3ryBh4cHXr58iYeEIL+wEOf916P//2f++s+fBQUOB+NXbEBhcQlcHbrgwMo1QrN7M/z8cfXufebvJ+mvAQjU/9u2bSsWOzMyMhgR6KYQ/ydr+vfvj/DwcADApUuXqANIkQkjR47Ezz//XG2ZVUNDQ4mUgKtAqkvAL168YB5gzdkBLCwsREZGBgDZXIfdu3fD1NQUbm5u0NZQx9ThAxnnb9bGHbAcOwUt+o6A/uDxGLloNR4//y/wPOVVBkrKyqCqrAQ3Nze0a9cOO3bskPo5UCjiIjg4GM+fP8edO3fAJwRzxo5gnD8AUFFWQoCvF95d/AO86DP4c8samBroCfURtXsz+DcugH/jAk74rQAg0BUUl/MHCCeA0BnAxjNgwADmdUREhAwtoTR3Vq1ahZEjR1bZLsn4P0DKDiDNABbw/Plz5rW0r0NYWBh8fHyg1qIFTA30MKFfXwz7aRXSs94CALgdrbB/+QI8PBaIC9vXgxCCgT7LmGLV8Y+fQk9bCyf9VsLUQB/KSkpYunQpdu7cKdXzoFDEjb29PZydnLBwZzB4hQ2rusErLMKinfvh7OQk9hmlyhUE6Axg42nXrh3joMfExDAFCigUacNms3H48OEqlXEkufwLSNkBlKfEB1kiy+uwbds2jBgxAv8+eYLtPrOxc6E3TPX1sOfUOQDAzJFD0KerDdoaGcK+gxXWzfoeL99k43mmIPZo6vCB+N8CLwzs7gB/n5l49Pgxhg0bhlOnTkn1PCgUSRAYFITMDznw2hQgcmIAn8+H16YAZH7IQWBQkNhtozOA4oXFYjGzgCUlJbh27ZqMLaI0ZzQ0NBAeHi6U3NXQcoj1RWYOIM0AFiBNB7CkpATx8fEoKChAawN9DO/dHQDQ/2t73Lj/qMrxvMIiHDgXAXNjwypLXgAwoncPmOjrITExETo6OhK3n0KRNJaWlggODkbIxUhMWbe13jOBvMIiTFm3FSEXIxEcHCyRsmKVZwCpAyge+vfvz7yujyYbhSJJLC0tERQUBA0NDfTt27faWtnihM4AygBZXYd3796hvLwcaampcOXaMtm+BtrayPrwX1WD3SfPQsNlJDRcRuLizThc2rEBStVITigocGBrYYanT59i1qxZUjsPCkWSTJw4ESEhIThxNRZ2Hl44FR2DsrLyao8tKyvHqegY2Hl44cTVWISGhkosO76piUDLAy4uLow4NI0DpMgD33//PT59+oTo6GiJjyXVLOAKx4fD4TTrb7CydoTTnj3DrMH/aQsRELDwX6Cp20AX9He0R+a7D9h65ATGr9iAmN+2QUVZWM7iQdpz/JOYDDabLfRNmkL50pk0aRIcHR0xc8YMjF26Hib6enDl2sHOygJa6mr4mM9D4tM0XLwVjzcfcuDi7IyLgYESmfmrgIpAix8dHR04ODjg9u3bSE5ORkZGBoyNjWVtFoUihKSqcknNASSEMI6PmZlZs64xW3EdlJSUpPqwadWqFTgcDkpLS6Gp1oLZ/jYnFwY62szfWupq0FJXg5WpCbp37gidAWNx+up1TBzwn9P48NkLuHovQZ+utvg79jYtG0dpclhaWiIyKoqpkHPzxg2ERR5iKuSUlZWivJwPGxsbXImMlLg9FTOARkZGzfr5KW4GDBiA27dvAxCIQnt6esrYIkpzR1pVuaT2FMnJycGnT58ANO/l38qOcNu2bevlNGVkZODQoUNQUlJi6oi2adMGBgYGIjldSkpK4HK5iIuLYyoeAMDl23cx4pvutdgMFJeWMn8/SHsOV+8l8BzSD0a6OrgSn0idP0qTxd7eXuhhW/Flx8bGBsnJybh//z6eP38uFsmXo0eP4ty5c9DT04OpqSlat24NU1NT6OvrUxFoCdG/f3+sX78egCAOkDqAFFmRkpKCmTNmICo6Gib6eujnYAe3byZDU60FPvEKkPg0FaePh2Hnzp1wdnJCYFBQo1YdpOYAynrZU154+/YtIzdQ3+swd+7carNsFRUVYWpqijZt2jC/P//5vMzMggULMHHiRJyIvIaB3bkIDD+P9DdvMXvUUKS9zkTY5asY8DUXei218Dr7HTaF/AFVZSUM6SEo2P4g7TlcvBdjgKM9Fkwcjfnb9qBjhw7Izs6Gnl7VRBEKpalR8WVn4sSJWL58OQDg2LFjWLJkSaP65fF4cHd3rzP7+MmTJ/juu+8Y57Dit7W1dbOurtRQunfvDnV1deTn5zNl4egXWoq0kUlVLiIlwsLCCAACgPj5+UlrWLkjNjaWuQ5eXl71ajNp0iSmjag/6urqREdHhzg4OJD8/HxCCCF9+/YlHDabKCkqEPsOliR692bCv3GBvPozlAzu0Y3oa7ckigoKpLV+KzJpgDN5dCyI8G9cIPwbF8iqaW7VjmNmZibBq0ahyB+pqanM/W9ra9vo/srKyoi+vn6D3+saGhokOTlZDGfW/Bg2bBhzHe/duydrcyjNjNDQUMJisYjHIFeSFxnOfN7W9pMXGU48BrkSFotFQkNDGzSu1L7m0BlAAQ25DhMmTGjwePn5+fjw4QPi4uKwdetWAAItwHI+H0fXLkXcwZ3o09UGAGCsp4u/tq1D1t/HUPzPOaSfCUHImsXoYPbfktPq6R5VKh7ExMQIiVtTKM0BCwsLfP311wCApKQkPHjwoFH9cTicRpVWzMvLQ1JSUqNsaK7QqiAUWVBbVa7ikhLM3bobeoPGQd35W3y78Ge8epvNtFVTVcGaGR4wbqULNzc36OjoYN68eSgpKan3+NQBlDINuQ6DBg2Crq5uo8Zls9kYPXo0APFVPPD9XxA4bDYmTJiAy5cvN8o+CuVLpPLSy9GjRxvdX2PizywsLPDtt9822obmCNUDpEibuqpy+Wz/DeFXY3F07RL8s3cr8guLMPynn5mqXOXl5RixcDXamRjBRE8PbUxNcfLkSfj6+tbbBqk5gLQMnICGOICKioqNmgVUUVHBtWvX0LlzZ2abOCoevM5+j3I+H69evUL//v0xZ84c8Hi8BttJoXxpjBs3jokXO3r0KFPrvKF06dJF6H0qCkFBQWjRokXdB1Kq0KFDBya55p9//kFhYaGMLaI0dWqryvUxn4f9Zy9iy7wZ6Odoj64dLPH7z4twP/U5Lt+5CwC4dDsBD5+n48jaJdixYBYSk5Lg7e2NoKAgJuG2LqQ+A6ilpQVtbe06jm66NLQaioeHR4PGU1FRwYULF9CrVy+h7eKoeLBjxw64uLgw+3bv3g07Oztcv369QbZSKF8aRkZGTL3OtLQ03Llzp1H9sVisBs0CTp8+Xei9SBENFovFzAIWFRUhJiZGxhZRmjJ1VeWKf/wUpWVlGOD4n/qAsZ4uOluYIfb/q3bduP8InS3MYKyny1TlSktLQ3FxMeLj4+tlh1QcwLKyMrx48QKAYNaLxWLV0aLpUuEAtmrVqt4Ze4QQlJeXQ0tLS6SxFBUVcfr0afTt27fa/Y2teODl5YWIiAgEBARAVVUVAJCamopvvvkGixcvRlFRw5aXKZQvCXEvA7u5uYmUhWpkZITNmzc3etzmDo0DpEiLuqpyZb3PgZKiIrQ1NYTaGehoI+u9oGpX1occRr9XQYEDV64d7t29CyUlJWRlZdXLDqk4gC9fvmTWrZtzDeDi4mK8fv0aQP2Wf1NSUrB69WpYWVmhV69e+PjxY73H4nA4OHbsGAYNGlTrcZMmTUJSUhLMrNpj7NL1MB8zGZPXboH/0VPYf/Yi/I+ewuS1W2A+ZjLGLl2Ptu07ICkpifnQY7PZ8Pb2xr1799C9u+BbDCEEmzZtgoODAxISEuptM4XyJTJmzBimgHtYWBjzrGsoxsbGIlXW2bNnD1q2bNmoMSmAq6srMzlB4wAp0iDt2TPYWbVj/v68KtfnEEKEJtAqz6XZWVngfnJylWNqQ2wOYGlpKRYvXozx48djyZIl+O233xAREYHU1FQ8efKEOa45x/+9ePGCiRGq6Tq8f/8eu3fvRo8ePWBlZYU1a9YgNTVV5LEOHDjAJH3URUXFg/j4eIwaNx4P3+Zg2W+HMH2DP5b9dggP3+Zg1LjxiI+Px5XIyGqFJ9u3b4+YmBhs3LgRSkqCknEPHjzA119/jbVr16K0kpA0hdKU0NbWxuDBgwEAmZmZuHbtWqP7rO8y8HfffUcTP8REq1atGMHvxMRERnibQhE3dVXlMtTVRklpKXI+5Qm1q1y1y1BHG1nvc5h9WupqKC4uRmlpKQwMDOpniLh0bE6fPl2jPhWLxWJe9+rVi/zyyy/k6NGj5NatWyQ7O5vw+XxxmSHXnD9/nrkOy5YtY7YXFhaSP/74g3z77bdEUVGx2uvn6upKDh48SL7++us69cB2794tFnvLy8sb1C4pKYnY2dkJ2eTg4EAePnwoFrsoFHnj6NGjzL0+Y8aMRvfH4/GIhoZGre9zbW1tkpWVJQbrKRUsWbKEub4hISGyNofShHF0dCRsNptsmz+L0fbr1LYNWewxjuREnCSKCgrk2LplzL7XZ0MJm80m5/3XE/6NC+SvbesIm80mr8+GEv6NC2TrvJlEQUGBKCsrk48fP9bLBrE5gHfu3GmUgOmCBQvEZYrcsmvXLuacAwMDydWrV8mMGTOIlpZWtdelc+fO5NdffyUvX75k+tizZ0+t13Lz5s0yPMP/KC4uJitWrCAcDoexTVlZmWzdurXBjiWFIq/k5+eTFi1aMI5ZcXFxo/ucOnVqre/1Q4cOicFySmUiIyOZ6/v999/L2hxKE+bYsWOExWKRnjadyIOjgWT++FFETVWFPDt1iPBvXCCzRg0lrfVbkYj/+ZH4gzuJC7cLsbOyIKUxfxH+jQukNOYv0tmiLXF16ELiD+4k/bvZE0VFReLt7V1vG8TmAPL5fNKuXbsGO4EASG5urrjMkUt8fX2ZczUwMKj2GhgZGZGffvqpRjX69+/fVztLCICsWrVKymdUN7du3SIdOnQQsrNPnz4kNTVV1qZRKGJl4sSJzD1+9uzZRvcXHR1d47Ny4MCBzWblRJoUFRUxjryxsTG9xhSJUlNVLv6NC6Qg+k8yZ+wIoqOpQVSVlcmwXl+TF+G/C1UDeX76MBna05GoKisTFotFbGxsSFFRUb3HZxHSSOGqSqxcuZIpqi0qrq6uTVZM+O3btzh69ChWr16N3NzcKvvV1NQwZswYuLu7w8XFBRxO1fp/lRk1ahTCw8OFtv3444/YunWrXGZYFxYWYtmyZdi+fTuzTU1NDdu2bcOMGTPk0mYKRVTOnj2LESNGABAkV4WGhjaqPz6fDwsLC0ZBoQI1NTU8ePAAZmZmjeqfUj1DhgzB+fPnAQDJycmwtraWsUWUpkpCQgK4XC5O+q3EKKdedTeogVPRMRi7dD3i4+OZONb6INYs4IaKFaurq2Pfvn3iNEXmFBQU4NixYxg6dCiMjY3h4+Mj5PyxWCwMGjQIISEhePPmDQ4dOoT+/fvX6fwBVTUBZ8yYIbfOHwCoqqrC398fUVFRaNu2LQBB4ftZs2ZhyJAhTGY0hfIlM3DgQEbj9MyZMygoKGhUf2w2u1r9Tz8/P+r8SZDKGdhUDoYiScRVlWvRzv1wdnISyfkDxOwAWltbN0jF3t/fn3EMvmTKy8tx5coVTJkyBYaGhpg4cSL+/vvvKrIQrVq1QkZGBs6fPw83NzeoqamJNM7QoUPRoUMHAIC7uzv27Nkjt85fZZycnJCUlIQZM2Yw2y5cuIDOnTsjNDS00VUUKBRZoqSkhDFjxgAQfME5e/Zso/v8PBvYwcEBXl5eje6XUjO0LBxFmoijKlfmhxwEBgWJPLbYdQAri6LWh8GDB2PatGniNkOq3L9/H4sXL4aZmRn69euHgwcPIi/vv/RtU1NTzJs3j/m7a9euMDQ0bPB4ysrKuHXrFhISEnD48OF6zRrKCxoaGggMDMRff/0FIyMjAEBubi7c3d3x3XffITs7u44eKBT5Rdyi0FZWVtDT02P+PnDgwBf1fv8Ssba2Zp5NV69eRXFxsYwtojRlxFGVKzg4uFp5troQuwM4fvz4eh/bsmVLBAUFfRGzV5+TkZGBrVu3okuXLrC1tcWmTZuEljI1NTUxdepUREVF4fnz53Bzc2P2iUMLUUtLC127dv0irx0giLNJTk4W+sA8efIkOnfujDNnzsjQMgql4fTt25dxHs6fP4+cnJw6WtTNqVOn0LVrV/j7+ze4TjCl/lQuC1dQUIDY2FgZW0Rp6jS2KpeoE28Mkshs6datW72yfn///XdJDC8x8vLyyOHDh0n//v0Jm82ucj4KCgpk2LBhJCwsjBQUFAi1rawT9uuvv8roDOST48ePE11dXaFr6enpSXJycmRtGoUiMvPnz2fu43379snaHEoDCAkJYf6HS5culbU5lGbC06dPibOTEwFATPT1iOfgfmTrvJlk37IfydZ5M4nn4H7ERF+PACAuzs7k6dOnjRpPIg7gtm3b6nT+Ro4c+UWk2JeWlpILFy4QNzc3Rh7g8x9HR0cSEBBA3r59W2M/v/zyC3P8H3/8IcUz+DLIzMwkw4cPF7qurVu3JhEREbI2jUIRiZs3bzL3sKura6P7o7qZ0icrK4v5H3K5XFmbQ2lmxMfHE29vb+LA5RJlZWVGR9eByyXe3t4kPj5eLONIxAF89eqVUPWPz390dXXlWsGez+eThIQE8uOPPxJDQ8Nqz8Hc3JysWLGCPH78uF59Tps2jWkrrn9eU4PP55MDBw4QTU1NoWvt5eVF8vPzZW0ehVIv+Hw+sbCwIAAIm80mmZmZIrWvePhz7e2FHv5ce3uxPvwptVNRzYjFYpHs7GxZm0Npwjx8+JD4+fkRHo9X7X5JfQmUiANICCF9+vSp0QGU1xmw9PR04ufnR7766qtq7dbW1iazZs0iMTExIs9eOjs7M/3Qpc3aefHiBXFxcRG69paWluT69euyNo1CqRfLli1j7t0dO3bUq83nyz/fD+lHts2fRfYt+5Fsmz+LfD/kv+UfZyenRi//UGrnp59+Yv6Hx44dk7U5lCZKSEgIE1Im7dlmiTmANZUsmzBhgqSGbBAfP34kwcHBxMnJqdpZS0VFRTJq1Chy6tQpkRS2P8fMzIxxIil1U15eTgICAoiqqirzv2Cz2WTRokWksLBQ1uZRKLVy//595r7t3r17nceHhoYSVVVVYmFiTE76rSQl//wlpPhf8VPyz1/kpN9KYmFiTFRVVcmRI0ekcDbNk0uXLjH/w2nTpsnaHEoTo7CwkPzwww9C/oaRkREhhJDTp08TJSUlYmhoKNHPO4k5gG/fvhWqAwuAGBoaknfv3klqyHpTUlJCzp49S8aPH09UVFSqdVR79epF9u7dS96/f9/o8YqLi2Xm4X/p/Pvvv6R79+5C/xtra2uSkJAga9MolFqxsbFh7tm0tLQajwsNDSUsFot4DHIleZHh1Tp+n//kRYYTj0GuhMVikdDQUCmeVfOhoKCAWYI3NTX9ImLWKV8Gjx8/Jra2tlX8DgcHB5KXl0e0tLSYbZs3b5aYHWKXgalAT08PXC5XaFtgYCB0dXUlNWStEEJw+/ZtzJs3DyYmJhg+fDjCwsJQVPSf5o6VlRXWrl2L1NRUxMTEYNasWdDR0Wn02Onp6YzAozgkYJoT7du3R0xMDDZu3AglJSUAwIMHD+Do6Ih169ahtLRUxhZSKNVTWZrh2LFjzOs9e/bA1tYWmpqaUFdXh7u7O5ztbXFgpS+KS0oxd+tudBw/DWpO38JspAfmbduNj/k8ob7ff/yED3l5YLNZcHNzg6enJ0pKSqR2bs0BVVVV9OnTBwDw8uVLPHnyRMYWUZoCISEh4HK5SEpKqrJPXV0dCxcuxMePH5ltV65ckZgtEnMAAWFF9V69emH48OGSHK5anj17hnXr1qFjx474+uuvERAQICQ23KpVK3h7e+PmzZv4999/sXLlSrE7ac+ePWNeUwdQdDgcDhYvXoy4uDjY2dkBAMrKyrBq1Sr07NkTjx49krGFFEpVKpfGrCwK3bp1a2zcuBFxcXHobG0NLXU1/JP4AI+epyPj3XtkvnuPzd4zkBSyBwdW+OLizXhM3+DPtC8vL8cw31UoKCrG1d1bYKiri7CwMPj6+kr1/JoDtCoIRVwUFBRg2rRp8PDwAI/Hq/aYDx8+YO/evULboqKi8OnTJ8kYJbG5RUJIUVER+eabbwiXyxXLUmp9+fDhA9m7dy/p3bt3tcu7ysrKZNy4ceTPP/8kJSUlErdn7969zNi//fabxMdryhQXF5MVK1YIhRcoKyuTrVu3UrkMitxROXwhOTlZaF9cXBwBQE76rSTaGuokaKlPtcu9YeuXESVFRSYu8K9t6wibzSav/gwl/BsXyAm/FQQAUVJSIh8/fpTRmTZN7t27x/z/hg8fLmtzKF8oycnJNSaXVv5RUlKqdvvhw4clYpdEZwCVlZVx7do1xMXFiWUptTaKi4tx+vRpjBkzBoaGhpg9ezZiYmKEjnFycsK+ffvw5s0bhIWFYfjw4VBUVJSoXQCQlpbGvKYzgI1DSUkJ69atQ2xsLFMPubi4GL6+vnB2dha61hSKrKmtNNzBgwdhoq+HgqJi8IqK0cOmU7V9fOTxoKnWAgoKghJwN+4/QmcLMxjrCcJpRvTuAaNWuigpKUF8fLyEzqR5YmNjA319fQCCmRgackIRBUIIDhw4gG7duuHhw4d1Hl9TGEdYWJi4TQMg4SVgUQsbiwohBNevX8cPP/wAIyMjjB49GqdOnRK6iJ06dcKGDRvw4sULREVFYdq0adDS0pKoXZ9DHUDx4+joiLt378LHx4fZdu3aNdja2iIwMBCEEBlaR6EIGDduHNhswWP26NGjzH15//597N69GxnZ7+C9dRdObVyJr8zNqrR///ET1h84ipkjBzPbsj7kwEBHm/lbQYGD/t0EZSGzsrIkfEbNCzabzSwD5+fn4+bNmzK2iPKlkJ+fD09PT0ydOhWFhYWN6uvSpUtiKSv5OWJ1ABMSEjB37lw4cLlQUVEBh8OBiooKHLhczJ07FwkJCWIZ5+nTp/j5559haWmJ3r17Y+/evUIXx8DAAD4+PoiPj8eDBw+wdOlStGnTRixjN4QKB5DD4cDU1FRmdjQ1VFVV4e/vj6ioKLRt2xYAwOPxMGvWLAwZMkSoNjOFIgsMDQ3h7OwMQPAcuHPnDgCgQ4cOUFBQgM/4UZg9aigmr9uKh89eCLX9xONhmO8qfNW2DX6e5i607/MS4HZWFiCEfLG1weUZGgdIEZXExERwuVyEhISIpb/S0lKcPn1aLH1VRiwOYEpKClycncHlcnH6eBg6G+rAb/Zk7Fv2I/xmT0ZnQx2cPh4GLpcLF2dnpKSkiDzGu3fvsGvXLnTv3h3t27fH2rVrhWbWVFVVMWnSJJw/fx6vXr2Cv78/7O3t5eKBWGFnmzZtpLLk3NxwcnJCUlISZsyYwWy7cOECOnfujNDQUDobSJEp1S0DKygooKSkBNYWZvDzmgo7S3PsCAtnjsvjFWCwzwqoq6rg1MZVUFRQYPYZ6mgj673wbIACR7A8rKenJ8lTaZZUdgAjIiJkaAnlSyA5ORndu3cXe9a4JJaBFeo+pHaOHDmC6dOnw0hHGyf9VmJ47+5MrEplysrKcTbmJhbuDIatrS2Cg4OFHozVUVRUhLNnz+L333/H+fPnUVZWJrSfxWLB1dUVHh4eGDVqFDQ0NBp7OmInJycHubm5AOjyryTR0NBAYGAgRo4cienTpyMzMxO5ublwd3fH6dOnsWfPHvrhSJEJo0ePxg8//IDS0lKEhYVhy5Yt4HA4UFZWxideAQCAEKDk/+PLPvF4GOSzHMqKijizeTVUlJWE+uth0wkbDh1D5rv3MGoliAO880jwYdOtWzcpnlnzwNjYGNbW1njw4AHu3LmDnJwcaGtr192Q0iy5c+eOkLycuLhy5Qqys7PF+jnWqBnAI0eOwN3dHWP79kTi77sxyqlXtc4fIIhTGeXUC4m/78bYvj3h5uaGI0eOVDmOz+fj6tWrmD59OgwMDDBu3DicPXtWyPmztbXF5s2b8fLlS0RERMDT01MunT9AOP7P3NxchpY0D4YMGYLk5GShLxcnT55E586dcebMGRlaRmmuaGtrY/BgQQxfZmYmPD098c8//8DK0hLR8YlYvvcgou8mYdJAF+TxCjBw/nLwCouwb9mP+MQrQNb7D8h6/wHl5eUAgAGO9viqbRt4rtmMu/+m4MqduzgVHQN9PT1oamrK8lSbLAMGDAAg+HyKjIyUsTUUeWbSpEmYNm0aE/srLsrLy3Hq1Cmx9imyDMzVq1fJsGHDiL6+PgFA+na1JWXX/2YkC1ZNcyMd2rQmLVSUSUsNdeLq0IXc2Led2Z926iCZMmwAUVNVYRTWV61aRe7du0eWLl1K2rRpU20atLGxMVm4cCFJTEwUbx60hDl+/DhzDhs2bJC1Oc2K48ePE11dXaH7yNPTk9ZipjSI4OBgYmNjQ7p160YGDRpE3N3diY+PD1m/fj3Zu3cvOXHiBImKiiL3798nmZmZQhJTR48eZe7B9u3bEzMzM8JmswmbxSIuXDtycccGwr9xgUTu+rVGiYi0UweZ5+jz04fJ0J6ORFVZmehoahA1VRXyww8/yPDqNG3+/vtv5v8wc+ZMWZtD+QJ4/PgxcXNzq7bEbEN/nJ2dxWojixDRAqTOnz+P69ev40x4OJIfPMCRtUswob8Ts//IxSjoa2vBwsQIhcXF8D92Gici/8HTP/ZDT7slLtyIw/ErVzGyT0/M3bYHqppaSHv2rMryLiBQxR4zZgw8PDzg5OQEDqf62UV55tdff8WSJUsACKoBjB8/XsYWNS+ysrIwc+ZMnD17ltnWunVrHDhwAP369ZOhZZQvjTZt2uDly5citdHS0oKuri6UlZXx+PFjEEKgra2NrKwsJCcng8vl4qTfTfknsQAAIABJREFUSoxy6tVgu05Fx2Ds0vWIj4+Hvb19g/uh1AyPx4OOjg5KSkpgbm5O5aYo9ebx48dYu3ZtFRmohsBms/H69WsYGhqKwbIGLAEPHjwYo0aNQvKDBwAAFSXh+JRJA53Rz9EeFiZGsLZoi23zZ+ITrwBJKYJqGIN6OGD/Cl+M6NMD/j4z8eTpUyHnj8PhYPDgwThy5AjevHmDgwcPwtXV9Yt0/gAqASNrDA0NcebMGRw4cIBZHnv16hX69+8Pb2/vGhXZKZTPaUh83cePH5GWloZHjx4xyUg5OTm4ePEi7O3t4ezkhIU7g8ErbFjMEK+wCIt27oezkxN1/iSImpoaevUSOOnPnj1rUCIjpXnSsWNH7Nq1C2pqao3ui8/n48SJE2KwSkCDFqkPHjyI1gb6dR5XUlqKwPDz0FJXg51VVednRO8eMNbTBYfDQYsWLbB9+3a8fv0af//9NyZOnIgWLVo0xDy5gjqAsofFYmHy5Mm4f/8+XFxcmO27du1Cly5dEBsbK0PrKF8Ks2fPFltfFbMBgUFByPyQA69NASLrpvL5fHhtCkDmhxwEBgWJzTZK9VTEAQI0G5giGv7+/sxkQ4UsVEMRZzZwgxzAG7GxcOXa1rj/XMwtaLiMhGrfEdh+7DQu7diAVi2rii8rKHDwdacOACHYsWMH5s+fDwMDg4aYJLdUOIAaGhoSr4ZCqZ02bdogIiICAQEBUFVVBSCQMPrmm2+wePFiiWRuUZoOrq6uaNeuXYPbczgcJlntzJkz4PF4sLS0RHBwMEIuRmLKuq31ngnkFRZhyrqtCLkYieDgYFhaWjbYLkr9oHIwlIbw4cMHbN++HYBA/ik4OBiBgYFwdnZuUNJWTEwM3rx5IxbbGuQAJj94ADurmh+Ezlw73D20G9cDt2Fgdy7Gr9iAtx9yqxyXkf0e/yQmgwCYPn16Q0yRa8rKyvDihUDctV27dnKhSdjcYbPZ8Pb2RmJiInr06AFAMJOyadMmODg44O7duzK2kCKvsNlszJo1q0FtWSwWwsLCMGHCBACCwvAVcakTJ05ESEgITlyNhZ2HF05Fx6CsrLzafsrKynEqOgZ2Hl44cTUWoaGhdcppUcRD165doasrkN25cuVKtXHrFMrnbNu2DXl5eQCAqVOnwtzcHDNmzEBkZCQ+fvyI+Ph4DB06FObm5rCxsWHa2djYoFWrVlX6U1RUZBQBGovISSB8Ph8cDgf7lv2I6Rv8cWrjKozs27PWNu2/m4opwwZg6fcTmG0Z2e/h4r0IupqauJH8COXl5WJPm5Y1z549Y5Z9R48ejZMnT8rYIkplysvLsWXLFqxatYopH6igoIBVq1ZhyZIlVLSbUoV3797BxMSkxpqdNeHv7w8fHx9ERUUxYQgjRowQkiZKSUnBzBkzEBUdDRN9Pbhy7WBnZQEtdTV8zOch8WkaLsfdRUb2e3C5XBw7dozO/EmZCRMmMEtwsbGxzJdICqU63r17B3Nzc+Tn50NRUREpKSm1ViX75ptvEBMTAwDIy8uDuro6Pn36hNTUVKSmpiI9PR2Ojo7o3bu3WOwT2eNis9lCAqb1gRCC4kpFtF+/fQfnOYtg38ESo516QVlZuck5fwCN/5N3OBwOFi9ejLi4OHTp0gWAYNZ21apV6NmzJx49eiRjCynyRHp6Onbs2CHys8rHx4epWd2nTx8YGRkBECgqVC5haWlpicioKMTHx2PUuPF4+DYHy347hOkb/LHst0N4+DYHeUUCx/PNmzdM+UOK9KgcB0jLwlHqYuvWrcjPzwcgWOWsqyRtamoqAEE5W3V1dQCApqYmunbtirFjx2LBggVic/6ABjiA+fn5sDA3R1T8PQDAs4ws3HuSivSst+AVFmHZngO4mfwILzLfIOHfp5i+wR+vst/hO5dvAAhm/pznLIKpvh42e8/A7Yf/omOHDk2yiPmzZ8+Y19QBlF9sbGxw69YtrFixgsk2j4uLQ9euXbFt2zaRg/MpTYfy8nL8/fffGDFiBMzNzbF+/XqRYkVHjx6NLVu2MH9zOBxGCqq0tLRaYVd7e3sEBATgTlwcioqKUF5ejqKiItyJi2MCyF+9eoXw8PAqbSmShcYBUupLdnY2AgICAABKSkpYtmxZrccXFBQgMzMTABoVaywSogoHRkVFVStQ+P2QfqQg+k8yqm9PYtxKlygpKhKjVjpkxDfdya3gHYyA6f4VC2oUOWxqLF26lDm3CxcuyNocSj24desW6dixo9B92adPH5Kamipr0yhSJDMzk/zyyy/EzMysynOKzWYTTU3NOkVbe/bsSQoKCqr0fevWLeYYV1dXkeyKiIgQui8p0qfi+cDhcEhubq6szaHIKQsXLmTeq3PmzKnz+Pv37zPHe3h4SMFCQhrkdcXHxxMA5KTfSsaxa8jPCb8VBACJj48X93nJBePHj2f+oU+ePJG1OZR6UlBQQHx8fIQ+zNXU1Mhvv/1G+Hy+rM2jSAg+n08iIyPJuHHjiIKCQhWHrnXr1mTt2rXk9evXZOfOnbU6f1ZWViQ7O7vGcdq1a8c4k5mZmSLZ2KlTJ2acu3fviuv0KfVk7ty5zPUPDw+XtTkUOeTNmzekRYsWBABRVlYmr169qrNNeHg4c1+tXr1aClYS0qDAOypgWj8qYgBZLBbMzMxkbA2lvqiqqsLf3x9RUVFMnBWPx8OsWbMwZMgQvH79WrYGUsTKhw8f4O/vj44dO8LFxQXHjx9nMjxZLBYGDx6MP//8E8+ePcPKlSthbGwMd3f3GnVK9fT0cP78+Woz+Cr6rMgG5vP5OH78eL1tZbFYmDt3LvN3xRITRXrQOEBKXWzatAkFBYI8iVmzZsHExKTONhXxf4D0loAbnHlBBUzrpsIBNDU1hdJnFVMo8o+TkxOSkpIwY8YMZtuFCxfQuXNnhIaGMpUdKF8ehBDcvHkT33//PUxMTLBgwQI8efKE2a+vr4+lS5ciNTUVf//9N4YPHw4FBQVmv5aWFiZNmlSlX1VVVZw7d67OB3hl6RZRS0R5eHhAS0ugq3rkyBG8e/dOpPaUxtG3b1/mXqBxgJTPycrKwu7duwEAKioqTCnYuviiHEAqYFo7Hz9+xPv37wHQBJAvGQ0NDQQGBuKvv/5isjdzc3Ph7u6O7777DtnZ2TK2kCIKeXl52Lt3L7p27YoePXrg8OHDQkkdzs7OCAsLw8uXL7FhwwaYm5vX2NfnlUHYbDaOHTsGR0fHOu2wtrZmNL9u3rwplDBWF+rq6pg6dSoAoKioCPv27at3W0rj0dDQQM+eAumzp0+f4vnz57I1iCJX/PrrrygsLAQgeEZUfG7UhSwcwEZnXoSGhhJVVVViYWJMTvitICX//FVtvF/JP3+RE34riIWJMVFVVSVHjhxp/AK2HHP37l1mPX/q1KmyNociBt6/f08mTpwoFOulr69P44C+AO7du0dmzZpF1NXVq8TrtWzZkvj4+JBHjx6J3G+3bt2Yfnbt2iVS2w0bNjBtN2zYIFLblJQUwmKxCABiampKSktLRWpPaRzr1q1j/neBgYGyNociJ2RkZBAVFRUCgKiqqooU32tpaUkAEHV1danFmosl9fbp06fE2cmJACAm+nrEc3A/snXeTLJv2Y9k67yZxHNwP2Kir0cAEBdnZ/L06VNxDCvXnDx5knlArF+/XtbmUMTI8ePHia6urnAW/Pffk5ycHFmbRqlEQUEBOXjwIOnevXu1iRrdu3cnBw8erDZTt74kJyeTkSNHkt9++03ktmlpaYwtnTt3Frn98OHDmfYnTpwQuT2l4VTO5B47dqyszaHICfPmzWPuC19f33q3Ky0tZRLP7OzsJGihMGLVXomPjyfe3t7EgcslysrKglR5Npt81akj8fb2brLZvtWxefNm5kZo6rOdzZHMzEyhD2D8f5ZoRESErE1r9jx+/Jj4+PgQbW3tKk6fmpoamTVrFklISJC1mYQQIuSc3r9/X6S2ly5dopIwMqKsrIy5v7S1tUlZWZmsTaLImFevXjF+T4sWLcibN2/q3bbyl8HRo0dL0EphxFp+o7KAaUVsVDmfj6+sOyMgIKDJZvtWR+UqILXFEVG+TAwNDXHmzBkcOHCAKej96tUr9O/fH97e3uDxeDK2sHlRUlKC48ePw8XFBR07dsT27duFqmzY2tpiz549yMjIYGIA5YHGJIP069cPnTp1AgBcu3YNiYmJYrWNUjMcDgeurq4AgJycHMTHx8vYIoqs8fPzQ3FxMQDA29sb+vr69W4rk/g/NCIJpC5UVFTAYrEACEooNTdoGbimD4vFwuTJk3H//n2mvisA7Nq1C126dEFsbKwMrWsePH/+HMuWLYOpqSnGjx+PqKgoZp+ysjI8PT0RGxuLe/fuYfbs2YyzLi+MGzeOKS137NgxkTLLWSwWvL29mb+pJIx0oVVBKBW8fPkSQf+vaKKmpoaFCxeK1L7JOYCKiorQ09MDAGRkZEhqGLmlwgFUU1NjrgOladKmTRtEREQgICAAqqqqAICUlBR88803WLx4sUilwyh1U15ejrNnz2Lo0KGwsLCAn58f3r59y+y3srLC1q1b8fr1axw6dAg9evRgvozKG4aGhkx5t7S0NNy+fVuk9p6enoxTGxoayigPUCRPZQeQ6gE2b/z8/FBSIqjTPXfu3Bo1QGuiyTmAAGBsbAxAoIvTnOqplpeXM9IAFhYWcvvhQxEfbDYb3t7eSExMRI8ePQAI9C43bdoEBwcH3L17t1797Nu3D9988w2uXLkiSXO/SDIyMrBu3TqYm5tjxIgR+Pvvv5kZMwUFBXz33Xe4cuUK/v33XyxYsAC6uroytrh+VNYTFHUZWF1dHdOmTQNAJWGkjbm5OSNjduPGDeTl5cnYIoosePHiBfO+U1dXx08//SRyH5UdQKmuGEoywHDw4MFMYOPbt28lOZRc8eLFC+a8v/32W1mbQ5EyZWVlZOPGjURJSYm5DxQUFMjatWtJSUlJje2io6MZaY9WrVrROqOEkPLychIREUHGjBlDOBxOlaSONm3akPXr14sktyBv5OTkMPeKoaGhyAkFVBJGdnh5eTH34tmzZ2VtDkUGzJw5k7kHli9f3qA+7OzsmM8Jab5/JToDWFkAsTktA9P4v+YNh8PB4sWLERcXhy5dugAAysrKsGrVKvTs2ROPHj2q0iYvLw+TJ09mZrTevXsHPz8/qdotT7x79w5btmxBhw4d0L9/f5w8eRLl5eUABLFvw4YNw7lz55CWlobly5fD0NBQxhY3nJYtW2Lw4MEABKslV69eFal9u3btMHToUACCWKQ///xT7DZSqofGATZvnj9/jv379wMANDU1sWDBApH7IIQwM4BmZmZCFYckjVSWgAEgMzNTkkPJFdQBpACAjY0Nbt26hRUrVoDD4QAA4uLi0LVrV2zbtk0oLMLX17dKRYHt27c3qyoDhBBcv34dHh4eaN26NRYuXIiUlBRmv6GhIVasWIFnz54xMYAV1/VLpzHZwACE6gP/73//E4tNlLpxdnZm7kEaB9j8WL9+PVM33MfHBzo6OiL3kZ2djfz8fADSjf8DINkl4F27djFTo8HBwZIcSq5Yvnw5c95//fWXrM2hyAG3bt0iHTt2FFq+7NOnD0lNTSV//fVXtULFAMjEiRNlbbrEyc3NJTt37iSdO3eu9hq4urqSP/74o9bl8y8dHo9H1NTUGF254uJikdrz+Xyh+ysxMVFCllI+p2fPnsx1T09Pl7U5FCmRmprKhKVoaWk1uBBAbGwsc//88MMPYraydugMoASgM4CUz3F0dERCQgJ8fHyYbdeuXYONjY1QEsDnHD16VOTM0C+FhIQEzJw5EyYmJvD29kZycjKzT0dHB76+vvj3339x+fJljB07FoqKijK0VrK0aNEC3377LQCBrtzFixdFas9isYRmAakkjPQYMGAA85ouAzcf1q9fz4Sl/Pjjj2jZsmWD+pFVBjAg4SXg5hoDWLmwe9u2bWVnCEWuUFVVhb+/P6Kiopj7oqCgAB8/fqy1na+vr0j6cPJMQUEB9u/fD0dHR3C5XAQFBQmJZvfs2RO///47Xr9+jS1btqB9+/YytFa6NHYZuLIkTEhICJWEkRI0DrD5kZKSgsOHDwMQxPBW/mIvKk3WAWzuM4AmJiZQUVGRsTUUecPJyQlJSUlMJYG6iImJwenTpyVslWR5+PAh5s+fD2NjY0ybNg137txh9mloaMDLywuJiYm4fv063N3dm+X7ZsCAAdDW1gYAnDlzRuRqMurq6pg6dSoAgSRMcHCw2G2kVMXR0ZFxvC9fvtysJM+aK+vWrWNm/3x9faGlpdXgvpqsA2hgYMC8bi4OYH5+PiNKS5d/KTXB4/Fw7969eh+/ePFiRmj0S6G4uBhHjx5F3759YW1tjf/9739Cs51du3ZFYGAgMjIysGvXLtja2srQWtmjpKSEsWPHAhDMlJ49e1bkPubMmcPoju7atYsJUKdIDgUFBaYS0Lt370R6X1O+PJ48eYKQkBAAglCVefPmNao/mWkAQsIOoJKSUrOrBlJ5+Zc6gJTqIIRg5syZIi3RpaSkYPfu3RK0SnykpaVh8eLFaN26NSZNmoRr164x+1RVVTFlyhTcunUL8fHxmDFjBtTV1WVorXzR2GVgS0tLDBkyBICgBCeVhJEOdBm4+bBu3TpmltfX17fR5SUrHEBDQ0Ooqak12j6RkHSWia2tLQFAFBUVCZ/Pl/RwMic8PJzJ6FmzZo2szaHIIQcOHKgx67e2H21tbfLhwwdZm18tpaWl5PTp02TgwIHV2t6pUyeyY8cOubVfXigrKyNGRkbMM7Mh1+vChQvMdXdycpKAlZTPefr0KXPNXVxcZG0ORUI8evSIsNlsAoDo6uqST58+Naq/vLw85r7p1auXmKysPxKdAQT+iwMsLS1tFkHJNAOYUhvp6emYP39+g9rm5ORg/fr1Yraocbx+/RqrV69G27ZtMWrUKKHsVUVFRUyYMAHR0dF48OAB5s2bx8S4UaqHw+Fg/PjxAATPzFOnToncR//+/dGhQwcAQHR0NJKSksRqI6Uq7dq1YxK7YmJiUFBQIFuDKBJh7dq1zOzfwoULoaGh0aj+KvsLUtcAhISXgAHhTODmEAdIHUBKbaxevRqfPn1qcPuAgAChmJH6IO6gdD6fj4sXL2LUqFEwMzPDmjVr8Pr1a2a/ubk5Nm7ciFevXjExgLQedv1p7DIwm80WkoTZuXOnWOyi1AyLxWLkYEpKSoTCHihNg4cPH+LYsWMAgFatWmHOnDmN7lOWCSCAlB3A5hAHSB1ASm1UZI41lNLSUkyfPr3WYxISEjB37lw4cLlQUVEBh8OBiooKHLhczJ07FwkJCQ0aOzs7G7/++iusrKwwaNAghIeHM+fDZrMxcuRIXLhwASkpKVi8eDH09fUbNE5zp1u3bsyHQWRkZIO+OHt6ejKzE1QSRjrQOMCmzdq1axk5rkWLFokldrnJO4DNTQqmwgFUVVUVyoKmUABgz549CA4Ohq+vL0aOHAlbW1uRA3+jo6OrFQpOSUmBi7MzuFwuTh8PQ2dDHfjNnox9y36E3+zJ6Gyog9PHw8DlcuHi7CxUZq0mCCG4du0aJk2aBBMTEyxZskToS46xsTF+/vlnvHjxAqdPn8bAgQPBZkv8sdKkYbFYmDBhAgDB9T9+/LjIfWhoaDCSMIWFhVQSRgq4uLgw9351ZeFyc3Nx7ty5Jivs3pRJTk5m3of6+vrw8vISS7+ydgAlXnW4Oc0A8vl8JgvYwsKCLntRqtCiRQvmg7kCQgjevn2L1NRUpKWlITU1Veh1VlZWlX7evHkj9PeRI0cwffp0GOlo46TfSgzv3R0KClXr5JaVleNszE0s3BkMW1tbBAcHCy05VpCbm4vDhw9j7969ePToUZX9AwcOxOzZszFs2DCpFi9vLkycOBG//PILAMEycEPiRufMmYMdO3YAEEjCLFiwgP6vJIiOjg4cHBxw+/ZtJCcnIz09HS9evEBERAQuXbqEO3fugM/ng8ViIS4uDvb29rI2mVJP1qxZw8z+LV68WGzZupW/hDdJB7A5zQBmZmaiuLgYgCAOikKpDywWCwYGBjAwMEDPnj2r7OfxeHj27BmePn2Kc+fOwdzcHJ6ensz+I0eOwN3dHe4DXbB70VyoqdYsoqygwMEop14Y8DUXXpsC4ObmBkIIJk2aBEII4uLisHfvXhw9ehT/x96Zx9WU/nH8c9tue0qrspRCStElZSwtthhMjUGUsTOJsS8ZZBnZDaUsQxkxGrL8GLIVMWW7CKkhlEFJSsttu3Wf3x93OtPVdlvuPTed9+t1XnXvPed5vs/tdM73fJ/v8/kWFRWJHKurq4spU6ZgxowZtFysWhJWVlawsbHBo0ePcPv2bbx8+bLeKSUWFhYYNmwYzp8/j9evX+Ps2bNwd3eXkMUMhBBwOBwqwte5c2cUFxdXu191D3UMssmjR49w4sQJAEJt41mzZjVZ2xURQA0NDejq6jZZu+Ii1Qjgl+4AMvl/DJJATU0N1tbWsLa2hru7O0JCQmBjY4PU1FQIBAIUFhbC2c4GoSsXQk5ODiWlpVgU+CuOXb6GopISuPbsjt2LfWGiL9TkTHj+EpsOR+BmQiLkWCx4eXnhxIkTSEtLqzY/sH///pg1axY8PDzAZrOlPfwWi6enJ7WC99ixY/Dz86t3G3PnzsX58+cBCBcQMQ5g0/Lx40dcvXoVly5dwuXLl/H69Wvqs+qcvwp69OghDfMYmgB/f3/q9+XLl0NVVbVJ2uXz+dT50rFjR1pmDCWerGNoaEj9/qVPATMOIIM0MDExwcaNG3Hv3j1YW1lBS10NNxISkZQqvJjM+2UvTl+Pw+9rl+HGnm0oKCrGiEWrqQUb3OTn0G2lhcOrl+DBb8HQ1dLEqVOnRJw/LS0tzJkzB0+ePMH169fh6enJOH9SpiIPEGjYamBAuDChop5yTEwMHj9+3CS2tXRu376N3r17Q09PD2PHjsWBAwdEnL/aaNOmjUhghEF2efjwIVWG08jICDNmzGiyttPS0qhrMl0zKhJ3ANlsNlq3bg2AiQAyMDQFI0aMwLBhw5Cfn4/bd+7ggN98qKso49aTZOQW8HDw7EVsnTsdA+3t0KOzOQ6vXoLHL1Jx5e4DAMCUEUOwa4EPBtjZwLpjB4Qs/U8ypFevXjhw4ADevn2LXbt2wcrKiq5htng6dOgAR0dHAMIk9CdPntS7jc8lYQIDA5vMvpbM6tWrcefOHSovrD5wOBwJWMQgCT6P/qmoqDRZ23QvAAGk4AAC/+UBvnv3rkH/MM0FxgFkkCZhYWEw1tdDYXEJeMUlcOxmCW7yc/DLyjDY/r8E8zZ6rWFt1h5xj6su5gCAkX0docJmo23btrhz5w6mTJki/ZJEDNXSWE1AAPj+++9FJGGys7ObxLaWTEW5vYbQs2fPJrSEQVJwuVycOXMGAGBsbIzp06c3afstxgGsCHeXlpYiJydHGl3SQmUHkFkEwiBJHj9+jODgYLz7kAXfbbtxcuNKdDVtj4yPOVBSVIS2pqhCvYGONjI+Vn/jv5v0N0pKS6GsXPPiEQZ6GDNmDCUtcuzYsQY9QGtoaGDy5MkAGEmYpmLOnDl16nHWBBMBbB5Ujv75+fk1+fWxoKCA+t3S0rJJ2xYXqUYAgS87D7DCATQ0NGyyRFEGhuro3LkzFBQUMG+sO2a5D8ekddvw9FVajfsTQqpNMk58mYpvlq7B4N4csXOYGKSHgYEBXFxcAAivLw3VkPP19aV+3717d6MFyVs6LBYLISEhGD58eL2PZRxA2efu3bs4d+4cAKBt27aYOnVqo9v8XKB/6dKlkJeXh4G+PiIiIhos0N8YpBoBBL7cPMDCwkJqaT8z/csgaRQUFFBaWgors/YI8JkCW3NT7Iw4DcPW2ijl85GTly+yf2bOJxjoiNbhffoqDa6+yzBtpBtGu/RDSUlJk5eNY2g8tU0Dp6WlYdOmTXB1dcWiRYtqjBBaWFjAzc2NOubs2bOSM7iFoKCggIiICNjb24t9jLGxscjCSAbZpHL0b8WKFY1aAFebQP8W32kY2tMGp4//US+B/qaCcQCbiNTUVOp3xgFkkDRycnJgs9nI4wmLzhMClPL54HSxgKKCAi7feUDtm571EU9epqFPt/+mGRJfpsJl9lJMHDYQP8+ahNwCHthsNlPFQwbx8PCAkpISACAiIgLp6enYvXs3vvrqK3To0AHLli1DdHQ0tm3bJnId+py5c+dSv+/atUvSZrcI1NTUcO7cOVhYWIi1P5P/J/vcunWLkk5q3749lT7REI4ePQobGxukPX+GyICVeBUZhtCVizBvnDumjBiCeePcEbpyEV5FhiEyYCXSnj+DjY1Ng/N964tUZOFbwhQwswCEQVr4+fnBzc0NFubmuMZNwIdPubj24BEu7FgPLXU1TBkxBIsC96G1lgZ0NDWwOPBXdOvYAQN7CbXHEl+mwsV3KQbb22GBpwcyPmbj1pMkdOncmeaRMVRHq1atMHDgQJw/fx4ZGRkwMTGpMVJbW+rJ4MGDYWFhgefPnyMmJgZPnjyBtbW1pMxuMejp6SEqKgqOjo7IzMysdV9m+lf2+Tz6V/HwVV+aSqBfkjARwCaCcQAZpMX79+/h7e2Np0lJOPfXbdx+koQLO9Zj0L8rf3f8OBOj+vfB2J82oO/MhVBVZuN/W9ZAXl5YGu549A18yMnFkYsxaPP1eLT5ejyOR9/Ay3/LGDLIBkVFRTh+/Dg8PDxw+fJl6v3anD99ff0a22MkYSSHmZkZzp8/D3V19Vr3YyKAskleXh74fD7i4uKoOusdOnTApEmT6tVObGwsRowYAQMDA0yYMAH9u3dD6MqFlPNHCIH/r4dhPGI8VAeMhLPPYiS+TKWOV1NRxvYfZ6CDkfB4DQ0NeHt749OnT001VBGYRSD1gMfjITw8HMch8/JHAAAgAElEQVSOHcOdO3eQlZVF5dwwDiCDtDhw4ABSU1OFtUUJwezRIynnDwCU2UoIXOiDrIvHwbt2Bv/bugZtDfSoz/2neUMQH0VtJwJ+AgBcu3ZN2kNh+AxCCC5duoSJEydCX18fY8aMwalTp8Dn8+s81tTUtM5qAt9//z3lpBw+fPiLVmWQNhwOB5GRkbXWW2YigLLHyZMnoaOjAwMDA4wdO5Z6f+XKlVBUVKxXWzweD7a2ttDXE15vZ7oPE0mr2Rx+HDt+P4XAhT64c3AXDFvrYPCPfsj/N5UHALzXbIEKWwltdHXRycICDx8+hLe3dyNHWT1ScQArJ7025wjgsmXL4O3tDU9PT0oFXktLC927d0dERAS1X1paGp49e0bVBWZgkAR2dnZwdnLC4qAD4BXVXHaqNnhFxVgSdBDOTk5McXoZYOfOnRgyZAgOHz4sIhMhDuJIT2lqajKSMBJk8ODBNX6nbdu2rTVCy0APUVFRKC8vR05ODt68eQMAUFJSAo/Hq/cDkpubG9zd3fEkMREAoFxp+pgQgp0Rp+A3aRw8nPrCumMHhK1ciMLiEhy9FAMASEp9jahb93BgxQLsWjgL9x88wKJFi3Du3Dn8/fffTTTi/5CKA6isrAwdHR0AzTsCWFRUVOW9/Px8JCQkiBT39vb2RufOnaGiooK2bdtiwIAB+OGHH0SihAwMTcG+/fuRnp0Dn82B9V7BKxAI4LM5EOnZOdi3f7+ELGSoD//880+DjxVXe5SRhJEsEydOREBAQJX3meifbFLhm1SmtLQUc+fORZs2bTBhwgRER0eLfX0NCwuDiUFVR//VuwxkfMwREelnKylhQI9uiP9XpD/+cRK01NXQ26oLRvZ1hLG+Hu7duwctLS3ExcU1cIQ1I7UlfxV5gOnp6c22GoiHh0e99ieE4M2bN4iNjcWePXuwcOFCCVnG0FIxNzfHgQMHEH4xGpPXbRM7EsgrKsbkddsQfjEaBw4cgLm5uYQtZRAHPz8/dO/evUHHiusAdurUCUOHDgUgVC+o0DtjaDqWLl2K2bNni7zXrl07mqxhqI3aZHmKi4tx9OhRuLq6wtzcHOvWravzIS0+Lg6uHJsq72d8FEYTP5fj0tfRRsa/1XkyPuZAX7sVAOHCEFeOLW7Fx0NfX18kyNRUSM0BrMgDLC4ullhCo6QZOHBgtU8L4lJRlJ2BoSnx9PREeHg4TlyPg623D05eu4mysuqjOmVl5Th57SZsvX1w4nocjhw5IqIzx0AvrVu3RnR0NHr16lXvY+tTfYiRhJEsLBYLO3fuRI8ePaj3mAUgsknlRaq18erVK6xatQrt27eHm5sbTpw4gdLS0ir7PUlMhK1FzaXdPk/TJYSABVa1n9tamOHxkyc1Cvk3FqnIwABVVwJra2vXsrdsoqSkhG+//Rb7GzBd1qFDB/z0008SsIqBARg/fjzs7e0xY/p0jF6+Hsb6enDl2MLWwgxa6mrILeAh4flLXLpzHxkfs2FkZIhHjx4xkT8ZRFtbG5cvX4abmxvi4+PFPq4+DuCQIUMoSZjo6GhGEkYCyMvL46+//qIW9EgqkZ+hcdR3XQIhBFFRUYiKioKqqiocHBwQEREBXV1dCAQClJSUQFOtqhyTYWuhz5PxMQdGuq2p9z9UEuk3bK2N99n/Bci01NVQUlKCDx8+wMDAoCHDqxWpRwCB5r0QZNy4cQ06LjQ0lCrIzsAgCczNzREdEwMulwv3MWPxNDMHfnsPYdqGHfDbewhPM3NAFISr2tLTM5Cbm0uzxQw1oaWlhYsXL6J///5iH1MfB1BOTk4kFzAoKKhe9jGIh4qKCo4fP47du3fTbQpDNQgEAoSFhTX4+MLCQkRHR1OzKJ8L9FfGtI0hDFtr4/Ld/0T6S/l8XH/wGI7/ivQ7drNEbgEPdxKFCz5yC3hQVFREbm4u+vTp02A7a4KWCGBzXggyYMAAGBoa1ms+/scff4STk5PkjGJgqISdnZ3Iil6BQEBJEezduxezZs0CAAQEBODEiRO02MhQNxoaGjh//jxGjhyJ6OjoWvfV0dGBpqZmvdqfNGkSVqxYgYKCAhw+fBgBAQHNcmamOVL5f5Kh6SkrK0NmZibS09ORkZFR48937941iVqHjY0w56+goABmpqaI4T4EIFz48fDZC+hoaqCdoT5+HOuOgEPHYGHSBhZtjRFw6BhUldkYP9gZAGDZoR2GOvTEjI2/YM/Subhy5wEUFBQwZMgQdJaEUD+REsePHycACACyadMmaXUrEebOnUuNpa7NwsKC8Hg8uk1mYCCEEFJUVESMjIwIAMJiscjTp0/pNomhDgoLC8nQoUNrvc707NmzQW37+vpSbWzdurWJLWeogMvlEl9fX8KxsyNsNpsAIGw2m3Ds7Iivry/hcrl0m9gsyM/PJ8+ePSOxsbEkIiKC7Ny5kyxbtoxMmjSJDBkyhNja2hJ9fX3CYrHEvkc3ZtPT0yP79u2j7IuJial2v++HDSSC+ChSHneBrJo6gRi21iZsJUXSv3s38ih8DxHER1FbVtRxMmGIM9FQVSEsFot06tSJ5OTkSOT7ZBEinSW5f/31F/r27QtAGBH75ZdfpNGtRIiPjxcrHCsnJ4ebN2/C0dFRClYxMIjHtm3bsGjRIgBCyYpDhw7RbBFDXZSUlOC7777D2bNnq/38u+++wx9//FHvdv/++2906dIFgDBPOSUlhaoYw9B4UlJSMGP6dMRcuwZjfT0M7GkLW4uO0FRTRR6vEAnPX+DKvQS8zfwAZycn7Nu/v8Xl5ZaXlyMrK6vOaF16ejp4PF6T9aupqYm8vDwAwnt1fWS05OTk8OOPP2Lt2rVVqr/cv39fKAoesBLuTl812L6T125i9PL14HK5EtNolZoD+PLlS3TsKFwZM2bMGBHh5OYGIQSmpqZIS0urdb+lS5di48aNUrKKgUE8CgoK0K5dO+Tk5EBeXh4pKSno0KED3WYx1EFpaSk8PT1x8uTJKp8tWbIEmzZtalC7Q4cOpcpfnT59GqNGjWqUnQxCjh49imnTpsFIRxtbfKdiRF8HKChUda7Lyspx9uYtLA46gPTsHBw4cOCLWJlfVFRUqzNX8XtmZmaTaVEqKirC0NAQRkZG1M/Kv1f81NfXx4ABA3D79m0AQOfOncUWWuZwONi3b1+tTpmLszPSnj9DwuHgWmsA1wSvqBi23j5ob9EJ0TEx9T5eXKTmABYVFVGFyvv27YsbN25Io1uJsXTpUmzevLnGz62srMDlcsFms6VoFQODeKxZs4Yqeu7j48MkqTcT+Hw+Jk6ciGPHjom8HxISQuV21pfz589j+PDhAABXV1dcuXKl0XY2F0pKSiAQCKCiotKk7R49ehReXl7wGuKC4CVzxHICeEXF8NkciPCL0QgPD8f48eOb1KamQCAQIDs7W6xoXUV0rSlo1apVFSeuup86OjpiyaVcuHABw4YNAwB069YNnTp1QmRkZK3HqKur4+eff8bs2bPrjJKnpKTAxsYGowf0QejKhfXK9xQIBJi8bhtOXI+TuFKD1BxAQChv8OnTJ3Ts2BEpKSnS6lYiPHjwoMYnAAUFBdy+fZsprcUgs2RnZ6N9+/YoKCgAm81GampqrYKoDLJDeXk5Jk+ejMOHD1PvHTt2TKSOaX0QCATo3LkzdU1+8uQJrKysmsRWWSY7Oxs9evTA27dvMWLECMycORODBw9u8OKM4OBgbNmyBe/evQOfz8egXj1wfsd6yMnJYd/p8/j9Ugzu//0C+YWFyL50Aq00RKcOc/LyMXd7MP64Ggt+WTlGjRqFsLAwtGrVqimGWyslJSXIyMioEp37/Of79+/FqkstDvLy8jAwMKjTqTM0NGxSB50Qgt69e+Pu3bsAgBMnTuDatWu1roR3d3fHrl27YGJiInY/v//+OyZMmNDghwBpaLRKbRUwIJSC+fTpE1UNRBLChtKie/fu6NSpE549e1bls59++olx/hhkGh0dHfzwww/YsmULSkpKsH379loj2gyyg7y8PEJDQ5GWlobY2FiwWKxGSURUSMLMmzcPABAYGIg9e/Y0lbkyy8OHD/H69WsAwqnv06dPo0OHDpg+fTqmTJlSrweiiIgIzJs3D8HBwdi/bx/+TnqKvx49xZvMLLQz1EdhcQmGOPTEEIee8AsJrbaNCas34U1mFi7s+BkT12zFlStX4O3tXWPeZ10QQqj7bV3RuvrWvK0NdXX1Op06IyMj6Orq0rIS+s8//6ScPxsbG7i7u9c4/WtiYoKgoKAGpUV4enqCEIJp06bhr8dJ2Ow7BSP7OtaYBvC/m/FYEnQQ6dk5UhPol2oEcODAgbh69SoA4NOnT9DS0pJW1xLB398fa9asEXnPzs4Ot27dgqKiIk1WMTCIR3p6OkxNTVFSUgJ1dXWkpaU1qtINg3QhhODw4cOwtLRsUOWQyuTm5sLExAQFBQVQVVXFmzdvvnhJGC6XW2N1DgUFBYwaNQozZ86Eq6trnY5K7969YWdnh2nTpqFnz56IDFiJFXvCMKq/IwJ8plD7XbufAJfZS6tEAJNSX8PKcwbif/0Fva26UAsAACA5OVlEAoTP5+P9+/d1RusyMjKaROIEEFY20dfXFyta9/miCFmCEIJevXqBy+UCAE6dOoVvvvkGBw8exNSpU6n95OTkMHfuXKxdu7bR+r2fLwSqTqD/Kle4EMjF2Rl79+2T2kIgqUcAK0hPT2/2DuDYsWNFHEBFRUUcOnSIcf4YmgVGRkaYMmUKQkJCUFBQgKCgIKxatYpusxjEhMViYeLEiVXeb4jGnJaWFr7//nvs3r0bhYWFOHjw4Bdfu1xXV7fGz8rKyhAZGYnIyEh07NgR06dPx+TJk6Gvr19l39LSUnC5XCxbtgxhYWEwMdDHiL4OuPbgEeIfJ4llS/zjJGipq6G3lXBF9si+jjDW10PGx2xMmTIFampqlHOXlZXVsAFXg4qKSo0LJSr/1NPTg4KCVN0FiXD27FnK+evRowcV2bO3t6f2sbOzw759+8DhcJqkzwqB/vv37yM0NBS34uMREX0IJSUlYLPZ6GZtDfcxYzF58mSpzxxK9S/6uRh0hfxAc8XS0hLa2tpU+HzhwoVMOSWGZsXixYuxb98+lJeXY+fOnViwYIFMP8EzVKXixhIfF4cniYnUjcXaygqOffqIfWPx9fWlFgPt3r0b8+bN+6IlYfT09MTa78WLF1i2bBlWrlwJDw8PzJw5E05OTlQKU1ZWFsrLy2FgYID4uDi4cmygoCAPA21tZGRni9VHxscc6Gv/l+unoCAPV44tfrtwBXFxcQ0amziLJjQ0NJp1KlZ9IIRg9erV1Gt/f39q7NbW1rh+/TpycnIwfPhwiTi7tQn00wWtEcAvgSVLlmDFihUwMzPD+vXr6TaHgaFemJqaYvz48Th8+DCys7Oxb98+LFiwgG6zGMSgOo25Cf0miWjMnfojAkFBQWJpzHXp0gWDBw/GpUuX8OrVK/z5558YOXKkFEckXVRVVaGqqorCwqplu6qDz+cjIiICERERMDExgZubm4j0DovFwpPEREzoNwkAQEDAgvjO1ed+mK2FGXDhv9dsNlus3Dp9fX1mFqoaTp8+jYcPhRU6OBwORowYIfJ5fcouNgV0O38AzRHAL4Fly5Zh6dKlLeYpiuHLY/ny5QgPDwchBFu3boWPjw+UleuvXcUgPSprzEUGrBRLY87GxqZOjbm5c+fi0qVLAISLQb5UB5AQgoKCAmhra4vtAFbmzZs32L9/P6Kioijx7IqyYppqQrmzzJxPMNARL4/SsLU23md/EnlPS10NALBu3Tr4+vpCS0uLuc80EIFAQMleAUIZLOa7ZCKATQJzIjE0ZywtLeHu7o6TJ08iPT0dhw4dwsyZM+k2i6EG6qMxp6AgD3enrzC4Nwc+mwMxYcIEEEJq1Jhzc3NDx44d8eLFC1y5cgVPnz5F165dJTWUJqNCn+7Dhw/IysrChw8fqK2m102xQKKkpARKSkrgcDi4evUq2Gw28nhCh/LKnQcY2c9BrHYcu1kit4CHO4l/w95KuODjUcorAMIqL9KQgvmSOXXqFB49egRAmO9XoQHY0mEigI1EFubxGRgay/Lly6kKE5s2bcLUqVO/iKTvL4ng4GAEBATgzZs30NHUwJQRQyjnr6S0FIsCf8Wxy9dQVFIC157dsXuxL0z0hXluairKaKWhBm0NdUyYMAHr1q1DUlLVBQoVkjDz588HIIwChoSESG+Q/1JaWlovZ+7jx4/1KuXVFPTo0YMqv7dgwQJ4e3ujjZERrj94hLSMTLx+n4lZ7kKB7YyP2cj4mIOUN8L73uMXqdBQVUE7A33oaGnAskM7DHXoiRkbf8GepXMBAL9duAItLS2RFcAM9YeJ/tWMVGVgCgsLoaYmDGv3798f169fl1bXTUZTJVwzMMgaQ4YMoab/wsPDMWHCBJotYqggIiIC3t7eMDM1RWFuDkZ81RuHLlxB4tF9aGeojx82B+LczdsI/WkBWmtpYlHgfmTn5eNeaCC1kGPu9mCYGhli9f7DgJwc8gsKqu0rNzcXxsbG4PF4UFVVxdu3bxsVgaqYbq3Lmav8XlNWkaiMgoICdHV1oaenBz09Pbx48aLOkp6fY25ujqCgIAwZMkTk/eDgYCxbtgz5+fno0akjdsybhf49ugEA/H89jLUHjlRp6+BPCzBp+GAAQHZuPn7cEYz/3bgNgKCsXACviROxb9++hg2WAQDwxx9/UCLpDg4OiIuLYxzAf5GqAwgIS7rk5ubCwsKiWhFlWYUp6s3wpXP9+nU4OTkBEJYyfPToERPdlhF69+6Ntm3bCqVJ/i0y33XcdIzq74hlE8dC320sflu9GGMHDgAAvPvwEe2+8caf29ZiiIOo1t3Yn37G8as3ai0yP3v2bAQHBwMAtm3bJrIwSCAQICcnp0bnrbrXTaVH9zmqqqqUM1fZsavpdatWrURu/gsXLsT27dvF6ktZWRl+fn5YvHhxjTmy9+/fB4fDof5GDaVCB7C2vxFD3ZSXl8PGxgZPnz4FAFy8eBGDBw+m2SrZQepzPEZGRsjNzW1WU8CSSrhmYJAl+vfvjz59+iAuLg6JiYk4e/ZsgxTwGZqWCp251q1bUxpzADCotx3iHyeBm/wc/LIyDLb/z1Foo9ca1mbtEfc4qYoD2LldWygqCKuJ2NnZobS0tIrzVjnit2rVKpw5c0Yq063a2tpiOXMV71XUl28otWkBVubrr7/Gzp07YWZmVut+dnZ2cHZywuKgAxjcmyNW+a/P4RUVY0nQQTg7OTHOXyP5448/KOevT58+GDRoEM0WyRZSdwDbtGmD5ORk8Hg85OfnN1plW9JIMuGagUGWYLFYWLFiBYYPF+Yt/fzzzxg5ciQzXUIzFTpzL1+8oDTmAFA6cxkfc6CkqAhtTdFrqYGONjI+VtWhk5NjQV1FBRfOn4fRiRPIyMiotX8ej4fY2Nh6210x3SquM9e6dWupy5fUpQXYvn177Nq1q16rofft3w8bGxv4bA5E6MqF9YqiCwQC+GwORHp2Di7u3y/2cQxVKS8vx9q1a6nXa9euZa5ln0FLBLCCd+/eyVyCa0hICEJCQpCamgqBQIDCwkI429kgdOVCfMrnYVnwQVy+w8U/77Og20oTo/o7Yt2M76kl+wDgtycUia/SwALg5eUFe3t7ZjqYoVng5uYGW1tbJCQk4O7du7h69SoGDhxIt1kMAF6+eoWZbs7U67p05mqrt67CZiM1NRXl9YjkVUy3ijPVqqenV2W6VRapyQFUVFTE4sWLsWLFinpHGc3NzXHgwAEqh7auwEEFvKJi+GwORPjFaBw5coS5ZzSSY8eOITk5GQDQr18/uLi40GyR7EFLBLCC9PR0mXMATUxMsHHjRpibm2Oitzf+TnqKGwmJSEp9DUKA9KyP2OI7HV1N2yEtIxM/bA5EelY2jm/4iWqDEILJXw9G3KOniLx2EzOmT0d0TAyNo2JgEA8WiwU/Pz8qaXrDhg2MA0gzurq6kJeXB5/PpzTmgP905gxba6OUz0dOXr5IFDAz5xMcu1Uv4SIvJ4dygQCOjo5gsVjVOnOtW7fGzJkz8ebNGwDA3bt3m4UkTH2obgp40KBBCAoKQqdOnRrcrqenJwghmDZtGv56nITNvlMwsq9jjalD/7sZjyVBB5GenYMjR44wqUONpKysTKRMK7Pyt3pojwDKGhXq4FwuF7fv3EFkwEpM27ADt54kY+rIoTgRsJLat6NJG6yf+T2812xBWVk59c+9a4EPAODDp1y00W2NmGvXcP/+fSafg6FZ8O2338LCwgLPnz9HTEwM4uPj4ejoSLdZLZYKnbl79+5RGnPAfzpznC4WUFRQwOU7DzBmoLCaQXrWRzx5mYZNs6dW22a5QAA2m11nmbEFCxZQC0CCgoKohSFfCpaWllBWVkZxcTGMjY2xY8cOjB49ukmchfHjx8Pe3h4zpk/H6OXrYayvB1eOLWwtzKClrobcAh4Snr/EVa5w8aCLszMu7tvHRP6agKNHj+L58+cAACcnJzg7O9dxRMtE6kv8mosYdFhYGIz19VBYXAJecQkcu1lWu18ujwdNNdVqn+wAQFNNFcb6eggNDZWkuQwMTYa8vDyWLVtGvQ4ICKDRGgZA6IgRQnAiOhZJqa8x/5e9lM6clroapowYgkWB+3D17gM8+DsF3v5b0K1jBwzs1YNqI+Wfd3j47AUyPuagoKgIHc3M8PDhQ5SWltbY7+TJkynprt9++w2fPn2qcd/miI6ODm7evImwsDAkJSXhu+++a9JIkbm5OaJjYsDlcuE+ZiyeZubAb+8hTNuwA357D+FpZg7cx4wFl8vF1ehoxvlrAsrKyrBu3TrqdeVIIIMoUpeBiY2NxYABQqmCBQsWYNu2bdLsXiweP36M7t27gxACTTVVHFmzFMP62FfZ72NuHjiTfOE11AXrZ06q8rn/r4dxJjYetuZmeJqZg7v37knBegaGxlNaWoqOHTtS038JCQmwsbGh2aqWjZOTE27euAF5eTlYm3XA9h9nUjpzxSWlWBz0K36/FIOiklJKCLqtwX85bs4+i3H9weMq7b569QodOnSosd/KkjDbt2+nRKIZqufdu3cYNGgQMjMzcf78efTq1avKPkwBgaal8vf522+/4fvvvwcAuLi44OrVq3SaJtNI3QF8/vw5lVvh6emJo0ePSrN7sSgtLYWGhgZme3wNJUUFHDh7EdeCN6OraXtqnzweD0N+XAFtDXWc2eIPxWqqJlQ4gBPdBsJv7yEUFxdLcxgMDI1i165d+PHHHwEA48aNw++//06zRS0bujTmkpKSqNw/MzMzPHv2jBKXZhAlOjoaHh4eyM3NBQAMHjwYFy9epNmqL4/aCjKUlZcjISEBAHDjxg307duXZmtlF6k/gsh6DiAglC8oLS2FlVl7BPhMga25KXZGnKY+z+cVwm3eT1BXUcbJjauqdf4qo6WuhpKSEqmXKmJgaAzTpk2jVkn+8ccfVE4NAz1U1pjjFTXsYbIhGnOWlpaUftrLly9x4cKFBvX9JVNWVoaVK1di4MCBlPMH1C0zw1A/UlJS4OLsDA6Hg1N/RMDaUAcBsybhV7/5CJg1CdaGOshKfwsA6NTJAoaGhjRbLNtI3QFUV1entP9kNQdQTk5OpKg3IUApnw/g38jfPD8oKSrgzBZ/KLOV6mwvt4AHNpvNhPwZmhWqqqrUdJ9AIMDmzZtptohh3/79SM/Ogc/mwHo/UFbWmNtXT425uXPnUr/v2rWrXsd+6bx+/RpOTk5Yv349Pp9QMzExocmqL4+jR4/CxsYGac+fITJgJV5FhiF05SLMG+eOKSOGYN44d4SuXIRXkYcQGbASZTwebGxsmJmLWqDFI6lYCCKLEUA/Pz/cuHEDFubmuMZNwIo9Ybj24BHGD3FBPq8QQ35cAV5RMX71m488XuG/Rb6zUV5eTrVROdm6qKQEMdwEdDQzqzXZmoFBFvHx8YGmpiYA4NChQ1ROIAM9VGjMhV+MxuR128SOBPKKijF53TaEX4zGgQMH6r3YwM3NjaqCcfnyZSQlJdXb9i+R06dPo3v37vjrr7+q/ZyZKm8aKgoyjB7QBwmHg+Hu9FWNCy8rCjIkHA7G6AF9MGHCBJlMNZMFaHEAK6aBCwoKUFBDQXK6eP/+Pby9vfE0KQnn/rqN20+ScGHHegyytwP37+e4nZiMxy9SYfHdFLT5ejy1/ZP5gWpjesAO2H0/G/tOn8ez129x7q/beJqUJJMOLwNDbWhpacHX1xcAwOfzZXLRVkvD09MT4eHhOHE9DrbePjh57SbKysqr3besrBwnr92ErbcPTlyPa7DGnLy8PHUeAEJJmJZMcXEx5syZA3d3d+Tk5NS4H+MANoyAgAD06tULGhoaaN26Nby9vTHiq94IXbmQEtUuKS3FnG3B0Bs6BurOozBq8Wq8qXQfVlNRxprp3mij2xoTJkyAjo4O5s6dywRiKiH1RSAARDzyZ8+ewcLCQtom1AlT1JuBQUhmZiY6dOiAoqIiqKioIC0tjcltkgFSUlIwY/p0xFy7JpbG3N5Gasx9+vQJxsbGKCwshJqaGt6+fQstLa0mHFHzIDk5GePGjaMWGtTG6tWr4e/vL3mjvjCGDh2KcePGoVevXpg8aRISnzxGa01NPD22n3IAf9gciHM3byP0pwVoraWJRYH7kZ2Xj3uhgZCXl0d5eTl6TJwNHU0NvHibAV0jI3zIyoKHhwcCAwNpHqFsQGsEEJDNaWCAvoRrBgZZQ19fH9OnTwcAFBUVYefOnTRb1HIpLS3FmTNnUFhYKHWNuVatWlHyGjwer8VpmxJCEBYWBg6HI5bzBzARwIYSFRWFSZMmobi4GHfv3UPQwtn4J/MDuMnChWi5BTwcPHsRW+dOx0B7O/TobI7Dq5fg8YtUXLn7AABw6c59PE19jaNrlyyeHFQAACAASURBVGHngplIePQIvr6+2L9/P/Ly8ugcnsxAaw4gILsLQQD6Eq4ZGGSNRYsWQVFREYBw+q/ySkcGyUMIwenTp6Grq4tvvvlGZNbEzs4OgYGBuHvvHoqLi1FeXk7dOAMDA5v04fPzaeCWomyQn58Pb29vTJ48GYWFhXUf8C+MA9g4wsLCYGKgDwdrYSEGnX9LHXKTn4NfVobB9v+d2230WsParD3iHgvzU+MfJ8HarD3a6LXGyL6OMNbXw8uXL1FSUgIulyv9wcggTASwFhqTcP392q0Ij7qKnTt3MuruDM2etm3bYuLEiQCA3NxchISE0GxRy+Hhw4dwdXWFu7s78vPzAQAfPnyocX9Jqg107dqVqg394sWLFiEJk5KSAjs7Oxw5cqTexzLKD40jPi4OLnbdsHT3r+hrawXrjh0AABkfc6CkqChS+xoADHS0kfExW7hPdg4MdLQBCBeGuHJs8fDBAygpKSEjI0Oq45BVaHcAZTkCCDQs4bqb1yz8fjkGBMCJEydEVggzMDRXli5dSt3Qtm/fXq9ICEP9ycjIwLRp02BnZ4eYmBiRz2qr3CFpWpokjL+/P1JSUhp0bEuKAH748AGTJ0/GpEmTEBwcjHv37jV6wcWTxES8eJuORymvcHTtsjr3J4SIlPKrXNXP1sIMj588qbJPS6Z2BWMJUXkKWBYjgA8ePMD8+fOhr6+PiIiIehf1/qpPH+QVlyI7OxuXLl3C8uXLGQ01hmaPhYUFvvvuO0RERODDhw84cOAA5syZQ7dZXxxFRUXYsWMHAgICalRJoDOneNiwYTA1NcWrV69w6dIlJCcno0uXLrTZI2mcnZ0bFP0DWlYEMDg4GGFhYQCEklEAwGaz0aNHD9jb26N3796wt7dHx44dxXLABAIBSkpK8PTVa9wLC4KJ/n8Lzwxba6OUz0dOXr5IFDAz5xMcuwmr1hjqaONOYjL1WUVBBgAwMDBo9Hi/BJgI4L8QQnDz5k2MGjUKdnZ2uH79Oo4fP47w8HAA9SvqffOvv3Dy5Eko/FshZMuWLYwYJcMXwfLly6nft2zZwkgqNCGEEPz+++/o0qULVqxYUatElqmpqRQtE6WlScJMnToVd+/ehZubW72PbUkRQH19/SrvlZSU4NatW9i1axcmTJgACwsL6Orqws3NDatXr8b58+erTWcghFCR5lnuX8O0jWhFD04XCygqKODynQfUe+lZH/HkZRr6dBPmCzp2s8STl2lIz/oIQLhwREFBAWw2GxwOp8nG3awhNKGurk4AkM6dO9NlAiGEkLKyMnLixAni4OBAAFTZYmNjaz2+vLy8xs+CgoKodlRUVMj9+/eb2nwGBqkzfPhw6rw+ePAg3eZ8EcTHx9d4Dapu27t3L6325uTkEFVVVQKAqKmpkU+fPtFqj7T466+/iIuLi9h/p127dtFtstRITk4W+3v5fDM2NiY9e/YkS5cuJQKBgPzwww9ES0uLdLKwIGNc+5F3546Sd+eOEl7MGSKIjyKC+Cgy0304MdHXJZd3BRBuWBBx4XQnthZmhH/zTyKIjyL8m38Sa7MOxLVnd8INCyKDetkRRUVF4uvrS/dXJTPQ5gBaWFgQAERTU5OW/gsLC0lwcDAxNzev8aRUVlYmfD6/wX0IBAIyZcoUqr127dqR9+/fN+EoGBikT1xcHHVOd+rUiZSVldFtUrMlLS2NeHp61vuGeenSJbpNJ7NmzaLs+eWXX+g2R6ocP36csFisOv9OQUFBdJsqNQQCATE2Nm6wE1ixhYSE1PjZwZ8WUA5g4bX/kdmjRxIdTQ2iwmaTr7/qTdJOH6Y+F8RHkdRTv5HhfeyJCptNWCwW6datGykuLqb7q5IZaEtQqMgDzMvLA4/Hk1q/WVlZWLNmDdq1awcfH59ak3sdHByoadyGwGKxEBwcDAcHBwDCmpFjxowB/9+6wgwMzRFHR0c4OTkBEAq5nzx5kl6DmiGEEGzYsAGdO3duUHoInVPAFVTO/wwMrL9UVnMmNjaWqvtbWz5ZS5oCZrFYcHV1bXQ7pqamIMLgFCXXEhmwEoL4KEwaPpjaT5mthMCFPsi6eBy8a2fwv61r0NZAVKC+naE+zm5bi8P+iykdRzab3WgbvxRocwClnQeYkpICHx8ftGvXDv7+/sjKyqrzmArHrTGw2WxERkZS471+/ToWLFjQ6HYZGOjEz8+P+n3Dhg3UzZBBPOLj47FixQoUF9dfZJ7FYqFdu3YSsKp+dO3albrhtxRJGAD4559/sHfvXgCAqqoqEhIScObMGdjY2FTZtyU5gADg4uLS4GOVlJRw8OBBDBkyhHqPKcggWWiPAAKSXQl8584djB49Gp06dUJISAiKiorEPrYpHEBAONaTJ09CSUkJgDBp+uDBg03SNgMDHQwcOBA9e/YEINSpayk3/6aiffv20NbWbtCxJiYm1LWEbipLwrSU8lrr16+nFj/NnTsXBgYGGDlyJB48eIA//vgDlpaW1L6Vf/+S4fF4uHTpEm7dutWg4w0NDREfH4/JkydX+YwpyCBB6Jp73rJlCzWvf+zYMYn0cebMGbHyNGra0tPTm9SeAwcOUG0rKSmR+Pj4Jm2fgUGanDx5kjqf+/TpQwQCAd0mNStevHhBBgwYUO/rUv/+/ek2naKsrIyYmppStiUnJ9NtkkR58eIFUVBQIACIhoYGycrKqrJPWVkZOX/+PImOjqbBQulQUlJCbty4Qfz9/Un//v2JoqJig++zXbt2JampqbX2d/ToUcJisYj3UFeSH31aJM+vpi0/+jTxHupKWCwWOXr0qJS+meaFTEwBSyoC+OzZswZPTXXo0AGGhoZ171gPpkyZgtmzZwMQ1vT08PCQGRkcBob6MmrUKHTtKtTciouLw40bN2i2qHlhZmaG6Oho7Nq1CyoqKmIfJwv5fxXIy8tT1zSgekmYV69eYeXKlVi4cGGzLyG4bt06lJWVAQDmz5+P1q1bV9lHXl4ebm5ucHZ2lrZ5EkMgEOD+/fvYsmUL3NzcoKOjg379+sHf3x+xsbENzmt3cnLCzZs30b59+1r3a0hBBltvH5y4HocjR47A09OzQfZ98dDleUZHR1NPAIsXL5ZIHwUFBWTYsGENeioZN26cRGwqLS0l/fv3p/pxcHBgViUxNFsOHz5MncuDBw+m25xmy/Pnz8lXX30l1rXJ39+fbnNFyM7OpiRh1NXVyadPn4hAICBXrlwho0aNEpmF2blzJ93mNpjk5GQiJydHABBtbW2Sk5NDt0kSQyAQkKSkJLJ7927i4eFBdHR0aj0nzc3NyYwZM0hERATZv3+/WOfx+PHj633ve/78OXF2ciIAiLG+HpnoNpBsmzuD/Oo3n2ybO4NMdBtIjPX1CADi4uxMnj9/LqFv6MuANgcwKSmJOhG8vLwk1k9ZWRlZvnx5vR1AScoavH//nrRt25bqa+rUqcz0GUOzhM/ni0wB3rt3j26Tmi3bt28X69p06NAhuk2twsyZMyn7vvvuO2JlZVWt7T///DPdpjaYynI9zXkcNZGWlkZCQ0OJl5cXadOmTa3noJGREfHy8iKhoaEkLS1NpJ0PHz7UeQ6vWLGiUfc8LpdLfH19SU8Oh7DZbAKAsNls0pPDIb6+voTL5Tb262gR0OYA5ubmUieDi4uLxPuLiIignlLF2W7duiVRe7hcLlFWVqb62717t0T7Y2CQFJV1uzw8POg2p1ny999/ExUVFep7tLS0rPHaVJc4PR1ERUWJdV1trrp4jx8/piKZurq6JD8/n26TGk1mZiaJiIggM2fOrFUPtyLi6eHhQYKCgkhSUlKdzlv37t2rbUdeXp7s27evycdSW0EGhpqhzQEUCASUQ2ZpaSmVPh8+fEg0NTXrvEgpKSlJZVr2yJEjVJ8KCgrk+vXrEu+TgaGpKSoqIoaGhtS5nJiYSLdJzYqysjLSp08f6vubM2cOKSsrI5s2bSJKSkpVrk///PMP3SYTQgg1zTty5EixF9sdPnyYbrMbhIeHBzWGrVu30m1Og8jNzSVnz54l8+fPJzY2NrX+nVRVVcnQoUPJ5s2bCZfLrbfY+4IFC6q0qa6uTs6fPy+h0TE0BNocQEII9dShpaUllf7Cw8PFukg5ODhIxR5CCFm0aBHVr56eXpVwOgNDc6Dyqv6JEyfSbU6zYuvWrdR317FjR1JQUEB9lpiYSHr27ClyY6Y72lFYWEhCQkJI165dxZ5Rqdj+97//0Wp7Q+ByuZT9hoaGhMfj0W2SWBQVFZHo6GiyYsUK4uDgQOTl5Wv8uygqKpJ+/foRf39/cuPGDVJSUtKovv/880+R9o2MjJhSqDIIrQ5gv379qBNE0v9Un0+51lbPcd68eRK1pTJ8Pp8MGjSI6tvOzo4UFhZKrX8GhqYgLy+PaGtrU9M8r169otukZsHTp0+pHCYWi0Vu3LhRZR8+n082bNhArKysZGIKtT61cD/fZHH6ui4q176W5dq+fD6f3Lp1i/z888/E1dVV5H73+cZisQiHwyFLliwhUVFRIg8dTUF+fj7R1dUlAIiVlRUT2JBRaHUAx44dS52QN27cIHfu3CFnzpwhISEhZNWqVWTWrFnkyJEjje7n80UX06dPJwKBgBw6dIi6+FbeJKVLWBMfP34kZmZmVP8TJkxgFoUwNDv8/f2pc9jHx4duc2QePp9P7O3tqe9swYIFdJskFo2p95qQkEC3+fUiPj6esr1t27YypdggEAjIo0ePyC+//EJGjBhRZ3qTpaUl8fX1JSdPniTZ2dkSty8xMZGEhoaSvLw8iffF0DBYhEi+hlN6ejpu376Nd+/eIT09nfp57949fPjwoc7jU1NT69QJqgk+n4+BAwciNjYWgLCOaUxMDFUP8O7du3B3d8fbt2+bpL+G8uTJEzg4OFB1kbdt28aUjGNoVmRnZ6Ndu3bg8Xhgs9lITU1tci3NL4mNGzdi+fLlAIBOnTrh4cOH9dIDpIuYmBi4u7s3SNOPjmtrYxg8eDAuX74MANi7dy9mzJhBmy2EELx8+RLR0dG4evUqoqOja71/tmvXDq6urnB1dYWzs7NI9S0GBgCQeATw+fPn1UbZxN2UlJQapbc0e/Zsqq02bdqQd+/eVdknPT2d0uBycHCgLfoWGRlJ2SonJ0cuXbpEix0MDA2lck6rpPQ9vwQeP35MLfCQk5NrdlWBEhMTReR/xN2ak3be9evXKbtNTU1JaWmp1G149+4dCQ8PJ5MnTybt27ev9bvV09MjY8eOJfv27SMpKSnMLBJDnUjcAYyNjW2w8wcINaUayq+//iriSNYm7VJeXk64XC7t+Xc//fQTZbO2tjZJSUmh1R4Ghvrw7t07yrFRV1cnHz9+pNskmaO0tJRwOBzq/3zJkiV0m9QgMjMzxRavrtjqu5qULgQCgYhgf1hYmFT6zc7OJidPniS+vr61SgEBIJqammTEiBFkx44d5NGjR4zDx1BvJO4AlpeXiyz2qO924cKFBvUbFxcnIqFw8ODBJh6ZZCgvLydff/01Zbe1tfUXoTnF0HKYNWsWdf6uWbOGbnNkjnXr1onkZRUVFdFtUoMpLi4mXl5eYl3LNTQ06DZXbC5fvkzZ3alTJ8Ln8yXST0FBAYmKiiJLliwhHA6nVjkdNptNXF1dyc8//0xu3bolMZsYWg5SWQTy9OnTavWs6tqMjY0b9MT49u1bYmRkRLUzZ84cCYxKcnz69Il07tyZsv/bb79lnu4Ymg0vX76kJCd0dHSYB5hKPHz4kCgqKhJAuFr6zp07dJvUaAQCAVm7dm2d1/O2bdvSbapYCAQC0rt3b8ruo0ePNlnbJSUlJDY2lvj7+5N+/fpR50J1m7y8PHFwcCArVqwgV69ebdYPCgyyidRWAa9evbreDqCfn1+9+ykqKhL553VycqIld6OxJCcni6zqWr9+Pd0mMTCIjbe3N3Xubtu2jW5zZIKSkhKRCgkNub7JMseOHatVesTa2ppuE8Xi3LlzIjY3RnexrKyMcLlcsnnzZjJ06FCipqZW6z3PxsaGzJ8/n5w9e5bk5uY24agYGKoiNQewuLhYJKolzlbfQs4CgYBMmTKFOr59+/YkMzNTQiOSPOfOnaOmBFgsFjl79izdJjEwiEViYiL1f2hkZCRT8hl0sWrVKuo76dat2xf5ndy6dYvo6+tXez3/6quv6DavTgQCAenRowdlc2RkZL2PT0pKIkFBQcTDw4PSxqxpMzc3JzNnziQRERHN+l7F0DyRqg5g5VVVdW39+vWrd/uBgYHU8SoqKl+E8vjPP/9MjUlTU5MkJSXRbRIDg1i4u7tT5+6ePXvoNodWuFwuNS2uoKDwRRerT01NJdbW1lWu6YMHD6bbtDqprMTQo0cPsVJv0tLSSGhoKPHy8iJt2rSp9b5mZGREvLy8SGhoKCOOzEA7UheCnjZtmlgOYGhoaL3ajYmJESl105R5G3QiEAjI6NGjqXF17tyZfPr0iW6zGBjq5M6dO9R5a2pq2mKT1ouLi0UcotWrV9NtksTJzc0lbm5uItf0Xr160W1WrZSXl4v8nc6dO1ftfpmZmSQiIoLMmDGDKmda06atrU08PDzI7t27SVJSEpPLzSBTSN0BzM7OrnGKoGJTV1evV+J4amoqVXYGaL6yCjWRn59PunXrRo1v+PDhtNcDZWAQh8plDsPDw+k2hxb8/Pyo76B79+6NrrPaXODz+WTChAnU2AcNGkS3SbXy+++/U7b27t2bctZyc3PJ2bNnyfz584mNjU2t9y5VVVUydOhQsmXLFsLlcpuN7A1Dy0QqlUA+59ixY/D09Kzx8ylTpuDAgQNitVVYWIi+ffviwYMHAIAhQ4bgzz//hLy8fJPYKiu8fPkSvXr1QnZ2NgBgxYoVWL9+Pc1WMTDUzrVr1+Ds7AwAsLKywqNHjyAnJ0ezVdLj7t27cHBwgEAggKKiIu7evQtbW1u6zZIq69atw61btxAWFgY9PT26zamWsrIyWFlZ4dmzZwCATZs2IS8vD1evXsXdu3dRXl5e7XGKiopwdHSEi4sLXF1dYW9vDyUlJWmazsDQcOjwOgUCARk6dGiNT1E3b94Uux1PT0/quI4dO0qlxiFdXL58mcjJyVHjPX78ON0mMTDUikAgIH369KHO2dOnT9NtktQoKioSEfNdt24d3SbJHLIwk8Hn80UE+GvT4mOxWITD4ZAlS5aQixcvkoKCArrNZ2BoMLQ4gIQItcJUVVWr/IN16tRJ7DyJzZs3i0wbP3nyRMJW08/27dupMaupqZFHjx7RbRIDQ61UltWwt7dvMXlQS5YsocbN4XCapRxVU8Plcomvry/h2NlRJULZbDbh2NkRX19fqSyOKS8vJ48ePSI7duwgI0aMIBoaGrVO61paWhJfX19y8uTJLzrAwNDyoGUKuIKtW7di8eLFIu8FBARg2bJldR578eJFDBs2DAKBAABw8uRJuLu7S8ROWYIQgokTJyI8PBwAYGpqinv37kFHR4dmyxgYqocQgu7du+PRo0cAgMuXL2PgwIE0WyVZ4uPj0bdvXwgEAigpKeH+/fuwsrKi2yzaSElJwYzp0xFz7RqM9fUwsKctbC06QlNNFXm8QiQ8f4Er9xLwNvMDnJ2csG//fpibmzdJ34QQvHz5ElevXkV0dDSio6Px4cOHGvdv3749XF1d4eLiAhcXFxgZGTWJHQwMsgatDmBZWRm6deuG5ORkoTEsFt68eYM2bdrUelxKSgp69eqFT58+AQBWrVqFNWvWSNxeWaGoqAj9+vUDl8sFAAwcOBAXLlyAgoICzZYxMFRPREQExo0bBwBwdnZGdHQ0zRZJjsLCQnTv3h3Pnz8HAGzcuBFLly6l2Sr6OHr0KKZNmwYjHW1s8Z2KEX0doKBQNUe7rKwcZ2/ewuKgA0jPzsGBAwdqzRWvjXfv3iEmJgZXr17F1atX8fr16xr3lZOTowIJJ06cgIeHB1gsVoP6ZWBoTtDqAAJAbGwsBgwYAADo0KEDXr16Vev++fn5cHBwwNOnTwEAI0eOxKlTp1pUYjkA/PPPP+jZsycyMzMBAAsXLsTWrVtptoqBoXrKy8vRpUsXpKSkAADi4uLg6OhIs1WSYcGCBdixYwcAoHfv3rh582aLfTg7evQovLy84DXEBcFL5kBNRbnOY3hFxfDZHIjwi9EIDw/H+PHj6zwmJycH165do6J8SUlJNe6rqamJAQMGwNXVFe/fv0dAQAAAYPjw4Th37pz4g2NgaO7QNvlciXXr1pGePXuShISEWvcrLy8n33zzjUhuRksulxMbG0sUFBRavMwGQ/Pg119/pc7VESNG0G2ORIiNjaUWEbDZ7BYr3L57925iYmJCABAdTQ0Ss3szEcRHkayo42T26JGkUztjosJmk7YGesT3u5Ek53IkEcRHUdvLyDBirKdLaenNmTNHRD6noKCAREVFkSVLlhAOh1Prwg1lZWXi6upKNmzYQG7dukXpUfJ4PGJoaEjt9yWLczMwVAftEcD6sHbtWqxevRoAoKWlhTt37qBTp040W0UvISEh8PHxAQAoKyvj5s2b4HA4NFvFwFCV0tJSdOzYEW/evAEAJCQkwMbGhmarmg4ejwdbW1u8ePECgDDHeeHChTRbJX0iIiLg7e0NM1NTFObmYMRXvXHowhUkHt2HPF4h/H89jO+HDUJX03ZIy8jED5sDYWNuiuMbfgIgjBb3mDgbOpoaePE2A7pGRviQlQUHBwfY2Njg6tWruHXrFvh8frX9y8vLw97enpJmcXR0hLJy1cjjtm3bsGjRIgCAh4cHIiMjJfelMDDIInR7oJ9TkyzAmTNnRJbi//nnn1K2TDYRCARk+vTp1HdjYmJCMjIy6DaLgaFadu7cSZ2rnp6edJvTpMyZM4caW58+fVqsCLC9vT359ttvCQASGbCSCOKjSJf2bclS7zEiUb6KLWK9H1FSVCSlN/4kgvgo8uf2dUROTo68+d8RciJAKM+iqKhY60pdW1tbMn/+fHLu3DmxZoXy8/Op4gEsFos8fvxYCt8MA4NsQXvi3P379zFnzhz05HCgrKwMeXl5KCsroyeHgzlz5uD+/ftITk6Gl5cXdcyGDRswbNgwGq2WHVgsFgIDA6l8qjdv3uC7775DaWkpzZYxMFRl2rRp0NXVBSCMFFXkBFbw999/Y8qUKdDS0sLEiRPpMLFBXLt2DYGBgQAAFRUVhIaGfnFi9OJQWloKLpeLwsJCmBjoY0RfBwDAoN52iH9cfV5eLo8HTTVVamFI/OMkWJu1Rxu91hjZ1xGGrbWrRPvMzc0xc+ZMREREIDMzEw8fPsT27dsxfPhwaGpq1mnnrl27kJWVBQAYO3YsrK2tGzNsBoZmCW0OYEpKClycncHhcHDqjwhYG+ogYNYk/Oo3HwGzJsHaUAen/ogAh8PBoIEDkZ+fDwAYM2ZMi15RVx1sNhuRkZHU6ukbN25g/vz5NFvFwFAVVVVV6twUCATYtGkTAODBgwcYM2YMLC0tERoairy8PBw+fBi5ubl0misW+fn5mDx5MvU6ICCgWaWmlJSUYO3atfDz88OFCxca9Z1nZWWhvLwcL1+8gCvHhnLqDLS1kfFvFaPKfMzNw/rQ3zHjGzfqvYzsHBjoaAMAFBTkMdieg1ZaWpCTk8PMmTORlpaG58+fY8+ePRgzZky9q4vk5uZSC+bk5OTg7+/fwNEyMDRvaFmaVlkWIDJgZZ2yAAsD90NOjoXOnbvg4MGDzBL9ajAyMsKpU6fQr18/lJaWIjg4GD169MC0adPoNo2BQQQfHx+q1FZoaChevHiBmJiYavclzSBFecmSJUhNTQUA9O/fH3PmzKHXoHpy6NAhKrc6ICAAcnJy6N69O/r374/+/fujX79+VNRWXF6+eoWZbs7UawICFkSv23k8Hr5euApdO7TD6qleIp9VvsTbWpghIvoG5OXl4eTkhHbt2tVzhKLs2LEDOTk5AABvb2907ty5Ue0xMDRXpB4BrJAFGD2gDxIOB8Pd6atqnT9A+PTn7vQVHofvwfjBLkhOTsaZM2ekbHHzwd7eHnv37qVe+/j4IC4ujkaLGBiqoqWlBTc3YcSnvLy8RucPENZalWUuX76MPXv2AADU1NQQGhra7CSp2Gy2yGuBQID79+/jl19+gYeHB/T09GBtbQ0fHx8cO3YM7969q7EtXV1dyMvLg8/nQ1NNlXo/M+cTFdUDgHxeIdzm/QR1FWWc3LgKipVkcgx1tJHxMYd6raWuhpKSEvD5fBgYGDRqrB8/fsT27dsBAAoKCli1alWj2mNgaM5I/EoVEhICGxsbaGpqQl1dHV5eXnC2s0HoyoVQU1HGvtPn4eyzGFquHpBzHIpP+QUix6emZ2Du9mDcTHgCORYLXl5emDNnDpPjVgOTJk3C3LlzAQB8Ph/ffvst3r59S7NVDAxCxyIyMhI9e/ZERESEWMfIsgOYl5eHqVOnUq83b94MMzMzGi1qGF999VWd+yQmJiIkJASenp4wNjaGubk5pk6dikOHDuHVq1dUpFZJSQkcDgdycnLI4xVSx1+58wCO3SwBCCN/Q+b5QUlRAWe2+EOZrSTSl2M3Szx5mYb0rI8AgNwCHhQUFMBmsxutcLB161YqnWjy5MnN8u/FwNBUSNwBNDExwcaNG3Hv3j1YW1lBS10NNxISkZQqVGYvLC7BEIeeWP792GqPT059A0II9iydiwe/BUNfWxt79+6Fn5+fpE1vtmzduhXOzsLpl4yMDHh4eKC4uJhmqxhaKnw+H4cOHYKVlRVGjx6N+/fvi32sLDuACxcuxD///AMAcHFxwaxZs2i2qGF07Nix3nl0L168wMGDBzFp0iSYmZmhVatW1HexYMECEEJwIjoWSamvMf+XvXj9PhOz3Icjn1eIIT+uAK+oGL/6zUcerxAZH7OR8TEb5eXlAIDB9nbo2qEdJq7Zggd/pyAq/h5YLBamT58u1gKPmsjMx38ZAwAAIABJREFUzMSuXbsACB3VlStXNrgtBoYvAmktN7537x4lC6CtoU72L58nIgUQvXsTAUCyL52oViqgYquQBTA2NpaW6c2SzMxM0r59e0omYfLkyUTwf/buO77G833g+Cc7kUQkSKgdYpRIOREiWgmKUIq2iFUjduxVirYoRa1SI0TQxmjVqH5L2oq0spDR2CNWS5BIIpE9zvP7Iz9PHbLXybjfr1denHOe57mvc5KcXOce161UqjssoYpJTk6WbG1t8yzhkduXlpaWusPP1cmTJ+U4jYyMpLt376o7pGJ5ucB+Ub/WrFkjX69r166SlqampKujLbVv0Uzy3bpW5X0+p687R/bI7/P3ju6T+na2kwz09CQNDQ3J2tpaSk1NLdZznDVrltyWm5tbcV8yQajwymwRyJ49e6hnXpvk1DSSUtPk4YDC6t/FHuNq1cQQcD5q167NsWPH6Ny5MykpKXh6etK+fXvc3NzUHZpQhURGRhIcHFykc8vr9mnPnj1TWVy1bt06GjdurL6ASoCDgwPHjh0r8vl169ZV6QFdv349CoWCH778lIGO/w0xO7a3QRl4Kt/rNaxjzol1yzji68eHC1ewZ8+e1+YqFkZkZCTbtm0DsgvmixEkQSijRSCXLl1i69atREY/xW3dtxz5aglvNmlUpGvdf/yE1PQ0qlWrlv/BVdxbb73F7t275dszZ87E19dXfQEJVU7Tpk2ZPXt2kc4tr8O/M2fOlOfV9uzZk/Hjx6s5oqJLTU3Fz8+PO3fuFPka48aN4969exgbG8v3tW/fHidHR+Zt8SAppWjTT5JSUpm/ZTdOjo60b9++yPFBdu3YF9Ngpk6dSt26dYt1PUGoDMpkK7j09HSMjY2ZOug9dHW08Tjhje/WNSpJoG9oON2mLiD2t8PUMDbK8TqR0TE4TpmHWXVjwm/fE/PaCmjBggWsWbMGyF6lFxwcTKNGRUvABaEo9u3bx8SJEwv1O2tqakpsDrXj1OnEiRP0798fgOrVq3P58mUaNGig5qgK7smTJwQEBODv709AQAAhISFFHk3R0tJiw4YNuLm55ViaKyIigrZt2/Jh1854LplTqNXRSqWSMcvXcfjPAC5evEizZs2KFCPA/fv3sbKyIiMjA0NDQ+7evVvoOY+CUBmVSQ+gtrY26enptLZsxKopY7Fp1oRNhwo33BAZHUM3t/nYt2mF6/vOpKWloVQqSyniymXlypX06tULyC7UOnDgQJKTk/M5SxBKzqhRowgKCirUqsvy1gMYGxvLhAkT5NsbN24s18mfUqnkypUruLu78/HHH2NlZUWdOnUYNGgQ69atIzAwsMjJX40aNTh16hTTpk3LtS5rs2bN8PDw4HtvH8YsX1fgnsCklFTGLF/H994+eHh4FCv5A1ixYoW8k8iMGTNE8icI/69MJtloamqip6cnlwWQJEjPZSPvnDyMeko3twUoWjZj9+LZfPPDcfT09CpcvS110dLS4sCBA9jZ2REREUFYWBiurq54eXmJotpCmbGxsSE4OJhRo0bxyy+/5Ht8eZsDOH36dB4/fgxAnz59GD16tHoDekVSUhLnz5+Xe/gCAwN59uxZnuc0b94cBwcHOnfuTFBQEB4eHvm207JlS37++WesrKzyPdbFxQVJknB1dcX/0jXWuI2lfxf7XAv//+wXyPwtu3kUG4eXlxcuLi75tpGXiIgIPD09gewe2zlz5hTreoJQmZT6O+yiRYtwdnbGqlkzfEPCiX4Wj2/YRU5uWAHw/yUA4oh4kF1c9NLtexhXM6ChhTlmJsZERsfgNHU+DS3MWes2nuhn8QRdvkZLUb29UExNTTl27BidOnUiMTGRAwcO0K5dO+bNm6fu0IQqxNTUlOPHj7Ny5UqWLl2a504f5akH8OjRo3h5eQHZvV/u7u5q//D08OFDeSjX39+fsLAwuZRKTvT09LC1tZUTvs6dO6v0htWuXTvfBNDZ2ZkDBw5gYmJS4DiHDRuGnZ0dE8aP58OFK6hnXpvuChtsrCwxMTIkPjGJ8Ft3OB0SzsOoaLo5OeHt7l7snj+AZcuWya/J7NmzMTMzK/Y1BaHSKO1lxmPHjpUaNWokaWpqSpoaGlI3hY3kvWmlvNx/6bjhOZYE2L14tqQMPCXtXjw717IBQuEdPXpUfv00NTWlU6dOqTskoYry9vaWzMzMcv39btasmbpDlCRJkqKjoyVzc3M5rn379pV5DJmZmVJYWJi0ZcsWycXFRaXEU25ftWvXlgYMGCCtXbtWCggIyLeMSlRUVJ7Xmzt3rpSZmVms5xESEiK5ublJtgqFpKenJwGSnp6eZKtQSG5ublJISEixrv+ya9euSZqamhIgmZmZSc+ePSuxawtCZVAmi0AAQkNDUSgU/LRqiUpZgMJ6URYgJCSk2CvDqqrPP/+cL774Asjuzbhw4UKJfNoWhMK6f/8+H374YY6lYlq1asXVq1fVEJWqoUOHyjuX9O/fn2PHjpV679/z588JCgrC398ff39/goKCSExMzPOc1q1b07lzZxwcHHBwcKBp06aFjrNFixbcvHlT5T5dXV15HmFRSZKUYyxKpbLUpvK8/H1btWoVn3zySam0IwgVVZklgADdnJy4f+sm4d9txdBAv9DnJ6WkYjNyCo2smuOTx/6hQt6USiWDBg2S91Vu3bo1gYGBKmUcBKGspKamMmPGDNzd3VXub9y4MXfv3lVTVNl+/PFHBg8eDICZmRlXrlyhTp06JdqGJEncv39fHsr19/fn0qVLeS5yMzAwoGPHjvJwrr29PaamprkeX1Bjx46V58wBWFhYcPToUezt7Yt0vZSUFDp16sSlS5eYMGGCvG9yabt48SI2NjZA9tD2nTt3MDLKubqEIFRVZZoAlpeyAEL2PqadOnXi2rVrAAwcOJDDhw+LhTWC2nh6ejJx4kR5xaa6y8BERUXRunVrnj59CsD+/fuLvSgBsrfG+/vvv1USvsjIyDzPeeONN+Sevc6dO/PWW2+VyhxJLy8vRowYAWTX8jt27FiRVzpHR0fTq1cvwsLCgOxFGPHx8SUWa14GDhwoF7Zev349s2bNKpN2BaEiKdMEEODAgQMMHz6cEb26sXX+tAL1BCalpDJ5zWa8vH3YvHkzU6dOLYNIK7+bN29iZ2cnvykvW7ZM7I8pqFVwcDBvv/02qamp2NvbExAQoJY4JEniww8/5MiRIwB88MEH/Pjjj0Ua+o2LiyMwMFBesHH+/Pk8yzBpampibW2tkvA1atSoTBadZGVlsWLFCjQ0NJg7d26RC+5HRETg7OxMRESEfF9ZJYAhISHY2toC2YlzREQEBgYGpd6uIFQ0ZZ4AQvYnaVdXV+qamRaoLMC8LR7cf/QYpVKiVatW+Pn5idVcJeTkyZP07dtXXo15/PhxudCtIKhDfHw8f/75J3369FFbKZgDBw4wbNgwILt4+pUrVzA3N8/3PEmSuH37ttyzFxAQwJUrV/I8x8jIiE6dOskJX8eOHalevXqJPA91CAwMpF+/fsTExKjcr6enR0pKSqknsn369OHkyZMAbNmyRXQYCEIu1JIAQvYnxAnjx3PG1zffsgBOjo7cvXePe/fuAdn7Vv7+++/iU10J+eqrr1i4cCEAxsbGnDt3jlatirZXsyCUttJcOADw6NEjWrduTVxcHAA//PADH330UY7HpqWlERoaqpLwRUVF5Xn9Ro0ayT17Dg4OWFtbo6X1+gfgiuinn35ixIgRue74kpiYiKGhYam1HxgYSOfOnQFo2LAhN2/eLNYewoJQqZX5uuNXFLQswO3btyULCwu5JEH//v2ljIwMNUdfOSiVSmnw4MHya2tlZSXFxcWpOyxBkCTpv/cIRfv2Ku8RivbtS7x0iFKplPr16yf/LgwZMkTl8aioKOnYsWPS/PnzJQcHBzme3L60tLQkW1tbacaMGdKhQ4ekBw8elFis5c2GDRskDQ2NPF+P+/fvl2oM3bt3l9vauXNnqbYlCBWd2noAc5PXp/uwsDC6du3K8+fPAXB1dS0XBVkrg6SkJBwcHAgPDweyC76eOHGi0vRMCBXPq6MEPWxtsLFqSnXDaiQkJRN+6zZ/BP83SuC+c2exF4d99913jBo1CgBzc3OOHj3K1atX5QUbr5ZIeVWNGjWwt7eXe/js7OxKtcerPMjKymL27Nl88803+R4bGhpKu3btSiUOX19fnJycALC0tOT69evlqpi4IJQ35S4BzI+Pjw+9e/eWVwouWbKEZcuWqTmqyuHevXvY2trKc3cWLlzIypUr1RyVUBW9PE94rds4+nXplOs84RN+Qczb4sGj2Dg8PDyKvFI3IiKCdu3ayfX2jIyM8q2917RpU3nunoODA61atapSK+mTk5MZPny4vOI2P7///js9evQo8TgkSeKdd97Bz88PgH379jFy5MgSb0cQKpMKlwACHDp0iKFDh8q3t27dyuTJk9UYUeXh4+NDz5495e2TDh06JNdBE4SysH//fkaMGFHoSgFT1mzme28fvv/+e3kBR14eP34sz93z8/MjODg4363pbG1t5bl7nTt3xsLColDPrTKJioqif//+nDt3rsDnHDx4kCFDhpR4LL/99hu9evUCsvcqvnz5shi9EIT8qG/0uXg2btwoz/XQ0NCQfvrpJ3WHVGm8/NpWq1ZN+vvvv/M8XqlUllFkQmX17bffSo0bN5Z0dXUlDQ0NqaddeynT/1dJGXhKSvnzZ2nqh/2lmibVpWr6elK/Lh2lf45/J28nGbZvqzT03a5SffNakpampqShoSF9+umnKtfPzMyUwsPDpW3btkkjRoyQmjRpku9WajVr1pT69+8vrV69Wjp79qyUkpKiplen/Ll+/bpkaWmZ72v46te3335b4rEolUqpQ4cOchsHDx4s8TYEoTKqsAmgJEnSggUL5F96PT09ydfXV90hVQpKpVL6+OOP5de2cePGUnR0dI7Henp6SnXr1pX69+8vZWVllXGkQmVw8OBBSUdHR9q5c6dk16GDZGJkKBnq60v3ju6TlIGnpIkD+0r1ateSftu0UgrZs0VyUthINlaWUobf/yRl4Clp16JZkttH/aUz366RLn6/XaptWkPS1NSU3NzcpGXLlkm9evWSqlevXuAkZfr06dL169fFB5tcXL58Oc89nPP6WrZsWYnH8/PPP8vXt7a2Fu9DglBAFToBfDVRMTExkS5evKjusCqFlJQUlU/V3bp1U1l1nZ6eLk2bNk3lzf3s2bNqjFioqOzs7KRJkyZJwcHBEiD9tGqJ1LJRA2nByMFS3O8/STra2tKB5QvlHr8HP3tJmpqa0skNK+T7Xv46vGpxvomIvr6+9Pbbb0sLFiyQ3nrrLfn+0aNHq/vlKPemTp1apOTvRXJdkrKyslS+f0ePHi3R6wtCZVahZytraGiwc+dO+vTpA2QXkO3duzf3799Xc2QVn76+PkeOHJHnOPn4+DBv3jwge4unnj17snnzZpVzgoKCyjxOoWJLT08nJCSEnj17smfPHupbmNOvSyfe7diewEvXCLl+i4zMTHratZfPeaN2TdpYNiLg0rUcr9m/iz36uroq91lYWDBo0CDWrVtHUFAQ8fHx/PXXX1haWvL3338DUK9ePTZs2FB6T7aSGDx4MCYmJkU699Xi0MV15MgR+funUCh4//33S/T6glCZqafMfgnS0dHhhx9+oHv37pw7d47IyEh69eqFn58ftWrVUnd4FVr9+vX56aefcHJyIiMjg40bN2JmZoaHh0eOSbZIAIXCevr0KVlZWVhYWBAYEEB3RVu0tbWwMDXlcWwsj2Pi0NXRwbS6scp5FmamPI7JeZ/gC9dukJ6RQU0zMzZs3IiDgwNNmjR5rVzUvXv3mDNnjnx7165d1KhRo+SfZCXzzjvv8O+//7J//362bdsml44qiJJMALOysvjss8/k28uWLRMlwQShECp0D+ALhoaG/PLLLzRv3hyAGzdu8N5775GUlKTmyCo+BwcHlZ6+pUuX5trDKhJAoag0NDS4fOUKNlZNAZCQ0CD3P+aSJOX4x/7KnXsMWPAFPTsqSExKYuTIkVhaWr52rFKpZNy4cXKZF1dXV3r37l2Cz6hyMzY2ZuLEiYSFhREQEMDIkSMLtG1fSSaAhw4d4urVqwDY29vj7OxcYtcWhKqgUiSAkL1fp7e3N3Xr1gXg3LlzDB48WK4XKBSdq6srNjY2+R738OFDHjx4UAYRCZVFrVq10NLSIjIykrS0NKobVgMgKu4ZFmam1KlpSnpGBnEJz1XOe/H4y67evU93t09w7e/Mh93eJi0tDaVSmWO727dvx8fHB4AGDRqwbt26Unh2lZ+Ghgb29vZ4enpSp06dfI8vqQQwMzOTzz//XL69fPly0fsnCIVUaRJAgMaNG3Pq1Cl5I/Vff/2VCRMm5FnbS8hbXFwcffv2LfAwj+gFFApDV1cXhULB6dOn0dPTIyEpGYA/zodhb90KRUsrdLS1+f18mHzOo6cxXL5zn87W/+1XfeXOPbpNXcCoPj34ctJo4hOT0NPTy7Eo8507d+T5rAC7d++W3zOEojl16pT84a937954e3szYMCA117/F/srF9d3333HrVu3AOjatSvdunUrkesKQlVSqRJAgLZt23L8+HF0/38S+J49e/j000/VHFXFdOXKFezs7PD29i7wOSIBFApr9uzZ7Nq1izoWFvwZdpFZG3fwz5MoJg3si4mRIWP79WLuZndOXwgj7EYEIz9fi3XTxvTokL2l2JU79+jmtoB37dox22UQj2NiCbp8jZYtWrzWllKpZMyYMSQnZyeakyZNKpWdKaqabdu2yf+fMmUKPXv25OjRo9y/f5+lS5fKIzNdu3Ytdlvp6ekquz+J3j9BKCJ1L0MuLT/++KPKxuTffPONukOqUI4ePSoZGRkVusyDg4ODukMXKqBvv/1WMjY2lgCpXfOmku/WtXJZl2Tf7ELQZtWNJQM9Pek9h47S/WP/FYJeOm54jj+LxsbGr7XzcpHzxo0bS8+fP1fDs61c7t69K7/XNmzYUMrMzHztmPT0dOnq1atSenp6sdvbtm2b/D3s2bNnsa8nCFVVhdwKrqC2bt3K1KlTgey5KgcPHhTbmhVAWFgYCoWiSEPn+vr6xMfHyz2wglBQoaGhKBQKflq1hIGODkW+zhFfPz5cuIKQkBDat/+vfMzNmzd56623SElJAeDMmTM4OjoWN+wqb9GiRaxatQqAFStWlOqIS2pqKs2aNePhw4dA9lxvOzu7UmtPECqzSjcE/LIpU6awePFiIHvV4MiRI+WJ30Lunj17VuR5k6mpqVy8eLGEIxKqgvbt2+Pk6Mi8LR4kpaQW6RpJKanM37IbJ0dHleQvKyuLMWPGyMnftGnTRPJXAtLT0/Hw8ABAW1ubcePGlWp77u7ucvLXr18/kfwJQjFU6gQQsmtDvXhTSk9PZ8CAAYSFheVzVtXm5OTEvn37sLKyKtL5Yh6gUFTuO3fyKDaOKWs257qCNzdKpZIpazbzKDYO9507VR7buHEjAQEBADRt2lTusRKK58iRI0RFRQEwaNCgAq0ELqrk5GRWrlwp3355HqAgCIVX6RNADQ0Ntm/fTr9+/QB4/vw5zs7O3L17V82RlW8jR47k2rVrHDlyBHt7+0KdKxJAoaiaNWuGh4cH33v7MGb5ugL3BCalpDJm+Tq+9/bBw8ODZs2ayY9dv35dHpbU0NDA09MTQ0PDUom/qnl58cfkyZNLta1vv/2WJ0+eAPDBBx/w1ltvlWp7glDZVeo5gC9LTk6mR48eBAYGAmBlZYW/vz+1a9dWc2QVg7+/P2vXruXnn3/Od3i4adOmRERElFFkQmW0f/9+XF1dqWtmyhq3sfTvYo+2ttZrx2VmZvGzXyDzt+zmUWwcHh4euLi4vPR4Jg4ODpw/fx6AWbNmsX79+jJ7HpXZlStXaNOmDQCtWrXiypUrpbYa9/nz5zRp0oSYmBg0NDS4dOkSrVu3LpW2BKGqqDIJIEBsbCxdunTh2rXsPUQ7dOiAj48PRkZGao6s4rhx4wbr1q1j3759pKWl5XpcVFSUSK6FYomIiGDC+PGc8fWlnnltuitssLGyxMTIkPjEJMJv3eF0SDgPo6Lp5uTEDnd3lZ4/gNWrV/PJJ58A0Lx5c8LCwqhWrZo6nk6lM23aNLZs2QLApk2bmD59eqm19eWXX8rzuYcNG4aXl1eptSUIVUWVSgAB/v33X+zt7eWJxL169eLnn38Wq1YL6cmTJ2zevJmtW7fmWNx17969jBo1Sg2RCRWZJEkEBATQqlUrzMzMgOzVwZ6engQFBnLp8mXS0tLQ09PDuk0bOtnbM2bMGJUFHy9cuXKF9u3bk56ejqamJn5+foWeziDkLDExkXr16pGQkEC1atV4+PBhqe2j/OzZM5o0acKzZ8/Q1NTk2rVr8rafgiAUg1qKz6jZ5cuXpRo1asi1pEaMGCFlZWWpO6wK6fnz59I333wjNW7cWKUG2/Dhw9UdmlDBREVFSTY2NhIg6enpSampqTkeV5Df1fT0dEmhUMg/j/PmzSvpcKs0d3d3+bUdN25cqba1ZMkSua0xY8aUaluCUJVUuR7AF/z8/Hj33XdJTc2eZD537lzWrl2r5qgqrszMTPbt28f8+fNJT0/Hx8cHW1vbXI9XKpU5btMlVE2//voro0ePJjo6Wr7v7t27NG7cuEjXW7FiBUuWLAGy56eFhoair69fEqFWeZIkoVAo5GoKwcHBKBSKUmnr6dOnWFpa8vz5c7S1tbl58yZNmjQplbYEoaqpsn+Bu3TpwoEDB+Qk5OuvvxaTw4tBW1ubsWPH8vTpUxISEl5L/kJDQ5k2bRq2CgX6+vpoaWmhr6+PrULBtGnTCA0NVVPkgjolJSUxefJk+vbtq5L8AUVeqRseHi6XCNHS0mLv3r0i+StB58+fl5O/Dh06lFryB7B27VqeP38OwLhx40TyJwglqMr2AL7g7u7OxIkT5dteXl4MGzZMjRFVLq9O5O9ha4ONVVOqG1YjISmZ8Fu3+SM4eyK/k6Mj7jt3vjaRX6iczp07x8iRI7l161aOjyckJGBsbFyoa6anp9OxY0f+/vtvIHuXii+//LLYsQr/GT16NHv37gVg9+7djBkzplTaefLkCZaWliQnJ6Onp0dERAT169cvlbYEoSrSVncA6jZhwgQePXrE559/DmS/udWuXZt3331XvYFVAi+X8vhp1RL6demUaymPE35BzNviQdu2bV8r5SFULhkZGXz55ZesWLGCrKysXI8zMDAo9LVXrlwpJ39t2rRh6dKlRY5TeF1sbCyHDh0CoEaNGgwZMqTU2vrqq69ITk4GYOLEiSL5E4QSVuV7ACF7TsvkyZPZsWMHAEZGRvj6+pbq0EZlt3//fkaMGMGIXt3YOn8ahgb5D8ElpaQyZc1mvvf24fvvvxc9sZXQzZs3GTlypFyXLzfa2tpkZGQU6tqhoaF07NiRzMxMtLS0OH/+fI6rg4WiW79+PXPmzAFg5syZbNiwoVTaefDgAc2aNSMtLQ0DAwPu3LlTqruMCEJVVGXnAL5MQ0ODb7/9loEDBwLZJQ6cnZ1FMeMi2Lp1Kw0aNGD48OGYGhsxtl8vDA30iY1/zrR1W2k5ZByGju/TaMBIpq/fSnxiknyuoYE+NYwNMTU2Yvjw4bRq1UqNz0QoSZIksX37dtq1a5dv8geF7/1LS0tj9OjRZGZmAvDpp5+K5K+EKZVKtm/fLt+eNGlSqbW1cuVKuc6om5ubSP4EoRSIBPD/aWlpsX//ft5++20AoqOj6dWrF48fP1ZzZBXHoUOHmDlzJobVqtHAojZDe3TlvblL+edxFJFPY3j0NIa1buO5+P02PBfPwTsoBNeVqj0IEvDpaBeMDAx48O+/6nkiQol6/Pgx7733HpMnT5aH9PJT2ARw+fLlXLp0CQAbGxt56zeh5Pj4+MjzNbt160aLFi1KpZ179+6xa9cuIHs0Zv78+aXSjiBUdSIBfIm+vj7Hjx+Xtze6c+cOffr0ISEhQc2RVQzr16+nf//+3Lh5k40zJ7FlnhsNzGuz7cgvtGnamMOrltDv7U40rf8G3WzfYsXEjznhd47MzP/mgX0zewqzXAbh3NmWxKQksTq4gjt+/DjW1tb8+uuvhTqvMAnghQsX+OqrrwDQ0dFh7969orB7KSirfX+XL18uD//PmDGDWrVqlVpbglCViQTwFaamppw8eZIGDRoAEBYWxqBBg0hPT1dzZOVbeno6ISEhJCcnU9/CnH5dOgHwbsf2BF66luM58UlJVDesluPCkBYNG6CjrYWnp2epxi2UntDQUAYOHMjTp08LfW5By7akpqby8ccfy4tJli5dio2NTaHbE/L28OFDjh8/DkDdunV5//33S6WdiIgIeYWxiYmJPN9QEISSJxLAHNSvXx9vb295K6rTp08zevRolEqlmiMrv54+fUpWVhZ3bt+mu6KtnNRZmJryODb2teNj4hNY4XmACQOcc7yepqYGRgYGBAUGItYpVUyZmZlF/t4VtAfws88+k/f2VigULFiwoEjtCXnbtWuXnGS7urqio6NTKu188cUXcjtz5szB1NS0VNoRBEGUgclVq1at+OWXX+jevTspKSkcOHAACwsL1q9fj4aGhrrDK7fu3L3LRGcn+baEhAaqr1dCUhLvzVnKm40b8tm4Ebley0BPj7CwMPT09DA1NcXMzIyaNWsW+N9q1aqJ71UpkCQJT09Pnj59iqurq/xB6VV2dnYcOXKEuXPncufOnUK1kVMC+OruMRcuXODrr78GQFdXlz179pRaYlKVZWZmsnPnTgA0NTUZP358qbRz9epVvLy8ADAzM2PGjBml0o4gCNlEApgHe3t7fvjhBwYMGEBWVhYbN26kbt26YlJyDmrVqoWWlhYZGRlUN6wm3x8V9wwLs/8+xT9PSsZ55mKMDPQ58tVSdLSYGrfEAAAgAElEQVRz/xHU0tQkS6kkS6kkKiqKqKioQsWkq6tbqITxxb9i14i8hYSEMG7cOADWrFnDqlWrGDt2LFparw/lDxw4kL59+7J9+3aWL19e4OFgAwMDQkND8fT0JDAggMtXrpCWloaenh5tWrfGvnNnkpOT5V75L774Qp67K5SsEydO8PDhQwD69esnT48pCS8n9R4eHnKP8YIFC6hevXqJtSMIwutEApiP9957j507dzJ27Fgg+42pTp06jBo1Ss2RlS+6urooFAqCg4NJSPpvpecf58Po/3b2fMCEpCR6z/wUPR0djq/9HH29vCfqZymVaGtrY21tTWxsLDExMSQmJhY4pvT0dB49esSjR48K9VwMDAwKnTiamZlVmYUHL4ZcAWJiYpgwYQLu7u5s2bKFjh07vna8rq4u06dP5+OPP2bNmjWsWbNGLteSm0sXL6JQKOTdY4a/PVpl95ijPxziYVQ0JtWr49ynD3Pnzi3x5ylkK8nFH3kl9fr/3+vbsmVLpk6dWqx2BEHInygEXUArV66US0toaWlx4sQJnJ1znr9WVR06dAgXFxfs27Rk56JZuB87ya6fT3LZawdm1Y3pOWMRyampHPlqqUph6No1TOTeo4h/I0lMSWH70f9x8Hdf6jdshNf+/bz55pvo6uqSnp5ObGysnBAW9N+UlJRSf/5GRkaFThxNTU3RzqMXtDzatGkTM2fOzPGxsWPHsmrVKszNzXN8/M6dO7Ro0SLPBFBTU4MGFuasnz6hQLvHPIqNE7vHFFNgYCCff/45CoWC2bNnyytvb926RfPmzQFo2rQpN2/eVBmGL6jCbAn5dpcu7Pb0FFtCCkIpEwlgAUmSxPTp09myZQsA1apV48yZM9jZ2ak5svLF0dERv7Nn0dLSpI1lY9bPmMg77azxDQ2n29ScJ+jfObKHxnWzC706TZnHn2GXXjvm7t27NG7cuMhxpaSkvJY45pc0xsTElMnqbxMTk0IPU9eoUaNIf4hLwtKlS1m+fHmuj5uYmLB8+XImT578WnI7bNgwDhw4APy3DeOJEydUjhneqxvbF0wXu8eUod69e+Pt7Q1kf5CZOXMms2fP5ssvv2TdunVA9nD/vHnzCn3tl7eEXOs2TiT1glBOiASwELKyshg6dCiHDx8Gsue9+fv7y5+QhewhHoVCwU+rljDQ0aHI1zni68eHC1cQEhKith0dJEkiOTm50L2NsbGx+Q5xFpeGhkaRFsZUr1692Atjpk6dytatW/M9ztrami1btvDOO+8A2XMHbW1tgewPUC1atODWrVtoa2ujVCp5/jyBYT27sXfpXDQ1NUlLT2fu5l0c/N2XlLQ0utu+xbfz3KhvXltuY8aGbfiHX+Hvm7eRyN5qTvQcFV7Hjh1f26GlevXqZGRkkJKSgp6eHg8ePCh0TT6xJaQglF8iASyk1NRUnJ2d8fX1BaBx48YEBARQt25d9QZWjnRzcuL+rZuEf7e1QG/4r0pKScVm5BQaWTXH58yZUoiwdEmSxPPnzwudOMbFxZV6qSEtLS15zmJO8xhzSx6NjIzkxNHFxYWDBw8WuM1hw4axZs0aRo0ahY+PD5A9z2vBggV06NCBzMxMunfrRnx8PA9+9sLcrAYAk9ds5he/c3gunk1Nk+rM3byT2ITnBHtulqcMTF+/lRYN6xNw8So/+frh4NClQv7MqFuHDh0IDg7O9fF27dpx9uxZDA0Ncz1m1apVHDlyhOvXr2NgYEDbtm3x8/NjsFMXPJfMQVNTE/djv3LgtzOE3rjN8+RkYn87TA1jI5XrxCU8Z/r6rfxw+i8yMrN4//332bNnDzVq1Cix5ysIgkgAiyQ+Pp6uXbsSHh4OZG899eeff2JiYqLmyMqHiIgI2rZty4ddO8tv/AWlVCoZs3wdh/8M4OLFi1WqN0epVBIfH1+oxDE2Npa4uLhSj01HR0dOCCMjI3n27FmhzjcwMJDnYVpaWnLt2jV50czLPYO+W9fyTjtr4hOTMHcewr7P5jGkR1cAIqNjaDhgJP9bt4xenWxVrv/5ru/Y9+sf3Hv0RK29xhWVQqHId9ed2rVr88knnzB58uQcy/T07t2boUOH5pnUbzx4lNT/n1axaJtnjglgn1mLeRD1lI2zJjHqi6+JT0nBycnptakCgiAUT8WafV5OmJiYcPLkSezt7bl//z7h4eEMGDCAkydPihIiQLNmzfDw8GD48OEARRr68fLyqlLJH2TXWDM1NcXU1JSmTZsW+LysrCyePXtW6GHqwmxxmJGRwZMnT3jy5ElRnprKIpxBgwaprJjes2cPdWqa8TgmFrPqxgCEXL9FRmYmPe3+S+TeqF2TNpaNCLh07bUEEKC6YTXqmdfG09NTJICFVJCe5+joaObMmcPXX3/NokWLGD9+PHp6evLjp06dkv8fEhJCzP8XgL9+/185AZw5dCAAvqHhObZx7d4/nAoKJnDXRjq2bsk3cybx4cIV/PLLL9y4caPU9h8WhKpIJIBFVLduXby9vXFwcCAmJgZfX19GjhzJwYMHc6yHVtW4uLggSRKurq74X7rGGrex9O9in+vk75/9Apm/ZTePYuPw8vISk78LQUtLi5o1a1KzZs1CnZeRkUFcXFyhE8ekpKRixbt3717Wrl0r3w7w90dbS5MuNq1p07QxAI9j4tDV0cH0/xPCFyzMTHkc8/rOMpA9L7K7wobjx46hq6uLpqYmWlpaaGpqvvb//G6Xh2OLcq6GhkaR5ni+2H2jIB49esS0adNYs2YNixcvZsyYMa8V4M4pqS+IwEvXMDEypGPrlgD072JPPfPaRD+LJyAgQCSAglCCRAJYDC1atOB///sf3bp1Izk5mcOHDzNz5ky++eabKrkDxblz55g0aRLJycmcPn2aYcOGYWdnx4Tx4/lw4Qrqmdemu8IGGytLTIwMiU9MIvzWHU6HZJd/6ObkhLe7e5Xr+VMXHR0dzM3Ncy3ZkhsTE5NC9R6+ysFBdXHQ3+HhmBhWY/+yT/I9V5KkPH+3bKws+f7UadavX1/k+Co6DQ2NQieTRenZ/ffff5k4cSKzZs1i69atfPzxx/JjOSX1BfE4Jg5z0//m+mlra9FdYcMhn7M8fvy40DEKgpA7sRdwMXXs2JHDhw/L5S62bNnCqlWr1BxV2ZEkCW9vb3r06EGnTp34+++/uXnzJkuXLgWyh4N9zpwhJCSEgYOHcDUqjkU79uK6cgOLduzlalQcAwcPISQkhNM+PiL5K+cyMjKKnPzVr1+fgIAAjh49Kt/n5uaGUqlk/sjBKqt769Q0JT0jg7iE5yrXeHVnmVeZGBmirOLTmiVJIisri/T0dFJTU0lOTiYxMZH4+Hi5xzcqKorHjx8TGRnJgwcPyMjIKHJ7ycnJzJ49W+W+v8PDSUpJLVBS/6pX83sbK0vS09Or5IdqQShNogewBDg7O+Ph4SF/Av7000+pU6eOvHtIZZSens7Bgwf5+uuvuXTp9bp9r87Bat++vcp9r+7rKlQMhV1woqmpKc8v+/XXX7G2tgayk5Rp06Zx9OhRdHR00HtlCFHR0godbW1+Px/G4B7ZZWQePY3h8p37rJ46Ltf24hOT0NPV5bSPD0qlUv7KysrK9XZej5XVsS9uZ2VlyQlcYc8tThxPnjwp1DDwq14uip9bUl8QdWqa8iRWdYGRiZEhkiRRu3bhriUIQt5EAlhCRo0axePHj1mwILvY8YQJEzA3N+e9995Tc2QlKz4+Hnd3dzZt2iTvD5qTQYMG5XkdkfxVTDExMfkeo62tzcCBA9HQ0OCHH34AYPTo0XLyB9m1BPfv38/x48eZPm0aQZev8jimKyaGhhjo62FiZMjYfr2Yu9mdmibGmFU3Zt7mXVg3bUyPDu3k67zYOeZxTBwpaWmcCQmnadOmdOjQocpszVcSrKysiIiIKNQ5GhoafPjhhyxcuJB27drlm9QXhL11K+ITkzh/5QZ2rbPn+12MuAtAly5dCn09QRByJ8rAlCBJkpg9ezYbN24EsktfnD59Gnt7ezVHVnwPHjxg06ZN7Nixg+fPn+d5bIMGDfjnn3/KKDKhLPn7++f6h7hevXpMnDgRV1dX0tPTadGiBWlpaejr63Pz5k0aNGggH5vbcN7uxbMZ3bcnAKlp6czbsosDv50hJS1dLgTdwOK/nqDS2jmmqmnatCl37twp0LFaWloMGzaMRYsW0bJlS/n+KVOmqCT1Lc1rsHHWZDmpB3gcE8vjmDiCr99kwqpN/Lnta4yrGdDQwhwzk+zFIn1mLSbyaQzbF0zPvj17CZKmVqFLDwmCkDeRAJYwpVLJ8OHD5UK5ZmZm+Pn50apVKzVHVjQXL17k66+/5sCBAwXe3eKjjz6Se36EyuWPP/7g3XffVbnv3XffZfLkyfTr10+eCztq1Ci+++47AObPn8/q1atzvWZl2j2momrSpAn37t3L8xhtbW0+/vhjFi5cmGOZooIk9Z/v+o5lHl55HhMb/5wZG7by89lzgERmlpIRo0bh7u5euCclCEKeRAJYCtLS0ujbty+nT58GsnvEAgMDqVevnpojK7i//vqLL7/8kt9++63Q565bt+61SeFC5ZCQkEC3bt14+PAhLi4uTJo06bWtEMPDw+UhQVNTU27fvo2pae4LN0DsHqNujRo1yrXXXldXl3HjxrFgwQIaNWpUoOuJpF4Qyj+RAJaShIQEHB0dCQsLA6BNmzb89ddf+f4hLA+CgoJwcHAo8rZkAQEBlWLYWyia3r174+3tDRT8w4DYPUa96tev/9qcXn19fSZMmMD8+fOL9OFVJPWCUL6JmfilpHr16pw8eRJLS0sALl++zPvvv6+yI0J5lZycXOTkT0dHh3bt2uV/oFAp/fHHH3Ly16hRI6ZOnVqg817sHvO9tw9jlq8jKSW1QOclpaQyZvk6vvf2wcPDQyR/JUBTU5O5c+dy9+5dNm3aVOSRC/edO3kUG8eUNZsL/X6iVCqZsmYzj2LjcN+5s0jtC4KQN5EAliILCwu8vb3l8gVnz55l+PDhxSq3UBa6devG6tWri1R3q127dmI7vCpKqVQyf/58+faKFStUtgrLj4uLC99//z2H/wzAZuQUjvj6kZmZ8+9KZmYWR3z9sBk5hcN/BojdY4qpTp068v9f7NTy8n1FIZJ6QSjfxBBwGQgODsbR0VHeQmvixIls27at3Bc2PXnyJC4uLsTHxxf4nOnTp7Np06ZSjEoor/bv3y/v//zWW28REhJSpHI/ERERTBg/njO+vgXaPWaH2D2mWO7fv0+TJk2QJIkGDRpw9+7dYm1neefOHXR0dORV3/v378fV1ZW6ZqaF2hLSw8NDJPWCUJokoUx4e3tL2traEiAB0hdffKHukArkxo0bUqtWreS48/vav3+/ukMW1CA1NVVq3Lix/HPw22+/FfuaISEhkpubm2SrUEh6enoSIOnp6Um2CoXk5uYmhYSElEDkwqJFi+Tv2/Lly4t0jcTERGnv3r1S27Zt5Wv99ddf8uO3bt2SnBwdJUCqZ15bGuXcQ1o3fYK0a9Esad30CdIo5x5SPfPaEiB1c3KSbt26VVJPTxCEXIgewDLk5eXFiBEj5Ns7duxgwoQJeZ4j5bP3aVlISEjAzs6OGzdu5HusqL9WNW3cuJFZs2YB2WVhirJ6PD9i95iSl56eToMGDYiKikJbW5t///23wEO/kiTh7+/Pnj17+OGHH16rD7p69WqVKQGQvTrY09OToMBALl2+TFpaGnp6eli3aUMne3vGjBkjVvsKQllRb/5Z9axbt07+hKypqSkdPXo0x+MyMzOlefPmScbGxtKSJUvKOEpVx44dK1Dvn4WFhaRUKtUaq1D24uLiJDMzM/nnIDQ0VN0hCQV08OBB+fv20UcfFeicf/75R1qxYoXUrFmzXN8LNDQ0pOjo6HyvlZWVVdynIAhCEYkEUA3mzp0rv1Hq6+tLZ8+eVXk8NTVV+uijj+RjtLW1pfj4eLXEeuXKFcnIyEiOZcSIEZKhoWGOb/rvv/++WmIU1OuTTz6RfwaGDx+u7nCEQujatav8vfPx8cn1uOTkZGn//v3Su+++K2loaOT7YbBz585l+CwEQSgKMZ6iBqtXr5aHglNTU+nXrx+XL18Gsvfa7d27Nz/++KN8fGZmJr6+vmUeZ1xcHO+//z6JiYkADBkyhH379hEYGCiXt3lZp06dyjpEQc0ePHggb32oq6vLihUr1ByRUFBXr17lzz//BKBly5Y4OjqqPC5JEkFBQUyaNIm6desybNgwfv/9d6QCzBrq27dvaYQsCEIJEgmgGmhqauLh4UHPntlbHz179ozevXsTHBxM165dc0z2XtRWKytZWVkMGzZM3iDexsYGDw8PNDQ0sLa25sKFC/To0UPlHFH8uer57LPPSE3NLu/h5uYm5n9WINu3b5f/P2nSJJW5xj4+Prz55pvY29uzY8eOQlUCAJEACkJFIBaBqFFiYiJOTk4EBwcD2UWUMzIycjy2adOmcjJWFj755BN5/9ZatWpx4cKF1/64Z2Zm8sknn7BhwwZat25NcHAwurq6ZRajoF6XL1/GxsYGpVKJiYkJt2/fpmbNmuoOSyiApKQk3njjDRISEjAwMCAyMpIaNWrIj7/55ptcu3atSNeuV68e//77r9oXrwmCkDfRA6hGRkZG/O9//6N+/foAuSZ/ALdv3+b27dtlEtfBgwfl5E9LS4sff/wxx54dbW1tvv76a6KioggLCxPJXxXzySefyDs8LFy4UCR/FciBAwdISEgAsgtwv5z8AfTp06fI1+7Tp49I/gShAhAJoJqFhoYSExNToGPLYhg4LCyMsWPHyrc3bNjw2tygV9WsWbNYhWOFiufPP//kf//7H5C9j+z06dPVHJFQUJIksW3bNvn25MmTXztm9erVOd5fEMVJHgVBKDsiAVSj7777jn79+hV4f+DSTgCjo6MZMGCAHM+YMWNwc3Mr1TaFikeSJObNmyffXr58OQYGBmqMSCiMCxcuEBoaCoCtrS22travHaOlpcW3337L4sWLC3VtHR2d1+YGC4JQPokEUA0kSWLt2rWMGjWKzMzMAp/n4+NDenp6qcSUkZHBRx99xD///ANAx44dK8R2dULZ+/HHH7lw4QIA1tbWjBw5Us0RCYWRX+/fCxoaGixfvpwNGzYU+Npdu3bFyMioWPEJglA2RAKoBosXL36tQn5BJCYmEhgYWAoRwezZs+WSEHXr1uXIkSPo6emVSltCxZWens6iRYvk21999ZUY/q9AYmNjOXjwIAA1atRg6NCh+Z4zc+bMAh0HYvWvIFQkIgEsY3FxcaxatarI55fGMPDu3bvZsmULkF3L7ciRI7zxxhsl3o5Q8bm7u8uLkRwdHXF2dlZzREJh7N27Vy7b8/HHH1OtWrV8z/H09JSTxvyI+X+CUHGIBLCM1ahRg+7duxf5/JJOAIOCglSGgbZt2yYKOgs5SkhIYNmyZfLtNWvWiCkCFYgkSa/V/svP0aNHcXV1lW+PGTMGY2PjHI9t2rQpVlZWxQ9UEIQyIRLAMqahoYG3tzdnzpxh2LBhhR5mDQ0NJTo6ukRiiYyMZNCgQfK8wqlTp6qsABaEl3399dfyz96QIUPo0KGDmiMSCsPHx4ebN28C4OTkRMuWLfM9fujQoXKpnxkzZuDh4cGZM2eoVavWa8f37dtXfCAQhApEJIBqoKmpiaOjI15eXkRGRvLNN99gbW1d4PN///33YseQlpbGoEGDePToEZA9ebswk72FquXRo0esW7cOyF7p+eWXX6o5IqGwCrr4AyA4OJj3339f/nA4cuRI1q9fj4aGBgqFAj8/Pxo2bKhyjhj+FYSKRSSAamZmZsa0adMIDw/n3LlzjB8/Pt9VdMePHy9Wm5IkMWXKFM6dOwdAw4YN+fHHH9HR0SnWdYXK6/PPPyc5ORnIHjps2rSpmiMSCiMyMpJjx44BUKdOHQYMGJDrsdevX8fZ2VneA/y9997Dw8MDTc3//ly0aNECPz8/uRexbt26dO3atRSfgSAIJU1sBVcOJSYmcujQIXbt2kVQUNBrj+vq6pKamlrk4ZYtW7Ywbdo0AAwMDPD396ddu3bFilmovK5fv06bNm3IysrC2NiY27dvU7t2bXWHJRTCsmXL+Oyzz4DsKgTLly/P8bh//vkHBwcHHjx4AMA777zDqVOncq3zGB8fz+HDh3FwcMh3SFkQhPJFJIDl3OXLl9m1axd79+7l2bNn8v3p6el59tgplUqVT+wv+Pr60qNHD7KysgDYv38/Li4uJR+4UGkMHDhQ7j1asWIFn376qZojEgojMzOTxo0b8/DhQzQ1Nbl37x4NGjR47bjo6Gjefvttbty4AUC7du04c+YMJiYmZR2yIAhlQAwBl3Nt2rRh48aNPHr0iA0bNtCyZUvmzp37WvIXGhrKtGnTsFUo0NfXR0tLC319fWwVCqZNm0ZoaCjp6ekMGTJETv7mz58vkj8hT/7+/nLyV7duXWbOnKnmiITC+uWXX3j48CGQPZybU/KXkJBA79695eTPysqKU6dOieRPECox0QNYwUVERDBh/HjO+PpSz7w2PWxtsLFqSnXDaiQkJRN+6zZ/BIfzMCqazvb2BAYFIUkSvXv35pdffhFFfIVcSZKEg4ODXHzc3d2d8ePHqzkqobB69erFb7/9BsDJkyfp3bu3yuOpqak4Ozvj6+sLQL169fD396dRo0ZlHaogCGVIJIAV2P79+3F1daWumSlr3cbRr0sntLVfT+gyM7M44RfEvC0ePIx+yoCBA9m1a5fYsknI09GjRxk0aBAALVu25NKlS2hra6s5KqEwIiIi5Np8lpaW3Lp1S2VqSGZmJh988AE///wzkL0o7ezZs7z55ptqiVcQhLIjhoArqP379zNixAg+7NqZ8O+2MtDRIcfkD0BbW4uBjg6Ef7eVwd3e5ocffpDf8AUhJ5mZmSxcuFC+vXr1apH8VUA7duyQ/z9x4kSV5E+pVOLq6iq/FxgaGnLy5EmR/AlCFSESwApm69atNGjQgOHDh2NqbMTYfr0wNNAHwP3YrzhNmYdJ90Fo2vfm2fNElXOjnz1DW1uLavp6DB8+nIYNG/LZZ5/Jtb4E4QUPDw95PliXLl3o16+fmiMSCis1NRVPT08gu3LAmDFj5MckSWLu3Lns3btXfvz48ePY2dmpJVZBEMqeSAArkEOHDjFz5kwMq1WjgUVthvboyntzl/LP4ygAklPT6NXJloUfD8nx/Ov3HiBJEl6fL6CBhTk1TEzYvn07ixYtKsunIZRziYmJcskQEFu+VVQ//vgjMTExAHz00UcqpXtWrVolF37X1NTkwIEDxdqiUhCEikckgBXI+vXr6d+/Pzdu3mTjzElsmedGA/PabDvyCwAzhw7kk1FD6NQm53pcve1t2b14Dv3fsWfDzAlcunwZFxcXjhw5UpZPQyjn1q9fz5MnTwAYNGgQ9vb2ao5IKIrcdv7Yvn27SimfHTt2yHM9BUGoOkQCWEGkp6cTEhJCcnIy9S3M6delEwDvdmxP4KVrhb5e/y721DOvjb+/P2ZmZiUdrlBBRUVFsXbtWgC0tLRYuXKlmiMSiiI8PFxevW1tbU3nzp2B7FGEKVOmyMetXr0aV1dXtcQoCIJ6iQSwgnj69ClZWVncuX2b7oq28oIPC1NTHsfGFvp62tpa2LW0Iiw0lEmTJpV0uEIFtWzZMnkLsAkTJtCiRQs1RyQUxfbt2+X/T548GQ0NDby9vRk5ciQvCj/Mnz+f+fPnqytEQRDUTCSAFcydu3exsfpvH1YJCQ0KPz8rMjqGs+GXkUD0AAgA3Lp1S141amhoqDIPUCj/lEql/P+IiAgAjIyMGDFiBAEBAQwaNIiMjAwg+3f+q6++UkucgiCUDyIBrCBq1aqFlpYWGRkZVDesJt8fFfcMCzPTQl0rMjqGbm7zsWpQD6VSyc2bN1X+eAhV06JFi8jMzARg7ty5WFhYqDkiIS957f5jamrKu+++y08//URcXBx9+/YlOTkZgA8++IDt27eLhT2CUMWJwl4VhK6uLgqFguDgYBKSkuX7/zgfRv+3OxX4Og+jntLNbQGKls1QtLDi3JXrtGjRgurVq2Nra0vHjh2xs7OjY8eO1K1btzSeilAOnTt3jsOHDwNgbm7OnDlz1ByRkJucdv8Z/vZo1d1//vTlYVQ0mRkZdHV0lPcR79GjB15eXmIHIEEQRAJYkcyePRsXFxcO+/xFr04K3I+d5J8nUUwa2BeAxzGxPI6JI+JBJACXbt/DuJoBDS3MMTMxJjI6Bqep82loYc5at/HM3rQDNAApey9QHx8ffHx85Pbq16+vkhAqFAqxe0glJEmSylywzz//HGNjYzVGJOTm5d1/flq1pEC7/6wOCqJt27bY2tqyadMm9PT01BC5IAjljdgKroJxdHTE7+xZtLQ0aWPZmPUzJvJOO2sAPt/1Hcs8vF47Z/fi2Yzu25M9//uNsSvW53jdN954g8jIyDzb1tTUpHXr1nJCaGdnR+vWrcUOERXciRMn6N+/PwDNmzfn8uXL6OjoqDkq4VUvdv8Z0asbW+dPkwvA5yUpJZUpazbzvbcP33//PcOGDSuDSAVBqAhEAljBhIaGolAo+GnVEgY6OhT5Okd8/fhw4QpCQkJo3749AA8fPuTcuXOcP3+ec+fOERwcLK8IzU21atVQKBQqPYUNGjQQ84sqiMzMTGxsbLh69SoAhw8f5oMPPlBzVMILf/31F2vXruX8+fNERUXRtV1bTm/5Ck1NTTIyM1m8Yy8nAy5wJ/IRJkaG9LBtx6opY3mjdk35GjHP4rEbN4O7kY8xMjJiwIABbN68mRo1aqjxmQmCoG4iAayAujk5cf/WTcK/21qgXoBXJaWkYjNyCo2smuNz5kyux2VlZXHt2jU5ITx//jyXLl0iKysrz+tbWFioJIS2trbij0055eHhIQ08XVsAABA6SURBVK8C79SpEwEBASJ5L6bQ0FBWr15NixYtGDx4MK1bty7ya3ry5En8/f05fuwYl69cYf+yTxj6riMA8YlJfLRoBa79nbGxakLc80RmbdxBZlYWFzw3y9foM2sx/zyJ4tnzZOo0aEB6RgaNGzfmxIkTJfF0BUGooEQCWAFFRETQtm1bPuzaGc8lc1Q2eM+PUqlkzPJ1HP4zgIsXL9KsWbNCtZ2UlERYWJhKT+H9+/fzPa9ly5YqQ8dt27ZFV1e3UG0LJSs5ORkrKyt56P+vv/7i7bffVnNUFV+vXr347bff5NutWrVi8ODBDB48mDfffLPQ1wsJCcHW1haAI18tZUDXzrkee+HqDTqOm8G9o/toWMeca/f+obXLBAJ3beRh9FM+XLiCPXv2MHr0aK5fvy7qPApCFSYmb1VAzZo1w8PDg+HDhwMUaT6Ql5dXoZM/yK4P16VLF7p06SLf9+TJE86fP6/SUxgfH69y3vXr17l+/Tr79u0DQE9Pj3bt2qn0FFpaWorepzK0adMmOfnr37+/SP5KyKvzJ69du8YXX3zBF198QevWreVksGXLnLdsfNWePXuob2HOgydR+R4bn5iEhoYGNYwNAQi8dA0TI0M6tm5JZmYW9cxrExwcjImJCQEBASIBFIQqTCSAFZSLiwuSJOHq6or/pWuscRtL/y72ua4I/NkvkPlbdvMoNg4vLy9cXFxKLBYLCwv69etHv379gOxexlu3bqkkhH///bdchBYgLS2NoKAggoKC5Ptq1qyJnZ2dnBB26NCBWrVqlVicwn+ePn0qFwLW1NRk1apVao6o8sjrg9WVK1f47LPP+Oyzz7C2tpaTwebNm+d6TmBAAN0Vbdn76x95tpuals7CbZ4M6+lIdcPsBPBxTBzmptnTL7S1teiusCEoMBBzc3MeP35chGcnCEJlIRLACmzYsGHY2dkxYfx4Ply4gnrmtemusMHGyhITI0PiE5MIv3WH0yHhPIyKppuTE97u7kXq+SsMTU1NWrRoQYsWLRg5ciQAqamphIeHqwwdv9it4IWYmBhOnjzJyZMn5fuaNm2qMnTcrl079PULP+9RULVixQoSEhIAGDt2bJGGJoWcFfT369KlS1y6dIklS5ZgY2PD4MGD+eijj7CyslI57vKVKwx/ezSQewKYkZmJy9JVKJVKvp3npvLYy53qNlaWHPLZKxZqCYIgEsCKrlmzZvicOUNoaCienp4EBQZyyGcvaWlp6OnpYd2mDQMHD2HMmDHyal910NfXp2PHjnTs2FG+LyYmhgsXLsgJ4blz54iJiVE57/bt29y+fZsDBw4AoK2tjY2NjcrQcfPmzQs1D7Kqu3PnDlu3bgXAwMCAL774Qs0RVS5F+YAVHh5OeHg4n376Kaampnh5eeHs7IxSqSQtLU1l959XZWRmMuTTldyNfMzpLavl3j+AOjVNeRL7TL5tYmRIWloa0dHRYqcXQajiRAJYSbRv314lwVMqleU+KapZsya9e/emd+/eQHZB4rt376oMHYeGhpKamiqfk5mZSUhICCEhIXISY2JiQocOHVR6CuvUqaOW51QRLF68WB6Onz17Nm+88YaaI6pcitvDHhcXx9y5c3F2dkZTUxM9PT2V3X9e9iL5u/XgIT5bVlPTpLrK4/bWrYhPTOL8lRvYtW5BfGISOjo6xMfH07lz7otJBEGo/EQCWEmV9+QvJxoaGlhaWmJpacnQoUMByMjI4NKlSypDx9euXVM5Lz4+nj/++IM//vhviKxhw4YqCaFCocDwpZ6Rqio4OFjuTa1Vq5bKDiBC0SQnJ3Pnzh0iIiKIiIjgxo0baGhoUJwCCy9K8yQmJmLZpAlnQv4G4G7kY/6+eRuz6sa8UasmHy1aQeiNCE58vYwspZLHMbEAmFU3RldHh1aNG9K7ky0TvtrI9gXT+eN8GNra2vTq1UssABGEKk6UgREqnPj4eIKDg1WGjvOb0K6pqUmbNm1Uho7ffPPNMt0TdceOHezevZvJkyczevToMmv3BUmS6NGjh7zd36ZNm5g+fXqZx1ERPX/+nIiICG7fvi0nei++Hj58WGLtvPnmmxw4cIC2bdsC4Ovri5OT02vHfdynB5+5jsBy0Ogcr/N/7d1/TJT3HQfw9ykWBeWXgJwU8eC5QofWCAQ8JxTOrsSZNvrP/DGMQ0WidTE1zhqbrtncppW2lqAulZ2gVUZUnHWu2vmL2lYEBEWxt4CHP0o9BOFWBY+jcLc/CM847uDg4JTz3q/kEvPc83x5iMa88/l+v5/v+d0fICl6BgCg+cfHWL9zD058fRkt+jbI5XKUlJSwNyeRi2MAJKdnMplQV1dnFgivXLmCJ0+sT5t18/T0RGxsrFkoDA4OdsjieL1eD19fXxgMBgBARkbGUz+X9fTp05g3bx4AICwsDGq1mr0Ye9DpdBbhrvvT0GC7BctQjBo1Cps3b8b7779v8XfiyNN/iMh1MQDSc6mjowNqtdps6riqqgpGo7Hf56RSqcUpJl5eXv0+MxDFxcUWa64UCgUKCwshlUqHPL4tnZ2diI6OxvXr1wEABQUFWLRokcN/7khiMpnQ2NjYZyWvubl50GMGBARAEATxEx4eDkEQkJOTA5VKNaAxBEHAgQMHoFAo+rznaZ3+Q0SugwGQXEZrayvKy8vNKoXff/99v89IJBJERkaKO5jj4uIwffp0i2a/tnzyySd4++23La5LpVIcPXp02Bfk994EdOjQIaSmpgIAYmNjUVJS4pTrRG0xmUzQarV9VvIeP3486DGlUqlZyOsZ9ry9va0+s3PnTmzYsMHm2GvWrEFmZqbN9anP8vQfIno+cRMIuQxPT08kJiYiMTFRvKbValFWViZWCktLS8X+eEBXoFCr1VCr1cjLywPQ1dImOjpaDIRxcXGQyWT9Th2XlpZava7VapGUlITs7GxkZGTY/bt1twEqvnQJVTdvim2ApkVFQTF7NhobG8V7d+zY4dThr7OzE3V1dWKo613N0+v1gxpPIpEgJCTEasgLCwuza/OQrZAllUqRm5uLlJSUAY/3rE7/IaLnEyuARD0YjUZUV1ebTR1XVlaio6Oj3+f8/f3FaePuU0z8/PzE78PDw1FbW9vvGOnp6cjOzh7UusBbt25hdXo6LhQVITgwAK/FzsAMeTi8PD3wqPUJKms0OHulqxF4YEAAVmdkYOvWrQMe/1np6OjA3bt3rVbxamtr0d7ePqjxRo8ejalTp5pN03Z/ZDLZsDcXV6vVfTbXXrx4MXbv3m3272Og8vPzsWrVKkj9fAd1+o9KpRrW03+IyPkxABLZoNfrce3aNbP+hBqNxuZzcrkccXFxiIqKwpYtWwb0s+Lj41FYWIjg4GCb9/YMA5nrVuKNObP6DAP//OYyfrdLNaLCgMFgwO3bt83CXXc1786dOzZDd29jxoyBTCaDXC63qOSFhoYOetp+KNra2uDh4WHWCsbX1xd79uwRWxzZq3fot3X6z6dP4fQfInI+DIBEdnj48KHZ1HFJSYldmwismTRpEo4ePYo5c+b0eU9+fj5SU1ORmqK0azrw4MGDWLp06bC8b39698jr+bl3796ge+WNHTu2z/V4ISEhT7Wtjy0RERGorq4GAKSkpGDfvn3D2nS75+k/N6qqzE7/maVQPPPTf4hoZGMAJBoGJpMJGo3GrEp49epVse3LYLm5uSErKwtr1qwR1xZevHgRmZmZKC0tRUNDA16d+QrO7douruczmUz4g+ogcj4/Bd2jFsRHRWDXxrcQFTYVAHBHW4+t+/Jx+NxFtOrbEBISgrS0NLz77rtDagfz6NEjq7tqNRqNXT3yxo8fbzXkCYIAqVTqNOsXz5w5g6ysLCxYsAArV650+Nm7znD6DxGNHAyARA7S3t6O69evY/ny5fjuu+/sGmP+/Pk4cuQIxo0bh1OnTuHbb7/F58ePo+rmTeT/cTMW/yJJvPeDzw7jL3kFyH1vA14KeRF/zvs7Ll67gf8U/A0TPD1wuvgKDp/7CgsSZ+O3H/8VPgGBeNDQgGXLluHDDz/s9z2am5uthjx7e+T5+PhYnaoVBAEBAQEOD0tERK6OAZDIgUwmE/z9/Yc0PSwIAmpqagAA5eXliI2NBQAc2/57LHh1tvhzgt9YivWLFuKdZb8CABja2xE0fwm2r12BjIXzzcbsbgq8fv16nDhxAhqNRuyRZ+2j0+kG/d6BgYFWN10IgmDXBggiIho+bAND5EAajWbIawN7TqPm5eXhxUmBqHtgXnW7fb8e9U06vB73/zVf7i+8gFdnTkfxDbVFAHxzjgLBgQE4efIkHjx4AG9vb7t65E2ePLnPNXnD0UCbiIgcgwGQyIFKSkrsftbLywuhoaHYtm2beK340iXMjXkF+784a3ZvfVNXhW6Sn6/Z9UA/X9yrf2AxtpvbaMRFyvGPi5f6fQeJRIIpU6ZYreTZ2yOPiIiePQZAIgfqqwG0NT4+PkhKSsLcuXOhVCrx8ssvW6yFq7p5E79O+A2As1bH6L10zmQyQQLL9XT3G5vwdWUVJBIJvL29MXHiRKuVPJlM9lTPKyYioqeDAZDIgcrKyvr8bty4cUhISBAD38yZM/ttY2I0GmEwGODl6WHxXdDErspffZMOUv+J4vVG3X8tqoL3G5ugXLcJ8pBgPKxSo6mpibtHiYhcDAMgkQNNmDBB/POYMWMwa9YsKJVKKJVKxMfHD6q6NmrUKLi7u+NR6xOL72STgxA00Rdnyq5iZkRX09/2n37CV1dvYPvaFeJ9PzQ8hHLdO4iJFBATIUdFTS3DHxGRC2IAJHKg/fv349ixYwgLC0NCQsKQ1sy1tLQgTCbDhfJrALo2flyr1sDPawKmBAVi/aKF2La/APIXJ0MeEoxt+wvgMdYdS19PBtBV+Ut+axOmTApE5rp0bMj6FJEREaivr0dQUNCw/L5EROQc2AaGyEkUFRUhOTnZ4vryX76G3Pc2io2g9x7/ArrHLYj/WSR2bXwL08KnAgDy/vVvrPjTx1bH5n8DRESuhQGQyIlUVFQgJiYGhdvew8Kkn9s9TncfwPLych4XRkTkghgAiZyMMjkZd2uqUfnZngGdAdxbq74NM5atRaj8JZy/cMEBb0hERCMdV38TOZm9OTnQNuuwdkc2jEbjoJ41Go1YuyMb2mYd9ubkOOgNiYhopGMAJHIygiBApVLh4Jfnkbb1I7Tq2wb0XKu+DWlbP8LBL89DpVJBEAQHvykREY1UnAImclL5+flYtWoVpH6+2LFuBd6co4Cbm2UfwY6OTpz4phibdu2DtlkHlUqFJUuWPIM3JiKikYIBkMiJ3bp1C6vT03GhqAjBgQGYGzMDM+Rh8B7viR9bWlFZU4tz5ZX4oaERyuRkfLp3Lyt/RETEAEj0PKioqEBubi4uFxfjRlUVDAYD3N3dMX3aNMxSKJCWlsbdvkREJGIAJHoOGY1GnvBBRER9YgAkIiIicjEsERARERG5GAZAIiIiIhfDAEhERETkYhgAiYiIiFwMAyARERGRi2EAJCIiInIxDIBERERELoYBkIiIiMjF/A/sIP0tq8dNAgAAAABJRU5ErkJggg==\n", "text/plain": [ "Graphics object consisting of 86 graphics primitives" ] }, "execution_count": 114, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Gr = Rook0(3).cayley_graph(side=\"right\")\n", "Gr.remove_loops() \n", "Gr.plot()" ] }, { "cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": [ "# %load -s rook_lattice rook0.sage\n", "def rook_lattice(n):\n", " r\"\"\"\n", " The right rook lattice\n", "\n", " We take the monoid convention, where 1 is the largest element\n", "\n", " Examples::\n", "\n", " sage: rook_lattice(3).cardinality()\n", " 34\n", " sage: rook_lattice(3).is_lattice()\n", " True\n", " sage: rl2 = rook_lattice(2)\n", " sage: matrix([[1 if rl2.le(r1, r2) else 0\n", " ....: for r1 in rooks(2)] for r2 in rooks(2)])\n", " [1 1 1 1 1 1 1]\n", " [0 1 1 1 0 0 1]\n", " [0 0 1 1 0 0 1]\n", " [0 0 0 1 0 0 1]\n", " [0 0 0 0 1 1 1]\n", " [0 0 0 0 0 1 1]\n", " [0 0 0 0 0 0 1]\n", "\n", " TESTS::\n", "\n", " sage: TestSuite(rook_lattice(3)).run()\n", " \"\"\"\n", " one = tuple(range(1, n+1))\n", " Gr = Rook0(n).cayley_graph(side=\"right\")\n", " Gr.remove_loops()\n", " Gr.relabel(lambda f : f.lift()(one))\n", " Gr = Gr.reverse()\n", " return LatticePoset(Gr)" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "Graphics object consisting of 86 graphics primitives" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rook_lattice(3).plot()" ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[True, True, True, True, True, True]" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[rook_lattice(n).is_lattice() for n in range(6)]" ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [], "source": [ "rl = rook_lattice(3)" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[1 0 1 1 0 0 1]\n", "[1 1 1 1 1 1 1]\n", "[0 0 1 1 0 0 1]\n", "[0 0 0 1 0 0 1]\n", "[0 0 0 0 1 0 1]\n", "[0 0 0 0 1 1 1]\n", "[0 0 0 0 0 0 1]" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rl2 = rook_lattice(2)\n", "matrix([[1 if rl2.le(r1, r2) else 0\n", " for r1 in rooks(2)] for r2 in rooks(2)])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## rook triples" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [], "source": [ "# %load -s support,Delta,inversion,Z,rook_triple rook0.sage\n", "def support(r):\n", " r\"\"\"\n", " The support of a rook (Definition 4.6, page 33)\n", "\n", " Examples::\n", "\n", " sage: support([3,1,0,2])\n", " frozenset({1, 2, 3})\n", " sage: support((4,1,0,2))\n", " frozenset({1, 2, 4})\n", " \"\"\"\n", " return frozenset(r) - frozenset({0})\n", "\n", "@cached_function\n", "def Delta(n):\n", " r\"\"\"\n", " The upper diagonal set\n", "\n", " \\Delta:=\\{(b, a)\\ \\mid\\ n\\geq b>a>0\\}\n", "\n", " EXAMPLES::\n", "\n", " sage: Delta(3)\n", " frozenset({(2, 1), (3, 1), (3, 2)})\n", " sage: Delta(4)\n", " frozenset({(2, 1), (3, 1), (3, 2), (4, 1), (4, 2), (4, 3)})\n", " sage: Delta(frozenset({1, 3, 4}))\n", " frozenset({(3, 1), (4, 1), (4, 3)})\n", "\n", " sage: Delta(frozenset({1, 2, 3, 8}))\n", " frozenset({(2, 1), (3, 1), (3, 2), (8, 1), (8, 2), (8, 3)})\n", " \"\"\"\n", " if isinstance(n, (int, Integer)):\n", " return frozenset((b,a) for b in range(1, n+1) for a in range(1, b))\n", " else:\n", " S = sorted(list(n))\n", " n = len(S)\n", " S = [None] + S # Delta uses 1 based indexes\n", " return frozenset((S[i],S[j]) for (i,j) in Delta(n))\n", "\n", "def inversion(r):\n", " r\"\"\"\n", " The inversion set of a rook (Definition 4.1, page 33)\n", "\n", " EXAMPLES::\n", "\n", " sage: inversion((3,1,0,2))\n", " frozenset({(3, 1), (3, 2)})\n", " sage: inversion((3,1,5,0,2))\n", " frozenset({(3, 1), (3, 2), (5, 2)})\n", " sage: inversion((3,1,5,0,2,4))\n", " frozenset({(3, 1), (3, 2), (5, 2), (5, 4)})\n", " \"\"\"\n", " r = [x for x in r if x != 0]\n", " res = [(r[j], r[i]) for i in range(len(r)) for j in range(i) if r[j] > r[i]]\n", " return frozenset(res)\n", "\n", "def Z(r):\n", " r\"\"\"\n", " The zero-after number of a rook (Definition 4.6, page 33)\n", "\n", " EXAMPLES::\n", "\n", " sage: Z((3,1,5,0,2))\n", " {1: 1, 2: 0, 3: 1, 5: 1}\n", " sage: Z((3,0,5,0,2))\n", " {2: 0, 3: 2, 5: 1}\n", " \"\"\"\n", " S = support(r)\n", " r = list(r)\n", " res = dict()\n", " for a in S:\n", " i = r.index(a)\n", " res[a] = r[i:].count(0)\n", " return res\n", "\n", "def rook_triple(r):\n", " r\"\"\"\n", " The rook triple associate to a rook (Definition 4.6, page 33)\n", "\n", " EXAMPLES::\n", "\n", " sage: rook_triple((2,0,5,4,0,0,1))\n", " (frozenset({1, 2, 4, 5}),\n", " frozenset({(2, 1), (4, 1), (5, 1), (5, 4)}),\n", " {1: 0, 2: 3, 4: 2, 5: 2})\n", " \"\"\"\n", " return (support(r), inversion(r), Z(r))" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(frozenset({1, 2, 4, 5}),\n", " frozenset({(2, 1), (4, 1), (5, 1), (5, 4)}),\n", " {1: 0, 2: 3, 4: 2, 5: 2})" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rook_triple((2,0,5,4,0,0,1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## recovering a rook from its triple" ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [], "source": [ "# %load -s from_inversion,from_rook_triple rook0.sage\n", "@cached_function\n", "def from_inversion(S, inv):\n", " r\"\"\"\n", " A word from its support and inversion set\n", "\n", " EXAMPLES::\n", "\n", " sage: from_inversion( frozenset({1, 2, 4, 5}),\n", " ....: frozenset({(2, 1), (4, 1), (5, 1), (5, 4)}))\n", " [2, 5, 4, 1]\n", "\n", " sage: from_inversion(frozenset([1, 2, 3]), frozenset([(3, 1)]))\n", " Traceback (most recent call last):\n", " ...\n", " TypeError: Digraph is not acyclic; there is no topological sort.\n", "\n", " sage: from_inversion(frozenset({1, 2, 3, 8}),\n", " ....: frozenset({(2, 1), (3, 1), (3, 2)}))\n", " [3, 2, 1, 8]\n", " \"\"\"\n", " from sage.graphs.linearextensions import LinearExtensions\n", " d = DiGraph()\n", " d.add_vertices(S)\n", " for (b,a) in Delta(S):\n", " assert a in S\n", " assert b in S\n", " if (b,a) in inv:\n", " d.add_edge((b,a))\n", " else:\n", " d.add_edge((a,b))\n", " return d.topological_sort()\n", "\n", "def from_rook_triple((Sr, Ir, Zr), n):\n", " r\"\"\"\n", " Recovering a rook from its rook triple (Proposition 4.8, page 33)\n", "\n", " EXAMPLE::\n", "\n", " sage: from_rook_triple(\n", " ....: (frozenset({1, 2, 4, 5}),\n", " ....: frozenset({(2, 1), (4, 1), (5, 1), (5, 4)}),\n", " ....: {1: 0, 2: 3, 4: 2, 5: 2}), 7)\n", " (2, 0, 5, 4, 0, 0, 1)\n", "\n", " TESTS::\n", "\n", " sage: n = 5\n", " sage: for r in rooks(n):\n", " ....: assert r == from_rook_triple(rook_triple(r), n)\n", " \"\"\"\n", " res = []\n", " oldZ = n-len(Sr)\n", " for l in from_inversion(Sr, Ir):\n", " assert Zr[l] <= oldZ\n", " res.extend([0]*(oldZ-Zr[l]))\n", " res.append(l)\n", " oldZ = Zr[l]\n", " res.extend([0]*oldZ)\n", " return tuple(res)\n" ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 0, 5, 4, 0, 0, 1)" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from_rook_triple(\n", " (frozenset({1, 2, 4, 5}),\n", " frozenset({(2, 1), (4, 1), (5, 1), (5, 4)}),\n", " {1: 0, 2: 3, 4: 2, 5: 2}), 7)" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [], "source": [ "for n in range(7):\n", " for r in rooks(n):\n", " assert r == from_rook_triple(rook_triple(r), n)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Comparing two rooks" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [], "source": [ "# %load -s leqI rook0.sage\n", "def leqI(r, u):\n", " r\"\"\"\n", " Comparing rooks (Definition \\reff{def-rook-order})\n", "\n", " We check for Theorem 4.16, page 35::\n", "\n", " sage: n = 4\n", " sage: Mon = Rook0(n)\n", " sage: rl = rook_lattice(n)\n", " sage: for r1 in rooks(n):\n", " ....: for r2 in rooks(n):\n", " ....: assert leqI(r1, r2) == rl.le(r1, r2)\n", " \"\"\"\n", " (Su, Iu, Zu) = rook_triple(u)\n", " (Sr, Ir, Zr) = rook_triple(r)\n", " if not Sr.issubset(Su):\n", " return False\n", " for (b, a) in Iu:\n", " if b in Sr and (b, a) not in Ir:\n", " return False\n", " for l in Sr:\n", " if not Zu[l] <= Zr[l]:\n", " return False\n", " return True" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [], "source": [ "for n in range(5):\n", " Mon = Rook0(n)\n", " rl = rook_lattice(n)\n", " for r1 in rooks(n):\n", " for r2 in rooks(n):\n", " assert leqI(r1, r2) == rl.le(r1, r2)" ] }, { "cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [], "source": [ "# %load -s invdict,transitive_closure,max_compatible_set,min_dual_compatible_set,interS2 rook0.sage\n", "def invdict(I):\n", " r\"\"\"\n", " Iversion as a dict\n", "\n", " EXAMPLES::\n", "\n", " sage: invdict(frozenset({(6,5), (4,3), (5,3), (6,3)}))\n", " {4: {3}, 5: {3}, 6: {3, 5}}\n", " \"\"\"\n", " import collections\n", " res = collections.defaultdict(set)\n", " for (b, a) in I:\n", " res[b].add(a)\n", " return dict(res)\n", "\n", "def transitive_closure(I):\n", " \"\"\"\n", " Trasitive Closure:\n", "\n", " EXAMPLES::\n", "\n", " sage: transitive_closure(frozenset([(3,2), (2,1)]))\n", " frozenset({(2, 1), (3, 1), (3, 2)})\n", " sage: transitive_closure(frozenset([(4,3),(3,2), (2,1)]))\n", " frozenset({(2, 1), (3, 1), (3, 2), (4, 1), (4, 2), (4, 3)})\n", " \"\"\"\n", " return frozenset([(a,b) for (a,b,_) in\n", " DiGraph(list(I)).transitive_closure().edges()])\n", "\n", "def max_compatible_set(S, I):\n", " \"\"\"\n", " Maximal I-compatible set (Definition 4.12, page 34)\n", "\n", " precondition: S is supposed transitively closed\n", "\n", " EXAMPLES::\n", "\n", " sage: max_compatible_set(frozenset({1,2,4,5}), frozenset({(4,3), (5,3)}))\n", " frozenset({1, 2})\n", " sage: max_compatible_set(frozenset({1,2,4,5,6}),\n", " ....: frozenset({(6,5), (4,3), (5,3), (6,3)}))\n", " frozenset({1, 2})\n", " \"\"\"\n", " I = invdict(I)\n", " res = set()\n", " for b in S:\n", " if b not in I or I[b].issubset(S):\n", " res.add(b)\n", " return frozenset(res)\n", "\n", "def min_dual_compatible_set(S, I, n):\n", " \"\"\"\n", " Minimal I-compatible set (Definition 4.21, page 38)\n", "\n", " precondition: S is supposed transitively closed\n", "\n", " EXAMPLES::\n", "\n", " sage: min_dual_compatible_set(frozenset({1,2,4,5}),\n", " ....: frozenset({(4,3), (5,3)}), 5)\n", " frozenset({1, 2, 3, 4, 5})\n", " sage: min_dual_compatible_set(frozenset({5}),\n", " ....: frozenset({(6,5), (4,3), (5,3), (6,3)}), 7)\n", " frozenset({5, 7})\n", " sage: min_dual_compatible_set(frozenset({3}),\n", " ....: frozenset({(6,5), (4,3), (5,3), (6,3)}), 7)\n", " frozenset({3, 7})\n", " sage: min_dual_compatible_set(frozenset({2}),\n", " ....: frozenset({(6,5), (4,3), (5,3), (6,3)}), 7)\n", " frozenset({2, 3, 4, 5, 6, 7})\n", " \"\"\"\n", " res = set(S)\n", " for a in S:\n", " for b in range(a+1, n+1):\n", " if (b, a) not in I:\n", " res.add(b)\n", " return frozenset(res)\n", "\n", "def interS2(I0, S):\n", " r\"\"\"\n", " Intersection of an inversion set and a support\n", "\n", " EXAMPLES::\n", "\n", " sage: interS2(frozenset([(2,1), (4,2), (3,2)]),\n", " ....: frozenset([3,2]))\n", " frozenset({(3, 2)})\n", " sage: interS2(frozenset([(2,1), (4,2), (3,2)]),\n", " ....: frozenset([3,2,1]))\n", " frozenset({(2, 1), (3, 2)})\n", " \"\"\"\n", " I = set()\n", " for (b, a) in I0:\n", " if b in S and a in S:\n", " I.add((b,a))\n", " return frozenset(I)\n" ] }, { "cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [], "source": [ "# %load -s inf rook0.sage\n", "def inf(u, v):\n", " \"\"\"\n", " The inf of the rook lattice (Theorem 4.18, page 36)\n", "\n", " EXAMPLES::\n", "\n", " sage: inf((3,1,0,5,2), (2,1,5,3,4))\n", " (0, 3, 2, 1, 0)\n", "\n", " sage: inf((2,4,1,0), (2,1,3,4))\n", " (2, 4, 1, 0)\n", " sage: inf((2,4,1,0), (2,1,4,3))\n", " (0, 2, 1, 0)\n", " sage: inf((2,4,1,0), (3,1,4,2))\n", " (4, 2, 1, 0)\n", "\n", " TESTS::\n", "\n", " sage: n = 4\n", " sage: Mon = Rook0(n)\n", " sage: rl = rook_lattice(n)\n", " sage: for u in rooks(n):\n", " ....: for v in rooks(n):\n", " ....: assert inf(u, v) == rl.meet(u, v)\n", " \"\"\"\n", " n = len(u)\n", " assert n == len(v)\n", " (Su, Iu, Zu) = rook_triple(u)\n", " (Sv, Iv, Zv) = rook_triple(v)\n", " I0 = transitive_closure(Iu | Iv)\n", " S = max_compatible_set(Su & Sv, I0)\n", " I = interS2(I0, S)\n", " Idict = invdict(I)\n", " Z = dict()\n", " for x in S:\n", " Zx = max(Zu[x], Zv[x])\n", " for i in Idict.get(x, []):\n", " Zx = max(Zx, Zu.get(i, 0), Zv.get(i, 0))\n", " Z[x] = Zx\n", " return from_rook_triple((S, I, Z), n)" ] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 3, 2, 1, 0)" ] }, "execution_count": 144, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inf((3,1,0,5,2), (2,1,5,3,4))" ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 4, 1, 0)" ] }, "execution_count": 145, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inf((2,4,1,0), (2,1,3,4))" ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 2, 1, 0)" ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inf((2,4,1,0), (2,1,4,3))" ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(4, 2, 1, 0)" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inf((2,4,1,0), (3,1,4,2))" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [], "source": [ "n = 4\n", "Mon = Rook0(n)\n", "rl = rook_lattice(n)\n", "for u in rooks(n):\n", " for v in rooks(n):\n", " assert inf(u, v) == rl.meet(u, v)" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [], "source": [ "# %load -s inversion_set_bar,sup rook0.sage\n", "def inversion_set_bar(Su, Iu):\n", " r\"\"\"\n", " Complement of an inversion set\n", "\n", " EXAMPLES::\n", "\n", " sage: inversion_set_bar(frozenset({4}),\n", " ....: frozenset({(6,5), (4,3), (5,3), (6,3)}))\n", " {(4, 1), (4, 2), (4, 3)}\n", " \"\"\"\n", " IBu = set(Delta(Su) - Iu)\n", " for b in Su:\n", " for a in range(1, b):\n", " if a not in Su:\n", " IBu.add((b, a))\n", " return IBu\n", "\n", "def sup(u, v):\n", " r\"\"\"\n", " The sup of the rook lattice (Theorem 4.22, page 38)\n", "\n", " EXAMPLES::\n", "\n", " sage: sup((3,1,0,5,2), (2,1,5,3,4))\n", " (1, 2, 3, 4, 5)\n", "\n", " sage: sup((2,4,1,0), (2,1,3,4))\n", " (2, 1, 3, 4)\n", " sage: sup((2,4,1,0), (2,1,4,3))\n", " (2, 1, 3, 4)\n", " sage: sup((2,4,1,0), (3,1,4,2))\n", " (3, 1, 2, 4)\n", "\n", " TESTS::\n", "\n", " sage: n = 4\n", " sage: Mon = Rook0(n)\n", " sage: rl = rook_lattice(n)\n", " sage: for u in rooks(n):\n", " ....: for v in rooks(n):\n", " ....: assert sup(u, v) == rl.join(u, v)\n", " \"\"\"\n", " n = len(u)\n", " assert n == len(v)\n", " (Su, Iu, Zu) = rook_triple(u)\n", " IBu = inversion_set_bar(Su, Iu)\n", " (Sv, Iv, Zv) = rook_triple(v)\n", " IBv = inversion_set_bar(Sv, Iv)\n", " I0 = Delta(n) - transitive_closure(IBu | IBv)\n", " S = min_dual_compatible_set(Su | Sv, I0, n)\n", " I = interS2(I0, S)\n", " Idict = invdict(I)\n", " Z = dict()\n", " for x in S:\n", " Zx = min(n - len(S), Zu.get(x, n), Zv.get(x, n))\n", " for i in frozenset(range(x)) - Idict.get(x, set()):\n", " Zx = min(Zx, Zu.get(i, n))\n", " Zx = min(Zx, Zv.get(i, n))\n", " Z[x] = Zx\n", " return from_rook_triple((S, I, Z), n)" ] }, { "cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1, 2, 3, 4, 5)" ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sup((3,1,0,5,2), (2,1,5,3,4))" ] }, { "cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 1, 3, 4)" ] }, "execution_count": 152, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sup((2,4,1,0), (2,1,3,4))" ] }, { "cell_type": "code", "execution_count": 153, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 1, 3, 4)" ] }, "execution_count": 153, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sup((2,4,1,0), (2,1,4,3))" ] }, { "cell_type": "code", "execution_count": 154, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3, 1, 2, 4)" ] }, "execution_count": 154, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sup((2,4,1,0), (3,1,4,2))" ] }, { "cell_type": "code", "execution_count": 155, "metadata": {}, "outputs": [], "source": [ "n = 4\n", "Mon = Rook0(n)\n", "rl = rook_lattice(n)\n", "for u in rooks(n):\n", " for v in rooks(n):\n", " assert sup(u, v) == rl.join(u, v)" ] }, { "cell_type": "code", "execution_count": null, 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