{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "anonymous-address", "metadata": {}, "source": [ "# Triplet STDP synapse tutorial" ] }, { "attachments": {}, "cell_type": "markdown", "id": "cordless-convenience", "metadata": {}, "source": [ "In this tutorial, we will learn to formulate triplet rule (which considers sets of three spikes, i.e., two presynaptic and one postsynaptic spikes or two postsynaptic and one presynaptic spikes) for Spike Timing-Dependent Plasticity (STDP) learning model using NESTML and simulate it with NEST simulator." ] }, { "cell_type": "code", "execution_count": 1, "id": "orange-zambia", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.7.0\n", " Built: Mar 12 2025 18:15:33\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", "\n", " Problems or suggestions?\n", " Visit https://www.nest-simulator.org\n", "\n", " Type 'nest.help()' to find out more about NEST.\n", "\n" ] } ], "source": [ "%matplotlib inline\n", "import matplotlib as mpl\n", "\n", "mpl.rcParams['axes.grid'] = True\n", "\n", "import matplotlib.pyplot as plt\n", "import nest\n", "import numpy as np\n", "\n", "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", "from pynestml.codegeneration.nest_tools import NESTTools\n", "\n", "np.set_printoptions(suppress=True)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "understanding-commissioner", "metadata": {}, "source": [ "Early experiments in Bi and Poo (1998) [1] have shown that a sequence of $n$ pairs of \"pre then post\" spikes result in synaptic potentiation and $n$ pairs of \"post then pre\" result in synaptic depression. Later experiments have shown that these pairs of spikes do not necessarily describe the synaptic plasiticity behavior. Other variables like calcium concentration or postsynaptic membrane potential play an important role in potentiation or depression.\n", "\n", "Experiments conducted by Wang et al., [2] and Sjöström et al., [3] using triplet and quadruplets of spikes show that the classical spike-dependent synaptic plasticity alone cannot explain the results of the experiments. The triplet STDP model formulated by Pfister and Gerstner in [4] assume that a combination of pairs and triplets of spikes triggers the synaptic plasticity and thus reproduce the experimental results." ] }, { "attachments": {}, "cell_type": "markdown", "id": "integrated-swimming", "metadata": {}, "source": [ "## Triplet STDP model" ] }, { "attachments": { "image.png": { "image/png": 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} }, "cell_type": "markdown", "id": "inside-south", "metadata": {}, "source": [ "The synaptic transmission is formulated by a set of four differential equations as defined below.\n", "\n", "\\begin{equation}\n", "\\frac{dr_1}{dt} = -\\frac{r_1(t)}{\\tau_+} \\quad\n", "\\text{if } t = t^{pre}, \\text{ then } r_1 \\rightarrow r_1+1\n", "\\end{equation}\n", "\n", "\\begin{equation}\n", "\\frac{dr_2}{dt} = -\\frac{r_2(t)}{\\tau_x} \\quad\n", "\\text{if } t = t^{pre}, \\text{ then } r_2 \\rightarrow r_2+1\n", "\\end{equation}\n", "\n", "\\begin{equation}\n", "\\frac{do_1}{dt} = -\\frac{o_1(t)}{\\tau_-} \\quad\n", "\\text{if } t = t^{post}, \\text{ then } o_1 \\rightarrow o_1+1\n", "\\end{equation}\n", "\n", "\\begin{equation}\n", "\\frac{do_2}{dt} = -\\frac{o_2(t)}{\\tau_y} \\quad\n", "\\text{if } t = t^{post}, \\text{ then } o_2 \\rightarrow o_2+1\n", "\\end{equation}\n", "\n", "Here, $r_1$ and $r_2$ are the trace variables that detect the presynaptic events when a spike occurs at the presynaptic neuron at time $t^{pre}$. These variables increase when a presynaptic spike occurs and decrease back to 0 otherwise with time constants $\\tau_+$ and $\\tau_x$ respectively. Similarly, the variables $o_1$ and $o_2$ denote the trace variables that detect the postsynaptic events at a spike time $t^{post}$. In the absence of a postsynaptic spike, the vairables decrease their value with a time constant $\\tau_-$ and $\\tau_y$ respectively. Presynaptic variables, for example, can be the amount of glutamate bound and the postsynaptic receptors can determine the influx of calcium concentration through voltage-gated $Ca^{2+}$ channels.\n", "\n", "The weight change in the model is formulated as a function of the four trace variables defined above. The weight of the synapse decreases after the presynaptic spikes arrives at $t^{pre}$ by an amount proportional to the postsynaptic variable $o_1$ but also depends on the second presynaptic variable $r_2$.\n", "\n", "\\begin{equation}\n", "w(t) \\rightarrow w(t) - o_1(t)[A_2^- + A_3^- r_2(t - \\epsilon)] \\quad \\text{if } t = t^{pre}\n", "\\end{equation}\n", "\n", "Similarly, a postsynaptic spike at time $t^{post}$ increases the weight of the synapse and is dependent on the presynaptic variable $r_1$ and the postsynaptic variable $o_2$.\n", "\n", "\\begin{equation}\n", "w(t) \\rightarrow w(t) + r_1(t)[A_2^+ + A_3^+ o_2(t - \\epsilon)] \\quad \\text{if } t = t^{post}\n", "\\end{equation}\n", "\n", "Here, $A_2^+$ and $A_2^-$ denote the amplitude of the weight change whenever there is a pre-post pair or a post-pre pair. Similarly, $A_3^+$ and $A_3^-$ denote the amplitude of the triplet term for potentiation and depression, respectively.\n", "\n", "![image.png](attachment:image.png)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "collective-stuff", "metadata": {}, "source": [ "## Generating code with NESTML\n", "\n", "### Triplet STDP model in NESTML" ] }, { "attachments": {}, "cell_type": "markdown", "id": "basic-given", "metadata": {}, "source": [ "In this tutorial, we will use a very simple integrate-and-fire model, where arriving spikes cause an instantaneous increment of the membrane potential, the \"iaf_psc_delta\" model. It is already provided with NESTML in the `models/neurons` directory." ] }, { "attachments": {}, "cell_type": "markdown", "id": "ruled-myrtle", "metadata": {}, "source": [ "We will be formulating two types of interactions between the spikes, namely All-to-All interaction and Nearest-spike interaction.\n", "\n", "$\\textit{All-to-All Interaction}$ - Each postsynaptic spike interacts with all previous postsynaptic spikes and vice versa. All the internal variables $r_1, r_2, o_1,$ and $o_2$ accumulate over several postsynaptic spike timimgs.\n", "\n", "
\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 2, "id": "thorough-halifax", "metadata": {}, "outputs": [], "source": [ "nestml_triplet_stdp_model = \"\"\"\n", "model stdp_triplet_synapse:\n", "\n", " state:\n", " w nS = 1 nS\n", "\n", " tr_r1 real = 0.\n", " tr_r2 real = 0.\n", " tr_o1 real = 0.\n", " tr_o2 real = 0.\n", "\n", " parameters:\n", " tau_plus ms = 16.8 ms # time constant for tr_r1\n", " tau_x ms = 101 ms # time constant for tr_r2\n", " tau_minus ms = 33.7 ms # time constant for tr_o1\n", " tau_y ms = 125 ms # time constant for tr_o2\n", "\n", " A2_plus real = 7.5e-10\n", " A3_plus real = 9.3e-3\n", " A2_minus real = 7e-3\n", " A3_minus real = 2.3e-4\n", "\n", " Wmax nS = 100 nS\n", " Wmin nS = 0 nS\n", "\n", " equations:\n", " tr_r1' = -tr_r1 / tau_plus\n", " tr_r2' = -tr_r2 / tau_x\n", " tr_o1' = -tr_o1 / tau_minus\n", " tr_o2' = -tr_o2 / tau_y\n", "\n", " input:\n", " pre_spikes <- spike\n", " post_spikes <- spike\n", "\n", " output:\n", " spike\n", "\n", " onReceive(post_spikes):\n", " # increment post trace values\n", " tr_o1 += 1\n", " tr_o2 += 1\n", "\n", " # potentiate synapse\n", " w_ nS = w + tr_r1 * ( A2_plus + A3_plus * tr_o2 )\n", " w = min(Wmax, w_)\n", "\n", " onReceive(pre_spikes):\n", " # increment pre trace values\n", " tr_r1 += 1\n", " tr_r2 += 1\n", "\n", " # depress synapse\n", " w_ nS = w - tr_o1 * ( A2_minus + A3_minus * tr_r2 )\n", " w = max(Wmin, w_)\n", "\n", " # deliver spike to postsynaptic partner\n", " emit_spike(w)\n", " \n", " update:\n", " integrate_odes()\n", "\"\"\"" ] }, { "attachments": {}, "cell_type": "markdown", "id": "385b96ca", "metadata": {}, "source": [ "When NESTML is invoked, the C++ code is generated for the models, and then built (compiled) as a NEST extension module, which is then loaded into the NEST kernel at runtime using ``nest.Install()``.\n", "\n", "The resulting neuron and synapse model names are returned by the function, because when generating code for plastic synapses, there is typically a tight integration of the generated with code with that of the postsynaptic neuron model. For more information about this, please see the NESTML documentation section [Generating code for plastic synapses](https://nestml.readthedocs.io/en/latest/running/running_nest.html#generating-code-for-plastic-synapses). Hence, the resulting model names are composed of associated neuron and synapse partners, because of the co-generation, for example, ``\"stdp_triplet_synapse__with_iaf_psc_delta\"`` and ``\"iaf_psc_delta__with_stdp_triplet_synapse\"``." ] }, { "cell_type": "code", "execution_count": 3, "id": "colonial-serve", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.7.0\n", " Built: Mar 12 2025 18:15:33\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", "\n", " Problems or suggestions?\n", " Visit https://www.nest-simulator.org\n", "\n", " Type 'nest.help()' to find out more about NEST.\n", "\n", "[13,stdp_triplet_synapse_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[16,stdp_triplet_synapse_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[19,stdp_triplet_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[20,stdp_triplet_synapse_nestml, WARNING, [38:4;39:4]]: Implicit casting from (compatible) type 'real' to 'nS'.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"refr_t\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"refr_t\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o1__for_stdp_triplet_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o2__for_stdp_triplet_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_r1\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_r2\" as it is solved by propagator solver\n" ] } ], "source": [ "# Generate code for All-to-All spike interaction\n", "module_name, neuron_model_name, synapse_model_name = \\\n", " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", " nestml_triplet_stdp_model,\n", " post_ports=[\"post_spikes\"],\n", " logging_level=\"WARNING\",\n", " codegen_opts={\"weight_variable\": {\"stdp_triplet_synapse\": \"w\"}})" ] }, { "attachments": {}, "cell_type": "markdown", "id": "settled-keeping", "metadata": {}, "source": [ "$\\textit{Nearest spike Interation}$ - Each postsynaptic spike interacts with only the last spike. Hence no accumulation of the trace variables occurs. The variables saturate at 1. This is achieved by updating the variables to the value of 1 instead of updating by at step of 1. In this way, the synapse forgets all other previous spikes and keeps only the memory of the last one.\n", "\n", "
\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 4, "id": "addressed-roads", "metadata": {}, "outputs": [], "source": [ "nestml_triplet_stdp_nn_model = \"\"\"\n", "model stdp_triplet_nn_synapse:\n", "\n", " state:\n", " w nS = 1 nS\n", "\n", " tr_r1 real = 0.\n", " tr_r2 real = 0.\n", " tr_o1 real = 0.\n", " tr_o2 real = 0.\n", "\n", " parameters:\n", " tau_plus ms = 16.8 ms # time constant for tr_r1\n", " tau_x ms = 101 ms # time constant for tr_r2\n", " tau_minus ms = 33.7 ms # time constant for tr_o1\n", " tau_y ms = 125 ms # time constant for tr_o2\n", "\n", " A2_plus real = 7.5e-10\n", " A3_plus real = 9.3e-3\n", " A2_minus real = 7e-3\n", " A3_minus real = 2.3e-4\n", "\n", " Wmax nS = 100 nS\n", " Wmin nS = 0 nS\n", "\n", " equations:\n", " tr_r1' = -tr_r1 / tau_plus\n", " tr_r2' = -tr_r2 / tau_x\n", " tr_o1' = -tr_o1 / tau_minus\n", " tr_o2' = -tr_o2 / tau_y\n", "\n", " input:\n", " pre_spikes <- spike\n", " post_spikes <- spike\n", "\n", " output:\n", " spike\n", "\n", " onReceive(post_spikes):\n", " # increment post trace values\n", " tr_o1 = 1\n", " tr_o2 = 1\n", "\n", " # potentiate synapse\n", " #w_ nS = Wmax * ( w / Wmax + tr_r1 * ( A2_plus + A3_plus * tr_o2 ) )\n", " w_ nS = w + tr_r1 * ( A2_plus + A3_plus * tr_o2 )\n", " w = min(Wmax, w_)\n", "\n", " onReceive(pre_spikes):\n", " # increment pre trace values\n", " tr_r1 = 1\n", " tr_r2 = 1\n", "\n", " # depress synapse\n", " #w_ nS = Wmax * ( w / Wmax - tr_o1 * ( A2_minus + A3_minus * tr_r2 ) )\n", " w_ nS = w - tr_o1 * ( A2_minus + A3_minus * tr_r2 )\n", " w = max(Wmin, w_)\n", "\n", " # deliver spike to postsynaptic partner\n", " emit_spike(w)\n", " \n", " update:\n", " integrate_odes()\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 5, "id": "civic-xerox", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.7.0\n", " Built: Mar 12 2025 18:15:33\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", "\n", " Problems or suggestions?\n", " Visit https://www.nest-simulator.org\n", "\n", " Type 'nest.help()' to find out more about NEST.\n", "\n", "[13,stdp_triplet_nn_synapse_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[16,stdp_triplet_nn_synapse_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[19,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[20,stdp_triplet_nn_synapse_nestml, WARNING, [38:4;39:4]]: Implicit casting from (compatible) type 'real' to 'nS'.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"refr_t\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"refr_t\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o1__for_stdp_triplet_nn_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o2__for_stdp_triplet_nn_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_r1\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_r2\" as it is solved by propagator solver\n" ] } ], "source": [ "# Generate code for nearest spike interaction model\n", "module_name_nn, neuron_model_name_nn, synapse_model_name_nn = \\\n", " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", " nestml_triplet_stdp_nn_model,\n", " post_ports=[\"post_spikes\"],\n", " codegen_opts={\"weight_variable\": {\"stdp_triplet_nn_synapse\": \"w\"}})" ] }, { "attachments": {}, "cell_type": "markdown", "id": "expensive-snapshot", "metadata": {}, "source": [ "## Results \n", "\n", "### Spike pairing protocol\n", "\n", "If we set the values of $A_3^+$ and $A_3^-$ to 0 in the above equations, the model becomes a classical STDP model. The authors in [4] tested this model to check if they could reproduce the experimental results of [2] and [3]. They tested this with a pairing protocol which is a classic STDP protocol where the pairs of presynaptic and postsynaptic spikes shifted by $\\Delta{t}$ are repeated at regular intervals of $(1/\\rho)$. They showed that spike pairs repeated at low frequencies did not cause appreciable potentiation in the synaptic weights, as shown by the experimental data (black trace in the following figure from [4]). This phenomenon cannot be captured by the standard (pair-based) STDP model, because it always potentiates the synapse if a presynaptic spike precedes a postsynaptic spike.\n", "\n", "The failure of the pair-based STDP model to reproduce this is shown in Figure 2A of [4]:\n", "\n", "
\n", "\n", "
\n", "\n", "Notice the solid blue and red curves do not intersect the horizontal axis at $\\rho=0$, whereas the experimental data (black curve) does." ] }, { "attachments": { "Screenshot_20250317_173836.png": { "image/png": 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jiveq7biFevN5nnc6HX6/wP5DKZk5wZx4F/xYdMDdbpffSZmfn5+amqKzIQYngv3vHFlsLFEmBeOEX6Jd+U44X3qtnKCXvV5va2uLzka73b506RINes34V7XKqY/iCEejER/07u7uPnnyhMrw8vLy1atXj7zVkjo/RyE+An9f48S2EXs7lUnn2RgzGAz29/dpycbGBr/HEQTBrVu3KCmkafry5Us6G71e75tvvqF6FEVRmqZLS0uUv9FoiEGvOD+2XujjGg3R2ogypp17DeJMivc1xogdcuKc29KilMrzPI5jam1sNl7qwjAsqBrwg9BO9E3x/+XcUlGQ+VgF24oSW4CKn6VPH+4O3jzxr88Pb+aORqNer9fpdGjVy5cvRVwr3qNrt9sLCwu0t9FotLS0RB2VMAz7/b69n64O7+/wFqm4tLitoi1pdnlB6f0BTfwwAAAAAAAAABcdBr0AAAAAAABQWhj0AgAAAAAAQGlhTi9cDO5UGU5MHnAnXPEldpbCyecb/CCTE4wzrVGPz0QVczvd+Yp2YobdhDa0u+U5L1++zOdt/vznP3///fcpKabLBkFQrVbpwC5dunTt2rVGo2GTxph+v08RbjzPa7fbPPZPr9ejuXz84O1UEP7pxGcXH7ZarfJj9n2fT0zN8/zg4ICSo9Ho4OCAPoWdtUJnwPO8RqNBcR3sEvtecRx3u106KjvflQ4jTdNqtTo/P2+Tvu9PT083m02btPlpqoxSam9vr9/vU1KNlyvf9/lR2bX0WilFMwxrtRqdcPX/2fuy77iO4+7uvuvsG3aAAAlSpChKlmV5k+3POTnZTvKc/zPJi/OUEyfnWLGtULEk2hIpEhQJkCAWYgazz9ylv4cKynWrBxegRFIi078HnFu3t+qq6u2iq0YIcOtCJqMo6nQ6zOEZUx3HYY7HrutSsUdRRJnsdrs7OztIMssJgqDRaKDkoyhCX80vvvjis88+w5xvvPFGvV5HTyHP84rFIlYVRVG73cbIRtAK7X6xWKTqZtoH40FSCHGaAx4VOJC07+B2i28ePHjwX//1XxifaX5+3nGcubk5IEGSZpSv0zAYDHZ3d5G8c+fOb37zG3QY3tzcXFhYaLVaQoh6vU71K7I+n8JoiJFUoay/M5Ez6Jhgh8Ph06dPwcf45s2bzG2MxQCjYa7iOJ5MJtjQkydPPvroI3QJdhynXC7TwFePHj16+PAhklprarGe51H9yhN/S52NSJemabvdpuG1CoUCnYuSbFBTx3E8z0MJMJ5932+1Wsy/nYrryZMn6JYsDK/1YrEI8pFS+r7PIg5QFdBn882Z2rR4XtBa03GEf00wlTEHSHO0nlaPCbbqnVnWbAsfaFJ+JRYvFNRamH7FyWoOkCdbOEyCud113StXruBKJISYn59/5513kPztb3+Li6kQYnl5+cqVK2iWq6urP/rRj3CJqVQqrVYLJ1hpLL7MWtLsPk0bkRHY3+8g7KHX4tUAW1rYiGJjD97Q55xgMGfiWxm9ZqNMAuw4yjqFz9B3LAuCwsodx1laWqIT6F/91V/95V/+JZKTyYSegjzPKxQKWJxWJYSYTCa7u7u40YSDHDv0wtaQcZtmI+4Cz3Q9iKKIdnZhYYFufIErJCHMAxbv9/uPHj3CZcDzPBpiGg5gtDguRRBmFtudTqe9Xg+D0LiuS4N+KaWq1So99Ha7XRoUan9/nx57nOxBPQiCarWKa54+AWbApQi+O+B7kTUMCMaI7cZx3Ov18Azs+/7169ebzSbmZ2YWZYMMHx8f7+3tIckOBuVymR4DRqPRo0ePIG7krVu3fv/732NSmqZvvfUWqgyO99jZ4XC4t7dHzyd03ZVSNptNeqaS2Qi3Ons2U0qdFoeMgUl4Mpl0Oh18s729/dFHH+FJZm1tbXl5Ga0oCAJm2/kYDAZUkvfu3fvd736Hoj4+Pr5x48ZkMpFSwqjBnG42/nk+mDbPBO0+kLQGnZ02+/3+w4cPx+NxHMcffvjhH/7wB0x677333n77bSTH4zHV5ng8puPxwYMHN2/exOijzWbz5z//+fLyMpCTyeTjjz/e3t4GUgixvLy8traGZLFYpAJBQ4JvUqigJEl2dnZoeK1ms4lx5oUQURTRrWGQjXEaRdFgMMDul0qlSqVy2jcOrfX+/j4NoOr7Pp2g5ufnoazjOMViEZO01tPplAo5H0xBFi8IMDPg6NBan3/DkK+g/FQGWBaRhMmBpHOYTNJZ1Hxp8ZLB5ts0+9tCTH1KKVOhQgit9eXLl2nBzc1NOt/GcXzv3j2a+oMf/ACrWltb++EPf0gDWVUqFTxdw5zPjuIUbFEQhml9961rhkwtLCwsLCwsLCwsLCwsLF4P2EOvhYWFhYWFhYWFhYWFxWsLe+i1sLCwsLCwsLCwsLCweG1hfXotXg3kewsw74ijo6OdnR30oGChjMCxivpPUodSkXUpBDBnjJeANE2jKELniiAILly4gJ6NUkrmUSmzAVHgDTwopTBJKZUkCQ101O/3qRvn7u4udU6L45hmhmgKSIZhWK/X0UVtOBzu7u62220gXdeVUtLiW1tbEBipWCw2Gg1UwWAwePToEbLBHEuklEH2B9MfP35MvWebzebi4iKS7Xb78ePHqO7JZHJ8fEx9cbvdLvLsOE6326WhgwqFAgj24ODg7t27yL/rutRs0jTd399HJj3Pu3LlysLCApBCiK2trUePHiHZ7XYxeI8QolAo1Go11NF0Oh0Oh8iz53nlcnmm71+r1VpaWoL3QoggCCqVCtbT6XTu3r1LFZqSyBNKqcFgQM1maWmp0WggubW1dffuXSRF1vJhDGJbrutub2+jQGhSHMfUGy1JkiRJ0K2o3+8fHR1hzcPh8OHDhxj6yHGcUqmEfrlSyiRJqHe053nVahVJBtpfIYQk3uPIHoK+6ff7Dx48QIXu7+/TKWU6nT5+/BjZKJVKc3Nz9XodM+isa7HWmrIB8Z+QnE6ng8EAveVHo1GSJFBEZj33GM9mtePxGN+APzMW0cbM5nke9RMzBcK6QDkJgqBWq4VhGMdxuVymbvDT6RR9dIUQa2trNPQUm37jOG61WqjfRqOxsrJCfXq3t7eZixqtvNlsUgNO0xR6MRqN7t27h5NPHMdbW1v7+/uYc319HVsRQrTbberxWyqV6vU6CgQiuqE0CoXC0dERdspxnEajgRLQWj969Ij6IbOgWcPhEELrFQqFjY0Nar0yG66GefExdZv6snhBYJJHM0NAqqkR8w0Fq5ZBSkmLKxL4AFKpeUA9WBsUpMXpM22UMQCN5rNt8Vwgs5s0x3GY2HOcaVFH0ghJUygUqJ0opWgcFhq5QJxEWsG5i+11tdZs7RbZ8Fp0YyYMx+NXworsodfi1UD+vMy2xQ8ePPjP//xP3GZ1Op2HDx/i4Pd9n0ad1UY0EXMiyFmoXhCiKKJhkxqNxl//9V9vbGwA6TjO5uYmPfjlMMlmpSRJUBRa63a7TQ9j9+/fp1t5YayddMqr1+tXr17FvWC/379///7jx4+B9DxPa00PYJ988smf/vQnIcT8/Pwbb7yBm9e9vb3f/OY3T58+BVJng28ppRYWFuhO0cmGqt7c3KQRp588eXL79m2qUArHcegiIaX0PI9O6ysrKxDq6auvvvrtb3+LEZgbjcb169dR5uPx+MGDB71eD8ggCJhwbt68SYP9pNnvMs1mc21tDWW7t7d369YtlFWpVLp48SK2lSRJp9MBTlqtFj3hN5vN9fV15P/w8PDWrVt4ZnBdt1qt4uE5juPd3V0a2vrHP/7x1atXkfztb3/74YcfItlqtSiT0AXUC0R+Qlsql8s//OEP4VwRZ7+VRFEUxzGqrNPp3L9/HwfsYDD46quv8NDred7S0hL9vjMej6lN0qBWwrB8pgWlFHx8AZIaM5tPOp3On/70Jyy7t7cXxzHmGQ6Hd+/eRdtuNBpvvPEGrYHtBhgJEkByNBrRaN79fj+OY9hYmztdfBZG70ajEY21Bp8D8BCVpulwOMR2pZT0a4IQwnEc2habQBgnhUKh1WqBZuv1OgvXTKN8X716laYeHx/T6NzT6XRlZQXNo9lsXr58eWVlBUgIh0bDnkdRhGIXQiil2CcPEFG32/3kk0/u378PL5MkuXv3Lg0e9s4771BTv3///hdffIFkrVZbWlpCE43jeDQaoah936/X6zhfBUFw7do1jNyutf7yyy9p8JhKpUInZyklMNloNGggKylloVDIibtmGjOzB4sXBHNWIYl/JlGzSOKzCdBmTrXsFMROFAxQG+YHTmYyYPbFnCGRtHihoApi02+SJKdtWkR2NmYFmfocx8FtiRAC5lJsF77d06/81Ma01tPplJ6TmUWxdY2tEa8ETh1RFhYWFhYWFhYWFhYWFhavOuyh18LCwsLCwsLCwsLCwuK1hT30WlhYWFhYWFhYWFhYWLy2sFf5LV4HMDeVJEmiKEIHiel0Oh6P0VEhSRLf96lf63g8pt4Up/nGvEyAgwe64oAvEJLMF8jE1+Y/jmPqUCeyVTE5g2Me+oR4njc/P0/zdzod6jA8Ho9rtZoQotlsrqysYKyXJEmUUuh86Pv+8vIyugorpS5cuAB+toCdnR3qrff06dOtrS0kDw4OHj16hAoFX0T0e5FSRlGELoVa65gEGZJS1mo1iO2klArDELtTq9XW1taAf3ESjQmtKDgBkEIIKSU1qiAIaGybxcXFjY0NKrrd3V30xa3VahsbG9hWFEV7e3vg9aqUOjo6gvfiRHRYT6fT6Xa76Bvs+z71IdRaJ0lCnUullMylkPrzlMtl5rlKDa/b7d65cwd9cQuFAkYUa7VazAs3DENkw/d9z/NQOEEQUIdJ13VbrRZ1CvU8j/JMLVAIIc8R3+U8CMNwbm4OKw+CwHVdbBdGH/IMYqR+yzPZQIRhSD1R6/V6q9VCe2g0GrVarVqtgjoozzAPINnv9zudDpLHx8ePHj1CJsHDihVHThzHYeOoWq1S19M0TalsmegcxykWi0mSRFFUqVRodzzPo5lZwSRJRqMRnX7DMER1F4tF6nStlPJ9n0bJEiduaYA0TZkPG5QF1zIq9lKp1Gq1kFxdXb148SKSo9Fod3cXyfn5eeobP51OB4MBSj5N08lkgl7oEM0L1a21dhwHzVsIUalU5ubmkETLqVardCAwmxFC0GVLGMELLF4apJQ5UwcOE5ZNSqm1xjcwaWAqvKEkAxuA6iwX7vxUhNmXcxa0eJnIV1OOypiZwRSNJN3eiJOQbKfVJqVkk7k5BVGSJVFOclr5dmEPvRavA9JslKAoiug5FoJn4pYF9rIs3Avbv+KzOMfa8yIAuyicU2A5xBVRkYDMpyGHZzaZUhJCrSLJwKZX2JviTrFUKtGYNOPx+Ne//vWXX36J+dfW1iB1Y2PjnXfewa2t53mu6+K2uFgsvvvuu+vr60C6rnvt2jUaefWf//mf6Sm33+9Tst1uP3r0CGW1tLQ0NzeHR+g4jnu9Hqo7juODgwM8uUkp5+fnV1dXhRCe59VqNcy5srLy/e9/H6PXPH36dH9/H7fjQRCUy2V6hFBKUaOCcz6Sm5ub77//Pup3a2vr8PAQJT8/P//DH/4QY0GPx+O7d+/CWXd7e5sGWA7D8PHjx6jB8XjcbrfxFFQsFiHiLpBaaxgaQAohXNelMS2klDRwbqvV+uUvf4lMOo5Dj2Tb29vdbhdPDnBQh1hBR0dHDx8+hPdCiMXFRRpgaTqdQtwvIF3XpcdLz/OWl5fpobfb7dJwlPQALIRQStGll+4axYl5A8/Uzk1Uq9XNzU3kynGcDz74AIscHBz87ne/w1hrIEb8uCClpIcZeEM5KZfL1IBXV1c3NjawU+vr6xDBWEpZKpUon9PplIaCe/jwIQ2/tLe398UXX9AYUd1uF+UDx1QUexAEv/jFL9544w0ghRCbm5v4YUUYsygTl+d59Xpdax3H8eLiIu3OZDLJiX0ynU6Pj4/pSKnX68hVpVIJggDnEDBIFhabxmVJkoR+WkLAXo1uuebn5+kJ/5133vnxj3+MpJSSfjjb2Nh47733kKvJZNJut1EanU7nk08+Qe2Xy+UoipBnrXVAAqIKIRYXFy9fvowkKhE+FtDQ1iJ7EJpMJlTdLOSMxcuBzEZQZwB9wV9pfLbAJHigX53M+Ye9SZKEffKg33fOLG5mALDupEZ8e3y2eKGgYheG5E2rO6dq2LwN/+NBcjKZROR3QCDnaTUrpcIwZOZBM7MuMMDqAM8u+ZT5nYI99Fq8htAnQJKeGGGOwAEJJJ01GNiu+qWB7qHFWdPN8wLIir89AZUqkCRRSCk9z6PTaxzHdA+XnvyXxvM83/fpP/dkNpo//IsSU0ulEj1Pep5HM7P/ucH/ZJANmIXZxE2NIYoi3LJL8u9ZKSVVveu6vu/jARJ26pgKOamdsB6pbJBMz/PoXh/+r4gZPM8Lw5D+ZzgIArAHKSU99U2n08lkgr2bTqfUmBOy5QIwDYpZH2vx2XGcQqGAGRzHCYIA2wrDkEoAPtMAk7QvkESFA89Yj8r+fxIqgXqEEFprJknG//OCUoraled5xWIRee73+4p8aQIxnp8r6COSIB/sI5AgMbZR0NnxGGcvYoxGo8FggNYLX6xwLDiOkyQJthJF0WQyocaTM9JNSCmBtzRN2Xacjj4T0AVsS2tNpUFVD6CmIoRIsvFCwR6QRJgvqXEK46qF7/u0C57nhWFI3wRBQD/E6Oz/+U11UwZgLCCJ8x50luZk9TB1m61YfOswLe2cOM10EWxKYTizuIWFMKwISHyTY2AANkEx5CQBoP4zs32L+Ba28hYWFhYWFhYWFhYWFhYWLwf20GthYWFhYWFhYWFhYWHx2sJeb7Z4NZB/K0Nl747W6/WNjQ28J9ZoNMIwpLf+isUi3q9L03Q8HuNNNvNiBr2K+dIAly3xel6lUllYWEBHR8dx4O4i5s/hkIlOEjckbXijNRqNpaUlJBlYVY1GgzJpCop5kEYnYVrYvUpgCTWilIJbx0BqremVXSFEHMfsliZt13XdYrGITZTL5Wazib6LSZKUSiUsHsex67roNCilbDabcLM6DEPqwuo4TpqmWDBJEkmccBjPAGqTTDhwQRSLu65L7/Q6jqPJRUetNbbFLm1CQazZdV2qzUKhsLi4iDfD4R44vShOI0iJk14gmaYpJYFhbN3zPN/3MQ4WXAEF+TD9wvDE3gVBUC6XkUySxPd91K/rum7WHSiOY3TIB5LaIbNJkBWSUkok06wz23g8ZleFoQtAwvV72lm4HoyZnz59iuNRSrm4uEhDgtF2AYxnAJJJksRxLLMXuYUxs1EjEUKA/LGIlLJaraIklVKFQgGLw+V8yiSaH4AxLAzZ4kvKvBACjRNBh6eUslAoYAYpZa/Xo0qZTCbIcxzHLFhXsVikJsoaQmitqYKEMVLoDCOMG/hg2/gGSOyjUkpnx6NP/C+01rVajfoPl0olWnm/3wd/YHAVpqIoFApUoUzdMusZLoSgPbL4toDWaw4Zpi8Glp+RTLlSSrN+RE4SgI1Q+gz2bCZZvExo4746m2+ZBs+pKdd16STvuq5SCk3rzAmEGTBrl3EoDPsB8pysfiuwh16LVwP0zCOMoch2MFeuXMEgQOLEEQ4Hs1KKHmaE4aM1cxh/u1BKFUkYXiGE67p0h8d2wwi6VxMn/ng0Z61Wo8ekN99884MPPkBSGNMcEzvdzqZpSqdXIcRgMMDoL0KIfr8PPEdRRKtVSnmehzM1dA0jKrmuOybBt8WJKyOSLjlQCSGKxeLi4iLWv76+/tZbb9EtKUWSJCyQ1cWLFyEEcZIkjx8/RiHDdxM8Jk2nU8dx6JFvOp1iPQAasQa8dpH0fb9UKqHoSqVSqVRCIw/DMCVH6DiOHceBrb/v+7SzYRhWKhVUSqVSWV1dxUNCEARLS0uo3zRNr1y5Qr2saTxqcXK0QzKKophEqYVTE+W5Wq1iNCbgH8jpdEr167puqVSibMdxTD8fjEYjJKWU9LiitR6Px/QUNBqN6GzAjrIqe2wQxGJpo0KI3d3dnZ0dJKvVKo24C4LFznY6neFw2G63gRyPx7du3Xry5AmQruv+5Cc/oQGNVfYbh8yeXpITAAl2BaZF/U6FEB75qCSEYM7tg8GAfj5QSi0uLtJ2KRu+79OvP/AGnwFsS5SQ2AeI1AiC4DgOi7dMhydwhZLvdDr37t1Ds5mbm9vc3MTPB8PhcGdn586dO0AKIa5fv04/wxUKBSpJKSVwmCRJr9fDwOZSShrCTQjheR77HkSHZ7FYLJKgX+IkRDM8e56XkJioSZJUq1W6xERRRAXLolVtb29/+umn8N51XQyG57ruxYsXaYhp3/eZCui8x47xFt8W1MmhkY0OGBqn7SWklGxaYMBqASxnTsGZSNMURorKfu4BNv6c79lrtvh60FqzpYok/q/xIMn2XbCugaZYPZCKz0EQ0JWoVCr5vo8GgJUgaFVa6zj7TZnNOWYXmIXDt0Ip5XfWqOyh1+KVARvnFEopOjKLxSLd7ujswU8aYdnZSP4ujFhgCbmCLlAmk2x8l3yw3lFZsRNCuVyGH+xBMLHnSMZMirMhpuI4Bp5NzqkGpZR0AZBSss6y5cHJxsKhZ1EhRKFQKJfL9J9ydN6Hmqm1lMtlPF66rosNKaU0CWaTpimVJEsVJwsAkmx5UEo5joMZ4BlJqBa7rLXGtpipQz34JgzDRqOBm3vf9+lHjTRNlVL0Wwk7i6rsf3qZEYoTPvHZdV20H9d1UQKmzdCCcPygh14mOtYoPW8ASVO1MbrxLwPLOZlMaFjgIAgcYkiu63qeRzVC2VBK9Xo97Dt88oBnBOOByYS+ge7PFB3VtTiROSXpG9d16VcJka3N930waXzDKmeAsqexTd9LKVln2UCgX3wcxxmNRvh5qFgsRtngouPxmJ6ZtdbMRPGZAmRIFQQjFDOwgUMNEkl842RDr0E9dDy6rkv//1wsFumwYlqI4xgsTUrZ7/fxPOxlf4tLnAxnJNM0pRZ7Wt8tXj5Om2EA+MbMZr6hyE89P0xOKJ5XKxbPEUxfZxrSaVDZz74zp7Ic6OwqyeYck0mS+L84s4lvF3YOtbCwsLCwsLCwsLCwsHhtYQ+9FhYWFhYWFhYWFhYWFq8t7PVmi1cG9NbEmTcoJAkJI6XMLzvzksa3DnrJRBhsS8MzhwE6xa6jsDda69FoRJ089/f3Hz58iCRrBXhATlzXLZKQYPAzoXg1cTQaQSAlIIUQYRjCvccoiugNRnDpRK6SJBkMBsfHx0C6rnt4eEhvLE8mE3a3kDo6RlFEeySl7Ha7pvTgIU1T5iOaJAncOUyShF4v1OSOsTCu/QBM00Lo3F/ghFRkI01TetERLvQCV1pregHS87wwDClXw+GQ+iI6J87AQog0G7NNCFEqlajzIfQRSRg49A01HmAYa4vjGCQGSbSzYBh4SRXur2LBKIq63a55PRgxHo+puMzK0UFUnETJQp5BZUBSCQshptMptZPRaDQcDrFgHMdU3cPhELQApM6GTUrTFK/uA5jcRFbjVIxCiCRJJpMJ+PTSu75CiNTwWKYDIQxDGjMJ7txSy6RlwRjM4UxJ+gZy4ht9YsAgf1ozK0jlJk6u22EGKSUV3XA4PDg4wE6BFqgEqAELwx0DIaV0SLQC4IFypbNX6GkTQEYk0EAURVEU0Rv4tHLXddkk0+v1qNv5eDymHhM41wGTVF/mNJIjSZpk8d0H6ItaPtNgdBLZEaCUYoOXjjJ4g88q+/Pm4nTzMOthOK2gxfMFU4SetdoiyUCTTKtgSwab3GjNOU0AGBssfz75SmD2+mFh8V0D3egDzJFPSTZ02dbBHKu0OEvNXzBeENI0pedAKaVLgv0KQyBs84QTH2MeqsUDRpqm9+/ff/ToEWY4Ojr66KOPkAzDkB6KQHQon7m5ue9///sYNaHX6926dQsjVymlLl++/PbbbwMphHjy5AlEmtnf3799+zbuZR8+fDgYDNAfr9/vf/755/fv3wdSKXXv3j0am6Hb7S4vLyO5vLy8vr6OZK/XOzg4oPP+73//e3xOkoQeC33f39zcpLFkML5Uv9+nAbSSJPF9H/1jR6ORysYdodtiIYTMxi6K4xiDYAkjlBec86mjIxzegAQ2wC0wTVP0TxZCtFqt9fV1NIbBYHDnzh3kmelLSlnMhkO7ceMGPUXEcczcgegxSUpJbRJ8YrvdLuYfjUZwmJlMJvQQ++TJk5s3byKTIAqsp9/vb21t0Vhi9DAgpQyzMYfZYfXx48d3795Fcm5u7vLly9hHz/Pwu8xkMqGRxvb29u7du4dku92mh17HcXwS7u7Jkye9Xg93qNPp9OnTp3jY9n3/+PiYcuVn440lSUIFAidkNI/RaAQh06SU8BUDczL4vk+/Ivm+n5KAZ7BpRp5F9mjnum6tVsvxj1VK0VSRnQlh3oAJhJ3w6UFOnAQ8Q7JYLFYqFRTdwcHB0dHRwcEBkEdHR+12m7qdDwYD5nZOBzsN2yYIh47jlMvler2O703HWvpxJI5jWk8URZ1OB/MPh8OnT5/SGalUKmEAqkKh0Ol0cILSWn/22WdfffUVkEIINlejYSilIPwbZmMCZ+pzSARpYSxMFi8IWuv8RZ/OqNkUDoecS6WUbGy2220aViAMQ/p9h67UwuAqCIJarYbjTmZjVYjsHoCOVshDuWJWZ/EioLXGj8LWdxB5AAAgAElEQVQAc7JlEzIFMx5qCTAhIzmdTqnZJEkC6wKQrB54Q0nXddmcQzOcaSdnZvjWYQ+9Fq8Gcsb8zDf5A/tZYTb3ogErHE6RsCzlzIkMbJ1j7zEpSZLj4+O9vT3MEMfx4eEhknSLJox5eW1tjZ42j4+Pd3d39/f3gQyC4OLFixcvXsQMw+EQ2hoOh0dHR3iSOT4+hv00kFEUHR0docqklP1+n0ZerVar9F+7zWZzZWUFyXa7Tf9d1uv1dnZ2cBsdZf+vWCgUms0mPUbimgGf4XGzrrWmm3u2wxDGd3qRNZs0+29Gpp00TWMS9Av+s4TyieMYT006G9enUChUKhXkajqdtttt/M9SmqZUFI7j1Ot1+hWj3+9jo0KINE1pF8Dq2LjD2tI0nU6nKNjJZAJ8CiGo3IQQg8Fgb28Pa4bOonCOj4+3t7fxH2VSSogpheTS0hINrpaQfy8LIXq9HkZRFkIopdbW1qjk8TnJBsSitwmEEEqpQqGAnQVtInl0dERNNEmSMQkIH0URdB9IYfxDko3HNE1hgAMZRVG/3/c8T0rJ/hXP5O+6LlVfHMeNRoPlx2dx0hA8g0XRwxgzV9aWiSRJwIxptcKYFpTx40A++UkqpdSIRF83tYCR5ACe55VKJSTplwgKKSU7bDvZf2uD1SGZZANTg0KR7fF4PBqN0FqiKPJI8OcgCCaTCbKttd7f36efDpkkvZPQ9FJKz/Owd4xDyDCzdxYvH9TCTYCatPGrMxSgTaZiivF4TA+9bFGgs6sQQhtXFcrlMlYupTSZgS6w98AV9i6fQ4vnCLYKmAbG1Me0hs907RDG1oItvmmagsaBZE0wQGpOnpykVwXW1i0sLCwsLCwsLCwsLCxeW9hDr4WFhYWFhYWFhYWFhcVrC3u92eLVgHl153nBvGTy3cFz77KUEu/aCSGSJAnDkN4cZm5FzDWRXYXysqFxHMehlfu+z3zb0F/R9324Pgrv4foNvYFDCwLPlA12jzEgvwIKqUEQ4D2iyWTieR69VkRvSAZB4Ps+8iyIPx5cy8T3cPsUSZF14nVdV2U9o+g9RnHyK6lIOtkYJEop6uDneR6tTZL4NzOrRVlBKl7jhF7jZSe44DqzswCfOC0DydSESUIIpZTv+8gMaAEym0xSO6F1CkMFoG5UqJQyCAJaG7tYnhKnVnHSWcYqQGatF0WKJD4LY1pQSlHbBklSfTGFMijjxi81Uf9kpACHtB4pJSNZF5hZ0md2C85xHKoFE6zLZneAGSmlOTRQFMKQJPCMlXueVyqVqHsCvSytlArDkI5upm6TKwTlSmZ/GloYIw5EhySYHOZ3Xdclvm1QMw4rUD0W11pT2xCG1ryTeS8MQ9oKPFCx5/TO4ruPM9VHda21pi4tQggabEIIEUURDQMhjBFKXTdV9tdZAchPDmM5SRbPF2xaYJDkzjmQJPHPMPerrFqTxGcAXRfM1NcefJBYWHw3wfwW2A7mTNB9lVmQTRN0UjBTXw5gDaM8mzzkT5GQKqWksioWi9euXcNwL1rrhYUF9MIVxinXyR4M2N59bm5ucXERHWKLxeKNGzcwspHneVeuXKFxd4IguHLlCpKIXq9HgxWFYXjx4sVarQaklLJQKNA95draGo1tU6vV5ubmkJxMJm+88QYK5/Dw8NatWzSGDZVbGIbvvvsudQmG7a8QolgslkoltLp6vU4PhEEQUCYdx2m1WvRsdvXqVUwVQhQKBVp8aWmJqqxSqbz55pvIZL1eb7VaeDBwXXd1dRUqZwOh2WxeuHABldJutyuVCgbOmUwmBwcHSHqet7GxQf1jL126tLS0hOSPf/xjqu633nqr2Wwin3DwQ7LRaLz//vuoUNAaVH7t2jVqRUEQUE9U8KPGhtrtdqlUgghnQggpJRySkbx06dLCwgKQQoi5uTla+fHx8WeffYakEOK9997Dyh3H0SeeVGE2stHq6ip1qMNsABg12Nlyufz222/jDlVKCYd8IF3XXVxcpPqlDQkhyuXyhQsXkBwOh7/4xS/QYa/Val28eLFUKkkpWawpNq7L5TI9ENbr9UajQe2ZzQn0CC2lLJVKdBy5rkv33CJbnG2jHccpFApa6yRJrly5Quth08LKygolwzCkTPq+X6lUsO+j0ejRo0cYYMxxnMXFRRpH4M0336Qu91LKmT7PQRBcu3aNRqRjoltbW6NGuLS0dO3aNSRbrdbGxgZ+ERgMBtVqFQ8VcRwvLy+jrHzf39zcbDabQGqt4zjGSRXeUEk2Gg0w4EKhcPHiRdo7z/OoCpgkhdELi5cAkHm+5GemSilhwkGSZtNaT6dTnL3jOL5///7W1hZm+Oqrr3Z2dpCMoogea8MwrFarWOHy8vKPfvQjuvhubm6iaUkp6f6BgTE/sy8WzxegEZxh5CxXavaGTey4PLGybvazoLmFo9NRkiRRFNGFDFY6zA8v8fk0E5oJWvA7a1T20GvxaoCeWoXxzyITp80XQJqDnI1zWpylvjTQ5VMYk0j+ZIRdAOZRVr7vLy4u4uZPa10oFNbW1syCSFLRsX1wvV6vVqtYm+d5y8vLuPlzXXd+fp4esYrFIhwvh8Ph4eEhLv+FQgGPmkKIMAwXFxfxtCylhH+FASmEuHz58sbGBpJh9p/VrAvVapUGyVRKBSROUhAEl7IHv+jkZyTCMCwWi9h9eiwXQriuOzc3h+1KKYvFImVycXGRHnrdbKRWFoQ2DMOlpSU8CZTL5VKphEdoKSWVKq2nVqstLy9jd8rlcpqm+P8BCDGNJwrf99fW1ugBcnFxkW7WL168iM9CiJWVlWKxeJrxF4vF9fV1bMvzvLm5OTCGxcVFOjyZFdVqtQsXLmDv2u328fEx7t5A3fTQe/nyZfpVQmX/FzocDmkMobW1NSklFgc2wB6ojQkhGo0G1ftgMOh0Omg51ISEEGEYsl9CojsYx3Gq1SrVC0MYhvSwurS0dOXKFdzRVqvVubk5yBCGIWWSwSPhlIQQaZpWq1U2YPGZMWkCA48B2MBhwCk3TdP5+fnTrEIIUa/XaaMwarDmcrkMOgISQr7jJw/XdS9cuEAnjUajQb8lsTAtOLm5rks/wAljyajX63T8VqtVqv1Wq7WwsIBm0+/3tdaooDRN6/U62rDneWtra/TT4dHREW2LNb24uAjzleu61WoV2YAm6Bne8zymQXy2eJn42pKXUtJZgibp7L92oyg6PDzc3t7GDB999NEnn3yCJDv0VqvVhYUFHFmXLl2an5/HLy+1Wo2u48I4QVl868ApdCZMa2EkvmErIDu1uq5LVxClFC2rdebHEXH+RHxtywd8w+IvAacqwMLCwsLCwsLCwsLCwsLiVYc99FpYWFhYWFhYWFhYWFi8trCHXgsLCwsLCwsLCwsLC4vXFqf6Dlm8IHwTjx16Nd8EdSYxkaYp9R2i3gX5BRnAJQDJM10CaP40TaMoor+37jgO9cKaTqc0qkeaplg/q5Y1mqYp5SpHSuKkv7RCVjmrTWTD0mCPzHqYglgqc/SShugY27Q4NEoz5PuHqBPnWyklVYGUstFoYIQkrXW5XMZAR1CQVptmwyYxnsMwrNfr6MoYhqGUEjXoOA71P6QIgmBhYQG7Mx6PW60WeodWKpWlpSUMVaWUarVapVIJSCFEvV6nHpLMB5LKXAhRq9Vu3LhxWuQG8Mb8c27iEuO6LnWxU0olSUKNuVar0SC0nucx4bARR63IJxGkhRBhGC4vL2P+IAio/6HjOHNzczBSmEaYzy2rJ47jubk5dAxzHKfZbLKYUtSoGo0GZRJCKyHJ4Pv+3NwcMqOUKhQKILparUb5ZzzTEFBCiEKhcPXqVRqnlA0TFiGMakEIcfny5X/8x39Ecm1trVQqYf2O46BJs/FFY3SJkwgfJJ27Ufm+T/WrsjGiqP/2TDA5v/vuuygTz/OKxSJInvZUGHOIMHpBWZoJNjEy2VJFsJqllGwahAxa63q9TvlkTFIDE0JIKU1vZ8xfKBQuX768urqK7yuVCq2cCYT1F5t2XbfRaNDVhHUnCAKq32KxSH0ggyCgE6zruq1WC7uvtU6ShBoDndmklAsLC9Tg2WAvFovAGLCaE7mKGpU4aZemnqlu2msmAaZNccKPNFYiCxNMmACqLCBN+6QkfeM4zpUrV9jqQ9e1+/fv3759G8nl5eV/+Id/wAytVuv69eu4LIZh6HnezBhv+IBgkwBJsXiBYAOQ6cUcrWzrdZqm2CwxnU7pYsoWNUl+CQJIWrPWOo5jyqeb/X2HJEnYjERTxatgTvbQ+1LBzFobEZVyoE/AE06QX1VqHHrdk5hv+QUZtHHopWPGBOUZRhQdhI7j0B1St9ulTKZpep5lXhjDnglKzlqK8nmmfWRlMVWSeDmYxNoliZzJM7vGirO9fg7/glQO3NKCLIRStVqlXLFgP0mSUI2IbLsw5eGbNE098uNActZmF+D7Pg0L1O12q9Uqhn2uVqutVmt+fh5IpdSFCxcwYoc4S87sTblcpkdTE3Q7K06OSYL80Ahmm0wm2DulVLlcZgZAwZgUs/hEBEHQarUwv1KKis5xHIyaMx6P6UcKdnj2fZ8GsBVC0DDXYtaumjJZqVTYJiwHruvSIFgUTObMipjlh2G4vr6OpNYaY4kBmE3SCKhCiLW1NdrlIAjCMMT6oS3oMpM/jcEmhHCyv2ED6qYaCYKAsv1MYHKuVqv0kJym6XQ6hQzmHoI2ahoVY4n1Mc1+KWOmzjY0DNqI/4dkuVymx0tmVAxM3awLQRDgiRfAOshqlsasC3BdN990oyiiRhiGIe1Ckv3koZSq1Wo5nWJg523P82ZOfTobvxdmyJndAaTZja8w1M3ARMdEzRYCKSV0ENR3/s7+HwQTLEIbW7jzi1Eptba2Rn/doNfrUSMcDAa3bt1Ccn5+/v/9v/+H82qhUKBx7B3HcRyHWjguZCKXK7MLFi8IbDya0yYbrfnHSwQb13Ec038szTz00qrY5BzHMVusaeY0e45ws4ESXwlDyptALSwsLCwsLCwsLCwsLCxeadj/9D4f0C80p30UFMaHkDO/i5hV5RShH3sANLPWmn6SYR93WUOMZI2yTzvmxyosrrWm/z9J05R9rIqiiP7bKooi9iUbP2KZDTGwgqwLZrWUFKSPWmuZ/e+KzP5ouDBqA0DHZ35KR5KpAJ/FSXFsyOwvTQWStYXPwuh+jugYG2ZO9oaJjhVnZJIk7D8V8C87Zn7FYvHSpUv0JwfxNi9kdo2fHMzprykofBYnWsgpjiTLI6Vk387zJSOMGhhofq21c/oPPFLQAQUkSRTC+Odevn6lYdsMMyWDMGujJEIaA0oYVSG01iBqfGPaGP3HL04RAPjXGXJyGkvC4Moc1EopZFIpRQULCqKVa61pj1iqMPrLUlH7zDhz+BdnpQIwDwg2m3gGWH5q/PS9qcqchswkVpwZMMtvCtas8OuBid3sFH3DUk3ZnrYQmJOPOW9QmAPn/GD586cCs7+IZ233tQedB7IpZ0ApRbVA53whRKFQoPcFSqUSvUVfLBZLpRK9zxySnzeDWZGOULQ0U9H5c5HFC8KZcqYZVPZfrHQOYRpkK6DM3rADG8P8+aqXxj0ac9I4jatXBfbQ+xygs/6WQNIMaBaO45ib1BzkGyiDecCg+aWxw8M5kW0y2IgSxlCk9TCWTFEEQYDTdJIkdLcqhBiPx51Oh5KscuwU3cgKQzKMq3xow2+B9cLN/hQqUyhK0lQHU4Epc6YRfBZC6OzlZ3kCmgHZkIa7HQMqURo/Ps7aZTbJUqE4kqyDWmtmz7Q2rfVoNKK3awqFAnro0YaazeZf/MVfUNfTUqlEfeQ8cmtaGJJkk36apkn2GidKQwjhOA79GVhIYpnxmbailKIsiWyq1jrJ3j9nN38Y0uw1ISkluhvgG3ymYFdSpZRMFFEUIRvAM9MRhTY267T7jNTGzGbWPJNtZkViViv4BjLniILamBDCdV2qF5AkJWeyJLLX/0wopTzi0Q36pUx6nkdrZtpnlTMTZe3mzwwUZpL5hiK/WvMNBRMd9J0pDkF7xwqaYNVS7Qsh8idnNtXT5/xGxenMCyHkWd9lKEtgDEyh1Ca11qYzkTCMUxiGwTjEgoAzO8gyMFJnp2tsSxvjGl7CA0jmzKZfezDVUPnQ9zmQs6ZBql/2y+ELCwvUqQdcfvB6s+/71WoVK5RSmpyYb8SJupF/pZQ2VgGLFwQqZ2l8WaOpbKIDQBG2vWE+g1JKFvHEnGFOU7eU8jTXDABb12Za3Xcc9tD7HKC1Pm1C/CZ41kpMNhjMRX0mWD0sp87+x9iEWRzza2NuTbN+C2mamozldwphFjwNwGF+tbQ2M+dpbT1TtTORXxxhdsGs+ZxVmQUppDEvi2zNOqtT01rYdmpmc67rlstltAQpJTuqzSx1GlijTFDm9o6B9YjitPcIJhmSwsG4kicgWWbjzGy05nwevgYYzzmyojDzMMaY3PI32SxJGseVnLIMZ+akGZjKTNnmp+bjTE6eC0BllCSJZ4CqO0d93xAg5JwKzaafqRdfD9AoNv2sTFKY3NLMZkEz/9eGWRU0x6wC35vPFoBvIhOqBThwIulkb/G4rkuPxEDiG9d12ee/88Pq91uBOdAo2PA0RyvAnIG11pSUxoL4TOo+rV3EmRm+48g7vVhYWFhYWFhYWFhYWFhYvNKwh14LCwsLCwsLCwsLCwuL1xb2evNzgJTyzJsJ5hsTcEsh5/pBfiWMDZMrBkzVuXdQz+waA+0C1IyVwwO9esFuSivjRwvhYWajTFD5cjN7wZrO6fL5wW4rsXpMDk2uZj7jGya6M/PPfP9MMG3DvDlDryWbXM1kgNm5zt6ZN0uZd5JzrnWBFbH6kYSGmJpYc6amxFmShEpoHrNOxhJJ5IDMNE/+WKCgbMAD6yw+AxgnZgYKmb0rxfwR2JjKx2kSyGfARL7YgeHT6jyNBwAtpbOOcKdVSPFMgv1WYHb/6zFplqI1M0sWs/IzDZpKpM+MxGdzFTMbOg051c4kWY/YvAfWQlPxOR8mw6aOmBGaRb4GGPPPpc7XBqYBU5xp2xQy6+3FDCN/9YSy518IckAN+JvUY/FNYM5X+RMFVRnVGmx4kBRCsMArLD+zZ2YAz2TPryLsofc5gBkrmNTMOSXfgFLya43ipFosAoabMypU9sRF50fATEPXWrPoRMyThI2QfOjsKRd+8gud7JMkUUphKCNhuMV7nkd/OTMIAjZcEdAQJXOYhEkB61HZEDUmzBZZZmia8SalBDcb+gafhcEzVa5JCsNyGM8mkxT6ZOMCTOZkZqJjmdM0ZT9fSX8YNkkSFjaJ/ZapQ34GHTLAQ5qmcRxju1JK9nuzFFrr6XRKA8OEYcjkzEydps60DdZlyiQOB6gWudLGHoXBVChJ/N8u0zc0M+u71pr+JrDM/p7naYISJ+rDpqWUZvdp8TTrVM/GozAyQ/1IMiW6J7G7aDYArVYbX1JYZgazCxTQLn9LgMUZV/nVCoMrmM3g2XEcqhEAq5z2URoxbL428mXFwDKz/jIJSMPjlxVnHZz5XgihszH5kiShdqKyszFI5jQSQNtSSs0chtAozelmI8MJY0hSmApinT2zKpphMpmw0DKnxYZhKmC9Y5KcmRnfMA5NmNrEN7Rasx7zzWsPKpAcmNnyJelmf4aATVwskgVbPT3P830fg/aZ5s1wmmGA3vPLWrwIsBFHFxRhbLyZjujYl0awRkbS3+mN45hWJaWECRnJnIaEsat5DZC3V7A4P5hZ5JOnQRv/TDhnQQTNL2cdxZFkoElmuzkFTdCGoEe4+dNaM67Y1kEaP1VymgRYd6Ahkp4Rhcm/2cevAegOfZNfrckzSRTiLDvJrzwHX68UgAkWtllYISiXZjh/p6ipQ7XUGGiqEEIbmz98NsEExcRuvjHNbKaaZO7/DMXpPQVo4xSUkx8yY5ellHS3lFNQZFPhmXbH7OnMzs6E2S7tFMhnZg1mQZHL1bPC7BQlc5CT01QQNXXoLE01wTr4Dfv4ImB24WszSQuaRkWPo3rWxyNanMlKG6HyGJO05py5iJUye2q+QZhJ5huGHE5yYPadSZKSafYjFBPUM+FrF7TIMTNTI0y/DGwlYqT8uv/pNdmgyEmyeHGQUubPVyYwg2kn+AygmyU2SwhjGqGAJJqabzyvIriwLCwsLCwsLCwsLCwsLCxeG9hDr4WFhYWFhYWFhYWFhcVrC3u9+UXhnFcC2EUCkvK/N2GwHnZFQRj5cy4tzATNfE5uhRBaa+qHIHNjF8nsFQ64s3paZgATyPk7xephrZCU/0V+9/MbxVR6O4UB6szvLEM+Swz5HCJM8dJbmoK4sAKYNqMoov4h4DqCGUChmGoiRykMVNGsTpAbvcNj1mMWoc/5TJ4TWmtWVX73zVvTFDlJAOg1PmcTM8jvO0mZASr284BKADik1+0ozwy0lRyGTVLMYtLM8zXAqj2zTnq3kClXG8FC8gHtMklmcpwb30Qy8jkNDZGrX2HYJO3veRjOqZwlUZHiewR7eabozI4gzMwMORlO4/lMQJ20jzmtiFz+RS6HFvmQz2/gULClmZFgKvntslQgTUUz/s0MFt8FUB2dqXoKlpNOFGfq+pkaehVhD73PH9IIiXEa0mwUGZjgqHWyWAX0WWudJAmbItlElhPsB4rDs+M4zJMWn4VRcDQadbtdbCgIglqthsVlNt5SmqZxHI/HYyS11ixUA43wEUXRdDpFcjqdQmQv4IEde6g0zjxgMNFRWUHlNAMLiMIkiVoDGdKcrB4W6obVI2ZNajlcMbAVkfURSVZDmqadTmc0GuGbbrdLSScbyiiOY6oRz/PCMMQ6gyCo1+s5YYSgF/ytEMJgjMV9cU9CIgGCIMAAHsII3czGETMVYbRF5TYTKDqqIGG4ygyHQxoQwskG4CkUCpRnyIAkvKEkBZMbkPiG8g8cUrNhbLAuMCRJQvUrDNkyJikppWQdBOAbhM6OOACripH4LGbpl2Ywhwkl2ZjC92JWtTmW7DhOoVBgw5MNQCo62i6k4rMQIjXiw3meB3ny9cXq0Vlfd+CK5aFgcs5HTk7WO8azOTXRSV5lA1lBBnwGkr5hapJSzpz3gCXMKY3wZmxmYyqQ2YHDOsjeSGM9YoA+UhIetDEQkiRhRsiWDCoKeEOfWarI6oLGDxPGxJhvKhZUdKagqKnQ96xUfiUMURTRtXg0GuHeSQgxmUxY6CPf92n91ESBhAemaHg+kxmLbxdsokhPwkZKKX3fZ5Gr2AaVzmxCiCAIMAMUZHZCjYHNSCJrKszaTSvCDGbSdwSnrvEW3wTn1LfOdWSXUsrTzwzC2A2cNuUhmO1ifnbAMMGGxHA4pJWnaYojCnjGJKUUjFXMqbMDzNw60B4lSQJ9lMbxQ2S5yheUCSYrBp3Vi3mKgFToWk5Ox3HYDgafhcEDa/RMsPys+0wRiDRNx+PxYDAAUmvdbrf7/T5mYDzHJPi2EMLzvEKhgDWXSqVKpZJzVBCGmmY+gyhQGtAXmiG/CSYKs+OsLfyLb8wiM0FLJUkCH2WAlEbsbnogFKdr5DRQhUpymKGCMkmRNUKzswxsDoERiuRMhulL2t8cMAUJwxLyhWMWp8LJ6R0C5cBaYSMohwdpBOBlsmLFWSqDzn4vcxyHft/MUQHrgj4BkPKsaTCng98ErKeUJSGEnPX5NZ8T1keqJlOwVG40yczGFEQtHzjEImZV9M155MzGLz7TerRx74Y2KgyeGcxUVhWrXGaXUW0MBwsA1RHiPLJipZiEITWnnjR7XImiiB5xYTuECmVMAsnesAdEDg8W3xHo7LwHZ1GwKKZQU5vs1ArrCzzDvIQ1sLLQKC1OI2i+HsibuC0sLCwsLCwsLCwsLCwsXmnYQ6+FhYWFhYWFhYWFhYXFa4u8S4MWLx/m1QUKdnclIb8xjS/x2XEcSppXIADme60144GScMcG38B9G7wOAReuaJ1m/d81QH/PzyfmhIfTCp72/rnA1NE5obNmo7VmF5jZjTjmRCSljKIIu0avaIpnuUbF3stcs/8aOL9CIdvXa12TC0jQha9Xz3nwtWs+s+CLGK1UMkCSxFcDpjbzb7Tmg9UGcya+yRG7Prclv1qg0mByzrcWJg194scLIqUrEZvKpJTnlySbkZ77BAU4Pz8W/wdhzcMCgcZgWoU5f+bnOf9UZtaTj/PX/C3CHnqfA7TWptnhM6y1aD0s6TTPHwQu23Ec9/t9PJ9EUbSzs9NutzEnC5u0vLy8srKCpO/7YRgiKYmfFWv36Oio0+kgOZlMaDSF8Xjc6/WwF0EQ7O7uYlXFYnFtba1UKmF+h4SqStNUGpsJJgGW6roueLuxHSc9aYuzfD4ZdNbZiYoC4GRDnoisr5QQAnqktWYOD0ySUkrKpNlZfAaSvWGOGSyDaXUzK9daU8fjwWBw69at7e1tTL179+6TJ0+AFIYVmWZDW1lfX//bv/3bVqsFJPvOIgzZIlcyG2YGNIJlTVHkg3qxAsDS8BkiQACplKJO7Frr8XhMD/ZBEKB+aXd01g9zPB4fHBygO7SUslKpUFl5nhcEAZI6uxSxHbkyAtgw09Jaw9hXSlEVQB6ak3YWeKam7vs+bYipm0kSiiMJejlNNZpY2tHR0eHhISbVarWFhQVkWxoDgdVJjUEIoZQyHaRnPgNoWUHql9nphVXL6un3+3t7ezjfFgqFpaUlNhZy2JDZPrIo6O12e3t7G2Vbr9c3NzcLhYKY5RtMVcDsxET+pAFvKEnB5Ga+QdJUEK3WZJL1aDweY/HpdNput1E4SqlGo1EsFjG/67p0HDH+Dw4OHj58CFZHTV0p1Wq1yuUy5qzVapVKBUltxERgNbPZTCnFRhktnj+OmOXTelhBlY2OxqC1NlnKMULWFgNKgFUrDF/9HJuxOFM4KNszc6psLD22D3Ecx/M8nLIgldbJjIGC6Ywmlh8AACAASURBVPe0bBYvE2yUMVIpRbWvT0LAauPfXSzgWZIkuCUTQgRBMBgMsPLRaBRFEa5rDnH3FUJIKT3PY0aYYy04h9A38JBf8FvEMxwVLHJA5xS2hEiy72dTjyDLoTD2ScyekiTp9/to3NPp9MGDB7u7u5ghDEMaasVxnEajgaQQImfHRtHv9/f395EcDAa9Xg/JKIrolsXzvE6ng2zXarX5+Xk89EKPsPvQ6PnnXyxucsuEk5JgWudBmqZYfCZLtDmaWRiTUQ7oJkwYk5ow+m42ioyBKDBVzDKzmVzp7KF3NBptb2/fvn0byDRNP/300wcPHmB+NuWVy+V6vY5kmt2Cj8fjn//855iBSdJkCTsojVC3tCyT/5kwa6On0yRJoihCEmZ5ZCxN0+l0Sg8knudBKtSD71m1URR1u138PGRaBT18zgS1DdMS6ButdRRFkJ8lgdzwDSgI26UFIbOT3UjBFyUkGZi66Vg2AfKB/MfHxzs7O5iUJMnc3Bw2BF04rV2ttc6Obsbzs+K0hqRhnxSTyWRvbw8No1qttlotNoXi80zQDEmS0H1Ju91++PAhblzG4/Hq6ipsZxlXTBT5jYLo6Bsm5/ziIrtCsdooyZJYK+ZYoEjTNIoitKvxeHx4eIgfj1zX9X2fLmSu61JSZwXS6/W2trboG4BSChrCN2EY0kOvMDorDPmcJi6t9XQ6pftOx3Ho0MiRgKkRlpNyZcLkmcJk2HxDATWASLE2YCm/oMVMmEKjlqlPP5QCmDEwK1JKUTNzjEOFNHYyCDZaSYrFtwY28E1tsjegeq31eDymM1u/36exSNM0pROd53nT6RTbmk6nuEyLWY1+jX8gsTfixBS/m5Y2e162sLCwsLCwsLCwsLCwsHgNYA+9FhYWFhYWFhYWFhYWFq8t7KHXwsLCwsLCwsLCwsLC4rXFM9zetsgBu7zOPCu01viGOVec5vkjhIiiqNfr4eX7fr9/584d9CHUWvf7fersNJ1OqdvYw4cPKbm6unr9+nXKJz6naUrv5T99+vThw4dIUsdFIUS5XG61Wlh2NBrdv38fvZvm5uZWV1fRK2AymWitkck0TVU2tEaSJNPpFEmtNQ0tA/6lUBtjUkpJ+87E2Ov1jo6OsKHE8OpEv00hhOu6zWYTosgAWJCS6XRKPSiGwyE6OVPNuq47Pz9PQ6eAEw6S0+mUdnY0GlFPDJbZdd0wDPGNUoqS2oihJYwYNpCqtaZm5rouddPVWl+4cIHGiblx48abb76JpJeNxhTH8Wg0wnYXFxeXlpbQhTtJksPDQzQGpVS9XqcxaXq93nA4FCeee9QaqcDTNB0Oh9RlLsmGiQ7DkNpJsVikYp9MJjTWGpAoHMdxmGDL5TItjnY1Go3a7TYyppTyfR8lGUURdYBxXbdWqzWbTSABNM7caDQaDAZIMnXPnAqwC2maohtPs9lcWFjAPCob+2Q0Gu3v71MzS4m3nlKqWq1ShZbLZeqnenx8zILYjUYjJMEmkU8mEK31ZDIBOd++ffvjjz/GgtevX19aWqJ8Um0mSTIajVBB2gi+Va1WqRUVCgXKMwNMFFi/lBKd32i1wnCKm0wmVEEPHz787//+b3wDoUFQv67rzs3NUa6EMe3Tyo+Pj+mkevfu3d/85jeopkuXLs3NzUETLPxSPmaaDQNlQ+d6CDP+cQIBEtqCImZPaVWs2iiK6KTR6/UePHiAa9NwOLx3797x8TGQYRj+5Cc/2djYAFIIoZSiFntwcLC3t4fk7u7u06dPoVOMh8lkQgumaUpJmIKQxK4BkiSBxQvIOI57vR6uAiDGHElS30shRJIkYN4wS2C70ggsd3h4SAcgq8dxHM/zsC3f98vlMs3AjIF1ipHihG1T0fjX4llB5caGCbyhL00hs+LUxszaGGjl8gSY9Od8s9q1ePmQ2dk7zY2ggSqLouj27ds0ms/Ozg6NwnPz5s3Hjx8jCaFnsaHLly/T6AalUmljYwMXMimlZ4TWy7eW0xag/FLfIuyh94WDzkRsylNKnWYxQog4jrvdLm6MOp3Ol19+ieu9MqJcjsdjukOdTCYHBwdIKqWuXbuGzVGLZIOt0+k8evQIyXa7/fTpUyTX1tZWVlZwVPR6ve3tbTjJCCGGw+HR0RFyBUdNeuhlIyFJEnqepJnFSWRLx3F0NhqTEMJ1XToyGQaDwfb2Nooadl1Y3Pf9er2OOw/f9yuVCj30JtngeOPxmH4+ODg4gDlFZ+N/BEEQBAGL30uZnE6nNCRYp9OhuzfHceg5MAzDubk5GqoxCAJMNScU3FchqKVhfsdxSqVSrVbDPKurq3ST/Td/8zd/93d/h6TI1gMTKJVkuVzGwwycErvdLpCu6xYKBVp5v9+HoL5BEJTLZWr8tJUoig4PD6kx08g3wgjEKoSgrUyn006ng0yORqPDw0M0Myd76PV9f3Nzk8YbR8AIQksAs8HOskOv53kQ6whIIcTTp09xKy+EaLfbNKCx7/vU5MCWkBTZrwBJkvT7fQiqtLGxgeoTJzaG+h2Px3t7ezgeRdZUHMeJ45hOGp7nUYvtdrs0ANVwOERtCkNrruuWSiWUQJqmECRDCLG1tXXz5k0s6HneD37wAzTmNE3pR6jpdNput3Gi08ahd2lpicbkk1LmHHqhOFZOtw5somN7jslk0ul0sOCjR48+/fRT1ODi4mKj0cDxG4ZhqVSikqQGLIwR2u/3MWS6EOL27du///3vcVbpdrtvv/12HMdSSjZk8iGNyPMMjCs6X80ES2VzCLW08yOKon6/jwrd39//4osvUJL9fv/zzz/Hz0OlUmllZYUGz2Mj/ejo6M6dO0i22238vimlpOzR755CiGazubi4iGSpVKIDkCFJkvF4jNYyHo+fPHlChxXbC06zca38bCyuKIrAvMFuUb8gUvox6OjoiNqJR6L1CiGCICiVStgudAFJmQ0eA+ZNJZCzf6WiY2K0+CYApSBpjr58UeeXzYHWGtX9TAUtXhrYQDO3cHRux6Edx/G9e/f++Mc/YtLt27fpF9WdnR36exxHR0d0P390dDQ/P49biGazWS6XcXJWShUKBTp35e+0RdaAX4mp49QTl4WFhYWFhYWFhYWFhYXFqw576LWwsLCwsLCwsLCwsLB4bWEPvRYWFhYWFhYWFhYWFhavLaxP73OAeYudeeqaGQCnvQfEcdzv99HvC1xA0X+9UChcu3bt0qVLmP/o6Ii6jD5+/Jh6By0uLg4GA2QMPEjhmToCCSEKhQJ1GoTYRUhSFyNx4jhEXYW11uhDwpxJtNZJNnJVu92m/gYsv+d51OOXSpWJLo5j6lK1u7v78ccfo4PEcDikAZZKpdLa2hr645VKpTAMqRuDUoqSX3zxxe3bt5Hc3d29f/++EEJKScOKlEol6nYrTvwlkBwOh9TLemtr63/+53+QjOOYhk5ZWFj46U9/iq6M4O5LXU+Zr4XMevdRFVAXxzRNJ5MJOqdprYfDIdXv/v4+9A7AnABVNmwSuIKgXkajUafTQTdIsDHqFPr48WPway2Xy/Pz88hwv9+/f/8+cpUkyWg0Qn1JKQuFAjW8J0+eUDYWFhbW1taQPD4+3t3dRTcV8OhGY2CW43neYDCgBo+xnR4/fvzZZ5+huZbL5dXVVfQmnU6nBwcHKDrP8yqVCq383r171D/26OiIar/RaCwvL2P+4XD49OlT7DK4y1Jn1OPjY/DpHQwG1LcQglJgPe12+86dO5gB9IUKUkrt7u5S0V26dGlpaQnJTz/9lNqkysbSCMOwXq/jG2Zarus2m02QD2NyMBh0u13U4GQyOT4+Ro2ATy/0ThhTihDC8zxqhK7rsohEdLSCKFAgVCMq6+IIYwHJfr9/cHCAGfr9Pm1Ia723t4fqLpfLFy5cYPMVhc5OqgxxHA8GA6xtOBxGUQTaN91uaT0gcyTZpAGiw/zwntbGnHLZHMJ41lrTsrRppqA0TXG4mYDxi1WVy+VWq4WChbgAuMwVCoVisUidpR3HoWwcHh7S2bhUKq2vr0spZTYoVJIku7u7NCjUeDymc5HrutRbmHV2OBxub2+jeQyHw4cPH2LcQaVUuVymC+iTJ09o1LparcbWUJhGgiDodrvYO8dxWq0WndW3trYePHiAZBiG1H29Xq8vLi6ijpRSdH2U2fWI4bT34sRsqBXlZP6/AOj+ixaIWafORnZIsrFFwOeTDv8kSXAYMgO2+A6CKYgZgMpurugEK0hmpVS1Wp2fn8ek4+Njaiej0YhG4SkWi/V6HYvPz883Go1qtQpkrVYrl8s4BUkpfRKcEmYG01AROUnfWdhD7/MB1X2OHbCJKSenECKKouPjYwwfenBwsLOzg+fYer2+trb2s5/9DPPv7u4eHR0heXBw8OWXXyK5vLxMY7jBgg2k4zh0gJXL5bm5OSSTJKH7V3auE9kIk1APTtzmRAy7NCQPDg7u3buHpJeNFex53ng81lpLI6Yc4yGKIsrk/fv3//3f/x0ngna7vbW1haeXer1+48YN6sq/vLyMs4CUslwuUzZu3779L//yL0h+9dVXn3/+uTjZNuGGu16vz8/P4x5FSgmBf7Bgt9ulJ/ybN2/+0z/9E8qn1+vt7e0hz9evXw/D8OLFi0BCxFrstZSyWCxSgbApEpGmKT2ZgDZp9Ol+v0+DSO/s7NAYCWyVrdVqq6ur2O50Oh2Px8jVYDA4ODjAjaZSqt/vU0lCqFUhRLPZTJIEd43b29v/+q//itEXQN3YI6XU6uoqDWU0Ho+pFa2trV0iX38gEhuNzUD3+iABlLPjOA8ePKD7ztXVVQjS++WXX/7Hf/wHnkxardaNGzdwoxxF0dHREW7Wfd8vFot07fn444+pJA8PD2mIxY2Nje9973vYx4ODg88//xzbKhQKKysrGGgnSZJ2uw1t7ezs0KgVMFqxnqOjoy+//BLHguM4NNaU1jqOY6rQXq9HQxZ/+OGHv/rVr5BsNBr0SFwqlebn57G28Xh8cHCAiiiVSu+99x7ECjo+PqZGdXx83G63caTAQMDxOJ1Oj46OsB6lVLFYRNuAdZdu7l3XpScBFnhDGJMDQmY/DE2nU2pFnU7n8ePHOFI6nY7neagCrfX29jb2vdFovPXWW3SHyho9jQcAzO2opm63Ox6Pp9OplJKOVgCriqpvPB53Oh18o5Rixx46A0spmazYzM/AjrKUZJ8+k+zuXGR5VkrR8RXH8eLiIo4j+MaK46hUKpXLZXoc9TyPsgEfNJF89913f/KTn8AaVC6XsXdRFI3HY7ogDgYDei6lJgSgrXS73bt379JoW3fu3MHPea7rLi0tIZNa6z/84Q9bW1tACiFWV1dXV1eRRPl4njc3N4dNu6574cIFOrP98Y9/pPUUs3HpYU5AlUkp6ScPJxsTCzJQMgdSyvNn/j+Cby4QmQ0tZoIlaeOTFh1WMHXTDOZcwYD152ezeGnImdthEiOJs6GUajabdHqZTqd0Qh4MBjSQVb1ep5/XV1ZW5ufnce6q1+v1ep1+oXvtceqCZ2FhYWFhYWFhYWFhYWHxqsMeei0sLCwsLCwsLCwsLCxeW9hDr4WFhYWFhYWFhYWFhcVrC+vT+xxwpr8EvbhPn6nDlQmWKqUE70Qg4YG6Ibmuix5okETjWk0mE1YcHbqYP4/rutRDIE1T6vWntY6iCPNDiCCsFoLKoBunUkplg8cw7y+IOYRkoVCg3l+NRkOdOPerrD+9zoZ8kFJS39HFxcXvf//76P0yGAw2NzfRLRBin2A0kUqlQgOrgDSo58zKysr777+PJPprOY4TBAF6WFUqlYsXL7ZaLSCllMxtrFQqLSwsIHn16tVf/OIXSI7H416vh51aXV3d2NjAcAVBEFBHRwBl0vQVobpG0TGz0VpPp1MayGoymdBIY0xf3W43TVOsDWI7UXU3Gg1sN0mSx48f0+Ax6ORcq9Xm5+ex4GAwoL6Ivu8vLS2hM5vjOJcuXaKiu3//PvWO7na7X331FSX39/dRIIVCgXqiSild18VUKWW73UZvPSFEo9EAn/YwDBuNBo6pubm55eVldIZhgvI8z3XdnHHUbDbp8Lx06dIbb7yBxlMqlQ4ODtDJs1KpXL58Gf3Moyja29sDL1kpJRVpHMcwyoDs9XpxHFNjoGwkSdLr9aj3exRFWFYYboFzc3M3btzAToFPL+q30+lMJhNkplAo1Ot1EN3CwgI49wIWFhZarRb6WzqOg3G5hBC+7ydJgsNTKVWtVul4pIE3xEnEOCRNP0baIyklm0XxOU1TatvUsIUQlUrlypUrmCGKol6vh0xOp1PmEgwGgCRDEATUdbPRaLRaLbSHZrNZrVbBtHzfp2ywVWA6nVL1dTqd7e1tKjo6jsDUkYThSWNE1et16uJL2xVCRFFEHbOjKBqNRjB1sNk4TVM6F8HigiR47aJSfN+v1+vIhlKqXC7jUlUoFJxs5Ko0TelUzwQSx/F4PHYcx/d98KuH91EU+SSulRAiTVM2s+EzgPYIKkQzS5Kk2WziOPJ9//LlyzjVa62Pjo7oKrm5uXn16lUkIfYBPKckUJlSio04iPKFZLVapZbfaDSofsHksDhTijBkZQJTWTazqv/j0EaMN5KYh5z5x4TKhjJys3HmYFjhG5j26VzHGspvy+JbAbMitoll2qSp8Ab+1ut1+t51XRqF5+DggNZTrVbX19fxzerq6vz8PG6zy+UyW7ZM2863K5YfSTPndwSnLtIWzwS6gjJln/YsjL0CA0uSUtIFEh5oHhroCJJotFg4V+CM6XkeLp+MK7p1EEIkSQIRdwFwRkLLLhaLc3NzyJXnecViEUfUZDKhO5g0TSG+CJBCiN3d3T/96U9I1mo1OnqbzaZ7smVnTLJ4PI7j0H3wm2++WalU6Gik04dSyicR6jzPW1hYoF2OT4JtAm7cuHGJxEnq9/twRtLZ6LW+71+6dIluWeiKJYRggToXFxfffvttJNmC53leuVzGGlzXrVQq2Edomm7ZkyShffROAkFJKdk6qrXGglrrwWBAj3zsUERPI0KIdrvd7/exyxcuXKCbv8lkkpCwZ/1+/9e//vXNmzeBFEL88pe//N73vieEWFlZuXLlCn4UiOMYNrtAFovFGzduYEBmx3G+973vXbhwAUghxK9+9SsaqmFvb48GdB2NRnA4B3JpaYkGGIvjOI5jNKc4jnd2dvDkJqVcW1sDiVUqlbW1NbSEpaWlN998E48uvV6PWrLneWyTHQQBVffCwgKNSXP16tUPPvgA89+9e5eevefn53/2s5/hJ4/pdLq1tQVReb766iva2UKh0O/3sTtRFIEWgHRdNwgCPFxNp9Pj42MaT2s0GlHz8H2ffqm5fPny3//93+NIKZVKdLA/ePDg6dOnKGcIcgYj5ejoiLbyxhtvXLx4Ec9Xh4eHg8EApRfHcblcRpt0XbfVauF4lFLW63X2LYxKks0MzOBh6wBMsj0iOwVRqxBCLCwsXL9+HRW0v7//4Ycfop0EQUAjwEkpaRQlE2BLSO7u7l68eBE/Nq2vry8uLs7Pz0spaaQikT0jCSH6/T79Srizs3Pz5k2UpMoeeh3HKZVKyJXruuvr6xCkjWZAUmSFORqNDg4OUL8Qpi6OY5hA2IaMFgyCgFrR4uJitVrFThWLxQsXLmDxcrk8Pz9PQ7i5rkvn9iRJGEmbnk6nvV7PcZxisQiLEbyfTCbFYpFaQpIk9OsendaEEDK743Rdl64I8CUCv3EUi8Wf/vSn6+vrQGqtx+MxZfKDDz746U9/iuRwOATLGQwGMNLhPaxueJYWQiwsLFCy2WzSMK0O+c0FIUQQBEEQ4BspJdUCtXwAW48gAzxQ5qWU0N8/Z7XIbu7pcz6YUvKl6mZD9FHlCiF833ddF03acRyHBKIzWcK2tNZmqsXLB9M+28S65HcWhPFNFkerEGJtbY1uh9588006mz158uTf/u3fkFxYWHj//fdx7C8vL29ubuKWAPYtmFkY1sJIJxv/n3IFAFJmY0Z+p2APvc8B+ROKzg3f90xgE6gJOmaE8Z9As/jM2lg2ZtZxHI/HY+yy67q0g1AWScaPMIZQHMd0uEYnv9sBAP5nMikMsdNsnueVSiXMwHokpaRDFxYSxiqtnO0A8FlnN3+e5wVBQLdZjHPYkiIZhiENUgobGio6tn+lPEsjyisTLMVM5gFQiuqX1cPIOI6n0ynmh3MCik4pxVblKBtVOzm5FADZ6Hacyl8p5ZN/s7iuWygU6B6UnS6SJKH/c4P/wiHbYFFUdADMn5Cf0QLBQqo0PjP5vo9Nw2cFZJsJFt7Ql272h3bgYIALA1gOtuV5XhiGuDKBQGBxUkrRcR3HMT2tMasQWTaklGn2Q5vOzk4mz/QMVigU4EwCJPBPK0dxUeUCSXvnui7droFt08ye52FxKSXk///svemXHMdxwBmZWVdfMz33AANA4AURpCzJtiQ/y2s/r73+aL/nv3c/7e7zIVmyaBEmKVomQYHEMffVVx2Z+yF6oqMiu2tmAJAigfw9YthReVTeR1VGFHnQL+811KIuAwDGmCzLKM1pmir20gb7BXWES9ODuSBRFAiWAOZRDEQCUX34DJFveqn1AgBWB6W5qqqiKHhwsV4ROOcqtsPE4Dhci3hEs8GWQCL3CReulM0oing/as6+D1UEtmQej0gVep772wfDUnCttTGG933+LMlam6Ypb/BpmvLxyjmHI0xZlrz14g+eSO09+uTR+i1f5FG4CrCIuMgcZ2JzJIGvD782r17dqv5KOfCdoLnKxHiFoqovSwCAD03grY6MMWma0oAc14+HmPom9gWhBGNqX2LML5HrTTCBQCAQCAQCgUAgEAh8hwib3kAgEAgEAoFAIBAIvLKE480vAf8UCl6k34sODqm6HpEAXbkHfhi4KAr//AA/rmaM4fohxpiiKMhDw33Pzs6ePXtGYhRFb7/9NolFUfCzo3jQgpKRJMloNCLVRDwOxw9pRHWtlc3NTR65OPGLv0lJgGdWFJ1WtewYY1qt1qzYAcOTuzJG42X0rLUCmCVSKfQwxdmackKWZpgkhzq99qIoIhNHdaU+RzcBuDgjR2Icx+3W7AicNpqXpPKM0ED9uIvfeET50G9xejlilo2stVmW8ZN4Kysr29vbJFZ1zeHJZLK8vEwRbm5u8mM2zrnxeEznmcfjcZqm3OhCVVWoz7a0tMRPTuKhTToGiYcVKRR4qsVV/RCvqh+nNMYYpkmeJEm326V2Za1ttVp067IsHbMMoZRaXV3Fc8hJkvAOaOq2bfBMKaXZ71DWWpFm5ihxF5AIrBKVUo4p4PG8a63jC/1tmDZmTblrtVqrq6ukt1kUBTc8BgD9fp+r9CileHVba3kJYJPjqUK4iL9dXUsQK5SSbYxpt9tUZdgIKc0YD9e23d/fp5gBQGstGhUvZ2NMzPQCEBTFRW6FCy5UiymRnU6HK4W2Wi1+uF1rfXx8TIrlWAt03nUuvBuWZTmZTOhMPg2SIoV4RTQtHo/WutPpUCJVXXFDa83TjA2YVzf3DF7TKsuSLFcBwPn5+eHhIaY5z3PeTkSyW3V7hO12ezwei/qlTGED4zFYT5mNfoM3g1DurLWkOgsAeZ5z5XYA0Frzlh+xg98+VVWNRiOyTWWtVUrRvXBk5sFF0QncRXcQHQE8zf/JZMLrFw/Vk8gzCACTyYSbwMAU8tYiGg+WPInAylZ4o9+BuXxNReQ8VSPmCABgreX9qO64EFHvouleOZpvnhdLmSy8GU4BLHZX4GD6n6QxHAAocE2KrKI+FXhjO7DaB6c0KwEH6mKVa8GVjk2v4CyLp1KmgtlCtLQKFzkoOudwgYSimAIQ/0oDcz37Q823h7DpfTmICuZVjq3NH78AQDVqe+PJe76gGY/HZOUyiiJrLQ9OMyuSJAm3FxrH8WAwoD7mnOt0OqLLIY8ePfqP//gPEt9///1//ud/JjGO44xZzNrb2/voo4/IQEiWZbu7u5RI59xkMuH9rdPpcEsqf/7nf84jx5UKiRsbG865PM8V6vVptrHRhosAtbGolbVq+08F3Pki7Rf/U2CM4R6iSDs3K5koinnk7VZ7eXkZf9cnDxVFkRIjNQtotNExi9ZEnRazIqNqrUiBAkVpnCLWu6L26TewFmitFdvLLMvIIqhzbn19ncfz7rvv/uxnPyMRV2kk4mKdrmRZxldsZVkeHh6ivSUAyPO83++/88475CHPczTCFEXRZDKhNSg+zaGtC6oN82YzmUy4cVSuVwzectY5l2UZBe/1ejdv3qS+oLVuMaNZ1trz83O+xbpx4wbuqc7Pz+M4phuladrr9Wi7hRtvCuics3Xzv3me8zR3Op1a/dZHDAzOt/24GUBRKWUvdgKlZ8Kt1+tRdnBIocg7nc69e/eouVZVdePGDW6S98033yRXADDGcGM/VVWZRvVL7qqZFmVVVdzKFz5u4yW5vb1NGxuR5qIouNFv59yjR4+4Lb2/+7u/+973vkfiaDQiy0AA0G63V1dXKTblbRqJ4+NjbvQb2wkFRKtINPwWRbG0tEQPdIwxv//978mEeBRFaZrykU0gduaj0ej4+JibfBONh+AFDgBKKR5PkiTb29v8ihiR+C4oiiL+9Ae8PRWvIwAYDof7+/vU2HZ3dz/66KPhcOicG4/HvMsIut0un3rKsrxz5w7tVJMkWVpaooKN41i0oqJu7LDb7fJEtlotHjl2K6VUWZbPnj3jz1uPj495PHEc82cl/DkLeO1kMpns7u5SbBiWnhfgAMIHKARFukIi1T52BHJSSvX7ff6QkQ/O4NX+s2fPfvWrX1Gy33rrrfX1dfIfx3Gv1yP/c1u+aGOYEl1XJEY/oiHR79eEP0qWaZAnkSfDOYcTJYn+0z0Or0HRErgTACyOA6l59mh2babhxqrR9Qq3XezBAVSL41bgFOTA9p+EBqea4o3AKWBLR4Gz4FisWhu+Au1xiAAAIABJREFU9LK6qhyzrqdBs02vA6WccgAArnClrdjYpROlZ/230OlEzV5jTCozGo3pLU5ZlriGR1F7ZgJ4U3HeezVfFE2UO9HvbxVh0/vyEe1AKcUnV0FDy8B4yINSqqoqWoLgmlsEF8McPZlGEYOg2JCk8XjMzfkaY/jXR7Is46sQY8wXX3xBsRlj+Htg8IZXU9e5X1pa4pEPh0P+mSV8czKNoT7UNJQbAGit+QsNAAc4XFyNegUCuNr4y8epa8FrE3BwaYxpOsRdwFdL4I1WDQXinKOAzjm+xHHOxewTUwDQ6XT4LoiHhYvVG10xpj5qW1sUBX9/Fccxf41cFAXuA/HND08VX3CLm6Ir3+mJooD6SK211uxDWbghoVEel/7UCJ1zaZrypQa9OsOdGBWsUiqKIio6/EFp9pPkp5k5zkHkGlid4g90Fd4wVVQL2PIpYKvV4vucqqryPBfVLda7PJ3WWtFoRYHQX/4DLqqMRJF3TCTdF0cqqsHJZKLYC2fn3NnZ2cHBAYoAwLflAGDrRpiTJBHFSPAUwsWbTBI7nQ5/nJdlGU8k/qZyVkoNh0Nq6nEcN2wCEZ4qay1fv/LmJxBphno8WJKUKmwb5EHVnyYYY3gDhnqvQXjk2FqoDU8mk/Pz88Fg4JwbjUY8v6LAnXN8kB8Oh0VRUCIxSXRrHMcaGo+IHFsLiTzvfOrB4uXx8HEPRfrtg7HxJ7BYmPgb00xOIoU+lCNeO0hUt2+XZRlvDKIo8jw/OjqiGtnY2CiY6Uc+6CF+41mEXwXMMfAN4TcPDrqShwafPg2V6xxcoZk036vZdRHqeQNegcsibnR3AFbN2/S65k0v2CZHB84BL/v6aw4AAMfCe64Kl/sOwFauYrtnDU7z+gVt2cqycsraitydc1prGv1Exxc0OM3luv7/KDSN+4FAIBAIBAKBQCAQCHynCZveQCAQCAQCgUAgEAi8soTjzS8f5506Vs/1CTWlVMQ+d5kkSbvdJhXKVqs1mUy4Mtv5+Tn/Jqq1lp8sRUMsdKrBOXd+fo7HtKL6V1KVUtwii7WWG89AdUrK4GAwyPOczunhYQkemzj26byja8JViPQ7IPCb2dWhgsUC56dwz87Odnd3SRRYa/nx5iRJuELpZDLJ85zOPVZVhR5QBAB+InQymdDh0jzP+alFpdRgMCDdYGPM3t4e/kaGwyFvY+12m9u2wROY1MziOB6Px6Req7Uuy5KfyhbFSEoEWMJ0Izw9yItOM7Vqfo4U4a4ocg/YU+iK1pp3dmOMZaejuS5DXDeYlKapMYYf8uRnMrXWx8fHVBTW2sFgwBUdhXKmqvf9uo4AgNdDY/Zp+yiKqC3xPg4ARVGcnZ1R7vCUu/BD5Hl+cnJCiscYJz+Yaq3leTw/P+fDoHNuaWmJn0SlkucpR5FfwdO8VCPGmPF4TPflR2cRXn34g+eIu9IV+o3VTZFrrasLi3GLigVRdTMQmDsKopTimVKe4TGoF4K1VtyOJzKO416vx483b21tjUYj5xwf8xEebafT4YqpKysrCbOnhbkm/87rR3N7ComtVour5kZRdHp6isVSVRXdBctTs1EiYgb84DItFa0114mIG5UnlVJR3bxWxGwQogf6LcQ8z/msfXp6ymdbPggAwHg8TpKEj2yicMBr5Bw/GXilIWuBQODlgOZe6l1NdlbuurhTKqj1emlHRliH8e/6ehM2vS8HPtP4U4h/hfAXUvQ7juPl5WWaSq21b775JjcH8tVXX/3rv/4r+Rd6VuPx+N69eyTeuXNnY2ODFgFHR0cff/wxbjbW1ta4OaI0TbmdmKIoPvjgA+7KdXpPTk729vZoDdrpdNbX1ymRuDzii7CqbtCF75HAM9JjPT3J14qpLSsAAHDztrgNjWcRrq4f65zjm08A+PDDD7mhI1PXwXb1HfLy8vJbb71Fz1bOz893d3dps6q13t7efuONN8j/V199hRaJtNZfffUVtZO9vb2U2XnWWn/88ceffvopiR999BHfPI/HY77EvHHjxp07d0jc29v77LPPKJ1pmj569OjJkycoWmtzpqmYJMndu3fJBJFiNlpRJxl/w8VGlFqvtRb121HEPQyvEbHhz7KML8FxoU8r7yzLVlZWSOx2u0VRUEXkeW6txeD9fp8XaavV6vV6VPWDweDp06fUp6Io2t/fp7W+qisA4xW+7YmiiPf9tbU1sQPhta+1Xl5epnu12+2qqlAnf8KsnQHA4eHhgwcP6L5FUXCzwHmeHx0d0RhirT07O+PDQhzHfBOV5/njx49J/Oyzzz788EMSb926BQCkJ5kws0mivxRFwbMzGAyePXtGmU3TdDAYUJr39/d5ppRSvGtEUYR7ZhTxCt4UEf0oy7Jer0ce8F5oSaHT6VCjQnj5R1HEn0pgE60vcWq/efUZY5xzfPgtioKLfPMJAOvr6y1mA388Hr/33ntYYqJVgDcDctder7e5uUmNXynlnOM622ma0hiSpimqT6MIXkneuXPnr/7qr0h89OjRr3/9a2ttFEW9Xo+aOg50XF12eXl5Y2ODxGSx7jdc2FqjisAcUabwB8/jysrKzs4Oif1+n6dZdHwuPnv2jDebP/zhD/zTCWJ+VEptbGzQfVdXVxOm0a21FptknkLwao1EnjVEiIFA4MVRurb7rKqaXSsVKc0+GgJQ2806mGr8OnBaa81O6br6iV2txNN2w7fBoWuHTe9LwDknpk/nbVFQ9GdZsVZgLqA9mzTLy8u0PzHGDAYDvvibTCZ8BVNVFX8ivrS01Gq1aLo9Ojo6PDwcjUa4GhNzIV+sV1XF37OlaTocDsn/YDAYjUZ0X4yKuhyWA4/ced8y4Wtu670Wpt+vI6w5qHmHBRoaTwO8ueIiiZtO2d/f59HGdTNXrv6ifjQabWxs0BU8a0BNNIoiYaz79PQUN3JKKW4zGdsh3aiqqsPDQ3JVSg0GA35sYWlpiT+mWV5evn37NolRFB0fH1OmcBNFmSrL8vz8nFpslmXcAiqwnYC11hhDucM1JYnOObHt4WtZ8PY5pv4qGPsFXcHs8zdLlm2wC/Z9MtzF4XX0KfovrwKtNZYtid1ul1co9l8SRd/PsownEgAsO+WhlErTlPZgaZq6iz0V7+MAMJlMDg4OqHzQghSV5Gg0evLkCSUDIyFXpdTa2hrf6VVVRe/tAeDo6IgPg7iBpARYa9vtNt6at3x0orvAxVacRHxPSGnGOCm4q5sD0Vq7+sjGlx0Ibx5RFKVpSv6NMUVRTCYTpRS/C3j9WtetMRljeDKmTao+mJOI3niWq6riaeZRAUCr1RLFvra2hmkT+1KeYAAoy5IPKcYYPpFZa8uybOhHmCkUwUtVr9e7ceMGic+ePdvd3a2qyhgzHA75851ut8sfjSVJwrOj5IdbauUcRREfcLAz8qIT/tM05Y8q0jTlaeaeeQU550ajEfe5v79P38ECgPF4zM9l9Pv9GzduUHB8jkYi5kjUBcfVlyU8JYFA4OtG9jYH/JyNBqhvin2mfVt8odPWzbQqVZtrlFLyVfDrTa3sAoFAIBAIBAKBQCAQeJUIm95AIBAIBAKBQCAQCLyyhOPN3yh4AIlEcRLJP32kmZJVFEUxMxuD55oazjLp+rdqxXE7x76MKiIRxzL5UTTEsiOOrn7MD0+m0b24T/COhPkXxYErFKdXFEDTR9C+TtQf485ziuoSGk7rkai15ieWnXOtVosfFW61Wvz4K56eJRHqMadpys8iRlGUJAkdKcQWy4PTaVgMSO0EY+Dp50d2lVIike12mx8+TNOUH7aM4zhjn7u01mr2BUvUGyf/aZqmacoTGccxumL6KRlxHPPDhFiS1MWiC1AEAF4UAJBlGS9Y7hO82OI45uWDBYuuWZYJfdc0TSlVWZbxM5xaa37SUmudZRkfFhJmYQgAUqZdia4iy7z2tdZJklCmEvYlW5H3NE0xKgqI4w+Kzrksy/ggE0URiVj7PFMJ02OEi8bDmQ0a84YU+q3nHRUmDyhS5DgqUtFhfVHRYX3xyAWqboAqrn+/utVqUavzs8MR8WDDWFQamHdKFaZZeG5Is88iz8o7Ksx9+qGEK3Y0FDGFIhf0GwB0XfE4SZJ2u22tNcZgMeJ1pVSWZbwRRo3GpQQiVdga6Si4iAq8SVM0BmMMVi72Vuoyxhjq10jKdBzAK0nsvHQljmPeRIXnF0EsCV5WtIEAw8Elq5wXWHWpS0M3ODsF6rK0LUC5mp5uM96neGvUP+rrAP0DJqwWzFnHvyrsKoCZdomCmqpRIGx6v2l4K6dtJyKWO3Ecr6yskIc0Td977z1SZ7LWHhwccN02qEe+tbXF7XbcunWLL3HKsjw5OUFLLWtra1yza3Nzk+th7u7uPrkwAgQAZVly85IAwJUA0WYJ6RKXZbm/v0+JxLuI5RFfd0ZRxEVcVuJiQmvrVEPvXTx2AFzmCnDpGNfo+DXB7+kuYNcuaUvUnCJmYKnT6fBWBADCnC/tW5CqrvHbbrdXV1cp5jiOO50O+V9eXu52u7Ql01r3+32+uEfrr3CxCqT0j0ajqqrIimmapm+++Sa1qyiKvv/9729vb6MIAK1Wiy8Ne70eV1/f2Ni4ceMGlUZZluPxmERrbcEsGMVxvLOzs7y8jCIA0B54dXW13++Tz16v1+12qX12Op133nmHStIYs7KywjNrjEGjSki73eZaf8vLy7y/Ly0t3b9/n4ouy7LNzU3KY1VVZDKqqpuCM8bw+jo/P3/zzTfJKJTWutVqcQ9ilr158ybv7MJK1o0bN9bW1kjElT3FsLS09N5773EVbjR9hCIv0m63izaxUFR1A0vD4fDRo0dU+zgmUJqVUuvr63yQ6Xa7vJy73S7PYBRF/lacao1nf21t7e7duyTq+m4qiqKM2R6L4/jdd9/lytJ8i6W1Xl9f57sXzZ6zAICohffee++f/umfqB7X19fv3buHzaPFbEeBt/1otVo3b94kEZu6GFHptxCVUlmWUZqBPd9BNDMEDSA3UZrZV+fVByAf1xpv1yqSwYui0+m88cYb1AijKNrZ2eHdmfd0AOj1ejwLURT1+3178XSVbqSU6nQ6/DHTzs4Ozyx4ZcVpt9t3796lCrJ163dRFPFncACwubnJY+OdFwD6/T62jbIs19bWePcUidzY2EBTf0hVVXxqTuuaw/1+Hy1jo4gNmCfDNlqCpAlFVJBzjj/pVt73HQKvHAs7wguzsPkB2mZaiAK+kfNpTrJr9KAqDbMHxwIFWtlEQe1Z/xQ3/bcAC3pYV7CtU1ke2hhdt1wVq3J202LiJiNmJCLRSctMu2k9a2V5lJdnJFb5H1T5kETlVlTdkBXv7w1j4KtK2PT+keGLDADgqwFjjFhDc3uSeZ6fnp4Ke6E8+NLSkrAnSb8BoKqq0Wg0HA6jKCrLkk+NvV6PT9iTyYTbk0SDK+Qftz00I3Y6nV6vRyvUoihOTk7IFddGYonGZ1Ox7jQXADgHFTQ9slJyJKjR7AqXuX5tvLzbik0vsOGMl3CSJNvb2ysrK3SFlj5IURR8TzUej/kXNfr9/q1bt2jtWFVVnuf8vsvLy3w8FYvs9fV1vFee5/yjNa1WC/eiKKZpurGxsbW1hWIURe+///7du3dRRA88Wj6IA8DS0tLq6iplqiiK4XBIa0fML7kaY1ZWVviLRFrhtdtt/gYSt1LUPtM03dzcpJJUSnU6Hb7twZhJFO+dxPI0y7IbN27wrfjS0hLl0TnX6/UwJSKzeIV+D4fDpaUlGhaMMa1Wi+rLOcc3/AAgjHi12+319XUSO52OWNxzWq3WjRs36JmIMabT6VCaeZFmWdbpdCidYj85HA7jOKZHY1rrdrtN8SilfEtj/EFMlmW8BIwxURRRlnEAwXuJout0OnxLLzqCMSZlr9CNMdvb29REtdYpO1+gteYPRMCLLWZviQEAH8pQRXS73a2tLdz8NG9Ukvor9BdEJBKvcJEXl2Kb1YYW6IsCUQtJkqytrdFMZ4zp9/u81YntVpqmfJeYJEm/38eM8H2pUqrdbnOfWZZR+pHmcuZjiLV2MplQ5Fj75Fkp1WVfNACAHjPNDeybas655eVlvp/Msoz7xOyQCPVEmvr75Far1W63eXBOQ+4QXvs88c65qqp4IkW5BV45mjrsZTQ3M9Xo4fmcrkBjhhQUCmYfvRMoFyvIlJvXrVxjulQOUMCidzMOACrgq18TKT64VQaqmWiLqpitvEBZ0InSWgGAWM+6clwVx0w8VPaAOQ9U8yvl14zw9C4QCAQCgUAgEAgEAq8sYdMbCAQCgUAgEAgEAoFXlrDpDQQCgUAgEAgEAoHAK8u8Y+uBa6LqiqnIXG0Zn0sVb4g4jjc2Nsg8TFmWcRyfnc3019M05WpjaOWCRKH51u/3f/zjH08mE2PM1tYWV5mL6xY+33jjDW6TJs9zYfeo1WpR9tM0XVtbI62zPM81M46CamxcpZCrFaEHrqWc5zkp0Rlj61/kfvVxAFwDRNdN44h2pT3TMljOqEFHTlproUUm4rHWch3doih4jaCWIyVD6Lah5hvXe+QNEsGwqP9J8XS73aWlJWqEqI5OVqCMMSsrK1yVsWJWr8BTBQcAofWXJAndy9XNtGAWeHAqkCiKeCLRDy+cpG76WKRBlLO5sOCKiGI3xmRMf9gYo5Ti9yJVT+WNNjyqNE3X19e5ZmPMTE9h3nkHFBWUMlPPAGCM4Z59sizjAx2VQKvV4uqy2rOTzNMcRdHa2hoZAlCeoqPQYhXBb968+bOf/YzEra2ttbU1yhf2CyxJ0Uf4wAXeUIzZIf9VVXU6HV6whplrwjTjb6QsS64bH0URL+pWq7W5uUl3xCGXlyT5dM7xhIlEChyziY00NJW5XOoBqaqKp0QMGqKpi1SpuhmzKIpWVlZE7Ytki+A8kXEco50LvAtPFa8g9EAWpNBVaMPysEqpOI7pinNOVFDE7PA557gWOgDwAQdBz0op7oRFwb31ej3eTvxIRNGJ4L5/XlYwzwMXCR5wkZ9AIHANFIA20swV74/OcYXhONbt2aocjFFKq5kqL/NpmXkIADB1Y0Bpkoju/Jr37rDpfQk0txtXt2zJETMQXlnk2RizvLxMQay17Xabz+JkLQPxJ3VOr9d7++23rbXKs3IpaLfbm5ubJOKml5IRRRFfKKu6pUetta5vesXyiP9GkZuoKcuyLEvsoUrDa2dMw1ugLGob4G2J6eECVgEf48RWjbv6iPHUXYCi1prvqcqyHI1GVIMiScAavKlbZGm32+12m6zX9Hq99fV1Mteste52u3wt6Fuc5k0dNxg8U7xfWGu58S2llHjKQxhjuDUmzDhvsTzv4I0DuNnmVxrQWovVMLDiwh/4V3kLZU7zTV19ww8AYogQwUXtQ33IwrY0t/EIa0MiHhEkiqKlpSVeI0n9MzwCbNIkrq2t3b9/n8Rer7e8vEzBnXNih0aIRL5cyrLkT4v8tsGfSCql1ILvz2Grk1cXY9nGD6OdW0FXoSGgGMbFkxTRoUTti+ozxnCLxD7iXmK8En2fI+pdmOhLkmRRQJjXy/h4JVDe55H8WqM0R97njjitVouPOddl0U3nioTvjTebRaECgcD10Ar46VrnfZWISSZSJmaToILajpeH8wZYPq/hKiV0Z2Lh4ikQCAQCgUAgEAgEAoHvOgufdAZehOYHrgR/AOOLAuGKr4b4lTiO+cNp5xx/ayqS5JzD41vKe6QtHtuLB/P4Go1iM8YYdghQJNI5VxQFvY4Wz+wBQM/7RpEQ8YpSTbbiAYA9B/NBp2YPDa7PTXOS68/rJIqdZQGovz3AQhZFzauYqlW8GPERr/JEdYvmUVVVyT5w5dc+b5Miqgba7fa9e/foWx3dbndzc5OfeDTG8MasGj/vzJMEAK5+7tE5x8sEf4hmSYiiE6/RuBPMqwKRjAZXqL8YR1fyIHwuSi3Mi5bf1Hn9XXj2ER64eGlYwr+pHy1d8aOt2AdUwDu2miQJf1WY1fU4oB45Lw104iJHNBvMQoN/7hlgegiCRD6swbwSEFVP13mrQFf6DV6jwt/cj8ivEH0aMsgR/Vq8vRQd8IpxLsKfNfwMYsMWReff1y+rBkTZ+rFx/HpZNIcKn36zEbnjeVfeZM2hoqArokAEDU7NvTXw+vEiDWBRWAdN6x94MVdo9GCUW3zGxxmx9Jqx4PIUpQEScItmZ+cA+AlmBcA7VmFdUTD9i8jEMVMSmf6DsrRffXVycjz9YjwA7B6cHp/OThV9+sny6fE7JI6GWwC1Bc91e/TVh8HvBGHT+3LgTQEnS2ooSim34NCyqn8Bb64fDp+KnHPtdrthhsvznJ+vExhjWq0W+hf3nUwmo9GsR+HHAElM6odjwQsuimI8Hp+fn6No2bdYEWMMP06Z5zmPPL4AAKxq/lT5i3BJsb8ADppS7Rq+PKxAKxWpi7MYuPrh1e0vj/gyy7Dzw83tCs+QkygOuKr6MqsoitFoRMmI618fNcbwNikaZAPr6+v/8A//wPS3a198BQBrLT/Jr7XmhwB1XWVUgGFp7ai1FpqrYlXNffLlu6gCVdf5BAD+OAC8pT8GJxGDkyhqE7xaI/8iHgHWV0OaxY2aKwj9iytzfzcj4vGz1pwqrtsP3rHkVqvFRf9e5kIbU/QRv8x59VVVlec5XcGRqiHL4llhFEW8ifoBee1ba+ksbtSoqOknmHdeuCxT/DcAKKVEsTeEBXZ3U3/u4OPn97mxdZ0XXm7AuoOq69mCtzOH+gM+kTWop1k0FYGfO1Hs+HCQxCiKRLIRvAvvzsKniOfSYhed3a/Qq6CUMsbwZDxHJIFXiObab3YFaNp8NuAuWzvR37m4BlflIlUt/tq5AlB6YbYWXQcAMOBmS2UPZ6F0bEustQbWs4ZlfjKeLpUBoJ1lSxnb9FqoLICD4bj8f//tiwcPnpDTZ5+qJ1/OhoWnuzuPn/xfJH7vVkcp+V6K9+jm3u2c84dKTnPwbyELV4qBF6G5lbwUrjKfiWRwEVfkc2dQWkaQKG506X0JjIpi41MyIbqfL179dt81msZl3+nS0UdwxXK7NFoRD28efti5LepSoijq9XoUraprhgNAURRip8dT5S/0OZhISif+8DPli3OLZe5Fgrv6PvkVP8H+FQ658rxcF1d/y31dXqQzXj2g79N5IxJzBK31pa0O47xuufGivkpYP2Fc5KgFGrxz8QtEQFFd6hMua4RX5+phr+5zETzNotx4Hb10FpWV8+ZEn4Y0C17EtZlLE7mI5w4YCHh8+9qSU9Cg2umeO8mqIaQDB0455sGBorcaAGCdq/jDd3COReYujjpaB4NhfsTe9B4eJvt7s63c2WlcFLOjT1WVNKTqNWRxxQcCgUAgEAgEAoFAIPAdJ2x6A4FAIBAIBAKBQCDwyhKON3/tNB9P4ueIxJmi5oNb6LnhGJJacHoZaTjlqOvGpRoiuRR1wVwRr/A8om4biajvND3ZqBQsSPBrgqgvIQp44/F90hXnnKhuYEqtiKivKIooZgwo/DdA59tFM4B6M5u2EuZBNMKG1gvzdHQV6wtzw4orKPqJJCf+4+qIIDyR/r0WlaprPFqplPLHDe6/YUjxEZ6vFbbhpn76+RW/KEz962vNIxLeizd+/3ZXRKSKuczBv1FDrn2nBlcu+skQYf1kcJobj6C5ITUgAi5qyVdEeUrac1N1adr8eJgjQL2c8bcoWPq96AohaqHB58vlujelLAvPc0s4EAg8NxeDVL2jMS0216jFUxQwPAfn4PzcnZ2Nzs7OyGk4bOX5TEW5qpxWs+lSed/6vO4owbnWDPLtJGx6Xz445fPpRDRfQrQe4dMy6ybkgf9GvVy6AvV+YowR9l1EcBJF8oQJFmG26rrwBWtVVVEUCZtDfJeLdpJIHI/HU1sySpkoUvNsgbwmKO8Rhl/1vB4dG0DFNk/XrQTHccxrxNaNjYlmo7Xudru85TjPlA5HNC3a9GKSeMzN1tH8Rig8cMqy5K3I1E0QifvCZZsoQjGTSCiKeMQV/y78iihnrTU3w2OtFWaxCGFjRiACKs+6D28YKNJv/4qfRw7W/lz/avGgBwDOObH9EDkSNxVNtCFJAODqH+bVdWtkzWG5K9YIL8nmsOifRKWU2Ozx4H5svEB40VlrxcMR0Vz9WaAB3vdRbAiLJUkipnmuf9EMRJobWgIiPIhbiAw6zyAcFbuqtzoRj5h3hOhn1u9lvDHUXeQVEfyKI8xc/HstQnltozksjcaiWrE2eUk2t5NAIHAVtNJ8pHPgnJ1dqGzNap2tG9IbDOCLh1CWcH5e/e//7n722WfktPt07fhomcSqqiI10+k1Gjv4VMRfV+/OYihQjWMsNA6S3xLCpvePTHPLoGkJaZ47uU/wpkAhNoDLRBKbU3gpinU4nDtFhDzZtv6mFxdP1lpQSsPrrox/rYqgoWpuKH5ReBALVtFsxMreLt6bIWLE5MssMXT6DYPT4OTj6tseqOfCj8q/soiGcrsKflHTbz82t8BKc/MCVClFhQwXIwb3z13BGzT8K+JeIizC3Gc0BPTT71/hXHHgIniqFiXvKly3uq+VZQF5EEUq+qPYtaorj+rPx7WyQDiv6V49rI/Io9+1rxi5iMevLL+pcD+u/orj0pte6uHr4Lo35d1EZNYvjUAg8AIo8IYU8aaXdzrR/coSBkMochgM3GAwGQwG5DQed/J89poKAOpveh002cF+7fga58tAIBAIBAKBQCAQCAT+uIRNbyAQCAQCgUAgEAgEXlnC8ebvGPJ0RP0M0tWPJPlhOc3nuBoCwjz/4oqIvEGkiwBw2QkNGarOi7i+CE0F1YzDwy/10y/MXZZVs9iAiHYwGJyenpIYx3GSJCQmSdJutylmPCtLMVRVNRgMSC9FKZWmKT8OXRQFuuJ1kUKekgYnFIVn7h9dRRBOc/Dno+F2i+A3FQmoqmo4HHKlX0pzu90W6ohtfxX5AAAgAElEQVQ8bFVVo9GIDpdqrdM05doKRVFwDQJjjDi+fvXjskop5535JPE5CoS4NOyl1cevNMQm4mEu8uJcV86lHgSLUoWlykUesy/S76uw6KaLEIm5IiKReGXu7+fAL4GGFDYk4zkQN2qIrcHJp8GzX5JXT8NVaAje4BQIfCN8bS1QvUjcC0cbmLrN9+Ac5EVZVdOp2YEbDAeT8YQ8nAyqswEzcDPJoZotAA727eG+zXMYjSZVmcTxEjm12z1bdEgsijzPZwFByfS8SNcWM/53kbDp/YbAhuKca15m+VcIpZRQ53N12xuurkl1qcGbyWSCLVisdLVnkYV+w4Xa7aJ1hvIM5/BkoKuw8MFFkWb0bIwBcKAmDmqa/XU0eEbqGBogahznviaVYde4V7cNrs6qqixc3Z2KXSkVx7EoSfoNUFst+a2OV1BVVbzZ/OY3v/nFL35B4vr6+s2bN0nc3Nx85513yKwUtkCK/Pj4+Be/+MXTp09RTJLk/fff58H39vZOTk4AYHNz8/79+9TMnHPC/JKpb8ZEImnzjJi6dd88z3ls2GsoNmttURQUm1+Si8DOwotOFKzoFH6xM0fQWidJwrPMPQwGgwcPHhwdHaHonBuPx9jZ33777R/+8Ifk0xjDrXydnZ19+umnZMcrjuOVlRUyaGetPTo6Gg6H5H91dbXX65HY6/WWlmaz6aV7YJEpEoUmKndCsDC5yH+XZcmDi8LBRy0kihKAuo0ijA39i+y4+oApXFXdFpFIg8+lHjjYNnjti1vz36JxXv0uPvymcNE1mLtEpIS51BBOovMK/IJqiBk8VxE5zkck8iIVM5GfWV4U0JhZ3orQ1TTaD1OLK5SD8YhmxtxBa83btvOsbfmZ4jRkEEW6IvIuqq/hFoHXglo7+mZQcMlB1EvT1OBBPV/cTjm3eM0G4ByUiwLnpf3i0cnR8XSXa6399a9//fv//V/yEKnvGf09Envd3urqbEu8tzv59NPzPLfOufH41vbaFjnd3OpqPdPp/eKLh59/9jmJKtJKGerB2Jev1aP5MKK8h4zXiurbQNj0fhMsahau8amJ78RnKfBWMGKh2Twd4loB/YsXR2LxJxDzrkBrzTOFCRbTP0+VSKTvmTw4KB2wx1cSs2isAQAA07gl/lppSJVrcHXOVZXjm14x9Ihag3n7XrgIJcLSbwBw9aX/kydPHjx4QOLOzg4Pa4y5e/cuxYBhycNoNHr48OHnn08H3CzLNjc3l5dndgWPjo729vYAIE1Tay2PhydDeQt9kciyLPM8JzGOY54p7AiUKvzBPVRVRW3YL0meX4FfdA2eBW7xS1GfPM93d3d3d3dRtNYOBgN88buysiIWvjzmPM8PDg7oewZpmiqlyBh7WZZ7e3v8awciGdzeO9KQSGh0vXrJ+ODoRKJIJK9cdBWi8IygE10Hr/pEgkU8l3Itz84z9QQLYph78UW4br1cMQHC2xVDXZGGyHkligr1HxYsCogi/fZBz1RlytsW+vB7NZRGczwizaJfNIe9lIZUNTgFXjuaesYVeO7glzTCZtfLaA69MM3OeS9OGdZBtShwZavj09GzvekTZ2vtf3/88De/+S156Gamm66R2OuplZXZA6/d3eH//M9RnltjzObmJn9U3VlKW53Zcbyjkz0wcvakshRDymvICw2agUAgEAgEAoFAIBAIfJsJm95AIBAIBAKBQCAQCLyyyBOSgW8VyjtAf3WazzCgK/97da6VquYjZP6VwBSvTq5V7FdHHPMTJ+iqqv7B9PoxUQxLwX2RTpYiJPI7PgfiiA6/KQBUVVUUBV0xxtjFp52xVF8wPV8HWHr4G8sN64WX51x4mQvPmFl+8ZvJuBhhnmPAuboIAI6d9/5mMhj4tuG3igDvF4FA4JvEgSvLioxT4oTO52KudQUAZVlyEcBFkXFOGWPiWCfJrCNrXZvonXPAV90Ljlu/toRN78vh6ksr7vPSGYirvCrPaoVYrPsaPrwnKKV4WK11lmU4Cwon5xzf52itecy6buZKpMGPylpLsVVVlef5ZDLTzi/LUuypeGyYEqUUKKe1u6SwXi2U0kkSgZuWPJYkFY4oZ6hvdQBAX1gIQ2/CM8XjnDs/P+cfOv/8888//PBDErmCKAAYY/7yL/8yyzIU8zwfjUZUg4PB4OjoaH9/H8U0TZ8+fUoKpQDw9OnTw8NDAOj3+6JxRlHEqx7qPUVYr9Fac5vSw+GQbD4BwNOnTz/99FOaMNbX13/wgx+0220UjTFZllFwbGNcQ1jci8CWTyWJfYd7EKJ4XiBMuDVTliUvyaIo9vf30QDV7du3uVVncdPxeEyFDABLS0sbGxuU2clkcnp6+uzZM/Lf6/W4dpBzrtmIHc8R1prwg4gC9AvKv8JFU7cSJIYgMebo+qiIiwkSgdksED6xT5E4NyOE82wZiEQKROTi1sozXkCuIneirEQfuRSRQhHbVaA78oBioL60YOd2qEX4Q5mfC/qNvZI5znD1iUzg1wjUi5enAUAaWVRKiTz6sS0SGxDrYF039IhX6Le4qQBbLI9NjGw8rGhXDdEGAoHnYDKZ/Pa3v/3th5+j6Jz77W9/+8XDh+QhVu1Izbrn8tLy+vo6iSsr6z//+ZtRFEeR2tnJ+v2Zuu+vP9j/9PdT8x8AcHy0n0/OSazKFqgk9Ghi/mwR+Jq41pJFKaW15muO5klOuIqVB3hrhUULEe8Jk5xo+TTsr2/oN8LXoPibL0TKuplWkWCM3FoLyin3um16lTERGRnEFYxYDdNv8Bbl3NX3SfE450ajEd/W7u3tffnllySWZclr/+7du5oZFC3LsigK2oNNJpPBYECx5Xl+fHxMGzAAODk5QdfRaCTy0pBIuOgLJIqF4HA45Pv23d3d3/3ud5Sq27dv37p1i5oWfnWJsmCtnUwmwizW3GW0c47vc9S8D/bQb/D6kb9+baCqquFwSN+Owk0viicnJzxa0WWKouBljj2I7qu1Ho1GaEAb4c8skIZEikaIOfK7PHj1hVe42ACG5f4bBqu5iERGUbQo+NVThSVJ0fqJFIgGLJoKLO6hIqB/C+7q4/sXLLrvXEQW+G8x7IsscNdFhb+I6ZjP4DH4xbioxYrJRYA16F/EH351i6bOXdED/V505SpYz4Qbc5TlfOktRGx+fgOBwDdDWRSPHv3hv//7v1F0zj169IieawOAqp5C1SXxfPmcP91eXu7cu7fZbreiCO7cgZUVcoFP/ucJf+g/HJxX5ZhEZ6NLhonXjDAIBgKBQCAQCAQCgUDglSVsegOBQCAQCAQCgUAg8MoSNr2BQCAQCAQCgUAgEHhlmaO6FngOhHbNIh0koZODV7jIQc8NOjxC+wuvcNH3z0XCT/y1btqgvKeUiqKI7OhYa9M0JTNIcGFZl0Q//VPzIQqUM67kOlTMH0CR63wyu3R4NHry5JRim4yr0+Oiqi4UtLSKTKT0hX+nnEvIZBR4yXBWOzdfbQx8I8s1LDSZznMAC1XOQJ2B+gzU9FPmWZbdvXu33+9PHZXq9/tknAkudBe5iD+cc2VZ8hxxcybOuaOjo8ePH5Przs7OP/7jP5IoqjtN05OTE9ICtdYmSUL6sVmWcXNNxpgoisgVr+CtRaMC70bNuLrS4GAw2NvbI/HRo0cPHjwgNd2zs7ObN29S0UH97lVVHR4ejkYjukIqoKurq7dv36ZSbbVaa2trlJ1p5/QyQiyqkbkcHx8/fPiQ0nx4eDgcDilImqbvvPMOisaYf/mXf6GAt27d+pM/+RNKlTGm1WpRw0jTtKoqMh2X57lSitsA49UHAKpunge8viDMXC3KvlDLFEPKpWhmywDmtZYGlFJxHFPwhkTCZZXCUZ7uaEO0AKA8U1XMUYqc5gQ3OBENfpojFzRkuXmO8ANeCz/yhns10NzqGpyQ5rYhUvWyEJrDfhr8Kw3woR4aC2TR9QAAuLpJMGzecysCJ6YrDj4wz4MYb31X7uHSGRODi1B0/apcx6/EASi2BuKpULWIrbVVVZt6eCKVUtrIspqBFopZ5Eo1JduCsw1LL7CgJnPXZk93T796ckxiWZTjyYRuvNRZurV9J42n02tZwtkZkFru0XHr/GALxnemsnMtFS2nM1NVb7x19403L1wBtra27t59g8Tt7bX33ouSBJytTs8eP92bGebIx1+kamacMtOPWtFXJBrYKMseXLzgFKZhfHxX0dT9NslF8Dx82wib3pePWjzlX7c1zB1YF3Fp47viwNd8UzfPhMmiqADA3/SmaUqu5oqbXgDnjLMsYfUbFmMYzuzVwdMvB//1wam109hOT8aPvzwu8qlJD2NMmqazbDrtqsy5WV/g8xYAOBs7O7enKHCNg+ulKFllhFVflfr/c2pqlK/f7//t3/7t7du3URR7GwDQWs+tOOcct6ikPAM8p6enT548IXFra2tra4vEZ8+ePXr0iMQ4js/Ozsi+QhzH7XabWnuaptxokJm36cVb+y1TTMwNLQq8PdVwOOTmsh4/fvy73/2OdnpFUdy7d+/8fNo+iqI4OTmh7WVZls+ePRMWqjELd+/eNcbQMxo0dEyZxcZJoXxEOTfn6PT09OOPP6ZEjsfj0WhEQZIkuXPnzvLyMgAcHBz86le/ooBFUbz33ntUyFrrLMvIYnaSJGLTq5kdMgCIokjszGst36sU7hmvcJEQowRcNqoImoeUZhZ1BJ9r3eLS6hZcmoVFrouuE5d6aOBaYRuy0OAEl7leyhWr71JeJJ5Ls9Ds+tw0t95r3VRds8UGFuHPoWqeFTQAcHVTf+izodbEHOHDXVX963p8ZJ4LDys8N9/0ZaKgdmcmqum/KdbZov5pAJ5IrbVuaMwK/C/zNOTQgSvn7WkvKEANAOYYft89fPbhR7P9JBoBpbLd2bzd1rd67elydzyGJ0+AHqefnWXD4zWY3JzKzmUq66UbUxHgvXdv/h//5w0S79y5c//+fRLb7Xh1NTIGJpPqP//zyf7hzNpoMX6cqplBrNQ8Sc1sD2xUUpYlbXrFvDwXMek3tBZ/hdDg+VvCnH4bCAQCgUAgEAgEAoHAq0HY9AYCgUAgEAgEAoFA4JUlbHoDgUAgEAgEAoFAIPDKMldTMfDdoPn0vO+6SAnEOed7XgSe2m+Iiv7C1DhBxe0eVVVFujF4hX4DgKqryqCCE16pKiXuyZOsFHCNjzRNer0e6fQqSMdDXRbTe2mtkyRhN9K2zJydhXdCI9El4GZqkDXcVcttDo1BdTSJOreVmWrtdrvdTqdDOlqoHMtroUG5guvZOufG4zHlrqqqx48ff/755ygCwK1bt3Z2dkgsy5J/99xa+9VXX5GSdrfb3dnZoVQ554qiIA1SrDuuwt1qtbrdLgCgoqxoRbwRigYptKyFTm+r1eJ6yLdv37537x5p7e7s7PR6PVLNtdYeHx+fnp6iGEXR7du3MVVInueotBxF0SeffEIpuXnz5o0bNzqdDorOueFwSMlQSqVpytVlm6mqin96/uzsbHd3l1JVVdV4PKaOo7UejUYY+Wg0Go9nn57P81yUhjGGkhHHMakow4UKGS9b6l+IcFVeT2+oMo6q6xMu8hYIBAKvDEopzcwi4HDKR7/m8dN3FaMon+Vx2BfDNf2G+pKgYQRGb/zODZ6vQnNwchTTFkgricBjao4T4V644TG4qAgSnXb8fZ9zrnKzRSlA6VSBOr2PHz/e3Z3aVQGA/37w9Ne/mpk4KcuST+KPvzjZfdhK4+laoizVYKDJvSwrcObGjanWrlJw//6tVmuWjvf/dOm9HyyR2O/3O52Zyck41lVlnVPOwebmVpLMzMHmZ5sr3QGJv/3tb7mNklYru0LhvUaETe93GNGTrwsfEPmYd5U4yQ/+oOAXA+hsXC7Lkm96uUEI9E+/AUB5m15jjDHGOShL4COk1rUxTmvgFnZaraTf71PcaVJA1S7L2aY3jmO2D1Ri02vrWywFiYLZ6FOjlvzrs7ikk0wtbbwdJVM7B0mS9Ho9mhUw8TyRYgrhmxm+EyvL8vT0lIwVl2X58OHDjz76iDxsbW3dunWLxKIouGHkqqo+//xzinljY2Nzc5P2k865PM9pS4bVx411d7tdTGSr1RKtjte7j7VWPCvhme10OmTiCwCGw+GPfvQjmo1WVlb6/T4lYzKZ7O/vP3s2tfTQ6/V+/vOfv//++ygCwOHhIRqUevjw4b//+79Tdu7fv/+Tn/yEViFFUQwGA57ZlZUVPm3zjgBetyrLcjgckofj4+Mvv/zy+HhqGVI0UQAYDocYw2Aw4LamJ5OJKI04jumphL/p5Q2DriwSod7GnGfEzi14XiYiCQQCge8QYmUC9TXP3EEPEUNfw3AK3qQAdQ+qvunVWvOhXgz76JlHSCa1dN1clpiYnMMFD12QqfIT2Qz3rhRo+kxGnaqq8ny2Y4zjKE0XrLKugEhjWdaeKWuteUmCAWCpsmBLW5IlLAe5U7mDAgB+99nvPvjgA/L54QeP/+PfviCRP18GAFVtmclI2eljcaUUf9+Qpsm9e2/dvXuXXP/iL3beeWcNRQBYuwFr2yRhvXDRliUugdStW7dv375DTmtddf9tkgAAHj6cJbLT6ULDQvP1IyxNAoFAIBAIBAKBQCDwyhI2vYFAIBAIBAKBQCAQeGUJm95AIBAIBAKBQCAQCLyyBJ3ewLVp0PFQnuWbZoR6iVBTQSNYeDulK62YzqqqaXGYWCXsCU5vudi+NftG/GTsesuqqmaajUk8U3QEUK7Szs2Co7UAQnH9D8HleW30oRa6RnHS6m1H8TKKxpiVlRUyCqW1juOYV4Sqq0MrpeZWU1VVx8fHpDuKKr5kegoADg4O/vCHP5C4u7vLjSKcnp7u7e3NCnYyefvtt0mRFeMh5RlUMeLJKIoC9VHPzs4ODg6GwyFen0wmR0dHZHrKT7yta1knScJ1aVDxm8SqqnjhGGMsUwmuqopbuXDOZVnW6/VQBIDJZIKenXOHh4eUyL29vadPn1IhTyaTx48fo/YvAGitubksuLgRiSKR3W53bW2NEqmUckxjVimF6rgoGmPKssSiGw6HlCQAOD8/Pzk5oRpEJ0okanMtugt4Pe7SzosxyKuBQCDw6iLUYvlvMR6KmasZEVYsh3yRD+YAIHR6eSIxLAbnkaBPLgI4pbSaLUUUQG1xdQXEjMBFOVuoC/1SrS23w6KNQ9tRF6A3np0Lw6QACkCpmlkXRX8AAMAYxXc3WDgkng2HB2cnlLQoibNWRrrHSuvYdJSyAKDzHZjMLGhA3oaSaVmrOIKE7mviTpJqpaa5yNJ0Y2Mty1pTMYvffXd9c7OPolKw8b00XUEJAEC3oKwXO1uTwnhcnZwMbeW0Vsv9Vrs1W/9kS3aZ2eGKe6cT/ZjEUgHAJi+c15yw6X2N8Aa7KYuuz0UMuwIcl0ls9gwArr4Er+ombYuiuNgIOROPooiPibVeHBsTZ7PBKO5Uy9slDZG2dEWuafTVWqdJZGaDoAYXATAzifRrynMfiHDefMBxAMxSQR2lWka9q1hwUZK4peQic1xIWZaPHz/+8ssvUayqSmxrv/jiCx7t6enpwcEBiWhkmPZy3//+999//33a9A4GA2B2s3DbxmMbj8e4306S5OHDh7SHPzg4+K//+q+TkxMUVd0mh1JKa80nrbW1tX5/OnmgyK0353meZRklMo7jsiwpeFEU3Oiic67X621ubpJorSXPjx49IovKcRx/8sknJJ6fn3/88ceHh4coKqWyLONbcbICjURRxF1/8IMf/P3f/z3f1vLGr7VO05TKxzk3mUzQaNbJyQm3p31wcPDkyRPabB8fH1trKVosN8qOUspay1PVbFgOvFYnOjheod/NnT0QCAS+E4iRMIoiuqKUooFOLGBwqiJxLjxm5xwXxSNI/4kkvzXUbRRrrbkZRQBwzuHY7g/L/Eo9SrrIpWssY5xz1s38OwXcVU3/KACIImcMu42yrrYcUrQ9BgDnXFkWvApMFKvZwkyJTEaREaUxvTkAABwfn/7Xg09oE91f6d+5c4dm58REWdaNjQEAM/6hOp/ZyFSjz1UxMzZlVJKkHbpzko06qwc6mj6AXllp/9mf3V1fm5qqyrLoBz/c2N6emrkCAKs1//qHNpCztqPqtXB8NPn9w6OiqOLYvJOatDcz+rW0WfU2ZpN4uvHsLHpA4lg7gHdIDIRNb+DbjnMOFP7XsEVUfGuqjYs0m0s0KAU0uRit0kRxo4JizOej7R8LBUqD4Smxwqa0P1NdAZwIyZ42zpo82rIs6Y0rABRFwefdsizpRSi68nkX42lIGC0RrLVlWdLerCiK8XhMLzCVUobZHAYAIU4mE57IsiwbFgf4g/LonOP5dc7xbSFcbBTxNy8rsVsuioI2ogCglHLOkWeYt+nlrugkEsnhWYB60fHMVhegyJ1gXrQ874FAIBAQzB0k/bH028bcZMPi64t44Yzy2zkuuunianpF3IjsJ1/AnZ0DxzyIJOL12UWlaqLAWlsUBX3SsihKvghyDpTTyhkAUC4GN/vmIrgUHDcxnSpIaZGmVKk0vrIGADARpFmUXrySTbMoa5msPXs5kVu4+KIIAIDSl+S/rGxRWvAOWylTey2jTIWmpxEH7C1w4AVeYQUCgUAgEAgEAoFAIPBtJ2x6A4FAIBAIBAKBQCDwyhKON3+HaT618iKncZ47ZjzkyQ9tKqblMvcoKY/Nj9k555zD/9uacoj0yWUFSvMHOgqYBi9opZVSLAYZlcABQGOBLEQ5Oskzj2bXOYjyuUo1Oeeqi4/UA0Ce52j6CEVrbZIkaxdqJwCws7Pz5ptvkjgYDMgzADx9+vT8/JxO7UZRNBwOuZprWZZ0L7w1P+LrnMMjzWmaLi0tkSaqtfbmzZvdbpd8CmVgkfGVlZXl5amJLwBot9tcpdk5N5lM6CyxUur8/Jw0dkajkdY6SaaHlLTW+/v7X3zxBYU9OjpC81RlWe7s7KysTG1N7OzsLC0tdTpTnRyt9fb2drvdRhEA0jTlekTieHMcx1ynN03TJ0+eUF84OjqKoogKpNvt3rp1iwrEOZfnOZ5hjuOYzlQDQBRFp6endOXs7Gw8HpNdK2MMTwbWTkMrcs6JRiU8+z2UQ2GbvQUCgcC3lmsNX9fy7E/ZYprjIk6gJAJAFEU0xairma6Ey1LoXG3YV0pdFuISvMBSnou1trQz9R+tTGQU0NpMgdZ6lkhAU6OzwlT1JeFgMJxMZgpQZ2dntEoBgIdfPvnss88ptuFwuLKyQpNvpNJcp0ZpANjdPd/f36eA4/GYT+K9Xndra4NqobM02riTxek0F73e0o0bS/3+1JBVkpgkvcTwCi+owWB8ejIg8cmTo88+/yKflFmWbG+3+/2Z6c04gohFXFUVV/6qqropnNeesOn9DiO0McVYI/aTPotc+QhIV+i3H8q/L/1WShljaEOCIt8YcFeohwUA59xUg1HZ0lWaKScoUHyQU2gx4QIN9bxr7RIz86JAKR4cx1aZL8IrD85CBwBosFMFAAC2IbgCbZTjqeKFg3XUkCylFJaAtXY8HtPceXZ29vjx44cPH5LPbrd7//59En/+85//9Kc/JXE8HqN5KuTBgwdnZ2doRhgA2u323t4e7biOjo7G4zGlyjknggMATi3Ly8t37tyhHePW1tby8jLfy3Gcc0Jrt91uczvJAmvt8fEx7fQGg8F4PKZmNplMjDG0n4zj+KOPPnr27BmKcKGoDABVVf31X/81ZWd9ff3u3btLS0soVlW1vr7O1XSjKOKNOc9z7pokCe20AWB/f/+Xv/wlZer8/DzLMgq+vb39N3/zN9vbU5sZ1trBYIA5+uSTT3jbzrLs4cOHdCXP89PTU7pvWZbn5+fUcoqicBfPHQihIcxFakVzRR/eJpt9BgKBwLeWqw9fV/eJ8FlbLHi01mKW57sX51yapq3WdBOFV+j33GTMvShwzpXl7LG4UiqKDF94XCGOGUrVFmYAtmFlxSnKgi8A4jgxWUS31korZvXKObAWLWZNUaZ232fPnj59ukviRx999ODBzLbT3uHJw8e7lOV33nmn1WrRFxxc2S0HmSsVAHzwweMHDz6mgOM85o/mb9+++ad/OjPkuXHDvvfnVbszjTaOTbebxTGtfiFlxlZ9FNQ+E/L06dF//uf/kviHPzz69S9/Mx6Pe73u+np/dXVmT2upB9GsUUA+yblp0vF47ClLv9aETe93Gz7qQX2Mc94rneeDL2SRq0eLq2TyL0S6QqIPu7tr6LrcyvHFFRatUgpqBu6vi4x9xmKXKc0eFrr6OeIoz5jBojpyztn6B3smkwntWpVSnU6H3l4CQL/fX19fJ3E8HvOXmf1+nxtG1lrneU5z1WQy4VsmcWsEJ3V8q0nzt1Kq3+/zLyeJVkfvOZEsy8iyMQCUZcm3l865oij4W1bc6OLvoiiUUvxBzGAw4I2Qbp2m6fLyMq1CMO+0cXXORVHE8xtFEV+yFEXRsOk9Pj4+PT2lTPEUAkCWZf1+n97AW2vTNMUFUK/X4+serfVoNKL0Y8Yp2rIsq6oi0VrrvGGhoSE1981AIBB4nfEn4uvCx1illJiJ+PwCdYOO4r4i7LUQs60/R7wAV43HOVfZ2RRvnHxhUE+Sc6wEFC6XmHue5/xp++Hh4ePHs6/4HJycHxwcUvDNzc3RaESvcKs8mZxZWzgAODub8HgcdIyZPW1P03RpqRfH023U6ipsb0Hn4hWs1hDHwB9r1N7MXEaeF8fsTe/R0dnBwcF4PM7zfDSasJUF1NsIWGf5wqOqZEm+5tSeMwUCgUAgEAgEAoFAIPAqETa9gUAgEAgEAoFAIBB4ZQnHm7/bNJyNeXkHVCTiAOTVD8P4B4H8NAuV4KmWi3JKRboWXNV1eiMFDfoSGkDT8ReZCFAASl6sy4uzt9gFAMSZmzk0uVrr1CVawVeFClkplSQJKcQqpXq9XpOYk7UAACAASURBVL/fJ59Zlon65cdu0zTt9XqkxNLtdpMkITFJkm63SyamUAGJn+mlI75RFPF611pz+xD+aSutNT/enKYpj1Y0vziO0zSlhpQkSavVolzEceyco8PPGJafrJ42OYAoipaWlihgt9uN45hEbPazE1bUVi8QjVkYssISoJTHcdxqtSi2LMt4WADQWuOtefUByB6ktU7TlA7F4TlwOgpujMmyjAeP45jr2IuSvC6i4ogXjDYQCAS+i/jjYcNgKKYMMQUgi4LzyYiuoOdFQQj0xX4LnFwP1XDOO4o8Y7qwupgl6c+U2W+ltFazlYaaLtjqqWELE3C2dlzY1ey6OGtsNZttqzKqylnk2vVapkWRqXJ9cJRCMfVf5nZ0elAW5wCgoOgvz9S7klanRceXAXZup6vrLrr4MG+vB1EE5qLSlAKcEi+8g7OaJ1LXN2Da1ozATAb58f7xTDwfpSZScdyK49TohDWNCJRm0cYqysxsdRTrsMurEYrjO4xm5uzAG9ouHekaaIjK1fVMcGD1R3YEF8GLXAHkKB9FEd8Y4Pp+ekWlqja21lMI6rJjC2x4ReXgi0Q5UM4px0fMenq1gbrpH8JN77wQ1TxbiFxwnHVFUbiL76eDNwWaun3jRaj6rjVJkrW1tRs3bqBojHn//fdv375NHjY2NrhCiNaa6/RubW396Ec/oi1ikiRLS0u0a0rT9P79+xRbHMe3b9/mpqFx0wUAy8vLXD0pSZLV1dXa9FCvA2FgSZiMGo/HpKUMACsrK9vb27StRdVcSiRuCyn4ZDL56KOPnjx5gqJSqtfrYZaXl5d//OMf0xYxiqJWq0VpVkrFcSx2ubxGrLU8zVpr7rnT6fCdf7vdvnHjBnlYXV0V9yJ14tXV1Z2dHbwOAOPx+OTkhIorTdOVlRUKiNGSiQ60B8ZVuNfW1rhljiRJGmqhGd7ZXf1BmOjmgUAg8GogZmExZqIZBfyNE4QYGOk3ABhj+MNcYSQCZ5BFAykffhHyLO4iUAqM4StJ9M5z4YRYFyrrFtoHVg4Ue6HgQOlZYiJgLyq0hiSepdOYCFxU28fSLwBnASq2RVQAULOCUk3a+XD2fYfxeW9wPJv1Erhzp/dDWn2l561P/q0/WxIUp4dn/09enAPAzs7OT3/yJgV8892V+z+aWTxptVrLS06pafaTBDo9ZS42Vc7Z0hYVrVqddnnqygtnBUkKbLUL1QSqmdky2P397i//7/8gMYlhu93V3W6329luJ+uzZgKJ0pGdFVTfdHc6GySupN3mRerrRtj0frdpGEBfFsrb0wqx4b5iFJ6LyAIf080FAAAuato/XhPxaNLZ2kAuklz//BHnaxxMKudsVVm26XX1jYS+zDo3wSdarXWWZbTtMcasr6/THhgA0jQVEyffXrbb7fX1dTIpqbVOkoQnA3dr+DuKol6vx98rtlotfGErQmGqSPSp2FeXwNtAuvqnHfANMz09ybKs2+3SpjeO4+XlZVpbDAaDTz75ZDgcooj+cbOaJMn6+jrt+adriotkYJp54QhE4+e1AAC4YSYP4vEBTzAAKKXoGUGapnybiq2C4omiqN1uU9j2BSiWZdnpdIRJMP6YqSE7V0FkmbhiQw0EAoFXhumEUZ+5GgZDMdv6PsUkIrjWvTiXeXPA1l7CnqgD2/imV0putmxSwBZWCrRm7yS1ioCdzgPgSbgQ+ZW6aKvYlszUZR4X+SzyOFrrJd+nu9vCHj+dPZsYF/bZ2eNJuQcAOztrm5vT7zUAwFtv9X/8Z7OH+AqUqt24dmDQOlfayrmL2dZqWyZuZl4TTAxszwuuqm16h8fDZ49mBqhXV9obSytxpLtp2o5MxpakRtXe9KY67jJrzqlm++MAb3OBQCAQCAQCgUAgEAi8YoRNbyAQCAQCgUAgEAgEXlnC8ebAteHHKa+Ff9pHiM+NH8clB3YY6uLUzezKlcN+fajpWSZ2hQn+eaSGSuFnorTWcRxzy0Z0bpY8028fDC5EHoSfjo6iKGFmrgAgjmM8VyxCNd8UGnMHAMrTDOdau2jJicQ4jmNmvSlJkna7TVqvANDpdPA8cJqmDSfE5l5vSKQAT0fTSeM0TZMkoURydV+oR2vqel9pmtJ5bBTTNOW54/WrtY7qavPYAEicm6mrQ9X0gvEEAoHA60DzckgMpL6dCOb4clBKfTOjt3P8YDBAPbPW2SKfqQpba4uiZIWjwM40frVWaVpbxmjPJJgoq7Is6Z2fUsqY2VHqRMW9XjutugDQ6WSt1mwBE8U19R9x0hvkgevaVOgUKEU3Ab+MnQOmeARaG1qnAUCrlXU77Tg2nU6Lr6mm8GYjW5FM5GuOV3aB7w4vODZRxxDxNEdL61oSmaMEPdPK3lpbliVZGAKAoihIQRRFrnCI47tSyjlwrqaIi1cIW1fKNQb8YaEBbRrPPKg5m+opbjaKzUMO63UaXbWKk4S7i+nQNBqychf2xpRSuM3D61rre/fubW9vo6iUunnzJrds5E8PnH6/f//+fZp3VX1qsdaORiOyg6W17na7fODO8xxd0SwTT3/zZD/3CoH6sSTevHlTa02JTJKk0+nQ1k5rHTMjzGVZ9nq9s7MzFOEibQDQ6/XQ3BReFykEb80hrG2JCqIaQdbX13/605/SlTiO2+02+Y/jmD8+AHav9fV1UaSj0Yh8RlGUMcvPxphWazZHWmuTJOE9rtPpcG3qqG4hDAB4fxTVPRfMwlV8BgKBwLcTMdrzoZsjBjon9xtyjhCIKWM8HnPrElVV8e1NVVUnJyc0IMdxzOc1qN8dl140ofBUiZmURmz/IgDAdO0zC35pHuuf1QDxZQxyLYqiKGYzURRFPLMnx+ePHx/Yi8weH5989tlnZK4ySVqb67da2dS2RZJE9+7d2thgH6FotVdWSIJ+v8+fa49Oqq/2viLbpWtrq2+9dZceJbd7KzfeWmt1JwBw+/bq1tbMINbShuEbXeccNzXqFMD0HQoAgAOnjZ4ZhHHKgFJMwVZr4M1qMICTg5nYbm/+5Cc/IfF7d9b+4qdvZlkcRdHt2zdr1VVxo15Q1RfV3C5pAMKmN3AVFg+Il8OHSOectZYvo6uqErtcMZ4iSoFt3OVaW3tIBnC9Ta/Ch3ALcPVb11B8OvBQ0OjsGlwVKG0Mnz9E4SilmiuCNr1896WU2tjYoK8KKaXws0MUyoffNMsyslPl45yr6han+GtG9EC/ReLn1vsiRFjxunJ5eTmOY4owiqJ2u82TIYKvrq6KzWrzSmUR1loej9a6YT3U6XR4SWqt/be7c6u72+1yQ1ZVVQlr2zwejITicc4lScITyV96+yzqj3OhFIrfgUAg8N1FjKLAZhB/lBMDptwQerMeH43LsuTbFWstn9estePxmK4458hCoU/DuO28b0z6uWBIJ68oasEVqLp5z4XJqKqqKGaLNl034jXJi73dw6KYTm3Pnj374IMHp6enKLbbvbfu2qWlVRSzLLl5c319ZlZ5+hCZxCzL+LPd4bE9Pj6mTW+v1+n1uu32dDpe21z+0z/bWlkHAOj3gW2WwcZFBbMKcuAqslMFAE45XhQXTEVQEaiLzxsBeIvYPIfBYCYmSffOnTskvvPO9o9+/H67lQCANDfpHN892/qSoFrwvOa15XnWdoFAIBAIBAL/P3tv+iTJcdwLukfkUXd1VXdP90zPPTgJgCIlkSbTYZLee5LZ7vuoT/sHrNm+f24lWzM9M32S2T5KFEFRxJIAiAEw99EzfUx33ZVHhO+HqPL0zOquAcChBIziZzNt5RmRkXFlhHtk+C88PDw8PDy+Ezh3jd/j24/Kl6X1q3dyzem3wepD1Vq/x9Ja10q0ykpnJXFrLS8rIhKq0vpiaQnRkNxFo/Tqp9tSdFTyCiKuLmgWwOrDBKpPqYDWpbv2M/FqASRWa7JSdRIyMiJK31EHueF8/XfO1edWIJvbiSIQcLk33rV7ecG4FLPSqSr9pLJWjSsOPPLbdWWbMaysgldu58hu3Z0ja62jKFpTOesX9SvA8vnJqy9RZUGdf1dWxGWQ+71aOZXflbri368Q68vu4eHh8W1GZY74XYCIBoPBeDzmK/v7+0+ePGHx9PRUznqDweCLL77g/UHdbvf69essImIgzvVFxPMG4ZXrbqIRk4gIAyAAC2L3LGKxRRkAysIqkD+oAgAREFlXtQqDOCwMkMko2X96wuK9O09/9tOP03ShmYzH48Nn8yRZZM2kOB3FoVqUPZvr3/z65OnDxIkA8PxZcvKi+CT75H5qk+KooavXt//wR1dgmfHeRvfqtTQMF4m3u9i/oJttBIAwJisUSwQKqLSfXKOS9UVGzKcICkvTqzakbPENFss+wa0oh65wJtox8bTwY7rQN7XkMLABAKk8RSPSCRTo4kHd4Yurs6JTbabJ2gb6Twdv9H5XQUR5nlc87uRwVlGjV7XqlbHvK8FaK3fgaK0lLw6sJIsrFoWcTiqmWmW3szGGIyhl5CnnFShdulEpheLMN1jdSFw+WQ4ReQQ8C+fOHy/bK6HWJyvPXn8pzs8DwGKzUGG7rppGfF3uqiWiNE2TpJgtoiiq7HZe/1yJSlu7K1LkK9baLMu4J+ASZ4qw0jEqyVbMWq31mn1fAIuN3wxcybZDlmXD4ZAjO4KoM2M6VF6xSiahrEid10AOVN4o7kSXk8qaBS3BV9xF/l2pyTX5PxOVpGhla5zEmiAPDw+P7wTcoFcZVCs4b6yrDJj8dxXW2sPDw/39fb7yxRdffP755yw+f/5c7lM9ODj413/9VyZ0uHjxYqPR6HQWp8iGYdjtds/zVTkvDwBAQER5xVVVhANiSX1SqFCdm1oFRGhtoQURUZ5bawkAwiCKw0LTePL4xa9+9SWLv/roy//5//zTbLbQTCoOzEkLhxsNbRZlt9beu70/n8+dCAAvjuajYUkdUmqPxff/9NL/8X++pfUyV9bmZk60cBgOA91sxEGgYMXpOoAotIUhugBXhkUwZaVOVjsRmAxs2Q1PYKM23YgWeQCAvVr6/Y5wJVMZTh8CAFiC4QBmRWEhbkBQ5GrrcP9742L5oJNMcW1P/s+Gs98Qj9cA69VTj9cM62fo8+B7yFfHN6thDw8PDw+PVazOKatXKuAIL435bQVKE5pBK8wpRPS1CivjyHsrQQAACEqhWpruFhDlMjgKO/Zr45vfWQGemw1XU6JEK5VTvq8a+p8cX2/V38PDw8PDw8PDw8PDw8PjOwRv9Hp4eHh4eHh4eHh4eHi8tvDbm7+rIKL5fC69MSsURJVzz9YTFElUtoJUNookSTKZTPhKUD4XFMtsCtZaFA6TRKS1lrmqZDIoHxPqnCTFFlyZsbN3fnwVuBJxERCxss+3UmTEqjv0vw9kHhxkNlazVM5zUe0VF9aK66lSSjYBIsr45fpfHJDDD1JKhWG4mhOGLbNV8aNl9jhIipU0V7tupSoqZeffDpWarERYje+gta7Valwb60vqUIlQea4sRSXP7ooUlVJn3r5ab1pr2ZlXu00Flbpan+evWFdQfq3WRPPw8PD49mP90OfErzXQUZm+Mc/z0Wj04sULjnB0dHRwcMDiYDCQPB3D4fDJkyc8WSPiYDDg6SCOY3mU3dcAvaQYuPh/NgiIBEPKgltkOYfkuZ3Pc+fE60KTJHH0HJu97Y3u4swhAGg06ru72yyevpi9+dabyXxRfGutrLooqo3HY5MfOZGIkiSR/s9b251LFwuH2GZTNRrFvHnrZi8IAvbptdbKWVUrpZVCdLNtyUlQIYKYH621uWggyokSy5Xh+gfw7dbSfEp5ET9N09LZQvOBTRZnMgFANholx8W5vQpIIyEAEOkkUZLiREWAghLs+Lii+fNvD/BG73cX1trhcMgHlwFAFEWSU6pyNFkldA3c0MyiLZ+sOx6PDw4OxOgTtdttfq+01s1mkx9kjEHBUouIYRgyEwMAxHEsaZOyLJOZDMNQKaWUcqq4VMfdjMPi14UbQ91vRNS6pPrLUABYYf/99wARWSpGeVzLkg1Lk0NecdVuVyijKsZbZd2h0tzOpmIxy7LRaMSV41q/YjPzbyKqEFCFYehSU0qt742Vkmqt14zdlR5bqShXM7IGHDjCeQjDsNPpVG6UlVxJpCLaFXpqWYRKnitZqkQGAFnJEpWadMnKvl0xkiu50uXOXckVlAu1WmkyKSe6K+QJBTw8PL6bqIzGXx08+lUDAACAiLIsYzsnz/Pnz5/fu3ePI3zxxRe3b99mMUkSSc60v7//b//2bzwvDIfDt956i63iZrPZ7/fXD9eMSg4VIkhtqnQfLf+dDSIygpxpNp8Nh0NOfzZNjo4G+fK4XccN6ZhQ3//e77VbhdHb7/darQUxFQC0m5vKbqbp4sbRaPTo0SOujTyDg4ODNDl0IiLW63U5D37w/lvvvn2Txd1dvHiRJQhaENcK1mlELNMsk0LrKk+p8oxPCpYGPADkSTIdjzmCTfJ8OCfDVi8qFEavMfngxM6mCxHg5OREcncnp8/Tk2csDgaDw+fPWYyAGtYoIESs12qRVJ9Si3mRq6NHjyRZaRiGv4Wm/BribEXK4zsB99mNRV3+llvRbs8biF8KVmQdnFHEmrHWWlo1iFiJL+cP97syLq8R3RUpviKUcngWKqP8+sjfRlTqbU1P+Fo1TGWbqmIgraLSGSodg3+/FOsjV0q02rirV74KVnvjN0vnm2F9kSXWxyRvf3p4eHh8CyAnRGutOxWPQysnKeR5LmfYPM/n8znreEmSSBPaCLb/rw88X8lZE3QGqHzugCugNHrn87krcp6XeIy11nFcrPPW67VWq5mmizjGmDAMubDWUJ7nabqoHKVU5VCDOAparcLw63Sg12MJbGSNEkf+VJeGCQsNsDx5lmuCiKworDXG5DkbvYhIQoUgY0ya2mVzE1E2n6ezgq45mUwSYQPPRqPJaMRiRhaWRi8aY8W3IkwMZEU/MWlazrSf/Uuobhr08PDw8PDw8PDw8PDw8Hht4I1eDw8PDw8PDw8PDw8Pj9cWfnvzK4DcsgJn7Yo8D6vbUdbcaK2dz+e8wSNN00ePHj2Xm/6jSDr+Xbp06dKlSyxWfAJpyangtnbI57ogFgeDwbHwpz85Odnf3+cIURR1Oh3eWNJsNq9fv87PqtTMmagUWT6aMwlABFheo0G5bYOAyhs6VDkCb1ZZBCO6i04ABCWPFEcqH75OLrVvgPVlp5ckS+CYC9xvgHJ0a2X6ilBjsb0HAV0gOo+dpcuKJTscDDPBpjCZTKTj0ObWVk/uBEKUZciNmc6mZrmBJ0lTY40SHt2tRuHRDQDuZZBi8ft8iHZfoOJ6WkHljcOy563r5CzyxTN/w0pqFby0P5+H1TTlFSKSrgpU3iSGiOwOXYGLWbnIKZ9ZFlmESj2fnp6enBTn2qdpOhP7r8IwbDQavBMsiqJeryd98vlxrgVXrzNWq5GvWGtHoxFv80PEer0uiQBms5nssVEUSfKCIAgqXuvngYhWm36NWMH6ez1ed5Acfl8dXtqLXhrh1aM005yF9XlaHwpfIcIZWLx9Il9nvIClXFfHnHL0wsVzgW/yQQhdqsuUEFw+l8M4kELQS+WCtO73entCSbt25erR4YKcCQBOTk4ODxduqwCw1d96/3vvs3J17dq1rc2tbqfrxHq9HuiyPl8Ul0BO49W2tGQzAB6uEdWiHA5EROIehNJgnmV2vtyEDAAHh4O7d+/xlDSdpEeH4zxbiORagQAAkjmBmLjG4+z0pNja/fTByZN7T7KlT+9sNktHiV2mE4G6ut1RtJgQlVb1TiuqF3PEzlbYqhf7xmNFUKg8AHmO87TUTLL1TQ7ZBKwBgDyZ52L/OZWny2Q+n45Gy64IaWJHg9Qs3WsVog4CPg2YDJnBzM4XJSKg4XA8nRbTa55DHhZbslUTWttFJ6xr7EdKIyJiLY6CoNCy0ARgC93gyOrR0YBF0FGz3LerL8LLIOO/BtOcN3pfAaisoTrun6/SOWhFNTxTr3VIkuTJkyfs+D6ZTP7+7//+k08+4QgV6uO/+qu/+uu//msWlVLNZpNzZYyZz+dEhIhxHEtDJc9zyRn42Wef/fM//zOLR0dHDx484EEtjmNJZLW3t/c3f/M3jUbDia50sioQSyOmUqpCtCMfnWUZ+y2jVqgED1BlilJaWmcIWImA8r0F0Kr02iNZyU+AhLoUv2QSl3DO5SVe5vK65nZCZXTJFDdQzFcEkGdgCzMpCEIdFIM+IrgSIWCgAlrW8Ww2++KLL54fLNZKrLW3b99++vTp8j743/77f/+v/+2/sUgARkx44/nsyfPn+dJmJku5KcicW83WO2+91dtY2szomByK9uWmd7fwjZVeQWUyRkSs1WpriK+w7JNDZQNy9bU6Z2Flgcp7xKi8raszR6UU7ooUJSpBbkmL0zfGTKdTfsu01v1+X7JTMJyjF2cmCII4jivvlKx2Bw5K01QW6te//vWHH37I4sHBwf379zl+r9e7evUqN8Tu7u6f/dmfbW1tOVEpVa/XXdUZx+G5hNZ6lW1LijJX8/n8k08+efZsQemBiLdu3drZ2eH4Dx8+fPz4MYvb29uXL19msdlsbm1tndmCUG41Hlsc3LjN4mprSrgiyNRWhzKP1xcEkL90eD8H53YqAAB46QLrmlBcO6N8QxBAhlC8JytYn2Ncaz6uDwWXMr9kpSGXCAwbYwiI7k+BkqluiUiQDBOQTA1RlcmcFNLayjwnBBGUko8lpFzkHwKl9DKTodYfvPe9N2/dXAbDZrd/8+otFn/5y1/+5Cc/YfEPvv/7/+P/+h+sXDUaja0L27zmqLSK4xhtOWcLiYBKDSgjEWXWjIoIqFQQSF3LWDQi2UAHcnl9Ms0PXxRm4c9//sX//bd/my0NxdkUXhwSj7KtVuvNN99st9sA8NZ1i8V98PjL4YcfFjROj7748qP/9U/pcukzjmsbGxts8G/32//lj25e3l3wYGGgo52u7hTzYysy9fCUxVBbGBWtr2ZzHE1YBGMxLxinIZnA0SNIpwAw2X82Oi6WITKaZVTcmGXZXCwKn87xwYlaWrWgtZYrEWS1mfYoKzJprCUxDwbX4+D6LovxVrwhZvzNbv3mxY0w0ACgrJUKLdS2Kdpg6eHf//29h8XK9aW42xMt7qZann/PnOPkRFaZ5iq61vpZ8tsJb/S+Asg+5EQR+BJU+pMIqcKpxZPJ4pUbjUbPnj17+PAhR9BaS6XtxYsXUqWrfA5yebbW4soZJ5XijMfj/f19Fg8PDx89esQRKuzNQRAkSXJeDZxZQHnRvZAVcXkF18yPCFj+JAkr81JJLGWECEguZbpVURkDV1JjnF1SgZdGOA+IUJ53Za0SgbHAPIEAqMGR7BdYxncrt8trNB6P+ZgEY8yTJ0/u37+/DIfBYFCuHZBVY4yZJ3O2Z9zSCXcGa0vWJiza5eyqqzR0JZoVJNKrXXQVa3qRC+IILqjy9K/+/lZuFCFVnFdwRiXPRvDDLfg/lpUZBIHMoYS7kXPiJqT1j5bZlvUMAMPhUK6APH78+Pbt2xx/a2sLEVnNQsT5fF4ZWNyjK1V6pjXIydISTszzfDQa8e4SRNzZ2ZG7D2QoAMRxXPnwy78rqLRXJZNwTj7Pg8yzx38+0G9h9K55Pdf3qDU3AgC9LMI3hF1bVFozMb+stC/H+fVBRBxMQCCmucU1eTNZafQCEJUUBgLQRXwCoG9Ymbj4v4RcTAdQCMVyPGK30+m02xzh4u7u6YviPI779+7Lj7cb3d6tm2+0l+cS6UBHcYQ8ZOFZzcDVU9WOJCxQTrSY05eL1HwnEGkSegiRlU/KjZ0nRcW+OBnfu/eY2blmUzw51Hm+uL3Xy7a2UqeqZUmpV03H+eHzgtn48Nnw8MlhmiwG9lar1YoaOl6kE1i42Gvd2F1YehioYK+nu2JROD2FTJi11oLkzUoSHM+K3mEMpCnwYD4bweERzMcAkD9+nCyXXwEghXFKBblUnudS3Z3M1MlJOFsWNgiCpNEotlhSaGZEecFQjVjSjuKLMQbFliXVaNU3ClO21W/19rajUAMR5DmIaZeae1BfLD0DgO5tT0U6iQ7X9GRaUb1WlQc5za2Gfuew+pZ4eHh4eHh4eHh4eHh4eLwm8Eavh4eHh4eHh4eHh4eHx2sLv735FaCyS2F1AwBvD1gNWr3CcDsP+d4kScbj8Wh5ctd0Om00Gtvb2xy/sr05CAKODADylDMAcBub1ZLCSm5gmM/n8ka5dRAAGo3GpUuXOL7WWvoQttttpRRvGjTGSMc5a61dOT14zc5SF2qtBURFJSecdRUHAARWbJ3B8q2wcnc1qbVpvyqs2W8EAAAu0+fkBBFQgdyNuSbPsvCW5GGAxpjZbCbJiibTyXhSHBYXBmEYC2/Mcq6pvCnXWCMfRUSWSrtngYjsYv/t+lfGdU7+vb6fQDmF1R07RFTpdZUUKrdXtuzy9cpu2PWlWHTdJfhdc6jca8vHX2dZNp1OeZNYGIZJkriNuxXXU3eFi+PSlKWr5KpyZTQayZd9Op1K59t2u33hwgVOrdvt1ut1jhAEwWw249uDIGAuvUrpzqzS1Yw5KKUkN5VSKgxDufGYVki/JEufqw3Os/xdyZW7In9X2kuK6+/18PD4dwZKt5eXvowIpbnrZdFfGRBL8y9UCbOqY8q6gpT0GCI4Xz8AgGIaEKfOLlF5CmKRLXTRl/EJjDFya7AW7r4AgFiaj+I47nQ6PHNFoaIs4O3NnU6HWQlHo9mDBwd849HRQB5ZrJTqbnTzdLFjudVqdbtdpjNstVoAUMwCFtPhGPKCB8vOjyktNoojgJKtMJrhi2Fpe3Oec5FxPtaTCSZTALDGyKkn1CGqYuewthajiDthKw43VK1uFvGdTy9XjjV6nIdpVmRDKSUTr9XrLbGfudFo1Jdb2QEgCMNsPocMiYiyrPCTBgiiVNeKgCJKmAAAIABJREFUZJ0uwSJZW239r4m1fbKkbEisv+s/EN7ofQVARKl1OciuwF2w0stxxSmcfwNAkiTHx8fsP3l6evrRRx8xXbNS6u233/693/s9jl/hd82y7Gc/+xmLN27ciOOYHxFFUbPZdAqii8wxv/zyy88//5xF6dALAO++++73v/99Lu98Pj85OeECdjqdWq02nS58M5IkGQ6Hp6cLRgFrbZIkUpWs0MNmWSYrQcZXUcQsweDYhsoOeHIyMdZIgmKyRMbyoKaUCoKAnWEQQKH0e13BqtFcwvlB6Camc7EmDAmBCKSVhWWijiiEJXshAJQMYAcX2SWyzH+eJIcHzx88eOBEY8zdu3fv3LmzvAc+/fTTm2+8weLu7u6169dYrAxweZ5PJhPuPFqp3JR8epN5kqTFVESWHHNDHMetVos7/6o5UavVZD/Jskx20VV7Ur5HzvpikYiyLJM5rxhCgWCuIqL5fO5mX1yCg9wPB6VUrVar2J8Sk8lE9u3KmpTWWmbSLWnxLD4ajW7fvj0cLqbter2e5/mFCxcAoNVqdTqFX1AlHUQkYWG6EYaL4AorC/Lhhx/KUaJer0vKqKtXr/7pn/4pi8aYNE359jAMP//887t37zqx2Wz+8Ic/dJlB4foLAFmWjcdjvjEIgnq9LptMZqlWq128eFHSNff7fcnPnOc5DykAsLe31+8vGE0AIAiCPM+5BmTr12o1mSuttcyD86PmnKjy4oIbNGSPlfd6eHj8zlGZJgD5VAJcCa2g8sISkPQorVqi3xwupXJqImMIKENLdEQAqjwi8bjtQASWiolvobGUo0iVwua5m20RrdJlRaLM2KcC4fZJQGTYprIE00k2SwojqtvphoI6OIqiVqsYVK9evfrHf/zHPJGlSTAe1O3SDozjeGtry43t//KzO//zb3/KN0ZRJ44L4oZ2vfGXf/mXXBeNRuPChQs8etdCq1VWUJNYe/D50WhWuATPTu+lk+JkkziKamJCUcOpPjxlpQgBQHgth5B1aBxSDgBxGDJzGACE7VbULRrIRhE1GlzlmWrfUrsGC84LR7bsxNk4+7f/99GTu8XMFUWRnI+uv/XWG//191nUWgeSX/bo6eHdX1GWkrWz6ZSpwgDg4gfNzWYxaydJwtQ/ADBPEqLSDIsiV07k36uoRIbyZE0rXwIc3Ou2PuX/KFRNNY9vgJd2CwdY6V7r+4QxZjqd8ke5wWDw/Plzppmp1Wo3b968du0axw/DUNren3/+Ods2ANBut6fTqVTaWAvPskx23JOTk0ePHrHIfNEOm5ubv//7v8/v6mg0evy44C1wn3rYPsmyLEkSLoK1Ns8Lsl++IkX+DQBEZIxBREDUxshTiSS78ircjYVorc1LRq8qzS0ASsuZaQVrnrUmaG3Yy0BAVZO5kkOleMp/CYTRa42ZTqaDwYLR3hhTOaXm6OiIuZ0BoNFsVDoz/3Zimqbc+mmauVmWQ3NTYgI3ubHGwLLnn9f/ZeeE5VNK6YiPorBin7j3kRN3kWV8WQoXU3YHY4zrsS4bfN1d4d8u6LwiwJLlgkWttXw9K2+rs7j4XZhOp0dHRzypNxqNK1euuOVtOU3CWZmstFEFsmYAYH9//9e//jWLb7zxxltvvcXi1tbW5cuXOf54PD48PORMZlkm2fK63S7zSFdylWWZtCcdZDYqFdtqtQrdDrFer8u6stbK7SdEJE1iRCQifpYxhse3CgF4xWo1ZTJnlwhnjMrfk2Ft03t4ePzO8TXfwHL09cPkq0M1j1gysMuhCqu7gUQgABAI6+Ul2Scia8nNtooAhWalFBCJRyMqBbAcroloaS0DAFnKsixJSpMv/wYArVUUFQNjt9vd29vjOFkaznotNnq11o1Gw00N/9+T33z4vz7mGy9fvvzGG8XU1tvsXbt6xZEVA0C9Xt/a2uIBXNk5po95Fsiy7OjJc8luOD7+fDZ8zGKj0Wg2myzqwTg4EEZveU6sabJxHmsCgH6/H4ol5nojbmwUcw00GrCxUdRkuAHN68CfgokW/wAAYDyYfVo/snYxpwMAlr+Wdfv9S9evs1jBYHpyfHqaz6bW2vF4LFWLjZsT2Zvd2nQh5vn6Ty/rUemEldeGVoxeF99NnSsd+FuBr6Y0e3h4eHh4eHh4eHh4eHh8B+GNXg8PDw8PDw8PDw8PD4/XFn57838kXrrDxm2xk795L4G1dtXrTG4nqOwcJiIZAcubANegsoEhz3N5NGuSJHKvqUtQPkVmknc+OBHc6d5ip6Lc4QnL3c6I6O5EuUmjfFgcim0kAEAmJ+nTayxlYlu10paInWARUWlV2WgkgWX/nzKKU/fOwrrz8c4NAAAAMipLNfCh8IhK+CHDyp6cdUDBpYHuwtkN5OB2IDus9hDZbYhInsSLCNYWG8uttVmayX04ZK01FtwRdknC+0tdHmRx5HOJ3A4rQVNRpmqo7BxWgtgJlrt9Kl2UI6w+Ol0Sfa3umubfABAEgTFGRqjUlduxzKLWurIxLAgCTtPtreUIeZ5nWcY7ul2QK8Jqi+Dac4ypTOu1GlOGVsqI5V3KWmuttWx9STEVBAGPOUQkH5QkidzeTEQV/9gwDPnRrnG5vVY7eSVxWtlhJevZWmuX5HmVblMR3R5sFisdQ2stM7mKNUEeryWqL5LA+V0B1wV+W4FyM+wK1hdpTdBXAf3WKSyBpRYTB8+ejzUtfB6+yi3nxiGkcuiqdiE1Cvd7KVZjAsDyIvIvvl6IRECZIWISBJsnqVlyc5CldJZkM6GVpTkYMd4aRHEAsrI2sBZYTTVG5Skstzcr0pQgaQ0A2maR2HQdoQ1BzOmUg804HTLaZoldRiBKcpMqu5gfjcmIjNS1lFY6LGauIAoCwcepa7Gu14AnEUQlKkRp0nGuNQEA1mKsFc7AEMcQCveiMIIgLLzMgpB0UPhLE4C13EAUaB0HQW2RDQQMaqHMlQqUbH2yVmpiJstMbky+oLaVGUZEkJQ0WOrd9Ooc1l8KngS/zbOhN3pfDSqqZKXJK1Yfg1ZITWWENE1nsxnbhOPx+OjoiImsOp3OxsbGG4JzaDabSaVtOBx++umnLO7s7GxsbLCi6VRwpyxi2bUgCAIppmkqfT5/9atfnZyccDqOrI8L2O12d3d3nfMhAERRtLu7yx53xhillEztww8/lL6arVar1yvIDJyHYb1eByC0M7QFUYHKlbJin8I8xVlhPGenp4Nn+zyomWmSHQ2dfwtAVcnWgG0VRDxyLdxmigbVhnRZq3ZAABltFRaJ1hq9bNKuYqSC+1FziouGiOLo4sWLzeaiYlFhq7dRaxYUC6DOsdsRQRU8zxgEURxzi1hrL168yK0JAEop6dHd6/VJzHBZms0m03TZZCbP4zgOw0UmtQ4Ojw7TrHDx/eSTjyURWrvVqtfrAGCNzfKCXKq/0Xvv/fe6na4TjTGj0Yg7szHmzp07BwcF0yObMQ7NZpO7HABcvHjx7bff5j55dHT08ccfM7kaEUnH8jAMr1+/LnvdZ5999vjxY1hQdBRsWxU0Go1bt25tLOkWiSjLMvk63717lz3wYcXE2t7evnbtGic+nU6lu+zh4eEvfvGLw8NDJ3Y6ne3tbefNGwTB5uamu+4gc+gsQC4dEclBxv2WJqJSSjo7xXEsrdxWq7W7u8tvSpqm/X5fmqPS6DXGnJycuGb6/PPPP/648Nfq9XqXLl3imLPZTDoDb25u/vjHP2Yi+jzPj4+PmYoDERuNRre76BsAkGWZZJzmhzqMRqPnz59zkR01l6NOefHihSz7/v6+a2iGDK2MbK1W6/r167KuoDxcNxqNiru1x+sKAjQQWHaDXAEuZoczsCYIXhb6kkCANWus4Ga28yes8wMwsKjPtxJx8f9sILyEeuLMWasALtebq1lHpDL5ZEkgBFVYNYtrhYhklZzS0S2scxKW1GxNlQCuaSgZ5B4p0iFcNWQZViUmEGwFUYpxoR1BnFKUEBMTBAYCeYIDAijxZFCIC6pLLNcylhgxk8Hk6LMH6XgxP06n0y+++Pz0BStphHmGQgf40R/9Ue/9D1isqVBhYbntHj9/4/kTy+QUw+T48WmWLkZjY/LZbDbPcwC4dTrf6RQL2VuRvlhY1hCPa8H+Q6YXTVEdPNCca6tMHo2tWlYOUW7yoFFkcnOnG9QLlWBre1sedJKlQTqPuVVwYfQuUo+17UV5pAgA4kYjFIQROtAkHJgxiqDR4Mo0Ks6iDi11NktghJ6STZOrSbDxwdLxGKHRaMRiyth5dxOgoLk6fb7/7O4dFocPHz/79DMzT7TW29vbmy3B87zR1JuFZW47Kq2JRYqItKDqdCu55xmlFf0BAJRSUsGo3KjOZ6s67/p/OLzR+wrgNEsWK429podV9OBKTGOM/Pgwn8/H4zETumqtHaMdxz85OZGkU7PZ7MmTJyyOx2OmEAAAKzilKieCVHp5nueSC24ymUhNcXNz880333SWDCzfAWZe1Vp3u11+qDEGEWVqd+/elV96L168ePPmTRa3traCIIjjGMhCOoZcHJ5ky8tZ8wmMimTzw2ez+3e4UfLBJHl8SNliIEBE+ZEtAIwwVEKDqbz2UW5VfobRSwClj88rICR7vhZicZ3ROwmjh+2N0yVNYqPRiBBpyVKrtK416lAXnArlmawEOWYprYOACSGISNp7AKBQvTguuBamkxJHgjUmTVO5thIGAQ8jWqnhaJQtJ7z5fP7Z7duSGvrC9nZvYwOWZg93/r29vZ3dHT4LIcuyo6MjNlPzPP/Nb34jWdlklgCg2+1KO9Bae+XKFS7j8fHxZ599JinE8zxn86ZWqyEil4iIbt++ffv2bQBoNBr9fr9iUvLvTqfTbrdl0Gw2kys49+/fZ2ZjAKjU29WrV2u1Gic+mUwODg7YDnz+/Pm9e/d4havX6x0dHe3u7rrfldFG5lCabQ5yhCGiNE0rY47kSa4MBXEcb2xs8JtijGm1Wvz0MAw7nQ7X83g8/vnPf+7WOH72s5/9wz/8g7sOANevX//hD3/I48CLFy++/PJLfvGvXr26s7PDzzXGDAYDJr5GRFM+N8IYIweNyWTCoyIAHBwcfPHFF9wQvV6vVqu5NZHpdCpvvH379ieffMKiUkou9jUaDTf+OLHf7/d6PTk+V35XqDg9Xm8YUKXl6jIUnG3ZILzEo+yM02W+Htbdu8boPfvqAqStlkRIVeA5pXXAl6UO627n6nCnGTCQ/5SuCKnyUCrtBQMLaGVyJdULkADSEvlTFee1sKoEUXmP2BqLFwAIM9LCyg1yDEUvCw0FOQXLb7AaQOVlozcoHo2O3tmJ6/pdNstO7h3PjhfcloPB4Nc//YiXaxGgrUxNVMVb3V3YvspiEEdBvZhBuuPh7uCEjd7Ri0H2+EE2Xxi3SZJMj46y+RwALnQ2b7YL3aMbBJu20MGyRM1OQ1bxcmMm4uAPE9C0bfJw0YJKqXa7LSey1sWN5o5YB790aW9vj8UZdEawxXVVmUMjZXthHioCAIgikPyFBml5/BIAUBBgFLHeRagyFdilaAkyC9zLKMm2UtO/XBw0UDlNoHYhBCi+60yHz57dKRaOR08OD5/smyQLw/BCb6sVFx88okasWkUmqY656DY2IKnSl/r5WbDWSi1ifXysvDjfBZz7Jnh4eHh4eHh4eHh4eHh4fNfhjV4PDw8PDw8PDw8PDw+P1xbe6PXw8PDw8PDw8PDw8PB4beF9el8BqMxH5TwEzvP+kqhsiJc772HJlSod0AEKr8KKWyMASBdBANBas18cAMxms+l0yqkppZw7gcuDzEaWZfLGCnGO49ThB7l0ODPz+fzp06fstVtxdHS+eY1G4Y2wvb19/fp1Fnu9nmQkcv6WLFYhayDLQeQ5m05HoxHnKhuOZ6enNl1kw6XJKWvAzOr6cgGIiCpeDTUDkfT/EVjxHCrBrvXpJQRzfuFe1OpDUuNo4aZirXUUuE5UWltr2ZnExShVSJnjowiyVpdJiTc3N6Vv6sW9Sxd2d1lM0/QnP/kJi3meK6WYBwugxGRgrT04OOB3wVEQs783CJfRSq8jS5Ln2VrbaDTYRcda+95770mfnIpz5mQyefGi8EPu9Xqnp6fsazoYDMbjMffJZrP57rvvdsSJ80opvp2I5vO56zlxHG9ubnI60+n04OCAM5ll2f379weDhSsUrDjDWGsl/VK322XWKwDo9/t7e3tcA/P5vNvtsk/vxsbG8fHxzs4Oi9/73vfeeecdAGi32xWf3oqoBcEyAFREVaa2/sM//EPnKuxQobkaj8c//elPWZzP54PBgNu32+2+8cYb/MI6P21HK+BYvvjG995778///M+5Jg8ODnq9Hvts12q1O3fuSAICK5zqEbHT6Ujfp0rF7u/v/93f/R2Lsl8BQLvd3tzc7Pf7APDzn//8s88+46Dj42Ppg725uXn58mW+9+Tk5JNPPuE3bnt7W2vNI2Ecxzdu3OAGRUTv0Ovh8bsAj1YVXQBhrYNsGXJMAABQgvPJQUQgQAsE5x7ZgDzvv5QZtxoBF/9hqcLJ0Xg+TyQ9gTzgAACUUlIhlEHg9BYyK1ohAECemTQtmI2yLJtOpzzOnzzY//RXvxodLGbA2Wx2eHjI06VCiCMVBkUpHt6/L71n82SWzwvVa3x4+OL+fVomHoHutNuqXcy2ly9fdj/a3a2G8OmNO526oBcxcZA3YlZjiCiX2m+EeV/ZeBGKiGEUSUaGuK/CVlE/zWYzFIolQRuozVWlFGpd0CFrsArmC49uRJA0GSrEqGDtAlViD7UAOQknXgArHMlRqebGhg4K3SmII70kAQUAXU/AFMxepnxiRaNRf+utt9HYIIouvfde9+JFDqptbfFvADDGyBsdmQh3G0e3KQ0WqcI5SLESRESyxxpjWGkBABS2j9a60kW/JfBG7ysAlY3e9X2ogkr3ktaIG+DOG+NWEccxq5UAoJSSXX8+n89mM04tjuN6ve7SlJ0YlocSsai1lsp6hRrXEfCw7pim6cHBAXOruneAc+6MXmkyOdWfxUajIflRX2L0SuQ5iDzns9lkOuWRNx2PJ8MhG70AJb4fTWCMqglaLEl0BAB1Qhkq8dsYveuJrE4bzXHcmNYW/QoRkyThetbWWnFOAAAAlYk6QPBayVHb2ko36/V6smvt7V2+uHeJxefPn//iF79gcWNjY29vT/ZJSQk2n8/39/eZTc1am2WZbG6OvDqSSs42RKzX6/wUImo0GnJsPTk5kcrB3bt3Hz58yOJgMBgOh5JgaTqd8jpOu92+desW97o0Te/cuXN8vORUBOC3JoqiXq8njRlHJud+Z1n29OlTmQ15DA8AWGvlasKVK1ekHVir1ZrNJtdDlmUbGxvc69rt9uHhIXOMbWxs3Lp168aNG7BiWlP5RCJ42UAhNQMAeP/99999910WHz16JGvy8PDwN7/5DY8P4/H4+fPn3BAXLlxQSjl7EgCSJDk9PXXaUq1Wu3r1qrsOAG+//faPf/xjbhFHdsV61WQyuX//PlesUqrRaHBkpdTe3p4cgqy1cmnswYMHkqZ+a2vr5s2bfHue591u11F3np6eyphQHvoajcbVq1e59maz2Zdffsnte+HCBbeY4sR2u33t2jWZDQ8Pj1eO86bP82fO8yHHSQSgNeMkEpLkoCrbrgSA7gq97ESY1VAuEa4cNZekieQiTdNUju1qoUwtsq1W9ExrzJmL80maTieFXerWiFllPXz06Pbnnw/2FycF5Hl+cnLCk6BCbGFosFAYnj154pioHJLjw/nBgnARHFXVdMrl2t7Y3Ln+Vj1e6ABRFPX7fTelNstGL7TbIAZ5qIXQrhdNphSEYSHGCi5EUC9yVWpcAIhmEBa0kUAktSCEpqIGdyKlMAjEGUCUY05AOQCAMWWjF2HJLboKIjBQHLvkNDJuYYWq3u7UamLKiAIIRCekU7BFM1lj5Jpsq1a/dn03QKWiqPvWWzWhNkO3WFMAWDDgspilaZZlrDPkeS6NXqeic2R3pdItJSpGb57n0spwCiGcley3B9/SbHl4eHh4eHh4eHh4eHh4/PbwRq+Hh4eHh4eHh4eHh4fHawtv9Hp4eHh4eHh4eHh4eHi8tvA+va8AFSdJWNn4zvvppUuGE/k3QNXR0V3hi/K3gyMKYtF5qLNYr9elu2yn05GuqkEQuBwSUeVGVeaaquT58uXLN27c4PIeHR2dnp7y7UQ0nU7Z68/t7OdsW2uVUtLR8caNGz/60Y9YrNRbr9dzfqEIoLCmyu6IJWeZtgYs8tyIN/aaW+xOYaZJ+s6Q8mUmsXQvAtQtBsJr11pLwmM2ACxOSS+B4HyXXQAgpLPvAwAAQjDnuixBW4dx3EzUop6jWm3vypXWkn4JFcbNJmjpELL4v4BCt6LlqpRr1Vgzn8+ZQwhWXIOcZyOL4/FYcjW5rsL9IY7jbrfLbqIuZU6ciKy1MvFms9nv9QDAOW1yt9na2mq1Wkx5ZYwZDofs4gsrr4bs9gCglJLe7PV6vdPp8JV2u91oNPiWRqPR7XbZXTZJknq9zpGJiEvnkuWgZrN54cIF7r3NZvOtt97idNzrKfN5enrKzu0AEASB5IebTqeSfEtrHccx305EURRxhcRxnOe5u/3k5OTwcOF/BUvaOW5f98ZxKCw68yJUa93r9SS12Gg0WsNa12q1mEwLAEaj0f7+Pr/dWuvT01P2ejXGjMdjV89EJJ2Hoyiq1WrsHd1qtfr9Pjt7a62NMdxtgiBotVocqpSKoki2LwDI8UprLYkAgiBIkoQzOZvNxuOx85Sz1sp00jSV/kiuY3Ptdbvdd955h3O1vb395ptvsgNzvV6XgySscIDpbyuNh8crgaa1XwxWXTmXoNIwXYUFKE9sJZwbAAAACKBgzYQDSG7yW8HaeYwAcgQqKThlnF9YAEBBLrEKhHWhAKAA6NwKE7oCARHJmE67YbGSS+I/pStSrAmf3moeA1CcXOkZhGBVNS0GEeYGWLUgQDE1A8CejfO48M9MbPh4VMx0W89Ooo/vhMthBxEBiz5IubHDqc1YE7Pz+WIYTGfpfFQM8mmawmSiloNVeJK1x9uAi4ksgzQ1xypbxEek2XiaqCIbYT0GwcYU13cbby5GRQDoxXGz2eDK6fQ6l25ciZbEVzrQjXrdTQ1B3ICoSAfqdZAjahBCXJMVT0oVb4BGiAMQAyxWe1IAtiABAQDZUO5mIaJjrXIgwEwpAg0Amc1zKNIJMA6XKhkAGAOZKRI+HU7uPTyYJ0vilUA3Gs1AL+bBSKuo06jFPAERzUckNBlq5tAspqfGpZ0rP/ohi02KG9TWoDDQ+sIuNAstOg8jkX3IA23rBREJ1qIoilhjd7wqrGlUNCs4izREBFbjVyhCnPrh4qym/C2BN3pfAbBs9FKZ14qWAMFe61C5sQLXNTm+E2VPMsZIw2A+n0tjoNFoXL9+ncVer5dlGae2RvnTWku7tF6vS53yxo0bb7/9Nvf1Bw8e3Lt3j28noslkItVomWdrrS7TYr377rt/8Rd/weJwOJSWgKP2ybIMEaOgDrKuKi/UxgYUfK7QuQjtt8S7SoSS4QERwvJUfN4s5bDm5VVytFkBrrvXAtnzH0ypuTmcs6GOWgeNhpKq/9rEi1BrDVnm9MryfDabSmNM9igAaLVab77xJouPHj2SLeIaiG9ptVpXrlxh+yRJEsmTDFCyIQGg3W47SqE0TdvtNo+tGxsbnW6Hu9l8Pj89PT05OXEiIkqTCQDyPJdjsbOLWGw0GpKAajgcNptNfjVardbm5qbLBgDMZjNJm0REkqYrDENpql26dImtqU6n84Mf/EDahPyaO9y9e/fp06csBkEga2Y6nZ6ennL8dru9t7cn30rHdMW/8zx3tz969OiTTz7haKPR6ODggGsSEbXW3EBEJOsqiqI33niDyw4ABwcHTM4EAO+9997777/PYqPRkDTXg8Hg6dOnXJPHx8e/+MUv+HZEDMOQa0+WJY7jZrPJNdnpdC5cuCDZ8rIsYwYXN0OzZa6UqlD0ISK3AgAEQSAzGYbhfD7nGhiPx8Ph0KVmjJHpzOdzmYc8z6XR2+/3f/CDH/CD+v3+Bx98wGNXZZCEFR5LWFnT9HhtgE5zOnfwBoKzB2cCyBeW7dmw68xPQFhnaSsAPNuoXQBtSbkvQAD23OIQQhpCdq6e8vJcnX8rIIBeezsAnckWSQBEJdomY40cfk15ekUsJUMItnzAgbwXQCmon5cvV96z69mCyss1KX9bC3OLubhkS2cuXKf6pVphQM5NfH9QKHg7D4/jn38aMjGktWBMcfs8tU8PzXQxoBljxoOB08TySZoOCpWMiNAUB0dE4U63+eMwWBi9KaaJeaayxVRlyZxmT6ammCNUVDdYLJvu3NrZeqfQvXZ2dt58800e+qJevX2rr+MzDA2yhVoCAKA1liyoACjiaiYiMqI9CRf/GJW1FSy/ZlhqMFVpWhL0UwAWMQ20QQSAsZnPjFCqkZqqyGRiYJoVLfD42fjDf/pkdLpQrmq12u7uLk9k9Vq4/b2LvdZy1iCyJ6dWEGFS2KbNguaqfe3KG9cKSlGVRcG0gYSAqOMAguKtypVNxbCRRYFpFPTaWI+jOA6W83IURWyXgnsvyiCi9UavvMXpSCL8O4Cz32oPDw8PDw8PDw8PDw8Pj9cA3uj18PDw8PDw8PDw8PDweG3hjV4PDw8PDw8PDw8PDw+P1xZnbLX3+LpY3RZf8eZiLpnVmGuglKrVanxLu92+ePEiu43VarUHDx4UsVeIrEaj0bVr11jc3d1ttVqcsTzPnzx54nJVoWABgG63cNIYDofPnxeHjztWGPbcOzk5OTo6Yte4RqOxu7vLvojWWulpbK3N81w6lE6nU+mWnOd5xR1aa82nXfN1ACAqe8us+tiIFkBapdqoyutAXy/6KwEqxCiEJQsCIGK5U5EV/jwAUK4iWjo/mcZcAAAgAElEQVSxWGuNIDAzxuDyAPEiskiHyh7pzWbzypUrLDoPUo5gjNnd3WWnDkTsdDrs4mutPT4+lo6ss9nMNXeSJLPZjHNVq9WSJEmihWf4bDY7PT09OjpyIiLWajXpOpLnufSfPDk5kZ1qMBgcHx9Ln95K9zbGcBGstdIvhYi4GrMsG41G3LfzPJ/P53yjc2CWpFBpmsqqOzo64iIAQBzHXDMAMBqNDg8PueZ7vZ70eh2NRky/BABExKLW+sKFC+46ALTb7Vartep4434QkQwKgmBnZ0e+3c+ePZNEZXfu3JEkZ/1+/9Klwq1oNBo9f/6ca340GjkvfSe6h7qqHo1Gz549W94Hjx49+vLLL7mSDw4OPv74Y37QfD5vNpvMuhcEQaPRkMm6mnciuD4suvru7u7169dZrDB7NZvN/f19x7Y1Go1kL6rX6zIdrfVkMuERcjqdSkKsNE3l6ISIlTpX5dfKO/R6eLwCEDE9lXxbEYCEFycBKaVKE9mKe7NUAuzqhC6uEDjf5yK1tWxcBchak+Sw9DU2xiZJYpnm0xgzGJDgT8nS1IiJLH/4yBwcsDidTksOk9ZMh0O7vH02mRw+f87qE2YGTyeYLlJTSjU3Njrb2wBgOtZsFBNTOp3OTk44V4gwnc1GS1vAGBMEQUHjgtSs71G0tRABbty4ISeF7rV671ZBQNXpdmv9nlr6SwfNABFLisqyIhGRBEtLRb2pAAEARQMSVHy9q81TEUk25jmhHEEBq3yBCqKgoAvRgsUKAJL5/Ohowr3u8Ojo8OBgNFjM2s1mU3KLpHPz7P79tGhegPEYxLxWr+00NksziBaOuwqVChSSAgTEUtnTPJvaQos2tkRdoZQmskSL6nXKD89rzr+39GaVRXCvoPgtRVwhzvz2wxu9rwaVTiP7AQk1utKZ1iMIgna7LbXqd955h7lVsyz76KOP/vEf/5FDK3jvvfd++MOC/O369eubm5ucgWfPnn366aeO8aXRaMRLej0AQERJz/P06dMPP/yQxSAIoijidKIoarVarKHu7OxcvnyZx8Q8z/f399kgsdamaSq5ZweDgVSy5/O5tIGttWEYuhcYy2McWZCGjKqMYwpQiwsEK+PcWsjxEb7era8KqLSqBViiapD5IMpzEiZWdZxS6OZ1Y600xrIs1UrL5jamxP8BQFleMDf0er3vf//7LH722WcfffQRE5XN5/OrV6/ysO7sMe4Mrq2Pj4+dCADDnR3X3PP5fDQaca4CHUzGE+Y5HI1GT58+ZRYoRIzjWFoUWZZJo/f4+Fial8+ePXv06BGP+y9evJAEb0RkjOErbo6XFcIPms/nBwcHXBw33HNdIeLx8TGLRCQtZAB48ODB/v4+ixW+3+Pj48ePH/PtFy5ciOOYX/bxeHx0dMRG73w+Pzo6cjZzGIa3bt1y1wGqXIvWWtmgWOa1QsRmsylnxI8//lhm8v79+5LT7tq1ax988AHfPp1Oj4+PudWIyFrLre8q1mXm+Pj49u3b7joAhGG4vb3Nz338+PHPfvYzLt3GxsYHH3xw8+ZNJxJRlmVcKERMkoQ5ogEgTVNuFAB4++23//iP/5jFw8PDL774gtt3Pp9/+umnTkySRDZ0FEWSASuO45OTEy7sfD6fTCZcWEcALntd+a0p+PAdvtZQ7+HhcSaIyJ2kgFg1POUrhoBUpgBD/nMWbJnnqAKz4BtbjqIAwflJSVBuzHhGZpF2kiQvjo+TpUpDaZo8e5qXlzLllKFODnFQ0EYOBgM5XtncDA4O5stR9On+/s/+5V94YAxBbWAULRf7643Gj//yL3cWg2pIUFhu42fPDj791LC1nKrT09MX2SIbjqKPx2odqO0b1zpbRTbef/99OQHhRcTLhbqrFtrvsrp0hjgDVlQQQalFOyq13tAtAbGq0VWUtAoqoVSiqqoyWRGApB/TAMsZMgxCJc7I0FgibRqPxw8ePOQ54tG9J3fv3h0uiaz6/f7u7i6vdOfz5Pa9z/Wk0H4DrZXow3v1dy9dKrT9RtxoBwVXolKBjkNc2q6ygLP57DQtFv0zk5X1GW2tNcvyG2PSNOX2VUrJyRQAcMWOlfOas5lZDILAG70eZwCXnwW+liaESzjR9U7WyK21+fIUE47Pv2FpMbKotXaLOk4kojzPsyxDxEo/Bih9pnA6KIuVyNZa+cGExLdZFjk1VwkVHV2+URU90mGR+BkhXxn4293+HwIEQDx32naDfqW6ZAeg5To4LcCXFyuFS3DnPBOr369kB6g0n4vAY6hrd9ncnJNlpjhXVorOkOOnuC4q81zphKa8VcHdy71OBjnIPLvfsgPLICuOXJI55FBO3D1U5qqybWE1zzLb7rdMzaXvRPdoFuUspcrfN6y18gquGL1a68okJ+snyzKphCVJ4oYIDq0UqjLmMKy10j7MsizLMs6Vo4tn6zrLMtnNSBjPfEWWsYIgCOQn9CiKpP2plMrz3C2l2fIBWqs9X0ZwD+UI6/PgcF5teHh4/DsD1/Jgf10QnLFbbBUEBETAg4Yb03m6NMbkuVlqU0SUp2kuVvlVlquyclUeUkozjslzee6GRZUiIC7G9iDPAUC5oR41CGtNBQGWzyl06S5CleK/7kcYBFKTjKJI2lQQIUTn18wai+i3GS0RfrcanUh8zahORHJad7+lWJoyLOVZxh/qAYCCQM7FlfjV6cblwv2tlH1lbirn+Qz682ri/5lwfo/08PDw8PDw8PDw8PDw8PiOwxu9Hh4eHh4eHh4eHh4eHq8t/Pbm3zncJro1eyQYlR10iBhFEe9/aDabzvHPiUmSDAYDGd/t62Px0qVL29vbLDabTSP2iPJuFvcU6TkclDddXLp0SbpwuB0dLNZqtV6vx8/d2tpqNBrs5uceJ/d7QHlzZhiGHBkAkiSRJbJiy6giVdpfRCu7l9bv16hUfzly5dZqW5VPQS/jq2x6+mZYnzKiVrDcywQudmlLy6KpFUAQhottTgC1em2zvzkW5FKVXtfpdLTYktSoN7a3ChKLSxcvvvHGG7wDdnNzc3t7u91eeJ5orRuNBneGNE13dnbk3vhGo+E6HioVx7FdPrfeaDRbzVZrcTI7EfV6PelcKnfmA4Dbmc8iEckN+f1+XxJfNZvNzc1NTq3f78dxzPGDIJDETkS0vb3tvNBdIjJl+btWq8VxzO+jtTbPcxmh1WpxiQCAvdMdNjY2wjDkmt/c3NzZ2eFturVa7fj4mFOr1+uckzAMpW+wbDsnytcTylWHiHEcyxdwb29PMo29ePHixYvCqazf74dhyLe7t5XTdz6xXKg8z09OTpzDRWULXBRFYRhyx2i321evXmXXjF6vd/Xq1X6/70Rr7Ww24/ZFRMfy5UQA2Nra4uELAHq9nqyEOI63trY4k5PJhHmw5HAKALPZTBIKhGEot2QrpTY2Nlh0eeAG0lpT2e9D+nF4vPawQOdPCutGbgRQ509VuDIZSVS9WstAWLcVEwDsORPZgi7jvAcjIECwJGdaBZaYJ6pAhDO2VwoQUNX/RIDQwML9FgGW/EiLMCmsPMVWI8hmUUQlp163J5mHkTwPZxNrF2MIWlK5UcWYQzbN3KZlk+epdP5KsmQ0t0uf3jzLJuMxjyrW5NlwYNLFTEREyqQhFLfnAaRxoQ6lcZTVilE07/bp8i2KFleiRu9CplrL0Rut0nms7HIIiuNnGzcy2ASAeYLTWTHuTacbp3jZBIvnToJ63NnuwzLZKNze7jcai4FOady80mj1i1zVLjZNp6hJqpPs0IhLzWMpk9b8dY2w4J9C/rMUVzQYIVUa0zlviUuVyNUOiaUPfBaB62kB4fFjFBBqWqSBKDqKylWQF0/Vs1xNZpQv+kktyTaDoLZUaHtBsEHUYR8lY2eTeTooZpx6d6MZF4q3yvVsWszdyXQyPBH+3jYM8rp7gfM85z4GAEfjo8G8YKM8efw0W/oVA8Dg8OjBw4es1Flr9/b2eD6t1Wrb29ul/eqi6l1rypbAssdvpZGkMlntCd8aeKP31aCielYae40yJG+sKKyIyOYEALRarXq9zjxPSZLUarUnT55whF6vJ5XsW7duSWMVACRHFLvYIWKr1WKNEwC63a5UMVutluS1mk6n0tiu1WobGxtSnb1w4QLTw8zncyLi5zqrW1q5jUZDljFNU1khxhh3BQEjFWlh4ykxQwEA0nJmdLClUawy5AEAkBgx3UC8bDEEgLJyQXLYq+C3equxOk8LLIzY85NHFWC1kEJYlkgR6Sjkx+g4evvdd7Z3CvrfirJ+5erVKChsswvb272Nwibs9/vtTod1/Xq9vrOzI4msJE+S89VkVl4ASNM0y3MA0EGw0evxa7K1ubW7u9vb6Dmx2+2ORiPZJ6UVBCtEVnKoBYCtra3NzU25WtRut/nNarVa0lQLguDatWvyvTPGuD6ZZdl0OmX7SmstreVGo9HtdiUTUr1el7lKkkSOA7bs/7y3t3fx4kVOrdlsbm9v83t0enrqbEgnRlHUbrddaKvV2hLLEKtTy9cai/7kT/7kD/7gD1i8c+fOl19+yWJlOUwpJX16e73eBx98wEsGk8nkl7/8pSNtdpXMN7bbbbkacvny5Z2dHc5nt9v94IMPuLmNMYPBQLoWO5ufxc3NTdleYRhKG7jT6fR6i44EAOPxuNfrudQuXLgg7dhHjx49fPiQxclkcnp6yrna2Ni4cuUKP9eNbDxYWWvTNJUjqlzs83i9QQA5kjl/9C7U/DIQQBNWl2slyvNaBch/zgQClleGK8gVmLNCLUAuZ5IykKhmKTLnZ0vZdXY8EDku5LNAQBaI+ZnPQo5oAABBaVBLUwRgybDMopjRAQAwJRL2SXWmzklnItQYyHOuehoPo0d3iQlTTI7DETAflbWzk5N0OgOAyWR8enLK+Z9bO8hzI/R+pcVyrVa21aBoOZQhxHEciw8VL2o4DAoVbrzRHm8Uo+j8xpvmT/93W1/oZp08/8Ffz3nom6fq2Uk4TRb9zhj7i+F4Pk8A4NkgvfeoIH+x+UYW7IFeZHK7H/3o/Xa3vchGoxHfunVxY2ORDVTQ6KmoUdSeUnEq57XYmqCY9QKlQ1EiAmUw5qaxZDPKLVgAQAAlOqsCFaC0R1CGUqV1AdgqdVBYejOULb8HqvRCGoRlPQEAgC5ZQoTKYChpzBhhQvVR0e3io3mw/wKWk/7GcPq9uJ61F0m3G42bAF3m/0/SO89Ph08W9M2IeOnt/t6SmBYA0iQ+fl5MKIPB8EhwviqjglQjobV2MpmkSRFzdPJ0OizoQr/46N/G9x6zeG8wHR6ecP+/efOmUoothX6//8Mf/pBnTEQMytxUctEcALTWcuG4Arf0T0SIKJfLv1XwRu+3CBXdXSmlBQmNUkp+akiSpNVqSeu00+lUFE0ZmmWZ/HQmHxSUiQriOJafktrtNlNGu1CpvtdqNVbHAaDZbMrPKe4Hj8vuZai8UfIVWl0dsNZaa3GFmxHKQ151UMSVMbICGUqlgY3c/CivnP/mrn/I+fcx1kZZX4rKML+CRccpDzxBEDgeWnlFVnstjuUdURhGom902p3NzU2+PY7jZrPJra+1bjQa0uhttVqSa204HPK9gRgTgzCMoohtBmNMvV7n3uveC5mr9b1Ifhd14C/M7ncQBJwaIkoaJCJqNhffnGezWYlaUylZV8ESfKNMFgBkiQDAiHMCAKBWq/X7fU6tXq+3Wi1OLU3Ter3OVReGIQ8FWmv5tlaq4uuiMmicnJxIUSm1pp6jKOp0OmxGaq353a9MjU7kK2EYNhoNrqtut7uxscHGszGGiGQZg/Lek0qurOA8g5XEAaDZbLr4nU5HrqScnp7Kpk+SRI5srmPwEni9Xo/EVhprbZIk/Fxc4cTyeL1hgVgtXsWaFxIB1hmmqzuYXh0IzjqqBxZUxuc9VgECWbWme9Pi/5kgoPJH1SoI7BqjF8EubydarbrSPF5OxBLKr9MV/dsQ5CJXxkBWGL04T2A8hulyC0yew+kpLNUnspaOjux4AgD5aJQIDv852Yk1vBqilJLrpBAEFFjCxZiDiBgqLUuktBGn1OS6JNpanbqbtDR6NUBLFCpIMayFar54lsnycfr0dD4EgGdGPZrJNeKAMObHRnGoe83GxuJBjUbc2e1u9AujN+5AWAyTkKYgjncAG5AVXdYqPhwHYNGdFbevBTCwONFJVTsNSkMVy+8BQakPYfVeICj3jEqMSq/BlRdBiARA7jVdAVqrRLfBzGCa4XJaD3LTUMrwartSdYAadyprIc3NvNjBpC3GqpjmMouZWIiZzdLBsNiEpXIMEoUE1trRaCSV+cnxi9mgOL1iNhiZeRE6G09OTk95Qjw9PR0Oh1KBd2Yqxweo6IwlrAlycNqa+1EN+3ZgzeDs4eHh4eHh4eHh4eHh4fHdhjd6PTw8PDw8PDw8PDw8PF5b+O3NrwD8Qd/BbXXjbQAu1EVQ5f3x67G6PUBu6guCoN1uy916nU6nQpxTSUHeHsdxp9Op1WpKKbdzj4MQUW4X1FpLvz4iYn9gWG5w5c2HLkGODOXKcVtMZQ04HwAWjTHy0UTktjIi4Bl0GBXxq9YrAJR3vyDAeoYQ+pqJL/FN7wNw965yh8hcVrpHuQBERG5DL6LConiIGIWR3NWpyz69SmveCQwAiCjbKwh0o17Pl73F7eCV25u11lotOoPV1u3adSIAKKXqtToA6EDHYh91u92S+1cRUd7ouoHkWpCepbCy7bbdbstNZW5PMnfCer1e6aIV1Ot1t9U2jmMtakOXfXprtVpN0GURUeXFabVacg9SZRduu92OoqiSSa6QIAiazSa/Gm7LrnsNV11l1rSXgxwHVkMl4jiu0HqJwMUua35ct9uV28hdyu6WIAiki4TbMc79RCklSyGDAAARtTjrG1a2N1eKoIUPCIt8RWtdq9WcKCscREM7yE4CS2oDHhhXRzZZFWdWu4eHx28LXPBkVTc2A4AtNpgTkZWHexPQLKe0xNQgx0mbGhI7fm2eW0GiqYan4cEBLrc3ozFqMoHS+bqZS01rXW80eC5WCo1GfqrSOqzVmEUSAk2bXagXk2+tXg+F6pUdnEoewfF4LB2R8jy31nIprLWSA2U8h6NjGhQ7svMXL06GwxEApGlp9oxjbLWKwezSZtDv17sdVuHCKFbLORxQVVUjRJADISkkEcNtS2Z5yQ+2yCQhIaFC5WKW2nSleUsgsETA7W2BTGXXvC1CASg3JKieKgpDpiDRlecVogXKaXFkLiqlROnigZmcFN3mxYsXw+GQp+lsMkuTxKSLJpvNZsfHx+yjlM6ng8FgPBk7ERFPTk7kLHka5wNduFOdnJw4ggyHiII61RQgEc1mM6k2u47BIgJILlKNqqIBchBf4Yuroat4qTpx5sVvD7zR+wpAKwRUUn8iojRNXaeUFgJHliIRFSNvWQnDMgVUFEXvvvuupKoKgkAmHpbJSBFRDnyOZtla665LDzpjTIVF5urVqyxmWeboqZwYBIG0BJxhwJFdzfDAba2lsnNmlmWSPHYymchH53nuzCogUJmCoo4BYGWUlBopLv+tgQjFcuTVd7as/BdY4+4LACiH4a8JJCKT09LuRUSs8AdQiRgJlZJzkcnzLEvBGRhxzAO31rrf77c7BXmY664sKq3TrOBICHSpUzWbrWvXr/MIq7UOw9DNYQCAiNICiWy0t7cnHcKVUv8/e2/2bMlx3/l9f5lZdfZz9+7bG9ANkAR3kRxKnFE4/OaJ8IMj/OS/0GG/2KEHv47DEQ7bI81opJEoCQshgOgG+jbufvZTS+bPD1WVmVXnnrrdQIMkGvkJNnjz1JaV+y8rf98snlU81PZ5kVL9nmv94zh++PDh8fFxESxqkF/FioJkgw0bSdRtYCLyi1xhBdlgAyKycTbG+GOO4u1sUErZ6/X85zZiNRwOHz16ZIONdFZKxXFsI1akpA0Oh8Pvf//7VidJCGENsIbRa+rTRkIIVXct9rtD1HssbCTO3bt3fWG5hhBA4+ZRFPke3VEU2RQbjUZPnjyxF7777rs/+MEPbCOjlPKnHqSU1u22oPDKtsHC2LbBPM/9V97Mff9Wg8HgwYMHRSI0Grr79+/7kldFS9Xestl3F0L4Hr/FL/bvQCDwWhAgUQlY1mwkY5BlpXsowFovZrPUNlaM7GKaz52cxGKx8Eca2Xy1virNDwBJkiznc7ebwHx6+PyzOCkvF0QdKa0hQURRry/jGECv3987PLTR0r1uvr8L21hFkRgOYdscKbA3RteN4kQcC6/t+i//+//x13/91zaYJIk/HJrP51maSlVevlgsTk5ObPt8Ncv+5rdXp5dll2GMmU5Lz8/hzuPj458WvwN46634L/6i3+2WrzPu0ruHoh9XPZEQvZ6vZQkha+MYJSG9pk5LoaV3NhF7pxtwDmeeEkiRKvKRCb4wi2hddmqMSbPc2Ow2rFe5NWuZOcsyq7YNYH49XS2cTvJ0OplMnL6xjqSOlY1koxPMTb7M5zlrAJ1OHEUuv9TZOnrhcuT87Oz3v/+97WFFZuJFbr9VXFxcfPLJJ/aoydPJyafraTmpQUTXk+vdsRNWfL4XP99zz1osFlbJEsBub/xg754Siuq7ugDAem5nZAAIUD9yHZOKIun12kU/1T58aunLGoMc2hBzFkIUg3w/Sf+kCEbv66ExlPRNO2Y21UeexgB0k8Z9GjTG3P6IbRNdF86RUjYu3zb0X6/X/ki30+n4Z2qt/Q+/ov7RZpPi9Yu/iwrjn9ywKxoTcswsCgOGgazW8jYNSkLNxN0MtlDMgrWf8weHmckY16kTob5MgLlN6NOw0XkOgKVU9Uaq0+1EpqaE5N8211p7nYcRtRIbRdFQui+3RRt3wxw8gMpUq88xd2KvC7E0kr+40PvhhoLhHWxO9zRKvtiwA9sZDAbF05m58aCWzmCT2NvdBxsV0BjjtwZFStpgFEU7Ozv2ciLqdDr+O/psxtNS/O4fbU+HXq/n1+4kSfyRYhzH/X7fj2fjFWxlj6LIN57H43HxWbgIFtbytsSk+tQJNoxe+5SCYvrABhuUDQiAjaLe7/f9ifYGjac0ri0iaYOBQOCbYXuDZQys2aN1niSpFU1kTmazbOLM2vl0Op1ObXA9mS/PnRW0Xq+n06mt74PlTL541k1K80bW5zdJiIGQpBQApdRoOHRxHA5x5wi2oY5jjMfO6FUSO0Pf6EUUOQsZSI358ssvbbDR5uR5pr1eI03T6XRqreKr6+Tk5MXJWZkCzGy3PIg6x36rfnDQ/d73xv1+2fz2Fe700GlpzOrtdE1VGWBB7O0kxaiNyxhoCJVJksWA4ZahcB0GtDbO6NUmy3JTaUoxc5Kkfqc/nc7nU7dtz8XFxcWF0zc2sTLdrUOgzKSzbJqbDECv1/MHMPLFSn7hOsSrq6vLy0ubI7GhQS5k9SUkTdOLiws7lmadJdfneuViBcZi5u72dCqeXrq0Xi6XxdaJZXC03zVxJKPNYZXMMul3VYCyX+oBKeTLf+ktgt7BG7h1ONG44Z8aNw87AoFAIBAIBAKBQCAQeAO4+dNB4JWg+qx/Y56j+BZaTBO2f3EqPknZYHGflvPbIaLG3byDbTQi2figsfmy8OZ+Np9CG1uq+J+/UL8kjmP/E1+e55999lnx2UdE3WJu9UZEY6FxPRaE+q5uG1/FZOE2tAVuflmsIBhCcy8lj/ajjA3dfA8yUJkv208kGlOs9Y0evMk8AEZrrXMU+TWbUfPrXP1K77baGMNu1lCQcC5JAIPtGjAABFC1trmgPsvLuu5JJaX072Yh+Dsw3oCpL6rZ/ADrl7HGNzoA4lV86X0aD3qlmzTi3KgIzNw46t+cmXNvI4Gi0t34adR4c/+ontK4VXvS+Sc3XtD3TQBARJPJxJ5jjPHzd71ed7vdO3fuAEjT1F8tMhgMZrOZbTeklPP5vCUxtS5dqgoa+dsoVKK+mn0TPxnrR9oorvKvfaXL8YqPC3w1/HzZrHH27yLo/7JZLxqNhn8y1VcfMKDZ+FsWNaoVodGa2eO1025lM8715rexyIa5+LTmhf2gETUHTaXKYYmQIopjqr7XEYhsACCAKcucpyokSb9DITbwk84Y+N5ezMLzrgQALxpsDK0S5NX5zFgs7OZAAGi5xDpB5Qll8yjL0uur67Tyn2RjlstF5u2bDa5lAtd3XYq1EX33rWzQi/eqnWkBdFW895v/VslyvKGUHI26cVx96SWKBh3ZiQDEcQxvtQhHSvdi++WTpJL9vvVLYohU9HQ16tZa//afP3r2hfPb/JsP8cX8hzYYRVEcu0j+198N1v/z36pqqZQqnUTKBTU5D77/g/7j75UpKQSNRnG3qwDsHOzfue9ayIMDM95bRlGVBVp/uUzglnc1ipxZzmdJ9dEbwHK59BddSymUt68SEdUGG1rnmXOWJoBQLg2bzxbLhVt/vl6t/VVFStbcf9Ismy+WuipIeZ7PplOb3USklPIdWVerhR/n+Xw+m7uvpr3dg9HdB/bmxhT+iWUkFYuhVjETgMV6dpW60ijPruQL98U4XafRbGXfLh71ug/3i4IBYKT6j3/mdnpnZpOtjXafowf9QcfL3+uxmla7JaOozN5IbNjtHY3HUggql325L9WpSVN23XT6f/6Hf5g8s8GH945//IOf2Q70yZMnv/nNb6xgymAwGI1GNw4tboQ2xvONZtNfV+X//qfDVisi8PJQ61I3qvvitlBU3eavX5WXL8cNlFIt0WgU+kbJ5vrqZWwMWBtji8b5xbpHG8zz/NmzZ8xMQqj9sRy4JToNBLPclH2qkAax2br/IQHKcMs+hMS1kYSFCVpwi7mcC9bihgsLDCHffq1gEedKbL/7ttf5mhguRk5b2R4jALesWdp2LWFjN/nAN0O7PbnZpfmYaut5Gyz2trXBOI6Pjo6w4XY7GAzardw3DyL6Tr3vH6B4ZegAACAASURBVAtbgJm5UbZfqSdq+EQ0KoIQIqpv/c3M/rOawcLe3DjKgKHWbWkF+cvvGtEwbHzfEzTekdkY7T+5ESvV2JK92y0cl+I46qiB9FxnreMlAAZrJBlc4kBGSnijc23IN2vzHL7xqZlSb36ACEqhijblGtcLrKvzjcHpKbx1yHxxhespgGy5nJyd2TxarFeffXmyqNYzc+nVWUWDqHO4H42dHWudVgriXqczrKlIDAYDm5hy/7j3o38nhqW/ZRSJvb1ux18BHOWwjj9eFhiT57lTPBFCCBXZeWGjKZlHWVreJ03Tv/nwr//jf/xtEQTw/kd4vnjPBnu93kC5OJ/9K/7ug7+zCXn37t1f/vKXznoZie/9pDPeK28eRfKdd44ODoYAOoN1f9c5uDKzNi64WqWnV9MkrTkE2aQwWp+dPJ9Pru3R8/Pz62sX7KloULkZA80vNybTerm20iQ+Zyfnl6dOtevy8vL09NQG406nP3Q5kiSJLxmVZsnZ5enaOl0LsbOz4y/hNpQbTwMmTVMrkAHg4P6Th4m2+ZLneeLJmI3RfZfvxugAuHxx6q+Llpcv5PnnNhgh6qBja0rn0V73R4dyXJqjOzs7P/nJT5wTIgmKu/D8n+3HsAIed3jsUrLb7freN5HkXqSL9GjMgF+B3Dp+4F/mJ4u//Q82OHp8/Itf/lJVFso777zz61//2pcXfSUa/RpvOAG1mEJ/Imwd3wQCgUAgEAgEAoFAIPBtJxi9gUAgEAgEAoFAIBB4YwlGbyAQCAQCgUAgEAgE3li2um4GAi9D4QjR4r3muxX5/kUFDR+AKIpqjhnGlG5aRJkQvs9VA2FqzksN2EDorS6jxACb7b63ADPd5IX1NX16NUFvv1YYEhotPr1oVX76yrT79DLQ8lQuTtjOtsuJbxGyCrwuGmI/fvUEIDb2Bm9Ubd+ViIjiOPZrt5Sy8PDRWmtPzKbT6eR53tJKvHlsJl3gG8Kmc0PhrJEFUsqX9zdjLrRtXBBe4S+OtvU4vmctPM83goHxG/VGIdn06XUBAIRG4+yfwMysncs9bqrsfv1VShXvqHOR5blNOkECsnZnIrKqTuUJHpxlZu3EftLVaj2fu6euM0yXVunKGJN4z0KWm/MJLyvNIebk/DyfOxfFgeaeZgDM7PtAyjh6u9fJPCderRTbtyNSd4/k7rgMAnGnE3u7vFAcoeftvyqlL5skhrvRXp+qXW2EEADVigM0RF4c8jfaJSIplO0GiciXGjPaTCbLRZU2aZqenp77jqzzhScXBmS6tk26irqj8ch6ovZ6PePt+Lhc6s8/P+tclmMkIej09PNeTwEQ8bXsuZ2QtKltSL5apWen07Ty6RVCdL39mYwxq+kkXTkf4MVisbJbQwHjbn+n57meRlG323WFRxskzs+c6jqL/mBvPB77NW4wHO4f7FvZS1OXk9BGL9azXJfvLqU8ODjwPWBVRwjlpXxdAa63c7Rz9y1UWdO4eU9Hd9ajrlYAPn7/d08/fWov1GRyTxBr1B8d7R5Z0bfBO3fu/PlPo90yGr1+/97Dh33nSU4QCpXnPDZ0PXmgzMCVpSiKfDEgJbSUVAxEiYSNPPy/AFSNVWAbwegNvAb8atbop5nZHvX/LmjIHlBdyoursYIBX+XJ2pfHqHOrkBVahazMn6SQFXJuMXq3vc7XpN3oBbaKURV4eiY3sO1aQhCy+gOxWQH9CivqSsjFGMUP+kdlfVN7eBW8UdN1XQX6uwARNVrCwDeBX+Q2haz8LGjIxggh/LLdqBe8IXPVsIHz+s7hjWdtNXoBQ+xL+vui0ABQG80C9YgJIYSqGZy1hzKb3BkzmwmitW4YvVWCcJooKctDRGQiY88kUEdK5V3YwCSJnrg9b+fT6dnZmTs8neP5GawEUZpeX1/b1oDTLH9+ZualTcXMV1dXy6UzsR4e3rm7uw9gMBgcHh5aLVzZiR8d7itrx0qJvT1YI4oID46xX2kIARA15WpIgmwmtPtbReiOUNn5bJCl8Bsw1hlTCkBFUewXKqrZwA1ybc7PpufnpR2bJMnTp88/++wze8L1dCdnt705MrB2sdrZ7R3sH1gzqd/va62tPtMqXXw5/Vij1AAzxth9ejM8S/iD4ncAWZatVk5zeL1Kz04naVJmkIqivf39TrdbBAmICJ792Czqh+OdO7v7Ntjr9UajkT1BgmIu5ZoBCE8QTkL5ckpRFPlW697+/qO337LdTRRFw+HQBklAOIEwKKWOj4/HYzfHMRj3up46t4xj6RmQGiojJyjVQCRQFxApAOz9X3u92Fnmc8b0zBX1e/fuvffeezZWuz9+9OS//8vuYRUNIdDpuH2YGcgZ/jCVajtu6C5pF2UQyJ8xIWQSa9w8Nmv+6Nf6RssW2NqQBQKBQCAQCAQCgUAg8G0nGL2BQCAQCAQCgUAgEHhjCUZvIBAIBAKBQCAQCATeWLa6HwQCfwCo7jTYcPG1MFiY7oi3eowKLjxvb0YwVKtPr2Bunf5puGhVEIzY6qcKIBdstj0VMGgVsmJSRrb49AJb36ig7crtcKsPSGt0gK/j0xuErP4gMLOfwQ0HrYaLb+NoI7iJ70/YcCvyHSC/I7SnVeB1UZQ0Zt7UbXInAUop3yN906e3UWj9uxVZaTOUmU1mfKdfEmT1bIBCbcaPCZhN8TsTW9GEokLVyglx7ULDxuv1BEHW6yP8hzJz7jvxsjGGPR9CgZoCVUfGMQsAKkN3ntg7EUhiZZ9DhsU8Q+Lqr84yrZ2o5Go2WU1LV1IAi+Vi5bn4cpLo+Yw9ISvSRtnPLVEU3ztE1Tgw0MuPtZewhwcHO7t7ADqdTndnx3l1RhGPRrpy8YWUNBggrnwiCbQzRM+5SDKh1sMQ/MQgKvKiDBoSOekiy4rjLIWf1IAkxAAMyywlVHdOE55PYaqkSlNzdZVkWXmf5TL98IOz8/NSpivP8i+/UPnqbnk2EEkxGrl3N9kqz5ymV9ShvaORUmUKdLvL0a5WqkwBg5XUE82LIsjMsUqLbJLRUHV/UPwOW6iqcpFlej5LdF4+N4qj/YPDbuUdTUCshPLfneD7mo6Hg72R80OO47jX69njgkl6CUdEUilR1CYWBFcf0yRZrSs9M2BnPL57944U5QlSyW6361dY8lRAhBC98TjyXIJFHFmXbAAg6X/hI7A0nioqlf8KsjS/ulxkixzAFxfnX0wu7KFOTKO379ngzsOH++89thpv/bcOadAxneqlBLFiCK/+gsh4VZBqPr1ERngDKIIrVwCITdF+2F8sEcu+cSnZzzr91Pkhd3TsF9zADQZGIPCN4g8sGlauUsoXrCMnnEOSZEM08pVor/btR7ceJjBtNeQAmJtt5RIGzPZriW952+2XAtjUQ/FoidPLsPW+ZZPccvtth6g9woHXR8MwaHCrneaf0Byvb6fliYHA68K3Qpm5IebcsHJFXbOtUUS5LmTVhEE5yG++JZEvjFRvztj+B2DUzFr4w14A0P7MYa5zf88CySYy3lMF1Ub2DNamppRTeylGklNlgAGA1oUkMeWaFjMrsAxjKEmsIYpU00enOCutKYDTyTTxtKbO15PzlbNy8zxPUyf6lHdoPRJ2UjmK4vF4FFemmuh2uj94S41Lc4WIDg4OfH0jub8jd0YASAihlE0tJqFFlHudpBDuKAAhu/DEigwbf/qADbE35SylUJFLSc35Ml9b21uQiDuxNcDARHlc5L7WlKYuO6/P+PcfyqxSXL68TP7hH5eT60prarX88IPfnV9UKl/M80U3Wf+wDAL9vbP9fWdiXU+uL85dsDeaPf6+iSubSinV7/dtkdYmX69nOq/pBRYR29+5e/foL+yPcRz3+wNRmaJCSCU79j5RFN25c8dqShFR3I1U5NcU2MIMIO6quFvTIvU7heaQwDtmAH8aIknStWf09uJ4POjb04ngdKsAZqOzzM5KECCVkl7tlgK1WialL5ssjCaTuGgRwbt2tpx/+OnTycUSwH/99ON//uJf7aH3DvZ/+puf2uD9J0+e/PrXbgS7F/FRP++Wt2KAyXBVnQkUyViyi0b5c4UQmthV9nqzALBGafc26efdnieBtb8eHSx3bXDgGcABBKM38EfHbyK3jUsIpISSXrP1mmk2MHW2HS0s3m1Hy2Z9K9z6XbS48fZ7tx0CQNjuutASp5dh+4ObPdwG2w4Vsd1+48Bro93ovZWGlevX1kDgjwsz+2U797fGQXMVQ8PoBWp2761GrwD5Ri+puhrw9uaMqa2NJAi/W6jFGFDGRP6mNkJASmfpMQMC/n4BjZqeAcK73FRdkGFoA109V2ukuTN6kxyLBDO3Sw1Pl2ZhbWDo9SJbe0GtjWeoayPzjuIqcQQJ39YhErITyeqTrBCiMxr0xu7LIe2MaGdYnApPgdmAQIq9Xo7JqQQDYEh/9yc27G+0wEzs22ZUaOWWv7AhAzZ+/0x+hjKRKDpYZjdXAEDnlCZIK9tttaTZxEyuyzNWKz25zqbXbheiPCc2bpZfoKb9LMgwnBFLIoviLIrLuynFUiWuBdZayhxcUxQv/ohj1e/ajXPQ6XSGg6G9UErVibuiMunjON7f3a8Zvb3InxFodB+qI6Lu1oEZA9tW+Jj6+EfGqfCe0o2ibs/b+qgOG5MLsssHsFG7QY3K27zPxsJAv+6bNMuKvULWWZp48whakPKWD0T9bjTwtnfqyVwKrmYTivWBtb0wqPx3M4Qbt8a8FcEEb6miZCG978luwikAoKi3gUAgEAgEAoFAIBAIvJEEozcQCAQCgUAgEAgEAm8sYXlz4GvRWH+yuRyl4ePRDjkn3jJoF+G8/E0CgUALr7EqveRK6df4xEDgJfG7jyLol8P2Mnlrt+XLVgFtixaBYpkjA4UARG3hZftTQPUThPDXYaJxLTN07nx6mdl4shLMvFhz4tZqpqtVtl4DMOtUT6acV2pSWuvViqvlzSIzvatptPAX5XoiQECn19vpu17bSJl7i3R1XyZ7kV3zGUXRcDSyK0JFrDr7+2pcySYRqX4fHbeCFEqVilPUeN9CEMxblVpfGtpIGyLyFz+TIF+8kojqWVhkf/kLg1drt7obhrJlrBMFYLFYTyZzm8aXp/jkI7LLmyeT7Px8MpuVyZWmiVRyMChXGhPRcBh3Op6mSZ9lz72FMWa+cEJWe7t7Dx896lYOtEopX9uJjUmTla8XaH2Yd0fHdw6O7O9RFPX6/UJNCgCRVDK2HrNRFHW7cRxXGUqklJD+0n2Q3+xb3+Ab4Vp5BRqp7P0tBUWVRhcAKVs/yBX1ol6d/ZoiSJAvCrVZy7xfmJn9Is0cx3GvZwAcHBw8ePDAHjm+f/fw0X0bHB7tUzdCNWRlRQbGX0UPgi1FfvErafSexWrobTBju5Jr4OUJRm/glWm0II3mpoF/tGig/RazcW3RjttgARGBQear+TsEAgGHEOIlLdUbaTg6MnNL3bcwc/D+DXzTtPdEqPdcm2c2fmkvsQTfY/QWmFnnDADEELWNBKSQmzGxiLrQo2D2nfcAwDdrtcFqDTt8Z2ZPj4oN5+dX+cw5316cn19eXgJI54vZizOdlnpLRuvVcqmr+ygWb6fDvdy5nva6XV9v8uDO3Tt3dmyQ9/ZwfGyNCu4rc9CxDs9EJKX3yhJiKMnqyxIppWqOrR0FG/TTiaG1qYl2iVpbRDB+uoq6xy9ETcqaagZUEUlhxxtZll1eXlqZJaPF5cl4OekCePbsi/ff/8C2qJen9Om/iLSaH9Ca12ujdXlUKbG329vbLT2WpRS/+MXbb799WJ4NXC4+mCw/scFPPvnEn1/48Y9/9O///X83GJQDJCVVv9sX1jhkZqOtbBIzp1mqjQbQjceDrnsKEQnhrFhjkGXC2lNCUH+gIlXdlgjC15AC6sYai/ZNJGC82QgCbDbU528QKxX5ei6tdZlAUkjfK7vh0yuJhV8/G3cighD2NdiYbL22QdJmb2e3ozSAn/3sZ2+//ba97snDO+89cUZvFMei33dFPc5zWttCSSAllI0VMRGj5gLewJimK7KfAsbAmDLNGuW13qETmk1ZwCcYvYGvBbW2TQWu2r/EmTcPNQg3zBkGAoFX59ZquI0breUbf2zwlZ8YCHxlGqXuVQvhLee3HmzAbiO4St3GHgLf8AmoglDvXgk1o7dR9ZhhtBOgMgZZ5j5hMZv12niqy8l0ury6ApDMFtPzszwpjV6t9WKxsOZWDHkouE9OCSm2GwUBAKJOpzceu/D+Pu65bV0wUDjo1lS+fASjY6C8F2kM6KUTr6qnG8C1tqfREG3uqlDPUPKzcDOrich96WVOs9R+7NW5mM26s2sF4Oxs8ezZuW/0PnsmrdFLFUWwE0cH+0M7ra+UPDraffjQfYOVl6e4dnLNg8Gg4330Hg5Hd47uDIbl5ZGKet2e05QudmWqkoiZ1+k61zmASA66kZPzbaA1kpXThBICcUy+xNutap3bpKqAMkLbeohafhDZT6aNQzfjfURFldRe8GXu4PKXjfFksTiKouIL/M7Ojj+/s390uHPHTR80YGUM3B5jxW4jr/Clty2pgI2mI/DVuMnACAQCgUAgEAgEAoFA4I0gGL2BQCAQCAQCgUAgEHhjCcubA98gjeU9mzDXlijdtlSy/ehWGLcsl2k/YfuRW9jYC65JmzcMEQj+7u2vBG1PrFvu2B5nuuV4scSqha1HGzokgW+Glsr4MhDVVExenq921bear5nUgZfBL1evmuBfp0ze0M75D68fJNsuMsOw1+5ToVfhTjUaxt9K19SD2lfcMVrnScrVckqT5flkylkpVcXGmCTxlzdn1xM9d8ubV0mSaw3ACKh+T1SLlg0b0eta7/2IZE8dxtItb1aDgew46Q1xMMaOO4phFx3pUiOWLOubGPuJIwBR874EkZ+UDFEpTvkunGA0FjATiGx3SQCzMP59jFP4AmB05WVdHGVjkxFAkubX83VWbVycJMmLF6vlslzebLSYnKnVPAMwny2SdWILUpYZFjlkGVRRNByOomr72U6Hjh+o3d1yuaxUYu+QhmOXv921jpYuKGSq2eUXcwoIoFoDzKL8XxVGbQtoJqji/Ym27qMLoLzQJpVLQv//vbRrKoZtDGO8fBEM5zsLEGrbSLdQKwQlXn4V/6k9uHZfBhv/fGY/1iLNxcopupn1OplOTVXRskwSOiqSADpdRdLbmLejNt7WQQCxsKM+AhX/c8f9/Cl/8SJJghvO07USz2zzsb56W4D8SHFzELaRkN9tgtEbeDVedWAhhGgIMvtDDWOMrzfYOgoxqOte+jSreR1DMFQT1WvQbnBtu04AkrmtETdMfk/bgNs6ACNEHqlaP1/npl7BwbxlFUe9g9ukNQsA3OAr5dMuN7YtmwiAP0IJfGM0BD9eieLCr3A5MzcUsL4LfIWECrwqzFw0WUTUKNvt6W+M2VRl84Otl7PgnDxnRhICvhqFASr5IgDEkMWwlIEMvvlFXIyFK5ZrrEvfWgCUJmLtZJN5tdSTqR0oLxaLs9NT63y7Xq/Pz0+TpNRbYmaT5/47GllrvaWUhQxS3Onsv/eOrPSiojja2z+Iu+VYXwjV3zmKupXmcHGh97KyF6Hn/B4Rx/DUKFmSjtwYnQH29aeIECt4Ur0CtUxMDGU5AAiiSFrJYTCBJfyUq+lWAVoLaHfbJIV1tQUwn5vJxKVzmqSL5cJ6dV6cJr/9z9ezSWkXJWny/OT5YlFqgBFhNEKnywCurq5Onp/Y8UOaXevOM8TlhbtHR7/5zb89ONgvgoNB55e/2r97vFcEBdHBnhgOnLSY+mCpIycT/cnTF6v0fRtM88dk+sIMiyCRgIl9O7/WtTMEOkWpExAt9iGISRk78UICkMr3HCcuJJRKjDG1DBQkGzosfhkDSzb+E91BNjU5Yqr7cgMtYsUMaAFTnU7Fm3uX5/UXzkyWapfd3ZPl4HfXthouLi+fffppVgm5qYO94a9/3jvcARB39+KO82DvKgXpTULVI0wCyijD5XCXiAQpv8iSEdD1d/TSIxcq2+b6DrAo4kto5h+6uYz9pDJkvJLPmmpZ8p0nGL2BbxYisn1Y8Yc/trBDFhu0f2/AG5W9RosxxsRGtN+67ejWNoMh4c8nNiHDtenlBvUp/gYMZhamMfPnsTVWFdtnJNsSsjULgLZLyxxqOcFsySYqTPSWKwN/GrRaAltpVPPvAvRVP4kHXomvU7QaXU/jPi1FncBMNaMXJGsNLlsZXcBvqxnQdeUf48kvA1hmWHrG2WpFK2cF8WzG5xf2/GwymT17llaD9eV6dfLl82Wlt8TMWmv3UgQedtB1I/jRaFRsn6P63e7+rrVyu73e3UePBsPSuIKUOLyDQRUEwPUOU2ybYQVQ9K3ubGZm9gTkSbBScGpMAKT/GSs3SA0ASEHCSf8CRVfiZVGjEBiuGU1phpVv9C748sodXq2yyWRlJwhOPlv99r9Mr87LhE2S5PnJxO4eJCXfe5Ts7OUAFovFdDIrfgeg6ZLVU6B8UnekHz7J7t0rU2c0kj/5ZffBQ++bOUGS++T4/Czrn7qgjBaZdrpWxiyJI+JqfoEF2E1jMEDkpQKDUGYLUeOjKPzsI2IiJjsBT4UJ6aWsqWV3XfMJdMOmRX7YCNYbmQMAMLpp9NaMZ/a/vRdhFygs5CqSDBCE/1wD8mfRM9aJ8RJ2seKTmf0gkX95Ofvwi6RS5+69nY3/TR73BIDRTncw6tsLkRqkfu2tJxSBWFjVbwIJ9kosA4ZuHgABAAyJpkXsYUC6+tLbSM24/hMbsJ0PqB8KoKoUgUAgEAgEAoFAIBAIvIEEozcQCAQCgUAgEAgEAm8sYXlz4A9Hy4KxW/iqC9gq/HU/r5dv7s6oLxN6bbTf9JZlma0X35oW205ovWvgtVFk7levhoHAd4Nb68gthxvYFpUBzdbdlwHW2l8symnKiefEmyRcrboEwElqdaoAFKuX/eZaSqkq11wAMoq8hcSEXoe95c1Rtxt1OgBU3JFRZH16hVIkpVtrKvydcm9kW7teUFxbntBogjYXe27oa7hn+weYYWqvDmb2r9Upa5dUWK30cunSebHMFgvn5Ller1crt7w5TVOGiyQJiqLIbpkrJfd66PclAGN0kvSK3wFo6uWibwWHer1eJ47tRq9RFPm+0MXCV/8dNnve+lHvgJ8uW7j1hAJGFRUAL33Vq1CP98Y7/gEwXNOOyfM8SxPrgJBlme/hX19H7f68lXLBtS0230BSBr4+wegNvDKvVJmJyDb0RWvitykNIatNZRF7VBJRQy/Bh7DhWOLDraJRMDd0vg7a0vQRATBtvQRzs8X32X4EAJEQoJa1GNtiVSBo65VU/ttK60EAW89ofSEAMK5HqEGtEQ68LpiZma3yTUGjOvvBlkMFm6O0gs3ffTW7QOA1YgvbZvn04bqaWlEXbNDvp4pg692YnIwOgI12jRm55/undWmsZtpcLTgpK6Ax5vrqarV0Cr3zk7P1xZUNLufz5XRqgx2igXBegnmer9dr9/pSvP3221SJQskoGhwfR9Y1lwi7ffSdFK1SqrCQVSR7g659fRlF8WiEylQDEeK49oKNl6W23pXqys0oesWqr2BQTsLv9bXx/JABoihWCgCDs9wpZGSZmc3SLCsvNcasVqvMKlcDV6eL+dRNHzx79vzzz1/Y4OXl/MXJtQ02xiHI9mj5XhSVzre9Xu+tRw/jjrVd8dNf6HsPGcBikV9fO+PZ0EUmPwaVvxwc7P/qV7/Y29stL1TiYK+jPC3lXNeUxrJ6MM/zxJsB0TonTxa0kE7bVkiJ3NHGuImN0b4nOZGSnto2Nko+lf8KbpCL2xYJAMzQ2j2L2TmxS+ELmGHjPtQiZQwAbOc4fE/vAgZrz6t+NpudXZ7ZYP7B0+z//idU6txpmi5mM5vyZj5m5iKdnQxVARv45UQKSGkjRoKVEjYujQYHDGLajOpX4NZb+DVoa838rhKM3sA3iz962BxJNEYejbFycbT4UUjZbIs9iNpagtaDACBam4Ztl1PR4rew7UpLy1Gioj9p/l7Rfm8q0uQmtvz80rRef2tK3gg1ZCgC3xhaa78nblTJzfLs/8K3fSXeVpc3K34g8Lp4yaK12dc0iugrGb0AtcxIwtQEb5HnSBIAnGZmOuVKqkprPT85mUwm9sTLzz6fvXCj88lkcn3tbLNhr3cwGtuICSGiKLLBbr93cHDQ7ZcfHlW3u/+DH/QPD4sgiLA/xNB9lgRbgSIDX22ICFHkTCUiKLW1OwHauyIiou0T0gzo+sWG3Tc3AEIqKQhAbpAbY7MszfR0lqzXpQWitZ5Op9ZEZObnT68uz5ww8gcffPDRRx/Z4Pn59fMvTm1QCOF/Id/pvf3OnSf9eKcI9vu9x48f7+6WwbiDP/8LPH4HABYLePkDIy5zccyV0TseD7//vSfDoVWu0oQFYC1zNsZk3vfohsGvtfYnKLU2wiuWRNRe9l1xrp/DAHspSUJIRU0Ls4XGM7dHAAAYNak2ZuR5GaSaavcG9bFPvT4W6mh+0P5tf/F/XCUrvx7NT06uP/qIK6O3yH17/zhZA1y2Bo30Za7V63LioQyRICldgpiK8ihoM57fDH+Yp3xbaSlzgUAgEAgEAoFAIBAIfLsJRm8gEAgEAoFAIBAIBN5YgtEbCAQCgUAgEAgEAoE3luDTG3j9+H4p7VDdVWPTQ6XwvCIiBnjjqIXQ5shAIHlbnFqObnssAe3TRkzMLfI93Ha1IWKQr/DhsyVGDm5/o+YPge8ERCSl9H0Xix9fPtig5mfV6jBp/w4E/lg0+pp2J95Gec6yzLlBaq1mE5k4XWVcXWE+t6HJxeXk8sIG18vlYjoFoI1ZrdO8ciYEOM+1MZ6Uo5Dxg7ENHr+190C6Qdro4ODg4UPrIkv1DkRGUW9nR0alPrOIVHRwiH7fndHrcHUURSUtHA4b3ScRCSfPGusofgAAIABJREFUAxSaSNv7Kqr1NgT4XSaB2mQiGcpAVunBgNCSK3VrAJNpPp+vAUwmk6fPPk/S0l12Nlv/7uMvp9NVETTGzObzNK18eoH5TKzX7rnXV1fXE3dbFd175/H3bXBvb++ttx4qVfbWR3vjX/zoybjyf1ZSjYYyisqbK0UP3lK7+wLAcIydHT/p+iwe2H47jqOeip1OF5PRERuXkpGIlXSXx+gJ76iCiqiSEwMk2Oil0WUkiSQQF+kNgBlGe566ICFF4alrDBsnAQaABCnniUpEIGobLgh4h4nhZzeD6pJudYhAPXc+A6pMDibBnrM3Uc33m5hrUWL4UqXEiIzntcsgpnoRrtk2/XVnsHQSbs8n0d+eCVvt7h3f+/lPft7tdYvg8NGeOrpL4z6AlaKVdlpiXYl+zxvSCXJlF8gF1uyrspGvgk5M0lDNJbiOylFT8ySbt0DxivYF6wkeIYFwnuFSTGLpGh8ljmu1+ztPMHoDr5mWse9XhhnNNqAOl23xzRBALf3u16H1rixuaWxajhrAbD+BgRZrumDbta1RDrzhNCze10hhM7yW+h4IfNM0jN5N/JJsjMmyzAr8ijwXF1M5q6xcZjx9ilMnjDT7/LOTz5/a4HQ6PT8/B5ATTWORVsN3IcR4PO52y9E2gMGjB907lfQUsL+/f3BwYIOjBw8Ofvie28XAGCcLBLAQRnXYE6CSSvnSvQzpm8lsjOHC6CX2bFoqZgC8juK2Ks3eeBwozCh7jKml8yWGzOHp7ELk8CYBsLpYn7+YAzg5Of37v//nxaLUprq8mv/d339ycVlmgTFmsVykmRVSJha7EFZBClJKX0D+zr3Dh/d/ZINvvfXwV7/6RafSZ75/jP/mL1GJLsMYk60TnZd2BRHFXSGVAGA0jLcxElFHirteGBDu7ZiJM2W0Z9Z2lKwsbQAKXfKMXsFSkRuiC8DoldHVzlIiAgs3EGA2WlvjloiIFEkCwIbzzGWQlCSVeoV5SKoPveoXci33NiABcbOV4etbARAbG3DUpvypVgqJIT3lNQDQVpUNACTVtKC7Sdxbueme+Vz9y6VwMsz3Dn/z7l/s7JRCZb27kdof0zACsMqTpMp3ABCq7wmeAfDfXhMtwboq7QKkpJPqEgacGdRmH2pILXwRbQi/sgLsvW8z71KIcvYHgJDzSDptPOkdCqCeqIFAIBAIBAKBQCAQCLxRBKM3EAgEAoFAIBAIBAJvLMHoDQQCgUAgEAgEAoHAG8vNq+0DgZen4cXn+/EWfzeC7tTS88Q5KPh/21+KHzeOBP5I8KZLiWOrw8pttN418K3BVuFGXWbmzdodCHxNmNlU2jCN3qQdZs7z3AbzPE/T1HZPaZpOp1PrxJtl2dXVVZJUUkZZdvjp0/7VdREEM11fU+VuCmCRrn0P0oOjo6N79wCYSK33xrryHSWi7mCgOk5iJz7cV7sjG+wPBv3h0AY7u7skPYmpwnGxijORICUL7aLyKOA7Ohp2QkcAajpABNcAE3yH3k0Y7K4FRL3R9w8B0FmerFL72CRJrq6uskqPKsvyyy+vV4tSEoyZp9PFeuUUws5O11dXCYDZbPbFF19kWelguVhk09ksTcsgM0cqUtbfkmj/6NFw7Nxr79w5ODras8HDu3sP375jg/v7O48fS3v1oJetlgvOy9yfzWa//Yd/PDs7K4JSyuN7DwoX0KOjO2+//bYrdEwNoaLCadoihPDlmgTVZD+Ya6MpIvJLkRCiWbz9oCAhpZf5REJ4J3zlnvn2vrn91tsupXoha1bcwkXX3ppAwt2LDedpxnmlicWcZ7lxTrqIVKw8BbgsSdOqyAHodrsPHj40lZ7cgwd3798fjcelB7jal1FUpqMUMlYuZjWfWwDG+MJUJIRSwn8RBmycmMCC2rRYah73NyUcbcuLG34KbCMYvYGvRcOOLYL2F2OMHyz+8Btu2pDQtH8XQe9oqNh/EOqzEptw0fLeBAOoaSg28XuxJo2xUuCboTlseq3Ym28+pdFQvPFspkDgm4CZnb7UplWwHWOMvRDAarWaTqe2iE6n088//9xauavV6osvvlgul0UwTpLH//zB/pdOuarx6P7hXv/AM7GOjx8+eQIAvS7eeoBRZccSoduFL43T76DrBHshJTyzpxksfrEQCRHVrAeuqfsYo51uNEBERZyJiFAT/mmHmU1NvYgaxoBf09Msm05m1sCYTCa/+93v5pXS9XKx/uCf/vXi7KoIGmOeP39+fV3NJgCzmVkuymGDn8Jay2XS0ZWUsRCi1+tFVrlaiHeevPPgrR/Y83/60+/96Efv2OD+Ee49tCFEEfp9lwDJKp2cX0wrLeiTk5O/+qu/ev/996uT45///BcP7j8C8Itf/dnjd96yoxTW0HWBJV82mQiy45uxzR6RvRkcAETkzHhACOknQvmHDYKkIvgZYd+nReTzRhqnt5YLRtuQgcp/NyDqkW3ADDZuTEACNWU1Nuk60Wk5acXMq9XKTogAGHb7vcjpw2XrxDd6e73e48ePucqax48fvPXWjjV69QCrqDRWlVBOigpQdSsXzOw9FEpJpWwGMZB7ackAC4JnQjfxrPobIIC3nEBeXgNFVXHBQJ2wvDkQCAQCgUAgEAgEAm8swegNBAKBQCAQCAQCgcAbSzB6A4FAIBAIBAKBQCDwxhJ8el8PDXe1xpL6bc5sr3flfcNrruED80o0Itxy281H+CcXPirWTcUYI4SwjjcApJQtaeW90eZzalD57xvjK938K11UIgDlOYRscqsDyNaj1Hpfaj/cxtYnVrTMsd16beBbDHNT0WWT1hLA2w9za3llsKmczhpu4wJCekWSUfNUFCAJpznDzLnWXL0FgZR07lsAuOHuJSR5agWbUaxFhlwDx60OeHzL66KowNug1oahcePNXqvt1tvhjZSvw0TcdmNjWgoP5VoUakbMQmsXaWbkOXwf1tUKlY8ugOV0cn116YLLpe/Tm2SpWcxFlaHdPD9eLLJK+Eoxj9992Hl8rwgC6HQ7fr822N0b7Dmf3v7ODg6PACCOcLCPbq88QEAUQXhenp3Id/FlIq8MAkI4nSoAaPTUtJG/5PtzCir+VccI5clEjWJF5GU2szbaeFmQpOs0d66Ms+vV9Gplg4vFwnfKXS/z6/PU6PLu63VyeXGRVA6WeWbms102pZMzM/d6Y+bSdxpAns2S9RJAMXKw1SSK47d296Ko1ABTSu7v7/V6ZcIKQd/74feOHx4XQQAPH47u37chdPoJhIszBBkI6zV6ef3iP/3nv55UQmXT2XS6nEe98lmdTmf/6ODeo2MAO3s73nWAgFC1iuOrfNENftO1esHGWOdnAIJEJ3YiZ0KIdZLJqEy6DqjT87ObTPPm5bGGKykLMi09MZothCDjK3Uw1xzFiammZFa+ZHkLJugtLsUSkPUDtbJsNPLMpQ+T3x7r5XLx0Sfp5bQ8l818Pk8S57Ub/eD7g4cPbHDY6969c+iO0rjT27OPu3//ML6rYCtlB5EqBafq1QIKXr0AWAhEkY23kDIi97JcH8IJQHz1QRvAYLq5HWUSTK7xyaGSWlD6L+ENql8P7ebAnyDB6H0NFKadDTbMwqKQFeVss0y0mHzYONpOQ5lDSlnXTHhZGrXCt1oBCCF8cQXcFkljjBXJNMYopTqeWKVSyheyAuC/AlyCcJGu/qFX42tc+pVpb8RehpbG6Wvd+ZaL2w63HbvtaBtf/crAnzxsqCHw4nNbPTFEvL3ua5AT4d3AgDPoYrBg2BgvDjGi2BscGBjN7k4KsktuPGuMSZJEm0oziUSvIyJPINRkufHUgKWKyZdAYfjSP0zM5HUZguzQmVE71KBhmTfYHFT76i8AidoIfYONqQm/OyJC26yVD9eymok1eXo+dQisSNdSp4HO4CVsA0oztUoAQBssF7C6MsyYL30rF1+e4vLChq4//dfffVBKEwFYLpfXk2urbRP3OoODHaXKDrQbRffGoyiqJKZ6Xf63/wbeqHp3d3cwKIVwAAyHu8Phrg0SEQpjlQgUgVr65fq4mGudL4napcxgf56Fiuz2Lq9ntZQb8rMAADYwmmxeExFJsuWEmfM8y3WlkwxMJtdW0wvAh++ffPgvz23w2bPPP/jgfXu31UJen0U6L++mlOr3+3ZkEqnu4d67va5Lq/EY45ErLGnydLF4ASCKosFgYEcLe/uDX/768f5haS3Hcfz47Ue7eztFkAhvf08e3XPlVYhadVwmi+nySxs0JHOO7Ss/PXn/f/nf/tfff/pZEVRRtL+319kp87ff6z1699EPf/IegDt37kDAzdkQRM3EQDMPmvZGraoYY/LMG8IJNeg77W4h1Hy1NtWsh2YMRpBVgShm9/z2rShwAIwsolViqKWyNSFAwUgnQgw2mj3LnAyUb0NL4c/a5KCM5I2P63JtRoAbjU+eUzZ3ySUlKAaXD8qvL6/+n7+Zf/ysCGqjr66uVl6ZHP9P/+Od4yMbPNgZHhy4MmZ+pH7Vj23OCBJSSWuuysI6vanBokZPJISvJCeJutjMYgfJtta3HX9Y3jATNCvjxWotuktyY+yUIubmJX7w69gg7Uf/NAlGb+APjV9Pvo115g9JSJ3Am8LWocDXhm+tKMWzGfCnyjenzevh+igBxcihGnYQ33C6/0Pz3q280snbYXDrqOo1PebVue3B7cc3krpG9d2JDfyP7cwwhZZuRZ45kxjgJNFr961Pr1d6tbL5qwUj69kBEhGkMcoblWsludp5CIDodkTX+yjX7QhvbteDNnYmqcNUK8yNYJPNZGk5GbcdbYFrFac+y5/nOq10dAEkSbpaJTYlV0u1WrE1eqOIldLKfXhkw8IfiApnbgMAUQRIAESKSNkP3UJEURzHcZkFcRx3up1utxTsJUKnCz8HGgMNylCfZyHA2PQxWifperUud06KjTH+jmtEQgqpJIDGlD0I4NuSeTPTtlMbIBHVLR/Un9T8DliLSHuUbmEzxv4vxTu3cHOKtF+DstaXZ1VLEaqLmDnPTbVewGhtklR7X3q5/u1EEJFvnUaKe266c5MboruNesFqv/CbHO02SoIL3pbO3zm2N76BQCAQCAQCgUAgEAh8ywlGbyAQCAQCgUAgEAgE3ljC8ubXQ8syXSJib21My5nM7Hu0ElFz8Uydxq0a5zfu5i+MASCEEEIUd2gcQv3ORNR4UONkH/9NsRFDZm44Hmut/aAx5saYbMYhEAgEXgbr6SpI+JJJBPL9Y7XR1mUXgCQqxUwAAETkq+4JooakEAnhr6DzFYNupHTArAItNJZkNxYxtq5nbsLMVotrE2KbVAAA3roezxgYz0tXiJpoF9B8o9rLNmFmePovxbpN7x114RBewdV6ZgBAcn29ev4lM7PW2WxmVzzCMGYzXpUrVAGo2UzO5zaotd7ztKYGOzuDO3dsUPU6/cNdEZUDJKXUYDRSVqqq2+XDIx6XHqQg9Ht9X3NICumnM1c+dUQCqOkNEdXTvEG94yu6a3cUgNcdE2DYuHRmNvWeXUopfNGsiizP57OVzstE1lovV8u8kqrKdf7l+YvZYmbPn06nvk/vl89XL07cQvEsy46PnYJUtu4c7oxN5fZZaHzY1dFSRMk6Mbm7uR2WFIxGo07nMYDhMLpzp2+9rMe73Xff3d/ZLdWHlFKHh9GwcoAlgrf2/AaUlN24XAsNgAT5Aij9fv/hw4dcxbnT6dy/f39Y3b3T6dy9c3c8HgPo9txNALBh45dVosbr3IB3tCGYwsypLc8AAf1er9/vF8Fut9u4c6OOtVS5W/EKWdHeuB8IgFfbCVT8VoVf9qFsoGue/vW3EYKk04FKs2wxm9mxYnJ2PpvOXCEkGu7sjPb3yyAAIa6urmyot7Nj06046v4OfMcIRu9r4FaTrN12tRhjsiyzvVRDrrA4wf4NNKWPG81rnueZ58LkC0oBiKLIOsBorRtdY72jbfS71LBLN2Pl/904P8uyxBMXSZLEb9ajKPLvJoSwd2tP4UAgENiESvUmF/ZgzW6Empu81vxKZhHZMZwg0el0PAODfOVnAEIp3+gl+IqnTUoj0EZme9vWsHINjB9nAgnP9i6GuS2DXa11w+at9SAkpG8Ubb0Nsozz3MUqjiF8I79+IYH8oxuu1ITKJixoTH2KLCWvj4CueerOPvn0s//3/2Nt8jyfXF25zsUYXF3zwtlmg263V7mAAtjf33333XdtUIzH8u5dZ7v3OmJ/TJWJBSFkp+NEa5TCvWOMx2UQ5SSyDTKLxmRu0a8RCUEgT41qc/8CHyKqTSdseJKzZ9Yyw7DTry5MJl31pwT0ev049u9WPne1XD57+my9LpNusVh8/PHHk+mkCK7X6//0d3/z7IunRRDAYrH0O/Fh//6w55SRnzx58qtf/cq+lKTdmB4SyvmC6+vrDz/8cDYrrdw8x+Risl6VOslEFEWRP4T48Y9/9M477wC4e1f97Gfdfr+MfxSLnX0VdcogESml/Ekn1W+zv+Koo1Q1ZwEYNrnJbck8PDz8y3/3l5fvlSnQ6/WePHlSWLkAlFLvvP34cP8AG9lnjM6StZVDE1LGnU5tLqxRO+tRVFHky3wy82Kx8I7j4PBwNBoVfxPVDHU0b13jlWbKNguZrzHVLJNC1KdxXpZcs0ndc6IIUeTfR6DTsRFZzue/++CDZTVppS+miy8+z8/Pi2Dc6fz4l788fvSoCAI4kfLjjz+2wQff/37fm4hB7UGB7xbB6P0ToujAvD6s2b01fuT6Z1WgaRn6J9t+1wb9yxu3tX/fih9hVBFo6cW5roHRuLwRLGi5WyAQCLSzbYTXsCc3mib7J1AM9Yr/WBpjQ6of3fo9taIRqZvj2GTzS+8rwXXzkhozmC8XBwDMTjGqCLZRvy3VFXcIqKfjRi/QeJivVgXk6/X6esJa53m+uLpaV+JDMIYvr+HZDDQawfvaw7tjO+0LQA2H8f6+s0+6MfbH8IxeRJH7QKQk+v2aUFIdreF/CXdvxMyiVm64mTwb1Lq/ekLXO0sucrf6jYv9Aivbu5nXHsaYJEls0i2Xy+vra/uhbLlaPv/ii88++8yev1qt/O1hDvcj7Dv73xgzHA5tXYjkuKf2RSWTzsxxHNvvmWxMrtM0rUXS/9oZx/Hu7i6A/X11fNwZDMoskAq9IWSLGlHrhwZBJIR7ijban0uKomg8HpvKluv1evv7+zs7pZEspRwMBr516mA2hq2k9qsOXWhjcV9jM4tIRf7OWH8YmoWGqF4mG0X0peFau9Esm0QQwj5cG7NeLpdVdTaLRZqmuvqoI5WKu91BNR0AAGblmgIg13nt6y5h87UC3xFaG4ZAIBAIBAKBQCAQCAS+zQSjNxAIBAKBQCAQCAQCbyxhefProbFwqLGsxR5tX+5C9QVyjZNvvNZfj4eNcxpLZfxI+g7Atz73xkcXFEe3rZtCfVl1w3kYgJTSbrUHIIqizTgXl7RHIxAI/AlD3F55Ww8yPJmjG6grStVh9lbONZplELN3KQv2ZoEliNhFjJlh3NpRAHzDY737k2muoPNPb6wQJLInExie2hZQW/knIPw4VCuuq5Yc4Lp/HXk6D1w8p/5cP8R0y6Js+2AW8FW+mLhl0TUzyF/rW7yjCxvKMlgJMWZaJ6hUlABkk4nxVilnSZJ5DqWTky8XqzUbY4wRUdyxPsnMpCLKnVRVfzQeDAY22Ll7Rxzfs0Ha2cHOHtveJ47QGUBWQSEoUm6FpBRMEdh34a5BVEtaEkKUSUskGjWBublhbLNk+LBXNhiC4KuNsTGul9farNfal8yYz9d+NuVZnuU5gOlk8vTZU+vTu1wurydX80q5Ks2y3Z37bz1wK8OTNM0zpw8yHNwdDe7aYCcaLebVtryAoMWKTu1QczadMjIhy2hEHTo47O3s2gJM/X7fHxLcvd/fPRAARrsUdUlWR4SEv+ExA4VsVxkGxEbS+Whjcu1t2gxmL+WVind3d2X1sG63O+gP7GJ4KaR1fW+MZxgQQti2jqS8IRb+FRu5a/2BARit/XTWWgMuAxnMxri7EVBXdWFbKX35PqCo9rVf/OoIwN/mFQCT8drJptxdo22vp4hhJpPXRf3KgGBDflOmAc/FF4IhXDxUrAY7I6HKaGhIdfdujjKDVBRfG03XTrnqFPkV3MrwO+u89o61TAt8twhG72uA685gDfOsMNuKpqBdyo+IlFK20Si0Mez5XPfgZWatdctzicjvPJjZDxYnF+c3RDga0IafSSMajef6MHOWZda5wtSlmwH0+/3Dw0MblFL6/jzGmDRNi0c09C0CgcC3BRYwJGpjqzqMpqFXp+2YAKmWE9hwWqn7SOW0iABvAAkAzMTs4iiEFExUta9sWKeZqWwzIjJKkR3NEQQJFwSADHAD1rIDqBAgX80IAFCOQ8ko+ENMY/ygMFDG67Xro1c2nGfuUSRIxYJkeQYRQGDlRaTebmsg9X7YTNPSjmdwTMYTg9GU56LWsPtQZmTii2+hVhLSnK5mWFe2mdbi9BSV0BGAq99/OnlxYoMXFxfnZ2c2uCB9hZwJcRzfu3dvOKgEfKWI7t9Tu06saHd3bzx2Xn/d8a7adXKvpBTXNIQEG2nTgASEIj+7WUace9lUt7EIEFWyAxDMlYHMBO3P4TByv2gwi1p2C/KndNiQlRQu8CXEmaG19SdFmqQnJ/PJ9bQIGjaffvrR6VktJQvH3SRdzWYXnhHIxriaEEfDX/38fzja/2F1FEJIX5lssVjMF04WO0mSTz+a2bqVZefL5T/ZgYoQpJTqVnpU3W78+M8f7eyU+SKEODo6slpNAA6Ohnt7EYBeX4z34UYHBKFco8HMaZLltnqCYsjohmmpktV6PZmUKQMgiuP+oGcTc2d08Is/27Fe2ULIXrdrRyYEiqOoSGhmtlJhAAiIOx1bFAi1wRIAWEO0DNaOmtwYz8pNVuvF1EUyWa5Zu6rDuc7WiakkpoQQqtcVrn0rxocMAAR/poUaClgMeLdFkfP2KSBNKvMaK0W16TtD5Nd8A869BBHII7PyJtOo/AeQNsKz8ClN4evV9To8HloJwsFO/3s/e8+OHvNZMtl9K7ksNcPTLP3HDz/68u//rggCWEb9RLnqPLz35D0vls2mN/BdIhi9rwHmxpDmBgO1OKHxe4PCerQnNM7cvJBbjW0pZYsp67N55wa3nmDZPNM3dM3GjkRKKV8QovEKxVfiItEaFwYCgW8LXI7umo2Dpf0DYzsCrV46DBhGMbpq2t1UG3Qy+/ZG0wpnZmNYlzFlIpLGDf8YIBb+C1IxlqyO17+FMsRGatgg1z7MMJWRBwCQEdBeJKn28kYz524QLgTgm2oMUmjZS6kWY4DqUWRr9DYOAAz2N39qINiQrn1pqZHlWKZYVh9v85wuprgu5XwBpM9eLJ49s8HrFy9Onz+3wfW4Nz8agajHEFHcrfaVISU79++rY/cFcri3N6q0iADI/kgMXRD1osE5OPHKpQBULam5LsPTXIrQ+M7opiZcKpZhNvWCUYNZ+Js5AeR/6aX692QUsarirLVYLfPZrExYY/Tz56efPf19dS5OTk5OT08BaJMk6cRwaW4VQk3Wxhv05MHeW+8+/rW90FeiAnB+cXJ27mzp09PTF89d9q3Ws8n0RJvy5t1u9+DgII7K+fdOl+4cD+4e7xZBIcS9e4eFclVBf0DdPgGIIop67ls7UK+7BhrGlyaPeKOYemht1on70guSbNy+W1EU9fu7NV10In96iarsZ3ayVQBICNEix83V/yyNE+t3M7n2N+DQWvs2c7E9ktshSUp4hYO5aPcMAFBtezXR2GytWSRrQQZyQd5GWDD1WBvUxJs1V8UIAKDYkMmqZQ4AXIkVbMiXks8TJG7jK0QA9e2Mj4rVOHa1NetlZhbFo9JIXi6Xl++//8lFKeYMwHR2OXLLOpbr1H9BbnzKDnyXaBstBAKBQCAQCAQCgUAg8K0mfOl9DVDrAmCU83dm8/dN/PtsfvZMksQt8Mjz58+fT73VL42b379///59t3teI5L+V2J/ETWALMv8HX2VUr5Kfpqmq9XKfnddr9fX19f2/F6vd+/ePbsPOBFF3tZzxhillB+NxWJRTDYXxHHc65XbzQMgIqVUEbeX/GodCAQCNUhAMACdZcZbQXd5cXVxfmGD0+vr0xcvbHC+Wp5NrvKqvY2UGo9G9gNXp9t9/L13dvZLl1EhxNHh0chbPctAfSGj97WvCLn/3obfsG+2gt4vRFAk7BdIIgi3RPcGGp8rue7TS4C3RPcVyPIsyZzbLV/N+Ysz5GVKrlar8/Nz52u6SsWzLzEvP/IQc7xeS68D6oL39pxrbu/w8PjP/swG9d4wPd4DQcXx/tFRz25KJKU8viO8HOnFcW27F+uvexMk8P+z96ZNdhtZluC57gAe3h4v9ggGGRRJ7VLuacqaGauqrraenj8wY1bzM8vq05j1lFV3znT1ZKaqsjJTUkqUSDFIBmNf3g7A3ecDAPcLPEZQSim1MP0Yg/Yu4AB893vd/R4XzGUUVM9GYo6NxiDL+DlK0MgM3BqdlDLfUEpkmMtnAb6JSSvNd2+hWm1OTy6fPD6x4cfj0dHRoR18Z7Pk+OhiXi5gKqWGwzE7W8hkasoH+t3d3fyk4iBE3HKLqEEQdDodl1emYWbNPbbYPhqNplO3KHc5PL0cunbUaDQ2NtwCe7N1oz/4gd0OHUVBv98Kw2KDaRwHt26v9JcKd1ki0el04phtpo0oCPNbpBS5vMlPtGE5GYaVg3oNsnniatHnn3/Ok3B2fnZ4eGDF3d3dn/3sZ1ZRCSTC4LrVQK11viSbqyj2euljz8AbWA5eb7TmAUT1ba12a2VlxYrtZlMlaVY6tButpRCyLDYSoraHWUhp166rnhcLMKivP5fBCRASpS8tgMpi+yIEUcBCBJBSBK5fMYBdodcZ3888OT4esh0cZtA32czs91MQAAAgAElEQVR6o4Rh2G637a7sfB+7zWpjzOXl5XF5bC+A1354b+eO25C/tbXNy+HavPB4yeGN3q8B9W5uAYvbep8LooUek0FrPZ1Ora4wn88fPHiwv++2FdWeFULwsUcIsWj05rGqfTfLMn7EWRzHNaP34uLCJufy8nJvb88eVb+0tDQYDKzRi+oG5kWjdzqdHjEHLU40AiCKolar5c1dDw+PPxFEEIXSpbMsY9sFj/af3v/4vhUfP378wQcf2J7t8OT4w/sfz8qerdPp7O7u2g6q2+v9L8lf37y9m4tSynar3eu500oXu/vK9shFK+oq1EeEqkdd9TUECoIv9loAqBu92lR2Kl6vJ1+DNEvHU0c9pU6Pkvv3TemseHp6+sc//nFcclPRZCbv79FF4RQqhGi325x+4o1X763t3LDi+s2b8a1bVsRKDzurIIIQaDSczzYRWjEiZuWmKVjpGyErxmUVRBDB80qxBLGcJ0LNIVGZVBs3hoZhmKeICGFYKdLazIjSSmXuijGGaw6HR8e/+91H1io+PDz84IMPrP05Go0fPtgbjSa5KISImSeqEOLeqzc3txyDxs7Ozs2bNwG02o2NzV4YFVkXBEGv17NFMBmrf/6/zj793Bkke3t7fNSezUezufPBfuWVV27dumU1is2tlXfevdOIS86hAO02WcsuCNAfoOHOS15AadlqjTR11ZUICLi/M4VBwDN2Nk/TzBXJp599+i//8i9WPD09fcYcxX/605++/fbbzNO1QhdXBzsAucZCAizUmfp7eHMl6Mqh06LqbdtqtpYHzu281WyqNLFGrxBC8q3Uoq49VhSnF7ZlHs1qryLktVSBVRARLwYJIcCNXgNT2vla8fY4OT09/PRTK5r1FdMg68PdarWCKIioqEVKVyhRjTGj0ejkxM28rCwv/+AHP7DixoabNQMWysjjLwlfuC57eHh4eHh4eHh4eHh4eHzf4I1eDw8PDw8PDw8PDw8Pj5cW3uj18PDw8PDw8PDw8PDweGnhfXq/fiz65Uoprfcsd0VYDMmhlEqSxDrwTKfTvb290ajwfcqy7PT0lPNJ1DyHnz59ykmhlpaWNjc37Re11kop87zTgGrHCAkhOK/V/v7+r3/9a8unNZlMTk9PbYD19fXd3V3r05skCTFuBq11o9HgHr+tVov78bZaLXsEPICKy4qHh8f3E2RIVM8X5TA5YdLVDd3gurtk/7sKojhLSEQRp7rpLQ02txzVnwbGjKJPS4kHn9ojfDSRCENZOjrKRhS2W41ucUCOEAJhwM/q0JAGzjE1d0J0AkheMeNMqJx8BAJ3BtZVL9ziTnnfLHir1a4IlYrM+RASiJPfQIOfuSmq7sMmzcxkZrQGDMYTJI6qanb47PKEOXkmsyk7fWQ+noxPz+1ZLGmarkSNJVkMCtTrB1tbNs1CiP7yoNl0Y0R/fQPMs1EtLSWM10o3G7rZBBERiahBlp6KKKBQaFfcQM7rZRFUDhitYrE+aVXhHDKhNuwwIQqJnVsMCTLGlb6QIj+2V+vs/HKUqcLXVCl9dHQ4LMd0ACfHR+cXZ1acz+d8iD8/G+7vn5jyCCullIiSVum23Or1N7ZuUKnUSRksLfXj0l+WiFaXl7tstG00ViJaAjC7lB8fhLr051ZKTSfTLCvcdJXS5+eXKWMmu3FjZWdnzYqNWEUNl5XrGyuv3N62Wdjrtzc2ZU5GBUBKiiJHhiQEgtCQKFJkDNI0Vcq1pDCSQSABCEIgXWU2RmcqNaX/MxFFYSDKA1iNMRcXpxcXF2VwfP7w4Scff2zFKGqsLq9bcdBfbjU7zbjIHEHCaKPKw3eIqKKKEImSmIuIKsRjxhjl2hwRkRDPY7ADAKP18eHhkEXyk48//uijj6z45MmTITuw+snjJ+//5v1Wq1DqOp3O1tZ2o1H2SEHQ7PWCqNJki4gsKlFVV34D4w7dIlDZYeYQ1YOytIY9wRgACQQ173/+rMm/VYTXWTYfjXSWArj4eG/0wDmKT07PRoenVgzCbkwdkkXqjGhCtCGKaqSDbBrrWVa4BM+F2f35T7Du/NXv/vj19VvuiKN2P4ZTab3d8xcNX/hfD66xzfIeM/9d46XI73KRI8uy4XBo7cmLi4sPP/zQMtQZY+bzOTdH0zS1tmge4Jyddnj37t3V1VX7Oa11biRzozRHGIacuSrLMn5Y3GefffYP//APlrlKa52mqU3U7du3f/jDH9pz9nLaLfs2rXWr1eJHz/d6vT47OzGOY24Se3h4vAQgTZRd2dGBYOlqngt+eu6XBhGkyJUuKQNu9Cyvr4ehU4WanU4QNWxXlgD0m1+lpaiIKAyl5XeNm3Gv1xyU54uSMFHEmIxgEBowFqUqFhNkRwXBaIEBUPWcVgVw07oGg8qJmzWRjGkkSZC6aFpW4UJMECWV4amC0RQHJ0gzGINnz/hRumfvv//s97+zYpZlfGAat6LT5ZYuNeN2u721tWXnVUWvE/34LbFWmLUyCNa2tjqMEmwqooTYeFTNAZWqdJ4CIKIoiix5DwGkSFS4qkKw4idULPw6qPwHADDa6FRZaxPC6CA1wj0vIlG1NwJUtOwC6VwdnZ6NxoWVmyTJb3/72ydPntgAH/3xt58/cuRqZ2dnp6fOEqidbrC+vv7WW2/ZK4P+6g/e+rul/mYuhmG4vb3tRlsDPSWTuLr19CkODgDg4lj9+6+T8bBI3XA4/PDDD63y0GiaH/x8un3L6QDvvvvu7u6uFbe2m1s33KjdbKI8LBkAIFCaos+FgdDO4jImSSezueMAa4tGGBYcYJyYKVPZbDLOSvNYCBGIdiBKG8nok6Nne4+dTfXhB3/41/d/Y8XXX3vr7k9et+Laymav3be6h1IqSRN74LUQQpI1qAEgkDKnTMsXD+x1o7TJlDUphRBBo1FnhCvTqrXe29t79OCBvfP+++///ve/t+Ljx4956X/yySf/93/5L5ZgbHt7+7333rPkeVEch81mwPnJDYqYECpxMOX5vVamjBm9hOpiAxnJ+yCdGc241oIAdkajBP8WwGYB1CwZH50k0ymAB//vvz76r/9qA9ZOCWm31iNaEkFZ24MGgh7KmTIVZMOWGVHZlXWbb/6v//F1lqi7W4PtZV4LXTeYo36wtsdfDBYHXw8PDw8PDw8PDw8PDw+PlwTe6PXw8PDw8PDw8PDw8PB4aeGNXg8PDw8PDw8PDw8PD4+XFt6n92tAzU0XuM5T94tDKTWZTHK3WACXl5eHh4cHuRcOEATB7u7u8rJj+JjNZjYwgPF4bAMDWF9fJyLn8kRkI3l9bCeTydmZo9YYDof8PQCEcCe5SymjKLJuJ/ld+xtAkiTj8diK5+fn1ksZQLfb5Q7G+Yfy6NkfHh4eHl8dQRjGbeeLuDQYcHqCp4cH7U57XnrAttttTkDQ6/c63U6nXbiNEZEMpDbMU46YS+jzYNht63z3FWEAZUxJXwOAeOdOgJBSmEoHa38DQDLHpXOnTObzyWRiY6aHY/X4wCQptE6OjtTlpQ2ZTSYd7scppWHdeKffam8tm5JiqtFqDdbXg3KMEO2mXF0V/cL1VAhR8Ut8EYSgMJDIBwsi67pIeQnUwDPZeRqWqIWviiSFda82ZKhavpPJJJm7wffiYnx56Ya56XSaMxLNk+Tw8HBSclMppfb39znfkpRyfd0RLK2srHDv6F6vt7a2Zkut3+/fvHnTekLGjaV+v28HXyI6ODiwOoAxONvX43OX5pMTc36uAcwnLaPXo6h4z9JS/O6762lasDo1YvPGj5KNG85zdXd3aX3dDfG9fqXEmJN4CVbXTY2JDaAqcVsQBg3mDs2Z5ziIKAgCW96CRFXTICEE1yU2NzfffvttK7722ptvvfWWFXd2dmTpLwqAiKSQgp6jLAEwMFoVpKGLFC3EosF/A4ABZ6IzWqsqYcp0OrVMpQCms6nSLtvnyfzi4sKWb7fbTZLEVg+ZZSpNFXubsNGm4q8CG428+ylFym/x9FZbikG136i3mqqcl3fZMRqtM6XyOGuj+Xs6nc7KyooVo9XVdrdNcVETwiDIMm1KajGldDMORVBmr4E22rncA4EUSeIajpRCWoo7j79seKP36wEnMyDGXPVVkCQJ52c+Ojr6+OOP9/b2crHX6/31X//1e++9Z8MPh0PO9PjLX/7yN79xzA3r6+tCCB4x2+NUurAFnJ6efvLJJ1Y8PDyUUnJCZmNcjxmGYbPZtITMNaIUY8xoNDo5ObFXnjx5cv++4+3Y3NzkxNG5CZ0POWEYfi256uHh4QGg0WxGJbctgE63u8HsjYvRcG11zepwg8Fgc3PTUvT1lvrra+urq44vFITMMGYjyAox8vNgdTSTK4cAAEF14pvrwZVubUxmlLb6K1HIokFEMggCrvxpXaG0GY+xf+iks7Onjx9bctrs9Hz66SM9mxtjLs7Opmzu8u5gcJtlRdTvN5j+ajaWzau3UJKIURyL5WVYgySUNGihUYr5jGol667LDilFw3IyV0cyqirrFVKvXORsPlTd9yZy7b68SSQZd7AhTUK64jPm9Oz0+MTN3v7xo/sffeTGtf39/U8//RRAlqnhcGTtHCLqdrt8yLu5u/H6645gaXV1ldvAN27ceOutt6x1J4QIw9Amej6jkwOytNmz2eyDDz44OipYtZUyf/hNsveZM4qSJEtTBWBl6fabd/+THbW73fC1117t94vcCRu4/TqW113eNRpBxFi7DIiR+0LKBcOn+AMAY6Ac0xNACBjTFRHFjbgRuQwhUkDRrNhsDkhQo9HgV6yNCoAIQRjyjH3rrbc2NwuKLwCvvfrmj3/0cysGgbQ2P8qMtSIAkPu6MSbNUpWpPCRXSwSRrM7aV/PCQCuostplWVJl5764uDg8dA3wcniZKldew9Hw6f7TsKSNajQa0+nUkm8RUTKbSdbYA6sysZwBgFxhY0ZvLtv7tfZmqp0ETMWWJ1p4oIK8vIsS1FmWJklOg6qV5vMUq6urfFZC37mZrQ9QWvhZpmezVGvLW0ZLvaYzenPw1j1PxxM3CdWMQ2/0euTwRu/XAGvy8SvXW5JfEEopa07nLMp2LTfLsjAMOddxlmU8JkTEF365WQ4gtyT5lauQ8zNbMX+Pfbb2nlzkd+2tHMYYHpMaNXSWZfwAAL6G7OHh4fE1gkS17zKBs2OAMAqllFYty2f67GSflEFtRk+byolxXw5c5fxqMFz3Mwv66PUqqjbgVLRJks1mtkNOZ7N0MsmN3mQ6nfHT8vo9nhVBGIbM3kAjRrOJsFQ24hhxDGtUBAJhaE3iLwtCpRC/HK7J9NotqmTm4he10nxJdjab8Q1Nl5eX+W4ppdRoNLFDXr4ayVV/YocdAIjjmC+h9/v9wWBgw1N1y5UkfSGzlDFWJ0libSqlMBzOLi4qo20e53Y8hzHlKTyQktptYfmzwwidDthRRwjDynKu0mDHYFWtvOeBGVzPqYtcfwBQnZmooFYKdbF6JYqi2uGIXHeimnG68LZaAzWm0Pqe0+QrfcpC+mrBc3uzBNf3kK8osAe01ipT9gAkpZRhj+e/nxOf5+ILBgOwEOUvh4WHbSRrd/IVDiuqMISUdntIfhynPSqJiISgyvxdFSohO/eH5xaTx18qrqw0Hh4eHh4eHh4eHh4eHh7fd3ij18PDw8PDw8PDw8PDw+Olhd/e/PWAbyzJdxx99Q0VxSYQtn2F736pbTPGgntJkiScIWMymfD9z3ngxW1aAObzOd8XPRqN+E4tIcTGxoaNxmw2Oz09tTu7iEhrt9FLa01VD+c8FVY8OTnJnZ1yZFlmD1sH0G63V1dXhaew8vD4XoNeML9q6Hk7HRmu6Uyvfe7LoHhR2d9qrdIkK9mJdJqSNrYjk0AACli0tCHe5csXRUyz24aggXwDrUb+6/kwxgjuYGcMtLabFSmXyptkTKDmNlpkDI0nSOblfcyn03TmxOToZP6scAEFMBoOJ+fnpvycTubot6gdEdBfanWsayLQ3dgMVtesKDpdDArnZwAY9NDruQ3MYYRG7DbIBgSSMFfWDwkEtcGUZZ2AcURIhm2cBUym7X5IAESCeC0kQLoXGWjOQ5ak6Wg6sjRCSun5bK7LkUsbPZoPk8xl3f7B/tm5o3t88uTZBSOyMkYsLa0AIJIb6w0iu0lerK8NOl23z/bG9trq6sCKS0uDftt5R1M2OH4a2dEwTdV47PafT8bp40cXk3GxgTlNk6NnenxZeK0bjcEgFq+6DAkCGUgCsDxYv3sXrWbxYLuNwZbpluNwECBqBc5/kgBhuBOvhlEs6wgCVQInomqFLvnA7G9WaAsjPQkgryrllmIHV9xEZFgnYoxpNtv9vtvLHQZRM3b53O12+Ye01lorG0sSVNeODNxOYwNBlFfgmnJyxWZ7FmvhIklS9Jb665sb9ubWje0bN3esGB5FqXJ75lfWVnd2b1mf3q0b272lpXavYIALwzBsRKL0vyACSVHQA9S2ahMMkY2VARQJXgKShN1EDQDQlRIDDLtLWiNlrnNKQ2WsD1K8uIWQcbNNJAEsbe2YV1kfsrNDK44XYCobh0/PVdlLzGbzk5OLNC1yo92KX7mz1eu5/erVpg9JWgbcUS7ju50FhLd9/mLhC/5rgDGG+/MYY4gqfZ/tq2vXXwittR3SlFLcpzdJEmMMd+kJw5A7xA6Hw88++8yK+/v7k8nE2p8549RzI3N2dsYZlff29p4+fWrFZrP585//3D54cHDwb//2b9YqllKmaTqbFRSgaZpKKS2fRO6Fwi3q3/3ud5wa+t133+U5ubOzs7a2lnt6PDeqHh4e3wMIcC15EVVdtoL8wWsCXGktlaDi73lvqcbKMO4jlaazy9HsouAoTuNmoHSj/FoMijXF1lQzsAyl5ZXreqyUMGd3DXJNFAA0TM1G4AhVGrH+E1mG+cype1pGOnQGZKZoOCQbXil6sIcT199ePHt2yuiXjseXB6NzKxIRZ3+J+p3W7c2gEQohtra3BgNnmzVWtqOB092FFM6DF0AgEYdO8xa5wVCKBJCpeG5WTZsQkCWVEZCr8y7vCLrILlOhSDLGqGRutWQAQaMhmdMgAgGWOp2lydwZscfnJx/c/9jSLM/ns2fPDqx/bJqmDx4+Pj1zc8qz2TRh5BTGSLgZEvT7/dde/wGAVrP36p2fLPULbqogELdu9QeDpg0ZyzBkc8RZFmSpc/E9PQl/+/80bPYcH11+9MfT2awo39Ho8rMHfxyNihobhuHa2lq7tJmFoNffWdq+6eyEjY3B6mofQLNJK6sUhgVvMAkTxdoSdQkSragTBs5JW2uj2GxCqtJUu7QTQgocP1x5sYA2hoSGfZygDZEuCoKAmoVGEPkcgTHGVHxciXjzzemYrAisrWytsDqpcrO2RBQ1OLuTSrLJeGrKJhwEYbvdFGVBFJ9mrw+CoDALCVX7sA5jKvWZpKt1IpS3X723dfOGvasI7ZLGHMD9+59Gf/i9Fd95992/+8//yWpTKyurr7x+r1U6KlOVzrowv52U/wAAaDICdt5CE81FYOfgCOB2PBlEOpElgxQAUGVSg9I5Ekf5jtkMw6FLchyh7ya8wiAebGznObncuq0cfzaiViS6rtocHZz98pf356U5fX5+fv/+p5PJJBd3ttf+z//jPy/fK9JuAM3Z0YCooYOWq5Mas4yttQTUlMItrnj8RcEbvV8DjKn0t9W+t3LlOj1oAflr7bPGGG4D59f5C4UQ3AbOssz2EQDm8zlfYuWrrzWkacoZBWezmTViAbRarX6/bz80Ho85FQcR8UjmP+zdPM41y/zZs2dW3N7evmQnYeTf5Yny8PD4XuLanq/eY1bxwrvXvZte9LyD4UGNMTrLdDkHZ5Qi45YjRb4CVXlz1Va99rv5TXuf/9bXJscYI5juDpUhTZ26Z7RQjmQYmcJ0DmvLZRnOhjhyRm+6fzRjx9qN5sOzqTPkoiiK49gOMaLdoFZErZiEaK0tL204iwLLm1hiIlXTQNfPTFQWq/MLHATDkrQIg2J13HCeWTImU5lm5LfGBEXIIkQlVoa0yc97AgAk6fxyeDGaFJO50+n08PjAzu3O58nDR4+Ojk5zEQsUjHHciRvOvOz1ltrtLoBuZ7C5cXN1pbBzgkDcutlbWXFGr1AgVryTCdgYjjON4ZlNIk4O6emjdFKy1A5H00cPzofltEWj0YiCFUmFnS8ltdvtjS2n6+/sLG9trQCIGkm3P5JBWdVhNJx5SRBBdSFem3x6qICB1oy33CC4tgYDMJXFXjYfll9dUJNyMdeF2K16MKcsAYiixpfQHIxRStkSJBI1JY5rYsh1rRol8lWozYWRizaBWu1WXJ7KA2CwPFhmtOe9o6MmY9vq9norq6txXFiGS0tLzXY7brrKc122c+QdVRnYEGki7WLl/gdAMAaGKoexuZ8AoBXYcjTSBLOpa84ib5iFRCTCKMhzIBo0UaYFAEKATUklR6Oz08ksKdrvycnF0ydHtgGGUiazhMpIEWB0JacFKrSEqVaGzcsYioBqXfL4i8EXa7ceHh4eHh4eHh4eHh4eHt9DeKPXw8PDw8PDw8PDw8PD46WF3978NYCqx+UtbqohIr43hl+vX6qCiGwYIuInQ9YYFLCwAycPb8XFWNXCW4zH45OTEyuen59zIqsoii4vL+3bhsPheDy2+6gnk8l0OuU+vVmWcfItIQQ/ja3b7a6uOvaC5eXlfr9vxVar9cIs8vDw8LgSeQ/3nH5uAUS1jpr3kAtd5Yve+GfaPWeM294KGK3zf4WcKTNJjCo+bNI0OzvT1ldFKVxeYDgsREBlGR8jmq3WUsupBEGjEbOjTRur/Wa/L5sNIUTQbLqDdoEacdGXBlWzk6iy2/mFyAPn/5fjhQGMMXzL8XQycVkBZNAp25Q7n83Go5Et5aPTk4ODg/G0GNfyA2/t+bpKqWYc86GqNhy3W712291dXV1dX1sD0Gr12u240bBEVpSmejx2TtrpWKUzF+fRKLu8dNsyj57J8/PQpmk2S8IwjGOb5PbGxkqvX5RLoxHduNEfDIpjfqWkwXLc6bjBt9EoCl+I6+sqGcO2qAJEFdVFCMF9v+15v1eBCPx7TMcpsNDWAEBrzZk40zQdDoe2RIgoDEOu5PT7/Sbb+msM6pWMfZSIpHQlmCeHR6MWRSsYUyVQysPZwMZcV5mNQfXNQoianmYTmCOOY5uoRqMhvrB2VOvWFpNz3YtqaaxCZ5nhzWo8nl9c2PCUZbIZU9lXCCnDOC6cpatfNdqYxNX8ZDq/vLycljyCs9ksDEO7tbsRNaRwqc+zmedcLWMIxLejX++G7fFywxu9XwOEEPxAeVrsxUtccwsLfT1VrdycesqeqN5qtWp+ubUxPoqibteRIsRxzAdmY0yWZWUXXYnVBx988M///M9WHI1GnAW61+sdHBzYrvng4ODDDz+0Ru9sNnvw4IGNmNZ6PB5b5iqlVKvV2mDOYD/5yU9++tOfWvG111772c9+ZsV2u80z1sPDw+PLwpT+iSSq2lBVkbNdob2ilLK8ernCbbvo5yiBddXwyn4eAAim+v1rQzNoDaYHq/l8Ppk4guWLcfLxYz0q5hyT+fz42bPJqCAogtY4PANjFe51u21m1vZv3H51d8uK1OnI1VWbY6IdBWsdCgSImnFcMXqjuJ72L5oeABViqvIav2Iq7nq1wFo7l0LBKHaMSTM1Z2wUT54+PWAOzEcXZ89OHFX16enp3t6eHUAn89nR5Vlaln4URcvLy5ZDSMrg9iu347iwJ4lobW2Nnzuwsb69vu5yMm5E7VYMQFDYCJeksMyO5vT08vFjF8mHn4z295wX78HB0dOnLs5GLZl0w1IQNZut5eU1KQstrhGrv/nbW1GjsOQbDbG721xaKoqJBJY3o/aSU/miqBhdZVCw/OYgkIBgZMWklOEsUFLWrNwwZLxlz5te5xIJUfGYrc3eK6U557a9O5/PLy4u7AT6wcHBP/3TP1lCkDAMt7e3bREIId57773XXnstF4EKJ2gegCchCIJOp21jRQSiCvkIVRc2yBSpyk1xe13QAu1ztUsBWHbkRKTsbhRF3FDPsuz01PmNE9Hu7m6nU9S6IAhq2tFzJwuwoBnW0iKBmvFcb41ag9HB1JCcn80e71nx5PBw78ED+7nGYKl75xVRNpxmq7V982Yz73OE4U68apxmF64hPPvsyfu//s2wNKdbrdba2ppN7/bWSqsVc/03LzILUbVsJEliVO2EYDGVHn8h8Ebv1wCqrqkuYnFq7Sos2r22exJC8G6O00fl4DoZAFFdUw2CAACPhtY6F6naL5+enj58+NCKSZJwIqvcgrXhDw8PT09PrdHb6/UuLi4sGZUxJkkSO1BprYMgsHY7gI2NjTt37ljx1q1bW1tOV5BSLo6gHh4eHl8CplTgTdUYI9TXfiq9dJ048Cqd8krUgn+hEeBFMIYroEapLMus0asm0/nhoTovrNz5fH72+PHQLu1qg/MRJo6juBFFfLmyOxgs7e5aEf0+NjacGRkJdGVxzE/NwhdVqikyXzq114yPxlx7F8XSd6722thqrY3m3I0X5+f77BiCx4fPHjxxyvrBwcH9+/dt+FSrcZbYQ4za7XYQBHYSOYoavV5/ZaUgYSaimzdvrq25Q5t2bty6ceOWFQUVlL1aYT51RnqaqqdPs9NTZ+V+/vn5Zx+7pfjHj59+/vnnVoyjtU5T2kq8urq6tdW0y1+9nnjt9aDbK3IgirC7C1e8hKCF0twGAF3SfpF4TnHxpmKMcbsJAClFdTn3evWnAiLUtKF6s6tqQfZnlmWz2cxamGdnZx999JFVVBqNxng8XilZoKSUb7/9dv47h8m5n0sQZ9JCfYk1txJtNHIFqdY55BXeaG0PsgKKFzmRSKBat6sNh/JKW0JImetpOYwxXPUC0Ov13EpGPUpXIk+OFfMY2mep/Hc1qhcMjuEAACAASURBVI29mgQ9nydsUWR0enr47JltR81kni31g7KKqizLsqx4nFBhksu0mrjpvMn5+ODg4LJULFdWVnZ2dqzB3263g0Dy1Evpmj5QPwGNiGRx8FVxod45e/zFwFsUHh4eHh4eHh4eHh4eHi8tvNHr4eHh4eHh4eHh4eHh8dLCb2/+ToOq25vzK/YudzkDkGUZpz0gotr2Zv6sMSbfgkILXihBEFjnpTxkxWvlK+83ru3B5n4pdX8YDw+PvwAQrttudv3dF4A/udC1cHqe2kcMAXzzIVX2xBkYFP+uQvVW7dMGpNlFvuPRmMreO131aJ0neup2PKrZLB1PjCq3N0+naZap0v0yM9oIoqDY10fGULNB3J2v3RQtd1SmiBtgzpkIJAQ5d0+R58ZCJgJA5eDWWpjnbSXkAYz9r0D9C5Xy17qyV9OozGQKgAFUmunyWaP15Wg8HTkH5uFkOp65rd3zJFOKZTvJqNG0W1UDGGliO1S12+1Oq9NpFbsrw6jRjJuNqBgliSgMIsn9CI3gZ5dqIDMGgFJmMlZZSdiTZmoyTuxBuwCyTPEzbINANptuLG7GUbcd2iGy0w2aLWo0CrHRRBCZICxeHoSVfcuU1+ca8guU//G7PM9F3UW7Tt7kfv8ZUHxJKTWdTtPUMRvxaoCqj+s35hhF1T3GxHuM4lJF+lIw1WaRi/YKobLvP7/Ow1s89yIHmSuj+Zxb1b3uKs1SexI4oNIUxpCrH0QkbJ9DuYt2HmuqVCsNk/J2TQjCwPqKR1EYx1EcFwptIwoFuX6FsJhZCwVRwTW3vgegK5hxvwiMMX/ysy8HvNH7Z0duXub1jBNT5bdq9Y93oGEYdjoda7hOp9M4jm23LoQ4PDy8f/++DX95eWl9awE0Go1f/OIXVrxz5w4fCabT6enpaU6nvLGxwT277t2797d/+7dWPD4+tnQRAJRSSZLYaOdJqKXiqrvGmDRNLa8VgOXl5TfffNOKg8GA+7TURhQPD4+XEAakq2pITYOpgepKS72TYM8aQuGGCphquMxkmWGmCRlI92QaGrQktYvuyDRlGphEFkZRIlRq0kyV2h5BCpF78JVIgCvZX4LMNKfM4s57yPz/SUZz9uBoCGa5zQ8PTj5/aMWLi/Mne4/tpKQmJIHQZTKFoMZat7u1lIskZHdnM14qRACD1dX+wIlhr4++ExEEphG5vBaCgrDM60rxZAKZZDSzRJwaRxjIijslgYQrQQNkgFN3qW5kVQ2Js/OzkyPH7jNV6TBLYDCdzR48fHBeuhcqpfce752cntmQ5+fnw0vnLhtBNJjnX7e78YtfvG0pXge9/qs3duNy8jdshP31ftS0g69sdXthw80XSNmWkvnLztqHD510camOjzIA4/Hkkz9+dnbmInl4cHo5dOXbajfi2M0Cv/rGxo9/fteKm5vdu6+uUjkN0Wg0er0mo7pU3d4kDIvKIwTabUjOsBmQYexNOV1VfgfUrFo3rHyJpJC8bhtNGbM3hcD1Pr282S1qCwB4eyYiyTiHlM7ymYhHew//8R//8fz8PL8+GY8PD58pVdQ6KZu7u7fu3buXi0LQYDCoTI4YbRhZtyUDey4oJ/tlQQi1qZuiigohwihycwBExFiFAZgyZClWs6MKJShlXUhGJmUzICl0ApWUvQpBCDj3aGOMMoWemUOUJGCajGLvkcTzG1CIZnB5Q0AIuweUDAQEQlfAajxRc8Y4df+T+//9v7u7KguSxH6sQYh7/aBdzBZF7TbFbURNACYI+KzF8en086E7NGTcoLfevDsv5zi2tzb/6q9+2l8qiMrajWil1ZXM37nml05xiKg661GpdQEI1Vz49rGoRfMrNWWY/1ZKVat6xWk+f5BfMczHO79+1Zufi1o8Xxj+uwZv9P7ZkdfdvJItzj5eU62FEI1Gwz4Sx3EQBHaEI6LhcHh05Pgna2cLBUHwyiuvWHFtbY2vo6Zpenp6mqZpEASDwYB/d319/fXXX7diu93mkRyNRsfHx/bK9Q11EbrKdthutzlzVRzHX4ITw8PD46UAmVwfLFETa6CqurI45rJnCTALK1U5tNEpmNELp+oBUBKIJEVldxQKJU0mCl0hE1qbTFub2UCIwFojAAAFuAWQGoQ20UxXjF7bbV7OMWaxOjkFY3Cd7T0af/ShFc+Ojp7ev2+nEXWvlb2yacrF20ajsb3ab5TsLyIM+z98vbN7IxcBdAeDFmP4BwKuEhitDSPpIUiY8HnZDRWkKTN6CSRYVkptBDMyDKhCo20ATWx+wABseRl5cTtxMpkdMaN3qLLjdG6A4XD463//wM7PZkp9/OmDZ2x8VEpxXqvN9tLNrjstb2mpd+fOu3bK9db61l+/89NeqayLkIJ+IEo12gCKYFeVAYzH4JRDw0uUZI4AcHigHzzIAFycT//H/3j87FlByKy1vri4mLITX954Z/XWK27eYX1zyxpyAG7fbf7w572rzwTSQAJUDrmpQlaquGsWIRCjwvTjQICw5jEAIFUVNl8Krnr0SlglIVe5+a36FaO1zgCcnh7/27+9z/i3iVhHIAStrq7s7BR1m4ja7RZXRRY0k2v6lzxnrsrkCkiIWtKvtaaBGoNWFbpaqRRBsXhmMPm/XBRVg9oAyhhLvQZAls1Gw/DX5nG0F0gjSEC2y8krSIX1qTLrpLNEjUtCeODi6ODJZ59aMY7jTqdj9ckAFMatoFVQxAfNFoURghCAMRUS7xHS/Zl7bRLS1taabbA3b26/8fruYFCszQRAW0Pwms6TBCBarJQ842uhvyu4tsY+x3ywuF7rrqH25i9ltX6pD303cWUmenh4eHh4eHh4eHh4eHh83+GNXg8PDw8PDw8PDw8PD4+XFt7o9fDw8PDw8PDw8PDw8Hhp4X16vwks7s63uMaDPAzDpaUl7ob0xhtv9HqFKz+Ax48f7+3tWbHdbttz6nNxfX3dir1ezxIbAEjT9OzsbDabSSnjOOZuRVpr/uBgMOAuvufn5/v7+9YP/uTkZGNjwz6+vb395ptv3rx5MxezLDs6OrKexjlvVs1voeaCb397eHi8HDAGJcEwUPcRAzgJaQ5a8LmrOWRdDxbAGJOVXagQgrtFCRIBY9w1MJzMWRs9n81sz5YkiZTS0gpGYRiEgWSse2maKubWGYYqCJhDLBE4zZVWSBLL3pRNJpOjI50kMBh9/Gj21BG6JBcXKXMPDYwOS3JmAL3B4Ie/+IXNPrPcM2/fNb3Cg04K0YnjsIwkSRFtrgXNZi4CCISoemdyV1wQUYWhyAjosiCUdk7IAIQ2jAPMoOJbSBDE/FCV1ul0art6larp2SSbFf552ujL4XDGcvLp8dFxSV8E4NGjvc8fPrLiXIpxIAygtZ7P55Ywgkj85Cc/idtFVgDYWFtZXXZ8jf2gsRK6rOj1euvr67Z6dMN2p9221UMbPTmdqDJRmcb+hbicldluzIMHjw8OjnMRwNnp/PzU8TUCTaIOAGOws7Nz48ZOflUILC2pZtMVwc7t5vqWI8Rqt/td5nS9tOqom78xGIMsNYxpDETEKj5AYDQd0FrzMV1KCkLJ1RwhYJuoMSZJUsNqCycuAZAplVeGRqNx586dwWCQX5cyaMYtG7LX6925c2d7ezsXiajdbtd8IGuEKexOXQ8hIktp9g2Dq0Baa67+5ad12BouhZQkmW8uhBBUuhRT0ctSLnBy9XoVogpzVeHuWul+TVWu8CStrKy88cYbVmz1er21NUvXHKxvNHd3RdnnBGEYhWHRdVR7+NXV7jvvFHojgOFwffvGtuVXHwzaS0ux7bqkgayw3wGwdWrhd3Hl+tvfBGqGQL0gqleoStHMb9X0ZGKHvACQUi4eiVJ7nL+h9rbrxRoWk2Bxza1vF97o/SZgK9liZeViDUEQdDod/sju7m67HMVns9mvfvWrR4/c8H/79u2NjQ0rdjodO0IAyMcA+0Wl1HA4nEwmQog4jjmj8mAw4A92u13O7XxycrK3t2dHiNPT006nY3WU1dVVHo0kSabTqX15TenEi5qfh4fHSwBjwIk6icC7gVzFqveFXPwKvYKB0VppYwCE5FQB5EYvuRFQQyvO76rNPEnm5WkcWZYJISzRURAEUjrt3BiTZZkNDIAI5VFBAGBQ4XSF1khSlJzG2XA43tvLJhMYc/Sb317+8aENOB6POSf/8urq1k3HRNVbWdm8ezewKs7aMn7+DpZKM0lrJIkzawlZU+qQqUc1o1dW9YGqqlTh2NG6Mo0RVNRPA6OZQioJENKWqFEqnc+tNp/OkvPj0/m4GEGyLNvf378oSZgB/Pbjjz/de2zFzz///OHDh1bUcSPrtJCzdm1vWxMxDKM33nj9lXuv2pDvvHHv1TtOq24atGpKM8cMdA5Lc5amenY5twPZPKWHT8TBRZGTxpjf/OYhP0nh5Gh8cuxIJVdWVnJ7rNPpvPXmO8vLK/n1MKQ33og2N11FWdlAz429SFOwUwgRNBaayTeCTMFkrhFGEYLAxUMpZKwSKWUyJgehCEJhS5+oovZobbIsZVMVxFsZUJwWASAMwxs3blhVJAyjfn8pCotJqHa7vbOzs7a2Zh9EYb0V4MoPFlQvs2D0kqhW/m8GC/YGj5XWORcb66NgLJUVPZdxuvxRS3uFpksAQXXTZ62/NZVLNSaupf5SePu2FdsrK0s7O+5ctP4SNjfBjsCEtvNllRf1+61+v2XFyRRrG27UaDTQ68HWC9IQwNXs+Lzkv0Ooqbs1UK2/XailHLX31Ixe3oIWqWGv17protaaX6lFqdasUH38mvh/i/h2ZrM8PDw8PDw8PDw8PDw8PL4BeKPXw8PDw8PDw8PDw8PD46WFN3o9PDw8PDw8PDw8PDw8Xlp4n97vFmr76fku/0ajsbOzs7RUnFyfZVm73T5nDB+rq6uc5qrf73Ox2+0GQWDf1u12b9++nSQJES0tLbVazpui3W5zscH9MYBms7mxsWFdTXJXYevs1O12u92udaPPOS3S0i1Ja82ZGADURO6v4uHh8XKADGTVf5I4fRIWPBWp6pRVdYPSWnPmGy2gmdeSABE52iRNMET5G+ZIoZyLpCRINusrq3PADaBtTKfskJuZCiZTUXLyCRlgniApkkHGhBAkCw9DAMHJOcaOgCq7vEzPzqx4cTHaPzhRpVusns+Ss3OTZQCyplBv37Ih+3Fzo+noCTvLy/2tLSvG7bZYXXV0U+0WOi3n+gaDIODZJwJBLM1CCJ71WpPRLn8MUHEyJEEiLAqGwFlkslSrqevGp7OpJS8EkCTz8Xhki2w4HD5+tDebOYaw46PjWUkYZgCVZdyVcZqkrWXHOPXu+js//qsfW7HV6fVW1ggIgqDX60VRMVpJKW9s7w6WCu9ZAOtBNxxaCbMEQ+eCjelEX1xkdvwdD5NnT0dpWb7z+fzw8NBSVxiDJKs4NQOz7W3njHv33kaz5cbNlZXu9vYqgEYUrW20muXoKoVZWUnaHRsQYUtQwNzzCMTqNgWCUPfQYxAwTcBVwjrI+dZWQUB2jYtkEEjuhS9l5SUkKnESgmpuhMnc1Q1BOa9V8QYChTIUPJGabLYDkBQ1G10Aq8ubb73xg9m8KIIwCHu9ntU0oijqdnvV1FUiaYwxpQs9ABCIp8LA6NzxHwCEIIhr8vlKmKKnuRLX36Uq6YmUkuekICEYG54wJKoUgALEvuBuEFUY6qqUeiCtkShkZW3OMn12BsskJ8isxOgwS6EZBqFTLGO1K6TjfInaLQyWXLRaTUMhdPHBJFFnp/MkUQAuhsMh6yU2N5Zv7Tr+1CBAp+u6HxlwWgBAAFJXspOKvxzKQCueA3BDAkBYGHG+DfBeDniOfywHd8TNqj1krmZbMU1TztHDFexF1CwOoO6IW2PhqWExwq5pL9z6jsAbvd8yeM3g1Tq/xStcs9nc3d3llfudd96xvwFEUcT916/H0tLSvXv3tNZE1Gg0+IPXv6fVanGTeD6fLy8vW2M1DCtDkVKKG71KqTRNrQigJtZ6AQ8Pj5cAZCC5Rm2q2h+V/yxqynmVOyUndLGiCpAx6uCck9kytRgYA5HTMifZPFFOG2hJGTJtu2CCKRHDdLWZlIpyO8uCyUQMR0VgIWmagGnzEWTEdf3jER4+sVL28OH4j3+04t7Zya+ePEzKVOQU+rkJuvSjt1uv3LUht27dunXL2cBBvx+uOdVQCCGCwGlwGiZlFNREFATcXBGGUPK7LsKoJMtc/tTHo0BSIJjy6N6jTnV25rrx0dnw6OjIisfDk88OH2aqyKuDg4P333//sqSknmfzZ+eHk6Qg65JSrq+vdzrOELyzc3trbdOKb7/99g9+8AMrbg7W727fKYZRXk0M1ASaMSgrBe3osTAc48hNSuD4WD18OLdssc9Oh+9/8mQ0LZ6fTCZ7e3vWko8C8+qGWu0WoxURbW9v37y5mosA3np3+8133NzEykq8vZ2nSGuRmnLKxxiTZgmvzFEYEqtFC+NwYK4zeiWMG5qfj+cXfgbMK9MYHEQyiCsUSVWIKi8dIMBMrDTNppPUGpwykEIIazYTKAyigBVcmmZZyniwZCNqNgFEQavTWrIaQhAEnW47DF0GkbjOpjQauixcAEJWzFNjjFaMsMcIIyscxXVcfefqKAAvuktUmS+oGb1SSGEgyvab95E84wVwRcyI+LRCDdpgPkdaZKyZTvWDh8aupoTSvHEDcbHWAkA2m5IthASt9eYym2eRBEZyZiQ0XM2aTrPHT6bDYQJg7/He/jPXQ/70p6/duuV6tjBE4Ob6FmAMpKqMC9XCUpBZ5q4IUeGhv37q6BtDvYO9pr4BKNVjY0yaOu63/Dp/T5IkNaOXfyj/bcXFjxLR4sWXCdcZ8R4eHh4eHh4eHh4eHh4e32t4o9fDw8PDw8PDw8PDw8PjpYU3ej08PDw8PDw8PDw8PDxeWtRdRjz+BOT74/ku+dqeeCq9c6/fK2+M4bvzhRDctT3397jmDbVbfOO+vcLFOI7zK0EQVPgSFjzX+YO1rwghGo2G9bSpxdAYo5Sy7ge5i6+9awNYcfGu/X1Nwj08PL5PWGzK/MriXRB33xKy6mAoDHdTJSLr0JtDQ+d+rkKIEAXdAABZDWmMSZhHqzY6jEJL49doNMIwtGwFkkQ2Gs1OTnLRGHN2djYaFR6/AIJPPpMPH1kRwyGVXE0AGo3olVdesR1f0Gg0l5ZEGILQev1udGPDhhysrISMj1A2m7x/fk6vKAX32jVam7JTJQBVn14SgrtjkhCSeZEqpXTmuJ2SaXJ5caaMNsYML4dTlpyDT58dfe6ceGez2WRS+OgCmOrZeXqpS8e+2Ww2GAys164IxOu9N0VYRENKubay1mHkTmuDlX7H5cDOjZ3VFec922x0krnOy5GPF0ZjdKbmYzegnJ6enZ87L95np+nekfNDHg6z4+NUl66nUyWIgjgu3ArjOFxeDi3VUyM0b+7ojb77XL8/aLXaVrxxa2lpybkkNpuu1gFwtY4gheQkQ9yrHIDWWhk3PgqihcH5W4DRVdViQdvhFwSJKAxs+BpbT5IkT58+Gw0LZ2ljzPn5+XjsKs+rr76a+7RLKeK4YenQhHyeNsQiZYxh3u1AVbGpPZkrVza0qKXhm4IxhqtAxphqnIuL9q7WRc8GgIAqrVVFEa00jaqeacZT/fTATAtWt2Q0Ovjoo/HxcS5SFDYbSaSdt+1gdbU7cJxtQssKJVg127LMjBPHOnh2Nn348NHJySWAy+E5p7ubzRLG7gLKqdPY23hxCgNjQFWFtpr6ahWtF/i3g1okhBA8ki+MYh4gr6s8cM2nV0rJq01uR9gruaO4FfNKwt/2wmjUUKtaVqy19O8OvNH79YBbbnml5KKt3NdXAmNM7nSei7W6S0TX8EstwlTtybyns6IQot1u2/hcEzFej3PwwEEQtNttGyBPrL0LIMuy+bzoT7XWNbOWm8S5+L1rQh4eHl8ataZ8fcsmcPJNISTniyUyNaYrDgOjoXOLSwoZCNeFhjCCkfckWWK5YQForZvNpiXtazabcRxbGziUYn5yMiqpcZRSH/7+948fP85FAM2PP40ffG7Ffq+3zDTF1ubaT16/R0GRirDXa9+6JeMYAG2vYdnZeCQEN3RIyAolSw7bZ5IgGdjcNFrrNDVuFCAyVMmqKOIvF0IKRh1skiRNEtsDX46G9598PkvmWulPP/v04ODAhvztf/vtB//fH6wYRRHn/G/04s5G17JG93q93d1da0/2B/0f/08/Wd1cy0Up5Ep/pd10BiRV5jQQyjCUzoZUU8yGCrlObAxKxVgp7D+dnZ+4weWDDz6+f/9TK372ZPTRA0dspbWxFi+A7srmzps/tZZ5v99499215eXSBo7wozvYWnbhlRJ8ZAsaJCNeY+1vIpAtIAIJKSo2AzQnlMp0lqRuIiYIREOYF7WWPzu01pZ4HABVSaGFrNA7SylEM7L2Sm0Mn06n//7b3z16tJeLSqnPPvvs8PDQBvj7v//73d1dAEEQRI1Kzac8L0sY49oBigJ1kZRS8LpdgxBCRFezXn9T0EZznQ0LhjrXiLTWmcpI27oEUTVdpChNo6oKp5RKWLvWZ2fJRx/pcj7o8vLyV//yL/tPn+aijKNNXPTGu7kI4LXXXmuy1i0RBIy5qob53BxfqLTsJ/f3L37zm3/f398H0IijRuwa8mg0KfVEAAgihKErXmPKmctCXijvasUqewOHil3Hrn+TIKI/WYnlqnUURVfpyfldbikEQcCXtXKjlwf4k6OEhU9rrXMThojCMOR20HcHX8KI8rgKtdaVX/kqNSnH4mu/XnyVFliDfc/iC2up+HMnysPDw4ODK0vVReB6X1TRJAC8qGezi6hGa5VlGVuqUGmqOC99dTqPiKSUotQ8giAIwlDmy8hhUCHtrX13IRpfBkWaale/IIwxOW92rtlw1v15MrfH+eQheXaJVGZKiTK3tdZCCKeEBUEUNawNLIWM4zhuuGVSozXYCVWSKnPBmoxhJezy2BhtwO3YLNNp6mzgJEnnc3Y+U1V7y20PmwohKAxlFBXlEkWIIvCz/LIM3FoRlSN+riu02q6ERVSXK+s19ltBLRJ1bad2O9+lcUUqjalMfOf2GOeerRqB1VZ4xTu/x/hqxVvJ5i/8KmOM0cpOjeksU+wgSZOJLFO15RPWzF5cClrDTj5o7bb+hVoa4zo6rxh+KSyORxbX3PoG8N3X8K+c+vLw8PDw8PDw8PDw8PDw+L7DG70eHh4eHh4eHh4eHh4eLy389uZvAtfskVsED3z9VoHFu7X3c7G2fYuj5ge/6D17fbSvD8x3sqH0KOB3a+Frkbz+0x4eHt8DEJgTLrCw+a50TCtBlV1zpurWWeOnMah0X1TtNIQxQbkdT1SdeEkpMEIBkakwdS9vZrSMAFR4nXVTo47OZvNym1/UuDCR6A5zSWulz4dx4t7WWV/rdB0bU6/b6wyWrNhYW4l2bpDd3txqUb+PKAIRoiYE5z2qZg0JMK6jBTIXIiKUyTckICR/g8oqWxPHl8MZ20o6GQ+HI0f1NJ9NR8OhzdvhZLx/fJBkqdb6YH//4vzchhwM2u/87DUrtlrNTqdrxajVag4Gdk9yp9u9ubPTKPczdzrtQXe5HZa8VkRChTpxaZxPkSYuCUZLw6rL8DQ52R8bA2NMppTdcK61OX42HF44tq3j82lGbtf06nr4o17fimEo4jiwFafdX16/3Q0bzUJsR7e2qNctXh4FaMaaHPMRRPFXgKSoemMWZWJgYMjoK7c+E1VrL4XcEVWQpJJM6/m42rkdACCuXueQMFfdglaJNszh0hDzUoZBhR3NmMpObwIRXCVM0nR4eZlmxcbys7PzR58/elh6v2tjZtMkCt3GcUGBVgAgFuNuWNU2C31KtR+o5fOfD1/pM1qbjG0kzhS477QylGmRFVeEhBRVPwLim+WJ7KO62k2kCrPU9gPZdHI+PEmHp7k4mU2CFnVXCi4DGTf6a8tLa45ar9HpUejaEZmgkvPVgkiVHs2SeVpE5XKS5P8ArK6u3GKMfatL/ZLMDgAEVWsVd4UHCMYI3g0ANWYHA2Kt7PuiRta036tEIuIpqun2Wlc8w3MmHdsd5YGtu/tXzxn+BsoJ4YypxfA7BW/0fj2oaF0Lhf3Fa0AtWK3S167UaJ9qBmRe/6yY13Ubng/JSlV8NnLHdysuxrwWK/6qGogoCAJHeSplo9HgHCdBENTez8kniPnuL0bDw8Pj+4GaRr3gp5gSM0YXoMho9oSGNiy41DqsMdySdNqfMWFqUPh2qooL5WSOsVPlJUzMerblmbiL5ioVZk8wVukfPj1nXrhy5clRSXMFgIj6rI/a/MHba2/ctWKz1bSsSABEsxUuDRyJVBCIRqNwAw0jMKKmOkQlJ7XmWjGIQGwQMBIQ0mq3xiBV80w7y/zzx0+elIw1AB5+ev+TDz+04nB4eXx87Dpko7UueBZr86Tv/uLNN//3/9mKS/2l1TVHsEymK7BmTZa4ES8NlsKwyEkpRDtuhCWnlzHIUpnNXU6eHeDC2deYTsCYofHg4fi3v93Txmitp9Np5mwGNZs8S1NHVdXv97tdZ+W+8e7gnbcZJ+0gvnGjJ0oGJiFF0JBUmnZCUBSRFEXWEZkoSoR0OUk1TYoaQIUYKS8UraGyirbOywuAkJyyDSGFQjoDQwglwIzPOgxI4cqWREADjL28AuO4pmowRs2TM5W5TG/EzTB0qdMKumQqAqC00Slvj6EUTSpnaoYX5x98+OHwsphbOTk5+2//9Zcff/xZLkopb9++vbrqKk8gIpUAgAkgBa60KQ1q8RdCgM1KENFCAqvy16FgvPAVLwiQKlWyKAMw84RYTlKSBfNMhkWtk1KGCISwqSAIN+EFEBWk5oA2YAVE04wuJ8jnEoDp8cnD/Y9GJ89sgNa6aK0XRSDj+Oab9wZvvWvv9rt9tpI6fAAAIABJREFUwcjVKZFw82aoErFhNs/2T4fjcq7w2fHlk5PLpydDAL/46Y//wy/esyHXNrpN1oiMNPxFBpV2ATI6rBS57eILUVfCk6AX5v23Dq6fozRW2X2HRbW5Zhdwr/g0TZVSNnzuU20Vfq5jPxc1bb/23drj3Ab5zmrs3uj9+lGrJQCoXLO9vh5cfxfPezO/slg7+QttHHLY33lLW3zz1wUejfx3dQr8BUn28PB4GVBRWSoKpwHMokbKoIGq0VuxgUV+wSHXdooABFNdA2DfUQblsglQWUkAEGjEoKQ01UgZM51nVCoTQTALh6IkRiKiOI6DcnYPQNhqNtZWrBjFcdh2jMSi0ZTdjluzFQJBUCisIuBruV8A9Y6fCyA4PdgYA+K64TxJ+fEw5+cXR4w49/Ly8vDw0CpegmDPipLVkwXiRri64bipB4PBeqk0A4DuIl2za/1RFPV6XTuvKoCQ3BqeMVAGbBIDWYrEkWRhNsXEHXSCy0t9dDLPqXonk5k7C8CoJB2rrFiKBxDF7XbXzQI3W/HamluOXl1t7ewsOdph0hBZpbYATDSGNNxSmsvjEnrhWSAf76r7FqhCTV1/iEgKVnepZlLUYQBVf0UF5vl3i4Os6mkoYYxRWrPzZEzElhFRJQQHjDas/AykgdtfoJSaTib2rJrxaHR5Oby8KGzgIAhUpqRwxUQQxaN53HkcF5PCrhCv+d8ZXB8hYxw3HgCjK/syyBhoYxswiWrPRriyEGu1RhtkyrJL6Sybp9NpUvQDQohWq2Wbp4zDqBk3mm52T4YRWAFBVA+Qq35fa5NkOilN9yRTSaaTTAEIw7DP5gGbccTNVFPt82upMjCoDhkmv2hBpmYVcuH7gueq5S/UmWv6fP7bXsnv1gJc/85aNK4JXLM42J3vELzR+/XjqxQ2MdP0q7wHL3r8+rvXoNYAPDw8PP7M+Ap9jgFXHCswFRWz1rVppTQ7j5SIiE3YCSFkIO2ptgSIIOCH3Ap7XkgeQIiKCk7F35dFLTU1BcYAyDQ38bU2NveMMfP5PJm7RYAkSTgJs144LiUMQ2f0CgrLefya0RsEQWW+v7Z8SQTh9irWRh5jjGLqrdZIU52mLglpgjR1z6Qp35MOrfL1LEMEKYU1rY1BBKnYCVVRJMPQKeuBFHyPbn1AzLPtTymilxA8G4gWCafpuhZaD1wFkeRU3lLyrWEARHnSFfCiV305XB3hbw8vTF81wAuDX42qcSJYEQgpeVcmg4Av3wFf7rNEJMhthpdShGEQRSGAoHrY7EKt+i4W0HcTX1Ynr/d1f2HwRu/XAFo4mLfSmIlMOZVS0VCeF/Ka9yyi5h9bC7wo8sB823DATvHKr/BI1nayEVG9E6yCBzbGCCHsrGG+y2LxbVYUQnDxhTng4eHx3Yc2lUNQ83ZtW/YLW7iGzpgro64e2RhQxcNCkACYCqU1knmxohsExRZiAEB6dpY8dpv6xuPxOfNT/fwPfzh89mxUXun1ejs7O91usTYYxfGte/f6g+UiNJFstfhRn61XtptrxdmzAGQUSebWQTIA0+yR50XeMZri77nIMpUw0zTLsul0bnvU0Xj8+MnjaXl6UJIkh4eH43I3sFbqcP/Z8MLt+L28vLRrbgDiQMYsCffu3fubv/kbm7ftdmttdSXfllyz4bubUXvdJafX7g36buEXpg3Ts9uyjUGWZfb0oPlMP9ubT0ZForIsffBg7+Sk8DAEcHnemoxc1iWJns/dVIXSQdSIAApD+eqr2+12EX8hzPranV7PWfi9XrPTYT69K/Hmult7D0OZZc6cJtKCErueSUQUBOxMY6OhDauThJotWFvAdQgCVFZ6q+EW1/grI+C3MRoSEIahZLusubYAgISQzPNYGF0JYAJjKloBH+Wbcfzqq691u0VtCcPw7/7j37z51us28K2dW3mVpHxBkbeMWtYRu0v1u6gsmsJordk+f8qjVGYvAbyj+MZACwQovGeTUsrAnbAqgoDCsBLPRa/soksxdl0XgAAC1hP2+/0333wzGW0Wd6Mo2tiQpeMGBWFz93bEzs0WQqTKzZQFOhDc2dpUVpVbcXjzZn9ebq7e3IxXV/+3yWQC4Ed3b6xuFc4jAKJI8gcVdGLmtp8XQoRBeI02qOvMDrJyanG9NnwLMMbUdizX1F2lFL9bU7yFELKcJqjlQ/5mKxIRnzYKw5Br+EEJG3jxbTXxepvF/r7qyncN3uj9GrBYb65CrQKJa71wXwjeYF4Iunpfce09tUgaY7jHr214V6HWZmrfxfMC8N9fKlEeHh7fA1RPTCWC20f6BaChFTMwDEx1Jxvlhm4hgSp0LsYgzWBdPdlibDYezY+OrHh5enqwv297p6NHjy7Pz8bDUS42m81+v2+9DeNW+9a9e8sbhaYIIrTblZNbBy30nJ2AoGblClC1q3e9YqV7rKjqgFY6YXRZSZJMJhOr8ZycnH78yacXpcPkdDr95JNPrCWvsuzzB5+dsiTXRq67u7feuHfXihsbG++9955Vj5aW+rdf2S0YGapDwFny7CJ1+6LbcbvbcjuHgSbQRKkZJ4m6HM6ycmP5ZKweP/7/2XvTHsmRLFvsXDOSTt899siIyL32nq6qnp7tCfNhZj7pd+j9NgENCA/QSAK0QYMR8GZGT3rTXV3d1bVk1pL7Ert7+MbFTB/oNLs0RnhmVtaSlWWnKhJ+SaPRaMu1e412D8dHBwszej6ff/TRV/fv3y9EANPxIJlZm9thoFhZW9/Zu0JErVZ05crm+vpiw2QQ4O23sF22D4A4rrRPIFDGEQNAliFJbGUL0qDMsEY53oguejQz0it2Py40sYmK8MKLsfTkjwMiKQPJ4syZ8w8Uvaji5QoIbruLnL2ZR7XXhVG0fWm72Vy0WqPR+NWff/Dnv/7AplYVJ2oZaFntaV3Jp/hgrBGF1oLINL8mIq2dTv4DwLF/HKeoeCNrjpAQkOx70Lr830CXjr75AQAgIimsh99qteKdXZ0swt0pjoOrV0WvV6YWeXNNR1aVZXnGeQGkrpmsrAxRJNfWWqz921euLJYC12J02Xh0vGWVq1SlRs8X/j5XVhwaWmvNx6N0tOirAcetpdrrJd4nHTu86BtFDTj1oGtOr/N+i3ek4vcLORqvGbyD4eHh4eHh4eHh4eHh4fHawju9Hh4eHh4eHh4eHh4eHq8tvNPr4eHh4eHh4eHh4eHh8drCx/T+oODRLIXITj4bPL2z4x/PkVs1PsSWxImYd1CPEGAn3XACB0UhTeZKqTRNZyXPCoA8z51Smd8eHh6vBwiQsJ+YIBApG38nCCFdrIAAoYRikWNFmJoRgxySfU6F8hzJzOSnR2N154GezgCcnp0ZVicAw0ePTx/Yr9RqrbRSphz5ZDpryRktQhnn/Shfb6uNRfCh6rTTq4Nkz9A1EcKIWJCojpto2O98QAgeCUm04OVZQGullYaGxujkeMoKeXBweHh4wMSjBw8eGfFsfHZwcJCXQZNJmo/OpiZcVkoRx83t1UUQnRDil2//stmy8bHtdtSMrQ3Q7/VWB/zLQ6u7u7tGP8dxg8JYCQlA60qDSQya2jJgHT8Mb+3bcL2jo8mdO19k5QeFZ7P50dGpIbLKsnw0PEsS24R5ng9WbTDum+9srAzs93WbrbDVsvfqdFuraz0CwlBubETNkhlHCKytZK02C7sVWvNPVwmy8ZCACBCyBiEo0gGVXNAggoaJDCcCUSyIxWwXH1GxkuBfVCnC8UqpQq/9DLgMPBp6uc0W8qFRBV38kkODqnG3FWgg4rZilmac6FsGMghsxG+aJsnM8odJGYZhZGb2Tq/zxps35/PF12jTNNvZ3ZmOp4UYBMHW9iqIsYiXpdZaa22HJxFRnSS8MqScT7cSj6YWRCRYlDIRyGE+cqv+OUG4uAWehRAiZnzjMcmG6YFARFJCSvtJaEk5u1eW69EE5bBSKh+NRvPZHEAcRu2G7asUhtRsWfMvEmhd17q0yoJQ9wcqMuNXJDrK5mykyIBTauuZzBa8BwCgMp3NrW6YN0j1oMqHEKAAi2/KSaFhPzIMKM2/ASZJR8IOcyGEgBQlA5wiZJVeAkWKf+IoUDJgtF6kq9/VWjIUvk841rKufiuoHmfLz1IJrXWe59xiT9OUk/ADiGP+cW8xm81M5kmScFoEk61Jz38XJXRs/kowfI2WyPnxCmK5AvX4juF0r5cBEXF/0hzkIsfynu3EwZvfhVgfjQbFtaYYxV1MDkUJzVmtdZZlZsJDyedsxCXl9/Dw+ImCQJIrKl3hLCFCQNxlcBEqsnZTHXOFKcsuyTGewuicw9P8s7t6eAbg+N69fUbjdHhyeHhyaMRut7u6umpUkJrN5i0xK2mc5r1QrTb12sKPVb12ttdLrg0KEXDNZL1gb7LgZwV0yEw0pVWuoDU09PHw5Hjferm3bt26ffu2Ee98feeTj/9oxJPTk7v375qP0zYardXV7ag0WLvd7q9+9avNkmI6ihr/4W//4eYb7xQigLW15mBgzSNVIXmFropEIAFFAKr02YDU/SasX3r3KT7+d3v2y69O/+XfvpqXn0qaTCb7+/tJshCDIO8MzsJoYbSFYfj2229vbm4WIoD33t954y37xeP19e7mpmXJajRgPvYpql4PqZy09eUcFhmQ5FxiQkIElauhGPGY1shz06kAItGAdT+gq+TAQK6ZTS4ESl5mDcorvX8paPHHDixzeglaOBdUQOqCWxelqjwAAwEhmPeVp5Nkbp+uEQvu9GZpOhlbE7wRiyi2dnO702p3rpmzeZ5fHY/SsjMQUavTqbgzoiyXUkpZW58gJFW/aE0Ebj8opTl5nqisMok6k5yDi2vxGbioFgssPRuQiFmniiAj5pwFkJICYRpCCyi2tJLk+vQM04XvmmfZ8PHj4XAIYNDpxit2BIleL+iukOHvDSLdDiFNnZMmaZ5fa0rm4Ty1xYgbImJ9UGfI2Xez0xRzSyePFMgjsgtipAOigsRQ5BrlQhhQdE42ZEhE0jq9RCTA+rZGToKv0+hq1RJQmXFQ7fjilXB6gYrF61jaVPM2DZRSPJ80TY06BUBEjtM7n89NVvP5PMsy7vQaqsI6ijJwL8PVonBfgxVPpJ/17d8fEefXqYeHh4eHh4eHh4eHh4fHawDv9Hp4eHh4eHh4eHh4eHi8tvBOr4eHh4eHh4eHh4eHh8driws3c3t8azhhrqjter8IPPy1wDO3xS8JiK3HDziZ87NOCXlKJ9u66JSBZyVKFGLxgDwOvkhjftcfoUBxF+esh4fHTwbEgq6cgaw1CE5MZAVudJbiwabZyXD+6MiI09Ho+OlTVYa5Ynimv7yLyRRAlmWtliWXamysbrX+zIqtVqvXM0pmeOfz5tHXSRkKJqVMksSS8DVCpRSPIXV4b7IsTfMFPQ+A8Xg8Go6MOBmNTg72dfkUs9ns6PioICM5erJ/dnJqUo5Go7MzSxSjcvXWW28ZEYS/+Zu/MXeO4/b6+qWoJK1pNBq7u7vd7iICNgiCK5cv9fuWYqrRqBoA1cDUJNGzmZWn09nx8UmWZVrr/f39IXuc2WR9Pl1EDgN48kTduWMbKEmT3Z09pU1NZlG0K8RiFghC1R0kYVSKgdzZ2ez3yzhdYO9qf33Ttlq3G7KANZh4tPrkQIs4wAW0qISZCaAWslzLgoOfJaJqADE5Mb1E/I2C5TAjOMGixQRXOcTwasx6mhO8AZBSRg3bizQwm9qu/s3XX3/0u9+ZhxoMBntX9sJwEfTbbDa3t7fj8nICoiiyoYx1AhHz+I4NULRXtVHs7yKkl7NtEXEmOQdKqTyzMdskhQzlD1/zSiluHTmiznPkGcyRQg2WhUzGk8OHD2flqEzT9M6dO0dHRwC21jeyXRvz2VZqdWuL1TIJCBuk7zw0IZAoCaQW4KxJD795cPd3d4xIFAjGENbc7Q0294KGDeq1+esqZwDAieVQMCSxJlDajjENKEGKnXWGkHYGmq6KP3TDLiCEMN2bLg7ZPRfGclZKHR0djcc2kPrs7GzKBuC9e/eePHlixCiKVlZWzL3CMHz06JGZU8Iw7HQ6JqyXiCrjsTxofp8bwWvgqLIffgQ9D7zT+91DKZWmqWl+IgqC4Dn7N3dEn9ljKnNADY7GRDVD3julrOj3+hy85C6oni2KZI4Ug5wPITN0jeg4yeY3ysRFeYIgWF4MDw+PVxhL2VC1rtgtNRVUQZ5zsys5OBh99oURnz59+vnnnxs2SzFLwoMTSjIAe3t7GxsLKmMAg1+8s/LL94yIKIIh/wVO/73b/uO/znPDtxTM53NjaugwUHnF6XUwT5MJ47B99PjRnTt3rHjv/p9+//usLOTJycmtW7cKw2U2PEtKNhoAa2trq6vWn3zj+s1fffgrI25tbb377rtRtLApm632xtZegzG1OpBhSSMDAI6b4Fqh87k+Pc1NU+zvDz/99MvJZJbn+ccff3z37l2TcnT6y7Phu0bMsoyziV69tvWXf/Vm1FiYwmtr4t13ZaezuHcQorcCQxZLhFYL5QMBAElOogQpraMLoGoYc5AgIThnK1WmNlLK+g8AhKjY3A6K29g7EYnqfZ0OS1Qp9OLIOVBK6XI5oA4hBC3nW/oBoKGU0oxzSAZByJze6WQyZSb4J3/8429+8xtT1bu7O7/61YeGWWdjY6PX6TRKH5gIjTi+qHIAQC8GWcGoY48T1dqgAsf+ISk5OzNQaTKVq2Rm+ZdkIIWM+Uj5YaCUMqR0ADjhEACVZTrLwRJwPTk/Pb3zzTfHTxdEfUmSfPrpp0+fPgVw/cpVKhndAWwIMXjjDdOriCBIcGLz6loewrDSlecJGGsSPv3sy//zf/w/jNhsNvv9vjHVLv3Z1b/4cDMku8Zhs64PQE7jJIiqdqNilMU5US4s9db54K1H1RH6QzcsABCRlHLJO57lKPqG1jpN00ePHnFGxuPj49HILkHevn373r17RsyyjN9Xa/3mm2/2+wvewTiOt7a2zPAsUi4pJD3LVzcujLt69cpgWek9PDw8PDw8PDw8PDw8PH7S8E6vh4eHh4eHh4eHh4eHx2sL7/R6eHh4eHh4eHh4eHh4vLb4EWJ6l4eM5nnuRDXM2beui23x5qwQgofL8nyKU0bEefflcHauO4nrZyvRQUQ8QVFIXmZ+9oWKce4Rg3qpuEi1zfdOMUx658K6yFvEydapirrIQ2uUUkXlmAQAeNSKieA1MLW3pB48furQgHI/L++AlsRPAkvP1eAMQeKBf0UfhgZAz+h1pB1+DwdLT2JxkwVeoIvrxd/5Imr3dXJdeg+Nal1UsyZHrudtzjq5KA11cQSW1lDKtooGdFUcDjG2RB2jo8Oz42Mjjh8/PfnGxpcmSTKIpYoWOiroNVt7m1IIAGubm+2VgUkZXtnM1y1DEoIAkaVgmbbkAdFBWYpM0z4oLauvmanBo5OpeFyIWuvjo2NOLnIyng6ncyMeHhw+frxIDGA2mczmMxP+1GjGb739diEGCIW2GnJ1bWV1ZcWI25ubN65dM2K/3++vrpmZLooaUsqL2lhrjIaUMBKa05PZ6MwWcjpNpxMrjifZycnMtMPZ2fjJk3GSpFprga2NVcs1tbu9FYR2tiUKARsdvb3dfOsdKqM40e3qS5dgyKiERLONoDxLhCiqRO1CgNg8JgQEez5iT+t2fBBf1icQ791E1SBeISrvAAgQVOnG/K4oQnzZAReVe1WL5kzK7hEOIsGv1RqV+F9a/GfkigopYnGZshOyyNCmMOcIkg/a6iSOSi6LAtkb3bt3//PPPzPiZ59/MRyNzBWbWd5ud9rtdiG2210hQ5hAZYJDOqRUDsWaSYiyzE6FE0AuwxKDEAKS98lqJfPnAUhQEAbmIUmSomJKKo9UVR2p8sbOXAK4HaN6XlXL61g7GemUdZuUdCqsmAtAkO20RBC2XHkgx+n8dFqSDmi9sXtpsLkOYGdvb/OtG4urgN7mBsUSYZmzJOgAapEtwZ2IqgMOTx8+ecyIA+/ev3c8s8R7Ua8x2F4RcpHbYLXbEaJtKhYIy+4eCELARxxVxgFpgE8ZmoRtEEkIwbRkDefEb1/YU14VONVeNwcK61opNR6PT05OzPH79+8XwdsFxuMxp4GI4zhNU5PbeDw+PDxMyrDsbre7urpqWCGIyOmTDs4t1bmi1hXiwFcHP47Ty+maRMHSViJN08lkYsSzs7PDw0MeG91oNIzTFQSBYR4jqmj8RqPBnd7ipqY9nMTFES4W3cuITiEdjgTBONkAEFEQBOd2nXMPcixxU58Jp8xFMdj5CpRSpladFnEqx1mGkFIaJkacd1MuKqWyLDOX53lORPxyADzzPM8r5BNEDsmWx2sJDZ0h516g1oAViUg67BocVDvC4Z7SyJlLRQQhFPd7c72gliEi6ZhKFVAOucTvpcXf+SAF5Ll5RBIkheTawfU+DXSN9JIbwlQ1oZ2xQ9BCLCmVAvLq6UopNJgNBqpad6QBVRZbo6Q9LsQcKnHzMqLSmCvkRtbIc/uMWuOLr/HwUXkW+59++s0XlrlqODs7HFsLYH1j4+bNm0bJxBura7/+RdjvApDtjmhakqe81cpaC1t8AVZdw5XGN0SPSyt1VVNbi4FeVG5jls3+dL//zbAQ8zz7+OOP79619CFPho8PRgdGnE6mnIR5Y33j+vWbRj+vra394he/KByD7Y1rg/6mSbmy0h8MekaMAhFHVquLYg2xLDZpCCUu8gSUwtPHOD60Rz750/CrL+3ywdHR6cGBNWcnk+np6dDocylF1AgEkRB07drbb1y1lGBvvDu7/oYl32rEcZuxZDdbzcGARNl1pKRGo+JvkuNSOI6CO1VzoYLaGcnZpIiq9VI5eR4qA7g+Gt2RVcM5hwCq3lgvJYUpYPPROs+VpRYTREJax29R3rK2NHSaZ3xmDykMAvvMZu6mypMWCsbeBdC5zvNSyRBAIO5U/O73v//Nb35jxOPj48clnRKA3b3Lq6sbhjin1+uFUUzMHYXmiwtapVnOTIIgjGRZ5qrjWl2SqEHKQLD2JVqWXkopYpu5AhKqGDaSPS8BgdJkmL24+hUCpb+3AK9HIKeK36uh+Kw3o3wqbW5TqWdsTkgCQhDArC4JgSg0Dmk2Cg6nZ4+Hi/HbiBrv/vLdra1tAINLmxs3riyuAkgIGQRsgiGoBpnbFus5rJACxO3W23/84l//9XdGvHf33v3RQyMOrqzuvHs5LAu5sbWyEQQtlrmpHZLCHYCVEaP4FELktDdJUHWqq4E/QyXnVxSO4e2gsNK11lmWHR0dPXjwwJz6/e9/f+vWLSPmeX7lim1uANylOjo6unPnjvmKwdra2vb2tiGyKgqwpBhOIfkYARarbPpVdXcLXOgUfX9wqsmBUcQFCq+JK27+MpCIuCu7HDxZvVXqR14SS3rGq4DnL57TIssTnwtzSfGjXvPn/i7w3TaKx6sM3vaV16AXWfHPB12d8pweVutxxTGNZ02U51z3ItDgfJkvkd2isPwIK7rWlblfO6efAV0tl3NZPe8L89W1iuai1ov/jai0fdujNdIMc0sYmk9n6Zl9p5omk2RuPS6VpZIQlLZgEMqwGUftJgBqNRBb1lkVhZq/aqhCCWSAsb6L30YUGmmaJ/PFa9Msyybj2dnIlmo0PBuNFi4xgNlsxt8Dd7tdrleFEI1Go9lsEqjd7XZ7Cw8BQLfX6/as0xsIhBcW2TEUa9BQVfLX+UxPJnaRcTzOzkb2RfBkkpyN7DarMJQACSGEEEAYBPZdbhxn7ZKNGUCzKdpta8/GsWg2rZcrBIKg0nMcOD1lScoXxMtk9DLXLsGLZltxPzTAc9DnTZf1KfU8UE1Hkhn62vwqRQdJkvAFndlsxleuta68FSjfH7jlXKC42YX3u+Cqc1Gvi6WoJteLv+IUoA2L9OJceVI7M1W9epbBfdaqY8d0YgleRgLIuqcapLTOS1NZQQdhGDdjAFEcB0zv1UF8LtK1ataVA2mSzhi9fJIkOdvFo0nLUMrS6ZWBlPwNrnY3TCyF+/Qcz7j0tYbzcihN0/nc7tCh6usuZ/tk/UXUcgv8RfHyOXzfWDJ/enh4eHh4eHh4eHh4eHj8tOGdXg8PDw8PDw8PDw8PD4/XFt/L9ublL7idXSdZ9QPcjx49+uabb4x4enr65MkTk6Ddbm9sbJio6yiK0jQt9qMnSZKmdmtWs9nsdrtGLIKBza2d2GDUSoXqUyilnATLr3XwzAQXgZfhmZk4Cerp69sYtNZEVL+QH3EilosHdxKYnItrzVkisx1uASkl33oRBIGTuVOYImfnoMdrD4e05CVRV0hLOhQRLe6+JNG3Ai8GFfcxYvHbHKgV+HuC1pqrhRykeM0TVcZetYxwnqhg2SmO6MojuPWoNfLcXKzTXA8nOllsuFJ5Pjo9TWblDjqtcecOPbFEHdl8znV7INuNYN2Iqxsb7Z2dwMwRq33RbKII8Q0CHkuaa5Wkdtf0dDodjUZmt+LTg/3ZbGbmlPF4/Pjhw9HpgrKlEUQYpr3mohhKqTRNTaAUgN3O7gatGTGvMiNsrG/euP6G0YSDwWDn0k6z2SSiXrfbbNq9iGEYOGGfbLZElun53Ab4zKbJ4ePTZM52MDOoHA8f0umxbY2nT4c83CsMgo0NW5NKzXd2bMxzGIp2JxSChBBXr3bX120hNzbyDtve3Gg0TJAYgCiKODVDXZk7BoPTJ/n0gfMu/1mhrjSWVAiRVTL8dwHNuDzqmdgLQULYzb0AlFZpZm2tMIoGA8sP1+l01tZsz79y9crK6kq3u9ii32w2AagKcweb9IlICMEZUirbYX8gFJuGnRubHkmAJlYfvOrOLazpzOTuZwbAKzaQ0hi3AKSUTmRflqZZqZFIByKy7RKG4frGOsqzURT1V1ebvR6AIApzZhs7NQxUCwHAUez2JwB0Ou31dasliIiX+cqVvfX6HhffAAAgAElEQVT1vtFsvV5LChsArhllobBcBD8XOKOsPh4dTegkkFJqrcMwXF9fN0xUAMbjMZ96pJTcqM6yjG9+3tzcvHbtmtHP/X6/0+k0GgtlLqV09O0zS8XFYviyk68ivnunt9CkyyctXk2j0Wg0GhnxX/7lX/7xH//RiEdHR3fv3jVO76VLl/7qr/7KWDztdvuNN97o9XoADg4ODg4scUi3211hpJeDwWB3d9cMxTiO19bWeM9woJTi6sZpZscPrKM+hTwP6t2LQz9H1PGSDle0CxfN7Ry/FLV+zB/WaT6qsb3VrzU6Mc9zxx5qNBpmvAEIw9B5xiLz4tmf+fgerw1ElUGqNik/A5UuWQuNckaJ062IqLj7i950efcs5nsDicr0sOjdTg4XKoPlqIaZLS1WrirRQTkJTmQlhQz52AeIVYquhuKSBuWgIrNa3VXEPMd8bqpDj6fJ1/fU2cL7ms1mn336qaWj1FoeHImhnSO2Njf39vaMGG2vN67vGDHo9aLtbTIxhI1ArjYplAAQBGCPM8/T08TG2d67d++TTz4x2uyTTz4/Oj4yc9N4NDp48MCEVEZhY3f9cq+1MOWFEJcuXdra2ipEAFffvrxz45IR4zjmdkmv299a3xYl044MZBzHi/6gG4Cl+osiwUxKZAmYAYOzs/zp03mWLUr18P7B//1/fXSwb8lUudpUCmdDMZ/ZXhcEsZQ29729y+9du2HEfl9tbyvTSRsNdHskJYio14taLWs8NNrtqF0hO+Qrm8UsYMTiCBfNTFTAsR+01kump58VqGZT8vato56Yi3meF2s6xXFzloiciTgUosK3xBaDAHS73TfffNOIg8GAD4S93b0333o7btoIcNI6KTuxIArCyIxWACIIKi7ZxU/3vcKh/y1UXfGbAAhyVNoChAoDYaH0rYqEJht0X6x7ck0ZN+JOx5Kih2HIV8qS+Xw6Hgdlehk34jiisonb7dYH738wv3GzEEUQdLe24m4XgFJpyoKuRRSFrZZt7qKOy1K4Wp3svwUuXdp5/33bQI6pfOnS6ptv7klZFjKQUSMwl2uNNF1kHqBC3vwzwZLR6iyMOl4GlYsLURS9//77b7/9tjn161//mhNGOEb1bDY7OzszGrXVaq2urhr9HARBq9Xi6trR1c5bScdZWCIuedIfF9+904vaHFZ4LOx8pTqKNXIjnpyc3Lt3z4gHBwd37twxlZ7n+c2bN03PyLJsPB4XRJ3D4fCYfcciyzLeGEEQzOdzMzgvYle+CPXEzhPVE/zwWN7J6o1SiEXrLLl2+VksvS8RCfbythgSFw0SLM3K4+eGmt/0LaFhp3CcN4vX8d3c+ll5VHo7PTv994GaWlCaLzfU1NqSMuriTwNFsiVJAShl1wCyTE+nqpy28+l0fHh4+uTJ4qxGcHIqxvaF5MbaGl84a/a63Q3LJIxOB4OBdW4DQkgojDAheMMrrbLcGhmT6eT45NjMEcPRME1TM/WkWZaOx6qceqKw0RStbLYQpZSbm5v8jcdgZWVnx7ri7Xa7WJwt0Gl111Y2uOozSFPKMlvIOucTXzpJUz2dKuP0DofJg4enT9gHRbj21hrTsUwTe9Ner1d+SgYApJTdrrW5V1exs2NXiBoN9PqQEkRoNsHMKlBIKJYVANTMteWoT51On/S4CM+cmrF0SnVsAFPnRbd0LuQqUWvN7eAgkHxBZzAYbG9vG3Ftba3VbhsrXOV5yiwxu6ZSgqh4z1rix+sI/PlrpbhoiqglvBgFORbPSFQ/tMkbBYBSKs/tGiXl/JtKi8HbKlnrScqo3Q7iGECW6GRqP/lGhR/uzD7mJ1W0vpMQQKPR4J65s8K1utrtdpvCvJ+naj0Culz8/RkOcadBHTh6zxGJLXh1OvYbYADa7TZ/8RvHcbGfosB0Oh0OLQl/FEXdbtdkVeiQ59ESF4nmN2pK49WEq3E8PDw8PDw8PDw8PDw8PF4beKfXw8PDw8PDw8PDw8PD47XF97K9+YXecQshiv3JBeI45iQlWZZNJhOzo2Nzc3NjY8OwJrTb7X6/X6SfTqcOkRXf1y6l5Nvli23ufEuAE8AtaoxKHLoaH4sXfOTvCs7WAiwthnNqSUoH9V0W7OQCJoFztoj3sHuZqiJqmXt4XIxqP+HdhiqbxLSuntXupXB3bLFrUYnJunAXG4DFZSZ1fWAsu2v12hqKPWa1HAtUvvBLtWzYbRa/KkWrfAuSsAhgLqBB/KPIQoPM93IB0hq68s1krVnWGqR57bHbZHMkI3Mkm87mJydmq3A+nkxPDrLRYgNzkswhVNy0W4UbciXo273B8dZGsL5qRDHoo8U26cZNhCHKcNmc1GyWKtIA5mmasm2ZB5Ozg4kNFX744OnR4akqn/dsNNVKi7IKgyBsD1ZMTTWixt7e7kpvQRshpNzZvbS1tVmex2AwaMW2VHHUDANGUSMC3i2VKom9NCZTncx5i2bs88CYTrLx0Ab1Dofpo0cTs7358PBYCBW3ynhmojAMzbymgU4nUMo2d7/f6nRsITe2w8GavXW3j0bLbm8OQ02BpiJvCcX6gSDNYyDPnSOeHy95+esNp3KWby+kpdspiW2Y5BcWv/mFqmYD8O3rrVZ7lfGn9Pv9TrtjdFccx26ZeeZaVxkIaqCafvsBQJUv5moA1W/F5xBc8xnQ4p/FtYTKVm0NkKq8aHKszDDTzcxaR12IFaY0WkA+G2dlxRMpnbcgyvQ6p0CIxsKkJyFJEoQGoARlbAcypMjI3phAgn2JV2tkqbY2GiGQJnAYAMJQtlrctBZS2syjSPJpS2uttZ1CtIbpdFSZaOugRXWej+Vnf5Lg47EQ2ckK6sN8yYVExMM5pZRErPmfBSdxXTS/DXQtoPWVwnfv9FKNa0HXNCY7iWazydPv7e394he/MGKaptPp1Fx+5cqVv/u7vzNObxRFKysrhXM7HA45IVaSJFMWxgBgOBxy8YmJGQOCIOh2uyYiS0q5vr7O4xYc5HnOHeZ6JIb5/aLgFeWgnm1e/a60lHJ5JJWo0iyb407OTnsVkSRGdDr9uY1rEmRZliSJ4Y5TSiVJwqsuyzLHB64/Jmol9HgdocE5PrhPAKq4YoDSSmnbbSSkIDsANXSuWI/VQOkVoFBQZLlki2MoZ1ACYMwwAi7mDiWAYF3AhZFUHUnsEaAJfHASFIHx8KJyrQa0EOfqghyUVUqlARjDUUAIfp/ac0pdsboCCrS09wny6nDONLG1QspzZCUPCUAkRBAY4480oBRYuxjQyRM8+hJlo5zt73/1ySfzkjc4SbPj03GSLJYshZT9Xn/nekkAS2Jt51p31fqTna2tNqMPle02en0jQkoEIcpSnZ2dffXgYDKdAbhz7+4TxgJ95+H9b+7fNeJkOh0Nh+bhz0ZDNVdhWZmDfv+9d981cbndTvuv/+IvdncWVFVCiI21Db5cG7c7jeaFjJpSBJRL0/7pHCcnyDJA4/Gj7PjIdoyTk6OTE8tVcXBw8OC+5bwYj6cHh6d5vqjzOA5W15uXB4uA5zAIV1dXTfyzEOivha22LcbqygqPNF5Z6a6t2luHIeLYVCQ08lzPi/6WB6RZN2oEDU6I9ZJw7Adnxvk5zwXOs+sqaShVGTTMQS5yFOYvzkvDp3WtNQ9uBxCEQcSCeN+4eXNQkjMDaHc6nMw5iiJuHWkgVyovJ31R9Cf3/i+Nl8uQoAmpmY8IIDsrQIPmIsr1OcazqDqQIAiSxn8mDTmHLBUqgYqsDdbOMpxaq/XPVPC0ZxXddaUmD27l8cLhbA0GrVYuy9FNQgaDWMtFuxCIQqlFDiANgrOYReGSCKRdpAo0tXM7Z+SZHp6qebnuRoROVzYatpQrK91ez4aMgiqOfRRJKlmsACiVz5OZLicFIUQYNAofWgjN58caaKl7QuAK6By8XA/4frBcjzkv3vhEjNq1XOQrmwCklPzaMAz5xCRqhAt1rcJFp1TOrVFLX4iFJV9/xlcBS3rVt8fySnEgpeSvZLvdLue758oXwJUrV65fv25UqpTSMI+1Wi0+f49Go6Mjy+eRJMl4POavHJMkMWIYhlprYxxIKVdWVpypl4PTCfxgKLoRF3X1hfNyj7eAM3LqB+tw7uJ0ZaeBUHWtC4fZ1JUjFkf45U5WeFbZPF4XOPNfIZqm1+RMYrriXFGVa1PrKl+z4tSbgCDSjmlY7WOVsizvfpUXAq7eq2dUOa/gOL0VkCbNzScDBcqr1Nb8VYkCJIi/n3ae07E03HmJql6rrlJO5wpJZutWCIDYWwANbT9EVGmC+QSnB8bpTfYfnnz9xaQkFJ3n+mCezUrPrdFo9Fc67dKuIhIrly8N9q4XIoBwdTVgb5YQRAgtrxVQecCMpidnyfBsCuDug4O7d++bU7e/+vKLL28Z0VFleTbXuX3TGzfi7e1L5lsdvV733V+8c+3q5UIkon63z+lD8lzm7J2qCw3i9ZpiNlnwmp4eqcOntmM8eTJ78sQu1z56/PSrr+4YcTKZHB8fG426vtnd2L7W7S3m0ygK1zZahvJEStraC/srdppYWxv0+3a9oNUMO21Wd1VkuZqnWbHYpIgq7/iFy7r/MnC7ZHXG+ZmjPvnWJ80Cz6w0Yi9snWz5vKy1zqu8smEYhoHdnTfo9yMmxnHcvviFgSm0kaqnz8MznuP7gCbkbBEWqChzyqHT80olNCRg1C8BWjBRIcit07tIwfJppLqb2LG/qsVOZFVKD0jHJ5QtVpfCiHQyMSY8BaFotBExfjmgKHMOkcKuSRUPxouvF38AoBWSuZ5NF7IQiGMdhjZ5HEcBe/+sUVmQpooLDK11rlJjQErISIQlt/Mzm/5i/Qn8KN3i5bFkVDqKrhiG7LyFk4njqtTF53ENLoJTqnr5+RDmQ7ue8hXB8l7l4eHh4eHh4eHh4eHh4fEThnd6PTw8PDw8PDw8PDw8PF5bfC/bm5dj+YaW4lvJRuSvywHEcWwCUQAQEd8D4Oxr55EkSikezF1ssjX5FDtyeT7OLtzloTI/zHv8egGcjQffH+p3qR/h4A1UPePhcRHI7Hdayh71XCDO4EJEbAuWG0f17bFMj/1YeNEHc7QxFVvBDeq6mo9oZ3Rr6CzXKgdQhDHYU5MJZlOzUzpNEjDlICU1Gg1DaxJFURTHxRcmi2QiDIlt0NJa54yzMM9UOrdbBpXSuWF2Ak5OhsPRaHQ2BjCfz3mpgiDgXzukKhvFbHqWzs/4BnSubwWRIGHSExGoUpl5rlK2j7GI7DCizrVijDWTCUYjnaZaa4wn2WxmU6ap3RwIQIpKNBCglbJxOv1+u91utttlTG8YNptRHC+2ngqBKAyCgIUWS2G/qFlrTxcEKp6zWhWLc98WlaHq8YJwDKRn4nkS62oQr9Z6PB47rJ/8k9QAKkxHtQatdJWi61xsIbjX4pn98nuB1pqHjVS4A6vgJ9xE5xbcTWShlOLbyHU1oo2IhHB0DttMvBiaFuwRqi1gfwKA1lAKhmwqy/R8nkyni2IIQXEzlExpCCGD4AXeli3URvH7x2hKj+8QTp+8CM+T5sfC9+70FkrZKDKttVKKz+J8GAO4ceMGj7p2NGCr1VpbWzNsz0qp6XRa5OZYMM4XtPM8n8/nJrf5fH5ycmL0i9Y6y7LxeFyIQoijoyPOBd3r9Xjm3PHGyzWw84AcfG7gB4sfWmsnxJz/PhdObvXMCzjHnbugmuDc8psExbVc5enqd+2dxYWLYhg8XncQgQTbeOJO4FUQVTiHUes5lR6r3Xn+go5fgsqb15M5vb2eYCm4FfWCl3KY8pUyEwsjaFnmuvIUeZrluTWzZKYCZnUhCMCo9SEEOAsoVeK3VJpOnzzOzkYAnj59+ujRI5vw5LF4fNvE9Ko8F0RGo4at9ht716KSgVlEUefq1QaL2o0H22HHiuPT0wmjIby7f/Sne4+NeHpy+vDhgyxb3Gs8nz86Pp2nGWqcOrt7ux/8+YdGXFlZ2d7eNsrqDx9/9J/+h//ekEgJIZrNpilzu93udrs9xt9DRElqHYP9fXV0ZPvk4eHB48e2kKPT2f6TkSGgms+z4+NplikAedLOMxuiHIYhL/NgMLi089dG7Pflzk5ozjfb4ealdiNeWKhCiDiOzeVEiNsiZJw0UaPBP50QyEoXdSBIRCyWj3cy0sSNdcCdRJbMIIV40WSEWmIPA611WqyUAMAieI9XF6/2wvTi83WR3ogG0+n0yy+/NMSfSZLcunVrf3+/EIno7//+799//32TXgrJrSNoPZ/N7Fkpg9CGfAshGnFs2IGJSFZ0tc7SNGd9KaiO2R8Gucpn+SzXpeNHIggCU5l8hCggZwcCqqhft+NqINOwdqWb4vTw+N49S1M3HA75s8dxo9vpRvFiDDbabRHHMKsPMgDn4dd6Np+lWQogDeOgZHUuwCdLnWE4giirfDic/Nf/+vHjx4vmllLsXV5fWbW29I0bl3Z3Lb2WA11dNSUSUaNh6oxqNLc/N/ABuFyzPX9dcRsbz8q20APuUQYnNwdaa8fmdxIbcUkmPy5+CG3iVFOWZdzPCcOQa9719fXNTUvUuRxpmqZpWqxBdrtdvgTeaDS4Is7zPMsyU4zCVTaLl1mWDYdDQzIshDAOcIE4jnluQghnOnH6wbdDPZMl/YaIlpytg2rrr0vw/ENoORynF7W6clZAnr+EHq8TCBXP7Zlw+6R255LKbKHxInm/YOJXAHWndykqfo3K84y9kaQsB/deiCpOLxHOs5ILaJUnp6fJ8RGAg2+++fqLL8wpMdqXB98Yiqxms7m2thaUOXc6natXr3ZXS/7CMMTly2AESwjaENYPTA8OzkoTHMC9L+/89vefGvHJkyefffaZ0e2J0sM0y7QGcOXKla2tLZPyjbfe/OCDD4x46dKlt956y3QtKfC//M//yZwVQgRBYF5wRY1G3IibsaWZmSfzjC0fjEbp/r4V7907unXrjhEP9s++/nI/L1/2JkkyHA4Lv7EdbzYi60uvra2trtrvMw1WutevXzbi3l7zww8HcenlyhBx23yt6TxILA1pyvXF5GpEFLBvk1SQk2NIOTOIMzzN74uOeDwPdO0VgjOBOq3gLDFfVO1Jkjx58sR4ubPZ7KOPPjLOGBG99dZb77zzjknfjCufh0zTlDu9AMxIR9GLLnZidWGqsfcNUsrKQtsPAq11mme5KvnkL1gdQFFgJgpop1orVawLL/lCI2cynh4fW6r26XTK7xsEYRw3opK9OWw0KAhs5QjJdb/WOk3TeTIHoCkQbHdIUQqDXCGfAeV63XCY3Llz75tvFsoqCGSuppOpXXPc3GSa+TxU+uBCaSwb/j8fvKh9+5x1RUROyiU3KizwixI8zx2XKPPnufxHx7IJ0MPDw8PDw8PDw8PDw8PjJw3v9Hp4eHh4eHh4eHh4eHi8tvBOr4eHh4eHh4eHh4eHh8dri+89WIJq0dhRFPEoFIcnydkUnuc5pw0sAkJ4mlarFccxgCAInHiVJdvNG43GxsaGKUaapmEYTqdTkyBN05OTEyN2Op1er8JZ8pwh5nU4m+mXBOEsh9Y6z/Ml8TxO4PGSMteL9EK79utHDIqsTCGLbHl6J1qmXkJzbb1BPV4jkIAwwaYaUCrnnVAIEqz1dTVUSuWKU+UKKSFZgJMGX93TWutMGSYVEAkpiXHYVuAcNhzQAEhDw94FcFJrUhq2VE70HQlJPNCqBucZDQQovOAUAAIE1IWnAUEZhNWTMsopYNo4y5BbfQuRQzDxbIz9pygjV2ez2cH+vqFCUEkyffggG40ATE6OW8Mjc12vt7Z58781FK+Nbq+7uyvL+NgwjhrrA5QELUmWff3VvaPRnwpRa/3ZowcPjm1uZ0dHY6acZ1qMlZ3I5Ebzl1t/btqiGXc21q9GYQzg0qX11TUbkLa1vrG9YUN82+12Twam6jpivUm/jsXhQp6vPLl7aXY6KKRG3JxNJoPVRdyj1vrk5JgzQZwcPBoe28BjaK1Yfw6C4L13r5tCBkHQbDYL+oPNjV6/b/kjWu243bLxzHEr7jCix24naA+EoVYlAUjbSTWglFXmBIByKiOrUcwRFUK4lCo0Ow60CWDMdZazfAK0pLDhzagq+RdV3XzgozZwijnFiM5nGn5WKOZ0U7fF7Gmbu1bnRXp+pDCZzs7OHj58aAyt/f39f/7nf37w4IFJprJ80FsMHCI0wpAM2y9QaFgmabBisM5n5QqvgK6IQRhIaQspgoAr3e8Q1UJXQCJoBl1dhr4SSJIkWw6KSRbaSmmdsYEdgCL2rCXlc1kHuRZIufpFEIC1SNqJJn1LGbV/tH97vKATA7AWReG1N+P24uMmshFRp48yzF6BslyoMmBYA2HUDMIYACggNqw1KvPYweHw4//y1enxpBDPzs6+vH1vf3+h98Io2Lu8xVuERIV/g0iBqvH8vGZJARk/ZGqLKCCcHym9wPfU8D8enCHJ1VoBJwEXHb3H4ShYJ2U9z7qZ/fxQVYJxrn8AENFF0e+vDn6I2cKpYqrRWjitwlE4vSZ9QU5o0hNRHMeF6JA0OC5fAXNhGIbNZtOISZKkaWrmTqXUycnJZLLQAqh96+Jbt6vTa+v92OlA7Mw5KNi5jOhkJaV0/Ml6hRjwa1WV49FpIF2j0Te/zwV/RqeEqJXKyY1f+8wbefykQSCYuVRrraBKu4pQ9MIy6SId65NKc8JP0hpCFLZXcQDQNr3SKs11SZwLIoro/Nm33uN4/9XF3F/t0pVeWnV6dc6JjgixEMF59zgfJh3h3LIuQNACii606DQoBdliSFHNLagSWbHyA0ByiP0vYTiihsOnt26dnZ0Vok7T9PAwn04B5HneYPmsbO9ee+9vRLDgswlWVpo3bghLfpODJuZe6dnZ3d9+fOfrrwtRKfW///7/+eibz8vESJKEr4RuXNq7fP0tI66trd24ccOQEq8Ptj9866977RUAGxudft/6ZjJHUH0+jqboN8TbDVoYnTppHT1Znw4Xl5MMH+7PRLTwvZVSjx8/5uuk6dmn2eRLI25sbOzs7Bhxc2v16tUd8/WgTqezs7PTaDSIcOVqa2PTroaEYYXHJ1dgnzoC1ZjFNGt7raG0NuMI0EQZsdYnCkD8+myp06uArOjwSieG2xaApFAQ4++twplBngfOfMQnX8cHBvCzdXoBCCFMXTnzuzNTo9YQZnodj8d37twxSzaPHz/+7W9/e/fu3UKMwuiNGzfW1xY8c0QUBSHTrq4KRLX5gOryXfXLXgA07CwPQFbfatTy/m6gl+ZMQjbIfjizDjNmlEbJEw8AAnB1On9YpYGK+kVAsOtsyJrBrGPveyzp/sxaoW8HQXBpL+ouvGIiIiHMjKOVTpM8N5MmURTFgRQAKINwKKNZEZ+ejj//061HjxarivP5/MH9J6PRqBAbcZSmmeBOrzuUNVGV/a6SQAG5qWxd6CRoAAIXTLsLVEv5mqKyDl4brVxENTGH43kuh6MEXhR1bczVjriY8u3VwYVekIeHh4eHh4eHh4eHh4fHTx3e6fXw8PDw8PDw8PDw8PB4beGdXg8PDw8PDw8PDw8PD4/XFj9EMIwTI4rqbnXn7OHh4ZMnT4x4dHR0//59s4k8CIJWq2V2jYdh2O/3iw+jb2xsrK+vmwuL6F8jFkfMb+eU1jrLsrT8JHoRDGOiwgAEQeBsVb9oe30B53kNLjpe4IW22hNR/Rk5qBqwXn/kiwrDw4RQu3DJHc8FD8Gq9wRUI5GcqKTiXkVz8OMerx20YnQgSqssy8yoJ6JABBAXxooopczgBZAkiWIB+UQiEBGVhD1aqTzNVBnTSySCNBIlHQiAMApkUPZD3u9qcWAkoMueSQCckQLijB+SJEkraiGVruZfw7knzz1YhS2lEy8HaHLoQarjMZ9M1MgGpg5Ho8PDkskJyA72Z1/e0mU8bZZl08nEKmchNi9fbgYBABVFyobsguTq/uGBWWNNnjwZff65CQyapdOHJw+n6YJHMEvTp48fn5VBZSD0+r1f//rXZXK02+1220aQrqxvb+1dM2Kn3dlY2zDqut3org9WG2ETwOnp+PDQEmIN96fD/Qp5oSHlAvDxHx6dnoxms1khSimTJLFTTyS73W6zuwh0BHS3GyfJIjGAQXOt33zXiCsr7Y0NS4XY6TbXNwaGHiaKom63U4T49vqSx6g6PAxElV7GYvoW4M1JBCmJh+NBsC4IVFmsoKF5pC6qExZBC7HgSBMkQtj5UZKskNu8BOoTRDHTGVEIwSffJUQVrz2EEEEQmBorZkmncvjU6ZgEBkUknjkVx/Hu7q6p81ar9d/8zX+4fu2aSX/j5s24ZUNPuaUEQEgZsbHvmBNaax4TiGohX5WJXqNaRkdN6lzlWiuUVWdOkAaVVFIAsjQdn54a4hWhdSPNJOMAC1otw+cHQCodMdGpurPx2f3795ql6ms2m+vr66byCSCy9cd+QiutkkrsKAlhxquAiOO4VTZoq9Xq9/vmvlEU/PKXb1y7sblIDayuWj0GQGmleWVRpRG1zrVODVEZgUiQgCh+m2QeBZb3fz54HT3piNUmsFSyhbgkcaEilhSDllJVFaO7uJx4d3yV8L07vUWNL5ml8ioF8aNHjz766CMj3rlz57e//a2xaBuNRq/XM5XebDYvX77c6XQAfPjhh/2+ZeZEzctd3lRZlnFyFCEE1z6O06uqwdxCCOehlvdIDqdbvFAveRkCj6JdioI959T47cCHXNETeG24c0Z1nBQpX6hOPH6K0BqKub2FE8ud3kYglvA35SrnTm+aptPp1HSzQASNsGXs+2Kwm7NEIgy0FMwm6JAs+n99EGhYr2Kh2NlZF4vZfQEByfz2HDLnpEM1ELsVAHpeG0EDsDzYJcxZSVVeGa3BxqMaj5ODAyMe3L//2Wefmcunhwent7/ISz0Zx/Ha2lqx5gggaDYvXbu2URDeDAZYXS2OA3j8zfGt3/VBPG4AACAASURBVD4wCw1HR0e3b982/uTR+PT//fqTg7OFsy2lXFtbM0YYCfHu3/31n/3Zm4UI4OrVq5cvXzZiZ7C2smE5ogIRxEFsakvnpGdSKwJw+/bTBw8em5TffH709afWpZ9MJqenp+Zh9w9nR8fD+XzRCaWU8/ncKCsRRL1eb3VzYQsSodHY4sb/O9dx05YRnQ4GC+JnABACsuIpMFDRtS4AgetmqooaIFXpoQXzo00BuST3XKuMOb1cdQOQRGHZCyVV1lsFXsrp5TNCgUrmtcmIp18+Al9vEBG3AbTWeW5J7+s1c5GVUhgw3Kza29vrliTh3W73H/7hH95///1CBIBazhxSSj6na62VtpO+UqqqfimKonoT/7jQGnnO9WKly2mt0yzN8wxAoxFGESea00z7Ip3PT/b3Z+UKrAT1SDTK2iMiynMZW252qRU3O6WUfACejUZ37txpNBdcequrq/1+3644UGE+lRJvolypUo8BICGktItnUstm3Gy3rY29t7dXGNUAwlC89/7Gzq7llHYaX2uVKc6NV7Eelc7zPDM82IJERKa5l/WinyGIt18N/KyuvgfSWjsq0TlbJwLkA5CnJ6IwDPnlDpyhWuTmHCl+yKXv5H5EvFq6xsPDw8PDw8PDw8PDw8PjO4R3ej08PDw8PDw8PDw8PDxeW3in18PDw8PDw8PDw8PDw+O1xbcPCv3WcHacOzu/wzA0QWKFGASB2SaulBoOhyb92dnZfD4vohqOjo7+9Kc/mQu73e4qCyrrdDobG5bdpAgaNNnOZrP79++fnZ0VohCi1+s1y9gJFNQ41VhwvrX9+Xeu11PWj3DwvfjFxn2+F9+JxeXb+lELrnCgtU7TVJeUXUtSOrv2dTXQSwgRVL8mz0FEQRCYBs3zPAxDJ4jX/F4uXnQLj9cABAgSJsJVCNJhpMo4WyJAy5wx7KRJmmY2iPdw//DpQxureXR8dP/+fVWOHaWgMhtnRYLCwHb4RqPx3nvvb29tL04DQSwCJVGMIFRiFRc0PgUIy4OSNMQyBatF4IYyVsQq35S9G0ELllKbf4qzSiFLTTgaaQ2lyNxIayjFg9Xy09OckX6dPX40evzIioeH2LfkTHImG50tU7GNOI77a5a0JpB3purh4QjA6eOj4/ln5XU43J/e/WakSoqXPM+TZtMwXeW93hsbl66UWiUMg9299X7PxPTS7ls31na3ChFAu7MWqBUjTg9aZ0+sSsmSZDYZGmWYJ2p2NleZAvDgwaODA0tkNTqZjs/s00FTt23jbmfJUbs3kWUAc7dH65fybhna1urizXf09q5JjjAEZ43YWkXLxsEhbJRhbQAAEhoCTosvQBmIs+hUeolSKtdM/ZKQLNadIIgC3mXP05oXqnqBSFaKpDWxrkVkJV0NDadw+Vh4GTiav5izjOjnBQ5RpT5ykCQJtyiCIChCguM43tnZMSxu8/m80+lMSrXQjGNuSgEF62C1Y/BWqLUIt1tQI1sB61YAsjzjBoaUUlxMYfgycEvJkBOmEoxwCgCxgUiBEg0tAASakDHraDxV+4fIFpU8Hw6Pb98el4allGLWajUiFs0vA2Km17//7rf/3yefGPHu3btPy2sB3Lr/8D//l9+Fpdrc3d0Nm4N+f0ErJYOg024F4WLGIUATFY+gQZrR2QlJIrSN1OrFN9/c3dxeNHEYBmtrK83mItJYSmq3A15ZaabyjLW+1JxXgIiIEzZCK7I8AkQCJEoVtKQFfhagmonuWNrsDMB0nTOgHDh+gXOXQlxyOS8DaqO7XmbnrBH58VcKF9tk3xvqtcaVYKPR4N5mHMecG3A+nx8dHRk2vDzPJ5NJIc5ms+nUUnHu7OzcuHHDiJcvX/7Vr34Vl5wBSZKMRiOTz2w2e/jwoXF6wzB87733Ll26VIgAptOpSYwaVYODJf3J6UDLoaqUD1rrLLPzARE1Gg1eDIcS7JmubOHJE5GUcgknVp7nnOIrz3NeFWEYttvtix6qKKRpUKVUo9HgDfrMYPflZz1eDxBRgIp7GYrA+qkaearSuR1Wo9FsPB4b8ctb33zyhz8a8fbt2//2b/9qqK2m0/nx8YnptGEYrqysmIWYlcHgv/uP/7HVtWSkQRwEUQhAkiAhTQfUGsqWCYvyXtw9FQJ9sYKV0GFBr2TA9IYmKKq6HMZugBKoUuxyRyXPaTq39ppSxClZFDAHUps+/erBnHm5hw8fP7n/0Iiz+RzjsSlk0IxaqzeN/RQ3Gq21NcO8Msuzj06Pjw8PAXzxxRd//MQuQY6z4GjWUOUjrK2tvfXmm3GpFvrd1b98+68H/QX3ftwI3nl3Y3PT8jM3wI00HB3TybEVn9zL7nxuV0COj4Z37txJ00UVJbPp8f5+miQARqORMeUB9NeCwYbVRb1eb2NjwyicXCSD0ek0WXSz1VV19c10sLKoun5f//Xf4rqdYdyeIDPISitVbGhBgMwv0G1TwJJIKyjF/OVcZ6m2DxvoIETMlGQgqY2LKd+glxFZSTQlLK0OqJJWFz1UA4Cu0J9BvBSPlYvlOn/52Z8zllsXWmvHRmq324X90Ol03n77bZ7SsWEk81sA6CwzK18ARCDJMYdYMTSjzES5Sm4sk6JDmf6ttZ4naZpae6MRx1F0cX++GBdWBAC3a7vICaMAdpgt0i+uEFqv5aKlAwCkCYwYWR0ep5/8SZcUfZOjo0e///3p6YKiT4RR69Jm2FnMNVpjPBlzxvj/6V//7X/77e+MWFSdER//6fPPj2eirOp33nkn6m5ullx6nXbznTcuD1rlEqSG0gt/XBPl5nsEQBhQ0LBrX/3N9l923jYrkiSo0SBuD1ZJ65Ak+XRqVVsUI25yn0pIwS5WEMIhV5PlvcXSRnj94QzYPM/rb7mMyBMvOVWI5nchLjHvlVKc/a44Ult1qvgRXFziYryyuLAufizU289pQt7eWmvTUZIk4epjPp9zQtfiCyimSxWeG3ee+VkhBFfTAPjvVwfLS7X87MvAqZnlN6q3oIfH88Da0bXu4/S6QnEbMcuyJEnN8C80gxnsWuskSUyfTNLUGew/GGqP5eCiIl10nIE/jq46KLqSgVYKJakyAJ3lhmMZgM5VxVfTKJfqAQAkiAQxUQGZ0gDSXCX8I1IZkjww7wYzpRSR+doThJRBGIQlC3QUhFEjjOx+n0BDslKIasVpRYw9FHmGLNVZuniKNFFpkqdJDiBNcnMcgMpd3cWVFRGItHkLRaRJ2FcaQkJKsA9duRCKW/6VFngO8NTVBnuG+PJ4Vq/0+Mniosn62XP08l625NR54Pei866uH/mBURTgomIUeuz8+tIaeW6+d6TzXOe5Kl/8QmSKvZnQWudZlrNXCFmWpUx0kOcqy7LF21sgy3KltCpFraqNxGrWeRCNSulJEH/1IASk5O9u3Ud15hM3dwfL+5XHj41nDPwaXjT9K4ifnpvu4eHh4eHh4eHh4eHh4fGc8E6vh4eHh4eHh4eHh4eHx2uLi7dnvQT4FhqtNdWCeJeg1WptbVnOEq11mqZma2KapuPx2GxlzLJsNBoV+xhPT0+Hw6G50Il3TZLk8PDQhJ/N5/PT01O+vTnLMpM+CIKVlRUe09vpdJxHqO+Lc0Se4NttCdDVYBilFI/pzfP8wYMHPLIxiiIeLjsYDAYDy8sSBAE/S0TFZv1iaxMvbZIkfGf46enp4eGhEdM0nZUhKwCazeba2prJOQiCTqdjxDRN82rAgLPDqqh5Li6vWI/XExpKg++acgeUMJtoAaDRiDSj8+kP+lxpnJycrK2tmUD0+XweBEFW7jFrNpu7u7vt9iJktNvt9nq9apgKCUkASLidryKTu+/LgeZFrMGSS9lDPDuN87f+udCoDKiCuQomJqcqqkyNnxwlpzau9fTOncmTJ1Y8OjbUBqjRBMzn89OjI1VuL5ZSnp6eGrWZQO2L9IwUgDAMd3ctyxM1V0V31+yL7na7ly5dMtq42eg2m03T4nmunzw5YcXQs5NZMmFRu8fp8bHdzT49CUf7NhK1UImmVM1ms7G9rZUCIMScyIYLDjaCwaadI9rtdr/fN8UQ3xx9/LUymjDPcyGEyVaIZ5IRVLYIFu1gUbtUlZ2FyKEwY/v8AUHCDakisKBuDa34Wna9kPV+x+GkdhJzkWdcVerAefd9frh5PQsvc6+fHJzJlId1FHO6qQ1dJQFRSj169Gh/f9+kX1lZ6ff7AOI4XllZ4YF/7izssuoRr3MiququKqjSQI6xURzikpAi0LYkz286focggKpvhHgRBTS0NnuYOZLJ5PjwMC8Dp4fDYUEXWohSyv7Gemd9rRA10B2NUmZNvfvuuwcsZEIKKRgBlYw7YW/dEF9du3at3++biazZaphwXwBaI01VnmsAZ6ejk/1jc6rTaW5urkqTsyYSlruCyH04UW3eICAeZR0EWlTp7jjHhC5hjvyc4VQF1cYR7+1LEtdPmd911Oufp9dVXsBnYklWPxV8906vrrpqRVPxtlxeTRsbG4UiLvDee+/97d/+rcmtyNycTZLk6OioCOXd39/nCv3u3buczHkymXzxxRemGLPZ7Pj42Bg0YRiurq4avqU4jq9fv/7hhx8WIoAoirgL7RSDd8dCfNGedC601tzoVEpx9sXxePxP//RPn31mKVIvXbq0trbQpwDeeuutd955x4itVotXrBCi0WgU5SQi/jjD4ZAvH9y+ffsTxig4nU6HQ0uOurq6evPmTcMQ1ul0bt682estGAWTJHHmXVUNv0zTlEdiB0HgzOKmyV6+Pj1eWWiNPLOqmQhSclZLyEDwqE7ZbbU7jHFHX4nLiFAAUspHjx4ZpzdN09HIrpT1+/0PPvjAjJQoinZ2dszoJqIgDMJiUhcuPQ+x6V/DdUkdMdfIK45OBcTzOg9EGq4Pch4WXm9ZdSoXWUYmLlcpZJnxt/Lp7NEf/nD41b3FWeDh/ftHTG2S0pw5OIoiTis4nJx99fA4UYsUaZpyOkBqhLS3Sb0WgNXV1b/8y780F+5cf+/tX/+9DBZrYYUSMM2dJTg7gSGvybLsD3+4M5kslvO00rf/9PjxPWu0nZ6eDYd2sW+tc+nS4KYRwzBstVrGgm83mzubG3GjAeDKFbm1ZXtVdx29dVvDQgjJeGL/6V9G/+t/zsyqYrfbFUIYRz0Mw+o6jAspwNYYoVTVjhSVprWTJkEIVTEiQYKb36LSKQgVExNaKa2gyzsRJCrOuXbiux0+KrLx2vWzujxCBMHCmwFopXMWCs71tjnCRQfOWW4/FOCik7iYv/iR1xi2nwAA8jyfz+dGlFI2m02jypRSk8nEqMEsy373u9/xqXxnZ6dYK9za2vrggw86Hcs2rjXTxua/EoIInLlKiCWqjEBSSt6CPPPFheXlRBSFUVgqiuKI+f2DgYCgps8NBEBZhsJ6LCJ4y8cZ7e/fvnVrNhoVYvGGwDxs0GhcffudrTdLZaV1PhwqRq3XfOOtPztdXAug0WgYywrANMcwsxwLg8Hg6tWrRj9HoeRvNbTW02k6m+UAvvny7h8/svxYe3t7f/7nHzYai5zDQLRbjaBkXC5mDKOsiBAJMNcbjYYMQ9v6JBSV31koUG1rpXJlVvSkkNB4nmnt9YOu2vMAnO+eFK+gjPj84BWO2pAp7mtER2FSTVfX4eT/nPh2z/ID4Lt3eut4oWnJ0Og/D5IkCcPQeE28bY6OjvhNlVKz2cwcmc1mk8nEOL3G/SvEwiFstSyha/0Rfph+wKcHrXXhNBZinufD4fDg4MAkbjabxiYDMJvN+EtUPthQPlFRHqdUStn3GwAmkwn3gSeTyenpqSmVlPLs7MwMKiml4+VWNaB9HHOEF6xu7nj8HKBR+G7OMaaaF38LSCn4Qrzjm8VxHMexUeVCyCyzSy3F6o/ZBBGGYRRFfAhQ9dXERShSLO2sy7qyfvbkT8/IvkTF7QGgL/RstFLJdGpsMgCT0Yi/2g1IhmQNGsdaLYzsefnxqPl8PhqNjFUt4qgx68o4ACCEMK8gAAwGg+3tbeP0pmk6nU7NwJ/P8unZPEsXDaQ1ptNkOFzYglrpg4PR48enhQhgOByO2COItD1oWE5aVNV1EAStVqsZxwBWV8PNTTu5dNfQXTBGn4N2OwKsdlJK8WyJ3AURF886z6EXjaSLkcCvdLIh2DIUIjtZ9ANtV0D0Mwrh9pSliYtSAud264pif57h8/xw9cJ3saD8E4UzgRai6aKi9iUSxZaY8zwv5m5zttvtFo7udDqtV7L9jVo3Iv79nmeBAF3pEpV7aY1qa/JRhkWX/hFAF2tn0qgMBuZRqCybzWdmK5zj5BBR1IybZnFBa5Xnls8PWIHYbFQmMj6vnaW5nBZEgQDQ7XajKDLWchA4H7AsFto0gPk84QpzOp1mmQr+f/berEuS27r3/W8ghpwqs6YeqrqLTbYoDqIoiZKOvOzra5/rB7/4c/oTnDd73Qd7XR/r6tBHV5RIimw22fNQ85hTBID7gAjEBrIyq9mcxCJ+q7tWIhCBQCCADWwE9kbiFFEiNC/BvtvgFXGIfF/dRPwNVkKsCXpvMOyqfmDMtl8WCXwFyTmbFCeIDRpjoPQuTirAfA+l8Yuql3+xOBEp2NozAAnbHtbFutdjjOHDYvshl42ShfFnR/i1+JLVgvMSVcTdy+qifKU3ES3Y/kdrzbcaKssyuDvNLjQCMLPkONCWhRBpmroL7bA40HJdLP9tce/LBVlkGMRLlVjke8k5NfFFIQIX3EIKKaWTBtLuDeM6dUFCCpm4WCmEIO4ReF51Iz+Tblvhl8ImNu9WAGBMeD97tqn+Vxi2mBmAUqYsjfMXqo2eTk39bbacTMqiLJlkU0rzz9HkryMvDRTLoyYBkVG9I45ISKbtpO5ERJbJpJUkLQBCZEAjmpQWk4mSZZV0UarJpBkOTieqmKqiVnqtSYTLlDEQQiT1+wKQZWmr1czutVpp3mpi85bMcuHqQ5pRksKq20KCBCu6RaUPwAAa9XYqRH4QhtWpcwiiZmSYv83tzOlzfttgEDv/5PCmCJoZ+crLTDZ8KPis/C0R9FOxOwiYVyDGGL6QqixLa23ET7DXzkvhRfkqV3/FW38zEGAbuEddB8Mo1opICJmk0o3KhJRau3U3SZaRkN4j+0smbL/FgsJb3qyQSOOUXikEX4pEgKdiGlMWxXRSACiKki/EUNpo0wggTxKhfpteui8PwYqNKpULJEzkW+crtv2vePl3wtev9NLM3sfB57tANwM8HXI2KojlJ0gpO52O/byZZdmVK1dc1NbWFl+fHFw4nU6Pj4+daleWpVsmDSBJksPDQ746enNzkydujOFqYTBTEnQkNv/uKYKZv+B5edBOzbobHR4e/u53v9ve3nZn9vv9v/u7v3Pnc70dwMOHDz/99FMXfOedd/7+7//epS+EELVBrzvH8vDhwz/9qdn19OjoiPeUV69efe+999yNxuPx4eGhmz8ej8dXr151z1iW5Xg8dt+NtdZCCD4ZwacqAXBdBXU52745YZv7RS4ZBCPQtHQCkfF0SqWCJQNNFIC81bqy0XyzuznceuMnb7tad3R08PkXd8eT6mNgb6Xzo7dee+WVV2xQCNFb6mS1EkVA1pJKFlWAtw4Dvs7UAIZkOGJgCKI02F2HIWCMHXtU+C1Rayon1MgKaiyrVIGymczCZCLPzlzhTA4ODz/7ohxWDzuZTHaeb49G1VfTsigffPHscK9ZuLG9vX3IPv6ofKXMV1xwMMiutpbdI5a9VzrXr7frbRiTJPlRp9M02ETScpdadsDXVmi+9H7ymfmvP/3ZPWup1JQty9RaqfHQsH2HiIiX9ebGxq0b1XaUAHq9Xq/bLMVcW+3euNYYbqRZ0unkrjCTRHS7UkoFoN/X7Q4bROZqms/fICQ9SMRuJqqlNCklCbadqEowzvWoVc8mAAgqgoAmakS98Fc7Ewk3dwCACIkQtloTSZpvDC4AYtv2kh1VcphNMIGIDBsIg6jkmz/D8CE3CJLYd35bhLz7dXMGQb0m4S1wPbdbeXFmL18wQvh+YfwljlR71vDPauCfagGQvxYxTdPgWj7TfXR09C//8i937txxUffu3XPjBwBXr161C156vR4flQUjlvPwDdbny0DYKhrEBy/XbQt2HhdMs7DIoF4QvHSNMdzHgn3EJpoEiaZSJ0Yt6UmzP7YBtHYtgYAUEmkGAEJxk4Dexo3X/+4flLPYIgEp3bfctN0a/Og1DBpPK9TpkpugBK7posNEipQyYcOhUmNSNO0xkbKV5S7XREQTTOslesPh5H/+228/++wegN2jk8fbjXlIkV99fZR2RTUM6xB1BZLafIgM0hYSVjbygl24CaYpAYJXroJEmkh3iIiIZDVpcGFDJu2l5WGvnZ+CwaLY74LZxr6g4X8pApE4GwwWz86K0NkjL85XufY74etXelHV7KogjL8oF4DVtVwwkK1WwwmO8CCPJaI8z+3Xzm63G9Qnrj4FFEXBF+WenZ19+OGHzl0TEQ2Hw8ePH7vz+/1+oPTOfv+cFyRmMWuMWdCXBA9uOzA3dj88PPzwww8///xzG+x0Ov/wD//wxhtvuPNPTk741vOPHz/++OOPXbDX65VlyTM2O/tg2dvb++yzz1yQv00A/X7/zTffdK3o2bNnz549c5ZvRHR6eupWWSuluB2yVXqDr9P8NQVCQSmllLJVYsHbjFwCCKbpGv0owA4Wm4YTNKI0S9vdxvZpdX1148ammy1Kcvno+YPCVAORVje7tnll69XazRKBpOGfNwlk4EYeLC9htshALFZ650eCtDcICxui0VT4llWi/iZQlJg0Si8NRzg4cupx+Xz76JM7k5NqxfJwOPz888+deUKpzbOT8njS3Hd/f5+vfBt3WqNuo/SuZYnWHdf8s3yjd/1XIq1W3HU6nc3NTbcAzxB0SkYSgKMj7O/bwwDw9PmDP/z+Ay4HCubfRVCZyzNB1fuSUq6urjrrEiJcv720cb2ZKbt58+bm5qYLrqzg6nUXgpSUZY0LMgOlaWSggXAArU1RmsaOI8DIoRSnkqrCkdQVOBaoqpkApabIPO3U77ZIgZlHh+8XCZDwSyTVIZPMHenZU8KkOBpUunYEwP8NUMl15pmkzOwh3t/O+7xNVM/IfB3M9kqzR76/BErv4oFvoPTOasi8W7TNyiU+HA4/+OCD3/3udzZojBmNRnzx13Q6ta0sz5tJIkswUDHwR2XkV4MLX46feHD6/Mpe0SzXDy4Nh1JBrBc2xjpLZGE+kyLAfUhIo9t62tjGGwPVGO4CBOrAlrz/aK3lletvtt0yFZEkSafT+JeShG4G5gWKOs3MIIC+1H2+FCXAECn2upUqJ1N3L2OoKOE6yfFpcefjz95//38DGJr02DRLY1Y3xydFYspqGEYKGhr1fQnVkzUYe3geM1++vd9CLNjNfBEGTS88iwHEwrqzIMPfGYsb+1dhgYQMBvAX8qVO/j7yTb2DSCQSiUQikUgkEolEvnOi0huJRCKRSCQSiUQikUtLVHojkUgkEolEIpFIJHJpebnV9ouw1iCevYRvkBksGZ81JuFGLJPJ5PT01KUWLE+XUnY6HWsjGkRxjw6oTXzdCVLKdrvtkhVCXLt2zW2JZvPAHwFA4E+CG6bSjGVOcC3PGP9tZmyD+YXj8fjk5MS517K7g7hsGGPW1tacPx4AZ2dnzlc+gIcPHzpTWwDWnse9CM124AiKbmtr66/+6q9csNVq8d2b7O4j7nknkwnfbawsy729Pb71rtba3dQWFL/X/v4+tx9eW1u7efOmC0oprXlwkMPIJYMIJBo7TACBSY4QgrslCUx5mAuSCutJoP5tbMWzQSsKksbQyJgZhxnOimyhGxWhwQRdaHAGA99Dix9NRNx1SnWI/fZcxRiDyQRaAzBHh3qv2ajs9OBg99EjXYuF4929Rx/9eVw3/Mlk8vz5c2fqrw2dlclUN9J4fX2d28fmm2+3b/7UBe32Ti5fx2Xr6Xhajivj2+Pj40ePHjXlDDGmXEECGI3McNhItkSmW1tbLp08p34/kfXOkK1cX1sv2nltCCeo12tnWfWCCFhZTnvdpqvqdHrtdlM47Y5XVDNmU8bU75FA3lvyvUkZGLefpI2UUjrnBbb7aF63gdH+3rvS98sa+QETDADAGneSJDx2sZmfEII7oTHG8L6V/JHVdDo9ODhwTkD29/ezLFtdXbVBIcTm5ubKSmOx/+tf//r1118HkKZpWTZbUttkvQ73O63Xrs0aY7h972ymeOsOYq289Q7xd3ROYg3FdLr76NG43tqNIDLqJZQDaPd6S3UJAxBJkgyWmj5BCEqSRiQJghShFziGNkbXG8IBECQWVA8SQmape4ppoU8OhpNpJcFOTk6U0rbyvHrj1Y033nUX3rp1/fr1zG0A3E7wwpuERiLfe76Ryq6Zu+ZzBOhCAj3QOgfmR3hSeZ632+3ANZlFKcU3m02ShHcPQgi+67cQYm1tzR3RWh8dHXGnUPag+x10RbPM9nmWQIRp3QzNbXBW4Xd67NnZWbDlwMrKyo0btT8eYDgc8h6x0+kM2b7n1osy1wTcewkU0Y2NDb5P/WAwcB3nLIeHh4HSe3h46IpOCNHr9ZxfKyIKasLh4eG9e/dcsCzLwaBxxNput9vt9gK5H7kskBCLtgASjZ+fizHG2J2z6qBX8YSotjRypys0YymOU5bmYO/RaEHByCnc38XfkJII3u5AAUJAMHciWmM6xXQKwOzv60ePXMzJ8+f3P/3Uee06Pjh8+Nnn47oBlmV5fHzsJKEhMZa9ovbbCWBjY+Pq1cYx8tW3f3HtJ3/jglzrA3B/Z/Tgk4PhpBJBp6enDx48cEJGGXlW9qY6Q+2Czl14+7Xbv/7Vr91Ew2CQ3rrVzfPq8Zd6eOM2+kvVyUTIMs+ZivDf/WRiS6Iiyz1Fl2aGw6Z+v4HSKyC4BzOuSQUCNwAAIABJREFU8aLuuVw9mZFCJtwsSngejCM/cPgYwAkfW6nc8QsRwlN7iqIIpvLBEp9Op0dHR649npycZFnmNiSXUv7iF7/gni9fffVVO8Vs/Xo2G24L0Wq1XD5nZvO+VbjG67dQA2+juQugWbnwwhTT6c7jx4c7OzZIED3Zz0ULwMrGRm95uXm/MpGdNvfn7EGA9GWZj9FacYfwEmL+YkwikikbharidDg+O61GgGdnZ0pV3xtu3rz5f7BtPpaX5dUrqZPrCdjMXyRy2ZnboiKRSCQSiUQikUgkEvm+E5XeSCQSiUQikUgkEolcWqLSG4lEIpFIJBKJRCKRS8siw9SXRggRGLXOs3G1cDvPJ0+efPHFFy747NmzTz75xFmsBfR6vbfeestagV67do0bpwkhuPHMbH4sNmi9OBwfH7vYyWTCb2qM4aY1i01zAwJD1uA3T2o2k0oplw1rpeyC9se8lAGcnZ09f/7cBY+OjsqydLewxkLOKIhf2263eVBKeVq7cABweHj49OlT97x7e3tKKefWq9PpXL16dWmpts+DZzBsH+fo6MjFPnr06OOPP3bB6XTa7/ddcHl5udfrWavCIJORy4WB5/QpNHwy1sB2Dto3yi3MZKKGpaoMWad6ONWTqaks1gozVShVs/F9aNDbBIyG4ff1vSBBSGieUQqknPEdWRkDZpMmTAk9aRI3xjMQnWocFJhWsaooTrZ3pmenAE4eHx190bTHvb3x/fuNQ6XRpL87+klRVheSoHw9bddCRguR9AcFc2dwKMRR2YigO481jZr2mCSSe+wbT8ujYqJR5TPri7d+cd21ykTK5e5yK2sBMATNWuvKytqNjY6Tde22XF+jpE44zzFYgssUEaT0zHSDV58SBOu4ZGKEbE4ggoZx9zbQwpCBACBIeK5uTGKPV2cqBdbPmKnUZaLK6k6qTMpSlmXVp5SlLHVSNB0oCQSu2JKFc8oirOIvyOKLiC46Qy7M1UKLQxBokeH9D5mg7w6GBK6rBcJuevbMBX26EMI5yADCPjFN09XVVdf59vv9n//85xsbGzYopXzzzTe51zruuYOPQ4QQ3JodM9n4NnHlY9AM2AAIIin88Y9hjdsAWkPzl+I/QtBStIYqXd0uT45HD75Qo8o6enR6dvTR3eO9PRskKdX1jbw/ANBSK8gaa2ElUaba1HLfQJdGNf0LkRQpkWdCy7NlhGwkF6AgCsXeCygRc9snpWJ5ud1pV1K138/ee+/n169vANh67dWtlUZitluiPSVZyzohNKVF2P9yKIX5Cma/8xOe+zAAFvb4AC6KXZR05IfM16/0zionXL2chbhLTOD+/fv/+q//6oKffPLJv//7vzsXC0FSa2trf/u3f3v9+nUAv/rVr9577z0X1el0uPo0C/fPPJ1Oj4+P9/f3Xexsnhf4nzDGcKdZQQkQc1kclIyNcsFKuNf31VqXZem03KIouB+LoiiMr4oH9z0+Pn748KEL7u3tcUdW1rPXuQ/V6XS4u+bT01M3HQDg7t27//mf/+lyJaVM09T1xN1ud2tryzm+0loPh0NXOEqp6XTKy/nu3bvuN4DJZMKdZpVl6TxFn5vVyCWBAOgF/a4xeoFPKQVdNkosJno4VidFWdW6UXk20eOJrhzCTfSkRMn1m6B7ZL6pjGG+NOEPDQlGkhS1BngO2tcQlAKfvNMjqOOm59YaRQEnc84MHhicVUE1mex9/sXRwQGAp/eL+580zmyOj0fb20br6iHKbGXUf0XLSoNstVo3Nm50u10b1InMNleng6Z1f/HFF8+ePXPBx58/ePzH910wSZI8b7xeXemLH28meVLda3Vl9Wc/+5nzPNfL01+9urZhE89SsNG5KjGtFXgAQiBNmawSoHSRLqYJmhVlk26FJvb2AZimHAEYocmmTvA0CoCgmdJbFmbcvE09SVSZqrIaRKoyLadJOa16zKJIpiadsryk5NUkMmJ+db6IxQO2xbEXRC/u8auCmgO5P5GAYMCglOKqLI/iaq0xJnD5Ntsp8xobxNrLXdD69XTnl2W5srLinEoS0crKihMFHPK9jUopA8ef0I2g+pZRSpW1JPcaLwkiKQNtnGey1CiZcCbfkRX5bucKhfHEiY3iye7h//OH6f6BDY5Go/27d91kPWXp5JfIpAbQU1eRN572lcQoLd18nzJqbMbKVO+IIFPRk0zpJb89JSQl8ypV+j1GKtGWc9ufyOTaes/JHK2xvLw2HhsA3bZY7rF2rYEpK6tEQ04hPRHKIEDAV9Q9zMvWjXlP0jC/bwXBn3GewSyMjfxwWdDDRSKRSCQSiUQikUgk8v0mKr2RSCQSiUQikUgkErm0RKU3EolEIpFIJBKJRCKXlsUWPi9JYA2LwBjDZ9b6xTously5cuXnP/+5M1wpimI0Grnz8zw/OTlx9qVPnz61PwAsLy9zv1Z5nvd6PWeSZ41hXD4nk8njx4+duyYhxNLSUrvdtkF7vvttgzzPWmv+gIGlbhBcgHUg4YLWroY7wLBWvjZoyy2wI+KmxXxjegC9Xi/LMpe+lNKVgBCC5/Ds7MxtcA9gZ2eHW/2dnJysr6+7x0/TtNvtust7vd5gMHCGQ0qp4XDo7JDte+SucTY3N3/2s5+54Ouvv761teWCy8vLSZIQ0YL6E7ks+JaYIZ7JXFAlCCTY/J0UUkrpqqiUtoJXJ8w0RqOZGS/QmAIRQQjpLJYIQT2cqZRB/pUyqjlilDLMAK88O54cPHIPVU6no9NTXZ+gTs3ki0KdVo9QluXus2dnp6cATg5zrRtPVEKIPM8bUSbTM6VLU0mJyWRyeHjo7Pp0Ik9TNZ02Nr0AuJTobMpbnbUm2Jb9fuJKZNCmrWWZ1iKq2+ttbV1x9v+tRLY6LaQJAGfkZiEB2TR6CCLi8QRt5hpwGUCTMeRF+29/QbWx1crUL9E3AzONHSMAEiJhoilJPa8Htgq5860fHW72OFMbIj8ggh6KVxX48io4U2vN7XKDC+GPPU5PTw8ODtyRYBiT5/n6+jo3ws+yjN+Xj6xgRWp9bZIk7vdsHr5DhCDXBnmuRFOiAABjguGQcH4OLBTY9PoPKATS1AlwI0VRlm7corUeDAauYClLl65fb21uABgMBn5SRkPrWsho0mRI1MKOIHxL4nOsTvkRSeCfpVShjs6mTtrZwbCrPHmaXl0etGtPCkTIc7JiOJO+0wMDCNetebeIRC4934bSyyX+LEopJ1wAGGO41L59+/bbb7/tLrceiZ1qd3p6+umnn1oHA7/97W+5qraxsXH79m0X7PV6V65ccdKTi3sAWuvAydMbb7zB3SQGT6SYU2UANKPlWlXNHVkAP42ruACyLEuSxKmIQoiSCeLpdMo7PABFUYzHlbceAO12+8aNGy64vr7e7Xa5Uu2KMc9zft+9vT0+ffDZZ59xB8ubm5tvvvmmS6fdbq+urrpMZlm2urrq3uBkMtnZ2XHvRSlFRPz9/uQnP/mnf/onF7x+/Tp/a8FAM3JpMab6NwdjDFdMBQk3kgAAELGuOxFNqwGQpqlMPO0F5Km5yijN/CpLVLqQIEqk5+83gPxhFYzngdkUpSmasYZSio9uz7a39//8J6OrIyenp8+ePnVNcnqidu+MJsdVrDFmOplUc0ZmIzev2uMApJTcCytUqko1LRspwWWCTuTJ6GDSb6bzrl+/zqXEzXf6N9+tHFMBWF3BjY2mAHLCEitoIhJSunGaBLpGNFMEDCGR1u6vMDPUM4Dmjqrq6lBBMEJp4SsGLA3BfDVb/FdmtKn8ZgeSJJAtMkkEE49Z3srSzFWkNE09HViKJCFfifDq79xKE7mkBF05iwkrHqcsSz5VHYwcgoHK7u7uBx984MQInwQHsLKy8otf/GJlZcUGiajb7fLUgmyY2g9W0CnbIzz4HSJEJY2JyHO9DpBpmpwxpiwKN2kIIIWQXJ8j8uaoDDyJIz1/8Uomo8l4dHZWR8pr1665KQORZytvvd15bROA7PWIGnVaw5RQindVQrAJWeFr3iHka6BCQLLwyXC6/fRY1y6pT09Pnzx54gaEy/3eb37xVmetUXq7XWGLhwpgYg8DAASQMgklorSK/ID4RpTeL0Ug1uEL3CRJuENCrXWe5y6YJInVVwGMRqOTkxN34dLS0lktswAIIUajEe+Kgs/LgQLJY78sX6XDCK4NeixeVkGh2SP8IFEzRYp6hOcSdCfP5jboSouimEwakamU4q4dkySxyrkLctXd/gjyzO+YpmmLbaCS5zlXVyKRl4EQfJUNq7jHTDsC3/tiwaUE8q8OmqSnuoVBrbQqCqf0qum0mEwapXeiJuPxZNwovW5WTpIO5uYF2yIukBKol1dYNBmlGofwmJESWZ51Oo1K3O2i12uGaRnQ8YdlfE8QYSAUmg+2fmGEYiYs9fkscNv9osxJwPiv1xeFRLDV6LxIW8W8h5qRx5EfLrO96gJ4a12M1no6nbrBie2p3eX8t4UWrjKbPZkH/3KwGTtHpM/IW/5E4UzYhfiPb6oVIva3kVI2Sm+SpGk1r0pSvrhoI1/evAj8fGOgtNHKLf9RRVFOp1WXcd7br7NGCzIVifywmCsQI5FIJBKJRCKRSCQS+b4Tld5IJBKJRCKRSCQSiVxavpHlzeFKsHDdiL8KxXcKJaXk612XlpauXLniluhMJpNOp+OW552dnaVpenx8DODg4ODw8NBd2Ol0+D7sQojj42OXEyEEN56RUna7XW6+tb6+fuXKFRsE4Jy1WIy/KbxNjcUvgj/74gVFUso8z13hdDqdwWDgLHaWlpb29/fv3r3rzh+NRnwdMhFtbGy44PLyMl94PJlMjo+PtdZE1O12uQHz8fGxLVLLcDjkRkfWLtelY4wZj8duhaRSajweu2ec1NigvR1fwNxut5eWllyQu+SxuCCRt7opcrkgGNEsV5t5z0Qg7unIP8HAaBarjS5NqdzKYW2UJlXb3ypNpYIztiUQQXLrLwFBhqqoBYvkDEGTW0VnjCmHY83cE5zs746OjlzwbHjmXOUBUNvH5T3l1gcPh2K02yrLSoyMRuXJiR6NK0FnjCnLyjXXaQZKG+cFkEAOVyLTRGZ5S4rG3KDX6zUtTgq13tPdprGvr/f7g2Y988bV9EqraYCDhNq6Ke0UaLxaAfAnTclUrxEInYMRNNW+tWBTIMET4ibZdtUxMTFABMNNuA2x9ec26K/e45EGwtROehS8VY/Ss2Yz2i42r5IqC12UZVFWoq8oC26VXWqljWeJbMhdCgAELKo8BO9sj5KtEZ/hAhlI9b85zLtnxcJrF/BSF10mglEN7yItQb/mDgoheIcYXDWZTJwXOgBPnjz5+OOPXSXM83wwGLjOt9PpTKdT11nPdpdBH+qC5NtE/EV1tVT/CaumARkmY4zhRU4AQXjyyQD1wmAAUBplM4SDEJCJu4Fstbqv3ExrXwlCinannSTVa6JUypUBWjkAZImVeNWZAimMGwsa96c+II3hkg1aczcQEkKw5LSGYgYkRzsnd+/cL+tsj8fjo8PDoh4MC8jRVE25CKp/CzJ13m0YaFwx2MIS80WDLfh5sQA8Yfy14rWFGRbGzvQJHt9UhiPfA15UVftSLJaYfOgAoCxLHrSekFxwY2Pj7bff5iolT7wsy+PjY2vK//z58+fPn7uo58+f37t3zwUPDw8fPnzotOUsywaDgUu21+v96Ec/Wlur3JZmWfbTn/6UuxEO3DyUZcnVyzRN0zR1GVvQZxhfw7d2tizeI0mS5eVlrm+/9tprTjuVUn766adPnjxxsa1Wi+uuSZL85je/ccHbt2+naeq6hYODgzt37kwmEyHE2toanyB48ODBw4cPXXB7e5t7CCuKIkkSV3RKKe5P0haUm7aYTCZHR0dOhbZKL/e7s76+fvPmTRdM05QPDrTWSiljDBFxQ+LIpYNgpNdL+c2ChOJKEpE/coBRzD1lYYqpmhaqGvxNVDEpxHRaVZ7JVIymGNWjAwL1ZJYJVrVqVYY0qAzywX4bw9UTU5bDxwejwwMX/9mHv3v0+Ucu+PDRo/v377vg2vj21tmvqR7iKJVOJqvGOSmh4iGOT1E9gjHQunI6cLKMo8GOPQ6g1Wot9ZecW6/OSn7tx8tZp5JXvW7vx2/8eHlQ+WeWAmvdpJs1wwUSKah59iVJS0lTtDJFUvBi9wcaNoaXiYSdW1ClKUuWjpmkdNKMnIQgmTr9jUACycJBTGpYV2W09UtVQQaCK4nkj3UNoKvBsZ7CNNN3QEpo5CV0oYtJ44NmcloOh8OzYeUYojvqjqajcVF5BcuL1lSXhecU1SsK0kIuUHqh/UxzRr7bmQD/8UISoAPMl5Nm4fAVCBveCyJe8rpLg/J9W/KuFjP9Pod32ZhReg8PD3kX/9vf/vaf//mfnVq7tbX113/9167vJqKTkxO364RNivenfKLfnmCDNntc6ZXSc2z+Tb/cBclzw3lP6BuD0rhJQyIkIoFkKWlf7VEahrXW0cQMm9kEZBl1u+5WreXVzf/rv2tVvVASJNKEXOJE1CVkBMAIYURzUwmz5PuZ99qbIVJ8RstgUoB9UdA6N0zpVVNTjJuzv/jjk//xP/7v0bgSDmmStNttUbu6Ot6Y/Oy9yZIvkCwtabrZ3CljkCGSi4QGaJHUILBXNMP86y7iK8qUb04Vj3y/+UaU3sXwOcXZYDDx2Wq1+JcKIQT3wq+U6vf7VmdO05TrxkVRcBfERDQej11vobXmyqTWOssydyTLsm63y3WzWdV0Xh+2GP6kNjibssN+QHaXpGnabrd5tofDIXfNGmyzlGVZv993wXa7zXVspdRoNBqNRkKITqfDi24ymfBki6LgsxI2zy4drXVRFC6TQoiybDzl2N8uaAuN665pmvIJhaDLx0z1iFxeWEOwL9xrGU2VOw8+5w8Do412Dpm1NlpD1xqINqR0M+kvCPB3PDLVf+sd1O+2eRYMQTWjLiiocVGeNerK2f7h4XYzDbf7+NHTe1+4IMr+6lS7+2pNSjUzPlOBcZ6MZHNvrStvVWdGHYrme3InSWQO127SHiXradatBGarnw9e6a+sVkpvQthoi37aPEahwBo32qXpMGUVwn98E5SAf4L9Fk8AYLzv8hDWrWlzqgTxzTuEf/oMxhvCaICLhOo1cYLY+lryx72Q3plGQzdqC7QySim2XkBprZ3Y10Ybv9Z9eeZdqwCWj5DglQTYejC/pcyW1ZdifsI/cIJ+akGfFUSF6qVPWZb8S+/R0dGzZ8/cMKbb7Y7HY6c2257addZmZhef2Vw5pTfI/7cJLaySNK/SGcB4Tt6JCHw9yGy63O2e1ihYKxMS2tjOAIBI02xlubkxEaXCxQJGy6mhcxopVbrjvAcyXgM0AO+KAGjjjSsL6EbSY3w62d3ZH47qebc8X16GG7mNR9PC2yOvQQNgXcl5nF/GXwOzb8Fx8T0vPiMS+bKEOkYkEolEIpFIJBKJRCKXhqj0RiKRSCQSiUQikUjk0vIdLG/mi2NRL+J1wSzLuCMrY8zBwYFbEGtPdpcTkTOmtWuS3YUrKyvXr193wSzLlFJuXZD1AMFtetfW1gaDgQ1aG91gtQ/PMxHxPAeLcu2yInf+4nRYTEhwl1arNRgM3MJjY0xRFNyOSAjBc9JqtbiPKL7y2cIXNQVvJFiBzN8IgJOTE3eCfVgey4NExFOzd+EnlGXJvWQJtuMoAOMvpY5ELMGyUm2MW8yMusW5aiOESJJml0VpqVuKAMEQb6Na14vmCl2Om/WBSqnxeNwscFXl5ORM1Z6rtFIHDx8M9/dtEMD2znPuEK4oCm64IYxnQ8VNDwDkqVjqLYm0WqloRYFt3b2rpnejedhOpzUY9N21vZXu2uoga1crHrvdbp4laW2NJv2tZQEQvCNfrqktPNlPyq48rEuZiK1LBOC9Pot/dWgd6yVuZnLC6oe3+Nlf/xhajZEvBkkkSeKqTXLeDuSRiMX2dDzIIquu1gVfvEcrioI71DDGLC0tuU6/3+8vLy87I6Z+v5/nuauxdjzA7/Xi9/3LwbDGHOaefLvNoMyVQtlIlfFoNGUlifEUzKY37Xbb7Ta5NygIKbO/CG8MYyrXiYTAdtQYf4dg/t5hjG9nTBCiMU0JJRCKsjg7awzNptOpENKNpvI8X1pacovbe0u9NHXdmkfw2g382jhzQiRyifkOlF4+dLBB3gJXV1e5j6ijo6P/+I//4GoSv7bf77/77rvWAdX6+jr3gLW1tfXOO++44HQ6PTs7czeSUuZ57pKSUnLLYSLiPqIx4wEiyzKuFtoo/hSBEawzrQkMjxd3QmmaLi8vu2fvdDq//OUvnQPYoiju3r27u7vrzm+329w+9saNG6+99poL2q7RZVJrba1t7etYMO+wurrKkyWijz76yOU8SZJWq+WCg8GAe9sWQrRaLTcZYecCrOMxy9nZ2T7TE5Ik4Y49rKG1TW1xWUW+9/jKSXWkxsAYbvZpvOZW6GJUNiOYQhV2wGeDaZp2Oh2ieoar2+3keauuZgRCQWziBUpVGtn0pBjunJna5uro6Pjzz++6Mej47OTBn/9wclD5lNJK7e49Oz1rtNxkciinJy6YZZmbVgPQOW1j1DyFzaTL81JXLt3qlL0qz2mabmxs2DksdYvKtxoZmKai00mbxpFK6uVUezdJpFzqdrOkihaETHgNSQhPDxR64QiI6n8XIQRJ5lRGkiSRegM+09jjaaOLsmRqL5Fg41mClKkQzXwBzajuXtUwYI6iYdCMKslz2gUS3rOQ8PSWLMt6vd7SqJo37PV6rVbLCcY8y0T0qxepsXMiLjir9NrhBBEFY4nFHB4efv755y6olHrnnXfckOCNN9749a9/7aRKr9e7evUq92t1odLr5I8xniJkFnob+TYx2milABARsZZPBkTC877EM2ygRiM9bDTGR/fuPXjwwAWF0sJ58AeuXLv24yRpJiWzlPIOEiYZWeIGULosUcDlqkaSEdSo6cYYVTsghJVk3FEVAWkKPiDUJJkoO3p6cOfOIxfc3d1ttVpO7Kyvr7/zzjvO9cxgpbOy3Ms9t2gVzIcDUI/9XCYFiTSRfrcQiVxavgOlNxATfJwBgOtIAPb397nnhoD19fU333zT/m75vouNMXzPIXPeJkM8G1ziAyjLkmvaQSwfUgPQWgcnB0GlKsH3pTo8IQR/IiHElStX3MfbyWTy7NkzvkuT/YLlgt1ud3193QX5VyaL7edsxvjjSNl8FgOQ5znP83g85u6a7dDQ3TfLsuBLb8L6EqUUEfETiqLgcxw8CvX8SFBDIpcfW7nmN5TAh5DW2jkcQj1ic5VWCJEkaZpW59vhaeJaigEAXu90vYtEUejx2VTXnwuOD06fPto+Oan02LPjg0/++KeD59WgRGm1e7R7Mmq03LXcDOqbAlhZWeG+8WQSfunlU2lZJ8tWV02/av55nt+6dctuV0avS/ppc22SIM+bIVlJGDGvUARvkyGB0KAllEZEdenbYPNz7pE58JRJEAnRpGw1XidUNbTymr4w3mBdCE/8zuTZz5VNuL6CCMZUlxBVfmbqOO9Cgt8xSZGmqZPAdr7SvSDJdfrID55gVBPghgT2HH7mgqtQ7yzogsaY1dVV1/mur69fvXrVKb2tVqvdbvMxw2JcOu7HXyBuiAJbVi7PdVm6M32MKUu+gdzp0dHOs2cuKDQk82vVarUMOxmSQGCeq0I0+9LrPOcD0DD8S6+B0Ya5xfbm3ACAf+aFFVDswLSYHLFN7+zekEmdWrvdXl1ddd/5l/p5nif1bKdH+BgGXq4EfLEYiVxmzmsikUgkEolEIpFIJBKJXAqi0huJRCKRSCQSiUQikUvLd7C8ma9XsQSrffgaXWtf6lbbGn+Vsj3TLhy6cInO4nVEAYtXK+Gi2wXXLk6Ks7hkBHMKJaXM85xv25vnOV/alNYuvixBHuxySq21ECKwNM6yjHu9CqyVhBD8DXKzWwB5nts1yTZIRPxk+/vCZzw3KvKDxti1X+dDRMTWmBEJIuG8khARQG7RmTGkNZTb0FBDT4yeNnWyKFRZagDj4/HJ4VCXlcA5PR4NzyajYbUafzya6lK5vR9JIxFJnjTW7+3MdJsQuq1Wl5nKt1UrXW1T7c4qzfO039hrYSmT/cwsVXYBWZYmbSFbBIASryQkIGB3owUAAUhj3AlkY+sFbgKG4K12o+r/+UEEZy+Et+rwOgPPvYuBdwoZa8XrIPJtERdnYjYyfIRK4lDweH4uDYyGbpZgwwhm5SuIAlNiMuA7f84IK+MXyYtDCyejxcJY/5FmoZfNFC5I+IdG0IsFzFSG6sjs8aBDJCJ+jnWZ4YKdTqff77vzu91uuOR+Jv0XIcib/eHlKnQk9+1y3kOdc8g0FhPGQJVlwVYsl0WhakkOgMhblkx22/C6sRsiA+25CgDYPTWIyAjY98XyQrMNzAiXK0AEgjDEjyIhRMoGw3m21Gt8zfS6rVae5Fndg6RCELmOgDOTJ/j+t+yvBdlazHm3fCFe+o6RyMvzbSu9xpjRaMRdGQU6VZZl3Otyu93u9XrO3ms8Hh8eHrpm3+l0lFLOyi6wZuHqk5lxzDDbafETAlPS4Fq+BTwArosCMMYEt3Z/+XEea7EOBlxQ+IbHUsrBYODuq7VutVp853qlPMO41dVVrhITEX+Kfr//1ltvlWVJRIPBgGu5S0tLt2/fdkGtNU/WZtJl2z67SzlN036/716ElFJr7TxOa62n0yl/RilloLfznFgF21oCB/mPXCpsbeIt0m+dGlKzsT7B8B5TSuSsZbXyXqfbd9VseEZQx7qoZF0xzo8O9N5SJYLKqdm5e3a610iknZ3do6NjAKfbB7ufPlTTyqHA6fj00d6jcVE7RylG8uBITKq7CBKvdbfy5WaEentDbK41uVxdXbUu9yxq9c1i828gKrmRZVmv15V1UGaivZzJtHooKUWJSQetAAAgAElEQVRvqWvHN6LxyQUAgiCKprCM0V1TuOZJRJRI56uKYBKjBPd0LTz3oUIAOStZqv67sPGHbOFYyhDp6rhnEGekKTN2OpEQLmEipJk/yPZbuhCSqJG3wWDJAJ4nbOlZqGnAGG1vLWZ0aR4saHJanLpMKEyWWp2iU5lh91udlpBp/fipghyV8qSuNkQyy4jZaQtRQjArwRAxt/M1HcDzlj/DAjEosEglBkhDBi+NQwsTx8IB+w8IY0xZlsEYgHfus0Hr2IJ851LGmMlkwjvEPM+5943Nzc3f/OY3Lqi15jft9/s3b95050vfGccsunaoabGZsb/5hbabdp0+EWWJ57nz62VxlSJReVEmgGmPAHzpo42ejE1dksaY7QePD55tu/gn9x7us+DKUn91pZHGrbxNnSXUDjvLVJ/hTLkJTaJEVM7zARAoMUmOtIqzR6sokG6eiLRBaZoyJ1Em6QL7WfK6NaSr7ZVXG8c0y1urP3n3NffY3V73+o2rWe26KklFP0tT5sMPunJ8YUiXopH5RCJNGglDRBTOhfp4HvBnUQATzrPQvMSTC2yJF9zzQs69YSQyt9/9JimKwmlBQLU/kAtm/s5D9qujkxpnZ2dpmjqdOU1TY4xNbXZLHm98Q8TFPQBjmDAKZdc52inHamL8CO8zgnsZY6zyZqPc8Vlsl+aulVJyfVIIEWwdxHckAjAajbhTqFarxQs2eN5Wq3X16lVjDBEFZzrXCC9CkKwtGXfE9rKuU7cPyFVo4TvryvOcP6NL3BjzzXW6kb8Igh4u6GeFr2753/4EIWE6VpLmadYiUdW6RE6hM1N/2lWFHA312WnVfouxevZ4tP+4mTx68GB7Z2cHwPGTnWd/uuOU3pEa7RV7U10JnxzFNYy79dcAKcXqyspqv3Eg//o1+epmU2lXVla40nt6+9bBL2+bxgNc2u02KyZSwnLqed2U0o79IDQElz3aH3IYDVXCqbV2yNgIMwNVwrALpK8jCkLoC4W3bjLaa4a87aMatBHskINl3hgyqrmQhADq5wEIM/cMWDzqar7i1/DUjNGmlkgC/PMO/KGRQjnRY/dECmUrTdtZNQ5upVlCQtZXSANRaJrUJUkkhPE2DCEDcb7/RQBA4rsY46Qzz/NlWHzp4pK8gPlJz4+5rCiluLIaaJuzwwl3JIgqyzL4BsD74sFgwIcieZ7z0ZHwZ5wvxPguNl2XSkQ8EduJu6cjokQmcrF+8tVY8ABE9QILw1zfoa7F9QFjjCkaz1VG69PDw73njZZ7vH8wPG68DPazVi6bV5YmKbIcdWPXcjrGtKi9wAuIjDJZe6EiUErtBOc5DAualwH/YGwENPnSyUf4RSE7WXu18X3Yz/Prva5bEpNkstPPBBed9nYOBbsURQlTsKKTUkjpe1StZgXnoZqlROeggAWCbsEDi0VK74WCakGliUTmM686RiKRSCQSiUQikUgk8r0nKr2RSCQSiUQikUgkErm0RKU3EolEIpFIJBKJRCKXlq/fpldrXRSFMx2xLhwaHwBE7XabW61wcxcwOxNLkiSBia/1OWyDQgjrLhhAnueBgRk3X5klsNoNDGMClw9BygD4IxBRcK/ASEZKaVOYNb8JTiNmDxyUDGaeKLgL93plg+63hT+FLTp3nJsV2SPud+AewxgTlEaQSR60dsjuDSqlAvthAEXRGISkvsdp1C/CFsts6UUuM/xt+55zKXCkC1O57AAAjMfjnZ0dZ5N2//6z3/+v/310cGqD/cHgYH9/ZbUyvlVT7HxWnu1WLcsYMxwOrZsAOptQUaBudHmSb7Y33TxhW6pXl67106r2Jkny6iuvrq+uV9HAq7eTjRuNNMtXV1vMpjdd30jWuqaWQkIIXvclQL4Jm2slKTfRBUCAZGVhBEjC1KfYFHlC0jccq/3EVBi4552FICDALjeBW1evhbJ7EhGSpMnGzPs7By5+Fxp4GfLiLnD1zNje3t5+9twFnz9//sUXXzjh9tmnd/740R9Pj+tq0++XqlzqVW4UBoPBxpVrje9uois3Nvu1U5nIpSdNUz5WCfri2a7KHlFKcc9VRVF89NFHT58+daddu3ZtZWXFBQNHANbNhwsGNzXGFIXnxC5JGvdLmBlRKKVsv0++ey3MeFr5S3CoYaxBsns6ECFxOSYikTRBY8xgeVmPmlHN0tLSrVu3XHB5bX1944YLtvt9maZOKAkhW0krqX0nEJEk6QQLgdzvKlc1RpMumwInQEo422FDUKKxutVaP3y0s793XB9Ap5W36lEZgCxLb95sKkNuZG4Sd2uZEBDKvgYDmKoLESTS2iciAMPcrMA93UyNjUQuJaFe9NWxktf5ebK+FrjktYqrCwZKVND2Aimf53mv11j2g+muQTqBMAqwd1nQzrXWnizz1bxADwxODroiG7zwjgCEEIEqzrEPyHMSdEWBH+zgXsG1RGTfgjGmKAouBGfPdL8xU7D86dwR91sIkWWZ802llArGCvag+218zbZ6YL/wIz8IFjUU0Ew8V3on08nx0fG0qEY828+f3/30072dQxtsdTq7+/udWozogk4fJZOjpk46edVFsm5y57soE1m/23cNv5OZV65MVzpVW0iS5PZrt69caZxtbv4oXb/JBOzKCtYblVh2l0S/1Wwu5EMGVNgRS4VSVVAIsG0sZsrCECDha5zNb1gt1zvgY/g2PCHEd4YCMKNgzr2U3A5SL0TY5A1/vwHGeM9oYGaydT6HBwdffPGFC96/f/+DDz5wwu3Rg4f37t8bng1tsL/Uz9LM9T4ry8tPnz7t1dN5QsqltVXPAeALZSHyvYSIgpFJ0EnN6+iNMePx2E0xj8fjO3fufPrpp+6EV199dWNjwwXTNN3a2nLBxWity7J0FZiIghFF0FMXRWFzIvx9ImhGW1446fTtYdinCIKQwvBmRsynlzGm0+2Z5UbpXV9f52O29upa9/qmCwYIEqnIpDx/ABkovd4ARglVNo71hECWwxWkATSrF1qb7ecH9+4/c0eWl5aWes03ns0bqzdvNp4RMQGdNYJQyFn5ez5EJJm/K+ulzJWkEEIk4gWTikS+73yZgUgkEolEIpFIJBKJRCLfK6LSG4lEIpFIJBKJRCKRS0tUeiORSCQSiUQikUgkcmn5+m16iYj7mrKGJfyEBaa2FzLPVAYIbU3BzH1nGQ6HT548mUwmNjidTnd2dkajkQ1KKV977TXuQGJpaanT6bhgkHLwjIHljD0S/HgJbLKLU1gQO5tJ90P6G9wH5kmBCe5sOsFNhRCN4Q1RWZaunLXWgf3whZVBSmmsIyuiC079aswtOADORuccLjR1mn8psCjWVP/nYnDR5fNZfJ0fy1+vATRL2rg/zQHNjxA8YyGqvQ4ZY4zh71NAps4rkgG4IzljMJxiwsyhDg/08XFzl+fb40ePK9tLAA8eqN//vlOWleOAw+1rGP6si+qEvGzlJxtZUTXnlOin1+TKjSbx8XhcTAsAmT5rqz2BymQrb7XWVrXz79LupLfeWOsvV/bqMkmu3d7sM6vd9vUOVqtYALrV0q1GhlDGPJbMQNZkixWtFFW5Slo4V2kIUno2sYFMIHjpzhLa0zJIhJUjYF7kfLl0PkR+vZK+wxYPCuO8exEZoEqtLFShGrd502lZlo09XlkqpZpql7faGzduONnV6XQG6yuddvUG20u9QpqzsoqVRpakvfdCEljwhsX8t/iNmdcRgLoazWXhvYPX8heANWQFqo5sQaf/FfG6RRO+JCq14X2ZFDjP+dN4OPrs40/29vaq4Gj0//3u/U+YTe/aYPnN13/sgnmSGlZFbe877xUJEmmaatb58tKYfW9CyjTPMXNm2Nsa6FJBNQdE4pcz4bzkHQaaPwJAxKqZ8Q32DbSB1zVUTu/UeDI+OtK1AS0RSUqcjwESlLbasrbaJaC12patxiBWSCnYG0k6LbS8cYjSyr1iI0gaKXR1/myWtRkXpgRA8MxlNRKjpHuaSozV4aIwz5+Xp2dVuCiK3//Hw48/vlOfjh+9fv3WraYH6eVZceWqC0qotFU2L5+M5lbHRIJSz+kCVQVrBAx7AzCUyIQP0ogWyhxaLDTS+aLMMi/phVfNuygS+WosUnoD5SfQbeYhhOB+qmYJtFMx46N4MfNO1lpzjwKBn4mA4XD45z//+fCw8m1zenr64Ycf7u7u2mCr1frHf/zHd955x52fpmm/77kp4VRSYz6LY1+cxT364rssyOTisgpYkA5mYoUQgdI7nU4DpTdIjdc6Yp2xQuP28GVYILSBmXGzBwFzrrcd2rlRABD42Z1h4V3taGDBGVosiFyUL1rUoxg/1eBVa5iSxQcDFsDAFPxFSZLW4a9FQFMVq7Vm6jElJKShqhIag0IbN3rTBscTccb8i3/2QD940DT2j/44/q//98QFd3fKe5/3nDTIdLpUtLqoal2mstbxej6s1NGlHP/nO/STa81z7u3tHR8fAzDqsZnuwTRqz9Wr5Hye54PexnvL3evV1BglSe+1zZwpvaa7bNqVs18AqtRlyUpGivb8dgQCXrRFBrz8lV8z4cOF4Ytozr/wysUniLrCT8tiPK7eJoDpZMqVXqW0r/S2NrduulqU5/nKyorr2jqdTinMaTm2QWlkCeUXfLK4e53L4of5qixs/C/CV7v6a8e5IBZCLO4fvwqmxh0RRniuywtFrF9DlqKWZpzR6eiTDz++9/nnNjgej//X//wtd2T1m1/9elB7CMeM0ktSQMwV+0SU+DsjwO8Egj5BJElWa4lBkv6ZRpWlLppspOGXDLNoHs0o6IKJequ310VnDJhPZgAoS7CBHIQACQBqdDLefaZqL/ZEJETjfEskibh6VeaNl9P2Wre93kwyQojGoxQAQUY0819KldNi6t6voDTVPTK10kvgUw0GeqqOCn0GIJFJnrC5LZNryl0jsblzD1dMzNMvyu1nVT2ZTqf/9W8P3n//j1U0UPztqFW7jAaw2htMt1wIWUu3+lOqi1obXerGHxWRJEFETObUFdAoUqxuCiESpqgDF6ifFwkN8ZKC7kIW3DMSeVkuqOyRSCQSiUQikUgkEol8f4lKbyQSiUQikUgkEolELi1R6Y1EIpFIJBKJRCKRyKVl0Vr8wIgFmGs1yk8zxijVuASgGfcS3FDTwi/X3IMNQhtRGzw3G0GaR0dHzl0EgJOTk52dHWegtbu7+4c//MFa7gGYTCaPHz8+PT21wU6nc3p6yg2Pg3II7IeFEC9uExuJfD0Yw62cTdhwRGVRvNgeB9ClMppV71RQGjTP5reG0b5tddAYiTyTs/n+MUg4U0tAaUwnhTaV4VFRFM+ebZ+dVa6nlDKfPzXblQE+ADy4f/r08ZkLPn2UbD9tjNlG43GW5640eiK/kXSz2hSqnedbV692220bzKlI08fHx0c2aOl2uwBa2Xq//SNBlelX3u0ub24mtU1v0mv3trbytcrUn6SUnY5nNnaemGJ4IiXyLZAkiTPJBnDlyhUWicFgsLKy4oLT6XQ0GrleIEmSTqeT1DaQWZZtbW0NBgMbFEL0eo09YeRbQwhhX8rswGB2APOlCEYUfGRyjlizdp+cwEejMQB0UZwcHx8cHNhjSqnXX399Y2PDnfXGG2+sM78A3V6PPJHy3XyloBlPVyzSlvP8TsGgsaqvjlh3FfXvsvTKioj7ABufnE6GQwDH+/sPP/tsOq6s6IWQeZ4LUZ2ZtVq3Wq3GmwwRUgluuRpKYy8oSCQycf4pBKSo/GdV8CwDECQTmQCQvuW2zTt/uPHY+abAyfH04cPHD+9X7ieUUlmW3bp1q4oGbr1669atV1zwypVV7u0wCe21gxo+t6obE1ZGr6qeU5sjkUvLXKXXGKO1dTYTEvQu9kzX9pRSk8nE6YRSyna77VyeYkZFVErxuyilitpXAWZOdj2cw+VECMHl8s7Ozu9+9zsXfPDgwfvvvz+uJebx8fHdu3eHw2pUbXxFfWlpaX9/n6u1Qd9pn9EF0zSNSm/kGycYSWgD1VRLU5bOsyUAIVOyXT4BIujiPdS0VNPGzUXSzUTWtKOgv9QwilQzOCAhIXmnKfBCfumIiNhwoVRmOBqXZZXsycnpH/7wwdOnT22wKPGfvy/u3G+ebufp072dyu0cAFPcNMVtF8w7nW6/77JxpZW/tTLoJtXt+kutt9/eXF6ufJyYyenwT093nu3YIICVlZXl5WUAV9a6P761nqb1w/Z66SuviFpbRp5ga5WWGv/MgP+OZsrBEyMLPIJHvhmyLONOFjudztZW4ygm6HoQjN3910dESZLwHifQkSLfDkIIN7qYfV/BzHXwBt1vC48VQpw7zrG/CSTIF3RShu3dk5vaBsvxeG9310m2LMt+9atf3bx5053481++t/VKo/ZACE/p/Y4gEp5XYP9BjTGK+WcOyo3IeE3DGMM9V2mNooDzAUZEeQ42xjs9PDh89BjAk6dP/+v998/OqrnONE17vb579b1eb3l1ddlNPBEhaUPOqIlzEEJkgrtf9byU2U6QC28pk1Sc45tdCAg2Pp1OzXCoi6K6cm9v+PHHn/75o8c2SESDweDdd99157/77us/+9ktFxwMkm7XhcJ+3BhjtNH1dIMgAWHO7ehnlV6tm5dIAIyXciRyiZmr9H4pAp2QB4MonNfZcGbPfzmCDk8pVZal8xtsN84J3Ai7Wwdfm2dZHBuJfG/4WivyooZ9Id7svzfjpjVKpcLdZbivVK34kMQYA2om6olIsFEbkRBCuH0mtBDVJQwro8ieKqooIaXgY1ApIZgb0sj3jWB0jjnVwMFjaWant8X9WuTbZ3E3bYz5Bl/ZnIQNAGN4xoQ/jy/8SvWXyteaw4WvCaZ6j1WXUHcKSnnBcMy2OM2vypd4Q8b/qq01mzohsl2MO1kIwYMX1gR/64SXxHzNrzMS+YvmAqX33FYXjBWCzkMIwUcDszOmrs27YHAkaPZBHvjJxpiyrJy2j0Yjt9EugGfPnu3sNF9vDg4OhsOh+zxbFAXvbEyNO58WrueZzVXkm4ZgFop4emnRTXhpwU8vfeXFGECHa6qaWxmAyNsoQhD/eKjJGLvVotX+eHUlb4cJI4xpdhaEIWW8SW4KN9ple1SSTcxFwzt5lqIgVQoASunptHQPN56ovcPJpKia9tnZaHu72N2ttNxSoRiqhGm5g1YrW21WoqbUz0X9ARZI06TVVq6FDuSoTZO0fqhE53pcFmfVF1ozHYn0LF1qpErWN3kfANJBQstdtwcEdbvotNCqPwhkCWTiTeyH+JuL+Ht7RvnxreGNhn14VHDahUI+6Phm77L48sjXy2xpE9HsO+XBgMWx8E/QxjcnMdUO5O6Al1q9vlcmsjfor6xV+8dmWbbU73fZwvg0TT0JelGWvi4W3MYAIBhe1WH83dr9mh80hErtYwcNWFdFgPBiteF7ApfTYjqeAFClSmSS1mt8syxrtdtu4Ubebss09fZG9jcVDwZ4RsB/aK8ACCAYOEOe6u05jNYEI6sYL0oEb09Kcku/01T0lrJBvbW7EGJltb201Oyr1O2lSdokUK/ddpAxrKwMYJJmT2MSmLemi4zb6AgAVUOCOuj+RCI/ALwRW9BDcK2PE/QNQohg6JAk3s7XXAc2xkwmE/6JNSAwuwpGHmVZcjuryWSyvb1tdd0PPvjgww8/dGc+efLkzp1m1+/hcHhwcMDn2NI0dRJTKXV6eurWthFRlmWtVrNwcXZNdbDomkVGvgkMYSrAtu8LSYDFa5kWiXXyO+UZFgyHwn7pyzA3UQBQBsMS9YpfCEJGnpGSBFgHCQHIJjgVaiKHsHWVmhXIBBAKsvowAAPd1iZnD09T5W4KSCETpteRSaRKGz3XgEp/sFfvbWgJyu3pU7O7DwD7+6N7946n0+qFHp2NP3m4fTKs5qQmk8nT+7unx9VKNjKmp8fLptmo91e3b79ys1mYeuNK+7XrzcCxPDud7O05Q+XTw6dP7r4/HVcW+8mpGN7JpvVqZ5nKtc3Vzuv1yINw7ZpaXjYAeusr+e0t6Uwz0oQ6XdQXQkiTt/lKvAAyCdhq2QTkLNAwUzKRbwittbOgCZpxMA6mmYlOO2PrjgT9o/EXEwWzt0mSRJuXbwf7joKhAo+yBN108DaDa4PUyO/xZ4cxSZJI1rqllG4tCQAYsjOJndXl//a3f3P7rTfs4SRJbt26tbZW7fUNoD8YIBxO8HyGDxiwYLtcywXXn4cxVCRCs4lRJdAohIA0WnCbXtNssQ6AtKFSsaIUlCSN+DMEpGh2lzUYK7BdZY+f7z259wjAeDxe6fSXskpQt7qdq69sterlv3mr1V1bR6dZDWzShGuN02LqGS+kKUkuum2GqlxJ6JSmbs6SACGaRzKaJqO0LHIAiQQzmACRkKzaSKJep7kykfl7/21z85VqflYIcfPGtZXVyi8AgNW1zmClyXMiK78cFm2kLpqxsTYGukVNvggmOddqRpCWadN7ElFl+mSDoGCCIBK5xDTNPhgBYEbuLyA4bXFnr7Xm0ie4S5IkgYbJIaKyLJ217Xg8Pjg4ODk5AXDnzh1uxLu9vf3w4UMXtEMfF8zzfHV11RmElGUZDHeklDwbwQPSzPCIRUa+ITRh7lxJOFsccsELIlx09Xl9CXBhwl8BDUwNynowUfmlqu9HgAw0btt1VShRTmQBQEAkBNF0nkagJDd9QAg8uOuyJG4bTAmv3WQIJnfZMBqm9IrOaL9EmlXGADA8wd4OADx7Zj7982Q8rl7o3vHZ7+/uH55WKzXKojjaHk3Oqn5aknlzZTLoNN321mDw8x/ddsE3tsTPXm8eY7Srju+Vpn6KJ0/2x/c+PNG1W7spiolxAihtt5PXf9XZbFTo3oburwJAa70lX7kmUuYchQ/XIIBs0axHCT5LQ0RsUiLy7eHU0UBQB1qrEGJ2kRG/hP+23SXvMQOlN+hMI98QCzrf2V47CPJ3FLzrWXjd0FqXWk1LNoyRgpj4FQL8m58BjBEA0na+efPGYGXZHpdSXr9+vd+vnOHB3iXIhleRjJO9L8GFKvFciDTrJgwM/7pLMNL/7GFYQyClUajmdAnwwjEAZJMzY1CWKJqOfno2Oj06AaC1bqW5SSpp3O70lpdX2v0lG0zzPG23wXzHQAr+dVoZU7B+jaTnioJAwRqlFIor9uA2vkSqbBeTFADSZhYUgCAY2SQkCBmbmDZGXt/o5fWaJCHEq6+ura9XlQGAlLNfdxmGtOYj9iCDze8QMiTYG7moqkcilxh/wBuJRCKRSCQSiUQikcglIiq9kUgkEolEIpFIJBK5tMxdSIyZ5UAvzuzKrtmVRfx3EMsvD1agTafT8XjMlzc7/1XT6ZQvYCaiYJk0TzbP81ar5ZY3T6dTbnj80g8eiXxtkP1XV8VwzZsXOpfFPqU4nieSF70IAAgw5GXG+L63tNZ8C8fJxFhfcpNJURSFc8islCJmMiClzLIUZbWSTQq0W7rdbnKW52nCNhMWkvhdjTFaKbfEzjZ83rq5rWaapUmaOcNdAkSSkJQASAivNL6kWDBfriwj3wFBT8RiIpFFELxxS2A/BQPNvDEJIURtRWk9wrvjYa0znjS+FDXSN3H5kgghpUwACKGJuWNKkkQkiagt6c4pSZ/gfQVF65c6DGAWLRcGsWfy+jsAyjOFEtyzlSHBNg64MM8XQl6/F4lELqbxOIUX7vUrY6b6Qj5aBaCU4nopEWVZxq180zRdYC5rjOFb4B4cHDx58sTpvbu7ux9//LHbX/f09PTTTz89OjqyUXt7tdke0Ov13nnnHRdcWVl55ZVX3H3TNF1aWnK5Ojw8/Ld/+7dHjx7ZYK/X4764Zgmk1QuWWyTyJRCEPEVSV0IiCN8bsA8J4i40EpIppQAIxAx6ARgFBWYdrblhECCFyGq7KQAglLo5WRjungUg5oIEKKc4PMSk2gwbRVF+8cXj3d1Dd8JHn57efzQCcHIyevbssCjqYWLW6i5d6Q4qp6ZpIlZ/+XYrr5pnKvE3r6jX15ox5dWNK6vr1ckA+voIwwMXHB4cPH782O1pdHy0lyTS+aXr9Xqvv/66s6MTrVbvF+/mmxs2CKJ2p2N96Yl2n7Is9M9ciwUDo7kP0xmE8Qd7UUh8F9DM7KeD92KYI8YX9AIBsVP4TjB8+1y/zIkCPcc7wfjOt7/U+yKiVp67SXMA2zvbdhxiOTw8PDxs5N6tW7fsaCRN0v+fvXftstu47j7/uwrAufeVze5ms0VSFCnRliXbsR4nk8lksiZrPCvzJl9z8g3GyWTWzMRxnCeJZFnWhZJ4ES9NdrNvp/v0uQCoPS8KKOzC6T5N3SiJrt8y5S6gABSqgNq1cWr/68LycjZfaBcppZrNphwdZWklWYLzJE6+K2qfUxWUW9cNAANKljk3RLrqKOk8H5hIijBfXF2N2QAgrXWSuBXjdLPRvnhBtyol5Ia3pi2MMaWUIQBorVvNSuE/VzoTd5Hl2SSbuJc9VqyVcfIUZL9UuJhtokYDsQaALEO5cjAAjEeTo/5JXn7vaDSihYV2khS1waxXVpaWlos4ZCLqdlt1wWmBKVZ3LrClcx2SrSdZl9P1KgbpX/FRDwReMjyZ5ed8GaSZmcYYI4UNlVK10UAURdJJrjGZTCaTSrGm3+8/ePDAne3hw4f/9m//5qzL0dHRRx99ZK1LzTz0ej255vvly5d/+tOfOl3oKIparZYzNk+ePPnjH//47Nkzm2w0GmpKktr9jS9TV4HAV4QIsfZkkgzE0EFstxvIG4po6Og0j4xBDDZCYcnA+L/0ep+oDJvcyF8wWIGryxNIlNAAgxMMjorkeGxu3967f3/LZfjg4927X/QBjMfj4+Nj1410FpY3L1xuzRWSHq1WcuPGpaWlQpA50fir1/HjNZsCAJWApFb3sxM8qTqN8WCwv7fnOo3RaKCUdlLt3W732rVrq6urRe5GQ7Dy2NYAACAASURBVN28SWtlEoDTktFN6Mgbich+gMEMOa6qQcW/wHcJ+bq7NWqd/Lk+8AxqRuHLHh74atRaTTLbTM/YdS5EFMWxG20w88nJiVwi8eHDh48ePXLJOI6t06u06va6M+bgGGMyIfOpiGbow3+HeLcw/eR7Azzlr3A0E7KSUtXZenNzTQKAKEmSbtf9tIs4wnzXU67yYfauqpWW8topkItbYOZxNnYPEitkUXWLRN6HYyLEcaFgmOcQv9Hg+Djf3j5xM5ja7SRJmu7x1FrN9TpxJcA8hf9cMHtOr93ioCmnd/rwarNsoLMfv0DgpedM5zMQCAQCgUAgEAgEAoEfOsHpDQQCgUAgEAgEAoHAS0twegOBQCAQCAQCgUAg8NISPX9kS5ZlNuahFkVTi9rVWrfbbaktUQviZWYp1fD06VMXTAvg4cOHn332mdx7+/ZtF543HA53d3fTMuiFmTc2Ni5dugTgypUrV65ccQdeunTptddec8mFhYXLly+7oN88z8fjsSvkcDjM83xQKhIQkQxLRiFC60WlyOTs2KHAN0QZRnM6qh7RUmPGTgZTPnNxd/aWga8g958z0LO+KzFmHEzEiLxgWz8siqFSiNBcZu8RJeKGTRKByIXxMGC4yVzofwDwrwFtdMZSl47zvMowGOi9Z+SCfPtHJ/fubY9GRTzt8GR87/7WUb/QmTPGHBwMhsMq5imeb9z6+TKApNHodru67Bbm59s3X9vo9QqhkSjSi4txs1lcV4PXkwM1Kk4LYPveo92dpy6Z7j2d7Dx2yYO93cdPHpiylDnladLipAilyhYu4spNtVkG/EcxLWwgKcKJgSIECkCmojE12L3a7DUXERQRnRFPCEAhlYJh9ZpWETAjuivwzWCtlX01pjvq2clTt1iY+VzdB5kMfEuQ0NGsNcGpW54Te2DNyru/jTFHg+NxKT5imH/z29/+53/+h8ugtZaR5P3jY6uKRADLjpx5PJnkedVLaKWTZtUtEFEmJBUUkSJfUl5y7r1+xQPZcGqEnKFWulJ1AlSWstBhoSjyQm0NI6+6vtHx8c79+5Nh0Zmz4XyScjkgVFqvbm7OL1UihVG3p9ptAKQURRHKVmCtmBWXtokIpDWJUjFByigbIha22PiVoVXcjLuuuWNCrFm7jp95MsmqGmDiCXMGAHfvbf/+vXvuwPFkNDg5cKZnZWVpcemnrXYhJ8FkchopcudBludSHyfSba0q0wyCCEMGKlME2Fv2G47h2Rhm+w8gwyyEOQA21WNIpLX+ujrSgcAPhed1epk5z3Opyex21c6glHJCqaeS++/59va29HLfe++93/zmN3LvnTt3nP+ZJMnc3JwzJ61Wa3Nzs9vtAvjlL3/5i1/8wh148eLFV155xSWTJOl0Os46DofDnZ0dp5h1cHCQ57kThdZaTyaT53d6MVUJgW8amr281teCGDBnuLWW/Oy957b72RmIZow2mEBRZZmmYPAYqIYazEa+VoqcmDMpSL0LxdwBn6n/keUoZTgAIM8h3gMcHuDufaTllq2t0b/+66ODg+Jr0eDk6LM77x/0CxF1pdTCwkKrVWlm/vity9euLwBYWlq6evWqE5da6um3rzYXOrWPGuW9G4PtQ/T33I7de7///I8fuuTJwc5gt3J6x+PxYDBwb6hqtfTSMkXFLee9ZVy6QldeLXIrjc4C4qqQjozohKiqU18ARAENYiFLOs0EECIn7K/mRE0gmfV4BL4hXO9dE1A81+Odgc0sD2Hmr+xiBb4ytVaTTcC+PvO51I6tqXXKU2V51j8+Oiq/khtj/uu9d//Pf/xHl2Fzc1PqaB6fDOyp7X/diRgYpxO5XEW302mWvSKA3FSDLqD4haFK1qCzzcVszjmQ2aSGK3ktTbGSqv15KtWcmNku+VZgWEoljo+Pn9y+fbxXdOZszGQ4NqWNieK402rPLywWuQHdamv7FYAZsioIBtZ5AwAiUlqR9BHJE8Sq2W/2e15NKikNBIAIHCnj+vY8z0eTLHWGkFU+LOrjwb3d3/7mD+5RYYxyOnQfo18ZXH7r7ddB5RdVYkOj3BkFQmq8cSZDEXlfQkmseERg5S2HBKBqOAZ8AyN6JDYQdsz4y2spxUolX+ZFCQR+wJzdgQYCgUAgEAgEAoFAIPADJzi9gUAgEAgEAoFAIBB4aQlObyAQCAQCgUAgEAgEXlrOjJO0MS21sBYbTyKlI9xGRy0YZjKZbG9vO40oY8yDBw/2yogOAJ9++un9+/dd8smTJ9vb2y4J4Nq1a+7vxcXF69evu5jhTqdz9erVubk5AJubm5ubmy5nt9uVwYREJGMnxuPxcDh0sTTD4TDLMlfs2l0DIKJa+JbYGQh8K7AxVcgOQLVoLvKUOpi9x7J6YumctehHozzLqgN39/L9/er5393df/Kkeh+fPcvu3BuXQnIYj7N+f5TnRf5Wq/mzn/2MdJHUmlZXW71eFaL2ytX5lbUugE6ntbzcdsH53YSSGCjfuyxN958+HZWdBufZ0b3bo2dPbBLA3tOnMhBucXHx2sYFlxyenBzs77u3eMQ4MFZ2BAAIoDyHuwdlOM9ltBiVwWAEKD/USSZmVuoZeGf7KicIfAVqilOOKuatZEaMrn2hZIbA941a69SS08/A7PzysbG7XAZOeW9vb7sU4DTGpGnabrdtEsDNmzf/4i/+wiVv3LhhT0XwemNGTUawDhtP9ZMwU8zx24KU0pFfe5nQtYqJpHKVF9ALjI6ODx9umVIHYv/Zsy/u3u3v79tkpPV8t9eICxuhtSZjqs4ZQBI7u+BDSpOTdjr33TTMuTwPEaS6KuBkq4ApVUwCqWrQm2f8+PH+wbMcwP37T/f29txzsrDYunrlSpwUNbC2dmF+vlGNQxW09soZ61hTVV2RjpQI4q1BqIuAyDZhO1YQR4sqURASX/A7N6JzRgiBwMvELKc3yzLZ4Wqt7WuvlHIyyNMwc57n7o06OTm5ffv2kyfFgDVN09/85je3b992+R88eLC1teWSURQ5eRsA6+vrt27dcpfb3Nz8q7/6q/n5eZvsdrs3btywydkmLcuy0Wjk8oxGo8FgMBqNbPLk5CRNU3ezVvhkhkWUXUZtVyDwzcBs2FRmjUjVn0mSloxRfbUBQEoJJ/nM55MZw2F+clK95vfuTu7eq8Yct2/fe/fdd11yd290/4t+lhUXmpubu3Llivu6NL/Q+8Uvf7y6tmyTUYSrV2lpqbp6dx6tDgAoBaXg7kbn3BhmKJ3ndDjc+vTT/bLTMFn24I//tffwXpEb6HQ68pPWq5tXf/6Tmy55dHi4/eSJq43d4+OPHm2dlKp1ighZJp1eZBlrTy3GVh1Nj34EdPau0wm9xHeBHA3bjl3urSVrnbz3QhFJPV67RSYD3xWyIWY0Sq1BlVhy4ixkBvlx3zBvb+/cvX/PJpl5MplYQU3L22+//fd///cuGUWReNLqfq/3EPqjGGOM/Fh/boG/JTRp6TRlJsuFprRWRGLMVuvoTg4PHn7wx3Q4tMm9vb1PP/748PDQJtut1uuv3ei0iu8FWmvKcwgtaDSSU51eIpDW0nGd3cHmxqTy84EqdR4BAMp3emsfFkqft7hWavL797bvfHoI4P79Bzs7O64F5xc3b9682e0Vt7Ow0F5cbLmPIUwwwlEHEMex8qZbRrOsypTH61UM1Q9VynV9LO+JQHIEq4iC1xv408H/7SgQCAQCgUAgEAgEAoGXiOD0BgKBQCAQCAQCgUDgpSU4vYFAIBAIBAKBQCAQeGnxQnNlbImc9A8UkVFVVINQGhiNRoeHhy4g9uTk5OHDh8MyhOPk5OTjjz9+Vko+5Hl+9+5dlwQQRdH6+rpLrqysyGQtpndpaWlzc9OF8zUaDa21DXqphejUol9qEVla61oGrbXLYPd6kTY+tjbqWwPfJsQ8S/SDpyJapjn76JnBmzZY6JSwIgAgnnVeyt069Wcw41hboLJUxKgCfAHA5JpZxPQaTVRdi41OMwXA5DQeIzfFebIc+4c8HBVxYsz8dPuwf3jiDvz0zs69+9XreXR8TN2GS15oN1YuFRH1AHq93iubm81WISzX7TRfv54sLRTF1BoX5tAtdgJAw6TJMANAeaYmI3dD6Un/6aPPsmGhXJWOR8f3703KuC823ErGS2sLNglg+eLFhaUll1zafAUbV11yFG3v7A5cj7RD5mGeDEqxrowbw2Yv65R3oRTiRIqvcPl2EyGZ2XzasJrRgBTNeKaAeHYQWuAFMMNkwA/jPLfPz/NchoxKgxL49vCiE2tSf18DY8xkMpFnTpLEnT/Sen11NSrbl5lh+JWNyzYJ4Mb160kktJ2IODcAGGD2upRIa9WoukgCJmkV0crgWJxHK81nG6qzu6Ln4KyTAsxQhkkanyxXItJYq6mOzlSZmTknzqg0Co3kwtpqZ37OJlvt9vrN15YuFDKEWuvW6gV0K70GNGNEZbNS8Q8AiFjIQjBgGOyuS2A/ZFuTp1wFIqqZdHF/xmCckbD5iiiOVdncUb641F1dBwAdX4oblYTN5isrm1eW2+3CYrbaCWmkeTlatpf0ihH5ElMzH2AGUzUIYrCBHBOxIlBZzwD8RvViehXJipx50UDg5aJyeplZ6nzYP1y3QUTOiqdpKqVTnz179sknn7gtjx8//ud//uednR2bnEwmjx8/Pj4+dvnH47H0ma9fv37jxg2XfOutt6TsYc3prWloMXOe5/ZsURTFQkKwhjVa7u6iKJKDGHtaJ6BlLyFHMDUH2NaG3BL41mFDpwlalGgpZXwKPGNQQFPSFT6eIREQQ2Vn7gWAEUgIUdbJIdzUKTSoJa0gS6eXkWVNk1fvglLQutqf5WSHJeMxdncxKd/XkzF/8Nnk6V5RKmPM3btPdnYqfebP7r1/98FHLrmxefnGjUoj6sp6750fX2zERak63e7ljY1GOWhrRFhtczuWajG+SR0M6HgIACcD7O4iL0ZOw+07n/7u/zjcfVDlZFO1l47m13+8vLHhdl574/XL1151SbW4gZVrLnmU3LnzxaHrZJ5o/Yd072hclKOfd/+n7oV0adXlV2f4Mwp5G+mZzw0TcjkwqkM6AlXfC+qIYUfgO4H8ZQhq1Pp8CGt4Knme1zSHgo14AdgxAFB8lZjdRrP3SvI8HwyqD2dxHOtSyBNAkiRv3Hj9xquvufzv/PTnsvVb7XYrqd79LM/TyQQAg/Os8pGIqNlsxq1q3DIcjdwPBgAaSaPRqM5jy19/LgVc1/d9XmYcRYDKmEqVQTD0KJNaU9QgJDVl0+p8xnBKnJZWMu62r71xw71brV735ju/WLy0ZpMEKK09P1CVysMEUNVpMsFAO1EoZk7T3K0jAEIckdSqUqRi5zwDyCE/PjBL/X7kKY2OyW2JNHpz2ml1xeCNDW61ewCu5xf/7J2b7m4Xl5tXX11IGsWLb0yepuk4La0vsWaQKuqKCErH3s3yrB6DwQbGWQ1mzjmrvssQNPEZ/VkErpTGiDjS/lD5ud+LQOCHzpkizLORAwKr1++GmJPJZDgcujWKJpPJaDRyOskAaqLQRCT92EajIXVZW61Wq9WSGaTdMsZIpehzccfONn6z9wa+G85p5Jm7+Zz95zHjeaDzTj1jL5/5AzIAqNOOdVsIANf9fC9pXwtmGON0kZHnmGQYT4rzGMOjcT4cVe/jcJwOx+JtzXOIRRR0pJrNqFEuydBqxc1W3GgUr2eiOInzOBLFrhWQGWwAwBjkObLiupym+WiQjapPY3LiBiEnYi2GLFEcxQ1htpMY4vcQo6OcVF4OJjJQBsrKuspAhtRZo4MaMxq+bIuzs3Cx9FHghwjNnOxTg0vkFrE/8AOj1qC11iRQFGkt+hBFJL+Sx0ksRxHVX0Wf7J9N9hI0c+95fBvPHNt/slNn7wOs9/c07B9N0LoazkVxrJM4kuLPNaiUFqZad1qXHPauMjUrbHYtsn+D9v6spQLACvLaRFBaRZECwJqkYWokcRxruwtAnnOWwX2+rX2RKKttZsnOZuoW4d3DLL7iFQOBl4DnGvkFAoFAIBAIBAKBQCDwQyQ4vYFAIBAIBAKBQCAQeGnxpjfXJtIopdxMGyJye0ej0e7ursv26NGjjz766OSk0MJ59uzZ7u7u0dGRTTJzp9NxM5aJqNfryQnMN2/evHr1qktev359eXnZJXu93uzpPW4a5OxsmMpgp0bbv+0fLmKHiGQAj93i/gYgg58B0MzYsEDg62PnW3kz33xhDjtf2HHYz/YOUgAnJ5MHD/onJ0X0wWjCdx6kzw6LmVvMfHR0JCfmra9fXFp90yUvbaxdv14EXAHYWGmvrPSSuJje3Gw2Wy3lQuljWyRRyHw8ZlGs0c5Our8HYNLvDx4/NmUU3Oh4i4ja7bZNKq1bvV7kgtlU1Ni8HC1VOjHNhQXIGXF+8KRSFMVVzxbHsQz4j7QGvPBw5c+b4+KfnS9XKoBZap1Mfcadj7+rNiWQVJhk9h1Q67fFnjrl/NbKAvr7vS3WZMiTB4vwYmAR0ytjIk5lRuvXQrKHw+HR0ZEL2orj2Bjj+hBF1Gg0YxF1pXQlqmSRnSoAG+BtCyBHGuTPi1Z+tNf35SmqdV5KQUqrGMMiDpmUkrqASRwvrlxMnTqXH5PTaLfi2txmeSGRJtR71BoE8l5JsWsa9q9DBK3lFh6P8ywt0lpTHOssK05pDJJY93oxioqpmq/VjmWIbn1kaLW3hPhhbYo2F/8qZtyxfXjEBnu0OJ7LJBu/Vul78lgFAi8eL1aW/Cimmg6He8H29/c/+ugjl/P999//h3/4h4ODA5tM0/T4+NjZj1ardePGjaVSajWKoj/7sz+7du2aTQK4fv365uamSzabTekSW/Us+W7X7NYM8SpJrYNg5jRNJ6UYQ5ZlJHRHoiiSulaYsj1OPctSyxwIfCPUgqEMy08tpHzh4JMTiIEHPvts+MGHBwD29g7ee+/9vb19uz0z2D2hk7R4F4hoYWGh0+m4A3/5P7z99i8uueT8fLS8XD3bc0212o10+SZZBTj3YimDaMLIi4KxMZODg7QM7wew/cEf9u/eAbD77NmdTz+dlOp3cx1zfVOtrKzYZNxqrd240XH6zDqiS2/RYuX0xlHkObpC6wVApKN2q53FRRfUHo7b7bYpByONZtOwSsvxLRGU9sYW1QCPmdlUTUDkDxaoElk5HS+Gi/2vEkrXXPXAt44xRjoY/pCxjvWmpNM7/RlUniGKImkxZ5888E1hJUWYWSlV+1RdY3brp2l6dHTkmrvf7z98+NCNEKIo6na7zh2N43jz8mZjvtKxr7kRWZ65YwFore0IQY5ebNKW323ROopjqTn0/XiK2ED68FEEMe4yR0f5kZBjiOOoWelRdzudV99+q7JbxiDLnA9GWse9XrkTgOx/AYAJhVqVUsTs9dQeRIpUOXWRCOR/APErvnYRKAUtrMBklPf7w9GwuGWt1XjcdK2vFOYXm8sXCqPjnScirb1eQn7CAFipTAos19qXRSAx7F3I/VR3komoOgNZ6erq5G7AwLk2pVEG7J1+X56sQOAFUxeyep5XIcuyk5MTaR62t7f394tRdW2sYB1CN6qO43hlZWVDCLFeunTp0qVqkI3nK4PjS2WWWHtj/7Z/uFPZrkSeuXYVeaxNip2BwDfPaaoVnkWs/dI7HOYHBymA/f3R06cHu7t7dnvO6Kd6lFePeqvVcj+xAuj1OhsblbJxt4uFaqkgtCN0E6ls5aFyeEaZ2WSZEYO/yWAwPDwEcLy/v/fsWSUCn0dELfcBK2k0Wr1ex11YRZifhxhiIs+9QZjveRKRUsoNf2ujYSIFeAtw1GqWqy12ZCSz1kZdM3/p9c9bG2ad0pyBbx/ZV5/bbzNzLb8zBPJvS81kBF4Mzhaf25qY2frGmCyrtHDtEhWug7JfNFwHVfjPcoTg/iqpnd8+G6cOJGRO23eJLN8b5O0o5c0yYmbht0Mp2TnrOG61W1V+Y5CmVQbrbkpqHSVxUbvntW/t/Ztukdl4NwTOc5M5nUVGmlbX1xpaKfeh1SvX1PwdJeZLAiBSU2slCWq3ft49kPiZasojBjPbveX/u+3V34HAnxrfy+41EAgEAoFAIBAIBAKBb4Lg9AYCgUAgEAgEAoFA4KWlPr35eYjjuNPpuAkTi4uLly9f7pWBGWmaDgYDF9Pb6XS63a6c3txsNmUg7tT0j3NWR6xlFnu+BHYqmpwAKU9lp4XIxYRrRarNQfrKxfiaTFfUiynJdG3IpMTW5FnTyGt/n4p3LZnZv3Vm77Eh0IxYSwZP38KMctRXwwVgJxIV4Ubebr+8qq4VJxPwjuXin0tqA+0+SxnGaEy5C5dlDAfjdFzNHN7bG/X7VfKLR0e7+4cAjgfHzVZjbr6MmyK1FDegilKRotW1pfn5ufI4rC0m3ah68tsKDVGqxBiV5dX0ZmZvUnWapQfH6biY6mayrL+1ZeczW076e1k2BhDHamVlyfUSC4uNzsp8c64IZktaTd1bQ2uxOExFiDsgETavDMQSx7mhzM2UBoaj4fHg2EXKDYeDPBuxKTKYbHQyODzuFxoEROi0Yo6rx0WpSCkNgMhGk5V3W29qgOrPoWSqQacOD7xYbLcvk2LnKdQy1w4POGw/75LfbEXNNnPuWva/tWK4vy3Tp3KMRqOdnR1n9A8PD7e2ttz0ZjtocfGZzHxqvImDnm+EYAvv3Y7Y+1z4tyRPxZjaK/4Gqtzn5DQGmUFW9bfHx4ejYbWWe358nB0XwqUAOnNzC57IAkOJmbcEEKoIGQW2WxzKl0IgxdaWk40lKbLWat9urd+gzOSHy8KPU0kn6dHRyNXB/u7owRd7g+PCgjQajfX19U6na5MmguHiYsxs5CPHAGqPBssgXgDypybm2p2c9aQ4vHuQM6WJmEDy5PaFAOwg2232bjwQ+FPDG5HXTJdE2pW5ubnr16+7nK1WK47jYamic3h4+Mknnzj15lar9frrrztB5iiKVldXF0SYYJIkMj4W/ns/XSRpJJi55q8+J0QUx7FTn7JOuCsGM08mk9Go6talriOAKIqex6R9qzBznuey6qzol8wgq07W29fBhjO5M9vgyRlnzrLMuR/GGPKlHcjXrmQ/Us7eo/2blPKshW8sspwzYZWjiBKhJ8EAuBqmMHOapaa0gUQUaa3P9pINaErDtzhVjkrKiBnGV0kkVkoUk6aCbuRNMMMqUVgMKGPF5RGTCZ5us9OEyrL8448ebz0uAukB3Pn8/oOHj10yH6f5MAXQarcvbVy61ipUoNrN+O3XVteWC/tNRPMXGu1e9RFqYS6a61aKWFojEs++SscRjsmZ3jTFyYnzeyfHg71Pbo/2K027u599+mx7p8gMNOJWHCUAFhYWfvzmX7qPX/HcXOfGjahblErpKJnrCXkqQrONWAyk/D7hZDA63K2u8uDhw48//dgJyZyMhuPjHc5KH/jQfPHpB5OjIn8U6dXVpV6vimpemF9s2o90zOQ0uwDAtp+7NAE0Q8jKZF6DMuTz6/8deCHUeqoZvRZstxBFrqObzjy95U+WmvSxDH+11Ix4jdk1WQTQliilaoJh1qAQEftaG7XmNmK9BrvX/Q3g0aNHv/71r12nsb+//9lnn7lRzdra2q9+9SunRVKolpxd6pqk1owbnM55ZtYpavcL+6W3PAEx58awNK/+uZVShf4Ws8ky2ULybzKGhxMaVl8VP/vX/37no49cMlOcCafqxs2bv5ibq+4j1tCAM8cGDFU5oKTySLEUf/IVIxgaVDa3fHn9NBMUEbtjGWSsC1qQ58iFIdMaQuAfz/YO//jhncmkyPHowd7//Y8f7j0rBrEXVlb+97/7u2vXChsRxXRhFdAEIM9MmqeuvkhzpHJ3YSunVRQWAIgQw1Q3a3xtCqVJ1dQNRWUQDFHqGqd8pYQ9osgNMdgW0HrhpGXIMs1UoggEXm6E7rzvI9WQ3kgcx+53XQBZll2/ft1Zi93d3f39fedPtlqthYWF+VKERmvdbrcb4kOg9ld6qFHr1onI2jaXdLu+FDQldSNPZS86+5deaXe/K2qV88KKVHNTxZ5TkIW0fzznaADTz6Rso6rTBwDDnAkPg5jkz7MMZmEAjeGM8srpBSlSciGBGrn/fZVQeT85vPUHcnh+jmIlLbjyTFgdhpM9BgADpFxdd2zQP4HTyExTfPF4ePdu9SPqR59s3blz1yVbmjsRA1haWnrtxqtLS8WvpnPt5Nb19VfXi/eRCN1l1eyK8V82Ql597gH8m+cJ8pNq02SCkz7cePeoP3r6YLBT+JNpmu7eu/30yZNiL7C4stFbuAAgSZY3NlYrnfbeEi6/jk4pVUWEOPakRfSsusvy8VD88jAYDA4OD1yPNMnGeTpkUxQymwyO+3sHSXHyOI563SiJxePRbSs0AXvFs696Huw/DPCe38B3gDUf9a1nYHM+f/4/ZWb7k1+T6TGA2Fltsf+dYY9q1qSW8+Tk5NGjR+5L997e3r1795zTm+f5cDh0h8y4iuX5n7Tnz3kqsiS155Xt7loGAZVbbM14OWWRDCPLkZbty3z4ZHvr08/d/qyh02Y1krx48SKMUPlihpr63leaZ6bifxX+Z8Spgyu8g2p3RyBjq6CAcxgxJ0krT45xPJ482zkYjQqT8ejh9qe37+08LczrpcPR4cFwUnr9xrAxhXfJ4Fx+Z2FjOKt+qiYC5OIj9nft6naYa07vbBvBQHVXUzntmYuTU/EPsK15zgMbCPypcHpvEggEAoFAIBAIBAKBwEtAcHoDgUAgEAgEAoFAIPDS8lWErIhIzkmuBfA0Go25uTm3t9Fo1MJ7xuPxwMUmAo1Gw82FBqC19pfzPmU601dDzt6pTeaxf7sL2RlHs6975lygF8s3cml5L3iOc56bocaXzS8hO5udvIVVT8EPUyECT61jX8X0gglV+z5H8eoXF8G5XM0iKnZVzw/LNAAAIABJREFUf9UL4BeJawu3+iHBaW6OR2lWTn4ajXB4mPf7RTLL8pPhyM3gRRk44JK9Bs03AWBxsdvtNjqd4h1st+IorgKHiKZv379XWyyXytN8PAQXE8XMeJz1+26RxvHx8WQ8dtF9WZbFSdIpI3UBtHrdZq8HIG63KUngeoZIg1RVO/UiTRfKW9wyS9NqyV9gPB5PJpNqenM6Ho/HeTm9eTQaHR8fuwiLJEmyLHVns89bkZyqmi/LjONn7AoEflicay6/QWoXmnHpml2DfywzO7EJAGmaTiYTKT8hg7BarZYcqCRJ8s1O4f7K2P6qvvWbwNUVgyejMR8XoTUM5Fkma1JHUbVqLRDZyBSvM/cbSLYXEXmxt98ksmKoZo79ecVpmp+cDEejwoikadpIEmdPW61mkmg3LI0iL/JGNsHpD+JMznh4A4HAt0JdyEomJbKPS5JExvTaUFI30n3llVfeeOMNF+EzHo8fPXrkdK2MMR9++OH7779vkwA2NjZWV1dd8uLFi5cvF6I7AKIoajQaZ1m1mg0Te+oYf+n5yWSS57krJDNLeYwoipIkaTabNglAay1jluBfjr6LEF970Vp87Oxo21p1WeBkOUqiKJpxO9M3Ox10LS8kv2KQr2mJqWCwWlLmT3PywmWVZ3jiaLpU1d8MNpQ7z4nBSislpjmc9YBZDBvnfALQpK3YBgO1teiVjdlx+OaeGbkoVZZBOK3Ic0wmVTs82e7/679/vrtffB4aj9Mvvtjp94sYMzZ8dDQZjSppjrW1tddff90lX73cfONaG0CzmayuLjSbpWabUhu9drfhvF5EQhQZsKUUj/pkgjKwDcDw2aO9e++brCj30eHhgzt3RicnxW7DajKh8nAdRddv3vxZGc8PIL78arSyDqDVbMbz81UTNrvotJC47ohA4sMCgNzzckfD4WhcBfE+uP/FJ5996pKffPLJJ5984savo8lwv7+TlTImrVZre3vb6cnPzfVarb9bWKj0q7Msm2QTAJq0jqQ0SPG+OGplrCEHftPM2BUI/LDQWgYunhLTWzM97r/PQ83i1PpqpZT7ql4752QyqWleSD+23+8fHBSSewDu379/9+5dF9Pb6XTefPNNd+b19fVbt2698sorNqmU6opved8V0/ZUVo41xLURQi2D+9sNBux22aCT0fj279/buV0F8e48fixb5OLa2oWr1Zjt0tWrmJ+vOrjYD1QlIq0rf7Qok9ems5Wxz4J8t9bk7tssACglhBGBNMXRUXWVBw92fvvb3x4fF9Y2Ur1bt24pKiQnlpfnX311cX29qEml0WwWV1KKtFbubpSyN1QkCTMtBKA9hakZqoiBQOCbof5LrzQbtT7RJbXWUw5G5atEUdTpdJyf0+/3B4PBcfmZ0Bjz5MmTvb09mwQgf5MBCnlnl1RKTatMub8xVUixx9tVc3qtm+eS9u6ceVBKRVEkf6Am/3uqPBan2fgXw7QDWauBs1rTIvWlajIks53eWp3XaqN2IduCLjldDHns9C3YkjCDfV+s5lEQeaKPxniZmWCEAgSmqm66VBJmdqpXsNcqHOb6YUTwvFx5ScD4+sxZ7jm9WcajatEE7O6O//CHJ4+2Cn3m0Wj0xRdf9Pt9mySiJG5FUfWIXr9+/bXXXnPJt97o/be35wFojXYbrj0Vo5khEr533SozqhEJgDSVTm+6v3d0714+KYaGu7u7n3/wgXu74yian5tvlL+HNJrNCysrV1591SYB4MoNrF0GAGMgf9eOm4jjqpTwKw5g432ZT8eT0aAq1eH+wdbWlks+ffp0Z2enWrJoPNg92E5L9eYkSQaDgRv+Li4u/vX//JdycJyb8nOYJs21+pFVw7PlQWqDsEDgZaXWyZ9LrZOvMb13Rv9MpUvMzNJ8MHM+pSktJ5Glabq/X6nf7+3t7e3tOae30Wisra05z3Z1dXV1dfXChQsu//eEGTWDqb21oZREGnFr4l2DsjE7jx/f+/hjmVk299zc3Pr6ukvOLy1Rs1n1fXpqFpbsGcnONaoyfDWPF1PGmP3fcrWGnEGYTiDmBuHg4PjevfvOvF5YeuWnb/63uW7R3AsL7eXl9txccQFS1RQlgMgqNBe7Tlvf8GzqNuJLHRwIBL48X8JQBQKBQCAQCAQCgUAg8MMiOL2BQCAQCAQCgUAgEHhpqU9v/gqcNWHGMr13essMajOdpic+Bc4i1NX3HYacycUMGzZaJnl6opc3E2pq9uyXeK9m4V+WbclmQOLKRFTNM/uGyvMcTF3JztAr/i5SVSZv7zlRVx4M8tosEAi8FBR9xJcZnATO5AdYjSQMangOAoGXlcrpJSKllPSUZJzbDKIo6na77kClVBRFLuSj3W6/+eab165ds0ljzLNnz5yuFYDDw0OZ/Pjjj+/eveuS8/Pz6+vr8myrq6su2lZr3Ww2bUjPdDclt2itpUb0ZDKJ49gF/Git8zyv5F4nk1rUCnwfkqbEnL4P1EJz9ZTMlfsbKCKg7N+1IO3arY1Go6GI6pTBPwDiOG632+5CtXEDEVlVMJu0xZOFTNPUhVEBaLVatWqvYsVZaeGeqAwkonaBHKgeV0WkSN5FzshAIi7XD70hk/uunef4ESUxVQ8PsVKGAICJc6oua42mOLHJYEQh+/vYq4LI8OTxwZ3Pn7rk4eHR48dPsqw44Oj45NGDpycnReXEcfyLzdfarUJaI9Lq9VcX1y4UakwA1q+sXbi04JLL8/kSdgGQQTSqFDLIGDUawoW6MTAeoYx3BdD/4kn/4Y5LnvQP+7u7Ljkej4+PJy7AOYpWf/bza+6B0c2kffli1C1EL7XWSysrLBRfsvm5LCEAmuJYR+5JyVUyjlVeJhmcGWNcjBnQSihB1aCx7nQ6VYtcxdV2u+rK3rhx9e03Xzflk5Mbk0p9ZqXiOHaPWbPZ/NGtn7Y7azYJIEm6OmoBAFEqniIGWIiIE6DBhCposIaidMZeIAYqqbxA4AdNzT6KPacgjYjNXLMa7u/pZA1jjDNk0voQUZIkUpijZtd6vZ4TpgJgjNFauyHB/Pz8lStXXOR/p9OZm6u07gDkX+nrl28fToEwS8uYjeHSQAAgRaT1madkEHuW7qwzU87xxLCrRsWEyHW3kYqv3Hh9Lqk6q6TRjJOqYnsbq70N0X92OtCVeJWBSbPMGVQiUv4ggaHklEOG97WXDBUKlkRK6EYaw9nYmFIkgwhxorWuThspsFg2RCmvvShG3K0yX76+8b/83f82HBbWdnFu+Y1rP+q2CrnWZjNa22h1nXgrwYlpKEVRJJ4rUgRVVTSDjax1shHMZ5NhlskgwFsJxYfANSHNEjK10ZIPAdGZT1Eg8HJRXxzIvZHWJklLxkLLSqK1bpVj8WmazebVq1ddkpkPDw+lE/Xuu+9ub2+75NOnT6W8xMrKyvHxsTNXS0tL7XbbSclbh8rtPbV4lprSRhzH0tNTShljnMGzMle1s8mqqJ3te8K0HtWMQtphh70pWxv1HCVpmjqlIsDzlgG0Wi3p9E6jlJLqzeRLTGdZJteNyPNcnkoOaDSTJ5VsaoMOBgtrobWKZJEY5HnFHswwKYRUFTNLH1jrGOQbG7vTwKTeWUl7AozZBKhuDsNn2H1YJe99Mvivf3/kktvb2x9//LH78qI1N5JcqaIYydzcjVvrly5dKpKx+ut31l6/Wo3D9JxSwoojP0TWBwD2ygCT46SPUokKzDg+llJVg0/u7v7xC5fc29t7+rTyzLnZy7srKJc8WllZvP7aT52Wu+o045sbeqH0cpk5TaWkWNY2k8gAiCMdNRpUVpZBNIJy7WcYYzZ5WbMEaB1F4sHQSUOj0uJcjbHcq8ZkaZq+9eM33AurVBRH1bWYWWraQSlq9yiWS240lYoBGN9n5fJ/FgIzMoUZg4mxhhBLqdMCGmGoEXgJkMbRJmfYYqCwPi5Zyzz72BrMbK0e+ZrDAKIomnEqOZAA0Gg0FhYWnLlpNpsLCwvOcimlpPIzA+ZMcwLMfKvVzL1n+aUFxnDqmTki+SlYdE8AAGKShqy210E569RUuk+a5MBQU3RxY2Ne1FW312uJJBa6WKiW86hhjEnzXDq9URTJIhNIVgnbbTJtAICIVTU+BRtk4zzPXCdPkVZSzVJ5rnQdFUH6qhfWl3/6zi/Ssm7nO51X1zfajcKmaI12W4hXEdwXASKSnjYAZv87KbuPtyDA09uchjJAiFvWiWaZDAbY9+wrDEgOAmpo4OxPJ4HAy8XZvUIgEAgEAoFAIBAIBAI/cILTGwgEAoFAIBAIBAKBl5bg9AYCgUAgEAgEAoFA4KXlTPVmmtK1AjxpqxnRMrVd8ihmbjQaMoL0xo0bCwuVAE+/39/b23PJLMuGw6Erxng8Pjo6cofHcTw3N2fFKlZWVuTa8dpfiV4pFcexK5gNLHEZ7B/uKsxcC4glIlkVtWr5rqgVwzaZTIqddWwElD1DLedgMJBB19vb21tbWy65t7f38OFD16bz8/NXr16Vgh/Xrl3rltpFWZbJmF77t2z9RqMhA6uSJJE3ZZvbGEOgJjdjrhrUGONELAA02lGjIx7mWoyxMcj96Ns6foiwUhB1kudsROCx0kpHGkXETnVclpntx4fHx0W4LIPvff7s6ZPD8jg8eTJ88qSq2HSs07QKFb5wYelv/uZ/dMlWC6sXjYsjazYbV65enp8vQqe0VhcvNVWvKiQpeAGkgwGOn6IMyXaB05ylo50n+aCQjmPm4eHh5OTEHZfvZdlJFac6Nz+/slaJlPDCCl+6Dl1UdbvT6ayvx2UpqRGpXg8NIfoVx04fBUDUzCgp4qZkLHdGBlHTVbki0ko5CRYichG5p6KVIqlYE0Vxo+Gak0hrnbiYJWbOJxMnc0VKUbtJQpcljpUtyanvj9tIAMBVrNop2au9AAwbI+LGFRIv6jwQeImYYS5rRoeIpAGabbZQ9PxeT24Nij2PO5yZ9/f3T0TPtr+/f3hY9carq6uXL192SSJaWlpyRY2iqNlsykIaY7yb8m3EC4KUimNXDKqZucIgyS1+zaeZVFjYPzjoHx4CMFmej0auo06azQtra81SqIWNSXo9LUKa40YDYnCFJJlxXQK01q4nVEppT5LynChmosKY+48JSCFpaBOXVUGkRbgsM2/vHPb7A7dFargAiFutRCgsNhrNK1dW3HPVipNeO0qqwF2crXlSh0QYtfwbp7XPi3+CAoE/cc50elFaEZeUnT75TqDXG/lJZq5Zi0ajIYWver3ejRs3XPLw8FA6vQ8ePPj973/vxsfj8bjf7zu5pjiO5+fnrTjwj370IynVGMdxsyn0Bn0hRyKKoshtsYoXrpDMTFP6zDUrLpOYqoEXRq0VZJlnF4mEh1zLeXx8XGuCzz//3CU///zz3/3ud0706+LFiz/5yU+c43rx4sX5+XnnA1un19VznufyWwOARqPR6VQSxHEcywHNaDTa29vLskxB9ajXFNpFWZZJ1a65i73G/NlauMzIMvCZmkPs6ziQUtLKmZTTceWhRUlknV4AzJUA1mSSP/hib2vroNzF/+//89EfP3hQ7AZ2d3d3hRLypfXrN6//zCVXV9d//vM3m83iHufncfMGnF1WCo2mczYBeAUGgBFQyWADhwPeeQIgHQ73trbcV4x8PO7f/3x0ULQvM+/t7UmhssXexoKQMl6+ePHmj37kkljdxBs/RVy6tXZI4p4fDbRMrVORxYyTcRynANIsHY1HzglkzayNfAwjpd1zQOfNSFFaR0KbnbRW4mUHKVDsCsJ5no1G7B4eRardpOSUnpAAQuW2znqdAAbX/F4GG/GdJec8yysRmkjlp1wyEHgpqJnL2udyaXHs3zOsVc3UGiE5CUBrLS27wxizt7f37Nkzt+Xzzz9/8KDqjd96662lpSWXbDQaS0tLZxWDmbMsq+6CiGlqybhvH1JqphSSVT4W1SULyeAs5XGlk7S3tWUrJM/yyXjs7q7b7TaTJCp/iiCl4m63KTrYOtr35IzQxAJIIYq0ExUmIkXK1TODzEy/V00pRRXbFSWNMz1RZmxv7z94UC1DkCSJXL9jfnnpQuw5vcvL4qurQZzOLNZMqiqfOgMX/ype+EMUCPxJM3swGQgEAoFAIBAIBAKBwA+Y4PQGAoFAIBAIBAKBQOClJTi9gUAgEAgEAoFAIBB4aYlqQaFiF2gqcNdmqMXYzIbOE8SCf8I4jnu9aqHz9fX1PM9d9OZkMjk+PnZJZs7z3B7+9OnT7e1td+Dc3Nzy8rJLLi4uXr582QX/jMdjZpZBrbacLpnnuRTaQamWYZF6UZiqtxeJvHStnqdLVYuzEnu8ZL/ff/z4sUs+e/bs6KjQPQKwvLz8t3/7ty5p6801aJqmR0dHLmbbqig5NRGrQSJjegHIAK2HDx/KKKzd3d07d+6kaapBS6numOqOWjE3oqrMr9680b71uktSp60XFqsQSwPkSS2WpoJAIJYBmZlCXjWx6ZvsqHoY9o929w72AUwmk53dZ8NxoR+VpfnTR/2jfilkxWgejN6Yr+LNkguvxMl1l1xcXV+78kqVXJrf3NQuPK2VjNqT3bhfhmBxnk1OMlPqUTGfDCaTSVV16SDNRlUhJ/3t8f4WgCxLj46O0rKSCUzN5WhtscxIl642qqsC7bmlVtftxfyFZayvu6SZW8rnNcpXgQFW4l0moriKIrMBZfIpVBSTIQCKo1hp99Cx0gbklMZ4SnMsgneeWkuyQi6CcokUK6qOIAKMSzGYE+UisYkAfXqwNwFScWX68SEo//68V47QgKspQMFEVF1I0dkh6IHAD4raUKGGtK1ui/y7Zqpm2CbLqXqNeZ73+/1x2Runafruu+/euXPH5RyPx5NJFdGaZVnNEsm9VnNxhnk1dE7Ip3dLAtExfSXqfR9Xm+yfMgPDRaay4f7+wclB3+384u69zz77DIBWOoljVYoFEoOV1s1SeIVgNDGqvqveIMzkGwGneQGACKT83ptJjkQM51yF/EKpKuLX7s4Mo3iKvJojqm42y/PdZ/snJ6V0hTHvvff+x7fvusyX1tfXhCJj3E5iKXxJSMdV960JkSwzw7BofIbCec1f4hmIIuEdKRPECjRD6sFKj3ytxycQ+BMncu7KtO2xG6f/tq7L9PazqBk856ZajC9zlSSJlPNdXl5+7bXXXDJN08Fg4K4+HA4fPHhgZXh++9vf/vu//7vLeenSpevXKwfj6tWrnU7HSVtZR8sVzCr7uaRSKsuy0ajSBWLmU9Uyvluma356i4N9NZEZ7OzsfPrppy5Zkxb70Y9+9Dd/8zeuNh48ePAv//Iv/X5hSsfj8e7urrtQnuf7+/tOJ8m2tZO5AkBE8uPCJ5988k//9E8u+ejRo/fee288HkfMl46P54UIx8aSvjBXPVfZX/+vmyd/55LRxoZ+/fXKiHEbvAgh/lwn12TKszFwwKhUP5E/PU6fVQ/DvY/v/td//SeAw8Hh+3fe3+0X2lQE1eRGhKJmiPCzn99667VKIPTWrVu3bt1yyWi5E12ad0lo6zGWydGAdj/BuJAbzSeT4dbj1NVkzk8eH/YPKi3oo/7R4KQSqzwa8sEJA7BCYu7ZjlvN1Z/c6q2u2KTS6tUfv7m6uekOxEKCOU/yrVDPBAAY0JiUsP5sYCoFY1aUx8Tl4AmItDwaUZ7oLAGg4ethkmHKgcqHR9V4AJDXVUXYE0aOyERCyArk+6LsnVkBkUI5yYUBQu3SBQSKhdcKQF4UIOLYnQe1EgPsP29E0KIqzn5TA4EfHjNMD6b2zs7MLD2MU5zeU/Ua0zTd2tpy+szD4fDXv/717373O5fz2rVrUq55MplIS5TnuVwnIo5jrbU7Ofl+OwMg6ejVIZzumhCgzthVUb9dAft7mWGM74P6p+dK14qNefZke/vhI7fzj7//w/vvvw+g2+msXVx1Ok9smFUUd4rfHhg8MeOMRQ/JXk9IxitVHMVaiOGT/PIHMHNuqhEgM/LcU0jVcRyJ9s2MyVIDQCmKIi0fHBK1nKbp3XsPtrYK5ao8z3/9T//Xf/+Pd13md9555+c//7lLdhfaTTGgMwaTUVWRcYSkBeW+7TLyDMYVEiCGW1xgBgTAf9iZvCbk4l8JKSrHD6ehUNrWMzm1UKduDAT+JDnbDfh+MG0s5QdXKrFJ6dTVfOnA8zN7zGGbwI0Azh2+1DfNhH3P3H5eEVQfm40BiyWLuGb7rbGvyuZ7KzWYMG3AZH7PTtlSMgA2bHJj8vKzUXFV+Ruid167Ek+VVP6naztccRsI4OrCBF+Zkw3YyNWAuJ4sKt+2pmuI8nTVZUgpb+kLpTw/lWoipVMV9c1QP209/cOH/IcoEAh849Qsl7QmNWM0bZumt/wA+JJlrtWPTbK1LJVxOeecNWvK0tLi6/Xd51757LM7kwd7a6be+l77nnOhWXyNQwOBwHeM5/Qy82wfxiL9zFORfQ2m8teOnT5VrV8We4oSyl9om82mvdzi4qKcvrK4uCgV6plZrlY6mUyOjo7cxNqDg4PJZOKKbc5zmGsd6LkV8sKolWpGTUqmK1m2oNZaLjGVJIlca9eu/OR++NVa53nuKjbPcyJys8is5yp/2u33+zs71boCJycnstU6nc7KykqapirP53e3u4OqnEnsGdp0MnG/NgOIO510d9c1CnOL89x72r1bJs5icDVnl/uMkyrD0bPjwbPqR9TD/qGdRJelWaSiRlz8XKCgmroZk/ult1oJ2WKfOpdUOtVJVRWsyulLltEudp9hUvxwwWk6OT7Oy5WHjGFjjPzxIUkSz8bHEZoRAKV13GqRa69mo7O42Jqbs0lSSsd+VdaeIkDu5alhhz8AYhK/sVLx7zTEEAsAK3sat2n6fapfdzYsFhAqTypv6pxT2dJQ4aiekzkQCEhm2JpzmT52ui+oYYwhoizLjo+P3S+9o9HILpjnsrVarbmy37PJ2rCk9j3d7QIKm+jZU61r3eaLgGvdbc3dlJ2cTcpOlsm/ryRJ7HqBnU6n2+s1Ssvb7nSUv14jEbnJz5huI8LMZdTPgeRitqfVqC0zEdUaJc/dj69I03wymbjZecYYpZUct7Tbbbk4YqORyJMRQamqGP7cxIKv0NpTz/K5WIsTCAS+LbyoFWaueU2n2htrHupbS4wxY7Hmm1Kq0WjU5iPJ09YuYYyRoTW2SLJUMg4niqIrV67Yay0sLPzkJz9xuwaDwf7+vkvmeW5n8liGw+HTp09d/M/u7u6TJ09cMkkSb1G+qV4+yzKXGUAcx3Ki1HeFdSld8tS2c8hGTNNUrnk7Ho/l1O5Op3Px4kWX3NjYmJubc60wPz+/vLzsPNUkSYbDoSsGEcnKyfN8MplIL/c//uM/3N8AGo3GuoggXVtbe+uttwDweJS9+//lD6rlgk02NFnVBE+ePpWT21vz870PP3Q1YPJmls5x5dayYflhW+dZj03Vgmacm7Sqya1HB9tPKo/65OTETtg2bBZaC3PNYiCllOp1eo2kOA8R9bpdWbGPHj1yYzIAJspMPHYPFjNnRkwhm+zR0QdIi+tqpdpJEpfvEZFqRAuNRmXU5+bm5PcC3b2g59cAUKNBFy5Q2QQU6WSxF7XKmyVqNxreosTMRpRZkT+eIWIyLv65dFWLmyAirTxxvLOeQWOQToR911DIUYYHExGpam6hRQ73DFdzqgHYx1kkwWJ4yDAyIA2AhpZ+L7v/FMnqWIKSu2oRvPbmJWfdr2X23kDgpeF5BhIOabYstfwzDjflsr1HR0cffPCBW1LeRtZIu3z9+vU///M/d8lr167JkCWlFInPxHJuMwBjzHA4dB9zSamk1ZJSCC8IY5DmnnNW87253iMJMwflr2m8vr5u73GuN3fl8mVXV61eryv8QyKKolgrf1agHBFR0RcWqbMbaxoiyCOIqPZFUmtSRSbvRvPcDI7HWVY8OYPB4PHjJ24dZmO41Wxdu3bN5b958+abb77pkhdXF2TryeEAADsBSz6VtUf4rHusnQdTxS42ncHzBgoHAoGvSv2XXpk868XGzF3MnOe5G+srpWx4jMsw257VPDd7NpdUSklrFEVRu922yWazKX2zx48fS+d5MBjs7Oy4Ux0fHz969Mi5doeHh4PBQP4+aWqfdf2akT9mArBfiGfUyQujVubZVW2T9puCrPPa3cVxvFCuUw+g2+3KrxiNRqPZbLr8Wussy1wxlFLdbtc5Y/bBcLpWALa2tm7fvu2SGxsbN2/edMl2u724uKiUMqPBwdOPh4Mtt+voKD85qQp5MhhsbVV7O/3+qN9395tnjXTc4zIext6yKyRzlKeLbCphodonjy8e7D3aqpxVKr8XKK2a7aYT7dBaz8/Nu7hxAEniaZ8cHx8PBtUvxpk5SU3lS9tqr/Jn++r4U+TFL8NRFC0vL7uTK6WX5rvNdvX+djqdbrfrkq0L6+3VqwDQauHSJbhv3kRoKETCRRyPIZqbAW+atPwAbrcQCX+SfecT5CJ6Z8IMk1UnJgZiliafxU+1Nikvw6iaD7CPci2zdyojBoPP8zOvPZyLo87JHwgEvjL2RZav87SdmmFbuRwhjMfjnZ2dR4+KmFVjzGg0kp/I5+fnL126JJPy2z0LYUsAtc/6zJxlmZujpJSKGg3vx9AXAzPEcKjwqGTlyO7KVmlVsaz8nys6nc6FCxcAzM/NXVy92GwUxiVutWLx/RS2NmbdLdclF74MRJjRxxJV3zO9G2VO03wyKWpjNEoHgxM324sZURTJccvS0pK9WUu32zz7hxvYwFvfwmBGISVTR/n4W2Y82IFA4Nvg7Pc+EAgEAoFAIBAIBAKBHzjB6Q0EAoFAIBAIBAKBwEvLN6/ebCcjuWkbs+cmnYrMz+fN0XXULqS1llObrNiSm9uTJEkcx262s93rwl3sAn3e/Emf2rXOKtILplbg56w3y4zMNBXCPX0hmZ/FZGm73e2dXQaUk+FdMoqlG2WGAAAgAElEQVSiKIqUUrmOAJWLdXqhIl0qSAHQcRLF1YwsFcVKR9VUIqOY2KleMEyWVxOJmTk3E3ZLFgEGphJhBnSimh1xcqWq6c2thqqmN6tGO04a1ZJFSZPihqxJRUKumYyGqR5RZRTJGb9ZorhDeZGOoihutWMxvTlqtbSYSq2aTRe4CwBJDFuwSHurySqARJIBRUUMEwBgqokI3pSs+n6FarZzmfXMF4fLfQxAoarjU9Z/qG0geVryp9OdNmNZ5ic//3RmD6ru6JycYHdDpzJ9uF/qQCDwJZm2y9asKKWiKHKhNMaYdrstY6OmtUWmDdn0yR3SzNVM3guEQEL3iZmN8bpkv0OS6+ECRXSYS0ZxbKcxR3GsdOTEq5RdVEAc6y1iP83Mnc9B1VdP12rVifu9JwMgcvaUFOlIR2Lw0Gg2WPyokySxXCuBaqebgmbv/tr3/FWYXSJgZo7vosCBwPePupCV2HUmzCxz1gyAUqrRaLgMNOUyzaYmIFG7FlAPtnFXT5JEduhra2syunI0GvX7feeMHR0dLS4uDkst3H6/PxqNVldXbbLVanU6HRl6OplMakG8UhhQ+cupf1fwlOqyrBCcZlHsxkioMaP8IuCS7XZbil42m005krBb3HXzPB8Oh/JrQq/XkzG9tSKxH7O9tLRklassVl5SKTU6OnqsFx72q1Ktrt68uLjokgtLi0tLSy5pjZrjeDDq7+ynqYv/GW0/2x6PnA4WMVpcfgAiULfXdQFOAK78+fVfrlcaGFEcJ3ECgLSKGw0qV18lokis9gyAVQpV3V3tYWakOVVaXHa3S0Ua7eZfupVdlVJJs+lqj0g12nORELKKk0YkhayaXbTmAEBrNJuVVBUBWnEl+8TUSMBiWUUlZa1sPVZ1qYGmdwvlf0oU5VSqRjGQ55lhESFMyGw1K4KuxiAKpJSicoxCIGItr0u+X0u+k8xERuznYqUoUTCO3CCGbJ9R7YMCKfGNg5kVG9iLeotxekcxgziXFyG/lERaqpoav32JFM2MkwsEfijUlDhg34WzkzWbLjtGm1Pmrx2bpqlUkYyiyFqrbrd769at+fli5XMiarfbNSEruU5vkiRyHQEimrZN7m9r8d3ZiEjrqFqvfJqz3URCrcv8MpC3anqe5+OjI69XEWdWRHGS6HK1WQIWlpeazapCLhqTGQNrZ7s9d/uKKNKEtKhkJoyiKBOLjGsU4lIWAmTHJ1sTgCbyRplEWpGrAmbUVCMYlJWrAAIwRFweLfvXPFJxr6HdsoVNuvLGa+3lYkhAwFy7004qI762dvHihUqdS0PllZ4GdAQtFzEgQ1F2ZqAygxDbJXMZEPYN8COsi6TbwpBiMURUHzqygvyyX8O3L1MYUCo+JEsU2AvS9vCKGAi85FTdUc0OzaaWuWaipMv0ZZlte6Zxl7a/CrrtWut2u+2S4/F4YWFBOr3GGOn0PnnyxBW70WgkSSJ1sGrKRtP+5PeEWl095+eG2r3U7i5JEunhx3FcG9/Ecezc2jRNj46OXNXlec7Mrl2IqDaCYd9R73Q6m5ubLhlFUbPZJKJBs5mr9t6wKtV6Z3Vp45pLLi3PL69UqhVy9QIARPvD/e2JKUp1zMdbR0+tArPdD135J0S00lqZa1d+/vL1H7/9znWXTJLEfk8hpXSSuNWAUEqgueQ4PUmz6imqDw3JsKq+pNQqJ2m055dWY2G2oVRlUYnQaCASL5rWcjwE0rB6m2yFmaoHg0kJI0cgJU0emTNtPQDFrHwlZHEqAMzI3fHMnJuU5erKkR0qFB/m3XZipfJEaGARFcsWV9TMsnyOctSGkTMPnEoqQFYBs2EmAAQmkjfrd3r2dfPeOPJOb89RYViMjwgAfR/7kEDgy2KMkd8u60P5mdRsFjPPPry2dAIRWfPUbDbX19edX6q13tzcXF5edjml1wogTVPp9Gp/ahiAmvMmtfEBgOudjsdX2/U8iE7epGk6Gnli+6LDUUpFwigQodNpt4TTqxoNZW+KrC9dHmsMRiNkReWwopTVRJw5Iq/nUiAl7oqBaikhAEAkvv0RvOEiCMavkjw38nBDZN1Av28FFOlmZUI4xoX1i3E55COiq6urK/PVkEBr72NuNkRarR4Ijj3rCsVADu+Lp4AIRsN+oq1ZAEyt3iQKbfUX3UPFzPUREVPxwfYsZu1kUIa6dbYk4LMndfLs0wYCLxXP5RQFAoFAIBAIBAKBQCDwQyQ4vYFAIBAIBAKBQCAQeGkJTm8gEAgEAoFAIBAIBF5avIn+MwJpJLVYl1NxGc49Zy3QkaaEr2acgYUMUu1A5esAK6WiKHKlarfbzWbThfSMRqPl5WW3snkURa+99trKyopNAlhYWJBhrkRUK/OMQn6ryIaYrgH3N6ZaTSaVUjJzlmUyIHZvb0/eHRFtbm668CdjzNHR0WAwcHt7vZ7Lr7W2GWwyz/M4jheFANU777zzq1/9yiWvXbsm9+Z5nqYpM08mk36/v7u763Z1u91XX33VJZOGjhvVLezs7Hz44YeujY6Ojx49feSam4gajYbTOUuSxubVq3Nl/A8ptf7KKwsiGOzSK6/OXbrkkjqOtX20iFQUVZFAzCrPWcZ+c8dwFbXL5EfLUs5C5qqmtKl1olvdIi4XAPkSGUSI4mnJqVOw22UL1iJ4asedcZrT8YNaGczKODFnANpX9sqVyUuljQyZy6igNZGqhUPVwmW/VMF8hGwnmJE7+ROAwJoYMiatjDMnxV866FaWmb3KtAJaIv017icQ+D5Ri8KdbRCt1f7/2Xv3ZzmOK7/zezLr0a/7vgAucPHkQ6RFkdJIljyhcNi71v4y3vll/I96dyMcu/auHd4YhxyzMxTloUiRwzcJ4XkB3Hc/qirP/lDdWSezuvsCICgJl+cjAurTmZWVldXIzFOV55vRyLUk/2QykcG39+/fv3v3rjdXV1e3traIiJm3t7d9EG89Ekk1inow8qYxRobptisQfSNHzLoz+lZd0nPhKudEPPPD+/d/94//6KVJIom+brf7w7feunjx4uwLUJJMg3hrmOvSyFrKsqZHIkKWwbcVkbVGxuWe+apE9vkUdeQRrSY0JpApvL/38OGTJwDG4/HhwaGf7w0Gg1deeX2wslKb7Mzm+tpK38f0op93W7e0wSTImp8GyCAYBBYfGBEOgKBIyKpFNN2NJmmKonzXLI5uX0o0YnG4sVDkXLWHE4lzTgoj21C9efmxQKOGF6kxRY5ckiRSxIKZNzY2fD3Lstzd3fXyS8aYtbU1OV5GtHuuM+v5XSDbGQC1nhdEyPz1JdTfRMJjkVLIwcGBnHOsr68bsfMBM5+ennq3Ns/ztbU1708ys3POu8TOuSRJpBb0W2+9JZ3ebre7MhvGAAyHw9Fo5JwriuL4+Pjg4EDmlFKcRTUqysZRPz4+/uijj/wAeTI8efj4of+Z9fv969eve52z/mDwox+9fWV3tzaNMbs/+MHmzk5tAkDaQSIEpaQmhmxwZpRlM1cAUuMgJT5jrakK1PzywSyPBSwoCyYY0W9MiG+dwXf645TDPrHj0OklK3dpYpQODMDBVVz5nImfRjZZw4lSlPosUOvIqpm+ggA2gdaq/9dt6j/PedoWNL3ImaUo54Tl404Eh04vtaQrI4qi8H4dgL29va+++sqbGxsbzjkiyvP8ypUrcviI8ONdTfu87fHUf+YZUxMcP6H7o8CuqoS+5uO9vffff98/rCeg2cMHWFtbu3z58pbf1IAoyTIjZkFuNOJ6ZGemNGu6JCIITS8iGPMMQvPRXIiAQKgqguOuMHDcgSdP9r/48isAR0dHd+7c8ZO0ixcvbW1f6XSnt5vIrK6uCG1EmCIQdYrGQGNBYkiHA8RQ/Ey9s/zV1E+1l4y3LpR8i7TTFEX5rvkTdNyKoiiKoiiKoiiK8sdBnV5FURRFURRFURTl3KJOr6IoiqIoiqIoinJukZEbcSBC+5uaKHaUoiAMgIhkxI5MamOMkYEN7dKWY62tz/VMR0WZrbXdbtfLWhDR8liLdguIxD8esp3btGslvzHG8CzcOsq5tra2OwtwBXDv3r0PP/zQm/v7+wcHBz4a6uTk5OHDh1IjanV1dX19KgpVVdXjx499RJZzrixLH5YDoCxLGeJSlqWMHy7Lsg6wLJ17Qu6u2Cz+v3z0wX0RwMNwLCJ4jo6OygsXfSzRRqdzY33V17nX6127es3H9GZ5fvPWrfX1qYAWGepsb0PGhpkUVvweiJrQ3KiRExvE5cqAXgAmEqNizFSdAADRPvcEJJDRRTT9MzOXimY8d8jZ4iKBOlWWzFIkisCGLAu5LiKSJVoYggPAYEfOX66BpajCRDISrNYZWcLyq5XXxAQplUJAFJ5nLNWKY2HdWxCTCeMAo9tBNmqrIHnJvVOUlwp2zlVNV0amJUonfu0EsiYU4GAZ9slcllIX4JvPv7x9+7Y333///d/+9rfefOfH71y5eMlYS5Wj0qGYjQIEGBP2TtG/v2VdCgOOhd4doq6g9Y831iAIMvD0TzulxWSMshkBkVg59Bzcv/uH3//eayXu7e31JkM7G0Q63e7FizudzlSLpNPrba6u2mByZWSnStYizwGwtUUi1aNCCAYQ+ldwFTvRNtaW1siIWMj2ISZ2iWydoMsECNafmxmPHk2Oj5uh/Df/7Zv/7933AfR6ve3tncHscvq8nrk89XebKLVIxCWQ4WCwpfCmEZz8TUb6GMaAEvmjjJnlpuAndsaYDEKSJHLqGAfD01kj2RLIACnmB18vm822f8uKco4J/jG03aS5UEsBos1TFgXEilPPBBE9/Yki5LGR430m3+a8LxZZjeW1ilKlLEd01MbGxo0bN7z59ddf/+Y3v/HmRx999N577/lD+v3+pUuXvBRWnufr6+uXL1+uzclkcnx8fHx8XJu1JJV0eouikDJmS5zePbhvTDOv2vvH3/ynjz/wprVW3sHd3d0333zT/662r137F//iX/T7/drs9Xq7u7teqMwYk+f5M/0AzjkLf0RAPUuRVsjyf8k2GpNbhweE51mSd/lJ5yDnKUBUKUP2aUs0y2oVQdM/inLecFVVFYEaZfBPKnQ4CJTIZ4hcy9vNHAzmqiydeBL6xcefvPvuu9789a9//bd/+7ferEaT/+Vf/88GxlSMsmJRDcoSUFMPCkc6BqRrjSiVuWSWGYwx3qEhgLn1HC5y5gLJePgnfGeIXhYjDKe6jwCQ55ipQgJ4fOer3/2//6USI+aAeTArbqObv/Pqq+sbU+Uqk2Wd9XXp9IKMfMpKNqUkBVAaTBK4BdUioMOQbmtRubJsCrKYJKZRkQQgny84TirHLFxq+aCQQIkzZpZalvzgm/GdO42O5n/7T5//X//n3wN4/fXX/+2//cna7Hn6AJ286qbl7I4QIqcXBrALvVYHko80iIKdEAACBeqeMYT6EmmBlzkXwhlvU3yxzwWFjyZCnr9YRTlXPOXkTlEURVEURVEURVFePtTpVRRFURRFURRFUc4t6vQqiqIoiqIoiqIo55alAQbKnzeRilW07/ny0KEl9Pv97e1tb964ceNHP/qRN40xMqJ7MBhcunTJa4Btbm4OBoPOLAyJwvBvZq6qSgbxejGtmii4uiiKOva4ziZjvzc3N7e2tqQp63z58uXXXnvNl7y1tbWzs5PneW1mWZZlma9YFO2MMOAZ8zIoiqIoNUTGiH6eRPhr/YX4DCAMf2XIzAxMiqIYN1Gdd+/e/eSTT7yZpulPfvITb7766itra2tJTZYFoZntTnuJ7FxEnTjLPqf/56A0diIsGQAZGdcqB5SqLGVOEyobwVrMBtOpKTIP+v1r1675gGdmds75kger69319XQmwUhJQlEE6cIQ1xjH4tqBsmrOUmOtVGOKR8/Sicjq6fi54P2KA3Mj/ugcn5yc7u8f+fS1tbU333wTwM2b1y9f3lxdnV7d2nra7TQBy7RcQQoAwvkSY87PUlGU8446vS8xkW8W+ZORd/r0bGxseGVjAMzsJaAAnJycPH782M2GqZWVld3dXe/0rq6ubmxsDAaD2kySJKpDpN5cVZUc8pMk8UUBmEwmtSfvnIv84atXr77++uvefOutt95++21vbm9vX79+3c9U6mPlxMWYQE8kmtPUZ/Smtfb5WlJRFOXcY6yVTu8cpMfEPP1vCsGQX3TGVTUcDocnjZjTxx9//Otf/9qbP/nJT/76r//am2+//fbOzo4xhoyxeU6B09t8BGbnbcwz/F5CnCHQf2aGkEJi57yoMlp+IGYeFztXjsfsn00T5d1u4PSmaaj4LjxCYHNj85133vEnqoUh/Rwg6fZXr1xOurPB2hiaPedtkDciruMUZriquThiRlEa1zxPz/M0y+TUkWRZZVWOi+aZhbWmk1oSimISdqgKqmbTlqLgJ08O7t174DNcunTpX/2rbQCXL2+9+ea1Xm/6PL3bx8qKia5P3t7WzQ8mS8yBD0yE1hGKopxD1Ok9P0TPYiPz6aHwnWrkiI7HY+kx1g6h9wmNMTJ17jvS566YJPKBsyzzr5cBdDqdPM+XVCPyeNuVVBRFUb4Tlg4BHI4RkaQ/EcnxKEkTIqoHne+0E5ceb6zb/EwI74vQagpqvbIUGUy9cmo2OtcPZ31p1loyhhZtp/csRNfHrWqGxCeKZLHPIMzLzPKJszEmTQ2mD9CNf8NcLyaQl7i0hoqiKIB/vKooiqIoiqIoiqIo5w91ehVFURRFURRFUZRziy5vfomJ1nMZY+SqsCBSaB5ENHelcbRyeDAYXLx4UZqdTscvQKpVr9J0upN7t9uNtl+XsTT1hyVLi9sr1Pzh7Vptbm56c2NjY322bT2AXq8XrbL2SWea9TfLa6UoiqLMWLag1VWuEOpNxpjEWtmpMrNY5MppnjE3ohKXd3dff+MH3nzltdduvHLLm9sXL5o0obq3D9SjwFG3TfEK2NAKcvP8b5rPlRjXUK9KFtpOAFsh5gRmAgMgOAtHPFu+yzx6tMdls3i7KkonhDm6g0F3ZSqQAYCS3K5t+Msg51CUvmom76Dbcfl0LAYREgsjgmkNYMR10OwSiax4AcIA2ImLY0MVmSaml0EyGQxgdlIAbBJxcy0yuGYhsnMoiiZOmQADMrOB3YI2t/tXhxtTG5iMuSgcgK2t7sq66c5imLIctjV7bSpFAIPkL4DDWwgKF6nrEK8o3wta3Yby8hD5ZtZa6eie6fQC8925NE2le3nlypULFy54czwen5yc+PE+TdPBYCBjemXAFTNLTen6g6xYpBHVrk/t9DJzkiRefhnAzs7Oa6+95s1XX331lVde8aa1tu17+8/ts7Td4KdpPUVRFAXMLFSdou51MhkfHx15NynLspXVVds4Y8xVJQ/vrw56q42n99O//EXSa3r+d9758U//4i+8meVZ0s1RO1UUOr2hm8MMF/o5Qe4QBnE4KARFgU8dFyL0NE9sIpzerJpY4cqaZohxlgvm2YBYFI8//vDw7j2fczxyk0lzqitvvHH1rR960+Qr+fWNpmKOuWrqAEuum1WJr3Z9fc1VMBxTk59Ejgy1Vw4AzJyyvCNcmYKpccUdqtKJxqkyVI3UpTHIrfwxEFXGV6Oc4GAfXssySbC+gXTmyprM/OCHl67eajZimEzGRTEB0Otmm1uNXLMh2ERcHIOlshjDRDeXqbnCqS2ajiK9cUVRzifq9J4f2r7c8xH50vUGP95M01S+Uk7TtBvqT0bVqF1W/1km1cj8Sy7BGCPPkmVZt9v1ZqfTkUJWZ7LkRG2eKbOiKMr3Cub6z8wM+0yeKfDXprOW0bgrs2Obw41NGjUmYLAy2BS7021sbqxtNIt6QEQtqeS5BOf4djBQgUtxyQlgo2HCv86FbA4Gpm99ATC78vR0cnjgM46GPBZObzEcQRaTWnS6omUZlWh2A5caXvy0lkEsi5vdAwKIpf9Y/z2rJJjAHDwvcBy/RA3EmYMbErY7O5QFxAMBMNDsZ8To9tJktnAMwKRArWKW50neCcS5g9sZerRT4q+iaknirIqinEsWd5CKoiiKoiiKoiiK8pKjTq+iKIqiKIqiKIpybtHlzeeHdmCqNNucmWEuRGSt9QuV27Gv0RpmCuNjo1XKAOSmfNGx9dLomqqqSqHwAUAGA7fLlMVGdZhLu9rSVBRFURbAsv8kCnZQNdYmacqzDpmsLYvCzYQeyrI8OTryO/EaY1bW1joidKXb7UrNwm6v0biqibpuT7iuFoh69W/XwRsiI1fxUrD8N67QrIaurCZHR240rs1yPD588mR/f7/JiQ6oCSaaA8ua1zG5s7M9/5gVFBpB9QDaLEEGEYUtGYZSM+RAPRkXp8cjPxyPx/zoUenjlrPcdPt9m0gdkKBhE0uABWCtef7rOwsd7hXle4I6veeHZ3J6o9R4yrKYJElkMG3tT/pDvI9am845KUBVVVWe51KPioj8dAdAWZaRD1y7r1VVjUajk5MTn0RE/X4jnuHlo2vKshwOh96s67zE75UnRasFljeIoijK95m6o/amCcWZ0yxbXVvzA0wxmRweHHh1w+Ojow8//PDx48e1mef5T3/606vXrs2y4+rVqzs7O97s9fsy4pfZOSGCJam8rwkAMGSk58ahm/pMEFGSWIjwWSIqRXEpGkd3CjOA4uTk/kcfnT7cq78rJpMPfvvbu7dv+1zXrr9+8eJVb4IIwbBFsStPBO9xtoYpBktZbQLMosV9srZ1wK64g4lNSKpARycKnd7JBGLsxf17hx/+7rPxeCpdNRpNHj3an0ymg/7Kav+X/Pbu1alSJhEGg6zTaealzCkjAUBEJG7f07B03A7ceEVRvieo03uueCb3THqqYcoyiCgSRo6QTi9ar3aNMfINLZ73TW9UjfabXulLP02zyFMT0dMcoiiKojAH/SczS4fDWGtEn++qqiiKYibge3Jy8uDBg/v379dmt9s9Pj6uRFff7/WyxSKF3Bo1PBz5nRQPBPMPezqISL55DJzL2o5gBuDKcri/f/zwYf3dZDJ5srf36NEjn+vChcbbfyrkBT33kNWqbED9XFvsdRTvTxV6o8xT6ama4+PJvXv7w+GoNkej0d7e3mR29zdOV4+OhuPx9AmIMQRwMEH4o7imOtwryveEP0aHoiiKoiiKoiiKoih/EtTpVRRFURRFURRFUc4ty9apKt9PmHn5ap9oJbBIiVm08OwpISJjDDMvCcediz/Qm2F6TL2COv5WURRFOQuKVg5Hq4inEb/TDnY0Hu3vPxmNputdjw6PhqNhMdu5NSlTF/bFDuzEnrdEFISQLoZA8ULcM5AreM+AWC74rVdZi9TmIwDAuWkyOwbcbDRjQ2kn7/Qbaa580MsGjVaFzfNg01tDjIVLmuskWfN5VzHnu7pmQUooy8UuTAzvACEotSyq09PSfzUcjmpqsygKY4wPTbKJTRKydlqcMfVvJzz79MpmfzWI3YU5TjxrzI9oHa8oynlEnd6XmyX+53JHjoh8/ujAWjtKfhMRnVQKWQFwrpm01B/kiZjZS5jUGaJKyqLSNF1ZWXHOlWUZSVUhzBldgrVWymXZUFgloq6Sv+S6ZaLAY0VRFGUuZIwR3TMRSa9pPB4dHh569eZPP/vs//jf/7cHD6ZxragVGWb982DQPxmdOGoGoHFVlEVTWmqTJGlOxgDPXKY20jljIPTdAi+H2TlEo97iYhn5hKgZx2JX0sJBJk8mGI4AuNPjceJOO9PBhXNz5e03Lrz5is/4yo9+duXWm97sra6g3ygbV8aWSXMuQuARM8XaXQhbwKAiNLVys0s2jKpq8hEgBZSZMRoHgsydjs0yMT46ki13/+7jd9/9xg/rd/5w57e//Ufv9Pb6/d0rV7rrUy3M9Y3+5nZ3c3taGhGSpKpEJYECVD8QqX8is3qxZe6CmxksRZpfZ8AsnqQAROTCO77w7iuK8vKiTu9LzBKftmZ5huV+YPzVjMhNnfsO1meoP0Qnkoe3TyQz176rcy7P8+hESyoPgJbKXLXhUH1UPV5FUZSnhAxRHCrVdOxlWZyenvgO9v79e//w7rvffPNNbXY6nd2ru/3BoDYrriZlEXinXLqqMcmQFfMWJjSv+1pECZGUsUzl2AtaOsQwbEW2WJzBOsgXwWWJ8QgAJpOSuEinBxKZtfUL8nnuxddubb/S+MDgQI2LyZTinBReAwOzF8pTKL7K0D1FxVxhehLRNkREib98dihLmkx3WQKALDVgMUQyZKnHh8Ovv7zvR/a7d+/duXPXO71bW1s3rt/o96e3u9/v9ntJr9/8eCpXBTMETIAx6msJ7kjquOPrTASiUPSK5W9wLlEyhd8svrmKory0nOEMKIqiKIqiKIqiKMrLizq9iqIoiqIoiqIoyrlFlzcrf15Ei5/rCOH2Kujoy3YGRVEU5c8E30XHfTWBqNnLPVKImOZ4KZDXxaHpIQKRv0CaIXOIz38unFGneRfqia6RiIwJzHDRsqIoyneIOr0vMZHj154uRLGsMjMReTM6ioiWBMFyGP4aHQvAmGYGU5YlM5czEQznXFVVUsgqEs06ODjY39/35uHh4d27d8uyPDo6evDggS8HwL179z7++GNvdrvdK1eueNNaK2N6mXkymfjrNcYkSROzBCBJkiiOtyimaqIArLVLGkRRFEXxFEUxmUy8ef/+/Y8++sj3qF9++WUt4Vuba6trv/zlL6/fuF6beZ7funmr328UjCtwJaJtTRC4+fwwgtETgKVQyiEe2RqIQFWFoqlVcXhYDYeNyScFn3izk+e9bhdA1uvdePONnZlUNYgSa40YegZbW/4zADCzGC5hYJMmVrhdwUjXernMNREZGACG0CiJzdxU/wUZdDo2TZtml58BMMOJOiZJtra26ps2zZLBSs/Ncmxurr7zzutra9OY3rxr19ennz3BrIaIZvclvBwiG/jbrZlIgNfPnkLMgUK1oijfC9Tpfbkw+ocAACAASURBVIlp+5/SkWu7o09JVE6Ec25JKoUOszFGVrL2eGWd6xe53jw9PT06OvLm3t7eZ599VhTFycnJwcGBPPDJkye3b9/25vXr1+U0K8syqd5clmVRFP5E1tpIz7nt8UrPPLooRVEUZRFVVY1nwkUADvb3v/n66/Gsf75//35Zlr777fV6b/6zN996663atNZeunSpk3dqE8C4KrgS2sELB59ng8Es9JcIFDu9y2ByDmKMqI6PC/G4dlgejqpmIKPNzV6/DyDNkgvb68gWz7tM4+0DtUMpKmkMLXdkn5H6LhDIWKkDHUBEaWZTqVwVEtYR1ia9Xs+P6v1Bb2dn26dubg5++MNrq6tT9WZjOe+XgRBW6IoSpp55zKzqT0lUSRCk0tiSKY2iKOeJeb2JoiiKoiiKoiiKopwL1OlVFEVRFEVRFEVRzi3q9CqKoiiKoiiKoijnlsWxJcqfPUQkg1HPjEuRGeoAV/m3Z3lML1r5I+SxdTSsrGRbFEpGzx4fH//hD3/w5oMHD7788svJZFIURa/Xu3Xrlk/q9Xrj8dibJycnUgFrZWWl2+36mhhjsizzqfUFLrnGWnDLm1HEr6IoiuJhZq9UBMAa0+31vLmxuXH95g0vZLW1vb25tTUeT4N+Nze3Xn/t9e3tadhnPWSMJ03fTsZkNvUmmMuikW8wxhhjyYeC+rFpFq06y1gjRi4OlI3mjAdylKsFpfwBRYm7d3Ewjdpl5tsffHDv6699dlofmPUmOncn7W/cXAXAxrg0d82AwmVZVZWI2k0DNUpnyKWNaQjJYq1kAhIGhS0gMbAk3nMQuL5IBioizNqKQ9kndhgfmbK5ITg5Ho5GzS0YDPKVlSYGu7/ae/OHl30treU0Z1+Xbjdb2bBZ7tNdUY0nw1nMNrVmCJQC4u43GJAJb5KAAQqFqgwHzUEECme/Mj1uOUVRzgnq9L7EfEt1Je+7tp1eabaR+Zdnbju9xhhZ7UiL6+jo6M6dO968d+9e7fQC6Pf7N2/e9EmR03t8fCydXmvt5uamNyOndznMHNVquZOvKIryfSYS4TfWdkV/u76xee36df8Y0Rjz05/91A8ceZ5funipN3OSmXk0HklVwjzPs6Rxe4qikNL6SZKkZjq+1F33NIHZkAlGp6gbZ8CFfo4cTjn0pxy7SdlIIY1GuPcH3L8/NZlv/8N//+B3v5vlxuC11wevvubN7vYV5CsAYKhMMmenZ2LmkRsXQqbLJIHCYmWpFB5YDvQD5yyAGAkLeSZmUOj6LhCjcoRCXC4zSgc3s12Jw32MDmfJwP37w/39Y29evb6WCuGxwWpvY6t55JGk3OlxS3J7Wnrl3Ph0XMyeYhBRp9MJHuUjAeZXG6DwJgkIzOG1E6RyFUCh/x/C7a8URTkPxF2RoiiKoiiKoiiKopwb9E3v+SF4zg2g9RpWmvXnOv/yt7WYZfMYY/w3spw2dZV8amQCSJKk02keEq+trV2+fNmbnU7HGFM/1482N1pdXfUvBwBcunRJbu0o9yuqWVTDmiiVnnHduKIoyveWyWQyGjW71KZpGq2s6fV6/lWwIWPF+8w0SUFNkAuDDYWLg8K3hPXqIW/6l7nRyPICYOffI7qqGo/H1ewNMw+HwwcPJn7PPOaqqlZWVqYmsL65uX7pkjcHIkmOJQRYa1i8gGVDHL69lBv2yN10n5amTQhAUPasLGaw2DWoqtxwOClni66LcfX11wdP7jf39+Dg9PS02ZJqfcsYs+ZNYyDjgYi4rEpU0xPXS7383SfA2oRn+zATkTVWLkpnhk8NISInm7M12xGXjjkN1/pCUZTzjzq954d6F1xvRguJiag1KjTfyOlClC2aTFDoEKLlMUqYWa58qx1Xmb/b7cp1yIPB4MqVK96sM88tvyxLuaBuMBisrq56M0kSeRVRIe0yo2+stWnaLKiLGkRRFEXxHBwcPHgwW+sLDAaDtbXGC6q33hV+TrztuXPOB/ESKEmTJd2vsSalJtUQRX27/3yWW0NYuDctwA5lE8RbjsdPHj0azTYfnhwdffHuu48+/LA2CdjY2Lh582ZtAtj54Q93fvbPvZmJ1iCxvo6JsjRNk2YaNiYUwjE1ICsmaXbRat5FBMMcM0gujqbpHzBQucbpHY/Lh3uPh8PpxZ4cjf6f//vdT3438/CBJEmsbWq1uvGXP/6Lq95MU4jn2CirajgcesfVWtvtdv0UwhjTyXPOxA01Rt44V7lqttJa3lwiIgRLwa0NTCBwdImIo4XhYVsGTdWKBVcU5XygTu/5Yblrt9xzW54ascSfRCvV/11/iDIbY+T8JnrxmyRJlmVz6zYaBXFfaZrKcqJJFaLJ0Dwzaqt2CYqiKEqbsiy8Qwggy7KybOJUrbV5njdOL5F8eVt7vG72XpGI2l6xZE7n/Iye4BRaeiAD3EhdOeeKovAjzng0Ojg8fPzoUW0S0draWrfbrU3UD2GFowuRJKF6uBQDHMHJN70Eki4gAUsrfRaLDmWwOKtjN5kUo9H0McTpcLi39+jOnbuzdHS7XbmWajQayiHaGAT3x7GrKife5Yo0YDpYx196GM3QHIzaDJim0kTEzO3CJUsTQ6eXl9RIUZSXmIVDi6IoiqIoiqIoiqK87KjTqyiKoiiKoiiKopxbdHnziyFaLhsts4lSPctX46B14Jn5vwuipb81sib1yiKRuJB2/Z1zciFctHRNlhwd287ZLlwSVfLMzPFXiqIo55p2Nz63J2Tmk5MTuZ75D3fufvXVV968fHmn129UBo01zjnZXTOxjJokNJsLndGPI16jSyxWpnK4KFWu2Z1LsKKVIQWTnINrhKwMkCZplc0ydDor25uTqzu1RUB/Z7uzvTFNBZKVPsQ2SzAW08syxKC5wkwAAEtIxDUYhhG1NMTUuqTwIoKyo5ZkCnKzyEAEv62tq9zpyfDwYLop0enxiECdTrOeeX1jbWXQSHMNBv3ZplEAQARmeSfYWNAsntYYAIEAVRRqG91+AlG9GJ7rmy2+DzLXWwHHjbMQRqt5FEU5/6jT+wKQWk3A1B/zYzcz1wJOPoPHGBOHJwmiA6NifZ4l5guhDmfyprV2nmLEslotSR2Px4eHzQ6AvV5PamAC8A0btVWaptH2v0smS3XSkgzLK6woinLucc5FUoiJ0FjCrJ+squr999//7LPP/Pf//e9+/e5v3vXmv/6f/vXf/M3feHNjfb3b6ybJtLsmMoYSzMJ6iTizpnF8iAyBYsFe0SFHTpJjlBUAEBEF8sZUVs1us2gFm0ZD5aTAaCS+JbkOLmHaXNtws2GiWt9Y+etfjf7VOz7Dytpqpye2D1jbxWrjA8NYGAuAAFvSEv0sYzkX28mSUJAGQAYkUut4V+/ZM5sJp755qD6tbDm5LzEATL1IBixgZ4nFcPzJ77/4wx8e1GZVusTaa9ebXRV+/OMf37p1y5uvvbnRaR5xAHAlV77aZFy3a3zDEsGYib+hzORcxizEukKJakPBJQuYyAVucPwsIb7YEBPtWrw8t6Io5wN1el8M0ult+7Fcj00t5n4pWXRgTZS03HxumDly6a21vnAiilxEmflMyrKUelR5nktXtn6aUJ8ratXlzwvaLPdjl6cqiqKce9pdvUhsYOa9vb0vv/zSf/Ph7z98973G6b1249rJ6Yk3u92Oc5WbeVyzbns2gtQnkst2AASDF/nMtRHAPPVsCZj6lTMcY6aPBQAINXlZlgpUDpOiOS8Z8XoWxphO1mmq3snzV65VVePWpp1OIndpog1ASBijqRe51iUIDEE6cuBGTAsAwlfXzFxx5UurW8J5p7f+f3Gy6E2vtKRvXJXl/pPDB/enMl1gMiZbWWlc+itXdl599ZY3t7eDt9pVxVUpp0Mc7qUAoHmwAhhmYidXAQROL/kLiWGYaKYRTXiWz3/mF6ooyvnmGdwGRVEURVEURVEURXm5UKdXURRFURRFURRFObfo8uYXAz21mNN3R7TSeNHitD8mZ7ZJVMlFdV70vaIoivJHgJnriN+yLOWmtQAMGblLbZ7nMhjYGCvHpjM7cwYoGjiWH+LX6TI3Oc8aetg5vzkwADeZVKORP4qMIZs2da6VLHxuQK6PjUbePyYE8kuez6wBu0Cry4/PRJAyHcaYPM96vdnybEdsMpQ+JJtCPY2zb+gZnHWnFEVRXhTq9L4AiEgOAtEQWKd690/6gWeOFlE5ImXON9ZaGeYaVSMiCt+StOufpk3ITjuYVmaur05ebFVVXp95rqBXVGeREjTskmtRFEVR5iK7XGaWZqT/FylXRV3ucDh89OhR7fF+8MEH//AP/+CTVldX/+qv/sqbv/jFL65du+bNfreXZ7nv54nC2FoA1ITbMrOrqqCSCOpB1gZ6VES1RhQAMEMIcYEIUogrvJyT/f2jh3vefPTgwddffOFmh3c6nfW1Dd8a3cHg6muv9dfWapNA1lpjmmGRkgRilISTosshjDAwV3wGYBiRbpMcXollVC8To268GiJLweI9ecXMGI4waSS3MRwWw+EEQLdrt7fzJJkeurIy+Jf/8mcnJ6e1yY7Gh6YcTcsiwvXrFy5ebIruDPzHKdH8QaTMwTnnXCCfJqXKzjhYURTlWVCn9wUQeYltfIbI5Vt+VI3Pc2bmZxJ2qmc/bRcUrXLoGTcHksUycy1GVZtVOJvBWaUtT1UURVGWEPW3UZ/PzLKDbXf1/jOAsiwPDw/H4/FkMrlz547co+idv3j7n731z7x58+bNzc1Nb6ZJmrS0jCTUvKsFEXFVRXpa0ktmIoqdXgIAZjgHeb3Geo3oNpPh8PDhQ2/eu337448+8s9nB/3B5UuXsnSqTbW6uXnx+vVGyonIGGIWbWUiaegFTm/t8UZOb2wKm0JZJwROL+J7RKa9o5GgmGA4bMzDw+roaAJgdTVdX8/8c/s8z19//brP5iqcPMZk6gIDwPo6+k1bxLPIJTd6DjydJDRfMEFdXUVRvhsWDgmKoiiKoiiKoiiK8rKjTq+iKIqiKIqiKIpyblGnV1EURVEURVEURTm3aEzvCyAKSokioyKePuKlXc7TH3sm7cI90VkoFKY+sw4yQ/3ZN04dURaV0I46m2sS0ZmnVhRFUTyyz2TmyWRSFIX/JssyKVK4vI/tdDo7OztVVVVV9atf/UpKVd149ca1G1e9eenipTzLvWkM1X1/bdaniE/jz8sw1sqoXVNUVAp5qpRAYoxwjHI2+MYSFSxzHj7cO9l/4s1vPv/8s99/7M3T0xNXFOSm+fMk2drc7MwkqXurq2mewTa14myNqQls5cSS19MCiDNZRwBBrK28+KghjAOJiwUwqxIAGAs098s5LopGG5KITNIUWFU42Hej0TS1ctVv//6DLz7/ZpoMJDazSQbg2u7mzvoPetTzSTKU2DD6fddtEpHlwcyRieDEZTAZEk0BQ1gQ4QwA9Txk2rBE9Y9QZuCw7Txzv5Q0xc4j/gEqivJ9QJ3eF0Db6V0+e3h6Xkghc3mmGj59ToSZiah2dGszcmjbtD3eaKqkKIqiPB9FUYzHY29S+Ogz0v+PyLJsa2sLgHPu5z//+a1bt3zS9s725oUNbyY2Sa3wpcGBO8qtzpyE/hJBukwAMKkgnV5jIdNLRjFLlb7a9JvmvCdPnux9/bU3b3/6+T/9/vfeTJIkyzJfscTa1bXV/kyvKe/3kyydKmYBIMvZgMNqyqHLOBNURFydEO0S3zQmg8SuCszBLkNs5JzNOVcU7KcexiAVIl9VwQf77vBwmlyW5Xvv/tNv/v7daTKwubm5vr4OgCZXyx/fMs2eU4EmFwhplyldPHazYen0gkg6vQTwsnmmCeW54x8gMTB3m4nF9ZliEPxQFEVRlj0JUxRFURRFURRFUZSXG3V6FUVRFEVRFEVRlHOLOr2KoiiKoiiKoijKuWVZrIXybYjCU+MopsVfSqJCZOTwXGSB7QrUyC/nsiSwFrNyRPqcIN7oG29Oa7AgtSa6xjPDgBVFUZSaqP+MYnTzPLe2CXRMkkSap6enx8fH3pxMJqPRyPfAvV5ve3s7SRIAg8Gg/jBNWukmtjENBSdlRhN4CpD/n/+GSZoxxgrxplbQpyH4S1g6WPR7Pd7a8ubw2tViMvFmt9dbW1/3EbGDtdWLN25k+VSOK0nTxFqU5TQ3AYmVulYxhPiCapMB04rplSxuBgDMCG8v2cTaRjKDxuOmDU5Piy++uH3v3kFtusodHBzK272xsXH16lUAFy5tZ53EzBqZpn9mEDMxi9BiZo4iail8fSKH9PaMI4jv5ul/c1PRroyiKMq3QJ3e74S2w1l/Ezl4y4m8TWauqmqJE9h2IGVmY4y1NnJf/ecImc05t0Sbun1SaRpjZIb6WHl4ZKI1afNEvrSiKIoiqYcM33tT+AiSiPI8z2eOXJvj4+NvvmnUfY+Pjx8/fuxLu3DhQqfT6fV6AFZXV2tRqxqHys1XGwLqWkW+mnzuCbKRclVEYiG96GgUoJnTy4yqavlMTeb+YCCkmpBYO+g18strGxuXr15tBqMsRb/fuNPOoSjgha8NgRd7vDWB3yg+M5ZpMFGoxRV6hAyuAmlnSpOm6YoS4xMUM8f88HDyySeff/bZ9IYy8/7+E/moYnNz8+bNmwB2dgZ5T0qPhRUGKgR30LlGMhqAIfIKXwCI4ucS8nrrC5J3qW0GLHscoiiK8myc1XEriqIoiqIoiqIoykuLOr2KoiiKoiiKoijKuUWdXkVRFEVRFEVRFOXcojG9L4AozLX+RppPCTMvimitic7SJjqvDLyp47tEYpAqkVFhtSkSzyY6kWycdlFR07VDfD3P16SKoijfH4jId5X1gCJ7XWut7EhHo9FEiDl9+eWXv/nNb7xZDwT+8DRNiShNUwBEVIno0gplBRFsSoGWFYHDXp2DkYAZTgojEYyBDBKNBg3nZNxnOZ5MTocAqrI8OjgYj8f190TUX1nJOh2fM7c27fe82QGvZ01AbK/Xp17eRKNaiwSg2YkIgAHPakVEMOTmD1UAKJR24tkVO+aiKishCmWNlRGxhmBIzMqIm7higJHEpxTtZAl50mh+udxeubDGswZh4PqFNedDfoFXXr1+/eY6gLW1TpqahbGzBCJHJGYmJgjDpTDsNhqomcGuuYkMIJTBIopDtqNZDBaGi1Nw/TFLkgCcna4oyvlDnd4XABFJUcTnhkOpqsghrM/y3L5fPQGSZjjxiGYWy5B1mFsf/2V9CdLppZbvLa/RWvtCWlJRFOX7BhHJDtk5VxSF907rVNnBnpyc7O/ve/O999779//+33tzfX19Z2fHF5hlGRHleV6PU6WXMgYKTAqeiTzVzy6FsnFKNrXWe0bM7FyjOEXMKByq2dhEhCzDEmmrqmoEpYDJweHhgwfMPBqNvvjiC3851torV3fXNzZ8zu3r1zuXL3tzZWNlQJe8GTXdzJ8S7lYaVMmwRRl7oB62YJHdOXaOAZRcHZan42radESUZVkiLjalzEqn1wZjpWVKFg/UxiBJmtV7OSdv3tjZWR1MbcLm2qDfa54CrG31Vje6AEBkmvszB0MOprnd8WUvnTwwoyqDLEEzE0zSEr4KcJDPUxrM7L8F+CcUizgrXVGU84c6vX9ePJPz+aL4k5y0JphnKIqiKN8ZUVcfPfqsqqoQ/mTtMPuHkv6ZabvTZg7e3sUb2oDP8DC+zQDEzM4xs6uqqiwr74ozu6qKVKOlv0WGwp2V2oS1Cq6A4kt8ajhsn1C6uF3q0nZrEbnt1hg7e/pARGlqs6yZ8qWJnaZOPfznhebUu2FJEoDnP/NZ5SqKorQ4o9dXFEVRFEVRFEVRlJcXdXoVRVEURVEURVGUc4sub/5TEq0uc87JlWNRlFF7UVkbWVo7f/SNz3xmTkm7kOikUQYKhaw4DC2uqkqakezKkmooiqIoS5B9b00d5evNR48e3b59W5oyNU3Tzc1NHwO8urrqP0clGxjDjXlmvx2Ma4Zg0UhGAcEiXQDMcE3q+PR0fHTkzb37929/9jkzF0Xx6NGj4XBYf2+tlVHHZxMtsWbmtn5SUzEihFHH0WLbaNXyDCJKbMIz5SoCJTaxIqY3iqwtinIipKdOD48PHu77ITJJkm63429EZtON3kqeTKWsrDWDlZzMrB5E/X6nk3uhK1hrppdIs/9qQqExgGFYXuGy8F8AYVtGzUChTtVZvxRFUZQXiTq9f0qcc1IDE9FsoCVk5T/PJfI/0SpNmrWrWec3xizJ2UaeJXJiqaW2JbWpiKienfjUsizl1ETqeEUsr5KiKIoiIaIkaYZ4Zh6NRrL7/fjjj6Vc8yeffOKdRgCdTuf111/3Jezu7tbSzailqsTYxBD6vPNGIgkRERmfTgBgA98o6uqdkLkCDh89uv/NN9785OOP/+7X/905Z4zp9Xq+tmmaXrm6+wyjBjMCoUfHbuFgBJBJLRnh9wZeIZjgpBs/w5Dp5t088Poo8CHD+p6cjh4fHHvz099/9vd/+64fcFdWVi5fvuxvytbG2s/ffrOzPjXTzOxcWZeXYGCMkHciQ1OJKAJMc2p2cKW4g8RkmUJJrSV+b9iQqJWq/X0gknLUQKzVrCiK8h2iTu+fGDkmzR2h5375YiEieZbIjJg7D5j7JWaVl6VF86Hl0yNmXlITRVEUZQlR/8nhM8rRaHR4eChNmWqM6XQ63qeq1Zvrz1GxhNBzWzwizBAFcONuLUSUVpXlZDTy5unxyZP9fVdVSZIQUUfsUVQLJj8Dss71wBQOVU0qmfgNZsyCZIofMUdEh1WOC/mm93T06NG+f1BeFK7fX82yrDa7WV6JpwNElCZJINZVhbv/sDhfcGLmep+hGgM6424GhM02n8UNoCiK8h2iMb2KoiiKoiiKoijKuUWdXkVRFEVRFEVRFOXcosubXwxLVnMtWcuEVqo0565M8ydi5nofRZlBViNNUxnQJWNraxZVLFoCF4XdRqkQ+zcCsNZ2u11/oqhZ6jMuaas2vvDlq8IURVGUuV2uxxgjR4Fer7e2tubNS5cuyYjfK1eubGxs+OXN/X4fYW/vYQriUFr79AJPtYgZAMBg58TiWlC4Sjka5rI829zYcM6laXrh4sVur1d/n6TJ6uZGPuj7nEmWQlTMMctdfIlhZvpSAMAG4GBD3XB5s4uGIyPLhiOwjOll9ldvAs2umNGwHI+bMf3x/YM7d+5789G9x6OTYTWr9qA3yJOsk01XdOdpai3D+otiRtBWRPO3JmYQw7AP92XAiF8OAWTDJcthJK6IEwYQXx+hEdMCiOoCm3Se/pmZ8Q8Y8ysdlTKfxS1NWJYK6AshRTmXqNP7AnDORWJO/m8AzExE3t9r9elNxx2pgyBMdc4Nh0Pvf1ZVtbe3d3zcqFxw6I6ur6+vr697s9vtrqyseLMtXuU/TyYTOfU5ODh49OiRN6Oz+Eur6XQ6ly9f7s1mHnVOf1H1tcsWiFojwjlXlmXdgGmaRk67oiiK4ok6Z4T9PBHlee6dWADXrl0bj8fefOutt+ThV65ceeONN3yva601xkwmE7T6bUphEqlr1erVI88mdMXBItaUmUdjFgOQMUng9nDgrG5vb//0n/8MzJ1u79YPXl/f2Ki/J2MGW5v5inB6kwTc+JNlVYydkKpO0jzPm1EbcNxoN3HtQDaX0IpiDq+YyJmpSFRtT9MJZEEUeYmCO7dP7v+hGdPff//D37z3njePDvf3Htz1jT+wva3+5urqdFhfW+tkPZh8ekOZXVkULB6LJ6klG9ym+opclRSTDrtpkjGUZiQ1NB0yVwrZZxNeOxFI/OqYpUnEJM1wssGAc+zEzymaTaVJltjm1CGEhX4vgzi+KwEOWCLubYF0ceGKorysqNP7YognAUT+G9nFt4lSl2Rm5qqqvNNbluXJyYmUIXHhfj9ZlnnnE4Cc69QsOpcLNaVHo5F0raMxiYjkvKqupK9G26dl5vaXi6jncMws21NRFEVZxJKhJ3qu2uv1NmZeIoA8z6UQ1NbW1tbWls9fVdVkMqk7/6gbt9Ya4SEskfadT9i1c1WxXFuUmMBVC0+d5/nW1haAXr9/ZXd3c3t7mkCEXo5MjHpVJWWFHbuyas5irIUJXmDWbtPsc+z0Nq9u6wzhFdsgcwDxsneIk9Py6HHzGGLv7v7tz+96syhOh8Ohb69qUnbSvJt1azPPMmMZdjZ2M3NZOhYtSQzRkphpbjPDMfsX6sycGiP2UQKqQF6bOXpqweEtjE0ywYOYwJmsX0YHTm+wiyEznuulK7WqEeHEg5Y29eHP+DNWFOXPnufoTRRFURRFURRFURTl5UCdXkVRFEVRFEVRFOXcosubXwzthWSLWLJMNyokWvZTVdV4PK5DqgCUZTkcDofDoc/AYUCXzAyg0+nwgm1voxOVZSkDvU5PT4+OjryJ8BJqZRRfrLVWCl/Jpc41RCTr0Db95+VfKoqiKEtwzhVFEURIhsoI1to8z72ZZZmMglmioRD1yd+mh2ZmV1VczYYJ58rJpBIDUGasSUStkiQTa7DJWiYCkOW5sbapChF4ujp2LkQkV3pTGEHDAM8CcWffLCzqaZgeHi6SRqvpksRkWTMry/MgRsk52+83N2V9fS3PM58/TS1JLS7EAbSt5bpULwAmgMTKbqJ6LhHl/DZMTzQfatbD11OUYErgPymKonxr1Ol9ARCRtdYPmW0nzX/TDohdMrGoqmo0Gvn8p6enn3/++cHBQW2WZXn79u39/X2fP/Jdr1+/PhqNvLmzs7O+vu5r4od8Zi6KQuoz37179/79RjHy008//eCDD7yZZVm32/XlJEnS7Xb97GF9fb3b7fo4sdp/9pfgnIsuOU1TGUWWpqlsvdqjbg+EiqIoSoTv1WtOT08//fTTJ0+e1Ka19tq1a5ubmz7DxsbG6uqqN6MRpNPpRL2uN2tRK/89G2YRIRlVg1AH/M7vwKuiOHzwaDKcDlXs3OGTJyPxMHf3YfDLywAAIABJREFU5ivbO40E49qlS/lg4E1XVa4sAdgk6a2vQ/jwcBXECIgkgRx6EjIUzH8qEeLriCobyBBHvmqsUbzo8gAAjl2FCgCxcaUl50dhJImUjMLWVj83zSWMRq8WRVOr7e3BtWtb/i6srg52dy/55xRpJ7h6qrdsCBz7JhWoXU0DwBiT5cbHJTuHyaRyjWg2pamxQTDwMqLBuv7YuLWh188EY4x8NGFNtMfEwgmSoijKs6JO7wug7uKfxivj8GWsfEfapnZHvabUcDjc29t7/PhxbZZlee/ePT+hqfP7zwC63a6c0KyurkYZPFIfC8DR0dHe3p43b9++/emnn3qzLtZXO8uyfr/v/diiKA4PD/3bg/qtrz9v7b7K+ZC1Vu6rZFqa0saY+vAlDaUoiqIg7Cerqnr48OG9e/dqM0mStbW1gfAY+/1+tzuVQQJQlqXU7V8yPFlr5bPLCqWQKgbmdNfzywHgnBudnIyOplqJVVXtP3lycnLiM2xd3oUYMjqDQaffaDLDuak8FRGsFTkZkxLCj4V8DwwYa41thp6qqsqyuXZnyPESleWY5RkZ7OpNmBhcNdrGdZUlvX6WUebNixc3d3d3vXnjxsV33rnlB1BjkKbNNVFSJXbc6DPVQ60c9FuCxrUvSkTGwl9EVfFoxGU5LYeIrDWLH87PIRzEg1YkkAsUpKhGZhCpAD+ts60oinIm2qEoiqIoiqIoiqIo5xZ1ehVFURRFURRFUZRziy5v/vOljrCSa4NZrI5ux8fKzACIKNzvjnmBkNVy6jXG3oyUq+oFybLYdp190tyzywxtlqcqiqIoU8IOt5aQ8AEydajIC+lRn6mIuNMP68CVY1e5ajpUsXPsWqJRS84nx5ToTPGJI9rJtPRMz0Rc+PSKHTvnmphewDk5uiLa8JcIRmhTRQNoazil9nmfE9mowe7Fz0FdK9mwL7CdFUVRngF1el8M0UxirncHgMOY3ghjjBwAJ5PJo0ePvJDyo0eP3nvvvTt37tRmp9P5y7/8y5s3b/r8w+FQqi5/9tln//W//ldv/vznP3/llVd8+UmSdDqd2mWNJD3Lsjw8PPTmpUuXfvWrX3lzY2Njd3fXl3NwcPDNN9/482ZZdufOHR94TER5nnulDedckiTyXMfHx3fv3vXm5uamFKtk5lr/mYhgSc4NyqqoXBNHZm1qTKPwGUFgu2yUZWJHdcxVjWNI06SgOYUzoQoVPiMMKgrilwLIGaoWR0oRw/LSOczyKc6Sei1JwlnFnsnC6wWwrPAzKrU8OZ4sPhvkFpyezlgLM/egBre02mcVfo7gs5pq+c0jnHX8cxG5VnO8wcAdCWDAgd3iapXlpCwb8fw0SbOkidWM/hkwc1WVdVmJsXaxeA87F8bPBi13dHT05RdfnZ6e1ubjJ4//83/+z19/9VVt5p1OORwXP2pqde36tW6niek1ZKR6syEjr48ZpYNzIMA6OFFHKm1SNjVhgMUvn1ASi+0ADg7uf/75ZDit5PB4+OVHnx8+mY441pj19XU5CuDxEa83Ib6U54Feky2R1bG4BMOyQQqbVtzkdIaccCANkynl/bUk1CUskKDp3JnZlRU3gwKRCYJPTegZEgxxU9rhk8nde0cAJuPJwwd7o9OpvJa1dnf38vr6ms+5sd5bXWmUHa+9uj7YbMoZDLq99ea8RDC1RliNITIpxHlB4QiyqDsiACUwjX82Ft2uc77lCIkNRt94dhO74tT652rkN9HRAMVxvJL4ZE8PLe1gCVj4rwygOdVUFOXlR53eF0D0+HyRx1sTPORu+cDS6a2dT78p0d7e3hdffPHll1/W5sbGxr/7d//ul7/8pc9/eHgo9T+++uorqbq8s7MzGo2kw+mRUlIAqqqSOyFtbW1dunTJm5cuXXr11Vd9Obdv35Z7GjHzkydP/EUlSXL58uWVlan2ZlVVkWM/Ho+lFpdUcsasfZgZRMROjkOFK4uq0R1JyCSLnV4DEGZP1+fAxGXg5bpqKo4yxWBe4Qw4LCsXcGY2k5gDJ8ucXgNYbs0eJIuPnbLo2OXFmm8x3tclP1fhSw6qWTRjAxaW6VlyKABwoy0TsGTONGNJyVT/QBbxFIWfF5Y3RH3zlt3CJY1cc2aGBQRCsmE3vny2zUC51OkdV5Nx0fSiHWIrutloxu3YFa6oz24os0tOXVUs5HwRDjfDo+OvP//8yZOppP/e3t5v//7dzz77rDa7vd7rr/3gwvZFn39ra1tegaGgc45gRjUTjUrDJjcV0UQ6wdHtrMClP2J8cPDgk09OZ/sOHB+efPqPnzx5NDWzLHvjjTd6YsTB0Qgnjc/MlFIuBizjkNUlB/eCQRWyAs2DhpKrSvwMbWUS0f0agyS8gkQ4jMyuLMUuPkTGQPqBxoROLwd3eHzkHnwzBHB6evLZ518dHEyHvDRNqyKZ7DQ5e700EYPg9k5/e0eodmH5vxOKZ3RR5oXHVqCJ/zdKhLRpNgD0FP/AgqKXT4GWpb1I4l+hoijKwhFOURRFURRFURRFUV529E3viyF6fytSYuS71np1sTcpjMKtI7L8N845IpL5q6qSO0wAkIvTmHkyaVaylWVZl1CbVVXVK4frnLLOGxsbt27d8ubq6ur6+ro38zw/ODjw5RwcHAyHQ78hcJIkKysr/tWxtTZNU184M5dlKWv1xRdf/PrXv/bmq6++6j8D6Ha76+vr1loQKFjdDOec3GbJmCVvksDMlavk4+qg2QHiOaFU0hafFUV5qfCd29IXUN+SaImmNUkm3pcZMqVr+itLJlwwCmtmO707rkROY0ywkashEiOIq6pCdKdPnjz54IMP/R5Fw+HQGHPhwoXa7PV6ly5d2tnZ8fn7vV7TOEBZuVLs8WOtTVPxdtpQkjTb0VeVGOaYrLx6BppdXgFXoWy20qHJxKBZ05Tn2dbWVp5OX29mWXZpd1euLeptbEDsq0RijItwrokGZlCJqoRYCk4w4im/oaBdiWRL1IuMxKDATNb48FoCkVgpXSMPf/z4eP/JdBMmAJ99dud//I/PAJRlcXS8P5lMX1zneU5Ecn1TtOrKuaCdjYFN4vMqiqIoT4k6vS8AZvZiIf4baXqstVkWrhwS8zDnnHdEMdvk1ru19Sm8z2yMKYpCrkOOhk8APrgLwGg0qv3e2iSioiiMMeyXEM/Y3d29cuWKN9M0lb70/v7+nTt3fDkPHz7c39/3J1pZWbl48eLa2jRIiZlHo5G8hPF4LNdg/93f/Z3cBPhnP/uZTL1x48YvfvGLetffipxcTFhWgfNsbdCqEc5VRTHxC5iJyJgmJIsIhkLHNl7jpwsiFOWlRfbGod8bddTBskxatp6+DYGk35uneS4cmNKVExnia2ySZD6/IUO1M8Nwk6IUUbs2TRPRHZGxSBuntw5F8b3x7du3/+N//I//9E//VJvdbve111577bXXarPX673xgx+8+eabtYn6IanwqSbjyakYUPJOniSNZqE1ppNP26Qsm31cAZAzwZLsilGIp5DFBOOjpvsdjRLTBA9bSm7cvOGKaTXSLHv9Rz+6cPlybQKw2xdJbDi/6MkFM1dVM8AxUUHJRNyR1Capae6IMUhEv84cRrQ4pqr0vxwiY9Nw1+LwMWkVBsR89dXD9//xS2/+7ncf/O3f/jcAeZ5d2tnu9aY+fK/XM8asiqvLssClL0sej5ty05TU6VUURXlu1Ol98TDzIqcX0byqRXTgsjlZ60RE1M4gP7cLr7+Jkqy18nW0tVY+fjbGVFXl5xb152aqwSzzy3fLPoM813g8Pj5unoifnp5KLa76Xe78FuPo6kRSC3+RzTcsA7YWTqQURVGeA0LcqwTxw+L7mqkDTECr249Z3KNWVTkcDf0jyLrn9L1xkiRJ+AQzjuBlduIN7ZxqNH3xnMQAmcocSAMGziWIKEkSn71+xprKR8PWtp5CzofBzZteBoOlnlYE0bzbMIMBZiEjUH+KhonFh5elG4+bRVij0bi+Kc5V8tFzPT7KuxCNQ8zB0Lb4hIqiKMrZPNVYoiiKoiiKoiiKoigvI+r0KoqiKIqiKIqiKOcWXd78YpArlMqyHI/HcgHwcDisI3KNMfGKssUcHx+PRiMfuVoUBTP7w40x0cJjF2o7RUuL68XP/pt6VZUvTS5WIyJpHh8fy9jg/f39hw8f+qs7OTnpdru+Gqurq4PBoN+f7rJQB/HWn2ui1VxbW1vXr1/35sbGhtfEAnD//v3f/va39Xq8ihyLDSdKV8p9ere3L1+40BSbpWmnk/u1YkQE02x6SyAj9lUkgIMdjeqLFw2yeBNYWvrciFrL1SSEsw5eeNqnZO7h9XXNTapZknQWNP2zmMX7Gi8/DvwtFvct2wYSWHLqM096VskKgCUNPOPMDMs48y7J4sOcwerX8NfLAMmACIS9JOqtWZv8FF1FuEmzdZRyEzOSsCFuSSEBAIgMGbl5jglqRcF52BhOEr9guDMYXLt5s5xVc9AfvPrGD7a3tmsz73RW1lalfBOF28saYzOx+DkxNtCjoubnbipG1fTGxcnR+LTRYkhgE7HVsEFhkgSzLXxstzdYX0/zqfwEO1SF8WufkzRN1wboiZ14Uxv0k4xgya8jlAkIYDauWTvNRAkS2cOmjqy8Gg4vjsLOmIiNaVakEzmIvouBiuU2Z0SQ0lZpajvdZoX2xsbatWu7ALq9zq1b19fWpnv45Z18c2ul223ObCzJFeZESEQQr53/k3lRLCl8SZKiKMpLgzq9LwATijDXe8969abT09Ovv/661mfi1sa8kjRNO52OL6oWZ/YTrdrz9NG2SZLked4VspZHR0dS16osS+le1pX0hRtj0jStS4vCs4qikM7z7du3P/74Y28eHR3t7e35Q/r9/s7Ojo8TW1lZ2d3d9cock8lkOGxizJi51nOuTQBvvfXWr371K2+Ox+NHjx5588svv/wP/+E/TCtjHExTz/X19cFg4M23f/Szn/z4F97c3FwbXLlkZkO1I2PSrJnw0vTPDHZwzk9RGRWcEw52Ap6vHsKwOGP72LnHTVni8QLTGi7ze5ckYXEqNe0wn0UHPgVcz6GXlL/A6a3PuezM7NVf5+Fv9SLOSF7MkpMickiUJZzZTGdmWMbcH1XDrOwwG8mgTQAUKNpxGE/pmKXKIBHZxAYOpBwDAJTATJwJgIXNhB9IMMSB4HENA2SIEvGrM4aFzjOj9nunuMSik/tabV3d/Tf/61/5LrTf7//whz/0Tq+19trurhE6WOT/AgBkWZpYId8AkNCjotoxJGJGWjgW2o17f/j8yTefeHPQH3gtQwDJYCXfukh2ehXdLL+SZq6cjo9MxtncNQ9zbW99Hb1ebQKASYOuMvS3URm4LgACLIvnCkBijWwrCh9DFA4TUUySIE2bJwAVUWEbH5mBshLPQBwwdP7+EtDtmTxvztUf5FtbTQsY88rqWg/Aykr/7bff3NreqL+31mxtDQYDIccNTOTPxlJHuMThE495nPEPYQlLyl2SpCiK8jKhTu+LQU54mLkoCu/0jsfjo6Ojo6MjzGSffM6ILMt6vV7w9kB8rt8V+2/qV6bSreVQRJqZo2mYpHaA6wztbNINHo1G+/v73jw+Pj46OvIZ0jTNssyrRnc6nTzPa73lmvabbXm6wWBw8eJFbz5+/Pjw8NCbBwcHX3/9df2um2wwZxlevCg3UjrcPxgPm1fE5aQv3ZH61a6QrooJpgpEjlkqRfMiT42wrNCn4YyDz0h+Xr6jYj2Ly5/bjgD4zEcAy+FlJ31+FlW35rs44/eRP6d2bOpC4e0nIJIVovA3G18FBw9MKPJXmMBzHolR/Zfwcqn1YCXqrNgYX6s0zze3t+3sqWK/37+4s7O1tVWbhqjTbR6qtgmGEwDOBe4lpo1CAByTeCFZjYajoyfezKhy3WZqwVUOazBzp03KnV7P+8xsTJV1ePZym4yxvQ4yMTPhsGuIq09w0wxRio16BRe0HblGWgsAO8g7RAQ2zXjjGBXEm2FmcpDC18yNwwzAWiN3e+r1upubGwBWVwcXL21fuDC9I0TodiH3YCoqFtLdAJ5Sw+tbErepoijKueSP0aEqiqIoiqIoiqIoyp8EdXoVRVEURVEURVGUc4sub37xEJG11i9jruWmaqknY8zy5c1ZlkXLz7yZJEm0nrmOmPWmjJ4FYK2VgVX1wmlfmnNuPB7X31hrZbGj0UgWG+2da63d2JiGJGEWW+vXM/d6PWutP0t7KZ0xRm4C3Ol0Vlamqh4AxuOxXyldp2ZZBsCxG41Py2qq6YWZrJc3EZ6rddpng0Bzlh4qivKyE3Qay5evB0S9TZu4O0LYDVEgGcUACx2+qKeURlVVZdkMGWXliqoRXGBA9uppmq2srHiz2+3mee5VBg0RgVgMQPz/s/dmzbbj1p3nfwHgsOezz3znKTNvpqSULMsOy1FVXa6eu7qfKvo79Pfye0e/dERXP1SUK+xou0OWrbRaykylcr7zmae9Nwdg9QNJAOQ+Z9+cLOte4Rd5Mw42SRAASRCLWOsPZr/YBCE638H9Mhs2RVHVc3F2lnuKg0eHh34IjBDCF1xAWaZ+9YWAUq6OQggprXtzp6EAdLzKu57EPqsvUfsgopbnsBCtXI0xWaF1c96yNGfn88JKXRiIuaZW8O0kSVwcchSpwcC9yIBaY7Lf70eR8l6AS1VZXYVAIBAIfAuC0fvdI4RI09TKNTHzeDyurMruIMMbrwBIkmQ4HPq/+Dszc6/Xs9kKIfb39z/99FO7w9HR0fn5uU2mafonf/InNnn37t3KbK6SldqWMUYIMZlM+p5wyKNHj54+fWqTX375pZ+8c+fOj370IzuQ6vV6GxsbNiml7PV61qz1DeCKSqzLJm/cuPHuu+/a5KNHj+zfAIQQe3t7WZYVRfGbj56/2HthN/X7Qz+mF2Dflu7Epn1dBAnf6O0OBAOBwKuIMVbdF6jsK5fqwEvddQdCq/c2xvg7C0HkSUZ1TC5jynye292JSEpZZSYiJZTrcM7O5pUeRJ28uDg8cebl2mRy4+ZN2/2ur6//8Ic/tDKESsnhYBjF9SuDAGm4bJYDAFCWpdWeAJDEaZI4ZcSOIaiz+fzg2JSlMeajDz/0Xwp7X/xq/9FvbPLevXt+y0xUMhBCNoUkKYW36ACIhPAkpIjINwoB1oY9s5+kIK99wORip9tRu13a11pGSL1sqG1rL+bF04PTrKhb8vTs7P33Pzg+Pql3ZiQlyyaml4j+zb/5s8HgYZUEsLY26nmvuflcn52VAOJYTqd9u6VjeANgtKQumQV7WoZdCzkQCAQCX4dg9H73CCGU9yVbKRXHcTUX2hlCLRu9vV7P/tIZciVJ4k/JEtFisfBln05PT/3hkZTS14iqDG+beVmW5+fnWuvKRK8mVCvOz88PDw9t8vT01J9AVkpdv37d2t5xHI9GI9/g9OlYvGgaxyaHw6HVWQFwcXHhTxH0+/1KzpqI8rw4PXW1y7Os05i+obt83q/LquFwIBB4FenMGWKlGcHdb47etkvodNcM8rWdOxgNXTotaCEENb2WiFoChGVZzj2JvrOzVudcvWj8j4y+rUWV7W1zYzZZ4c8wl0VRekavkp6kUoVXEmNMuZjrvNBaH+7tPfnyS7tp7/GTw2fPbHIymfivjF6ec9u8a5m1RESqdSE6F4X9teoACfgr9xjUXfVLrg+AZk8AlUV/+VsLAEptLi6yeV43zvHx+aNHT/f29qokMXqGrca2EHR6+n3/c0qaxn1vyaI0rdWqlEKawDf5u6ysBbdqEAgEAoGvx5Vv5UAgEAgEAoFAIBAIBF51gtEbCAQCgUAgEAgEAoHXlhV+NoFvjhDCuq5JKavFbLHkI1c57tpkHMe+XzTaLnNVJtYPOYqioih8L7LFYuEHaAGwTshoe/8CYGatdVmWQgh/VWEAZVnaqDAAWjs3vGrrYrGwCwJXDtLWv46I/Mjhsiz9pYmNMUTkl6Qqhk0C8B2t0zQdDodRRRxJ5dzRojjyVwOO4lh5WzuVvcwlbKUb2VfjK2SxepeXeExeVuxXHLqiSQhXbPhOqHK+qjlXnPeqQwKvErb76l7ObroLgbh9e6w4Ynlnv9skwPfaJbRDMKr4YCKgcsF2B+Z5fnFxYZOz2WzhqQzmee7HElePl82X6dIVxr1ikKDWmsCX7t/AYMMwDMOsDXtL+Cqp0p4LBk7SVHnduFRRVWP7SxvyolaxvBsDTL5/M5H/sd5v1O6hXwNj2Bi3OnuRl/N5Mcvq1+J8VmaZKfJ6swCRFErV5yNR+ae38S8v1UsvLy26vMSSjNfviureCQQCgdeZYPR+90RRNBqN7ECkCkytzMiOldsa9zQ6z/4vPpPJ5MmTJ1a9yRjzySeffPjhh3YHpZQfW3vr1q379+/b5Pb2th/Tu1gsHj9+XAk4n5yc+EJWv/3tb7/04rVms5lvAz99+vTv/u7vrFVpjCnL0lZ2MBg8ePDACjIXRbG3t3dyUut/VLpZ4/G4SlY7PPOCwZRS77zzjk3euXPnnXfeMcacnZ+d5WfnpYvpffMHb/34Jz+xyYfvvHXzxq5NJnFMIHIvcZZGL73U6yQDhTDG25vQErJiUMsubxAAw9Aq05XhZdtBE5e4NGMAECD1knHclTLgK6kyXJEtLzXUV6cq79WZ81UNUv146aYKeplbyopj8bKtBFwV3nd1XeqGWnEVVmSLlTm/hqyoLa3cWrPiAq7YBLDWZZ5XksUyjrvqA/7DS62sCARqBY+K1pmImNFIGaG62J4BqYtCNzJIAKSKfDtQKBFxZM9HQggpiYiBvCzK3Knlv/feP/3t3/6tTWZZdjF3Hzq/973v3bl5iwe1DoIQFAslmk6eiCClqwRDQsIX/ItlHLkYYMkCWbtBvAbghTanC73ItNbZ/un8hdPTunnt5saP3rTJazdv3n3zDZuMx5tS9UGXv9qYoImM39LtjwdGzZhcVLNSkZIuK9KSIMEAVWHD/q208rZi+Kb0xeli78WpMfWZv3hy+l9+9ujkrL4Qs4vZp59enJ3XF7SXyj/70frt67WdTyTGk75XKAgB6XVXcYphZfQSSPh3TffuFZLi1tfbtg28skLfjtXm+IpNgUAg8Mpw+Xso8G0QQviTkJU8VWUW+kpUXxchxO6us+uyLPvFL37x+PFj+8t4PB4MBjZ548aNzc1Nm6x0oa3RWxTF8fHxfD4norIsfUXl/f39g4MDm9Ra+5Oxp6enn376qc0ny7KzszO7w/r6eq/Xs+et5LLsAkjVTK9/Lq21r8U1nU53dnZs0nJ8cvx//5f/OPzIaVxtXdu+de+2Te7sbk/XnC3dgZiJ28qe3mDXEBjsPvIDAtw2ei/HgCXz1dsBrNrKYH25BQgADJYQL5l5WbUVV4xU+IrfLaslULHy8JdlTisyX2E9ApArc35pU6zeKl9mUV/FiuoAoG+a7evGiiv3zw0zm7I0WgMQStWCQs22ltG7dPO2P0oKTyYYQPVousM7XzBZG+25z5AQfuYkSHoSxJXRW9k3Js/yRj8JwOPHj9977z2brNxzbHJtvJbNF0lUm9NSCKXgJm+JAAJ7J0JLTl949hUAFAxvGR4QtT7alMzzghc5a60vFsWZs73XHl5/8PCeTU63t9ev3bBJxAOI+KpngQEtYLzG6TxRRpQG7isACSOFt4vhZqa4862yejqvvvXafUa2KA8PLnQzff3k8elv3j84PK6N7SzLnj/P5vP6NTceCaXS6Xr9xiGiJI28Lx4Qop7arZAKsS0ItW+6dm2lJLt40+8Q6t76gUAg8Dpy+XsoEAgEAoFAIBAIBAKB14Bg9AYCgUAgEAgEAoFA4LUlGL2BQCAQCAQCgUAgEHhtCTG93z3MbPWKq6QVQKa2drExpqNd3BL8JPLFnHu93sOHD2/evFkltdYPHjzwhT2llL5My/Xr12/ccIFVcRz3PIHNra2tt99+uygKIppMJv6mO3funJ05yag8z/M8t0kppS+wXJZllmW2voPB4O7du8NhHXybZVmWZb7Uc1EUVtcKABFZaS4Aw+HQj/idz+cnJyfGmOOTo4P9g/09F2mcZ7lf2a54JnMlXVNBZEBtWcyOgA20FU9ZqR0VCAReMWyv2wm7PTw4OHjxwiZPT0/39vddD0xE5DoDQaQ8IUAVqfXNzV6j/yeE2NjaGnkSfTKOyOvqRVtAi4iEVDaolJnLomAAzO+///7nXzgdwffff99XWNjd3fXlCd944/5kMh4OaykHAimSLnqUOr1eV0UuO7/IPS3o4myenboXSm80mmxu2FoopYa3brA2xpgf9Xp3fvxju+fGtd7ajqfePBjA68YhYj96lg1M6eJpWYBFS/Gt05eTkMITweqKYhD50lwWZi7OZ2UjvwxgMZ9nmYsNHkwn4811m+z1kp2dDXvxS4z/+I8np+f1m0spPRjMlKqjqZNY/ODhcGezfg8S0ebmpt/QhsFtjcKqjO0bEACMgfem6oaZd1g+PBAIBAJfnWD0fvdURq8dPPlGb0c7tGP0dqzlyoi1w6wkSW7fvu3v0KEoCj+3NE19A7JDZWpqrYUQk8nEV2/2Cw9gsVhYJSosFdKvHYAoiqbTqbWKF4vFs2fPrAltjCmKwjfUAVgLGUC/3/ct6vl8fn5+Xpbl6enZycnpybGzloui8BvTH18CALM/lGDB1NE4aQ0f2N/UWXckEAi8ulBtu15iLpydnDz2ZOqfPHny0Ucf2a6MiMhT4JVSJkliLa4kSe7ev782rT/YSSn7g4Fv9AqphK/n24HIV4ZmrbXWbAwzf/H55//4C6dc9fnnn/tSf3fu3Hnw4IFNXr9+fTgc+J8sW4v7cGV+tTs0L1XMF3OvU50dHJ/vHdrk2vb2eDy2XatUqre1VbXkG7u7aISOASCeIXLvCFAlpGxRqHW/AIANTAFuyskSSFpGr/epAQCYWjax6Lindc8lNXN/AAAgAElEQVTVwFwsFrmntnV6cnJ+fm6TJIVv9CZJvL4ee0Yv3npr+6Kp03CIN96AvbxSYDpEz72pXmK7CnGpYQ6gddRLYb70Rg4EAoHAV+Kyt0UgEAgEAoFAIBAIBAKvBcHoDQQCgUAgEAgEAoHAa0swegOBQCAQCAQCgUAg8NpyddBR4CvTCXM1xpRlrXhRYUNzOyIcQgil3CVgZj+YtjrEjw0WQnRlPDyIyD9cCOEXg9oaWkKIXq/HzETklwHNeS1SSn+HThmqMtvzCiG01lYvpPrDBt8SUVmWs5mLs2LmJElscrkkURRV/xciBrk9GQnDj1huHchMzK6QZIB24K4PAQpCeBovoh1WxiS8zBzEBCLmK/IFGIqv/q5kIF7y1enqnAGABFaFH19xLOPKTRXfLNuKl2YO0dXSaXHVJmr+W8Hqrbwq85e0c/eHhpeVanW2WHXoHxQvaYarrptl9fGSRBJVEZYkBNtYUmCRZycXLsjz+cH+x59/ZnvyLM9Oz061rpNRFI3Go0hFVXI0Ho031geTUZU0BNPuYTRBX11yQRBewVmQiFTVkd68dqOYOb2laxtbP3z4jk3evnPne9//gU1O1yZRyZjXQoOEKsDVZezf+Gz0xf5B5sW1fvbbj596Uc1lluvFwiZvF/e2dieqiUymJBbJsA5OFW3pg0giqsW0avyXCEn/ASQJ4fcxwrDMGc11oe5DZQwxu6BlgPyGJi2hCUBe8Ivn5cVFnY/W+tEne4ee9mFR5EXhXogPsjM5dk0RRaqXJrbYo1F+49pZltcaGWkq1sdpv+9eZFJIY/zem9piiuTH9Bqji6wAQA1uP5JSea8q0blp3LsVqF7NK293crHTX5MV3f7LThoIBAKvCMHo/Q5gZl9BqpKnsu+qymjsSFhVLBux/huuMSebsQKRr2u1TMdiLMuyKJx2ZedYKaUVr+qUrfNWllJGUT3UA6CU8s3UDlrr+Xxu1Z6rP2zBKvVmX8jKGLPC6BVCRFEkhIiiWMikZfRSasgZvQzVfmUTs1cpXmVqERBd2agAYOSV9gtDXLUJgFkawviYq0cZNS/Z/DKd6asOv+r3mm+abcXqrVeOyapx7OXbAID9ofwyq8tcZbtqjyvPTFdvAkArv1lg9bHdH15vXlLdFQ1Vsfr4q7cShJS14hBrzcZ11PN8cXTuNKKe7D3/8JPfWqP3+OT4iy++zIu6K0vTdHNz03ZWGxsbD7//vd2b16vkstFbAnm7VH5KApH/CzUvAuZbN25OYicr2HlHTNbWNnd2bBJaI89h1fWFgFItg9PDlOXp0yenT5/YX379s5/9+te/tkkVyyj2vm+q4p2376Dp/AX1SChqd9E1KoG68qUAYpBrdgKaC1JRAjPAvao6EI+Ndg0CtN+ShlASgPyCP/+4ePGiNmuLovzFL559/sUju2cURf77JZOjjRvu6q+t9ceTxLb0WGS3xV6p64aNomht7AQamcmYRBv3ipFSdl7l/uUts3KRLYDuS5yI4ph8oxeA/zAYY/zv6UIIekmfs7onvApa9QgFAoHA68LqDjQQCAQCgUAgEAgEAoFXmGD0BgKBQCAQCAQCgUDgtSUYvYFAIBAIBAKBQCAQeG25LD4n8DWhtkZUJ+zWD5G9LERnVSyNH7yEpZyNMf4OndyorVBFbZkroKWq5W/qFJKZO/l09LH8CgJQStmctdZaaxviq7WOomg8HtudAZyeusCqwWDQCRi2gc1CqagJqQIgLouR9vFDn4gvCxrsNLyX5E64bfg0FAi8+hhm44kvTKfTN996yyaTJImiyPaEXz76koSwqntpmm5vb/sxvTdv3rxx40aVFEKkaep3jEYI9l8K7f5Gl7rImkDc5g1SddFJmk7W190m5kqFqyJJEj8JoFaWsrT3hzE2yUVxfnp6eHhoN8ZxfO3aNZtc25hOtzds8satW9Fk4mQIIwVdolICUwrdEFZHpwggrrQE3Q+tFxkvvQM7b73WqRggX0fBoHpZ5Xnx9OnTzz8/q37WWp+fX/gn2tlZ3/Zqd+fO2nTqQoX7/dgvhhQiThLVSFVJqXydqqUC1+8p/xf/1KJRrKSlmN52UyDP87J04c1Kqc7L1/4dCAQCga9LMHq/A6htXnasRHjvKq21PzCSUvoiUtXQxyatvXfV1sqktL9EUeTn1sm8Y8r6uXVe2EVR+ApYcRz7hmilj2X3r17n/svYV70yxvhyzcaYXq+3tbVldwCwt7dn/2bmyWTiJ6tiM7OKoqRR3gIgL9VTaSDRHpcYoFyyY22yGpD64ypTD+2atPd3IBB4NTHt7vfa9es3b9+2yR98//t/9md/Znu29/7pvSzPj46OqmSv19vZ2UnTWjxvY2PjnXfeefvtt6skgKIorGo9ABPH7H14o7allOXF+ckZG9eLxnEsBAE0HI6mU2f0mrwwueuNhZS1kVdBhChyWRuDsnQWJzOKwu7PeX60v//okdN26vV6b3lm/92Hb7z5g+/ZJCWJ6Pdd5mWBxRxGgwi9HrxPkB2YW2UEmKFtN9p5kYGY0FEa7Bq9JK809oyGNgBjNlv85jcf/fKXde2ISMhYCPeaePDg5o9/7K7X7k1cv+5n27IopVT9fp+5vluEEMufWTsmaPtzdmtnKWX1Dq3qvvyWt8nFYjGbOaHHwWBg1bMCgUAg8C1ZZTkEvhm0NKf6mvFtakdEnbGCn9uKnDtHfcf8c+YdCAR+DyGi1ldCpfyZXiWVb59Uf1+VvIQre7KKythpdX3MVB3m93WdDvOSjuqrd4z1OVsl86sgpWx9TJQSRC5/qov3O+dlJ2UAlaXtf9iljnY+EUnpKis6H0aXIHh1v6zhvxmrX2TLFygQCAQC3xVXv7MDgUAgEAgEAoFAIBB4xQlGbyAQCAQCgUAgEAgEXluCe/PvFCGE71AnlqSn7N9V0vdtu3Sr75y22m/Kz6pKXvo3PNUNm/Q2Vk5irTjkTs4+VQnt/kTEzH5YHdoxwH7OaA5nZiEo1kVaLOymXpn1S6cEE5kC5CLfKrUTlyJo8mJ4a9kYu52IAD/d+RbUdpOzMMBoxa4BoLYjHF/tm8dgZheS3S0ECKTgS7Z06chtoZ0UV37Sou5xfoouydbB3Nm4dOnJa2iA25I2JJia69JpGbL/uwxGde6GzlnbxzFzJ3y91az13+4n5laZ3c5XFuer0m7Y3xG+e2T1t/2lelS7l+x3w5X31Ffi2x1dYwjGq7pB6+llIkinVqQJ8zybZXWfI+MoSpJ0UMsKJL0eSeEdzhCC/L6dyBdvWizm8wsXq7n37PknH/7W9oTDwfD69WtxkhCgdnZ6kQvjJMOk/WKS/1jPzs+O9vassoMkiqWrg5Ry0O9HTWdOhOn2ZsGeXkMUxcp1v4P1CRKvB1YE6UfbMhIJJoBYMYTruzTlmlwS1NKeIoAgXDZE7D/ADC5jmPq8hvni3GSZq/LxycnFhRPfWlsbT6drNikEK8UAVF/efWsLibvAMhJ+MPC1+1F/3QVdR33J7fFPu/MVwsR2B2Iikt5DTAThP9JLjxT79yxRLdZFVG2yMFGrY4si5StodMRBAHhlCAQCgcDXY7lLDXwHXDWsXA4Du2pPANQ2L6tf/GRHqmpFVrgst6uIomiFYqSUclUkGwDvECFEFEVWikNrbYzx5V6EEH1Pnqoj2mHLHAkxzOfT2YndtL4428jObbKvLyDmNglmX4pKExbEdrwrSMQqtrUgkID39YFBrfFM9dMlo24DNihNM4ghgKr/NTCwyujlwrDXFBCChLWZCQoYgK66ZAwqgdbnA/9chAh0hQIKtwZOHbsUpAne54M2DDKeiUhEgqR3gxDYC5Vj6EZbtUKSriwFRid0TYClb6UTwSslM8M0qj8AhAB5YqodjDG+Elv12cW/jYnal6ndAuI7CuVbalgv2382mNkXt6vsf9/oVUp9xX7gu4TRbouvB9Oqjz+Mq5+xNiWh9LouEvBvIlaC0sjmVZA5Oj87OD2ukhRHvclwulHL/47GExHHpf/EKdUKiNWAdlv39g4/+/RTm3zv5//4f/7v/8diUXdZt27d+ou/+IvpdEpE6U/+ZH3kjDoqjMy9xzyCL9d88PjJ3//n/7ywEtNJvLG+Fse1HZv2+/feejhZn1ZJSbj7g7dv/vBhlQQgjCbvsZL9CENnA4MIvikbAWm9ldmw13ct5Hzh7SmllOyaQiGJedgy1v2vTBp8rmyXUxT86ON8f99V+Z9+9atPPnNN98Mf/uCP/9i1z3CLp3c0EeLN6L/6X97+88IWg1nNIF0h0yRJYvcGSUXf8NAmqf14EitpRq6UBPK/lxCEMpAr7rvWp0Mibi4aE+lOt2K/AwJI08Q3epfe6a2O67tkRVXwz3XOQCAQ+B0TjN7fKUvvsJewev/VW78xRLQ6587WjvBGx7rwc6vszM7+qyerbQ6CjTRuXKWMVt40qYDuTNv4SQYbslKpIALI2bHd1323CLhqXE317/WJGGgN7OrfVmAAb0zZHdiLlx3eKlXHuuZL6/GVuLyyliXj5cpTMZYMv/rneuPSjz5+nl9bGW55ttNLXnKbvWbYKnNDe/sfFlfdZ5fcguQcNRjQRpfNFwTDRkin8ySVbBkrVU/lJYHWE6mLcjF3jipnp6cvnj+fN8ZqP+1dnJ2ncUJEuvRNaXQfofaVLIvi4uTEziHrXtpPlCnqr12CyGgn5kxESS9NUu+lX5bwPpEgJnR1kr3zUdV1AgAMw7OWDbRufYBj35GGwdXB3g5tjLQdIZecL8T8wnWkJ0fZ/gv3ffPsJMtdQ6IoYIiJQIpGaz23AcyK2asOgcjrb4UxS246PkTwvg11H6CqRt1f27S2dt6ZfsJHCLGqoQKBQCDwLXjJlF0gEAgEAoFAIBAIBAKvLsHoDQQCgUAgEAgEAoHAa0twbw68IrT9w4wxfuyiMbzkM+Y5thEJYvuDuCRmt+2KttLBrIqSrP5kwV2vRg9u59xxNGWw8KNYQfb/9Wbm5kSXQO11JgnUjul1dL1bGf725TO082nVjtDyDV5RdwBE9X/uF/fnMq2NSz7Jyy2xKrOOz3ynnP6dAwB8pUuhf9KVdb0E7lZidWt19+6w4uDWTcWM9s6VFFz193JT/EFBK5X/lrf6675WodG2JZcvFrd7ETaGvZjeo6OjTz75xCYPDw97aWp9gEej0XQ6XV9fJyI/pBNAWZbl3KkVzE9PzptIYAAvnjyZz+dWJSGOozRJ+/3ayzft9WQUuRjg6nSdkreez6V7o1tNBqHqQFr3GMjvygCU7LydRSuIA8zwwsxRLvTxs4vsrN6/KMyjRxd7e06kcDab+1HocSx6nhdzHIO8K2n/4qqoHktd2VJlA4FAIPBaE4zewKsBtS2ZsiwXCxfaVRaFH2MGgq9RI1jE5FRHlob+zNw2e/1hFACGL4tVlmWRZQBICplEvkBoZyBlYEpvwFfqstRuLBhLkfiCYZ1BGFNZGHhxy96IDgArxR2Vq24OAKq6eYN1MIxxIbJEkJKE11ZctYaF2tl2DIP22HcZKX3ZHdicOrmiHm7XP3FbfgmA1kZ7GrZE0QoxtUo+zSarEtpyaq3zPLd2LxFFKhHCXQi/9u1vFvAbaplWOwNGt0W8JFz9l+gc27oEAOBu2k6DV23l/+LvYI/yf/GTfwjYW60j4kVtlXYhhS+kJ4Qoy9IqopVlWZalvW2q+9O/iTVr4/cSeVkunJrae++995d/+Zc22Yvind1da/S+8cYbf/RHf7SzswNgMl23uwE4Pzs7fvrUJj/97Uf/9A8/t8k8y2anp/YGiCK1vb29sVHnIJMknUzgbEQGaXgabxCi9Xx25PqYW3cwgUX9QBARyD0ykqC8pihMkRmnIMUkU+EEC7TmLDNWl+7wxfnf/KcPnnx2VCXLUn/55Yujo7Nmd/RHg7Sf2uTamtrdtSnQkIS85LkgEgzB7a+K/vUiqjsdmwwEAoHA600wegOvBstj/bZKbUstEyC0xjck6MrZPABtS6drkLVzBjeTzAIsWS2JVzkYLWPasNGeFpcR3ekRHwaY4dS3APIXt2gtsvMSlgwqcDMEZUbHemS0LD20ZZ+q0aXb+jK6+37lQ7sGZNsGXrYJfZYtvQ5aa9/olZIvvQzVJbBU7b8y4xadmV5mrK5/p1KdpK0Rc9e5wN9zue4v1Vr/w6Hj4sHodBndmV72Pii8fKbX2wrAGHePYWmm99rW9s69B1YkfzweVzO9AKKlmd6FN9N7tL//xccf22SlTG6TWus0TQaDQb01jlszvWDAtO5ptB9RQqtJmLs7cz19SpUJ2UAQwjuQwf5Mr14SjNKadTMNPp+XT5+efP75QZUsy/Lx46cnJ05m+ebtm4NRXSMAUUT+TK+JoZsOu/tcrHrasPphDAQCgcDrRxgPBQKBQCAQCAQCgUDgtSUYvYFAIBAIBAKBQCAQeG0J7s2BVwACIpI94QI1ZQlkzoOunOf+MphSKuVFdTKREeT7s7XdGiv3uJa3m5/oBIPVRwDMxNz2M2771xGEv1mQlOQ8/QREO9uWK2ElS9VyLX6ZO17b5dI6W3Z+po4XYCdXAtoKMK3tXP9ruLRIzQ5tz8iaq2vRaTo/vpA7TrudTDqepcytSnc8fo3h6r9mK5gNtzww653pkir4elrkF4Q716/CrwRhKb8r22LZe/Yrwpc5P3d++YOCGcy6ak4hxIqmoDoIwt4YVB1cb2Ym74JVf/tXv3N5iY30AvIHSbQ1Hdvk5tp4Yzpx7s3DvpJE1U3IGsYVUhAr5b5NJ2kyGA1tUkoVJ7Gt1HAykXFKqun6pILw9e4IEK0v3STgBTYzuH2Leup/ALyOgSFsiASAouTcEx+Y53SWeQ9UpAdpKZquzxiAnI6AisRgFI2mdTS11nJRDOO+K8b69nC62bfJ3jCC02cACSYyVcFa3SkxsSBP9qDTyVPH+7nK0v+tE+HsU29q59Di6mMDgUAg8C9EMHoDrwCS5K14/fu9G/aX6THp3x7a5D5/cVE6G3g6Xb92/Zod7ZUqWfQki3oA1ITa2nEJKRJ+tJ+g1vgpgoi8ARCz0UYBECBTkB2hEpGUqhVCSUZ6o59YMnv5SNLSk7liZuNF/IJJSQEXbUrUCqNjaosqaaN9QSOjUWlmEZFSytfskX4+lQnsD9brob/7wfsbYNJe9HRlT9rcmKkVM8jQ7RBCFZFUTXO1B5htg4EIQnhtJRTB+15ABHhNV+TlYuHFEBpdlqXNUEoZx6kdZJdaz2Z52dwtQpCQTLJWiyVAQAmSABhkpYYAMHOptTVHCUQUtyO6W21FVAjpSkWCfAMDkID3XabB/8X+jaap/V8qqt1cqciplFVJ+/fvM6vDL9ndcZewemupy/l8XsXS99JeRxvZf+ojIWUU26xiklyUOqtln7jQkilqrqCCUGgJybFh9rTW0nJGhVNj+tP72//bf/gfbHJra/uN+29ao3e4NlkfiYhmACif+zfSINZqa2ST5cO78M46GI82d3dlk08v7a1v7rioYClFrw/3+Y8holZrUespNITS22jYfRsCGoFmAoCiJK+uONjjw32357Pn2WdfXtjkzja/9aaIGtO914vX1ydxVJd5upP85N/tPvgjF7VL9MC/b8ejUb/vjN6NjSGNnRYXKV0/ZXVVvPpwTMa/3K2bTLL/BRJU/7NpA1VceWcRgdRKRznGUiTzV2bFw/AyLYcVhvpLWHHSQCAQeE0IRm/gFUCAxrK3Hbmpkt4cfDCzydno5GLkTAgFubOxZUdOBlEBYZoxSmX0WrkmAhhCesMs0R4CyPaAgCGZBQBmYuNNhlSWmjcmlR2VKPInHgAUBKdxamDAZIdZBBAJ31htG71dmLklHqtNWWigkrppGT9iOR9/pES0SpqLfR1rAJWV1SQqtVd/3PxVFYy7gzki8i0hktzR2vVPo7XJczcOrkR3re2nVESkRPPJQ2tT5Losa5tZSNK64KZWXOVLAEAgeFeT2RhTekav8NfBavDSgok8o9ebRax+8P4GUNu9ftL+vdp27ZjHrx8dd4qvhWGTF/U3jjiOfZG2znNAREK6F6IgwdqwFaMyRnhGsiQSbaOHDJNnIipTKO0EqG5MB3/6/TdtcnNr+55n9EIpSgWoAADN8NY6iiSrgdOU3ticZt7WycbGzXv3rFcLMzF7c7CCEMWQXjE7XVsb439JAgxaNjB538sKRuHten6G432XfPal+PR973mcZZub53FcF0Nzf2NzoqLGBh6o6/dH64v6QRNCjEYj/9tEGiexci3QkQMk0iTcU+ZBgmNid2AH4tUWIkPqq/cgYLXR6zfk14JWXaGXc1WBV/NtzhgIBAKvDCt67UAgEAgEAoFAIBAIBF5tgtEbCAQCgUAgEAgEAoHXluDeHHg16MQ0sreEJgA22jki4rJlXdtuX9z6iTrrUTLQ8fi6woP0Ja5ozN1sVu9P39Q7bRl7mo5j7KrTV7ykjC+BrvYI/G7xr4jheuXkCq11ntcxugCYWUrfvVkXRWFjeqUhY0Tlr/61+RYNFfhdsto//AouuZGvyqe6G7u9hL9z+0BuLzNORKR1FSdA3Ha6Blo/EFF7MWG3aYl22Py3xebFgDam9Fyfy5I9RQVo3e5+a/U81yfZTeg2TCAQCAQC/1wEozfwCkBEvV5vPHYxvXt7e4eHTshq/rQ/+8xJofzgBz9YX1+3mlI0mojBxAbsFbo8nZ2VldATAAZyF4RFRGmaxJ74c25M6kWySin7gz4AIgirjwQAYGMKa4ozF0b74WdKKeUHDQrjR9sRSEine8UsWcMLEgT7pjlByFYwGxH5mUuKlIyq36V0Zaz+8gfnrWwBkuhEUPpDZyKSUtj9ifyxLCqT189NtsOau2G5K1kxGs6yLC+cWfvZp49+8+EnNvns2bMPP/zQGhXGsB9XTERRFNl7YzDo/bv/5qdvvHnH7jCZTAb9AQAhpJKe3i9BCGFH8wTRUj9bhlrKVcxcaBfoKAS1rj6RlK2A705Mb7epvU2dA5fpZOVtef1RUg0Gg+oDWRzFrZu5ffXKsvS/leR5TkT2PlFKDYdD2wUNh0NtzGzmZAWyLCsKd32HQqiRE6CS/b4fp/rs2bNf/eoDKwWe9HrrW1sqiojo7r03tnev2z2RpsK7vqN0INe2bDKu7uTm/iYhEfmqdUSoNaErGPAr3THSSwNfdFkITwMLANXHGq3fe+//+/jjL+2WTz5YfPFbJ0+gVBLHqU2WZTSejNO0Udvqxb7aX/U8MteNU7V5+y5tXSYCyeYDFgCAr9AgIFpp9FP9LxAIBAJ/KASjN/AKQERJkvgangcHBycnJzZ5cqqOD9wAbTgcnp2dWWMgUnHPm8sz2swX86yoR2lsoOfMRWPMEI1Go9SN2cCmZM927fd7/eQSfRRmLovCn8ApirywpjXA3cVj2kZvNUhrthsjNJO1tZlh2krIEoY8uRQlVWssKCQ8G9ino0RV5WwRgquxcUVn3EhEdUlbvzQwIFpTvV2L+puOMjvHlWW5WLgVqp4/f/7+++/b5EcfffQ3f/M31gIpy3I2y6xfQBRF4/E4jusruDad3Lm3vbk1qZIA4jiutioJ5bVoe7YKVOkxr6gRkR8/UprS/wICGCnY1oyolflXZ/nAznxjd/qxc8led4QQ1tokrLKDtNFZ7iy3yhfAtpWUMk1T2wWlScLGWCOZmReLhW/0pgOFXs8mZZJEngV5fHz8D//4D1Z9bTQa3bx5M0kSIlqfbvpGL0URvM4o7auUPEu0LJHn/jNGSsLvB4z/NANtl5fO46k1Cm/CNo4hpbvDucnMGP78sy9+/vP37J4f/NPZb399bpM3b9588OCBTRq91u/1e/262EksWxL3ICml1fQi70PDpRB1LqJY6h4qiFbf6d3HIhAIBAKvOaveLoFAIBAIBAKBQCAQCLzSXD4XFAj8XsGMRR5dLJx/4Lzo594EpUQ6FG5eZRRtD5Mt1czTSTWMtawWBAGQXeiTzy/OzmvXxLLU+8+PZxfNJA9BSiW9Sdg3b1+/e2PHJgFRTR0VhT49WeR5PX2ny/L58+dnZ83inASllO+auLG+vr6+bpNJIgaDZtVaQAioyM1ZXJznn3+6P5vVMy/GmPl8YRfaIYHBSCepm63Y2d3dXN+wSSlEVYMsK/cPzrKszkeX+uT4PFv4Ia+tKNzrt6a7150buZIibhYXAaCN0IXbnw3KUremEo1wSw0ROtNOEepFgBlgdpMt1dSNrXs9AWWzJQCt1Z6UipLEXe7p2tbNG249mPOzcmvjczsLV5S6n2amWVe01+/fuX17OBxWyeG4v7l5LbW5ESIVS6EACFGtSuLKhdakUmtRpWWY201LZOOKq7TW2s9veYLLTlT5IaPLs1fLv7xmfMvqee4TrRW3OhO/yiDxvgL3RLSW9PO0DpoYylifz+eHtXdJqWYflb960qsnfhmcZVnpzZO+/eDm+PY1m7w4PH/2ZM8mz88WaTJSqn6cR6O1rc1rvX6fiHqDNShvdVkRw5/a7ayUJKXvgmwgSu3cQ4gghYsvYMY8N7kXi3t8fHx66hYTvlgUZ3M3WT0ZD7Z3pjaAI47VYJhIKaBpbbx589pdu2ekL3bXnaf37s7O7TtuTfV799eHwyhO6sGGkgLwV3cSKkqoeTSISCnle+yTkP7KYMytoA8BKf328SCIFdO5RAyxYrMBMa5ca1e8bKaYvvVtexmrz1lvfslOV/DPUNpAIBD4PSMYvYFXAMN0vkgPTl2M3MVCLArn7ZzyeKzWbHIrebA1emCNXsREhbS+wOf7xbN/OHjxvB6/XswW//ir3zx7UUcIM/ji4iLzvGf/w//6P/f+/U2b1FpU/obnZ+VHHxydnNSrcc7ni7//2c++/NKFum1tbo1HzoB8+NZbb77lqrA2ibe2nONikmAwdEGgh8/O/uo//erZs+MqWRbF/sHBfF6fS22OI1UAACAASURBVEq6dnOwNnWD45/+9KfpD90gO40pTQDg7Cj75T88Pji8qH5fzLPffPjZ/v5RlSSAqBVB91//93/6b/7tH9lkrydp5AagRU7zC+cSWRbm4qLUbuFQgomsKUgC45HvmwkBoaoKMoxuWbUdg6/ry51UxnJNHPXiyOV78/obwuzapODx558cZo3RWxZ6dpGbppDr6+s//elPt7e3q2ScyPt31kYja0JTmvZVlAAQkATpLFtGd73Y9gKyXP+rMcSGPBOLyK3LCmhNRVHYsWZnKxERke+ZrLW2Rq9/vTrJ6hc/ueze/Cqyeki+wngBANQtorU2XrhBZRLaZKRJeS/EaZReH07jRd1rTFQv3zs5zeozlWXx4d/+fDGzK/Fy0Q5tiP+n/+7BwPnMH36x98GvPrVJCDEaudDc7e3t+w++PxoOQTTZuIbI9RJQCsI3em1tAACyFXdrNOYZlc1NJwXSnnPRNwbHM3124Qr5q19//sknrlQnx6eHjVUP4NatW++++661P6fT/v27m0kqWIsb2/eEnto9//h7CyWcZ/j6+tQ+XwDSQTyZptQYzwwYJtdUJJN05AdFdCN6Cca7/trAu4ZQQkZXxHGs/iYFYkg/3KCDZuirjV72Vie/DFru0r4aq8v8cvibGr38socsEAgEXnmueFsEAr9nMMN4AwJmwd6ogiCFdzMLkpKU8CcHvcEAGda5KRvNljLT2byYz5oQX+aLs7kfMpplpR/1au0xY1CWpsjrbUWu5/P84sIdOOznSeRmTvJca2+aRWuw8WpUBcw1243mPCsW82a6sihmF4v5vM5cSprPVdpzh5el5lb71FkZw0Wh82amN8/K+Tx309pARzamyLVfWebWOIwN2DNHjYHW7IzeyghsUoLB7aBB+3f9h7fJH3HVhbdblwZjROT/KqWMIhdlrVQsZaRkfTwbIaUzT5WKk6SXpvUXkzgRUkWe9g+IRD0BuDSDSu1Z8S6rtlW0MmSGPaYyce2FWAr/DnxzWk9F6xr5M4jdu4xAUgjZ3BgCxMYYq45W6nyxWHhCVh2jtywKf0bSaOPPAwsVSSXsDSaEVFIpFaFyB/AvPYmlovm04lvr5685bX1+uwOxYTQeDwBQFDrLnNPHYpHP565nyLKiKFyvoku2vYoUMlLuiUtjk0Susv1+3Os5UzyOpRBkjV7jP9oAqse59R1nVYXRPRor2ycQCAQCgZpv9DEyEAgEAoFAIBAIBAKBV4Fg9AYCgUAgEAgEAoFA4LUluDcHXgGYeZ4vzuZOc2U4GE6nLqhsfGtzfGvTJje3tqAAG8xG0LkXm8lqNBoXeb2518/u3L7TH9Uhwcx8dHR0cVEHwQJYn67ZRSYBRJFofPFMlmV2rc75fH5+fm6FrIhobbzmezwqRb7XX5rKKHZufSpqeTVGcbS+vqF17UNYrRpqzyUlrU9744nLrd9P/EU17VojQpBSyi6XUpYmjmN/ydCOe7NSqrOgiFcDzOf5wcFMNy6Ss9ni+fODLLMu3IJ1jGZxKCnFtWvj8dgF325xT6gElZ+p56S4mGd7Lw6yhXWtJN9VmwjpkKLU/TIaDQcDtyyzEDwcuspPJv2NjQ0rZJVnpZIz3UQ6jsejtbXR+noda60i6veSOPZ845sGucTLsvNT10uzVSm0o22JWm6bAq0Vj6uTrnBpXrFpNZ0Dv3E+ryHU8qoFkRN9AkDEzDYiuizL09PTah0jAEbrLMvs001E4/HYf6wGkzU/nH28uXn7/n2bFCoSidu6Np3219aSfh+ATJJOMdzfgC510ZQBgDY6z3MXti0URX0bhSsEmGGfX6355PR0/8C5ZB8cHBwd1eH9AIrCpP7ySGna6/VsqHmSxFKSECDCcBgXhVOSSyIZe97Og0Eaxy60RKlV61lf8aRdSesRCwQCgUDgKxOM3sArgGFzcHbw5YHTiPrX9/71uw/ftcntN2/uPrxtk+Pdsei5kVZZ4uLMrUZryvTWzTtbm/VgsNTm+r235o0IszHmyZMn/ljw4cN706kbCw4GVI0qjSmPj4/29mqtqdls9uTJEytkRUSjwXA8cpo0SSK2ttxIcTCkkVO6AbXHt8PB8J233755s4nFzfPnz59bo5cEJlP0nN2Hra1JI0gMANREPEsp0jTt9erKCyHHo5GNQ8aS0dvv93wLEEDmovywv3/66199WjTRiXt7e//4j7+wArDMQhcxm3q8myTxj3707o0bbtHRd//oloy2AQiBavRc8eTJ0X/8v/6f58/2mx1JSreYpxDY2BWjibME3nnnHX8h0CRKrl1zDXt+vv3OO2/bQs4uFnsvjmxya2vjjTdu37hRC18JycOpTpr2ARCpqDo1MVVj8oqOiVRbvEt2r0UQsWe9dLSChZBCKD9/4EqLtBPu64ycqw+xvHSHP1w6Vi5z/WA3W41hu7zzbDb74osv3HKyQCykjfiVUt6+ffvWrVtVEsDuvXvwvsrd+t73Nq85nTkohTi1t4uKomQwqJTeRZzAC1DvsFjkLb3l2ezw4MBG4Q9Hwxv37vSspjRDa1gbOc/1Z599+cmnj+s08NFHH33xxRc2ubmxvbPjntb19fXNzU1b5cFAxImMIjDTjRvDnR2nI6gEK09MTAjhRAQBJjLUCoan+l+NaD84L6Vl9wYbOBAIBAJfjWD0Bl4BGFzoIiuc+RXF0WTiTMbpdLqx4RbsSUaJVSMCwIAundELFkmSimaUphlI0Ni8MMYsFgvfruj3e5G3bI+dRAW4LMuiqOc58zzPsixrbEQiKsvSDpoBECGKvAmQCC3ZUYavFSql7A8GaOR/8zyfzWbWDiSBft+kPVfIKFL+iB2mzo0IQgg7+SOFlEr5QsEdo1dK2TGTfF2rotAXF/M8r6t8cnL24sXeyUmt+MpGlC2jN7l163Q0ckP/xaKs5p2q1rXnybJyf//k6dODKklE/oSzEICShXaXYDab29WbAKQxksRVPk2jwWBgrVywSNO5EHWZ0zTp99N+v/6KQYLjKJfSExkSnpDViiE1fasBNxHwlaNLyFNy9v8G4P8d+FZQd+KX4b4vGGOyLLPuA4KESBJqHmAhRJqm47GTak96PXhPWToYpL6BrSLEiTudEFCqTsrmj8swxrgbG8izfDab2wlnFUWA+9JSGb32+dUGi8Xi/Py8TgMXFxf2OxqAck37PUMURVEU2V+UIkFUNVKSSP+JkwR5ZZFtV3Q5V9c1EAgEAoHvkq866goEAoFAIBAIBAKBQOCVIxi9gUAgEAgEAoFAIBB4bQnuzYFXg1KUuXRLSmIAtebuXjUQMvH9PPNi5pwAs5m+OCyslJHWZBZkXe4EiTTpx0mdmzFiOkkEXMTacOivSQmhgMo1WrBMWKX1eZVhlXLUuBwTgUVWaOdMmJcXWeGcCWMtQS3/Zn8VUZKcpuAmaDCK5SSL46QuNBH3R8aPRI0TwY0vdLVLpQUlpOgP4rKRnkpSsb09ThLnU0jWmxcAMBrHUvku2S1n5zSVk2m/yJtI43K0e22jP6hFpJhFmcdGu5je9Y3ReOKibdOeUhGj9iQ1NmcSUDKJVB2jTAQpW+7NUpDvHEqIwF7TsfA9jY1BkZuiqH+az8vjowu7HqkU8dOnR4S6zFLRBovB2FWSIxEpAYCZjbfUKhtTlqWxbsYg4shrOoqiVogoiFpfFbtr/BIRozm8E6lbbfaT9hc/vrf6cbWH83I+rxzE/lrRXVYunQzAeaF3wqqJ2w7qDMA5tEsSvSjpx7U2FRFJqWxjKimno0mvUa5SSk0m0+HYBVxEUcqeQz6xhHBaa4ZV2QjpASAlVLOSrdHkBxScn12cn7tO4+z8/NCTG5jNZkdHR9a9uWRxY1HYXgIAqucbACAFBv10beJC/7e319m4hcR3dzd3tms9PwDTtX6akFL14bGCIHsdWtejEwbgu4UDYCJqf14n8i8KqH15Dbdk7mjJ67x1RxPBKhZ2WH1ndC//Eiw61fSgqzcBANyTHQgEAoHfF4LRG3gFMGRO49O93p775Z4Z/YnTiBpsRYMtF+SZnR8ef/LCjpyO984+f/9pvqiHd3GcTCbTKGoGrP105913etu1+DMD925ul6WLRE3X08QNBUHERhgAoq/72+WoCRaVs3JyS0+Kxi4FyujZ4YVTndk/23h+vGWTiEcbyp3FaF3qwpZZJdHurSGb+glllreKHWNcHWWUC+mSvX7MNLdJg0hzDCBKo/tvbViD37D5/rtb2guI7QzOxtN0MHbj4CqIzyavqX5/dN+agqen27fuDGbz+rxsqMhi3Yz1lVI3b9xcm7q2u3ajN5oYANroonSqs1GC8eDGxagOiSSQkC7SWAj006wXu68YSkyIPdkuI+BVKJ+Zo32dN5b5kyenf///fnx2VstxTybjo32sb6xXyX4/+vN/e+vO/bqQBIwnk35fAdAl51lpB8aLLDs6OrIh3AJRJDck1bHBQvLmBg2Grq1UKqVnBBsD7ZnQgoiEG3YbY6wycIUNwwZARE5Tum3EMjuxpeUkESnlTLV/MVYGR38VxIqoULzEeEHTzGRINtLiAMDuy1ed9IyvftS7tbY1am5mgv8coN/rfe+tt7c36k5DSHn7hz/cvH3b7pAkfTN3n8pIRqLnxPAWM3F8RGzqHJMe1jZIRQCwyKi5cwHgZz/7+O///pc2eXpxfHDiukGtdVmW9jm6e+/Oxu5t5vpEUtJwGEVxfRYp5ZsPrm9tum7z3e/ftRoEAKZro811Z7cnaToauptHCESyKXGrVwBgjGdhaqO1dnUgUlIktqMhQJDf7TB59icz67LwRe/jiKX0LrBg8r7KSYrhfaBsQWbVnUEafq/RgQUZV+YlCM3nyMuhVg2/HlcX+SV8pRNemvtXOjIQCARedYLRG3gFYKAQ+Vw5ow4TRNtu5iSaCNV3r/PsfJGfHNix4Gz/6OTR59msnuvr9XoDnUe9egZS8GAQF+OxP5PYA7n5yTKFduNVGObaelGseiYe1COwkkwy5GToimHELGtsJACL/GSendpkriWEG4CyKRmZnewVCoMU5IZWgtrTwhARyI0sDRv2xnAGsiqjUGI8Sa3VQ4AQw2bu5xJYFOxlS5XZ2yCkSpKxnYYZjhRjYcfNxoh8EZnGTpBSbmxMh56o9HBEUcIAqDSlKa2FLyVF0SDx1MJ8eS0SrKSUws3zC0rA3gJNbswMALpEtjBZVl+X89P8xfOTk5P668PFeTkaPj88WFTJ4Sh5+IPp9q4bN6epTmIAKAvkmZuyms/K05O5raygJFWlbOTQpMR4SJ5dAzatYTEzsz9v3F7GpTJW7cmowdula+5aOkZvRZUkIm7PDL+KrJ6xewnVvcEAKrPVb4q2Lc7wjV4l5DBJTepuDHcrAMO0f2198/pOLcgspNza2plsuE9apoA3hwoS8GXrtMFiAfsJiwS4MdB0icLzaHn+7OTDD2pBeACns6P9k2c22blJ0t5wdpFlWZ1vFAmAZXMbEmgy6Xe02X3Go3RtfIUBCYAZBt6T5s5riOF9P2DWml0fIiHQbfcOzRUCAGajjfHsfmb/OgkyLFxHR5BgviRLAOCVt06rzEsQIO3qa5dz6Tn/BbmqGRxXtcZVvwcCgcBrxco+PRAIBAKBQCAQCAQCgVeZYPQGAoFAIBAIBAKBQOC15UpPp0Dg9xljTMur03McBUBCiDjmZgcZRVIq1USCCSG01jY4k4qiyIoia5IEEUlhnQKvRpCIozhpxGyMNsPh0F89uIco8XyS0zSNIueUK9unqBYCtZVi1sYIbuSahCCllH9IlGghXQv46xIDoEb9xf7RbOh6wHk+m3XS19NCJ5axDREppWyksTECWuomkFVKKaWwOjotqOWsK5Xo99VwaBun5dxLgntp7ItvKeVHy7YrWFdZWB0sKYXyliaWUkopvdVHpRBuZwDWsZrZlKW2AcxZlp2fny8WtV+0oDxXA0nNEqmK5vNer+cut0iE8prO9zoGUBSlbm45oFp/tbBXXwjhr1RMRHEc2zL7TdfJtvFurn951R2bvz3MrIuy6h9MWRovcNpo9mLkQWjd6IvZXJfaXhEi8pewViqScSzjOmpXSCmI/CWt80znC6+DygzP3ckuznB+5nYnIbVOFAsARC05NKWk32kkSTIY1HpvqLsFaQs+HA1UpGSzZq4Qy48G+bd6h87dwoyW42uljHcpHcfa9tO93IO0+pylrUvpFp0bvlXCQCAQCASuJhi9gVcAQm0G2V8Wi8Xx8bFNTtKBP1SM19bWGlsUACUvzp8u8ovaXMnz/NmzZ3leR84lw2GxvrF2Wm8lQVt3dsebznbtjIbtwHHQ7z98482syacoy+vXr5+cntg9s+OLojkpgDfffPPu3bs2ORiQP2I7Ojr84Ne/tiGjh4ezX/7yyWlTqjRN79+/v7ZW6y1JJR68ub2140KCx+OxHz0rhBOLbY8/u2gNTzUGLEomF1MohZTKKSoxpBDCZtPv965f33VfHxhGCyvPA5CUMZE7PIq4qrIUMml0cQHs7kR/8RdxNrMGP5jJjWwJiDQ81a6trfG4Fr0CANUexkdRNBqNrJDV2nS6u7vb79eNMxqNdnd37beJwTBeW1vzm67fT9JUAjg/v/jiy2dlUZ/3yZMnf/3Xf33UaOcS4lhuW5XvNE3+1b/6yRtv3KmSAG7dH+ymLsa3KMo8d1bu06dPPvrtB7bpjDFaazuaj6JoPB5bayeKot3d3dFoBCCO414Tjg6gLMs8d5JgAPy/Kwt/hZ3z2rOYzV48epovFgD29vZOTtzjebJ3eLx3YJNJkvT7fXvvHjx99vzZs6wRaRsMBrdv3+7368s9GI2uPXy4c+t2lSSiJIpw5lTrPvpg/zefHNrkwdHB8xcuFtewMCytFXn//u7/+O//ZGNjDCCOEHmR4bu70wcPHtikSikeuKs5HKbb22PVPACj8fD+ve3+oDbFiUgp4T1HlMSJ8ESkpYQnlwYlhW5k3lHfk8b2UUJQ5Jn9vuXKxJq9OFuiSLqzEKRv2RoDrd3RRFCqJQslhGiruGm/nzTGlJ5KFoSRhEtNX0Ld21xOV715uWsMBAKBwGtFMHoDrwhto7coinkzHgVQlIVv26leT3lmTH6uR5NJIeux4Onp6enp6VkzQk1m89GzfSNrG0xIMdlaA5zR28FOY8RxvLW1bX83bDa3NvOyMWwYR0/3Lo6cctW1a9c2NjZsUsoMcIuRzGazR48fz2f1L48eHfzVX7334kU9Rh8Ohz/5yfnOzk6VjGLVH3LSLI8EIPXsKwAkcOkMK4DOULAag3pJ9oWsoCBagrdV5eusoyhKksg1fJVzkzkz8hy+JrGQ9RiaiOy8JYDRKBq92YeuM2JuDYsZWJTI3Wgc/T5a1TXwJWmEkEmSCFHn3+/1RuORtb2Hw+F4PLZGc38Q9Xo9O10PIIpUFAkAuiyOj46yZj728ePHv/zlL58/f14lCXFEW4JqK6jX6127dn04dFJG6zuxMa6UWhvrXADg8Ojwo48+siq1zOwbvUmSbG5u2lIlSdLr9awl4Je28lloz321WLHpD4GiKE4OD2bnFwAeffGFvXwAXnzx+NnnTiOq3+9PJhPbyczPzs/OTnVR375pmg4GA/utpD8ej7d3RtdqISsw4+wMjRcAgL1nhx988Ngmv/zyy48//tgmVSzjXmTPxTyfX7xrJgCgEjRdEQCMxoPNzVojGsBo2t/YdV3T+vrg7t2tKKpvDCERJa2JYv/iEyCV8s3LKIL3FIING8/o1bqlKC6lUKoxets3FYN99xCBlusEIDpLTvlPtxBg3+Ik91Wx/qG1Ehu4I1cOA9nKoEWr/u19ugd104FAIBB4zfjDnQEIBAKBQCAQCAQCgcBrTzB6A4FAIBAIBAKBQCDw2hKM3kAgEAgEAoFAIBAIvLaEmN7vgEqExiaprfPpY4xZHWLXOaqzM7XjWpe3rkh2RC8rtdjqF18YFoDWTrMUS7IinXzQLlW11e5gjOkEaC0Wi9NTF+bKzFYbBkAURX5LAqhaUippiAu4TTKNemMXtRuN+hh4kXDU0izuXZte++nbplE2ms0u4jc3bPRsFMfXbt0cNtF6RDToGWSukIIlSu/zEBHbeFkivy0kpPZCafvTtbLvNIf6vTQqXNQfGYNGnBnAOJ0+vPuOldeaDvaPXmT7+7VYl1JqEJXFbL/eu1Cz462zfdd008GGGLnLdHx8fHh4AqDI8+OTk6LJVim1sbnptTmN19atyBMAJoUmTrXawQ8AJiIS7RuYXLweM5em9G4eYilEoyULgGV9CQ1Xuk12i4CKvN6o3axAbBB7kX1KtQL0WMCJZwGqVwzXz8omGvM8P+lvHpj0vEpu7Yo//293b926VSUjJW7cHI4m/s2DeVYA6I16b/3wnpX22b27Ptntn5/V+TBTngtj6hsjUuqth9d3dtwlGE6F9G4GSeTHU0qxxtGbLOrM54v58fFRWdZ3eJrI0nAa1zHAg6F6883+aDwFQEItCneWzz7f+/nPPyyae3u+yPYPToum7kqp8WgUNSLDvTT+0x+/fedmHRkOYDAUaeoKeXGB8wubwuHBwePHT+zjrI3IC2Hll6SUSZKIpnPo99TDN9Y21lMAZdmK5X7xPPvtJ+dGN/loneW5VVzvxfr6OOvHdd2VlOsbG/YWNcZ88MHHjx87Fajz8/Pz8/oqAIhUP1ZO1ixOkuFwIJqmnp8dH3z+UT6/ACClWhPu3j7NNlm7K3JyWOw9cxJuJws8Ph7kzdW/Ibd3Rj+W27tVkofJbLg2b0K2mVGaSDvxJhRrWbzpVLJur8XX3nZ6VP1Bf7o+tcLmuzubgx3F/QIEJBKRK9XtB9Pe2OUbxSrp+2LOUdpj0dxFQkAK0er4Wy8BkGpFuQrR+uzNBHj68EKQLxdPRESiybCVr4Ai794mUFuSuZUigSRynQoRCRK2l2EgEsTe8y8oIi9kX4lURO5FIBDhcoF4ALL7Wb9T6hXjHyK4Ql3GFaesWb11Bd/4QAAgQGBVoa/msuFKIBAI/P/svfuTHTeS3/tNoB7n3U92s0lJJDWSZnZ2PDvSru24tq8j9od1hB1x/1v/6LgbsbFxd9cej62ZuyPt6EmRFN9s9us8q5D+AadQWTh9qkmR0og9+QmJ0VmFQqGABA4Shcy6ZKwf9JUXhpmbAT+stBIlzBwZdRJpPXqkeRmdQvOsR6Zh5pbciqLwH8ihZkgh+PCY4nGSJImMXmkSn1vmcCP/RzB6mXmxWIwra9MfkRGYrLWNICXM3ug1xjpCIaY+Jkvyfn1h0s3REVPOJtn2YLuXh+nebDJJr/Z9QFcAibHbg2E3FWZP6rCoC0mc2EJUkTHLmKeEaHaXGoMqfhKA4WCAgTAgnUNZz6rBBqgrtpcNr++/4yr16NjBg3cf724u4zM758bj8WJaxZ4t09np2aSK7QygnJRU1rmdHZ/ev3sHwHg8/vbbb0Od53l+6913t7a3vWiM6fa7SVp/BAWUQHxmyTkXigT4KSrWzasYbuGKUnwHRn53BwAbU4IAlI4XIm4TyLIwZAlsieqFBSBlJPKe3CgCE+Qnq0xWdAfjoMOd8Wln82iRLM2kzf3Nn3+4/dOfXg/po6nxdLrwkZ+zbvbW1n4o1dXZ7vVb+8GeLMrydHw2Dx++Iur3+3le59QZ1o8AwBJZcR8yA06uhcn93B0/PyvCkkdnBkvcyZb3Kp0j0/FrE/MC0zoeFu4/PPuHf/pyOl1e+Pzo9Kuv7k+myxjgSZJsbGxkldE7GvY3B1c2B3VgpDRBJ6vVZjLGYW2p4euvTn77269CM80LO54krjJ6fZTsMHpsbuQHu72djQ4AN8diWQQAeHR//vFvTopimc9isTg9PQ09fbNbLA5OtnrLp8qyrHcz6W5Vg4Zztz/+8n9//HsvAnj8+PGTJ9XqD9DJtnqdpS0KYDAY7O7uhiGrGB+dPfiinJ0BeOutt2RQqHQ+Qlmr+tnJ0ePHj8PDPl3g82lnFj5YtbV11H1vc/OGF22fpt18Vg05zDTrWLEWgXK4SDbqhbOt4XBr61oQNzY2rl69GgrZ6XQ6m5bTAgCnJMORXzkYXjmog7TL0VWIy5okIkPxsC8x5/8uLaHIVkXD6G3QvIOBlUNZO0RyjFweCzkSgNq0PgdrXvhOLbm8CHWhflhe6aZ/rEIriqK8Aaz5SVMURVEURVEURVGUNx81ehVFURRFURRFUZRLixq9iqIoiqIoiqIoyqUl9q1RvgNElKZpcLUiolW3K3+EiNa5+3pW3bFkttHZ6EYQiXFeVhIfhCb8LU8ZY6SXb3SWmoGpmDkExPJnvReuF40xshhElCRJuC8Aa60s83g8nlautl58+vRpWZbHJ8dnZ3XoGgCHh4e3b98OYp5kVza3gmjTNBV3ARESG7xAk05nsLlZVt6YhkySZg0/szRdeu0CAO58+eW339wJYpIkSZoCSLJ0uFk7TJokGV250hnUQaFgqLGu5ByExzJMI9pWkmWDzc26JrP8r2Ank4kXnXPz6bSs/FSNMVevHWxsbnoRwGhrS5a5KJ2/9ujo6PPPPz88PPTHjTGff/llXWZjbty8uXvlSrjwZz//s/c+eD+IcXMD0t8bXs2qh2BGYm1I7zW2oQCVy5kxJrF1hTMZ1/AnJIjYNQQ4x7LmmrmCfE1XGNO4L1EjIE2jw5xHkhjyXs3GsCiTNSbPclsVm8FZJ3dcu1NmaWaTugmytOFkbhObdZbVDuDqwfCjj8gFl9HZ9snJTnD4Ty1GHaRVZnmebW2NfA1I72UAe3s7/+7ffbhYLC88PZ1/8NOT2WzZRr57Bu/Zfi8fjWoH0VWcc8HzFsBsNjs5OQk6maSD4WhrWTlAkiS9Xi+MD4b4s8++ffjttwAOD49DDDYAX9+e/OZ/HYWce73e9vZ2GGRsMX/WeVaOl07Axpijo6Nwlpk/+fSTu3fvSu/SggAAIABJREFUehFAp9MJccgA9Lq7o77w0LY2y7LQ+p1BvnN9IzUOwOb1vcGVustcOV58cFy7Rx8+O7t/7yg87GePnh7+/rOTyjs6z/PpdHpyclIlt660RvjI5plNk1pbbt54Z5DXZzudjozY1+l0RqNRKKQfFX3Hkd3tXBodauUnoNExFEVRFEWpUKP3NWCMiexAJ6I0M3NZxexJkiSKGvWKyCmOc05GgYoMTmaW0yNjTLdbBxaWWGtbLHNpTgAoimI+n4f7+mtbzJ40TaPIVbJUZ2dnjx8/DuLR0dH9+/eLojg7Oz09PZX5PH369Kuvvgri1nA0uVZPfPNuN82y2qQkQpIEc8caM9zaqu1PBlzTGMoyaUDevn371//v3wYxz3P/CN1e7/rNd/qVlZvmedbrNYxeakZHLYqG0cumYfTm+UC0yHB75+CdW95EBMDOudmMRUwpmyYkm8laCCUsXOmN3sPDwz/84Q/379/3x51z4+l0EQx+Y27durW3txcuNNZERq+8S1mWRVnUlnnTJCYia62MURwR6tiSNSJaD4NKULAwowYhwJUIsX8BmAQySBRBViSIGlpKAEOuB8mWPocksUliAThA2veJMXknTyujkwzZNDUyvG34CwCQNZXKJlaaxAfdbPNaHXM4wgAZat1hRlkudYddiMgGAHt7O//hP+yEI5Mpnj5D1byYTqf379+vw5hldjhce1MAzjVi8nkzL1TdcNTZHY6SKuSbMSaYagDKYvovn349nx4BuHPnztdff+2PA7h/f/4vn03KqgUPDg4+/PDDfn8ZPo3m02fm2SJbru+UZfn8+fOw+MXMX99++OhxbUL/9Kc/vXHjRhAH/b2t0TtB9KHyQpmvbPQ+fO/qRj8HYK9v2l3RPctGAz95NL/79TjU5D9+8of/9egQx0srN+90ZOR5orR0PWPqlbUkt4bq9r11651bb9eRq0wzBr7vKUFsIbJpgdisjURFURRFUc5l7fRUURRFURRFURRFUd501OhVFEVRFEVRFEVRLi1q9CqKoiiKoiiKoiiXltfpX6oEIj+r4E+76qDVjnTEdc7NZrMQ6qYsy8ePH5+e1uGdkiSRfmJbW1vb29tBXHUqY2b/73w+D9kCSNM0bcbgkUwmE+nmN5vNjo6OwuXdbvett94K3nrMXJZl8BJ0zqVpGs4CSJJE+hAeHR1JV8AHDx78/ve/n8/ns/nswYOH80Wd8tHjx18Kn9693d2b79R+fcPRhu12QisYkCVbt4kBUgOuVnyYUXIjQJABTC12h/3N/TrU06JYTOYLAOVi+vTw8KyKNZV3OjtHR4PwdATTyY2oyXJelGfLxABMmljxREhSynPhhwxYJ0Sm1CA0IIENmGoPYeHECgCjzdGNd28AGGwOn588f/L0qT/uyvLk9HQ2n3vRGHr77Xd2dnbChVf2d5lrZTg9PT06Ogri0fHRgwcPiqq5E2u73a6p9CrPsr29/V7lmUxEeacjndiNMWQMAAZkdCkGsahxxtIRN2DIGXGAWEqIvGm5LIrZpCiWjq3lfErlgtyyqsmVBnVuBFDUKZmXUbOIjBHhtYhzazgUc1nh9cUucrctUQfjgi9kXVAiSoQ7dFmWMiCcJU6tkw1qyRpLAIisqUJJAUjY2aIMt80co8tFpXRlXo6yflEsXU8TSwe7ZjSoozc9vffV3U+fBPHe3eO7d0KsJjx9+gRHd0NLjUbpB9d6ne5Sw42hxCZB7aaT4stHT+bP7gHA4R08+9ofB7A/vHLl37+Pytl7d2f3Zz+7FmIKJHwyWjxJK3f3oihPziaYn3kR4O39vLO5W4l4719d/7NfvBvETr7V69XdsyzL+XweanLYSbo7ucksABo4pEvNB4DEIhOxprbMTpGHFtx4wkl+ZJOlL7Gx1vHDstIix7lFLxUNQTIQGwBDEJpPTe93rPwWvOBPg3rwKoqiKMp3Q43e1w817Q8f1MqHepJGrKdlEuOvCukXi8Xz589ns2U00el0+utf//qbb74J6UejkQwQ+rOf/UzGSc7zXFqbHl+eKGbyaDRqMXpPT09v374drNzT09MHDx6EwEjb29tbW1uhGMzsI1150TmX5/nGxoYXAaRpGq4F8PDhw48//jiIn3322d/+7d/6sDSLchZmnAC+vv3N2ThMi7GxMXpLBHTdW8x7o0Go29QmnSyvq9oQ0qS2J5kxr8IELRNIEwyDnY39d2uL+snjx0+//RaAnS6mD4pgunS73YNrB5u9OhhVtrllbF2TxWQ2O1oGwgGQ2oREPVOnS5tZHYbYMicst2KQNSTkkkuuQgcDMAQjrLcrV3d297cBjMfj/bf2z86WdVUW5bPDZyEotDFmf39/U0SBvnLlCnPdIs+ePfrDH/4QxNu3b//6178OStjpdHZ2dtJ0GZR4Y2P0Vx9+FMJiGWO2d3b6QidNlhkZJbuCQdy0PbkZbsrCyacDACc6DsmKQVnM5+PjoFfF9AzFzJRLJbRuYdnVYc08QnJFsQwYZo0MTWSI0tSGuzJQinIyuHBF6er1AhSAkECNYN3G2kxYQbOinJ+eiejN3O3MqVJCMkRZTj4OlutABMQqTVHyNIwSpeUhuxD0yyZJf7iVpFWdE5Mdg5bNB+DTf/gf//w//nsQv/787lef13GSe73uaDgKxtzuW4N/+8FoI4RJb1bh0dPps9988/z+/w8A397B/a/DqZ989H//5f/zb5NKT4bD4bVr10II8dnp42dffjk/Wfbu+WL+7PiEp1XkKsK1d/c7w3rQ+Kt/97O//DcfBRG2S0k9skXGI5ULWpzCt0tSIqkHOpgcIvzyoJf0d2rlvPLM5f1HyXi5ImDSWYm9hVuWqnS9BKOc1o6TsD3YOmJfRPRD4EV5JBD9mvgjUlQURVEU5UU4ZwKq/JgJEyNmjsI1R+K5U6h1RDMwceYcpCnu52rhvuumbpKWSZvMCkBZ4TMWCeOU7BoJLixDzNoSAavzztpaXj7wUvJ/tN9anuSmiIuufSmIDBEAMiTDcTOzFIlIRtv2R8LfHlmZzrmqRQCgLEvnnKssPec1Q1bIa3yiNri1CV9XGTh6mfdaiVUBLA7Kv6mR1hdIFksa10QgA1NHumZQIzWzc2KXh3OlK+ulJXauKgkAENgQvF55WbYvEQCGX4hht/yjOmWtsVWka2v9K/9lPssw842qlX2DiBrBuo0hGTQbluQXq3wpaphAVbs1bnEODd1fZhTy8n9L8XXy0kOWoiiKoigvQ2PDlaIoiqIoiqIoiqJcJtToVRRFURRFURRFUS4tur35NRDtKyYis9yxt8Ra68UolsnqVlJJWZbT6TTkPJlM7t27d3KyDDNTFMVsNgt+cQCYWfrHPnv27Pbt20Hc3d3t9Xrn3tFaK514ZbwrALPZLPhwArh///6nn34aNrhOp9Pnz58H0Tkny+A3BoebEhEzh8QAiqKQgayGw+F7770XxE6n4x+TwYwSIm7Txsao36+dRX/y3nt7e/tB3NzcSNM03NfKzZHnwc5Jn94o8WA43Lt+PYh5r+dj8BiijKypkuedzmBz01bheQC4ophX7QXg2aNHT+7dC6IlY4U+JN1uvrVFVeWn3by/v5nky3ah5j5kBpdFWTR2ojb2e2dp1slzAIlNBoNBmizzKV2ZJEnwsgYwHA6lFiWVrnryPJcev4PBQBajKIonT54EcTqZPHr4MGx5TZJkMBgMBgMvSsbj8dMnT4Im2CTNByNTFZKI0iy1wt/S+k2qa2BmLsU+/3pXPAA4x8ZQ0OqobwJAc288odrnutwWu0zMaO6oBzs0IlWh2cHJNPbAMvPSVRgAUDJKoWjOsbzWWkMJk11m75wbn576+GFHh9MnT+pwaPPJ5Oz4OJQ/MVmeDoMrcq/Xu/nurWQUxnkmOFBdjNlkEoYUz2g0Cn9vb29fv349VNfelSvGOVcpz3w+f/78eejvJ8+fnhwd+bGi2+1eF13m2sH+wcF28OntdrsbG1mIcNZJuubq3qIqZFEUSbcbvNABdLd20/4wiJs7O5ADKYOLxlbqxlkCDC2Xd5vdXAaaAgBu7jHmJUGSsQCNsZFClq5saBGVsRe6oHGj6idDHpFIdY1V97yspKgoiqIoikeN3teAc242m9XzziSREaSMMWF6Jy3AC/GRq8Kc8vDw8De/+c3Dhw+9aIzpdrsyclVRFOPxOIhfffXV3bt1TJqf//zn165dC1MrWZI8z6WhK8PtAjg9PX306FEQf/vb3/7X//pfI8s2/P3uu+/+x//4H+UROVMEUJalNKFns5mMoXX16tW33noriGdnZ3/9139dliURJZkMOoPZbCbL8PZbb994+50gWmusrZ+CGCQnuxHMXJYsAil7j8Mg7h0cbO9fDWI5mSxOTwEQA4Wjqt3J2s72dhJahHny5OnsuI5c9cUnn/z+n/85iK4sS3HTXr+/vbMTIiGP9nbe/Te/7G0t4/dYY3u9Xj0zZsxms9m8rsnxeDyb1uLW1pY3erMsu7p/1QUHS0ZRFEFk5sViIdcdsjynKsougNFo9I4Ii310dJTnebAnx+Px119/HRp0c2Oj2+nuP37sRR/mane3jrsb1OLpkyf//R//cVzF0+oPh9du/aRbBVpLkmRzc7OTL+MAESGxnUQ0aAQXhatiNQMo5vP5fB7Uw9v5YVknSeqAwwDAzK5kEbubiHwrMBEQ1jTAjouyqK0goATLcFrWWisCX1HS8DV183kpNLagcr4o6swZzYUnZ3Iiu7xXOZs9efjw+PlzAL/73ef/9I+/CymPjo4e3L8fWmRrc+e9Wz/vdpZKuLe3t7GxUUcUh4MrCHUxjg4P79+/H8TM9A4ODoL47rvvfvjhh6G6hqNd68qiGmSeP3v229/97uj5MrbTbHr27b17x8fHALa2tuTq1c0Pf/Grv3jXVkavtZSkNtQNF5tu+894sVQGBkrnXLDliEx3QFkdFCrNMmmvckE8q58IiaGs6dZsk2VDTKcQTYAshQg1xSWzq+Nvu9K50skVOqlFaZrUvs0AgxdFox8lSZaY+tqI1R+CdUZv++9FZZhXQ9BKtoqiKIqieNbOI5UXh6OgSszMLCcf4e+XmpFw83s/i8ViPB6HFyDW2jzPo6mSLMZsNpMv9OTfEdR8zxAVMnp5O51Oj4+PQ27epA+XzGaz6KV3+NuLcoqGqq6CmKapfDGYpqkxxjlHhCQjm9S5nZ2dSWt5OBh0OmtjpcIxCG2hZ7gZcqkpJkmaVC8hAbAxy4/JOEZR1t86MsZkWXhVC68YYh48n83k+6uyKIp5XbHOuY5YfcgG3aIoQmUSyU/8ACtaV5blQhh+IToREUWrGDaxoc59/bc0mTG28R44SeTE2i/3hIaY5Pl0OpHtIm0GAMEU8Qs0oTbI2Pl8llQ38pofLHNi4sr8W0dDqZbhtKojzLLM0QMuka1fpwQ308psGWCStwWhvgsAUPx2ulFIsIOIESVKWImm3tpAVBTFfDYDcHZ6+qz6ABWAw8PDR48ehXouC1zZPioWS3EwGBRF0dQchpDLspS9O8sbtnen0xkM6ijonbwD9tGtAKAsiul4PK4acT49WywWviTW2vBFIgC9XqfbzW2VMxEaL0qNRdlBKurKmEbVdfpI62XEGG42X6Qp1Hhd33jTy3X9e7mRz8ppNJQnDmrGzPXSUrOtLyRq/ZciuhE3f3oURVEURfGcv7qsKIqiKIqiKIqiKJcANXoVRVEURVEURVGUS4tub34NEJExJmwza9mr1r73rLEnE/B7m6Ptzaenp17Msuztt9/e29sL6afTqdzD/OzZs6diG+Tp6WlZ1qFWiMiH1/LI7c1lWcpdqZPJRLoKO+cGg0HYEsnNwFQ+QSizPxUy93eXm2n9ZukgEpHc3myt7XQ6/qokbfj0csky0FFauQsuYbFz1Mti2yM19yYyEawVOxuJDUH4tZKpHTsBwBokFgAcs+M6Y59MbtLM0kRs8hxsbOxeuRLExXQ2HdcRibI8I9R7mAmUwKaoAuewocIBy6pm5xbHp9NKGQAcPXt2dHwURD4Z03gGIE2S/mCQVjuc/cPWHstM1lHiROsfj8+e13uwHTsr2mtE6c2d/Wl/uYF5PNgcpt2gdYPB4J2rb29vb3sxy/Nu0qF6fzd4OvUf9S2eHs0ePpueLcvPp9N7Nkl7y7rKs9xNp8PhUhOITLax0+mJFbpo5zCzlFJjukmSVg06tUnHGK4eOQNosWDhWB5vYg0bmEvnikU4XZblXASWgzG2k4Xt6AQYVxrRf2cn47Ozeqf3yfPnz0V/nDOPyzp1v9+7cmUvSZfNlKXUscZWyuQWi8nx8cmzZwAmR0eLSd0fc2sOdneCtu9sX3nr6l6/t6y6nZ2tPDVwyzZw5eL4+cPp+NCLAMbHR6g+swyg20m3tupAVsPNYWdUb29O0xymVkIiZxNK0ypMANLd3e1RzwDYvbq/e632DR5sbZIIHxa1HohgDLjqzrSSgoAoKJSoZyYuTK2ihtiS3B3tyFT7lhOCE4NIAlShwgCAHdsyKAObApgzL/WEeQbMgTDAJk29IQOSw4TB2l+BVdp/F9ohamyy/875KIqiKMrlRo3e14A3IIMY+dl6U9bPS1ajlaxaueHIdDo9OzsLUYKeP39+7969EJB5NBr9zd/8zb/+1//aiwBOT08nVWQgAP/tv/233/72t0G8cuXKeDwO5UySJDjdJUkii3FyciJdTx89enRPxBwuiuLGjRvB0J1MJk+ePAlWrjFmNpuFYnhzSMbxcs5Jy/zx48dffPFFEN95550rwiyULoUEJ6M3u6Fj4UGXpqn0v2RmJ0IT+TlvOE8ESxDhmhh5DhkH298wQI35KyNh0wWA0jmahbjBZMgkhmydbb65mVbmB4CbjkfD2qI4PTo6fPQkiPP5YjIeB5vKOupRNjCVKyPDTgriyv2yKI4//+bZ/QdLEfjs88+++eZOEHe2tq7s7ALY2Nj4xS/+fGNjGYGZksRsbZMwxTtzmxd1XT358svD298EcWNz84qIRPW+6e99+O9D3ZbWzJN06eEM2DTtb26lVRQ3Y8yw17OnQsMfPC4PDwFMPv306d//r5PTZdzgqcHj3M0qx93hYPDRR3959WAZPCyxSfbnfzF66x0vAkCSylBGBiyDb/XT5GqvWy6WHqTZfPo8S8eV4bdpYE5PysPK/jTGdHqmsWiytHx4PivGZ8ELdDafHR4+LyrH6TTPdw6uduoYUaDm6s/9zz579NWytwL4/e9//9uPPw7iyXT29Ows9LsPPvjgv/yX/7KxsYxb1ht0urf20sGyJovT0weff37n888BPPji7smDuj8eHBz87Jd/FbrY7u7+n//8V/3+UuvyPN/uZ2a+XFyYTc5+9//93e0vPvEigLtffWWK2v7f39n4+c8/qMVbt6588E5Qfp4xThfOLWvAJPNe35RueevEDn/67i+7GQEYXj3YeLuOSJcNthMZ+Mn/UYuENIPw2G9AgAXk2gkgbeCFdZNEDAU2yZPahiR24HIZbc5adMUIbAxsnS3b0pkimLLOjh0fMj9bnuUEOBS/mAVQoNoqReCErAzXbEwd5Pxc5JArxZeyWpdj48tcoiiKoih/mqjR+3qQ047vPAVhZudcmP34V6byTe9kMgnmaJZl/X5fvuntdDrylawx5nkVWBXA2dmZfCXrX02HOZMsc1mW0i6dTqfRm95+vx9sM2a21sqcnatDnvo/6gkokX/GkHg6ncovpsgYSKje9C4v5xLCykUdbScgrNxqlSGckFF2AYgZN5ZGcBM5IY3PWQMso/uyrd/wwxgm+QqZTJoaWxe0PxpBvGBMyBTjRvjl6WQSvoFDgIVJqje9AKNYBAOMF0VxMp4e1q92jx88fnqntoX4ZExnUwC8M5m/9Q4nlfGcphiUJEw86yDXC8qTydnD2hTvs7F98erPJKPtK3WVZBmGw9r+NAZ5BzLMcllCfE6Gz2bu8ARA+ex49vhwVjX9KRb3+fQMS1UfjUY3rl3r+tfpQJqmi8kYIiQYjAE3LArZ5xJjutaG16gda3NrysoCSQEqFhw03BhknUaDV39yWfJ8Vsdtmk4X47O6a5QFisJK00XqJzA7PT6uAlkDePjNN19++mkQj8bjh+JTQ7mh08NneRXR2FLhii24pfJwUUxPTk79esHJSTEVGwQM7e9sh2Bju7u71/avBKPXWJtbqt/0LmbPnzx+cKde1BifHMvYTp0829ysPw402Bjkw37ov6WZL87GqHXU2QRJ9aY3T+32zmijnwHoHewNDupPiMF2ZSBrULNTkX/Tu95EJDTe9EbmIrlSmMTGEJOrFYIcOV5ebpo3jrI1jkW8ZTYF85x52dzMc2Ah3vTWWwAAAEQv86Y3sngVRVEURfm+WT/PUBRFURRFURRFUZQ3HDV6FUVRFEVRFEVRlEuLbm9+DUTbg4HG9lpmXiwWXjTGrHr8hr+LopjP5+HIYrFwzsmNxEC8d1peTk3XYn/fIJZl6ZwLl7fsr/P7qIM4m83k7mUiyvM8XD6fz5MkCYVMksTa2pnNP28QfbXI3KLtzdHXd5m52t7M7Fxj+2hc53WFe6KzhHrjMYGiQFeRE68vpxSjSl9mTkTGwCxTkhGxes6DjAmfKgWQ5nkuPELZmHlZllVNdvt9U7sHxxBRkiR55T0LoNvtyhhg3W7Xb3n13zoOx8GA48bXSp2DaJFiMZdNcHp6enhYxz1KkjTNqw3ngGHOhkPx1ITSgZd7TZl5dnZWiB3di6Oj4uQEwHQ6TZIkfBI2N2aQwNCyGIPBIM/zcDZJEleUc1GqYjYrZVVT46OpJ0dHp6enZbUdejKZFOKLx75lRUfAdHxWCoV3zjlmAIvx2eToMHzxeD6fHx0dhT7VmfVGu2PZoGVZhr3QAE5PTqVuB+d8T6fT2c2yoGZbW1udTic0aJokXBRldUk5nxeLReXpwPJTulmWdTqdsL05y3OTJiZ40RvjmEP7snNJksgvWg8GA6ke3V5XZi7HE3gNT5LgWm+zrNPvhwfOUpt2OzZPAYQC1LDsYS/D6lVEkOMeyMiwc1EfZIAZvre3dk+fY93x2UuNUaVmNSeKg2+tvdbnu/5sRPxEAp9JyKolpaIoiqL8ibMyNVFeHm+BBNE5J23X+Xx+eHjop7xyegrEcZKLopAz4/l8Ph6PpU+vMaZhCTgnzdosy+SEdbFYPHz4MIiHh4fT6VTOYnu9Xvhb8ujRo88++yyIx8fH0je40+ncunUrzK6ePn06mUyCkbyxsdHr9UKILGttt9sNon/eEIAagLwRgOPj49Go9iDd3d3t9/vGGGaUi4Vb1J7GNsukveGcc8IkJh+POhg20mkVYOZSBLIGwVgbIiExeFEsyqJul3JROOFQ2snzrq86MqZrICJmUdNIAPyEe0ne6yXSwNjc2rhWB/spyzIsjgDI8qzbH9SXN6fIhszu7u5A1IAxZldEnEqtzZIUQL/flyoHZsznkGbwdArhwv3k/n3ZKKZpyW+MNq5dPQhaNNzbe3trqw7mVDqcngbn22I+//zjjx+JKGiTw8P5ySmAyWSyubk5HC7dR4tuun8wcJ3KBs7zmzdvhqhOhmhyfHRfBDx79OTJU2GKgyDDNz97/PjOV1+FnjUvi9PZtKxiFE+mUxAF5ZlNZ5/+7ncPH9Q95ezsbDqbAXj+/PDuvTsySJsPeO7F0cbGvzk52a9iFLNzx8fHcrXoX379v29/8ocgHh4eSvPy/Z/85OcffWSqmjw4OPjggw/qLsmL+eHh/Nmydx8fHT19+PDJkycAnGMZ7O369es/+clPgrXc39gaXNnLOsse54pidnxcVu27mE12d3bxk594EUCapnJM2Nu/JsMEdIdDQq17lKbpdjcsAY02Nt7b3AyLC8agk5dpwgBsljU0lhkslpnIm4j1eRhq8+k1zfDpaJivlmzX1hpO5IOgh47jUBTL9TJrsdpDK/ywEMSyLIuiHp/9iBFav1l6ACAZFB1gGLkCws1YBucavT7zqMcRUYspG+Xjx72W9IqiKIryJ4sava+BaF7iIzmFuchisQhxlYuikK9ZZJwqL85ms3BhURT+Za8X/XvaMG82xkQTKWutnL8652QQZv++K2QuL4w4Ozvz02vPdDqVr/56vd7m5mYoxmKx6Ha7Ids8z6XtzcxpmgbRGONXBLwI4NmzZ998800Q9/b25GeWOp1OVU52ZRmm1wCMsPcAcPOJTHMCSs0Pnjh20kgmIjJGJnHOFaVol8W8mNVlToLlY4gS0whnE9Gc19o0taJUmbE9s74DskM5j2IjBYjQ6/Xq97xAtKIB53xY6W6323xfxz4CUyUx5nNp9E5OTp49W0asBSBjcQO4srObgMIHkFyaXmOuDQnnMJ+HYF1uMjm8c+feH2rDb3x2Np1MgWXw8LrXDLvb1/bRr95zpqlfPfEiAcVsdjKpC/no7t1vv/02iNw0eg8PD+/du1frgzHIbDCTisXCGwdedOyePHjwzee1RX10dOQ7zqOnTz77+suwrpSm6WAwCMtb2zvbN27dzLKlHjrnnjx5Ihd07t65c/fu3SCWZSlHie2dnV/8q38VctvY2NjZ2QnLE4vZ2fHjh4vZsv9Oj48nZ2dVPLm8LzYIDIfD7e3tYPTmg42s30/y5SBTzGZFWS7CG+Oi6PW64ZtSAIbDYViTAjAYbsrME7lc4u26pIvKKcYy58OhUHIHGsNHI3OusZsAzb4QWWUEcPQVoxXWnzUk470BEBYvAGY4t/wsk1zrOQ9pQDL78XX5FOfYqJHYzJwdWCyHOVdnBcQ2MCqL19PYmtFKZPQqiqIoirKOF/1xVRRFURRFURRFUZQ3jvUvmpQXJlpun0wmjx49Ci+Ijo+PP/nkE79DOHon7He0BjFJErkTNcuy4XAY3gWdnp4ycxCTJIleCPg3w0HM83x/v/5qiHcaDC/9rLWLxUKXB80JAAAgAElEQVRu5wuMx+Pj4+MgTiYT+cmi2Wx2dnYWnuL+/fsff/xxeKX8/Pnzjz76KCQuy/Lo6Ci82i3LMssyuYH5gw8++NWvfhXEn/70pzdv3gzi5uamLzCBrE1JvNw1ZOXrHGKyYgWHmKIXsCQO+BfmJL/bSya8uWHA2CQVuVmyqfiOa5LlodbYNdw4m5Al0/DLNab5baTmHknnuChRFZMJZWY4OCsysxOujMxsRzyq39F1+/nW1Xp7M7NjV8L79I42XPVinMhQp4P6Q0rMPcviFfruX/zsz3v1sDCfz+WW+9FgePXKFWuWWtTf3k62++hX6UsC9VB9IJdm2eCDd3Z6dQ0MJlOvDGmSdrqd4IqZDLuDGwdJb/l+0hrTy7I0vEBmLo/OnPi8EzGc2H/e9PbGYjabTibBF9ckSWI64UUcO2YyqB4BxlpjkyACo8Gw1+kCGAwG27s74Y1cp9PZFi9j+8PBBz//8+1qp3FZLIqyDDcFsL+3R5O6Pw6HA6n5b//0Z9d/8n7Y3tzpdG13I7wzJ7Lp4IrJl07ao3zzV//2r9/54C8AsOksPxMNANjf3x/sXk+qz0QlnS7ZNKxmmiTNNzfT6uWtKwtO3GhcDwt5txe+qwwgz3tpp/Z6MN0ubEe8ZbUM0VMcuZLDa1UisrZD3uOXnXy1y7DMdc0QG6L63TvYgDLw2h8j59h7WXvkC1gAsIZWXYgDZJGYZWGMleu8jKZIlpKsfpwkMcbY8BEpQ4k1SdWdE2sJGVhutmhAaIzPcpMOEP9kePygGv1GyL890YWr+SiKoiiKssr6uYLywnBzr9rZ2dmdO3fCptBHjx793d/9nXevHY/HcqtwtL15OBzu7e2FudH29rZ08/NBcaRPbzQfWiwW0ujtdrvXr18P4u7ubrTTNdiiUT4nJyfSiXc8Hstt0mVZyjLfu3fvn/7pn0LAnkePHv3lX/6ltKXlHM451+l05O7KX/7yl//5P//nIB4cHLz77rtBrDdsE9k0tfIDsED4XCgAw9TctmAaX+YlNAxMQmISuQfSwbA4nyRZo2eszGz94zG7siy8bXkueZKbhpXb2IQJRmMb5sK5chZMBZfYeZ45YTMzGmW2o658ph72pYs2wzFKAAQikKtSVjVRX1hyx4mqPNj61e6HfxbEoijkdvQsSfsikJVNkrTbFdubLXcp7Gulothw77u3a1O8WCydpdM07Xa7QdV7/d7V69c7YZ+tczwec6XMrnTP3Ldn89qJlxjlolbCkl0pzN7ZZDo5rb9KneRZL02CecmOQSZ8TJhsYk2SCqN3MOr5XpZ28t5oEKzlfr9//fr14J5g82xw9WraX9b6Yj4fn5wuxvVW8OsH17byeqvwzZs3fyKcaXsH1zbf/2ltipdw87p5TdLNHVyxrPmuMf/XrWovtO0gqY3esiwL0euNNWTTsNmbUtvdzevWZh7u7aKo0yPL6s8sA4CBCAoVwZCWLBxh4Sjs4SUgt8m5PrNcFtIhn2ANWTHqGHDt9LFKWS7KZZ8DgKIoylJ0hMzYptEr+4UxANXV1YSd7IGGkNaFoiRtWrkmTWxafTs6sZaQw63LGVSHFHidOPEhdyA2nlctZEVRFEVRPGvnN4qiKIqiKIqiKIrypqNGr6IoiqIoiqIoinJpUaNXURRFURRFURRFubSoT+9rIAo90ul09vb2gidkt9v95S9/eXh4iBWPrMint9vtjkajkNVgMDg4OAgfI3n27NmdO3eCe22SJE+fPv3666+9CGA2m0n3y+l0urOzE8ThcJimafCinE6nR0dH/jMqvd7SidGzubl569atIDrnpI/u6enp06dPgw9zURR7e3vB8Xhvb+/KlSvhg7HOubOzs1AqZi7LUubW7XblR0dHo5H84jEA76VMgCWSH+vksmx8E8UQVSFnLoRATNyIItW8lHFOmJkAEYVrifz/S+JvbEZFYm5+x4UaNyaiNK2dJm3zrC+VcEGMyhd9OJSqf7xPb/Nss1SEOqYXYI2FUAZrrdSNxNg0ScMjGyJ2TgYZIkOgpd+jAQYbG0Y0aPjisU2SLM9DXWV5HjtsC5d147iztUlJHUvselFkIiiUazpn3r97V/YsJnKWQpnzLDNUhwSz1u6//VYigjmlSeI9yW2WZr3agTnP897mZvhck0nT4CcMwBiztbsrW3+6sTM7rV18d7e3e5ubQcy6PemUDoRqAwBDJskzlyx7KxGZNF36TpvGR2vJkHTUJ0NkmouZ3NQVMvG3ahuqzk0Rq9pS/0mwtv4MkNezJa4RyIoYJkmC3Bguz6VsXG4SqgOP+dqQMaIqP9uAYyc/CswMX+44fJSB7LwgGFN/gYxAcujzsQyCUhVF2bjJKhzXXETLCBPRGFKoUXmrYvhbURRFURSJGr2vgWgSNhwO33vvvTCnmU6n169f9/Gr+v1+sA+xYvQaY6TVZIyx4ZOwwIMHD7744ovwIdAsy7755hsZFmsymchAuycnJ2+//XYQd3d3sywL5Tw6Orp9+/ZsNrPW7u/vb2xshJQHBwcy1lS32x0MllFkAdy5c+ef//mfQ7F7vZ78POm777578+bNGzdueHGxWNy+fTsU0k8iZbStjY0NGblKfuMXQFEUk8mEmYmom2VG2EW8WIRARwBMliIX3xS9aPIX4gajmp3KGWjJZfiK7yoW1pIF/Cy/zolAUUjtOIh0Wco4yTCGhKFDxpAwvdgApi6Dt3ibwbcgczcw0rIlkKniZp1nD0uxcT5NkkRUjrU2xGrGSlbsXLlYBFUnoiRNqUpvk2T36tXG5H6xgI+6bJoRd6Mli2ZVEDDMegMRu2jrxg1vPNcpxOVfffJJQlRUSy3j6fTJ0eGiSt/tdi0RKmMmTdMPfvkXrqkw3k6CIVRmJ/xNnFueAmCI5OpAklx7992DmzfDEV4wCtFAZWlksPSsS46C3UsGlIoyJNaYnlwiIVNFRpLGMWBgTCIuNICl2uhlcNlQbjK2EUKcOVRFdUScXdEVFu1EBBHUHID41rVzEN2TkoSqDxoDuKB7MqMoRKnIJokVVR2ZiyWhkP2CXcGF6CnGOfh1grIsZcRBkza/5k2UUK2TBJJB+4qimM1mYYCd5zNXygBwAJqDyAWPGC+rrR7xyPHEI9c4FEVRFEV5QdToff0QNd69pGka3tZ2u90WozcyniPRG1RyLT8yIKPozcwsi+GvjS737zGi+ZYxRlqeeZ6H8gPIskxma61NqjdjXvR40b9JDolX8Ya9FKP0ddlWJ4SizHzBJPN7g0TBCKDmy5ZmmeMnWC1049n96fiiF+a7XttUkkgJgUauyz9DQxA1nonIRK3vqjeyxiBYcZ5olSGyQmWsX8AAjdeV1KjJLM/TJAkWo02s1PxIwQiwadJ4z+yXFwAYatiHPkPxsFHzWWvjUknzZLGQGnt+kOSQIYNIvjn1t2vez7N6bPXId2ZVRVeIC3W+0vFKulZY5hPnuNKCcQJJy9tYZmnfn4NsLj8K1eMkN0/7I9+VdRavoiiKoiivi/MmXoqiKIqiKIqiKIpyKVCjV1EURVEURVEURbm06Pbm10+0+85a2+l0/CbePM9loKZo76jchOmRZ/v9/q1btzqdjheJKE3T8XgcEjCzzHx7ezsElPKiDKPl/2Zm59x8PpfOwHI/NoBOpyN3O3c6ndFoFOK77O7u3rhxI4TXun79ep7ncquefEZ/RxnIKmyx9sitzgCIKEkSZib4CEl15ZC1SEVNWvtCe0HXQGL5h8EW8bZciUHY2EqGDKSXIwzkftAoE9OMIXTO/lWEa4hgsfRFBMBgB5J7KAmInHibInxiClJ1nLhRLgNqbgElufOW2IDXbm8mgIjJVIeIiG2cvkGyfGSi5t5fMDWcSRswyAh/0eUhIZHwYgUoS22/54LSspswz8qlH8GEXZlY1C6mBGthxfVye7N0NfYVHIpBYGMbCZqQaW55TSy47kcutaWsAGqsQJKBsaaxJlnHcYtrImpOkDji9/6G9gEZauhJrSNLUV68QrOemUCy1WSbEDWq1BCjbOmSRM37JkIJqdkK5yF3OBPVvQaAZUPVI0c79U9OTo7PjoN4djZ+/vx5yOnTT35/dnqyqAbG8enpgwffzmbLyGRnG8ffPrg/6A29SESj4bDb7XoRaHnWJdFQ/4J8t6sURVEURVGj93tBTk3SNN3a2vJ24Lk+q1KURCn39/f/03/6T8EHeDKZ/P3f//0XX3wREmxtbcmIUzdu3Lh161YQu91u5ADsnPOm73g8lvFdrl+/LiMqG2PkXHFra+utt94K6Xd2dnZ3d0POo9FoY2MjPBQze6dfLxKRt7G9CEDGhkHTyPeiN6HJnxIVQlkWh8aRtfUyU0OKNzwQiDgyycTfVP9jGjN7gKhpjdEyYSWu+HzG1IcMKGtM5j2RfE4WnrUnAPBKNg2a9iQAJ+TmhcSwRrQCQFwHZzoHsst6JUA8HROX1nHTmpNYasZvcgZOJDaQdpEZDrP9Pap00j2hp/e+OZ0v1Swvi0Unx6Af0gPN1YeQ8aodzo0BMwp/FUGNkMMAWxlrrTB2asUDN3MyoNQmdShhDwGAWzV6o4ubEjc1LgPZlg0+7UYv4pNOHCEGXCVZA1s/LFPJpljXvsQGlIgQ4oRmKO+2VRSAwLKiDGDFqo0BGVrGeLNEsgPevXf349/+7yB++eUX//M3v+FqZHv4+PHDu/em1ei0mE3/5/+c5Z3lauD25s6Vzb3nx8sAfom1v/jFn781vO5FoBlWboVobCeidT8EauUqiqIoymtBjd7vHf+6Mj768mRZJoMqn52dWWujyFXSaOz1eltbW0E0xsh5lX/p6o/IIKUAiCjLmlFZBf49sDSSNzc3w9vaXq+3+rBh3ubndlExZFbRzI8q/N/yFMzK7PwVJocrlzZuxuck8LRObFeJLPOLMLHJhbUFeY2s3jSajUeGWNQuHCdosrYGmOSHk1aITlHjlWP0SpYSS2kaXtZzkiyY51WgrAWYo1fuUYHlvVbv26TlWYmirBrXsjEuNmolxMQryw8AwKDGqsI5Sdo4N88aWl1nabL+6kY3Wemt3Cx1A7/VYH1dtdzUE7dSoyD1E0W6OpvNjo6eB/Hx48d3vvkmDEfHJyfz+bysBsbFnE5PTqbVm15r7PHJyUkVtT5JkkWxiMvxMsT9SFEURVGU10rrErqiKIqiKIqiKIqivMmo0asoiqIoiqIoiqJcWuKdqMqbgjFmc3Nzf38/HIl8enu9nowLRc2gWWma9vv9NE2NMb1eT0aukmGrgPgbksaYTqcTNgES0Xw+D9ubfdSrsMOZmaUbs9yufC7R9mborj9FUV6ZEGRAHjTND5L7EH31yGbNeD4Nfh9Jlgy3BkkVPG9zc1MOm9ZaMkaOXrx2I7+iKIqiKH8E1Oh9U8my7MMPP3z//ffDkTRNpZU7GAx6vV4Q0TQgt7e3kyRxzhFRFFM6BIj2lGUpPYfTND04OAjifD4/Pj4ORm+appubm8EleD6fZ1kmS7Uaykv69EbIlLRiDyuKorTDDOfYjx7MjWW1LM02NzeDeP369fF4HBJM5tMbZ8+LKuh3kqb9QR2wYDgY3bhxIwT8s9ZmWaco66EsMWQuCjqtKIqiKMoPhhq9byrW2t3dXRnaKnpNKsMmr5LnuQ+zTETy3ewqzjn5VaEkSfI8D+ZokiTys0NJkmRZFt6fOOde6k3vKo3EavcqivJyMJY2b7xpxVorI/b1+/3t7e2QYFrM0kFWcj2yySh9/d5gMBiEbxQZY6y1Oj4piqIoyo8W9elVFEVRFEVRFEVRLi1q9CqKoiiKoiiKoiiXlrWbWpU3gvatwqtxoSRy13HzTINoQ/K5YjgiY2UFQjHay4OLErSda3uC9pMXQ+23vmRc+LTtCb5TXbd9odcT3ZSoZa87AyAKpxlg8fVZrv4LrLu5T7P2Niv5vBS0/r4ACLwuwbrjLwIBF3yHt/XkK8ArTVjDAK09+aq0xJNKkiTP6/gFvW5vMBiGISgtM2RUVhEHksR2u12bLMMT9Dr9PM9DXCtjDKkHr6IoiqL8iFGj9w3mXAszwMwh9Oi5BM/bKJ/I8w1AFIlKnImDOVtrowRFUcznc/+3dw+WmUcOw9GtpXVdtM/WW+a2AAH1A5xLW9bAK5gZbbRmymiYaq+Z1ltfwPdQJgaVZFoyttTcleIcpI1hiIWqMJmCTEnLNi/JlGSFaEuYUmiEWaM8DNSquQJX/62DCC0d1BLy9VcT2DKb8xIwqGWNgOGt/XUpvHvrOdlWrLvQQ20JiEE4N3MGyrZdRdTs6zGE5VOtgez6/s0MuGWhyJAsxf7eQa/XD+J8Pp9Mx0EsXDlz83o4IhhrwtMnSbo9utLJl5ECiajT7TRKsf5xFEVRFEX54VGj9w2m3egtyzIKjCztSWPMaiBlz6rlKW8UXWKMSZIkpI/yZGYZ5soXSWYe3Uv+7UWfm5+nl+cUdknrZBwG4NYEwLlz9Vem/ZYXlck/9eun9aYX84qXn4cD3Hq7hnw9yPvGekvyCJNxIFcdcZEIcjBOZLdOeRhYG1gcQG1MrefcfAEABE7WX01gw2sWPYi9cXkuDLiqws6FwC0vyQFeqduXgc7XWSZfqvOhVjMePtf1rFmyWEIMVxWKmoozGo4Gw2EQiSDjLTtwiTLcmcEll1w9HYEMpSTMXAaHs4qiKIqi/Nhos5oURVEURVEURVEU5Y1GjV5FURRFURRFURTl0qJGr6IoiqIoiqIoinJpUZ/eN5jIZTfyto38Y9FMIP+OvH8jP1vvtRtE51wITAUsvXZDeu+FG3LzDr0hnpY/3uIh7HMLIhHJGFqKoiivDWr4A1/oy0xEIj1hxZe43btYURRFUZQ/Imr0vtlElu25gakC64ze9hDKPuRVEJ1zMig0M0cGswx85Y3ekOBFjF6ZmzHGZyiSKIqivAZo+f8LQZAWL17ERo4PKIqiKIryx0O3NyuKoiiKoiiKoiiXFjV6FUVRFEVRFEVRlEuLGr2KoiiKoiiKoijKpUV9et9gVp1dpS/uahSoyKc3iMYYeSryE5YuuDgvW4l36A252YpwNkkSGRbLWhu5+J5bSAIIMOvd5NaeAHDRWTAQx/z6UXBBsS8RBrDrG4EAitrINcVmTZFD4sCVb3jiYB1sJVqGZdQazGtX/ghIaG2pAND6MmO1zE0IZBCXvIaJ3JrridaW2HeTyPlUwgAbrIS4q1kZUiRMKNdmvcSsycGc+yxLCACvSUAAE9H5Jytaz5JZJoiKxgwZCpCo0RzMYK4rmsHsqowAEIxlMuF6Xv5fQTDrW1dRFEVRlB8aNXrfYCITMQpA5e3PIPojUgy0GLGrUNPo9XdpyTkyeq21LUZvS1ZLI2E9518GACDggklzOy3Xttz11fAZf2/Z/7hggFqr2TAgQ5WvGL2yooyDFUavdUgcEmkDA1ZezuffO7KCVolKEWEYqMPDxdD6/ggADLg1BnfL2g8AArVXJa/J1tP6yP6B1l3d/kTtnbfZug2WurE+Z/AFvXvdwMEuNnrleMlMKOuMmZmdC+MrGZBxazIGlq20vsyKoiiKovywtPxqK4qiKIqiKIqiKMqbjRq9iqIoiqIoiqIoyqVFjV5FURRFURRFURTl0qI+vW8wzCyd6MqyLMvaidAYEznfhr89wQE4ily16iosTgI4J7SVFCOY2VWec84555wspHOuPW6WoijKd4fBVYws5oZHcjSukXeHrjCACHcGZhhDzMsURN7LuM7DOeeCHzmQGLLrnIkVRVEURfnBUaP3zUZajIvFYj6fBzHLMmmOroZolraozEeGnvKElMA58bHakVauc64oiqIowtmyLGXmUKNXUZTXBwPOwQ9vrhm5yhhQM4SfNHqJYBqreY3AVAxmKqXZXLhCLudR8lLxARVFURRF+X5RA+PSsvqGVlEURfG8yvjYtrllyatkryiKoijKa0aNXkVRFEVRFEVRFOXSokavoiiKoiiKoiiKcmlRn97LgzEmSeoGtdZeGGIq/CEda40xq6GtpNhylpnlWR+5SjoPSxffcCSILVuyids2DLY+KJoRZ16e1sxbzl5wz/UXVlyQwWWitXnBURNH2tBwtwSTY2KmSr3hnBSJGa6KbQT4S89tC7qgSC9X5iZM4PX5E6MZVqmGCeFZzoGA9aUioBGk7uVZX2TfCN8tc2YU60sNwLSuzxLaQ0aZKmfymlNJUeiqVVpKRCAUQD2UWSrIiFG0pY0URVEURfnBUaP38pCmaZqmQYyCMEd469QbmWVZRpaqvDCKXOXN1JA+OsvMMreiKGSoqrIso0BWRVFIo1f+HWFc6xy0nbXVUPFdE1TBXM+HLypyy1kCG7zKM68r8ivz3Uu0FgaYsK7tafm/PMSQyU0z6BA5Z1xplgZJaZwzZS1S6cg5Woo+83Pryt+j5XHbzxK1WWqOqFjfPQmU2HWl4nK9QcUAt+kdpWgEtFtl3ZUAqlY6PwmBiI05v9QrLShgOIcZCwNyhbQRSTmCLF9g9MLb6sSO5LIaG2IZ375ZyJZaBABHmBHVgQNTy43mplwIiqIoiqL8kVGj9/LQPpdtRxq9La9bPe0Jgi0d/l4nRokvpj1hy9Nz69kLeZVrX4FXLPWbRUvbnmd9rBwQMHnDryKqxKbYXsltt3llWlZMaH25zquNGvGBnnMgvHhnW0dbBueX+GL8M61b9ADg2tYPLqSxRtAsv5ReqvTss63LTMv/A20VpSiKoijKD8wrzCQURVEURVEURVEU5ceNGr2KoiiKoiiKoijKpUW3N19m2ncOh+3Q0inXi5FPrzgZuwqv7qmWcbBMRTh74eUSufmZmNa4XiqKolxM5ExBzK3DT7RD2V9aHaKWMGSKoiiKovzoUKP3DabdYpThprBiABORtcsgLqun2sXISI6MWCkmSZJlWZZlXizLMkmSlzJ6F4uF/zultD2xoihKC44boeOby3GIRxdmOAQrl5nZudonmhzIkZV+yDo6KYqiKMqPFzV6LzORNdt4y0EU/fvitKdftYHD1JKZI6u4Hf9mhpkJxFbfqyiK8gpwNCRe9KYXIigYA47ry42+6VUURVGUNwn16VUURVEURVEURVEuLWr0KoqiKIqiKIqiKJcW3d78+vE7cuWRl9rT+/0hS7Xu73OJCi/Tv8hzrdaG/Lslc4QN2CDQitOcTLh69mVg5rCR0d/rxxA0649fgh8K8tXeRkMtYp1B47wr3aIoikXhxbIoIfNnlGVZFMuzBDCRvLsxRLRcDZS3Wf3+LYV/zoWaKrrC+is9fG6SizTdnzz/xrTiuBpx/mUCWv9U7Tm3QoBpXYE13zl7XrYbw99GDj4recaDz/L/INdXEBFg5Xd6o0H0RQZG5U+QWMda9WT1p7k9vfJGc2Fzv5TyrMNnErJanYMpPxjtc+lVffCsppQwc5Rte/qIl9Wx1ULyS7ox/sCo0ft6kA1cluVsNnNuOR+y1mZZ5v1aX0oVIt3FC+ifhJoRp5xzoUj+rDwlbxTd11obQl75szI9iYBY5+LT+7+dc1F6H+kqiNZaGWmGiJIk8X9Edihz0wahl6scCTMvioWsnDRJo4daNXiWrDnsubBAFyWgi5Osp7VoPzps65MynBM6aciQkQpcBhMXwOl48vjpYQiBdnR8SmxSk3qRnDk9Pnv+7GgpAmmaWht6CnU6nSxL/KnIDmOhdpVCri02rV4vMEDS2kK0Ruuota6qC9YmWJdtzfqT1a2/U+ZrDgMAiJAT6nEggi4weqktd2Z2zpfKkvXjiccPKoGyLP36iMcYskkSzhMIiRximEEsBg3nWBbDmIRofamUN5zVn+boByhKEA7KHxoA1tqWXy7n4tBr7b+2yhtNWZZSPYwxcrxanXqZ5oc2ItUKRMrpnCuKIuTj79KihMrrIqrkaOIdNRMzy7NStNZG0WQlck0fgLU2TZeTn3OJRqpICZMkablXNKCF8YqIkiT5cQ5WavS+fpi5KIqgCszcrnMtROr4UgPTauKoC8m/peJGnS3S+CixP7J6r4DMzf8hE0e/4kQkb02tFrWcXlNz/vqyRHOLJElkblErvBSvUCi86tVvFKb1YcumLcVEJBd0yrJ09fn5ohhPpvP53Iuz+QJMhipFYizmi+lk6iUico7l3CLL8lDzskzMDIbUM0LjV+oc1p8kwHxXvVqfqz/Vcv6VIDQe//VB9H3+EoUhyFhjzfrxhLl09SAAspYA0b7Rs7NrDFbM0QzGtquG8qYT/VSJM+f8ZPgjXhXl2chuiWBm+cMEoOUHUXnTiZp7VanWmbUQChafANDMyt8lpGTm9pUX5ftjXXtB/GwF0bf+hS3VrkXt+LtE5oA4H7NayGD0/mhHqrUWvKIoiqIoiqIoiqK86XyP6+t/shhj8jwP6x+0sgslEC2TYOW1agurGZZlKRd4oi0Q0VaZ6FS0EBj+9mJ4aYbqcaS4WpIWovTRrVcz59bXyIGozNFi1Wq2UZ5RGVaXr8LfyvdEeyVHTbZYLOQGnocPH967dy+In3766W9+85uwvXk8Hj9+/DiI9+/fJ6Ld3V0vdrvdjz766Pr1616E6BpRl8HK/rFXWctc7fvK94Rs0OaZBqujhDh5DlGC1cy1fS83LRrif0SiI+Hf1eProMrBJ4iqVJeY1eaOfnHapzER4ezqSJWmaVAkf1b16odBtgU1f3H8kXWibyB+gfmwb18pipMXs6pXUjdWS3juj+bqo/14UKP39WOtfcHZMDf3IZyrJdHY1KLxRVGEmT2ALMuincPn5o819w3M5/PZbBbENE3bPUBkD/F/y54Q9aioVGbFZynYBtEdw3F5JPwdeTX4bKMOGWUoRW7dR6R8H0QVHrVOtP9qPp+fnZ0F8csvv/z1r38dxE8//fQf/uEf6u3Ns9nR0VHQhyzL/uVf/iXPcy9ubW1lWdbv970IcS+v5+G+XuWCmp2rRS9FpMDK9xHtbXQAACAASURBVMGLNxM1d2TJpj+X9gSu6a+lXDIuVKp1Z19wbuCJVq5Xf/WUy0T0M7e6dv9SyrNugDLGrCqV6tUPQNQc6xrIE53ybeQPtlyFlzFA1iHzX9UNeXb1EV7x1j8AbdaOoiiKoiiKoiiKorzRqNGrKIqiKIqiKIqiXFrU6FUURVEURVEURVEuLerT+4MSbY6/0I8i2j0vzpyDtVZm2O6p68RHeqKcI5cP03SLj9xOViERbGM1JTfdZSPn2xf3pF3NWRI9wqrjQUT0UFHVtV+rvDpeYVq6Q/Bm8aRp2u12g7i9vS0jUTnnJpNJ0KuiKCaTSdB2a22v1wvxQgaDwe7urvxYdJouv9IcOdR5xZa6/bKK0eIbo3x/yFaTTbBa/8YY2b6RQ91q+hZeKrHyJvLi3Vn+6kXJIr2SuurPhr9XReVy45yLPrja7jC5Ts3alarloPJ6kV+KIqJomrrKi48wrwI1Z+zyR9DT8jsYiW8EavT+oESjD1r1+GX1KfoYdPu1zrnZbOYLY5oxObIsk13xpbL1rEvjH192oaIoZGjoEF4osC4rrJyKxCjubgvUDJmIlWZ62YZQXhYf9ScaW8X5eBkiz3OpKteuXZPt9fbbb7///vtRRwtw8zPaWZbdvHkzmNBElGWZX+XxRq8syYt33lVWlar9B095LXi98jXvnJM6Fs05IlFeiKq9XrzFddC43Kx250gMf0NYL5FWrCqVa34xftXOUaX606EsSxlDNMuy9hiicnyTquWHMpkyUsJILZXvAz/xkL07mmlHRCMMxCzotTeWzDAacORkaZXVAerHz4saBsobwUt1htVOtY6XylZRvm8ihTTNoN9JkuR5Ln/+ZXrnnDEmnE3TNJp3qrYrnhccHhXlBfEaFUYYVTDlxVFtuQRoI/7RWbvMoCiKoiiKoiiKoihvOmr0KoqiKIqiKIqiKJcW3d78enjBTQvRjuJo4+W5+ypD+tWz0uUMK7n5I1KUEFGSJP7yaHsnM0vHg9WzLf4hkeifN6R3zlHzA+uRS0N0azRzi24UPbs4c05VSFpOBV4kjfK68O0llWG1/qMuJhNkWTYcDoOYpmmSJOu2N3PTpzdJktFo1Ov1QoIQyKrF30Z5gwitH+nYhT668uxqyhaFVP4UiEYVcQZYUZ4XHEwuHAaVPx0it50LnSfXqVn0C+iPtIjK94Rs0NXGah9DXoqWuTFWbrSaQLKqPPJyP8MXJ2vas/0jokbva0DadatEKiLOxHq/qiWRSskEzFwURUtwv9VOJS83xshQQPJUURSLxSKISZLIOE/OucViEUoVdQl/03DEOSdz8+6U8r62GTbZOSfjWsnMjTHnDuieqOpWn10SJV7lwgTK64VWYolFOOdkF4u0bjgcymDOvLJ0EhH1qSRJpLZITVvVKymudmcprnJhAuW141XFt1TLmICV1iEiK+Lhr7ZdNDjLcU+59ERtHS1AR8oQRG5GR1slulA16k8Za62cLLWPMH68io6EP9qHPuUHgIj8crw8Is7HPyjfudWifNC8ETdnR/4uLXoVnY2Gryg3STS3//HQNtFUXpBVJYtoOduiFlG23Pxqiz8SJZBiS86o5oLx0YooW3Fm+bMtj7QjS+UfQfbk9ieKaHk6n7M80vJ0yo+QC9urpfWj5Z4fJ9SM76r8kFyoXetYd6EfqWSDrg5Byp8U7b37xXXjxVMql5v2ydIqLQlW50tSVH4YiKiljdA6yXld+Fu8lAK0lKQlnx/tD+J3WUhQFEVRFEVRFEVRlDcCNXoVRVH+D3tn9hxHbiR8AHX1yfsQKXEkzUgjjy0fY8fGRjjWEbvPG/vov3LfN2If9nCEvQ7fntEc0nhGByVK4iEezb7qxPeQH9NZie4iKZEU1crfA6OyCoVCAYkEUERmC4IgCIIgCBOLbG8+A6o3LcB/+WEbAEvm3lWxW8BNrI+Ly8JyY16R9KC6YCwf5mnAXp+J1Bszz3OWFUtsjBmXOUsJZ0YenwS3nitycBML501FcwCuIlHxArYJAfggrfVp9/OIXl0M4xrFWsv0ZFzK10Aad7JxVYW2+Klav9pYnSor4V2nelxjUAvmmq9qvaKIjl0Mx7bCCW0IczB0m55iTzAtObmqsGdVJK649HaRRe8ZoI/zOC+KAjTgWO1kil6RWGvNQkzBSTzO85y6mBdFwWIy4yLZ932mx1S01tJwWVrrMAxRdGFZZVk2HA5BhAUwrSvP8+gr+L4/LvOKqgDYkr4ivXWiiRhjUIQbWQ2cyo1ZeEP0ccEVsEMBbko2eLAEbvrXAHorPshaW20EVPm59GOQcH5U6FKe5ywQYBAE5DqfdrBMqFlw8xejMcG4SsW6c7UpoHqV5znNh332pRbGFYUJg01L3NCkeKyOZnSYXmvNJnKok6YcBVqNmt6IXp03rtFg2PJM2/f9kZFKrLVpmtLJPP7eBCagrUknt4DWmukJKxUV2SVmoCqoeNO3iyx6z4aKBrbl//RWpFTl4bA6pTpuZFXldSCYSBSxPHiMuIWk+Xied+xzKfS5rm3Vzj+rT5U5clqTzewCtJF7jGdOm79w3riKhMesvY7tR6/NGyrGm9wrvDm2vC59PcsDuE35hrohXHLsqGGCiien+kZ6VZRqsnEtUvXgRSdUurzVCFTlhNpy8pTCm0AbyIW1QkWLsMl8dSDP6ocC9FnViauvvhO8/jAvCIIgCIIgCIIgCJccWfQKgiAIgiAIgiAIE4tsb36XYBsesiyr2AzDdurDRuITbp9g+dCUWZZRxwO2IRmewp6LIuzAobkVRUFfoaJIZ87J92nQVxAuhlNpwmVondcow2vcIpyW165kZqnUqKzomZOkFyaJ6uamV9klpjbkCkeU6r3iTWYa7o2oPK6O0TNw7N4unDlvWMm0NWlWp8oWErsqAbCrp8r5XUEWvedOhd6cZEjDM7bs75Fl2cuXLzudDp6p1+tRFKHYarWmpqZQtNbSMC1ZlsVxbK3VWjOXAHfxnCQJip1OZ3t7G0tSq9VmZmbw9iAIpqam8EFaaxqbCtbPcRyDqJQaDof9fh9FFkhGvW73Y3WlnR959zyvImd2ht0uXADsU4txQnEw3CarEBnjBgBVeaOrFRWJ1ajOLkp1AUCjjGviiiYDu4c3GmPCMMQmYzZEjQqLJe07wbDuzD7+2nJMGjRfrtqwmDRuPmwgqzaDwjuNcWIOUd047YhDLRINFwr/acAHudkK54E7ElU3nyonttaCMlhrWZOZ8oydmSatNbvKzjCowVFO5hOALHovCNAbV3uYjaMJXNWk2pzn+cHBwc7ODl5tt9uNRgPFKIoqTGRRFHmeF0Whj4JsIey52NmAfr+/ubmJHaPZbHok6mkURc1mk65dcbxXSsGzaG5ZlqVpSkU8fhNYt3dx67aCUyUW3hxoPmp8T2V5T54SGaktx+ZzbAIGfYqWqcZFMbJxXVhrgqVCJWRrFeWYhSzLKlYvwiThGij2jYNtwqJ6QtXGzYfpWPVThMkGVqf87ImBOZ5Syv1QQhe9MLaediwTXoMTjkQjAVNAWw0vsearbsrqq2CRaDknTzfEgAqCIAiCIAiCIAgTiyx6BUEQBEEQBEEQhIlFtje/Y+DGA9iEwHZG0W0JdC+EOm5XA4PeODJbPANloCKmfA1YIdmjKad6HeE9h2qRaI5wEsD4nJVlE943qMKgIonxEU6FjFzCaaHDFoqiPIgses8eW16LUk7lca7KYQyGw+GLFy96vR6Ig8Hg17/+9XfffYcJ5ufnaeSqW7du3b59G8W5ubnV1VXM3/O8ZrMJT6dBDpRSBwcH3W4XxZcvXz579gzFjY2N+/fvY8Ha7fbq6iqGqpqdnf3pT386Pz8PYhzHeZ6ji2+e577v08eBDzCKmA/Q7/d3dnZoJSDz8/PT09Mouqtl2gTGmGO7PW0IRvWNwnmgndhj5OIxHYcG8FBKxXF8eHiIWhQEwdzcHA35psr508yrm94tBrnIzxRFIYGO3grYCu53QBZ9AI+VUr1eb319HSMORFE0Pz+PamOMYcELqjVWmCSgrWkTs+Z+9erV5uYmirVarV6vK6WCIJidnUUtAg2kLpfM/dIYw3SMXBQmjTRN6Rixu7u7tbWF4tzc3LVr12iEFN/36VDF1ANVy/XprVBd4fxwJ5m08t2+z5qJNj2eV87I5RqfdruNYhRFU1NTrkog6AqunEHNhSZW5Qg+lxZZ9J4L42bD9rilF70KmWA+SZJsbW3t7e2B2O12//KXv3zxxReYfnl5eWZmBsU0TdnMfnV1FY89zxunnf1+f3d3F8WnT59+9dVXKK6vr3/++eeo6FNTU1tbW/ig5eXltbU1XLumaWqtpX2VPTcIAlpItvweDoc7Ozsw72T2otFo0EWvcgwB++4w7mUB1xgJbxfWmkxk/Us5HSfLMkwwGAxevXqFq5dGo9Fut6nWHZv5OKpTutlSnay2A8J5wJqgeoQeDoebm5vD4RDERqPh+z4sXZRSvu9HUSSL3vcWrXVFEx8eHj5//hzFRqMB36NrtVqr1aLGp2IgVs50Vphs8jynv5Sxt7f35MkTFIuiWF1dpbOpCg3UZEk8MtnIk8J5QycMrAmgyegZCl0DV7fd4eHhxsYGiq1WK8syvKXVarVarQqbUxQFHSUriqScRa9y1uqXEDGpgiAIgiAIgiAIwsQii15BEARBEARBEARhYpFFryAIgiAIgiAIgjCxVG3XFl4b5m6BW+RP5QSYpmmn08HABru7u1999dWLFy9A1Fr/8Ic//PGPf0zT0+3109PTBwcHKB4cHHQ6HXwE+KeByDbx7+/vU3+kzc1NdCRWSi0vL//yl79EXyNd9mSbm5tbXFzEeFpJkjCXgCzL0E1OKZUkCXVisdbSQA5Pnjz59a9/PRgMtNbNZpOGufJ9v1aroVir1ahYFAX16jTGsGpnDcGuuj4J7hnhDLHW5nmOraC19jwP6xwOaBMkSYI+ukop3/epj8ru7u7Tp0+xLxwcHDx69Ai1DsIRUaX1yjGlsB8x3YYzVMzzHDsOJKYJWKmKchSlPM9pRxDOCa01Nkocx1RtoiiiRiNJksFggOL6+vrvf/97DOnXarVu3ryJUffq9fonn3yysLCA6ZlJyfNcjMYEw5qb9e5Hjx794Q9/QLHZbEIEiunp6VqtdkK3TOU8RTkmSJgkNjY2aAiiBw8e/PWvf0Xx7t27CwsL6BAeBEGz2cQRypYjWWitfd+Hq2yCZ53oEpffD3MyoN1ZOwFusiwbGbQVwVYLgoDOTLrdbr/fR/Hzzz//v//7PxRXVlY+/vhjTD83NxeGIc6lPc+j0yFrbZ7ntBjM/kwAsug9e8CIoAhKM051KmxNmqb7+/txHIO4ubn51VdfPX78GMR2u/3LX/7yJz/5CaZ//PgxtZi9Xo8uejudDl301uv1KIqgyzFndLbo3d7epovemzdv/tu//Rv2mW63+/LlS1y4tlqthYUFXPQOh8MgCOg7pmlK5/psGpqmKZ13Pnny5De/+c3h4aHneYuLizQG3dLS0tLSEopKKbbopdlqrV2jT1uEGiPlzEUq2kg4E6C9sI2MMbVajX0uoX2KrU+CIKAfRHZ2dr788kv8egIijgpra2t37txBFdVah2FIxx7USVcN6BlrbZZlVK/YUMS6PE2pnBDTwjmhyQeUwWBA1cZaSyNRDQaDvb09bLX19fU//OEPaPqmp6f39/fRBE1NTS0uLtLI82ziOM7gC5MB/UinlGKm4NGjR3/84x9RbDabEGNyaWnp5s2bNAQj/brnwoZmZpGECWNjY+PBgwco/uUvf/nNb36DYpIkP/zhDzGWXqPR8DwPLVhRFMPhELVFa91oNOBqlmV0OjRytiN6dfGwHyth/wFiWGvxWzybHe3u7tLQs/fu3fvv//5vFD/++GO6uu71ejMzM6hFMD9HLYKnUC1i85YJQLY3C4IgCIIgCIIgCBOLLHoFQRAEQRAEQRCEiUUWvYIgCIIgCIIgCMLEIj69Z48txwlgHhQU14+COvAkSXJ4eIgesN1ul/o9WmvDMKROZQsLC9Sl8N69e1988QWKURR9+umnmMDzPCyY1pr6NBZFgY7ESqk4jqmnwdOnT3/1q19henZvlmX0h7CNMUEQYOgFeDvqXvL555//+7//O4rMt+Tx48cQgsgYc3BwQL12Pc9bX19HsV6vo5eCcnw+oZA0Z1bzzCPLGENrUomH3jkDniS0kn3fxzbSJCYHwHSS+fRubW19++232JW63e6LFy8wfa/X+4//+A90CNeOT2+apuBtyzqy53lhGGKpwIcK/XJBx2ghwzCkjjdFUTCzMHneMhVU9yDXElbgZuWeoaC3LWsCYwxtd+rLpJR6+PDhkydPMJDV4eGh7/tob6Mo6nQ61DmTNfex7cteGV+hcMIN4LFSSpcDRjCDqZz0Ew+tEPbu1VXhXnXPIK5+sjMsOMW9e/c2NjZQDMMQBq+NjY2iKDD+GRgfpja0GMwb0xjDIh0I5wEYcxSttXEc0+4cBAEkYP0xz3MWTap6IsHGtYcPHz579gzFZ8+e0bAs33777X/+53/iSAeBrFg58ZjC5jN5ntPREwrparhw5rAGYn0fJx4IbRR75NOriPoBe3t7nU4HxS+//HJ/fx/FJ0+e0NnU9PT048eP0YnX9/16vY65+b5PPX6NMbdu3bpy5QqIcIY++l1EDOjZA9o5zgAx40LFoiio0g8Gg93d3V6vB+Le3h61vNbaRqMB4TEA3/fn5uZQ/O1vf/urX/0KxZmZGYxcpZSCzga5MZOX5zldMbLoL/fv3//8889RnJ+f/973voedBMLqYm7GmCiK8CpUC11R/+///u/vfvc7FNkgkSRJv98vigIGIVrIe/fu0QU/q+0sy+hT2O3GmDAM8UFFUcRxTOe7bChi01DhPKA1DD1o5CQDcK/SRe9wODw8PMQM7REgep732Wef4WCjtfbHhFnOsixJErwxCIJWq4U3ZlnW6XTo7IHNLXzfp0NaURS0zFprZgomGFr/I6mwisrp3Sw3N/Nxz2o2m/TTWLfbPTw8pFdnZmbw0Z1O5/nz57jkqNfre3t7+N0tz/P9/X38Iqm1brVa9KscW0KzIjFDR18hLQfhZ2/neR5VKmbZ3KqYeAxZB9L+pZzaYDXjitVVRzusazS63S4N0GidD9/Qplrr//mf/8GmB7XBj8LKsRJxHNNs6Rdk4fxgM4Qsyw4ODnBGQVuN9UecsWBKOpcAHaNqVq/XaSy9/f19apGYQnY6nfv379N5Cw5VSinP8xqNBu0LnU4Hylyv11utFpxXSsVx3Ov18EboQczkCmcO2ATaplEU0dZnsxqw7SgWZHVgyjP24XBI5yFs6NnZ2bl//z6m98rhmmEkwquNRuPTTz/FVW4QBL7v01UGXUQA9I2qTeglQRa97wyn1afTpj85Z5gzGwPgDD0GEQ6YXT7JjYDW2r2KZ5iIZ8aJwnngVrh75lQinmFX3TPjRDjAS9UinqTHFeJ7xRu+u1vJ1RU77lnVN7oiHrtA4urbWQ4VIk1cnQ8TwSSyBHj8PuDWz0kuuWdYYpeRg0iFiMfVonvjyUXhnIB6xqpmIp6hByNTjuye9OrI21FkwKVx6eF4pEjPIyxl+aJwLrCqrhZdg8P+0kvsjIt7y7jjcZcmhtLWC0EQBEEQBEEQBEGYJGTRKwiCIAiCIAiCIEwssr35bKDbAPI8Hw6HuDs/y7LBYADb8dlefFW5f+Dw8JBFrirIT9Uz94CRUA8BcHPF7fjW2iiKcPsNzSpNU+ohwPb012q1VquFbxEEgTEGPd8Gg8H29jbmVhSF53mzs7Mg5nn+/e9//9WrVyAqpcIwpN6Y7I3SNB0MBkVRaCeUURiG1B1Ca00rFtxdUFTldzTGMEe4vOyDbYyhz2L1I5wHtPmgwmmdMw+6NE1pfBfmPZskCfVZ0mWvFWMMjdygHK3DM9Dd8Krv+7VaDW/M8xxiy4GoHbdzz/OY94v7juTiJOO+KT3DTOJJYBm6+SO0nt3AIdTQRVHUaDRQHAwGq6uraG+DIJiamqIuc91uF2/Xo3x6aYAGW3byBJ1EEc7AAfPsYnaemSYwZSgqx6914qEVwuqKaUVFnSungZjownw1WSArOInHtJD0oVAkVioK0yKv7EEqnBPMmBdFwQJZ0fGINigMGShqrYMgwATW2oyEzNTOrGYwGFAXblXOPAiCer1ODUWapqhmxhg6PFlr+/0+6CSzbFmWDYdDvJG9rHB+0MFIObMaZvm11iMNlKs2SZJQK5HnOVNCmtg4Ltz0uF6vX79+fXFxEUTP89rtNrU5rgmlr2CcBc4lRAzoGcBUOUmSg4MDVLt+v7+xsQHxqFjKoiiYJa3VasyoYYIsy+hcH+wd010qMvsbx3G320UFbTabrVbLGGOdoEHD4RCjZymloii6du0aimtraz/+8Y8xn62trXv37mH6/f39b775BgNXRlH04Ycfolu8tfZf//Vf7969C6ILvDKK1DqH5RC7LH4vMx8sshHkg+8IrYAN4RqRy99vJwywy7TamchGZTY5gNtRTNOUhjGDboUJjDE0kIMlkwMA+5ExhmkFXlJHMyHsYvo4LfJ9n0WtYLPk9w1qCWld0fMIq0yKe4meATMIebLZQBiGNCyQddY5bj40AZu/skVvlmV0IlKUgxSqcubGGDo5prAyM4yz6K1IPKlAvbGBzK1M9smDVR3cjiJ0T1RF0A2mse4jEHa1VqvBqoMV0lqL0YYAz/NoqZjRcFVUOA9Ycxtj6vU6Kg8dMmBWhjeGYdhoNLDpjTHh+ID/yund7ohDRaaxWZaxoFnMhuAr+L5Pp0NFUbiGrkKZhbOC1TMzKUV5xs7Ae7XWLP4Za1A29ChnIHOfi8dhGF6/fh1/lcAYs7y8TMc1hinP094JLZJF79kDFhPVN8uyOI5hYGPayUSwWag37ghnrUVlpVo7DpoGcsPMMWc446ZE0fd9Oleo1Wr02w8EG8Tbi6JIkoSm11pj/7TWtlot/McvnKGPZkNIlmVhGFprtfO7Mv1+ny1s6EODIKAdNU1T3/fxpeAF8blQQjZ3FC4SXf7YrJ01MFv0suamvUYRtQHR9/1Go4GzB5iIYHMXRWGMYUGYITc2yVDO4BGGIR2lYNcDigz3Qwx96MRDq04dZ77YVXYvE90zVLTWZkc/IpKWfxOiVqvRYM5FeV0KE1DMqij/t8e1IdWL3rz8LztVLiToJJxh75JlWcVMiKkoK9V7AtSYdb7espoMy5uD2PKyKM848zynkdvdinVVjjUoFWF7lDrSRixkURRFUbBVLhXDMGTLlQplEM4K0CVsbs/zms0mncZ4ngfTD2bGoyiC/yWAaIyhg0JRFEEQUDuQlkO1s9bX5UWvLv9XLU1TYwzerp2vrtZaeAXf+XTCTARTZuGcYGYBuj+KzHyp8jiIyqC1bjQabNFLU7KhhwE2BNODMqAYhmG9XseBzDj/FmZUXLq0jJ2iCYIgCIIgCIIgCMK7jix6BUEQBEEQBEEQhIlFtjefDZr8phbsQ6BbXHBXAz2vlKLbDOCq1ho3DMB+FbwKW3Dxdq11lmV0iy/bKhNF0dzcHIpTU1M0zkEQBPZoGzPb6xIEAd31x8ochmGtVsOCRVFE9+QYYzBbpZS1FndlAI1GAx0G1Kj9WrQwuMcMqoLu7WG/x80KGQQB9dbL8zyOY7qjg20jgY3l9IxwkYCSUM2nHUE5+4IajQbVfHY1L7vLep5HXeVBl1C01jabTbodCB+ty9vJ4AweW2tT4nIPiakS0l1DSqkgCOiWJFbIiYdWnXJsDhNd2O0nFy3Zqci2Codln17WIqbsZ1sUBW1uOIPF1lqz3bOs9XNnezO96nneuO3NeZ4zC0kBrcNb4GXLSSYcrEZ73A7kIAiYTwTtrbDVkOaWHe2KxzN4DND8XfWm6WkkIfaUWq3GfHppqZgfB7wjisI5wXQJRhBsCGttvV6H6QfrnkEQUJ9e0DHaPVutFk2fl3e0mrK3gtaa6RgV83LAVO3Eo8LyM1VnonBhsIkK9XRQoywMPYOtr7WGWTdeYnaP6SR9onLGCLBUeHsQBDMzM2isYBDExGpUIRlU68pXLguy6D0DUBdB9DyPzpZgsQq2zBhDzQ2b9cKAhzf65QA8SZKEJBSHMabf7+/t7YGonEXv3NzcD3/4QxQ/+uijhYUFalJhmEcRabVaGL1NOV1oampqfn4ee0K3263X6/giQRBYa3F6l+c5zOdAVEqtrq7SpTh6OwO1Wq3ZbKJIeyP2eYDNX4vy4tkvR24AKrprdf9kNkU4c7TjxKuc9qKiO1dgU0N2L828KAo2nXUXq3AAKjdON9ynsJSs47CvNvZ9Wp+41eg2LjtDYfey3NzMGZhz7nxkpC2SJMlgMMAEQRDU63WqGK61pLmxEJpRFFETxJQBlBBFz/Mwlj57l3FWGtDl7zLWWfhNPNTys6pjJoWJrGJBxKrTo2IIVagZu8TGNf/IqVJrHRAnT2gvWgyWDyRAsaIAwtlCqxp6GZ6x1iZJAlqntWY6xlYj1DNcKeWX3W6V06YVoquieGnkGUyZlsPUB0FAvwLbIzCBcB5oZ5KTJAldArCvci60yej56uaDh7J7x6XXZc9wrTX9Lqwcs8nGUHq12mC+RaqqWHhtQL/hmOocU5E8z6laQDI8AwYU08MxXtVa5+V/TbB5VRiGU1NTKDabTRq0tiBTf/pQpZTv+1TR2coc1pO46IUlPX1Z2gPhgFp5+sVUOeuNZrNJ/w9cAet7zHcfJxmAPuWnTWYR6EgjnAfQQFQJmR1nImsR7zS/5FEUBU5ZlFJaa/otSZFnsX5xWth3Gc/z3PUJipONW5NuF6Mig93LcnMzHwdTG102C3EcU6MRhiGNf1aNtZaF1ms0GjSulbvoZZsR0Dizd2GGjqHf+0VvTv6FzmwIdYu6YgAAIABJREFUm3WxiqU3KqVs+SMUjNR4C4zFJ1QGpdRgMBgMBiiigTLlKHrHwtTm5KouvCGsrWnNW2vRtoOe0GT0xjzPh8MhHWuiKKLpmcZWU5S/lEHfp7eP6/hxHFNtZJbtPTQabwvWXnH5d87CMHT/VTOSvPz1FmcsALMSxpiTGy41KjdyUanxagbgVVv+cZnLwynqQhAEQRAEQRAEQRDeLU767xHh5Pi+32q18PN8GIZFUcA/Adiet6z8Cz3uV0MqhmF469Yt9LY1xvz1r3/9+uuvMUGtVqP/oU2SZGVlBUX2H9Td3d1vvvkmSRKt9fz8PN1UPBwO6U+Zr6+vP3z4EMWXL18+fvwYPx0NBoPd3V38ANlqtaampvA/zFEUsd0RDFZm9v+6nPxYYlb2f6jVavTfMvAPZxRV+X9Hxpjqz07sfynsQ9ppP5UJp8VaS7eBaefXFzTxmQfcJsNj1tDswyd0KzyjnV0A+P3VL/9uNnwBpcWgH8ghW1ZmJrKCvT9KxV7cPeMmqOBUiSlJkrBtftQaG2Oo3dNas/+ysueyf4/QXTlKKWMMte2gHvQqzQ2OqS7hJQbTIrcawdbRk5MNrZDq7gYnqUjTs67t1rObG00fxzH9L5yrS/gsqlRwnhYjLztu2PJ+EOP8iJpwTtDmttYmSUIbwvd9mKvQlnXRo8YapqV4rEZtDmJbkJgyKJKD2+vxEvW2U87/G6FU7u3C24U1tyINyjwZWYNW61ie51SZtdYsARPZ1LooOxLq8rhGc2P5XB5k0Xv2eJ5HN7ZFURQEASgK2/PGFIiNu3AVz3ied/XqVTSCcRx/9tlnGxsbmH5ubq7dbqN4/fr1GzduoNhsNqkWdjqd+/fv93o9z/Nu3LixsLCAl9I0pQvRXq9HF73r6+tffvklZtVoNKiLbxRFzWYTf4mXTStd2M5SRlEUcRxDtdAtqcrZg62UYj2TbV3DYxfIn6ZhMw/qhSWcB/B1A9sX5nYVttiWP2Gw5jvWjptRSw4kTVPYDAafbOjVohyEhnZP7cx+WDHcIrEz7zMXUxXYsoC1li1EmXFGBxBMgMfQ+tRKROXgIq7DBX0WU2A8qY6rClfNGO+bXtGaPNW7v+HqkSqGclSr2WxSXUKsE/2OFbh6SsCms8LFUBRFSn7iW2vteR795l4BHWug81aoKCxIUBzpd4P6wJRHO9+F4aQiS/RxuHoovHXc5SX0fWstG1yU8++iCiuRO/HPWOszFfU8j41cdNQbp3KXmbFVIwiCIAiCIAiCIAjvOrLoFQRBEARBEARBECYWWfQKgiAIgiAIgiAIE0vVRn/htWGuOGEYgsj8iHCbPkLvAs9GPNNut2/duoW/oJskie/7V69exfStVov6Ed24cePGjRsoLi4u0r37nufV6/WiKHzfn5mZoT69s7OzdNe+MQajZyml4jju9/u0VFevXkXH3Xa7vba2hoGsPM9jnrfslZkDQLfbpb88fHBw8OzZM/ReoJVz5coV9BxWSs3Ozs7Pz6Ooyl4NzGlBOa4I7Krv+6whyEXh7NFa03gJbr9g/pNbW1u7u7soBkFAPaxardbCwgK2qS47O6Vpure3h65TWZa9fPny8PCQJgBfmvn5+Zs3b6K3TBAEzWaTdmGmNq5YoervFa7nj3qDCmG5MS8jOIPHg8Fge3sb4ghubm5S88IKMDU1BUYSxHa7feXKFWz9JEm2trZQbdI03dzc7PV6ICqlvHIYs7m5OWqgpqam6O+TK+fp+ArUj0s5Q8lrV9oEQ3s6PU9d7pVTk8xXjZEkyeHhIbZFkiSvXr3Cn6QqimIwGNBAZb1ej/5g1d27d3/wgx+gCP7hSql+v//dd9/t7+/DeWttVg7QyNw419bWrl+/jqI5LiKjcB5orelMjBp2bFkA5mxUIemN1tp+v49KVRTF06dPX716BaJS6urVq1euXEGReXXu7e09ffoUz+R5HscxVZ6ChJzwfX91dRVmYo1Gg/56pfBWAPtDTZDWmnZ2NufZ3d19+vQpimmaDodDyCEp/yb8zMwMjeYzPz+PywSl1HA4PDw8xOd2Op3nz5+zIIt4DMsBXEdorVdXV+lAZsq/RO3OjSG3y2yjZNF79tjy755prcMwHKkKYBPpmQp8379z5w7qepqmMzMzOzs7NAHN7caNGx9++CGK1FIrpXzfr9fr1togCObm5paWlvBSrVaj0acWFxdv3LiB4qtXr54+fYqmdnZ29sMPP8ROEkXRwsLCyBgeACsGq5BOp/P48WMUNzY2PvvssziOdXlRpJS6efMmHR5u375NF73VT1HOvFlrTdOw9MxUCWcOtC87g8fW2rz8o5rPnz//29/+hmKj0Wi1WiiurKwsLCygArDmS5Jke3sbV7mDweD3v/89HV2Co9+Iv3HjRhAEqMzNZrNer9OuUd15mVK5vD9KxZoAaoadweNjYbmxqaEtr4H39/fv378Pzf3w4cMXL17gJfZjqteuXfvkk0+wJGtra0tLSzjA93q9Fy9edDodEPv9/hdffLG1tQWickp19+7djz/+GMXV1VUaPx8mxyjCeAG307FDOTWjnSGDJn4/Gac8eZ5TxWAVywYURhzH29vb+I3j8PDw/v37uFjN83x3d7ff72P6fr9PQxBFUfT9738fxSzLYEm8t7f3xz/+8cmTJ3C+KIpOpzMcDjEli0b5i1/84tatWygqR82Ec4IqldaazvWpYc/LoafYly84g8dZlvX7fbQ5aZr+6U9/un//Pib4l3/5FzoTYwr86tWre/fu4eP6/f729jauXmw5sGK9Xv+Hf/iHDz74QCm1uLhYvegVjboArLVFUdCxiY0CTHO2t7f//Oc/o9jr9XZ3d6GJadRPdTRUoXj79m061uzv7z979gybeHNz88svv6Q2h7Z+FEU3btyYmZkB0fO8drvNFr2sazDlcZfBl43LXj5BEARBEARBEARBeG1k0SsIgiAIgiAIgiBMLLLoFQRBEARBEARBECYW8em9CNAJxPXXYvvjqQhOGlSkHiOe5y0sLDAPQ7qfvt1us8zxWCnVbDY/+OCDJEk8z5uammIOZtTNHRKg6Ps+xuVSSjUajdnZWRrsp9rlTJe9ba211Ffz8PCQOt31+/2ZmZk8z7XWLMJHkiTPnz9HcX5+nnpYeZ5Hawa8KVBUJGwM4JHgE8rxm2JVJ5wHrJJpE4DnG23fR48effnllyjOz89TnxaI0IZ6mKZpt9vFrnRwcPDgwQMMH2KtrdVqN2/eRDFNU9TJ7e1t1LrZ2dmlpSWqV6w7uw5dAlDdg6qvngTaCqzz9nq9R48eQewDz/NoIAC3m1OTEkVRp9NBQ9HpdLa3tw8ODkDMsqxer2O8EGa6gc3NTTxuNBo00JHv+9Q5CqwiFEZXejuLgrlgdbG6glpF0W1uPFbOGJGm6WAwwCbr9Xrdbrfb7YLoed7a2hqN7/jo0SPq4J3nOY2NNxwOIebZwcGBMabRaOAlGoxAKZWmKfUR3dzc/Oqrr1CcmZm5cuWKq2nCmUNVxVo7soPDJTpJY2lgKoV6NRwONzY20Iakafrw4cNHjx5h+k8//ZQ+N45jGnSg0+kcHh5S9aDOlkVRJEmChQmCoN/vg06yGCvQEfBB415NOFugkiuqmrpkK6XiOKaBEo0xq6urSimtdRiGdJo9NzdHp+hzc3M0QspwOHz+/DkqYbfb9X1/XNgd3/d7vR5qke/7/X6fLgdcn148dsXLiSx6LwjQBraeNMbQUdmUA6Mxi2mMCcOQpo+iiBpcVdY5mFeRiyVmZmZ+/OMfU8OHl9i4G4YhXVFAmZneM11nAwa5wiciaZrSCnn16tWDBw9QbLVaKysrsCKt1Wq0cr799tuNjQ0UZ2dnaZTLRqOBwcPU0chES0KXK1AkWqqiKOgEiF0VzhtbDvmQ5/n29jaN2faXv/zlV7/6FYrXr1+nQYMajQZtvuFw+OLFC5y/bm5u/uY3v3n27Bkm/qd/+qebR4teSADzEmvto0ePUE9WV1dv3ryJM11rLZ1kgIpWjAcuxyaYYM7w3ekEDkTa+vv7+3/605/W19eVUj//+c/v3r2Ll5rNZrPZRPHBgwe//e1v6b13795FS7izs7O+vo7fSnzfX1hYWF5exsTse9/29vbDhw9RbDQa1EDVajUa1l474alOCHt39f6tirG5QaOoXrFxyq0rKhZFkWUZnoGQp7jk6HQ6u7u7GPq71Wr94he/uHPnDt77X//1X3R9AiYLxW63C0GwhsOh7/sYZsbzvMXFRRq56v79+6CrwLfffkvjjX/yySfLy8vvWxNfPK5JUWXVwuOiKNI0xcRMCeHbB85wut3u119/jZ/10zT985//TANZ/fznP6f2p9fr4QpZKbW1tbWzs4O5TU1NffDBB7h6ybKs1+vR2VSn0wGto1ZOKWWtpapujPF9/wwNsjAOc/RlE2B1nmUZbb5ut0t/ouLKlSt37tyB5e7S0hI1GlprmlW9XqeDS7fbffDgAX7HhxUvJtDlCXlRFPv7+zTxxx9/TKNeRVFEv/u/i8ii9x0Dldtay/SVdaFqK0bvdWcDDJoVmEhykVOdVTW2PGG11sKCE0rLBnuasij/z62ak6cULglMMfJyMOe8/INGbvsWRYEJYHaLt8M+ArrkwLkyPBRzY93EfYp7Rnjr2HLob2pDPM+jpswYw/SEtj6IeNU65ve0BgpyoGeEN+EN65P1bnYGjmkCqjzWWjQaeIYmtkfmC05iSrA81Pjo8v/5i/Iv4lCNEi4JtL1cqCaAGuB30vwImhiPQWTKwM5QmwPHKEJKqnXCOwdrOLAVYHnoyHXszJ+NXKpsgpiIaqNGDVsTgHwyFARBEARBEARBECYWWfQKgiAIgiAIgiAIE0vVPlXh9YBtb7grQGvNtjOxlFRkewloAsgEE1hnfx2mAWw5RhSDlortYYCNMSgeW0i3zBUiIy//tnu320WvOaVUGIYzMzNRFGmta7Ua9c7/9ttvMayIUopGGVFKeZ5Hf55blYvBXoFWBT1Jxcnb43HZYFqnyjtRG40GbdBGo0G9VqpdkvI8pxFB4jimuwSNMe12e35+HkRrLXr/giMfdqKpqSnqCqXKToOsm7i43YpcnHwu8t1p/o1G48aNG+D5dv369ZWVFbwUhiHVoiiKsixD3UiSZDAYoM0ZDodUbTzPm5ubQ7VRzkvt7u5SV6gkSdiGfDyuxrU8FaaJWbb3AVv26aWwMxVjJYg0QRAE7XYbvdc8z7t69Sr60UVRNBgMMC6AtbbT6VB/vCzLaBOnaQrKkGUZ+NTBed/3Z2Zm5ubmMOX8/Dx144yiiDYo2JD3rYnfCqzatdaugimljDHUxZF5fuV53u120Q4MBgNjDLZ+EASzs7M0LkCj0aDPjeO40+mg2O12B4MB9emdmZlBnUzTNAgCnE1lWYZBsw4ODthUkL4OHIhSvRWoUtlyULR+v0/jmPi+//LlSwjrE8cx9dNm4STm5+fHxalSSjUajbW1NRzXmGInSfL06VNqgrIso1P0Y30bAciW5nx5qHoB4fXQTlQSbHvYkU8vMZjTjud51Bix1Smdc7uweFSq3ME8z4P+AzpKOxt1O1FKBUFAFd06brdUhHenD6oooVIqjmMa5fLly5c0kFW73b5582a73TbGQGwqvPTHP/7x5cuXKL58+ZKKWms6luhRnyEqCkkTA0wUzhZbDq2htfZJGDZjzMLCAo1PyKK/VEeQStN0f38fAyEeHBzkeY5pfN9fWVm5ffs2pq/X6xCE5uHDh8+ePcPVchAEw+EQu4bWmgZLgzPs0RTWrYwx1YvkCaO6B1XU20hYbux2Ki4sLPzzP/8ztP7HH3987do1vJSXPcO/++67OI6xjeADHP0CQiPWhGF4+/btmyT+WRzHNDcaplUpRee+Sinf98Hw4plxNcAMLLP5kAntOO+VUinSiPDutHKYGXdrhiUmV1Sz2VxdXUVlSJJkfn4elQFWFBh311r77NkzGmo1jmO6Bh4MBqAMWutarYbB8MIwvHHjBgRlBeI4pqXq9Xo0W9bcwjlhyzMi5XxXxWO23mAdMI7jly9foh0oisLzPAy5XBTFRx99RMN3z8/P0+d2Op2nT5+i+OLFC/oRdmlp6cMPP8QA8nEcb21t4WjV7XY/++wzmE2trKyg6qqjuR8zI3gsnB+snrXWtBXg6zyKOzs7dDK8u7ubJEkQBFrrer1O/wPUbrdpQPgf/OAHqBUuCwsLP//5z+n0iQI/k0E/tSRJQv+fFAQBjVrPKI7CAWqtfd+vXuy8LWTRey5QVaaMOw+wLgEiu8XtNlSk2PJsSTlj/Lh7XQtYXYaRZ04IG13wiziQ53kURfV6Hfo5XfRqremsIk1TKuZ5Dh0PzyjyFvoIepVBr7722wknxB6BZ1gDse+LzJ6601kK6BjOFUA38KrWOgxD+mU0iiL4B6AxJkkSHIfSNGVfnfQp1xj0XlGqi8H3/ampKTAd7XabfiBPkoR+FvQ8rygKtJkwfleoTRRFmJu11hhDTZAxhlq2/LhYa68Ny8o6dm/iwRpwa/VUVUETw8IAW9AY02w2cQCCDxw4F7TWxuX9I8xQ4AcvYwy1Xb7vwwCHKVlYbzoJVqNeUDg/sLZBMUbqknb+w0EpioIaGeibOJYVRVGr1ehyha5klLMPLk1TapGstVR5jDER+TmPIAiyLIM1cJIkVDlh7kdfR/TqMmCtpQ3BJsODwaDf78OiN8syOiNimkmHIRff91utFv0XAqUoCjbXomMiiOTiCNhbXEJOMWMTBEEQBEEQBEEQhHcLWfQKgiAIgiAIgiAIE4tsb37L0J0A7q4Atm/B3Vrg3oJUb7zRWhdFMXLHDmzBoiIrJHsozcTNkCV2RXoLbAdCMc9zcwTbkMOovqqcgrkVSwsGjyPXhfOFNZ/bWKADeCYIArrXPQgCujEMUmKDFkVBd7+DUqGGwwEmhgMoQFEUcRzjFiPYJIYpXQ1xdZuJFe848Zzt+7KapLrBqj0IgmazCa2cpimNkzccDvv9PopxHFOfupmZmWaziZsPkyTRWqMFBjNIDTIrBtNY16RADnBcXTn0jdjbaa3dzkLFiQerHV6c1U8F1RWly8EptNa1Wo1t/KPbCDXZtqrGNDf+pdnSNC7GmJP7cQgXBu28FNiQjJd6vV6/30evbGMMDZ4H3lt0IFNK4e5ldZxPBPT9Cl3KjkIQ5XlerUX6/QuA91Zw24hWuy6PILVajQbvnJubW15eBm1hvjbWWjqQdbtdGihnMBhkJK6eu4hQpBi2/FPScIYW2zVrrCSolu7LXhJk0XsGsIZ32xuvuueZxtAzuhyZozgCr+rystZduVFPRXoJRNoNaMEgwBWKqmyIWZnZqAz5YG7WWlpmNcpDgN6eJMne3h6KED01iiKttT8mkgSKzKzDo/EqS0+x1iZJQvt5FEXMZaLiduHNsdZ6JGabW+HMibfVamE4EKXU9PQ0i2uVEyfeJEl6vR4OA8PhMIoiTN9sNo0xVMNB2ZRSaZru7OzgjSsrKykJZcS6G5ypUHXP895bpWIVpZz+eyqgd48TVflxvu/XajVoiIcPH3799dd4aW9vb3d3F0Wt9c9+9jMUV1ZWrl+/TmMO3b9/H/UkTdMkSZgTL/XGRM9wIAgCalQ1WT+D6C6TAKZFbhpmq98rvVJHVYcibXrWQ90apiKrN9/3m80m3m6tbbVa2BDdbrcoChqoTGtNIxJFUcTaBe6Fp+CD2EPhDL2RhY2BbFnOwplTFAVrGtZM2VGYd2st1bFer7e1tYVWYn9//8mTJ6gnjUbje9/7HoZ8z/O80+nQr/xaaxo0CJYrKNIpilJKa03HFEiJhcnzvNvtwmwqjmNqi0ZqHTsjnAcV45Q6+iaC4uLi4t27d1G8fv36P/7jP9ZqtSzLNjY26Dz5+fPn9GPu1NQUnQ49f/6cBuCkcxjlKHBRFHEc4xLa9/2iKNjIhcdKqTzP6SDoeR7+++HSapQset8yFfqnysYIDirSM9GUl6PsKsyl2OMAU/5Pr/u5kT202mKOfC65Xuob0OVQzLIM3gIeUfGU6quqsgfa8sctLV893wa0gdzGYvM89p/eMAzZf3qp1oFdZv/pxfTwMYW1OBSgKIrhcIj/6YVYNZjSLaSr6nSa4nneeztbdevqDWEZMpG2Ap1JJElCfwRiZ2cHwnQD8/Pz165dw6xmZ2dbrRZ+N4QI4Wi7QBOoKWPfZTzPY5/h3EKe0M7QZCMVtfrMZKO1xldmIxqrYbe2K+qqem2ZZZm1tuI/vTBmoaiOng5/8VJFAQA2FlcUSThDQKlQYdymtEd9n+lYkiTdbhcV4/DwsNvt4n96QUkw+l2e57Vajf2nlyoVLq0BV4Gplrq6lKYpzKaK8r8WhLfFSEVCUTv/6Z2ZmUFxYWFhZWWlXq+nadrtduk8uSgKGuP98PCQhl/u9/tUkdj0G8BiwKSFTYZd1UKwIwAwzFWkvwyIDRUEQRAEQRAEQRAmFln0CoIgCIIgCIIgCBOLbG++RLBdAe4mAbpzwN1F4KavABKPvMXNdmQyoOLSSFhubHeEdsKBFEVRFIUetQGV7thhCWDfCD6oeoeGciq2fFF4+7g7u1gzVWwD01obstVfa10UBfpK5eWfdAbNwdx830eFhI3QcOwCD6UJqFIBbsGoKJwJtPmUUkVRpGkKZ4bDIfWgM8bQH8lsNBrwk+AghmGoiVUZ2Xasuf9+2SkGM0GgG3hGNOHNOdZEuLi3UOhVMAsoFkVRr9fp5kO2E1UpBT+RCoCfjjoapzBlMcrDiD2IKTMeC+dNhf7Qzkux1mZZhluUsyyj3mF5ntPgeXme9/t9GoKIiVmWuUajYj8zUy10sDRO1AP3XuECcDs7g7aL7/tuVAgAIt3gJVMOSlJtJUBJaBpXN7AYcFBRbJoYgfTu+UuCLHrPANa6bmO7ZwBd3sQPoIYxfdJa0ym4m0CVtbO6VFpr6gZJcVMyhxD2FJaeop0ALSyrXq9HJwe+7y8tLaHYbDYHg0G328UZA16q1Wr097WDIKDOMMwPuaKE6qgqmEcWuS6cO6An7AwVYfaAorWWaq+1lv6MO7qCgxiGIY0xk+d5t9vFwA9FUWRZRlscpiZKKWPMwsICBpKZmZnxSLQtGDloOdncwpT98WzZCZBdnXgqTJNyhlVrLatJ9xbElpeXeZ7HcYy3HxwcfPfddzCVfPTo0cuXLzHljRs3aKSQmZmZ5eVlfBBYNuoKrohTJSgYinAXLXOaplQni6Kgze37PnX7hGfhVYolEQeVUnrU5z8qvm8wvaK1wSqKwXTM1aK0HLUOgrej+Omnn6LyWGtfvHhBg6KlaXrv3j0UgyCAzyvW2iRJUDGiKKKzVaVUTiLwKaWGwyENxEod+YTzQ2tNTT3TK7gKfZ91zyRJNjc3cUrT7XYPDg7Q3zKO4/v3729sbICYZdnnn3/+9OlTEJVSvV6PemPCg1CEqGaoHhDgE68WRRHHMT46SZLp6enV1VWlVLvdpprjeV71B1zhPABVQRuind+k8DyPmqDp6embN2+iuLq62m63oyjK83xtbQ3DoSml/va3v1Hj0+/3memjT7HW0t+kAB1DZbDWGhLxBNSPlqpwogPS5be1Nssyay3tI5eN92jWda68tgVxb3TPAMwCjmTcvQC7Wp0Y0VqzlKxHVeM+lJ6xzkqArk/CMMyyLEkSY0y9XqfP9X2fxqZm9gJ6Jh20oB9iAopbseNSCudHRZ3bcqQxgDYZ06I8z6maeZ5HfyjC9/0kSfCDOoT2pda5OPo/sNa60WhgPhDKiCkV1UldXrqzN8qyjE1w31sqOiPAKrY6PUvMlivdbvfZs2cQQPXly5c06OXt27fX1tZQnJ6eXlxcxAfFcdzpdFDrilEBXSuaG7UIRZrYGMNuH4dbFVSsqJb3B6wQt4HwWDlVp8qTOVtevcC4gwngQxgm8H1/dXUVIxJZa9ln02fPnm1ubqIIQdHUUT5orHQ5iLc6snUoQjGoiMfCucJ0iYE9l60B8jzvdrs4uPR6vTiOsQXzPN/e3sZlbZ7nGxsbz549A1EpNT09TfeeTE1N0R8pYItVulZRR+sN+pEuiiL4x0AYhlS3K95LOFeKoqC9G0YBFNmIUK/X5+bmUGy32xCw0/d9piee59F/HdHhD6DKDIYOLYk7EhljUHQXve4ARO/N8zw/2jp3ktHtrXBJiyUIgiAIgiAIgiAIb44segVBEARBEARBEISJRbY3C28ZtsGD7b3BDSG583PBLGV1PsLlB7fNnHnbUX2AYyrSLYWwe4eWhN0Ix2/OGWYlVEPbl1U73alF251dUs6NSqmi/OPe+BewTuQqPBbeCag+gAqhFsExNRqFE5KKtT6KLFu4F1Memw+5Ilw6dNlRE47pZlEqWmupiOlRpGoDIh4DTCeZauHt7o3CW+HYhqB9n7YmiGh2aLsDNGfj7JrGY4Ddzo5d++Pm8E4ji17h1NA+UBQFeK6T66UErucJTdxsNqmV/+CDDz755BMUG43GvXv3giDQWtdqNeo0tbu7S91dVldXbxKn/6mpKeadD54GIGrH34CVio09wnmTZdlgMMAlhDGmXq9jNAVdjrUACailpj4qSqmi7H5Zr9dXVlYwckO9Xr969SrqUq1W+9vf/kZdYjqdDjhl9fv9tbU1LNXa2lqr1UJPcrdUcBKP3U5Bg2+xGyee074vTf8m93a73S+++OLFixdKqYWFBRr/wxizv79PU2J4M6VUo9GYm5tDPen3+81mE904lVJ//vOfHzx4AMda6yiKaPseHh5ev34dxaWlJeqFBaGhUaxAOw5XJ7zxPQEGIKWU1ro6PI/bVekZ5nLf6/VevnyJ3pjD4ZAGKPI8b25ujjbo9vY2+I0DzWaTDmRRFEHiXq/39OlTjDoDHnpPnjzBlN988w118lxeXv7oo49QpD7nwoXB5g+bFzdgAAAgAElEQVSKrA08z6PRJRYWFn72s5+hY22SJLu7u6hFWmuIwQtilmWe59F4nD/60Y/u3LmDYqPRoCFO1tfXd3d3MfN+v/+73/0OlTBJkp2dHRzmiqKYmpqC3FZWVmi0IVAhOh3CS8L5oZ3YTroclfDw8JCOR+vr619//TUVHz16RJUNyfP89u3bKN66devWrVsoFkWxvr6O86XBYPCHP/yBTq7wr1IqjuODgwMaAKXdbtMw9fQHDpSjPIaE57y0U2hZ9ApvhD0K14ZnWJdgC0hb/rAdhmEYhiguLi5eu3YNxaIonjx5Apn7vk/zGQ6HdDyYnZ1dXl5GMQxDah3Yypz1c0jAFr14LFwARVEMBgMczv1ysH41aq7PpiA0UAcoGKYPw3B2dpZGupqfn0fRGMMir2LOnuctLCxgPvPz8/V6narrsbB+IXp1Qths4FRoramqDAaD9fV1WFe0Wi1qXrTW3W4XxaIoqGlaXFxcXl7Gbxy1Wq1Wq6FaFkXx3Xff0YhEzWaThtar1+s0EP3U1BTVHPr97liYRWUd4T0HBiCllCEB28fBqo6JdBQYDoevXr3CJUSv13v48CEGUvY8b3Z2FuO6QwIarPv27dtXr15FEft+lmXdbndnZwfOw1ezra0tTPns2TMqLiwsXLlyBcXp6Wk8Fi4SZhzovjP6qavdbjcaDdSiLMv6/T77IEuvbm9v04Hpxo0bN8m3+1qtRnVsMBjU63VU8jiOv/nmGxxTiqKgsdY8z5uenoZvfPTjHUCtq3U2zQnnBJsAsDFuMBjQOItbW1sY6Fsp5Xne06dPwf6HYUgbtCiKlZUVFFdWVqj46tWrRqOBihHH8d/+9je8ao/AM4qotO/79XqdzrTBZKHI0E5Q2EuITMIEQRAEQRAEQRCEiUUWvYIgCIIgCIIgCMLEIoteQRAEQRAEQRAEYWI5hWeRIKhRPgDMXYS6vijHb4rFHPI8j96+uLj4k5/8BMXDw8PNzU3wRmBeB+BgiSIL1eB5HktvjMEz4GGFBbPi0/K28Tyv2WzSQFbMMwRcWVC8cuXK97//fRSDIKCtv7KyQp1n4MfcMfMgCH70ox9hkKE8z/f392kgqyiKQCfb7fbS0hLq5/T0NHXaVI4ruKvqtC8wVReqOXmXZLoBvRvbpdlsXr9+HZyUlpeX2+02piyKgvpy53lOPcPDMEzTFJusVqvdunULHSzTNN3a2oKAZwBzdlpYWKCR9paWlqhPr9aa6gYrv/s6VMRjgBk6N8FkY4zBinV95mnl2HI4CWMMTe95Xq1Ww/TtdntlZYUGDSqKAj3AISvMTWs9NzdHfTuXlpaopoVhCKaj2Wx+/PHHVDFUuZDXr1+n8c9u3779wQcfoNhsNt+39r0kMNVica0Qt7c2Gg2qdfSuLMuuXr1KfXpXVlZo0KAoiuiIs7y8fPv2bZw+pWkKagmi1npqagrVIwiCtbU1yI0GF1BKZVkWxzGWxPO8KIrcviOcOa7O0O7cbDYXFxdRTNMUQ6AppZIkgebWWuMUBZiZmaHWZnV1lbbm4uLip59+io/u9Xrb29vMzxyPfd+fmZnBqbUxZmFhgU7GXPtTMQW6nMgkTDgd1lo6NdTlmJm2HNfK7QN5nlMrz2Yei4uL1Mpvbm4mSZIkCWRLn7u6ukojVy0vL7PQR+5cEAsDx7RsbjmFi8TzPPoJQzktwsSlpaXvfe97KPq+T8eAhYUFqlRBEND5aLPZDIIgjmMQh8MhRvcFGo0GhMRcXl6+c+cODepAdQwmvhUWn2ms6NjFoMuL3kajsba2BtrFliJxHLNFLzVNzWYzTVNcUEVR9NFHH2GDxnHcbDZpsM0kSehMYnl5eXV1FcWpqSmqhEU59Joi6mGcH5xg02g8VkefIOmZ903N2AhCYTXj1jm90fM8OreDVsD0g8HAWtvr9UCEEEQoWmtnZ2fpUnZhYYFqWqPRgCC9rVar2+3i1DbP883NzU6ngymvXr26sLBAxbW1NRSFtwXthkyvKLocyMfzPNrrGXmer6ys0A67vLxMF73sY+7S0tKtW7dQJw8PD589e4YDGXzbpfbqzp07MEdiX5AhvBYudcIwDEhMaeFcqZgwNBoN+mGUKc/BwcHz58+zLNPOovfGjRt0rGE/ibKwsEAnVxBFD9VGlRe9URTdvHkTlVBrPTc3d3LdsO/CP5BO+jKCIAiCIAiCIAiC8M4hi15BEARBEARBEARhYpFFryAIgiAIgiAIgjCxiE+vcDqYKyNzF1FOyAe2xZ85vbDEvu9T94P5+XlwYrHWZllGfQ/m5+fBSwoAJ0yEuW/pI+gZPBYuA6xFmLMiE9vtNnViMeXAVyx2iCpnrrWmzjP1ev2jjz6ifnTg46SUmpqaqtfrmLPn/Cw79AU4hks0ge/7VL1P7hgjvCG0s09NTd29exciTjWbTRoyIM9zaiWKoqBOufPz82EY0lajgY7CMFxdXaUOeCy3ubk56tXJIg4AmBstMNMxeglEclEo9UFwxGVX6XGFqMp163lerVbDnD3PW1xcxBGnKIrZ2VnmAU5Va2pqig5JaG2CIFhYWGg2myAWRTE9PT0cDjHl9PR0q9VCkaqQcJEw9aDd0FobBAGMC2z+Y8sRT+AMHmut6SCitZ6ZmaEWZnp6mrpxssxrtdrS0hLqZLvdDoIAYx35vg9nUGy1WpgDmw7V63UsmOd5MjZdDK5SkYvKGEM9dVlcK5i05HmutQ7DkOrG/Pw8tTae51HTpJSipml6enptbY2OdFS3fd93c2OzKQp7BSZeTjSz+4JQDYT+Q9HzvCiKTq7rLLqP7/vMso8jd2LhVljqLMto4DvP88IwHFdIGKhoR6jOXDhvrBMjirV+EAR0eGDk5YhEuhysm4mqPC9RSqVpCirqeV4QBBVqkyQJLZW7yh13r8Co+EjhigzQFhTZ2tUYg2FamPExxtD2YjMSVX6uqzaMintdiqJg8fxwNsxuZB0BioGiW+b3zXDlRz8HoLVmHZBVHWt9rxxNnVUsoygK2tm11rjsAYbDIW3QKIpGfuZQp9QT4a0AJgVb6ti+j+R5DnE38QzrvFEUUbVh/dd9hHsGSZKk2+2iSnue12g0qEqjSWEDImh+Rc7COcHmmWwAqgaCdcPtzNCFYUjbnYV99ssBOEEZsBjGGJabOwCx0Zlyqle4JLxjxRUEQRAEQRAEQRCEkyOLXkEQBEEQBEEQBGFikUWvIAiCIAiCIAiCMLGM9YsThJGA6xSK7oZ+1z2POgkw16lq/wFNol5V38h8Y1Q5CAQrJCRm6YW3y4U1h9v6TJdQW1y1YV6CpuzoxUQX9o7Vid8fzrbpXUMBDedectuLikxJGNbaU0UZcKl49Ml5vbsmCdqm1VXKWsft3dTjl2Gt1VpjhvQY8DyPWQZy8e+BFeFGdi+FXWJKWH2vcIbQaq+wAwytNdMEysjmc88gaLgA7ZivMAwxgSFxAQC8xKZk44onnDduW7O2qBaDIIAzrKFZtqCE9AyLa8XGR7dUlDzPWSgEdjseq7LGusPrJUEWvcLpcOd2VLNB6WlfZf2zus/keU6jZIGHPaSpnlC6q2UMmIln8NhaS1351SXun+8J9gh68g1bhOVGoSqqtTbGUO3yfZ/ei8dFOZgNzDkqlJlBxwN1gsFmsqloHeBUlcMSsyEfqx0iuOD56kfAYI/lBCXBW6y1w+GQRsxqNBrsudW4mlNdnnG83l0Tg3ZmeAjrYqyiWH9kI4gLexDLnIXWY8/KsgxCNLtGwx3X6L22vBQ35TD1wrlCx4jylbEYY2j4ZReWVXXO+VGQNoDNnXzfZz9aQXXSWpumKaj0scZWuBhYZ2c2x1rLJh5U1FpjyNhqLWJTbjQ+AMS1ogkqlBC0iIbFqtVqFRpeHAVo1Fr7Jw5Se8HIolc4NRWdRJX76siUI08irNuTK8fADET1U9QpMxfeLaob91gdo1MHPAmKjWfg4Fg1Ey4VJ2+vY1Pa8g9WjVSkcRybuXDmsDp328s9g7B7RzYfPekmgMypAcHzbmLh3eVsW5NqCygPzd/9YsKoUGnh8kObTx8Bx39PNIoKWwfHx+ZAOa0WnTb9BXNMnxEEQRAEQRAEQRCEdxdZ9AqCIAiCIAiCIAgTi2xvFt4I6zjxqsq9E7BFB0XcsEHPUJG5QdLjiqe4l9wSYho4ZpnjsXBhjKt22NM17qqLLkcTcdvXhekknqS6ba2lXp1untW6zTRQOCeqG7oC1nwQp6qi1aiD5UhloCLDlrcpvnaZBaWU1hrq81TVyNIbYyqajCWGJ44bm9Qobz1QFeYZrpSifuNKKdcRjj2XXBHOEbe5ycUqqtuI5gMGh55huqGcYlRnztDlwFcU6igOyU6Vs/B6uFp08mqvaH02TrFkxhgapoR5/FYDulERudZ9IzCkFaV968iiV3gjIPQUDvCmHKjDVf3iKI4l4HkeHeNZB1NKUR96mpXv+yxwyDj7ro5WL/QMTD6oSDO/tN11UgE9cQ0oAM1BG6WirZVSuhxg/NjWZGMGKkNRFEmS4CVjTBAEFXrC4hy681eqhNWvMNmwqd5rUH37uLqt1gQwTZhznuc03J3neTSAh9Y6DEOqZqyt3XdkT2eKVF02YRyucTgh2hkyxqmNcvK3Tuxu1tmTJGERGev1OhzTp1hrkyShYxwLh8YK+RqvKbwGrm6wMYIen7wjg9rQezHWFMBmNaryRyiq0Vp7JPAVLRXM2ahlY5GNhHNi3EwDYE0wcik7spnSNKXxmcMwpGFcQRNQhDNUrB6nwjCkAx9TQut8+wMFHlnOS4IseoU3wh3+VaXGu3NBBr2X9ig9flHk4hagumNrrd1bhAumugmqr1JeozWpetij/8KB+uElyHbczAMUm+VDrgtnRnXFvkbrI9SOsdY3zn8CmTK4D60o55sUUjgrWBOcqkVAPahILvJvu77vj1x+QCY0Qu/JR1LhXGHNhH/pmdeD3sv0ZKSRoeKpwHuZtYGPs/ggfZqZlfDauFqk3qx9kWpbxFr/tIyb8CD0cXr8BOnycNnLJwiCIAiCIAiCIAivjfynV3gjjDG+7+N3JmNM9Z4Nay37Yso+FNHtPfbIFQou4Xk16vtTxdcs9yns61d1IVli4byx1hZFQT9e0v+5qfJ/TlzgdhTd5mMi+76OV7WzTfpYNXAViYrV/xgUTg6r2ArgP2mQHqwTXtLlz9Jm1G9s4oNcnWQa6DZ9hQ2B45PogJuG/TOwoiO8D0CjuPoAFc7q3K3McUDz0WzZU5guZVnGPHHob6hqreHfuVpr6lOntWa/e2mt7ff7KHrOL0uf/BWE88OMd4Kt6J7a8Z6NoqhCqRjsiUVR0N3RYL5GGiV2IyghPrfiXYSzpXoEYYC2UBEtkmvumE8EucKxo2ZH1bdQivLeBHXc4y4hsugV3hRqNOH45N2ATSxYPz85YBH42TLsQRWFdEtFLgoXAdszz2aczEeF4Zr1kVMBKo5sYkMiFSnnLkb1VTX+KcK5Yq3FqSFzvHQ9negZNrSDTUC9AqWqbtBqg1N97zjENDGstXR7MIUuL9XpJ/fU5tiyNyaoCtWWOI6pE2+9Xo+iCEXwD1eO2mitqfedUqrf7w+HQxSjKDq5CRIujHG6BHqCoj4KsYZn2EhUPZBVUxRFkiRokUAh2TIJjymghFSZy9eF84KOICCSixytNWsaTM+mQ2COUKyeQsMIwkxZOUkVbNE7riNcZqpqRxAEQRAEQRAEQRDeaWTRKwiCIAiCIAiCIEwssugVBEEQBEEQBEEQJhbx6RVOB3NLUEr55JevtdbM34Bt+mdiURT0F8aYo5QiDifM/8H1dmBODuSiUuUE7r3Mg9Q7ze93C28OtA5tQWMMdU1xr+KxC7ip0OZ2W/wk7WsrfYPhKi0VPJeK7Coeu6JwTmitgyCAhmBKxdyTXD2p1WrYgsYY6jJnrcX4WAALruYqAx67oirbt4rErCPAGTe39wddjjZHYQ0KTUZFPFZHukHTmzHx7QCWG2t9ViRWyAq/Ps/z8Bd9QWRKhcfCRVIUBbaaHu/Pb50ho7rzsgTK0QeGa2HwdrdIODyxUqmyfrplEM4D1l7quGmMGtXfoUGPbTI2rjG1oZaN5WOdn5JmJsgYU6E8RVEkSWKt1VpXRxt9i4weLQRhHNArUDTG0J4MUwFMAF2C9gq2pk2ShC56rbUVY7w7YFCRXnVHDmstnoRjWuY0TXEGo7WOosiN4yqcK26cmAqLSVtzJBX3Kud2pkiIHfVLrTQx/VYCVp6qN1sSq+NK9V7BamZcE4zEbb6K240xLFYQkuc5DT5kjKEN5HlerVYbl3NRFFmWUaOhnVjQeHwsoGlwzG50C0Dnr6CT5OKI9JMNa7UKqJEHaNV5nheGIT3DsqVd25aHOaVUEARsaKNgIZlJUY6VYDZEuAxAq9FZzbg2Yu0LZgG7pNv6bJiz1rLuXKGQYHAwc3qslLLkUz4tvFLK9/0oit43Q3EZ8DxvnOa4UM1RR7oBZ1jbsZR5nlNDx3SMJXZhli2KInp7tb2FIRXKWZ3yLXIZyyQIgiAIgiAIgiAIZ4IsegVBEARBEARBEISJRRa9giAIgiAIgiAIwsQiPr3C6YDN+lRkHgLMt6Taf8AYQ71n2b2M6kusVOTi/3fCYZ427Co9czldESYbUw6uUNHWSildjhHFqL5XHXc7AopBRZZztapXi+851ZVTXVfViavvpTDjA+2Lt1fno09pNIqiYL6446yodaLOsJK4XmFUmZli05xdwE8MxWMTo0ciK7/bmyrycWGOjuxeVipWZjijnOZzMca4VYdoxyYw50za2UH8e9IjF0oU3QR4nhbSrTf37SreSLgYWOvDGXL972jH3Zc2t3sXy1aV09hyCAk3pfsseoyZwzFeGqmZwiXHVZ5xMMU4+Y0AHde01qe63RgDYSNPe+NFwg29IAiCIAhnSJZlLEx9EAQjpwUsjghLw0KhsLUWnKFLNRbFhJHnOb2dZc7I8zxN06IotNZBELBwxHQioccs+UZirc2yjK7z2YTJXWDTxCjq4+KFsvUkewrLFmL/YHqYzFVknqYpixU0LqY0Bd69oglcDXHPCIIgCCdkrBEXBEEQBOEdgq7rzhzI/FwfIVCkqgVBEM4QWfQKgiAIgiAIgiAIE4ssegVBEARBEARBEISJ5Xi3E0EQBEEQTg7zIFXlAFRuABsW5opc4fFpyJURZ1y/U+bISq5w51s3cwYmcPOhojrlvtzqYriZU/BerTVLyTyNXVj66sTVGBKHTzk5K5I5vQRlpu/uKoYgCIJwVsiiVxAEQRDOEoiEhCJEQiLXS9jxgZGrV4BsyTSSirWcPk2cT3jWyNxg8YYivA65/v9PwgFLrEbFo6awxKwA9BVYShamiz2XPdQeQU+yDCuobjWsEDjPisFKwmqSFunk5REEQRBcZNErCIIgCGfJqVZQbMVFU1bcNRJ3uUVFxmkzf23OrxhsKUthTTAuGUITn7ztgGMTALb8IzTqxDcKgiAIb84xH4kFQRAEQRAEQRAE4d1FFr2CIAiCIAiCIAjCxCLbmwVBEAThjKnY02utpe6m4AAM6XWlm25FnsCxCShu4urdtni1OpkqJ4A9ve6zgGOzcjnJLSMfd5IbEZoDbSA8Q0XXNZdircXG5dcEQRCEi0IWvYIgCIJwluA6B0VyUWVZNhgM8CRdU7VareqQVyw+Fo33a0lALHW0fq5YQrOVG1uaaq3pIg1yw2M878KuQrYsq+ocKhgXTGskNKUxxverJjy0SKwmlVJZltGrcRzTM1NTU41GA0UGthq8+Kne/VSJBUEQhAqqxgBBEARBEF6DikVvURRZlo1c9Fav6Ky1FdnCGfdkBSxx9RKr+iqFLSDJlTda8QKvffupbmQ1SeNRF0WRpmmapiOvjuRUjYLo8f8hFwRBEE7L2G/AgiAIgiAIgiAIgvCuI4teQRAEQRAEQRAEYWKR7c2CIAiCcMbQzbRZllEX0H6/v7+/T/fEYuJarRaGIZ6vdso9FrY5tlo8FfTeY7cNuw869hak+l7chDwyQ3rSTUBzzvM8SRI8k2XZcDjEBiqKIkkS2l40rpXWmm51Hgk83S2DIAiCcGHIolcQBEEQzhLP8+hi9fnz50+ePEHxxYsXDx48wJVSvV6fm5sLgkBrfffu3evXr2PKRqNRr9dRVErRbLXWbB3F4jzRdZq1NssyeobFHGa5sZypyII8sZU5W6aCxzKKWmsW6Jg9CNexACuzMYbeDt7R6ihbmhUrFft2kOc5LVWn09na2sIHHR4ebmxsJEkC4mAw2NjY6Pf7IAZBcO3atenpaRC11j/96U+npqZAVEoZEl0MEmCZ2csey2nTC4IgCOOQRa8gCIIgnCVsiTUYDJ4/f47i48eP7927h2uqdrt97dq1KIq01levXl1aWsKUQRDUajUUVeV/L3U5TjKsHnEBaa3N85z+w1k7P490wiWWtXbkv6kRumplidkTXdiiF5e1gO/7NAd8I601ex22BmaFZKWK4/jg4ACXwXt7e+vr64PBAMRut/vNN990Oh0Qa7VamqZXrlwBUWvd6/XYK7NHu1UkCIIgXDDHDD+CIAiCIAiCIAiC8O4ii15BEARBEARBEARhYpHtzYIgCIJwjtC9r+poXzHuxQU/VdiOy9xB2S5cOIPHWmvmtevuK6ZnsiyjjqzsKiukK2L+zM/WfS4T2YOKosB3hIPX3v0LO4dp5q8H5IMtAsfoiAutgyIkY++IxxW89msKgiAIb44segVBEAThLEnTlHqipmlK10Wzs7M/+tGPcP05Nzd3586dRqOhtV5aWmo2m5hyb2/v8ePHKA4Gg8PDQxSTJOn1enT9yVbIbAldq9V8/++D/rVr15aXl1Gs1+utVgtFCDGNxR4MBnt7e/Air169osVgS74oimjwrTAM6/U6FqNWq83OzgZBAGIQBPPz81EUgcgWn5CARq5ib0QTu5cqFpnM43d6evrDDz/EF7ly5cri4iJGGjs8PJybmzs4OACxKIrhcIiRybTWnU6nwvGYvdEJV8hKFsmCIAhniix6BUEQBOEsgZ/AoSK5qFqtFl0WLi4u/uAHP4AFJ1vn9Hq9p0+fonhwcLC9vU2vvnr1CjOHf7HimkprTVdfxpjp6elGowGiUsr3fSpqrWnQrH6//+rVK1xFdzqdp0+fxnFcFMX6+vrOzg6mzPOcLrZbrRZGNlZKNZvNubk5LEaz2YzjGFe59Xq92WziGlgp5fs+rQT6L9aRVF8dhy4HkW42m/RbQ5Iks7OzWLGdTifP8/39fRDjOP7yyy+xIYwx/X6f/esbjwF8I9pALqz1bTkgliAIgvAmiE+vIAiCIAiCIAiCMLHIolcQBEEQBEEQBEGYWGTRKwiCIAiCIAiCIEws4tMrCIIgCGcJc0w1xtBAR6rsvWmMCYIgDEN2Xim1uLhIYyDt7e1Rt9vnz58/fvw4jmMQB4PBy5cvUWw0Grdu3ZqdnQXR9/2FhYWFhQUQlVJLS0t4VSlVq9Wob22j0Zifn0cH1CAIBoNBHMd5nq+vr3e7XUy5s7Pz6tUrFNfW1tBlVynVbrfn5uYwgBa4+MLLKqWiKIqiiLrXnsqLtSgKdKZlsaneBGNMGIaYcxAE1Ek7SRIWMMzzPFp1FW7GzOnaLbB7RhAEQTgTZNErCIIgCGeJ7/s0TrLneXTRa4xhV3HRy5ibm2u32yi2Wi26Bj48POz1er1eD8Td3d0vv/wS4yrPzs6urKzMz8+D6Hne/Pz81atXQVRKLS4u0ohTnufRUjUaDWMMrtB83+/3+3Ecw4vgQ5VSGxsbjx49QtEYs7a2hqLWemZmBt+u0WhQ0ff9MAwrVonVWGuhPNr5tac3AT5D0HcvigKDOWdZxoJRsUXvCYE4VWdVZkEQBKEa2d4sCIIgCIIgCIIgTCyy6BUEQRD+X3t31tzGcbUBuLtnA0CAILiDi6VoiWS7ZJcdx5W4nMSXucp/yH/MZSq5SJVTjpfYsZJYG2WLRUoUKYokiG22/i46PN/BGXJELZYl8H0uXOhZe3qGMg7Q5wAAAABgbCHoBQAAAAAAgLGFnF4AAIAXiRdYUkplWcabLo3z2GTOLMt4vqjIHa1Wq7wS1ezs7MzMDJW2yrLM8zyeicqTeIMgaLfb7XbbNZVS9Xqd9yHLMkpbdXiear1eX1xcTNM0y7KVlZW9vT1adf/+fZ6xHAQBr481Nze3tLREpa3CMGw0GpTE6xJx+eDkeS6umvM8j2c1a63doYrJseIWiLXWWr5WZFm7w1I3vCPHNou5xLxalTqub6f0oo4DAAAKQS8AAMCLlWUZjwPTNBUhFg9g3AsX3ogdaa0zMTFRq9WoeXBwsLS0RDWlsizzfZ8HvUtLSxcvXnTNIAguXrzIC1mJsHAwGPT7fWpWKhUeFVcqlampKaVUmqb37t2jGtFKqZs3b/JoOYqi+fl5ai4vL1+8eJEXneastVmWZVlGS8RYCaLiFw84RUDo4nNqitBUjHMQBB4r/qyPYmnHlSWjqDjPc940xvA4XB0XUT9bsPqijgMAAArTmwEAAAAAAGCMIegFAAAAAACAsYWgFwAAAAAAAMYWcnoBAABeJK21qLfEVio1WqGKvzbG8GxSQVQ2OjY3mFhr4zim5Nssy+I45sm3fF+llO/7VG7KNem1YvmlLgWXp8vyLqnjrr14+SW80VJVgjFGnM71qngK0Y3yhFie0KsK4+wSgCkHOEkSnjAsNi4uoddisyc66TgAAPAMEPQCAAC8SCKIEqGaqCDFwzZeFrjIjlY28n2fV1ESQV2e5/1+v9PpuGYQBL1ebzAY0AZRFImiULxcswhWrbVpmrr/xnEcxzGt4gGwKlSBKolgHdFtMXRFIg50Z3e95TsWu8F7Yq3lFyu4y6RmkiTD4ZCGzl0+fXxgjBEjoI7uqSOG8fSxK10dKXk2AACgHIJeAF0rH5sAACAASURBVACAF+yJkduxGxy7kBNxHVtzDB4k53leHnHp0a9GBbcvHYEfp+SYz0DEroI4FzXtCeN5ktNszA9OF35s070gxSUAAPCTQ9ALAAAvmHjff5oY4yTFEOJ5jvaKeIGXUBwfjk7kgsmS85Yf56nwQxUPW7JWa21Hw9fi7hy/utE1Sj1pX85aW+yVGDpay1cdq7j9M3tRxwEAAAS9AABwKsUQhTeJ+BFUz/NEguhTSZKET/L0fb9kYmrRSRNNn9bT7svHSh+XX0oHFNNuxY78vGJtnuc819RNP6a1anTkfd8Pw5D/Xm5xrqzYXXD9dN8Yl+T05nnOM4ezLBN9juOYlmit3W/k8g34wcXuxenfNHpuVGm5+J1ecQuENE2HwyGdyPO8MAxpezeNnM7reR5vionTbgnviXhy+LXb0i+oy48DAABP5dnfiAAAwNkhIi518rtwEbectNkpiSCqJHQpch12/3UxhtyCec5+csUTiejFKa4Vg1zeJWttlmU01Dy8V0dhHg2XC4D5pw/lB1eFq3DbuwPyVWIz1ytqil65QJ0WGmOCIBA94bsUnyXxAQrty4fUDSM/TvGOcCIUD4IgiiIaOjeM/ER8YIsPJO+JUDJuRaZQtQsAAJ6Z/McaAAAAAAAAYGwg6AUAAAAAAICxhaAXAAAAAAAAxhZyegEAQKlCQqkgVumTy/AYY0TuKK9r5VIiefolL1aUJMnm5ubBwQFtv7OzQz82qwp1g5rN5uzsLG+22+3nqZv1+hK5plrrLMsoHVprLX5f1/d9XhTq2FvJuQ201r7vR1FEy8Mw5KXFijmunDEmCALKtnVPETWTJFlbW9vZ2aHtRa9qtVqtVqMmPWmuV3TqPM8PDg56vR5tORwO+bXPzMzMz89TMwzDWq1G5xLPmHrSnwYAALz6zuI7AwAAOJZ4Z1/+Rv+kMEkEDKIWkYgoXNBLYc9wONzc3Hzw4AGt3djYePToEW2f5zkvULS0tHTx4kXeXFhYoOZZ4+Jees1HPssyXupZKWVYCWJH3NCT7r7neTzKFcFzedCrtXbVj/lCHvRubGzcvXuXVolyzfV6vdFoUDMIAlePWmsdhiFtmef5w4cP+Wcle3t7/JOU8+fP809GpqamWq1Wec/JScMCAACvslP9Ew8AAAAAAADwOkLQCwAAAAAAAGMLQS8AAAAAAACMLeT0AgCAUqeo1iOSHk9KARUHMaxslVIqTdPDw0NK4zw8PLx16xblW1pr0zTlWbvtdrvdblNTZAjv7+9//vnn1Lxw4UKj0ahWq64ZhmGz2Tw7da34HcyyrNfrUV5rEASPHj3iVaCiKOKpuWr0xrkcYLbyf9I03dnZ2d3dpSW9Xo9vye/dsYwxvJOHh4dUbavX6926deu///0vbby8vDw3N0fNKIqmp6epGYZhpVJx1bD4tcdxvLa2duvWLdoySRLeycnJSVHEi+/ultBrNZqIfsrUXwAAeKWclbcCAABQzrI6ug5/6+9i15OKVzkUNvDNxF7D4XBvb4/inAcPHvz1r3/d3Nx0zSiKrly5QgWZtdarq6u8PjOveqWU+vTTTz/77DNqdjqd5eVlCu0mJydrtdpZDnrp0wTf93d2dniUW6lUeBFmcfeTJBkOh/yGumAvy7Lt7W0e9Ha7XR5P8lrcqvAJiHgY0jTlZZY7nc7Nmze//vpr2iAIglarRc0oimZmZqjpqi4rpfI857F3nue3b9/+29/+RltGURSGITXPnTsnim/xoSs+5HT5qvAhDgAAvBbwgSUAAAAAAACMLQS9AAAAAAAAMLYQ9AIAAAAAAMDYOiuZTgAAUI4nLromWymzMQWXEeqyIsVmPFtSKbW7u/uvf/3r8PDQNTudTrfbpbW+77fb7fPnz7um1rrVatXrddpApJ5WKpXhcEjNhw8ffvXVV5SqurS0ND8/T3WtzgKe09vtdnlO78OHD/mN8DyP324xsHme80xd3/ejKDLGZFm2t7dHh1VKJUkiikKJ42RZxmuP8cfDWut5HiVdB0EwMTExOTlJGywuLp47d46aCwsLjUaDmr7vuyzlwWCwubn5+PFjt3w4HG5vb1OqsFKq3W6vrq5Sc3V1tdlsUjMIgjRNqWPGGN/3eT95+TSRtAwAAK8FBL0AAKDUaIna0+Bv/V3I5KIdETyLOsAbGxt//vOfd3Z2XFNr7fs+bR8EweXLl9977z3aviTSVkrV63Ue29y9e3dzc5N2uXbt2vvvv89LH40x9+EC3ZQ0Tff392mcXfklXoAqTVNRdZkHq+JhqFQqU1NTvu9nWba1tfXo0SNaNRwOeakwEfS6u08nEh+duKCXSkxFUdRsNvn9unDhwjvvvEPNer3OPwEh/X7/5s2bd+7ccc04jtfX1/f392mD5eXl3/zmN9S8evUqLwqdJMlgMKCh833f8zzqp7U2TVMqvZamKYJeAIDXDoJeAAB4eay1/Ku/Ypj9tLE35w7Ow5XR9WcLj4H/FxCzARFRrmiqwleyAtvwBePnFQ+DiJkVu8WWfVNd7KEuzGIQx3kqP+rlAwDAj+EZ31gAAAAAAAAAvPoQ9AIAAAAAAMDYwvRmAICzQkz7fM5JngLNIBWH7Xa7W1tbdN6NjY29vT3Kt5ycnHzjjTeoqlCj0ajX6yXTR4uppxMTE9RM07Tf79Pu/X5fTNkdY278aRJvEAQ8P9b3/dXVVZ4uKx6G/KgOmSPmAwdBUK1WjTFZlm1sbPBCVvfv36fXSiljDK9rZYwpPmbU1FqHYUjNLMtarRbPtm00GlSWTCnleR7vZLfbdcWrdnZ27ty5c+vWLbc8z/NKpXLx4kXa8o033lheXqYmr2KljipX8Wb530X5WgAAeAUh6AUAOCtE4VkeI6nneyuvtRYlfOn19vb23//+dypl9P3333///fcU9F66dOmjjz66cuWKa3qeNzMzw4v98h4qpZIkoZJCSinf92dnZ6m5u7t7//59Otf+/j6v1TTetNZUzVgpVavVVlZWLl++7JpBELz77rs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} }, "cell_type": "markdown", "id": "356d2857", "metadata": {}, "source": [ "The triplet rule, however, is able to match the experimental results (Figure 4A of [4]):\n", "\n", "
\n", " \n", "![Screenshot_20250317_173836.png](attachment:Screenshot_20250317_173836.png)\n", "\n", "
\n", "\n", "Let's try to replicate these results with NESTML." ] }, { "attachments": {}, "cell_type": "markdown", "id": "secure-north", "metadata": {}, "source": [ "### Triplet STDP model with spike pairs\n", "\n", "Let us simulate the pairing protocol in the above formulated model to see if we can reproduce the frequency dependence of spikes on the synaptic weights." ] }, { "cell_type": "code", "execution_count": 6, "id": "conscious-trailer", "metadata": {}, "outputs": [], "source": [ "# Create pre and post spike arrays\n", "def create_spike_pairs(freq=1., delta_t=0., size=10):\n", " \"\"\"\n", " Creates the spike pairs given the frequency and the time difference between the pre and post spikes.\n", " :param: freq: frequency of the spike pairs\n", " :param: delta_t: time difference or delay between the spikes\n", " :param: size: number of spike pairs to be generated.\n", " :return: pre and post spike arrays\n", " \"\"\"\n", " pre_spike_times = 1 + abs(delta_t) + freq * np.arange(size).astype(float)\n", " post_spike_times = 1 + abs(delta_t) + delta_t + freq * np.arange(size).astype(float)\n", " \n", " return pre_spike_times, post_spike_times" ] }, { "cell_type": "code", "execution_count": 7, "id": "similar-command", "metadata": {}, "outputs": [], "source": [ "def run_triplet_stdp_network(module_name, neuron_model_name, synapse_model_name, neuron_opts,\n", " nest_syn_opts, pre_spike_times, post_spike_times, \n", " resolution=1., delay=1., sim_time=None):\n", " \"\"\"\n", " Runs the triplet stdp synapse model\n", " \"\"\"\n", " nest.ResetKernel()\n", " NESTTools.set_nest_verbosity(\"ERROR\")\n", " nest.print_time = False\n", " nest.SetKernelStatus({\"resolution\": resolution})\n", " nest.Install(module_name)\n", " \n", " # Set defaults for neuron\n", " nest.SetDefaults(neuron_model_name, neuron_opts)\n", "\n", " # Create neurons\n", " neurons = nest.Create(neuron_model_name, 2)\n", "\n", " pre_sg = nest.Create(\"spike_generator\", params={\"spike_times\": pre_spike_times})\n", " post_sg = nest.Create(\"spike_generator\", params={\"spike_times\": post_spike_times})\n", "\n", " spikes = nest.Create(\"spike_recorder\")\n", " weight_recorder = nest.Create(\"weight_recorder\")\n", "\n", " # Set defaults for synapse\n", " nest.CopyModel(\"static_synapse\",\n", " \"excitatory_noise\",\n", " {\"weight\": 9999.,\n", " \"delay\" : syn_opts[\"delay\"]})\n", "\n", " _syn_opts = nest_syn_opts.copy()\n", " _syn_opts.pop(\"delay\")\n", "\n", " nest.CopyModel(synapse_model_name,\n", " synapse_model_name + \"_rec\",\n", " {\"weight_recorder\" : weight_recorder[0]})\n", " nest.SetDefaults(synapse_model_name + \"_rec\", _syn_opts)\n", "\n", " # Connect nodes\n", " nest.Connect(neurons[0], neurons[1], syn_spec={\"synapse_model\": synapse_model_name + \"_rec\"})\n", " nest.Connect(pre_sg, neurons[0], syn_spec=\"excitatory_noise\")\n", " nest.Connect(post_sg, neurons[1], syn_spec=\"excitatory_noise\")\n", " nest.Connect(neurons, spikes)\n", " \n", " # Run simulation\n", " syn = nest.GetConnections(source=neurons[0], synapse_model=synapse_model_name + \"_rec\")\n", " initial_weight = nest.GetStatus(syn)[0][\"w\"]\n", " \n", " nest.Simulate(sim_time)\n", " \n", " updated_weight = nest.GetStatus(syn)[0][\"w\"]\n", " dw = updated_weight - initial_weight\n", " print(\"Initial weight: {}, Updated weight: {}\".format(initial_weight, updated_weight))\n", "\n", " connections = nest.GetConnections(neurons, neurons)\n", " gid_pre = nest.GetStatus(connections,\"source\")[0]\n", " gid_post = nest.GetStatus(connections,\"target\")[0]\n", "\n", " # From the spike recorder\n", " events = nest.GetStatus(spikes, \"events\")[0]\n", " times_spikes = np.array(events[\"times\"])\n", " senders_spikes = events[\"senders\"]\n", " # print(\"times_spikes: \", times_spikes)\n", " # print(\"senders_spikes: \", senders_spikes)\n", "\n", " # From the weight recorder\n", " events = nest.GetStatus(weight_recorder, \"events\")[0]\n", " times_weights = events[\"times\"]\n", " weights = events[\"weights\"]\n", " # print(\"times_weights: \", times_weights)\n", " # print(\"weights: \", weights)\n", " \n", " return dw" ] }, { "attachments": {}, "cell_type": "markdown", "id": "cosmetic-rachel", "metadata": {}, "source": [ "### Simulation" ] }, { "cell_type": "code", "execution_count": 8, "id": "passing-character", "metadata": {}, "outputs": [], "source": [ "# Simulate the network\n", "def run_frequency_simulation(module_name, neuron_model_name, synapse_model_name,\n", " neuron_opts, nest_syn_opts,\n", " freqs, delta_t, n_spikes):\n", " \"\"\"\n", " Runs the spike pair simulation for given frequencies and given time difference between spikes.\n", " \"\"\"\n", " dw_dict = dict.fromkeys(delta_t)\n", " for _t in delta_t:\n", " dw_vec = []\n", " for _freq in freqs:\n", " spike_interval = (1/_freq)*1000 # in ms\n", "\n", " pre_spike_times, post_spike_times = create_spike_pairs(freq=spike_interval,\n", " delta_t=_t,\n", " size=n_spikes)\n", "\n", " sim_time = max(np.amax(pre_spike_times), np.amax(post_spike_times)) + 10. + 3 * syn_opts[\"delay\"]\n", "\n", " dw = run_triplet_stdp_network(module_name, neuron_model_name, synapse_model_name, \n", " neuron_opts, nest_syn_opts,\n", " pre_spike_times=pre_spike_times,\n", " post_spike_times=post_spike_times,\n", " sim_time=sim_time)\n", " dw_vec.append(dw)\n", "\n", " dw_dict[_t] = dw_vec\n", " \n", " return dw_dict" ] }, { "attachments": {}, "cell_type": "markdown", "id": "respective-police", "metadata": {}, "source": [ "### All-to-all spike interaction" ] }, { "cell_type": "code", "execution_count": 9, "id": "active-pipeline", "metadata": {}, "outputs": [], "source": [ "freqs = [1., 5., 10., 20., 40., 50.] # frequency of spikes in Hz\n", "delta_t = [10, -10] # delay between t_post and t_pre in ms\n", "n_spikes = 60" ] }, { "cell_type": "code", "execution_count": 10, "id": "psychological-reflection", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Initial weight: 1.0, Updated weight: 1.000062712440608\n", "Initial weight: 1.0, Updated weight: 1.045481723674705\n", "Initial weight: 1.0, Updated weight: 1.1180707933363045\n", "Initial weight: 1.0, Updated weight: 1.205329009261286\n", "Initial weight: 1.0, Updated weight: 1.4186655196495506\n", "Initial weight: 1.0, Updated weight: 1.5813821544865971\n", "Initial weight: 1.0, Updated weight: 0.6678711978627694\n", "Initial weight: 1.0, Updated weight: 0.6653426131462727\n", "Initial weight: 1.0, Updated weight: 0.6450780469148971\n", "Initial weight: 1.0, Updated weight: 0.6180411107607721\n", "Initial weight: 1.0, Updated weight: 1.068737821702289\n", "Initial weight: 1.0, Updated weight: 1.5937453662768748\n" ] } ], "source": [ "syn_opts = {\n", " \"delay\": 1.,\n", " \"tau_minus\": 33.7,\n", " \"tau_plus\": 16.8,\n", " \"tau_x\": 101.,\n", " \"tau_y\": 125.,\n", " \"A2_plus\": 5e-10,\n", " \"A3_plus\": 6.2e-3,\n", " \"A2_minus\": 7e-3,\n", " \"A3_minus\": 2.3e-4,\n", " \"Wmax\": 50.,\n", " \"Wmin\" : 0.,\n", " \"w\": 1.\n", "}\n", "\n", "synapse_suffix = neuron_model_name[neuron_model_name.find(\"_with_\")+6:]\n", "neuron_opts = {\"tau_minus__for_\" + synapse_suffix: syn_opts[\"tau_minus\"],\n", " \"tau_y__for_\" + synapse_suffix: syn_opts[\"tau_y\"]}\n", "\n", "nest_syn_opts = syn_opts.copy()\n", "nest_syn_opts.pop(\"tau_minus\")\n", "nest_syn_opts.pop(\"tau_y\")\n", "\n", "dw_dict = run_frequency_simulation(module_name, neuron_model_name, synapse_model_name, \n", " neuron_opts, nest_syn_opts,\n", " freqs, delta_t, n_spikes)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "piano-limit", "metadata": {}, "source": [ "### Nearest spike interaction" ] }, { "cell_type": "code", "execution_count": 11, "id": "inclusive-galaxy", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Initial weight: 1.0, Updated weight: 1.0000000027196625\n", "Initial weight: 1.0, Updated weight: 1.0086627050654013\n", "Initial weight: 1.0, Updated weight: 1.0903003652138468\n", "Initial weight: 1.0, Updated weight: 1.2776911537160713\n", "Initial weight: 1.0, Updated weight: 1.4771400111243256\n", "Initial weight: 1.0, Updated weight: 1.530550096954562\n", "Initial weight: 1.0, Updated weight: 0.554406040254968\n", "Initial weight: 1.0, Updated weight: 0.5544062835543123\n", "Initial weight: 1.0, Updated weight: 0.5555461935366892\n", "Initial weight: 1.0, Updated weight: 0.632456315445355\n", "Initial weight: 1.0, Updated weight: 1.2001792723059206\n", "Initial weight: 1.0, Updated weight: 1.5398255566140917\n" ] } ], "source": [ "syn_opts_nn = {\n", " \"delay\": 1.,\n", " \"tau_minus\": 33.7,\n", " \"tau_plus\": 16.8,\n", " \"tau_x\": 714.,\n", " \"tau_y\": 40.,\n", " \"A2_plus\": 8.8e-11,\n", " \"A3_plus\": 5.3e-2,\n", " \"A2_minus\": 6.6e-3,\n", " \"A3_minus\": 3.1e-3,\n", " \"Wmax\": 50.,\n", " \"Wmin\" : 0.,\n", " \"w\": 1.\n", "}\n", "\n", "synapse_suffix_nn = neuron_model_name_nn[neuron_model_name_nn.find(\"_with_\")+6:]\n", "neuron_opts_nn = {\"tau_minus__for_\" + synapse_suffix_nn: syn_opts_nn[\"tau_minus\"],\n", " \"tau_y__for_\" + synapse_suffix_nn: syn_opts_nn[\"tau_y\"]}\n", "\n", "nest_syn_opts_nn = syn_opts_nn.copy()\n", "nest_syn_opts_nn.pop(\"tau_minus\")\n", "nest_syn_opts_nn.pop(\"tau_y\")\n", "\n", "dw_dict_nn = run_frequency_simulation(module_name_nn, neuron_model_name_nn, synapse_model_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " freqs, delta_t, n_spikes)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "successful-capitol", "metadata": {}, "source": [ "### Plot: Weight change as a function of frequency" ] }, { "cell_type": "code", "execution_count": 12, "id": "biological-drunk", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots()\n", "ls1 = axes.plot(freqs, dw_dict_nn[delta_t[0]], color=\"r\")\n", "ls2 = axes.plot(freqs, dw_dict_nn[delta_t[1]], linestyle=\"--\", color=\"r\")\n", "axes.plot(freqs, dw_dict[delta_t[0]], color=\"b\")\n", "axes.plot(freqs, dw_dict[delta_t[1]], linestyle=\"--\", color=\"b\")\n", "\n", "axes.set_xlabel(r\"${\\rho}$ [Hz]\")\n", "axes.set_ylabel(r\"${\\Delta}w$\")\n", "\n", "lines = axes.get_lines()\n", "legend = plt.legend([lines[i] for i in [0,2]], [\"Nearest spike\", \"All-to-all\"])\n", "legend2 = plt.legend([ls1[0], ls2[0]], [r\"${\\Delta}t = 10ms$\", r\"${\\Delta}t = -10ms$\"], loc = 4)\n", "axes.add_artist(legend)\n", "plt.show()\n", "plt.close(fig)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "6572c782", "metadata": {}, "source": [ "Verify the results:" ] }, { "cell_type": "code", "execution_count": 13, "id": "7626009a", "metadata": {}, "outputs": [], "source": [ "np.testing.assert_allclose(dw_dict_nn[delta_t[0]][0], 0., atol=1E-3) # weight update near rho = 0 is almost 0\n", "np.testing.assert_allclose(dw_dict[delta_t[0]][0], 0., atol=1E-3) # weight update near rho = 0 is almost 0" ] }, { "attachments": {}, "cell_type": "markdown", "id": "interior-parliament", "metadata": {}, "source": [ "### Triplet protocol\n", "\n", "In the first triplet protocol, each triplet consists of two presynaptic spikes and one postsynaptic spike separated by $\\Delta{t_1} = t^{post} - t_1^{pre}$ and $\\Delta{t_2} = t^{post} - t_2^{pre}$ where $t_1^{pre}$ and $t_2^{pre}$ are the presynaptic spikes of the triplet. \n", "\n", "The second triplet protocol is similar to the first with the difference that it contains two postsynaptic spikes and one presynaptic spike. In this case, $\\Delta{t_1} = t_1^{post} - t^{pre}$ and $\\Delta{t_2} = t_2^{post} - t^{pre}$." ] }, { "cell_type": "code", "execution_count": 14, "id": "adequate-diesel", "metadata": {}, "outputs": [], "source": [ "def create_triplet_spikes(_delays, n, trip_delay=1):\n", " _dt1 = abs(_delays[0])\n", " _dt2 = abs(_delays[1])\n", " _interval = _dt1 + _dt2\n", " \n", " # pre_spikes\n", " start = 1\n", " stop = 0\n", " pre_spike_times = []\n", " for i in range(n):\n", " start = stop + 1 if i == 0 else stop + trip_delay\n", " stop = start + _interval\n", " pre_spike_times = np.hstack([pre_spike_times, [start, stop]])\n", " \n", " # post_spikes\n", " start = 1 + _dt1\n", " step = _interval + trip_delay\n", " stop = start + n * step\n", " post_spike_times = np.arange(start, stop, step).astype(float)\n", " \n", " return pre_spike_times, post_spike_times" ] }, { "cell_type": "code", "execution_count": 15, "id": "certified-bubble", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pre_spike_times, post_spike_times = create_triplet_spikes((5, -5), 2, 10)\n", "l = []\n", "l.append(post_spike_times)\n", "l.append(pre_spike_times)\n", "colors1 = [\"C{}\".format(i) for i in range(2)]\n", "\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 3))\n", "for _ax in [ax1, ax2]:\n", " _ax.set_yticklabels([])\n", " _ax.set_xlabel(\"Time [ms]\")\n", "ax1.eventplot(l, colors=colors1)\n", "ax1.legend([\"post\", \"pre\"])\n", "\n", "l = []\n", "l.append(pre_spike_times)\n", "l.append(post_spike_times)\n", "ax2.eventplot(l, colors=colors1)\n", "ax2.legend([\"post\", \"pre\"])\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close(fig)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "treated-jerusalem", "metadata": {}, "source": [ "### STDP model with triplets\n", "\n", "The standard STDP model fails to reproduce the triplet experiments shown in [2] and [3]. The experments show a clear asymmetry between the pre-post-pre and post-pre-post protocols, but the standard STDP rule fails to reproduce it.\n", "\n", "\n", "
\n", "\n", "
" ] }, { "attachments": {}, "cell_type": "markdown", "id": "adult-observation", "metadata": {}, "source": [ "### Triplet model with triplet protocol\n", "\n", "Let us try to formulate the two triplet protocols using the triplet model and check if we can reproduce the asymmetry in the change in weights." ] }, { "cell_type": "code", "execution_count": 16, "id": "liquid-offset", "metadata": {}, "outputs": [], "source": [ "# Simulation\n", "def run_triplet_protocol_simulation(module_name, neuron_model_name, synapse_model_name,\n", " neuron_opts, nest_syn_opts,\n", " spike_delays, n_triplets = 1, triplet_delay = 1000,\n", " pre_post_pre=True):\n", " dw_vec= []\n", "\n", " # For pre-post-pre triplets\n", " for _delays in spike_delays:\n", " pre_spike_times, post_spike_times = create_triplet_spikes(_delays, n_triplets, triplet_delay)\n", " if not pre_post_pre: # swap the spike arrays\n", " post_spike_times, pre_spike_times = pre_spike_times, post_spike_times\n", "\n", " sim_time = max(np.amax(pre_spike_times), np.amax(post_spike_times)) + 10. + 3 * syn_opts[\"delay\"]\n", "\n", " print(\"Simulating for (delta_t1, delta_t2) = ({}, {})\".format(_delays[0], _delays[1]))\n", " dw = run_triplet_stdp_network(module_name, neuron_model_name, synapse_model_name,\n", " neuron_opts, nest_syn_opts,\n", " pre_spike_times=pre_spike_times,\n", " post_spike_times=post_spike_times,\n", " sim_time=sim_time)\n", " dw_vec.append(dw)\n", " \n", " return dw_vec" ] }, { "cell_type": "code", "execution_count": 17, "id": "moderate-surfing", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "27.0" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# All to all - Parameters are taken from [4]\n", "syn_opts = {\n", " \"delay\": 1.,\n", " \"tau_minus\": 33.7,\n", " \"tau_plus\": 16.8,\n", " \"tau_x\": 946.,\n", " \"tau_y\": 27.,\n", " \"A2_plus\": 6.1e-3,\n", " \"A3_plus\": 6.7e-3,\n", " \"A2_minus\": 1.6e-3,\n", " \"A3_minus\": 1.4e-3,\n", " \"Wmax\": 50.,\n", " \"Wmin\" : 0.,\n", " \"w\": 1.\n", "}\n", "\n", "synapse_suffix = neuron_model_name[neuron_model_name.find(\"_with_\")+6:]\n", "neuron_opts_nn = {\"tau_minus__for_\" + synapse_suffix: syn_opts[\"tau_minus\"],\n", " \"tau_y__for_\" + synapse_suffix: syn_opts[\"tau_y\"]}\n", "\n", "nest_syn_opts = syn_opts.copy()\n", "nest_syn_opts.pop(\"tau_minus\")\n", "nest_syn_opts.pop(\"tau_y\")" ] }, { "cell_type": "code", "execution_count": 18, "id": "revolutionary-coffee", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "47.0" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Nearest spike - Parameters are taken from [4]\n", "syn_opts_nn = {\n", " \"delay\": 1.,\n", " \"tau_minus\": 33.7,\n", " \"tau_plus\": 16.8,\n", " \"tau_x\": 575.,\n", " \"tau_y\": 47.,\n", " \"A2_plus\": 4.6e-3,\n", " \"A3_plus\": 9.1e-3,\n", " \"A2_minus\": 3e-3,\n", " \"A3_minus\": 7.5e-9,\n", " \"Wmax\": 50.,\n", " \"Wmin\" : 0.,\n", " \"w\": 1.\n", "}\n", "\n", "synapse_suffix_nn = neuron_model_name_nn[neuron_model_name_nn.find(\"_with_\")+6:]\n", "neuron_opts_nn = {\"tau_minus__for_\" + synapse_suffix_nn: syn_opts_nn[\"tau_minus\"],\n", " \"tau_y__for_\" + synapse_suffix_nn: syn_opts_nn[\"tau_y\"]}\n", "\n", "nest_syn_opts_nn = syn_opts_nn.copy()\n", "nest_syn_opts_nn.pop(\"tau_minus\")\n", "nest_syn_opts_nn.pop(\"tau_y\")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "extra-minnesota", "metadata": {}, "source": [ "### pre-post-pre triplet" ] }, { "cell_type": "code", "execution_count": 19, "id": "close-seating", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulating for (delta_t1, delta_t2) = (5, -5)\n", "Initial weight: 1.0, Updated weight: 1.0003735276417982\n", "Simulating for (delta_t1, delta_t2) = (10, -10)\n", "Initial weight: 1.0, Updated weight: 0.9998230228609227\n", "Simulating for (delta_t1, delta_t2) = (15, -5)\n", "Initial weight: 1.0, Updated weight: 0.9984719712644969\n", "Simulating for (delta_t1, delta_t2) = (5, -15)\n", "Initial weight: 1.0, Updated weight: 1.001383086591746\n", "Simulating for (delta_t1, delta_t2) = (5, -5)\n", "Initial weight: 1.0, Updated weight: 1.0005542494412774\n", "Simulating for (delta_t1, delta_t2) = (10, -10)\n", "Initial weight: 1.0, Updated weight: 1.0000931206450185\n", "Simulating for (delta_t1, delta_t2) = (15, -5)\n", "Initial weight: 1.0, Updated weight: 0.9991105337807658\n", "Simulating for (delta_t1, delta_t2) = (5, -15)\n", "Initial weight: 1.0, Updated weight: 1.0012383200640604\n" ] } ], "source": [ "pre_post_pre_delays = [(5, -5), (10, -10), (15, -5), (5, -15)]\n", "\n", "# All-to-All interation\n", "dw_vec = run_triplet_protocol_simulation(module_name, neuron_model_name, synapse_model_name,\n", " neuron_opts, nest_syn_opts,\n", " pre_post_pre_delays,\n", " n_triplets=1,\n", " triplet_delay=1000)\n", "\n", "# Nearest spike interaction\n", "dw_vec_nn = run_triplet_protocol_simulation(module_name_nn, neuron_model_name_nn, synapse_model_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " pre_post_pre_delays,\n", " n_triplets=1,\n", " triplet_delay=1000)" ] }, { "cell_type": "code", "execution_count": 20, "id": "alpine-consultancy", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot\n", "bar_width = 0.25\n", "fig, axes = plt.subplots()\n", "br1 = np.arange(len(pre_post_pre_delays))\n", "br2 = [x + bar_width for x in br1]\n", "axes.bar(br1, dw_vec, width=bar_width, color=\"b\")\n", "axes.bar(br2, dw_vec_nn, width=bar_width, color=\"r\")\n", "axes.set_xticks([r + bar_width for r in range(len(br1))])\n", "axes.set_xticklabels(pre_post_pre_delays)\n", "axes.set_xlabel(r\"${(\\Delta{t_1}, \\Delta{t_2})} \\: [ms]$\")\n", "axes.set_ylabel(r\"${\\Delta}w$\")\n", "plt.show()\n", "plt.close(fig)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "alert-provision", "metadata": {}, "source": [ "### post-pre-post triplet" ] }, { "cell_type": "code", "execution_count": 21, "id": "proved-broadcasting", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulating for (delta_t1, delta_t2) = (-5, 5)\n", "Initial weight: 1.0, Updated weight: 1.0062479573893428\n", "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", "Initial weight: 1.0, Updated weight: 1.000866326114126\n", "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", "Initial weight: 1.0, Updated weight: 0.9891001725245149\n", "Simulating for (delta_t1, delta_t2) = (-15, 5)\n", "Initial weight: 1.0, Updated weight: 1.0145678210263605\n", "Simulating for (delta_t1, delta_t2) = (-5, 5)\n", "Initial weight: 1.0, Updated weight: 1.002324000740848\n", "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", "Initial weight: 1.0, Updated weight: 0.9985412039818167\n", "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", "Initial weight: 1.0, Updated weight: 0.9893305597962446\n", "Simulating for (delta_t1, delta_t2) = (-15, 5)\n", "Initial weight: 1.0, Updated weight: 1.0091647069686789\n" ] } ], "source": [ "post_pre_post_delays = [(-5, 5), (-10, 10), (-5, 15), (-15, 5)]\n", "\n", "# All-to-All interaction\n", "dw_vec = run_triplet_protocol_simulation(module_name, neuron_model_name, synapse_model_name,\n", " neuron_opts, nest_syn_opts,\n", " post_pre_post_delays,\n", " n_triplets=10,\n", " triplet_delay=1000,\n", " pre_post_pre=False)\n", "\n", "# Nearest spike interaction\n", "dw_vec_nn = run_triplet_protocol_simulation(module_name_nn, neuron_model_name_nn, synapse_model_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " post_pre_post_delays,\n", " n_triplets=10,\n", " triplet_delay=1000,\n", " pre_post_pre=False)" ] }, { "cell_type": "code", "execution_count": 22, "id": "plastic-stewart", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot\n", "bar_width = 0.25\n", "fig, axes = plt.subplots()\n", "br1 = np.arange(len(pre_post_pre_delays))\n", "br2 = [x + bar_width for x in br1]\n", "axes.bar(br1, dw_vec, width=bar_width, color=\"b\")\n", "axes.bar(br2, dw_vec_nn, width=bar_width, color=\"r\")\n", "axes.set_xticks([r + bar_width for r in range(len(br1))])\n", "axes.set_xticklabels(post_pre_post_delays)\n", "axes.set_xlabel(r\"${(\\Delta{t_1}, \\Delta{t_2})} \\: [ms]$\")\n", "axes.set_ylabel(r\"${\\Delta}w$\")\n", "plt.show()\n", "plt.close(fig)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "initial-interval", "metadata": {}, "source": [ "### Quadruplet protocol\n", "\n", "This protocol is with a set of four spikes and defined as follows: a post-pre pair with a delay of $\\Delta{t_1} = t_1^{post} - t_1^{pre}< 0$ is followed after a time $T$ with a pre-post pair with a delat of $\\Delta{t_2} = t_2^{post} - t_2^{pre} > 0$. When $T$ is negative, a pre-post pair with a delay of $\\Delta{t_2} = t_2^{post} - t_2^{pre} > 0$ is followed by a post-pre pair with delay $\\Delta{t_1} = t_1^{post} - t_1^{pre}< 0$.\n", "\n", "Try to formulate this protocol using the defined model and reproduce the following weight change window graph." ] }, { "attachments": {}, "cell_type": "markdown", "id": "lined-voluntary", "metadata": {}, "source": [ "
\n", "\n", "
" ] }, { "attachments": {}, "cell_type": "markdown", "id": "primary-spending", "metadata": {}, "source": [ "References\n", "----------\n", "\n", "[1] Bi G, Poo M (1998) Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18:10464–10472.\n", "\n", "[2] Wang HX, Gerkin RC, Nauen DW, Bi GQ (2005) Coactivation and timing-dependent integration of synaptic potentiation and depression. Nat Neurosci 8:187–193.\n", "\n", "[3] Sjöström P, Turrigiano G, Nelson S (2001) Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32:1149–1164.\n", "\n", "[4] J.P. Pfister, W. Gerstner Triplets of spikes in a model of spike-timing-dependent plasticity\n", "J. Neurosci., 26 (2006), pp. 9673-9682" ] }, { "attachments": {}, "cell_type": "markdown", "id": "shared-spice", "metadata": {}, "source": [ "Acknowledgements\n", "----------------\n", "\n", "This software was developed in part or in whole in the Human Brain Project, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreements No. 720270 and No. 785907 (Human Brain Project SGA1 and SGA2).\n", "\n", "License\n", "-------\n", "\n", "This notebook (and associated files) is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.\n", "\n", "This notebook (and associated files) is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 5 }