def model_augmented
[notebooks.git] / fmda.ipynb
blobe4a3591f26b1adc325dd321ab1e8d386986997e6
2  "cells": [
3   {
4    "cell_type": "markdown",
5    "metadata": {},
6    "source": [
7     "# Imports"
8    ]
9   },
10   {
11    "cell_type": "code",
12    "execution_count": 1,
13    "metadata": {
14     "id": "WzwJ619dAlA5"
15    },
16    "outputs": [
17     {
18      "name": "stdout",
19      "output_type": "stream",
20      "text": [
21       "Requirement already satisfied: pygrib in /Users/jmandel/opt/anaconda3/envs/ml2/lib/python3.7/site-packages (2.1.4)\r\n",
22       "Requirement already satisfied: pyproj in /Users/jmandel/opt/anaconda3/envs/ml2/lib/python3.7/site-packages (from pygrib) (3.2.1)\r\n",
23       "Requirement already satisfied: numpy in /Users/jmandel/opt/anaconda3/envs/ml2/lib/python3.7/site-packages (from pygrib) (1.21.4)\r\n",
24       "Requirement already satisfied: certifi in /Users/jmandel/opt/anaconda3/envs/ml2/lib/python3.7/site-packages (from pyproj->pygrib) (2021.10.8)\r\n"
25      ]
26     }
27    ],
28    "source": [
29     "import numpy as np, os\n",
30     "if not [int(i) for i in np.__version__.split('.')] >= [1,20,1]: # check numpy version\n",
31     "    print('Upgrading numpy and stopping RUNTIME! When the notebook completes, please run again.')\n",
32     "    ! pip install --upgrade numpy    # suggested by Efosa, see also https://github.com/jswhit/pygrib/issues/192\n",
33     "    os.kill(os.getpid(), 9)          # kill the runtime, need to run again from the beginning! pip install pygrib\n",
34     "! pip install pygrib   \n",
35     "from grib_file import GribFile     # Martin's utility layer on top of  pygrib,from wrfxpy"
36    ]
37   },
38   {
39    "cell_type": "markdown",
40    "metadata": {
41     "id": "X9rvlymMZdJg"
42    },
43    "source": [
44     "## Kalman filter"
45    ]
46   },
47   {
48    "cell_type": "markdown",
49    "metadata": {
50     "id": "NPgTHlCLAlA-"
51    },
52    "source": [
53     "The Kalman filter provides an estimate $u$ of the time evolution of some unknown process, called \"nature\" or \"truth\". We do not know with certainty what the nature is, but we can observe it at regular intervals (steps) with some error. In each step, model $F$ advances the model state $u$ in time, $ u \\leftarrow F(u)$, and attempts to reconcile the state with an observation $d$ of the true state, so $u \\approx d$. The filter modifies the model state $u$ to balance the uncertainty in the model and the data (this is called *analysis*) and the cycle continues. For that purpose, the filter evolves also an estimate of the uncertainly of the model.\n",
54     "\n",
55     "More generally, instead of $u \\approx d$, only a part of the state is observed, and $Hu \\approx d$ where $H$ is a matrix, or observation function. Basically, $Hu$ is what the data would be if the model was completely accurate. "
56    ]
57   },
58   {
59    "cell_type": "code",
60    "execution_count": 2,
61    "metadata": {
62     "id": "-bvUtJ_OLwQA"
63    },
64    "outputs": [],
65    "source": [
66     "import numpy as np\n",
67     "def ext_kf(u,P,F,Q=0,d=None,H=None,R=None):\n",
68     "  \"\"\"\n",
69     "  One step of the extended Kalman filter. \n",
70     "  If there is no data, only advance in time.\n",
71     "  :param u:   the state vector, shape n\n",
72     "  :param P:   the state covariance, shape (n,n)\n",
73     "  :param Q:   the process model noise covariance, shape (n,n)\n",
74     "  :param F:   the model function, maps vector u to vector F(u) and Jacobian J(u)\n",
75     "  :param d:   data vector, shape (m)\n",
76     "  :param H:   observation matrix, shape (m,n)\n",
77     "  :param R:   data error covariance, shape (n,n)\n",
78     "  :return ua: the analysis state vector, shape (n)\n",
79     "  :return Pa: the analysis covariance matrix, shape (n,n)\n",
80     "  \"\"\"\n",
81     "  def d2(a):\n",
82     "    return np.atleast_2d(a) # convert to at least 2d array\n",
83     "\n",
84     "  def d1(a):\n",
85     "    return np.atleast_1d(a) # convert to at least 1d array\n",
86     "\n",
87     "  # forecast\n",
88     "  uf, J  = F(u)          # advance the model state in time and get the Jacobian\n",
89     "  uf = d1(uf)            # if scalar, make state a 1D array\n",
90     "  J = d2(J)              # if scalar, make jacobian a 2D array\n",
91     "  P = d2(P)              # if scalar, make Jacobian as 2D array\n",
92     "  Pf  = d2(J.T @ P) @ J + Q  # advance the state covariance Pf = J' * P * J + Q\n",
93     "  # analysis\n",
94     "  if d is None or not d.size :  # no data, no analysis\n",
95     "    return uf, Pf\n",
96     "  # K = P H' * inverse(H * P * H' + R) = (inverse(H * P * H' + R)*(H P))'\n",
97     "  H = d2(H)\n",
98     "  HP  = d2(H @ P)            # precompute a part used twice  \n",
99     "  K   = d2(np.linalg.solve( d2(HP @ H.T) + R, HP)).T  # Kalman gain\n",
100     "  # print('H',H)\n",
101     "  # print('K',K)\n",
102     "  res = d1(H @ d1(uf) - d)          # res = H*uf - d\n",
103     "  ua = uf - K @ res # analysis mean uf - K*res\n",
104     "  Pa = Pf - K @ d2(H @ P)        # analysis covariance\n",
105     "  return ua, d2(Pa)\n"
106    ]
107   },
108   {
109    "cell_type": "markdown",
110    "metadata": {
111     "id": "K9pD9grsAJMq"
112    },
113    "source": [
114     "##  A basic exponential decay model of fuel moisture\n",
115     "\n",
116     "\n"
117    ]
118   },
119   {
120    "cell_type": "markdown",
121    "metadata": {
122     "id": "EHGMoaVWao89"
123    },
124    "source": [
125     "The evolution of fuel moisture content $m(t)$ is modeled by the differential equation on interval $\\left[\n",
126     "t_{0},t_{1}\\right]  $,\n",
127     "$$\n",
128     "\\frac{dm}{dt}=\\frac{E-m(t)}{T},\\quad m(t_{0})=m_{0}.\n",
129     "$$\n",
130     "where the initial fuel moisture content $m_{0}=m\\left(  t_{0}\\right)  $ is the\n",
131     "input, and $m_{1}=m(t_{1})$ is the output. Tnus, $m_1=F(m_0)$. The parameters of the model are the\n",
132     "fuel moisture equilibrium $E$, assumed to be constant over the interval $\\left[\n",
133     "t_{0},t_{1}\\right]  $, NS the characteristic decay time $T$. \n",
134     "\n",
135     "We can build the general model later by calling this simple model with different\n",
136     "equilibria and time constants (drying, wetting, rain).\n",
137     "\n",
138     "Since $E$ is constant in time, the solution can be found\n",
139     "analytically,\n",
140     "$$\n",
141     "m\\left(  t\\right)  =E+\\left(  m_{0}-E\\right)  e^{-t/T}%\n",
142     "$$\n",
143     "For convenience, we use $T_{1}=1/T$ instead of $T$, and the model becomes\n",
144     "$$\n",
145     "m_{1}=E+\\left(  m_{0}-E\\right)  e^{-\\left(  t_{1}-t_{0}\\right)  T_{1}}%\n",
146     "$$\n",
147     "In the extended Kalman filter, we will need the partial derivatives of $m_{1}$\n",
148     "with respect to the input and the parameters. Compute\n",
149     "$$\n",
150     "\\frac{dm_{1}}{d_{m0}}=e^{-\\left(  t_{1}-t_{0}\\right)  T_{1}}\n",
151     "$$\n",
152     "$$\n",
153     "\\frac{dm_{1}}{dE}=1-e^{-\\left(  t_{1}-t_{0}\\right)  T_{1}}\n",
154     "$$\n",
155     "$$\n",
156     "\\frac{dm_{1}}{dT_{1}}=-\\left(  m_{0}-E\\right)  \\left(  t_{1}-t_{0}\\right)\n",
157     "e^{-\\left(  t_{1}-t_{0}\\right)  T_{1}}\n",
158     "$$\n",
159     "At the moment, we need only ${dm_{1}}/{dm_{0}}$ but we put in the code all partials for possible use in future.\n"
160    ]
161   },
162   {
163    "cell_type": "code",
164    "execution_count": 3,
165    "metadata": {
166     "id": "eqcs0zEiAn0j"
167    },
168    "outputs": [],
169    "source": [
170     "import numpy as np\n",
171     "def model_decay(m0,E,partials=0,T1=0.1,tlen=1):  \n",
172     "  # Arguments: \n",
173     "  #   m0          fuel moisture content at start dimensionless, unit (1)\n",
174     "  #   E           fuel moisture eqilibrium (1)\n",
175     "  #   partials=0: return m1 = fuel moisture contents after time tlen (1)\n",
176     "  #           =1: return m1, dm0/dm0 \n",
177     "  #           =2: return m1, dm1/dm0, dm1/dE\n",
178     "  #           =3: return m1, dm1/dm0, dm1/dE dm1/dT1   \n",
179     "  #   T1          1/T, where T is the time constant approaching the equilibrium\n",
180     "  #               default 0.1/hour\n",
181     "  #   tlen        the time interval length, default 1 hour\n",
182     "\n",
183     "  exp_t = np.exp(-tlen*T1)                  # compute this subexpression only once\n",
184     "  m1 = E + (m0 - E)*exp_t                   # the solution at end\n",
185     "  if partials==0:\n",
186     "    return m1\n",
187     "  dm1_dm0 = exp_t\n",
188     "  if partials==1:\n",
189     "    return m1, dm1_dm0          # return value and Jacobian\n",
190     "  dm1_dE = 1 - exp_t      \n",
191     "  if partials==2:\n",
192     "     return m1, dm1_dm0, dm1_dE \n",
193     "  dm1_dT1 = -(m0 - E)*tlen*exp_t            # partial derivative dm1 / dT1\n",
194     "  if partials==3:\n",
195     "    return m1, dm1_dm0, dm1_dE, dm1_dT1       # return value and all partial derivatives wrt m1 and parameters\n",
196     "  raise('Bad arg partials')\n",
197     "  "
198    ]
199   },
200   {
201    "cell_type": "markdown",
202    "metadata": {
203     "id": "hLPJT3FcA2a7"
204    },
205    "source": [
206     "## Kalman filter demonstration"
207    ]
208   },
209   {
210    "cell_type": "markdown",
211    "metadata": {
212     "id": "kIA3X8vluFdd"
213    },
214    "source": [
215     "We demonstrate the Kalman filter for this model on a simple artificial example. The model is solving the differential equation for one hour. The equilibrium $E$ is constant during the hour, but it changes over the day so that it is higher at night and lower during the day, with a 24-hour period.  First, we create the \"truth\" by choosing the equilibrium $E$ and solving the differential aquation every hour, with a small additive noise. The synthetic data is obtained as values of the \"truth\", with random noise to simulate observation error."
216    ]
217   },
218   {
219    "cell_type": "markdown",
220    "metadata": {
221     "id": "bBv10PTiChhm"
222    },
223    "source": [
224     "### Create synthetic data"
225    ]
226   },
227   {
228    "cell_type": "code",
229    "execution_count": 4,
230    "metadata": {
231     "id": "-_pz-wXnCMnP"
232    },
233    "outputs": [
234     {
235      "data": {
236       "text/plain": [
237        "<matplotlib.collections.PathCollection at 0x7f91c983a690>"
238       ]
239      },
240      "execution_count": 4,
241      "metadata": {},
242      "output_type": "execute_result"
243     },
244     {
245      "data": {
246 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s58fqT6aqVG9dFMUDpNmuRflotWtW5MyuFnIyACysqx/9/CgX2biuecoFVwgN5fq9oQUSKO5HIxWYd0WekKHhNAzbaYxfv+97foSEUHpzGa5H6OjyWEyZoz1tc8/p5pMsyC3P5ttnpWcjWYZ47FjFPUX9xQdNw4YPNi4MUl59FFyJAvzDFBP9Q8/NG5MUqTzbLb92SSYZHX7DyK9QTkOeO01YMgQ48YkprqaFPXEUY/9+2kTX7nSsGHZ0LEjtUIRL47C4ccsRo7cPJvpgFZdTREY8RgHDQL++IPEhMzATz9RWnVKivW1Tz6hSINZ5vnaa4EFC6x/N+s8i6MeZjv8yEVmPv3UXKl6jz0GXH217Wtz5pCyrFmYMAEYNcr698thnoU6erM8z1IHD8cBJ04Ar75q3JjEVFcD06dTRFigoIAyocziKPP1pdYngsgkQN/p6dPmmWel/dks2R1y63a/fsCKFdYSBaM5cIDWP7ESb24usGqVeeYZsJZoAebbn2traUzi1HmzrdsmwW20GkVuru1CBAAXL5qn1vHsWYoGFxdbXwsPp9/N/BBFRFAEVkgHMZpOnWwPkAAwdSrQp48x45Fy9ixtLGavxSwrsz38VFVRKtyFC8aNS0xxsf0GbaZNsaoKeP554Morra9FRprn4APIR+DMhvSQC5CImVkceWVllIJZWGh9zWyHn4EDKUVU7BSLiKADulmeZ7l5joqyPfgaibBui88Q5eUUURJ6URrNjh1UqyzO2GnZkjK1zDLPn39u/+yaad0+c8Z+f27WjKLXjRsbNiwb5NbtH34g5W2zzPPzz1t78QqYyTnh4UHfo7jkSfg+zTJGk+A2Wo1CblOcOdM8verkFqLmza0PlxmYP5+iwWJjwWwHtJdeopoUMfPmkZy5GZCLetTWksrsK68YMiQ7cnMpRVSs9Ge2Bb1bN/vetmZSYfb3J6EMcSZHixYUvb7uOsOGZYPcPO/cSZHN48eNG5cYOWdjy5bmuQ+PHqU53rjR+prZ1u3ISFIsDwy0vnbXXUBFBdCkiXHjEiO3P//2G63dZkBpf+Y488zzL79QmrqgeguYb38ODbXPKFqwgDI8zIBQzyi9F1esMI8ieF6e/bptttTWRYuALVtsXzPT/iwg1otp3pzOjmZKszYBbqPVKCIiSMRDjJkeIrlN0dOTHiSzHNCOHaNFXfygd+kCPPCAtV+mWTFLvWhAAJCYaBtx8/CgA6RZRAry8sjAEs+zmQ4/PG9tPyGmVy+KtJuB4mJ6VsykrC1l7FhSTBTPc0UFtQJITzdsWHUI8yw9QJopMiO3bnt5kaFYVmbMmKRs20a/xPj5matP69KlJLglZu1a4I03jBmPFLn6by8v2p/NdC8qrdtmOEPwPEXgtm61ff2KK6ytjoymRw/q9S3N1rr9dvMY1sKaaOZ5liqqA+Zat7dsoZ6s4rpgLy8KbiQkGDcuE+I2Wo1iyxYSzBATEUGHSzMcLpRaeJjpQZfWHQFU5/r+++aoxywsJO/jV1/Zvv7++1TvY4Z57tiRlKw7drR93UzzrGQoCO8ZTVERCZRJx/jkk6RybAaWLKHxSUXK7rqLlGXNwJAh5HASY6Z5LiyUn+fLYd3OyDBP3e3zz9srixYWAvfdB6xfb8iQ7Ojd2/6wGBFBz7oZ5lkpld5sjm+podCzJzmbzaDdUVhI2UTbt9u+fuwY8NFH9KwbDcdRyyppWrqZ5rmoSP4+BMwxxsJCcn5KxzhjBp3NzFB3e+QI8Ouv9iJqp05RL2E3dbiNVjNhpgNacDDVXbZoYfv6ffcBN95ozJikyBkzAC1QYlEAo8jLI3EM6YYTEkIRLzPMs1g1WIyZ6j3GjaNosJiWLalmxgx91i6XHq2AfTQ4O5tqz8zAoUPAuXO2r5nJY+/rC3z7Ld13YmJjKZ3eDL1ahXmWrttmaVMGyBsz3t5Uc2aGe/HcOeqNKV2fzbQ/T51K6aFmdirL7c8BASSgZ4baYCXDf/t2Sms2w5qzbBlF/M2sl/Dbb/ZieWZ6VpTmuUcPEq0zw9oo3GvSdXv2bCobdFOH22g1gq1bqRZTqvJnpgd92jQ6QEjbTdx+O6kWmgG5SCtAB/M5c1w/HilKxoyZvJD33ScflTbTpvjAA7YtPAA6/KxcadtOwSiUNsWdO4E2bexTIY0gL48MfOnzbKZ5HjrUtkE9QHWPwcHmGGNAAHDzzfZZCTfdRB5xsfKjUQjzLE21XbSIxm4G5IwZM83zwYMUhRGrlQPm2p9DQihqKe3J+s03wObNxoxJipJTeeFCYPly149HitK6bSZH2apVwBdf2BtWZnIqA/brTUAA1d3edJMx4xFTXEy18lJHWUkJsHq1OfrdKq3bZptnE+A2Wo0gLY0OtNIbtEsXSh2NjTVmXCxcugSkphpfG1dbS6JVffvav9eihTkOFlqbolnG2KiR/esjRlCNhdGpM7W1FMEyehxqxMRQymOHDrav+/nRsy7u62kUSgfIli1JidToGutLl2ie5cbYv785lDIzM8nhWFVl9EiUmT2bDBcpx49TX0+lzApXcekSKYrKzbNZDmhazsbz5107HjmWLqV0QilNm1p7yxrNsWP2TiiAxGW++87Vo7FHLcVa/L6RaK3bRj/PFRWUebdmjf17Y8bQ3mg0/frRMzt0qO3r6enA6NHmaKmmNM8REeaYZxPhNlqNQE6xFaAb9IEHqCm30YwdSwcgKV99RSIFRnunPDxIVl2q2AqYp97jcjFapfchQB7Sjz82PnUmK0u+LhigbIARI1w/Jint2pFK9OV4+ImIIMfA2bOuH5MYQSVT7l5ctQp4+WXXjkeOpUupXYu01q2sjA4/ixcbMy4xCQn26csAfa9mn2ezRP2V9udOneiQfv31Lh+SHW+9JS/Es28f8Mgj5mj51qyZfPmGWeZZOMPIncMAc4xRKZvsjjtoro3en/PySC9BzjG7fbs5IupKmCmiHhJCQSspZtmfTYTbaDWCvDxKh5KLcKWkACdPun5MUg4cAEpL7V8304OuhFk89u3bA7fcYj/PTZpQuqvcIuVqlDZFgLx7Rkfg1OpFPT3NoSqbl2dfiwnQPHt7m+Pw8+ijwL332r/eoQMZ/pWVrh+TmMuhR2turvy67e8PrFtHa6bR/PorRbikmGXdbtGCRAjl0vqjo80RUVDanz097dPrjULJCZWRAbz7rvHrYmoqZZ/IKdCbpUXUI49Qdofc/uztbY4xKjmVo6NJ5Vgq3ONq1PbnDz6wF1wzgg8/lA9umGl/XrRIPvvATI5vk+A2Wo3g9Gn7gmuBkSON74/J8+SFlBujsDgJHnOjWLaMUqGOHrV/LyLC+PEB1P/ym2/svaEcRwv68OHGjEtAbZ737KED2urVrh+XGGEele5FM8zzo49SCqsUjqNxm2GMU6cC48fbvz5iBLXyiItz+ZBsUJvnhQupfs9olNZts8wzz1P/U7n0YLOs235+wIAB8t/jN9+Yo/5bbX9+8UXKQDGSy2F/PniQzjFyEV+zrNscJ192wHGk5mq0LgbPUxaH3DxfuEDCZSdOuH5cYi6H/XnrVvserYB51m01+vWjDgRm6IZhEtxGqxG0aWOfXy/QpAktSEZSUkIRNrlG70IDaaPHmJ9PvwIC7N8bOxZ44QXj6yDVogaXLpEUu5FUV5MnVM54Dg6mtBSj51n4+Ur3Ynm58a0J8vPlxwdQKmHXri4djh1VVcDeveZQt1WiZ09S5m3d2v69Cxdo/BUVrh+XdBxK8xwWZvyzorZuN2tGWglGr4lHjpBxWl5u/57RqY4C77xDIjJyLFtmvCPvctiftdbtsjLjn+d336UonBzt2slnwrkSjqPvce5c+/fy80lE0Wi1bWFPMfM8Xw7rtmCcSmnRgrRFQkNdPy6T4jZajeCVV0gRTo7QUOMPl8LPl3tQhNeMNrjUxjh8OPXINPoQNGCAfHQLoLqzceNcOx4p3t7AG28AV19t/57wvZr5XhS85Ebfi4WFypuKGVKk8vLIKPzlF/v3CguBtm2B//3P5cOyISaG1G1DQuzfE+bZ6HtRbZ7Nvm63bk0po9de69Ih2fHnn6TMKydmtW4dOXmMrseMiLAXVRMw+zybbd2Wi2Q++CAd1I1OtV68WNk58eOPxq+JAnLnGLPMM89TxpvcPJtljAUFyuv2woXAvHmuHY+UCxfI+VBUZP9edTU5yYyOqJsIt9FqNsywKXp6knenfXv79xo3poO4UqTYVRQU0DjlvKGXLpFqq5w335UUFMhHggFzzHNlJS2UckrQZjEUBgyg2qigIPv3unYlQQpPT9ePS4zapmgG1A65gYFUQ290/daxY5TGJYdZDj/vvSevhgpQfZnRqu9q82wW1NbtM2eo56PRoiMLF1LKvBxmWLejoymlccoU+/eEdfviRZcOyQ61eQ4MpPXcaKey2rq9eDF1cjCSkyepP7lcrbxZ9udZs0jPITjY/j2zrNtq89yvH4nXGYnaus3z5hH5Mwluo9UIunUDXn1V/j0zbIpRUZSqMHiw/XteXiQidMUVrh+XmIICWrjlNr6NGykFe98+lw/LBrXF0gzzvHUrfYcbN9q/5+VFBw6jxzhgACnzys3zwIHAZ5/JK1S6ErV5fvRRSjUzErVN0dubDpBGz/P77ytnJZjl8NO/Px1y5Hj/fePbeGgZrRMnUkqkkait22aZ52eflU/VA8yxbnt4UC9yOYPQy4uckc884/pxiSksVJ7ntDRaF1NTXT0qW8y+P2dmUpsqufRVs+zPaowaRWcwo+sxIyMpm0iOfftIFd5ILof92US4jVZXw/PA4cOU6y/HHXdQgb2ZOX6cfhlJnz7yinCAOQ4/PG/+TVHrkPvww8ZH1HNz5ZV5BWprjVc4nj+fhI7k4DggJ8e145GiNc+hocbX9ail3kZFkWCUr69Lh2QDz1PKoNEHbTV69gQ2bwZ69JB/f9cuYP9+lw7JDq01UbjGKHhe/V5s3ty+v7qrOXCAsk+U1kWjxwcAH32krGB87hzVDaekuHRINmjN8+WwP5thjK++SkEMOcLCKEDj5+fSIdmxYYOyuGlSEnDbbS4djh2XwzybCLfR6mouXiSBHqUbtG9fUp01km+/pToFpcP2lCnAY4+5dkxSZswA3n5b/j0zHH605jk0lNKXjRQpEAwVpTG+9BIwYYLrxiPHbbcp1+GdPEkHtCVLXDsmKbNmKRv3Zpjny2FTVDNmEhIoXdNIBeGSElr3li2Tf3/RImphZeQ8BwdT9oFcXTBAh0gzz7MZ1u2SEvV1e/5849vJ7N5Nh3Alx/f8+dTH1Ug8PORLOgBzzHNpKTnB1O7FsjJjW4FprdsbNxqfObF5M7Bzp/x7Fy8CCxZQkMasmGGeAwPp3K+UMWaG/dlEuI1WV6O1EJ09C6xZo7whuYJz50gMQ23TMfohUouumWFTBIDHH1dOJ7zySuC11+TrSV2FmlgGQLXBRkfg1A65ISH0/Rk5z+XlpGxbXCz/vhnuxaFDSbE1PFz+/TFjKHPBSAoKrMqnZkRr3S4pocOZkfO8dy85HJVUy82wbn/xBaU8yhEWRoJcRtaoXy51wYDyGFevptpgI5k3T1nIyAxrYlAQGa6PPir/vhnGqDXPcXHG36dq+3N5OfUG37DBpUOyITeXzmBKit9mmOdRo4Dt2+X78QLmWLdNhNtodTVaC9HataTmmpHhujFJKSggT6mS5LsZHqJOnYBbbpF/zwwiBY0akTKvXF0wQAvpk08C/v6uHZcYrXm+6Sbj04PVNkUzzPPx4xQB/Ptv+ffNsCm2aUPPilKa1vz5VMdnJGrzXFNDdcFKmRWugCVaLb7OCH7+mTITPBS2dTOs22r1ZU2b0r53442uHZMYrXnesYMUjo2MtqqJHAHmmOevv1ZeE82wbgsoiUHNmEGOyObNXTocGzw86OcrzfPvvyu37HEVLPuzkY7vs2fpmS0tlX/fDOu2Fu+8Y/w8mwi30epq/PxImVeuHyFgjofowgVacNQOP0a3GSkooLQKOby8qAH8mDGuHZOYigra9JT6IlZWkiCFkSqPV15JaWZmPuSqbYpmEKPQOuR27Ejpw0oq0q7g8GGqZzQz//sfZSbI4elJaqnZ2a4dk5jLwWhVEzkCgM6dyYFhJO+/D2zaZOwY1OjShVpEjR4t/35BAUUxjVTb1ppns6eBe3vTum3k3nfwICnzKrUSCQigMRqpcPzII6SorTSGZcuA11936ZDsEO5FOcwgIqS1bpvBgfLcc9SmUYkePYzv9W4imIxWjuNGcxyXwnFcKsdxT8m8n8hx3EHLr60cx3UVvZfOcdwhjuP2cxy325GDvyzp0IE84t27y79vlsOPWtqJ0caMlsgRQGkpvXq5bkxSVq6k9FU5uXqAVOvatJFX7nUVI0aoq0xeDvNs9Bi1NsVu3YDPPze2HcrcuRQ1V+Lll41XYB4yRFlACDD/PF8O6/YrrxibNsrzlI7555/K19x6q7Joiivw9ARatFBvVQYYO89qAkKA8c8Ky7p94QJlIhnFyZOUpq4UgcvNJd0Opf3bDBg9zwCl86upAxs9Rq11e8AAOosZaRSmpqo7ZA8fJs0ENwAAL60LOI7zBPAxgJEAsgHs4jhuOc/zyaLLTgEYyvN8Acdx1wD4DEBf0fvDeZ4/78Bx/3sxw6Y4eLByChdAHsp+/WhzMsITqSVyBNCmVFlJkS4juBwOuVlZdDhr0kT+fbFIgRGN4GtrSYVSycEDAPfcY6xByFIDV1tLv7w0l1vnoHWA9PQEzp83bp4rKoDly4HevalOSw6jDz/DhpHoiFzvaoAMneHDlVP5XIHWPBsNy7q9f7+xWTzbt5NR/dhj8nNphnX7u+/UNS+aN6cIV1WVMUrCLPNs1FoooKXncPEilSN062acQfPUU3S+mj9f/n2j92cA2LNH/X2j122t/TkkhObYSLTW7d9+o/KdqVONm2cTwRJp7QMglef5NJ7nKwEsAWAjb8vz/Fae54U7czuAKMcO81/E++9T7Y5SaowZNsV771X3dnfvDkyaZFzqDIuhMGsWcOedrhmPHJeD0Tp5snoEzugxenoCd99NynpKPPWUuWvgzp8HvL2x6/YFiIujTOy4OFLadxks0WrhOiM4c4aUeZVq4ADjDz9hYaTMqxSBi40F1q2jiLFRaM3zr79Sf221FlLOhGXdNnqeN2+mzAOlsg6jnxVAXZkXAJ54gmr5jGp9U1xMz4naPL//Pn3PRqGlnG+GeV6/Xr3XvBnGqMXvvwNffmnczw8JIZFBJZG/ykpSON5tYBKo2fdnk8FitEYCyBL9PdvymhK3AxDn//AA/uI4bg/HcYpWBMdxd3Ict5vjuN3njNpUXcG5c3TzKR1+wsKAP/4wtu2NVt/L/HxSOC4qcs14pPj5kSdcLQJn9OFHS+TIDLUUWovlgAHk5TWqP2ZJCW3aarVPFRVkGBrFmDEkOqI0zxaF41WLC5CRQWfhjAzyp7jMcNVKJzT6XmQxZkaOBAYNcs145Ni2zcWehnrw00/AwoXK75eXA4cO0fptBJeD0aolctS4MaVEGhnxePZZZQVmMxAZSWm3t9+ufM2GDdT32Cj+Dfuz0cbMsWNA//7Ali3K18TEKGdyuYJJk0iISWmeOY6CNGolC85GSznf6Hk2GSxGq1w4TdYNyXHccJDR+qTo5YE8z/cAcA2A+ziOk3VF8zz/Gc/zvXie79XM6PoqZyIUriuJ33h6AmPH0sNuFC1bAg88oPz+rl2kcHzkiOvGJKZ5c+DNN9X7Nprh8KMmlmEWkQK1TbFbN4pkKqVQOZs9e6jOUakPHEAbjpHpPR07Uh2eyjxf5IIQVGU7z2VlwJw5LhgfYP7DD4sxM2cOtdEwikWLgAcfVL+mRw/g+eddMx45oqO168sAc8/z5bBuZ2QAd93l0mHZ8Omn6mJWhw5Rf22j+2OqZWIZPc+eniSGqXQOuxz25wkTKKrdoYPrxiTm9GlKp1frcfrXX3RWMytmmOeBA9WzyYxet00Gi9GaDSBa9PcoAHbSeRzHXQHgfwCu43m+zpXL83yu5fezAH4FpRv/d2GpO/r7b3XvlTMRRBSUlHkB4x+i8nJ1ZV7A+E3x2mu124i89x55Ao2ARSyjqgo4dUq5B6mzuRwOufv2qadwAbjAhyIU9mPMzHTWoCQsWULGvRJt2lA6vVH1kCzzbDQs6/b58y6cVAk8T8I2ag4eo9ftQYNImXfAAOVr4uONO4QD5q8LZlm3S0tJWdaotnnbtgHTpwM5OcrXGL1uv/yysnKwQFiYeu2wM2GZZz8/YxWOWdbt1auBF190yXBkeegh7axFo+/Fr76icSph9LptMliM1l0A2nEc14rjOB8A0wAsF1/AcVwMgF8A3Mzz/HHR64EcxzUS/gzgagAGu/8MhmVTfPRR45T1SkspPdjMkZnFiyntUm1TDg0l47aiwnXjEnPNNcDDD6tfc/vt5GUzApZ5PnWKvNHLlytf40xYjVZBjMIInn5aM+pS6i1vtLosmWLECGrloUT79qRwHB/vogFJYJnn998nR5pRzzPLum3k4efiRer7rKZGLozfqL6JXl4kWKXULxigesy1a103JilaqfQAcN99NE4jYBE5Mnp/PnqUUunVyoyMXrdZOHmSotpGcOkS9aJXExm8cIHKpLZvd924xFwO+3NKCjnK1DDaaNUiIQHYu5cEUt1oqwfzPF/NcdxsAKsBeAL4kuf5IxzH3W15fyGA5wE0AfAJR16fap7newEIB/Cr5TUvAN/zPL/KKf+Ty4Urr6QIlhpGPkSsC5H4WlfDMsYJE+gwbpQXMiODvKBqtQqnTtEhRM2gcBaeniRA0K+f8jWXwzyLxxge7vwxSWEwZkqn3Y5VS4MA0b4dEECdaJxOSQl5u/v3p1ozJXieDplGiLeMG0fpji1bKl/j7U2Hn8JC086z6dftZs1I4VhtTXIm69eTUT1njnEiQVqsWEHOTjWOHCE1cCO4nPZntbKSZs3oV0mJMTWPs2fTOvLcc8rXGKlw7O9PvWTVqK4mhePYWPV93FnouRcLC6msy9WYfd3OyqIyt48+IjFCOQID1fVb/mMw9WnleX4lz/PteZ5vw/P8XMtrCy0GK3ien8XzfCjP890sv3pZXk/jeb6r5Vdn4bP/aR57jKIzapj98GO0SIGWiAJAXsrJk40TzLj6avWUTICah6up9zoTf39S5lWrBxXm2agWFCzzbIYDmsam2OvbBzDoy9sQG0s+lNhY4LPPqHOU00lLo+dAzRsvGKuvveaCAcnQrBmljqo9q5fBPJt+3Q4LI4XjMWNcMyYpa9eSKr2np/I1f/9NCsepqa4blxgPD/XSGMD4iLq/v/mNVq11+667SOHYKJGeNWu0NTk+/5yyF8yK0fPcpAnVYl7m+zOSkoCff3bNeKTk55M4q9qayPMksGdUyaDJYDJa3TgQLWVewNhNsXFjMqw7d1a+xtubPNLTp7tsWDZoiVkBpGz899/GKcteDofcffvUowpGixRMmUICOGrz3KMHKRwbVYfGkk5YWYnEq88hPZ0CNOnpLjJYATZjxsuLDsJGzTOLkqjRjrI1a7RLNoYOpUimEVwudcFa63ZVFQkJGdVB4JFHqDWQGkau2506UcbBDTcoX+PtTan+amnYzoRlno2GZX82UjF81y7KjjlwQPkao/fnGTPIGaoluAWY22iNjKQ2lEbAsm5zHPD448YZ1ibDxKvKvxCep7zAF15Qv87ITTEmhtTeOnZUv27MGKp3NAKWhejoUWqTsWOHa8YkhkVEATB2njdsIIPv2DH164wc4xVXaEeiO3QghWMjUkZZ5/npp6k5qxGwGjNGzvNnn7FlnwDGjTE2VrsI+aGHgA8+cMlw7GCd56FDtVWQnQXrmihc62p4HvjwQ3UxK8AcNXBaZS9HjxpXd+vjo302SEsjw9u9P8uTnU0GoVYauhnuRTVGjKAAgpo6rjMZNozOOWr8849xPYMvh/3ZZLiNVldSWkqeZLXG4ABw//3qkvbOpLRUW5kXoAd9/XrXjEnK5MkkVqWGkYcfFpEjwFiRAiHlV2uM8+YBt9zi9OHIsmuXdl1PTQ3VBht1yF2xQvv7MXKeL4dNkeUAGR1NwmUREa4Zk5jycuD119WjHkZz7bVAbq56hgxA37VRqrJmN1pZ1+127UiHoKbGNeMSs2YNcPPN5j7Avvsurd1qVFVRRNuINPDLYX/Ws24bpXA8Y4Z2tp2vLxAcbJy2yA8/AHfcoX7NP/9QIMnM5zC30VqH22h1JawLUVyctnfIWXz6KSnzarU5ef557Yixs5gwAbjnHvVrBLERIx50PRuO+HpXwjrG6dONS3m8/35KVVfjwgXy6n/3nWvGJMbDg2qXtVR3L4d5NrvRGhkJ/O9/xghSnDtH0Xytg/jXX1M95JkzLhmWDd7eZNBr1fAbOc8sqfRGPiuCqrLWGO++m6JganVozuLgQVrrtH72k09qayoYiZHzXF5OiqzR0erXXQ7r9p49ZJgZwdGj2mn85eWU2rpunWvGVB+MnOeYGGDaNO3abrfRWofbaHUlLKp6APX6+/RTY+oxWUQUAGMfolOntMWBjKyBCw4mZd5Bg9SvGzUKWLpU+7t2BqzznJWl2YfUabAYM0bOc34+1ZmcPat+nZGbYmIiZW1ozXNiIjB1qmvGJIW1NybPmzvq4eNDUQ8j5nnlShI50sLIdXvLFuofqkZoKKUwG6UQLYzBrAjrtla2VkoKsHmza8YkZcYMiraqYeSa2KwZ1U1Pm6Z+XdOm9Ku01DXjEsO6PxupcMyybnt5AW+9ZYyI0KFDpFi8erX6dUbei1ddRS0czXzeNhluo9WVsG6KR46QN1er+bUzuHCBTUTByIeob1+KfKhhpEhBSAjNn1YErm1bEhsKCHDNuMSwimW88AK1JDEClk3RyHk+dAiYNIl+V8PITbFFC3KeaM3zHXcYF5lhNVrDwrSfe2dwOWROrFgBvPee9nVGrtseHtprnbc31dtPnuySIdlQWqqtzAtQHWbXrtQ70dWwrttGzvPKlcDx4+rXeHtTVoKZD+JTp1Ik0QjtjhYtKMNJa56TkigjyQiEe1ENI+dZUObVaq9ldB09CwsWGNu/2kS4jVZXEhFBtZht2qhfZ3RaCssB0qhNkefZ0swA4JdftNOIncH588D+/UBFhfp1paW0EGk1v3YGM2eyNU6/HOa5cWNzp3B16kS1wWp9Up3F6tXAb79pX1dVZUxaK0BGgFq/RIGgIGsKpyu5HIxW1nV74EDK8HA1PE+OvFUmbtM+YABFykeMUL+O5ylN9/Rp14xLjJ792YhnRRA50jJmAErR1Wov5AzWrqW5PnnS9T+bldmzqfuBFnv2AF9+6fzxSNGzPxt1hrgc1u2bb1ZvOyjQogVlCLhxG60upX17SpXQUhIVFvyiImePyJ6iIrYNp3Fj2uCrqpw9IlvKy+lnsoxx5Ej6zl3NH39Q7V1Ojvp1WVmUHrJhg0uGZUPPnhQl1MKoeRZ+Juu9aNSzIvx8NWJjSR1XS33WGXzwAVva6Guv0cbo6nkGgFat2Ax6s8/z5bBuz5pFtcGupqyMnGQsYlbXXktONaPQEo0xcp79/NiUyI1ct6ur2e7F7dvZ1iZHk5VF7Wy0opinT5PCsZnrMY2a56oq6iBxxRXa15p93e7Zk64dPdrpQ7KjoIAtxXv7dsp6Y2mZ+S/HbbS6ktJSoKREOyUgJIR+N+JBv/lm8vJpMXMmsHu363uxCd+J8B2psWULqS26GtYxKsxzUhKdSzw86HentIrbvl27uTpgHaOWMJej8fGhKCGLYf3ccxTFcTXCd6I1z0Jz1vx8pw/JjqIitmfFqHkuLqb+p8nJ2tdKBOJc8pwA1HYpN1dbuKV5czIKY2OdNBAVWOfZKFifFYAiOJmZTh2OLL//Tvuflhqrkfvzl1+yReBat6YymkuXnD8mMXrm2ShY92eeJ4VjrVRnZzB1KnDnndrXCf+HkhLnjkeKjw9l8Nx4o/a1ISHq/eCdBes8e3uTDokRfYVZ1+0dO6gtj6v3ZxPiNlpdyTvv0MOh5S0JDqbfjdgUp00jIQUtoqLIQ+VqBUXhoRW+IzXmzdPu/+gMWMcovC85iN95J3Wl4Hn6/c47nXAgv/NO4Nlnta+TGaNL8PYmZV6tVHqA6oKNSHkUnk+teS4vp2jiF184f0xSiovZnhWj5jkvj5RO9+/XvjY4uG58LntOADqgRURoe8TDwoDPP6fUQ1fDOs+C8NupU84fkxg9zsbgYGP2vv37SZlXqwbOqGdFD9Onk2PS1SJ/VVXUdqllS+1rn38euO02549JijBvWt+NkfOcnKytzAsY60BhZeNG4M8/Xf9z27Ylo1prXayuJoVjLcEmZ8C6bhvlVDYhbqPVlRQXk9CD1qYYEEBRsLvuqnvJZVEFFmVegJpff/aZ6+vgmjYFPvkE6NNH+1qjDj9FRezz7OlpM8Y5c+wd/WVl9LrDx8iyWA4bRgfdpk0dPAANzp0jZV4WBW2jFI5vv50UOusxzy6juJjdUABcP0Y9xszUqXV9AV32nADA8uXA/Pls1/I8UFXluvVaYN8+4Pvvta/z9gYuXjQmog6wH9CMOJwVFdGzyvI8jxjBZpg5msRE4MMPXf9zWYmJAQ4fBsaP1772xAljFI4bsD+7DNZ1OyyM9mZXRzL37CGFb5bSJiNaQwHA2LG0Jmo5Gz09Se36n39cMy4xrJFWIwNZJsNttLoS1huU40i8xZKL79KoQo8e5AHV4vhxMqpTUpwwCBWaNCFxpbZtta816vDD6j3jOJvoEaCcFefwbDnWTTEujiKZrvbYHzhAqcHHjmlfO3euMfUoLVuSsI0WMvPsMlidE0Z5cvUYrbfeCjz4IAAXPicA1ah/8AHbteHhSBn7sOvWawFPTzqIa2FUZKa8nMbHmqpulKHAum6vXVvnQHEpK1awdRXYs4cEXnbudPqQ6o1RTuXISGqrpIWwbhvl+Ga5F8ePJwdvp07OH5OYCxeo1RtLPebixcB99zl/TFJYlXmN3J9vvpktS+xyiKi7CLfR6kpYN0WAGtVbetq5LKrA8/rTCV39ELEq8wLGHX5mzaJoMAs//GCzoCtp9ThUw0fPPBulcMyaeitcY8SGs3o1ReFYMOpe3L2brU1M+/Zk/LtaLEpPBK6yEj99chZxccrnEacMn9XBAwCBgTi8tdh1UWDAqszLkt5m1Lo9dCh9CSxOnr59SeTF1bAaCkYhrNss9yLPk+PP1ZlQf/9Nc8ySfm6UU/nhh9nTVTt2dL3DVs88G4We/XnfPmMUjm+8kUrYWDDqXnz1Vba64MuhJMFFuI1WV6JHLOO998hwhQujCqWlJBqjJ13B1Q/R77+TMi9Lu4HgYDJuWQxcR9KnD6kOsnDVVTb9XMeMsRevDAgge8Jh6JnnnBwao6sVFPVsiiEhJDhSWencMUl57z129UujDOs2bdjSGKOjgWeeYVMmdSQ6Iq37p7+JSfeFIzdDfp4d/pwI6DFmgoPhWSo/z07TFiotJWXegwe1rzW6NkpLmRcgkb+vvnL+WKT4+7N7PcaPZ9N+cCQXL5JBY+Ya9cxMYOtWNlEbo9ZtPWzZwl4a4CgqK6k3ekKC9rVnzgATJ7q+h6cewa3gYGPmuaiIPTXZiIh6bS2t3SwR4W7dqGzPCGeeyXAbra7kllvY+4aKHiKXRN8Afal6RqUr6DFmbr2VIk0sKSyOhFWZF6AN3qJwnJQEfPON7RrGcfTfSEx04PgEZd6JE7WvNSoyo3dTFH/GVehxQj37rOsVjouKgDffBI4e1b7WKIXjxERS5o2K0rz0179pnoNhP8+entZopsPTcPVEPUJCEO4r/6w4LYitZ91u1oxqsV3tnPj9d9r/jFARZeXrr9nV5gsLKe/bldRnTTTz/hwXB/Tu7XqF48mTjVGbZ8XXl5R5p05lu/6XX1yvcKzXqQyYe38WHCiuJC+Peo9//rn2td7eNEYjFI5NhvsbcCU33sjef06UTjh3LkURxDglqqAnVc9IQ0H889UwSuF41iy2umCAvLhPPglAPg2c54GVKx08Ph8fUuZt3Vr7WqNrHVlSs4w0rFk3xcmTXV93m5sLPPEEW2/MigpSOGbZQB2Jry8p8zI8o+kF9F2HwH6ea2rod6fUj+op6wgORvuIYtes1wJ6jJnQUOrTypKm60j27gUWLaK1R4sff6Tn/uRJ54+rvhgRmRGUeSMitK81soUVwPa8JCZSza2rU7JZlXkB6o1phMIxK0btfe3akVFt9v2Z9d5avx5Ytcq545Gix9lYU0MKx64eowlxG62uhFWZF7BJJ0xMJKHe2FiKvMXG0t8dGn0DyAv/ySfk/dTCz4+iia72WBYXA4GBbIZoTg59USypxI5EZzqhMM8uSwM/e5a8syzKvH5+5OVz9YYzaxawaRNblHzoUGDJErp/XYmeTTE72/UKx3o2RT8/+q5dPc/LlwOvvcZ0qW8z+q7ljFYxDq8fFVqhsDBlCpo8MN0167WAHkceUKdw7FKKiymqwLJuG6VwfNNNwMcfs11rRA1cXBwp844bp32tnx9w5ZUkOuRKiorY92ej0ONsTE11varsrl1AixbUKkYLYX929b147bW057Lsz2FhJKDp6iwLPZFWI+5XPQ4eDw8qR2K5J/7luI1WV9KtG/Dii2zXSoRbEhMpe0/I4nPKAahpU0pfZumNKVE4dhl6DEJB4ZhFgdaR6NkUjUgD37+fUoNZlJ+NUtaLjAQGDWK7Ni6OvL6u9tjr2RTnzaPotivRY8xwnDEH8eXLmZV5p9xB37U1PZgHcAiAvdiMQx09rMq8AKXAPvywa9ZrgfJyiliz3osREcBDDzlxQDLoWbeNKj1hVeYFjKtRZ4XjSBTp5ptd+3MjI4EhQ9iu3buXzkTbtzt1SHbozJxw+TxfuEC1qloteQDjFI5ZlXkBcrKcP89Wo+tIbrmFfc9duhS4917njkeKHqeyUfuzCXEbra6ithYoKWFfLOfNc32dwvnzlErIWjD/9dfAr786dUh23Hkn8NFHbNcakZaid55FC5HL0sD1LJYALej33+/gQWiwahXVwbFglMLxnj11qd2aGHH40ZM2Klxn4hTrq+5ph/2T56K6ZSyA/8HDIwLAFQDsD+YOc/TU1lI2yV9/sV1fVcWeeugohg+neqz+/dmuDww05l7UYygIn3EVwrrN+qz07Qtcc41zxyTlr78orTs93bU/Vw+PPspezyIoHJ8969wxidE7z0atiQD78xIf73qF46lT2TLyjGTuXGDaNLZr9+0DvvjCueORojdDxuyOMhfhNlpdhaD8x7pYNm5M9Ueu5LffyPOpIZOflETBrX0z38eaxK+c239Qih5lXiPqevTOc3AwOQkuXXJdGrjexfLKK20Ujl3Cu++SHDwLeXmkcPz3384dk5S2bdnqywC6Hyzz7DIuh01RT7Q6Kgpdlz6N7je8A+AODB4cj3btBgDYb3OZQx09Fy+SMu+hQ2zXv/UW0Ly560U9ADZlXsCYyIweZV4j123WZ2XGDFLNcyV6lHkB4PrrScXPrBjhVBaUeTt3Zrte2J9d2YFAr7Nx82bmEguHoUeZ9+xZyuxy5f5cW0t1IqwRYSPmOT6eFPv1nCHcfVrdRqvL0LsQ7dlD/RVdeZMyHHLvvZcyjjIygCKEwKe8CNOnU2axS4zX7dtJSIEFIzz2fn7UA27CBLbrb7mFalgsqUAuSSvUey9u28auquko9BgzRhx+CgtJmZc19dyIe/Hmm6mum7Wubc4cdnVzR6EnAldbiwN//omPPvoI99xzD9auXYu77roBwDlEReU7x9GjNyvBiHlevpzWEVZD2YjDzzffsPWRBWgzcbXCsV4HjxHoXbeNUDieNIk9zdII54SfHznnp0xhu15QOHZlPeblcC/q2Z8B0tBgKUdyFDk5lFHCGj01oiThiivIu9qkCdv1wcHmVl93EW6j1VXoXYiSk4HXX3dt6oyweQQFyb6dlAQsXCg4r/bgJaRiIZIBbEZ+vhNUO+W4/XZS9GPBiIXIx4dUYlmUeQFSOO7Vy7VCAML3oTDPdrz2GqnQuhKdbUbqPuMqcnLoO2HojZmUBDz8Aj33w7oXuS4zwdeXerSy3luTJgHXXFOXSeHhQb87dbx65rmqCofGjgUA3H///fD09ETHjh0BAIsXH3WOo0dvqp4R9+KePaTMy1IDB5g+zWzWY49hUmEhDrgy5bGqijQaWKMeP/9MKZmsNbCOQO+6bUREXY8yr1G1y3q46SZSOHaldoceZV4AeOkl1/cMrk+6vyvnWa+Dx4gxFhSwiWEKrFvn+uCBCXEbra6ieXNSJuzVi+16y8P259Ji1x0gi4pooVQ45M6ZI862+AobkYvlyAdwNYAdjlftVBoj62Lp60sKx66MHgnKvKz9LnNzqc2IKxWO77yTUorM3Hhbz6bo60u/jMhK0NgUk5Lo6/4lfwimYgn25TZ3jXMHAJYtI8cXKzk5WDl3H+68kwI0PO+kFjJiDh4Evv1W87KkJCCugy8OwgOe8MDOnW0BoM5oPcrSi7Y+1DfS6uoDmsq6bcekSa4X6LnpJlKm1+D48eP44osv8Msvv6Bbt2747bffXDA4kJPxyBFSRWXBCIVjvfNsxLqtd3++6irXKhzv2EHKvK5WBNbDuHGkzMuaBm6EwrGeSKufHznzXfms6A0SCQrHrizrePll9uAGYG5FbhfiNlpdRbNmlDbDepNaFoQPXy1y3QFSw1CwVeRMRRSaYi9CALQEcC2AVMe3Z5GiZ1MEyHvuytrgvXvZlXkB8tTfeSd7yrMjiIzU16fRqMOPnvQjV0ePGDdFofduJmLxA/xQjOtRVlbtfOcOQGmjH37Ifv38+ej3/Ei7XsFOdUYxKPMKhn9GBnAQXmiOENx7rzeSkoDY2Fj4+/s7z2gVlHnNHGnVuybecgvwyCPOG48cv/9Oh2sNvv76a3h6euJIkyboFBqKJ598EtXV1S4YoE6McE7oUeYFjFEb1ZM5AVDkyJV1t3qUeQFS2u/enUpkXIUeZV7AmMyJW24BRo5kv97VJQl6I61jx1LUs0sX541Jit4zzg8/uL58x4S4jVZXce6cPmVey6boU2G7GDn1AHnnnaqHXFsdjZM4jYHoj5MA/gS1n7gGkZFOVM6sqSHvtp4H/dtvKfLpKi6HyMyqVcAff7BfLxx+9G6mDWHvXmqmzcrixcADDzhvPFIYN0XBieOPMjTB6wA2ANjrfOcOwHSAFKcCf7woGI1qi0DPsi1OGW9NDW3CGgIdguEPAEdRixg0qlsHPTw80KFDB+cZrVdeSd73fv3Yrm/bluqUYmOdMx459BoKgsKxq55nxnW7pqYG33zzDa655hp0DAnBqwkJSElJwaJFi5w/xtWryZHHeqMb4Zx47DF963afPsCYMc4bjxRhns1ci6nXmOF5Mlw1xCkdytSppE7NiuBUduX+PH8+jZMVVyscXw51wXqyyQC6D7/4wrXzbELcRqurWLaMlHlZa1RDpD0JrWRkOClVuG9fVQEha0uWagDpqEJHFCAMQDsAvwPIhr//daitrXXwwCyUlNDveh70998HvvzSOeORoz5tRsSfcwXvvKNPXjU4GKiudq0IQLt27PVlABkXllRRl9RkMm6KgqMnHJmogOCtX+/43rtyaHhyxRFMngcyi0PgjWr4wT5FyinjLSmhInkNZV6rHVGGbFSjDXwBWNdBf/+OzjNaBViVeSMjSRFST9pXQ9GjzAsAb79N5Squep4Z1+2//voLubm5mDlzJhASgusbNULv3r3x4osvOj/ampGhT5nXCMEtvdx6K1PqvcPQq8wLUCeAW25x3pik6K1RN6rWUU8qaEgI7c+uSm3Vq8wLUPryG284b0xSBGXeFi3Yrj93jsomXFkzWp9ssqoqY5TpTYTbaHUVej0/cXFoH3MJiyC/oDslVXj7dkDl8Ce0ZGnZMhNANTr4e+E9v6fQGIWIje2Pm29+HSdObMNxZ/WX9fcnZd7rr2f/TEgIzp4ocq2wDGDunoR6F8ubbwZ27cL3P/m45nssKGBW5hUM1AHcNtwc/hfuvReuqcm89VYSY9IwrAVHzwUcx0UAHDh4eKxzfO9dOTQ8ueIIJnAKW7EXeQAaw/aA5pRewcL4AM170WqPHQMPIBmT6t7LyAB27+6IjIwMlJaWOn6Mv/1Gc83aCqG2lgbFWtPuCBYtonWRFVevOYx73+rVqxEQEIBrr70WCA4GV1yMRx55BJmZmdi9e7dzx6jX2di0KTBzJtCqlfPGJGXiRGD2bN0fq62txTvvvIOzzhZ19PenkoTJk9k/U1Dg2r6zejOhjHAq643AxcaSwrGrjJmsLFLmdWUwQC9du9KmFRbGdj3HkbgaazcAR6D3HGbEvWhCmIxWjuNGcxyXwnFcKsdxT8m8n8hx3EHLr60cx3Vl/ex/huJiejBYlf88PPDCPF9LZFMeh6cKz5ypqcybmAh89RXVJn36SC0evPQ6ClLOIj0deOihQQCAw4cPO3BQInx9VZV5xRG2pk3p17L1wcg7Xuy6uuCiIn3zrKKg6LSIod4auMhIJKX0wh33eLnme8zOJmVejQicOFL4BF7HY2cfx8KFcE1NJqMyr+Do8QzeBk8APby7wtt7MyZPZiwTaAgaaaO2mZDzsBk/IAZAPvrA07MVgK3O6xUMMBsz1gyPIwCA/bAVEaqqogh7ijNaKuhV5q2upod1wQLHj8VRuPrwU13NpMybk5ODmJgY+Pj41JUkXHXVVeA4Dn/99Zdzxyis24GBbNeHhNChffBg1NTUgHdFyt6RI+zKvACVxQQHY9vSpXj00Ufx3nvvOW1o9cbVtY6CMq8eBWbA9SJ/OoyZzIEDMaNTJ4ycMgUPPPAAzum5R+qDXgcPALzyimtrl/Uq8wYH4xSAOT//jCeeeAL/uELY6sEHgTvuYL/eiHvRhGgarRzHeQL4GMA1ADoBuJHjuE6Sy04BGMrz/BUAXgHwmY7P/jcQlHlZ048AJB54AqtvW6paHuXQWjPGxfLkyZMAgDZtScHzzyUUyezZsyMAD3z/vbqxUW/OnAF+/VU2iiFNdczPp19FCLFLsXZ6XfCmTezz7O1Nh5H77rN5Wfr/caiRqLcGLjcXBx/4H4LL8mxedtr3yLgpiiOFxQhGCIoUM5YcXpO5bBlFgxlITATaxa9DX47Ds2PjUFFRhp07dzp4QDIcPgx8/bXi27YZpRvgiz5oi+sQENAffn7ncMcdXzuvVzDAPM+C4R8cnAzAG11RIrnCiQrCgoOH9Xn28SG1TFd6w6dNozRrVlzdaqRNG1rjNOorc3JyECkoyU6cCNxyC5o2bYru3btjjbPT9oTolo79GTyPitJS9O/fH9OnT3fe2AT0Oht9fICSEqzbuBEA8MMPPzjXuN62jRwTmzezf0ZG5O/MmTOIj4/HH3rqd1m57jpS5mVN9/fxcb3CsY55XrNmDTp27IgffvgBRUVFWLBgAZ588knnjw/Qd4ZwtcLxiy+SvgArPj541dMT8zZuxNtvv43HHnvMaUOrIzGR0uNZCQ2lX//xXq0sK3QfAKk8z6fxPF8JYAmA68QX8Dy/lef5AstftwOIYv3sfwa9hgIAfPstBlWuQ3q6sq6HQ2vNGBfL1NRU+Pn5oaUlNerjeUWWHub+ANpi+fLDzonA7dlDD7lMbzzbVEcrgjEjxWlCOFFR+pR5AVmFY7n/j8OMRL2Hn9RUvH7hDnSCvcKxU75Hxk1R/LPlnBNiHF6T+dtvzMq8Fy5cwK5du3B1QACGhoSA4zisW7fOwQOSQUaZVxy9v3iRzmRANoBUVGAaMgOW4ePPluKaa67BihUrnHvI1aHMm5gIDB16BJEejbAOoyXvtgPg6RyjVW+qHuD66BGjMm8dJq3HzMnJQcuWLekvN98MPPooAGDkyJHYvn07SkqkzgoHEhkJDBrEdOmlS5cwe/ZsrGrWDE/3749du3bh559/xsWLF503PkD/GcIyz+t37ABAzub9+/c7YWAWLlyg1m2sWQmArMLxE088gZSUFPziDAHF+qxna9ZQFpqruPVWMpQZ+PLLL9HI3x9HW7XCzvfew7333otFixYh3Zkp13pLoIRrTRytrq6uxvLaWtzYpg0ef/xx7N+/H5ecnW59+DA9M6yMGUPXd+2qfe2/GBajNRJAlujv2ZbXlLgdJCer67Mcx93JcdxujuN2Oz29wQjuuotEgRhJSgJO5odg8WfFiIjYjh49ttmlCju01qy6mqwixkhr69at4WFpuG2rcJyAmppDzonAqRgzSsbTc3gFbWF/oHOaEM6qVcCKFfo+8+23VE8hQun/4xAjcf9+UqJkxfJ9yxn/TvkeGTdF8c8uRrDFaOXtnOhOqcnUsSnu3r0bPM9j8IsvIvSJJ9C9e3esX7/ewQOSUF1tp8wrl43A80BQEEViYsL74bcH1yFxeC7Gjh2L3Nxc5x5yr7qK6rD69GG6PDk5GQktwuvmWSAgwActWrRxXqRVr7PRlQc0Yd3Wc4Bs2xZ49VXyXriCVavIIMzKUryktrYWeXl51khrVRWl9/E8rr76alRXV2PDhg3OG+MTTzAr8+7YsQMff/wxrsnPx7uHDmHgwIGoqKjAn3rqivVSVaV/nkNCcAnA1iNHcMstt8DT0xM//vij04ZYr7TR3r1tIvBbtmzBt99+Cy8vL2zZssXBAwTV2/bv7/h/15G89hqzMu/WrVsxtGdPxCYnA6dP44knnoCHhwdee+01542vPpFWoS2Pq5RvdTobt2zZgvM8jxs6dULfvn1RVVXl3L2vqora63z0ka6P3XDDDRg6dCjS0tKcNDDzw2K0yuVRyN55HMcNBxmtQn4C82d5nv+M5/lePM/3atasGcOwLjP69VNV5hUjHC4vVAcjGIU4fXoafv11ELp1excxMXQod3itmQ7vWWpqKtq2baugcNwFQCoyMpyQwqCyKSoZT0VobFE4tuI0YRkAeOstYN48fZ/54AOSMheh9P9xiJGoV5nXck8093GRQA/jpmitdaRIqxdq0NS/DHffTc+HU54TAR2bolDj3eXWW5G0rxNSU0dgw4atiIkpd27P5YULyZtrQS56X1UFABvQuHFjpG1pjqvmXwmsXo1rrrkGHMdhhV4HTH1gSNUrKytDWloa+neKhBdqEB9dZjO/ffs6SUHY3x+Ijtb3GVf2x6yPodCyJd0Mbdo4Z0xSMjKALVtU67/Pnz+Pqqoqa6T13Xept3lZGQYOHAh/f3/npwgzIkSxHmreHDe1bInVq1ejWbNm+FnieHQogjJvJx3VVcHB2AagoqoKU6ZMwYgRI/Djjz86L3uiPhG4W24BvvsOAEW77rvvPkRHR+Opp57C8ePHcV5PXSILepV5AUpVd0X6N6BLmTcnJweZmZkYILTHKS5GZGQkbrvtNnz55Zf44YcfnDPGjh31KfMCtD7V1MinwzkDnc7GX375Bb6+vhj9/ffoa/k+d1gyFJyCkDWiY4ylmZlYvmwZ/vnnH3Tr1g379u1z0uDMDYvRmg1AvGtHAciVXsRx3BUA/gfgOp7n8/V89j/Btm2qyrxihMNlEUJQinMAMgBEYuvWR/DSS9+gthaOrzULDCQFyuvks7eFtEKO45GcnIbKyjZATAw6xJTjG8wQXZkAgEeLFk5K1QNkN0WxAWPlfcThfczD0wgFZa87VVgGqF9kRiadUO7/4xAj8cIFMqwZRGuEOW/Smv4/V/Yudr4xCFB6VFYWEB6ueplQ6xgbC3yPRIxvsRPvL/TFJ5/Q8+GU50RAxzwfOnQI4eHh2PPJSSy9/S8UFw8HUImsrG3OE7OSMWaUovQXL27AkCFD4CmkqBcXIzw8HL1793ZOXZnAsmU01wy9q48dOwae59HZUpJwdHuRzfx27NgRJ06cQBVZ4Y4jKQlYuVLfZ5580q5G3WnUx1AQiuRdpXDMILiVm0vHgrpIq0h0xNfXF4MHD8batWudN8YbbgDuv5/p0vT0dHAch9c6dUJSq1YIDAzE9ddfjxUrVjgvpTAwkJR5J03SvlagaVOs69oVnp6eGDx4MCZPnozU1FQcOHDAOWPUGYErLy+3eV4XLlyIAwcO4J133sHVV18NgCKJDqU+6f6Fha5TOM7IoLlW0SIQ2LaNWqj1HzyYXrB8/3PnzkWfPn0wdepULHCGIFy3bnQQsWTaMRETA/Tqxa7C3lB0lEDxPI9ly5bh6quvRlBQEFq2bImoqCjnGq316CO7+8AB1PA8Ppo4EQDwIWN50r8NFqN1F4B2HMe14jjOB8A0AMvFF3AcFwPgFwA38zx/XM9n/zPMmAG89BLTpcLhsgCh2AehVHglgO5466238N13vONVZQVlXhkJf3FaIZANni/H2rVtkbTYA8/P85MYVwkAgPHjnSDGVFREXlIZhcfERDr/WoM2ewE8hEK8i6fxGr554wx43olGjHiM9amBk0RmxAaZQ43ErCzg8cdtInByiOe8GNQU/NjOIsyd62RjECAhm6goJo94YiKNJZuPxPK83rjpFi8nDUqCzkhrly5dgNffwNyKRwEMBuAJYJ3zxKxkNkX5KH0mgFQMGzbM2vzd8tmxY8di586dKCwsdMIAAezeTTcaQw1ccjLVU3du355ekDwvHTt2RHV1dZ1InKFMmgSMHeuanyUo8+qJetTU0MbxySdOG5YNxcW0Wako8+bk5ACANdIqUTgePnw4kpOTnde25fBhZrXRU6dOITIyEr6hoXXju+GGG3Dx4kX8LUrHN5La2losXbkSX50/j549eyI4OBgTJkxwbopw+/aU1qrW8sACz/Po378/br3ySiA4GGe3bsWzzz6Lq666ChMnTkSvXr3g7e3t+BRhs6f768ic2Lp1K/z8/NBtwACbz4aFhWHt2rXo27cvPnHGM15QoN/hNW0asGsXewuahvLQQ8CsWUyXbt68GZmZmZjg5VXXM7hv377ONVrrkSGzxZKufGO7drjhhhvw888/O7/u1oRoGq08z1cDmA1gNYCjAH7gef4Ix3F3cxx3t+Wy5wE0AfAJx3H7OY7brfZZJ/w/zI+OxVI4XE7Bj3gN/QCEA+iMJk0ewJEjRzBr1jrHq8oKyrwyheHWtMJtAEYAAKqq+mLOHIvC8cwldcZVTExbeHv7IjjYCW1v7r4b2LBBMZ1w5UpxVg11VypEBnIB9OmchqVLlzp+TFIYxDKkrWxOng9GZVERpkyZgoceeqjuOsEgc6iRWA9l3mp4oxOO4J2q+52nuizm118pGqyHvDzgf/8Dcl2UyHHkCPDVV5qX1dTU4MiRI0hISMDpckEUrBGA3gBIjMkpYlYy8ywXvffyeg8c54Hx48eT8RgQUPfZHj16gOd556TdAlYHD0N68JEjR+Dt7Y22EyYAixfbGWkdO9orCDukZdS0acCnn+r7TG4usG8fvvvuO7zzzjvOPVi0bUv34jXXsH/Gy4vm2VUHcYZ5FozWukirROF42LBhAOC8VhQ6nFDp6emIi4uj6KzlkDt8+HAEBARg9erVzhnftm2U1s0YeVywYAGmTZuGkJAQvGtROW/atClGjBjhPBXh669nVubdvXs3Dhw4gCWbNyOlpARPzZ+PsrIyfPjhh+A4Dv7+/ujZs6fjI60Ocio7DR0RuG3btqFXr17wCQwERo60UTj29fVF//79cerUKcfP9fPPU4mRmZk+nVmZ94033kDTpk0xNSAAsCht9+nTB2lpac5rH1SPuuCtO3agI8chrKoKiYmJKC4uxkq9WUD/Apj03XmeX8nzfHue59vwPD/X8tpCnucXWv48i+f5UJ7nu1l+9VL77H8SHZui9XDJA1gPYDgCAji8+eY0eHg0Q0XFBzbXOyRas3s3PeQyKpTWQ/UUAJWWMfWk1xctwqCKtXXGVUaGFzp37ogtW7Y4frGMilJVeLSO828AawCQ4t8qAI+98w6mTZuGjZZFyWlobIpyrWxWbQ3GrNzT+PHHH/H+++9j06ZNzh0foEuZFwCOohMKEeo81WUxy5bpFijAyZPU8+yIi3xiXl52yrxSkpKAmJhTKC8vx6JFXVDhJ1Y4HgFKRClxjphVeTlJA4vmWRq9j4zMBcctwK233oI2Qn2jKKogZwg6FB1r4pEjR9C+fXt4t2lDhqQkNS0+Ph6AdawOaxn122/6lHkB4PXXUTVsGGbPno1HH30UHTt2rIsUmwZXHsQZlHlzc3PBcRxaCM4IicJxz549ERgY6DwxJh3KvKdOnSKjdfr0OkE7p6cw5+eTY45RmXffvn0IDw/HoaIiDFi0qO51p6YI69jvk5KS4OPjA19vb9wO4Ks//sDDDz9c9xwDwIABA7Br1y5UODKl9NZbgSuv1PcZQUTIFTA6lS9duoQ9e/agvyAq9ddfwG232VzTqlUrlJaWOt7wqk8njEOHgO7dqbbdFRw5wqTMe+jQIfzxxx944IEHEBAWVrf3Ob2utV07crJ37qx6WW5uLrp06YJ//vkHW7duxQBLO7Xhw4cjPDwcSU4TxTAvOpqSuak3VVV0iNTxoPv7AyOwAEAeggKG4rPPgJkz/VBbeyeA3yEtDW6wMaFizNChuhRUonwXgGHW1y2HH2vNK3DgwExs27YNTZp87Nh6vVWrVOvLrIf/z0DR6U/gheb4AsASy2Hn5ZdfduCAZDhwAHjkEcW35cRwHq+Jx6KaKjz11FOIjo7G/fffj5qaGueMrx7KvACQiO9wA352nuqymPrWBQufdTZVVcC99wIKbWuSkoCmTelMm5tLafL5+QnIrySFYw61AIYDqIav7ybniFldfTXVD/XqZfOyOHo/YcJ88Hw1nnvuOesF331HqVUA4uLi4OPjg2PHjjlhgNAV9UhOTkbnzp1pHV23DrBE5gQaNWqEqKioOqPVIS2jKitJ3bge6YSbiotRVFSEJ598Evn5+Xj99df1/Rus/PknGYSS74NljC6LtD71FLXlUSEnJwfNmzeHt2CUtWlDCseWchVvb28MGjTIOU5HYX9muBerqqqQnZ2NVq1a2SgcA8CIESNw9OhR5OXlafwr9UBn7XJubi6ioqLgERhoY3A5NUV44kRASFVVobq6GkuWLMG1116LGdddhy0AIsPCbNchAGPGjEFFRQUW6ulBrMUbbwBTpuj7jEXheN++fc53PjE6lfft24eqqiqr0SpD69atAcDxSrP1iVbzPHUtcMazIaWqCkhIYCp/eOONNxAYGIj77rvP6sjjefTs2RMcx2HPnj3OGWNEBHD77ZplHRs2bMDhw4dx3XXXoaCgAAOio4GgIHh5eWHatGn4448/UGyy1mXOxm20ugIdG44QIcjPBzhQfYxPTd+69yMiJoMisLZKig02JlQWy7lzAT8/wSqmhrF1okAhIcg9WiSqeQV4/n4AY1FQ8ChmzTrkOMP1jTeA+fMV3547F/D3rwTFVq8D4IdAz+HYCqqheeihh7Bu3Tps1tP8XC/t26sq88o5F8qxDkAs5s2bh7fffhsHDhzA+zraI+miHsq8APAAPsDdHp87T3VZTH3EMkTCLU6nqAhYsEC2Llj8/BLCNZ1xoTYEHuDRMboUwEB4eDRG9+7fOrfGWiFVj+d5fPvtt5g2bVrd4QYARSEs3l9PT0+0b9/eeUYrozKvoBzcqVMn4Nw5GqNMGmbHjlYFYYe0jKqPyBEAhIRgOSj69txzz+HGG2/ETz/95Jw+o+npmsq8srgyesRAbm6uNTUYoDV0zhxKf7YwbNgwHD582PGRo4oK4NprSRVVg+zsbNTW1lKk9f33SeHY0p/1SksEzyk9mHWmE+bm5lJ9sCSi3rRpU4waNQofffQRUhjE+HRRWMh0H65btw5nzpxBYmIiHps9G00AfHjjjQgKCrK5bsSIEbj66qvx4osvIt8RomG1teSc0JsBdvPNQFISpk2bhlmMdZL1plMn4OmnNUUId+3aBYDSWAGQIS7ZSFpZHD6nTp1y7BjrE2mV1Kg7FcZnpaamBsuWLcNNN92EsLAwup7ngYsXERQUhPbt2ztPoTc7G9i5kzQJVNi7dy98fHxQZvHADly+HHjnHQDAxIkTUVlZ6bySBJPiNlpdQVAQRQjHjdO8VBwhSEYy2gHwq2haFyF4/fUuAJoD+KvuMw5RlVU5oCUmAvffb7FIEWcrChQcjLzjxZKoBgfgawCVuHTpF8fVQWoslomJwAMPbARQAmAcYmOBGfeS2uKUqVMxd+5cNG/eHG/prZdkRVDmPX5c8RJ75wIPL2xEb+8gcAUFmDRpEq677jo89dRT2Lt3r+PHOHMmiTFptJWSppJW+IWgW5ti5xpYAjojrTk5OTgrKNC6YlNUSeGyj/AdAtAaQCAW40b0xQ4cSfMHz/tj9OjbsX37T+C4bMcJqgn8+iulwilsillZWSguLsbAgQNt39ixg1LNLIgNQYezeDFTT+M65eDOnVWdEx07dsSxY8dQW1vrmJZR9WknA4APDsZyAFcOHIjAwEDMnDkTZWVlzmlBUQ8VSgDUl9RVCsfXXw888IDqJTk5OVYRJoAOj5mZNoIvQl2rw6OtQUEUCbaocqohGACtWrWyS2Hu1q0bQkNDnZMirHOec3JyyAkgo0y/YMEC+Pj44Prrr3dslIZx3U5KSkJISAjGjBmDNt274/zMmZggo4rMcRzeeecdFBcX48UXX2z4+NLT6bAkSpdmJT8/H8ePH8fu3bvrDAin0L07tczT+B53796NiIgIq6OnoACQGKeC0WqKSKsrncqMzsaUlBRcvHjRugdKFI67devmvF6t330H9O0r9JxTZO/evejevTs+/vhjjBw5Eu0FIUIA/fv3R1hYGH7XyGL5t+E2Wl2Bry8JZcgo80qxRgJykIfjSAQQgpK612++2QMDBoyEh8ffAGodpypbVKRap9e6dToAICsr1lYUKDQUVRW1Mp9oavl12nF1kAyLZWnpcvj7+6Os7EqkpwNXdBuDwMCZWLz4ZXTqFICEhAnYsGGDc9JvMzNJmVelrtJeDCcD1TiPGVVHgNOnwXEcvvjiCzRv3hzTpk1zbD0PUC9l3tpaYPDYEDTzdqGCoo5NccSIEWjdvTvmAXjnxQLHqmrLoXKAtL/XD4N6FwO5iMSZ2D6AlxeSkoB16+4DUAtgoeME1QR27QK+/15xnoXesQkJCbZvvPmmTXp7VVU8UlPTwHEVzv1OVahTDu7c2apwLHPY7ty5M0pLS3Ho0CHHtIyqrqbomx5lXgDJxcU4BWC8pRVF3759ER8fjy+//FLXv8NEcTFTfbXA77//jt69e2Py0qX4JDPTOdFfKQzKvHaR1tpa8piJatt79uwJHx8f7Ny501kj1UTo0RoXF2dXkuDp6Ynhw4dj7dq1jtdz6NCBarkZ5rmiogLnz58nJ4BMRD0mJgY//vgjTpw4geeff95xY2RYt8vKyvDLL79g0qRJ8PPzo+f5yy8Bi0NCSufOnZGYmIhFixY1fM+ur4Nn+XLstGSEVFVV1UU5nQKjMu+uXbvQS1z6IZPuHxAQgBYtWjg+0vrQQ5TaqgeJg8epMEZad+/eDQDW73HKFNo3mzYFAHTv3h0ZGRm4wFAbqxth3fbzU7yE53ns3bsXPXr0wKxZs/DXX3+Bmz+fIv8AvLy8MGbMGKxcudJ55WQmxG20uoLTpynyUVCgeak1ErAEAI+bAISgyCZCcNddV6O29iz27TvoOFXZe+5RVebNyMiAl5cXIqSpr0uXYlrsdoV/tAWA046rg9SItPI8j99//x0jR46Ev78/kpKA++8PwJzScEzFbmRkAJs3D0JRURGOOEOwh2GxlEYwmzQhYYKBos83adIEH330EU6cOIFVq1Y5doy//gq8/bb+z7kynfDoURIpYCAvLw/Hjx+Hv39TzAHwXHETx6pqy6ESgbO91ysAHIfQBqqV/2ksGfkFkJuLOXOAS5daARgP4FMAFY5tfyM8KwrP86FDVGvbWSoEITr8UIvSjiDD+oTjv9OpU4HPP9e87OjRo/Dy8kLbtm3JCA8KkvXYT5w4EcHBwXjhhRcA2J7vmzSph3OvfXsgORkYNUrHh4DllvTVaydPBkARoxkzZmDr1q3IysrS9W9pokOBGaAo2/Hjx7Fn507cd999iIyMdG65BKC5bldUVODcuXO2kVahtZlonr29vZGQkOD4lL0tW0iZd7vSPmbl1KlT8PDwQFRUlOxBfMSIEcjMzESGUCvjKATVbIZ5Pn36NABL+6AJE+oUjsUMGzYMt9xyCz799FPH1eAyRFqXL1+OixcvIlH8IPK8aprk2LFjUVRUVGdk1Jv6pvt7e2NHeTk4y3fv1Ofl2Wdp3VGhuLgYKSkptkargrBaq1atHB9pvflmuq/04OlJOgtix5SzYMyQ2b17NwIDA23Ev8R0794dAJwTbRWeFZXn+dSpUygqKkKPHj2sL6am0jndwrhx45Cfn1/Xs/e/gNtodQW7dpEyL0MPQWuEIAmB6IRARCDIt9omQnDVVVcBANasWSP7b9SL6GhAmiooIiMjAzExMfCURm44TjaqQbSAh8dpx9VBakRak5OTkZGRgXGWNGwhVfMWfIuRlhrgykpSsXTKxsO4KYojmFOnbkWQvz+ZNaID2tixYxEWFub4Nj2//KJbmTcpCfjipxAUZxe5JtomtOSQGYe0hYmg7ufpmQSgLcpgFepyWg9UGWVeAdtn4RiAGgAJaNIEWPB4Gvr9bxZw6JBEkfs8AFKodVVWwuHDhxEZGYnQ0FDbNyxGa1ISZRdXVgobOtW1OvQ7XbaMSZk3KysLkZGRVpEeBQdKkyZN8MQTT+C3337D7bdvswlYlJc7aMwMLP/nH/Tq1QuRIofAKIvh63Bl8MhI1XVbTHl5OTZs2IAZM2bg5IQJ2B4QgJCQEDz++OPOaYEioBGBE4ymSOmBVuYg3r17d+zfv9+x49WhzJueno7o6Gi6F2XE33r37g0AzintYMSmfdD06ZQKLsOcOXNQVVXlOJGwW28Fhg9XvSQpKQmRkZEYOnSo9cVWraidnQIjRlCbvQb3wK1HmxHh+h0AOsfGonPnzs41WhnqRffu3Que5+vuNQCKa2Lr1q0dH2k9coQpAGPH6tXMvVMbRLt25AzVqFHftWsXevToYT3THj4M9OgBWNZopxqtDFkJwhpiY7RK5nnUqFHw8vLCd999h2qN+th/C26j1RWIFkut3oGJicCLL6YA2IdS3IEBsbmY8cVgmwhBy5YtkZCQ4Fij9c8/6ZcC6enpiI2NtX9j+XIkLp+KzxZSqjJgzUgMDIxAkyanHVcHefBgnbKpHKmWA3C3bt0AWA2AIohbjcQCiMTjj29yvPFVj01xy5Yt6Ne1KzwBm8XI29sbEydOxPLlyx1bQ6NTREEQFnq05AW0winnRjABUmy9915g/XrZcUhbmHzxxXZ4e3vjzJme6Ih4cFgLwLqhOqVFz+jRVPci3kwsiCPpggjTa691wfnzwKjJ1roea0TW0moG5A13aFaChtHapUsXm9eSkoD3vw4BSkpwy/RaUMaR4PW31rU65DutqKC5ZrgX6+rzBL79Fnj4YdlrW7R4EEA4Kipesnm9Xsb2ihWkzKuj9+/p06exY8cOjO/SxUbRt0uXLmjUqJHjD7zPPAMsX8506T///IPy8nKMHj0aXEgI+paVYc7TT2P79u2O3UvEVFTQL5V5FiJBskarJKLevXt3nD9/vs4wcwg6InB1PVoBMrZefRUQCZl16dIFnp6ejjdaJ0zQbBskkGu5X1u2bEk1c/n5suJDbdq0qYu2ntdI32bizTdVlXnz8/OxatUq3HjjjfDwEB09/f1Vax2bNWuG7t27N/werWd6MN+oEXYA6Ne6NQYNGoStW7c6Lx2ToQTKLq2V/gKMHWs3z61atUJmZiaqNGonmamoIGXeBQsc8+85g5YtyThWKeuoqqrC/v37bb9DANi3jzIjQfddZGSkc8SYGM5he/bsgbe3t202VAjtz6ittfw1BOPHj8enn36KFi1aOEcEzmS4jVZXYFksf14TLHvwvvdeW0N2z55lAICsrEmK6b99+/bFwYMHHTfG119XVebNyMiQN1pTU4EffkDi+BKkp1szfXgeGDasBc6fPw2O4x0TodNQ5hU89kIKs2AAFCEEIRA2RQ7AIJSVbcIdd/CONb50borFxcU4dOgQBvbrZ/t5C9OmTUNpaaljG0jrFDkSotVFaIwLaALAiRFMYXwLFtjVBSu1MFmzZju6d++OJk388ChOgUcNqCUU4dQWPQqpPUIk/cknD8Hb2xuPPGIx/EQKimPGCB8X6txPwdubhEgdUpMr1C7LUF1djaNHj9rUswpOgcwiuneDINQ6BoIcPVYFYYd8pzqeFTuRHpHCsZikJOCBB4IATAawBZTWbEW3sS0o83p5MX9kxYoV4Hke47/6ysYJ6OnpiQEDBji3B7MGq1atgp+fHwkaWe7FmZMmISoqCi+99JJzoq2VlXSYVkjBAyhl1NfX114UTCZ6JDgkHXqQZHQ21tbW4ujRo9aexoLCcbt2ddf4+/ujU6dOjjdaCwqYFaJtjNYPP6QaPYXSjjvvvBOXLl1qeP9bBmXebdu2obq6Gtddd53tGww9g6+66ips3boVpaWl9R9j586kzNu8ua6PnbhwAQUA+kZFYdCgQSguLq7TBHA4DMbMrl27EBsbi2ZiMcXp00nDQLIntW7dGrW1tch0lPe2vtFqgGqyb7rJMeNQIzubshtVHAvJycm4dOmSbbRaJnOie/fu2Lt3L3bv3o0TJ044boxPP01OHhX27t2LhIQE+Pr62o7RonAskJSUhF9++QXl5eVYtmyZ48ZoUtxGqyuwLMjPvB4ie/BeuNDWkP3xx2Vo3bo3opo2JcVhGdXJ+Ph4nDlzBgX1SdNQGqPCQlRRUYG8vDyrh1mMgpR5UhLw118twPOXABQ3PEKXn0+1mCoLR15eHjiOQ3PLpiSkahYjWBRpBYBBAHJQXp5ZZ3xpRcCZuO02Uua1FPJrsXPnTtTW1mLAqFF0I0hSZ4YOHYrw8HDHpgjrFDkS9rorcABz8QzCkG/zusNR2BTlf141Kip2oXHjfiguBiLREs3hA+BnAJTB65QWPb/8AsyYoSlXf/jwYcTHx9umtQLYs74Y33wjnO+agQzDU+B5a1Ckwc/L0qXAH3/IvpWamoqKigobo1VwCizBNPTBDpRBnJ7dBcA2ALxjlMoBXcq8diI9O3faKBwLWB0bXQBcBGBbV6jb2GaMwInXjvvvX46mYVG4ArCpDY6LA1avHozDhw/js88ctGYDpMyrEHWWsmrVKgwdOhT+/v51/yffigo888wz2Lp1K1YwKDnrplEjug9vuEH27draWvz4448YPXo0GgkiWwKPPw7Mnm3zUteuXcFxnHOMVo153rdvH/Lz8zFcSIGVUTgGKJ1vz549jnUC6HA25uTkwMfHB02aNNEUwOnRowf8/f0bngGQlkabrcqCJRz6O0rTNmUi6lKuuuoqVFVVNczp06MHkzKvlH8s9f99hwzBYIu42qJ6KBAzwTDPe/bsQc+ePZn+OaGdmcNShOtbFwzIKhw7hW+/Bfr0UVXmlY1Wyzwr3bp1Q3JyMnr37o2xY8c67pnu1w+wlPkpsX///jonXR0ShWMA8PPzw4QJE9ClSxfnOVNMhNtodQVFRYC3N05k+sq+bfsc5KG2djsuXLieTt0rVsiq0QrF4w7rtaayWGZlZYHneflIq4KU+Zw5QFWVkJ5B6RYNitBlZACPPUbCKArk5eWhadOmdUaCkKpZGRAKD5uoi5BmtRmZmcqpp7oNBn9/ZmVegFKDOY5DvwED6LMSL6mnpyeuv/56rF692nHpPTrTg4WDfgek4BnMRwTybF53OAqbovzPOwygDHv39kNVFVCCEFyNQACrAaSjUSMHiZRJ2blTVZlX4NChQ7bqvI0aARyHzSuKRM4rDhRtPWVnAzsroi2nHCw4BXIRiV3og2qI6/uuA3AKHh57HaNUDpAXvGNHzX6EJSUlKCkpsTVa33pLtkzA6tgQ0p6tG3i9jO3iYlqDVRQebdeOcpSXr0Fh0Xhwls+L3xfWnQce2OK4DI9Dh6h3rQYZGRk4duwYrrnmGnpBtG7PmjUL7dq1w5NPPunyuqht27YhNzcXky2iVTZMnGjXJi4oKAjt2rVzrNEqKPOqzDOAun6II0eOpBd4nuoAPvjA5roePXrg7NmzjhM4AnQ5G4UerRzHyUaPxPj4+KBfv34NzwBgMPyPHz+OsLAwMqbFMIj8DR48GD4+Pg1rJ1RQQG3pdLBixQo88MQTiI+PR6cZMxAbG4s77rgD7777rnNUrB9+mJzfCly6dAlpaWl2pR344w+gcWO7s6LD297UV4HZ8pnUc+fw+eefO7+GXmPd3rRpE0JDQ61ZE4CsMv1NN92EadOmYfr06Thx4kSdkn2D+ftvEpxUoKCgAGfPnqXe5GImTaIoskzLwoSEBLfR6sZB3HsvsG4dYmJZFB5/AwAUFl5PrvtGjWQ3HMFoPXbsmN179UJhU0xKAgYOpIjFU0/F2h+2FDy5dIAUjNY8yev1gCEt5fTp03bqxomJwLiLizElVrzBdAEQDGAzYmKUU091Gwy//FLX+JmFrVu3okuXLggODqbatMWL7a4ZNWoUSkpKHKcOd/QoWfKMCNHqItD3Hoxix0Xb5FDYFOXEvry96Ts5f57Sq4sQgvvgDcAHwC3Iz3dS3ZGCMq844hYTU4zMzEzbw4WHB3D4MF4uelDyD7aCUNMqpd7Py5QpigrMhw8fBsdxNhui4BRojjO4DV+gJcQ1gxMAeGLMmB8d5wTo0IEcUFdfrXqZULtokx4s094BEDs2hNRhipB4etazLRhDfZnt2rEWQDmqa65DCUfrtu37vQF4o6Jis8t6VwsI6aoDBgygF/r3J8eLReBq/vz5SE5Oxtdff+2ggVnYtInEohQO+D/++CN8fX3rxPNsyMujGjMJ3bt3d6zROnGi7Nor5a+//kK3bt0QLjhaFPZnQTjFoSnCOiKtgtEKgKnVyODBg7F///6G9WxliMCdOHEC7USp1HVcfz2JOKng7++Pnj17NmwffOYZWncYOXz4MK677jp06tQJGzdsgKfF0HrzzTfRsmVLzJw50/FOnltuoe9DgdTUVPA8b9OvEwCJiBUV2d2LkZGR8PX1dVxqaz17VwPAeV9fjExPx5133ulcoTKNdbuyshK//fYbxo0bZ1tb7eFBSvGispqOHTti8eLFeOONNwDAcem306apCmIKwagOOu7XhIQEnDt3DmfPnm3w8MyM22h1BTExwKBBsgdv+7K4ZQDaISbGkkKj4IWMi4uDj4+PY4xWnpfdFIUowdmzZLSeORNnH4EMC6OCd8niTQdI20ir9fV6wLAp5uXl2bfkAWQUjj0BDADHbcbcucqGgW6D4eefgY8/Zrq0pqYG27Zts9ZxLVoEyAhNjBgxAp6ennVe/gbj7a0k9SyLEK0OaEH3RvvmRY6LtslRXk5jlNyL0lZBsbFA795bEB4ejpiYOACUBp6AUgAfA9iExo3fcs4YZTZFabQ+K4s8nufPS/qgduqERrFhkn+QIq2Avfe5Xs8Lz5Myr4Ja+bFjx9CqVStKE7UgPB+tkYYvMAtX4GDd2hQb2wRdulyJ5OQfneshl0Goz7OJtCoYrdZnPBhUh3sYAQHAN9/U836NigIEI08B2zViOYBGAIaikKc6Pdv3AwD0BPCPY9LrhXWbIepx1OLVr2vvEB0N3HgjYFGPvuGGG9CrVy98zLh+MXPhAglZKSjzLlu2DFdffTU57qS89RYwZIjdy07tn6hASUkJtmzZUqcCXYdMPaaQwuzQg/mMGZrKvAI2wmUakVaAjNba2tqGGYQMTuXjx4/bG1sAPZxPPqn5IwYMGIDdu3fXv3e5ziyjd999F76+vli9ejWa9+9PCzxI/Oall15CcnIyjh8/Xr+xyMHzmsq8ws+zM2YUyrQ8PT3Rrl07x2XktW/PpMwrpaamBpM3bkReTQ28vb3x/fffO2Y8cmjM8/r161FYWIiJEyfav7lqlazCcUREBPr27esYo5XnNTMnhHO93TwnJ1Oa+8aNdp8RMqf+7dFWt9HqCv78E1i1SvbgfffdUhtiHzw9h2HePMuJUaHew8vLC+3atXNcpPXwYeCBB2xeskYJ0kG3SpR9BLJ3b/KISw4Xc+cC/v62RmuDInQMm6Ki0fr770j8fRo+X1Bd9903bjwIPH8YY8YUKBoG9aqBY9wUjxw5gpKSEmvkQ2GeQ0JC0L9/f8cYrRUVwH332fT5YiExEfh1LS2wX39Q7DyDFQDGjCHxFovcvHQcQqug9HQgO3sThgwZgnnzOAQEAC/jecQhHcB0eHhcDU/PT5xjZMnMs320njaOpUslaVzff49vr/tJ8sy3BnAR3t62tXH1fl4uXaJ6HoVNMTU1lXqeihDWpsAI+n+1bVqERYtof01PBx58cArS0tIcdxD/4w9aMzRSKG3adwiEhAClpXZCG7bKzQnw9j7UMAfLM88Av/2meol1jagFCYCNBuCLJ5p/AzzyiMwaMhzALkRFlUjf0I8wzwxrTnJyMmJiYqx1o5cu0Tpg+X45jsOoUaNw6NAhx6qVq6QTlpeXIyMjA3379pX/bHAwCY5I5lk4nB1VSa/TxfXXA+IWLDKsX78e1dXVuFqaGSCzbjdq1Ajt27fHnj17HDM+gAz4SZOYLrWJtMbFAa+8AojTICX069cPnp6eDUsR1kgbLS8vR1ZWlnyktbpaUeFYzIABA1BRUVH/KDujgwcAzp49i6SkJNx6662Uzuzvb2MQXnHFFQDgWKP10iVS5v30U8VLhJ9n9z0qlGkBZPg4zGiNjCSjTqOsQ8ry5cuxITsbH/fujTFjxmDJkiXOU2DWOIf9/PPPCAoKsn+WNbj++uuxe/duZGdnN2x8DOt2SkoKvL2969K7bRApHIsRsrrcRqubhvPaa/QL9gfvTz4RH7SqAZzD+PER1oNW586KancdOnRwjNHKcbLKvNZowEkAUYClzo01SuDvH2r5zGk0aVLPFD0BlU0xKQmIja1FTs4Z/PJLhH0Kc2oqsHQpbhpHCseLFgG+vlRf1qHDVowZYx98rJfBoGNT3Lp1KwBYI60qdT2jRo3C3r17cY6hdk2VwkK64RjqMqTCVL+s1fbYOxSVptsA1ehlZmZi8ODBdcZK49jGuMA1RWwshxkzJiI/P9NxB1sxMsq89s/EIQBByMmRWC0ffYQhyZ/aOK+aNaON6dlnT9k4tOr9vGikcJ08edKmlkeY65tvBko86DMfzrV1Tlx//fXw8vJynIf81ClKHdVQ5lVMDwZknxdhfX3qqS7g+WOYPLnSMeNVwBrd3Q1yzo1HQABw7TsjgIQEmeyaKwFUY8qUfxr+w6uqNJV5BY4ePWorgJOfT5E7kTJ53759UVNT41hjS+VezKBCX3mBP/FnSmwNfCH64LCD+IULtNCpsHbtWvj7+zMpHAMk4HLIIuDTYGpr6aDL4ICzqwFv0QJ49lna3xUICgpCjx49Gma0du4MPPWUbK0dYG1HJxtpFRSONfaW/v37A7DunbrR4VReuHAhKioq8OCDllIOiXNCMBodarQypN6mpKQgIiLCPjNBIdIK0HeelpbmGF2MrCxNZV45FixYgOjoaMzYtg033XQTcnNz8c8/DlgD5XjmGeqGIUN1dTV+/fVXjBs3Dn5yNa833ki/ZBBUr/9QEDhkhqEuOCUlBW3atLGKOAqoOCeaN2+Opk2bOm7dMSluo9UVaNSjCAetvLzzAHhcdZXIi7V0qWJPrOrqeKSknATHVTWsRcb581SLadlYBKxRgmQA9vVvACh6N24csGRJ3UtCquSFCxwoRfg0ysvrOTaBWbPIMpCIONS16sjMB1CN4uIW9inMogVduP7MGaovO3duM775hkpqGmww6NgUt2zZghYtWlgPbCoKiqNGjQLP847rU6cxRjlhqluejMCSL8uAO+5o2Bi0+OknSoXT2BSFA5ag5piYCKQvP4jap55B+u7zePFFEpxxaLsggR9/tOuNaR9ROwwgAbGxkiXWMs9i59XatWS0xsefsnFoOcPBc+HCBRQWFtZFWqVznZxDn9m7wfbw06RJE4wbNw6LFi2qO/w0SHGbUYVy/fpccFwIGjUKtP6MKVOA7duBoCDFzyUkJKC6urphh8rx44FHHlG9RHCYBAcvB+CJqKgxtHa03wX89Zdddk1MzEB4e/uhpubv+o9LIDiYItYqNXCAtVWLjaiHzOFHiHju2LGj4WMTULkX09PTAagYrQoHNKE0xmFGK4PI0Y4dO9CrVy/b9hMAiQPef7/d9Z07d8apU6ca1qJFIDWVIn0MDiObdjeAVeFYow9r7969ceDAgfpnpvTqRS3zFL5HoaZSNtKqchAXExERgbi4uPqnMeuoC/76668xatQoa3qmpCQhJCQE4eHhjjVaGcWsZA3/0FDaN2Ui6h06dEB1dbVjxJi++YaUeXUYrSdOnMCaNWtwxx13wNPTE9deey2CgoLw8ccfo7a2Vvsf0Ev//orKvDt37sT58+dxg4KaOQoKSAlbhvj4eDRp0qTh2UaMzgnZelYV5wTHcf8JMSa30eoKGI2Z05aQfwuVpsgCSUnAqlXxoOhsasNaZKSnA48+aqdmRim+NaAejSRuYheB9PEhb71Itc42VTICwOmGK6H6+1MdlsQjbv1ZQpphhP3PEtX1WK8X6ss2o6yM/gsNNhh0GK07duxA//79SeERIOU/hY2gZ8+eCA0Nxfr16+sxKMn4AJ3iMkRpuQeeesle4djh7NxJDhANZd5NmzYhJCTEVujo+HE6OOXmIjo6GgkJCfhT1CvTmVj7rgJUm3oInp4J9tF6mXpMhys81tRQ9E0mhUuIeGRnt0FcHLX3E8/1RQShBh7YvNL+AHnbbbfh3LlzWLFiRcMVt4uLAV9f+qVAUhKwdm0OeD7S9mdsiAT69lWskwSsqVIN8jofOqR52AdorWjdegWGDBmIrKwwWjvefruu3ELsoMjI8MOQIQMbpoKqk8zMTJSXl9tGWoOC6IYV3YvNmzdHXFycY1VRO3SgyIWPj91bzEar5IDm5eWFtm3bukQ5HyDhlv3799v2dBS44QZybkgQHAQOyYTS0WZEiF51FvcxjosD3n9f9XPx8fEoKirCmTNn6jfGggKmWkxZo1XlIC5lwIAB2Lp1a/2M60ceAWbO1LysuLgYp06dwhBxyZNM7XL79u2dE2mtj9EaEAB89RUwYoTdWw7NTCgupkwjmedZic8++wyenp6YFRcHNG6MgJMn8cgjj+Dnn3/Grbfe6rjOCAJr1igq8wprjo2qvxiV4AHHcejYsWPDs7ciI4F166jfuAzV1dU4ceKEvNEaGEjrtsKzIhitrtaecCVuo9UVMKaNChtGuPiw+c47wOjRdtfOmQNUVgppYbQx1tswVPD8JCYCr7ySBuASgM7yEUiOszuI26ZKUqTV/nWd/PIL8O67di9b/02r0Wr3s0SHH9sxDAKwE8AlxwijpKRQ010RctGompoapKen2y5K338PKKTleXh4YPDgwdgoU3yvCwZPblKS0J5D4AxI0boWd2bMYfL2NwhGw/+ff/7BwIED4Sk2biWHn2uuuQYbN25CTExJw/rvSpk8Gfjyy7q/JiVB1HcVoO8sH/36dbF3fsgcfoKCgtCsWTPH9dLr2JE2baE1h4iTFnGmBQvaSuZZgMMVOIiXih62e2f06NGIiIjAl19+2XDFbYaox5w5QE1NDgBranBZGfDuU2eAL76oq8eUIz4+Hj4+Pg3rP8nYZoTneRw/fty2d6KCWBRAPScPHTpUfwNBYONGOgDt2qV6mdCmwSbSKqzbknuxb9++jo20TpqkuGakp6fD29tbXoeABlOncCzFYaUxgOb+fPjwYVRUVMgbrQoKx4LReESmXV29xgcw3YtLlixB+/bt0bVrV3pBYZ6lNLgbwdNPq6apnzhxAi1atLDvxQswiUUJ9O/fH7m5ucisz4Z9662AJcVTDcEosTH8x4+3Uzhu376941R5Ac0I3IULF3D+/HllRVmel3V8O9Ro1VECBdCYP//8c0yYMAER4eF1CscvvvgiXn31VXz33Xd4R0fHBSamTqUyKBmETATFNUdl3QZoDW2w0RoYSKUZCsGp9PR0VFVVWUXzxMgoHIvp0qULLl68WL/n4zLBbbQ6GwVlXjmEQ4xNpDU3F5DJ/ad7Uli8rBtNRkY9Ducqm2KbNrTp7tjRWTkCKdkUbVMlrUZrg3p7/vST7EJk/TdtjVabnyVSOLYdQz8AlQAOOabvqESZVyka9cknp1FVVWXb91YlgpmUBGzaNAQnTpxAVFRe/Q0vBWVe6Xit8ACmA7gewFW40uNr4K+/6vnDGWHYFM+dO4djx47VpQbXITn8eHtfg5qaKmRlrWtY/10xPA/8+quNMq+9AUfRvRMnZLy5Cptiq1atHGe0qiBEWi9daq14TTI6yygcA0uXeqG09Fb8/vtKZGTI11cz75XMyry5AGyNFq/sdCoXOHBA8bM+Pj6YPHkyFi1aVL9WHjrW7cLCQpSVlSFKfJCQMRQEB9bTT5OH/eWXGxht1VDmFRAOWR2lip8yUYW+ffsiMzOzLuvHmaSnpyM2Nta27YQYQeE4zP5e7NChA06ePOmYKM2MGcCwYYpv77I4BWSN1rffBgYNsnu5bdu28Pb2dozRythmJC8vD+vXr8e0adOsGTzC5zQMwgb3fdd4VhQjhABTWx4BwTF08OBBfePjedJyKCzUvFSYMxujNTGRDHMR7dq1w+nTpxvWKkhMhw4UFVAwSoWoruL32K4dcPvtdi+HhoaiWbNmjou06lBgfv3111FcXIznn3/exqnMcRzmzJmDESNGYMGCBY4TZdJQ5s3Ly4O/v7+8Wjkg61QW07FjR+Tn5zdMX+TUKcomU/g5mu1u/vxTelCrQ7g3HOpMMRluo9UVHDkCzJ5t97I0Cvfnn3RQsIm0hoSQsSHZnMnICgbQFKTua6VeqXrCz5IgeOntDjxiJAdxW/GRFgDOwd+/pmG9PRU2RevPEozWFvYpzD17kkd82DDJ2Eih1sdnf8P7jl66RMq8IgeDUjRq3jw62ceILeUVK6h3l2SeBUOyoIBSlXJyNtXf8Lr2WqpBFrzwEuzH+yeAvwFMBLAb93sVOl+IiWFTFKJnQ6TtMCSHn+++GwjAD4A1Qt3gNPWyMvJmizY9e0ONakrOnu0ifYNEUWQsO4e2JVi+nJR5ZSJ5FGmNBOBv957ALT5L8O11P9m8JtyHxcXXAKgBCQ/ZI2NfyPPss2T8qxAdXQt6rlvavB7Yki0y8+CDD6KkpKR+vUdl5lmJrKwsy3ijrS+GhNC/YWkFJnZgAT0ABOOzzzY1zIHCWKOenJyM8PBwhEkn56uvqCxERJ8+fQA4sK51/HjFVi2nTp1STg0GaE3duFE2oh4fH4/q6mrHOHreeUdVmXf37t0ICwtD69Yyjp7gYJpnybrt5eWFDh061O2fDYJxnn/66SfwPI+pU6faj1HDsIqMjERgYGD9I60qhgLP80hJSZFPDQasCscSRXM56h0RLisjsSgVZV6B5ORk+Pn52Sq3CgrHohpMhxsIkZGkGaGgzKvY7kZAonAsxmEKwjqM1pycHHzwwQdITEykcg2ZiPrdd9+NjIwMrFq1quFjA+isXFOjOMa8vDy0bNnS1qkjpkcPOicp1NoK5+AGPdcbN5IzLj9f9m3FdjcMCFoVqRJ9mn8TbqPV2XAcec4k6QhyUbiffjoDX98ABIkFRhS8kFbjKw5SoxWoR6qe+GeJOHLkiG2rBDk6dbJRDbRtPdECQC3eeONsw1qlKGyKws9q1Og0gEaIjQ1UFVGyHVscOC4YQ4bst7m+XgIzBQV2yrxKUafTpykv0ybSalE4ls6z1ZDsDiAIwEaUlQGCqKFuOE4xqms73ioAjwJoB+B73HLLXOyqLMPOhsq9ayGjzCvln3/+gZ+fH3r16mX7hmRTzMryAdUtb7e5rEGZMzIOHvso/SEAzREbK6Ok2bgxKWVKSEhIQGZmpmO89irKvKmpqfD1VW5/ERsLvBn3EYYcthV/s96HgiEuXytaUuKgFGwATzxxFlSzb420BgQA9z7NZrT27t0b/fv3x4cffqhf8KOqigqVGQ4OQguEI0ei0LQpPV4PPk9r1Y9f0HzaOoQ8AfRBdfX2hjlQGGsdk5OTbVODBUaMALrYOlZ69OgBjuOwf//+BgxMhIoyb3p6urrRWlBAEVAZtU6HpTwKyrwq7Nq1C7169ZI/6CooHAMUqXNIpDUhgZR5ZdYNMUuXLsUVV1xhP9caKY8AlaA0KOVaJUMmJSUF586dQ79+/eQ/Gx6uqXAsEBoaivDwcP3jZIxWA3TmiY+Pty09+fhj+v5FkVrBaHVYXauGMm9KSgo8PT3l26AAqhF1hxmtc+bUdcLQ4qOPPkJ1dTVeeuklekHmLHv99dejRYsWWKAgNqobjVR6xbaIAjfdROcwhTVLMFoblCKscS8eP34cYWFh1GpJjsRESoGWoWXLlvDz83MbrW4awLlz5MkVpRMC8lG46uozqKmR5LkriBQIxldAQBzkjFZAx+H8jjvoYkujeTFHjhyxTZORY+lSGoxkfOnpwN9/08L+8ss7G1ZXqLIpJiYCo0fnoX37CPkU5spK8vgvXmwzNp73wKBBXVFaaq1JqrfADJMxQzRubI20CgbyzIfoc8u+tZ1n6xx6ARgIgCK5+fn1+B4FZV6FA7zteNeD0s5fRWysDz76aAaCvbzwvqPEgpT4+WdAo4H3pk2b0K9fP/hIxSDCw6l/5113ARD+P/0B7AFgbUjfoFRwmU3Rvq3JYXh4dJGP3h86RJL8EoEfQRjCoemEMs/LyZMn0a9fW9kWT999R89F87b2KVLW+zAU1P5K3mitrGR0lo0bR8qrKvTrRxG2Zs0ibVS9J85kTye87777kJqaqj9y2LgxZT9oKPMCVqN17tzoOuf5j5iMvtiOGfc3QlKS3FrcD8BBZGQ0QF2WodaR53kcO3ZMvj5q1y5A0v/Z398f0dHRjjv0KDgby8rKcPbsWXWjVaP3JOAAoaPjxylCZdkb5MZ5+PBh+dRgjTF27twZ6enpDVcQFpR5VRzHVVVV2LlzJ6655hr7Nx991K4Huxzx8fENi7QqHMIFAcHhChF38DyQna0YeZISHx+v32jQURd85MgRecNf/O8AaNOmDTiOc5zR+vXXpMyrsD/v378fHTp0sG+DIh6jitF67tw5FKiIZTExYICigJCUdevWoV+/ftYMBUHhWBRR9/b2xqxZs7By5UrkafTsZkLDIMzNzVU3WjWIjo5GYGBgw4xWYY4Unuf09HRlxwSgqnDs4eGBNm3a1GlX/BtxG63O5tQpWWVeeYPyNKqrJakhMTHAwIGyPdoSE4F7740Dx2WC6g/tP8qEgjJvTU0Njh07pm20qpCdPQRAKM6d+7lhdYUaaSmqHjRvb5IHlpEC7969Ow4ePFhXU1FvgRkmY4b+3qtXBkJDQ7F8eaM6A7kI9LnXnymy+W5s53AIKPX0fN1YdbFjB/DDD4peRNvxrgfgBX//MZg7F2jUqBFub9MGP1y4UNc70wiKi4uxd+8+7Ns32N4J4uFB/wFLRGTuXMDHpz+obpkcE/XqvytGRpnXNnpfC447gpEjE+Sj/SdO0AFU8h0KRqtD5OqLi+mZlhxuSktLcfr0aVx9dRubNix2Amsyhx/b+7ALlIxWgNFZxqDMK6gp//VXnK2qd0AAqUszpKoLKeTXXrvPsWJcIig92APV1VaHYx5aYif6oqzKG3PmyK3F/QHUIjh4d/3bBsXHU2RApab1/PnzKCwslE81e/tt2XYtbdu2dZzRqlDWodmjFVCd59DQUDRv3rzh0SONaLWwN9hldQioKN926tSpzmnQIDSUeQHKoKiqqpJXRb3hBiYBovj4eGRkZKBMugGy8PDDZJDIsG7dOkRHR8unVwvExZFznwHBuNalkMoYaS0uLkZWVpb9mUdmnv38/BAbG+s4o1Vh3QbI+bR9+/a6XrWyqNRjXnHFFQDQcGXwv/8GGO7nkpIS7NmzB0OHDrW+6O9PJQkSo3fcuHHgeR5btmxp2NgAytJau1axJEEz0vrnn2RcK9RMO0RBuKiI1jaFdTszM9M2C0+KRt1tmzZt3JFWNw1AYbGUNyjPAAi3PcCMGAFs3gwoLPhxcXHg+Uvw97etX9N1OP/5Z1lJ/JMnT6KiokLbaH3vPVmFYwB44QVvAOMBLAcZD/WsKzx+XLFfLaCxGHGc4oPerVs3lJaW1nmmlA7cmgdxmcOPtEejYBz4+WUiJiYGDz5oNZCLQPeH96Vim+/Gdg6FDWAz25ikaIgc2RpfG+Dr2xuffx5UZ8zc+/vvqAbw888/6/zBOpg0iTY2BebO3Qaer0VR0eA6J8jNNwP33mu54Nln607+iYnA228Lm/y2+vffFdO5MzmgJBuvEL1PTT0Fni/DpEkqkvqAjFEYg6CgIMcYrQqGgnCPt23b1qYNi112gsyzYtvSpwuod7O8CA6Ts4xBcEuxTQbHkQiTRg9VANi4MQpAKC5cOKDPabZhA9WYKSh6i6FIawQoG4JohrOYiS8RiWxkZso5sKgnamnptvq3DZo8WfNi1f6YCumEDjda69OjFdBUvnWIgrBGBE74HmQj1QBFxpKSZEsaHKYg/OSTVIKjgvAzZNPAT5+WVTiWEh8fD57n61ejOXOmrGFcW1uLDRs2YMSIEcp1hIwKxwIdO3ZEQUGBPjEcRqNVVjlY/DnJ89K+fXuXtF46ceIELly4oJxiDVD2ioLjYPDgwfDx8cFfDRVSnDRJUZlXzLZt21BTU2OvO8HzdXX+At26dYOfnx+2bt3asLEBpMw7YoSsMm9paSlKSkqsPYzl8PamFHAVh2iDjVaN+u+MjAx1o1Uj3b9t27Y4efKkc3rgmgC30epsFEQU5KJwZLS20HWAETb9J59MV46caPHjj7ILkVBsrmm05uZScbkMZFhNBFAEYF3d64LKMXOEwcdH7gsDQA96bm6u+mKk8KB369YNAOpquJQO3JoH8fJyqiGUaRskNQ4yMjLg6Rlrkw11AWHIQwt4odrGGE1MBKylDb1AwkKUIuzhoTMywyCikJgIHD58EZ6eu/Doo8Nt7qG27dohIiICu3fLi/A0GBllXikLF24C1QT2t/nYwoWW7+K772xSHmfPjkBsbCwmT95W//67OlA89Ago1Kh7eHigU6dOjjFao6KowboEQbRGNeIhjFH0rNi39OkCoAp9+x6XzSTQdJYJCo8a92JKSgqioqIQGBho/2bnzuIHQ5Fnn+UAdAVgVRpmcprl5zMp8wJktPr4RNu8FosMfInb0Q37ERMj58BqAg+Pdqip2Q7gJARhqwYLhUlQVRxVcOS1a9euLkLbYGbOBMTRFgtMRiugekDr3r079u7di4qKCtn3mdAwZoSIcIzSBhAVRdFumXuxTZs28PPza3h9MIOK9ZEjR8BxnLxx/c47mkrdQANEjlSUeQ8fPozz588rpwYLMCgcN2ic8fH0AGrUzSoa/wrrttACxSEGgoojb/t20mVQjbTedBOVnsgQEBCAwYMHN8xoZVy3AdKd8PT0tB9vhw52Csc+Pj7o1asXtm3bVv+xCQjKvDI15kL6sWqklaH9UseOHZGdnY3XXnsNK1eu1D/G55+niK4M58+fR3l5eYMirW3btkV5eblj0q1NiNtodTYK6UfSQ4yHRzUo7dOadlhWBnz0ZBYd0BTq/ISbu0OHdOXIiRYKm6KwgKsqBwP02UuXqKBNAu31I0EiQtYIHcfpqBstL7dT5hVz5swZlJeXq9cBKHhyO3XqBC8vr7qDhVJKr+ZBfNw4+v9LhE3kyMzMxIkTtoeg/eiOlsjDeoywM5Dff18Yky+oFo4cBDU1OiMzjD3WtmzZgpqaGgyTtoFYuRK9PTywq6EpRkqUltINrLIpFhf/A1JfDbJ5necth32ZBb1fv351m36DWb6cDuFnz8q+LaS0tmmjIHaksikKjcEbzPPPU19jEUlJwG23Ue3lhAlR6vfMM8+QKIgF+5R5SjU7efKQepqxEsI8M0RaFds7LFlCzjYNyAHUFcBBkOqx+HUVGEWOAEoP7tYtysa+FTInmngW1a0dUgdWbW1/UBp+d9AaWc02NoFx44CrrlK95Pjx4/Dy8pI3DoODZddtQYHSIXVR774LTJxo97Jmj1aBL79UrH0ePnw4ysvLG5byqKHMm5GRgWbNmiFAwWGKigpy2MoI1Hl7ezvmMM7QLzg5ORmtWrWSH6fCPEtp164dOI7TvwZdvEhnlM8/t3tLs55VPEbGSGu9jNaoKNLuaN5c9bKjR4/C19fX3rEXGwu8/LKdwnHnzp1RVlZW54RpECoG4fbt2xEcHKx+FquuJuEzBQN61KhROHz4cP3Le0pLaaNlWBM3btyInj172gt4+vvL7n0DBgzAnj17cElDFE2T9etJmffCBbu3HGW09u1LWTJPP/00pk2bpr9dT1QUYAmWSBGcZKpGa/fuqgrH/3YFYbfR6mxUNkXxIaa29hyoLtW2pvVUjg95MS1NkaUIN7dws9cLhU3xyJEjiI2NtVUzlkOlzxoZgX4ARgGgvoQcZ1+iqxphuHCBIsEKKRlCBEnVaJUoHAv4+vqiU6dOdUarUkovkxNARZlXoKioCEVFRSgpUV6ULl60NUSFMZGY4VAA+0GRa52RGT8/SnnUYMOGDfD29sYAqXf+5En0yslByvHjjutNJ0bDUKipqQHH7QYgHzXIzISsx75///7IyspyTC1uWho5TxQicCdPnkRQUBCaydxrAGQFPQQxri+/TMDZs2fxySfyBnF9EcTFLlzIAeCF7Ozm6s4OicKxvREVD8AL588fUk8zVqK6WlOZV2iToWi0fvyxTXaIkuI3OYC6AigHYN3ENTMnGNuM8DyP7OxsDBgQha++sgbcii016vdNL1L8TsLC+gEoBm3DhSDBMB1aBBcuaK43J06cQOvWreEloyStVI/psEOPijJvWloa4uLilHu0CowYAVjq8aQMGTIEHMfVGUb1IiGB0m8VovaaqXqCwvHvv8u+3b9/f+zdu7dhh3EGZ6OqYKJK3a0YPz8/DB48GElJSfoO4irR6s2bNyMuLk45Ui3AoHAsEB0djYCAAH0pmllZwO7digd9gcxMKt2xUQ4GyNh97jmK2IpwqBbBs88C8+bJvrV9+3b06dNH/XlZsIDuYxmDDQCuvvpqAMCaNWvqNz7GNVFwJNmlBguflbkP+/fvj6qqKuzdu7d+YxNQOUPkWs7QqkYrQ8/gESNG4OzZs/j0009RUlKif+6XLrUTwBNgMlpvvFFVm8RttLppGHfdRac+jQc9IkKoSbXNxQ+JVn+IGjVqhCZNmjTM06ewKTIpBwOq3inB4AoOjgeQhZiYajlNKQAqEQaNFC4huqVqtC5ebOMJFh9yT57shm3b9tuMWfdB/McfgdtukxXMEpNp+U82bWq7iXuhCr9hPG7E98jPt4+gJiYK++0QALUArKIFzJGZX3/VVOYFyGjt06ePfVpmSAh6gw7qexhq/XTDEPXg+XIA8vWiMTGw8dgLc/zQQ5Si9MYbDkg/Eu5FBeW/tLQ0tG7dWrl+q3lz8krcc0/dGK39O+n/9cgjRxomFnTttcDjj9f91RopzQb1PPVQd3YcOUJvWmrG7M+bPgA6wN9fWYxJFUGZd/x4xUtUBYQAm8OPmuL33LmAn19Xy4coRZgpc4JRbbSoqAilpaWIjo5GYiJpS/E8cLqM7uE+8cqHnzfeuBne3m/B2vN2rT4tAsa6YEXDf+JEYPt2u39DiDI1+NCTkkKRlaVL9Y1LzO7dige8sLAwdO3aFRs2bKj/GPv0oRYeCo5ZTaNVIzIzYMAAVFZWNuwwrpGSWVVVhePHj2uXJDAYhbNnz8apU6fwp0L6oiwqz8qBAwfQo0cP7X/jkUeY+7jVqz3Pl18CvXtr7s85OTmIlHPsKigcC2nEDlF9HzhQNnOitLQUBw8eVE8NBjQNriuuuALh4eH1TxFmzD7Zs2cPKisrMXjwYPkxytyHwv+twXWtKvciU6S1cWPg1lsBpZ7CFpo1a4arLHOlW0DqlVfsum0IMBmtGkRHR8PLy+u/bbRyHDea47gUjuNSOY57Sub9eI7jtnEcV8Fx3GOS99I5jjvEcdx+jsIk/y0UlHmlTJ9+2vIna6Q1IAB4fp4fRXVUPD9xcXENM1plNsXq6mqkpKSwGa3R0bTgKkCCOHEAqrFpUy6UnkdFZ6zGAVKItGrWR1mQHnJLS7uhsDAPn3xyRvvDSmzfTt4vjciHsCjNnh1rk4ZcDS9cgz/RxaLKKmdU0PfTD4A3hLpW6+uOoaamBvv27ZMXfAgOhqCh6ZS61poair4ppHAJNdYTJnSy+5rrDvuNGwM1NRJjsBsAX3zyybaGK8cWFZHYg1zkClajVREPD/q85T9gm3pLRmtFxaGG1TUeOGCjzGt1auSA2tVIX5dw4gR5/OtaudinzHt69oCHx+aGt/OQISkJ6NKFajHnz28vP2eiiLqa4ndiIvDJJ51AddAH2DMnBGVeacRFQpYljTpKKsTj50f3iIqhcPvtQfjqq0cRG9sWQDf4+v6tT4tAw5ipra3FiRMn5EWYAKBlS6BvX9ILEBEQEIDIyMiGH3oU1m1hXIoOCTHvvkulIQoMHz4cW7durX8ks6BAthYTIOecppKnxjwLh/EGpQg/8ghwyy2KbwvKwbIiTABzpBWgvpktW7bExx9/zD4+BadyaWkpUlNT65RrVZkwgam9lIDu9jzFxbTuajzPikYrALRqBbz1ls1LwcHBiImJcUykdc0acvRI2LNnD2pqaurSUhXRcKBwHIcrr7yy/k6e6GhS5pWWDUk4cICcgz179pQfo8x9GB4ejtatW2PVqlUNz0pQmOe8vDz4+PggLCxM+fN+ftR6SKPsAqAgSYsWLfQbrSrOxoyMDAQFBSFUpv1kHatXk8KxQq28l5cXWrVq9a9te6NptHIc5wngYwDXAOgE4EaO46Sr4wUADwB4C/IM53m+G8/zCrrx/2J++gn44AO7l6XpbEVFZDC1bBlum5Y6ndNMnYmLi2tYenBqKqXbiUhLS2NTDgZIXnzzZkCpjg9Wz1F6err+ulGNSOupU6fQokUL5bojgApDLekx9ofcbgCAl146YPcxZhjqjgBrpPXOO2NESr0AwKEIIQhGseha28/S9xYAoDeEulZdkZkbbqAFWYWMjAxUVFTI184EB6MpgFYREdi1axfjD9VBQgLJ6Y8YIfu2kA72xRcdsWiRQgr3okXA/v2SOfYB0BPV1dsaLnKjsuHwPK9ttAJUc/rddwCkc9wCQDMA+/QrQ4uR3ItWp0Y2gEiZ1yVIDrlyKfPPPnsPSksL8LlMHZsm69dTXY9M9ElwNpw5Q0br2bPt5VOZRRF1LcXvmTP90LlzPMaOPcCeOTF1KlOxuNCjNTraVogJHAfs34+fYh+1S1sWr/1z5tDz+9hjV4Hnt2DCBB3tRjQirbm5uSgvL1eOaJ47RxEoUf2ygEMUhBUiM9nZ2erjEqNR6zh8+HBUVFTUv2b98cepHlOGc+fOoby8XD21VUWZHrAexhsUQbrtNtWWNUKUT3Gv7t2b1hsG76a3tzfuuusurFq1qi6DSROF/fnw4cPgeR5du3aV+ZCEM2eYFI4FdLfnYRCzqq2tRW5urrzRqqJwnJCQ4JhI66RJsh0ShNIlxbZLAgyprb1790ZeXl79RHqCghSVecUcPHgQYWFh8sKYKgrHU6dOxdq1axEbG4t169bJXqOJiiNP6DChmAUlhiE9nuM4DBw4UL/RqjJGIbNDdYwMCsdt27ZtmMKxiWGJtPYBkMrzfBrP85UAlgCwWUF5nj/L8/wuKPVA+C/zww92C5FcOttXX5HRmpISbp+WqlH/FRsbi/T0dH19y8TIKPOqSujXAyEKmp6err9utLycPGcqRqtqajAA5OXVKRzbH3JpUz17dj/T/0UWhk0RoEXJx8cH4eHhdWnIguFahBCEwLoQSc8Y1lTrIQB2Izq6tC7LRFOJubaWUoM1DiKC91rWaA0LA8LD0atdO+cYrRokJyejRYsWCA0NVU7htiz29nPcH8BeZGQ0QGkUIGNLoe1AXl4eLl26pG20fvcdsGoVAOkccyCF6D3g+Xr2FK2tJeVE0b04ZgxA9fI5EIxWVWeHTDqh9Pt+8cX+GDZsGN566y396q3nz1OfWkmEDxA7lFJAGQVxKCujjC2b70IUaWVR/O7atSsOKvTeawiC0WoXaQWQtL8zbn20qc06P3Mm2SDSVGYPj6tQWVmJzZs3s//wmTMBuboxC4otgwQyM0nJU8ZYcIjRqpDur6poLEVDVVaoa/1HQaRPExVnI3OqnoZTuX///ti6dWv99meeJy0HlX9fVTkYIB0DWxl6VSZahLOYo8MdO9LGJLnPhIgbk9H67ruK66ocQnse5h6pDKn058+fR2VlpXKkVeFeTEhIwNGjR1EtaeWiC5l1W+DgwYNo1qwZwsPDZT4ogiENXIh+1itdPS2NUv0vXlS97ODBg7jiiivkDa9p0xTrUubOnYt169ahUaNGmD17tn6BIwB44QUqPZEhNzdXW/gNoLO2gmEtZeDAgcjIyGDXy1CZZ4ChHAFgEosaOXIkDh8+3PAaYRPCYrRGAhC7Ym3d9drwAP7iOG4Px3F3Kl3EcdydHMft5jhut67+W2ZHZlOUS2erqsoDxwXKix59+y3wwAOKPyIuLg7l5eX6+pYJlJUBs2cDmzbZvMysHAxQGmFCgp1iqRjBWy2kMeuqG73uOqCqStEjzmS0hoSQeuKlSzKH3DAAMfDx2a+vDY8YxkhramoqWrVqZSOoIESeixFcZ7QqGRWJicDSpUMBVOOLL8h7r1TPZ8PFi0zKf4LRKpu6160bcPo0+o4fj/T0dMennyxbRsq8ltRWaTbCpk1Hte/HVauAG29E22ipIdUfQAVatNjfsDG++KLifa6pHCwgOvzYZx30AnAEQJn+vp2A3TwL7WpIuKsUQBQ4joxAxWeOYVMESD0xJycH31mixsyo1EZZnQ3HAbSB0PvUTin7qado3eF5psyN9u3bIzs7mz317NprmVLEsrKy4OHhIXsY2vbQUowt+8HmtaoqexHXsjJg8eJB8PHxwSqLM4OJ996j7AkFNI1DlXlu27YtTp8+jYsaB1RVFOZZl9EaHFy3bssREhKCtm3b1t8hobJuC1kxmofI//0PeOIJxbcHDBiA06dP1y8bqqSERAT/9z/FSzZv3oz4+Ph6KRzL0b59e/j4+LB/p9HRpMwrEZ87cOAAGjVqxFa2ozHPUoR9gDlFmGF/FgwPOQdU3RhlnpXOnTujsrKyYU4elf1ZMAI1ERSOVZ6rbt26geO4+mlSrF9PRqeC0BNA0epDhw6hi1IXhZoaRYVjjuMwfPhwzJs3D0ePHsWPDOrwdkRHKyrzCpFWTRQUjuUYaCmLY86k0DiHMRmtDM6JmTNnIjAwEB/IZHle7rAYrXJxaj0uw4E8z/cApRffx3GcrGuY5/nPeJ7vxfN8L0XlzcuRwkKqsxMhn86WCp7XiNAoIKiF1StFJT+fUoMltRRHjhxBXFyctnIwAPj6kniLirfJ19cXLVu2rH/trYIyb1VVFbKysrSjW8IBrbBQ9pDLcd1QWblf1vhTUia1wddXtsG8lNTU1Lr5EhAiqJkBHXEOzTUjzwMHDoSnpyc2btyoWs9ng1C3JbkXBYT/46OPHoWHRzOsWqXslb/xxhvh7e2Nd999V/GaenHyJCnz+vjIZCPwOHnyKLy8NCL/aWnAkiWY/2ShZI6ptuyqqxwgxqT4o8lo1bwXGzeu23DEWQdET5DQ1n4A9ejbWVVlk5lhvT+EZzMSPA+otpcTPStqjBw5El26dMGnn36qY4BQvRetDqXjAGwPXzbfRePGdEjmOKbMjdatW9c1bgcYnulz5zTr3wB6ngXhCymTzi/AbHyk+W8AQHZ2IEaNGoWlS5eyRRhqasgYUeH48ePw8/NTjxwBsocfIWrXoB6jXbqQMSdSohbGFRgYqN5XW0C4R1TuxS5dutS/prCgQHFNZI60qigcAw2sa9VYtwsLC7FhwwaMVxE1Q3Ex1SEyiPABlCLcsWNHHDrEKLSWkSGrzHvgwAHliJsU4f/HaCwI7XmYjdbnnlNU5hUQjFbF50W0botxiIKwwjzX1NTg8OHDbEZrs2ayCsdiGjVqhPbt29cvAqdxLwIUlCgtLVUe76efUsRfJcAyadIkdOrUCa+88or+/reLF1NtsASe59kjrY0ba+59At27d0dAQAB+V1APtyMoiHrJzpxp91ZJSQkKCgq0lbYZnpXGjRtjxowZWLx4Mc6caYBWiwlhMVqzAYgLdqIAyPdfkYHn+VzL72cB/ApKN/7vUFBARdMi5O/JFAQEKKQA33MPIKfEZqF///7w8PDARkv6q+7xAXZjTE5OZqtnBawPkfBvKVBvwajFi8mCkSErKws1NTXakVbh/1dYKHvI9fPrBkpJtFqAZWUkaMgUyfztN+Dnn6EGz/NITU2VTddLTASuK/0et/FfaEaeGzVqhB49emDjxo2a9Xx1CIuwTIG/rWjRMdTWxsv/H2trgeuuQ8u//8b06dPx5Zdf4rxI8KfBFBSQFdGokYwxngugGHv2aERaLf+/iSMKJHPcEk2axKCysoFG66hRilZkWloaOI7TPuSGhtpsikLWAZ3thLolqyc8I0NHtLVJE0qPGjcOgPg+EKIsUZLXZWjalDzCs2er/iiO43D77bdj165d+g5sonmWMncu4O/PAzgJoK3d+3XjPnaM5sFSm6WVuSE4EtLS0lTVhusoLJR9VsQkJQE//XQYGRkJsoZvhX8oQqG+JgrExAA333wzcnNz2eq5jhwh0ZBff1W85ODBg+jcubNymwyVdXvYsGHw9PTEagXlXib69AFef93OQygoBzMZMxMmkMidylwkJCTgxIkTKC8v1z9Gmf1ZgEkUBaD0ahW13S5duiAwMLB+da0K+7PAypUrUV1djetUal5Z92cxV1xxBXuk9fPPKbVXNJ+1tbU4ePAgW2owYP3/MY7Rz88PrVq1YjdaBw0CrrxS9RJNo/Whh+iXhI4dOyIoKAh33XUXXn311fqltSrM88mTJ1FeXs5mtAIUONDIuOvZs2f9Iq0q67aAcM8ojpfBCeXh4YGnnnoKycnJ+mvVX3wR+OILu5fz8vLU1ejFSPZnNby9vXH33XcjKSmJzckjeEllxKCYnWSMCsf3338/Kisr8ZmCUvHlCovRugtAO47jWnEc5wNgGoDlLP84x3GBHMc1Ev4M4GoADpBZu4yQibTaR/qqAKRh5EiFB6qigk5iCjRu3Bjdu3dvmNEqGuOiRTU4eDAFK1Z0YkuT9fYmD5LGg15vo3XLFkWDkKlHK0BRUFHfUekht7y8GyjCZXt75uczRjIZyM3NRVlZmXKNmQ6GDh2KnTt3IipK/qBm5xipqaG0IZm6GFsD8RiAePn/o4cHqQfu34/HHnsM5eXl+lQmtRCeFY6TMapIVODCBY1Iq+iAJp3jq67qjy1bttS/9hugA6qk7YFAWloaoqKi4Ovrq/5vhIZSRFQCzVlLkCCTrTqz7jRhm38TEEdabV+XgeNsFI7VSExMhLe3N7766iv2QXXqBEyfLvvvJyYCb755BsAlAPbPdN24T52iyAljyqXYaGXKTlCJwAE0F3fcUYWqqhQACbKGb9tejRHKFdp8ztvbvpSX4yg4Pm7cOISEhGDRokXa/yFh3VaojeJ5Hvv27UP37t2V/w1vb5pnGUOhcePG6Nu3b8OM1gsXZKMBzO1uACAighSOVZ6phIQE1NbW6lOTFXj8cboXZWASRQGADz9UdKoCpObZp08fp0Raf/vtN4SHh6srywrzzHgQB8jQzsnJwQWVVNA6hGdF9D1lZGSgpKSE3WhlMGak6FIQXrWKVNFVyMnJgYeHB1ooCQ1df71sOr6/vz82bNiAAQMG4LnnnsNHH7FlV9jQujXw999kXIvQNAKlxMcD8+erXtKjRw9kZ2fj7Fmd/cBF+7MSBw8eBMdxygEPRueE0C5Hd/RawQklRJZlFY2lNG6sy8EzZ84cBAcH46mn7Bqr2HPyJM2PTFaicDbWNFq9vUlQc9Qo1cs6dOiAF154AYMk99TljqbRyvN8NYDZAFaDTo4/8Dx/hOO4uzmOuxsAOI5rwXFcNoBHADzLcVw2x3HBoP4tmzmOOwBgJ4AVPM/rKNr5F5CVBbz9ts1L0khfy5ZpAGpwww0KG3loqOZDNHToUGzbtk2/XLgkAkdRiGwAFQDas9fVMTzocXFxyMrK0i9YIGP4CzAbrYMHk/GrkDrTsmU3y5/2Mw3JxqjieaqBW7xY9TMnLJumotH66aeqwipihg0bhsrKStx883Y2Jebu3SkFXGYBs/5fzlt+xUteF2HxQnbq1AlXX301vv32W6bxMiHacOyNKmp3ExXFFmmVO/wMHToUOTk57KqYUnheNQJ38uRJ7dRggOrTZJT9yJnFgVKEbY1WZkfJihXkoLG0B7I6yIRIa0s2xelXXyVlWRnEqbW9ejVFt27jsWjRIlRKizWVuOkmodBWlp490wEAvr5xNq/bjFtnZKZFixbw8/PDqVOntLMTeF41AgfQXJSXpwKohNCqSDpHbXqFIty30Caj46uvSPtIfO7jefo6fv7ZD5MnT8Yvv/yi3UpIw5jJysrChQsXtHtk7twJPPOM7FujRo3C7t27659Ncf/9gOSQWFlZiVOnTrEbrRcu0H1oWeflaFB65h130NotA1N9GcCUTjhgwADs379ff4solUhrRUUF/vzzT4wfP145mi7AcIYQIxhJTNEjmf1ZiOQxG1vdu5NAnZYegIiOHTsiJSVFO7LJ89QTWmE9E8jJyUF4eLhsqj8AimAqRCh79uyJ5cuXY/To0Xj22WfrBNqYadSIIsGSdm8HDx6Eh4cHuyAmw71YbzEmjTURoPG2bdvWvse7eHzCv6VCTEwMAgMD9ZW8CfuzzJq4d+9ecBzH5kQZOxaYNYv5x4aFhWHOnDlYuXKldgT70CFab2UcBrpq/QGA4Rz94osvYvjw4Wz/3mUCU59WnudX8jzfnuf5NjzPz7W8tpDn+YWWP5/meT6K5/lgnucbW/5cbFEc7mr51Vn47H8KHx/yckoQR4EWLqSbVTF1oXFjoLRUNjojMGzYMFRUVGDHjh36xldWRrVblsVozhzg0iVBUKBN3SWafb9HjyYVQRXi4uJQXV2N3Fzm7HJCZbE8deoUPD09lcUTNBAO4Lm5cQBCIDZaAwKUBRdtjKrycjIWNPqUaBqtZ8+SIJbKPAvk5g4C4IF58zbA35/GyaTELIP1/yLUNcdLXhdhOfwkJQG7dl2LtLQ0REamNbz/qfAD+1D1gH02wjEAjTF/voaCokXhWG5BHzZsGADUv09dWRnNjYKhkJaWpi3CBCh6qgVnFqUIHwNgK4LD1Abn3Dny4vr52fybQUE5AJohNtaX7f5YuhSQqdORS609ePB2nDt3Dl9rtFNiRUiTevHFOOU6VZ0pjxzHoVWrVkhLS9NWG66poZIMld7TNBeCkZQged1CaCi8L11E+okqm7TllSvpuxMjGLzTpk1DaWmpthquRtqocCBVjbQCFPWW1JwKjB49GjzPY41MjRgTMut2Wloaamtr2Q9mZ8+Sla+SJti2bVv4+PjoN1qrq8m5U1Ji9xbP80hPT2czWkNDKZ1eZd3u378/ampq9Pe37tqVnJkyYkZbt25FSUmJej2rgI46PQB1QjpMKcIyWQl///03goKCtJ0mAi1a0MOhQ88kPj4ely5dqhPMUkRYtzUMLtUerQCwcCHQq5fiPHMch48//hjV1dV45JFHtIZvS0oKdZqQpLgfPHgQHTp0gJ9lPdeEwTkhrAm678X581XFNgGqY1YUYRLGB2jei4KhLvRmZ0Jlnvfs2YMOHTqwabRMmkQqxDqYMmUKAIbvVMXZmJKSgrCwMDRVWI9t6NULmDxZ1xj/LTAZrW7qSX4+1YVptAdJsYggKW7kDA/64MGDwXGc/gP5jTfSg27ZFGn9F4xWa01Zfr5GtPXzz1UVFAHbtje6UIm0Jicno3Xr1sreUYGCAlI4FkUGbWs5OVC/1n0ArIfk999n6CmrcYAUOHHiBHx8fOx7OgowLuhJScBDD4WA+rWuQn4+7XWLFqkoMSclkTKvjKffaiAKqVbxitG4s5WNsfmPQkyfDhQUjAQA5OauqXf6qg3z5wPffw/APhvB3z8DsbGtMH26Rqpe+/bA6dN1NZ1i4uPj0bx58/obrSp1wRcvXsTp06fZIq0bNtBzJ3O4oHNbL1Cquq0nnKHNouy9mJgIDBmSje7do9j7lCocfuRSaysqRsPXdzDmzJmDQpaD8ZAhqqq3wvpw332xynWq9UgnbN26NdLS0rTVhr28qLe2QgQOEObiMGgLjZe8buGBB8jokqxNapFeIWqoqUQqU9YhZt++ffDw8NCOdC1bVtczWErPnj0RFhZW/xRhmXVbSOdkNloZIuqCcJBuo/XMGVKkl8mQOXz4MAoLC9nTCQFVYZR+lnYuuutaW7WiTUpmzREyRoR7RpWPPyaRHkYiIiLQpEkT9kiraHw8z2P16tUYMWIEfGTaWslSXU0ifDrOBoJYmGaKsMazIpCTk6Pu/GaY59atW+Pee+/Fr7/+ihIZZ4giK1dSb2hJphyzcrB4jBprYkhICLp27arfGRUToyo4tn37dqSmpqpH9lq2BF56SbEThJhOnTrpi7SqGIR79+5ld6AICsc6apOjo6MRFBSkbWSrnBVTUlLYam4B2rB07H3/JtxGqzM5fZo2C5XUJoBu1mbNmikLPiQkKNbdCDRu3BjdunWr34FcpMxLh66TAHwh7WxUnzpOMQcOkNd66NB0fS1l/Pyo15wEnuexadOmOtlxVQICSLwky9q9yf4A3g3AQcTE1NQdkpl6ympsikI09803T4Dn22DJEgVVUsaDuHXc14JKzs9op48eP06HAhmPrfB/bNQoGYAvYmJiZaNxSUnAH6nxyK4Wop0dQMI+a+pd56uGOBuhQ4dcJCQwqI2qwHEchg4dio0bN9a/Z+KYMbIpbEIUnWnTyc4Gliypa+0j5aWXhPo0a9YEU0ovQPcOx9nVOmpGEaQoHH7kDS4OFRXvIz8/Hy+99JL2v33+vKoyb3p6OsLCwtBIRfCjIUbrTTfx6s90dbV9XxoRSUlCq8LDIMcePVN2cxQSUqdwLEYt0tu8eXMEBQVpG629elE9pkLrhH379qFDhw7KbVAEvvwSeOst2bc8PT0xduxY/Pjjj/VLvZUxWjVr3qQwznNCQgK72q2AygFSONCPHDlS+99hMKybNGmCDh066K9rTUsDFNI4hRRUJhXmIUMoBZcRjuPQpUsXtkjrvHk2BvGJEyeQnp6OURo1dzZUV5NT1eK0ZIHZaFVxNorRXCMZSxLGjBmD6upqfb2DZdbt8vJynDp1ij01GGCOqI8dOxZbtmxBgY6UcXzzDTlcFXjnnXfqVGsVCQ4Gnn9e1fgV6Ny5M/Ly8tjHGB5OZ21L1FPg7NmzyM7OZnNAAeTEatJEs6e9GKFPMpPRynGy67Yuo1Vn5sS/CbfR6kwYI3CawhTDhlEYTSN15qqrrsKWLVtQLPTHY+GLL+p6wFoPY6kAWkN6e6hm4Tz+uOqmmJQEPP98nYqKvh6Ua9fK1sAlJycjPz8fQ1jqQH19qf+W6EG3//90A1CGzEzbA6NmT1lmZd5UVFW1U/5/M26K1nGPBXWf+lPh/yOioIA2RAVjITERaNduAwYN6o2MDE/ZaNycOcDtNZ/hRiyxvMKBtNXWAqhhS19VY9AgxbYEubm57EbXtGnAggWybwUEDLX01jylvxdvVBSlgcuoUOqqR9GY53vuaYbmzdsgIGC7/pTvggLaECU1btnZ2fpS6BUUFJUMriZNuiMgYDree+9zxMbW/r+98w6Povr6+HfSC4SEkBBqGr0m9CqEKkhRigJBEKUoNuS1YW+IXVGwIIJSLIiiiCJFkBJagCSEFmpCJxASEkhIve8fZ2fr7O603QR/9/M8eSCzM7Mnc+/ce889zfFzdRIblZWV5by2o58fuXXOmuX4PDNiYmJQUFCAa9euOX6nd+2i8WLjRpt7iO8z5eI6CNE1ODRUoo1OnQJeesnGeuTI0isIAmJjY53XQO7ZE3jvPbvvc0pKijzLgpNMme+++y6CgoIwYsQIXJdZjsSIRDunpqaiSZMm9mPerBHHbSdjYqtWrXD27FllMjrYbNywYQOaNm3qvPwEAAwYAOzc6bTkWZcuXbBnzx758gHk6tOnj+RHYgymLGtmejqwWlb+TCOdOnXC3r17nZfz6N3bIhfD+vXrAUCZ0urnRz8KlKhatWohNDRUF0trYWEhcnNzHc8xMjdQunfvDj8/P2WWTHF+Nhu3xTAJWd47Ig8/TDWsnTBkyBCUl5cr86J4/nm7E+bp06fxyy+/YNq0ac5dcC9elIzptEbc2JLtIuzlRdYBq3ZOSSHvOdmWVhUbogBZho9I5KqwIC/Ppp0BID8/H5cuXZKvtCqMUf8vwZVWV2I2WDqqCyh7h8WJdWj48OEoLS3FWgfp923YsgVYvdpqMXYCUuUmHM7fpaUOd6YocYkfKE42DYD95DKy6qICxp1MWUorYJMsyvbviQMA1KqVKu9+IoyRW6pVEgXA3CpaAXquje1bJevWBbp2tXEntMYkdxwo2+yfVsclyMvDDZ8Qu8/14sWL2L9/PwYPHmz3FtJKaX8AeQD2ynNfdcS+fZITRUlJCbKzs+VZFACyKEskRFi+HPjpp96G3/5VtnHiBFFpta7BK4mMSbFfv84ICdltf6PEHm3bktJuRkFBAXJycuQtwEVq1pSMC5ZSuLy9SX+8ebMLgJs4c+aC4+fqwN0fIEurU6UVoIzlcsqmGDhzhpK11ap1yvGGhYPMvKb3+RbofW5lFMWmjS5epAdm6Bsizrw3GjVq5FxpvXqV6m9KcOXKFZw7d855PCvgNIFenTp1sHLlSpw6dQpvO6lzacPLL9vEXaWmpsrPKCtTRsCU8CfZSSiOBXbcCYuLi7FlyxZ5VlaAxv0uXUi5diLj5cuXccVJSRILHGzwnDt3Tv5G3sKFwP33y/9eUFbU+Ph43Hvvvdi2bZv9E9essfAmW7duHWJjY+XF95ujoNSISKNGjZwn1mvdmjagHFjanJa7AWQrM35+fujZs6cypVViTBTDJGSNhSKDB5ObsRM6deqEWrVqYc2aNfLv7aAvfvrpp/Dw8MBjTsqkAaB2kOGWJVqYZbsIHz5MIUZW75cY3x8XFyfvPipKRAEk7/nz5x1vnL3/vs18AJhCBLml1TlcaXUlhk71+9YQu3UBr1+/jsuXLzvurMeO0UpxxQqHX9elSxeEh4fjN5lFxAEYByLTYoyB3IMtJxyn7onBwbSIshMHYFJ4ugLYYfgeW0XIOtHLpaxbqDVhMLbM/N3mnlu3bkXdunXl70Ra7U7ZLsBbAPBG166p8u4n0rMnJVKQWIyZ/r7zoIVuY6vjZsTHAzt2AE52BE1yCyBr63r4+5c4bJ9zB/Nw8mqw3dqUf/9NSb0dKa0NGwLjsRS70QkeENu5LwAPeHn9Js991R63btGPxKR46dIlAE4WFObYWfxQkrEWoIRbpNQqcmv+6SegQQPJxjt27BgaNGjg3B0TkDUpdunSBefPn1eehfKhhyhhiBnihNjMQdF5Gz76iNyYrZBSuIKCRG9a0cp83OK5mm9CNY20386AKQGOrIXa++8Dn38u689Zvhz44gtxnDjleMPCgeeEqemPgjaiWlkdN8OBRd2RpTc2NhanTp1ynBX1wQfJnVIC0bIgS2kNCXE4bgNkOVK8CAeA6dMBM8Xv+vXrOH36tPzFo8jmzXY9MER69eoFPz8//P677TxhFzueUElJSSgqKsKAAQPk3aeggNJCZ2Q4PE2MPVUUp+eg9JLTGExzZLSzNUFBQVi7di0aNGiAiRMnStfBvXWL8gf8SN43BQUF2Lx5s/xnZy2jQkVBdPl3SHAwecdI1MYUEcdZh3NM8+bk8SbDtb1///44fPiw/KSTEgqh7MoI5uTkAHv30sDiAE9PTwwaNAhr166VV1f21i0qvSgxJubl5WHhwoUYM2aMvP4os6SM4gzC+/ZRZl4rpTE5ORmxsbEIdhLTbERhZnqR5oZEpA6trb6+kh6TipXW/v0pWaCW8n23KVxpdSWGzLyvfhJity6grMQU1atTph0nL5GnpyeGDh2Kv/76S375CcMOn2nRdQlAIcwtrbLcE8UX3c4uk8nI0w3AZQCZVscJ6zjTYORhYMVabPjOcvBnjGHr1q3o1auXvCL1ANCvn0Ushe0C3AcNG7ZAaWmqvPvJwPT3ibtrjayOK8dcboprzcfjj2922D4bTkRjN+tocUzMCh0VBTz44Fp4etZFerr9WJPZs4EI72vohGTUgNjOYfD2HgY/v68xYoRpUSPXWm7EQRIFcRdctqXVzqRIfVwAJc45anVcBpcvkyInoZgqqj1ZsyZZZxwsLMTELYqLq0tMYuIYo0hpdfBOWStcplKOYlZsiu89c8Z2E+rcmXJ84fUYNuZ3krz3lStXUFRUJC9r62+/Oc1mKUIbFuLijxa5djcsHLgTmt5bU9Iyy+NmqHQzi42NRUlJibHfS+LA6qFYaQUcJpcBKPN2amqqvLqdAC1wDx8W400AmDLRKlZamzaV9GIxJzAwEAMHDsRvv/0mP169SxfKzFunjsXhDRs2wMvLy5ht3CkFBbSJ4CSfhKrSPA5KbCmytMpIIiRFrVq18NVXX+H06dN4//33kZubaxlvbaX4L1iwADdv3sTEiRMVfY9RRhVKa1ZWFkodZdw/eJA2/B2cIyoaDsfI0FDKLSJjHhKt9BslQgwk+fRTiySRACmtPj4+qGPVPx2ybBnQsaOsMWfIkCG4du0atm/f7vy+DsbEr7/+Gjdu3JCfMVmmRV1xBmGJTSjGGJKSkuTlPRHR4B4MOHFn/uQTqrFqRUZGBjw8POR7JwwZQlZlBZ5G/xW40upKpk0DSktx4Jz0Dt+ZM8APP/wAb29vdO3a1f59FLxEd999N/Lz8+UnZDJMiqZFl2Xm4MhIme6JTqxHJuug+HfukLTeWisQIaD7nbxmWzrhwoUL8l2DAYoPskplbr0AT0iIQ2pqqvx7AqRBJiRIKiGmv1tMEtLavtW6pIRcmWRYj0S5b90aiJo1ayIra7HD8x+6MRfTsMDmeE4OkJVVCmA9yssHYdo0wa6CmZgI3DMpGAAQAqo/uWwZsG7dE7hxIwc/GnbbpcqiOHXDdRD/Le5Wa7W0mvq4pdIqewPBjmLNGFOmtNapQwrw2LF2T2nbti18fX2VK63x8TjVc4LFhsHKlRnw9PRU5q63axfVU5VhKTA9vwagBG7HjcetN6EKEYjpZZ9h8g+2ccGAKY5LlqVVgWWGxpVqoNLhGVbHrXCwQDO9z8dAGyCN7L/PKhc/oou5w2RMDixwKSkpiIqKsp/Yz5wHH6T4MidWiISEBGPiO1mcOkUWKTP3Q3FcVewe/NdflHvBCffccw/OnTsnv5RHkyY0MFnF1+7duxdt27Z1nAjMHJntXKdOHYSEhChTWu1sThQVFeHatWvKLK0yZJQiISEBo0ePxuzZsxEREYFWrVohh+KILMbE4uJifPTRR0hISEDnzp3t3s8u778PvPOOoktiYmJQXl6Os2YJFm345RdymXWwwD948CBq1KjheGOUMSpJ5yxJGsgVPDw83OjB5JToaEq4aYZYcslpDV5zFIw5gwcPRkBAAJbLiY+x431SWlqKTz/9FAkJCfI2ycR7yBy3W7ZsifT0dHkbUaKMZmEdJ0+eRHZ2tjKlNTQUeO01h+7kUkRHR8PX19expXXhQslSchkZGcbrZVFRQc9QRnnE/xpcaXU1goCGkdKDZf36N7B48WKMGjUKtWs7qD/p50f1XmUMRH379kVgYCB+NbNAOLR6+fsDdeuaLcbEWKpY+RlLAaBZM9qFtJMUQrQONmzYCkA1VK++U9J6a61ABCMPAOATHmxxXKxH261bN5kCyiMuLg6XLl0yuqTK4sgRcsmRmFzEvzswMB1AOCIjw+1brb29yRVcQUYjX19fjB8/HqtWrTItJCRwrJjtAnAdwCCn7rLd7qJJ6+TeXONmRu/evdGqVSt8+OGHmDdvHmbO3GjXs8AuXl7AoEGS9QgVW1qbNJHcDTf18WYALgDIV9bHc3MpeNEq5vjq1avIy8uTr7TKwMfHB+3bt1estBaeuYptO70tNgzWrDmKsLAY+eUnAFKqf/iB4jKdYHquHqCwguPG52rdlb1QCm+U2O3iiuK4FFhmTP2/PSjjtvVxM7p3Jzczidhy0/t8HEADREb623+f/f1lj9vmiJsLDuNaHVjg9u/fL38BWb06uas5WRh37twZfn5+2Lx5s7z7SmxCpaamIiwsTJnlCKCMsjLiaYcOHQpPT0+sWrVK3n2PHwfS0mwOHzlyRFnGVrGdnfRFQRDQqlUrZUrrJ58A//d/NodlxWCaozJOT+TDDz9Ehw4dMHLkSBQXF5tiIc3aecmSJbhw4QJmKUiOZkG3bmQlVIAYGuTQRTgvj/q5g1wRBw8eRKtWrZx7bfXrR4qHEzw8PDB48GCsXbvWsRVYZOFCCg0y4/Tp08pcgwFFrq3VqlXDiBEjsGLFCtyyKrVjQ6NGFLdsFT70999/49y5c3jqqafky6ggHrN9+/a4fPmy400Jkdxcm3YWrcg9evSQL5+fHxk3OnSQfw3I07Fp06aOLa128jkoyhwM0GZgzZqAnOze/zG40upK5s8HnnvObrbIfv2WIz8/33nwuiDY3Z2yVkh//dUfQ4YMwa+//oolS8pQqxbpknatXnv2APPmGRdjQUEnAHjaLXtil86dKd7DXg1S0L2ysrzQp08nNG68U/Le1s9KVFrHTg+2OO/IkSPGQUI2r79Og68DRNe1tLQ0+S6uDhaQAP3dzZsfQL9+bRxbrR20syMeeughlJSUYJmdeosAsJ/F4RnvT+x8uglkNSLrl0OdWWInVxAEzJw5E4cOHcLjjz+O7OyRoPhdSxzet3FjsqgY3GLNuXDhAry9vREaGurgBmZ89JHkbqbYx8PCyAUsIiJDWR+3Y/VQlDlY5MEHgQ8/dHhKx44dkZKSIi/mSCQvF1fLgy0OlZcfxfXrClyDAUWLH0t39cbw9j5ufK7WSmF/bEAJfDGs9m6pWxmVVlnuwQoWP6ZxpQuAIwCu29+w6NfP+IE4BggCrYUEgTZfIiKOoV+/Js7f55wcWQqXOfXr14e3t7dzS6tEXywoKMDx48flK63nz1PCJCcZWH19fdGtWzdlHjyAxQJNTMIkO5xDROaYWLNmTfTq1Ut+XOvbb9vUcy4oKMD58+eVu9LL7Iui0irbhblfP1LmrBCVVtmW1p49KcOxkr/LjAYNGiApKQnLly9HvXr1THkzzNp5/vz5iI+PR79+/VR9B44cke3uLyJLaXXglQCQp8yhQ4ec17tV0M4AbaLk5eXJq8375JNkETZDdmy/OQq9OyZMmIDr1687T8jk7U0DoVWpll27dsHLy0tZmz/wAFkyZSBa7EUjhUMkFMLt27cjJCRE2fsMULlKGRu21jitLSsxbpeXl+P48ePK1rIqvXj+C3Cl1ZVs3AisXWs3W+T+/V8gLi7OsWuwyJQpFmnlAftumBER9+HKlSuYOnULpIxvUlavpKQkPP10Hdy4MQexsVHIyvKWv5g3R8Zk3K1bN6SlpeGLL76w2RW3flZh4R7Ij2iCOxNrWZx35MgRxMTEyHenACgb6qlTDmMJRde1xYtT5bu4OinhUV5ejoMHD6J169bOZVSRFa5Nmzbo2LEjFi1aJH1CSQlqnklD4rACiz5o0gH/BRAPIBiAE6tsRARlOLZ67t7eD8DP7xCAHwHkA7B1i1Ibx3vhwgXUrVtXmZuUHRITga1baQJ7772jyvp4hw7AyJEALDeLhg8nd1hFSuuOHbRh5IC4uDgUFhY6r9kpUlKCAFaIXJj3xXIAx1FUpGBCBBS7E4ru6k8/3RgeHicxdiy9Y9abUKK7/4MzgyXvk5mZiZCQENSQyNwrKWNFhdOkI6J8CxYA4eGdATCEhyfb37C4cgUoKLAqV2XKYZOVxXDy5DFs29bYeay2wgzHAO3Yx8TE2Le0MkYP1krhAmizDVBQ3iEnB3jrLYr7c0JCQgLS0tIcenQYsVJay8vLcejQIeWuweI98vJktXOPHj1w5MgR55YjQHLcFuO/xaQqspGpWLdq1QrXr193HK8sUlZGFhWJ3T5ZiYPMqVmTNgTllhqygyAIuPvuu7Fu3Trk5eXh07Q0XPzxRxxkDGlpaZg0aZLyTQmR77+nbNMy2lmkXr168PHxcW5pdTA/X7p0CdeuXXOutAKKNpX79+8PHx8f5yWDSkpoUWYm440bN3D16lX1llaZ43afPn1Qt25dLF261PGJKSkUQymR5KhVq1bwd5I524J+/WRnshbDZGQprV9+SXKasX37dnTv3l352qF3b2DGDGXXgLIyZ2VlGeu2WyC2s5ViferUKRQVFcnrfyIqk0X9F+BKqysxmxStYyd79jyDtLQ0TJgwQd4g/+abNiss63gxgH7/9dc7IQjVUFz8k93bnTkDyqAyeDCwbh2WLyer7/PPP48FC2xjH51y4QKtTmXEHvXq1Qvl5eWYPn06Ro8ebZMi3PxZLbk8EEEXM2wspEePHlW3sGCMEmfYPSUEkZGR+OOPVPkurk5KeJw8eRK3bt0ylmVwKqOKgWjkyJE4cOCAdCFuwwTWtneIRR+cOxfw978FYCeA3gBkZIlu0oQULit3m5deEgyZeUcCqAXAsu85ve/ChaTVGhK9mCuFP/98Hj4+Ml2DAdqx7tTJbkmQ2NhYeHl5Oa/vZ81jjwEff2yzWZSTcwyAF3bsiJJ/LxntbG71l4WhnfMMmw9EFoBi1KypcKdZpTth48aNUVxcbHTnst6EiqlJMg6bKL2IPHjwoPwd5zfeoL9Z5oIkMRHIyKAEUE88sdv+hsXo0cCQIZLjK5EDIA/FxU2cx2rPm0eWf4XExsba36wQBFpQSWQPVpSECVC0+OljqBe6adMm5/e1cg8+f/48iouLlVkTzGV0Mm6LNGnSBIwx5yWDRBmtxm3VSuvq1TSgOkFRBuFr12hjQqK+qmL34Fu3KAFMerrTU51xzz33oKioCJ06dcKTL7yAqcuW4fvVq+Hp6Yn7ZJRbsYu4CSWjnUU8PT0RFRWlydIqumvLUhoUbCpXr14dvXv3tqu0pqSk4MEHH8QpMYeGmdKqKnMwQAPt0qWy3aw9PT0xZswYrF27FjfMkqbZkJREIRPFxcZDjDHs3bsXHRW6dCM3lzL9ynCb9vHxQXx8vDyl1dfXfCceV65cQUZGhrJ4VhEVScEAYPTo0RAEAT/88IPth9ev01xltYGSbngnZRk1zOUDuKWVozMOBksxNqhvX+mEJDZUVFhkYgTsu1ueO+cPxoYB+BWA9MDQsCGo1t/atcCVK1i3bh369OmD2bNnGxcniggKkpXhePly4KGH+gLYhVq1fkJ5ebniUgpLlpTh0KFjWL26mbzMtCIyF+Jk4UqV/EzymTdq5LBMjZg1U5bS2rs3lb5RiGjBSJdalNhJopCYCDz11C4AxQB6y8sSbQfTc/ECMArAagA3AdA84vS+ly8DZ8/ihz+q2bi037p1AadO1ZPfztevA8nJ5mltLfD29kZsbKxypdXgRWCrzBwHEINXXnFcX9cCGYufFi1awNvbG6mpqfJc1T09kdH/URzxNe8/9Dc+9pgK92AnGVulaNyYMgib7zSbb0K9OTOPDpqNiyYX3Aps25aCatVkWglVWHSCg4PRrFkzx7HChs1G++7sYiZwBzWXRf7801gORAmNGjXCiRMnUCZRKxdFReRKKaFR79+/H+Hh4fLjRhUsfjp16oTg4GB5dcATEsjyYRhzVNWcFFGgWItKcYaT8jMAJC1wR44cgZeXl/Iao02akBeKE1oayqXIimt1UHrp3LlzCAoKkp8sqrQUmDQJkJsYyAF33HEHQkJCcPz4cfTt1Alr1qzBZ599hv79+yNcxZhhROVC3KFXAgAsWkRZou0gtkVLGaVslG4qDx06FMeOHZNs708++QSLFy9Gm4QE/AhYjImq35egIJo8Fbg1DRo0CKWlpY5d/yXc/U+dOoXc3FzlSuuqVeS1JLMcUOfOnbFv3z7nscHvvEN5GAzs3LkTANQprSpqBgPkrt+zZ0/88MMPtiEAYWH0Hk6bZnE4PT0dgiDI638iXGnluAQHbimbNm1CrVq15LsE3H+/jTJjb1xq2BAIC7sXZBGwXWAYrV6GwfdEURFOnTqFgQMHypNFisBAwNPT4YAuWqjOnBEAdMbVqyMA1MBnn/1l/76ffGIR/L98OTBt2mmQMt5cXmZaEZmLH7JSZEBUusyRfOYLFwIff2z3funp6fDw8JC3ez9nDvDuu87Ps0JUiA9IBeY7yIbq7f0vPDw8kJvbU16WaIAU9Pfftzhk+VzuA5VNojgZqfJ+UjKW+QZg8nQfCZf28ygvr4vx42WWz5HhItWsWTPJLH8OlcPGjYFHH5VQZk4BiFGSP0vW4sfHxwfNmzfHX3/JdFUPDUXT9fPw4DfdjZbNkBBSWh9/XKGFq1o12kiYMkXRZVJKqwW5uTQAGZJCWbrgngJjBdi6tZ289zktjTIwy7GqmdGlSxfs3r3bflyhYbPR/rpP/NvIHdxhu6v0nOjatStu3ryJffv22X6Yng60aEH1S61ISUlBu3bt5LtoVqtG47aMxY+XlxcGDBiAtWvXOo/JbNGCFmfe3gBMliNVSuvo0dQXZSzERRd9WUqrHUtro0aN4G2QWzYbNwJffOH0tNDQUNSpU0ee94SDjOqKarQCitrZGd7e3li4cCFWrlyJv7p1Q2NBwI0bN5CoKp7IDJUuj05rtcbGOozlPXjwIGrXro0wifqZNrz+OpWnkcno0aNRo0YNTJs2zWIDqqKiAn///TcGDBiA1jExmAbgmlkCIdWWVoA8oRRsyPbo0QP+/v5Yt26d/ZPy8izGbYBcgwGgg8KERUq9eDp37oyioiIcOHAAO3bskN7IA6jqwvr1xl8Vh0pYy6jS9XbcuHE4evSo8fvPnj2LpUuXUnJPDw+bhGDp6emIjY2VV+NdpFo1igvWORHp7QBXWl1JYKBNDTiA3Co2b96MhIQE+b72Ei+RvQRPs2cD778/GILQEIClcmFh9TJMYOsNA5wmpVVMIuRgUrS1UHkBGIikJFoESSoMBw9aZHikeouiskFKoFNrh0hsLP3hTuJ6yC2TwdfXcndUUaZZMw4cOIAmTZooi/tQSJ06dVCrVi1ppdXfH7jzTskkWf/++y/i4+PlF94GgLNnKZOgGZZ9sSeAMAC0GSGrffLycLUsWMJ4VGD4ITc4WZsUMibFZs2a4cSJEygtLbVItnP//Q6Uw+xswNtbYu18GkCMspjd2FhAxqIzLi4OBw/KdFUvLQVKSiwsm6NHZyA0NBS1atWCO6hbty78/f2xZcsW6QRSCQnAc88Zf7UcE/YDAEpK2sl7n69dIyumot0CWgRduXLFuDC0weDuLzW+EscAeAKIAuBEl1IRow6YXHH/+ecf2w/tKDOFhYU4dOiQskWajHHbnEGDBuHSpUvOy4IdOWIRJytajhqqCWyvVo2s/jLmyqCgINSpU0ee0rpgAfDooxaHjhw5ojxpC0AJhF55RdapcXFx8pRWB7Wrz507p0xpFZMI6RQDN2LECIwcORI++flYEBqKvn374u6779Z2U5UhCTExMcjLy5MOjQFImUlOlv4MpLTKtnJ16iSZLNAetWvXxueff44dO3bgHbNyPikpKcjOzsb48eOx4LvvUCAI+MCsVNOpU6cQEBAgT5G2ZvhwRYq1n58fevfu7Vhpldjg2bt3L/z8/JTFYgKK427FZEwDBgxA9+7dcffdd0u7MluFaR08eBAxMTEIVBPHrXLcBoBRo0bBy8sLzz33HH766Se0b98eEyZMQL169fBiXJwpSYKB9PR0Za7BAL3Pr77KlVaOzhw+TJYzK06ePImzZ88qc8MVXyKzHW57CZ4SE4GJE72RmDgTwHYAO4w1Na9eNbOmGV7KdSkpiI6ONtYHVI0Tq4L02nIwyssv4e23pa1JZw5YJsuge4i7iM2sjjuhTRt6CE4S5oixhOPGpUo+WwvKy2kX10Ea/AMHDshzDQYoo2xEhKyEVuYIgoA2bdpIL4batCE3cCsZLl26hJ07dyIhIUHRd0kN6GJfJDxBiquppqPT9snNxdVyKa8E0YXIFNPqVAmWsWPfrFkzlJaWIjz8lNEVGbB97MbvKiujWKuQECtlJg9ALry9o5VtaLz5pqSlzJq4uDiUl18EkG3zmc0z/eUXiusxsyAfOHBAWfkOcx59lORUgIeHB+6//3789NNP6Ny5M65evWp5wl13WSzuLf+G/QC8AbSU9z6rrD3ZyxAL+pFUrKlZO1tmRTb3RiZ3cMDb+UaWxLgth/DwcLRp08ax0mq1iNy1axfKysqUlXcAaIdj3jxZp955550A4NxF+KWXgDFjzL4iE3Xr1lWWOE/kyhXKcCwztrtp06ZGpTUtLc2+VfjOOy1i/0pLS3HixAnl8ayASSGU0c5xcXE4fPgwis3iAyVxYmmVHc8qotLl0SF5eehduzY2btyIatWqabtXu3ZkJVRYH9NhBuGyMhrH/pL25iopKTGWu5HF8ePAihWK3uexY8dizJgxePnll/Haa6+hoqLC+P4MHDgQrdu1w7333otPv/gCTz/9NNq2bYu5c+eicePG6pJaqVC4Bg4ciOPHjzveyLPqh8nJyYiLi1PulaDQoh4dHY3IyEj4+PjgySefxNq1azFgwABUmCfsEsdtK6VVsUItMnas4prBIqGhoXjjjTewdetWjBkzBjVq1MC6deswomNHzElLQ7rZhl9RURFOnDihXGkFaBNdTkK3/xhcaa0ExEQWipSF4GBSkG5auqxaJ3gyV6q+/HIyatasieHD35N2/fT2RkmjRti0Zw8GDhyoPuufyAMPUGY4O0hvstMi6P33/5S0JmWm5CH5RLDR+lqzJkAlK+oAMGUYVbSB72TCadiwIYKDg+Hrm2r32RrJywMyMmzaRaS4uBinT5+WvxCqqCBXOEdJEezQpk0bHDx4UHaJlI8++ghlZWWYZhVj4RQ7mxOJiaYFPtADZIGkQdVp+3Ttii1BwyQ+sFVaASdKcFiY00yZ2dmUkCcv718nghm+S0wWFhxspczQJP/II9Hqsm07wZRt1XbBbvNMrZSZsrIypKWlob3CRaCRPXtsagfK4csvv8TDDy/Fvn37EBb2i6Wb9eXLFolWLP+G/QBaAfCR9z6rtMw0b94cM2bMwPz5822Vr4oKSpxk8DoRx1fG6KNlywBv72MAGsuLAQ8Jobp/0hmdHNK3b18kJSWhyNq/3k6s49atW+Hh4aG8dnVgoOz44IiICMTHx+PPP/90fKJVZt7MzEx1ro4Aja1vvQXs3y/rdFFp3bhxI+Li4qQV7Fu3KN74wgUwxjB79my8++67KCsrU6e0hoRIzs9SxMXFoayszHE9RwDo04fcHa3KP924cQMXL16UVxbKWka9s406yZyviBo1KDO9VVkVZ4ib7WLpMQvEcduOjFu2bEFhYSH69+8v78t++w247z5Z7SwiCAIWL16MBx54AK+//jruuusurFy5Eh06dKAY4F278FrduiguLsann36K0NBQzJkzB78qLP9jREU7i152dq2t338PbN1q/LW8vBz79+9X7hoMKB63BUFAcnIyTpw4gU8++QTz5s3Dzp07jTVYAdi0c3FxMY4dO6Zeab3jDuChh9RdC2DWrFk4e/YsFi1ahN27d2PAgAH4atQoBAF4wWyD8PDhw6ioqJBv1DBnyBBg8mTVMt6ucKXVVZw7R7GY27bZfPTPP/+gbt26ykpkqIj3CAwMxLRp07B69Wryp7dmxAhsnjcPN27exGCrotGqeOEFhy+6tDtzbURGxuH6dWmrU7WyXFwqDjFaX/PzAUE4CnMrq2y33YICOtlB/ClAg2RcXJwxE6dDHCTLAICsrCwwxuQn9lBpPQKAmzfboLCwEF5epywVhY8/Ju3AbGc/JycHX3zxBcaMGaPcwu7AzczUxj0NR7bJa5+nn0bw529LuGNmGv611GIcKjX16lFNQgfu7vPnNwe5dzpZfIvfZWX1EJWZX34hpXXiRIUL8r//ptrGTmrBiUqrt3eqxXHJZ2rlTnj06FEUFRWpi+kBVC9yv/9ewHffJYI2ldIs3awHDQLGjTOea+ovDEAKgHby32cN78qcOXPQsmVLTJ482XKTx8cHeOopuy6ADRpsBXAYTz/dQl4M+NNP07ijwkWtb9++KC4utq3zaMcCt2XLFsTFxckrF2TOggWK4h7GjBmDHTt24Ntvv7V/kpWrnqqakyIK576mTZsiNzcX7xpyA+yRKi11/jwt+jZuxLp16/DSSy/h5ZdfBgB17sEKEqOInjxOXazDw4H+/W0mzZ07d6KiokJeqTxzfvhBVnZ/RTjJnK+IsjLKcCxzc0KkSZMm8PT0lM7I7CCfAwCsXr0a/v7+8hNiqkyA4+fnh0WLFuHzzz/Hli1bkJaWhkGDBtGHmzej2ccf4+ShQ8jNzcWmTZvw/PPPGy3IilFhaW3atCmio6OxcuVK6RN8fUWLAQDyYLhx44byDTKAPMmWLpXMfm6PsLAwo5vvhAkTEBgYaFmm5/p1kws8KKa9rKxMnQVTvN++fTITckhTq1YtTJo0CTUNz61maSmeA7Bm40ZsNWwAiOFcquTU4MJ8O8OVVldx6RK5ZFpNtGK23AEDBiizbHboQG51CuMix40bB8aYTT1UkVWrViEwMFD+TqMjJDIcm2PPnXnYsJ4QhF2QynR8FM1wAOIuVBZKSz8AY+moVq25Y7ddKQIDSXGTsfiJi4vDgQMHnFst7SwgxTjJpk3JZenEiRh5GWBVTorLlwNLl4rP6YClonDpElm4zJIozJs3Dzdu3MALL7yg6HsAUKH6Tp0kPxLbuGHDOADV4Ou7Df7+FCvqMIkSY5L9Iy7uKAAfiPGDgLrYYutnT8nA7gLwDwD7NR0FwfBdAQHkZmYV+yS6UyleYNy4QZZMa/dZK0JDQxETE4NWrbY5d1XPy6PFhWGM2G9Y/Km2tKp0J3zxRaCoSADQBqKF2OhmbWWZEdu8Xr1zAK6iZs128t/n6tWB2rVll7wRWb4caNbMD4cOzcKFCxcwZ46ZFfvGDUpiIlHnMzk5GXfddRdiY2PxzDPPyPsyDd4rd9xxB7y8vGxdhAcPpsy8fn7GQ8XFxdi1a5fR9VkRGzfSIlImM2fORJ8+ffDwww9LJ4oCLNq5rKwMZ8+eVa+0Vq9Oz1GB0goAGzduBGBHOTQbtz/66CPUrVsXmzdvxueff67OeqRAsY6NjUVgYKBzpXXPHrLsWbF161Z4enoqV1pjY4G6CkqHyeGnnyikRQ88PIAHH5T8mx3h6+uLxo0bO1ZaJTaVGWP4448/0L9/f/n5JjTUxxQEAY888ghSU1PxyCOPYOrUqaZ7+fqiYZMm6uIvpWRUKJ8gCHjwwQfxzz//SFusX3uN4rYNbNmyBQCNUYrx86MMx0ozdBsIDAzEyJEj8fPPP5vqMcfE0KaHYeJQVMZIig0baM0tt0a6HHJz8aSvL+rXr48nnngCZWVlSE9Ph7+/v/Js5YBrPCduBxhjVe6nffv27LZnwwbGAMa2brU4vGPHDgaA/fjjj24Ro6KigjVr1owlJCTYfFb2+uustq8vGz16tD5fNm0aY7VrK77sp59+YgCYr+8eRo549n7uZAAYEMM2bdqkTsaQEMYee8zpad9++y0DwI4cOeL4RIl2XraMsYAAUeb5DADz8rrAfHws/56AADrXgo0b6cMtWxT9WZGRjAFFDPBgwCvG74iMZIxNmWLTLgkJCaxz586KvsMey5bR9wgC/Sv+Ta1a9WeC0Mb538wYY2FhjD3/vM3hYcOGsfr1W0re3yE9ezL2yitG+UztQT+CwBjwl6E//e2w3zli+vTpLDg4WIZAViho5+nTp7PAwEB269YtxydatfMTTzzBAgICWFlZmXL5GGNs6lTGwsMVX0bPljHgMQZUY0C58Zmz4GDGHn/c5prVq1czACwpKUmdrDKx7AtnGQDm7f2RqU/ZGbcZY2zIkCEsIiKCnT9/Xv4XHj3K2NixjB04oEreTp06sV69ejk9b/v27QwAW7VqlfIvUdHO2dnZrE6dOqxv377SJ5i18+nTpxkA9vXXXyuXTUTmuM0YYydOnDC812DNmjVjUVFRtietX88YwNIWL2YA2Jw5c9TLxhhjN28ydukSYzLfta5du7I77rjD8UkS4zZjjN1xxx2sY8eOymXcsoWxTz5Rfp07UdDO5owcOZI1atTI9gNDO0u9z2lpaQwAW7hwofwvcjA+qGbKFMYiIvS73759quS7ePEi8/LyYk899ZTthzVqWIzbw4cPZ7Gxsepl3LWLsfR01Zdv2LCBAWArVqyQ/HzWrFnMy8uLFRcXq/0CVeswhzz9NGMxMeznn39mANj48eOZv7+//THUGVOnqlpvVzUA7GUK9ENuaXUVdtxS/v77b3h4eCi3bJaXk8VMYayjIAgYNWoUtmzZguzsbAuL04dv/4vLxcUYMWKEMlnsoSAZhTli4pBRo7ZbWJPM6kQbOAggEZGRJ5UnDxKRuTsl24WrenVK6GG2g22ZEfU0AD+UlUWgpMTyUsmEQg0b0m6hQpcrivH0A5XhSLc8LpFEITMzU93unhXmJUusM+6ePdsDjKWDkhURkn9zRQVZHM0swSIZGRno1Kmp89hia86fN5ZCsc1aLXbR3gD84chF2Bg2VlIiWQw9Kek0CgujHVvPpVBgUR80aBBu3ryJbRKhBhbceSdSEmYa3++vvtqPevXi4OnpKVMoK2JjbeLp5GBy3W4L4AaoJBAQ2aCC3K4krB6ixVpzMjgnWPaF+gBiUFq6xdQnHVhmUlJS0K9fP9RVYq26cYPcMu0lOHFChw4dsH//fsukI4cOWSTbAkyWD8VJmACTRV3BuB0WFoapU6di06ZNOHv2rO0JS5eS1Qwaa7RayyiDqKgo+Pj4oGXLlpg4cSIyMzORZ31tXh4qALyyZAkCAgKUx/VbExBAVn+Z71pcXBxSU1Mdlw6SGLeLi4uxe/du9OzZU/oaR/z5J/Dss4rnZ7tUVFCWWmdzpBJUujy2bNkSJ0+etI3/vuMO4NQpsppZ8ccffwAA7rrrLvlfpMHSaheJzLyaaNeOvKEUEhERgREjRuDbb79FofmEWVFBcVkGGSsqKrBt2zZ1Xh0iY8eqKu0nkpCQgHr16mGhmABz505aeFy+DIAsrU2bNoWPxJpCFhpCT+zy/vvAyZMYOXIkBgwYgGXLlqF58+b4way2rCK4ezBHV8wWP+aK4jvv/I3Y2M5GP3fZZGVR+Rx7MQcOGD16NCoqKvD886ssFIw9xSfhDQEFBTrEswL0EpWUKI4DqFu3LmJiYlBUtN1COfl8znUcFZphDH4AlT05B2/vFqrKzljIKGPCad68Oby9vZ0rrZ07kxu4mQJomSToFIBoANJugjYJhRo3pmwvCgPzTYpCc5iyK1Ofu3jEclIsLy/X5q731VeU7KiwEE8+aasQiorp9evdQQYPy5gym7/5+nXqkFYTd2lpKU6ePKk+xszQzvaTNvkD6AtgNWrWrLDRmS3ckL/9lpTq8+ctSuSkpZ1GSUm04/qp9uQDZPXFhIQE+Pj4OM3YurxoBHqsftbwfleguDgFp0/LrHkqxbPPkouiApYvN99Xa2v4Nw0BAcB7L0q3M0Cx3/7+/spLPDzzDDBrluzTbftCLwDbkJVlUArtbDZeuXIF58+fN25myUZlsiiR9u3bo6CgACfM3dRmzDAqhCK7du1C8+bN1ZU2UjluT5gwAYwxy9gykSFDAMOzEpVW1YmYAKpNu2SJrFM9PT3x2muv4b333jO2l3VWdXbtGqYD+H3zZrz66qsI0ZpMKD+fwnd275Z1elxcHPLz843PRhIJZSY5ORnFxcXq3DJDQlS1s12uXweefFJWFnTZqHR5bNWqFRhjOGpdn9TXF4iOlgyr2rp1K9q2bYuIiAj5X9SsGZCURMqwXuiZzAqgDbIVK2CzSy6DadOmITc313KuEedng4yHDh3CtWvXtCmtGssveXp6Yvr06Vi/fj292+npwNdfk4swNGYOFuUDXOJ+KwgCFi5ciFdeeQWbN29WV9YIAO65hzaNzDc0/wfgSqur8PMDYmPx4/qaZoriVZSUJCMz807lC0nR7JiT4/A0qbjJ1q1bIyYmBj/++LeZglGGbbiIONTCrFlBzmMtdZRRSt5Tp3rgt9+2Y9ky0y6wb8FVNGUZ8EUxqDYiMH16M21ZWseNo7IbThB36p0qrRJYJgk6BSqPIedcMxQORKaENs0AnIAYH1xeDizI6IW0eqaNiQsXLqCsrEx59kkRDw/g6lWsWphjt6nPnAHq1xcVb8t6tzZ/s3gTq42ckydPoqysTJ3SGhpqvK/jTLRjAWRhypSNWLRIunyUuYw/rgsxvs9ABcQarSKyawbXqkUbHk4yZS5fDrRsGYiSkl747LO1Fu+m9bs+5/ELYMYX/BiAmygra4fx4zW+1zIRre6mPtEKgAf8/dOwYAEwepw3ZeaVWPBlZWWhYcOGyjOYp6UpWjTb9oVeAK6hTh1DPJydviiOA4qVVhVjojliPLJF7GhOjo18x44dU1/aKDSU4v3FDJwyiYmJQc+ePbFkyRJLi+H162TVu3IFACmtgiCggUSdaNkEBCiKD541axYGDx4s6TFTXl6OR5KS8BWA5595Rn58siMqKqg8VFKSrNPj4+Nt5LJBop3FBC6qLOoa+6INdt4VTdSsqUo+sc6qTVzrpk3Ae+9JzqcHDhwwtoNsAgOpNqaeltE//wTWrNHvfhs2UIZjg9VRCd27d4eXlxf2mtWMtW5nTfGsImbzs1oeeeQRVKtWDe+9957pXiEhyMnJwenTp9UnYRLlA/R7VwDg8ceNSUAbNGiA119/HUEKM2Vb0KULTbgKczrc7vxv/bXuZMIE4MQJPP9GgJmiuBEAQ2npQHkLW3OCggBvb+NCQAopV83x44GwMAGhofEoKjIf0NchG6XohFbIyZF271SMuGPkQEZ78gI9UFGRjSlTTmD5cvrs4xfoPtkIh2g9rFtXhQJjzv/9HzB9uqxTRRcuh7z4ImC1WLTMiEpKq7e3rferZEIhxmjAVNhBxIQ2gtAMpLCa3BFfK30Jw/e+bPxds7ueoZ0XzrHfzg0bAu+8EwYgHICp30n+zWJ/CQ+3OCzWWhQTqyiW0XBfqazVJkYCCMOnn37usHwUrlwBAgOt3udLAIpBlnQTsmqM1qgB7NpFu6V2sHw/BqG09AjGj8+EIJDO++CDlu/t2tzOmI9HDVeLSg5lDlb1Xu/aRYq1VIITCWzdsP0BNAWQRs+yWjXKzCuRGCorK0vdJopZO8vBti/Qwqt/f1qIie1s3WFUK601ajgdtx3RokUL+Pr6WiqtV65YvCtlZWU4efKksmz05kyeTObxOnUUXzpx4kRkZGQgOTnZdPDwYbK0Gha+mZmZqFevnnpXPQD48Uey/CskIiICtWvXNrZfWVkZxowZg6+WLsXzzz+Pt999V3upN0BxO7dq1QoeHh6O5xerdgaAbdu2oWXLlgi1jZ1xjsL52Sl2xm1NLFhA9aYV0rhxY3h7e9sqrWvWAG+8YbOwv3LlCi5duqROsfnhB8mqEKqxysyrGbE9VLSzr68vWrRoYVk5ITeXnp/hvv/++y8aNGigzd1f4bgtRUhICKZNm4affvoJp0+cMI7bv//+OwCYsjOroUYN4LvvZBk4ZPPbb2QR1oubNynDscLNxtsdrrS6GMsF7GYAQQDay1vYmiMITl90qdg9gDaLUlJaAjgJU6bUhQiGDzwNdVLNkW0tsqZ1a3KRkumiZilvAgABt259jBdfpM+CirMBmCutnpg/3+SGKysbrzWMyX7J4+LicPnyZelyQSJnzti4W4kKZP361wDkIyQkBosXw7ElT0QQyEqfnS1LRuvvZUxU6kU3KQYBFcjKMj2re+7JBKBdaS2/ZL8vzp5N8rRo0RI+Pocc/801a9JGQuPGFodFVy9VSmvXrkD37gBgVVfVGl8AD6Go6A/p2DwRwwLS8r0VNwYslVZFNYMdYPl+iJZyctvKybH2/mIIwxXDuwIAOwBUA2DKdqz4vS4vJ/fgc+dknS49prVFUZHBNfPaNappLBEbfObMGbcordYZqmvWjIKHR0MsWfIzIiMZ/q5xH/D55zbXpaamokGDBsqVBUEAmjZVvRvu7e2Ntm3bmpRWxmyUmczMTJSVlalXWjUobSNHjoSnp6dxoQjA1B5hYSgrK8OmTZu0WT0A2kD58ktVl7Zt29boHvzKK69g5cqV+GDaNMzp3VsfhRWQNT+b4+/vj2bNmjkuq7Z+PfCyabOxrKwMSUlJ6i1cotKqYm6RxKyddSM6WlWGY29vbzRp0sSYNdZIdrakfOkG5UFVfcynnyaFRg8YI3d/6wzhWtC4OREfH4+UlBST90THjjTZDBiAkpISbNiwwVjXVTXh4bpsnsyYMQOCIOCzHTuMf/cvv/yCqKgo5VZ0cwSBDE9q1h5SMGa3L6omNZVitXft0u+etwFcaXUV06cDjz1mtYDdDNrZ91K3sHXyojtShMvKWgKogJ/fUZCF6A/kYQY+hfTutWKlGqC4ztdfl71qt/yORgCeAvAFsrI24swZIAz0t15BGEgJi8HZs74AHCcAcsicOeTaI1HSwhpZyZjsDESJicCvv1ICmm+/jUFiIhxb8szRMKA3aCAOsqTwVUcBSuCDRzHf+KxycrIAAB980FCdW7hhwdw8VHrxExpq+tv69m0FH59DKC9n9v/mpk2B+fMBqyQ8R48eRZ06dZTXnQSAxx6ziIETn720XjQNAMP8+fPt38/QzpZdW4wzNLkHKyrHM2YMMGmS3Y8t348mIOVYOq61Ogrgh2LDuwIA2wF0BeDl4J5OEBUjmYtc6de+K4AsKgS/ahXFhFnVpi0qKkJ2drY6pTU8nOqgynifRcS+sHQpcOuWgIqKFwBsxZkzX2Hke52x3HOCzTUpKSnKrawi6enKazSZ0b59e+zbt4+SMRUUUNkuszHn+PHjAMjapIqrV+mhqFg4BwcHo1u3bpYxcGJ/CQ/Hn3/+ibNnz2LKlCnqZBMJC1PcziKdO3dGSkoKhg4dijlz5mDKlCn4v9OnaYNVT8LCFCmETj15mjenUh4G0tLSUFBQoF5p7dCBkjnqUd4OsGhn3UhNBd5+26KmuFxatmxpa2mVsFYDGutjKmxnhxQUAHPnAnJqwstF4+ZEu3btkJ2djYvm47SnJ+Dpie3btyM/Px9DhgzRJuPUqVRCR2NSsPr162PUqFH45uRJ3KhbF9evX8fGjRsxYsQI7RtSaWmyY9SdUlBAir+eSqvenhO3CVxpdRW7dgGZmWbuaOcBHAeQoKrOJABKOvLQQ3Y/dqwrksXlwQcPIyRkOYByAA/aPVuVUs0YxVHIjAOw/Y63ADSDp+dDaNCgDFcQhnUYYKa0NjNeI2VVlmVJUvCit21LiWQ+/vhjvPrqqygoKLA9yWxStLb8LllCSqviGp4aJsU5c2pAEOpAVFrDcAVeKEcBqpmdlQkgAgsX+qlzC4+IAMaNw13T6tu43QYE0Bws0rJlS9y4cQNnHGlLhYWS1reMjAx1VlYHSLkKBwREoVu3cfj444+NLsk2jB0LTJlidX06yFJL1n9FNYMBsjxaZYE1x/L9EAAMArAJ5JJsibjBUxQYhgYN8gyy2ca9KXqvFU6KUs/W338yatasjxkzZqBC9FiwmrjFvtFQzaATHQ20bUuLAoWYxpCpAPoDeBqNC1fhy2dPWZxXWFiIjIwM9UqrRiySMfn6Ar//DgwfbvxcrKuo2tLq5QV8/z0t0lQwePBgpKSk4MKFC3TAzAI3f/581KtXD0OHDlUnm4gGl8fnnnsOzzzzDDZs2IC2bdti7ty5+ls9RBkVxMDFxcXh7NmzyJG65upVSrJilnVajGdVlTkYoL6jIMOxUxITqY6lnrVf9+yhF1PF/Ne6dWucPn3acp52YGkNDw9H7dq1lcuog2urEVco/hreFcAUb230AvjlF2DaNKC8HGvWrIGvry/69eunTcYWLYC+fTV5eYg88cQTyC8txZLERPz5558oKSnByJEjNd8XTz9NVnA9cGU767WBcrugpD6Ou37+E3Va69Vj7IEHGGNUGzA0dBkDwOrU2S+vzqQKpOpRmn6KGeDFXnjhBZaQkMBaN2rETng1ZZ2x0+ZcQZBZC9OaigrGvL0Ze+451fL6+FANq5de2mr2WSkDfJiX1zNGuUy1IG1ld8iqVXTi3r2yZOzevTsTBIEBYPPmzbM9wdDOUn+Lt/ccBoAVFBTI+i4j48YxFhOj7BozWrRIYD4+XZggMHZPxA7GAHYn/jKTrS8Dukg+v8hIZd9lr0ariFg/cs2aNfZv8tRTjFWrZvx13759bNasWSwwMJA9/PDDygQS2biRsdBQxvbvlyXzxYsXWXBwMEtISGAVFRUOby1eDwxgPj7x6t9nJ+1s26f+YAAYsMGm3bqA2nnTM3+xv/6i+rO+vv9YnGO3Rq49xPdZon6uI5mtn+0yyq7GFg8YwFhgoM0169atYwDYFj1r4snAcgw5wwB/NgoBbBEmGc8pLCxkiw21PH/99Vd1XzR3LtVqVUlqaioDwL755hvJz8Vawc76rV1UtLM5Yr1Lo3yG9zkjI4MBYG+88YY6ucwRx+19+1TfIjs7m+Xn59Mv9eoxNmmS4wuUcvMmPUuZrF+/ngFg//zzj+2HO+h9Zn/9ZTx0zz33sBgN8wJjjLG33qJnWVXR0M5//EHj47Zt20wH7bRzhw4dWL9+/dTJqHF+tkCinTVTUcHYtm2MXb6s6vLr169bvrczZhjn58aNG7NBgwZplzE7m7GfflItozkVFRWsY8eOLCwsjEVERLA6deqw8vJy7TLq2c4HDjAWG0v1X/VC4Xq7qgJX1GkVBOFOQRAyBEE4IQjC8xKfNxMEYacgCMWCIDyt5NrbCdkxlIa4o0NXwxEVBdx/P1BcvBmBgSE4d66t+uy3164B+/fb/ViM15IKuwoI8EG9ek2wa9cubNu2DYPatEFsWQa8fC3dBwUBePhhBdYi64sV7EJax5dFRgLz5g2Al5cXSkv/NItDzARQgkmTTJmD7RllnBprFO5Cbtu2DeXl5WjSpIll3JbIsGFAr16Slt/S0pPw8AhHtWrVbK9zxJAhlEFLJb16NUNAwFGUlzP8+pW5i7VIFgBpV0xF7qPl5U5dnq2zOkq+Q9nZFnHQTz75JN577z2EhoZiuJlFSRH+/mT1kNiFlJI5IiIC77zzDjZv3oy1a9dayhnJ8NvcLKNronh9nTrpGDu2jfr3OTzc4S6pbSxuAgAfiC7C3t70rgsCwOo1wL5xHyLh8VZISkqCp6cn5s/v7DyG2hGCQK6ECkpCSD3bsWPHol27dvh4zx4UBITbtH8WZZpSn81aJZZjRQMA07AKhThXjcbEW7duITo6GpMmTUJAQAA6d+6s7otOn9aUHbRNmzZo1KgRlZY5cwb46y9KwmHg2LFjaNy4sXp3OHHcVrlj37p1a9SrV8/kIvz448CaNVixYgUEQcDkyZPVyWVOWBglWsnP13CLMFSvXt0UF6y3pVVhhmPRkyc1NRVpaWmWMfVWSY4YY9i6dau2jK0AxWsb6pNq5ocfqMyInmhwbbWxEAJkCf7kE4vzysvLcfDgQfVx1npaWl2RzEoQgB49VN8zKCgIjRo1Mj1Hw7ty7NgxHD9+XLtrMAAcP04Zjh2sZ+UiAHhZEBAIoFOnTliyZAk89Mioq2c7t25NfVGrhdochevt/wzOtFoAnqAMPjGgFVMagBZW54QD6AhgNoCnlVwr9VMVLa1SljRzy4W5haFlg+uMAWyW9/tm58cwT8/h2qyss2fTzQoLZclrbfEYNWqUwVID9u8zzzAGsF8/yXJoKVNMXBxjQ4ZoukVCQgJr3bo1Y/fcw9jw4cYd1KSkJOM5ztrDLseO0cnffadIpmeffZZ5e3uzvLw8yc+lLb9xDOir6Hv0YO7cuQwAu3TpEmMLFzIGsCZ+WQaZyhngzYDntFlau3dnbOhQWafWq1eP3X///Xbb7HzrAYx16sQYY6ysrIwFBgayxx9/XN0fLyK285Ilsi8pLi5mwcHBrGfPiRZyVge9z3vHfWA898qVKwwA++CDDxzc0Qni+1xUJOv0ZcsY8/Prz4BoVr9+jt2+3qtXL9axY0f1crmAjz76iKyVQhub9h8+/CXm6enJSktLld/4wgXGOndWZT2y7o+ByGC+AGuFTiwykrHXX9/DALC3336bXb9+XblsIgrbWYq33nqLAWAn336bMYCVnDjBnnnmGXbgwAHWsGFDlpiYqF4+xhhr21b2+yzF5MmTWVBQECs0m5t69erF2rVrp00uEbVWZCny8qg93n9fv3syxtimTYw9+KCidq5bty6Lj49nvr6+bNiwYaYPvv6aZMzKYowxdujQIQaALVq0SJuMGtvZggGmcVs3VIzbIhUVFSwsLIxNcmJBFz0AFi9erE7GCxcYO31a3bXWLFlCiwdDO+vGmjWaLOqjR49mUVFR9Ev//ox16mRcV5zW42/X0M42XKf5mWmZi6XQYdx2Ob//zlhycmVLoQm4wNLaCcAJxtgpxlgJgB8BWJg/GGPZjLFkiMUhFVx7u2CypM0DQOYKMYbSOinQlbNF2II7cKhUTIyRDeAUysvvUJeVV0SBlVDK4iFavYKCgtDNUB/qnqlh8pIDyUWHnZ/BgwcjPT0dZ44dA8rKsGHDBmPdVBEpK60sS1LdupSRUeEu6/Dhw1FaWmqZcKSighocUhbe6wAOoEYNFfX0GKMMxxJxnnIQ65oeOXIEaNIEeOQRvPZ5uMFidxFAKe64I0oyHlV2rHVAgOzdcDFBhr045GsZJqvHsWPHcPPmTWN9StWoiOvx8fHB0KFDkZS0GoWFpmcvxosuX2eyzIjZJzVlRW3TBhgxQnZymcRE4KefHoOn51lcvBiP8ePnIizsZ3z3XQll+M3IwMULF7B79251dRxdyD2G0j4vMMt2LSwENm7MQr169eDl5SV1qWMCAihZxsmTii+1tmTXgQemADiEfcjKuobZs1MBAPfee6+2eno6JMyYMGECBEHAdxs3AgC+W7cO77//PsaNG4ezZ8+qj2cVadSIsparZPz48cjPz8d3330H/PILbm7ahB07dmiPfRPRK8svQBbbgwc1ebNIcuIEpYhX0M5xcXFISUlBcXExkpKSxM1+m8y8YpK43r17a5PRiXeHIrKz9bUQApri9ARBMGa+BUAJ3558EjAkXRIRM0mrHrvr1CE3ET24/36a57XUMJZi7lzg3XdVX96xY0dkZmbi3LlzxrwdW7duRVRUlLZSNyJ6ZrIW76G354SeiY4WLaIY3rIy7fcyZ9gwSrD2P4QcpbUeAPNaEOcMx+Qg+1pBEKYKgrBXEIS9V6qgudvkNnkZwE8AbhqPWy/Gs1EbvbEFq436uThoxqnLyiui8SUSlb7+/fvD+9o1mrz9/TUIJIEOqczvMtTGWnv+PIpq1sTSpUsxYsQImyyysrPxmhMYSHXbFKZD79y5M8LDw/Hbb7+ZDu7eTckt/vlHIgnNLgAVeOQRFcrD6tWU4dhqspVLXFwcvLy88McffwA9ewKff46xk/yQmQkkJZEr5vPPR6pT+kUUtHOHDh2QlpaGrKzjkp8Hl5iSZew3uAu1a9dOpiB2EOsaK5wUR44ciYqKXAD/Go+Fg+5xNMdWaVVVMkFkyBBKcqGgUH1BwTB4eSWhvNwHwAxcvXovpkz5GkemfISL8fFI6NMHnp6emDDBNgOuKl580Vg6SCnmLta9e0cBiMdR2Ca6unkzC35+KusEyahf7QjzrNK1cAX3AWAoB7ANJSUpEIQgREdHO7mLE3RImNGgQQP0798fi5OTcTkgALPffx+hoaE4ePAgGGPqMweLrFwJrFih+vI77rgDHTt2xIcffojyJ57AtnfeQWlpqX5KK0CFiRct0n4fLy+gZUtFbu+yULEQ79u3L+rVq4dZs2YhJyfHmAka2dlU19jfH6tXr8bnn3+OmTNnau+Leru26q0oBAWZlE0VxMfH49ChQyguLia3/E8/BcQEYQaSk5Ph4+ODVq1aqZMxK4uqEDgqkaYET099N2UAzRmOxTXYmjVrAC8vsLp1sW3bNv02QzXWr7bAFS7WADBoELBxo+wSjg5JT6ckY2o2Zh1x/DjJ+D+EHKVV6m1iMu8v+1rG2ALGWAfGWIcwvQdCHTBZ0jqDMu/uMx53roiKykdrbTUcdUhlLggCxQk2agQYrB+6MnGiRW05NTRr1gzR0dH44vp1fHfpEnJzczF16lSdBARlZrSayJzh6emJoUOHYu3atSgvL6eD2dm0SxocbGP5rVEjCR4ennjhBRVxcBo3J8LDw3HfffdhwYIFyDt71mJ37/DhwwCAyZOjcP/9dGzpUhVWdgWT4hNPPAE/Pz8EBLwg+fl3wTPI4ghg37598PPzQ/PmzRUII4EgAJMnkzVTAQMGDIAgBAIwFbgXLa0eEaZJMT09HbVq1VKXfVIDL74IFBd3ApAB8uBogdLSFTi6LRv3VVTg3Llz+Pvvv/XLdFtYqGrzxLYkFUM04kD1Y9cY/hXJwsmTkZg+XUXdZUHQZaPszBkgA03xDn4GZYTeCiAFjMXhhx80xkfVr0/9UBw3VPLss8/i8s2baFxUhMzMTCxZssRoedNsadWIIAh45plncOLECfyenY2NeXnw9fXV1+K/fj2QlKT9PkeOkDKTm6v9Xuao8O6YOXMmsrKykGgYfHfu3AkAqHj9dSA9HefPn8ekSZPQrl07vP322/rIqMffLcYF660oCAJtJqhc3Ldr1w6lpaWUQ8FOHdk9e/YgLi4Ovr6+6mQ8fx544QXAuryOGubO1b/0EqB5TGzevDliY2Mpj0dyMk48/TSys7PVZ662Rs94TFdZWuvXJ+uoHoYdV2zwAFQq0BXr+KqMM/9hUKG9dWa/zwIwy865r8EyplX2teY/VTumNdsQF/qeMYaSMomafsZiOTuCpiwclw3HJjKgjvLsndYcP64qHtOco0ePqs8y6UZ+//575gEwQRBYo0aN2NKlFfrF3qqMuxWziB45coQOWMUdmZOQkMBU92Md2nn//v0MAHu0QQPWs3p1Nm7cOFZRUcEiI+OZIDQ1xLYqiAW2RkF8NWOMvfbaawwA8/W1zFZt/d29evVinTt3ViiMvnTufC8DwhhwgwGMPYSvjfHfpnM6s4SEBG1flJXFWK1ajC1dKvsS29jpVxkgsFcRxwCwuXPnapPJGoXtLGI9JgYhjx0yxNObfo4yoJABngx4weZvk90vdYijt5S3FwPiGRDAgCe1j9s6srNTJ1bH25v16NGDVVRUsOPHj7Mnn3ySlZSUaLvxL78w1quXpvitsrIy1igmhgUDrE5QEOvTp482mazRoZ0ZY6Zx+8wZ7fcyR0OcXnl5OatRowabNm0a+/zzz1lISAj7448/WO/evVlgYCDLyMjQR8ZbtxjTI7Oqq+IIGWPsq68Y++ILVZceO3aMAWALFy6UbGddciboGY/Zvz/F5OuNDvGYM2fOZD4+Piw/P5998803DAA7fPiwfjLu26fPO/jbb5Tl9+xZ7fcyp7CQsRUrGDt6VPu9qnA7VzZwQUxrMoDGgiBEC4LgA2AMgNUydWIt11YpTJa0MFBeqV3GmNbBgy1dQyORhWbIwJgp1Q3xUgfg59dGefZOa+rVAxYvpsxwKmnatKn2osuOKCigjHDWwYsKGTZwIL7p0QOMMXTuPB3TpgnqaopKoTKuR8xOaCwIb2cnt7S0FLt27VJvZdAhliI+Ph59+/bF/LNnsfvmTXz//feYOnUqsrJSwNgzMHeykFXf1pru3alusMwYjf/7v/9DREQEgoPvR/362UaX5IXzbiHwahYaR5ZAECqwdWsKqlfXGM9qjooYkg8/fALAFVSv/hIEAThbpzP2jfsA9zxMVtWKigpt2SdFatQgq//ly7IvsfXUGA2A4SMcQJCXFyZNmqRNJmtU9kVr75MwXEELAP3xPICfDUd/B7Ae5LnSWwwPNyK7X/bsCWh0j509G+jol447sRZATwApAAoBxKt7P1xEl2+/xal//8X69eshCAIaNWqETz75BN7e3tpunJMDbNmiaczx9PTEX199hWYALubno3///tpksqaqW2bCwsgqo2Lu8/DwQOfOnfHPP//g5ZdfxvW8PAwdOhT//vsv5s2bp58l3deXXBm0EhQEFBUBWaT/agAANaNJREFUjzyi/V7WrFwJfPutqktjY2NRvXp1imuVaOfDhw/j5s2b6NSpk3r59KyP6SoLnA5riGHDhqGkpATre/XCtl9+Qa1atYz5MnShXTt9YnmHD6ecBvXra7+XOSUlwL33asr8bsQVdaEBfeNubxfkaLYABgM4BsoE/KLh2MMAHjb8PwIUr5oPIM/w/yB71zr7qYqWVpFlyxjz9BzHgHoWFoFHHjFl611YfQYr8aO6VqWlpczHx4c988wzlSu4NU2bMuYKmX77jR6KThnNsrKyWMOGFVbWJfpRWlPUSGIiY9HRii8rLi5mPj4+7Nlnn6UDZvXLzNm9ezcDwFasWKFOvooKxnx8NNXfWraMsTp1Utn9CGTz/Uez2NjOButWHQbcsnmWTuvb6sCOHTuYv78/a9eunbFe4t+vUp26gVjLANol9/FZqI9l66GHVLUzY1T7UhAEtmvXLpvP9u7dywCwZVqFVNHOUhmYBaEFA8BmtmypTR4pxPdZZl1jEWtLq1hHdkL4WsNn8QzozoAJDAhmQInkO+6Ofily+M4ZLB/VGNXBFa3BqfrI0bu3/tlq9URlO9uQlMTKAPbHq69aZBLWBZXjtg12xm3NaPRgevXVV439bnOtWmx8bCx74okn9PWMOnyYxsVjx/S7p95obOfevXuz+Ph4xl54gbEaNSw++/rrrxkAbZZrPetj1q2rf71gxhjLzaUMx2oyshsoLS1lNYOCWBuA1Q0NZXfffbdu4jHGGNu+naobVFX0bOdRoxh76SXt97FGr3G7EoEr6rQyxv5ijDVhjMUyxmYbjn3JGPvS8P9LjLH6jLEgxliw4f/59q69nXnxRaC8vAuA8yDdnDZW//rLlBTooWFX4F3HlA21pKREu1VGZP9+QLT0qYUx4NQp/YP/AVVxPZKUlwOMoWHDhjh7VlpO1UmtVMZ7iBmMjdkJe/SQTBiRZIi76q4ygQ0EgZJFqUxiIsYTXrzYBgtRgoKiaJw//w38/KohJOQFUMyeJYpjrRkjq3pRkexLunbtipUrVyIlJQWzZs0CAKz8nHarqY7sLgBASUl7fSxbQUGq++GcOXNQr149PProo2DHjtHLbWDdunUAoD3JjIr6mFJZs0eNGgdvLy88/vrr2uSRIiYGuPtuxZllrROTicmsxjwehtmzAS+vYaC41lUAhgGQthRqygGgkOY1s5HrFQaKavECVWlroY8cx48Dhnhy1TBGdTH1iKWzRq9snvHx8ExPx5CZM+Gvd5K/6GggJET7fVyR9RbQPJ927doVAHD33Xej9/XrWDpqFObOnauvZ1RuLvDNN5TpWAv79gEzZgCXLukilgUaLep9+vRBamoqcmbOJA8CM/bs2YPg4GBticvEOHqt7wpjrokLBii5X1SUpsQ/Xl5emDd5Mq4CuJCToz1ztTUrV1If0sqLL1IuFb3RWL/agp9/Bt58U/t9rNFrvX0boYOfyP8WpCiJyXV2WR03YDYpHjAkMdGUZdScyZM1JzpCfj4lEHLFYKnSXcE802hUFLBr2iJyZTp3zu6CUfVCMiwMuHFDkcIlEh8fj9TUVPJAGDkSeOstm3O2b9+OmJgY1K1bV6WAAJ57TrXSKmazDkI+fFCKbITj1q2WCAvLxmefPaat1I3IyZOkFP78s/NzzRg8eDAeffRRfP7559izZ4+xn2QjFMAHABoBaKUty7aIhnYOCgrCm2++iX379uG3e++lQugG1q9fj7i4OH2SMKlYoFlnzV6+/FlkHDuGqJEjtctjTevWwKpVlG1VoYzmynWzmvQ3DpoYjsRE4LXXhoOMSgUApOWW3S8XLSI3MxXtbMGVKwiIDEdAQCCoWlscAG9174c1eri25ufTbtTff2sURgK9Fj/+/kCrVjQ26M2bb5KypBVXuWQClFTntddUXdqrVy9MmTIFH7z6Ks3PrpBRr3bev5+SCKksy+aQ8HDV4zZASitjDFu2bKHMvGbs2bMHnTp10r4RkJICfPmltnvcvEl/q5Z1gj0KCqjkzd69mm4ztlkznAaw6ccf8fDDD+sjm4jGdjaSnAxk2Gal1wUdkvy5lJYtKUFdx46VLYnb4EqrQkhRigNZq0wZMD08zGIsO3YEDPE8Bw4cgJeXl36xAHrs/Lgqpsf8ngpktM00CqxdcoUmxNBQiXIyxI0bKuNa77wT+OILFReS0nrlyhVcuHABuHbNJmaSMYbt27drz5qZm0sp+1UgKnwV8MALmI2tuAMAcO6cv/r6ttZoiKV46623EBERgTvvHIF/8C5eA3AZG0BZtl8H4IWaNRXfVlcZAao92axZM7yUkYFyw70KCgqQlJSEgQMH6iAgKGYmIUH15cuXA/GxRZgccxptGuSqj/N2AebK9bupA0n5NSj6L7wQB6A+gEAAtrGPivplRQXVqdW6uLhyBbWah2HBAqBeve8B/Kj+/bBGj8WPq0o7iPds1Yo2CrWwbRswb56xfnWVZOVK6ouuYPdu1ZsKfn5+WLBgAWKrVaMDVWhT2QY7+Rx0ISyMFlRWVlK5dOrUCYGBgdj05psW8/z58+dx8OBBdO6sIqO/lIw+PtruUa0ajVtPPKFdHmsqKoDnn6c4dS1cuQIfAAnDh6vPtmwPPfuiqzah9NhsPHUKaN4cMHho6UpQEOkaoaH637uKwpVWhZAC5QOgN8i1jSbn8nKz5ECzZxtdAXbs2IGmTZvq98JX9cVPUBAN5gpktK5zCwDBpVdwQ6A6daKiZf1e5uSoTMgUHw88/LCqVOZiKZGUlBSyQk2bZvH5yZMnkZ2drd41WOTxx4E+fVRdKlqgb6A65uAF7EVHi+Oq6ttaI7azig2UGjVq4IEHluH69WiUIh+vAyjFVACtQbnaaKNYswKmMWGGl5cX3njjDRy+dQu9kpOxZMkSrF+/HmVlZRgwYIBG4QzMmgXMnKnqUnGzJ+jsQfyDvqh7bre2BGX2aNhQeyaiBg3Izdiw0BMEAaGhcwC8A8DyPYyMVNgvdXBtXb4cuJSejcVrwvDii8C770aCsWj174eUjFV5szEoiGoJmnkUqOLXX6lPuyL0ZO9eGhO1ukcHBQF16ugjkzV6tLMrFUKV9attyM4GqldXHDYgi4kTacNaZWIdb29v3HHHHfjn4EELS+Prr78ODw8PPPDAA9plXLXKNaVq9EJj/Wojfn60meWKdtZLaXWVuz8AfPaZ9gn14kXg6FHXbeT9/juwa5fz8/4jcKVVIaICJQhjAGSCEiQT1lkmN2zYgC1btmDChAn6CaDHpFijBvDAA0BsrC4iWSAIwJIlwLhxsi+RcgUNRzYuM9NAlJhIG5PWqMrsWVxM7j1Xryq8EGjbti0EQUBqSorkDt/27dsBQLulVcPmhGiZDsJ11MdZeKBcHxdHczTWWfv++z6oqNiGKKzEIDwJiiOcC3FIKinRIWNr8+bA//0ftJhtR40ciY89PHClrAwTJ07Evffei4CAAO2bEuaUlKi6TNzsEeNFsxHumky3FRU08Wph+3Zg61aLQ3PnjkdAwGMWx1T1U40uj6LyP6h8Dd7Bc9qzk0vRvj1ly9SCK5UZvXDlArK0FNi8WUMyA9DCcdYsm76oG3psKnftSq6jKjctHSK612isGexS65a3t+YMx30SEnC0rAwXDMrW0aNHsWjRIjzyyCOIiYnRLuPWrcDHH2u/x9Ch2vqzPfSKu505kzazXIEeWZhdGRcMAE2bal8nu9JIBACPPkq5Dv5H4EqrChITAcbuBiXq+NHis7ys60D16ij/6ivMnDkT0dHReFIiWY9qwsJoQtNSUqZlSyqdo7FMhF3uuw9o21b26VKxqWG4gnwfy0nR3tiueMw/e5YWkH/9pfBCoHr16mjUqBH27d4tGXe0fft21KxZU7s7uIZ2FjdWHq75M86iITrVu6CPi6OUjCoXaGKbbUdPrMUnIFf7BMlzVNO4MfDBB5RMSCVCQQFmVFTg6KxZWLt2rTHuTDfPiQ8/JJdMFe0sPp8wUBtQMisXrIH0cJF64w3g2WctDlUFV3XApPynIh7H0BSAys0wRzz1FLmlakFc3Llq8TNpko3niGJc7aonfodarl8H3nmH4uBcgRhHr7HkGwICtLuf2uP4cRoXtXDrltHVX3dyc4EpU2iDQiV9DS7AX584gdLSUjz++OPw9/fHi3q91BryJRjJyKByKq4qQahXiShXER9PuTG0bM7cugV06QLoWYrHnEOHgE8+IUOHWly92ahXsqjbBK60qiQyMhjAnQBWAKgwHm9f9yJw4wa+2b0bBw8exHvvvadvLMC991LgtYascLh1y7UxRydOAJs2yT5dKmZ1tc8olN9naa3VLSGTONkqsB6ZJ4q6cKEztmzdTY7hVhP39u3b0b17d3horYUXEUH/qszOmJgIvDuD/r6dJ8L0V1gB4LHHVGftE9usHfYhDNIDri6ZY2/epNhjtfj6Aj/+CGHQINx5553YtGkTPvnkEx0EMyBagVW0s/h86oDaORvhFsd1IyICuHBB2z0uXpRc5Oriqh4RQRYLlS6fZ84A4biMyfgaEbhocbxKMWYMcOCA61xbL13SnLjFXjvrgopx2wbxPXOVjA0aAE2aUNIstaxcSTWwq3Jc8C+/kPeEK/DyAhYuBPbsUX2LuLAwjAXw2vr16NOnDzZu3IiPP/4Y4Xpt+Ijzs5a+KF7rqk2oiAjt2Z1Hj1adWMwpfn60oaxlfezvTxZrV2QPBihG/amntM1/7mhnrZ5QtxFcaVXJ7NmAj88YUOkbSsgUEAC8mJiJfAAv//YbevTogZF6Z/SMjaXAay27sI8+CjRqpJ9M1nz4ISnXMpGyuHRdNBUdllgmKJBSblW5E1avTsqCWRkTR1gnirp5sytyC64iCyBN1sD8+fORkZGBPnq4dUVG0r8yZZQkMxNFNSIQ1czPmJVZV5fHhx4CRo1Sdens2UCAP8O/6I0X8LbN57q5M0dGajOZ+fmR54DC7Lmy0dDO4vsQhUxcQB2UwFd/N3CAOk5WlvrrGaO/z+xd0ZVq1YDVq43J75TSsCEQjxR8jamIwSmL47qxfz/d8N9/1d+jenWKo9eyYemIyMiq3c7iuK1FRvE9c5WM48eTBU1UatSwdi0N1K6ywC1bBowYof0+Wjdm7aFDOwt5eVgUEYGurVph+/btePPNNzF58mT9ZBTHba19sU4d7cnP7LF8ObBjh/Pz7MEYJRXLzdVPJmu+/BL46SfX3V8reqzD6tcH7rnHde0sJoH4H4ErrSpJTAQ++2wQ6BFuNLq29YnJxBwA2bm5+Oijj/StsQZQ/Nsvv2iLM8jMdN1OM0ALgpwcyqYjEwuLy7ESJPa7bLPTrJs7IUA1/2S+6LaJoqie3ov+o41uKd9++y0ee+wxDB8+HNOnT1chkBVt2gCff67JhfvSrkykFURbZGXWNVavqIjcZ1TEZCYmAt9+dA3VcQNZiEJoKCXa0tyu1kRFaRvQMzIoA6PWGDB7REfTvypkFN+H5XWfwf1YCk9Pk1urrpsT/fvTYlztM7h2DbhxA3uvRVuUtdI9YZRK+WbPBpp4ZwIAMhEFQMdNE5GQEApLOHXK+bn2WLiQlHNXER2teNy2QBAoG6orE9T07q0pRt34nonvXVXk9GnXKdUAcP48JRJS287XrpHS66q4YID+fpXZ8wEAXbvC7+JF/LVtG/7++2/93IJFoqOpnM7ly+rvkZnp2n5YsybFB6vFMG67VMavvwa+/Vb99YsX04ayFm8qR2iYn408+CAlqHMVWsft2w3GWJX7ad++PbtdaN++PbvjjjuMv2+4917mC7D7x493zReWlDDm4cHYyy+rv0dMDGNjx+onkzU//cQYwNiBA+qu37uXrl+1SlexLBg5krFmzWSdKggkjumnlAGBDHicMcZYeXk5q1+/PuvWrRu7deuW62SWYNkyxiIjScbISPpdJMsrmi3HWCvZ6Txd+PFH2e0sKWcVa2dJnnuOMW9vxsrL9ZPJHB3e52XLGAsIsGzjgADLvlCpGNr5Xp9VrpNx8mTGWrRQffnBIc+xYngzD5TbvEe6oMe4HR3t2nFbwft82/LKK4z5+Ljufa6oYGzgQMbmzlV/j+hoxsaN008ma8R2Tk9Xd31yctUft11NeTljpaXa7jF6NGOPP66PPFIcPcrY9OmMnTql7vrbYX5+9lnXvs/FxTRuv/KK+ntUVOgnjxQXL1Jbl5W59ntcBIC9TIF+yC2tGunduzd27dqFoqIirFy5EoNW/oJQIRRLl30AQQBq1dLZouDtTe4Gand+ysspWMuVO7nivdXK6GoXLoCyyn72maxTbd0EveCPVgjw3gYASE5Oxrlz5/Dwww/rG7+ckUFZju0gVd/W3JL6XNnb+BpTbK7TLVZPZjvbk3PrkkzL+7gC0dKqNj7s9Gky/brKFc7bG3jpJUBtNuLycqQ8+S1qF1pa8HRPJFRcrD65TIsWGBqRjPUlvSwO6ypjjRpkxVTZzi0DM+HTKBLlzEO/MjfmaB23y8rIUutKq0fz5lTDWu27sns31YZ0ldVDD15/neRz1fssCMCRI+pjg8V2dsf8rNaS6Q5rdaNG1EZq++KsWZRzwVV4eGh301+xAvj0U33kkSIvj7y11JaIEvtHVZ6fMzNdOz/7+AD16ql/V8rKgOBg4KOPdBXLgogIynLs6em676hCcKVVIwkJCSgpKcHq1atx//2TUM464gI7AYDcb3NyyDtAV8VVi8vj+fP0IrlywtFrUnTlYNm1K9Cvn6xTpWJp78MZlJSmGTcrvL29MXToUH1lnDbNYeFxqfq25orAzsgx+NcqIy+gY6yeTNcZe3JuXWq4ztWT4q1b6rPrudqFC6CF9MCB6q49fx4f5ExCP2y0+Ui3zYmrVynhxTffqLve3x9/Xu6APITYfKSbjNHR1M5q3fVcGYspomXcvnCBxm1XytimDcVTtmmj7vpt24B333XdAhIgt9bYWG0JZgID9ZNHCi3tfPUqbcC4sp21ujyK14nxfq7gnXdI2VIbXrVpE3DsmL4yWTN3rk1G9CqFVuOBvz9tprp6rVjVx+2kJIrDUcP585SUrXp1fWUyp7SUNj+2bXPdd1QhuNKqkZ49e8LT0xMPP/wwbt0qRDX2CYAaFufoUnPSHC3xHr6+wMsvU5pwVxEWRgH8CpIxWZCZSRN3cLCeUlmSnw/88YesrGtSsbRD/AtRBoYtW7Zg5cqV6N+/P4L1ltfJ4sdhCaDLl/HVxB2o6W+Zkl/XWL2wMJrYnEyK9uT8Nvdu4IcfXNvOCQm0uFCbuMwdk+KtW5T6Xw2GZ38atgsL3TYnQkMpIZXaxc+ff+LR0B8lP9JNRq0LtD//VK+Uy2X4cKBXL+fnSeEOq4eIFqtHcLBr32dvb7Koq23nKVNcG18GaFNaIyJIcdUzaZA1YWFAixbqLTPuaGetuGPc3r8f+FF6XHPKzp1AXByQmqqnRJaEh9P8rHateNddlCG6Rg3n56olOtoUC68Gd7RzgwY0/6nBHV4JXl7k4fLbb677jioEV1o18scfQfD0bI+8vDx44n7kowuexXs25+laPiE6mnZwVCTAQe3aVDOxdWsdBbJCEMhypDaDoqsTUQDkgjVsGCXZkYFFoqjDhehbdB3hgYEYOnQoMjMzMUplFl2HREU5bGeHJYD+/hsD3+iORW+e1ydxlRSCIGsDxZ6cZZGxVMbDlbRsSdbqEFsrn1Nu3iQLrav74jvvUMItNe+z4dlf9ouyOKzr5oTYzmoX4l98gdcD39Un87c9tHp3hIbadFTzMle6JI6aORN4801114oTiKut/gMHqn8n3bGA1GIlvHmTklkdPaqrSDZERdEiXM37LOKqzMHivQ8dAtQmDPT2pjrnruTSJWDQILL8K6WwkMZtV78rTuZnhxw7BqSludbqr3Xcdgf9+1NCxw4dlF9bUQEMGAD07Km/XObs2gXMmKGund3hNXg7tLOOcKVVA2KsXknJQAD+iMIEAMBZNLA5V9fyCVOn0sSrJqbi0iXyWXY1u3apX+VNmQI895y+8lgjujapWeRmZiIYQNp772Ho0KEICwvDsGHD9JSOiIoiq8fZs5IfOywBlJkJCAKGP9ZAex1MR8yZAzz5pMNT7Mn57cg/KP7L1Rw7pq6dfXyApCT8FjDOtVlvnbSzQwztPOuLhq7bnBBl1ODuXzM+Sr/M3/bkmz5d3UJVzHhrltnXWby4asrK6Ecp48dTLKarF+JeXsDx4+qudYfSqqUEhViexNXPsG1boE8fdbVav/mGNg2qco3Wjz8G/vnHtd9RrRp5a6WlKb/WHYqCeP+KCk3jtv5Fta2IiaHNGjV060Y1Sl2Jj4/6UjAeHsDSpcD99+srkzVHj5K3lpp2Pn2a2rmBrU6gK1xp5cjBFKv3IoBjaIxiAKayCSI+PjqXT6hblwqYq4kdmjWLJlVXs3Qp8Pjj6q4dPhwYO1ZfeaypVo3cpNS86IZrIuLj8euvv+LSpUsIDQ3VVTwATl0eHZYAysykfuKq2mAiMlweJeX8iqH3l2PUx4oooXt3smYqxdsby093Q+KLUa4rGwRoc201tPPYB3xduzmhoESUBWa1Oy28FTJ1ljEwEJg/X13Yw4EDZAE1i5N0Fi+uip07yc1MpneHBYJA3gKuTrahZfGTm+t6RaFaNcpuqHKzEYDrZRwxAti4keRUyvbt9ONKSysAzJsHdO7s2u/QgtjOavpicTHQqROtkVyJFqu/u+bn1atJ+VcKY7Rh4Op+CNCG4RdfKL+uvNw9mzta5ue2bSkhmKvbmSutHDmYXH59AdRHNGgiNVdaQ0OBRYt0XqDdukU7Pzt3Kr/WHbvhAH1Hbi5w/bqy64qKKPPijRsuEcsCFS/68uVAl6ltMAmL0ea+5li+HPBwVeKRuDiKu42Ls3uKXUXAXe189SpNikVFDk+zkXPgVdIC3NUX1Qzoe/ci+cllKCkstTise2ZeLZPi+++rW5Qo5Z576I+uqFB2XU4O7fS7o53LytQl3JKIO3IYL66WOnVooaVG4Zo92/Uxt4D6cRsgi/V7tqExunPffZTpWCnujAtWiztCYwAar/fsUd7OV6+SQvjXX66Ryxy13h3x8ZTJun173UWyICqKLGhqsqq7q53Vrk2uunF+XrsW+P135dd9+SXF2165or9M5mgJPbnnHtdmiBaJiiJPnP+BWq1cadWAtWdHFDJxC77wbRhhrEZ49aoLrB5eXlSy5c8/lV/rjmyogPqF+MGDQMeOrnc/AhRPiqLL4O7z9fEtHkD62WD9rW7mBAcDQ4bQzodS3KW0/vsvxR4pzdTojgQFImqthCtW4J2cySiHrXVL1xj1+vXJgqZmUqxVC2jVSkdh7NCvH405ShdB7lQUEhPVxTdlZtJOeO3axkMO48XVIrazmr749df0rrkasZ1EV1olCALFO7qaefMoxkwpxcWUZ8GsnV1CRQXF0quJX3bnpjKgvJ1PnwaSk9W5uCtF7bjtLqKiaCJQUzWgbVuK53Q1qamUuyMjQ9l17vJKEL9DredESYm69ZEStIzbubnusQY/8ggZelyZpbiKwJVWDVjH6q3HALzh/RbeetvFj9XLi3b4lL5E7qgBJ6LWdcadyswbbyja4RNdBrtgJ1ohHYALrG7WbN1KrmZKWbqUlAxXo3Zzwt2TYlaWcithZibOe0VCqpy1rqFIXl5UT09pXHRZGS2MXZmBUkS0EF69quy6Dh3I7VZmeSlNREaqbmdj0LIBh/HiatEybp875553pU0bying76/sus2badNAbekKpVRUKF8MzpxJ2eJdWZIHoPsXFipXFMR2rsqbyu4ct9u1UzfQTpkCuCIxop7MnQu8+qrrv6e0lLy1qrLSGh2t27jtEsRxW+ncV1ZGIWhvvOEaucypXt31pbyqCFxp1YB1rN6JyH5oufhp/S2rUkRFKS+TceYMLT7duZNrltxEFuLf5MoacCLNmilyMxOta/PwGD7A0zbHXcKrr1KJIqX06EFuUq5GbGelfdGd7RwVRVaWCxeUXXfyJPybR7k2663I1KnkdqeErCyKB9q3T2dhJMjNpaQeS5cqu04QyLLljglVbTvn5NiMiQ7jxbXKWJXH7aZN6Q9t3FjZdbt3A99/r740hBKWLSOl+vx513+XWtS0c34+hYI0auQKiSy5Hcbt558HNmxQft3+/e4JLwKAl14CJkxQdk1ZmXIFTS1q27l2bUoI5q61oppx+9Qp97n6Z2SQO7ISsrJo3K5f3zUymVNSAjzzDLBmjeu/q5LhSqtGjLF6RcXIXLEHifeWOr1GF+LjycKiJA13SAgtSHr3dpVUJkJDST6lyZiSk2nnzZW1wUQKC8nClZws6/SGDQE/FKE10pGCeIvjLkOs5aaknffvB37+WVvJBbmEhgL16sl+hkamT6cC8O5o5zvvpNqMSsreFBUB6enIjYy3MDqJRpQXX9TZLTw/n+LElLSZ+MwdxDzrhtp2fu89YPFi18hkjbhJo1TGjRtJ4bLCJYmjHnhA+SJ3zx761x3tDNAfrHQBmZxMmxrueJ9jY+k9UdLORUW0KaQmdk4NasbtmjUpn8PEia6SykStWsDgwcqTRe3Z4752FlFiUTeM2257V27eVD7X/vwzWeDU1uZWQq1a6sbtO+6gGupBQa6Ry5y4OHoeSrLzurud1dR5F8dtdxgPvL2pvVwWq1Z14EqrXuzZQ9n41NQVU0O3buT6oaTmXEgIuc7ExrpOLhFBoLgNJWV5GAOSkijbqzvw9CSXsZ9+knX67NlAD9+98EEpkkAyusTqZk737pR4KyVF/jWLF9Pi2B2Z/wSBZNyxQ9l1QUFAQoJrZLImJoYSIiix9qWmAqWleHV9d4sKUeIGue5ZhNevp2LuSto5KYn+JndkAxfbOSlJ/jWMAR99RK6j7qBdO4pNVSIjQH9bzZqukcmaiRMp/kgJly7R4tMd7QwAkyYpy8Ls7nFbTTvv3UsLd1e7EoqoGbfdWeZGECgnhtJyIZGR7nO9ZYzWVM8/L/+a5GRaF7mrL4rtrCREY8cOsiy6w1qtdtw2y6Tucrp0obCCrl3lX1NcTGURXVFqUIpjx6hSwv798q8R5+c2bVwnl4jaddhtCFda9UIcFLp1c8/33XUXkJen7IX4/XcX+7JakZFB6b6VuHGtXEmKpDvw9aWYO5kDemIi8N5wOncXurqmHqY14uSrZNJJSqLJ3h1JUQByYV6/Xv6i6+xZ4LXX1NU9U0t6OrkVyqVrV3SpdxZ/lfS1e4qu8cxa2llNvWY1dOtG48e5c/LOP3WKFiPuGhN9fYHPPgNGj5Z/zaJFwIMPkhuXu7hwQVkt1BkzaBHprnZu147eTbnvp9jO7lIUFI7bAEznKlkYa6F7d7KoK4kN7tWLXPzcSWkpKQBy+fhj4N13XSePOWJir23b5F8jLtrd2c5A1R63+/Qh7zW59VpPnaJM50pDQdTi4aF8gz04mPI5uGtuqV6dygcpKVe2Y0fVnp9vU7jSqhc7dlA8kJrabGrw96daZnK5cQMYORJYuNB1MllTUEC1E7dvl3e+ILgvFlOke3eKCXRSskUkvoja+Qqr5Zp6mNbUqUMTzq5d8s4vKKD6au5aQAJAixbU9+VOPP/+C7z+Om26uItly0g5kdnOALDnQn0UIcDhObrtAYntLHentLiYzL3umrQB5Qs08Tx39sUpU5TVn1y1ip65q+ufmtOjB9XLVoI75RPbS25fvHKFMli7s50VjttISnLv/FynDvDdd/I3lQsKSEalCbC0kJFBi//ffpN3flGRe63BgKmdb92Sd37jxuQC4852jo6WPyaK87M7x+1p02jOletpJP4t7nK9BYAVKyjjttx2PnDAfXHLgPJ2BshDwF0GGEDdBsptCFda9YAxmuDdOWkDwC+/kCIqZyLZvZusCe4cLNu2Jf9ZuS/RqlXAunWulcma7t1pt3nvXnnnL1ok251YNzZskG8l3LOHfFjd3ReXL5eMC5QkKYncg1u2dK1M5ihp54oKYNIkjA1znrVZ13hm0Y1Lzvvs60s1SZW4zmmlbVuKm+nTR975O3ZQ7Js727m4mGJU5WRFraionHFbSTtv2ULuc0qzf2pB6bjdpQt5Mrij9JLIiBFkaSmVkUOistqZMeDECXntXBnjdkwM/Su3nWfMoA1Kdyqu3bpRvKjc+XnkSOCrr1wrkzWJiZTUUQ67d1fO/AzIT/6UlOT+cdvXFzh8WP78nJAAPPmk6+Uyp1s3+eM2ANx7L3lEuou2bSl++do1931nJcCVVj3IyKAMlO5UCAFatP76q7waV0lJZAlzl9sMQK49nTvLnxRfeYXcj9xJt27knnLkiLzz3RlbJhIbKz8RwL591M5KYtL04JtvgA8/lHduUhL1Q3fFlwGmfi+nL2ZkAN9+i8eHZdlkDjZH93jm7t3JDVRuzTpPT/emuff2poySYWHyzr9xgxJ6uLOd8/Op/uGPPzo/NyODJnh3LyC7dZPfzlu2kEITEeF6uUS8vSlpkdxx212ZUM3p3Jli2uQkirlxg0ouDRrkernM+eYbsvwpmZ/dOW4rnZ+TkihbqztyJYiIayo5MubnwyIBgbt4803grbfknVu/PrmAu3t+fvRR+evTypiflbRzZY3bSubn5GT3lKIzx9ubQjqU5ky4zeBKqx5ERQH//AMMGeLe7xVfWjnut0lJtBPuzqx/AMmYlkZuMY7IzQUOHXL/QFSrFn331KnOz12/HpgzR1kMkB7cuEE1V//+2/m5zzxDbqPBwS4XywIF7cwOHcKHu7rDw4NeHbckvAsLA5o0kf+uAOjydA+LsiehofSjawkUc0aOpGcoJ0HH9OnUF93NuXMUN+qsnQHyDnBXtlYRFe1cKYsfoGqP27Nm0WLcGbm5NIZWRtbKq1flhU0EBZF3jLtrd4olrKpyO1f1+TksjCxqcqz4K1ZQX3RHVl5rysuB69edn9esGWVUd/f8HBJCVsyq3M5Vfdzu2ZM2G3JznZ/74ovuyQJujSBQSSV3VI6oLBhjVe6nffv2jCODsjLGGjZkrH17xsrL7Z939SpjgYGMPfus+2QT2bGDsdq1GUtJcXzeG28wBjCWnOwWsSQpLLT/WVkZY23aMBYTw1hFhftkEr+7YUPGOnRw3M5lZe6TyZodO6j93nnH4WnrX9rC8lGNtUcyIz8bxgICGFu2zA0yzphBfbGgwP45ldnOcklPZ8zDo/LeZxntzC5fdo88UsyYwZinJ2NHjzo+b9kyGjsr431u0ICxhATH51VmO8vl9dcrb9yeMYMxLy/H7VxWxtjOne6Tyfq7GzRwPm4zxtiXXzp/p1yB+D6/+67j88R23rvXPXIppTLH7YoKxlq1ct7Ohw8ztnat++QyJylJ3rhdVsbYokXO12uuQO77XNXn5wMHaNx+7jn3f3duLmPNmlXOWKISAHuZAv1Q3knAnQAyAJwA8LzE5wKATw2fHwDQzuyzTADpAFLlCndbKa3ffcfYo486VnhcydKl1IzOVv2ZmYzl5Bh/XbaMschIxgSB/nWp0uDs2Vy4QEr1yJEuFMIJY8YwNny4/c8XLaLn/NNPjDE3Pz/G5LXzXXcxNnOmiwVxwNChjAUFMZadbfeUyEjGaiDXqLCKP5GRbpAvJ4cGdUdYtbPbycuj98BRO995J2PBwbQZVRk4a+cLFxirVo2xuXPdK5fI5cuMVa/u+H0WqayFz86dDt8TxhhjgwZVbjufO8fY5MmO2zkwkLFRo9wrl4icdhbf561b3SaWBUuWyJufK5O5c6mt7ZGTU7ntzBhjFy8yNn++/c8re9wW23n5cvvniOP29evuk8scGfNzpXL5MmMTJzJ25oz9czZsqNx2ZozG4z177H8utrPZetutDBlStdvZCt2VVgCeAE4CiAHgAyANQAurcwYDWGtQXrsA2G32WSaAWkqEum2U1gMHGKtbl7HOnStv8VNeztikSbSTZk1ZGWO7d9vItmwZWbfMlQaXW7tKSmiguXbN9rPt2xmLjmbs+HEXCuCEt9+mB7F4sa3FUmznLl0Yq6ionOdXXs5Yu3a0c3/woOVnZWWMff01CfLBBy4UwglHjjAWF0fPy5qcHMbWrmUCKmwUVoCUf7dRVsbYli3Sluk//mDsvvsq93121M4LFlSNdvb0pI0e6/c5J4cWt97elf8+N24svUmRmkqbQM6sX+7g+HHbdhZZvZoWw5WFo3bOzTW184kTlSIeY0zRuF0plJczFh/PWM+etp+J7/NXXzFWWup+2aw5elR6fmaMlIWTJ90rjzlz5thv5+PHq0Y7t2tHHlFVddw+fJjeZynPjZwcxqZMcbwx4E5OnrRtZ3G83ru3cq2sfftKtzNjjH3/PbXzhx+6Xy4RsZ2lxu0qiCuU1q4A1pn9PgvALKtzvgIw1uz3DAB12H9VaR09mrGWLenxBQYytmtXZUtEFBbSwN22Lf3UrUsyPvMMY8xkHZRSGlxu7fr4Y9PzEuVr29Y0EVamaytj9OzatCEZ69VjrH9/Ol5ezlijRiT37t2MMfvPULS4uswCu307acc9epiOtWtnaud27Ri7dUvHL1SBOJmcP2/ZzgYt//9CF7u/71lz//2mdhblGzCgaigxjJnaGWCsRQvGHnqIjufn0w5qfHzlt/MLL5B8DzxAv4vtLcr96quVKR09n+Ji+v/KlaZ2bt6c5KtWjZTXymbCBFM7izKOH1/ZUpkQ21kct197jY6fPk0LI/H3yqKwkLHWrZmF6+OuXZbtbBi3K41TpxgrKqL/f/yx7fxcFcZtxhjr3t1yfm7ThrEnn6xkoQyYt7M4bi9cSJ9t324xP1ca5uO26F77889Vq53/+MMUHvN//2czP1f6+8wYbeBERlrOz82aMfbWW5UsmAHr+bltW8bWraPPli+vGvPzrFmmd6UqbIg5QKnSKqfqbT0A5lXGzwGwLoQndU49ABcBMADrBUFgAL5ijC2Q+hJBEKYCmAoADXWtI+ECatSgmk333091AWvWrGyJiOPHgdq1Tb83bUrZPocNw/LllGuosND+5brVnJRixgxKU/7FF5SBTcTbm/51Zx1CKfz9KfPub79RQofq1em4hwdlIo2ONrazveeUlWX5jMXfAZ0S9nTvTl+enW06FhkJNGpkbOdKf45iZsnUVMqyJNKtG/DII4g/0BoBVv1Q9yy8zli0iJ7VihWWCQvOnLGUubIQ2/mrrywzx1avTkkomjev/HaePZtS+ovplb286NkZ2hmtW1eqePD1Nf2/enXLdp04kV7MkBC3i2XDRx/ROL1nj+lYaSnVxHRnzU57iO0sjtuhoXQ8KoqyaDZoUKniwd8f2L+fyqX16EHH/PwoqUtVaefoaNP/Q0JMfdFsfq709xkA5s0DvvzScn6uCnIBpnYW5+eSElPSqm7dgPPn3Z/EyhrzcVtcP1SvTv2yqrSzebLQsDBTX6wq4zZAa4gPPrCdn91Ve9cZ1vMzYMrif9999FPZ7fz22yRHRgbNzf8hBFJ0HZwgCKMBDGSMTTb8fj+AToyxx83O+RPAHMbYdsPv/wB4ljG2TxCEuoyxC4IghAPYAOBxxthWR9/ZoUMHtlduXS6OLKKiSIlyRGSkvPKG/+vYe5aenpRE0Br+XC1ZvpyS6505Q3VOZ8/WOQsvh8PhcDgcDqdKIwjCPsZYB7nnyyl5cw6A+XZqfQAX5J7DGBP/zQawCkAnucJx9MOZFdXt1q7bmNmzYVO/UxCkFVbAxRbs25DERFLiKyroX66wcjgcDofD4XAcIUdpTQbQWBCEaEEQfACMAbDa6pzVACYIRBcA1xljFwVBCBQEoToACIIQCGAAgIM6ys+RiSOPa5fUnPwPk5hInmfmNdYZs19zvap7u3M4HA6Hw+FwOFUZp0orY6wMwGMA1gE4AmAFY+yQIAgPC4LwsOG0vwCcApW8+RrAdMPx2gC2C4KQBmAPgD8ZY3/r/DdwZCBlHQwIAJYt49YuNfz1Fymq5kgprtyCzeFwOBwOh8PhaMNpTGtlwGNaXQOPJdQPDw9bpVUkMpI/Yw6Hw+FwOBwOxx5KY1r/W2mlOA5JTOQKlF40bCidjIknXeJwOBwOh8PhcPRFTkwrh8Oxwp67NXcF5nA4HA6Hw+Fw9IUrrRyOChITKXlVZCTFsfJkVhwOh8PhcDgcjmvg7sEcjkq4uzWHw+FwOBwOh+N6uKWVw+FwOBwOh8PhcDhVFq60cjgcDofD4XA4HA6nysKVVg6Hw+FwOBwOh8PhVFm40srhcDgcDofD4XA4nCoLV1o5HA6Hw+FwOBwOh1Nl4Uorh6OR5cuBqCjAw4P+Xb68siXicDgcDofD4XD+O/CSNxyOBpYvB6ZOBQoL6fesLPod4OVwOBwOh8PhcDgcPeCWVg5HAy++aFJYRQoL6TiHw+FwOBwOh8PRDldaORwNnDmj7DiHw+FwOBwOh8NRBldaORwNNGyo7DiHw+FwOBwOh8NRBldaORwNzJ4NBARYHgsIoOMcDofD4XA4HA5HO1xp5XA0kJgILFgAREYCgkD/LljAkzBxOBwOh8PhcDh6wbMHczgaSUzkSiqHw+FwOBwOh+MquKWVw+FwOBwOh8PhcDhVFq60cjgcDofD4XA4HA6nysKVVg6Hw+FwOBwOh8PhVFm40srhcDgcDofD4XA4nCoLV1o5HA6Hw+FwOBwOh1NlERhjlS2DDYIgXAGQVdlyOKAWgKuVLQSH4wTeTzlVHd5HOVUd3kc5twO8n3KqOlJ9NJIxFib3BlVSaa3qCIKwlzHWobLl4HAcwfspp6rD+yinqsP7KOd2gPdTTlVHjz7K3YM5HA6Hw+FwOBwOh1Nl4Uorh8PhcDgcDofD4XCqLFxpVceCyhaAw5EB76ecqg7vo5yqDu+jnNsB3k85VR3NfZTHtHI4HA6Hw+FwOBwOp8rCLa0cDofD4XA4HA6Hw6mycKWVw+FwOBwOh8PhcDhVFq60KkQQhDsFQcgQBOGEIAjPV7Y8nP9NBEFYJAhCtiAIB82O1RQEYYMgCMcN/4aYfTbL0GczBEEYWDlSc/6XEAShgSAImwVBOCIIwiFBEJ40HOf9lFNlEATBTxCEPYIgpBn66euG47yfcqoUgiB4CoKQIgjCGsPvvI9yqhSCIGQKgpAuCEKqIAh7Dcd066dcaVWAIAieAOYDGASgBYCxgiC0qFypOP+jfAvgTqtjzwP4hzHWGMA/ht9h6KNjALQ0XPO5oS9zOK6kDMD/McaaA+gC4FFDX+T9lFOVKAbQhzHWFkAcgDsFQegC3k85VY8nARwx+533UU5VJIExFmdWk1W3fsqVVmV0AnCCMXaKMVYC4EcAwytZJs7/IIyxrQCuWR0eDuA7w/+/A3C32fEfGWPFjLHTAE6A+jKH4zIYYxcZY/sN/y8ALbbqgfdTThWCETcMv3obfhh4P+VUIQRBqA/gLgALzQ7zPsq5HdCtn3KlVRn1AJw1+/2c4RiHUxWozRi7CJDCACDccJz3W06lIghCFIB4ALvB+ymnimFwu0wFkA1gA2OM91NOVeMTAM8CqDA7xvsop6rBAKwXBGGfIAhTDcd066deOgv7X0eQOMZrBnGqOrzfcioNQRCqAfgFwAzGWL4gSHVHOlXiGO+nHJfDGCsHECcIQjCAVYIgtHJwOu+nHLciCMIQANmMsX2CIPSWc4nEMd5HOe6gO2PsgiAI4QA2CIJw1MG5ivspt7Qq4xyABma/1wdwoZJk4XCsuSwIQh0AMPybbTjO+y2nUhAEwRuksC5njP1qOMz7KadKwhjLA/AvKL6K91NOVaE7gGGCIGSCwtL6CIKwDLyPcqoYjLELhn+zAawCufvq1k+50qqMZACNBUGIFgTBBxRAvLqSZeJwRFYDmGj4/0QAv5sdHyMIgq8gCNEAGgPYUwnycf6HEMik+g2AI4yxj8w+4v2UU2UQBCHMYGGFIAj+APoBOAreTzlVBMbYLMZYfcZYFGjduYkxNh68j3KqEIIgBAqCUF38P4ABAA5Cx37K3YMVwBgrEwThMQDrAHgCWMQYO1TJYnH+BxEE4QcAvQHUEgThHIBXAbwDYIUgCA8BOANgNAAwxg4JgrACwGFQRtdHDe5wHI4r6Q7gfgDphnhBAHgBvJ9yqhZ1AHxnyFrpAWAFY2yNIAg7wfspp2rDx1JOVaI2KLwCIP3ye8bY34IgJEOnfiowxt3cORwOh8PhcDgcDodTNeHuwRwOh8PhcDgcDofDqbJwpZXD4XA4HA6Hw+FwOFUWrrRyOBwOh8PhcDgcDqfKwpVWDofD4XA4HA6Hw+FUWbjSyuFwOBwOh8PhcDicKgtXWjkcDofD4XA4HA6HU2XhSiuHw+FwOBwOh8PhcKos/w8uOhgY9DWvPwAAAABJRU5ErkJggg==\n",
247       "text/plain": [
248        "<Figure size 1152x288 with 1 Axes>"
249       ]
250      },
251      "metadata": {
252       "needs_background": "light"
253      },
254      "output_type": "display_data"
255     }
256    ],
257    "source": [
258     "import numpy as np, random\n",
259     "days = 20       \n",
260     "hours = days*24\n",
261     "h2 = int(hours/2)\n",
262     "hour = range(hours)\n",
263     "day = np.array(range(hours))/24.\n",
264     "\n",
265     "# artificial equilibrium data\n",
266     "E = np.power(np.sin(np.pi*day),4) # diurnal curve\n",
267     "E = 0.05+0.25*E\n",
268     "# FMC free run\n",
269     "m_f = np.zeros(hours)\n",
270     "m_f[0] = 0.1         # initial FMC\n",
271     "for t in range(hours-1):\n",
272     "  m_f[t+1] = max(0.,model_decay(m_f[t],E[t])  + random.gauss(0,0.005) )\n",
273     "data = m_f + np.random.normal(loc=0,scale=0.02,size=hours)    \n",
274     "\n",
275     "%matplotlib inline\n",
276     "import matplotlib.pyplot as plt \n",
277     "plt.figure(figsize=(16,4))\n",
278     "plt.plot(hour,E,linestyle='--',c='r',label='Equilibrium')\n",
279     "plt.plot(hour,m_f,linestyle='-',c='k',label='10-h fuel truth')\n",
280     "plt.scatter(hour[:h2],data[:h2],c='b',label='10-h fuel data')\n",
281     " "
282    ]
283   },
284   {
285    "cell_type": "markdown",
286    "metadata": {
287     "id": "z-3WLAEpD2yJ"
288    },
289    "source": [
290     "### Run Kalman filter"
291    ]
292   },
293   {
294    "cell_type": "markdown",
295    "metadata": {
296     "id": "T4g-RrrYAlBD"
297    },
298    "source": [
299     "We have used the same code for model and for the truth, and run the Kalman filter for 10 days. The graph below shows that the model state was remarkably close to the truth, even if the model is fed only noisy observations. This is because the dynamics of the model and of the truth are the same. After 10 days, we let the model continue without any new data to simulate forecasting the future, and the agreement with the truth was still very good."
300    ]
301   },
302   {
303    "cell_type": "code",
304    "execution_count": 5,
305    "metadata": {
306     "id": "_-CjONZkD18n"
307    },
308    "outputs": [],
309    "source": [
310     "import numpy as np\n",
311     "import matplotlib.pyplot as plt \n",
312     "\n",
313     "def kf_example(DeltaE):\n",
314     "  h2 = int(hours/2)\n",
315     "  m = np.zeros(hours)\n",
316     "  m[0]=0.1             # background state  \n",
317     "  P = np.zeros(hours)\n",
318     "  P[0] = 0.03 # background state variance\n",
319     "  Q = np.array([0.02]) # process noise variance\n",
320     "  H = np.array([1.])   # all observed\n",
321     "  R = np.array([0.02]) # data variance\n",
322     "\n",
323     "  for t in range(h2):\n",
324     "    # use lambda construction to pass additional arguments to the model \n",
325     "    m[t+1],P[t+1] = ext_kf(m[t],P[t],lambda u: model_decay(u,E[t]+DeltaE,partials=1),Q,\n",
326     "                    d=data[t],H=H,R=R)\n",
327     "  for t in range(h2,hours - 1):\n",
328     "    m[t+1],P[t+1] = ext_kf(m[t],P[t],lambda u: model_decay(u,E[t]+DeltaE,partials=1))\n",
329     "  \n",
330     "  %matplotlib inline\n",
331     "  plt.figure(figsize=(16,4))\n",
332     "  plt.plot(hour,E,linestyle='--',c='r',label='Equilibrium')\n",
333     "  print(len(hour),len(m_f))\n",
334     "  plt.plot(hour,m_f,linestyle='-',c='b',label='10-h fuel truth')\n",
335     "  plt.scatter(hour[:h2],data[:h2],c='b',label='10-h fuel data')\n",
336     "  plt.plot(hour[:h2],m[:h2],linestyle='-',c='k',label='filtered')\n",
337     "  plt.plot(hour[h2:hours],m[h2:hours],linestyle='-',c='r',label='filtered')\n",
338     "  return E, P"
339    ]
340   },
341   {
342    "cell_type": "code",
343    "execution_count": 6,
344    "metadata": {
345     "id": "d0EFhTPZAlBD",
346     "scrolled": true
347    },
348    "outputs": [
349     {
350      "name": "stdout",
351      "output_type": "stream",
352      "text": [
353       "480 480\n"
354      ]
355     },
356     {
357      "data": {
358 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ujrnZPfNMHCgOP6anhMShPXRSYPqPQ9FzZh0yrNolK3u1k2YwZ2CnBzYs6fh56go+XIS/vxnKQXXkJsrfXtaCaTdOBacVm3f1mZCp6TImnaSjB984L6/tG8v5cxOeR47dZKAyRlnNLz22mvSk+kUGJ3PTtOzWbDRKTJu2iRZf/1M0bPPhqws+2TyxN13SyBZ0zPITPV//9s+mTzhqWennc8OgUN2t/9BeD6gigJPPgknnGCfTHrU1Aijnj7rsXq1HOLff2+bWG7o21dGoeg3R834cYqTY6RnJxloNTWSgdHLOG4cfPutkAk5AZ99JmXVmzc3vPbSS5JpcIqezzoLXn654Wen6lmf9XCa8WOUmfnPf5xVqnfPPTBxovtr06cLs6xTcP75cNppDT8fC3rW+uidsp49AzyKAlu3wt//bp9MetTUwOWXS0ZYQ1GRVEI5JVAWHy+jTzSSSZDPdP9+5+jZ7Hx2SnWH0b49ahR8911Di4LdWLNG9j89E29uLsya5Rw9Q0OLFjjvfK6rE5n0pfNO27cdgojTahdyc903IoAjR5zT63jwoGSDS0sbXmvbVr47eRG1by8ZWK0cxG706+duQAJMmQLHH2+PPJ44eFAOFqf3YpaXuxs/1dVSCldYaJ9cepSWeh/QTjoUq6vh4Yfh5JMbXsvIcI7hA8YZOKfB08gFITFzSiCvvFxKMIuLG15zmvEzdqyUiOqDYu3bi4HulPVspOeOHd0NXzuh7dt6G6KiQjJK2ixKu7FkifQq6yt2OnSQSi2n6Pm117zXrpP27QMHvM/n1q0le92ypW1iucFo3/7kE2HedoqeH364YRavBicFJ6Ki5HPUtzxpn6dTZHQIIk6rXTA6FK+5xjmz6ow2ojZtGhaXE/DEE5IN1jsLTjPQ/vpX6UnR4/HHhc7cCTDKetTVCcvs3/5mi0heyM2VElE905/TNvQhQ7xn2zqJhblZMyHK0FdytGsn2etzz7VNLDcY6XnpUslsbtlin1x6GAUbO3RwznO4caPoeN68htectm9nZAhjefPmDa/deCNUVkJ6un1y6WF0Pn/9tezdToDZ+awoztHzF19ImbrGegvOO59TU70ril5+WSo8nACtn9HzWfzuO+cwguflee/bTittfe89WLDA/TUnnc8a9HwxbdqI7eikMmsHIOK02oX27YXEQw8nLSKjQzE6WhaSUwy0TZtkU9cv9IED4Y47GuZlOhVO6RdNTISpU90zblFRYkA6haQgL08cLL2enWT8qGrD+Ak9hg+XTLsTUFoqa8VJzNqeOPNMYUzU67myUkYB7Nplm1j10PTsaUA6KTNjtG/HxIijWF5uj0yeWLRIvvRISHDWnNaPPxbCLT1++QX+7//skccTRv3fMTFyPjvpWTTbt51gQ6iqZOAWLnR/fdCghlFHdmPoUJn17Vmtdd11znGstT3RyXr2ZFQHZ+3bCxbITFZ9X3BMjCQ3BgywTy4HIuK02oUFC4QwQ4/27cW4dIJxYTbCw0kL3bPvCKTP9bnnnNGPWVws0ce33nJ//bnnpN/HCXru21eYrPv2dX/dSXo2cxS0a3ajpEQIyjxlvP9+YTl2Aj76SOTzJCm78UZhlnUCTjhBAk56OEnPxcXGej4W9u2cHOf03T78sDezaHEx3HorzJ1ri0heGDHC21hs317WuhP0bFZK77TAt6ejMGyYBJudwN1RXCzVRIsXu7++aRO88IKsdbuhKDKyyrMs3Ul6Likxfg7BGTIWF0vw01PGq68W28wJfbfZ2fDll94kajt3yizhCOoRcVqdBCcZaMnJ0nfZrp3767feCpdeao9MnjByZkA2KD0pgF3IyxNyDM8DJyVFMl5O0LOeNVgPJ/V7nH22ZIP16NBBemacMGftWJnRCt7Z4L17pffMCVi3Dg4dcn/NSRH7+Hh491157vTIzJRyeifMatX07LlvO2VMGRg7M7Gx0nPmhGfx0CGZjem5PzvpfJ4yRcpDnRxUNjqfExOFQM8JvcFmjv/ixVLW7IQ956uvJOPvZL6Er7/2Jstz0lox0/PQoUJa54S9UXvWPPft226TtsEI6hFxWu3AwoXSi+nJ8uekhX7JJWJAeI6buO46YS10AowyrSCG+fTp4ZfHE2bOjJOikLfeapyVdtKheMcd7iM8QIyf7793H6dgF8wOxaVLoXt371JIO5CXJw6+53p2kp5PPNF9QD1I32NysjNkTEyEK67wrkq47DKJiOuZH+2CpmfPUtv33hPZnQAjZ8ZJel67VrIwerZycNb5nJIiWUvPmazvvAO//26PTJ4wCyq/8grMnBl+eTxhtm87KVA2axa88Ya3Y+WkoDJ47zeJidJ3e9ll9sijR2mp9Mp7BsoOH4bZs50x79Zs33aanh2AiNNqB3bsEIPW8wEdOFBKRzMz7ZHLCo4ehW3b7O+Nq6sT0qqRI72vtWvnDMPC36HoFBlbtPB+fcIE6bGwu3Smrk4yWHbL4QudO0vJY+/e7q8nJMha18/1tAtmBmSHDsJEaneP9dGjomcjGUePdgZT5u7dEnCsrrZbEnPcdps4Lp7YskXmeppVVoQLR48Ko6iRnp1ioPkLNubnh1ceI3z8sZQTeqJVq4bZsnZj0ybvIBQIucz774dbGm/4KrHWX7cT/vZtu9dzZaVU3v30k/e1M86Qs9FujBola/bEE91f37ULTj/dGSPVzPTcvr0z9OwgRJxWO2DE2ArygN5xhwzlthtnnikGkCfeektICuyOTkVFCa26J2MrOKff41hxWj2fQ5AI6Ysv2l86s2ePcV8wSDXAhAnhl8kTPXsKS/SxaPy0by+BgYMHwy+THhpLptGzOGsWPPpoeOUxwscfy7gWz1638nIxfj780B659BgwwLt8GeRzdbqenZL1Nzuf+/UTI/2888Iukhf++U9jIp5Vq+Cuu5wx8q11a+P2DafoWbNhjOwwcIaMZtVkN9wgurb7fM7LE74Eo8Ds4sXOyKibwUkZ9ZQUSVp5winns4MQcVrtQF6elEMZZbg2b4bt28MvkyfWrIGyMu/XnbTQzeCUiH2vXnDlld56Tk+XclejTSrcMDsUQaJ7dmfgfPWLRkc7g1U2L8+7FxNEz7GxzjB+7r4bbrnF+/XevcXxr6oKv0x6HAszWnNzjfftZs1gzhzZM+3Gl19KhssTTtm327UTEkKjsv5OnZyRUTA7n6Ojvcvr7YJZEConB555xv59cds2qT4xYqB3yoiou+6S6g6j8zk21hkymgWVO3USlmNP4p5ww9f5/Pzz3oRrduDf/zZObjjpfH7vPePqAycFvh2CiNNqB/bv92641nDqqfbPx1RViUIayahtTlrE3C589ZWUQm3c6H2tfXv75QOZf/nOO97RUEWRDX38eHvk0uBLzytWiIE2e3b45dJD06PZs+gEPd99t5SwekJRRG4nyDhlCpxzjvfrEybIKI8uXcIukht86fmVV6R/z26Y7dtO0bOqyvxTo/Jgp+zbCQkwZozx5/jOO87o//Z1Pj/yiFSg2Ilj4Xxeu1bsGKOMr1P2bUUxbjtQFGFztZsXQ1WlisNIz4WFQly2dWv45dLjWDifFy70ntEKztm3fWHUKJlA4IRpGA5BxGm1A927e9fXa0hPlw3JThw+LBk2o0Hv2gBpu2UsKJCvxETva2eeCX/5i/19kL6yBkePChW7naipkUiokfOcnCxlKXbrWfv9Zs9iRYX9owkKCozlAyklHDw4rOJ4oboaVq50BrutGYYNE2bebt28rxUWivyVleGXy1MOMz2npdm/Vnzt261bC1eC3XtidrY4pxUV3tfsLnXU8PTTQiJjhK++sj+Qdyycz/727fJy+9fzM89IFs4IPXsaV8KFE4oin+Njj3lfKygQEkW72ba1M8XJej4W9m3NOfVEu3bCLZKaGn65HIqI02oH/vY3YYQzQmqq/cal9vuNFor2mt0Oly8Zx4+XGZl2G0Fjxhhnt0D6zs4+O7zyeCI2Fv7v/2DiRO9r2ufq5GdRi5Lb/SwWF5sfKk4okcrLE6fwiy+8rxUXQ48e8PrrYRfLDZ07C7ttSor3NU3Pdj+LvvTs9H27WzcpGT3rrLCK5IUffhBmXiMyqzlzJMhjdz9m+/bepGoanK5np+3bRpnMP/xBDHW7S60//NA8OPHpp/bviRqM7Bin6FlVpeLNSM9OkbGoyHzffuUVePzx8MrjicJCCT6UlHhfq6mRIJndGXUHIeK0Og1OOBSjoyW606uX97WWLcUQN8sUhwtFRSKnUTT06FFhbTWK5ocTRUXGmWBwhp6rqmSjNGKCdoqjMGaM9EYlJXlfGzxYCCmio8Mvlx6+DkUnwJeR27y59NDb3b+1aZOUcRnBKcbPs88as6GC9JfZzfruS89Oga99+8ABmfloN+nIK69IybwRnLBvd+okJY0XX+x9Tdu3jxwJq0he8KXn5s1lP7c7qOxr3/7wQ5nkYCe2b5f55Ea98k45n6+/XvgckpO9rzll3/al51GjhLzOTvjat1XVOSR/DkHEabUDQ4bA3/9ufM0Jh2LHjlKqkJXlfS0mRkiEBg0Kv1x6FBXJxm108M2bJyXYq1aFXSw3+NosnaDnhQvlM5w3z/taTIwYHHbLOGaMMPMa6XnsWHj1VWOGynDCl57vvltKzeyEr0MxNlYMSLv1/Nxz5lUJTjF+Ro8WI8cIzz1n/xgPf07rhRdKSaSd8LVvO0XPDz1kXKoHzti3o6JkFrmRQxgTI8HIBx8Mv1x6FBeb63nHDtkXt20Lt1TucPr5vHu3jKkyKl91yvnsC6edJjaY3f2YGRlSTWSEVauEFd5OHAvns4MQcVrDDVWF9eul1t8IN9wgDfZOxpYt8mUnjj/emBEOnGH8qKrzD0V/Ru6dd9qfUc/NNWbm1VBXZz/D8RNPCNGRERQF9u0Lrzye8Kfn1FT7+3p8ld527CiEUfHxYRXJDaoqJYN2G9q+MGwY/P47DB1qfH3ZMli9OqwiecHfnqjdYxdU1fez2KaN93z1cGPNGqk+MdsX7ZYP4IUXzBmMDx2SvuHNm8Mqkhv86flYOJ+dIOPf/y5JDCOkpUmCJiEhrCJ54ddfzclNZ8yAa68NqzheOBb07CBEnNZw48gRIegxe0BHjhTWWTvx7rvSp2BmbF98MdxzT3hl8sTVV8O//mV8zQnGjz89p6ZK+bKdJAWao2Im41//CuefHz55jHDtteZ9eNu3i4H20UfhlckT119v7tw7Qc/HwqHoy5kZMEDKNe1kED58WPa9r74yvv7eezLCyk49JydL9YFRXzCIEelkPTth3z582Pe+/cQT9o+TWb5cjHCzwPcTT8gcVzsRFWXc0gHO0HNZmQTBfD2L5eX2jgLzt2/Pm2d/5cTvv8PSpcbXjhyBl1+WJI1T4QQ9N28udr9ZxZgTzmcHIeK0hhv+NqKDB+Gnn8wPpHDg0CEhw/B16Ni9iHxl15xwKALce695OeHJJ8OTTxr3k4YLvsgyQHqD7c7A+TJyU1Lk87NTzxUVwmxbWmp83QnP4oknCmNr27bG1884QyoX7ERRUQPzqRPhb98+fFiMMzv1vHKlBBzNWMudsG+/8YaUPBohLU0IuezsUT9W+oLBXMbZs6U32E48/rg5kZET9sSkJHFc777b+LoTZPSn5y5d7H9OfZ3PFRUyG/zXX8Mqkhtyc8UGM2P8doKeTzsNFi82nscLzti3HYSI0xpu+NuIfvlF2FxzcsInkyeKiiRSakb57oRF1K8fXHml8TUnkBS0aCHMvEZ9wSAb6f33Q7Nm4ZVLD396vuwy+8uDfR2KTtDzli2SAfz5Z+PrTjgUu3eXtWJWpvXEE9LHZyd86bm2VvqCzSorwgEr2Wr9fXbg88+lMiHK5Fh3wr7tq7+sVSs59y69NLwy6eFPz0uWCMOxndlWXyRH4Aw9v/22+Z7ohH1bgxkZ1NVXSyCyTZuwiuOGqCj5/WZ6/uYb85E94YKV89nOwPfBg7Jmy8qMrzth3/aHp5+2X88OQsRpDTcSEoSZ12geIThjERUWyobjy/ixe8xIUZGUVRghJkYGwJ9xRnhl0qOyUg49s7mIVVVCSGEny+PJJ0uZmZONXF+HohPIKPwZuX37SvmwGYt0OLB+vfQzOhmvvy6VCUaIjha21L17wyuTHseC0+qL5Aigf38JYNiJ556D+fPtlcEXBg6UEVGnn258vahIsph2sm3707PTy8BjY2XftvPsW7tWmHnNRokkJoqMdjIc33WXMGqbyfDVV/CPf4RVJC9oz6IRnEAi5G/fdkIA5c9/ljGNZhg61P5Z7w6CJadVUZTTFUXZrCjKNkVRHjC4PlVRlLWur4WKogzWXdulKMo6RVFWK4qyPJjCH5Po3Vsi4scdZ3zdKcaPr7ITu50ZfyRHIGUpw4eHTyZPfP+9lK8a0dWDsNZ1727M3BsuTJjgm2XyWNCz3TL6OxSHDIHXXrN3HMpjj0nW3AyPPmo/A/MJJ5gTCIHz9Xws7Nt/+5u9ZaOqKuWYP/xgfs9VV5mTpoQD0dHQrp3vUWVgr559EQiB/WvFyr5dWCiVSHZh+3YpUzfLwOXmCm+H2fntBNitZ5Byfl/swHbL6G/fHjNGbDE7ncJt23wHZNevF86ECACI8XeDoijRwIvAqcBeYJmiKDNVVd2gu20ncKKqqkWKokwCXgVG6q6PV1U1P4hy//fCCYdiVpZ5CRdIhHLUKDmc7IhE+iM5AjmUqqok02UHjgUjd88eMc7S042v60kK7BgEX1cnLJRmAR6Am2+21yG00gNXVydfMX6329DAnwEZHQ35+fbpubISZs6EESOkT8sIdhs/J50kpCNGs6tBHJ3x481L+cIBf3q2G1b27dWr7a3iWbxYnOp77jHWpRP27fff98150aaNZLiqq+1hEraiZ7v2Qg3++ByOHJF2hCFD7HNoHnhA7KsnnjC+bvf5DLBihe/rdu/b/s7nlBTRsZ3wt29//bW070yZYp+eHQQrmdbjgW2qqu5QVbUK+Ahwo7dVVXWhqqrak7kY6BhcMf+L8Nxz0rtjVhrjhEPxllt8R7uPOw4mT7avdMaKo3D99TBtWnjkMcKx4LRedJHvDJzdMkZHw003CbOeGR54wNk9cPn5EBvLsutepksXqcTu0kWY9sMGK9lq7T47cOCAMPOa9cCB/cZPWpow85pl4DIzYc4cyRjbBX96/vJLma/ta4RUKGFl37Zbz7//LpUHZm0ddq8V8M3MC3DffdLLZ9fom9JSWSe+9Pzcc/I52wV/zPlO0PPcub5nzTtBRn/45ht48037fn9KipAMmpH8VVUJw/FyG4tAnX4+OwxWnNYMYI/u572u18xwHaCv/1GBHxVFWaEoiqkXoSjKNEVRliuKsvyQXYdqOHDokDx8ZsZPWhp8+629Y2/8zb0sKBCG45KS8MjjiYQEiYT7ysDZbfz4IzlyQi+Fv81yzBiJ8to1H/PwYTm0ffU+VVaKY2gXzjhDSEfM9OxiOJ71YRE5OWIL5+RIPCVsjqu/ckK7n0Urzsypp8K4ceGRxwiLFoU50tAIfPYZvPKK+fWKCli3TvZvO3AsOK3+SI5atpSSSDszHg89ZM7A7ARkZEjZ7XXXmd/z668y99gu/Decz3Y7M5s2wejRsGCB+T2dO5tXcoUDkycLEZOZnhVFkjS+WhZCDX/M+Xbr2WGw4rQapdMMw5CKooxHnNb7dS+PVVV1KDAJuFVRFMNQtKqqr6qqOlxV1eGt7e6vCiW0xnUz8pvoaDjzTFnsdqFDB7jjDvPry5YJw3F2dvhk0qNNG3jqKd9zG51g/Pgiy3AKSYGvQ3HIEMlkmpVQhRorVkifo9kcOJADx87ynr59pQ/Ph56PKEkkVbvrubwcpk8Pg3zgfOPHijMzfbqM0bAL770Hf/iD73uGDoWHHw6PPEbo1Ml/fxk4W8/Hwr6dkwM33hhWsdzwn//4JrNat07ma9s9H9NXJZbdeo6OFjJMMzvsWDifzz9fstq9e4dPJj3275dyel8zTn/8UWw1p8IJeh471nc1md37tsNgxWndC3TS/dwR8KLOUxRlEPA6cK6qqvWhXFVVc13fDwJfIuXG/7uw0nf088++o1ehhEaiYMbMC/YvoooK38y8YP+heNZZ/seIPPusRALtgBWyjOpq2LnTfAZpqHEsGLmrVvku4QIK1VRS8ZZx9+5QCeWBjz4S594M3btLOb1d/ZBW9Gw3rOzb+flhVKoHVFWIbXwFeOzet8eNE2beMWPM7+nTxz4jHJzfF2xl3y4rE2ZZu8bmLVoEl18O+/aZ32P3vv3oo+bMwRrS0nz3DocSVvSckGAvw7GVfXv2bHjkkbCIY4g//tF/1aLdz+Jbb4mcZrB733YYrDity4CeiqJ0VRQlDrgEmKm/QVGUzsAXwBWqqm7Rvd5cUZQW2r+BiYDN4T+bYeVQvPtu+5j1ysqkPNjJmZkPP5SyS1+HcmqqOLeVleGTS49Jk+DOO33fc911EmWzA1b0vHOnRKNnzjS/J5Sw6rRqZBR24E9/8pt1KYs1dlrDVkwxYYKM8jBDr17CcNynT5gE8oAVPT/3nATS7FrPVvZtO42fI0dk7rMvNnJNfrvmJsbECGGV2bxgkH7MX34Jn0ye8FdKD3DrrSKnHbBCcmT3+bxxo5TS+2ozsnvftoLt2yWrbQeOHpVZ9L5IBgsLpU1q8eLwyaXHsXA+b94sgTJfsNtp9YcBA2DlSiFIjcA/e7CqqjWKotwGzAaigTdVVc1WFOUm1/VXgIeBdOAlRaI+NaqqDgfaAl+6XosBPlBVdVZI/pJjBSefLBksX7BzEVndiPT3hhtWZDz/fDHG7YpC5uRIFNRXr8LOnWKE+HIoQoXoaCEgGDXK/J5jQc96Gdu2Db1MnrDgzJRdch2zPk4C3bmdmCiTaEKOw4cl2j16tPSamUFVxci0g7zl7LOl3LFDB/N7YmPF+CkudqyeHb9vt24tDMe+9qRQYu5ccaqnT7ePJMgfvvtOgp2+kJ0tbOB24Fg6n321lbRuLV+HD9vT83jbbbKP/PnP5vfYyXDcrJnMkvWFmhphOM7M9H2OhwqBPIvFxdLWFW44fd/es0fa3F54QcgIjdC8uW/+lv8xWJrTqqrq96qq9lJVtbuqqo+5XnvF5bCiqur1qqqmqqo6xPU13PX6DlVVB7u++mvv/Z/GPfdIdsYXnG782E1S4I9EASRKedFF9hFmTJzouyQTZHi4L/beUKJZM2Hm9dUPqunZrhEUVvTsBAPNz6E4/N07GPfmtWRmSgwlMxNefVUmR4UcO3bIOvAVjdec1SefDINABmjdWkpHfa3VY0DPjt+309KE4fiMM8Ijkyd++UVY6aOjze/5+WdhON62LXxy6REV5bs1BuzPqDdr5nyn1d++feONwnBsF0nPTz/55+R47TWpXnAq7NZzerr0Yh7j5zMzZsDnn4dHHk8UFAg5q689UVWFYM+ulkGHwZLTGkEQ4Y+ZF+w9FFu2FMe6f3/ze2JjJSJ9+eVhE8sN/sisQJiNf/7ZPmbZY8HIXbXKd1bBbpKCiy8WAhxfeh46VBiO7epDs1JOWFXF1ImH2LVLEjS7doXJYQVrzkxMjBjCdunZCpOo3YGyn37y37Jx4omSybQDx0pfsL99u7paiITsmiBw110yGsgX7Ny3+/WTioMLLjC/JzZWSv19lWGHElb0bDesnM92MoYvWybVMWvWmN9j9/l89dUSDPVHuAXOdlozMmQMpR2wsm8rCtx7r32OtcPg4F3lvxCqKnWBf/mL7/vsPBQ7dxa2t759fd93xhnS72gHrGxEGzfKmIwlS8Ijkx5WSBTAXj3/+qs4fJs2+b7PThkHDfKfie7dWxiO7SgZtarnP/1JhrPaAavOjJ16fvVVa9UnYJ+MmZn+m5D/+Ed4/vmwiOMFq3o+8UT/LMihgtU9Ubs33FBV+Pe/fZNZgTN64Py1vWzcaF/fbVycf9tgxw5xvCPnszH27hWH0F8ZuhOeRV+YMEESCL7YcUOJk04SO8cXfvvNvpnBx8L57DBEnNZwoqxMIsm+BoMD3H67b0r7UKKszD8zL8hCnzs3PDJ54qKLhKzKF+w0fqyQHIG9JAVaya8/GR9/HK68MuTiGGLZMv99PbW10htsl5H73Xf+Px879XwsHIpWDMhOnYS4rH378MikR0UF/OMfvrMeduOssyA313eFDMhnbRerrNOdVqv7ds+ewkNQWxseufT46Se44gpnG7DPPCN7ty9UV0tG244y8GPhfA5k37aL4fjqq/1X28XHQ3Kyfdwin3wCN9zg+57ffpNEkpPtsIjTWo+I0xpOWN2IunTxHx0KFf7zH2Hm9Tfm5OGH/WeMQ4Xzz4ebb/Z9j0Y2YsdCD+TA0d8fTliV8fLL7St5vP12KVX3hcJCieq//354ZNIjKkp6l/2x7h4Lena605qRAa+/bg8hxaFDks33Z4i//bb0Qx44EBax3BAbKw69vx5+O/VspZTezrWisSr7k/GmmyQL5qsPLVRYu1b2On+/+/77/XMq2Ak79VxRIYysnTr5vu9Y2LdXrBDHzA5s3Oi/jL+iQkpb58wJj0yNgZ167twZLrnEf293xGmtR8RpDSessOqBzPr7z3/s6ce0QqIA9i6inTv9kwPZ2QOXnCzMvOPG+b7vtNPg44/9f9ahgFU979njdw5pyGDFmbFTzwUF0mdy8KDv++w8FKdOlaoNf3qeOhWmTAmPTJ6wOhtTVZ2d9YiLk6yHHXr+/nshOfIHO/ftBQtkfqgvpKZKCbNdDNGaDE6Ftm/7q9bavBl+/z08Mnni6qsl2+oLdu6JrVtL3/Qll/i+r1Ur+SorC49celg9n+1kOLayb8fEwD//aQ+J0Lp1wlg8e7bv++x8Fk85RUY4OtnedhgiTms4YfVQzM6WaK6/4dehQGGhNRIFOxfRyJGS+fAFO0kKUlJEf/4ycD16CNlQYmJ45NLDKlnGX/4iI0nsgJVD0U49r1sHkyfLd1+w81Bs106CJ/70fMMN9mVmrDqtaWn+130ocCxUTnz3HTz7rP/77Ny3o6L873WxsdJvf9FFYRHJDWVl/pl5QfowBw+W2YnhhtV92049f/89bNni+57YWKlKcLIhPmWKZBLt4O5o104qnPzpecYMqUiyA9qz6At26llj5vU3XsvuPnorePlle+dXOwgRpzWcaN9eejG7d/d9n91lKVYMSLsORVW1VmYG8MUX/suIQ4H8fFi9Giorfd9XViYbkb/h16HANddYG5x+LOi5ZUtnl3D16ye9wb7mpIYKs2fD11/7v6+62p6yVhAnwNe8RA1JSQ0lnOHEseC0Wt23x46VCo9wQ1UlkDfLwWPax4yRTPmECb7vU1Up092/Pzxy6RHI+WzHWtFIjvw5MyAluv7GC4UCv/wiut6+Pfy/2ypuu02mH/jDihXw5puhl8cTgZzPdtkQx8K+fcUVvscOamjXTioEIog4rWFFr15SKuGPSVTb8EtKQi2RN0pKrB04LVvKAV9dHWqJ3FFRIb/Tioynniqfebjx7bfSe7dvn+/79uyR8pBffw2LWG4YNkyyhP5gl56132n1WbRrrWi/3xcyM4Ud1x/7bCjw/PPWykaffFIOxnDrGaBrV2sOvdP1fCzs29dfL73B4UZ5uQTJrJBZnXWWBNXsgj/SGDv1nJBgjYnczn27psbas7h4sbW9KdjYs0fG2fjLYu7fLwzHTu7HtEvP1dUyQWLQIP/3On3fHjZM7j399JCL5IWiImsl3osXS9WblZGZ/+WIOK3hRFkZHD7svyQgJUW+27HQr7hConz+cM01sHx5+GexaZ+J9hn5woIFwrYYbliV0UTPM2aIXRIVJd9DMipu8WL/w9WhQUZ/xFzBRlycZAmtONZ//rNkccIN7TPxp2dtOGtBQchF8kJJibW1YpeeS0tl/umGDf7v9SCIC8s6ARm7lJvrn7ilTRtxCjMzQySID1jVs12wulZAMji7d4dUHEN8842cf/7YWO08n99801oGrls3aaM5ejT0MukRiJ7tgtXzWVWF4dhfqXMoMGUKTJvm/z7tbzh8OLTyeCIuTip4Lr3U/70pKb7nwYcKVvUcGys8JHbMFba6by9ZImN5wn0+OxARpzWcePppWRz+oiXJyfLdjkPxkkuESMEfOnaUCFW4GRS1Rat9Rr7w+OP+5z+GAlZl1K57GOLTpslUClWV79OmhcAgnzYNHnrI/30GMoYFsbHCzOuvlB6kL9iOkkdtffrTc0WFZBPfeAOArVu3khOusSOlpdbWil16zssTptPVq/3fm5xcL1/Y1gmIgda+vf+IeFoavPaalB6GG1b1rBG/7dwZepn0CCTYmJxsz9m3erUw8/rrgbNrrQSCyy+XwGS4Sf6qq2XsUocO/u99+GG49trQy+QJTW/+Phs79bxhg39mXrA3gGIV8+bBDz+E//f26CFOtb99saZGGI79ETaFAlb3bbuCyg5ExGkNJ0pLhejB36GYmChZsBtvrH8pbFkFK8y8IMOvX301/H1wrVrBSy/B8cf7v9cu46ekxLqeo6PdZJw+3TvQX14urwddRiub5UkniaHbqlWQBfCDQ4eEmdcKg7ZdDMfXXScMnQHq+YorruCWcJEelZZadxQg/OslEGdmypT6uYBhWycAM2fCE09Yu1dVobo6fPu1hlWr4IMP/N8XGwtHjtiTUQfrBpodxllJiaxVK+t5wgRrjlmwMXUq/Pvf4f+9VtG5M6xfD+ec4//erVvtYThuwvkcNljdt9PS5GwOdyZzxQph+LbS2mTHaCiAM8+UPdFfsDE6Wtiuf/stPHLpYTXTamciy2GIOK3hhNUHVFGEvMVVix/WrMLQoRIB9YctW8Sp3rw5BEL4QHq6kCv16OH/XruMH6vRM0Vxyx6BeVVc0KvlrB6KXbpIJjPcEfs1a6Q0eNMm//c+9pg9/SgdOgixjT946Hn37t3sDFemy2pwwq5IbiBO61VXwR/+AIRxnYD0qD//vLV727Zl85l3hm+/1hAdLYa4P9iVmamoEPmslqrb5ShY3bd/+aU+gBJWfPedtakCK1YIwcvSpSEXqdGwK6ickSFjlfxB27ftCnxbeRbPOUcCvP36hV4mPQoLZdSblX7MDz+EW28NvUyesMrMa2CHhQ1XXGGtSuxYyKiHCRGnNZyweiiCDKp3zbQLW1ZBVQMvJwz3IrLKzAv2GT/XXy/ZYCv45BO3Dd2MqyeoHD6B6NkuhmOrpbfaPXYcOLNnSxbOClzPYm1tLQcPHmSfP5KuYGH5cmtjYnr1Euc/3GRRgWTgqqr47KWDdOlibo+ERHyrAR6A5s1Zv7A0fFlgaGDmtVLeZte+feKJ8iFYCfKMHCkkL+GGVUfBLmj7tpVnUVUl8BfuSqiffxYdWwnK2RVUvvNO6+WqffuGP2AbiJ7tQiDn86pV9jAcX3qptLBZgV3P4t//bq0v+FhoSQgTIk5rOBEIWcazz4rjShizCmVlQhoTSLlCuBfRN98IM6+VcQPJyeLcWnFwg4njjxfWQSs45RS3ea5nnOFNXpmYKP5E0BCInvftExnDzaAYyKGYkiKEI1VVoZXJE88+a5390uVYFxQUUFtbS2lpKUeOHAmpeID0BFspY+zUCR580BozaTARQKZ19eVPMfnWtuTmGOs56OtEQyDOTHIy0WXGe2LIuIXKyoSZd+1a//fa3Rvlj5kXhOTvrbdCL4snmjWzHvU45xxr3A/BxJEj4tA4uUd9925YuNAaqY1d+3YgWLDAemtAsFBVJbPRBwzwf++BA3DhheGf4RkI4VZysj16LimxXppsR0a9rk72bisZ4SFDpG3PjmCewxBxWsOJK6+0PjdUt4jCkn2DwEr17CpXCMSZueoqyTRZKWEJJqwy84Ic8C6G4xkz4J133PcwRZE/Y+rUIMqnMfNeeKH/e+3KzAR6KOrfEy4EEoR66CG46Sb264ItIc+2lpTAU0/Bxo3+77WL4XjqVGHm7djR761f/ix6TsZbz9HRDdnMoJfhBpL1SEmhbbzxWglZEjuQfbt1a+nFDndw4ptv5Pyzg0XUKt5+2zrbfHGx1H2HE43ZE518PnfpAiNGhJ/h+KKL7GGbt4r4eGHmnTLF2v1ffBF+huNAg8rg7PNZC6CEE3l5Mnv8tdf83xsbKzLawXDsMEQ+gXDi0kutz5/TlbY+9phkEfQISVYhkFI9Ox0F/e/3BbsYjq+/3lpfMEgU9/77AeMycFWF778PsnxxccLM262b/3vt7nW0Upplp2Nt9VC86CI4/fTwOq25uXDffdZmY1ZWCsOxlQM0mIiPF2ZeC2t0V5F81il467m2Vr6HpH80kLaO5GR6tS8Nz36tIRBnJjVV5rRaKdMNJlauhPfek73HHz79VNb99u2hl6uxsCMzozHztm/v/147R1iBtfUydar03Ia7JNsqMy/IbEw7GI6twq6zr2dPcaqdfj5bfbbmzoVZs0IrjycCCTbW1grDcbhldCAiTms4YZWZF9z69KZOFaLezEzJvGVmys9Bzb6BROFfekmin/6QkCDZxHBHLEtLoXlza47ovn3yQVkpJQ4mAiwnbCDoMb4l6GWFBw9KdNYKM29CgkT5wn3gXH89zJ9vLUt+4onw0Ufy/IYTgRyKe/fCqlXhz7SCtUMxIUE+63DreeZMePJJS7fGt5bP2shp1SPo/aPaKBQruPhi0u+4PDz7tYZAAnlQz3AcVpSWSlbByr5tF8PxZZfBiy9au9eOHrguXYSZ9+yz/d+bkAAnnyykQ+FESYn189kuBBJs3LYt/Kyyy5ZBu3YyKsYftPM53M/iWWfJmWvlfE5LEwLNcFdZBJJpteN5DSTAExUl7UhWnon/ckSc1nBiyBB45BFr93qQCE2dKtV7WhVfSAygVq2kfNnKbEwPhuOwIRCHUGM4tsJAG0wEcijaUQa+erWUBlthfraLWS8jA8aNs3Zvly4S9Q13xD6QQ/Hxx2HiRA7oiFHC5rRaZUS1wxCfOdMyM+/FN8hnbVQe7ImgBnqsMvOClMDeeWd49msNFRWSsbb6LLZvD3/8YwgFMkAg+7ZdrSdWmXnBPvI3q1AUIUW64orw/t6MDDjhBGv3rlwpNtHixSEVyQsBVk6EXc+FhdKr6m8kD9jHcGyVmRckyJKfb61HN5i48kqpKLOCjz+GcI2h0xBIUNmu89mBiDit4UJdHRw+bH2zfPzx8Pcp5OdLKaHVhvm334YvvwypSF6YNg1eeMHavXaUpQSqZ91GFLYy8EA2S5AN/fbbgyyEH8yaJX1wVmAXw/GKFfWl3X7hMn72799PYmIiKSkpoXdaAykb1e5zcIn1KTf3ZPVFj1HTIRPw3d4TtEBPXZ1Uk/z4o7X7q6utlx4GC+PHSz/W6NHW7m/e3J6y0UAcBe094YK2b1tdKyNHwqRJoZXJEz/+KGXdu3aF9/cGgrvvtt7PojEcHzwYWpn0CFTPdu2JYH299OkTfobjKVOsVeTZicceg0susXbvqlXwxhuhlccTgVbIOD1QFiZEnNZwQWP+s7pZtmwp/UfhxNdfS+TTD03+jBmS3Fp1zXP8NPWt0M4f9EQgzLx29PUEqufkZAkSHD0avjLwQDfLk092YzgOC555RujgrSAvTxiOf/45tDJ5okcPa/1lIM9DVRX79+2jXbt2ZGRkOCvTqt3nZLKMjh0Z/PGDHHdBVwCysqS1yhNBDfQcOSLMvOvWWbv/n/+ENm3CT+oB1ph5wZ7MTCDMvHbu21bXytVXC2teOBEIMy/AeecJi59TYUdQWWPm7d/f2v3a+RzOCQSBBht//91yi0XQEAgz78GDUtkVzvO5rk76RKxmhO3Qc58+wtgfiA0RmdMacVrDhkA3ohUrZL5iOB9SC0buLbdIxVFODpSQQlxFCZdfLpXFYXFeFy8WIgUrsCNin5AgM+DOP9/a/VdeKT0srlKgsJQVBvosLlpknVUzWAjEmbHD+CkuFmZeq6XnLhnD6rRecYX0dVvta5s+3Tq7ebAQSAauro41P+Tywgsi5i+/SPU/qLRs+TKwNviBnkCrEuzYc2bOlH3EqqNsh/HzzjvW5siCHCbhZjgONMBjBwLdt+1gOJ482XqZpR3BiYQECc5ffLG1+zWG43D2Yx4Lz2Ig5zMIh4aVdqRgYd8+qSixmj21oyVh0CCJrqanW7s/OdnZ7OthQsRpDRcC3Yg2bIB//CO8pTPa4ZGUZHh5xgx45ZWG4NVf+QuvcCMgkzKCztpphOuuE0Y/K7BjI4qLg9NPt8bMC8JwPHx4eIkAtM/DRM9eePJJYaENJwIcM1L/nnBh3z75TCzMxpwxA+78i6z7xYv3U10dJqc1Pl5mtFp9tiZPhkmT6ispoqLke0jXdCB6rq5m3ZlSjn377fJn9e0LkE1x8S0kJIzkkUfeDm6gJ9BSPTuexRUrhJnXSg8cOL7M7Pp7WjK5+HXWtLDY0x4MVFcLR4PVrMfnn0tJptUe2GAg0H3bjox6IMy8dvUuB4LLLhOG43BydwTCzAvw17+Gf2ZwY8r9w6nnQAM8dshYVGSNDFPDnDnhTx44EBGnNVxo00aYCYcPt3a/a7H98HGpmwH55pvl/BSqB7ekRDZKEyN3+nT3aot5nMhXdAO+BnYEn7XTTEarm2V8vDAchzN7pDHzWp13mZsrY0bCyXA8bZqUFDl58HYgh2J8vHzZUZXg51CcMUM+7i8KTmAKH1FRU8CqVe0oKspg//791GqzWkKBr76SwJdV7NvH94+tYto0SdCoaohGyOixdi28+67f22bMgC6941nLQKKpYelSeV2cVmFUHDBgANdeey15wextbmymNdwGmo992wuTJ4efoOeyy4SZ3g+2bJHkyBdfqAwZIkmxsKBbNzkrzjrL2v12MBwHqmc79u1Az+dTTgkvw/GSJcLMG25G4EBw9tnCzGu1DNwOhuNAMq0JCRLMD+daCTRJpDEch7Ot49FHrSc3wNmM3GFExGkNF1q3lrIZqw+pa0P4999L3AzIm256hYkTJ5KdnR18Gf04Cp6MnBnsoDnjgPOA7sAnwR/P4olADkWQ6Hk4e4NXrrTOzAsSqZ82zXrJczCQkRHYnEa7jJ9Ayo/CnT2yeChqs3d3k8knnI9KETU1bZk/P4Pa2lo3NuGgY+ZM+Pe/rd//xBOMevhUr1nBIQ1GWWDm1Rz/nBxYyyDacJCbb87j5pvfp3NnlejoebRo0YkHH3wQVVWD+5lqzLxOzrQGuideeSXcdVfo5DHCN9+Ice0Hb78tj0R2+on0S83l/vuhpib04gUMO4ITgTDzgj1so4FUToBkjsLZdxsIMy8I0/5xx0mLTLgQCDMv2FM5ceWVcOqp1u8Pd0tCoJnWM8+UrOfAgaGTyROB2jiffBL+9h0HIuK0hguHDgXGzOs6FOMq3Tej6uqFAPxolc0yEEyb5tPI9eTRyGMJBdQC/wbaAZ+FNmhaWyvR7UAW+rvvSuYzXAhyZmbTpk2sXr266XLpMWsWfPut9fs14yfQw7QpWLlShmlbxYcfwh13hE4eT1g8FLUgTjPKaclG16vtKCyUhRLSEmELBqS+FPjF95JpUVcCeOs5JMGo2lo5hP0QdGiOP8BG+tGZHCoqXuGVV65g0aIFKMo8WrQ4kZauEr5iq7OwreDkkyX6PmqUtft79JA+pczM4MngD4E6ChrDcbjWs8V9u7ZWWl8nTYK+Kbn8fcDHbN4slc8hx+zZEsiz+qDbEZy4557A9u3jj4czzgidPJ7Q9OzkXsxAnRlVFcc1lMFFT0yZIuzUVqEFlcN5Pj/xhMhpFeFmOD4W+oIDqSYDeQ7feCO8enYgIk5ruPDVV8LMa7VHNcVsJuESAB588Mfgl+yNHOmTQMhzJEstrwNdgVuAs4DZJCRUUVcXZLk0HD4s3wNZ6M89B2++GRp5jNCYMSP693ng9ttv56KLLgqCYDo8/XRg9KrJyZLuCCcJQM+e1vvLQJwLqRUNT0+mxUNRC/S0ZT+VFLtebUe7dmFwWv1EcvUZTFWF3aUpxFJDAt4lUkGfFQyynl95xS8zr96P2EtHurMDkHFgEybcTk3NQY4ePZEU199aEoqIvlVm3owMYYQMpOyrqQiEmRfgX/+SdpVwrWeL+/aPP0q3xDXXACkpnNfiF0aMkNHmIc+25uQExsxrB+FWoLjqKkul90FDoMy8IJMArrwydDJ5ItAedbt6HQMpBU1JkQUSrtLWQJl5QcqX/+//QieTJzRm3nbtrN1/6JC0TYSzZ7Qx1WTV1fYw0zsIEac1XAg08tOlC706H+U99Bv6PmAvkMzRo/O44YajwTXIFy+GjRtNL2sjWTp0ANgE/MpZMZ1pSSmtW58NlLJt2++hGy/brJkw8553nvX3pKRwcGtJeIllIGgzCTdu3Mi2bduC36cXyGZ5xRWwbBkffBYXns+xqMgyM6/moI5RFnFF2x+55RbC05N51VVCxuTHsdYCPYWkUYEY74rSjj//uSMAe/fuDbJgOviJ5OozmAALGUMe7WiJu4EWklnBmnzg91nU+2MqUWygLyAEONXVqwEoLDyRuLiWQJAzrV9/Lbq2Ogqhrk4eOqs97cHAe+/JvmgV4Xa4LJ59s2fLs3bWWXKvUlrCXXdJ0GL58hDLGGiwsVUr8a67dg2dTJ648EK47baA31ZXJ3HKkHM6NmsmLQmBBFmLisI7dzbQSig7MuqBZuAyM4XhOFzOzJ49wswbzmRAoBg8WA6ttDRr9yuKkKtZnQYQDARqh9nxLDoQlpxWRVFOVxRls6Io2xRFecDg+lRFUda6vhYqijLY6nv/Z1BaKgvDKvNfVBR/eTzeLbOpZVnhD0AFFRULgttrds01fpl5p06Ft94C+IgoJYo3auZRtPkgO3eeTFxcPPAt69cHUSY94uN9MvPqM2ytWsnXV3OTydtSGj5imZKSwPTsg0HxjTeO1GfiBg2aHzyZA+2By8hgxubh3HBzTHg+x717hZnXTwZOnym8j39wz8F7eeUVwtOTaZGZVwv0RCe3QEF0GRvbjmuvbU18fDw5oRxJ4ads1LMS8ney6MxuCkir/7NCNisYLDsznhUeqzkOcVrPB2KB9kAPDh4MQaY1UGbemhrZhF5+OXgyBBvhNn5qaiwx8+7bJwGKuDjqWxJOOUW201B0w7hB27ebN7d2f0qKGO1ZWdTWhqliLzvbOjMvSFtMcjKLPt7N3XfDs8+GTLLGI9y9jhozbyAMzBB+kr8AnJndYy/l6n5LOfXiVO64I7BHpFEINMAD8Le/hbd3OVBm3uRkdtKF6Z8P5b77wsRr9Yc/wA03WL/fjmfRgfDrtCqKEg28CEwC+gGXKorSz+O2ncCJqqoOAv4GvBrAe/83oDHzWi0/AqauuY/Z136sa49aAsQBf0SMtR+D22tmcbPcvh1gA51bt6MN8MNHJfTv35yqqgnAN8yYEaIT/MAB+PJLwyyGZ6ljQYF8lZDiVWIdUmKZadNg/nzreo6NFWPk1lvdXp4xA267rYG4JD9/fvCcxEB74HJzWXvH6ySXu2d7Q/Y5WjwU9ZnCUpJJocTUeAx6T+ZXX0k22AKmToWefaLJYCkKClVVbVm+PIrOnTuH1mldv16YbUzgWVEaz1F6sJXERCF8vOGGEM4KBst61hx/ObNV+vELUAqcBDwK3Aco7N0r/09QM61agMfqeo6Lkw8vnNHwSy6RMmurCPeoke7dZY/z01/pNlL4wgvhyitp1Up4cEJetadltwI4n1FVKstqGD0aLr88dKLVI9BgY1wcHD7MnHnyN33ySYid60WLJDDx++/W32NA8nfggFR3BtK+axnnnivMvFbL/ePiws9wHICef/pJumI++UTe9vLLcP/9YZAPArMhws1w/Mgjwi9gFXFx/D36Lzw+byz/+pe0j4ccU6dKebxVpKbK1//4rFYrO/TxwDZVVXeoqloFfAScq79BVdWFqqoWuX5cDHS0+t7/GQTqKAC8+y7jquawa5fG67EYGAKkAWOAn4Pba2Zxs9y2DRRlK326dgLgxcdLXDPMJwHbmDlzd2gycCtWyCI3mI3nWeqooZRkEut7CRsQMpbjjh0DY+YFQ4bj6dPh6FGtzro98FvwnMRAjZ9t2/hH4Q30w5vhOCSfo8VDUf+7jYITegS9J/Prry0z8xYWwrJl0Dx6MT1SWqIo8cyZA5mZmaF1Wg2YefXVCEeOuLJaLlSSwO7Efrz4ahyTJsF334XYyA2AmXfqVDjxRMiIyuMptIO+J/AAEsSDLVtiaN68eXAzrYGW6kH4s0cWmXnr4dB+zH37tNYTpCXh7rsBISldvLihNTYkyMiAcdbmwh49KlW6s1pfwZ9G/8qyZVJZeORICOWDwG0Il57nLpEyhe3bhcslZCgslNFtVqsSwJDh+L77hHw/JPyJjdnQfvrJ1WgdJlx1lTjKFvDmm9CiWTUbu57B0mcXcsstUhgS0orrQFugtHsdnK2uqYGZdWdzafel3HuvrJOQV1uvXy9rxirOOEPuHzzY/73/xbDitGYAe3Q/73W9ZobrAK3BxvJ7FUWZpijKckVRlh8KeX2DDbjxRiEFsogZM2B7QQofvlpK+/YwZEgNsBzQWCzHAmt4+GEDT60xqKkRr8/CQt+2TQW20stVptvAcCyy1dUtC00GzoczY+Y8PcjVtKMSmO32ekiIZUCYeb/7LrD3vPuuWD06yN+jOa1XAuuA4uA4iatXBxZKdH3eKXgfOiH5HC0eivrfXUqyy2lVvYLoIenJDOBQXL5cbKX85oc4Pmssxx0Hc+eG2GmtqfFi5jWqRlDVhkq5zm2P8vUf5jB1fC5nnimkOCE1ck85RSyD44+3dPuGDTCgXT65aN5BT0D0266dtOO3bNky+JnWQION4TTQtH07EAOyRw/4+98lehEOzJolDuGePaa31NVBXp4uoVVdLeV9qsrEifJn/vprCGW87z7Lqb0lS2Tk+qSC93lm3SmMHSstz4G0FQeM6urA9ZySwlHiWZidwpVXSgzr009DJ2KjykZHjHDLwC9YIMdhTIz8O+i46CIYPToE/3EQ8eSTlpl5Fy6EE4eVkbnhB9i/n/vuk4Dkk0+GUL7GZFq1sTzhYr4NMNi4YAHkq+lc0G8TI0fKcgvp2VddLeN1XnghoLddcIEEb3fsCJFcxwCsOK1GdRSGT56iKOMRp1UrULD8XlVVX1VVdbiqqsNbt25tQaxjDKNG+WTm1UMzLgtrkkmmhP374euvlwHlpKePQVGgdeuRQC29eq0MjnwBRM82bdqPqpbRs3dveUt9hmsQUra8jJDY4j4ORTPn6QjvAxVAw5T6kBHLAPzzn/D444G95/nnhcpcB/l7tiBFC6cjy2ZBcJzEQJl5Xc9Em7gwEfRYPBT1vY4lpBBDLa2alXPTTVKZoCgh7MkM4FCUHu88CkoPobQ8mW3bxAD/9NNMDhw4wNFQhHRLS6VkVNdgblSNUF0t31u02ML0O57llCdOhtmzmTRJPr9A4y+NgoVSvfJyOahH9ytlOyoQA3Sp1+/IkeK0pqSkBDfT2qwZdOoU2Ht02aPa2lr++Mc/si2QTGggaIyj0KGDPAzdu4dGJk/k5IhV6KP/Oz9fnsX6TOszz8hs8/Jyxo4VNYST2NMXtCzWH9t8wGUd5jJ7tojqEXcMLjRm3n4BdFclJ7OI0VRWR3PxxTBhgjitIfMbGpOBu/JKeP99QAITt94qy+2BB2DLlsDaEi0hUGZekFL1sNR/ExAz7759EtweM7JWXigtJSMDrr1WMrCffBIiGfv2DYyZF2R/qq01LocLBQIMNn7xhYsy5YMr66cNLVni+z1NglY2EoCMZbsLmPlVLb/9JoNIVq0KjWhOhxWndS+gP7U7ArmeNymKMgh4HThXVdWCQN77P4FFi3wy8+qhGZclpFCGRhgwC4jikUdOpa4O1q2TlbUkWCureXMJFZ9rXL2tlRUqCmzZIuW5PY8/nt6dK3iHq113xQODgWUB7WeW4eNQ9CRrEZQThTDcRSEZp5ASy0DjMjMG5YSPPQZRUVuAXsBIQCE2dnnTncTCQnGsN2/2e6um8/Ru8vecPKI09M4gSHnUnj3Qtq3P27Rex8xM+ICpnNNuKc+9Es9LL4lhWVcXwp7MAPS8bh20bLkCgB0f19U/xqWl0qz+wgshqLE2cGbMsvRHjkDr1i9x4/Q/SS69tJS2beG444p5992vjd8UDHz1lejawuzqTZvEjuvftZytQK9unVHVmHr99u0rXQMpKUHOtM6YAd9/H9h77r+/vkc9JyeH5557jm+++SZ4MunRGEdBY1ILF8OxBcKtXJdVUJ9p1ZGOxMdDVhb88kvoROSCC+D22y3dumuX7IFP9nuXGV3/TPPmQmj/3XchLCls3lyYeSdPtv6eVq2YM/guoqNVsrIkybhtm4yLDwkCzMBVVDQEzUBibGvWCNPxxIny2sKFQZaxMeX+xcXhYzjOyRFd++Ai0LBokXwfnRUj/3B9/o89JsUrU6aEiA9uyBD5Ja652JbQuTMMH26dhb2pCKAFSlXlKJo4UaqOOnSQLq+QOq2NmCO7fE0stWo0L1w4F7DcnfRfBytO6zKgp6IoXRVFiQMuAWbqb1AUpTPwBXCFqqpbAnnv/wyuvhr++ldLt2rGZRGprGKI69VZwEheeSWN99+HkSPbApk8/PCS4PSPasy8BhT++rJCgTit2Rt78fDjCR7O4ghgBWefHYJhrSUlEiU1YHicOlXsX/ekzcfUUcqZQB1byc3N46yzbiM7+8Hgy6aXsTE9cB59PZddppKQsJmkpF4oSjOiolqTlZXXdAdszx649178UTzrdV6KDAXftLSExx4LsTMIQmTTsaOliPjUqSLLXjWDmXkjuOzKmBAJ5YEAM62pqctRgKerX9ddEaf1qadCUJZgcCj6ytI3ayb1Rht1701Le4WtW89j7dpdwZcPpG56xgxLPXAbXO3U/XtVi9Pq8cf07SuZmpiYIGdaG4PJk+HMMwEocDmG+UFPGbmgMfMGEiXUGI4HD5ZFHsxxWkYoLZWaRR/MvNq44vpMqwfD8fjx8gyEbGzL+vWW03o7d4pzHZ+aWC/fBRdI8EdXjW8r6urg4+9b8Fb+2QwbppCcLIVeIS0R7tVLPCXv6LEXVFWqdK86eQ8kJ3Nw4TYeekg6Bi68UPyb2NgQlAg7vdw/gMqJhQvlqBwyJtHtvWlpEuAZORJeeikEMhYVBR7wuuQSIXawOoKmqfjjH+H66y3d+vvvYnOfH/NN/czgkSND7LQ2okJmwWrZPy/tuZwLLpDKjv/Fka1+nVZVVWuA25CmwI3AJ6qqZiuKcpOiKDe5bnsYSAdeUhRltaIoy329NwR/h/MRwGap2WMX8ylP8iBwCFhGs2ank50ta1EcyJGUly8JDqusxsxr0BjuXVa4FYjhuecyheH4mo/qM3BpaccDpdTUhGBY6003SV2lSTnh9997VtX8B+jHLaQDcOutL/Liiy/ybigHrlsgy9CT4XTpAtvzk6kqqeDii2WvBTF2y8uLefTRXtTVwYAB7UhKCoJx2Qhm3hpi6Uc2T1ffHjrWZT2+/FKywYEgLw9ef70hZRNqZGdrs598orZWboXltCeF9vX9mKA5rQcPhsBpNdCzUTVCTIwsp+rqnQBsiIurf29NjWzV33wToiGZWoDHQnlwdrYYsd3O7c+2+Hh6epRJ9u2r/ash0+q5zhq1R15yCfznP4G9JzcXVq3i/ffhtddkPy0IVVazRw/5cCZNsv4erXezqgreeadh0wkVLOhZc1rrM60eDMcnnSQ/hoyANIAg1K5drnbgCy6oN3LHj5e1NXu2r3c2AYsWiUdvMfX48svy6KakqDzzVA0gI+AmTAghi/B551lm5l2+XLKqH/3ekc2H2/PAEymUl0v2SFGkHHzYsBBkWoMUVA4ZAsjALVokzn1c81hhK9MxHMfHS1Bg584Q6Prhh6XFyMm4/HLLzLz/93+yNqYkfgPz5gGSqd6xI4TjgxrRF7xwSTR9lY2kVR9g6lR5JAMtAvpvgCV+d1VVv1dVtZeqqt1VVX3M9dorqqq+4vr39aqqpqqqOsT1NdzXe/8nEcCh6G1c/gSo3HPPJKKi9BUWI4HdlJfvb7ozsXy5LHKD3ivvssKtQDf27ImB995jXOUv9eWYv/02AoD585cFf7Ps2NEnw6O7nFuREUHXsI+ziI1uwZdfSq/pvn372L9/f5CFc8HPoehJhpOTA7MWpnB97qN8+qlwdc2fD1tdDMm9evUCoH379uQFIyPSCGZegI30o5hUdu+GefPmcdJJJ1FloayzUfjqq4AJCti+XWa0ZLvHxDZs2EBlKEqSYmK8mHk9MWOGBKAqKlR27VpB56j2HgzHGUAUKSkhcForKoQaWKdnfTm1ooiNoyhw5ZUq+/aJ05odE1P/jBQUyKD1hQtXBF8+CGhPzM6WRE5+YizllZX0HDDA7XqfPvK9slIyrUbrrFHBva+/DoyZF+Af/6D6pFO57bYGp3XHjhBlWgNFebk4qTExcM458Kc/iRcTyrSCBWbe3Fx5FusTxto+NWECZGUxrNdhmjcPIRlTAMy8O3e6nNbkZHmgxo0j/sO3Q1vCXFAggTmLzLyrVkl3xfrdyYyZ3AHOOgs2bQptiXAAB/6MGbI9dYg5yBGSuO7b85jX/2b6dG+oFx4zRpJzQd2+r7oKTj45sPcUFEhU5aSThJo3lLAYVD56VIYp1HNKDRwo9dUuPYMUzZWVhcDxaswkjN9+k5GPgwYJQaC+LjwUyM62xMy7bp3E8O64AxJL8ur1fHaJ6Dlk22LPnhJk79/f5225uaLa336TAM6z0XfDu+9y8rNnMTZ9U2imdDgcAQwli6DRqK4WIzKAhd6sGUxATsCY6O9p0aIVjzwyjDq3qltXxzhLms4q68OZ8S4r3Ar0lNddUUgtqzFgQB+gOdu2LSM9PUhzRTXMmuUztOQu54eAQjQX8jY3UFObBagkJ8suv2JFiAzxNWvgrrtMLxuR4dxb+wTv1V7GAw8ICcXtt8Pmza6+YVdEs3379sFxtBvBzAswlfe5gM/p3Bneeecd5s2bF1rHvzF9wdp7XcjNzWXw4MG8baE/KCBUV8Mtt8CcOYaXZ8yQyO3ll2uJ372o6n7S1c4kU4qCtohjgQwGDgyB0zpxolh7w4e7vayVU9fVSbmgqsKtt+ZTVlYGwIb+/eGPf0RVVXbuFONnw4Ygkb15IoCsx4YNcr7vkyHRdPYoNW3RQmJaZWWSaX3wQdVrnQU8MqqqSqzDRpQTzi8dTEkJnHKKZFjXrg1RpvWHH8Qh1FKV/vDiixKRat9eyEDuvhvatJGWgVAx9DzwgIzl8YF9+0SMep/s3XfFqzn/fPj9d2Kfepxx4+oTIcGFdj5beBarq2HvXujZsUL6lg8dEqfmxhu5YPB2Nm4MUbV1gL3LublwTso8lCNHROjff4frr+f889TQlQhfeKF4mn5QUyMJ2bPOgvcyH2Iwa4iOURi9+hW3JswzzpAtLJARxH7xf/8HF19s/f6KCklpxsVxdGcuddffEFrqVotB5VWrRK2jRyOL4umn5YN16RlVxTXcIfjiNiZb/fLLUj9fUyMKDUmzrQvV1TBggKXa6P/7P+lauPXaCvEMa2shN5c+/7qBbuwgVGYi7dvDddf5bev49VfpXDj3XBhYNI+JNT+AohC14Hfejbueb79RnTa5LOSIOK3hQAAHjpYhKCjAZdzWUFv7A4MGnU5UVJQH6etQRIUrm84q62OzfOwx6Z0Q1AHbiInpKaRAKSnkbizR9bxGI32tP1NUpHL99UF0XP/v/+CJJ0wvP/aYlvxSgQ+AE0iKbsVCxoJyDnFxKZSWvoOiKKFzWnv18snMaxRcqEDS6o8/Dv/6l/i9n39+ABBnFaBdu3bs378ftamGZSOYeQHu4HluinqNxx6DuXOFCKAwkBljgaARZBlqixa8CRw+cKD+td9++42amhp2BZtEQ5vibtAXrF+/DXgbgNbqYKJQ6dtJHMSoKGjRIpOoqBDOajUp1VNV8QsuuQRUVbKsLVu2ZMOBA9C/P3v37uXIkSMoSgL79q1o+nNnBIvMvBpzcL9+cMCV9WxjMKu5b18oLk6hurqa3buNm30CCu41huQIICWFmZxNfLzKyJGyRg4ezA/NnNFdu/wy87rhiy9kzEi7dvL3tWghTKDz58PatSEQ0Bpyc3XVjb/+KgHKv/xFmGWvvBKefprzBm5n/foQZI4qK8WDaqgxN8XevRLwOWPLM/LDvn1CkBQXx8VLZK6sSSyraQiwnDBvXx33HrhbogAjRsjBsmABrX7+iNNOk0IWC1x8gaG42NJzOGeOdCPdeNJmTtr5Nu9yJXnTHpFA21/+Uq/gCRPkpUceCRJnWF2dOKGB7GXPPy+//LvvODV6LkdrYgIbFxco+vWT6gc/JITLlsn344fXSeCpWTPJ3v3zn7IffPxxPT3Jzp1BljHQTOvmzfDZZ/Lvu+/20nPQYXGt1NZKUddll0Ha+8837PfffIMSE8PLSfeEjqF3715YulSceB9YuVJidxVldfyLu6lu11H2/H/+k255Czi/+uPQtSQ4FBGnNRxISpIM4dln+71Vn4nbQH8y+AiVQjZvPg+Af/xDf3czoCPR0Tuazirrw0CbOlVPrJgLVDB1ak8h4klOJm9LqUdW42qkhflHjh4NMLvhT0YfG9HUqVLmAauBzaSlXcbVt0hGZsqUG8jL20+bNj1p3rw3y5eHoE9PY+bdYt7PaxRciKGaEbGrUIoKmTxZomrff19EdHQMSa4hmu3bt6e6urrpjuI11wgZk5+xUp6lpJUJKQzpXsrYsbvqncCQOa0BZlr37YPfsvO4DnhGl9GZP38+AAd0jmxQ4KOEyzuTXgW8BJzOj/yBkSwhe0czVFV4zw4fzuS333Ia33Nphi+/lFI4k0Nxzx75M8aOhZ0uq+b0009n9+7dHP7qKza6mM47djyX6uoCdgdlQLAHPvzQ0kydeubg/nDgiPQEtzVwxvv2hUOHWgKQkVFs+H8FFNxrzDgZQE1OYSbncPLYSg4fFmtbVQtCM4IiEBbKQ4ek3u3MM2UuqYvhmEsvlUX+5ZchEBDpdZSN2RT79ulImKZPl2DG5MniMDzxBMTGMnnNn4EQZFuTkiQTfOGFfm/duRNSKWTIrCeFRRUkujd9Oi3nfc1ZSb+GpkQ4QLbR4Ts/oWfJCgmiHjkiRJBDh8J99/Hys5XExYlagpqlsbhvz5ght538y4Moic249pIKzr8oRsYcHT4Mjz4KyCP59NMi4yOPBEG+XbtEV1ZLfAsLJZJ89tkUDBrP7zszeIIHZZ2EJOUPHHec/E4/n+Py5RIbz1jwidQJd+smm/o118j/ce+9dO0gddW2Z1offLAh61Fa6qXnoMNisHHzZlka4we79DxsmFQmpafDgw8y8ciXxC8OkZ6FTdVvmfTKlaLO76/+hOGsIOYfj0uA4pprUIccx7+i7uWHr8LEyOwQRJzWcCA+XogyDJh5PaG3DfNoTydeQCGO/PzTALjiCqnAiYrS/utudOu2o+lMriUlPvv0tFKTTz+VHfCyy3rIC6mpVFd6MgVfCrQH/uX1NzVZRj8bUVkZxMR8RXR0NFu2XMigIVE0bw4ffRTF0KEJDBgAlZXDQ5Np3b1byuw8+ir1MCLDqSGWq6tfg/37URQZ2ZqQUAikUVUlxnk7VxlJk/taG8HMW1cHzcbUkV93sD7LClBUVNQ0WcwQYKZ1wgQ47cJiAJ7/cSmKotKlC3z77e8AHAw25agPA9L7Wf8E2A/8kVwyOJB5PMTEMGOGlpHJBPaSk1MTHEI1DcuWwQcfmOpZSxIPGNDgtJ7pYrzddPfd9U5rhw6ysXTpsiL4jrVF1DMH94cDrs++TZ3nniPXq6rE2PvDH0q81lnAc4VrasQTDnB+14bSjuykG+dkFeoCO/m88UYIstWlpZb6qwHJXqoqV358Jhd9PJmXdp8l2d82bWSmzBdfBF8+sMTMW59pPXBAmrduuAF695aUYIcOcM01pM//ktTYIyxdGhoxrWDXLjiD74kpPywzZED2gz/+EVJTuSvtLX75JQSV1r17S1mEBT1XVsJZhz+kuGWmOK2lpbIPPPII7N1L5y0/8+mnMiLq4YeDKKOFfbu8XB6zqeccJvr7b6Qs5cMPpV+0Xz9Je73/fv0YrP795Rx67z3JjDUJgY4Z+f57+ZuysljaSQIaT9XdRU3zFEskfI2CRWbeZctcnR8ffiiR5V69GqYr/PWvsHcviYt+oV27EGRa//hHKW21gsOHJSB0ww3yc2mpoZ6DCouZVi1vkXXYpecXX5QPtlUruOsujiakMOnAW1ZaYwOHtm83lDB6QVXFaR06FCYcED0ru3PECYiORnn0r2TU7aX8m1+avjaOIUSc1nBg/36Jzlkw8j0zAXtZQQrDycxMqn/txhvFkVi1CqZO7caRI0HYlW6+2Sczb06OrLGyMillzMwU5lM+/phLMhd73B0H3I4QSK1teumyBj+ZVlWV/bFDh320adOGWbPSuf12mF72J6bwETk50vJRXT2M3Nzc4BAb6WFhs/TMYKYLsTFjWVD//vR0GDKkkNraVGbNkutamXCTZf7ySykVCxBTly/npJ07+eijj4iLiwNCmGnduFFICiwgL08S27Gx8rkUqEXAQnJyitm9ex0Q3kyr97P+ItAXmEjXZvv56NQ3IDeX6dM1uvreQC2wMPCeS38ypqSYrud16wDO4ZdfnmLnzp20atWK448/HoANRUVs3LiR5s1TWbnyFKTkf0XjyYzMMGUKvPaa39s2bpS9p0cPOJifTzKQYDCk/sILoVmzlgCUlxe72ffp6Y2YK9yrl3jMp50WwJtg5iHpmz/rokTdGqlm0aIj7NkT0H/lHwEwMPP99xTGtWXm3qGsWFrDrbeKo/j770jv6Lp1gZNOWYGffbuyUpLAHToAP/4oL555pjSbaXvq5MkoR48yreP3wS/ZW7BAfvliz3PMGzt3wiRmobZpIyODQP6+hAQ491zGHPqavN1VuvFwQcL554uDYkHP+3dXMYE55A2e5MZwzMSJoofPPuOkk+Tl//wniD24FjKtM2dKduvGXnMly3TmmXJwaxUhU6ZImbEuXX3mmfJfN7k4KtBy/9mzxYHp148lFQNRFJVKEtjQ81whaAuFw/XQQ7Lv+EBpqWQJjx9SJZHPSZNkZqr29+n03LVrCDKtV1whz6MVzHXp+eyzRS6tB8BAz0GDxQqZ5ctli+mw3qXnESMaLiYkUDjuXM7la9YsC5Fj7eN8BtlrSkpg+CCdnnfsaGCjmziRqsQUJh7+rH5m7/8CIk5rOLBsmRweLhIRX9Bn4pqxhL3U0D5mnFuG4JRT5PtPP0G3bt3Iy8uj3MCICwidOkmtoAlycsQg37NHTuPOmnWuKIbZQ7gRebw+b3rpsgY/mdYNG0TOtLQCWrVqVV+qeSXvcio/Ado5I+Q0Qc+2WjwU9RnMKVMgqVktA1jvRiLUrFkRMTFpfPyx/KxlWptMfvTFFwEz8779diVbSw9zsK6OH3/8kX79TgVC6LTGxBjO+jMaYaKx+6mqNuomEXgXWACoREdnBt9pNWDm1eC+FqqB5cC5pKcrvHzvDka9fj2sW6fLyE4GWgPCbB2uqoT160FRfuall/7J1q1b6dq1K926dSMuOprsI0eYN28jZWV9qa5uBvQHZNZIUB3rr76y5CTt2SO2TmysBCDaRkcb1jWmp8MVV4hOHnusxC1hUVERJJktYOZvLRk+HDL6t/QYdZOPq2I9eMjI8Llv16OmBnXWLL6rncRV10Sx/fx7WZw4gZQUFwfTeS4jNBQlwn4ycJrTlJGBZIPbtJHSW/2okXHjoE0bLuQzVq8OciYzAGbenJ11nB41G2XiREhNlRd1jnV8RQkn8wsrQ8RdZgWHZy+kBUeoOPF0YYO77z65EB8vjNFffQVVVUyfLv6Ee8tRE3DVVTL7xwdmzBA9D8ydLR7D2LFSgXaTa3riKafIs6L1QCKVNBCEGbiB9AXX1YnTetppkJrKEkbSP/MI/fvDF1GTxeEKRfOyhX7RlSvl+T+1+UKJAJx+unxm2lrR6blnl+rgZ1qzsy0lYAD5DDU9z57dMDvVQM9BQ8+eEgz106O+bBkMO66OqB9det6wQdKark26+VWTSaWYos9DpGc/dqK2h4yL8qHns8/hPL7ig3eq/bXH/tcg4rSGA7rN0t/swKlTG/o3KvgVgNueu8stQ9Chg5T1aU4r0HSymR9+kC8T7Nol2cGcnBzatGlDMy2NMXMmU2dO4dVX6tCSr1KRmIai9CQubl3TS5c1rF3rc6Zgg/2bT3p6er0DUEKKx6iRIUAUb74Z5L7WRszeWrAARg2uIJo6N0O8qKiQ9u1TmTlTHIWgZVoDJFGYMQNuvnkbKiqxnAHAhg3nEhMTF5ry4KoqYebVlSFrchiNMHnjDbE1y8pyiaYlcAEwA3ECY6mtPZuDBw8Gl0jo9NMlPTR0qNclfSZdWLZrmDKlP/n5cNpFrkOqpESXkU0E7kZGWS8NblWCj0Nx7dpyVLWCgwcP8uuvv9K1a1c+/jiG9rTjjepqNm1ahWSIAa4Efge+BoLkWFdWiq4tPIv79jUE6A8cOEDbvn3hzjsN7+3YsSUA1dXFbq83ytn+7jtxlgKY/bt/PyxZonLOwJ2wbx+FhYX1femJiQWS1QwmHnxQ0lf+sHw5SnExM2vP4PTTQUlJZmT5XKb/qY7Fi+GnLZnyPH/9dXDlq6yULx961jJBGe1qGxyFqCh5j7anRkfDBRcwZN/3lOWXWyZLtoQAMnBx61eSXpcve0DXrvD3vzf0zpxyCmpyMhcpnwXfaT3/fL9jgzTE/DyLamKIO32CeKUFBQ1e/mSXwzV3Lt27N2Rb/VRvW8NTT/lk5i0okJjEpZeoKLN+EG80Lk5KnjU96x1rV79f69bS1/fTT02UL5Dy4FWrJP1/+umoLZJZwkhGdTvEuHHw0tZTUVu0CI3DZaEFSss4D9w3SwK8EyZIrbCWtQbRc1ERE5jD7t1BnDBTWSnGpxX2X1UVm1LTsx4Geg4aOnQQ59hHW0d1NaxeDed2btAzIHp3JQZSJp/KYaUFaXNCoGcLdtiKFa7Z5Ft1ek5JkZJrV3tM3GWTSaOI7a/PoV27EJHAOQwRpzUccG2Wn/+UbGh433KLuyOrJQDPOGM53bt355ZbvJnkRo4UH66rq092R1NrQP7xD5/MvDk5Yojv3r27oTQYxFP85BOmnnOYXbsaKn1UFdq2HUBV1XoUxdhBDxh+mHk1f66srID09PR6B6CEFFIo0d2ZBPTh669XBLdHL8CemdJSqcgbO6rW/f1IFrN37zTKyqS1JikpiaSkpKZnWgMkOZIyVhl9Us3fgLVUVV2NqqaFJtOqMfN69AUbjQoqLxdD5rjjpDy4HQrwV4S9eiEwktTULlRWVlIaCl54k9IeLZN+7rnSjHnXXf3kgva5l5Zyxhn6t98CpKIo/8eRI+YBrYCg9S4boKYGNm1qyACqqkp5eVemTYOTa69AKLoO0+C03gEMQEr+jwTHsQ5grehJeg4cOEDb3r0N59vNmAGPP6492yVe1wN2tjVm3pgYy2/57jtQVYVz3joPfviBwsLC+rFVffqEINNqFa5G0JXxYzjpJOqfxWsmH6ZjR2mDU0+dKKULLrKroKCqSoxpbZCuAWbOFBs2q/lK8Ww0A1KfVQCYPJnYqjJOY3ZwS4QtBhvr6qDrltnUoUipY/v2sjG59Et8PMo553BB1FesWR5kQ7yoyDJDdPryWfzOONr1bAH//reUPupLR1u0qJ95M22atCk0ef6tBWbeRYtk75kybJvUPmp61mfUQRyuwkK3wOUpp0irs2syV+PQv78w87Zp4/9ejZJ14kS2FqZTRBojO+5j3Dg4dDiB4qxzpCoh2A6XBWdm2TKxxRJ/myWBjBYtJKP+wQcNh4pLz6P2fUZdXZAreMCaDbHNQ8+XXCK9rBoM9BwU7N0rH5KPRs8NG+S5P7mmQc9eY/MSElje4RyG7PqSFYurMSCsbzz+9CcJ8vjAypUSH4j5SafnlBRZY9oePXEiaosW/OeUz6iokBjAfzsiTms44NqQH/xHiqHh/coreke2lE8+qaRbN9i0cSXHlZdjRDvZp49wVqSlSZS3yU6rj82yslIcwi5dJNPaWW+16gxxPWbMgIMHBwLbgPKm98MVFEgvpo+dIy9P9uySEikP1ko1S0n2yLQCDKeubjkPPqjWy+srA24J114rtYytWlm6felSOevHnNZCHgStdAYhOerbN422bXErEQ5KpjUAkiM57MRpfZgPSKMDksEModMKXs+i2aFbWSntPDU1ubQjijY0B+YCG4iN/YgpUyTgE9QS4S++EDZOP/U4GzZkA4prdjH1n/uKuaW8847evmsBTEJVV9QnRZq8Xj7+WKamG2DbNqiqktRK9+7dAVi4sCvl5TCL20jkJxQeBK5wvSMWeAXYQ2zsW8Ep9w+AmVc/DuXgwYO0gYbeRx0kwNLS9VOx1/WAnW2LGTj93nH77dAqrY5BrKWuqIiioiLi46VHbeXKAtavl0x80HDeeaZZZzcsX87BmPb0PClDen1df1N8ZSkPPigOwZLE8fJML1wYPPlatJDn8IILDC/X1Yn/dPrp0Pz32bKBnyrtB9x7L9x2W8PNJ56I2qIFp4fKafWj51Wr4ISKWRR1HSbpP1WVjUlfAn7eebSsLaRu6bLgljBbDTbm5dF63xp+jj5N+BK0v0l7lhMSpDfuhx9AVRk6VBKdTa4A2LFDDlsfG5Z2dPfNcRE16J1WXcCWiRNFTl3l1ymniH/YpKDP0KGWmHkBSQkPHQpt2vDbOikDH3lCPFlZcvmb6PPE4dJmzwQLFvS8YgWc3C9PZuOZ9du79Nxlww+AGrwS4UD6gmd56LmoyJ0VykDPQcG778Lxx/sMKGjZ6l47GvTstVaAA6NkPd8+eplbIrvJGDWqoc/PBKtXw4m9PPTcubNk1StdjMEJCSiTJtFl4w8MHKAaTeH7r0PEaQ0HSkogNpatu+MNL7svhDGo6u0UFJSwY+dOjsvLM2Sj1QLXBQWtad68edOdVh+b5Z49ImPnzqp3plVb6CXumY3p06GubgAyM1WYSJvUD5eTI/PRNCpRA+TlQXq6SkGBZFq1Us2qxFSi8GQbHQbsZ/fuXNPS04AdhmbNLDPzgiRxFAVGjYmS97qipDU1NZSUlJCWlsp550nQt7paSoTDXR4shv4mmpHOX/kX7ZHfHx+fGpryYJND0ZfDIT0+ubQgiYloQ8v6kpycwfnnS1Q9qAzCS5f6ZObVsG/fBpKSupKoNbm2aAGKwu/flXgFr6ATsA90z2lQ+0d1kINNnNYHHniANm3aUFgo5EG5ZLCKU1B5DNBnJMYCaZxwwsbglPvX1krPkZ95hIcPy1dGBlRXV1NQUEDbjRsN2wQksJGIEEe570dxcV8yeHCAH2ZpqZS1+WB49Nw7KiqguERBAUoOHaKuro7lyzViFfnM77gjiGRW69ZZmndYvXAZi2pGMGmS6wXdvn399ZIsvP3DMagxMUFIu1nHokUSlLjoIiTL26dPwziuCy90HxMXE4Ny4olMjJ0bXKdVY+b1oWeAn76rYgTLSDj9JHlBVSXl9fzzDTeddBKqonBc0ZzgERyB9WCji5FlQ5vxcpx4Zo8ATj5ZPvStW4mLE/u5yRUAFhz/LVsgLQ2ar1koHBpaWbVnRr1ZM+mB1NU6ZmXJUmwSb09REZaoYKurZY8fP57vvoM77kugTx/od/XxZGYKEe7d37p6d4Ndj3nnnRL8NsHRoxIfmNjCxbyj9RB/+61Eb/W24oQJxOfvoydbg0fGFEg12UJvPW87lMJrr7lsXgM9BwUW9u3586F1y2oS1i1t+AxbtGh4vwtD75Zrdw6ey9atPs3PwPDzz8IwaIKiIjh4EE6K99Dz5MkSKNGPLJwwAfbt4+TOWyNOawRBwi23wJw5dM70x/x3EMgGvqSkRE7lIfp+Dx00p3XzZoVu3brVj61oNEwOxRkzGng+7r//EBUVFcZOq0emVQzIga6f1nm83ghYKEvZvx/ati2htraWVq5s59SpcPaRD7k403NOgpAxtW69wrT0NGCH4YsvZLCcRSxcCAMHuj7CBx8UdkiguLgYgLS0NE47TYz2RYsk09rk8uCNGwNK9Tz2GERFbSIR0XkypSQmQr9+Ic60ejyLRmRfGm9Kfn4dkEciLbmVF+uvFxRA27YhyLSaMPPqM26dO0N5eTYdO+rKWKOiYP16Hi35g8F/2hkhbnKXs9Hr5eKLTRmY5WCT7NDYsWM5cOAAmZmDAGjDAa7lDTrg3TSYktKNmJggWT+9e4sFMHGiz9u03sUOHeCQyzlr27Kl4Z4ogQ0FaIk+0xoVVUNy8p388MNT1AYyG8BCf5nR3lFTq3BYaUGBK1BSU9MNOWrFaa2sDN/sau2emB2bWc5wxoxxvTZ6tAReMjKIjZXOkOWbkjiYOSK45Xrz50vEwWROzaefuvhEzkZSSMOHN1zMy8PLOx0/nq7VW8hbtjd4Ml54Yf3e6wvbvs4mgUqan+iSMSpKDF39s5ieTlmPwUxgTnD7Wq1mWlesoEaJoTjTxWxsdD5rzEYuZyErS7I6TeqgsJCB27rVVUm9fLm7ns87T0ic9JgwQfqfXM22zZrJGM0msaQ++KDsO/6QnQ2VlexpO5xzz5UJLfN+VYlWpbLmqacgISOdjQlDqJsT5NLWK6+Uz8ME27aJwzfg6HJpW9AYrGNj5RnRP4suPU+MmRu80tZAZld76Dk/PoNTd73KtGkNJEOeeg4K/OzbVVXSun/juGyUysoGGaOiJKOpa6vpNTodhgzhnBayVoJWfnvJJT4JMTdvlu/9yj30bASXnicoczl0SJzd/2ZEnNZwoHNnGDfO0PB2t3s1YqB8EhPF4DxOT2WuQ5cuEkzatEnImJqUaVVVw0NRyyJoi+DQIbGgd+3SOa1padLw7lEqKQZkdyABvdPa6H44C4diXh6kpsrml67NkgEThuMhQBRjxy43dQwCdhg+/1xmfVlAba0cwPXEn++9V880oWUw09LSmDBBEnqzZwcp0xoba8jMa4bLLlOJi9tMSqKUkfZqU8Krr8KgQSFyWisqREaPZ9FzVFBmpjDUt20LGRmHgFriSWMADZHmli1D5LQaHIqeGbc9e6qBLbRo0c/9vf360SIzzeA/7eT67j4TpVHrRVXldDVhK9+0CdLT3deJtj66sYM3uJ5BrK3fmzIzJbhSU9PEfaYR0DiQMjIadNgmLc3QaW1Y4ylomdbERLj99m/Iz8+hurqa3YEs6o4dafDyjGH23xWrKRTWl422AtLQAgW+3hcQtH3bX9ZjxQoUVWUZIxpaSzt1gksvrWfAveACsd2+OTJeIvnB6mstLBQlmjDzfvWVxC2Sj+TKBj5sWMPFf/4TTjjB/Q0uA63nvrmhmZ9ogsOHIXq1i2xCL6NnPyYQd9oExrCQtUuCSFl99dV+mXkBWLGCrXH9ad0poUE+cF8v3buL/nVOa11dEx1CC0HlLVtgcJcS8bz0n+HUqXD//e43a461Lus/Zoz4QVplZMCwWmXkIhV5ackw4uPl7G0zurts8Mh/8de/wvdHJ0i5lMwuazpU1S8z75Yt8r3jwRXSo5vgoWf9s9ijB3TsyFmJc+qdoCajVy9LzLyUuOu5thYumncbebVtiI2VeBlgqOcmw4+e584VLrILuxis51mz3Nq0NBnjly0ga8TR4Ditquq3cmKTdGTRYb+HnjWG43nzGm526bn/QVnP/+3Z1ojTGg788APMmmVoeN90k96HWIZkChSOHv2Itm3b0t7EQIuJkail3mltEkPq+vVSt6aDdxZBxt189JHOkh4xQowND+PiscegWbNooB8gqygxkcb3w1k4FPPyICVFDEM3p/Wbb5j6zSW89nJN/WffsmUi0I+yshWmjkGjeuAslt5mZ4shVG8T6/p6NGcwNTWVlBRJimhOa2lpaePHG1VWwq23BnRA5OXlcfToYe6+SyLUbz9fytSp4lCHpDz4jDMkFHrccV6X9KOCdu0SvoUTToCbbxbPZjbX0oVdgARNo6MhPb0ViqIEtzzYQM/ea2UbUM22bR6EQR98wLvnfmYQN9Cc1gZvptHr5ehRKXEzORS3bYOUFHFa09LEgdb2pubt5e/q0aqE996T83XXLvjDH6CsrBs7d+4KLFtphm+/FeX5CcJomdaMjIYS77Zt2ggji4cc2t8QF9cSKCY2Vn5evfo5YlxkStsCmUP64IN+2XTN9oj72rxD4Zlnun5Kd301ZBNMOLICg6Znf3uOq4Frf8bw+gq4evYd1wesKJJk+OzQSfK5Bovm2Ec5YUWFBHlGjqSBfVBvQCYni/Os1/OgQVS1SGMCc3xV1wWG886DE0/0ecvcuTCkbgXVzVPE6dPg2Y8JxJ0+gQQqKf8liMMT//lPKQ30BVWF5ctZVjesnriMLl3gb39zl1lRxAGeOxfq6hg1SvbKJpUI+ykbraiQNqOxzVwpNr2ea2rcGY6160lJbqWjY8bIEdbo0nArAR6AFSuoa5HMs99056qrXLPUmzVzcwgHDYK5jCeqqrKJ3r4OR48K885//mN6izitKi22rPBeK+D+LCoKTJjA6Mq5bNnk2R7VSGRkiFPnp62jPpXqknHmTPh1bw9eHPEOZ5yh8tFHrmVtoOcmw48d9vnn8isHVK2Qz02/NowwfjxUVnLT4EUsXy52R5NgYd/evBliY1QSN3roGdwYjoF6PbdZPxeFuojTGkEQ8OST8oW34f3SS/oRGcuAvqSmHk9dXS1DhgyRKIsJ213v3uK0du3alfLy8sYb5opiyMzrnQ0QpzUvL9PzgiFkKs4AYB3p6fJ3NrofzsehOGOGfH779sGcOeK0ttKTIW3bBh9/zGVnC8Pxe+9JSRoM5+eflzNpkurlRDTKYbB6KKJxnajk539ARUWFW1+P5rRqDsVpp8kZ0Ly5ULg3OttaXCwPnIXGDK3UNSNDQn6Hil2l3i49pKamcvjwYaqDzZ6owcfQbRBjd/duyRIMGSJOa3K7nhQqrcjMlMREQQFs3RpDenp6cDOtBsy83mtFPuOiIo9M6wsvcMKG/7gFr6Q9RZzW1NQ99QGtRq8XPyVc27fL+JXU1FRiYmLqdX3FFXA4St7z78dK3X73eedBVFRXamqqyQ1gBIwpdu4UK9kPM6++PFjToZY9N6pAmToVxo5NoX37g9TVlbF//3PMmzeP21yEPgE5rRZgVD2TmAhnPT2BApeHmJCQhmRbGzKtPiaDWEd1tV9mXgCWLWNvXFfaDdDtiQUFYox9/339SyNHwvy6MdRFx7hH8psCH89ijhwndOmCOK1RUTKfVYP2nsOHG16LiqJqzHgmMIfNm4LEilJYKL/bB375BUYoK4gePtR9b/LsxwTIyqJWiabdhiAZ4nV1Yuj6C0q7SKEWVw+rJy6jXTt46CE53/WYMEFKMrOzSUpyG0/ZOPTvDw884N5rp4O27AZVGwQnNIZjvcMVGytBLZ0zM1ra7hvPExZApnV3+lCOVkXxB62TwyM40bMn/MYJ1EVFB8/hslB6u3kzDG+9m6jCAu+Mv/7/0DB+PCmVh2i2Izs4RMd79vhl5gW8glAvvyzJ/asX3chllynk5sJvv2Go5ybjwQdNhw/X1Ajp89lnQ8zqFfLg69f+pZfKlx4nnADR0ZwaK6XgJvyG1mGhL3jzZsjK3I1SUOA/OAEwfjxRBYcY1zKbdev4r0bEaQ0H/PSjTJ0KO3eqtGq1DBjB6NHCtnbccccJC6jJTKyaGnm477hDnMhXX91jeJ9f5OdLL6aHQeedRcgBkujcObXhpcpK2QE++qj+Ja1UUnyvgUAehw+/SUXFYRqN66+XQ1mfQdX9Ls1pqKiQbMbvv+vu023o2v1i/w5DVQ/y9tu5XHWVewa8UQ5DAJnWBQsgPX0td945lWeffdbtUNSXB4M4raoKhw5JRHBzY2t9LNLV60tdNebgf7w+ho/eLBcWCp1sQc+2fvaZeJx+DkXNwMrKot6JWvpOCXUPPMiu5fn1s46//16cnKA6rZ9+6jUb03utCHNwp04eZVQuPeuDV0IukkZcXDOuvnpPfUArFAGewkKJXcTEyCxjz7LmDfvkPSt/dTd+0tNh9Ggh1NiyRUqEm8S4bZGFcu5cWZMtWsAf/uAqD77ySli8WMLlBujQoQN5ecuorU3innv+yIQJE3jkkUdo1qwZWwNp7jrnHLjrLp+3aNld7c/o2NG1d/RaRqHLun766TSaNZNMa+fOYqcFI1lNcrJYUD564ADU5ctZUjucfvr4iYHxM3IklNOcAx2GhiXTqo0Wr3da+/Rx16mJgdbsjPFksptDS4NEiWqB5Gj5omoGspaoER5Zj3vuEcpoPZKTycsYwdCSOU0b0aJh2zaJANfXVJrA5SisQJdp1RiOPXsGPfpaR4wQktJGF2sNHy6N0Safo7bsOuevEO9F79yaGeITJoiB44pctW8vz0qjE5tW+oKrq2HNGn4qHMZpp+laYJOT3eRLSYHEtsnsTB8ePIfLIpnV6a0NHP/UVDk3PbOGLj2fUDsnOGRM77wjzLxWnFaXnrdulc6nG26QjP5ZZ8kyf/FF17hRDz03GaNHmzLzLl0qS+HCc0TPXlnMoiK8PqjkZBg+nFZr55CeTtN71S0GJ05NM2lH0P8fGlx6vrjVnEimNYIgwIIzs2fPHvLzDwIjGD/+HABGa6FFA8yY0cAoLlF8eOyxgsaxUu7aBXff7cVmJiW++ldyUJRMHn9cF2mOixPPQMda514qeSHQjaqq67jttkk0Gs2aySboERH3LsuUbMazzxo4rSUlHveLFXf06Ca+/949A97oDJdFp3XJEujbV2R99dVXqUtJqT8I9OXBIHtWairs3n0ciqKwXONrb4x8ECC5zCKgFRVHM3jgrw0Mx5rTGvS+1qVLJQDih5l3/nz5qAcObMg8ty0oEMMpN5dOnaTS6ocfoE2bNsEtDzaA+9xVgC1AJ554wiMN52H8AMioZYWUlM7s2dPIwJMetbXiABiUcGlxqcLCfHbvbsXll7uvnyMkUUsUv3/v3ZJw9dXitH711Y6mM26Xlkq5Q7wxozrI//XLL/L/qyoUFx8AEpi5vLd4WCZ9ki+++CJPPfUJ8CD33vsdP//8MykpKfTo0SOwTOu6dZYIQqZOFYLMsWMrmDRpGscdtwH+9S8KXbOqbrghlUsvbUVGRgFbtlQyZszhprGgBoLDh1F27mRF7RD3NrSkJG0+WP1LbdqIU7C82TjJpjS6eVCH3r0lcxEX53XJzWldvtzbgDQh+YseL60oCcuCNPTWjzNTVQXVq7OJVyu9ZbzgAglueKBs2AkMZzmbVwehr9XqmJEVK6iLimEtg9zHGHfpAs89535vp06y8biif336yMfQ6NheUZGlXsyW2wzKHc0Mca1kWxdAGTNGMq2Ncq7vuguuucb3PRs2QGUlc0qHuXc8GfQu9+oFS+JPlLVSER49b9kCo+NWyPk4aFDDhcREeOuthmCEhs6dOdq+C1nMD05fa2mpVBoZrGc3rGjQ86uvirjXd/kZWrYkcfs67rpLynSvugpqxnrruUn46SdTZl5tzxmaIHo2fBYN2vE48USUpUsZ3Kui6W0JGRkS6Dj5ZMPLNTUS5Dk+2kDPzZvLvu25Vjp3hi5dGKvOZ/36II7mcSAiTms4YKFsdFn9vK8RjB49lE2bNnH22WdLBlSbc6XD9OlymArEQauszG8cK6VJ5GfqVGmH0RAXt5tBgzq7O3SK4mWIu5dKdkX6+x6gsnJB452cL76AZ57xetm7LLMAiGbvXt3fojN+3O/Xwqibg0OMsnmzDN3VwSgbVVsrm2fr1vKZ7dq1ix+vuqo+Uu7ptEZFSUZx4cIk+vbt23in1UIkd8aMhrI9qAV+ACYBCtNyptdH+zXZgp5pteD4Hz16lM8+e4CuXT+iouIIubm5tG7dmjitJNz1PE+aJFWOS5a0ZcGCA42fv+uJiy6CN9+s/3HGDDzmrgJsIyWlp3fww8D4SUqSxENcXKfAiILM0LevHNravEsdNG6mPXsKqKoymiesMIi1/LXkTq8rU6d2AqKZPXtH0xm3LWQ9pk/3DOgfANry7J8OwhtvmEbmU1JSuOOOi4iLe4yysjNQXNGEgJ1Wi2NGVFWMyQ4dlvPaa69x8skns01VKaioICUlhZgYKVE/ePAg/fv3Z/v2U1i3rgkOgoZ588QA8jUr0tUKsJ4B7plWbd/2eBZHjoRvCseJQaeV+DUFkyebZgh37ZK4Q3s1V3q0PA3IkSPrGY7d0L8/h2NT6bAjiE6rDz2vXw8DjcpawZjhGEg8LYs4qjn07ZLgyAeWnNYdif3p3KtZA9moiZ4BOVTmzwdVra8w1whgAsaf/uSzTH3rVujZpoSo7VvdmYPBmCwKpFQ8Kcmtbnn0aOH1atQ2edVVcO65vu/RZavdHP9zzvFiOO7VC344ktUwIqep8JOBKyyUGFrfihUSkXXPKMhGZJABVU7IEqc1GOX0VlqgSkpE4cOHU1govE3nnw/t29bVMxw/8gj8/e/w/vvw9JwhXnpuEqZMkTYoA2idLW33mqxng6AyIGuluppJ6Uub7rQ2by6tGe3aGV7etUseqV5HDPRswHCsl7H3wfkcOaIGx551KCJOa6hhwszricWLFxMdHQsMpl076N27txhb9cX/7nB/KDXjs4CcnEaU6vk4FLVqkyVLoEWL3YwaZcA84nEoepdKKoCMtlja2M39s88MNyLv35UPpJGZqXu0dQzH7vd3AJoDWxrPaqyHBzOvWTbqpZdkU0pKKgYgPj6eV3TkC0VFRSQlJRHryiTNmCH7+datsHPncObPb6TTasLM6ylvA5YiQYAzADg5ag78+CMQwkyrhUPx229/p7DwH6xefSldunTh119/pUOHDl7Gj1aGWV7eFjjQ+Pm7eqiqNMXomHmNHDjYRmWlAcGDyaHYtSuoaqfgZFp9QPPZVDWfhn3DHRvob8hw/MUXsShKZ7Zu3aELbLjD8mHZKGbeg0AbYvbuknaBNWtM3xsXJ7GF995r2Jp69OjB9u3brRFJWdy3Qcqty8shLk50V1JSwsk//MDao0frCeFatWpFdXU127dvZ+/epcA6Hn3Uvxg+4YeZF6inksymvzfhp0FWYeRI+CrfRWkerMyHCXbtklaMqLWr5YWhQ91v0BiO0zyexago9nYey6CS+cHp07v6ajjpJNPLy5bBUFZS17yFd/nlv/4F48Z5vaf95LHUoaD8HgRD3OKYkdoVq5h/ZCiXXOJR9WGWPRo3TkYDbN2qG6HXSBn9rJUtW+C0dq716qlnk4w6MTHipeqcGc3HWLs2QPlUVQI4rnFypli1iqqEFmyjh7vTOnWqOOY69OwJ3xW79rBgOFy9e0ta0mQsj5at7rB/lfdnqAl03XVeL8efnEVbDlK8LAhzb6xUk61p0PM//iFvefhh3DLqiiLn5oQJ8NKrMaijRgfnM/TDzJuXJz5gs02rpOekRw/3GwyCykD9WTWmdj4FBZZGY5tj506pJjOZMaWtwTb7TPT8ww+ehpogK4vEwwfpydbgjThyICJOaziQnQ0uIhA9tCycoqg8++yXtG49Hoh3r+pLSRFnw+N0dneyWiKOoZSbNqpUT/tdHtA4e7p0qaCgoIBOnTp53eNpiBuRkyQkjEBRoljU2IYUk0PR+3cVoCit3EmUhg2T3eqkkzzuV4BeKMrmxrMaazh6VJh5dQEGs2zU44/Lv+PjiwG47rrr+Prrr3nz+OOhuprCwsJ6p1BzJLWEZkXFcIqL83jhhUaQ4Zx1lmRQTGZ+ecv7HRANnAbA7TEv1+s5ZE6rhUNx0SJ5zu+//1XatWvH5s2bxWn1MH7ef197R1vgMFDRuPm7epSXiyesOxS9natioICjR3t4XhBSFAPPrmdPOHKkE/v372fRokUMHjy4fi5pwJg5U8gjDFJ5Db52PlqFhieujPuId8/9zO017TlU1W6AeXOUp39hioceEuffB7y3Gsm0Nu9gkpnxwB/+IBw+b78tP/fs2ZOqqir2WqF/NNCzGbQ4g6rKP2bPnk1JdTXz6upIq69IGIaidKNhTc3g1VebGECx0qOenU1ldDPK23T11s1bb0lbiA7HHw+HaMORDr2C47Sec47pqJadO12lwdoh4+YlIHvqvHmGGfWyYVn0Zgu7lwWhV/3pp30y8y5fDoNiNqAMGuBN2JScLM+Kx/kc0zqVbfEDaL0pCIa4FT3n5xOdf5C1DGTKFI9rvjKtAPPnk5EhCaBGZ1p9OAqqKob4yCRXC9HAge43aAzHng6EJuO6dfXOZqMzwuXl8nz5YOYFIDub3NT+xCdEudo2XNAYjusaWHh79YIi0qjoPiA4DldGhjR+mjDzbtkCrThEfMlB788QvBiO6+HSc4vVQQqg+HNaXa1iea0G8vzz4u8PHIhhRv2mm8Re3dLWXc+NRkWF7NsmMublCamfsiFbngfP9Tx0qNhJOj0DcrANGECvA/IZWuCyNMe8eRKMqx+J5o5Nm0TPcUUmejaDS89ZzPekp/mvQsRpDTUURSJnHsy87mQ3q6ip2c7BgxcTH+/BL2IShXR3vqKBVPQjFQIu1dP/Lh2ys8VBLi0Vw6GjUVlCv35uxAr60T4annoqiUGDBjbeaTU5FLXfpY1yiI/Pp2fPdNOeVG/ZepOQsNnt/kYRzBQVeTHzmmWdNLbymJhiFEXhqaee4rQ+fbhu2TLef/11N6fV25GU0qoHH2xktlVRTJl5veX9DhgDpHLllbCsaghL98pzHDIiJgNmXk+sWiWb/S23nM3ixYu58847ue6667wOxYakpcZKImWUTSqdMQjweGfpxTNs3dog09qypTBlemDAACgt7Yyqqtx6662sXbuWJUsaWVrog5l32zaIiysHKjDKtGZmwlNdXuCE9e7kbw3PoW+n9fDhIJVgA/fdp/9JBXYQE5PJLX+y5rSOGCGJmn//W2yQHi6j2FKJcHW1NCqbZD300HzgLVt2oyipnHBCFhOP3khzoM5Vgv3hhyejqtuRqoXTgA+oqalrWgDFSq/j+vVsT+hP3/4GR/2ECV5G0dChsj1sbTtO2OI8jbdA4YOZd9cul9OanS2VMJ5edVGRZEAN6DoTThEDrfCbBU2TT2Pm9YFly2Cgko3iVl/tghHDsQs7O2XRs2CR1wzzgDFggDDzGuwb9XCdO0e79sNLTLOSx9695dyeP5+oqIZpBI2CjwqZzZslM3VcfLYc1J7l3m3bGjMcgxjiqirPIsLt0LZtI+S0mK0mO5vNUf3o08eDVuHFF+Xz1zlVmrh7u2ZJo21T9eyHmXfzZhgY5bIvzJ5FEz2XJrSmy54gOK3Tp9dPwjBFtuj5+c8zqKmRmbaAoS173nmy9N/e7q7nRsNPKX1enssUz842/gwvu0zIT432rKws0jYvJJqappUI+3kWt2yBUS186HnqVLwjU0Dv3qitW3NSVMRpjaApOHRIIrm6ckLQjMAfEAP3EyCGurrzvfcrE5ICzflqcFzdRypAAMb5DTfIzampXpeyXQGpfa5od4bngQOyyF991Uu+Xbvg55/l50cfhTVrRvHzz0t4771GGEI+DsWpU6Xtt1cv6NWrgL59PTJIVVUS8f/wQzfZVBU6d+5FRcUuKl2kI40mmLHkzAhatpTvilJCs2bJ9OuXSOtNd3E8cM9DT1BYWFjfM+qtw8FANIcPLw/cOdCYeU0MUXd5c4HVwJlkZsILL0ByTBnP7TgbkL5BCEGm9fPP8TfBe/Nmec7btUsjKSmJp59+mgsvvFCsmbIyuPFGQP/3nI+MlLkRONq0UnCDQ9E72y9r/c47DTIH69YJJb8Hwc+AAaCNvVnl6pHbotWDBQofzsz27XDccdo+0WAEJyZKZnrXLmjTw7tEquE57IaU6R4x/NVVVRaDZWefLcyrPjBqlHyXeFgucJipU/ty4TUm5YQGuPVWcdSXLAnQaW3ZEr77zi8zLzQ4rStW7EFVRYe/cx/d+JgNG19gxgzPdTwV2AMsMC2ztgQLvY7q+vWsrupv3G64bJkMgNZB47tbljBOHM5GezEumAQby8ulMrU+02pknJmxygIZ5wyjnGZNL7/dskX+aNfZYCTn/nWHaFl9KGAZy47LIkk9QsWi1U2TUWPmrR+y643adWLkdjq9v/fFu+/2msEOSHRi3Dg3MqYmZVpNjPC5c+V7twqXnj2Dpqoqi8go86QRrukymX36mPLsmMNKX3B+Phw8yJKy/saOv/7/QSrFFQXWpmTJPGEf7QqW8PbbUupgcj6vXg0ntfHhzJgFJxSF/T3GMaJyvi+uLGsYM8aUQKgervU8Z67CqFFCUgc0MBzrMuqxsdLp8dzikageem4U/DiEubnQK0307FXZ4Q9ZWUSVHWFUwpqmOa2ajkzW865dMCbVh56NGI4BFAVl3DhOip7v6W78VyHitIYaO3caMvPm5KgIs+4I4G3gVCDNO1jXuTOMHWtIBzZ1Ktxyi3YGpOPptFo2zk2YeWtr5RDr35/6kjrDTKsPaAadVDqORlVLmTZtY+AOl5+yFC2CVlBQ4D6jFWRn/P57jLjA+/btDahs3iyGbKMJZiw5M/Lz8OGyf69fX0xFRQo5OVBGOtOAA4V7WLZsZX0m01uHiUB/YHngWZolS+CTT0wzH+7yrgYgLm4sjz0m++t13efxSeEp7NsH0dHRtGzZMvhOqx+UlkJubgHQgoSEOPdMeFSU/AEuo+ixxzSSw2TgdWATMTGPNq0U3ICZ1zt7L8/S7bd3837/1q1igHqUPOqd1piYGJKSkho/2qi0VNa0R69jWZlk+YcPF4e5det04xFPBsZPw3OoHfTGRj5YDJZZYObVzuUff4SffxZr+sor+4qOo6P9ZlqBegbQs86Czp0zUJQEZs4MbsNPQ3nwbjQd5tGBdVzM0ZoeTJ/uuY7PBeKAb0lObsLYoD59JDNg1tNaWIiSl8fK6gHGCeN//ct7XAtiU/5U7urTbGqJsElbR/2M1kxXr6GRAelDz6lt41gVO5JWTS2/9ZOtXrsWeteZlC+DOfMtEO/KBud/2UQZ/TDzApQszKaUFnQebRBUvuACcwKirCxZaLm59OkjevHuz7eAO+8Uh8QAc+aIeZGwI9vcUejSRYL7nmjWTA5MD6d106YAGVKtZFpd2eqFxf28xTTQc0KC7J2/1jaUWTcJJvs2yN+6eDGMTdsgh7GRHWbWjwnUjcmiOztY80MTZ2z//LP/yEZ2NlW9+rNiRQMBNCB/21tveTm9Z58NFTSjsOvwpn+GHTsK5bxJS0JeHgyO9eEQ/vCDGGdGTdOu8tsLWs9vutOamGi6b+/eDUNishulZ7Ky6FS9g5KNQZil7lBEnNZQw2Sz7NSpAinRK0F6tRqmzbsZMBMmiOHQzcAARu5TVYiKkjmAGhITsW6cf/65NyU+kpWprHR3Wg0zrc8+a8hwDPCXv+h/khE+R48uCtzh2rLFdF4tyGbUrp1Kfn5+PflJPRTFdKGPHCnW3G+/iYNgZnD7NcQNjB+9M6N3DhISxIhdvLgYVW0JQAkpiFkRTXX10Xqn1ViHxwMLycmpMrpoDj8kR+7OlzhezzzTwIB7yzeTqCGWzz+Xn9PS0oJfHjx5shxsJpDPowBIr8+EX3GFBG8AKTNzWf5Tp4pdLphIs2Zn0KrVZ42ffwqyGDZu9Dp4tey9JPG2k5LSjiSjOaImTJmdO0Pz5p0AhYsuuohBgwY1bR6vgXGmRV9btpTg1ueftzIe8WSwVhpG+pwJTADuwqxM2FKwzALhlpZo7tkTNrqshD59+ogga9b4naEK0j4E2szoKFS1C7Nn7/LvHP76q5QxWmDQbWiR3QPIH9+ag1zDm2Swl927PQNCzZH51SsoK2vC2KCLLvJ9s6u3bD0D6NnT4LpJOWGPHvDr3h4yAycYTquPGa29m+2WLJWRAemL+RbY2i6LTvmrDEtzA5IPTJ/FbdugHz6M3OOPFx0YGJfdT8hgB12p+62Jhvj99xv/bh1q1m5gA/3o19+g9WP/fkOGY8Ctr7VPH3kOG0Xics01ho5xXZ0spXPG5KMcPNgoPZOV5TZWpm9f8eEDavkPwGndgA+n1WO99OoFi/Z0FEOsqQ6XDzKrrVtlD+tbm22crQbx/kwCB12uED3v+aCJMk6ebMrMC9Rnq3cm9KO2FvexQSAPmEdmZsgQsYnWJGc1fXxQ8+ZiMxsw85aVyVbRu9bHeo6NlRJwo4BoR9FzltJEp9VP/3dODvSoNqlKAPOMOtSv54wd85vc2eFURJzWUMOEROHeezVj/zHgZeCy+muBGDBdusj3QYNaER1dYJw58YdPPzXciPT8GPv27SM5OZkWRiUNubkN1qEH3J29nkjWa1U9y7HlDENcnHfa0gVVFRFaty6jqqrK22kF04V+yilizS1cKBZyp051gLeh5tcQr6iQHkKDsUGe819zciSBUF1djJBoQSFpVNOOVIQkSSsPnjoVvP+cc4ESoqJ+DiwzY4FEYepUSUgrynbi4pK4+eY29dd69FRo316ISTQZg5ppNWDm9YRMFBKnVf+2V15xPUPvv+9W8njbbbIeLroIrrmmC1VVxuQHwYIcZtvo0sWgNBhMe9SjoqB//yQGDfqaZ555ht69ezfeae3YUZo5PbBzp3xPTJTglldFgl5G3VpxH+kTBbwFRJGScqthJYHfYJnG8OjnWdy8Wf6U5s3FaU1OTqa9xg3Qv7/RwvDCQw95vtKZ2trd/oNmBQX+mXld2LsXYmPLgEK0TGsmObzJdQxhNZ07ewewkpKGASuprXVPFzWZKEwPV2XJegYYtguaBfJ69oT8AoWqkeOa7rRec41HukVQP6O13EcWE3waaOVDxxFNHVXzGsmTAH6dmZwc6E82qlnWo2NHyXYbPIvdu8PCqCzSNvzetMGJFlisE3dmswGTMvCnnzZn6taNlWk0yZEPZt7168WPOaubHz2b9WNC/bgRbaxMo+Ts00cWoOFCcCE7m+r4JPbQybw82GO99Osne746rmF8UKPhI5C3eLF8b51vUpUA8hw++KDhpYRRQyiPTiJmUROcViv7tstoXHy4P9HRBsdQ795eDMdxcZJM//5wEMYHacy8BoEs1zh3Mo9kyzNvRCpqNn5JQ1YW/Qrms3evypNPSgFfwHj4YcnoGiA/X0zJjCIfVQm+Mq1DhlAVn8TI6vn1f+9/GyJOa6hhUn40frw4ra1adUdRbiIqyntYc3k5vHD/Hnl4Tfr8tJLEjIx04uMLjDMn/mByKLoC9fTtK5lW09LglBQhs6jyzvy5O3sK0B3YiaIEkGGoqPBi5tXjwAG5pXVrcUgMjXGTSO7xxycD7Vm/XhyEiy76AchC77haMsTPPlv+fgtsb7t3a9HsYjSndTXH0YE8irgBaCA6AkmCuzsHpwLJ1NV9GlhmxsqMNYQLQVW30bFj9/oZlwB8/z0jopazbKkczG3atCFXG3wWDJSViXfv41AUFbo7rSDP0fTpGG7oo0bJoZ+enk5RUZG1kSdmmDlTjPCDBw0vS0nrdvr0MSBhAp+H4oABsH//2bRt25ZevXqxf/9+Si30bXrh4YdlrrEOM2bAtdfKv596SpxWw+AOiOGjG73jXTLfGbiGkpLfeOWVOq9KAr97j6ZnC5lWzcbctGkTffr0aXgeP/pIgm1+4F0h0RnY3ajKCTPs2QN9+mifl2x4JYie06NL6vcOfQDrX/8aBhQBuyzIbIKzz4ZTTjG/vn49R+OTORCdUR/cdENysuG+rbWcHegxToxAk3m4lvDMM3DhhV4vazNa0/a7DhmzTOKbb5r2PneeMppaotj/aRMMcT/MvDk5Uk6omGU9KislYGvASB0bC/u6ZdGi4lATZsngf15wQQFJZQfYn9bPOK5romfAbaxMz57yJxp00fjGkSNio7z2mtclrZ/1+CQf2S1NRrO9buxYEUzXewsBOq0dOwp3R5s25vds2EBeaj/i4xXvwrbMTCHm8GA47t9f9sb8vlmS+m0sDwH4dAgXL4bMpAJiCw6Yf4Y1NZKONUqxxcRwsNto+hXOb/xyLiuTg9bXs+hyWmdu68ewYQZtm82aGZ59Y8bAu9vHour03CjMnSvMvAbBdM2Ja53vI4tpwWltXnaIXmzhT3+CSy4x5c0yR8eOEiwyQE4OpJNP4hGTqgSA444zZjgGiInhcP/R/9UMwhGnNdQwORS1ssoPP0ylrs6cpHHnvjjZCEycA81pralJp7y8nIrGlFaYHIrZ2fL/JyX5cVrN5qxh1Ncp7KOeAUmfGYbCQskEm9RkaBmklBQfxrgHw7GG+Hho3rwXe/aIUdG6tZzYLVsuCDxr7YOZV4NrtrYrEFgCeB5SF6AoaRw61BBl07I0DWyG8Ui29SvKy6usZ2YSEryZGw3w668A2xk40CNbuH07w/d9zeYtoup+/fqxadOmpjmBevhxFGprtY/X22kFl7FvELEfPVoci5iYVqiqSnFTaPV37JDgiUkGbvPmCmAf/fv7ybR6ZDK7dBH7/OBBedR7u5oQG51t1UEjF9PO8eJiCe7MmpVm/AYPhmNjJ6ofUM4JJ+zxqiTwi5oav8y82pgMzWnduHEjffWDRl980a06xIzx27tCIhM4QKdOvhljLY0ZoYFDpkcPcVqTkyV6X4ro+dbLSww/k2H1Q+29y48tcxEUFvreb9avZ1fSALp1V4yIpE37MTW7fFMrV19rYxk9fTDz7tjh0tfGDdIfbhZAmTABBg0yvDTmtBas4rimld8OGCDltya/PycH+qk+slsaw/E33xhejjpRyvWq5zTRsbbgKFT19JGZAd/lt+vWkXC0mKwsWTsBbek+stW//y56Ttu/wTy7Bb5LHlNTRU8uZ6ZTJ7EpAirR3LNHSoR81Uxu2MD2hP507uzBHAzi7P75z3imsoWLANa1DEJf60MPNczD88DixXB+bz+O/8svy3NsUv0Uf2oWA1nHvK+LGyeflT1xwwbUpCS+XdPJuzRYe6/Bczh6NByqSaW8WxPHB/mwITQTOnmvj/Xsw5YF6stvlz89n//8R+y4gIM8H3/sRYCnIScH+uJ6sM30fOmlPrlJok4UPe9eWxygYMcGIk5rqHHjjWL1mTitWhmox0SceqR08r2IWrSQfaqiQozMApPZTz5hcihm6yoU/GZatf/HA5rDpf33LVp0A3YC3oeHaYbBTwmXRtjSvLls1mlGwyI//NAtEqw3cisr+1FcvAFVVeudhPHjlwRmiH/6qaSy/JQHaX+j+ATFaJnWGKr5mnO4lJ9R1UO8/PJZbhnUqVM9z9uLXO//xXpm5ssv/TLzAsydW4ui7KBPH+/B2yNYhqoqrFgBAwYM4OjRo9bYWK3AQtZDPl7jGaOdO+MWsdd0/Mc/yvUFC+Q9jVojGrRn0YT5LztbHsYePUwyrW3aSGbi5pvrZWwYfSW46y7YurUJTutZZ8G999b/6J0pPQS05OGHjTwZZOFPn17fNGbsRIkDuXHjRvLy8jj55JMZOHAgU60sFo2Z95xzTG/Jz5dqw969oaSkhLy8PHenVWf8+GL8fuwxidU0QP6YO+7Yg09YYRt13VZWBrGxsghXr+6EqsL+cnmGj+9jvG8PGDCA6OhYoqLcndaAuAh8OTOqCtnZrFdNSoNBMqCLF3v9H1qWaXnNEBGosSXCmzdLZuXjj70u1WfR9YeMEZYvNzXw0tJgU+ss2u9eIhnPxuD442WEh1H/OVCyo4D0Gh/ZLT+ZmZ5n9uIAbSj6pomGuA9HQWMOThjqI4vpQ0b9WJnbbpMgsEn1ojF8rJU1a2SMUv2IEbMgy113yWBlM4wbVz9WplHjed58U2ZgmZ3PhYWwfz8b6Gcc1zVhONYeiyXFDeODGo2xYw0rJ8rKhBdofFsLpfRgaiu2u3AcUajs/biRQSgr1SfZ2Rzp1I+qaqW+XdpLRoPnUCsj3tpmXNPGB/l4FvPyIJVCYvP3m6/nli3hqqswJgGgfkxUi9Xz61UVcEzvb3/zmrahQWtHAAJnN3Yh+cwsolCp/a2J44McCktOq6IopyuKsllRlG2KojxgcL2PoiiLFEWpVBTlHo9ruxRFWacoympFURo5XPIYhgkzr6fTevnl3m9NTISHH0+QrI6PMsEuXaC0tAkGucGhWFMjNkf//lBdXc3+/fuNSZhA/r6xY03/ez0hzgMPdAOqkBEW7jDNMPgxILVMa0JCMdDwmZrB08itqRkAlPD443vrx4wEPCNz8WKJfvnJtGrOyS231CGZ1pYA1BDDJH5gIOuAKMPMs/vnMxFIAr5t2ggXD9TWwqpVe1DVarp393C8kpMZjizh5cthoKsUen3AoUYfv7x3b9MSLkko1CCfm7vTWm/st2wJtbWGzuDPP8t78v2w1vpESYk0WRqmrmDHDnFeMvVDivWIipL3u54TI7bqykp48cXuREVFNc5pXbPGjZnXO6ixFehmHuzYulUi/q6SRyMW7Kiovq5ftZFvvvmGOXPmUF1dzQcffEBZWVngMuswY0ZDlf0TT8Czz4p12kef5dBl1H0xfk+d6t6u37atLJYhQ/xEejRmXq+Uizu0Kuq6uj0oitKwRyYkyDNi4ijEx8czaNAA+vdfWV8tEx8fIBeBL2fmwAEoKGDhYRMSJoAOHWSkSJx7a0piohRkbNkZK7X1jXVaTfbtujp5xHr3Us3H3Wh45hlpDTFB9cgs4uuOUrloZeNkLCoy7MUEORuSdvvJbvnR8+gxCr8zjvglTXBm7roLrrzS9HLJog0cJomMUSZZTH+ZVt1YmfPOk8fixRcDkM8kqFxWJkRWgwbhX8/nn+97vFSW+1iZgMfzlJbKvmu2nl3Z6mXl/c2Lkbp2hX/+0+2l5GQ5l9dnK27jgxqFn34yLCNfsUKOxoHRPnoxwW8ARRk1kpqoWBJXNFLGTp2Emfekk8zv2bCBvcmi5/piEk8ZDZ7Dtm0lWPZdaRPHB2nns4Ge8/JgcIwfxz8hQUYPmbVd6MZEde0qfE8BO60+go1aO4LqS8+zZ0v1werVhpejx4ykilhargvCXF4Hwq/TqihKNPAiMAmpCbtUURTP3acQuAP4J8YYr6rqEFVVhzdF2GMSn30Gzz/v9fLPP4vT2r17Kl26NOwzHTp49IddrvgunUGc1qIiybQ2yiDfts3rlNqxo4E5eP/+/aiqap5pHT9eDBtPJ0cHzTCLi+sKQHz8TrfrPjMMfjKtO3fK5lFeLp9pS20Qqh7PPQcTJwJGRq5YyE89tZ7NmzcTHx9Pbm4ue/fu5euvv65nLvUJf31HLmiOwmWXHQZUUlM1WRVKSCGZUq97Nbg7D/HAUKKiVlnPzFxwgWzIPpCTA1VVQoTUw6N/h+RkWlFA1/YVLFsm5cGKorBu3TqLAvjBgAFiiUyYYHhZ1CDZ9CuvTDfupXzvPVi92tCRqasLQqbVx4GjqrB/v8hnSnIE0nP6/vuAeXXBnj3xdO3atXGzWj2eRe+gxnpggHmww8PINWLB/vOfWwHpfPXVRhYuXEjr1q159NFHAdjqj3507lzp61np7WhowYYDB+Tngwfh8cfFOnXLtOoy6v4Yv6+5RvaxM8+ERYtkI8rxNyB1yhRLzeJaK+PRo3to164dcZoDqCiwejWfZd7tVbasVQCsWjWM7OwV/P3vKvfcI8/P+ef7/ZUN8JVpdQWSVlf3N8+0HjokGag93lnnHj1cTNjjxokB2ZjeapPMzN69wkEwtPWehn5IM/jqdQQ6XCwlzHs/bKSBdu+9pr//0CHoUeUn6+GDmR7EGN+QnkVK0S7DvldLuPZa85E1QPWabGG8HWASMB0xQvYbswWvGysTGyvFYbNmGY+CNITJ+bx+vTzTw7tJFtOnng8cMGc4BjeWYyDw8Tz+yKxcBB4LikwyrT4YjgcMcL09K6tpPeCTJxtOSNB8kw7FPnoxwX9pa2IihzoN47iyRpL0JCWZMvMC9dnqbPqTlia2rBd8MBxPmQIvZ4uet7zZyPXsI5CXlwejk/300GvwVR/v0rOSu4+xYxvhtPqQMScHjovLNu+hB98MxwDNmrGt5XAy9/yPOq3IfI1tqqruUFW1CvgIcNtBVVU9qKrqMqA6BDIe2/jkE6+NaMYM+OijIoSYSOZ0alM+Nm826A/z0/+VmQn79zcY5GPGjOGFF16wLqMBM2+2bm03dkarHhoRSF2d1J5dddUO6wQuFRUSOfPhtHbtSn2vomGmNS+vnuHY28iVw7Sk5Dfy8/M5x1W2+MYbb3DBBRfwuEmfiRssMDyCbEpxcRAfLxvOU0+l1Dv0JaSQQsNG5GljeJZaJyUNITZ2LXV1tf6ZmOvqpDTYjyUi0Wsp9/VyWtPSoG1bhvcsZdkyaNasGT169Aie0+oHGzZAq1bicJ52WrpxL6Vrozd2ZJpQQq+hY0fJPhkgLw+qq32UqGt4/32xCjG3I4URuzeLFwdI5VlXJ402umfxjDP0NxQCucTGDjAPdhiUE3qyYD/yCKSk9GXlyo0sWLCQMWPGWO/Dzc8Xw84jwwfGWdOqqvVAHIsX69hRdJlWs89Q//rgwVJil5GRgaIo7LZcU+8bmh9SXLybzh6CzFjdn6vubuVWtnzNNeKDiM88lLq6Am64IYeoKOHJCSipec01BjMlXNAxB5tmWnfvFiZPA2fBzWmtq2ugLw0EJuX+WhxmQJSfLKb2Xh8B21HntGETvan9tQlGro+sRz82UJ3gI+sBfoPKlSPEEFcb03urqhKt8/H/J+6UcTeGzMEgaXNjGvoG6MbKaLxZi6ySMvftKweTx4OmJcuOi7eg52eeMd1XgfpxI3qnVVUD4D2y0Bdc1zyJbdWdzTOtJs/igAGioprRTehrNdi3NaxdK5XH8dv8ZKv9lYEDNWOyGMEyVi9qBPfJjh1S6n/kiPF13ZzbQYNMfK5LLjElL3nsMXhvTkf2xHRh13vzAyc4Apmx+N13hpdyc2FwnKu32ld5Wu/epo414BZAGTtW9gnLcQofegb5v3rV+NGzP7IooOy4LPqXL2PVwiaMD3IorDitGcgAOg17Xa9ZhQr8qCjKCkVRppndpCjKNEVRliuKsvxQQAO4HA6DQ3H6dKipKUJIeEQF1dXaKASD/+Pdd+GOO0x/RZcuUFkpB9KSJUtYtGiR9fLW8nKZC+Kx0eqZg/e5VqRpefDevbJzezCW6qHtEUeOZKIoCu3a7bBO4HLuufIBmURq9U5rTEwMiUYUiikpYhUePWqwX6UBHQCR/9NPLwbi+OtfH6Wuro4dVkLOFjOt27aJrKWlxYBkhbUMainJ9U6rWeZ56tSGFrEbbxxCZWUZ06Zt98/EfOSIf+Y/NKd1O/Hx8d76HjIE9u9n5Dlt2bVLJtMMHDgweE7rV18JM6+rWsCTXGf+fOjUyQdDNIgzeOml9Ohk1OMWhPLgRx4xfc7lMRGn1TDbr0Fn/BiV3mqoqBjO7t3reeWVAOT10LM2rqYBsrBPPXWA+ZqzcCgCjBnTl6qqVWzbtpUxY8bQ02W0+nVaffRGGfuSvwHHc/PNMQ3P9QMPyL6jqoafoef66dVLbq+ri6N9+/b+ndazzvLNzOvCnj3yfO7fv4tOHo7Noj9+zJnln7i9Vl2tJ3GVMSRHj/7Ghx+KD++KZVjDs89K9YQRsrOpSGrNIdqYZ1p96LlHD0mOHRkwSv7AxpQIm+hZczS6lFno3UpOrt+3jZCSAmuTs2i/c4Fvkh1fMprsibt3S39ZVQ8fWQ+A11+H++4zvZxxxmAOk8ThHxrxGR4+LAbs668bXy8qosWRPPLb9DfdR3wxHNdDN1amVy95FteutShjp07CzOtBdLhmjbT+ty9sup7rZXSNldGKLiyXCPs7n7OzqejSF1AMJxvVy2iwVvr3F9G3JQ2pHx8UMHycz2vXwpi+RRIV9fUZagzHPsb6pJ+XRRzVHPy2EWNl5s4Vp9NszJ3LaPxhd3/zIQq1taYMx4oiRXu1o7MYcng+n37imx/EEJ06mTLz5uVBn9psMWp9rWcThuN66MZEaV1xCxdalM+PHVays5C0Sj9VCRaCE32niZ5nPdqE8UEOhRWn1Ui7gTxNY1VVHYqUF9+qKIphaFhV1VdVVR2uqurw1gYsr8csioulz04HsZeKAPeMYGNHfElCTAzyL1wG9UGTkRxeKCiQ0mAPQzM7WxwFjTkYfGRa4+PlDT7CTfHxUi6yd28cnTp1suYI6mHCzFtdLYZjt27SJ5yamuo+pkWDZqAVF5s4CgOBLbp/D0FV60hIaMGGDTv9ZzLj443n+Omwd+9eli//mOTkWfVZ4ZYtW9ZnUHcn9uUQbfxmnseOlcRzcfFxABw9utrtuiETs9a3ZeJMaQ7i3XcDbCM9vRtRJux0l14qFSrPPCOEMtu2bWsca7Untm8XZt64OENyne3boa5OnFbTcS07dsBHH/HE/cUGOm6BosQ0LdPqA5rT2qJFCjEmPa+A6MB14OhLb71xFlDHQw8F4MlUV7tVZnhnLsWwWLNmgPn/oVsrvnDKKX0B6V8dM2YMiYmJdO7c2b/T6uNZ9A4olSIMuye5P9ctW4qRrCiG5cue66dbt4bnKDMzkyVLcnyv6UOH/PazggSh2rXbwrZt2xjjMQtzcv7L3IavipeBSPb/F/bvqeaLDrdR9dYMaxmG2lrf5EPr17OvZX/fhOE+nFYta7d6ewsx0hrjtA4cKM6cR4BpyxZpO0veu0H6131lALVnxMezuL9nFi2qixoirYGgqMh0T9QyrTED/ZQS+mA4Bhg1LoaFjKFuXiOcGT/79uElkt1qdYIPGUtLpQ/RFwmfbqxMbKzY9ZZjkTk5hsy8a9bIx6Js3CAK95Wt1v4+X85CVsNYGW08j2Wn9c9/NmXmBWDDBgrbiaNgul50+7YeGoPw+k0N44MChomea2ulaGJCOwvZ6tatDRmO9Ug8RbysRs1r9fMssmEDdYnN2VzRyXw5/Oc/st59JKY6T82iDYd4789bAo9Dffih9AZ7QCqXILPMB3OwhpYtfZ99ujFRxx0ntqQJebg3kpIky3LNNV6XDh+GDiUW9GxhrSSdNpY6FI7+PL++1ea/BVac1r1oE9MFHTFi0TGBqqq5ru8HgS+RcuP/HRQVSdO0DmKYeTutppHSm2/GmIpNMHo0REXFEh+fzP+zd97hVVTpH/9MekIqEDokoUjvVZqAYMXeRWXtbV17d9fyWyxrxdVde8eKvSKIoqBI750QSoAQICSBhLR7fn+8d24vM3NvQnTn8zw8ITcz9547Z+ac8573fb9vgbNqu2FvtVMQyreNazye7a1bt5KUlBQ85FF/iPT3CkJurnhVO3bsyBZdPckI770nFkwAtm+XgV33tAb1cOnf78CBgIvcuDh9ER+LlOU5FeiDpv2NAwd2sXVrZWhP5uefw8cfB/0Ky5cvp0OHDmzbdj5Llpzh8vbp7Z00CU479C6XqVfDep7T0kSRce3aHkA8sMzvGD9Hkj4IBwid9hct2kRRUWf/7+hwwGmn0WbWW1x0kaTD5eT0RinFGmdoUESUlIgVkZYWMEwUYNOmMEar8/udNa7Er4+bNdNITGwemdF6/PFBw5t0o7VZsxChwXobPSZFPfTWf69lINCSffu+Ml6Lt1kzCY865RQgkOdyFZBOYWGIDZbmzWVH+K9/DflRPXroOabxJCWJ6kbXrl3DG60e/ezLlCmy0e1mLlAHjAU8vs+6ddIPzuQs3/Bl3+dHV8TNzwelOrB27bbQ0QkHDgR8VjyZNk0kC3buFG9qbOw5Xn+vSs4ii1BjYozze/1A6w5xjD48g+MOfMDs2SE/Vli9WkRDPv3U/2+6cjC96NkzaGWEkOP2mDFis8+YgYQIz58vGyJmGDIEHnvMb2LTlYO1NWGUg0GSfOfPD9kXdcNlbqz+wcJCPMD8rFO8fj+t2U1CvzBG69KlIeV2e/eG3+NHkb59Vdg5MmD7IGgb10wXQ73vBQYWuaE+26esTJ8+JjytL78sob0eA5jDIef37YssJrp3D3Ej4v5+odroEZaZlCRzvmGjdeRIOPbYwH8rES9mYYZcw6BG6003uaXoPejeXWyRq6+Gn+pGoVZFr583b5bsqEHJBnMxCwtDGoQ0bcr2jF6022LxWQkybgOwZg2lbbqjiAlutBrYhNLLRLXe/Iv5rIQHHoBXX/V7edcu4EAJmRW7wl9Dn/k5IKNGwapVxB8s4ZprZC4wtMmj75IGWEvrm2RAeKM1lMIxQFYWNUf1YnjdL8GEiv+wGDFaFwJdNE3L0zQtATgf+MLIm2ua1kTTtDT9/4jkaZSkRv8gBPC0TpkCMTH+RuuECUHeo6pKVmJByMyUesOa5l7ImzZaPdr49tsy4Xz9NXTocIBXXnmbkSNHBvZggrjdUlPDPui60ZqXl2fO0zpvXlCDULd98/LcntaAtGsnFayd+C5yRUEYxGCNB+4FllFZqS/MC1znhqwpG4SCggKUUsDF1NUdZuHChQBkGMiDDcQxx8CiRQnEx/cgkNHq57Gqq5OVYsuWfsd6G4gOYBN1dZ39v2NMjKgHLlvGbbfJZLp0qcQBRSVEWH9WNC2ouM6hQ2GMVo8Fmm8fjx8v9YwjMlqXLvUre6CTnw9JSQaN1gAGgL+XMQY4GfiOK6+sMW64hnxPEWHKyQkRHqVpXgrHwdDVfDWtP++9J5ambrSqUGEjPXqIXHqA9580CR5/3POVn4AE4Gjv77Nli3hOwgkqOfE0Wtes6YBS2/Esu+X3TIfwwIEsUq68Uu/GD4AR3H13O68+6jwokyztgNd58fG+qbzHAoWMGLGR5JPGcgw/886bBlyt+rgdaPzYvh3Ky/l5fy/69w/xHvHx0s8BFtiZmSIq6zJa5WEP3y5P9u8P6A3YsAGO6qLCK8qC1IIbOlQiWYLQbmQuhbTh0HcWFuK33x5Yuh9cOXparzCG9b//HXRTFcQxs7+nlKEwrdoSxru17+c1HNKa0O/UEDl6ej8bWYg7y4307i32T7BIUC/0Z8Xjed66VTxHffsSvqwRGDJm9HIjnnmtho3W774TyepAOPt5Y0JPYmKC6wxx+ukBw/GTk6W2+fDh8MDsUWjKQj937AizZsmz5oG+cdC52umtDlcqoFs3kVwPwb4eoxhQ9St7dposK+MxPwdk9Wq2pvZE00J0t5HNia5dqWuWzSh+MV8DNcgm1JIlHgahkXsx3KaDR5moe++ViN27/OqqBGDzZumfAFGJBQWSjlCXHKaf4+NFUPP440N+VOL4UYxJ+JVRR1ssH9RICWu0KqVqgb8CM4C1wIdKqdWapl2jado1AJqmtdI0bQdwC3Cfpmk7NE1LB1oCczVNWw4sAL5WSpnJ2vnjs327u96Lk0mToFWrElJSstA0t8pasPQksrLCPkTHHANVVRKGlZ6ezp49e0IvHHV8PHC6183d/Ic5eHA/xxzzWOj3MfCg5+bK5cjN7ciuXbuoMCr9F8Dw1/E0WkN6WkeNkokkSOhM8+Z6Eoan4JUG5Omf5HW8l1GllOTAvfde0K9QXl7u/J9omP3inHi92vvii8GFVXwYM0byaLp16wd4LyYD5sP27y8h4D6TIvh647YDlUDXwIajcxeyRw8RY/76aynNYjrcOxAeE06wMTstbR/x8fGkBqmr6OlR9+WYY8Ro3b7dYk6rUiE9cJs3Q3z8/tAiTCD5aQEUqQOHrU8ESqmsnGtso+Trr2WDxrkQ835PBawiLi6ECJPOP/8prvQA6KHkeXkdiIlpQatWx/L223I/du3alYMHD7IrlDzlhRf6Jtp6oZdKEDvlR2AYkOx9XxtZ/HjQqpU4JrdsgbKyHKAK8E6hcN3vSoX0wIEYuBIRvwbZCDjPz/DtNCiLlokHvLz9r78u2kfudZ94f6ZP/4H5SWPJoJT8j5cStmpQKGPGuYG0oKKn1MgMxYIFcM89Af90/PES9bm/uzNxy2zY4w03+NW9qK6WPhjUaodYNeEWkPv3y30YIjKnV2+NXxhFwoJfzOfYXHmljN0BSCkw4PWA8OGEQOZxQ6gmnurZJq9hCE9rVRUk5a+huFl3YuLCLOUMrCE8y8ronjJDe5EB5ufFzvLD/XOduZjhrmH//iJQF6ICgWe5ERAP5/r1oYVeAbknTj016Himj5Ur63rQsmXQambiwdS/mA8DB8IXX0DmBOnn8m9M9nNamniCfcq9rVghe8XN9hjwVoOhezHh2FGkcZBNHy8318ZQY6LTW72ytgedO4t9HbR9+vHB0DRiRo1ktPaLuYh/fX4OMCYuWQI9jXgxQWTmr7gi9DFDhrjKRDVtKuP+N98EvT3crFwp422A9L0NG8SwdnQ10M8QvpbtqFEkVh9kTJbJfm7kGPG0opT6Ril1lFKqk1JqivO1F5RSLzj/v1sp1U4pla6UynT+v8ypONzX+a+nfu7/FAkJAZ9gh6OESZOycDjghRfktaACwZmZUvQsRHjWmDGglHifTjnlFKqrqz0MpRBUVEgcmHMwuvdeTy2EbcBUYDLPPBNm9XPCCeBZkiIAubnynGVmitujIIT32IsQg+WWLdL8du3CeFqDoC/A9+7tDsQB7u+QkgJZWYGNVi+jqrJSjIUQ4i5lLhn6IcTFxbFggSTIe3la9+yRCdlAGN5OZ4D+ypX9gN1kZe02psQcAG8DUQ/t7BbYcHQufqZNE7HJLVvigJb8/LNFmX/fhgyR7AF/A+7fwFkMHLiPZs2aBff6OxWOAw3oY8YANKOw0KKntaJC+ibIxkh+PmiaAaM1SNv1sHVvxiOe/xmhbi83xcWyi5uU5PWeYuMXAfu48MIQIkw6H3wQMFHHO5Q8BodjBfv23U9xsWz+GlYQDoHuPL3rrlJgCTDG/742mJKgo2mysZWfD9nZ+o3tfUFd93tdnaRkhKg97e6Lj5DNrbN9Xgeysog/fJCCjTVeYcvffONpW3UC2lNT8wM3fz4GgGGHf+Tnn8N8oVBho073zEp6h/a0gizggoianXCCtHPGyjYSivbTT2HeLEAbfdqXny+RD/0TDYY77tkjVn6IOMHOneG32FE0KSkMGZHkR22tGCwB5kmlIHvPag7HGfBuZWWJsRdi3B48OpmFDObwjHAd60PfvrKZqcvve/Drr9C1bjWxfcIY/mDImHFtaP7yi0tIx1CIcICohFmzZMzpl2DQu9WqlTwc4fRMPMrKdOsma5Ww46I+bgdbG6xeDSkprCwNoRwMslAbNChoP2saPPVCCku1gez80KTRun69VJrw0YZYsULWhbFrDXirwdDmRLsLJPz24Lcm2/jII8HFNp2G/8/7Qogw6e2DsPeiNnoUeWoLRUtMrCtC9PPixTAyS/o57PN89tmiQhyKlBTZqXBuoJx7rry8aFGYNobYbFy/Hnprq4nva6CfBw2Cc84JfYxPmag/C4aMVhuL7NsneWHOUFBPPA0sfX0XVPTNwIMu92crkpIyOdaZu2EoRPiCC+RBd06K3hPALKAauIN9+8KULXz55ZAKiuCedxMTpZSKXs/x+eefZ9asWcFPDOFpXbNGImvi4sJ4WktKJGfnrbdcL3kvwFOA2YB8B32R/OyzrYAkPI1WP09mmLwjcBut8fHZdO3alZqaGpo0aUJ8fLz7IIMD+rRpnqk1siVeUbGGt98OocQ8bZq4GgO4cLwNRLkZk5O7BvTG7anOZO5XB7joIvfXdjja8MsvOy2Fr3rxyCPw7ruAf23QmJivgU/Iz/8+eGgwyEO0e7crp9OTbt0gKak5+/dbNFpD5AUfPCgfW1trwGj96Sd57gIsLvzXbWlALrAl7FwLBLwXJ00SB37nzmIoTJ5sffHjn2vckurqRBIT5W+tWhkwWkePDhFW4rY7hg5dBjj47rvh/ve1kXBCHzp2FKPpppv8jVavZzouTmprB/HAgee6ZwYi09Da53VE8X3PHj/XjfcYqyHe1jksKmxFbZfujGO2lJsJRYC0DhcrVlCSmcvBmIxQ+kDCZ5+5agb7MnCg7AHNmIHE1v/0k7m81gDjth7O2aXaoDFjwKMeHw87Oo+RXwwlBDspKpLPDxAhs2oVdKpeQ3k7g94tCF2aZxj8xBhS1y00V/M2L08mqQBjzo5VB2jLTpoMDmP4g4gt/v3voY9p1048nbNn07q1pMcb9rR6tE8puWfGjYP4jQa9W7W1IsIXbtNBdh5h9mxX0FTYEOFQzwq4wtR37IwJraVooJ87doSDg8bQcd9CyncacBrofPONFCr1UU9esQKGdTsgu9ThrqHexjBjYnqPdmxL6EST3008KyCDW7ABxWm0ztrVg7FjQ7xHmzbw4IPhn3tnP2evNNHGEAbhkiXO0ks9eoR/nnWF43Au/DFjZG1fXk779rJJE1baI8RasXBVCa2UgagEkAkr3NzXtq1bnOBPhG201ie7d8tk4RPaVFlZSVVVlZfRmp0dwubp1St43o2TzEzo2fMBevT4jlbOpAzDCsIeyrzeC+NVQDIg1rTZPE5f9Lpt11wjC9v33luHw+Hgjjvu4D//+U/wE4NIYColm0gjRoBSKrSnNSVFdlS3u6s3+S/ARwHN6dDBbfxddJFGmzZ5JCfnB/dkhpkUp02DRx4pB+JQKpH09D7Ow32ON7gQ9263WDhVVSWh+2fDBlkUOD1wnugGougrrEPTMnjppZZ+xu+0afDVpm7sqPXNi22Lw7Ez4vsjULv0nNT4eHmGtm3bFtpoDYGmQW5uMw4f3ovDYTKMEOSGO+mkgCFssv/ioLLSgNG6Ywe8/76rtI8vDz7o+0obYmJ2hg/pBbl3NM0v17GwEJo0EWspLy8vwIk+BFn8BPNqVFXJHt2rr7YjOTk5tNG6d2/IibSgQIylQ4dk061NoCr1ERit116bA0BW1rbAz3RtrWddGj+mTdNLFZYiWS8iRuC3mZWR4VI49sR/8+EhYD05ORqx48cyil/IXx/GOBw0SPIxA5VOWLGCDYl96No1hLifzmuvwRNPBPxTbKxEyn30EWw7arx86QUmSigEMFpXrJDL0bpktVybYKWrdAz2c/LAHuyObRNQOTQoIRaQM2dKflnyIIMbPJ7vF4BmzWBD+/HEOOrMeazz82XFHYDqZbJCThtqYJE7ejTh3e6IsMaPP6LV1tC7t0FP68MPexnEGzfKM3z88bi8mEHk0d3U1sqmqnPTMih9+8p9M3OmcaM1xGYjONvYoweFhSFEmDzPD+PJzDp3AvHUsu6Fn8I0zKeNPuN2ZaUsHUc2NWj4gzGPOrCr5wT67P+Rkj0mNqHefDP4vbt6NYdjUyjNyAlZ4pT0dPjHP0KqbQPQty+HmmQzuHSmcU2rli3lguluTyd79siUm1ex2tg1fO89eWDDpTxNmCD37U8/oWmyKW7IaNW0gON2zLro9zM//ihpGn8ibKO1PgkyKZY4X9cNLF1NMShjxog6UpjQmZNOymHlyqEkJ8txhjytr77qqgHrXozprAR6IIq6YcJwbr895KQ4bZqMVUIG0Jrp09cxdWoBFRUVrrI6Afnhh4A5cGvWyEJ59GjZCKipqQnuaU1MFMUEjwc92Pfxfb1fvzy6dt0SvKasAWVe8bSmU1ursWiRDNh+IkwGJ0Xv9umDX2no/ikpkQkxiLEwaZJEAGZkrGfw4K5cdJF/COu998LldS9xAe/7/KUNsNNY+GooRo4MWJbA4XBQVVWAponHKqzRev758N//BvxTkybNgFpiY8uDly8KRrt2EgYeQIVSak+Wo5QjvNEapp+vvVZSm1JSZH5LSWlLs2aFxkK+S0pkQvTZTd6xAxISJNQqoBEYqI0BJsVg3t5mzaS9U6fGUFvbiV9+CZ6DGC5fdOtWicrQx6+AJdCSkiSs8+67Q3wJbzp2lFPq6jJIS0vj4ou3Bn6m58+X8SJA9If+PIsW1xxE2Xg8zZoF2MzKz4f77vPzHvmHvrcnJaUpU6aANm4sqRwidol/dI4Xo0bBv/7l/zwfPgzr1zO/ok/4fFYIq5T52GNyO53577EoTQt4TYISoJ+XLZO5Ln7dKnetkFDo43aYMbFXb40ZdeNxzPrBeL3WEJuNv329nzbsInWIAaP1uOPgt9/CljyLP2Y4FaSYM6ynThWXZQASNohKTXw/A21cuVKSLsMxYYIsAubPZ8gQCXcMW85jzBgvLYbvv5efLqPVSC5mUpL8C2ehxMTI+DtrFs2bKZo1i9DTWlICO3dS3aUnJSVhjFaDGyg9rhxBBclUfmFyAyUjw+s66WkSPRxONSIj4cHXXGNIESjznAmkcZAl/zEhz3vXXUEnzMpFq1lV152rrokhmNyEi127AuZ0ehETQ+nAYxnPLNasNrjBHBcnE4dPPy9dCpmUkFq209g1NLohOmKEjE3O57lHj4BSFd4cOODXzyDBF62M1DPWMZKj/ifFNlrrE4/BUs+djImBQYO8jdb160Pks3oSRmTitNMkemv1aknmN2S0zpkDX3zhsxjTWYXUEhRChifW1ITcmXILl+h0p65uLY88IgOyp9Hqea1CGRZ63tfo0e6NgKBGq/zR60EP9n18N//z8vLYsmUL77zzDqeffrr/CUrJSsxHRAE8vaJitALU1ATxtLZpI/WLQtX49Gu3bviWhu6fAwc4mJAV9Lru2iUb+kqtc6nC+hLcKG0D7KV9+xB1I42weHEQ795uoJpBg64GDBitP/8cUBFh2jRYvlzv3H3ByxdZQIxWkdoMa7QamBTHj5d5yeGA665rQ1nZTmPCan37itHuQXm5PNeaVkjz5s1JDKHE6qJp04B5wYHEouLj5TP0yPOamg4sWbIt+HUNEe4PYuN5Gq1B+zs1NazCsSf6/ZudrXH4cAfmzQtyQ4dQ5vWOcpiFRKIMIzU1wGbWrl1ywTZs8Ho5ZF3ZceOoI4a8DTNCf5m9ewOHma5ZA3V1zC3vY8ixFk5Ar3VrKeuzbGsWO1oOMme0/v3vfnlXy5ZBvz4OMWZCJr8ZbyOI42YmE4jZt1c+xAhBwgmrquDAXKehYKSNLVpI/K93rSY/evRP5CeOofY7k8ZMkA2e9O2rOBSTGt6LCSL+dvHF4Y8bN04miJkzufde2Yc+99wwaXFffeUVTTZjhgSjdOqEGMtG+9lIqREQw3rXLli9ms6dwzvE6N1b7lsfUTAAXZ62uJW0MRpGa1JGIqubHUPbtSb6OcCYqO91dShbJWOdkX4+6SQJMw5D56tknCn7ODr3Ys3SlazWeoerkiYMHGgobC/h5Am0YRc7ZxpUY1qzRlKMfNa9S5ZAL0w8z0b1EhITZfHpYbQWFoYuNczjj/vNB+DMZ2UlNUkG+9mop/VPiG201ifOm+rzn7NcuZNKwa5d8jAsWZJFaamk1oQ0WjdskJXihx+G/Lhhw2T+/Okn8UwYCg92DkT+obJ7gd2A7IYHVKT1JDNTFlFB8gD8DZ5uwDqKiyVpZvfu3dTU1HjlmSoFu7cepvklJzHnls/93vPnn8XO69hR8lmB4OHB8kevgSiwWqvYjZ7k5eVRWlrKFVdcweeff06lj1gCo0bJqNO3b4jvXY7kJ4Keh+pntPbvL+oaYVwk3u2W94yLKw3ZPztWHWDz3sygtSm/+07aWFZW6BLT8aVDB7iIt/mdIcTg2c/iubv55hCKseE4fFj+BRRRkAXR0UefzBNPPMFll10W+r2CLH7uvVfUgwXZnTFVvuiDD6B9+4DW+4YN0LKlSaM1xKQ4bJhMgDt2iGe0qqrKtTETkssvdyu7OdEjdR2OQtqGXJV58NRT8uE+BDK40tN9o2nbo9R213X13ITqmhO8n0HuTd1o3bt3L5mZmd553548/jiESivwYNo0b+d7TU1OcMM6ROSEf87/aCAxuNI2BM1dDlhXtmlTdrQZyuD934VOqbrsMgmn9MUZz7mcvsaM1qyskOM2iENh1CiYqcaLF9qIwB/Addd51XErLRXb5pgOW2SHw6gx8+OPASMwPDnmGJibOF5+MerJDBIJNW8eHFXtTOY04g0uLxdZ6DDiY716iWEdt2m9V5pK2DYG2eBps3cl2zN6GVMaNdDPgHzW4MEwcybp6VJ+tn17KQvpO+0B8iyfcoqkOyCX4scfxflMcbEsbswYrUbGOP2e+v57V8h/2O907LEBa2PqSbtb0w0Yrd27S8SbAU/YwaMn0Kl6HbsXmuhnn/tQ3wdotnOl3DxG+nnfPnGPh4k2iG2WyZbmg2m3dmZ49WWQfq6qCjgmlm4qJr2iiLj+vcMFGwhGSsoATc+Tfo6b/b2BN0U2qu+5x89qXLgQxjV3Ps9G7kUzyvQTJoirf/t2lw5pSG9rYmLAiEmX0drVYD9PmCAhWWbV0v8E2EZrfeJU5r3/mSwfg1AehjffzHKFtoQMD05LkxkjzEMUGyvzx/ffJ9OkSRNjnlbnDp//oksvkNXLmCKt/qAH2Wby9wJ2A0pJTPwBkJzUXbt2+RnPmRzgeMe3zHxzp9fZSonReswxsng25GkdP94rlyLQArxDB3+tkY7OIo9VVeJJNGQ8OHF/b7enFdoSE9M0vHETBM92S+h2Gn37lobsn5mb8vhdDfZ6raICbrxRDITLLoOYGNkBDGa0TpkCreL3M4SFZODu59hYmen79nX3kVFvuYsQIgorVsjs3b17LrfeeitH++4q+BJkUpR7XDda9/q8boCiIjHkAux0bNgArVsbNFqbNpXdpRALi2HD5Of8+bgMzcIAtd38CDCJ6WNMRYUJozWEB9PX4PKv5dgB2MvWrRV+m1A7ttXx37i/MqtsSMD3Li6WoS4nRzytzUPlPH72WXA1Sx+8VdGljUptDbxhESKc0P08FyIV4Mb7vO6BhbxbgOKBJzBILWTXyhClmYJ5PZYvpyY+mc10Mm60Qhj3gESATisaL953I2JHVVXi+fDIN9HzI4ckm1hAguzoBohi8aRJE+h3QivWxvdGGTVahw0TZd7Wrb1enjkT+morUZmZYawYJ+XlMoCGyVXVjVbXhxghWIktpehYsZK9rQwY1WBIRMjFhAmSu1xSQvPmcom2bJE9opISvEXCfAz/l16S/YjJk3F5MaPpUQfEiu7aFWbOpGNHGVtC6oOtWiUb/oEOWrUKMjJYViz9HCTISGjWTLRFDKRXtL5E+jn/RYP9/OyzXiKRINc8IV6RsGGlsc0TEFG1wYMNjTnVoycwoG4Bv30b/thQY+K3j0s/D70iuh71mJz2FCR1Ne6xDrAJpZfMHd1U+tnQ82xm3J7gfp71VNSQea3PPCMy+z6sX6foxSoSBxjs54kTxatsItLoz4JttNYnV18NNTWs2OG7iJWHa/fuLN57T8LrQq7DTTxEp58uG6qpqdnGjdasrACLLhmI2rbtHVyRNlAbg0w6/l5N2Zaqrp5DivMPO3bs8DMgspzXavN+74k7P18E9fRUGkOe1qlT/aTMfRfgY8f6R5f179+fjIwMLrzwQudX9PmOL70kJwYwQtzf2220pqRo3HHHB9zjWx+xulomeAPeI73dhw9DTEwG+/eHXoxcfnAqV+NXT4V9+9y5Mw6HeAo2bQo8c0+aBGdcmglAFlJ/8p134IUXZBKfPl2MVl9DxVAYbghRlA0bCgDo3z835Hd0ETIf09vT6n7dAEEMa6XEaM3ONmi0tm4tBvAFFwQ9pG9f2ZSdP9+dg7pz586gx7vo35/8UZd4bRhMny4bWnv37jButM6fL/VUDXym//VrD0CbNtv9NqEqaMJ1tf/mivf884LBfS/qntaA+aw6JvJ6/DcmcpAQ8UPccsstPPPMM+4/hViguZ9n/WY+KXgUikWjVZ1wAjEoSqeHWKwF88CtWMHWtF50yI0NlTbs5rLLJL8s1GYfMrz9wkhqktNE6TQc+fnikfrqK9dL+rjapcpEjh7I5736atjDzjgDvq45DvXzL8a8wUcdJQOTT0m6RYtgSMoqtN69jS0KDfZz69awM7MnB1LaiAvTCEE2JyoLimim9lHR0YShYKCNgLhJHQ5XKPjYsRLlPWWKVKbp1csjjchjTKyqkgCNsWNh6FDc0sNGDa7HH4dHHzV27HHHwZw5dGlXSV1dGMf1xx9LyGygvnSGL69arZGREcYe1ZUfw0p7w1Fn9mJ3TGtivv8u7LGAqET7XKeCAhjYrght3z5zhj8Y6ufcq44jFgernzFgFAaJPqmpgTUfSD93Pt1gP5sYtzfmHUevfXNQFYHc/EHa6JHWsXmzDG89HM4wdSPPc7Nm8MADgcPJfendWx6K774jL0/m7JCe1ldeCZgkXrR8N83ZR2w/g/3scMg1NKPm/ifBNlrrG02jQ47vgyIPbJs2Wbz+upSFaukryOpJUpLUezUwEB17rMzBSrVwhQeH9HolJ0ObNgGMypVAFo8+6r0LHZRu3WQXMiEh4J9176C+wG3SRAwjpRyMdWqk79ixw28BnMkBABJaZHq9/vvv8nP4cPlpyNNqgH79RPR59273a7m5uZSUlDB58mSvz3Kxdq2sdAKEdejfW9MkPFj3Wj/yyHi6+9a1jY8X68eEolFiImRmZlBQUOqTj+yNMcNsHRDDf/7TOegRw0+WSWvzohLXZsZpp8lM/8knhTz3HNxyi2+ouYEw3Lg4OPHEgPUIt2zZArSiY8fQOWMujjoq4OpjyhRITnbntIKBsHdPSkokt8gn53jvXl1fwaDRaoCEBJkzzRqtFdv28stv8V4bBl99Bc2bV7Nnzx7jRmtRkago7gof8u0/dsjNdskl2/1u5ThqiKc66C2u53HpOa0hPa1GPTMEuv/lhdat83nhhRf46KOP3H8aMULCzALklk+aBP/9by2a9hwwlpycHsGjUJKTDY/bnrQ4YSB7aUb87BAL3kAeOKVgxQqW1hrMZwWJ4snODhuSNnQoxCYlsKbNBBEjCxeWFmATatky+ai0rStlkR5WscXJu++GDQ8GiTL6NmYiMTXVxnJvN250S9p7sHaNoku1QaEocPdzmHtR00Qw6ue0k0WtKIRCtYtnnoFbb/V7ef8cMRRUL5PGjJHn5eijpd88NhyefFIEq886S5zorj959PNbb8kel0sbbdUqMQCc1QzCMny4eAmNMHEiVFbSv0S8/iFDhA8ckPvc93lWStrYuzernN0d1qYZP14MjzDExGqs73QyPbbPoOaQgX5+5RVJDfJgyxY4pqnJqAQToa0pxx7NwYQs0n/+yrfSjj+dO0uDTjrJ6+XvvoN2pauoTjPRzybyMSvGTiSFSoo/MBDdUVLi189z5wIoWuxZZfwaJiWJc2PQoPDHappIrM+YQWxdNV27hvG0BtFz0FabjEr46iuJ2DIk7/3nwjZa65Pnn4c77wywqJMBZcKEDMrKCJ+8rmlBd6d8DdJPPpHx/MCBbNavL6Z5c7Elg3q9FiyA555zGVe6EndCwiq6du0VUEU2IEOHSr5H+/ZBD5k0ST5/3Dg46qi2pDoXLSeccAIgRqvvtdKN1guuy/R6r7VrxXukR7Ia8rQ++KAMviHo109+Ll/ufW3z8jTmz5f39jNag4VwOZk0CeLiymjTJj201zpEP4eiQ4cMlCoNVm4RgCWqH7fHPxPmnTYCOWzfHkKoJ8BObvPmzYiLS2D37p3ccENwYcCQtniXLuJR0eNiPdi1awualovhSjdPPRVwN3PSJHjxxUwgHvg7iYln8swzZcZUeSGo10PXVUhOFqM15D2oc9llshIMweDBonzYsqUYrYbCgw+UsLcu0+ulujo4cECMT8NGq4nFj3e4OsTFiUHYpcs2P2NxAjOpJpFTW/4e8L10ozUnx4Cn1cTiJ5hhPXLkl1RWVpLvueodP961k6GPAZomayFNg1tv/RSlttO3703hn+d9+wwZXJ60y4lllnYcrZd/FzyEPNC9WFAAe/fyY9kA40ZrYaEIJoWRYE1MFJvik+qJck4AY8+LAFEJy5ZJBIFmRpwHDI+JTZtC7OgRlMVkeBlcQXn4Yb96zuXloO3cQZOaUuNt1DTD92KvXvBe+UQJhwqpbuRk/Hj3zqwHlYtkkZs82KBhPWqUKByHjH91Ehcnxsk337hyYNu3lzDLadMkwvKzz5zHevTz88+LLMN4Z2qxS4TJaAjj2rWGw/055hhITSVvtYzzIY3WYFEJhYVw4ACqZy9WrzawR2GinwESzpxIOmWseWlu+INvvFE8wh4UFMCAeJPeajPRHXFxlI88ifE13/DV52ESW+PjZSD0KdUyfz70YSWx/U3081/+Ip5MA7S98BjKSaX83XAS1gQ0COfOhZ4ZhcSWHTB+DUG8FgY2bAEZQ8rKYO5cevQQjbmgBBi36+ogc3s99vOfDNtorU9mzYJvv/XLnUxLKyElJYNly2Lp1y9MaLDOlVd6ycpD8DDMVq2gujqbrVuLA3rfAnm95s2D226TFKSOHRVJSasYN87EQ65jIDF8+HBYsUKjaVOZQEeNGkVKSgqFhYV+1yq7RQxlrY7ihEneHpe1a0WASRdC1Q1JvzIyntTWyuwWIpdQ11J6/XX/a/vII0GM1jAlPOrqoKamjFat0oIe48KCKlzr1hmkpJTy2mtBDqiupum25Uw6tdwrf9ffCNwEdAntlW3VSm5YDwVaTdPIzJRaoqEwHIbrw/79BSQn5xnSJwjHxRfH8uKLnwMnUlX1KW3aGFg46uiuBrw3NE47Tf4cH7+fJk2aGFPn/fXXsDUv+/WTZ3XHjiSaNm0a3tNaXU2KqqAE/3uxqkoMXtNGq8F7UQ9Xv+02iIlpi6ZpbN++3c9Y1MP9L7slM+D7FBTIR6enK4qLi8OHBzschkqc6OOKnhrZrJlY2Bs2iLjd7t27qdDDA4qLobzca3wFt4bN3r1TgU6sXXty+FxtkwrHIJtxi1pNJK1ij6wKfVFKjGofg4vffpMfHG2s3A2IUf3Pf7rzD0Mwdiy8uP1E+eXrr0Mf7GO01tXJYm5AzyrZ5TFjtOpjooF+Pnp0PF87TkR9/XX44wOM2+vWiSAKUC+Gda9e8EXFsajExPCGdW2tHBNgt09buZLdtKRFzxDPhydNm8qGoE8odFAmTpQQEp8xStMkBWnGDOmSZ5cfw67357BK9WT5crj0Uuft7nDgcl8a5d13JQ7ZSMmixEQ47jhSf/qKhHgV3tMaaH52hi/va9ub/fsNNtXEpnKvm8ZzmEQOTAvTz9XVMtB7tPHgQbn8XWtWShhemHKHXu0Dw+N2y8snks1eFjwXpv7y0qWSQ+mTE71ogYPeMauI7WOin8ePN6ZkDfQZnMismONoNv+r8GvLF16Qdnowdy6c3dXC8zxmDNx0k7Fjx4+X+/GrrxgyROYLqdvug97PPoZ1fj50q11JRbqFfv4fLHtjG631icek6Jk7efrpJTRtmsXy5XDJJQbXNP/3f35b+v6Kv/K7bFa2APYAgR/0bdsQBZWTToIZM5g2TTaL7roLnnrqAGVlZXTq1Mn4d925U1anBnKPjjlGFjHbtnUDYmnduhvt2rVzlb3xvFZvFR1P+q71fh7SdevAM7r2wIEDpKamBlcaBekLpULmO2VliUH35Zf+1/bwYQn7DOhpDRGWvHGjAzhI+/b+BaUDNsDkQJSRIUbrihVBTnVOYH3HZHnl706d6lmlQQEbiYvrHDpc9qijxOAaOdLr5fLyNjgcwY2qsGG4r7wiVq1T1cft4arl4MFtJCbmhTjZh48/hiFDApcEAS699ERiYyVveG3Ywmoe/PWv8PTTfptF+sbQhg37jYcGG+hnT69/27Ztwxutzn4+QKbfn1JTTRqtZsIJPejSBaqrE8jObsW2bdv8NqE6NpU2njo58CbPqlUSPVFeXk51dXXo8OCHHpLvbHA3Y9Ikt8Dr3/7WmtjYWJZ7eAy36HKd55wDEycGHF+hFJgHXEJ1dWz4XO3nnhPPv0m29jqZGi3ew6XlgabJgspXPXj+fKoTmrCS3sY9rSYWP+PGQRGt2N9pUHij1Sc8uLBQwkqHpK+Twd+sQRhm3NY56ij4ioloRUWSshGujT7jtpfRajTnFqQG6tSpYQ/r1Uvyuvf2OVYmmVAL8f37ZWMiQH3VlPxVrKKXIV0ZQMQP3njDnWcajhNOkN2TABErZ5whYmlDhsCN9zThqndG8+4XqcTGelRb2bZNLC+z/exwGFennjgRrbCQE1svs+ZpdW7UrHSIwWXIaDWxqZzWqgkrmo8jZ0Xgfl66VAJu8pc55ykPo1UfitqVmDT8c3Ik4s1gmHXMSSdQp8XS7NcvPTXT/Jk3T1Imqtxl7ZSC3Qu20cRhsp9LSkTp10A+ZkICrM6dSObBwvClrBITvXbii4tlvB/dzLkhZ+Y6mkg9oUkTGRy//JJzzlZommTW+FFaKnOVzwbKypVSkqemq8n2ge1ptYkyQQbLwsJCkpIk5O/YwHok/jgc+I4qwcItxfbLBqqRUiv+dOiAbOV9+y0UFzNjhjx3U6ZAp06ywG1nSL/cSXq6IYXjadOkKgdAZuZNwPP8/HOil9Eajrfekl37L75w5+iWlJSEz2c1uBDXPVz+iBd3v69caufOIcvULFgg/daxowGjdcwYjK84na3KyKC2VnZAb7rp77zqu3EQRERh0iS4+Wb9t/1AKeed19l4uKwHVVVtEEVVf5o1M6A+XVQE27fz3pepXiHt8p51HDiQZ7yeammp6Nz7y9oCEunUuXNTEhNbmDNanQuPwMYMLF5swmg1sPjp0UPaKnN1G779tjC0GnNsLOsnXM/aRP/7Z/hwC57WMIqtgejSRX42bdqebc4BynMT6v9uOSAHeDyrniG4v/wizsm9e0U5N6Sn1YJyYmamREguXBjnuhb6OOcKEXZuNgYeX/UcIsl3Cpur/fXXrnIgZmjTPYOfYsahPv3Uf8FbWSmhJr434W+/sbnpYJq1iPMVxA2OicXPkCFy+Jz0U8QD7Jn478vYseL5cI45eth318pl8h8PFfewmDCsu3aF7zgBFRMT0ODyIoAHbu1ap3Jwu3Yho2f8OOooQzl9uh28vP1EUYkJVSYnWOmlujqa7l7N+oTepBkI3gHEQLj0Ur22WXgyMyWkOMA1HD1amrRxIxw7pJyvvoJ//1sxYYLHkKHn2pn1qIPxhfhJJ4GmcVbCl2zeHOK4114TCWRfVqyAtm1ZtlWur6E9CpObyhVjJ5Jbs4kNX/r38zPPSERXn7FNeZ/zvMbEggKIoY6MwtXmrmF6ukyeRsOaMjMp7TOKkxxfhha/DhDun58POWUW+vnTTyVqyYiwIHB43Ek40Kj7LMzz/OijXtaiM/CEnnXSz6aeZ6M1g3UmToRNm2h3aD2jRkkz/PYpsrPlObz6aq+XVy2voyerSRlSj8/KnwjbaK1PgoSlbNu2jdraDjRvbmLz5+KL/YyZYONShw6QlqYv9vwVhF1eL+fgu6myLfn5cPzx8nfdeDRltDZpIjuzIQZ03UOlLwYPHBgIXM2//01wo/WZZ7yS/6dN837m9ZDolSsPhM8lNLj4CW4zxqJpGf6e1ldegaefDvp+S5fKTmqnTgZWGI88Ao89Fv44DzIyMqisFKP1009f5knfXMkAaqj79u2jsLCQ+Hi9lrwoIp53XuicX0AM9Mcf93opLa0tEHgSCljfz5eSEmoTU7jiugSfkHbZclYql4suMlg+x0CIVLduEBvbgzU+qgkhRcu6dIHrrw+6WVRZGV1Pa0KCRBN88w2sWdOG6uqdodWYmzWj6/fPcdmrI1yeTf1SdOlSSFJSkvH2pabKRsKVVxo7Hv1z5Gdycge2B5L0LCmRAcgp2OYbgquXsnr7bRm3Qnpaly8XBeaQK1Z/hg0TIbccZxLuBU4VZ5en1bnZGHh81cPP3INEyFxtC5ETIBH40+vOQNu0yT9JauVK2dH48Uf3a5WVsGwZvzqGMWCACXs+NVXGbQOLn7g4EW2duu1M6ahPPw1+cI8eMlA7I19cnqOdC0QsJWSNNx/OOUfuRQML8aOOgv00Y1vOKL8cQT+CeFqPjl+IZkQ51JNZs7wLAQehWTNREf4SZ2h3qBzOYIrqa9eSWFvBtuYm2miin12cdpp4I31iHePjZcqbPh2+Gf5PumgbOXhQ896UXLRIPq+eNicACZsdNowxBz4N7Wnt1ClwLu+iRTBwIKtWmYjAffBBKU9jkJ53nwrA7Bs+pbbW/brDIfsHxx0HvTse4mpeZH+ce5NwyxbowRpiqyqNqdh68uuvYXPUPUmbdBq9WcWSDwLFtDo5cMBr3AbZFx7EIpTZfjYZxdNzXEvmM4yq9z/l11/xuo5e/Oc/InDmRA+iyS5YZP4amvG0Apwq/cynn3LhhXL59c/fvl2c37t3IwsLH0GwA7+uIYVK4oeZfJ4feCBgvvufHdtorU+aNPGrAedwONi+fTv79nVg7FjDkW0BHyJ/cRG3QXrFFfoI7K2K4+X1ck5g36+TxUBERqu+Qg4xKQbzUM2bB23atKWwcCc5OXUug+Httx3c/9ZbbF282Os9fJXuKipg1SoDntZOneSLh8nr0cMyfVMTU1KgefMsU3VaAVasEKO1eXMDnlYLZGRkUFVVRbNmFZSX72Ht2rXeGwDJyRLu5SGSdcMNN3DiiSfy009ipBcVidHaOYxQFSCjsL4KdXLyyW0Qr76/Z7+i4hkuv3wcKlQo3IED7K3NDHB/6Ll2sugwVD7HwKTYrRscPtydtWvX8s47yuXpu/jiEKJle/ZAfHzQtXN8vAmjtVMnjFRi79dP1o11dW2B3YAkVgb08NXUQHW1l2fznHPkmd+/X2q0avVc161NG7ndDh3qwLZt2/z7fOxYuPNO16+BxoTqanj+eQOe1v37xYtpQm0bRDOuuBiaNpWOPOWUU0hNTXV7Wp3h/oHGV1iGpF64vWohbSkLOeogUS9fcCpK0/yNw0DGzOLFUFvLV3tN5LOCoXHbkxNPhDn7enI4t2too3DtWq88Wd3Tmr5+gXhZYmONtzE1VVx4BibL9HSZcn9ucY60IZSU50svwfXXe71UuKqEvOoN4lY2wyefwD/+YejQfv3gp03tZGfCU7Xal2C1q515psV5JtqoiwiZmbuc+ftMn+73pzPPlD8nlO3lpWb3cOyxkuvq1cZevYzn0IK1lIRzzqH93mU0O7Ap+Gn/+Y9YWJ6UloplMWQIq1aZiAQfMiSgWGAwsvu3o7jL0QzZ9pFXNZ+lS2U6uegieOnNJMq1dJ5Y5A73z8+HkQkL3J9phtNOM2VYx58v/dzkW/9+dhFgg2fRIhgWswB6muxnk3m3Q4fCR5xDyoZlXDJiE6ef7hd06H4/jzauWgV9ckuJ2bDO/DU0O263cz/PZ58tdumdd8IHH4i9fMkl0Lat4t5+X7t3aJ0kr7TQz5omCse20WoTVdasEc+ZB8XFxVRVVVFe3oFx40y8l/4QeSwCffPF9HIqkybBFVfkOo8SYyQnB556Kp/WrXvTrZvTCHQ+lDOWtiAvz502qquUtjYcY+YkjFch2NpSRDraUVdXy7ZtezwMhpU8tHQpz+oKKCHeo6rKgKe1Tx8pLBpml183Wi+80P/atmvnY7TW1YkFFEIGf906MeTS0w0YrU8+KWFmBgStdHTxqY4dN6LnMM/0LF7fp4+EgXvshm7cuJGVK1fy669ljB0LmzZtQtM08vIM5I4GGNBPOUU3wHy3vMuAB6mq+pEVoeTZS0rYWxeo/xYArQF3WGvYkEwDO/bduoHD0Z3S0lIuvni3l6fPE9dn1dZKrlVWVkBjJi5OkZKyz7jR+n//5+0pC0K/froAUBvAgecmlN+z8PHHfoXifvrpU9LSHmH79u3GQ4N1rr9e2mmCmBgx/DdsaE9lZSUbN/qEaJ98stfiPtjzrNeYDulpNbn40dFTQXft6kpKSgoDBw4kLy9PjFaPfvZVRRZ7fyniZRXjP2yudoBx2wgtWkCLPq1ZlT7CP9YsUB1ZZyzcPMcw33Tz8BQUSO6tAUToXWNxzlnw00+SYhKI++6D88/3+oi81oeJWbHc/AKyuFgUjsMpFjvp2hU+qDkTNI3dz00PfulPOMEr96+mBrI2O/NgrSxyS0oM9XO/frI0qD3jHIn9D1b3M5indcECSrUMtC4GNhg9MRvy2L69GGhhDOsxLdcya5ZHBSOlxEg0Wr5GZ8AA8RKa8Yo5DeuzmR7Y21pbK+OYb21hZ75zTb/B5vSiNm6EDz809Tw3v/psBrCU1/++mQcekM1EvUzv8cdD7wHxnHuuxrP/TeC220QMcupUODZ1gdQcNbKR7IlZg6t9e3blDGPMvum+e9FuAkQNLlygGBqzEG2IyX426VHPy4Pf20o/Pz18Ot9+6y4l7EIft32M1lNbO59ns/fiBRcYrxmsc/bZsHQpzQ5s5qGHJGLo/POlC2fMgDMHb+eR5Seycpl7PVtZCTlFC6hMtNDPe/aIWMD/GLbR2sBsc63SxNNqmMxMWb0eOuT1sqdXxbP8QteusiBLTFzMaafBli2Kb765mlWrVrFUV1iLj6e6cw9mL2jC8ce7Q8p27NhBy5YtSQhSczUof/mLh969P6E8Ej/8oBs9bg/h4cPLAJi+/5DL++pvE7wOjETTNhuv0RpmwunQQS53YqL/tW3atKm30XrggOQl+fSLTlUV7NwpntY0IwlIDoeEwoVURfBGN1qzs915M997hMkEQt+YqK1dytVXi9Havn17kpKSwn9ggM2Jkc6VclaWXh+xGjGyXgRn2aLPP/88+HsefTRz0k8N8IcFwBB0I0EnpHMtOzusUqaU5dGVvELntW7bhls1MTPTz5iBGrp1u4bS0iJ6mhFvMYCuZi1GK8C36N5Wv+fJx5iprYVNm/5NQcE9zJ0717zRumCBX+1AI7zwAhx3nDSua9dt3mHWRUVeQiv+Y8IbwDVkZorRGrbkDZgOv+3eXXSMFiy4halTl5GSkkLHjh3FaHU4RDjJGXaij69KweHD1cTGriYmph/gvUkYlKwsqfsXOEk+JMceC/89dIm7DrROoFzHX35hf1ZH9sW0ML/53qSJ4XjiVq0kMuOVkrNkPgr2TPso8xYUwPjs5WIZmjUIDx0SheMlSwwd3rUr/LqlNSW9RlL8349cBoIXhw9LvvHOnS4x5scegwEOp0fOSI1GT7KyAs7PgejXT57NdT2DezIBcbd//73nQANA3fwFLFSD6ZBrcvlmJVTduRAPGoIfSDk/P1+iIMz2c0aGeKuMbO7qdOhARe+hnM10V+kxL/RxO4DhDzD38CAqKmDCBIOf99lnojZloJ91tLOlnx8dOJ0HH5R9u+nT5RZr0QKYP58H2rxEVZXi2WclMuaRR+CU1k7D36xsvoV+jj3vbAayhF/fCRJn/e67YoU5qauDksX5ZNRa6GeT47amwedLO1A3aAinVE3nuedkj26uZyUhn36ucoqUj0x0ejHNPs+jR7vFV4ziEZlw990SkPbaa5KKctxx8OLZs0injHuec9eQX7MGBrGQsq4W+nniRLjiCnPn/Amwjdb6YscOycX0qcWmG63Z2R1MpfWY3Z2KjY2lX79+ZGcv5osv4N//fotZzoLr5fqi8cwz+fG51Rw8FONVM3rHjh3mQoN17rkn5IMeLJw5JwcqKvTP88yDWwbANnUYpTaydWsdpaV1Puurj4GFwCG66Al1wSgvlw8MkX8KMkj26+enng5IDU4/o1X+EPC9xIMnRqshT6sF75FutBYV6XksR/Hhh7N4+23nVuTTT4t14FT+q62tpaioCIB+/RbRubMYrWGvn06AMLMOHTrQq1cvWrf+huTkCqAT0BV4jJiY8XTpcjRfBFDBdHHbbWT+52Gf++MAsB4xWr0JGZLZtq3Manq8ewCefx6gh/O3UNXAnZ/l4/XQjRmJkLyPVate4p577uGGG24I+V4uvvtO4p7C1ILTjda4uP5AS+ByYCTJycrfw+cTTrhuHTgcBaSkyO/tQ9RQDojFfMx334U5c/SF9u+uMOs336zhip49WetRqsV/TPgIeJGePVeQkJDgquUctH1gKfz2kUegZ88m3H9/F+rqcBmtKj5e1MkChACuWbOGuroaNK0/t91G6BqtOrfdJuOOmfA5J8ceC9Nqz6UuIQnefNP9B18P3KFDMHMmP6WcTL9+svY3xUsvhXEXe3P++fDGiv6UZXeU+LdA+ITqFRTACKvhjibnvq5d5dB3q86mN6vI/yZAfl9hoSz6Zs1ixgxxDP/97zCEBVTmdA2pBh8QE8IoeiTPwqIOztjHIJ7MFi3EmvJ8QCor0Vau4HeGGCuV58l77xlS9/ciRIgwEFg5f4HFfq6tFYVjg5sTOgkXns0gFrNzbgCDK1BUgt7GLl345KemJCebEMS0IoCTkwNDhnA2H/Gf/8CcORI0cKKzehQ//ki3p69m8+oqSkpg9my468ZKEtetMH8N9TaaHBOzr5F+rngzyL2YmOjlMVi+HHpWWOznVq0kydNX/TxU+7Ih9rxzYPFiJo/Kp0kTeQsXpaXuEHjEj1BbCz0PSj8H8HaEprRUUi4MCXI4cfaz/jw3by7aZ/pHN60p4k4e46tZSS77f/WiSvqwgrjhDdPPfwZso7W+2L1bYkB8JtqCAjFax4/vYE78ctAgCatz1ygJy8CBA9m3bylK1XL//fcxxDm4lHmUAvn0U1lPee40FhYWmvfKQECFY0+ChTNLDrtuhXgbrU3RJ+zPgAnU1p6MUu7yh/Hx2xgw4ATKy8u5N2TMKPJFq6oMLX769RNxQY/IZECMVi/14CAhXLqgT9euoOd5zp6dHlzkR8fCpKgbrUuX6ouzS3A49nLVVcvkM3bvFg+X03NeVFSEwxlb07q1hIpv2rTJWD4riKpkgInqpJNOYuPGXzjttOcRj3kToITU1L+zceNpLF68mGefDaIQrZTf/dGihe5d8v6ssCGZAfAVWJK9o9ZAOqE9rU7jMCVFwsx8PKkSTrWAwYOPZsqUKcQY3S09eFAWTsHCK500ayb1iHv37kCHDtuA+4D5PPDAWn+D6cABWVw4x4iFC2uB7UyadC0fffSRcYNax2w4oZN774Wqqn7ACOAuYAcVFXD33Wt5dd8+vvTwtOp9rg83sbEFACxZ8jHZ2dmhc3DT0kRBxeQO9bRpEh6+erUIWD7yiBitlZWVFOXni7XvmzgPfPrpMgA6dOjH7bcb/LAIcohHj4aKuAxWdTpdDA693MRJJ4k7W4+KmDEDDh/mxT1nmFkHupk1y2cFGJpbboFx4zSe2z8J9cMPgVVAPTxwtbXideh7eIEknJqdW9LS5DqaMFoBpmw4mzpiaDEzwEDrMW4/9ZTkYv84WzEh/XeSRltYQJowrDt1kqlo2TLg3HPFSAukIrxggX/Jo6VLiXHUsSjGgtHaqZN8UTPk5ophPW1a4AilDz6QlBZPFiyQMchs1ElMjNSACVTmKQRxF5wDQKsf3/X/Y7AQ64ULUUOG8OWXsvYxvKyyWh/zvPPQFi/m2nHrWbYMrr1WNvJc75WYSIejktx7W0uXyuLDitFqYbNRy8tlR7uhDNn8bmCP9QMPeImGzZkjGzyOJAv9nJQkybxmSiqCCDQAKZ+9y1lniW3oGqY7dpSBxjkp6un0LbcttHYNZ86UNXew0P1gnHuuGLuBnueSEm5MfJF27eBvf5PmHvhxKXHUkXlcw/TznwHbaK0vgnjgFi7cBqRy6qmZ5t6vXz9RrguV4+XDgAEDqKw8RKtWb3HgwA7+9re/kZKS4vK01j00hc/eKOGkk9zrH4jA03rddWHj8gOFM0tkaTMgGdDjPhWwjP1cgnjE7gN+BH4CqvjiC3mP5OStDB/egSZNmoQXmYmJETeEwd3wykr/ItG6p9UlMBNALMNXEVX3tN5xR1pwkR/3B8hPE4ORbrQ6HG6jFeI4fPg9ycfUF5DO66OHBsfEpLBp02IOHDjA3r17jRutf/+7l9CDbhD+618nUlNTw/Tp9zFw4EB69lwKlFFWNhqQ0N/bbvsysLHesiXcfbfX/XHjjbKT26bNoIB52yEZPVqECsCvrurWrfql0JAQYd1orQF+Aw4jmycDgdvks9q0kbw/n3yr/HyIidlOp07eIXxhMdHPJ5wgoU4bNiSQn38ZAE2aBMiH9RHL+OWXnUAtAwfmcfbZZ5t/ps0KtziRDYFYJNS3BhAF4l275GHa6bMTNGmSLryqiI8vAKCysjJ0PivI87x7t/Ei8AR6NqXc69atHQHY8vXXEj/sK9wCvP32MjStCXPmdDZeDWj9ekmON1of04O0NEnzmxY3WcItdUGmvn29JdQ//ZSajGb8UDOK0aNNf4zpxU9cnOhffd30YjSHQ1zrvnh44HbskPV3bvECMYDMGvIxMaa8CrrRuos2/NZkPMM3v+2TAIfr+67Y14aZM+GGG2BMl0KalO1GM5v/BrKRsHu3qCaHQRdbXbYMuTdiY7096TqvvALXXOP9mtOLebj3EOPlbnR+/tlQLVk/LrlE7t9AOcVduvhrRCxYIOOkj0pqWPR+Njvm5OSwKnsMwze95W9YBxKzKiyEwkJ2th3M1q1u4VdDWC01cuGF8v3efJOjjhJtKNdwHKjKhO6ttnIv3nknvPyy6dPSrr+Evqzgi4eW+f/xmWfwrIkzZw6MTlpAzMAB5vsZJGbWQ6jNEDk5UhLwrbe4+CJFaalPRaaYGJfA26pV0CG2kPg9hdauocXUE89+9kMpUtpm8fTT8ihdeils/0T6OXaoxTbanlabqBEkLGX58m1Ae447zuTEXVcnk6KJXMeBzgV2RcUDQAJDh04kPj6dF18sIyYGnnz4MEVVWZx5pvuciooKSkpKrBmtJsQoPBGjVSM9vQMpKdvQNGjbdisSHtoPmIjkSPYBqmjVajljx0JpaSllZWWu0hWGMLhA00O4fOtZZ2VlUV1dTaUeNpKWJlaFxw62vyKqGK01Nd6rjICCQh06yCreRHhahisecD2QBbQHTgNeZ+vWw36Tom60tmlzPBs2bGCRM1/OsNHqgbcRMAJIo7a2mqFDb2XHDg3xtoKo/7anpmau/3d2OMTj6JNDvWDBAuLjj2LYsMyAedshKSx05WEFUqh136IDkI2QE4DOwHAgDzgaWEJsrHN3ubo6YDH0uXMdOBzbef/99sbK8eiYWPyceKJEgP7yC+Tl5ZGbm8vs2bP9DzzhBJaOvcXlUX7nHVHV6Ngx12CjfOjUyS+fzgju0O3OiKf1O6CIzAzZwt8V4DqKx3ovhw9XuMLoQ+azWiTQvVBTA+++K0Zrvr6zHiDcf9eufDIyOtG+vQnl24MHxUsaVOEkNIMGwUtbJqC6dYOHH5aHYPVqt9hWdTV8+SVrOp1CHXHmRZjA7VE3MW5nZ8OE67own6FUv/qW/wFvvy1eM+SZbUERmUUbxGi1ggmvf26uDCU9e8L+iZNpV7eVg9/87H3QgQM40PjHW11ISXHuAeiFHa0sclNSZOPNoCpyv34yt6iWrSSN4e23/cN6Ahgzdb/OZwdt6XGsSZFEkBzeO+4wPT9z/vlS58Z3Ie5wyOal5yRZXS1eQivXECwvxDcePZm8mo1U/fSb9x9Gj5adRc+cxt9/B2DmAWnjySeb+CCrntZWIfo5gDIvv/8uawqznnGQna5Ro0yflnHledTGxNNk+pveY6TDAWVlrjY6HDD/52p61UTQzxdcYLq0HyAbKBs3MjbpN9q29dC//O03WYg4055WrYIz2kg/W2qj1dST1q2D9/Pjj8PmzZx1luS4vvMOHJv6O3WtLPazbbTaRBWPsBTP0MT167eRktLBdIg9W7fKAxEstyQA3bt3Jzk5mbKy7cDxPPxwBmVlaRw8WIZSsKCqL/FUe+qiuAway0ZrdbW5PADkee3YEZKSOtCr1zYcDnjuuWUAfMDDnEJ74CFARD8mTJgPuPODOxgtpK230cCE0727zNO+RquuDuvKax06VMLAPUJd/EWCyoEkwF/Yyu/YLl1kNDNR98xttFYgIa8A1wD70LSP2bXWe1LcsUPC+fr1ky3mCy+8kKSkJAYZFSt48UVZtVZUcOONnkZAPHAKkMtXX53t0kYQNCAH2OX/nUtLZSHl0UalFAsWLKC2dkjAEnth8ejn0BVRHgbuIyZmHZqWA7yMePY1YmMnU1dXIPm/b7whK+HCQtfzrGmwYkUxsqHSwVg5Hs/2gaF7cexY+WhdUGbs2LH89NNPrhBvnWmVZzLyiztcHuWamgIAVqzINdCgANxxh3vH3yDTpvnuq40AIDFxJf16ys76zgDjw9atkJhYAMBlTmPHkNF6++1w992G2xfsXti5MxeAfN0F67OILC6Gw4f3mjekre7YOxk4EEoPxrL78vvE2/XZZ+JZdl4jZs6E0lK+jD2D7t1NBeJ4t9HCuH3JJfAWl5CwbqX/QDlxomvnr6AATsKp3upK5DPJypXwVgDjOACxsRLN+K9/QdL5p1NGGgef9za41P4SruM/fP5jOvff71yjfvedROKYrekIsqj/xz9cBlE4+vWTUwoKgMmTxR3tqybua8zU1eGYMZPZjLPuUbfQzzRtCqecIg+354ZTaSnceKN3u3/+Wd7fVGkEnzZaeVbOOotDpFD+nI9hnZgo8rOe8b/ffQdpaXyUP4i+fcWeNEy3blKjz0oHhOpnz82JujoR4DKcaOvDli2icFxdbe68Zs3YP+IUzqqaxndf+vSzUq42rl4NvUp+JrGu0nobLUbxcPbZkJJC7Dtvct11cpmWL0fGh5dfdhVxXbUKTomXfjYtwqS3D6y1MVg/O9E0Mbbvv6+O4/ie2AkWr+EZZ8imkW8UyZ8c22itL5KSoFMn3v++qVdoolLbqKzsYNwjo9Osmfzcty/kYZ4GcufOcbRtK0ou2dln8/77oFQ6eo7lL4yiH8u4+273OaNGSc6hpZxWg20M1N78fNizJ4f162XRuGzZMmK0GCayjaakAn8HcklNbU9trRitW50LTFNG64UXGtpa1XfqA3lawcNoDYB/c8qAwLFcQZtuYiDyFnjSjdZxQGeUeoGX1h/D8rZupa316wuBOEaPPkFaV1bGl19+aXyjIiYG9u7l01f2Bejql4BFbN8eH6AMaStgl/931t/EYyenvLycXbt2oVQfa0Zrs2au9w19e2QCD3H77QW8/fbP5ORcgab9QIcO27jnHlHm+/33313v9f6MLJ/wUj0HW0SOwpbj0WneXDY8wohzTZsm92F1Nfz73/L7uHHj2L9/P48+usIrT/eRG3aivLbICwCN227rYM4LbBHd6+59T/QG4KyzVlCrxNu4M8BiautWaNasAICLLrqINm3aGPP8L19uqHSQTrB7oXXrJNq0aUO+Xt/YZ1dRxoFi2rUzabRaGBM90e2nOa3Okw2tBx+UqISmTeWmuOMOyMnhwwPHGYlMDd7GJk3w2WUKS8eOsHXY+VRqyajn/+P+Q2mpePWcZYsKCmAiX6HatTO1GedFSoqpsOK775aI3T7DUviIc2g6+yPX96urg2vnXcSLXMNdt9dJfrLDIWVRjj9edivN4nBIeah58wwd3r+//Fy2DIlPzcz0F0nat8/7Ppw/n/iy/XzFRGse9UjuxcmTpT+//tq7feDdxq++krWPVaO1aVNL7es6KI1POJP07z7wVvadPVt2L/T5VCn5Dscdx5JVCa5+MEyTJlIb06xQF0j91IwMkZT15Ouv5brpzJ8v6QCmXMAezJwpCsdOr6MZsm6cTAuKOfRh8H6eM0eeZ0diBP3sMT+bIi1NigR/8AHXXnKI1FTpXtd7ZWWxb59UyxhSLP3sG8FluH1grY2nnhq4n2+4wSUC2r49PHDCfGJKIujnYcNkwjWrOvxHRynV6P4NHDhQ/VnIyRFTVf5VKEDB/6mcHJNv5HAoFR+v1J13Bj3knXeUSknx/Dyl4EYFiap///3O38cqGOn6+/X82+f4txSgHn98vfkv++mn8iaLFxs63L+9DylAvfZapRo48DSVouUoBepEvnYd07v3OSovL08ppdTzzz+vAFVYWGi+rQb4y1+UatnS+7WZM2cqQP3888/ywj33KNW9e5jvdaGCTiohwbtvUlLkWC8cDqWaNlXqrrtMtTU1NdV5b13k8RlTnK/t9rrfjj/+EgXt1YwZSt1///3qhx9+MPVZej+f1Gqxz73j/peTI9/N+/UbFGT4f+dff5UDvvnG9dLatWudbZ+mfv/dXPOUUkpdeKFSHTsqpYI9F97/kpP93+LQoUMqNjZW3XPPPUrdfLNSTZr4PM9KwSfOdrqvhaZZaG8Agrd7hwJUbOyTXq9vo516jb94vPYXBW1D32+h+O03pYYMUWrVKkOH+18b/V9rNXnyZNWyZUsFqKSkJOVwOLzOHTRIqS5d/qUAVVJSovbv36+qqqrCf6hHPxsh2DW95BKlRo4cqUa3batUkyZ+5/3rX0pBprriir8a/iyllHvcNvk861RXK5WYqNSttyqlPvrIfbNOnqzUI48oBar2869UXJxSd99t6SOkjRZ55RWlXuRKVZeYpNTevfKiz/N8+UWHVbmWqtTVV1v+HPXee0rdfrulUyc0XSTteeopVVOj1Nlny6933eXx1Rc5j3nzTWvtM9nPFRVKxcQo9Y9/OF+46Sal4uKU2rHDfVC7djIJ6dx9t6rVYtWwbiXW2mhyfvaipkap9u2VGjPG/VqAcVt17qzUSSdZa59SSuXnK2VhPq+uVmpU7Dxpz/PPu//gHLddLFmiFKjSqa8pUOrJJy208d13ldLnf7MEwyn1OAAAVe1JREFU6mdf7r5bqdhYpUpKrH1GhP28M769Wpbl0c8LFsjN6uzns85SKj+us1InnmitfUopdcEFSnXqZO3cee5+vvVWuVT5l/2fq59ffVWpfkg/q9des/YZDoeMBevWWTv/xhsDP8+XXur+PdJ+PnhQxq0DB6yd30gAFikT9uH/mIne8HiHo+nKqR3ChCwGQNMkJNO5ex2IQPlacD8wn5Ur9fCTNHRPayYlxFLrc7yEBz/7rAVPa+/eEiJlMEbNv73iBrnvvh0sW7aILJUDwB7cqifbtw9jy5YtFBUV8e2324B42rZtZdyTpJRhj0K/frJZuXu3+zXd0+pSEN62zS/cSldE1T2N8fHl5OSk89pr/srJfvmZmiY71VJI1DDuEGHPWCc9f2w5W7e6vemzZ+8E2pKbCw888ADjzO6WOkMk63YHvxenTJHv1qOHbHSKGn0roJQzz/QJT2vaVES8PEru7HQpkrZxCauY4uijYYSEpvrXVfWnslIUTj1JSUmhT58+4mktLoYWLQI8t/oL7nIyZhz/oQj8PAO0BbpSV+eZ16rIptjrWRFPa67rN8NeYJ26OgkP1r2PYQg+pvVh7ty5FBUV0bJ5cw4fPswBn1ycbdsgPr6AzMxMMjMzycrKMlYnOsyY6IuvQnXTpvJMvPUWLF3akbXltaKS4sOSJTXAAdq3N+lp1TRRBrK4Gx4fL7pLixcjoXFTpsjN+uGH4k4880y29DiZ2lp/PRxTbbTIWWfB8zF/I6bqsDvBTO+P7Gxqa6Fixi+kqoMSMmyV+fNFMdkC2qCBLG0yEp59lvvvq2P6dHji6o08MmaG+6t/9ZVcB6vhywbmZ0+SkyXS1FVW7W9/E2+g1OISvv9eRO+cqK++5teYkfQfm2mtjXpou8m5BRCxnRtuEDEePfzIo58BUYvbtMm65wgklNdCfl98POzvejQbMgaL2JTuWd2zx90+cHmKl7eRyCNLjv/bbgsstGOEG26QcVUfY5SScP8ffvBu48iR1ry54P6+JsZFF3Fx/NznBvqW/IRaukxeGzxYojqOO47qasj/bgN5tZsie55btLDWPpC5fbD0801/c6Bp8O9fB7q+98cfw0WZTk+xZy1HM2ia5D9YWnwQuJ8D3YuR9POyZRL6PH++tfP/oNhGa31x3XXw17/6LGD1VV0HawvbMA964EVjFtBPD/UnJiYdXRjoAFk8y00+x+8AMtmxw3xdQTp1kvA1g1/Ov71y3s6dv1FXV0g7ZPIqxv2gHzgg9RMfe+x3p9HaHogxnk/4yCMySAQoaeFLIDEmv/Bg34HIyaRJboX4rl3LyMlJC6icHBALA7putGZmegp0yIz8L07gep73yHUsBNryxBOEL8ETrH1A92aBFz/Nmrm/27HHitFaVwdPPSVt2+25CwAyMTz/vJfytJ5bnZ3dxnzdSYC//tUrB06/9qEMV8/1os7QoUNZuHAhjqIiyM4OcGtvR/KVZaPGVDme888XCcEghN7YGgv8DM5NpzTKSaLK61nxNVrDv6cPukSuwUVu8Me+D5udoljHOEv87PQok1JZKR9RV7eV3NzcQG8Quo3l5YaeZx39Xnj7bTlNX98eOtSR4rI9vOE4z++cxYslTMySONTKleZrNHkwcKAYrQ4HUnYJJOn+kUfglVdcCudGyyz7sXevXBTPhbNBMjMhY0QvFqSOE3Xtw4fd90uLFnz9NQwt/lJqzVoNJQQZY032s87QofB/h26GggLWPvY5V14Jt275q2yw6nz9tRwYifhXdrYpg1AXYwLEWDv9dNEL0HequneXGGyA7dvRVq7gi7qTreWzgixwd+/2rm9nhiuukPBYvc65Rz8D7hDXSIzWZctEcEwv72SCnr00nk+4WYxnXQDAudno4uuvYfBgFu9oCcg+u2lM9rMXHTtKP7/wgvRzebkY2fruxfbtUmsvkmsYyeYEcODsKzhIEyofftr9YmwsxMYydy6MORSFfr7qKlkgKWX+XE2TWtobNtBu5becfTa8uvkYDrY5itJSqeB1VrL0My1bWm/j8uWGc9T96NRJwsE9+7m62t030exnq8b/HxTbaK0v5s+HggKmTPGsDS7KlElJedbWMLffDpdfHvTPRmzFHj3S0bTyEEcUAO2tGdVKiWvSYB6A/2foL0hx5ngGMIPjvBbiHToMIDExkVdemUVd3VaPcwx6kkw86H37ys+nn5bqKeXlAYSYPCZF31qgus1UV1fmk3dqoI0WPa0XXtjaw3GSTSwtWIWinFSPowuBNrzyCuFL8ASiVSu48EJOvrqdV917kHvds6pCz54izLNtG7RyKl74Ga0VFX7KvLpR07WrBVW9EHg/j+42Dx8u/exbXm3o0KGUlZWx7phj4MorA5y/Hdk40YyX49HZv9+tAhuA0M/gOCRiQursZiP3c2WTbNq3BzFmt+NrtJp6rk1OioGubXIyNGnidmcc4/zpabTqhvTBgwXmjda8PHlQy0ONaYHx92TnAYrn7pzrdVxFBWzaJNcgbBmeemDgQPl6mzYhURiffy41Z+66C7KyXHUVLXta4+KkbE2gkiYGOOkkuOvgveKRf+IJLw/c20/v5TLtdbRTT/G/OcygGx4WFmh33gldbj2NLeTxSNJDTH2y1nuzcc0aKXEUiedIb6OJHLh+/WTt6jrl5ptlTHjuOdlIePZZt+r0O+8A8BUTrQjDComJphSO/cjKkk22996TgXLSJLkp27SRSeSdd6BXL0uK4y4WLJAH04LB1bs3/Kf4bBxt20kdK4fDu583bBAjZOJEVq6U7rJk05iM7vBD7+fnn/c3/J39HLEXEyy3sceILF7nUpI+c/bzxx+LvHZdHV99qbhYewdHjwj7uUcP2dG2GuVx9tkSyvbQQ/ztrw7KalJ4a9IMvv4acqo3kLP798if59tuM1VOzY9bbmmYfra6gfJHxUwscUP9+1PktLZt68pHeecdpZo1UwquV5qWpt5+23oOUSiM5O4dffSdStMSVO/Oh9SmuK5qKL/5HNNWwUXmct90DOTdhm7vYQWaggQVG5ugkpMPe7UtLk7OOfPMMxW0UNBawWSvY8LmE+r5HosWGWrjiBHynqDUc88pVVdXpzRNU3//+9/lAGc/B7r28fHys1OnzurCCy809HlKKdN5ekopdcIJJyhA/fjjj6pHD6USEqTdLRKGqn6gTuAbZ7vKnTmYjwa8P8zmWr/zjpyjae48Vk/mzpX3/eorpZYuXaoA9fHHH3sfdPPNSqWmun5dvFipQYP+piBdXXONufa4mDVLHrolSwy1edcupTIzlRo71jvFb/Xq1QpQb731lt/5cr8drXr0GGetjWH6OfTzvMfZjw8rUGookucz+/Zv1DffKAVbnH9/2XWO6ZxWC/mYga7tww8vd7YFtSI5WQHqjTfecJ0zY4ZS4FDJyU3UTTfdZKKBkaE/1+5/vyhA3cwE1zEVFUq9/rpSMNv1fJlm6lTJ4bLIsmXSvldfDfz3666Te9dyamqEebfLl0v78geeLfm2l1+uVGqqWr9eqSe4RdVpMUqtXm2xcU4iydNzcuBVZ07w1Kkybuv5ZWeeqVRamlLFxZG18dAhU53w/ffSHC9JgVNPldw8/ft+843kvGVlqUUtTzI7Lfjzz3/Ke1tl1y6lMjKUGj/e+7tOny7t9XiuLRFBP3/5pZy67t635D8vveTdz+edJ9d29241aJB8BUtYmJ+9cDiUmjgxaD9HlBOsv/8vvyhVVGTp9NJSpVqyS1UmZchFuvFG1/x8faso9fOePUp98IHlNiqllHpL+tnx4ktq8GClsrOVatVKqc+SzlMOZz9HRDT7+fvvJYd35kx3P598cmTtM7nebqxgMqfV2EFSxHA94iq8K8DfuwG/AVXAbWbODfSvsRqt4RboLhwOpRIS1KqJd7iOT01VKiZmlBoxYoT1BuzbF3YwdxvI3v9SUmT87thRxHluOW2VUqBGJC70OK5IAWr4cCvqBE7atFHqsssMH+57TTMyWitAtW49xMs4AKWuvFLO+fjjj12LYPi7OaNLT+L/9ltD7XM45N9RRyk1wbmWzcrKUn/9q1OQ5dprlXr99aAiNDExSrVo0UJdbUaE5N13PRQ6jHHeeecpQK1du1Zde617EXv7GWeoBFADXJsT653X7e2A7TUlIlRbG/aQkhJ538ceU2rXrl0KUE2bPu/9DE2apFRuruuckSOVgrNVXFw3o93kj97P331n+JQXXpBTvv7a0zA9qAB18cQ7laqs9Dq+dWulUlLaqr94iqWY4aabvIz1QPg+A97/eqv4+PEKHlcJsa3V3HMfUWrbNnXvvUrFxPyoANWixczw41UoTjpJqWeesfLtXFRWVimIU/FaW7WreY7z/nvE1aaXXlIKihWgnonws8zgf11F4Gpi4mnOdosQGyiVkPCBAtTKlSvNf9BNN4lRZBGHQ/RtxoxRSm3dKjfowYOuv48fr9TgwZbfXjA5bvu2r21bpa45aatMNP36KTV9unrpuqWqkkR16LxLw79JOObOlcWflU0Dz4Yef7xS6emy2LvjDhGZAaUeeCDyNpqkqEg++sknZWNi2zal1JYtYvgPHereXL33XqVAHZOxVFkdalxE0M8unntO2nbddfLw1tYq1a2bCBIamBNCou9yWhj4d+yQU5+d6lDqmGPEMMjPFyts6VL54733qtpapZKSZK/UEjfeGNHzrJSSdgXp50AbrQ1N585KvdjX2c/DhyuVl6fWr6lVa+im9rWKQj+bXIcFxOFQavRopbKy1Ix+d6jc7IPqxmOWuvo5YqLZz6efrlRdnbym9/PSpZG2MDrP8xEm6kYrEAtsBjoihSaXAz18jmkBDAameBqtRs4N9K8xGq3eXg+Hn+fC0/jq2b5UKVB3xz/usSByKMhQxx5r1XWklJoyRd6sosJQe30NbFFNfFYB6rPrpykF6pNntrqOa9HiO+veBJ1+/WR3ySJDhw5VgGrW7AalzjhDqdNOc+2gzpsnx1RWVqqUlAxlyZO0YYMcbFIl8o47ZJ1z4IBSHTt2VJMmTfL6u7/Xxv0vMTFR3W5R+dIoV111lQLUgQMH1NSp8rm7dyv19uWXK0DlJMx0tme287rNDthWw57WESOUOuUUQ4e2bavUxRcr9dZbtQpiFNzn1WeFvY8TlVolc2GTJkq1bj1cjRtn0YOplLufPTyk4aiqEmN/1ChfD2cTdTOoRRc+4Tq2uFgpqFGaFuP2uptFf559jOFgvPOOLLZAhAiPP/5GlZCQoGJiYhSg5syZo5SS9Vpu7msKUBs3brTWtijTtm1/BSeoT7QzFGQoUZJWKilpm2rf/hIFZylAfWrWC7Rzpyz8LHiPfD3ZKRxQkKSaM1nl5Cj14IPy+sMPK/XEE6JUvtvK7r3Jfg7EP/8pb7H54feVAlW9aau6/XalVqxQqkMH2feJiL59DT/PgbjiCrEFD787XR7g1FSlQJXFZoihHSkRKBx7sXGjq21q/HhRxG3eXKmyssjfe/ZsWUCa6Oc2bZTq318Uok891fniY4+5b8rrrlMqMVEdOPE8BdbFUF1E2M9KKRmkhwyR9rVuLfM9iLc1UiyM2zoOh3jbLr1UiWc/KUna99hj4uXKylKqpEStXy8f8frrFtu4c6dsLkTKo4+6+/n666W9550X+fsqJaFNEXjUzzlHqY453v2c31P6uei/H4d/g3BE0M9erFrlnhRPPtmrnyMmCuO2Usrdz8cdJ9Es0eznzz9XauHC6LzXEcKs0Wokp3UIsEkpla+UqgbeB07zCTHeo5RaCNSYPfePgjv/6U1gElDlyqHU6xPq+YHF2yuZw2hW13gqY2wHSlm61GKdOjCVqxBI9KdnTwDJreyWsAyAM67Kdh13001LAOinKxBZIcJ8D73m6r59w9i24TDU1jJzprtuKkBSUhLnn38WAC1a5IRW4/WlTRtRZDSpwHDaaZJ2+e23IsZSVFQkF002Z4LmCqanV1JVVeXKhTWEUqJwXOP7OAUnJyeHVq1akZ6e7qprunYt9HUW9DvlL4XOFBSRyB00qE3A3E7DudYpKYZzKXr2lILkf/97LLK/tcv1t4oK2L++2JV3tGGDlNmrqdlJGwsqki4s5PUkJMApp0ipRc9cxziaUgRMm+HOrV65EmAnSjlo376971sZo08fqTlnUFxm0iT44ANJSdu1C2bMGEd1dTVNm8rNN++zz9i1U/H779CyZT6xsbHkRJJ3FEXefXc68BL3qH8CbYCdwHccPtyH7duno2nfANDDbLHRlBTJU3MKPZnBV1W6DcVkkcFeyti61f0snHsuHDwo95Gp51gnCoIZl1wi6V9vzhJV9zdntOLxx6Xs9PbtEeSz6nTuLPmyFrnoIigrg9dLz4IpU6gdMIQHYx7k6Ws3RkdOOwKFYy86d4bffhPxt1mzZD749FOp/xgpmzZJbUYT/dyvn2jwVFXJuKMUol1xxhlywH//C6edxqMtnwFgzJgI29iiReQ5cLGxUgs0K0sGonnz5GE588wIG0dEeXqaJvVvly5Fcia/+ELG1jvvlHHio48gM9OVum1JhAmgdWsRrYiUO+4Q4a2kJFGZPeUUeOaZyN8XRFjisccsnz54MORvjaXwDXc/Z2+YyxOZ/6TF1WdE3r4IxaJc9OwpkyKIyJZHP0dMtISO7rhDBvBZs6RPotnPp54qAmv/QxgxWtuir3SFHc7XjGD4XE3TrtI0bZGmaYuKG6Eallt1sxh4D5gA7GfbNn9Bjz20ZAxz+MLLPl8BwP79ERitET5Enkbr4eJdogSYnOz6+9KlS+nYsSOZkTzwkUiZ4zZaYSjfFvamsmlb3n5b5kNPFdnrr7+eHj16sGpVv/BqvJ40aSIiDSarig8dKl/ts8+gffv2bN++XRbLiYnwww8BRWgALr5YSuOYWux+8YUMuitWGD7l1ltvZfny5WiaRr9+oq3y5ZfQ9cILiY+Pp0nWWgoK4MILVwEJ/OMfHb1Kf5gWETLRz4MGicbL1q0ArQFvIabMardYxpIlAIrS0giN1vR0qYNgclI86yy3mqxOEhkUAev2+RqtMihYNlonThSRCxPPW3m59G1dHcCxwAUcOPAZeU2ymD31RcaO04iNhayszXTo0IH4+HhrbdO5915X6SCzeAqTXXJJR6A96+iBGK35wKVAO2AFnTrtZ/PmzRxl1vrS+9nimOOpKt2cYrpR7WzbG1RX3wS8Tnb2Qfbu3UtWVpa16xkFwYz27UX09fWFPSlKyWPK4wk0awarVomhY1k5WGf6dCmjY5HRo2Wh++STUPevJ5mVeDIPOP7B0adGoMbry2WXiVEYKb16ydi6caMYsM6NvYixsBA/9lho21aqF+3bJ01yDcgpKZCfzxeTPuDRN1pxyy2iOxZxG6OxvkpPl7XD6afLwH7PPdHZWEhPF0P4xhstnd6/v2yQVlUhc31JiQhbLVsmFxvR3EpIkNvAElu3inK3b400s2iaeDs2b5Z/H34oIofRIBKFY9yitl/OSYeOHVFnn03fjK0sn3hvdPo5IyOicdsL/bnz6eeIOfFEMTQjFd/Ta6slJUW/nzdulDb+D2HEaA10hyqD72/4XKXUS0qpQUqpQZbKCtQz7s3i2xCH8e/AdXToYLSMxEoA2re3OlIS8e7UgAEgdVqhLDub0pNPpqyszPX3JUuW0N+kMefH5MleteXMcuGFF3LrrbeRm5vHf0sv5M3dx1NSImO7JwMGDGD16tXWSlDs3Qse6qVGiI2VDbJvv4W2bcVoVUVF4g3NzPSr/5iRIYv1iy6yYLRa2JxITEykhXNx3KIFnHeetKeiqIru3bqxzFlbQX724ppr4rn4Yjn37bdNGP2ebTR4H/7tbzJei1HfGk9PK8CbmTe5dukXL4bExP3U1FRHZrRqmpRoMFmI77jj/OfkVJpQBMS0cpdOWLkS0tKkfqllo9UC997rWQ2iCfAutbV96VjVlJ8ccWzf7uC772D//s101MtlREJFhanNEx3f6JOtWxV55Dv/2gZYimxeTAU6sWVLEk880dF8CSZNi3ijDGQMX09XdjIcyWK5FPgPcBlXXDGV4uJia2MNiMplnz76ToNl7rgDig6l0qVyOQUFok6ue94i9rRGiKaJg3DTJvh8zzBmHRhEYmL07EFA6pbOmxf5+6xdK6UomjWLngcXLEV33HKLPCP62Pvbb/LT8eD/werVFMbncumlMnc//HCU2qgr30eCUjKPdu0aHS+1jqbJgj4uztLpAwbIlLx6Ne5+GDbMq07yggXi4U5MtNjGwkIx0levtvgGHkydKvdixLsRPkQ4JnbvLlVbPv8cWLSITQ9/RP7edOvK1b6YrGscEn0d4tPPEdOunRjAHo4dyxQXi1R1tPv5+efdURn/Ixjp4R1ITQeddkhslxEiObdR4e1JOw+4CfiIm24q8It+uoB3WUs3WuC5qF+BpuXwyCMZWCZCKfNOneDDD8XTWnbssVxQXs7kyZMBKC0tZfPmzZEbrRMmwF/+Yvn0AQMG8MQTjzP14UpWql5cN+sMOneWecJSTdFgbbz6atOnjRwpIXBJSe2pqKigRFyHLiPTMyR7wADZ9a2qsmC0RsEzc+utUmrmvhGz2bOuC7Nn/0ZtbR3r1i0D+rFzp25MmCh140l2tnxAZWXYQ1u2lAVtRQXExLTC09OakgK5z90mOwKIp/Woo2SIiMhoBQm5uvBCU6ckJ8OQId6vZZJIEXD5Xd6e1latpH9aWq0Ft22bXEdd/t7gKYFIqe1BLWXcdNMGRo6E/Px8OnXqZK1dnpjoZ098o0/SKeMrdHl/vV+HIvVmxZ574QWLJZgi9CqAbEqW0JStruiYe4AK4Cg++WQhq1bttV7uZuBACTXwvbFMcuyxMGfQbaTGHWbkSHEEvPyyOKVM7s3488knYgFbqIOqc+aZ0LljHZfXvsi76wcwYkR01nsuotDPgBi+N94o93U0sRgJFRsrRkJGhhit//0vNM9N5atVuVx0kWxSvfdeBEaWJ48+KsZmpPjWnYwmL70kg4EF9OXL0qW4+8GjTmtdHSxaJJFTlolmfcyvv5bNmGgTQV1jEJvytNNg9mx5m19+kdejZrSChII98EB03qtjx8hqsgaislJCjX3r4Flhzx7vesHRokULGcciGLf/aBgxWhcCXTRNy9M0LQE4H/jC4PtHcm6jwjf/CW4AYvjHP/7NSSd5h4bmsJVurOf8K9Ncx2vaCvr162POm+VL27bw+usRbV/36iW7ouXl5axcuZINziJ/uidugLhjrVNeLpaHdwFE05x6fBWvjnwDpTSGDhUb09KCNhAW83r0CbGqSvZhduh5dD4Td02NlOkdOdJdz7W+Pa2B2nrssfD89tMorj2NmpoyTj75WxyOYsB7Y8JQfVtfRowQS7S21tDht94qG+jJya2BImAOqanX8/K/K2mydytdcqrRNPj5Z4iNLQSiYLSC4fZ58uST8jMtTSbv6tTu7EXjlCuaAbIpsWoVZGbuISYmxlqeI8gqde9eqW1skGDpgT9wPwBt2syjrKyMvXv3Rs9oBdP3oq9xnU0xPVjLBGbgzhC5B89gHOUTg2P4vhw1KuL42ClTYHDSSo6nNbAB0RSMAwZSV7eUDRsi8LRGkWFvXEP+T9v5/nu5Nzt3lvSoSKPA2bcP5syJaMyJjYVvXtxBN9axqyyVCRMibJMv0fbMRLs/s7PFSrcw98XEiCH1ww8SqFR6wMEpp8BPP0nUY9Q86YmJ0fFGpafLov7aayN/L1+mT4c33rB0aqdOMm4vXUrAfl6zRjQTIto/imZ9zOLi+jH8o7CGOPVU2Zf4/pgp/PLxHpo3x6WXERUGDIBoRCmddpqE3bZrF/l7eVJdLYIGX30V+Xt51guOJtHcQPmDEHb0UkrVAn8FZgBrgQ+VUqs1TbtG07RrADRNa6Vp2g7gFuA+TdN2aJqWHuzc+voy9c2kSbK4kdrc7YBzKS9/mTfeKGPyZHdoaOe0PdQkpTL1pWQ2bYL4+CpgPSeeaDXz30lysngxIwj7S08XT+v+G29kZ2GhCAoB69atA6CX5UQPJ7Nni2dhzZrI3qdpU/7yy+Vs3Sq7fL7rAEuGlo7FxU/37pILs3evDI7bt22D1FQ/d8LSpTKfjxgB+/eLpzUrK8v4B6WnywdFMBBNmyZdcDFv8mDCXAC+//5Z51/7+R1vLMTdg2OOgX/9y3BoWGqqOHOqq1sBdbRseT4HD/6HhPU/c/pNuXTaNhsQw2XlSvG0tm1rNHU+CFdcYWm1N2IEXHedbGD+9hvc+lgfFIq95eWA9O+hQ5CaKoZMjNVFoIV+DpQ7rWlQwQCSYtNYvHgem52bKVExWi1Gd/ga19nI+a1bKNq1uxB4FVye1+AYui+ffRaeespU+3yZNAneHPMaH3EB4GkADwC2UVOz2bqnFWDsWHjiiYjaCED37iQNHxBdDyZEbSHeJaWQuYzky/sXWU1LDE40RIRA7uXU1IiEpwKSkSETk4UoHoCjj5bw6n374Idm53FRp1/5298k4yZqrF0r4+LGjZG/lzvnI7pE0M8xMbL8+PVXZJDOyPDq599/l58RGa0R5tF7UV/GzDnnwJYtIhplkREjoGl6DQ8tncj3v6czcmR0o+mZNw9efTWKbxhlotnPXbpITHq0ieYGyh8EQ6stpdQ3SqmjlFKdlFJTnK+9oJR6wfn/3UqpdkqpdKVUpvP/ZcHO/SNz772eqUk3A+VUVr7KN9+4Q0MvP7WY+NZuNdSamg0oVRe5QQjixXR6Ra2gG61r9+7FoRT79u2jpqaGnTt3omkarSMY5ICIQ5hd1NWBUnToEFzvwLShpWMx30NXMN66VXYHt7doEVAwQk+78jRaTXnjNE3EosaPN91GcOcT7tqleIUriavKQtPygJnOI/xjCU0LfColXnUTYaNHHw233y73V1GRhAi//7IsnopxT9x1dWK0Rnwvpqdbvg8feUQCG66/HlrUiTLT7t3S5hkz5JikpD2Red/0vB4TE45v7nRODpx9NsTHKUYPHMjs2bOja7R27ChiKyYX+L7GtZ4qcf4N2Tz6aDPi4i7DyPQTDeFZo3RvuoeSON/+1KMSDkXW1xs3Rr6Rp5TEA0cjl86XaKl59u9P7MrlTLzlqOgb1nl5omQaKfUVqhfhiv7oo+Xn6acrxpR+zttnf8HUqVE2FEpKxFDYtCmy91m8GG66CXbvDnuoaSL0qI8bJ0ukfbdMkR0ADxYsEN27iAIz9Dz6SJ8VpeR71se9mJkpeVQWc4NBTn3uiuXspTk79yVFrlzty/Tpcg9Fyr33Rnlnx4mF+TkoH30E//d/kb+PL9Fab/+BiGLW8v8G3obSIGA0MJWtWz3CED0mRdEwWQtA9+7dI2/AFVdEJHTUpEkTAFZ5SKQWFxeza9cuWrRoQVwEgxxgOVzBU2k0NxfmX/2ahDLt2BF04Wp5QWsxTw8k7Hbt2lbExcWxPTsb/vlPv2PmzpW1fps2YrTGxcWRmppq7oPuvNOy0arnE6ZTRgI17KEFSo0GoEWLTqSkpHsdb6rUjc7mzWIUfvSRqdNOOklXzZOflSUFAOzB0yDYCTQjMdIkrgj6OT1d5pjFi2HDVCkFpUclfP+9bJqWlRW7xK8iaqPJZ8W3nNW0abB+QwxnXX4BW7du5StnOFNUhJh695aSIHq9KRNt9DSuuzWV73ji5BZMmmQslcnwffnaaxJmZqGfvSguJiWnhY/zyB1KH5HRGo3Q1rIy2Y367rvI3icQ0Vr8JCeLLGt6evhjzaI/kJFSXyGZAP/4h+U8vWOOgSuvhCfuPyg5JvXRxmj185IlIiJkoiybYfQ8PYvP87hxYg/OmYMeFudiwQLxska8EbB0qeW8WxeHDsl3jUYajC/l5VJeZdGiiN7mgm5L2UIes9/fwzXXRKltOhH2s4uFC6OTdxqIKIj81Ss9e8qCZPDgI92SBsM2Wk3ibyjdAmwlJuZTpk2DiooKTt+6lRVOZYwVKyAmZi2aptG1a9fIGxDhzk9MTAxpTZo4tYyFoqIidu3aFblnS28fmGqjv9IofPtWsUyIzZoFLSdz8KDFvNYTThC1Cwv07w9798bSsmUbtm/a5JczqZQYrXra8f79+2natCma2VmypETCeyygb6w4iOEepvAzo4FjABg1ql9kpW50LG5O9O/fn3PPvYisrBcBWEg7HuB+itCN2dXA98TGRiE/JcJ8j4sukhye17bLxSkqKqK8XDzpxx8Pe/bsidxoPfdcCR21yLRp0L9TGVd0nM1T94ur5v3336d58+auqIojhadx/diy48X4dYpl3HNP6HNN3ZcOB+zYEfnioriY5t2zeekl8bJLO5qSnZ0LEFl4cDQWPwGEZaJGixZibEa6UfTLL5KE6Zug3JiYPl3uxfrg998tbyokJck93ynVmeNeH/0crRw4/fz6ytOLifHzkhplyBCpdjP7/+Z5zfOFhaJFEJEIk2cbExIie4/UVBm3/va3KDTIB4cD7rrLablHQHExCdQw9rT06AiBeRLNe7G+NqGisdmYny+5ZXqIVjRJTxdh0WbNov/ejRTbaDWJvwE1EeiMw/EUV10FDz+8kM83bOBFpzLGr79Cauoa8vLySI5GvFQUFj/pKSl4TgdFRUXs3LkzOkarhTw9X6VRgMyaYg5qki+qe218n8t9+ywKMvXvD9dcY0naUk9LSE9vz/bPPvPLX9q8Wex1vbSlbrSa5oYbZMvYAvrGykHSeIR7WMRgdKO1f//+fp46S+Jgej+b3EBJSUnhgw/eZvJkseqrKeFBHqCGBGAeMBAoQ9Mej0whGiLO94iLkyjtzdWSAPXNN0V8/73sUxx3nBitEYvz3H231L2wgL7Zk759FT9wLLm7C9G03lRVVUUnNFinQ4cIEsidtG8vYcbOhZ6mBZ9nc3JM3pdRCG2dNg12r9zD619lc++94qRQStoxatQA58dE6GmNNMysvgSEQJ7nlSulVlYkfPKJ3NNRjWl1smiRjImRhkenp0eU6xeSaPRzfRqEFutX+7Fnj+gZRDsvGCTUs6bGsrBOfLzUDf5hVQsvT+ODD4otHEFxAzeffipe9cZKtPIxk5JkM6s++jlaRmt9hfsD/PvfEZaqQOoOr1tXfxt5n38uyp//I9hGq0l0A8o9J8cCVwDzqago4j//WQrAl19+yfffK+bMgZSUtdEJDYaoTIppzlBV3fune1qjotaqaVJA0ESpkUC5qS3YQ5FyD0STJsnGpC+WBJmqqiS8x4L0f9++8hXj4tqzPYDk/1zRPPLztJomgs0JfWMlnVLasZ0Y6khJ6citt37J9ddfb+k9/Yiwztonn2QB8aSxiRP52vnq60ASsIra2gkR20l07y6yxVbVfYGzz1I8pd2PRjIffFDEuefKtR08uJrS0tLIPa0gKoUW0Dd79HxRCQM/CYhSPquOwyETbyTMnSvS0B5MneofQWEpVD3CkEfd+D+x7ise5U4/dXK9DFhEntaBA/VC2dapT2MmWtTnArKmBn78MQIxA2ThePfdfvdi1IiGR/3ooyV01OKmZUj08JoIawbXq3crPj5iheNxYxXraruwM0lSJNatkyyCa6+NSMfSzc8/w9NPR/4ep5wS2f0cjGjl3d5yi2xm1QfREBGqz7xgkDrEkc6l9RkhAyK88fLL9fPejRDbaLXApEm+myZ6CZr5HCxZAMD27du57roV5ObWUlKygR49ekTnw7OzZUKLoKRMunOy6ebUL9+5cydFRUXR8bSC7Nb37Wv48EC5qdkUU5bgPSkGG9tNj/nbt8sC8ptvTJ4om8udO0PloTbsAJTPQnbuXLGRdGn4kpISc8rBOhH0s76xck3Tj9hOB4a03clLL8ETT0wkMzPTfFtCtdHiAm37dg1oxQ7i+ZaTAQV8AxwPyOAe8VzepYsotkawStHKy7hZPU1OVhLjxhW58s7KyuR7R2y0PvmkhGRa6Gf9+ujKvCJmdSIQZaM1GiFSDz0Ed9zh9VIgUamGDFXX0Y3/ZfRnA5LC4bkZduaZZzJ27NjINh5vvlnCUiNBX9zV1+Ln0kstK9+6qO9QPf0zrFJaKrVKFy6MTpt80fPoIyz5RkpK5OGnwdi4MXIl68OHo18XU6ekRAbZH3+0/BbHDpUavC9vGktNjQQuJSdHHjDiIgK9BBfr10s5lfqISoDolYiqL/r3l9C0SDZnDh+GYcOiXIvHg9WrpaZYVZX196jvzcZoiUX9QbCNVou467WClEWIB+aTGLfEJd2xefNX3HLLFqqqqqLnaT33XEm8jkAwKc0pxtSzZ0+Sk5NZuXIlDocjOp5WEGXC2bMNHx4oZ/WLhLOpO8/bWxs1QSZ9sjXhPfIUitq5EwoL21MFFPuEGM+dC8OH17F6texOWva0tnLmeFpUZ5w0CR67Sb7fb5uyI6sPHIy//tWyap/0WUvS2UA2e4DlwC7gJJ9jIuTQIXAqOFsiMRHef5+W7dsTG1vE7Nkyh+1xThIRhwfr94aFftavT2ukn/fQAhhOauoVnHXWWZG1y5NWreSmj4RduwIucqMSqt6qlXgsLG66bdsGLSjiCl6mFbu8Xgfo0aMHs2fPNi+mFm3OP19EEuortHX37oiFW4L1c1SwMG77oT9n9dXG9u2lzFZZmfX3mD5damA35rzgjz92hxVFm7g4eOUVUU2ySL/sQi7gXR74fjjjxsGsWeIYjdp+jz4/R3Iv6ufW1yZUq1aRqzufc45lYbGwJCXJhnIkybLJyeKxrg/1YJAc9Ztvjmz+a4h+jjQS6g+EbbRaZMoUz43QZKAfMTE/UenYxFgSiIsdTFral3ToIMrBUfO0duokidcR7MKm5+cDkJOTQ8uWLVnmLKETNU/rk0+KcW2QQB6Xo1+7ikFveQsUBDJuLYUTpqWJsVBQYOhwX6GoQ4egsioXgO0euR7PPy+bpy1afEWfPn1Yv369daNV3xUx2MaAFBRQmdGK3G5JLlXmiPNEPbn8cqm3YoEpUyAmphU5/M49PIx4WQFOACz2ayByciLbXk9KgvPOo2Vurks9GERxG6LgaY2gn/XnIZcCdtKaahJJSYnnhRdepq+JSIew5ObKzW8VPTk0NzdKDfIhNRW++ELGRQt06AD9WcrLXEVH8r1ejxpLlsgb/vST9fdISxM150gV3oORk9O4+1kftyNpo/6c1VcbL7pIJgHdqLHCt9/KQF1fHrh33oEzz4z8fSIM4Q1KFPpZO1DCa63u5eheZcydK8LTV1wRxTbq43ak92Lr1pGLnwVj2jRnwVqLKCWiYiUl0WuTLy+8AB98UH/vHynRWIe1awdnnFF//ayLQPyPYButFpk0SXK0ddLShuFwzKfOUUc+Z1Fbdzrl5b/zzDOS99AtWuEL1dWyyxlBnkG6M9ShQ4cOtGrVivVOufCoGa25uaKSVF5u+BQvj8uGaiaNL/LbaY5aOCFIzT+DD3ogoSgQkYjtTsGtN94Qx+Npp0G/frIrt2jRIsrKyqwZrX36wH/+E1FBud3zC1henuelymxJuCoYlZUSPmMhJ3PSJBhzdCbFONhKLnFx3xAbOxBNaxlZv/qSmxvZgL5+PcyZQ8sWLbyM1qh5WvPy5KeFNurPw7Q2t3MxbxMb6w5rjermxIQJshi3mge3fz8cPMii/XleZa2i2kaw3L4pU+Co+AIACsgForhpopOVJWkJ+fnhjw3GK6+IcV5f5OWZHre90DRRQ61PgZoxYyLKUXc9Z/pz1xjZsqX+jGoQGd1PP7Xez/v3i9FbX3nBIN/fono+AEcfTdKuLXzzSzrffRfFsGCdvDwpp+MxJ5imoKB+78OmTSU/2CrOcbte2/jyy7J4ssrrr0vZl0iiqUIRwfzs4rLLRKCuvoh03P6DYRutEXDVVaKvMXo0vPji0a7Xv+Yezj/vBkaNGsVPP/1EmzZtyMjIiM6Happ4MU3Wx/QkzWmB6Z5Wh7Nma9TCgyN90FeulJ3qzz/3+1NUwgnBlDETOLdSduC2lpTgcEjp3OHDZdOwokJCw+bNmwdgzWht3lxUI9q3D3mYb31bT0OgesMW8h25XsdbEq4KxhdfiLKggRppgdo5vFsie4D73myKw/Ebd999YuT96kukRuvrr8OECbRs2ZLi4mLqnIZR1Dyt7drJRbHYxkmT4LJ/dWd+yrEumy3qmxNnnikx0T41Dw3j/G6Pf5hbfxsoV14pGz0WmDQJrj6+gGri2U3r6G6a6ETYzwA8/DC8/37UmuSHbihF0saMjPotv/DxxwFrYxtm1y6JUqqvEGulpKTas89af4/6Nmb0frbqJczPF6O3vgwFMLWpHIrMTClPFnWndW6u5FOef77192jeXBaQ9cX69SLSY9X4r++oBIi8n9etk3S0aGp1eBKNcbu+w/wnT5brEKgu5J8Q22iNkDFjRG26X79hzlfSaE4W73+Qxi+/fEt8/Cl07Toxeh8YHy8PktWHqK6OdOeOjG606rSMVp5PpIufhhgsb73V21UegkBhgkmkAGls3ryZhQvFwXDNNRIBUubMZ5rrzPmxZLSCTDpLlwb9c6D6tp6GwJ21D/MyV/qdFzWxQoP9HKydBzeBA/iyoACHw8G4+lDL1I1WqxPHli2Qk0OXo47C4XDwiXPHdM+ePcTHx0e+GRUfD/fd566RZJa6Opbe+AYtK7w9eFHdnAARorAqLtOjB6e0Wsj31cd4vRzVNmZkyGLaYj/3bFJAQucc6lRMdDdNdCIdt2trxVNbn8ZM9+5icFl9Vn7/XWpD1qcxEykPPijtq6/QVk2DtWut5wbr/Vyfc5/+3pEaM/V5L3buLH1k9V68+24JfaovYmIiD9P/8MPINjfCceCARGtZLRGl3x/1fS9GMj8XFEjIXX09zwkJUrTb6rNSWysG9VNPRbVZXrRqJSrHVjeV/2DYRmuEjB0r0ZHLl+ciqqd92YWzMj1NqKn5gnnzXoxuKFwk3qPCQporRYymeRmt2dnZJERLrTBak2J9DpZHHw3jxxs6NFAu7fl8BOSxcWM+06fLmvSUU+RvpaWlAKxatQqIwGi9+uqQhccDhS17GgK/5ZzPT4z1Oy9quXoGPerB2rlrkYQVf/Lbb8TGxjJ48OAoNcwDfUfcqrqe0+tx4YUXMnDgQK677jr27NnjqtGqRWML/8EHxR1ghcJCnth3KeOZ5fenqG1O7N0rghevvmrt/ORkvi4axAH8VbSj1sa8POlnq+F69ZmLqRPJuL1zpyyA6rONffpIPqVFjzW//CIFbutrAQni4evUKTKBGacQYb0RST/v3SsbMPXt3YLIN5W91Sijy6OPirFldXydPRs2bIhum3yZOtVPEb1REanzIDlZNlPr2+vf2MftefMk9MYKhYUiypaWFt02eVJTI5sfv/xSf5/RiLCN1ggZNUo2OK69VgNeJpl7kfIdbqqro+z1iCTfIzGRy26/nR9ffZWsrCyX0Rq1fFYQCe7vvjMlxuRFQYFM3PUV8gEykHz5pSHVtUC5tBOTZwGdWb16M9OnS9qf3lzd06qcu4eWSt5A2MVPyBJARUW8OPlXmiZ7S/JHNVcvO1smtjCTYrB2/nLoZAC+//FH+vbtWz/qrGPHyuLC6oaMc1KMi4vjzTffpKysjJtvvpni4uLo1GgFmbQ3b7bePmAL/guLqG1ONGsmglRWFz9ff831zQKHtUatjZEu0L7+2rpRbpTTToNjjgl/XCAawuuhE4nXIzOzfsft+HjxqFvt5yuvrN/8MojMaG3VSgzXqKoG+ZCdDT16RBbuX9/9HCkNYcwsWWI9XP+336BfP3CKYNYLLVrI/Gx1rXjyyaIQHa3UtkDk5blz4a3QEP3cvr3Mf1ZoiKiEuDiJcPnss/r7jEaEbbRGyJdfyth/4ADEchIVnMgd/MvvuKjWj87Lkx0cCwI4tGxJxr/+xehLL3X+Wg9Gq6aJ58iqgmJ9C1GAhGCdeirMmWPocK9c2jUVHFv5FSnx7dm+fQsFBQ4vEV3d06pj2dOamxuyn0OWAPruO45/aASv/V9hdISrAqFphjZQghombSSfp6qqihFWw2PD0bOneKutbBwcOiQeWue92LNnT26++Wbee+89lixZEj2j9dFHRXDLyvPsvPZFSbleL0d1c0LvZ6sL8f/+lwebPBYd5e9gRBrd0ayZ340aKl/cErfcIjKmVtAnkPoWEDr+eOt5eg2xgIzES3jokIhZrVsX1Sb5kZsri3Arz7NOfSkH6++9ejVcd5218+Pjpc55fbJ7N5x4onj+zVJRIeN2fT8rYebnkGzYAMuX16/XP9JxuyGYMEEEHQcNMn+uwwHHHSeeo/pk/ny46SZr/dwQUYN/hH6OIrbRGgF6rp5+L+ciC6bt+IvnRLV8wlVXycRrJadi925RGnOiG61RE2HSmT/f+irvyivhzjuj2x5f9NAmK4vcggIyKeUfZ1UCVTRtupNTT3X/uaysjDSPcJCIjFalxMAOQMgSQAUFoGmc9tf20RGuCsYjj8CNN4Y8JFg7Xzlziev34cOHR7lhHmzYYK2fExJg3jw+S7nQZby8886NxMTEUVhYGLlysE6Yfg6Js5/v/m+H+tuc0NsYQbh/0/650VP+Dta+666ztlDVFW89lH3D5YtbprZW/pnlooskF7O+F+JxcbBxo7VzG8JojaQEhS48VN/XsG9fGDfOWq3WV1+VTYPGXKP16afhhx/q9zNSUyVaa/ly8+c2hKGgv7/DEdG4Hd2FYQA6dpTNGisMHy41SuuThATrpWBiYuDtt+Hii6PbJl/WrZNoLSv9vGWL9HMYQc2IsY1WGyP45up1YRPgLpugk5AQ5fIJbdpIAXMruUN33y2TqpN68bSCDCY33GDt3NNOgwsuiG57fElNlTApKw+685z+Q7sD8PHH+V6CmaWlpQwePNiV75hpNYwqTMhjyBJABQVyn9RXbTAdAyGPAdv5ouLE1y6liVOSv16N1hEjxJtplvh4pm0ZzqR73aq3hYWtgYuAKCgH60QS2urs5wv+kli/mxNWVR49andGTfk7EE2aSKHkYcPCH+vLihXiAfXIkwyXL26J336TMDOD0R1eaJpEC9S32EYki5+Skvo3FFJTRXXV4mYjUP9tPPNMmDVL2mmWuXPlX316WgGeew6GDq3fz4gEvZ+t3ItVVTBkiKyR6pNIvP4NNT9/8YUY/2ZRSjYM6vs+BNkw/O9/zZ9XV9cwmzuRzM99+4ogWH33s2202hjBN+Q3z+lp9TRamzWD116L8gLt8GHZ+fntN/Pn+uyGt2vXjhYtWjAw2tLrubmyiPEJlQ1LZaUoLx48GN32BMLCgz5tGgy7qg+X8jo3/EuMtS1bvPMRy8rKaNWqFXl5eWRmZhJrdaHZr5/En/frF/SQoIZAQ3g9QPKvvvtO+i0Efu08fi9UVNAyPZ22bdvSvj53Iq0O6IsWsfDGd6iuqPF6ua7uVkCenagQyaT4+OPWFiVmOeMMsdic5bEMs2+f7PQ3xL1YW2tNcCtA3lHIfHGrtG4tCy0rBteUKfWfcwvWx20Qj/W//FNjos5554nSsVkaMi/YKg2RGgMyXi9YYL6f9+4Vg/Cbb+qnXZ5Yje7o31+UrOuznAxI+9q3t6aq3lD9bFUUba/Mzw3Sxm+/DVjeMCwvvCD5ts7yc/VGJKknZ5xRvwrROrm5EonzP1Cr1TZaI8A3siOXAg6TSGKHViglm0B799aD1yMuTkq2fP21+XN9asClpKRQVFTEmWeeGb32gfWF+KpVMHhw/YcfgelJUQ8Z/L2wHW/wFzbs6gXE8vnn3uVGSktLSU9Pp1evXpGFkGZmwsSJ1uoeNpTR+tNPkntkVqnReV8cN3gwkyZNio4KbzCsegk//JBH911BHb6bDj2BBVx11VVRaBxSCiU21tqk2Ly51Mqtb8aPlzHH7CKoIQ2FSZOs5TcVFMhOuEfJr5D54lbR+9nKvfjyy/Ks1TeR1PDUNMl3rG+ee05yzMxSVSU6C9Eq7RYMh0Ny6a3kLzfUuG21n7dsgYULrYW4myVKtVrrjdxc2cXSywaYoW9fyeesb5YtE+0OA7XUvWioqAT9M6xGTlRX129daIhs3C4paRhv8LXXiqOnPlWKGwm20RoBvrl633McD8X/k38+XM+XNS5OdvjMPkQNUQNOx2roTEOorek89JCpHT49ZHAYv9GLlUA80IGZM/09rRkZGTz++OO8+eabkbXx558l1Mwsb78tRkZ9Y3Vzwnn8fx97jMceeyyaLfInN1cWZ2a9hAUFFMbloAIMkzk5g6OndhwXJ/X0PBOjjVBbKwvj+lSg1NE9hHv3mjtv0CAJuzVYXioicnIs97MradlJyHxxq0Qybu/Y0TDjdp8+oimQnGzuvB9/lE0Dq6UrzOJwmF8M3nKLqMXXZ0kekPevqDBvKOj93BBzX4TjdoPciwMGWNsluvJKvJQRGyNTp8L999f/59TUSLRWYzZa8/KiNm7XC/q4bXbuq62VFLSHHqqfdnmSllb/pbwaCbbRGgG+uXqbcsbT8/Xbou9ZDURurvkyGdu2yeKzIXdy8/NDHuaH/p3qswacTrdupsLM9NDA5/grT3Cb89WOVFS4++Hw4cNUV1eTnp7OUUcdxdFHHx1ZG++/H/7+d/PnjRwpYVL1jd7PZu/Fhuzn3Fzxsuzcae68zZtJ7p5bv6q3OlddJWF3Zti6VfKBFi+OcmMCUFIioh5vv23uPE0Tz1ZDTKhW+3nfPr8xMWS+eKRtbMzjdteu8kW7dDF33u+/w7vvWi8NYYZ33hGjurCw/j/LKlb6uaxMUkE6d66PFnnzRxi377oLZs40f96SJQ2TXgRw331wySXmzqmtNW+gWcVqP7dsKYJgDbVWtDJu5+c3XKj/+vUSjmyGrVtl3I5WGlEoqqvh9tvhq6/q/7OOMLbRGiGuXL3KKgo+XMCkc2vCnhMV+vcXD4sZGe6sLFmQjBlTX61y06yZtM+sGNPChbLzVp+1wXQqKsTDtXChocM7dIAkKunNSpaiG4SdiIlxG+Z6jdaMaLVfr+Vmpp+XLIGPPoqs5IJRmjWDtm0NX0MX110nBeAbop9POEFqM5ope1NZCStXUpLT38vppDtR7r03CkqynpSVSZ6YmT7Tr3mInOeoYbWf//UveP31+mmTL/omjdk2zpolBpcP9SIc9Ze/mF/kLlggPxuin0G+sNkF5MKFsqnREM9zp07ynJjp58pK2RSykjtnBSvjdtOmoucweXJ9tcpN8+Zw0knmxaIWLGi4ftYx41F3jtsN9qwcOmR+rv3oI/HAWa3NbYbmza2N26NHw3vvQXp6/bTLk3795HqYUedt6H62UuddH7cbwnkQHy/9FdVFSePENlqjxYIFosZnpa6YFYYPl9APMzXnsrIkdKZTp/prl46mSd6GmbI8SsG8eaL22hDExkrI2AcfGDp8yhQYmbiIBGqYh7QxPr4jDsdeSkpKALfRmh6twX7ECBHeWrrU+Dmvvy6L44ZQ/tM0aeOvv5o7Lz0dxo6tnzb50rGjCCKY8fYtWwY1Ndz//QjPClGuDfKolUDR+f57KeZupp/nzZPv5KEGXm/o/TxvnvFzlIKnnpLQ0YZgwADJTTXTRpDvZrUslVkmT5b8IzPs3i2Lz4boZ4BLLzWnwtzQ47aVfl60SBbu9R1KqGNl3G7IMjeaJpoYZsuF5OQ0XOitUrKmuusu4+csXCjrooa6F/V+NpOi8euv4llsCG+11XHbQ0m93hk2TNIKzESlVVVJWUSzKTVW2bBBKiUsWRL+WB19fu7Tp/7apWN1HfYHxDZao4U+KNRn6Q5PTj4ZDhww90B8/nmE8pcmWb9e5L7NhHFNny6GZEOQmCg5dwYH9EmT4F+nybHzOZqcHLjttsEA/OZUci51qjFGzdOqT75mJp1582SybwhRFJAQ5u+/N77o2r4dHnjAWt0zq6xcKWGFRjn6aIa13c431ccGPSTiEiieRNLPVuo1W2H4cBk/duwwdnx+vixGGmpMTEyEf/8bzjnH+DmvvQaXXSZhXA3Fzp3maqHedJMsIhuqnwcMkGfT6POp93NDGQomx23AfWyk6RpGGTFCPOpmcoOPOUZC/BqSmhoxAIzy9NNQ3xoEOrqw1y+/GD9HX7Q3ZD9D4x63x42T6DWj9Vrz80Xp3GwqiFViYsxvsGdmip5DQ80taWlSPshMubJff23c8/MfFNtojRa//ir5QFZqs1khOVlqmRnl4EE46yx45ZX6a5Mv5eVSO3HuXGPHa1rD5WLqjBghOYFhSrbo9K+Ufi5WzSkogPvuG0Z8fDxznINZ1D2trVvLhDN/vrHjy8ulvlpDLSABevSQe9/oxPPTT/Dgg7Lp0lC8844YJwb7GWDBznZUkhLymKjtAen9bHSntKpK3L0NNWmD+QWaflxD3otXXmmu/uSnn8o1r+/6p56MHCn1ss3QkO3T+8vovVhcLArWDdnPJsdt5s1r2Pm5dWt4803jm8rl5dJGswJYkbB+vSz+P/vM2PGVlQ3rDQZ3Px8+bOz4Ll0kBKYh+zkvz/iYqM/PDTluX321zLlGI43079JQobcAH34oittG+3nFiobLWwbz/QwSIdBQDhiwtoHyB8Q2WqOBUjLBN+SkDfDxx2KIGplIfv9dvAkNOVj27SuqNUYfok8/hRkz6rdNvowYIbvNixYZO/6117zCiVNSUhg8eDA///wzUA+eVhAxCqNewgULJIa1oe/FadMC5gUGZN48CQ/u2bN+2+SJmX52OODSS7kgO7xqc0QlUHzRw7iMPM+JiVKT1EzoXKT07St5M+PGGTv+118l960h+7mqSnJUjaiiOhxHZtw2089z5kj4nFn1z0gwO24PGyaRDA1ReknnzDPF01JjQEPiSPWzUrBpk7F+PhLjdseO8tNoP990k2xQNqThOny45IsanZ/POgtefLF+2+TLpEki6miE338/MvMzGBd/mjev4cftxERYs8b4/Dx2LNx4Y/23y5Phw42P2wDnnisRkQ1F376Sv7x/f8N95hHANlqjwfr1okDZkAYhyKL1k0+M1biaN088YQ0VNgMS2jN0qPFJ8R//kPCjhmT4cAlPWbvW2PEBcstGjx7NokWLOHToUPQ9rSA5yEaFABYvln42k5MWDV59FZ580tix8+bJfdhQ+WXgvu+N3Ivr18Mbb3DDqVv9lIM9ibqK8IgREgZqtGZdbGzDytzHx4uipNHawwcPiqBHQ/ZzWZnUP3z//fDHrl8vE3xDLyCHDzfez3PmiEHTqlX9t0snPl5Ei4yO2w2lhOrJ0KGS02ZknD14UEounXhi/bfLk1dfFc+fmfm5Icdts/PzvHmi1toQWgk6+prKSBvLyvASIGgo/u//4J//NHZsu3YSAt7Q8/P11xtfnx6J+dlMPx+pcdvM/LxwYcOUovMkPl5SOsxqJvzBsI3WaJCbCz/8ABMnNuzn6g+tkfDbefNkJ7whVf9A2rh8uYTFhKKkBFavbviBqHlz+eyrrgp/7PffwyOP+OUAHXPMMdTW1jJ//vz68bQePCg1V7/7Lvyxt98uYaOZmdH7fCOY6Ge1ejVPzh9BTIw8Og0ieJedDUcdZfxZAYbdNtKr7EmzZvIvqiVQPDnrLLmGRgQ6rrtO7sWGZscOyRsN188g0QENpdaqY6Gfj8jiBxr3uH333bIYD0dJiYyhR0K1cu9eY2kT6ekSHdPQtTv1ElaNuZ8b+/ycnS0eNSNe/A8/lHuxIVR5famrA+fcH5Ju3URRvaHn56ws8WI25n5u7OP2qFGy2eAU3QzJvfc2jAq4L5omJZUaonLEkUIp1ej+DRw4UNkYoLZWqQ4dlBo4UKm6uuDH7d2rVJMmSt1xR8O1TefXX5Vq2VKppUtDH/fQQ0qBUgsXNkizAlJREfxvtbVK9emjVMeOSjkcXn8qLS1VMTEx6u9//7v65z//qQBVVVUVvXbp/TxoUOh+rq2N3mea5ddfpf8efTTkYd/fN0eVkaoGslBJnI1SKSlKvfNOA7TxppvkXiwvD35MiH5uNKxcqVRMzJF7ng30syoqapj2BOKmm5SKjVVq3brQx73zjoydDd3PtbVKtW+v1NixoY87kv1slAcfPHLj9k03KRUXF7qfa2uV+u23hmuT72e3bx9+3FZKqRdeCP9M1Qf68/zYY6GP0/t50aKGaZdZjuS47XAo1atX+H5es0apb79tuHZ5Mm+esXG7tlap114Lv16rD4w+z419fl6xQsbtO+9s+M8uKVGqW7cjM5ZYBFikTNiHxg6CE4D1wCbgrgB/14BnnX9fAQzw+FsBsBJYZrRxfyij9c03lbr++tAGT33y9tvSjeFW/QUFSu3b5/r1nXeUyslRStPkZ70aDeGuzc6dYlSfdVY9NiIM55+v1GmnBf/7a6/Jdf7gA6WU//XLyxukxowZo26//XaVlJQU/fYZ6eeTT1bqllui/9lGOeUUpdLTldqzJ+ghOTlKZVDiMlj1fzk5DdC+fftkUA+FTz83OAcOyHMQqp9POEGpzEzZjDoShOvnnTuVSk1VaurUhm2XTlGRUmlpoZ9nnSO18Pntt5DPiVJKqRNPPLL9vGOHUldcEbqfmzRR6uyzG7ZdOkb6WX+ef/65wZrlxVtvGZufjyRTp0pfB2PfviPbz0optWuXUs8/H/zvR3rc1vt52rTgx+jjdmlpw7XLEwPz8xGlqEipyZOV2rYt+DEzZx7ZflZKxuMFC4L/Xe9nj/V2gzJxYuPuZx+ibrQCscBmoCOQACwHevgccxLwrdN4HQb87vG3AqC5mUb9YYzWFSuUatNGqaFDj9zip65OqUsvlZ00X2prlfr9d7+2vfOOeLc8jYZ693ZVV8tAs3+//9/mzlUqL0+pjRvrsQFhePhhuRCvv+7vsdT7edgwpRyOgNcvLu5alZycrq688krVokWL6Levrk6pAQNk537VKu+/1dYq9fLL0pAnnoj+Zxtl7Vql+vWT6+XLvn1Kffut0nD4Gawgxn+DUVur1Jw5gT3TX36p1HnnHdnnOVQ/v/RS4+jn2FjZ6PF9nvftk8VtfPyRf567dAm8SbFsmWwChfN+NQQbN/r3s84XX8hi+EgRqp9LStz9vGnTEWmeUsrUuH1EqKtTqn9/pUaN8v+b/jy/+KJSNTUN3zZf1q0LPD8rJcbC5s0N2x5PHnkkeD9v3Ng4+nnAAImIaqzj9po18jwHitzYt0+pK68MvTHQkGze7N/P+ni9aNGR9bIee2zgflZKqXfflX5+8smGb5eO3s+Bxu1GSH0YrUcDMzx+vxu42+eYF4ELPH5fD7RWf1aj9ZxzlOrZUy5fkyZKzZ9/pFskVFTIwN23r/xr00baePvtSim3dzCQ0VDv3q6nn3ZfL719ffu6J8IjGdqqlFy7Pn2kjW3bKjVhgrxeV6dU587S7t9/V0oFu4YvK0B16jRExcV1qR8P9ty5Yi2PHOl+bcAAdz8PGKDU4cNR/EAL6JNJYaF3Pzut/Fubvd7w954vF1/s7me9fccd1ziMGKXc/QxK9eih1OWXy+tlZbKD2r//ke/ne+6R9v3lL/K73t96u++//0i2Tq6PHqI/fbq7n7t3l/alporxeqS55BJ3P+ttvOiiI90qN3o/6+P2Aw/I61u2yMJI//1IUVGhVO/eyiv0cf587352jttHjPx8pSor5f9PP+0/PzeGcVsppUaM8J6f+/RR6sYbj3CjnHj2sz5uv/KK/G3uXK/5+YjhOW7r4bUffdS4+vnLL93pMbfe6jc/H/HnWSnZwMnJ8Z6fu3VT6p//PMINc+I7P/ftq9SMGfK3adMax/x8993uZ6UxbIiFwKzRaqTqbVvAs8r4DsC3EF6gY9oCuwAFfK9pmgJeVEq9FOhDNE27CrgKoENU60jUAxkZUrPp4oulLmDTpke6RcLGjdCypfv3rl1F7fPUU5k2TbSGKiqCnx61mpOBuOkmkSn/739FgU0nPl5+NmQdwkAkJ4vy7mefiaBDWpq8HhMjSqR5ea5+DnydpLbs5s2LgX6A6CHp+k5REewZMUI+fM8e92s5OdC5s6ufj/h11JUlly0TlSWd4cPh2mvpv6I3KT73YdRVeMPx2mtyrT780FuwYNs27zYfKfR+fvFFb+XYtDQRoeje/cj385QpIumvyyvHxcm1c/YzvXsf0eaRmOj+f1qad79OniwPZlZWgzfLj6eeknF6wQL3azU1UhOzIWt2BkPvZ33cbtZMXs/NFRXN9u2PaPNIToYlS6Rc2siR8lpSkoi6NJZ+zstz/z8ry30veszPR/x5BnjuOXjhBe/5uTG0C9z9rM/P1dVu0arhw6GwsOFFrHzxHLf19UNamtyXjaWfPcVCs7Pd92JjGbdB1hBPPOE/PzdU7d1w+M7P4FbxP+88+Xek+/nhh6Ud69fL3PwnQhNDN8QBmnYOcLxS6grn7xcDQ5RSN3gc8zXwiFJqrvP3H4A7lFKLNU1ro5TaqWlaC2AmcINS6udQnzlo0CC1yGhdLhtD5OaKERWKnBxj5Q3/1wl8LauAVKAWGAf84PqLfV29mTZNxPW2bZM6p1OmRFmF18bGxsbGxsbGplGjadpipdQgo8cbKXmzA/DcTm0H7DR6jFJK/7kH+BQYYrRxNtEjnBe1wb1df2CmTMGvfqemJQJ6MW7v2oH16sH+AzJpkhjxDof8tA1WGxsbGxsbGxubUBgxWhcCXTRNy9M0LQE4H/jC55gvgEs0YRhQqpTapWlaE03T0gA0TWsCHAesimL7bQwSKuK6XmpO/omZNEkizzxrrEvAwgDnb95hSo092t3GxsbGxsbGxsamMRPWaFVK1QJ/BWYAa4EPlVKrNU27RtO0a5yHfQPkIyVvXgauc77eEpiradpyYAHwtVLquyh/BxsDBPIOpqTAO+/Y3i4rfPONbqh6ohutbk+r7cG2sbGxsbGxsbGxiQxDGbpKqW8Qw9TztRc8/q+A6wOclw/0jbCNNlFAN0rtXMLoEEqMKT09nfJy+xrb2NjY2NjY2NjYRIM/l6yUTUgmTbINqGjRoUMgMaa+xMRk8swznbj00iPRKhsbGxsbGxsbG5s/H0ZyWm1sbHwIHG6dyksvbWfy5MlHplE2NjY2NjY2NjY2f0Jso9XGxgKTJol4VU6OCDLpYlaXX55KTIz9WNnY2NjY2NjY2NhECzs82MbGIna4tY2NjY2NjY2NjU39Y7uEbGxsbGxsbGxsbGxsbBotttFqY2NjY2NjY2NjY2Nj02ixjVYbGxsbGxsbGxsbGxubRotttNrY2NjY2NjY2NjY2Ng0Wmyj1cbGxsbGxsbGxsbGxqbRYhutNjYRMm0a5OZCTIz8nDbtSLfIxsbGxsbGxsbG5s+DXfLGxiYCpk2Dq66Cigr5fetW+R3scjg2NjY2NjY2NjY20cD2tNrYRMC997oNVp2KCnndxsbGxsbGxsbGxiZybKPVxiYCtm0z97qNjY2NjY2NjY2NjTlso9XGJgI6dDD3uo2NjY2NjY2NjY2NOWyj1cYmAqZMgZQU79dSUuR1GxsbGxsbGxsbG5vIsY1WG5sImDQJXnoJcnJA0+TnSy/ZIkw2NjY2NjY2NjY20cJWD7axiZBJk2wj1cbGxsbGxsbGxqa+sD2tNjY2NjY2NjY2NjY2No0W22i1sbGxsbGxsbGxsbGxabTYRquNjY2NjY2NjY2NjY1No8U2Wm1sbGxsbGxsbGxsbGwaLbbRamNjY2NjY2NjY2NjY9No0ZRSR7oNfmiaVgxsPdLtCEFzYO+RboSNTRjs+9SmsWPfozaNHfsetfkjYN+nNo2dQPdojlIq2+gbNEqjtbGjadoipdSgI90OG5tQ2PepTWPHvkdtGjv2PWrzR8C+T20aO9G4R+3wYBsbGxsbGxsbGxsbG5tGi2202tjY2NjY2NjY2NjY2DRabKPVGi8d6QbY2BjAvk9tGjv2PWrT2LHvUZs/AvZ9atPYifgetXNabWxsbGxsbGxsbGxsbBottqfVxsbGxsbGxsbGxsbGptFiG602NjY2NjY2NjY2NjY2jRbbaDWJpmknaJq2XtO0TZqm3XWk22Pzv4mmaa9pmrZH07RVHq811TRtpqZpG50/szz+drfznl2vadrxR6bVNv9LaJrWXtO0HzVNW6tp2mpN0250vm7fpzaNBk3TkjRNW6Bp2nLnffqg83X7PrVpVGiaFqtp2lJN075y/m7fozaNCk3TCjRNW6lp2jJN0xY5X4vafWobrSbQNC0WeB44EegBXKBpWo8j2yqb/1HeAE7wee0u4AelVBfgB+fvOO/R84GeznP+47yXbWzqk1rgVqVUd2AYcL3zXrTvU5vGRBUwTinVF+gHnKBp2jDs+9Sm8XEjsNbjd/setWmMjFVK9fOoyRq1+9Q2Ws0xBNiklMpXSlUD7wOnHeE22fwPopT6Gdjv8/JpwJvO/78JnO7x+vtKqSql1BZgE3Iv29jUG0qpXUqpJc7/lyOLrbbY96lNI0IJB52/xjv/Kez71KYRoWlaO+Bk4BWPl+171OaPQNTuU9toNUdbYLvH7zucr9nYNAZaKqV2gRgMQAvn6/Z9a3NE0TQtF+gP/I59n9o0Mpxhl8uAPcBMpZR9n9o0Np4B7gAcHq/Z96hNY0MB32uatljTtKucr0XtPo2LcmP/7GgBXrNrBtk0duz71uaIoWlaKvAxcJNSqkzTAt2OcmiA1+z71KbeUUrVAf00TcsEPtU0rVeIw+371KZB0TRtIrBHKbVY07QxRk4J8Jp9j9o0BCOUUjs1TWsBzNQ0bV2IY03fp7an1Rw7gPYev7cDdh6httjY+FKkaVprAOfPPc7X7fvW5oigaVo8YrBOU0p94nzZvk9tGiVKqQPAT0h+lX2f2jQWRgCnappWgKSljdM07R3se9SmkaGU2un8uQf4FAn3jdp9ahut5lgIdNE0LU/TtAQkgfiLI9wmGxudL4DJzv9PBj73eP18TdMSNU3LA7oAC45A+2z+h9DEpfoqsFYp9ZTHn+z71KbRoGlattPDiqZpycB4YB32fWrTSFBK3a2UaqeUykXWnbOVUhdh36M2jQhN05pompam/x84DlhFFO9TOzzYBEqpWk3T/grMAGKB15RSq49ws2z+B9E07T1gDNBc07QdwP3Ao8CHmqZdDmwDzgFQSq3WNO1DYA2i6Hq9MxzOxqY+GQFcDKx05gsC3IN9n9o0LloDbzpVK2OAD5VSX2ma9hv2fWrTuLHHUpvGREskvQLEvnxXKfWdpmkLidJ9qillh7nb2NjY2NjY2NjY2NjYNE7s8GAbGxsbGxsbGxsbGxubRotttNrY2NjY2NjY2NjY2Ng0Wmyj1cbGxsbGxsbGxsbGxqbRYhutNjY2NjY2NjY2NjY2/99+HQsAAAAADPK3nsaOsogtaQUAAGBLWgEAANiSVgAAALYC5aJLgNv1HO4AAAAASUVORK5CYII=\n",
359       "text/plain": [
360        "<Figure size 1152x288 with 1 Axes>"
361       ]
362      },
363      "metadata": {
364       "needs_background": "light"
365      },
366      "output_type": "display_data"
367     }
368    ],
369    "source": [
370     "DeltaE = 0.0          # bias\n",
371     "E, P = kf_example(DeltaE)"
372    ]
373   },
374   {
375    "cell_type": "code",
376    "execution_count": 7,
377    "metadata": {},
378    "outputs": [
379     {
380      "name": "stderr",
381      "output_type": "stream",
382      "text": [
383       "ERROR:root:No traceback has been produced, nothing to debug.\n"
384      ]
385     }
386    ],
387    "source": [
388     "%debug"
389    ]
390   },
391   {
392    "cell_type": "markdown",
393    "metadata": {
394     "id": "vqyB2Yz3uCsD"
395    },
396    "source": [
397     "We have recovered the fuel moisture from data with random noise - we **filtered** the noise out. "
398    ]
399   },
400   {
401    "cell_type": "code",
402    "execution_count": 8,
403    "metadata": {},
404    "outputs": [
405     {
406      "data": {
407       "text/plain": [
408        "[<matplotlib.lines.Line2D at 0x7f91a893ea10>]"
409       ]
410      },
411      "execution_count": 8,
412      "metadata": {},
413      "output_type": "execute_result"
414     },
415     {
416      "data": {
417       "image/png": "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\n",
418       "text/plain": [
419        "<Figure size 432x288 with 1 Axes>"
420       ]
421      },
422      "metadata": {
423       "needs_background": "light"
424      },
425      "output_type": "display_data"
426     }
427    ],
428    "source": [
429     "%matplotlib inline\n",
430     "plt.figure() # new figure\n",
431     "plt.plot(P,linestyle='-',c='b',label='Estimated state variance P')"
432    ]
433   },
434   {
435    "cell_type": "markdown",
436    "metadata": {
437     "id": "Ccr-uKbmAlBE"
438    },
439    "source": [
440     "Now what if the model is wrong - different from nature? That is always so in reality. Now suppose that the model and the truth are not the same. That is always the case in reality.  Consider a simple case when the model thinks that the equilibrium $E$ is too high."
441    ]
442   },
443   {
444    "cell_type": "code",
445    "execution_count": 9,
446    "metadata": {
447     "id": "spMdGW8oAlBE"
448    },
449    "outputs": [
450     {
451      "name": "stdout",
452      "output_type": "stream",
453      "text": [
454       "480 480\n"
455      ]
456     },
457     {
458      "data": {
459 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\n",
460       "text/plain": [
461        "<Figure size 1152x288 with 1 Axes>"
462       ]
463      },
464      "metadata": {
465       "needs_background": "light"
466      },
467      "output_type": "display_data"
468     }
469    ],
470    "source": [
471     "DeltaE = -0.05\n",
472     "E, P = kf_example(DeltaE)  "
473    ]
474   },
475   {
476    "cell_type": "markdown",
477    "metadata": {
478     "id": "DQeF7J8T4j2i"
479    },
480    "source": [
481     "We have found a good estimate of the state $m$, while data is available. Also, the estimated state variance $P$ converges with time - we have *learned* the variance that balances the noise. But for forecasting fuel moisture, we need to continue the fuel moisture model into the future, and we can't have any measurements from future. We only have the equilibrium from weather forecast. And the forecast and the truth disagree - as soon as there is no data to attract the simulation, the model is doing its own thing."
482    ]
483   },
484   {
485    "cell_type": "markdown",
486    "metadata": {
487     "id": "6uXVJj9koGF2"
488    },
489    "source": [
490     "## Real data"
491    ]
492   },
493   {
494    "cell_type": "markdown",
495    "metadata": {},
496    "source": [
497     "### Fuel moisture RAWS data"
498    ]
499   },
500   {
501    "cell_type": "markdown",
502    "metadata": {},
503    "source": [
504     "Try to load the data from a saved file first. If that fails, retrieve the fuel moisture data from sensors on weather stations in the Mesowest network. Get all stations with fuel moisture data in a spatial box within one hour, then pick one station and retrieve the whole time series."
505    ]
506   },
507   {
508    "cell_type": "code",
509    "execution_count": 10,
510    "metadata": {},
511    "outputs": [
512     {
513      "name": "stdout",
514      "output_type": "stream",
515      "text": [
516       "File â€˜raws.json’ already there; not retrieving.\n",
517       "\n",
518       "loaded from  raws.json\n"
519      ]
520     }
521    ],
522    "source": [
523     "import json\n",
524     "jfile = 'raws.json'\n",
525     "try:\n",
526     "    ! wget --no-clobber https://raw.githubusercontent.com/janmandel/notebooks/main/raws.json\n",
527     "    j = json.load(open(jfile,'r'))\n",
528     "    print('loaded from ',jfile)\n",
529     "    # Take the first station in the boulding box that has data between time_start and time_s2.\n",
530     "    # Then retrieve data for that station between time_start and time_end\n",
531     "    time_start = j['time_start']      # start of data time series\n",
532     "    # time_s2    = j['time_s2']         # end of segment to read coordinates\n",
533     "    time_end  = j['time_end']         # end of data time series\n",
534     "    meso_ts  = j['meso_ts']           # get meso observations time series\n",
535     "    obs_lon =   j['obs_lon']          # where we retrieved observations\n",
536     "    obs_lat =   j['obs_lat']\n",
537     "except:\n",
538     "    print(\"can't read\",jfile,', creating')\n",
539     "    # set up bounds\n",
540     "    time_start = \"201806010800\"  # June 1 2018 08:00 in format yyyymmddHHMM\n",
541     "    time_s2    = \"201806010900\"  # June 1 2018 09:00 in format yyyymmddHHMM \n",
542     "    time_end   = \"201906200900\"  # Nov 1 2018 09:00 in format yyyymmddHHMM \n",
543     "    #time_start=  \"201810230100\"\n",
544     "    #time_s2=  \"201810230300\"\n",
545     "    #time_end  =  \"201806022300\"\n",
546     "    !pip install MesoPy\n",
547     "    from MesoPy import Meso\n",
548     "    bounding_box = \"-115, 38, -110, 40\"  # min longtitude, latitude\n",
549     "    meso_token=\"b40cb52cbdef43ef81329b84e8fd874f\"       # you should get your own if you do more of this\n",
550     "    m = Meso(meso_token)# create a Meso object\n",
551     "    print('reading MesoWest fuel moisture data from',)\n",
552     "    meso_obss = m.timeseries(time_start, time_s2, bbox=bounding_box, \n",
553     "                             showemptystations = '0', vars='fuel_moisture')   # ask the object for data\n",
554     "    # pick one station and retrieve the whole time series.\n",
555     "    station=meso_obss['STATION'][0]\n",
556     "    #print(json.dumps(station, indent=4))\n",
557     "    lon,lat = (float(station['LONGITUDE']),float(station['LATITUDE']))\n",
558     "    print(station['NAME'],'station',station['STID'],'at',lon,lat)\n",
559     "    e = 0.01   # tolerance\n",
560     "    bb = '%s, %s, %s, %s' % (lon - e, lat - e, lon + e, lat + e)\n",
561     "    print('bounding box',bb)\n",
562     "    meso_ts = m.timeseries(time_start, time_end, bbox=bb, showemptystations = '0', vars='fuel_moisture')   # ask the object for data\n",
563     "    obs_lon, obs_lat = (lon, lat)   # remember station coordinates for later\n",
564     "    j={'time_start':time_start,'time_s2':time_s2,'time_end':time_end,\n",
565     "       'meso_ts':meso_ts,'obs_lon':obs_lon,'obs_lat':obs_lat}\n",
566     "    json.dump(j,open(jfile,'w'),indent=4)\n",
567     "    print('done')"
568    ]
569   },
570   {
571    "cell_type": "code",
572    "execution_count": 11,
573    "metadata": {
574     "id": "3bXopS3btyz0",
575     "scrolled": true
576    },
577    "outputs": [
578     {
579      "data": {
580       "text/plain": [
581        "Text(0.5, 1.0, 'BKCU1 10 h fuel moisture data')"
582       ]
583      },
584      "execution_count": 11,
585      "metadata": {},
586      "output_type": "execute_result"
587     },
588     {
589      "data": {
590 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\n",
591       "text/plain": [
592        "<Figure size 1152x288 with 1 Axes>"
593       ]
594      },
595      "metadata": {
596       "needs_background": "light"
597      },
598      "output_type": "display_data"
599     }
600    ],
601    "source": [
602     "# process the data retrieved for this station\n",
603     "# print(json.dumps(meso_ts['STATION'][0], indent=4))\n",
604     "from datetime import datetime, timedelta, time\n",
605     "import numpy as np\n",
606     "import matplotlib.pyplot as plt\n",
607     "import pytz\n",
608     "station = meso_ts['STATION'][0]\n",
609     "time_str  = station['OBSERVATIONS']['date_time']\n",
610     "obs_time = [datetime.strptime(t, '%Y-%m-%dT%H:%M:%SZ').replace(tzinfo=pytz.UTC) for t in time_str]\n",
611     "start_time = obs_time[0].replace(minute=0)     # remember obs_time and start_time for later\n",
612     "end_time = obs_time[-1]\n",
613     "obs_data = np.array(station['OBSERVATIONS'][\"fuel_moisture_set_1\"])\n",
614     "# display the data retrieved\n",
615     "#for o_time,o_data in zip (obs_time,obs_data):\n",
616     "#    print(o_time,o_data)\n",
617     "%matplotlib inline\n",
618     "plt.figure(figsize=(16,4))\n",
619     "plt.plot(obs_data,linestyle='-',c='k',label='10-h fuel data')\n",
620     "plt.title(station['STID'] + ' 10 h fuel moisture data')"
621    ]
622   },
623   {
624    "cell_type": "markdown",
625    "metadata": {
626     "id": "pY4hPeATK9wZ"
627    },
628    "source": [
629     "## Retrieve weather analysis for the duration of the station data, from our RTMA stash."
630    ]
631   },
632   {
633    "cell_type": "markdown",
634    "metadata": {
635     "id": "dQ-uJI2sy6I3"
636    },
637    "source": [
638     "Create a function to transfer RTMA files in GRIB2 format from the stash. The function returns zero if the file transfer succeeded. If the file is not available, it returns a nonzero value. Note: if needed, maybe in future add more sophisticated checks, check the return code of wget and if the file size is correct."
639    ]
640   },
641   {
642    "cell_type": "code",
643    "execution_count": 12,
644    "metadata": {
645     "id": "mxZABVDxt0gd"
646    },
647    "outputs": [],
648    "source": [
649     "import subprocess,os\n",
650     "def load_rtma(path,file,reload=0):\n",
651     "  url='http://math.ucdenver.edu/~jmandel/rtma/' + path \n",
652     "  if os.path.exists(file):\n",
653     "    if reload:\n",
654     "      print(file + ' already exists, removing')\n",
655     "      os.remove(file)\n",
656     "    else:\n",
657     "      print(file + ' already exists, exiting')\n",
658     "      # add checking size here\n",
659     "      return 0\n",
660     "  try:\n",
661     "    ret = subprocess.check_output(['wget','--no-clobber','--output-document='+ file, url,],stderr=subprocess.STDOUT).decode() # execute command from python strings\n",
662     "    if os.path.exists(file):\n",
663     "      print('loaded ' + url + ' as ' + file)\n",
664     "      return 0\n",
665     "    else: \n",
666     "      print('file transfer completed, but the file is missing? ' + url)  \n",
667     "      return 1\n",
668     "  except:\n",
669     "    print('file transfer failed: ' + url)\n",
670     "    return 2\n"
671    ]
672   },
673   {
674    "cell_type": "markdown",
675    "metadata": {
676     "id": "THI6gElyHOOc"
677    },
678    "source": [
679     "Next, functions to get the files, open as grib, and interpolate to the station coordinates"
680    ]
681   },
682   {
683    "cell_type": "code",
684    "execution_count": 13,
685    "metadata": {
686     "id": "PL3gxK67AlBI"
687    },
688    "outputs": [],
689    "source": [
690     "def rtma_grib(t,var):\n",
691     "    tpath = '%4i%02i%02i/%02i' % (t.year, t.month, t.day, t.hour)  # remote path on server\n",
692     "    tstr  = '%4i%02i%02i%02i_' % (t.year, t.month, t.day, t.hour)  # time string for local path\n",
693     "    gribfile = os.path.join('data',tstr + var + '.grib')\n",
694     "    remote = tpath + '/' + var + '.grib'\n",
695     "    if load_rtma(remote,gribfile):\n",
696     "        print('cannot load remote file',remote,'as',gribfile)\n",
697     "        return []\n",
698     "    else:\n",
699     "        try:\n",
700     "            gf=GribFile(gribfile)\n",
701     "            v = np.array(gf[1].values())\n",
702     "        except:\n",
703     "            print('cannot read grib file',gribfile)\n",
704     "            return []\n",
705     "        print('loaded ',gribfile,' containing array shape ',v.shape)\n",
706     "        return gf[1]   # grib message\n"
707    ]
708   },
709   {
710    "cell_type": "code",
711    "execution_count": 14,
712    "metadata": {
713     "id": "ccp10kurAlBI"
714    },
715    "outputs": [],
716    "source": [
717     "from scipy.interpolate import LinearNDInterpolator, interpn\n",
718     "from scipy.optimize import root\n",
719     "def interp_to_lat_lon_slow(lats,lons,v,lat,lon): \n",
720     "    # on mesh with coordinates lats and lons interpolate v to given lat lon\n",
721     "    interp=LinearNDInterpolator(list(zip(lats.flatten(),lons.flatten())),v.flatten())\n",
722     "    return interp(lat,lon)\n",
723     "def interp_to_lat_lon(lats,lons,v,lat,lon):\n",
724     "    # on mesh with coordinates lats and lons interpolate v to given lat lon\n",
725     "    points=(np.array(range(lats.shape[0]),float),np.array(range(lats.shape[1]),float))  # uniform mesh\n",
726     "    def res(ij):  # interpolation of lons lats on the uniform mesh, to noninteger coordinates   \n",
727     "       return np.hstack((interpn(points,lats,ij)-lat, interpn(points,lons,ij)-lon))\n",
728     "    # solve for xi,xj such that lats(xi,xj)=lat lons(xi,xj)=lon, then interpolate to (xi, xj) on uniform grid \n",
729     "    result = root(res,(0,0)) # solve res(ij) = 0\n",
730     "    if not result.success:\n",
731     "        print(result.message)\n",
732     "        exit(1)\n",
733     "    return interpn(points,v,result.x) \n"
734    ]
735   },
736   {
737    "cell_type": "markdown",
738    "metadata": {
739     "id": "jvnpq6S5AlBI"
740    },
741    "source": [
742     "The interpolation function needs to  be tested."
743    ]
744   },
745   {
746    "cell_type": "code",
747    "execution_count": 15,
748    "metadata": {
749     "id": "NVMJBYI7AlBI"
750    },
751    "outputs": [],
752    "source": [
753     "def interp_to_lat_lon_test(lats,lons):\n",
754     "    print('testing interp_to_lat_lon')\n",
755     "    vx, vy = np.meshgrid(range(lats.shape[0]),range(lats.shape[1]),indexing='ij')\n",
756     "    i, j = (1,2)\n",
757     "    lat,lon = ((lats[i,j]+lats[i+1,j+1])/2,(lons[i,j]+lons[i+1,j+1])/2)\n",
758     "    vi = interp_to_lat_lon(lats,lons,vx,lat,lon)\n",
759     "    vj = interp_to_lat_lon(lats,lons,vy,lat,lon)\n",
760     "    print(vi,vj,'should be about',i+0.5,j+0.5)\n",
761     "    test_slow = 0\n",
762     "    if test_slow:\n",
763     "        print('Testing against the standard slow method scipy.interpolate.LinearNDInterpolator. Please wait...')\n",
764     "        vi_slow = interp_to_lat_lon_slow(lats,lons,vx,lat,lon)\n",
765     "        print(vi_slow)\n",
766     "        vj_slow = interp_to_lat_lon_slow(lats,lons,vy,lat,lon)\n",
767     "        print(vj_slow)\n",
768     "        \n",
769     "#gf = rtma_grib(start_time,'temp')      #  read the first grib file and use it to test interpolation\n",
770     "#lats, lons = gf.latlons()\n",
771     "#interp_to_lat_lon_test(lats,lons)\n"
772    ]
773   },
774   {
775    "cell_type": "code",
776    "execution_count": 16,
777    "metadata": {},
778    "outputs": [],
779    "source": [
780     "#%debug\n"
781    ]
782   },
783   {
784    "cell_type": "markdown",
785    "metadata": {
786     "id": "LQbWB_3GAlBI"
787    },
788    "source": [
789     "Now we are ready for a function to read the RTMA files and interpolate to the station coordinates"
790    ]
791   },
792   {
793    "cell_type": "code",
794    "execution_count": 17,
795    "metadata": {
796     "id": "b3JJH3XPAlBI"
797    },
798    "outputs": [],
799    "source": [
800     "import pandas as pd, json\n",
801     "def read_interp_rtma(varnames,times,lat,lon):\n",
802     "    # read RTMA from start_time to end_time and interpolate to obs_lat obs_lon\n",
803     "    ntimes = len(times)\n",
804     "    time_str = 'time_str'\n",
805     "    j={time_str:times.strftime('%Y-%m-%d %H:%M').tolist()}\n",
806     "    for varname in varnames:\n",
807     "        j[varname]=np.full(ntimes,np.nan)  # initialize array of nans as list\n",
808     "    n=0\n",
809     "    for t in times:\n",
810     "        tim=t.strftime('%Y-%m-%d %H:%M')\n",
811     "        should_be = j[time_str][n]\n",
812     "        if tim != should_be:\n",
813     "            print('n=',n,'time',tim,'expected',should_be)\n",
814     "            raise 'Invalid time' \n",
815     "        for varname in varnames:\n",
816     "            gf = rtma_grib(t,varname)   # read and create grib object, download if needed\n",
817     "            if gf:\n",
818     "                lats,lons = gf.latlons()    # coordinates\n",
819     "                v = gf.values()\n",
820     "                vi=interp_to_lat_lon(lats,lons,v,lat,lon) # append to array\n",
821     "                print(varname,'at',t,'interpolated to',lat,lon,' value ',vi)\n",
822     "                j[varname][n] = vi\n",
823     "            else:\n",
824     "                print(varname,'at',t,' could not be loaded')\n",
825     "        n = n+1\n",
826     "    return j"
827    ]
828   },
829   {
830    "cell_type": "code",
831    "execution_count": 18,
832    "metadata": {},
833    "outputs": [
834     {
835      "name": "stdout",
836      "output_type": "stream",
837      "text": [
838       "loaded from  rtma.json\n"
839      ]
840     }
841    ],
842    "source": [
843     "import json\n",
844     "jfile = 'rtma.json'\n",
845     "try:\n",
846     "    j = json.load(open(jfile,'r'))\n",
847     "    print('loaded from ',jfile)\n",
848     "    if j['obs_lat']!=obs_lat or j['obs_lon']!=obs_lon:\n",
849     "        raise 'Wrong lon lat'\n",
850     "except:\n",
851     "    print(\"can't read\",jfile,', creating')\n",
852     "    # Set up environment to read RTMA gribs\n",
853     "    # we will need current numpy for pygrib - needed on Colab, tensorflow is using numpy 1.19\\\n",
854     "    times = pd.date_range(start=time_start,end=time_end,freq='1H')\n",
855     "    varnames=['temp','td','precipa']\n",
856     "    j =    read_interp_rtma(varnames,times,obs_lat,obs_lon)      # temperature\n",
857     "    for varname in varnames:\n",
858     "        j[varname]=j[varname].tolist() \n",
859     "    j['obs_lat']=obs_lat\n",
860     "    j['obs_lon']=obs_lon\n",
861     "    json.dump(j,open('rtma.json','w'),indent=4)\n",
862     "    print('done')"
863    ]
864   },
865   {
866    "cell_type": "code",
867    "execution_count": 19,
868    "metadata": {},
869    "outputs": [],
870    "source": [
871     "# %debug\n"
872    ]
873   },
874   {
875    "cell_type": "code",
876    "execution_count": 20,
877    "metadata": {},
878    "outputs": [],
879    "source": [
880     "rtma = j\n",
881     "td = np.array(rtma['td'])\n",
882     "t2 = np.array(rtma['temp'])\n",
883     "rain=np.array(rtma['precipa'])\n",
884     "# compute relative humidity\n",
885     "rh = 100*np.exp(17.625*243.04*(td - t2) / (243.04 + t2 - 273.15) / (243.0 + td - 273.15))\n",
886     "Ed = 0.924*rh**0.679 + 0.000499*np.exp(0.1*rh) + 0.18*(21.1 + 273.15 - t2)*(1 - np.exp(-0.115*rh))\n",
887     "Ew = 0.618*rh**0.753 + 0.000454*np.exp(0.1*rh) + 0.18*(21.1 + 273.15 - t2)*(1 - np.exp(-0.115*rh))"
888    ]
889   },
890   {
891    "cell_type": "code",
892    "execution_count": 21,
893    "metadata": {
894     "id": "tZIK59bJAlBJ"
895    },
896    "outputs": [
897     {
898      "data": {
899       "text/plain": [
900        "Text(0.5, 1.0, 'BKCU1 Temperature (K)')"
901       ]
902      },
903      "execution_count": 21,
904      "metadata": {},
905      "output_type": "execute_result"
906     },
907     {
908      "data": {
909 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\n",
910       "text/plain": [
911        "<Figure size 1152x288 with 1 Axes>"
912       ]
913      },
914      "metadata": {
915       "needs_background": "light"
916      },
917      "output_type": "display_data"
918     }
919    ],
920    "source": [
921     "%matplotlib inline\n",
922     "plt.figure(figsize=(16,4))\n",
923     "plt.plot(t2,linestyle='-',c='k',label='Temperature')\n",
924     "plt.title(station['STID'] + ' Temperature (K)')"
925    ]
926   },
927   {
928    "cell_type": "code",
929    "execution_count": 22,
930    "metadata": {
931     "id": "LbyqcuXYAlBJ"
932    },
933    "outputs": [
934     {
935      "data": {
936       "text/plain": [
937        "Text(0.5, 1.0, 'BKCU1 Dew point (K)')"
938       ]
939      },
940      "execution_count": 22,
941      "metadata": {},
942      "output_type": "execute_result"
943     },
944     {
945      "data": {
946 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\n",
947       "text/plain": [
948        "<Figure size 1152x288 with 1 Axes>"
949       ]
950      },
951      "metadata": {
952       "needs_background": "light"
953      },
954      "output_type": "display_data"
955     }
956    ],
957    "source": [
958     "%matplotlib inline\n",
959     "plt.figure(figsize=(16,4))\n",
960     "plt.plot(td,linestyle='-',c='k',label='Dew point')\n",
961     "plt.title(station['STID'] + ' Dew point (K)')"
962    ]
963   },
964   {
965    "cell_type": "code",
966    "execution_count": 23,
967    "metadata": {},
968    "outputs": [
969     {
970      "data": {
971       "text/plain": [
972        "Text(0.5, 1.0, 'BKCU1 relative humidity (%)')"
973       ]
974      },
975      "execution_count": 23,
976      "metadata": {},
977      "output_type": "execute_result"
978     },
979     {
980      "data": {
981 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\n",
982       "text/plain": [
983        "<Figure size 1152x288 with 1 Axes>"
984       ]
985      },
986      "metadata": {
987       "needs_background": "light"
988      },
989      "output_type": "display_data"
990     }
991    ],
992    "source": [
993     "%matplotlib inline\n",
994     "plt.figure(figsize=(16,4))\n",
995     "plt.plot(rh,linestyle='-',c='k',label='Dew point')\n",
996     "plt.title(station['STID'] + ' relative humidity (%)')"
997    ]
998   },
999   {
1000    "cell_type": "code",
1001    "execution_count": 24,
1002    "metadata": {},
1003    "outputs": [
1004     {
1005      "data": {
1006       "text/plain": [
1007        "Text(0.5, 1.0, 'BKCU1 drying and wetting equilibria (%)')"
1008       ]
1009      },
1010      "execution_count": 24,
1011      "metadata": {},
1012      "output_type": "execute_result"
1013     },
1014     {
1015      "data": {
1016       "image/png": "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\n",
1017       "text/plain": [
1018        "<Figure size 1152x288 with 1 Axes>"
1019       ]
1020      },
1021      "metadata": {
1022       "needs_background": "light"
1023      },
1024      "output_type": "display_data"
1025     }
1026    ],
1027    "source": [
1028     "%matplotlib inline\n",
1029     "plt.figure(figsize=(16,4))\n",
1030     "plt.plot(Ed,linestyle='-',c='r',label='drying equilibrium')\n",
1031     "plt.plot(Ew,linestyle=':',c='b',label='wetting equilibrium')\n",
1032     "plt.title(station['STID'] + ' drying and wetting equilibria (%)')"
1033    ]
1034   },
1035   {
1036    "cell_type": "markdown",
1037    "metadata": {},
1038    "source": [
1039     " "
1040    ]
1041   },
1042   {
1043    "cell_type": "code",
1044    "execution_count": 25,
1045    "metadata": {
1046     "id": "PQKSRvRSAlBJ"
1047    },
1048    "outputs": [
1049     {
1050      "data": {
1051       "text/plain": [
1052        "Text(0.5, 1.0, 'BKCU1 Precipitation')"
1053       ]
1054      },
1055      "execution_count": 25,
1056      "metadata": {},
1057      "output_type": "execute_result"
1058     },
1059     {
1060      "data": {
1061       "image/png": "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\n",
1062       "text/plain": [
1063        "<Figure size 1152x288 with 1 Axes>"
1064       ]
1065      },
1066      "metadata": {
1067       "needs_background": "light"
1068      },
1069      "output_type": "display_data"
1070     }
1071    ],
1072    "source": [
1073     "%matplotlib inline\n",
1074     "plt.figure(figsize=(16,4))\n",
1075     "plt.plot(rain,linestyle='-',c='k',label='Precipitation')\n",
1076     "plt.title(station['STID'] + ' Precipitation' )"
1077    ]
1078   },
1079   {
1080    "cell_type": "code",
1081    "execution_count": 26,
1082    "metadata": {
1083     "id": "Dwbt4UXfro5x"
1084    },
1085    "outputs": [
1086     {
1087      "name": "stdout",
1088      "output_type": "stream",
1089      "text": [
1090       "[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1091       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1092       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1093       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1094       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1095       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1096       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1097       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1098       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1099       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1100       " 0.00000000e+00 0.00000000e+00            nan 9.99900000e+03\n",
1101       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1102       " 2.11780963e-01 3.37612349e+00 7.65368785e-01 1.46232200e+01\n",
1103       " 0.00000000e+00 3.63216038e-01 5.35815321e-03 0.00000000e+00\n",
1104       " 5.81764222e-01 1.18612397e+01 2.05358153e-01 5.35815321e-03\n",
1105       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1106       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1107       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1108       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1109       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1110       " 1.07163064e-02 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1111       " 0.00000000e+00 0.00000000e+00 7.32178060e-02 5.35815321e-04\n",
1112       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1113       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
1114       " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n"
1115      ]
1116     }
1117    ],
1118    "source": [
1119     "print(rain[1900:2000])"
1120    ]
1121   },
1122   {
1123    "cell_type": "markdown",
1124    "metadata": {
1125     "id": "_yRu_7WvHc6P"
1126    },
1127    "source": [
1128     "Precipitation from RTMA is in kg/m${}^2$. 1m water depth over 1m${}^2$ is 1m${}^3$ with mass 1000 kg thus 1 kg/m${}^2$ is the same as 1 mm of precipitation. RTMA values are accumulations over 1 h so these are values in mm/h. So 9999 mm/h = 10m/h makes no sense. Replace anything over 1m/h by nan and try again."
1129    ]
1130   },
1131   {
1132    "cell_type": "code",
1133    "execution_count": 27,
1134    "metadata": {},
1135    "outputs": [],
1136    "source": [
1137     "rain[rain > 1000] = np.NaN"
1138    ]
1139   },
1140   {
1141    "cell_type": "code",
1142    "execution_count": 28,
1143    "metadata": {
1144     "scrolled": true
1145    },
1146    "outputs": [
1147     {
1148      "data": {
1149       "text/plain": [
1150        "Text(0.5, 1.0, 'BKCU1 Precipitation')"
1151       ]
1152      },
1153      "execution_count": 28,
1154      "metadata": {},
1155      "output_type": "execute_result"
1156     },
1157     {
1158      "data": {
1159       "image/png": "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\n",
1160       "text/plain": [
1161        "<Figure size 1152x288 with 1 Axes>"
1162       ]
1163      },
1164      "metadata": {
1165       "needs_background": "light"
1166      },
1167      "output_type": "display_data"
1168     }
1169    ],
1170    "source": [
1171     "%matplotlib inline\n",
1172     "plt.figure(figsize=(16,4))\n",
1173     "plt.plot(rain,linestyle='-',c='k',label='Precipitation')\n",
1174     "plt.title(station['STID'] + ' Precipitation' )"
1175    ]
1176   },
1177   {
1178    "cell_type": "markdown",
1179    "metadata": {},
1180    "source": [
1181     "Fix some missing data, then we can use the data for up to 1942 hours until a biger gap."
1182    ]
1183   },
1184   {
1185    "cell_type": "code",
1186    "execution_count": 29,
1187    "metadata": {},
1188    "outputs": [
1189     {
1190      "name": "stdout",
1191      "output_type": "stream",
1192      "text": [
1193       "(array([1942, 1943, 3450, ..., 8942, 8943, 8944]),)\n",
1194       "(array([3450, 3451, 3452, ..., 8942, 8943, 8944]),)\n",
1195       "(array([3450, 3451, 3452, ..., 8942, 8943, 8944]),)\n",
1196       "(array([], dtype=int64),)\n"
1197      ]
1198     }
1199    ],
1200    "source": [
1201     "# fix isolated nans\n",
1202     "def fixnan(a,n):\n",
1203     "    for c in range(n):\n",
1204     "        for i in np.where(np.isnan(a)):\n",
1205     "            a[i]=0.5*(a[i-1]+a[i+1])\n",
1206     "        if not any(np.isnan(a)):\n",
1207     "            break\n",
1208     "    return a\n",
1209     "\n",
1210     "rain=fixnan(rain,2)\n",
1211     "t2=fixnan(t2,2)\n",
1212     "rh=fixnan(rh,2)\n",
1213     "obs_data=fixnan(obs_data,2)\n",
1214     "Ed=fixnan(Ed,2)\n",
1215     "Ew=fixnan(Ew,2)\n",
1216     "\n",
1217     "print(np.where(np.isnan(rain)))\n",
1218     "print(np.where(np.isnan(t2)))\n",
1219     "print(np.where(np.isnan(rh)))\n",
1220     "print(np.where(np.isnan(obs_data)))"
1221    ]
1222   },
1223   {
1224    "cell_type": "code",
1225    "execution_count": 30,
1226    "metadata": {
1227     "id": "0SSWIbGCAlBK"
1228    },
1229    "outputs": [],
1230    "source": [
1231     "### Define model function with drying, wetting, and rain equilibria\n",
1232     "\n",
1233     "# Parameters\n",
1234     "r0 = 0.05                                   # threshold rainfall [mm/h]\n",
1235     "rk = 8.0                                    # saturation rain intensity [mm/h]\n",
1236     "Trk = 14.0                                  # time constant for rain wetting model [h]\n",
1237     "S = 2.5                                     # saturation intensity [dimensionless]\n",
1238     "T = 10.0                                    # time constant for wetting/drying\n",
1239     "\n",
1240     "def model_moisture(m0,Eqd,Eqw,r,partials=0):\n",
1241     "    # arguments:\n",
1242     "    # m0         starting fuel moistureb (1)\n",
1243     "    # Eqd        drying equilibrium      (1) \n",
1244     "    # Eqw        wetting equilibrium     (1)\n",
1245     "    # r          rain intensity          (mm/h)\n",
1246     "    # partials = 0, 1, 2\n",
1247     "    # returns: same as model_decay\n",
1248     "    #   if partials==0: m1 = fuel moisture contents after time 1 hour\n",
1249     "    #              ==1: m1, dm0/dm0 \n",
1250     "    #              ==2: m1, dm1/dm0, dm1/dE   \n",
1251     "    \n",
1252     "    if r > r0:\n",
1253     "        E = S\n",
1254     "        T1 = 1.0 / (Trk * (1.0 - np.exp(- (r - r0) / rk)))\n",
1255     "    elif m0 > Eqd:\n",
1256     "        E = Eqd\n",
1257     "        T1 = 1.0/T\n",
1258     "    elif m0 < Eqw:\n",
1259     "        E = Eqw\n",
1260     "        T1 = 1.0/T\n",
1261     "    else:\n",
1262     "        E = m0     # should return m1 = m0, all partials zero\n",
1263     "        T1 = 1.0   # does not matter\n",
1264     "        \n",
1265     "    # model_decay(m0,E,partials=0,T1=0.1,tlen=1):  # T1 = 1/T, partials 0=none, 1=dm0/dm1, 2=dm1/dm0, dm1/dE, dm1/dT1     \n",
1266     "    return model_decay(m0,E,partials=partials,T1=T1,tlen=1)"
1267    ]
1268   },
1269   {
1270    "cell_type": "markdown",
1271    "metadata": {},
1272    "source": [
1273     "# Kalman filter with RAWS observations, followed by forecasting\n",
1274     "We run the model first with Kalman filter for 150 hours. The observations are the RAWS data\n",
1275     "After 150 hours, we run in forecast mode - the RAWS data are no longer used, and we run the model from the weather data without the Kalman filter. The weather data are taken to be RTMA interpolated to one RAWS location.\n",
1276     "In a real forecasting application, the model would be run from weather forecast rather than data."
1277    ]
1278   },
1279   {
1280    "cell_type": "code",
1281    "execution_count": 31,
1282    "metadata": {},
1283    "outputs": [],
1284    "source": [
1285     "# run KF on an initial data seqment\n",
1286     "import numpy as np\n",
1287     "import matplotlib.pyplot as plt \n",
1288     "\n",
1289     "hours=300\n",
1290     "h2 = round(hours/2)\n",
1291     "m = np.zeros(hours) # preallocate\n",
1292     "m[0]= obs_data[0]             # initial state  \n",
1293     "P = np.zeros(hours)\n",
1294     "P[0] = 1e-3 # background state variance\n",
1295     "H = np.array([1.])   # all oQ = np.array([0.02]) # process noise variancebserved\n",
1296     "Q = np.array([1e-3]) # process noise variance\n",
1297     "R = np.array([1e-3]) # data variance\n",
1298     "for t in range(hours-1):\n",
1299     "    # using lambda construction to pass additional arguments to the model \n",
1300     "    if t < h2 and not np.isnan(obs_data[t]) and not np.isnan(Ew[t]) and not np.isnan(rain[t]): # advance model and run KF\n",
1301     "        m[t+1],P[t+1] = ext_kf(m[t],P[t],lambda u: model_moisture(u,Ed[t],Ew[t],rain[t],partials=1),Q,\n",
1302     "                    d=obs_data[t],H=H,R=R)\n",
1303     "    else:  # just advance to next hour\n",
1304     "        m[t+1],P[t+1] = ext_kf(m[t],P[t],lambda u: model_moisture(u,Ed[t],Ew[t],rain[t],partials=1))"
1305    ]
1306   },
1307   {
1308    "cell_type": "code",
1309    "execution_count": 32,
1310    "metadata": {
1311     "scrolled": true
1312    },
1313    "outputs": [
1314     {
1315      "data": {
1316       "text/plain": [
1317        "[<matplotlib.lines.Line2D at 0x7f91d0789910>]"
1318       ]
1319      },
1320      "execution_count": 32,
1321      "metadata": {},
1322      "output_type": "execute_result"
1323     },
1324     {
1325      "data": {
1326 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\n",
1327       "text/plain": [
1328        "<Figure size 1152x288 with 1 Axes>"
1329       ]
1330      },
1331      "metadata": {
1332       "needs_background": "light"
1333      },
1334      "output_type": "display_data"
1335     }
1336    ],
1337    "source": [
1338     "%matplotlib inline\n",
1339     "plt.figure(figsize=(16,4))\n",
1340     "plt.plot(Ed[:hours],linestyle='--',c='r',label='Drying Equilibrium')\n",
1341     "plt.plot(Ew[:hours],linestyle='--',c='b',label='Wetting Equilibrium')\n",
1342     "plt.plot(obs_data[:hours],linestyle=':',c='k',label='RAWS data')\n",
1343     "plt.plot(m[:h2],linestyle='-',c='k',label='filtered')\n",
1344     "plt.plot(range(h2,hours),m[h2:hours],linestyle='-',c='r',label='forecast')"
1345    ]
1346   },
1347   {
1348    "cell_type": "markdown",
1349    "metadata": {},
1350    "source": [
1351     "Let's check the state variance $P$. $P\\to 0$ is a common problem in data assimilation, called filter degeneracy. With increasing cumulative amount of data, the variance of the state decreases and then the filter blindly follows the model. The underlying reason is that we trust that the model is accurate. This can work when nature and the model are the same system of equations, but here the nature is the nature and we need to recognize that the model is not accuratel. We guard against filter degeneracy by adding process noise $Q$ to the model. Ideally, the process noise variance  and the data noise variance should be about the same, then the assimilation will split the difference between the model uncertainly and the data uncertainty."
1352    ]
1353   },
1354   {
1355    "cell_type": "code",
1356    "execution_count": 33,
1357    "metadata": {},
1358    "outputs": [
1359     {
1360      "data": {
1361       "text/plain": [
1362        "[<matplotlib.lines.Line2D at 0x7f91a8be1f10>]"
1363       ]
1364      },
1365      "execution_count": 33,
1366      "metadata": {},
1367      "output_type": "execute_result"
1368     },
1369     {
1370      "data": {
1371 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\n",
1372       "text/plain": [
1373        "<Figure size 432x288 with 1 Axes>"
1374       ]
1375      },
1376      "metadata": {
1377       "needs_background": "light"
1378      },
1379      "output_type": "display_data"
1380     }
1381    ],
1382    "source": [
1383     "%matplotlib inline\n",
1384     "plt.figure() # new figure\n",
1385     "plt.plot(P,linestyle='-',c='b',label='Estimated state variance P')"
1386    ]
1387   },
1388   {
1389    "cell_type": "markdown",
1390    "metadata": {},
1391    "source": [
1392     "Clearly, there is a problem - the forecast fuel moisture is too high. We need to assimilate also some parameters of the model, not just its state. "
1393    ]
1394   },
1395   {
1396    "cell_type": "markdown",
1397    "metadata": {
1398     "id": "jivOYEhiXMi5"
1399    },
1400    "source": [
1401     "## Model with an augmented state\n",
1402     "In reality, the equilibrium moisture $E$ computed from atmospheric conditions\n",
1403     "generally does not agree with the data. We want to add a correction $\\Delta\n",
1404     "E$ to $E$ constant in time, and identify the new parameter $\\Delta E$ from data. \n",
1405     "Because the Kalman filter identifies state, add the parameter to the state.\n",
1406     "Define augmented state $u=\\left[\n",
1407     "\\begin{array}\n",
1408     "[c]{c}\n",
1409     "m\\\\\n",
1410     "\\Delta E\n",
1411     "\\end{array}\n",
1412     "\\right]  .$ Since $\\Delta E$ is constant in time, it satisfies the\n",
1413     "differential equation $\\frac{d\\Delta E}{dt}=0.$ So, we want to estimate the\n",
1414     "state $u$ governed by the\n",
1415     "$$\n",
1416     "\\frac{d}{dt}\\left[\n",
1417     "\\begin{array}\n",
1418     "[c]{c}\n",
1419     "m\\\\\n",
1420     "\\Delta E\n",
1421     "\\end{array}\n",
1422     "\\right]  =\\left[\n",
1423     "\\begin{array}\n",
1424     "[c]{c}\n",
1425     "\\frac{E+\\Delta E-m(t)}{T}\\\\\n",
1426     "0\n",
1427     "\\end{array}\n",
1428     "\\right]  ,\n",
1429     "$$\n",
1430     "which we write as $\\frac{du}{dt}=F(u),$ where\n",
1431     "$$\n",
1432     "F(u)=\\left[\n",
1433     "\\begin{array}\n",
1434     "[c]{c}\n",
1435     "F_{1}\\left(  u\\right)  \\\\\n",
1436     "F_{2}\\left(  u\\right)\n",
1437     "\\end{array}\n",
1438     "\\right]  =F\\left(  \\left[\n",
1439     "\\begin{array}\n",
1440     "[c]{c}\n",
1441     "m\\\\\n",
1442     "\\Delta E\n",
1443     "\\end{array}\n",
1444     "\\right]  \\right)  =\\left[\n",
1445     "\\begin{array}\n",
1446     "[c]{c}\n",
1447     "\\left(  E+\\Delta E-m(t)\\right)  T_{1}\\\\\n",
1448     "0\n",
1449     "\\end{array}\n",
1450     "\\right]  ,\\quad T_{1}=\\frac{1}{T}.\n",
1451     "$$\n",
1452     "The Jacobian of $F$ is\n",
1453     "$$\n",
1454     "\\left[\n",
1455     "\\begin{array}\n",
1456     "[c]{cc}\n",
1457     "\\frac{\\partial F_{1}}{\\partial u_{1}} & \\frac{\\partial F_{1}}{\\partial u_{2}\n",
1458     "}\\\\\n",
1459     "\\frac{\\partial F_{2}}{\\partial u_{1}} & \\frac{\\partial F_{2}}{\\partial u_{2}}\n",
1460     "\\end{array}\n",
1461     "\\right]  =\\left[\n",
1462     "\\begin{array}\n",
1463     "[c]{cc}\n",
1464     "\\frac{\\partial m_{1}}{\\partial m_{0}} & \\frac{\\partial m_{1}}{\\partial E}\\\\\n",
1465     "\\frac{\\partial\\Delta E}{\\partial m_{0}} & \\frac{\\partial\\Delta E}\n",
1466     "{\\partial\\Delta E}\n",
1467     "\\end{array}\n",
1468     "\\right]  =\\left[\n",
1469     "\\begin{array}\n",
1470     "[c]{cc}\n",
1471     "\\frac{\\partial m_{1}}{\\partial m_{0}} & \\frac{\\partial m_{1}}{\\partial E}\\\\\n",
1472     "0 & 1\n",
1473     "\\end{array}\n",
1474     "\\right]\n",
1475     "$$\n",
1476     "Here is a function that implements the augmented model $F$. The input is\n",
1477     "$u_{0}$. The output is $u_{1}$ and the Jacobian $du_{1}/du_{0}$."
1478    ]
1479   },
1480   {
1481    "cell_type": "markdown",
1482    "metadata": {},
1483    "source": [
1484     "### Define augmented model function with drying, wetting, and rain equilibria"
1485    ]
1486   },
1487   {
1488    "cell_type": "code",
1489    "execution_count": 37,
1490    "metadata": {
1491     "id": "GHtAaGp9WSHT"
1492    },
1493    "outputs": [],
1494    "source": [
1495     "def model_augmented(u0,Ed,Ew,r):\n",
1496     "    # state u is the vector [m,dE] with dE correction to equilibria Ed and Ew\n",
1497     "    # \n",
1498     "    m0, dE = u0  # decompose u0\n",
1499     "    # reuse model_moisture(m0,Eqd,Eqw,r,partials=0):\n",
1500     "    # arguments:\n",
1501     "    # m0         starting fuel moistureb (1)\n",
1502     "    # Eqd        drying equilibrium      (1) \n",
1503     "    # Eqw        wetting equilibrium     (1)\n",
1504     "    # r          rain intensity          (mm/h)\n",
1505     "    # partials = 0, 1, 2\n",
1506     "    # returns: same as model_decay\n",
1507     "    #   if partials==0: m1 = fuel moisture contents after time 1 hour\n",
1508     "    #              ==1: m1, dm0/dm0 \n",
1509     "    #              ==2: m1, dm1/dm0, dm1/dE \n",
1510     "    m1, dm1_dm0, dm1_dE  = model_moisture(m0,Ed + dE, Ew + dE, r, partials=2)\n",
1511     "    u1 = np.array([m1,dE])\n",
1512     "    J =  np.array([dm1_dm0, dm1_dE],\n",
1513     "                  [0.     ,     1.])\n",
1514     "    return m0, J"
1515    ]
1516   },
1517   {
1518    "cell_type": "markdown",
1519    "metadata": {
1520     "id": "8SuVNg8TsW4d"
1521    },
1522    "source": [
1523     "### Run the extended Kalman filter on the augmented model"
1524    ]
1525   },
1526   {
1527    "cell_type": "code",
1528    "execution_count": null,
1529    "metadata": {
1530     "id": "1No3g6HyAEh_"
1531    },
1532    "outputs": [],
1533    "source": [
1534     "u = np.zeros((2,2*hours)\n",
1535     "u[:,0]=[0.1,0.1]             # background state  \n",
1536     "P = np.zeros(2,2,2*hours)\n",
1537     "P[:,:,0] = np.array([[0.03, 0.],\n",
1538     "                  [0.,    0.03]]) # background state covariance\n",
1539     "Q = np.array([[0.03, 0.],\n",
1540     "            [0,    0.03]]) # process noise covariance\n",
1541     "H = np.array([[1., 0.],\n",
1542     "             [0.,  .0]])   # first component observed\n",
1543     "R = np.array([0.02]) # data variance\n",
1544     "\n",
1545     "DeltaE = 0.05          # bias\n",
1546     "for t in range(hours):\n",
1547     "  # use lambda construction to pass additional arguments to the model \n",
1548     "  u[:,t+1],P[:,:,t+1] = ext_kf(m[:,t],d2(P[:,:,t]),lambda u: model_decay(u,E[t]+DeltaE,partials=1),Q,\n",
1549     "                    d=data[t],H=H,R=R)\n",
1550     "for t in range(hours,2*hours - 1):\n",
1551     "  u[:,t+1],P[:,:,t+1] = ext_kf(m[t],d2(P[t]),lambda u: model_decay(u,E[t]+DeltaE,partials=1))\n",
1552     "  \n",
1553     "    \n",
1554     "%matplotlib inline\n",
1555     "import matplotlib.pyplot as plt \n",
1556     "plt.figure(figsize=(16,4))\n",
1557     "plt.plot(day,E,linestyle='--',c='r',label='Equilibrium')\n",
1558     "plt.plot(day,m_f,linestyle='-',c='k',label='10-h fuel truth')\n",
1559     "plt.scatter(day[0:hours],data[0:hours],c='b',label='10-h fuel data')\n",
1560     "plt.plot(day,m,linestyle='-',c='r',label='filtered')\n",
1561     "\n",
1562     "\n"
1563    ]
1564   },
1565   {
1566    "cell_type": "code",
1567    "execution_count": null,
1568    "metadata": {
1569     "id": "ESJQ8dWiiork"
1570    },
1571    "outputs": [],
1572    "source": [
1573     "DeltaE"
1574    ]
1575   },
1576   {
1577    "cell_type": "code",
1578    "execution_count": null,
1579    "metadata": {
1580     "id": "CJDcq4QvNhJI"
1581    },
1582    "outputs": [],
1583    "source": [
1584     "d=np.array([])\n",
1585     "if d:\n",
1586     "  print('yes')"
1587    ]
1588   },
1589   {
1590    "cell_type": "code",
1591    "execution_count": null,
1592    "metadata": {
1593     "id": "Y4_pVyy_IOHm"
1594    },
1595    "outputs": [],
1596    "source": [
1597     "for d in range(24):\n",
1598     "  print(d)"
1599    ]
1600   },
1601   {
1602    "cell_type": "markdown",
1603    "metadata": {
1604     "id": "t8tMN3qOx3IP"
1605    },
1606    "source": [
1607     "# With real data"
1608    ]
1609   },
1610   {
1611    "cell_type": "code",
1612    "execution_count": null,
1613    "metadata": {
1614     "id": "2IAGpfAiFtRu"
1615    },
1616    "outputs": [],
1617    "source": [
1618     "! pip install intergrid\n",
1619     "from intergrid.intergrid import Intergrid  # docs https://pypi.org/project/intergrid/\n",
1620     "from datetime import date\n",
1621     "import pandas as pd\n",
1622     "start_date = date(2018,5,19)\n",
1623     "end_date = date(2020,6,1)\n",
1624     "for d in pd.date_range(start_date,end_date,freq=\"1h\"):\n",
1625     "    path = d.strftime(\"%Y%m%d/%H\")\n",
1626     "    print(path)"
1627    ]
1628   },
1629   {
1630    "cell_type": "markdown",
1631    "metadata": {
1632     "id": "sQhxXLtbC5mc"
1633    },
1634    "source": [
1635     "#Experiments"
1636    ]
1637   },
1638   {
1639    "cell_type": "code",
1640    "execution_count": null,
1641    "metadata": {
1642     "id": "IavCNH4AC23l"
1643    },
1644    "outputs": [],
1645    "source": [
1646     "import numpy as np\n",
1647     "a = np.array([1.])\n",
1648     "b = np.array([2.])\n",
1649     "c  = a @ b\n",
1650     "print('a',a)\n",
1651     "print('b',b)\n",
1652     "print('c=a@b',c)"
1653    ]
1654   },
1655   {
1656    "cell_type": "markdown",
1657    "metadata": {
1658     "id": "Uvsbbv2XZ2Hd"
1659    },
1660    "source": [
1661     "# Testers"
1662    ]
1663   },
1664   {
1665    "cell_type": "code",
1666    "execution_count": null,
1667    "metadata": {
1668     "id": "OsOqvQk6ZXZV"
1669    },
1670    "outputs": [],
1671    "source": [
1672     "# a basic ext_kf test\n",
1673     "import numpy as np\n",
1674     "u = [1,\n",
1675     "     2]\n",
1676     "P = [[2 , -1],\n",
1677     "    [-1 , 2]]\n",
1678     "A = [ [1 ,2],\n",
1679     "      [3 ,4]]\n",
1680     "u = np.array(u)      \n",
1681     "Q = np.array([[1,0],[0,1]])\n",
1682     "A = np.array(A)\n",
1683     "def fun(u):\n",
1684     "  return A @ u, A\n",
1685     "F = lambda u: fun(u)\n",
1686     "H = [[1, 0],\n",
1687     "     [0, 1]]\n",
1688     "d = [2,\n",
1689     "    3]\n",
1690     "R = [[2, 0],\n",
1691     "    [0, 2]]\n",
1692     "H = np.array(H)      \n",
1693     "d = np.array(d)\n",
1694     "R = np.array(R)\n",
1695     "ua,Pa = ext_kf(u,P,F,Q)\n",
1696     "print('ua=',ua)\n",
1697     "print('Pa=',Pa)\n",
1698     "ua,Pa = ext_kf(u,P,F,Q,d,H,R)\n",
1699     "print('ua=',ua)\n",
1700     "print('Pa=',Pa)\n"
1701    ]
1702   },
1703   {
1704    "cell_type": "markdown",
1705    "metadata": {},
1706    "source": [
1707     "First try to approximate Ed Ew by ML following https://www.tensorflow.org/guide/keras/sequential_model"
1708    ]
1709   },
1710   {
1711    "cell_type": "code",
1712    "execution_count": null,
1713    "metadata": {},
1714    "outputs": [],
1715    "source": [
1716     "import tensorflow as tf\n",
1717     "from tensorflow import keras\n",
1718     "from tensorflow.keras import layers\n",
1719     "from sklearn.preprocessing import MinMaxScaler\n",
1720     "from sklearn.metrics import mean_squared_error\n",
1721     "from tensorflow.keras.models import Sequential\n",
1722     "from tensorflow.keras.layers import Dense\n",
1723     "from matplotlib import pyplot as plt"
1724    ]
1725   },
1726   {
1727    "cell_type": "markdown",
1728    "metadata": {},
1729    "source": [
1730     "First ML following \n",
1731     "first simple example following https://machinelearningmastery.com/neural-networks-are-function-approximators/\n",
1732     "We want to find approximate the function that maps (t2,rh) to (Ew,Ed)"
1733    ]
1734   },
1735   {
1736    "cell_type": "code",
1737    "execution_count": null,
1738    "metadata": {},
1739    "outputs": [],
1740    "source": [
1741     "# Define Sequential model with 3 layers\n",
1742     "model = keras.Sequential()\n",
1743     "model.add(keras.Input(shape=(2,)))\n",
1744     "model.add(layers.Dense(2, activation=\"sigmoid\", name=\"layer1\"))\n",
1745     "model.add(layers.Dense(3, activation=\"sigmoid\", name=\"layer2\"))\n",
1746     "model.add(layers.Dense(2, name=\"layer3\"))  # alone just linear regression\n",
1747     "model.summary()\n",
1748     "model.compile(optimizer='adam',loss='mse')"
1749    ]
1750   },
1751   {
1752    "cell_type": "code",
1753    "execution_count": null,
1754    "metadata": {},
1755    "outputs": [],
1756    "source": [
1757     "# select and separately scale the input and output variables\n",
1758     "sz=500\n",
1759     "train=250\n",
1760     "t2s=t2[:sz].reshape(-1,1)\n",
1761     "rhs=rh[:sz].reshape(-1,1)\n",
1762     "Eds=Ed[:sz].reshape(-1,1)\n",
1763     "Ews=Ew[:sz].reshape(-1,1)\n",
1764     "print(t2s.shape,rhs.shape,Eds.shape,Ews.shape)\n",
1765     "print(min(t2s),max(t2s),min(rhs),max(rhs),min(Eds),max(Eds),min(Ews),max(Ews))\n",
1766     "scale_t2 = MinMaxScaler()\n",
1767     "t2_scaled = scale_t2.fit_transform(t2s)\n",
1768     "scale_rh = MinMaxScaler()\n",
1769     "rh_scaled = scale_rh.fit_transform(rhs)\n",
1770     "scale_Ed = MinMaxScaler()\n",
1771     "Ed_scaled = scale_Ed.fit_transform(Eds)\n",
1772     "scale_Ew = MinMaxScaler()\n",
1773     "Ew_scaled = scale_Ew.fit_transform(Ews)\n",
1774     "print(t2_scaled.shape,rh_scaled.shape,Ed_scaled.shape,Ew_scaled.shape)\n",
1775     "print(min(t2_scaled),max(t2_scaled),min(rh_scaled),max(rh_scaled),\n",
1776     "      min(Ed_scaled),max(Ed_scaled),min(Ew_scaled),max(Ew_scaled))\n",
1777     "x=np.concatenate([t2_scaled,rh_scaled],axis=1)\n",
1778     "y=np.concatenate([Ed_scaled,Ew_scaled],axis=1)\n",
1779     "print(x.shape,y.shape)"
1780    ]
1781   },
1782   {
1783    "cell_type": "code",
1784    "execution_count": null,
1785    "metadata": {},
1786    "outputs": [],
1787    "source": [
1788     "model.fit(x[:,:train], y[:,:train], epochs=500, batch_size=10, verbose=0)\n",
1789     "print('done')"
1790    ]
1791   },
1792   {
1793    "cell_type": "code",
1794    "execution_count": null,
1795    "metadata": {},
1796    "outputs": [],
1797    "source": [
1798     "# evaluate the model\n",
1799     "y_pred = model.predict(x)\n",
1800     "# inverse transforms\n",
1801     "print(y_pred.shape)\n",
1802     "Ed_pred = scale_Ed.inverse_transform(y_pred[:,0].reshape(-1, 1))\n",
1803     "Ew_pred = scale_Ew.inverse_transform(y_pred[:,1].reshape(-1, 1))\n",
1804     "print(Ed_pred.shape,Ew_pred.shape)\n",
1805     "# report model error\n",
1806     "print('Ed min max:',min(Eds),max(Eds),'diff',max(Eds)-min(Eds) )\n",
1807     "print('Ed MSE on training data:   %.3f' % mean_squared_error(Eds[:train], Ed_pred[:train]))\n",
1808     "print('Ed MSE on validation data: %.3f' % mean_squared_error(Eds[train:], Ed_pred[train:]))\n",
1809     "print('Ew min max:',min(Ews),max(Ews),'diff',max(Ews)-min(Ews) )\n",
1810     "print('Ew MSE on training data:   %.3f' % mean_squared_error(Ews[:train], Ew_pred[:train]))\n",
1811     "print('Ew MSE on validation data: %.3f' % mean_squared_error(Ews[train:], Ew_pred[train:]))\n"
1812    ]
1813   },
1814   {
1815    "cell_type": "markdown",
1816    "metadata": {},
1817    "source": [
1818     "Get data (labels) "
1819    ]
1820   },
1821   {
1822    "cell_type": "code",
1823    "execution_count": null,
1824    "metadata": {},
1825    "outputs": [],
1826    "source": [
1827     "obs = obs_data[:sz].reshape(-1,1)\n",
1828     "scale_obs = MinMaxScaler()\n",
1829     "obs_scaled = scale_obs.fit_transform(Eds)"
1830    ]
1831   },
1832   {
1833    "cell_type": "code",
1834    "execution_count": null,
1835    "metadata": {},
1836    "outputs": [],
1837    "source": []
1838   },
1839   {
1840    "cell_type": "code",
1841    "execution_count": null,
1842    "metadata": {},
1843    "outputs": [],
1844    "source": [
1845     "import numpy as np\n",
1846     "import tensorflow as tf\n",
1847     "from tensorflow import keras\n",
1848     "from tensorflow.keras import layers"
1849    ]
1850   },
1851   {
1852    "cell_type": "code",
1853    "execution_count": null,
1854    "metadata": {},
1855    "outputs": [],
1856    "source": [
1857     "model = keras.Sequential()\n",
1858     "# Add a LSTM layer with 128 internal units.\n",
1859     "model.add(layers.LSTM(128,input_shape=(3,))\n",
1860     "\n",
1861     "# Add a Dense layer with 10 units.\n",
1862     "model.add(layers.Dense(10))\n",
1863     "\n",
1864     "model.summary()"
1865    ]
1866   }
1867  ],
1868  "metadata": {
1869   "colab": {
1870    "collapsed_sections": [
1871     "jivOYEhiXMi5",
1872     "Uvsbbv2XZ2Hd"
1873    ],
1874    "name": "fmda.ipynb",
1875    "provenance": []
1876   },
1877   "kernelspec": {
1878    "display_name": "Python 3 (ipykernel)",
1879    "language": "python",
1880    "name": "python3"
1881   },
1882   "language_info": {
1883    "codemirror_mode": {
1884     "name": "ipython",
1885     "version": 3
1886    },
1887    "file_extension": ".py",
1888    "mimetype": "text/x-python",
1889    "name": "python",
1890    "nbconvert_exporter": "python",
1891    "pygments_lexer": "ipython3",
1892    "version": "3.7.10"
1893   }
1894  },
1895  "nbformat": 4,
1896  "nbformat_minor": 1