diff --git a/Config/config.json b/Config/config.json index 2434b97..28deddd 100644 --- a/Config/config.json +++ b/Config/config.json @@ -1,10 +1,10 @@ { - "Number_of_cycles": 10000, + "Number_of_cycles": 1, "Amplitude_mm": 1, "Time_in_beam_s": 5, "Time_out_of_beam_s": 10, - "Exposure_time": 0.0002, - "Img_Processing": 1, - "pixel_size_mu": 0.275, + "Exposure_time": 0.0001, + "Img_Processing": 0, + "pixel_size_mu": 1.1, "long_time_interval": 50 } \ No newline at end of file diff --git a/Config/measurement.json b/Config/measurement.json index d0f2a6f..149b814 100644 --- a/Config/measurement.json +++ b/Config/measurement.json @@ -1,4 +1,4 @@ -{"std_test_mov": [-10, 10], -"std_test_wait": [1, 5], +{"std_test_mov": [-1, 1], +"std_test_wait": [4, 4], "backlsh_meas_mov": [10, -10, -10, 10], "backlash_meas_wait": [1]} \ No newline at end of file diff --git a/Images_doku/Corrected.png b/Images_doku/Corrected.png new file mode 100644 index 0000000..3aa0a68 Binary files /dev/null and b/Images_doku/Corrected.png differ diff --git a/Images_doku/TimeNewCtr.png b/Images_doku/TimeNewCtr.png new file mode 100644 index 0000000..66ca7b4 Binary files /dev/null and b/Images_doku/TimeNewCtr.png differ diff --git a/Images_doku/complete.png b/Images_doku/complete.png new file mode 100644 index 0000000..4712c60 Binary files /dev/null and b/Images_doku/complete.png differ diff --git a/Images_doku/ctr_improvements.png b/Images_doku/ctr_improvements.png new file mode 100644 index 0000000..a66177d Binary files /dev/null and b/Images_doku/ctr_improvements.png differ diff --git a/Images_doku/roomTemp.png b/Images_doku/roomTemp.png new file mode 100644 index 0000000..ece1b9d Binary files /dev/null and b/Images_doku/roomTemp.png differ diff --git a/Images_doku/stable_x.png b/Images_doku/stable_x.png new file mode 100644 index 0000000..877f3f7 Binary files /dev/null and b/Images_doku/stable_x.png differ diff --git a/Scripts/Test_y.py b/Scripts/Test_y.py new file mode 100644 index 0000000..18c6276 --- /dev/null +++ b/Scripts/Test_y.py @@ -0,0 +1,66 @@ +from time import sleep +from pathlib import Path +import sys + +import pyads + + +def check_path(path_str): + try: + path = Path(path_str) + if not path.exists(): + raise FileNotFoundError(f"Path does not exist: {path_str}") + print(f"Path exists: {path_str}") + except FileNotFoundError as e: + print(f"Error: {e}") +config_path = r"C:\Users\berti_r\Python_Projects\StagePerformaceDocu\Config\config.json" +check_path(config_path) + + + +library_path = r"C:\Users\berti_r\Python_Projects\templates\motion_libs" +check_path(library_path) +sys.path.append(library_path) +measurement_mov_path = r"C:\Users\berti_r\Python_Projects\StagePerformaceDocu\Config\measurement.json" +check_path(measurement_mov_path) + + +import motionFunctionsLib as mfl +import time + + +plc = mfl.plc('5.67.222.118.1.1', 852) + +plc.connect() +axis1 = mfl.axis(plc, 1) +axis4 = mfl.axis(plc, 4) + +print(axis4.getCoupledGear1()) +axis1.setAcceleration(10000.0) +axis1.setDeceleration(10000.0) +axis1.setVelocity(3) + + +axis4.setAcceleration(10000.0) +axis4.setDeceleration(10000.0) +axis4.setVelocity(3) + + + +axis1.enableAxis() +axis4.enableAxis() +sleep(1) +print("coupling: ",axis4.getCoupledGear1()) +for i in range(3): + axis4.moveRelative(0.5) + axis1.moveRelative(0.5) + sleep(5) + axis4.moveRelative(-0.5) + axis1.moveRelative(-0.5) + sleep(5) + + + + +axis1.disableAxis() +axis4.disableAxis() diff --git a/Scripts/__pycache__/metrology_functions.cpython-313.pyc b/Scripts/__pycache__/metrology_functions.cpython-313.pyc index 0499887..d7a5390 100644 Binary files a/Scripts/__pycache__/metrology_functions.cpython-313.pyc and b/Scripts/__pycache__/metrology_functions.cpython-313.pyc differ diff --git a/Scripts/metrology_functions.py b/Scripts/metrology_functions.py index 9434125..9ed0d79 100644 --- a/Scripts/metrology_functions.py +++ b/Scripts/metrology_functions.py @@ -52,7 +52,9 @@ if not os.path.exists(workdir): plc = mfl.plc('5.67.222.118.1.1', 852) #TODO!!!!!!!!!!!!!!!!!!!!!!!!!!! plc.connect() -axis1 = mfl.axis(plc, 2) +axis2 = mfl.axis(plc, 2) +axis1 = mfl.axis(plc, 1) +axis4 = mfl.axis(plc, 4) #insert try catch later def get_pixel_size(): config = myu.load_object(config_path) @@ -203,7 +205,7 @@ def aquire_avg(camera_a, nr=10): com_y = np.average(y_array) return com_x, com_y -def run_repeatability_series( +def run_repeatability_series_n( motor_pv_prefix=0, ntries=100,save_images=True, run_analysis=False): #improv @@ -227,12 +229,12 @@ def run_repeatability_series( #enable axis clean up later - axis1.setAcceleration(10000.0) - axis1.setDeceleration(20000.0) - axis1.setVelocity(-3) - axis1.disableAxis() + axis2.setAcceleration(10000.0) + axis2.setDeceleration(20000.0) + axis2.setVelocity(-3) + axis2.disableAxis() sleep(1) - axis1.enableAxis() + axis2.enableAxis() sleep(1) #--------------------------------------load coordinates from file----------------------- x_coordinates_json = myu.load_object(measurement_mov_path) @@ -246,7 +248,7 @@ def run_repeatability_series( #---------------------------------------------move------------------------------------------ #add multithreading for simultanious movement of y and x axis for mov,wait in zip(x_coordinates, wait_x): - axis1.moveRelativeAndWait(mov) + axis2.moveRelativeAndWait(mov) sleep(wait) start_pos_rbv = 4 #???? meas_pos_rbv = 5 #???? @@ -287,12 +289,12 @@ def run_repeatability_series( analyze_repeatability(savefile, pixel_size=pixel_size, units='um') #-----------------------------------------cleanup----------------------------------------- - axis1.disableAxis() + axis2.disableAxis() camera.stop() del camera -def run_repeatability_series_motor_off( +def run_repeatability_series( motor_pv_prefix=0, ntries=100, save_images=True, run_analysis=False): # improv ntries = init_nr_of_cycles() @@ -315,13 +317,21 @@ def run_repeatability_series_motor_off( # enable axis clean up later - axis1.setAcceleration(10000.0) - axis1.setDeceleration(20000.0) + axis1.setAcceleration(50.0) + axis1.setDeceleration(50.0) axis1.setVelocity(3) axis1.disableAxis() sleep(1) axis1.enableAxis() sleep(1) + + axis4.setAcceleration(50.0) + axis4.setDeceleration(50.0) + axis4.setVelocity(3) + axis4.disableAxis() + sleep(1) + axis4.enableAxis() + sleep(1) # --------------------------------------load coordinates from file----------------------- x_coordinates_json = myu.load_object(measurement_mov_path) x_coordinates = x_coordinates_json.get('std_test_mov') @@ -332,14 +342,12 @@ def run_repeatability_series_motor_off( for i in range(ntries): # ---------------------------------------------move------------------------------------------ # add multithreading for simultanious movement of y and x axis - axis1.enableAxis() - sleep(0.1) for mov, wait in zip(x_coordinates, wait_x): - axis1.moveRelativeAndWait(mov) + axis1.moveRelative(mov) + axis4.moveRelative(wait) sleep(wait) start_pos_rbv = 4 # ???? meas_pos_rbv = 5 # ???? - axis1.disableAxis() # ---------------------------------------------capture------------------------------------------ x_array = [] y_array = [] @@ -377,7 +385,97 @@ def run_repeatability_series_motor_off( analyze_repeatability(savefile, pixel_size=pixel_size, units='um') # -----------------------------------------cleanup----------------------------------------- - axis1.disableAxis() + axis2.disableAxis() + camera.stop() + del camera + + +def run_repeatability_series_motor_off( + motor_pv_prefix=0, ntries=100, save_images=True, run_analysis=False): + # improv + ntries = init_nr_of_cycles() + print(f"started with {ntries} cycles") + if os.getenv("EPICS_CA_ADDR_LIST") is not None: + pass + else: + os.environ["EPICS_CA_ADDR_LIST"] = "129.129.181.64" + + camera = ad.AD() + pixel_size = 1.1 + + savedir = os.path.join(workdir, + f'{get_timestr()}_repeatibility_{motor_pv_prefix}') + safe_meas_settings(savedir) + savefile = os.path.join(savedir, + f'repeatibility_{motor_pv_prefix}.dat') + os.makedirs(savedir) + camera.start() + + # enable axis clean up later + + axis2.setAcceleration(10000.0) + axis2.setDeceleration(20000.0) + axis2.setVelocity(3) + axis2.disableAxis() + sleep(1) + axis2.enableAxis() + sleep(1) + # --------------------------------------load coordinates from file----------------------- + x_coordinates_json = myu.load_object(measurement_mov_path) + x_coordinates = x_coordinates_json.get('std_test_mov') + wait_x_json = myu.load_object(measurement_mov_path) + wait_x = wait_x_json.get('std_test_wait') + print(wait_x) + + for i in range(ntries): + # ---------------------------------------------move------------------------------------------ + # add multithreading for simultanious movement of y and x axis + axis2.enableAxis() + sleep(0.1) + for mov, wait in zip(x_coordinates, wait_x): + axis2.moveRelativeAndWait(mov) + sleep(wait) + start_pos_rbv = 4 # ???? + meas_pos_rbv = 5 # ???? + axis2.disableAxis() + # ---------------------------------------------capture------------------------------------------ + x_array = [] + y_array = [] + for nr_img in range(10): + sleep(0.1) + im = camera.get_image() + sleep(0.1) + + if (1 == init_image_processing_yes_no()): + + com_x_tmp, com_y_tmp = __process_img(im) + else: + com_x_tmp, com_y_tmp = image_center_of_mass(im, plot=False, verbose=False) + x_array.append(com_x_tmp) + y_array.append(com_y_tmp) + com_x = np.average(x_array) + com_y = np.average(y_array) + + data_str = " {:6d} {:18f} {:18f} {:8.3f} {:8.3f} {:14.3f}\n".format( + i, start_pos_rbv, meas_pos_rbv, com_x, com_y, time.time()) + print(data_str, end='') + # -------------------------------------------Save---------------------------------------------------- + with open(savefile, 'a') as fh: + fh.write(data_str) + + if save_images: + imobj = Image.fromarray(im) + imfile = os.path.join(savedir, + f'im_{i:05d}.tif') + imobj.save(imfile) + + # --------------------------------------------analyse---------------------------------------------- + if run_analysis: + print("") + analyze_repeatability(savefile, pixel_size=pixel_size, units='um') + # -----------------------------------------cleanup----------------------------------------- + + axis2.disableAxis() camera.stop() del camera def analyze_repeatability(input_file, pixel_size, units='um'): diff --git a/data/Temp/20250723_131041.dat b/data/Temp/20250723_131041.dat new file mode 100644 index 0000000..18f207c --- /dev/null +++ b/data/Temp/20250723_131041.dat @@ -0,0 +1,3461 @@ +26.5 26.2 23.398 26.433 26.127 1753269041.3173199 +26.4 26.2 23.435 26.493 26.133 1753269061.3223839 +26.5 26.3 23.458 26.546 26.12 1753269081.325517 +26.5 26.2 23.463 26.629 26.106 1753269101.330125 +26.5 26.3 23.487 26.72 26.111 1753269121.333649 +26.3 26.0 23.508 26.853 26.121 1753269141.3375318 +26.7 26.4 23.469 26.93 26.081 1753269161.326268 +26.4 26.1 23.502 27.082 26.108 1753269181.348994 +26.3 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b/data/data20250807_alignment_tests/20250807_164424_repeatibility_0/repeatibility_0.dat @@ -0,0 +1 @@ + 0 4.000000 5.000000 34.720 33.795 1754577881.764 diff --git a/notebooks/.ipynb_checkpoints/Analytics-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/Analytics-checkpoint.ipynb new file mode 100644 index 0000000..0de1608 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/Analytics-checkpoint.ipynb @@ -0,0 +1,1395 @@ +{ + "cells": [ + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T12:41:08.574768Z", + "start_time": "2025-07-26T12:41:08.481768Z" + } + }, + "cell_type": "code", + "source": [ + "import sys\n", + "from time import sleep\n", + "\n", + "# Imports\n", + "\n", + "from IPython.display import display, clear_output\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import time\n", + "import threading\n", + "import os\n", + "import json\n", + "import glob\n", + "import numpy as np\n", + "from datetime import datetime, timedelta\n", + "\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "#from PyQt5.QtGui.QRawFont import style\n", + "from pywin.debugger import close\n", + "from scripts.regsetup import description\n", + "from webcolors import names\n", + "from pathlib import Path\n", + "#TODO: Move script from frederica to scripts\n", + "def check_path(path_str):\n", + " try:\n", + " path = Path(path_str)\n", + " if not path.exists():\n", + " raise FileNotFoundError(f\"Path does not exist: {path_str}\")\n", + " print(f\"Path exists: {path_str}\")\n", + " except FileNotFoundError as e:\n", + " print(f\"Error: {e}\")\n", + "\n", + "meas_scripts_dir = r\"C:\\Users\\berti_r\\Python_Projects\\metrology\\metrology\"\n", + "meas_scripts_dir_local = r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Scripts\"\n", + "config_path = r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\"\n", + "\n", + "\n", + "#check_path(meas_scripts_dir)\n", + "check_path(meas_scripts_dir_local)\n", + "check_path(config_path)\n", + "sys.path.append(meas_scripts_dir_local)\n", + "#sys.path.append(meas_scripts_dir)\n", + "#TODO: mirror struct from jason\n", + "\n", + "#local includes\n", + "import matplotlib.dates as mdates\n", + "#import metrology_functions as mf\n", + "import myutility as myu\n", + "from matplotlib.widgets import Cursor\n", + "import ad\n", + "import sys\n", + "import os" + ], + "id": "ca3c9c7af43b4e58", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Scripts\n", + "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\n" + ] + } + ], + "execution_count": 1 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## Temperature time plot analysis\n", + "\n", + "The two CrNi temperature probes show a peridical temperature fluctuation of 1${\\textdegree}$C which is unlikely to be true.\n", + "Reason, only the CrNi probes have this fluctuation and the P304 at the same place dont show that fluctuation.\n", + "For future data analysis i recomand to pass them throug a BP or LP filter since it looks like the avg is still usable.\n" + ], + "id": "ca5359d36ec7f8ff" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T12:41:09.122901Z", + "start_time": "2025-07-26T12:41:08.783281Z" + } + }, + "cell_type": "code", + "source": [ + "data_folder = r'C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\Temp'\n", + "%matplotlib widget\n", + "\n", + "\n", + "# Load the newest file\n", + "\n", + "# Load file\n", + "file_path = myu.find_newest_dat_file(data_folder)\n", + "times, temps = myu.load_temp_data(file_path)\n", + "\n", + "\n", + "# Initial plot range setup\n", + "initial_xlim = (mdates.date2num(times[0]), mdates.date2num(times[-1]))\n", + "colors = ['red', 'green', 'blue', 'orange', 'purple']\n", + "labels = [f\"Chanel {i+1}\" for i in range(5)]\n", + "\n", + "# Setup plot\n", + "fig_temp, ax = plt.subplots(figsize=(10, 5))\n", + "lines = []\n", + "\n", + "# Plot initial downsampled data\n", + "def plot_initial():\n", + " ind_min, ind_max = 0, len(times)\n", + " step = max((ind_max - ind_min) // 1000, 1)\n", + "\n", + " for i in range(5):\n", + " line, = ax.plot(times[ind_min:ind_max:step],\n", + " temps[i][ind_min:ind_max:step],\n", + " label=labels[i], color=colors[i])\n", + " lines.append(line)\n", + "\n", + " ax.set_title(\"Temperature Over Time\")\n", + " ax.set_xlabel(\"Time\")\n", + " ax.set_ylabel(\"Temperature (°C)\")\n", + " ax.legend()\n", + " ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))\n", + " ax.set_xlim(initial_xlim)\n", + " ax.relim()\n", + " ax.autoscale_view()\n", + "\n", + "# Update on zoom/pan\n", + "def update_plot(event=None):\n", + " xlim = ax.get_xlim()\n", + " t_nums = mdates.date2num(times)\n", + " ind_min, ind_max = np.searchsorted(t_nums, xlim)\n", + " ind_max = min(len(times), ind_max)\n", + " step = max((ind_max - ind_min) // 1000, 1)\n", + "\n", + " for line, temp_data in zip(lines, temps):\n", + " line.set_data(times[ind_min:ind_max:step], temp_data[ind_min:ind_max:step])\n", + "\n", + " ax.relim()\n", + " ax.autoscale_view()\n", + " fig_temp.canvas.draw_idle()\n", + "\n", + "# Hook zoom & pan events\n", + "fig_temp.canvas.mpl_connect('button_release_event', update_plot)\n", + "fig_temp.canvas.mpl_connect('scroll_event', update_plot)\n", + "fig_temp.canvas.mpl_connect('motion_notify_event', update_plot)\n", + "\n", + "# Run\n", + "plot_initial()\n", + "update_plot()\n", + "plt.tight_layout()\n", + "fig_temp.canvas.draw_idle()" + ], + "id": "52db5e2c12fea30c", + "outputs": [ + { + "data": { + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ], + "image/png": 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szJr1mfh9+PBzMWLEBZp7+iuvTMGMGe8iEPCjX7+BGDPmJrRr1y7lMfz772K0adMWd931AC655LxGHyOGYRiGYRiGYZjtBY5BT0YsBtTUNO2H9pkm5MLu89WiZ88+ptnOBw3aWwjTKh98MAPXXHMDnn/+VVRVVWLSpIlaO+PG3YRTTx2G119/FxMm3I8//vgVH3zwnrbt11/PFm29+OJUnHPOeZg06UmsXr1K/DZ9+tuYNetTjB9/N5599mUUFhZizJhRCIdTl0IbMuRg3HbbBOTn56d93AzDMMxOSDRYr3ekKbR9oKSxesQwDMMwjQ5b0K2IxZB/wlFw/fZLk+42NHg/lH/4OUnYKdetrq4Sf7Ozs9Nq+4ILLhZCO3H88Sdj5szpWgw4Ce4nnXSq+D/Fse+112CsXLlC2zYvLw+jRl0Dh8OBc845H1OnvoLFixcJ9/k33nhNWMzVtm+4YSxOPvkY/Pzzj0IAZxiGaXGQoBYLA3YXWgKOmqVALIJIds/UK0dqAEeW9l977XJ417+OcO5eCLY5XrQjsDnEH/emmbBFahHoMDxl086KuXBW/o5g6+MR9XY0Hzd6P0UDsPvXIpq5q/YT7cdVOReh/P0Qzu6DaEaXlPuzhcoRc2QCdnfK9fJ/OwK2aAgVA6Yhkr2H+XqBTchY9wp8nS5EzN064feMlQ8By+6Gp88k+DuMSNk/u389XOU/I9D2FMCmt2nYQmVwVv6JUOHB2lgLYlFkrHoKzppFCBYegkC7M7VtvWueh7NmMWq734CoqxVgTz0Nc9QsQdTdGjFXgfi/s+I3RLxdEfO00e3TVfYjPBvfRTinL/ydL0H2wqvgrF6EigFvmo6F8VjswWJEsnqgXkRq4NnyKQKtTwAc3uTrRgPwbHgbyBkOW7AS2f/egkDr4xCksRW/h5RxlMbZFtwCZ/W/CBUOia8TBqJ+wJnevKfeCAUQXePbh/1K3D/OvLTmjAzDbD+wgJ6MFv7AI6GZIGt4OnTs2En7TkI9ucgTnTt3gcvlFm7qK1Ysx3//rRDC+dFHH6et3759RyGcq5DreyQSRm1tLTZv3oTx42+B3V73QgsEAlizZnWjHCfDMExjk7VsAjJWPYHyfWYjnDdIW+7e9L4QAp3V/yDqKoK//ZmIedpatuPe/Ak8G9+Gr+vVsAe3IGZ3I1Q0VPxmC5YgZ+FVCLQ7HYG2pyJz+d2Iersg0Ol8IOwT69h99JyMouCnfWGLhRFzZCHqzEflni8iXLA/vGtfRsbqp1HZ71VEMnsg5++L4dn8Map7PgJ/x/PhrPgFefPOhD1cjpjNjbL9vkPuX5fAFq5E2b7fCmE9b4ESPhRZcT+CRYcJYS5m9wjBMtjmBO1YaJu8uSfDHq5AdPn9qO1+HdwlXyCcMxCRjM6IZHRF1tLxcFUtQMyeCVu0FpV9n0cob29kL7kNni0f6caGjqOq77NwF8+CPbAB/o4XINj6WKGMyFg9SQiE7uJPEc7ZE+WDv1I2ikWFAOqoXYaMda8inLkrQkWHIfevi7R28/48E9U9H0Iob1/EXHmw+9fBs+EteLZ8BleFolR3lf+Ein6vAXavEIJJ0Kbxz1g/Vfye88//wVG9CMGioUKh4Nk4A57izxBofbxOkZH714WirarQwwi0OQUZ614WQnfMmYP8344R4x5xt0V1zweFUoMUDa6Sr5C9dJzYnhQntVV/oWb3e+As+wk5i68TyzPWPA9/uzNR1fd5ZKx+BlFPWwTanaHsNOJHxrqXEHUVKn39eyRi7iJU7/EgPJtmwrP5fUQyuqF0/5+EooaOndaxkWCpncsqoagQ4zX/XJTv9SGcVX/BFqlGqPAQsdxRs0z831X+IzJWTYI9sBY1u40X54bOPWwexGwOBIQiI4bM5fcKhRaNlz1YgmCrI5HzzxXwbJ4pFAi1Xa8Wigw6Ftg9ivC+6QNxfXs3vAV36bdK5zZNRW4oBFflH2J5ycFLxL1S8OtQ+DpegJoeE2CL+hFz5iNv3jCh9KFzGWxzInL/PAvush9Qtu9XiGT31o6XjiVz5cOiH7S/mt1uV/qgKm3WPCvOTzhvL901SvvN/+MEodSo7vko8n87SnhqlO/9qV4BYkYsBu/aFxFzZiPQbphQHGQtuxuRzO7wd7rEcg5J9xkpU9wlsxF15qKW+hrHu/pZeDbNgK/L5XWKCwvovsqdN0zsu6rvc+J6zv37EkS8nVDd63HYA5vEfUvKGffmj5TrY/0SOLKPQDinv0EJskjcxyBlWVwJFPV0MFfSMQyzzbHFKIB4J6O4uCrBSy4UCqKkZAOKitoLYVVAK9XWNlm/nE47wm5v2ooBciE/4YQjcPnlV+KUU+Ivdombbx4jksTts8++otTZxImTNSs3lTN78cXn8O67H2Lp0iW44opLhLW7X78B6NmzF6ZNexNOpxO33nqHiEGfN+8PPPXUc1rbZ5xxIi666DIcdNChOPbYoXjwwccTktHl5uYiNzcvYd9WqG0ed9yJluuYnqethIa7Vasc0+uC2bbw2Dcf2+XYx6KKm3MqS50ECS9EoP3Z2jJbsBitvt1F+7+/3Rmo6jsFjuq/UPhz3FIXJ+rIgb/juXBWzhfCF1lmbdEAgkVHCMtq3vxzxHrhzN3gqF0BG6KoGPC2EGKyl4wVAhpRMfBd5M1TntPhrD3g9K9GbZf/Q+bKR80P1eYUwo5347tK/1ufIKybmf89lvaxk4BMAmQygoWHCkUECShkZc8iC3M9iTqyYY9Up7VuOLsvHLXLYYv69P3IP0AIvfbgZrgq56W9X7JEe7Z8CFeFeSnPiKejsOSTwEEKkFTE7F7UdhsjvAgABzzFnyJdQjkD4etyGXL/+b+E32q7XQNXybdwVVkfm7/9cPg7nAvPxmmacJ1qLOn8Zax9XlyTyQi0Ogru0u/FuNP5tofSd/MnRQIJlaTASAdSMlXvfj8y1jwHZ/VfaW1DSg5HcJN2Xona7tcje9kdyjJnnjhed/kPyvG0ORmVfSeLe85d8g2yl96aeMxtThJeEqREUI+3tutV4jlSs9ttcPjXwrvuNWSueiJhWxJWa3a9VSiT/B3Pg6vyT7Eu3f+kBHBV/IGchVdq13GwYAjsoXI4q/8W/6/e7U74ul9reqw5C/4H76a6EEKhfGh9PNylX2nPCG1cvF2EssTf6ULhrZH3x4nwdb5UCPX5vwwVSg6xv93vEwoY74Y3xP9JseWsXY5g/oHwd7oIuX9frGuXFBCh3EHimVY4pz8c/tViX2WDvxSKs4KfDxACPR1XVe+nEM2MPy9jMdiDm8TzCbAha9ldYmxJoRDKHaB49kR8QmkTKjgEUW9dHiTC7t8gFBnusjkItD5GKA9soVK4Sr8Xis2YMxc7Itvl+3YHwdaIY6+21RSwBT3VmciqcyPc5jjtQDia/upOJw4//ChMnz5NuKxTNneVOXO+E5+RI69M2c7nn3+CAQMGihhylbVrV6Nr1+4pt83JyUFBQSFKS4txwAHKxDYUCmH8+LEiVr1v335pHw/DMIxGxA/P5g8R9bSHd+0LiHrJA8gmJtO+TheLCTRZ52p63IFIVk+4SmbDWfOvsEq5SxRrbMyeoU2gK1yFYhJIE1iyLsqQEEwTcdm9lyyHMRI8wxXIXD1JW+4u/SbetkcnFDlrl2nf8/48K+FwMlbWCdbUT8JKOCdImFSFc0JYp7fEh8bTHo7ABt36NCYZa6folsnCOR2PTXV9l1CPB5uUkCeCLMXuzTN1FtlkkHBO4yHGy0Twi8GOSOYuYoxUASaS0R3+9mcja8V9Sj/KfzRtOwab6Ec4qyeqez0mrM10Xaj7zV42XqeQEBbSWFiz1joC68RHW4eE08J+wKavdfuJugrEb9THrBX3Il387YYJa7+zZokQvl2ScF7Zdwrs/tXIXnYnMv97XFvu63AeMta/ltCWd8Ob4qMde/wak69jGRpLdTzJM4L2R67ZuQsu0M4rjbPdvwae4lnadvURzkW/Nk5LUFrZI/p7SOsz7LBFapCz6KqkbRrbUIVz0b+4skcVzsWycIUmnBMkALb+ambSfXg2fyA+MpmrnlT+rn466bak8Mmfq4T9Zax9CfbAOtjDlZoAbIQETpms5RPEdWf3rUFICO9b4N7yqVA6yMI5QR4u/vbnwGYypiQ4Zy+6BpGsPUTYBI1D1sqHhcVbFc7F/paOhy2meEUSJJyLfpX/oBs3lfzfjxWKFH/b08Q+tH39e7PwTFDvfToussqTIsxR8y+ylyrWfqHUy9pDu2+FQJ63D8r3+gD5f5yoKcwoFIOWRTO7w735Y+EJo17LGdl7omLQdOE9ZA+VwdfxQlT3VpQljqq/hSdBbfcxIoQie/ENqOr1hBLCI4WTuEq/FeEZ5M1BygH6TselhczEInCV/aAoIygsQg3RYZgWDgvo2zlkcb700gswZsyV4jtlRJ8373c8/fREDBs2HN2711mJkrnKL1++DAsX/i1Knc2c+R4WLVooyrWlw1lnnYPnnpuE/PxCdO3aDS+//AL++ms+unS5rRGOkGGY7Y5IrRAGySKqIxqGs2qeiJWWYzzJNZOm9sJlNRZDxqonNRdhM0gQVYVRWywk4p3NrGCyUGO0TBlxVc0XH9XaSO6uZOnNn3uyEJBIIeAu+15qO6BZTWliLQvoZphNkgmyxtXscrOY+JJgQxQfvFRMSsm1OpK5Kzyb3tcEMRLEhaC68lEhwKju8KGiwxHJ3A2ZK+5Dze73IpzdW0xeM1c+IsaobL8fhesrtZX7z0jRVlWvichaOk4IHgRZxWq7XYvaXW+Fs2oBnOU/I1Q4VJwrUl6IOGX/ejh8/yGS0QW588+D07ci7qr9rJg4e9e+BNicwoOAXLTdxZ+J8xp1t0XR9z3rjmGPB8QkmhQwOYtGx8eijRBKyX0fUR+CrY8Tbrr2wEaEyf3WZhfrkBeFr+tVIgaeBBMS7tRxUQ6E3LHvhsO3ErZwjbCC1+wyFrW73qxYQApcCH/YTwgFoby9hCdEVZ/nhDtw7p/niOMjN21SgkQ8HcS14KxZKMIf/B3OE9cFXX+hggNQ1fcFMeF3VC9E7vxzdddBsPBgER5BYQ2qBTNYOBTVfZ4WbuNkSXUENwqLcXWvR4Ug4aUY7VgENbvfDV+X/xPWSHLTL/hxL9E2ueBX9Xlac5N3lf8irk0SoNR8ChWDZmrrV+9+j3BVptAIVWgL5e8PZ8Xv4rowI2Zzab+RpwhZzylPAF2L6nmjsc/9cziiGd3FPhy1SxAqPEy4l5MbuqoQIOtrOLOHCDMg9/Fw3j5wDX4MZeHO8Kx5URP4jF4PslLF3/4sZVyE0uN5cT2QyzpZwKmv1MdQwf66tnwdLxKeCCTskzBJ1zW5wAsVQrhCtz8SLP0dzodn03vwdR0l7smCX5QwAIJyCVhB3jKyQq5kyN/IWnYnvBvfER4EhOyFkfv3pabHKQv+VXs8pDwP4s8vEpbzfz9Gt1/Plo+VsWk3TFjOKa9B3T3k1YTuZNDzRlUUqUo/d/HniPjq8g8RJGwblY6k5DEq1VwVv6H1V3qLucO/Snj9hHMHImfR1brfyLui6Lvdtf9TWIezar4Yf0/x52KZ7NGTt+Bc8QyrGPieWI+eDep7IpzVC4G2JwlFGOV28HW+TFzDNDakPKCQEPKcoOdNxcBpWj4HhmmpsIv7NnSdbpCLez0s6CqbNm0U7uq//vozKioq0LFjR5xyyunC7V2NG0/m4u7z+XDvvXfil19+EpnayZrevfuumD37c7z55ntJXdzJHT0SiYh1Pv54JmpqatCzZ29cffV16NFDSeLDLu6MFTz2O+DYxyLI/+VQYeFR46Rz548QbpFkzSNrXPUe9yOcvadIGBUqPAg5CxUBjYSszNVPNXjXFJNMgp3Dvx6hvEGIZO8JW7hcxLmqwq+yn0tQu8uNusmhCk30KL5VTcJGcZ4kpEWyeyHvj5NgC1ejYu8PFZfpcLWIqRZC79+XKG13vADe9VMRbH2iEBpIEKLJuvitw7mo7vUEnL7lKMj3ouq/rxHKO0BJeBYNIXvJzQjlDUag/VkJcbLZ/94k4q2rdycBySnGmdz3SdjS3E/j469PWBYRxy67jrqKZ4t1yKWUhB2K4SaBNObIEftIF2flPHF8/o7/SyvZHp1vEm5rd7mpro/RsDJeRUMR9XaOJ+iS+p8CNZ5XxNZbJJqj8aMYbt11v7lEue5pG9mqFosKDwsaB0qYR/HEppP5iF8oInRJ3qIhYTF3Vc4Xyo5g25N0id4y/nscvi5XIJLTt65voQrF7dzTTusrKX+i3g663VEiwIx1rwlX+ZgrddUTCuMggSnY6ph4Ur8wbOEyLVkc7YcUESQ42X3/aW27Sr8RChWy9jor56KqzzNaXHLaRGoVYSwW0xQ3yhgsQ8zTGkXtOynPnUhIeLyQoOXe8rEQtP2dL4srPP4Vihtfx/MRLDpSWHzDuQNQtWfcSyQWgy1UrFzX8VhzyitAISWksKJ4fvKKoePwdxiuS5JHVm3vupfhLv0adt9aVOw1U9zfMu5NM4S1ndy+VYs3ucuH8g8Q4SCe9W/A33kkIlm7wbvmBeQsHiMEa3+XkeI68K5/A56N78Bd9p3pEJUN/ka0QwomozWfFHTkkUFKEBKEKVRGJdDqaJFDQF1Wtu93QijPXPGA4mreeaS4lijmnLwHVCt7bZdRQlmU1Xl/4KsjE/pDyjpS7smeORX9pgqh2IjRG6f40FVwb/lEPMdVxY6V10dLgJSagTYnirwQ6dxLjQHPdZoP23bq4s4C+g4goO9MsIC+Y8Fjvx2NvbqSiXugo2oB7KFKkeyLJvhqUjIzV3Cj63IyKvq/Jax2lMxNTe4lE87aXUxkCUoKRe6jZmQuv1+4LZNlqXyvjxDOHyyWe9ZNFdYxkZQqVKYINELQUyb89cGz/nU4qxeKtgSqkBnxi0RoZAUNtjpKLOfrvvngsd+Bxz9SI+5BstI3FqSsyV58nfAIoVhuU1RlgVmm/FgM7s0fiDCIYJuTkf3v9cLlXfesigbgKv8N3rXPI+rpiJo9pBALivn2U0lbu8jPQAoVeoYoySwDCco8Xd9D5cKibA+sFzHq8BSJsa/5/R7Ya5ahuufDwgODlJA1u41D1pJxyFzzrNiWvHpqdx2L1l/kank6SJHi63a1eI7l/H2ZUHySp0J1byV8gxR92YuvF0qzyv5vCK+K3L8uFoogcSg2h8hNkLX8LnEc4Zx+WsiBCilD6ZhI+agqC2p2uUULhdGGzFUAW8QnPDuoqgOFvpAXAbmyG98VVCnAs+WThPGp7TwStbvdJpSYlJBwW7q+83On+bCxgL79wAL69gsL6DsWPPbbx9iTNS5v7ulw+NfA1+l/wjXYXTxbWGpo0mUVP9xQggUHobL/1DrLZTSEnH9GiphsSr6UsfYFIbhT4jWykJFAHWytdwHVEYvAveUzMSk0WiabA77umw8e++aFx78Fj324Wng0UIZ3ihknKEzGVf6rCBHQe4sE4Nk4XXgQJXMXJw8RckenMCTNi4VCJqi6gs2BnL8uEe1SDD6FLZB3VZTc0eNx6PTOIS8QD+VnoKoOuQNFKA9VhKAqEkK4Nuw/d+7p8JR8IbyRana7Q4SxtP5KqcRRvfu9wuWeKm7IUOhJxYA3dOUrGxO+7psPGwvo2w8soG+/sIC+Y8Fj3zxQNmBX2RxkD7gaZWv+RNSRi2hGVxFzTPG4ZEl2lf2EcHYv4ZLsCKyvV/sUc0oWbUpWRVnNyS2ThHkqE2YPFQurDrlAlh7wm8gYbAuVwBHYCFfZd8IFWFiJrGr+kktiEmv+9gBf980Hj33zwuPffOwsY0/hGxSjT0ko1bAXKodJMe+Uq8EWrkCrb/RVhwjh9r7r7UrIUWP3aScZ+5aIbTsV0DlJHMMwzE4CxZrm/35CXQKh1RNR4N8ovlISHdUVUUVOipbMXb1sn1nIWvGgyJ5Nkxyq+R1ztxL1jemvnBCOIGsJxe9S+Sv6EBS5SOWMkqHFC26ngjnDMAyzbSFLPeU+kQm2OU58xO+uAlT1elxY5Ckkwhb1i+VUHYLyWZQc9E/98y4wDYJymJDCnjwdKJ+DGbZQmfjocq3sBLCAzjAM08KgWrFRd6GSwCtULoRnz8Z3EWh/pi4zuqt0DpwVv4ps15FsJUO2RjQgkpjRZMRV9r2IocxYPVmf3TcunBNG4Vxbpe1pYsJT2+UKRKm2bvmvYmJT252yIj8qEo2F8/dDxSB96SAi5mlj2mZCXxmGYRimiaB8AmpOAUrGV/R9b+V7qATeDdPg7/Q/bHdEg/pEmcb/y8STiVL+GMqPEslKTJgqQ0kHKZxMVHGgcnUyET8ctUtFskKqUkA5Cnxdr4QtsBmuyrkiEWL1HvchRPldxL5jsFEpxVgUBb+qyyKoHFBXYhLRMDL/e0RUWMhc8aAIo6OEjb5OF8FH4RZmSnqR72WWUP4Hiw4RRgMyFlCIBYrDQKuLdetSZQhaz1n1DyIZXUXyTppz5f55NqLejqjsN1XJH0GhfV1GNblhgF3c47CL+/YBu7jvWPDY12UVJoGc4t8oezDVig22OhrOyvki+zkJ11SPll5WlESIXm4iS3PVn1obFNNHruFUhzjmzIKrcp6ieY6Fxe/kZk4Jgag2Nr1kRVbpeKmyin6vwRYNCpd2d8nXyF56K4KFh4rsyfSiZYt148LXffPBY9+88Pg3Hzz21mQtuU0r1Ull3sr2nYOoV18yrrnGnlz2yQuNkvJlrJ4kSg2G8/cVQjNVwKD+RjJ3F+/tin6vINj2VGSsegpZS25F5YC3RJ4AQSwiKqq4S74hCVUpxVk5DzE7Jdp7E6GCA5G19HZRltHXbXRdWJkjA62/VBIgUllDEl5ru14Ff2elZGDW4huRuWayrs/lg2Yid8F5WglPNc6/psedoiIJhdmJeU3p19rvNbvcJJL1RTJ3QdaSsVpZSCPk/UCJFt1bPhdVNshAQeOTuewurSxfOHM3UWaSSiyS0kUllLuXyHOQse5lUfFBhvIsUOgfhfgRFf3fQN78c8T3sn2+EOUy3WXfIKffZWgKWECPwwL69gEL6DsWO+vYkxU678+zEcofjHDOAGSufFAI0qGc/lot7m0FxYeXHfCriAUv+vVQhDydUb735zohXJSZMtYwZxqNnfW6bwnw2DcvPP7NB499CiK1KPj1CDir/4a//XClRGBTjD1l+i/5AuHMXYWXmm67cCUK5wxAzJElasqrVPe4RwjkZvjbng7vpunKIXk7oWy/n0Q7lE8mf25d6cdklO73AzybZgr3c1ssaLoOCcFUtUQVYpuLUE4/xBzZjZ6sVobG0e5fD5szCzizTumwLWEXd4ZhmCaEXKgyVz4sBGQq/SKXf6mvcE4vjcp+r8Jd8pUoN5O58hFhXfd1ulTUF6dkONmLbxRWc4I07bQ+ubZRTVyctAIVpVSrVm8hZ+GcYRiG2alwZKKq95Mo+HUovBveFDlVyPpKOVMoC30kp0/j7zMWVcrbrX5KWLSrej0hatdHvF1hi1QBNpeYK4A+EqpwHsodKFy0ZSFaFc7FIfnXotU3nU13HXG3Fe/6qLst3OU/6H4r/PnAlF0nC7UsnJMlvrbrFcLST/tNV7iu7v0UPJveE4YBclEnl/J0oHPiqFkMF7npS0RdhbCHSsV3qjJjI3d+aX+0Pi0nizitW93rcWSufAiezR+IdfztzoS7+HPYwxXadurxhDO6N5ngzAI6wzDMNsBZ9pN4icYcOajZ9dZ4HPgB4oUmu1zJUGbzsv1+EDFxuX9fIpKyCTe0sh/g73SxSKIWydgF7i0fibbUGO9w3t7ir6/j/0TW9JhTqV1LBNoNE3/tfnKjbws4Mup26HADtgAVJWcYhmGYnZpw3l4ItD5eZIH3bnxHLCMFOFG+96cit0s4b5+tU2JHAyIumxLSOWv+hS1KSnKIhHUFvx2ZdjOUm6Z8n9lC6e8u/gyeje8JQZtqyQdbHSlC2qg2vJWVvarfS1JjNcibe4ZOUKewOQqHc5MhofhzhHIGItj2ROHe7ir9Dt6N00Qct1prvrL/G8LV3Nf1ajhJyZDVKz5X2V9UiSFlhHftiwi2OhwO3xo4aleIOQ0lfw3nDhDtkJWa9hfN6CJc1lWjhb/dMATanCSEZqp5T27ulPvGVfINvBveEP2hajP+tqeiZo8HhIt8OGegCB30bpwOd6wMtXmHoma38UpsPuy6soHVPR9GxNNelG/1d7pE5OTJ+O9xEQJA2f/FMbY6FlUD30IrNA3s4h6HXdy3D9jFfcdihxr7eNIV5XsUBT8fCGf1P0k3KT5kpXix2iI+OHwr4e94oWUm08Zmhxr77Qwe++aDx7554fFvPnjs0yRSK1y7Hb7V8Gx8W2eBJfwdRqCqz6QGj33W31ciY/2rOsuzqOkuEYNNCK72UJm2LFh4iLDwZy2/B7ZwDWp2uw2R7F7SRlGRdybmKlR2GA3CveVjwOaBd8PrIku96HvPR5Xkcep8RdteuSicVQvgXfsS/J0uUEqexqLCPZ6EV2NFFlIOeNe9IgToxs6y7qhagNy/LoWv04Xwd7k89frVC0UiOWMSu6297l0lX4rxplh+m8PFZdaY9KmsrMQrr0zBd999jdLSErRr1x4nn3wazjjjbNjtys00ZMjemDhxMgYNUixtTUmyfVdVVeHppx/HDz98j1gsiv33H4LRo69DTg672DItF0f1vyIBCiVSq9njfng2Tkf2omsAhxfBgiFCw64K5+SqJseOqVDCN8qOHugwohmOgGEYhmGYBByZqN11rPgaaHNCQow1JRejkDJK1ErhYYG2pyDY9hR9G5Ea2IOliHo7KRIiSYaVS+AqXSqEc0rm6us6Sij2yTsuY9XTyFj3oti0tssokZyVErIV/jAAtkgNyvb/VavPXtX3efN+2+xiTqFhd4uEcQRlK3dV/CGSqxmF7LrtlVC3cG5/VPd+XNduJKuH6SZRTzvU7nITtgWRnH4oO+CX9NfPVjLxNzahosPRHLCAvp1TUVGOkSMvRKtWrXHzzbehffsOWLToHzz22ENYt24trr32RrRkHn74Xqxbtw4PPfQEbDYbHn74PjzwwN24++4HmrtrDFNHxK9kNi84GME2JyJn4RXCdYw+lPGTYsaU9arg3TQDoA9lJd11HGq7Xy9KocVcrYRmOkoxX552irs5wzAMwzAtkmCbE7DlyErkzhsm3LxVMtbUCcneTe8hWHQEggUHIdjmeBFHLazckRpRPYWE/ZyFVwFVC5AX38bf8QLU7H6P1kag3RnCyk3J6Wp63KW5X5ft/zPsgfWacN5gHFkIFR68dW0wTQoL6Ns5kyc/BZfLhUceeRIej0cs69ChIzweL2655TqcfvpZ6NKlK1oiPp8P33zzFZ55Zgp69lTcdK6++jqMGnUpAoGAdjwM0+REw8hYM1lkWA8VDhEJY+iFTJ+aXW7WynAQqnAepfIg2b3gKv9J/D+Yf4Ao20HaZ4qVIprKfZ1hGIZhmMahutdE2P8clpCQTMVdMlt8sGy8bjkJ9bJgT0Tc7VATt9Cr0DyjeOgGXVw0QbHY9GF2PlhA344JBoOYPXsWRo0anSDMHnjgQXjiiUnC3V1lwYI/8fjjD2Ht2jXo3bsvxo27U/t9zpxvMWXKs1i16j+43W7su+8BuOmmccjMzBTLaZusrCzMmvWZ+H348HMxYsQFYltKY0Au9jNmvItAwI9+/QZizJib0K5du6T9t9tteOCBx9Cjx+665ZFIRAjvLKAz2xJKxEZualQPPGch1fr2oGyfz0X8EiUhyV46TqxX3WMCspferm2XteJ+zTpOMVm5f12orNfzQQTanw33ppkiC6mv0yWA3dVMR8cwDMMwTGNANdHL95sj4tPzfzsGrqo/xXJfh/NgD26Cq/xXRL2dtYRitZ0vF4na8uadQdHkCOXtDdeAO+Ff+iZqyX2dqqgYMQjnzM4NXw1JIMGzNqxP3LAtccbscMMrXL3TgVzYfb5a9OyZWPqB2jDGfH/wwQwhlOfl5WPChHGYNGki7rzzPtHOuHE3CaF6n332xZo1q8XvH3zwHs4++1yx7ddfz8Zppw3Diy9OFbHuzzwzEQcddKiwzk+f/jZmzfoU48ffjaKiVnjzzdcwZswovPrq23A6rS8xsvLvt98BumXvvPMmdt21B/Lz89McNYapP47qxSj45WDhak5uaPbgFrE895+RiLpaw7uuLrupLJyryVuCrY5BLcWP2TPhK/9RZCOlDKNEsO3JTXw0DMMwDMNscxyZKN9nlqgrrlZRkTOPOSt+gz2wQbjGUxK2ygFvwb3lc9TuNhZFHXdFtecgTtDHpAUL6EmE8xNmHIXfNqafoKAxGNxuP3x46udpCenV1VXib3a2PmOhFRdccLEmtB9//MmYOVOplRiNRnHNNTfgpJOUZBIUx77XXoOxcuUKbdu8vDyMGnUNHA4HzjnnfEyd+goWL14kBPQ33iCB/Cat7RtuGIuTTz4GP//8I4YMST/mhQT9r76aLdz1GaaxoZdk1JUHz6YPRM1RgkppyFCWUyNRRzYi2X0QzuqB6t5PA1Rv1F7n3VHd85Em6D3DMAzDMM2Ow4uYw1v3f2m+Hs4frFuVMn+L7N/p2d0YRoMF9CTY0LLvKBKaiaqqyrTW79ixk/adhHpykSc6d+4iSpaRm/qKFcvx338rhHB+9NHHaeu3b99RCOcq5PoeiYRRW1uLzZs3Yfz4W7SM8QTFkJMlPl3ee+8dPP74w7jqqjEYPFiJ12WYRiEWE0na8v5U6oGb4et8Gez+dUJgj2T2gK/LSIRyB4nyIcHWx+ljwGwcesEwDMMwDMNsG1hAt4As2GTJblIXd2f9XNw7dOgkBO1//12EXr0S3dxvvnmMSBJHbuuELECrXgLE0qVLcMUVlwhr94ABg3D22SMwbdqbhr4lXiq0PcWLE3fd9UBCMrrc3Ny0joMs8M888wSuuOJqnHnm8LS2YRgrvGteQObKh1HZ/3WEcwcha+ltyFw1UbdOxN0W5ft8DnuwGI7aZQhQKRJHRkJb6dTeZBiGYRiGYZjGggX0JJCgnOXKalIBPRyO1mN9Jw4//ChMnz5NuKxTNneVOXO+E5+RI69M2c7nn3+CAQMGihhylbVrV6Nr1+4pt6V65QUFhSgtLcYBBwwRy0KhEMaPH4tzzjkPffv2S7r9p59+JITz0aPH4Mwz9bUmGSYdHNWL4F0/Fb7OlyPq7YCcxWPE8oJfh4paozbU3VP+DiNg969HTY87EM3cRXyMLmkMwzAMwzAM01ywgL6dc9FFl+HSSy/AmDFXiu9t2rTFvHm/4+mnJ2LYsOHo3n2XtFzlly9fhoUL/0Z2dg5mznwPixYtFOXa0uGss87Bc89NQn5+Ibp27YaXX34Bf/01H1263JZ0u8rKCjz66IM49tgThKKhpKRY+y0/v0DnUs8wRuz+DchYNRGZq58W/89YMwVVvR7VraMK5zGbG+X7fIpw3j7N0leGYRiGYRiGSQcW0LdzKGv6pElT8OKLz2HChNtQUVGBjh074pJLRuKUU85Iq40zzjgbS5b8i2uuGSVKqJE1/cILL8Xs2frajVYMH36eiEV/6KF7UFNTg549e+PRR59M6eL+668/iyz0ZEWnj8w773wgktUxjEbEh+wlYxHO7gVH7XJRk9wWC2s/26K1yP2nziU9JGqPU4ETO2p3u42Fc4ZhGIZhGKbFY4upgcgthFWrVmHChAmYO3eusOyee+65uOSSS8Rv69evx/jx4/Hrr7+iTZs2uPbaa3HccXWJzNKluLgqocxBKBRESckGFBW1FwnTmoP6urjvjGyL80Qh/61a5ZheF8y2Jd2xJ2t59qLR8BSnVhpFXUUoPeB3xNxFjdvZHQy+7psPHvvmg8e+eeHxbz547JsPHvsdY+xt8bZ2Ogs6lfu67LLLsOeee2LGjBlCWB8zZgzatm2LY489FiNHjkSnTp3EbySk33jjjdhtt92w++67N3fXGYZpbGJR2IJbkDd/BFwVv+p/gg1Ve76EYKsj4V37EgJtTkTW8ntgD5WgZrfbWThnGIZhGIZhtktalIBeXFyMXr164Y477hDZybt164b9998ff/zxhyjrtWHDBrz55pvit1122QXfffcd5s2bxwI6w+xoxCLI//04uMp/0hZFPB1Qvcf9cFXOR6D1MQjnK9UJfN1Gi79Ve77QbN1lGIZhGIZhmB1OQCe39ccff1x8J897cnP/7bffNLd2EtZJOFd55plnmrG3DMM0KuR7FC8x6Nnwlk44Jyr2+gCRrN0RbHtKM3WQYRiGYRiGYXYiAV3msMMOEzHnQ4cOxdFHH42PPvpIJD97+OGHMXPmTBQUFGD06NE44ogjmrurDMNsJZnL7kXGf48hnLMn7IHNcPhX634vGfIXohldm61/DMMwDMMwDLNTC+gTJ04ULu/k7n7fffeJLOEUe05J4SZPnoxffvlFCOhvv/22iFmvD3EjXcplTMuFzldjnTO1Hb4GmpaM/56Es/IP4IDJyFxxv1jmqvhd+z2UOwgO3yqEc/oiltkVfHoaF77umw8e++aDx7554fFvPnjsmw8e+x1j7G22nTiLu5HPPvsM119/PQYNGiQs6rNmzYLdbhe/XXHFFSgqKsJdd9211fvx+/1YvnwFWrVqB7fb0wg9Z7YFwWAAxcUbseuuu8Dr9TZ3d5iG4t8CvNdG+V4wCCibW/fbgAeBdocDBQNELDpsDsCm3PMMwzAMwzAMsyPToizoZDH/888/dW7rlKU9FAoJ93aq0a0K50T37t3x77//1ns/JSXmZdYoi3wkEmu2UmdcZi01dH7oPJWV1cDlCjVKm6QRKyrKMb0umEYm4kfmigeF5VwrkhcXzmu7XYNgm+OV5G90G5TUNGdPd3j4um8+eOybDx775oXHv/ngsW8+eOx3jLG3xdva6QT0tWvX4sorr8S3334rSqsRf//9NwoLC9G/f39MmjQJkUgEDodD/LZ8+XIhuNcXOkHGk8Q3zPaF2TlsiW0yejJXPIzMlQ8nLK/pcQdqu41R/sPnoEnh67754LFvPnjsmxce/+aDx7754LFvPmLb2di3KL9RiiXv06cPxo4di2XLlglB/aGHHsLll1+OE044QVhO77zzTlEf/fXXX8f333+PM888s7m7zTBMChzVi5Hz96XIWvmgtizibqeURjt4Jnzd48I5wzAMwzAMw+zEtCgBnSzjVDotIyMDZ511Fm699Vacd955OP/880V5tZdeegkrVqwQwvqrr76Kxx57TAj0OzuVlZV48snHMGzYSTj88AMxYsQZmDbtDaHQUBkyZG/MnVuXgKspSbbvsrJSjBt3E44++hCcdNLReOaZiQiHw03eR2YbEIsgZ8H/UPTtbij8aTC8G94Wi0N5+8LX4XxUDnwHgfZnAp1Oau6eMgzDMAzDMEyLoEW5uBPk2v7UU0+Z/kbx6FOnTm3yPrVkKirKMXLkhWjVqjVuvvk2tG/fAYsW/YPHHnsI69atxbXX3oiWzJ13joPNZsPkyS+hsrJC/J+UMeeff1Fzd41pIJ4N7yCS0QWejdPh3fSetjyS0Q2BtqejZpebAIeS4I8TmjIMwzAMwzBMCxbQmfoxefJTcLlceOSRJ+HxKNnnO3ToCI/Hi1tuuQ6nn34WunRpmfWjg8EgCguLcNFFl6FTp85i2dChh2PBgj+bu2tMA3GVfI3cvy/WLYvBjuo97oe/0yWAnR85DMMwDMMwDGMFz5a3Y0jAnT17FkaNGq0J5yoHHngQnnhiEtq1a68tI8H38ccfwtq1a9C7d1+MG3en9vucOd9iypRnsWrVfyJb/r77HoCbbhqHzMxMsZy2ycrKwqxZn4nfhw8/FyNGXCC2pUp9r7wyBTNmvItAwI9+/QZizJib0K5du6T9p3Zuv72uRN6KFcsxZ853OOmkUxt5pJimwrte7+FS23U0anpM4DJpDMMwDMMwDJMGPGtOAmX7q6lp2k99MgySC7vPV4uePRPj8MltfNCgvYUQrPLBBzNwzTU34PnnX0VVVSUmTZqotUNx4KeeOgyvv/4uJky4H3/88Ss++KDOPfnrr2eLtl58cSrOOec8TJr0JFavXiV+mz79bcya9SnGj78bzz77ssi6P2bMqHrFkl955WU4//yzkJ2dg9NO48R/2xOe9W/CVfIVbKEKeDZ/pC2P2Ryo6XEXC+cMwzAMwzAMkyZsQbeABOUTTsjEb78pJd2aisGDw/jwQ5+otZeK6uoq8ZdittPhggsuFkI7cfzxJ2PmzOniOyWTI8FdtVxTHPteew3GypUrtG3z8vIwatQ1IpHfOeecj6lTX8HixYuE+/wbb7wmLOZq2zfcMBYnn3wMfv75RwwZcnBafbv66uuF0oAs/HfcMRYPPPBYWtsxzYur7Afk/jMSMdgQztsbtqgPEU97BNqchED7s5WikQzDMAzDMAzDpAUL6Emw2Vp2wTwSmgkSbNOhY8dO2ncS6slFnujcuQtcLrdwUyc38//+WyGE86OPPk5bv337jlr9eYJc3yORMGpra7F58yaMH38L7PY6S2kgEMCaNavTPpYePXYXf8eOHY9LLjkfGzasF4oCpmWTsXqy+GtDDK6K38R3X5f/g6/bNc3cM4ZhGIZhGIbZ/mAB3QIy/JElu7a26fbpdNrhdkfTNjp26NBJCNr//rsIvXolurnffPMYkSRun332Ff+XBWg1dpxYunQJrrjiEmHtHjBgEM4+ewSmTXvT0LfES4W2j0Qi4vtddz2QkIwuNzc3af9raqqFlX3o0CO0vnXrtouWnZ4F9JaN3bcG7i2KS3ugzYnwbP4QwcJD4O/EGfgZhmEYhmEYpiGwgJ4EEpSzsppufyQD16cEOAnNhx9+FKZPnyZc1imbuwolW6PPyJFXpmzn888/wYABA0UMucratavRtWv3lNvm5OSgoKAQpaXFOOCAIWJZKBTC+PFjRax63779LLf1+/1ivbZt22nrkbKBLPVk1WdaIJEa2MI18Gx+HzmLrxeLSCiv7P86bMESxFyF7NbOMAzDMAzDMA2EBfTtHCpRdumlF2DMmCvF9zZt2mLevN/x9NMTMWzYcHTvrlikU7nKL1++DAsX/i2StM2c+R4WLVooyrWlw1lnnYPnnpuE/PxCdO3aDS+//AL++ms+unS5Lel2RUWtcMghQ/Hoow/i5pvHwefz4f7778Lpp5+JrKz04uqZpsNVOge5C0bAHipLyNROxNxFzdQzhmEYhmEYhtkxYAF9O4eE3EmTpuDFF5/DhAm3oaKiAh07dsQll4zEKaeckVYbZ5xxNpYs+RfXXDNKZGona/qFF16K2bM/T2v74cPPE7HoDz10D2pqatCzZ288+uiTKV3ciVtuGY+JEx/BtdeOEv8/5pjjcfnlV6W1X6YJicWQvfhanXAeaH2cKKEWyVLyBzAMwzAMwzAMs3XYYmog8k5EcXFVQjmzUCiIkpINKCpqLxKmNQcUgx4OR5tl39sL2+I8kUd2q1Y5ptcFowjnGaueQPbS23WLS4b8jWjG1oUi8Ng3Hzz2zQePffPBY9+88Pg3Hzz2zQeP/Y4x9rZ4W00BW9AZhkmKq+w7TTj3dTgX4Zx+iLlbbbVwzjAMwzAMwzCMHhbQGYaxxL1pJvIWnCe+RzK6obrnQ4CjCTMnMgzDMAzDMMxOhL7uFsMwjEo0pAnnRHWPO1k4ZxiGYRiGYZhtCAvoDMOY4ir/Rff/UOEhzdYXhmEYhmEYhtkZYAGdYRhTqNa5SkW/15Qa5wzDMAzDMAzDbDM4Bp1hmATcmz9CxprnxPeK/m8i2Ob45u4SwzAMwzAMw+zwsIDOMIyGd80UeDa9B1f5j+L/tZ1HsnDOMAzDMAzDME0EC+gMwwhswS3IWXyt9v9wdl/U7H53s/aJYRiGYRiGYXYmOAadYRhBxpop2veYzYXKvpMBu6dZ+8QwDMMwDMMwOxMsoO8AVFZW4sknH8OwYSfh8MMPxIgRZ2DatDcQjUa1dYYM2Rtz5/7eLP1Ld9+PPPIArrzysibpE2MgGkDG2hfE19ouo1C+zxeI5PRr7l4xDMMwDMMwzE4Fu7hv51RUlGPkyAvRqlVr3HzzbWjfvgMWLfoHjz32ENatW4trr70R2wN//TUf77//Lvr3H9jcXdkp8a5/E/bgZkQ87VHTYwJgdzV3lxiGYRiGYRhmp4MF9O2cyZOfgsvlwiOPPAmPR3FH7tChIzweL2655TqcfvpZ6NKlK1oyoVAIDz54D/r23bO5u7JzEq5G1vK7xFdf16tYOGcYhmEYhmGYZoIF9O2YYDCI2bNnYdSo0ZpwrnLggQfhiScmoV279tqyBQv+xOOPP4S1a9egd+++GDfuTu33OXO+xZQpz2LVqv/gdrux774H4KabxiEzM1Msp22ysrIwa9Zn4vfhw8/FiBEXiG1jsRheeWUKZsx4F4GAH/36DcSYMTehXbt2aR3H1KkvY9dde6Bz5y6YN++PRh0jJjXuki9gD25BxNsVvs4cYsAwDMMwDMMwzQXHoCcjFgMiNU33Cdco+0wTcmH3+WrRs2efhN9sNhsGDdpbCNMqH3wwA9dccwOef/5VVFVVYtKkiVo748bdhFNPHYbXX38XEybcjz/++BUffPCetu3XX88Wbb344lScc855mDTpSaxevUr8Nn3625g161OMH383nn32ZRQWFmLMmFEIh8Mpj4EUAiTYjx49Ju3jZhoXd8nX4m+AyqnZ664XhmEYhmEYhmGaFragWxGLIf+3o+Cq+KVJdxvK3w/le39OEnbKdaurq8Tf7OzstNq+4IKLhdBOHH/8yZg5c7r4TsnkSHA/6aRTxf8pjn2vvQZj5coV2rZ5eXkYNeoaOBwOnHPO+Zg69RUsXrxIuM+/8cZrwmKutn3DDWNx8snH4Oeff8SQIQdb9ocs7+TaftFFl6GwsCitY2Aal6yl45Gx7mXxPVQ4tLm7wzAMwzAMwzA7NSygJyMNIbk5IaGZIGt4OnTs2En7TkI9ucgT5FrucrmFm/qKFcvx338rhHB+9NHHaeu3b99RCOcq5PoeiYRRW1uLzZs3Yfz4W2C31zlkBAIBrFmzOml/Zs58D9FoBCeffFo9jpppLDwbpyPzv8fE96irFYKFQ5q7SwzDMAzDMAyzU8MCuhU2m2LJjtY22S6dDjvCMW/aioEOHToJQfvffxehV69EN/ebbx4jksTts8++4v+yAK1asImlS5fgiisuEdbuAQMG4eyzR2DatDf1fXMmXiq0fSQSEd/vuuuBhGR0ubm5Sfv/5ZezhBX+qKMO1pLFkTX/yCMPwmuvvZN2DDvTAKJhZC27U3z1tz8L1Xs8ADiymrtXDMMwDMMwDLNTwwJ6MkhQbkqhxWkHwtH0V3c6cfjhR2H69GnCZZ2yuavMmfOd+IwceWXKdj7//BMMGDBQxJCrrF27Gl27dk+5bU5ODgoKClFaWowDDhiiCdrjx48Vsep9+1rX0r799ruEpV3l3Xffwj///C360apVq5T7ZhqOd/1UOHz/Cct5Va8nAEdmc3eJYRiGYRiGYXZ6WEDfzqH47UsvvQBjxlwpvrdp0xbz5v2Op5+eiGHDhqN7913ScpVfvnwZFi78G9nZOcL1fNGihaJcWzqcddY5eO65ScjPL0TXrt3w8ssviLrmXbrclnS71q3b6P6fk5MrstF36tQ5rf3uTDiqF8MWDSCc23+r27KFKpC17A7xvbb7dSycMwzDMAzDMEwLgQX07ZyiolaYNGkKXnzxOUyYcBsqKirQsWNHXHLJSJxyyhlptXHGGWdjyZJ/cc01o0SmdrKmX3jhpZg9+/O0th8+/DwRi/7QQ/egpqYGPXv2xqOPPpnSxZ1JD2fF78j/7RggFkJlv1cRbHvyVrXn2TQd9lApwpm7cVk1hmEYhmEYhmlB2GJqIPJORHFxVUI1s1AoiJKSDSgqai8SpjUHTqcd4Xq4uO+MbIvzRJEMrVrlmF4XzYndvxaZKx5CxrqXtGURbyeUDvlnqxIY5v96BFwVv6K6x93wdRuN5qSljv3OAI9988Fj33zw2DcvPP7NB49988Fjv2OMvS3eVlPAFnSGaYE4qhYgb/55cPhW6pf71wrBPZrRsDAAW7BYCOdEoP2ZjdJXhmEYhmEYhmEaB31ab4Zhmh0SwPN/O1YnnNd2uQKh3IHiuypgNwRX2Q/ibzi7D6IezpLPMAzDMAzDMC0JFtAZpoWRtWQc7JEqhHL6oXS/H1DV8zHU7HY7QnmDxe/O8p8b3La77HvxN1jANc8ZhmEYhmEYpqXBLu4tGFtwC2zhakQzugA2R3N3h2kCHDVL4d30nvhe1WcSIjl7ig8RjlvQndWLGtZ4NAz3lk/E11ChUnueYRiGYRiGYZiWA1vQWyqxCBz+NbCHy2D3r2/u3jBNgLP8VxT+uJf4HsrfXxPMVSKZu4q/jtrlDWrfs3GaiGGPuooQLDqyEXrMMAzDMAzDMExjwgJ6SyQWhd33n/Zfe6gEiAaatUvMtidr+T3a95pdbk74PZK5m/jrCKwDIrX1attZ+SdyFl4lvvs6XQg4vFvdX4ZhGIZhGIZhGhcW0Fsg9sB62MMV0pIo7IENzdgjpilc292lXyNmc6BkyF8IFQ1NWCfmKkTUma+sX7uiXu17106BLRZCsOBg1Ha/sdH6zTAMwzAMwzBM48ECekuidr0or2UPbhb/jTlyEfF2E99t9bSYMtsXrpIvxd9QwUGIZnQ1X8lmS3Rzj8VgC5UmbdtR9Q+8G6aJ77W73MjWc4ZhGIZhGIZpobCA3lKIhQH/RtjoL9nM3W0QydoNMUdG3e/MDou75CvxN1h0WNL1Ill7iL+eLR+LPAU5f12IVt90g6vkG9P1M5ffg8Kf94ct6kM4YxeECg7cBr1nGIZhGIZhGKYxYAG9hWALkUt7VHwPZ/VG1Nsp/oOSaN8WiwhrqRmVlZV48snHMGzYSTj88AMxYsQZmDbtDUSjSnvEkCF7Y+7c39EcJNv3kiWLxe/y5+KLz8NORcSnlT8LFSa6tsv4Ol8q/no3vIXcBedrGd/dxbNM1/dseEf8DWftgYq9ZnI1AIZhGIZhGIZpwbS4MmurVq3ChAkTMHfuXOTl5eHcc8/FJZdcolunqqoKxx13HK699lqcdtpp2O4J18DuXye+Rj3t9S7ImkAVExZTVWBXqagox8iRF6JVq9a4+ebb0L59Byxa9A8ee+whrFu3Ftde27Ljjf/7byV69NgdDz88UVvmdLa4y3Kb4i75ErZIDSLezgjn9Eu6bjhvLwTanAzP5pnwbP5QW27M7G4LliDvzzPh9Cmx6uV7f4aYu2gbHQHDMAzDMAzDMI1Bi5KEyOJ72WWXYc8998SMGTOEsD5mzBi0bdsWJ554orbeQw89hM2blTjt7Z6ID87af+P/sSPqaqX/3WZHDA7YEIm7uetP2eTJT8HlcuGRR56Ex+MRyzp06AiPx4tbbrkOp59+Frp0sYhpbiECeteu3VFUZDjunQjvhjfFXxK8Kc48Fb4u/ycEdILc1kkId9Ys1q2TsfZFuCp+E9+jrgIWzhmGYRiGYRhmO6BFCejFxcXo1asX7rjjDmRnZ6Nbt27Yf//98ccff2gC+u+//46ff/4ZrVu3xo6ALVxV95+MdoDdZbKSU7GeG+LQg8EgZs+ehVGjRmvCucqBBx6EJ56YhHbt2mvLFiz4E48//hDWrl2D3r37Yty4O7Xf58z5FlOmPItVq/6D2+3GvvsegJtuGofMzEyxnLbJysrCrFmfid+HDz8XI0ZcILaNxWJ45ZUpmDHjXQQCfvTrNxBjxtyEdu3apSWg77qrUj5sZ8RVPFtYwmOww99heFrbUI302q5Xi9J7vm5Xo+j7XrD7VgllD+I5CxySwB6z6a8NhmEYhmEYhmFaJi0qBr1NmzZ4/PHHhXBOQh8J5r/99hsGDx6sCaS33XYbbr/9diEkbmuoD6Ga0Lb5VAcRqvIhXFWGUG0EgUgbhKKtxD4TiLu5izh0CXJh9/lq0bNnn8RNbDYMGrS3bpw++GAGrrnmBjz//KuoqqrEpEkTtXbGjbsJp546DK+//i4mTLgff/zxKz74QIlvJr7+erZo68UXp+Kcc87DpElPYvXqVeK36dPfxqxZn2L8+Lvx7LMvo7CwEGPGjEI4nDqx3apVK7Fs2RKcf/5ZOO204/Hgg/egpqYaOwWxCLKXjhNffV0uRyRnz/S2s9lQs/tdqOn5IKKeDsJCbkMUGWunwFG9CFlL74R3oxJ7TlT3fHBbHQHDMAzDMAzDMDuqBV3msMMOw/r16zF06FAcffTRYtnkyZPRu3dvDBkyZKvaNvMiNi4jQXnGCW9j42/r0ZS0G9wBp354lhCw6zoXP00GC3p1tWJ9J4VGOlxwwcVCaCeOP/5kzJw5XQstIMH9pJNOFf+nOPa99hqMlSvram1TPoBRo66Bw+HAOeecj6lTX8HixYuE+/wbb7wmLOZq2zfcMBYnn3wMfv75RwwZcrBlf0iAJ+UA7W/s2PFCaTBx4qO4667bcf/9jyY9FhqeNLzB00Jtp7HaSxfvmhfhrF4oapv7dr2pYfu32RDO20ckicteMjbh55KhqxATAnzLpLnGnuGxb2w8r70M188/ofqJpymRRqOPfdZttyCaXwDfdVufVyTzrjsAtwu1N926Ve14pk+D+/NPUTVxEuBNXb7R+9wkOBcvQvXDjwN2xT5g27IF2TeOgf/c8xE6/MiUbdhXLEfWnbfBN/pahPfaB45/FyPznjtRe91NiPQfkLC+88+5yHjsYdTediciu/VIOvbUdvZN1wFuN6on3IOse+9G4JTTEDzx5LTGI2m/ly9T+n3NdQjH35X1wfnrL8h4ZiJqJtyLaBpha65Zn8H71huofuRxxAoK4f5wJjzvv4fqx59ELCc35fae116B6+cf07qejdC+3LNnofq+h4DMTN1vZuPvnfIcPO++jeAJJ8M3arTye0kJsq+/Bv5zzkXosCOQfc2VCO+9D/wXXGR9zN9/C++U51F9/8OIpeHBlxY+H3KuvgLBo49F4PQzG9SEY/48ZD7xGGruvg/RDh3NV4rFlHu8VWtxjSQQCiH7hmsR7t0H/sv+DxmPPAh7Rbm4HprjmS+u5wm3K9fzwL0a3E7mvRPE39qxt2NHht+3O8bY25rw/LVYAX3ixInC5Z3c3e+77z6cffbZeOutt/DBBx9sddtFRTkJy/x+P0pL7XA4bHA67UJAt9mb/k4iwZz2rxPQHS5QCLrDFgWcdU4PhYUF4m9tbbXYJhVdunTW1svNzREeCfT/7t27ISPDg9deexErViwXHxLOjznmePG73W6Lx7XXud+T63ssFkEw6MfmzZswfvxYsZ5KIBDAunVrtP05HPaEPjqdbnz++VfCPd/pVNouKMjH//53LsrKSkzDGKJRG+x2OwoKsuBNY0K4tdfFNiNQAixTXkj2/hNQ1L5Lw9vqcixglsW9z9ita7cJadKxZ3Tw2DcSYxTBwjv8TOCUUxp37JcsASY/Lb7SpBguk1CodKH8LRMVBWjm+HGk4W14W89MpNgpeC67BDjmmNTr33qT+OMdcTYQV7zj5muBj2bC89FMy0olOo65BPjjD3g++UhZv88J4pg8fy8AVq9OXP/ow+jFAc+aVaKvScf+2Y+Bb5SSl4VLFlMMFjwfzEivX6k4/H/KWH01myYc9d/+eEV54amqAL79NvX6IxRh0tO9C/DEE8BFSnUUz6D+wPjxqbcfc5X44z3tZOCss+rX1/i+vK0KlH2boBv/W24QY+z6/TdkjY8rjW68uu66ePdd4K3XxSf7uqut93uaEgrpcdmBGTPQKDz6PDBjOjwzpiNn5MUNa+OIQ5R+5WYBU6ear/PXX8Czz4ivWXffkfj7s88Cr78qvpKgjvvvFt8zrr8W2GWXpn/mH3IusHAhPJ9+LO6vBlFaCjz2sPiaefutQH4+dnT4fdt8FG1nY99iBXRKFKcKetdffz3++usvjB49Gq1abX0ysZKSqoT3bSgUFJbkSCSGcFh52JzywZkI126D+uOxCJzVf4vM7JHMXRBz0EVDgrkNcDtEH0TW9jh28Q+IRkKIxvtGtG3bQVjPFy78B7vv3ithNzffPEYkidtnn32V3cZs2rFFozGhhKD/L126BFdccYmwdlP8+JlnnoNp097Ufqd1HQ6ntq1KJBJFIBAS3++66/6EZHS5ubnaNrSucXvC41G06+pvnTp1E383btyIgoLExGY0NnSeyspq4HIp+95aSBdCN67ZdbGt8K6aguxwDcI5e6K88HygWMpFUE8c3gOgqGooW/snwuMinL+vcmBb0W5T0Bxjz7TcsbdVlCOWt20mabaNG4XVNtamTcMbCQSUyWiGkutBIxSC+maqLKtGaPka3XHY169DzONFrKgo6djbqioRy8wijaaueceajdo9XrJ0tXYMYrxy85Kr9aNR2KqrlPWoLxtLUai2ta4YsfwwbL5axLLrP3kpqKoG9bRq5RoE0njWqGNUtew/BPZS1s9duQpqIFZxGm0ULlmqxebR+q3UhLFr1phu3youPMT+/RclxVV1Y79uC2LRmLD8i3HML0Dm5lKo9t7YmjWa51Hx5grN4q9RXU0vMHNlCQngdGKl66SVqhwIBPT9DIWU6yqFokQdu8iSpShTt6djo30ZrNTy+oE161BF4xT/v2/tBtTQ9obrQr331GtQXb967Ub4rc6LxRio20bffAultymCpNhHVaU4zqLWebprv5V0ExRvqRTXc97fC6G2Wv3fWmSncY2o+w0vW4HyRnr3Za5YpV0T6VyfRmyVFVBnMoHyKnEuzHCuWAv1iVG8sSzBayH37Xe0+6RkxTqtzbLN5YjkJukXGZvi17d27W8sRcxvfs3Z165BLCNTe1ZZ0WrhQq39hoyL2Nf6zXXPok3lAF0TqZ7/dM2Rcaa+1X4ikQY/53bU9+3Ogq0Rx15ta6eLQSeL+ezZs3XLdtttN4RCIfz555944IEHMHDgQPEh9/fx48cnlGBLBzpBZh8jZMV2Zbka/eP2BODKtMOZlQlnbhFcWe74b2695VzD3MWdypEdfvhRmD59mhgjmTlzvhMfKr+Wis8//wQDBgwUMeSnnnoGevXqg7VrV5vHwxvIyclBQUEhSkuL0alTZ/Fp27YdnnlmohajbgVZ6Y888mCsX6+UmCOWLv1XuNF37Ni5QeewoZ9t0ablJxKAd+0UsU9fxwtEgritaS+c2RPVu92B6j0eQKhgCEL5+yEGW9Mdz/Y09vxpsWPv+mAminbrAu9TExu/7S8+R9Geu6Owbw84v/+uYe1EYygc0BtFPbsjFgjqfrNJVUXcn32iOw73O2+jsH8vFPbeFfYFCyzH3rZuHYp26YTcU45P2LetrFxrn1x/aZnjz3liP9mjr0ja75wRZ6Jo187CJVUsC0nvEZ8PeScdi6LuHYFNm+t//QSDuj4l/YSlHCq1vrrlnjpPqLT26axTXqjjSEQ6dLS8xsW6bk/dskgEBf16onDPPYS7f1GPrnB+8zUQkCzbkgBgW7tW3+amzSjq0QW5Z52euM9QGIV0rQ3qK47Z2A/jceYfNgRFe3QDKiuTH7fUL+3cXngeCgf0SuifvH7Um6E759HsHGXbi85XroulS5Fx/z3KNfvkE+IazL68zlIcc9TtT9d+RQUKB/VB7mknWu7bvmWzEATFNbx8uWg75xzFsq+tH9Er7mPBkNJGKFi3TFqH7sNUYxSzNd77T7KVNGh7cV2pY9+mjfV+/L66/RieL/Rx/fB9XUfK654HMZ8/6f4zb70JhXt0h/OnH7Uxyhs6BK26dxDtyOt6XnwBhQP7iOekfeHC9K7HrXmH+Orut6xbbxLXIIVmWO6zslLcK3TP1HdfeSccLZ5ztg0bGu3a2J7ftzvbh2jMtnY6AX3t2rW48sorsWnTJm3Z33//LeKfZ82ahffff1/7UEI5sqjfc8892N6whSvE35gzPS1MTM3sHku0GF900WWoqanBmDFXYt68P0RM90cfvY977rkDw4YNR/fuqV2faHyXL1+GhQv/FkL1k08+hkWLFgqvgnQ466xz8Nxzk4RCYM2a1bj//rvw11/z0aWLYg23omvXbujUqRMeeOAerFixDPPnkxLmHpx44qnC+r6jkrniQThrliDqKkSg3bCtb9Bmg6/7GFF+jWG2V/IuVtxis+9UEic2Js4F88VfWywG5/w/G9aI3w978RbYamvhIHdpCfvGDdp377Q3dceh7TsahWv+PMvmKT6YcP/8Y8Jv9rLShO+Zjz6k7I9cf5Pgma2Ev3hff03pB1lr49j8Prh+/VlZ7/NPUF/UtmxS/yzx+XT7VYl56pnwNR4OJZBcxaMdOyXfTt5PeTnspaUihjfzycfEoqy7xsMmCQzyODmWLdU15Z3xDmzhMNzff5OwG/umjbBT+3StVNQJUqZEoyIm30bhZnP/SL6utoM6BYXnkw9hLyvTrgVTvF4hKMv/F9t+rIQLel98DlmPPCC+Z0+4TVkWvxaJmMGbQ4Vi/2nfrnmJ/Y5JFnX1es2Iu2dTbLoOg7u/LRi/poLSfEd2oZbOS5MHiqaR+NaIY80a7buNrL8W2Gp9CWOg/b+sVFwjKnZJIUjPI0siEWQ+P1k8ezxvv6EtpmuOcP2kf9Y4FyjPRrq2PTPexbZG7rt3+jTxN+v2xFw6Wv9++1W5VxYtrLek5Pr9V/HXTaExDLMdYG9pbu19+vTB2LFjsWzZMnz77bei5vmoUaPQtWtX3Yesx0VFRaJG+nZDNARbqEx8CErelRY25WVniyYK6FQ/fNKkKSJGfMKE23DeeWfh7bffwCWXjMSVV16TVvNnnHE2+vTZE9dcM0q4um/atAEXXngplixR67MnZ/jw83DCCSfjoYfuwYUXnoNNmzbi0UefTClkUyw5JYOj8m1XXHGpqNu+9977YPToMdhRcW/+BFkrlclUdc9H078GGKalEY3C+8qLcPxD4TrbHltpCTKeewa24mJ43ntHJLBKe1tZOJSqRFDiLc87b6XXhjxpNlj97OQ+b7WdpOikY9CYNUsk00pr3xSrafxumMSL3zZvVsaoXHnHyMRUy7MkEOkm9xaCWFLiQgMJu/U7BzV1P0gW9HSISZZth5TINJajV3i75nwHz0xJ0HRJArpJDHissFCnOJBxLNcL6Pa1a03Xo1CGzEelqhlxy7WL4s4t3J+1/WcojtSu777R9Tuhn474tE0S9lTBykygjXkzdAoko0CX8drLlvsSx1RZgczHHxYKDE9c+SRf80KRIY9nIACb5NGn3W8GLz/xW3kZMic+ol8YCCZe37G647HVStdOCijpn/eFydp1qhEMiuUkrHlfekEIspZIgqB6vqjfGZOegi1uTCIPEnHflUj3N53Lb76C901FMZZaQJeOS1JOkHCePe5m/XFt3pjWeDj/+F37HunWPemxGe9Rz+efKm38NR/e114W4RB0jHSN1xf3h+/DObeuL0mVCxbx7HQPet+aqjsXdK9Q20aojxnPTxJ9TvzRXu9nP8NgZ49BJ9fmZ555BnfddRfOOussZGRk4LzzzsP555+PHQGHbyVsEeUBHbO5EXOkl5wnZpHFXYVcym+5JXkGzDlz9A/H4447UXwIGmeKITdy8cUjdX9l3n33Q915u+yyK8QnnX0b+37vvUm0/ztYzfO8+WeL78J63uak5u4SwzQYEpJzblCUgFs2VzZauzFjfHec3Msvhvubr5Ax8TE4Nm+q334lwUueJBecoCTeKtutR+pMxBSzqWKY8JPV1BLZ8qUKsjQxPvpokAqz9KsfEOm7Z1Krn86CHhfyZYua7IXg+uUnIZxWvmqYfDqcCYoGUnaoxIwx1mmgWTvTEtDrJuOyAkF2cRfWUYppToYsoC9fpt9WJRJB/mkn6LeTS7PKCoI4lD3byjrrWPWf/v/rJAGdzmX83OWdeQqckmJbjE9VJfLPPs2ws6gQFHTjRsuo32co74WS/gMRNROq4sfvkIQ0JyXIk8ZOVkLFMrywS16JRqFF9hQwI+OZJ+GQhLKSwfuJftk3SUI/uefHLfNGIVT7fzhRQM8ZM1pJAievHwwIr3LZgq7zbKitRawweXy0ej7o/rYXF8NeUqKrWJD51OPIiidZI6jvgeHnmjclCZHiOAuLkPu/EXD/OAfO+XNRNflF5F72P7i//1ZUNKiYHp8bBYPIP1OfLDKpgE7x+YYxUBPGeQ2CpEN63iSzoMtKTE1pIgvlBmHYJilanIv+EfdpweEHKf24YxzsVZXwTHsL5bO/s9xnQh++/xZ5F59v+rw2Uy7YDMpPlcL99c9nune0e2XeQp0HTf5Jx8CxepVQHlc/riTX1Ig/5+r17GeYnd2CTpBF/KmnnhI10OfMmYPLL7/cNC77q6++wmmnGV56LZmIXxPOxX8zuqXvhhV3cbeRi3tTBkAwjYZ39WTkz6u7Xn2dLwPsLUo/xjD1osGu4mZIQkLEwlWZhHNCFc7rg859VBJezCyxlm1I8cnGSbEsrCRsJwnSmiu4tMwooJi2IVne1TbMBHQSzkWbn31iKdjJApmsWCA32HpB76J4W7ICwfIYpMm/bHGPuV06ASjlbnUCep1lW7Z+U6KrhO3kRGYmAjqiEUsLesL5Xie1L42nLJyL7YIBnRJEWx53fZfHja4vu5S3xbFCUj7IxD0ddEJ3JALHfystxtGmt6AnERJNd2ewmKru8g5p/2Rlt1QAxPdHbtNG3J/UKfoTxlPyPLGXFKfn0m2AhHPC6JFgdLN3JQkvsFHWfPk4YzEhnCvtfKH8/f5b3V8zpY5oq8Y6mZpdPmfSve2e9VniuvK5T2JBt9VWJ1rHZU8G4z0v52AweLqQcE64jN4aKaAwDK09g2eP6bmUvCWSQQK41k5FhelvHnXs5HmzQRHpWLokrf0xDHZ2AX1Hxa66tTtyEM7uBzjrUdpGWNBJmKcMBdsgqzyzTbGFSpHzb13t4srez6B2l1uatU8Ms9U0wOKqkn3tlcglq0p84iQLF7H65J8IBpF9y/VKWyYutKbWWzO3R5rMvfMW8k88GvYN683bkGO3DZPiZC7usquuZv2WtnfPiVujkuhrZYFW+y61m3/0oeZWfEko0gRbWVCWlB2uH+eIdtIOHQiHRUy/rk+xGHIuvwj5RxyM/MMPEu3lnXq8iD/XnQNZMJUspfZKRXB1z/5cbO/4+y8xgc4/9jC4v4wLVZKA7pRiw22Sh4PRJV38LifHMxHQSaiVlQi63yj/wIb1yD/yEHjfeA0OycVdE+rNlOeBoCbYyJBg7vztFxQce7huH06p344Vy+s20AkYcQFdErrF+vJYSAILCYo5N16rF5iTuXSnQBW4dUK/TkC3sqCbzF1MMuAXDe4vkoA5pPtQ76Jfo7mv0/VFSRkTO6n/r33LFv0C47NCSjyY0JQ0lnSNyOMcGqxUyDHDmLfAdGwqK5B/3BHIP/ZwZN13V91ySUA3s+4mC1nQta+GCxDqdarzmIjB++pLyD9mqAiPSbj+04n3TwE9V3RjQokpTzlOhIKYKhckpUHmfROQd/pJiSEKxvG1fBfF7xv5uIzrmtwL3penoLB/T+SeP7zhJeS2FdEockcMQ9Y4pWRlKnJG/x9yRl6YlnGPvDXIC8h4r5IXBD2PnSb5JrYljkULxbPA/dFWltem83/oociI59rYXmATXhNhiyiTwijFHNfXcmqzCzd3xYJOL5atqIHLNCl2/1oU/Hyw9v9Q3mAEOpyz7ZLYMEwLF9BFLGM8YZT9v5WIdt9Fb8mVXclTQG6YGVOeE99d516A0NDDzfcpx12rk2TDhCV31GXib86oy1DxnkkiIZ2AbrColiXGfJsKoHFBVt7e1FJKEyRJEDV1cZcm3655c5EpTfDr+lmT6OJuYUFXk9vlXH4xSv9UkkglRR6PeJ9IiPW+l5hcyvveO4jsupvp8eg8E+JWxLxzlOSZ5DpMydYo6Rq5FRev2aJ3cf9X6qdk/XbKru9m1ksTK7KdBDGLa5qun6zbbhFJ/lzXjNKFA9B4CpdsoxCoWtCrEhVC5J6b+3+GCjQBv04o1R2DpFBQk7YZlUI6bwLJGmu0wNL1LytL0oVCAETiO1MBvTKJgK4cvxyXrh2L02XqYu8il30J3fMhfu+Q27e47h+6D8Fjjkvad0oGqOuTIX+D7JWRsK18bBUVcErW/GTvcV34hcXYZLzwrJa8TLeenKA3kqjY0I2HmTeIihzOolrQZWGXFGrXK3XlKReAUUBPFf6QklgMDsmrhMbE+e9i4YFAn6qHn0jcRhKIs+I10t2ffZywmvzclJ8hxv0bfxf3riSAml2XFHNP9yJ97GtWI9o1ecLjpoTyTXi++Fx8r7nz3qS5Q0gBpCYRrbn9rpSJNDMnPir+ur/5EsEjjtaW55+uhMPmXnQeSufFy+s1AZlPPCKeBXkXnbtVYXSe96cD336LrG+/Re2Y9BQbLQG2oG9rYjHY/evrYs/TzNyeQDwO3RZlC/r2gmfD2yj4cV/YQ8oLvXr3+1C+zxdC4cIw6UJur2aT//pC7oV2OXa2oYRCcCz8Rz85jUSEW7GZO286k0vdhNnCzdgMz4zp2neyumr7WLFcF9MJnQU9iUVPtmgb0AmSBjd5K9doOnf2DesSBFldXKv6XR5Pw8TYzMXdmCTOzHXZbPIuj7XsKpuwDblN/7XA1IJkX7lCCGva/9U+WVhmhcu5lICKYoI1pP7QBF4W/Kh/JJzr2paymMthFsmyrmvHRQIDXbtSmSrtd7peLCb6lHTK/eUXdevKYxI/Ltn6rREIasJruGcvhPbsr7RXWqJLyCXa9PngWLbM9BjsJmEZCRZ0SSBUPRHEd4MF3/n3fNjX1S/RFwmw4d59lX7G+6K7j2ULuvHeKCtVjsXMw0UKb0iGThkQb18V0Fx/zReWPbnUoangHAqJhGfivk+wyJqsHwyKGGbdsVVV6hLBWVqvw2F431CUkLq9VFcrz3P1nFh4bNC+adzEuvH7uuqRiQj36p3g+aJ5FGzckOD9IyvxtL7KITdyMj+6VhME9MT+RQ310ZMpN2jMKfxCxfv2G7rrw1S5YPK8MVtP9p7R5QcxQXdcJLTL/zd5D6hKUPG9vExJhNoU4aWBgPAa0iUmrCgXz1sNSSCXn8HpJBdN+ziCIaUfhue5WQgS3dvyPdKYxArqkig758/T3+P1IYl3XTqI+9CQALIpYEnBQDq1v+uDLVwFe3CjlhgOdk8DG7IutbYz0djnZ1thC5Yg5++RsEeqELO5RI1yX+eRbDln6gW9+Ar36YdWfXbdOle7WEwk+yncb2DyhGZpkDPqUhQeur8uOzFNDIsG9UGr3ruknADIlj9NsJMmWPWx2qiloghVgKIJQ9F+A1G470DzDOKqIJtkP2YTAb2Lu2FibjHRLtp7T118q3q8ukkqtUXnVno2GC18soVeFW4TYtDttqQWdK1Nqa9ysimVaPv24m/mg/eg8PAhwoqh283KFSjad4BwRdbapjbpOCyUHkaBVCfkSOc+94pLUTD0AFPhMtwvvr9o3aRRdbFX2vGZu4dLffROfQUFh+xPpUfq5eLu+uM3UyFZvi5M90kW9PjklXIrxFq1UpaXliLSqVNCO7JHgJwXQQ7LUI9TvY9DAwclWNzNJtLhPnsq25WWovCgwagPka7dEM3P1/VFfo7orMyGccq6ZwIKD9hLeFHUdSacWDIvzWeGeu/JyoyCo4ei4OhD6zage8kwKc+641bxDFTK6RmUIybnNue60SgceoCw+Gr9IGFJ9v6wuCYynn5CL0Cq29Pz/IC9kHvp/5QFFsIt3dtFvXcVzw+1nWiHDloCzQSPAlq/3x4o6t9TX6VBtqCry+XnmPRdtG1UNMou8irhiF5wk5MvGo/D4KlByk/PW28kTxKnvufke9vkuSIrpIzPSw21Dd2Y6BURNpPkhfI5zhl5kbgOMp4ysfY3MjlXjkThYQfC88EMbVlR/17ieasJ6bIHlEFJl+w48v53jjgOCmkwRbpfMl5+QfQjY8qzulViWVkJpRbpes4/ObkHS0OJ5tcJ6AVHHoJWfXdr2Dwo7j3WEEg5Tvdhq14mCTu3MSygS5nIiaDVjd5AbHHrKRH1NLwkXEx1i9/JY9DV8+PYihuuKXBWzYcNyoOkfPCXSo1yTgrH1BOydKlCiFmZmnShF6ljzWoxIXPOm7tVfVJrJMtWUOfCv1PGeJtaw1SBVbZOm1mjLYR+ORETHR+9vN1ffZFgXZDb1FxudWXTIjq3ZdmCopFEQLd0sTRgI8stTW5rDAI+CQxS9mKj8K1L1qQqD4wKBsmybNpPtWa5hYt7XfubdO6lcmws4f7he8vJoFniOvU8yZN1Erw1bwLD2Oms6/KxxIUFo3AVzY57pcmZvi2yymeNr8vkndB+RUVC2+mgXltmFha6xtQEarG8PMTifSXBLtqhU0LyNdndWafEkM6/2kf13IUHKAK6Tap1bkyaRUQ6d0FDibbvgFi2kjfHTgouismXlEa6OG2DJ4epYiN+negS9yVB1wZd07FYQhiDLrO+iZKC6oGLv5Oe1NeFt1BokLXXVIkjC+gWFnQnWR8tEHW81Vheq+MnITIuBKt9jWblaKX45JwUJOTKOTx0iiKdi7uJBV16VscyMxOUo2YKCOFFIG8nly80rmtyP8nhC6YWdDVJnKxgMbGA6pLEpXJxlxVvoaD+fWA8h5QvQ1rmjI9n1kP3YpuXLY0nMyRFYl3/lDFSc4PIY5o094n0ftXej3T9W8Rhmyk4qe58MgFdVSQ4//lrm8Tq28ws3w0Ju3BJc2+Ld5QVuuSbJuVLtyUsoMex2x3IyMhGdXUZqqsrhSAYCgW36hP2lSIcqEAwYoPPvRuCtryk6yfbZzBiF+1sbZ+21w+NDZ0XOj90nqiGekvGWTlf/PW3PQ3h3AHN3R2mhUP1dLNuH5uY3Ep66Zll801JOIyse+5E9m03J2SQFjz0ENxxgXtrkCe4ZB2i2PK0LOiqNVgWfiVBS1tmkmgrYR1ypywt1WJ0dRM0kxrcsjApLLzSWJvF6CZLEmfWZ9M+RqNi/BO2pwmhHHcaCMA75VkRD+769mu9ezhljI/FEq1Gdrte4KE2JUVA1qMPipJZ2TdfZzr50Jqhyb9hEpTx9MSULq1iDC0mymTtMlqnNQtomhMuTSgwrB84RamOIe9bxJOb9TGJ8oiEwKTxvFbEPQDkTOZ1nQtqwmssJ0+b4NqMChqR0fwjYSmMFhZq/VEtzbLQ61i7RljBVEVXuFcfvdDm9yPnlusT2o907YqGEisorBPQV64Qng6Wmc5TKOh05zCZe7QFdO+QkJG0HrrNpn/OpZj4G2PUraA8DZnPTUopoDvUcxP3WjAilBt+v4jBN+2fyX1E145ayk5Hba3OmqyzLMsu7hXlyJwwHvjyy7p+bJAssB6PJqTF4uX6zBIc0jMs+3qlvKYZ7g9mICMey6w+t0iJVjl5SmJbZgJPXDGhE6JN4vB1WLm4awK61Bbdk7JCOH5vUaZ/spJbVqSIRpH5wD0ilMr11Wxk3n9XWskWKRkklaiTn+Gm60kJ2MJ9+yX8nvXgvXD99IO+WkUqC7qZ0tCqz7KCM/4sM3qBkFLM+8LkuvXkd2hjhM8ZCSYK02YeDwnEYsh8/GG4P/4w4Z2V7Lnh/HOumIfJzw5ZAWWWV2JbwiY9idxc5cVIQmBjYAtshi0aQMyZjVggdZskdEYttFC2UCVs4RrEHFSWpoVllWxCSDhXz1NLt6AT4Zw6N1CGsSL36v+D+6vZIkN0ybK6Ek6yEEZutvWFJvIJLspxy5uD4ndvvFHU4t5y8taVrJSFbjoOyqpe/qWFpVWOMVYnQ7LQZTI5TafOtta2nOOBhMKMDN1EWlgADfs0WiLMXJ2TlVmzil027WN5WaIFvrZGN9lxLv0XObfcoHxf+Lc+A3ogICa2CTHnpLSUPA2EwGyYjGTfYW1B1jVlmPhl3zkOwcOOQIRiYK0SqZFyJDPTvD3y3jBM9imGODx437RDGlRrntHDInDiKciY+oriBhtPricLjPUhVUxnUgu6iYCuJImr1CzoqFbGTpwXwzVDsdTieE49Q0t8SNuScGz0SqHEXrF4SIQmoNOkMhyG++s6AUwmujUW9MIiTbmQ8ebUhN9lhUhaZdzoWnc407ag6/ZVXi6EFSK8+x5C2DVaxMV6aSj16qMANCudpt5f5H0jK/jU+yfSpatiXTQ7DnoOW7m4m4yhUJDELej6PtTq8hVQLgTtSSK/P+b+kVBOThezTuckLuhG8/JFOUursoeqpVfsX1YURqPIu+QCpbmhR9TFS3u9iOzWw7IMno6o6pYutSsl2jQjpQeTHEJFilBZGI3fW2rYQTQehpKwj2AQWQbrc7hPPwRPPDnprguOV+qtw+sBHnnQcj2X7CGnKmvlvBrr1iL/5GNR8cIrDXJx17BQdug8nOI5OkSeB4NAnzP2RgSPPEYkzpNj4+ka3JpnjGmfQibW7hTXAuH64Xtk3TtBfDcml6P7JSa5zssUHKWEycQKC1F7zfUJ1zcdY2TvfdBUsIAuQfXW8/KKkJNTgEgqjV2qtkLlyP/tEuHmXDboI8S87VPsGygoyEJZWY2pN6dnww/IWn0fggVDUd1LcT3c2SC39pZuORfEonCV/yy+hnNZQGdMoJtcijl2/vF7ohWO1pFeRlbxsclwylmuDS91OdFQffub0KahDrgqbJhtb9+8MdHFXY4JpAkBWbikybupy7ncvNerlMKS2hZtVVYqVifZgk6TarJky9p/Y2k12YKu9l3uI7VBwiA9j2hyXp9zU1NrIqArcaQq7g9n6qzc6uRfFQSEy7jR/S8c0sVqCpfzetSMlnGZlNMhxULEIsZc3V/UIqMw9Vmu8a1aZwLSJDRwwsniPFgporR62oaxDg3er24dvw+xrOy06qknI7Tv/lpN+VSowoG6T9/Fl2kCNh2bujyamwt7/DzSebG6ZkL9B8JL7sa0TqUqoJu4GscnCpGePeuWletjpGUinRtuQY8WFiCWZZ3gVhxj/D5R+0oKBDlHgA4656TMaYiALgnjlS9ORcztFhUYXL/9IvfI1M3fsv/GddO8n7X7i657KXZaVYJGOna0Pg5K0GiRvEqEwhig8Ag1Bl3fhxpdRnPNykdu8mYx5FbhRn5/nQWd8g0kEdB1yIpOyYpK7zLV4k+Ku/AudVUctHXkjPgq6j0iW70tYv1Tui3HLz+dUo/uSV3CTyV5pIpzcRoVLNJ8L8mkDC2TlQbx68r0vpeVzSnyycjJRXU5BMzWNbHwi8SVUg4Gbb8lxUJAly3sdA2aVlFJMXcwRd0mGDIV2mMpthNJSeVtzMLT1H2ozy0pEa8uZEe6R00rrmxDtgNpp+khIdDlcm/VJ6via2QEV8LpzoEzp2ta23i9XsvfnJ5MeIOrkBH4d6v7tr1+tgvhnCa35T/DEViPqDMXofy6hEcMowqlhXv1RdatN9YtNExUXV9/iaKe3eB9b1rdQjNtcirM6seqmbvVWD8iiaue563XUbRH16T1sZPFwmU+fD+K+vbQBDSji3v2TWOQPX6sbpuiPXvo3Mws3Q7V7nffRTm2jRt1bsq5oy9H4cDewhokk3fGSbqJpS6BlXiJxycr1dUo3HeAqCUrC/QkgLXq0kbUyqVJklUWdzNoX9SeDLmdZz1ep3j1SHVfZUFOO06TSaTW5ziu778T5WkaguuHOYn9fvUltOraFrlXjjTdhmKmk1myjO70qtVP3YYE29oxiteAafs0DqQgkMZDxJ9LQkvh3nsq/diKOt9E4IijEpZFs7KF8JxAvD+qBT28Z38Ejj5WWRYMatblWG6e5mEgC+iU3V2GLI3RHPJrAbJvuR6Fe/fTlarS9YmEtrx8YfHUvCYsXMy3JgZddnE3g0qeiXucPCXi+4+2S2KUUO+lBuSSUStFkGAe2X0PRLt1h+9Cfck6x6qVyKd7PE0oyZ2HjoGecz/9kHYiTXEO6VqTFFN0HajnNppEKUJKTeP9EjzwoHh/EpULNP4xr5mAXqsXlJYtFc/U1p1awf3d10n7T6XOtHYoxCOugKNrVTmW1K7/QnkY3052AfZMexMFxyoCm1AsZGcjYrgmTAXIaFSE9VBiLm29FFnCrZRd5FVCddR1VTMoFMpYdlNWbNbDi0YoMtKFBL2PPkJh712VsCXjMUjvd9Uzw+xelnMMpLSgm3iemSXcE8st3mF6xVd8Xbp/SVG8sq4vpkkR161F4Z67IzPu8ZIO4j7s1R3On38SSucErPKcrFiGoj67IWPiY7p3dea9E5Bz1f/pvdWKi8W8gN5nYl9/zoX7y1naOtGCAri++0bMwShko+4YWUDfIfBsUk5qoPUxjdJezKW4ddtC6bl6Ms2HZ5NS+inY5kTAYRIzxuzUiBqra9doSYsIo6snuYiT62bGSy9oy1JZQ8wwcx9WX+o21ZWQSOJmnDv6/5Q61CPOtFzHOKGV48DJHZWsXplPPKpZYuVEP/Ixau2VlupKqJnVkpaJdN9VOza53jW5+zrWJ5aUomzCptYbw2TF89nHQrAUtWQNk2ma6FAWdKqxWp/a7ZlPJ2YDdv/0g+7/phN0CoHq1Fnp1yeJddqNk9h03dlloq3biL/OxYm1br3Tp5kn7ZGVKEnGQRXQw3FXV9Xapl6jFPca3jXRDVbGVlamWWUprrBi5ie62Htx3UiZ/VXUEmFWBPfTK1L9Z58rSqKpfRVkZurK/iQkbdMs5XmAO16tRXZxz81FLDOrbgIeFxJIwJahevHCHZ7O8+xZcKz+T+QPMCParp3yNx63TmEGqoJK9EOCMsgHDx6KBru4mwjoqiJBHP+Wzch64B44427U4d6K670p6vOmAUpHVYCSwynU+6JundTlHkNSnC/dO2SFp2cu5X0wKhxVBYila7CUoNG+VrmuKeu9/5xzEWnfAf5hZ6P2/64SmfxDew/W4tSNz2d1jI0WffE89XoRy6wT0INDDlbWra3RZ9TfsgWe995NefwJxyEpRKPx688ql0MCaiUDKYeKHAqhKhaiBo8Cs2ewLRZF/rCTkwqaob320SX1TKYYdH//jfjo+qqLQa/SW+uTvBeMqGEm1itImehJaLz4YnF+jMeXkNBPtaCblZeTvNNSWfDpeZm+i3v6AjpIyKVcKrJnmkkpWMoVQcrxrIfvR7qI+7C0FLmXXmCadNTU7V1UabhNPBuy7x6ve654PtW/K2lsM5+ZKOYF1H/aFynMZcUHrZNz7ZXit8wX6jLZ29fpLfPbGhbQtwEkRLuLlUzCgXbWk9r6EHUptSftwaavxcfUg1gM7i1KPeZAm/Q1+EzLhl6KooaoheZWaHvV//+7WCSGMYOEEvfsOk2thjETrtPEVTgUFJY0q7bFvv9aAOeCutrQZi6U2mROTopmMsGhetGkWda2I0HDIkdGgsWJJi6RiE4r7frtZzFWcoIs169KKIgpsntsigQ7kV1kAT29RF9yFuC03P0s2hXJ+9KwoKvCWX2Qk9tQBmfKpq0qDowkUzgko/KpugmIJjwbXf7TgARwz0czrX+PxyuqXgB0ruh61uJ6PR5Eu3RNGpcsW7eKV24Q1mpCVhx430qMkfade37Svle+os/YTYI45VComPZ+3bLMTCGoJhwXKXCmvqJdy0IQj5eeEgmpKqQs7nGh0jXnOy2btVq+THwvKlKs1ZLgmwzVSk0xk+LY35tW52IeX6atW1CIinfeR008tpLwn3p6glXTDGpLzUCvwyCgUBI11/x5QnAJJMtrEZ94p1JsRTp0tLT6yveTrChIl9oxN6J4saI0kgVlx4b1cKxZZaoIMaWmVnefqhN9OjekfCmd+w+qnn4ONXfeg9J5CxEatJf43fnHbyLZmP7gPKbKNjH2NpuWxZ0I91OSzyqhEBWJ4Tf1RI07FvtTFUTT9Z5FVog4XZ8PWRYx1qprvjFMQt6nhsk7xiiI+s/7H4pXrIf/9Pj8OhAQzxPh5WUSVuGWPZIoi7vkTu7+9mvYV6+u21c9am2nCm3S5TagMWqjKEAFhveJTQ5nq7F2cZcrBKQKQTAV4K2uDZPEqGJ/JvMNUkYa2zYtmdeQjOvqtqGgeQhIfJzo/pE9yXReEtJYGhPlkZeHZ8a7Cd5ncqJI8f43uw5TZM1vbFhA3wZkLbkNtlgIoZz+iGTXxYc1igU9XKZ3TWVaFI6af+Hwr0bM7kGw8JDm7g7TCJCGXdQQp/rMJi+3wv0GoeCko2GPT8wKDt5XJIYxc0stGtgbbhNX8ZhbL5SYJTGhl13hkH1E26YumPT74UNQcMTB2svf1IKubiu9/BI01dGoqHWuJk1JlQHVWE+brMsZz09C3vAzdLF9NFa22jSSSIlGJbfRJAI6WZcoGZMmoKeTpCqlgF6bIIComZmNuL//VpcgygpZEEsXNQGYICMD0bbtGjXBmSwwy98bkpGXhDOysluhup1HunXXciDQ9awS83hF0iz1dzNUJYSwXFnUX3bF8znIBE88JWnfSSBWrdBKI666PskCelGigE6Jo3LGXFW3Hgni8SzYosxa3GMkmlMnoMvXkmxBj8TjdFUBKRXRNm014ZvIeHmK4u0hWdXF96xsoQCh61lV8oj90PI0MqlT+2YW9HB/8wol4UF7a14tpqjPmxRlbSNJPCpkC3q64yUT7dIlwXtBxfOpXgEWGrS3pdApnomSUKh6ikTbxO9VQ14Gdbn3vXd1JcdEm6pix2hBV8deuubD/eLKqZoanaAmXHgthK10LOjUB9XinW52e3p/ZLz4vPUzSI1FTxImoWHyLDW6wouxJ4+WnHjZwkAAueedjfyTjtEJ46bvJ+Hirn+f5J13Vt26cSspeT6kwqqsZF2/S/XKCKmSQoJyWmdBT+LiLh1LKgHdzIIunsMm8wKrSiROKRGcvF9j4lbTfCdbE2pkt1ta0Ok9T+EThQfvW3fvyZZ1OVzAcO2QZdxYkhHRiP4e8vus507boJycFSygNzJ23ypkrH8NMdhQs3vj1U2MuuMCeiwCW7hhGWqZbY9ns2JBChUMARzmGY2Z7Qud1tSoMZce1s5lS5TkY/EXhufdty3XTWVBpxgoI2odUysBSo7TVgUZ0zq29OIJh/WTOMNxWQniZsmLrF7O3ldeNF03HfdTpZ/+9AT0zCxEunbTrFfJBPSKqXXnxL5an5GZCB50iD6uWGpLV5KoAVY7q8yxluu7XIjstptuUmomIKaqH56K8MC9UD3uTlQ9MlHr49bGcGtt79YDtSOv0C2LduoilCrGBGKqUJtMKNMEAJqgp3AvDfUbgJoxN6Dy2ReFYqPq/kd0CeV0OJ16N2a17QwpRMnuQDjunpwMcV2oglZ1tZawSAiEJl4UsuIm0qmTllAuHbSM01JsslY3Oy60GwXY0D771jVAFQ/SSOBkFNBrbh6n5Ay44RbT9asn3ItYa/Ns2IL45DdV9m11POTwCxV5LMlrwYzaSy9H1cP6kJLaUVej5saxiveFw2F6TpzxevThPXqi9orR8I9QMpOriHuFlBuqBVsSrtSEmVZKA7MwCe23+HVjFIw113fpGa+GbZCiS44rFv1pgBChPtuFcB6/F41UPvGM+caBgOYhY4Zq+U9HQDcTyowu7qoCQVOE+f3Cc4MwVi1JaF8kidMLXxRyZtxXZLfdU/Y1VfUO2coskrJKoVpGZYbOgq65uCdXNpuWdkzjPW6W06U+Sh1SIBnbMN3X1hgTbXbzEJhgEE5ZsWVSNlX3PZ17geZt0ljSnM9M2UTvRcpx0lSwgN7IuEqV0kLhvMEIFSoJPxoFuwdRR/whzXHoLZNYFN51inulv92w5u4N01jIcVYGi4/8UBfWNmldXdwb3cImsdDatgZrYCphziwmW6+tL0sqtAkNsXxc0oTFOX8e8oaZWxyp5Fcyam66Vav9m64l2wqdRjvJ5IEsaWoJH5okWll9SMANHnUs/GecZVoyqfaSkYj02F0/QZL6YN+od/uO9KhL5pUO9bWgk1AUbdteL6BLQlej4XTCN/pa4TaaloWrHnGYVY8+hUjP3vr1s7MThC3ZykYx2FbY1PhjCwFCh8uJ2ptvE2XLCP9Fl6L8rfesj8Pk/Ogs6A6HKDWXCrLKqv0jLxqaIJIFm5QEZmXo5HtdPd+x3PSuFXKHJ3QTVvU3yR1fFhYjffrqSzvJZQmt9kOu95IS0TfiAlTf9zAicQu+jP+scxDeZ19EVAuyGYccguxRI1OGo8Sk9sm7o+b6m80t6Cbu9xTvXXPPgwgNVFzKtb5feAlqqZ34dRs1uebJzV0T5u+4W7PUinYpppzuFTWfAFmwpeenWifdrF2xPJm1Pz7GCS7u8RJ3jnXrEgT9VFbcVKjPa+256fHornuZ0EGHCKWXEZEMMS6wGZMe6lzcTcaEcj2kwigUafXg4/2k5IRmMdpmkItzzjWjUu4zsntqAd0YokEx+Ln/GyHeoaJfkhAr3inS+Uuwfpta0KtTu9hL1577w/eRc+n/NNd6Kxdzs7KlRnf9ZM91al9tQ/P6MCjpqWSsV8ojY4RqzmeNvcE0JEG0aycLeqKLu/u7b5B3zjBdgsq8k47RVf+od/WSSETLIUI4LcIZ6139ZithAb0xiYaRuVrRMAYbUziPE3MrGml7sGGxhsy2xVn5Bxz+VYg6chBom9ylktl+kCeRxsmQrCG3UZkr6cXg+Ffv4i5nuNVQX05y3G04bJqt12q/pn2JT2hki4sOyvgtZ7KVLAH5xx9pWerKsSgxeViC8BWPs0sVn0dWqGToSp0kaUu4HnfspJRaC4Us+6hOEtW4XYcUdyjIzNIsParyQo4htK9fn5ioqB6utVbutJbrF5KAXifkUN/kuOKGxLQbiRhc5lMJ6GaTadllOgGPWws/0NYvLDKN6VUnemoSLbPfVO+LVPeHvK4OkzJVqiu46fmR70u7TaxDlnkieMAQ0/0Ka248lti58B/xVyiQKIY4hQVdiylP14IeF9BrxtxoeVyiPVmRZLPBf5qitBBW8P+7MuV+RAiAZM2Oxe9xM8FYS6yX4lqikAj5eWqWiC148KH6RHXyuMjKDpMKL2omclIu6JYbzkGya14LOZCVAfHvsSzlr73CJBFXknaT5ReIedymnkqqEkdVLlIZQGMSQOP/00V7XqsW9IyMOgHYuG6r1ubl9sgqHX//mHnA1AnoidtG26fOgWA3WpLjwqOqCJMVx5al/eJYvduMhHdPHZ5q9AChbOGeTz5E/jGHmQvCy6UM7AYljM7qG59H2C0qMui2kwTLvIvPFzXqs24fmzQzu5nl3agEp3eP1TVFyhzN0yCeoFEnFNfUJFeCxGLInnCbSMDm/NUip47d3IKedf/duv9n335LQtigVSULK0iJKivFKDGnFelWeGgMWEBvRLL/vQHOauVBESo4sNHbj7qVB6k90HQaHCZ9XBW/1517dm9vMaQq0ZIKu1xqxqCR1r2Aa2v12XTpJSHX0DQpQ6LGYsqJscTLJUVspihZZpiIyMK4yFxO9XgNArpW5slnqMUt1wlNYpExy4iuaz87R7MQWbnXqfjPOQ9lX3wL3wUXp06wk8z9jibcdrsW82qMh0/IJBwXDo0ubDQ26sRUaMlp/CRrvBo3TIm1Kt58FzXj7rScbFOG5bJZ3+iyg5uFLaS0oMtx0V6vLkmZ7jcLAsccL7wazCDrYNkcxZVXxTiBrnrwMdTccpv2//CAxDJjkT2sJ7JkidO5VNPzcchBpiW4VKtd8LgTUPbZV6i96toEJYDjP8WN1kqAkKFsyQmQS7PkrVL53Eso/WlueucnHktc8f7HKP3uF2t3eZdL24c60YvsGo/Hjgt1MrJiQL025aRjZAnW+vv8y7r9qsJnYNjZqJjyqr5d+VoxKJKqnpiEsk9mi3vQf+ElKPvcvBxX6ZzfUPLnIiVTfkEhSn+ei5IF/9YJSCZCqCrUGin5/S/TpG9E+bT3ETjp1Lp1F/yL0h//QFjyviBlmCzEp1JQqcJ8omu8/hyYJr9TjyUeYqLbl+peHW/HvmZN/QT0ZMqXuAXdKECF414lweNPFM8V4QlCWd2l9wYJ8encF1Z5DNSwFiH0Gjy6KISIzp/Yp8lxiVwLqsBm4gFTlyTOREEleQmljVrJQRXQly6pfxsm14YMlfBLhVBKSC7UahZ7dSyTZVk3WtB1790kddCN2KsS5zdkVRZYJWE0CRkzJsej+017bpn03b5BmQtEO3auy4YfF4wp8V5SZEPGqpXm+wiFYE9RvUWsZxZPX1/vPUMMejKsSl5uC1hAbyyiIXg2xstrFR6CUEHjJwiLeuITy2DTZhJk0sNZES8vk6d3qWOaD8/bb6DVbp0t46Hr7WpttKBLAnDG85NReNiBlklaKIN5QtuqIC6XY6muTpn9NPueO5F19x36vkjKAkqEQvXHE9zW4hM4Wq6rBZtmttVU2b1pAhbLiQvoSUpyiX44HAj3H4hooblgJLucpbKgE6qbe9J90noWWauFgB63oFOys6zbbzF9aYf7D0Lw8KOENdZqsh3t0BHhAYN0CaLqb0FXMnpbubhbubvLbsc0AQ0ZSohpx7H7Hgl9Mk6+ox066BJkhXvp3dXVfVji9YhJvdwnUbfbbFKuuq3bbCLJWOCEkxKEVEqspXxJLYiYuZOL5WoJNGEFP0gb42h7c+FRI+4KTgJdhNx4k/XB4IKvWhXNXdwTLeiyBSi07366WuaywkO7Bsj9/rgTda7/uhh0oyKJStqRpwJZqex2kYfADFFnXBKqSfjWKVfMPBI6mHtUUIZ+tdqCEaF0kOJVaR90P8vx2uTyKh+H1fnV2lDvTWNVAEOfrQRpUtioSg6dBT1urVeF9pybrzPdXo1RT1ie5DmgWdANSeI0pQfdG/RcIUGXPDKk5w8pYVKNSTIBXeuDNyPBxZ28Iuj8WY4XVStQXdzNQlRUpYZZqT4Tbxqy1CdFfa6mE+qShPCe/ax/SyMGncIZci881/yZHItpY2L2jEwwHBjroNP2aVQkMV4r2jyFchHELehGZZbxfU+lQo2x+3SvWeUDofdj5rOKt3Ckc2ctCV5Rz+5ijuCerVQyskJUhDGbU0jKDnvxFjj/qctYXx9sUilXM8S7VD4nZEFPs6Rgdj1qum8tLKA3Eq7yn2APlyPqKkTFwBmAPXVm1PrCFvSW7+JOhHIHNXdXmDi5V10u/ubccE2D29A9uI0WdCk2ziw7uy5JjFmG23htczm2PR0Bnch88jHLfYnfn3o8YZs6F+5avUtbimQ3Zm7eZM2SawmL9rOz03L71ruMZqV2cU8SU6a25T9reNJ9qu7ioQMPtmgnS1dnmCYgZt4XOiHI4lg1S7fkeisLYmEat379EDj+ROv+kou7HEdsdHG3ECxkC5Zc8suImdLD2Ca5CYf2P1C41FKMvplwkSweXJ3oV740FeEeuwtLKRE46ZTELMmGbNckiFAZJXLr9V10qe63qCFHQ9WjTwrBgNzpw913EQJF5QuvmB+3dK/JAmDt1WPE9Vx92wTzgzG4Uctu9qT0ofJZagkzWQkgfu/cRVlu5uKeJ8egK8KSb9TVoi+VTz+nvwZy83TnSCcQUDUDKSO/zsU9jXuSPC1C/QeK85Q2hjjV4KGHCaWbtl+jcGxVQo+uIbPEhIYM8/JxpBJGZWttVLaSG/qsG09JMIx26JRUERE4LXmeGSsB3SpvhUhgqcagG6qFWCkfZRdkca9bPEuTub+rLu4apHgixZqM/Bwz8ThQLOgl1h41Wry/iYu7SWUKszh2leCBByEUDy+xipVPFyslJ73bYq1bp65zbqizLT/jaW6gKs0DRx1TLwu6cNMnJXo9Xdzl65fysaiW/IrXp+nua6Pre87liV5slHchldJb7FPy8KFj8L79hrlgLd3f8rvdKYX+pfK6SxdT76kk9wOVw0wVTpCsusi2ggX0RsJVpiSHC7Y6cpsI5zoLOgvoLQ677z84a5eL7P1hFtCbBffnnybWlY2juoySS5r3hckJpTdMqamBd8pzcP67SF/z+LWXtXJrdpMyJpaZ1U013Wo2Y+nlTC+KNC3a3ldf0rTOCWVPTNzYtNJA9JsuSVx6iYYc69dqrtMlS1ej4r0P9e1n56QVP6ubSFpMtN3ffa3Uff/916Tlu1TLOCWAq3xysra85LcFmkBIqJMNcgs2y0YsJvyG2GbT8ytZTq1c3DVBWkrAJQsCtTfcDMyfn9zLgDJny0JWhleLq1XatqUW0EmgsRCgzTJoG4UKMZFxu1H+4eeoufchc3dgt1sp42V2DHFBlZKGlf3wO0KHHqYlmyqdv1hkVrfEZkPVpBdQ9czzCJ50KgJHHm1pdfOfewHKfpqL0t//Qtkvf6Lsxz+0SXxCs7IXjOwiXFCI8q/mwHeVuTKPksRZKmo6dUb5Z1+jduzt8d8MVRniyghToVLynlGFFZr0Ul/IdV3nAm8Q0I21zmX3cp33RRrxybXX3YTyL75NqChRH0TdeEmoTlD4mFyLQoinrP5pZFuWny0pczBI93KyZ5LcR9m7Rlfz3iTG3T/ifASOPrZu/bx8BI44yrRd3f5MlCUVb7wjnl9GxY7WLwtBST6vQnlj8SxNFuedaEH3Jgi+8vvBzE3dM32adl+piTZNQ7lMxsSsPSv3csqBUTHjY+0aM7r01zcvh6UShZ4v5LFRz7h++Z1LOWfUd3LEJJ49IZmpwTtPZONPw1VbJ+hLSlc5CSp5QdHzV01ymTHlOTjkRGgm3kAiXK0oSSUGs/skfhyOZSb5dmhOE43C+/qrcC740zT0rz6u6aEkFTVSlRwVzwPZazENxQDd28Ywom0NC+iNhKNGuSDD2UpGzG0Bu7i3XLwblPJNocJDEHNbl0JithG1taKWaf7Zp8FmiKVSJ9BE7sXnI2fsjci5PrVFPeveO5Fzy/WitrBK3kXnIue60ci6a3zyJGxxZKHZNMZJFcQTLOjpWbRzrr8anni8mVnpFCOa1c/n02nR092flqQrPskUGaulCTkJEOkkK9LFTiaZVOWfchwKjkueOVvOVB884middVSemMvuerLwIvdDVWCoqEm+rIQMK8ukZpmx28zLQsW3C5nEdOuSqcn9dLr0gkIsZpqoTD5OstZZTvpN3I0TLei5KSfT1H7g1NPND8JoiauHi6kR2bVaqzHdlBgt6LLl1ZgPwDDmquBtdq3r3LjNFCDy9WaYWBotgLIgp8tXIGUhT0maz4K0mjpeCVPQYs/pGrYa1xSl/cgNX2cxTmVBlxVpyQR0KemZrPhJJ8eDzgWY6ofLCgSr2HYzYUgViN3mHgZWiRhjCRZ0CwG9bT0EdApTMnjdyO8H3XUf33/Gm1Ol33MSPCeodrXStomAbvJ8Ch6iKPISMHoDGf4f2id1GUQdYXMFaV01hfqV0pQ96hwrl2vv5Gjr1slzrJiEz4l69knq0KvvITlfgewVp6tSEl9Xff+7fvkJhUPrQp/MzgtVIQhLFR+sMOYcoBKwsgu71rdgAN6XXhDhd7mjLqvrZzyvSH0F9EiXLnX9Nzyb1VKTVtRX8SJwuYWCOa0KIo0EC+iNhKNWyc4YybQuEdN4Lu7JLz6miYnF4Fn/pvjqb392c/dmp0R+Ibi/+iIhDknNNOr+QfF0cX+it/ya4bawxhOZk55U9puiJqYus7rpSytoYkGvTpkBXcb1m5LoKy2vAMmCbqNM7ir12B9Bbs9KQzadOyZZPtKZ1Mh1tuVJZdVjTwm35nQ14WKdePI20VZRkUigVPHa24pFSS4vJU0kzFwb5Rj0ZJp1neXUQmBQhSPZ6qr7PW55910xGtW33yXqkBshd2Vd6S8Tr4rK515OqDMuC2l0/PJkm6wAlZOnoOq+hxE8MtHt0mgJNyogTK2C4RBqJtyLwAknJ/yUygWVLOt0zsvfq3MTtUJ2hTVLMrfNsest6LokcQ6DK7ZBcNAEPxMXb7pnyKOj/N0PTHcbk9sm4U4uPWQQyOT4X511vR7Jw9LNR5EOdF1QyED5+58oC0yyMmv7i5oL6KVfzkH1nfcKLwmdQJpioiyHICTNnC67wkvXldE7IaW3Clme5f7Vo2Shep8khEa0bad4AZlY8MX6CTHoFi7u8dCJdAT00L4HJF4vOgFdUmi0MrGwUmy8UZEX9xQyV0Dp7xXyqgkec1zdPqRnoPGc68ogZmYh3KtPQvOUhJTK81HizoSu1taYurGroSL1EuQMSVkpqajq4k7KHqPyJCHm2VjCtbYWjhV1Wd+tnoea4j8U0r1X1eRrYszUvAkWClNZya4tIwF978EifKji1XjSOQO+8y9C6JCh6WXJDwThfUeZJycYMVQvwHpkX492rqsOEowrArU2U5QeTLtKhpyUksoP5uSiYnLD8xnVFxbQG4NYDI5axYIeyTRPgtK4Lu5sQW9JuDd/AKdvBWL2TATa6B8UTBMhJVPxzPpMWGMKjqor0WOcGMtxUyr2FcuRf+QhImEKYRTWjJACIJXVWljYfT7knX4inP8uTvw94EfO5RfpynooWdzTr21rX7cG+cceDs/sWSnX1WLQRR30Wt0kOevWG1HYP3VpGZrQBCRLtbacJnVOZ8LLr/ZKE28FSaiXJ5WUuKwm7iacLqSxlwkddgSCcdfTaHauqcXYWHpJ7UdaWZB1Fs0809hSbXIvx26aWNAp2ZPvyqsR7run+eRfEvATSubQRLhNG6Wms7xd125S/3J1/a294RYRO+u/+DJTF3njBNpoWTGbYDv/WiCWy9neU8YcG1yFQyaT5+QCenNY0PXjFZXivclaZnmNkOCWIkFgYPi5CEklxXQYJs+qNdIMnfeEFKefTlk6rf16KuuSQdcFhQxE4/GbNl+Sti1c3CN79oOPSsEZni3GOO0E4S1DDkWx9iDQWYTlBIsW8cmWyjCawDdQQNc8TQyKHf//LtbCQsyQc2CQ8GBpQTe6Icu/GY4zeMyxCeEcuhAop6R0tEgQaVSI2JK5uEtKCSpd6ad8E9KzSZcwzmhBlwROUk5FTZ7rpESovXEsam5MrGYhws5M3vNq9n4t0WAKMh+6D/lHH6oLWSLFsao0Fwk/Dc/SxBh0vTU/94LhIqTOCvVazR4/Fs65v6PgYH21jIwXn09UYpg9B0ixYKIIV88VKcZU13gjlLfD+B5xWmQ5JyOKc3FduKBZibN0kuKpyIqVgKTQSQcr7xbjM0TnRRN/l4UPsXhObwNYQG8E7MFNsEeqEYMdkcy6yVFjE3UrN6Q9tAWIJXcHY5oGV9mPyFtwnvgeaHMC4KzHS5lpNOQkYvSycv36s/7lRlYaueauictg9rib4Jo/D7mXXagsSCGsOZYsgS2FhZc06N733oH7+2/N21j4T11manWb8rK0Xc4Jz5dfJGitKZFO4PAjhUVUFXhrrrtJm7SKWDk5i3tNDTKfnwyHRZb2sCTcRnr31eogi3avuV64mFVMVeLEo7n5qbN86wT0TH0pMaq/mkbGc9V9tsoknlxru6hIWKHI0i0nebGyoFvFw8vIk3idS6tszTJLEudyWruOm1i+jElpVI8H37kXiL+qYC5PwESdYnnSTl4E0gQ4ldJJJ6zQOUji1k3Xl+jPZVdYCyRpJFlqkIu7SWKpbYXq0VEbTwAnQ94PRM1N43TL5TEXfZXGIdynfmFwlFBPFV5Ef+LJyYKqF4tEpHdvMakM9+6boCRIl+q777dWrG0lspJJ9WpSUa+jwLEnWDcgK3wMAnrVQ4akmJIwQs8+uY64jM4iLF1XZkq8ZMnMyFtK51FjEd9shnq9GF3DU96vkiBMSmcrC7qVNwAlapSvDQpFICVPgheF9D6KdOwsBHhSSEYMse1qyUzjs8BHCkGz5Rddqn9emeUokOKgjXlV5GdfpHcfXWlBFf+ws00t9UTt6DE6RY7RMyKd5IpE1kP3wfXnPN0y+8aNdS7ulE/EcOwJtcjjFnT13edcsTxpjhK5OkfBMYfpkq3J6O59k/ElC7bZfnT17i0UrekosVTcX86yTPaqhgKm6+IeczoROHO4+EvP56CUnyQdhDejybspNHh//X7kBJ1N6Nqusm2yme1kOKoXir/RjC6AfdudxKi7tUhCZotFYAuWIOZJUt6GaRJcJV9q32u7J07gmK3DvnaNsH6kskDJD36q1e0xCL0k8MoxWbLbnLbdmtV162/ZkjRzuOhbWalWG9uyX2WlOhdsI06T2uj2TZtgs6pfSi6fP/6BwgOsS/kVL1yhTCwiEWFto0mc75zzRVbanJGK8sE57w/Yaupehva1dccu4xt+rsgoTb/nn63EGYf30Cfwqb3pVmHhUuO6jcKnmRukTYr902V0pwmX242S+YvRultyIYwm3eQOGUvivklWt7Kf/hDPTV1CMJPzL1zcTSYI1H819p4I9xtQt43OgpWTNEmcbPFLcLk1qY9ttBapHg/VDz+BmltuF+dTIE0cgkMO0icRo9/kialFjKuGFIMf2k8/WRHtSW3X3DYB1Y8/XRdfXR+LYQPQxQc3got7QoZxC6qefg7VE+6rG28J36jR8A8/N1EAksbc2FeqOZ539mlwz/kurf2T4FW8eKV2zZDlvnjRSlPhgYTN0l/nI0aJ3mTlkEkWcivIw6J4yCGmx7vVSEpBygviWFtXQ5zcacWzKw3XcjMLeuDsESg+7Ei06hsXriQBnUIpiv9ZbuE5k2muBEpD+JBzWZAyVh+DXh8X9/g9nOAFkPy8yd4UwcOPFIppM8yOhRSrlBhQ9tBQvTiMArru/x6PSBAaszuQOfFRbTEpjqrvfzhBOSHOafwdII9J2SezEd5rH12lDNPElVL/jDlfZEWYSCIphaGQ1bfymefrSuVJyQ/JZZsUXiJTu1CC6MPDwmpZxCShEakQWdTj1ztd00arrfjN5xOGBCrbqFrQKTwr55orhICeDN/IK+D64Tu45s1N3hE51MNoQSfreXx+Qoq92tHXIfsOxdNAF6ZgpWg1yUmiNZ2ZqZtDZd0+VtlPdk5CxnTHurXCku78a37yY4lD1xF5r5TQc5HOn8uF4qWrkX/CUaaeiqlqvpd+9YM4xminTmjVo4uFBb3hyTMbClvQGwHPZiWeNVSQqNFuVOxOxNzKS5MTxbUMnFVKJsyqPR5CJDu1ezCTPvZNG1E0qA+Kdq+LNbLCGCuc8YqS2M034nzld39AF89lKgBLyZda9dkVzoV/J99naYnooxnqpIKsKraSOuHOiGNRYhIy8cJMYkFPKE8lQeWwxGSIhA9yrY1PMITFm16y8Rd0xmsv6zT+uoQy8nHk5Stx5ZKCJKE2qsOhzxhtEBzMLegRc9dvdYKamZm6Fi4dXzLhXG2TJkbGybLBhVMQry1shI5Xze5MZbxkwUcXoyZZu+qSxMlCUqZ1+aj6WO4pu7AsPEl9Dh59nG5yLNz2ZQt6KldnuS2TGHWdVZCyt8sWx3pYDBuCrgRWGuc9FWaZlU0xjrcxzICEPmPpLkMJNh1ud72t6ELIkBVMtE+TuFHxG1lxjbW+62Hp0j0v0lk33i8tEVyaFvSwSYJE8eyyiLc2Yiy1J7aXPHuMibnEOTRrW76f00gSF+2oP065uoAuMV29XNzNY9BTKlZkV3Cyhlu6uBeajzU9b6VnYeAoJTTI2I7R40w8UzMzdS7+JGSqbcklvVThXNvO4Fkiv1vsa+oUNtp60jlNqKohXaKhoYfr9kWCoM6iLik8yRVevafNxlir+V7PJHEyzvi7ne4POu7w7onZ7UkQLzxkP2Q8+3RdDHpWplCKp4K848KD9k65nhx3nuAtEAhoc5houw66azut6zfJM8I4TxGl40TelasS1s0//URhdMhKs8Z4LH4diWdd/PkjEtaaPBPMoGeDHAoW6bsnIn36JoZ0yRZ0i3Kl2xK2oG8tET88m2aKr/62p23z3ZGbuz24WZRai9QjMSvT+GQumwBP8afieyRn22Xv31lxzv1D92BPhlXsUnjP/sqXYECnfdfVAK9HQjIZSsJiVsqMoAc9ZWAlly0r1zOrLOH29et0yV4SSDJpq5w4KWmfrSZ8jtWrzDeIJ26SYytT1UZNsKCbCOg6a7KshZcTsBUWJj0nam3pxoL6Ed5nsHCJpMmjWkc+0qEDqu+8B5mPPIDquxT3X1khQvFvlDWWPAki772jTIbVl7k0+Q8deJBo2yyRkTwxCPfqLSy2KpT0LuP5Sai+5wHLvtfcOFacw8DJp4l9kncB1YIV5YpsNtReda1Q+kTTEKKq7n0QzkWLhGU4AYcDNWNuFMkRjdl70xWsGgpZkslVVtSD3wrLVvkHnyH/mcdReUd6k8GGQNY5ctW2b9og4oiN1F5/k4hbD5i4XDcm1ePugHPpEsuSc41B+UezkPXAPZq7f7rx7bU3jYV95QoETjq1XvujZ5znk4/gMxlXouq+h0SW6sApFpUFkiCXlTK6S5e/NR0Zz09GtaE0YNUTk4CrRor7RbY0W2Zxp7amf4ic0f8nLIe6coS9euvWI6EhGTVjbhJeZlqYiew10GN3ce4FFtUXtHboebFxA4LHHi/+Twkf/fQssZErdiWq7n3IdP86AV1SRNXcfpd4JvpHKOE4Gm63sNyTe3fU5Pnt2FxXQphqd1PW75oJ98E7Y7qpBZ0y+/tPOQ3h/oPEM4HKiVHfKS+L//wLDcdbJ2Dpy1fqlREiYWdc0SDH+FNpUXo3u6QSYWYEDx4qSoTqlLU2m3IcvhpUnn0esq+4TFiR1ePKGn+r1iey9AdOOQ3uzz6GvaQY4f4DkfHSC4k7ysoy9YwQYQv5BXUKAlkpayyfV1sjQuo0pYVkJU52/aZDtEMnwDD3IYUxhTWkK4hbYVnCMEUoT+11N4p5JSVJpXOSPfYG+OjdqEJ5LtxuLWeCbnxZQN/+yPzvMdhDxYh42iNUuO2TB0Q9bYHqv7gWejPjqFmKrJWKOxcRzk6cdDNNh1UdS9W9miYqNInUiE8U7f+tFMlU/Gedo2VcTRfnQiW0xZT4w1y8ACXXeSPqBC0tYTmFIESCh5y4ygyrmEZLt7B44iZduTKT8ly6fRi10FIZqbpGJPdUOVZWKsOU0urXyDFhYmzsduHSTKgCOrmpk6Wi8vV3EjfKyECllOFWjgsUbcrnSmrbaHeQLVYVr7+jlQUUbR52hPgkw5gojpQFMjW3JWaJt8J/yeXJ93WzPt66KammidVWEt7/AODEoxEtrgJS6/4ahteLylfesPyZrD2V8ZwN2xLf6DHbfB8kJFW89V5a68oKTRIAKl9TypPWB3Jlp48V/otHik9D0IWHGBSNocOOFJ+EbVq1QuWbiqDleU96Rlh4OIi2DjoEFe/M1EKVVM8h4/M73Dd5GUKyAstj6Fy8UKcQVAV0U88ZSeAwPi/IKln1/MuoVxZ7OVSpqAiVb+jDzLR9pZkElDx4jF48xrAGGuOq56R+ut2ofPG11N4G8rtFEuqo4gAlNdSOI0cR0INDD0flq28i//jE82/Ef94FOgFdE7zJE+DjjxEsrlK8zCQ3bzJCxOIu7iQgkrJBfd+4P/koQUAXygZyyTYL2cjKQuVLr6Fwv0HKAl0uCv114PnoA2TEK9IIJbwUArW1IUvRDomefhWvvmmaJ0DGf+ZweKclZntPVe4znZwNVL5Pzhei3re6NrwZdQJ6UfNa0NnFfWuIRZGx5lnxtWb3ewB7ejFtWy2gxxPTMc2DvXYlCn4+SPt/KKc/Yq4G1FVk0sciw6+KVby4/DKQhWHVgl5wxMHInPwUcv/P3Bpj2mZ8ImJm/dbWUQX0qqqkAnq6Qns6UDK0VNQnWRQROuCgBHdStQSNJXa75o5MChLdxC0+Lv6zzzXPfm5SqkyGsryrlsGtJcH12OD2rh6DXPKnvlBcaDrjLk8stsatkmFaMmqCO+yrzzjdnIT79Td3wbbIUJ60LUrOlyY6F3zp+VB7+ZXir++c8+qdZJEESdGPnr0QPFT5bqVUlV3HG4rsyRLpoc9NUh/IqkoELTLWC2s+/T2l4V6quvwAutAkSWg1lCGLdFYUpVooT4p5CBE4/Ci9+3TcXd6qL3KdcPNa7yZyRVyRbarEJsE9rlhI8BwwKLVzrr9a8/CjjPW6cKgUArocphMyCVcxyxOiHrdaztNMwZDgmWWCLoGdvDwzRUiISaLAhDZ0uWTMQySaCragbwXOqgWwh0oRdeQg0CaxBuy2IOrmUmvNTebKh2GLxhM29bgL/g4mrqBMcshtvT6TD9JoWgk5sZilgC67LCZYckIhLZOqWv6DBMqaG8Yi56YxSV2ryeKslkajOGR7Rbm+S/GHuWP9+rRc9BuDdDJbpxPrrFLx0usIHhfPqOzxoOzjL9KuDUs1nd3ff4MgJZuStPaVL00V4QhqrKMgM1MkDBLXhNw/k7rIlEDH9edcxZV7Kyn74ju4fvlRHI/ZdULJvJx/zkXQpL53ugTOOgcVObkID7JO6idwucT+qMZ1vWrvtjBKf54LByU+jEQR7s1eRYyemlvHI7zX3sg9/SQgtazTJIQHDELFm+8i0qWbmISXffqluH4bEkZBcdjlb88wrRJihITEsg9nAVTdQbK2izEaOAiBo+uvGKQs6qRYIEshWW4rXn4D4T59RX/KZ3wslJD5m9eiMmJDcGhyr5x0Kf3uFzjWrUHE4J5fH6rvuAehwftpCgYjVY89Jd5FwSOOavA+SJglLzOhLJWUsTrlqMHCHDz2BFQ+/zKC+8dDRGLWFy0pmstnfirynVASOve3X4lcNNRGQl/MnvFqKTpjHgKT5GRq3gczF3ey/urKEUoZ2pPlNBDbuFO7uPvPHiES8AUPrCuNWfHme+J9n/nEo3D+85elgl2tclA251fhak7rZj36oG6dMCV/+3U+Co4ZaunVaO3inlxANxtLs+opqpFEHt90tm1sWEDfClyl34i/oYIhTWI9JyJxC7qDXdybDXepUjLL1/F/8HUd3ailhHYGnL/8jLwLzxFxtsFh6cVgknbZzApJAlTeOWcglhnXyObkinqbWv1hC1coSlYkZ7yNtGkr4t8iHTrBf+El8L411TI7qiqga//fZRfYjeuq9cYtXO+toBit+m4jtqMJXjrCdz1eMsHjT9T9nzIhpwuVvPGpApqkoKASbGGT5GOUwdmIXYpH1Lbv1h2BVBb8NKEEc8Ek8a8UIxnc2jh3ux3BE5RycOm4Cm/vRHbZTXwYxhSvF8FTTwcKcwAKMWghBA+vE/wos/jWQMnK0iW8736JCz0eBE49o2E793pFFn4VTcEad3kXU5VWOcLNurHCO0gpIRLEbQ2GfieQnd3wMZEwhiAZE6cllNJyufTK4Ii1gB484kiRbEys1qs3fEkUFmb11TVFvtFibhbKFS/ZaVoKkARyeRvVMk8k8eRSSnK6UwvBIkZen9+B+kHLPG+/USegm4S2qYoJyicS7NgJ9s2JhsZo127Ke/74k5Hx2kvmfbCy7ksKCJHDxijgpxEWJ95fP3yvHVfdtuzivl3hKlVOYqjokCbbJ7u4Ny+O6sVw+FcjZnOheo/7WDhvALmXXyTKVuVeobi1WSK7kwXqysnI5Fx+sWhLs2ZLWXjFQ9zigUwWdDmru1qvVLUwG7XHoYGDdIJbsjhB0hJXj7/LVPiuvvNehPba2zI7tVmmVzMqn35OZw1PN9GSzVDexAhZXMj9rDFcyOt2akPwkKEI77qbsAylCyUaomOsevxpoVWn5Dt8vzEMwzCNhmSxNktcpyOJi3t9KiUk85IyWmrNykGq61hZ0HX/l+ZOct34xD7lJhWCa68YLbwFa6+5zroNKRSOElPK2fzN9hFt2z4hhC3cs7dOCWGGmfBPBA8YIowVlME/GC8ZKBNzpBZ55fAEtqBvr8RicFX8Jr6G8ky0oNsIdnFvRqIB5C44T3wN5Q0GHNY1IJkkSC5XjvnzgPatgDZ1SbGoNii5S9nilnDNgm7SFGVJT4h7UhPjZGUnasTV7WprdXXANTcwVUCXEp2R67H70481i3qksz6mzJgZu+Tf/2AzaG5Dg/ZC+cezhWsd1S+lDL5qIhQqT6RmK6ekOGr5s5jDYZnNPTDsbMXiYLeLOrLpukXLNWeNbNmsjHfJsjXmZci2gopp7yuTm3q0Sxaf4pUbhFBOSfy2dZZwhmEYZufCIeWSCZl4cslQrW4rzFy6rUiaZ8Q4ZzGLfU7i4i7Pr4wW9GS5UEj4loV7Y7LXmjvuVpKNJnmHyy70FDZW9t0vKDjsQDgXLTQ9FrkKAMWxl3/6ldZ+zEQxYSXYqwRPPAXFlMjR6dSSvMpZ2W2x+iW3053TZjAO8IyngThql8EeLkfM7kU4J/3EIFtL1KMk9hBZ3JsotpVRcFbOg7PmX/G9uqd52REmDaSHdMERhwB9+ug009m3j0XeuWeJBCYaUvkaGVsoaJmYhKzgyTTGtnh5ERm1Jrcumy9Z06U+R7p0SXjZ+uIlqWL0EKe64MY6svQiVV9sBkEz2r6uz8GjjzWtD24KtafWkU3z5UG1TlPSyMK5ID4uDdpOOlaGYRiGaSzUihnifZtEKFRWTiagp29BJ2HYDHX+oFtmd5iHtBEmIXzGOZEcg57UxT0nV1iek1YhSPUOd0jb0ByI1pdKK5rFe9d1wNC+M4mALnlKJkBj4vFosfzRNm3TisHX+rRHT3NFShoJAhsbtqA3EFe5Er8azh0A2JvO9SHqUS5MSlJmi1Qj5uRi6E2Fs1pJJBYsOhyRJlTK7GiYaUZtJSWIxV29M16ZoiyTtLlyfVkdIX3ZFTk5j4g/TxJzZC8uSeyb5uIuCegZGbrELUY3OHJp993/iHBxo9rHykHoXwTG0iKy5V/n4q7Wbaf+SR4EjQVly3WsXY2MKUq5L/TtC9/g/etdi5hhGIZhtneq77hbZBP3jRqdemUpSVz1hHuFMUElapKt3bIZqwSENF8xKqLNDHHqHMpmQ+XkKbCvX4/sCbeZW9AD6VnQSRilGPqaG24ReXYahOxCHj8Oy7kbIfXHXqqfj8WSWdBNMsQnEI8Zpwo0vqvHIDsSELHvqXIv0Bys5pbblMSx8vwxSYLAbQUL6A3Eu16ptRgsNC8Lsc1wZIms8fZIlXBzj7CA3mQ44gJ6OGsrE6Ls7Jg8eO0bN8D90Qdw/vO36SZqCRLb5s3IueEa4bZVc88DCdriiGSNFjWok7hFG18IYpu4Rlq2Xossr1KCEBKoSWhXa/oK9/KMDOECVte4XQj7anZ5o3Zddq/XabVtNvFydNSzNFvaZGSIWtKagE5Z6x94hJ1xGIZhmJ0Oqj1f/eiTaa5cJ6T5Lr8SjiX/ImPqKwnu2qkQddDNlqcb5yxZl9XkeqqArrOYy+XbUmQ5V/tUe8Mt6fXBrA0Tqzsl5E0He4lhPuZ0bl3FmrhRhRQP/v9djOxW6SemrL32hnqFN2wr2MW9AThqlggLeszmhL/T/5p8/5qbe3Bzk+97Z8XuX4/MNZPF90g2C+hbhclLiAT0nBuv1aznCcQTnXg++xieTz+C58svkDHpaa00iUpMKpeV6oFqKylOWKYJ5tLLQWidJUGfrOtybJLly1au/22IFaNSY9qhxa3Xkbj1n7Lbi+VHHo1tRXD/A5Uv//d/22wfDMMwDLPDYJhT2MvqwuREmb40kV2n5TrpZl5z0Xgtdt32JgnUfOco+ZFqrr1eVzOekrtZ1XnX7acBZQWNBE6Mz2XiYQOEzZ/Egk79PvcC8bdmjF4oDh51jNYvozU9qYu7IRQxnbrq6SDXfW8q2ILeAJyVc7VEYarLeVMiEsXVLudEcU1I9mLloUeEs+tiVBgJSmhGLzAr1yT6rbYWMWMZEXoxbUpelUCzoFfUJTlzz/o0oca4LvbbIsGats8tm61d3GXLO7mrS670lDyFYsq1WpkWLzZF2C82TSAjW9BD+x+Isi+/19zKqLxZ2WdfCY18lc8vaqwXDtm60j9GKl5/B66li5F/5KFAiT7RHsMwDMMwKQT09cocIJXFN6EZSUAX1uBgEI6NG0zXpRwzpT/PFfl0igb2tozPrn7wMfjPvQDhAUqllKonn4Xvsit05TuNNdb1+0kv0WyqsoFls7/TKR0QsI5BF/2+72H4h5+bUGY0PGAQSr/6AdGOHYWbP4UTqIl1rWq0y4SGHiHmUeE9emFrstcU/7VUzMHk8Mmmgi3oDcBZ/W+zWlK1UmssoDcZziqltmMkoxvCuemXitqZyB57A1rt0gH2lStMf8+99H9o1Xc3URbNiEN+0ZmhCug1dS5Kjg3rE1bTJVaziBlStbHOZUutt5eTlZCwLrvSu906i3g6FnSji7vxRUlxT3KJkvCgvZW6pG3bIrL7Hmh0srPFPjjxGsMwDMOkxpjZvMHtSFVXSFgPHnNcytrcIn5a3SbfJMmc240wZaFXFQUej/J/eS6T5H1vGRdfT8L9BujmMinHjPq5z76mCo5I3z3FXIty+OhKtqUzb7HZlDmOSSK9+rDN5mBpwAJ6A3DULBZ/w1nNc9LqaqGzi3uTEA3A7l8jvpbt8wVg2wZZrrd3amuR8dILIiGId+Z7ib/HYvB8+L6IyTaLr7ZLNcnNUGt5GsuqJewmR9KsRswFdGOMlqlQbchWatxG3o9VyRSdgG7QvlY99pSo7V3xghK/lory6R+K9cvf/ySt9RmGYRiGaTyqnnpWCIqVz72kWa3Du+6Gihen1ttdOjRwkFDcB045XSQlC1FysmuuT75/mjfsvgeq721YFSEqCRs45jjhjq/2O3joYfCfOTx1Bvut8NYTc5e3TOaF9cB/3v8Q7t0X1beOx84Cu7hvhYAeyWoeV2euhZ4au38Dou7WgH3rL3GHbzVsiCLmyELMrcT/M3rc332jKwvifXkKgocfqWU8t29O7sLunf5Oei7uKQR0nbt5A5J6WAnoCBsEdDlGPQ3NszGBDGmGy378I+1+hQ46pF7rMwzDMAzTeER69UbZD79r/w/3H4iyn5SQ13qRkYHyz+vmTET5l9+n3Mw/4nzxaTCU9f3Vt3SLgiechG2JcHtvhLlLrLAIZd/8iJ2JFmdBX7VqFS6++GIMHDgQhx56KF544QXttz///BNnn322+O3oo4/GO+8kn9RvEyI1cNSuVL42mwVdTRKXXOjZWXGW/4Ki7/dAwS9DGkWJ4ahVrLuRjF3YJdgC149ztO9Z99whEr4VHHqAtsxh4k5eLwJ6AT3cfRfLeC21lEjogHgiNAMRqS6mlYt7uGdv/TY9DPe605GyNqh940bLJHEMwzAMwzAMs80t6OvXr0dJSQnsdjtatWqFtm2tJ8JmRKNRXHbZZdhzzz0xY8YMIayPGTNGtLPffvvh0ksvxfDhw3H//ffjn3/+wS233ILWrVsLQb6pcJX/JqypEW+nZkkQR6j7tQdYQDfDXfyF+OusXoiM1ZNR0+OOxhHQM3dtlP7tiMgly9TEbXJG0q0V0NWa6PZqJQY93H8AnCax7uRuTlpWKtnmu+iyhN/L35qOaNv2KBxapzzQbZ+lWNApJqz6ngcQ6q/kGwicegaqt2xGaPB+8QNK/eh0rF9Xn0NkGIZhGIZhmK0X0P/44w+8+eabmDNnDsrLy7XlNpsNRUVFOOiggzBs2DAMGpQ6sVZxcTF69eqFO+64A9nZ2ejWrRv2339/sY/q6moh9JPATtBvv/zyCz788MOmFdDLFEthKP+AZrOmRt2cJC4Zrso6dxq7T/F22Bo8m94Xf8M5fba6re2eaBS5F50nsnTWTLhXW2yrTCwPouL4d7FSu7wxLej9BgLvm8Q0uVwioYpvtPKckAntuz9Chx2plSTJeOO1xO3VJHE2G3yXSiXI7HZR9zRZvU+GYRiGYRiGaTYX9+XLl+O8887D7bffjnbt2uGxxx7Dd999hwULFmD+/Pn4+uuvcc899wgL94033ogRI0Zg2bJlSdts06YNHn/8cSGcx2IxIZj/9ttvGDx4sBD077tPqQ8sQ4J7U+Iq/0n8DRWYu882qQU9VAJErRNe7ZTEYnBW1Anojnhyt4biLP8ZropfELO54e+o1GvcmXEs/AeeTz5E5uSngHBd6TFbZV35Mx2RCDJefK7e+4l06GhqQVcF9EivXlpZslT4zzhL/K0Zc6MunskMXZm2ZG1eMlL8DRx9rOU61XEFRtX9j6TVJsMwDMMwDMM02Ax055134sorr8S+++5r+jsJ7fQ55JBDhNWbLOy0zWuvmVitTDjssMOEy/zQoUNFvLnD4UCnTnVlBsiV/uOPP8ZVV12FJhX+4uW2Qnn6mn1NScxViJjNCVssLDK5R716YWZnxu5bAXu4zpPD7ts6AT1z5WPir7/D8GYLaWhRSJZjqiOuZie3sqA7F/wJ96zPxHff8HOR8aZJtlMqUybVNyeoJqbsIu5YvBC20hI4/lM8IqK5eSj79ic4VixHwREHp8y8Wj3+blEuQyUqlQGJ5uWLOpcJZdqSQGXRiv9ehpihfJqMb+QoBE4+rVnqZzIMwzAMwzA7mYD+6quv1mv9IUOGiE+6TJw4Ubi8k7s7Wc7HjRun/eb3+4VgTi7vZ52lWMfqQ0M9023BYiH8xSgKPatHo3q4q22l1abNjqi7DRyB9XAENyGWwQK6iqtyrlav3OH7T4yPLRYA7Pq60+mMPZ1vT/Gn4ru/22jOD0djImUzd2zagFgHRfi0W1jQC44eKv7GMjLgu+FmcwGdBGejgN5/ADwff6D9n7bTbUtlznJyEOk/QN8/s3PksAPt2kL3UzzWnIi2bq0J6MjOSv88t22jb9OIzSbGp6VeNvV65jCNCo9988Fj37zw+DcfPPbNB4/9jjH2tiY8f1sdSEmJ3Dp06ACXVEPvp59+Eu7qu+7a8KRalCiOCAQCuP7664WbvNvtRk1NDa644gr8999/eOONN5CRkVHvtouKpFrJ9WHzPPHHltUNrdpum3JbafctqwMQWI98TyXQqoHHsyOySvFwcHQ+AVg+5f/ZOwswJ66vjb+xdWMVd3d3CqVIgeKlQltK3ajbV3fvv+5CCy2FUihS3N3dXRdZ1n3j33PuZJI7k0k2uyywC/fXJ90QmUzGct97znkPYC9EfGg2EKlxLJKZ2YZ7WJ9zdJnove3TD0p/Q6uiUq3iPRSuCcI8l4yYQu7Y4wzhtNA1a4bY1kpndDeJicChQ55/v/EGwmvU8Lu8SjUrex/3Oh3iAz0X4mPcd42vvQp89hnQsSNimze85n5BS309FFw0YttfOcS2v7KI7X/lENv+yiG2/ZUjroJt+1ILdKoRpxpzEsm///47qxOXoTR2qkG/++678eKLLzLDuECgiDm1UuvTp4/7sfr168NqtbJacxLo999/P06dOoUJEyYwo7jSkJ6ey7RZSQk5sx0R5PAcWh85aZKbdFlBm4gOnkDXLUofjyDSRWnHYQ4p23WpyESnrAdNFeUGtURocHUYCw4j++x+WOO8J1QMuXtR6fgE1xubIb3Kk4ptH3ThGKjDtdWUhOwy3t8Vpt582t+sdZmjWjWYb74VxpRMyNI279AxFNF2cToRl53tN1JsjktAbnoeYqOivaPtXOq5edgI5I57FkH/zWLb3hfpFsDp2ifxrsecQUFID3A/BdsA+VKdNnA4QDe24MvraXElKek1R1B2iG1/5RDb/soitv+VQ2z7K4fY9lfHtte5llXuU9znzZuHb7/9ViHOie+++w7Lli1jbdBq1qyJ0aNHB7TM5ORkVte+cuVKd4u2PXv2IDY2FjExMbj33nvZa2gC4GKi87SDSrOT9PlSRNUW1uiSnWCBrptdNoorShEnu4zTAWOOyyMgqi2CQ6oDBYehK0rW3Eam9OWefxz5Cc7KSoGuc7nkO4IqX5PbuFLPLop/Fw0f5XZTJ3TnzrHtQsZtOofD77KotRm91lGturdAT0hw33U6nNLrIv3Jc8ARHgmo9onTFBTwfrI2a+l53zW4b8vieii4eMS2v3KIbX9lEdv/yiG2/ZVDbPsrh7OCbftSu7hPnToVr732GjNx82XyRqnp1IKtJGntzZo1w8svv8wc30mof/LJJ3j44Ycxbdo01lbt3XffRVRUFFJTU9mNb+12qTHl7Cg37baoBp3QW0QvdBl90RnoHAXMQM8eWgf2UMnl21B4SvP1QenLPP8oOA2dNVO5PPM59tcRXAVXPaqrli4zw/s1ZjN0Fo9A119IURjEOU0mZt6mhaOyNKFkr6bhl0D15PLnupzhnWQc5w+upMZNkMZjPrA3bsJ6omcsXxfwewQCgUAgEAgEgnIr0M+cOYOWLT1RKC06d+6M06cDd9Emp3aKvlNdOZm/vfLKK6yV25gxY7Bw4UI4HA489NBDbsM5ul02F3eHFUZZoEd3uDyf6W915Ai6WQh0GUPBYfbXHlYX0JvgoAg6E+7J3i92mGHKXKt8f+5exb/lbesI9qRgX3U4nYi6fSRihtzIepwT+vPnEN/Iu3xEV1QImKV2Z0TonxMQ274FjPv2SIuKilK0KbP09EzeOSpLkxyOqp5ODG6COQM/u0ugR3lH0PNfeNn/VzFR0UfgUE90e7PmJXqPQCAQCAQCgUBQLlPc4+LimEivphURc3H+/HmWml4SKLX9m2++8Xr8119/xZXEmLcPOkchHMZo2MPqo9wIdIuUhi0ADPmyQG8g/XUJdIOGQDdlbZT2Z1Aia5kXnDofxrw9sFbqfm1F0IuKELx0MbtrOH4U9noNEDxjuuZLdUVFigg6e8+pkwj7QurzzaLnnN+EvVYdAMsVEfSCZ19A8Ox/4QwKhsEVgecFus4qucQ7oryvG4X3P4SQ33+FtXNXxeO5H32GiDdfQe5Pv5VuGwgEAoFAIBAIBBU9gt63b198/fXXzMBNC5vNxoR2SVqrlWdMWVK01RbVlrU5Kzcp7iKC7oYM4Qh7uCTQHSFSiru+yDvF3ZSxgv21xPaCPVKKohpz911zEXQWFZcpksR30CKptZwXRUWAxRNBd1MoLcMZFa3oI26v5YnCO5IkgU49wdP3HWO9yTUj6Da7zwi6M6YSMnbsR+7PvytX6577kXb0DKxduhX3dQUCgUAgEAgEgnJNqZUmtTpLSUnBiBEjWD36vn37WDo7mbr9/fffGD58OPv3ZUtBv8QEn5/B/loS+qM8oEhxr0iuB5cQQ8ER3xF01TYy5rrM5GI6wx4itfTSu0zh3MszJ1/1EXSdS1yz+wX5rM7ctEGqyy66+VbvCDpnEidjOH7MI6q5FHd7rVru+44EzkXfaFQIeV6g2+u7slOCfKSrG43abdDocYFAIBAIBAKBoIJT6lEtGbWRMP/000/x4YcfolCOojmdiIyMxMCBA5k4j4+XmyBVbPMxU/ZGOKGDOdHVjqmcRNB1Tgt0tkw4TbG41jHkH2V/7WGSw78jpBrbZzqHGTprGpxBHrdwQ4EkKqlcQe/IZ/d1llT38zpLGvSWVPZ+WzkoabgcEXRdbg50+XnQ2aUotr1hI+VrzZ4Ud2v7jjBt2cTu6/Ok1mbOiEgyknC/ntqz5b7/MXQFhe4adPdznJAngZ41ZxGCp05B/kuvuR/O+fI7GPfsgs5ihXnkqLL94gKBQCAQCAQCQTnkosJOVF9Oruqvv/46i5bn5OSwx6i1Ghm+XS24zeEiW8ARUk6iqYYQOIwx0NuyoDdfgP1aF+gOM/RFkiGhzSXQoQ9imQYG8znm5G6TBbrTDkPhCY+hnEWqNddb092LM+ZJhnHkBg9jBK5aCjwCXU+9zF0RcieLcod5RdBlkzh7vfooeOpZRN/pibI7IyIU0W1ncAiK7n9Y82PVAt3WqTOsHTsrXmO+/U54x+sFAoFAIBAIBIKrl4sS6BaLhdWgh4eHX1Rf8vKOMX8/+2sPb4zyBIlPSaCfhz2ifK3b5cZQcAI6OOAwRMDpyi4gyMmdBDpzco9uxx6j+zqnFU5dEIuy6yD5KFDEXMaYKzmTy/XpVyu6wgLPfWqXRiLcJa7ppqCw0B1BJ5M3r6g4CXS+lCCEqy1XE66d4i4QCAQCgUAgEFzLlLoGfdasWRg5ciTuu+8+fP7557iaMeQdYH9tEU1QnpDNy4STOwl0Lr2ddxJ31ZcbXNF1ZXp7bUBngNMklWHo7PmAXYooG1wRdFvEle95fylhUXH5PhdBJ3HtDFEKdPacLNCDg2BPUgv0SEVtOYl4X6ij8wKBQCAQCAQCgeAiIuhffPEFvvrqKzRs2BDt2rXDvffei+joaFyNGPIPlM8IepBLoJsv4FpHIdA5HLIBHCfQjfL+pPR1ls4dxfqmU697vSUNjtAa7gj6VS/QuQi6nmrQuQi5MzRU+dqiQujkPuj0fHw8nHo9dK7+6SyCznd18BNBV5jE2aTe5wKBQCAQCAQCwbVOqQU6pbSvWbOGOblTT3QyhrsqcdphzD/E7trDlaZZ5SaCrnIfv7YFel3F41q90E3py9hfa0wX6QGKuAcnAoVnWJo7ubbLZQ22qz7FnTOJy85yt1pjaefqFHfWZs0TQSdDOGdcPHSpFzwCnXN590qR5+E9KoRAFwgEAoFAIBAILi7F/X//+x/sdju2bduGP//8E3r9le8NfinQF56EzlEEpz4Y9jAp4lpecAS5Wq1ZRC90Q6GPCHqoqxd6oUug2wsRlLGK3bXE9/O8MEQykNNb01i7NnJ+p3p2R6inl3dFQH/qJEIm/saEMgnukAnjocvM8P0GXqDn5DCndoLS271S3FmbNU8EnXDEeswJneERitR1fynuCoRAFwgEAoFAIBAILi6CTuns48aNw9WO0VV/bg9ryOqVy2cEXQh0TwRd2RLNXYNeeJwZmJlytkHnKIQ9uArsfPo6RdBd7dWM1mzpvfS8rmJNPMV2bCWlnOt0CFowF8GLFyJ49gxkT/+v+Ag6n+KuYRLHUty5FHjCUckj0B0RETBkZgZmEsdTp3xNfAkEAoFAIBAIBFeKUquPMWPGYPPmzQG/ft26dbjrrrtQUevPbeXQJV2YxLmwF7pT2NURdBLsTp3B5XZ/Boa8fexxW2RLhZkcQiXDM0PRGXeLtYqW3k4Rc7ke3HDoABPnRNDqlb7fU6hss+ZOcQ8KAkJVKeqcSRwoxZ2Eemyc+2mW4m40BJbiDiBr5jzkvf8xcMMNgX9JgUAgEAgEAoHgKqbUEfTXXnsNb7/9NtLT09GnTx907dqV1aVXqlQJDocDmZmZOHjwILZu3Yp58+YhISEBb7zxBioa5bXFmiLF/RqvQWfRcdoexmg4TXGqJ0NY9gPtR2PubhjzXPtT7cgfKUXeDYXHoHOZ7tkiyq9Aj3h6HKDXI+9/X7kfC1q+1H3foXJY9wVFxd33c7JVKe5Kk7iI996CIyZGel4zxT0STr623GTy+9nWrt1h69YdEfxEiUAgEAgEAoFAcA1TaoHeoEED/PHHHyyKPmXKFDz55JPIoT7KHDExMejWrRvee+89dOzYERURQ55kEGcrZwZxhD1UMkDT23Kgs2bCaaqEaxF327TQusqouAuKhEsCfY8nI0I94RLhEugFx5jvgPy+8oguIx2hkyay+/kvvwFnnDQpYTiwT9Od3e+yuAi64fgxd726MziY3dTos7Lcz2tG0PWcQBfCWyAQCAQCgUAguDwCXaZDhw7sRiQnJyMjIwM6nQ7x8fGoUiWwKF65xelkEVXCHt4A5Q5DOBxBidBbLsBQeBK2a1WguwS1I7SW5vO2yBbA+X9gzNnuO4IeJe1fY/Zm6JySaZk9oinKI+5e5XQ/P48JdN2FCzCcOeN+3HDyRGAL44Q8LTfsi/9J/6D0dFWbNQWUAq+qQWcCnY+gCwQCgUAgEAgEgssr0HmqV6/OblcLOmsG9DaXYVg5dfOm9SKBri88AUS1xrWI3OPc7nJsV2OtdB37G5w6h/11GCJ9RtDd4jy0NpzG8tk6UFeQ77lPWSv5+YhvrjTHC5k6ObBlFUop7TKGlPPuNmpaEXQZOcXdGR3teSwiEk5XCrxAIBAIBAKBQCAoORXLovpKOYMHVwMMfqKJVxB54sBAAv0axSALdJdjuxpbVBvYQz1O4UXVx3rvz6BoOIKkVmuEOb4/yiu6Ak/UW5+bE3i0XGtZrgh64Zh7FY8zF3dVDboC2STOFUln9yMiYB40BObBw5D35nulXieBQCAQCAQCgeBaRQh0P7jT28PqXv7PPnQQ4e+95b+HNRPoUlq3oeDaFej6wtOKnude6HQorPkQu2uNbIWCWk9qvqyo+n2e+zUexOXCuGMbwj58B+CEt4z+xHGEv/smdKmpngfzubT07GzobNZSfzb1NidszZqjYNxTnicoeh5ABF3xGrpvNCLn14kofPTxUq+TQCAQCAQCgUBwrVKmKe5XrfnYFRDolXp1gc5mgy49DXmffe3zdXJkWHYyvxYxFJ3yG0EnCms8gqIqt8NpjPFpXlZQ7yWW/u40RV9Wz4FK/Xqxv86wCBQ+8bTiuejbR8J49AiM27Yg+985Ginu2dBFXkQqviuC7gwNhTMqStkizZ/Jm0uY25pwveQFAoFAIBAIBAJB+RHohw8fxokTJ5hzO7Vfo3p0MoyrqMj9sKlN1+WGxDlbhx3b/b7Oca2nuNvyoLdKWQYOPwKdxGaxLvcUaa995SK/hmNHvB4jcU4ErVmlmeIuCXSPsC4pbhf30FA4ojz15P6i53xqu71hI2RPngZ7otTyTyAQCAQCgUAgEFzhFPfs7GyMHTsWQ4cOZe3WSJxTa7WbbroJZzhn6YqGMXsr+2uLbnvZPlOXlYnYjq3c/zbt2YW4BjUR26Ihgmf96/V6e1htj1Ga045rDaPLJ8BhimWR74qGLltqW0Y44z018FoYd+9EbJumCP31R/dj+pwcxTJ8EXNDD2Ym56sPuncEvTiB7nneckM/2Fu0LHYdBAKBQCAQCAQCwWUQ6O+++y5CQ0OxYcMGBLsG9u+//z4qV67MnquI6IvOwWA+Cyf0rG75chE8awYMJ5Tp6vrsLOauHfXAWK/XO4KrwKkLYu7j+qKKOxlSWgz5B9lfeznsUx8IhiOHPf9wOPy+NuLZJ2A4k4ygtasVNehkFFccpt07Efrn716P68+fd7dL80pxp1r8YSM0l+eoUrXYzxQIBAKBQCAQCARXQKCvXr0azzzzDKK4AX5sbCxeeuklbN68GRURY842T79sY8Rl+1xniCSMfGHcskn5gM7gbi92Laa5G/IPsL+2iijQnU6Ejv9ZIbbVOCp50vKNB6Qe7jy63Byp1VoAhPz1B4L+mwnIfdTz82E4K03q2Os3gCMqxsulPffH35B6Jp3dFKseHx/QZwoEAoFAIBAIBIIr4OJulgf9HBkZGTAaK6YPnTFvH/tri2xxeT/Y4t+Ru9LAPjCohNq1XIduzD9UYSPoxo0bEPLPFPe/dbneAt0ZHePluM5D4lxL2Gt+3v59iL5vDMK++UL6t6vm3REXB6ePCDozijOZ2M0ZFs4eMg+4KfAvKRAIBAKBQCAQCC6vQKdac6o5J5M4MoUrKChg6e6vvfYaBg4ciIqcOm0Lb3xZPzeQdGXjdqk2Xt0LXX8NCvSKHEE3nFLuL71WBD3Cv0M7lT9QFD0QbM2kyabg/2ZJn+8yoLPXkxzrndHRfmvQs6bPRuF9DyL3W08NvEAgEAgEAoFAICg7yiS8/cILL+Czzz7DiBEjYLVaMWzYMBgMBtx8883suYrI5aptDv3+GxgOH4TOXAQ8MS4gwy/qNa3Zaq3gGmu15nTCUHiS3bWH1UNFQ5eXx/46jUappZ5GqrrO4p2ZwhO0cjnsNXz0f+dw6nTImjYbcc3qwbhvD/SnT7nr32316kuv4SLoOqfTaxm2dh2Q165DAN9MIBAIBAKBQCAQXDGBvmvXLjz99NN46qmncPr0adjtdtSoUQPh4VJKbIXD6eBSpy9hizW7HRFvvOz59z9/Q3f/Q8W/T2UmJju5X2sp7jprGnQOM5zQwRFStcIKdEfV6iyaTi3TvF6jSmu3tmwN064discMp6U+8H4hl/a4ONhatoJpx3bWvs+4VfKHsDdqwv46wzmvBY10eoFAIBAIBAKBQFABUtwfe+wxHD9+HCEhIWjQoAEaN25cccW5q2WZzlHI3NHl6PSlQJef5/2YK4pKba98vk+V0iynuF9rAt1QeJr9dQQlAXr/bcHKI7r8XPbXXlWaXHBH0OXe5IRaoHftXqrPklPWHQmJ7K/h/Fl3b3VL7z7Si/Sey4FOw1NCIBAIBAKBQCAQVACBTqKcouhXC8Y8qa7ZHl4f0BsveQRV8Zgrilo0bKTP91Hvax5HaC3pcWs6dLbA6pGvBvRFyeyvI7Q6KiKeCLok0PU52QieMgkJtZIQ/O8/0mvUAr1bD/d9c59+AX+WM0Sa8HFGSmnsQXP/YyLcXqs27I00fBZ0pflGAoFAIBAIBAKB4GIoE/UZHR2NN954A1999RWqV6+OoCCpRZPMxIkTUZEwuNLbL7XxmJZAl8W3o0oV3+9TmYk5jVFwmGKht2ZAX3gS9svtPH+FMJglgW4PqYEKLdCrVJP+XViIqCceYfejHr4PqSNGSd4EJMzbd4QjPh7Wzl3c7+drxovFFUGXjeBM27a4l8uc2l3kP/M8gufPRdHouy7+CwoEAoFAIBAIBILLH0Fv0qQJS3O/7bbb0L17d3Ts2FFxq7gGcQ0vsUDL9Sm+HUlVik1xJzd3ioReq2nu+kJXBD2kYkbQ9W6B7mNfOxzuVPPsiVOQM3GKou1aScLcTmqVxkR9tCIy76iirN0v+L/XkLlyg/t1AoGgfLD05CKsP7u2TJa14vQyrDkjlbhcDAczDuCfg1Pg1DCV1GJ7ylbMPSb9ZslY7Bb8tf8PnM4NwEsDQJ41D3/s+x2pBans37mWHPy+51dkFKVrvj69MJ29nl5X7LItufhp53f4bc8vKLQVYsqBSTiWJXW7uFho2RP3/oa0wrRSvT+lIAV/7puAfGt+QK8/mXMCk/f/Catdat1K34O+j91h97nsAmuB+7E9absx8/D0Uq3r4cxD+GzLx1h+amlAr99xYRv+t+UjbD6/0f0YrTcdF6dyJCPY2UdmYHfqTr/LOZt3BpP2TUSRrXx5qGSbs9i+KG69lpxciA3n1ms+t+ncRraNaFsRdC2ga0JZQscmHft0jgVyPNN5VdrjWWZV8gp2EwgElyCCPm7cOFxNGF2tu+yXuMWaZoq7y8VdLZy02nFV6n89+5uxehMT6KacbTAUXDsC3VBUsQW67EHgiIqGIzwCerUnAV8HHuJdY29r2hxwpcIXi8Hg/iweR1JSyVdcIBBcVlLyz+P2uTez++cfyYJeV/q5dRKqt/w3jN0/9eAFhBhDSr2sHlOkCXhaxuB60jL90X+69Ju1/JZ1aBbfnN3/cdd3eGf96wg3ReD4A2eLXcarq1/EXwf+wISE8VgyahXuWziGTTiQcPmi97derx+7YDQ2nlvPbt/c4L9F5OQDf+LVtf8nrePppVhwfC67f+HRiy8de3nNC0wgTz88FbOGzS/x+2+eNRgHMw9gT9oufHjd/4p9fadJreFwOpBvzcP9LR9G57/assd10OHWxqMVrx0xcxAOZx1SLLv31G7sb5WIauhUpXOJ1vWZFY+z7U0ce+AsIkycAakGd8y9BamFF/D1ts9x4sHz7LGfdn2Pt9a/iujgGEweNA33L7q72H3R95+ebDk0OfFy59dRXhgw/QYcyTqMlILzeKrdcz4nF0bPHaX5HWkCbPisgbA6rGySZ/uYfRg6cwB7bu/Yo0gISyiT9Xx97UuYduhvNlEwaZD/scWk/RPx2tqXcDTrCN7s+m6pPo8mAm6ePYTdP/HAeYSZwkq1HIHgaqRMIugvvfSS31tF47KluOd7z4Trz0kDFEflyr7fR3Xqds8sODmAO+RWa4XXTqs1MvMj7BVVoMtt1iIi4Yz07neuKyr0qiEnMmcvRN4b76LoVs8gi0wF8159C5kLliFr6kyND9NrpsU7KvvO1BAIBOWDc/ke4UqC62LIs3jeX2ALLBpbHGvPrC7R6w9k7HPfX3V6eYm+16yjM9jfXalSNwsS58Tc48rIvIwsFKcfmlrsstMKpag8sfD4PPf9QDME/EHinChtFgSJc0KdgeALEueEOiK7NUXq3sFD4pyYd3yO330VKOfzz7nvZxVlFvt6EtVEga3Ava0Xn1zgjj4fyNgf0OfKy1lyqmwjyxcDZQKQOCdWuo51LeRMAUKd5UDbgMQ5QSKfotcyWebit2+g/HdUGjssPrmw2NeezZOuSekXEUHPMXvKNYvsnDmuQCAoG4GuxmazMVf3efPmITY2FhUKez70NlcUO7T4/tIlxmpF1JjbEPbx+9op7i7h7UjyL9B1WZ5+6U6jyZ3iTjXo15xJXAUU6GH/+wimTRvYfWdEBJwaXQ/kNHQnRb+NnmQXW+cuKHzsCXc9OXtNcDAKn3gatrbtYe3VG+b+0uy6+3lXBJ1/D2H3U0ohEAgC5+vtX+D2OSOxLWULBv3b1y3EKK27199dMXB6H1wokARESaF0a5ls16CWUkspijb14GS/76WU1ZGzh7gH9XanZ/BfaC3EV9s+w+g5N7NU89ISSNo1LzrMdk92ULChZB04DDrpWkYcyZSED9Gpsv8or1Fl+Pr8iqfxzPLHsfDEfNz0bz+WAl7IpSDzmQUZRRmK99K2umverfh084eKxymlm/Y97ZdnVzwR0Pf5cOM7uGfBne7t88baV/DAwrFuga1Gx3mG/LjzW9y74C5Faroa+h78BENEkDQZTGUBI2bdpEj9p+XcPHsoft71vfux49nHMGTGjdh4Tvq9krE5bLh7/mh8uMk7espPtsjp0lK0dCh+3f2T4rXq70nL5f8STjjLdLKkJNB5M3LWYIzf83Op3r/xvGeCpGGs76BPkb1I8/wgzhdIWQXy9soye8Z//HbSYtaRf9nxzU8AfLTxPYydf4fXREC3ah4TWspC8EeORboOmbn1LilF3HVtztHZGDyjPzvetPj38D/seTq/6JzxB52H9J2p1ELmm+1fsuuzvG2pXIDOYa3tR+UIlIHy8OJ7L/vxJhCUaYr7Bx98oPn4L7/8gkOHPCdIRcBQ5IpgGyKY+VpZE7RgLoIXzGO33I8+8/k6h8ttWwtqx6XPzFAIuWuuF7rDDIMlpcKaxIV/9J77PhPoEd4RdLnFGh89VxDCpaZyAp7BDeL4FmoOdQRdpLgLBGUCpWkTS08tZn9JpFGq6uyjM7EvfQ97bMXppbil0e0lXjYvEHNcguqDje+wSQC6+Vvmi6ueYX9JYDzR9hnFgJoilu9ueJPdn3NsFkY0kFJsL4VA56P1/IRDUIkFuieusCtth+fxYjquGHSe57OKsvD73l/Z/T/3T2B/31j3CqpGVNNcR4qAxoXGuf8988h0Juzp9lwHKSWeuHXOcPd92i+vdX4LMSGVfK4TDf4/2/oJu78lZTPaJrbD9zu/Zv8el/okWiW28XqPnourUIox0TKhlc/U6RBDKDLNnuMn3CRNBr+w6mn294ed3ypE16rk5ewm892Or9jfwTP6KVKv96fvxfzjc1j98P91fNVnloY8MTR+90/uZb94/bOKY5CHjk+TwQS7U1t40uvl7+ALSuMvK37Z/SNWn1nJbvc2f6DE76ftpHVMqeFFucVuVqR7U4kLD0XRA82CeWDRWPb3590/4N3u0lj90y0fsb8rk5ejd80+imNFZtGJ+XigpWRaq4V8HSpSTSaUBL7W/bmVT7K/Tyx7BP8N947gP7z4Pvd98ir4v06v+VyufB4+uOgeLL9Vmih9e730evJVoBKPjzZJYzA6hwfVHax4/697fmITBXT7v46voXb0pWu3LBBc1gi6zI033ojFi6XBSkVBb5YufI5g3xHsi8Fw+rTns7L8pCaFedfi5D/7ovS+nBzo0j2GOBSJ95jEnQR8zLxfTehdEylOfQicJs/AqUKg8h5gKe4R3jV67hZrocXXiDoN6sGpaoBikFPc1TXol+Y4FwhKCokVioj6ihzS88eyj7K/NGDl0zwDWfb+9H3M1Ew9QOTTcYuD0nXJdEyNv+gzL4j5lE5fdahag3jeAE1ehpzOGyhyVNPMrWsBJ6wDNR/zt2x/8FFeXpQFGZRdX4rDoPdE0M9zwoWPxsnbiczPtN6Xb/H+rrmWXJ8mXmqjuKOulOXisLqic77SvHnhbNIbcYFb31yr9vEt+w/I5m+E2mSLj/qFGkMU24nEHw+ZwQXKoQzJQJeQzxva93wUku7z0WBZhKmzEOT13JfmEbD88Wnjorv89wnkOOWzDHxxIvs4WxYfWdYiU2Pf0TWKrlXyevHXJh7a73J6u3riQg1/LpodFsVn8eZ5BL8//WVP0DrJhBu9x5Tq9/LHxoITkk8CnRNncpOl75h1xB11lzN51MeTGjoPqcxC63qttT3UkxG+oHWnZfvLSuInMmTU11ct88gM7hpP115539J2oM+lZdB9gaBCCvSCggJMnToVlSr5nj0uj+jNrgh6cNVLs/xUz8VEn+wR6zyUrixHPHlsrdq4U9wVEfT8fDiCq8GpM0LntEBvDnzAWdEN4lj9eQA/xuUJwwXlj4YUQdcS6NIPiTM4ABOnYiPoBi+BzgzjNCaCBIIrwW97f0HXye3wyWbtjKwvtn6KzpPa4KXVz6HFhIZo+lu9gJdN0eGef3dmpmaLT0i1rUTbiU3RckIjnHPVU/qDBsoNx9dCk9/qeA1seWHlLzKW7UoL1YJEX+uJTdBjsnfnk0xFBF1aho0TaIFg1EudHMycCM0so/rVQERTPhfp478PL9CLS9cl9FyKOz+Y5wfeNJhuPbEpWvzewP2YkXsfiXE1CaGJXiJfhoyweM7knVF8lr/JGdr/3V1meur38EKLSg94QeHrmJIFOv/8jgvbFRNbvEAOMYYqJqHU+4qi4IHSfUoH9wQVn3YtH5PS8vM0RZhdY9/+uOtb3DSjr+aEFl+Kwad05/mYuChJBJ1M0DpOaoU6P1dB+z9baNblayFvYzKzo2vV9zu/cadL07Xp0y0fKl7b/PcGrMQkkIksOSKtFr1kxvbx5vcVrz3PeVKoMxB4eBd9OcOEP16dcPi8Vq0/u4Zd526c3htt/mjKDOTIaPCdDW+w53PlFHebuViDvCEz+mPYrEFez2ltDwdXzuAPuobU/7UGmv9e30+HBqfm5A2/DbQmV/nJpMeXPuz+3aHtMGB6b2agSPcDnagTCK6YQG/cuDFrtcbf2rVrx/qfP/20lEZV4SLoIZemNtdw3FNfYzipPXNLhl9E7vsfKx53xEqRYmq9xQt9ZjamN8LhSvW+FtLcZYM4+TtXJPTnNQR6uIZAz5QGz04+ld0XhsBS3HmTOFur1iVZbYHgkvJ/q551D3a1+GCTVHco14LyIqQ4+Mj5fs5wSh74rz9XvHEXLwDP5CmjJ/6i8PygN8fs24F6oWvi4FTuSb8DRjlyZfORAszDD0SD9EFe68Ovt1b7rUAJpC0TP6mhEOh6T4p7IK3QjFyqekrBOc39Q/X5aiHHp8BrRe5oosBXui4vEOVMBxn5ONQS6iQ2afJHLbblyQp++1Okkhfs/H2t6PB57rvTd+UjvXymhklvUny+vyhuIJzMOe617vxxrV6+LMK0jleqt1cjb08rJ5zO5Xu2d/5Frj/xxValCz61cwsEMmsj3tv4lvTXVR4iC2h+cpH2u4WLhBd3nsjntVqga20jZQQ9PyDTQ/n84wWp+pznr6k0WUYTL3J5DnVb4Ese5PX1dx2mc0I2ICRTR3X0Wmt7OAK8DvGTZJQN4Q9+8oomuPh1tqr2EZ2HfNmAvP7y787+jH3uCbulJytWhrDgGhToJMQnTJjgvtG/J0+ejDVr1mDwYGVtR8WJoJehQC8qYqZwxp3bYTjqmXHTn/Yl0KWoZtH9D6Pwbk/djZPLRtCf8UTfZbM5j1Hc1S/QDUXSxdke4qkZvOw4nQj94RuYlgV2kQ6ZNBEhv/+KiGeV5kEkzrVq0MM/cc2aBxBBdxo90SEtge7UaLNm7eYxhBEISgoN4KjXsdo8qjTwA7U60XUDfh8NvMh5mI9SacFHmQIRgcWlqqsjvb7ElHqwzUcap+2bhqeWjcOyU0uKjcQqI+jS+ts1SgGol/j7G952p3bzA1E5gs4/xossmnSgusxAsgnY53MDaT4SxlqJuRzT6buRORN9N16gp3Mp+3ytsfzdKKX0g41vs2gtRXxp0kY2jwokxf1otnfvcgcXkc01e0dh6bjwFUEnh2kauJMhGgkNfoKm0HVsyeJNna7N7zt1Ci2fAUDHFy+6+X3DHxtyBF19zCkEM3eMk/s3/xy1qJvvah9XEuTPlSPw/Ofzx7VadMn/5lPW/RkEPr/yaXYM8yUcvBiTl0fr8fGm9zXNzORfPyprocwbtemaOi1b69yjFHY6Bvl9TfuS7/vdLqkDfKF1DFKaN63PmjOr3OcQXUPJsO9dV2RaXYZC/gL+ujr4S3Hnv7csOvnHHHAwE0uaWKDH1dvJX992+RjzV96jFu8kpGlbk6EmlWVoCnTuukZ93n9wZSmoOcZtX/napkber/z3IJNJ+ZyV1l/KRKJz4tfdP2qer76gFoDFQe0f6bqh3rZq6Prx1rrX8Oa6V4vtfECTBfOOBZb5Qm3zyPQuECi77Ked0kQMD5WB0LnAlwxdDjKK0tm14GIzFeg4+Hjtx367KFy1JnEzZszAK6+8gghVmm52djaeeOIJfPWVNONWETAUnStzgR723VcI//RDdnNyKcWG06c0X89HTJ1c/2tqxeXU66FzOGBITvbqp21nrdaWw1Bw9bdau9SlCIFgWrcGEa+/zO6nXvA/6NelpCDy6XE+FmTSTHE3bd2iENda2Oo3gPHIYZiHDg8ogg5XdgZhHiT1HxUISgP1jJYdnC+2T/Tu1J3u+9UjA++eQQNe6oNNXFe9J+rFeFKaefgoEy8mSgKfyqkWcnwk1+t93ABWHtTSgGHUP6PcJkX77vHUimrB16DLEww2V9slnjHzbsfe9N3MOZp6bfPRTKNL2PLihBduX26Toopbzm/CP0Nm+V0f6Xt5liOLNlpPMnkiBtUdgtvmjGD3G8c2Vgyi+UEwP3iWI7+D/+3PBNqRrCNM/JPQp7Tk+SOXKXrAK4UyJ9A5d3f3si05bLtTBForxZ0XtWpo2Z9v/Rifb/2UCSo5G4Fffz7l272NbEWKOnP++9eMqqXY/uQgn8L9m7/Pb2v5+6vra+kYbIbmXpMFJKCSc5XldHfPL7lRYf2YBjiUedAtqvj147edOnNBnrzRSnEng0C1iFudvILdePhJI7mWmRz0v93xJUszP/7AWc0sAzr+SMySwP+k5+fu5y0a546aQf/28SoBoYmlA1w2TowfgcbXnstQ9HX/xrfd18x/Dk3RdMHnz1GtSQx+YsefSRxfziILef46RhME/adfz+5HmCK9Ji78iUr5XPXn4s4LYXmbJOeechtqvtVVmbrP1ombSLt97s3sb6uENn7LTnzVwcvu//y1gcofqHuF+niVz4nIoMDNoUONPgx8OfpN6+X2mPhwgMccWM2Mw9PZ8UzUiKyB+1o8pPk6cqaXs81SHsn267dA1+VHl0jGhv1qD1AYXWpxx7xb2N/2lTuibVJ79+MjZg/GqZwT2Jm6A1Nu+heXi2+3f4Wvt3+OL7Z9elFjjOWnl+LFJS+WyVilQgj07du346QrRXvmzJlo1qyZl0A/duwYi6JXJOToc1n21jbu9DjN6go8FyydzUeKoiuCrk5dptp0Z1g4i5jrz3AC3WU6Zg+tJb3lGoigyyZxjpArJ9D1PiZYNF+b7z0gtDVoiNyvpHY2WgJdxrTbI17UZM+YC9OKZTAPG6l8Qn3RlkW+TofMJauYb4G9UeOA118gUEOD9bKCH8j5imJqwQ+WKTrjU6Bzy5dTM0ua0l3I9elVR35S8n1HFvjBo/zZ/IBRFt/+BlqaKe4agofEOSG3eOPFkixK+EH3OY3UfHJ2DgT+e8kijJ8Q4Afuu1J3olFsE22BzpvouYSeHD1de2aV+7tvTdni1S6Nj57y+1greknbi14TERSuGUGnzw7yEYkrtBZgGVfPy6cuy8euVpkDbWveVDDcFMG2lfydeJHNIuh8ijv3nFakkRfI6mOQF8y0fstcnQVKS5gxHJXDq0oC3SWQ+Wgan56tTnGX/82nuMuRzUANAvmJGHlbbDovZe7Q9qR1ktvH8TXocqR5wt5fFQKdT5/3hZY/Ax23fPQ630/9t9YkkZpjWUcDntS7ueGtLJK4/cK2EkTQOUNI17ry5z9//1DmAa+IuS/hS6+TzwF/Lu68ECZo/SNMEX79BHiB7i+FnZ8AKfQxSeCJoHvWg9ab77kuT9zJ7ONc94ujJGVWq5OlrAlf8BPHWoaKWq/LMmeiUojvVtb89YXuFyfQPa9V/p6ROOd/Vy4XZ/JOK45zvrNByZbjycC5JlLcQ0ND8fXXX7PoOB3c1FKN7ss3em758uV47jnt1h/lEocFxrx97K4tQpqJvhLINehejweRQA/zcoN3C/RrqNVaeYigU4p7wNi901Ft7TqwW3EC3R/kwm6+dTRAxoL8qvmKoNPntmwNa5dupfo8gYBSmFtPaKIYyJD4ITOg+xfeXez76fdizLzbWBsyOZ2xSBGdDnzQsyd9l08jLx5+ECtHoNXRoe93fIPqP8Sj7z89NdM2+ciTWjDxqclq+GXJxkrq99M2UZg3qa4tWinufAS97cRmmm7U/OfIg21++6pFHhEVFO1OLyUDPbW4o6jMdVM64bmVT7kfowkH+p58emqDX2sq1p/PYkjn0oT5wfPI2YNZb26tgWqDmIZ+J1b476UVveT3vWYE3Zyt6IPOs+TUIuxM3a75XIFr/X0JdHnfDas/Am0S27q+VzpL8eV7a0s16Nop7rwDNh3nt/w3zH+KOyeYaVB9sWaASeFJbmElH1P85/FlI94p7rleE0ryOaEVHS6ullpePp9JUe+X6hg5239GGKUEt/ujOUtzVZ/7gRjPycdjSgD13/RZ1NbMH7Q9fE1Q0Ln69PJxuGFqD/d3v6PJGDZR4lWDbstn1ws6JqhfO38OKloqutaVv47xE6MUDVZvF63zgVLE+QwNPkqvhhfCxPsb38b6c+v8+iE4XeuvMHJT1YmrOyv4WgetCDptW/mclc8Vfvmpflzh1Yxb+hBL/fYF/x3ouF14ZCHaTmyuKXT5bc9vl5dXP4+Gv9ZEs9/qs1IfuTNEcaVVBH+sfrv9S7Sa0Jil3GvBn58rTy9j1376DeAJU3UCoOOg99TuLDX/UlAn2mMEW/vnymzcUBpCDZ6sZF9dYnxB1yoaEzy25EFUGIFOxnBLly7FsmXL0KFDB8yaNYvdl2/03H///YfRo0eXaLkUlb/vvvvQpk0b9OrViwl/mdOnT2Ps2LFo3bo1Bg4cWObReRLn5ILuMMbA4arnLk8CnYkwWaCfOuFVg+5gKe6AoeBwycRjBcTgEuj2KxhBp1IDN8Vsb12h9yx3wUOPed6uYRInk/9/r5Zi5XwLdIHgYqAU5rP5ZxRpqJS6SU7Is4/OKFZgUw3nghPz2CCFaqbVA0l1WqQ/9nItonyJMvVA2ld7oJlHprGBGgkxrYgNLyTVLYP81S0qTOJcQoZ/Pw0Y1ANQ9UCZj4jK4ouv6U3OO80Gv2p4Qy15YF5cBJ0iNCS4KL2URNi9C+5SPE81/wcy9rN9zUOi21dKLEUw+Ag3pQrLNeWKmlinw12fq0aOnKujVnK0lI4beUDsq45e3vfaEfRsv+m6vpCPC742WYaWl+FKcadIl1yzSm7+svcALxK3Xdjq/je/PLXoXXF6GUs3JWq4SkL4SSL+eDmYKWWZxIWUvh1p5fAqiAjyCHQazPM14vyEgJeLu0aKu7zPS9pij18+PyFHQoy/HlE2itqQbOyC0ex6M+q/oQoPBCI9wLpjJtD5HuQ+otdzj80udllkPEgp/lrQtYnc23en7XRniUQFRbkjiPyEAq0DmRbSMUG92vmJOoVA14ig847+ocYwr+PfV4Sbrjf8uvqCF8Iy8479V+zyZe8EGa1yHv567yuS7dTK0LKbFZF9OlcoQ0ZrMigQqOzFF4qJK0su7p19LzsGaXLa30Quf77/svtHdqzQ+UYeIfncb4dWGzkefhKNyiko88KX0OR/I5eeWszeO/voTMVrKANIPRG1J20XS80vrbeLP6yqTiU0bijJBL5MsNEj0EvSnpWg70djAtp+pfnsi6FMRu1//PEHoqOV/ZUJi8WCnTt9p+eqcTgcePDBB1lrNqprf+utt/D9998zoU8/vI899hji4+Mxffp0DB06FOPGjcPZs4EZ2gSCMUf6wbNFtb641l1OJ0zr10KXlla2At1oZCnuavSuCLotoimc+jDorZkwuDIBrkocFugtqeUrgs6XK+TlIWj2DBg3rPc8Vqg8sXM/+xr2Zp4sDV8R9Oxf/0DBMy+UfN302iZxgmsPMnFLLUhlokXd83j7ue3F9gEOBH6gV9yggTd8kYUEP2jU6gPuayDM164f5Xr+0mQBPzjRMonjew1TVFYdlVKj1du52PVL28VSR9UC0fv9ys+jgTKZVMnbSlGnbdFOcacBrbq9FD8AXnt2NYs6LeGiIr7c53nxQ9tO3s50HK07qz0xTsvy16ZMvY0Wufosa+1vLbTKA4ih9Ye7B/ZyuyxfEyYUSV51egXO5nqPG9hAvQTlFTLye7Q+k45r2RCOBLochabzRb3Pab34yCQdp/IAVSvFXXbX7lZNMvuUj18aK8077hFBMg0qNUJpqRxW2b3uJMZnHpmuiESdyDnOJtzos73LP86zSZ213HEjTxbxtfyBQtHFbSlb3EJq6117cGMddQsvnd/Wh+pJBNp3tK9ocshfhI22OYmX4uq/5fKEpLDKPpdFnxnsY4JCK208Kjga4Sbv8R+dn7xY5c3T+OXQ+bf+7DrFsf/v4X/c9ymbQU6Jl7No+IkXnrmcyFZPytGEws4LUraJLIRrR9XBO90+8EphT9UQw2R+SWKVvDk8n+EdQecFvK/rjjxhx08UULSdF+z0HbWMM6uEl3xsSdfktWdWu89b/jeFxDG//9TXGuXESa7PbCF+cslf9xBfv8XpRdq6hP+NlDOX1JPedE7xmXP8JB3f0q+ssGhkTqhd931BmQLUq54mOjeeWx9Qq1O6/q5OXsmuAbQ/aNJLzsIg5EnlCmUSR/Xob775Jo4cOcJENo/BYMCePdIPSXGkpaWxFm20LKpnr127Nrp06YKtW7cyYU4R9ClTpiAsLAz16tXD+vXrmVh//PHHy+JruEWtLbLFRS2HaoJjbh0Oe7XqyNhecqEsu7hrPqfRt1pOcYc+CNZKXRCUvhRBGStQGNkMVyNyn3enLghOU+mjAhcNf6ybzczsjQj/6F2E/Sg5YWas2Qx7w0ZeEXQy/FP824dAtzdtWqpVs9euo/x33cB7RguuHujHhtKGKXJHdZf0I7z5zl2oFVWb/Xi1ndi2TIxTznE1XlQLS8v3BS/+ZPHCD060Blu+BBc/WJBTHklMUro9/72Ki6DTAI0f0GsJbl4kewlsHwP1G6Z2V/xbnhzQEvjkqCxzoeAC+vzTAzrosWfsIcWAkuoOpXVWbic99CwKJq8LrS+fKrn5/EbWx5iHH3zwkIu64nv80wO77j6IRxbfz4S+L1Hiqx7yePZRL1FExj0PtXqsWHdj9WSO+vgYWn8kZh6RjIsG/tsHW+7c7bOG85NN77MooxY0KOPN+AJFXh+t99I+kNufUQRbFuAUBVP3r6Y0ernWmFzwad9Q9D0pLEkRNVPTtWp3VnYi98beeH6DV3SeqBdTHxu49OKSkBRexS2mZTNBHory0W3igCnuY45S0Gmb0n6mGw/t8xCE+Iwg+4MG2NSbm0gMS2IZBIPqDMYClTN9cem/PHQdenLZo0ywftrzS7YPtJh6cHJAE3MXXJ/dNK6ZzwlLOkYdPjLvtKKRLILuSnHnockeXkjR9bV3zb5e1ziKAg6ZcaPivZQJw3dTkCPo0cHRbCLQl5j5ZvsXPqPXHf5syf7uGLPffY2i9Hkto7dUjUkUOmYoG0hu5xaIsWdxkU3+mkHHntr3gj8XT7omrMkUka/1DwTyOnhp9fPs+Pmuz8+KrBYS5Pyk6qZzG9CzhmTQp95X8jmUbfHuDMFPsvMp7FponQOya70a/jdSPv7oN5VP06ft1uvvLjhw73HEhsQpfsvJu2SIa7K0rLBo/DbQZI13zyMlNLktm/ORkSPfJpO1hPSxgGEzBzEfl1/7/4HtF7ay41wuSyLo+zaNL92Y/IpF0N955x1Uq1YNP/zwg7s2/dVXX0VMTAw+/ljZy9sfiYmJ+OKLL5g4p4OChPnmzZvRsWNHFolv2rQpE+cy1Gt9xw6PAdvFYjDLrbsCdxHWImip9ENrkI3cLIENQNz46XvtDPe+QMsu7uyjYl2OkZkVy5yvNAKdGcRdTKbDxcJduHTcPjZt99T4GFyt9HSFhX4FOd9mzZ5UGbmffom8V96AvZ626VVxFDzxLArvGouCJ55B4Z13o+BF716qgqufhSfmsb8kDORBCLl0l9QMpyQmLP4czQl+MCkLb76GUCuKKacJ+5thp2gCDe60BCQ/APO0B/Kcs5Qiykd2iougqwWTP6MmHjY4ZMJZ7XSdr1gfSgOl7UDrQRFvPlokp9/zWQsEXQr5ulyacFC/pjjkGkOtFH+KLvqKnsvb31ctKG07uXd428R27O+hjIOKwXNsSCx61+zjc/mUDUCRNbWgV7+HBlbq1NnqETXYX1/iXEZeNonZQJGPV3lSoGd1ftBtUaS4k1O29F3y3MeMug57QJ2b3O7g8vnhaz/GhyagZUJrdv9Y9jE2bjrhI8rjy0AxECgSrBW9VUORdTn6VznMdyccOYLOH6+BIotf4vUub2vuL2qpp+Wv4AuaXJGjydQGLdBWW/J+4b8H7QM5gl49sobfz/RVUsH3tJchd3Etkyy6tvH12Pz1la83Lw4ShbKAlJ3MtVoHqqFrrvw+fpLqYMYB97lBAl3r+KOJSO/l2RXinEgr8J+N6jvF3bsGnc5xPqWdviOf8i5f+1slek8oFMeX2z5ztzaj40AtoI9nHdeMPvtKcdc6DqnNYyDeJ+x5jXPAV0mC1jWGovXydZtH/n3gjzXeDLOssGqUNvgrqZDZkiKNcQhenPub7KFjRDZZpY4h8iQUmTLKXGy7tysSQT98+DA++eQTFtUmN3eTyYQ77rgDcXFx+Pnnn1m9eEnp3bs3S1+//vrr0b9/f7z//vtMwPPQ8s+fD3yWVMaXptO7ems7Q6tfXIY73688OxP6nJJFpyhK7v58bj3oMV6g26vXgCH5NBPo8uttMR3c6fpXUrtejvpzSm8vi+8oL6Oky9LZPBeP6HvvQu5X38FRq7ai1z259pu2bETU/VIrKL7mnP88hWAPDYX57nuk96OURIQj/zPlj1x5PBxKu+2vFehH/u31r2Nv+h480mocrq8pRYYDRStdk+oH2bWEi9jSv/y5iBfHuXzPjzi1Pdtwx1afgoD/kaMWVPSxZgffr7fAa32yAhgwk8Cm9D3+W8w68i/LIlC4TFtz2SCQF/dkvqMerNDH0/Z7ZfWLTASFcHVsJPR2zd3JIngf9/zMKxrqjx2p27zquqcf/ltRy8jX/s06+q9XmjYNhNUGSzQU5YXpgYx9eHqFj9aOPmiR0IqlA1Jqvpb48hVxJ+Yfn6MYzPiKytO2pFprOg4pM0AWxZNvmoY2ie2Q+J13uZxMmmpQS4SZlCVhDywa6/WavrX747c9Hj+b4rihZl8v08FKwZVQJaKq18QWbZdJ+ydghavH7p1N72bpyJTWbXYUubNEaAJCruP+adf3nuWGxLoH0hSl7l2zN3uM9jMt92DGfhzJ1DZApChf3Zi6rLSBhAa1imqd1NbHawOfdFBTJaJyQANwErn0PYnK4ZWZV4UWtM9J05am5v+C6xggs7JbGt3GzlOK+PLQcfjRZt8trfwJPDLE02qNp4WU2eJk6yJfa3MsWW5hWy3Sdzeg3/b85D5mZG6sPZDV2WapPp9qf00GI8K4SZK7m92LCXvHM7F5JFsZQZ9x+B/8tf9Pn9kuWvDRcnl7vrvhzYDeS/vxXH46bvnPE0HdkrIRX2yVsi1CTWFICItnqfO8QJI9SHi00rq1znv158s/F/xvHkWCb/lvKCK41mlUcsT3VqfyjPkaJSEdK3dCoPxzaDLrMkFGlvK5vD9jr99yL9oO/E+uhfsNJIFOz2llAu1wlQ/Ibuv+fra1Pp9+97Te4+s3bHPKRq/HKDOClsH/ltPEhnq5NAlJGQWD6g5Gv9rK7A1fUHkEXR9f7vS6Zoo7bSet9adShZfXvIhRDW/1K+JZ6ZDDgnfWv8EyeCjz6PUu7yhMQOtE19V8L51nl3OsWiYCnaLmlMpO1K1bFwcPHkTPnj3RsmVLHD9eup7c5ARPKe+U7v7BBx+gsLAQQUHKeh36N9W5l5S4OB/5DRZJ+EVVbgDEFpdE4Qe9ZxATl3YW0Gix5Y/Q2GiExrs+P9TznePpsUqeHyJDu7ZA8mnoc3Ol54joLsBmKRsgPsIMhMTjqiNVGiiYomt6vncZ4PO4CODsoZ7osUMHALt2AemegUyUwQEMlNLNeGJqJAH8ujfypKQbbNYy/V4VgRJv+2uEE1kn8M12qTcqtbEe1XZYid4fFOztPZBceIIdX5HpHmETWSlIIUBLSppFmar4+PKHsekBzyw2z3lXi0SiSJ/H1sWoynRVr4/jQmCRILMpB+HhIX7FGhEU6USYzffPnyHEwdaLXHcpdZf4behv7uc3u7IQiJuaDEChPXCBrk4z1TIaInMorXrP6lHVkZyTjFRnsleU36pTip3HlpbcdbZF5WZMoB/O9tTNy/C161pQvZ7BZkCwLRgJqQnIrJSJ/AjPOp7MlcYCDZPqIfZYLDIKM5CpO++OuleJj0dCgv8exIX6bGkmwjVI+urGrwK6Vnav28Ut0Cufq4xOGzth+fXLkRMtTZ5HBUdJqY8uHunyoFtEG61GRGdHI6JeBJIiExUCvfrp6ihaUoAtnTa70ybrVq6B6PMRqHOsDmxbioC6DiAWaFC1Ni7YziAsP4xtn54re2JP8z2wDbS5B/VdanRB7apV2edcSE7BL1t/hN2oEixOoP2W9jhX5Rwat26IGpUTUTO6Jk5mn2TibvGRhYABqBRaCUEnghBWEIbjdY+jZU1Pm7uS0qhqPRzP9I52U0TXXGhGrZO1cKL2CTgMDreoaJzUSGF6x0OR3bgqkXAWOKC369n7tKDvdSpbKeL2XNjFjrPw8HD38WINrqbZL5onKjsK+eH5bHuSOd11ta7DkmPepQCn807BEaw8l57o+AS+2qSc8CZowio8xgiD3uCO9qXjnDtqfEfbW/HhRqnPOX3eqpOrkBieiAv5F7zEORHp8hgq0inP7ZiQaOmaHe65Znet04kJdAuKkJHvEXJnC5Lx1obXNH0W/FHg9IxT4yO0S1Vqx9Rmv0lqImJMGDfz/xSTWp9s/tB9Pyo0gu2r+nH1sO2c70k8X23WsmwZfo8LQ7DTfR1Qt3ZTb2et8o+PN0v18Ty9G/eAcaFRs52lmseWePcsP5i/G9kOaSw4qMEgzD2sLMGwG83Ka5fRcw4U2vPZc/Z0DT8W7rqfYUn1e/3LsmhPNFWKDWPHLI8pS3vydU+Wd/cKXYiN/YbyEwhWqL4P9blf8Rn+2v8HuznfCMy4us+3PdnfVHMKkiKSvJ4PjzJpfue357+Cvw/8xW5f3iiNmbRwBJnx64Hv8MPOb92PWXRFaJkolWYwTNr7/EzBqcs6Vi0Tgd65c2f873//Y2nt5L7++++/45ZbbmFu7lFR/n9wfdGihVQHbjabWau2kSNHMpHOQ+I8xE86uC/S03O9TbcdFsQVpbDf/fTCSnCmlUxUe5bjQMSxk5DXKnfrToRlZtHvpaIFlo5bgewZcwCnA9EjpDYhBU49ClyfH1ZogZzUlJaWi3BDEORLdEGdBtJzRUVIO5MmubybLagUWheGwmPIPrkW1jipVutqIjzjONsGBUhwb6eLgWbE6KTTPC5kiopoRgiwWt0tzULTs6BI+jtzBllrNkFKTpTIO3UWWtXlGVYdHPy6B0fBPZWSnMz29bVAQNv+KoTSnCm1lY8S02O8KKV/n87meg0X5OBCarbf9jxq8lXmhMS+lP3s+MrK8fzQn01JY1E/HvociuCbDCaW/kUDTnX7L5kTGUqjuc1nN7PPkL+TXCNI3zm70COEkjPOse+UnqNMOzty5hRzjpZJyfAfvaPoJkUcD5w5iuzc4tO6D585idRC362nUjLT2fonp3m2f3K6djRk2u5/kWcuWSp5aaDtXzeqPhPoKw4rU81J5GRfUF4z+KyBmMwY6Jw6ZMZ6f+cHWj4stXAyhWH87p/RYlcLND7cGKH1QrGz9U627JqnaiIvIg9p8Wnot6gfgs3BWNN9DaqdqYZ9TffBaDOi2d5m6La2G+LTpSvZ+aTz+OnBn5j4qnu0LhodbARnKyecFgO6He6GmjNrYu7f8/Do/kdxoNEBFNxhQ5ohF1G6aOgzdMiJymHLLwwtRGRuJK5ffj0WvrkQT0c9jZnDZuKbcT+iQ+1O0rXSCQRZgtByV0smSE1WEzK7Z+EJ61OIrRoHncGAhAsJ7DUjp49EbGYs4tLjsL3NdqQkpWDSM/9g0Pi+GDhvIA43OIw4VMX60VuRb8vHD6O+QvO9zbHm7tYkfyUAAN3TSURBVLUI6xWBJvuaQO/QM7E3doI0AdTwUEOcrHUSp2ucht4cguBDobjrj7tY7+8B4QNw9r6ziHVWhrPQiHvH3+veRnWP18XKPqtx4/wbURBWgPixiez71NpeB/2+7YeikCKs7bYWHTZ3YIJ8+sjpaLO9DQbOl7IS03tksddHFUajzbY26LK+CxJTE3G6+mmsf2QDBk0ciPCCcPxx5x8IskRi7YBNOJ11Co/OeRB1jteBvqsRu7N3IionCm23tWWP0cTFDUtvwOoeq9ln2g12hNqi4DQbUetELYQUheB4neMw2A0IiQ1Bn7l90HZ7W6THprN1PVPtDLJisjC09s2YsXEGm4w4W/Us6h2thyrnqqDVzlbYb92P5JyzuO2b23Cw4UF2LNGxRdufjqfzlc+zY6xO9XqIWhPFjp0FNy5g2/zGP25E3WN1MePxme7fSatVD5PFhOZ7mqP2idqIT4vHf3fOwUdD/ofDeYcwffzfGPXPKBxofAB9fh3AasPJJ4NMBe+fMhZD/xzCvuuSPkvQZ1IfrJ+yARG9IlC5RhX80n8CS/P9sehHtv60nzeO2Y6Of7Zmn7nm541ovLUxDjQ8AJvRhhWPrUSXoi44d+N5VNbXwuJRK9i1zKg3MaPOvw/+hR93fgedQ8fWlbbvqVqS2NTnGHHzPzcjZFYoareszSY9aFAaaYpi3/V4mkeUVtIlsnMzZlUMLsRfAGio7QRC94ehIKQQUCWiRORGsPOi8YHG7Jza2WonnFwwKSVHMmyjbACTMxhxaXHsmCwM84y7v7r+Bzyx9BEWdZah73H61HkcTfdtoGVwBrH1jzT4zo7xJ9DP5Sivva90fAMhxlC8v+Ft1qUgPTsLqak5LHpeFm7ilLEQZI5EpeBYr1T0QDmSchzHM6T91Sq2HeZCKdDPZV5QjPNyCzy/ITlFuey5Exf89+++kJuqWAb9PlM2CP1WEL5+lw4mn0BimDIj+Vy6dhnBqhPeWRi0Xnv1ynTv7EJpnXkOpHheo36OMiVoX/say+w6vwudq3q3Az6floFEXS57P5WWyGOoHWc8WV8Z2b6PAfod/2Kzx0OB2H52ByoZPcHM3ee0vcOSs86wserlEullItBfeeUVPP/881i0aBFuu+02TJs2jYl2iqpTBDxQKGJONeV9+nhqyurXrw+r1YqEhAQcO3bM6/XqtPdAoDGmepypLzoHHc2H6oPhMMV7+jOUkKh77kLwPE/EQ3/kCHSqFHdnXDx0aR73SkvHLjCkpihM4uT1c5qClOvNGcjZ6nEpa3RAmoyI7doOzqcMQB3AkLMLltirT6Drijwp7mUp6rSOCyJ4xjREPnI/a6vmiI5BOhn/UUp6kXdUL4ai6BwRr7+s+VmO8Eivz7I1bgLjAcm05VoSq/62/dUI1aVRP96BdW/CT/1+Z49Rv1Fqa/VBj09wX4uHWNT0/oVjcGfTsQpzlKEzBrK0wHWjt7p/hP2hlS5IBiq0rfnIQKHNjEjud5J+6AdO78PaD93f4kHW53TSoH/QReMHU6tdF6W57k3bi/7Teilqhq+rfr2iXpuiqE8sfZQNWnla/N4I++85jrhQyQTSV39qmbox9V3O7ef9DtCoVRd97xumXoffB0zy+bp8K7XsorGxJ2p4Klvb7X7JycU+TeLkASwNhGnQ58xysEG8JViV+eUE+i/sz0TPuq7rmBCxBlnRq0Zv7Ni1jQ2qj3Y/ympt0xekYu/knYjtF8te13pHa3Te0BmVsiqhQa16mHPTHPRd3BehhaGYestUOPQOPPTjQwgtko6XQw0OMTFEgp3E6eN9n4Z5RxGMoUaEZ4dj2MxhMDgMaLZbEtwk+AibwYZTNU8xUUm02ybVkm86tQk1TtdAlfPKmuPKKZXx+juv41SNU6h5WvJ16bSpE2zTitAuU3qvNU3aDo0PNsaCBrNR/bqaGLf5MQQVeg5Gu97OBEVEvjTVGZ0Tjbsn3o3NE9dhe9gmVL+uFu7ffT+qn1GlE68BTuAouxGP4lGFyz2tk7xeF6zn8MLvUrcMEuM5j2Xj1ITjsOsc7N9E9wndgAlAW7Ty2sdJF5LYrePmjth9YhtqbPNEdGm9H//mcWwv2gJLSpFbnMv0fLKH5zBY68Q/zSah8Xap5zvtsz5L+7i/9yvvK71EYt+PwYHcfRj0wUCE5Hom92ok10CNVzz1z7f9fRvWn1mF08ulY/gJPCE9MQcYBOVvFr2WGDFjhLSPjFZY2luAQuCe36XSK8Khc+Bo16NosF0qZYnLiMOQ/4a4I8shRcF44ocn2HewmCwIsnr26eH3pIE77Q/a93TLicxBVG4UWu5uyfY5HZ8ZIVmIny5Fc+sfr88G5MF50gT5bf+7FTuityLrWBbyknNw7557Fcfgwx8/hOMfH0LEiDCMnDUSeqceTfc3Re6DmTjV+DiqvloNrfRtMGz6MFRPrsa2Ge0/wg4bHt/9OPLa5CPrUDqMfY24edrNaHCkAbZ33I6qd1dDm71t0O+/flhftArD4MlsKkIh+qM/ttXbDofdiVYJUsmB3WJHiD0ElYJicf2y69FzlRQpJBb2W8gmi+LWxiFxr3R8jN0uXfuP1z6OI4+Sv4BUp0wZIBmxGQgzRuDGBTeydab/ZgyfwSZPaPKGtv/ivotR+XxlHKl/hL1+zMQxin1AE210rVnTYw16ruiJNgfboEZ8NawatBoR5yPw6HePsutAXngeptw2Bck1klEzshZ61+iDo98egiXIwiZjaMJrzkczMKDOjTA012Nv870s64QmlWiiha5poQ1ocleqbW+8vzF7jDJs6DrUtFozYLGTTfJRRklRqHStj02PZde9jZ02ImlVEoYtHYq5g+biUKNDLFX+hlr9sO7sWpw5lQxLshXP5D2BmUf/xaT+UxFaEKqYWPBF8/iWrI1WSGEIrCarO1tF8jTQsd+f0gp0+i2SU8zrRtdzueR7fguzzTmKMY+iD7o1jz1XXFkJ1ajzy3hx1bOYvP9PLB61Co1iG/v0RqGJooRQpXby5XPBp9TL0HqdyzvnZTKnHsPxE/rq54bPuol1kFl7+xZNbwW9zqCZqk6T/bmWPPSZ2gNJ4ZUxa9h8rzIVf8ajL6/27opEYwIai2h1h+Gh/elwXL6BapkIdHJXp1rzYFdkkdqukaM7Rc+TkrxTFHyRnJzMWqetXLnS/T5ygI+NjWWGcOPHj0dRUZE7ak4mcvR4WaDnRN/FFBnw4lzuV67nTNzYZ8TFQe8S6E5y/jaZFDXITi71pPDhxxA8ZxbMI2+Rngv3HMiOatXhiIiEPi8X+txsmFYsh55au1H2ZR2qQw+8xV1F4nL3QI966F73fX12FoLWr4Gl741exm8lQcu1Pef3SYgeNYztc8HVC/W3pdoqcp6WBfoDi6SBL9VrkUAncU6zy+QKy9esyanP1AO5c5UuxX6W1g8VRZpJuCudbZUCmH7s5Hri19dKk0xU37rtrn0BmdFQ6tsba1/2+vxVycp0Q2oJ5KtumWqv723+QEC90akWV26t5q+NyujGYzBx33hWq52ce1pzOWR8IwtuXuzL/YhlKNJE+6ggPx+JGYlssEkDYhLgF5KkQV215GpsYLy13Vac7peMoV8NYZFhGvBSNI4iek32N2Hv6bJB2p804DYHmfH3bX+jV/Ub0Oa3VkycbbNtR7XQ6hg1bRR7HUU7gy3K2oDaJ2tj3LeeuvPn/vec13dseLghu8n8O8vjTB3pzteSkMU5YbQb3eKcRxY1vpBFsIwzUxrgUJSXhDe/LsmrTiEIyogKiQRZnNNEB014yNgKbDix4Ciqw3etr4y6BR3P/t+VnWam9VVOGPmChOSq61ah46aOLFJNZGzzDKpXDluFulvqMPG366ftxa+jRYcL26XJ+qzoLBytd5RFzElcar7+ILB03ALmiE6ijI7B1IRUJkR5KHIqi/OSYrKZsOzuhV6P0zo1WOvxmSgMKWSiq+q5qmxbb/9iM0Jd+X68MOS3He1bGRLnMvLj8V94Uq1D870nJNe+7jH9qwJtU7qifwtg5Ia6uXty2O3QNGkyvDq80+MJOreCNwZjx8atwHdAA0jftc2mNvil3rcYiqHSukYaYM/1nght+30b/DT+KwRFBqPG9bWQezoH5zacQQiM6AmPOCf6L+rPblrUOVEHdV6ogw1n1mC4aQSa/9gEiNfhxMbD7nOPtrc8oSL/u9/ifuw+TXjQJAvtR56wwjA2+SNPABEx52IQaYlETKtK7n1A5979v96PvJp5SDOloNpPlVHzpHKbUQeK6APRGHFoBGKyYljmC38MplRKg7OPE9W2VUX7vz3ma3SM5/TNQ81Z0vlLWTI0UUHXSDlLhES6fA0ZPXk0lvdaDrhsrcJTw/Dkl0+y7+aMtaJ1m1bY8OkqvJj5IpuIpMmJLe23sAyMpvuasmsuLfu/wf8h8UIiEm5IQOvtrTFs1jB2zf3tnt9wvsp51IuWut746koRCPRbJP8uUhcEMuDkfw/VLex4kzjqeEHZAMWZFdJvOb1ONimUy3geX/oQFo1a6dM8TzZKLY3RKfvcogz35IPsK6BVw+6rZSE9Tm0ZiU3nN7CJaDV6nV6xTWTosTlHZzFPE7rRZAa1gFS2qStZRhsT6Jzvg5Y3AkGZhLmWXCSwdJUKItCpP/mECRPQuHFj9m9KOWjQoEGp0trJZO7ll1/GSy+9hDNnzjDzuYcffpg5uVepUoU9/uijj2L58uXYtWsXq08vUwf30vTVdjoRPH0qbC0lN1WekH+neT3miPPMoDuDgt2mYTI6LurljI1D5jpPHRffB91RuQqc1H8+Lxe67GwYzrlqjlzjSGOut9HP1QBlO1yKHuiGvXsQtGgBrB06wdrNE9Xwhc5ccoMbNxqlGfa69ZGxNbCWhILLCxmNkSDrWk3ZNks2NTmbfxYDXL14ySWdfsD6apiikHO1ulUPEWIMVhh8RQRFejno8oLSoREZJ6gHK4nG66pL3Rx8RZNJ8CqcbTm3X5odJ3MqNfQDqHbHVvNs+xfxx77fmYN4IC1q/JmKGXWenyd1XSGPSW9yuyVT1MKXmKdB6yc9P8fqMytYP9N9KXtYGmd6XDqL1o1teR9rY5S2fAJsG63YsHgNso6no0deDxYtavhbA2Q2S8eFxAssHTitZzpSrakYMmEwG+zuaLWDpdjSsig9mFJ6SZgRXdd3xYGkgwgxhyAkNQRPfO2KYPqAxMHoSaOBiVZEu3JV2y5tA3DzG2pxTqnCjQ6Vvtc1z/QR06WU5xN1WASc0mEp6tUstzkOhRxEg8MNWFSOBr30nSi9mSYdKIW8z5I+bBvsb7IfQ/cPgyXDjNWtVjMh++D4B1E1ryrafdsZbx6XDA9b7WiF4TMlc6lu7/ZCpQaxiK4dg8fefQDrGq5ladvd1nXDqh6rsKnfZnRe0And13ZH1S7V0Onl7tjy2Qbs3raTTYIcbHSQrRelDdPA/te+E1GUUYStX2xEhxe6IKhbCB76cCybELl1qrKVVk7lHGQbs937TIZNltz6N+pG18cj5sdQd2B9nF2XjHWLVmN+zXnY1m4bVvZayaKG7ba2w5MRzzDxlxaXhlXNV2JtkzV4cuFTqJpZFfk5+diZtAOzh8yGOdjM0r/vxf1YdmIJW/93qn6A0I+CkJ2Rhb9G/8UmeigSSgyZPYSJHksDC6a1n8bE+Aub/g/WHWZU7Vodwa+H4a2Vt7JsDEq5JzFDLO29FLGhceiwvD2b0KgzoB6ajmmJM6tPYcf3W4vNFtQb9TRahsNiR3K1ZLYtJjedhux5mTj87wEmzL9+/GsUhEvn3cttX0fiM3HIOpLJzpsTtU4oJmGIj174iEVMScyN+HcEy/7gSY1PRURehDv6nlw92T05NHOoZKDYNq0d2ua0Q9puaTKMF6F7mu1B5l3ZGLvuHhydfQhnq5zFP6P+Ycf0SNvNyD6QBXOWdM0zh1swfcg0dsw6dU6WJUL75o5Jd6D+UaWxXn5YPmwRNkRfkM7JkzVP4ropfbDqtiWodaoWe+yfm/9hxx5lXtjNdhSaC3DoH087M5mi4CJ27mgx+8k56DX+OsWkxbYvOU+PNCfSlknfe1ubbWw7ytsnM0aKTFO0X0YtzrWQsxzqHKwDSA0WFEScisCaV1bAoCjYlKjzUgPs+2YXQnND0XeJt+dO0jfxGP/nd6iSpQzYxWTHIGaapyiQJrno3PY3wXf9iutxsOMeWAYUImJvGPQ2nTuDg59skCciZaEvQxksT371JLuflpqO+KVx7uvpwz8+jJTEFEQ+L61TJVMs6h+uzzKN6PiglH/yr6BIf3ZMNitxoLKaQw0PITcq1zuC7nJxJ8NEMsojQe3LTVw9mU0R6eLaPpLQpXGCeiJhh8vwzNdvobpVJY0Tftn9g+IxyvhSt8aUoUls2ZOkXkw99jtOkxEzD0/HsAYjWUnI9MP/YM6xWYr3UWDgn0NT0CyuOfc9tdcxpcCTgaB2kH92pef3c/O5jczUlHe315qA8Ae1GOQnQ7TKLGR+3fMT3qv2FiqMQCcxTmJZFuilhVLiv/vuO9a27dZbb2Xmc3fddRfGjBnDRD89R+n0I0aMQK1atfDtt9+iatWyEWl6i3SxcwQHHvGXCfnrD0Q+PQ6O+ISAXk8p7l4YuV1hK96UgnBUrgwn1fifAUuj16sEuqHgCGDLA4zaPbYrJDRbyLm4lyWRD4yF8bBkLJN25DScUT7qpVy5OjqqS/e1msHB0FFvdF8I2/IKA/0AUi9x4sxD6awmm6fvNCkasuq2jWgc24T1YibW3b4V9SspJyq7T5G6LKgJNigHatRmSS3Q+R8NLXdXEtzDZ0mTBEfvT2bphL5+qPLVAp0bHNy78E737LYadf9uNdRGitIDSaCnarTQKQn891X3/FZ+ZgSqRlRz99tWp8tRhIQ43FEyMKoXVR9BG02I/i4Sj1943B3NDfkyHOFnwzHum3EsWryNpSIBN8DjnD/opLR9Gar5z9Y7PRO0vVZKEyQ89RdKUZlAoXWgsfDxGseZUGY4wAaQk+6YhN4re6P1NukzdzffjXkD5zEBQgPkxX0Ws/TVoYbhuH5nb+zZsJMJPhpgUuR9zB9SV4k7Nt6L3b9uR+rOC6jZpw72hO/GuxfeZIPP3S12szpgc4jZPWC7oU1//LZpPNZ2l44PqtfuldoLE9pPcAu0CWM9kztvfvI+czF/c55U6nbh4zS81P0tBEUEwfC9lIFA4p8E0bzXlyEiwfNbda7/eeSl5WFxv8UIHR2OZanLKPcYK3qtQGi1cNzz1iMIjQvF4L9H4r7vPKnXMpX7V0X9wdKERfN7Wrknn3a33M1E6caOG9mge1nvZVjTdhOeznocm49tZNHwNwe8h0a3NMWppccxaEc/ZMRloFJSLHqMlFqoVetWA6uvX41tmzwTTDaTDRs7b0SfRwdg11278e3Wb1nEn9Jmwz+Mxh2t78X+9H149W9PmnpqYioiu0Vj89rN7N/xLRMwZO1wTN07GRfWSeePnPJL9ecDag/BzoQdOLRd+p1q+mNLdK7aVdkfWQeWBlzwlRnrZ65hx0Hram3w3de/IPtENuKbS+OUWjfUQdc3e7L+3/9tnsk8BLa13cYyOig1mYzfno56Dr0+lgTX0dOH0WNRJ7b8djd1hGGIAfXvbogbl97g3vdsu8dUweB/h+LcprO4bf8InIo4xQQkRS67ruvK6vTl9GMSNV8+9SV2Dz6Enz/6DouxEPubSmI2uCgYP1nG48X8Z5EdnY3Hpo5DeNMI7GgjDcSjq1fCh0M+Z/fzz+ehxYSGqJRZiU2SLOq3CD2r9EbfHwei5nN10XNpZ7beS/ssxcSHprJruDmbyjpMuHXuCBw6pzSUI+h8+a3xn+hQpRP+HTwZByofwOTbJ6NxUlP803QGXv78eSxptBjNLW2YJwKVg1ANPvk8UJp3/KtJuM/6APb8thOnlp1gJSStHmmHnVO2YWv8FvYeSkmn1HmK7LISFAOwo/kOHEk6jMMPHGTnH4l9XnhG1YxG8/taY9vXm5BiOY+lNyxl6dmj54yGtciKBf0XsEmq6snVWZR48Bzpt2tv071sQmhvs71M5BJb225F+/wOMB8rwq/3/cpS5uVrDZUwULkM7TMStfogA5ukIWjShbJ1iCP1jqD9bd0wPnw86qytg8FbBqMgu4DV9MuvIeQJkWN1jjFPC5pEoIkyr9IU+n2rloHYMx7RSecqlcfwHJ9/FHpXVsycQXOYkSOduzQ5RxOmgSCLcx4qVcHzFNldhyYbG6Hjmnbu7UGTs1S6Q2VFtK97L+vNJlGoPGP8veORVSmLRX5JOB/OPOiOYFObQrmFpS+Bro4W029tWqGnFNYXJCxlgc6n0dPkgFzGRl0plp6SJvq0Wpm+uub/cChTOStDPg0kerWy8Khjh0ydaEmgEw8uvodNBv6573eWIajmz/0T8PzKpxSPZXGTFoHw+rqXFZF5MoJVb8ucYtoD0j4KNYa5JyBoOwXaWvHrbZ/jvf4VSKBHR0fjjTfeYM7r1atX93JbnzhxYsDLotT2b77xtEDgIVH+559/4lKgN0sngiOo5DXtod+6XJa5unI11tZtYNohzWo5YjyzxbxZnBu779kbvmUb9c6WRSQT6GddhhI5gN2UBIM1Bca8PbDFdMbVgt58HjqnFU5qaxJcuewWXFgIwxGPoUXQsiUwDxvp/z1+Iuj2atVhPCbVPgoqNnyvVkoF5wU6X2NFUdmGlTwRzG0XtigEulY9uIy6F3JMcCWclGfaNNBqA8T3XE3JT2ECnTcKk6PN5DZMs/NKge45ln2Jc/a5xfyIURup2BBp0OMrvU5GHsj4+6yClHwEVwqB+aSFuTDTgJNqG6n2kSKylLobERmJLlW6sQF9zqIs1Eqpib62vmzwRwNBecA5K2E2lj62AN2nkaCRRI0Mi5qqTveEVklIOXoO+jwpfTA3IheRed7mMDTgpNR2rUFhWs00mLJMLEXdWGhkETiK8pL4oYgPRdFIWJNApeh7iz0tWCTwm3HfoHtRD9x92314c8WbrB7z/kn3IzYmDpOGTmLu4+tv3YDdTXczMSW7pdOgkVJEZcEU3DAEdYY1wJMzPGnvx+odY6Zhj7Z9AtF1YtD9XU/f7uQjyche5DpmdMCzPV9kgxfqt02tZ+gY5yEx1aBeY5iPmTUjsTQI6lWjNZ7v8BKyijLxcOtxTJwTlIJ5w9Tu7HMONDmgEOfE+z0+wT8Hp6BjlU5ol9Qes/+a6RbCmX0zmTiXWX7LOjZopEkE8mag/sBjm93ntT7uyRsdMH/gfDzX/v/wUPXHUbNqbUQviGFieFXPVWg+VhL09QY3RMbpDHdNpPq7yTSJbYpbG9+B5vGSuW1QSLDCgKuaawJJbrPGw0e/6L7BZMCQZsNxvOgYGxxT60DKuiGhX71zDRxNPqL5XhIBPLHN47E6QzJ4omuBKSLILc553un2ActA+SRSykbc1UqaeaLoPU02yDRq0ASfWL5grQVlB+janeshc7tygE3Ph1eOQP0hDVGQXsBq10m4fHvDT3jMoN1ZoFLVWKSPzMD+/ZI4/2Pg36xOdkDzwbj7uzvYY4feOSJlBrmy2vmWY/R5eZF57Ha6ppRpFBkUCb1Bj/qUzbnM81ny9Ts4WpoUDQ8J97o+EmRu2KJzK8RHJuD23feg/u/V2T6l61Z8i0ScGHACeal5bAKKRPmcwR7RQkRFRqN2h3qo3b8eu46Zwk1sHzjG6PDqTGmShiYq/hjzB2vPRR4ftJ9nbZkFkFaLAnKRizUJazD8sVtwe/s7kXU0k52zpjATWj7QBk1+qot8SOf+jod34njOcffELm0HulHZQbt97TC391z3dYEyEkjQUvbHqAF3YOyc0ez70sTGoPWDkJRYBX9V+5O5/9P1qmfo9fjtsUm4sDMF64PXsmtS0vkkNimxvst6DLWNQro9HamdUvHZJ9/i+r+6Mg8NKkeha/DYf8YivnYist/KxcQ9ExFkDmJCmrIoXlv3BrZlbmHXMUpxp4mRJjc0x6JD37HrfWxGLItY0+QLn4lRuWNVnD92Din682ySjz6PJu9o0o0mPcjXgDIxKJuJTA2f/exZ9r55A+axiZHeyz1p1XMHzkWP1T2Y2M6olMFMJLf8bwMiOYtfKukgcU4kpCWwtHj3vs6NwlNfPoVNHTYh8q5oTLswFaYcE4oiixATEsOMUvnrBcF3jSDU9dbURlNuTekP6lVeF1KmB7UNkwU176j/Re/v8NuenzHt4N84lXvSK2o9+YC3rooLiWOeM9Sdwx9UX8+z9fxm7E3TzgRdeHye3/I4f+MBGXVWoFZfcz5TQQuqv6fJYVmg253UfaLs+7iXC4HepEkTdqvI6FwRdGdwCQW60wkjJ+y0oJrzwgcegemxB919zj3v1zgg/QzkdbnKg9PhcsmPvk/ZV9ce3JQJdFP21qtKoMtp+/awhoC++LQtykaIuvcuGI4dQf7/vQbLTZKJDRHy648IXjif1X7jXKpisiRo4XxJoDs09o8TCP77L4TMmO4lyg1nktl9R/WagBDoVwXKWm2LwpWfr7sy6Y2Kf6vrsqnvc+ACne8F4I3cW5nnPJcORqlhNDmg/jGLDo5hs/L0A82nv/kzVeFxR+n8RLOjXD1n1bP0BLVHInGaXC8ZcWHx7jR4Mj5i36GK9B0oddD2oxm/z5JanCUiFg+GP8giRZQOS6ncvVb0YoOmLaO2IistA899/hxMZumaUB/e0eqhvwzBIXinmqohM7QfH/oR79zxIQ4eO4Jz45NZGjylbN8++XbUC6mP+/99DKdXnMRXOz7D1PgpLM1x6KyhzJCN6hiHhA7DK0+9icEL+yNl+3kMmjsIcV0S8F2d79ximrYFvV4WcgcbH2TimhywKYJtrWVDbII02UER3A3vb8a7132InKkvssdiQ2Oxv77KE0AHNK7TxN3eiiZLQlTHFnG0/lGY2nvXBaujPD2rX482SR6fF62UQ3Lh1SrJIGhgSoKIBLqaFvEt8X73j/HyGm/THqJTlc7sJnN9jRuw/PRSdl+d0tksvjm7FUeIKlOF1kt2AS7unKMSF/V3k6Ht/Gjrx7nPUW5zqkGVzw81shEiu++a3Ao3hePlzq+z+1+6ekmzzwml/an8XH45sgkiEc+1WI0O8v3dqHsDbYdPNFpNqaHe2zx8FwoZmiSRMek9x9ioRrexnvGLTyrr2UnwkjDmM2b611Ya18nHGd/vXH2sqgkxSBM46ownNfw+oUwc2WuCJnrkzJyI8AjFhAs/QfDeRimaRgZqTeObY8Fxya1bvg6y1yZ5JgG0jrNXu7yF2tF1vH4H3OtVoyqMIUbEN0tQlB5ERkUhMyfDfWykFqZ6nYc0IRfcIQQFGQWK81+G0q/lNnfnqp7Dpoe3YEi9YTi+QXJqp+tVepV06PQ6JLWpjKhT0j5IqZyCGSNnMO8DypiSxVXtuDowhQXBarOybXay9knk/J6PR7rfgX8OT2GvkU0yadIp7v1E/LtEirZStgddw4ZUGoF5pv9wttpZGJsEsaDTrKGz0K2gO/54Y6r7uKP2XW8uf8P9XWSTNyohoXbPu1rucj82ddRUNpG6ucNmtl6UldG+sAOmdJ6MfF0+ywaijAVKZ5+w608cn3EEzjpAbppkXugP2gZUQkWeALrderzgfIEti8o/DvY/CNxHveBDJcNQnZN1gai3oB42n1mPpne1gCXXgqazm8BcpYjtL+L+RXd7TYjy0OfR5w76ty8O33eK1YLTxLuM/F56XWJoIv6v46ssg4cE+uPLHma/z2Obe09iytCkXovoVsUKdGpRyUNjIN7lX8Zqt7L1VcOPk/IsgXcvquTq3KIFBSj8kRCWqPjcsnD+vxRoO4+UEDJ283erCLhT3EsYQddleiJKTlcveLacGM9F2BkeyerF3f8O5cxOeAHYVnL7NA+72efnFd1+J/tr6SrV6fhKw7YZpXIDY/YWXE0YcyWBYIuUIhXFYTiwH8EL5sJ46CBCJinraiNfeh5BK5Yh9IdvgIPK9J6gpYuYuNeR6Z4apxNRjz/s9bCjiifl3l7dt2kR1bgLKg684Yh6llt9YednptUmZEezvCfy5Ai8emBWXBs1rRT3FO4HR/7xURumyYNKMkGTW58R/H1/HMjQNomTIaFGA34aiJBbryy8e6zqgQHzBjChSunVPTZchw87/w+NDjRClbNV8MDPD7D2Ux03dsRznzzH3KojZimaGDKzIr5WVTbOav9PO2z6YC0T51T3S/Wmcu0w1WOSGZUaipi8+cabOFf5HItYr+26FrokHRCqY6nElHr88OL7kOPIYRFVSlmlQeykOyfB8FkwQmJC0GBYIzi6U+cPJ2tH9sVTX+D7R77HmepnENY/gplDGXRGNsj8+cGfEfRgqKIvOA0cO1RTXgtocEZiXBahNEiSCQ0JQWyYR5Cp2+LJ8IKa3PTV5RMyWgY8fFRSXgfF80bl8/Kx+9F1HhGpfL1/ETWorjRhymee+IJfF16YlgS1oOT/LQ9Wu1XtEZBAp0ix1roRwZx4Jyq7otu8eJWJMHn2sZYpFT8RQM/bOCFbKYQ7H3R61jpMhrIefA2itWjqqgv1Z6YXCE3jPOZgb3aVeoDLZo/qbUiQsKP94CvDqHdNKb37/hYPKc4H9bGq5euhnvjQgs9qkAU5QdtSNt/Smoggl2weEvS8KKfJUC3417jX1XWOUgRUi8Rw7WzB2GDP/qeWYFoTQESVCO1yQNqe6mMySB/k9XvE/+7xkyTy5JLcxYNKnOi3KylcWSpaYCxk2Qxa1yzF9cm1mW9vLGVN8NuLrp2ZLbMU+0K9npRpwz4vvADb225n19j4UGmial+zfVh2wzL3RAtds/u+NwChYdJ4nLI8aNKheUJL3PjDYDx0+gm0mN6WXdfTPsjEvYcexYleJzD/xvnM3I4ts8k+jL9nPPNloHKBzMRMOIscTJwTVLbQak4rFo2/5a9b8No7r+GODXei58qezEtj8yfrMaHlT5jc7Xe0WNKC+THEBcchLD8MedtyYMyTYqjxqfGolFGJuc1Tq0PSuTUiPbX5v+/5lRnP8pNcVKtNrfXouJS3Gd2n7AW6vbr4Rb9Ra9rP1H6ThD9/XVFzY22u7IsyXTIPurNQeChLL60wzW9gQV2SF5kTySbrw/PCkZii1GYN/PxmnC/G/8YeQG97GWZKSm08ucnGChVBJ2bPns36n586dQozZsxgae3UGu3BB7VTmsqvQA+sjlxGl+8ZcOm41PSMzbsQ36Cm27GbF+jgBTqf4r5uHTIOnYC9su/aalvrtqzNlyNBOlhZDboGdlfKiynHYzB3dQn0lgG9XlfkieL5cl03UlpdpDSQLBoxCkErlkKfkQHTpg1wRmr0O7R6D2xlUW7assntsK9F3itvoPART6RFUP7hRa460synkJM435++1/3vY6rZbz7lTIZ+VGmQwQ/omcN6MRHtfel7mMDihTw/I0yz3k3imnlNIIS7BJM6gk7rEQjypEOP6r3wfx1fYan43Sa3l9KbdVLkL8oRhbG/j3WbJmnRY0F3ZB6+gNuP3u5+jFyDeUMfa7AV171xA0KqhGLm61MRfdpPD10d0OPj3vi2ylf498g0ln6ZG5nLBmoUqa5/pD5u/fdW1O3dADd8cyMy9uZg8/bNmHD3BJYmT7WwQ3qPRCjCsH/Zfp9Ou96RU4+gorRzGbmHO0U0tQbmM4fNRdvaLTDuP8msSAsSofxgmPooU9RARhYPatoktlMIumBOqHze6xs8vWKcpnO/lqDmo7vseY12OHQMDq9/Mxto37PAM7AmimsFSMJh99jDPoWFYl04kRXLCdOyomVCa+wYs18hbHn0XHcVoke163zWUaqFA7UD8jXxRgZFMsW5Rocbw2HlJlb444voWrWH+zqjEOhBxfefXnjzclZWMmzmwIBSa7XYd88xhYge3uBmtEvq4DZx9Ff2wm8HnokDpjA/i2qR1VmnBl/HotxVQUv4UQYDpQJrQaJSpkp4Va9z2Bfvd/8E/x6e5o5YU1/uaG4789uBhz+n1eeJr4nZymHa60JRc/f9kFjNEgpf77+10Wh8cN2nrPREfX1TTxRY7FbN7UWpwiS69ri6i8jXQ9p2fPRXngDWnJzgrk+U6j996H+Kbc9vU/XvL21zfl1ItG1NUQalbmk0Grc3vpN1QHl0iTRR9EGPT9Gv9o1M5NIEhSwcqSzm9a7vMEFrCDaykorNY3ehang1Vtax+9Y9bPkUmY/KiWKCXqb7LT3xSPMncWFhCoqsRShoX4ijzxxE7tZsbPpoHXuNHno0WFgfDVzjczU0Cf3K9FeRs0X63aEIPKXtUwtO6nhBpQmUPbao7yLsuX4vK32qe6wuTFFGbEpdh7sm3oUlfZawTIisL9Lx3PLnsPA2T8ZKmDUMj337GCu5Iv5dOoUZxI6wjmDO9lQmUPNkTRSFFCGqXRSbsNpwx3Y2QdPhl5bMuJHKOWRW37aJZX64l58fhriPY9C+dnts6bCFtbujMgb6/T147AAzl5OFd1x6HOs4Ueuz6pjwfz+hdr+6sNSyMg8A+u1ufKAxBs4biBO1T7DPpfKC80nnWYbDyp4r0bBJI+YAT4xufBf+OvAHu08T/uH54cium828AqgTBvkx0O+87F8hB13I2JOyGajkwf377ZQ6pFAL06zKWbjtj9vYuhZ+a8VDXR8NaLKzXAn0v/76ixm4kds6ua4TzZs3x/vvvw+LxVIhouh6S+lq0HUF3g6EzpAQOKM9s6e2hg2ZoZumKOcj6MHBUhS2GFdVXvxRX24t7NZaLOnGUHgCOksanEEaxnQVEEOeVNtiiyw+nZHgjdp4sc6jP5sMHJZOOnvDRrAYDAj5ZwqCli6GtUtXv8vkcSR5flTsNWpqv6ZqNUDl0SAo3/AiTR115Ouf3t/4tmJgq46Yaw166YePBvP8gIhEtdplVc3K5OV4d8ObeLvb++7HUgo8gwXqK67uLc4PaikNrUDh4l5MBN0JNusfb49HbOtY1C6sBRx0IHpgNEb9MwoNDjVgqdln1p9E+OZghGf4FucyVE/pC6odJCO0A7UOY3PKJiSPPYU7/7yTORWv67IOSSlJ7POoL+5tBXfgzZvfRUy9Sng28/+YQOcHThRFofTxouk2DOwktUZqlSiZq1HNsWzCRRG5cNWgX2uf8aKTj+TS4FTObNAS6PzAnOqFa0TXUAxO1dDyIrnoKgkzPl2XIp1yixtepDSLa6FYv2C95zOacNFNrcg6H5WkdecH4+rnZejYpQEtmQqp4QfQvkjiItH+UNdqXwr4CGpx68lHAylF25dAp5RmfxMVfMRaK+OAj8TSdqZJMF9Qu6I/9v0mfS43iUH12MVB60zHrZwiXxrkaCVPzahamgJL7RLta5+SaCVxrp5okCcbZUgo8JOg/D4gbwCa1NSCnxyqFlG9WIEup+mSYBtefyR+d7XCpH0cyQ3etcQoW2+NySh5XX2luKsnyviouft+SCzCVeer5/3e+4V8EVh7Kq6Dh7wO6lIQPoLOT1DGhyUCGfvchmBuga7yQ5CP2eIi6CR+1NvdwF1D1a7iody6UEmX1kQEZbpQtgM/eUMTRnIEmr/G1Yqq4zVZyEeqba4sD/IOUPdZpyhzbKV4xN7m2datJ7TB7FHTkLE/HY1vb4YDkz0T+Ox37P6qODb5MAZWGYyTK46j6ukqCnFOEfgBCwa4He7lLh3UQq9SVCzazGwtmYnOtWM3tqMe/fdTPZypegbVzkrXsq4Lu7IyKziciFtfyS3OifObpEhzS7RkIpZa0lEXDvIHMLUORc7JbJyadQyGSkZW3lX7RG3MHzAfVc9WZd0OQhoHw3m9E+03t2f+AXKryfp76zMvgBuW3uDuVLBsyQK069SWCeLOGzorOhjkIw97J0jlq4/gEcV2rc91UiCRTjcyVUyqX5Vl6aGyDjfVG8IEeqcNndzbi8YQ5BUglx8QJNJpoiO2YzzrftF/cn/F/tjeeTt6z++NJgeasK4Gy29f4e6OEDTfjIzkVJw+dxx1v/T9O1HuBDr1PX/33XfRq1cv/O9/Uqrb0KFDERMTg9dff738C3SnE3pzKVPcC7z77cmt07J/mYDQ8T8j/+0PmKGb+z3ZXFRGyySuJJ/v4/26QsAe3gjG/AMwZW+GJcG7pqvC4XTAUCj1crWHac9A+jNy8xVB1ycnA9WkmXNHbJzkEfDPFOiTT0GXL5kF8egslmJ7mzMhroHO6p36Iyjf8ALI7DD7FO9qMUcRbYqGy4ZK6RrpXVTTzq4M3HlMaV6BpJz/sPMbhUBX17xrIacoU60azfJT+haZk2UVZOBoo0OIqBaJYTOGsdlj+iGlmuhWO1shtDAUbbdLJTgtVksCcDPWsxS9Zmjm7pmdvjDVnV6+pvsa9qMtp6JT6vnJWidZHXn3Nd0RFBKE4XNuw+ztM/DHxt/Qb1E/RERE4o+BE3GymnSeTz88VVpxA5hgp2gBzajTTL9MQZt8Js6JBpUa4tHWT7A6Uto3fWv3d/dxrxdb32+KNIlzdQq3Vqs4fhDNiwrKJnALdNcAlU/p5cWX/D6qCzyTe4bVT/+063vF55Ao4QW5VtrgtCGz8OKqZ9wuuo1imyjSnlmKOzeIJaMiqvtedmoJbmnkyV5wryM3QUFiRZ3aqxZFfDs8tZgnyjItsCxS3EvDL/0mMBH2hitdm2fuiMX4cOO7eK/7xz5Fh1pwvNr5TTa5JtOxSmcMqTecpflrpVJTFPq/ozPRvZrULWJ0kzFYcmoR+tbybuNIrR7vbHI3m2jg6+C1Mh98EWg2TWngJx6rR1THwcwD7n8/1/4lHMo8pEhvVsMLPPXkz+83/sXOhXVn13g9/2bX91jrp9FNlF493inuVX2a7mlBHStkqIMHX+uvFSkntPZxiJ8I+jPtnveZLcNn8LRIaOXTI0TrfJEnhXnBTdzZdKzXBLGZOyao1p4iljTpQ5FIyYZQ4r4WDyk8F4jrql+PJ9o+7TVpQdv3s15fKbazVoq/gxPW6v7W/HnWPqmjO1NFhtzLZbNI/nzgJxD4/a/eFmr8td/iS15kwhLDMWrxnchLzmG/UQ371sOch+diXbe1WHTdIoAS0roDG/Ubcd3Z65hAJ5o91hJfNf8SNaZUQ8OVyhaFMh2mt/dpXiqLcyIyMxLT+0uT9ZXgOT6p9CsyPhIFF6QgIxnjkfAn9DY98JANk4N/Z60CibqQhOqgeVJKe5sdbTB39gzW7rLPtj5eLQPl18mQeOeN+S6GxNREOJ+04Tbcxv59/JdDeFX3KpxFnnEUiXP1BKh7nZT2Ue5WqHSToZaD/SdK24MI/SsYq7EcQZFBGPylsnVfuRboZ8+eRb163qY8NWrUQFaWf7v78oDOlg2d01K6FHeNCDpFwgnLkOHs5vWenDIU6KnarYzC33gFti9bMIEeuugr2Lo1hqO2JxWlYju4GwNusaYzW7T3FbfdWf94V1Sc2qPJHgFkAmc44p2WLL9WjTPUMwhi/em18CHuBZeG1IJU/Lr7B9zR9G7FTHggUOrijzu/Y6YqvmrQ/fXbpB/ztKI0d+RN7ajOL49P/aRlaqUfa/HZlo/xYKtH8dPO77DpnJTu5Q8aqFM9W/qrF9BiU1MkRcej6rmqyEM2FkJyIW4NT7uwLhu6BLQelHJHQr5xTBPYOznxXvTbSI9PZ4Y8N7e+Ff/snOJu10Wc7XEOc0YsYi2DKEK4L28fqxH8b/giDAodhi5/edK0+Uj44Ybedfw7LkjdMdR1rwQ5QcsCvX5MA7/ROhLnaqduPr1aTpHlB/58ZEsRIXcNFPkIuoNLjZKNompE1cSMYXOx88J2L4HOr68vgd46sS0WjFyOpO+lz+5RvadCxFBUL5gb9NP9+1s+zG5a8BMU5Nru9byG0NvlSm/ViuxqiZHSokxxv/gIui/Ro2ZI/eHspkWHyp1YSq6/SZxEldB7ou0z2Ju2GzOOTHevxy/9lf4o6mWRwze/D6bc5N3CSD7ePrv+ay+TRtkwLRAuJoJeHEVctJaimLxAp3Np+pDZft/PCzy+gwZBUdKZw+Yh8bsoL0FGkf1/hypd1rWM7KqEV1OYp5VEoJOxHfW+Li7FXQu5DEUdQf/4us/9Gnnx9bs9qvVkEzlaaJ0vshjmszueaPMMBtUdjOmHXBOjGr97dE5/0ftbdv+b7V96Pr96L9zaeLRiUqpNYls2iaiVrj57+AJ2jeGzKtTp9urjkZzNfUXX+9UeoGjteWOdQZg4YLKiREiGF/L8das4zwx/nVh8TegYggyIritNmra5pw2qDaiLXyf/yozv+O+4ruM6GAoNeHzIM+g0tit66vvAMdSBXwd9B+t2i6JriBzVtbdy4PMhn7PoN6VlU2s7cs2nriDkbN9idwvWoo+i2TLkufLHXX+wlnE/DByPj5e/B/1uHW6e7u19ReI8um4Mso/51nFn159BCELc7e4os43afTY62IiVrclQ+z+KvMcjATur7UCDww1YJwHqYvJm+/dwfNkRxNwVh5VvLUGrXa2wodMGxKfFKyLoBKW5y2767u+Ub4XRJWcvJFxgKfo1T2uP9wwhBtiLfO9HuW0pdVRRU6VTNVTr5ttfqlwK9FatWmHmzJl4/PHHFRfP8ePHo2XLwGqFy0X9uTGa9t7FR9BD/C/D2rEzQidJred0Wi7hJcDaqQtC/5JqL3jIFA30W9cdCEpZi7iOrZB6oXw6FQaK3hU9d4RUJwvTgN6j41uh8X3L1T3M0131aUFBirp+0+6d3su0aAt0W0eP4ZMzTDsN0dbYk2IquPRQTSzVKVFN9oKbl5fovSTs1O1H1CnuWqKb50L+ebdA1xLz8uCEH6RQ5DdQ07YPN73Lonta0XPZ0bl2VB3mqkq1oPHH4vHI94/A5rCwH7SqBVUVP9wmm2/H483tN7P0ti7JXfFo9jg0GNkYy59ahMNNDmNdt3Xo9HhX3N55LNacWYX0WdL5ROnjCREJCnFOkHkbiXN15JUG1VqRCC3kmtOb6klp61rwab58rZzWgJWEj69Bdbdq12H20RleabzVI6TaWqJeTAN3JFuu/+UFep0oj+CVsypktGpH+cE/f+zR51PNpBxB5UXwyAajWJ2yjBRJ1U7J14IX4FR36fW8hklc16rdAqo3v1jKOsVdjvxfCuLDEvxOdPSs0dst0C8VfPZCcZFBnsH1huK3Pb+4TeOKgyKkq5KXs3Tv4iiyeyYNhtYfwXozq9Op/cG/VmvCiqdVopTxUxz8+aOMoCszH6g+nTJqbqztiZ41jm2quEbw/aF9RdC1CHWdo+pShOKWIYtyWjc6d32VP/DXQRl54o6fqBrWYKTmtiXRrgU/iVifu17Jxzw/4UHw11f5u/GTEqdyT3lNilIUfMO5dZop7gnctbh9UgfFhE+CykuC37a8PwP/+1PcpAofzVcTyISO7L5P303uFiBDLTcX91uMb0b/zBzz5dcmfVUNj819kKWLUw367ha7MWjVIDzcfhy299oOxxYHTtU6xW7EoUaH3Mtc230tDNcbMb7/nzj0z35s/Gwdpo2c5n7to6vvRwEKgBZA85Gt0O67Njhx4DhrTXfrptvQbGgLdPy/bjiz9jS+f+FLya8lMhfTbp6GlqbW+LPf3zi5+Di++e9zNhkvd2E50uAIK0exZJtx05ybcKDxAexpIZWY/NT3N/y0+Eds7LzRvZ53Z4ymyABC9oXAMtSCTR03sVaqlMpObfY2dN7AMu+odSrVlDdLaYZvbvgRIbGhiKodjazDGdCbDHhzystYlrCMZQBSC0CahKAbTRZQiV500xiMnf8QHFYH3p77Gn4+8wOqOKsg2ZTMsglXNF+H+2bdhSP1j+B0jdO4ccmNWNF9BZvwGNhqMIY9cwv0rn1zOSiTX6hXX32VmcGtWLGC1Zy/9dZbOHHiBIqKivDzzz+jvKMvktIYHcH+TUECrkF3RdDVpG/ayYzHzCNvAZ58FGWBedRtyNHrWe069UEPnj8XwfOlHwnjvINMoLOOQzpKrc9S1MZXNAxFrvT2kBJEQou0U9x1har9lpLiLk+gNPdAl8lj7dyVlTXY6zdUtNLLf/o5WLtdx7a/rXNgEUlB2SCbiMhtp0rC5vOeHxBfJjX+IugECWdKPWSv1YygW7wiFCzF3U8EnVK4v9vxFbtPDqfBJ4IQlhDm7nH7c6/f0SiqCbL2ZeLElmNoVas11u9Yg55d+uDf76ewWW1nghOpCWlI3JfAUt1O/3QOUw/+hSBLELtRjRj1pY2IjkSPMb3YD9rc7VL7oMieUeg7UBqk3rP3YfYd25/tjGGuATofJSG0BDdvCMUPKikdmwZJM4bOxfBZyhQ5NTOHzcfJnOMY6GPwKIvG6UP+Y4NQfvDlK4JOA0sypaKBtjw5Q49/eN3/2AQHRfkolZKPYH/X52eWqXFzw1sxquFtrE5bFubk4i7TMLYRW3YVjdpWrbpU9WDR6kozXXTzSjYJMrLBLYpUa4o+0foQc4YvRp411x0pmjVsPht0aw3UfQmgyhFV/Ar4aUNm43TOKfegviyj5VrElrVAD6RNZylpHtcC3/f5hflC0HGh5rbGd7BjhCLwlwp+Eqgkkyevd3kHrRPaok8tT32mP37u9xvmH5/LhH1x8PXOtzUezSbZZOftQOCPMV+mcstvWcfKjfgWfYHCT2CpncgXjFzGvD+o5IDPAqDzgDJiaBKET6fl/SMCjaDz1xaia1WpW48v7mx6N7t+9q7ZV1O8rz6z0mdkmE8np8ylPEsOq9VXR62/vP47NplSnECvF+0R6H1r9cdXvb/3Wn86JmcPX8hS6LUmC3kBvvSWNViVvAIjGoxyt7JTt+miSVESn7WiarFlkw8GCcAzeWdwc0PP9VG+Zvx90wzF9Vldwta5qrfnEI+NO+YoI+OhRfcitfCCX6d9Lfxdv9Rp/sHBIWyCe94gTw/xzQO3YPzYrjh2wLudGXmQ3NVsLP5vldT3HUl6Nhne/tnO2NFnJw6u9XQs4tvCRoVEoe5XjfD87OfYvz9++wu0dZ2btW6og/H3jWf3RzS4GR9X/5y1vYyNiENswzj8p/POIqLfuYOWA5g2apr7sQ96fMJ+r9WGjjJs3GMA64RCkNndV09KYx2etDbpqDPAc7yFJ0m/n2nnM5B9RtqfK3tJxz6xLn4dq6//Y9gU1k2Abv835DU0OdIMN9TqhyOZh1g5WZPKzXDqwClKd8OmTpvQ6u62WHVgFVvGiOtuveS/cZdEoDds2BALFy7Ef//9h6NHj8Jut+OGG27AkCFDEB7uvxVGeUBvPldqgQ6tFHdXDboaSjE3l3WaudEI862jPR+92nNQUn2L026ELswGVAGCli+VentXUAyF0qyfPdSPQLdYEDO4H+wNGyP36x8U9eIkyqPuuROmDWuhy1SlUl1wpUYFB8FRyf/gL+K9t3x/vKukgW/PVnjfw3AmlszbQFAyKGNn1H/DYNQb8NegaV7pq7LREtXePrviCXzW62tcX/MGv8ukel01lEo+dv5oZggzb+RSTdGtTkGk3p6sV2mWZ2ZbhgYqI2cPwYGM/YrUenUEXW/Xo9qZamwGnVqf/Dt/Kq5bdR1zOpVrvFMSUxBiC8GZN0/gDDyz88uxiP1dOHE2wiF9p29v+Zb19u64qSPrBxthjWICXxb5s4dKqaYPtxqHx9o/iWWnFgPbPYMiHkpnpEGUL2GpJdCt3ACQN+WRazC7VevB9plWb20ZcjTv1Kj4QTilfavRMmOSxeeNdQYyQSMLdIpkU9T6kdbeXir0g80LMPUxpXbZpmVr4c/4S+2kTKKABB6PWuh1rKL8dxdXlLtE0cRiIug0wCaX48tFOJdlEMuZY5UW9b4pS2g7jlQJBB66Pml5AFwqAjHr44/F25tI7VwDFRtatd1a8KU7tI2oN3pp4a8hPOTnQLdA4UU1n0LPG7DJHQfU5x3h6xworv+6Vi212kRNXVOtdQzz2/BUzklFTbws0NVt/9TXQPVkBh9B93cs8AaA/LrTemltK6JzlcCCFJT942sZPGQQxiNPGGqh9ZtP7cj8mRz6SnHvXu061iklNVkaOwbSiSIQga7+bdL6rZK9TbS6M9gcVoxqeKtHoHOEBflO4adl8ZMDvrI36FgN5Hyn84XPaCCG1h/JfuPpuPHX4704on10pfDntWEJtiAkJFTxWvnYTiSzQ+5xi6s0NjbKM4nky8Cx3PdBJ4KDg9G6dWt269ChA7p161YhxLlc20w4ggOfAZPR5StTbghnSPE7Mvfzb9jf7N8moSxRpFY7AGeG60CuDxiOl/6EKF8p7r4FunHndpi2b0PI33+xSDef4k4GbcFzZ0Ofnu5dWuCKrlME3Rl78YM/WoatSVPYGjaCM/7qcNAvz2SaM1iaJQnwba42K/yPqezOe9ucETiTl4z7F91d7DK1ok5kzkSzzvsz9mF32i7F7LsWFF3+59Df7PVaUP3u6uQViscojdJSJEWamu1phm5rujFTtfvG38farZz94TQe/vFhNN3f1C3OCWpPEi2f7670uNjGyiiF0+TE4j6LkZaQxvrBUprZgSYHsI9rD6d4vatHKj9YVddGq1G3IUnQEOh8hIZ6p2tFcIurM+Z/VMsCPsrEp5f76wFbHM93eImJsYda+s+YojTLJq50WXr9a13edj/3cqfX2YD3o+s+w+WAUkqpZdFQjbprEh2tEtqw1H6t3uVkdiZT1gKUzKno2Gse39Jnj+lA+LjnZ2yA+3N/ye38aobqgimdlia8ygPf9fmFCeIvb/TULpcUMiijiaL7mpdNC1+K/NPxRDXLJDIpAkntvviSmEDpU6sfO3f61PSYS2lBpnXyxECT2GaKaw9FhAmKQJeUp9o9z64VFKl8qNVjrMyBTANbu85Z+fpC19kW8d4GuDJ07tNE64A6N/n9PBJb9F3pGKMa/NIy5abp7vXW4se+49l6U1ZKWfN2tw/YZ9NnFMfn10vj9lc7S0EafxPIgfpp8NB3VE8capWAyK/REtGF9iJF2j7fTtVfJg39bpu4z470IYK1vDvIrFa93nxHBPUEGPkF0LrQuaKGsi+oLZ4/In1MHhTnIRAcgGkpX/4QFxJ/RQV6mUwhp6WlsfrzHTt2ICoqCg6HA3l5eUykf/7554jU6iVdjtCb5RT3wIzHik9xL76mquiOMSiiVPdi6tVLitfkwEE7QMdbfd/mZhUFY54kIuzhfgQCFwEynDgOuIROwJBJXFRgtWNOkwm2tu1h2rje+0m9HplL17jvCy4t1NebF9HtK3fEwhPzfdaj8VETnk3nNqJpXFNW48sb8GhBPYOLF+jnfX6WZm90J5Ay5xye+ekZHKt7DI0PNlY83XljZ+zdqPRFmDVkFmsd8my7FxB/LAGmMCNaPtQWxlATDMEGpGw9h5i6lWAttOGXIz9g7d61XutRYPP20iDkNDS+3666NlqNelafrxPkZ/m1flT5GXwS6P5m2YtL1y4pfAsxvt2Wr97EgUDGVSceOF9sDTBFE5fdshYOp4Ntc/71T7V7jmUylKSO+GIgQzKaQPH1vSnVl9ZTK0L4c7/f8a3jpzJ3cCdoALjy1g1sgHgxqYb3NL8fj3d/BHlZ1ov1aC33/DN4pt99ebmhCOaph1JQvXIC0tJyS7UMEklUclJW5wNFM/eMPcyOVzquFo9aWeoMC5ps3DZmb7HH/qOtH8e9zR9wfwZ/PFNE+NzDmV4+FYFAkfDTD6a633vk/mQmLGj5G+/YAYNej6BIJ7IzC322ZJOzY/bdczSgc5iuF+T8fzEChlL0j91/1uc+pbICmiy4FNdAymrit5k/aKLr1IMX3OuRZfbdKrQ0EXStbaj1mHzcaLXyo5ap/PHEm0VqZQXKUAcCPivFV5tALYFOv09jm92PUf8NxcZz0niYfBHUyNehd7p9gFc6vcH60s855jER3DnmAMsaoTGT3WnH1IOTSxhB9x8U1uoSoIbGN3K/dr49YSDvLZcC/ZVXXoHJZMLixYtRvbo0a3Ly5En2+JtvvuluvVZeMbgi6PbSRNA1TOIC7nNdxuKcrU++cn30W7Lcdei6sxVYoJOpVa5kMmGNauPzZbo8T0aD4chhpUlcADD/gAAFtTM8HE6jn1PI33OCSybQl59agvuaP4SxC0b7bB1EPWDVTNz7G55b+SSG1huBWUe1XZLVAj3Lxww69UWmNMELBedZ2r2aIHMQOm3shOPBRxFSGIKB8wbieJ3jaLK/CWocltZNLc55TtY8yYxTqF/poYaHmMdEoyHNWFqjmsrtpR9KutqEpQXebomo6poF52f8i4ssqQe2Wu23mnEGVHx6dxBXF6xOMeUZVFeZ1lgW8CKGH4RQ67aLIdBBJQ0Q6T8TvIXv5RLn8nf3J+jk9dSCBoaXMtJQkrRhf9D2zMPV3/KyuH15JbjYY5mOsbI+H/hj9mJLHwI9/v19h9KIc6338p9B5w7ptkqhkbDnG4udnAr0e5TVOV/cPr2U18CSbG9+PUjMqc3eLkag82JaxqhxzXMLdI1IsroDDN8yz982pIyJMC7C7uu1vDEqD72e/178JHcgr6fyAkqLD6TsK8rH5AFfXkfXPppI5gnkOK3LeSnwJQ98N5TLRZkoiE2bNmHq1KlucU7UqlWLmceNHu0ZJJf/CHopTOLyNSLol0B4B4ouVzUrLbdmpnPqlHc6fkXBmLeftcJzGGPgCK0TmEA/erjEbc3kHvYBvZbaqtn9t2sQXB74CPDBjINYxEXP5VnlDFebLIL/IZB5YZXUqzUQcU6Qwyxfv8ZD9WiZ5kxm+FaQpfzRjcyJZPXjHbZ0AJYBndCBPd5yt9TxwqFzKFLXZU5XP41lvZfh3xFz0GaH1Huch+/t6gtHMaMySu9KK5R6mVOt+30tHnRHhmjGm0x61H2dtfhfr68w+8gMDK43TFEXRm2DyHzvhY5S6zM5Ei6lDDoVAw6t2fAJAyZjztFZeL+Hsu90aSDjNKozD9IHo2m89/acNHAq5hybzaIDAoFAIBDwfNrzS9ZJ5cGWj5RJintJDS61hKravybgCHpwNCsfGtfmKVZOpPV7SGaQD2t4sWhFtvnoc2CtM+MC7rJRPVJ7koDKOWjChMZfVF4oezCUpLVmzaiamutUYSPo1O/84MGDaNCggVd/9KpVS542fsVq0EPKysX9ygl0Pd9jnchw3WIBQ7A0EVERMebsYH9tUa0VaexqdHmeCYrQX36EIcV/mrIXPhz4fb1WJwT6JTV+e2v9a6zWtThTEj6CTmJ94j6pnqxTlS4s5arQVqRIJ1enndOPmHq2tTguFKT4nD0nU6aahyLRZlJrHGl6BIYWBtanNLNSJu779T6EFfr+ofz71r8Rlx6Hfov7YV+Tfay1id6hZ/1Cqbd4ta41AOl0cEM1tYHU5VJ9uy+mDp6Jt9a95hbocr2dzJPtvE1nfHFX07HspvYCoNZNWn19n2grTY7w7EuXMmZ4qM5xQB3/7u6BQsZp/szT+ta+kd0EAoFAINASitTuq6TwkWNyuifBTR46gSJH0LXawqk7wPA16HyEXA2JfcqGeJ3zPynp7yGfrUMmrhfTOtPop8uGLx8c6pQyYcBf7P7IWd7dXdRdALSozKXm85MMsjFfhRPoI0eOZK3V9u7dizZt2sBoNGL//v2YOHEiRowYwXqkywwbNgzlCqcTerPUYssRlFg2Ke4lEXllTNGIUcyt3dagITOF09lsAOmSjoCxzjaAakwuoXvtpUJvltou2EO9e8r6Mu0rsThnEXTpAmPp3BVBG6Temz6x21F0y+0wbd4IawvfhiuC0kHCWm4nVpxAV/dHlftR9689kC2H0r6Sc0/7TCU7yLmoFwe1xKLP23Fhm2arECJUF4pBswYiLiMOiYcT0HWWtnPtxo4bmZt6VE4U2m9pj019NuFg44OsJ+epmqdYL1Ayc1ND7rZTDkxS9OMNpC6XWqP8sFMpvPkfParPpTT/smz/xKcPlsR4iUyOnl/5FLpV7YG1Z1cHPAMuEAgEAkF5Re4TL6fJU4tSEuhaJWrVNczWjC6xSEKdot0ULabJZmoDSG1YCTI9XHB8Lu5r8VBA3Ry00uVLCi9iG2iYiKrhW46qBbrJj0CvV8m/US1BXTQogk5ZAXvSdrHHkjQMa9W0T5IyGtXO/L7GepeSMlFqEyZMYEZw1GqNbjLk4s4/RgPI8ibQdbYcljpNOIISLmkf9MsB9UXPql4DtuYtEH3rcJi2bQWoRWFLwJCYgqD0xbAklN5t80qhs0pmHI6g2BLV4JcY177L+fNvxPTtCaM/53uLBUV3jYW9fgPYWkjpyYKyg1LEA4Xv58lTM7KmW5CnF6Zp1mVR5DxPJfD9QT+I+zP2KvqkU015u63tWO9winY3MTdl4twf5yqfw/yBnlT8JX2XsN61OAMmypNrJPt8Lzl6U3uvpLDK2J22s9h+uTK9avRmkfJb/vO+DlPNGPXVrRtTDy39OPyWhk137GTbuCTO65RiT27KNFlwKPNgQK3IBAKBQCAo75H3+SOXsqBB75p9WCR87ojFqOEar/CQcCVzzGBjMDpPauMVXZ4+9D9WSkcT7FvOb2JZg8QPfX7F1pTNiiwxfzXoWi3bSgrv3xAXGocVt65Hr799t9XrzrVA5cdkbFkG3/K0bnS9YteFghjUgaVFfEukF6UhLMqIKH10sd4LZFK3/JZ1rDSPr1l3VFSBvmzZMlRU9BYpndNhiAAMJTNQKo8RdDI4s3aTWqpYu/eUBDppTDJWvB4wZW2skAJdb81wOacXI9C5GvTSIEfQycndckNfGH/xnb6ks1oU21twadPd/UWI+RR3rR7clNr98poXvCLo/xycgieXP4oxTe8JeF1qRNbA2WPJGDprKA43OIz8wYVo/VlL1D3und0xb8A8nK16FjVO12A9zOPT4jH5hX/x+sKXsSBvrjvdXk69ohQtuW6K2quo09VkqEWJ3H+XnMIDhbYhiXQt5Og09Xcta0rTsoh+7LtWkyYeStLXWCAQCASC8ky7pA7sJuMva61JnNSCU4afrObbgPbgBC8JTP7fhF7VWZsM35LzTvs1XisJlF3I0zSuGRuraJnfqU3Yci1K/6xQg+9ofyCT9TSekdtLRodEIz4+MuDOEeVlvFFmuc4HDhzAsWPHYNEw5SpvUXMenVWKqjmDSterurzVoPMUPP4UTGtWwnD6NPSHLzCBbszehPKIzpKOiAPPoqjqnbDG9/Ep0B0m/3UtfA16aVCYxIX4vkAwLFe/C/CVhK8TJ0d0f27EvtqEJYQl+I24P7ZUMkEbv+dnRYQ8oygDeVbPsURp1hdWnEdqQipqNK6Jav9WQa1TtSRRvkh7ndLi0rC13VbYjXZk1s1CTHAMxrS/D7EN42A7aUXO4Rx3O5Kz+VIJRz2Fg2iC+8fzUpEYnogQfagiDU4gEAgEAkH5gtoLfrv9y1KbpFKW3HXVr8eetJ0IMYTi1S5v4rc9v7BARll0yKCytNlHZ2BEg1Hux/4aNA2PLXkQH/X8TPM9fw78Gy+vfoG1XuMZ2/w+/H3wL9axhcZ/fx+YBL3OgLuaSd42lwvK5NuTthvdKbuxIgr0Tz/9FL/88gvi4uIQrIoel8e0dh69Ja3U6e0+Bbq6F/kVwhkdg6wFyxE8619EvSEd1KZsqkM3A/rysY4yocm/ICTlX3ZL63nMa8JEF2AEXX+REXQ++6E4N34WQRdcMviIOdWQawl0ciydeWQ6TrjM2uT2ZvJsrnpGl39fSr63R8ENNfti8k3Tcff80Zh/fA57bOmo1Zj/7xxE/BUKm8EG41wTcMo7T2pTh01Ii0/Di9VfgbnAjE8r38vEuVz7Pf7GPzQdQatEVPEIdM78hNWEXWKB3iiuEf4dPPeq7wctEAgEAkFF5t7mD7DbxYyppg3x9B0neDF9sVBEfOMdSgdbimLvuNu3x0+/2gPYTU10cAzWjd7q/vebXd/FlUBtllvhBPrff/+N9957j5nFVdgU99IK9FwpCuaIjYU+QxKRKEGrrssBi+ifA5x5JugiChCUuhCWpLLvI1wWLu1E6KkfUFD/VcXzerkG/RKmuDtJEHK9y4ttl2cVEfRLndYuU2QzI1IjgE4tTmQjOaJaRHWcyDnuTtny1feSUq7WnV3j9bjc2ismLwYP/vggElITsO7jFYgokLIpjHYjcMTJhPrk2ycjOzobj698AtZUC5ZfvxwhlULQ477r2boX/lBItqGMyuHKFmg2MmvUcA3l09Up4n6p6VFTlGcIBAKBQCAQlCfKRKCTQVyLFi1QEbkogW42Q58sRbjs9RtCv2lDuUpxV9RVOwHH7hgYuqQi5OykcijQt7vvB6Ut9BLosklc8TXo2inuTqNRcrQvLnrO1zkXF0F3lKwtl6BkWB0WRQRdi5mHp3uZr8gCnfp6+nItpdYjlMYu9yXvsboHHHoHIsZF4Nyms6j1XXWEnJP2v93mMQfJjspGwz6N8XrlV5GaKF07Yr9LZLPQul1BLFIuz1RT7/Bscxb7N5m58eRbPSn5sZx7KaWgUW/Vnak7cEeTu5ixHbVy4+vny4Klt6zB/GP/4dXrXkV+djHnhUAgEAgEAoGgYgn0F198EW+//TaeeOIJ1vdcr1caEZTnXui6Ugp0EuYxg/oykeYIj4C9Rk2YZIFeTlLc1ULTuTMU6AKYMlcD5Eh4Bfr6aaEvOguD2dOf2ZS7kz3mCHEdNw4b9Lbsi4qgO2NioEvzuHhrvkaV+VDeJlquFg5nHsILK5/GM+1fwHU1vOt6qH3ZG+teQfM4z6SfxW7WXJbNafMS6DKRfiLoVrsVeQtzUOd8HfRd3BdVz7mOtY3ADExBCFT7vo4Ox53HMHHMRGy9ew/yJxcAro+OCanE6rceb/OU4i3UosMt0FURdN41Xr2OY5p5G9aVtUAnZ9OWCS0RagpFPi7Ot0EgEAgEAoFAUM4EelFREeuBPmbMGEXdqOy8TD3Ry3sEvaQmceEfvQfDOUlU2uvVV7RWc0ZevBtiWSKvm+6U5Favt+fBkHcA9shmKA/oi1xZCCG14AhOhCl7M4LSFqGoulQ3r7N52m05jdGlarNGEyh6DYGe99rbiHjndekfwcoc6uJS3PNefcvv8wJtHlvyAHakbsfa2auR+phUIsIzeu7NSCtMw/qza92PFfkQ6HYuVVxOcZcJ0gdp9s2OyI3ADUtvgGmHHnfjbs3l2urasbDxAjQ62AiPvPMkViQuw4Q1E6T3myJY1LsgL9+v+ynfQ5Mi4zwFnEC/vfGd+GX3j2idILVQ0eL5Di/hk80f4MWOr/h8jUAgEAgEAoGg4lMmAv2TTz7BLbfcwm4hxdXtlleTOFPJIuiUMu2+Hx0NuNpzyYK9POGOBBdZYItuh6CMlTClrYOzIA6OJFdkr7AQutxcOBMD71NcVngc2mNhie/vEugL3ALdXX9ujAG4PosyuvR0Jq6dEZHQ5WtH0C0DboJp+zbFY+kbd8BRo6ZboKsj6P5S3DPWb4W9bvnazxWFlIIU9/2MonQEmalQW8dapVFkmcS5GrPNk+J+LPsoi4A3rNQIVpVA51PJ7aq+lZXPVYYlyIIR/45A9TMeIU+s7r4a6XHpGLx/CPo+PhAzak/D5q2bsbnjZnx6wzdYvNNj1U7Gc7GhcVx7Eu1JIz69nnqU+kpxb5HQCtvu2osEPz3Cn2v/f6zvee2okrcrEwgEAoFAIBBcYwKdWqvdeeedqFHDk156tdegOyM80TFHpViAq28ubwJddibXmYtgje7ABHr4jLcR+eGzSN+2F47qNRDbtR0MZ5KRvn0fHNWU4uVS43ZoD6oEc8KNCD/6LoLSV7jd5j0O7hot1vLyEN+kDquzT0tOc5v2qbF0vw7qzomOOlLfamdYuNTPnptkYY/7abNmr6cUXILA4VO6m/3WgGXanH0kHddN6YRTuSc132N2RdBXJa/AzbMl/4Tv+vysMFuTe3/KyM/VOVYHfZb0QbWzqih2aAFmDJ8Bg93A+pmT4/qwx0ahceum0G/ylH9QFN5q99TDUzp7pWDPsRgVrB1Bp/pxmcrhVRTPVeLqztWp+VpQJlKdaO8+6wKBQCAQCASCqwvv/M9ScO+99+LHH3+E2aydhno1CnS+1jn/jXdgOH3K/W9njP9e3Vcsxd1shjVOMrHS181m0zNBK5axf5M4J0yrVlz29eMd2u0RLdhfnaMAxjypNEJvltphOYKTvN5rOCm119JZLNCfOwt9picdnscZGobcz7+Bpef1sHTtjrzX33E/56AMCG47ud/jI4Ke/0zZ1gNfa4QYQxQimiLd5/LO+hTnvEA/kL7P/diGs+thc7VUkwkzeqZh7E4bE/+D/xvsJc63tt2KT57/BIcbHsaBJgfc7dDCjJLAN6j8GSycYR3Bt2+L9hFBP19wzn1fnWr/Wa+v0LlKV0y5SWlyJxAIBAKBQCC4timTCPratWuxY8cOzJw5E/Hx8TAYlIPbpUuXolzitENnTQ9IoJM7eOgP38I8ZDjsDRu5BXru+x+zNGnZzb084klxL4LV1BLOolDowguBloCjHEwmKHqc63SwRbZEUMYKGHN3wxbVGgazJHTswcooJMNk8txdJ7XNciQkQp96QfkZNiuK7hjDbmqcUVEA+QmoU9xVEXXC3Lc/Cv5P6TAvkNiTthurk1fioVaPatZ+y4QYvCc+jmQd9rts2cWdN1c7mnXYyySOIuitdrRCl/VdcKFrKr5/9HPEwhOt3tViF85XPo9tbbfBqfdu/i1H4NUCnVLqeajfugy5tWuhju7zUL/z2cMX+HxeIBAIBAKBQHBtUiYCfcSIEexW0SBhqIMTTvp/Me7gYV/8D2FffYbwj99H6oUcdzsvqnsmLH36wXj0CGxNyofxmgKXq7zO6UT4/z6GLrcQ6A+gDaArLFC+lm8zdpnQWzw16IQtsgUT6IbcXaoIutIJW07bVwt0W/0GCFIJdEe87wkYZ5QcQVeluGuITGsPb9dxgUTvqd3Y38SwRIxseIvP1wVzEXSZfel7/S5bjqArBHr2ETicDiSdT0LHTR1xrO4xhA4IxfCZw9nzlWd4jpf9jfdj3sB5yI3y71guR+DbJLVTPN46sa3i3wa9MgVei361bsSikwswpJ60PgKBQCAQCAQCwWUR6MOHewag2dnZrC861Uzyju7l2sGdhKGG+RiPYe9u5XtdEXRnuJTqmv/iq7A3agJz/4Eob/DmZ8ZtWwDS5CTQW7n6hl/hft68SZws0AmTW6BLEXSHVgSdK6swrVnl8QBY73EAz/7zb7919SyCrmUSxx2/GRu2wbhpI8wjfQvPaxkybpM5nesp99DCqPM+13an7vT7niKXSVyexSOws1OzkJibiKGzhrI2ae22tcOJ5COK99W+sR5+cH6LHa13oCi0CPNGLMHAf/v4/Bw5gt6rRm/82Hc8Gsc2Zf8eUGcQq3lvGd9aM8KuxZe9v8e84/9hWP2KN3kpEAgEAoFAIKjAAp3qPH/44Qf8/vvvyM3NxcKFC/Hll18iLCwMr776KoI0UoUrQv150OIFiHjpeeR+/QMcVbhe7larO8XdbRYXEYGiO7VbNl1xuNrqIBKulJ1LJbVxVMO9Tylyt25B+GcfI/ejz2C9XqpXv6wp7kygSyLImLODGcV5BLpWBN2z7sbjxzQN3Cz9Bvj9fLkG3SulnRPo9jr1hGu7Hxaf8KRr77iwHR3+bImn2j6HO5p6Sgre3/A2VpxeqnAwl/nn0N9+l29xmbTJEfT41Hjc89s9CC9QWv9lbpBKVrq92ws1etVCbMM4jP3uLvZYx8qd0b5yR7+fE2byLG94g5vd92mykVzUZYzFTOgRcaFxuKup1IlAIBAIBAKBQCC4bCZx3377LWbPno0PP/zQLcYpqk616R9//DHKK8UJ9Og7boHh1ElEj7jJnQYtG5O5U9xdEfRyjV61m6mcdp10NyRhFnRFnjT30Am/wnDiOGJuHX7FIuj28EZsn+gchTBlb+EEOjdJIsOluMtYr+uJnK9/YPdzfhxf7Od7UtyVEXRby1ZwxMfD2oJSDcp3NsiV5nCmp4acosYnc07g6RXj3I9R5PuLbZ+y/ueHsw6VePlF9iLkn89D4vfxePyrxzHu23EKcX6y5klYjVboDDr0/qo/Wj3Ylolz4ul2z7G/b3d7n/19tPUTPj8n3GUSVxxPtnuW1dLf2/yBEn8XgUAgEAgEAoHgkkbQZ8yYwcR5hw4d3Gnt3bp1w0cffYQnn3ySRdErsoO7zm5X1Gobjh6BLj/fq91aRcK+qhoMHc5AH56GoDRPj2ce04Z1sNeoecnbrqkj6CSGLZWuQ0jKdJgyVnA16N4p7roiZeeAzNkLYWvRit1ShwwHQn23SpNxT75o9EFP374f4HreC4D96fsQERSBGpE13Y/lWLJ8vp7qxN9Y90qpPy+0IBTmXwow8e+fkejwnKspiSn4Z9Q/iM2IxYnaJ1ApsxKW37IO8c2V5/NLnV7HU+2eR6irL/kbXd5BZFAkPtr0ntu5vcBW4NWmzR91o+vh4H0nNQ3vBAKBQCAQCASC0lImyiM9PR2JiYlej0dFRaGgQGVCVo7QyTXoQXHFv5b7HoYjh6HLV6W4VzDsiQ1gWHEGGASEXJig+ZqYITeyv2SKd1ki6EEeoz5rbC8m0EPOToLelsOM/LRc3HUWpUC3ders+UcA4pxwVpKc7J1hGuJMFVW/1kkvTEfPv6VtfOFRz3GRY/F9jEw5MAl/7Pu9xJ+VmJKIhocaos9Sqhl3gPdc1/cz4Psu3wM6IC1B6jeeUjnFS5zLyOKcoEnEhFDP9apqRDW3i3xEkHZP8+KWKRAIBAKBQCAQlBuB3rlzZ/z66694++233Y/l5eXhs88+Q6dOnVBeMfgzH6PHIyKhd6WyKwT6oQPQFRZWbIFesyawCHAOBIIK1gG0CTxtm5U4nZcuxdteCJ1DSlPnnfQtsdexv4YiqT+7ucqtgFFjWxd5Utyzpkwv1XqaR9yM8CMHUHT3/aX5BtcUZ/PPKNLW5RZj2eZszdcXWAsw68i/Jf6crsZu6PVLTwRZPb4ALe5rjZdavoiT505gyq3/4qVzr2HNmVVYfWZliZcfZPAs99XOb2H8np/RNrEdksKSSrwsgUAgEAgEAoHgitegb968GTab1Of3zTffxL59+1hau9lsxqOPPoqePXvizJkz5Ta9ndD7669NglE2DyMKPMZWoZP/9LzG1WatouGoWQtIBZyn4qUHhvh58SXMgpCj506dEU6DZ1s6QmvDHiKlUDv1Iciv/7rm+2WTOPOAm2Dt3bdU6+CoWg3480/Y2ihbawkkPtvyMX7Z9YOXA/v5fKn0gMj1EUG/a96tWJm8nN0nV3QtooKjoLfrEZEbgfC8cPRf0B/9Xu2rEOeL+i7CumHrcSjzIMwhZkSYIvB0++cxfeh/pfpOvEAfWPcmTBsyCy931j7GBAKBQCAQCASCch9BHzNmDNasWYO4uDhUrlwZ06ZNw/r163Hs2DEm3OvUqYPu3btDrzYoK0f466/tbr/lChjqU1K0F1JOHerV2JMqw5DiEVT26jXYX8eGJOhrpQEUsF4I4IT3e8mx3hmudMsu+/rzSsrot04Hc8IAhJ3+EQW1noAjRLsOXu6D7nT1eheULadyTuLDTe+y+/c0fwAWVz9yIqXgPOpXauA3gi5Ht6tH1EC/2tpu+knhSej5T0/WJk2LrOgsrO+yHuu2upwNWSq6dzZFsCHwY6BNopiMEQgEAoFAIBBcRQKdWqup6dKlC7tVFPy6gzM8gtF4zNPnuSKSuWQ1ou8fA9PG9ezfjnhXre4RHSyGrgiyrwPa+BDo+XlwIumyOLjz5Nd/A5aEgbDG9vS9ALNF2+BNEDB2h539NegNir7jVFd+ocAzMWW2m2F2tTsjzuefKzaCLlMzqhbCTeFMRNNyiF7Le6HG6RpIHZPqJc71lQ34q+ckZMVkoSikCE698noTYfLOXAkugWFbnei6WDhyOeJCXRkkAoFAIBAIBAJBRa9Blx3bKyT2IuitmX4j6Lxzu45Lca+IOJOSYO7b3y3Q5dp5io7bHR2kvmu1tN+rz8+D43I5uPMYI2CNu97/++UIerBw0y7tRNugf/uw/uIrbl3P+ntT1Pz6qd28RHeRvRAWh9krxd1qt7pd0HkBzlM5XDrHKodXYS3YwvLD0GtlL/ZYvTfruV/nMDlw6/y7sD1qGw7MO+BzvcM1IuiVQiSzv0BpkySi6AKBQCAQCASCq0igjxw5MqAU9qVLl6K8Rs+pvtlpjNF+kcsIjsfcpx+Mu3ex+0W334mKRNGYexAyaSIsA25y187r8nNht1UDKHhKOr0hAFWbahLxlwq9xXcEPRDkGnSR4l46SFhvu7CV3T+WdRQNYxth5pHpmhFxs83sleKudnBPDEvC6dxTXu9NCpN8HqqEVkX06ihUO1PNK4192s3T0LFVZ4xrmYSos5z/gwbhRk/Jxbc3/IR3N7yJn/r+VoJvLhAIBAKBQCAQXGUC/Z577kFkZMU0SVPUn3OZAPrk0zBt2gDz0BHQcQ7hMvlvvgd7w0aoiDhjKiFz4w52X39aElG6nBwE/7wAeNj1ojcAjKWwqOd9OpeT/eVOcef7sZOTvLVLN+8n5X0kIuilglzWZQpdUfAFx+dpvrbQXqhIcd+Zuh3/HZ2JZvEt2L/DTRHMvE2mVUIb9ho5ck7R+rbz2iDxP2UrNHtVO3697VfkRuWiebQ0KRYV7C3Qn2n/AjOsU2fvjGp0G7sJBAKBQCAQCATXrECnAfKgQYOYSVxZkpKSgvfeew8bNmxAcHAwBg4ciGeeeYbd37JlC95//31mRFerVi28+OKL6Nq1a6k+R2+RamsdQcra6tgubVlUNjc3V5HiLqPZK7sC4oyJgVOvh85qhWn1FtYPHZJvHFAfwP7LE0H3m+JOmM3ufuxpR5PhjIzS7IPurCBmfeWNApundCPLnIVCWyG2pmxm/x5UdwjmHputqEvnI+jrz65lt6faPsf+HR0UjRCjZ6KkVlRtt0CPT4/D7JHTkLhGKc4/ffZTjOs9DrmbpUkgu0PqDBGl0Y+c2qAJBAKBQCAQCARXM2VqEnex0DKfeOIJREVFYdKkScjOzsbLL7/M0ujvv/9+PPzww+zWv39/zJ07l7VzW7BgAXORL6vIrZwyHbR4AXQWi1uUy33QrxqBHhmFvM++Zinvps0bAQpMvkKhTgBNVAI9P/+KRdD52n/9uXOwqwQ6CXjCGSIi6BcbQc8oSke+NR9OSOd2vWiaqfFgthVp1pcvOrnA3S4t1Og5P2qG18LoSaNR9WxVpFLGis0JY6gRRe0twFEnZnaZgbzIPISEefad1SGlbkRzEfTra9yAVzu/iebxLfF6l3fQJJYOUIFAIBAIBAKB4Oqj1D3Qhg8fzqLaZQlFxnfs2IEPPvgADRo0QPv27ZlgnzNnDrZt2waDwcCEeo0aNZhQp8+n119U/+0gH8Iwx1NXa6/jMbFyhl2admNXgqLRd6HwAVduO22OOdJdZ2uPm3cgKe4hE39D1B2jStUvXecy6vMVQefLDPRp1LjdiYjnnkL4m68qny/jY7Gi8t/RWRg5ewjO5p3B7tSdGDlrMLanSDXmxUXQM4oyUGSTUsyD9EFercyK7BRBt3gvwyotIzIoCuH2cNz8z83ou6gvkv4Xj4aHGyIiP4KJ8xrX18KtK8fgienPod3cztjTYg97Hx91lx3lKV1e5sm2z6JFQiuWtTOuzZO4oVa/i9hCAoFAIBAIBALBVSjQSURHuJzAy4qEhAT88ssviI9Xtj7Ky8tDTEwMsrKysGjRIhZpX7JkCfLz89GwIbmalRxdMeZkeoVAr+t54ioTgo5K3PffKf3R1bMDsYGnuEc+9ySCFy9E6C8/lvjz9Wa51MBHuyteoKech/7kCYROHI+w775i0XO3SZyoQWfct/AurE5egV93/4SRswezPuSDZ/QPKIKeWZQBs13a3iHGUIRx0XA5xV0rgn4i57g7Lb362upovrc5uq3rBvtaKV09uVoyBs4YhpumjEB0bcmQkV82CfQBdajGAniw1aPsr16nh0lvYvcbx4mIuUAgEAgEAoHg2uCiTOLKGkpt79Gjh/vfDocDf/75Jzp37syi6XfccQeLqFPKu91uZ5MEdety4rksU6tzc9yp0/ZqnON0RW4tp4EjlvMQoE1Cna0aA7gDwGQq/A68Bl2f6umZrUaXng4EmZQ15E4HjAWSZbw9vIHy9dlZcJqClBH08+fdpQbu9HdXDfrVNnFSGo5lH3XfDzWGsppywuLwjnrLyO3RZIFeaCtyt0sLM4X7jKCPbHAL6yX+6ZYPoXPoWJ/yCEMkKi9JVLyn/phGGPnqaCTFKMtQ+GUHG4Mx/sY/cCrnFFumzIF7j7MJhNiQsvW5EAgEAoFAIBAIyivlSqCr+eSTT7Bv3z5MmzaNRctPnz6NcePG4frrr2eR9HfffRetWrVCvXqeFPRAII2ts7lSq4NiNTW3nOLuDA2Fo36DS67P5eVedv0fp5qgWOwS6J3JlQvAU1SDnhfQepGY1nxdYSFiu7QB9Hpk7DsKGKQUen3RGejs+XDqjHCE1fFsgwsXENuhFWxNmiD/w0/di9GnnIO+yCMo9YUF7gg6QoJLve2u2LYvY5adop0nEWRQmub5+m6FihT3dFhcEXQS+OEmZQSdoutyH3QS1d2r98DPS77HmIljkBuZi9ABYQg+L02UWEwW1BvXAP1fliLjavhlUwTdZDCiboxyso1q2ukmuDRcLcd9RURs+yuH2PZXFrH9rxxi2185xLa/Ora97jLuP2N5FucTJkzA559/ztLYv/jiC5baTgKdaNasGXbt2oWJEyfirbfeKtGy4+IiAWc2ux8ZWw2R8d6t4vTZUvRRHx6OiHEPA0sXAj16IF7jtWUJW7fLSVgt5b83AOjXFWi0DiCN1wAItRYhNIDvHQq79uuOXgCypO0Zf2Qv0M3VLu3safZHF1kf8YncRMH6FUBBPkxbtyDmnKendlhWOsK4/m+xwTrALv07MqGS5n4s19u+jMlxSFkhhC5IquWW8XXc6k853PfzHDkIjpCqXsKDw1A5Tll2YAoFjK75kOjwCDSuVg/DZwxHXEYcu+EH6bm1Xddicb/F2PbgNt/nS5inewKlslf0bV+REdv+yiG2/ZVDbPsri9j+Vw6x7a8cYttfOeIq2LYvlwL9nXfeweTJk5lIJ8d2Yu/evWjcmEK7Hpo0aYLDhw+XePnp6bmILkhlXz67KBTWNI8JmroS2h4UjMw8K/DHVOkB7rVlCc3K0MFD63YJDPL9ov7OBTldEbZ8HXA9gLqAOSMLuX6+t/x+c3au5usM59JRSV7239NR0Kglux9ybjvIxcAc0kDxvqCMXMhxU/OkyZCT1+3LV8C5Y6f7oM08cwEReQWgSuXsIrtiP1aUbV+WpOVIWSHENxu/UT7nY9ukZKZ77udewHkqRWAXhiDYCpRThalZmcjZmo9aJ2rB2VCPPW/uR+2Ttdlzdr0dBocBttp2rOu6jj1WmGtHmkn7cwttnokBh9NR4bd9ReRqOe4rImLbXznEtr+yiO1/5RDb/sohtv3Vse11rmVdkwL9m2++wZQpU/DZZ5/hxhul/tdEYmIijhw54uX6Xr169RJ/Bu0guQbdborzu8OcoWGX9WSiz7rSJ6+Detvvov5WAIYChiWH4bTbAH0xh0tRkfa6c3Xjpo3r3a8xZkn9tm0RTZXv4wz6ghfOd983nDsL0M2FLr/A0wc9OOSit1t52PYXg8LwzewR64Sv78W/51TOSfe/Ke2cb5nGXvtLHqInReAe3AP8DuxxuQpSxHxJnyV4rcFbsFayIn+LlDYfZAj2+bnBeo+pn81hq/DbviIjtv2VQ2z7K4fY9lcWsf2vHGLbXznEtr9yOCvYti+1i/ul4OjRo/juu+/wwAMPoF27dkhNTXXfRo0ahVWrVuH3339ntej0d82aNRg9enTJP8jpKLa9l/uloaG41nDEJwDHPP829jmMyP2Pa7+YO9p5QzceXWGh536uK6JqL0TwhVnsriWur+L1+hyp/KA4mEmc6zOFi7uyZVpp3kNt1tadXcPuhxhC3EZuwUXBuGf8PcAkT9SbvSY2BIc6HMbqHquZSVx4tQiEBnlEPRnN+YJapsnYncp0fIFAIBAIBAKB4FqlXEXQly5dytzZv//+e3bjOXjwIL7++mt89dVX+PLLL1GnTh389NNPrF96SdHZcqCDJDYcJjn5+uoU6AczDuC2OSOYCJo4YDJaJ5LzmzfP9gNW1QJW/UYR9HjYTgF/nwBaBgEtqgIhZyfBCT3ymn4N6Lh5HQvnEC4btnHorNkwFq71/LsgH0EX/kP0zjtcJQRJsEW3V74nOzCBTpF53iTuWoG8GMbMvw06nR4TbvwLTjjZPl5xelmJl8VH0IlZR2a4I+jUCi3hQgL6LeqHWqckrwJLkhXGCwb8f3v3Ad5UucYB/E2adJdVoOy9t2wUQZANogwRRFERcKPXefWqV8W9cCDolaGILBFQUDYoDvYessreZXc3TXKf/3d60pM0SVtWAv3/ngeaJmnGd05Ozvt97/d+pjCT9Ft6r0z5q4ekJWidJNHWaLE7tKXVcgvQjfS1z4mIiIiICrqgCtCHDRum/vly6623qn+XCkEjOM2RImb/QYSjjGGJtWvQb4eWyJGkw+ry0oOLvQboyU89Kx8X0aqlz6gj0r14Cfmzgsg9qL9mE3FMCRHTALtEHP1O0kv1EVtse9ff6inm6nJa9ki54nRI4Y39xOpYIYLNtgSj6ckSs01b6xpSKz3pHvAbKujnBsu/mU+fUpcdhbX1tQsCjHQv2K+l/iekJsj59HMXFZwbl1mrUbSm7Dq7U06lJrjWQQ83Rci9390rhRK1igD2knbZM2Kv/L3qDxnS/GGJLhMjRcOzO7iiQ2PkQoZhekKI/6yGduVvlb+O/CG9a/cW8dh1iIiIiIgKoqBKcb9aTJlamrXD4rGEkz3nSF56R61I3bVi26mtcjz5mOv38+nZo9FpWWtce0p56VXX5VSryGL7P/KbVvtLsc2zS2rcIHU54vAE9z9OMwbohsd3OiT6n6fFem6F9nsf3AHVu5PFnKm9poT2JyS1olaV38iUxxR3y66dagTdGRYmjvIV5FqVlJEomxM25vn+WO5Ml5hx3rU2+cVItmkp7j2q9JQQU4jEHY+T+pvrS5g5TM6vPOsKzmHRkMVyIfS8HC5/WMKqaR1bxjXKMYJuNnS25DaCPqXHj7Jn6CEpEVXiol8/EREREdH1JKhG0K8Wk10L0J1WjwDdlr2El3a7VWztLn3E/mpBYN5xRhupXqSm/N5fC4wTDSOaqfbchynHNBXZ+NcQkVuyr0sMFQmJuF0iZKKaN154bQ9JrDtKHBGV3EfQ9fnlKBCW8ItEHBmf/SCFRaSmiClKG7G1xTTEg3p9DeasEXR7qdIScjy7s8GTZbNWpMxeuYprbfVrUa+fesimhA3yc68F0rJ0q3ylpWM03XEJVS/0EfTS0WWlg72TNB7fSMIywuTCuURZE69VY4fN9TfLSusKkf3iKgAHxcKL+QzQQ8z+twnui/XWiYiIiIioQI+gZ6W4Wwq7X29zH4m016glzhiPID6I7T67S1XEPnBhn+u68xnZo9GpttRc5wBvKZ1zl0gKFXGmFJf04lpV/dCzy6XQliFqlNw479w4dzzs5BztOcs+ILakG7QrG4mYymc9Z3Rtn+9DH0F3lMu6sw+WrVkBepVqci2PniM4h1/2/pzvwm5n087IhXRtjfmLoQf71niLNB/ZVAXnUGhpjFw4cF4SoxPl0+Gfysw+M7UMiCyh5lD1s6gxQA+NcQvQiYiIiIgofwrk2TSKxIHT4n8EPbNa/gvQXU1Td3wvb654TRUNgxMpx12jonrQfSHdMIKeNVoKc+Jny8t/vqDul2ZImbZnFc8zSgwTMZ05I8nVR4gjVEtHtp5fLTH/u1fCZ82Qn2uKPNFVJDPlgojDIeK0S+ipBep+6aXvEvu5ytoDYfp7ViyNpdV80eeg28v7D9DNZ7VK/PYg307+/HZometyyci4PP2N5wi6cd63L3fP7SuDfu0vfxz+3XWd0+EUy94Qqbqnqpx/6oyEJIbIucJasO8McUqDhxrLlw9/KWeLuS/ZZkxfzzGCXjAPKUREREREl0WBTHE3u+age46guwfojgpa5epgNXzpI+pnh4qdpGWZG+V4shagQ7ItSQqFFXZLcTcG4g8u0OaU31jmZmmRS1o1UtzNZ06LLfpWOd02XiLj35Gove9IeMgckffmyO2vaferfUqk34XzYgo9J2bbWXGaw8VWuLlYT/0qUlJEUG+vrIhTTGIrhkXWvTOf14JER7m8zSvPrFFTrlUL9v/qupxo6EzJz9JoqLiem8UHF6qfBy7sly9Sv5JNX62T83vPSRtpLSKtxYmOmeomGdNnjISlh8lDDR+V1t1ukeTR3pdu01Pco6zRruuiQ6OlSalmeXoPRERERESUUwEfQS/sdwTdXrq0BCtjYbBTqVol8xOG4nB68S/3FHdt5NUYtCOQNxYd80aNoJ89o9rHdP6cpFZ4SJzOMBH0Xxhi4x3FtZH2kNQD6nd7RAVB3GdKcorMz75fWqHBklmooc/nMx86qP29jxT39C7d3NuibXZV+WsJshcWH9AyDeCCYVsZ2ezu+2WyYQQdKe55Dezh5K4TsvyFJSo491RkaDFJD0+XC4UvSFgpLejfcO926VUNFf7chYVoKe5Ws9V1XaQlSmoVqy2/9F4k6+7dmufXREREREREBTpAT/Se4m5c0xsjuGX9p1gH0tn07LRjh1NLZzeOoCfZktTPC4Yq7qmZ2hz0vefiXdeZTCZJy7reF1Uk7sB+Kda0vhSvXkEivhgvtvQm2o2dRCpn5WEkW0ViW94g4Ysnqd+dydFSvEoZiZjwtchsEZkrIqNF0qzaGujeRP/7GTFlVdN3+EhxNwbktsZNxBmXt9TwYLPh5Do5nXbaa8V94zSGKmPLuAXyKVmdL3Am7XSuKe4Wm7aBmhVqLl3ndVWXIytESdr9GTL6kdFyskOC1BnUQOJuKeP6m/CsJdLKxpSTmsVq+xxBj7BE5igK16xUCykfc+1W1SciIiIiCpQCmeLuaw66KTPTddlWv6FktO8gwepManZgdy6rSJg+B10vPuY5KpuWVcV9z7ndbkFhmj270JuvEfTwSRPFnKwF/dY/fpfMQvUltPzfIi1F9opI/2NaMTkIXz5d5A4Ry5KNYkozzGmfov0wpfruEAid94v66ShWTDKre09dd0ZFuS5ndNICzmtR/Lk9br8bMxs8pzHc/cudcvLRC26V1/UUd5O3fjanSK0dtaTe1npS+5/asrPWTmmQ1FAyD9rEKU4JfSFC5jq/k5OnTkrtAfXlllodZOPJ9a4/DzOkzQ+sPUi+/2eiHErUMhuMAXr7Ch2kdrG6Ur9Eg0trDCIiIiIiKpgBujkrQHdYs1Pcrb8tFXPWkl6OEiXl3OLlGF4O2GtMSEmQ5YeXSfcqPcXhdMiv++ZIuejyKuDuVKmrSm02jqKCcf3zSf9MFIc4VACnS7GlqrXQ31r5ultQmJcRdD04d1VrPxolsk5UIA73FhIZkxWgq/nmuN+J7OB8aWWRTXEivXaIlPp+othatBKxeOx+SUkScuyo9p5WrPe9dJphu6R3dk93v9owsl02urzUjvVd9M6Xs+lnXGniNofNbTqCN7/unSv7zu+Vyf9MdF2Hyu9tyuWcz4/AvO+PfV2/19leRzLFJrbCNpnSc4p0KdtDtm7crKqud6jYOcea5voIOsRFlVIp622ntpJ/zmxzS3HH/Pff7vpbZWIQEREREdGlKZABumeKu3nfXinSLyvSxPWhoQENzqHvz7fJP2e2yzNNX5Dz6edk7JavXLct7PubW+CNy6jkbhxB/277BPXPCFXcZ+yaJoeTDrmPoGf6n4N+oUxxzHR3/W5GITjMSf9BtHWxnxLpHiXyJzKkMZirFXoXSdB+nA0XufW+rNdeVWTe99PEdtPNkjZQK1Sns+zTUu8dsbHiLFpMqwjvhTMquzCZvU5dCZQtpzarkW3QR7fzQ+9kqVSosuw+t8ut4r6ucFgRtf3h/vl3e30cdOQY1d1a1y04h9TIVGk7/FaZWWWG7D26V37eM0td3ySumcRGxOaoyI5Rdk/lYsq5AvSY0BjX9QzOiYiIiIguj4IZoNvdi8RZ/tnufgfPkd0AQHCuj5AmpJx0u23rqS1qVN1tLeyM86455r6givvBC1oBNx3mLxuru3tzvnghtwAd65Sbz2jBZeY6kWM2kfJWkXew3PnzIqJPP9YGw+Vkdka6HM2K66wr/soRoIfs0VLv7VWzlk0zey+RkNG5qyQ/84LYbm4b0I6Ubae2XNLfn07NCtALZwXoXkbQy0SVcQXo3lQ4UEGarGsiy9ssF6vNKjarTfr8mLOo27hXx8kzg/8ji1cvVttF76RBUTedsSK7XmTQ6N8tXlFLwVUpUk2qFL52154nIiIiIgpWgY9Eg2AE3ZSk/e42gh4gGM0euuB+1+87zvzj9X6eKe7GAnG+IIDXR96LhhVVheYueBlBj7BEuAX7iVGWHOuUm85oafXpISKDT4o8XFikD+K7+tp9nBfCxXQ4zTWHXZec1bTOiEgpdP9ASes/UCxbN4s54aQ4YjFSL5JZNZfgz2qVlBf+I5fb/zaNkUnbv8U7lAfrD5NBdR9Q129J2CSvrXhFrfMdZY2SUbd+pVLDjZ0kF0NPca9YqJKrs2TDiXXy1qo35LUb35R6xeu75np7U6VQVekyt7OUTCgpDTd7r4rvMDlkRt8ZYs1KSS8Wlj1K7rn2unEk3DjPXVe/eAMZ2W5Uvt8nERERERHlTYEM0LFGNzgsRdzW3XaxZC8ddbX9tGemzDesje1Nuj09R4q7Mb3dU7Ui1VVhOCyzps9Xx6jt2ZNn1ait5zJrpaJKq7nOusTwkBzF9EKOHFGX0ywii1O0fxMKi9yfNf/cudEqJskK0A39Haj0DhHfjlM/w36d47rN1ghD8CKOilrACplVqoplb7ykPjhMIsb9T1LvvleulA/XvOuqjv/2qtdVcTRUJu8xq5NbhwWuv6nszW4BOi4jaL/YFHe9HkDP2V3U9u035w7Z/kC8W8V2PQ1dFYZzmKTtL21VcO7N/M7zZWu9rZIUo9UOqBCitWmxrHR247Y2QmcB1krvVLFLvt4LERERERFdugIZoJv0AD1UG7E1nzgRsBF0pBJnOmyqwnqx2ChxOHPO/fUW2OmBNuDy5oRNOe73c68FUjGmoipA1nRSfclwZLgCbwRiG06uV6O2hxKz56R7DdC9DOKGHNwv58NEzkZkX/fcKZE714lEFhMxT8vOSvA2gu6NZauWMq6PpKv3uvQvST62T5zlykvhwcPEXqWqXC5YXxwBeVxUSTmVcsoVnEdbY1QQvObEamlZulWOqQN60GzPWt4OkIUQac1eciw3uL++3B06S3QIzuFUaoLXkewGsY0kY3qadFrUyXXd5vqbpdL+SlIosZCU71BRqvStJjPtsyUpIbuwn9VsyTHP3FuA/vtdK9VzVyiERe6JiIiIiOhqKpgBelYBLKdVC1b06u1Xew46CrvVnVDVFYQNuWGI1C/aOE8BujHFHcH0GyteyXG/JiWbijXEKim27CBv22ktCK5UqIr6ue7EGvXPqLRH0JZozZnKjXnlVYeLFDKs0HbKKhJdTeSVVeHyxrnsUXnPEXS0vreZ4/oyd1hiTWcPD5Oai9qqzoUjD50Wq6/K7hfhvnkDZPHBhfLXgDUiqRnqurLR5aRl6Rvlx93TZfH+BSpA98U4go4shPwE6APm9pGjyVoWQlxkKVU13VstgJR0rTOg6JmiUuxMMWm1vJWELc3O8FjdbLXM6zpPQuwhsnPIAYmJ0ib5l51XTjYnbHTdL9SsbYSiHinucYYUd8B7qGBlcE5EREREFAgFMkB3pbebtUDHfPx4QEbQMVpqHCEdu2GsjLjp7Vz/7nTaaTmZ4j7q7w2Cc30pLKREm5wmcZgdKjp2jdo6RYqeLSo1dtVQKdGZlkyJi3QP0BPMOYvPrSwnkhSm/fM0okWavD4vOwg3jqA7zCLpFpHw7CXnc3AWy07DRto3gnM4nnJMysfoFeguHYJzQIX8m6vcqC5XLVJdGpRopAL0w0kHvRZL0yucZxjWj8+tEr4R7vvX0T9cvyPtPCa0kKSlZj9G4XOFZcWbf8iwr4dJRKohTcHAUdYpizouEqfZKRarxRWcg2e6vWsOei4p7kREREREFDgFN0APzQ5UzCeOBWQOepItOwVZh5Tz3GD0/LifOeeeEKz1mtVLGmxpoH6PrxIvRYsUkf5T+qvA3OzUgrmu87vKmaJnpNhNcRKREqGqgl8ofEFOOLXXZDOLfNFcpNtube65P5vjRMpfEBnTVOR4dnFw1yi6vwDdgSXWsqRnBeeQmOFezM+X77dPlNLRZaR9hQ7q92+2jpP483tkUJ0HpHrRGjnufyzpqOw6vUtdrlqkqisNfE78TxITqlX6N9InIRgzEz5a+768dtObqpDckcTDMmvPjzK43lC3UfUfd02XTEemLD/8m9vjFQ0vJoXDCsv5c+ek4aaGYnaYpcPiDrIhc41ESHZwfrLESakaV03G1R4rO2rtkOebvyS2dTZ1W5gle91yrwF6VmeUZ4p78Qh9TTwiIiIiIgq0AhugO61Z85ydTjFnFTxz3RZ6lQJ0LwFnXgJ0jKDrS69VLVJN4s/tcd12Q8nGam55tMRI/JxdsmXcRjFbQ1zBufqbvVVl31O7pZbUyvHYxc4Wk5hfo2TYlGESlRwl0+6aJrX/qS3zJV0W1r4gIzuvkvH1wuThTYbcdi+WVhb5vZLITzmfQs1Dj/WzIpzTkOKeZpj/bUzr92XnmR3yr98ed61NvvfcHnl++b/U70eTjsi4zhNz/M2x5GNS+Jw2+ly5cBVXEIu5+99u04rZeUttN2Y/TNw+Xnaf2yk/3TFPHl78oKw6tkI2J2yQ/3X6RnstKSflkcVDvL7mKEuUFJWi0mH8rVLqRCnX9WGx4ZJ8TuvEWdhpoaxusVp2DN4nz4x/Wl3XqLRWVA8sJo9Cfh6TCEKzRtAxv95itqiOAoye4zIREREREQWHAnt2rheIM508KWaPZdawjFegRtDPp+dcC9vT7rM7VYEyjJJWiKnoCtA/bTdausf1lKnPfyeWNWZZcGxujr9d0XKFSmlvcLSBZKTa5MSgE7LlwGbpsEQbbYbEMedUwAj3TtKqpq9C2vU2kde2dVW/JxSJl4iUGZIa6T3S3lHce3BurOSelxF0Y+q4sXK9L3pxNb0DxPg3xtsw/1+HwL1C0XKuABYj2v7oqe2eFdZXHP1L/URwDrP3zHQF6Ile1jgvElZEJnefoZY3q/l3Tbfg/GD5g/Lk0uel4fe1xJJpkam9Z6rOimLhsbKs39+y5dQmaVc+e5uFeATaZo/14a1Zc9DxXD/2nKNG8VmpnYiIiIgouBTYAN26ZKVIzVSx7N3j5cYrNwcdAWevn7pLo5I3yO3V+uS4HXOuYWj9h+XrLV96fQy9qniJiJISFhIuVeKrqLToBtEN5Md3J0vmqXRBBnl4bIRYI62SeOiCXIi5oEbDj5TTsgU+GjRKMpIzxFo8VMp9VVzNcy53uJyao155f3ZVcbCb7RJpPi/pmYbA9VxVuWP2HeoxSySUkBNxJ9wqv+1yn+rsxlsldxSGM585I46oaEky2+SOHzpK67JtpHf1vq77GCvXu/7O6ZA759whZaLKyOe3fqlGhnVYG95YgT0pI0keXjRYVh9b5VbgLSH1pCtdHSPNnvO0PemV1r2tFd5lRju33w8nHlIBu7fR8zbl2knTUs3FlmKTivO1ufVL2i+RjNAM2VJ/iwyTJ9R1YRHh0qbcLa6/q1u8nvpnZDFZ/I+gZ6W4Q6syN6l/REREREQUXApsgG7ef1rCFs4T04WcKeVO65Vrll/2/uyqnN6hQvZSWbpTqafUzzLR2oiuP0hRvvfwfbL7u+3q99+/X+y6rWrPGnLz2+0ksmSUZKbaZPifj8qR3VpwfnvV3mKNDlX/dIs6LVI/UUxu8Q3L5Y21r0ij0Q3FXsgu4+4aJ08cipGFKWWk5cqWklz0hFTeVVdq7qopr454Vf3d7Ntny8YbsquG74xDynX2MmS5jaBn1msoocuXiTM2Vhbs+1VVIMe/rpV7+E1x33HmH/kja073h7d8qtZ116GonDFFHgH+zN05l6ODE8la0T1UUy/mUencZ4DupYDc+pPr3H7H+vMIzosnFJeSJ0tK5X2V5UDFA3I69rT0utBLflu0WA4u2SfWC1Y5W+Ss/HXTX+II0ToPzqedUz8jLblXh/dMVR/e+Bk1D16H+epERERERBTcCmyALhcQiIdK5Pivr/gIOtKpN5xcpwqUYb6zv5RtFBiDMtFlctz2Vcfx8tCiwVL2cFlJjEmU0uVKy7Ex2WuYl2tTQZKPJ0mp5mWk3cfZwb8lwiqjOnwlH9zyifo9whLh+7WanVKxaSWZ2mqWpD+aLo8uGiqp+1NlY8c2svHgAhWEl0gWuW1RglTYmJ1i3WpFKzUKf7jcYTlU4ZAci/QenMOyyiJtDrgvtWavVk1k+TKV3o40bN3BC/vd5t57MhZDO5F8XC6kX3D7XS+OBscNbe/pRNIJV7G1QmE5C8MZpWemyYX08/LX0T/93i80PVTOxp+Rbr90k+Zrmruub7a2mfp5QLLXmoflbZa7gnP4M6vSe16Wbwsxu89Bxwj73qFH1fz25MxkVbyOiIiIiIiCW8EN0M+LhE+fIpZt2rrg9tJlJOTYUXXZeZnnoP+yd44MXnCP1I2t75aqjPRnT4eTtOtKR+UM0EtGxkndvXXlzol3qqW+kMacJIkSGRcl96x5UCzhvjcnAtkoa1SeXm90aIy6f6Q5UkpFa/OiN53KHnlOChXZ2uRv2R8TKk3WNZGolCiJOxknnRd2lgxrhvz4+I9yynZKpWonFspZCO/1W0RuOCZy+87s6zKra9XVMYKOVHTdttNb/Y6gI1jWnUg5LueNI+jJxyXWkK6Oefu+JKRo89PDQsJyVED3lGZPl7vm9va71J3FZpFHxjwix84dlOaSHZx7U/6WirK3zV7ZYNrgdv2IFa/meQS9ZrHaOa7Tg3IG50RERERE14aCG6CfEwk5ucP1a9qAeyTq4/e1Xy5zgD5952T1c9vpLVI+przr+kOJB33+TZFwrUibEeZHt1jVIscc47r3NfAbnOdm5u1zZeK28aqQWN3i9d0C1MZxTWX81q9V8KtLtYocLxUhB8svlaW3LpXB4wZLhUPaHOpQW6gMGDlAXU4LS5MJD0yQ9LB0OVf0nHrN+hri0+u6B+jpt/cR68oVknbPfXI2bb3r+m2ntA4UXwG6cY45AnLPFPe8dkroEKDnJt2epqYo6EodKyWnip+SiMhIKbu5jHq/yCYoei7nNkSbrGqxSu4ZfL+0a9RBokpFi8lsknFbvhLJXhrdzf4L+3y+lp/vmC/jtvxP3mz9bl7fIhERERERBamCG6CfFTHbtDm+yU8/L44KFV035XcEHQEsinQNqvuAK2h8/e+XpXOlbtKuwq1uI7eYk6w7kHjA52MWCi2kfoanhsudP9yp5i2fOH1UKuzUAuHJAybL3SsGSnhiuNS9N3sJtYuBYmz4502Hip1UwG4sqgYHrdnzr6f2nyq3WNvJFwO+lgUPzpXjq7VMhPD0cHnky0fU5fmd58uudrtcaf2TG2iB/pMrRXbHiuzeN1ae/VqreH76L20+PPx+eJnr8rJDS+TZ356SmNAYKRdTTh6s/5BbobYTycdU6rnx9zJRZS97gK5XcYeaO2rKgKkD5ECFA+KME6m0Jns/Alw/vd90sVltYnKaVBE+W6hN/tXoBYkuoy3tBoW8rLfurRPCU8syN6p/RERERER07SvQAbrJrgXozshIsZfXAl9wlMqZXu7L+fRz8u/lz6jLCMbLx1RQa2cjaMc/rMVtDG6Nae2HLuQeoDde31itW45/B5dpI6mb62+WXTV3SeywOOlTtd8ljZ7nBst6NS7ZVNaeWO3zPilRKXIyLkGi4qKl15y7ZPTCz+STdR/KoImDJPaMlmLeeUFnOVzrsFyIviB1t9WVwucLy+yb/5DTEU5ZXklE1rwtd1TrI9WKVve53jkqtGO9cd29dR5wW4btRMoJt3Xkkbae6qXSuj+oig+NSzbJUfBNZ99ql4GTBqo6AI03NFbXVTxYUSQrISIzJFMsdos4TA6Z22OuJEfnLCYXFeqedu5v3nv3Kj3z9R6IiIiIiOjaVDADdAyApiFN3Kb9Hh4uttZt5PzkH8SUnCzJHTrmuWGM65YvOrBAHqg7RPadzy7+heDcOIKeZk/LU4p7pDVKVvXYIFNHTXS7PrV4mizovEBdjo2OvaLBua52bF2vAXqoOVQyHBlulc1R4K1qjepyPv68fHfvd6rqOwLymKQYuX/U/Spw1cWejpVK+yvKkZ5zJL5avCs93VeA7inZluQWgB/3GEHHOvPe1pr3J9yijaBP6fGjtJ/eWo4kaUX79HnlyGYotquwFJOcAbW9sF3W1Fojy9otk5vSWss6WSvni3hf195zXrjeIeOpb4275K3W7+XrPRARERER0bXJfzWs65U2cO7ijIhEZCkZHTrL66W2Sc0ptSXekIruT7Jhqa1F++erdbYnbB3ruu5o0hFxOLV51558FS2LskardOjV9/0thU9lB4JVHqguOz/Z5RqRLRrufzmwy6Vakeper4+L0grI6fOyPe+Peefzu86Xn27/Sf1uDM6h4eaGUvhCEen5c0/B1PST8SfEkelwpcGjqJ4/CL6N6d9Hk4+6jaBvStggozZolevzKjQrxR1t27Vyd9f17Za2k5ffelktLecJhfEmDZwkpklW9X7Tw9OlcNMiPoNziLZmp7f7S3F/qMGjV207ExERERFRYBXMEfQcAXr2smMfr/tA/Xxz5esyocukXB8qyZbolr6+82x24Tl9zrnDT/VwI4zQorhYZKko2fXjP3J6m1ZZ/FTsKTWPeelzf8vitUvc0s+vhmpFqnm9Pi6ylCsLQB9Bh8qFq8jN5W4Rq9kiSw8ulviq8bKx4UZptKmRSvve3GCz1P6ntoRlaMFw4QuF5ZURr8hex05Z0lvkzM3acmqVCldWhfV8QbV34zrn60+slTJeqt9fTIo7hJsjpPP8zpIWniZtl7d1u9+ox0bJ+cLnpcHmBmpN8/2V90vhmCKu26v66NTQRXukuFcoVMFtHvytFTrJ6bRTKnuBiIiIiIgKhgIZoJ9PFfmruki3rEFyZ3jOdcHtjkw1v3zJwUWq2JuvauDGJcGM6eu6+HN71NzpvOg/tb9U2VtFzpY9K0sOz9cev2OyjGkxRuwWu4Rbw1wp2FDsKo2sVjUE6MaCcaWiSruuNwboWJP7x54/q8slRxdSa6vP6T1HRk4aLd8d/kZmr5ot87vMl4oHKkrDTQ2lzj91JMShreO9e+ZOKXe2rJxqlCAVC2Fyuv/OkRRDgI6U993ndl3Sew03FImLiA+XVitb5bjP+AfGy6kSp9Qa64V6FZF1h7S56jaHzRBwV8zlebI7AiDGkOKOtvym6/eX9D6IiIiIiOjaUyBT3L+uKNJ9oMjmOO13Z6SXAN1pl8cWD5OHFz0oL/7xrM/HMs5xzrBr87GN9p2Pl8SMnGuBeyp2uphUi68mZqdZYg9rI+NlW5eXCwOTVHCup18bg31/lb8vpwqGQLlcdPYycaWiSql0fEAhudzWVkcRuagI7f5pEWmys9ZOlRnw6fBPZczDYySjuxbgtl/WXh774jGpnFRZrBlWKXI2e2Tas3Mkv0XgvClxsoTc9819UiW+ioRZtMD5zM7TEvmiexCtV6M/WOGgax55piE7olx0Oa8BtzeYq+9pYO1B6mfhMO/vl4iIiIiIrm8FcgR9V9ZA54HCIg1OYKg00muAjvRsmLrje/ms/Rivj4VRW51xyS/dMRQuM6zN7UujjY1clzPDM6VqmxrS9duesvrvNW7roGc67H6DvCvBYrbI152+UUXYVh5bIQezlodDivuivr/L9/9MlMdueNLvY+hF0SItHm1tEjlb7Ky6uKbpWgk5ZZKWq1qq9PeMZ1Pl6XNPS1h6mHxz/zdS4WAF2VZ3m6REpkiIPUTOnzjnquKOee/6EnZ4Dm/bwpd7Jt2j0uxLHS8loR+Gyvl95+SnXtPFlD0grszsNVM2N9zs+j3CEqkyLXQdK3aRF5r/RxqVuEEs5vwt1QdvtX5fioQVlduq3p7vvyUiIiIiomtfgQzQ92QNdEdlBWDO8JwjpXZDIOxPkmF0HCnxnlRlcUPhMiOz3SyhGaEyePxgKZlQUl03rd80qdC5kjzR4zkVgBuDcKSX2515S5e/3G6v1lv93Hpqi1uROCyL9t8bR+T693qAro+4e7Po8AKRriJpPTOky8edJe14qkSIlt0weMJg9bPDkg6u+x/94IAUKRsttVrXkvYDOsmejVqAXju2jqw7sdbtsTGvG6njaHMU4EO719hVQ11GcA4RaRGycOgvcnDpfrElaTuJzWKTT5/8VM1Dz7S6t32mM9MtowHb6pmmL6jL605kd6zkVaQ1Mk9tSURERERE16cCGaDvzgrM00MMVdw9GNcu9ye3ZbyOJR2VRC8BepO1TaTbr93UaDCWIIPjccdlR60dUju8riswN2GI2eCuWgPViHWTOP8p5VdK9aI1XJfrFW+Q6/1vr9pbfoqfKU83fd4VhOameaOW0v+3QfLH6GWybvJqKXLed8q39YhV+k/rL3a7U4YVe1hWJvwtT/Z6Rt7dNkJ6zO2hAnEUqdvTe4/c8O0NUuaY/yJy8T9rc9hLNIoT20sOeWH906oquzc2e4YMa/CIrD6+UjpU6OS3SrtRndh6ubQAEREREREVRAUyQD+fFXunWXJWcTeOjuaFsUic0cK+v0mnGbfI4aRDOW4rHlZCOi/orAqj6cG5tVyoTO81XRVUizIGdx5p7C1Lt5IVd6+TMob5zlfTY42elJalb5IiYUWkRrGcS455Gt3ha3mu2YuuwD5HirsX5WLKS2RclDR7sZU8UGyQDP9suAq01zdeL0XPFpVySeUkPjZe6r7YUFLeT5TC6wtJyAyTlJFS0lt6y95ZO6Wf9HM9HpZGq/mu79e6p+oeWXLrEmm9sbUM7viQxDUuJWValZM5+2dL+nbvwTmk2zOkZ7Ve8lds3RwF7TzXOTcum/Zii1dzbQMiIiIiIip4CmSArnMF6F6ruOcxxd2wzJqxQJiv5bFMDpPUO1JfQm2hruuK1CwqN0xvLv+Z9ZLf4C6vS3hdSajQ3rx0izzf3xpidQvkI31UwzfSq8PHWAuptPIvHvtC/a6PZA+t/7DM3jJbKkZWlX0D90rt7TUlwhkh5VtVlOQTSXLmH22ZNk92s132Vd4nNTJqSGzR4hJdJkZMxULk3fLvqqJ1f1T/U764b5zr/uGWnPuFkc2RkSOrIPt9RvocPc9LFgERERERERU8DNDBRxX3i01xx3xn/POENbWbrGviCs5XN1utlhs78thpSUhFtbqca2R7prhf6/Iygo7ic3pwD54p5nr7oHPkXOHz8vkTn8t7t34stzXuI+kX0mXB4Dmy+MRC1bZOk1OGjB0ihe1FxPpEuByscUTe6Pq+qxMEHTFpX2qF5lJs7oXlvG1DI+Oyap6KhheTu2reLbvO7nBV4A81h0qv6n1zff9ERERERFQwFegA/UghkXdbi3S3n5Pfd8yVEpElXLehOrdxze8zaadl0vaJ0qPKbVLFsC64txT3CI+RV1RBH5w2VMqszFrXDUFnaLosb7NcHCEONSpdKCx7yTQ873UboPsYQdeLuOnLt/mjTwFA26dlpkpKVIpEFdYC7rBCYdJzRl8ZMlorKgcfP/2xqjbfoFQjGSqPuj0W2l6XkpnsdltuI+i5+fzWLy/p74mIiIiIqGAp0AH6K+21ny9Ozlm0y+50uAXoL/3xvMzc/YN8vPY92T/seK4j6FA3tr5sO71Fnir2tIS/nT0am9Y8XSbV/06SYpK8jiwbC9TdULKxXE98pXfHhMZIeqoWoGOpMW9p76iIX7VINcMIOtZBT816XN/BNOb1F4vS1pb3x1iRHcyS3VHiTdfKPXJ9TCIiIiIiorwq0AG6PxiZNQZs8/bNVT8919dO9jIHXR95Hddmoiz770JJn60FkTDyqZEy+NahcnjdYbe/MS6nZgzQsbxZsi1ZbohrItdzijuWXzuVeipHWyzr97dsStigirFN2zFZulXuIX8c+d21xF1q1vYID/EdoI/vPEkVnrtcvu06RY4mHZbe1e+8bI9JRERERETEAN2Hcx5rmusjtZ4QPHsKDwkXh90hWx5fL+l/ZP/d9trb5XyR8xJp8V8ozWGY/45gdWCdQXK9MKbvexbW86Zu8XrqHzxYf5jbEmbGEXTPaQVGPar2lMulU8Uu0rVy98v2eERERERERDr/ObwBcOLECRk+fLg0b95cbr75ZnnnnXckPV1LfT569KgMHTpUGjZsKB07dpRff/31op+n1LFSUnF/RVVV3Ztz6Wd9/q0+wu10OlXatS7ueJzU21JPip4pKsueWihH/jgklkir3PZDH+m4uLvM7D1T3c9i1oqfeepVq5f6eXft6ycg96ZRiRtUwbTXb3xb/f5pu9HyXpuPVPD+xA3/yvXvy8VoS8ytO7FGjiRpmQilo93XN/+w7afq52ftx1z066xXvL4K/KsUrir31nlAXfevps9d9OMRERERERFdMyPoCHgRnBcqVEi+//57OX/+vLz00ktiNpvlmWeekYceekjKlSsns2bNktWrV8vzzz8v1apVkxo1ci5z5c/jqQMlZGxxsdgtsqbpGvmlxy/5qtB9OvW0FI8oLssOLXGNtN94+CbpOLaDVtTtR5Gdsl1d3+bd9lK+bUX13jL/1FLmE1JPen3cGf1myMFjx93XQb8O/dpniSoIF2WNknvqDHKNnu9+8KBrdNyfesUbSMnIODmZcsL1u740m25Q3QekV/U+PkfmfRWo85wvv2PwfrGYLKrQ3+s3vinRodf3tiEiIiIiosAJqhH0vXv3ysaNG9WoefXq1aVp06YqYJ87d678/vvvcuzYMfnggw+kSpUq0r9/f2nTpo1s2LAh388T82kFFZxD4/WNJSpJSzmPTI6Uynsri9ludktX93Q85Zj8sneO9J/bW/1eLrq81F9VL0fF9doD60nNu+rkmFeNwNQbjCAXhAAQwa7eBsYAGpeN7eQL2gmp5rpOlbIvG+UlOIcGJRr6vA0j6FjuDa+rIGwbIiIiIiIKnKAaQS9RooSMHTtWihcv7nZ9UlKSGjFv1aqVREdnrxE+evToi3siZ/bFEEeIDPvfMDlb9KxUOlBJXbe03VJZ3na5uly9aE05knRIzqSdcf3NsbNHZMk786XT6U5S8UBFiTsbJ5ZUrSmPlTomRaxF5eFfhktUqezXCt91myYzd02XYQ0ekQ/WvHNxr52URxsNV+ntCPYfqDvkkh7rq47j5e11r8ng2g9dttdHRERERESUXyYncq+DlMPhkLvvvluKFi2qRjDLli0rYWFh8tNPP6nrMLreoUOHfD/ue4PfkN+3rZQDFQ9I3xl9xezMmUiws8ZOOVjhoDjvMMk5x1lx/GWX07Gnpci5IjJwzj0iiTmb7Vzhc/LJU5+oom6ftB/l9zWU+CJ7dDfhsQuCgePY2Bg5fTpRgneLXJ/Y9oHDtg8ctn3gsO0Dh20fWGz/wGHbBw7b/vpoe1PWYxW4EXRPSGffvn27zJgxQ95++20197xbt27y5ZdfyqpVq1SAPm3aNKlfv36+Hjd2SDGZt2ieuvx56c9ldOxoWT9qvSSaE6XUiVLq+pq7aqp/9pV2SS6TLIV2GdOls7fwwfIHpVJaJUkOSZZZXWYJstyLRheS4sX9b8DetXvLzH9mymPNHnO779Xa8JQT2z5w2PaBw7YPHLZ94LDtA4vtHzhs+8Bh2wdO7DXW9pZgDs6//fZbGTlypCoCFxISIkWKFJHXXntNFY2rW7eurF27VqZPn57vAD1TsueVny12VuLuLC8ryoyRPw8vlwfHPSjlD5eXpKgkiU6OlpCkEI/gXCSjWIbE375Xfio5W7o3uE2GdXhCHlwwSA7sPZD1BCFy6lTO9dGNPr75C+lT5S5pU66dui971wKHbR84bPvAYdsHDts+cNj2gcX2Dxy2feCw7QPHxBH0y2fEiBEyZcoUFaR37txZXVeyZEmV5o7gXFe5cmXZuXNnvh8/NCTM7fdIS6T6h9Hv2XfMlkr7K8nGRhvltfg3xD7FJunNbTKr8o/ScFNDOVzusFzokSROi1PSTqVJ3xp3idkUoiqBGx8/t50Aa6F3rNhVXTbeF5f54Q0Mtn3gsO0Dh20fOGz7wGHbBxbbP3DY9oHDtg8c5zXW9kEXoI8aNUqmTp0qH3/8sXTpkl2dG2ufjxkzRux2uxpNh/j4eDUvPb+wBrdRpDVKLakFp4ufVv9qF6sjAx9+QJzPOeSro6Nlx9odsqP2Du3+SZFSJKyoulw0vJj6GWao9h4REnFR752IiIiIiIgKrqBaZg0BNyqzDx06VJo0aSIJCQmufz169FBF415//XU5cOCAWif9jz/+kH79+uX7eYyj3dkj6NlLnzUr1UJ+u2uFRIdGS0y5QhKRFbxDiClEUjJT5GjyEbcA3TgqH2Zxf3wiIiIiIiKia2oEfcmSJWqEHCPl+GeEVPYJEyaoOegI1suUKaPmp2Muen4ZR7s9R9C128Pc1uOuXrS663KVwlVl97ldrt9jw2PVz3BDgG4M9omIiIiIiIiuuQB92LBh6p8v1apVk0mTJl3y84SGhLqlu2MtbWNQbTVb3e7fsWIXeb7ZS1K/REMJDwmXO+fc7rotJlQrIOdwOlzXNS3V/JJfIxERERERERUsQRWgXy3GFHd95NxzBN0Io+nPNvu36/eulXvIvH1zXbfB+pNrXbdj/joRERERERHRNTsH/WoxzhHXR86NAbrVMMLuzTNNn1c/b63Q0XXdA/WGqp931bzbLT2eiIiIiIiIKC8K5Ah6qDnnCHqUNdpnirunBiUaybp7t0qRsCKu6+6s0V/qxNaTGkVrXpHXTERERERERNe3AhmgYx65sUCc+ol10H2kuHtTPqaC2+8YNa9XvP5lfZ1ERERERERUcBTIFPe4qDjpXqWnlI4qIwNrD1LX1ShWy3W7seAbERERERER0dVQIEfQMdo9oYt7Nfh6sdmj36uPrwzAqyIiIiIiIqKCrECOoPsK2jG3HFqXbRPol0NEREREREQFTIEcQfdl+m2zZPrOKXJnjQGBfilERERERERUwDBANygWHisPN3w80C+DiIiIiIiICiCmuBMREREREREFAQboREREREREREGAAToRERERERFREGCATkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURBggE5EREREREQUBBigExEREREREQUBBuhEREREREREQYABOhEREREREVEQYIBOREREREREFAQYoBMREREREREFAQboREREREREREGAAToRERERERFREGCATkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURBggE5EREREREQUBBigExEREREREQUBBuhEREREREREQYABOhEREREREVEQYIBOREREREREFAQYoBMREREREREFAQboREREREREREGAAToRERERERFREGCATkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURAIugD9xIkTMnz4cGnevLncfPPN8s4770h6errbfRITE9VtM2fODNjrJCIiIiIiIrqcLBJEnE6nCs4LFSok33//vZw/f15eeuklMZvN8sILL7ju98EHH8jJkycD+lqJiIiIiIiIrtsR9L1798rGjRvVqHn16tWladOmKmCfO3eu6z5r166VlStXSokSJQL6WomIiIiIiIiu2wAdQffYsWOlePHibtcnJSWpnxkZGfLKK6/Iq6++KqGhoQF6lURERERERETXeYCO1HbMLdc5HA6ZNGmStGzZUv3+5ZdfSp06daR169YBfJVERERERERE1/kcdE+Ya759+3aZMWOG7NmzR6ZOnSo///zzJT+uySRBR39Nwfjarnds+8Bh2wcO2z5w2PaBw7YPLLZ/4LDtA4dtf320vekqbj9LMAfn3377rYwcOVLNRx8wYICaj+6Z/n4xYmNjJFgF82u73rHtA4dtHzhs+8Bh2wcO2z6w2P6Bw7YPHLZ94MReY21vcqJ0epAZMWKETJkyRQXp3bt3lyNHjkj79u0lMjLSdZ/U1FSxWq3SokULNW89P06fTpRge9folcHOE4yv7XrHtg8ctn3gsO0Dh20fOGz7wGL7Bw7bPnDY9tdH25uyHqtAjqCPGjVKpbJ//PHH0qVLF3VdXFycLFy40O1+9957r/rXs2fPfD8HNlCwfkAu9rWdOGGSkiWdVz19JjNTZNMmszRu7Mj3cx86ZJIvvgiVJ57IkLJlA79Bgnm/uN6x7QOHbR84bPvAYdsHFts/cNj2gcO2DxznNdb2QRWgx8fHy+jRo2XYsGHSpEkTSUhIcN1WsWJFt/taLBaJjY1VwXtB99prYTJ6dKiMGJEmDz1ku6rP/dhj4TJrllU++CBNkpNFGjZ0yE032SU9XSQkBNsp59/gA2KzaX+7cqVFNmwIkQULUuTsWZEiRThHh4iIiIiICqagCtCXLFkidrtdxowZo/4Z7dy5M2CvK5itWBGignN49dUw6dfPJkWLXtnn/PVXiyxdGiIZGSYVnMNzz4WrnxERTpk1K0UGD45QQfgbb6SL2SzStWumhGt3kb59I+Svv0LE4dAicQToJUtqKSM335wp48alSuHCWqCOzACMtDdt6pBghE6Fl14Kl4EDbdK6tT3QL4eIiIiIiK5hQTkH/Uo7dSr45oAgGC1ePCbfr+2TT0Ll7bfDXL8//3y6PPtsxmV9bQ6HyDvvhMrJk2apVs0hI0ZkP19etWmTKVOnpsrRowi2o3O9f40adpkyJVX69YuU+Hiz/PBDitjtIjfeaJewMJHffguRTZtCVPCO91u6tHujzZ5tkaeeCpfPPkuTnj0zc32+AwdipEyZRLFq/Q2ya5dZZs3SRvfLl3fIBx+kq+3iObr/+uthKk0fjh9PVJ0R3syYYVGv95VX0iVUuztdwn5Pl45tHzhs+8Bh2wcW2z9w2PaBw7a/PtrelPVYBW4EnfLvn3+0iLBePbts3Roi48ZZ5dFHM8RQT88npKH/+KNFTp0yy9q1ZundO1MqVXJIo0YO+eUXixw+bFIj3wh0//wz565Su7Zd/vWvDBWkHjmivY6wMKekp5ukenW7ui4lRYtoly+3yPz5Fpk0yeoWhL/0UoYkJor88INVjbgnJJhkz54Q2bUrRJo0yQ7k77zT9xtavz5E5s1LcY3Q4wM4bFiEujxkSIQ88US6em9ffhmqRrpbtnQf6Z461SLDh+NvwuTNN9PVdXfdFeF6T3Dhgkm9/gYN7CrAPnvWJG+/nS5bt2bfBwF9nz6ZrtfwxhthcvKkSSIjnfLtt6Gu+4wblyYtWtgv+0j+vHkW9bhVq2pHIGQp1KjhkBIl3I9IaO85cyxSs6ZDmjTJe2bCokUh8t13Vrn/fpu0b395Xz9e044d5qDNlCAiIiIiuho4gh5AZ86IFCuW3SuTlhYj69alqFHi3IKxmBhtfnfbtpHyzz8h8u23qfLKK2Fy8KBZoqKcMnt2igrOELDXr++QmBinrFsXokbAa9XSgrbbbotU1xlZrQgmU+Xuu30HxE2b2mXu3BTXaDECwZUrQ1THAAJZBMzt22fK7t1mefnlMDl1yqQCbqPnnkuX557L8Dpav3p1iDz0ULgcO+ZjONqL4sUd6n2ePm1Sc+DHjPE9TD15stbGeidGpUrRro6Eo0cT5fhxkzRunPsovzdov3bt7NKrl00eeUTrJPBUpoxD1q1LVnP0jdLS0GFiVR0XeO/odKlSxf+OOnmyRd58M0zOnDGpKQNVqjjkt9+S5eefLfL44xHSqJFdTRlAZww6OcqWdcjq1RbXdARsR7Sb3lHx8cdhqgMDNQWQqaC7cEGkefMoOXNG2yarVydJpUpOFVgnJpqkTBnnJfVG9u5tU9MlRo5Mk2LFnNKkiV0VPbycxQzfey9UZVoMHnx16jTs22eSb74JVZ+LuLggOOB4YI9+4LDtA4dtH1hs/8Bh23uHtkANpeiLO+3LE7Z94Jiu0RF0BugB8tFHofLee2EyahTSuLVR13btYmTbNpGJE1OkSxe7KxjHKHCXLpkydKhNli8PkbvvjpC2be0yfnyqVK4cLZmZCIqT1Ajqf/6jDSPHxjpUAHrokFlCQpwqmLbZLq76WnS0U378MUWqV3fI33+HSPPmdlXMLa8QvPfsGekWxK5alSzlyjn9dl5MnmxVz7VokUUF3nv3muXvv7Xg8vHH0+WVVzLk889DVYDqqyNh7VqPKDhL3bp2+fTTNPWeqlbV2hAwhx/z65FVkB8IyPX5+HmBTIOlS7U2BeyPjz4argJ0o3btMiUpyaTabMSIdFcwrf9Ns2ZRqlMmN8h2QEeOpwoVHLJoUbLs22dWHTb6PjJhQqp0747nFjl3ziRPPhkuf/yRnUXx4YdpcuedNmnXLkptl7vvzpBPPklXNQOwfyLAfv99LRsht4NdeHiM6nAyQiYHOhrykgniCR1Cf/yBfS5TdYKgswKfIR3eLzqpMHUCnQGrVqFIoUVefDFdypd3XlIngF4UER0iN94YpT5/3bvbZMKENLlc9u41SaFC+JJwXvYvrZQUrb30TsIKFQrc18NVwZO1wGHbBxbbP3DY9jnp51743vvpp5QrlsXHtg8cEwP0a8eV+IBg5Bcn+qVLO9TIojHQRDo0Tvw3bjSrecgY4b3llih1u8XilAYNHOo+CJKgcmWHrFiRrF7jf/8bJv/7nzYa/M03qfLssxiRNrsKqiFoKlTIKbt3J0lqqhbML16c95kLGN274Qa7DB3qfbS3VCmHCsY6dbJfUts8+GC4/PKLVRo2tMvChSkXVakdI8xIg0aleP3v0b433RSl2g9p17j98GGzhIc7ZfXqZPXcbdtGqRHgu+7CPHhrjgDVW4CLjAO0TZEiTnnxxazceZGstspQI+5TpljlyBEEpDb5978z5OBBk+okGTkyVI00o4OgZctMNWUAgWKrVpkq7X3y5OzRfQRv48enqSyE3r1zj0ZvvTVTZUGgwwXF+g4c0F47MiYw7x4jtv7UrGmX5GSTfPJJmjz9dLh6782a2VVtAGNK/5AhGSqF//bbI2TFCourUwGBNzpJbropU7UNtqkOATXe39Kl2v3/979U9djYj42dMevWmdXnAVMGtmwxS9u2oTJ4sPfXe8cdNtVBdP68ST3OLbfYpW3bTKlY0al6vNEBExvrVD/xuUKHR//+Eeo1vPQSpjbYpHv3SDlxIvdODHx2//gjWQW/3uzfb1JBsbde9iVLkPURoTJISpRwSOfOmTJpUva2+P33ZKld++K/+LFff/BBqOo0GT48XBVoxLb8/PM01WnjmY1xMV9a6Ay8555IWbMmxK0zA5+3S4VMC0xh0TOGriR85n3VgggWPFkLHLZ9YLH9A4dtnxOm+z34YPb57xdfpMqdd+Zetyi/2PaBY2KAfu3ARtJP7uvWdagTfP2D+s03VnngAZsKTBFYYUQMgS+CZKQc33qre6CKAGPPHrNKMdYDue+/T5GOHe3y7ruhKmX4YiAAQurw5s25n3l36WKTiROzR+ji400ydmyoNG5sVyfFTz0V4Rp1vvlmu0ycaFWBFQISLG9WqpRTzS3GfGqMIv72m0WNXOP6y3Wii5NmjGrWr2+/7CfpOPnHdoqI0HpDsR2RRq73hGJb4/kxSote0v/8JyxHwPbJJyJ//21T6fWdOmWqYnt6oIZt/PHHofLMMxlSr54jTyOpGPH3ltaMEWmM+qO99Y4WBPEowIeR6A4dMtV+hrnyGzeGqBoB8+f7H5lHEPrll2lq/n6fPhGyY4f3fQaZFDt2JKkK+fr7QvCalmZydVagpsC//hXumgpgnOqg7z933eW9IwEp86mp3ntebrklU83fx/QH1DNAEJuQ4L4NunWzqYAenS2YouAr4wP7LVYHwJSO48fNbs8/alSa25et0WuvpcnIkWEq2PflX/9KlxdfzFAj4NjmOAYgEMb26dUrQqX/z5qV6hrJxmcE98WUCHR8+ILtiqkjehFCdCx9+GGYDBhgc8uK8GXo0HD56Sfv+wFqHNx7ry1fBQjRmbR/P+pORKrjoZ7R4+mhhzJU5gZs3myWDz8MlcqVnfLss+kSFZV7IKwvqYhOMnQAIAto1KhQGTs21e1YiqKMgGk5Ouyf778fpjrEUC8hNNTpc4UK1HpALQwc01E4slevTFUg8mI6LvS1UvE46ITC5wWZIcjkQYdaflbJOHdO5OWXw6VnT5tbJ6fxhAHHJvz+v/9ZVf2OOnXsqpbEpaRb4jiD4xAyUPCZW7w4RGXiYFviveH2SzkOo2AnXi86c/7733TVYQY7d2rHMdQu8Qf7Eoqb3n67TWVjoRAnjq3ohMW0qN9/t8hjj2WoehdXZuWTSPnvf5NVZ+eltMG331pVxzy+N40d8+QbA5XAYdvn9PDD4TJzpvt3Kz7Pjz+e4fq+vhzY9oFjYoB+7di/P1E6doxUxcgwIjp9eoosWWKRhx92P7HHyRlGqREkY6QSJ4jLlmlpyWg1jHoinVcPcPLLM+24Zk0EaxmugmK+/PJLsnq9evD/zjsISnyfyCCQwIgvOiOMI9feqpIXBDixmjnTokaQcUKMtHaMrJ8+ffUOnDgpf+65MPnuu+xtjWyKv/9OznGih9eEbXjHHZEq4Dh6NDsqatEiU6VP6+nOCBaxryJbY9kyi0qZ79vXJhkZ2LfsMmSILcccdr0DBwEkOmbq149ypfwbIf0LGRBdu0aqzgCchKP4HoI0BK/6snkXA9kF06alugr94bPVq5d7RwDS/C92mgamIHz1VZqsWWNWQTpOqtFmGI1HYFC4sFNlkWAbvPpquqqfYNw2Rp9/nqqmbXz/faia04957d6mUiBN/+uvU6VjRy1bxmRyyvPPZ6jtiUBXby+8Noy8d+uWqUbesVwiAh0Epuh4wvacNs2a61QGdNRhX8gtKEWnz2OPhavnHzBAZMqU7NvQsXX77ZmuGg7oSFmzJlkVo8T2MB7rkFExaJBNdSihQwoBN7J/MCUCSz/iM4X9HO/NE6bg4L1iH8V+9P33VnUyhCwMHG9RpNJzugeCOGwbtMWgQRmuaUD+OjCQBYOaEsiIeffddLe2mTDBKtOnW1X749iIDAx0IrRvH+XKJkGnFqYTbd9uVp1B5co55OefU1RGAz5PCIDx2hHwYtTFbHaq59A7wYYMQeqk9rpOnkyU1au1aRXVqzvVl/yCBcnSv3+kFC3qdGVQAT5nyIrB47//fqia7vPdd6kq2wqZM+hoRIYIbsf7QJYJOjmwD2F6AjpE8BlFPRLjdB3cD4E6MoyWL/d+rPnXv8JUUI8OSewLgOMPvg/RKXP77ZHqdh2On8OGZcjzz4e7rsd9MY0I2x9TiYzPg+fo0iVSrZChw36G4wuWrEQHsQ7HrnffTfOZ1YLjGgqPYurVli0hKssst0yVevWiVIcb9ifUArlY+BzpdUY6dsxUnXB4bnzu0fbo0EGnIT4jaLfLBR3Ozz4brvbXe+65fB0YOKZt2GCWhx6y5btjHp1w+Cyhsxx/7++8goFK4DJ92PY5tWgRpY69GChZudL92DN6dJrqKK5aVZsyeinY9oFjYoB+7UD67rhx2SffOHF2OvN24o8gHV/CSFXPiwceyFAjZAgGK1Z0qJEYnOS2bo0U2FQZODBCjTrixPPWWxH4JKr5MPqoKYISdCKgsFePHjZ56610FRDghLB+/WgVkP31V7Ia1aL8OXbMpAIhpE2XKHH1D5yY74sRQnQWYL/46KN0vydc+hxnnJTeeWeE+nKfPj17VNYT3gtOmHyd3Or3wYg+TrCefjpDHXwWLsRqAKEqeNLhZHblymTXc3l27uDEDifoyCZBoI/gCiPyCNwQbGMaBkar8CX39dfugS8yG5YvT5KyZd0bHxkXffpo34rbtiWpwoYo9PbRR2GudH9kiXzwQZgKLPWOC3yeZ8xIVQEA2gwdMpiG4Pn4nu2AaRhz5158l/nTT6erqQ7IUEE7PPKItvwfCjVidDcvHXnFijlchfh8HbvQiXLHHZly220RsmqVRU0DwNQKdDYNHJihngej6ggabrjBoYI/BHVoLwRnmBKCn55QR+DDD9PVPqYfXzyzAlCMMb/1Ga6UPn1sKrsJWR169hIyErC9ESx4y6DA7ciSwVKRnoUr161LkoULLW5TWvxBNhCC4a++0vZnBGj4HKD9hg/PkE8/1Zam1CGwx5QRfB6feipdNm0Kl8OHfdfJQMcB6iToWVTIlMFylXqHGgJBjDgbs0j0zypqH+QF9tGXX9a2OXz9tVWN+Bs7DNFZgvZCpwM6BHPL6PEGHSoYbcfnHx0yqBuCDh587jBdw5/bbrOp14gOH2SV4f2h0COKWL72WpjqDDLCkpzoVAGsRII2wpSa338PUXVCjB0/+Dyhwx2fKXwfoOMbnXbGzh8cp9E5hroVyDxBll3nzujYt/jsxDNCJz+O03rnEDIE8HnE8RMZAshSwfkBjpfowNODcEyVwr6Ccwi9RsemTWZ1X3RGwMaNSW4FOnG8w7EAx0Os0IGgGx1U6GjxDJpxXzwHOiORgaLXd8E+gQ7MZ55JV5mAudFWQcke3PjuuxTVPkb4TCKjEB0VOF5hqdW8dogjkMX9PDse8fpRkwcZc8hkwvcXvm+wHfGZQdaKMdsFWUtoT31fD6QxY6zqM9WmjV11bl2uVVFwPPz3v7HqToj8+9/pOVK1GSS6Q4dszZrah2vnzkR1THnnnTDXMV2PDXDsRUeht9pLvga68B2KLLwOHbTvCWRTffxxjHTrlpJjJSG6skwM0K8dOEgjcPFMyTWefGJpLixbhiAFJ0VIqX3mmfAcVc/1ESOk5eJDjFRMnKADfke6LL5YcMDEiAJOnPBljzRqY5Vszx0IFaDnzLHKgw9mqNRtfNFiTrMxhRX3wfM2bsylqS5FoL+0cPKCERecZAQLtMO0aRYVsDz5ZIaaQ65PBfEHJ8P6KLgv+Czcd1+ESifHiXBcXJQUKpSz7fE7gluMWuonzDhxxeguiibq0w0wuodAGOnaGNnEieXjj+d/ZAlfqJ98Eqq+nBHs6vC5xQgsOgAwbQE96thmSKdHmji+0GHx4mQ1wukNTiaxMgE+00Z6HQkj9NYjMPM26rx9e7LrZAAnowcOaJ9/LN+HOfDeOhRxUozjBAJavH4ENFqVfIfMm6e9ns8+04pVGkd00EGC4oCo6aC/LsxJR2oyptAYoUNAXwlBD16Rpq3fD50DGDnGtgRkMaDzsU4dh2pPb9kXXbva5LXX0lVNDWQV2O3+A7nBgzPUKDm2IzqLMO0IwbjeGYHRbezDnlMrvLnrLpuMGJEmEydmF6FEB8zFTlkCtLcxYL8ajFlaeD/okDTWRgDs2wh886taNbvaF3fvvoh5BCLy5JPpMmyYTfr1i5Bt27THQGc0phfhhBaffbS9t30D2SK4z6uvej/Y4Lv8qacy1N9fTIbbsWOJroDwgQe0+im+IPvG37QZQEFN1IvASXqtWjE5PtenT2v7xcKFyWpaDY5D+Jzpf4vjKjoSkC1g3IfwGcEoH457OLagcxWZgej8WLYsWWWD4P3rRT91mJ6gd8T4g1VA0Lk6caKW3YSAA8cyZE3oK4x06BDpNhUPn3Fkf6DAJI7hmDqHKYLIfNH17Il/Wicq3gM6bzHlYs8e7VhuzDh48cUwlaXyn/+kq9H5ZctC1GMhOPfXWahP/cF0HExrGDw4Qj02Ankc/9DhAtgm996LFU8c8vrr6apjDZ8TZJugkxPtjveK941pL8gGMQZk+D7D/fGdhE5gbCuc2/nKIsB3R+nS2fsAOsK2bk1S7x8d5dj2yFh64gnUB8rfuR1e+1tvZR+jPv44TU2X01/L5T7XwWPg2IxOHkxbuphpOSjqiql2mEo2cmR6ns4zLhfsS5iyh/N4FC7WaR2VYTkG7lCjBuf4OmTu3HNPhMrG++qrVLft9cILYTJhQqirIDDqSeG7DJ3wO3ZcfObOtQCfFUx1QkfhpUzVWrkyRB1P8LmFi5mylt/9Hh2C4Cu7hQH6VQjQ69fPVOlw6NXHvEecoGCkCT3JSE3DCAhGKtHTfdttma4vDKTIoocSaZvoaUYQjlFFnAwiiLnYlPFAB4kFGdv+6tN7na/ECcOlTtvAyRFSmnFCi8AXc4eNJw0oOIiOPb3GAL6kMUqFdH9/cPKFqQc4mcUoLb64Dx5MkrVrzWr+9/LlFjU6iDRvdPK9/nq431oTnnBSgZMldOLhuITK9L5OYCdNSlGjN2+/HSOlSqXJo4/afJ5MIiiYO9ei5hqjUwRfYOhQwklp376RqgMDtSxw8o5jIVJvkdmAyziJRu0Bz3nbOKEDnPziBBlF/fQpRkh3fvPNdJUloG9LZJhgRN8XpFSvWpWU43kwmoYpAuhoMKaQ4+QbJ1QDB+bMW0T9EWwDnDDjRAMnvXid6FRFZX5kFeDEFyPLeMxatewq0Ni+PefZA/7m/HkUEPU9bIeOk7ffTlOdCXidyAhAajqKSaIT+ddfU+SJJ8JVhzEMH56upqpgmoKxcwfFjbD9EexhNBZTE9B+SH1HkIR5+fgd+yumy/hy//0ZahsaC4eiMw0nSygY2b+/TQXXGE1Chxnmb+L1ohMG6elffIHpGwhsbaqTR5+Tjv3988+14AHLcCKDDKOZeqo4TpIRVBpTSTHS+N//+g8kkRWBNkHHNzrLULvDV9COk2vst7VqmeXPP30/JupvAD7nvmpa6DZtSlLti0AYI+zoyHrqqXDV1i+/nKEKu6JzCdNd0C7eOtJ0CIYx9QPnHf5qWuQXTnLxGUWHHvYZTLHJz3QhZHMgy8CYXYL9FjVLWrfWTo6wIg2ym/CZwOcf+y3qhHhmTHmDkUrsL+PHh6pMQex/GMzAPOA6dbI/99hHjJ9jPZMEHaX+YN8zdrqisw7HGASv+HzrHW/eHh8Q5OMYj84tdCyicwgBOYIuPQME7xmZIjhuo9Pm/ffTVLtXq+b0GhR6mzqFfQbLo+r7Ah4T7f7sszmXpNWPo6jpgXRsHDf0rCojbKcxY9LU9w8+b198ESPTptnVlBl96smMGRZ1nOjTJ9MVgCJbA+fDmDqEn+hgRSeTMYtuypTsKXJ6/Zbc4DiC7xVsY8BAwBNPaI9x770ZKpPQEzqjkbGCjIC8rl6Cjlq9QDOyYDC4hmw+ZLehY7hHj0z1vfbuu2GuOj5GyETB/HTjIB6OW2gndCL2758pgwdnZ90hQxbHLwSkiBO6d8/uZfLcr44cSbys89uDCbbt/fdHqPMPfC9PnZpyUYOIK7NWf0K74hwCtYswLetilqzN63kmbkNWM87T8JnRM7G8PdbVUCAD9Pj4RL9pv3lxuedvM0gMHLZ94BTEtsf7ROCPjkE9CwAnExglQlCKLyDcBydIGFlCWi4yfhCI5FagDAECYPQKJ2QYBUAAZRzhw+jRL7+kqN7oS217zKnG9BpMP7gUeH6kyiJLAQGgt+kI6ADAyRRGsmfM0KZQoBMF87GRmq8vWegNOhmQGoyT3jffTFMns3gOjN6iMwZLAiLbAM+Pedy+TgLROYMTEM/t8NtvIdKvn3bSjdRazDtHWjY6eo11HnAdplsgrX3jxgg5csSmTuSRJaW3g/65QGYBAl+M3mlTYELV63ruOW0qCkbqMDcdJ9RIbUUNAJxYoPggnsfXXGz8HYIqjBAg7R6ptuhIwX533302Neqod/gguML0K5zMYn/ats2sskT8zZ3F/fA+vBUsRJozAmTMS9e/g3FfBKRI+/QcPcNtb70VqrI+XnghQ9UUwNKielDUvHmmTJmS6koBx7bB/oDU92PHzCoQw+04UccUBDwn2i4sLEYFdqi1MWNGijoZxAi0cQUDTwi+sI+hIwIBBU74UX8Bo2OeENBAyZII1ELVNvEHI00IBPA6jUElPld6BotxZBgFIZHa/vjj4WpwAfsJUvOxX2PUG6N6+qi8L+iwQJti5Q09gwKfD281Izzpqb961iFqiPz0U6pa1eTmm7UpNMhC0UfNcT8Eh57TMS6FPjKJY+T48Vb1GdczMZDdgYKI6GTSM2hw3EM7oSP0asOUFgSZGEHFfql3hKFNPLORvMEyt9i2Rsg26NYtSmVwoqbE5MmoPh6hOoP+/DNZZWyhPdChMG9eigwaFOFWvwbi4rR6SsasDBxf8T10yy2RObJXUBsDnQ+YYoGOWQxM6R2T+Kwh0xSFQHEMQNCPIFwvIKkHvfffH672HQTj2O9Qt0Kvr4IOSRyTsHIIXhc+zzjm3nqrVhcE0wHQseINsiRQDBP7GPZhZJPgOw7T3dAhhQDPCO2C7CFMKcN3ArJ5POF7GVm03jrptmxJksaNo9w6unBMQeYYXgc+f2gjfZ80Wro0OU8Fhy/F/PkhqsMMncn+CtFiBRp0KuB1Xwx0RuDcZfZsq7zwQro6Lup1VwCdVGvXJuer3gKm2Nx2W6TPAtqYlorzJ3SSGeMwTPnFd6uebYwOGRwP8f3g61wHGZg4xqLTDd9Pn30W5urExzb2rB+C79oKFRigXzHBGAwUxEAlWLDtA4dtf3UgcEdQiwAIAbCegnkttT1eI0aMMEKpf9nnp5MUacDIUDB+4eIEEKOal2M0AycqGC3Gco4I0BBc6a8PJwEYYcXIjf66A9n2GFHC817O4mVXknHqjL7iAALSH37QVlTwhAABo/c4yWre3P3kVG97zN/GtscImw6dB6gTYKwDgYAY01eMI6HIrECmDYpE5lYNH3OfkXmhPyaCAmQ74AQd+4g+1Q3ZCOiMe/PNUBW4vPdeurRrl6kCGJw8Yr4ssiz69s10dX4gkwVZIjgBN34WsP/Vq6eNPKPYJKYq6Uty6lP4kDWD4wGCEAQymFaDYomYq4/gXx8Zx5zxn36yqPsiIwTTSNCRMWBAhKujBFNkMKKoXc6eFmIcFUV6OFLucVL92WdW2bkzWXW64cQ+NzfemOmaI49OGqT9ow08O+VKloxxBeMISpEtggyNnj0zVcYQIKMFKffo3NIDVqwMgjZEwIlsDMwbRpsg/RpZKXrdAtQOQiCj10HRs5Ew6o1AGZBRg8+V53RIoypVkNGgFcTU66wYffRRmppSafTWW2lqNP2FF1DgU0sh9taZUqMGRhu1TqMbb9SKIecHRj0xtdL4HnODqQDIPNXfP/YLvD50emIuPDr4kH2BGg95gQwdPIZerNQIRZFRgwL7u1acM1I9l7Fzyx903qAzzLis7Ny5yTmOE0Z4HmRyeJsug6AcQTBW0DGmxGPUHFkk6BjB5wWdiXa7Rdat07av3hHqC+qZ4NiETll876EtjZ0d/iDbo0GDaNe0IXQKozMRdSl06PTF5w9p+CiGiil7yAL09Z365ZdW1YmJzGO9Q97YMW2Exxs5Mk1NNUOboX0xhRPHZWRe4RiHjhQs94vBA3wv653U0KpVlNdpfp7GjUtVGc7IdsZ3OaaHYPocMk/QvliRCJ9ZHNcyMzFtKNH1/rBsLjKd9OOK9/ecqjpokHmEjl4cE5B95u+zfTkxQA8SgT5hK8jY9oHDtg8ctn3gsO0vHkZJkIGCTIeLyYTLre1RWA7zitu1s6uCcEhzvNSiThg9RWossiLwujEdzhcEkAhOLjUrBdkU8+dbVBo63icCBYwoYX54s2a5j97hvujUQjCEE2AExMaTdz01GaPjqIavn2Cjo6Fp0yjXCD5WndGfT8881IuyooNh9GirWhL16FFtOgpqgKATA4EdAi+M2qJTAqNbGDVDrQxfUPAUhUQxCptbWi06fV56KUxlT2D1C+PcYiPU+kEQjZF6BDHIisD0ltmztfos6GjRM3RQ5wHz5BFAo7MHnRV6cI+gBUEDMjBat9aCeMBILwJ1rMaA+hjIRpg9O1Wl3q9fb1Yj/sb6HkbIIho9OlV69IhyjQrPmpXiCjbfeCNURo3KW6CNrJuxY60+sxywDCqWP0RnJtpOD1YRoGL+NrYj6ibkNnXCON3AcyWjvEJbIshFR62xQCEyQLCkq3EE1xMyBNBZY5zmc+BAoluA6A2yUtDRZYRsgmnTtH0NHbQI9rTji0NlIWC6Djp5EKCjE+PLL2PkjTe0TgJMU0LmDKbQocMUxaGRcYD9B/vXAw9EqMAVc/s7d45SnY07dya5LdWKGinotEPwjhR9fEbxWe3Rw70uhN7uyMTAfo5sA2SXGKd96DVxENzj2INVPPC60JmBAp2YhgZa7aBM1dmMTgkUsDZm1mB0G9N/8RMr/hiDWWRZeKspgs4MBP7olMASyHpdn9zgOIGpF2hjtIveSeavYwzHE3xusUQmOieM8PnB8RL7tz6SrkPHIDK9cFxDVsfVwAA9SPCELXDY9oHDtg8ctn3gsO0Dp6C2vbbkoTaCdblghBojfAicjXCijeAUc5wxRcIY2Ptrf/yOzgwEPsE0Rze3KY24HW2rL6/oeRumkGC031hx39c20muz6JAq/uijEW4pw0jzRjCBQB+BJdp60aIQdT3Sw3UIXPr2xTSeENcod4MGIs2aZagOo7ffTlcjqUi9x9rfeBzjyDkyRzD1BZ0nKIBmXBpu2LBwlf2AqR+YYgQI7tBRgakO6GwxdiwgqEYQhqk4mPaBUU3UpnjkEdRjQQdApqpfgc4w/DTCNBTUO/EFqe9YzhBtjLbD3Hh0FnzxRZoauUVdkWrVYlyrPKDdGjWKUsHgc8+lq2lDuUFQiyUmkW2hT1N47700VTshL/C6nM4YNSXMWF/ivvsyVHaKXgcBo/HPPJOzQB1gJBpBODqJkAViXMECI+SYroUgH3UmUHwSU92My1ki+wzT5fQpDXqwipRydBDltqKGXtTQuAwvAn9kq6Dt0TlnzCh6/vkw+eab3Kdw+PLzzylqlSN0RL3xhpZRgrRzZDANGaJNM7oYnjUpMM8drx8dC5hKgv0dxS+91fBBujwD9CsoGL+YC+pJQzBg2wcO2z5w2PaBw7YPHLZ9YLH9809fMhWBNlLYc5tWYYQRVUwvQC0LzI1u0yZSwsO9tz0CcBQtxXrgWHVCn7bgDUZXMSUDo6neKq8j8wABJAr4IesFBf8wWpwXS5eGyH/+E66mY2EOMbJYUHBQX/7MCKO2WA6yalX/OxNGuFEgbsAA7T0hOwQdCegwyKt168yqojhSzrHUMkZV87psn77fIy0bFd6NNSIwAu4tOPa1BDTm6mMqgt5R4A2yOTCvHtOr8BpRG8IzRX/9+iRXNo/nyg4IxJFSjznXnrULjLBqDmpZeINit88+qz0mVipAUT4UNURnClLSsVIHOrW8pbM3yZqmokMHFDrtMDIPCNJRewJ1LvSCf6iNgOkRyHRAZgYyKtChZBxZRx0KvYMEWQn//JPktqKWDkE6at6g2J0+fQL1ZTBdJrfCoZcLA/QgwS+twGHbBw7bPnDY9oHDtg8ctn1gsf0D51pue7xejNCioBdSmzEyjEwNTI/ASPy11PaYi43OkJEj3TMWdEh9x7QRdMrUqOG/IBkqm2OutXE02VhRXoeCsRh116FIIYqjelsT3ltRQrQ96jEgWMe89unTraqqPQoD+lpaFx0zqEeBaR16YO3N8OGohm9R0wWmTEHBR0zN0JZ+zQ8E7eiMwGtFWj4KpaIQIjIEVqyIkFq10uSRR2xq+g46D/C6/HVC6XB/jLpjX2MV9yssGA9O1/KB81rHtg8ctn3gsO0Dh20fOGz7wGL7Bw7bPvjaHgVcEfQiYEQhV9BXAAGs5oJaEph+4Dm/H3Pdt21LVgE/CrYhkwFZFijsqK9sYcykwIoNWInj229TvdbvwAoYyHh44gltpZCrBe2B4Boj5PiJZSsbNnQvfBks+/3VDNCv/noTREREREREBRjmiVeoYFfzrJGKjTW/kTqvQ6DasGGGKjCItHoU1mvbNkoVb+vcWau6jnnp+vQBY6V2I9zH1xJ1OqRvBwLeg15zAiPgjRpd2SXorhUM0ImIiIiIiAIABQSxlr2/28uU0QLo335LVvOiGche3xigExERERERBTlUgsc/ur7lvhI8EREREREREV1xDNCJiIiIiIiIggADdCIiIiIiIqIgwACdiIiIiIiIKAgwQCciIiIiIiIKAgzQiYiIiIiIiIIAA3QiIiIiIiKiIMAAnYiIiIiIiCgIMEAnIiIiIiIiCgIM0ImIiIiIiIiCAAN0IiIiIiIioiDAAJ2IiIiIiIgoCDBAJyIiIiIiIgoCDNCJiIiIiIiIggADdCIiIiIiIqIgYJECyGSSoH1Nwfjarnds+8Bh2wcO2z5w2PaBw7YPLLZ/4LDtA4dtf320vekqbj+T0+l0Xr2nIyIiIiIiIiJvmOJOREREREREFAQYoBMREREREREFAQboREREREREREGAAToRERERERFREGCATkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURBggJ4PGRkZ0qNHD1m1alWO2xITE+Xmm2+WmTNn+n2Mb775Rt3vhhtukJdeeklSU1Ndt6Wnp6vrmjZtKq1bt5bx48f7fazt27fLnXfeKQ0bNpQ+ffrI1q1b3W6fO3eudOjQQd3+2GOPyZkzZ+R6avujR4/K0KFD1fvr2LGj/Prrr34fg21/edt/7dq10rt3b2nUqJHcfvvt8vfff/t9DLZ//pw4cUKGDx8uzZs3V+32zjvvqHaCQ4cOyf3336/avlu3bvLnn3/6fSx/7eF0OuXDDz+Uli1bqud6//33xeFw+Hys3J4b+wH2FTzXoEGD1P2vp7bfuHGj9O/fX+3HnTt3lh9++MHvY7Ht88ffsYD7feDanvv9lZWX70CeZ14Z/tqE55lXnr92WVuQzzOdlCdpaWnOxx57zFmjRg3nypUrc9z+yiuvqNt+/PFHn48xf/58Z5MmTZxLly51btq0ydmtWzfn66+/7rr9jTfecN52223OrVu3OhcuXOi84YYbnPPmzfP6WMnJyc6bbrrJ+e677zr37NnjHDFihPPGG29U1wMev0GDBs5Zs2Y5//nnH+c999zjHDZsmPN6aXubzebs0aOH8+GHH3bGx8c7p0yZ4qxbt65z586dXh+DbX952//UqVOqPb/++mvnwYMHnWPGjHE2bNjQeezYMa+PwfbPH4fD4ezXr59zyJAhzl27djnXrFnj7Nixo3rPuA1t9cwzz6j3/+WXX6q2P3LkiNfHyq09xo0b52zbtq16jhUrVjhbt27tHDt2rM/X5e+58bNRo0bqMfG6n3zySfU5xd9dD21/8uRJZ9OmTZ0fffSRc9++fc65c+c669ev71y2bJnXx2Lb55+vYwH3+8C1Pff7Ky8v34E8z7wyfLUJzzOvDl/tcqqAn2cyQM+D3bt3O3v27Kk2rLcAXT+Bw8b0d+C8++67nZ999pnb32EDp6SkqI2OLzzjY3/xxRdqo3vzww8/ONu3b+/6EsJPvAb9+Z977jnnCy+84Lr/0aNHnTVr1lQ7+fXQ9osXL1YfxMTERNd9H3nkEefUqVO9Pg7b/vK2Pw5uzZs3d7svfvd1sGP75w++ENDeCQkJruvmzJmjTmT//vtvdUKqf1HAfffd59a+Rrm1B06Ujcet2bNnO9u1a+f1sXJ77k8++cRtu2H74kvQW6fmtdj2kydPdnbp0iXHSfPTTz/t9bHY9vnj71jA/T5wbc/9/srKy3cgzzOvDH9twvPMK89fuyws4OeZTHHPg9WrV0uLFi1k2rRpXlN/X3nlFXn11VclNDTU7TakIdWsWVNdttvtsmXLFpVaoUPKhs1mkx07dqh/mZmZKi1D16RJE9m0aZMr9QuPpac24XrcbjKZ1O/42bhxY5WGpt9ufK7SpUtLmTJl1PXXQ9vj+latWkl0dLTrutGjR8tdd92lLrPtr2z7FylSRM6dOycLFy5U6YqLFy+W5ORkqVGjhrqd7X9pSpQoIWPHjpXixYu7XZ+UlKTeR506dSQyMtJ1PdpDf/+YhoD2Onz4cK7tgVTuY8eOSbNmzdwe68iRI3Ly5En1e/v27eXzzz93PZa/5/Z8roiICKlbt67r9mu97fV0d0+4Ddj2l8bfsYD7feDaHumg3O+vnNy+A3meeeX4axOeZ155/tqlSAE/z7Rctke6jt19990+b/vyyy/Vlwe+wDxhrhRO6ODChQtq/kPJkiVdt1ssFrUDHj9+XMxmsxQtWtTt4IsTRPwNdtBixYqpeVcxMTHqtoSEBKlWrZrb88XGxsru3bvVZXzRGZ9Lvx3PdT20PeaYlS1bVs1j++mnn1TbYc4o5oMA2/7Ktj8OTAMHDlRtjvbDwREncFWqVFG3s/0vTaFChVztB/gCmTRpkpqziffv7/3hCwjthXbLrT3wWGC8XQ9McTuunzFjhoSFhanrcnvu3G6/1tu+XLly6p/u9OnT8ssvv8gTTzyhfmfbXxq8B1/HAgR13O8D0/ZRUVFSvnx51/Xc769e2+M7EMcfnmde/bbft2+fVKxYkeeZAWr/qlWrFujzTAbol2DPnj0ydepU+fnnn73eHh4erv5BWlqa+unZ+4nf0TuK3iFvtwFu10d2dCh84Oux9Ofzd/u1LiUlRWbNmqU+oOgkQQ8+PsQY6a1fvz7b/gpDLyY6SR5//HFp166d6uF88803VbEMHFTZ/pfXBx98oAqW4MQVRVD8vT9cNraXv/bwtm08214/6c5L2+d2+7Xe9kZoOwQo+JLXR1TY9pfG13sAjIRwvw9M2xvfB/f7q9v28fHxPM8M4H7P88zAtX96enqBPs9kgH6RsLFffvll9WH1TIX0Ru8N9tx4+B0pWegZ8nYb6Dug5+N5u79+X1+347muByEhIapn7LXXXlM9Y0hpQ7XH6dOnqwOnEdv+8kMKMD4DOHAC2n/z5s0yceJEef31193uy/a/9ADx22+/lZEjR6rULrw/9Pj6ev+e/LWH8QvKczt5a6/cntvXc2FU+npoe2MH1aOPPir79++XyZMn+9y32Pb54+s9gNVqdavIq9/G/f7Kt73+PrnfX/22R1o7zzMD0/Y4t+R5ZuDaf2wBP8/kHPSLhKUXNmzYIO+9955K78I/XPff//5XhgwZkuP++JBjg546dcp1HeZD4IsHvTZxcXFy9uxZdZ0OKRbYGbx90eD+xscC/K6nXPi63dhDdC3D+6xUqZI6aOoqV66s0iA9se0vv23btkmtWrXcrqtdu7b6DHhi+1+8ESNGyIQJE1SgiKWN8vL+PflrD9wGetqp8bK39iroba/Pu33wwQdVqhuCdxyHfGHb54+/YwHm+HG/v3JyOw5zv7/6bQ979+7leeYV5K9NcBvPM68sf+1y8ODBAn2eyQD9ImHjIN1i9uzZrn/YcOjpfOutt3LcHx9w9LitW7fOdR2KDWCOBHZA7HS4bCxsgvvib4wHBx1SPNBBgN4lwM/169er6/Xbjc+FAwr+6bdf6/A+cKKAXjEdUsEwL90T2/7yw76OKR5GOJEwzs/Vsf0vzqhRo1Rq48cffyzdu3d3XY/3gQ4SPaUL8H59vT9/7YHjGAqbGG/HZVznLfDJ7bk9nwsjnkgPv17aHvPR0ZuPYljfffedVK9e3e/jsO3zx9+xgPt94NoeuN9f/bZHQM7zzMAec3ieeWX5a5eSBf0887LVgy8gfK2DDlgmxLj8RWpqqlo/VIe1Qxs3buxctGiRWkOve/fuam0947IluA634T6474IFC1y347HwmIBlH1q2bKn+Hkth4SeW39CXIlm/fr1ar3H69OmuNfoeeugh5/XS9nj/WPYIbbZ//37npEmTnHXq1FHrGwLb/sq2/4YNG5y1a9d2TpgwQS0rgZ94z1iHFtj+l77UF9p35MiR6r0b/2VmZqr1PZ966inV3l999ZVahkhfFzg9Pd11v7y0B/4enyVsW/zD5fHjx7tuP336tDMpKUldzu25Dx06pJYywfX6msRYou9aWpPYX9tPmzbNWatWLbX+s/H6s2fPqr9l2186X8cC7veBa3vu91debt+BOp5nXn6+2oTnmVeHr3bZUMDPMxmgX8EAHZdxfyN8ibRq1Uqtrfjiiy8609LSXLdhrb7nn39effngoICd0fO5jY+PneyOO+5QX059+/Z1btu2ze3+uC/WG8XjPfbYY84zZ844r6e2x4dm4MCBznr16jk7derk9kFj21/59scaoVgjHe+xV69ezr/++st1G9v/0qCt8J69/QOcLOj7Pr5wjG2PbYT74cQ1L+2BE+C3337b2bRpU2eLFi2cH3zwgdvJLY5rxrVF/T03/Pbbb+rziPVHsV7xtbYuq7+2Hzx4sNfr9bVU2faXzt+xgPt9YNqe+/2Vl9t3oI7nmZefvzbheeaV569dFhfg80wT/rt84/FEREREREREdDE4B52IiIiIiIgoCDBAJyIiIiIiIgoCDNCJiIiIiIiIggADdCIiIiIiIqIgwACdiIiIiIiIKAgwQCciIiIiIiIKAgzQiYiIiIiIiIIAA3QiIiIiIiKiIGAJ9AsgIiKiy+ff//63zJo1y+99lixZIuXKlbtqr4mIiIjyxuR0Op15vC8REREFucTERElLS1OXf/31Vxk/frzMmDFD/e5wOMRut0tcXJyEhIQE+JUSERGRJ46gExERXUdiYmLUP/0yAvESJUoE+mURERFRHnAOOhERUQFx+PBhqVmzpvoJuDxv3jzp2rWrNGzYUJ5++mk5dOiQDBo0SP1+9913y4kTJ1x/v2jRIunWrZu6rW/fvrJ69eoAvhsiIqLrDwN0IiKiAuyzzz6Td999V7766itZuHChDBgwQP2bOnWqJCQkyNdff63ut2PHDnnhhRfkkUcekZ9//ll69uwpQ4cOlQMHDgT6LRAREV03mOJORERUgN1///1qRBxq164tlStXViPq0KlTJxWYw7hx46Rfv35y2223qd8xyr5mzRqZMmWKKkxHREREl44BOhERUQFWvnx51+Xw8HApW7as2+8ZGRnqcnx8vEqHnzZtmut2m80mrVu3vsqvmIiI6PrFAJ2IiKgA86zmbjZ7n/2G6u9Iab/jjjvcrkcQT0RERJcH56ATERFRrpD6juJyFStWdP3DaPry5csD/dKIiIiuGwzQiYiIKE9z1bGu+sSJE+XgwYPyzTffqH+VKlUK9EsjIiK6bjBAJyIiolw1atRI3n//fZk8ebJaam369Ony0UcfSbNmzQL90oiIiK4bJqfT6Qz0iyAiIiIiIiIq6DiCTkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURBggE5EREREREQUBBigExEREREREQUBBuhEREREREREQYABOhEREREREVEQYIBOREREREREFAQYoBMREREREREFAQboREREREREREGAAToRERERERFREGCATkRERERERBQEGKATERERERERBQEG6ERERERERERBgAE6ERERERERURBggE5EREREREQkgfd/jPZdEzT4HwAAAAAASUVORK5CYII=", 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measurements\": nr_of_cycles\n", + " }])\n", + " if os.path.exists(STATIC_LOG_FILE):\n", + " old_log = pd.read_csv(STATIC_LOG_FILE)\n", + " new_log = pd.concat([old_log, new_entry], ignore_index=True)\n", + " else:\n", + " new_log = new_entry\n", + " new_log.to_csv(STATIC_LOG_FILE, index=False)\n", + " print(\"Static test logged.\")\n", + "\n", + "def remove_duplicate_static_tests(log_file=\"static_tests_log.csv\"):\n", + " if not os.path.exists(log_file):\n", + " print(f\"No such file: {log_file}\")\n", + " return\n", + "\n", + " # Load the log\n", + " df = pd.read_csv(log_file)\n", + "\n", + " # Drop duplicate rows\n", + " df_clean = df.drop_duplicates(keep='first')\n", + "\n", + " # Save cleaned log back\n", + " df_clean.to_csv(log_file, index=False)\n", + " print(f\"Removed duplicates. {len(df) - len(df_clean)} rows deleted.\")\n", + "\n", + "def get_pixel_size():\n", + " config = myu.load_object(config_path)\n", + " return config.get(\"pixel_size_mu\")\n", + "\n", + "\n", + "axis_path_1 = myu.get_latest_measurement_dir(2)\n", + "print(axis_path_1)\n", + "axis_path_1 = r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250718_alignment_tests\\20250718_113013_static_0\" #uncomment for specific path\n", + "axis_data_file_path_1 = myu.find_newest_dat_file(axis_path_1)\n", + "print(axis_data_file_path_1)\n", + "#mf.analyze_repeatability(axis_data_file_path_1,1.1)\n", + "\n", + "\n", + "def pool_average_1d(data, pool_size=10):\n", + " data = np.asarray(data)\n", + " remainder = len(data) % pool_size\n", + "\n", + " if remainder != 0:\n", + " # Truncate the extra values that don't fit into a full block\n", + " data = data[:len(data) - remainder]\n", + "\n", + " # Reshape and average\n", + " pooled = data.reshape(-1, pool_size).mean(axis=1)\n", + " return pooled\n", + "\n", + "if pooling == 1:\n", + " x_vals1, y_vals1, times1 = myu.load_xy_data(axis_data_file_path_1)\n", + "\n", + " x_vals = pool_average_1d(x_vals1,10)\n", + " y_vals = pool_average_1d(y_vals1,10)\n", + " times = times1[:len(x_vals)]\n", + " x_vals = x_vals*get_pixel_size()\n", + " y_vals = y_vals*get_pixel_size()\n", + "if pooling == 0:\n", + " x_vals, y_vals, times = myu.load_xy_data(axis_data_file_path_1)\n", + " x_vals = x_vals*get_pixel_size()\n", + " y_vals = y_vals*get_pixel_size()\n", + "\n", + "\n", + "\n", + "#Calc statistics\n", + "rms_x = np.sqrt(np.mean(np.square(x_vals)))\n", + "rms_y = np.sqrt(np.mean(np.square(y_vals)))\n", + "max_x = max(x_vals)+0.1\n", + "max_y = max(y_vals)+0.1\n", + "min_x = min(x_vals)-0.1\n", + "min_y = min(y_vals)-0.1\n", + "std_x = np.std(x_vals)\n", + "std_y = np.std(y_vals)\n", + "x_p2v = max_x-min_x\n", + "y_p2v = max_y-min_y\n", + "\n", + "\n", + "log_static_test(std_x, std_y, x_p2v, y_p2v,len(x_vals),axis_path_1)\n", + "remove_duplicate_static_tests()\n", + "\n", + "print(f'Statistics| X | Y |\\n'\n", + " f' STD |{std_x:.2f}|{std_y:.2f}|\\n'\n", + " f' P2V |{x_p2v:.2f}|{y_p2v:.2f}|\\n ')\n", + "\n", + "fig_static, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(10, 6))\n", + "fig_static.subplots_adjust(hspace=0.3)\n", + "fig_static.suptitle('Static Measurement')\n", + "\n", + "line_x, = ax1.plot([], [], 'o', label=\"X Axis\", color='tab:blue')\n", + "line_y, = ax2.plot([], [], 'o', label=\"Y Axis\", color='tab:green')\n", + "\n", + "cursor1 = Cursor(ax1, useblit=True, color='gray', linewidth=1)\n", + "cursor2 = Cursor(ax2, useblit=True, color='gray', linewidth=1)\n", + "\n", + "ax2.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))\n", + "\n", + "\n", + "# --- Initial Plot ---\n", + "def plot_initial():\n", + " # Plot full data first to avoid axis scaling problems\n", + "\n", + " max_time = max(times)\n", + " min_time = min(times)\n", + " line_x.set_data(times, x_vals)\n", + " line_y.set_data(times, y_vals)\n", + "\n", + " ax1.set_title(\"X Axis Position Over Time\")\n", + " ax2.set_title(\"Y Axis Position Over Time\")\n", + " ax1.set_ylabel(\"X Position um\")\n", + " ax2.set_ylabel(\"Y Position um\")\n", + " ax2.set_xlabel(\"Time\")\n", + "\n", + " ax1.legend()\n", + " ax2.legend()\n", + "\n", + " ax1.set_xlim(min_time, max_time)\n", + " ax2.set_xlim(min_time, max_time)\n", + " ax1.set_ylim(min_x, max_x)\n", + " ax2.set_ylim(min_y, max_y)\n", + "\n", + " # This is critical: tell matplotlib to autoscale *after* setting data\n", + " #ax1.relim()\n", + " #ax2.relim()\n", + " #ax1.autoscale_view()\n", + " #ax2.autoscale_view()\n", + "\n", + "\n", + "# --- Update on Zoom/Pan ---\n", + "def update_plot(event=None):\n", + " xlim = ax2.get_xlim()\n", + " t_nums = mdates.date2num(times)\n", + " ind_min, ind_max = np.searchsorted(t_nums, xlim)\n", + " ind_max = min(len(times), ind_max)\n", + " step = max((ind_max - ind_min) // 1000, 1)\n", + "\n", + " line_x.set_data(times[ind_min:ind_max:step], x_vals[ind_min:ind_max:step])\n", + " line_y.set_data(times[ind_min:ind_max:step], y_vals[ind_min:ind_max:step])\n", + "\n", + " #ax1.relim()\n", + " #ax2.relim()\n", + " ax1.autoscale_view()\n", + " ax2.autoscale_view()\n", + " fig_static.canvas.draw_idle()\n", + "\n", + "\n", + "# --- Connect events ---\n", + "fig_static.canvas.mpl_connect('button_release_event', update_plot)\n", + "fig_static.canvas.mpl_connect('scroll_event', update_plot)\n", + "# DO NOT connect motion_notify_event\n", + "\n", + "# --- Plot ---\n", + "plot_initial()\n", + "update_plot()\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "pd.read_csv(STATIC_LOG_FILE)\n" + ], + "id": "39fcd9032d757549", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using daily folder: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250726_alignment_tests\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "no measruments on that day\n", + "going one day back\n", + "None\n", + "C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250718_alignment_tests\\20250718_113013_static_0\\static_0.dat\n", + "Static test logged.\n", + "Removed duplicates. 1 rows deleted.\n", + "Statistics| X | Y |\n", + " STD |0.04|0.06|\n", + " P2V |0.53|0.50|\n", + " \n" + ] + }, + { + "data": { + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ], + "image/png": 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8+vHHH/cZ4r5582a5++67VZh206ZN5ZprrtEKtfcHQt3B9u3bcx/74YcflHGiefPmct555ylvrmcY/PHjx2Xw4MFy/vnnq/fDIz1mzBifIe6G9xxceOGFuWHt3iHuOL4IN8exaty4sVx++eXyxRdf5NlXvAfGhGHDhsm5556rjtMdd9wh//zzT8Dz8Oabb0qbNm3yiHNPgTxkyBDlRYeQBwh979u3b77XduvWTe65557c/3/55Rd1nLC/OE7YztGjR3Ofx7m76KKLZPTo0dKyZUu1D6GkE3iOFeMYz507V0VI4FggZeHzzz9XKRp9+vRR5w/GpQ8//DDPdvbv36/OKY4h9v3qq69W2yGEEBLbUKATQghxNUWLFpWXXnpJCZ6bb75ZpkyZIs8995xUq1Yt6Htnz54te/bsUR7aQoUKqVD3r776Kk9OOwRr165d5e2331bC/OTJkzJw4ECpUKGCDBo0KN82s7OzlTf+2LFjMnz4cHnjjTekVKlSSjTCO2+FjRs3qt/Gd8I2ER0Aby3E8H333afy5yECIczBCy+8oL4fQvwhzPE9sD+TJk3Kt32IRkPUQqjee++9+V6D7V5//fXy3XffqRxx7MOZZ56pjsFbb72V57Uff/yxSh2AmIcgXrFiRcBUg1WrVqnzAHHvj9q1a6uoCBhMAM4JjB4IPzfA+Vm9erUS6QD7imNTq1Ytef3115Ug/vbbb9X388zwg+ED24JRB4aKkiVLip3gXOG7YQzVrFlTpTFgrNapU0cdRwh3HKtly5bleuhvueUW9V379eunzgkiNHDcKdIJISS2YYg7IYQQ1wMvJAQPQt3h3YXQ1gGeY+Sew0MJ4GmFRxhiF8XnPL308+bNU3nHCLmGoEQ4NowD3qSnpytxChEIzyiAAIPI8lXMzhOIRhgADODJXbBggfIu4zvCE47H8D88qvCwGuB73HDDDUqA4zfeB48x8rkBvPmIEChbtmy+zy1Tpkxunnn9+vVzc9C9j9WaNWtkwoQJal9A27Zt1f5CZKLQHgwRALnjeCwhISE3ogBeZXjAS5cunW/bKK4GfH2uJ0g9mDNnTq5AxzbhIYeBBSD8HZ8NMYxjOWLECLWP+G1w2mmnya233qoEOQwTAN8BBoSzzjpLwkHPnj3ltttuU3/jHODcYUw88MAD6jEYHlBPYdGiRerxb775RhkaJk6cqCIwACIhYIDBd/FlZCGEEBIb0INOCCHE9cBbDcGFAmrwMG7ZsiXoe/bu3SszZsxQodLIW8cPPJrIR/cOc4dHFV55iHR4rOFt9pdrjPxo5CYj1B6iD15ceNXhmcX2A/HHH3+oomPGD8Kb4X2FMH/55ZfV91uyZIkS+ggv9wTiEvsOYW4Icgg85G6PGzdOHRN4kw1RahZsF9s3xLkBhDI8vsiPN4DBwxDnwMjPx3nyheHNTkwM7DfANo3XIpqgRYsWKtTfYPLkySqUPzk5WRlJULgPYh0C3PhBTj9C5g2hbwDDRLjwPGaGgcQQ3sAwWiCFAGAMlytXTo0BY7+RBoBUDEQj2F3RnxBCiHOgB50QQojrgWcbAhReahR6e/jhh1WusqdI9AahzqiSDi+sd1sstBpDuDTCqg0glsuXL69C6SGU/AER/f777ysv988//6xy3JELD88+qpQHCp+GIMNrjO2kpKRIpUqVlKA0MMSZr0JpeMwQeQg9hzDG94RxAT8QishLh8fWLPhciEZfnwlg4DAoXLhwntfEx5/yB8BQ4QsIf+DZ4s0XOMfGawFC2fG94JmHFx4pBAjtN3K4AY6ncUw9wXn0xFc0hF14nj9/x8gT7DtC/j0rxHuC5+wOwyeEEOIMKNAJIYS4GoQ1I/wawhwiGPnhEGQIsUYLNn8gTBiCFTm+nqCAGMLT0dIMoe0GEP8QTshnxuMo9OWvCB3y0yGEkWuMUGXkxb/77rvKU+rZRs0biEQj3N4fhjBLS0tT++It3Iw8dXiR4enHD3KsES2AY/LQQw8pT7NZ8Lm+cujxmcBX6LouiBCA8QPHCeHf/sQ5WpghIsAAqQzIcUeYOzzmEO/IiwcIdQcYDyj+5uv7OJXixYurUHzP0HxPgqUCEEIIcS8McSeEEOJakNuMPGzkhaNSOEAhM+R+w4O9ePFin+9Dn3TkUyPnHKHgnj/wjmN7yAM2Cq6heNd7772nxC4K0uG92L4v8JnwtuM98IIjdBpGAOSIe1ZhtwpCoyG+YZjwZOHChWr7CPvGfiN0H558ULlyZZWXjnx0f/tgeLn9gdBweLi9jyk89DBUIHfaKvhsFHBD2DkMI97g+6BiPoQrzq8BRDjOF4qpoW4Awu2NPvEwXiCcHJ51GD2MHxhPkC4Ase9UYFDYsWOH2n/PfcfxwTgMFBlCCCHE3dCDTgghxJUgDxvCF+IQ1ck9Bebzzz+virwh1B0h5t4hxvCe433oo+4LhE7//vvvKr8Zud5oNYZwd3hv8b4bb7xRVeSGx967Vzj+R0V4eG7hwUcIOLaFwnIoZBcqKMTWu3dvVZUc+wKBChH66quvqtx3tCnD5yM8Gl5/vAatvlAJHhXqIdx9YXicEZaPgmSe4f0AxgwUxkMeO9qbwYs7ffp0dSwhro33WwWt6JBWgMgD5OJfdtllyssNz/hHH32kPPWvvPKKEtieQJRjf5CjbVRvBxCxGB8w4OBvHCeE4SOKYNeuXX7Dx50AjjXqBqCwHNr1Ic0BYwhRGBh7wdoHEkIIcS8U6IQQQlwJvKAomIWibd6iDbnSyE2GcMRv9OQ2QEEzhHijwrlRddwbCHeEyaNi+bp165S4hWfXEEYPPvigErIoAuddURt54/BcY/9gKIAoRLgy8uQhvOzAEP4QcShoh++B4mjYL1QJB/g8CFrsC8QtvLFXXnllbuVwbxA9AM8/9htFyt555518OdNjx45Vz8MYgPZm8FLjO2K7dgAvOaquo34AhDqOHcQpCtuh7RgiAbxBtAQ86wjtRwszT6666iqVNgCvM44Tjg0iDBA6rtOGL1pgP3EMcKwRsYG6AgjfR3rC7bffHu3dI4QQEkbicjwbgRJCCCGEEEIIISQqMAedEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gAo0AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBUKATQgghhBBCCCEOIDHaO+B00tMPSU5OtPei4BAXJ1K2bHEed+I6OHaJG+G4JW6FY5e4EY7bgnWerUKBHgRcPLyAIg+PO3ErHLvEjXDcErfCsUvcCMctCQRD3AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBMAedEEIIIYQQQmKQ7Oxsyco6Ge3diCkSEhIlPj58fm4KdEIIIYQQQgiJIXJycuTgwb1y7NjhaO9KTFK4cDEpUaKMxKFku81QoBNCCCGEEEJIDGGI82LFSktyckpYhGRBNXxkZmbI4cP71P8lS5a1/TMo0AkhhBBCCCEkRsjOzsoV58WKlYj27sQcyckp6jdEevHipW0Pd2eROEIIIYQQQgiJEbKysvIISWI/xrENR34/BTohhBBCCCGExBgMa3fnsaVAJ4QQQgghhBBCHAAFOiGEEEIIIYSQqLJu3Vpp166VfPPNl3kez8g4LjfccKX8738j/b732LFj0rFjG7n33jtNfeaYMW9Lnz69xUlQoBNCCCGEEEIIyUdWdo78uWW/TF21W/3G/+Hi9NPryPXX3yxvvvmapKXtyX38zTdHq37uvXvf6/e9v/02S8qWTZXly5fKtm1btT/zuutukhdeeEmcBAU6IYQQQgghhJA8TF+bJl3fnS93T1wmT/ywWv3G/3g8XNx2Wy8pU6asvPzyMPX/n3/+IV999bkMGjRYUlIK+X3fL79MlbZtL5BatU6XKVMma39ekSJFpESJkuIkKNAJIYQQQgghhOQCEf7Itytl9+HMPI/jfzweLpGenJwsjzzyhPKIT5v2kwwf/rxcc8310qhRE7/vOXjwoCxYME+aNWsu557bRqZM+UH1Kwf4jRD2vn3vzhPW3qNHZzl69EieEPeTJ0/KsGFDpHPnC+Wii9rKI4/0kz17dkukoUAnhBBCCCGEEKJAGPvL09cFfM3IGevDFu7etGlz6datpzz77JOSlJQkd955T8DXz549XfUiP+usVtK2bTvZsWObLF26OLfa+sMPPy4rViyTmTOnycaNG2TcuA+VEaBIkaJ5tjNp0meyePEiGTnydXnvvbFy9OhRee01/3nv4SIx4p9ICCGEEEIIIcSRLNl2IJ/n3JtdhzLU686sVios+3DOOefJ119/IfXqNVBe9UD8/PNPcvbZraRQoUJSv35DKV++gvz44/fSrFkL9XyNGqfJTTfdJq+//pqUKVNGLr74UmnV6px829mxY4ekpKRIpUqVVNg7wuoPHDggkYYedEIIIYQQQgghirQg4tzs68xy9OhReeWVl5TARj75okUL/b42PT1Nliz5U+WfGx7z88+/QGbMmCbHjx/Pfd2NN94qiYkJsnnzJrn//v4+t9W16xVqe127dpJ+/e6TuXPnyGmnnSaRhgKdEEIIIYQQQogitViyra8zy+uvv6Jyx4cPf0UJb+SFe4ptT6ZP/0WysrJUrjpatOHnyy8/V/nls2fPyH3dvn17JT09XT2+du3fPrdVq1Zt+eKL7+Spp4aoivBvvz1a+vXrk5vPHiko0AkhhBBCCCGEKJpVKSnlg4jvCsVT1Ovs5o8/5su3334lAwcOUhXW+/cfKPv375N3333T5+tRSO7MM1vKBx+Mz/358MNPpEqVqirM3WDUqFMeebRxg5jPzMzv/cfr58yZLR06dJQnnnhGRoz4nyxbtkSJ+0hCgU4IIYQQQgghRJEQHycPdTg94Gv6t6+tXmcn8G4PHfqcXHrp5dKyZWv1WLly5eXuu++XL76YIKtW/ZXn9Tt2bFfF37p376Haq3n+dOvWQ7VoQxX2WbOmy/z5c+WBBx6Sm2++XTIyMuTDD9/L9/lHjhyWV199WRYuXCDbt2+Tn3/+UeWzlywZnjx7f1CgE0IIIYQQQgjJpUOdVBnWtUE+Tzo853gcz9vN//73imp15p0j3r17T2nQoJES73je4JdffpJSpUpJmzbt8m3rssu6SmJionz//TfKe37DDTcrr3rhwoXl/vv7ySeffCwbNuStVN+jx9VyySWd5bnnnpIbb7xK1qz5W4YOfVkSEhIkksTlRDqo3mWkpR0SHqHIERcnkppanMeduA6OXeJGOG6JW+HYJW4kUuP2xIlMSU/fIWXLVpKkpNDyxNFKDdXaURAOOecIa7fbc+5GTgQ4xsZ5tgrbrBFCCCGEEEIIyQfEeLhaqRHfMMSdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gAo0AkhhBBCCCEkxsjJyY72LsQsOWE8tqziTgghhBBCCCExQmJiksTFxcuBA+lSrFgpSUhIlDj0/iIhgw7lWVkn5dCh/eoY41jbDQU6IYQQQgghhMQIEONly1aUAwf2yoEDadHenZgkObmQlChRJiyGDwp0QgghhBBCCIkh4NktU6a8ZGdnSXY2Q93tJD4+XuLjE8IWlUCBTgghhBBCCCExBgQkwtsTEqK9J8TVReI2bdokd9xxhzRv3lwuuOACee+993Kf27Jli9x6663SrFkzueyyy+S3334LuK3vv/9eOnbsKE2bNpX77rtP9u7dG4FvQAghhBBCCCGEuFygI/yid+/eUrp0afnqq6/kmWeekTfffFO+++47lZAPkZ2amiqTJk2Sbt26SZ8+fWT79u0+t7Vs2TIZNGiQes1nn30mBw8elMceeyzi34kQQgghhBBCCHFdiHtaWprUr19fBg8eLMWKFZPTTjtNzjnnHPnzzz+VMIcHfcKECVKkSBGpXbu2zJ07V4n1+++/P9+2xo0bJ5deeql0795d/T98+HBp37692ka1atWi8O1ILJCVnSNLth2QtMOZklosWZpVKSkJ8ayKSQghhBBC9OGakrhCoJcvX15eeeUV9Tc85osWLZI//vhDnn76aVm6dKk0aNBAiXODM888U5YsWeJzW3h9r169cv+vVKmSVK5cWT1OgU6sMH1tmrw8fZ3sPpyZ+1j5YsnyUIfTpUOd1KjuGyGEEEIIcQfT16TJCK4piRsEuicdOnRQ4evwenfq1EleeOEFJeA9KVu2rOzcudPn+3fv3m3q9f5gy8DIYhxvpx13TKSPfLsy3+OYWPH48K4NpMMZnFALMk4du8SaV2Px1gOSdiRTUosmS/OqsevV4LglboVjl7gRjNcpK3bIQK4pY5q4uBgV6K+99poKeUe4+4svvijHjh2T5OTkPK/B/5mZ/1mePDl+/Lip1/ujbNniFvaehIqTjjsW66NmLfD7PK7BUbM2SM/Wp8XsIp64c+wS82Dh9Mx3K2XHgeO5j1UqWUie7tJALmlUSWIVjlviVjh2iZvAmvKZd7imJC4V6I0bN1a/MzIyZMCAAdKzZ08l0j2B2C5UqJDP96ekpOQT4/i/cOHCpvYjPf2Q5OSY3n0SgsUJN1snHfeFm/fnWax7g93E8z8v2SpnVS8V0X0jzsGJY5eYj5Tx5dXA9X33uEV+vRpu9rhz3BK3wrFL3MifW7imLEjzU0wIdHjMkVOO1mgGp59+upw4cULKlSsnGzZsyPd67zB2gwoVKqjnvV+P7ZgBkz4n/sjjpOOO4h26r3PKPpPo4aSxS/SByEY+YCBenrFezq9dNo/4jpXaFBy3xK1w7BI3sYdrSuK2Nmtbt25VbdF27dqV+9iKFSukTJkyqiDcX3/9pULXDVDdHT3OfYHH8bzBjh071I+/1xPiD1TWtPN1hBDngUq6niLbF7sOZajXeYpz5At6v8/II8TzhBBCiAGirLRexzVlgSbeaWHtDRs2lMcff1zWrVsns2bNkpdeeknuvvtuadmyparEjl7ma9eulXfeeUf1Or/yyitzw9f37NkjWVlZ6v/rrrtOvvnmG/n8889l9erVMnDgQLngggtYwZ2YBm0v4BELRIXiKep1hBB3YiZSxvC4w3MeiJEz1qvXEUIIIQApUKhrEgiuKYmjBHpCQoK88cYbKk/8mmuukUGDBslNN90kN998c+5zEOE9evSQb7/9Vl5//XXVOg0sXrxY2rRpo7zkoHnz5vLss8+q10CslyxZUhWbI8QsCGdFuGog+rev7ZqcU0JI6JEyVjzuhBBCCjZYK6LoaCC4piRxOWg4TvySlsbiI5EuqpCaWtyRx91XrimsnJhI3ZRrSgre2CXBgae767vzA4puXO/f3NlSLZymrtotT/ywOuh2h1xWTzrV910rxQlw3BK3wrFL3DxuJ/6+MV8f9IK+psR9GEbttMOZyhiOKAK3GiqM8xwTReIIcTKYMNvVLhszkwchJH+kDHLHdbwa4axNEUuLFEIIIflBRxAUHeVcH1sFV+2CAp34hAtE3+AYnFmNbS8IiUWwCBjWtYFWpIxRmyKQx7104STZfShDtdXRnUO5SCGEkIIB15R5C656s/vfgqu4L9tx/3OTtmGIexAKYuhUNBeIDFkjboVjN3bQvYm/NmuDjF24VWubOnOov0WKgV2LFE84bolb4dglboTjNrT0Mrdom1BD3B1VJI5En4LYNgiTAzxcyCnF72BVl82+nhCnwrHs+3j88vce9X/HuuWUd8PXogBzoa4415lDWRWeEEJIQSMSBVenu1DbMMSdmF4gIg/bjBXLySElZi1qDD8lsQLHcvDjUapQojxyUR3peEY503Ol2TnUzCKFIZGEEEIKUovTWevSLd377NY22N6iLftl4Zb9ykveomopv4b8UKBAJ2FdIDpZBJjNeQn2+t7n1pDbW1V3jPGBkGjne7n9eOw/flIe+26VrDzrkPRtV8vUXGl2DjXbh50QQghxO7qFVKes2i0PtKtleo1tp7bBWuH5n9bIweMncx8bI1ukZKFEefziM2xdNzHEvQDjHd6KYkZ2LhCdHFJiNpxU5/Xv/L5J5dGE43sxFJnYRUEOpfZ1HekcD4SyG2HvdohkX+8PZ1V4QgghxIkgqhbRasHYd+yEpTB3u4zfhqbxFOcGB46ftF3X0IMeI5gNI/cXzmnXAjFc4fJ2YdaipusxC4cH0slRCMR9FNRQan/XUfcmlbSu7eHT1kn7OqlqvgpVJPt6v05VeBTKwesIIYS4d41+UZli0d4lx4B76qUNKsini7YFfW2aBeO4HcZvnL8R09YG3cbI6fbpGgr0GMBKHrW/cM5g6C4QnS4CzFrUzE4KdhkfwhmK7OTaACR8FMRQ6kDXESJfdDCs95ivdMS02TnUbB92Qggh7lyjV5q6Rvq1q6WMvkSk3elltQR6qgXjuB3Gb9z79xw5EfSzdh22T9cwxN3lmA0jD6W4kZkFotNFgFmLmtlJIdSKk+EORca4QDj+3ROXyRM/rFa/wxWeT5xFQQulDnXO8zVfGWLa7jnU6MOOxYT34qGg1QUghJBYXaPvPHBcBjq0eng0MER0ICpYjCDTuV973pd9pcKZ0Sp26Rp60F2MlTBy3VDtUoWTZP+xE3kuDAxg3QWi00WAjkUNz+MY4yItUyTJtMcs1Is0XFEILBBWsIEnOBhuDqX2jgzB/1YLugWarwwx7e0ZwbG7uG45mbp6d77HdeZQPI85m9EthBASm2t0w62CgmPFkhPCUgXcTYQ7gqxDgPu15305UCqcLnbpGgp0F2NFwOmKxv4X1JLyxVMsLxCdnk+pMxlknMyW+75Ynvt/Cc0cfbsu0nBEITi9NgAJLzj/o2asD/q6By1USnUCvm6uJVISbNm2r/kqkJi+r21NyyIbr4ul/H9CCClo6KzRUXAM60zWFdIX0VYJZvwOlgqHtcTBjKyAn1GhmH26hgLdxVgRcLqiEeI8lAWiG/Ip/U0GaJeAioz48cSo3Kh1kdpgfAhHFILTawOQ8KIbQVO6SJK4DX8312DXqsFFdcvJzx6V2nXnK39imiKbEELchZ21ecw4TxjBGJkIsgQ/92Ud51Ucmp4HoX8H+3QNBbqLsSLgIunZDrc1LByTAULZB0/5O+B7CiUlyFXNK8uYeVvCanwIx7lyem0AEl50zytaLiL3yi0h1qHmmeM6wlwQSKD7+sxFW/bLwi37BfftFlVPFY9bvuOga44bIYSQ0Dvm+BL2VqIoGcEYHeP2Eg3nBZx2d51bQxWz8261Fo4+6BToLsaKgIu0Z9sN+ZSek4HqBx/kIsXzk5bu9PmcncaHcJwrp9cGCAesVv8fm/cf03rdyJkb8tSgcHr4nW5kgD/6tqspo2au1144YSGH3EHPm/QY2SIYVZ4lG51+3AghhFivzYP1xQfzN+cTbZj7+7Wvbbp2ESMYne28qFaqsPx0zzn5jPPhqCFAge5iMWBVwEXasx0Oa5gv75UdF4juReopXjx58IJath4/u8+V02sD2A17yOe9Zr5aut3S+HZ6+F2oER8v/bIuaJtJY+EEK7q/Ode7n4LTjxshhBR0rNbm8WWo9Zz7H/tuldx0VlUZu3Crqf1hBGPk0XVeQNdhDJxdo7T6Cafuo0B3uRiwKuDc4Nn2hz/vlR0hJqF6jkdOXyclUhJl39ETth1TO8+VVaOOlQko2p5rVqu31sfTjeF3oV63wcS5wbQ1e+Sn1fph8E4/boQQUtCxUpvH3/rCm5/+3iMvXl5fXvxlrU8hH+sRjOFeC2bZsG2cSxSBC4Yv51Ug3XfhGaGtLynQY0AMWBVwbixiFGhSNDxboRxrHQ9zICCAPCu/lyqUKI9cVEc6nlFOQsHOc2XWqGPF8BRtzzWr1YfHKu/U8LtQr1tdPl+yI+LHLdqGLkIIiWV0742z1qWrOdxMzRPM/f/sPaotzmMpgtHsWtDsvW66DetMM+fS23kVTPe9fEVD6ZlaXKxCge4AMWDHAsyNYtssOE4jpq0N+rqR04MLL3/HXMfDbNYzhzCnlWcdkr7taolT0DXqWDE8OcFzzWr14bPKOzH8zu7rNhwEO26+5qRZ69OZokEIIQ64NyLPvFnVkipa04wxGO/TJdrdjezEzFrQrNiebtM6U7d+DYrDeW5PR/e9Pnuj9Gx1mliFAj3KYiDankangsG/eGvexapuiO6uw4GFV7BjbniYn5/6t3aLpmAgB6lBxeLSsW45R3jPdLZrxfDkFM81q9WHz8vs1PA7XLe9z62hFaoWDdKPZsrUVbt9Xm8++7cXSvSb21gQUzQIIQWXcEYSmbk3Yv1yXxtzokvHe166cJI8elGdmJnTzawFYYg2I7azbFxnmikOZ1b3hbrWokCPQniMwS9/75HHvl+V73UFfQE2ZcUOeerrFfkE9IUmwsT9nRNdqxt+iiUn5AlXD5Xh09ZJ+zqp2jcVu8J31ERyKEP2HTuhbgLbDhyXr5btCLpdK4Ynp3iuC2K1+kh4mZ0eflfd6ybqFHDJj5q5wef15rd/e5BFXUFL0SCEFEzC7cgyc2/c9e9aShd/hlZv+gUoMOzGNCfdtSCKPZsV20tsXGdaXStGwrlDgR6F8BhchL+s2SODJucX5wV9ATZ9zanFqq9qyGbChNDP3BuzVjdc2HbmtWJS1xWmdoTv+Lqp+cPYLjyQEDkY0xD1OnhOVE7xXBe0avWh1h9wS/hdsIWKbiVWf8CAZWbxpUt2ju/r7fnL68mrHsLdDAUtRYMQUvCIVMoctnFdiypa68x9RzO114bXtqiiFdWF+46vCCu3RtnqrvHQicms2E6zcZ1pda0YCecOBXoUwmOys3N8es7DvQAL1QoX7kreKsd8+rp84twT7z7D/hg85e+QPcLhyGvVmTDsCN/RrTDqjeeNBAXudPCcqJziuQ5HD/lYwbP+AIwww6atkyOZgVM5KhRLkf4d7G/BGAzP+WPL/mMBIz/MtJHzR89mleSLxdu1q7oHI9h89cT3q7XmM92oLEJiETd6EEnoRDplrt3pZbUE+ocLtirPeCCMrkLYt6+97lu6EVYg2vV8rKJrLEebZLNr59I+HHBW15k6a8WqJVPkp9W7pfy/Qh3v0dF9oQ5JWwT6woULZciQIbJhwwY5cSK/92HVquBi1M2YDY/BglgXM57GQDexUK1wkajkrSOgdRezviYw3WMJ0fLnlv25xxEtMkbNXJ9n33BYvb1idk0YoYbvmKlKGQgdkeJtWWxcqYSUKpzkt0+8r/eEir9xb3cP+VjCiBB5d+6moOIcNK9aQtbsPqTSPgzjVbjRiQDxvM6xIAq1jdx7czdL4aR4sYtgU0Qo4tw7KstNbW0isZ8kNghnG6NYIVavo0inzOmsXwyMsHXcd9BByKBoUoJcf1YVuaN1DXUOMH6Pn8y2FGGFbUc6ytaOsaRrLIfhv0XVUqpNsu7aefraNK1i0WbWmbh/BupX/+fWg+rHW8N0qlc+YI97KxrBdoE+aNAgqVOnjvTv318KFSokBREz4TE6F79ZT2Ogm1gwKxzCmm9vVd3vRWglVz7Ye17sUj9f6zFdAX1OjVKyeNvBoJOe9wSmeyxHztyQ5xzhOPZrX1uFvxqTFvqc60RBWJkwQg3f0a1KaQeeXmhjDAYb33Z6rnUK/tnVQz7Yjax5VXeFy2P/J/zp/+biyZR/e3/jRmp4BuwycPirXm4mAsRK4R5/HDsRfF5xEkN/XisZJ7Jyrfu+Kr/b1e7RznBLt4ZuEueENw/v2kCuDqGNUSyI3li+juwKZdY5l7rrF2+gwTxF/ZETWfLN8p1yerli2tGy/vAU/pGIsjU7lvwdV92Czt2bVNRKJa3w773NTGSomXUmvsfU1bu1XuuZnqb7nqgK9N27d8tbb70lNWvWlFhj2t97pGThJK3JWTc8xm5BF+wmFswKh7BmhOD4ugit5MrrvGcQJq3Okqequa6Anrtpv+jiOYEhx0fH8+09QeM4olUaDBGd6pfPfTw+Ps5ULq+vCcPXBBdqmHg48ru9rcreXmididNuz7Vublo4WhD6u5E9272RnFWxmDgR77GG/610KcCiwa7wOl/HsVzRJMnMMmd6Nlu4J5bA937qx78DFiSyo92jnbmgTmjFGClh5hah5zR0IsFenrFeera2xzDnRtHr5OvIDuxImdM5l1ZTAkGgThuRuMo//XOrulZCjWwzO5YCHdcTGs4zozK6bjoi0IkMtZKOZ8WpFWp6WsQEepcuXWTy5MnSp08fiTWe+2mtHM44qTU529XGyIwFSOcmFswKF6gvIRZ1ZkSw7nsgkmFZhMg1Ps/u42eAhZHufpkxRODv4skJqsgF8mgQqgMR+9L09QHFrGeUAdIdvL31F2m0YgtkvAlHfnf/C2opD52vRabOGET0wZe3ny3JifG2LHRRBDBa7dwC3cjuGbdIXUOo1h9JgokAXzfTwomhHZeR0/WPrxkvudUwdYyxcMwfbiJYteBQ2j3adb05oRWj91yChRaiooLVOYhVoefm8OYFG/dKnZLJBU70OuE6Cje6a0Jcu1bPJY6PHSmBvgi3gAOz1u9VP6FEtpkdS8GOK6JydTDWqthnpJJ6r4cr/Lt2xud+tnib1r396UvOkLNrlBYzWHFqReLc2iLQ77zzTrnyyivlyy+/lCpVqkicV9b/xx9/LG5HZ3LGwA2Wk6AD5tLnO9fXutDsDmd+/qc1Ks8UE6OZSQsD3Erus+dFjx9cjI+GKKS9KVU4UZ6duibk7WAxgEmibJFknwu574rtUguvKXe3DuoxeW3WBp/jBNsb/2fwKIwH29Xye9MNh6ED4tyfF1pnDMLLt3zHQcuebDMV6b3P1zXNq6hjpevJ8n4d8tKw78Zi/oWf1gT16pwfwUVRMBHg72Z67GRot5hdh/XC6+zykuuMUbuLOnp7pMNV5T2SeLZ7NMZ6xtaDknQyK1eoel8fduaCRrsVo9m5xKowc4vQcyq6i+YP5myQ7g0rSNPKJdU87dlS1LOoU6yJ3mhfR5EARtxjJ4JHeb0ya0O+Fra65xLr3Vgw6oYS2WZmLOloA0TkmqmMjrkSdZ48xXmpQony4AWnor26vjtf+xz9umGvaYHu1Ha7tgj0AQMGSJkyZaRjx44xn4PuOTl7L+SxsAlVnIPnL8+fn+0Pu8OZsRhF729cHGYqGeP7WzEWeN9AEEptN5i0jtiUV+pZadPqwgspAKGOk0BVLO2uPh8s1SLcrdVCCT/D+Rq/cKsynCFfKJgny9fi3UxBwBwbFkVmQmKDiQDUehg1Y72Ei2Dn1N/+hVrMLdAYvevcGjL2jy1y1IZr/prmlaV5lZK5UTLZ2SIfLAhe0MbJGO0esaALJFQ9rw/da3fBpn1BBVE0WzGGMpeYEWZuEnpODdfXXTT/tHK3+vHXMUE3YgHfTcdL5xTR65SWpuHCzLXq65xo9+Heqp8y6QbMRLZZGUs6xxXP4z78doD2ckaEsL96Vfv/Tcsyy5RVu+WBAA4sX4QretcRAv3vv/9W3vPatU/lCYTCrl275Pnnn5d58+ZJSkqKXHbZZar4HP5esWKFPPfcc7JmzRpVlO7xxx+XZs2a+dxOTk6OvP/++zJ+/Hg5ePCgXHTRRfLEE09I0aJFQ9u/fycCX4sbs/cpb++MlRzdcFl+zIhzWKoxwHGhWSFPH+0j9l8gdolzXfwtvLAAWLRlvzw35VS+aCgEm1CDVaW0M9XCjjwxf15reENQtC8UcI36i1YwRCzG8My1aTJh8XZbKnH6Oz9WQtH9LTB1RMDwX9aF1eMb7JyGK3TQm26NK8qMf63wdt5kYdxBwZ9o3Ljb1Cwja/YcDstnoz1bsHopngZH3Wv8/flb5Pu/TkUS+buPRasVY6jj0Ywwi0XvZqTD9c0umv1N055ht9VLFdaed50uep3S0jQcWLlWvc+J7jnKiUSscgTRjWyzOpZ0jyvyy4N10dGpV2XVAG3m+4ejpbJjBPqZZ54p69evD1mgQ1T37dtXSpQooYT1gQMHlAiPj49XYfS33nqrXHrppfLCCy/Ir7/+KrfddpvKfa9cuXK+bX322WcyevRoJejr1q0rL774ojz00EOqmF24FjdmF/JDL6+vcrBDsUY7wfJzSf3ypqqkB+yjXdR9NxOdhZeVEO1ABDvWZqpS+kM3p0lnDAbywofqtQ4VFCy0+7O8zw/Ox5h5m1T6wlGPtmY6oej+IjN0UwvCBYqxBIqsiGQ3ARS6DAfwwh89EZ259Y/N+2RE94YSHxcnv23YKz+u2m26wrA/sC0zBkfUj9C9z3gbvrzvb9FoxWjXeITBsCB6N6MRrm/3otlzjtCZdwOBFLdoE+p918lYuVa977m669FmVUpEdL0RCczOK2bGEs6NDjj+WAP766JjR10oO+dVoy3v4B9XO6aTiy0CvU2bNkpI//TTT1KtWjVJSEjI87xu8Tj0UV+yZInMmTNHUlNPTfYQ7MOGDVP/lypVSgYPHqy2D2PAb7/9Jp9++qkS3t6MGzdOCfjLL79c/T906FA5//zz1WfUqmWtiq2VxY0/IMPhhTdbrMeJlp+KJVKUAMGFhx7CZgY3RKDnDQStqiqWKCQ7Dx4XN2Pk5GNi0vFWmQE3E39FUcyE6gUjJTFeTa46XNGkklY4kzf+FkeRvFna/VlFkuLzjGl8R3+TvmfLjleDRAoYkRkA42ramjSJJl0bV/D5uDHuw7V/jSoWkxU7D0usk5GVI/dPWpErJhC2h+P68+rdMmnZTsvbxVVoRujD4PjF0u3S74LaploGeRu+8D2MVJNwtWI0opQ8C3ca1Y3tEMOI5klJSggqRmPJuxntcH1/nQlCIdQUINzraqUW9TsOIpEKoFv92k0pFAZmr1Vfhghd59VTP/wddXHuLz3DKmbnFTNjyaxhyFcXnXBH16VanFdxPRdLbqjSfGNGoM+YMUPq16+vwtPx44l3wbhAlCtXTt57771ccW5w+PBh2bJlizRs2DCP+IdnHILeF3h906ZNc/8vX768ypPH60MR6HYVCcLF6F3F3CqG5cdOD63ZPN8xczdJq9PKmLY8wUiBQiDGMRg9e6Pscrk4NyzsZgpbmMFXBfxweOqxjWChQsE+L1DaRiRDoCMJvK7GmNb1zui07IBQ+mD+5nzFCYMRzFtplXfnbpaJi7fnibKwO1LEF39ZFOd3tK4mifHxpo9ftPH0UoJQDR85Fud4FPZLSYiXjCy9Od570esv1cSOVoyYS3BtfPzHljz3oDGyRRmNbzq7mjStXEJCBdeRjsfYrd5NX8IyWuH6odQL0CWUFCB/RolIpgL4W/vZ3dI00pgVWL4MEbrOKzPpnHbxwuX1pGalUrJ++34VNfrn5v3y7rzNEYlsC3Us2WEYCmd0XYUQ51WdvuyuEuhjx461YzMqtL1t27a5/2dnZytPeOvWrZVoX716dZ7X79y5U/bt2+dzW2XLls1jLDh69KgKmff3ejPh3HZ6Q60UdPAFLh6jFUGgQmbhAv2Uf7aYg27c6F7/daMtOdNOIJA32S5w3JCnalQYh1HA7s8NZMkOtoBCzt/trar7Hdt2TdIlUhLktlbV5dXZG8UpGOdmxLS1tooms+cXNytU/Dfj+bRaORZEIpLHqqehZpmi0ql+eTVWMPaQs/6Zj5oDTgXdA3RaZoYLuwv7eVM0Kd5SK0bMQ+g+4s/LCsGO8GbME0WSEuSoRlXoYATzGLvRu+lPWF6oWbBWp0CgLpEy3obibPGXyhasaKevtA871n6RKt4XCbD/uF6xrgzGdS2q+DVE2FmLxyzYr2lr9vgUuxeekSqpqcVVe0DkwNuZ6oIe4FbPve5Y0hHzgaJIwpna0z/EedUJUcm2CvSvv/464PPdu3e3tN2XXnpJVq5cKV988YX6/4033pCJEydKjx49ZO7cuTJt2jSpUMF3mCWKy7399tsqP75q1aoqxB2cOGFtQsbAe6h9bRVuZadANwo6nFXdt+UZg3zx1gOqeFoZVDiPE9mLNjhFk1U4uOdATEyIk7IuzOHGjW7h5n0y/s/YEOeRPG6d3porhzVuYlbBxOorCEZnAYXiWre2rCZLtpwav95j1q6CgLiJVypZyDFWT8+w4HCLmmBgzmp3elmVShJOcffiT2vEGVlbwccy5knMt/jBfI5IADcQTXEeCVDMc+gva6XVaaV93t98MX2NvpdVZ7FvVpxhDHneoz33G4twiAPc1zyjCfCVbjizqnreKfg7jphPddc7RoHAAfAUh/jdIlm/IhRwzo37o8490Vfahx3Hy5jTIo2/sR8q+D7XtKiiNTcjxRJpM74+345aPFbBfRdtwnwdH2PMGL/tSnWBUUB3XvF37nTHEj7ngtPL+twG5pMRPox9xlgPV2pPyUKJKl3AROC23+82vGsDGRLA8Osagf7aa6/l+T8rK0vS09MlMTFRmjRpYkmgQ5x/9NFHMmrUKDnjjDPUYyj4NmTIEHn66adVSP11110n8+fP9/n+e++9V4W5d+7cWe3HtddeK/Xq1ZNixYqZ3pcyRZPk6S4N5LImldWgrjR1jew8cNyvJ8dswYkVe45IRny8lC9eSFrWLJM7wUxZsUOe+W6l7Dhw3O9+DenWSO2XQc1KekVsnMbHf26Leh6QGwmnOIex56JmVX3ecOeuT9cKe7z83QWy10OIQ0jjWrqkUSWpXdm+BdjQX9bJreeeJq9OW2trLlcopIfx3ATD8zjjXIVb3EUjTFAXjN6KJQv5HMuPdmkkny/dIfsD1HQgkeO7v3apH+8x7Avci0fNWiDRAvfshTsP57tHG/sNxi3cmm8+gscMj59Xr7zf7xZJdI4jLhvsd7C5FfeEgd+ulDvOO006NqiYZz1jhj9cYjSrXbmU8oTq3hO91zh7/vWsv3ljC0eMBTP4Wp9i7D/Zub6ULpoiuw8dz7emNbNtYx4IBDbrGTHqPWfonJNwUMnjfnNJef+pNWXLnho7F5UpJiW/WyUHQkxF63pmtdzxaOXcBZpv/eH9/bBtjGnvucJzrOPYBNNRVsA6B/NPv451pE+HOiEZi3qWKaZqjkRToMfloHR6GDhy5Ig89dRTKk+8d+/ept4LIY7ibxDpENi+xD9yyocPHy5bt27NZyDw5NChQyoPHsL8nHPOURXg27dvr70vjZ6eKoczTp0gWFRg/YF1CIPAH0O71FfixEqouWFlAoE+wxOE0t54dlWVHwcLrh1eO0QMXFy3XL7e0U7jztbV5L157u5L7FRgjX2og+/ODC9PXx9SJAmuJViYu7wTnjx9J9DvgloRTzdBvu3NZ1eT21v/l1qAvqBPTM6bHlTQMOZuXwSbz82A3q+f/rnVVm9tQcffuVu4eb/cPXGZRItgfX6DRa3gXv9d71b5PH7h8EgGIpzH0YqHGO1aHw1TdWdvkuLj5IRFz4D3+QtlnsV669teLV0Tlm5mzjQ7BuyYj405w+w5sateS6D7jfzr4YU4373noCzacqqQ8JfLdkjGSetxaL7GkK/5BJ8V6PgG2/dA4POCremM/Qy2H6ESanSK1XkRn4uiydVKF1bfFcaIqHrQfYF+4/fff7/ycpsR6GiNNmHCBBk5cqRccskluY+jLzpap8GjDnEOuwJarcEz7guId/RKv+KKK9T/y5YtU2K9efPmlr/TyzPWy/m1yyqLj6/Kop5tqTBQx/2xxbRYNizQ2JYuv23cq37s4KpmlVV4h5Evcl/bmrl5JPM37dOyakaSb1fsshzabBghYiXv3W4wxn2Z7zC2f1wZ2jgwriWn5PrYDcbWlU0rW5oDQgH5thANOG1G/j9yHgsqxpzcvk6q33637f3k05mtHo1zjvz2JpVLOKYKbCyAUMmiyQmSfiRT5QxjPJcvDg9d9KLFUDAvWP2CYFErGGvvz9ssd55Tw28OeKlCiXJpgwrKmBmuvGLdfFBfObW66xndNmyqL3KY6mX4wqo4N6LXZq77r8BtKPMsHDoQUnYU2Qt3BXlsH9dkOMaA7raDVT031hdm2vZi/kYNDKOmz8a9R2SMBecP5iqlE4IMLXian/p6hW0Oim6NK56Kcvn3c33NJ5i3MrMC75hx7KyMGYxhnchKvA6fEc7Uu90m5x6r8+JVzSqpOh2+rrdQQ+3DJtABirqh0Jsu6KWOPHMIeuSO79nzX9GxmjVrqmrxn3zyiSokN2bMGFX0zQifz8zMVP+jUjsqvUPEQ+yjHRv6qD/88MPKWIBWbVbBwHrs+5UyY226z+c9BxpO0IAL61gWH9HKNzTEufcEj6rUThPnxkUYzJPhryAR8oM6nlFOGlUuoYp5RTtf2Gn4ayWDsRFqSLORw+mv2Ijb+5KiUAmKXYUyB4QCimJ9vWyHamv19fIdUlDRnUd9FcfBYtGM0Iaxz2gp46R6CHaTnBAXdJFnJziOvs4DxGu0OJqZpXLm7Zpjga95AvMsIpXwE45K4Bjj6Uf1ximMBGj1BwE9ba25TgJDf14rGSeylGGlcaUSuSIoUn2RwwGKDXoWyNQtCGpGEJgV26FUkNf9LKv1AXRa8eluW6fjCdottjAxFxv3bMNI8ueW/ZYE+pHMrODdb/6t+ZAThns+zrW/+URnjRtKRwZdUYvX4TMioXNGWmwBqZsnD3GOY2VcP4gAMq4f5POHgi13uJtuuilfOzWEuP/9999y6623am8HRd8Qwv7mm2+qH0+wrVdeeUX1RId3HC3UPvjgA+WpB4sXL5abb75ZbQNF4bBP27Ztk169eimB3q1bNxkwYEDI39WfOPc1GAzxEajCbCQJFr4DCyL6a3u3B9OxukWTaqUKnzrOU//WDi3F4gqLgfiup85TseQEU4txTPqZJ7MdnXtrB7jZe09udlXgNLbjSxxhEYcia3aHiCME3GwrQLN5+49ceLryymLChoUYnqdvVuxUi/pIotPWqiCge4P27teK82dGaONYw9iH8RyrkSEAx/LnMPW4N0M05147xLnnHKsT2urZbs8OkW6mJaJn6yIIF7Mg8uGpH//2aXzFNdavfW1L/cidwPNT18jBf9MgQ8FbEJgV2xAGvrp16IwbM59l9f6vI/zsrO794Fcr5LnO9bXmYhRz9P6eun3UzX4PI0ogHCtq41zDix8KVjsybN5/THush7OSu+64C2SUMtMq09/188hFdaSnRk2AsOagw1PtTXJysjRu3FjlfbsZzxx0Xd66ukm+hR6seQs275PPl+xQFrZoAKEQKG84Wu0oQsU43phUzIaWomfkN71ayquzNpjKqcbNLjsnx5TFP1oh9fA0wcBitb3QhXVS5armlXMnLyzQ7MhZROSDEd7pa7JECKuxqLODTnVT5dcNe1Wf8nBQKCFOFj/dSY4cPKp6VXtP2MHC8pxiZIhFvOdkXY+R2V7MuMa/ufNUHiDei+r2TjDiPdCupizfflCmBzEw6xLurgBEb4xZxey4NsSdXXO/HcBxECtRb97n1GwLUyM1IFDUmb9xE+yzvIV9KGNgyGX1VKtLf4RjfHU8I1XdjwPde60eGzP3GwMnXUOB0Emv8byH6rb5NVIJwuGAMTPuAhmlDIcR8uQD6YJg7WWLpSTKimc6SVQ96H369LFjMzGDd24cBvbZNUpLfHycfLggegIYOZX+ehci3DucFmwMfGB32KenZd9KaCna3KHFm25ONfLMHr2oTu4Na3LNXVr5/0WS4qVvu5pStkiynEQO96rdeaIZ7BJvvvZ3QIfaMiiEImEIZ8SP5+RlRwivZwi9v/xLO5n6d3i9fsezcqTDyzOlY51Un0YYu87vXefUkFds7vl+e6tqUqtsUXWT/WrZjpgLz/a21ut6jPylYOhY6/FehPXaaWSyKqY/Wbg1ZsSMWwqfhsuI4c8jFMjg5PlcmSJJ2j3GjbUBvsvUVbtVXq5TiKXx7Nm7WaddG8KZv1q6Xa5oWlkO/ZsGYWXc6HyWdwRSKJ7lYGHD2Dbu+3YaNX/RiPbxd00Z878ZQ6vnmtSf48EN+EuvMb4PxKv3OlaHeuWLyRVjFkR0jZHqIzrFX1tJPO49d3tH/Rj93nFdIOI4XEQviSuGQWn+lKQE20KD7GLiou3Sr30tGXxJXSUWEM6Om3XOv1a9cF4wgfJi7Lqx4beV0NL+X/+lFcKPMPjve7dSeUoGqJ6vI9DhtR30/Wq/FkqcC1/haQYpCfFydfPKpr3vAzuebpvhxZi8YL1H3k0oVdw9b/7Z2Tk+v7sTPI9mQduScEZIwMhWu1xR2xf/LWuUzl2coNAZbsDwOny+JHAhLLfgeYMOdnP29hgZKRjvzv1HKyfRc55Hzm20CYdIxDYRAeMUY05SPOb/eDnuESqORWX3JpWkeqnCeQTr3eedJp3fmW9LteZAoDjh+rQjSkxF0+AEdA1MnhRKjJfTU4vIsF/Whf1YFVSMMQpD3id/blUGdbQl1TlXMFCYHVve40Yn59tbvFpdZ3kLV19g2wgLjkYtAn/rc7OGVhi0PL3K3nNkyUKhhZ9HA+PeiCjbUA2cqGdlFyU11kG+DCbBjFLe2zTEOaKQPSMKwq2bKNDDAG5mvhZ6ukUHwsW+4//lgeHGgAJSkfAmYCFnHIderavLu/PM9zgtkpyQJ4fXsGB5G0GsWDx18+u7NKqYR5yHak02LJTNqpaUjnXLycqdh/yKu4ysbJXfqpuGYBwfTGB2n1/PRUGonn/c/IdN068IW9BBLYv7J62wdZveNzDPXOxYEOie38+Kxyg3Cqp6aS2B7jnPhzI/hAr2vrjJSvRma39826vVqUX+oQxlmI6WkEPGx4nsbFX8s2vjSgHDMlGgLJz76RllhXGEwk12n38zBierwNgxZ+M+y+8ngbm8YQWVlhcOA44/vNegZop6eYKx/eLl9dW9W/da8nSmBAKFe1ee5X8tFC4gpv2ha2i9qG455RAJdL0fOO7eFpyROie4Zx7OyAqYlmmEyn/8x5aAofXe485qkUNjrkWhTGN74Xa65lUbxFawEMSC0Hux5gSMAlLhXjji+8IjZwzuzxZb87p6inN4nmGl9FfwBI9Pvqu1ytW1Eyz6vDGsyaEAQXAsMytolXxUiQ32GnhYX7+yscqnwnEI9wRijG7vY43JE9ZGHeidiS7+Fk5Omq/s+n5mPEZWjodhDMC8D+s6CjehJ2o0wLUZzuKkWOznVq0vnuKI6xjF22D0hAfEX87kH5vDJzphIECUlXFvsuP+4A2MrmYMTsSZfP/Xrogb7hCp54mu08hXiPComevzXPNYl91wVpV8cyTmRDOFDTGmz6tVRq5tXlmKpUTO2wyR9+7cTSqVA3O32bU71l4//22uDaEOBa1Nar8LainD75OdztCquo86RhhfgcadcT/GuQ1l/vdeG4Tb6UoPehjBhfrB/FN9To1CcY0qFbetUE+kwcIgJTHe1ASExYlRMMmu8HZ4nj0rsPsCF+5NZ1ezzTodKDwrt1q/iSry3hf9pW/PC1o8UCfnDgtyHG9jcRqpqI2k+DgZcWVjtQAwwkkxkdkRBu+Zx9+qRmn5/Z99WlWPSWCKJCXI05fW9XsNWQ1ldAq4BJ7vXD/P97PqMdI9Hlg0IITPO6S4eEqCHLIwN3ieK6tFHsOB93wY7fQtnSgIM1XLrXLj2dXyRVn5q2OAlKlLG5aXyX/tNtXh4dp/DZ9YcMID64QUg3CSkhAnGQ7uIuMmXpm1QXUYsVKp2sDfWg7rsvELt8nzl9dTtXas9GH3V4sGqYCI0jHb3s8snutFz7xrnbn/pA1jtHShJLm4fjmpXLKQEubo456Vk6NqCDmhE1QkwNjBPXTUTN+pmTgul9Qvr/QIdJXRMcu7E5Bn+0Y7533Pe124I+RsEegHDx6U999/X5YvXy4nT54U78LwH3/8sRRUYJXDzRdtltx+gWFhAG84jA7BqjV6hqCHy8ofrH0Sqpx+9q83JVSChWdZadXmiZ2V/c1OIHgeV+yeECYZGCaWbT+Ypyq7zmdjskULHh2Qxz9jXXiMW5jsr2lRRcugUye1iKxNOypuR0fwmS2SFkmC5Z89f3l9FS5ph8co2PEw5jvgaxGnK869vxOuD9SRiI+Lc5ShxHs+LF3EWV4e77xZOw3Egc6dES3mqzgUQiNfmv6f1/FwZpZ8vniH6c84rUyRfK1QYxmKc/uwkk9utoDdk5NXK8NooGrtvggk/GHoR3RKJPGuSRJo7m9SqbgtrSdh3EBBaeN4DJ7yd4G5zg2CVYPfd+yEz+J13m1SwzXve64Nwu3EsEWgDxw4UInzLl26SLFixezYZEzhxtZl/nIOAYpeBAKLSuSGGJ6EUHI+QumriYsHhXpCuXj85br7wkoV+XBgdgKxq4DfhEXb1ALVTNE+o4hdtI8ZRFHNskW0zh/EuXdVz1juEY6x36ZmmYgU1jJD10YVfRo+sZB74pK6+cS5VY+RN/6s9WqfglR0hcDyFXqOxzFX+fMCACwOkeYSzerV8PAMvChvpXssgrBfTsMwVIZiIC6RkqAdFXV1s8ph99ZjzAcqJhqrxMp86wR85ZMH6u5jVPDHfIRrKdiYxnnCGEXXIjNh7cGuUaSvRPse6Wvub1yphFz61lxbPmvvvykIusLSzPzkBnBvDqYvdAq7gnA4Bn2tDUKNoA27QP/9999l3Lhx0qRJEzs2V+DAgjJak48ZMBnpiG1YuFCIxxDO4Qx/DLZt4+Ixu7C9o3U1VRTKTHiWE0KCA00g/rx+RpRDqJXB8V5vg4nOZzvFO/jKzA3S74LaWgvgWFksBjNyRaqwlpV2Wf4Mn5hLh/68Vo0r75u2WY+RP3xZ63UquuIaeePKxurvhVv2S1ycSIuqpdS2jM/0dy5CjdIJhG6xRxQahUHNOLaR8Ex7gloXxzTvlYah0oyB2FsI4nvqguKnMBih+KrdRnl87xvOqiqfL3Z/0UYrxMp86wR8RQf5Ep5IV/M2nkMQ2mn8NQiXEydcUQeeczTmfbuEmWEECSYske9+TfPK8lmMzQfoaGAlLXXoz2tVpX3UQjHW7FbGVNHkhIDRrP7WBuG6N9si0CtUqCDx8aw3ZxU3iHOjMA2KHpkVzuHMg9bZtnHz0QnNNwRAr3NO0xbm3p/1Ypf6Muj7VVFZVASaQAJ55/C4HakAvgwmwT4bzznBEowbMUJ1nRrSHS50DGh2GNlgHe/auKJMXLzddLoPjJiPdKyjbsDwWKCPaiAwlv1Z1nWMRlbQPUbwkiD80whlDKXIk12ULpqs2juZ8VpgnrOrhaMuuuLcs1ifmaJA3nO22VaPRvHVcHzv9+aa734Sa4Srt3xBAdGNmD994Sk8YXjzZag2c4/WNf7a6cRBxyCklNp9DQbaP7v23ZizdIQl7p/vxtB8YESQnbBYW2jfsbwdqmCEt7Itf+JcZ20Qjgha20LcBw8eLH379pUaNWpIUlLefLTKlf8L/SLuBDdFFG7YHKAVRSithqzceHX6anrefJAfXSu1qDz/05qAAkG3HUigm2A0xDlELvruYmLyVZzFl9fP7ptM+tFM+XHlLjVh4jh4WjT9fTZuSNEW557HAeIJRgN0HBg1c4PEOjpGrlCNbKjMek3zKupcWxEaMGKmJCWoMWSm96g/L04wo5EVQs1vD/d7A/Fk5/pSWHLUsShTJEmrMNHwX9Zp14+INAjNhUEWeYpur/0S65yRWkTWaNb0QJFadCmBoQrjFDm6qJ1SEBzsxZPjJTNbQiqQiusVxk0jb9cXdoYG+1pXeNdmwLxrx7yGNebNZ1eT7u8FTjOyQqD9s2tONtadTiu4GQl6NKmUW/QtVHb/a0Dufe5/9ZBCAdtBPSudqDq7I2htEej333+/+t27d+/cx+Li4lSxOPxetcq9OVMlCyXI4Qze4MELP63REtG++ioHG7iwngEznstgQtrXjcDTm+69eAvVg2Zg5wSLCqZJifFaBdwgcv1VIQ2GHTcZnApfgjbYfth9Q7LSbcD7OGBcoZporKNr5MJrMBbNehQBQr+ubFo55MWHIbbNbCOQFyeQ0cgKduS363xGOLyI8J6nSE7uPKnCNoN8hlPFOXoRv/jzWgpzlwBxrptigWsL161RgGyAi7tMmKFp5RKqSK8d9QcC5e2C9+dvts0L6N1b3FdtBsyZuGZ1x4A/sMZAKpbdNTqCzdmhVvKuUCxF+nf4b90Zqc47kULnvH6wYIv6KVc0ybb728cLNkupwkkhp+Z9s3ynEug62F1U1xaBPm3aNIlVLjyjnHz8R2wUeQsV3YvGl3DWDSu94PSysuHQCVm/fb9qMaHyoGauD5g7rdtawVMowpuOgmZ2etAMzEywwSajx/41XFhZhAS7EXuC747JMZSbmz/jp6dFs3qpwvmOtd03JO9iWxv3HpEx87aY6i8cjv1yYvimbrQIXvPIRXVUe0OzoFq14bUJ5ZgaYtvsNiLlkbArvz0QiGKye4xgb56bvCpPfuOJrMilXSEsFYWB7BIF6EVMwgfGx/Od66n8fBhy3p8ffG4NRo7F67nDGany5o0t5KmvV/jtqhAL6Uo7Dh6XkTPsLXjlK7oIKYx2taYFSClE1GKgehU4N+P/3GZq/PlzrKCYnd0Em7ND8Zxi7vMsrBuJ1l2Rxsy1badx5fjJHDl+MvTtmUnV8I7OOxCiccAWgV6lyqm+nHPmzJH169dLdna21KxZU84999x84e5u48tlOy2/FyG+lzesYEs+zIV1UsPeA9IOMOH4E4M6YaX4+5zaZaVOyWQxuvWhb6cZEe6vSI+3YLXbg2Zlgn30ojpqoRPMcKGqRAYJzQ9UQANVuL3783qCY3FF08qWbs66lm/PbcMYgM+rWrKQCov3vumGksdkHDPj3GIRqSPQ4aGI1I3SqJCLOQL9XY2UgG0HjkcsLPe6FlVMRYugKvrKsw5Zms8885ZDOaaYAzrWLWdqG5E0tIQrvx2Eq12l97VrZuwhUiWUkFscFyxQ8bNoy3559PtVEfd8n1kNEQMHgr6uS8MK8t1fu6Sg9/3G+UlKiFfz628b9kb8872v50saVZLm5YvK4q3+a5wY6weExcMLrWvk8r63herltUokuuD8smaPDPIw1NlpCMD6w665a+jl9VWFeF/nWjcFUwczczZeAweE7voJ236mW0M5q2Kx3HWuk4oNh2Ot8cvfu7UFeChRkOHArJHf0BYmaoyGT6Dv3LlT7r33Xtm4caMS5llZWbJp0yaVe/7BBx+oInIFDSy2v+/dSomiRpVLBBRXwSZ9LEZ7NK2kLdARMvNg+1qyIe1IxAtJbN53VOUge+Yee2JFFJvpb6hTpMdMdVErmJlgUWQJr/22V6ug3nyrC1eIP7TIeuyiOgFvNvBuW8HKggUTtVVLfW77l5REv5WwPdGtgeDZwzhcN8qrmlWWC89IzWNkGv3rxjz7FqZhmY92p5c1/Z6+7WpJg4rFZdi0dXlCx3TbIJmplO8LXBtmzkuoIeVWCEd+u1MrHYcizsGD7WrlHhcsuqMRlr5292Gt1ISzq5eKiEB3sjg3wLiGwQj3+kji73oOtK7wfA7GWh1xbnRxQUE1hE17VjaPpTZ3hvBQReEsREfpGgK8oyBDOf8t/r3PG9GT8Pob58YO7z/m755NK/ldT4S6fjIKCVcoX0LS0g75fU2g1ncjp6+LartNs8ABg3RnXYxuJ/Eehhhf0bSRIlppB7YI9GeeeUbKli2rxHjJkqcmz3379snDDz8szz//vLz22mtS0IBn1PBY4mLLzs7xO7EHux1jMapbIbBX6+pyxzk1Tk0sZ5ST4yeyAwrWm86qKlNX77Zt0P+4ao/68ZV77CscHXg+1rxqybB7ksyGrFhBNxdFJwzdDs8ZxFSwz3Fi7pOnp9mX2NGphK1bA8Ff9Xt/N8pArb78AXHuWSnX1z5FosBgKMIVHmzvqBYsZL9Yuj1oUb1AlfKDiXzPfc7tPRrmgo9WCUd0jpVQfWOc2jnH+2pNgx/P7eN61clRx1gwiFZxJNTuuO7MqgE7fHRrXFH+2atXyAwkJ8RJpguEtlXgicb1b6UmRSiEej3rjrGaZYrmXr/e1zFEg9VoNqeh29YrVL5Yqt/bWuf8+4qetGuax7ZX7DioXb/H7PoJkR6hGnrD3ZpWd/7WAc4Pne5J/rqdeGKsOxB1OPSXdXL0hLniwkWSE1SVfzNEw8hvq0CfN2+efPbZZ7niHJQuXVoGDBggN9xwgxQkvMNsASZAnfwh7wWqd4hNMJEBsd37vNO0PF6e276vbU016GeuTZMJAfoqms2R9RSfwHtCVVY1r9x2iPpnuzdSoT/h9CRFYjFoGGaG/rI26HEL5NW303MW6HOclvuUx9gUxdDjQDdKRMfo5jh6TvSRWBSFc6HrS4DqFtXzrJTv3Xc3kHfKe58jUfDRSeguAFExH+fCc5ziHhAuzx9a07zUtUEebwcWUEbbGye04wxGtVKFfc4PuOcBs565WBbn4OkfV0vjypFbtEIwwOkR6vVsR6cFY95BSsbnS7arMP8TLmzUXurfWhPv/P6PY+75OilZdhq2O9QpK9PXpodUv8dsIVUIX4j0S8r7bnenY+jVNVCbwfO+oTt/h5NUH9eg5/HYeuC46Xn50QtPN51G6Bnl5UqBDmF+4EB+q9DBgwddn4NuFl9CDItQnXAUTDC+FlfBRAZuXgM7nq5yRHU9Xp7bNgY9fppXK+VXcOTYXP3d1wWCz71n3CL1PbHP4RLXkVgM+uslatarb6cxIVhVa3/5+9EAVncIdCeEHge6URrbHPfHVvlt414tgRmpcGXv9Bkd4eqv8KLdi19fxxQiz4wRxWifGK6Cj05Ct0o82tl5fnecT4QGhhNvbwdCia2040SryGi0XMR+YCx6zg+oQG3F81MQwHoG97dIULrQf+mCTum0gOsL0Vv4yTyZrVLIQq0WHWkgJO+ftELcAlKy7DZsL9p60LZ0SLzm0gYVlPgLRtqR0O/9noYiI9UPnnUraa3e9w3d+TvYNhF5ZCXtQOcavL1Vdfls0TZTTkOk3uIcYb2g20bXM8rLlQK9c+fO8sQTT6he6I0bN1aPLV26VJ599lm57LLLpKDhfVGbEVgQ595hHXaIDN2Qy0Dh+IagNutJN1t1GIJixPR1cr6fiTFUcR2JkBUrN5JZ69J9niO7jQn+xiMWXE4R54al2e5UhHCEHhvbPKt6KVmw/bA8/tXyPIs1LAi7N6mk+tPjxoexF6lw3hwP7wMWOMHmimDdD8K9+A33/OZmrFaJj4QxyHuOsjIWsN/XnlnV1irSOnjuhzGOMH93fdf+fsrEPFe3qGyLOA9XpwXsG+q7xFJRL6dhXKN2zmVFk+KDGlXMpkPiHqsj0NGhyA48DUUGp5cr5jMSKNA63HvMhxJNadRvwDZQH8AKOtdgQnycilbWve7wfTCvo9I/7ldwbOoQzb70tgj0Bx54QNLT0+WOO+5Qvc9BQkKCXHXVVTJw4EApaHhf1GYEls5rw7kY1fG2oLribS2rqb6F4QITA0JXfXnGQg3FjkReqpUbyZRVu+UBH+E0doee+xpj0Q659se8f/aqfUP4s9M9o9jP0kWTpX/7Wmp/jarsaCHl3Z8egj2SYGz1aVszqDj3V3hRJ9zPrsVvQRDbkUzVCPcCw7s9YShjAV6R8X9skSMnItfmzdd+2NkLmoSG3bne4ei04G+biAg5lJEVlcrvsYRxjdo5l+nOMWY+U9cwqVNrySowcBdPTshXQBctOnXHvNUCudher3NOC6mFLu4n+A529x1HQdP7vlie+3/JQglanxHN1Ku4HENR2wBC2v/55x9JTk6W6tWrS5EiRcTtNHp6qhzOMH+DGHJZvVxPOBbuXd6ZFzTMHdXXv+nVMqoCBB6+uycuC/o6hOLrhIeEirflz/DmgWD5+N6FkSKZlwor3RM/rDb9vreubuJTnPgTT2bBMfjmzvxjTPe8Rxtdb26k8eV5DtY6rnBSvBwzIUQMYX8yK9tS7+FShZP8VvI3PIbBFha+xo7OsYjFnPBoYiYNwey1beRdm4l88me8sTIW0O4pWEVpeL9CFfG+6sUY+0xvqHOAofPHu1v7HN8QIKmpxVU1bLMrWaupPGa2if89RUEwdLthFBS8r1E71im4j0Ks6c5v/tZk/gg2f2CuRLFYq+M22GcHioAzO+ZV673vV2mPSe/7gM66wo5jnvXv90IU6o+rdueJjDAb8WtlzeMPY36KuAf9jz/+kObNm0tiYqL625OMjAz566+/cv8/++yzpaCBKqcGOLkDLgweAtW/Q3QqDluxFuKmGYmCYt4Xlqc3L5gV3Ch+F428VKtWN3/H34ylMBD+PJh2Wqbt7gwQavGWcOPvhhzM8xNvIWTMaC/z/V+7TB/fQJX8dSI+dMP9wtVmjFiLMtDx6pQpmqSK4ZQv9l+4t2fv6GD9yf3laloZC6ilsvKsQwHTbbo2rqQVShosEszbU+PUSCI3cWn9crmdXJya6hTudCdPQ70ZbjizqqPSzKIFjNc3nV1NRdTYFXpttDg1YzSxkg4ZjggNHXQj4MyMeazzdcS5vyKOVj3xVvuOn1mtlIpC9bx3DZ5ivdhdtLrAhCzQb7rpJpkzZ45qr4a//YHed6tWxU7fSF0rJwaFp6cvUNVFf5b8aKArLFFsQffCC8WCFWhBCMtWoMUffht5S3gevyMlFKzeSHSqx+oWt/Ak2M1B97wbEzHQMY74smjaQbh72esSyoIeHkC0p0IVbN2QMTv6s/s6dro3RN3XMUzdOeiMlxeuaKw6Z3h6czx7RwczNgUrPml2LATrPoJ7SqgCHXOX9z6bSU3SqdjsDWpBtK1VRv7efVhenb1RnEiohfq6NKwof26xt+5BNPNAQ8HsfRX3TnQGefGnNZZb2FltAeokEFlWO7Vovvt7KPc+o8WpGaOJVYEWaSO1zjrEypoJ1dx1QEStv7WlFedSKGHlCR73G9y7rMxDTtFklgX66tWrff5dENCxcvry9Pmqumjkh0RbaFgp7oN9DnThGYspYHfIoOeC0N/iL5SCV6Fi5UaiWz0W1TbHL9wa8Bzhez59SV3t3G2d845FhFFNFzcEX3lOvjoDwKKJMR/MC+e0XvY6hFq0pmujigGFhr8FQigRFb6OnR3th4hzCeTVeah9bbmkUSUVbukLu403ugTqPoL5x44ILu99NvMddCs2+zKQtqhWSr3XaXnuF9UtJ89dVk/Vf7FSwR7fE98tFANiLM07Zu+rAGOkTc0yctnb87QdG9gGRBIcJ573ejeL9EBROWbvfZ5rK92xdNe5NUJaJ0bSSG1nBJzn+hnnQAeMu0B4ap9g60A7ijhn/RvyPm2NtU4TdjsUo1ok7sILL5RJkyZJqVJ5T/yuXbuke/fuMnfuXIkFPG+ysHKOmLY2aF659yTjq+qikzBb3MfTUghrG8LRVPi7140CE6rO8TJDoMVUqAWv7MDsjUTXWqtzji48o5x6HRa5dm0TFn4sInwZPr4rtsuv4QPbRvssu4v9OMGrEuo+wJuGXHUrfbw9r72Ji7ebanvkvd92tR8izsWfVycxIfD8EE3jjb9FbqhRJP722cziHYWedAR6l4YVZNDFZ9gaBRMulm071XYKrQtrpRY1bQA07mGBDEJmvbtunnfM3Fc9wf/XtKii3dHAO7xYVatebS683mkEEpTec1mwloieayudex2iSFCg2C3YbUQ1U4dD9/o0tA/mQju7KHjja33q1ihNywJ9ypQpMmvWLPX3tm3bVEu1lJS8VhQ8jmrubmbUFQ1l18GMfF5ITBDFkhOC5rI4xdMXzhwaHUuhMaFatcz7wt9iKlzhPlbwdSNBVe9Qc5P8nSMj/QILR/yYiRjQOe9WDR/hENNO8KqEsg8Io0IqjHfVX7Sa8s6984dx7eH4mhHo3vsdjvZDxHlY8eo41XgTaL56EEVMZ6w3vc863xXPG4v3ckWTghqdF2zy31M4WCHJSLPr8H/rFX/Gd9zDPl+yw2fqgefcHyjMFw4Ouw3XTsVqTnL1UoW10yas1BSJJskJcZKZFTy5OdC6wXsu82VQ8nWMde51SPFA1fNohzjrYqcR1WzantnrM5w5+tNtLPDpBO1mWaC3bNkyV6ADX8Xg69SpIwMGDBA3Ayu5vyqLCB92i6fPCTk0eK9Vy7yZBWE4wn1CwftG4qt1XKh5Tsj1hiD3ro1gNmIg0HkPxfBht5h2ilcllKI1vsKosDCA1wT5d2ZuVGaOr79jF63iNsTZONl4E2i+io+LM73POt8Vzxvvu6Jp5aBeTk/R64ZK8Z7rFe97F/b7m+U784hz5OLDIOIveiqYBxTif8Hm/TJ7fbrpKKJYXk/pzunovR2JNWdKQpxkaIhqHXTEudn7mpljjNcFq43kBA9qNIyousYdf4XhoqUvssJQ4DPa2s2yQC9Tpoy8+OKL6u8qVaqoHuiFC+tZ/GKFWM/bDFcOjbew/GbFTjnqVSirSFK8HA3QRifQgjBaOZPROK5GIbyngrR0M3Oz8bd/oRg+dG4gZooJOsWrorOg99UqMFibF7OLAzOGgkDHjhXYiS+cbLwJJAKt7LOZ9+l6OT3vNU6vFO9vveLPqIBiZmiLF9/1VGi7lfOGfP5wtD1zEmbv+6GIrnCsOe0S57ogQrVxpRJhOcYYZ8HWGk7woEbDiKq7Lg5UGC4a+mJJGKJGoq3dbGmz1qpVK1mxYoXf18ZqmzWnhv65AVycmCD95fBBnFvtZR7rhpNoRQyEYvjQzcWD18tXpwNPMC6c5FUJtqD3Frw6bV7Mni9dQ4FOZVJWYCexYryxus+679O9hyAs3OxCEu0VE+PjbUsJ08HfeiUSaWOcd+wTXaFEdjmFw5lZcsWYBWEp6ut0J040jahmOjk5iTTNc3XOaaWlUaXiMmbe5oDduJyg3dhmLUZD/5yOzg3/p7/3yFd3tJTlOw6aWlwVNMNJpG42oRo+ghXNQ85ov/a1pVBivJwqVeR/XKCNm5OuK3y3C04vKxsOnZD12/dLatG8Y9VKb1yz58vf8UWe67UtqmjntRPiVBFlxctqdZ913qcrhCCykdqFa1T3uq5Zpqh0ql/elpQwXfytV5yWNlZQsCq67C5CiHBm1CCINOEq6hurThw7jKhOXz9n+bkH6J6ruf/sk+5NKsnznevLY9+vcrR2Y5u1GA79czK6N3yIc7M3/IJmOInUzcaOiRvXQ3Z2js+JEdtFqGQwnLoQxHg6p3ZZqVMy2W/dinCfLzd6OXWJ9RBYEphots30hxkhZHiYzV7/3td0mSJJ+YpLhkqw6JpY9Di6hVCiQBBtZkertYEdTw9adBEFTgslJYTFkGR3PrjTRWg0jahOXj9PD3APwPjQjRrBePrmzpaO1262tFkD69evl/Lly0vx4sXl119/lenTp0uDBg3kqquuMrUdtGZ7/vnnZd68eaoq/GWXXSb9+/dXfyOM/rnnnpM1a9aoAnSPP/64NGvWzOd2ULRu9OjR8vnnn8uxY8fkvPPOk6eeekrlzttNLC+Kw0W4b/gFyXASqZuNHRM3RNaomXq9NWN1IRju8xVtL2dBEWckcjihbaY/8Lm9z60RvFjcv4ZFK9e/9zVttu5FMFIS49UapqB5HN2ClTndjlZr8JxDnOM3WrcGais4qFNd9TscxQ/tNso7WYQ6ASeun6cHuQfAGHX8pP+6Vb7Gk9O1my0C/bPPPlNt1j744AMpVqyY3HPPPdK6dWv5+eefZfv27fLAAw9obQeium/fvlKiRAkZP368HDhwQInw+Ph4ufPOO+XWW2+VSy+9VF544QVlBLjttttk8uTJUrlyZZ/79MUXX8iIESNUf/bBgwfLoEGD5M0335RwEIuL4nB6tSJxw3f6xWcXkbzZBAujDrTIs7OQh5sXglwcxI44I+HHSW0z/WGmWJwd13+wBbRZoYRtBBJAsexxjFXsuNd2qlcun+fcaOXqT7QFSmNzklHeiSLUSThp/ZylcQ8wGylijCcnazdbBPp7770nw4YNU63X4OGuX7++egyF5Pr166ct0Dds2CBLlixRue2pqacuDgh2bBv/G0IbvdVr164tv/32m3z66afy0EMP5dsWWsDB+459AhD4vl5HouPViqTX16kXn1tvNp497WFRR0E3/MCD9PWyHX7PPybZPzbvC/nzY2EhyMVB7IgzEl7ckP9sJWw91Os/2ALarFAK1nOaRkV3YYegnbB4e77HDHGO/uto8eYt2rzHJQokBip0eHnDCvL9X7uiYpR3kgh1Ik5ZPy+JwQrtERPoCEs/88wz1d8zZsyQa665Rv1dsWJFOXLkiPZ2ypUrp4S9Ic4NDh8+LFu2bJGGDRsqcW5Qt25dJeh9ATE/c+ZM5XUvWbKk8rTDcECc4dUKdMPH1Ih7AG/4zr3ZzFqf7vOm6+/8+zLmWCVWxgUXB7Ehzkh4cUP+sxWDsx3Xf6AFtLH9zxZvk1EzN4S8YKVR0V2EKkC8PeXe4J7+QLtaPser97j0VejQs8vJgk37ohad4RQRSiI3t1co5g4njy0CvVatWvLdd9+p/G6EtHfs2FFOnDgh77//vtSrV097Owhtb9u2be7/2dnZMm7cOBUuD9HuXYxu586dsm+fb4/cfffdp0Ltzz//fCXqIf4R9k6c49Xyd8OvWLKQ9GtXS9rzhu/Im43Z8+/PmBPoZvxgu1oqVz3WF4JcHLhfnJHw4ob8Z6se5nBf/9j+Nc2ryPiFW20RQDQquodQW60FEudmDaPBxg2jM0gk5/buTSq6YjzZItAfeeQRefDBB1XO+PXXX6/Cz5GTjhz0t956y/J2X3rpJVm5cqXKJQdvvPGGTJw4UXr06CFz586VadOmSYUKFXy+d9u2bVKoUCH1+RD+w4cPV/nsMBqYIc7559DRXq2zqgeevC8841R7qsVbD0jakUwpVyxZOjatKvv3HQ5YCZu44/w3r1oyqJj35iGI8DNS1Y8xLtC2DNty8qRqzBWcM6IjznjcY3Pc4rrXERr7j52I6nfAvWx41wYywoen0JjTokFiQpwM6HC6DAwggLB/eJ3u9oLd1yOF08duNNE57yishUJy3uMVgjpQQTgD3Js9jz2M9/7u2YHGjVOvHTeP20Dnwm0017wH6FKtdOGIzBmhfkZcDiqz2QC83YcOHVLh5CAtLU39nZSUZFmco+jcqFGjpFOnTuqxSZMmyZAhQ+T48eMqXL1Vq1Yyf/58+fLLL/O8F1+pffv2MnDgQJWHDnbs2KEegxe9adOmIX/fgsw3S7bJAxN8pxZ48uq1zaRbsyoR2SfizPNfvnghue7deVrbrVSykDzdpYFc0qiSDXtJYgEsMtoMmy47DxxXaS/exP0bcfPbIx1cu/ggwflh2Xa595PFQeePaI8DjNd569Nl7oY0NTrRdrF1LWfUR5iyYoc8891K2XHgeO5jnHNjn2DnHWN2wca9svvQcXW/blmzjPpf5779aa/WaozrfI4OvvbFCdeO24jFa33Kih1yz7hF6u9QRavnuHUytrVZgyBH5XW0W8vKypKaNWvK1VdfLaeddprpbaHQHIq/QaQb4hz07NlTunfvLunp6aqlG7ziVatWzff+vXv3KkGOHHWDSpUqSenSpZVn3YxAT08/FFOeXDusainZ2dqvS0s7ZNriVLZs8Zg77rGEmfO/fvt+rdfCYv9il/pqLJodM06BYzc8IN3Fnxco59/n9+09HPH9ihXcMG7jT2YFfQ0Woz8v2Ro17+70NWn5PIAT/9isvJhO8ACeVbGYfH3H2T7v/5xzYxed816nZLL6AZhLaxVP0qqpgNdhGxj7vuZoXJN3j1skd51bQ3ktddac3vsSi4Rz3AY7F4hUcMJ8ZGUcD/MTZXFx3XLaVdw9x22kznNUBfrChQulV69eShCjLzkEOh6DYEdIuVFATgf0Lp8wYYKMHDlSLrnkktzH0Rcd3m941CHO4SVHq7Vrr7023zbguU9OTlbGAoTbG6J9//79PgV9IHDxxMrEb1cvYTMFcaweu1g67m5rgWfn+cfn64DFQ6yc81j5Hk6hfZDiVHiexzu2x62ZWgTR+A6BiqYOdFArwPi4/DnvTj3nsTJ2nYDZ847X6+SF43Uns3KUaAqEZ0HZUoUS5ZGL6kjHM8pJQcfucYs1X7Bz8fKM9XK+S7uetK+Tqvbd17q2UeUSWoWIjXHrhvnCFoE+dOhQufHGG/O1MUMPcnjBIbh1gKBGnnnv3r2VqN+zZ0/uc/DIo0L8J598ogrJjRkzRuW8w6MOMjMz1f8oVJeYmKjy1NGeDV5zCHb8Dc9548aNpSBiZy9htlwpOMaYUM8/Jk/ckPcfPxlwm/uOnWAlbuIXFqcq2Di5UBxbAZJYRLdqv9kWWFgLPPbdKpl+xh55rvOpqDliDwWh60mCn8KanmuEWevS5cdVu1VdEjcXGbZFoK9du1aJcW+uvPJKGTt2rPZ2UPQN3vc333xT/Xjy999/yyuvvKKENkLbIbaRo160aFH1/OLFi+Xmm29W24CXHAXh8HoYDTIyMuTcc89VxoK4AlhNJBwLCLZcKRjGmFDPP8bTpQ0q6BWcYSVuEgBWvC+4WGljFikKwqKYFEx0DKNW79s/r0mTBZvnyuMXn8H1ok0U9K4nCf+uEfCDFoBuN+jbItCrVKkiy5Yty5dvvnTp0nw9zQMBzzl+/HHBBReoH1+gYBxEvEFKSoqqLo+fgk64FhD0ajmPSHpzdM9/u9PLagn0aLZJIoQ4FydHbRX0RTEp2IbRUO7bB46fVNd073NryO2tqnPtGMORRpEmIQYM+rYI9DvvvFOefvpp2bBhgzRp0iRXnMN73r9/fzs+gjh0ARELF0EsEWlvjs75d7L3ixDiDpwatcVFMSnIhNpvHbzz+yb5etkOW1LwCjJca0WnLpOjBTryvcG4ceNU2Dm818gZf/755+XSSy+14yNICHABUXAIpzHG6uTmZO8XIcQ9ODFqi4tiUpDRub/rYGcKXkGFa63o1GUKF7b1QY9VUIrf7UcIwqrru/ODLiC+ubNl1C9clAhITS0eE8c9Gvy5Zb/cPXFZ0Ne9dXUTUx50OyY3X9uItvfLTjh2iRvhuA1f3Q8Dio7wwLHrHHzd363glLWom8dtrK+13DI/G+c54gIdxdzefvtt+fnnnyUpKUk6duwot912m/o7loiVid8tCwjecJ1njLFz7LgtxMgMHLvEjXDc2gMXxZGHY9dZeN7fN+07Ku/O3WxpO2YdCG4jEuM2ltdabnFQhirQLYe4v/766/Lhhx9Kly5dVFuz9957TzZv3ixDhgyxvDOk4OXvEWeHONlddI41CwghsYgTw+8JiSTe9/fjJ7Jl7MKtprfDgoqhw7WW+7tsWBbo33zzjYwcOTK3qnqnTp2kV69eMnjwYCXYifPgAqJgYKcxxs2TGyGERBIuign5j77takmDisXluZ/WyNHMLO33sR4SsQs3d9mwrKR37twpDRo0yP3/rLPOkpMnT0paWppUrFjRrv0jNsMFRMHALmOMmyc3QgghhESPjnXLSfs6qfLB/M3yyZ9b5VBGYKHOgorETlJdXCTbskBHDnpCQkLu//Hx8ZKcnCwnTpywa98IIVE2xrh5ciOEEEJI9Ncid55TQ25rVV0J9bd/3+T3tQW1yjgJD81c3GUjPto7QAhx/uQWCKdOboQQQghxllBHCp73ugLrCKcUKyaxV5cpEE41CoWULD5mzBgpUqRI7v/wnn/88cdSsmTexXqfPn1C+RhCSJRgX01CCCGE2AXrIZFI0sGlRbItC/Szzz5bli9fnuex5s2by+rVq/M8Foc684QQ1+LWyY0QQgghzoP1kAoe0Wz91sGFRiHLAn3s2LH27gkhxLG4cXIjhBBCCCHRZfratHxOHqQ5IEIznE6eLBf3g2c/NEKIFrR4E0IIIYQQM+LcV5okxDoeD1ftgelRMgrYBYvEEUIIIYQQQgix1YMNkRyIkTPWq9eFwyiw26t6u2EUwPNOhwKdEEIIIYQQQohtILw8UIszsOtQhnqd240CrhPo6JdOCCGEEEIIIaRggNxvO1/nVKOAowT6sGHDJDMz8AFYsWKF9OjRw+pHEEIIIYQQQghxGSjMZufrnGoUcJRAnzlzpnTr1k2WLVuW77mMjAwl4K+55hopVqxYqPtICCGEEEIIIcQloGo6CrMFAi178To3GwUcJdC//vprOe+88+T666+Xl19+WU6cOKEeX7BggXTt2lU+//xzeeKJJ2T8+PF27i8hhBBCCCGEEId3/0HV9ED0b1/b1tZnzaJgFHCUQE9JSVEC/N1335WpU6fKFVdcIY899pjccsstUqdOHZk8ebJcd9119u4tIYQQQgghhBDHg5ZmaKXmLZohksPRYi0hCkaBcBCXk5MTchm7H374QQYOHCgnT56Uli1byttvvy2FCxeWWCAt7ZCEfoSILnFxIqmpxXncievg2CVuhOOWuBWOXeJGCuq4RdV0FGZD7jfCy+HBDqdInu6jDzqMAhDnkeiDbpxnqySG8uF79uyRZ599VqZNm6byzdu1ayfPPfecXH755TJkyBA555xzQtk8IYQQQgghhBAXAzF+ZrVSEfu8DnVSpV3tshE1CtiJZYGOHPOXXnpJypYtKx9//LGcddZZ6nF40IcOHSq333679OzZUx599FEWiiOEEEIIIYQQEpNGAUfkoD/zzDMqx/ybb77JFeegSJEiyqs+ZswY+f3336Vz58527SshhBBCCCGEEBKzWPagT5o0SerWrev3+XPPPVe+/fZbGT58uNWPIIQQQgghhBBCCgyWPeiBxLkBQtvhTSeEEEIIIYQQQkiYBDohhBBCCCGEEELsgwKdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHIDjBPquXbukb9++qp9627Zt5cUXX5SMjAz13IoVK+Saa66R5s2by9VXXy1LliwJWMTO18/XX38dwW9DCCGEEEIIIYSEuc1aOMjJyVHivESJEjJ+/Hg5cOCAPP744xIfHy933nmn3HrrrXLppZfKCy+8IL/++qvcdtttMnnyZKlcuXK+bf322295/v/www/lxx9/lAsvvDCC34gQQgghhBBCCHGhQN+wYYPyis+ZM0dSU1PVYxDsw4YNU/+XKlVKBg8eLAkJCVK7dm0lwj/99FN56KGH8m2rXLlyuX9v2bJFxo4dK2+99ZYUL148ot+JEEIIIYQQQghxXYg7RPV7772XK84NDh8+rER2w4YNlTg3QMh6oDB3g9dee03OOeccOffcc8Oy34QQQgghhBBCSEx50BHajrxzg+zsbBk3bpy0bt1aifbVq1fnef3OnTtl3759Abe5fft2+f7772XChAlh229CCCGEEEIIISSmBLo3L730kqxcuVK++OIL9f8bb7whEydOlB49esjcuXNl2rRpUqFChYDbwHsbNWokTZs2tbQPcXGW3kYsYhxvHnfiNjh2iRvhuCVuhWOXuBGO24JBXIjnNy4HldkcKs4/+OADGTVqlHTq1Ek9NmnSJBkyZIgcP35c6tevL61atZL58+fLl19+6Xc7nTt3lmuvvVZuuummCO49IYQQQgghhBASAx705557ThV/g0g3xDno2bOndO/eXdLT06V8+fIyfPhwqVq1qt/t7NixQ9atWxdS5fb09EPiTBNG7FqcypYtzuNOXAfHLnEjHLfErXDsEjfCcVuwznPMCPTRo0erfPGRI0fKJZdckvv4vHnz5LPPPlMedYhzOP7Rag3ecX8sXbpUKlWq5LMNmy64eHgBRR4ed+JWOHaJG+G4JW6FY5e4EY5b4hqBvn79epVn3rt3bznzzDNlz549uc/VrFlTZsyYIZ988okqJDdmzBjVJx0edZCZman+L1OmTG6l97Vr16p2bIQQQgghhBBCiNNxVJs1FH3LysqSN998U9q0aZPnB8XgXnnlFdXPvEuXLrJx40aVo160aFH13sWLF6vXIazdIC0tTUqWLBnFb0QIIYQQQgghhLi8SJxTSEtjjkikczZSU4vzuBPXwbFL3AjHLXErHLvEjXDcFqzzHBMedEIIIYQQQgghpKBCgU4IIYQQQgghhDgARxWJI4QQQgghhBASW2Rl58iSbQck7XCmpBZLlmZVSkpCfFy0d8uRUKATQgghhBBCCAkL09emycvT18nuw5m5j5UvliwPdThdOtRJjeq+ORGGuBNCCCGEEEIICYs4f+TblXnEOcD/eBzPk7xQoBNCCCGEEEIIsT2sHZ7zQIycsV69jvwHBTohhBBCCCGEEFtBzrm359ybXYcy1OvIf1CgE0IIIYQQQgixFRSEs/N1BQUKdEIIIYQQQgghtoJq7Xa+rqBAgU4IIYQQQgghxFbQSg3V2gNRoXiKeh35Dwp0QgghhBBCCCG2gj7naKUWiP7ta7MfuhcU6IQQQgghhBBCbAd9zod1bZDPkw7POR5nH/T8JPp4jBBCCCGEEEIICRmI8Ha1y6pq7SgIh5xzhLXTc+4bCnRCCCGEEEIIIWEDYvzMaqWivRuugCHuhBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gAo0AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBUKATQgghhBBCCCEOgAKdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gAo0AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBUKATQgghhBBCCCEOgAKdEEIIIYQQQghxAI4T6Lt27ZK+fftKy5YtpW3btvLiiy9KRkaGem7FihVyzTXXSPPmzeXqq6+WJUuWBNzWlClTpFOnTtKsWTO5/fbbZdu2bRH6FoQQQgghhBBCiIsFek5OjhLnx44dk/Hjx8uoUaNkxowZ8sorr0h6errceuutcsYZZ8gXX3whl112mdx2222yfft2n9tatGiRPPTQQ+o1X375pSQnJ0v//v0j/p0IIYQQQgghhBAdEsVBbNiwQXnF58yZI6mpqeoxCPZhw4ap/0uVKiWDBw+WhIQEqV27tvz222/y6aefKiHuzfvvvy9du3aVa6+9Vv0/aNAgueWWW2Tv3r1SpkyZiH83QgghhBBCCCHENR70cuXKyXvvvZcrzg0OHz4sW7ZskYYNGypxblC3bl2/Ye4LFiyQiy66KPf/atWqyfTp0ynOCSGEEEIIIYQ4EkcJ9BIlSqi8c4Ps7GwZN26ctG7dWol25Kd7snPnTtm3b1++7Rw8eFAOHDggWVlZcscdd8h5550n99xzT773E0IIIYQQQgghTsFRIe7evPTSS7Jy5UqVcw7eeOMNmThxovTo0UPmzp0r06ZNkwoVKuR739GjR9XvIUOGSL9+/eSBBx6QV199Ve666y6Vjx4fr2+XiIuz8QsR7ePN407cBscucSMct8StcOwSN8JxWzCIC/H8xuWgMptDxfkHH3ygCsWhEjuYNGmSEt3Hjx+X+vXrS6tWrWT+/PlKdHuyZ88eadOmjdx///3Sp08f9Rg87fCkwyPfokWLqHwnQgghhBBCCCHEVR705557ThV/g0g3xDno2bOndO/eXVV0L1++vAwfPlyqVq2a7/2lS5eWpKQkqVWrVp7HUGQOYfFmSE8/JM40YcSuxals2eI87sR1cOwSN8JxS9wKxy5xIxy3Bes8x4xAHz16tEyYMEFGjhwpl1xySe7j8+bNk88++0x51CHO4fj/9ddfc6u0e5KYmKgKyq1evVq1YwOo3g4vepUqVUztDy4eXkCRh8eduBWOXeJGOG6JW+HYJW6E45a4RqCvX79e5Zn37t1bzjzzTBWqblCzZk3VE/2TTz5RheTGjBmjCsHBow4yMzPV/6jSjkrv6H/+2GOPqVB49E6HNx5/N2nSJIrfkBBCCCGEEEIIcYFAR9E3VF5/88031Y8nf//9t7zyyiuqJzpC25s2bapy1IsWLaqeX7x4sdx8881qGwh7h/cd1dwhzBES37JlSyX+41iVgRBCCCGEEEKIA3FskTinkJbGHJFIAvtJampxHnfiOjh2iRvhuCVuhWOXuBGO24J1nmOiDzohhBBCCCGEEFJQoUAnhBBCCCGEEEIcAAU6IYQQQgghhBDiACjQCSGEEEIIIYQQB0CBTgghhBBCCCGEOAAKdEIIIYQQQgghxAE4qg+6E2Hb9Ogcbx534jY4dokb4bglboVjl7gRjtuCQVyI55d90AkhhBBCCCGEEAfAEHdCCCGEEEIIIcQBUKATQgghhBBCCCEOgAKdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gAo0AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBUKATQgghhBBCCCEOgAKdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIUOTk50d4FQgghpEBDgU4IIcSVPPbYY1K3bl357bfffD7/66+/qudHjBgRcDv//POPel2rVq0kMzPT0r506NBBHn30UbHK1q1b1T54/tSrV0+aN28uPXr0kC+++ELsBvuL/TaYNm2aPPLII7n/z58/X+0HfkeKI0eOyBtvvCFdu3aVZs2aScuWLeXaa6+Vzz77TE6ePCnRAsfK+/x4/9x0003y5Zdfqr9xPgkhhBArxOXQXE4IIcSFHDx4UDp37ixJSUny/fffS5EiRXKfO3z4sHTp0kWKFy+uxG1ycrLf7bz88stKnG7atElefPFFJQ7NsnLlSilWrJhUr17d0neBoLvwwgvlnnvukQsuuEA9htszBOvnn38uU6ZMkWeeeUaJVbvYvHmzOk4NGjRQ/0NggrFjx6rfeG7dunVy+umnq+8Wbnbs2CG33Xab7Nu3T+3LmWeeKRkZGfL777/LhAkTpGnTpkq845xGGhyrvXv35v6P/cA5Hz16dO5jOEZlypRRr8UxDTTmCCGEEH9QoBNCCHEt06dPV6L25ptvlkGDBuU+DjELYQtxDk+0P7KyspQgvuaaa2Tx4sVy7Ngx+eSTTyTSGAIdBgJ4zD3Jzs6WSy+9VOLi4pRQDxfeAj2SYCly9dVXy549e+TTTz+VSpUq5Xke5wbn+JJLLpGXXnpJog086gsWLFDjjxBCCLEThrgTQghxLQjRhqd83LhxsnTpUvXYn3/+qURe3759A4pzgPD43bt3K5EOzzneC6+xJ3369JHGjRvLhg0bch/73//+J/Xr11cizVeIOzz62F6TJk2kdevWMmDAANm1a5el7xgfH68+a/v27bmPHTp0SIn5jh07qn27/PLL84XBr1ixQm655RbliUao/K233ipLlizxGeIOcY7vgh8jrN1XiPvy5cvljjvuUOkALVq0kLvvvlvWrl2b+7zxnrlz58rtt9+uvN7nnXeeEtUwhvhj1qxZsmzZMnn44YfziXOA/cd3+fbbb2XLli2yaNEi9TkzZszI87pVq1apx3/++Wf1Pzzww4cPl3bt2kmjRo3UWPnhhx/yvAfH4IUXXlDbx/nyNPSYxTvEHccYxwsh+jhX2D6iIDZu3Kj2HfuDY3TVVVepffdk4cKFcuONN6rnEeqP9ANPLz4hhJDYhAKdEEKIq3niiSdUaPFzzz2ncsgHDx6s8pchjIIxadIkqVOnjhJvF198sRQtWlSFU3uC7SF8/umnn84Vvm+99ZYSoBBO3kDkDxw4UG3v3XffVbny8+bNk4ceesjyd4SgM8Lnjx8/Ltdff7189913cuedd6pwa4hwCEvslxGejudKly6tjAmjRo1S0QE4JhD33uC7ISwbPxCTDRs2zPcafIfrrrtO/Q1BO2TIEBWWDsG5fv36PK+FQQL7hP2B8eC9995TEQ3+QL0AGCIgpP2BdAaAdAQYB3A8Jk+enOc1MIyUKlVKbQde+fvuu0+dT4TOv/nmm0ro9+vXT77++us87xs/frwydOBYXnnllWIn8P7DgASxDqMKjlXv3r3V33fddZeMHDlSHUccM4M//vhDGVQKFSokr7zyijz++OPKeIIoApx/QgghsUtitHeAEEIICQUIMohoeLohmuG9hABLSEgI+D7kOiNEuX///ur/woULy2WXXSbffPONEtP4H6SmpioBC2EHkfnRRx/JGWecIQ888IDP7UKgQ1hBhBl5yNhHeJ8hGhGq7g+EsxvF0PA3vO4IOV+9erX6joaXds2aNUp4QnCCtm3bqvdBYEIwo/Advh8EHcQsqFWrlhLfyGv3zuP2zDOHccNfrn6NGjXknXfeyT22bdq0kYsuukhee+01efXVV3NfC48wxDE455xz5JdffpGZM2f6zaHHOcMxCpTrbhgoDO80IhTef/99JVhxvHFs4R1HGDyO+5w5c5Twh3EC59U4TjBUoHAgDAeJiaeWQZUrV84jkO0Exxsiu3bt2up/CG2cuw8//FAdG4D6B8OGDVN1FUqUKKGOdc2aNeXtt9/OPdbwpMNIAaPSDTfcEJZ9JYQQEn3oQSeEEOJ6IBIhwuB5hNCCkAwGwqWNHHQII/xgO/jtHQaNbXfq1EmeeuopFWINgeevCNjZZ5+tRCAEIIQWQpUhZGFACCTOAbzg8F7jBx5dhEVDkCPPHnnyhsCrUqVKrjg3gGBFSDdC/REVgKgChKBjnxHyDUMDQsgrVqwoZjl69KgyMCAX3tPwATHZvn373FB/A+99w2diG/6AuDbEsj+8n8f3xTaNMHeEvSMNoFu3bup/hNnjeMObDuOF8YOQduS6e4bmI4UgXJQsWTJXnAOcB0NwG8A4ATD2MHZwDo0oAGO/q1WrprYDwwMhhJDYhR50QgghMQG8oxDWgcKkPYHwNQqweQMPZ8+ePfM8dsUVV8jUqVPltNNOU95Nf0CcwssMD+kHH3yg/oYog1g2CrH5AyLeqOKOkG94uqtWrar+Njhw4ICUK1cu33sN4QeRh1B9hG0jrPvHH39UnnN4mSFekRJgtsI4wuIhFo3P8P5c77B5fJYn2P9ANWlhcIDwhDg1Ihe8gWHE8HYDGGFwrBHmjnOI3/CyGxED+/fvV59p/O8Nag8YwtyzA4Dd+IsK8PeZOH8Yl0iPwI83KSkptu8jIYQQ50CBTgghpMDx119/qbBxFJI766yz8jwHbzPCylG0yxBwEI7IGUZoO8LLEVqNHO9AxgIjnBq52x9//LHK2YbXFIXCAglVeM6DeWQREu0NvMIAeedGSLtRnA0F2BC6j+J5ELGB9t0XMBTAG52Wlubzcw0PsFXg1Ub1fITCo3CaL4wK9p692+FFx3mBgQDPGznyxj5DBOPY+0InyiIawLiCY40cdCPv3hN/BgxCCCGxAUPcCSGEFDiQxwtPJCp3oyK55w8KqcHjCzFrgFD1nTt3qoJrqKyNnGvvwmgGyCWG9x3eW4gphICjAjfwrMRuFYTQb9u2TRUf8w7ZR094GAAgVlE9HuIZIenwNCOHHSHp/vbB00vvDYQuCunBG+9ZjR3CGLnlKAgXCqj0jm3g2Bmeck8QXo9Cc0g1QASDAf7HcUb+e3p6ep4e9ijghxB4PA+jh/EDA8vrr7+em+vvNOBxR7E+dA3w3G+kLWD8eVbVJ4QQEntQoBNCCClQoNI7qn0jlNxX+DHafEHcoUo6qqEjvxpVuFH0DOLwwQcfVPndqMrtq3UYhDE89HgeYdsQsPCew8uM50IFfdJR1M2oUI5Wcc8++6wyOqAqOEQ4wroRJo3XwCuNfGzkokNQo7q8L/A+VIvHaxFG7w0K5+F5FL9DJXUYAWDgwPE0CsJZBcYBGEHg/UcVdQho7AeOH6IAkBoA0Yr+9p4YFdvhfYcRwtMrjsdhzLj33nvV8xC2CBmHoQKfh3PoVFC4EOcVxxwt6FDMEFEPOCa+KuwTQgiJHSjQCSGEFCggWCFAjcrevujevbvyviIsHG3SENputG1DCDLELsLG4dX1BsIQReRQhAw55RBb8KQj1DrUUHCAbSEEH555eI5RQA6V459//nm5//771WvKly+v9g1h3ig8B+EOowE8sP6MBKgMDg98r169ZPbs2fmeR8Vx5NSjajq+05NPPikVKlSQiRMnquMTKjCMIFceBgCcI4h+GEPw3WDswHeGEcEb5NXDUOIdGg8Rjvx/hImjGjrOn9FyDZXdnQyKCo4ZM0ZFbSANA237EAmB4++vyj4hhJDYIC4nUNUWQgghhBBCCCGERAR60AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIIcQBUKATQgghhBBCCCEOgAKdEEIIIYQQQghxABTohBBCCCGEEEKIA6BAJ4QQQgghhBBCHAAFOiGEEEIIIYQQ4gASo70DTic9/ZDk5ER7LwoOcXEiZcsW53EnroNjl7gRjlviVjh2iRvhuC1Y59kqFOhBwMXDCyjy8LgTt8KxS9wIxy1xKxy7xI1w3JJAMMSdEEIIIYQQQghxABTohBBCCCGEEEKIA3C0QO/du7c8+uij+R5fuHChXHjhhQHfm5GRIc8995ycc8456uepp56So0ePhnFvCSGEEEIIIYQQib0c9MmTJ8usWbPkiiuuyPP433//LQ888ICkpKQEfP/o0aNlwYIF8s4770hOTo4S+iNHjpQnnngizHtOCCGEEEIIIdEHOujkyRPR3o2YIiEhUeLj4wuWQN+/f78MHz5cGjdunOfxCRMmyLBhw6RatWpy+PDhgNuAuL/mmmtyt3HdddfJZ599Ftb9JoQQQgghhBAnAGGenr5TcnKyo70rMUfhwsWkRIkyEoeS7QVBoEOEd+vWTXbv3p3n8dmzZ6vnIM7hIQ9EqVKlZOrUqdKlSxf1/08//ST169cP634TQgghhBBCiBM85wcO7FWe3pIly0lcnKMzm111XDMzM+Tw4X3q/5Ily8a+QJ87d67KMf/uu+9k8ODBeZ5744031O8vv/wy6HYGDhwo999/v7Rq1Ur9f8YZZ8ibb75pen/CYBQhGsebx524DY5d4kY4bolb4dglbiSS4zY7O0tOnDguJUumSnJyofB/YAEiOflUqjVEeokSpfOFu4d6fh0l0FHY7emnn1YF3QoVCm0gbd68WSpVqiRDhw6VkydPyrPPPqv+HjJkiKnthNJknliHx524FY5d4kY4bolb4dglbiQS4/b48eOSlhYvKSnJkphI77ndFClSSI4ejZcSJVJC1q2OFugIW2/UqJG0bds2pO0gBH7QoEHy4YcfStOmTdVjL7zwgtx4443St29fKV++vPa20tMPSU5OSLtDTACLEyYtHnfiNjh2iRvhuCVuhWOXuJFIjtsTJzIlOztbsrJQJI456HaTlYUohWzZt++IJCWd8HmeY0Kgo3J7WlqaNG/eXP2fmZmpfiOXfPHixdrb2bBhg2qpVq9evdzHGjRooA7izp07TQl0XDyc+CMPjztxKxy7xI1w3BK3wrFL3Egkxi2vC/eeS0fFO4wdO1blnn/99dfqp0OHDuoHf5vBEODr1q3LI9pB1apVbd5rQgghhBBCCCGh8PTTj0uPHp1VeL43Dz54r9xzz+2qSJsvFi1aKG3anCXvvmuu5lifPr1lzJi3xUk4SqBXqVJFatSokftTtGhR9YO/g4ETuWfPHvV3xYoVVZj8k08+KStWrJDly5ervzt37ixlypSJwDchhBBCCCGEEHeTlZMlS9IXybTtP6nf+D9c3H9/P5Wq/PHH7+d5fNas6bJkySJ5+OHH/bY1++WXqVKlSlX56acf/Yp4X7zwwkty3XU3iZNwlEAPhR9++EHatGmT+//LL78sdevWld69e8vdd9+tctufe+65qO4jIYQQQgghhLiB2TtnyvUzekr/+X3k+SWD1W/8j8fDQWpqObn99l4yYcJ42b59m3osI+O4/O9/o+Taa2+UWrVO9/k+FASfOXO63HLLHbJr105ZvPhP7c8sUaKkFClSRJxEXI4ZE0MBJC2NxUciCYxiqanFedyJ6+DYJW6E45a4FY5d4kYiOW5RJC49fYeULVtJkpKSTb8fInzwosf9Pj+4xQtyfsULxG5Onjwpt99+g1SvXkOGDBkuH3zwrvz44/cyduxnkpLiu1r677//Jo899pB8993P8sgjD0q1ajXk8cefVs/t27dPbrjhSrnqqmvlttt6Ke/6/fffJcWLl5AXXxyhQtybNz9T7rjjLlWrbNiw52TFimXqsy688CK5//7+kpiYaOr4GudZCroHnRBCCCGEEEJIaCCM/fWVrwR8DZ4PR7h7YmKi9O//iMyaNUNmz54pn3wyVh566FG/4hxMmzZVGjduKiVKlJA2bdrJjBnT5NixY+q50qVLy333PSDjx3+kvOvff/+NrF+/TgYMeDTfdl55ZbgULlxEPvjgEyXeZ86cJt9++5VEGgp0QgghhBBCCCGK5XuXyp7juwO+Bs/jdeGgWbMWcvHFl8iTTz4i557bRlq1OsfvaxEC/+uvs6Vt23bq/3btOsixY0dV3rpB585dpWHDxjJixIvy+uuvygMPPCRly6bm29aOHTukWLFiUrFiJSX4X3rpVTnnnPMk0lCgE0IIIYQQQghRpGek2fo6K9x00+2SlZWlwtIDMWfOb3L06BFp2/ZUuH3VqtWkdu3T5ccfJ+d5HQrMLVgwT+rWrSeXXNLZ57ZuuOFmVWTu8ss7qoryCHmvVKmyRBpH9UEnhBBCCCGEEBI9yqak2vo6K6SkpOT57Q9UbwfXXdcj97Hs7GyJi9ugQtorVKioHvvnn1Mtt9evXysHDuyXkiVL5dvWxRdfKmeeebb8+utMldcOD/4NN9wivXvfK5GEHnRCCCGEEEIIIYrGZZpKuULlA74Gz+N10eTIkcMyb97vcuONt8oHH4zP/XnttbfU81On/qB+Hz16VEaOHC53332/VKtWXVWF98Xbb78ue/fule7dr5Thw1+RO++8J0+ofKSgQCeEEEIIIYQQokiIS5D7GjwY8DV4Hq+LJrNnz5SsrJOqQjtasBk/qMqOvHVUfwfvvPO6FC1aVL0OBeh+/nmK/PHH/Hzb27z5Hxk1arisW7dWNmxYL/PmzZE6depG/HtRoBNCCCGEEEIIyQUt1NBKzduTjv/D1WLNLD//PFUVcfNV8A1e8C1bNsvSpYvlq6++kH79BqoK8RDc3br1UAXjUGDOkwEDHpMyZcqo1mt33XWbpKamyoMPPiyRhn3Qg8D+mpGFfU2JW+HYJW6E45a4FY5d4kbc1AfdAK3UUK0dBeGQc46w9mh7zp1AOPugs0gcIYQQQgghhJB8QIw3K9si2rtRoGCIOyGEEEIIIYQQ4gAo0AkhhBBCCCGEEAdAgU4IIYQQQgghhDgACnRCCCGEEEIIiUFYD9x9x5UCnRBCCCGEEEJiiPj4UzIPfcKJ/WRmZqjfCQn211xnFXdCCCGEEEIIiSHi4xMkKamQHD68XxISEiQujn5ZuzznEOeHD++TwoWL5RpC7IQCnRBCCCGEEEJiiLi4OClZsoykp++UvXt3RXt3Yo7ChYtJiRJlwrJtCnRCCCGEEEIIiTESE5OkfPmqcvLkiWjvSkyRkJAYFs+5AQU6IYQQQgghhMSoJz0pKTnau0FMwGQEQgghhBBCCCHEAVCgE0IIIYQQQgghDoACnRBCCCGEEEIIcQAU6IQQQgghhBBCiAOgQCeEEEIIIYQQQhwAq7gHYdnepbL72C4pm5Iqjcs0lYS4hGjvUoEiKydLlu9dKukZaTwHhBBCCCGEkJiGAj0Ijy8cIEdOHFF/lytUXu5r8KCcV6EtRWMEmL1zpry+8hXZc3x37mPGOTi/4gVR3TdCCCGEEEIIsRsKdBNAKA5e9LiUSCohB08cjHnRGE3v9ewdM9Wx9ncOBrd4IeaONyGEEEIIIaRgQ4FuAU9xHquiMZre66zsLBm98pWAr8G+IZKBkQuEEEIIIYSQWIFF4mwEohFe51gQ5zA4eIpzT0MEng8ni3YvyvfZ3uB5ePcJIYQQQgghJFagB91GIBo/WjNGWqSe5dq8dBgYRq8cFfA1o/8aJcUSi8m+zL1hCX3fc3SP1usQek8IIYQQQgghsQIFus2MW/+h+nFrXvq4dR9J2vHAAjktY48MWNA39//iSSWkx2lXy42n32KLUC9XpJzW62AcIIQQQgghhJBYgSHuYSJS4eB2gn39aO17pt936MRB9b5uP3WSmTumh7wfLcq3UAaOQOB5eO7NRAYsSV8k07b/pH7HQipCLH4nQgghhBBCCjL0oIeZYMXMIl0p3d/n4XHsaygczToqzy5+Qlbvv1561bvH8vdKiE+QPg0elKd9VHE3QHSC7vZisV1bLH4nQgghhBBCCjpxOTk5OeJQevfuLWXKlJGhQ4fmeXzhwoXyyCOPyLRp03y+b+vWrXLhhRf6fG7cuHFy9tlna+9D609a5/ZB926vpsuIlq9JfFx8rlhtULqRrNy3Qubsmi2/bP9JDmTuD7vIggAfv+4jmfTPROXx9v48fLf+8/vY9nlWW9HFxYmkphaXtLRDMmtH6CLUKHjnDzdW3o/F7xQLeI5d586qhOSF45a4FY5d4kY4bgvWeY45gT558mTp37+/XHHFFXkE+t9//y233367pKSkyPTpvsOps7KyZO/evXkewzY2bdokn376qSQlJWnvx/Q1v8nuY7tyvcBzdv2aTzQGAznanqI4XuIlW7IDvsefyLLicYegG7l8aEDjQs/TrpFJ/3wm4SaYePSeuEKJMMB7r5/RM+C5guD/pP2kiBT0syNawmnfifwHb7rEjXDcErfCsUvcCMdtwSAuRIHuyBD3/fv3y/Dhw6Vx48Z5Hp8wYYIMGzZMqlWrJocPH/b7/oSEBClX7r9CY4sWLZKpU6fKN998Y0qcgyZlmua5gCAuEbIOobUo7Q8Zt/6joNvwFOcgmDj3FxpvJaw5mLfV4JdtUyUSmO1fjtc1K9vCkujF47rt2gJ9hlNC0vFdv/rnc8d8J0IIIYQQQoi9OFKgQ4R369ZNdu/OK0Rmz56tnoM4Hz16tPb2Xn75Zbn66quldu3atuwfBCCEYHZOtnyz+at8AtwOvEWWP6FtFKPz9kxDzC1NXyzDlj6n9XkHTuyXIglF5WjWqXB+X+h4/oNhp3gMJnp127CFu12b2XPnbxtmIjfYgo4QQgghhBD34bgq7nPnzlU55vfee2++59544w25+OKLTW3vzz//lCVLlshdd91laX+W7V2qxC5+FqUtlPf/flsG/zlIrpzWRbUaC4c49xZZOgXc8LxRxRtiDmHQ2L9jWce0Py+QOAdX1rxW7MAO8WiIXm/B6lk9X7cNWzjbtZk9d2a+ayDYgo4QQgghhBD34SgPekZGhjz99NPy1FNPSaFChWzZ5sSJE+Wiiy6SChUqWHr/4wsHSIIkyInsE6bErnfeuRVSC6WqHIYVmqHaK/YtlYOZB7VC2q0Ufetd/x5pWLqRjFj2ohw6eSjk7+UL43F/z5sRvePaT1Qe9WD52k3KNg34eaFg5tz5iiqwUl0/3N+JWB+7hDgNjlviVjh2iRvhuC0YxMXFkEBH2HqjRo2kbdu2tmzv5MmTqtI78tlDwUzl9pLJJWVEuxHq714/97L0eXESJxWKVJDza58jS9OWyoJ9c7TedzThgLyx+jUJBzgGm7PWSo/GXaRbw8vk0V8flSn/TLH0vdrXaaNaqQWibFn/hRX+2PmHlujdlr1BHm/9mPSb2c/v6/B8hXKlJFwcP6BnyDieeMhnMQmd7+p5fCPxnYhYHruEOBWOW+JWOHaJG+G4Ja4R6KjcnpaWJs2bN1f/Z2Zmqt8o8LZ48WLT20NoO0T6eeedJ5HiQOYBOXwoQ+WoW23LliM50q5CB7lk0qWmwppfmP+CHDkZOEw9FKavmyXVE+qoHPxHGj4lrcq0kVdWjMjTJi7Qd8b3uqdeX9m392hAixMmrfR0/9UtN+zarLW/eF1SfHLA1yzd9pek7z8gZQuFpwf91vQdWq+btfFXaV2yneXvClILlVP945sVbaWqg5LIojN2CXEaHLfErXDsEjfCcVuwznNMCPSxY8cqQW0wYsQpT/SAAQMsbW/p0qXSsGFD1ZItkqQdT5Pfdv5qSZwjPLl9pY7y2cZPTL/XijhPjEuUkzn/HfNAoGL91G0/5hZha1exg7Sp0C63inrp5DLqdXN3/+a3v3vbihdoTUh4jb/XldHMry6VXEaGLRsS8DUfrn0v3z7a2UO8RLKeJ3vKth+kQpHKUrVo1TzV6HW/6731+8oVp12l3sMJP7oEGruEOBWOW+JWOHaJG+G4Ja4R6FWqVMnzf9GiRdXvGjVqBH3v8ePH5dChQ3naq61du9a2yu1mKK0hDL1pW6GdElgNSjeSm2ZeLZGiSEIROXhS35BgFGF7qvkQKZVcKre9WUJcovrOnh7/kkmlpGOVTqqtmp3eaWxLJ7fc2F9dzFRV18XYDx0+8mEswLHT+a6GOCeEEEIIIYS4F8dVcbfKDz/8IG3atMnzGMLlS5YsGdH9sCIMweL0RbJ07xIZt/YD0+8NBTPi3JMhi5+S/vP7yPNLBqvfzy5+It9+o3XbpH8+U5EEdovHztW6Bnwe4nZf5l5L2w5WVd2KMcEshrFgzq5f1XcJBJ6nOCeEEEIIIcT9xOXkMMAiEK0/aS1HTuiHjsP7eiI7UwlXcgoI1E/aT9ISkcjZQLE05FD7GpnB+oF7hqkvSV+kjAdWGNlqtKqqDqFuhPB7hp7b0QfdzLGDUPf+3oEiFOzYb2KOYGOXECfCcUvcCscucSMctwXrPMdEiLvbQYE0wB7UeYGohFgMJHiNx/dmpEmtk9VVMbp4STAldG+pc6fcePotuUJ0v0cOvFmwf76MAVby1PFa7JtnCLvZY4dtQIjj7zm7Zufm+CNCAT+e+2XXfhNCCCGEEEIiCwW6jSCU28jPDpY3XNAIJHhRFG/Gjl8CCkqdfuA/bPlWCXTj9W+ust5ybtuRrXkKyIWap479mrzlG0k7vsfSsQMwPGCMTfpnot/9urrm9TLRR4HBcOTXE0IIIYQQQuwlZnLQnQSE4T31+0Z7NxwFBC8EorfRAv9DUPp6HK+HqAfwHOv0PsfrdF/vj9SUcvL9lm9szVOHuO7TwH8/9kAYERk6RoovNk6IWH49IYQQQgghxF4o0MMAhCEqnMNbaaVAWKyhI3iDCco9mp5nHHvkns/cMV2s0rl6t6Cebk9jAPYPnzlt+0/qtz8BDM+12TGB1yINQNfokC3Z2vtNCCGEEEIIcRYMcdcQl55F4gonFJFjWUeDvm/2zhlyfsX2MvaCiTJu7Ycybv2H4kZKJJWUgycOhLQNCF4r+deGoBy/7iP56p8vtF7/6l8vy1EL/eA9w+pR5E933z5e+74KOT/k0fM+UL63Zy45Qtf9hdL7qtBuhLqHil3bIYQQQgghhNgLBXoQxpw/Vpal/1fULDsnWwYsCB6+/vWmSeoHYu2yIC3BnAr2fUDjx+SRP6yFZsdLvDzR/FnJyjkZ0n4EErDemBHnML482vRJ1Y7Ns2Ddh2v0Pu/Vv0bI0ZNHTed74zNQMM/gtOK1tIq6bT2yVewARgEnwErzzoTnhRBCCCEkelCgB8FbTGVmZyrhGSyU2ACiC95jVHhHgS83AYEYivccxwih/k6lT8N+0iL1rDyPvbVqtM8ia77wJc49Gbl8qPKWBxM33l51X6IIomny5uBpAnESJzkSuG/H5C3fyg0e1e6jASvNOxOeF0IIIYSQ6MIcdJOs3LdCW5y7mSIJRZRg3JexN6TtQHCG0u4sXKDaubfgQN66rjjXAQaZsWs/0MpRNwxBF1a+WP32Fs84F2kZwfPwm5ZpHvQ10c5DN9rlBSsM6CR06wy4GTeeF0IIIYSQWMMWD/ru3bvlvffekw0bNkhmZv783Y8//lhiBav5uxBrt9a5U3kvfXmnft/5q/y0/UdxCkezjqr+2sBMxIA3pZPLyLBlQ8RpoK1br3r35AphCK5XV4yw/XM+Xve+fL3pizzRE1Y8krrj7rTiNWXJ3kW2bc9udCrR43mdyINIURC8yjgviPhw03khhBBCCIlFbBHo/fr1kz179sjFF18shQoVklgCXtWSSaVyQ46NlldWqFK0qnzSflK+UGYwbdtP4lSsinOE9QOr7c4KxxeWY9nHJByo1IM1Y1SIO84BzsmBE+Hx9HunNljpSa477ioXqWLr9uzGTLs8z9SSaHuVY72v/Lh1HwVNwXHSeXEjzO0nhBBCSMQE+l9//SUTJkyQevXqSawxYvmLqoq74TGDBwl/WxGdWJR557RDAMBz5Yb8dO/85mB59Xhu7u45lj8vMT4R1oGwgcr6+MH5bFuhnUSaUcuHS0ZWhpQrVC7oYh3PBxt3eL5rjR7y+cYJQV9nGIYija7n3oqH324B5EZvv9Xv+eU/Ex3fAcBpAtfM/hSEKAxCCCGEOEigN23aVDZv3hyTAt2XxwyLKl9etUCgWJq3KPLnnXMqnuIcUQX3N+wvr/01IqBI/2XbVMufd+jkIYnUuf1y0+dar02URMmSrKCF2HSAx/7Fpc+ovz0NQL4iLPBY7eKnBxTeeH9yfHLQ8enZui3S6HruzXr4wyGA3Obttwr237NNoBMjLwKd32AFFiO9P97jraBEYRBCCCHEQQL9+eefl+uuu06mT58uVapUkbi4uDzP9+nTR2IFLMrQ29xsVfa+DQfkq8odzDvnZCAuhyx5Sut1JZNLyQGbC8WhiB1E8rGs8ITA++OkhNYyzh/GYr1IYtE8reIKxxdRBoHM7IyA729d7lw1JjGusNjHot9uwWp4DLFNnM+SyaW1vP9WIgHMePjDJYDC6e13Err7XzihcFQiL4KdX++5ONyeaTPjraBEYRBCCCHEYQJ91KhRsm/fPlUkbtu2bXme8xbrbgeLsG83fWlKnKNi+AWVOpj2zsUK9Us2kHl7fre9iB2K18Ua3n3cj2UHbuVmgOOLH09xYqdn0ZfH0Iogwufb5eGH+FmavlheDlNxMxQ4dLJX2S509z8ac7mOwLWjxkOwcHVP49Qbq17THm8FJQqDEEIIIQ4T6NOmTZP3339fWrZsKQWB7UfzGiECeXkHNHk8nziPBa+bGSAczy3fVubtnmNri7qC0O7OLIY4ear5EDXu7Fj0B0vFMCuI/Hn4kTbxQKMBebyP/kRTIIOBHQII2x/916igr4NxokHpRqr12t6MNKl1srpUT6gj8eIebyiOK459sCKJR08ejbiQDMWQqWuYCRaubmaseY+3ghKFQQghhBCHCfTKlStL4cKFpaCgWyn72TOHqirhvsSGrncuVvh996/R3oUCxZDFp9IPfBmHzGAmFcOMpxrCJzsnW179a0Ru+gME4purXpP4uFOREf5EEzBbu8GMADJTG6J9pY5y08yr8+xn8aQS0uO0q+XG029xVNiyP4MHfjpW6ZTbVtFJQjKUzzOEstGlwZ+hJ1C4OqKfJm78xPJ+h6vmAiGEEEJiF1sEet++feXRRx+VW2+9VapWrSqJiXk3e/bZZ0usoFspGx6p9Ix05Vnbn3lKeHi+PjWlnOk8divgczpX7yZVi1aVfRl7g4ZngqKJxeTIycMSawTr5+5dpd7N4Hs+u/gJiY8LrQCVGQ+mjqfaEIlzds2WST4qhxvCyN/2jZxjs+gKIF2DBOYBiHNf4g0F1z5a+5589c9E6d/4UUcUAAvmJYZhRUegR1pIhvp5GGcvLn3Wb3G5YOf6i40TQtrvcNRcIIQQQkhsY4tAf/DBU16tJ5980mfe4qpVqyRW0K2U7Vmh2xdpGXsknNxY+9bcHt+GtwjiQ6cFF4rgrdy3Ijff0u4Cb5ECxolHmz4p+zL3qgUzDCUQrf6IFXFuZwGqPcf32ObxNBsq7A+zRi0zAkjXIPFw48flpeUvBN1PJ1Tp1ilqptM+Uvc42tkOTUfgBiKQEahTlcuCbtdKGo3ncbKz5gIhhBBCCga2CPTVq1dLrONdCMtfHq0dIET23PJtZOq2Hyzv6y1n3JFv0ae7WIQBwvCCpiQUclUrOE/6NOyXm2JgAI+y2XMWzPPuZPA9UUgNYeNmBROE3RsrX7XF4xnNloKeAshTPBppJoYBB8dFN6R62d7F2mMomlW6zVQRt0NI2t3uTmfOsnrdWp1fg+F9nMLVVYEQQgghsYktAn379u1Bc9TdyoDGj6lwdV+ixrNStp3e5n6NBoa0gAy0kLayWER7pUi3MwuFQvGF1ffIyMpQKQae5w6Pty5/rlwzvbv2uXKrODd4ZvETefpc6wgDK4IagghRCt5Eq6Ug9ueJ5s/mfs9gHnwcl8uqddXcun5F82hW6TZTRTxUIRmudnf+9itYilCkr9sSSSWlf+NHfH5Hu7sqEEIIISR2sUWgd+jQQYWy5+Tk+GzH4+YQdxTZ+vdr+QQLLCy8IQTtCgVXXkuN9b/V/r+6i8VIeT2LJhSVI1l524uFwvHsY/LT9h/Vj6/jgvD9SITtw7BTv1RDmbdnju3bPqNEXVlz8G+t13qKcx3BZFVQ+8t7j1ZLQexPqeRS2mMZ+4jc8WDCD+MJ1/y49R9q70u0qnSbrSJuRkh6RyOMXjkqbJEE/vZrzq5ffRoUzq/YXiun3s7omYMnDgQN82crNUIIIYRErM2aJ1lZWbJ582b53//+J/fee68UBOxcgOvmp6OVlpXQZRBssWhWpKnK1TWukslbv5U0j7zlQMW0DB5q8piMWjE8n5C0C+9c20VpCyXcFEksquoQGOLczjD5J5o9Kx0qd5SZO6bLc4uftJw7708whSqo0Ze8WGIxaVq2udp2NFtI4bPt9uDD2IPvZiY3OlpVunU/FwUkp23/KXceCSYkrdQTCDWSwNec5U+44387BHrr8ueZ6kCBY4LuBN5FQRnOTgghhJCICvQqVfK3HatevbqUKFFCHn74YWnXrp3EOtFYgCN39sLKF4dl22ZFmqpcvW6MKsx2S507VdV4zxzfW+vcKd9v+SafeDcWrZsO/6O8l+Fk5PKhysvnuQ/h4ujJvBEBhjjvedo1SlDM3T1HPt/4qent3lT7NiXOjeiOfw5tkI/XvW9pH/0JplAFNcbCgAV9c8/v1iNbJZrXpdmxDO85xuvkLd8GFFm6udHRrNKtU2QN3Qs8uzsEE5OhRNaEw1jjS7iHWlwO4eqXVO1susUaPs9XIcpQw/wJIYQQUnCwRaD7A6Huu3btkoJAqAtCpxkFrC6k4f2H0L6g0oXyZ9ofebziJRJLyvkV2kv1YjXUgtrwsAL0jEZbqnC2nVPbPiFRZdaO6XJO+fPkjJJ15ZbT75CvN08yFW6PY+ZJlaLVbD/Pdo0rQ5QUTywu4aBQQmE5HqA2AlIMGpRuJL/unGl621WKVpVP2k8KGOpt5EbD8BNo3Jqt0u0vPNpKdXQ8HyyCxTsCI5CYDDUaIZxzlvfxuad+34BdG4KFq0/Z+r3t+xjNgoGEEEIIKUACffTo0fkeO3LkiEyZMkXOO+88KQiEUm3YG3ihkYMeyNMbbq9cqAvpmTvypj2AgycPyOxdM0R2nSqA5+mlw/FDz2i3Vow3Y8CAd9nAiDhYtW+FLEibF/T9iEYIpcq6znmGqC2ZXMq2PP1DJw9JOAgkzgFSDG6aebWJwm95j4tOzrARYj1+3UeqpZfZYny6VdAhsmfs+MV02DS2Z9YLHEhMhpL+EM45y99xu7rm9fmOmy7hMBZGs2AgIYQQQgqQQJ8/f34+z3lSUpJ069ZNbrvtNikoYKEMsRVqqDbag4Fo9s4Nd0SALy8dxECwAl2xhhFxYFZQ21HAz5dgMoROJIroRQKj8BtqJOjWODAjJA2vLTzug1sMkRIlCsvG3VtUNfuSyaXVeMZrdNva+auC7ktkh6vYXyAxGUqIerjmrGDHDbU6UCwQ+77tyFb5MMypNMGIZk0GQgghhBQQgT527Fg7NhMTIPfaKt4esWj2zrUzIkDXSwcxUJDEuVkM4WhX0TNvwRTNXuXhxkwBQn9C0juEGiLcuxhYyeSSqpuF2e4KoZzTcBX78yUmrdQTCOecpXPccI6QrmAcn9OK11KFDMNVlNKpBQMJIYQQ4g7CmoNeELGy+Opeo6dqC+QrxzWavXP99R9Gbi/Ch+3A00tHz1JgEKqN1AFU3NYRXvAaXlzlMq3Q6Gj1Kncarcud69PrrVu1/EDmf622zBQIW5q+2LKYDlexP+/5DMdk8uZvgr4HaRuPNn1SpWN4FopEK0rd+cvbGIK0C7RHNFq6GdvUuRa8jw/OAboMeKaahAquKeS8extsvEEkB6q860ZVEEIIIaTgQYFuM1iAmg3Thjj3l5MYrd65xgL5RHamPNLkidwFsbFYRm6vXeHvxnZ0vXO+KmyjErW/dmMQDJnZGSF554skFJGjWUclWhROKGw6dQKC/rYzekmvevcENfJEq1e505i353f142nEsCuywJ+nG9uHRzcUJqwfp357nttQPbXeof4YIzotIC+v3k1apJ6lvtewZUMs5c17G0NCbVNoGCs8hT9aIXp3WzCD0a3C85pC28tAY8W7w0EsVHS3UryQEEIIIf6hQLeZObt+NSUEo9mCyWzBJSwoDWOBneHvaPGUFJ+s5Z3Dftxw+i3qx9vDtmLvMlmS/qdk5+RIieSSUjqljJQrVE4dX5yXUPY3MT5RJMv/88USi0tCfELYcrePBSmI5otP1n8sP2+b4lMIeC+q90Sg9ZybMLzeyF+GV9SubXp7utHL3mqlcU9QYBA/nsIP4z6UaBd4hD2Flq5H/mT2Cb/fK1g0gT9jSCjiHKQfT1f7FMzDrUvP066WW+rcrh11FKtt1wLdK9z8vQghhJBoEpeDhEnil7S0Q6J7hCB6rp/R09QC0K4Fml1ejGDeQs/91Q37tRN4z2/2sTDW4aO175v2QiNMvFuNK7Xeh32LdgGqYOcN48RXxXE70xZiCbuPy6Bmg+XCyhervyEYhyx+KmTxGeh8h2IA8BZaCFHvP7+P1nuDebyxbc+8cKvzZ7QY2Wp0wMgmfBekLTyz+ImAue7exyEa3ui4OJHU1OKm7nVm7xWEOGnsEhJNOG4L1nmOugd97ty5snz5cjlx4oQqkuRJnz56izq3YyZM2E4vg11eDJ08ZM8wXe8c+UhUSEa1bO991l3Qotf65C3fBGxf58uLiLBV3X2Dx/W5xU/6DbePFjhvyH19ZcVwnxEeFOe+sfu4wJOLMYuIDjs858Gu0wsqdZDV+6+31GrN28trJn0nmNHBVzSBW9IsdPLIjXD3YIXoPI+Dm7zRZu8VhBBCCFOiIizQhw4dKh9//LHUq1dPihYtmq/lWkFBNwT0xtq3yC1n3GnLoAzUYshsCKXOAtl7Ye2dI48KyeH0qnvm1Zpd0GJf+zToZyrUHdtbuneJ9r7hWPxzaIN8vO597e1jf4H3dzHTGiwY2G44BaFTcHqbvrdW/0/Gr/sw7POiai+3ZozKBUcNgnqlGsirf42wlIJhCC2z6Ttm50u3FIk08sgRXfFAowHKCOJrATJ75wyt7eF72zmPRwIr9wpCCCEFFzcZoWNGoE+aNEmJ9K5du4qd9O7dW8qUKaO27cnChQvlkUcekWnTpgV8//jx4+Xdd9+VgwcPSps2beTZZ5+VUqVKSbjQLcrUIvVsW8S53V4M3QVyoNcZXnWEUdvtTffM17eyoMXxgoBD/ujP26bKwRMHgn4eWmnphLd77lu1YtUtGWq8K/bDS2dnpemCwKETh+Tm029X5wARHRM2jJfjFvL3w8mhk4ci8jnj1n+ofowb4BcXfqfG16K0P2Tc+o+0t4NrCuHadlf5954v3dZ+DNEVMHohQuHu+n0sp/2gKj2K6bnJG23HvSJWoYeIEELy4jYjdMwI9ISEBGnSpInYyeTJk2XWrFlyxRVX5Hn877//lgceeEBSUlICvv+HH36Q4cOHq5+aNWvKoEGDlEAfOXKkhAvciLEYDrQ4s7MonN1eDN0Fss7rUGXdKv4qshv9qa0YJnwtnINVZjfaJpntnW3VUOMdjYDvGWw8FQQS45LkZM4Jrddi3CB64eqa1sK6QwU1C7KysyImwnXwvgFaEU0ovmjnOPQ1D1rpgOEEMM5QGA+FKc0aJXEcgNu80XbeK2IJeogIISQvTImyhl5ybRBuuOEG+d///idHj9rThmr//v1KWDdu3DjP4xMmTJBrr71WypYtG3Qb8Jz36tVLOnXqJGeccYYMHDhQ1qxZI1lZAUpxhwgGlhGurCPknObFMAwMgdAxMFjNJcW2n24xRMoXKZ/vcU/rmhnDhKflzvs9hjiHKPD1eXhc53ugOJzn4suu46gznpwOjCChoivOPfl846cSKZLjk6VtxfYyotVrMvOamfL0mc+LE8ENEDdKK6Jpx7Gdtu6Lr3nQ7hD6SPLlps8tRQzhOKB9pdu80XbNcbGEv/uMYSDD84QQUtAwu2YnNnrQFyxYIIsXL5YpU6Yo8ZyUlJTn+WCh6N4MGzZMunXrJrt35z2hs2fPVs8dPnxYRo8e7ff9eH7lypV5QuPPPvts+f777yXc+GuzEw4rut1eDEMQBsrR1jEwWF1IYtvtKl0gVzS8XGas/U3SjvsOETRjmNCx3CXHp8iIlq/l9nk32rKhArOVwnV2HcdA48mO3u6R4NJql6uK8ZEmkkX6MrMz5dedM2Rp+p+SUPgZmbdrnjgR4waoE+njzbTtU23bDxi+YCn3ROc6jSVw/BGhg2OBlAMdkLLhlBBtO+e4WIAeIkII8Q1ToqIo0Hv06KF+7KoGjxzz7777TgYPHpznuTfeeEP9/vLLLwNuY8uWLer33r17lcd969atct5556kw9xIl8npLg2GllhNEZpuK/+YTQ2QWCk8eWpOyeiH1eJ3u98C+P9PiBRntw8DQBwaGSsENDKmFzHnoPLeN/UQ/8eapLfy2n9DdPl63Yl9wy11axh5JiI+XjlVOtb+avSNw+yBfn+N9fO04jsHG05ydv8rTNvWiDxdtKp4vTco083kc7q3fV0auGG5bIbxoA2NJv5n9bIkaCBd7M9IkMT5B2le6UCZGMMrA+zjhuvQM117hkgruodK9Rk9pV6m9qm3xxkpzPdmRNnRjnVtsv48Ycxd+Y+7TnbOsznG5BoAw3hsjjc74xfPe457YN3YJcQsFbdyaWbPH0jGJi3OAQDfyxI8dOyabNm2S7OxsqV69uhQrVszUdjIyMuTpp5+Wp556SgoVKmR5f44cOaJ+I+d8wIABqjDc888/r8Lc33rrLVPbKlvWeg+7CuXaSbh5vPVj0n9m/3xeQ+RxG89XKGeuMF6P1C7SreFlsmj3ItlzdI+UK1JOWpRvoYSzDu3LtJHSi0vLvox9QV878OyBcn296/NtO9Bxx/YrLKsgu4/u9ukpxXevUKSCtK/TRqb+o+f5y0w6ovoVIn/4jRmvar0Hn1O+cHkpVjxFFhz8Nd9xCvU4BhtPPcp1kRIlCsvQBUNl19FdEkkqFK6gCrIdPek7rcU4B+fXPkeWpi2V/mf1U+OhdEppqVC0Qu5xSMveIa8vfV1iiUB1DbxD4+F9jySnla8qH//zbtTEucGqI8vU9WlcC5kHT83ZTiAlPkUysjPCsu2u9TrLgYwD8uw8860YIfA2Z62VsyueHZZ9W3x4vgxeNCjffqEtJR4fecFI6VijY57nzM5xv2z6Jd98VSK5hNxU/ybp1aSX5bkx2uiOX+M+Q+wllHUaIdGioIxbM2t2t94DwoEtAh29z1966SX55JNPVI43+qAnJiZKly5d5JlnnpHk5GSt7SBsvVGjRtK2bd7wR7Pgs40q8BdeeKH6GwK9e/fusmvXLqlQoYL2ttLTD/n15DqBZkVbyeAWz+fzYqQWKqe8GHg+Lc1awaqaifWkZol66u99e83VF+jb4KGgIeLwtFxcrkuebcPihEkr2HG/t94Dfr3HmADuqddXbTf5RN62f/7A63CclqQv0ha7+JxjJ49Jr597BfQehXIcg4HzO/6CL+SrjZ/L65oF7cxieLtLpZTK9XrBA/jMoicCHpt2FTrIJZMu9eldq5l46jhcUeVaGbtyrOND9cNBpMU5eHB6PznsgAJ27yx/R75a+3XutaJ7nUaCcIlztGWrGFdDBs671nIKxoZdm9V8EgizHmrMuaVKF5EX5r3oc7+Mx/B84yJn+dyWzhwH77yvOftg5kFlpMM88FDjR01FFzkFs/cZN+OkCAjd9QIhTqIgjlvdNXssnueoCnTkhaPi+ptvvinNmzdXHnTkpA8ZMkRGjRqlWqLpVm5PS0tT2wCZmacWsFOnTlXb06VcuXLqd61atXIfQyV3sHPnTlMCHReP0y+gthUvkHO9WnQZN81o7Xu7Sh3k6v2BK2kjRzFefO9jsOPeNkiuP57H+xuV1ksDwOvweuS961A4obAcyzqWT1jic56OcMsIHMPup10lEzdOsD1M+O5690vPmlfnWYBhgXb9jJ5B3/uZj3NvHJ+nmg9R/aOx7w82GhiVHu3R8GBHGyeIc++xgAJ7Xap1U0ZFeGv9gdQBjJfDWc75DmbbsvX8qYscy7a+CCmTkqrmKX954rpVxD3fj7DCYhkpWiHay9KthWjj82BEDgTm0kjPnXZh9j7jVpxapd4N6zRCCvK41V2zE5sFOoqvvfrqq9KqVavcx9q1a6daoSHEXFegjx07Vk6ePJn7/4gRI9RvbMMMlStXlvLly8vq1auladNTVWTXr18vcXFx6rlYxLtFlxNAb+B6pRrIq3+NkAOZ+22/oRs91wMVNDJbzEi3oF5yQooS6E4pCKTzPa3wxT8TpGKRSnnOldUq/Z4MWfyU+g2RjtZk0aBEUkm5rFoX1ZaNRA8U2MMPDCbBUgdwziR8jTjCTijiHIUhMb/5E0ntK3X0aRD1brPn6/0IM9cBBe2s9Pc2M2fYOXdGqid5QSiaxz7GhJBwr9mJzQIdIe2+Wp+VKVMmNx9chypVquT5v2jRU2FjNWrUCPre48ePy6FDh5T3HEL81ltvlddee02qVq2q9g0F5zp27JjrXSeRAQKsbcV2YbsgdQwTZirr61S4Rqiqp8HBKX2L/X3PUDiVf5p38WXHtrMlW3nN4+NekBNR8mKjOGB2TnZUPpvkx4hmQD6avxDwgycOiBsIRx77kZOH5fklg2XmjvxdUXBNBopWApgXMN59RasgzFyHces/yjMPdqzSSS24GpRuJCv3rfA5x0MkL0pbqLV9O+dOX4aI4kklpMdpV8uNp9tfbC+SHVwiDavUE0Ji1ZkY0wK9devWytuNH6Mw3MGDB2XkyJF5vOrh5IcffpDHHntM/v77b/X/7bffrorOoTAc+rN36NAhX1V4UnAuSF3LnY4nBIvSSf985siWEfiercufK9dM7x7UiGAGz8WX3dt9pEnkw9v/gzFVTiOSLfLclMeOiB1f4lwXiEZEM9kZso95ED/xEq+Mbt6iFFgxGIY6d/rz9qJjxEdr35Ov/pko/ZHvHkA0W/G+x6qHyEwf42jf6wkhJBawRaA//vjjcvPNN6vibkau98aNG6VatWoqL90qnn3Mg7V1834MXvR7771X/RBixlAQzBOC3sU6Al03XN5u4MmyU0R7L75KJpe2dbtG+C482pGmWdkzZeq2HwtEiy9djPoKJPZqFtg9Lxh4inPPsGerhDJ36nh7ke8eKCw7lFxrJxik7YZ9jMU16RaEkNjAFoGOomvIQ589e7Zs2LBB5Z5DqKP3eHx8vB0fQUhECeQJwY1WpyAQXh8NwrVIMrZbrpC9aSL7MvdKn4b9LC/or6p5nfIsmhXZOEdNyzYPS+6+W7m65vUqXLkgHI9AofS+wHyAIm06xrmCdFzsJtS5M9R8dyflWjtF1OkaTDYd+kd1QrGynzrf1fs1Tco2dcUxdmpxPUJIjAt0kJSUpFqaGW3NCHE7/jwhTi8IFC7PvbFdnTx9s9vFccbCd+TyoaZarkFQohhh73r3ytL0xaq1H8JYdTDOERZIt9S5U4W+6oIoilhqDYd84gcaDVA1I4zjGiyn2e0MO3uUJMYnqnH8+spXg+a3r9i3XKVjxLpAj3aKwfkV2yvBZFUomTFQ4txj3oiPi1fvK51cRkavHOWIXGsniTrdOX/c+g/Vj5n9hEAev+4jmfTPxDxzt/c2/B2Px1s/ptqNOvUYO8ngQwhxD3E5qPBmgfr168tvv/2mCrDVq1dPhZT7Y9WqVeJW0LOUpf8jB4ZRampxVxx3Jy2gPDHaoNkZto3v9Un7SbmLUn+LjlC3i33HgnlJ+p/KlwfhDiH85qrX8nwfb0FpoLNfvs7RzB3TtVu9QZyjNVza8d3yRph6z0cS72MZjvHjNLzH3Udr39cy0Ixo+ZoMWzYkpo9NtPCXxx5sLvX2gKIQ3oAFfbU/F4XjdI16BiNbjQ5rGHuweSwaos7KnB9sP7HNYEZZbEP99vPZiPgY3OJ51abJacdYZy71notI7OOmdS4J/TxHXKAvWLBAWrRoIYmJiervQLRs2VLcCi+gyOK2icspIYje2CWgDYy+5d6fEWrFeN1FkJnj7Gu/PCtOe7/XqiDFMfE2HISLlPhC0rJcK/l116ywfYZxLhCi2n9+H4llvMfdtO0/qQrpwRjUbLAkxScXiBSASHB3vftlz/Fdynsa6Fz5Szfyda2jngUq3oezjgLGwYWVLw7Ltp0s6t5aNdpUZE2g/dS9R+F8StypjiL+BHpqoXKmjkekjrHuXBpugw+JHr7WLonxCa5a55LoCHTLIe6eovurr76SQYMG5VZwNzhw4IA8+eSTrhbohLixIJDdLdcgRBEG6ilqjDx9ndByq94xK8fZbCVlq33dcUzuqd9X2/NuBc+2UOC66T3CVkzPCN21q4ZBpyqXydGTR+XXXTMlGtQrUV92HN+RpzCav3GnmxYSSjoGyc/nGz8N2mYRxxlh554CLVDf90gUm/Q1Xuwy1jq1Yjq+34wdv5h6j6/9NKKkXl7uuwiw2fOJlAyzxyNSx5jF9Qo2/qIs+zR4UHqkdonqvhHnY1mgL168WDZt2qT+/vrrr6Vhw4b5BDoKxiEMnhASeXwJVVj0P173vult+cuXwwIUwj1YiCjE+b31+0rplDIRiTQwI+itLo5wTEoll/JpCPE2SJgB3v57GzygivF5H6dQiukFw1iQhlrDwFMEYzHe7adOcjTrqESaO+vdo4oA6ogmnRxbz+JlxrU1YtmLMvX/7d0HmFTl1cDxs7uwNAFpAiJVEFGKINgCCmgwgKIiEAUpMcaCxIqC0YCKihCICWA+jRXQiCJWwE8EpIiFKFUQPzDSRHqVtsuy33NevZuZYcq9M3dm7t35/55nYafduTvzzp173nLODzMd71tuVq7kFfo7I7wb7Hz2TCdIvvO676lMYhdruZOTBGgLtn6csqDOSadCvB2ZgfvpxqwrO8/j1n0TfY2ddPyheImWe2D4kj9JhQpl4s6dgMwQd4BepkwZGT9+vOgMef15/vnngzK265r0smXLyuDBg93aVwAJBqp6AjZz8/sRpwvGEi5Bkt2TGA3OkzUtNBGJnBzp365/k74mX+9ZLnklD0pufjlpcnJTeW/DW3GtUb+72f0RZxbo9Tq1fsTSP0dN5lUu5yRdwCQHjx10/Pe0r3mpoySAOgV1aIs/m2z8oSf5+v/g5n9K6iyDSHkCNDi32r+WR9P3Q4OfU8vWkm51u5uyaYkkftTfTypZPq4OmH91nCb9512XltKCbiibUzao0yXdmd9T6fJaXU17mrHxXdly6Ac5fOxw2E4aq1NTEy7qyHO0XCXxBK6JBnVOc6jEG6xa++n2sqtIz2OnE2Lzwc1Jz0ofT8cf/LOMMNFSj6MWj5JX2k+VbPH23wIfBuiaGG7OnDnm9759+8qECROkYsWKbu4bAJfpF9ugs+IfhQ037c/vowSJZKW3/iYrEAxcV3ZNvZ4y9fspjrY7oNFNMaf9W7kAogW9XepcKR9uniHx/D12gtVAOqrfqmrrqPu74MdLZd7Wn78vEhVterPlnmZDi07idN3sm99PCZrRoNf1qH+dqQAQuiwk3NR1DfjDnYTN/uHDuDpgtNZ81zpXOaoc4CW6vvuSGh1lya4vzewZKzgvk1NW6p5UX9bsWyXF1SvfvWR+7ArXTgNnJCmnx+NEg7p4MovHe/zWAHdHAgk17a5BD/d6hOuEcFKBI56s9H6q+OJ1Xk3EG4ud2SZbD20192tR2XtLJOENrhQpnzx5MsE54BNWIGJOfOIQOpJiBbjReHmUwDqJcirW3+R0u+VLlJc+v6w1j0WDXn0PI73uurbX6fro0Cnc0bZv3d9ukr8HWz4cNsh14obTB5hkSpq4SQPrcG1YLwfuk5XUKnS5gV7W6/X2UOFeN71OT7L1hNGiJ1f78v+7vj2W0Nfrp/wD4lcakM/fOveEpS2HCw4V6+DcbRNWPRWzrFs4mvtC258mN9QAWDuLItHb9D7WfXX0P9bont4euk07x/lwdEnVyOWPBuWCcEI7ALVTOep9wgS5VidEaKAUT94Iq+Mi8PNvV6Rjqc6kubbeb81xMdr7F+29tPs4P4r0/iXyXqSK7SUUR8g9gDSVWdNN6/WUWUNxzeLuZ0t2fumoHFG0jLOxpi9qnXFNdOblkQKn00xDg9NIbdduCS8dPe/X6EZH++ykPFws4YLtwOmFWiNahZvKbkciU1wjZVSONv1RA5Eu/9sxai4AzRUw8zdzzXR3p5md7WZ+DyzRZs00SPZ0XxRP1uyR0CnzkapURKpoYadjKZ7jfDJoEKt/1968vSdUzQisgx54zNXP8vUfd497KVesz79yOu3aOlYt2rZAZm+ZZSt5ZXEYTS5ulQzczN7/1AUTGEEvxksnstKVxX3ixIlFo+b6e7Q66AC8RwMtt0aNY2WN1wB15qb3PH0yES6pXqSTQid/h3ZMzNj0btSTRR1FsTt6HvgFo/uWqGh/j5tVChKpLBBpGmi0/dM157ES9entej+d7u40s7PTKb/W583O+kRL6ZwyciSJ5cLgD1fXvVYurtHBHI/CdchpwD1t/evmx/o8q3DBtN1ZH6GjgNpu1x/4j6Ra4N+lMwc0Mad1fG5epYVUr3ay6RQN9Mq6ia4H59bnXxNDfrr9k6DZIzpzR5esnFbutIgn+3pZR+/DlRSMtrQg3iUJfubVSgZuLpurUbZGUmcV+nHtfqos8Elnlytl1s4//+dMhMePHzeJ4rZv3y5fffWVNG7cWBo0aODOngJwVTxrCqOtl7MC3FfXTZSXw4wY++FkIlzA167GJQl90dlZ9x+4ZtqueLMqqxtO7y91y9dP+Rd3aCeINSr/2fZP5IPN001ZtkAVSlaUe5oNiau9aAIvJ/dzmtnZae4C6/Pm5H0jOIfS4Fzbm44qxmIdZxNdUqLtNXDU96MfPpT9+fskXfTv0s4J/f6wko2GGxfSk+9k5nYIlxBQkz0GPme4k307HXNPrRwtF5xyUVACSzuPC5e81c/8Xp5O34dYJVg71+9s7peMmaJ+CUDTYYGPOrviDtADaTB+1113yV/+8hcTkHfv3l2OHj0qhw8fNtd17tzZjacB4CI94dOefzuZpJ0c3Gdseq9YnUy4MYocafQ4kS/NRE5OWlVtk7aRh3Cvp079vrXJH0195GW7vjKpn/Q+Vib2eGi2dif3c5rs0EkyvcCZJ149qUTqxUqAFth2nHbIxbPWOnC/9LOo5aBildBMtWjfH05mpyRTuJN9O++fzm747dyr5e6m/63k4ffR5HikOvGs26PNGgTGmt328qqXpV6pRtLO5WDQTgAaOlMwU0bXC3zW2eVKgP7EE09Ily5dpEWLFvLCCy9IqVKlZO7cuTJjxgwZN24cATrgQWZk10ZdbSfrxzPxZCKRKfSJfDHGe3Li1YR9+jpooB4tI7wTWkpNk8DFWoOu94u3JFK0zO+ButTuJvN+nGPeM2vWAFLvkuodpXPtK2TYkgck7/jRdO+OOf6qaMdgbTup7tg5eOwnmbjuBfGiSN8fevL99vqpSamxHq/Ak32775+uTQ8M7v0+mhyPVJanc3O0WdtgpBmE4UxY/Te5yMVg0E4Aqt9VmpgysFMwU0bXV/rs/NSVLO5r166V/v37m9roGph36tRJcnNzzTT4LVu2uPEUAJLACjDCTYfU6cV6W/9GN9r+AsnEk4l4Ro91iqb+n8gXc7xZlTOlrI9OE9W15dHo7dZ0UjtZ98O9dvoZmnbZDJPkr3zI50g/V/qj0181oZwmDnpy+YiEpx8jPvO3zZVHlj6Y9uA8MKN/rIoJ2nZ0arvd2t1OVMw9Oeiy1S61jJ6XfbnjC3nx22flxW//KZ9v+dwky9TXKN5Sbslinexr4LTnqLOcL1YmfS+VMdX90eSy1muvvycjk7ydY7EmS0z0eyxWpnhtV062df3c7raDc62EYbUPu2Jl8bcTgGpHcuiMHT9kxneD385PXRlBr1q1qqxbt04OHTokq1evlqFDh5rrP/30U6lZs6YbTwEgySO7bkwv9tLJRHHntF55pvSSB7LqnIfWQdeR89A66IksRdD3QjPwa6I/a4bEDwc3hz1Zs7OkBMmT7uDzqjrd5axKzYrKa2nbsY7Br6x9OezItbZFDdTL5JRxdf9LZJUwM6Q0uZnO7NDOIz/4138mF/0+ed3L4mWfbJ0vjyx9yHGZOSt4M0vRSleLmfROEwiGm6qt3Phu1+AtdKaQ1ojXdqw5VCIdG51MHw+9b8/615uSoeFomcyzKjWN+/vMzmjzY0uHFZU1jfZ3JFLdQLdn5zWyM9KfaGDppendyeC389O4y6wFmjRpkllrrgnizjjjDJk6dao888wzMmHCBBk5cqRceeWV4leU+0otyqz5m9/Lo/ix7Ub64g7NeJwp68zC0ZJrmq1dE8LpmnOd1h6YiMntNYl2Pgd6YpubUyrhbNOhQZtVikuT7nlt/TCCBZ5g62idBgSxKg8kg3ZKfX/gP0lNrgbnHjznYSmZnStjV4yUA8eCM9WHKl+igjkHD+wI0OuOHj96woyRWEF1KDsBaLjkWk6mj4e7r3akRvs8xFN+02kpNNW+5qXy1c5/Bx1Prb9DA9pYx/podOaV5u2J9hrFev2t197J3+SkvGJxUZDi89NEy6y5EqArHTnX6ezt2rUza9CXLVsmpUuXNjXS/YxAMbUI0P3P7pdJcZPOtktJFW+xe6KktdGzs7KLMto/uWKE7YA98AQx3Huv008HL75DvKRciZPM+mYE61W/txkRTJeyOWXlUEFwBQWknwZvdqdMx8POd7GpKT+3e8yZP6GBjZPzgERGoAc2uUOuqdcz6HntdFjvOLJDRi5/RBKlM1Di6djKkiwpX7J81Nwluu3rT79B+s7rZSuoVIl0FlidQlaVhOJoQQrPTz0ToKtFixbJd999Z8qt1a9fXy666CIpWbKk+BmBYmoRoBcPmVjmg7YLi64R1DXnTk+GYp08WNOR7XTC2BktiERH2AJPHGONZNlRseTJtmtwZ5p4X9/SOWWkVE4px9OnUTwy/CdKv5Mnt39DVu/5OmLnrpNRWWv01clIpRtBpXVuoewG+m4djzTvSLwzlUKPs+HvU9FWeUPrtU+ksyNwO15SkIQs++ESu2pHZefaV5pOb7vPEW3fEg3QXVmDvnXrVhk4cKB8//33JjAvKCiQDRs2yKmnniovvfSSVK9e3Y2nAZChGcuBTFjr5mY5Pqc5Ciw96l1najFba1ZPKllenlkzXhJ1Wa3LZdr61xPeTnEUb+fHkYLDMqDR73+uVb59oev7hfTpWueqpC850GOMlnUL7OBJZF2zdV8n2bKt3xNhJTlzknzTrc7CeIJzfY17Ne4pTy9/OuZ97QTnga99pO8Qv1Z4WZDgYE+kvAzhOkZ0FpF+R+lP6HOE286ibQuTOhDlSoD+yCOPSJUqVUwwXrFiRXPdnj175L777pPHH3/clFoDkFncqB8OZFqZIDc7tyKdrOnIq06tP3TsYNCIUqfTOptycG+un1J0fWhmeqd0BOieZkPMyTMBuvueWTMh3bsAl/VreKPJlZEKobMvrGC3b8MbpbCwQLYe3mp7W1aHo92gXp9Lj0NuiTUanSw6XV2zstvJF9KrQR/p26i/fHXgU1f3IbCz1/oOmfh/L5hEfn6t8LLARk33aIFwuOBeZ6bYqeIR+BwqdDuRZj8EPu6Smu3TH6B//vnn8vrrrxcF56pSpUoyePBg6dOnjxtPAQCAL9gZvY52MuRm51akgF/pdbuP7pQG1evIhh1b5JElDyU8QlShREW5ou7Vkh2QMdrKJG1nOqieQB0tOBIzKRZQXGk+gnQvk5q87kXHj9FM8k5mEGlZvKvr9hC/sxOcK03mqbMiDuTtk4an1Hft+fWYGdrZq98hraq2thWg69r8u5re76nlhwU2suxHyzofKbh3WkUl3FR4O51Bum9ta7STtAfoGpjv23fiNIz9+/f7fg06AABOuTldPVGRAn69TtfJVapcVobM/7k8aqL2H9snrau2KXq+cKMY0dbY39Cwv5k6mMg6SsDPjhQcET/6x+q/m5FF7QgsW6Jc0AydSKP3GrDaWYtdnLy1YarIBndyeygdEdZjZuh3ip2ZXOVyysktZ/4xqOxjspLOOtnuSgfLJEK/2/R5Jqx+StwQb7vUfVu152upXq1tegP0rl27ykMPPSQPP/ywNGvWzFy3fPlyefTRR6VLly5uPAUAAL7il1wMS7YvSXgdaCBriqvdhEWhnRZW50ak0Qt4x3lVL5BeDXrLI0sflAP5zHrIZDo6GU/liHTPFkgXt0oq6jEy3JRvOzO5DhYclFErRgSV6Pz4x9lhO5UT+S5zupZ80TZ7OTXCLad4Zd3EpCZXtGv30V0JPd6VLO55eXkybNgwee+998TaXE5OjvTs2VOGDBliyq35FRmZU4tM2PAr2i782m4X718oQxYOiXnfMjll5bCNclyaCVhP3mJlZ9Yp78NbPmamwYc70dORkFfWviwT170gbqiYezIZz5OAOupIVNOTm8nqvatcC1rdXj/uB5FqeDuZxRRN6EwHu7PBnJY2c5KJvkPNS+XPLUfE9dhku/nMgfLH82+L+/GuZGfIzc2VJ598smgt+ttvvy2LFy+W4cOH+zo4BwCguKtWtpqt+z3S6gkT5Ebd1i/J7+xMUdT16JokKtoozMzN74sbdL/uPHtwQjXcA+n01OKsbfX2Md9ri578a71mJ1m0kVy52aV89X58vXdlyoNzVVyC89DM+IE0+NXAXTtOhzR/SEplxxeXhc5mshKiaVCc6FpyvZ/d+wf6+Mc5Mu/HuXE9Ntk+3Dwzoccn9A3z5ZdfysiRI2XMmDGydOlSqVChgjRv3lzOPPNMKVu2bEI7BgAAkq/VKa1MABuN3t6y6rlyd9P7o97Pqke8ZOeXtp47WsZnO0G+Xbpf7Wt2NKM1oX+rjqJFo/efdtl0c4KrtesHNrkjLcFEqrSrfrEMbzUi5ntt0fdIa2nf08ydPAZIXKnsXLmqzrW2O1lQPEQ6nmonqAbY41f9VY4edzfHQWCAHcppyb14jvnjVo0pWt9u97GxjvmW8iXir2PuNCGdawH6u+++KzfccIMsWLBA5s+fb7K1T5o0KaGdAQAAqZWTnSODfgmsY2Wdt9aHhwa5etkqSaNT2+2W94mW8dluuSYtGxeJtV+B69ut0SQNtvX/wCmSkf723Oxck4zo0lM7SaVSlaU4W7htgVw7u6sJurU0lB36XkVqGzhRnbJ1k7p9rYIw+buXWNKRYSIdT62p31rrO1Uj906O4db97N4/tHqAtTberp71r495nx71rpOLqieWiT0RcSeJmzhxoimjdtNNN5nLr776qowfP1769evn5v4BAIAku7im/azzkZLfOc2+HqkWvMVuuabHzh1lpsrrvlTK/Tl43pO3O2Iio3BZ7bOz7Gfct7tffqajbVruyy7rNQltG3uO7jbltGLRWQnbDm+VaevfkEyw8dCGdO8CipkKJSvKjiM7ZNmuJUHHvVRM/Y4UHNs9Vlr3i/fYuuuX7yE7BjS6Sfo07C//u3l61CSkb61/I60zpeIO0NeuXWuyt1s0IdyIESNkx44dUq2avfVsAADAf1nnQ4PceE4Co9WCt1smSG+PlGQuWX+7nf3KJKEdLYFtQ9vF1O+nxHwPr6nX0zyuWeVz5KmVo2VffuyR35JZJSW/MF9SjWSDwXg9vGF//j4ZufyREzoX3VwqFEmk4NjOsVLruB8vPC5ztswyHaxVS1dznIXdOl7Hei7txKhZtpa8vX5qzAoh6V7GFPcU9/z8fJMczqK/lylTRo4c8Wf9RgAAMp0VXOlUbv3fbuDr5CQwdNp5tH2x1rTHG+Qn42+3s1+ZJNp74PQ91Dbx+qXvxFw7rQnQpv/mI7m/jb118m5JNNlgcXTZqZ3SvQsIYSVwe/n/njej6skUbSaUnc+/1nHX8nyPL3vY/J9XcNTR82uAb3WmxnouqxPDzqyedCveaUgBAEDS2V3/d8Pp/c0a8FjBuSXWmne723FbtP26tt5vJRNokGznPXD6Hup6/1gJ6jQhnd6v95m9Y6551xN4HZVzO9lgxZIkYFM/5f8Ud2ZwP9DPs06L9qNJ616UsStGJvU5YnWSRvr8W1UGQkeyrcsVbFYh0ADfqptenPJgxF0HXTO1T5gwQSpWrFh03R/+8Ad5/PHH5ZRTgl+YNm3axLVzN998s1SuXNmUcAvNHq/11efMmRPxsfv27ZPzzjsv6LqTTz5ZvvjiC0f7QE3j1KKWNPyKtotMbre67vGeLwbFvJ8mZQtd/22HlaU31vTzVAu3X3rZzmvhd2POGyetqrZO2nsYrn5z4NRdq+2+tfJ9GR6jzrL5P4H6yOHyEeQdz5Pfzr06o6d3F6c64qHKlSgnvzntCrP0RdvqK+smysS1z6d7tzxFOy76NbrR8edfO7ceX/5w1M9O1VLV5P7mD8qK3Utlw0/rZfGOL6JmoA/s7AvM6q6j5en4jJYrWU4+7/156tegq0GDTvwCuvfee4MuZ2VlyTfffON42zNmzDDZ4a+55pqg67/99lu58847pVSpUlEfv27dOhOQT58+vei67GwmDAAA4Da768WjJYWLJlxiNy8It19urFHvXren1ChbUyrmVpJqpauZTMX/8804z6x7t9b+J/M9tJsXwG6Cw3D30VG6aGtRdfTUCtBCn9ca6U8k8Pe74hqca8fDwWMHZdr6182PtqWLa3RI9255Tp2T6jn+/GvHm05nj5VnYufRHTGD+ED62dbPqj6P9VzacezXDrS4A/Q1a9ZIsuzdu1dGjx4tzZo1C7p+ypQpMmrUKKldu7b89NNPUbfxn//8R+rXr0/COgAAksxa/xctWHFzvbjfX4tIImWOV+1qXFIUrGoyJU2sNGLZMDkQI9lRMqTqvbQb1NsJ5qNVH7CbwT/c84YL/MuXrCDnVm0jX+9ZEZTwSrfboeZljjLkI/0dD/reaqCOYP9Y/XfTyRWtaka4cm927XMQXJv36Ps3pErpKkX7Ek/ZNt9PcU+mBx54wATW27f/fLCzprgPHDhQrr76ahOc6/T6uXPnRtzGyJEjzTT30OnxTjFdNbWYJgy/ou3Cj9xut7GmJWeScK9FJCeVKC83NBxgaqzriLndKfyxTnj7N7pJfsrfL7O3zAo62dX3pEvtbo6n7HrpvXSz7Sa6hCLS4yNd76RtBMqW7LRmly6TU1YaVThDVuxZJpkontdfPzO3NblDTs49WRZtW2BKCRbXpQHRjg/6Wej98bUpmwVULc5jnFemuHsuQP/ss89k2LBh8v7778vDDz9srgsNst96662YAbrWZz927JgJ5rdt2yatW7c2gX/o+vhYONlOLYIc+BVtF36UjHbr1fXi6WC9FtaJeSShU62dBMJ2OkXCvScq1gmzrgMd2uLPtkfIUsnvx9zQ9yTcMgZ9/bvWuUpOK3da0X0eXfpQyvaxR73r5KLqbYv28bPti2Tq96+l7Pn9RpdEXHjKr8zvkT4zC7fOk79+PUr25e2T4ipc8ke7eUrcViHGMpZiuQbdbUePHpXhw4ebAL106cQyQuoUd00wp0G59kE89dRTcuutt8rUqVMlJyfH0RcAUsd6vXnd4Te0XfhRMtptiawcaVnVe+vF08F6LfSneeVzZEKENdChJ5BWmaRH9ES3ZvQg/ZKa7aVtjV+mbh/ZKVVKnxgURHpPBp11V9QEa388+245t5r9RHCp5Pdjbrj35OKal0R9H1VO1hMyftVTZo1usmgSr7uaDpb2p3Ysum7elrm+Cs6TNUrdo14vmb913glLGq6t10tuaNQ/ZgdW25rt5B9r/l6sA3TtMNRjUuBrsTtN083zjueLH3kqQNdR8aZNm0q7du0S3pYmmdMEdVagP27cOGnbtq0sX75cWrWyf+JQpUr5hPcFzvG6w69ou/Aj2m3yda96pVx1dhdZsn2J7Di0Q6qUqSIPfvJgxNEdDTD+Z80485ic7NgDC9WrXRLXPlWoUEaeXPykbDu0rej6GmVryJDzhshldS8TrytubTfW+2i1o+dWPidPL3va1efu26SvdKjTQVqd0iqozRUcL5Bxs8eKn1jBuduBepfGv5GH2v3JvP6vrH7FBNqaB+Lltc/LBz+8L0PPGxr1c/Pvrf8O+qxFUzq7tElwfejYIfET7bzYWLBW2tT4bxWvBsfqpGVfjhQclowK0Hv37i0jRoyQ008/3bWd0aB6586d0rLlz5lB8/LyzP8ffvihLF261NG2ypQpE3S5SpUqJqu7Tnd3Ytcuf06d8ivtCdcvW153+A1tF35Eu029+iXOlPoVzjRTPqOdqGtQsfXQVvl47SdJzWB/Trnz5dX2b4YdudXp416V6W23R60+ckp2rRNmZcRLZ3P0r3+zed/37A4OCLWt7jm6R7yiTE4ZOWwj8Lqw2kWy7sA619Y969KROjmN5N1VM8N2jujn+e55d0ed+fL99o22n++IlhWzseS9VHYpMyh5pCByGbJQWoVASwUmy4w1M82xzqKvm87MiJW9HQkG6FrmTBO23XjjjXL77bdLbm6uJGry5Mlm3bhlzJgx5v/Bgwc72o6uO+/QoYOMHz9eLrjgAnOdBuZ79uyRBg0aONqWHvQz8cCfbrzu8CvaLvyIdpt6O4/stH2/ZL832ZIjLSoHdwL4pT1kctttV6O9XPRLZnoNQv++aqwcOnYwrm3pTI4Vu5aH7Qyy21aTSYO7gWfdaZIoagWDwYvviPmYz3Z8KsNaPiYbf1pvRrgTpXkdtK1pp0g0eru+L+Gmu1cuVVXcdvT4UcePSWZwrqZteFNysnPl1iaDio4xl9W6nGz4NsVdGPyll16SsWPHmmRuV1xxhXz66aeSqFq1akndunWLfsqVK2d+9PdYjhw5Ijt2/Lwe56STTpJzzz3XZHJfsWKFrFq1Su6++24zdb5x48YJ7ycAAEAiNIGUm/dDZrJK0f261m/k/uYPJrStSGWp4m2DmuSub8MbzRrtRN3d7H75da3Lzd/aokpLM5pttxTY9E3v2n6eXvV7n7BtvWwlPrM6Q6LR2/V+4ejslOplq4sfaRZ/J7Sc4Lwf/5vQW8scIskBuurUqZN88MEH0q1bNxk0aJAZ6f7+++9ly5YtQT+pMHPmTLPG3KL10s866yy5+eabpW/fvib4t0bkAQAA0klP1GMFGXq7lXHdTlZwnYo8Z8ss879eRmax6rKHtisdfbYjMBAPbE86Yl21dDVH+6Il/l7r+Jb87oyb5N5mQyVegcFxYKeEjmbbocn0AmvRR6Jl0PR5dMT3Xx2myV/PnyAPnvOw+V8vW89vt7Z2pPvpvus6dT/qWvtKx48Zt2qMGa3XtqQdFxVz7bXFTOdambXZs2fLXXfdJQUF//1C0E3rmohvvvlG/Mqv5Tv8yu9lU5C5aLvwI9ptesWqYx6uXFGk7WRa/Xnarv0SbmdVaip95/WKOvKr7UUD0Uh12p2WqwrcntJtjl35pEmo5sSY88ZJq6rhKwk8vfrvrk2ZfqDFMDMLIRa75cI0sA9dLqDvy9d7lkteyYOyZttaeX/ju0GdBzrTwOnrkypnVGgs/7f/27geW6FkRdmfvy+jMv6XS3eZtR9++EFGjx4tH330kZnqfssttyRcIg0AACBTRjwTCa4jBflWqTa7QT6K37T3QNqeonUG6e1WcB7uflZwbjdBmzXN29oPbYMnlTjJ1trxQFpPPBKdMu1WgG53yrw18yVWZ0fozJdwnR66BEBnGlh17u2urU+HeINz5eXgXCWjHF+iSiRSs/yZZ54xa9Fr164tkyZNktatvVkrEwAAwIs0cNFAI3DEM1z963B0RE5P+qPR23X7draHzO4MstOeypU4SVpXPV8WbpvneJq3tXbcSVb1aOvf9XMSa2Rfg2DJkqjT3J0sJbGm19vp7LBE6vTQ6fcT1z5v3hftyNDX3+nr4+ea8mVzysqdTe+T1XtWyrsb3xI/q+BwhknSAvTLL7/cZEvXae26xjsnhwM/AACAGyOedjhJWJXMUm0oHp1BdtqTBpXNKje3FaCHBtd2glsngfOibQtjBkWDzr7b/O8koHZz5ovTTrRYr48GtYcKDhWLEWb9O/Yc3S0/HNosfnfPL3kWQttEygN0zZI+ZMgQOeUUe1NCAAAA4J5EE1Yh80TrDLLbTjTRVzzTvKMFt04DZzuBr45qWoFvoktJ4p354rQTLVbw//XuFfLm+ikx90/v36V2NzNCHy/dxsU1OiS1NNoza8bbvm+p7FJxlZSLpXyJ8lKqROmYsyxua3KH/M8346K2IatNJFrvPe4AXUusAQAAID0o1QY32W0nVlAS76h0YHC7aNsCmb1lluzL2+socLYT+OroemDgG+9SkkRmvsTTiRZpX3XGgJ3gXNe139Cwv8z7cY6t576qTnepVe40KV+yohzI3ycVcyuZevP6nLoPXqhdni3Z0rN+b3nlu5dc3/a19X8r9co3iNme9X1pV+OSqG3IahOaxDIRCSeJAwAAQOrFm7AKSLQ9JToqbQUy+nNrkz86DpzjCXzjXUqSjk600H21M2NAg9iHWj4q7Wt2NPfX6eN2XFKzY8TXxU6bSIUe9a+T/mfcKO9tnObqWm+dZdGnYX/b7TlVbYgAHQAAwIfiSVgFuNWe3BqVjifo8cvsEbc60ezMGDgux00993AZ4+N9bqd5A9yWLdkmONf69NZa72j7cnmtLtKqahszA2Bv3l7529ejowb0uj2327On6qAXV9TXTC3qmsKvaLvwI9pt8UAd9HTvTfHih/akI8S9P77Wdm33dIqUxd1ipxTinC2z5PFlD8d8rmvr9ZJp69+wvW92yzDq3/DXlU+6OnodTeuq58l51S6QbnW7S252btztU9vJq+smmtcksMZ8stuzdXyK+/EE6NFx4E8tvnDhV7Rd+BHttvjQE1EvjPykCm03ufzQntwIfP3S6bFs1xK554ufR5FjJfALXM8fSTwBaqRgNxn+ev6EqLMqnLbPVLdnAvQk48CfWnzhwq9ou/Aj2i38irYLv4z2BwaJX+9ZLnklD0pufjlpWsl+kGhnxkDFkifbyh4+sMkdck29nnEHqIHBbqXcyub3ieteELdU88jMh3QG6KxBBwAAAOA7Xlo3bHetfTwdS3bWgl9W63JbGdcrlarsavb6VlVbS93y9WXE0j+7UjP9dvJmEKADAAAA8Kd0ZGdPh1g10jUjuZ0APRmJ8zQ5XaLBuRszHwp8sDTDDgJ0AAAAAPDxjAENTtNVdtFu2bsyOWXkcMHhoGn5OvKvf1OiwfQCHy13iIUAHQAAAAB8PGMgnWUX7Y7Kjzh3lGRnZbs+wr0gQsJADdb1ei8lDLQjO907AAAAAABwZxq8jhwH0svJDFKteu/R6O0tqrQ0nQuXntrJ/O9GcF5QWGBGzqPR2/V+fsEIOgAAAAAUA+lInJfO0fuVu5dHndav9Ha9n19yFRCgAwAAAEAxkY7EebGS2CVr9H6XzfXvdu/nBQToAAAAAADfjd5Xsbn+PRnZ65OFAB0AAAAA4LvR+2a/rH9PR/b6ZCFJHAAAAADANZqUbdmuJTJnyyzzf7KStOX8sv49mmStf08WRtABAAAAAK5IdU3yi9O0/j1ZCNABAAAAAL6tSX5xGta/JwsBOgAAAAAg6TXJ/7rySRNIJyNwzklD9vpkYA06AAAAACDpNcn35++XV9dNTNk++REBOgAAAAAgIXZrjb+1/o2kJY0rDgjQAQAAAAAJsVtrXEfRdbQd4RGgAwAAAAASoknZypes4OpoeyYiQAcAAAAAJJykrXu9Xq6OtmciAnQAAAAAQMJuaNhfKsQYRdf65DrajvAI0AEAAAAAroyi39NsaNT73H7WXb6sT54qBOgAAAAAAFdcXKO9PNzqCTNSHkgv6/V6OyIrEeU2AAAAAAAc0SD8V9XbmWztmhBO15zrtHZGzn0+gn7zzTfL0KEnTpH48ssv5dJLL7W9neeff146duzo8t4BAAAAAMLRYPycKq3k0lM7mf8Jzn0eoM+YMUPmz59/wvXffvut3HnnnVJYWGhrO5s2bZIJEyYkYQ8BAAAAACjmAfrevXtl9OjR0qxZs6Drp0yZItddd51UqVLF9raGDx8uTZo0ScJeAgAAAABQzAP0UaNGyVVXXSUNGzYMun7BggXmtgEDBtjazjvvvCOHDx+WHj16JGlPAQAAAAAopgH6Z599ZtaYDxw48ITb/vGPf0inTp1sbWf37t0yZswYefTRRyUrKysJewoAAAAAQDHN4n706FEzJX3YsGFSunTphLb1xBNPyDXXXCONGjWSlStXxr0dYvvUsl5vXnf4DW0XfkS7hV/RduFHtNvMkJVVjAJ0TebWtGlTadeuXULbWbhwoSxbtkwee+yxhPepSpXyCW8DzvG6w69ou/Aj2i38irYLP6LdwjcBumZu37lzp7Rs2dJczsvLM/9/+OGHsnTpUtvbmTlzpmzdulUuvPBCc/nYsWOSn59vtvvcc89J69atbW9r164DYjNhPFzqcdKDFq87/Ia2Cz+i3cKvaLvwI9ptZr3PxSJAnzx5sgmmLbqGXA0ePNjRdvT+t956a9HlWbNmmW3rT/Xq1R1tSz88fIBSj9cdfkXbhR/RbuFXtF34Ee0WvgnQa9WqFXS5XLly5v+6devGfOyRI0fkwIEDUq1aNVOGLbAUm/5eokQJW9sBAAAAACAdPJfFPV46rb1t27bp3g0AAAAAAOKSVVjIBItodu5kjUiq12xUrVqe1x2+Q9uFH9Fu4Ve0XfgR7Taz3mfJ9BF0AAAAAAD8jAAdAAAAAAAPIEAHAAAAAMADCNABAAAAAPAAAnQAAAAAADyAAB0AAAAAAA8gQAcAAAAAwAMI0AEAAAAA8AACdAAAAAAAPIAAHQAAAAAADyBABwAAAADAAwjQAQAAAADwAAJ0AAAAAAA8gAAdAAAAAAAPIEAHAAAAAMADCNABAAAAAPAAAnQAAAAAADyAAB0AAAAAAA8gQAcAAAAAwAMI0AEAAAAA8AACdAAAAAAAPIAAHQAAAAAADyBABwAAAADAAwjQAQAAAADwAAJ0AAAAAAA8gAAdAAAAAAAPKJHuHfC6rKx070Fmvt687vAb2i78iHYLv6Ltwo9ot5khK8H3N6uwsLDQrZ0BAAAAAADxYYo7AAAAAAAeQIAOAAAAAIAHEKADAAAAAOABBOgAAAAAAHgAAToAAAAAAB5AgA4AAAAAgAcQoAMAAAAA4AEE6AAAAAAAeAABOuKSl5cnV1xxhXzxxRdB12/YsEGaN28e9bEFBQUyZswY+dWvfiUtW7aUO++8U3bu3Fl0e2Fhobn9ggsukPPOO09Gjx4tx48fj7i9hQsXSrdu3czz6v/z588Puv3TTz81+9qiRQvp16+fbNq0Ke6/G/6XzLYb2IZvvPFGeeutt6JuT9vigAED5JxzzpEuXbrIJ598EnQ7bRdebLccc+GVtrt//3558MEH5aKLLjLnDEOHDjXXRcIxF35stxxzMw8BOhw7evSo3HPPPbJ27dqg63/88Ue55ZZbzO3R/POf/5SZM2fK3/72N5k6dars27dP7r///qLbX3rpJZk+fbpMmDBBxo0bJ++//765Lhw9UA4aNEi6d+8uM2bMkGuuuUZuv/122bx5s7l9y5Yt5rLe/uabb0rlypVl4MCB5kQUmSfZbVdpZ9Jjjz0mixYtirotbYPaNqtWrSrTpk2Tq666yrRlbbOKtgsvtluOufBS2x0+fLisWbPG3O+FF16Q7777Th566KGw2+KYCz+2W465mYkAHY6sW7dOevXqJRs3bgy6fvbs2ebgkJubG3Mb2rP4wAMPSJs2baRhw4bSt29f+eqrr4punzRpktxxxx3SunVr07M4ePBgefXVV8Nua+vWrWZ/tEe8du3a8rvf/U7Kli0rK1asMLfrgbFp06ZmVKhRo0YycuRI+eGHH2Tx4sUJvxbwl1S03W3btkn//v1l7ty5UqFChajb+vzzz00v96OPPiqnn366+dLXUR09cVS0XXix3XLMhVfa7qFDh+TDDz+UYcOGmTZ39tlny5/+9Cez/XABFMdc+LHdcszNTATocEQ/8Oeff768/vrrQdfPmzfPTOHRKTuhdHpQ48aNi3r7tCfw17/+tfl9165d5uCiU9mtE0XtodSDmuXcc881B5vt27ebyx07dpTx48eb33VfrOfMz88329JpSdb0o+XLl5tA31KmTBlzMFy2bJnrrw0yu+2qVatWSc2aNc0JX/ny5U/YXmDb1bZ51llnmS/awLZutU3aLrzYbjnmwittNzs7W5555hlp0qTJCcHRwYMHze8cc+H3dssxNzOVSPcOwF969+4d9nqdGqlC1+ooXX+j67x02k0gnb7+9NNPS8WKFeW1114z1+3YscP8f8oppxTdT6ejWb2Ier1O4SlVqtQJU4A6d+5sDnD33nuvnHbaaUXbC9yWqlKlitkWMkuy2671pao/kQS23Vhtk7YLL7ZbC8dcpLvtli5dWi6++OKg++kMPA2UrMdzzIXf262FY25mYQQdSafTgapVqyY5OTlB1+v6Lz0IXXjhhWZqzk8//SRHjhwpekzg45X2GCo9gJUrVy5oW3qdbkunDGmvo04fUocPHz5hOpJetrYFuNV27Qhsu7HaJm0XXmy3gddxzIWX2u4rr7wiH3zwQdBaX4658Hu7DbyOY27mIEBH2tStW1eaNWtmsrRrYD5r1qwTgvHA33XaTiQ6LVOnrvXp00d69uxpDnhKeyBDD1J6Odq2gHjarlOR2qb2rke7nbaLdLZbC8dceKntap4aHeHUdb9t27YNuw2OufBju7VwzM0sBOhIuY8//tisNbfowUUTX+zZs0eqV68eNNU98HftnQylGTa//PLLoOs0+YtuS+n2QssJ6eVw2wISabtORWqb1lQ12i682G455sJrbVezYGvit/vuu88kO4yEYy782G455mYmAnSk3KhRo+Sdd94puqxTftavX28OOHqgOfXUU4MyDOvvel3oGhvrIKilKQLLSWjCowYNGpjftSZk4LZ0KtDq1avN9YCbbdcpbYPaVq1lHUrbqtU2abvwYrvlmAsvtd23337bjE7qCOTvf//7qNvimAs/tluOuZmJAB1Jp1NtdBRcE1sonZ6jPYfz5883PYPae1inTp2ipBnXX3+9jBkzxiTi0J+xY8dKv379ira3e/fuokyX3bp1M9vW++vBT6cLvffee6Z8irr22mtlyZIlptakPpceDDWxhmbFBNxuu7EEtl3N6KqZs7VN6ra0jWrZlB49epjbabvwYrvlmAuvtN29e/eaEUitC921a1fzOOvHejzHXPi93XLMzVCFQJzOOOOMws8//zzoOr2s14e7btOmTeZyQUFB4bPPPlvYvn37wubNmxfedttthVu3bi26/7FjxwqfeOKJwtatWxeef/75hX/5y18Kjx8/XnR7hw4dCseNG1d0eenSpYU9e/Y02+rcuXPh7Nmzg55/3rx5hZ06dTK39+/fv3Djxo2uvxbwl2S13UDaTqdNm3bCdYFtd/369YV9+vQpbNq0aWHXrl0LFy1aFHR/2i682G455sILbXf69OnmvuF+rMdzzEVxaLccczNPlv6T7k4CAAAAAAAyHVPcAQAAAADwAAJ0AAAAAAA8gAAdAAAAAAAPIEAHAAAAAMADCNABAAAAAPAAAnQAAAAAADyAAB0AAAAAAA8gQAcAAAAAwANKpHs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day_timex_stdy_stdx_p2vy_p2vpoolingnr of measurementsComment:
020250718_120836_static_00.1035410.1265690.8248000.74230001000raw th cm
120250718_113636_static_00.0765270.0578640.6818000.52010001000raw cm
220250718_113013_static_00.1413050.2346151.5079001.38470001000raw upscale th cm
320250718_123917_static_00.0502430.0509070.4972750.44667501000raw upscal gaus fit
420250718_123917_static_00.0502430.0509070.4972750.44667501000NaN
520250721_084639_logn_term_00.2188071.5834761.0519504.8587750100NaN
620250721_103850_logn_term_00.0424870.0016500.2849750.20330002NaN
720250721_103850_logn_term_00.0356310.0242470.2849750.26792505NaN
820250721_112553_logn_term_00.0497561.4502720.5467755.3741250134NaN
920250721_112553_logn_term_00.0496891.4614770.5467755.3917250135NaN
1020250721_144023_logn_term_00.0152620.0209000.2305250.24180002NaN
1120250721_144023_logn_term_00.0696810.0694540.3790250.40212506NaN
1220250721_144023_logn_term_00.0887590.1340690.5437500.611125013NaN
1320250721_144023_logn_term_00.1037730.2261480.5781250.873750022NaN
1420250721_144023_logn_term_00.1854740.4234300.9832001.703150063NaN
1520250721_144023_logn_term_00.2344430.4611951.1044751.839550099NaN
1620250721_144023_logn_term_00.2376100.4591191.1108001.8395500103NaN
1720250721_144023_logn_term_00.2265530.5142041.2824002.0502000160NaN
1820250721_144023_logn_term_00.2000721.1147961.2824004.0640250208NaN
1920250721_175607_logn_term_00.1212990.0837370.5839000.475550018NaN
2020250721_175607_logn_term_00.3274073.1979951.74000013.5523500968NaN
2120250722_081704_logn_term_00.2031450.3494770.8316751.602500037NaN
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2320250722_081704_logn_term_00.2113851.0682601.0404003.713125075NaN
2420250722_081704_logn_term_00.1937271.9873691.0910006.5747750124NaN
2520250721_084639_logn_term_00.8752306.3339063.60780018.8351000100NaN
2620250722_105004_static_00.0614940.0533330.5036000.4299000100NaN
2720250721_175607_logn_term_01.32078612.7828426.36000053.6094000971NaN
2820250722_081704_logn_term_00.7749077.9494753.76400025.6991000124NaN
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3120250718_113013_static_00.0353260.0586540.5269750.49617501000NaN
3220250718_113013_static_00.1413050.2346151.5079001.38470001000NaN
\n", + "
" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 3 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## Measurement dashbord\n", + "Statistics of all measurements, multiple plots drop down sith mesurement selection and statistical evaluation\n", + "\n", + "- Zeilscheiben plot mit statistischen kreisen, auf der seite je ein binning plot\n", + "- FFt\n", + "- Moving avarage\n", + "-" + ], + "id": "62f32f705df821b4" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T12:41:09.634778Z", + "start_time": "2025-07-26T12:41:09.576648Z" + } + }, + "cell_type": "code", + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# === CONFIGURATION ===\n", + "ROOT_DIR = rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\" # ← Change this to your root directory\n", + "# =====================\n", + "output1 = widgets.Output()\n", + "output2 = widgets.Output()\n", + "output3 = widgets.Output()\n", + "def list_subfolders(path):\n", + " \"\"\"Return sorted list of subdirectories of a given path\"\"\"\n", + " if os.path.isdir(path):\n", + " return sorted([\n", + " f for f in os.listdir(path)\n", + " if os.path.isdir(os.path.join(path, f))\n", + " ])\n", + " return []\n", + "\n", + "# First dropdown: subfolders of ROOT_DIR\n", + "first_dropdown = widgets.Dropdown(\n", + " options=list_subfolders(ROOT_DIR),\n", + " description='Folder:',\n", + " layout=widgets.Layout(width='50%')\n", + ")\n", + "\n", + "# Second dropdown: subfolders of the selected folder\n", + "second_dropdown = widgets.Dropdown(\n", + " options=[],\n", + " description='Subfolder:',\n", + " layout=widgets.Layout(width='50%')\n", + ")\n", + "displyscatter = widgets.Button(description='Display Scatterplot', layout=widgets.Layout(width='50%'))\n", + "displyFFT = widgets.Button(description='Display PFT', layout=widgets.Layout(width='50%'))\n", + "displyRaw = widgets.Button(description='Display RAW', layout=widgets.Layout(width='50%'))\n", + "\n", + "# Function to update second dropdown when first changes\n", + "def on_button_clicked(o):\n", + " with output1:\n", + " clear_output()\n", + " print(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + " display_my(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + "def on_button_clicked_ft(o):\n", + " with output1:\n", + " clear_output()\n", + " print(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + " display_my_ft(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + "def on_btn_clicked_raw(o):\n", + " with output3:\n", + " clear_output()\n", + " print(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + " display_raw(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\{first_dropdown.value}\\{second_dropdown.value}\")\n", + "def update_second_dropdown(change):\n", + " selected_folder = os.path.join(ROOT_DIR, change['new'])\n", + " subfolders = list_subfolders(selected_folder)\n", + " second_dropdown.options = subfolders if subfolders else [\"\"]\n", + " second_dropdown.value = subfolders[0] if subfolders else \"\"\n", + "\n", + "# Trigger update on change\n", + "first_dropdown.observe(update_second_dropdown, names='value')\n", + "\n", + "# Initial population\n", + "if first_dropdown.options:\n", + " first_dropdown.value = first_dropdown.options[0]\n", + " update_second_dropdown({'new': first_dropdown.value})\n", + "\n", + "# Display the widgets\n", + "display(first_dropdown, second_dropdown)\n", + "\n", + "#------------------------------------------------------------------------------------------------\n", + "def get_pixel_size(path):\n", + " config = myu.load_object(path)\n", + " return config.get(\"pixel_size_mu\")\n", + "def scatter_hist(x, y, ax, ax_histx, ax_histy):\n", + " # no labels\n", + " ax_histx.tick_params(axis=\"x\", labelbottom=False)\n", + " ax_histy.tick_params(axis=\"y\", labelleft=False)\n", + "\n", + " # the scatter plot:\n", + " ax.scatter(x, y)\n", + "\n", + " # now determine nice limits by hand:\n", + " binwidth = 0.15\n", + " xmax = np.max(np.abs(x))\n", + " xmin = np.min(np.abs(x))\n", + " ymin = np.min(np.abs(y))\n", + " ymax = np.max(np.abs(y))\n", + " neglimx = (int(xmin)/binwidth+1)*binwidth\n", + " neglimy = (int(ymin)/binwidth+1)*binwidth\n", + " limx = (int(xmax/binwidth) + 1) * binwidth\n", + " limy = (int(ymax/binwidth) + 1) * binwidth\n", + "\n", + " #---------------stats------------\n", + " #Calc statistics\n", + " rms_x = np.sqrt(np.mean(np.square(x)))\n", + " rms_y = np.sqrt(np.mean(np.square(y)))\n", + " max_x = max(x)+0.1\n", + " max_y = max(y)+0.1\n", + " min_x = min(x)-0.1\n", + " min_y = min(y)-0.1\n", + " std_x = np.std(x)\n", + " std_y = np.std(y)\n", + " x_p2v = max_x-min_x\n", + " y_p2v = max_y-min_y\n", + "\n", + "\n", + " textstr = (f'Statistics| X | Y |\\n'\n", + " f' STD |{std_x:.2f}|{std_y:.2f}|\\n'\n", + " f' P2V |{x_p2v:.2f}|{y_p2v:.2f}|\\n ')\n", + "\n", + " props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n", + "\n", + "# place a text box in upper left in axes coords\n", + " ax.text(0.05, 0.95, textstr, transform=ax.transAxes, fontsize=10,\n", + " verticalalignment='top', bbox=props)\n", + "\n", + " bins_x = np.arange(neglimx, limx + binwidth, binwidth)\n", + " bins_y = np.arange(neglimy, limy + binwidth, binwidth)\n", + " ax_histx.hist(x, bins=bins_x)\n", + " ax_histy.hist(y, bins=bins_y, orientation='horizontal')\n", + "\n", + "def display_my(path):\n", + "\n", + " axis_data_file_path_1 = myu.find_newest_dat_file(path)\n", + " #mf.analyze_repeatability(axis_data_file_path_1,1.1)\n", + "\n", + "\n", + " x_vals1, y_vals1, times1 = myu.load_xy_data(axis_data_file_path_1)\n", + " #x_vals1 = x_vals1- np.mean(x_vals1)\n", + " #y_vals1 = y_vals1- np.mean(y_vals1)\n", + "\n", + " # Fixing random state for reproducibility\n", + "\n", + "\n", + " # some random data\n", + " conf_path = path.split(\"\\\\\")[-1]\n", + " conf_path = conf_path.split(\"_\")[0]\n", + " print(conf_path)\n", + " x = x_vals1*get_pixel_size(rf\"{path}\\conf_{conf_path}.json\")\n", + " y = y_vals1*get_pixel_size(rf\"{path}\\conf_{conf_path}.json\")\n", + "\n", + "\n", + "\n", + "\n", + "\n", + " fig, axs = plt.subplot_mosaic([['histx', '.'],\n", + " ['scatter', 'histy']],\n", + " figsize=(6, 6),\n", + " width_ratios=(4, 1), height_ratios=(1, 4),\n", + " layout='constrained')\n", + "\n", + " scatter_hist(x, y, axs['scatter'], axs['histx'], axs['histy'])\n", + " plt.show()\n", + "\n", + "\n", + "\n", + " import matplotlib.mlab as mlab\n", + "\n", + " # Fixing random state for reproducibility\n", + "def display_my_ft(path):\n", + " axis_data_file_path_1 = myu.find_newest_dat_file(path)\n", + " #mf.analyze_repeatability(axis_data_file_path_1,1.1)\n", + "\n", + "\n", + " x_vals1, y_vals1, times1 = myu.load_xy_data(axis_data_file_path_1)\n", + " # some random data\n", + " conf_path = path.split(\"\\\\\")[-1]\n", + " conf_path = conf_path.split(\"_\")[0]\n", + " print(conf_path)\n", + " x = x_vals1*get_pixel_size(rf\"{path}\\conf_{conf_path}.json\")\n", + " y = y_vals1*get_pixel_size(rf\"{path}\\conf_{conf_path}.json\")\n", + " dt = 50\n", + " t = np.arange(0, len(x)*dt, dt)\n", + "\n", + "\n", + " fig, (ax0, ax1) = plt.subplots(2, 1, layout='constrained')\n", + " ax0.plot(t, x)\n", + " ax0.set_xlabel('Time (s)')\n", + " ax0.set_ylabel('Signal')\n", + " ax1.psd(x, NFFT=512, Fs=1 / dt)\n", + "\n", + " plt.show()\n", + "\n", + "def display_raw(path):\n", + " axis_data_file_path_1 = myu.find_newest_dat_file(path)\n", + " #mf.analyze_repeatability(axis_data_file_path_1,1.1)\n", + "\n", + "\n", + " x_vals1, y_vals1, times1 = myu.load_xy_data(axis_data_file_path_1)\n", + " print(\"h\")\n", + " # some random data\n", + " conf_path = path.split(\"\\\\\")[-1]\n", + " conf_path = conf_path.split(\"_\")[0]\n", + " print(conf_path)\n", + " a = 250\n", + " b = 2500\n", + " # Convert pixel values and slice the relevant time window\n", + " scale = get_pixel_size(rf\"{path}\\conf_{conf_path}.json\")\n", + " x = (x_vals1 * scale)#[a:b]\n", + " y = (y_vals1 * scale)#[a:b]\n", + " times1 = times1#[a:b]\n", + "\n", + " # Compute statistics\n", + " stdx = np.std(x)\n", + " stdy = np.std(y)\n", + " meanx = np.mean(x)\n", + " meany = np.mean(y)\n", + "\n", + " # Optional: Prepare stats text box (currently unused)\n", + " textstra = (\n", + " f'Statistics| X | Y |\\n'\n", + " f' STD |{stdx:.2f}|{stdy:.2f}|\\n'\n", + " f' MEAN |{meanx:.2f}|{meany:.2f}|\\n'\n", + " )\n", + "\n", + " # Create subplots\n", + " fig_raw, (ax1_raw, ax2_raw) = plt.subplots(2, 1, figsize=(10, 6))\n", + "\n", + " # Plot x over time with mean and ±std deviation\n", + " ax1_raw.plot(times1, x, label=\"X Position\")\n", + " \"\"\"ax1_raw.axhline(meanx, color='green', linestyle='-', label='Mean')\n", + " ax1_raw.axhline(meanx + stdx, color='red', linestyle='--', label='+1 STD')\n", + " ax1_raw.axhline(meanx - stdx, color='red', linestyle='--', label='-1 STD')\n", + "\n", + " # Optionally add statistics as a text box\n", + " props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n", + " ax1_raw.text(0.02, 0.95, textstra, transform=ax1_raw.transAxes, fontsize=10,\n", + " verticalalignment='top', bbox=props)\"\"\"\n", + "\n", + " ax1_raw.set_xlabel('Time (s)')\n", + " ax1_raw.set_ylabel('X Position')\n", + " ax1_raw.legend()\n", + " ax1_raw.margins(0.05)\n", + "\n", + " # Plot y over time\n", + " ax2_raw.plot(times1, y, label=\"Y Position\", color='blue')\n", + " ax2_raw.axhline(meany, color='green', linestyle='-', label='Mean')\n", + " ax2_raw.set_xlabel('Time (s)')\n", + " ax2_raw.set_ylabel('Y Position')\n", + " ax2_raw.legend()\n", + " ax2_raw.margins(0.05)\n", + "\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "\n", + "\n", + "displyscatter.on_click(on_button_clicked)\n", + "displyRaw.on_click(on_btn_clicked_raw)\n", + "displyFFT.on_click(on_button_clicked_ft)\n", + "display(displyscatter, output1)\n", + "display(displyFFT, output2)\n", + "display(displyRaw, output3)\n" + ], + "id": "3e70c2ebec687fe0", + "outputs": [ + { + "data": { + "text/plain": [ + "Dropdown(description='Folder:', layout=Layout(width='50%'), options=('20250715_alignment_tests', 'Current', 'T…" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "679b2a06602f459dac397eb838b3bf92" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Dropdown(description='Subfolder:', layout=Layout(width='50%'), options=('20250715_133131_repeatibility_0', '20…" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "27fdca6954f44679b7ec236bb37f2992" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Button(description='Display Scatterplot', layout=Layout(width='50%'), style=ButtonStyle())" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "04e472e7131640cb84450bf2eddf5fe5" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Output()" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "216ae33b6a64400e95e42d054b46f955" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Button(description='Display PFT', layout=Layout(width='50%'), style=ButtonStyle())" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "9fabae9096b643129b584fe40ecc844e" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Output()" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "001a6aed26ca4ce28fbca9cd32af9130" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Button(description='Display RAW', layout=Layout(width='50%'), style=ButtonStyle())" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "30d256f3f0ec420c93f19cc064fb09f3" + } + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Output()" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "ae9c7e6f769342f69204b6d0526b44f4" + } + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "execution_count": 4 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T12:41:09.776589Z", + "start_time": "2025-07-26T12:41:09.659609Z" + } + }, + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "np.random.seed(19680801)\n", + "\n", + "fig, ax = plt.subplots()\n", + "x = 30*np.random.randn(10000)\n", + "mu = x.mean()\n", + "median = np.median(x)\n", + "sigma = x.std()\n", + "textstr = \"hello\"\n", + "\n", + "ax.hist(x, 50)\n", + "# these are matplotlib.patch.Patch properties\n", + "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n", + "\n", + "# place a text box in upper left in axes coords\n", + "ax.text(0.05, 0.95, textstr, transform=ax.transAxes, fontsize=14,\n", + " verticalalignment='top', bbox=props)\n", + "\n", + "plt.show()" + ], + "id": "9f3a5361dcc6f7f7", + "outputs": [ + { + "data": { + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ], + "image/png": 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Bearbeitete Punkte\n", + "\n", + "- Wie besprochen habe ich das verhalten der Achse untersucht, nach dem \"Betriebstemperatur\" erreicht wurde.\n", + "- Ebenfals habe ich begonnen mit der Optimierung des Regelkreises.\n", + "- Nach Recherche habe ich eine grobe Temperatur kompensation modelliert aufgrund eine Papers der EFEL über einen Aufbau mit vergleichbahren genauigkeitsanforderungen\n", + "---\n", + "## Messung\n", + "Es wurde über Nacht gemessen, mit einer Zykluszeit von 20s. Dammit wurde die Aufheizzeit verkürzt und mehr messungen durchgeführt wie mit einer Zykluszeit von 50s. In der Zeit, in der die Raumtemperatur konstant/glatt gestiegen und die Baugruppe aufgeheizt ist konnten akzeptable resultate erreicht werden. Die Temperaturschwankungen am Morgen hatten einen erheblichen einfluss auf die x Achse. Es ist noch ein leichter Anstieg erkennbar welcher eine korrelation zu der Raumtemparatur aufweisst.\n", + "| | |\n", + "|--------|--------------|\n", + "|Messdauer |15.5h |\n", + "| Zyklusszeit| 20s |\n", + "\n", + "### Stabieler Zeitrahmen\n", + "\n", + "![](../Images_doku/stable_x.png)\n", + "\n", + "### Gesammte Messung\n", + "\n", + "![](../Images_doku/complete.png)\n", + "## Room Temperatur\n", + "Die Raumtemperatur ist über den \"stabielen\" Zeitraum konstannt gesunken, was Statistisch eine starke negative korrelation mit der Position der X Achse hat.\n", + "\n", + "![](../Images_doku/roomTemp.png)\n", + "\n", + "## Temperataurkorrektur\n", + "\n", + "Von der EPFL gibt es ein Paper, welches sich mit der Thematik von thermischen Einflüssen bei \"high pressision positioning\" befasst. (THERMAL BEHAVIOR OF AN ULTRA HIGH-PRECISION LINEAR AXIS OPERATING IN INDUSTRIAL ENVIRONMENT Emanuele Lubrano, Prof. Reymond Clavel) In diesem Paper wurde eine 10x verbesserung erreicht. Ich habe die verwendeten Methoden getestet (etwa 40' investiert). Ich habe ein modell anhanden von einer Statischen Messung berrechnet und dann an den neuen Daten(oben) getested. Ich konnte eine erhebliche verbesserung erzielen.\n", + "\n", + "Kleine unterschiede konnte ich schon nach einem kleinen Datensatz korrigieren, bei gösseren Unterscheiden èberreagiert das modell noch etwass... das könnte aber mit bessere Datenaufberreitung und mehr Daten erheblich verbessert werden.\n", + "\n", + "| Farbe | Typ | STD [um] |\n", + "|-------|------------|-----------|\n", + "| orang | Korrigiert | 0.0797 |\n", + "| blau | Messung | 0.2358 |\n", + "\n", + "![](../Images_doku/Corrected.png)\n", + "\n", + "## Aktuelle einschätzung\n", + "Es kann mit dem aktuellen aufbau in einer Kontrollierteren umgebung die geforderte präzission erreicht werden. Es könnte mit wenig aufwand durch einbindung von 3-12 Temperatursensoren noch eine sprübare verbesserung erreicht werden.\n", + "## Controller tuning\n", + "Der geschwindigkeits regler war sehr vorsichtig eingestellt. Von Beckhof ist ein PI-Regler vorgegeben jedoch wäre ein Lead regler mit DC-Verstärkung besser gewesen. Ich konnte trozdem die Bandbreite verdoppeln. Die Dämpfung ist knapp unter dem Idealwert und kann bei Bedarf noch reduziert werden.\n", + "\n", + "| Regler | Gain Margin | Gain Margin | Bandbreite (rad/s) |\n", + "|--------|-------------|-------------|--------------------|\n", + "| Alt | 15.5h | 15.5h | 497 |\n", + "| Neu | 5.31 | 53deg | 1080 |\n", + "| Ideal | 6dB | 60deg | - |\n", + "\n", + "![](../Images_doku/ctr_improvements.png)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70b189cd3543994", + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T19:11:29.972122Z", + "start_time": "2025-07-26T19:11:29.966473Z" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/Analytics.ipynb b/notebooks/Analytics.ipynb index d09e55e..38ad8da 100644 --- a/notebooks/Analytics.ipynb +++ b/notebooks/Analytics.ipynb @@ -1,13 +1,25 @@ { "cells": [ { + "cell_type": "code", + "execution_count": 6, + "id": "ca3c9c7af43b4e58", "metadata": { "ExecuteTime": { - "end_time": "2025-07-24T06:29:19.643098Z", - "start_time": "2025-07-24T06:29:19.585285Z" + "end_time": "2025-07-26T12:41:08.574768Z", + "start_time": "2025-07-26T12:41:08.481768Z" } }, - "cell_type": "code", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Scripts\n", + "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\n" + ] + } + ], "source": [ "import sys\n", "from time import sleep\n", @@ -63,40 +75,57 @@ "import ad\n", "import sys\n", "import os" - ], - "id": "ca3c9c7af43b4e58", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Scripts\n", - "Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\n" - ] - } - ], - "execution_count": 1 + ] }, { - "metadata": {}, "cell_type": "markdown", + "id": "ca5359d36ec7f8ff", + "metadata": {}, "source": [ "## Temperature time plot analysis\n", "\n", "The two CrNi temperature probes show a peridical temperature fluctuation of 1${\\textdegree}$C which is unlikely to be true.\n", "Reason, only the CrNi probes have this fluctuation and the P304 at the same place dont show that fluctuation.\n", "For future data analysis i recomand to pass them throug a BP or LP filter since it looks like the avg is still usable.\n" - ], - "id": "ca5359d36ec7f8ff" + ] }, { + "cell_type": "code", + "execution_count": 26, + "id": "52db5e2c12fea30c", "metadata": { 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+ "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "data_folder = r'C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\Temp'\n", "%matplotlib widget\n", @@ -124,10 +153,11 @@ " step = max((ind_max - ind_min) // 1000, 1)\n", "\n", " for i in range(5):\n", - " line, = ax.plot(times[ind_min:ind_max:step],\n", + " if (i==2):\n", + " line, = ax.plot(times[ind_min:ind_max:step],\n", " temps[i][ind_min:ind_max:step],\n", " label=labels[i], color=colors[i])\n", - " lines.append(line)\n", + " lines.append(line)\n", "\n", " ax.set_title(\"Temperature Over Time\")\n", " ax.set_xlabel(\"Time\")\n", @@ -145,7 +175,7 @@ " ind_min, ind_max = np.searchsorted(t_nums, xlim)\n", " ind_max = min(len(times), ind_max)\n", " step = max((ind_max - ind_min) // 1000, 1)\n", - "\n", + " \n", " for line, temp_data in zip(lines, temps):\n", " line.set_data(times[ind_min:ind_max:step], temp_data[ind_min:ind_max:step])\n", "\n", @@ -154,239 +184,33 @@ " fig_temp.canvas.draw_idle()\n", "\n", "# Hook zoom & pan events\n", - "fig_temp.canvas.mpl_connect('button_release_event', update_plot)\n", - "fig_temp.canvas.mpl_connect('scroll_event', update_plot)\n", - "fig_temp.canvas.mpl_connect('motion_notify_event', update_plot)\n", + "#fig_temp.canvas.mpl_connect('button_release_event', update_plot)\n", + "#fig_temp.canvas.mpl_connect('scroll_event', update_plot)\n", + "#fig_temp.canvas.mpl_connect('motion_notify_event', update_plot)\n", "\n", "# Run\n", "plot_initial()\n", - "update_plot()\n", - "plt.tight_layout()\n", - "fig_temp.canvas.draw_idle()" - ], - "id": "52db5e2c12fea30c", - "outputs": [ - { - "data": { - "text/plain": [ - "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" - ], - "image/png": 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", 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path.split(\"\\\\\")\n", - "\n", - " new_entry = pd.DataFrame([{\n", - " \"day_time\":singel[-1],\n", - " \"x_std\": x_std,\n", - " \"y_std\": y_std,\n", - " \"x_p2v\": x_p2v,\n", - " \"y_p2v\": y_p2v,\n", - " \"pooling\": pooling,\n", - " \"nr of measurements\": nr_of_cycles\n", - " }])\n", - " if os.path.exists(STATIC_LOG_FILE):\n", - " old_log = pd.read_csv(STATIC_LOG_FILE)\n", - " new_log = pd.concat([old_log, new_entry], ignore_index=True)\n", - " else:\n", - " new_log = new_entry\n", - " new_log.to_csv(STATIC_LOG_FILE, index=False)\n", - " print(\"Static test logged.\")\n", - "\n", - "def remove_duplicate_static_tests(log_file=\"static_tests_log.csv\"):\n", - " if not os.path.exists(log_file):\n", - " print(f\"No such file: {log_file}\")\n", - " return\n", - "\n", - " # Load the log\n", - " df = pd.read_csv(log_file)\n", - "\n", - " # Drop duplicate rows\n", - " df_clean = df.drop_duplicates(keep='first')\n", - "\n", - " # Save cleaned log back\n", - " df_clean.to_csv(log_file, index=False)\n", - " print(f\"Removed duplicates. {len(df) - len(df_clean)} rows deleted.\")\n", - "\n", - "def get_pixel_size():\n", - " config = myu.load_object(config_path)\n", - " return config.get(\"pixel_size_mu\")\n", - "\n", - "\n", - "axis_path_1 = myu.get_latest_measurement_dir(2)\n", - "print(axis_path_1)\n", - "axis_path_1 = r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250718_alignment_tests\\20250718_113013_static_0\" #uncomment for specific path\n", - "axis_data_file_path_1 = myu.find_newest_dat_file(axis_path_1)\n", - "print(axis_data_file_path_1)\n", - "#mf.analyze_repeatability(axis_data_file_path_1,1.1)\n", - "\n", - "\n", - "def pool_average_1d(data, pool_size=10):\n", - " data = np.asarray(data)\n", - " remainder = len(data) % pool_size\n", - "\n", - " if remainder != 0:\n", - " # Truncate the extra values that don't fit into a full block\n", - " data = data[:len(data) - remainder]\n", - "\n", - " # Reshape and average\n", - " pooled = data.reshape(-1, pool_size).mean(axis=1)\n", - " return pooled\n", - "\n", - "if pooling == 1:\n", - " x_vals1, y_vals1, times1 = myu.load_xy_data(axis_data_file_path_1)\n", - "\n", - " x_vals = pool_average_1d(x_vals1,10)\n", - " y_vals = pool_average_1d(y_vals1,10)\n", - " times = times1[:len(x_vals)]\n", - " x_vals = x_vals*get_pixel_size()\n", - " y_vals = y_vals*get_pixel_size()\n", - "if pooling == 0:\n", - " x_vals, y_vals, times = myu.load_xy_data(axis_data_file_path_1)\n", - " x_vals = x_vals*get_pixel_size()\n", - " y_vals = y_vals*get_pixel_size()\n", - "\n", - "\n", - "\n", - "#Calc statistics\n", - "rms_x = np.sqrt(np.mean(np.square(x_vals)))\n", - "rms_y = np.sqrt(np.mean(np.square(y_vals)))\n", - "max_x = max(x_vals)+0.1\n", - "max_y = max(y_vals)+0.1\n", - "min_x = min(x_vals)-0.1\n", - "min_y = min(y_vals)-0.1\n", - "std_x = np.std(x_vals)\n", - "std_y = np.std(y_vals)\n", - "x_p2v = max_x-min_x\n", - "y_p2v = max_y-min_y\n", - "\n", - "\n", - "log_static_test(std_x, std_y, x_p2v, y_p2v,len(x_vals),axis_path_1)\n", - "remove_duplicate_static_tests()\n", - "\n", - "print(f'Statistics| X | Y |\\n'\n", - " f' STD |{std_x:.2f}|{std_y:.2f}|\\n'\n", - " f' P2V |{x_p2v:.2f}|{y_p2v:.2f}|\\n ')\n", - "\n", - "fig_static, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(10, 6))\n", - "fig_static.subplots_adjust(hspace=0.3)\n", - "fig_static.suptitle('Static Measurement')\n", - "\n", - "line_x, = ax1.plot([], [], 'o', label=\"X Axis\", color='tab:blue')\n", - "line_y, = ax2.plot([], [], 'o', label=\"Y Axis\", color='tab:green')\n", - "\n", - "cursor1 = Cursor(ax1, useblit=True, color='gray', linewidth=1)\n", - "cursor2 = Cursor(ax2, useblit=True, color='gray', linewidth=1)\n", - "\n", - "ax2.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))\n", - "\n", - "\n", - "# --- Initial Plot ---\n", - "def plot_initial():\n", - " # Plot full data first to avoid axis scaling problems\n", - "\n", - " max_time = max(times)\n", - " min_time = min(times)\n", - " line_x.set_data(times, x_vals)\n", - " line_y.set_data(times, y_vals)\n", - "\n", - " ax1.set_title(\"X Axis Position Over Time\")\n", - " ax2.set_title(\"Y Axis Position Over Time\")\n", - " ax1.set_ylabel(\"X Position um\")\n", - " ax2.set_ylabel(\"Y Position um\")\n", - " ax2.set_xlabel(\"Time\")\n", - "\n", - " ax1.legend()\n", - " ax2.legend()\n", - "\n", - " ax1.set_xlim(min_time, max_time)\n", - " ax2.set_xlim(min_time, max_time)\n", - " ax1.set_ylim(min_x, max_x)\n", - " ax2.set_ylim(min_y, max_y)\n", - "\n", - " # This is critical: tell matplotlib to autoscale *after* setting data\n", - " #ax1.relim()\n", - " #ax2.relim()\n", - " #ax1.autoscale_view()\n", - " #ax2.autoscale_view()\n", - "\n", - "\n", - "# --- Update on Zoom/Pan ---\n", - "def update_plot(event=None):\n", - " xlim = ax2.get_xlim()\n", - " t_nums = mdates.date2num(times)\n", - " ind_min, ind_max = np.searchsorted(t_nums, xlim)\n", - " ind_max = min(len(times), ind_max)\n", - " step = max((ind_max - ind_min) // 1000, 1)\n", - "\n", - " line_x.set_data(times[ind_min:ind_max:step], x_vals[ind_min:ind_max:step])\n", - " line_y.set_data(times[ind_min:ind_max:step], y_vals[ind_min:ind_max:step])\n", - "\n", - " #ax1.relim()\n", - " #ax2.relim()\n", - " ax1.autoscale_view()\n", - " ax2.autoscale_view()\n", - " fig_static.canvas.draw_idle()\n", - "\n", - "\n", - "# --- Connect events ---\n", - "fig_static.canvas.mpl_connect('button_release_event', update_plot)\n", - "fig_static.canvas.mpl_connect('scroll_event', update_plot)\n", - "# DO NOT connect motion_notify_event\n", - "\n", - "# --- Plot ---\n", - "plot_initial()\n", - "update_plot()\n", - "plt.tight_layout()\n", - "plt.show()\n", - "\n", - "pd.read_csv(STATIC_LOG_FILE)\n" - ], - "id": "39fcd9032d757549", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Using daily folder: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250723_alignment_tests\n", + "Using daily folder: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250726_alignment_tests\n", "no measruments on that day\n", "going one day back\n", "no measruments on that day\n", @@ -413,9 +237,11 @@ }, { "data": { - "text/plain": [ - "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" - ], + "application/vnd.jupyter.widget-view+json": { + "model_id": "d3286213b25944489c0b715dd1b18da7", + "version_major": 2, + "version_minor": 0 + }, "image/png": 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20250721_103850_logn_term_0 0.035631 0.024247 0.284975 0.267925 \n", - "8 20250721_112553_logn_term_0 0.049756 1.450272 0.546775 5.374125 \n", - "9 20250721_112553_logn_term_0 0.049689 1.461477 0.546775 5.391725 \n", - "10 20250721_144023_logn_term_0 0.015262 0.020900 0.230525 0.241800 \n", - "11 20250721_144023_logn_term_0 0.069681 0.069454 0.379025 0.402125 \n", - "12 20250721_144023_logn_term_0 0.088759 0.134069 0.543750 0.611125 \n", - "13 20250721_144023_logn_term_0 0.103773 0.226148 0.578125 0.873750 \n", - "14 20250721_144023_logn_term_0 0.185474 0.423430 0.983200 1.703150 \n", - "15 20250721_144023_logn_term_0 0.234443 0.461195 1.104475 1.839550 \n", - "16 20250721_144023_logn_term_0 0.237610 0.459119 1.110800 1.839550 \n", - "17 20250721_144023_logn_term_0 0.226553 0.514204 1.282400 2.050200 \n", - "18 20250721_144023_logn_term_0 0.200072 1.114796 1.282400 4.064025 \n", - "19 20250721_175607_logn_term_0 0.121299 0.083737 0.583900 0.475550 \n", - "20 20250721_175607_logn_term_0 0.327407 3.197995 1.740000 13.552350 \n", - "21 20250722_081704_logn_term_0 0.203145 0.349477 0.831675 1.602500 \n", - "22 20250722_081704_logn_term_0 0.209741 1.011976 1.022525 3.516225 \n", - "23 20250722_081704_logn_term_0 0.211385 1.068260 1.040400 3.713125 \n", - "24 20250722_081704_logn_term_0 0.193727 1.987369 1.091000 6.574775 \n", - "25 20250721_084639_logn_term_0 0.875230 6.333906 3.607800 18.835100 \n", - "26 20250722_105004_static_0 0.061494 0.053333 0.503600 0.429900 \n", - "27 20250721_175607_logn_term_0 1.320786 12.782842 6.360000 53.609400 \n", - "28 20250722_081704_logn_term_0 0.774907 7.949475 3.764000 25.699100 \n", - "29 20250721_175607_logn_term_0 0.330196 3.195711 1.740000 13.552350 \n", - "30 20250722_165648_logn_term_0 0.305185 2.463318 2.038375 9.713625 \n", - "31 20250718_113013_static_0 0.035326 0.058654 0.526975 0.496175 \n", - "\n", - " pooling nr of measurements Comment: \n", - "0 0 1000 raw th cm \n", - "1 0 1000 raw cm \n", - "2 0 1000 raw upscale th cm 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day_timex_stdy_stdx_p2vy_p2vpoolingnr of measurementsComment:
020250718_120836_static_00.1035410.1265690.8248000.74230001000raw th cm
120250718_113636_static_00.0765270.0578640.6818000.52010001000raw cm
220250718_113013_static_00.1413050.2346151.5079001.38470001000raw upscale th cm
320250718_123917_static_00.0502430.0509070.4972750.44667501000raw upscal gaus fit
420250718_123917_static_00.0502430.0509070.4972750.44667501000NaN
520250721_084639_logn_term_00.2188071.5834761.0519504.8587750100NaN
620250721_103850_logn_term_00.0424870.0016500.2849750.20330002NaN
720250721_103850_logn_term_00.0356310.0242470.2849750.26792505NaN
820250721_112553_logn_term_00.0497561.4502720.5467755.3741250134NaN
920250721_112553_logn_term_00.0496891.4614770.5467755.3917250135NaN
1020250721_144023_logn_term_00.0152620.0209000.2305250.24180002NaN
1120250721_144023_logn_term_00.0696810.0694540.3790250.40212506NaN
1220250721_144023_logn_term_00.0887590.1340690.5437500.611125013NaN
1320250721_144023_logn_term_00.1037730.2261480.5781250.873750022NaN
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" @@ -2068,8 +1627,8 @@ }, "tags": [], "ExecuteTime": { - "end_time": "2025-07-23T14:06:57.965272Z", - "start_time": "2025-07-23T14:06:57.953933Z" + "end_time": "2025-08-07T14:46:40.906170200Z", + "start_time": "2025-08-07T14:12:03.840798Z" } }, "source": [ @@ -2090,12 +1649,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "[-10, 10]\n", - "[1, 5]\n", - "-10\n", + "[-1, 1]\n", + "[1, 1]\n", + "-1\n", "1\n", - "10\n", - "5\n" + "1\n", + "1\n" ] } ], @@ -2104,8 +1663,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2025-07-23T14:06:58.747813Z", - "start_time": "2025-07-23T14:06:58.477370Z" + "end_time": "2025-08-07T14:46:40.907172Z", + "start_time": "2025-08-07T14:12:03.861481Z" } }, "cell_type": "code", @@ -2179,7 +1738,7 @@ "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, - "model_id": "1b2cc27f5b7d444b96e0eb4eeb684ffb" + "model_id": "35ea1d0c8c094a8f857f475f84ad0034" } }, "metadata": {}, @@ -2191,8 +1750,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2025-07-23T14:06:58.899494Z", - "start_time": "2025-07-23T14:06:58.893719Z" + "end_time": "2025-08-07T14:46:40.907172Z", + "start_time": "2025-08-07T14:12:04.069811Z" } }, "cell_type": "code", diff --git a/notebooks/Messbericht26725.html b/notebooks/Messbericht26725.html new file mode 100644 index 0000000..cec9319 --- /dev/null +++ b/notebooks/Messbericht26725.html @@ -0,0 +1,7630 @@ + + + + + +Messbericht26725 + + + + + + + + + + + + +
+ +
+ + diff --git a/notebooks/Messbericht26725.ipynb b/notebooks/Messbericht26725.ipynb new file mode 100644 index 0000000..bcc98b8 --- /dev/null +++ b/notebooks/Messbericht26725.ipynb @@ -0,0 +1,128 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ee798c5daafd13a4", + "metadata": {}, + "source": [ + "# 📊 Resultate Messung\n", + "\n", + "**Autor:** Roman Berti\n", + "**Datum:** 26.07.25\n", + "**Versuchsbezeichnung:**\n", + "\n", + "---\n", + "\n", + "## 1. Bearbeitete Punkte\n", + "\n", + "- Wie besprochen habe ich das verhalten der Achse untersucht, nach dem \"Betriebstemperatur\" erreicht wurde.\n", + "- Ebenfalls habe ich begonnen mit der Optimierung des Regelkreises.\n", + "- Nach Recherche habe ich eine grobe Temperatur kompensation modelliert aufgrund eine Papers der EFEL über einen Aufbau mit vergleichbahren genauigkeitsanforderungen\n", + "---\n", + "## Messung\n", + "Es wurde über Nacht gemessen, mit einer Zykluszeit von 20s. Dammit wurde die Aufheizzeit verkürzt und mehr messungen durchgeführt wie mit einer Zykluszeit von 50s. In der Zeit, in der die Raumtemperatur konstant/glatt gestiegen und die Baugruppe aufgeheizt ist konnten akzeptable resultate erreicht werden. Die Temperaturschwankungen am Morgen hatten einen erheblichen einfluss auf die x Achse. Es ist noch ein leichter Anstieg erkennbar welcher eine korrelation zu der Raumtemparatur aufweist.\n", + "| | |\n", + "|--------|--------------|\n", + "|Messdauer |15.5h |\n", + "| Zyklusszeit| 20s |\n", + "\n", + "### Stabiler Zeitrahmen\n", + "\n", + "![](../Images_doku/stable_x.png)\n", + "\n", + "### Gesammmte Messung\n", + "\n", + "![](../Images_doku/complete.png)\n", + "## Raum Temperatur\n", + "Die Raumtemperatur ist über den \"stabilen\" Zeitraum konstant gesunken, was Statistisch eine starke negative korrelation mit der Position der X Achse hat.\n", + "\n", + "![](../Images_doku/roomTemp.png)\n", + "\n", + "## Temperataurkorrektur\n", + "\n", + "Von der EPFL gibt es ein Paper, welches sich mit der Thematik von thermischen Einflüssen bei \"high precision positioning\" befasst. (THERMAL BEHAVIOR OF AN ULTRA HIGH-PRECISION LINEAR AXIS OPERATING IN INDUSTRIAL ENVIRONMENT Emanuele Lubrano, Prof. Reymond Clavel) In diesem Paper wurde eine 10x verbesserung erreicht. Ich habe die verwendeten Methoden getestet (etwa 40' investiert). Ich habe ein modell annhanden von einer Statischen Messung berechnet und dann an den neuen Daten(oben) getested. Ich konnte eine erhebliche verbesserung erzielen.\n", + "\n", + "Kleine unterschiede konnte ich schon nach einem kleinen Datensatz korrigieren, bei grösseren Unterscheiden überreagiert das Modell noch etwas... das könnte aber mit bessere Datenaufberreitung und mehr Daten erheblich verbessert werden.\n", + "\n", + "| Farbe | Typ | STD [um] |\n", + "|-------|------------|-----------|\n", + "| orang | Korrigiert | 0.0797 |\n", + "| blau | Messung | 0.2358 |\n", + "\n", + "![](../Images_doku/Corrected.png)\n", + "\n", + "## Aktuelle einschätzung\n", + "Es kann mit dem aktuellen Aufbau in einer Kontrollierteren umgebung die geforderte Präzission erreicht werden. Es könnte mit relativ wenig Aufwand durch einbindung von 3-12 Temperatursensoren noch eine spürbare Verbesserung erreicht werden.\n", + "## Controller tuning\n", + "Der Geschwindigkeits regler war sehr vorsichtig eingestellt. Von Beckhof ist ein PI-Regler vorgegeben jedoch wäre ein Lead regler mit DC-Verstärkung besser gewesen. Ich konnte trotzdem die Bandbreite verdoppeln. Die Dämpfung ist knapp unter dem Idealwert und kann bei Bedarf noch reduziert werden.\n", + "\n", + "| Geschwindigkeits Regler | Kp | Tn |\n", + "|-------------------------|-------|-------|\n", + "| Alt | 0.145 | 0.015 |\n", + "| Neu | 0.21 | 0.05 |\n", + "\n", + "Kp wurde so gewählt um die Crossoverfrequenz der integrierenden Strecke nach rechts zu verschieben.\n", + "Tn wurde so gewählt, dass eine kleine anhebung der Phase bei der Crossowerfrequency zu erhalten, ohne dabei die Gainmargin signifikant zu verschlechtern.\n", + "\n", + "\n", + "| Regler | Gain Margin | Gain Margin | Bandbreite (rad/s) |\n", + "|--------|-------------|-------------|--------------------|\n", + "| Alt | 11.5 | 97 | 497 |\n", + "| Neu | 5.31 | 53deg | 1080 |\n", + "| Ideal | 6dB | 60deg | - |\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "![](../Images_doku/ctr_improvements.png)\n", + "### Zeitliche Auswertung\n", + "Die Zeitliche auswertung ist weniger aussagekräftig, da kein Unit stepp gefahren werden sollte um die Mechanik nicht zu strapazieren jedoch kann auch an einem abgeflachten step gut gezeigt werden, dass der neue regler schneller ist. Somit kann ein kleineres Kp für den Positionsregler gewählt werden.\n", + "\n", + "| Regler | Erreichen des sollwertes |\n", + "|--------|--------------------------|\n", + "| Alt | ca 5s |\n", + "| Neu | ca 0.5s |\n", + "\n", + "### Optimierung\n", + "Die Messung wurde mit einem Kp= 10 für den Positionsregler gemessen. Mann könte diesen gut noch bis 50 erhöhen um einen noch dynamischeren Regler zu erhalten.\n", + "\n", + "![](../Images_doku/TimeNewCtr.png)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70b189cd3543994", + "metadata": { + "ExecuteTime": { + "end_time": "2025-07-26T19:11:29.972122Z", + "start_time": "2025-07-26T19:11:29.966473Z" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/controller_improvements_log.csv b/notebooks/controller_improvements_log.csv index a58e5f9..46ea677 100644 --- a/notebooks/controller_improvements_log.csv +++ b/notebooks/controller_improvements_log.csv @@ -30,3 +30,9 @@ timestamp,description,measurement_id,notes 2025-07-23 10:28:59.189434,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction 2025-07-23 10:37:17.152356,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction 2025-07-23 16:06:57.448192,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-07-24 09:25:29.802605,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-08-04 08:16:40.209891,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-08-04 10:08:57.458225,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-08-07 10:14:54.174727,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-08-07 10:16:11.738536,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction +2025-08-07 16:12:03.814783,Tuned PID gains for better damping,meas_20250710_120000,Observed 30% overshoot reduction diff --git a/notebooks/sandbox.ipynb b/notebooks/sandbox.ipynb index 086357e..61676c7 100644 --- a/notebooks/sandbox.ipynb +++ b/notebooks/sandbox.ipynb @@ -6,8 +6,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2025-07-22T15:05:19.237001Z", - "start_time": "2025-07-22T15:05:19.171109Z" + "end_time": "2025-07-26T07:09:44.745838Z", + "start_time": "2025-07-26T07:09:44.662792Z" } }, "source": [ @@ -75,7 +75,7 @@ ] } ], - "execution_count": 1 + "execution_count": 2 }, { "metadata": { @@ -172,8 +172,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2025-07-22T15:09:12.330740Z", - "start_time": "2025-07-22T15:09:12.188939Z" + "end_time": "2025-07-26T07:09:49.740401Z", + "start_time": "2025-07-26T07:09:49.473670Z" } }, "cell_type": "code", @@ -259,13 +259,13 @@ "output_type": "display_data" } ], - "execution_count": 8 + "execution_count": 3 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-07-22T15:09:24.145183Z", - "start_time": "2025-07-22T15:09:24.140602Z" + "end_time": "2025-07-26T07:09:53.673941Z", + "start_time": "2025-07-26T07:09:53.667050Z" } }, "cell_type": "code", @@ -326,13 +326,13 @@ ] } ], - "execution_count": 10 + "execution_count": 4 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-07-22T15:20:48.534564Z", - "start_time": "2025-07-22T15:20:46.975646Z" + "end_time": "2025-07-26T07:09:58.051877Z", + "start_time": "2025-07-26T07:09:56.053437Z" } }, "cell_type": "code", @@ -441,13 +441,13 @@ "output_type": "display_data" } ], - "execution_count": 24 + "execution_count": 5 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-07-22T15:09:17.267472Z", - "start_time": "2025-07-22T15:09:16.942192Z" + "end_time": "2025-07-26T07:10:05.391660Z", + "start_time": "2025-07-26T07:10:04.843230Z" } }, "cell_type": "code", @@ -589,13 +589,13 @@ "output_type": "display_data" } ], - "execution_count": 9 + "execution_count": 6 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-07-22T12:28:27.478317Z", - "start_time": "2025-07-22T12:28:27.312550Z" + "end_time": "2025-07-26T07:10:12.816470Z", + "start_time": "2025-07-26T07:10:12.322313Z" } }, "cell_type": "code", @@ -725,16 +725,16 @@ "traceback": [ "\u001B[31m---------------------------------------------------------------------------\u001B[39m", "\u001B[31mValueError\u001B[39m Traceback (most recent call last)", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[17]\u001B[39m\u001B[32m, line 82\u001B[39m\n\u001B[32m 79\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[38;5;28mlen\u001B[39m(T_sink))\n\u001B[32m 80\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[38;5;28mlen\u001B[39m(T_sink_measured))\n\u001B[32m---> \u001B[39m\u001B[32m82\u001B[39m R_est, T3_fit = \u001B[43midentify_parameters\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink_measured\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 84\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[33m\"\u001B[39m\u001B[33mGeschätzte Parameter:\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 85\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[33mf\u001B[39m\u001B[33m\"\u001B[39m\u001B[33mR1 = \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mR_est[\u001B[32m0\u001B[39m]\u001B[38;5;132;01m:\u001B[39;00m\u001B[33m.4f\u001B[39m\u001B[38;5;132;01m}\u001B[39;00m\u001B[33m K/W\u001B[39m\u001B[33m\"\u001B[39m)\n", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[17]\u001B[39m\u001B[32m, line 52\u001B[39m, in \u001B[36midentify_parameters\u001B[39m\u001B[34m(time, T_source, T_sink, T_sink_measured)\u001B[39m\n\u001B[32m 49\u001B[39m R0 = [\u001B[32m842\u001B[39m, \u001B[32m1.0\u001B[39m, \u001B[32m1.0\u001B[39m, \u001B[32m1.0\u001B[39m] \u001B[38;5;66;03m# Startschätzung für R1, R2, R3, R_sink)\u001B[39;00m\n\u001B[32m 50\u001B[39m T0 = [T_source[\u001B[32m0\u001B[39m], T_source[\u001B[32m0\u001B[39m], T_sink[\u001B[32m0\u001B[39m]] \u001B[38;5;66;03m# Initiale Temperaturen für T1, T2, T3\u001B[39;00m\n\u001B[32m---> \u001B[39m\u001B[32m52\u001B[39m result = \u001B[43mleast_squares\u001B[49m\u001B[43m(\u001B[49m\n\u001B[32m 53\u001B[39m \u001B[43m \u001B[49m\u001B[43mresiduals\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 54\u001B[39m \u001B[43m \u001B[49m\u001B[43mR0\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 55\u001B[39m \u001B[43m \u001B[49m\u001B[43mbounds\u001B[49m\u001B[43m=\u001B[49m\u001B[43m(\u001B[49m\u001B[32;43m1e-4\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[32;43m1e3\u001B[39;49m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 56\u001B[39m \u001B[43m \u001B[49m\u001B[43margs\u001B[49m\u001B[43m=\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink_measured\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT0\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 57\u001B[39m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 59\u001B[39m R_estimated = result.x\n\u001B[32m 60\u001B[39m T3_fit = simulate_rc_network(time, T_source, T_sink, R_estimated, T0)\n", + "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[7]\u001B[39m\u001B[32m, line 82\u001B[39m\n\u001B[32m 79\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[38;5;28mlen\u001B[39m(T_sink))\n\u001B[32m 80\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[38;5;28mlen\u001B[39m(T_sink_measured))\n\u001B[32m---> \u001B[39m\u001B[32m82\u001B[39m R_est, T3_fit = \u001B[43midentify_parameters\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink_measured\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 84\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[33m\"\u001B[39m\u001B[33mGeschätzte Parameter:\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 85\u001B[39m \u001B[38;5;28mprint\u001B[39m(\u001B[33mf\u001B[39m\u001B[33m\"\u001B[39m\u001B[33mR1 = \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mR_est[\u001B[32m0\u001B[39m]\u001B[38;5;132;01m:\u001B[39;00m\u001B[33m.4f\u001B[39m\u001B[38;5;132;01m}\u001B[39;00m\u001B[33m K/W\u001B[39m\u001B[33m\"\u001B[39m)\n", + "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[7]\u001B[39m\u001B[32m, line 52\u001B[39m, in \u001B[36midentify_parameters\u001B[39m\u001B[34m(time, T_source, T_sink, T_sink_measured)\u001B[39m\n\u001B[32m 49\u001B[39m R0 = [\u001B[32m842\u001B[39m, \u001B[32m1.0\u001B[39m, \u001B[32m1.0\u001B[39m, \u001B[32m1.0\u001B[39m] \u001B[38;5;66;03m# Startschätzung für R1, R2, R3, R_sink)\u001B[39;00m\n\u001B[32m 50\u001B[39m T0 = [T_source[\u001B[32m0\u001B[39m], T_source[\u001B[32m0\u001B[39m], T_sink[\u001B[32m0\u001B[39m]] \u001B[38;5;66;03m# Initiale Temperaturen für T1, T2, T3\u001B[39;00m\n\u001B[32m---> \u001B[39m\u001B[32m52\u001B[39m result = \u001B[43mleast_squares\u001B[49m\u001B[43m(\u001B[49m\n\u001B[32m 53\u001B[39m \u001B[43m \u001B[49m\u001B[43mresiduals\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 54\u001B[39m \u001B[43m \u001B[49m\u001B[43mR0\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 55\u001B[39m \u001B[43m \u001B[49m\u001B[43mbounds\u001B[49m\u001B[43m=\u001B[49m\u001B[43m(\u001B[49m\u001B[32;43m1e-4\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[32;43m1e3\u001B[39;49m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 56\u001B[39m \u001B[43m \u001B[49m\u001B[43margs\u001B[49m\u001B[43m=\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink_measured\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT0\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 57\u001B[39m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 59\u001B[39m R_estimated = result.x\n\u001B[32m 60\u001B[39m T3_fit = simulate_rc_network(time, T_source, T_sink, R_estimated, T0)\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\_lib\\_util.py:689\u001B[39m, in \u001B[36m_workers_wrapper..inner\u001B[39m\u001B[34m(*args, **kwds)\u001B[39m\n\u001B[32m 687\u001B[39m \u001B[38;5;28;01mwith\u001B[39;00m MapWrapper(_workers) \u001B[38;5;28;01mas\u001B[39;00m mf:\n\u001B[32m 688\u001B[39m kwargs[\u001B[33m'\u001B[39m\u001B[33mworkers\u001B[39m\u001B[33m'\u001B[39m] = mf\n\u001B[32m--> \u001B[39m\u001B[32m689\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mfunc\u001B[49m\u001B[43m(\u001B[49m\u001B[43m*\u001B[49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m*\u001B[49m\u001B[43m*\u001B[49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\optimize\\_lsq\\least_squares.py:926\u001B[39m, in \u001B[36mleast_squares\u001B[39m\u001B[34m(fun, x0, jac, bounds, method, ftol, xtol, gtol, x_scale, loss, f_scale, diff_step, tr_solver, tr_options, jac_sparsity, max_nfev, verbose, args, kwargs, callback, workers)\u001B[39m\n\u001B[32m 922\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m_dummy_hess\u001B[39m(x, *args):\n\u001B[32m 923\u001B[39m \u001B[38;5;66;03m# we don't care about Hessian evaluations\u001B[39;00m\n\u001B[32m 924\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m x\n\u001B[32m--> \u001B[39m\u001B[32m926\u001B[39m vector_fun = \u001B[43mVectorFunction\u001B[49m\u001B[43m(\u001B[49m\n\u001B[32m 927\u001B[39m \u001B[43m \u001B[49m\u001B[43mfun_wrapped\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 928\u001B[39m \u001B[43m \u001B[49m\u001B[43mx0\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 929\u001B[39m \u001B[43m \u001B[49m\u001B[43mjac_wrapped\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 930\u001B[39m \u001B[43m \u001B[49m\u001B[43m_dummy_hess\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 931\u001B[39m \u001B[43m \u001B[49m\u001B[43mfinite_diff_rel_step\u001B[49m\u001B[43m=\u001B[49m\u001B[43mdiff_step\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 932\u001B[39m \u001B[43m \u001B[49m\u001B[43mfinite_diff_jac_sparsity\u001B[49m\u001B[43m=\u001B[49m\u001B[43mjac_sparsity\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 933\u001B[39m \u001B[43m \u001B[49m\u001B[43mfinite_diff_bounds\u001B[49m\u001B[43m=\u001B[49m\u001B[43mbounds\u001B[49m\u001B[43m,\u001B[49m\n\u001B[32m 934\u001B[39m \u001B[43m \u001B[49m\u001B[43mworkers\u001B[49m\u001B[43m=\u001B[49m\u001B[43mworkers\u001B[49m\n\u001B[32m 935\u001B[39m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 936\u001B[39m \u001B[38;5;66;03m###########################################################################\u001B[39;00m\n\u001B[32m 938\u001B[39m f0 = vector_fun.fun(x0)\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\optimize\\_differentiable_functions.py:605\u001B[39m, in \u001B[36mVectorFunction.__init__\u001B[39m\u001B[34m(self, fun, x0, jac, hess, finite_diff_rel_step, finite_diff_jac_sparsity, finite_diff_bounds, sparse_jacobian, workers)\u001B[39m\n\u001B[32m 599\u001B[39m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[33m\"\u001B[39m\u001B[33mWhenever the Jacobian is estimated via \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 600\u001B[39m \u001B[33m\"\u001B[39m\u001B[33mfinite-differences, we require the Hessian to \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 601\u001B[39m \u001B[33m\"\u001B[39m\u001B[33mbe estimated using one of the quasi-Newton \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 602\u001B[39m \u001B[33m\"\u001B[39m\u001B[33mstrategies.\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 604\u001B[39m \u001B[38;5;28mself\u001B[39m.fun_wrapped = _VectorFunWrapper(fun)\n\u001B[32m--> \u001B[39m\u001B[32m605\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43m_update_fun\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 607\u001B[39m \u001B[38;5;28mself\u001B[39m.v = np.zeros_like(\u001B[38;5;28mself\u001B[39m.f)\n\u001B[32m 608\u001B[39m \u001B[38;5;28mself\u001B[39m.m = \u001B[38;5;28mself\u001B[39m.v.size\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\optimize\\_differentiable_functions.py:698\u001B[39m, in \u001B[36mVectorFunction._update_fun\u001B[39m\u001B[34m(self)\u001B[39m\n\u001B[32m 696\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m_update_fun\u001B[39m(\u001B[38;5;28mself\u001B[39m):\n\u001B[32m 697\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28mself\u001B[39m.f_updated:\n\u001B[32m--> \u001B[39m\u001B[32m698\u001B[39m \u001B[38;5;28mself\u001B[39m.f = \u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43mfun_wrapped\u001B[49m\u001B[43m(\u001B[49m\u001B[43mxp_copy\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43mx\u001B[49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 699\u001B[39m \u001B[38;5;28mself\u001B[39m._nfev += \u001B[32m1\u001B[39m\n\u001B[32m 700\u001B[39m \u001B[38;5;28mself\u001B[39m.f_updated = \u001B[38;5;28;01mTrue\u001B[39;00m\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\optimize\\_differentiable_functions.py:415\u001B[39m, in \u001B[36m_VectorFunWrapper.__call__\u001B[39m\u001B[34m(self, x)\u001B[39m\n\u001B[32m 413\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m__call__\u001B[39m(\u001B[38;5;28mself\u001B[39m, x):\n\u001B[32m 414\u001B[39m \u001B[38;5;28mself\u001B[39m.nfev += \u001B[32m1\u001B[39m\n\u001B[32m--> \u001B[39m\u001B[32m415\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m np.atleast_1d(\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43mfun\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m)\u001B[49m)\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\optimize\\_lsq\\least_squares.py:263\u001B[39m, in \u001B[36m_WrapArgsKwargs.__call__\u001B[39m\u001B[34m(self, x)\u001B[39m\n\u001B[32m 262\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m__call__\u001B[39m(\u001B[38;5;28mself\u001B[39m, x):\n\u001B[32m--> \u001B[39m\u001B[32m263\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43mf\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m*\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m*\u001B[49m\u001B[43m*\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[17]\u001B[39m\u001B[32m, line 44\u001B[39m, in \u001B[36mresiduals\u001B[39m\u001B[34m(R_guess, time, T_source, T_sink, T_sink_measured, T0)\u001B[39m\n\u001B[32m 43\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34mresiduals\u001B[39m(R_guess, time, T_source, T_sink, T_sink_measured, T0):\n\u001B[32m---> \u001B[39m\u001B[32m44\u001B[39m T3_simulated = \u001B[43msimulate_rc_network\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mR_guess\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT0\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 45\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m T3_simulated - T_sink_measured\n", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[17]\u001B[39m\u001B[32m, line 29\u001B[39m, in \u001B[36msimulate_rc_network\u001B[39m\u001B[34m(time, T_source, T_sink, R, T0, output)\u001B[39m\n\u001B[32m 27\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34msimulate_rc_network\u001B[39m(time, T_source, T_sink, R, T0, output=\u001B[32m2\u001B[39m):\n\u001B[32m 28\u001B[39m \u001B[38;5;66;03m# Interpolationsfunktionen für Quelle und Senke\u001B[39;00m\n\u001B[32m---> \u001B[39m\u001B[32m29\u001B[39m T_source_func = \u001B[43minterp1d\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mkind\u001B[49m\u001B[43m=\u001B[49m\u001B[33;43m'\u001B[39;49m\u001B[33;43mlinear\u001B[39;49m\u001B[33;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mbounds_error\u001B[49m\u001B[43m=\u001B[49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mfill_value\u001B[49m\u001B[43m=\u001B[49m\u001B[33;43m\"\u001B[39;49m\u001B[33;43mextrapolate\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[32m 30\u001B[39m T_sink_func = interp1d(time, T_sink, kind=\u001B[33m'\u001B[39m\u001B[33mlinear\u001B[39m\u001B[33m'\u001B[39m, bounds_error=\u001B[38;5;28;01mFalse\u001B[39;00m, fill_value=\u001B[33m\"\u001B[39m\u001B[33mextrapolate\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 32\u001B[39m sol = solve_ivp(\n\u001B[32m 33\u001B[39m fun=\u001B[38;5;28;01mlambda\u001B[39;00m t, T: rc_model(t, T, R, T_source_func, T_sink_func),\n\u001B[32m 34\u001B[39m t_span=(time[\u001B[32m0\u001B[39m], time[-\u001B[32m1\u001B[39m]),\n\u001B[32m (...)\u001B[39m\u001B[32m 37\u001B[39m method=\u001B[33m'\u001B[39m\u001B[33mRK45\u001B[39m\u001B[33m'\u001B[39m\n\u001B[32m 38\u001B[39m )\n", + "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[7]\u001B[39m\u001B[32m, line 44\u001B[39m, in \u001B[36mresiduals\u001B[39m\u001B[34m(R_guess, time, T_source, T_sink, T_sink_measured, T0)\u001B[39m\n\u001B[32m 43\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34mresiduals\u001B[39m(R_guess, time, T_source, T_sink, T_sink_measured, T0):\n\u001B[32m---> \u001B[39m\u001B[32m44\u001B[39m T3_simulated = \u001B[43msimulate_rc_network\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_sink\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mR_guess\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT0\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 45\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m T3_simulated - T_sink_measured\n", + "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[7]\u001B[39m\u001B[32m, line 29\u001B[39m, in \u001B[36msimulate_rc_network\u001B[39m\u001B[34m(time, T_source, T_sink, R, T0, output)\u001B[39m\n\u001B[32m 27\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34msimulate_rc_network\u001B[39m(time, T_source, T_sink, R, T0, output=\u001B[32m2\u001B[39m):\n\u001B[32m 28\u001B[39m \u001B[38;5;66;03m# Interpolationsfunktionen für Quelle und Senke\u001B[39;00m\n\u001B[32m---> \u001B[39m\u001B[32m29\u001B[39m T_source_func = \u001B[43minterp1d\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtime\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mT_source\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mkind\u001B[49m\u001B[43m=\u001B[49m\u001B[33;43m'\u001B[39;49m\u001B[33;43mlinear\u001B[39;49m\u001B[33;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mbounds_error\u001B[49m\u001B[43m=\u001B[49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mfill_value\u001B[49m\u001B[43m=\u001B[49m\u001B[33;43m\"\u001B[39;49m\u001B[33;43mextrapolate\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[32m 30\u001B[39m T_sink_func = interp1d(time, T_sink, kind=\u001B[33m'\u001B[39m\u001B[33mlinear\u001B[39m\u001B[33m'\u001B[39m, bounds_error=\u001B[38;5;28;01mFalse\u001B[39;00m, fill_value=\u001B[33m\"\u001B[39m\u001B[33mextrapolate\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 32\u001B[39m sol = solve_ivp(\n\u001B[32m 33\u001B[39m fun=\u001B[38;5;28;01mlambda\u001B[39;00m t, T: rc_model(t, T, R, T_source_func, T_sink_func),\n\u001B[32m 34\u001B[39m t_span=(time[\u001B[32m0\u001B[39m], time[-\u001B[32m1\u001B[39m]),\n\u001B[32m (...)\u001B[39m\u001B[32m 37\u001B[39m method=\u001B[33m'\u001B[39m\u001B[33mRK45\u001B[39m\u001B[33m'\u001B[39m\n\u001B[32m 38\u001B[39m )\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\interpolate\\_interpolate.py:286\u001B[39m, in \u001B[36minterp1d.__init__\u001B[39m\u001B[34m(self, x, y, kind, axis, copy, bounds_error, fill_value, assume_sorted)\u001B[39m\n\u001B[32m 282\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m__init__\u001B[39m(\u001B[38;5;28mself\u001B[39m, x, y, kind=\u001B[33m'\u001B[39m\u001B[33mlinear\u001B[39m\u001B[33m'\u001B[39m, axis=-\u001B[32m1\u001B[39m,\n\u001B[32m 283\u001B[39m copy=\u001B[38;5;28;01mTrue\u001B[39;00m, bounds_error=\u001B[38;5;28;01mNone\u001B[39;00m, fill_value=np.nan,\n\u001B[32m 284\u001B[39m assume_sorted=\u001B[38;5;28;01mFalse\u001B[39;00m):\n\u001B[32m 285\u001B[39m \u001B[38;5;250m \u001B[39m\u001B[33;03m\"\"\" Initialize a 1-D linear interpolation class.\"\"\"\u001B[39;00m\n\u001B[32m--> \u001B[39m\u001B[32m286\u001B[39m \u001B[43m_Interpolator1D\u001B[49m\u001B[43m.\u001B[49m\u001B[34;43m__init__\u001B[39;49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43my\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43maxis\u001B[49m\u001B[43m=\u001B[49m\u001B[43maxis\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m 288\u001B[39m \u001B[38;5;28mself\u001B[39m.bounds_error = bounds_error \u001B[38;5;66;03m# used by fill_value setter\u001B[39;00m\n\u001B[32m 290\u001B[39m \u001B[38;5;66;03m# `copy` keyword semantics changed in NumPy 2.0, once that is\u001B[39;00m\n\u001B[32m 291\u001B[39m \u001B[38;5;66;03m# the minimum version this can use `copy=None`.\u001B[39;00m\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\interpolate\\_polyint.py:58\u001B[39m, in \u001B[36m_Interpolator1D.__init__\u001B[39m\u001B[34m(self, xi, yi, axis)\u001B[39m\n\u001B[32m 56\u001B[39m \u001B[38;5;28mself\u001B[39m.dtype = \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[32m 57\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m yi \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[32m---> \u001B[39m\u001B[32m58\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43m_set_yi\u001B[49m\u001B[43m(\u001B[49m\u001B[43myi\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mxi\u001B[49m\u001B[43m=\u001B[49m\u001B[43mxi\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43maxis\u001B[49m\u001B[43m=\u001B[49m\u001B[43maxis\u001B[49m\u001B[43m)\u001B[49m\n", "\u001B[36mFile \u001B[39m\u001B[32m~\\Python_Projects\\StagePerformaceDocu\\.venv\\Lib\\site-packages\\scipy\\interpolate\\_polyint.py:128\u001B[39m, in \u001B[36m_Interpolator1D._set_yi\u001B[39m\u001B[34m(self, yi, xi, axis)\u001B[39m\n\u001B[32m 126\u001B[39m shape = (\u001B[32m1\u001B[39m,)\n\u001B[32m 127\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m xi \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;129;01mand\u001B[39;00m shape[axis] != \u001B[38;5;28mlen\u001B[39m(xi):\n\u001B[32m--> \u001B[39m\u001B[32m128\u001B[39m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[33m\"\u001B[39m\u001B[33mx and y arrays must be equal in length along \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 129\u001B[39m \u001B[33m\"\u001B[39m\u001B[33minterpolation axis.\u001B[39m\u001B[33m\"\u001B[39m)\n\u001B[32m 131\u001B[39m \u001B[38;5;28mself\u001B[39m._y_axis = (axis % yi.ndim)\n\u001B[32m 132\u001B[39m \u001B[38;5;28mself\u001B[39m._y_extra_shape = yi.shape[:\u001B[38;5;28mself\u001B[39m._y_axis] + yi.shape[\u001B[38;5;28mself\u001B[39m._y_axis+\u001B[32m1\u001B[39m:]\n", @@ -742,13 +742,13 @@ ] } ], - "execution_count": 17 + "execution_count": 7 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-07-23T07:16:42.160862Z", - "start_time": "2025-07-23T07:16:41.989570Z" + "end_time": "2025-07-26T07:10:43.678051Z", + "start_time": "2025-07-26T07:10:43.296728Z" } }, "cell_type": "code", @@ -781,8 +781,8 @@ "\n", "\n", "\n", - "times, temps = myu.load_temp_data(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\Temp\\20250722_081812.dat\")\n", - "x_vals1, y_vals1, times1 = myu.load_xy_data(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250722_alignment_tests\\20250722_165648_logn_term_0\\_logn_term_0.dat\")\n", + "times, temps = myu.load_temp_data(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\Temp\\20250723_131041.dat\")\n", + "x_vals1, y_vals1, times1 = myu.load_xy_data(rf\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250723_alignment_tests\\20250723_171434_repeatibility_0\\repeatibility_0.dat\")\n", "\n", "frame1 =pd.DataFrame({'timestamp':times, 'temp1':temps[0], 'temp2':temps[1], 'temp3':temps[2], 'temp4':temps[3],'temp5':temps[4]})\n", "frame2 = pd.DataFrame({'timestamp':times1,'x':x_vals1,'y':y_vals1})\n", @@ -906,7 +906,7 @@ "text/plain": [ "
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" + "image/png": 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" }, "metadata": {}, "output_type": "display_data" @@ -919,7 +919,7 @@ "[[-2.31598881e-01 -6.57158630e-01 2.06947596e-01]\n", " [-5.03325247e-02 1.00419656e+00 7.25101257e-04]\n", " [-8.36276655e-01 2.82292796e-01 1.04725353e+00]]\n", - "[ 9.18732571 11.00840123 91.40767015]\n" + "[ 6.27697777 9.18971239 69.07482423]\n" ] }, { @@ -927,13 +927,13 @@ "text/plain": [ "
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}, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 27 + "execution_count": 8 }, { "metadata": { diff --git a/notebooks/static_tests_log.csv b/notebooks/static_tests_log.csv index f3b1154..391b2d9 100644 --- a/notebooks/static_tests_log.csv +++ b/notebooks/static_tests_log.csv @@ -31,3 +31,4 @@ day_time,x_std,y_std,x_p2v,y_p2v,pooling,nr of measurements,Comment: 20250721_175607_logn_term_0,0.3301964676496112,3.19571055057788,1.740000000000002,13.552350000000004,0,971, 20250722_165648_logn_term_0,0.3051845471762281,2.463318189260276,2.038375000000002,9.713625,0,1037, 20250718_113013_static_0,0.0353263689337634,0.0586536655624352,0.5269750000000002,0.4961750000000009,0,1000, +20250718_113013_static_0,0.1413054757350538,0.2346146622497411,1.507899999999978,1.384699999999981,0,1000,