Skip to content
Snippets Groups Projects
Commit d62ba377 authored by tuhe's avatar tuhe
Browse files

Updated docs to include description of Autolab

parent afa3d54e
No related branches found
No related tags found
No related merge requests found
...@@ -25,6 +25,17 @@ if __name__ == "__main__": ...@@ -25,6 +25,17 @@ if __name__ == "__main__":
from jinjafy.bibliography_maker import make_bibliography from jinjafy.bibliography_maker import make_bibliography
bib = make_bibliography("../setup.py", "./") bib = make_bibliography("../setup.py", "./")
from unitgrade.utils import Capturing, Capturing2
import os
import subprocess
# with Capturing2() as c:
out = subprocess.check_output("cd ../examples/example_framework/instructor && python -m cs102.report2_grade", shell=True)
out = out.decode("utf-8")
with open("snips/deploy.txt", 'w') as f:
f.write(out)
# os.system("cd ../examples/example_framework/instructor && python -m cs102.report2_grade")
data['bibtex'] = bib data['bibtex'] = bib
data = {**data, **dump_data("../examples")} data = {**data, **dump_data("../examples")}
......
...@@ -3,18 +3,27 @@ ...@@ -3,18 +3,27 @@
| | | |_ __ _| |_| | \/_ __ __ _ __| | ___ | | | |_ __ _| |_| | \/_ __ __ _ __| | ___
| | | | '_ \| | __| | __| '__/ _` |/ _` |/ _ \ | | | | '_ \| | __| | __| '__/ _` |/ _` |/ _ \
| |_| | | | | | |_| |_\ \ | | (_| | (_| | __/ | |_| | | | | | |_| |_\ \ | | (_| | (_| | __/
\___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.5, started: 16/09/2021 17:42:18 \___/|_| |_|_|\__|\____/_| \__,_|\__,_|\___| v0.1.17, started: 20/09/2021 18:56:39

CS 101 Report 2 (use --help for options) CS 102 Report 2 
Question 1: Week1 Question 1: Week1 Question 1: Week1: 0%| | [00:00<?]  Question 1: Week1 
* q1.1) test_add...................................................................................................PASS  * q1.1) test_add: 0%| | [00:00<?]   * q1.1) test_add...................................................................................................PASS
* q1.2) test_reverse...............................................................................................PASS  * q1.2) test_reverse: 0%| | [00:00<?]   * q1.2) test_reverse...............................................................................................PASS
* q1.3) test_output_capture........................................................................................PASS  * q1.3) test_output_capture: 0%| | [00:00<?]   * q1.3) test_output_capture........................................................................................PASS
* q1) Total.................................................................................................... 10/10  * q1) Total.................................................................................................... 10/10
 
Question 2: The same problem as before with nicer titles Question 2: The same problem as before with nicer titles Question 2: The same problem as before with nicer titles: 0%| | [00:00<?]  Question 2: The same problem as before with nicer titles 
* q2.1) Test the addition method add(a,b)..........................................................................PASS  * q2.1) Test the addition method add(a,b): 0%| | [00:00<?]   * q2.1) Test the addition method add(a,b)..........................................................................PASS
* q2.2) Checking if reverse_list([1, 2, 3]) = [3, 2, 1]............................................................PASS  * q2.2) Checking if reverse_list([1, 2, 3]) = [3, 2, 1]: 0%| | [00:00<?]   * q2.2) Checking if reverse_list([1, 2, 3]) = [3, 2, 1]............................................................PASS
* q2) Total...................................................................................................... 8/8  * q2) Total...................................................................................................... 6/6
 
Total points at 17:42:18 (0 minutes, 0 seconds)....................................................................18/18 Total points at 18:56:39 (0 minutes, 0 seconds)....................................................................16/16

Including files in upload...
 * cs102
> Testing token file integrity...
Done!
 
To get credit for your results, please upload the single unmodified file: 
> C:\Users\tuhe\Documents\unitgrade_private\examples\example_framework\instructor\cs102\Report2_handin_16_of_16.token

\ No newline at end of file
......
# This file contains your results. Do not edit its content. Simply upload it as it is. # This file contains your results. Do not edit its content. Simply upload it as it is.
### Content of cs102/report2.py ### ### Content of cs102\deploy.py ###
from cs102.report2 import Report2
from unitgrade_private.hidden_create_files import setup_grade_file_report
from snipper.snip_dir import snip_dir
if __name__ == "__main__":
setup_grade_file_report(Report2)
snip_dir("./", "../../students/cs102", clean_destination_dir=True, exclude=['*.token', 'deploy.py'])
# from unitgrade import evaluate_report_student
# evaluate_report_student(Report2())
### Content of cs102\homework1.py ###
def reverse_list(mylist): #!f #!s;keeptags
"""
Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
reverse_list([1,2,3]) should return [3,2,1] (as a list).
"""
return list(reversed(mylist))
def add(a,b): #!f
""" Given two numbers `a` and `b` this function should simply return their sum:
> add(a,b) = a+b """
return a+b
if __name__ == "__main__":
# Example usage:
print(f"Your result of 2 + 2 = {add(2,2)}")
print(f"Reversing a small list", reverse_list([2,3,5,7])) #!s
### Content of cs102\report2.py ###
from unitgrade.framework import Report from unitgrade.framework import Report
from unitgrade.evaluate import evaluate_report_student from unitgrade.evaluate import evaluate_report_student
...@@ -63,202 +95,171 @@ class Question2(UTestCase): #!s=c ...@@ -63,202 +95,171 @@ class Question2(UTestCase): #!s=c
import cs102 import cs102
class Report2(Report): class Report2(Report):
title = "CS 102 Report 2" title = "CS 102 Report 2"
questions = [(Week1, 10), (Week1Titles, 8)] questions = [(Week1, 10), (Week1Titles, 6)]
pack_imports = [cs102] pack_imports = [cs102]
if __name__ == "__main__": if __name__ == "__main__":
evaluate_report_student(Report2(), unmute=True) evaluate_report_student(Report2(), unmute=True)
### Content of cs102/homework1.py ###
def reverse_list(mylist): #!f #!s;keeptags
"""
Given a list 'mylist' returns a list consisting of the same elements in reverse order. E.g.
reverse_list([1,2,3]) should return [3,2,1] (as a list).
"""
return list(reversed(mylist))
def add(a,b): #!f
""" Given two numbers `a` and `b` this function should simply return their sum:
> add(a,b) = a+b """
return a+b
if __name__ == "__main__":
# Example usage:
print(f"Your result of 2 + 2 = {add(2,2)}")
print(f"Reversing a small list", reverse_list([2,3,5,7])) #!s
### Content of cs102/deploy.py ###
from cs102.report2 import Report2
from unitgrade_private.hidden_create_files import setup_grade_file_report
from snipper.snip_dir import snip_dir
if __name__ == "__main__":
setup_grade_file_report(Report2)
snip_dir("./", "../../students/cs102", clean_destination_dir=True, exclude=['*.token', 'deploy.py'])
# from unitgrade import evaluate_report_student
# evaluate_report_student(Report2())
---------------------------------------------------------------------- ..ooO0Ooo.. ---------------------------------------------------------------------- ---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
72cd3c247bde457b1bab3441f579961a92feb3ac45c3d60c5abd0217e477d22173e876e4fa3b5aa9de7b8ecca2a10f0a92a6a65a500a1d357e1df4f1d26c6ceb 28268 febdd28d5f815b84049c4bbc5cbdd138912d943553b414adb16f14f6f2d56484fd5cf58dc03d16d36dd6a8285553061e406c3a76db95563c20adc87ee95a1f0f 28760
---------------------------------------------------------------------- ..ooO0Ooo.. ---------------------------------------------------------------------- ---------------------------------------------------------------------- ..ooO0Ooo.. ----------------------------------------------------------------------
./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4IWEUpBdAEABDnVtg2D5l0hTzCulYE/mPjCRVSQLVBoDFQ+OoiI5AfvAzsOXOt00ZJDCkNHDZDyemB5togJOO/cljpTT0ISbXVXUtARc7G8VMzeldC0cuPoK78TyRWOV8JMzaSHDcjyIjOmN32m ./Td6WFoAAATm1rRGAgAhARYAAAB0L+Wj4IaAU/5dAEABDnUpnh+5YXiqpff8T/c7BYGt5x+V+59gW5HOQ3m5OaGKJ8wim3sGLPe9ZEJ49Fc3CU+0tOvqDcOCCLullcPZYJinAUVH18XZs/FM4XzpELwFfNcd15lDir1vOvIISqts5H6SZX4
TB1mx/9bcllgbWIpWcF9Q3EkmiIAwdV7TA2MHxuGe0JAXymBW4LRmyDFgYfRV20iYTOe2uWim+6bhkUAanrYlB15vmDvU3y8Vh7Q6EeDDfPcPS/JX289r0OJ0EkGYVhANZFq8Pj8mCd8J3BM09kaveAu//92Pl5A5tfAeoZ8mdgcr36TQSSl 7vFFSXjrMOpWm0flVRgadpeyFfSxotgh0Q0LNtoxDyyNg4jGbFE5xkPAFljk2BLe1uIWdDx1N7bPNg14XprYlB15vmDvU3y8Vh7Q6EeDDfPcPS/JX289r0OJ0CbvPaKhYaPThjaoSaq+Kq3bZlMN10T4qhF7SedhN/UgGZt1mPQz7Zd6p0r9
944B31yizpJQRnP1O6Pyatm6R4iwylTIZFCgy8zZ1PQej8cc1zYlDIa7xkRKtzPQA6uUwQf3qTgwEE/39tj/iUHqCgB5NJez2jGZ/Fe0BkAgm/iCJbXaEyg1IM7X+JPocZEykfgFGju4mzphybwNSUrkiPT/YZ8ltEg7WfrvEwwu4AJ0aq7R A3DtMkbCN0WaSUp4FT0H5zlXiD5vgrwwIB4d0PpgxR2lXVa61eoPoPqtQ2za2k3wVxoVSj1F9ymtsXzVfE5Amn8Cm+V+2F8g2XNoUMd5oiG/C6eVVWdPyG7JqU1jMe/kT0ZHUvJS/OpAGJeObXjSIlMf6Xv8arQdCtTeT/3ZFauzCl2Pw3RN
9XyoyAlvnWF/0hipiah8p2v43WCXTV8RM9+Ybn7kSW9dQ6m7gwOEmWVsRvx+t/ISTsFBSY6w6e+24k5JWEaj0owmqx43e4RA6oVq0XVi6Lkm7/Ndysyx24XP9BWhUrlGXuvnBuqM2OigezFDJusFtmsd77HKLJgthXDU/ti6oI5SHA/GM/LD Wqza7Mmh1JL9QlJZuBrRzo+F0SqWf5Q+I8F+C20jeCftHRl/CnBC31RwbMVMtw9VN1dIprN3NvUlKcCzHNwWx6k4Br9zecRD70pmG8UGHfSjsw4l2y3ouAJnvOawSMhhoo1qFLnOW+rO2aOk6MLLxWkllNhl5kv7YTwBUz2d+e+vMxavwK0h
E6gIydoiFXDE5pwgi6sNExyd+RpOm5bCJwJbRh7SsF9GFLBplNFa4sbV/7dEppYvg3o6+CNna2BnGOYMglTXAb8mJQCfPcHGxQNeEyyO2ftLO4afEIBZWul5rEMzbo1dyA6/0nGSZxk6QPE65gVCFLrfOsEcHAZukJ/FvOBcsGBY1K+AWrzb dGTu8QNnKX6IrapC1wnz6MrhdRwFn5qFzyAhTtSNLPryCrKEgm1vKwFJyYgBCP3/alKYhktqnC3KqP3j6Wq6anDduZUWOzABqOIybz5VkWWNMaSsMrk0NoUb5jkTt6CPdhymC5jFot+IgMGtGudfk71DpGbtHBUCFuUjeUxDxXvOLVH0OgXc
ooO6zdvAAqT6hwjx8Xp9T6LeCcBNzMMURyCMxwNQcGt7LKOdDZklgwxc6GM1gwAcbzH5FSPzxY2OWdu4KfSwtnYUOHfZy3P7WVI/8RrRt3nS0ZkZEXRQ/Bsy8j6HIeKxSLznhr4i5nMLoUUJMfZb3E3Di1gnxAMGr4Zop9Iy7FXiobjnfcGp uGKF4HkyrRB4VGqHfMEsl7mpDHu92nYZ+V/Rl3IYj9TdDQ8aVrm9mw2IIvIR3IOMSWjF1HSh45UOhVZ4OxX+84z07fd8PgBDMhuCkfVqvGTeyClomImwRDpqSHfif83sIeIAEPObsjfGKY4/kcATFmn/6eSAUzBHJXg0xjIh163paCzpzhoT
XgMnvIyIB6m357zczGrzBKjZVdU4azBhIUXddNq7hT5En8QPfoCJpMuPUBfr54Xjpy7H8eZ5cm+K5ixYpvdB7F64nVVJvRGM58pkHMm/Q4F/LWXvizUrxVJOxddJw6PBFFEvXbzPbg4gTRNc+hmQRnQ19iAq9tld01Ul1Ejdr+wUuinvFCdi KBzEqLUNaEAtYhnidp4Dr+4QwFiAOcELoFerHREZk+adPsLc2mzIphQGxFTL9PVsZr54/FO7+dlAOnxA2cT2RBgfYH8QPvCMin1wiox2FRmeyxtV+blxIofUxjTQGa7ir2NoMrVSaff2RAmoLB9ihidGpNQx5b8LfuIBSn0lkoyCO1ndJ4s8
kilzV9dF/Jja7zg3dy+1QKbM0Vn3tc4AowR07SnkXQXphFzT0wtXQief9dh+Klh/G8yIe6sPmWGbUOYcjflPHQvxk7HjRRZ+GDXSHKPTb2rj3NsDI8tZoTSN/GjfNVgilxQ/DjF918g981M1OV0vUJKVvZc+7J+HmmX/xDrfxmiWBgxGPkmd vMrVrZEbRuPmkJWga5G24OqcG/luylJWMXbIITVrafg3fz2SUu6hTnIGEGZQG9Gl4+HOvtpIkP/UkDPsdMX7Ovaxpe/3sVb5YdCwIcoOxXOvEMHjQAgEGzzoaeChaixjkuu7rgVstR3zr/fR+MAWM+UMVZk6takasRr/Ojl/EwJGXzuBTHjM
AYExV5pdy3f6/hQspd3f001rUITFWfgDa9Z//pfug2+PuaI2OlKOxIeKVpzqImXK40d/Jsq+sWoIZdiTkS7dQCqecj6FpbHAoHbR3ccRCL212tI+fO+rq6zHPnh/ycGcwnGfKJsyXBwcLauLgGs0oOMz+mtbTqE5xWsAruizASVHvn4U4uy6 QtWINVHQEloq///8S56KqZv4Rmmms/qwd72RaQW9VjP5BE/vaxYQAC7xRJftg2jd4a9EMu4MkDcAy2ODAcr5Jt7jU1yJagi6ZDEglcxVaSCMVp4jv3ecaSnG8U4j0XldMpNxLzIAWBIHC836ugaJwPJnrHI9W32lep3mNsTvfOzUtMeLZdvq
CZREMx1xCjls0lf57H8e0vK7G5JRMpYFnjxbsF8TIOgUqw6v0QbW+htemsrgDGdltgT8tvf7VvXETlBF/slOkGrMz0oa2y29GvSCC2N3tTvjhHnRRRoqidy0Pv5s+2iJY68HVpwaqgylAra40rAsjlCEtRt+pDejOJbNXtCWI4fU3K3KCIqW T+y5/l3RA9MNyccrqhwW+PtwKvm0HYfnddvflmBivAPRkL80UR1mZeet453/DxX0FwkaVtwWxfCHKIucPsMTbmmtkfnPtWel6DeNY9PWCSYxyasi+Q3wXbr0WCuIAgvfukNswmpYRgN/qCAdhe+UPaWmn411bhy+gOrbCeXHhsgaDsdpMrS9
wc+jN2vOjUB2oO8uu4MlO7CZxcMqiYq8bYoJxYnADeeAm9g9a/IWyHvlTpqGfZD3FEV9djnv7VoW3+NrrI2/GqKpvumB2TwxN3Jm+zlKx+uihgZtJ4bjfUw0LPEKyds5IKME2UAsVHWmXHyr7uMISJ/vsy3TbC1wtprc6cX5GfOHU/6bqEjR ChBH+DQshqPWTBCYcY3mToFziRMkhiC5NvFBHKGfE8vp9qzRgLwXDrwh2iwjGhqE5Ruc1VHEUN5VfojLM/nLjPlxyTm58e4ACG8NK4ATOzvT+9zRcfTCb7S++ie5ei1FmyX+VKJ6AbqFubLGICdYsZqJ3gvjqX+ZeXJ6lsZXOVy+C3fs0miD
Z/NJhcnlrMaCTg9hH95tQP0TashEoiyoZIkjUUKYna4Ov9roXj3NfDqXZDmUmGWFaUFkQY1/jKH7m4vNLPpS4i9fDr2VpV7gIOn4HNg6M23PXcVuqfqn0eo08G39C8B4f+yeSR3u2hZvtbPadeqzLP/6+UA3DrgJzXaXlWZUQupwtakPsTcU x9MSgwRtmF0jv2IlR7375iqMxeGc9phWsfifxYek/PndIWv+xRI5FFVyAkG2roSWmcla97ls0UEKm/aF1Z3aDS7W+D6EHoEyL8L6c0OJbox+9AtS/MO85KMUxl8eoLa6X+4kMTT0HNrHj6rregTf3kDHC9cD6a4RlTyEs4xdCKfVMWRmnki8
CCPshBsM1g/RsIJeNMvDN7lq6GtUEM3w2y4qDSPrw+Qesdvv97Fzr/yF8eYQCGn1cD02/RisSnXWGkQ1POYmYksEGJmyiojky3Ta1eBBDBbU0uOAykWh6Sb62prmYzfsyeDTTqXqOye07eJRHSiYKJU2DkGHO0drMQPqJP98jyGUzu+OsV5s HSbSWHol9SZhHtxD+sWa8qIAhUKWfiOuFmpzEJlL8XEgGLRTlqbAGBfybnK2Ep0I5wJOrzHyK6Ime8g1opWmSY7r3rnU0yOQcr2kIoGhzBSFc+Wcgj501wyyOQ6/KfDoK9Zc2rABAyXjWSjr7q5csPNH9Sexsa2e4gdsEg5IYG/ZpAkSAXZt
qD5A16HzwCOM7nlXm0nNo/d+bF2NCEPKPzTnzJh9FFRNw81+7hURVUIvjG2Fwcm1fMuFZS3t8j2R0wBxGoGmQD4RO8QnWCfQ5hDYObxjvszHL+AWiR8mChXGVNEAfObyp7r64VbIfSCLGAXiu7WvSv1r52ADbd5s3Ec3KWxbGJ345+zGXFcw qhTKIJxz6UtUAUfQiBd+fgwgBo8Ie9Ux4r75CFDncmsfgD9HAtnr08WCZMoWtAjsXHL/E6ttiA/FuJCXA2BeLMGfgcxgG6jxu38e3V+gFTkMLSWU+870cXrX883p3ufk1nQbbOnAddodirssgQo+VSBWEKIjtkE5GS2zPda2qZt+7lSRPc69
VLQKA//rehmh11xbK4VMXmOqUM132RRK+/vGveLG49yO5pLQVshW/OJygis31HT5GaDeUmkdjyfb0F7K/c0CtwyXPkrap6JpofkNJ6gZsZzFl0SFxZ3GEMXA0yo8YZOZkZ6IKX0pP3TY9ir+GHjS9ijprNeU4sY0e9C121spvrSY175dyYEV IzzcfcERUcs6fxtT+3OFqrz+iNEjS42qbaFB5dQEiFgrYvSDaqw2VItaHl1TqUgMrFuLFFdYMG1zda8oYeAO+w2+hmYLbskk7+oyXSNaY4Y57sshkQgRU0yWH0bVpe42GpdLvtYSEFWzmeZV+fgrzF2csGt5dqrNrat2mXTs1Q9kYyKpJL4F
DFsCHe9PIJGtFrsU+vCj0/H1uKD+lapUxSnWnEAVo0wMMEsOnIStVGLzFzR6dgckU/oFVnccje4oJxKpLBhiWKCvZnmcHYG/cpbzYfXV+GTPEBD5T0yXF62YxTi0Wa9ygySk0y/5w1Q4ShnIDCuGyFuD23qpPBCvcStlcQ9rYbsu6hBH8tCt VA0fAaY0F6ITD+HnSGVzQVH6daLy8lw3h4I2rs7p82m7NfLJySddkYSt6bwL1RsCWbi2XkvVHIxLChTePHLrfs3QmagZ7FQLQk37vJaU5BhEhpD/OeU5+wKbV3l8iJPegikVZqHGU6sK+KKi54kS6B7InnwoVyoxfA/CbSJm+DYuSHj63gqr
stoh7NYQu1V9zSBha8y7BZZNOoX3PnLmLxhgZ2/8QdJm9bYalMg5XwZg3HcpqARAHaMhVO3PYxDs0arH4r5HUPYRa4ngRgpURIKivdkQD3nH258jWSaBQUMnC4yzqgJqVR3rpv6ITzP1BwKBpkA4oz9pP8OHFKBqSqc7aHfrlviyTGyutY9n AOMupTUlYV3885DXIpbZp+iCldwQhUJqsNoDszITOSsCpBmHFgexvHTmGaXk0lrzGVDdgNYjXyiLK79Wu96Xro16wFYvQlanRP/8Vqs/9KNn5gMKOCBq2qbIm1+9V+mg5NHxNxjLqCDxvfhlSY4a7VCp5gHv4k0O1PyXGbtOR8gQPm8NRTbT
hrW7xAwzFxWpcp7+tMIcBCAwXA+bIG4K8RDyOSjDL7bsfauIpXss5hRUM3KmIqx+zZW5+hQbyc0YQmrvyOpZpN9cecPQEarRBG3qt3vRW3YEuXS5TovR6A3nXpeO6XUCJYl3FVzy0b7eXzFaaHOHQeR3msIw6E1DqToQkYYPqvDo82/gkifq M7Ka1a06FsXZ5b6WfJCMmh6/cBSlHmBmV/DChhpqeVkKOwJa5L/dKuosDkCsDVAkjeG1tmoAzPpsKEBmiMlBFp95QmiUaB0M4FQAruz589t2I44MjigtZ2rIVFJc8qcW/+D4diCMDr0H7PiJAtGtj4mILcLk1tg86Bg5V6OoRVB5DqzZpIlN
9gBpZaXzYDc+IW2ysz0nwKtRpsYiKRlzCav+h16sW+ZI/lMlH0DJ0tJeI9ujTOFmdDRNLm9HQ/HSdvnRWmGoMfWArtbAcbMmSFOPc2NiA1UI+KDk+/DsWG8Qg9cDaD1OYKNT2qxX2bDpCcOSbNuDlV1vqAZjIBj5+6FyX9YQccnCCOsc1+IQ b773lNTGYjfrhqsU9QXENuP2I0x6y9zuj0ltfF8lDWg6MqeW22q+W7lMgdyCD3m4V67L5PXSATPoVt0g0Cb3OrxfOFjK32fbye+0Uo56Tu9kkonhyu9AAbXlTp/BnaBJEa7D2rl2OomC+NtEM31kVhMg+HEOOTOtrSjnsv5VBHTUpcmnGmi8
dXh00HPd3y7BgBWJrlFgcoiFw3j2OX6cnkaTCK2JUG5DFMxhHHlIf/wgjdSBI1juNbWeCqGcYSiDRqlGI7vl/yudas2B12hf+lfCakz3SuN7WQv+B5JSifinmuuW6RcipJJqpQb8zGNb9F0j+Op+HNT9/OR4oYn3Vc4gvotMkoKFAkI+pT3B wNA99wh3BeABkpoysycf28rYqJ4t/wFnb/5NBsjDa8TQ1JPU3DW3U20KO+Zen0+wA37G8KkERuuEQePiBl52ptW7VEW+h0H3m35TMNinpZpe6vMKz8UUQEK3gJAhjPZmRIXQgSWOLRpQWO7ggPscH6LmO30SQj6cJ1E6iLdC2n4AjGzm1nuV
/tppacS+pwLZHY8RY8eJykvKl9O+UXt+wJVW8nlFwlmH7dmV4G/4gQRWtMo0hZDvZ5ojRoCW18QPw44nyQek/k/8pCS0Sl5IcyKEvYLjpxYkW9THE+wC2sJNU1Z6l/kdI0fl1ueM8V8O7ur0BiG9bl331VV2JzyUYHo8C6BFLElTOqBH4nA9 yVXjO51zqfCupC5bFTMg5rm+cw0WUrkfW/0gunwg6Xzv1zFzl4geAwMdBZtqXuxwz10sxXiPNvgnkAzam/vUmvh09Qzs5m9Wp5tnpb0jHJHxy5jiOZxS+lVKCGrsTSiG5YoimoIBzzCTYVHEZNQBLUTR1hUB9EsWIOzIvyqj9uPkaxGNGTkM
c79M04ZTcoQ81yEoX/VRyMdsmC02RxChZz8Ui2TYp6aiFRPjusCxoAlZNUincigorv6UP0qiki03uZmD0CghR45Cqbmots2s7BdaKF0YjSC0RifawMowEoC2TgLjnUDEsNPuP7uG+G5pIbqO9e1S4IwzI07OvBm2nP/EsFNMhqu799LY3eHn DVYe+yUYZ6w2kMV1gGbqBsaN/dI4IaZppVt/weQ6jl0qUVV5MedbD3L8YspDZ/ujbHHNVmIFlHq0Q7R8DQNGhvOgBD6HWPYFh7QM1v7Jln62aLr/uqULyAn1FT6tDWVaAqEYZg/w9QWyKvUV+WfXQJ4lKa3pJemPocAxZ2XcMpjuCvJduHA5
IZAAWPaydYqayHyJsIdFXXsXpQkMVTuCdl/1UXwGFRpT1VYh2Jv/FGUvVToYJlkNrg1iERAWuYoNOrmT9J+V0qdvxg4Z4oON88qDLRTg0sIustiv8LELVE269r7rTPVxKuFZZsMe8DK909EzzGh4WGorgOR5w8qIzzdF317zb7F1iHcd2w/F P1BtnVV+3zldT+UTaJ9sXt6RgMHCtI4DiGzbiK/pPiic43lhF8PDeCdZ+OpMKP74mHqQub0U9nloFy2T9pL4saUhGLF7PmwhN09jKQG5vIEU/bQLnZiaM/0mxnSJnhzr8Y3wsHjS2x5V626BLrt1+CVevUusrpA8vlIzHXoHqJZ357eHLMfI
9LUK26MfqA23B5Ka1iacE0P5OtA6P6dfNHq45lrltE6SI0/g12H4TNeGHHu151QSdb5zL41BJRSUsF3oE4cw1LbXkKJuuPOKVgVRj/NDkIMsoKDzFgdptTYRiibYKfmvBeGPasxlJ9mD/PwWmamo9P6Te/k/u8kGS32oQDZkuq0GwSl8ZnRB BorMkyWx1Gqb2QQdn5UlSS2pTy3c1veGXU/DyEJfyikEDj4wboGe2jzUZjsKMupA0TNFXa816Isqn20FlC5Nw7fBIqfCO94vD1OTMUhkIrqqdbCD+78uej7uPRLvcxGc7AUP5/BJaPYhw0N68tvweCsDpW7DPeKn8JiRUiDIFRWuv5pEelSR
NTOhQ7erF+7uV5SrAs8YTdpkRBX07XA+d95nm7gdz3IhlGIjK6IQ8SriP+fruQK5g5xjXLDN+9g3cTAMhhRjj+eXIi+zPOv5N9XfoODgAwztJv0eFJ9MR3l0ETp8Bgav3s1X3E3R30nlz9bnBYkIu+NKDkOBwwkvXDGhmTZBWS3h/T3nX0o4 wkPUaxl4gSb+7bn58tG0GFpCqntxSobYax62YRAn6MmoCDunE764GBOguSrRtRXhed0ZX2tqddPYx4ZfkaDt+EfhZgYZtf3MuEJaMRlvimUsTAnWibN/6ihWgZXzM/uExwZKhXwtKYyWNakHwg/3tcsjc04GHwvaJs+CiARiqnyKzrRT8wuV
+xMbOg5Ihyywykix9795cGKJhtU+sbvEMfU/sL8sEa/PV2HgFX51nywJNjAoZSc7Gti1LXfTilRo8nac07sdOd/GMw0w8E46CLfP2+N1ZXj3Iuxr0AKNVfkvIEQQgMsDJC53l5MJFSUREmh0uc1q4IRwAVKDAqIhE1DKYEso/csZH/Man50C wF1CqrUX/mMcCXmuMkZHhbUD6tQpe4kHHr9dgEREg09ff/hY9fYEBCl6XqoihryBDz/+5TXsC056eFLiaIJs46Q8J5cWEdvBG5J+njC2ns94USTlfXQqKbZAQ9kYqf2U9jiD/l70D/KK7sVHLMDG+M69abm+Su4vF9hnGsLj9WFGq5Vr3bo1
RSHAcsKwvwo83BASLRRsKb19hyWdTP6JN0MQotD0zcj1R/BddpSk4ZvMJubvDsClnaba8+1a2uhGFatG8zH68Z/f1UkCRNehzCh+lGPB8QIWhWv6AGYyB/0+6zfQ/sUCu6s4611gtnqe02L/GZ95WoyxoZG3TGuk5OrXUSKiKRdXrBBDgaxq J4CTqpmsq/Kzmr0aSX9tGjAA8P7atzDaqXPmO06kGsOupk33tCfX+ZV04TUogykuGdx5N82X8QLtrVWemQPeAQDLKzy+AKJjf2UOQIHX7nX5OXt00ZJsDZhoq1iv7xE5ZfBJKycwA4R8Nwtcom7iC2MR7DHuvqZ6UOCJvKzazRCjrweNOhoe
vAvHDBhosjx8QEFyOpsruaX0WMdr2k8NQArd8yzaETUYAf/cfh2AzA47e0SP70Y8VjRcwznzqPMHyAPmLFXJp2lgB7mU5CY4s3BBhyQ6vNaGCBSmi2/lN1Ev1JYUyZj9hC+iPMnQ9oShUwUN+2S3Led1X7zGvdJbCWFXDrTUIDqgLlsngLl/ lYVpc9MuR2blkCv6lmRUSf9J3535+BPjPEl9vCPCoo/eaT1LrGKtpDMUen3wRqot1TLda0PqmbDMZrTgDf62AmiAE8ZiwSuJ4ol0SK5olVRd+aPiZSSeXOPxWba+89TDlDO16vvv6jJRKH9ymwswMFxH9W2OX+rN+FOFJQnaNeeOfRNZmSPQ
KVEvfkObnfmiqMY9DuDYvqpk6Q59hQF/Ct86IG2BdiOzUMAl6yqfuTP2OXKtOMK321q5bF3DPWFd0lcJGxsWjm32t+zj2lfAvbpL0agRWBHmvfpfsNySBBoAGkboJQCfHSuftT14pOjMQrFFy9aGxvrNTmO1PJ/Uk5f1PsgeB6WzpJ8DxjEw 4Lu9y1wULbF988vY25NS5VC/5mihgVeakXHHw+pq8SvOrRE8ts3A6BJxB/gM8IqJNTzmI7V6WTrKNk9mncVN+f1b75fz0fjK85VUQVIV/Hr+sK8izFPCgqTnQdbsq9HEj0NQ/nnB8Gw8VZrTFDhOu6BTOHvhn3qMqCXUFiYT2yTMOUOA7z7f
h7Qp20l6SIEYzpTeX5SyZwLI5/Rgtn6h8OICKUgPe+kB8Yzpn1+RmK0crQCwQGnGIJItxShYNpeDNa7pZpHde84lrjkeEljcK8kywp+hNI6D9IxW9bFyKEIJ2H9/6o4UY0VevVXBm9pIoz2B4V4Z4qaPKSXyv5b2T//YjupD76x98CBIGxSV F1F3Cg3iCtJG6wr25DplrcAHh7mAEgph8hZ7KMnWotZMHC5h4unab/e7+nW6sl0BONwQOWRYbT5mGV+Mg0Pv7PgrRgWdo52PYS7P4SzMklrCOyq65jFQqKwSIhPxTaR7jPhmWIPY0BJGQ8V3UdVE/Vx285UCOpOye5Ct7lgsKDACIkpFY2pg
rrzVo1y3hJPlIKvV/LnrM8pjeGJkxWAemdlz5OZjkntf1rfw1Oeclg3H1LhptzCnUvUCE0lcDPWFtYxc6tVZomK4gnI5u8BBFuXeIhmYqm+8Yqct4VooShcyX3oqY7pug4/X2odv0WAE+wp699AV4ssFGsreSRilT5Qm9H4pY2I+1RpdmcPn AcvSp0Z0/5/DSKd5Vgfe0OzCv280Hc1Wk8BT9ppKgtImliR4Ih6C7CBY2Pc1vhaykEwAMl2y9v062qctJWwHDN93/M9a1hOVSfR4uMczGEYqoud2b1CnJsF4UaylZMq2X4JtViR+9oj0ihrzgD9YaflG9qs47wWmWHgt2zEURauaE1Giujl+
zASu/yxZQjJANmsyXFQPKDJVRUgOjfr3rThV6lzR+x4YpbMbQGjWwNT1kkQ+Unt5tj0rcJ+SEkFdEuOH6+6SUlqoXBht1L0qoD++40ZTAfT+LcbEi5KDdhW0DuGC16N3X83CSQ9/fBUopMjKIQEa9ClWujFU/lqyPBJ1fBmHbUk0FcaTInQC 31IEQgySMmtegsb9MmqzfT97aDg6qQynvpwHnXxOiG+8/Xh6r6/+xF54sR96jENe3MJ00XIo2hnDWtclGLcwaQCQRHSQuCqNeZS1VIn93lzw70zKpvrXDP3bBetEBMUKsMDTHP8mv0JriGLZhU1QG6i5AIBKxMzrb+/FahCYejP9kWQd1/RH
oXIKIOXSronW04zrd5d+Tgn3lISJ0QYOoQ8hcv3GWC2m+S+KBujHX//3Pdw0C9HPtRStmNFWwO7JFBw7R8fukB9wEtviCtSiPRiGi8DcSB5tnmt+H8/aMRyep4G0vM1E2KTYEBGdb+sEX4HKeHWPc4Uwpl1kyPwGL6W7yh7ka5hsOgxU4ATp 8zqe33k4R5B1PcSDkSzxb60ueF0RAxxJyl7KVRVSG/9rE6tl0H9Orn2mLp46WXUXno54KvrpGXAzRkhrlGkcdPeXCT8RjjLhp65BBSKhUJeu7n/33vvl9uMlM0HdNZ2RSx2TY1TobzTl51bOvbQuBEzs5EQcsi2ZJWYMf2GnNCUkEVGlELqJ
CXP7OHU8dsome+hym5LcLhxVFXm0qMuU4rfXCumHLaVnK2lQ43SGW2jgvVUDKRzGLL7zD25IL6T7mIJcUSW6B6WamJlxgeAJapxr/gnnSJXVmzI3JHhuUheosD6wJNMuOowUhWBayC6FNcQ8n6fUe5CP9vvtpkZ5zo6fqtreLfZBRnyDwT30 S+BFZAXLQ6+LSnUYQt2Cj2VotFUcCWnyHPBasijbux/BAsB0w9I4rhWIylC6r5ObikTiWcZZx5yEcHsqiXxJi2cj4sZ/wV4xr/EbpCOGe7BvKc5tiwprNTNJT07dwoCiaVSc002Dfhaz74sUy1bxEXo+CvZAZc9hZ/xmrae7hODG9YMFKVhr
H3DbUFyog1KdkDMwzk7eX4857wmAfUI9LkURdgzWL9DJkRHcNZz2YmrPiSfIA2yYvMVwrB2wEUldm1OsAECerb2ZnAjgwK5Dq/4uJQ8U1cW26gF5opTFyFLd50NnPAbO/kLFBVopipdaIPGGXcmER42+EXZH6B42jWgyerFwvlundHynZU8R k52xjCAFdvnaakGS4I+R9AiOjlA9hlUI5Obc6yp0haF7BcPtmcMMUAp4TkdFlie+kUdRkcbrabO8EILOey9sCjFlyJjzl67NzRN42fhXpm4y+UotlHCmcBlNTrt0Xe9mEc728xXhA1b8dzGcgOIpH1UBhaqgcaC42a+jD0Fxvfob084/81iX
gRcpa3xhBBd3p8WruQG+U6+wyY+OuPQwL8bOGltAdmXUo/vlguoG9LzKHLX8LxJmDnGjA8T7VyeSmvzPoP2td1apWHL27ol+EtIBoCE1J1+96BRRk26irysEHYoUvipL1XkYwdP2LOb+nvBz/GMPR1kqpjXIWQH5Jyq/DfJVmxNFAzhoV0Eg 9KNKCYiJUPvzCbvz2EUF0ev0fyAf4/v8GW/EOQJd5LgS4SE4dx2icaJX6/cKbSUJ+1EJYERVbKoBLXQR/pokHfLYmXFPq4oWc4xHmRL+U0+aPcTQMtinaib+j1nRB2InVlt1Oz4JJLlue3yZevxw0TwSj6xaWi7lsFzJYTX5t74Pe5jGnYU9
IQjikqUQL0Z4nDPibd1cemhI6nL/RJPYGF2o9t0/cjWjfuXrfTMGClTFY+Bdh9forJInMvYUpoch88p+a/JvvNHct9VsWkp6ke32BGrcgAnre4MCxgzs5+/LVjIG5ZRIi76HK+APISGsF1CUT1ZbeG9FeNmMlT19JfYscyrgLtA/oeLnz+tc zhs5BrSgoSCzVo+XbT2dI94kEr4mqeRkYZ9Gkr1DpeqwZEEOV+gWBo2FoAP8QzN9uMdkg9sN1fiPli11ghaBqT4uuQHox4Rp2uFIwXHPlVUygA5H+1msT7EhpnOpZGIoC04JfuUGGl06iephTPO4nT8Xc0nrJA5pWuQpYXIS47TnGxqutyHy
sZK1j0VdZ7yoRaBIQe3Hllad7NSMM+eZauaMCUfiQHlYhIRFPltTgiWKoZGmNzw8wOVWIGOK2hjOVi9QumTjHEb2KeRAjhb0MxWsM26gDOl3hSuIRvyxRVPzEgqMaLlie7GLLBRllXufQ9UM7AXXPrjYJjG600U7owOWv44/Jr1Lz4FvsoJ5 YTxqqDhwnCXpG5pY/CF5qtsTj9OvX0p9KoI/2vCLLac7IZT2PP4brR7uK3VlYPblooHCvc0FtEujFQbX6sm7pl3LBeQDSPv1s9kOMr7bx6xrAA3VN3WQMARfGpCM1kEzNOYWK3VhFf4qB7PUS9wmvoiZpz0QEmGvKsPpALNGrCDcilyDc0vg
QKy8cZ1heHCd43xuiq3OXwdYTVBABw4SaOSCpp5cxpPMX5iv8Q4oG7sjaHWJM096DbfnsQAa6d3/s5qI1qE2+oB12JEp3Q2pY8c5I7nGBKxUTmaDt3AlV/ZuVnXxyMV8e+qFYTq5SLdrMa2RQ7sPuHe6bX6lBmZK7vwVijaFnxe5xDmlMRtJ 15/mAa1hscHTpRDyGeK8cBdrQVUWkYa38NiFPV9QDsd9IpRSqJI18nA9rf917qZC+tV+FHtymLdshz99b/AJG1CNsv2Gkn0luunSj2QvcF1mQaBh1YcWKklU8IN4DBkU5BjRfUy0oSVQQMpabFR62slQHknkRfgzowNSQ4V1pFCybodrrjS7
fGxmYi0UaSab84TgSD6WThP24povcGnOHHuURUmK8khHmpOp24AlDhSukJOkc8Sf57pSeporKCdEZD4ECzLU9Gqk0ojJhV0ETsAUWp3lKQk4qN9tMnJHpVSu9Epz4/muLOzn8A4TYHbkKO7q/jyRr+tOeejJvEnhc7ORH6PIH8GukANko4cZ W64jToT6Uow3Tq9Mjc/bmSN++Mo0MGGdr2enSSYaY6cQtUgLTLSIQRODxEEM19P5Oq5qWCa9NBkVXcJiZLYauqpj7NnknlJio7TxwlZfxijwo/zGWyj4p+gViX8c5m30eCSlRCXbfmsI+6XcZzqx9DG3VexWwNKsobLWmR0cnn18jD1CjDgW
7oe9apEtv/tnt4+mRh2FVCVctFMd5egqTz/bmvxq3AdML5/JiYiTQGINP8vOlfwvPQK7vOpfzyT0Lkhr7VzggGGXg2LjsBOKBE8Xa0qeA/HBQIggvYG33GeqI6FNG0h3Cg6oi2U58ugcKmpxum/rE9Hf+fYFjZnSD/S+ABg/XJmNAMRMGwq0 WnTkvqlckV0m1F6QuS1C86JSCmeaWzYS/JB7+aNc7AkwZd87XdGsMF08HcwXXfT2K4AUIv/X2+Wqt6503ipGlRA31F97CPVcwBEjX5YvLJIoWK1Dwdbmr4JpUYNLQGDhZ+QdUs2LQrnRcZjMQU6AD/OuV2l4g2mU17Wq+9pQFlQzfYevZv0X
HQx0vlyjGl77010Eyhy81qmTjcTjXcXKSm01YRM2lhU4IRWYi7k4fqqK39BD4ihGyXfO4AJDwY9dTCkq6QZgVOoBrb/QVE3Sc24i9sOS3zFw4hqfsvE/TNRutRt71+PuvN+Eq8wX90fY+/pE6q31LIquMOYkw+QhnjCDKiDLsDSoACXuavWp dbyHGKDNnFUhlaCDZLfM5Ur7yhamr0a89DENRR5LwFNLWk63N6nwBUPlk7G43XFSWfZnvllZg7dWBPo5Ck9BRqZdva7xILkvzs/QwB2BkasfFnLIbSfstNvKgGQSUUQwPexHbEoqnKbz5bYwtXFAq65yYA6J2LIHvg2DYjea7LCHMfGGxJ3Y
lDpPiAH1Svnvnz1q1QsqOVZbTEwYrRdnpsqjTEOLiojLL3E5F5I5hdF3l0npE+MdrYCwymap5vG3nA3eDFBSrxss04q+GszdYneFx7X3CEahPIKQdJ6wclt5VXPi6I+t2rjRct5ptXo+CNnY8FPaaUi+gdgHmt8a3qnt+qzvkVmq2nMfEEy9 UYubc3LqYAcw3Dr69JBa1INJROOwRdaY7dVU69sk5OrunDAN0v95wiDVz+cgZOSAM1Q7Bvz/Zj9bPUG8LVU0IDLgAV8ICEnSXCtgVQPKCVZnMnZ/VqfugnPybMct1nPgExXn+DUX9iO6Sxu/BXAW1npRCr1gx1fiNxEFUgcV/VGfkuE0oi4P
7DdoGpwS8ZO8jIV3egzdFZEiNCa32DOnJQ83BqOAJ0DMRodnZq+ylsDalW4rQNOA6XfRzFV22NHGhr5CcSGDmkkvxs8jDWM/jv8LJl6rpWHoTRDg/enhCunT7IQLhHt3cg2gxVHAUJ40RvKzhl0D+CZSysUzed3APjuvL4Q9bMMnuV1CEQLd wMENSqLW6uyHmecsJVZj7pxGtVwHbHPjOkX99NXY/NSK8To3hxOe9/0rFo+Q9lnK7NqjcQRurv3QBUCv9M09dA8D9G2Mqo33dyHaIvi9Q2aBmwy/itXXlFo1J5AlxqrzWPSAfQCJwdzi4SkOtjvTBHfkusa4ukDWAuUD96aoa73+s3FDxws1
uKxvAdvwPNWK+bc7ctjMPlKeh4Qm2lHrql8Cu8qzMQrW9/ZedGshEnjd4MwmCqrEs6T+LmQ6N9O/srjGdYlmNTTSjMEoYAkmEfr7yPy5eIfzQLSs3zQhXv/GHNxEBU1bLRzkG6mBu38ZMRx0J/FAtlEYlL0DngZPL2jo3t6C8QCbtDHNCTmW iKyImel4rungNvx4fEPHeEv7PPKZdqca3LedkaGErZPlvg0mP33Zu2E7lD/Q5wbdX+ReFiGi7Uwk+/K3KGl9uwTZm8JLV2TIccqltot5eyv/bnb3GMRHmgNj/dcjSR5yZ9dj9U/Svw1m++5uxJsQQx2FyIQgDAtGbkrD0bV3YuQANvTxr212
ZI8wwO17B4svvZma2sSoUARxvAFXo6gFb8a88cEQuJYlGSLvNN06wHH6io/NeUiURckZ97jgeQkSmVzmxqUfW+c+DmU23GxRPwLgZP9/4RSkbm/ZXHXtcF14ttGc5GmyciUoz+GFwiK4YV+OAKMqXBG4lA5Cu4FLgCRFj9b6/dMdnFK+F0KV 8oCXDeVkbdSQA9B5QsDibMah/bDaOcltuHtuagnt5VeWv2d/GQJZkargKDh/o/PaqR5ZBxNxo3v1se/mvUYiNVcSX87sL0ef6M+ZXepLSX7gxOwiS0c0tS6BEhIpBYjJTsCgLs4dc3tJJZ1hbXC9zYM6OYMcQ4tqCqtUVaw1dzX8VqhMeIf+
q1hGuhGMjGl8ZoGxiGonLKKft01ZaNSaofWYwVRoEWxuaG/CYvoyvHyYVs8uNuRzC958fxDMhbqTotngcrBeQNla2FrW8sSqOEX22qZ9/Vl28gMINJ+raGyk5R9hSynyPkS0SNdnIcarwKe/gLbdlmnSm4vjm9WnIyfPorW09rfzUJ+RG/E6 lu6KUcn4hR8MBlE7CJjLbrhD+H72LjJYiF68BhsOS1X7HEqq5oSMUocDYWy/368Wf1sKUetggmFoj3wp4EL0qYOUpHMBAMwosW5nJALkDhfXrgFHmOQ8mLeHG7c3WZOxI+cSU2POpRofyWU9NoExE1JL01cLQUTfAbUEz4pfGWqtU9jKgpWn
XwiQ5RowbyeMBp8e4s35yhRt8K1Ay5BJUU8Zuk1qtjGsFSO0SjG4ujkPSumucbbbIIsjhyJNDorR7a0dQbjr69apmaYjldlZqv6EuAPlcgld8/s6cH4NYPevlE/CXmDbzBeYVhj4tpAmuH3igY9oi8Katzr1fHOQAzY3ClK9zmX3KhivukEd boUp2b7hy1pn/kE3L6DnmfktneM0rxev1Q3uKqgT3ycXfcMzaCrnLoZnjx0KK4lhGbYVkowK/ic4NFoHbnkH1fFtUFt4DCqE2fgmEDo8ZnRUJP1AFlootys6A0XExaCw3I4hlY7OgWO4wBUBlWyvVLxlKyU34sl0HtyRQGjM9pUQLpa3R6CR
pg4CJef2Pmi1MFS4EvN8maT4XuI54UcpMmaF2l4G8WY25FytW7FTSGSj94iy2TntSZQDwFCUfAhjqXpdDaVb4rCdBmkUtc+9HJOLKqRQWKM4zN8kldVOGolNkhPsq8lfwF+kUTCufFjX5hjKXVMx5zxM2o7oF4Opa6/jgJ9T9stPGPtiF6Si fwB4CJwKxacqMKWJ9Q7CbNiKLzY7kTC5qmZlVFS6DdJ1pJgH/4N5Dl+lt3BhLJxwrcblpSo1LX16ofgffOpLq2m81k5FWm5uL07khdcKr1B+LeCRF9YersQAHcGsgsMVuWZxJvDIvm232VBg1BVJGjfKBLzOiXLYPgsIx88EkRvbDaIh6fx+
KrkQ9fuRtioMDmlsacbW3coFjuUdftWEorXlp5bqYrKk0KlB2lMQZ2kQSPRKPcAKI2RD117x/+rAXBlXqUp/47y1soMx9/92PfDxVoWSkJfWfwTg46Fj/iDvnHfmewX9FW64WSGIqUo+LnqccqxUmYesAkkykMYC/YqVrgnOu6hvATdjJ8lh PksPu/16WAY2re+cYyXiHZEvp1Sy8F5sICVspikd10SRElHp1njFmo+SAjRVdCGqYkD8Jepp2q/uTkYxzzGc2bps/3Cf85ZpyBw824HchFa3c5vMord6BuRgpd9LiAgN45rgRFGng9sV71zQzg4DBqWyN5edtzbwxJOp8topIRwYa3vvWZC/
5GRvTu53RQD+CmGSnrlUGsCZsHIZczp5NIUGet+r5vO6FsuIgmNypYaO6Mo+VIZpNdXDRp8bM1CMxlPBl4zu+LdN2sxk6HzxZDfJnoguNvhaLRZbOSjVqj1N9fB7j4lQZb3C8gXSmerrjMDABD6VI26WDrIkc7PuzxbsXIFoLNftDUjEiC53 L56vNMv/+cD8Y3WyYKkzLNWt1L4E+T0jQ7sAY39WeZ+bMsjLvIXrfpw72Motr4zxRRX5uHTDl/L79aMPbBmJrDuJoBpORHVQig4ovYw0CKOR00gInSaDjA20Rq8XkDmywkKSm/EGwfjd9VmmC1EvbVlme7eGLrkyBSvx5UKZ6zsoCnqCAg1J
DOZ57DYXnAAhuG0o5pX9woaT8p+1Fannh8gGvQvPjJ7KcA5WR3OJiES+cLRlfUAA16C94wXZcuVusti59UK86KZFyD8Q8jBoRD1/q9+lTqOSELoABs85JefOhWkBq9iK69onHOIWlAP3aMJF2WvumUSXynnpOHXJQq0CnREeaykynW7mUZDf Q+k/Xt606W83BY0A/vqypKWcf0pMjr8yRubC3CzEck6KLEXAl8B3CfbA5aHdfkMN3snqiupxK9c1WGGP8Jpqry5om/Sd92jQ1WGNsl9SFXsDHZHjiaIzqPLktpabN2rDJdxmp83Gi6TJI7eu6p4BXmyH/O7IMSsPSMcWBir1j+4oA5fYEZQg
zWuLXlAja7Djmd75um+F9QCf0AYAuA1TtPzKTvW2cNw30uXwQjKimEGUD6s/y6oHhrpXdQGR0W6VDmNevQpDh2Knn1BghbS9nWmbKgJyvL8jqjfULXuRIJdkIZbOfpcB4kHlaQEPXTrjjND+eiPNKsF6SkGMZfiTThO4oPLvMEsgEnjW+xl+ lV9FawPMx2FalSKF1v/JzgsXzAJnZ62JWAO7Z0Cf/VFkq/HnYJQoWgsG1S7E/m//j0sOS/4K9WyPS4Ext5tVbTWZVXwdpSLElgAWUTcXLgE/YQHeWnZ5a5SpcMmjrdkwT51Kg9S2Cp6PGgyCxpQx1l83SWqrGoar55x9TFL5ewGLHzch7jei
0QvqI4lg3p9rOQ5RhiYeU0fNM5vnGI8tudC7GtozVfV0m97cuvCY4CvXas1y/KxCiyZ5uc4jExLMh7tSQWZjEEWb+7WUzCngTlaXbhKeoNAC/fbe1r2P9jP/cVbDUpVexZE5JpLULlW16UMbtWYOwmKUIIrQ50gOEqUDDd6Q/I6+8fhC2wic FgZ9k8r+cJlVedajCZT/Ln/wL48Lhi+T1z+VrW/Y5IbYOxnBce1fzwL8Mhi/ZVytHHsX5DKIM0T6on4Y2c0t/SwtfvBh1txGeQQR98kl00j1oJKkzMYxtnzUWKgonxvtxljORHILESoIzFgrA6kswMV1MWtS9Jc1C3lFPDbqRowZZiBkrc6h
djtRplQV2ce1DGU6qRkxdSjT7WNK0zoHJwvp8Zl4xA0pek3X7bguxUGkFCYboX7h70gkoq3Ir2LOn+i1qlRxdrbmmySLkndNBVDeo4J/caPDtoCKfKOGlIG/wNDuSo9LDLYaEUHsuSeqLQudhirpThd1EU2ic+yYTqD/EgHDrj42DxhX6BqX I91BgpCzOZnnkuw5y08atMTvXd/1NwiI1vODjCU9IW2RkMcA9XL5G0BR6358fhtbWOuo7vtJK0gGo6+6ElMRMXUFYJnCy47hDi81EB447Kub8GlIGoKzgKIab3KTiGCWYkrq0HK6SAXot9iM5FpKANgZjIXf3SAb6BCgtgXv7qqCXhp8YmEv
BsjYqX/rqNvBCoG9+AiFUfbxWgggO1uE5t9p0CUZPFNEWzE5VgQo0JUE6K6F6JguS4aoe/hkpBTGBGPov++9zQiUwhaJaixaJiBHDxGkq5iGU7bnNpYB0Dbj7petXe+WGjPruAnM2yhUMF5px4IZdHTYVc/9cKLLsqIMkIx4ud9iaQ17dL0I UIPby4SI657x/TPTZcxS3sagXD9Ixaq+VHJTQhLA48DoQKFiGozG4nKUu9TanXUAwDmQqSyfn9/O6WE5Wfl1+E17aUteMKMUbFnnNEwIJl7yPdYPkiwqCa+XsCHXn2yaSifxcrBKIcPgO6277HGWcHe8gbt1Z/togObJKa3iOMpUiwsyt30v
oLV1FQf3duP42QTXoiY9NSMCpUgl0fh7mdLIkvz6LXnQWoHrgre+ozeH9ATebZ5FfuM4e7pxF91rCVD7gD4HWn9YDclMAgZbjSycLyj4z88Odc03CCx3hsWzuqsz5H7Cl12zgY0nGjloPlPXpTtl7SB6TSYuB5+aBsc3J1kPZXkGGYItUWLe gfTYDUlkcuWX+O3vlHUdb5GGMMLgM6IEwoNCU9sUlcUdey9MBueUCpHqyualxssccJ/kZsk9Z4jOnpfuXuNHyNJkiEFCgjuGVeW4+hsJZ5etO/yjV0k1eGXz2IhX8+qVsmh68PWB7Cay0nPDCrnKtUEyqxZDmAY0D0D/WKYzX+NoW1I5i3x5
375ISllfD9B77xzcMJ8K3+z8UBfsUrxt6tbjK/1HV56gqnZkQNrPCHPYuxMpFzd/FI5DKO2rucCMtiu/GPXjQlih7CmDxKIXmsokm3wapVa4dKfOo28xGcreRYmY4qwNKX0SYiM+o6hHVOZ2okqcBnjnQlZ5dkijN7U24BFMIw3RNCYqWDuV arXQAv3rFvwMgHVSXOBkj/6v6j8Mj3YpKo8o6uCiGNeEMwx9SAAFhGm+5pMfLmKVl2fkHjMdeSpOAFbzPTq6lUdhNa2o9NUKOif8pB+ZSS4lJGKJ/uewvv7Bgbgnjp19om5Wmbu+c2805N96LZO824Ej9UpsjLb5/faN+w9jX3vzhp2Z26Hi
MgthgnvcZQ0t1+bT7hs3uftn/9LoSCuonrf+OvfD78aBWM8WPmXv/cJ8kfozpYbuiI7XsduZ8Of3UDOvNcQ6fs8wCon3lH91N78Kz7jcwI2pvSvCnZfQKorw/4Nj9+AfGP8EyNyhR1uSck1+N7J6QiAb00lwV6FQqDPDGdXDQajxAoKR9ER4 30ik6zj/iz42Ms2q1vhA8Et3k4StPTYCALcRF8aqMTwO3aDIZ0NSV88wh2FXuLfVghWFSz2BtIFV5K3QtWvV7l4eF/CdcBnNgZKlRPwjGYDq8y7nOGZlrxPl2W3nmtegOyuOTB8fIk5icdHtixHQ7zv3ouRX7udVPichtVqHCh58AO48E2Wy
RFn4s4/mbM6ZQ3FiJEW1ajdnFA5kKN2UQCTLE1VWSm4PZoRmeeKkVMzqpiJSRSNlHsnBWuZosRHpre772Hdu6MbYMcWcA0gaJ2sjxNTwct0RTWjNE51k8Kd/4gicWBT7yZu+6CZBdrDGUwjWMtS8q4bl+3luqIpDq5r/yBmrsXXnlMYSzmor OXMRmNWSdc53ISy7xZx0BDo5xff5qI8feVoHKwfebm47/cMkm4F8o51wEKNFlK8d7U0wAZ0zzdCiCm/qXSjqtXOaFDsHkQOqlBscpJg3UQ7kiggslRQcSsZb+btIfdfTb/p/NXBKthJDJcauVCybDULZL0LoI86UDlPmXAiT8RZ3FpFkJRNS
YnnnmnxXBu1Tn9dQEDafsG4l9uMcSln0TqiT2hm/Gbn6fuX8KHTw/AURuJAQ6dXGGYWBgP5gXN6v2YdxxBRUCRxRigFY/vTvnKWMfOi3dk7AG2TrHg2zNQNxm7SmcCqTEWhrwatOv1NOtuM/GeeFXDe48qGau0XeQ01QxocC0uZvH2tG7aNG y79jgzUAyu9htJL1YUZCuS1kPlqEhN7X3bRvYjv24fPtZQR8m62/+zF2OSdPWTqEeuBKaz91/RrvTj0pckXb4/tOfj9vuReftphVXuuK7uLTcXEwIzYEHml/D3HGhdbJ7K8Z4fWcz0WcewCqgtUlEUA7+8zYvjYog9tEMC5Z45KmyJcIMQIF
3z4TPQKPLE3engnbmMDiToJowTZNl6iHcXwaBeOT28fBshQabAxqAQu7uQ66K1J9g0pDW/ot0evoqlfuIA4fM7D2nh4WQfPBGatwtpwLN+Cv+VDMM6LuOg7D6Zv/AFrstORdokWF9qxZujT9cQzbCN645C6NufeU2PAilXP1/4jop6CjriBH 3Qkj7Ea97a4LWKeV+PtXdEL34w254WWSGjdOj+SJdousYRs3RW1GQiwqcnndgjg72Qprdn3cgm2bNIzbRxnbXOwVdVMHntGDRdLjLcoTIXGTuGreS7Rdsf0drBDkflUdLjAAK7wbkndtPqZT+V/o5jsxPgSeic+Y7afzTYFgkmWgIvl8VgEm
auGfGQ370pufVT1S2hbzFt0cYhYeGKcJC9jIR/Z2ASkQeAB4/JqdiBpZTIRrVLaZbrHtoKwLhaUhd0fftuuJL9YTSQqScMHfaZ2HdYRkYKUSBfqOZTAxt45PIdeTexp25O4Qd4wfzhCres/A0Zi1lfpZy3MUTZtm5kuZ3F8dUOOoT6LZxCeS +xzq5uIW+Lz6ZrKsI2FuUh8DSPFds/uYhUWL20rTmGbKeBaimLDYZDyrorhM9MfjN8FmsEUWVlMk9rKti0gb/pJzHhJQdxQiapJiHmGBTwO3UU4KO/KCHLHdNa73el3dmty8c+K7lS1k5uVH432gpbLlbAGGv6Aa2pk16l2YoEtqtnBWAclY
AML8Dmk66DvHip0yEAyxp4WPN48faCXx/imYuuZ+6K+4cZanZKi0zBbtt2PH556gBlqa0iyIGVGPLXB/8dguBF5GTsH+P747bcN83VZ9d6WTcEoWZ7S5VfYJ2/YgBUITK5zbLihgBJEiMfmrA7zQtEdgTR8JfLRd9rPzXLldEFqq0tNxpfJh iu4ngnD1MXZeefjz/cgPuxK1wdM3vopdj8sRHhhkiDRfh5K59ApKROiIVPNT07JBCRD7z8NWe1tpOiMAqRIqJY9qiDF+dCSdC4tGaIYI3RzIYzCq2/+NxxbEJNFrRSM0iuAOnvZ+2nbjeKqJQEfuZkeURJUNor9duQ8wB9/j7g8YLIWihs0+
/COO0j1PiZtMSTnN4rBcJgWx7wmfCBaE4FKHbrYYegMm5NI6worfOiMVYdTlkX/Uc30QQvaO4O6+V4Wz+oYOFKc0x9gZqNKsh5a2C/a0WTeq0NNn+gAyqYU3T/W1tBAv5gEXQl1lB+ZshDBrLO16pPOe8yid4TASmEdvbPzd/QxeSe4M4VCn GRAoeLqFjo83/v7m6xAcDUfIkcwQ8fMqXES3NxT/Y4wLoJ2YR2V7qoA3qidCVvMjVuqYqtVS+lrL91YxgN/EygwRbBjro/G1KeRU0HIlzkYyvPfnCs4+dVntqgRPivhfIvlrH/oyHaX1+9UfAeyRzK3fFl1o7ITAkcMtIH/2PQQsY8pQ4bdW
77Vg8vM8D3Vylgy+ksEWrPQtfIALpqiiLndYl38MPrbBTB9clN7I5aiMB2hs4MitHeNcT7EUD9jNlZH2GRO83sjI2xY9HfaGIlGcnCa+MiK8F1Q0f2tsyprqZGlyczcNbv4RbpFvrqlvyIjQcCHB2oA8wYb1D6r5in+90Q/LcPSFgTH0nfxS GLc0c8H2DHx0BOkwag6rG/eTIbAEZ2EAszP1ovRBHd0tPfuQXYCBQ4hE33auAJYzT0Y/Dy3k1mFoMYay834DfkciuPSBSLwKjEl6NSvvj4q8WlKj7sx4YfPjiZ9dDx3DLO90VoagAyzLu/w8O5Exb6SVCjIDy5kPoorLc6jcaJM38xpgfvI7
dB2r1osxQmu/UfXRw7aGnil0DNAXhpLai1wdYMZMNevtyR/IOIqEpAMjUgjyWLYBvzUjlgrY8PmqHh3ynSC8/23kmJNoI+/MYfMS2PxhSND1srGoqUUqUYAtM1ia1jOEEkWJswURUbLKYB9bRnBautIUK0THvsGAYT3GBYeIlWoRdUkC196F sgDNxkCtePl1M4CxdO1dpPJWXV6Lj+1KSvmAzAs15oZa6gLyLJCGm/r59kWy2kWffZpPM8ZC5D4ocXGP3BOlpKX0YB26S8HF3+l9EfOngh9qREb4FpDIzYyKz693yvxKCk+NpS1KY2HLE5nB/Ty8/s6T73HgKiPJQ1FwMuvQVqSlIbXh6KdB
1xWZ+MkVrTwjtO9SiAxoq1i1G4q30ZIMZngutczJCuRo+UElxVweX4mV+3UfDM3tH+YYegqqN40CIHMF+Y21a1w1U8YnFY53+Hz5LrWQEQfR2St+3phz6kTH58PIclJxwc7FVE6yG6RNKsAKv/dN9frHioSh+jTrOkSOjzHog8NjxPlF6FjD KSJ09PuwUQuBEZ/DgBijo455H8xTWQOLmy3JI6am6+J6wBHN/6vIbiPt/mUuBiax9W8CvH5Cmq+K4Vka07FJpvCpMqERU8J9U5T1VRLTGA42rW5z+JqalMNfpAoqCzZCGGJGxfYYWEU6beWgUmmgXxPDWx+bvTJUxKsgsZGeUhBJ88/IaEjA
AXimR2SzkJiL3h2IfHq5lbHgK8LVfn1ZMExhTR+PxD8kJjQTg0q9D4XhHVgxmuzr9Ni7P+Tu0gc89MCG6YXucNApnNaWUDl3TM7ihQD4ZIqNAx6SHw/H15/OyQ1DDpdvLCCQ9E0kC4WuHyJ7ryms6/31EKdtNwS4y3l1eIDASEm30aLM2F1V NIFL+5w9fq5ZOtYWStd2xp6sVNH49imhZgPgsLxXw57X/IzeY2IKq/HYe/r81YtJM4qkM8ib/NJVDTPdO9Z/455z5Uh9tw90qIuYeXDL8UrddIDbxlGNX8OTXoxu2uZJYnh64taxWE6/oDQW8tGdnH66qcpbFvoklgNVEts5WGNrsrvP83c7
MBYiCt5U4wq6cxnC23IunBBD0kknhVUl7OC9wvLDgxRrJ20AZtSZAHPqLAvOTAHMq5oVgQIMfTMWAIs5aOFO9+rqMOHBYLB4PtK+WhJmUbRsctrr8VyNZq4++3XjFh11O2tBvnr5jrZo6/TWSYHu7pzKfBkk/H6KsPTLdbKF2+o614F6tDDk fh9p2u7fOUH3kjBMPZs2eESiu/1V81wClBC3yPq0ZT9BOW//+JnSCgs8uMSUF+Qc/iqlCp2hiF0b99ZYEhjt/L8gRjLUYTBJDpfX1JMSd3KuwpPQJyD2gtCE8SynEDnmHFaBvfzigT4krOkqhf1G/x0WiSBDkdIb5vBXRt1htytXTNHs0SWU
h6yymm62qzNa/Rkvr49tbfZUpi0R99dDT1V4FEeluTryCUk0JgvWtuHY5I4S7Ii6NGQubWMK94qruqPl7du2qMABU0Dxal0+uInduEmE9Qdhb1C6icBVSdZkRP6lBgiVE5WO5naVgLgkxUuuk+PKs0InKH8+J1ftX7rBxFRo3jMG7fw/lZdu KyoZDNWH1hyVvd2L/w2cuhCcdyrG1RGqQIzEN861x/R/PfYlF3K+ei+tApBQ5Uu2rNN84Y6Sr+TByKZdBghsyM/3V/LTJ+HnHVpGjy7vRLxBILVswzrAzZ8VaVBb+9pGjdlgKtlcdT+TxaVx4it1wiVAB+C+gBlmVnxG+hgzjURJbdKAnmhP
H1YLIqeInFHd3/gMUcmBmWO8m5BiSm5KV6dtqnvgQ/e/39goGj6mUjuoN1upCcmAv0FYYojRdlin6SA/07D3hZCApi3RL6gHQ9vtKvDzOXYbEDr6xAHpS5YhV9KqEqUW+oaqa6kYUwXeoE54HnrJuYbj2/31AaSCpTx9PF+4SvFttT5A5Sye ivMQ5fxP88boL+WGKBGutHa4BD5LTprEpxJNkpGAJTTbqCrAwRQQAKnZ4QikK2xUBZxpj4lYkV+3ZjO4ODUVl7KnK1spk2Eu9b/ND7UV82HFBB/2kH1TjGTwxIZu8z4gb+3MNHDcHiCJvFaAg2hhYu3ORB3ZQhB3y/7qAUvTyKgKNeXKHg8/
FJhcMyNV8J9cIQI0Lj9ij/0GkSkm7EGDoMZchakneJKjOAM4+RY+yk6yKmEY3FC9423keMw4SJMKssImXemGC1CUr6RRhw6ayWesWGUO3lFWoTT/XOZdnOLYNFwlLMefCaAKipXkdz/HJ388UzAwQfamHSkRhAQ4IP/gkJdYJFdz3EgwV8cu ggv02PueS+v+aqeOoJdm9IT4MDpw2eB7kaURbs5DLQhKvYcAzjMWWh1oGMetVR8a6ervcUwUeFnTr/4/nyFUPyafNfxIXUjh5M3yOLC/FTDNIrahbsG1aetJIBzfaO1HIkrkPOAd/riBYgxwAhTkdD1VCaLQchXx8HafvkB5CBQVuIYoTFlX
9A73r60OOwdZrekOdDmTTYX8xBdx97OHHJQkfEHbieh0AFSCIU+PRdpfp04XLtmdpxw0nlD4rj0IAJBze94Y+pybvp38gugH5AkiOuO7NQBYfQ7Yu0FOucGSqr0+Li8cnb0sgnXUwo6RnatKfcUPq2gPo4PduvDWtWP2xwiEcNH0E/xI0AQs MxfpO04r3VGKCe53HpFRb1pS56qX8/8IgYohvmIT3zxMcwjxowcy/w3IOZS2RE479zlFqZODamkaS8wjAAOChNXHlWapGb3R7FzithSbXbPgOIvsFT6x3TeAeGDWV+pv2vSEwU4GyDIXhsihpDGMLCMUwi90cXlZGaFUxanOd8Q1K3Z5blHp
2m50Zv8tkPL/g4K68t8x5L8q6ZsczI5uighCY2B47L4XkL5Lsn50CRROBF4/j+hCS0OY5Ej+5jrfhdC9ClEjCzS3APRjoB4O/zcy24Btv/rEEvVLJeV/+hnQg8t0uHO9QyfafIkM/Lh1p3gw/pgAUB3nxZ2JITrrCpAMxhnkjiK6QtnsFX5d sXrH7Vs/9WhHBZLPFgbfhyAhCM8gBCteK6MttcZIyMs5ELiSjbOt1Vo2mdZMz5hY5jSgVQn3AC3c//TN+NjCSqjMQjbXFzouJMJRaOUGuutsHTYq7r4uS2+YQiCjab8vSxB41iuxXuWAukd3nCZ5mHLW3G7glQJHe25OGpx7kBLbk2maTeM0
UAxn5ToLOkwvjnIFuhB0zXyQp2tEKAX8whjwM1DtLPsLR7Sh0Ii6YhXoVt2aWA7yQ8itaanoYJwJTbKhP9u2NVK3w8Z6mPH+1OEuyvXceqwUsxqGXI4a/MSMe0g49HA5fL2GW/RI6sCqYiKBXFobPOeeD9DVMHu84wAKBOEef8Q65U96KEY9 yCLNLRHFKnx3yGIiOrboMYNA4/mNMPjJ2bCN0Jia4+VrRfDqykjZ3nvbU7moulCRNJ4HwMVRyOeKFqOwCziZ9oRDa0Jlgn8fGxkRDYKaF8Jf2w3gHqQp3d8DoKVDRQEjd82nHTF9zKCsnjXA+dioq0J3cb6ryXr4Eo8TyUnjMJ1meZBlt7eT
m4zS44fIfqKF67RxtKNwHyWqKSP4pUInC9T7F/EAVPW/tRsqQKJ9XVHDH/HzXVQoBT/0CTwg0iVVocs500X6JRqlbqG9zjleeVsAvLTxEiovMCPaP48tZ/ZSiKaD5Z6QvOgUqwxV2si0+hvIqFkBON/TCywTe0QIhQNblDgZOr2FRqyxTuiP MXEV4QhBslZyM3f+pRLk8qZ+SJubLFrUEp+bAB25iuovP6qzJVN7WfcG7QdB20qHUtqo40Tjsd2N70uMypPC2DPN3eYQeZfcD21n6LobgJ9QFnbxDV5fTLTNAFjdn2TjcRPgJ47G5kE6eb15db2f/obBq06rmhFA9NpONgoR/83l6k+kEVeL
tLjO8Y5plJW6ewS0DwZ3/fhKRYozISMTYZgQmhkjZKPujq4CKdZZFcGnYf/luzcA3hFcmjC1RwCjotnyM3j5gzY1NLf4IjL1b6XNfKYm7Q0Eml8UNBUjQX19FBPbO3N3bwgkYwGuUeu3dbDQ6PCZ2NoVvwuTarQIleAMF7khdFFrxukj7rI2 V9UsQOZvvo9D0Ies9eXJkHJMWEMgCQQ9dSwM1+VW7f2QvzaNeRU3sQ5PzVGZX/ro1jadLfWVpFu4vH9BDPrR/WazB8ir8ihmE0hSrVc0jaF5Ja6Kcl5hKllwdePlV9xGnxhZK3ZdRB+m8/BR93mwOA5bnKpyOknIRxIXcFxK2rlx1fyyXQ3q
WP4ub8F6FsGY1CpmaH08OKXg3kgAD0paq5U0OoQejCQES0cgFZticfj3j/mG2i8+ZMgMyYa8tmWOmPhvEmEj8pAKVIEDo6BPnJNOuwfnfJoT5sZgg6AWyjzYuLZv0Md8gzhTXba7p3Di2fngVaXU565QDNUjRgENtTNI876KiP7wNs1tqneI CoEwLJtomnDCzCLGo8hD1TItqesMIAeHNvWjW0EF2so7eKv6/I/moudXCfK/HkB8oT3fye2XuHHmL66Y6/S+DqdoEVQfJHaJ8ehWnC/yGHddZOP1wM/tfsX46Rv6uJOAMfQRU0QYNVHJWOrEEGcIqhHECyD4vnA735gCHmR4Tpr6vusxktOt
w1y5HXoAGRunJDxbPO1wwkZkB2lHqMzShievU65l3n95HIn62S7Y+o3TE47VNghTKXKSdmpzRHVP0lKvbeQG009yq7EWvVLa5z7JCEX3gB0IKdyFqeSCzp1rf4U8hfA0OxioHa9FUoWeTgZ/LAVmivko/TQ5IIR+saMaid2QjKcWhCWDNK6y yMu9tnvK8RtwlxY3t/cOxaeFibbhUguAGJpdPEzjG+2AV4bBItgWD0lGzxjI4YW21UTINKCgMZ00ZJzl+Snoo/VXAWdqFVADf+LU93S89aO/qwKmAkqBXjtRjlK6NZnLrQ7vhHtH3ivvGXkSox1byIV9scP0WhAPDdaOGM1/4HTEKueAlVhb
6TpcIh7lHdZ/MF4Iq4E49D/uha71Bu6AXjA1i8yvhYpL/SW+E5EiRc9kuQ3mkibrFZXE/ul/gVfHuUSFoi/vhb/3QKsCmN2G3rLWLXb0VCW+1ZOr0/VvlhOYbVWR0jlNWSFKU8v4KBEhfCV6ahIBcAfaMIC41rglEUCFcnRl+YL5HQVUQBGF kKcT05apdbGP2MIBa2I7WrWlYLx0N9ozXQaYIzeCXSN5Jjr9RPLxeyqLWjtdQXX11YazBtwBkjQqfuG9/QWnm1TAljnw8xTCVzxy2Ulpt/SteV/glYIECjMHAp5TRIZejJfYe+vKy42/7Ma8/nETuR1j8pQoB4B2mj/1/sh/DvIhJsbSuySi
xCb2t/lgROIlpu+vLX23LA6XOmt52NqiDVDrqdKQbPwilkWJWN0iNVlJ7tAVjfcDXtnh2ed5fkGmj2dS74IaZUBb6E9AGwrbN+mf6bCaGUNtPWyqsVHbRrK6bEw/L1ayyvXCGyLstApnZJMsvcgZ3Z7cNp6VtZ6KZX3fD+8S+ca904RLh1EN 3Il2L8PbVLpmCBZX6D/Pbs/KML2g0ybjw6oiMEsFJlCbp/jxbMYnZLVLQe8JXY6XyT03PiE5BuhtXAAJugPiI0T2+RUBKwKsNzcFyVnopdr5+LFO4/OjK0bDrLID/ZfdykDPBJJwvShGp4vmtXWHd+JrcFxKZGeeNhq49tf8DQQOY2qlvvXV
4fZumul4vVOTGZHyp7yj0sq55GdnE3uovbS7iIlEcsg0BL6pB9s3DL19VXVMt87Cwk3GapxxV7u85TwUZA9RCKURKgAj1qtjsZfmLjQXY7dnmkQBoxPJ4Fn9OJZIFDqaebA2Tjkvt9m0rICBCUHPZpcm+PgDTn6QkkMSkRXuEJ/AxEkrRfB6 uTRJOGZsjcFZTTf09h5HLY+JgcxVIXbalL1tLrTu0hv+cT7rvXDgEhGn2pWv7vk5kAOT6oPsYoa8FFKSVZIJG8nMOGDMCyjtqiVQ4QV+Lr5GyIjDgtXkYadsKCXwJi4hwZJTc96A643Om8ywmelbxicRWbuurURFOExakE/wo/fDSR1q++CP
RM2XxvYhQhz52ALaNhGxGJxtdiXaCdWjUoullx8KaMWmhXETrUflPDnW67HGbG9e0t4LusEp4IQtGsG+7rBUI50dkV65ldvCdvOh7gNOmRtBSQfLdda3GJVmp9qNd+MDCWADnJdds8TnEYrTdE7qrVk/4oNpMiQ3043MK4DJZn/4KWqDwuDM ZBWwiBB0xEoUb2rhgT+FLac8XkEoOI/FKP/SA9EoEm1uoZcZS3zY4gjCGWrZJTm1vq5f5BY9Hh6a795pRFKi0Hzg2cJtc8OrSohDiVDgDE95qcuIbhjMHSN0vW4iPsoAP2+KNBAjBGvUEbGFAeQOyV92/7XC5G0p6DdM4ENnHb6VEtu02K3W
6+YYxckg/NAbRxvsUKhsIQUQpXNG5ifks3bJ1ieLYZkqaFyUHbIrHbGeMmKzI0hKP68dg2yMWYV7iZH61Qaw8u1cdZcWXxlJPvIzLGdVkJc2j/7Kj0JK1fNBlG1qEl3WNxsvcJJuWIlIJrt54WNj9jKAuEIHc0TAQIQVO79A3ajDAaNrZaQG 2Hn+DWMFS9c+gQSqucpwB9exHGoLdaB1Nx53h23uLryevxZyJnUSs13QoQA2CYTzha22pRKNOipbxMZWA+tpdIPAr1RwtZn3M+evD8gJdtEIGzuwG7HRtergYr76kox3dxgUjzwWc0POubLxaJBJGsV1H8EPfrjycFgEe23eC7DC0VSwtiaJ
+CZzVWF1FPXu1vi5TsiUEymC0z6AT2HulgaVkC0h+nw7e7i7J46v+m1P+5/D/Kqy4PUFS1CXug9FQ9nmj7EssYzZELyBH883zVRtU9IEkUoLc/4u8S3QULZgvwI9tbshwtfKkZX3h5OoXSF5y/TUA4gEaJsPVAaMvcMCHPhMKsmYWRSrc3cP IzFVd4GftuBcgObWsKYgPgW03/Ca5/OH2501egfaWFnUlXtJPuY6k5htx6+JkI2xrpIrOPLuuuQmNg0+yiHLosHA5i5n1TQJrTowlYbW8OGMPJiMXK2jE0YFfJoeWkdmY+LxuCBf3LjAJ0T19YpVNRM2daNbsd4Lk45RdIHsuAhv6lp3KWLJ
Nr34UybSl6owkJp0QRRYEDmVDGiOBj/sdHNFJigTD2VI2tmPZsDKzn2VvaLhFuIeY/DNe92diaLucUpbTz/dUontes9wuqu4QGJaUpr5Y3Xfk9EBNGhyLslXYnbnbnxduR0NQQ6xr5I7GQMp7Mr0O5ezFtm/Dk4b3h+6heQ6dq0ReISFwxP8 9fVJWIPuVS2k8F9x90zEYVdQf5BCBIkHhAhrzscbDxI/SVG+Mrcyy+z+L2KiF4EmCgiTlpJRHGNShxAEuG5qqfwp17CEhy9BZIJ6xePJ4bDjUIHxOd1A1V1MI2Nd9S2IX3hNnEmXMzhoYqpvndX5Y9y2v/pdtj8rN5e8g9o5hx4mBaAqB4Za
mFqfDgV3aM3RoUjKmOkrVodjEDMauW0INX0QQWhsIuHreS3QGywUkf60m0XUVCLzFIqCOeOlBpaXvBdwZJELpqyum4RYeAF6MCXX9/kw0bYev47a2754iCvosot2/qD2crL/mdQ7BDn87NaXhuLWSAKghRBzaw0BXVej99XZUi2Qdixk/JE1 EqMQC5ee0HGYN5q0PyYNi0TWRTpsHmNYh05+6iE/WrN9QjwPQOlwFmZhVEQRbfNNhs5yaezzkVmn1C9VLs44zzhZm7kixlJkujbIz751kFZWc8/fblPRGK7+PwilQVk/HcyGBpw/8yYPL4YrIzA3atUIfOccAnqsaO4OQ8vTa3uo5e0Ug/aV
dipIMyZgphJekGELM6o98cotGJ5hCtWcktLIqYAf2M6IcxJcNh6qQ1/rrqHG3D2NKPhFrKx90AfWDfTtvM/fKGyENiEP5byhLHAssIbmQr6lpR/bmkX1y/n1zv1Cs6/C8At46YBS0XszjvaNoFD+OMtvPZ2zntxIiZj4ji7EuykRsjOuHIYc 0pHTWZ2zqIRM6u37uIQaLdPnJXITuuigcOl2x+8Ee80Kdnt5LhR5Y7rbh8SOLgC5f7HcCcX4pyLbdew8PA34S1F/YuoN129xguTq9zTk1K9zAGidC+4myvfuBiNK50/AKpMjdS22eY455B/asmGHQhTygQK/79ifuShJirH2CfATECNG/QAm
srCF/ICnyJ6SlxWz7eE4MfjaJW7oHbUanyP1ffJrJCqGHVS2XVaduxYdzIaOyo/EyCKmrbfnoktVszt2oFCWLHc+YprGFzcXR+GrcMjK8QFTHumu+Ezks1j6Aa4dtTW7cZwDu/kECbArLP9O6nCsd+1uZdXlnK6Qje1iN3132OkFRceIjB/U zQE00pKH2JnRmtOr707C6B2sdUYTEcCL+JmaHOzYVWFB1WrzXlgZelSqCoVHnW5g4WK2MrjktK0z8m7cX+BNwiBxR4NVq31VEd6ICHNvnSIp6CAW8YILXEFnH0OQqzmgroKdiiylkCiEUVl36OLDyymgT1MgHeGobBi8/LloUNGy5HVrvaQI
H8E/RzlE4o6LHqjJ8wAqTjeQMHVtFMd8jBqHIddCSRliaHOMNeLBNW3KyFaVqkuP4l7fKTeW5ox5VQVHtrfv1GEcd/RRr5uXnH7BWt71PVRstDnwBdrNsprvr3gT/Q5yuQnsyBSNVThaOPlVELal+6MwoqscpYB71Ins44ICslZZONR64ljD mc1MWktlEAcaqJHnfGei5DjaJ7FdJM9bL+L7IATmkHMv5k3WtL45pnTw65BqI+S4E6GkXaDqKkEfD563AS753bHVwvGF4nwRfm38cjQclO6A+l9ESAIJAEw6uJE9rPmm1AHc7peW6uUwsyaVb1SqItSVx3IsB47zphH6r3LGbH3tI0jG1RTO
DgT0W2vZWEmgjY/Y/teZ09YXN85Ohb44sAR7iyHRvmcnBKfDURgRqnbWJ0rg6Fosl5RVDYN/WUrUuJDLT1T8UnkqJKBo4h8kMHxnMCgXGOVsotLgsKPxcjylZZHFiaJ4zEE9CgvR9xQmY6RluzXt6bqsuxJSoLBEoWtGmZFRaUZGCxi8NWop PXkqj4DMAENHn3Hg0O4ZPjvVXowCVeqNWexY8qgA7zaYPhfxFKko/HNpdMxyYuLm436ts57E+5AL/3VJeEDpStLx0TnROYwoi5OVfsjheq0DZQDKVs92onOBgXrJZalcu0+o+Lkva0e3m8W6ZN41CSIv0JsPeJ4GBiLWGSRhXsU+jIAE4ni0
89ssSYzGesbUEcEPyMaTDVv3sI6PFRd7WdAYAPSKkCKusYtpBDV/pKaSvQxTnao4LJxzYUcKTxKoE/phsmgtlE+KnlyB8Piov7y7i0HQBOtidlixXIL/bB7QGxGWtbnJZxtDOV//bK0lYO0PdjgNHlWkOa2Yf9tGCDQjolp5BI/MMwyJY8Ap y229d14eKl3WrV+Kq9p3samAMzLjshjR/xPqBS5vkDauUU3jiDGCNad1uibISE8nTZVuv9nC5PPXi73oiZ0jT7Zer7vHv9V9cqUADbF23IsHZ/FxVDiKJaLxIxYQg49deOcygk6Sm2iPRsEYk72l/+slF8IDxvtClXFcHXdSko8JeIgamtK5
QERYfntMefRZ35Ei2na1nS+q2lcLjo4jKCOf+GAJymTHz+l0qnhIFAmTd8zmVa2Vhys9eh8e8XsWiJOY43uW2I7P1wwQJdRJJzrs8FnK3ylNj5TUDBtsJER6uAm55CqZpVFTXFwJPiyd1wd58tXYKMsAnD29WTITvIP5xWp2TiLxGsOyqfNS 3F9oDyI6mgG1W118r8QBFfcuW5G/PrBOpKZbjwCcpyi4GkcQ4u9qNpwHP6NV2YTzpKE0decyi/MCMeU0Oh64VicFA5CNi1qoDgc3l2wtOj/ZjkuaRqSGrB2sG+N39b650xmGjset14mfF1uoEfNZ2xDLN9qOZXNqCrEHHhWQ5SwVS1XKZ5Xm
e9Pkfm/4r1oOMOIbmmZOLC6KlzAYZeCLurP0NqmKmz8AO0xhJtRmC5zw0SOO/M2GUFr/C6vVkwijX+DmquZn2BAgIjk+IZEt3DvVnAOMIED/jUqokH4Y5eLrreue7O+agBNULO/6P5GXDF6UIXHy6NVDsnBZf0vJgPzIO3ms6Q6MQb98qQQg T2FOj21lIp9mEfTLTNeYKG20UEyTO5pN9MRCZ/guUxxwQzTnmBG9vSJuQUNa9dvA0zCfCWSZzkVB0Z7dCw/3efn1imR63ZnCAv+E5NiZdN6qLsVOJoXlHJbh4A9Ip9AX3eNrn2Z7s699V/0iYD3XJ3+YEMZr7TYqpIyhpzbQO6fbr2iNDwji
A5i2dC/HIEYBqbL63S58B79AG1rrAsHbeec2wxO6irLhHWeIC5KPjEAjec8wIXMft4weJjAK6Gf8Cwn8HVrSxA5PRI/L8wdjz9eF+WQHtCCZI+8OtW1Qk19XN3yMM0PBXaGr7E6LPiIAwana0ib4ZkmFrrJiH2DHKZq+lxjgFFdU7SAf4BBl +rE/j/l9G5vGon6TAwxu1O7iph++/bKSzqEJOUNP2rAOkY7/K4rJjLWN+XeON1pH5iKKkYQlp1D/LdvHISp8oCa8cZkDB0BITXPybEuyI2kdiV1HcZyu0N8TDy2Uy6u98voLl62PmInoRmtXTgY0rU4S+PC8I1hkpXxwGdbgWlKutuIW/rL9
K+IAS9xLSoFyOfmNJLwuSLkytNv26Duk6XIkI5deRIEwb9HOYPSyVU6lVtprnTzWqsV0cOxLqbfzBeeAWzgaXuvhLzenX/ZMS3cj+fSxdRj/PEZPMI7Lz7tRQXsFp2oGwUo6iB7gZIr+rQvgylTGLt/zftt27QWQGUCtJXs0pHOOW7q85iYX Az+6MekOz/10ZU3xqWAmfadEEYREOhUcukqyZNGv7+5AgMwtf+3scO0yB1gHGW7eFQrlaBqTlq7smrmIPWaRz7x0Ynt7QPrzhPJA7EjTVLgKpXSES1Ac3vjLa3CYmBnIYu7zt8UlGDBsZh02x0bjuIxut24ZQdrUxEhFjbNwQeyqnqqG1IDf
oV8ZMrdrVFm2x9PX6kcBAgbC4ZUbZ7zB4a6EXdQ1pjURT4wnJg0exyXDRvYKCCidV7boNsHtZyL49r8M3GmqCPvHEb8sTLDY0soQAlnOvUdxmDw9UpYYJ2dLj65rSHZdmyjuX0hCfG3CUqTkudx7A5Z5LsIRwJKD3cBx2Z7wbr3uKmwtv+BS hKvDaK1XI0ilreANlaT5/qFLdOF/2enucyJ4CpFjKMwztmr1820JvMepT1bHf5itIr4IyM2msYoitzJCLHB+gSFQxb9R++Q7Xy+ELdH2pdRKbfbUVamvzJm+CPnje/QBB2HSIWyA18Utb6EPKCTAbrDYX/UPRGS0s0CihiNHTc6wY0Fn8XYc
c3UTXFMTogS8Rnwx9HEvejqZATdihj1+pv3+GqcAuk6tBCvDFyHQ52JCPJSF8poB5MEtvWT1iH2cIHZPpkkDyWV+MGNrE6a0fSlVg3GRLBIygGgCST8lcwNWtvpZCvplBXkQq1JGyQKxfN0OqKhJaq0yYIHS9xMi1DGkiuaHCuGdgekgJvC7 lPYxY2r4CcNm6WC1gTVocXPhih23rL0cD4TX+AvVEb30XSBa4htILfGyhB7/OQu1QjR6RHzipB/YyKTkvSROQ6rLm5T4vpo4iiYLDzjympCK/SWNrEUGH0QvOe04gqgBWnHb3rBB3yX6zQeHbS+7sLy/jTZ0yiPd7fXnjsVKPl6r4qn6J+f9
66tvBbeiwYWLHZARYBj+mtyBXjRcqx5pNFMcdZYiHw0VzJJbIpg7KETNBiINYiaS1CApTvg5lOzJ3DKWGepiNFsxbv81I9d/7UoJ9l1NLkd/3bDK7XAlBEtkiJ3TBzZLmGR1VFcNmqDdXL4NjdSWzENKLXrvGpzlFldhWkBn305E/eiN/aPm 7TtMGfb/NlOpJmfCqyyw7BsrgaozvrRglOSxIx5nDAYXLH8YlapPwgSuDrz6p8tJoWJXgPDGpDW7giwjK407vUiX7umDUd6uS9CCqprJHqqy7D0POsLpyERkFR9Z3B15iZzWIbFSEJMhR45HcjW5MDAwL8i6jTIKKG00LJPZNnXTUUELMMdk
6AtFaMiSPu868XD5+N+43yhL4ZqOJczgczS3zreYNAs2fMA7EVVrc9W5eAXmOvfbocjY7xHanrSul7u+Kle4GuKrG1cF2FOQsN4zQft3zUnLpLEUS7PwK2j283Anym/AWH+eXnLEBAzPrX38/NrkbCzHBDL+jnRoRveRiQEOyFb/FoChxD3J HNIlOS8yMvMKBIVOrwetUJ4j00inbIYfyTqREX6je579mOcVCsXqj50nzV5jMHdk3W+LIf4UaEnpHsUmGlnzkltAZUJdN/eejDe+T7WIyIdveD2jlVFiCzVXZ9sBfwAmSx5Nj2KRlwp+kCaBGfKrjgrLljaDy00r7MtQ86qs/4u/42XdiGzR
a5ek6ERtImjoJ0jB+oxehC/lFXjgfKZvVg0QMG3FPz4Nvbq6d50P4O1nMYrYcKswnmdJDiPVx+u/lpwXgmHUqQ0py+zMLCWhR5xDTd2sldEYtqqVYHdoPdHO2ltRQl41g6FOwQ9l3EakPYsXPYr8swlOtpd+B2xYGmNportizg2ZYWyDevbw B86YugKQBL4KLXKGGw+9cms2Jc43LuOWCOkEqD4TbFGZoHjige8/H6IIBwo4mYI1ukjSDXXkYfHUubSxN2p4bRg8t9MnHYVyAChoMlX7gaQpvpSNJ/4r2u56u2g93ed541DjT1VCwcAuZPyPhoMGxFECKOZIWP/2FeuyywYpjqr5VqtOxRhV
rEOp14M1IvW0SzpjhBjtxilSIEbErg4AMtLt3/nqg4gaV0i5RTbjj5mXCdeo5R3iq+jeWyqcB89kQD4GH9P8Th13PLgG2S8/81Lb52G7Z842S0bkCBThPFGsauPiqrmxV7e9q6rAI3vX2Je9M+jKaVNF9/kLr0pDLE/+ZA+PX415tDLLiyCT uOoD+7uNkUaZWHLihAdLKASlijC6oIW6gZhjXBMpkQxxL2TdKt8AFoKGWcukCgMBEKmwToqRTJW3I3o+VxEK/hQTPO5FjDI0Ei/FrTVTobbtSBMRAazgI+Krt7Sdic0Chyti2NfTuC1SaERy8Gtj/hNnBjSOmR0vN/VQ1CBc44HzZevE9sEG
D+4O1yCb7g9U8nRW6yROnaSlWkC1gK7wUJxD2otnyp9VozgwX9RXnYSYstkzNucAazDr4ZtF0XmWXngmKlZgAQNOabpYkNtr8CJsk/2FglGbr3pU5oRDiWzwCaSh+977nKDqWHD6EUmVtPpLa12t7awKSsu2knYQ8C7krVNhrciz1BNpCeN/ 2QMutFId/NhQyzbtRH+OIYpEUS5lNRckNqGA2DAn8PLbZq62DQJVmMXZ31vxx2jMTS5McvX/+0Lh34fVK+VNpQACM/8XOrr/KM+BmXonpNeYuoiLDixI6lDkTDuXRjtp5K9ZJh77TFfbNrBMpHIGAcUywfV6+JEef9ZEm3FC6skGPZ+nGZBF
wCVNqt7+e7g1frXpNV5PmYrXNZ0VgfZsyTnT5wFpxFF3Sz/FB+YIyMORXO7NkZn5i8BtITj1c8GluLhFEbD/2I/0pcagB9RgMwXUEbTbXtT3nn5wofc4egV3BkqRXYRe7iQ516+W6KFhjxFaptGB+X45rU7hz/KgmxknffnFGygyWsmvbATG xl1PzTgjZ0T1TAc82hhD/HhoEGvJzadlOocABjDlQadNHaVh8uWCyvpJV4pjfGJIKzmINBRL2j6ANLKvZExxlZYpXe0o6EpCzTueCakEb2zVKpOLA/9wwbcPXJ1bKmZrPMU7INuyxZyBgc1hSpyt3T1z/iRDKTWnGUQImVnerRIed/izPfdX
3VF+yLu8KH8TtvkTpj99fVD8vNZOdL4vG8FKeIQ7RLinZ/WQLondlAHexOX1x/LaSLtsABHm5uUEsBhBpIH4LQEYjEYeKKQ5/soDEYjSmszOtG84hZ7OvUYgCxmHkeYS3XPgtm+mXhJUM38xM1KtOvDG8ckZNGg9BmNvrnSHczEC2RptJ6i5 ZYPLN9183UwixK/Hj6a2jcN1RfosTsbPTKoUF3zw8RT9ga8nob06o7SVR+DoWHn0ep19KEFe+6M6u09nyDhFxHE69qyZ020b9WQ0rdofoGq9Q7I5OC3Bleftwugobv1fI08RlPPqn8zg/ghwpPKFbLOBaz2lNx0XgeqUThog9mpl/xMZZTl1
0RAlB9c8BRhTZReEH3Zf2uvWFkmQc4EBIl2m+KJuMYORnX+nWoZ164jVclDN1SEHZ7KpuEvh2RC4OOA1gbbRRVEFkCJES5pVYAVB+LbjtFx4n+L9X/g5mGhexTlzuVoPbjRoonj9myMmfO4igy3TJlTHZP++Rf2cx+EhFjFH7Qvf2RDKbgUL OgV6z2iY0Xtnt1vHWdeXCOKLz1Ev/q2dkxN+tZOI1PyessND7o1DB3KcfH13D+wIvrexXdoEeQJ5R3VgOMDh0mTBP3bAmka0M+fyOoHcP5IcDXwinYR1VPo0Ph/QC+xZaVEPiLbwo6iR+rSW75XR7hIDXSSogzT3gUU6qfm6a/PKDOgrh41R
fw8UZQ3+3gjTw8gQrnLDn0EzISrKBkR+hwPMrZ8123InloDirZ6Yayq6xXsFJE4D2ftSSdi+i/O8w85aa18xUotrUiZ8vT4crQL5OKKo6cWtqc+n5EJ4YT0PuMHxQ53n+e8hmhfYDqkKKLa7IXE62FQYLrf56Mf3qVxp/zXsd9mUopwFM5ww 2o+HxgOQv4OLi6lMKiKw9vbyRT6ndAsW7jsoToOlYnkgiP/sVLiYeUvXZ4k7Jve6C3CqXnmUfkKEtiogHZcGofDom2a1EoYUII5LxIizK9vzq61gjjw4fttka8SJz6rnb45/dsoaDj2DJoC7hdu9OD6TXKbp7qTd5KxKYFJnGNxOzuJsbAP/
8PwHz9P90zZ3vdJvooEBdB2qqQnCrQuC1ibOmObVHnoqlr7crMaXJ733kgNUXABF+VmyRoP23c6YsB6NrEMu2CzvO2ACJ6jYcCkBNcQQURsX/ZrY/dVEZst+3yMC8E12CnaF76V+AmA4Od1XYpQwd2h6umw7yXN3E4IP31p4fV5n+QwD2G0P I4X42qtZAkFfTunymZ/BiZNk3XCqaX4xCjvGcBTtY/G+4KJwdOTYovi/u5Uu/i4elSumaAQqYvd1+mjHc8o8Io3WoDBf9FyrmQMip0kzooT9stBhVRMM/dHm6vnykfIaQgaf/JmOCtBUHrWINR5ua57C4OvE3CCUgYhZ6M/jSwdzR2zvqfi+
K4sMnL0KP///dJgGotaQFlwcYuEu5eeKjtISu2p02uA+EeCZX3E6YVqIkpuEUwh1l5RP5HTl7JdsT9xaAJpJa/zIqD4dWVaMV8Az+MuAmhpxsKiVwLjL5cjdKdaIQgLB9rqLM2G4n9geTC6kUZdZhaKnN4iMUpKWn2K6tNP9IAkkz+zvAegy W6p/DVTg1X3n1X2CTe3GuceBgqE49s0zyPJGg4+DbJXP8Ykr4GCK2vtUYM+t3X84+utKKV2WfAx90bY2zCzXwgGjCgS6FDEf3+5z+h7VkTgjsHb95ELcUpBrpF9ULg3YlHIW5BIk/8km8qmI/d32IPgEOLfnzMuGA6DjjxJyKmREL2KCk7Vf
eYQsGYsm4x6RYvZnO1YIkWIhIbBK8onfsRuvSMjKFTfIkJl9Mpz1G9jG0QVr1AehniLQp2cJ2asgcENbxyqLPsfN7pXMaUnCMF/XMquuwUeUIHxoshU0rdX27QLi3b2phXuwMEe50Vh4Gtw7KZBDQsDruR7Fx9JWp/pPqSUB4Gm4kvnaHTn4 dEaRAUNdxDdzp6N+lcxzgXK5Lm8w/8DaTL7O8NgPbgvQ+d/ck9K5LjugDRok5umMVCJGwaQXX3H6up6Rh8fznOwT1RNggy1SLD0lM/PPTU6H2A9EJ08iynK3/lS4pxsmBIcldTuUufVNrh7jxoZI0RbpUbz+8BVXvhFvGy8X0Iio254nCMf7
+/ZP6mthx9BIfV+Amv0EHe1iPwGFiLeBLopIoNWNl1pMZAm9JVL07wNABhumxy7L3KwDtmg3cZM1oO77aBYUFkRAaDdL7sgfSQmjUNtc2zJ239eozCgoeOZh1flZDzhwnMBoRIR6d6FAFSOVW4LyqT7HvAFoEL/zPgj4YS3keJnPAvqTRW9r 8rUqzVulxnAqtLKrwCjx0bHsvMK28Y+0YF5xpqMf0C1wDe2qEG0ChF8d5PgfpotKU4MlVQ4ij3hBFy1vn/8Luk6AK8eHDSBipPsFlr4FU1yQ9FlsgmVPV99AkHvBvpNF0IOKlOVJ61W+rosxuAsHLvTHXGkOXZYiHK29Kcczrgg73gzSejD1
CsyQ38CZCD1BRJjsG+DFAVCqB41AdyY/LF3e9e8xE6ryUVhUTl/GpNvjo2dz0gyHgP4U2QEx2fNKp307nBySwO0MvLhiMX4lThT9SQSsVKP37fRxXifuWydviNBu3P4M1jhvzieYPJv+sCCRrskbOVMwZQ3JXDghkRuoMh4RovFlmkhoF+Hg zwsfw/KzdXCSNtmQCZEyzh5c8JbExF0jThk08c4ZVS/WiSVRwg4YVtV0akGYNPdFQpFkfmMXC/rQ/MZy+j6OBXRCn76FIdzY86niOsMV/t69JMWTg9VZI4M+5PnlzErknSsdcT9IOqy7Jyo03gNgd0z8PcImInvmf7iBR1XXe/244GeL2kDd
Qu7FeOfCJ8UnuLr6HtfV69cCx9re8S4PgTwV+SYk3rdT7QFoHi/I6uM3THR1aLgrNJme/2BdKAHgqXsR0FucoFTQTzjz2IcIUXLXbVOdvJ3naeR6D8IgN2LkrdwHpSQi7K4atJgrpRnFxFCDM2Umu7NqDvBmkzwODc/JusxseLjENOPno6i9 p2/oG1dNnFPNvCEe01rk4MjPG40oHg2UQh5LHvRKMo0/2lhUeFevrYOIOYNl9oTMaRzpIXbS4/LHAxDJWiFGFXsCs3LJUYcNzGyTDUqDAWaB8HjirTfKSOb1Ql+QmqHY+68tVVf4xPARmc7cHNUEEr4ZpzfbabeFeygTI68bRdBRQ2xmGWKF
pHTbCzC7NC9QmwraGiYhD5OF8GduO0a9PdlynTvRv/ZP3ujmmFvgpTqlEoZKhDKgOPRuOkO4wVUi0Na34OgmiSV4s+RIhLVf5FBI6zS0pVq05AoZbeW4k1y+DG2PTjnXsa763IzhTBC8Wlj5Ct9PfPkgLcM9SiWdW87VWKoscClyo2c4wFca bzRk363nH0NXVt02Tm+B/RHl0tM3ToHuiprtflddBnNqYlld+tEgjTfmvRZQ30AFtQX+FCguMcokXv8KkpHUqxCiuvWTJg+htnxV9S+AKz7O38Sb9PJxXuzCWgMEtgGwRELzfi4puqf7wLk/0sxwnnUIAleiwKYaZCKloFDM9tJktpGYquRk
RBnMMJLDpuTnc6ihvxyBsd83V7UMrB/J5HnJd8V20cjtH48ByPx+y8APOl21nYT4ho90IUHFvycRFuCL8IR6T9BQBB4PSQL4quIIEyREOcIK0KqA5YcUcJ3DYDfEgujqawrCZKFFcvKdOxjJuZxaly4knZ0bd1mYMuDy5Ef1Q1A+sJttDhnn 3Lk7pFGrHvP6E69SCJ/3FLl+qB7xY6Tx0H/il80jdP+7uBCv8LlrIgRIq7ny7yLEh1jXmKM0k4XerluPIIJFpyWQiBR057QWjpvwb92zkkedC1AewqQ0E9oq/knfj4qQ5rTddWmlUV7ZhJFAFMBCZxQVAgCVivpw3vDrYDemg9zRS+788zK7
bvIPfWM5iH7uJnPVzIgVPwZ4VnV/Ipp26gWDPuRBj7yw1XGgxTIkgnZQRJbVnlkAYWA0LeG+pB/4n/LWjC+4rmw5skb0SBixp65CS8k2A0J0ay785UH9NGCw616yVvPv5XYojpszODeGXWW2ALQ/dh4XNjf5uxeh2/U1qbFW0C9KXsQCau1f ihKWuJ0WN8krlC2yySQ/UFRtBM3kbzDOO7UK68aMvmP8oftNs6iYtlF94+sgf22Jn9cpZigRfPNj0NJuGg79q0QH5IDL1qW2/dxbDpV5ghFSeVp8cvapvfiSv8yVbiy9Djl3RFKoSvygk+fMUt0KkUt/hZqHglSgrS6nra9x9wUfJ6MVDW5U
WJ2WCnXGy0aIxpGUA+7YN3Vl44TeN91L+JbITD09JzXE+UiHG/jgtidfxUcNpG/0LYfl81BTKWZCDgFjdSc2XV67b9fkMJ/6VKJkexvHygMlIhL2IHFRss4/GDSqu88jl3T3X444TqoMVpU1zmtuhVs+35smXaU1BTe7Ja/KyxfiatXSZcbG fEDl9Skf48XwTIkqo4+2jO5NubLZ4WwMhHHefZK7ta2Wt1hdNFntYyzCeUorqFZuJ2Mk2/HgVJKTNuMXKv8yFacwPdXiy3zIcxe/oxiJARI+G3GJFwLghqrHWvp6DxOf7EI37Vnn9B/0U/H+PeP9Aj0JBCn11pS/fTv0Q3aA+PPbCGBZvlmL
SUzGTr+I6xNB490g9tiNFqYLU6fSFLkVdy913ZRPQQrQA8mjcyTi4ztcEjhRrFLUAKzvlb/Liq0s8zYi3bcHeVjhdxv2gX3xgsn9kWvZNTkp8rBtTNnIQxPk1M1GgaylBqrzFuNcYaIGy9pEqc/QtWq2O0RHlCbcAFUQQlhfklH8fEq7lipk Azgu9ESJEGe/349Zd9F9MmpzXmlsu9oomyjcfUzWumNFJvrlTgnPDXN2uVsoklmxuHWzksCFSyurWbb9c5uJKOxJ/PlfEQubYJikaP8x3R/LTG9mujuOWXhzNQ6cABOP71cMFpq+q0SHLcs12wfxzCKp+eudo8wt78EUKGEPxv3CitnAU2aM
Dwfcv/A6puLoGrODdpfw+KjJyg8M4KPhMbWs3uA+LGnrXy1R1dhdIam5H7j2F2TkTlrYF/OVmyTU4xmIkZd98PA5bF69w88mJtx7iIE85G1Xlf/Gr58R8NYl9Tzgz2zFy4cXKLyD+8G/8dsbSZL/azP2dpldDDp45d3EgJE6D//APRZhxeG9 16/OgYxF/LwDq8EC7/6h4QlgJj5qE2AUYKlhAu9B7JAvAKooicEziYj+JUO61jzkaN3qQ7HI52pwctDzPEQogkPcOHrE51kN5x792pm78rHcT/pFGawkSGsuycI8UpCjCRqqvGqSQI+p9dleLwOvIDvrh+x/UpeUxo4Q1keXflS1XO4+c6Lv
yoRQl2WDZpgYjES6DwYGvNoqH4NFlQgsNPY8T/ufJ9qDhfEytWFxoIFah3aJpURq5AwJhsYYlSo68ENWe+hJcXuuM5zokqsQNxk6YstfBnguSXUW9a2F75Ym4FhzWpXpWeeEGdJbmhpqfxeeMq21pE9fJjjxM3ss0tATR1Q+vF6YLDFISZ01 3gP+zNDRQ5HxN6TcVeAtZPP8cKYriJr9JQUGHpVLq950CpjPUpKGPdXtB9+y3/rkiNQAbaSMzyx3w/JkxSSuvhtMH0TrC2t5kBHRgGrh+rWTVNQwqb0UWAUoICICrzDovV8KdgLM4reIXEVNgBFu6dciZjsPEqfcg08VXM5z/Yo2Bv35g5OP
V9OGqSsiXTwIynQIgb/UNfkhLAQbzizu4fOUaWCCAhcnPxe+5YyqPw4cYDkqO2ugb9sNlqx8Cut/Wr+xvaWzie6QrKjdEUSWS5jeYuJiriO2dp2zNPi7tn3BYJg438ahLGMubvcTZPVV280RU8NVOj0y9dLQc/k42+0kEvNCmjHnA6JWLKQz KBmP4QVC3ybqJ5OUnSo4Yp1mYkI1PXM4f/ceXFZDD1ZaIa8kfsadcGf5aTOhPFZmuKE0ApUDtnaQPXmDGFVckAsyu3xWavM8dYUaNfB5Vhjt9rZZQdIA2Hzftyjgj6SvQrHmXuBYQFbX85Q/pR9b8rHN9+Rwnh/vsl1s4U8/I75ad7sykA+P
pXCKYSMLq0XwnIVoQRYz79bZY5/E6x8FZCp3dOJSiDTGbl0VNzwIcmlT7GqzMvq1byi11uG4E9joAzI2blWKVHY+mYn9WPIXuyfSiwTD2t1DaycAOdYka/CTgOWXapXsXFqHA/R54HLusQ5xPdte2XirXaledlMXU3bFiuS0RH6wMEqNe4Eb YcImFD3eC8q7Er3eNL6q3vZ9HP6GHn7Jpj+5jQUA9hE5d453gWBvIzBfCSS9yD8xV7DQyETQUjhXg3DaFnPYjvbeKqqMCYlKOfWm7Rx6szVcXNOxGaf1ggWTxcVnAI+Gvh0D/wxIkmKMJBCSivzYY4YcRKuXX39AskRbgHfvek2GpHVrBRdC
huf/OIWSvhwQ5HgT7juc56FUWHXFr3/MnSMeApqt83pkO74l8TyATaLnllL6Uh4XHO4IXyI+hBh3Bekf1rARwAgm0jfMTq8zFA/kDBV1cvxTtJDWusAc/nUz0LVpD0UVyS6b5U90Reu//LmfgjoJHJvuRZCNl6o2NDfF0CfuSUk0IUQYb0sa pCuyk9iA/y3KIDiWBEr7YpNbHgHiGYyF6kuoNqHTYdBYWONTcWk0B5AvzZ+ZX5l5SRpqzaLdyEOXuonnw2pcUPt/PwoBpjnpt1+HRyJDU6FBVGaUR+wYi0Ujm8OoaWzRudvs5pAjip5NLlsIaBUk+/qGeYygsOkXelgrc195vwDmoVr7Z+AW
2uaW44N89YuUMAFj4GFqKJRTDRUiztOaqr3sxgMCISXrvfWoSJdnLsMqnIVtcgJFtw21X6S9TdlDakLdieBJaCZuhGBEaNPzWVRDXqG4S0SJXLoI+hHS85voM2CXMCGlIRKAd0yQcUG5N/d8BHQ55YEHspedcBGbLk/k7/8DaUoH2h1ZjGZ3 cbuj2HMs5h0Ls56a0QndlEua3T1aiuyYuLL1r/smIlmvaAqebBU9OYa4PRsZTvReUxqNLbctX2F8y+C/ptOkK6f58RXeFIJooxj0T8shAQ2vp3VkQyOCu2PjQZ7HSrlqDYjERTaMk2aqSe+ND9x+kJBGLQjCHVK8H5whpE70w20CV+4hszmE
in1eYyxDhX9/tjoYWvmLdVIEevsDhIy83paNah4Beoa2YMSEhF63Uzayzs2fCftJgh8cBvx53qf5XXzG84MF5mNhkdQHQAaNt5/PfrH8IyYKpUROqyjsBKrPR/liCWdR9oAZfAtF7zrMCXHqzVUB2Bx0dzprPJV93cbHinUaqWwHmKZoonrU YV/8lyecK6kzFIzVDYRRmhOjkHEXJrBHOJOK/6qzQqzryQ/QgjDN4nO97aNaUoRxxOa2vQVGDs3GM1NvEy0Ddmq9D+6xS0BRFItWqqFOVnpruDmkenhWKjNNZK2o+LtyiYzUPlGC9IQE71d1Nieqzoi24XRQ/r6jA+3mugywhWm8b8VqM4CE
l/mpw+KF4NzwCxjVXZXiPWpw/DnpsLPuBTzC62o1waKkRqDCWZrqquamwd2rEBSNtkEerGAYHDStD+okEHNpxsRpmfiQiWneWxQ0CAp39QDPUnXn6wMOxYXmluu9Fby9bMucIyuJ8ZkTUBTIA5noEsfjccpm85KDNkrUq2JQK8bZ1QSXqCEP 5QcmSaLLUCRnSFGpD9FDN1C57dzyChJIZs/kKpOvPIoSzYxJhcI70BMvogLDViGM+DmjSLKQJLAzo0Z862g44Fl5RoVN/MlRIG9vwB9W3xSlwVG+sIrp22MYRYVXfigmgTJXEka5fXGYA+zrIc52oC6PajEFkwTSaUW1gsqFdEFQZTv3vPc+
4LVe1Wi9NKluzkej6Hl0z2+tdKf55y97k8I3l6PH//5RPYphn9Qf4g8/o4Gfo44BYtUqHaEAuhSe30UnPsSZlRe2X5ZIWNJzcRDo9scmMzYsb4gNwcPqIQBwzcpOCV5FRRZd3vwcb73l1q9zabCPPgcg9UuVO/WwI65Cyjy5Rnio59Mir8ph QBI5SYm5s9EEth6j+pteMdrqD/4q5gk+QzOqJUoY+Yg+yZxklIuiOQDc4UqwgaceZQs7ZjISEneabQAQUTDYb4QL8erMVHdv8yN0ytEn1jVjwpkTyosNSAa8WQxsUHMoJLqyaSIsFhqgzGfH1xbECu3BAVPJws6loS/HIPUy04Eb8Kqhayu0
KYwEAwKGtr5jBqOB/chfMzJPdEBkdqWHHIr8RVhvnAzrm/t/spbTMnqznwcwLKHKooMiW2eZiOeWVokdPcD9X0R4pZmiBhwensBo5o1qGkD04AWwUzlReMxGn+sIdBe8EJa32AVqyVx7B+DRbdMzmSv4CUsZkNNw9tRoRP9OS54IANWjKEvm o1ak9WCp1nXD1dUxA4k6IuRL/D2wB8Wpd8XlZVzXu2MhQJ4ocQIRfcm8f3pjwTQUpDxBXkXkGAnfJrXAWDfPY2wkkWvZDG7SKtfYMF0ikU9BjhKQFUZf9iE6/vZXKAq8jnh/aDDacnz9xms+lQHI8GeiTqFHlDO01s6JJ35NJtdciBkRREPd
/wQYKoS3hOuIW06NUL/YfF9YxACnUrP4hSM1M7IuUmBvWbmIUuNpX15PBvThf08Es+cafjtd+WIkWXKaNJTDecdDpFCvnUZHpk483HsCStJLj4UlK9M7dXDsceLRDnRPhc9Kepu2g5UtDs611XbZmJ4rncYuy6VGffNxl1ECxH3nR0Kvjjmt RhyttjsfPCvmtpnNXCTFqH4Z9sOzAKzk7rOZbP09YBlHNagSaD1Hqc3GHP6VIeV18tkH53RiHOSi83tdUbgoVyqkOXfSKCv/ahwVOnPrMMWWbRjcoYPGJwdspEf5EeCCttk8d5HXpySmbUCcFsOGvEcds8B252PreeqIZi5AJeeI0px8MbNV
3rMIBCbgnP84zUJVEMw48QV0HnpvMfnz9SnbZ1VVjAwUXbsSbjNmhyP17xfmpccwmdAa5EHggqGlvOnfOL/JHdROQx0fh1NBeGRAiJ7ai0wRDfT54F2JgNDP9eUKMEIj0Fi/1/T6Bz7N/q0QFj1na/L7cPH3ptqwYXasvZZIvwqdbQ7cHoTk IZsF0Kxin8M38IH3/ql1ooPyaXBXWpQ5fGLQd4AX07HjXYRWAW2bbQjVEB5Xr9tqK6mdHmV6HOjv8ERszsCLixnEcJVDU0RtoXMv25hjzNMzKAxiyfx2FdxxvsZ2VUP34kyfDQqEw/QrCy35DL/ecQfJVSHppIdBEoOaoOHBmcGxqki89dfN
eTuk6UwPX1KuEcRTrjy6Bvav6oq801rpQ7A9yftvOSiHqt+r8Suh3qkOd7i/CZxSIVsVVmUExbgigzaWc1SZekA4kbUw+Y/WgcPAZOhSF9CTf8ScpD12I+1k1evtJLyWe2AH3hDnIS3O46yELJ8EsVmg/XXuSFTt1DGKRs9NQtrU77oQbORE vGR9a8rzNWqDTDKq8J/sL6qnRBfI8dTmScd3D70Xq6LQRpoDJZB4vWxdnzN9pQ6SV6I1nWQnTpgn7lilKwkslxzS6ZpZn4k0Y1C+44Jv+QeXGjZ6VWaXda+n8WbLLbdnd6viTKNf0y5Ze2l0S9AWtE4KoYPDbUfsrauthxVFMXnkwkcks4Gg
mMgQimDzPoKp/eEbyaTalhYcYwTJq/YivCK1IpU5Kh3EwqcuPhMBw41dBh9+GStSyR6R0D7qNluVxUE7+Aa6ElJ9IlzkCpa539ufgBRA4OOOdQxoaIorP9L7IUuUAkb3dTnuWjfjNy+SqGqu9r/W6hipBDRKnLNPbHVB2Pc6rfOY40Apbmu8 jGORkEeESF3Hlo4hEvECHMp/Qp8exrZg5TskGaV68p1D6dViYqfwe9nNNzLKaeDCpEwQ4n8ESDfG/wUS3Fi/ZzaGAqfTw2cmcwbu3UB0pFcrQg0UnCxgIEU9aKPv76sVBlu86AQCLLHRMmwuOlg5iSMZCCmflgsuQ5T5+HmxWJXavQtAr6BD
la96xT1mauKjF9Z/S4JqEvkh14jx/9a5PLQTHXizGmuv0Lc4MHbZ0hPZMY2aHdx7Oqnn1gPfl5KFnzhIQ8Un04oAWu1ytphwCNiP5tcZ4WtgOBBix7yqFvO0NYyppA1NqjAoxv1IyU1cknNqPa40nTSJ7/CBNOuS8WwokWm4nvzMDP6gL4Eg s2ZSUN2S1gfp1CaW00ZB6Tzn6hMCzeMouTlCXZHfwwJV3KcgF9xI+ROdsmvj3qfl2Z8f58tZWlxCg2iIGj+mNcOVLl22xPj3dtzoU/bIyJ/QKvKkXB37Nw2xdpG8JA/05JyefDI2NrbbuHt47L8hEmSF4R9HXpoOJKOvXKCHe7xylKoM2Gr9
q6PPTEfzWgbqOkwbXp52ryf5M9KQy1wS5f28YUzawMHiE3Sui6nwk0/1zSGyUzfaWxNzR87oy5i+lP1xAk7WV4uQRFhud7DjX/IezmMh5//Hjmt482UB/fGa5SUnshl7gmBcqBaDdThmpHPNSrgEqlWt0LBzSNZLf8lEl7BmyZtJdrqouaV2 2al5y+nviCNqsEmpP4XYja2MkUvNFM9Dj8dGvbsJnIosM9OK3e8o7nBXlRKPt16ANzvMu8aFAjNpLLIN4ZhTRA6cu2+ZAwVKQJvMRpHuB7OWlVHjahFsYjA6JR6ZzXzMBMjdPBTUymC1C/KDuqFdvk5zlUnirHTUhL84RtkV3JkKB5ZkmptJ
Sep5W2ZBvvmponiCjU03yPHPCgOq3X1hFJNriHJoFXH8y/cntuREZEF8+N8fJke2oJTsmPekqP2hdEiVWylQ+McQbWB7C44PQrifGjCtCalCfsjW0HJlE3h2XtIbQIMazUYqTnVWqw8IumCWHarj2CJgnGZleosxLzPnNWSb7GJzkGCCI7GL a35XwLxOJ0Qfah/4YIlJ1PbLm2xGYNrG/fhgVzpnDraBHOKaWtR6qooxBIJLNOjsMQn8fURPJN920K+V5dXwtiiJBppqoNtKuNvY0Xm8HWDY4mILWg56MknHTlSVkf057EDFc2eiQdqdq7mqMTJXxgXL4k8PACcvK1B3XA40MVeDGYRg+VSP
ubi++DKdiZlsFcKHKW+a1km7G0WDiHv1Knq4Vpy+3k1Kt14pOVc9Prmsb+iBcuvDLXLVoW86DtxZEMeEob0VP3BE9N9XF1zZB0Ki12JjXXzwLPBlVCKNAW/wT9AHlvAIffxm4dACLLqZ+p8UUHaKnx7hRY+2ifoWw1OEpxTHHi1h/8b0FxBe CDv60+kj5jV5Wn6HS5SVGVhrrQGLjfjGoGFgazZoUcVZANrP1RCT+XdCMFjznsFbLY555fG26SgdJ5kPD9r3WXLXqCShxA8UQnuOIur69e6wM1FLc+vyRY0fwUlUKlz2g15HdFUvs2iKJujGbJVmBoxXDggHLHL3Sq8hneOsH57TjFhSleh5
zk7bHXsihF4RHk4veAEVYWc+QVNF/JTci9d3NkLzOLuDuYjPO/c2ftYKd/+rLIIVy7KfdZHBoauo8r5kKxuaLToyzuDM9vvZw5CeVXlfiB5e356eoiYS4RLdHyAsWi+rS7dAHNmH6MHKkbX1RNKvkdz+OHZk/OqSoyaFmUeGoVxyAacPCROx pgLEyYqqcptWhekEjFHxx2ikjGapvcwf1dRuK9e2U0mlanN8kubA4CAVM3eZklQgHqAFLjtnqPWUdWSqRzQZOg885tl64RIsiRRKxRxXIfHERQeoYTMG1RUNNvQxTmnSSeoCztnCd6f5mfueuNjp+WvhcKDBYPF/+1m45hOaCqUZ1+YNosyf
B8bf7jkOmQJf6gb8OlKZlCiRk5qZOi5zo3dtLPoYifXlFTpNyJ1Cv3mtCi+xwoE2aTd0nZRtow5YMQsZMCw6HfU+5x3xdpFFY1mFaHmjfWqmYjcmdi8pzyB+1lTdRyoN4B+Zf9GAnjohX0P6aKv5IEqBTh/KFnG/6UOvT1176hg+lJVtPmpr /joyq6jCygR7jSx/TsLhuWyKRDZ9YOc/M8cXrZZiuNR6GCeMWDQ5Q56IKhi8lDkCXHHpzp4hdhroGUokx2admdlVfm+47tKmFkbPWcEay0wyt0R80x72vgJsxukyEZe6uMnxlOUqxY0Jf1jyaNNUFMIvK8newd9+eu23svYOgzOllUjcdST8
1auk6fyhHzktpqPjNX/Rf/5X5GwUGc9rvSFRUxwUPjzxAjNwamn8JTN/uxUM/rg8L5EhDzFA3y2KBNPypL+ozP3en8CnYXPBF028wx5wnWu42dIMvli+N4B+9woQ6azz9AMZTLk9Oh1Wj/EURW7tdK0XniH72BjflC37OK2Q5InGMdtuZORh kfeCZa1CtoxBBtdxsKot97y9WF8Z1yo9QDXvSDEBf7QArJzGmeoz+vPavxPhRS0Pj9qW801YBMzOrhzKJ8WYS3Vu77qdV6lWnVTAykwjhOX8DfTptsF66GjD+b/tkCv9W2VHCXaKcSsRyRuOC31b33o+5fPb3qEUI+ZxXjFRW2V9cfYf6hBf
+s+pss0+U8vKn/sWnko8iAHuxgylWRyIwtpV3OXdmEnQT7qFyZU1opSxLfNwLcCBEzv+E+plHps5liyzcucX1SvVxBHxbjujKIdVwGhpepT3BHRBNwi54aqnJsln71V0p2/TAtfA8IfkehfRd6bJcz2GZ+P80kIMTSJcw/Qip77OUb4Hv96E 5WuINDDkjCu9xMfHJITHk4emWbjItSON1cm7BMhNRCa4GIRgszN2o0GCLftfI7g1igb6n2doHHDyrxmX/MPrr5ub3NcuhDidBoiOPu9F9kwJd7FrOaj0aeX6JUdfDBgfUWcIgqRXczcRTmQKVpDDV33EsGCmohO5v/izj9B1YztJ1wMfik/a
HNa2x38wDvHxAzVCAJieZgABw+PSCc+p52vcIx402cfBCZR52HV1WBKkJF1zh58RZPWpXUUqR9JWoEG8jy/9ZxB2aPOW6uNCrZtrHEucsVwtdEalRK9PmwT+xB93m+AXbFcLc6G4GPWAF+BkCmEzs3xlqMrKwnX+II1GVTLKaeK+b12R7rCK 4mwKX/YVI259nT4P7Wyv/OJlDnNED9QO+JKjLiGZ7REv1qBRn4+tSWK56/B52rLcAWqdCfbRdlekUFFkNtVkWwHDOhfvcjQjSVt5QPymMLUBbvoRRB8u0yW92ruuvp3xPiboc8E5cICWOYw8P0xa4WT1BMwg6O5B1UhJMHOWYnMzMWeB+rVm
/UXSaGXwE+Vn9F4Q7nD6bOX+p8Aym2bBBhmq+PNTcJ1Ok7SdHj7lXbdeWQstSpMWYXxSm0BRSjRRRj4pGbb9qlJTxtli2jAyk3IRUphkJJKbMky42SyNXWhbXe9OLsb6F9QSfxtbPBXOUfXn9md7RMJSOkoE2Lh+Lfu9Coqm+WhTcQCJed/B 51AsOVs7v/J6wFs7VEBk4kAFZbgKcMGeNa9e5bbFuqctazPngCahiasRk0/4r2EJkNt49fYrdafHyjcMxmJ6Ydn+ibFrGrr/2Vimvwi77X9qYvpfOYe/IYKnby36L1u791SNZbKF9nrb5rIsAo0MgRZL4F9XjR9TSjyfoPQVObpLRfKSLO01
+qPPhkiJh9pb0Odcr01iZcdYrE75DKEdVLfkbmlbw1ZRsCvKLjY/Y60LwbS8eh8PTftMQz96n00BKwsDFMNGGtVAYHPRxvFpyFJySacz0U2tJtVybTAs0DjKCEjQOQuFruX8s0FH9BAEvrcbgOtXss3xieFgktDdOkfzoaCgsXqLLZwCw43B Asq5GlFemYNIP+qgyE2GGw1+Ism3K8jxiXWNcn2mTROEirLvznbKD/gPI2EM7VAt7s1Lp0qzEiFHrPLXLQEVJuuzq13wDfEYFBKcymiMEq1xvYAmA5INZfMjKK7yZVKXHzI5Et+e2oA6X8+g/kdwxgQ/zyiu5bKdt7/U9vOrtRe3ZQR25ZIz
YhodjxklNHD8TX+dQ0n97zFoxIN4xgyrjkEphkbA4/QbSuxThpQs0QfD3V/PkfJikWa5x+tGpwWd0WQlH0R3j2sCO4DSRSukWFRK1C9xQ05ZlXOa0UDThj8lpVsgz36XCP5dxrbbJRlM53a0Manz3zcW09mvQGLnOSeKxymnlM+cChIcaDaw T1LtOoCzKdTIPGntUAwKCQwfO9lkU6c8UdKLbcVnfyDvwEKGtniNs92h+f7sTBhIym7f+vp+A4/LHif3cuJP+Qvie3ZnsVXr4NlqHYLEaxOZ0MZS8SlBTGuCMju9+WdFz1Tw2p3v87PEcT+OqNAoS1HbBNBWNXa0XwDixS/5IpAjP4hySKql
wqcKSVjkX6eZXcGeNuBtc+CMkaG9vorkWYVuLItfIG/3sDkuh8DRFj9mTeE6CpyXv9/b5QewPTKJ3mul54Lfh1WSSa3SWSlOS9CIEH8kusXqA74s7Hm7+DiQYsjLemYH/mxdKvWow10D0QJw7MQKajxJLzuXBRLkq9D3vEPGbb+m5dCEQekh YEpZRv56UD+Rb+FUWKp6IQUVPe6N0TQkSDyKelRrjf88rxZ8LLCk5izHJT/zhE+zZx6HWUdqWSVu6E0pLk1/8HoBG+iAjMMUNZTCfGv4pmxsRboSWuXLaDvigSsgS+qOe3lUccuKvAKVpsgPivY+4Wguby0b5fsBmEvW+K6qssSoLEXdv3Na
HJ48n6PYTwz3h2uI7Bt3fOhZCUH3I4ORVMC/ZelCdjauJAQf/Jzjl2KYj8g+6Zwy5cdyIzCqiwWSR+WoUgOjB7YMKuUnBL4w3jxaqJGTFWldG/a/yhihEFT9tVpOidcJjk6U9/bPP2uW6p31tMSJG9BLrBGhHqmRZAaIUknXXwqBzcQ8xdCe boK2RdquDgfqXQugOgGxVZq0iYV9puLheFjdnyggKmCkCN1ODL6u2BGOM3j+nZuNjqJG4SRUjouztHO8C78cdt0Ya8WiU2qPKJU3tuoNGY9bW0uhuS7QgcXjsbIhVGyZ55uBtK+htm7iufG6ImKDpfUbgF5mZv7KfzQGNThRu4g6s5PLhzoT
7Tpa3BUmUivK1hFhWmqBPwqu4clk9gO5iGXeZp5vfFP7V6tEDg4SyzH32Ufs5elc43F9UCCxUqicnX4ShypA+I9B/Ge4KuLLHLqGg3zwzw8QpVJ5gsocJqlg272qDFkIV5/4MEOUeaPijlCDMRfBXUhU6AlJ34/AKQ8O2FQi5C4TFWSdtwC0 wUEKBvI2n0IFgI5h/8hvy926BsGP82ArSvQ38RQd9sYj6P4tispm2qRWAOktjQU0zSKbbLoxfSxuVqUCNgWw48eskyJAN7Ah/lOZzuA8ULNTsmbZcvTRuNvgcjD7kL2PKmc0JxGuPKgExv4PIMRqzLIoGSMluykZ7RDMloJbHBX4LChCOOuc
axwLTk0zHoxvgYuyOhN124hX7RR7JzmDtRKF4PrVyBDroSjK5pQ6og4F/v4kJEzFUXan3MGHZT4hHOUJ1+ufXcXHO0UlCQaS9YaCddf/SZkJL9iUdFZ9sycGeE52hLYEXU4GVqxyjeOfEEGfPX4yYJ1U3eKqMCPJfyBUlxuDFaz95Z6IggMU Jv2O1nhB1QmU5/m8bkuyk8m2bFmmMRrCD3fQm2kwpUBLhT9upCZOQDeJnc9nf9hf0mUyo0unwB6RSjagOVoywZz2Wcb5bxa8OnjL7Uk/9nxcAOq4xakaVzzCIEBbuepRJxJtml70NHXCdqjUcW1MlD2ATPcXI+2DkQwWP9uqvrTQkgiNBUno
27AHQL/GT+LpdH5gjCsHt2YqT+ddqfXzwet2RtENVyxa8maaK1jMvD4ut9FUCVAEqSqi2JH26+leiOpHt4yCzM+7rZNTeAH+s0lL0exJHZ1+rlyYOZslaXdXeeVayM9SPbL6f2fu6QUyoUIGVkp6KbgoPL9zijKFGwatvfpz2/t8cBwOIm8L ZcqoMNDvJTRNTFQV/E4MxngPCNahiNJWvLkDqqHHowEHdwoE6NWp/l3AOrKjftnPMLx/863fMEgTJS5nODQQO7TGBBVMpEz+gQqb39877kreBHhvk5EcsvEekH14eg18+GbYEKLLonteRBRu5xS1qFSbi8bAGu3yMlJEVF9h7TgfGwYm6UX7
X/mxRAextAbo5jc6AvpkAhNokm8lBTh786eo372242XCTBT6mzVYNYE8EmQYaDLGhslmLgGNuPFrekMU1ZSDsJXx63tMaAzbSdP49ob5oNUebm7x5WUs06KHsK5urk85qVyo1JUtWWiHLnXPTsyBO0q93Qknvy+OUYlkLZlkqJyG1Ugm6BlR riUXFgiZGOun29T8Q2ahD9s4i/e3QggiEx1cDA7FwfSYo3Y0mvV3mDDoLgw4gzZUnfTofMVXGBturIh+NiXSpzi5dxbUxmM6oDfInXwEWzIFXVMlD3Y6Yv1PWD6/pZISK6i8y/nNOu1+9Z24L2gnXbHgxg29fcCforBZDZCVO3NK5ehnVz5c
7ShGYwo38wAw3TiETE2jOxLyqCa5281F9n/IR8YhJ765yDnh1Ml5sTa9MswHc6gmS2P+vATWGbr37t6WeCcqJSHx8wyP0vzG7qdTEVm6NYgU3WkAWAxHUIFeae2lQJaWC75dVn0+HXSfe8iKriCK29W656sbM33IMSgxNr+sJXxDfYfI/NmR YcLS8CyY+jaLZwK1lsR+xU06iQURsKg+Lwo0NNqm2N+6Vut0eBM6F4XLxsisyafVVIYK1w2J3C294AaiTiYxpPGMP94ZxlUtpdcNJvs9nWyphfNpYcxtcK6OZtoEt4HUjVsswRnwvavTmD+8HHOzPdw3jEk1dJ+P8pK4zaTArLUTAP74FZTC
ara682qYkPlku0NwZWz9GI395oToV/ejZR2+sekHttZ0x29+vYX4CKF3jD+mc2JOBMaO0djYtuuum/AyRMAIKqNJNygaNt/M14PswAduHYJImwmObQljzwL1o2sArHh5oPHbbULYlJ2JqgxZQ6YJVZ7DNp9gAGVepR4O86eKgaoI34PvqMGB Nnm/ov4eJNKGegsSsLTHXS397cLyzvWN9blUFkinITkHbcnYjEta1oWHqqboKOt+miV18ntQ9R8Zpu3Um8yoE3Ryt60SaDKkznO0Zgu6lRJQkEz8yQoW8sxuT0GtTiQKEdEQd43JXImxzxahPVP0xzghhmbArwwFY9dk2gcpV3v0Pum0iuER
rsbJAf5Se3smxgvhw1ZHLno14rwlGKgFI144yoYlm8/LhXWJMBNddjzGY2Of5AiaHKBRR76AoQGT2+7LIqiyB71N/vzoj+4PgTGnT1cKMO+vpZ0AUOrgTFmHVyADP7JJUzUQ6wXP4oWKzUzw1IgOmw2bKSp/Q5Y/XntUfXVa0P4qWRoOqdoj zm3IPJDaHLx2u4JOFmDeZ2NV//QeK2k8M1CADDL8lRhuEaMJpVRfl0stlH5dkHJfbhTiG+WDcsCYkVAvbF0Z7qUWyx69lyCZGdwDxKIAJYsdiwr3HT6Z5FQaKxb3JqmluQGY1kBPsNcxQJK4R4KQ1A8kaTF866/yB1c3YQpqcYJN87Z9hY3/
eQCadSKCadxMz6nuhpS+j2DYUIJXZI1lzOUHCsQpV+YT3tLDd5xpmQEfMTrRFkJyTGzrrgFOuQgFPwozfaXR6OyvF4l+Q10h3T9L9kPsqLCDFGuByB687djAtOgD9X04RiCpsydpBGGZwPwQUvNVB27f13z4nK+KUWzHN6xNy7wCsZQDRnXo YDwOsFmZIEYjR8sm54nq+8O0ujtnXhNVcerQW9v2pcdZWEJwlYvxAWhJi3li9CZy2mnmMi4QtlqoUk/boST0jKE1RgCZ6J3w38zhTvIlvTSB69BxW1c+bqeAa+dsD6PO1y41F8pCLlQrKx6BZpZHZEg2qX4OLe8mm2cPdlZ44PaeR0OLE0zk
KgihK0h3s/2cMOwwfs0j0+DQDcO7o3UJ7ASbnzu107ymgsffF71elvrqYue3u8XG74o7SKnzI1oi+1Hv6fI8lnHf6otWV1k+139Tzl49CmGsNA5dZ55EqsTzUwTVlvhLrxXFa5x+o0biKc0vvCoDYPeGEY78Q+umaiscdwT5vqeGXNPqV8lc 5XYiIA/4/0YHGhxrbjdzXxkFQE1YcwtaxGAglS7p5RSc53aPzrFNrbjles0J0US0kyUChQY4VqXwcoICJXvmdfw5bYwEHNANFqVsyDRso1/+B2MyV7zncsRwn6xOv5lRNQzi1iIKxrxI7bFOqvAa2Cz7saAsOJD4rsXvJ1fHw/mflrtrtcWq
ROMYLeJo1RT/qEMSGI5ZKOK9UaZNS65PHggFseFTlJ/fR/w/h0xPKU0SGT3Uy1YWfziTPTnFm5TlVIq7G6lOpvo+Y1DTvcFsQXGCyNWSrsvIy52MwsNkkR/VE2Oxx8eFn41tRDwqPD6XyFqMAi0bOakKialwAAaylAYWLAgyLd3yxxGf7AgA 7R9htPt732b4SgIW7DbgZEnJWOMWZYIBb00/iHPU/Wa7bJjLq6I62ZnseV7X8NGQCaYnhnHOCjimjVHmRuix2xZ2XFqE+uBSRsgiSgc1mGf3l12C2B2MMu1L+5Y5V2XWcQXM7Qrhznhde81SavGDSNsNjRoNI07gNPQNEeVJcAfwZTzDvdap
AAAAEWVo=. o+1EYLkd5ynW66Nzx9qn5U7ssepkhicoz5JnHtihE+HxAy/UxcP0Br4XqxwGJqXW3CTXLBImrObgtWsCnaYKxDcylksQt/mzpRe/nc+yGrDfVRImj0K5ZVv8poCzbbbpI6cGVPEjU1VbWV6hH/YksMZWwIKuXXd7QWwDyJjQbNzqQ/DVkKI3
\ No newline at end of file PWRh7ws38aWtAEB5K0iZXth+ibonyOsCVV3JtiFD9gYjQJlHu+OWy5ZRo+YFxF/cIsMgwsjLeCZmeSGarSuTQqIaeTdMeHH8nonco7eS/DLVDi26lc5i7d2c2KSdJTzwZcaVNLNYqEd67IozwO//moUSOtegn+/mPJWduwQw9Gp+0oFaegZr
Ac565LCJIMB64s7GzJ+Jfb3nT5bXoX8iaoiiBHvdexR2J0CU0CzXmeFimpyIYJw/de7qbZKA+O86iy1JxSKud9sUX6gAAAADWR8wNzkus9wABmqgBgY0CV6SXB7HEZ/sCAAAAAARZWg==.
\ No newline at end of file
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment