diff --git a/.gitignore b/.gitignore
index a26571ec756e050af10a9551d0287c675e5a6f80..82365f31cf080ed74078017ddc48fcc4416fc0b9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -9,21 +9,15 @@ cache.db
 *.artifacts.pkl
 .coveragerc
 *_tests_complete_grade.py
+tmp.txt
+tmp.zip
 # Lock file. DISABLE checking with gitlab (and syncing), so you *wnat* this on your computer, but *not* on the students computer.
 **/unitgrade_data/dont_check_remote.lock
+cp/ex03/simple_function.py
+cp/tests/unitgrade_data/Week01Dummy.pkl
+cp/tests/unitgrade_data/Week01Palindrome.pkl
 
 ######################## Comment these out upon release. #############################
-cp/ex03
-cp/ex04
-cp/ex05
-cp/ex06
-cp/ex07
-cp/ex08
-cp/ex09
-cp/ex10
-cp/ex11
-cp/ex12
-cp/ex13
 cp/exam
 #cp/project1
 cp/project2
@@ -32,3 +26,12 @@ cp/project4
 cp/project5
 cp/project6
 cp/tests/tests_week01.py
+*04*
+*05*
+*06*
+*07*
+*08*
+*09*
+*10*
+*11*
+*12*
diff --git a/cp/ex03/__init__.py b/cp/ex03/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..2eb2a28773da65c74f1d40b5ea20c4dbdc83b382
--- /dev/null
+++ b/cp/ex03/__init__.py
@@ -0,0 +1 @@
+"""Exercises for week 3."""
diff --git a/cp/ex03/ackermann.py b/cp/ex03/ackermann.py
new file mode 100644
index 0000000000000000000000000000000000000000..507cfd1841c3f3a416fc13b8464b8c9ea90639bc
--- /dev/null
+++ b/cp/ex03/ackermann.py
@@ -0,0 +1,12 @@
+"""Exercise 3.10: Ackermann's function."""
+
+def ackermann(m:int, n:int):
+    """Compute the Ackermann's function :math:`A(m, n)`.
+
+    Your implementation should use recursion and not loops.
+
+    :param m: the variable m.
+    :param n: the variable n.
+    :return: the computed value :math:`A(m,n)`.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/bac_calculator.py b/cp/ex03/bac_calculator.py
new file mode 100644
index 0000000000000000000000000000000000000000..f181296ca90751408bc3efcc1679400425b7a0b3
--- /dev/null
+++ b/cp/ex03/bac_calculator.py
@@ -0,0 +1,12 @@
+"""Exercise 3.6: BAC Calculator."""
+
+def bac_calculator(alcohol_consumed: float, weight: float, gender: str, time: float) -> float:
+    """Calculate the blood alcohol concentration based on the alcohol consumed, body weight, and time since consumption.
+    
+    :param alcohol_consumed: The total amount of alcohol consumed in grams (float)
+    :param weight: The person's body weight in kilograms (float)
+    :param gender: The person's gender, which must be a string of either "male" or "female" (str)
+    :param time: The time elapsed since alcohol consumption in hours (float)
+    :return: The calculated blood alcohol concentration (BAC) as a float value.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/bisect.py b/cp/ex03/bisect.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f56037453e5519c7392fb7824067157ff98a30a
--- /dev/null
+++ b/cp/ex03/bisect.py
@@ -0,0 +1,38 @@
+"""Problems for the Bisection project in week 3."""
+import math
+
+def f(x : float) -> float:
+    r"""Find the roots of this function.
+
+    You should implement the function :math:`f(x)` here. It is defined as:
+
+    .. math::
+
+        f(x) = \sin(3\cos(\frac{1}{2} x^2))
+
+    :param x: The value to evaluate the function in :math:`x`
+    :return: :math:`f(x)`.
+    """
+    Compute f(x) here.
+    # TODO: Code has been removed from here.
+
+
+def is_there_a_root(a : float, b : float) -> bool:
+    """Return ``True`` if we are guaranteed there is a root of ``f`` in the interval :math:`[a, b]`.
+
+    :param a: Lowest x-value to consider
+    :param b: Highest x-value to consider
+    :return: ``True`` if we are guaranteed there is a root otherwise ``False``.
+    """
+    # TODO: Code has been removed from here. 
+
+def bisect(xmin : float, xmax : float, delta : float) -> float:
+    """Find a candidate root within ``xmin`` and ``xmax`` within the given tolerance.
+
+    :param xmin: The minimum x-value to consider
+    :param xmax: The maximum x-value to consider
+    :param delta: The tolerance.
+    :return: The first value :math:`x` which is within ``delta`` distance of a root according to the bisection algorithm
+    """
+    # TODO: Code has been removed from here. 
+
diff --git a/cp/ex03/body_temperature.py b/cp/ex03/body_temperature.py
new file mode 100644
index 0000000000000000000000000000000000000000..725e783bc3f585cf1212588310699547a5712dca
--- /dev/null
+++ b/cp/ex03/body_temperature.py
@@ -0,0 +1,9 @@
+"""Exercise 3.4: Body Temperature."""
+
+def body_temperature(temperature):
+    """Calculate the body's response based on the given temperature.
+    
+    :param temperature: The temperature in degrees Celsius.
+    :return: The body's response as a string.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/compare_numbers.py b/cp/ex03/compare_numbers.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b6fd2d3bb062d2dfd4d5a14f99204457bf79adf
--- /dev/null
+++ b/cp/ex03/compare_numbers.py
@@ -0,0 +1,10 @@
+"""Exercise 3.5: Compare numbers."""
+
+def compare_numbers(first_number:int, second_number:int) -> str:
+    """Return a string based on which number has the greatest numerical value.
+
+    :param first_number: first number.
+    :param second_number: second number.
+    :return: string stating which number is the greatest.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/exponential.py b/cp/ex03/exponential.py
new file mode 100644
index 0000000000000000000000000000000000000000..f08265374a013a3d1e76aada84fd257dd4aa3812
--- /dev/null
+++ b/cp/ex03/exponential.py
@@ -0,0 +1,12 @@
+"""Exercise 3.9: Exponential function."""
+
+def exponential(x : float, n : int) -> float:
+    """Compute the exponential :math:`x^n` using recursion.
+
+    First focus on the case where :math:`n=0`, then :math:`n > 0` and finally :math:`n < 0`.
+
+    :param x: the base number :math:`x`.
+    :param n: the power :math:`n`.
+    :return: the computed value.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/heart_attack.py b/cp/ex03/heart_attack.py
new file mode 100644
index 0000000000000000000000000000000000000000..f60ff1694b0cfa27bc1c399c1c60a271ce058268
--- /dev/null
+++ b/cp/ex03/heart_attack.py
@@ -0,0 +1,11 @@
+"""Exercise 3.8: Heart attack."""
+
+def heart_attack(age:int, weight:int, smoker:bool) -> str:
+    """Return a string indicating the risk of a person for having heart attack.
+
+    :param age: The age of the person.
+    :param weight: The weight of the person in kilograms.
+    :param smoker: Does the person smoke cigarettes?
+    :return: A string, either "low" or "high", indicating the risk for having heart attack.
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/ex03/solar_panel.py b/cp/ex03/solar_panel.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c3fbe0c9da19d1270e95e7143780b3fece523dd
--- /dev/null
+++ b/cp/ex03/solar_panel.py
@@ -0,0 +1,11 @@
+"""Exercise 3.7: Solar panel."""
+
+def solar_panel(move : bool, swap : bool, hot : bool, empty : bool):
+    """Print out whether it is a good idea to install solar panels on an object with the given properties.
+
+    :param move: does the object move around?
+    :param swap: does the object allow swapping or recharging battery?
+    :param hot: is the object hot to the touch when it is running?
+    :param empty: are there other empty places near the object?
+    """
+    # TODO: Code has been removed from here. 
diff --git a/cp/project0/project0_grade.py b/cp/project0/project0_grade.py
index 62b1eaf97826dd89d87ea6a72ca7914db660c847..16c12c784e044274753c931e6041280aa8efa6e6 100644
--- a/cp/project0/project0_grade.py
+++ b/cp/project0/project0_grade.py
@@ -1,4 +1,4 @@
 # cp/project0/project0_tests.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
-exec(bz2.decompress(base64.b64decode('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8eT1ZuL4GY7Z8GHwacjCUy4aILxsbzIsEIVcD5Xtk2KggVucsTUypbG+g3sILsiM61lCMGxRUgNjheo7XL1MtJUe15NW25696qN/KgH9Wd+19Hudns1saBJZBlMxBsUFI63HbIzuQE+KgoSXWjYkNUwK4y3qd8+LtnWs4YoVO1JM06mkx87HGo+Q02xCG2MvgbYtE8x5YE056b7nVcofbIHQtC0CW6NzrHZWtpjZnErODp+GNN2OaxzFNcYjFczibrgknZzAwHlqZBHBPeVd/IyMy25zZrlR1KqjeOpk3xyuzmupTOmVTeZYZSO5G1LBckjG+BLSQ8SYN6PrM/ievXnXXWzorzO1pMTTPlRcR4ChUeZGRu0SvuxdRgvR10q8xBapHcvZZYrRxfwZBT6ZEllZY8A2KyiRc1ZU8nbsgWKrHghOo12xqh00dLRyVlBEb++kV2rlBcg3QRTwBzw0g6S12DFdiyEZCkgSLiKbrKjlZvctaW+8C5J/vNS/ejEjDg52Gz0K3qWzekOPeZwmURo7sYJzBNT1ccQkTO+m6U5C4Vvrduczhhfw7EshrbsDqyJnU9DbPSVIvy4ab4W7ExTIwm5VteRZh1JkDO4C5Zo51gd1SJ0Nine0B8KPm9l3cZMGlNePSRkwizKGxsInj5Y4mqaM0rA7GKa6DpOt3dZBYQXwxwNXKzfhFmIyD4dnQN1Bw3m8L4Mu1OYFbCMuD8l0TU1tm8jji2hGLwSn24TrmY1rLDCTmunwPWt58d712xZnc7Cs6wHFkutfUOtTjekCVwmiChPC8y5jBkIVrFR6u2G2BnzaexlSxrfXnSxisjIKwieWg8TmUBNId7p1pOlJuI30w2apauZQnDDhRYiLtMKtRltzmEFDMikpRtFqkkDQF4Kwi1EZNOtQq1zitWVJ5mQ+vU7zitWw84nn09WjiuOdWbR45W5MddaWC7xWNd9GmigrzNGOJkYG+Nwft7SRDor2IkDvXEdIMTCWRI5ouFGJu6qWJxmOUco5xN/zzefHDXIpPqxfGezxnoy5mc9jnxbCJ/IhpU4zM641xyl4oLhMm5sVN6lPkjdg9ixSMxGbLqVBxyouEhygiZwKQUpYyVER2MjCj3KlMDlrKUzfczRmsHYq8Mm0IoesfRYXdgdne7q1iQ3aXJnaU+mAy63kgzOyISW/LLrRezn6VxXYcMTHeDnFNz9afVMXM/GOUHYjuOPFGhXK3y55oz68pLcaubjKVWwllt3cLkldUVFIPHaIOEu053n/o7Ybrz2n02m54G4rsIuRPocObGL5t1nVQw1egeEi2ePe3OcxhOYxbVNYRvMdDeSEYOVLIqaYFOswBxCGQiYbjBottAtsesUBmyPqH6hfI3E5L3I8jgPW//S58zZjWrAdf16HSn7FXo797Mz/m/S5rbzrz7PVXnpziKIP0I/Z8z69w4lOsLFpaPlCH3T4JH4YlEI6MiKZn00dmwR8a6523kmwkckdxjNACZ49Z/4f7UubukhOEGTtMUdvKzdWDtQlKqO2+C7eG+5dDFXUcpIh8W6sGN1VNAhBSVBfeM8K0YgaVKvL2ZJd3xeDe81T8VOB5ZPlHGHiJ85Eo9O973xPgVdafX5aSnYjifnP/iNca+/OkWpq3l+h92cvrlbOwq8uUtzyOaOry6o0EeerksHyuqwOYz/HjhPUVK9cnu7v2WwiRkLLDswfrNt+kr3xxcicSlR33X4xln113zzxfdhnfPf8dtKZ883iWRYuOJUh5qQs1rOeEivzPtBDntTe6Y+ab0Q4cwwMWDWZ4eEvUdb7+4du1/t7Jzff6FJZ202DfzKEHV/XP2cb/p8PL33MdPv5cSWj79+kKC702Xp04yytXsv5de29ctOoq7BN32xjNYZHeJIWbpDh0eIfHgiEoLERMArJw44uy89czP3KVApAQgpsYbE1SRUVUj+NjVc2MIjBC4NsKTdAf5P87owgLxogOMqx6IDTVoUMXUwLBVKKl96cetSk96FPX/N4XNWeC001pPuUW81FaFpPX9unLTZfN8Qsret10/u2PwmdnA27u/t6ztZVJ5l0xO7uotiXUsWwoaK9Q5xQKmKpmWy6FrBQFiYaMEBoQRjaDgCxP3d8FP56+ew+kFJeKu2QqwdrI9DRJhDJ/uLwZJdoesxJUoVP3Lks1F5CC0Uks4hWLplo/JtxWPKhKT/pYwRrY8CadrVWwV4+osqH7udVZl8ORpMHoxhoFk4gUrr+HbfRvxNz/0VGiqVUUFSK80lQqlahJFST8qCwRYJJRQJNn46Sx7/yVSaJQomNTVRR8T5Q7ZMpgg/rVlJCF1AeJR8x5P3OJYwKDCP4lVCL5fR8Xl/R/kJ4zYec+Ssa+K+CjygFYG+wuRAGrffqPtksYKuzMmj78/kOJ4/L7OCqiKqqKiTtYQ4PHfdKeXv4EvwzdMRRYA23x8u1T31tUla/ZphDHTvbsMChs/aqKQVYfdEJzn3RXLxVzu65O7cndmVxm24VfS543KZW+hRrxk14//d0eF3cIoZzwPky+BUxdEN6hR0GMMhkxgsQr3/rHHGQwVwjUTHhQGIRtFvBJAUKipNsVuj6nZPRl6/ydvl9c7CBpcuqzo5IFYVM8OqlEMNpt+r+Ve7wMZzH/3nV0pcrz/v4stUctDeDdy40xxg1Q1TRBGy7t2PVWYIoyLHinCNJxJnMslVsaSpqk9/vMaQfl5d2NNPOiVxDLeLufCZ6dzvDXzu12zxDQnrMeEzeBPF258+cSnr2av99DjrcY9KnMt4eI+VM3556zecwSnLa4cxJIlJ3tk02b9QUFzgVV5o+6Gkfw1+q5+6dtZREGmo4m3TGJiCiZoTOyDH1HgirZW328VFyl5e0l9xX21o5LprQYy3nvgyhIWXOxe+sc84MCOMXo0ux6ApQTOVKTyTAicsv6yYxIm7XROkEEDfj3RsWebqzmZeSupBQW8ycjgFBDl4nMMId3aUnT2Ia1Lj64JbXx8jyLwURMyCjQNHR2CZOfVZgzuoMICON3Q5VH1KvDGZgST5hWFEVDnG64DIjyBlxiG9rZum7rj+xpTNHSKTsNX0K/TFSe56FfnS866RAo4uScnAVY3mvibFq4atczJFifQRXMMgR798MuRcndwNlkr4BQi6BxDQ0xUE5P99AiQnBzWyXkYo4WBgxlsc5v5I/9Vzgy2dUfer56vkSNCFvO0tybLGzuCT7rQSTS6KIRJzFYwm7DBdyGLar+bt4/VjAjsmuuOui8GEzqaM3M3WCu9mEMpmkDPOtfKrT39abxd2TVlO8x3u8iTg/vR7MRMuLHzXPP3nHnvo1V67YMXSSLq+UIyTvkzjwIPZnAtWw82yUxHykx7xfOuK49ubLGq44Ij6yIJMjR7xUr9/r/u+zGhv0w21mOqFFCrH8py98pxKFeAlKqglPk8bkdVXJ7VhfheCF2r3Z3+mRuseqfrmS3eb+qUtSWkk79d5KScl2QSKvdUoKY/sXlfCd5/RGL4S5S6pumZfiUqk1VX56RzXZl5RN3slfOco/I0S4yr3aDa1Xzx9ctw64Sq0HyGH6LI8cUdsyx38rP3U3UjlD4LTr3czTPf1PDpFkOgEgorQn/II0WrrfwKow9KOU9F4rnaeY/d3fbn0Yg5U2Zbjrx6z8ndp1NuL9EQPKxIxKEdEt78ZYGbkuxPC5CzFJZLMVDaZlJbQd9kjttCVZtdtffxi212X3I2tYa/G46FydjLOWfdu3Zz0zwMFuPGDeCq1J0JKQm4LN5AMpQYMMNfb5XpYM0zb/kurSh3kPpGPmWndTp1V7c3wY5COJh1wzdfJyDk5IwdrIaKONht0wN+chUKWczUpCojsw9sWR8k/a/HF745SlTIfKIjKRgRkpL9fjShPGKZTmpSe+nt6TmLQo7ujlhWe6j01E4pg5Oct4Jiz7RsFS6VzRnGO7fM8mZaMEGyTxObx2S3xzw3hmcxvv8N73smUtvE6nSFSxDSsq2xXO1hapuSP0Uy0K4YzzB5Jkf+azgWD5yql0fOeX+HbE836vsff7378teyNd1IXOmzvSb//MandamMiEsXe1XSVeEZcdbS59kdM9sc5os2Kzs8omqTnLlglkcJnEUlrKPot7EM9fzcb4Y0ufD4b9FkylP7JYywo9Hfc5osj1601xpZG6zluWcfVg4TR6Y5d0jpXFN5r56xmSSFV7ufO2NOdZdE64Sg9sufjiTzTzw7vvyIpNfYvpsWvnPsvv14WklfdY6d0om/GhhPw8nlN97VfWHu+0yktIbZFrPvo+5SwE5wyodalPRd6OGXstvnfvwst3nQ7SvGhVQtxg9WlVRW8ED9Lbp9Lzljb6NsK8ca87+Xy7/jvvNjVL8fslpGPOO25IPp018i9aPlV7fh06SPS1ttEE/h+1L7ts47J9rx5IeUX7s49zctohIVBZPmQ6UsYNIla2NZ7a1rLpSTLyxYich3LTUzq7EXXvhzMp/TeT3rHa5nr4ZvCuT6l6+6vaUdss4omZRP252y67FDNFkaOSk7pAkEq9vbBQ+zsbjx6jba2bt9oNR2YglzP1Egb7vurU9ZDhxhOc2S6YyExV3+S6oaCJIhkQSRhAPDx04S5fOsTS4khwinSfZu+/Fgqw3SQj+/IDERIToYw4jDsHZuicqJmpb5vCtvo9JvXJR5YvUVJjkCcKorN3xoSSTHxw5NZYCbdJdd548lij/lLT39WcXHNfj/1g4Uo+L7zj1tdFk/HG3mmbVSeu7Xu9Sxxn0V8MMZNSrzbJMsnj1ppT4VYJS4WKdhPiEqaHtyCVDUnqU6Xt9O91jfAx3OPaWrSF1bFTW9upStB9ffliTVtJShlkQzXFSdPf9HE403W64dJlknTrciDF40qxVSDsJWhdpHdxzn4cC0WBx2N51+PLQojbc8Ca8XPDhnUywfculoO6X0QXzpN9Ms5FEfN11XOOCc4Ea7t144zVXORDmRJ9KjsbTKmoS20h5qREHIsGNKZ0fq00kS7rho2+Zpg9Gt9E52YZUwTYHVwaROe25ypeHxwcntB02mVKThze0EpoVr1IJNjr0kE0yZidWdtCuMLBxHDstmu/xqZYXI3Lpw5dLILGNWRLWZBLyfGF9O+xcdc9C3gXDo12zmY3ce2hnKZjhy8+5V24U7r4Ge/TrP0nggrth6uDyyyIZvFGRnwieU4OPPhn3MHfbTndY45krFtiRR2vQrD5HCGIQQO+ng/K7BpnVp88yAjt52uTE/cVaTdXZcc28d8qGKMEUu4Ypt6aSJt223YE4vTlv8KNmcOHKR1+z2gmQMgf7qNp7KuFiprLBD/MhRAbP4sn43TozY9SZkJDZC6ibX/HI/CrdF0kB5dxyN5IoI6q7fI7jUCXbaLBZGEDbGnpex1WDEQ9PfhTQVoyjwKKRL4b5UkfxwlKU3uLwmOR7xPs/xWRJcX1tjiYFHlj9N6uQPwIRxr9j/KP7lv0F2KBtVX9BtronvD+Lr0rPK9KLmYJES3ctUvszlexnjns4Y2hvgNSSZ8JrD3Ufh0HLMcrA+aYwwdmshvtTRZSQk6Mrd+pZtdO2UYtHyb6UvoEhMfb9obHXjoHARvfqIyHikxI4Ca1/iTzOqb6aXR7cebevhmi3Hm/ZKmb08u+vSWGMSIxmisiMF44SKp7iecimtCdJ4XrK61xsYpq1Slar0fH1SvknpgsWjP2PL0xMs9fOs8lyOfo1nzMqxX72oKKqyFHM5I95Py+vTpBZWGfi0oR/i0qqwWLMW71tMmHX18dVbDBhSmkaSLX79to1DFKOLJMmKoEtAalmoAYERvBtlOllNIMQJWEVlsAMpwXQtsY4Es8O+amoQvqTaeIMKONX9WmlgPOl1/5moDuHRfE2RQhEee9bCsZsqQE6saTmTmF6F7EgxLhf/Hq9upXEAE3/AZA6VehdzR3msyNgZYjAwo0YDQBcgwOwfdFfE1hufoTBvrx9HgKMD1tTQ1P16zESIXV3DucB6CVjJkaWJ9G0ggbqRvGJBozVP8O06ohikIEPRWVru51WrPkbYYPDMu0++mTZtZMSoGndVyFxqM8Iuwsd9JSGAdhvCnSOThnUgQkD0aTSHhjiMdxrtzu8NZviqGUB6nPVQRweenYcUQQ1Ysn72NY74NKAuctJRpkvAqNdri2DJi7f9Dnc77+dLCd5RquEwyriG6aaL1cqzGmsTSXstu+ieCoyZAmTAsAoiR4dRGIjZycdnVF0STQjx55RxWaFjZmYasqDe8MMfO9riXXphW08zujSFQoYywzQJCFUpBkHPrIax0YtDIzMC5JuvBmBzFVLzFEl4BMidvp68aaQa38jBgZLKlA0dXJ4cppoCIFIRsIKJIsKBG256iMw+Zqcm7xjrUzkdugYH3A3IzDT8hj1HAD7YoEBMji2DZkgyLkw6pDbT4VCe+c+5sihP5bacdzGmRiFf5l6HANAoH7Q9DI03DYt+Zutf5HZI/V76H8lLtPT8sf3JRWUoWBWWKCVJJSZYRebSXzu7JMgvh6eWjR+yrhR7+ZTJBwn6To6mCiG8YKSKRT/IhKQgjARW0bbRWMTNRtgoDQarJasaTBVb+mttctijYiqxijUWiv9ytyt6a5WNSWxqvSrmi5typtUxqimG0alDSFUbYqywBEBSa9Ntj2aZ0hSENkpkEZFWxF8Xq88tsUaKNBRV6VzGMmosaiTUVGjUUlAWxsVaNzWt8lrxtESVEKhIZxail4uI7ggXPHPPEejnhwdkE/ZNHIoDR+TlC0D9UZACjU+XnOsrd+n2ei1T2NG/Cl9pysfS9cL++XkWtTWWVD7XHju/Gd080sqRD4M/5d+T9Prt+ZwRpWpa0YBZlGQhCiNIu7pMAwRGySTKaUWJkyZA0zRMslMyGmGUyIJpGgGSGhDRZElMohK1JQWYqCkwSRoyitQYGKDLM0DSIRoUJFgQrUpAMKQIpiRiCMQQhoSovJcKLJoTAxkwsbECVqWa1MYkghlKImEil+NXIBQXpzTLnJBkYkNamhk2SSRMQNAiiKGSmYkhmaZGSiy7tcQmkq0EjCMmSZhkUlJpWoNkmkSU1qYUhMjJIfa3SL466BKSMZBoymaJgYZpGQVqRpmY018d0NkUxiTBFMkkzMZMwISZTEpNtUzKTAvLrrIBBmSkYaSSTBRjIMClEZIIxRJMmJTBJspCBSQEjMVMTu4wygIjSGZSoUokMihCJ8OgIDRMmMoMSYAjQpil110kmZJISGhKGbRYzYozWoDQYFmSZETQE2JGrUYj4v1+34mr8v3N8XuwIvdjvquXj3XwvS4+Z6za1iKchKYyIKQwxlwaxzDvDD/tz1+Itu7rj7JlspxBn9f7VYJYOYqPCTkZRnhemUk4T7/Zm2v6w+Ries9oiR8CRyAkPfqfqRoSKtMkIFaiYSxCTTEaQJmlFIJaAmRtUsCJYhEQrUKSSZJAaMGRGTFkMaSUmMlEwRkKQwChlKBaZRjP3q/P52ShUMlKTCMSJqEIiRpCSWGZIkpJpCGI0xJIAGRIhgFEiwmU0vrv1+vJNJkNjY2qBpkSJeurkUiEhKBnO1qRpgohMz+r3IUywMgzMzE8ckMiKYSk2SJi2oUpkxtUxCikmTSERIkSDYZJmkSZlkZIyUMAZTMyTKZlCQRK7uUk21CtTDESEhSiRljUjCd1diSbEmnx9V55IYVJlv1XSZkpGE0QZkQfHdKCWSRB883ZFEHy7ckr4cu7qTRoIjMzlcoZoMgwYigEUw+O7DBYCIibBo0hRKlJKa1KKCiRWpDCMxmhBKJ53CGBJkkEZBDKUAjWoSaKTJRCSUiDJEWmkSlGSgUBpIwpKG1QgkZ4urU0oAUzRcuTCBYiD4uZL6b719F4u3q+IyAJd3Tr1Ewkc3DTp5efoJ829GzsDbYeR07TcXKVcuyPykwYY1PNcXdbL6Aq3tyfZRY7+7riUiKuVyW1jke3X7WpTGvTbJ0DOJutQlm+F+geQNkgeAJWiXBhx4OVr3gAul5bWiXNTKmELBDObKFThbGWhWHPSTLYpZe1cNZnvADiB4DLh6jd5fbZC/fay5zrIcH2e8ALwZeT3gA4aDsN86Ou6+6ri1q7zUK4jMyTrjJ94AS+kW8EMie10oiDIQ2CEDystKq8p7sGGTGpwLtBw5xox8HVG3dFdrGZYTKNbRGy9xB0W4GJox7NgrSKlOiKZeW2jXqru9jdB6b0VNXR7GqFd2ZCtw0opdbU2buXuTDG403goXmLMN7plpp4T9WjdWZMV6HY0/ct+rCF9pPw1aoLgcQtA1X1C7lR61omQ7mmzm6S7ENA7m1uXquMSUq5XYgq2Nj5NjutTCK3p0uwqI+y5LwbWoOVxuZtimLlZujSQ9GOQtUD8ULuVYndUXSXKp2qVmayLzc59bd+8AITHuVszdHbCikVT0mJCks3KtvaB1m82vO2EjjbvIyculcuwxlXdYhFuYw59H99W/budb+iU16I6zq/aH59+d17359Nue8AIxeXlVdJEvBWsZkqiq26lU/zdPo+s7XIKUsNztN4QxfKmCGIEw7dwoXBDYdsmXtuAzq0bd0wDHSd1QKc177wAsp3nZpMv2528XeDe33gBV5K3xy5dQOPbreRt6i+WBynkVZoHgN6GSjURVhWaiz7avNr76ra00uz6wVFeqdI0NgV5VAiXDqly5m+zYk0pt/RSRe8AMfAeAW1XwmF4hS+h29y4SHguLKU8zVtWW+ZRsRi8x3dV2Ho742MCj9wOaNtq+yo2aiZyGGrnDr8PAHA9NdWh5SgvAjJ28LYRA09lp1Rkh94AZdyTBcey8481Ibqu3LwK93o+NhpnlaGk1mBvRl4dGe8AFdLtGlRA7tXHXnWdz26Eq5kZ1LOIqFXlVT13W2lSByW694AH3gBljFzWCbcnN1he5HgOXNyhjN8ae8r1qK9rr2dxlWVQQVbS2iQjzR3V+/aGjB99S0MpND5msPUfhhsTtwohl1lEMrRovYwy70ThqruEk10tCWZU4pZTl5xwb1XRgmVdSXo3KGZWXEH5JhrPeADh4VTO0smYmuRsVXcxvBVvQm8wVyJqLEMo+8AEOW102UWJsG9W9ox7VA7n5YfdwdClg5fOjUBoJG6uMD7BV2Ls+8AHWtW39uvgO28oRvZYKPU4VLs3a3MpsqxDfwwcdQecaHSxYb+lWfnWBMZ8HQRH8BfFxITdiaMgP12ffAwb91pdneo6Fi63R55z8kjzgvFdZtt9mazcmIUboSrdm83HvC8WXWmih2LzA3w8BNFVWjgxJBGNitwCiKNT3gBfouKJG2iGoK2z0OKSW3OuJ5gtZtFKFZ5bMbKnoB4A7KKOvO6U8Nd+a+sdY+52qT+cy961r1clyYrlSz60RrKlDEcTUfxO6KSwMi6Li5VC+e+8AMmwkbU7F7bL4vNwZj7a4ibV8lJQ3Vmds1UeGTRXB8MeYsFiqezYFxyhhrDF1Nbl6HTG5wyYbl5cNyjZGNU9guzQwQPus7ks9OEBxKuyTNqzkrnBw1Ai62qGe8AGtsKpl+8AKzaOPMt5RxWNSzc232YxXb27R0OpuW0hL01QscFjrCM3andp3CZB1dmpglhYLXYLwxVyFvQ1c4+8AKvQzrPvACiZRudXMOlSm5BeB9fd2ml7YpwapsSEN4MURVYgisVFJkgkKTApEYoGFKaG1QDRJpiQ0gpDNqmEiSCKiKIxmhJgJITYlmCUEIxmYwiNa1516+V9H0ehwTNXYpQGpy7Lu0I5mIKZqQj94AbRWhDS7dSQsQ57wAYhlxVMCMiG4teMXoVSajuWLmzaBIvNFEgvwArM2ngIyP6mOPt5ADMFcAclyYGifE1InxFQIUC40zGxjd1W+KOK1NetUJavFq94AUFszKgdx3K13pd5oggvIVoLJq63LEg32BPCPUKG6WylspbgyqiqzJUz3ijTkWR2gaTlVd6bByKU6d2qgoU9wbEN1h6louBl7G2gXQ0ZoxCmn5acq2stWB4CjmwJLS8PrykWqaMrIchG6Itm3Hx4vfx3vt7vfzMYhiDUkFAiZFmGpkMTapmTNhghkYw0zDEsiUkKBJPp7dZiRMX0PXXvz53Jl5oIr5P3gARWIukbuOkcphppfXls6al3eG4X5Lg4Lqk9CRAySnOZVZMIK6XcsjdS8AT4+JCiKyj1qsOHH3coATYJfvACWusdgXIaT4kAk0+wp0IvQhK6JuqvbstDw+I/D5k3tLFQDDzj35lC3+K7B2xfNSdfPkFVbkHdVr6keL3PkaNK4rfH61lVtYN2BQyGfPWHAySyrgoXt0RRII8blXgq7BCM8gQPAUe3O05vHguIXrBYgSQkYxuDIWQ2bSdUBN4qVeaQxNSDQDZsoUhCgRNl93tyTEJNiCUiUiaSZDTK1BEEREMUmCkCyQSkJZDIEjfHy997+56O972SQAkA+BJJPUKqBd91KZClX5wrHmbFCX8vjqGXdL3gB8DL2jKOYvTLRoYHzo5N13Fid+8ACy7tyYjoHgDH3bCH86aEo19xOSlPfBWutUGK+3r20aRwI1Lb4U9u5ei6BtxN5GUULQZEY1Hat2fHUss5JrWph0+FVATJu97FoKDEqgMWatKYmbtkRHMrD14LyLonplV1ODZD3UaxIl+SqghRlXfUNeYKWuXzE3JgWg9dYEDQ41frursqE6LV2Obzbrclcq94AYrrHrPvADXa3bG4pmwDKCxUOnWN2m3ogcyxZIVMnjVwqBjniycQ8m0yrrCfeABKHKaddgafX7wAIZur21Lo7IMwLE72Fd7coMp5i3ZsxOqfYqOXtTFVyoapBKxKNkHLvZYrZsU9rHCZfjyW3Kwbqt4/eAFQwkVOy84gaClpto2qHXnaup2ct41S5kS4VA6zsKu6NS7nNghC6ehZYqwqrZjoTKF9u3UyFXV1d3gzLx3ValnEg+oT11ZvkNmhMdPeAHM1bFt4FaCKEq3Fd7ujXWNdKBDLow75UZT4gywkLWdIdLzNm4Mg9UYryx3y12InuBxSj1V0opvBOW9m1Zu6DTauXZPLCxdLtlwqjExLCMiBa3Z2O6DzaY0rBr07Juk5Q7feAEbVVBxnj3l3UQPAXSCw057N2YB4BO4OFVfY70dmKPtl2zIZdczKuzmzIVabXvADr6pRWLeNCEaMzqymLy+wRvuDiqs2J9Jue8ACNVBIWFerseXL5IsjEyZQkqoB5e+BHC43ETbOUcG1jOhScoP74ZV51FlN0MxCeHgLrFDWy3CW3QqXdWDcQYtA+v7jZfsy63SmKOvcnTDnbZGnrXpOopH3gBXZd+8AOWd06hq7kTe52BVLs2usZCmFfm17wAsojsoG6cifPbB3ZXLNN5u3wLYPTTxhdY5YzuY5AjaqJCxmHao+2XOPfIW4FVL7q3tz7ZB3ulVYu13vABB+zFX0Tsg1tnfh2A6+StProSIRBEVtoOy+aIgDBsb58c0Y52YK25l3QyszheS7m2iLGOrqtkszrrH7wASEoF1wcvMyr0mcTbZqwquwQ8x2j7wA2qqqQMBt1BMvYJTlCNWMQnbZ4IzjkYO8aOVQyFOYqLsXMKlvOFodMCxNTGmzMeNQy9SN3KYkgQISEhJGTMk+fbVcMSJKEyxSaCBUmT7vzvPJiMyJIzETRFMkIJJJkxUSRBFRjGOtcNb303oxrhxWa1xrx4a/gxmXtb33Gw7DzQduoHtKlLduoxA5kItlZu6cj2VA21DM94AWH7hSbuq2mKRy9vuHWMF4nrj7ox1oCFYpi1MNRLZnVkylLwxTUxWRIQlSEO1iXUQ47cNwvjesmYZSNp6oxSpISenJbZxcCQeL1ayZztvVYxYQM6VhRRVikVVVuhc5KtGn3gBgJZvrZYvoO3A8bFWK1ULzduwuCVl5Bfe7u0TJzg9LWqlYuidWAnZp6GugVpC8b0sTm/AgEEEggnFc4G6Yq9VUe1Ra1FFSC+1VoXu1x+oGiASSCT7CyLf1ofH0+uXV2MuGtdAmjuffP676mp1kfJx3n1Y7+fWHay8quFcsQjYo2TESdRar3gAuQvgVozbwdUXdw4bYmCuhnLet9ecNkrAUQRSvdyxMJFsdUoyNdXOUqnVNR3dc3NZBHiSPEHx8fMgEzY0gAZkkIpJTJTSQxjIlI0omCZRJpE0CMN83aZERRFjGKMHcKkA4SAVwxrwxrdHwfDnsR+YP2D55dAldTNlYLtBcdhvabFZkaI62m8CzaeZrYZCtBezYsJAQJJPiSQT4HLGUtrXZHavTieXQ5rzwHhKdEkkgyF1TFNpKqSGJLCsVc4PEHxIPjDAa0b3Eu3lrc0XmY49daWePF68lMaq0aNs+8AFAahqAyZWOWLF81ZYmNOisq6dVA8rO7HghAIPiUyqAYKw9uzqrLgnvAAzZCWCQfEwaNPjMkmTPeAG0sB9hxAVjrbbT9I7D94AWDk0KWJptXou8GWLt3cUgQyocSzbNkOcKc3BR4VvHTyBVDL27zhG0nzp6B4DMjCwVbu1uMZm95vR17lYeugPALRgbZxZVqB9l1gXPcNyhW0KuwqJzu7jpoiZ3YCTQYy+F9jWPsam6veAFPaz3gB3to2iCGe8rlUtjGq1lmsOBdI3lrOaIIZVGc9dYD1X7wAVdWKkq7J9E9UDL74XDe7kraq8eWjc94AV0GTvluS3uWEbfZnlJiSPKWsUEpg7l1eIWkMvqps2zNhjOl1mQcMCIgMgVuZnXdiV3b1zZjKY2PCKzZz2WdtzrqYB4Bu+xjKfrenuwYjxyxjoibtVeZk9Dy2Xohya6wblQ28Eyr5m5Tdnq5YsmWuHPPZzxdbp9DExd3levBgrdUIW1rOTesMF9XbBUNceZtvHdqbd46zoFStTRsapeYzXs7c516l10/mMb7fvr+0YpFpljbPxqzQVbW0EHFEllri5zQlOFYRqp3hEm5Ga3Bo0jU5trduV2066r8ZWSq6imyHK4s8Oh64c40eZqbp3qvI1jlYoqp54eAhLuWNCrnlYqQmVd1Je2IFUzqb3NridXRQUlarOM3tvWY6TTrtoa904eiF2z1Y2Dl1eboRolQ1Fg6pduTawmxD9dffd9li76H6aNCl6E9+470xjOoHNkIM4VcwM1WQ3MmVxdFYQ3dx6IR01abdXDMvfRXsGKmxHkIZ3ZUlurRsGObcdJyq7Lu6fOe8ANdsCpVQ3sDEvQLrFKZoSuQ2CLME94AQSveAHVWXKVOs1CEiaWLpe8ADhNQWWet2ZvCyRXcMh7DZ5YTgvtwO6zdA8BdLK3cKWv3gBMoPdFS/YCoJqqVxJ7Hd90qVm2KzaG3mYbS2ENGX6uMzrOIzBTqqSmnC6xc87NbQMUzYE3W6ZpqxHWkR4N2wYHuDZurPZfvADtvBZtLjC9WxVZF68aAaNnqhVxDLsjdgM0SjS9ZFe8AKsEEcxXbVYFjzSkziEzOhurWWR2rgLnefvAB5mYqhzdW3sbaBMpFq1rsJmC6GtMEW3M28O9jVysrLgu620RXdDxHMTPdUMubgNaH3Zeg9YY6UIkNOHnhSHG8zI0IcmcZZ6dFqQRJmTMvUNiSzmON4ENDfdm7eBwZVXm7ewZRkErhJclVZHbW5Z292s6B3heXAUe13g6/jlrpoKCVQF7tmuMRJ3xUmcDFMaDmYjytZpPst47NX7wA3puom1dhQUm+NVtOBbswPFoWpVvbaSrGQJbiq0is5aegFRqpqptdiU41Tqy3V8BVSZJouoOwQEGveAElzOt3VhUSCoQGlqpq1lLFT14u19sq36pMVJhauQijYC5dvZ3QTehRe6b28yLL5Xl4RvDm+0VxXVNJp8vXqI43l0rymzPeAE176rmYXTEdR6MdZdzp0vtUZbZx6GTRFu8MsXMzrWKirvt3BdLN2RyZQq7hxA7L490Urq6r6l468ravnNt0M7NOi8rRDQ4h69yydFPCkmMJO7WX4yt6uFF5a7aN9XciO4LfAg+JJ6UDRZdyX2yTlfdOfY8XK4cGyzuvswMt8LoFYKt6pwg7TnesEMjawHJK5rxma3mZCOq1lCeHgDgMDXU51qngu4MOdlOjWQ1UBW1Q1S+Ex2SWyOyxG6s1p33gAaut3Vls/KevRg3Gp987G/LMHWDws1KQhYf1T7bwzpUvY8+v7lfLOkbpKdLNhipw0X7ayqiOPLu51pqXdUQmMkDIIYsaL4RMXpyExjNy8S8C4apWg8/b7qEvYG+G/lzN+ZQiJ0nq1LGCoKqKDGKskaTBgxQZIaZJtUSgiSRZMTJoQSKRCKSZK1CJkyMaZNqhIMMZpJJjapom1RCmCaRIiUNBRksy+vrhMwpMizNDAUmZJsPv9zGIxUkgucbVKSCNkTK1FaiiTSCw0SlRkmJQJES2pIkwmJgNEmkUZNpmJCszMQgbNgaKUhEwJBKaSSan19yjIpFGW1BhiKa1LCIIMGSiSikyJFIhmY0Sem4lGaZ1au4TMjJXK6WRWpmkJElhSNArUSzIoiEhKZZkFEwUyCgSJMe98jrxmKShpDMoTJRiGIoiVBiSQJaRCNFFEGIFG2oxIYSkxCRGChREySJD33EkIJkoTREjISBKRvr63SiKUMNkmVFiAUiITMhkkepdFMkTFJgoBGxILNKJtUYlJG99zZLKKee/PBlM0MkMkSIxEoZA0FCAFjERYkVCi/tK7jfBcE4UECGl6uITJCEkkT3wRvHtpIrr7g4F8DiVKrAQEYjITCYyQySkTEhGUlEKRYxWokqaZgmpAbNaiCSNESxEBEQlMYExtUpLJJUmTapoYkiTTMjGLam1QUkzFJtqPq7caGNGkjQkEhFJhCEz7/XYwIBIhNEQaa1KURgVMliJUIjJkimQyYURtUZMRJNCy1piiTENhRWpjSChgiTUIhk0iMySed0yJljImyaSZLWikybJslhGzzu0ZKKZCkmAkoiJgxhQjMplMImtRFamkiNlSF3XLRDKY0ijMwimmKtIQGJIomSl53AkRd1wZDLamYSQiUWJ7/N97z1CA0YSTQTKGSZoCiEZDGWN8NyOcRtUNtRICQmZYiiEIImZEIJgwkM1JGQoZJoaGSYmIFAAYMswUgDEjRZKUZrUSomSgRGCUyjIiJiiTKBbUjSUhAY2SNqkmMSIYxpgwIRJYwIwAqE0AhS9rjeNdKYzFNJMlKYpBJGiZNvpU0ZsKc63upNEgiSLBYCnPvc9PPt6acrIsMMN0ot3DyiVObLXDGMGYCNRUpp1VtZaVKzVKRuQcdiKqus13GDAhLhoydHxhm6tUGGEjMl46vnjT55pQSuhZFa7q0TV5CTlyHLjUj1A0sUJq3d3WXdaq1cDMtSd2t9Qm5yb/b+zLy97774jbY37Qt74dN2sUdUZdXk3taJ4tcGMbWWk+zLqR5so9Sv1Urd3kV85Vk5cztdo4L5isqtEauwxBttHRlVlmys2pQcIiE2ajTT6zN94Ad25xrTxfavW1kRYUNZ7YMhFdRpcCMxauXuO0DW3ePhR19VaetUN3TpmoIX7n2le8AD60rxOybjUElF20IeG7mXmQRWkFrOC/EVNyxF3ZfdHz1894VnazQYvqm7jxt9mYyOqhQWsuDe4rZebXUqfqYu8gSmLIJxvaVMV1651p3HgxCXHdXheWebVM6OT03QNE1mnX7fZrG9vGb7X3bIWq9ygo0Xtq8FYQcTQ56ZDGND2uWDrm5UA2BM5664atWtJBvq4y+RHapCDe52XeV1m9Njnkv7ZNrr1X0dYJcz4V95kU6ui8y+323r1uFqdPeADPvABjbb2f6uAfXTED++7q6weQOXt+8AGxW19FmTqphPF0OkZlmWDhTgtXpwSvDwFZeJnHB2uyN2t86G9Z2g/PFho4bUaCPLp0wzRoYJiCghrqFV0Dq7gvPyZ7fr4kc4r5ThSxZmhb8NGLNDFN6Ehlm97Lnlxtg75DOfWTNjpK4nAx2bw7TRhiGCHrrErzV1m5pRCs+mPEPncLmYNmK64Rl3JusV4Xhd793pNqj1N5yudeCnQd+2kGdU3AxxrXEmIGD3vAA3FtUOlEiDVmbY3eRDQwWCGOSDOnkL7cbrmwzvsMy7L0ULehF5WvIZGNr3gBQuH1K7JOULvRWNUIMO8wmM06RBwVyoD1g4cIPTtMjWW+EQBq83p5uXzPXtVQyvVR2kNMWNLcDFu4ewI68COgyLzgrbUOchdgLTRdLAKWwbhOgqJPqVNQi4eZ3LuSCQdpZ02bOvBRbzgsuhQcORXCGK0Yw7yvTjpnnHT5XiyLhWixo2HZvvACpA0l7M54MrpuTprV3WodrNUN3Y+0PDS0cWcP1CXa+47fGi/dp2/uydt1UCu9l7teRrO+veY2xwzg10vgqiqqxVEEWNsMIxkoKEIGQoLICjMyFlECTRiEkZtUlKIiMEkgNlFkTX4u7GZGUyI0wykEUJSFFEhQgkggERQJfbX4Lli4xXw+u7TzG/yEN9w7G+mrJaSmdjOdgrZW56XkN2sgVgUO5g45s4X3cZCKlVtwY1IGah5pLJu6YNWbj4iGg5Uq+hlrjWvndeIJ8SAXWXOa1c1wednLiyCq3rsWvKaqIPiCSRdi94xhLiczMcRhCQhCEm2MybT1poC/JfVuokfCqyXmqG9D210qiKSQZeQdk63L4IyhJ2sw18b+H1cHuJiqdBY0CSfEgnxK757t0NBC2kSMU+yZYunTO1REb+EHXXPSQT4A2ntDrEGg+8AJElb922ePvAAs1hOq7WZuDZECL77eHzzOG40PlXza27491muqySRqJZFerMh4bJYWDRu33ZUwEnQqWWp3My8sQOq3ZTRoHEZk6sOODJoaj5AMkkkkgkgkeJJO1TBKYTapJYLGIipEiEmRZLMFMf4OuZsZtUpBkJSYlGApJI0BFEX09yTN67fPz5+t/PrduAmXhZlfU7rCSt/Axml5XV3XRZFWMePhdXUXneq1yXE9AcVEcTUg0Y9XXmLTUog+8SSCSSSGNeY5ZLxUOIzpDsFA4d445fCDDqzlhPiSAd2mJ2gZ7GtwgW8GczGWjLqFKlSVCqki26cxrRmR8+ix13rfasvlXbK1A7XbwV9wQdk6SqbdLvNRtEqCzFV3QDeJi0JjupUuwxnVXvAC/e0g+e6i4M7Gb13lykiqMyFs7iwWd8SAfUmJW3d6ghTF2aY13XX21XmBVplDNtSaT5uDAzMNkZGQgjFI00lMyRRRSuclakTMkaFGYyMMUksQIMIQxJImRM2iBikKLAvjvXx68UQxElAoyI+dULGIegdSs668aOTfHShSi8786sWrl7gqr/VW1yFxZXDVTrjBp64S9oIOZ7qR3ZtXRkVbSU0skZBdJLO/V2vUL31UonvvABr3gB8Rn3yfucvaGZujqE6qV0N3LqkcDHbOgvumRTa6BkSzs3cObl8CgyISWOJQ29tFkioBdaU3L6BbyBK5e8ANYPsrrh2UNpQXz0c7t0RtChmxg4CxFQ4qCyuw8/PUCqJzhbt+bKBpxLxVYfZVsTo8wPKVWTJhYYdKqOJsLG7dcbE/dZRkE8+5Suuctnz0UvWYTelDnV52bBmNb2ZTsYHSLLNELevjCODva6Cw83dgo925UhOa7rZZd3V3UDPYKp1pFS6Fd1bm6EdfDVSrg902827UoN2erqu0EcM1QZV89V8reysXTevuqhm3NUJTURXZ2vll4OtX1jbPE8du8S4vXZ3rvBRsNYqkb7Lm/Vkd/TjdDX3069sHdSs0FSGB3WLdCmK0q3e1mZevLZFceD3t2aKU7blA5dBqPsPZQGvBid9nT0oWOsdxy76lQeqi263URYy6/QuJz47K/V+8Gj9P07Av0oVOtfkX0WTD+IRyzM/U6rsXzo19YKFs5ZhPKqgNN5uDEa1zxdY0+HLIqoDL0iWL7YsMAlbu1ql6ASSMYHgKekY7DpFvZmY3Ymbp/MsYD7wAlYO7gi66MOwZjz1O/pUd3STS6sltYqvZe7Wri2unczm4KGTQHoiBNRTZVBXE6u1RaWctc0lB1a5c7a2SjW1l4tvBQoX7wAy0bqqvd2+G6R3NjqKwOO4znsDo5uIEEWvTzHSSs2tv85UNHUPmimeke5bbfH62HRTuH0tZgzBq7o8pEcIbeVWNOA8kkNzW8W2oHUM2jfUFyXTrPYF2CnWt3Q7Q6EsXJZLrC7V5imlqEbjao9smTt1pPNUBsvcMDWcbFnupxwolTkxc5OYlgadpaYR0rMOBQgsKU9zIB4CTamGVKRDX1x2WvIcE9dG9Fkccs91oVu4o8yxdTb0VknuwZeLbT6KsoPaoJulqd3MrcKusB0jdquzKCrBUylnHPaT3bj9DfKzw1U8s2KIY61Muw93DHmn3gBcyrODEDVyLuzszbXke3r1dbdn3dlNIXWDW2NCd9SuwK0VPPUJp0KNW9gUuVZPYfD4MRdzRiea9O7A0isKgaMoOUNYlwwyiinWr9JypIzEgyEQmYJgaIUUaBmH09uSkTSmU2DImIxAyUjFYiisRB16Zu86mavXatuZ0vbfGM4zrirONdYdbZytafFGylmQjVdDKeI+ly6QFHVl9gOe3yj7B0wVW0MplbvTrvOFHkLXYrxkTic0HCpWqOpxJHiASASSXdsskKgh22r63eJN3QhBJBBBjtbTw2ca9DRiQ94CeIPgT79fz+34V9sqHTzZsFpW/eADDxsMk/C7ptJbVapxw72PJ4eA7WZlRHq8UESjId0HDdTnhFRUIbUZqEEggnMekOChtUSygfEre5+YIZ3NxA1g69xcCST4gkkVminWBdxnA4KXvADg633gBVTCFrQHgJKjENkabbHWeS0bqreuz2qsGqljbsoIIres3eTc9XEXxXT84J99Sumj9YghZow0SDx++QwFFpTgRTNHTvI6NtTbCzq3RmX25EKHd9EWIDLERKKGmMykQwGCNMSSSMMlM1qU3z7rJIQ0syFaiAlgIrl1ahkxB814e8PY3pz7PpTyg7MLa52F8KmYtGuooJKcRTlVBafJUH3r2GazVUc7QlpVPaeYD4a814DhZBMeUNLFnYLkpe821juhlYakKTeJe94BkSYpZ1A3pO7Y3Aqwbpp7j9WOLxRG28uXQzaK9oyDE7K3UPJJC1rVXVALBvaxeFbqgMkbUzrYVuDIKB1RUmMibqZWVV4jljw8EQh+ZxdqRD1pnh4Z578Z3Lx2Hiy7x+rpOz5Oa3mg20JQVFRZp2nE2HLOCczshpBMcDUopOZkKlS0mceVeeUsOpG08AzJWMDNkRdgG3CZmGQFEogIyCJUQTjFEqCA4EUQwJwijlEWQc4pUMyIiEiAQZ0KWS8nNazsg6oAOFRRQeaKqqdtTVEDea3STS54Osth/dA6zbgcPx0ByBRkRSHLCTZrQHbEB9EQVQ4RRG0FKg5QFSRBQ3QQXaWkKRA424aKSaunAxGsDGbthTnBLQVAx6PJp7w7MBAB3wRVkZEB3wADY7jttuvc1zbNmGWFZdWLmzeXoX7N7h+wHGUAghf7HN2hh/Q/HtQha4YGKIrsS47u7vjDlgvcuudChiibp2aENCFeNVQCpKm2eqhNUIHXgwZa7t9KF+AIOyCDkvC9h9+30B1frn3SR5fKW/rv+HNfG/1W0Q/q/S/3M9lm2hvS/NL/cvkn6ZpUdvoRjotovTlfifUFzLB+Py0XkOYol7No7f1H8Pb6j7zkWe+jZ9l9mndbn3iPHxPLAYR+cViK3MQ83WFgbYkPSjZ8L3f+of9wz+kfXEMQZ5TPmNa8iOuJ1dvNuv/fNcQ9qTLJlA3d3SKyvfUPcnDXbjj02KN6Ni6Q97TCGGuNBSqIr7+aXyMF3QuGiOzqj5kUTpSeccT5WEQmnDl5jVJDRxm6I81qU84etM0KUbnLzdIQ6EzpGEc6cGeZRR/WnnlMMeFw7pesxDKBnqZElNSIS9HusV2WpnOvHZteHD5W6y2cs+xUYFeRNb6n8ttY3NZ8ePym3PGmF/bSU5/bKkFVGTLKfVG5Tv6Ut+ug+6s8eOdarg346iwrnSCRrE4vuYpr3H0E/iZ/b/MkkMY3uHTmapp30eJQfr/TaRGQP95BK/VSyVFkVqSf1FFAXly9CpcC5QBIqhIKVLa9Itrmoqxp47ao1v3bYsSmFsFkwwLZBSBLYECxu6ayEAEIASYD0MMg9vqSJCbadOy2tWi4jGCJFl0lcYIwni0hM1DOm48LeqStg2WlsqH9W6RuGG09/Y64PuCeC6wPDG0fWiemT0v4zcmXuPBlkw364waYpr9w/ti8wZehbW6Mox+SCR0ZSDlj18nWsq9ZhbVqRXK9Xkz9C61051XYVV11rjW5FmKWzCcyf7w1MN60mYdUjU8uv1cCwm0GqjFSCDA3a7U3UiXnOuc7yXpi2QSvCDBFJm7ruTVnUs/7bGbVMKlp4wSWpc7oolPTf9hK9BLRMZ2Mj2PJpTzDvN4GX5DfnwTsX9C8R4Dq684zi+lY6tF+2+34h/s8PcAJnBxf2S6EGZNDQYxjKMYXo4JNnGfo1GZUKEp57/wfCM/6U934fvGfThaxfM2ZfIT4Gb/xE+j/ufN9X0/Y/8H+P+01ff2bF3FBK8ONHQaUdH9Frs8WKCFc1ZzvfraEOOfw/xcDwt+uLn6mgsGCwxhhVB3GqjvVYs+uRfKEkhqysPNWKX1mltDFIkr7/8h8chuHaR53Q6bBrT7fk+BN1qqoEkknvx77VxUmiHeEDnSgobPzHl8PHnPTcov5H3FG5EB60lzuf00U29uuDLIPDSTNmf1UbgwU4HLlkwGQ8XQx2AhgQgKNf9cH4ZDQqQJQN5mGEM449j+bzDsbc0/gGW3sseyhs2p/kE+trW5yaqvYIIR7PEIIQzLTpqS9iQQH+vkV4eoEhty+EnHhorBGJ9RXiJf2V4ahiWnoQ+DDfwGjj1+9+Nef3BswyNZ/hqOoNpSwumgk7wrced/9+89smdohvIDSKnPCQs4FTubNZMp6fXIesMkA+uCowESIwGQgcPSg+vwr2XeTpnYD+Xcdj6TsTC9ix44dWO00P7JrOYmL0hdXkFykejpl7EkxvkYHe/LrFRzszTe2XE4TKSsdQO2rIdsP7p1XnFU3l/XvKrvaNUMSzEsev1+YOxad+jdzvKcg5G/c+SJ80bBIENw9bVJDn9ti2bIky9FAe/dvczQTbfDUPnLotxc9Rctuptr0X3/rb//ODGRyMQtXcaLRhLicDA5n4BmCZMYezZjTZqSFL13UBColqEQhL8iAcZVMVDmlWCWZVs5CYFU/MHK/YGIwgMA9zfzUfHBUXInNuqVVVZehCtYB9BZcnOUz0TpC1QgyDsK9B7yrzLH0Fy8EjIlz7bbSHDSnb+4poh2MbT9eJxzlrPq+7F1ROa04eTAOWTNIIu6yZuGPs5u8P823apTWFdkK/eKz1ioj4q0ORyj+x/0125+cKaIa2JYmZzBEDnIENj7gh9LKKfiT6roSSQe16tG+TYtehUcqfulGEi/9p0bqZopRPdJ/8ju+CwKdsf3+Huzr4fwtghd7u7smeYepbR2EEX+vnni59GYYPAbF5+I1Y+R4i91ydX5O2Ytd1ew4x9sH5Fm1D+eciG/dowdiY7f366nT1+XCD2zyzRPRn76ZBoaOJOvRk/9f9g8Bn0K/Hju4U2fuX0QG7fxdQ4epU5Fx4bkLjVyTv58AY4skg3iHQeNVGLFaaGMGB4oaSysTJ9l4Y3Gf1f1DGyeZ+NFZAztDBsdc5I/d4/hDIiDBUweLwH+9tUxIS8HZ1lEeyXeumD/GffCT3EaSiJeyuEp/8tfCLJCY1TOK1nd29JySupf7k3wrMmW+HrrOkTR0xrZgwiuUoU7lZJoyBbL8KlDEgKIj0fJSbRx7qSPJfVGU6H9iJSowv44TzPm9VnjE2vbbzhneO0eT3SWzz+/yc53ndnVyP1eMmRYqFFlNOiS90Uo5aZnpZPlKqQgyRRJDzffOzR/3znJ/q1iMV+itj9KqI2bR+zKzMX1j2kkteE8SRSCiqv2qQyKHqRhMJIB/5Gwdgp7p63+7GsPamOFM19qJLyVVVC2TsvN7KLvinTLk8gWzw40RWyL5fm/m4xvXG8do0heWHvJtXWawq1HEb8dQZxmUozMdHaU0cacyIaF7F/ajm5zedXxbPxaLl1FluGY69jdiav3ur+Dff7oaNXDHKCKYcI+wrjycXMs6nlFc8FVmzPZWEXHaRbXWetXENZSFwIkrSIi+8qKkhQ7iSHOtO0CfTuka605okJksLTvM0XlXMWtsF3c7kOVnLxysxvmGVpDwPHaEq8zrxxKWndJNaWJED/dIX41n7vLaN/+NOX2eBWRq01a5tK3eGsX4xrOZ2UQjfq95dgsD5jW157ak60s8Jfo+T0oTgSUFoMu4n47p1nE6oU846Q2sOkkp4SvKC2eVhT9qhdHfJW8ZEpSRD8pekcqFIlhdan5LvN/CUSvNjSOeET9ZWJH3rkQlSMMzGheobSK9IzC1gfTxB/P+d1LfjsdqqXPyOCRiDFPtzVpwqGt1BRLrAyGxij7HDaEhWvdGcpnyOXghhfYymfOntLMh+FOdptvLvecOST8ezjElHSJ4uTQubjPvQ+U1SmND3qt3Nb/Yx868EevRN3C/XK3E77tpS5FVISQva3SjhrNTZ44oEYKIe71WG6BhFFVSa/uTw4lwfcIvV8VKgYqktY4JbsSeE9K2US1c7bZ3k4uhUlqdrvCaEC82MIxhhREWaTQvmvm7QhC2jqVhLxZaUYzt4vq2imx8r+3W+lAnD52HBJITKY7uw7GY46ZuNPI6iufT8oKLBRGtjg8aFFKBFTSaehR2nk8FDHAkeaY/Xd/NZiKYziCyST3B6TIZ15LNaV4U98+K+NfxWhJ0erCIJI+9Y4u1Ec1VECweIEfxfZW2yikO2qO7SXfIKIJYu7vCPzxjCWtNYJ1eUd1obqlmdKzDelX4F1bLaYuI5Xq4c6fr8nC6LvKDwk+WKcL0f6XdtUWQ1VzfKLJ74ZTKnn0dvoMJSiMKJkqJvsjng/wVNs7fLa05bZX+MqcqwF1l7PjOly7472MVY3mQ+thPewtCIqYe1A0JNqjOL8zCY1Fj0cCExCYb2oY6ZdmHWjlSNB6JTnKRw6UlSftrHJR/sp4qRK3ti6u79U3S+FolRTlnKfVxvRVkMOyw+Px08ufYp1s5Xc/nUpZFMWtNpHXMr1Lqhjy9co7Yeyap2uUxlE/PL+Wjl6Sp99ZHAkbb95MKUIVDlujpJ/GxY40xNZ440vNCmM7SUQzt5wPBxjBeufFQn31aUOGHN0m5r+X6syzZomZx0IPdy6hb6+Mr5uFu7v40wp+n/jE8p3VfDs7e23Dt7bEuSnbAnjnSqmuMXeVFXHtt/x7plZGYYpvIThz83aDyf3PEj8r/GSTM+M7vZXxnWUtyKmvJ02TO8KFvP8f+Xwsl4I7c5QboySD/111/Y7D7T9K/2anomLDJ52C7I8GEVQ4Mfz162r5/nxqAdr9OWgwBaaJUjAQkuNBrdaxRlsDKH0fKEDmgMexO5Eqgv9glAwGQC2IyUur+Z2OMORD0PeQYFwpEzCjGtdWBMAuGHtf2BmI+vSBqTvMfr3mUHs4cRxyYaIGYyaFTS7YZuFLUWWCloPj+lzEw0GQ1k5UHsNQdYocqimjBJFJCbR0Bx9oazaO/amnpMx2dhjinWZWKgqdOlQKYBqH7APrwpMIoHUs6aBqQ+4iHAPDHeG/AV8fMUjqFYxRQLwBiPUCnIZFj+B+XFrDKuIVjSDpM5UEksUKrlhVVVUoNkZrjW0UZ9eDuFP046QjOwfqeWqmHOMcDdlTt6omAGsoJ30NYw6Q4pDtQevTc3KdW+iYkhrYU0yxiPEXvDpGxM+ZWoQ7hEHcSTsDrOvPYR1CqiiMdDfzm4JAWwZCgoP28CSpwnCidgXtyVRTohemkJzKlg/dgh5czWwlIsCpxnBKLLwihdVsPRpO6xA7w8TmzDSGeZmnXK2A4gQYFkg6hoOs2nOGA5EVOGmHhLB1BRAPSQAsIalge8SBrHSO+211a8RiYUlKgyjmEBuGTdujtzDcF7jT4ZYsGLazatWSH07TLiNg6dDOf5jjOfyOd/RYdyT0TTU+1zyNDQwsXuzLb2y3TO4MkTjB9hq3C5khQecKPSxNMCROuav6zNNhEer4pMo1UuG39tvfN3bnu8mmGide81El+6q/UgzO3uDAQ0AcwWbBixjFOOKUHgd/A4Q05mmp6woNDkIaDCcareiVCMVzRQghsdlBbCT50DEvwZf5Cj5hDVRRkv2sRytfw+/8Pb7axtOL1Tio8pIPXwLLE9R1qVDvbra5xtYihc9LxXO7GImCebWAVRRwE/YJWjVpNY1Vfj2n3PW/kXXulopCApYzPL/B9bZvS0baFsbUPzoe64Db4+/89uuB7uL7R4BQUFfqtKsMsgUyBIMgxtlJqKNpfVe78gVp9W/Tmq17q9tSyIyNspy26kl/O/BXvb8tfcRXfovoplJem4+FgNXKlTNd1xld+S/x+6978NglTP0W4akJE/iUjpttqFBCsmqJBDbdULQT1XR3qg/gPIN50MWQpFE+k0n87F/W3CNkJ9N06LwgPEhQhGeVWBGLNAy47dFaCjC/vOXok5NEb5UJPPRfq9HgWuTogWjkwuUZnuKtNrCGwopm1MGy4FjuOtNSQAC435KIfyi2eZJzEj5iBZJBj0pkAb2fbK9S2rkaNiqMmZWt11cFIZZK7miRgECQkZ6i5KdFl4o7cQ6yCwgJ+ggTn+WrMnZFPVFcdfSJNIQeMWYKCoygnkjOmodJpQbChNvWM2MJgAaE1aMA7BSXMGiud5GIh2rtUvAXaVR5RPE3PlkSjUIXiQg6qDebbn2kIEOp3B85+KoCB6mVmQ0Yqxg94mgQX3cfvKP80w8iwweYN4D/III8BikQkQawe+JqXeVKSoyPGA5GUYBt1QkU0mR3s7Y+AMAuCEKkQLYIJomG5wAzFfou9ucN7VNBGJ2q2bVUqUERooiQXFROx/GFABbEdx3IEYBIRihIAMBIQQDf0X765d4dJLYq/fGFh8P054N6GgOmmuMaISInmDbYN6VBSoDwo85ioztNEwBkFdxM6yfWQYejSb3nw8q+ucwVy9AiHBurBlggeDF5MBsMUwRRkKNVigYarDH2ZioOsC+Yy+jD0brFbMFV2K+dFAhFJqc/87IXNjeHDjyLgzCXTQhe18lcSxoyrdVaTVqJhHMmrJO4uSBnaIZEMzxVYB6gNIufR+3sKIlfWF3rg7ep1EAJAqgLG13J8gRdwh8kUuQ9F5BmQWTiiXLvVr83lkOx7sunDK9YNt34vkh9Y5al/EV7XIrdd0pWozSmE4ZhMxQfCR90v6v9//TGV/7PA/t88WJhxqDjc4EpPrLlvhL9FphUOY0HJJc1/sq7f2mFUdLXiLH4Qlj0j3sZclNECUFC/+rBWrz9X5bMxRBPUA5j8wfPCgIeD/HB3QHEmAJF2H1FHEh8KK//604g83u2j9A4BriSNPp61xQpRb6s7xuSKZZYM0ue814YPvHlpwmjqHxEMlwDH6K9P5nBfEdyieY+I7TOBNYk5ZomVhxguLOwkI+fR6TSI36cSYszoupoZ+bFfsQwh5145fAfyCDYfqCviDCYGYMiX1IyFdwqQH1bvyJtwnWv4qIByv/vbkecW4yaoXx2rxW8ap+bQGgRAZw4KIcizEVMQqUQ1SULA0pGCke2TobbO0GVVFzQSM56+z41+CBn8Lq1Nf0fSQOE+EPGWJzYe4EWTFMKBuNVtstyKWGhbksFGjQHcqOOCYkJCQBvkmgqFI6vHmPBLMTYaU5pGRunOa0VCgPTYfkiFj4sAfRpb8tO53vWHK5a5GTQQyb6vPKnjuzS7btbrdddS2xLiMbWD+MNHu0qfyiWDXv3+gJy3mNFhE4WMvINUdaeks2AkGD8IUR8floLTb0wBlz3hc6Nny2UjleEZeo3kLtAFEfaQSkwk2bwbCanzViJEwlLDRagg97+ZwGdBccB+syFKIDiPvlghAIscCceyrkS5iqHVUR/nAuCcg/6BgHtuf8vVWkWG4lIbQqqK0E6KpdmtQKp8wXYrX0+ZqigKjD0TdHauTG1KhEp1U219lukLC2PQFqbnpC1gYgGSHH2Goo32xrvctGIfFPky3Cc519ExgXTJoFhgRExc/IbTpkzWKGyKO6JQKIlshp4lIEVboHUKKFSMT5r0Ape8xxE9CggQcleDIrF4bQwaBUrSFKdGJIyohlKi4ypbJBDTdCGRDCsKjeAHRljpVkWY597EWKxRCqZLTTWYyqVIS05GlVt6yGFUpWDYacIhDataumqtvFqLlsLHFd2zBxKd0/6GqnEE2OyG2Xce0YQXHxYwMIXAg3jSmHKtBNOs/3GRcIT6Cp9v3f0P9kDIb9K6u9EaINFQOtldap5msNTAlSDid9TENRDJGbefW1NtPsCwNghgOBDYN0TAYN4lkoKGzQ6j5Epuvk1unsseaPp32uabIe9ubDCowMNN16p2oUyIfvhxKD5YqZ4UJxL61RIcOycwRrN4uFCDEmZu2HGcmE3oIc3AHwbRGXdUIItxh41dwGTcvVMmuV5TeVOqmrm6yrzqAWCFkoovTiMEP4GhjD6nMDTbxCw0PGEC/woJVOtold7MKjeKtRstuCqMUbpqlGqlI1RBqp4YD9bPv1KnqH27NEdhCg3lBgB59x3FULIgQxDvRbOD0hxo1nT1H7S5zPY1x6a/GZS0NqhK101B79VbrYXMJj5g5XMlVSpT62cMnKigvRAo9ofjDmeJ4PkXYiWwKmgHwP1JRlh9wgezjKSMesALBXhBpe/SD34iGs+4IF8P7X/HkaQ19/lZ5iYD3hVCgJLGKcIyFT1euzcQ9BVI+JF8s0DjRoO4hz00TiWjYJLFFFNFAeGXR9xcLH9Innkm5RDcwDJAxAwQzYBIwEYFSjGfNdXt28DvlE5Uj8MJvH8VWyVGZz8euTGVQZFcfIkjUK/SYZHdiFQIyIJgMC6nSbvR0Y+kw8tUm1rVaO061iZNKRFujSIjnbois24ltgxHanwcLnO8LVJ6J2nRQayL7SQ8ET4jL2ZMlmeTijrsMYqwc8fHe+jpItaMjfUmmj9EofI8nZHS55NSuyOEn367mzUNdkUcdh0Zy+Fq+wYhBnTrXARFaMK1W6s1LYnWVEAtMQso5QfyIPyZLb3ljEiGh6zwJ55TjYKC3j6SleNNiziqBNxdbHXfyONGNnD7FhpYViSo5bT271yYOLrRjnWlcS4WTTNpu0PTgQzYttvjY0sO6EnApZIVQzkyWdpyeTrvXPPVlcB35q7EaO0oKzezrRjpGoLWoc2PB0hl0mLOTrwpl4MXW4TxyIKonuHZzRs4AwQxuTFmLVzggxbSZOcR4ZiHChjUMnbyz1gwIlzNTua15CO99Lm9HWzgnIq85TydWTFX3Y9Bw7o3FWWMRTB5Y1CQqTvQc3br7TuUsoJkwTNmxdseBOnlpYijp6mm61aypuYN2+ZhPa+sA9mB8RQsGv75XLUOVEcp8PNQryJliCzvfbIxUK1VDENCQYRUEXULQrsVrqCbH26t3uG7ZvLluNF2ht2OFlCexL0AB+rwXrHUKF2jgZYaMQ0WZJmVG9WZzSB1kwGREflZhZ+n5mv8v1C1CQAT4/jHn+KAyj6Oj0mFn+DO3G9YT1xuVDhw1ZhsuzyVUTAJ65dL9HXbjee1mz4JHyJFJHyQhhon1NkHhCjaPzyzc6798WuMOZO/aZ0s9nmt8q8DyzUe49mEJ/wC8v51uX0kVUJ9xnuMIGofV4EHxX7qh6hXUZ8/9J8gFYGpZYQoKGqCOkLwhWScBi8wFZmjPOi47GD2spWmxPlSK0SYg7YskMCoQst4404JP+cXjSr+HLDaNePpOFGxrf0U8ep9jbrAa2Hoeao57UywQpotZ4Q5bJ4w8vDtmbc2UZrRoplYqr9Z0clbBYK1srQMQJIpHVdgWMKsA6oN2ZOsmQhqWC4xyPwEOzdoNtBiTEmdH8eVZm13tm/NMZhTaNve2ItWNDK1xXZ1ssSajrdQb79cLhLEQSoEHWgREveaFamdpByVZ/dyzaL2qtJcMfQx4Y3YzZ1D1qtbftIdd+E2+2YRgidwsTnejB1bLE0dI3tgbrkdNVqq0pjJrvVm7GMxwwDgFrXoECMs3JilPsjMLuuOrxoVaiFlCeNsTL+at90jxV65roBRHGRdiX612kn9f6mc2JBC4eVIVsXSzba6MPh8EBPiWPqaJi5OM6OeN1PkY9W+G/u+r7i8+WyZVzTUtSWSNMBsCcHJKGg0DcDBNQQYMSja5DgLrcGgIMBISAG8KCPAgaB0roTMOQKhsKqwrBVhsuqoYWVAIGKcBkL9kqFHIomhNxEKk2BNyAgGBDfiF3IXhQJ7LpSS1QQIwJhAN95n/SbW4OA4QaNQuA5P7wjgfMQOlD7KDkannADWTuAn7GBwtgxRIIigxNSw0/nCwQoIiIIKSHSXJOXAtOcYa1XBTBKLI6dQwWfWWXu3mzLIDyX6YL86vezQKX6eom8qtipzoRBV0KiERyg5suVERENbmmcNVTMvqSfya1M1nbASiPwE5GEmhZJ2Y6BdwqZEdYdw4mkbHZK4Yg6YXMTHRZGdHXfIq/YCQLM3o7zYZgDsQF1ccw0DqNFyRTa8SjfFyTjxsWjpIJ82H9VgHrw3RNqgi3+Yzzd3LbNfgf4RhLjo77Clwg2QhmJ/CIyC/M6hdYH5v1fTftDTE1zYGskQQPWoMnrYBp6yWd5g9ZpWsNJqE1RVRkHe5YpocrUQtaQCiyBVPRGltcm/b/PxrtPJ1zXUlqTM1dK7FCiiCEgrXSBNB738MQTKEh9mtPplSuNGYYOYEOz/Z6QAmt2qHlWGZDm5/pSuMLc9UvUaShCfQwowVlp2QrkEU5TRvZ8QwO511iFiBIhUErgHFLOnqYhIYeU1fCPVnJpTFIKHaRUAkBCjRwVHAch9YYg1RMV6heWZ5e2fSnichEHc5D9Y8CIck8bVaqRMmlcpP2wLEY0VBVTOg+FMpRYCEMAeD7bkSTSMsEXspFXWMNfhMGKlbtAYFQlBBGNsxp510RaUug7HQQQZBV2AD3J2pqaQgrnkVHAQmI5kFwYGlKP9uZtzEuOREDVOimnyFNQ3NROFijBogwTCSquT0/hpxJ7rGqAUqLUViVVBDTwN7v1lkkvplWE2A/3EETcCnFmhst4Vw59dFLlzl4r562pSrl7zkiUUUig4rCKE8IGmJtGZD8tBx9pLDnQ3u63z26zU2RUXSygaSSOSINRI41mB2WFszGTKfxhzyYXN/CbEYcOArg0OqNGitUVq5Saa29ZmnTgysZSWmoEEcqLJlNV1nw55zcGev4oQCBUq2TMhQkDdkDKApERYAJqRAKsngninF+SFpB6wsLtkBYQFMRhVhCliskQIJakskQO/1VgETAFDbpJcJcxKJSYA+MijIiCQRUGKQiocP3ZamhhzEISisPR/lYMA9hAoxMKLBkEgjNo0s2GUA4QDOMREJZBOJbkKWPEjYAvhY52yn9pCRgBAZE3C3wg+Wu2x/j1NzeRA4oCcogxmI4N95AH1bHRH4iBxHYj8QQyTEhGpDP7efX7dcsWOEDBH/CPQBdOoh7464ObqDYEo3m4fjT4f9sExmpPjNLr+QwqJiGwkCUUDRVEoojRyphRQ1Cu8HhBD0ABFxLpSHgrr//WlGQEPnPN1R05W9XxHxge3t6+vov2Q+LGly2owd4FRKKiUJUEYo1Kqqoqul0FtaVys61uPTqvwXjvTW9K13cmkudNWuJtuVddXbFLu25CmtpZkhLFx3c7dX/F53GuhjGmUgwsqiWyxhaVGFB8M+hm7W5EVKf0NWftLr9FNFTs8Q9xxlYOnGip2MhslMINrLV7MQMMDRkm6AW+QwAtVFkFTCKhCILsMjNbCDhFHVzX/w31by4n1fkH3z9NU/rt+8LDVUGgB4/o0HB34WOPWWeqfsh2HYA1FSHsfwpjBPVIhy2JbvA5+cPYN9wuoQ88CEkYBAPni5wDxA+kNhT+Gg8t8/D1TZ5vS3vDMVqD88AhMSMjpoUPzfR+BkVCoT+HazqkMZ4e278bMLp5VjyXh4EjsWVamZixiKOwgslhAVCDaD78zBe0LJCzQRIjGcWj2bmZiTKBQgiRmx17cTQDy8C+H+sagxViKyJFwO4nUoNQvJ29PDORB4QQ6M1TmeNShWv2VD7P5sk84ml9szD/T9j1wzap29raMqf5e8itBSDZuwtmKq3DCWOLK4Id07+o+AGDqhkYnEa4EU9HPrtw/vrdpb2eNho5srFu8+UoeEbzluNXO7SUuS5ynN2SBMpkx2sfE9jNiHMDzx6iy7X1aAfT9p6T1nv4gapAheivfKwovalDcQAoPLy82vGrXLW6zKmIXXW+/Nr9cQbN1BeYXQTTCwZqlUBjaqlQFhsZbw3RReCiUSVQdunp0uM9yoebMwmgQSMUWNF5yCiHkt/lo6LmF64GIHsQ0u1Lk8kDM2YkQqu6rES2gpGEqUMKg2i279GJY5IcXQG/VWtsJxFyTp11KSrmJON87khUPT29JeQj3Cvv8Kt+YVPBhXe2hFICQBg2sziFCjwMC+g3QIEEYyERBMVAnSNnq3Q6eNy0dm7JSfdEj15rt5dKty7uyaZqupzW4+ukFlKEkEPHNN0lTvGriJo1JGS6nLnYI5kzCjlVEIYOAh9FzdL400jm59llINoe9siIRh7EKP5un6WqhQNV+kZGKWMFTYNi5FhuEoCQVqARhUIquzlA264hmxktsVcrpWktzdmx1Fbfmptt01qvt5cduvIIV2P7topEQBZ9pkNDuIaELInEn3w6lAydoyjdREQYwnUdMKNFFVAgXY8FKiGDaGGJ7jyphdc+yG+BpS+CljyeSc9gySce7x9lS7yHFr8+OVh464QkIQQpIqRGzMkTSWk1RlctphV4BFBvekUsj+UBkCPkqlwpES45BFZEIQ4R8XmMe7e8PdfB+Xk8rngfw84nMelTLiSDN2NOJvaZ3/u64Y/ixmSISh3hXdrniVcIeoLn7fX17VqNmzK+MU/ZHC25SQVhx+WsCGBJBsPo5EX9C2vjzCPwUzgQJIzA/gcen08u2rEfvs1JpADodMDtQXUIIO/LU4MIKty4IY+ZwA3n5VevD3vB4EoPH4fCIRIS9pHHE4spfulkIqsapjevtjxiLAhttK3WbLL8xU3I2STL9leDpeQX+9mD00yYoNUrwRARJi2XUBZKCRzLpkEmLiqRJ86mmmQODhvFKN1CkWmkWRaHSqy8LpMJlIKtaY44c1lrQ00MQ0H3SSHzBPcRPLwCFBQ8gPzi2Tq+P9WJiPyL3IanW+zB1hpNoP0BkQFsH0TEF/lAWoCB54hYiihgMNQQUOHlRNE/Jf0mgM8IkgTVSvR7TvDjiID7IHX8+BQGE3n0HtS6v2GASFHi2dkYFix23JBmBhaUToYxgmnTVOrREfXYOsIuDw4gjZfxko+JiTdVX21ZrzlN1T5ynjESRQkQ9cAwgoVCQFkA/gZA90GZT6l/KWyQWBe6pcKYUQOMMhg+r3Hoeh6EYCA6HRXBjUyxszG+GMCFH1uPmcDrtjj1ESjcIGlU0wAoVdQfYTws/sQ3vN3Z49JNDIJP6hQLGkM2TvBWpvF7J5Jt7N3Xyv3rH4aNubJqoR2cLAvev2TlM32ffS0cuMz4JSgIEO+q7NtYVDCwhWBVVFoTWXCwsMKXPHm6OYXoP+Cc2AkXqCJ6JUJbOUBDWJ7A5chIgwRRLGQIHZI1BUkdBVLVUq1VHwKtg3jH95VCXiEDSlUl7j0kFokg8HnUweZk0VuZUlropvt9XnvW+ttUbSlQ2JUZkyANbFokLG2TbUUiwhAiJAkijE6NZ9AQF/aP/wg0PW+FhzLdiQwEDnFT3mogFCh2Chs2/2q1fhmmqS1EjZtSK2mbTFplkmzBNGZXvvsr9ajI7x7ADwIQlCQzQ5AYH77UdglL7Tzh6GBIlEk29wu64uJmRYRSE4kwuSkdQLIIjPFMGNchexijQQQwJD02niWgJSZ0hpg/45j3QpDyvYe714HQP3Sqomba2rYoHUoB+JEPbE5Xju5PNxbpvFE51PLtOg26Q1KvRNQWM6Ck0PYRBtq1iYBPIe6aMSOiigCvr/N1b6OyRPvK+Jgxk6wAzMaHsCjyPX116Y7RsZoUVLEgpDc2KMxxmpRqBSl2yFyfChxFb5wuAQ3+fM6KwJuFCZilogJiXPrN6QoPRsaiEkjGAvgOztGQHmfhwDcv81X8P1PZrzZNrrc4B9x6BIYbmgd/Ggu3Y5gfxUvZLl+fn6ul68THOqPZThWRl2aX5d+F3mtMhodHIywaLSF+yvSkWuw5rRFOFm2VTdKLSYiFpYiVVDY1pFQQJCB/WOiCyny6wi44SOyzWHQMdOnSIDpvW3Zwm5Cvm07MwgZcxtTdk8TGtgg33VO9OWsdjjVtwyc9IQxro73wbzxfq9m1Ea1niSecqpAVIfBiHfGCr7jIYEClIt1mFypcWE0oLGG/A/SvAUZ7uAMVfIUemBAgO7zajRAm0fOJAXMHH4R2b8V/S/JqkspmUgNLKW1KKdPSY/+Pw+UMPT5Pty//oHhjhe7xdoJuLPIoUuHI2JHGoHNAkFUwd4SSCTNz6KPGE5QJPI7LKukiNUNCrKopaiicWZLo0Eozuqi3fLt1vfF0360uYo2+Cuu9N42qNF8pa67vFeHq5O7pkiWddWLhdmsU7qLnFe10gVE8fLeUt5u18ZFN2vXmyLpOp3M7buXJd9Hy9+Pbk1eLJaADIUSIogixGE0khkKs9f88MCw3m1zMqNFJ6fVvxT+P9mh8kV908SK2h3BHUSIeEHuSAiB1BkpOyTxJ0mYCK+BksoIvOfPpmHNQ00yJRxM9ea5A8jvonmKH8Sp+YwYEaBhUB9/3udA0nSKBv5AbOhW1ksiP169S55sPq0pTqQnh4HvGSosHAnNsgjEUgoeppYzDhlVVjIcsVbA5mYZIXKQtdgORFkSwxdaGgz3P42IgcRyaVetwJjIESCOZIJNU52gCD1y4QEid2q3qOs7SodMnTFXSdmnDHAPa8zwuc238w9C4nPMyngmKidBQHLx5/mm/WSa3ToLkLC0sxRAWcqfPAUOM8iCCEEhIkgIB1myCOEUaYpY05WQWyqVkI0CGKu9bWeWidTs4kKuwrX5ynyGFBgQpIYSENFR2eTeL0hJ3HHz8EG9vDQzhjTvs+7i/DjiQ2mwfEGXwqkcfPoFQxwNzQ2DBUGAsguBF7EHmvHeTSccY2ROCiiyq9+Ol0RlPTBvhjAfuJBdm2ytBSbRFUxkIGn+kSBTbvXl+MmNnlC7gHyLYqYwukGg0LT37HYl1vBMaH0e85FjsOup56BuQ4J1vGSQgwic/aH1fCUfUrkEu7uTdLl3UQ02kulFF1W5aubUbJmtlKRqkYqFNQSBE1ndUuYwbHuKmfmwTgEPnslBY+UUEBkMy4XIbm6TCFjM9biiZDBLmt8QzcjqIdpvUDj0k0kI1wH6KbWuhz8ls2Xiag5+cU+qCakHSNzExANFFAyGs3FgvLsj5DcWeUPGqO0xN8TG70vKgPK2VA54vUcCA8XII1grSlKp/CIoFJhi4NhAspyLtoZSt5t1+mGz1zjHhSUa3Vz8cNkDycqnUYWG1VwZO8TZDCSRdzSdfeN+835cq/mgoIzm2wtYObfjsumRCOawouPpxt0zqWqDBBTy2avSphBg08BcwrB1igMWMrAKypi0MMYftpWGaDRheaP3mWZdZpNMwz/uEo0GsS4RcsqWWz8KqosIYylSQ9HKzMGBlBEaurqrc5kxnBcWExMzMmDBQgm5oUYkpgzHeK63XWmum4vFcEE1lvfnlotCSaeY6grgwVLBGYFiHJl2SlFgWRsEZtGauguYhETCEVa1HV+FVog7bEO3USI3RSV2wKHKIfMSVVR5kV8u16tFeTV5LV40ZaW3LpQktVLpLA2JErBAgKkNJA+6ZZHa6PGvMLu9Vi/LY7F2Qa07EQwyuu6E6JSJk0qSkCzTWXLUcYqEinOQcUfWdGDSajRDzFUEj2wu5hF0sCabamIefAFA2bQwgCqcmEKYsRhbJqkCWOFQG1cis/SYGSSA3Ed45LiBdb3LLYElkCoUAmOzBc3GkLoLSzGeRxenpJXtT5zgGrIxkWCgjCzM8BJQwp2KKh+vIyuYYoVzRBkkIyTtuUPMc9twu9TJf009v2MXPJnqIFWGPIAzJD2GQvfQDVRvEqI4wpo0llkALF7WFLwWmXLm9abSXMk9a3WXrqWvLOrrelAM0VUosFVBDEHTIUMGRMVUwFeNTNtJkYZCixaNJjY00rWWUWr3da8ltuu7b70NCBSo7G4HOQDG4xSGmSGiDFIINoyCpJIqDoEzoEhC+PjxqfmoyB8mFgjMVB2B0wZCBDR9W4K/5kV4NEAgwA3xVtud8AMKGycOvb3IYB/QiR7136iRVk5MGMFiVrOfklJ669nf5LFiWIe5LL4yXQoJIHrGCMkIKCM9TTIe5Pu8dJ46hZk+SzJMhZsrQmAEpFtqE89SqtAqdO5oeIPYdfU94QqFHTRCxQdBUKWFIMSBV0TQvQuVDNDQQoYG/i+ae9q81XmpkRsrWpabLS1o2smo1JajFhyS3V6nUs0pObd1U111u7buq8zflvXreXa+XrvJozu5oxMJUpBimBTv4TUzqlHOTJDDfYDmhmprml9dksHxNKfkeGAnzoGPfVpKqtUpCH+EYiVt92mJprpef2jR/pzQbigiOiGWExEy4PtGjlHYYVUfGmcb5yu82CbuXsb0SzKE1RmsybNA4FhAP0kGLBZ+caDaw1HSm1qm6dFvTPEXZLtHI9pcgPrlHyUoZF6NBAYbm60CSZBtqDi4B0tj5YSLCYgmQH1PURJAAiZnv7GvsdtTLDGZO7W6k2V8bXzKVDoDQJkqvQalNiGnNBfyP5iB7j6S+31b7ZlpNtWKvr1llCSZRgjrP2+EcDiYJzZOLAweMrBdCgWOLew3SjKQYBJPnuWVD74oniuoIMgbILdYXT5UszpXiq7q7auuot1cmkWNeI2+5La3qmS1r02snSYWHAGB0QsEVchTfBfMoZmihIytDSoWiq2qlLqaksh80TNNEhAA3gack7ThRbCIwMw7DM+T7PEDw9Bg7GoaSxY3C3kFO7cBoIOMWFqTBxvi27EDFVgL6gx0e1jCUgMr+BFFqmqtg2it6WxJXrzqybTSrxa7u16a70QFc0AUCOyBQod1BmYm0IFBqUbNj3gOIfeEX/CjCEQaMC2iIHAhQXAuUQ2BU9Yh/U4hiLkEGgmSd21NEJEJAU6RU7iIK8CAKFAQFC7tiEN76fXRIVP6vh7p/G564ZRPZ9stC0CNRaYhemtdPGKOVfZt+a/SVMq7tYPy29sU6e6AL6IQiLUEP84q2iJZPLJPIv4Q8/zCMiTeE2EcqhUBGQKYGcLr6Z9VefK/m37MiTSSzRJYp8NSSJ5oFEHEPDxCRgQHTRmBpLlGmCMjA+N8VV0qHrXLYeQ/b8LBIKXhIdrTTKKO4+Mq/98q0JKgs+lpKgASwV97Slus9fusJUPRpKqfo4AHVtk9FBZfliSCGJbsO07ighKysfC1SBUoBvQqF29LTxyJ8DKosUycEzL/Xz/YYEfTAsV3IMn6I4sziwhF5ZEJmVsoweLaDKIdFMKs4DByUJFHIG1VIqyA+DkDdb5Y3gphoKoyGZCFmvBgdPcQDsTgR6ggUBBCx9a23m5rH04+wkAjCBc4HYJBPeWLEB1IvRHs/EH/CQebbsXmflxH9EkKJkdPgsxNwR1OyHdqjGQqhiqgJaiqrye6EVew5j9LkPBFBpQm2HUKclOwgEel3in6RSi52gteiSCM71doRTeoZhbO0mkOGnYn4fj1ueaTTEH+LObke85zhCbqyDYNdOJTk3PUizHXtCbUxsbCflumizhHINRu5jnKWQMAivVgI3UekNtD+8i5Dv2nfgwQs1FUVJFkUkSa02WitKa2LYyK1qQmKlmbYbRYk0mj9X3fH3p38E7rPmO/Ddd6fx2WXSNOYh+zznh20QlCpCiFcicHEhzlBxSG3dQXIaKBpPEjg4eyynHvzeRvBi4ov6mnLSSz/5Vqi3gu1FUc3r8qvMyqJ/dNbtwlK1tV3oIaYRpHSzOKqgwrBYbpum7sjN9dbxS6yotOxA/trmGT+eTGXtZQ1lFby7RjI+q3cMTKFi1a16GigqDUAgEIu0ixWhGjpJ/Q7ebm5vMDZLCHSDEDSEKYAQIQSmJZBwfOaNUIkLObXxMKIXAoAuIFtiFDCaCgIQaIJMAv2jDwl4o4B79+HkDBKmHpH99Hub3nZMhIMGQZCfHD2V72WuUNe9awhQh+gGOs4x2LDns/oFgXJt7YNKzlyY7Xwl5E+qLy2v6EvBU6vsJ/IgwWPnJ9pUDBNeztuQ6rfOxRYcRj16l1x+gvEmi9hkHULcOg7+1JBv4T1E9mDVFVRH5JjJ11l5JRoURvMBFJVRrUsWhKLuyLBAbaEiPqy8KsMmpeuuQDIgUhGZeZ3lxWlrd2xcxpd0lJQqMoQpKGrZKlJ2SyBWditTAPxsLLpVTHVWSqouMtFNNME1WiARTDKcGTJfQnEIzzk9eMytwnRd62ViWZqLOLxNGBpBJChNEhRRcsGKDZQuMBgxRhJLDDhBAsbrAIxQQ6qndctljeFBpiQdKrgxM9/4NXwIMIECN9FMosxaD7wgn0kYR9av4EBAwADs08odW2i0kvtLX4ZJtHRIbXiFoBpDBOgadv3qFwgaiIiYK8RWxQJsVSiifTDjpz+fqelDQYuYhpRdIVChAhcSBCmpTYIMQ5+wXViLbVYYoKBKjZhjgwUICQyCExSkHvOsR3BDRWAg7qm5L2UoU+lDeL3UAYS1FIUMD4HYHIAwHn9idPK5uIPE75CRHfvKTgysNBO/X1k2EhqNAYpwieBOYDm+O1JIe2E8tmweemh8Snu0cz5B0M/X00fU6GqoRpMQB73LONVBVda0DiWCDUmHQc6xOQxIph4vAwaIHGxBnEAqo5dPKIlbdjpAmx0xMRbB9mFXQUiCGKk5BuFE+n89aLZfxkxKTd6j19J0ptuwpKhcggr72z537ixwIzvf7SBthTA1QuyMZ2Bos5aq4RfthT1Q29V0O5XSMkBmL6snRYqCNJ53XPuoxwoJrNKCxlJBcvWrs2Q+fTYvFVVfnoxhlCIlKjBpt/cgcX/1RRpptpOqaMiHHI69qq/aX+N53JMiF+AE9LQdJ5DzhQeIgPsCF5nuszpJ9dyG+MSHuw1tKlI3VEVFYIwaYjQRAzFEC5QgZiB7VA/Uwk7j8sgNKGmLDSB8UUIMUZBskQIHZsoBwBiXagikisfOAFbUg/OaAMoCaYRiISEIe4UP1MNu6Hx9Obuk7uotaHNqD0IKfZw9IdJwNjoDTOXOoPwgmhDpC481erFTURtpNreeXJM0LEuyvMoRwiBSVTdqEpkpKUiEIFFyolCEBqhAgo7MBQwUuwLq3NctRW5Wupu67btpVsm2NIXLd1O0a2NrWIxV227LjdNdpqV1TK6tNGvtWtdqS2NM1KvN9lfbstTVimRA0m31NPxwXhCJBtHyFJa1MDylFaNww+N8zmOBoo61Yc+g3aKGRlTEAqi4JPI+2XmJ/fP+9ErdaeiMSZ9h4S0o58vzO35FbF2iB3TrRbpuShOi0RWUGGWGXpS3p6szEn6sn7j2b7ydE9gcRi4YQPd2kuaS/HyBmcY5VmaKciTjEJtLTqTn2J2nVkiE3M8JaSHHcdvZdmofi1y9RJ5tVtuWfXktZlLlNc1kCiNTRRggY6PwMLqm9UVFrcFK0eBioX6w8iZQdZGoZybDsKabUbTODLTJaBniaYxLG1G2XGAFrQuhnMHYCGZvxVl1yiGtEDAJo4VeCqmivsuu+bIgOyODL5yaJU7MV7gfy4aWVj1PPLHVujmkcWQW7LMOsdYyZC2Yd6+gPiN1x4RpZe927Vk3bleHUPGkT2HfVjVaWuqSGlNNqmjV6qaUt1UzX3LyNMEdHkzSqoM1VZssyOnsXEM6bzMN3kUqF/hJK99983S9RC+4UoMgZF1VqHQofUu9CBQv0pVBl41Hl5xjWpo1iGoL7yP2/bcMtnRoDeBYa5n5Xq/NzoB+ZlTCPq9WtQMdPqWUHU0Z9YA+fAYT+2F5YtFInxKIhopjjPy2cd4X5KI+ch8NZ9TiZTVTw1rTY2tDYuAUNEMHSl76mUmQmEVDJkQzMwVjcEgcnOAuRYHgSE4XiQfr9RqYNjiFAgnP62c5uXjwzQrSQGyFXeY7UpuoO78gZWkuWsowHu4PDoVHUUNozZ7fV1vHGT0Ei0wRzaMSi+b/8/U7rWM6m5oumlBm5RVE9DgbGumRO1oUcsVSmS6vW8rzmyrahBZOJkISaeBOsjscvWUG1XyaQOhX6d15qpQpeb1nzlSiS0fGC8PMsQrgp4xseGqwgWQSEcCOSEru6n4n6ojz0DY4BBgmm/2EuKR4LWvhZVu+9j4StmdsvZ+7oLhmbqse3Ac8lCPwWKPrTA4MIyoONcNuAmqu3cZTsAQ1sMEuxUmYbaGO0IUGXDJZV4y2n3TJcLhUPXC0oqaJUFUEppUeXdqL33aNZ56q78WdNiBpkzawBSFtkwE0sCmOkiZAZKBoaDQHrZvIEi83Gizag63z59RA0G6naNHLRsa2n6jqUaGgVyEQhDvqFEZ990Lfhd2ymUljKqoR/LihHOJRHJFWIy7q4uUy3pdu7YrvLrkcxcjKrBQBQWjj2RxhMSrXJRSiK1iwtW5B02PC+uXM5vKsSRhyUfr4bKsxDMwo4iF2BFmFu7qoqgqi+ii6xdwaY5VOVqGAZhJ815LFWX3Aek8j5MOelngTfwlCN+h5RhFA0RwYjdTIvEJCgpquvwrVId9jtxcpjMbVYCywnf7mJp9CA8BdikQk2NZtZCLASwUfaMgdyr5880xZ8fbkt0KShWKsc1pghWmf3NqYdDXTJo92oiOpfCdCHgyRGEYYKkcKw6hadlJGIIWXA8QAthKJpUDvNrwe+Bt/F3u2Tgex6amOQDkuZD4qKIZnGoH8oc4yMvc5TJvKWQ9aFnj9FHmd1aVKMpUJ76w2Q7WZmpQrycTYI6rmzQJc21Mq114xywUMHITUUkYoJPlCnnlfj9a/PL1vWusl0unNc1aVspUqGMCCPGgpUmSQKkuBdSFSPyL81iplqvbRl0eKiAlGGmGJC8ymqsRao6KmevPF5xDuSS3ncu6u1vLqS2EtIFMApuxuyQCkLUkzGoJEmgh1KAN2dLLnZGhFpK51H11OxMISwB8dfSbPZV2ttmitmCuqq85eRtnBWqVdfLXeAR8drmwu93a8fF25uzkECnZEb0iVFFxRSJQjxPt6h0BjFAo1PwzAZiUCQD6DA9F7vaP9QCL1F2pMm/Uy9c3RiFIXR3ppD8WfKw3lhhUuzC3urS5AuBiQ4hku0GMjIrbJn4Sp3s+APMeARlzp54zHO8Ak+60L1mpOt7JYMOaMPJoZA+H5QYIIWHNmmvsq/0JgwiwEQxE0Q7OOoY1mRAR3OwQyA6bjw0W3V4zlM3tR5ko8avObo4DnQ9lG1wt7bjj2T39hlRlktSvLtZsO3CzzeHmXRaCmbh6Lz1kyt4D7aAR4YfcAEUYpteaqPPXmI4Nk2G6C9Izg/uZYiZVJKpkC6XNXveIInoZ1rBDTCG3WueDVjowgiJPyMOxstmDuPo5ujBx5HFmhd8syPk4Cys6pGGQ75Bl7wcXRvHOC0G0B1azxowu7u+t7LxRodcTFaXbOSTtWg1VBnHE0s62MZl3qEGg41liJjQQVRcWNnFVIrnFd2FmcFYM4xjvknKs0XDQLOmX2o48LLKQVh1riJHbWM2J9UqrSKnMlawZOqSdDpGxwMBlUOk+hXyyw0qmdyjkwIEFeJtOl1Mi/XQoWcODwssSH+T2Nii1WBslsVMWCQgClEQKgBoIrRToEhhrudMU2Iby3KsRoEKmNMoYzFBA3bCZZQGFTIOlKYytpCNErCwqtNMVAzEcUlDSO7N2G1uDbSXizMzE95A+9pZ8Ng6/1/X0g/ZUrgRWpnnHBKaQNSBFlrFR/U1d1A890FBCBMERfk0wesa351i8L3wXvewKx+cMsQTUIOZtjxrfy8blTWsIyfObZPWVLYW1m9xDsMnJzTlJxVCtZqmgwYDGaoNUMYbmTWiCmMEosLLygoxCUkZRQWk8AxgRk5lKWQQwQGDuTZusB0UigdIq68OsCibtbGuVC43Uq9OlDmorvi3ME7Xn2ZxfHaPeONYmmPPR0UBq6EIK3QizAMMFFWEpojJGS8hcoYYuAcJrduZhwDitM41MDSCZ+tI+4iGZgoMiEsIcYaqm8GEE9enh48bOnIOIITgFQ2BhHlxC2MRYM4mOyMQSYDTTN2CoimRhZpLySyNhgMGDgXHBLFFxi4ttgXDs7/cba4iYOTaADbbv9eA2eHmd3prIoO9kSEbmTGoUHmh0xsOZMSxFSulRIJY5hDoxQP3PKnRqoLyERZFAzTSWLDoMDHjiYLyXqeQN3MyNBkqGJFAoiC5ZE2VKKKhNhTVqKoQuiyze2sRgWLMYqWKoDIjcqjvWu1ddumpjY2B0vLvElu4xIgWWyYYVVXFWAFwllSmAwslyWWEN4biGpxrBPVOmpufDjcRlplIrY0JJMZBUQRimWhUI6bu24BJDUvQa5ZwbFANRkxgx1lmmmqfg02knKvlBIsEgkTLzCVkDhshUHYroZI9bplOpYztDgmTiP5GCKPHY+/jRxFUk7kQQYiJQRaKPpfHNTGSkuNDEL9VUIYAHAPqVC1GvQo7oMIkwdCRnDvwWZQrdnKwmFyrJg4SQ595yMDgoGoYAfTFBoUqIiUTwi0hmAo0Y5lFF6Uuhc/soumF5zl1F9+V1Buim3ANka8OnjdwDChdW4JB0nTfGxcidwA4vG/XTHaZ8yapYxuGx6u4KswVCdQNekBqkIYmWZNSBIqXajbTs7HZ37q4S5CYMKSYtyyMHzoFVkQsFVRYDURpktu7q4WypIUFMYjAxirEERKIGDSwoQZiFQS7TBJiI2MxUaAH2HM58fI8f29vuTRTSd9iyjJi6KFG/7j3pkcNOlMXSy4E5BOwEJ1kJDqSKcbtTcesAMDMMUg9ENkAHoijqIcqPNVVX7/AowIJBRzJr8JalOlGS59SZdX5HLWzI8DyqVVQM3SqKsOIiBRRCJyIWA2CFJ7lpKPWcxXaGerVedNbGSXloY+s2KOgIJZR1SiyPbiZGiFdQeATeEPHAWcBBGRQQEikGapLSes+4035SDG7niAaekoTCAJuUiC5CFk8zuJwh9/8WTu9vwo9LiUMoVS7XjgbKH3nv+JcxmVRkotB7cYcYhQrDYLl2ywUSBbVO3mVAtFJBaJgGiIbJKuAWwaKGTDHEBJiZaJlSmsVId9Fc+PjtmB6zs1hLhEkGlWnrqrE3A0gHtHcJsB6QxVvrnBBsKJaIkgZARCk3gc25LGOubqWoFHR1khCGNGPdVyWPJyFTuX5vQiUnACQnVCWXrVTn6YGbwK74AaBNO0ECcCCcLhQiZCiBUjFIoLJmRaviXMW9Lu7mb52avXa/Z0IREkUG/mzIh0kXexsEMAcgMvYPvwRNyDsFDUTdi5gnZEWBCRYfOUAsIO8X9+eoB8JALqYOlClP5GLpqiENZJ11y3XdaXdt9+7X3qVNW91hfIHxVKD1VYe/wpieeUHuhUX25V7PRYsHz0ZEvcVqisXXy69sGRGFuOp7sSMX+IiQuzgkyMN32AeQBrLA+oEYkLNghPXIqvXiXTKvKwCSyQblWJEOpbrA0dE9EupPSQlPwYhn3f4j2mMIPVIEzBg6jazLRiEdpfWqj+mE33DgocCZ99ZEjCPeazxHEIkOPCt8DcEUMHmWsongFtRufE+2eV35/iqvhNA64u3Jc53bcv+Hm3RaKTJtrGlpvhWW3fg3VdaKkAbMtIM85tdfPu+4ghCGaJlgV+HdZPD0c1pi13HTR9M/MGA/EBsGD94RWRByOw8CcOXADvRZyolB8ocicqqqqj7EpUhbKVoSRI0FA0muumi4AY+Efw1FFoaZxYbiDmeNYBFeyQqgk3pPr+qj6Lhgm0u6JB9ogNoGHCQ4SN5vYfPc5PA2swXEzJDCju0HrCw56MqLH4EAxYGY0mS2tBELD0P0BNZwQPa/XN5sHwDYyQPSM+0yiJQMGkpQMYFyKlhnJ0UJyh/X3V1/o8J5ssITu/jzOVndyrRWlG/EA+WhiRXtK8SivKmBNrDKhw4lyltZjwKR/uIYXpIkDyfNYNRoquo6DxDa6+3yNpKWPhIS8DQwboeeiBIRbNUpVCoq6bauXjbXkvvoYySQCRUJAbxT1PhWVhoT5rFzxwFM2lQrVV8X9sAda+rgLLEcHWX6pyc6xpo+wR9I7sEUdrXyJ4PQTX+Y7QfmMqhdNKz4N8xB5IninXJD9J3qrj4XInEVpnn0xKiCGgS0shbpQQ6FShKgN1ZlnM/ZmZnRBqsMj1qKVgzGOQoxRVmuJiYUDkbg9pLhZIvMDA8+TdE8z9kMUQOOtE0X1GQaZSmZcGEFGkgGpzOWrNFLh/qOwTMgBqadnt+MHlI+cN5IS5jZEiF5uAhH+ib7IdvYnOJPUfcF7mB9kr7yZQdEW8xDSBQhe55CHH3nxTDo9v895Eo95Yodne0zOpfC7+ry/5l8GcP8i5pMcfSaDWTalUHHeOiM/+UP8z2+n/zP/ou5IpwoSDEP2S4A')))
\ No newline at end of file
diff --git a/cp/project0/unitgrade_data/HelloWorld.pkl b/cp/project0/unitgrade_data/HelloWorld.pkl
index fc8d10fedd5b66f54ae3acf93d6e4667ec46c7b6..1fe24a64a268a0c52c8ea31c7d624c7d7b197293 100644
Binary files a/cp/project0/unitgrade_data/HelloWorld.pkl and b/cp/project0/unitgrade_data/HelloWorld.pkl differ
diff --git a/cp/project1/project1_grade.py b/cp/project1/project1_grade.py
index ac8cb425130fe1993b3ca3a0410d7723191c4e6e..889b67b028f4995c9a4ad51a082f4e53b16b0463 100644
--- a/cp/project1/project1_grade.py
+++ b/cp/project1/project1_grade.py
@@ -1,4 +1,4 @@
 # cp/project1/project1_tests.py
 ''' WARNING: Modifying, decompiling or otherwise tampering with this script, it's data or the resulting .token file will be investigated as a cheating attempt. '''
 import bz2, base64
-exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
+exec(bz2.decompress(base64.b64decode('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')))
\ No newline at end of file
diff --git a/cp/project1/project1_tests.py b/cp/project1/project1_tests.py
index f332ad10a9367e4358e22647efdcced8f9768d23..b2804eb56c6df4a32f5d5c1aa1062e20c351d79a 100644
--- a/cp/project1/project1_tests.py
+++ b/cp/project1/project1_tests.py
@@ -7,83 +7,79 @@ import unittest
 from unitgrade import UTestCase, Report
 import math
 
+def string_fixer(s):
+    return s.strip().replace('  ', ' ')
 
 class TestNormalWeight(UTestCase):
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_normal_weight_01(self, mock_stdout):
+    
+    def test_normal_weight_01(self):
         from cp.ex02.normal_weight import normal_weight
-
-        normal_weight(1.47)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Normal weight is between 40 and 54 kg.")
-
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_normal_weight_02(self, mock_stdout):
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            normal_weight(1.47)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Normal weight is between 40 and 54 kg."))
+    
+    def test_normal_weight_02(self):
         from cp.ex02.normal_weight import normal_weight
-
-        normal_weight(1.96)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Normal weight is between 72 and 96 kg.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            normal_weight(1.96)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Normal weight is between 72 and 96 kg."))
 
 
 
 
 class TestSurvivalTemperature(UTestCase):
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_survival_temperature_01(self, mock_stdout):
+    def test_survival_temperature_01(self):
         from cp.ex02.survival_temperature import survival_temperature
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            survival_temperature(186,0.15)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Survival temperature is -5.0 degrees."))
 
-        survival_temperature(186,0.15)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Survival temperature is -5.0 degrees.")
-
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_survival_temperature_02(self, mock_stdout):
+    
+    def test_survival_temperature_02(self):
         from cp.ex02.survival_temperature import survival_temperature
-
-        survival_temperature(356,0.33)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Survival temperature is -7.0 degrees.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            survival_temperature(356,0.33)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Survival temperature is -7.0 degrees."))
 
 
 
 
 class TestUnitConversion(UTestCase):
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_unit_conversion_01(self, mock_stdout):
+    def test_unit_conversion_01(self):
         from cp.ex02.unit_conversion import unit_conversion
-
-        unit_conversion(4, 3)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "4 ft 3 in is equal to 130 cm.")
-
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_unit_conversion_02(self, mock_stdout):
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            unit_conversion(4, 3)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("4 ft 3 in is equal to 130 cm."))
+    
+    def test_unit_conversion_02(self):
         from cp.ex02.unit_conversion import unit_conversion
-
-        unit_conversion(7, 2)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "7 ft 2 in is equal to 218 cm.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            unit_conversion(7, 2)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("7 ft 2 in is equal to 218 cm."))
 
 
 
 
 class TestHadlock(UTestCase):
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_hadlock_01(self, mock_stdout):
+    def test_hadlock_01(self):
         from cp.ex02.hadlock import hadlock
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            hadlock(35, 36, 12)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("The estimated fetal weight is 5820.8 g."))
 
-        hadlock(35, 36, 12)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "The estimated fetal weight is 5820.8 g.")
-
-    @unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
-    def test_hadlock_02(self, mock_stdout):
+    def test_hadlock_02(self):
         from cp.ex02.hadlock import hadlock
-
-        hadlock(28.6, 29.6, 6.3)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "The estimated fetal weight is 2070.0 g.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            hadlock(28.6, 29.6, 6.3)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("The estimated fetal weight is 2070.0 g."))
 
 
 
diff --git a/cp/project1/unitgrade_data/TestHadlock.pkl b/cp/project1/unitgrade_data/TestHadlock.pkl
index bd6d3bea5842c62ce2b3a59f1ea42b8b4f17084d..2fba0f0ca9fd6d993b77665a9ae8d744424eb469 100644
Binary files a/cp/project1/unitgrade_data/TestHadlock.pkl and b/cp/project1/unitgrade_data/TestHadlock.pkl differ
diff --git a/cp/project1/unitgrade_data/TestNormalWeight.pkl b/cp/project1/unitgrade_data/TestNormalWeight.pkl
index 7f783c62a67482415947e1ceb6d43139beca2851..11dde91630a70bdf4279a26ec1485a372b7999f8 100644
Binary files a/cp/project1/unitgrade_data/TestNormalWeight.pkl and b/cp/project1/unitgrade_data/TestNormalWeight.pkl differ
diff --git a/cp/project1/unitgrade_data/TestSurvivalTemperature.pkl b/cp/project1/unitgrade_data/TestSurvivalTemperature.pkl
index a19c6d7dcf47b46034fd5f5cb09a31ce7f4f0a19..b7de549eca45c1eeacef170c0904d8e0a3580356 100644
Binary files a/cp/project1/unitgrade_data/TestSurvivalTemperature.pkl and b/cp/project1/unitgrade_data/TestSurvivalTemperature.pkl differ
diff --git a/cp/project1/unitgrade_data/TestUnitConversion.pkl b/cp/project1/unitgrade_data/TestUnitConversion.pkl
index a5366c9ce746caa0364e3ccedf9c1c52ac690fef..e694ca2907da1d7d27d0c7821fc0518a1b85502a 100644
Binary files a/cp/project1/unitgrade_data/TestUnitConversion.pkl and b/cp/project1/unitgrade_data/TestUnitConversion.pkl differ
diff --git a/cp/tests/tests_week02.py b/cp/tests/tests_week02.py
index 807029cd70fd8b04ddb6d0001001d39c1503f87b..aa5d8e3fb6bef03847ab18a4f9885100ffce2512 100644
--- a/cp/tests/tests_week02.py
+++ b/cp/tests/tests_week02.py
@@ -4,97 +4,100 @@ from unitgrade import Report
 import cp
 from unitgrade import UTestCase
 
+def string_fixer(s):
+    return s.strip().replace('  ', ' ')
 
 class Week02FullName(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_full_name(self, mock_stdout):
+    def test_full_name(self):
         from cp.ex02.full_name import full_name
-        full_name('Donald', 'Duck')
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Donald Duck")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            full_name('Donald', 'Duck')
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Donald Duck"))
 
 
 class Week02NextThousand(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_next_thousand_01(self, mock_stdout):
+    def test_next_thousand_01(self):
         from cp.ex02.next_thousand import next_thousand
-        next_thousand(123998)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "124000")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            next_thousand(123998)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("124000"))
 
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_next_thousand_02(self, mock_stdout):
+    def test_next_thousand_02(self):
         from cp.ex02.next_thousand import next_thousand
-        next_thousand(-123998)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "-123000")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            next_thousand(-123998)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("-123000"))
 
 
 class Week02NameLength(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_name_length(self, mock_stdout):
+    def test_name_length(self):
         from cp.ex02.name_length import name_length
-        name_length('Anita')
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Your name consists of 5 characters.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            name_length('Anita')
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Your name consists of 5 characters."))
 
 
 class Week02WindChill(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_wind_chill_01(self, mock_stdout):
+    def test_wind_chill_01(self):
         from cp.ex02.wind_chill import wind_chill
-        wind_chill(8, 12.8)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Temperature: 8 degrees feels like 6 degrees.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            wind_chill(8, 12.8)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Temperature: 8 degrees feels like 6 degrees."))
 
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_wind_chill_02(self, mock_stdout):
+    def test_wind_chill_02(self):
         from cp.ex02.wind_chill import wind_chill
-        wind_chill(8, 25.8)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Temperature: 8 degrees feels like 4 degrees.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            wind_chill(8, 25.8)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Temperature: 8 degrees feels like 4 degrees."))
 
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_wind_chill_03(self, mock_stdout):
+    def test_wind_chill_03(self):
         from cp.ex02.wind_chill import wind_chill
-        wind_chill(-2, 12.8)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Temperature: -2 degrees feels like -6 degrees.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            wind_chill(-2, 12.8)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Temperature: -2 degrees feels like -6 degrees."))
 
 
 class Week02NormalWeight(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_normal_weight(self, mock_stdout):
+    def test_normal_weight(self):
         from cp.ex02.normal_weight import normal_weight
-        normal_weight(1.73)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Normal weight is between 56 and 74 kg.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            normal_weight(1.73)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Normal weight is between 56 and 74 kg."))
 
 
 class Week02SurvivalTemperature(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_survival_temperature(self, mock_stdout):
+    def test_survival_temperature(self):
         from cp.ex02.survival_temperature import survival_temperature
-        survival_temperature(200, 0.1)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "Survival temperature is -27.5 degrees.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            survival_temperature(200, 0.1)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("Survival temperature is -27.5 degrees."))
 
 
 class Week02UnitConversion(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_unit_conversion(self, mock_stdout):
+    def test_unit_conversion(self):
         from cp.ex02.unit_conversion import unit_conversion
-        unit_conversion(7, 5)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "7 ft 5 in is equal to 226 cm.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            unit_conversion(7, 5)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("7 ft 5 in is equal to 226 cm."))
+
 
 class Week02Hadlock(UTestCase):
-    @unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
-    def test_hadlock(self, mock_stdout):
+    def test_hadlock(self):
         from cp.ex02.hadlock import hadlock
-        hadlock(31.1, 30.2, 8.3)
-        out = mock_stdout.getvalue()
-        self.assertEqual(out.strip(), "The estimated fetal weight is 2990.7 g.")
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            hadlock(31.1, 30.2, 8.3)
+            out = mock_stdout.getvalue()
+            self.assertEqual(string_fixer(out), string_fixer("The estimated fetal weight is 2990.7 g."))
 
 class Week02Tests(Report): #240 total.
     title = "Tests for week 02"
diff --git a/cp/tests/tests_week03.py b/cp/tests/tests_week03.py
new file mode 100644
index 0000000000000000000000000000000000000000..7f9920eaa9766f57448319d833e4f744bf5fc8f7
--- /dev/null
+++ b/cp/tests/tests_week03.py
@@ -0,0 +1,195 @@
+from unitgrade import UTestCase, Report
+import unittest.mock
+import io
+import cp
+import math
+
+class Week03BodyTemperature(UTestCase):
+    def test_body_Temperature(self):
+        with self.capture() as c:
+            from cp.ex03.body_temperature import body_temperature
+        result = body_temperature(34.5)
+        self.assertEqual(result, 'Hypothermia')
+        result = body_temperature(36.9)
+        self.assertEqual(result, 'Normal')
+        result = body_temperature(37.2)
+        self.assertEqual(result, 'Slight fever')
+        result = body_temperature(38.5)
+        self.assertEqual(result, 'Fever')
+        result = body_temperature(40.1)
+        self.assertEqual(result, 'Hyperthermia')
+
+
+class Week03CompareNumbers(UTestCase):
+    def test_compare_numbers(self):
+        with self.capture() as c:
+            from cp.ex03.compare_numbers import compare_numbers
+        result = compare_numbers(5.,3.)
+        self.assertEqual(result, 'the first number is greater')
+        result = compare_numbers(2.,7.)
+        self.assertEqual(result, 'the second number is greater')
+        result = compare_numbers(4.,4.)
+        self.assertEqual(result, 'the numbers are equal')
+
+
+class Week03BACCalculator(UTestCase):
+    def test_BAC_calculator(self):
+        with self.capture() as c:
+            from cp.ex03.bac_calculator import bac_calculator
+        result = bac_calculator(0.028, 80., "male", 2.)
+        self.assertEqual(result,0.02147058823529411)
+        result = bac_calculator(0.021, 70., "female", 2.)
+        self.assertEqual(result,0.020545454545454547)
+
+class Week03Ackermann(UTestCase):
+    def test_ackermann(self):
+        from cp.ex03.ackermann import ackermann
+        self.assertEqual(ackermann(0, 0), 1)
+        self.assertEqual(ackermann(0, 1), 2)
+        self.assertEqual(ackermann(1, 0), 2)
+        self.assertEqual(ackermann(1, 1), 3)
+        self.assertEqual(ackermann(1, 2), 4)
+        self.assertEqual(ackermann(2, 0), 3)
+        self.assertEqual(ackermann(2, 1), 5)
+        self.assertEqual(ackermann(2, 2), 7)
+        self.assertEqual(ackermann(3, 0), 5)
+        self.assertEqual(ackermann(3, 1), 13)
+        self.assertEqual(ackermann(3, 2), 29)
+
+class Week03Exponential(UTestCase):
+    def test_exponential_with_positive_power(self):
+        from cp.ex03.exponential import exponential
+        self.assertEqual(exponential(2, 0), 1.0)
+        self.assertEqual(exponential(2, 1), 2.0)
+        self.assertEqual(exponential(2, 2), 4.0)
+        self.assertEqual(exponential(3, 3), 27.0)
+        self.assertEqual(exponential(5, 4), 625.0)
+
+    def test_exponential_with_negative_power(self):
+        from cp.ex03.exponential import exponential
+        self.assertEqual(exponential(2, -1), 0.5)
+        self.assertEqual(exponential(2, -2), 0.25)
+        self.assertAlmostEqual(exponential(3, -3), 0.037037037037)
+        self.assertAlmostEqual(exponential(5, -4), 5**(-4) )
+
+    def test_exponential_with_zero_power(self):
+        from cp.ex03.exponential import exponential
+        self.assertEqual(exponential(2, 0), 1.0)
+        self.assertEqual(exponential(3, 0), 1.0)
+        self.assertEqual(exponential(5, 0), 1.0)
+
+
+class Week03HeartAttack(UTestCase):
+
+    def test_heart_attack_low(self):
+        from cp.ex03.heart_attack import heart_attack
+        self.assertEqual(heart_attack(25, 55, False), "low")
+        self.assertEqual(heart_attack(16, 45, False), "low")
+        self.assertEqual(heart_attack(30, 58, False), "low")
+
+    def test_heart_attack_high(self):
+        from cp.ex03.heart_attack import heart_attack
+        self.assertEqual(heart_attack(45, 70, True), "high")
+        self.assertEqual(heart_attack(11, 70, True), "high")
+
+class Week03SolarPanelTests(UTestCase):
+    
+    def test_maybe(self):
+        from cp.ex03.solar_panel import solar_panel
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            solar_panel(True, False, False, False)
+            out = mock_stdout.getvalue()
+            self.assertEqual(out.strip().lower(), "maybe")
+
+    def test_good_luck(self):
+        from cp.ex03.solar_panel import solar_panel
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            solar_panel(True, False, True, True)
+            out = mock_stdout.getvalue()
+            self.assertEqual(out.strip().lower().splitlines(), ["haha", "good luck"])
+
+    def test_probably_not1(self):
+        from cp.ex03.solar_panel import solar_panel
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            solar_panel(True, True, False, False)
+            out = mock_stdout.getvalue()
+            self.assertEqual(out.strip().lower(), "probably not")
+
+    def test_probably_not2(self):
+        from cp.ex03.solar_panel import solar_panel
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            solar_panel(False, False, True, True)
+            out = mock_stdout.getvalue()
+            self.assertEqual(out.strip().lower(), "probably not")
+
+    def test_sure(self):
+        from cp.ex03.solar_panel import solar_panel
+        with unittest.mock.patch('sys.stdout', new=io.StringIO()) as mock_stdout:
+            solar_panel(False, False, False, False)
+            out = mock_stdout.getvalue()
+            self.assertEqual(out.strip().lower(), "sure")
+
+
+class Week03TheFunctionToBisect(UTestCase):
+    def test_f(self):
+        from cp.ex03.bisect import f
+        self.assertAlmostEqual(f(0), 0.1411200080598672)
+        self.assertAlmostEqual(f(1),  0.4871688735635369 )
+        self.assertAlmostEqual(f(2),  -0.9484917234010158)
+        self.assertAlmostEqual(f(math.pi), 0.6145000731172406 )
+        self.assertAlmostEqual(f(-10), 0.244199939520782)
+        self.assertAlmostEqual(f(117),  -0.9996260520700749)
+
+
+class Week03IsThereARoot(UTestCase):
+    def test_root_exists(self):
+        from cp.ex03.bisect import is_there_a_root
+        self.assertTrue(is_there_a_root(1, 3))  # root exists between 0 and pi
+
+    def test_no_root_exists(self):
+        from cp.ex03.bisect import is_there_a_root
+        self.assertFalse(is_there_a_root(3.2, 3.8))  # no root exists between 0 and 2pi
+
+    def test_root_not_found(self):
+        from cp.ex03.bisect import is_there_a_root
+        self.assertFalse(is_there_a_root(1, 3.5))
+
+
+class Week03Bisect(UTestCase):
+    def test_base_case(self):
+        from cp.ex03.bisect import bisect
+        self.assertAlmostEqual(bisect(1, 3, 0.1), 1.8125)
+        self.assertAlmostEqual(bisect(1, 5.5, 0.1), 4.0234375)
+
+    def test_tolerances(self):
+        from cp.ex03.bisect import bisect
+        self.assertAlmostEqual(bisect(2, 3.5, 10), 2.75)
+        self.assertAlmostEqual(bisect(2, 3.5, 0.1),  3.03125)
+
+    def test_no_solution(self):
+        from cp.ex03.bisect import bisect
+        self.assertTrue(math.isnan(bisect(1, 3.5, 1)))
+
+
+class Week03Tests(Report):
+    title = "Tests for week 03"
+    # version = 1.0
+    # url = "https://gitlab.compute.dtu.dk/cp/02002students/-/blob/master/cp/tests"
+    pack_imports = [cp]
+    individual_imports = []
+    questions = [
+                (Week03BodyTemperature, 10),
+                (Week03CompareNumbers, 10),
+                (Week03BACCalculator, 10),
+                (Week03Ackermann, 10),
+                (Week03Exponential, 10),
+                (Week03HeartAttack, 10),
+                (Week03SolarPanelTests, 10),
+                (Week03TheFunctionToBisect, 5),
+                (Week03IsThereARoot, 15),
+                (Week03Bisect, 15),
+                ]
+
+if __name__ == '__main__':
+    from unitgrade import evaluate_report_student
+    evaluate_report_student(Week03Tests())
diff --git a/cp/tests/unitgrade_data/SayHelloWorld.pkl b/cp/tests/unitgrade_data/SayHelloWorld.pkl
index f1073128438caba5ca4c91796365aaeb70179020..51b96574301062d2f60fab3f3ce6cc9c4f6a1187 100644
Binary files a/cp/tests/unitgrade_data/SayHelloWorld.pkl and b/cp/tests/unitgrade_data/SayHelloWorld.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02FullName.pkl b/cp/tests/unitgrade_data/Week02FullName.pkl
index 3699c7c81c59fd295b016b9c9dd343dc10e103e1..04d1b625bb6fff66ec99df4f6ccb9c925d7d57c1 100644
Binary files a/cp/tests/unitgrade_data/Week02FullName.pkl and b/cp/tests/unitgrade_data/Week02FullName.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02Hadlock.pkl b/cp/tests/unitgrade_data/Week02Hadlock.pkl
index 994784bcff903f33f58a8f88d7a8f532b618e04f..2d4de0d0c156197f078f52d350e6d8ed656ff75b 100644
Binary files a/cp/tests/unitgrade_data/Week02Hadlock.pkl and b/cp/tests/unitgrade_data/Week02Hadlock.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02NameLength.pkl b/cp/tests/unitgrade_data/Week02NameLength.pkl
index 9aef2392bbd9c24cb6c72d8d01ca7b2f73105611..182c924067867e7913f67a2cc83fde7bf09ced04 100644
Binary files a/cp/tests/unitgrade_data/Week02NameLength.pkl and b/cp/tests/unitgrade_data/Week02NameLength.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02NextThousand.pkl b/cp/tests/unitgrade_data/Week02NextThousand.pkl
index 48bd0e8b1ce30ac8e2ec7839885c8547d2780c5c..dcc6f867f99aa42e64994799a4b91d45a45ebe69 100644
Binary files a/cp/tests/unitgrade_data/Week02NextThousand.pkl and b/cp/tests/unitgrade_data/Week02NextThousand.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02NormalWeight.pkl b/cp/tests/unitgrade_data/Week02NormalWeight.pkl
index e2c23c390104b23ece97cb377ca0aa29d27a6ac7..1f72fdad573ac6608f6554b5c8c97f69bb1eb674 100644
Binary files a/cp/tests/unitgrade_data/Week02NormalWeight.pkl and b/cp/tests/unitgrade_data/Week02NormalWeight.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02SurvivalTemperature.pkl b/cp/tests/unitgrade_data/Week02SurvivalTemperature.pkl
index 121fc3780ffb306400913dcc62405facad5ebbd3..4dcc92ad1f1ae118cd41cdbf171e888eb5b2fab2 100644
Binary files a/cp/tests/unitgrade_data/Week02SurvivalTemperature.pkl and b/cp/tests/unitgrade_data/Week02SurvivalTemperature.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02UnitConversion.pkl b/cp/tests/unitgrade_data/Week02UnitConversion.pkl
index 285fe6fa2bc1beed32eaace89ef3984ed77ebb9a..a5552ca91fd515524a4bd296e91056564828cb4d 100644
Binary files a/cp/tests/unitgrade_data/Week02UnitConversion.pkl and b/cp/tests/unitgrade_data/Week02UnitConversion.pkl differ
diff --git a/cp/tests/unitgrade_data/Week02WindChill.pkl b/cp/tests/unitgrade_data/Week02WindChill.pkl
index a2e442878d97d3a7e3f590dc0dd1932d5829fe6a..7f996fe2c48d73420abd931571b2ec926c83d63c 100644
Binary files a/cp/tests/unitgrade_data/Week02WindChill.pkl and b/cp/tests/unitgrade_data/Week02WindChill.pkl differ
diff --git a/cp/tests/unitgrade_data/Week03Ackermann.pkl b/cp/tests/unitgrade_data/Week03Ackermann.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..8a7192b3afed92237b7b71904d92642e00ba8ab1
Binary files /dev/null and b/cp/tests/unitgrade_data/Week03Ackermann.pkl differ
diff --git a/cp/tests/unitgrade_data/Week03BACCalculator.pkl b/cp/tests/unitgrade_data/Week03BACCalculator.pkl
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