diff --git a/.github/workflows/rbc_test.yml b/.github/workflows/rbc_test.yml index 39eaf59d..42eb1274 100644 --- a/.github/workflows/rbc_test.yml +++ b/.github/workflows/rbc_test.yml @@ -43,7 +43,7 @@ jobs: python-version: '3.10' numba-version: '0.55' - needs: [lint] + needs: [lint, heavydb] steps: - name: Checkout code diff --git a/doc/conf.py b/doc/conf.py index 045ac8e6..e4723a86 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -87,10 +87,10 @@ html_theme_options = { "github_url": "https://github.com/xnd-project/rbc", "use_edit_page_button": True, - "logo": { - "image_light": html_logo, - "image_dark": html_logo, - }, + "logo": { + "image_light": html_logo, + "image_dark": html_logo, + }, # https://github.com/pydata/pydata-sphinx-theme/issues/1220 "icon_links": [], } diff --git a/doc/envvars.rst b/doc/envvars.rst index 8b2e6468..1bc34fb6 100644 --- a/doc/envvars.rst +++ b/doc/envvars.rst @@ -9,3 +9,8 @@ Debugging If set to non-zero, prints out all possible debug information during function compilation and remote execution. + +.. envvar:: RBC_DEBUG_NRT + + If set to non-zero, insert debug statements to our implementation + of Numba Runtime (NRT) diff --git a/doc/index.rst b/doc/index.rst index d4123d97..7e906e3c 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -22,4 +22,5 @@ and llvmlite tools. api releases developer + nrt envvars diff --git a/doc/nrt.rst b/doc/nrt.rst new file mode 100644 index 00000000..d258c1a4 --- /dev/null +++ b/doc/nrt.rst @@ -0,0 +1,169 @@ + +Numba Runtime +============= + +RBC includes a simplified implementation of the Numba Runtime written in pure +LLVM, which differs from the original C-written implementation. This approach +enables RBC to extend its support to a broader range of Python datatypes, +including lists, sets, and strings, which was not possible with the previous +implementation. Python ``dict`` is not supported as its implementation is +written in C. + + +List of NRT functions implemented +--------------------------------- + +The RBC project includes some functions from the NRT module, with changes made +as necessary to fit our specific use case. Here is a list of the functions we +have implemented, along with any relevant comments. + +* ✔️ ``NRT_MemInfo_init`` +* ✔️ ``NRT_MemInfo_alloc`` +* ✔️ ``NRT_MemInfo_alloc_safe`` +* ✔️ ``NRT_MemInfo_alloc_dtor`` +* ✔️ ``NRT_MemInfo_alloc_dtor_safe`` +* ✔️ ``NRT_Allocate`` +* ✔️ ``NRT_Allocate_External`` +* ✔️ ``NRT_MemInfo_call_dtor`` +* ✔️ ``NRT_incref`` - Memory is managed by HeavyDB server. Thus, this function has an empty body +* ✔️ ``NRT_decref`` - Similarly, this function also has an empty body +* ✔️ ``NRT_MemInfo_data_fast`` +* ✔️ ``NRT_MemInfo_new`` +* ✔️ ``NRT_MemInfo_new_varsize_dtor`` +* ✔️ ``NRT_MemInfo_varsize_alloc`` +* ✔️ ``NRT_MemInfo_varsize_realloc`` +* ✔️ ``NRT_MemInfo_varsize_free`` +* ✔️ ``NRT_MemInfo_new_varsize`` +* ✔️ ``NRT_MemInfo_alloc_safe_aligned`` - Calls the unaligned version for now +* ✔️ ``NRT_Reallocate`` - ``realloc`` is implemented using ``allocate_varlen_buffer`` as the former may free previous allocated memory, which result in a double-free once the UD[T]F finishes execution +* ✔️ ``NRT_dealloc`` +* ✔️ ``NRT_Free`` - Memory is freed upon UD[T]F return. Thus, this function does not free any memory +* ✔️ ``NRT_MemInfo_destroy`` + + +How to debug NRT methods +------------------------ + +By defining the environment variable ``RBC_DEBUG_NRT``, RBC will enable debug +statements to each function call made to NRT. + + +How to generate ``unicodetype_db.ll`` +------------------------------------- + +Alongside with NRT, unicode strings also required functions which are +implemented using C, in Numba. In RBC, those functions were copied to +``unicodetype_db.h``. To generate the ``.ll`` file, run the clang command below +to generate the bitcode file: + +.. code-block:: bash + + $ clang -S -emit-llvm -O2 -Ipath/to/numba unicodetype_db.h -o unicodetype_db.ll + + +Supported Python Containers +=========================== + +List +---- + +* ✔️ ``list.append`` +* ✔️ ``list.extend`` +* ✔️ ``list.insert`` +* ✔️ ``list.remove`` +* ✔️ ``list.pop`` +* ✔️ ``list.clear`` +* ✔️ ``list.index`` +* ✔️ ``list.count`` +* ✔️ ``list.sort`` +* ✔️ ``list.reverse`` +* ✔️ ``list.copy`` + +Additionally, one can convert an array to a list with ``Array.to_list`` method. + + +Set +--- + +* ✔️ ``set.add`` +* ✔️ ``set.clear`` +* ✔️ ``set.copy`` +* ✔️ ``set.difference`` +* ✔️ ``set.difference_update`` +* ✔️ ``set.discard`` +* ✔️ ``set.intersection`` +* ✔️ ``set.intersection_update`` +* ✔️ ``set.isdisjoint`` +* ✔️ ``set.issubset`` +* ✔️ ``set.issuperset`` +* ✔️ ``set.pop`` +* ✔️ ``set.remove`` +* ✔️ ``set.symmetric_difference`` +* ✔️ ``set.symmetric_difference_update`` +* ❌ ``set.union`` +* ✔️ ``set.update`` + + +String +------ + +* ✔️ ``string.capitalize`` +* ✔️ ``string.casefold`` +* ✔️ ``string.center`` +* ✔️ ``string.count`` +* ❌ ``string.encode`` +* ✔️ ``string.endswith`` +* ✔️ ``string.expandtabs`` +* ✔️ ``string.find`` +* ❌ ``string.format`` +* ❌ ``string.format_map`` +* ✔️ ``string.index`` +* ✔️ ``string.isalnum`` +* ✔️ ``string.isalpha`` +* ✔️ ``string.isascii`` +* ✔️ ``string.isdecimal`` +* ✔️ ``string.isdigit`` +* ✔️ ``string.isidentifier`` +* ✔️ ``string.islower`` +* ✔️ ``string.isnumeric`` +* ✔️ ``string.isprintable`` +* ✔️ ``string.isspace`` +* ✔️ ``string.istitle`` +* ✔️ ``string.isupper`` +* ✔️ ``string.join`` +* ✔️ ``string.ljust`` +* ✔️ ``string.lower`` +* ✔️ ``string.lstrip`` +* ❌ ``string.maketrans`` +* ❌ ``string.partition`` +* ✔️ ``string.removeprefix`` +* ✔️ ``string.removesuffix`` +* ✔️ ``string.replace`` +* ✔️ ``string.rfind`` +* ✔️ ``string.rindex`` +* ✔️ ``string.rjust`` +* ❌ ``string.rpartition`` +* ✔️ ``string.rsplit`` +* ✔️ ``string.rstrip`` +* ✔️ ``string.split`` +* ✔️ ``string.splitlines`` +* ✔️ ``string.startswith`` +* ✔️ ``string.strip`` +* ✔️ ``string.swapcase`` +* ✔️ ``string.title`` +* ❌ ``string.translate`` +* ✔️ ``string.upper`` +* ✔️ ``string.zfill`` + +Additionally, one can convert a text encoding none type to a python string using +``TextEncodingNone.to_string`` method. + + +Examples +-------- + +Tests are a good reference for using the methods defined above: + +* `List `_ +* `Set `_ +* `String `_ diff --git a/notebooks/rbc-heavydb-black-scholes.ipynb b/notebooks/rbc-heavydb-black-scholes.ipynb index 76b2f1fc..dd4bc5d9 100644 --- a/notebooks/rbc-heavydb-black-scholes.ipynb +++ b/notebooks/rbc-heavydb-black-scholes.ipynb @@ -85,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -94,15 +94,15 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Running with rbc version 0.7.3+4.gaeb2ae6.dirty\n", - "Connecting to HeavyDB version (6, 1, 0, 'dev-20220323-6ced1de2b0')\n" + "Running with rbc version 0.9.1+64.g86ada05.dirty\n", + "Connecting to HeavyDB version (7, 0, 0, 'dev-20230310-d961893816')\n" ] } ], @@ -148,7 +148,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -245,7 +245,7 @@ "1529 1530 2.0 0.059524 125.0 11.3580 100.0 0.0" ] }, - "execution_count": 7, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -271,10 +271,11 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ + "# NBVAL_IGNORE_OUTPUT\n", "SQL=lambda query: list(heavydb.sql_execute(query)[1])\n", "SQL('drop table if exists black_scholes')\n", "SQL('create table if not exists black_scholes ('\n", @@ -291,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -313,7 +314,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -392,7 +393,7 @@ "1529 125.0 0.059524 2.0 11.3580" ] }, - "execution_count": 10, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -405,7 +406,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -465,7 +466,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -483,7 +484,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -515,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -542,7 +543,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -568,19 +569,17 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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CZ4GBn8u+e5fw+aeEhSV8Fh6uaGpJcHZ2pmbNmixfvpxly5ZRs2ZNnJyckmzj4+NDdHQ0JUuWjH/P2NiYIkWKcO/ePQDu3btH0aJFk8gVT+y8BW7cuMHy5cuxsrKKf1StWpXY2FiePHkie87Sdzih3d3dSZ/IZlu8eHFiY2N5kJoi6FRUVFIdERHQ6ME4qsfsZEA/3Y+ejiwqVIDlheYCEKKz4urVHzyhH4Bwb6Ps2bNz/fp1goOD2bx5M23atOHEiROKJzB06FD69esX/zokJESRAmNjQ7y/0tQ06WeGhgmf2dt/LuvszN/6Oi0tEz6zsBCe1hdp3759vOtm7ty5X+dLv8CHDx/o0qULvXr1+uwzOQHCzs7O2NnZxStMn3Lv3j00Gg1ZsuibghkYGHym6ERHRyuY+ed8y+9WUVH5eTE2hs3vKwAQei71XFOsjBKs5z9jnRdh5cXExCR+sSpYsCCXLl1i9uzZNGnShKioKIKCgpJYX968efOPJnxTU1NMP9U2FNCvn/7xJTJlghcv/l42carcp7Rtq398TapVq0ZUVBQajYaqVat+9rmnpycmJiacOXOGjBkzAvqF+tKlS/FBqzlz5mTnJxP/NLaoQIEC3L17N/7/EsXAwIDGjRuzZs0axo4dm+R/jIiIYN68eVStWhUHBwdAr+wkjjUJCQn5zMJjbGyMTvf53Y2vry+vXr3C1dU1/rcYGBiQPXv2L363Tqfj9u3blC9fPv49ExOTL363ioqKyt+xcWPC8zMXvnPBlO3b9alDjRsLi+ayec5V8mNla4TT2EvJC/zHSHGdl9jYWLRaLQULFsTY2JgjR47Ef/bgwQN8fX0/c2f87BgaGnLv3j3u3r2LoaHhZ59bWlry22+/MXDgQPbv38/du3fp1KkT4eHhdOjQAYCuXbvi7e3NwIEDefDgAWvXrmX58uVJvmfw4MGcPXuWHj16cP36dby9vdmxY4fsgF2AiRMnki5dOipXrsy+fft4/vw5J0+epGrVqkRHRyexHFWoUIFVq1Zx6tQpbt26RZs2bT77fR4eHhw5coTXr18TmMiHZ2ZmRps2bbhx4wanTp2iV69eNG7cOF5hqlChAnv27GHPnj3cv3+f33777bNifB4eHpw8eZKXL1/i7+8v+zeqqKj8vCQuV7Vxxj/c5X4LVqyAhQsViVoYRZGf62SNuPlFj8J/HSHlZejQoZw8eZKnT59y69Ythg4dyvHjx2nRogW2trZ06NCBfv36cezYMa5cuUK7du0oXrw4xYoV+1bzT7XE1cr5OyZPnkzDhg1p1aoVBQoU4NGjRxw4cAD7j0epu7s7W7ZsYfv27eTNm5cFCxYwceLEJN+RJ08eTpw4wcOHDyldujT58+dn5MiR8dYNOTg6OnL+/HnKly9Ply5d8PT0pHHjxnh6enLp0iUyZ84cv+3QoUMpW7YstWrVombNmtSrVw9PT88k3zd9+nQOHTqEm5tbkvTwLFmy0KBBA2rUqEGVKlXIkycP8+bNi/+8ffv2tGnThtatW1O2bFkyZ86cxOoCMHbsWJ4+fYqnp2eSYGAVFZXvyP798IWyDakBE11E8ht9bQRKV8Rx9CjUOj2EWuxib1RFvfXmZ0MSoH379lLGjBklExMTydnZWapYsaJ08ODB+M8jIiKkbt26Sfb29pKFhYVUv359yc/PT2QIKTg4WAKk4ODgzz6LiIiQ7t69K0VERAh9p8q/m1GjRkl58+b9LmOpx5CKyrcjOlqSgtxySy97TpJSyykWHS1JkUVKS5GYSDGHj323cSdMkCR9epMkNWkiJrtiRYLsPLpKUkDAt5mkIP+0fn9thGJe4tJ0/w4zMzPmzp37TYNQVVRUVFT+nYwaBROf34I5cLguVKz4o2eUPEZGYGQQDURBxPeLfE0cDrhrl/LvOURlsh+IpkLTlM8pNaH2NlJRUVFR+Sokzsj8GqUlvhdnQ39hHU1ZvCvtd/PAfCwwDuizWkVo0gT8a7YBYBsN6DLY7qvNK7WgKi8qP5zRo0dz/fr1Hz0NFRWVFJI1K1Q2PUm9DJf4pHzVv5qJL1vTnHV0WliYRF1Jvindu8OK/LPYbNaCQ4fEZE1NwdH0AxkNnwPwQTxsJtUjnCqtoqKioqLyJU6ehEPaMvAChpv86NnI4/p12BNUKv51WJi+9te3xs4OWrsfh+s7Ic9qQLwfW1f7DYT5R+DQuCmQ9SvP8N+NqryoqKioqHwVEteRTC29UffuTXheJ8dD7O2zfb/B4+JuIyPB3FxYdkjG9eB/BarnQ1VeUgFSKuk/ofLvQz12VFS+HR4eUMT4GpiYYGGR60dPR5iOv1zA1vY7Ki9xhIUJKS9PnsCFFyUhPB+FCCLLT1hiN1UpL8bG+uqH4eHhmItqqSoq6I8dSDiWVFRUvh4DB8LA2bXBwQFy3Py+g8dV1/5C4c9/okYNSLt4PDx5Ql4rZb31lHDiBMy+OIQPdKfNGmjRW0y23aX+ACzglaq8/NsxNDTEzs6Ot2/fAmBhYYEmtdgmVX4okiQRHh7O27dvsbOz+2JlYxUVlZTh7Q0D3i8hLMCK2rOht8CCnGLq1IHChWH0aCGxfPkgn/MueHIRDDp8k6l9iUePYNtrffX5Q33ElJckmJr+lM2NUpXyAsSXi49TYFRURLCzs/vHXlsqKirKiYiAnZH6fm2Z73znwV+/Tlo8RQFRwRFoovXNGv/NFCkCM3MvYcS9ZnTVzmbAEC2nK0DevD96Zt+PVKe8aDQaXFxcSJMmjdpVWEUIY2Nj1eKiovIN+VF1Xs6cgbNvWkG0I78+0TfjFWHlu+p05BTRm01YWAU6dfo280zMr7/CsoF3CQiE3OWcgDSyZb28wCvLbl6E2TP9SQM+RJkSGvrt5vpvJNUpL3EYGhqqC5GKisp/lg8f9B2PixaFXKkk9vXECahsegILbRBjx9RBSfqvEvr1g4sv+8BLuDUKVq6ULxsTAxIaotHndn8vD4ytLZwuNURfXnfgHqCG8HekMQnCzdgPayswMHD5+pP8F5NqlRcVFRWV/zJDBkvMnadf/CMiwMzsB09IBpcvwyFtWQBG+2vB0/S7jJvY6vD6tZjs5Mkw4smo+Nff1ascl/2ooDkjksSgLFsZlGa53tRUYsVXndq/HbXCroqKisq/kDjFBeDevR84EaVEfL8Oze3aJTxP1KxemN1uv9GsWcrnI4wS5SUOK6ufMmBXVV5UVFRU/oXMmyvRm1kMrXCerKmk/tiYMfDQuSQPyUoO15DvNm7//hCbrwCSVy6mTBGTzZgRylpdoSzHcYgSNNukgBcv4OC7/BykMi9fiskuXw7GOzdjvHc7i9/W+SmVF9VtpKKiovIv5LffgO59ocxosCr2o6cjizRp4FJMZgLIzOWdhjQb8H3GNTAAkBRFCbdqBa3+11Xv84px/Opz+zv27YPOF8bqXwyHx83lBxrHxkKMpF++JVMzfrpoXVTLi4qKisq/k7h4iNTUnhn4LXgyrVlF/ynfoUHQpyh1v8Tt6x9owQgIkL+toyMUtH2Eo3EI0+9Wp/uDXmze/O3m9m9EVV5UVFRU/s38COXl9WvQahWJWmr08w2L+H7LS2go+EU74ffBWtG0w2NN6WiwhKba5YwZpfv6E/wCBQp8MgeBv7luXbhctj97i4zmQVBa5gU05eTJrzu/fzuq8qKioqLyL+TxY9hGPdbc+oWnT7/z4CVLwuLFwmJ370IB41vUYQeTWt//BhP7MmPHguudQ7hG+NCli3j/MgMklsS2ZwNNOXr4+/Q/K1gQQqv+ShC2RHXqTunS4t9hY5wQFB3y/UKM/hWoyouKiorKvxDPrAY0YBstT3Rm9+7vN+6MGZD/2TayjWzCjRtisrNnw9rIBuykLqU8/b7NBL9ATEzC8xUrxGrLbNoELZ+Mi38d9iH2a00rWawMI7AlBONIBTErkkRGi3cc7b2dS4bFmDD+52o6qyovKioqKv9yUpJJK8rr13BdlwfvACeCg1PwRd8xVbpQoYTn5uZii/i9e7AlqCIAc+nGgYW+X3Nq8lD4B5sbRlG+0AcK6S6Q3kmZmy+1omYbqaioqPwLKVVS4vQZvRWhVKnvN66FBZigxcJER0yMRfICiahZE9KtmQ5hH0hj6P6NZvg5LVqAwbAhmPveJ+2aBYCySnOZeIKjyQ/I3BFUXk6cgOXXewHQrrgZZUDvN0oNlQy/EqryoqKiovIv5NSJWDAyguLFoeTZ7zaugwNUNz4CadORLVuB5AUSUacO1LH6AynsDRGxM9Dp4Ht1cWlmtw98b0KOSYgoL336QPtN1cHaGsdzx79bxtHKldBm7x4Ayp+/wh9X9HEwcvD2huXPKwFQKuB+gvKSRn5/pNSO6jZSUVH5Obh3LyElNjWQktLxKeDaNdgRXYMdzwsoWsf7ho7BEB2Ww/sKx8x8FQSzs2xsIIPxGzI4RWJO5Hfb34m9aseCCyqOa/J5b8slCnH65PeL1fk3oCovKioq/33evNF3Nzz7/SwYX41UVufFiBikj0vLd9a7SMmgN6K92Ec1Nh2yTRIA/K2wtk76WkRR/PVXuFfuN+6V78ay3c4U4RI1e2X+uhP8l6MqLyoqKv99IiL0lgx//x89E2GksPDvspjGMWsWvLbNzuuSDcmSRVw+s8EzinCB8q4PsBALmVHM0qVQxHsNXtxh0wHr5AW+wJDbLajBPhrPKP5dCtY2bw6vyrfgf/Rksd0AmjSRL2tnBzksn5PD5hXuGfQWl9BwQ2J/IuOLqryoqKj85+kw2JHM+JCuTZXvbw24dw904oXP+vbXoEHCwO8lTZt+g3n9DYGBsCaqEYueVeH0aTHZ/v1hdNhAnuLB3ELLZMdwpJTHj+FSRG7u4UXjifmJjpYve/8+7Awqw5FXOePfEzlGYsdPJGzyHEXF8VxMA+jJn3RgSZKMKREaNoAezGFonTtKDrNUixqwq6Ki8p9n6UZrwBqC9UYYS8vvM+6CP6Px7n0AahkzaVMWTEzkyx4+knBvGRT09ef2dzx6BP0jxsML+P0wlCsnXzYkBN5K+rYAuoiobzNBGYSHg62tvG3XrYOxT2YBUMLwAg2qhWNlVV6W7NKl0GHEMAAWOUHHjkpmS4r8a4N+N4ZRfaDaXDDOrfh7Uhuq8qKiovJTEfUd19RNmw04GtsHdsK4GISUF2trCdCnSmf2iOV7GcoTu3pEw22cnCCTwTOI1SkrvKaQkSMh+q+lXPdPj0MhT0CBvwsYZf8/qhTwBDt5ykvizOQUhSZFR+sfxsayNn/5Eh745wFDQ3K+1uBiY/PTNWdUlRcVFZX/PL9kj+LWAxMsjKNwdRXQIH4gq5bGEOpVBIDcU08CNt9l3JAQ+NV4O5ZGWpo1EwjEACZNgklLCsO7d6Ap841m+DkmJjAl3Uzwvw3NpoNtP9mylSqB2aI5kDEjWd6+hTD5adbp0kEx27uYSxG4uIj5yM6ehS33OyJRmQZsJY9fGDbudrJkd++GrhcmArDsALS1sfnp+gOoyouKisp/ngvbXiF5eSENHA4M+27j/u8PLcFFKsFv3TA1bSkk6+kJ8DHXOCqc76W8rFsHm6PrQTQMk+l6Sczt6Oz8wR+E3cxAg7X6wNTviqAJpHRpKJ1mCRQsBecDhVw4FSrAuSJ99Mpao2tC4964ATOeNgRgJv0oWDuKy0pTy62tVeVFRUVF5b+GuWksEAExKal3L05Wz1jCuEe42RtiYlJQsC0VpUv7xzqwkjYQBJ43BJWXd+/0AUkpSVNSGj+i0YCVlVDO8oYNMOX8XIiKYvxeqFFD2dAAHwS8PvnzwzDPDWBoyLVrvzLl8W5Cn9jwVxV9leOfATXbSEVF5efhOysBQ0eZ4EAgGWb259KlFHzRd0yRatoU/jAbzh8MwMlWIG3nI5aahH0sPO1atWDqVOExr1yB5YF1WU4b/N4puydf86AQzud2YLF+CcuWyZN5+xauhWblmjYXgYFi49WvD2eK9MVGE0JO7lIst3ylqUgRmJBtBRNyrSV7drgf4cHLcAfevxebQ2pGVV5UVFTEiImBtWu/e7VanQ4uXkQoDTaOc1dNGc0oBp2oyc2bX39uf4e5ecJz0T6Fd+5AJQ6RjQe0H5b2607sH6hWDdoar6UxG/ngHykku2EDLNM2o4bRAS7ZVGTyZMHBg4P1BQUF2bIF2r0cTzuW47pkHCdOCH7Bx2PZP8qWCJ2p7NhXAwMw1kRjTBQasWbWpEsHJezvEZyzOHfJxfLB9wQnrcfWFqyNwnE19cfgJ1rRf6KfqqKi8lW4cEHfCe/hw+86bJdOsRQtCk1+FS9mMWSqA2MYzR+3qnH37jeY3N9gZCiRltdksn6Hvb2YbL9BRhyhEt5kY9nu79uzJk3oIzLiS6NWpkJyBw/C/Mj27I2pikXEe6ys5MueOAGj/Hsy6FRt7t8XnPAn+PnJ33b8eLC5fYaWh9oA8Iu5t+w06yZNoHHaE9Q23Mvz5womKkkJefsKrWstWkBI6568zF+blmJhVakaNeZFRUVFjLhKWN+52tuSZfp7rW07xQNHTl5KMIGIWkBSwokzhrwhHYRC7hSW4JAkhO/ulaDRgAXhhGFFeEr+4ugoRDozVq0KWm13eA+hs2H+fPlD1asHB2be4WpkLkDsP9ZqITRWr2UdajCfSvfmQBt5Gm5MDKx5rW+QqDuXkNouhFLlJfEBoQbsqqioqPwzdjVLEIyER61Inrz6fuPmyxHB9fvmmBiJ1zyxtowlNEwvk5Kgyu9Jw3o6TA7vIRYDps8wAKqLfcHt25A5s6Lg1zpG+4iJkchYojzgLFtu6FDosLk6pE2Lh/dTfYzRp018/gZzc+Kr1IoqmEWKwBmPlkTff4RFxRIYtjsgWzZNGvAyfQSWlljaGgnVS0nsFgz/EAvIV6zfvYMXIZ5gbExGbuAgoLysXAlDjq0GjYbZm6DRT1jnRXUbqaioCBH8QX/P89TPLJktvy5rprzkJr9wZ/ZhYdklk97yF51ZkmUSab9f+Ah1a8TwG/P4zW2XcKZR5w46dlGHPdQih/0bcatL2bKwapWgEHToANtiarGL2nSpJaadZskCJYwuojWx5jCVOLhHfoDSkCEJz6sL6mkAZgZRWPMBwwixVtg9e8KdbA2402ISxXMGCSkB1tbwsFhrXpCeTUvELB8bN0KB8/MocGo2jgRQc0pp2a23wsLAT+uIX6SDXtFTLS8qKioq8vlergwAL08tcBvsxJsrNqr+AVgEtgWBoV97an9Ln25RMLQ7eJQG49rKv0hJllREBMIpMOgrEEfy0aQQKRawG0ft+1MJwxyvEVHckdmXafBgGLwkm94U0kSwqVJiUpIqbW2tV15kHtg3bsBx/2KAIzWeRWGbUdnQAHtvZyQoSF+lODmsrMDd7A1oDDAwcGby2TKEBkfjsVCiU+fvdEL+YFTLi4rKT0h0tP7CqyRhqEMNP4pxjvK53v6YRnAKF1Tgu6dKX71uQG12UvH6dNnpt19EcN7TpkEt7RYq/tVYKHgVwN0d8hrcJC/XMYlRtr8sjfT+nzAl4gqCknQ6iJEMicEQSdGgEKUzZMCuMnSNncuksfIsRidOQL9H3ejHTK5dFTuZcuWCrhl2JXlPrt7VqhU8K9uGZzV+o359GLq9KBMZxvq1P09baVV5UVH5gaxcCQ0bSty+/X3HrVMzhnz5YNBAce1l8aCHnKMERwftx+g72m77TE5HM9bSZWlRYdmoKHhMJm4Hu+Hrq2DwK1cUdYYODtGwm9ocDS0snpwlSTzBg2OUY881VyEjysCBsCe2OkefZub4cbFhJ0yA65aluE5+3K0ChGR9feF6TG4qudxlBGMZ1lIwBUeSFCkvv/8OxvduYkwMzV9O5bCoZ1GSMDKIZfpeL/6iKzt2Ck8BTZRYW+ly5WB+zjm8rt2Jp26leddzrKKgbgsLMDDQn8chQT9PW2nVbaSi8oOIjIQ2bQA0BAXGcuTo97uX2H9If+pPm67hj2mCwnHmmu+ZtgPMXu0INIMzMC1UdhwoAHe8TSjAY3gFHcfBokUCAwcH6yNC9+zRF0ERwNwsQTkU3V2tOxqziif6F2vhdDcoWVLsO5SMCzBCO5xTFCF8UG4OVwYbmZ0JRo6EFSEnIATu0Z4clUsAnmKDp/C4Wh9RD+OV+p5Fcti5E/a/+h2OZ4h/L1Rm+EiNGvB42lbev4zg9WsFf44kkdY8BOyCQXonEu8bj0YD28ffwXxYH9KMXQx4iH9JKkS1vKio/AvQRX9fc6+9lb61cjaPFLRYVrjIKCky9ymPH4ttX7SRW/xz0WkvX6lhUOwkes3KLOyxmrPQhLS8xsPQV7hgm9/rpLELIp6j6dMhi+YRue1fkDOn2LgAd2JzcIJyXHrslLKMeAHhBg1A88gbzdMnVKwoNoyHB2Q0fhn/WmRfXbgA8wOaMv9WKcb/9pKr5GfP7EeyZLNlg8OBBVhLC0b8lSF5gb/D0jJFqdK1q8dQiSPkcRWPB0utCCkvkyZNonDhwlhbW5MmTRrq1avHgwcPkmxTrlw5NBpNkkfXrl2/6qRVVP4LmCaq/xUR9n2r1XovPkkoVtzZJF6xrfO0bLRmBUO3FxGWHT9OwtpSx6SJ4r+3QaWEvkSiSoS9TYI5vVxZsbE37TTlDwYx50A24fXlxUsD3pCOpzp34eqndrYJ8xz8y14yZZIv268feJvk5lbNoRQvLjYu6Ou8AGg0kpCyV748dDVZSteCl7AjSEiLSKzUPn0qf0yArl3hbqZa/GkxiGW0pVe3GLEv+EjxIjrycx0Pa/l19i0M9O6iCG0KbAGCysu5czD4YQcG32zB1askmCF/oowjob194sQJunfvzvnz5zl06BDR0dFUqVKFsE92eqdOnfDz84t/TFXQq0JFJdXw7BnMmCEsptHAvgFHOEp5Fk54JywfHa0vIa8k6NbROgorwjCKEQ9+XbTHlVW0ZvKJEnh7i8mOGKlBG23IsN/FMyJa1w5iAH8wougBXFzEZCuXDKcUp6jCATq2ETP9vHqdcJkUVZrMzSWsCMUK8Rocm1ZHIaFBQsNkr5VkySL8FYqsY4sXQywGtGQVrwfPInNm+bJt2sB8i/7Mb3SUdLwRWpCzZ094LrfCbWIsDCLp7rietqygTEH543bvDlcyN+JKs2kULv4xkkIgXbqr604mMpQ/Wt0SOhfXroXc5xbiuH0xvz3qzwbvAnxiC/hbrl6FqU8bM/VhPX3F6Di/3k9U60VIedm/fz9t27YlV65c5M2bl+XLl+Pr68uVK1eSbGdhYUG6dOniHzZyHaYqn+Hrq18bvzfPnqG4B8zbt3BPWZuOlHHkCHTr9v3H3bcP+veHWHHXT7VfXlKe4+TNLH7RqVIhhty5YeyYFFhtUpK5A7x+Lba9i5PeTeWeViy4EaBu+RD+YBBj823D3V1MdvUfrzlFGQ5QTXhBf+iTEBooJ401Mfs3hxGKDaHYYGKgzBoAKMuSUhj8euwYrItpzGpa8SFYWQBotx1VsCMQk67tePJEnswff4AuUxYkNFy9qHBfxVWrFdhfrq5QwPweBdK+xNrlYz8DmUpAeDjUdTxNRxbzW+nbQmUD3r+HO2GZCIiyZsGz6jS9Npi9e+XLJ/muKGsekpXL142+ils2NZCimJfgYL0Z18HBIcn7a9aswcnJidy5czN06FDC/+FA0mq1hISEJHl8M8aOhdWrlcnu2gVnziiTPXAA4ZB/wNsbMmeKJVMmiTt3FIx76pQ+yFAQPz/ImiWWvHn1+oAIgYGQ2UOHlxfs3y88NGzdCp07C4tFRsK9HQ+5t/aacGooAJcvQ58+CgQTESUWPxIWBnVmlqcOOxg9U+xWMzoajp/WL6qjx4hbMSZu8GQ8v7Nku6OwbPOKCRqL6NrY7dd3DGIKXWu/EB43nhQqXKKKwC85ExbSxK4+OcTGwkYasYLW7NySgvgiwTlfuABbY+uy1bdQyuJfFe5rbYwRwdgRrTOUbXzRaMBAk8Jg8JSU2gee+ltxluIcPG8j66fPnw9pzu0gDe/YeUGs/5SxMVgZJv1fP8isr1e/Ppwo1J8T5UZRuTJ06W1Kdh5SeHRN4RuKVIukEJ1OJ9WsWVMqWbJkkvf/+usvaf/+/dLNmzel1atXS+nTp5fq16//t98zatQoCfjsERwcrHRqX2T2bElKY+Qv2RiHS/v2KfiCkiUlqUULZYNXrixJ/7AP/o5atSRJf1ZJUpEiCsZt3lySSpcWFpswIWHcX34Rk504MUFW0dE1dKgkZcggLHbjRsKYnTsrGHf6dEkyMxMWCwpKGFejiRWSDQxMkK1WLFB4bGMjnQSSlD+3Vlg28X8UEyMm+2bzSekhWaTnTfpLkZGCA1+8qB90715BQUk6sshH2k0N6VDZccKy0oMHCT/40SMh0QlDQ6QOLJI65LssPGxsQGD8sEULCP5PHz7oBc3MJKl4cSHRzJkTfu6MGWLD+vpK0i3zwtItcknaDr+JCUuSJNnaSiMrnZGyGT2S8qd9Kd25IyAbN/E3b4SGXLNGkppa75YaOx2RrpBfen/ytticvbwkqU8fqVmzhP3m45O82LRpCdtvbLNbbExJkqSKFaVHNXtJY4vvlWakmSSdPy8gW7myJDVqJEmSJLVrlzAPof39lQkODv4m6/eXUJwq3b17d27fvs3p00krIXZOdNf8yy+/4OLiQsWKFfHx8cHT8/OUuaFDh9KvX7/41yEhIbi5uX22XUqJjIS3Mfq7TFEL7JUrsNO3PZHvHPj1EhQuLF925UoYfXoFoGHGdn0DMbm0bAnH90dgShSdOilwAkNCsxABihVLeF6rlphsiRJgYxKBaUwY/SaI2dgfPoShW5vD2xLUWgbt2omNrRRfX6g1rRVEVqLmEIlJk+VbMhLfKUmS8sqWN7zNk9/oE7znHMD0t3ZYrDyDcDpqIiIjE25Y5ZDGPpo0PAKDVyBoiUgyqCAdRmXgKXtIez4Q4ZtLSaIOO3hBBhxapOXwefmiw3qHw6ROUHkgUFBoWA0S5oQTgYVwk8Plq41YxWGORlbE6kIYA8fqU5Hl8PZtwnPRLtpubhBGDGcpwvGbRal0H3LkkCc7bBjsDD0Lt9Jw0KMpGWvmBq9Z8gdXmIZ//TqsD60JobCRqzjVieadzLo4vr7wMjwv+HmQ+BSW4zny9ITaDmcg4D2uZkHiFaclCU/rt4woeB6eL4WiQ5KX+QIlS0LMxq1YZ3fFyqpY8gL/ARS5jXr06MHu3bs5duwYGTL8c3pY0aL6glKPHn059czU1BQbG5skj2+BoyNkMvMjh/VLzARbsly7BmOft2fqw3rcuCEmGxICTyJceBKRTrZJMI4mTSC0VnP8C1WjY0cx2bVrQbN2DZqLF4TbpBctCvd+HcET97IMHiwmW7YsBHcdwtu0eZL0KpHD27ew9UFutkbVYscOMdnEDdIuXxKLAYmKglt+ztwiDy+ei8WtpKQ0vo0NZHDQr2h+78W1gIxOYaTjDTbGKauLodgLo8C0v3CbMz35H53m/CIs/vSVCQBvtPYsXCgm22+SM7uowzUKcNvbREjW/72GW+Tm0lNn4Wr7qzea4IQ/GXnKqK5vhGRXrTPiKPqc4Q+xlgQHJyOQiMSeVxOxnwvAMV0ZOrCUnpfacOGCfLkXL+BOrBd33jgRZWEn5L5ZswY0Tx6jQaLfKIEiPl8gPFL+0jZ/PpR4upYSG3pjbw+97ZYzvNhhHGV4VOvVg9yWjzlBWcotasHlywonbGUl32cURyJNqUMHWOk5hrkl1gjHg6VWhJQXSZLo0aMH27Zt4+jRo2SSkbt3/fp1AFxE0wO+Mh06wOMKHblXsYdwV9lt2xKei1ZufJ8o405R3IokKbKeJA7P2bhRTNbSEnLY+uGh81EU9a90zol9taLKS2Id2tZaLMgwcYDb6rViVaLs7GBJy2MsoT2Hl4qVbjUwAHeHhIu74lL7CrSPnSMuMZduLGlxNIniJ4cjV+05SGXOvvIQH/ekHX/Sk8XHsghbQMsVSri4iyzkAHtPJpiWjA3FFNS/VpqTh1sU2TSQ04Itd/5absJz3HmGB3WLv01eIAkJSrirgR92dvIlx48HH6PsvEpfmD/+EByWhFRpELNUm5mhz64yjUJjaSGU/XLpUsLzmSsc/n7DLzBkCDzJXJHyae9SnLNU+OWdoiy8xo1hVuY5jMu3hWTuy+OJjjUiBFtiYg2VxxdZWSX0VJKBvz/c+uDBrSA3goI+vvmTNWcUcht1796dtWvXsmPHDqytrXn9cbWxtbXF3NwcHx8f1q5dS40aNXB0dOTmzZv07duXMmXKkCdPnm/yA4QwNVV0oc+aNeF56dJisoUKJTxX0Jlej4I5J64+KucO4osoUEDiUTDnEiUSnpcqJQHyzRqJAykjI8SuWolTNIsVjAaMZctaWED7Evdh9TLI3wsQu+2p/ssLsj3ag1nFUuh0WWV3HtbpYMx6L2AMHltsaV8oWZEk1C7yBpgPBbKARQUh2UoD8wMH4SLcE3ApAOw5Yxf/XPQQGdbxLfcuf8DcRIelZXox4Y/YEcjzFecB+W2LzRJVyU1RrLDgyjZ1XBQBZapDlqxUeLcBwxHya4+Ym0NmHkO0Awhed+7dg2iMaMFqymV9RZmKg2TLLlwICzdk0Pu3ToXAhxRkWAng4AAORi84Wn8OLFgA/daBRl5HyFKloK/DcvDIRIYMZROaM8rE1cSfHNzDwskSU1P55//ly3D4aVPwt6JOPiu8dDp04VoMLZN3DaxbB73O68tEr9kLzZujN+X+RKnSQsrL/PnzAX0husQsW7aMtm3bYmJiwuHDh5k1axZhYWG4ubnRsGFDhg8f/tUmnCLMzEhQU+Xj6vrl53JIvKiK6gLv38Pz4EwQEoPbezElpF07SHtwFTx6RNk9Y4TGvXABxh/sCYENab0JGjWSL6vVwj6fX9BG1CHtcX3/DrnY20OLXNcwu3OFvPVbA/Lt3QYGcKLdcsyWzcNu2k4gnZCssaGOGJ0GJAWVbuPulhQoe8Pr3IRt7aHFUjDJmrzAR3Q6GLfFCxgJk6H9JOGh9aSwFPvmzaD09HZ2Ftu+crFQXuMJnjmhm1ggx5Flz4kpVxENEoTPFJKdNj/BaiNS8wRg4vAIAmr9CoBBZHch2YL5Y4HD4KKFZwoXJQX/79ixsD5qHgDjzergkU2+8hLHLT8nFt//jQ/BMdTfLS927vffwW3lBLSBYXiNaQLkFR43/g5RwFxUsybUTDsVylWHLOLKS9/0G+n7pBfUagtF5XffPHMGhj7uBMDQm2BKBAXKG3L2ouyvSIqNjd4k85MgpLxIyZi03NzcOHHiRIom9E0xNVW0wPTtCz23lofwcIxrCziAgZw5YUGOWZgG+pG34RQh2ZkzYcJx/YXWq4yY2yl7dsieYx883Q8FxJQXX1/Y/TwvkBfDNWLKy5UrUH9vJ6ATlBcroGZuDqtrbYA7U6D9r4goLwBlPHyBS5BevJ552ITZGA3pj2aDN6CkGhjCt+VaLey46AE0wuW2PYJGvRTx7K054I7JOyNEHbrl8gZy/IY9IL425skSxrtHwbhlABMTwTuBOBQsyOnTxgC+iuQzuOh4/dYQQ42OggXF3Iqli8cAO4lFQ0RwJyxEAjrjTh4LC71vMzpan18rF0lKeVq5QuX2ebAN/3tQFQD3K/KUF2dn6G+zCAKfQYESKFJeDA31N6kKU6UBvQvnjbz4pE2bYMntaUAgw33PUUps1CRoMSM0WF46fa5c0Ml1D5iZ4elZkfPnoe+xCYSGQpc50LNnCiaSSvhpehs9fAj9rzanh3dvdu1KfvvEGBuDuYEW8+gQ4S666dNDl/S7aWuyjvz5xWQTXzdEMwYAxRevxG5T0diTd+KFYr+M4LwfPICCCzpSkMtM/J+V8HDGhrF6J5XguJIEUw/lowsL6DRZLOMnLAyazC9HEzYyeZ+YW/XT4zBG0DqfqWMFPHhG1TWthWWX9r/DCMYy0WEaVauKyd5YfZtXpOdC+7/EBBPzneu8GBuBCVpMNMqqf1VjH4bEYtW0lqJac/GpYAKKRKNGoNHFoImOYt0aMWti7dowyGg6g4xnYqNVcEJLElYmCYuwaBwqIKw03bsHez6UZY9PDgLMXJUV9UNfGivb3lm4nN6InMLwT57AgaCiHKAab0PEMkFq1YLtuYezvfR00jtHkZfr5Mgo73dXqAALc85kYeFFFC2qPyXOv/XkToQnL1JQQik18dN0lX7+HGbcrAyAzTn9CSoXrRaeR6QnMsQa2+f6VEK5nD8Pe33awPu3/HoTREJ/8ia68ciYUb5cErRaRPP36tYlPrupRDEdIq1OE2dy5coRg8gh9v49nHroBdTF80Ysv8j3/BARAVf9XAFXirwUu+AGBMDiY4WBgeQ6YkpNgbb0L1/C4O0lgBKwH/6KRbiHDQA6sQXGwABW9rjA6z83Y9qqCSAW9BKX1n3L34Vjx6ByZfmymVwiGcsoMHOFMgOExo1HgQKSt3E2nvOetG/fIVzAWZI4QgVukoeInbnp+qs+TkIOZ3e91/uLi5UABAtVShJGJGiHERHy09JfvNQQQRZGXhlAGsqQdpKGYTLdg4m9HuPGQbMW8qfcvDk07ziCGCs7wiPMCQmR31V61y64q+1DyAMP9rZYg9vBJaQbfFT+4HEIKi9LlsD0VwthK6QzqEX+xUHMqCsWj4VGQ2wseIekBcQ9MJooMau+pyd4Op0BV1fqzveG3PlhzFlAZjOqRNf1uMQKS00YIFD3IBXz01heEi+qop6je/cg6/VN/PLqABMnislevAjjnrZiXHh/4Wyj5s3hbdVWBBs58vChmGxEBPS/1pIesbOZPVNsYbS1hWF5djOWEfToILbIFC8OVxpP4QoFOLhG7Ox/8ADqb2tNfbazfL3YXUxi3ezSbbH0GX9/GLy3LIOZysb9CuvpfETk2LKwADcH/W3p3odZhNsxtCr9jIFMo1e5m8IWwcQoDntRoIC89jfiEoU45eOaJBNPDr5+xgTiwP3Y7CxZIiZ77IIFLVhDP2by+54SYlWY41wKCn7v23cabAjBDV8qZHsu5EZt1dmMbHiz/llx/kdv1m6Rn06fOAg9Jlo87cYnNhPG715h6+/Db7/Jl9uwAYZEjWXikaJkc4sgt/aK7JYK9+7BjrBKrKE5N73NFZe5fx2bhn2Pssn1/DBlCnj6HMBz8RAePAB7swjcDV9gJcOA27s3nM7dlVasZJtfUWGrfjxxGRYKA27z5oXoabP5YJ6GKWLRCamWn0Z5+eUXONVmMRfT1CJRTTxZJG6WJapEJEbUfGpkBM4mwdjEBGBiJKaArF8PMx7UZC496NNfzE9vbAwTCm5lBONpVkvsZLKxgQLOzynANVztlQeDzlguliqZNy/kTqO/Wt1/JljIJxEr94uV+DY1BUfLCMwJp14BX6GaGmZm0KRIQuMX0fTfeBQsqqv7XaUY5yiX9q5QCm4SlDT925mGIlyizJbenDsnJps+TcJqtm2r2ILceZQLbxIFcYt4Fa7eMiY/V8l5W54rITH121izjuY8x51D7dcLByknRiSMY/ZsGKcZwRQGMbafYHEaPk2VVtg7y8pSf9GTqbHNmwf1/BfTkjXkHd+I58/lD1WtGoxznImhJqHegNz/OCAAHke78zjYiRw5IGD8PJ5ZeMkqCGhqCqE6C1bRmlXvqvNJmz/5xGlKinxsekuskYON/kf/JM2NfhrlxcYGSmV9Q2EukV4wyzLxRdZasHZS4nb0ixenoIGeoLkoJXfiKRk3JbKKXWMfMTPSm+cjo8QO65SUIHJ2Bv8pSwnHkm2d98lOdY7DzEiHATosjbVCsSexsfDwlRUPycqLNwJBnB9pUfYF5yjBsZIjKFNGTNa9eUnS8IbyEXuEW1rPWJews0V1rvMrE1pYR4SJZoUlzHNH3aVCHZqjtBLXyc/9KE/xvlmJd4+gslelfAytWElmuwCOU5bd0+4LyQ/XTGQQf9C0coCQHIAVHyhpdZ3KHCRvLvkFiPr0gW1mzdjWbifpXAz0B6pC056IWKVKMNx+Hm97jMO3cEPeN+km2xVqaQnOhu9xNv+gj4e2thZSusw1CQeyiFL84QO81DrxMtyeCEOxhpBr1kC+i3+Rb/+khB5ycXchiu+CUhc/TcwLoL/VVXCXmjZtwnPRkvWJa8TY24rVLkmCVotINbHEptqxA0IA+ZWLX7yAM48LA2HkuRNLToVKhRQRKfRr06eHbPbveBJoS1pnCdHa84287lLs1VbMalUlNjab7NgTa2so6fGCM0/1Val0OsSUkBS4FcbUvcq43fmhTUcov0i2XFQUZO9bA6hBuVXPODpaYbVfBXN+/s4cMOc4aahZQ8eeffJ3VmBowiUn8bkhBwtTHQepjBmROE3cCdjLlu3TKoDACXMxJ4I6rhFg31627Ja9CeedSLIPQLmS0bhc+hj1LriID+0fBWPbwKCJMOwkpBP0syk8Lrt3h13aq4AJ56hJ+v63kbuvCxWCQka74ZciXAvJTyilMToWSYmayRebqVYN1swLIjDWjpIZnmFhIX7hcTCPwMEhDKLfyF7dRo6EkWtL6gMhi/8BT631+y4sDDm+owJWD7lIYSzS2ZJ2kPwqposWQb9zmwCo0RzSGyzmw5zizK6RfBkBf3+48UGvgcdX/4gLfAkOFm9/ngr5aSwvgOJU6erVYWGmSSykE3lziaVmmJlBCZvbVOAI+XKJmfO2bAHNrp1okGjbRWwhr14dpMZNkNAw4jex2JPLl6Hpid9oygZ2HhRzwQQFgWbun2iQMCiQT0gW4F6HaURhyvM1J4VlB5U8wxx68UeTy8JBs7+XP8camrO5zynhceNRcGzFzzMF9VaOP8nI1asKhRUoL56uCbeXIUFiFhBnO/05kNnCL0lAuhwMDKAyhynNaXK6iZnXuzcPZDgT6K+ZKbyvj57Vn3vGRAm7jSb8Hs5mGrGZRhhECmbAxCkfcRG+CjNoRH+vvz88x43n2rToMFQ2rkZDmWGlKMtJOveVl/1XsyYEpM+DhIbTTeYgo4D7F8fFyiplqdJx5nUZLpzbt2HH+1I8IDs22neKdYbjx2FRbAfWXckmK2PT0BDMDLSYGUbFX0PWnvPgDwYweZZyt3lq4qdRXmJi4MZbFy5q83D3jpipO18+6JRmB51YjIeL2AJlZgZnCvbiCJWYPEysdHNAImvvio3ijfviSYHrZ8hsMZ/KRaUFlj5ioFF2t/j2Lcw8V4yZ9OHoNfl35HFUz/GE5qyjYV4fYdfPq2BLrlCAMw+dheLt/P3BtEsbTImk/jGxwgyfKmeif3HpoSUpzUm63ukhJgh4Lz1NZnzIwT0yugoq5BMfcIQKrMotqAV8ilJlz8JCuRKgkD3UoCWraLiztVCfoHjilBeBBXnePOgiLaALCwjxl1c7JA57e3DlJa5mARiiE99fHxUBKwu9YhsqomcqbMyYRFZJn6BETN+bk8FMZuyk5M1su3ZBK5/RtGI118KzJ7t9YrJmhYZOJ2jodjFJVpScqffoARFlqxPRuC2NG+vfm7A8A4P4g/GL0/6z8H+En8Zt9OED5BvXEGhI1b6x7D+YAveNQAvewEB4F54ByIrL+yisBQL2vlrciqAikFsgVfibIbgav3gB/Q5WA6rR7eJtRAreR0fDuxArwAWLgFjsBGT9/SH98HZAO1gC5zom7cqdHFExhoAhMTFix6OJCUxveY1lq40wS2MrVJYc4PRdR6A0p99AmbUfy4vLRKMBn7hCflMfIdLRunTeEOAYmIk3cho5Px1BzMaOIMaKWowkiWiMCDF1JeK9OdbByO7bNXlIMEEtuumr80qbxPxzksR9crCGlvAUmjzTNz4V4Xm4I+/IT/h1K4rUk9do8cAB2Im+O+PCWmKhSQsWwILlntCoMax6JaS8BARARKwLBFnSvmEI0QuXkqZ+I0DQjCKovAwfDvOeXCZwih0jCu3D6+1xsl6BgiJNwD/+rzM2u/GKwaRfH8XI2QLyUVFCZSlq1YJaXiPB3Z1n41cRVLEh1qXzkT7vCHnjfTKWrb3+eVikETExX3H9+Jfy01hekqRKR4qXgC99dwEFuEKTtmIWkBUrIPuFlWTnIXsPiN3St2sH83LP40+6s37KMyFZgHsh6blAEc5dFnPUZ8kCVVxvkwVvCmUTC/5yd4c+eY7Sh5nsHSV2m3n2LFjNGocVofy+SuwuJgk6Mdeejw+kn9CN9Lyi7waxdvKfXtdF1lRDQ7Ax198V735bRPiuvF/NB9wiD5fqTxS7SH+CaKf0JCi1gChwVy3b6cgcejGOkVy9Jn7zsZlfcQp4iNuR5axYIV+uchktjdjMr2zRL1CCJM7cEdldXfuaUZTzuPeqR0GuUnpSDd6K9nb8iJKmn32vt6Ee22jUV2aHQvQWgQwR3mQY04mOraOYymAG1BFI0VRoeQkPh8BYOwDGXa5OM98prFkjT/bgQRjt34PRZyrj6wvWcbGzYckvj1WqwOyMM2htsIoAyY5LZ5Vl+mTMCHmdXpLZ4GmSljIijBqlYTMNOTTgQIq63acWfhrlxdQUOld5Si9m82sNsRNDp4PzH3JzjQLcfSDoU0iMghS23zLupTvzaFJe7Kp17hx47Z9BMS5QorO4KeVA5Wl4k41L08ViQHLkgJklNzOTflTPJdZlWaeDsGhTwrBi4s5fhCy/mTJBTif9Ppp3Jh/3xRIz4nkdZJaiTEOR3lf29rC8XUJsz/HjCgdVoAicnpTwvwqLJ76NF1xkzt+2Ijv3yXhtG5MnC46biHLdcgptX6BRZpqzLv61iCckVicxg75MZChLFoppAd0HW/EXXUjPC56XaxVv4pfDvQeGXCSpmUbuOTF7NuTjGgD5MgaI61ySxKFXXuygHvvOKax9ZCWWQTN4MGhevkCDhP2WRUI1U5ydIZvx4yTvyd1XBw/CmICejDmrV14WTg/lGOU4Nv5ssrIFC0LXNFtZGduKdiyn/8AULKlxWU4KqVrTiIYW+6mU/p6w6zs18tMoLxoN/NX3PrPpQ/eWYtaEyZMhRtLb4G4/FOu3kzPRNXbknyko8iC4wvj4KB8qCd8xVfrTrtuBAuUp7O2hvMfT+Nci8XqJEwr2P8wsVEzQ1RVejF3KC9Lj36wn2bLJl4WE9G5IgRKh4D8qkCmQh2TF17kg48eLyQ5eko3+TGMGfcXLuD+z4CHZ8Y12Fa5guntWwkEdoRW7dAWHJlzNf7U9JPQ/aTQwgGn8zkQWLhOzxV+9acQN8vGSDGSQnoskDKLRgAa9lbi9xXr6Fz8r29Xl4QHXKICEhmsjtwuNG4eFqV5RC9caynY7FSkCDQ230TCvNxaOHweVuSAn1nGCoq3wFbj3GToUHrhV5l2vcYyvfoZZJoNo1ky+fGLKVDalHCcokPalrO2NicbwYxXlcOEU/kQIxOpcvgzTfBsz7V7NJHXIsLVVU6X/k8T5jlLQG2XX/x4D8lvLVq0Kmc1e8jgyPe+DUqAOp0CJsDSLQZKMvlsqbTyCcy5YEFp6XWH13YKKhrY20WJLEGaWhkiS/II8GTJA75KXmX2mkPC4RkaQ3vYD8AoQTGUF8roFsIbmmGVwxquJfAd7RASUG1EZOE/hC+/5U3Bcc9NYsvIIou1AsHbRrO0ZiaI/AA8mP+cvgTox7ScmFFj5VFlNjrxZwxnDSJ7jhnnV8khSFtnHdOYMURi/eIyDdTSb0vaABg+SF/pIYLAB0sf7vMiUNOEWDHw9vvuDXivftAmGj4YStcClhPi4ggrmunVwO2YMudIFsOpVRVyWTgIayJLt0wf6/N5S3+Y8Qy+9yVvmguzomKJpA+BkEc7v9e/C/mlQdjJy7s87dYLKa9tBqVLkytVBH9Oo0ci2GGk00Md2OYbB78nYoD0g7yZ140aYf2MmPDCjzw5wiihA6ItgMj8kWeX65EkY+Fhf+jjjzUQVlX8i5eWnsbwAxDsTBRdVNzcobXWN0pzEwUz8jDI10PshtFFi2sP16zDlUUMmM5jLt82Egu5q1YI7VfpyBy985+4WUly2bweTVYsxQcv0nYLFOIDFd0vQgcW0/KuU8N11t7xn2UBjtrfYRDqB3kYAkyseIgh7XnccQSGxVj94pXlHVfZT1/O27D4un6FA0XO1C6c562hgvEuoD0tsLFz0ceIiRZn7pAaH5ZeXSEoKUrQBFu5zE4qncLDRnwtZDX0YO1Z8vJGMYxGd+V/zC0LH9KFFT7lPTs4WHyCsRFRomrAYzRshVqXu+LZAIjAj3D2H+L6OO+E1Gv2CKuJSSIFrb+tWmBg7hOVX82BJGDaEKLrxGTkSMkU/wGlwe+7JaEY1bhxEumQiEDsiC5Sgf3/xMeNTpSVJ9u/Onh2qWp6maqaH2Nsn+g6B1MFp7v9jCkPo1uC1bJnnz+F4cAGOv/Fi1y4odWAE1e9MY+1a2V+RhOhoeGfpgfczk4TaL/9hVOVFBq1bw8mcXThJWUpkF7+7PpRnAC9x5enyE0JyFy7AkAftGMpkCvctJVSB1c4OvGxe4MU9HIzFSvzHxkJ0rBHRmDBgY5EkKdvJcfIkdDrRkqV0YM2l7MInUXHXZzRmE3U9bwtVM46OBv9wC/xx5EOoeCXjzkVusJ/qbK86Hy8vYXE9gspLSAh0WF6aDixmznuBdJ8vcPu2/G0lCRYezMhCOrFDW1W4Su7xKRcxJeG3ivzsZpX8acsyGhjuFBrzM1KSKq1Q1owISuYUq1ZragpRmHCK0mx/V1J5PR7B2iV37sApSnGKUkR/SIHr18hYcap0cDA8jc3I+3AL2XqAqSYKO4Ix1SpQmBKnSoN4/MjHAQMD4Z55AS7ctSYkmeoW48eD5uIFNLduspuaio+txK5rOfuqdm3Y7DWSzaVnx1dxX7QI0lzZR7atk9mZwtMrNfBTKS+1+mYlO/fJ3zQFmSwK3DfpTf1xxQ9HE2VNt1IwtB7BRfXTXjcisSefXue+15xv3ADn6UNwxp+hZwVahn+K4ITDw6HbxnJokNDs28vixfJlIyJg6ZnsLKUDhyPE3AGWlrCtb0Kwr8jukiToMj8/XVhIPXZw4rBYNGfxnEFcoSCXKMStMVuTZPIlx599fVhGeyYzRGhMgGv3zblIYa6TV7kVQ0Gdl7JFtdRmJzXYK25dkyQek5mqvouo/2YBCxeKiccjWLtk8BAowynKcIr6axri7Z28TBwjR8IRwyoc6bUDJ4twxXVxHB0hrZE/nrbv5OvHCrONtm6FXu9H0utgLZ5+0FeKiw5UFvw6ZQp4vT1OsaWdhXoVaZCE9lXv3hBRshIRLTrSpw/0K3GOkZbTqVo1edn4GjEZL5PhYzJY4nion8Hy8lPFvDx5ZcpDsmP1QiyVFmBLQHl8KYl2dQYGV5Jf6mHtWph9dR4QysTL4VSsJ3/MKlXAzewtzyPTkNExlNhYweCEOAQX5AoVoH2WEyx9VFZYPHH59M4FLpM1q3z/jbc3zDjUAPCkyh0T6ssfNikiJirg2TNov6gpUJjqV98wQED27VuYfyZP/GvRTslx+MWk4e1bSCPQF7JczjdcIx9mOTOTtstWZQMDw0cacEpmH5g4cnFX/8TRD5SEckVF6U18AqWQa/XNwisu4oYvvpEbhIcMwZpmpwYTHtGRQgMk/pgm7ySePSoAltXVv4g8Kjyu0lTpLTuN8aM7ByaV4LF3ESKijRi+FNrL6WyQSFnY8ygHA17Kb8fwyy+AwXHuWLdjr0Etws55Ut1fXsX5cePgqHYfzPFk3SkYua+2Pmuh6FJ5g4O+hoCg8nLyJMwJaQtXYE5zMEaLSwV49ip5WX9/CIpyh0BHMkSSxG2cnOUlfXooankLjI2xCwoSmreRERhptGAYjYcHTP/1PNwcDVWU+Msgc2ao5X4T2w8vyJq1hqLvSE38VJYXOzsJOwKxtxLPhZ31pin9mMnQlTmF1sbXr+FiqBcXKUpAoJgdNFMm8C3fFgkNT8etForFeP0aShwdjwYJo97dePw4eZnEDMm1m3MU42rnBWSWH59MxYogdemKhIa/Km8W6rL86hUsuFmCBfzGlge5hW74bG3B3SYIgA2+xbl0Sb5sWBgcfezBUSpyL1Aw0OYTRH6voyMc7bcbgEtSITp1EnPf2FlGk48b5OC+3lcvE40GlnRP8F9ERgi62VIQTxEdo2ECwxjBWP6aK34TAfAcd7JPacfdu/JlxsxPQ29ms/d5Ho5TnuvXxLJCArHjORnwfiR2Du88YMpO6pDe9B0TDYfTpIl82VkLTOnJn+y+4sLdEDeeRLjIrvPSoH7S/1RJJtuSc140DFpC6631eSizVMudO3A8tizHH2XQ3/QIpP9u3gxdgqaQLvYlYwN7cOiQ4JwTEY0JH8Lk/VcTJ0JW3yNkXTiQa9cgf35o43qQXp57km0W264dnM/ZHk/rdzRjHc5NKygvtRC3r2KVZSwVLw67mqxmtUNvqldXOIdUxE+lvJzZG0IgDvguOigkt2ULnP6QP/610gSc9ecyKq9MLmg9OXgQzgXo3WO6WAPhVh9Zbd5QjAvkt38q5BZIQgoyldY8KsqBA/K3z5oVxpU7AsC7KFsh5SUxS59WYPdu+dvb28OkWmeYxBC2u/Wgb1/5skZGUMA9oZFJZLhCJULw2NBooH2Fp4xhJBMYRs9WYtkJ132suUY+HpBN+D/WSLEMZwLjGcGqNWKXnw51EqK/H753EkqqWL7DnuUkdFUN/yC2QNRmF+48J1vnckI3LxNmWTCQabzSOjJUN4EaVRVUiwNMDGJwNgyQ3RiyfXt4QXqukp+79YZRurT4mJamCauw6PUjHgF316FDsDCiFW+ktIyKHMYi+X1K6dcPLrrU5WLbeVQsGUl+rpIvs1g7ljiqV4flJRczO9Ms8uWTJ/Muxp7nuOMfYqo8Bj4u8EXGIhEWBq+19ryOtEt6CqrZRv9RFKZKJ77D61TmvlAFxH79oLGz3tS89VomWU23vkhKUpYRjslM4DvWeSlYENrmSmiOJPqTzQwTLrYiQ+fIAX/V2xf/+ulT+bK2tjCk4iWGMIW6xvuSF/gEc2Md1dhHPbZRopD82JOoKJhzMBtz6MH2wLLC44I+c2cYk2hdXeygLNynBAW4Rg4ecOJ+WiH/euX+v8Q/j4wQUyDGdnnJUCZiSiR2puGKqsYaGegIx5zTm9/IF5IkzBQGKH+GwMo2YkAEq2nB6t6XiBg4krcZC8vPwJEk0vOK/Fwnp+ljkY4mvHgB96QcuNl/YILbAv4sukp2XZyVKyHc1J7w6fNxcyNFfYYiBJR5d3cobHqTwq4vObwznKsU5MgIeQkSBQtCS6tttMx1LcE1ZmOTvM8oDknC2TKMdPiR2SlEdkHAW7dg6esaLH1URn/NESjqN38+uFzYjsvmOezZk+gDOzt9wIviC37q4aeKeVGabZSYerkeYWIikNOKPoI+DpGhw8IgOMIecMEuVIdIWYzcuWFoti3w8AF1WtqSJ0932bKXL8O8sx2AcjT2DqeawLgALz/Y4k1ZtI+zkMcPXGT2drSygoZZbvLuzlvMXB1wdRULYi3l9owd1MEsRyZyNJRfM8XAABzMExYVxYuTAkETo1j28dE/3dsPkOe20mqh18rCQGEMA2O4ehPy5ElW7MukYDUut6YTRztA+fLytr/unbCKLhz/DkgvNN4Efmei8Who0w5K/SVbbvusp0Q1boFR716Yz4yECPkm0K6/O3IEDwBaFfcG5JcPGNYrjHftukHpMnAKvfKSOLXkH6hSLhpYC2V/hbuCqdKJETQF9O4NW3W3YC28LL0A17Q6yNhKlqyJCaCJBBMdT57B8ntN+fDsPWV3Qp06/yw7aBA03dSQBTEdKRG6n9xdJwOC1fXi0pxB9v5q0QJajBwAtRtD1o8WdkELxpqKy+DVKhg+EZx6y5LZvx8GPRoKj2DLVag/uCyveE36SrZcFSiUmQRbW33qZWQkiioTpiJ+LuUlzuYqqLz06gVtNtWEW7dwzigSzqmnkdNxcr09hmn1ijg6VpEtt3IldDv+sUHHRLjfOlExomQoUAAK5F4LD7eCQy+h+T59Cst8ygJlCbp1hYLv9OW35eDtDYU2jiYEczgI605A06byx66V+S616AR5q0PZvULzdrUOpQ67wCwfiPUppFZ2b97ijGnBX7DoIx6UCQgrAVotnLufDiiLE/7kVqhE6DBi8mRk14eQJIjQGgLmGBCLmeC4Xar7Mne3R/xrkbXRyFDCiGiy8ZACWQwQVV40oLegCi7IebNFAJchy8e7WgH5s1f0Nz0WhLGyxUGwkq+81K2mBZZAASu98qLUb5ySTskpMRVZWECY/NolQPxd/8uXMPbyR8X8RPLKi6cneJqcoXzmZ3DlChQbgZDyEmdtMDHRX+sVpkoDsi0v27bB1idjIMSJAcb3yJuCuklvg015izXGMrqAZ8kCdR1OgaUFLi76op6SBHX+V4kATuPWDNZvVzyVVMFP5TbatVvDeMNRjNiSTyj919YW3E3e4M5zzGPFnb+1Hc8ymKn0KXjqsyqSIviJ1cdKIAWWpm2+BTkqsJZ7e0NIdMIF53ulSj94ANXWtaYa+1jwup7wcGbGOpzxxyb6vXA31pAIYyYzmNEh/Vi3Lvnt4wgIgPIz61Ce44xkrNBvNjODP5om5HGK7C6dDiyb18WScCpzSFgR+PO3u+ynKj1tVjAo9x48POTLvtt5nmhMuENu5YuquXnK6ryAciVCQao0QM7Vw7AhGK+KCgPCLS31c5YZzNmuvQZbgtAgsfV5YaGA/QoVoJ1mGe2K38fc2khxwEtiA5NsPUKSEiwGAv/xs2dwSZuHS6/S68cSVfYSuVn8/KDI0i7keH2c7skYrG/ehNUBNVntXRQ/Y3eh46pKFVjoOYWFJZaRPz9kTK/Dgye4Oyf/u+vVg+1ew9he/n+U+Gig1mjg1D0nzlKSq9f/+82NfirLy6ZNsEo3Gg5Aa3+EMjQiY034gCPadyY4aZEd93L1Kpx52QDIS3U/S7IkK5HAp1k+30sRqFIFemQ/yJ8PqigRj0dDLHnyyNePg4Ph9ksPoAQZgu1IJtD/M9kDj7MB2cgeLqblBQbC9su/AG3JFhhJSQHZJ08g87CPV7gYqLcRxT1VRHa0sTF0reiN3/rjmKIld/3BKMlZPk1pLGrqCIuQn/4PUJWDVHV7CV65wKum8LiA8IFVqmMO3nGf9CHvORoxUdGQ+x9mxo+2RG20p0txeTJnN78i9pePPrmIQYrGDYkyIxQbQkLlxzWFhoIOW3ShJiw9VogwRpH2f1H81if5CPo3byEEfeGPhvfGM3YNjBghb9zu3YHenaD1n3BNg+TzAV0MspT6o0fhqa4NnPeixq+wr9NWrFfNI/1QgRLQcQqmgPIyfTrMeb0TlsHgNPA+ai4fVuZibH35KeJxGBvDJd90QDo8n8Qi+x7f1FRoznnzQt60O/W9ADK14+yeQEifGabuAZSlOtvZxBL8AaKjUtBjKZXwU1leEiscogvykBc9cMafDDP7c+2afLmjR6HX4z70Yg43Xok1ZqxaFd6Wb8IDsvG08SDKCsZlXgnIxDiGM/xSXaE529hAY/cLdGMufTNtT9JcMjkKF4b91Waxn6p4F29D/vzJy8Rx9SqU2tiLUpzhr5e15At+grfWnZfyeqoBevN2+221ac8ylgcmY9v+hE/j4rSR8i8alpYwpKr+j9lGA2p1F1HXwMoshukMYCK/07yB/ANao4EKuRNybiO0hmKlceJ+tBILiCThRzoekpXb98SULZ+X+jpNxyJLMP5eQ86dky97/b4ZFylMnT9K0Z5ldJ2VQ3ZMo5WlhA2h2BAqfOGIjoYojPFwCCUnd8mWQf6dedXGNtgThFObmgxam48xjGbZCnmXbHu7pK+VpEqffZwOq2X/w/DaJYYNkye2YAF0iPmLDmv0KcPVigRQMvIIHu7JnxfPn8P16Fxc03oRgjWh/sru1i5dgsVhzVh/J4+s68CsWVD81WaKr+zK7dv6659GI+n7pBn+84nRsyd4e9VlSblVHIgqR79D1YRS+JOgtDJwIq7ve00UxjxZfjL5jVM5P5Xy0r077HJqx8EWK4RM3Q8ewKHQhNb0il3ICgoAOJsEkw1vMhq/EkpZ3rgRCh2fxkjGMeFufa5fFxu3dJoHzKUHMzL/SZEiAvN1hqpud6nKQTwNn4oNmohJb9rzl/x4TAoUgPNt5gOwT1uR339XNu6qD/U5fVr+9sbGkD2NvmR8Xq4zcYT8g8PGBibVu4AX+ui8E9cEixAmXn0FDkpDQzgy6iQtWUV27pMvY4Cy2hQKS+3XZhfZeUi+TmINqOysE9KLRjxux0mB63PdPpkoykWiYxIuebJ3mSSxhPaU5yjFlnYSqrpaoo4jpkRx4bkLd8nF0SmX5QsnwsJM/9vDZK5ra1bqeIQnfSwXMtRuvvCND4CpkY6waFMkxEstxCOQ/jt2LOQPPEqBEzOxJQTPWvITI8qUgZ5Wy+hZ+FwSi7UcPeDpUzivLcD5l+6EhelDZmL2HSYIe7bM+ecqdw4OkMX0OW8jrJn1riUzb1SUXRPnM+JSwuT2UpCkz8yldhltMSbmpyix+1MpL/nyQS37M1R2vSPUN2f9ergb6QmAhZFWyN1UsyYUs9Y3nvn1cFe2bBGYcGIUlK1PgfhXEERYy3Nzg+IuT+Jfi1wEjIwgrUXCSS8ytKsr9C1xAQAtZkIl/t3c4P7g5UhouE5+8mUTj6WIS8ONjJJ/OkoSBIUZE4QtH7BUpFGvojX3ycm14VuFOjzn6VGa3Nyi6cMxwsrL/B0uXEGvtOhiDYQsPvfW32QvCdW3lIa9LKALqzqdwFDA8POMjBynPBf8MiquogwIxUQUKxhDNfZRLf8b1o1/zF6qs2zUU9nynjxmZtopTLQYTxX5eQLx2FlE4ZXGn8KGV/RpzzLo3BkWGv7GwubH9NfJFFgTIiLl+zF//RX+5zCa/1Xdy9ixcKtwe57U6U2lSsLDAmBg/7HWvpx0aUnCwjhB+5d7XOp0EKUzJCrWSB/KZGiovyGQsa82boTKt2dS+eCApDdb1tZ6heYnqPXyUykvgN53lIIFeUuFeeTNK3/7nDmhqdOR+NfCQyssRJZ4MWqT7gC1BLwwb9/Csdc5OUY5nofYJi/wKQrnnCUL/FkuQbsTXY9tTLX8yiZasprSpeTXOXBwgF7FlNeXSYIC4SNUJARrwtfukC0TEgL2vzXFniB+ZXPKJi0oe8fXmjvkZsPrcrhf3My0afJlhyxMuC3uVP6RcK2W/FxjY55x7Ez/Gy1ayJdrVzeAXsxmeAc/upiuoGWeW7KrIe86YsEWGsa/Fjms8+eOpgwnKJ3jY4E9AY1rxtgP7KMG+0adp06NGKqznyKZZNbkiTsHzcyE/98BA6BQ7AWaLKrEiX47uGhQnCEyW1FVqgSdDJbQqeQ9rKzg6QcnbpCHq+eTj/UpWxa6mi0HwJNHlM4l1gQzDhcXyJ32HR7IK7A5axZIHpmQhv2eYGWOK2cuUwmom+kmh4oO53TJwVSW2Wpj2jQwvXAS05WL2LkTdu+GQUyh29qS+Pr+s+zTp3A4uDCH/XInrR1mYKBXYFTl5T+IAuWlfHkY7zKX8fxOVtNkjqovkMY4EC/uUMDWR6jE//btkOvMQjRI9LnRFh8f+bKNG4NUrz4SGpZnHhvfvEsOx49DhSO/U4FjbH5XRr4g+sSEDT6F0CBhcusyI0cKiZPH6RXvcSDM0Z3//U9M1sE8gk00ZhWt6N5FrPS8o0UE0+nHn/SgQ/sUFHhSkI1iRzDWfMA4Rpkp4QDVKFTXVZEsIGzCsDJL2LfPo9Ph7/8PG/8NObnLwlanhAo+AqTjDY08LlPbaJ9QIOboLn7Mpg/jfnulN88L+EGGTHXgLrkwIhpds5bUFuj7uXBqMCcox7HJesue4iynOJeCqP9GgWvPxweuUIgrvs7EmFl9DNwRa94ZR8leBcjHDep2TT7LqmVLmG81EGnAQB6Rlb1DTokNltiNoiS1XKNJ8MLYyrO8PHoEB4KL8SAwDfnT+VHS/KqsHlBf4uhR+CO8B/MvFuL5c2Xfce0aLDLqyh/7civ+jtTCT6W8fPgAzyR3Hr61k108EfT+1N/TLeF3JuJpIn5ENHM+zB1yc6V4DyELyMuXcDdMH8Q527cB27cLD60nBZamfn6DmDBB/vZHj0LTY10AfX8RkZR0ACODWBwIxCIqSMis/+4drLmdlzU05woFhJUIa9Mo+jGT7sylcnnBnjuSxCtceIQnD+/LD9h9/RoyDGtFBp7Tmb+E5mxkBNV+SYhGfP1O/s6KjoYGfxSjAVsYbjRZeF8FbzjARQpjaxJOOsO3Qi6npQPvs46mTGOAcmuRgjovSRBUXuIwJwIDrbJu1qtOuNPDYC4dFhVV5nYSdL8sX2nAcMYx/E1PfSVjgYqrhoZgRDRGBrFg8TFtWXR/fdQCrD7qXHL7DAGKso0+IwWp0gA7T9kziSEM+cvjH6exciVUezKfqrt7cjUih5By6uYGZayvUSbtAxwdSRLKkFzYS58+EFq0EqEtuiZRprdsgc4BUxh0tBr378ueSqrkp0qVXrwY+l7dCldhbSOFKa2CikBkJETGWAG2WEbEILM1ydcYWrFgjhxQKd0tDr/Wl3J/I1BJ/VNE4oOAhIuI4ML26BG03NUEaEIfZlIwMhK5gU2SBLoYAEM0SBhGRiK3iczbtzB6S0Xmo6/b7tIuilcyLfs6HbwMsgKsCNA4QaT8YmCWlrBvwBGKtMmBHy64ONoB8vwgkgTbLmYAMrAtBl5vuczgpmIppYW5TFCnQfpueiPlz7thmXfAx47QkWKtrKevSUc4w7F/lp0eEeKtGOLQWVgTFhCDWZS8Rpq/dwsksN9YjM2NFS+oh645sSq2G5yDQf7Iq/cUdy5oNARGWRJIJsLuGZFTRtryug0GHGQ4PIf/UY+qDWPZtFWegrt5M2BgCvMXQIaPwS5hYbJO5uhokCRjiDHAWIKGtbT4/7kcu6oVAc/kB5ckvXKq0Qjt67FjYY3fMZhry/LqEBOchw9+BmS49bFLtiDL1pmynUmwC3oFyixWa2YOb+Qrec2bQ/M53cDLC0ovIX16qLCjNzauVmQp+c93jCYmYGIYAcbaJKu4nV3C8/+65+insrwk9n+KKgInQgtQgz1UODNOKOj2f/8D+wv7sSeI3a/Fsiu6dIHrxbrSn2mMTiueMRClM+QZ7jwMSSdU4C5PHpiZfxVWhOKkeS+U5ZQ+PbTwPE8LVrPNogVjx8qXPXsWMi0fSSYeMy26l+LuqoCQ8nPzJhiPGY4xMXRjntDBERIC88/li3+tjZJ/h2loCBns9HeHe6TqLDyWRcxSJUlcpCjPcefiXGVZLABLbhQSSi1PUap0YgQV1CmrXRnJOIZe/RXfCGde/XMiyBeZsNQFowd3sJ07kcMyS480rx1Kd+bR2W6jYmuRpVlCcI9cI0b/UVbUYhe1xhWhY3cTPHlMnuF1hG8mQrHhzWsFTT81GgauzE0bltNrqLzmSE2bgmlMGKa9uvDqFUycILGQLkxtJHB8ajTC1rW3b+FhjCcPA5y4cQPKbOpJjed/sXBh8rKnTsHc0FbMvVI0ft/a2iacx/9kpS9XDkamWcDgAoeIMbHgeoC7UG+0xGTODGXdn5Df6Ja8+64vZBtVqQKL8sxhc8FJFJdZxyi18lMpL1mzQiPXM7RKf4RMmcRk38bYs48aHAvMp/jgFM1HNTKCvNaPmcZARtn/j5IC1dMuX4Ya50bgwTOy+x4Scv0A5LZ7QSg2vLPxZOpU+XIFCsDqcotZTSvqxW4VGjMiAp6GOPKUTMykL7u3yd9fHh4wp/JOAGbRlwYdRE0+eiQ0RIcqD35tWk7+ypIuHTyfsJKOmiVEYk6XzVV48ULhwIIF7l7O30knEq7sitZkhanSs+lFMc6Rb3Zbbt8WH/ZDtBkZY3zo1FH+gly2Yxay8YDh8xJig0Q8IS9Iz9LoVsx9WoOLF5PfPo7BE2xozAau+thw0a0hd9r+gZeXPNkzF43ZQy32XE6HpWXCIiXHGzJ5fAyH0KfapMMPZ3slufCw7mhaVtKGrQcFOjsmJi5WR8akR4yA3EGn0AwdQuGoM9RZUJ1nz+QNY2EB9pog7M3C48NVZA7Lpk3QI2AcPfbXjg+U7dYNtjl35mjzxf+YaVWhAoxJN58mWa9SY3N78j/fyeTJ8ub8RUQaQn6BPHmgY77LNDTbQ3qxzhupjp9KealYETaW+ZOV2ScKWTEmTYLGT/+Ify1itcmUCTzN9CvS0Bfd2LhRvmwSBFeXmzfhiH9CWtQPSZXWaoV87SYmYG+qX1FekZ4p0+Qfni4u0KPAWZzRF1+7fldmKgn662spd/1VaxGdyVdFfjFBNze42mclV8nPEzyY2/mGbNk4zDQJ+1ixIUPg+NBowNUhkhGM42LmptyqN4JSpeQPNXlzFiYzmJX3CusVcoGUofdBhlwnHxcoxo03LkLlKNaO9mYTv8a/jgiTP+7jl6Z4o2+NXNzuLpWcbwi16rhNbjr4T6HHkwHsFWi5dfi0KZtozDUfGwo7PsbLQl4GzKeUKAHNzLfTMf8VWTFG+fPGUokjSO3a44crW+Yo6y1i+XGssHB5FkUvLyjDScpkfaV3yRka6uNPZCzIL1/CHZ2+IuZlXX523csqOxh86lQISP8LAYOmULUqDKx0lTGGY2jQQJ78pxQpAvVcLlDe/nryHbklCUvjhIBm4XAqBT2Vbt2CFW+rs8K7xOeZSfb2+t4j/3F+qpgXQFG2UeJ1YZtHX2oPnilbtlEjcB0zjlJ3/uJBVGYuXNBnAslGYdrxpwibEBPHnnzBPClLVpL0i5vMnNTSpeF9p6EY/jkLCQO0keJZP3E1U2Jj5ctmyQKnOizHedRv+OMstKtNTSF/+rfAdf0bCkwYjQy2kNPpHWb5cuDh0USWzIcP0HRmBWAXhbjMaAXjuvECNwcfMNOAvEbHAAxdmROYDJvgIeNIPyea3/rIi6fI2LwEYegz2MwMo4iOlq9kViocTCxbqZndG/MH1/mlWA3kXsJsrXSEvQnA1dOcs/lG6iMiKxyQN7AkYU6CVqlYwRQMFD6wPpCYbDmRVq/FqUVVus4aAhVqgVtB+WPGBWsIHB87d8JjesPh3KydG4hlzbJYzZsPJN86fNw4YFIF6PcnOHfVvylzQTYzAys+8CHRwahkXzs4wNSWt+DwaKg2DJKJNGzVCoqs7QOlSpEpU4JyjK2tbCuIg1k4LYs8wOLSSYpX7CRLZvt2WPdwHLyxZeBlfWyOT1QWgt++w+HBPzfh3bMHhvqMAB/Yfg3cEzeitbdHOFMiFaIqLzJwcoIcpo9Bq8VZ91ooCwbAzCBBKxcZ+u5duPCqKpCBMuE35YS7xVO9OhwvMQzOniGriS+u7Z8kL/SR7duh+465wDTGMpIOAgoIQEysAaMYjxZT3GfF0kugHYxGA3PoiRExuHQbC6SVLwx4kxVjojHYeBIQMCcABbhKMLZkyJodEMzhjTuuFKRKlzE4TZl0/pC1NKSRp7xER8OeG26AG3uoRfDyO4yrnbQZniwU1AFJzASGU2xNNL/1EZPLZXiP2x1mQXmBMsqAARK7u+yGfv2g+zNAnjvj9oa7UKgQbLoKsyz1qV4yyVktI/c5AcBKp37kbjpDtuye5f5EFywKy1bDKjHlxdZGAgLA5uP1QySDJnFcEghpAYsXwy5mwUZ4My6INDwAMwX58OjbBfz1/hAhM9OwqjLxTQS/xLx5MG9DRt51H03Yxj2YlyyAQ1HBHlZxN1mJU8sTR7F+gcKFobDlNshjA06JlBcbG9lRr07mYazqfgHadIbmbZATPH/vHmwMqAQB0OKV/hKSZ0k/ADpOg0WLZA39GdG2TgQFGBLjp7dI/1dRlRcZ9OwJPZc0gBs3wNBDeMic5k+5QgFM7S1xGiG/dsGRI9Dr7gD9i2Bo0xaWL5cn6+ICLk53gJMQhZD1JCICXkU4ADCQP4hdoKNTL3njnjwJA3cP5SL6YmTFN0ULKS8A3Zmnf1KmH0LKiyRhahQLMZIiS9UBqumfjDsD/MNV9gvjKlFegoJg8o5iEDOeX8I+0CJSJGo2KbMO5mJgiDzlRaeDnRdcgXo4RWaidOQ9obG2D7sIEydQD31RvYhw+VauaoUDiDx1kYxm/spNGAoW5CQoTJW2NfpAK8O1kF++8pLOWQe8INAshovavIT5GpD5GWQUa2OlR2Devs81hJMdwtzIhgaDlHbhVpgq7e8P17VeoEVeirgk4WwVgbNdEGjeJmc0+Uw2nsSp5ckoL5/Jor858DfJSPCLUOxe6+PTvsTEiTDr7jF4ZMIW5yuUBuJ7DAiSuAZYcjpT1apgt3AquKQjT57W8e+HhIBt3+5Adyq11HHoyH+3u/RPFfNy5w6U3daHog9XMUP+9ScpChZFC0MtBbhGrpgbpBUzJCQhBXFcQkWmLCwgvbn+ShOIA0tXytdxAwPhon9CFVWtVkGWQxwCisCZM6CZOgVNTDQD+EORBUTJuBERcPapK1XDt+LMWwqMriM7sys0FKYcKsiU2IHsCCkntBjb2oL/nHVU5mD8e3IPzehoaDCjFA3YRvVrEzjpl1V2YCRA3aKvqctO9g47zSEqsXS8/HiKzaNusZvazHWZIPwf+foZ85SMvIj4GKzynZSXvDkiKcY5Ctk9UmylOnjViaInplLh4mT52YqJUqUBIctL+67G5OQ+ORf0pjezGfg/+VUqBw6E9TRhfeej2DiZ6CO8FTY3srEBY000TqYh8kOjNBr9RUigZsq+fTAupDfjTpTRn38pbHJ4+DC4bptLzksrWbDg77cLC4N3OkfeRVgTbSRWE6dbN3iWtw7Pmg6mUiW9u6td6Uf0Zha1qv5zgHX+/NA17Ta65jiRJPnE2hoMDfRZmoH+guWrUxk/leUlPBxOvtAvrEXke1EACI0xZxfN0AY74HFMX3VXDps2wYp7fwCBDI+YQjGBMcuXh8meixji0wkDdLik1SCkbyZekLVa5JYzrVsX6tbpjsmGlURjIq6AfKQmu5k8JS8grzGKjw+suFADSENZjlPxO/VVevoUhmxqCGSnMofoIDCury+UnJdQp97/hbLrpWRgRGSYDgOZtUcMDMDRMpLp9Oe9ZUZMWzfBxaWV8LhhOnPK3vgfE9Ygu3Nw3HFVvWQIcAQyBwGCpgQF7qoC7fPynqdkmRqKNyhSXp6/MWHIgVaEPa9Ihf9BLxkWxfUzX8PeElChMez4fqnSh06YEEBjNKdccLKAkRenExZpRP/V+mq0/0iiU/ZPesImmCrT+KpvrbERClfG52UFnppUJ+xiOsq2JEkmz5eYNg0u6dbCooIsaAw9ekCvE031F996MmrzxF2zBJWXXbtgfuhAOA61XkPjXvl4wBusK9ngk0wGX0QERMVag9YMK50+xjjx7/ynm0YHB8hs/BwszDGz/Xh9lfkH29qCrekbsEoLHw1cS/vdhlN9oW5LIJlSvV+wpms0UKVIMAbnz5Ajf7HkvyMV81MpL4nXbpGGcAD+OntasBbCodki+cqLjw/sCdLnOHeKWSTkvsmdG3J7bGCwT2f9G9M+INfHHxAAL0MyUg5/HHlP0Q4mrNokb85xbDVohFGsFofRi5CrgNStC1K79rBsGRKgcZefC/v4MYy7VB2oTgyGFA+Kijunk8XKCoq6POOCX0Z2UwvXrWF0ryVPXwsMhA13cgO5cSCADimIATE21BEVJc9U6+wMx3ptY+WfISx704bNO0qzYJm+vo9cfuE2WL2DtIVBZhaLkRFMaXadg+v8OfIxnVZxqjQIl7x/hCcHQloRed+Wspf1oShC8q+tKctx6JqTEzKTu2atcSaU4bxeloa1t5yBPNgIlsaJMbEgQmuMFBSLjZ28m4gT50wIoRYPX1jSI98pLJ/fp0QJeQGdv0+24hIbMJgmsaU4nPHXd1mWk05fpaKODMdXsYK28e9ptYhlOmk0zJgB88J2wEq43AsKJhMrfOYMbKcxXIHZWr2SjY2NrBijPXvgdmRv3uwqTwGtGWaRQeS+ry+aKcr7EBPeYUVkYPIX+oEDYe7LOzAVLjfW/0YXF6iX8wE2j69TqNDfx6H17w/9l1WHSpWou2E0T7iBTdP0nL4mPmcgwXcUEoLSPgN7l74Gr9rQ4SToHVn/SX4q5SV3btBOmoHxpLFo5gfJltu9G5a+6h//WunadpxypD8bRaGSgsGgJiZ6t49WS/J5e3q2boVOJ+YAEIAjlvfEe5PUMj+iv4vIocBfZWqKRqtVnCU1iWHMrK0jQqZ43rxwvuVcas+txu7wCvRfC61nyzY2xTOfbvhP8WVldXkXent76Ff6ElEXrlHU+i4tu9lALnmV+czMoFzWl7w2vMiy2DaAQk+Iublwa4FBde5Tb91I/sz9F2YvfShVqqMsWUmCV+/NAFdMomxxFp20JHGDvPTw1QdC/XFcvvLSoOx7QnceYz3NOElZDG5Lsu8F/lidjleMw2BzgklCtidEkgjFCpvVy4BlVP5Vx0GZBe76jLHnOrswXa4jctAqWLUKZGajJCbOC2KsiSYmJvlAkEH9YmBEO7qPdOLD2OmYjRiIsXEN4XETX24UemBkZxtt3AgrI0fDKeBj5/HJO+QpL926Qc0NraFaNTJnbo67m4TWxwebdE5Ikq1QsiToS1xs635YHxjePJkg+o/WonvPLPAmD/Y+gjV1Pk2VhmT3lySBJGlA0qD59Bxw0Mcr/tczjoRiXiZNmkThwoWxtrYmTZo01KtXjwcPHiTZJjIyku7du+Po6IiVlRUNGzbkTUrqy39FDAzAxNIYTZTYgnrhAmwLqQhAQzbTrYt8X2Lv3vAyv76h0Sz60n+QYABVXLlsSFFWiKRTEHsSt/IriR+JkxVQXgoUgIN1/ox/rY02ECkTA4BposwuudPOlQue9p6Jl6G+GcimC+6yjQlp0sD0WseYYzGYlo77FP1HaXlDUScfytpclZ0doNXChgsebKAxp3QlFI2bDW/+V2knU63HUaWKPBlJggwdqpKBl5To5MVDsnL9lqHs/6neqDz8irLO4QsH+bCO5pTOGxI/F8G6j6R1jMF7ylZe4cLKxfIV+rgUfICIMIWVnwVjbfp2CmMmfZje4S7lyoF20AiiPLIzfLgM4Y9/SOHsIZQ3OEnx9M9lZ0kGB0n444h/qCnly8PQtEsZX2h70nTcv2HhQnhGRp5NWoNzXLmkFBRek3se5s4NNc2OUDObN7a2sH9XND5k4dqEfckqLjlzQhXTE1TxfJS0ca6Njf6mUc5BqtFgZQ3mhGNuIm998PaGXYEl2fUsT0LVZJnKy6RJYHjxHIZLF7F79ycfxrVxUJWXBE6cOEH37t05f/48hw4dIjo6mipVqhCW6ITs27cvu3btYtOmTZw4cYJXr17RQGmloG9BXFaI6Kr4ka4soFIp+Vdcc3NwMU5IMxSpXaLTQXSsIdEmlsSiEVIEsmeHjm4HaG22gZOU5vomb9my167BkJvNGBI1hrMUV2Q9eWKcjRvk4fIN+ekCjo5Q2e0+Ha3WU5LTlM/1TqT+GQDdbdewwqwLG1rtlt1XycQEMtoFk834afx7wj85rqS5AkWvvOFJzv86jeOeHWkiL1Oa0FBo+ld5mrKBtm8mc/VFGqGCb/EIWm0S88jXlOw8JH+fsrK/4uCVhMpwG9378+uv/7Dx37Bnvi8RmKFbtkp2UsfKUY/ZQw1WT/AlS+ZYXHiNJfIUiQFTnGnLcgAqcYhCueUfHD3ahDKBYYxp/VivvAi42JrVj6QPs+lT9ylGRmBiY6Ys60ewjUOLlhqc8ce5b0uKFIGJ2Vfwe/bNsqqSOzuDu+Y57g5hGBrqs2ZmXi/P2LddWL/+n2V79YJtFi2YUfsYAwsf5w+nyVStKnvaeuI0lTiXpgxzUffucMC5JQdark7a30tmZ+k4rhwLJRxLXi6UV8Vw40ao4z2DOgd7cOmS/r02w93Izn3S1y+idInSX9AsLP7zyouQ22j//v1JXi9fvpw0adJw5coVypQpQ3BwMEuWLGHt2rVUqFABgGXLlpEzZ07Onz9PsWIi4arfCFNTveISEyO7+V7XrlBvfRMIDiHru4tC7hvQn0/9rf7C6EMgHg07Aw6y5P78E/oc12eTOPOWLlMNGDdf3pilS0PpvH/qS+36+gqtxnfvwpT79QDQEo3DQwNyyMwcfvwY9t8vT/f3ywAw7hlLVFfZQwOwKMMYuH8fBq8Co+QiExMhSZS3vAhRgZAjI1gKtPAG/mc3kqmBAzEb0oc0aToIjQsIKy9RUeDt5wCSF7Yx6cigUIl4HOVGwc1D2d5SH3MkixT0J2pY/CWcO8eWRNVuw8JkNq/7SB7bZzQy3QU5pguNDWBtZwhGOoiQrwhULBIK7IMiH+BVohogMjTcnUet8KYFDubhHIqoAkN9kFvVr0OTDzB4EjQpD76W+n0dG/sxGEQQ0U7JoFypToyS1PKPSkRYGPTbXQGoQP2NEk2b/r0ZpGBBKGi0G8oW0GvnixdDiSHyx0y82hsY6OedXHvmL8nGEWcFCQ7Wm1i/wO7dcPT1QDjpQbeOVmQBxZlZAC/emvCQ7BCg/5q/K32QIQOUsLoBFpbY22dJ8tny5bBJt5PA6VlZVFlvWf4vkqJU6eCPyegOH31sV65cITo6mkqVKsVvkyNHDtzd3Tl37twXv0Or1RISEpLk8a3Q6WDRGS/+pDsb18qP2E2fHgqa36OgjTc2hCq6EExLN43JDKVrIznFDj7nHWlYsd0m+Q0/JYUup1n05ZeORWRvf+MGdD+fUHcgOsZArL+iJCWk2wgoXA8eQOu9TWntN4X1sY0UWUDcjPzIav4CN4v3woUIb+tyMj+gCbOulZXdit7PD3JPakFu7RUGnKkvpERYWsLMpufJyNP49+T+5LAwsGzXCEs+UHNtc6F9ZWAAmwdeZDONmDYmjFYGa+hS8rbs/fVy7UkCsOdU9YkpS2cXzEaJR6NJWsBMVBYUnUuRUQbkGNEIN3ypX1fmCfGlVOnwcFkNS3/rbUJhLpK5dy2uGRXmio+t7HW8cGGJmuymZh5f/f2dpaWY0pTof0rshgkJFLgQCP6/79/D05gMPA20TagKYW0tX3n5Ai2n5qEo5ynb9G+KvACnT8PMgLbMvFqOl+9M9CeIzHmXKwcT0s9jQuHt8dV07Z0MsCMQd4fQf/ya1q3hjFdnztSZ8llrD29v2KutyLkX7oqal6YWFCsvsbGx9OnTh5IlS5I7d24AXr9+jYmJCXafFAVKmzYtr/8m2nzSpEnY2trGP9z+qQvWV6DzosL05E9mzRWMVf4Yx6HDgMgQ+b7yu3dhg39FNkTW5SWuQguyqyuUtr0Z/1qrFYw6Uxh7UqkSHC83Kv51jM5A2H0TR89qD2UrL2Fh8DAoDQ+jPHhvnE5okXj7FlbdLciq0Hpcjc0nJBscDHseZmVPRAVuG+YVkn30CDJP7cIvIWfo9qgffS+34LKSBs+GBkLjmptDn0p3WExH2qc/QLfM+8icOXm5OMK1RoRjyd77nmSM9qZlC/E4jv7dI1lp25MFdfbKdtHZW8dgT5B+URNUAmoM9KIUp2g2IL1+cVN4h3vyQVq2UY8tO+VZXg8t8cWbLFwa8LExmYKoahOjWB742fACN/xeie9rnQ4Wnf+FWfRm1ZLkrz8PvDVcpjBP3lpR4M0+Ci3+jWsyM2BGjZDYTW129z6s/5+srGTv64sXYRe12HXDPd5AvXbAVfZQg2m/y3RjxCmYAv/v779DpncXyTSrN/fuwaFDMEA7ns5bqnBPbg3GT4Jjrj2y4iJFuXxXZs6j4LxLloRhLssYln9fvLtq82YNgfaePBs8/++MPQn8TbR64nPxG9oCfjiKs426d+/O7du3OX36dIomMHToUPr16xf/OiQk5JspMIaGYGQYS4xOWd+cNA9P8Q4HslaL4uFTeTLbt8PvPvqWzjt5QHqBC3ajRtBofh8uv85A7L37WMyYR1wUvly2R1TlBWWIWudCvwryZNKmhbTO9xiZYQmPXphhWrY4Ol1mWXfXBQvCylIL4eVL8j/ZQu5mg8Aom6xxT5+Gamv1StMok0mMVpip9EFjg3+QEdYyS9s8egS11rcEWtLdegV/ah/KHis6Gp4E2CV5T+5fbGUFHYrd4c3FZ2y4XQOd8XxKzIS+fWUPTyWOUKmQlX4ihavLktFo4Be3QMKeB/AYT3zJyOtXCrVTUQuIJBGLhjBDOyLDLTEMSEiOSI7zd6wJpBTshcpOrQk/lZf6L5HVPdfXzxgdHhi9NqbjhEx4sw27sdE0HJi8bEbXaMAHMnxUGkSUro9WCANDDekctGgC3uNoY4ec8vHFajlxhSiM6hsQHgldlhRGogiF50XRKpmEJQMDMCQGXaJLvLDOpdFw+jQ02TSTsAgD+o6BUaP+WWTCBNjJLpgLb0bqvS3Nan+AafvAPYB/qjsSEAARunQQbEVaNxOMoqKQomPQGIsvU+fOwfTADhAIdR/rg3L/jvnzYZ//UlibkVmtiL8JsHfQKwbGBjqiow2/GGXw229QZ10zKFGC9yE9mUZ/wnYXpFNT/c2nIlLYWbpzZ2hzpDV2BGHccKfi7/m3o0h56dGjB7t37+bkyZNkyJBQuTFdunRERUURFBSUxPry5s0b0v1NfWVTU1NMRfNZU8Ci/g8wmjqBNP2mAvKOrufP4VX4L7yL0V9lU9QjUYFwIccnwCVwld8pdMsWGH9qNtdDPnZEWgy9FyDkDhmTdQ28OAZtl4GJvNt6d3do5XkWYr3h6V3F7qoxUUO5ueQBMxqAh0fy2xcqBA/bT2b85hzMD2jC/EVN2F0XatYUG/dQZBl23Ymh2DsSsiX+AUNDcLYM412YJbbGYfyVYxaFK/wuayxHR1jc7Ai+1+eyO7IGm6PrYXBebL6A3gwjYB63sICbk/eha9EKR4sIzMPfY2ftAAj6yhRUQgV4hStu86cAU/i1i76Qoygd/KfAIch5X57yUqSdF294QsZ2UfF3pmGRYr930PYSPGQb0sBs7DgrT6bkr+m4TRDmjc14vfeavkPqnFtA7mRlY3QQgzHoYtFowMpcR2i4ER9k/NWHd0aAjQ07B5xk24oQLBzNSJ++orxJJ8LAAF6F2QGy2/x8jswMml69YE3YA/hYacCMJhStAMdldFQpVAiCV2yDrFmxs8ud1F2VjB5w6xbs0laBhzAm0W88cNAAM1tDDP+3EIy/HAOXMSNktLgOrq70PQqzQkfBMaj8VEB5+dR6kkLlxcYGSGcID5T1o0otCLmNJEmiR48ebNu2jaNHj5Lpk/DzggULYmxszJEjR+Lfe/DgAb6+vhQXbmv8bWhbN5CWrKFKkSDZMgsWQLHHa+NfF/GSv1BUqgQz3fS9COqwC4+GBWTLAopdP+/fk6C4ICyuH9fISH9iiSpcceZMwT5Srq7QOlvC6r3tbnb8ZZ5/5uaQ1d6f3KYJVhO5epOrK4wrdwQNsTyMzkSdHR1km9izZYO3w+cgOTgS1PQ3mtgdEHLfAJhpEvZRpIhFMC62wNRUkZJoSCxBq3bjhyub58vb0TodlB9RivIcpdcQC2HlZf3xdGwlIfswMkL+73238zwxGDKmZ8JclYS9dO8UzWQGM6PNTaGMjmMPXNhBPXZfcJIt9yHMgBBsCQk3Eu4TlDNLDAW5TAFP/UK2YMgz1tGUOYOey55zncJ+LMs7i7l5FpI7eX3pM2xtIb1NCNkMH8mykLVsCRMYxoR6lxJyGmQqL58SiTnhH+S52Dp2hHV23VjXaBsZM0LDhnCy5FCulepJDfHyNgBY2hhiaGOVfNbOx+td4hwOkRpCnyFDedm2DZr7jKX50Y5fvlbZ2+tNWf9hhCwv3bt3Z+3atezYsQNra+v4OBZbW1vMzc2xtbWlQ4cO9OvXDwcHB2xsbOjZsyfFixf/d2QagSJFIDFHqECFUaOBMrK2L1IEiqRbz6rgOlwNycKLdwqsTHFBtwJzNjTU1zzRxppQmYN06maMsbG8ssBBQfAi2A0+2ONi6oqjUlOToPLyyy+wouJKnIIeMeOtPstIdOjMxi+o5HAFM1NIkyaZcqAfcXGB4aVPoLl2leHBAxWNG5/VoUDRc+Q9D6dux2xQT6z/8kZOqdy3byF91/ZAG2qfuM1WR/HCZ0DCsSXTpyBJcPyOM1Ce44vgotUawn1tmFYHWbVi2k7LhZb/AVCbnRQuUA05LhSIsxrGUrv8B1wOrsDCwYz8+bvLkq1fNpDgbUdwKleFjl2toc9UKJMLNPmSlT112ZxwqnDZR796x8ZqZCcrZnaPJvr+I0wzuAkHCq/6XyBsLQyz9gLVaf5rFIzcAF49ILke8ykIbh45SsMl9sLMX9h4Bl6MWqz3Fw1P/qatUSOASVAzM1gWBiBEY0sg7oTekvAq9/eJVoULQ+T67ZArFyd9M5Iu6D5Z3TMh9/gA4q0Ybm7glumFPtMymZYGU6bAmC25oW1b7HIPSPqhnR1yaxA0aQL5Ng7DwiMN+fP3SXb7qVNhwrXjcMuQTQ3058/t27DzXUdC3tpQ95zeUPclbt+GdQHVIABa+ul7HSXB3l5NlU7M/Pn6PN1y5coleX/ZsmW0bdsWgJkzZ2JgYEDDhg3RarVUrVqVefPmfZXJfhUUKC8lSkBvh1Vgb08GnxfKCpGZh+Aa8hJTZzt0OktZ7ps9e2DVnRE8iXGjJZnIf8OaonXlXTQ7dIAOW+vrM3d27oQ880Cm8rJrF/yfvb8Maytr3//hTwgS3ClWpdSFuru7u7u7Tjv1duru7u7u7jp1d6NAsWIhEPK82FACRPZO7+/vmZn+z+O4j3ua7CtrsbOz1rkuOa+OpwVv0VLr4fSV8PcmJECcSsG09304GF0SzQwXDtaXJvE9OtN6+jluQVGhBG4lpog31Gho5nCaZkXfCTtdhQPibYEKVrf4M8tGFM425MrVQtK4gMklqXIzDf7ZE4HPoFAiVuc/UW0GmLH/fRHyB+6g61xBrlzSnH+xQ/PNaKEOMyREml2ATzCHvjSCwaGIlQ5IQZF88RTJeV74IfiKIy/LR72H/e1g9EOwdBWeD5EkostYb95wEoBAPFEsX4C5eWtRtvtXBEOO/LDyDNgm16ya4i4CoXoGpFfQ2NgIbFck7tyFE9SBR8ltVFKSUCW0NtG+rmUvZ07yAQZDeCf9TZ4HDYJBf3aALlOEXbt0aZj6ECgobsz0Xgx7e1HeHnt7sJeHgW1sxi7Wzs4GycuXLxAclweCffDPDgWz3AIXN1EtheLj4UeSHahS29U8eABjX3YGwPu2fvJi7HMPvy9OeGgTPA5oaNRYYqHHvwSSyItGhK9UoVCwdOlSli5davKk/i+hMlOgxJ74b2pEpDQAQt5EPa+ZgmvgzSuTvDbHqs2Fbdtg/jaQtxFl8+IF7AwRsmxvsRimQvBAcbkYP2FC+EYb/eLmsHZBIFsbiiMghw5B8x0rU18IlbjWajS4W0TgbikDixDRh66wMLjzPhfERJBNZUMumXhRvpRxKypuUTF3pOArzy2BvABJGhlxZvYoYxRY/EhbIqoPX75A/dltIK4ytXfaMh0EEqFvddeCuTkUyxrC3Q/Cw/A0PqfoskilEgavKwksJ+/h7AxKGVcE5HKI27Yf2rZh3eww+o2wwdosnsREcR7FeT1foF66HLfajWAtJiW/AsKGbEoShkyWWhUikUS4OSXgGREE8igwYT/YdtSRp0whZpk/M2qISCZPXyotgbzsOWDOFwbCcX/6K2yRm0qYQMgs12iEZ8TGSOWNjj1Cuw/Ujx9GHm/txoxgOtED4Uf4C6XSz5/DhdiOhF/xoe4DoQVJeixYAHM+HoDNcLknlJdQbeTmBnkU70ChwNZWkNYW2xCyf39ov6shFChApsp/pXkvIQFarBN6xFVdoKZRY4m5bP8S/Fa9jQBKtczCfX5g2TKJeCntfrRl+k3JAfnFcFUKJOetgGSPQM6c0D3bGda8F/R67gV6mZys56yIRa0W215RCxLn/OgR1NrXC+jFKPvDzHB/JH3MlHEl3OTgYFh6pgJ3oopzbGENYBr9x8LixcZtVSq4/8UD8CBvaLKUgEgS4eICd8Ye4F7P5ZQyu41CE4dcLk44LSEBVp7zB/xhPnxnMupFnvy1xbitTAYKyyQgnl6d4+l9pztmIUHQ6axRW4C+9T/C0iVQsYRk8rL+WCZU9MTpuD2tbGyQJGKRflO1tUUTHQMinAkD24USNmMlNm27wHprkzfUrXsVHONPOA5jo6T33UpU2BGFEz/ea/BJFAisPixeacklFsIGWOc6icRoJd3mCa16jGHXNjWJLi6wdBkOjm3ThruMkRcdKFsWOHQQhwJZsbQMEGckkbzMmgWHwg7Cam82thHCRi9i/YgKzY3DY8Tl+6R7EK5dgz6vhBvmckM3edE5b5HtcPr0gT5rmgu5BZWEqEaJEnCw0Toc7l0gZ+dNem2dncHZ6is4epO+e62tbWpVbXioGsmJ+P8S/JJI3b8RVlbCA6oyoW/O3Bf1aMtWms4sKXr9mjYNLO5ex2LDao5RV9LG2L07vC/VinEF9tPFfDPDKt2RvHYkJMmJtHAjOFQuug9MmTKwutgKRmQXykDMzdSibTNlgppej6jpdItdWYYR1mM0YtOdrl2DUvtGUur5RtaENjGd6JmbS9oU790D5zljcP78kFEvukqyDQmByefKcyyhxs/XxJrLZGBlnogVSq4/d+IQDThyXNpCU1R2n4Sps4hyzc6sWZJMf2Iq45i9w9f4hekgl4OZnYlicSaIJw5Z6kdvVjJxsSuJCjt+RMlMahY4YQLYf3uJfOKfXL1q/PqB7cOYyCRGdgiUrkis5T2xtUvdHMXcsknz7enKWnouFMJNHbvIcSGcbKNa8fGj+Ck8DPXhabwfX76Iu97ODpyIxMk2ATMzmLSvIINYwMSpxs+6rduAE+E4DWj/M9l+8GDY5TuMNdV3oKfoNC1MEBJ8/RquJpTi6sfMxMYKApCFFvegXMRRJhvpk3rnDuyKrc+ux/nSRIi0PUT6IkdlykAfx630CbiGmxuEmGXifZiD6EKD9MiUCRoW/UzlxDP4Sv9JAsLtmzfoA6vpzl99RX7p/0L8fp6Xkkk43DuFVdECJCZ6i+0QAMD5wLwcJT/cERYfMUQiKQkSNcJt1lhKqwpxcAAHq29M9t8H305AraHgIk7n5cEDOPOuCcOfJydyzoKbzQSSLxbT/Dcy3e4v5BXLQfklxg2A8uXhZPXZ8P69sMjHi6+uioyEW8FCBZvZNzmubxMo/BZR1TtZs8L4Uid5+ETO4qdVeWBtT8v10KWLcVu1GiKU1oA1cTKbX/KO1TU/ScGC4hqyZMsGytlLYNw4smhCacQhPCeoCBSXxmGyZ83GBu5PPQJ/jqW2xz2+BctJVJuRaOQ0nwEppdImiMV1X12KzxzHbqAXe0R2aE7B87dWWKwUnscRkxFF2hoMz004l/Eelpk8pSBaI3ipRPGu5Pv89J01z2VNibuZk5oiS+mnLXUikMVYLsvJH2Oh54mm2LRvioeH8bYXB09Z8zddsTybxCpSo0ZgPJVj/CglIY2683ejScw6mBs7WTRmZuI8c+mx5HAWvjOIHPtUTFxo+NqYGIjECdLzOxEVNFOnwrm4o7A0B+W/OhPECmJnFWCNmBCbjuFS8CMiCUPn9NWrYVXkKtgFD8amkpbixWFdje04Pb1Goea6XalNm0LT0ZOgRmPOfilL3m0LABgzXzi4moRfLJUGGNBTBfPWQr4OgIimVP9C/Hael4UL4BS1ODz4rGjiMmcO+L86xtH3qU0ixO4VXl5QzOYpADPVwxm2tyx6xIYNQ+IGdf06qcQlGZJySTUaLMzUyBUWpoXJwKQEVhlCaeSNiLw0vTWaU6fE2WXLBpPKnmSI60ZiE604EVVetEy/QgG5XYWM08UvauJ89bBoL0bWrHCy83ZOOrTg8djtHDVryMCB4my1YWMt3LM4pQk/SYk5TXI5FM4aQWEesndjDKeoweVxp0TlYqrVsPZMVtbSlaMnzU0SqQO48NSdk9Tmwh3xG+qywa9YT2fG9E4tARU79M2ndlylPHefWuPtDfms31HC7a2kfkzrDrvTLHQ17Q8058ULcTbbD9uxlP6sOupNkSJQ3ekOZd1e/nQ8SUGhQlDb5hItcj0w2lqtWsVEWrOTGe0ekTRzNlFOWZg9W/qYALY2wncWHWP8AfH1gTw8I49XRNqiBBEb8pMncD6pEudfZWbPYUtW0Ystl7OJ8q6tWAGJ7l4kTv6LAgUEotet2nuGMI8W9UwL82XJAl3Kv6JJ0l78DBV3/WqptC6dl5gYDMmav3oFxyPKcPxTAd3J8r9BZ+nfjryY0jcnNBReJ2QFYK1VX76MX4mXlzjb7t3hTt6O9Mx7icvqssy7XEJsSDQtfiHpFqBBtkdi8kAz4leaukmcc506kNSrL9tzjPn5mtShFbLURCaxtgULwvPeCzmZSejJFKF2EB2OsLODmv7vqGl1kfzZY4VEFinNnJI38wFdY5nKWCZ3EJdoHBkJXTdWoqtmLYuvFhESWUzo4VC2kgU1OEP5zB9EVcCp1dB9RXG6s5bRk6xZ9rgic4I7cuSIuPGsGtbCDDVvvgpuy3iV+MzXttWD6cxGureIpHy2T9S0OPezJ4xRaIWIe/eGJ+V7cavKaCpUED08Ntap36vJeaQSEjr3rvjOU/Jyf6mgiNevHxzPO5RdlZel7X5sADIZyGylEcxz52Arbdl6PQcqFexcFMwNSnF+zl2jtsuXaXhGPp5N25+2ZYTIyp8U2NpKC7GZmYFcloRcLvzN5uawZvRr5jGMbo0Mx3BatIB5duOZV+dUxnXdyUk0AfDwgPq5X9HK6kDG0mUdOHYM+n8aRf/LLXn6NPX1LwkePCMPT2/rf062bYO6bxZT91h/7ur6Wn4D8vLbhY2QyQQCI2FTtbEBV3k4WFiQy/ID3orMknOgrOSpG4vYod+8gWehZUDuQTGzj3hJmHONGrA7YBpYWVE87jLZSnpAodWibA8fhvFnZ0OShjHZttHCU3ry65PY7BwPqYjyi4K696CoBG2+gtZvmBhwAEXYV8qX7yveUKMhwPoFgSPmYbVxFTazRLpekm0dZFFkdQjDKi4SZ2cJrlZtTxMIX7CUI71MRr/eahj3F9QsDhjQMk9GXBysv5YbyM36bRDLSLzXJ9Khu8gHM2XOZmYmdZYGCA2X0e9oXaAu7XdCfRFNvJM0oMGMbF7x3A/0wGrbTqC2pHGzZ07k8tAjMGoUDBC3KQcevgMVyqM58hDIL4lEFGvpx0eC+b7OnRmZl2Lj7UTu3O1E2e5c+A1l3SaYLVwBlJAUZsueRQ08h6xaf6PYZoPalUo2yaFQtVqUxPasuXJOshVWQv2ZUKq8BXALXE05dQltP8bdmklkrDkDDIRyN26EdQdcYMoUPjXsR2yxCtj26Yinp0gNI12l0mCUNFWvDtVtV0FZS3BPJ1bk7CycgpRKDLrLZDJy5IDDvY7AuHHQyfjp59YtWPq9FXyH+h8hXz7hdb8BdYinPoW6qnjw1PBn6IWFBQl2zoS9j8NZlXpm/y/h9yMvINmbMG4cjNteTnAN7HwA8SUkD9k3/0UaR2zAqnwJ8ubtL8pm/34Y8WQGPAEYSra131nXEKqIkGvx8wM/zyvCIh0cDvFGlJq0EBYG9yOFRJNpH9rxNeksVR4KbmtjuHoVZl0YzKHPqQJxbrckkBeNhvzWb8lf/KTw6y4ugbwAlrIEPN3VoAoCiXHy0or7vO+aXNI+5J00Y5BMXiIiYN2FoqDqR97LdtQBk4/0o5lJ+bUJdOhu/NrERLjxwh0oh/NTGfklhH7kcljV8w6sWol65CL6DBX+TrHTLuEfifr5S/IUz4Xj4R+QJD3kBAgbclyc4OXSp3qWbt6QBBbJJ3pbW9Gn0rBIOd9xx8M5gVE59wpZlVnFkZf8uRKAe+AfTVQUBMpyE/PZnczfhVJZg9CnviqCvPz4AYk4Q5QFztY2QmV3XJzgKpSKFBsx7kgdc46KggvBws784YN+U0tLQKYEqyRy5QIc34Ht14zaK2KRkvgitlxaR9xUaeNCBJlQPooiW4mM5GXWLNj44RiscWBrawhIKcGXoomTftp2SYSEy4kywLkqV4ZJnsshsy85czbI8P7IkTA7Ogwmw/U6iC6a+DfhtwsbrVwJjZQ7qLWiCe+k7E+/IsWu0ZDHOYiqzn9Tzu1FmsQ7KXgf5SatZNnEOZuZCeq8AA9+5GDwkx5cFtFfBITqVW3iAiZGnSSGnK5ehUyrJpPpxUWmXSxn2qApmjgSbOPj4dV3Z16pc1BpYmXqcYS+g8Udc0JDYdihSgyLn87WPclMS6QHxM0Nnk7YyVOZVh6WSKn9mBioMK02FbhC117mvDTPx4N34kJlcjn0qP6OHqyhc1sVG3tcZjfNGT08UdTY1+Ze5yal2TgvNHnS4u91TJwZMdgQF2+Wmi0v1mOko1RarAckq7cKP16TzTvepF5OKdiyBXLf3UbRo1M4etSkjxAdfqnX2g5XwnDt0pCFZ/Izk5GsWiEunNm3l5rF9Gdx+5sCH7exERYFEzVTUtY7cxKMVy2mJ6giv6OLF2FlXEdW3iqSqoov0vOSYVwteHWuiRffqNlC9+Hv2zd4muDP09BMwqNoayt8lojnumdPuJOrLXeaz0gjRtesZhSd2EDrqvqFBStVgvFeqxlf/Dg5c2Z8X5ujmlr59E/Hb0deHj6EQ6o6nHqdQ3LrhzcRrhxPqM6BJ/6i81YOHoSuH8bT9XwHHiXll7RYly8PU7OuxtM6AgAPRaSYQ2ZGSNQu6dABlI1as7PI9J+vmZJuU8b9NYfzDKdRI3HXv38Pix9XYXFwK26H55R0r1QqCI61J1jtRozaWpiwyFr49+9h4Kl6DAwdz95XhST9sS9fQq4FfckVdoNLj105Rj2u3DDBoZlCnERujObmkNcrgrxmL9g17hH7acz8MdJXqVu3zcgddImAVX1F93NKgUIBHWt8ozl7KZFPYsVRSvmIhO/Yq3lZ7IiheBPfXxIxe/sW+t3sQOdXY9i61fj1F9a+5TX+3Fz39JdKpbWrE8XsybfuW3KOKlx4IOQvPHgADa6MpNK9eaxaJX4KozblYzQzWbJGXJZww/pJ9Gcp/Wu+xMoKvgXJuGddjov3HY0S3OUrZPRnMf23lP75N5YuDbETZqJy95VWgSOBKG7eDL2j59D7YB0CA4XXev7pgT8vydSmiqkC0jg5Ct9fxA/dXhQrK7CXRWFvqRS8exJKvL29oZjNM4p5fEojTrd8Tiwb6MJfbR+bNmnA3x/KOD2lvucd03Id/wX47cJG2mFLqYfzzc+KM+nTGPgEx/+G2iJC9ffvw/rQRhAKLfPvpWC8eB310qWhdOZNjK10RVBDs7GBhntF2cbGQnS8I5ciS7L6bTVQq+lzABo3Fj08JR1fsr7COhSBbylSb6oomwYNIKhZX/j6Fdt8WbH9+4roSr0nT2DgNUF2fcrHs5SQQCIUCsju8J3EuATOv/Jlm6Y1rkcTqVXfuM85KAgW3ykLlMXs4980MzVBORlizTNlgl0dD8PuPcx7sxEnVRCxQ+14UAPyGk97+bkxtqj1A6YchILTEdMp3dIShtd5AsePsdVrOIGBwsIseoFPn08BwgPnKCI0mWx7476CN/KOKM9lp2ULJHsjuywrTjj7yTRIwcptxq/fcNQdJb1wPOZIzkqw7EF5AOyuQztxESABNjZovgaiERet4sEzS+Iohfy5PbkKQ4ccV7CN/U6+fI2N2vYc7cIDzqH4U03cCCFqc+SDELstbqTaqUyJRBxunIKixbj+yhVVgpnJScZTpsCymEuwEm53F0qI9eHIUThGfzgHk+OTBdPMwdzVBoNxEOD8eXiX2BFu5KNSXfimLk3sq6wUCER0gYQ2Ar9b8Bp/iBScRvoiuX36wLrgjzBBzt1GaQXtqlVIIGTHcdxLFgUyZ7CdPh2m7wqAli2h5HQalS1LGJfw6WLNjsPS5wyk/o6M9VQycDhr0wbaHJkGnz9D+YsmTuSfjd+OvIwfD6OOVsSqSlnsSs8QZXPmDFwL6cPM16nJJqZ4Ip6r/PD8JidzKLi6SjSWGEZZvx76X9iZ5rVabyWMp9GQzSaYztnuQtQ1yC2OvCgUoLCKBMsIsMtmcoXUuAvVmCl7RpueiDpllikDb7tMRXnqEtbP7nGDbVSamUgtEUmk2lh4qQhJzCTvMg19+hqPWTs5QYfCD+HFc/J2LUvvZQVR7LgAGJfjtLODFoVewoEDnC8CN244gtqE3FmJys/W1jC79V04PpKyCwezr+9ZbFwUeHlVNmqr0UBCohlggSwBLEz0gCzZYMdW9UbYCpUmiiMvlQtHEHv9PlkDSnLglAdhNCbnVXEy2cOXZiOUFeRcrOKgVpdhKdM+c9uRxttWEptoyYQpgtidMbQZ4skzbuAwPJHIaChTc6uQy1W5sfiBk6F9j4x5QGZNjIPF9eHPfex/FwDDhuIydjogocmYjnFNVtt3cBBYvUp/9uiKFbArcSVsg+HeMOfxCngMW84ZJ5hdukD5nQOgVi28vYUfvYurDBfCsHeWo1TqJ9aJiaDCCnQU661ZrYEdjaHTNkBPWxet/JYrT5wJowJ+DyTIt6fPjbGzE5ixmBwBQ3k1rq6Cu+4/it8ubOToCB62MTgSKao0FODUKZgQOhBlogVVne4yvfAOcSdjoG9feJq3GUMKnWXIq74UOT2LgwdNmPivlCwnwyQeYUqOTwokzjkgALZWWcNkH6E3UrTGTpr+mUaDlVapdLzIHJD8+eFWp6Wc8OwMwGIGcPiwONvMmWFT80NschzIH30icCYC6wwKXcbh4wO5Ld4Q4PFFlFBcfDyce+7NOU0VHn1ITkw04Xtq0kjD5kKzWVl0JQVF9L+Ljwerds2xQkXNJjZEy+wJwoNPb8Qt1l0WFKITG9i6L/UYLHbah6Y94gw1WDsj5KcuTqwJ4YAcOeD2sB08tQxg5kwRBsknXLmZhphEBRrMTA5DSMm16dYqmjFMY2TL94DgjQuasopYhQsrVoibM0CT+gk04QCV8opszpiup1LZstDHfQ8jCx7Hx8ew6YK5SdyhGHcmHk7b30tE8mz6dJcUiLld5cpBZ8UOOhd//LNKeONGCPUqwPtBC8iSRb9tlixQxPwhRby+ZSwoSnEdiewsnaKJI2at/fQJbkQX4Ma3bGk/XiYz2s165kxwfXQe17UzOXdOz0VubkJi3X8Uv53nBfglzZQJ/tupmOU95BLXVdbdHdwV7whw/vzzNcl7jAnNFbNnh4bu14kzs6FboTvUDtqIzfBLomwfP4aTrxpCUhI1vGIoZMK9StTI+Z7gSnyMG9bBggaCMfj4QNuctwgM/8zG+NZYff+Cj08+SePKzGTM7v4CyzVL8ekxHjHtXe3soITXZ2IVt3++pow1rMqZBulLpaV+wTIZY8fC2J1NhEy8QsYbI4WGQrWFDYGGVJ0Ty2a8iH8H2cVWFaQP/ZgYUyjUvhDvCMK9dQLBInLINp3zJYlOACxyGo+iXDG8vEQmRWnh2s7PWFYug83m/UBZo9cvGfKW+Il/YT9sGgqFL8XzxoDqAbgY7/0yZZUH4czl3c5M5HcLwvrHN7y8xDS6gY6NfxA0dzNWDZsBWSSRlwGdfsDEP6FTKcAPCwvw8LEAZTioJcghS/SO1WpgwWnU0FFGRENo2BAaFlwubIa56hi0FfRn7kG2sDS7y/Y7/oQwAPMlSfTV47Hq2RNq7OsDLVuSs3IVonYew0YZRkCAcTViwOTqrHHjYNzi6tB/MOQck/ZNEURCG4+PfUJRNC+Wu04DlQxeu3o1THm9GV7DyZ5QM7lKe8UKWB9zlshZ3myuKvQ7So/YWAhTO4E6tSN1Bri6Ctm6v1D59E/G70leJHoEunaFKtt6QKlSFIgNNOmE6+8UQufsF7FSRpIvX0NRNgsXwoTrx4i8Yk9pjzfUMD9PpbNQrZpx27p1oW6RiYKryccHPn8XXXJ4+zYMfyKIMczLchLfWAXySHEpDZ8+wY2PJXn8yYnJlzoBI+j6B6xdK25sNBq8LEN5PXMvdOsGM9RIdRAOb/8N1iyGqgMQ1Zs+GQpZPJemXkLx5zCcZ58EXCSNK5W8JCZCWJQ1JLmh+AEO1qY1/Tt33QYfvmLRMQmVuIblaWFtLXpxlsmgYt5gePaMQvnLEJKsFh0bJ21xLBGgYkDMDsgbB64iyYvW5pTZzxIIBsTFMVpX/w4TN0HNP4QXUhIrY2ONxqzW7HflI0PxeqLi66ClQtfNQeIy9kf3Coe5Q6FXUSCLye0UfkK7s3QaFTg9SJ+XJAKaZC2eNE0rxXZo1pOHMXx1Lr6yCJ9lKr3kpXp1QL4OyhWAKlWoUn6fcJIqKZK86IIUcTx9G7yzs96y+jNn4E54L7geQMev4J3JGkj4pe84KAhuxQdAPLrVcxF4ib/lB7C2xsYm48kwMRG67qxLaGI2svZIYNma/57Qy29HXt6/hzvh1VBG2VHqFaKUKvPkgTy2lyCHE3xIgHDpcvllPN9RpvJTePYMKosjL/HxEKkWFqsbwX7cwI+k8+LIS8q4gORqI20MPVmLoTyl82Ahj8YYrl2D1lcGpXnN5HBVirEIzZRXr2DF5cYQWJTq9zIJmikSSaaZGVQoGgPcAR+JcQGZjIt37fhKa+KPedCxpvGEzrdvIfekvkBfOvSHTSnaJSJgZwdjat2FU6f4SyNsyAmJZqJkTyIjIWB4U6AilbvLWS+hQ7OVFVyccB5at4ZZP+g/yIwcr05gV7IYYCSmADxbdgF698Jq1RXobm16SXvKhix2k0i/qabUksbEGE+40Tb9BS9VcDA0XNGJmIh6VBkIixaZ8CEiycuwcTY84yhMKcrOEzZE40nseznZROjU5fbXEHn2JuTww8zMLXXcX6i5dXKEryEQGSXiIJJCIiTc6/h4SNTYgMoCa+3fwC+Srv37YWXQRiI2ZmJGXUFfRRuHD8OiiFFwAap+Bu/c4quNypSBwW6bwceXLFlS8ylTqoMcLWJQqXT3gRg4EAauaySUpOroO2duDrtvZkFJdgpclpB/8y/Cb0dezp2DbvfHArDyvDjykgYSicDbt/A+qgR8zkVhl0+4SrB1cYHc1h94EZf152v/L/JWqlSB3SVm8jbKg1HPu5g+LtDSbDelS7cQdW1CAsTEW4PaHoWZDQoQ5i2CvHz8CPP+FhYA66dBkshLVBQ8++oLykJ4RjiQRYLtq1fQYVUXCK3LzcZOwHZYDC1niGvcmQYSynAdHGBao1twbgLq/kN5Of8oirLFUKuzGiUvSUnw/rs9YM/hoxrKmI8n9kciPZZAf3H6iQJkMpYsTIL1jaDfTqClUZNcPjHAK8icJLnsuM3U/CjZR5bJrixckUxuTSQSfwd6Ek4VOK2magfD1+6b+w5Vu85YzF0LMclzFuuK1wrPyeVw870n4EmW1xLCklrjHHmUhWC6INskp8uf+k2u3zHnOnXhHrTvruEQgTAMAttitLPz4nkJsKI0TN4CtsmZsiKVfZ8/h0hKwlt3imlFtiaPjSe+S2echvbHYJhPm0RICLH16QPrwz7CBHjaQsgPevIE9n3tRtR7SxpcRlIriBR8+QInf5SBH4JX2SgkkOo6daCO9xyoUBHypJKXvn2h/8UWyOOiofFx6ZNOhpuzms9BckIlSoL8W/DbkRft7qRSN+TTH3LR5tB44hPMGDsDRo82brNxI0x+swrewMkmK6ipPCZ6vO7dofv6toRlLcKVxNJYXTxFjp6bJM05KtGaE68KE/+jIVlF/oCzZYNs3tcJibXlpKYGVi8eUbiw4Vh3CgICYG6RLfDjB5XaeFFsakvoKy70c/w4NNosHEenHX/OGDCNNSUfLROjlaIe8MePoeymfkA/hhz8yjwJ48bGws3PvkDa/vVKpXHyYmsLDfO9FsRiqMuAl/2JU8podVpo72AUyQv9jJlmML8Z9NwAFp2MmslkkMkhDn5EIrfKxI2vgpry589GDNONC6QSS6keEJkMjcKahGiVULUkIqR5+LorMTShwHUV955Y8J6mxJzzoWkTjDYqjIkzA2yQKc2wAeqPLcRXzuE7QsUnI+SlWL444Abkj4PHNoLMfkKCZM31lOfBmljMZRYY+01Ub5eJZ3zGuqMzr78Irw1c4Mc71uE+N8EgeUk7rrQ+Qenx6BG02TWOqAg1HccJpdP6MGS4nBPchMkQPiTVi9CsvTV02Q5+NdBHXhISQKOxQKY2w1wDsl/wcoHg5B7/vC0AHjf1r30bNsDlqAWwtwBTOgn6KynQ1kjRVeHVvTtU3d4DKlXC3789V25a8Fzek5gjfnRuIi7Unh4WFoCzAwQa+UEaIdCX94ZgV74wzhu2ILUFx78Bv121UdGiMLvYDhblWEDFiuJsQkPhrcqXNxGuhMbbE51ka1pI08KEDs2Ai1UMDQu9p5bslGhP0cGDUPPudAJOzaTltiZ0iF5uvEJBGxoN7lY/ODvqNMeoy6hh4hRUc+eGobmPMjTLHorlTr5JKuluy7Gb89CXpUyYLk5Yq1gxuNp8PldzdGDtPifkJOJQx3giZ3o8/2TLbYpz87b0n4aHBywwG8rKNhdEdQ328YGDnfdz0K4dDRvCkjd1WfulDg8fShzY3Fzwk4t8tpyc4NvCnXzDi/27hfpQhUwpVtMv49iWlpI3mTVbrTG/eAarnZvYskX6sHPmymjGXjquryJKMDJzsxLYEUORJtkAsEsmO1ExIr7n5BujVkPfreXozHomTRCnVluzqw85eUXR7kVQKEB98Aix2HJwjfEQTHConK/4EBiWeuL6KRprZN4ndkQShjNhW45RsiQ0sTxKu4DHJnWzBnjy3ZOPiT4/BeAkw9xcCNUZyK1q0wasEmOwHNibGzfAb+EAvIL+plcv4x+fNy9UM79ItZzvf5JE7WonQ2kvly/Duvh2rLtbOMP0mjWDsE5DSCxWij59MtoWLAiNbE7TKM8LnJ2FJNwe6pUM3ltB/L3SRUAkJAnrQ7YizrgRijz8vymx+9uRl7x5YXjRcwxw3UZhcQUDTJ8Ofu/P0ud0UwDyWb4y3pckGRUqwBiPNTT3u0fLg20p+PEokyaZMHGJ1UYfP8LpsGK8jUn1Ef9y7omptiJDMB4eUNv3EbUdrwOwnL7sOCQu9uLkBGU931LW9gGZfZJIQo5SZSZqQ/b0hIHFrjLQcSPHrzlSktvUH+wnatzChUEzaTIaL2+CgmCQ7Rp6Fr8nOWSkHRmTxANkMpPaGqSgeHFQT/mLOLcsosqG4+Oh5YKytGQnk2cku0sknJBP/+3Gaarz9yNzkpKrfMRGjl5vus5XvDi3NTDN/TXlcN6tnZLRTOeP5q9F25iZwYozfmykM0dPiFs6P3614A05eReoQCYDM3vxORGe7moy8xFft9TvddRQFcvpzdo+dw0+2w72GpyJwNkugSFDYJ9XP7bU35nGq6AX6Uql7e3BxjKBTHwz+lw3bpjEIBYwqOazNF5uQNKGbG4Ob0Od+KbxJCTE+I94xAg449CUMz12kTU5yl6kCBxqtpELnq3pIbK3Y3pYW4OzpxXyCAMlx1pfhLYHUNQBV9+XaOReHTsGg7+OYPDlprzQJ1hoYyOkOfxHy6V/u7AR8Eul0lc6rKTcpekw6L2o66tXh+peS3iSrwV73hQlkjyU/ChxUJnsl5Jui2T5TpePk/DvsgAx7bDj4uBHsqiTg8wGaxDGNuab10bKnFNsRaB0aThecwE8fYrXq4t8C7VEKfVPlsnIlxc0929jlSs7arWb0YrS7NlhYbVDELmPM+6tefraCmW8hOqZ9GEUqSIgMhnlysHNVvOwuX0Rr77GhYC+foXif3QCVWMa9IKVUnWAkudsJpeBrfg5q9VCIiBkIfSKmlWrYG/cfmKXZGd1AyG53RBqTigDnIYNUNzlLdaJUWTKJO4U4emiAr6BaxLNmkHufdOxKVmATJkyNqZLj0oBkURdvo9vQAnAkpEjgWljoHYOjAm3PXqlIIEiWLyxxsZKTYzSnDiRhMnJQY0r33F0sAUsJMnHn9oYKHRY3XgWqApA2y4K6LkSAkqBrKR+43QEBAmVbDPnmvOEjbC8DKuaCmHkmBVbhLLLeQkY2jZ69UiC/kOg/SawThXDSkqCaHsfIj7JcInW3R8yb16owGXI6YeLizeudkpsooNxcfJBzLqVngi4u0ODYl/h4lld4rg/MWUKDNtbFrp0wc9PB8uRQLratIEi+8ZhXywX2bIZjkfOnw/LXhyGj9ZsaCVo1YDwNW18VJ6I7yqybNUt0Hf9Oiz83l7oSP1J8HjrxH9Y6+X3JC8SF/oiRaCt/SHwzYybU6JJJMJKnoiZLAmFJg65XBwJOH0aDr0dTFKYK/Vs48kV54PVRw2ZsxjfWHv1gs77GoKLC4qGNbHovASqzASMuwS2bYPup4TcmtW5H9IdTDrV159amh9cJGsfOzbvk2Z7dOkHZK1bYrtoIyCinbUWNqxVw/aS8OdmMJdWZtmmsZKgOauwrV8PyCHJFjCNvCCsjyWzh8CtRyBCfVmthsAftoAtq1bBa8uDKJdkY31jhI68pszZBD2Ily/hVHxl+CitGKVU0QRuFJsh9M9odkuckdbmVKcO1PHaAvlqgbtx8rJ/2jOoWANmvgAcU3dPEUmodQb48YV7+AxUcXXFY6w6t8Z++UFA346Rihs7PwqMbscloIK0Ds26YG4urF9SpW6leMfOyTlLR7gCy1NUZ8WWaOvxJMyZA6Oe3YBnsKeeEI5JjylTgOlVYNgS8OvN9w1HoXlzmBsGiCgL1wURpdLe3uBt/hI8w3R3ok8hLzp+H+HhEJOQCaIc8VAJnvYKmU+AbzC4GiYvoaHwWpUVVGmXDJUK+u6uAlSh5gY17dqJVFNNh7dv4Z68FaEX81D9jcCD/0v4PcmLlRUaZbzo/iTt2kG7icOgQVOhwF4qedFo8HP8TuKi5ciGDoFV4nJA7t6FJd9awDdY9hzgFbV7JnH8hPENxtISLOWxYGEDtsmJhfHxkktgeiwuxH6O4D3UntU7jF+/cyd03LUJNBpUGkvAnZAH0sle0SIa4D54RIi6/scPeBPiC3F58AyzwgtMEov7c6QK5gyEtpmRRF60TriJMfHIRJSkfvoE3Vc3h6hi1JgDwyVsMHI5ZHaOgvAIPpGZc6oK8EmvHEUaxMbC9H1FgMnk2iKjg434JFSFAj4uPggD+mO1/jlL1qcScTFTH9fyBezaiW+bwfDJNKKXppTW1FJpMzPBCyKRRAih5hdgL1I7JB32XPLgHcOJXZGJCeVM+ghRlT+nLlgSSmtkl31o3ZBfKvH+OSZI05fRgnbiq+hUDm19GjFj6oKDg8AG4uPJGMfSgh7SpdHA7heFCFN3x2ZlHB17p10/x42DpYG3YCHc6SDk3mFnJ4pc2tiAqzwcLCywsEh1RTk4gEymQaORERGahC6vU8+eUH97OyhalDwlhun8/MOHYfCHOfABtt7875GX3y7n5fFjsJ45AfnHt/TubcIHmJhbIJOBzFohbBBJ4pL9dCE+zgRbieGbLFmgYaabNPS8CcAx6nHxhrjKiqQkUCVZJBOXlGElqjum5HBImPPNm1B05yiKvtrJ8pVmwiZsSphN4r0KCYElN0uwJKYztWqBxfOHWCyYzenTxm1jYuDUq+ycSqzKkydI8tp4e8PHyRv5aOUvhECSIebRjIuDqUcCmMo4tu+QsexSAeYylI1rjSdlm5lBZtdYMvMZj0wyRo6EiBI1UHXq8VMh1BAmt33OZCbQs1O8ZC/VwWvu7KMJZ68mf0e/uiGL3GQ61Q+jL0vpWC8sNTlJ7LzThW8WbnRkJLOZuCWn+Dz2dERAbe9EREiCQftxM2xpy3bazi3KsWNQ/ekiyh39gyNHjA+3YWU8L/Hn5dzDqblY2uTFBOTIAdU9H9Hc7QKZDYRwgLTkFER9x4sWQdPojTTd3JgvX1Jf/xTvwRPy8eS2ac+JTAadl5eiDyuYNV/kWd/eXhQpHjMGvuetyPeeY6mkJcZrZgabx75gP41ZNFq3/lLmzFDK+iGlPD/orWjS7p/3CxI9/1j8duTF3ByUiRZoMJO8t0WprBh6uDJ94+aydKk4m1mzwPvpabzXT+XSu+RfrciBO3WC2wW6cLPBVKoVCqY9m6lRQeKkk4mABqF0WAxq1ICDJadxsORfeLkJK6TYHBBnZwhwekeA3WtW/vmJeCx5s19c+cyNG1D/1EDqP5vNntPJv8j/B32V7t6FXKuHk+v9SWYutpY07ufPMOB4XQZETuPUKUhMljGW6lBISIA7IVm5FFOU+/el2U6cCNEFy5DQe0CaRVAMZDIYsL4Iw5nLkpUiF2etU6qdHTg6aLBQmrCpSdV5+asAzdjH0KnJysc2NmhiYlHraKinF8kb46xZkDn0b5ymDefaNcMm0/p+YSn9+WtAoGS12vSwd0o9RRtzGs1b48AoZjB+fWpb9qlTwfztS5wXTtTf0yYdgoPhbFgRroXmSbOx64OvjwZ/XuPvFf3TM73mVBbGM4lxcwzX/nbpIcefl/gPb5hm/65eHU43W8lu70GGSW56nRcQ5V27exf2JzRg/+NcacbNM7AGBXhCq276Q/XPn8OFhHJceJtF51CuTsIDFqZDL6VIEWhufYTmeZ/89C4l2DgSFvYLTSyBdi0TaMxBSmX9ZvhCA2He4sVhRun9rPGdKE564V+G34682NlBIe8QSsjukD278et/QqMhIUnO/LOFWU4fjh4R5wGJioLARA8CYxxRyaR5E7y8oLjdc0q6v+PMjLtspiN/9IkQZfvsGWz+Wo3N78ojq1kDOWry1xBTapCM5EXk791v+I4rz7bdF2VWuzb8XXM0f5fqTc+20ViSgCxeHBH49g2Ofi7M0YhyHL9ozXVKc/6ug6jNydcXeue/TG/XXbx8CV3iV9BmY23evzduGxcHr8LdeZWQnZBQubAgmOC1sbeHIvavKOv6QpS+g78/RE6cT6RzNmbMgBKzWlBJfZ6xYyR412QyrK2T+8cliCMC9vZwetgJTlOdqVM0WFsKN9hkJ4atrWTjoGAZnQ83pVXIEhYskD7kjh1gd3of8v27RXUdbz8lN03Yx4DJ7oAw3c+JXkTGW4tWjwd4/N6Oc1Th6GUHUQ7UJVudmMR4Zm0V1IdHjDRjt3kbTvQ9ZDSCu3a3A7MYxYK9qRpC2lVphjbHob1iWMhAFnR/kmYcU88Ci3Z4MIXxzNnmZfC6L19lvMaf10EOGSMxRhJf58yBVknbabW6OuHhsGS/D6OYwag57qZNGnCwFZ5tQ9/xzJlQJeoQVVa10SlEN3VkFOvowuoBjzK8160b7Hbtw+4Wu/Dzg6NHwXLnZlyvHhL/XOsrlYZfKpfOkwdGVb9HN9aKbiT8b8Jvl/Pi6wsPxu8TZAwnijuyLV4MO77sJGZH6g9XCN8Y536OjpDZIhCsrFh9ISf3GIHrOhndhkqcuMS+OadOweBnf/z8twYz4k1Qic7kYw6EgZn0ChqpIRhtrNtixTquwySIHJpWs0EX8uaF5ZV2wNWrDHBvyZL4NvAIhoYI1RKGYG4OzopYUKmYO8+JI7JnxP/hyaU6GHVxZ80KW5rshQsX8D+xmJJThgp+36rGK4bkcnBQqEAWhYWWizc2WoL6agokhDMtLaF6vq/AWSgqY+3Yd5iNG4Pb6FmAYUafmAjH7/kA9XG/ZUbpygjeiGBpHYuVKjM23i0IFERzDQYPNm46rfNrEleuwb3bKORyN2LUwk4uhjcdue5KJE3Ic034Ebi7g7dlCHZWiZibG96Qf0ImY/B4B85yDv6CqD90V81oY9FmF14xCZdtCYxcLqhX43QGfAuBlbg2IdrIlg3KOD3D3kKJq2sRvde1aqSE3ouhYU1UNQsQ1ak/1k/vIh903fgg6SuVAHtH4b+VKjmJBnpCOtiDK9+Tb0w6URkj5OXqVThAS7gLC+Nh1T5XHjEKxW41M41oAS1cCDMO5IGBA3H36/vz9Wa1YojdtgWv6tUBA62lDaBTLwUM2wD+NYFiGS/QSuTVfh5EpVMZKpUGvffr82f4FpcPgjKT64eB9fE/XG3023leAGGhT0oy0I4zLd69g2vKYjwI9mZup4fcpShr5onzCQ4fDh/z1OJj10kcuuXJKGaxaLVxufs0MCEHJD1KcpOAnBKV9X51XIk6L3XrwvfW/fleog7VqqX+qCUNLZOlEeISY1u6NIT1n0BYzlJ07AgvNLl5H+YoalN0cYF2BR/SzmY/JUticqm0QgH9671lBLNo19j4wOHhMOpAGUYlTGXbNiRX0Gkvmq0axNKCPVQpaDwwrlRCw7mVaMhhxk2xIDAQtgZWYfW76ty+bdg2KQk8u9TGk0Ba9UjtJxQXK04db0izj4xgDp1bxODuDgVcvlDS9jHuJhzM+/WDL9U786JqH6EhoCFo3Str29QlU5yzScffZmcnamfbOCuIi1Tk2IzUE3+zZnCt9mROFhhG1apixhfIqp2jHLlS3O//zj0zTlOd0w8z/fR6zpgOJ6jF1bHHDBak7dmewHfc+b5ib8aWUU5OggtEZJzP1jaVMBnzcjk5gZfsG16OsWmI1ZJ5KtbRjWkt7uu1rVcPRivmM7ryDVx09WK1sRFuoggS4OEB5bN8oLbVeaOComfPwqTgPky6UYt379K+pzS3I1DmzbNnutew5cuhxJudlNg5nDt3DAzi6iqsR7+SG/YPxW/neQHSejGMHZ3SoUyBKIryN3jGIbp8L3nxs7LQoFSJ34y/fIHPUfkgODu54m2E0UQaV6kCS3MtAAcHakytjH/t0jA1uVzTCI4dgwU3JoHMjKHXHARhaRP8zSev2fOJbij3+9CntvHqG0tLcFXEgMUPWrWSUfD8IhTVymFlpeO0YwBDh0K3gw2xKlMUr+ITJdk6OICjLBIrGzlqtbRnAxDIixQZ0uRnQyaDxYPewNFR0LQlYNjV9OMHzDpbDChGiQWgSqxL/Fc55R5DgQIS5/wLeRxPnkD7iz0B+PMQlChh+PqgCAXgSTYSeDrrCNYj++Ow4iliSvi1PQKVK8OjTnPh5Eno+MSo6YvNt9A0bYp82zV+VpGJbDZYpXcugnmMV68sdOgro+CJWVjXqohCUdqo7ZopgcR27I35pDlAgdRxRSREFC8YD1yGgpFp37C3h9cixfVMaHI4cpwl5zkN0yF2nPBIV6hqAZYXwLOBYckVPZ4EtRparK5DBGfJ0SWRNZsyfsiqVbDwQFaYPh1397YsmJOIskp1bKaMAWqJmnsGpMRvIyP1XtK8OTTvMRnqjgEPHd+pTCaQAH3kRcvzkjcvXB6wW6j77q5/TBDIy/SQfhACFd+TJo2hT18ZGzRfYBI8aQn58hn8KP1wdSUBc368Dse1kNRma/9s/J7kRdubIIK8zJkDcw7khJYtkQUkt3Q2YTNfO/YtjPkD5z9mAcbr1jZuhLFP1sITsD+nJj/XsO6eg3N3jY9VqBAU8jkkyMfmrippzl++wOnvRQHwOawiglbEn/SkXV397uIU3LgBa273hHgVa1vYA2tgLXRZKE3jrkcPYPg4qDUeHKSRFy8v8HIOAovPGTzXBiGTsXgxLD5cGNq3h3xTJdkCkjwvERFw+F5+iG9BzutQxkQScfs2dGEgAAvPGScviYnw9psD4I/tF/CRUEFjaYlwit29i2wdJmJjIz4BFSCbRwwEB+Pr7U3enAnAB7COQxR5SQ8JpdKZnFVAELhqHeHt7Mhw5NWBFx8UBJKf6E8qOnUChsyAihpwME5eKhaPA05CiXGAULUbYZWZ6EBrXCNN630jqlNyehLxq5VZIJp0ARnyOORyOPHAkzh8+H5Ld/xa8KB9BNcYkEOpilbAJcjU3vQYgUIhrPe/KLUf7+xJ6MdEHGPSrmPz58PB77uRbfBiVdvkRr8p1UYm6CalQLu0XBfvKl0a+rtshcyZ8fHR3+cmd+/KvCQB35oqPhnJ/f234bcMG/VdU5RObOCPieLKf83MwEymwUymQaYwPYzSrE4szdhH1QDpbT6jYuTcoAx3nktgACn4hdyTDdssacMOOi8rKWrte/MG1r6rxtqvaRs5Sg39AJKUkK9ehQLbx1Lg+W6WLUN6+EZ7sZcQglGrITLOksgkex4+hK6Xu9Dm1WRR/Xq+foWOuxvQMXo5a9YgqQw3Uya4OGAPFy1rMFWLY4n5k8PDIfefLcjNS/r0lRGLDSG48eG9xqh73tISxjR6whim07Z1En5+sLDOCdY4DqNNG8O2ZmbwbsUp3pGDPeujpZcdp8f/QrtExGZsZ52EPT+wtU6+OSaGBkHwLmS6cxS/PTM5dEia7U+IEF4rVc8VOYlYNq5DdDRselqcFeGtOHHC+HAdWicwjsmMa/ok7WFFCnnRAUc7IVwUHS2yiVaKFo8Ignr7NuxLaMC+x/4ZI3K/2CdowQJQPL2Hz7opHD2a9r2XL+GiqiwX3mdPnaadnRAjNfKMdO4Mx7P04njjlRRKp8MZEACNHC/QKdd1nQS3QQNY7PkXiyvv06+uC1glHy5CwuSm9S77B+O39LxsPOdLLJ0ocErFdCmGMhmPPzsRRWm4JaeMiAzukyfh3LchcDUrPerYkRNEb8glSsCgTDvAzY1lL6uRkCCTLhFjQt5Kp07Qem8LMDenReI2Tp5Mjj0rjSfOaqNuXWhyvCeKTq2wtq5m9PrPn+Hq2xIQkpnCzyGPBBIRHQ1PwoVqquBgJG0wHz7ApuvV4Xtmyp6FahJI0/37UHz2WGAsxbrC3aelAMh0R3DeSIKEzVyhgIo5v4L8KpnbgsvJ7Vh/fEHxehMlDgqNOjlyhhDoAz/akTFXIT20VsFMmWBg1cdwbS2UmCttYInkxaVZFZTEULixnOv3MI28JBOBb99g8e3GRH8qSEk9EuwpeLn3EZQsCfvuA4WljZtux9C+t8bSXl6+NSeeAsjf25AvuQT++3cYcrgFP4KLU+ovQStEF5KSIAk5sqQkIiOh0446QB2arhYqAg2hS/tE6DsBWuYGi/w/5xpkmZeotw5kDdevGbdpixnvGA97C/BH87Sah/ePfMGuTAFsNh8FKuufgDZZE5kftGgRbIndDBvh5Vh+5pusXg2rIk8TMc+TTdWhTBkDH6LHS6JNHkTlvqZ8ydHRBkVBc+WCXHZXIJtNBlXtTp2g06YpQhJNPgOTNuLZKVrMDPvnV/EolBmVKotBnb5/G35L8qKwTCJWKSc+XgIVTV6EGgzLxXuu4zEkgaBOxs0uXYJZ37vCd6gVGiiQF5Ebco0aUCPrfChUiJknCmORORNmO/YDjcRNN0kDGli42pa/2YBydnHW1zEuspuqzmtJ7+4yap8ZjqJ5PWxtqxgdt149eFxjCERH47lpNa5ZtkJAfhBBXm7dgtaXhEqBWYchjwQSIZeDnYUS1GoiI205F1WCuGDI+1YQyDKEDx9g/LXaQG1GnoJqUpNfk6GdKCxmP/b0hKUNT8LZs+RpN4smg7PyN+9IapqJjyKLd5DJyJ4d+hS/Dd9PQIGJRk2srKBjmZdw/TpFqnbi/Pm0SahGyUt6mKh0e/WlO+HUQ3ZCTj0R3dJj482IxwalSkVUFIzcX5PYGGfyz9QwcpThRfzQFRcSaYL9FWtq+Amu+L+uVgIq0fGUYfLyEyaEBj98tSCRHMgDrciGkNdQ3/c+9soQcuQwLL7RqI83z3mEY79EIpLXmqQk2HI3H5CPpGsaQPffnc8/EdmD+5j5+2Ntnco0YmNMqGQDli2DUS+PwUvY2xKaNtV93aZt5pxlEuyD4ekEmzPltAdiITJCp+2tWxBEfXiQhZrxwiP1zTKA6JdO5DYxxBYcDHeUBUEpCErqwuDBsCfyMUx14GKTjEq02bNDBc+XuCgD8fVNK6S0aBHMP5AdunfHstBYALouL04Ih3Dto2DDXhGT1EdA/gedpTdsMYcDtaDtZLCSWuL6z8ZvSV4urXqBeetm2K7cB+Q3ev3Vq/DwRzu4V5yIaMENp1RJj2X+iLfiG5mI/2RGVom2Vg5WgEb0Zr5gAQy9eF74x3aATnATlsZK6xDQuDFguxpKeIEI8uLkBE6On0H2QzhNmKhIvGgRrAo+g3KZA9vqCz1DDKF6dYjqNgRu3mRn6XtUWzAZgHkHYcgQ8ePeuQPTgroTf9Od5g/J4M5NDwcHqOX3Cr58oUaTyqwsvR7rVQtwnvHA6FguLtC39D24th6qzmLsSAs+kA1ChE3KaOsKExtCOjjAxq6X4HoPGNyJmBgZmiNHsS7sj1wutTESwuk4MVFI6DDSXuAnZDI6TMrJO47gPiGB4AHGTQpmi0b16j3+2fzRaCxZcUnYxGucVjNylOFs8PbT8xHFPvJNVfGkU9pUt6go/SQASHOfly+Hac/PEPfShk21BbJuCNW6ZuUNb3DrnkBIM6hYESo2WgNXrkCt+0b/Zkg7Ne0NPDJMjb4lfOPCCNhTCuYdJcG+Lku73sVm3WKy9l8KGAk96yqV1iK0JkeOUiavZ0OeOhUOcxiWQPB4QaJiyqcTsBlOdcCg0Frr1lBo9zioXh03t1SC4eQEZqhxsIgjIUF3fmN4OHzR+ECk7kKoypXhUse1sHcvNEibKG1hARYowTLpJyc8dsudIBqQ5boIbQpDsRwnJyG2bIqtNjw8xEsZ/IvwW5KX/Pk0wEtwEtfXZPduWBg6BU5Cg+qx+J1ZiV2jhohJuu3eHWpt6wTFi9N3dh+e8A26QkIH48mvQGrSl0SdF32QZK6de/IrSrciCVehQjC/+FYIDeV8wYEcOiQ0LZO0WCaLtqVAzH5eoAAcbbwa7tzhaJ6V/HlO6CybSwR58feHE202CdnVwz4K7DD+ubQ+csn32d1DhieBWLvbEx9vl+bvSA+VCl58dYWk/Dh9gsy/kOMzdiwwvxO0HA5uow2a/fgBmXu2BBpQrbUF+w6AxtYOFZaovsVgn0U/eUlKgpEbCwCzyb7GKjVqpBR3ELi9+IYQ81j+kUQtBh4Tpbv/i04kD+XuDqdGnsF+1p94Tr+I7o58GREfD18SPACxbZH0lEqLeKib14ri2/J9WNesCwgid1ZW8HztVRy7NcNp/U3QdwzSIiAWFtC3SSCs2wjFZ2CUvOhA3rzQJvMV7JMiyZlTP2P7a6KK0MpNYeQorKwqp33TIrmrtl5vQloSKUUzpV49qGe5EKo6g3MqeenVC/pcaItZRBg0092zw8UFfGWfwcEBc3M9cXFXV90Suzpgb6chKAyiYww/12FhEKHyhQgXvOLI+Hs34HmZOxdWvzkCG23Z1EaIauqFh4d+t9O/GL8lefkVIjB2aBylzgyF1jkRQ16yZ4fsNnfA14VMITKePE8dWlKVtoUgOy9FnbeMw2OwtKTHrFyU7VcExbB+eHp2N2r78iXc+FwFLCwp+xpySiAg2tBoQGVpjzJCg01C6p+gDzlzwuB8p4R2qFUGcuVYJAqLJMzMpDVly50bRhc9hfXnV1Ss2M/o9S4uUDfHc3h+iS8Bqa+bJKljbS0wC7WIzoyQhkQcOiwDc2+YsRasuxo0+/IFCs1qD7SnzSjYUsSauFgZmmjJ1f+p8xZBfjQa+BFnCVgSEyMkYDl0aEg08QTUVfH3Y/22SUkw91AuYDjl9yfQt0sMYWOnYNuuLSAigUxrQzY3h7tLrmPbvzNOy84CvgZNp3R5h2rpKly7jQTcsbSEGmWigZvg8gPQLxazaGcmYhiN405XnHOBj+I7NvJ4rKx8jE65UdUogjbuxq5ydcBTeFFk75spg0NheU8YdJEU8gKQu4AFEATKCPSSl/SQUMnWpJ011/gGPR352EggTJUrQ+Xq6wTp7nL6yUvJ4knACQjomGF3efgQ7lt0I/JkLpq1FPpzaaNDeyh1eCw0boKNTXEKF4YuPiexU6jJlq2uuL8zHczNAWdHeP9W7zXz58P8dflh3HjIobvJIa6uApHQ97vW8lJd2PMdy5KFsd24FdDfC2HWLJj55hS8gQudSNPa48MH6HmwL5Ef21JrAkyalNY2JAReqHJk6EitE/+f5+U/BIkJrO3aQdGtw6BMaXL4Jz+MJhCfcuVl2F88gKJkIcR0LF62DBY83AMvrGjtKcPTfADxx/PQtaXx+G/r1tB6RX9BUrjLFhjxCWy/i/rGz5+H3g+HA7D+CuS0skIdG49MRCjj2zd4HpwPYmNZ2xG2fHgB8+FCIyT13Rk8GAYfbir88GpvF2eUvLnlzg3Tq56GgwehvHHy8hMyGTVrwqGyM7BSRpK/toR0bu18CBCeDym14SAsihYWkitZPn8G+fZhwDCadxE8hZIhMgnVzAzyekfA169k9hXKHCwtNBAH0RLDCf36aGDsVKgdgCjykg5C5/GXYG1c339Q00+wdA606MNPoqLdbNCA0t209d4EM51sG1S8+wKdDvcWbBqfNDru3BFBsLEDjLzGT/Ii0vOiF1Kk401ochgeLiOYTJC+RPcXSqUBtm+HGREL4QTkf56RvLRoAbT6Cxr4gW1xatWCWqVWCXMuYhp5AYT7ZUDnRRRcXIT1JTxcUK1NxpUr8CK2NdwNoEmYcJmPvw3wHRJMH1OjgVNvhMNx1ucZ31cowNHsB1hYIJfrd9E+fQozn40mOARarIOuhs9E/yr8lqXS91/ZcoZqHL3iKCpsWKIEdLTbR8eC93H3SXaLm3AsnzzVjAPy5uzofFLU6TgsDF7FZ+HVj0wsXQr9EhcxdH8FgoIkDPqLoZ9Jk8Di9VPM587k/Hnj1586BVUuTaLKndkcP576ukml0hISZ9+8gRl/12JGUGeuXsXkUumsWaFB9sfUtL+Oj/GDdRpbgItvfDhBLS6eSTBq9vgxyMaOQRYSTPcUh5hIEmFvDz1KP6KH+Xrqaq3rYtRqw8Kg5F+NKMlNRoxIflHk/bK3h6czDvOU/KxZKSQIlC4UR0UuUiqf4Y1NLocrUy9whXIsnR3366XSKT8icfGbjNCuCpGCXyiVjoqCOmuaUT7uFAMHGCkd1JF7AogSXpswx57OrKf7AiGnL0lhQyzWhAUa/yF6eSaRnbdk90h3X36xVFpbu0Qn79K1GIusNvoJXcmvjo6/nPjaa31panOc5u3Thhc3bYLuP+bT/UD91KaXIp/LgABo63CYtnnu4eGR9j3taq742IyJOBMnQkSuUkT0+5Py5fWPERkJm16X5URkWR4YT8P7V+G39LwMHOfIZc7AFFCORXz5mAllx9++QYjSH0K9yR4NdhIqaKytwUUeAebm2NnZ/Qy5mhTOkBD6KV8eluVbApaWXM7bk+3vLUwaN0cOyK+6h5W9FU5OxhOjgbQLmATC9eIF/HGrCQCTz0E5CRtMXBx8i3QBlQ+OYeAigTS9fAnDdraH4MrUXwkDJpUngRMU+VPFPeNFYT/xc80VOW83N1jV6iw8+pPYgV04tC4ExatHFMpXHjCcNJuQALffewAeeL+Cfftg1fsVxH1zZnILER6ydJvM0Q0hkLMyjDwH6E/qlsmgXO7vwDXIrxa+X5lM9PfUd0k+1KwgyyJ7xs7CNPKitbm9i3AmjKIor0I5A7lNmya8IX7wSKwnLASy/1KptIUFnHjsC/hi/ncippwf77934h2NiTjsRusaOnIlgMNnFPxNZyzPJrEGKNgiN0+Jxb5xIj+MFIZtXxsHe/1gyS6wapH6hgjy8vUrKMkOQbZkS+eprVED7Dcvw0mhpEQJA5UvJpRKd+0KO6MCYbQljxqlVhjGxsL6B+WJCIsnyyYNHTrqyUMxIih3+p4r76iN6w3jhxLMzYX11si9at0aWk8aKWhK5C2a5j0HBwjfdhz7tvWRr/7CT6+dRGiTov9a5Oi39LwobFIfUtEbcvIiNHS4Gf68JPPwlqLayy9cCIXeHqDQ5hFCDwoJ5GXYMAgtUoPQTsPYvh02ugxhR9NdRpsFpp/zu3dwJrEyR5/lEJW3lT8/9MlylD45TlK9OhSxfUEZ91eivEUFCsDoXPsYnX0nCxfCxSJDOFV1huGEsmTs2wcWW9ZhceUc8+YhvV+PNiSQl5s3Ice6P8nx5jSzZyPpO4qMhCOv83BEWZ0nT8DaSjhNi/GAWFtD6cyfKW1+hxw54MwZGKccy/AjlXmrP0SfFjIZNjZwbdZVzlGNv0aJa5FsJkvCDDUyGXz6BCcjS3MpKLfB4ga9SAmPiS2XTp73z0R0kURgzUlfVtGLfSeE3frJJwfOUpWDZ+2M6x/pONU3HZqV4tyl6kDDksS1SkXQkMPUKJv895nieUmGlRWYy4XJKmMNT7pxP28C+JuK/dMyq7/mWtGU/XRdU9b4hpQSzUxe82KUpomVhYZC+VUdKRx+gb599H9A++5W+PEWv8ENMvyEihaFvoWv0tbukO417Bc8L/HxEIstsaq0iXVqNfTfXYk/1ZPZtFH3/d65E/6In8AfR8vr1XFxTY4U/YhJ22epQwdYbT+U1Y2P/vTUPn4Muy3bsv5iDjHdJ3SSJpkMnLI4ICdJdKKwLmTJAs9mHeY7rmxdJbG33T8cv6XnpXVrGSXPTsWqUR0sLIxLzyuVkJBkC/GWBAbCa/whwsT1y8QNuWxZKOt6FPwswKml0euPHYOtz/6Ej7aE9YUTH9fCRzje27hIlTa6doWuW/sKFL6i8dyTokWhaIGtwoZUppUk70lSEiRqhEfyxQuY9Kwl8SE/qH4Oo03oihWDAzWXwZs3uFaZi2+D7sTFdqBGaw07dogva1ep4FOCJ8ofmXAIEkTYpGBE+2+oV67Gs213wDDL9POD6702CnXhfwQxZgxMj+gPt6HOO+P6NBlKpUG0Oq96xRro0wf2q1m9OvU9k55pE8M3w4bBBuVnYofbc7eG9P4tAyc4c46z8BdEjzGcYuTerAIxxJC/kZzbD4XX7B2Es5sq0Ux0lfeXL7DkVmPiPhWi7C5oaeSn2HxoZr5yFedhuTl6VdiUgg/dxLZeJSy3PQTy6LV99saKlwTg/C7taT9NubSeyNG+ld+JL1cFlq0BKlC8GNg/PI9dQG4SE70NJ8/rCFdZWMDVt16AFx4v1Yiu7koPJyehIZYOtGwt4xTh0M+at42E9JJWWwYRHdSDxqNhxgz9H5s5MxQ0ewyZMmFpmZq/ZGcHZmYakpJkRITqnvfhw7BVNQzOQbdwITc3PQ7u16DI4YLT6gWYmXX8+XqFClDBeiuUcAMXIZF5zRpY+GMt7INrw9OkyGSEISaZ0iXSUE8lI7CwgDwBCiAMQkPA3gSF9n8ofkvy0rW7GfSdDDVdwNo4eRk5EhZ/egJzhPwXV1koVvaWJCUZV/MqUQJ6OO2CzJk5cqQM08J3Eb/Wh2XNRDbQ03ZnSvAIPHsG20JqQAgU1eqU+n+de5IBEubs7AzFXN6CSkV0dB4m3m8MgOUl4+QlUyZolO0BhN0jogB8ibAD7AgPTcKghgcCL2uT+y4EfkOtrkeW1UIfmkHTBb0cQwgIgJDB02DPHhR//Y3du3BYORnq1cEYefmJ5Pusrb8jmUSkVNCJNdRa+Nq3hxZHO2MTHYxFl2MGzWJjYeSmksBi8q2U03cAqRM3Ql6SkuDROwegELZvzYiLgzCNCySKm/bdhVfR9OuHYulpIBN2DqmO4+how+QlNl5OHJYoVanaGw0by8h/fTn2tcuTlFTQ+ARkMkJDYcb1ykBl4s4aJy/3nlrzjrJ4PEslIM7e1kCC0ftlZZmEgjisLNJuuE2agN+BOTgFZMfTs5lO22yZ1cBLyCx4tVaslsP6qtBvLVhIz9pM4adWKDFHhj7yUq2SGq9LO6FceeRyHZVQBsp/Y2JkROIEWs/C3a9CVu+nT4bnN2MGzFhSGkZOBd/BP1+XyWDLuBfYTBqF15iFQDbDH6QH3tmtwFYF4TqIxC+oKBtECovS4Xk5exZuhPaCm3no8FHwsOhFSuwoOBiyZfuFCf2zIDlsdOnSJRo0aIC3tzcymYwDBw6keb9z587IZLI0/6st5aj//wombshLl8J378J8GTyHXCL0vJo2hVWeE1hVYw9yOZxRlufyp+ziZKZ1zdmEhJdy5WBsls1MLrjbYB+MFGg0oEnSCP+vQRIB+fkBJsy5WjW4U3cCd4r2Sk1gRfqfbGMDPi6x5OQVXu6JRq/Plw+21dnCNt+RdO4sbVwLC3CzicVNHi4s8FKTULXuVevWcLLAMC7VmELZsobNPn2CgDntCIi9KkjE/0Lyq7U1ODlqsIyPMtpHLj4elp7Nw1L6c+SYcPHqtWa0lu+m/vyqBkOpCQkQMLImATyg2wAbvL0hp8V7CroFiqoqL5g9mkI8IpefkMDYrLmMMRaz+aveVYOaOAAFskVTiAfkyp5KIoaPlLNcMZRZdc6nUUdOj6/B5nzGh8AQ8zTjmNxWKYUJGMmJeHjwPXHYEHjwVprX69aF0dl30TvbiQyJnj+R3nsilwu/RRGhvWVrLBnObIZvKkRi8s/HzAyUJy6gxJrjKz7qtR07QsVW2rN1wA2dniyNsws/QhN0hlN8fTTk4Rl5vCIwMxNuk9wsCUcihIo2E9GmWQKNOETJLLo7E44dC+cVdTjfd3eGCqg0MNRZWuuHU6sWzM62lOWlN5JHv2ONpUuh7IftlN3Wn/v3M75/+YkLK+jFX5t8MzwqJ0/Cn9+H8OfVOnz4YGDOkJa8/Icg2fMSExND4cKF6dq1K031aETXrl2b9evX//y31T+xoYKEDTl3bqiuuAxeXjg45JS+mWsNmQIx5hcvwsWv3eGuNy2fg4/cifgIc+yUGFxsAbp1g8Y7WoOvL5n+moPdiy3CkSBPC8OGCCqi/U4JHdw2boaOpnRllcm4dQvm3BpOfEwCnfbplxTXhUKF4EiLjVhfPkX2nlvFGSUv2JaW8HnjOaF72dyvgJfoObu6QvOCz1G8eEjJksbDc9q2wC+RiJw5IafPE8GF4GL4WpUKHnwVkm4LfIShS3LwgT1YjfRhm/EK3oz4hSaHt2/DTnVzeCqs7WKrtP78E/7c3UiQnQ1YbNwg3Qm3Y0dg5FwoHQ8O5Qya3lx8W8gYXf6ONCJtIjRXCncqzHc+49cxnkcv4OzAg9gsnY3nlCtGp/zm2AsoXAjN0RtAqdQxQfyxXBejNEU6XmT+yI59FlxmOByG6dr58+7JAm5iyo51zDksDDKNHkKiehh1OyZx9Fjas/PK5UmwJh/8tR6cOqPRQMLmncjatYWl0ZgirgekljnpmXfevJDX/ArkrGm4ubkOobqEBEhKskCWaIZFspO8fHkon/uwcL8z6+8h8+EDXFcWgUDdPHblWnO2sgL2QfPpJrTtSMajQDde0IzgHS50qGT65/zTIJm81KlThzp16hi8xsrKCk9P07Kj/59BAgHp1w/6zWoP7TpC7ikme0BGj4YRx6pgVTAXFjVWGr3+4kWYENgbAuHaYDh58zTchG2NMNrB18kJnKy/goMV2GHynB8+hG53+xAfHkfzA8ntAgxg924YemIVaDSUsYPdH4UFu5QOrQK9SCYR9Qp8gCvnIbtxE6USQmOcIMEDhyiwN9EDkjkz7O52Uuh410UkeTEx9+TjRxizuxFE5qHKWoFwiiURMhkozBMhMQELC2tOXHbgGc2wv2Lc0xQTA2vP5gfNAPyOJkvcSyiVvjPxMEyciMO8m4BZmnCNoYO9mRn0qv4GzpzGv04nwPyXkl8B6aW0uuxFl/8K6s1VA8JAfRV8EgDDyospe7hMnrqZn7/rwGu6E7XTh341DVQ7GsppcHQ0SCJu3LMkmmrI7ztTJUUnTWSHZoNjgsmaKY6OkKgWCEtokBq9jv/kmyaTAfZa+VRidJP0lUrDL5VLf/wI1xOaEnrTiwqPoGBylLF3b1gX+gXGw5NmWnlbIjp/G4N27k36yFGXLlBxay8oVYp8+QyHAecusmAje2ArVPpDKMj4L+D/pNrowoULeHh4kDt3bvr06UOoSTGS/ztMnQpe3+7hMnMkN29KMPwVzZTkqhB7GzWWibFG3fPpoe1pMSn9RMKcPT2hjNNTyri8QKWCda8qsvV7LVE6ATEx8DnOjc9K958uZ5Be1QVI2tjOnAHfbbPwfXCURYv4NQ0RCcQ2NBR2PSvIrph6/P03tOvrgDvB2LVraHRPjIiArQ8LslXZnFspkQGRf3OOHBA3cxFxDp6sXw/WySfGuHjjP+kfP2DQ7vIM0ixg7VohMXLb29KsCWrAxYuGbc3NoVjWUIpx72fn3j/+gPd5avO92yiDVWUWFrCix11W0IdhAxNS/16RHp/Lj525THnuP9Y6c0ndkNP/8ESU/zYsH0ZzdlO7fDJJSsnxEfNs6SAgC1cp6Mlqhm0tSni4mEnrgJMT6ogovY9prz9cqMEZ6o0XSnD37IHm4auos6Ud9+4Z/uils2O5QjmuTL2QNpxnxIMBGCRccjlUCoikOqcpU0DHxq6v2giMEtQ1a6BX/EJ67ayaISQVJ7fji8yXp08N/KyNlEpfvgytH/9Jv3vdROldiSHVM2dCkn9ukoaN0KnV0qoVrMs6kQM1l2VIUcibF+rbXaC+3zOdCcba0A4t/pe6BPzPE3Zr165N06ZNyZ49O2/evGHMmDHUqVOH69evI9cR2I6Pjyde64n68YtsVQxiYuCb2gPUEjzlyT+sGzfgVEgflNe8aPvYeNLtggWw4d0+2OTA2jZQTEKuTdu2UGLTAMidm5Cm/Ym59gAr4vH2FlF3rDVnQJLnpWlTaLpyCDg4cK7xbhYne/TFmNvYCPLpaKBOHTcWuExGcfEk9qOvGrW9dQuWX+8JMTG0Pgm1frVUGkRtMHfvwqBdAyGyIx1XQU+FQqixTEw02oDq9WtodaAN0IZBGyEqVs533CFeGFqKizYuDj6rshIbKsPti4jwi9b3e3BrDBTKgfXaFUB98YMiKPS2O9gSaEm3zdKUkCF5cXSJAnWw9CIUCQS1yh+lUHOZ4iNV3E7xJoj1vOjYGLdsgRmv9xP1xoFldfQ3WVz7xxs40hL+fAK4pH22HPT0wjEAO7vUTTIqSjgs6MKaPU5EMAzrvZ7004qK3bwJNTYtJkqlYMQ4QWbeGF68gL0/asIP6PtFqArUh4L5koBrkCc0zfH21E1HHjOEyI3ZGV5D97Pdb5iCv7kK43JxoXHGCq4LW79A/prQ8wqgJ9SXXucFjH7HZ8/CjsRucB3+iE5b4dO7rxmbNJ9gMjxtLWz82vj8GSKT8kKgC/56qs60CYI2OcqdGyqaX4PMvtjYaGXN2tuj/hGD2kAVm0yGUEtgJtNZU1C2LJTNdQ0cHMGlr8G/3xDq1gW33cvx8JKTK1dPkz/nn4b/OXlp3br1z/8uWLAghQoVws/PjwsXLlCtWrUM10+fPp1J6Rs3/B/D1RUyWwRiZSPHwkJfxptuXL8OEz73gM9Q+Ilx8hIYCA/i80JI8gFRwqk+Z07I6XgNsiRCR+h4fIaQdFXrrFHbd+/gRXhJ+OJF6FYYvmcR8SoZo2cJ1VNiUbIkPO46D8XZo7iOND5uy5bQcnsPISmjx1F4pwR1IBhJqAR4/x42vK0IQIHHkDvBnThlNqzeaMjhZ9hV5ekJzbLdhchI8uSpyvyd3nxkHrLZnszbaXjcyEi4GijUJVf6ABTQEiIU1T0zFT4+MnLI3mKdyRG12vCRKHdueD14CWzZgv2UG1y9CjX2/AXA2OWCh1AsfP2sgC9gbtyl7+QEW7ucgY0b8R28OU2Vk6S0FxPExLRx7x5setmXuHgzWp4VEralYOtWGHX3ANG3bVhaXWjjoQ/9FuchgZX4LnRk/DzhtR8/4Ems8L1L0eN4EepGDEWQ3U6kiBGeuPmwE1H0weaIG52TzxxdukCVI8Owq1EGD4/mem1nrnHlNXNwXZdAv3mprysUEKUSXLH6IiE920bxbfwyzFu2BfwkNTnU5z1Zv9mcHcyDQ9ApRDd5efLcjOuUhZd6Pial/FdHBc3SZTKesRg2lWRWc+EgtOmMN5/5A/USJ8atzmAiCtrKvrqcRiNHwva42zAL3vYW+tGlR/78MKv6KdzvHKdYi/lpbEfOagi9RkC2UYDQmb7i8jnEJVoyaKTxikWDcHHR7y4x4i1KQeXKULnYWYEpe/9/5EU0cuTIgZubG69fv9ZJXv744w+GDk1VW/zx4weZRauwmYbhw2H43qZCgLL8WqPXr1oFx76vhl1Z8NM6nYnhIObmoJApQS7n40cLNn2rSXysmlIiOhYDaR9QCZ6IPXtg5JO58AR6+8O3OCdAeodmOzvI7xsJ6pfgJME2BSa2JYiOhuwTWwOtqd5Tzemzho/0xYvDnuorhCSdZjcp/KczDxmC4oCaeQYt0yIpCSpPq04818jTQ876bYavz5IF5lU9AvfvU6Txn1SuDOwsDkNGg5dhlmhlBX4u4WDxETwwjURoPxsg6l5bW0PbEq9g8w6ouJmoKFjQ8hq2u9aTq9cqDJWWJyTA3dduQCmcnkOelPi5VA+ITMabN7DwjbD757pvnLwMb/qWpD378G3WC7AkIQG+xAuaHsYctutOeqOkJ4VPqhif/JqDA9jIldjJ45DJDDT/TLcLlx9agu/cI0cfFW+MkJdxSz35wDI8l6noPFl4rVo1INMRyGYGjvrJi86O1Aj7WZ5MYTgGvyJr1lI6r+nXIQrGj4eOZQA/OneGpke6YitX4tDCyEOdgnQboxh9GT1TTjt50Fm1c/ioGSfpD2dhqkr4Pczb4s4D/sJyY5JB8jJjBvyxvyQMGoS3d1oWW6QINHE8i6OnDU5OZYxMUDcyZ4YRjV/BxaVQYB5pfiPpng+FAuISBXeL0fXWmFaLqys8z5gwGB4OPxK8IdKJTCIKOPDwEHqo/Ifwf05ePn/+TGhoKF5euis+rKys/v9TjSSBCDx8CAfjasEL2PsXVLs6GQVK8tX8y6jttGkwbU9haNiQXZazaXVnAABzToskL9owscrJ3h6y2IdjpYzE2TmbOKP0Mv2mlkpLsK1dG57WGwHBwbj03sjEicLrghKptHhEiqKoUiU3ekCpUgUS+w+GCxeQTbuP1WxXEnEn4YlKv1EyvLxgSMmr8G4nVP4zeXAJSaha98rLC9oWfITt6weUKdPeoFl4OKy9UBzi+5PvGNStaybcaxNyfOztYVDDd7BrDZRchCE32Y8fUGZafaA+9UZqOHJUOBjejihD9Nco8molM6aHUgklRtQCHlKynxVNtPKhxUx7RucXsGcU9OgIOOLiAr42odhqorG11aEpYgTt20P7c32FzaHjNdF2NtYaiIAYU0ulQVSuzeIx34jpPRTLMVPRblyZOTM8m3UEOnWCYXGAsZ1LIB6O7kqhX4mRVf/VGzNiKAzvHCms9dvp0gWqHB6KY6k85Mih+wR//kgMODvBzl1gqaOy0dJSILpGVGNTxrSzF/5DlWBYSDBrVsDsMfiEZuiO0bkzdN4wRYjD5slIXipXBptdG6BEcezsDLjS3d0F9h4Zmdadkw7OzlDA6zt2316TPXtpvddduwb3I9rC34VpEij8/tMj3sGdsBBzSPf+tGkw9/0FWAVXOgpyGAbxH+wsLZm8REdH8/r165//fvfuHffv38fFxQUXFxcmTZpEs2bN8PT05M2bN4wcOZKcOXNSq1at/+nEfxkmEoGsWaFY1ifCj09iQZXUUunwcIiI94YfrmSKBRsJcy5bFiZmXgsuLrTs0oRZFnMEP/vQ90ZtT52CjY9Gg6UFfa9COVNyT2Qy4uLg7Ju8KGPq4HkFgw3EQDgJOzh+hZivkAnaVPqK1cWT5K7SDGNVHUAaIrB8oQplhYpYT58AGNYZkslAbqZBaJsNVhZJJKrNSFJL0JbQZkcmVtBkzw5bO50SumG2MExeQkJgxJFKQCU67BA2tDfyZiivZ6VOB+NdxzNAW+LfmGhKOty9C/XOCV3IJ+zVT140Gnj8yQlwwv1DIuXKwbUW87G5dwXvXnuND5TulNqwITTsNE5IROtoOAv11qKbaHr3RrH0BKAl5iGi2qjByLxEcR7fUd5sOQRtG8YQuXINrnXrYkz0bN7wr8QMG4di2AQgZ9pxjXiqaleIAfZBheEZ39ROnjV07NZ+LkUmN3cZYMtV7sNwSBzMz6TdUqWgVOZr4BwJjrrJy8/h9ORxbN8Ou9W7CVuYm8U10j4ri+cn8qNAGZg0GVtbwcU9eRJE1W6E3ci+yOW/sIcYKC3v2RN6DukHrf8CdwPkJSXzNSQkLXlJdzry8YFHfx0R2N4oFfrWrn37YG7IRDgDhd9mJC9v3kDOGROBibQeKtw7k+HhgTIokqigJNwz/Te6AkkmL3fu3KFKldTmaykhn06dOrF8+XIePnzIxo0biYiIwNvbm5o1azJlypR/ntaLBCLw118wbl8RaNMGl0IjTa42KlwYllbcgdXb5xSvN9GoycKFMOnpEXgKC0vC+eM9UH5pSqMVQomeIZQrB+WyrAd/f8jbRNLf+/IlbPsmSNpWfwkJH7KjjKuE621BMdgQ7tyBvU/bQ5KGUiehyZpGQCOazjdOXoA0C8G28c+hWlfoXgkQmRiZbFuktBVwAzIFGhPYTR03GaHHbmFZtRyy3U/RPvGKsQVEk5cfP+DaKz+Ir0LmJ8kljCkbjMh4dgqWLIFVsVthG/w9QlD+1YekJIiMtQScsYhOzonUJi8G9MwVChhc4zGcPk2+hoMAmaR8ClurBIiPR6FQ4OwMZXIEwb0H4G7YTv8HituQC2aPBh6BX7oOvSI8IFcf2RNOZfwfCp646ROUsLIftDqMMfLStFoksAVqDErzusrWmahQsIpGf88wY6XSIJAXXT0s/hcdmvWNa2K1EQhOrv1xteGjkCirTV78c2qAe5Aj/OfOVLWWBVgchyw14VfJi9ah2yS4u6PEitCnkfgkV9otWwYXotfBljzMb6eVZK+daKzdIloCUiJsAKEhaVsbBARAK7sj4JsZN7fCBj8nMREyjepGmLovpeolcOPOb0peKleujMbAA3rypCkKWf9v8fAhbH3RlfhYNY0vCG5DQ3BwAAf5d7CPFUi0iV6bbNmgb7FbEHwcCk+UZBsVBQdeCacCv8eShzZZ5yUyEqosagI0of4kDYePGN5QHz6EGa+EOP50rVCtMk6DOBahBQkVQ9euwdhjwyE6hu5boV07cyHhyIR8GysHK9Hjpsf583A45A/iTnvT675hEvH2LdTZ0g5oR+8lgjggtrYCu4iPN3ii9vKCPR0Owt69ZBmwia1aOn7Gph0YCL7DuwHdaNZZyI/C1hYVFiiD4nAwEIGxtYX5rW/B6aHQQ9iQs2eHSVUuYHfnAiUaTdRra20N0Rv2CiJFe6MAO0ml0jrxqxuysc1YF6Q0otSxVm7fDm2P7QdgwVoYNCjDJcaRcvLX402o0taTZwRi096Rt4ECUb74pSgxwYlkvQ5lDKR+NK6jouDNNVCrFjJZugZbjo6YXt9tWLtEL0R8x8+ewXd1WXjrQwldOSCOjoZ1XkQcFqr28uc8SmgsRI/MzYUKyd0JjeERTNGeorYQoR7y0ro1FNo8AooXx9+/VYb3HR2hQv5QnJ9coViRqkBqhnT79tB+0hBo2BRyGyYv5uZgZi4Qlm+BpisV/9PwW/Y2evECZr1oBIDvHePkBfi5CCmVEKjyQRkZgvM3/WWOKbh4EW6HdYFbBWj9GXwlEJ+CBaGN03FwdyNbtlSXh+j9OH3uiUjDDh2g7vYO4OSEouVihgwRXo9XSss9sbODKc0foNizmZydpgGGvW9BQfDkWz4I98L/E2SWkIT6/TtcCBS0uGumqJcrFKIIyOfPcORROQjzoOgtKGmbPK6I7+n6dag0eyokTWbwSMGzPD+oLQRB1VeGyYtOaG+MBsiLvT00K/hS6CpXQliXM22fj3WebGTJ0kTioJCzdTHeoMKzropAMZU3WvDxgfH178GdeVBhojRjCSG27N2qouEdAV2cOHA8+cVfKJWOi4NltyoQGRFPltUauvfQvXkF7r8J1avB4UdALtO6aGtBrKfqe7gcNR6YhZtncEzN2p6ZJ2wgZlhW9lzWYRsmJwhPbCMEsaVPn6Dh7g5AB7qsNkxehvdXwsS+0GsfmKWSF7UaIq28iAxWYROk2+Fz4KgFgfSGU370bEKGtg8dOkCTU31wjf2Eddsjad/UdygW8R1PnAi7VGdgIXwYmrbXz9u30OvwQCI/d6HeJJgwweBH6YWtU2r4JzTUSNNWES0giheH4g4HoIAZeGQkL2ZmcGnVCyjXGDo9AtKFtCS0By9VNIHIczfImsePNGHTfzF+S/KivSdIdUbcugWVNk0EYMQ84xoLR47AnO+j4SKUfg++EvJHmjWDZlPHQNmyJLQsQdWXK1DMn47NUmPNLNIiOhqmHKuEMm4GeZdr6N3H8AnD0REcbb6BfQIJ7jCq0XMUB3fg33IExiS669SB82XHQlISuZpOx9vrNeyZCzXGYIy8nD8Pbc4LSa8L9sGgWqYLzQUGQqB5SeKeu1LYkGsewZXd54KwePx5GEp2ET+uRgMJScLPSK1Omy5izNzTEyZUugB371K83jAAqkyqTBj3ydramkOnjQ7/EzVqQI3MWyFvcfAxTF6srKBOvg/w7BlFigj5QJaWwjMRHSvBpawrn8LYCVar2ighAR6FZiUuJgAHA4m+KXgfbANkI1OQIHAXHQ3TTlch5ocluRZr6D9A/7hXHjuhoTx2jy0okjl1KsP3lgHKUGVLIt176F4OrSw1gAosk+culws3UQR5iY41Q4MdslgzUh5BLy8o7/0W+8jPZM9eUa9tqTY5eEsQ7u0TCE7npTh80YErdIIrwhqWPirvnSmRqJdfsfFwB8z/J6XSV69CpS0LARg+B2bPznjNvKVWXGY5rIbuSzOSF2dncM4M3MoYzn3+QkYkJeGNG8XVgm1cHIRZ5SDmkzVeUaZJ22s0cOadHwB+OpS+R4+Gk8rrMMubo83R29+ocICMiJM38MjthFotHJTmzoUp+wvAgAF45uj189pxG3Pynk3IR7qz4Yjuz/sJQ78XA80Zjdpq4chRM7CuCB03APpbFvyb8FuSl7Jl4ULjBSge3yFL1y1Gr793D97G1YOn+bDXOrGYEIVBY2lFvBI0cSLzIpM3AwsLhCaDqiBjHACARYtg8q2jcFfOgmow61QAEECdQ0lGyYs2LCxgRrdXcHASNOqDMfLi5QVebo+F0Ic3qUzRhJvVZZwvj7lFUpfc3H1l+Np69SCuYy94/hz58IsMGwaLI87CarjZHYPKr+lx6JIjn+mDcrsXQ410s7a1haKZPkN4BD4+BWjSBAJ2/oF1UgzZGywyaOvpCROrXITXq6G+QF4evLMnnMLEvjRe6QSYlCjs5gbH+h6BoUNhrPC9FAtIxPXNTRzy5wIMHSnRn0+RlCQQc5EJvxERUGxWK6AV9f8wHpL0dFZCeDiuzkIyQFISzDhZFChK9QNq+g/Q7xWs9kcJVFymyEgV95K7m1hbC43/1ElmRIYniZozwJQpsDPxb2ImeHGyFgYbtOZrlodPROHdXMWX5GKP4sXhcrcNsH49tDXSLlkPnFxT/9bISDI0aDy54Rv4+cH6s0BVXF1hapO72O7fTN7OcxHlQTWlVNporTRCMoeOUumBw8w5zU2YCD+GCkRl7lwY9/oCvIbDzaG+ntL0Bg0gy955ULky9vZpFfhSojZmqElUyUgvLP/+PdzXFIYvQjhIH6ZOBfZ1hRq1wFvQenF1BVfZZ3CKSpOXu/+CM0/ogM1ZNRsM3Qtj3hMDpeWSoFAIocZvuptT/hvx38jckQhXV6jk95lS8js6y9PSY80aaBG2kha7WxIbC60LPqaTYqfR5FUQ3KR7PPuzp9FmrKzAbMxorMO/Cn1spCIlb0WEuzAuDkITnQiNt8dM61sWyo5FIH3ICcQTEF22IrxN+fLBmHz7GZN1KyVKwNM3VtyhBPdeOxj9k+VyodePwkyFhUVa75qx/TxfPthQbTMbMo+jaVOYvdKBfixj2Jq8BhczgMKF4W6nxdzN3JihQ4VTWznfDxS1fCwuTy/dH2ZjrcEKJZZytR4DAYmJEPTDmqAk99SN5Bf6BG1el8hlKnJ0+AWD14WFgf+Y5vjzkl69tN5IPton/dB/rE9IgJmH8jKTkezYLU/rpYox/lwGbjxNIN4c2y78wWl6KkUZsdfx/MhksHvKC05Qi7UTDJCIdB2ag4LgiTov78OdTG9fIyJRuEaZaBpxgNqlIjK8t2ChjGc2xQgcv1x3fnW6OdvZwdjWbxjMQmqVNy3c5eEBtfO+p5XZbr1r35ghSjbSkY0D7ujvFO7iotOTYKg7ABj2GLVvD7PNxzC78bUMvztnZwjfeowELNi9LKPgm7k5WBJv9DcHCOXSIkqOHZyE+x6rlKdpk6INpRKikmyJirdErW/olD8m3f1asgQqftlGxa29eCw2B9LLS3BJ/0fwW5IX4JeSbre3P8YGRW/aG65mBQQtl2Z2J2mW+3Ead6QpXpufREBl/FTu7Aw5FZ/IaR+EmxtcmHKJG5Ri5WzjKnUfPsCJ0BKcCCzM169IEkD7Ce0+UCDqDy5UCKYV2sW0nOspWxasbWWYocbWKkHc/dJa/cqUgd6uuxlS6KzhNvcIhKNT3lt0cjlMkSKgsEn9WYjmAv+DUmmAD+ffocSaJ+tvGbzu9WvwnNofz8gXDB6cdlwJofBUiMzjUKvhdbAjr/EnUOsQl7VnTayJpXBF/TXaKhWM3hHAaGayZqMF1tbQp9ZbhjKXlg2k9wmSy+Hc7LvcpCSbZwcZNB3a9D0jmEXHZmmTg5s0VFOLUwT46G/6sumEB2voxp4Twk5qbw82slg8bKL0bkwpqFAkmhqcomKRdDuvg4NAXgx8WSvGf+UATdg08W2G9/z8II9rCJ5JX9McTgwi5Ts2Ejdq39uOAjyiwMCqJGlxQi8vOD7qIjuSWtKjk+41qHb1RDqymY6VP+qcl1oNRz4VZlNUY/bvTnvzmjRQM4gFDKr9HItkL0bu3NDU8xodfc9hqnapTAZOWRwwQ6OTNG3ZAvEKJ+LnLxP0YgzBw0O34m06L9WGdRpekItvC3fqJXFjxoDDuwc4LJic2tssHZavNqe2+WlKTqqbRmPu7Vu4rCzJ5c/ZxQuP/sfIy28ZNgIkkZemTcFv62QoXRpv75qmER+ZDFtbKJ0jGKu3T8mftyLGuOPq1bDh1QYIcmBeB/h8PwfxtMH5iJo6zQwP17Mn9NzQSmjkUXMtJEYDt8AnFjDsEjh4EAbdnw7AtovQJod4AhIeDoFRwirjFQ5lOhTnA7F4VjPj3Rej5mkW87OnkpDbWMGqjaDoKMKYn4tIkybQZPZ8YfXzF6E7rzXusOFmdDjXEetenbCykmYLSCcvWguf3MG0ZNC9e6HLse3EqS2ZuxgGDpQ2rtg8DpkMXO2UEB2NvX3qkT8uwRwlFkRHiwx3JQ+5bPBLODkcWrYCDCQm6UGVcirgNrhFAr56r5ve5SXsGgU92pFGKjqlN5GBiqOBi3MSyRryLIyn+UCYPh2mn64IxYpB6ZUG57d12gc4Xgum3wW0al8dHIS4V0yM/oQsYyxUaqVUyjhGvuO3H+Q8oQB80pFSoV2i7a6jvl0Ec264qBoaqlNyegJNtHTs+vZMhCFDoIMHKISckjp1oE6VJUK4o5yRGK4hGMsdEStN4O6epuT63j34rKoNT/yoqpVbl6uAJSg+AUGSiyy18eIFnEysDp8Ej5+fn2mf8/AhzHk3kcB7CtptEIT7/u34LT0vKhU8CvflTnQeXhnJpQCoXh2G2a1kWLkbQoa5hPCNNpyc4Prk01ygCpPHGPdifPwI12IDuPYtB5GR0HxeOdqxjcnTRQi2pYfU0I8WyvQsgAdB5Krnb/TavXsh/4Wl5L+wlH37QJkgR4k1sXHSHzW5wkJIuRdBBD58gHUvy7MuuB4PHya/aKIHpHYdGR0Vu2mR/2mGREhjiI2F+1F+XA/LbVSN++FDcJ89Avev9xk1KvlFkR4QOztolO8VjSyOUaSIsO5GJdqQqDE3+ieHhEC9ZfWol7CfGTO03hChmeLmBt/nb+E77mnKs/PnjKcQD8iXTb+9lRXsG3yJfTRh4litrtJgerm0yMZ9eqG9GevDz5+5dME3fWtExzUVqM9hevT6hZ3NgPDanNWOjGAW49ZnT30x+dlKCDd8r6ytNdgSja1Ch1tJzP0yALkcnO2Fzw39rmf9TE8ibG3FV5TpIyD/g9yRz5+h3eXe1Hy2gL+SxdXnz4dGcTtotL5xxnQSR0eDfSty5YIa1pepke2VXlHJFM4lIynNLZ89G1TZc6MaMZZSujtEpEFEBGx+V4EzESV49Mj49f8G/Jaely9foNCCrkBXWo8XqVyYPo8jKUlIPLAwTCSioiA2wQVi7HBWgaV2CEa7mY0RyGRgaZGEKsEMpVIkaUrfVTplXCMoVQomZt8AtnYUKNCc0EgLQvAgMcJIAogO5PVT4fj1GW7Zs2DM45MBMploAvL339DtalcAZhxPbr0g0jYxEeITLCHJGosUCXKRVWGvXsH04y0guCS1dwmaJyU3CbXl/eYLsWlD436PtQVsU9fmFPJiZDP39YUDHfcJ5W4DQ7l4EfI6B6JQRuLmlsegbVwcHHuaDciGbbIw7bZtcChuPTHrcjG7MeQx/BEZcH7Xd8geAJNOA9V1XmNuDk2KfwIOQNnkeIRILR+NBsZtyQ1MIctma3oOS35DLHnRQyIik+wJJQeRj8zJ1yhj1Q7AooGvUU2fg9PgKUBykpxY8qIHR25nIpz65LwiwlOlY0MOCYHHCeWJeO5AgVeCFqU21u1x4BkjcNiXyJRNwmvFO+fnASrsq0OYgVyds3uTM4B3HABZo7RvGiEvsbGgxg6UFtjp4RIT+4di9tcUvHv3J40IpKFSaSOxkb594ZjqBYx34XrTjGq1lx678Jg+hG3wZXBVw9WH+pCUBNseCz1d7O+K0K1ycDBI8nr3ht6zOwvdbPNN13nNoEHQ/3wzHJ1kmNXZ8/N1uRzkJIA8SZQLQvt+/Fe6BPyWnhepMv3aUCqh/PR6lOAWPXoYv37CBPD8cBPPJX9y5w6SPCCTJoG6YADqfgOpXh1m9nzLAgYxuodYdadUPA905A7FuH3PeJVBqVIwIftmJhTcR8GCkMVXTXbeki2TcSKQKxd0zXyKrllOkysXHN8cygMCODv9tlHb/fvB++AyvC/vZG1Kv0xTWhOkQCR5OXcO7FbNw+7RdaZNk2YbFATrH5dg/Y/m3L4trVTaygr8nEPxk7//mXR5+qIl88yGM2VPHoOaWulRqRI87Tybe9mampQM/uAB7IxryJFXeUwrSJDqAUnZ1VIIvIh7PW13bqbxJxt2pGZjvw+15w7FuHhTkSY/Qyz6DTDDjzcUndqUD3oUCDrWCqI7a2leW+tv+0Xy4mAvbNSRUfo3wA5/+FKDU7QckzFWcP48VL05naa3/+DQIXFjJsnkJGJBTJyRNcCAR7n/fD8qcpEyHXLqfL9GM3sciMKhXQO938eAgTL6sYwmBUS4vUFIMjLyXIWEwAey8SHMQWfy68p1FvRjGeP2F82Q9nHkCMxLHMi8cwEGE7C1o2ShQcIgLVrANMtJTKtzJY0i7pcvcEZWg333c/DJWEGZgXCVgwM4e1phFq7HYySyVDpbNng66wjhOLFp2S+qLP9D8Ft6XuztoVuFl1hdPk1Azd6IFl6TyTA3h6sv3QF3LJ9J90RIIS9Cwlsys5bB4PbfYekiqNYDY42VzpyBo+8HQZQr3R5Dw8G5eMcd3AcmECwi0TjNZ+2OAG8/WHAEqGfw2ooVoWLhxcLkK9SAb+L/3rg4CFQKK0BsrKArcTexL3FnitGho379BRDE4FaVXQ9BQZSoNZqzZ2Hg6fnEKc0YKaKdgjbUaoi1dEUZJsdBh4aGIbi7Q68yD7G+fYnSNfsbvDZ/fng9YJFQMjtJUNbbsgU2Jc2GI9AyyGD/NwEmJAr7+EDo9FUwcSIWa78C6Sp3jO3JhspCJIZvGg3OziPeIG/uyavPkkwB6D7CmbPcgbHwY4B+HRC/rpVI5D0FO7ly5Ezq69ruer0bV7rKnbdvYc+75sQExVD5vNDYUx+6TsxCKAdwm5yVtQdSX7+8JxhF2SI4bNoG1NBpe+VvW95Tg0x/Z/TOaFfU6BK83Tz7G3FN2yKftRgoAkDePBp4fA/bnFlQq930VwOlQMfGeO+FDdepCM8Ez6G5KTtIyi6fLv+kYw9LrvMShnrysLHwOAcGQscdXfnxtSFVRpM2zKkFJyfwJBAcHDAzyyjnoE0s0qe9bNoEu9WzYD+0WJiaBpUe1tbwctMN3DvWxnH9HSCn0F/Lai7UcACX1P4ne/bA4JdL4SVsvQxt2+q5F2JSD1xcEF9SpBsWFpC3mA0QCd8Cwd54CsA/Hb8teVnT5y5c7g8dOmNMu2TAAFgT+AYmm3OzkaANoUnSIOaoV6AANLI5DT7euLjkp8+sAnxnF66jHVmxQ+LEJRCf27dhwbfW8A2qvNUyVYmMsZsYctJrK2LONjaQxSYEkpKws8vEvn0wL3IynIXy7wyTl2zZoEeuS8BLCBjN0aPwNFJI4DTmJnVxgWq+zyEikhw5SvHnnzDjwyNYad8mawAA+CZJREFUCOcaGd6cihaFJ51nw7lzuA4/TqZMsKLTdbg5CFr2w6hrOd3i9UskQqSisFwOLrbxIAv/qTjerx90ONIK2yyuONdcptc2OhrmHi4KjCf3DkHiHBAeMLncIHlJSoJvYQrAC6tQcPWFLyEWvCMH8sAkozmTZyZdhQnjcfhrLylJt3aOqc7jmBj95OVjiIJEsuIekpYIlCwJYVuO4ZjFEScnY615Bbx6BaPuJiuiXjD8fJy66cAXGuF7I+24mfPaAd9BaVruiL8/jCx7BefHlylf+48M7xcrEA9chfypjGzrVhnsKQajN4DcNKEyRxeB8Viaq4mKkmcoSy5RJBHbW+ehcADgkcEeEHZSe/sMLOLLVxmv8YdvafnimVfZgGx4PdMfqlm9GtiYFaYvAO++Gd5v2xaKHxqPS34v/P37iPxrM8K/qD0QCSHB4J/sfdJBQMRp4oiEm1uGXJ1r1+Dxj9bwdwka6VE7zoCU2NG3bxnjjP9C/JZhI0ASEUhIACXWKBMt0GhAefwCasy5utN4+UzXrnDAszcHmm0hTx44cMWVPbTg+CXDhEknfkHwrXWjWPqylN51TRDFMiXZN32ptAji07gxfKjfnw8VOtCli7QQDJBmEbG1BVuLeNzkYUIOiwEULw5nGi7mjH8fOnVKqxFjbNo2NpDPLZh8irepC4i1tbBTGxOJ0YEuXWCn5yCONFlLjhz6r/vwAWqsbUWNH3uYO1drXBNLtF1dIbtbFB7qQINpXDExMPFwMSYyiR1a5Hvbdhm9zFbTblVFvuj5WURHg8/AZvjwlTadhS/FxVWGGyH4usYZLDuWyaBaoRCqcY4SRVIvrFNHRl+LVYysctugh8zLJR4vvuLmkvbA0akTbC8wjRXFVpNTdySEeJWMeCx/KhRIIpj6kMKyDOxsj/e+IAo7Xu/LmGGZLRvMbHmX0QlTDDc81WaDlpYCcTAy6c27rJjJSGbuzXhDdu4yQ6lwIn7OEp06RgumxXKKWpyaeM2gZ0fj7ELkl+g0S4qDPbjyHVf71Be1vSCqOBE6LHpQpgx08r9GA/sLabwwIBQ47TJvw66uJ9L0XtKJlNhR+nLpdKw7IADGFDrMzKxLKV1a90etWQONglbSaE8HXrzQfU18POz5XJpl35qya2fq+rZrF/QK/YteJ5rw/r2ROacghbz8R8qlf0vPCyBpQ/b1hcLmj8HNDYXCE3Nb0zdzK0vxprduwb3Q5vA4D/VT+iIB6hil0UBXx45QZUs3yJmTXOX/oGFpFczvD+0PAtkN2q5cCWOv7AczM1bvhyYNxROQ9Fi10Yo7rCR+WSkWNUBvVv1PaBGQ5s0h3/ZxKLJ7UahQxtOUTiTf58qVIXrYRNi5E0Zn1MkwNK6/P1RzvIO1vTkuLgGSbIG0SajGmJPWnEHo2l3C8xJ4JoCT/uSVmBg48zo7kJ0sT4Vqgj8P1yQu2pVCC0U2+9NV1WHiMfHKFViV0AX+hmFBWt11jeDUCQ1YecDsDWAh3RvQqxcwcQJU6QvO+lUjP244L8gwb/vKz6TbFDg4GKwKcW9SjijiyddIxZNXgqjh3pY7sTl9EL9e2wzO7/62pyRVr4nZtjNAodQ35HIh1GbgfttaJwExYKPHw+viIjxjSh2dCPWFI0RU7ixdb81NZsImGLUx7XsODoCTtf55iwiDzJwJYz++Rj3PnKPVoG5d4fX925Vg7w6rd4CN4NmytobI3aewa1Ebs/WfAJEPli7oEccrUwaQ7YViFcBYDYWrq/C70SYvOv7mgAAIqHwGzp6FIv10ftTjx3Aotga8gjERuodLSoIWa2sDtamwMJGWrUzfsp99deSRRTu+7fCgbVWDzeP/Ffh9PS8SQiF//gn33Wpwv98acudGkjchPS5s/sRHMvNo/V2j1x48CH2+jqfP+Za8fAnlW/tgTgJWtSsbtfXxgdL2Tyjt8VY4aUiYc1wchCY4Ehpvj0oF23bKGSabR7+NJY02lN23D4peXkDRC3M5eBBOnTFjNT3ZdN1fvJhSMgICoK3vJZp6Xc8gf54eSUmgUstRJZmnJuyZqLfSti2cKT6aw2WniypDzICUZ8vI2B8/wpCTtRkSPo59+7TeMCEZNCEBll4qxLqkLpw+ZXgDiYmBHXdzsiOxOdeuSRvXyQmODzjGceowfnzq69onZH08wNwcmhb/QFP2Uq5M8oZsaSm88audpaU+XNqQqJfi4gJNS3yitvqoUe+7m2MiHoRk8Pg8fQq7Ldqy5kJOggzr6xmeCOhMenn+xoIHFOLx23S7sZ3dLyUaAwZLtH/CQPzPxgbUyefmNNEQHSRAJgOHTNaCwJyx79hY3FEPeZGCZy/l7LTtypKDmfn2Dbp3B8eYLzj+0SejB8SUjuXpYG0NdtaCpzH4W+oz1KYNrHMdwbp6ew16aLWxYqWMVglbGLS/Mi9f/tK0/hH4bT0vlYcXJ5gneLf14Mx1EQb/I7n8bH5y4DNYS8/41sjMhB99kpBUajThzsTcEycnyGn9GeTm2Nl5snUrbNcMgUswLFxvh3dA6O789w/B3RwW9mtNMAHRBOTAAWi2RShRmjUPRoxItv2VSiURthER8PdHP4grTZY3gohU6ZEVCeXl/4+9s4yOG1m39tN2m5kpcRgcZmZmZmacMMNkwszJhGfCzMzM7DCjA3bimBm/H7LdJKm7nTn3u3dy9lqzTo6kUpXVUtWuF/ZLtpb2nLkq3TYoCBbfqgBUIOm8IIYIGEQi8ueHyD/mw/LlKP98r+FyEUpASL8c379D+431gfq0WybU+goJgRvBZYj+7Ebu+1C8uHhbCwuoV+gTKE6CWgmZAQOg3dHO2Pv54F1OPKrS2hr2Dr4kmAUnqj1bA/7e1FR4+ckGyIvVZ1N81XeNBmSjyFoEHBw0hMe0UalQODG3HpGtcEnAXHPMhoqbaWHjRpgbuhoOw7mnemIW9GiXJH8PwVQrN7jpAB9e8gCnwYmEdBOOHToEhyIXEr0zNxNaC/F4YpgzMYrQFj1IHTcBELFmOTqKRwkbiOzZoZjje9wV33F1Fbm/9t+bzoxlrGPbt8OT5ClwqAyjO4oH3cbauRPyzQyTr7qp1IZi40aYE7UOjoDfE4FzR+AAcSKvmB6L3rRpMH5fKWjRAqcS4yWvmzfyGxbTJpBl8AjSK0uXLQtlbXdDUXNw06NYmgb1v/nf4Dn6ZS0vLwKseEYBXn0wXvBt1zlXljKIJVv1291WroTaXzdRe3t3nj3DKItPy5awwWcCG2pvwc8P/PJDKW5TMd93vbLkOkh3XxjQb7du8KpsZ141HUnDhsbFgJiYgLlJIuYmiZiYCB/oA4cqPB+2Wq+89717MOZhR8a86qWyCPwPpErfuwfNj/eh+Zv57Nyp1q8BbR8+hBq7+1MjYCNr1gjH3gRa85o8vP1g/N4gMRGClZ68/24juz6YmICtRSK2JjFYWgrE4Pa8CzymIBuXGr/be/oUGh4dQJsP89iir1apyILt6wvFvILIyVsdD4ZeWFvrJS8pKZB/UG3y84IOfbVEOvQsEhrQGvfTp1D56FiKPNqSITymjWOzHnCB6mycr+YqsLERdhAGlOoQgyFZTntP27OJzuw5K75bqDm8CI6E4lZJpjKkGu7fh7/CW7PjRXE+fpS+rmr5BJpxkObldXPm37+H9dFtWHi7Mvfu6bYdM8WaZuyn2cwyknyxcWO433UxJ726Ub++2gmpBgaQlz17YEbqeGacKCnKY1+9Auv5U8ny6YawsVFDeDh8S3HlW6SVdI2hNHiqJXkGBgoWbj/FM/w8fujGijk4QGQkqcnibj87O3A3/YG7bYxsnFm/35R0ZwO1s4sQbCOIc82aMKfQJjYVnGNQXb7/7fhlLS/2tqlE/4jAxsII8pL2osxc48IDlmKxOpkhy+SbvHgBZ+Iqwfu0b8/TcKtNiRJQwvEgFIgGr06sWwdsKgPjNoCFfHzA16/wJTo/BGcjdzjMmKHgCE+JG+fN5QaGxyQAjBkDPQ81xaJFQ3Lk6CN7ba9e0Gt/M4Esdd0vHLR9C3ZfMjatUnj6FOa+EESxfO8LmSBRpi7EBkdgEyGdwgiC/7aKx3OIjSNLlmLExsKyC2WIjR9D9vUpdO0uzdODguDA+2IAFHuedtDKisza810ck0kJi8DJ1hK5P9rPD653Ww0nTuAxXHhWBw5Am2NCoMH8v2HECMnmGjAxgVKF4oCn4BiNhhS9FpydYXHzi3DkCHm7zAP+wSBUfSRCa4G6cAEuxo8h+mhR+nYyXv780CEYf28jETetmVFXKIQqht835yWVafhstKL/GNXxpCS48lmIASv7zvB+AxOciSYnPI4lV0npSOEjl+yJoyXWV+xpUEx1vGZNMN+4FnubZIoWFc/jH7bAhwA24b0ggVZjdM9HJ5gTjg1E6lpi2zWIIGjFHqzrNyK9bIK6MJtBv7HIwnjrFvR4JIgwzj8vzFHquHTdjBs0g1t61lU3N52g143bzPjA77CnAONbqNKwT9114Q39iNjoyYhqmUvP1kiV/pGC+r69Z0/Ym/wFxsKnTvJzY9WqMK/4Vjxj3lGx4kQ6doR5K0rB+FmQRVWTIz4eco7pSERqO0pWS+HCZYn5x5BUabE4m0ygdGkoXeOuoKPhK/JC/R/DL0teXpz6INS92XgRqCJ77aZNcDl8PuwvyORuah6YRFOjrcZ3nljxhcbEX/KgaRPD4jkzoFQKq5QBloi//oLfn2yEJ3DkikBmnuEHPwwML1D7qPLlg3wOj8GlAFjJtBFpC2S6COaRI9B8n+AKmr0SlYS+CKpUgYt1ZwkiHO0vExkJY/aWAcpQc1MyXbsb3u/9+zD10jBiQ+PosEnwckgha1YYV+YMvH5DlepCmeXnZz5D7tyw8hwgnUdrawvlfALA4n5GDPVPpUqnBwrreT/s7WFIVX84uQLqC+QlSxaYXPsqNpeOU7z1dMm2SUnw4bs9pObEJlBzJ4q9PQYr3KV9NOfOwbSQIRACtd5IkxeFArpW/wDnz5OnZhtA2HTExsKTyGyA/Nw+c3duUphI6R0JGuQl3QJiSSypqYa83AKy9mtAEo0o3i2BezJy631mZecre/CdmcAHNdmfsmWhbNHTgt8xuxEiRGrImceU0HsvcM7lRGysuwY5mTIoGFb0h0GFSCcvnTpB3YMDsLFMxrORfE0mKejTlzEYbm5CwIsa61q/1YyLTIXdMGaziqQsWmvLCVbCFuizVNxt/ccfMOBAHRg0CBeXxjrnHR2hSsFgXJ5colTxOmSmjhYI7tTiNe7D4cOQfaJwUISAmJvD90hLEjEhPDRz1rkMmJoKBEZN8yEhAZKTzSFRiUUKhhfnzJJFqHPwL8Av6zYyJm7l8mVYF9eJdXeLExoKf4xLZCsd2DP8ml7iPGcORPoWJHLkFEqVgsmzLGjKIdosq2ywpTsDCkWmiYCdHdgrInCzidZrGhWFsf2qM7r0WlB6ULs2XKw6iYulR9Ksmaa7yuBU6bR+NdKsY+T1eGrUgK9dxvC1SF2GDxfiPw58KM7JiPKSKYzpyJEDZlY6zkz3xdSrl3YwXTU2E0GoPj7QMMdT2tgdw89P+rqwMNh0vxCb4tqoXGwGSu2Lwc0N/mj+kJFJs6lZQ/ql/v4dcv/entyprxiglgAWFQXXootw4nNhST2tqCioMbs2NTjL2AnCgmUoWTMxgQ2/3WUD3ZkwQkXO7O3BRhmHpzI4UzvyrFkhbt0WYrFm3Z8S76iWSB2ArZXwEUX/jFipHvn4GQO/soL+zBwonnu+bYcJL+xKc33AFoPk7j08oJBnMDlS32p8H9r49l3BZ7z5/EPX/1ewIKyof5gdTv1FhdeObgsnEA++bjgpPxg3N8EXqB5AK+U1clQtU1JzZpEiUFNxjpr5P4umzJuawsWVz9hHS8Z30Vy8S5eGJopDNCnyzjCXp6enLknX2sEqFJA/Wyx+PCWnl/j36O8Pe6Lrs+d5Ib1xxPEu3nx6m5DhEhsxAqw/vcR67mTu6s/9UCFLFuEhGr34/O/Df8lLJohA/UamdGA7LYu90ct4LSzA1iQGW4tETE3B0kr1kuszoMTHQ1SyFVGJFirCYSCJKFUKBrrvYmCB82TLBitWQLhPQb4Nn6O3bs2FCzDs9UCG3e2Ev3/awUzGnnz+DFcSy3LmdXa9YnEeHlDF9SlVnB/j4yPMEfWyP6OZ7Rkhy8sIKJWwb+I9jlGfJZPkZwYLC/C0CsfT7Ad2dprEx6A/WZvBGlhcMQNqE1/RonCk0w52OvSldWvpJp8+Qdc9TegauZz164Vj/h+cuEBVzl020BUqliqdyTiOZ8+g4u5h1P+witUSm/qkJDj/zIvz1ODBQ6HvVq3gWPEJXKz2B1XkDaCiqF8foob/wdfs5WUraZ+aeoMz1GT5TM2MFRMTsHCV11zpNKsArdnFiBkq30PzGuF0YCvNqsq/W5N6fmE+I5jQU8QFqadwX+eGIfRnFV0byfRhbAaNnZ3erJ1GXZzIwmd8e+hWVPf2hv513tA2fhMFCogMxzEFD77h6SQ/R43cVYYW7KVtF5Xpec6UOI5Rn2Pjr2gQ0T59YIPdIPZ12KNfh0UOEsq+Y8bAQZMWHOx/0rD7e3oKv1v65kRiB/vw4HueUpC9U56Inv/7b2gdvJLWe9vJFnFduhQsXzwg699TOHrUgPHJIUsWYrDi3c3/+wWOflm3kTGBs5Mnw5B9VaFTJ3Ln7q3y9WRGLK4dFD80Bcv61bCzq6q339nPb8NzON8avnyB0/EridtciFmthah9KdSrB/WyzRfsnIXSXBcGEpB792DxZ2HlrPBK2J1+SipI7EdvcgfL6wM8fAhn3zUDMyV1ngjW1XGv/oZXsP+aIERnKIoVg+MdtghVA9sbEZCQhua1ImH6CcgbARggQZm2mJcsCV+Gz8dq+99Yz3pqdL8Zlhc95CU6Gl589YL4grh/EjZFgEAiMmG1aT82G8+5gN3oJCLEpSVUEJtw1UmXhOKbpSV0KP0K7tymVGXV1ltd2dagTV0ab8qVC3L5PhEilTO7MBmwINcs+gM4ByVEIt3VA0JFcvL3X3UnhtYUViui+PecYDjUCXpeQq5UR78W32DOQmjdFdCKWLe3JyksioQYo2q0akKKvIhYi9L7/Km0chD8NjExAsmV8nvr8aUfuenGC1pgd0n1e5QtmQScgOI9NZLlatYE3I9DFmuwbSV9U0NSpeGn06Xx8iIGK0Luf+fk82zcS1wEuyowraNmbM3PVuBOh3qJkHTXaJ48UN3iKnh6YWdnYK40UHFYaa4Rg0XDZGLjM5Uo978Gv6zlZe9xK2Yxlsnb8updz318oJDpMwp5fBc4j4mJ8NFmIlW6VSuYYL+MEeWu6Rds08KNG7Ahth07HhUyrDLoPxR7snkzFHu0mfJHJ3L2rPy1167B8Od9GP6oB3fu/FwRTMDgjKEbN6DtpQG0fTaZw4fV2oLRbhQLC/ByS8IxPsjwmCS1WeDwcSXTTP9g7PYisvPk48dQ8u+BlPx6hPnz1U4YkDrs5QUrGh9nhe1oOnYUjlmlLYBxCfKf9bt3oBwxGGV0mGaAaxp5SY2S7tvJCbb2OMtWky4MG6Y67uEBQ6o/5HfFdFo0F9+JOjhAzJotxGDFgT1qvktDdW3kFmQjA4V1BgbGLTLGWte08OED2Mwcj1lgAL166bk4E9oljfpnoQgPqDJQlQ8dEwNXQgtyLKikrKuhRsUEWrKHFiLZRoAq6OQngl7cPIS/KTJGaZh1U89v/PkzvEjNy4tAB+lMzHRmoSW1byyKDqiIDTEUbeDNqVOwIrkfK64U0c1ySn+vJMbdrBnMd5zO/FrHZTMxc+SAip6vae5wFl9f4djgwXDOvT3numwwqgK8nbMwocUnmv7sY/j/jl+WvKzfYs54ZjFlv8hLpwfx8RBq7kHgNxO9CvC3bsGmqBZseliM4OC0gwaSiNy5oZbNNWr5vsDJybiUZVEYGHvSvj1cL9af6/WmUKNGJmJP1FCqFIzIvocJ+fbo/chCQ+FRuC+PonKoPiwDrUWfPsGuD+XYFVxDJcBkoFhcYCDse1uMfaHVea6ebWRAv9evg8+aP/B5dZ5ZaVXt9+yBScmTmXO6ZObKz1tbC7+TTHCSiwv0L3uP/jabqFZNONalXSKjmcP4Fi9k1+rUVEhOETSD1Mtz5elVFStiyF9VjyKgyA7XyQkW93rM1NTfaVpH/HkrFGBlnowVcZqGHQPIS1ISlB5TndLcos9QLTOFvb3wGxuiHyBCBPbd8GYhw5ixwlG0ycv11wggC6c2q7l+fpK82NhATILg3gsPE4/JSklOJQWFZAm1R49g2MdhdL3UkyNHNM+9eGfBI4rw9L3qWQUEQOWNvWj4YxNLlkiPbfb4CPbQmt3jRHKhgRRHZ0JxJOCprgXn3GUle2jJnqvyQiqbtir5ZJqNuMWrdONMxMiaHvLy22+QP/UZ+Se3U82zWli2xoK6pqcp/Xtd3QriRmRe2DoKZqGQCDP56dTGRrinBCmuUQNG2K9lRPnrmoHvWqhcGa702cw+my40aWLQECVRopQJlcxu0L7w48xUL/lfhV/WbWRhqXpRDbYIpL3cAwbA31EfYSo8biMEsUlhyxZY9mMhHIZb79JcLgaSl549oeeCXoIPqOhC3N2h+8FmWJYrhleZyUaN+c4dOP29F3E3PGnzRH7MXl7gZf8U3KLBRRCz6pP9FFapMeTP30y2u9q1YWfRmWBhQekqI8iRAyoX2SwsxEVlTL4Iaa/dziwEYMUu6N+fn6rX8z3WlkhyEP9cgZ+MUu7du9DytJDxMW2PoKic0a+eSS0+Hr5EOwAOGXOrehCqnPfH3R0GlLgBr15RsaJgAklMhCZL6xPNRfx6JbN6vVyBGE2GMnSYAiaOhaZZQSEd7WthAaWyBsLnz+TIUTLjeGyiKXGYExWdyeyIdN9RRIS0H0TLehIfD5+TfIkO+YZjAJI70NRUuPPGGXDG6lWixvH550oSyRRc5iUwZJz4lPb8ky2QD6sAE7JpcbN56124wUL4G8au0RV/9HGNBz6Dm5a1CPSTFwlrkYMDFMwajkPAY/xylkAsjc+3YSE+k0KWRgkEiBhBPn6Exa+EKu+57kGjRqpzVpYpWBONlYXqeahLDURGShc5zIDEe5+3U2neEIpL80SCwzTPjZthxy32oJibSopEBWiAHDkV4J4IYSpC+OULxJEDgmzIofbZpaZCrLUrEd9MsNYjmSCHFy/gVHItCBASd7IJSWpMmQLXUo7DUj+2tUJv3EvJMkqUty/hWcyLsX/kYdKxcjB8GJ6ebTWu27PPhAtmq4hYXZGZDdTcwuowJFUaVKnlmRRFTMfMmcDJgcKu0itzGWf/W/DLkpdRo6DLsXZYdmmDs3ML2WtfvoTAhHLwLislo/8B1dhMBr96eYGXwxehFoyeqPiVK2HZ453w2opVHYT03/Ef+8FH8HskT14AjY+qUiWoVHGTYN4o10y2Wa5ckMvzkjC550gTKbG0zJSpNjISOqxtTGxCPkqOSmHOPGlDYYMG8KH5UPj8GcfeuwGo2ysL93mLWa8UEowom5OUBIce5yUutR0uRxOp20jad2RhAVntQiE2DgcHYbfZty80PNgHm0rFZSvY5sgBf9Y9BKE7oLVAXpRKOPnQk1S8iL1vJIkw0NLk4wO3h22HSZNgumr37Jc7Eedvz/HMlhW9ojxiSF9VIiOR3Uqq4cEDKLteSDkdNE8ITpSCqUkKpKRgYqKavBUKmLSzAHEUpsimBIboFlgGwG9AdeA5ZfskckPLZeLoomIr4eHoFO4TIyBTZ5tzkqtET8jLybrSCrnZmhUjiFiyN4HnamFbZmbw+O/bAtsf+Q7ILv2HS0BDu0TLc/Rw/1vhI99/FagACLETw+s/w/74Dgq2HIfeSUQCjk4KCIDQSMFyZ3Carja0tF7a9rThCm9hICT2UaVK794NbY/vAWDBOhg+XPdW1auDw4ENUL48lpbi0f3pz8tEkUJ4uGrQ/v5wijrw1LBY9aXLFHCwEzToAsWng+I+ZA3W+WQuXoQ/E/rAPfjtiwR5MRRubsLOJjxcFQRjKPHRxr8kXfqXJS/lygE2ZyBHMb3aJXPmwN/hh2AtPBkqWCLqWV3EwscVW1t5FtCmDfhtmQDlypItWxPmzoWZL24S/9KCA/Wgbl0jB24g8fn+HZ7F5YQ43fjLTLucjGmovjsw0NKUJw/0zn4akpPw86uPQgFHHvgCvnBHPr/b2hp8rYPB6jukraFW1sIYEpNMZMsp5M8Pc8vsgS9fqFRzMMnJ0HJZNaAaVWYlUbeReDsQirp97DkVTp2CsUJWQdGiUNT9NriagZ10WzEoFGBjmUxUrJK4WOnJKTUVUlMATFCkb8ZMTIRnnUlL1emdoZC1KEw9BtQXveb7d2g6rzkkF6P6BJgxQ+2kHiXU+HjYdjk30I0sZxTUrqdpoJGzUpmZQdLOfdC6NRwJBRxV3dokE5dgmunszxEjTeh2oStOXZtgY2OY1Pqr1wquUQE+CeuJFHkRKlJbEC+2KqY/Lwm3Qim/GLJ9u42bX0HEyGShQnBt4FacNy3GY/JtzZMihMvKChYMeAPHp0Kt/sgFGsuhQkUTXB+ewKlMfhISsmts5gb3iiFw4FTo3hMQSUdSh7s7hvhVDambNXgwMLQHdFsFjuLkZeRIGHGhMXbedpjUki+oqRdeXno19g0ZN2CYJSU9kPz7d3B0ZO1aOPFjNezOztyuRoo7ZskiVFL9P45flrwAmQ5g7d8f+i8fIOya8i6WvbZSJahktwVKmYJ7E5KTITxFWNEMTsPNBBGwsAB7kyhQmqJUWlG3LhwoOwuL5BgK154m2zYwED5H5oUQH3Km1zL6CfeNobE2FSpAheIrhQdTrb5GyEdcrHy9HjHUrAG+t7ZjU7U0SUm5JclLrlwwqugpSPWH8oPTHnkqqamKtH71QCpzJxOp0gAfDz3AunYFzHfeAoqKNnn4EIr9MRGYSJ9+qNKTjfmdxFKlQXbcCQlw/Z0n4Im3lgZOg2F5ucdXUms7EyQSqBwdDT3+rgRUosHSVGrXEzaU7Yq/wObhdSpX7mbYuLWwYVYgpv164Tx1HlLPq1uNj3DuLDlrqwTu0lGrFuB2Dtx9wUKXvBy54UoKjbG/bkG1NFdD+qMyN00iLk56Gi2UMxavkCd458qFDgHRE9B5YMEbKFUJFt4DdItN2dlB+eJx8OcdsEvGoO9D3bUnYR3rN8aBl5xFObEIpxronl+6Qgnrm0OHuWA5SONcxxaxMHAhNK+OHHn58QNuJNTm28NUCt0WtFZqV0vE98YuqFwZhcI341ovL6ju+xr74HfkyVNb/98oAXt7wN0CQjSDYrZuhSQbB1i8GFsPA9UstbVeRAhI797Q9HAvHHK54ltR14c2bBisDHgJM0y51lRXrVgdIzcW5hEnSGjrzvl7grVoX2wDeA4TjE1m+q/l5V8AA60J9eqB6/alULoMLi7lVG0zQXzc3SGf1UcsLVKxts4me+2mTbDv0zI46MmMHoIv9mlkaeKjLCnwQeWzFcOYMTBmd7W0WWElADmyPxCYu57SAFu2wCj/deAPe84JNZYMXRRjYyEqwQHibbCLE9KuO+6YRVxsCoNmwnjp+mM6MDWFoG1nserQDKudz9E7cC1MnamEOR2hwyqwyK2/QdoEpFDAvN6vMFuzHJ/eEwE9AaxisLY2LN1ZhPg4eVkCCRBjXDDoH3/A+ojHxE525GxdQbjLmH5/Ngg1JNKcIDwhFIPdCR4esH3AZWGm79yFzOQQ1G9oApwGn69IkZf1g+/DuR4wohFgo3uBk5Nk9kzr6UWI4xBFpyXg3044tngxLD+TH2WLJlBkruTYzix7JpjnVjwivaheBvRYXgxCui8kLEx/sIZ6nzLp0rcfmHGPGigfyhB3Jyf5lGM91gR/f2h0aTQAY/cJ09SkUXEwuxMM2wemKvJStCic67MTliyBjjKWGkPiQdzc0BZVsbYGFJFglWj46+flBbdv8/IlhCSXhncelNDKHM+eHbJn+QL8ELXuJyZCPJaQrN8DdOWRPTepi8I/1fi6dmpISIDex9rwKaQMvp2TWL/5/y4F+GWzjaKi4JOJL2+CbPXO1a1bwxzrqcypf0FlHrawMNyNovZm9uwJzyv3xr/mCGrr2UQ8eQIHo2px8E0hfvwQPBM1b86kwY1JhokVaX8RmYy1efYMimwcTp53J/n9d/lr168H9/M7cT/yN7t3C3G67yNdCExyy1RmpbuXKXZEoUyUJ05fvsDhgGIcDi7P27dpBxUK4ywgahjR+RuDWUbLagbG6qhNmrGx8EGRnaeBzrKS9f7+UGDtUAoEnGDOHLUTBpAIa2uokDWACma3yZkm8xAZCQEpPgTH2Mhm0AUFQfcddegeuyKjmCQgzLxKpWyFZm9vSFm+ghSlObt2aZ7zyWpCNt5TKEuoKM+1tobVXa6ymj78NiBF8wToJ8dSqdLq1oTMQoa8iMHSEpS2lj9RCAqWbXOhI1toPKm4/G0yoV2yeqcjcxnF8j1a1pV/4lmB0c9LG25uqn9neI7kVnBjim/q6/gnawR9/gwdrw2g5uPF5MsH5ZOvUH5+S/HbOjhIktMsWaCY2WOKeX6VVTwGcPMSSIapIpXQUMFd+9mzJJ+HL5CsDi4GMzPYeyc756jJ9asGWJX/F+OXJS/z5kHW1+fJvX4Cly9n4gYGum9SUiAlVUFKqkL1bWbSXfXTmikG9lusGAz02svAfGfImVMgII++efI6KQdfvhjXpY0NuNtEkdX0s4aQmSS0d08GarVcuQJNLo2kyZNZHDyodsKAisUZ/arDwDpBb97A2CuNGBs0lJNpiuiHDkH2U2soeHmVbIXm2Fh49sODZ4l5NGtAGkBe8uSBq703cNW1aUbNJxcX8FR+J5fDd9n1LjISNtwuxIakThrv/q5d0M9kDR3XVSMgQLytQgEKUlGYKHQsK3v3m/BemYdH47ZrZFylw9IS+lR9QR/WUr+B2gAN+HuTk2HJsdwsYTB7DmrtFtO18Q0RXxN5MCkpEGqblbefLUTTbKd2ecNMxjGoq9b9bW1liZ4+XLhmxjY6cuS+jzgPMCAg81mYFxeoypGDmjFhc/52YwxzmbZe01rZalgW3AnCql4VyRTsq/u+EYMV4btPS3csRV4MDCL19YUpje+wQjGQHt0MWETt7YW5SyKiduRIKM0tSs9oJmkQio+HnQEVWB7Yil07tcZpRBaPQgHbHhXhXEJl/Rc7OgpWMRGMHQv3Pepzv+9qUbVidaz7y4QfTrmJnzIbNzfhtt6mQXjbRRpVH0+hgKzewrsSFpbJgN//JfhlyUumiEDay33yJDR+MpvaZ8dw4oR8k8GDwfTTB0ynT1GVkDfQAjJxIgTmqkhgv8mUKyckD4wrcoTJWdYJAcdGjDkhAT4levAmwk1vjFytWrA812KWl9tC8eLC+m9llogTIXprf2TPDo3drtPY6w5Zsgh+3KAxi/joWpJJk+TbHjwIxc4tpNjlZezZk3bQCCVkURigVnvsGFivX471nYvMTfcAGJi58+EDzLlbiznBvbh0SdVlOuR4k6kp2JvHYW8SqfFcL/nb8xc9WLwni/yfrbVQTJgAX0s14XXLsZQvLztsUVy+DKsTurPNv6C+WERxKBSZU3A1gLwkJcHQDcUZyhKWr9FU/w2LNOW1dRHuP7XIVFjWoUPgfGwLuS7+zdq1uudHtXrHOGbTs73We2Rnp5+8SFmLAAcH1TGx9e23ub50ZAuD50i7Szv9np3qXKDZmLySZEQd4TFmfMeduARTyaFbWoIVcVhbiS9uFy9Cs9fzqXJkNPv2aZ6r1NQFK2KwbSWfieDoCJO6B9A/dQUV/bTYhpTOC0i+W69ewR1Kc+eDm6RbJTkZ2m2ox6DkxaxYriJ758/DZjqx+Xpug94fd3chJi4dQxVLGFrjoQ5hj4uDu3EFOfPZT1VmJZPw8ABnDzNMgtUm70xmG504lkI49gQu2aX/4v/F+L/r8PpJFCgALV0vYmGrxNu7ov4Gai/K589w5LsgHNL6YyY6N9ACYmcHdsofYBMF5kJ2wcyKxwQ52fLyspyXL8Plr93hblbavRXcKpXXTwVg+BxYsEBP52p/b86cELP0L0EJ6k95h2uDBtCg2B/C7FQ97eMw8O8NCYEHETky/g1w4rYL3+hM8l57upeWblu4MMwouhMiIqlQQXg269fD30G7iV7nzoomSBK+5GSITRYWxIyJz8qKVCApKl4rvFM/fH2hTZ772Hx/R5Ei0mn4ZcpA+LDJgqrdzNcZxxevNGc/f8FWaDNXcNUYDAPcZL6+8Gz0evjzT+zn3Mk4rm4Zy7SCfCbM+02mlOATd3Fu78aZGwY00Frbxo6F1TEPYCHc6yRUxFBHaiqUGVkFuEXhwbb8rZVokplKye/fw+nvzYiIgEo3hSrRYhi2JBuRrMVtkTuz1mmemzwZxp2thVOjijgXmKLTdt95R77SEd+LCUhlkLt5KuGRIDoYFqbyIq2c+JmY/sMxnzgbUGXfZPE1IQdvsc9iT0KCTJ0PGQQHw8Eg4WNq9FrzXHwCxGGFaYIBTCrdd/TtG7i60ne4NY+4CmPzcaWJZsxU5xXl+MYJ3HpasOWA7q1MTMCUpLRG4ntya2uwtkwmJs6Ub19V41u8GA6xGdZD3dnodeEolfBy1wM8WlfG9v4VFKVGQOvl4KgZZPbhA5Ta8BvwG50WCErlOjCGgIhlZ2VC8yVbPktwMf8/H7T7y5KXZs2g2cqZwmRbWp68jBwJu8IewCx7zrU0TuclZ06oYH4b3D2wsfHl6VNYea878d/DaXQI4xUTDSQCZ8/ClK+/wVco+Uozli/TMv3JyUKUmZmRy7mlpUHBvqamYGkSn/ZvgUyMXeTOAzZhsTCZ7jKiV35+4FfgoJABUFYgL1++wJWYkhAj7+a2t4cizgEQF4e7ex4AqnTw4SpJKOorSJLJ0i5eHC60WAr37+PbS6iQWKQI7Gy9R6jJ1EReQ0gMdnaqCUkvidCevAwIFDY3h/zuIaB8DWrEqH9/aH2kK3Z5vcgikh2RPp7NFwtCSl9ynRRJ9bezkyQvqamQlAigRJEEyjRz98M3tnygBO4vpSU/lUrYNvg6LF2K+6h1qE9dmuJr4u3vvHYCSmP2WrcPb2+om/sNTgEPKVq0ueQY1OHvD33u9gVgxllp8rLlpBvB9CLnyQRmaZ3z9QU8IiD+c6Zt4C1bm1Dk4hLcahdDqVTVSqtbMQo4ABXHaly/fr0CDpaCQWPBdXSm+lQne9o/dd6cSSQ+eIppjhyAnvon6um/wKNnSq5TAV7ovtZn7rsQSF18b4m7jfbvBxRmsHotuEtv7BaO/Irl9AlkGTIGvancMshdxhmIgkBpE6W6Dk9oiAGigPqglp7t7w/vY+vCs3xUC9Osf2QQFiwwQOzrfzd+WfICGEwEfvyAgJQsEC7szJs3h+9tBmLx8RVW/U/Jth0+HIYvaiFE6uafzKlTsPxpDQA87xhAXrR9sZnMcnJ1hZYFn2Hx+imlShmmZSEZe2IsebGyEsasx6/cpQt02ddWeMg9j6Q1TVNiTTQ1WlwyPQ7UzCSJhATpV71qVXjQfIpQbKiXsPVPVZiQgimkyPM1Jyeo6vMaXt6BHGonfiJVuksXqHh4LHZVS+Dh0Ua0yfv3MH53cwgtTK2/oUcPtX4zVZNAULfN6vkVFDGS+mWhoTBwdzWgGq3/0iQv16/DgZAxRJ72pHta+qs6goPBvV8PoAeNW6Vy6JBw3NoalCRiZpqMdhpzOkxNoX3FAFi6A6ppKoOWLAkdnE9g526Fm5t4sVOVwJ3uuTx54MTQE0Luaod4dBYZEdePIYTJIMgEvl7/6xnJTZtj+tcRpBba3r2BOcugUCuwF//bdSBDMAEOnLAkhO6YnvGhaz3d8xUqwNcR83HauhyL6e81zm1dHgb7i8PSo4BInrU63NxIQUHo23Cc9ISP2NulEvgDIiJ/jgD0HWAK0zdB9lakP9O+faHuoQHQoSO2tgZY4UFIlVYoBDM8iE5Mjo7Qr85bnE7toFCTQWiLPm3dChdC58Lh/Pzeg4y6RWIID4fTUfX4+vQTeU4ILvZVoX/DTrg/VohTNApdjVDt/F+KX5u8WFpKBlOpw9ERvBVfwc4WpdIOKyuwckiE5DCjn6Ax9YkePYKXkXXgZWGqBquVFjAg/qN9eyi5eSjkz0fx4v1xd4c93Y7CtGnQTZ68rFsHC+5tgcfmLO0gyNloxJ4Yoc+dkAAzjpUhjtlkW5rEgCHGEZ9hg5II7jYEq37dSEkpI6nVIoaBA+G3M80wU6ZCy4P6G6hNQH5+CuJu3MYybzYSE92N5ms/kypdsybU9DoM2eLAUZy8hIbC9seFgcI43hHIy6tXsOlZB6KDoqhzQkjxN6ZfQO/CJocHD2DuZ6FKZJknuuRFCg/P/0Dp6w3rDwMyioASaNsW2q6ZJ7gh/HQXcIUCkvYchBYt4GgwouWrnZwElhoTg3bwgmvbGiQQTrGWFly6KRwrUADWNjyA3Y3TFOr0p+TYLv35mOSOnTFffQAQSdd3dkYzWluFbF4JwDvw0ZMb6+qqa1qUibXRF5c0ZbE9/vyN+dIUus7XPW9pCZ7ZLDSk/XVgwC6j+3BHNpNAcg8lH2vBlcNh4OkB+/YDTTWuvXQgFIti+bHdug1RUiT396rDNc1Vpva8GjQAWAnVS4C1geTF3FwIRPn0SfJbMjODlWPew6kJULMN2uTl6lVYF9MB7sGAH/Lk5csXaH20GwCdtqpi1H9l/LIBu4DBlpdFi+CzY0E+T1hJ7vT5J5Op0sWLw61uK3jgVY8RI+SbbdoErb4uo9WhLjx/LixOPotG4PrlAQMHyrfNlw8a21+kcfbHGdZZY2JPnsdm53m4d0ZQ35ITeZnGREGgSgYHD0LduzOpe2kC584Jc8nUA0WZyxh27NTbtQ7adDRjACvpXvapfuKiNYmYm4OZrUWm0lnX/GXKbcpweeRByTI9GhATfIuJkfVpf/oEs25UY1ZIX91q3XZ2Rm/p37+H6Q8asyiwvayAZkwMnH3ly9mkKjx9aly/Li6wqfNpNil76LyD6jEzYvzHzAwq5/lKZS5RQK30ktLh5+oEAZkLFFZHui9EJFUlIkZJJPZEx6r69fSEXlVe0jZ5m6z13S97LIV4Qt7suu6O8HA4E12O3e/kqzzrhZsb2mlS336Y8hVPgn6IfK8/QVAz4OwszH+GEHQJWFkpSE7b/QUGCuEqJqRiYqrQ+Yk9ctvhSDjKqLCfGDTCS+jk9NPp0h8/wk7r7igm/4EiJZncv7cTN3j+AxW4QfAYpSPwSzLNmsFsuxnMrnVG49yvhF+WvNy4AdXPTqDCvWWsX5+JG2TSfWNnB6VzBFMk9YGkpLgUTEzgS4QdP1JdDDEY6SJ9zHqCxMzNwd40CnuzmIz6IpM352YS01i+QZ7yBwTAqZBSnAoqytevQqyCiYnQX2yMAcFp2r4hpVL4T0/MzJ494LD3LxwuHWLlSrUTBmQbZfSrDoXCIIIaFQWPf3jxOC53xgY6Lg6qLGhKqdRb9OwmHTDz4QOMv1Sf8SEjOX5c66QeElGgALwZvIQ3HhWYKsRhG5zl9OkT1FrThlrRhzT0ZaKi4HpUYU59KcSTJ+JtbWygc+nndFZup6qWkaNmTTjfYB53C3SmY0fdto6OcGn0US5Rldlz1H7jdHYoM+jUVAiJMicEJ/F119BAYamducwi45c1igI8Iaev1m+Z/htlMuvj2TOofXgIbd7PY+NGkQsMvW+a5UX98tId8+DNV4p11hQBuX0bRn4dTt+L7TOy47Tx+6Bw1tCbFQO1ma1Wn6Bbs8yIZ5EvHxS3fk6DrA8Fy6ZcW2trYR6Q0Ew5fBiWMoilZwroDa+LdcnCxzeJqmwrQ602ajhzBtq9nZnx/998dxDP9koPfBF5ryZOhEduNXg0YCX588v35+AAc3q9ZANdmdIvkLp1YYztn4ypfM3odeTfgl/WbRQeDhe+Cm9M7fcGNkp7uUND4fSbksT9SCb3NcEHLIX16+F0yHLYm4sZXYVifIZaQBo1Ao8Ns6FgIbJnb4SpKWRxjMIiLBA3NwMUY9XGDKjywxMSNHPFtTB0KAzdXTfNfPM3IFSpDYuCOCP5mkIBJ2fdx3zMUJxmbQUkygYjuMlOvm4GqanUeaimEGtAanliIkQkCoughhSEAbEn/v6w4koXCAuj+XGon17WxwBV4Rs3oPY2oRrgxOWCV87MDC6/cAfcMX+WubrzSTYORIakYhYlbiK2sICcTqGg/Ahp60iBAnCqyxasj+wi67BDRvf5+DFU2CuYAwetli+SKAZPT/DMHwhv74h6ZiShVAqMWYZkxsWBS6/mQHOqd0ji3EWtC37SmjBwWT4ecZHE9tm5rkXcHvx5VfAtrP6EhsqznZ0QxB4XJ52iIrMwagR0imzMz962J4F6WN22oZqEWrK/P7TcP5/vERb0GgELF0r+iQA8fw4L3gvV3Qs/hCpVdK9pUT8WWAf1W6OjCpyGM29yEEA3YlfAALVI5OlL7PjAGkyXF2SVeHmsDAwZAkPOjhaEdoodgXTLhRiJUCgE9ithwVizFo6wFHZAh2XSP8fChTDi9UN4DbvrQCv5QveS0C6y6Gobi0Ih0qkMKfb2Bm+zF+DxXW99PYUCRg9JgHWbwKcv4JP5woz/Evyylhf12BNDKomqvygfP0Lb/e3o+mOh+I5JDbdvw/bYZmx/XFhlLTFQ56VqVRjp9Dcjy1wiSxbBdBgwfyevycPihfKpiOHhEBDvTkCkI3FxwuJefU49KnCVPn0N2GFofRh/TfvKERqyddJL2Wa9e0NY1aaENe9O69bCsVqV4qjCZQr7yi8ut27BqKfdGfWsB7duqQ3F0orYiESNWkfasLeH/HafyW/9IWO++P4d1rysxqLPbTgto7f14QOsfVmVtd+a8uCB2olMKhKbmoKleTImJCM3aD8/ONh8Awe9+tG9u+r4/v1gdnAPzmd3s2KFns7UJnpHR6hdJIiKSRdl/efOzjChxnUmWMyncWPV8X8kCFWfBURkwr14ERabjmDG4SKZijV+9gwqHhhFkWc7M6xQ6khJgSWHc7KEwew+KB68dPe5LZepwo2n9rLvmToSLO0JxoWvr6XJ8dWHdlykCrce6kZAe3rCuAb+zGUUnTvodtpxUk4acJzuk6QJv6UlvA13ITLVVsNzVK9CJM3ZR/0KmpaKfyrQePiy7PRgPcMXeGv8pPtPWLKO3vx9ysASymoZNHuPWLCSfqw8plv35Plz2K7sxIrzfnwUk6cwcB1Xz5RK9xw1bpImvNirp8HepEKFYG7982yz7sUz/Pi+cIuoBWTYJDuy8hHbri3EBT6NISDp/iF1EaZMpEr/W/DLWl4qVoTokX9gsWcrprNey167Zw/cj50IJyowtJtxQbfaSEyE+1+zEh9XGvsHQt0Oo5DeeXy8rCDBggUw7dlJeAanOgnCcxeeCtaAlEfGWwPq10kGjkE++UAdCwuwUEaDuZWqDt1PCM0NHQpLgr/BZLjVQDoItGFDaNhghOD773IGENwjfU8Jwcl996K3HIM6du+GY1HLiN2RhyltBSOUGLy9oVeBaxD4lZIlVYHQYSduYl6jIootTwE/0bbOztAk91N4fA7U4ibU3T9GLzDpliaZ1CxXV5he7wrcnwWtRmYc9/CAIdX8sbt0jFLNxItQpaRAdKwSsEMZK/IK2tsbXatn9274M3YmnIK6H1UZtOowMYEGxb6A/32KlNL8IVNS4NpnYcEr9V58zEPXFwWWUHF1Eq27617j7C4EVFmaJRERodRY5KSsJ86dGxBNMAVbJvBYgtM3GetHCBfJMyael201z9nbw8yeb+HYfCgzFuPMVQLc3MDFNg63qHe4u+YlvTjj6okBsLclTLoNqLT4K1aES62WYn//Iln67DW6v3S4upvCcyELMDr6JwJI1cjL3OXW3GIlrIL+KzUv27MHfg9cBIGQ9YFucOvIEal0ONoB+vTFzq6aZHc5c0Jlz5e4xX3C11fI+lQnPoZyAW9vGNXxCxz/S/a68AgFn8gK8YLxxSjNJm04Owtm3UwpSP778MtaXpRKsLY1wTRBv/7I4cMwM34EM8+VJzRUmOQXNrvEn2ZD6dZNvu3UqfDGvTxvhiylQAFhMSo7pwVVUi8ybqyBFYvFXD9GxtsoFGCuFPpLSjSQ7WunaEPmlG4NlPivUQP2lJzFnpKzqFlTOKae5WNs14bGgFSrBg+aTuJBkc4ZKcf37sGGqFbsfFZUtiRCgQKwtvo21maZSrNmquMWTtZCwq0hwcJaM6anJ1TweU9dq4uSpe7Dw+H4y1wcj62mGZ9iba3S4zESLi6wuNsDpqVMoGk98ffr40ewH9Mf+7hvqvTsNKSkwItYX25EF+LODd0MmfBwaLemBu3Yzny1LBb1gGipx2VhAUfHXOIojZg1RdNUmm5NsCIm0xvR7TtMiLV2IXb2Uk3iIgNba+E7ivjZVGkQdSuM6viVKUxiaCeRmgVpcHGB4G2neUYB5o/WbzZwdYXK+b9TNOG2ZB3HxIRUElGSmCy9PAwcZMIK5WB2dT+eERcHsPPPHzyiEPeWXdM7FkAgL0FBGhZKdfXadKjrmIjF+1WtCu3ZQfuyb+U84lStCpd6bGSvfXcaNhSO5csH5bhOuZzfNP4WvVD3HUm8eJ6e4Gn6DT+XIB3l35cv4WJ8OS6+z2ZYlQmFgjiPbLx/HkePHmAb9Brb6WN49MiIMf+L8MtaXoBMuwUcHWFYvWdwcClUW4Sc+JCrK7gqP4JzGFig8QLHx6ZgNH80kLwULAitHU6BmyseHkKt9bAjV7CoVw2TvS+APJJtr12DC5+6QIIbrV5C3rwYTEDEEBBqSzgFiX9oRslK0tflyAE5vK+n/R/VsXLWD7B0ssLGJq9R/Xp7w1+dzmO9dS25Bm1F6ndycIAizp/g+9uMAtLq1rXMSM5nrMj6goVFzMZFisDVAduENLdu4gvS69fQYHtnoDMDV8Ly5cKtXkd4EEMRTG/HUqiiTNETKXO1ugy73CoggpQUyD+hJdCS8oMTuXZL83xcHOy8kwvIRdwVQfwRhLT+ErvHYp3Pl4IFBxjVJwhrSOKGrSi7dYLlMWgHEJiYwPahN2HxIlzHrEU7ZRWEdwAXG1ESMWhlAVJYju+ftoyZoTpevVws4cdO41WiBOCp0w5gSKsvxPy9HZfWPRCtTi5DXkZ0DIRl06BzGzTUBLWRrlT7/buwWuqDnsysUo29eEgiVs2TiZGYHlu2UsCw/ZDVCSxVwS25cyQDTyCHftKemgq/HazDp5R9OHeM548RcQR3GgpDhwGaMslVqsCiYhtxTPhGhQqjxG9mKLSKM86flwoLK8CEv8Cxh0xDLWgHvohg5kyYeaaRYGIvqll7YuFCWB2yD9aD/xD9Vvh582D0p1fwp2CdjE61gYRfN/TFaMvLpUuXaNy4Md7e3igUCg4cOKBxPjU1lUmTJuHl5YWVlRW1atXi1atX/9R4/1kYGDg7ZgyctWnC2b47Ve+rpWWaZKgB9cnV3i5LSxjU4DUjmUe7pvLEaexYsHrzCKuF07metqb/sasAw1jIjPny1bjatoVd2Uaxq976jMBXK3szTEjVS9guXoQJAf2YcLclz54Jx0JjLfmAL8/fmMn+yc+fw5avNdnyoTLv3wvHWv3mQWEeU2pgWaM/tAED4HqRfpyvO4cSJfRcrHVzW1voUTuAdqnbKV3MOEtE//7wrHgH3rUcSY0aBjQQS5UGWctLfDwERDgQkOipu5vMRKq0QgEFhtamGA/o2l9PBKAU0vOdJfq2tITa+T5S2+QMhQtrnlMqwc5aeDlCfxj+QxcvDu2yXKWJ+42MJBZZaD1rhQKULmlqriLbchMTaFfpE+3YSa1qMi+vhGDcymO+rGAge45qxq1sXxPJMRry18B7Om3SMal7ALMZx6ieEtUC08hL4nfdcRuM9IemHvQil0GTHtz8s6ueq6tOirYxUChg700fDtGUMxeUNKiZQBc206XGZ51rixSBoWWu0c16l6Q1MuOm+uDmJuxI0r/NzD4HHx/W0ZP2bGP8/lLSn7qTk2gKvrFQD/A2MYFCymcUcv9m7B7jXwOjyUt0dDRFixblzz/FhZnmzp3L0qVLWbVqFTdv3sTGxoa6desSl9nCev8hxMbC+ntFWBXblSNH5K8tUABqKC9RI3eAysSdSfeNqSksHfCCeYymd1v5ANbERIhLtSQuySzj+1pyIBuLGcbmvSJle8UgppKbid+iaz9LsvMBvzFNdLIj1XHyJHR+Oo7ONwZyI61OjaWV6jXT+7jEYjUMSHe+fRt+u9ed314M4qJ6JooBJCKjXzW4u0N+529kNw3QW4xSDEev2LOUQczemkXSg3PrFviumYjvu4vMnKl10s5OeFgSjb28YErVc0yxX5AmsiXAxkpwDUbLmKFfvwbv6QPwDnvK0KEi/YIkefH0hFP993PKsinjRcJiejQLZTBL6NlIV8DM1RXez9zGe7KzZo3WSUMUieUWmXS/gj4NAbnFTUbtVhR6npUhaDPUG1siMW9YW9fCZ+iiqm55SUO7sdmpyRnajsuhcWlqKjwKy8q1lLLcviL+MZYoFE9lLlGxQJh8vy4uuuTFSCKQHoP6PcRU1VTqN5LJNoqMhBCcCIky11+gUqssQQaM9DkOHGFJb9axg/bMOlZMeoqSeK/q1oUxNssYU/lqxk8oh9y5oZLna1o5nOavv+CRS3UeDVojGY/3b4fRbqP69etTv3590XOpqaksXryYiRMn0rSpoJC4adMmPDw8OHDgAO3atfu50f6DiI6GHptrADVosCKVRo0MeHG1Yk9SgcSIOMxlotUeP4aAuOrwKjcVI9Ks8gbGj3h7Q1Hzp+DoiLW1YDa2NE8hHONTlgGDXT+tWkGhjaPA15fSZQelNVX97cZynwYNIM+1dVjWrERqqrSgQUwMRMY7gkKBvXowqLW13oXt5Uv487UgKZv/ESoNEnUNEYlghuBgeBaUByKsyB4gyORntNXzrK5fhwE7x0DUb/RZKVhsAJb9ZcNJlsJW6Lc8E7VH1BdG9S1XGry9YVKVC/B2AzRQBVF3bvCDxF378anXBClXQ1ISfI20BWx1YmvrDC/II75gVtuZjzICqlJYPCMatg2FRgXQTos3NYVszpGg+KjrQdFDXuLioMWcqsBRik02Y+Y8rQsMJS8S+PgRzka0JDTIkspapQ1uLbwKQ4dgtfQk6sGvGVGqcuRFj4ZIIkqi00oihIZKxODrWVT3nrbnsskSgucXY2E1YW2++sCGT9TE54FmfFBqKhQd34BUGlJmSAI3RYxG6+f9gD1VYe5poJZkvykuboR9jcUkTPX47z40I4oqmDx2orJ8YWkAdu8C64LeuP85AwVyktAI36/E79uugwnHCIHB8KOj6CeTgSHri/GUU6S0duLsbf1jlIJBVkIQxv3ihc7h5s2hud1MqDMQDCgOXLUqXO6/DVauhAZff11/URr+0ZiXd+/eERgYSK1aqhfewcGBsmXLcv36dVHyEh8fT7zadjziZ5UfDYS6qU2IPdEj36r1oti0b0wMqZSol8Ddh9LNli+H1aFbYQv4j0zzaxpotRkxAkasbCKwiWJCobz9iz5A1y7Yzl+LlAaD1JgPX3HiE/1I2O7OEBF9h3TkyQN5HC+Db6EMV3758sD+fVgVyYOlZWHJttWqwfI8S8DenpIlhbSOMeNN4fc+0HolWEmTl61boc9pofTqX9vV6vVYW2faPB1vZks0TiR8iMdTwkV9+TK0OC6YEeZsh9Hp9eoM6DcyEvyDhUU6MFB13NpWteBER4uTF1dXaJ33AXz9QpEimhuCHmvKEcxB3AeYsW6HzAC0FrZlk0NgV3/oWBgp8qJUgq9jOERE4OKiSTC+h5sTiBdmIQYEk4shnSDKkQitMSclQYSpGzEhqdiEinPM5GQ4/sAb8Cbhjm5a8aHbXrxiOOHL3JhSTrOL1FQIjVACTigjwN5R9/737kGP+wJRn3lGk7yUyBUO3Ie8Wv2amAik6ycsLzlzKvAzfYGTjw1JSZovaL62RQkmmOxtrLkrIRoIcPqMgtUpg+E2jPgsnq2lPmQ762QiopVEGJcUpoFz56D27q2kpJowcYGgbwTQa4wz/lzEYlwycXoUxAFyFzAH10T49oXoGAUp2EKsUiQqCVIdHIkLjSM+NBVHJ21Cl4qhhQ+vP3PgNrUxuZdKcjIsWqDAn82wpjyrWhueOVWwINiYxmKRHMPgJh9wcND1awcGwopHrQl9U5Yym6FzZ+1hG0lAPD2F2mXpAc6/cKr0P5ptFJg2e3toJbx7eHhknNPGrFmzcHBwyPgva9asotf907C2hlV97rGBrowbIu+S+PwZniXn5VmQc4YmTPo7E58Zb1gmXU4A5cskU54bFM4aJnvdunVQ9e3fVN07OEN6fOZKJwawkqGr8us3rWph6FDY6fobG5rsl1V0LFoUBmY5yMC8p8mTHhOsUAhbyky4qx48gC53BtPq/gR275a+rl49uFNrDHfKDqSNWjmgnB3K4kIIpVsa916FhsL58BIc/VyM58+lrzMxAQvTRCwU8RrlCwYNUrDFqhf7ux2UzF7x84NdjTezy3sYnTppnjt8y53DNOHcFRmHttjEZ4Babe7c8GHsKj44FdfI+gHw8VGQlY/k8YyUTliSq5BpZyecM8L9cvo0uOxeRdbb+1iyxOBmGli8wZGRLGDa9tw65vvERHDp0RQXQmjcXnxlUt+py7lF1bFuHTRMOkCVJS3ENtYAFOpagqx8pFpn8fdvwQJ4mqMRV9su1Un/DY1QEoILYRHyGyt1l0O6J+TlvidEY83Lfbqsp3fzHwxjIb2aZMK0lgZHR0hJFZYPDX6fGWNAWrp0tZbO2BOJU1tdTYO4OLAc3BvrlCiaN9Ulr6VLQQOO0qBIgN46ZJ5ZhAvMTJL58QPOX4CtdGLrjVyGaX6loU0biOo1jB+48kdTf8xFwhDDw2Ha1Rosj+zGKfkavobBy0uIjM9k8dV/E/6/p0qPGzeO8PDwjP8CAgL+R/o1NYW+jb/QlU3ULCfvkhg7FgpE36bAvO4ZAkml8kdTlhsUzSvvVmjcGKbYzmVKjYsZi36tQX5k5x2FWxqQPSNWVRr0EoH37+FSdCkufcmdsQm2tDbS9aO9QBmgOCsJS0u9bbNlg6Ye12nqeTNjIv/2DTa/qcDekOqyKYEuLlDS6R0l7V9p7Dyt08zwMbHSO5Q8eWBUwWOM8tlGmTLCsdu3ocaJ0TR6Pp9t26T7rVUL4voMIa5oOSZNUh2vXh06OhylWY4H8rWRJIiArY2wCkRGG7mzSo/xyWTNmSNHFXwkG0+m7BVdBAIDoelfjWkat4MFC0RuYGIipO6IWF7i4uDIQ1+OpDbkzh3VcfWaSFJGDGtrCFmzmxCc2L9Dl/Q7uaqmssyUkcmfH/5scpKdNj10UsCldsfPn8Ox+Fpc/pBNci35/N2cT2QlMFiGgEjEROTwjiM3r8jmLb+idu8OV0sO4kWDYRmKuVYWKVgTi7WV7tjnT45iISMY0VgikcIAa4CHB5TyDaKe4iR++VXXd2sdzWjmMKLVB733yICa1osULCzI+E7CRKyCkyelcJRGHB12VuN9EsOatQpC3fMRO3GmrJXKIKRncEiQefWNS2iIxHM1xnqSFiS0eV08/SLm0u9g/YzC1r8a/lG3kWdaml5QUBBeatWigoKCKCZRs9vCwgKL/1/h0j+hXXJh3WsoVR6m3UM7rU8dDRtCQ5uFUP038BQCMT5/N+MD2bEPMiBTSRs/YbUZNUpBt8tdsezXHTOzapLXhYdDeJw7RDnjph57YgAByYAY8dHznOvUgTqlZgh+jVoHAMM0QORQpVwCeT6ewbFEcUC8glmhQjC31C548waqddDpN9O15wytqySCS7u/YV6hJHYbtyIWd3D/PtRaMA7ih9N7LMyerdYnZD74VakUfisJFhETA4ceC+nOtiLxEosWwZro24RNdedgNTLIIAjrc+MV9YH6NJ8J+/YJxz09oW7u19gFPKNIkca6N0V4nZxsEoEwsUxnBg9W0PZ0Lxxb1sTZub1O2wbFv8L9exQqXQuxac/dHQY0DoDDGyDvGo1rrj93Asph+9yMwmqZyIaQLm/XBGyigvBwlQnCkCAvN9c9FmqPrH8CFJBsnjMn5MwTLOilaAeXiy2Melx7o2Y58ZEdWM4tyEaJkBcfH7g957yQ594jgvQfZUiPSJgyFrqXAHJKjjkdoaFwNakuX/0TSLJSUJtTmBQvjkZsUdqfUbFIJCl375PPrzA6gn5GuF88PQFvawgSvAHrVqcQ45sH5szFwaGlfGNtpJMXie/c2RlOTLyC0/TheM06CajYzNixsO37HZhnx8kWgiVWH/7YmpdrnOLMpOxAdrgNv4UKv8evhn/U8pIjRw48PT05q1YiNyIigps3b1K+fPl/sqt/BgYSgSpVoLtyM91LP1ZNWD9BItxcU/EgEA9H+bY7d0Kf7zPoc7w5b98Kx94FWnGP4lx/aCPr+pk8GeILFCd+4HCqVxeONWhsSlflNtoWfiprWl2+HLI9OES2HXM0qx0b6vrRmkiWLoUS30/it2yAxo7bEBQvDi9+W0aARymmTDGgX63J+q8V8RyjIdsG3zBqzNmywdiKl5lqN496euIIAfFFwpAMGglkzWeNB9+wThKPAUtKgpBYa0JSnDTmzTF/WFKEB+Qa2jjzluVMpGmnIzwcnifmJjDa3mD3S+7ccGLAYXabtqNrVwMaiDzrqlWhjecl6rjd17F0mZnB0XFXOEoj5kyReX/d3NIqQGqmtVYYXYkKXKf3CE3WNGwYfCvflNi23ZDIYeDJxrt8IisXt3yS7lcqy8mYeAgPDzIqg+pDupaPBHk5cdGaXbRl72U9KTByKdoG4tkzaHxuOH3ejqVymXhOUZcT08QniXNbA7lAdVYPkgkAMtSK4emZYe3x8kwlF2/J5RGlv3K9Fr5a5+INOXnzKEa0rIRSCXWrJ1CG22S11vwgQkIgICULAeEOBiluANx5YcsZjJAK/xfDaPISFRWFv78//v7+gBCk6+/vz8ePH1EoFAwdOpTp06dz6NAhHj16RJcuXfD29qaZuvzo/xIkmVoQjTVh3+U1QHr3hr+tBvJ3u1OqeI908mKo1Ubto7p0KJxAvHi54qxMA6Ho39rIdqx9UCZjIeo93I6S3KPC+Gqym3qlEsxNkjBXpmCi/itnUphv926o8modpfeMlq0TtGgRKC6cR7FtKzt3CseCguB+QkGeh7jrTwbRIiDW1pDXN44s8W9kA+m+f4cbP/JwIyy/RuCsITEgYsiaFWY1uc7vpjOpJZ1wIYnkZAi3cOdzkFJSPfPBA6i2qz/VPm5k9Wqtk3rScC0sII9zMHmUbzViHgI+KXhEEd4G20v2GxQEo49XY3TMH+JxRDLkJVs2CJqyiiDrHKJ1l5ychIrkvtbfddYxW1uY3uQW0xW/06GDSJ8xMbK1oPQujI6OP5cqLbYYy8DeHtxcUrCMCcl03OSrVzDoSV863R/B1q2ZuwcgLMZqL/7Ok45soCu7TzvqXqtUCs87M/41dRj5vMSgZqAn8HvaRKWv8ncmM8p0OpaIwzQG3m0rk5s35F49SnpYEpWlHR3B2+Qr3naRBiv7Zsmqmsw32/bn/sB18ro3/2IY7Ta6c+cO1dO38sDw4cMB6Nq1Kxs2bGD06NFER0fTp08fwsLCqFSpEidOnMAyM2IZ/2HkblWMD0Tj2SyBr4Z8f2KxJ5mwvPyM1cZCSzPF6JoiBsSt+PlBG+fT4OiIl5eQdhEUBJcjimX82xCkPy4rKzBXJGCpTCYlJRPiadbWet0vJ05Al/OCWMqf+wRxO0D4nRQKw9w32pOmAf2+ewf7/GtAUG4qXE/LygJWrYLfbp+G27CxEXTpots2LAwufhKqg5d7p3XSzEx4TyRIRJEi8LL/YiFF63dVY2trQSbf2hoSEsSDbX78gHmXygHl6HGCjAKaIGReHY2cQOTRnPTpoKv6aWoK7naxYBIMDrr3HjIEhlzsIrxjDY5rnLOzgwn17sKx2dBqGjonQSCZ6tUD05CYCHuuZQPa4XnRhOpi1jAZHRBDkOLsSjiO/PCPIreal2ZYkzdw6CC+zXqjKtilNm65eA09qdI/fsDyx8J86nwTOnYUuUgPM0pNhWfJ+QgMKYriZALV65ozbFFWvrIB30UJtB6tef3cubAu1p/QSR4crwqlSmmeP7XxK4nlK8Pf2wGZFN508iJWzdBANuflBX+0eoLXnqUUajMG5DS3HKSFCCdNNuEOR2FhEXa1lJ8XIyPhRGgtvr7MRs4j0MiAlG4pKJWpJCUJf6tYwC5ARh0GLVPk3Lkwd2Mx4aPxE68lpo3p02H2nVo4Fs2G4vAh8PHVW5H63wqjyUu1atVIldkBKRQKpk6dylSx8q7/y5BhPIk34EPT+ptnrXLiKZuIn1aInXWkv9Vhw2DTt6cww5JLzYT0OkNjbUaNgh6760O9euQqMgSABg0VZDuxEovqFTEzK2LUmFNSINbCmdgfCuwTpD+2Fi2gxewJUKwYlBTIS/qQFaSQkCBtsPPygnJ2T8DCHGdnId1owgSYeKqWsG2vs1my7dGjsPjmdDBRMPKkIOIECO6XhATBV2JU8RGEH0aP++b4cei3dwEkJTF+NfTtm3ZCYACy/b54ASOvtwJg8ikVeVGfPDPjgXnyBJ6btyfyQnYatTNcU2LtWlh3tiB06AD5Z+hvoIVbt2DOt+7wDaq+yEThUBB2yHIFocSgbmkSIS9xcdBhRSWgErXnJ+uQl+RkCLf2IexLEnbf0RX9MsCdUbVHTq4QCh0hobWqrtbCnk/g0Ajo2wmdgBs7O0FkKJNQz3LSFmGdsNqXaBbhtsqFCTJZWKmpUGxyUxJpTrERCdzXsxhHRMCrpJyQJM71vNyTgQDwkN9cLdrmzkX2831IKY5VFLhF3c7uPOMDVt1deGFA7oWlJUweHAJ71oBnK/mLLSyEnZDIoG/fUXCCBvBQv+j5jx/Q5oBg+mu9KRUvVwimDjzypkYierOVNPq9rWDsqGQaNzXBzk58EQhKcuEzxQk+b0bV6lpVN4x0s7m5ATkc4dP/TGLL/2b8f882+v+J8iUTqMkZqhc1frd24oIlW+jM7qs+sul10dEQkupMSKy1KkYlnTXosbx4e0Nh8xcUdg/K8H4MHAgrrEexqPE5sTk+A7dvw9qQlqx9XC5jHRk3Dmw/Pcdt0fgM9VtD0bUrxLfsQHLNurrZGGpo1w6ulxjI9bpTMtwtCgUGxct8+gRnfhTnzPdiGZvZ1FQ48zo7h2jMuePSz8vPD4bmPsLQbPsyyiEArFkDjRL2UX1Zc6SqVMTEwMdoVz7Ge2oSjfSHnokMq+zZobbXY1o4XyB7dvFrKleGuEGjiMtXlOnTNc+tXQutItfTfW8jyXGLTXwKBXotRtmywaXem7nk0JgxYzTPqQehShaLk0uVBsPcN1rotLgU1TlHy+4yL7UMTpwAl4PryXVtM6tWaZ5LSIAGsyrTgKOMnSydHODspiKomum/4taTkBDY9aUSf32qy+XL4vecujEb45nB4g2OouezZYPrvx/jFblZsUjz/V590IMlDGXDAfG26TAxAQ8XYcVO94TM+e0Tq+jLzEG6ViFnZ3BURpLD9ttP6Zzd9jfnIM249to9w/jy9ZspAfgS8N0IS3tatOnw+V40Yz+tZhQTvWzbNmiXup26yxpKpqYbAnWph68ByUz8w5R6nKTegtpGh6gVKwYnTpsy8Dfp72HoeGtKco+6c2v+M5lBWbPC/1BW7v9m/NKFGTcsi4S9tWHcEaCh5HUTJ8LxmEuw0JuDrYUAc3X3TVycdA07d3fIY/oGHB0xNxfMh/sOmHDfZAbxO0swrqWk8KsAsYXCgJpM+/fDrK9T4CuceyEQIaOLDar1a2YG2JhB4H8uVVoKdWZWJZVqlJ6UwC3xZBRKlYJSRTcIK26lFhnHnz6Fowm14Z2wIGVoz2gNzcsqFJKTsbERTBypqZBtUBOiCaZQHQsuXhfvt1gx2F17Dbx+TYHWczOOV60KVVuuhkuXoOED0baCRkwSmCbpfImGZLJIQo+lycYGKuf4BOY3QStbv2FDOFd9GnYRn8nZbJVO26goOPEgDyQ2xfeWZjZRBuTIiwTxufTIkQCq43VffCdgYQFLOt2GLZvJ2ns+2qKSclWHU1LguL8X4EXsHelteanSCuJOnMetgBt6BSCBDx+g7RFBdazvVoGMamPBrixEMB6/nfEMFTGEWVhAuXIAbyDxB7IFGGXQs1MCcQsW4t2iEVCIzg1+wOQ10HAAkE3j2uHDYfjFTsKDqXNY92YGMhp169aPH0LgtbtrMt4vPmPp7ATIaQSoIY28XHjkwn0KYX5TPBPh0SPYGdcU3gjaW+qy+Lu2JZHo6gl/rsDeXl7J3coKFv72Btflk8k5aDrTN/5ntcXUrabBwUJ2mAaMDZjKmpVXH8z5ZlYaPvhQPAZ5OYZ/KX5p8mKo++bdO7iXUhw+kWFlWbtOQUKOPFjOmYqdXXvJttOnw/Q15QWVt3yCX3PfPtiaMh7OQJ8fesiL1LgzES+TOzfUsL+Dlb0ZTk56/AFiE5gxQnNiqdJivnE19OgBHfe2AEtLLDpuy7iNtUUy0XFKYjKRuGNIynPDhvCl1RBhNep/MaPf4EgLYrEmNFTatObpCa1y3oMft3WzWX8ia6duXbDbvAI7Txvy59dNwXn/HhafbgAhuam6X5Aaz4ABsTpSC5SPD/jkDhBysUWyewMDofWmxkBjOi2DzVpewOhoWHa7JmHBluRcA336qM59+QIFR/aAxPY06QobN6rO2dkK45HS4zE3h8F1X8CWZdBMuzaA4K6sn/cNju/9KVbMyHTXNPz+O7BtANSoD14L9V5vHME0MFDYW0VeTi54QlKvvlgs3kFGmXUJTJ5tCQvHQ2kXDCFeODqSkcKohQs3LImiIcrbLtSTKUo6fjyMudwIt8KemJVdB8CZLUFCKfjNZ4Ca+scBYGFBsrsXn0Pl67XJEVThtwgF2wSD/AnDBqfA8i3g1YOO7X0oe2oqNGuOhUVm/KTyqFIFEnfsxTWrFe7uqkJk+/bBnajxcLIMQ3ogK/6pjn1fytEydjjEAqvhyWCh/t6vhl+bvBgYOGtqCkoSha1y2o4vW3YFmH8E6x9GO9/UrTRyXOD1a/gSVwY+Zqd4JJpp2npIRIsWkHvDRChUkHz5BHLVuTN0Xj9a+ErKbJdsu2kT/PV8NXy2ZXY3VRyHwSJ1Wgvju3dw4G1T4oLCqXRZfIcKgnXHTBknvJVqfufxXb/A6lV4dR4AyJShF9nVjx0Lw0/UwaZILixrrDR4zAC5fOKIe/uFrO6e6ARqakNs92Rrm2nyUqkSVPI7LBARX13yEhgIS25XBCrCRRV5efoUjgV1JibImgZ3dIMxDcJPkK7kZBh3uAJQgdq7kunTR2UhSUmBsFhLwFKHW10+HI6lX3astmwHmhrdb86ccGzoKRg0CDolok4WLCwgZN0+6NUT0x0BgEw0p1al5NRUyNOvJvCK4j3t2X1IdamHB8xvdQO7PX+Tv/cqxCaCwzMekTx0ONazN6Fd60mjT9Ah9yXzRQG3wM+AjYpSKZhC0qPp9QQKywU3D5zsxlOOYDc1iYgxopcAaYutrxK+q8U3ZcIPtXgxjPr+kaRUJWvoTZPNHYFqOtf16gVtT/bAySoOu2ZaypH6/l5tpGmSERhIp/bJ0H0KtMgFVv88eWndGlr/tVYweWZXkZdjx+Cv2KFwEToGG05e+v5VWv9FvwD+S15AL3nZtAk27XOCGTMg5xDVCWMsIGof1dCh0PZgBywb1SJHDukAkmXLYGngTtgCNwcJJvply2D155PErXBiS5N0k7MuSpWCUk77oVAMeKtZhgwgIB8+wKWoEhClmt+Cg+HAi0rEBjpQ8BzUkNiRHT8O255PgABrBqW5FV68gOG3hTFMPidNXgBRAjJ+YDisngV1myFLXkRgbw84JkFCuKGlTzLwaO8rQWhmwS0gExOGnZ1M4IhgiTj2uCyE2VNUqxggIJAf7cqJenDvHox63hMAl5vi5CUuDl4GukFyQZw/qXS2NMYtQV5cXGB+owtw+jR+7XX9ILa2YGKSSkqKgtDgZNTdO0ol5PMIhaBveHtrlsJ19rUFYuXLYRuSKp2cLJh/1CKmFQpwsk0TuNMXUuPmppP6+ybQFsiNe6CmpIKdHYxo+R72rIWSCxBTz6tSNBy4AMWk54nX4W58oAbfD1nRorJM1oo+qKVLC0GrpqDrkRQgG5dkpL6MmHiTEa4QBwdIShVGmYA5Hk7ilk4XF3DxToBPX34+WtPOTiAT/0C6tEFwdf3H4lSyZkklOEz499CKt3F2/jXJzC8dsLtoqSkt2EeDBTUzJ1VgQOyJGAoXhjqOt6ji8SJDENVQBAfDk4Q8vAl3NXZdE5BJif/Pn6H38ZYMDpnMrl3S1z19Clu+1WHLu0oZpRSMjrXRhgFaLfv3Q56Ty8lzaZ2unL+hYnFiqdIg64KJj4dvMbZ8S3TS6CI6Gpqtb0rNuCMMHSzuw3/xAnqfaUfvL1PYv1/kAhkSUbAg3OiyghveLRg6VHfI6WMQw+vXUHRZb4qGnNcR/ktKghcJObgZkoeHIgVHnZxgRLW7jLBYToMGuudNTODAzGecozobp2lO1p6e8Pz3bTw3L6Jbw8jKSmj8E0UOZXVADLUIaFleAFzt43HlOw52IvdIj5qXKihrgEVg7AxbanGW9ksriMsQGGFNSP0aSHIy+DQqjhlJ5GmsWwg1MhJm3qnN6G8jWLtW9zaDu4QznQn83tkAiX8tfZnMIHduKO4WQGPTY2Thk/zf6+Skm5YFnL+gYDvt2H49u8H1iWLds/HuWdxPvXIGQ+S9GjkSztk341yvbWTLJtFOBOMmmrLRpDvnqM78huczjEi/Gn5py8utW7Cf5vBEmHtk01G1Jr9Xr+Bdam3iH2ajYoh0CfYdO+BG5DQ4UoIx3dREmQwgPjVrguWGVVCwAJ6eQtESGxuwNYnGwiwFhUJPEQ+puBU9sSfjx8OY/eWgZEmU9f4Efo6AFCgA25vuwOr6OfJ1WyN53YsXcONzLTA3p9IbVOJLBpCIiAh4He2V8W8NWFvLVtt79Ah2+reCiAjqX4WKFdXa6en3zBlotFmobjh1YVrcBIIL7OB9X8CXhNuJZGqf4OBAUlgUSXGazx8EXlPW5xNYPoDsquNly8KuOmuxef0Qv9bLjO4yPBzyz+oKdKX+mBSOHTd+3I0bpcLYC+ASBBiooKVQyJK18HBw7toR6EDdpgqOnRC5KD0oIixMxJykH2/fwoiLQwj+EEPD2YLLUaGA7xuOCX7YXcHoyNKn9xkenmmNdldX1WL9/buQTAJw/6UNyZTE8qU5hfJJNE7DuXPQ69pmAmPs+WO+/LWJiTDhmJB2Xm9vCr17a/7GfdtHwKSZ0K42cr9fYiKc/FaGoMCvOOxKoVUbE5astyeIGVhsys4fMvEy6qhcGe6N2qFWzv036YtdXES/5dnzTTnFdlgJ4bP1W68WLoQR757AWthdLQE9Sdo/DxGLXv78kN/8KuQqJ+vJ1EbrtqYw+hx8/Agmhsh//zvxS5MX9QXBWAPKypWwKHgr7IQrg9QWPC2cOQN/xfWFa9A7xDjy0qQJNHGaDTU6ga9AXkaPhtFHG4Cvr6xmSmIiJKeYQ5IS8xRhU3v/Pky7PIy4sFg6bEGnknE6TE3B1CQJTJMz1lwvL1jX/iyWuzeTe8AGyX579ICmO9qDjw+e9YRZ1N0d2pV8BTcOQX5p8nLuHAx4NAKAjVeNIy8WFuBiHgGpqVhYqNTTAgPh0rdqRAeEUPQelNCtWs+zZzDjsRBn4XzTOPIiBXNzMDdLISHRhKhI8V1/vnywruZ2ePaMIs01dZEePYIKK2YTlWBB36HopP8CouTUxwdaF3kJ709Jxng6OUHvUvfhyWMqVe6scc5B9egI+5GMKOkyJFUajLKA+PuDv0kPIs8WoFUnTeXVdKRXMU6RqIvRf3E+HnOJ5Ha+XHusOp6UBLuuZgPa43HBlJqNxIedkgIHXhYEwFemCKgGHBxIwpSIj1E4iwRNPv9oTQp+WHxQSiqh1qsHzvvW4ZrXGU9PVaZcjSGFCOMO+YbE81wiyy4d5ubwLkqoMhgUBGULRhF65TGeBYugHa+lLrEg+RsbgJQUaLyqIdCQ8vMTadXGhLU77HjCeGx3JfHHBiNuljUrp6lFOA6YXnGjuYgCfkICXPhenOBvtXA6lkr9BpmUNUYzU6p1R3Nc+QYD7XjbDL2FHY1FSAjUXN2X4G9dqNg2lR071cad2Vz1rFnJMG3/ovilycu8eTDjWHEsunfAMe8oyeuOHYOXiQPhYnG6dxMm+J8hPuHhEJSah/ivrmQN04yi14HYQmGAxP/vv8OcF/7wAi60FFJ3f/yA/R+E1bv4MwMGqtavvT30rPEOtm+EMuuRCiBxcgInq89gb6a5mzAmU0kLHfvZcZRQYtrbEVRLPDurXTtot6ub0Ef3YxnHHz2Cthf6AzBhnzh5kcKGvXY8YCExfxZmYT1EXXweHtAkmz+Eh5M3b1WNcx/33sGmSQ2sd9xCrLCetzf0LHgDgs5BaU3yYmMDUQlCTJase1CMRFhby7rJfHxgTbNjELAMumiSF6USejb4gvWxPeSt3x7tAnkGQY68SIx5xw6YE7oQTkLhF7rkxdQUSucIhndvyZunpOht776w4TaVUTxNJSWNsIOw6HVcXh4oT435yZLkRd3yGhWhGa8jhUrdc3OVJEwbppCYpPunle5fkiieUrBfAo8ltOyaNYNmy7YLK6p3C5Er9C/Snp7gYh2LR+x7nJ39ODTvBZSvAgseAoU1rlUq4dCMR9hP+A2PaRvRMN2BwQuqhQU42SUSGmlG0NefEIwByJqVkcznIUWxmpNMjEgds8REqLuiKdCU6nOSqN9AtXz1751MwzPDoFNnLCz0x4DkyQMVvd+SJfIZOyMbEowbRGaeS8jB1hb8A4SX6/PHRDSyEcD4VGlQmecyW5fiX4BfOubF1RW8bcJxMQmVLci1eTMMS5zLsP1VMgJYa9SA3z3XMr30QXLIZDGOHw837Otwo//GjOvWr4d8/jspcnAaJ8TM3/qQyVibjOrQGMAjpFxOBjVGnHDp8TdVrgwr/JaxotgaypZVG2uCCeE4kphsKm8EERmzIemsVavCmZqzOFN0BC3VsmwPHlOymGGsOZ9XMqShVCk4WGcFB3OPpG1bzXMe2SyxJRqTaOOd6k5O4OcdRjmukzuHbr2fqCi489WHO3GFdOMADalmLTNLr5sexFKG8FsT3Z3dq1dgOW4oluGB9Owp3j4iyZqXygJcu2OuMYzQUBi0uwqDEheyfr1mG32/k60t3Jp8jFuUZeliccuLk6vwEVuaJcvFSUvCwQE+bzpLHBYcXKUWxyETt2JhLSygySkmma3BKUAkJqJ340B+YxkdG0u8fGrInRuC1+7nSWoBJg5V++MlFrfGDZKpyiXyu8i4kA1YGKcOC2MVfVnaX9gN/T3nO+eozpGZhpqu0pC+GMvA2hoszYVvIThI8x1o1iSFwSxjcN0Xkppb6ihXDq6MOMCOlLZ065RELl6Tyz3yP8IFzM3BxT4RL77gbK2at798gadJeXka5GL0dD7oxW8oSEUxZjRv3vzDA/4/gl/a8gJkmgjUqgW1cm6AvHkhh3RqZ86ckNPsHvjWyNBsUv+4MlMaCQsL6QBBtX6rWd8EZxccHIT6OaVKwadhC7DasR7bWY8l2967B3eDm8PT7NQLUJtX0s1NsbGaTEgbWgtjair8SHIkLsENk08peGcR58yFCkEh36PCSpVPJRCSLRvkN3mBtZcDKSl6otO0Zp+cOWFe/bPYXTpG0fYLRJt4eICHx2NI/qKh52VtrbqX3jgfsVkvfUXOxErq5ARP/7wg5EAP/w5oBmQ9fAgVN/4G/MbwxbAg7U9LSYGQVBciI10x/Sh4F42GTA2Z1FSIT1ICSkkZ9lGjFaxJegKL4F5nIWELBFKy/FIRoAhtTkD37qo29eqB86bF2DkpKV5cJuZBBrv3mmLh7oDFvOlgPyjjuJkZLOlyFzZtJEvfeUhZVBQK8M5nByQIRMLHh5QUmLrTD/gD363m9Bik2aZwURPiLl7DsaAPiYm6UZedawcSf+gk3nVaIJtu7+qKtmzs3H7vYPtgGFgX7d9fFGrpv3ohYx0r0zIrLwnFoa0lH/Tc6rdRVjB1DWSvChSlTJE44AIU1b2vHFYe8uEhwss6tEUAOtYghN9nSr9AzJfOw7fnIDTicYxNlQYhLio6mvVzv8OWPLBwC9iJFZf6eXy/+hJF4UIw7SpQARDET9eHX4NF8LS3oBJuCD5+hOX3VXEKhlak/rfhl7a8AAaRl8GDYYdZZ3Z0O6FZM8UY4qP2UeXPD52yXKBX1hPkzi3dZNIkyPb5KtmWjcjI/Hj1Cua8acmUF225ckW6bZ8+cN63G+fbrqJYMdVwfTyScI7/KhvQdvgw9Pk4kT6XOvFErfp8orkNYTjw/ZP03/zuHZwMLcPJz4UyMieio8FtWCey8okunfXYZUXcZAsXwjOP6tzts8aQDZoG3N1hZINn9E1cLplWngGtfidOhGuODfAfuDZzsZjp6boSJp/kZIhLNCUu1UJ8ApIhEVKIiAC3sT3JmfSS3j3FLRQZkNMAAVF/lYUFFPMOopjpQ0lipO5+kYmT1kDJktDf7wKdXI5Lx9rqsenb24OFk7VONoqZGQyu95LBLKNFU5mq1aCjuZKSAlN2+TGFyazfprulX7xEwVWXJhztuE3UnbliyEv+ohfThuspQZJmefmphSjd1/b1q37/h0xmVmS0gnAcCY8yYG9rayuYRLTTpIw0YTx8oiKUzSt+k7xu9IhkhrKEFkVeG3V/UaS/aJ8+/fy99EDh9vMVuNOhnV0k5zX4N+OXtry8eQMPo+sQ/zQ3FQOkLZfly0N55V4oUQZs1KK7DRCLE0P16lC9wkphZq8oHS0eEgIfk7NAuErZ99kzGHtfkL82uySImRmFn5Dpd2tfi3DCyNcsgefi4pzs2QOjnyyAJ7D3qpCkoR4fFBebgiGxBDrQoxrr7w8Hn7eB5GQa3RUWwwzY2QkPMEGmGqUI/PwAh6fgUBzkTNESC8XVR/a8oTOR+73oUVfXWHXhAtRaKSi5TpiMTn0jORLh6Qm/lbgGb15TsaKqZLVGQchw8WDMly+h9fLe8KM5raapMqQykB7RKbKwZcsG94dugpkzYZr4glyqFHTyOIWrYxJeXqp8ag8PuD1yJyxditPMq7oN7ewEkaGfgUQ2isHBDO5C0Ku+jDwNODpKByYZ0O/Xr1Bu2QiCQ0fToH0qu3drLfyGEgG1xbjPjhpEsB2P2V4s2aJ76Y8EO4IoQNhdc0o01vxGc2ZNhLdvsc2SBTHtGh14ehpeal4C6XOvGQkER+ixUME/QgL+J8lLRmVptXFXqoRQFb5IYRwc9BTZVYO5OTSoGI7d1eMULZRC7twd/uHB/t/AL01eDhyAka/nwmvYdUOP21VsEjJApO7dO/iRWBQ+eVJQ3dtiQNCtgwN4mQSBtRVmZvYZzdKR6biV2FjZjJEmTSDr31MgZ04KFVIFdFpbpRAeDTFGch+lEhqXDcL85mX8ytVBJ2BNbbipqQpIVaDQHp6eOI7792Hyc0EIz0uMvIBgAUmfRNQQEQFfwr0gWom7dtq7HtJ04wZMOj4UIqPovh3aq+kBLvzTnH1sgk3QdEYmsndlTPs5c8KyWgchYh+0UJEXpRKaVfiGxbVz+FWsC+iaA+Li4GGQB+BBOZF5+49pSnYpnhM21Ier1URqsehB8+bQfNtaYUEvqCIvFhZQKmsQmNwTz8CVSZWOjoaBaysC6ymy2IThUvH1rq6Gm3tE8OCNLf7mvQncmoXuNYXbnZh4BaZPw3HqbkTfXQcH/dYxGQJibw8fQ4XvOzgoicxOy8cu23HK/E8+zSrB3kceQDtyXYpHW1IHYPhIEzbxBObA8+6adYKOrvkC+QrAmotAFb39Jrt7EfwuBqsI+P7elATyY/LRCj3Z3Rro3Ru67myA58OTmJY9LX2htbUwCWr9xnUbm3OGJOisIKyJYRlDi3b5cJTTfOpXgou44/GfDH5VKgVrlxp56dEDeowaDK3HgLfh5AXg6KFkcGkP1mWA/5KXXw4/E3ty4AD0Pb6e+GQlM1fAgAHi102dChsizsJyeDZQcBlldK6n0xkzYMamUkJwQFEhG6VYMdjXeD2W96+Tp4t02rEYkpLgyNO8xNIO5yOJ1G0svsMpXhyKuxwEv3KQRUVeqpSOJfT4eTyLFQfcRdtWqAB/ZP0bnJ3Jn79ZxvFDs55Cjdbw2yukZE5XrIDfTgsRzJu3aqVy68mgkYWdHcmYEBsYha0IeTl2DNofFdK6F2+GIWoiyvrIy/fvcPqzkF5b7Z12t6rJUCzsxdERqvq8grAwcuTQzZBYvN2de2wkbGwB9lw13Gi0f8FbKN8eejxEjLwoFGBllgiJSZiZ6cYuBQfD89R8ECmhIK8vVRoEkigVSSjRNsXWnqjwVIhAp2J6QgJsvJobyE39cymi5CUgAM5EtuLHHQsqXlcra2FA3+nYuBEWJayBo1DxpWCIqVssCDgFpSRcTpmooq0Oa2vwdY/F9ttbsrv7km7tKNO3GJE8JVcfb46c13+fS5dgScIA0IiVFf975eoEGYPt26HTjYuk3DBlRTVYtsCbZzzDfkAS4V30Ns+AmxuQ1wYe6nF1AqkursR8CcdMzZCakgIpmIIBr2Y6nr8y5Sy14Bu0ZjclN7szu6V0kd2fwZUrcEoxleBtJRjUWC2+JbPpTeluv0IG1LH6l+KXJi8VKsDs/BuwVCZSsmRvyesiIiAh1QWirXBKFnyMycnwLd4RyOSamsl4GXd3aF7oFTw+AzLxMps2waHPS+CQF9N6Ch9LSgo0X1INqEblWUnU1aMdoT0L7FgZBtnrwfBTgIgQA4JGSkXfv4X0hwLNVCeMyVTSwtWrsPPTKGK+OdLjmvC7aaN2bThebgokJ1OwvmbacY6ulXlPMtnrJPDOiJL0ISHwIaUoMe99yB1keO2RdHTsCGUOTsC2Sgk8PHSLBZYsCReaLxVWnZ4PdM6fuWrFUbrAHcGIoRFvlQ65QGEJK0bhwhDz+2xBrGj5F53zjo5gZxKFo3UiiYkigRyGwEgLyKNHUGTebGA2vUfCGuN4OQAPHkCPe0Kw75TTKvISFQUOndoBbanVBE7KbOzV4wky4l5lgkFv3oTlryYR9siSngeEtGd1VBpSkljukHuQGzuPiPepUMCHky+EXcMYVSmKFwHWROCHIsAwyVj1uKypvT7SeV0VlBtOoVM6HOHZRGw5iFMWW1xdtQooGrGgOjikkQZ+Xmm/5KVFPGUTti1M+R4mfs28efD7l9fEz7HgRHWhgClAvrwphJ+/CzlzYWKiu0ERg7ql/TJVuHwCpif958jLtJDfIARqP9cKzs2MxUehENi6rLLqvxu/NHkpUQJKFDoqsBM/afLSqxfsjv8E4+BDByGDw8EBstsFY5EYhYNDdsm2NWuC7fY1ULIkjo6CL+PhQ+izdyTxIf3pMA9GSUvMiMMAl9OjR7A3qi68giFplkozM1XdmdgYPTscsQksXegkM1L76eRFJt7G0xMqODwBpSlubipZ86dPYdknQf+i/DNx8pIlC2RxvyewSi33n6lSGEtktPgkkSMHdMtxEWJj8fNTxSDt3AkD7v8FwMaT0EVkJ1m/PkR0HghPn2I+QnN7XLs21PY+ADljwMn4SscOjqp4FUnyIgY95AWQXaCmT4cZF+sJKoHlNmqc+/oVJu2pC9GeVFivmTGkAZHU3/h48H/nDimlcXmNRrC6uoaO2LDt7eH5zH0wfhzWK59KdpkObd6kEriTD9itXRtstq/DM/Ur5StoBwPpIjAQtgQI+j4VnumSl/tv7IihJImv9RAQkVgOB5skFNFR2NpYSjTSRPPmUOLETLJ8uYV35zGYrfsAnuIRwO3aQbvVi4Ug31wS1Z8NWFR9faGk1xc8Qp6SK1ctmteJotzKA1jWqgsYF+Ueb2pFHFYo4xMlr7GwgPhUgV2ov17LFybC6rIwbStYG+ZG+e03+O1mZ1peHsK58MxUMDUc6u/mN+l4ZOOQCRXpfxN+afIC/FSq9LtuU4Woyz4iRWDS0KkTdBo8FpqOBU+BvMTFwc2vQlplpcyIJGZyzAoFzOn1GrM1y/HuNR4QNyWoq/OaJatFsxuqOCsVHwSypKtlS2i5epiw9a+rKqCkXq9Hr9ityIRbokgS7gF3ccmfGzF3V9myULbsKmFWqaMiL4b0q1SCnXk8KGPFg3p/orL0zJkw6WxVHDs2xDXHaI1z9+5Bx3XDIbIPPbQJsCHkRQYKBZKukPBwWHe7KFCUpEvi5CU2Fmqt6MCPmHoUbpHM7n3CC/T1K5Rb3A5oR7vfBZdDOpycoHSO7zi886dwgRpoB3WbmkI+rwjgpWRx5jx5YEWLM7gc20yB3irSZWICpXMGw9u35Msjr1JYvDgUr+gPly+D9++kpsKbrzZALqy+KPBx1LxeQ5E4TPd+ZqYpmJGMUqnHmiFSWfrjzhtCdP/eV8iaWdOQJQtkKRkHD+6AadrmRI6AODuL1gma+qcL31iG9crszJUroorgtbgz6ZDABDrGQ/kfsLInDLuAseTF0s4cvkJUnHhMHAhkqbDDB1wVITg6FledyESqtKMjkNOZZXfHEh4eDZOnYGlZx6gxG4o6deBo3aV4frxFrnZCBPUff8CRiHOwxJO9rSF79v9I1/9a/Je8GEAESpaE2L1HoUABLC3VFOmMyTZS+6jSzZLmxKNQSNsoDx2Cm2Gj4FwxBvYVFFmTkyEozpm4WC8svwjHxDBxIgzdWxnq1sW1zMSM4yO7foc1S6F6H6TIy/TpMPXhTXgIJ1sKHx6gsp5kwk82aJY3TzhL8sCCXJTmeqLxFHXrwq1GU7H++BzvTtpVF/Vj1+YEcK4II3eDXBUTrX79/KBfnjNYx/ygcOG2Eo30QCYIFZCNH8mWDXALgaTPOglaMTHwPEQIutXeyU1e5MA5LhI5oiDnaoorEgP6Jf4zmYVhaQm33rqShDvWrxIwJLvMyQluLbgipKcNEKkhBHrdGS4u0L/xJ9i3CfKuJV1Xxdoabk09KewkFseid9pTKzaYmAh5BtcHXlOldxIXtZKkypSBl4OX47hjFQ7TdLWTwg5cFMw5R94hpl2SAUtLwbwklrVjrHZJYKBh4h8uLqIS81sP2/GS33A6kshcQ/tMTtYceyZcIZ362/FodApDBoOUikezZtCs41zBD9NQ19VqNLJkocC3P4FkyPsjU4mQhsDXF3zLBMOTi5BGeD98gHvJxeBzJvW+fnH8V+cljbzIzYtjxsBhs5Yc7ncsI5MSMCjbSAxFikDKnHnEO3iwdKn0dSdOwMyowcy8UiVjXggKAp/JvckV+5jfZLS8HBzAx+wbPnYRmj7cn4g9Wf6ngiamR6g1vy6fJWJHli0D91tHcN+xhGMqlX7uPLbkPDW49MgZidI0knB1FaThC6Y+llyIIyLgbbQHb6M9dPX7MmmJKFMGVlbbxQKv+ZK1qwDZRTXF1p6osCRRb9mDB9D6RA9av5/Hzp0SN5CwgJiagoNFLA4mETpFG5+9MOEyVfD/6CKawRsUBPOulGdeVD9OS8V/SGTQ5MgBj4b+xSP7ikybJt5UoQBXxyTsCcdaqXKX2NnB4Mr3GaxcQT0xhYBM6NroIN2Coe03MiYw0tNT8Ekk69GEQSBGeXIm4xb5Vjyg2sB+z52DwSbLabO2NvfvGz5UHfj4QHIyp06mcpQGXLhlLX2ti8s/k3KcHmzzkynHQ4dCZJQJc+frWZZ+MqNMA+nE638C6aQ4bQI0NRVSw81M/4f6/5fhlyYvV66A3bqFmN2/ybhxei4Wm4QMdd9otVUoQGGZOdePRoZUnAGCb9owIPYke3aoZnObaj4vNciCvz8cTm7I2Ze+4lkoCBaB70lOfI+z1yhNb6mmVpupEkd6LBi7d0Ous2vIdX4du3ZpnVQqBaKZmRgQPVlOAQGw6VV5NgU34JGWIvqBA6A8uAe7U3tZvly3bVAQ7HlTgj3htTXEADXg4CCqIVK+PIQNmkRY7tI6JCKdq5mZJosO/csXGH26NqMjfmffPt3z377BnGeNGfeuj86ztLCAQh7fKaR8LutyD7j+mXAcuTLvRsYxFxdY0uIiSyxG07WrSCMZXZuEBDjzxIsz1MT/gcyuPj2b7CcWt1QPT36kOPL2TggmJtCx0gc6soXa1SWsGY6OwveUIBPXoscS4e8Py8I6s/tVMZXQbiYyUV6n5OQ0tag7qxqNOErfyeKK1F++QLltg8jz4Qz9+mme27PkC7cpxdnF0ircGkh/ET5//uniQAZl1KXHU6n1NWeBkm6sp9uqskZNq8c/FWYxQ5jK7//5OkFeXoJFLM1V99dfkODoQcLsRRqp6v+FYfil3UamphCVKGxbjeURwcEw+3Rd4kPdKSETuDhuHByIuAHzXTnWClUdpHTiI+M2GDIEWu1qAw0bkju3MNtbW0PzUgFY3LlC8QotkZUcF0MaeUmKipP88bt3h+5LegvFhkovyziuHlQptZ47OkJOi89gboa1tcpMdfgQmDpZYfHXSkysu4m2PXkSNj4aBxYWDLyqVanb1jZTMvsZkCE/J0/CxFMzICmJkTvRrFFkaytLXu7dg66XewEw66iQyZMOGxtITdsf6KnmIIqQEPCPq0DY11jyPpbIihR5d5YuhT/P+WHRpikUnJ2pfseeF0wjnY9AmzaG9asOpUcmSISM5SUiAmovqAfUo+HvqRw5Kn6LFGdXwnDih380eQx8XtrI1rs2AfwgS9MEAgJhy6CbcKUzjG4CiATPqpMug6OqNaGe5fT1q/C/83ZkJYHxuO2wo88Ew+7TZVpuriOTTpUGS0u4+VHwOed6m4L6PrZw3njgLuQ1zD287oArhxWH+DS4LKZO9iRzB7shubjwMxYkObi4CHNndHSGKuOpc6acoxtcghVGGDLGbcjLAxYDUP/NKUqqFfT8p/HFNCtfKUHYgUhq9kqzEP4nKkH+IvilyYuDAxR0+4ZFWCA+PgaIBKlNfFFRsOBSaaC0Tp0WdXz5As9T8sE3wX+eAUtL4cVNTJTcbuTLB/ksrkLOghlCl1ZWsG/cbWjZAQb8AJxF2z5+DG+iasLrglRWE16r0dGLSySSXF9JSopxm43Jk2H8iSrY1CqPdek5otf07Qt9N7YWBG3q/J1x3NZRCaaJkCBtdnn5ErYH1QCg0QcVeUlMhEdhOYkML4bdPfHK0LlyQQefC2n/rqZxbs8eOBC7hsgNeZnRVJcE/PgBd0IF1TSdTICfIE0eHlDK6xMOoe/Jnl1XCrlKFQjoMgHu3MFuxEmd87dvQ72z4wH4fZfhkg7W1oC9hSRZy5ED9rbZCWfOkKPPWp3z6hog4WGpGFLVWAd2dkJ6mxFuiRl/e3GHfYQPKcyp+4LBzFhU7ZadK4RAZ4hvI3xasbHQb3V5YAOFFpoySo+V1cVVQUAQBP0QvhF9a9nFd74E04LUHUm00qp9tOxAVpIYitt+GzoNlb5HrVpwrc1iPO8exau/QD6mbs5OFDMouDHBYPKSJbsSbgv/7sFflOzcENC1vjg6gtI0BbvkMKyV1miQMiMX1EePFRxKbQyfEP6jJI6vpTOGfhbD9lTkCzuw753K2u36r5dD9txmPEhLXiszsQ4xw+XLtv0M6owqwhPuYjkwmZieanPvL1wZ+mfwS7uNChSAx8P/5q59DUaOlL5uxgyon3iQ+n82zJiL1eMM4uOlP3Zra3AgHAfLuAxGn5wMf14syEKGsXVTJvyd6b4jGXPR+vXQ7OtKmu3vyvPnquMpChOS0zirrPtGZAJzcgIPhzhsE0PldydS1iQ9gm9SiIyEknPbUi3xNBMniAfMVKsGW4svYGuJhVSvrnnu0SPYGtWMQ68LiLrlFQowVSRjqkjWGPa3b1B0WS9yhtyhVy/xsRUpAn+W28yf2eepApvVzt0etp0zFo1EKzBbWkIW2zCymH/TyFpJh14hMblFRsbS5OgILfye0cLqeEbRRHW4uMDe4Vc5Sw3mTtIkbtHRcPFtVi4mVtCuI6gJhUI0XVrO0njlriUHaM75x246liorK5jYyJ+JTNOp3q0OZzcV40k3+iQmwqYrudhEV86c0z/lVaxsSj2O07HcG4Mssp3nFKQVexk0RTfIePS6PAxnEfPXigszpsPdHcoXjyNHyF2dGCZj0LSpgrGOq1iWfQFzGc2AjuJlC0xMIPb8TUJwYd9ciTpBBi6q6V4jE4XwbZqRgJm+7KqfwK4rXuyiLcfOqnzoG1bF85x8PF9w1Kjn13/A/xxx8PQWooHjEkwzZYn9LzTxS5MXwKC4lfv34URqPU48zZZxqYsLXB5/nFuUZtEc6V3GypUQ5pCNsGnLM3QtFAr4bX0pRrCQP9dkYntpQNqxFPL7KSjBXSrmCcpcEbhMEpCMtjIumC5d4G2FTrxtOIgmTVTHNer1hOkheyITrrpUuNh63r49JLXuQFLNehpB0GZm8PCLK+/IwecAcdKUIwcM8DvPAK/9ohYhHBwEn4exUcoI2UZjq99gtuVkHf2Qjx9hxo2azPjRl3PnRBrry3KSgZkZtKgfSw3Ok89Fk3x8+ADV1nakWsQh5sqkoty9C3NTRzH6UMWMeJ6PHyHvrG7kjb4vullwdFJNR9pkzcYGpjW/xzQm0bkzkihdRkFds3N0LPo40xva5StNOe7cifUN9wq7cD1puI5pxDM04idTVby8BEnjtO961++POUwjlk823HrVsSPMKrqD3xIX4YJuGrQ6lJ7idYIePLfgJmW4+9xGpJUuevaET00GEF+5NqnPX5CABd8O3TR4zMbCNb1MUKgy46fJ6pNCPl6SzyfKKLdP3bqwOOsCBvAnA+q8+o8WOWzU1JR+Zn8xubaQsnbiBCyKH8CiSyUkYwj/C2n80m4jINOaKWZmUKlIBHAHvOPRG3uiNvGZmICZMoXEJBPZoNuvXyEsIRcEu5EjTs3aY4DlpUEDcNs4DwoVwte3fsbxVWtM4e+yMHw52PUTbbtjB+z5MB+OuzHpoWBByICNTaZSpf39wT+lC9GXi9DsM6JVmh0cwMHyK9glgxphMTeH35p8wPrQDnI364VoGq0MunWDpkd6Y2eVhHPT9dIXai1OtrZgaZ6MXcIP7KwckK/OKAFHR2Hxi4xE1LwiY4nw9IRZ7R/BhalQbRLqe43372Hi1fpAfUafhBo1VO0+fIAz35sQGZFChVtC1pQo9GmAgGC+yAjUMhwXL8KYwGEQCCUeQcGCggXk1XcnwElUjXXhQph/viSOPVpgnUPET2KAO2PiRGDLAKjZEDwXAMIr+2LOARgzGuvVjzEoTiwtMyQ+Hqr9XhO4RskRFiwXUf4d2C+Z8GGjceneipSUMhqL55bRj0iePhOHscuRKqmh0ScIkdzZslG/bAhwFMobOT9lyyaoNuuDRHBzq6E+vOYmLiMSCRaxGGrD2RlB2v+AWtr1f9AVsmNbCpYlcuCxYjoKRcefvt+QcjchYDf02AHmef6BEYpj6FBg5Vwo0hgcKrJtG2yOmwmHoFGwjKTBfyGK/5IXCwthVk2RjtTauBHWHXSD2bOx9+qp2RYEEmFIJTD1e455humMKbiNXoSUmNOUKbA6+BIsB/9eULSocLztlAJ85jJOfb04fFH8/jVrQk2nNVCuJWSpr3lST2XpJ09gb3htCId+ajEgX77AtZAaxEQmU0IigPTsWTj6fjBEutBD7Zo9e2DG97lwGvI9Eycvclg25jMcGguNG2MseXF1BVfPSEEAzIj4ZjMziD10BurVg6UfAF/xC+UW1XTCEh6uQ16CguDGuyIQZkG+52p1r9Th4iLcPyxMq2KkNB48gF53BGI6/bQueUlMhB+RNpDshrVIHaGMfkFnYXNxgTFVrsPt25SqP1hyDOqKoukbexMTcLaOhZhYbGx0/xYvL8AlDmKDMxVmo9G5mjXB1BTyekYAr8BQUdK0SskpKXDjlSvgitULcVNl3yGWMGoRFM0OJpoPu2WlIGA3VJ2vt8vnsdkIoBYhmxNoO1Hv5dLIkcMw0TZHR+FH+acqNP8D2UaGwK+4JdiHQJhuaYtM4X9SHU5NQ+i/+Dn80m6j+Hjov70yPfiLWdOl3RE2NuBIGI7WCZr8xgALCCD6QbevH0YbdlO9hLhPWg63ntpylUrceiSj4SDRL6CqLG0kbt6E1jdG0PXJaI5KZHvcugWLAtuz6Ekd3r5VHTckU0kW6b4jCVfIoUNQ4cpcKlyewxGxGjKGiMWJQY9GjFAJG1JRiN5i+IYitGQPHfvrMoT796HZiX40e7dIWudFgkQULAiHm63jcJb+dOsmPmSpYT98CF4LR+H19R7jx4t3G2bqwgvycv2GQiPQ3MMDZtc9z2ybabSS0furWhX21FnD+Tx9Mq7LkQN+TFvJD7vsrF4t0VAiNVwD+nb1rq4aSrVGtU2Hp6cq7UcfFArhd5LLrDKg365Tc1GH07SflFtw6WaWCGTPji8fUJBK2dYScsTApSsmzLKcwojNxQgIUBtH03CGsJg+TUQE86Tg4yPMKSKKvf8RaJGAu/cUnKEmZx55GC3bEu+Tk1fk5s6T/1CkrjrUxj1wIOy06sbOzkc0ss3+C8PwS1teFApYdTYvkJfKJ5IYN8m49o+/uhBDaUzvpFBSwpJw8CA8jh8JZ8rSv7va5tmAuJXy5SF+0w7Ilx8np2IZx9M5U1JmtY2srGT7HTUK+u2pBRUq4FJJVeTQKJl+LdStC04bF2HjaE6JEgNFr3n/Hp4Fl4ZkJ4p9TduJpyN9RZbI/AkKguthQrUz0dohMuTl+XM4+ao+xMZS7YHKwgWoSJNEvwcOQIuNgitq9lxB0FAdR6678IqWOF7KZPZF2guTFPQDZR6VSdvFBRrlfAYvLoKfZhM/P1jd4CB2N05TqKOIwIwB6D3Mhj28gMnwobugEKoBPYtxtmyQrUwAPDshluwiDQlRvuBgKDyiPdCAOl0Fa6gkPDzgzh0jOtXEu3cw+s4YAj6k0GAepG7fAe3bk3okEg1/pjqcnX9aOM0zixLuQ2qqgm/fIPmbBalkxeybKV5GeO5Kz25BQFrl9ogo6SCOI0dgXsxEuAqN36gKFU7sFwzLhkG/Mhhqqjr7tQBv6M2ydgXoyRAsD3rRTzfB7p+Dh4eGou+IiZZc5AzMgNiJGBW74jWxB6H0I+fyEN5M1X/9T8HTU0gFJa0siXIfFCuSkU36XxiOX5q8mKmV0NAr+AY6E3a14cX5wS1yDUrgdVPxJnv2wJb43+EEtFVLWTbEatO1K3QdOwxaDADfYhnH7x8PxCx/TpR7jiNV3VlqzPv3w+HwRcTtzsnEdkLGlTbs7cHe7BvYhmtkUObPD3OrHMHm+V1KN/pDtLsuXaDall6QKxf5KqlyUkuUgBJ5zwu7yazi5OXAARj2UNAl2X5RKB6XAT2WFzlER8O1b0WJ/BaJz01h0lDHnTsw1F/IdV9+RYu86CFN6hBbzx2dgA8QHq3U8UzmzQuzyu6HgE9UqjlItzHQZEQeLhBObDVbEhINMxx4ekKfqi/g2lYorEteHB2hWb5n8PEDRYqISd2Cs7Oqox8/RMiLIUhfYNTjemSsCUFBcCOyBuHvkyjiD8WKqc6lpEBguDVgLRvc+PEjDL04hKB30dSZItSPSUyEi489gZq43IfiUjFAatjzUgj0yvIwNaMos+yzd3Eh8XsYKfGaQpLB4WaAC6ZhCpykjSAAtGyloNC5JXhWyYu1dX18epQnho8U7prAw+fybdURr1B9tNl8EpHylbqoeV81eFcmLD4jVuXmAWsgAIaxGOc1ifSbZ/RtDEJICNxV1CbQ35yCEtIJxiA0Sng+b0OdiY//z1SVBuHdbLZnHIFfx9GgF6xb95/p51fBL01eFAq4v/I65v17YvfnKaR2GZcuQUByO7iVh+ZdVBYIC3PhI483rGK9BqKSrYjFlYSAFHzKG9fWytECSJa1nowdC3++9YeFZpxtrop7uH8f1ke0hAjo9kmcvACiE1i2bDCq+h14sw5Ki5MXHx/wsX0EHgpdCRobm0yXVO09xonTvCOysxfvPuvGafTqBb32NxQYafcDGuc+f4Y6W7sCXem0XJe8yGH7KRdeMomoZb7Mrqa7o3N2hvJuryAuDm/vwjrtd+9IQZnfB4c1C1Ao2mmcy5kTxhY/BYm3oJI4eYlLMScSS0gWvCnq6dMGpUqLBATnygX722yHDRugj3hl0AoVIGbnYVyy2+HoWE26Hzl4eAiqs9oDl2ABd+9CsytCGtLkg5rkxcQEsrlEwo8fuLtnl+12/wvhpfZ8KGjUREVB7Xl1gDrUm5TC8RPyw06Px1KQQkxYot74kV27oNeNk0ResWZlZTQUa306ViOBYIp3SODeI9HmGejSBVi8EXzLgGN9+YtlULCokpTnj8nBO7YuKQDkEr2uWTPIt3cmLspwClYX0W0yIug2S3Zlhl7Kfxp370KdS0LF7/F7BfLSuW0ila/MghYtMTWVmtTEMen3VKZOU1C+dCIWFtJFIX8WNjZw/4tghhSyF9N2Mv/VeckUfmnyAlCsQCLwDFyk/SCLF8P+1M2wHr7MUJGXbs3CiVy7HZdGzZEqdTt8OLTd2wY6tMfLq3nG8cods+LPd8w7phAvpmAqh//X3llGR3G1AfjZuLsRF4IFd3eHosX9o6V4kQKlLdaibYECpVgpbXEp7u7ursFD8DjRne/HkGQ3O6s4zHNOTsvcuXPv3Z2d+86rBpicUlIgQXCAVPUoXdUETCa4vbxaqLSeSKWyZWFU8DxwdKBgwRZqbU9jzLlNMCSISpCcwotCgejkaabQcPZUPTcuVjPpWsWKsLjMZEh6QYna6k4g85bbs41RsAaGJWqOW6UKHKw/Bq5fh/b7NdYUlMcaLB9DylOTnFDDws24s/Mq7kEOJCdnV+FMToZHcS6Q7otTTA6hBkThJeOlgGtC1q1OnaDTX7+KjpghVbOOX74MtSb0hoROtB0CE6RzFQIQY+9HNHmJ2RxD2dYuPHsGv28tCymDKbwajfBvXRWaPTzg1vil8OWX8Kd2oU219lhiTDpg/GZkZQW31p4lV6OSWP1yBPRoPaytIT5dfCi8cskdFZ+I5hUfkbJ9LwGV6mKMp/niJWZwtJFo/3K8pvW8vHkhb6Ebooe+Yb7gWun6hRkNDw7lkntFit1YjtOQIWjYM18T3ir1ZDMtR107pEKf4dA6H1gaJ7yMHKWgWXPIl+/NCS4gRhPZWafjmhKNm50r8fH2pCjdIMEG1wzjTF0ysvBiuNOtBGMGx8Kcr6F9YbQJL8WKQTGLzRBRDlScVm1sxJ0sNd1MV6CTdChtpvSkQ4jw8YEIy6vg7IytbfavvWtXaLy6C7beTvjUniLZ99IluBpXDSILUf5xjoznJoZKA2TYOpAUJ6BIUM/dkknZslA2+F+xVHYO4cXTU4G34iGOblakphoXU+jqCkObXMJl9TzytxsJqDs6BwdDcMBBUVMRri68ODhlfzFSQpNeFAqtfhyAzlBpEPMEsbEWtO8IPtlFjA4fhmpzRSetbyfAuHHq/dLtnIjHhdQbCXgX1CK86Hvjk3BCTUuDe3FOgJPe3BRle5fkCpdx7JpOXGvxUiO2VgAq0GGlpvASFgZjau/G+cBGireUSCJjgDnDxgburjiC5+eVsZ5+BsiHjQ388NkZWLeW3C21eCjnIKiUF5BG2s17zN4aDvTEf705jSUS5OXKBXndHuGedBcfnxJqbfVLPSb90FFCS1fF4BDti6IK498hF2B7a/jhFlmliA0lOFgUXvQhUZyxRtcg7nAVty98OKKt5lYOmjYFJu2HpK3ASajazbj5GkFgIHxX/zTeG+dRrP1EXnUbUyhymIrfEGZmEH/oAmbFi8KQQ7TvUZaFibdgOFxvK97/MobzSUcbAQYJL198AdMUfZnWar/65vUKgk/F8koaso7mpe9q9Y4fMwZKPt1CyRn/45rKC9Seg5bMUnTnt/W5tWZqHDIEzgfU4/yXU9R+mF5eUMDzMSGKW1pfyBcsgCZ3ptJk/RcaxQaxs0OZmkZKonTYaHQ0nErMw6mngWpBI0eOgMXvv+F06YiYi8NIZs2CaL+SXOs5WXtko5bNzdoaxva4y2B+4bNyxoWFfvutgo12n7OvxyLtkcr6NlVDImh0oS+SRQLX9vVx4znVmmjZ9Azxa5AY18ICfB3j8TV7oKntyYGPn/h4iU+yMEje9fGB75pcolfKZMqVNT3k1r+gC9akZr2W29rCT81O8RPD6dTRwOt6eYGlJam3H9D775L0ZjrTZkq/mZcuDZcHz+OAbS2NTMqrhp1kHY2YMsrA7z9XLpT3H5j6fpCNobl5vLw0TLm37ltxnXBuPjAy1W9IiGEC0yvi4gJjetyjL1OplFdLVNl7ilnQy5dc1fAuGZP45IWXU5HO7KIqO/Zr99KqXx96K6bTu9oFtZBfgzPdSmwUv/wC62jEil671ByHVbl9G06kF+FElK/aELNnQ3dhBv1XVNDtQqJtgzJRe5KSAvY9OmCOkjrSfp7MnQvFL8yn+Kph7NuXfVxVUDL5wezoqNVx9sIFmHG7PjNu1lUrh5BF5k6rTV2g5bMqXRrquR6moucV3WnHtWgxbt+GtcJnzD+Wj1u31Nu2bgWnvybjdGq3TvOLVCSLpye0DD9FS6fNasUgM3F2FG2FsRLC7ZUrUHNBZ2o+XChZ7ToLCeElf364P3gK9z2L6cywC1C7rjntzRfxTbXjZGSICrWNXf9jo93nDByopZOzs1h5V5tN0xD/gEy7gko0ilH9QXxN9vNDsp6EFO7uonZN25uIAeM+ewa55wzG9t5V2rRWvlLOlEFXutKXKYybqV1LKQjwxD6IC/EBnDqU/YBxdcrAnSe4OhqZgjskRPvv63WT8zv+UAocurqKmvO7dylWDBqab6JhgUi1SE4Zw/jkzUYdh/pxnl3YDc0gsZ+RnQ3QvDx5AklKf3juSK40lQinzGKMOvqam4MFaS9tStkGUdUb3SS/FXt70fVdC7Vrg+OfkyE8nLCwhlnHrawgOU2cR2K8cenuXV2hXHAU9ncvky9fde0n6jKjODhojTbavx96XhRz+887LJHwLVN4kTDfpKRAYqoDpCmwS0ZTSNEhNB09ClP2fQUJCbTdAA0aqLevWQNf35gEN2DBAfV8WOnpEJ8mSnWpupy+JYSIiAhY2uBf2LYN2mpKklXKpvBs7Q58ihcBfNXa4uJgx60wIIwCV6WHvH8fWi3tzdM7XajVV6xUbSzffa+AuT9AmVbgVBKAenkjwXI7aFPTq35PKjd6fDz8uLw0CD9T8B/RJ0crzs7izSolvBjIrVuw2+pLbm7LR986Vyi15Sd8Bv6J6u9Qjcxkgs+fq2foMwJnZ7j9zJF0zLgTqXJDGOnQmZ4Ovx4oD5SHiTBUR348/6+bkUILCnZJ5dxLof/40htiefSlh4CyBo+rDAzmIhE8xZ1C8Zav6kajm8zEKC/9g5q2t+MwUdDNhduNtda6ffcoFGJM+t27DJwMA0e0gC9HQ65+73pmHxyfvPBi/XKjSkk14AGR4yHS4xt7dnKZlF5+nK0r7Q/x9dewKOkS/AQ3OosRJlnXsrbWqbWZMQNmrPSHvn2hUHa69I4dodyqQdhVKom/v44qdRJzjouDUzFFSHxgQ6CWLLlVqkAVz7lQqhYEZQsvCgWUyhsHly5RILwAUjb84sWhh+cK8PQgKKhq1vGAADg4dL0YijEgAynv1T/+gGEH1oCZGX+1gMY5w891CBF6ebkppj+NxTyHfLR0KXRa97c4h3nQo0eOvjoqS9+9C4tulgeg2CVN4UXVCTWn5cjBAQq4RsGLZDw8QpHixg2Yeqk7z+4lUmcBtG+v0qjjbXPhvDRwrw9frgCaaz1PG1ZWcOCWGH0Xel0lMsJYpDKK6sn6qkRBwt1YnHyzha7ERPh1WxGgCE1W6xZezl9QcMy+Nw9X5aVNIzFKztg380OHoMtV0T/ml4Inac9CqKFZgTsL1XIKJgov5uZQICwF5dXrFPDzodaQ4qSwh9zfuPHXMsOvo1qNu2CBDLQJXAoFeHtkcOeBOQ8fqXwnJmoxvAe24wliygGP1mk8fpNKGC8vBCA28hkO6fD0mRnR5IKYNzjma+DiRViW+h13V/vRur7eRBcyOvjkhZeOrdOoeXYS1s0bIwj5tT9XJX7QUQ/NuEpeeCLKIEY7c5pYV6lSJajkuR5CleAqLbwsXw67noyCzXkY/GX2G//581B11dcA9JsLkydrGUTLA+zw31egTDkYdgYorNFerx7UC5ogSjGFqqo32tuL19USAZOcDM/Sxd0+pybi3DlYfq8b8TetaboXKldWb69WDf4p9CtYWVG+omba+g793VlNHAnNHXn2zPA6IklJ8NA8Nwl3Xcj1xPh9qUQJGF18Jc5PI6lUSb0aYeXKcKHFKDh5Enock+z/9ClMPVcNAKdDOYQXXWRKTRKapuLFIWHQKFiyBItfLkl2z/x8HInDUrBGra6TMZubt7dR6dDL9SzGUdJwrCkQY1pdSVauhBHPJ8IuiDgr/i7z92sF1KNmRwULFuq/RmbCNoB7z/Tr9EevyMdl5pPWy52l27OPNxheggw2ET7MmWl/6R/3zJEUcC0MXZdg2/FzkqlM3AXjczEcOiTWKPvqK90hLE0bphEzZxG5qpdHEPKoP/+M1Pj4+MCTlwK6CXVIjWLAUGv+4AUpvWy4UBV8vJUEcetldIFhBSXfBVevwqibHQEIOfJSeJFDpU3ikxde+vYFvhsKTYNAIR3a17QprBHSobuCqEbZGksnJwXOxGDjaElamvQPpmxZSF/6HxQqhL19nqzj06fDuherSPkjlD+bmuBprifF//79MCO+A5yEzo+yhZdXTtOfqco3pbNqXwnhxcUFwm3vgoUFDg651NouXoSfroqCWsBxTeElTx7I47dDHCO3pvCSrjQn4WUay+fP1YUXPz+o730ClBkEBqpnMFu8GL44shiAOatF521V6tSBG00Gwr17uH2hmeO/YEEoWGU/bNoEhSRKKetBNZGYZOZ1bQ8+c3Nx15bwQTA3B3urNDBP1lpr0sICUnbsx6pGJZh0kcyw1wcPYNq2apDgTOnVmhFDGvj4iKFRiALp/adOkBGIQ84otszlWFmgxJzYBDGyKdPM6uYG+watgV8n4jZGd9HBnKG0SiU8jBMT3MXEGCZ45c8P0z7fQ8DqaUTUag9bdJ+/Zp8rx2mP2S5BLXpw6ykP0qnLkxMGCiDOzqKGUYdZ1xDKlhX/9PHbDBuY2xVqzwBFHv0ddFCtpgXnr4j/X7loPK8cf60DGxtIeZlB8/59WPZXIqwOgT+Wg5WOuhXvGFWh+BW/4k+eT95h1xC/FbF2jRmCoFDbK+bPhxinIKJHzNRaaLBPH1hq04mlnTepPVQvXYItadXZfTNYt4+bNh8QE+sT5coFg6oeY6TVGE2zTE6kxs2UfkwRXvT0/d//4Gqp9lxtPJh6OXJ0qdbrMcVyFBwM+S2uUs7/rsZbYY0asKHCWDaUHKlh9lEN6ZZyt3FwgFDHx4Ta6oi+0RVtpCdUOiAADg7bxBXyMGNytonxxAmovLwPlSP/Zo42a4auEG0DsPJRMYW85NEjGLevIuMS+7JZT7K3mzeh4oahhJ/7j/79xX+HTviK0PgzDBok3SeisDklOE6diLtqt7eVFVQMi6ai4oD2xIovqVwZ/ij3LyvCh1K7tihIBHvEE8xNtTwwunB3h97tntMo/T+8Uu8ThyNJL7R/T26e4nugUql4lY9czScibtVOUrHk2DrTfXf0Ym4uSpEq2rGpC9z4kWFMWmRcwZ2pv5uJNb5QsGqCFmeq10Tu3BDhcIvaXqfU34Pecy1G3rywrs9WTlMUd5cM6r5YRd2ZjeVajSYgCy8WFuLTTYfwEh4OpTlC6eBHavZkQHwF0BdtJIGqU6i27tu2wW9J3fjtQCk1f01BgBfWLjx7rtAqvwwaBCdzNeBk1+lERGQf9/KCn1ufZETaMBrUl34LHTECHC8fxfH3sezN+ZKrp9ZPFhIPkR4zCtGUlXTpZ2TOCsSony2fz+FAQGsN7UcWOswZ48bBxTxNOdh8IrlzGz5uaCi0Cj3GFx6r1T5HQ8cFRCHCxCgMKysoV0ZJHq7hosxWvcTEwL6oMPYlleD2bc1+K1dC45i/qTKvEwcPmjBnyFaNmJgV2doaDtwN5HpGKDcjDdN4zPnTjOOutdncYZHxZtiX5M8PPapepnnKIgIDRS3bzQnLuUkof801wuQVEEA8jjh/1wtn4mjaSnsSs9//MOOKXTGejJquptV7smgbMTiza7kRoe4vhRdLCwFL0rVGI742ctQJmrzAkxH8yM8LcunopONab4H//Q/Otx7DlqCvqPgmayi9ZhwcoGFDKMIZbl16wRZlLbZcDjYt8OIT57ULLyNHjkShUKj95dMI/XjP0COA/PILHKEsR75bo6bGBwzzW5HYKEaOhGf5K5DUYyDly0t3W7oU+ieOpv/GWmqS+dy5YLdrA+5r/mKhFvu9vz8Us7pAMZ8H6uHdoO57IkFqKiQo7UlIs9HQUkxf5EJH/qHp6OKSmogZMyDi/BIilg3XEHw2HHZnNU3Zst/4uEAPD6hdMIry6Xvx9dVsT02F+HRb4tNt1aogq+HqqjtZnASlSsGSJkuY4yG+xWtF1xufhwfK5BQSH6snFTx3Dnrub0vPW4PZtEnHtTMdbXIkE9PFrVuwNq4ae6PCNVJKPH4M/5wtxj8JzTh6VMdF3N3FN3OVjS0sDHZ2/pedbp/Tv7/uOXh5gUIh4MJzbM2ScXSENkUu0sZyhe4SDR4e2vPaGPpm7ecHUVGazhfGvJlrTSikSXg45PGJwz3xjtoQzvbpOBOnpjnURWQkfH1vEM129+HPjRI3+psgh/DyShjxmb0y/v7ZoewfSqg0ZNuOTM1ULgO8Ic1LREQEDx48yPrbv18zbfr7wpAhEPDiKp7ff8lVUzSdJjrdOjiAq0Matmlx2rPrasGoFP8mmH68vSHC+hoR7g808g/s2mfJfDqy+kSgpBzw+DFcTA7j4nNfDeWMfabLywsdC9ZlRtFRGfrPP8Fpxyqc1i5g8WIt19anAdEVoq1F0xQdDZujCrH5WWmNPC6ZBPRrhhWpVKiqrra7fRtmXKrKjMefc/Kk9mll2TpUNphq1SC1V39SCxZn1CjNLqomrJwWq8hI6Lz+czo/mciiRdqHPXzUjF/shvPN/CJZucccHKBayC2qWR8kb14dc0ZUasbvPc1z3Fj8w0V8fWFRm3UscvxKM6JLFYmsr2lpcOauG2eEwlo/ZzX8/cWY4cemJzETXN2IdfDH1TyW0hyheFE9G+RrEALi4mDqhRqsiqnOoUsu4sE3aAo5cADKnvqDkPVTmfIy4fa8H++ykXos/DHS+AtmCi9vw3zj5yf+ANPSmP6nNYP4mUH/FnrjzsKvzEvhZW67ncTY5iJm/EwxIk7GKN6I8GJhYYGPj0/Wn4eJoYNvg5gYuCf48STRzmhBYP9+GBPXh+G7q3H9unSXUaOgcvIWKk/7nAcPcjTqqRPUrRsscfySJa1X469SM9LPD6r6XKKeyyE1BzCD0SO89OsH50Mbc77Tr1kFHTNRVeVLyRFWVuBoloCj5QuNWh1blzzjPr7cmbdTctxdu6DfjT70O9aOM2ckTnB2FoWIdCOTZ2WixQdk2zaof/B76h8bycaNEv105JfZtw/q7RxMvfO/sHKl9LDpgjkZWJhc9+Z2ig+7qMqS1TZZ96iZGViaZWCpSJesidKiBTxo+TUvylajm4mZ2jduhMHxw5l4qLx04j8DsA9/qT0wJqOoRF6bx4+h6JgWFFWe1J7gTgXB148nuHNh78vrmPBmPnqMgsCEizzPcGYYPzFutJYEdJn4+Lyy8KL6e/5rqz9z+IKVm4zMdGsEGRlw5ElubqX4ZjmQVi2ZQD02U6OUlvTdOq6lWLpE9Hopa0T1U1Px9xe/1wcPWLzSil8ZxK9r87z3SpjnaQ4cd6jK5p1WpAkWONumGv0CK/OGoo2uXbuGr68vNjY2lCtXjnHjxhEYGCh5bkpKCikqmos4bfnu3xDu7uBn/gBrRysUipw2Id3s3AkjHvWFR1DuGpK+FJcvwz5lRbghoaDR43RbujSUtl4NhUPBuUnW8apVoWrTaWIURxPpV/bISIhOLg53Ayico5ZQsd7luctjfGo6cF5b3TYtT4CRI2HI1ho4NquFV55vNdq//Ra+XV5FnHydGWptAeE2wANA2nn1xAmYEtUCoqDSdc16I7dSfYmhCML+RIpVVfeb8feHWu4nwNyCXLk0M6DduAFTzn5BzN14aufIl3L/Pmx6KNakaSy1x2bml9HjXKuNIhHp+O09i39YIJDtMVqpEpxs8iNcu0aurvO19v/uJ1sWsQv+gCtfi5FVWWiZj6MjOOZSwHlNf5XgYJhRZzUcP06hFqO1jitVAA8wThDw9BQlWgPV++fPw+Qrg3j6TEHLRdC2reFDqVK+R2EO8wSz1gLPasPo5aWAnynwt4IuXQy7hqogcUNLZeZM4uPhZEZFoi8/IvhIduXyhbt8EWiH+05r6rXTP6abG+z77QSB/ZoSrLhNN2EOxaam0uxLw+ZsLJmRk+6Kp5ib53j+GXmvv+3CgqM3FOM0y4n73OmD8t6cOBHGJOyChbDR6l/qvedOxu8rr/0rL1OmDH///TebN29mxowZ3Lx5k0qVKhGv5c113LhxODs7Z/0FmKRKMJ2xY+Fe7mrc6DqOwpppSwAxF0pH/qHj3CpqtYQyA5XAeJ/dO3dg8dPazL1aSbN+kCraHvZ6BJ/Jk6HCw5VU+Kebxlvz03grnuLB0+fGf/2BgZDX7TG+wn1N52V9ZGp8TLT1Fuhfm2KcpsNXmmHWjRrB1hLfsbXyaGpJZH569gymnavK/JjPMiN3DSI5GSr/1oziGUfp3EHzzbtAARhZ6D9GBs2jXDnpa2xel85xSrG6j7rGydkZinncpZj91axNRAqtQoQ+tPj4eHtD9+JH6e68mAoVtHevUweWVp7O7oK9afgyV2FyMlx85MHF9DyamkQppNLs63hYP3kCf12vwppnlTl9Ovu4nR10q3iRboo5kt9vTrz9RC9XpVJBZCT8uqUwvzKIVasMmPNLChaEGkHX6MYsCnJe57yvXoWqawfQ+tZ4/v47+3jHyUXpwAJG/CpRiVQChQIq1ncikLtYmunR9LwGcueGlHmLeCJ48PPIV/fBmD4d3J3Tmfjrm1d/bD7mzn98zrZjLkz8MYl9VGTf6D3vvRZD1UR0S5DtRaby2jUv9VRiXAsXLkyZMmUICgpi2bJldM1ZtQwYOnQoAwYMyPp3XFzcWxdg9Pmt7NoF6+gIh2GiymnNmkGBRT9g42ZHkQrS1Wrnz4d/VzvBuHFYBPXKOn7kCLQ9Jno8/roVyfo0WbzGUGmAYP8MLKNv4O3jgc5Ktyb4nujsa2kp/mkxV7VrB5UWfAW+voRXG6HR7uKYwYsUc5NqHKr6gOTcz9u0gcbL20N6Grad1HO1WFvDgWueKPHC/Lxmro6ICIgovErcnMtpeaV3dBQdQKTsRgZoc2rUAItlC/H2URAUJKoi7t2DjefKwVMPih+HkiUlOr5ClBOIG1vuMrdh1RZ4afm9dAmK/9EL6EWPn8SsyLq4dAnW8w33VodRuhD8MbM9xFaj4TgYOlTzfFWHeNWPy8UFZrXdA4f7Qnf9aogyZRUkb92Nf14HFAqpD0c/JUvC9qE7xazQelATMKMFpDJIG0xAACgUzCo+C+WxE7j1+wUwTitsKGZmYBX0Mqro/n0ID+fOA0vSCcH8gRXGbq09e0KPHhZvxeXFP9gcjoj/7+muJJQDUODZK330b4MSJeCLiENE3UohMjmYhcfy0DiHdlxGP288SZ2Liwt58uThuhanEGtra6xVVRjvAhOdbsPDIdzvpBitpCV/hIUFoEgHc6Xaj8oQp9uEBEhRukKiDS4ZOdSytrY6NRjVq4PVP3MgogDe3uqv13vXPAe/3DBhPdBAo+/KlbDtwXDYHsSAa+I61XBy0i+8SHD+PFyzbEniviAatkUjL0quXJDL8SJ4Jkvmt2r9WRKJ8+bhU6c2IFE1V4dJIjAQDn+3Ftex3+A5+SKqt761NVhbJYIiDXK4FygU4OKQTnycgLmg5U1YnxlFodAdQaOHBg2gQZmV4g0RKAovly7BV7vbADBsrabwkpEBa28UJuZFK5yXptEsZ5ivoaafV3RCPX0aBt/sCcD/dsLB2/6AP/m0+IiFh8PZYctxH90f99/vYKpyeOhQGLp2KOTLR1rEPPYNXgc/T8B1nHHBA4m+4bRhDQDFfzJn5E/S53l5wTeNruK9djYFWw8DRLPm1C/PI8yahVeP0eh8UVDFxgb8/Oic8RdwEupqGfR1kelQd+8ehIdTqUtu7hBJrq6pRJng7/y2rCDjxysYf7Q6vo1KYhU85O0M+hooXhzmfHWcVv18+FXZH+bDrZ9k4cVY3rjwkpCQwI0bN+jQocObHsp09IRKz5whMHFdHhgzFlfXFuqNJoZKFywIv1Veid21M5RsIBEugpj9d97zazAaLrYV81eAmHaj1/IWvHhWgvJj4TsJpU/TptD065+gVmcIyGEb0OOwe/gwzIxtA2egzQN14eXJEziTVI74qAzyXdYsgLhvH+x/0BlOBtIqUqWWE6JKeWbSAlgCJwdDsWKSw2tl0s/pMK87NF2FpPACWp+c1tZQpngacA3M49CQjnRs5vd3XsW6ZEEUs3QUqtP3xJaIoHn2DK48DIV4CLiHmlO2Bt7eouOOgSgU0Pz3qghUo8zPaTRTqSIhCKI5BcEMhUo2WK3jxseLEratLW5u8L+iJ+HqVcqVa613HqpKVEN8dm1soFBhBQj3ITkWbHPUcTBmZ3xprrK0hIrhD4EDoC1XjxbSAkJZR7D4/8e0h7FYWcEvgx/D2olQsAuZwkuvBrdg1nRoPMzgMWNi4KTb51y/pKQkAsWNm7LxZGbYNLSC9ntCcDAQooCoW+94JiYQFgZKE+tfyABvwOflm2++Yc+ePdy6dYuDBw/StGlTzM3NadOmzese6rVw9CgMvduDAUdaas154esL4Vwn3Cfe9CR1OR66wcHwdfljfGkz3+hNPD0dVpzJw4aMuhw/bty4wCul+D94EGruHU7Ts6Mko2t27IDvHvThuyONuZbDGdig0gS6zCg66vVs2ACNT4+k8YFB7N6t5dqZ2cO0mVK0jGvj5SQqzUxMnbpvH3zxdDxNV3Vgp4rby/79UH79d5S/+CfztfvriuTQgBQoAHOrL2Su/wjJFP1mZuBkL2qKYp6rC2aHD4PFz2OxuHmNb/RULIix9+MyeTm+TfzMgoJgbuO1zHX9BkPeRyIiYEnnzey3qMr8fwUyRo8jw91Le1ZgyLYdmRqelYm/v2gKedVrvESvsirTdvSKEUe7d0ONs5P56sUU1vHZG1dlHDxtxzjbH+k1vQC3bkHjqrG0ZSFNq8a80XFfCyEhcPMm128oOEshzt52fu+jjQAIC6ML85hGb6Z9vsfgWmsy2bx2zcu9e/do06YNT58+xdPTk4oVK3L48GE8pQqZvAecPg3jb4mCVcQ5NEKDdZGcDI/ScpESI+CipVbL9u0Qmf4/OBBBm07qae6xs9Ppt1K4MDSw3AJhYTg4ZIcyqZmckkyo+KvH9+Trr6HNsqZQuTLhxdUzkanO39jAsPr1wWPRVOzDfAgJaanRHh0N9+LzwpMAwp5LFE+0tBQ/Mwkh4uZNWPtYzPbXUtt+lVn599kztWJSN27AkXuVQamk9HWJqLFM+5bEuKtXwxcrZoJSyeiZ0u4RkZEwN1r0eK15STTpGY2PDzx6ROqLDKxszfHzg//lPwRP90Nxac3d2L4PMR/7Iz49BgKm1a0p0qsCd7iMZ+c0HknVVtKDqyu0avQC/t4D5k/EW1Uh6L5lVYWXl1/Gw4dQa3RLSKtIrYFixIZe/PyyhRcTd7S1Gy0I5QaRhNHzKz2/tdckvKjWOTtPQVJStJagei1s3AhjXgyDI/DZZZg6+B4saQ9DjqHVHv6+EBICq1fTsbcjhzgL/UH59buelAEEB1NXsZVEYR9WFQtg6VTlXc/og+O1a16WLFlCVFQUKSkp3Lt3jyVLlhBmdNXBt4equ41W64+WB9+OHRD03yTynFzCzJnSXefMga/Sp/PVkmqaL/x6/Fb69YP1jm1Z3/k/NfW7szPcmb6Ox3iw8m8dqkct8161CgaaTeKr+RUlX0z9/KCY9UWKeUdp2GFDQ+Hb8nsZ6zReo/4QQOvWsDqkP6vrzdLQKFWvDt+GLadPyHrJWlD//gulzs6l1IaR2rUnLi7a6wTp4Vq8DzupxtL/LNQ+mt27od2JAbQ79Q27dkl0dHAQVRkS46akwNNUR56mO2tVwGlzQg0Nhf4RW+nvs5hSpbTPW6mE8FHtcFDGUrmi4Rlje36VwVfMpnHhm2rHHR2hgt8tKtgcJ0SL9S0Tb2/x+k9iLLLT6xgrCGRqL+7eNchB+cxDb9byGfMWZ2d4TkuDc1HunKOQQQXt0tOh+YrWlI3bQtPP0sQEd2Qn2zOU2FiIfBkm/fSZHg2IgwPY2pJ096nmZ2WE9iQsDAY2FCscrqAFFZu+2TxZahW0VS1H73kIryDA7hdlmPf0Mw4de9M1FF4vk6Zb46OIxoFEjt15OyUVPjY++arStWvDjupjsH4eTe7m0yTPOXUKnlATLvhSJVW0b4N6fSKTAn/s7EhLSiP9hWSRZRGJjcLMDAICFcBT4AWZ9nVVRoyA+Q/2w1RH1rYQfWwy2b4d/kjpDUehWzRai0pKERQE45ocgQvjoYpmnpd8+SCf824ISZV+aTPR2Rdg1iyY8XQHsZM8mV8DtZom//sftFjWAlxdcWo2W7J/7x892cpOmAB1vtV0GNbG/gMKTtgMJmZFBF81Ri2s2cEBcjtEQ0Y6zs7STiuVKsGZrlNx37IIjyHZcdoFC8KkMkvFktk1tZtVzczgeZI1iVjyMNrA6sSQrbrKUY66YEHY334m/Pcf9NGW6EekXkNz8p5egHfNwqSlFc42m5qSZl+qCJMEQ37xZAtrYQo0GiYKfwoF2FmlQWoq1tbSFdxVsbCAvVd9eEIAlpuVrF7fHGhO4/6itsxQMrVwAdwhI0P3D+XHnxT8mvyQ+CGOHKgI5cuDonEjQKBs/TQO6TPxvsTODn4dmcBv69PJeAuP6Fq1YEWtWfjfPkDez/8FIwW8d4VCAc2nVeEZNQHoxizxga7NH+49QqGAh0rxAXnjiRNaKsTI6OCTF15y5YJcQTfgxWXQIgAPG65gA9tgEjz5LvtN2tcXPs97Drv71yhWrJlk3+7doc7Kr6BVK9zcsu0Fz56Bd9/upGf0pF4zJRs36VCCaQuVBq1S05MncDMjCGLEuj+q6KuUrHNcyBZAdL1F6/Jb0VJCtXhx6O2zAlxcCA2tqdH+/DmcSckHKZpZ3+3swM46BmzMQIsg6OGVHa71+HG28FK2LEwpOAcEgXLlNNPRrlgBU5LGwXaofVNdeGnQABp8NkBcUxfpzMHOzlA4fxosvaCp/zcw8V2+3Bk8PXGdYD9PwIOMDEhNswClNRZpSBfvc3AQVYtG1ETKyaifzGDuYCjfDWwLc+kStJ/zFTxpTssJYnkNfaQ4enDLrhjHlllx+0l53F88J/8eqKJFU57LL/u3EB39MpGkHyROmg0DBsACwyIDQ4Lh6Wkl5mYC2spd6aN6dUio0Rj7HWuhq+6rWFhAvOCYNW9VjLZahYVRld0oMSNP4TIYHKlkAqGhEFr5MUzdDC5vbJg3QmgIPDsDZgolvwu9sey5AhTvv/ASFgZeNnHkTT6Ns40RLyQyWXzywgtgcqh0/vywvN1qMdlFC2nhpVo1qGb+D5QrDA7ZwoutLaRniA/pF4km+K3oEV4cHMDT7AnY2GJhof6m+uWX8Nm6bjjl8yWs1EiNvrduQVRSUbgfRME4NKv7OjqKtoykJDSrPurByQnllWtkSGy4NWtCzdDJYgrZIprCi4sLWCnScLFKJCPDRfPaenaIhg0hYP0MPEoE4eJSP+t4RAREhK4X+xfUFF505YgxZFxA3IETEkRJ0sr4jWj/XiXYF4A+/wId2L4d6s7+DYARY8TMxxooFCjdPXl2OxGHZHVNoVG7aUBAlj0hKQlOPvAFfClnYMb/n0YrGJN0EpZkHqnKFwu0Cy9NmkDohmn4FPLEy0t/RJM21m2ywCXUjZRhoxm8uRrs3UeROl8ZdQ1ra7D+719RXaknK2NwMOS2f4C/1UMcHYsCUCbPM7h6lYi8RQAjTBsuLmznZTa+CVGAkb8zY/H3FyX65GSaDgjhEfvxHBjG6t1vdthXpXc/C+K6DSCkSVFY/q5nYziffQZV8kSx/Gxl9s2GOz9gWqmXTxhZeAG9EUOtWwkU3/gTfNYIW9ui6o16nG4ByY3CxgZK5I7B9vo5CuUpgdRXMXEibI9fBnNDmd1G/ebedcGLx7QgY6U1bQpoDjlhAkxYWBS++AIKj1Rry50bcvvdBIsYyWfi77/DxHtLYRHs74lmFtaXXrtCXDyKHMJLbCzEp3hCggseOTbMo0eh1rzJxKdaM2Ao/Pqr5ti66NYNvtrdEcWjh/C5tJZDlxajTRtoM3kehBUBz/rqjTo286ZNIc/y0bh4WlGy5GCjxwXUK0NLlcXWh52daAYyIpx1/Hj4PuoWyonmbKyBpI+SQfj7Z8U5KxRgaZYOSiXm5oYJYarh8obQuDE0nrZGdLD2zCG8GGGu8vZRQIgv1g+uMLOdpXgz9zBOeAFE1Vnz5npPa9sW2h6dAFu2QK1LABz+eZ8ojU15hFaVoBYE4B7+WD02wzuX8dM2iky/pKgojl/y5x4V8Lv0/msEOnVWwM+bwSIaMLHm2TtAoQDBwUnt3zLG8Z4nUn7zJCfDpXh/TseFanUEbN9O4EdG8GOz0xpVlvUVV8wix92pUMDxGcfZR2Wm/qBZfwbg3DnYnF6TzVdDNYboNSGQVizjq3F6cmDqMt+Y6PhaoE91nImhYGXN+L6JEyHg0lYC/hnNvn3qbTY2EJdqi4CZ9kglHWYUMzNQuLpIhjpfvw4rHlZixd0yuh06PTy0m1G0jFukCLTNc4L6drslI8oM4UxMEOtoyMK/s00P27ZB2IrxhJ1czqxZBlwkICBLiHBzg2q+V6jmcCzLpSQn9vagRDSVqS756lVou641baMnsWCBceMWLw6p3/9IakDurCrE+ihaFNrkPUlP54X0KH2Cvx376K8vlCuXVvOiUbwMpX1rZH5Wrxivu307OCoSCOQusxfkfOi8fhLdAzlPBGsXJXwYocaqvO3v+DURXsiaMhymjNtVU5SxnzyfvPBy4QIUmDuQYvfWMWGCCRewsxNDIdKk7eEpKfBCsOFFqrnmQyFTEjKh1o/Dy5DlhBcS1zUEJyetsc6VK8MAl78YUHKvpJIgIcWSOJz1R1/kwNUV8no9p5TiOFrqdOrHzU1SeNm4EVqcH0GLg/05cEBHf09PTYcZQ9BSkfrkSeh/sgP9r/Vg717t3TuNy0sj1tFlREDW95WYCJHxXkSm+BmWQkZFiChVCnY2nsLOPN3p3Fn69JAQKOV2g/puh9WErsePYfGlYixO+EytfpAUDx9C1XUDCbu8weCChjkpXhwW9TnE9KQu/NFgA51sl1Fen4eijw+qxZPi4uDnbUX5OX0Aa9caMXjmxva2duSAAPGLNTEnUCa5ckGiIGo1L19/8wry5kNyU4jzNB5WmOP/XiIDM26vP//Gx30thIbS/tQACnOGwl9Xe9ezMZix05w4TDkOd/0Tr/c8Iv195JM3G6maNYwNlU5Ph1q/1COJw0T8T+AviURj7dvDirRY6A93P8+RRVWP38off8Bvq4Jg4EAcc/dVa+vdQ8nTr/rj0LUNSmVp6YquWub94gVcT81LXHQqHlcgb1719kaNoJHHOKjeDEIqa/QPD1ViF30ZHz8vcmaqjYiAz523gocnXl7qsdIBAXD557XQuTMMTiGnE+KcOTDp9CK4aMXv7cSaPhro0pwYgocHHDlChkq5hT//hK/WiRX75vwlRi5poEV4uXIFfrsqmqBCTouCnxQ+fhacuQhp6WY8fy7KYFZW4GkTB+kZ2ObMJJuDW7dg2t1+3L2tpPafojVQHw0bQsN2U8Ty53VN24gcHGBPpGiv9LuSDliYJgiEhooC/r17hunIfXxIf/CYxFhRSRgTA0PWVAAq0HKheI/qIzkZlj+tz82rXnjuzk+Pt1JwRyXVvqurSaHSoJ5r6MHjN1+uOTS3GWwT///WA2t8EMDiw7BlCHnyciClJLcIAcMC2t4PLC3FCDxdVVlltPLJCy/u7tC51HmsTx+hQhXNwpG6MDeHPRc9EfBCkCjapxc9mhc7O7BTxIJtCuR4fnX8wgq++g3KRIC5Zma99evhWNxA2FWC7t3EN7lMLlyAUgvFMJGeU8W0/cawY3MaOOWH7xYD6j4JrVpBq7GDxF28iEToeab3b3y8egIUxBwol18EwwvRtzUn6ekw81QFniR+g/ukNPoMyHaArFgRfs09ExwcKFq0veS8IyOh+l/DeBIzihZfwLx54nFByDavSCEIkGjryZMnDpjdwSStUdv2ZpTfP45cdYtgZSUKO/Xrw6NWfeHaNeirS10kflyTzopOzHb7DRNeAFHTlEPYK1ECIr8cB9u34zR0h87u9vbg6piGMj4RezNz4KXKz1hBINPxJTJS76lJSRDyY08eJ/anaqN0du4x7TGlUECnJXURhHqwBGZwkur94LffTLqcQUzbnp/DLCCqnS/bT0Hn30oA/xL+qy3Dxxt+HWtrmDoV/pqVxuDv37xNoUoVSFy5mVDPBLzd8urv8J4gCOA/6guiXhYls7N+KWB/KJisgpb5gL7lN4OPD8zrtAfODIAO0sJL2w5m7CAavnbiSpPs6BOFAuysM0hMtkCZLv02WrAgPP1vF4TnwdpaPU/EqFneXGYRqUPz8J+uenFSG4WZmfhaLLXLI6bLn5kwAPZA04fqwotq9JDOLLnaNigHB1Fy01WxWFeYdebAOYQXa2twNo8Hc3MsLDTt/Obm0H9RSdIpTbF5qfTJLkZO8eJQPHC5WCEvv7TwYm8Pt2NcAHj8KLvyr6cnlHK+Cgrw8NDMRHvnDgSP+w74js8HCixfnr22WrXgUI0fIDaWoBbSeYIAOnYEJiyAgGhwyOEsbIAgoFYj6FYGYG6YBiRTeFFmFzGysYEQl+dgec+gYsX3jkVjly8QfthEdHRdFh8pB3GWFN0lRtMZRHAwGZjz/MpTzJXO2KWoJ4hUxdYWElKtEDAj+r7ohOnhASu7boB//8Vv4FLpjjmwtgY/rzTuPRQ3/3MUJrcBCe5ehW3HnFlHOzgnuuws2BMAdKDczjSGG3mtPn2gT5+3k3ytVStotWWZWD3Vb8ZbGfN1oFCAp7cZUU/BgjRiFm8BGr7racm8BT55nxdAfMqlpmrdDGJi4BHePIqz1Tjl8aYTKFFwfLF0sq8RI2CnRR129lur4ey5Zb89S2jDygPeZGgpWKwTBweTEr55esIXFS8zgEk0qKel2JyujVGhEFXiuoQXbWTWJ5KQmvr3h5hStYlp34cGmsWuxeLMLuJmJmk50rOZu7uDu2MK+blIkFe2tqtJEzhacQBHqwyWNEdkBgoBPHmYodFW1v0aZZ0vqQmIkvj4mOyE6uwMuyef4jphbJgWycmT0HxLN5pH/sKyZTo6eniIJaZzOmcbYfqxC/URBZ+7d7l7FwZsq8+AmOGsWmX4/Gf/Y40F6XjeO4Xb4yv07av9XIUCSkSkUIqjFA+NEedgB02LRNLUfK1RJTwmjBOYgVizwZYkrQLT68I/IPuR+qplld46YWEQGcm/692YQXfmr/8wCu5UqWFJbbbQkz94kfrmTWwy7wey8ALZji9anF58vCGESEI84zUq8Nq62Yrv77qcbrVsFHb22ReTitQ+dAgWpX7OolP5pGUUBwfSYpMkBZ8+fWCLWxu2dFigEarq6gpzep9hIgNp3VBTczNmDITe3knozEGcPKllTW5uGplbs9CxMY5bHEQX/qL9IC12Xj2b6qyxz9hIPVYNPy19gg4thoUFPNlxlotEML3vVZ3jqGJnB7VLPKUlS6lVWouqykA/DlOFF4UCqnzmRBiR2Dy6w8OHsPJmMVbGVOfyZe39+i4uSyPW0Lr9KzzULS3FuRtSFloLxgrne7elcJQyLPhyj3qDkeaqtl2s6R60GcHZhSQLZxYvNm4exjJ4MFwu0oqEtt0oVQquTd/KNXKz9E9pDel7RWgoPH3K0Gm56MkMvv/DhJD+d8CUqQq2+HVlCv1wsvtwwqVlXg1ZeIFs/bUW4eWvORlEEkbkr6uyFAdZGBoxJPHQnfe3gpsEEz1xoWR5gBkzoN2LP2m3qKHGnjd+PNjcOI/VxHFs367Zt0ABqG29h9rhNzWTzIG6+SYHT5/CzfRAbsa6S34k+/bB17E/0nF1M44cUW+bOxeqRs6l6so+nDih2XfVTmf+pguLtntpl1N0bFCNWttRj82UcDMxNDJTPaISyaJvXIUCtvx5l6W05rtWN0wb9+XYGVEPsyx9ly7ByFONGXnnf7ojpDJRrRFkIBuPebGORmzZm32DPXsGGyPzsTGxik7BR43AQLhzh7AwWNp0CUs9emmNcpIif371f+fLp6eDi4v4u5T6nowlXz6T0wIYS3Aw5M0jYB99A4UCcudKJDc3CPDTouF8n3hZgy415UOLlUYz6kDmo+eTF14EAcr+UJNCnKVZGxN0yq8Q7hwQZEawzUO8LZ9paHT0YW4OKYI4Xy1uL7rRIbw4OICX+RO87OIl086fOwdTH7Zi/o3yXLqk3nbzJuxJLMWe++GS0aJOLqIGQBAU2opa68bRUdQE5LAbTZsGNrs3Y7P0b5bryrTp7S1KI8ZuiqpJ5lR4+hROPAvmRFw4j6TT9QAvgwpmjcLq+gW+epkn7dIlGHW2KaPu/o+DBw2Yg7W16NNz5w7VqsH99kO4X7ge/fpp7+LrL95YcYnmWdq9CxegwcquNLg/m7/+0j/s/fvwW1pPem1txPbt0LLAeVrab6B4cQPm/JJKlSBj9lwEFAgurvTvr6eDQiEKmlFRgOis/SDGlgeCj/HWSr2S0msmKEgMD/vA6D2rEIHc5kmCLTP5ikkDPhy713xFR35mEL+sen+LAMu8Xj55h12FAs7dcSKJQnBDS8SQDlPGpgNORNKTpMX+9K+tmUH8l1/gcPpSmFWUOS1Fa4sadnZo28U7dIBSywdB3Xp4elZXa/PzgyKON3CwSsXJKb9kf50mGB3Cy48/wo8Ly0DLllBynEa76hqM3Uj+mGlGekRhnEcPws6ug1rbgQOw+35nSPemxVWxSoAGCoUoSKiWZ0Y0S6QIViCQVYlYEktL0elHRXjZtQv+Pt0PzMz5Yp+40WqQ6VycQ3jZtAk6bBcTBE1bBr17Sw/r5gYPE8S8HffvmBYRERsLZ9ybcn2LH6WaQiH7WLB6AlKatZf8s8Acm4hQvMb2w9xGh6OJDh48gP4nxO8qdRu09DKsHpMq5uZAxMv71NAcKC+1PSBGHocM/wL4gtY9Mcr8ExdUiCuUJD7dker6T391cucWhRcdfnTvI7GpNtxFjH4pxyEK19blzf9+Me1aXY7RCcXfAoMMEMhlPnw+eeEFwN5GCcnJWFsar4iaMseOLUyHBdDtdzTMSocPw0qawWmYJlWBwNFRq+qkVi2oZTkLKvqAi/pjt21baLvqW1H4qLVFo+/DhxCXHgJP3QiUiOxo/X0ox7lGymf+3DUyZ1uNGnCw2a+4XtiP3xer1dpGjoRhq4pD1apYVpuk0TdPXgU43wdFlIbeb88e+OFed7gHha9ICy/JyfDIMYInF20IepotU3h6QlGHa2BpiYtLsNa579sH/yknEfV3PgbUFIsyXr0K/94Xw5Cr3dAivNjaiuFKJuaYcXSEPAFJON89T6HA3IAbFSrA5hq/QHQ0eT6fqPcamzdD60szARi7HgoZsDGGhCrAzwyis9+ig4Lgx/Kb4epVytXWL9Co5hy5fiVdulq4IeS0Heng8mWY/GAEt8/a0WKulpw/BiAI4DygKyBGEq5aLTpov0lOCsW4pGzNk1Ex5Df3AmrhctKC0rXe7LivSoECCpzME4iwvEpyso3+Du8Rx+6IVXUF4cPITSPz6nzyZiOAhzsvkIgDx/++INk++08zBvIrAxeX1MgnZ+eQ/WMx1nJ06xZsEuqy/GRYpnZcGl0hy1oEn+HDIc+Tg+SZ0osrVzTbo55Yc4Pc3Htioz05n5ZxPT2hXIFY8r04lVnmKAsLC7A2S8PaUqndFObiYlqkEqIfUNDVbZRYOpht27KPt2sHp0p241S976lTR3v/c+dgypN2LL9RgosXDR933jyokbGFwuPacOpU9vE8eaBX2GZ6BayhUCHd17iy/wlHKcO0DkcB0YJVx/ccddyOEWJAIdzw8Oz/v3795f8YogFRMb+AqNAYVm47wzxmUFOz/qUGLi6wcNR1DlCehT9c5kmSHU8yXI03V7oaHr0SFwezr1VnS0xZjh9/GW1U+DpNzddQqpThQyoU4OOV7S3855/GTNg0ukwtSnsW0m+sF3V+qkgdtjJg2JtP8f+qDBwIMV0GcDC5BKU59q6nYxQTJ4JCIdCxnSlhmzIfIrLwAijsdfutrFxtxiQGMmlzAVJzWJZ69VLwr003VnRap+nMi5g19r7Cn/vj5+Ptrd62aBHUvzOTlpu6cPSoCRN3dDQpVBrA3cscd54Q4hEvvWx9b/WmhkqDpNkHoEULWBc+gHW1p2ndoFTDzR8+zNFogCZCtdxBpuWoVSu4UvlLrtTsRdOm0v3u3oWdyRU499hHTdAsXRp+LzaX3/NN11olWW1wMzN0F1/STng49K1zhan0oXGtJFbfKsLq51UkhVONcXNKx0aaM9r2cqU8h7h74hGev32P592T/PCDcfPfuBEUoteL3vwwqrm7ou4p8fKClf/bwErrtgwYoL2fFJ81yn7Mpb+FYJTw/G8nN8vrxsoKFBEFSMSOBOxJfPHhbA8DBsDz5wr+ni+HSn8qyGYj0JumXxc1agDOayE8COw+02h3cwMUD8AlSSNLrqrWQutbrK5NRofmpWxZePHvcsibFxeXwhrtq1YrwCkUhgwH12/U2jZtgsPP+8HeCL68l6OkQSaurqLglJaGhlevjjk/ewbnFVV4etaNAjlKE4SHQ7jLfgiMBy2R1HnzQpPQs/g+v0ChQm00T9CjiahUCfZ3nE2ubf/iO1DMDOjiAi7298X7QEIAhWx/XSuzNBISJDYnQzQgFhais5KJwoujI0z5KQ62/M766K9pvLUnAKNXwPffS/eJj4e9KTWJuniX4G2iKdIk3NzED+oVwqVV5ScNwTMH3t5wdNoRgvs0xOO3I8DLeH8TUvxPmaqg3p+iVOo7yojkNCbSrr2CMgcmElbcmf3mVXBcv4iANt8AH4BQExFBGDd4iA9BzVO59eH47Eq+PMp8vMjCC+iNGJo4IZ1h26rBsOHY20vYJAypLC3x0C1bFkbkW4qjEEexYl9qtLdvD4sSYuEbBdcaZ0UyAmK6kOHbWpAYVYJyv2s6inbpAl2G9oEWfSBQU3gBtGpAtmyBKTF94QDUvy8tvFx6EcwDqpG2Ip46bbI9eI8fhzPPm8GFAtSLQqOw444d0PLIzwD8vBYGDZKYl44NqlQpWNVtkxgrXl1CeNGDuztUKKeERUfAwnDH2c6doePeL7C/fxVFKx0VGPWh4oSakADRcZ6QnI5HTHbmZp1k2o6iooDcOk8FMVKo4Rrx3mr/bw7hxRhBQKGA3LlxeXSVhrkvwf0oIiKMc0Tp1AnmzEjj4mUzZszQ/YasUECpWi7AE7hzG8JCdZ6vC1tbaGq1UXSgLWPyZQymaVPgn32QnEyzrq6wfiR07AvYv/nBX5WIiHc9AxkZg5CFF2DNDgeuMIgXC8IYUk+9WCNARAEBOAh5Hkt/YoYILxKUKgWlSm8U671EaAovggACZiChyEhOhjnHiwHFyNivPcpFJ69Q5LDqDxV5xE4CBqRyR0WGWLkSxkX9CFGw84qm8KKarVZCbjIMX18xYuXFiyyt2bZtsOzKN3DPnq+OQ8mSOvoHB4v2g6gog2uL2NkBfs5wSkJlYKAJ5sIFmBo9ijsXHWj9j3jNlmtER91f54o+B3pxcQEPD/KlnmV8qcfw4AGVqmn/8lU///t3xLICBw7AZ9N/grThfD1KzAKtj/R0uOldkRuX0xhZcTsl9kyGL/XXKVLF0hIOH7ckJUXzNyZJ5neTGXb8KpE7CxfCqFGm9zeW8HCMSkH8nrD9Qi4eviyb4eYk+4/IvL/Iwgswd74V6/gZVkKPOIkHq46HZkYGvLByI+mpOY7Ze2kWR47AA2UjOB1E3WSJa+tI8R8WBqXNjoG/P9bWuTS6ZRIfl12nx9B5A1qFl+7dof6SjlCtGnnzdpHs6uMj8Og5PHxqgWBE5Gzu3DCwwmE8Tm+jfP1ham0xMRCb4gPxbnhJfJZZZO7IDx5kFfw7dw7+jBZrmtS+aYDwAuKmGBjIvXtw+XERsLEh4gHa0/z7+YmqDJUFr1kDQ7dOBqWSYYuhjQ5lUEwMzL4haivCT2iJajIAIXc4Dvev0DVfJB6KA1Beu/Di6Ag/dLhNwPwxFOz+PRBEejo8TxG1jYZaSs+ehRIbJgPQgZP8q/jNpLkrFAYKLiDeAP7+cP06Dx5A+z+aQXJRaoyF774zcuDPPxf/3hbh4eL9JZU6+z3m+InsH3L/Dk+AAO0ny8i8Qz4cj6w3iK1d9g/WWLeXKVPA8dRevOf/yrp1mu3jxkFTVtF0Rh3pJJ86QqV//BGO2FbjSL8lGqYbV1c4PWEL1wlj/h/GO+1GRsLYB10YcLQ1Gzeqt+XLB7Vt91E79LpWU0b79goGM4Fxn59QS/3etCnMyTWcOTWXSCa9DAiAXzuc4dvkUVSuqJ6Q5fffIfjsWoKXjGfnTh2TzxRedIZoaee+RRA7qcZf/1qQkADr1kGt4+OotX+EWgSTBn5+Yk4eldw4sbFwKT6AS4lBetOXqJZpuH9XSWAgtA/eT3uvrQZHEe/cCc4ndpBrxTSmnddfFVGhgJ9GK+jGHMq7iOFVtrYQ7vKIcKtbapowXRQoAOZm4vd1NsqAao6vgWfPYKNbe37bkJudO2HntUB2ZlTlgnRQ4PtF4cLEZDhwYMvL36YJvjrvAtXEg5H33nw1axkZU5E1L8DXX0PLjZ2xa9EAT88WGu03IhXEUwTuuFEo42XCrZfYqURAmuDvmxUxpFN7IdFgbg5FCgtAJJjFkDNT2dixsPbZRpjlw8LW6v4yILpdfH9aXKvlHqifo9CxtnEzGfSdJfw8DooqwCI7NKhUKSjl+h8USgDf1tKd3d2ziwUaET6byZBZoWzhFFEN8nHrgfgddOwItRd1hly5CKitmVhPlZETbPmTnTAXivUyfNy1kQW5QT+SRyYzdLLoHWhpCU4WYpJBKyvdPg0+PnBg2knC+9TBY+w+FPnzUabCTDEDW/3aBs0hKAji00SV1Okn/uBrwKbo5ydO9KZYUqF0abjaZbzo3PSNYZKAjQ10a5uA64JpFHcy1d5nHIcPQ4Oz4nfZev1bGfK10WZiSZYQA/MButOobRprNurp9B5QrhzsaDSFYmtH4tpuPeCtr4uMzDtB1rwA5ctDc5cd1As4ryaMZNK9jwXFOE2x7+truLYEBkJ1z3M08TqAn59m344dYTxDGN/sqJqpB8Q9y2t8f2wf3aJtWxMmnpnqViJkOTISjqSX4MhdP0mhyl3l5dmUCs2AuBvrCxuRIvN1P4fTS4EC0NJ1Gy1Dj+us0Hw72oozFOVxnE1WuLOHBxS0i6Sgyz29UQeZViMQ9/MSJeCH0EX8kG+FzlwtQ+eFM4DJ/PiHR9bH06YNxDbqSGyN5nTtqntchQLKN/PBkycorhleGFKVkBAI90+iLpuoZLbfsE7m5uKNelOlHpQJ/iN//OtIe/vVzLldm7oP5jF7ttGXMApVzV1qikDi+GkkOngbVNLgXePjr/5eGBP7YWheHB2h+q/1cfW1k+sFybzXyJqXTGxtTVKd1K8P9T/7TfTGrHlYo71ZM4CfoW5usC+t1mZjA48TRGnJJL+VTK2FCflWQkNhVfcteMwaQ9Dw3ajKsY8eQWxaMDxzJ0DKTycTb29p4UXfxvhSckqPfoKFSvrWZs2g2dihojRRXLvTiq+vAktSyeWUSHx8Ds2NAer5ypXhm7zrCBFuULRoP0JDoXT4v+KTu5h2vwi/QHMuXoPkVHNiYnIojQw1C+TKJWbqvXZN/LeRQoSZGVw9l8pG12m0vL2MkXe7MvJX+OYb3f0ygsO4fyEe64do5BsyGIWCmLASbDlbF15AAUOLOppIUBB81+o6eZb+RNFu47G7lA6KF2BCCbK3TdmyUMr1Oseei/e3b64PoDBjJuHhom+XjMx7jKx5yURHxFDDehl0Zwbda1yTLFSIk5NkjSA1JDY3Jyfwd0+iMGcI8dVMcztjBnRKmU2nRbV5LJHC/9JjD7ZSiyXr7DSSb/35JwieXghjx1GwoGZfe3toUjOBisI+Ahxj1NpGj4Y8UbvJM6M/587pWJO3N0RHq/m8pKdDitKSlAwLrTWGmgwKx4Xn2FYtLX2OHkFg7FhIrlKX2/V6ULSozlMlqVQJfml2iJ5JE9X8UPTRb4A58x16sLPrQkkNnUEoFGJa3qtX1Y8Zg4sL6V5+JOJAotKOtDTdp2/fDra7NhC0aSZ//JFjLsaiWivgDWNhAWPGKOjEvxQx03Ujvn+0agVHByx5mZJPweK5ptiUZWRktCFrXhADAmLM/XjxyB6PeDRS3n/dKwMG9YT/LQSbcM0LODsj7Y2rGysruLvssJjp7tvrgLpjyt69sCSjHRyDUYnq2WUBvhntzEa2wiSo8a1mu15UKyVrVIzUzdGj0GbLH0TH2/H1MFGgAPjhB5hw5Qxcgd3NkMw6m6y0IhYbyBCVRu5G+n/a2AC5Q+HMmaxjd+9CZEwReOhDgccGfBYFCoh2u7i47CKVeqhfHwg5ANZmYN0uu8EI7UlsLBxwaMnVHQ5Efwu7t4yC1FT6LYHWWlyEpHAM96Hgo3Nga4enp+5Kut7ekKYUf+qRkaLS5/fdTeFBCWqth4YNDR+3VG1XHqz04ZprGUqOWWN4R1MJCREl7bNnMbr0+rumSJF3PQMZmY8WWXgBZs2Cfic3wElY2ARN/xN9m5OJwgvwSqYfV7fsh/nz5xIbtiGh0iAKLypVEEuVgg52/0FYGO7uRSW72tpCZJzYX6VAs0GEhJkRuuMm/oFmJCUFGS28AKIH8sqVWf9cuhQGnZsG52DFXmjeXE//zPCey5dFD1ZDBRB/f7Uss2fPwvorzSE9jbon1aM1pLhxAxrs+xYAq8kCqamiJiM62rDhM6lW25JzBwqTUrAi1l/s03luWBjk8Y2nQNR2Khapwb17Tkw9XRkA+4PGCS+t//uctXTA8nkaMW/j6WFmBkWKEHf0MivNPoe0doTuFU1/7z2lS+s/R0ZGxiQ+sFeZN4OqI62xxeYSEuDzhU2onbiSgf01bSAtW4ID8Tj07iRp+snSeDx7ptE0aRJcsS7Mle/+kXQGbtwYhjlPYVLNDaYE7RBv48lF8rN1q3rNlw4d4F+PAfzb+D+tZpXAQLC1SieC8/h6ZBd8Cg2FKrZHqeJ/Xavj7IwZcKNIc/bUGUeAShqJv/+GyldmU3ntQA5rug+pExYmSmym1lfKlw8lCm7vu8OMGeCzezE+6+awYoUB42ZVRYSTJ+H7i+34/mpnjhlQyy4iAizMxfskNdV0J85B5ztShNPkO75A77l2dnBlx31W0Yyvih83eUwASzcn0rAiCXvOnn2lSxlMRpHi7D1sRZeldemSPIM5c97OuK/MS+eidMyJT/gwHHZlZD4UZM0L4n7U0O8UTqmPCQnREbIq4SNgZQX/nQgBQnhxOI2c8mByMiTiANoqN2dKHRLCS65ckMvsOnjHSpZFadECWoz7B8LLgmcDtbYdO+DSi65wqARtn0lbhToO9GQ1F2EU3OmKmiChbb2ZODtD4o4jKCpVhE7nANGxpls36Da5EzRoAEV/1do/pwYDxPDtfQnFIUG/TLLsRgnOMJrH/0tn9irxJXeI/wJwdiFPHv2qhPHT7PlJkUDSN3a0agUPU8UPSF9OsbTQvNyctYv4oxmUKG18EThra/hpUDy5xvel2JQuFD48W1S79NOV2EaTEw/9OUswCOLnpjdRcO7c4s164QIlOlXnSKtJcOwYuXosNmrcipUUnFp6mfIcxMbmf0b1NYWnTyFg7mRepH54j6ozZ6Doy/TYboWUPNX8icvIyJjIh/dEeANUrQpVm/4lOpnU0hReuvaw5AjnYLA/x5qoZ361sgIbqwySU82Ji9E0PQQFChTkPPj5YW6uKUEsWufIPsUMnv1Skt9rmOC34uoqKfgsXAjzEsfDOqjxUFp4CQjMFk7u3cshvBhgRlFk1pu5eRNJr2BdBATAPt3mDl1MXRPEAb6H1TA5UTQjVA6aKUqihfQLL46OkCSIXrd37kCwTTSYmWFv76W1j1IJLkO7k5TWm4IdUzl32ZwaNWBtmTGQlkahOiMNmvu3Y51gzgaINd35tVJVC/bszaAop3n8uIR+4cXCQsw+eOECTk5Q2vs22J03OoFqz57Qy2yXmIQl4s0LL25u4OQo8OJlVP0fNgPI22XSGx/3daCqeXz2XFZyy8i8TuRfVCZOTlr9Vm7dNuMCBblwz0VyT7+24iwxOHNqsWbs6LRpcI7CnBu1SlKA2LlLwUyhO8tO5pb2e9AnRHh5mZZrBahQATp6beK7gmvx0r5na8fHR/SejcxR48YQ/5GAAFFiUuH77yG1aGlSv+xFHYn6l6qE5c2WuzOjjgGDI2iKFwdfxziaWm/gh+8FblbqyM2GfcSielowM4NAf9Hkc/2mOUqluIzPch3nM59javljdKJQQLFiYhVLE+v19O0Lz0dM4cS3KyhRwsBOERFw/rze6CRdKBRAjx7wzz+mX8TI8T5rbE4T83VMtB9OF6uFVK/+VoZ+ZYKD4cuuShzsMlhsnIJLRkZGD7LmJRMdTre2tgIOxL8Mc9G03/iH2wJxEK/DaVfLpqrqq5LTVHL2LDzMqA5XAqmordZPrlwIJ0+RkiMfy5dfQo3l3aFBA3x9P5Mcu1UraLX6X1H4CWuUdfzXX2HFw9Xwlyfz2qA9db1CIT6hVZOfqbZpISMDhh1syN3nfnj2SWPSNPEzNTcHc0U6WAh6xepu3aDZie8pGviMwCIzdJ8sQdmycH/hHmjUCAreMrhfvYYWFJ66jPDqYaSmljC8Tk9OKlQQJduaNU0KWXZ3B0YOMPj82Fjoe+U7Dp6yoXArJf8F8MGkrJ8z1wzuThOrb+rLQPieMftPM2bO/vACpWRk3nfkn1QmmblaJN6E169IIR4n4uf9J53fI7MAkAnOo716wYlCnYhsPogyZdTbxoyB2mkbqP1HE0ln39u3IWjeCGyunuHLHEWpy5WDdtYraFfsou7nvYTvya1bcCS1OEfuB+gsln3+PAxMGUOzpa2yCuguWAAtoybTcm17Ll2S7mduDtN35mMBHVi/zjTNQ4UK0LhWEkHXtmfvwUZoMRQKsqNBjhwxuO+k38xYmmc4o/P8my24mKA9ESpXYf2zcpRe9wO/32v8xp1fHRxg9ZV8XBdys3mTwNHoQI4lReRUfr2/ZIYXaUse9B4jCy4yMq8f+WcFpKZC/ZmNqKDcS9dO6ZonGJIxVqEQU9Ma2Tc4GIqHxRGScA5rIzOHurjAnRhnUrHmwX2J8vWGbKohIaIUlDPLnQFERcGkm81YFV2OgwfFY2fPwvL4eiy/WkS67MBLAvzETejBIzPT96OiRcXIn7g4ZsyAwOP/EbhiIps3G9jf21tM43rokPhvQzURRYvCiROAGG12J8mDO8leRkWqtZpeic9Yz7EXhehztS+7dxve1xTMzaFsOQXWJJOUbE6ZZQMpfWMxM2e+2XFfF0L1GqRjTnp8klpSRBkZmU8TWXhBrFm39ZwPB6nA6dPGv0VfvmHJEocv+G1loEah4z9mQA/+oMf8cto3Nz8/yXTczZvDMPOxDKtzVDKPmpMTBHq9oBBnCfNONHregFi/JC2N1Ku3sg79/jsI/gEII0bq9KeIiMj+/2uXjdtRZv9pznmr4jz98Y+sN9Pjx2H246bMvlgxpzJImmLFxP+ePUt8PNxN9eFuortxVR6qVWP/6id0vTiAQafbcfKkAX1KlRJjpNPTWbYMgrb9SdDOeUb5NRQr+fYttvP+MSe2ZE22VR/71sd+Va65lsaSdCxJp0aNdz0bGRmZd43s84L4wu1kn8HzeDNSXuhQA2h5M58/H8bGz4ZNUOA8+Ppmt23cqGADPWA3jE5BozgjoFV4adkSWnb8ERo6gYtmwiuFAm7vjISCRaD3fqBCVltSEqQpHSHZGocclbBV6flPGTYRyYOigcQnIl3+QAu+vrB+4hUKDaxFwPCVQEm++w76rKgCtWvjWep7rX3LVzKHCODq+axj69bBj/eGwT3YfFEidDsHyrz5OW1Tnq1jMniYD3wtH4OlBTY2hiW9EQTo93AoU29lJ+grdll/ojlKlYIXL4g5fJnMEHFjadwYpk+Ixyv2Gi38DlG7thHlrU3E1xeoUZGA2evoU6g8REVRtqwpFUHfPtcis2/gGzfe4URkZGTeC2TNy0tubLpKKpacn39ao23xMnMmMJgJa/JJWld8fLL/39hMqYIAZzIKsvF5WTas1JNkRIqgIPG/OZ7oPXuCS8wtXEb2U82ppsHjJHtuEUJKmrn6JQwJlVZAg+4BBJrdR3FKVFm4uECAZTQBTrH6nVkLFBALWprIzLmWlEg+wNDNVfD3h/slG3O/1UDq1TOsv0IBx58aUdzoJWN3lCE313CtVBBLS2jhu58WufYREmL4NQoUgHtnn3OSEgy935t8+Yyehmk0akTe54eZajmQqX4TjMqu+y6pWhVCAsQwqdGj3+1cZGRk3j2y8PIS1xBXLElHyjN29t+WfMsEvl1cRFJ4qVwZJhZfyII8P2qkLZ/6m5JTFOXUyDVaHWfLj6lPAzbyzSCJr0OfEOHgIGpuVAv9GUGRogrszF5QyfOSTudcrdjZieYb1ZwthjqwFikiZvJ6+aE2aQJ/BYzgr2rz1UxS2lANmd26yTRHiMbNReWjC8+ZWfJPatbU3ycFa24g5mhJSoJlJX9hWYmfDeqrht7kLG+AMmXAywvlyVM8Tf9wInfs7eHUOUsuX4ZOnd71bGRkZN41svCSiY+PaDMxyNlCnSJFYED107RTztfI9REaCkU5Q9Gg51hIGOkUCgj0Ezfem3fNpf1m9TmS5s0LV66oHSpUCOpY7KBOnps6KyD37w+xvb5nr2PDLHPJ7t3we0Jnfj9aWrqkQU6qVhU7qQotBji/3gmrxsLExgzs/BRBEGWgLm5r6FLgCP7++ofNmxe6NI1hOj2Z3ty4DLWZfPkl3Ju5jue48VXqNIPy3TRqBGYKJVXM9uHjlqq/gy7u3n2rdpCUdHOm5p9BXq7Q6faotzbu68DZWfzOZWRkZGThJRMzMzFs+M4djaaffkhlFU1Y9c1+7T4hYWFivpMUbXUAtNP5CwuGWv7CPy02qEXefPEFeKfewXtoFw1H4Ezu3oUBT76j4ebe/KqSjX/gQNjs2ILNX6zQ6Ttibw8W5UuLieZeDrJsGfSJHU2fTfUNCqV9WPozfr/XmIaV4zhzBtYmVGfttfxSiX/V6DGnGO1ZyKSF3pw/r/tcKRQK+GulCz1LHiP3+t9MCll2dQW/zi+zKuub8EuKF4dH+6+xW1mZxhYbTE40B4j3nLYCUm8Ac3OYeO0zrhPO5sRK3Lr11oaWkZGReW28MeFl+vTpBAcHY2NjQ5kyZTh69OibGuq1cPs2/GP1JT9tLMGRI+ptFcum04Q1NCkVpdXxlcKFxexrOZObGLCxDfnWjLElVtJKsQwrq+zjsbHwCG8exdtpDSe2tITJZ2uwIaEKK5bkSJ1q6KZau7a4q61da9j5OeizvBJ9+J0N+51p2hQaP5hJ41WdteZ5yaReg+wPM2toUwSB7t3ZszGR705+zncnmnPxopH9ra3F6KEdOww6XaEA93J5oHx5MaOfIHwwCd8sLKBVO1ECd1M8Z/v2dzwhGRkZGRN4I8LL0qVLGTBgACNGjODkyZMUKVKEOnXq8EgqD8p7wpEj0PnKUIafa8GuXSZcoGBBErDnyOoHaiHRFy/CAcpz4JqX7lQqxYuL+UZUNm8vLwjmJsHucVqFJh8fyJ9bNF14Kx6bpgRwc4Pq1cmY+zdnTgt07gwLXHqzoPnKLH9gXXTuIt5G5qTz5LHhSVuaN4deta+xl0oMrXeatDR4obTmRYaVcbk82rfnkHtDxqUOZNzZBurlAgylWDHIk0f/eZkoFPDdd6w/6EqV9d9QfM9kNmwwYdx3wI8/QpuWGeQr60JtHXVIZWRkZN5bhDdA6dKlhV69emX9OyMjQ/D19RXGjRunt29sbKwACLGxsW9ialo5flwQRMlBEFq1zMg5KbFh2TKt/X/6SRAUZAggCNOnZx+vVzcj67rPnumYwNatggCC8shRISlJ5bilpfoFJViyRBDO5G0hCHXqqDe4uAjCL7/o7Jt1jaGnhXxcFMzNMoQlSwRB8PUVhFGjDOqrVApC2+bJwlGXWsL2ogOFsQ5jhLGVNwl37hjQOS1NEHLnFoQKFYQfvk3L+qy2bjVo6CyWDT8nBHFTAEFYu9a4viajVApziv+RNec//3xL48rIyMi8h7zN/fu1a15SU1M5ceIENVVCL8zMzKhZsyaHMjOZqpCSkkJcXJza37ugSBEY0uE+G6jPnMK/w/79cOgQw/53HwdvO9bQiPvPbLRqNurWBeGlIivwyjaxQvWhQ1gnPqcpK/VPoFo1lGHhjGl0GCdHJQ3KPYUDBzCkil6rVlD4pxawZQv06QObNqFQgCLmOZ/91VQqhYwGFy0Kc5n8ZCjNODpuO8aki1UoYOEKa0qt+o4a12cxNOF7hpbeoTdPCyDaMf75R8xQN3cuwUjUSTKAfJ8X5KmtP15u6RoRX28MhYLQER2wVoh+TrlyvaVxZWRkZD51Xrc0dP/+fQEQDh48qHZ80KBBQunSpTXOHzFihABo/L1tzYsgCKIKoXXrbBUMCP2YlPVPO+s0IS1Ne9fP6qcJDuaJQjJWWf1vEyDM5gvByiJdSEzUPXzbes+yxqrO9ux5zJ9v2Px/+UUQHB0FAQQbkrK6R0Xp75qWJgjt24paoms+FcWOM2YYNq4qly8LwldfCcKePcb1O35ceFKzldCfiQIIwtGjxg/9/LkgJCcb3+9VSEgQhB9/FP+03RsyMjIynwJvU/OiEIRXCZXQJCoqCj8/Pw4ePEi5cuWyjg8ePJg9e/ZwJIc3bEpKCikqETpxcXEEBAQQGxuLk1RO/LdBVJRYpDEjg59meDBvtSvW1tB3oCU9emp3zHzxQswS27LqI4iJEYsmASt3uXIn3Zd+/XU7dd68CRPGCxw/nEbRPC/488coUa2RN6/hDqEZGXD/PjVbe3AnyoK2nSwZOcqwvoIAp0+/zLqfkCCGIr1lR9RRI5UImDF8uFzQTkZGRuZDIi4uDmdn57eyf7924SU1NRU7OztWrFhBkyZNso536tSJmJgY1qxZo7P/21y8jIyMjIyMzOvhbe7fr/3d1srKihIlSrBDJexUqVSyY8cONU2MjIyMjIyMjIwpvJHCjAMGDKBTp06ULFmS0qVL89tvv5GYmEiXLl3exHAyMjIyMjIynxBvRHhp1aoVjx8/Zvjw4URHR1O0aFE2b96Mt7f3mxhORkZGRkZG5hPitfu8vCqyz4uMjIyMjMyHxwft8yIjIyMjIyMj8yaRhRcZGRkZGRmZDwpZeJGRkZGRkZH5oJCFFxkZGRkZGZkPCll4kZGRkZGRkfmgkIUXGRkZGRkZmQ8KWXiRkZGRkZGR+aCQhRcZGRkZGRmZDwpZeJGRkZGRkZH5oHgj5QFehcyEv3Fxce94JjIyMjIyMjKGkrlvv43E/e+d8BIfHw9AQEDAO56JjIyMjIyMjLHEx8fj7Oz8Rsd472obKZVKoqKicHR0RKFQvNZrx8XFERAQwN27dz/6uknyWj9O5LV+nMhr/Tj5FNd68eJF8ubNi5nZm/VKee80L2ZmZvj7+7/RMZycnD76GykTea0fJ/JaP07ktX6cfEpr9fPze+OCC8gOuzIyMjIyMjIfGLLwIiMjIyMjI/NB8UkJL9bW1owYMQJra+t3PZU3jrzWjxN5rR8n8lo/TuS1vjneO4ddGRkZGRkZGRldfFKaFxkZGRkZGZkPH1l4kZGRkZGRkfmgkIUXGRkZGRkZmQ8KWXiRkZGRkZGR+aD4ZISX6dOnExwcjI2NDWXKlOHo0aPvekpGM27cOEqVKoWjoyNeXl40adKEK1euqJ2TnJxMr169cHd3x8HBgebNm/Pw4UO1c+7cuUODBg2ws7PDy8uLQYMGkZ6e/jaXYhTjx49HoVDQr1+/rGMf2zrv379P+/btcXd3x9bWlkKFCnH8+PGsdkEQGD58OLly5cLW1paaNWty7do1tWs8e/aMdu3a4eTkhIuLC127diUhIeFtL0UnGRkZDBs2jJCQEGxtbQkLC+Onn35Sq4Xyoa517969fPbZZ/j6+qJQKFi9erVa++ta19mzZ6lUqRI2NjYEBATw888/v+mlaaBrrWlpaQwZMoRChQphb2+Pr68vHTt2JCoqSu0aH8Nac9K9e3cUCgW//fab2vGPaa2XLl2iUaNGODs7Y29vT6lSpbhz505W+1t7NgufAEuWLBGsrKyEv/76S7hw4YLw5ZdfCi4uLsLDhw/f9dSMok6dOsK8efOE8+fPC6dPnxbq168vBAYGCgkJCVnndO/eXQgICBB27NghHD9+XChbtqxQvnz5rPb09HShYMGCQs2aNYVTp04JGzduFDw8PIShQ4e+iyXp5ejRo0JwcLBQuHBh4euvv846/jGt89mzZ0JQUJDQuXNn4ciRI0JkZKSwZcsW4fr161nnjB8/XnB2dhZWr14tnDlzRmjUqJEQEhIivHjxIuucunXrCkWKFBEOHz4s7Nu3T8idO7fQpk2bd7EkrYwZM0Zwd3cX1q9fL9y8eVNYvny54ODgIEyZMiXrnA91rRs3bhS+//57YeXKlQIgrFq1Sq39dawrNjZW8Pb2Ftq1ayecP39eWLx4sWBrayvMmjXrbS1TEATda42JiRFq1qwpLF26VLh8+bJw6NAhoXTp0kKJEiXUrvExrFWVlStXCkWKFBF8fX2FyZMnq7V9LGu9fv264ObmJgwaNEg4efKkcP36dWHNmjVqe+nbejZ/EsJL6dKlhV69emX9OyMjQ/D19RXGjRv3Dmf16jx69EgAhD179giCID40LC0theXLl2edc+nSJQEQDh06JAiCeHOamZkJ0dHRWefMmDFDcHJyElJSUt7uAvQQHx8vhIeHC9u2bROqVKmSJbx8bOscMmSIULFiRa3tSqVS8PHxEX755ZesYzExMYK1tbWwePFiQRAE4eLFiwIgHDt2LOucTZs2CQqFQrh///6bm7yRNGjQQPjf//6ndqxZs2ZCu3btBEH4eNaa88H/utb1xx9/CK6urmr38JAhQ4S8efO+4RVpR9eGnsnRo0cFQLh9+7YgCB/fWu/duyf4+fkJ58+fF4KCgtSEl49pra1atRLat2+vtc/bfDZ/9Gaj1NRUTpw4Qc2aNbOOmZmZUbNmTQ4dOvQOZ/bqxMbGAuDm5gbAiRMnSEtLU1trvnz5CAwMzFrroUOHKFSoEN7e3lnn1KlTh7i4OC5cuPAWZ6+fXr160aBBA7X1wMe3zrVr11KyZElatGiBl5cXxYoVY86cOVntN2/eJDo6Wm29zs7OlClTRm29Li4ulCxZMuucmjVrYmZmxpEjR97eYvRQvnx5duzYwdWrVwE4c+YM+/fvp169esDHtVZVXte6Dh06ROXKlbGysso6p06dOly5coXnz5+/pdUYT2xsLAqFAhcXF+DjWqtSqaRDhw4MGjSIiIgIjfaPZa1KpZINGzaQJ08e6tSpg5eXF2XKlFEzLb3NZ/NHL7w8efKEjIwMtQ8KwNvbm+jo6Hc0q1dHqVTSr18/KlSoQMGCBQGIjo7Gysoq6wGRiepao6OjJT+LzLb3hSVLlnDy5EnGjRun0fYxrRMgMjKSGTNmEB4ezpYtW+jRowd9+/bln3/+AbLnq+sejo6OxsvLS63dwsICNze392q93377La1btyZfvnxYWlpSrFgx+vXrR7t27YCPa62qvK51fUj3dSbJyckMGTKENm3aZBUn/JjWOmHCBCwsLOjbt69k+8ey1kePHpGQkMD48eOpW7cuW7dupWnTpjRr1ow9e/YAb/fZ/N5VlZYxjF69enH+/Hn279//rqfy2rl79y5ff/0127Ztw8bG5l1P542jVCopWbIkY8eOBaBYsWKcP3+emTNn0qlTp3c8u9fLsmXLWLhwIYsWLSIiIoLTp0/Tr18/fH19P7q1yojOuy1btkQQBGbMmPGup/PaOXHiBFOmTOHkyZMoFIp3PZ03ilKpBKBx48b0798fgKJFi3Lw4EFmzpxJlSpV3up8PnrNi4eHB+bm5hrezg8fPsTHx+cdzerV6N27N+vXr2fXrl34+/tnHffx8SE1NZWYmBi181XX6uPjI/lZZLa9D5w4cYJHjx5RvHhxLCwssLCwYM+ePUydOhULCwu8vb0/inVmkitXLgoUKKB2LH/+/Fke/Jnz1XUP+/j48OjRI7X29PR0nj179l6td9CgQVnal0KFCtGhQwf69++fpWH7mNaqyuta14d0X2cKLrdv32bbtm1ZWhf4eNa6b98+Hj16RGBgYNaz6vbt2wwcOJDg4GDg41mrh4cHFhYWep9Vb+vZ/NELL1ZWVpQoUYIdO3ZkHVMqlezYsYNy5cq9w5kZjyAI9O7dm1WrVrFz505CQkLU2kuUKIGlpaXaWq9cucKdO3ey1lquXDnOnTun9mPKfLDkvCnfFTVq1ODcuXOcPn06669kyZK0a9cu6/8/hnVmUqFCBY2Q96tXrxIUFARASEgIPj4+auuNi4vjyJEjauuNiYnhxIkTWefs3LkTpVJJmTJl3sIqDCMpKQkzM/XHjrm5edZb3ce0VlVe17rKlSvH3r17SUtLyzpn27Zt5M2bF1dX17e0Gv1kCi7Xrl1j+/btuLu7q7V/LGvt0KEDZ8+eVXtW+fr6MmjQILZs2QJ8PGu1srKiVKlSOp9Vb3UPMti19wNmyZIlgrW1tfD3338LFy9eFLp16ya4uLioeTt/CPTo0UNwdnYWdu/eLTx48CDrLykpKeuc7t27C4GBgcLOnTuF48ePC+XKlRPKlSuX1Z4Zpla7dm3h9OnTwubNmwVPT8/3MoRYFdVoI0H4uNZ59OhRwcLCQhgzZoxw7do1YeHChYKdnZ2wYMGCrHPGjx8vuLi4CGvWrBHOnj0rNG7cWDLMtlixYsKRI0eE/fv3C+Hh4e88fDgnnTp1Evz8/LJCpVeuXCl4eHgIgwcPzjrnQ11rfHy8cOrUKeHUqVMCIEyaNEk4depUVoTN61hXTEyM4O3tLXTo0EE4f/68sGTJEsHOzu6th9TqWmtqaqrQqFEjwd/fXzh9+rTas0o1muRjWKsUOaONBOHjWevKlSsFS0tLYfbs2cK1a9eEadOmCebm5sK+ffuyrvG2ns2fhPAiCIIwbdo0ITAwULCyshJKly4tHD58+F1PyWgAyb958+ZlnfPixQuhZ8+egqurq2BnZyc0bdpUePDggdp1bt26JdSrV0+wtbUVPDw8hIEDBwppaWlveTXGkVN4+djWuW7dOqFgwYKCtbW1kC9fPmH27Nlq7UqlUhg2bJjg7e0tWFtbCzVq1BCuXLmids7Tp0+FNm3aCA4ODoKTk5PQpUsXIT4+/m0uQy9xcXHC119/LQQGBgo2NjZCaGio8P3336ttah/qWnft2iX5++zUqZMgCK9vXWfOnBEqVqwoWFtbC35+fsL48ePf1hKz0LXWmzdvan1W7dq1K+saH8NapZASXj6mtc6dO1fInTu3YGNjIxQpUkRYvXq12jXe1rNZIQgqqS1lZGRkZGRkZN5zPnqfFxkZGRkZGZmPC1l4kZGRkZGRkfmgkIUXGRkZGRkZmQ8KWXiRkZGRkZGR+aCQhRcZGRkZGRmZDwpZeJGRkZGRkZH5oJCFFxkZGRkZGZkPCll4kZGRkZGRkfmgkIUXGRkZGRkZmQ8KWXiRkZGRkZGR+aCQhRcZGRkZGRmZDwpZeJGRkZGRkZH5oPg/7tEiOkQRd6sAAAAASUVORK5CYII=", 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", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -713,7 +710,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.9" }, "vscode": { "interpreter": { diff --git a/notebooks/rbc-simple.ipynb b/notebooks/rbc-simple.ipynb index 13cae75d..0ec3ddef 100644 --- a/notebooks/rbc-simple.ipynb +++ b/notebooks/rbc-simple.ipynb @@ -331,6 +331,7 @@ } ], "source": [ + "# NBVAL_IGNORE_OUTPUT\n", "rjit.stop_server()" ] } diff --git a/rbc/heavydb/__init__.py b/rbc/heavydb/__init__.py index e432731f..270473f3 100644 --- a/rbc/heavydb/__init__.py +++ b/rbc/heavydb/__init__.py @@ -1,4 +1,5 @@ from .array import * # noqa: F401, F403 +from .allocator import * # noqa: F401, F403 from .column import * # noqa: F401, F403 from .column_array import * # noqa: F401, F403 from .buffer import * # noqa: F401, F403 diff --git a/rbc/heavydb/allocator.py b/rbc/heavydb/allocator.py new file mode 100644 index 00000000..a837afee --- /dev/null +++ b/rbc/heavydb/allocator.py @@ -0,0 +1,18 @@ +__all__ = ['allocate_varlen_buffer'] + +from numba.core import cgutils +from llvmlite import ir + + +def allocate_varlen_buffer(builder, element_count, element_size): + """ + Allocates ``(element_count + 1) * element_size`` bytes + """ + i8p = ir.IntType(8).as_pointer() + i64 = ir.IntType(64) + + module = builder.module + name = 'allocate_varlen_buffer' + fnty = ir.FunctionType(i8p, [i64, i64]) + fn = cgutils.get_or_insert_function(module, fnty, name) + return builder.call(fn, [element_count, element_size]) diff --git a/rbc/heavydb/array.py b/rbc/heavydb/array.py index a10613f4..71a4b0cc 100644 --- a/rbc/heavydb/array.py +++ b/rbc/heavydb/array.py @@ -9,7 +9,7 @@ heavydb_buffer_constructor) from numba.core import extending, cgutils from numba import types as nb_types -from typing import Union +from typing import Union, Optional from llvmlite import ir @@ -58,9 +58,9 @@ def deepcopy(self, context, builder, val, retptr): with otherwise: # we can't just copy the pointer here because return buffers need # to have their own memory, as input buffers are freed upon returning - ptr = memalloc(context, builder, ptr_type, element_count, element_size) - cgutils.raw_memcpy(builder, ptr, src, element_count, element_size) - builder.store(ptr, builder.gep(retptr, [zero, zero])) + dst = memalloc(context, builder, ptr_type, element_count, element_size) + cgutils.raw_memcpy(builder, dst, src, element_count, element_size) + builder.store(dst, builder.gep(retptr, [zero, zero])) builder.store(element_count, builder.gep(retptr, [zero, one])) builder.store(is_null, builder.gep(retptr, [zero, two])) @@ -101,7 +101,24 @@ def my_arange(size): def __init__(self, size: int, dtype: Union[str, nb_types.Type]) -> None: pass - def is_null(self) -> bool: + def is_null(self, index: Optional[int]) -> bool: + """ + Check if array is null. If index is provided, check if the array at + position given by index is null. + """ + pass + + def set_null(self, index: Optional[int]) -> None: + """ + Set the array to null. If index is provided, set the array at the + given index to null. + """ + pass + + def to_list(self) -> list: + """ + Returns a Python list with elements from the array + """ pass @property @@ -165,7 +182,20 @@ def T(self): @extending.lower_builtin(Array, nb_types.Integer, nb_types.StringLiteral) @extending.lower_builtin(Array, nb_types.Integer, nb_types.NumberClass) def heavydb_array_constructor(context, builder, sig, args): - return heavydb_buffer_constructor(context, builder, sig, args)._getpointer() + return heavydb_buffer_constructor(context, builder, sig, args) + + +@extending.lower_builtin(Array, nb_types.List) +def heavydb_array_ctor_list(context, builder, sig, args): + dtype = sig.args[0].dtype + + def ctor(lst): + sz = len(lst) + arr = Array(sz, dtype) + for i in range(sz): + arr[i] = lst[i] + return arr + return context.compile_internal(builder, ctor, sig, args) @extending.type_callable(Array) @@ -181,6 +211,15 @@ def typer(size, dtype): return typer +@extending.type_callable(Array) +def type_heavydb_array_lst(context): + def typer(lst): + if isinstance(lst, nb_types.List): + dtype = lst.dtype + return HeavyDBArrayType((dtype,)).tonumba() + return typer + + @extending.overload_attribute(ArrayPointer, 'ndim') def get_ndim(arr): def impl(arr): @@ -193,3 +232,14 @@ def get_size(arr): def impl(arr): return len(arr) return impl + + +@extending.overload_method(ArrayPointer, 'to_list') +def ol_to_list(arr): + def impl(arr): + lst = list() + sz = len(arr) + for i in range(sz): + lst.append(arr[i]) + return lst + return impl diff --git a/rbc/heavydb/buffer.py b/rbc/heavydb/buffer.py index 4a472655..04b6c874 100644 --- a/rbc/heavydb/buffer.py +++ b/rbc/heavydb/buffer.py @@ -206,18 +206,23 @@ def heavydb_buffer_constructor(context, builder, sig, args): ptr = memalloc(context, builder, ptr_type, element_count, element_size) - fa = cgutils.create_struct_proxy(sig.return_type.dtype)(context, builder) - fa.ptr = ptr # T* - fa.sz = element_count # size_t + llty = context.get_value_type(sig.return_type.dtype) + st_ptr = builder.alloca(llty) + + zero, one, two = int32_t(0), int32_t(1), int32_t(2) + builder.store(ptr, builder.gep(st_ptr, [zero, zero])) + builder.store(element_count, builder.gep(st_ptr, [zero, one])) + if null_type is not None: is_zero = builder.icmp_signed('==', element_count, int64_t(0)) with builder.if_else(is_zero) as (then, orelse): with then: is_null = context.get_value_type(null_type)(1) + builder.store(is_null, builder.gep(st_ptr, [zero, two])) with orelse: is_null = context.get_value_type(null_type)(0) - fa.is_null = is_null # int8_t - return fa + builder.store(is_null, builder.gep(st_ptr, [zero, two])) + return st_ptr @extending.intrinsic @@ -422,9 +427,9 @@ def heavydb_buffer_set_null_(typingctx, data): sig = types.none(data) def codegen(context, builder, sig, args): - rawptr = cgutils.alloca_once_value(builder, value=args[0]) - ptr = builder.load(rawptr) - builder.store(int8_t(1), builder.gep(ptr, [int32_t(0), int32_t(2)])) + [ptr] = args + zero, two = int32_t(0), int32_t(2) + builder.store(int8_t(1), builder.gep(ptr, [zero, two])) return sig, codegen diff --git a/rbc/heavydb/remoteheavydb.py b/rbc/heavydb/remoteheavydb.py index eb52cc94..01057307 100644 --- a/rbc/heavydb/remoteheavydb.py +++ b/rbc/heavydb/remoteheavydb.py @@ -1101,6 +1101,7 @@ def retrieve_targets(self): target_info.add_library('stdio') target_info.add_library('stdlib') target_info.add_library('heavydb') + target_info.add_library('NRT') elif target_info.is_gpu: if self.version < (6, 2): # BC note: older heavydb versions do not define diff --git a/rbc/heavydb/text_encoding_none.py b/rbc/heavydb/text_encoding_none.py index 09cdb591..b760261c 100644 --- a/rbc/heavydb/text_encoding_none.py +++ b/rbc/heavydb/text_encoding_none.py @@ -5,20 +5,25 @@ __all__ = ['TextEncodingNonePointer', 'TextEncodingNone', 'HeavyDBTextEncodingNoneType'] import operator -from rbc import typesystem -from rbc.targetinfo import TargetInfo -from rbc.errors import RequireLiteralValue -from .buffer import ( - Buffer, HeavyDBBufferType, - heavydb_buffer_constructor) -from numba.core import extending, cgutils -from numba.core import types as nb_types -from .array import ArrayPointer -from llvmlite import ir from typing import Union +from llvmlite import ir +from numba.core import cgutils, extending +from numba.core import types as nb_types +from numba.core.pythonapi import PY_UNICODE_1BYTE_KIND +from numba.cpython.unicode import _empty_string, _set_code_point + +from rbc import typesystem -int32_t = ir.IntType(32) +from .array import ArrayPointer +from .buffer import Buffer, HeavyDBBufferType, heavydb_buffer_constructor +from .allocator import allocate_varlen_buffer + +i8 = ir.IntType(8) +i8p = i8.as_pointer() +i32 = ir.IntType(32) +i64 = ir.IntType(64) +void = ir.VoidType() int64_t = ir.IntType(64) @@ -50,20 +55,19 @@ def match(self, other): class TextEncodingNonePointer(ArrayPointer): def deepcopy(self, context, builder, val, retptr): - from .buffer import memalloc - ptr_type = self.dtype.members[0] - element_size = int64_t(ptr_type.dtype.bitwidth // 8) - - struct_load = builder.load(val) - src = builder.extract_value(struct_load, 0, name='text_buff_ptr') - element_count = builder.extract_value(struct_load, 1, name='text_size') - is_null = builder.extract_value(struct_load, 2, name='text_is_null') - - zero, one, two = int32_t(0), int32_t(1), int32_t(2) - ptr = memalloc(context, builder, ptr_type, element_count, element_size) - cgutils.raw_memcpy(builder, ptr, src, element_count, element_size) - builder.store(ptr, builder.gep(retptr, [zero, zero])) - builder.store(element_count, builder.gep(retptr, [zero, one])) + zero, one, two = i32(0), i32(1), i32(2) + + src = builder.load(builder.gep(val, [zero, zero])) + sz = builder.load(builder.gep(val, [zero, one])) + is_null = builder.load(builder.gep(val, [zero, two])) + + dst = allocate_varlen_buffer(builder, sz, i64(1)) + cgutils.raw_memcpy(builder, dst=dst, src=src, count=sz, itemsize=i64(1)) + # string is null terminated + builder.store(i8(0), builder.gep(dst, [sz])) + + builder.store(dst, builder.gep(retptr, [zero, zero])) + builder.store(sz, builder.gep(retptr, [zero, one])) builder.store(is_null, builder.gep(retptr, [zero, two])) @@ -102,6 +106,12 @@ def make_text(): def __init__(self, size: Union[int, str]): pass + def to_string(self) -> str: + """ + Returns a Python string + """ + pass + @extending.overload(operator.eq) def text_encoding_none_eq(a, b): @@ -138,72 +148,74 @@ def impl(a, b): @extending.lower_builtin(TextEncodingNone, nb_types.Integer) def heavydb_text_encoding_none_constructor(context, builder, sig, args): - return heavydb_buffer_constructor(context, builder, sig, args)._getpointer() - - -def get_copy_bytes_fn(module, arr, src_data, sz): - - fn_name = 'copy_bytes_fn' - try: - return module.get_global(fn_name) - except KeyError: - pass - - # create function and prevent llvm from optimizing it - fnty = ir.FunctionType(ir.VoidType(), [arr.type, src_data.type, sz.type]) - func = ir.Function(module, fnty, fn_name) - func.attributes.add('noinline') - - block = func.append_basic_block(name="entry") - builder = ir.IRBuilder(block) - sizeof_char = TargetInfo().sizeof('char') - dest_data = builder.extract_value(builder.load(func.args[0]), [0]) - cgutils.raw_memcpy(builder, dest_data, func.args[1], func.args[2], sizeof_char) - builder.ret_void() - - return func - - -@extending.lower_builtin(TextEncodingNone, nb_types.StringLiteral) -def heavydb_text_encoding_none_constructor_literal(context, builder, sig, args): - int64_t = ir.IntType(64) - int8_t_ptr = ir.IntType(8).as_pointer() - - literal_value = sig.args[0].literal_value - sz = int64_t(len(literal_value)) - - # arr = {ptr, size, is_null}* - arr = heavydb_buffer_constructor(context, builder, sig.return_type(nb_types.int64), [sz])._getpointer() # noqa: E501 - - msg_bytes = literal_value.encode('utf-8') - msg_const = cgutils.make_bytearray(msg_bytes + b'\0') - try: - msg_global_var = builder.module.get_global(literal_value) - except KeyError: - msg_global_var = cgutils.global_constant(builder.module, literal_value, msg_const) - src_data = builder.bitcast(msg_global_var, int8_t_ptr) - - fn = get_copy_bytes_fn(builder.module, arr, src_data, sz) - builder.call(fn, [arr, src_data, sz]) - return arr + return heavydb_buffer_constructor(context, builder, sig, args) @extending.lower_builtin(TextEncodingNone, nb_types.CPointer, nb_types.Integer) def heavydb_text_encoding_none_constructor_memcpy(context, builder, sig, args): [ptr, sz] = args fa = heavydb_buffer_constructor(context, builder, sig.return_type(nb_types.int64), [sz]) - cgutils.memcpy(builder, fa.ptr, ptr, sz) + fa_ptr = builder.load(builder.gep(fa, [i32(0), i32(0)])) + cgutils.memcpy(builder, fa_ptr, ptr, sz) # string is null terminated - builder.store(fa.ptr.type.pointee(0), builder.gep(fa.ptr, [sz])) - return fa._getpointer() + builder.store(fa_ptr.type.pointee(0), builder.gep(fa_ptr, [sz])) + return fa + + +@extending.lower_builtin(TextEncodingNone, nb_types.UnicodeType) +def text_encoding_none_unicode_ctor(context, builder, sig, args): + # Note to the future: + # You shall be tempted to use "context.make_helper", + # "cgutils.make_struct_proxy" or "builder.extract_value", but avoid it at + # all cost! LLVM -O2 runs SROA (Scalar Replacement Of Aggregates) and + # suddenly some IR nodes becomes NULL values which are deleted by DCE. + # Stick to plain allocas + load/store and you'll be fine. + + # It seems to be safe to use context.make_helper on a previous allocated + # memory! + uni_str = context.make_helper(builder, sig.args[0], value=args[0]) + + llty = context.get_value_type(sig.return_type.dtype) + st_ptr = builder.alloca(llty) + zero, one, two = i32(0), i32(1), i32(2) + + eq = builder.icmp_signed('==', uni_str.length, uni_str.length.type(0)) + with builder.if_else(eq, likely=False) as (then, otherwise): + with then: + bb_then = builder.basic_block + p1 = cgutils.get_null_value(i8p) + n1 = i8(1) + with otherwise: + bb_else = builder.basic_block + p2 = allocate_varlen_buffer(builder, uni_str.length, i64(1)) + cgutils.raw_memcpy(builder, dst=p2, src=uni_str.data, + count=uni_str.length, itemsize=i64(1)) + # string is null terminated + builder.store(i8(0), builder.gep(p2, [uni_str.length])) + n2 = i8(0) + + # {i8*, i64, i8} + # ^^^ + ptr = builder.phi(i8p) + ptr.add_incoming(p1, bb_then) + ptr.add_incoming(p2, bb_else) + + # {i8*, i64, i8} + # ^^ + is_null = builder.phi(i8) + is_null.add_incoming(n1, bb_then) + is_null.add_incoming(n2, bb_else) + + builder.store(ptr, builder.gep(st_ptr, [zero, zero])) + builder.store(uni_str.length, builder.gep(st_ptr, [zero, one])) + builder.store(is_null, builder.gep(st_ptr, [zero, two])) + return st_ptr @extending.type_callable(TextEncodingNone) def type_heavydb_text_encoding_none(context): - def typer(sz): - if isinstance(sz, nb_types.UnicodeType): - raise RequireLiteralValue('Requires StringLiteral') - if isinstance(sz, (nb_types.Integer, nb_types.StringLiteral)): + def typer(arg): + if isinstance(arg, (nb_types.Integer, nb_types.UnicodeType)): return typesystem.Type.fromobject('TextEncodingNone').tonumba() return typer @@ -268,3 +280,17 @@ def ol_attr_is_null(text): def impl(text): return ol_attr_is_null_(text) return impl + + +@extending.overload_method(TextEncodingNonePointer, 'to_string') +def ol_to_string(text): + def impl(text): + kind = PY_UNICODE_1BYTE_KIND # ASCII characters only + length = len(text) + is_ascii = True + s = _empty_string(kind, length, is_ascii) + for i in range(length): + ch = text[i] + _set_code_point(s, i, ch) + return s + return impl diff --git a/rbc/irtools.py b/rbc/irtools.py index 220b4a23..3c5436ef 100644 --- a/rbc/irtools.py +++ b/rbc/irtools.py @@ -1,32 +1,60 @@ # Author: Pearu Peterson # Created: February 2019 +import functools +import os import re import warnings -from contextlib import contextmanager from collections import defaultdict -from llvmlite import ir +from contextlib import contextmanager +from typing import Optional + import llvmlite.binding as llvm -from .targetinfo import TargetInfo -from .errors import UnsupportedError -from . import libfuncs -from rbc.externals import stdio -from numba.core import codegen, cpu, compiler_lock, \ - registry, typing, compiler, sigutils, cgutils, \ - extending, imputils +from llvmlite import ir +from numba.core import cgutils, codegen, compiler, compiler_lock, cpu from numba.core import errors as nb_errors +from numba.core import extending, imputils, registry, sigutils, typing +from rbc.externals import stdio +from rbc.nrt import create_nrt_functions + +from .errors import UnsupportedError +from .libfuncs import Library +from .targetinfo import TargetInfo int32_t = ir.IntType(32) int1_t = ir.IntType(1) -def get_called_functions(library, funcname=None): +def find_at_word(text: str) -> Optional[str]: + """ + Find called function name from a CallInst to a bitcast. + + Example usage + + >>> text = "i8* (i64)* bitcast (%Struct.MemInfo.5* (i64)* @NRT_MemInfo_alloc_safe to i8* (i64)*)" # noqa: E501 + >>> find_at_word(text) + "NRT_MemInfo_alloc_safe + >>> text = "%.5 = bitcast i8* %info to void (i8*, i64, i8*)*" + >>> find_at_word(text) + None + + """ + pattern = r"@\w+" + words = re.findall(pattern, text) + if words == []: + return None + assert len(words) == 1 + [word] = words + return word[1:] + + +def get_called_functions(library, funcname=None, debug=False): result = defaultdict(set) module = library._final_module if funcname is None: for df in library.get_defined_functions(): - for k, v in get_called_functions(library, df.name).items(): + for k, v in get_called_functions(library, df.name, debug).items(): result[k].update(v) return result @@ -36,8 +64,24 @@ def get_called_functions(library, funcname=None): for block in func.blocks: for instruction in block.instructions: if instruction.opcode == 'call': - name = list(instruction.operands)[-1].name - f = module.get_function(name) + instr = list(instruction.operands)[-1] + name = instr.name + try: + f = module.get_function(name) + except NameError: + if 'bitcast' not in str(instr): + raise # re-raise + + # attempt to find caller symbol in instr + name = find_at_word(str(instr)) + if name is None: + # ignore call to function pointer + msg = f'Ignoring call to bitcast instruction:\n{instr}' + if debug: + warnings.warn(msg) + continue + f = module.get_function(name) + if name.startswith('llvm.'): result['intrinsics'].add(name) elif f.is_declaration: @@ -48,7 +92,7 @@ def get_called_functions(library, funcname=None): result['defined'].add(name) result['libraries'].add(lib) found = True - for k, v in get_called_functions(lib, name).items(): + for k, v in get_called_functions(lib, name, debug).items(): result[k].update(v) break if found: @@ -57,7 +101,7 @@ def get_called_functions(library, funcname=None): result['declarations'].add(name) else: result['defined'].add(name) - for k, v in get_called_functions(library, name).items(): + for k, v in get_called_functions(library, name, debug).items(): result[k].update(v) return result @@ -309,7 +353,7 @@ def compile_instance(func, sig, except Exception: raise - result = get_called_functions(cres.library, cres.fndesc.llvm_func_name) + result = get_called_functions(cres.library, cres.fndesc.llvm_func_name, debug) for f in result['declarations']: if target.supports(f): @@ -317,8 +361,8 @@ def compile_instance(func, sig, warnings.warn(f'Skipping {fname} that uses undefined function `{f}`') return - nvvmlib = libfuncs.Library.get('nvvm') - llvmlib = libfuncs.Library.get('llvm') + nvvmlib = Library.get('nvvm') + llvmlib = Library.get('llvm') for f in result['intrinsics']: if target.is_gpu: if f in nvvmlib: @@ -352,6 +396,19 @@ def add_metadata_flag(main_library, **kwargs): main_library.add_ir_module(module) +def read_unicodetype_db(): + + @functools.lru_cache() + def _read_file(): + unicode_file = os.path.join(os.path.dirname(__file__), + 'unicodetype_db.ll') + with open(unicode_file, 'r') as f: + s = f.read() + return s + + return llvm.parse_assembly(_read_file()) + + def compile_to_LLVM(functions_and_signatures, target_info: TargetInfo, pipeline_class=compiler.Compiler, @@ -381,6 +438,9 @@ def compile_to_LLVM(functions_and_signatures, typing_context = JITRemoteTypingContext() target_context = JITRemoteTargetContext(typing_context) + nrt_module = create_nrt_functions(target_context, debug=debug) + unicodetype_db = read_unicodetype_db() + # Bring over Array overloads (a hack): target_context._defns = target_desc.target_context._defns @@ -395,6 +455,9 @@ def compile_to_LLVM(functions_and_signatures, assert isinstance(user_defined_llvm_ir, llvm.ModuleRef) main_module.link_in(user_defined_llvm_ir, preserve=True) + main_module.link_in(unicodetype_db) + main_library.add_ir_module(nrt_module) + succesful_fids = [] function_names = [] for func, signatures in functions_and_signatures: @@ -415,10 +478,10 @@ def compile_to_LLVM(functions_and_signatures, # Remove unused defined functions and declarations used_symbols = defaultdict(set) for fname in function_names: - for k, v in get_called_functions(main_library, fname).items(): + for k, v in get_called_functions(main_library, fname, debug).items(): used_symbols[k].update(v) - all_symbols = get_called_functions(main_library) + all_symbols = get_called_functions(main_library, debug=debug) unused_symbols = defaultdict(set) for k, lst in all_symbols.items(): diff --git a/rbc/libfuncs.py b/rbc/libfuncs.py index eda13c3a..009f34c5 100644 --- a/rbc/libfuncs.py +++ b/rbc/libfuncs.py @@ -24,6 +24,8 @@ def get(libname, _cache={}): r = LLVMIntrinsics() elif libname == 'heavydb': r = HeavyDB() + elif libname == 'NRT': + r = NRT() else: raise ValueError(f'Unknown library {libname}') _cache[libname] = r @@ -70,6 +72,29 @@ class HeavyDB(Library): '''.strip().split()) +class NRT(Library): + + name = 'NRT' + + _function_names = list(''' + NRT_MemInfo_call_dtor + NRT_MemInfo_init + NRT_MemInfo_alloc NRT_MemInfo_alloc_safe + NRT_MemInfo_alloc_dtor NRT_MemInfo_alloc_dtor_safe + NRT_Allocate_External + NRT_MemInfo_data_fast + NRT_incref NRT_decref + NRT_MemInfo_varsize_realloc + NRT_MemInfo_new_varsize + NRT_MemInfo_new_varsize_dtor + NRT_MemInfo_varsize_alloc + NRT_MemInfo_varsize_free + NRT_MemInfo_alloc_safe_aligned + numba_gettyperecord + numba_get_PyUnicode_ExtendedCase + '''.strip().split()) + + class Stdlib(Library): """ Reference: http://www.cplusplus.com/reference/cstdlib/ diff --git a/rbc/nrt.py b/rbc/nrt.py new file mode 100644 index 00000000..e6542c18 --- /dev/null +++ b/rbc/nrt.py @@ -0,0 +1,690 @@ +import os +from numba.core import cgutils +from numba.cpython.hashing import _hashsecret as hashsecret +from llvmlite import ir +from contextlib import contextmanager +from rbc.targetinfo import TargetInfo + +void = ir.VoidType() +i8 = ir.IntType(8) +i8p = i8.as_pointer() +i8pp = i8p.as_pointer() +i32 = ir.IntType(32) +i64 = ir.IntType(64) + +REFCT_IDX = 0 +DTOR_IDX = 1 +DTOR_INFO_IDX = 2 +DATA_IDX = 3 +SIZE_IDX = 4 +EXTERNAL_ALLOCATOR_IDX = 5 + + +# Function Names +NRT_MemInfo_init = "NRT_MemInfo_init" + +NRT_MemInfo_alloc = "NRT_MemInfo_alloc" +NRT_MemInfo_alloc_safe = "NRT_MemInfo_alloc_safe" + +NRT_MemInfo_alloc_dtor = "NRT_MemInfo_alloc_dtor" +NRT_MemInfo_alloc_dtor_safe = "NRT_MemInfo_alloc_dtor_safe" + +NRT_Allocate = "NRT_Allocate" +NRT_Allocate_External = "NRT_Allocate_External" +NRT_MemInfo_call_dtor = "NRT_MemInfo_call_dtor" + +NRT_incref = "NRT_incref" +NRT_decref = "NRT_decref" + +NRT_MemInfo_data_fast = "NRT_MemInfo_data_fast" + +NRT_MemInfo_new = "NRT_MemInfo_new" +NRT_MemInfo_new_varsize_dtor = "NRT_MemInfo_new_varsize_dtor" +NRT_MemInfo_varsize_alloc = "NRT_MemInfo_varsize_alloc" +NRT_MemInfo_varsize_realloc = "NRT_MemInfo_varsize_realloc" +NRT_MemInfo_varsize_free = "NRT_MemInfo_varsize_free" +NRT_MemInfo_new_varsize = "NRT_MemInfo_new_varsize" +NRT_MemInfo_alloc_safe_aligned = "NRT_MemInfo_alloc_safe_aligned" +NRT_Reallocate = "NRT_Reallocate" +NRT_Reallocate_NoCopy = "NRT_Reallocate_NoCopy" +NRT_dealloc = "NRT_dealloc" +NRT_Free = "NRT_Free" +NRT_MemInfo_destroy = "NRT_MemInfo_destroy" + +nrt_internal_custom_dtor = "nrt_internal_custom_dtor" +nrt_allocate_meminfo_and_data = "nrt_allocate_meminfo_and_data" +allocate_varlen_buffer = "allocate_varlen_buffer" +malloc = "malloc" +free = "free" +realloc = "realloc" + +nrt_debug_incr = "nrt_debug_incr" +nrt_debug_decr = "nrt_debug_decr" +nrt_debug_spaces = "nrt_debug_spaces" +nrt_global_var = "__nrt_global_var" + + +_debug_functions = (nrt_debug_incr, nrt_debug_decr, nrt_debug_spaces) + + +NULL = cgutils.get_null_value(cgutils.voidptr_t) + + +class RBC_NRT: + def __init__(self, target_context, verbose=False): + self.module = ir.Module(name="RBC_nrt") + self.target_context = target_context + self.verbose = verbose + self.debug_nrt = int(os.environ.get("RBC_DEBUG_NRT", False)) + + gv = ir.GlobalVariable(self.module, i64, nrt_global_var) + gv.initializer = i64(0) + + self._define_types() + self._define_functions() + + self.define() + self.set_hashsecrets() + + def _define_types(self): + ti = TargetInfo() + + # type_sizeof stores each size in bytes + size_t = ir.IntType(ti.type_sizeof["size_t"] * 8) + + # As a reference, here's a copy of the MemInfo struct defined in + # numba/core/context/nrt.cpp + # + # struct MemInfo { + # std::atomic_size_t refct; + # NRT_dtor_function dtor; + # void *dtor_info; + # void *data; + # size_t size; /* only used for NRT allocated memory */ + # void* external_allocator; + # }; + # + # And the LLVM representation of the struct above: + # { %"struct.std::atomic", void (i8*, i64, i8*)*, i8*, i8*, i64, i8* } + # %"struct.std::atomic" = type { %"struct.std::__atomic_base" } + # %"struct.std::__atomic_base" = type { i64 } + + MemInfo_t = ir.global_context.get_identified_type("Struct.MemInfo") + # First argument must be "atomic_i64_t" instead of size_t + if MemInfo_t.elements is None: + MemInfo_t.set_body(size_t, i8p, i8p, i8p, size_t, i8p) + MemInfo_ptr_t = MemInfo_t.as_pointer() + + self.size_t = size_t + self.MemInfo_t = MemInfo_t + self.MemInfo_ptr_t = MemInfo_ptr_t + self.sizeof_MemInfo_t = i64(self.target_context.get_abi_sizeof(MemInfo_t)) + + def _define_functions(self): + size_t = self.size_t + MemInfo_ptr_t = self.MemInfo_ptr_t + + self.NRT_DTOR_FUNCTION = ir.FunctionType(void, [i8p, size_t, i8p]) + + self.function_types = { + # defined in nrt.h + NRT_MemInfo_init: ( + ir.FunctionType(void, [MemInfo_ptr_t, i8p, size_t, i8p, i8p, i8p]), + ("mi", "data", "size", "dtor", "dtor_info", "external_allocator"), + ), + NRT_MemInfo_alloc: (ir.FunctionType(MemInfo_ptr_t, [size_t]), ("size",)), + NRT_MemInfo_alloc_safe: ( + ir.FunctionType(MemInfo_ptr_t, [size_t]), + ("size",), + ), + NRT_MemInfo_alloc_dtor: ( + ir.FunctionType(MemInfo_ptr_t, [size_t, i8p]), + ("size", "dtor"), + ), + NRT_MemInfo_alloc_dtor_safe: ( + ir.FunctionType(MemInfo_ptr_t, [size_t, i8p]), + ("size", "dtor"), + ), + NRT_Allocate: (ir.FunctionType(i8p, [size_t]), ("size",)), + NRT_Allocate_External: ( + ir.FunctionType(i8p, [size_t, i8p]), + ("size", "allocator"), + ), + NRT_MemInfo_call_dtor: (ir.FunctionType(void, [MemInfo_ptr_t]), ("mi",)), + NRT_incref: (ir.FunctionType(void, [i8p]), ("ptr",)), + NRT_decref: (ir.FunctionType(void, [i8p]), ("ptr",)), + NRT_MemInfo_data_fast: (ir.FunctionType(i8p, [i8p]), ("meminfo_ptr",)), + NRT_MemInfo_new: ( + ir.FunctionType(MemInfo_ptr_t, [i8p, size_t, i8p, i8p]), + ("data", "size", "dtor", "dtor_info"), + ), + NRT_MemInfo_alloc_safe_aligned: ( + ir.FunctionType(MemInfo_ptr_t, [size_t, i32]), + ("size", "aligned"), + ), + NRT_MemInfo_new_varsize: ( + ir.FunctionType(MemInfo_ptr_t, [size_t]), + ("size",), + ), + NRT_MemInfo_new_varsize_dtor: ( + ir.FunctionType(MemInfo_ptr_t, [size_t, i8p]), + ("size", "dtor"), + ), + NRT_MemInfo_varsize_free: ( + ir.FunctionType(void, [MemInfo_ptr_t, i8p]), + ("mi", "ptr"), + ), + NRT_MemInfo_varsize_alloc: ( + ir.FunctionType(i8p, [MemInfo_ptr_t, size_t]), + ("mi", "size"), + ), + NRT_MemInfo_varsize_realloc: ( + ir.FunctionType(i8p, [MemInfo_ptr_t, size_t]), + ("mi", "size"), + ), + NRT_Reallocate: (ir.FunctionType(i8p, [i8p, size_t]), ("ptr", "size")), + NRT_Reallocate_NoCopy: ( + ir.FunctionType(i8p, [i8p, size_t]), + ("ptr", "size")), + NRT_dealloc: (ir.FunctionType(void, [MemInfo_ptr_t]), ("mi",)), + NRT_Free: (ir.FunctionType(void, [i8p]), ("ptr",)), + NRT_MemInfo_destroy: (ir.FunctionType(void, [MemInfo_ptr_t]), ("mi",)), + nrt_internal_custom_dtor: ( + ir.FunctionType(void, [i8p, size_t, i8p]), + ("ptr", "size", "info"), + ), + nrt_allocate_meminfo_and_data: ( + ir.FunctionType(i8p, [size_t, i8pp, i8p]), + ("size", "mi_out", "allocator"), + ), + allocate_varlen_buffer: (ir.FunctionType(i8p, [i64, i64]), ()), + malloc: (ir.FunctionType(i8p, [size_t]), ("size",)), + free: (ir.FunctionType(void, [i8p]), ("ptr",)), + realloc: (ir.FunctionType(i8p, [i8p, size_t]), ()), + # debug functions + nrt_debug_incr: (ir.FunctionType(void, []), ()), + nrt_debug_decr: (ir.FunctionType(void, []), ()), + nrt_debug_spaces: (ir.FunctionType(void, []), ()), + } + + def set_hashsecrets(self): + for v in hashsecret.values(): + gv = ir.GlobalVariable(self.module, i64, v.symbol) + gv.initializer = i64(v.value.value) + + def NRT_Debug(self, fmt, *args): + # only debug if verbose is on + if self.debug_nrt: + builder = self.CURRENT_BUILDER + msg = f"[NRT] {fmt}" + if not msg.endswith("\n"): + msg += "\n" + + gv = builder.load(self.module.get_global(nrt_global_var)) + cgutils.printf(builder, "%*d", gv, gv) + cgutils.printf(builder, msg, *args) + + @contextmanager + def nrt_debug_ctx(self): + if self.debug_nrt: + builder = self.CURRENT_BUILDER + try: + self.NRT_Debug(self.CURRENT_FUNCTION) + builder.call(self.nrt_debug_incr, []) + yield + finally: + builder.call(self.nrt_debug_decr, []) + else: + yield + + def define_nrt_debug_incr(self, builder, args): + gv = self.module.get_global(nrt_global_var) + builder.store(builder.add(builder.load(gv), i64(4)), gv) + builder.ret_void() + + def define_nrt_debug_decr(self, builder, args): + gv = self.module.get_global(nrt_global_var) + builder.store(builder.sub(builder.load(gv), i64(4)), gv) + builder.ret_void() + + def define_nrt_debug_spaces(self, builder, args): + cgutils.printf(builder, "\t") + builder.ret_void() + + def __getattribute__(self, __name): + try: + return super().__getattribute__(__name) + except AttributeError: + if __name in self.function_types: + return self._get_function(__name) + raise + + def _get_function_builder(self, fn_name): + fn = self._get_function(fn_name) + block = fn.append_basic_block(name="entry") + return ir.IRBuilder(block) + + def _get_from_meminfo(self, mi, kind): + builder = self.CURRENT_BUILDER + table = { + "refct": REFCT_IDX, + "dtor": DTOR_IDX, + "dtor_info": DTOR_INFO_IDX, + "data": DATA_IDX, + "size": SIZE_IDX, + "allocator": EXTERNAL_ALLOCATOR_IDX, + } + idx = table[kind] + return builder.load( + builder.gep(mi, [i32(0), i32(idx)], inbounds=True), name=kind + ) + + def _set_on_meminfo(self, mi, kind, val): + builder = self.CURRENT_BUILDER + table = { + "refct": REFCT_IDX, + "dtor": DTOR_IDX, + "dtor_info": DTOR_INFO_IDX, + "data": DATA_IDX, + "size": SIZE_IDX, + "allocator": EXTERNAL_ALLOCATOR_IDX, + } + idx = table[kind] + return builder.store(val, builder.gep(mi, [i32(0), i32(idx)], inbounds=True)) + + def _get_function(self, fn_name): + fnty = self.function_types[fn_name][0] + fn = cgutils.get_or_insert_function(self.module, fnty, fn_name) + return fn + + def _get_function_arg_names(self, fn_name): + return self.function_types[fn_name][1] + + def _declare_function(self, fn_name): + fn = self._get_function(fn_name) + argnames = self._get_function_arg_names(fn_name) + if argnames is not None: + assert isinstance(argnames, tuple), argnames + assert len(argnames) == len(fn.args), (len(argnames), len(fn.args)) + for arg, name in zip(fn.args, argnames): + arg.name = name + if self.debug_nrt: + fn.attributes.add("noinline") + return fn + + def _ensure_impl_exists(self): + # Ensure for each function in function_types, there is a corresponding + # implementation + skip_list = ("allocate_varlen_buffer", "realloc", "malloc", "free") + for fn_name in self.function_types.keys(): + if fn_name not in skip_list: + defn = f"define_{fn_name}" + getattr(self, defn), defn + + def define(self): + self._ensure_impl_exists() + + for name in dir(self): + if not name.startswith("define_"): + continue + + if name in _debug_functions and not self.debug_nrt: + continue + + meth = getattr(self, name) + fn_name = name[len("define_"):] + self._declare_function(fn_name) + builder = self._get_function_builder(fn_name) + args = builder.function.args + self.CURRENT_FUNCTION = fn_name + self.CURRENT_BUILDER = builder + meth(builder, args) + + def define_NRT_MemInfo_call_dtor(self, builder, args): + with self.nrt_debug_ctx(): + [mi] = args + self.NRT_Debug("NRT_MemInfo_call_dtor mi=%p\n", mi) + + dtor = self._get_from_meminfo(mi, "dtor") + not_null = cgutils.is_not_null(builder, dtor) + with cgutils.if_likely(builder, not_null): + dtor_fn = builder.bitcast(dtor, self.NRT_DTOR_FUNCTION.as_pointer()) + data = self._get_from_meminfo(mi, "data") + size = self._get_from_meminfo(mi, "size") + dtor_info = self._get_from_meminfo(mi, "dtor_info") + builder.call(dtor_fn, [data, size, dtor_info]) + + builder.call(self.NRT_MemInfo_destroy, [mi]) + builder.ret_void() + + def define_NRT_incref(self, builder, args): + # with self.nrt_debug_ctx(): + # pass + builder.ret_void() + + def define_NRT_decref(self, builder, args): + # with self.nrt_debug_ctx(): + # pass + builder.ret_void() + + def define_NRT_MemInfo_alloc_safe_aligned(self, builder, args): + # Just call the non-aligned version for now + with self.nrt_debug_ctx(): + [size, align] = args + ptr = builder.call(self.NRT_MemInfo_alloc_safe, [size]) + self.NRT_Debug("ptr=%p\n", ptr) + builder.ret(ptr) + + def define_NRT_MemInfo_data_fast(self, builder, args): + with self.nrt_debug_ctx(): + [ptr] = args + self.NRT_Debug("ptr=%p\n", ptr) + not_null = builder.icmp_signed("!=", ptr, NULL) + with builder.if_else(not_null, likely=True) as (then, otherwise): + with then: + bb_then = builder.basic_block + mi_ptr = builder.bitcast( + ptr, self.MemInfo_ptr_t, name="meminfo_ptr" + ) + data = self._get_from_meminfo(mi_ptr, "data") + self.NRT_Debug("data: %p\n", data) + with otherwise: + # there is a specific case where ptr is NULL and doesn't + # crash Numba + bb_else = builder.basic_block + data_null = NULL + phi = builder.phi(i8p) + phi.add_incoming(data, bb_then) + phi.add_incoming(data_null, bb_else) + builder.ret(phi) + + def define_NRT_Reallocate_NoCopy(self, builder, args): + with self.nrt_debug_ctx(): + # Because the previously reallocated memory might be freed by + # realloc, RBC cannot call it in this function. Therefore, instead + # of reallocation, RBC allocates a new block of memory and returns + # it to the caller. The caller is responsible for copying memory + # from the old buffer into the most recent allocated one." + [ptr, size] = args + new_ptr = builder.call(self.NRT_Allocate_External, [size, NULL]) + self.NRT_Debug("ptr=%p size=%zu -> new_ptr=%p", ptr, size, new_ptr) + builder.ret(new_ptr) + + def define_NRT_Reallocate(self, builder, args): + with self.nrt_debug_ctx(): + # Because the previously reallocated memory might be freed by + # realloc, RBC cannot call it in this function. Therefore, instead + # of reallocation, RBC allocates a new block of memory and returns + # it to the caller. The caller is responsible for copying memory + # from the old buffer into the most recent allocated one." + [ptr, size] = args + new_ptr = builder.call(self.NRT_Allocate_External, [size, NULL]) + self.NRT_Debug("ptr=%p size=%zu -> new_ptr=%p", ptr, size, new_ptr) + msg = ('The "NRT_Reallocate" function is a custom implementation ' + 'of the "realloc" function from the C standard library. ' + 'Unlike the original "realloc" function, this ' + 'implementation does not copy memory from the old buffer to ' + 'the new one. Instead, it simply allocates a new buffer ' + 'with the given size and returns a pointer to it. The old ' + 'buffer remains unchanged, and it is the responsibility of ' + 'the caller to copy data from the old buffer to the new one ' + 'if necessary.\n' + 'See RBC issue #536') + self.NRT_Debug(msg) + builder.ret(new_ptr) + + def define_NRT_dealloc(self, builder, args): + with self.nrt_debug_ctx(): + [mi] = args + self.NRT_Debug("meminfo: %p\n", mi) + ptr = builder.bitcast(mi, i8p) + builder.call(self.NRT_Free, [ptr]) + builder.ret_void() + + def define_NRT_Free(self, builder, args): + # this is a no-op function + with self.nrt_debug_ctx(): + [ptr] = args + self.NRT_Debug("# NRT_Free %p\n", ptr) + # free is done automatically in HeavyDB + builder.ret_void() + + def define_NRT_MemInfo_varsize_alloc(self, builder, args): + with self.nrt_debug_ctx(): + [mi, size] = args + + data = builder.call(self.NRT_Allocate, [size]) + # TODO: check if data is NULL + self._set_on_meminfo(mi, "data", data) + self._set_on_meminfo(mi, "size", size) + self.NRT_Debug("%p size=%zu -> data=%p\n", mi, size, data) + builder.ret(data) + + def define_NRT_MemInfo_varsize_realloc(self, builder, args): + with self.nrt_debug_ctx(): + [mi, size] = args + data = self._get_from_meminfo(mi, "data") + + # Is this the only function that calls NRT_Reallocate? + new_data = builder.call(self.NRT_Reallocate_NoCopy, [data, size], + name="new_data") + + # RBC/NRT cannot use realloc as the old memory gets freed in the + # process. Instead, memory is copied from the old buffer to the new + # one here. The previous memory is freed upon UD[T]F return + old_size = self._get_from_meminfo(mi, "size") + cond = builder.icmp_signed("<", old_size, size) + memcpy_size = builder.select(cond, old_size, size) + + self.NRT_Debug( + "memcpy %zu bytes from data=%p --> new_data=%p", + memcpy_size, + data, + new_data, + ) + + cgutils.raw_memcpy( + builder, dst=new_data, src=data, count=memcpy_size, itemsize=i64(1) + ) + + self.NRT_Debug("new_data=%p - size=%zu\n", new_data, size) + + # TODO: check if new_data is NULL + self._set_on_meminfo(mi, "data", new_data) + self._set_on_meminfo(mi, "size", size) + builder.ret(new_data) + + def define_NRT_MemInfo_varsize_free(self, builder, args): + with self.nrt_debug_ctx(): + [mi, ptr] = args + builder.call(self.NRT_Free, [ptr]) + + mi_data = self._get_from_meminfo(mi, "data") + eq = builder.icmp_signed("==", ptr, mi_data) + with builder.if_then(eq): + self._set_on_meminfo(mi, "data", NULL) + builder.ret_void() + + def define_NRT_MemInfo_destroy(self, builder, args): + with self.nrt_debug_ctx(): + [mi] = args + self.NRT_Debug("mi=%p\n", mi) + builder.call(self.NRT_dealloc, [mi]) + builder.ret_void() + + def define_nrt_internal_custom_dtor(self, builder, args): + with self.nrt_debug_ctx(): + [ptr, size, info] = args + + dtor = builder.bitcast(info, self.NRT_DTOR_FUNCTION.as_pointer()) + self.NRT_Debug("ptr=%p, info=%p dtor=%p\n", ptr, info, dtor) + + not_null = cgutils.is_not_null(builder, dtor) + with cgutils.if_likely(builder, not_null): + info_ = NULL + builder.call(dtor, [ptr, size, info_]) + builder.ret_void() + + def define_nrt_allocate_meminfo_and_data(self, builder, args): + with self.nrt_debug_ctx(): + [size, mi_out, allocator] = args + alloc_size = builder.add(size, self.sizeof_MemInfo_t) + base = builder.call(self.NRT_Allocate_External, [alloc_size, allocator]) + builder.store(base, mi_out) + out = builder.gep(base, [self.sizeof_MemInfo_t], inbounds=True) + self.NRT_Debug("base=%p out=%p\n", base, out) + builder.ret(out) + + def define_NRT_Allocate(self, builder, args): + # allocator is always null as we don't use this argument in RBC/HeavyDB + with self.nrt_debug_ctx(): + [size] = args + allocator = NULL + ret = builder.call(self.NRT_Allocate_External, [size, allocator]) + builder.ret(ret) + + def define_NRT_Allocate_External(self, builder, args): + # allocator is always null as we don't use this argument in RBC/HeavyDB + with self.nrt_debug_ctx(): + [size, allocator_] = args + + # ptr = builder.call(self.malloc, [size]) + # allocate_varlen_buffer calls malloc using the formula: + # malloc((elem_count + 1) * elem_size) + elem_count = builder.sub(size, i64(1), name="element_count") + elem_size = i64(1) + ptr = builder.call(self.allocate_varlen_buffer, [elem_count, elem_size]) + self.NRT_Debug( + "allocate_varlen_buffer=%p - element_count: %ld", ptr, elem_count + ) + # self.NRT_Debug("malloc: bytes=%zu -> ptr=%p", size, ptr) + builder.ret(ptr) + + def define_NRT_MemInfo_alloc_dtor(self, builder, args): + with self.nrt_debug_ctx(): + mi = builder.alloca(self.MemInfo_ptr_t, name="mi") + mi_cast = builder.bitcast(mi, i8pp, "mi_cast") + [size, dtor] = args + allocator = NULL + data = builder.call( + self.nrt_allocate_meminfo_and_data, + [size, mi_cast, allocator], + name="data", + ) + + self.NRT_Debug("data=%p size=%zu\n", data, size) + # TODO: check if data is null + dtor_function = builder.bitcast( + self._get_function(nrt_internal_custom_dtor), i8p + ) + dtor_info = builder.bitcast(dtor, i8p) + allocator = NULL + builder.call( + self.NRT_MemInfo_init, + [builder.load(mi), data, size, dtor_function, dtor_info, allocator], + ) + builder.ret(builder.load(mi)) + + def define_NRT_MemInfo_alloc(self, builder, args): + with self.nrt_debug_ctx(): + mi = builder.alloca(self.MemInfo_ptr_t, name="mi") + mi_cast = builder.bitcast(mi, i8pp, name="mi_cast") + [size] = args + allocator = NULL + data = builder.call( + self.nrt_allocate_meminfo_and_data, + [size, mi_cast, allocator], + name="data", + ) + # TODO: check if data is null + + self.NRT_Debug("%p\n", data) + dtor = NULL + dtor_info = NULL + allocator = NULL + builder.call( + self.NRT_MemInfo_init, + [builder.load(mi), data, size, dtor, dtor_info, allocator], + ) + builder.ret(builder.load(mi)) + + def define_NRT_MemInfo_new_varsize(self, builder, args): + with self.nrt_debug_ctx(): + [size] = args + self.NRT_Debug("size=%zu\n", size) + + # TODO: check if data is null + data = builder.call(self.NRT_Allocate, [size]) + mi = builder.call(self.NRT_MemInfo_new, [data, size, NULL, NULL], name="mi") + self.NRT_Debug("size=%zu -> meminfo=%p, data=%p\n", size, mi, data) + builder.ret(mi) + + def define_NRT_MemInfo_new(self, builder, args): + with self.nrt_debug_ctx(): + [data, size, dtor, dtor_info] = args + ptr = builder.call(self.NRT_Allocate, [self.sizeof_MemInfo_t]) + mi = builder.bitcast(ptr, self.MemInfo_ptr_t, name="mi") + self.NRT_Debug("ptr=%p\n", ptr) + + is_not_null = cgutils.is_not_null(builder, mi) + with cgutils.if_likely(builder, is_not_null): + self.NRT_Debug( + "mi=%p data=%p size=%zu dtor=%p dtor_info=%p\n", + mi, + data, + size, + dtor, + dtor_info, + ) + builder.call( + self.NRT_MemInfo_init, [mi, data, size, dtor, dtor_info, NULL] + ) + builder.ret(mi) + + def define_NRT_MemInfo_new_varsize_dtor(self, builder, args): + with self.nrt_debug_ctx(): + [size, dtor] = args + self.NRT_Debug("size: %d\n", size) + + mi = builder.call(self.NRT_MemInfo_new_varsize, [size]) + self.NRT_Debug("mi=%p\n", mi) + + is_not_null = cgutils.is_not_null(builder, mi) + with cgutils.if_likely(builder, is_not_null): + self._set_on_meminfo(mi, "dtor", dtor) + builder.ret(mi) + + def define_NRT_MemInfo_alloc_safe(self, builder, args): + with self.nrt_debug_ctx(): + [size] = args + self.NRT_Debug("NRT_MemInfo_alloc_safe -> NRT_MemInfo_alloc_dtor_safe\n") + NRT_dtor_function = NULL + ret = builder.call( + self.NRT_MemInfo_alloc_dtor_safe, [size, NRT_dtor_function] + ) + builder.ret(ret) + + def define_NRT_MemInfo_alloc_dtor_safe(self, builder, args): + with self.nrt_debug_ctx(): + # wire implementation to unsafe version + [size, dtor] = args + data = builder.call(self.NRT_MemInfo_alloc_dtor, [size, dtor], name="data") + self.NRT_Debug("data=%p size=%zu\n", data, size) + builder.ret(data) + + def define_NRT_MemInfo_init(self, builder, args): + with self.nrt_debug_ctx(): + [mi, data, size, dtor, dtor_info, external_allocator] = args + self._set_on_meminfo(mi, "refct", self.size_t(1)) + self._set_on_meminfo(mi, "dtor", dtor) + self._set_on_meminfo(mi, "dtor_info", dtor_info) + self._set_on_meminfo(mi, "data", data) + self._set_on_meminfo(mi, "size", size) + self._set_on_meminfo(mi, "allocator", external_allocator) + self.NRT_Debug("mi=%p data=%p size=%zu\n", mi, data, size) + builder.ret_void() + + +def create_nrt_functions(target_context, debug): + nrt = RBC_NRT(target_context, verbose=debug) + return nrt.module diff --git a/rbc/remotejit.py b/rbc/remotejit.py index ee76aec5..075c585b 100644 --- a/rbc/remotejit.py +++ b/rbc/remotejit.py @@ -761,7 +761,7 @@ def start_server(self, background=False): """ thrift_file = os.path.join(os.path.dirname(__file__), 'remotejit.thrift') - print('staring rpc.thrift server: %s' % (thrift_file), end='', + print(f'starting rpc.thrift server ({self.host}:{self.port}): {thrift_file}', end='', flush=True) if self.debug: print(flush=True) @@ -777,13 +777,13 @@ def start_server(self, background=False): Server.run(dispatcher, thrift_file, dict(host=self.host, port=self.port, debug=self.debug)) - print('... rpc.thrift server stopped', flush=True) + print(f'... rpc.thrift server ({self.host}:{self.port}) stopped', flush=True) def stop_server(self): """Stop remotejit server from client. """ if self.server_process is not None and self.server_process.is_alive(): - print('... stopping rpc.thrift server') + print(f'... stopping rpc.thrift server {self.host}:{self.port}', flush=True) self.server_process.terminate() self.server_process = None diff --git a/rbc/tests/heavydb/test_nrt_list.py b/rbc/tests/heavydb/test_nrt_list.py new file mode 100644 index 00000000..f1c4e467 --- /dev/null +++ b/rbc/tests/heavydb/test_nrt_list.py @@ -0,0 +1,144 @@ +from rbc.tests import heavydb_fixture +from rbc.heavydb import Array +import pytest + +rbc_heavydb = pytest.importorskip('rbc.heavydb') +available_version, reason = rbc_heavydb.is_available() +pytestmark = pytest.mark.skipif(not available_version, reason=reason) + + +@pytest.fixture(scope='module') +def heavydb(): + for o in heavydb_fixture(globals(), + suffices=['array', 'arraynull']): + define(o) + yield o + + +def define(heavydb): + # Defines simple methods just to verify if NRT is working and if any there + # are any symbol + # + # List of methods: + # [X] List.append + # [X] List.extend + # [X] List.insert + # [X] List.remove + # [X] List.pop + # [X] List.clear + # [X] List.index + # [X] List.count + # [X] List.sort + # [X] List.reverse + # [X] List.copy + + @heavydb("i32(i32)", devices=['cpu']) + def list_append(t): + lst = list() + lst.append('abc') + return len(lst) + + @heavydb("i32(i32)", devices=['cpu']) + def list_extend(t): + lst = list() + lst.extend('abc') + return len(lst) + + @heavydb("i32(i32)", devices=['cpu']) + def list_insert(t): + lst = list() + lst.insert(0, t) + return len(lst) + + @heavydb("i32(i32)", devices=['cpu']) + def list_remove(t): + lst = list() + lst.extend([t+1, t, t+2]) + lst.remove(t) + return t in lst + + @heavydb("i32(i32)", devices=['cpu']) + def list_pop(t): + lst = list() + lst.extend([t, t, t]) + lst.pop() + return len(lst) + + @heavydb("i32(i32)", devices=['cpu']) + def list_clear(t): + lst = list() + lst.extend([t, t, t]) + lst.clear() + return len(lst) == 0 + + @heavydb("i32(i32)", devices=['cpu']) + def list_index(t): + lst = list() + lst.extend([t-1, t, t+1]) + return lst.index(t) + + @heavydb("i32(i32)", devices=['cpu']) + def list_count(t): + lst = list() + lst.extend([t-1, t, t, t+1]) + return lst.count(t) + + @heavydb("bool(i32)", devices=['cpu']) + def list_sort(t): + lst = list() + lst.extend([t+1, t, t-1]) + lst.sort() + return lst[0] < lst[1] and lst[1] < lst[2] + + @heavydb("bool(i32)", devices=['cpu']) + def list_reverse(t): + lst = list() + lst.extend([t+1, t, t-1]) + lst.reverse() + return lst[0] < lst[1] and lst[1] < lst[2] + + @heavydb("i32(i32)", devices=['cpu']) + def list_copy(t): + lst = list() + lst.extend([t-1, t, t+1]) + l2 = lst.copy() + return len(l2) + + +@pytest.mark.parametrize('method,ans', [('append', 1), ('extend', 3), ('insert', 1), + ('remove', 0), ('pop', 2), ('clear', 1), + ('index', 1), ('count', 2), ('sort', 1), + ('reverse', 1), ('copy', 3)]) +def test_list_methods(heavydb, method, ans): + _, result = heavydb.sql_execute(f"select list_{method}(1);") + assert list(result) == [(ans,)] + + +@pytest.mark.parametrize('strategy', ['array', 'arraynull']) +def test_to_list(heavydb, strategy): + + @heavydb('int64[](int64[])', devices=['cpu']) + def to_list(a): + if a.is_null(): + other = Array(0, 'int64') + other.set_null() + return other + else: + lst = a.to_list() + return Array(lst) + + heavydb.register() + table = heavydb.table_name + strategy + + _, result = heavydb.sql_execute(f'select i8, to_list(i8) from {table}') + result = list(zip(*result)) + expected, got = result + for e, g in zip(expected, got): + if e == []: + # It is not possible to distinguish an empty list created by a null + # array from one created by an empty array + # list(null array) -> [] + # list(empty array) -> [] + assert g is None + else: + assert e == g diff --git a/rbc/tests/heavydb/test_nrt_set.py b/rbc/tests/heavydb/test_nrt_set.py new file mode 100644 index 00000000..293f851a --- /dev/null +++ b/rbc/tests/heavydb/test_nrt_set.py @@ -0,0 +1,104 @@ +from rbc.tests import heavydb_fixture +import pytest + +rbc_heavydb = pytest.importorskip('rbc.heavydb') +available_version, reason = rbc_heavydb.is_available() +pytestmark = pytest.mark.skipif(not available_version, reason=reason) + + +@pytest.fixture(scope='module') +def heavydb(): + for o in heavydb_fixture(globals(), load_test_data=False): + define(o) + yield o + + +def define(heavydb): + # Defines simple methods just to verify if NRT is working and if any there + # are any symbol + # + # List of methods: + # [X] set.add + # [X] set.clear + # [X] set.copy + # [X] set.difference + # [X] set.difference_update + # [X] set.discard + # [X] set.intersection + # [X] set.intersection_update + # [X] set.isdisjoint + # [X] set.issubset + # [X] set.issuperset + # [X] set.pop + # [X] set.remove + # [X] set.symmetric_difference + # [X] set.symmetric_difference_update + # [ ] set.union + # [X] set.update + + @heavydb("i32(i32, TextEncodingNone)", devices=['cpu']) + def test_set(t, method): + method_str = method.to_string() + s = set([1, 2, 3, 4, 5]) + if method_str == 'add': + return len(s) + elif method_str == 'clear': + s.clear() + return len(s) == 0 + elif method_str == 'copy': + s2 = s.copy() + return len(s) == len(s2) == 5 + elif method_str == 'difference': + s2 = set([1, 3, 5]) + return s.difference(s2) == {2, 4} + elif method_str == 'difference_update': + s.difference_update({1, 2, 3}) + return len(s) == 2 + elif method_str == 'discard': + s.discard(1) + return len(s) == 4 + elif method_str == 'intersection': + return s.intersection({1, 3, 5}) == {1, 3, 5} + elif method_str == 'intersection_update': + s.intersection_update({1, 2}) + return len(s) == 2 + elif method_str == 'isdisjoint': + return s.isdisjoint({0, 6}) + elif method_str == 'issubset': + return s.issubset({0, 1, 2, 3, 4, 5}) + elif method_str == 'issuperset': + return s.issuperset({1, 2, 3}) + elif method_str == 'pop': + s.pop() + return len(s) == 4 + elif method_str == 'remove': + s.remove(2) + return len(s) == 4 + elif method_str == 'symmetric_difference': + s2 = {1, 2} + return len(s.symmetric_difference(s2)) == 3 + elif method_str == 'symmetric_difference_update': + s.symmetric_difference_update({0, 6}) + return len(s) == 7 + # elif method_str == 'union': + # return len(s.union({0})) == 6 + elif method_str == 'update': + s.update({0}) + return len(s) == 6 + return 0 + + +@pytest.mark.parametrize('method,ans', [('add', 5), ('clear', 1), ('copy', 1), + ('difference', 1), ('difference_update', 1), + ('discard', 1), ('intersection', 1), + ('intersection_update', 1), ('isdisjoint', 1), + ('issubset', 1), ('issuperset', 1), ('pop', 1), + ('remove', 1), ('symmetric_difference', 1), + ('symmetric_difference_update', 1), + ('union', 1), ('update', 1)]) +def test_set_methods(heavydb, method, ans): + skip_list = ('union',) + if method in skip_list: + pytest.skip(method) + _, result = heavydb.sql_execute(f"select test_set(1, '{method}');") + assert list(result)[0] == (ans,) diff --git a/rbc/tests/heavydb/test_nrt_string.py b/rbc/tests/heavydb/test_nrt_string.py new file mode 100644 index 00000000..84141e16 --- /dev/null +++ b/rbc/tests/heavydb/test_nrt_string.py @@ -0,0 +1,273 @@ +from rbc.tests import heavydb_fixture +from rbc.heavydb import TextEncodingNone +import pytest + +rbc_heavydb = pytest.importorskip('rbc.heavydb') +available_version, reason = rbc_heavydb.is_available() +pytestmark = pytest.mark.skipif(not available_version, reason=reason) + + +@pytest.fixture(scope='module') +def heavydb(): + for o in heavydb_fixture(globals(), load_test_data=False): + define(o) + yield o + + +# missing methods: +# encode +# format +# format_map +# partition +# rpartition +# translate +# maketrans + +def define(heavydb): + + @heavydb("TextEncodingNone(TextEncodingNone, TextEncodingNone)", devices=['cpu']) + def test_string(t, method): + s = t.to_string() + if method == 'capitalize': + r = s.capitalize() + elif method == 'casefold': + r = s.casefold() + elif method == 'lower': + r = s.lower() + elif method == 'upper': + r = s.upper() + elif method == 'swapcase': + r = s.swapcase() + elif method == 'lstrip': + r = s.lstrip() + elif method == 'rstrip': + r = s.rstrip() + elif method == 'strip': + r = s.strip() + elif method == 'title': + r = s.title() + else: + r = '' + return TextEncodingNone(r) + + @heavydb('bool(TextEncodingNone, TextEncodingNone, TextEncodingNone)') + def test_endswith(method, t, value): + s = t.to_string() + w = value.to_string() + if method == 'endswith': + return s.endswith(w) + elif method == 'startswith': + return s.startswith(w) + return False + + @heavydb('TextEncodingNone(TextEncodingNone, TextEncodingNone, TextEncodingNone)') + def test_replace(t, old, new): + s = t.to_string() + o = old.to_string() + n = new.to_string() + r = s.replace(o, n) + return TextEncodingNone(r) + + @heavydb('TextEncodingNone(TextEncodingNone, TextEncodingNone, TextEncodingNone)') + def test_split(method, string, sep): + s = string.to_string() + sep = sep.to_string() + + if method == 'split': + lst = s.split(sep) + r = ' '.join(lst) + elif method == 'rsplit': + lst = s.rsplit(sep) + r = ' '.join(lst) + elif method == 'splitlines': + lst = s.splitlines() + r = ' '.join(lst) + else: + r = '' + return TextEncodingNone(r) + + @heavydb('TextEncodingNone(TextEncodingNone, TextEncodingNone, i32)') + def test_just(method, string, width): + s = string.to_string() + r = '' + if method == 'center': + r = s.center(width) + elif method == 'expandtabs': + r = s.expandtabs(width) + elif method == 'ljust': + r = s.ljust(width) + elif method == 'rjust': + r = s.rjust(width) + elif method == 'zfill': + r = s.zfill(width) + return TextEncodingNone(r) + + @heavydb('i32(TextEncodingNone, TextEncodingNone, TextEncodingNone)') + def test_string2(method, t, word): + s = t.to_string() + w = word.to_string() + if method == 'count': + return s.count(w) + elif method == 'find': + return s.find(w) + elif method == 'rfind': + return s.rfind(w) + elif method == 'index': + return s.index(w) + elif method == 'rindex': + return s.rindex(w) + return -1 + + @heavydb('bool(TextEncodingNone, TextEncodingNone)') + def test_is(method, t): + s = t.to_string() + if method == 'isalnum': + return s.isalnum() + elif method == 'isalpha': + return s.isalpha() + elif method == 'isascii': + return s.isascii() + elif method == 'isdecimal': + return s.isdecimal() + elif method == 'isdigit': + return s.isdigit() + elif method == 'isidentifier': + return s.isidentifier() + elif method == 'islower': + return s.islower() + elif method == 'isnumeric': + return s.isnumeric() + elif method == 'isprintable': + return s.isprintable() + elif method == 'isspace': + return s.isspace() + elif method == 'istitle': + return s.istitle() + elif method == 'isupper': + return s.isupper() + return False + + +tests = [ + ('capitalize', 'heavydb'), + ('casefold', 'HeavyDB'), + ('lower', 'PYTHON IS FUN'), + ('upper', 'python iS Fun'), + ('swapcase', 'pYtHoN'), + ('lstrip', ' python'), + ('rstrip', 'python '), + ('strip', ' python '), + ('title', 'My favorite number is 25.'), +] + + +@pytest.mark.parametrize('method,arg', tests) +def test_string_methods(heavydb, method, arg: str): + _, result = heavydb.sql_execute(f"select test_string('{arg}', '{method}');") + + fn = getattr(arg, method) + ans = fn() + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('method,string,word', [ + ('count', 'I love apples, apples are my favorite fruit', 'apple'), + ('count', 'I love apples, apples are my favorite fruit', 'orange'), + ('find', 'Hello, welcome to my world.', 'welcome'), + ('find', 'Hello, welcome to my world.', 'orange'), + ('rfind', 'Hello, welcome to my world.', 'welcome'), + ('rfind', 'Hello, welcome to my world.', 'orange'), + ('index', 'Hello, welcome to my world.', 'welcome'), + ('rindex', 'Hello, welcome to my world.', 'welcome'), +]) +def test_string_two_arg(heavydb, method, string, word): + _, result = heavydb.sql_execute(f"select test_string2('{method}', '{string}', '{word}')") + ans = getattr(string, method)(word) + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('method,string,sep', [ + ('split', 'BMW-Telsa-Range Rover', '-'), + ('rsplit', 'BMW-Telsa-Range Rover', '-'), + ('splitlines', 'I\nlove\nPython\nProgramming.', ''), +]) +def test_split(heavydb, method, string, sep): + _, result = heavydb.sql_execute(f"select test_split('{method}', '{string}', '{sep}')") + if method == 'splitlines': + r = getattr(string, method)() + else: + r = getattr(string, method)(sep) + ans = ' '.join(r) + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('method,string,width', [ + ('center', 'banana', 20), + ('expandtabs', 'H\te\tl\tl\to', 2), + ('ljust', 'cat', 5), + ('rjust', 'cat', 5), + ('zfill', 'cat', 5), +]) +def test_string_just(heavydb, method, string, width): + _, result = heavydb.sql_execute(f"select test_just('{method}', '{string}', {width})") + ans = getattr(string, method)(width) + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('method,string,value', [ + ('endswith', 'Hello, welcome to my world.', '.'), + ('endswith', 'Hello, HeavyDB', 'HeavyAI'), + ('statswith', 'Hello, HeavyDB', 'Hello'), + ('startswith', 'Hello, HeavyDB', 'HeavyAI'), +]) +def test_string_endswith(heavydb, method, string, value): + _, result = heavydb.sql_execute(f"select test_endswith('{method}', '{string}', '{value}')") + ans = string.endswith(value) + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('string,old,new', [ + ('bat ball', 'ba', 'ro'), +]) +def test_replace(heavydb, string, old, new): + _, result = heavydb.sql_execute(f"select test_replace('{string}', '{old}', '{new}')") + ans = string.replace(old, new) + assert list(result)[0] == (ans,) + + +@pytest.mark.parametrize('method,string', [ + ('isalnum', 'Hello, welcome to my world.'), + ('isalnum', 'Company12'), + ('isalpha', 'CompanyX'), + ('isascii', 'Company123'), + ('isdecimal', '28212'), + ('isdecimal', '32ladk3'), + ('isdecimal', 'Mo3 nicaG el l22er'), + ('isdigit', '32ladk3'), + ('isdigit', '342'), + ('isdigit', 'Python'), + ('isidentifier', 'Python'), + ('isidentifier', '22 Python'), + ('isidentifier', 'Py thon'), + ('isidentifier', ''), + ('islower', 'this is good'), + ('islower', 'th!s is a1so g00d'), + ('islower', 'this is Not good'), + ('isnumeric', '523'), + ('isnumeric', 'Python3'), + ('isprintable', 'python'), + ('isprintable', 'python\n'), + ('isspace', ' \t'), + ('isspace', ' a '), + ('isspace', ''), + ('istitle', 'Python Is Good'), + ('istitle', 'Python is Good'), + ('istitle', 'This Is @ Symbol'), + ('isupper', 'THIS IS GOOD'), + ('isupper', 'THIS IS not GOOD'), +]) +def test_string_is(heavydb, method, string): + + _, result = heavydb.sql_execute(f"select test_is('{method}', '{string}')") + ans = getattr(string, method)() + assert list(result)[0] == (ans,) diff --git a/rbc/tests/heavydb/test_text_encoding_none.py b/rbc/tests/heavydb/test_text_encoding_none.py index 6cc142b5..f9868386 100644 --- a/rbc/tests/heavydb/test_text_encoding_none.py +++ b/rbc/tests/heavydb/test_text_encoding_none.py @@ -184,3 +184,17 @@ def fn(t): result = list(zip(*result)) expected, got = result assert expected == got + + +def test_to_string(heavydb): + + @heavydb("TextEncodingNone(TextEncodingNone)", devices=['cpu']) + def to_string(t): + s = t.to_string() + return TextEncodingNone(s) + + table = heavydb.table_name + 'text' + _, result = heavydb.sql_execute(f"select n, to_string(n) from {table};") + result = list(zip(*result)) + expected, got = result + assert expected == got diff --git a/rbc/tests/test_externals_cmath.py b/rbc/tests/test_externals_cmath.py index a27a3183..a6bd5008 100644 --- a/rbc/tests/test_externals_cmath.py +++ b/rbc/tests/test_externals_cmath.py @@ -12,7 +12,7 @@ @pytest.fixture(scope="module") def rjit(request): local = False - rjit = RemoteJIT(debug=not True, local=local) + rjit = RemoteJIT(debug=not True, local=local, port=11542) if not local: rjit.start_server(background=True) request.addfinalizer(rjit.stop_server) @@ -23,7 +23,7 @@ def rjit(request): @pytest.fixture(scope="module") def ljit(request): - ljit = RemoteJIT(debug=not True, local=True) + ljit = RemoteJIT(debug=not True, local=True, port=11543) define(ljit) return ljit diff --git a/rbc/tests/test_numpy_rjit.py b/rbc/tests/test_numpy_rjit.py index 192eb9d4..516d198e 100644 --- a/rbc/tests/test_numpy_rjit.py +++ b/rbc/tests/test_numpy_rjit.py @@ -6,7 +6,7 @@ @pytest.fixture(scope="module") def rjit(request): - rjit = RemoteJIT() + rjit = RemoteJIT(port=11541) rjit.start_server(background=True) request.addfinalizer(rjit.stop_server) atexit.register(rjit.stop_server) diff --git a/rbc/tests/test_remotejit.py b/rbc/tests/test_remotejit.py index 1a29160c..8ef35f9d 100644 --- a/rbc/tests/test_remotejit.py +++ b/rbc/tests/test_remotejit.py @@ -16,7 +16,7 @@ @pytest.fixture(scope="module") def rjit(request): local = False - rjit = RemoteJIT(debug=not True, local=local) + rjit = RemoteJIT(debug=not True, local=local, port=11540) if not local: rjit.start_server(background=True) request.addfinalizer(rjit.stop_server) @@ -26,12 +26,12 @@ def rjit(request): @pytest.fixture(scope="module") def ljit(request): - ljit = RemoteJIT(debug=not True, local=True) + ljit = RemoteJIT(debug=not True, local=True, port=11539) return ljit def with_localjit(test_func): - ljit = RemoteJIT(local=True) + ljit = RemoteJIT(local=True, port=11538) device = tuple(ljit.targets)[0] target_info = ljit.targets[device] diff --git a/rbc/tests/test_unicodedbtype.py b/rbc/tests/test_unicodedbtype.py new file mode 100644 index 00000000..79ada91e --- /dev/null +++ b/rbc/tests/test_unicodedbtype.py @@ -0,0 +1,38 @@ +import pytest +from rbc.irtools import read_unicodetype_db + + +@pytest.fixture(scope='module') +def db(): + return read_unicodetype_db() + + +@pytest.mark.usefixtures('db') +def test_unicodedbtype_functions(db): + # ensure there's a unicodetype_db.ll file and it contains the + # required symbols + required_fns = ('numba_PyUnicode_ToNumeric', 'numba_PyUnicode_IsWhitespace', + 'numba_PyUnicode_IsLinebreak', 'numba_gettyperecord', + 'numba_get_PyUnicode_ExtendedCase') + fns = list(db.functions) + assert len(fns) == len(required_fns) + for fn in db.functions: + assert fn.name in required_fns + + +@pytest.mark.usefixtures('db') +def test_unicodedbtype_globals(db): + + required_globals = ('numba_PyUnicode_TypeRecords', 'index1', 'index2', + 'numba_PyUnicode_ExtendedCase') + for glob in db.global_variables: + assert glob.name in required_globals + + +@pytest.mark.usefixtures('db') +def test_numba_PyUnicode_TypeRecord_struct(db): + + try: + db.get_struct_type('struct.numba_PyUnicode_TypeRecord') + except NameError: + pytest.fail('Raise exception') diff --git a/rbc/unicodetype_db.h b/rbc/unicodetype_db.h new file mode 100644 index 00000000..69c61f02 --- /dev/null +++ b/rbc/unicodetype_db.h @@ -0,0 +1,46 @@ +#include +#include "_unicodetype_db.h" + +// To generate unicodetype_db.ll, compile it with +// clang -S -emit-llvm -O2 -Ipath/to/numba unicodetype_db.h -o unicodetype_db.ll + + +/* This function is a modified copy of the private function gettyperecord from + * CPython's Objects/unicodectype.c + * + * See:https://github.com/python/cpython/blob/1d4b6ba19466aba0eb91c4ba01ba509acf18c723/Objects/unicodectype.c#L45-L59 + */ +void +numba_gettyperecord(Py_UCS4 code, int *upper, int *lower, int *title, + unsigned char *decimal, unsigned char *digit, + unsigned short *flags) +{ + int index; + const numba_PyUnicode_TypeRecord *rec; + + if (code >= 0x110000) + index = 0; + else + { + index = index1[(code >> SHIFT)]; + index = index2[(index << SHIFT) + (code & ((1 << SHIFT) - 1))]; + } + + rec = &numba_PyUnicode_TypeRecords[index]; + *upper = rec->upper; + *lower = rec->lower; + *title = rec->title; + *decimal = rec->decimal; + *digit = rec->digit; + *flags = rec->flags; +} + +/* This function provides a consistent access point for the + * _PyUnicode_ExtendedCase array defined in CPython's Objects/unicodectype.c + * and now also as numba_PyUnicode_ExtendedCase in Numba's _unicodetype_db.h + */ +Py_UCS4 +numba_get_PyUnicode_ExtendedCase(int code) +{ + return numba_PyUnicode_ExtendedCase[code]; +} \ No newline at end of file diff --git a/rbc/unicodetype_db.ll b/rbc/unicodetype_db.ll new file mode 100644 index 00000000..c76eccc9 --- /dev/null +++ b/rbc/unicodetype_db.ll @@ -0,0 +1,2297 @@ + +%struct.numba_PyUnicode_TypeRecord = type { i32, i32, i32, i8, i8, i16 } + +@numba_PyUnicode_TypeRecords = dso_local local_unnamed_addr constant [497 x %struct.numba_PyUnicode_TypeRecord] [%struct.numba_PyUnicode_TypeRecord zeroinitializer, %struct.numba_PyUnicode_TypeRecord zeroinitializer, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 0, i32 0, i8 0, i8 0, i16 32 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 0, i32 0, i8 0, i8 0, i16 48 }, %struct.numba_PyUnicode_TypeRecord { i32 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i32 16778244, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778247, i32 17826821, i32 16778247, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778250, i32 17826824, i32 16778250, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778253, i32 17826827, i32 16778253, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778256, i32 17826830, i32 16778256, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778259, i32 17826833, i32 16778259, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778262, i32 17826836, i32 16778262, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778265, i32 17826839, i32 16778265, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778268, i32 17826842, i32 16778268, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778271, i32 17826845, i32 16778271, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778274, i32 17826848, i32 16778274, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778277, i32 17826851, i32 16778277, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778280, i32 17826854, i32 16778280, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778283, i32 17826857, i32 16778283, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778286, i32 17826860, i32 16778286, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778289, i32 17826863, i32 16778289, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778292, i32 17826866, i32 16778292, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778295, i32 17826869, i32 16778295, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778298, i32 17826872, i32 16778298, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778301, i32 17826875, i32 16778301, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778304, i32 17826878, i32 16778304, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778307, i32 17826881, i32 16778307, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778310, i32 17826884, i32 16778310, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778313, i32 17826887, i32 16778313, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778316, i32 17826890, i32 16778316, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778319, i32 17826893, i32 16778319, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778322, i32 17826896, i32 16778322, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778325, i32 17826899, i32 16778325, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778328, i32 17826902, i32 16778328, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778331, i32 17826905, i32 16778331, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778334, i32 17826908, i32 16778334, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778337, i32 17826911, i32 16778337, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778340, i32 17826914, i32 16778340, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778343, i32 17826917, i32 16778343, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778346, i32 17826920, i32 16778346, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778349, i32 17826923, i32 16778349, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778352, i32 17826926, i32 16778352, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778355, i32 17826929, i32 16778355, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778358, i32 17826932, i32 16778358, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 16778361, i32 17826935, i32 16778361, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555581, i32 18875514, i32 33555583, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555588, i32 18875521, i32 33555590, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555595, i32 18875528, i32 33555597, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 50332819, i32 19924111, i32 50332822, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 50332829, i32 19924121, i32 50332832, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555622, i32 18875555, i32 33555624, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555629, i32 18875562, i32 33555631, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555636, i32 18875569, i32 33555638, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555643, i32 18875576, i32 33555645, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555650, i32 18875583, i32 33555652, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555657, i32 18875590, i32 33555659, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 33555664, i32 18875597, i32 33555666, i8 0, i8 0, i16 26377 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 0, i32 0, i8 0, i8 0, i16 1025 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 0, i32 0, i8 0, i8 0, i16 5633 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 40, i32 0, i8 0, i8 0, i16 10113 }, %struct.numba_PyUnicode_TypeRecord { i32 -40, i32 0, i32 -40, i8 0, i8 0, i16 9993 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 34, i32 0, i8 0, i8 0, i16 10113 }, %struct.numba_PyUnicode_TypeRecord { i32 -34, i32 0, i32 -34, i8 0, i8 0, i16 9993 }, %struct.numba_PyUnicode_TypeRecord { i32 0, i32 0, i32 0, i8 0, i8 0, i16 9344 }], align 16 +@numba_PyUnicode_ExtendedCase = dso_local local_unnamed_addr constant [1236 x i32] [i32 181, i32 956, i32 924, i32 223, i32 115, i32 115, i32 83, i32 83, i32 83, i32 115, i32 105, i32 775, i32 304, i32 329, i32 700, i32 110, i32 700, i32 78, i32 383, i32 115, i32 83, i32 496, i32 106, i32 780, i32 74, i32 780, i32 837, i32 953, i32 921, i32 912, i32 953, i32 776, i32 769, i32 921, i32 776, i32 769, i32 944, i32 965, i32 776, i32 769, i32 933, i32 776, i32 769, i32 962, i32 963, i32 931, i32 976, i32 946, i32 914, i32 977, i32 952, i32 920, i32 981, i32 966, i32 934, i32 982, i32 960, i32 928, i32 1008, i32 954, i32 922, i32 1009, i32 961, i32 929, i32 1013, i32 949, i32 917, i32 1415, i32 1381, i32 1410, i32 1333, i32 1362, i32 1333, i32 1410, i32 43888, i32 5024, i32 5024, i32 43889, i32 5025, i32 5025, i32 43890, i32 5026, i32 5026, i32 43891, i32 5027, i32 5027, i32 43892, i32 5028, i32 5028, i32 43893, i32 5029, i32 5029, i32 43894, i32 5030, i32 5030, i32 43895, i32 5031, i32 5031, i32 43896, i32 5032, i32 5032, i32 43897, i32 5033, i32 5033, i32 43898, i32 5034, i32 5034, i32 43899, i32 5035, i32 5035, i32 43900, i32 5036, i32 5036, i32 43901, i32 5037, i32 5037, i32 43902, i32 5038, i32 5038, i32 43903, i32 5039, i32 5039, i32 43904, i32 5040, i32 5040, i32 43905, i32 5041, i32 5041, i32 43906, i32 5042, i32 5042, i32 43907, i32 5043, i32 5043, i32 43908, i32 5044, i32 5044, i32 43909, i32 5045, i32 5045, i32 43910, i32 5046, i32 5046, i32 43911, i32 5047, i32 5047, i32 43912, i32 5048, i32 5048, i32 43913, i32 5049, i32 5049, i32 43914, i32 5050, i32 5050, i32 43915, i32 5051, i32 5051, i32 43916, i32 5052, i32 5052, i32 43917, i32 5053, i32 5053, i32 43918, i32 5054, i32 5054, i32 43919, i32 5055, i32 5055, i32 43920, i32 5056, i32 5056, i32 43921, i32 5057, i32 5057, i32 43922, i32 5058, i32 5058, i32 43923, i32 5059, i32 5059, i32 43924, i32 5060, i32 5060, i32 43925, i32 5061, i32 5061, i32 43926, i32 5062, i32 5062, i32 43927, i32 5063, i32 5063, i32 43928, i32 5064, i32 5064, i32 43929, i32 5065, i32 5065, i32 43930, i32 5066, i32 5066, i32 43931, i32 5067, i32 5067, i32 43932, i32 5068, i32 5068, i32 43933, i32 5069, i32 5069, i32 43934, i32 5070, i32 5070, i32 43935, i32 5071, i32 5071, i32 43936, i32 5072, i32 5072, i32 43937, i32 5073, i32 5073, i32 43938, i32 5074, i32 5074, i32 43939, i32 5075, i32 5075, i32 43940, i32 5076, i32 5076, i32 43941, i32 5077, i32 5077, i32 43942, i32 5078, i32 5078, i32 43943, i32 5079, i32 5079, i32 43944, i32 5080, i32 5080, i32 43945, i32 5081, i32 5081, i32 43946, i32 5082, i32 5082, i32 43947, i32 5083, i32 5083, i32 43948, i32 5084, i32 5084, i32 43949, i32 5085, i32 5085, i32 43950, i32 5086, i32 5086, i32 43951, i32 5087, i32 5087, i32 43952, i32 5088, i32 5088, i32 43953, i32 5089, i32 5089, i32 43954, i32 5090, i32 5090, i32 43955, i32 5091, i32 5091, i32 43956, i32 5092, i32 5092, i32 43957, i32 5093, i32 5093, i32 43958, i32 5094, i32 5094, i32 43959, i32 5095, i32 5095, i32 43960, i32 5096, i32 5096, i32 43961, i32 5097, i32 5097, i32 43962, i32 5098, i32 5098, i32 43963, i32 5099, i32 5099, i32 43964, i32 5100, i32 5100, i32 43965, i32 5101, i32 5101, i32 43966, i32 5102, i32 5102, i32 43967, i32 5103, i32 5103, i32 5112, i32 5104, i32 5104, i32 5113, i32 5105, i32 5105, i32 5114, i32 5106, i32 5106, i32 5115, i32 5107, i32 5107, i32 5116, i32 5108, i32 5108, i32 5117, i32 5109, i32 5109, i32 5112, i32 5104, i32 5104, i32 5113, i32 5105, i32 5105, i32 5114, i32 5106, i32 5106, i32 5115, i32 5107, i32 5107, i32 5116, i32 5108, i32 5108, i32 5117, i32 5109, i32 5109, i32 7296, i32 1074, i32 1042, i32 7297, i32 1076, i32 1044, i32 7298, i32 1086, i32 1054, i32 7299, i32 1089, i32 1057, i32 7300, i32 1090, i32 1058, i32 7301, i32 1090, i32 1058, i32 7302, i32 1098, i32 1066, i32 7303, i32 1123, i32 1122, i32 7304, i32 42571, i32 42570, i32 7830, i32 104, i32 817, i32 72, i32 817, i32 7831, i32 116, i32 776, i32 84, i32 776, i32 7832, i32 119, i32 778, i32 87, i32 778, i32 7833, i32 121, i32 778, i32 89, i32 778, i32 7834, i32 97, i32 702, i32 65, i32 702, i32 7835, i32 7777, i32 7776, i32 223, i32 115, i32 115, i32 7838, i32 8016, i32 965, i32 787, i32 933, i32 787, i32 8018, i32 965, i32 787, i32 768, i32 933, i32 787, i32 768, i32 8020, i32 965, i32 787, i32 769, i32 933, i32 787, i32 769, i32 8022, i32 965, i32 787, i32 834, i32 933, i32 787, i32 834, i32 8064, i32 7936, i32 953, i32 7944, i32 921, i32 8072, i32 8065, i32 7937, i32 953, i32 7945, i32 921, i32 8073, i32 8066, i32 7938, i32 953, i32 7946, i32 921, i32 8074, i32 8067, i32 7939, i32 953, i32 7947, i32 921, i32 8075, i32 8068, i32 7940, i32 953, i32 7948, i32 921, i32 8076, i32 8069, i32 7941, i32 953, i32 7949, i32 921, i32 8077, i32 8070, i32 7942, i32 953, i32 7950, i32 921, i32 8078, i32 8071, i32 7943, i32 953, i32 7951, i32 921, i32 8079, i32 8064, i32 7936, i32 953, i32 7944, i32 921, i32 8072, i32 8065, i32 7937, i32 953, i32 7945, i32 921, i32 8073, i32 8066, i32 7938, i32 953, i32 7946, i32 921, i32 8074, i32 8067, i32 7939, i32 953, i32 7947, i32 921, i32 8075, i32 8068, i32 7940, i32 953, i32 7948, i32 921, i32 8076, i32 8069, i32 7941, i32 953, i32 7949, i32 921, i32 8077, i32 8070, i32 7942, i32 953, i32 7950, i32 921, i32 8078, i32 8071, i32 7943, i32 953, i32 7951, i32 921, i32 8079, i32 8080, i32 7968, i32 953, i32 7976, i32 921, i32 8088, i32 8081, i32 7969, i32 953, i32 7977, i32 921, i32 8089, i32 8082, i32 7970, i32 953, i32 7978, i32 921, i32 8090, i32 8083, i32 7971, i32 953, i32 7979, i32 921, i32 8091, i32 8084, i32 7972, i32 953, i32 7980, i32 921, i32 8092, i32 8085, i32 7973, i32 953, i32 7981, i32 921, i32 8093, i32 8086, i32 7974, i32 953, i32 7982, i32 921, i32 8094, i32 8087, i32 7975, i32 953, i32 7983, i32 921, i32 8095, i32 8080, i32 7968, i32 953, i32 7976, i32 921, i32 8088, i32 8081, i32 7969, i32 953, i32 7977, i32 921, i32 8089, i32 8082, i32 7970, i32 953, i32 7978, i32 921, i32 8090, i32 8083, i32 7971, i32 953, i32 7979, i32 921, i32 8091, i32 8084, i32 7972, i32 953, i32 7980, i32 921, i32 8092, i32 8085, i32 7973, i32 953, i32 7981, i32 921, i32 8093, i32 8086, i32 7974, i32 953, i32 7982, i32 921, i32 8094, i32 8087, i32 7975, i32 953, i32 7983, i32 921, i32 8095, i32 8096, i32 8032, i32 953, i32 8040, i32 921, i32 8104, i32 8097, i32 8033, i32 953, i32 8041, i32 921, i32 8105, i32 8098, i32 8034, i32 953, i32 8042, i32 921, i32 8106, i32 8099, i32 8035, i32 953, i32 8043, i32 921, i32 8107, i32 8100, i32 8036, i32 953, i32 8044, i32 921, i32 8108, i32 8101, i32 8037, i32 953, i32 8045, i32 921, i32 8109, i32 8102, i32 8038, i32 953, i32 8046, i32 921, i32 8110, i32 8103, i32 8039, i32 953, i32 8047, i32 921, i32 8111, i32 8096, i32 8032, i32 953, i32 8040, i32 921, i32 8104, i32 8097, i32 8033, i32 953, i32 8041, i32 921, i32 8105, i32 8098, i32 8034, i32 953, i32 8042, i32 921, i32 8106, i32 8099, i32 8035, i32 953, i32 8043, i32 921, i32 8107, i32 8100, i32 8036, i32 953, i32 8044, i32 921, i32 8108, i32 8101, i32 8037, i32 953, i32 8045, i32 921, i32 8109, i32 8102, i32 8038, i32 953, i32 8046, i32 921, i32 8110, i32 8103, i32 8039, i32 953, i32 8047, i32 921, i32 8111, i32 8114, i32 8048, i32 953, i32 8122, i32 921, i32 8122, i32 837, i32 8115, i32 945, i32 953, i32 913, i32 921, i32 8124, i32 8116, i32 940, i32 953, i32 902, i32 921, i32 902, i32 837, i32 8118, i32 945, i32 834, i32 913, i32 834, i32 8119, i32 945, i32 834, i32 953, i32 913, i32 834, i32 921, i32 913, i32 834, i32 837, i32 8115, i32 945, i32 953, i32 913, i32 921, i32 8124, i32 8126, i32 953, i32 921, i32 8130, i32 8052, i32 953, i32 8138, i32 921, i32 8138, i32 837, i32 8131, i32 951, i32 953, i32 919, i32 921, i32 8140, i32 8132, i32 942, i32 953, i32 905, i32 921, i32 905, i32 837, i32 8134, i32 951, i32 834, i32 919, i32 834, i32 8135, i32 951, i32 834, i32 953, i32 919, i32 834, i32 921, i32 919, i32 834, i32 837, i32 8131, i32 951, i32 953, i32 919, i32 921, i32 8140, i32 8146, i32 953, i32 776, i32 768, i32 921, i32 776, i32 768, i32 8147, i32 953, i32 776, i32 769, i32 921, i32 776, i32 769, i32 8150, i32 953, i32 834, i32 921, i32 834, i32 8151, i32 953, i32 776, i32 834, i32 921, i32 776, i32 834, i32 8162, i32 965, i32 776, i32 768, i32 933, i32 776, i32 768, i32 8163, i32 965, i32 776, i32 769, i32 933, i32 776, i32 769, i32 8164, i32 961, i32 787, i32 929, i32 787, i32 8166, i32 965, i32 834, i32 933, i32 834, i32 8167, i32 965, i32 776, i32 834, i32 933, i32 776, i32 834, i32 8178, i32 8060, i32 953, i32 8186, i32 921, i32 8186, i32 837, i32 8179, i32 969, i32 953, i32 937, i32 921, i32 8188, i32 8180, i32 974, i32 953, i32 911, i32 921, i32 911, i32 837, i32 8182, i32 969, i32 834, i32 937, i32 834, i32 8183, i32 969, i32 834, i32 953, i32 937, i32 834, i32 921, i32 937, i32 834, i32 837, i32 8179, i32 969, i32 953, i32 937, i32 921, i32 8188, i32 43888, i32 5024, i32 5024, i32 43889, i32 5025, i32 5025, i32 43890, i32 5026, i32 5026, i32 43891, i32 5027, i32 5027, i32 43892, i32 5028, i32 5028, i32 43893, i32 5029, i32 5029, i32 43894, i32 5030, i32 5030, i32 43895, i32 5031, i32 5031, i32 43896, i32 5032, i32 5032, i32 43897, i32 5033, i32 5033, i32 43898, i32 5034, i32 5034, i32 43899, i32 5035, i32 5035, i32 43900, i32 5036, i32 5036, i32 43901, i32 5037, i32 5037, i32 43902, i32 5038, i32 5038, i32 43903, i32 5039, i32 5039, i32 43904, i32 5040, i32 5040, i32 43905, i32 5041, i32 5041, i32 43906, i32 5042, i32 5042, i32 43907, i32 5043, i32 5043, i32 43908, i32 5044, i32 5044, i32 43909, i32 5045, i32 5045, i32 43910, i32 5046, i32 5046, i32 43911, i32 5047, i32 5047, i32 43912, i32 5048, i32 5048, i32 43913, i32 5049, i32 5049, i32 43914, i32 5050, i32 5050, i32 43915, i32 5051, i32 5051, i32 43916, i32 5052, i32 5052, i32 43917, i32 5053, i32 5053, i32 43918, i32 5054, i32 5054, i32 43919, i32 5055, i32 5055, i32 43920, i32 5056, i32 5056, i32 43921, i32 5057, i32 5057, i32 43922, i32 5058, i32 5058, i32 43923, i32 5059, i32 5059, i32 43924, i32 5060, i32 5060, i32 43925, i32 5061, i32 5061, i32 43926, i32 5062, i32 5062, i32 43927, i32 5063, i32 5063, i32 43928, i32 5064, i32 5064, i32 43929, i32 5065, i32 5065, i32 43930, i32 5066, i32 5066, i32 43931, i32 5067, i32 5067, i32 43932, i32 5068, i32 5068, i32 43933, i32 5069, i32 5069, i32 43934, i32 5070, i32 5070, i32 43935, i32 5071, i32 5071, i32 43936, i32 5072, i32 5072, i32 43937, i32 5073, i32 5073, i32 43938, i32 5074, i32 5074, i32 43939, i32 5075, i32 5075, i32 43940, i32 5076, i32 5076, i32 43941, i32 5077, i32 5077, i32 43942, i32 5078, i32 5078, i32 43943, i32 5079, i32 5079, i32 43944, i32 5080, i32 5080, i32 43945, i32 5081, i32 5081, i32 43946, i32 5082, i32 5082, i32 43947, i32 5083, i32 5083, i32 43948, i32 5084, i32 5084, i32 43949, i32 5085, i32 5085, i32 43950, i32 5086, i32 5086, i32 43951, i32 5087, i32 5087, i32 43952, i32 5088, i32 5088, i32 43953, i32 5089, i32 5089, i32 43954, i32 5090, i32 5090, i32 43955, i32 5091, i32 5091, i32 43956, i32 5092, i32 5092, i32 43957, i32 5093, i32 5093, i32 43958, i32 5094, i32 5094, i32 43959, i32 5095, i32 5095, i32 43960, i32 5096, i32 5096, i32 43961, i32 5097, i32 5097, i32 43962, i32 5098, i32 5098, i32 43963, i32 5099, i32 5099, i32 43964, i32 5100, i32 5100, i32 43965, i32 5101, i32 5101, i32 43966, i32 5102, i32 5102, i32 43967, i32 5103, i32 5103, i32 64256, i32 102, i32 102, i32 70, i32 70, i32 70, i32 102, i32 64257, i32 102, i32 105, i32 70, i32 73, i32 70, i32 105, i32 64258, i32 102, i32 108, i32 70, i32 76, i32 70, i32 108, i32 64259, i32 102, i32 102, i32 105, i32 70, i32 70, i32 73, i32 70, i32 102, i32 105, i32 64260, i32 102, i32 102, i32 108, i32 70, i32 70, i32 76, i32 70, i32 102, i32 108, i32 64261, i32 115, i32 116, i32 83, i32 84, i32 83, i32 116, i32 64262, i32 115, i32 116, i32 83, i32 84, i32 83, i32 116, i32 64275, i32 1396, i32 1398, i32 1348, i32 1350, i32 1348, i32 1398, i32 64276, i32 1396, i32 1381, i32 1348, i32 1333, i32 1348, i32 1381, i32 64277, i32 1396, i32 1387, i32 1348, i32 1339, i32 1348, i32 1387, i32 64278, i32 1406, i32 1398, i32 1358, i32 1350, i32 1358, i32 1398, i32 64279, i32 1396, i32 1389, i32 1348, i32 1341, i32 1348, i32 1389], align 16 +@index1 = internal unnamed_addr constant [8704 x i16] [i16 0, i16 1, i16 2, i16 3, i16 4, i16 5, i16 6, i16 7, i16 8, i16 9, i16 10, i16 11, i16 12, i16 13, i16 14, i16 15, i16 16, i16 17, i16 18, i16 19, i16 20, i16 21, i16 22, i16 23, i16 24, i16 25, i16 26, i16 27, i16 28, i16 29, i16 30, i16 31, i16 32, i16 33, i16 34, i16 34, i16 35, i16 36, i16 37, i16 38, i16 39, i16 34, i16 34, i16 34, i16 40, i16 41, i16 42, i16 43, i16 44, i16 45, i16 46, i16 47, i16 48, i16 49, i16 50, i16 51, i16 52, i16 53, i16 54, i16 55, i16 56, i16 57, i16 58, i16 59, i16 60, i16 61, i16 62, i16 63, i16 64, i16 64, i16 64, i16 64, i16 65, i16 66, i16 64, i16 64, i16 64, i16 64, i16 67, i16 68, i16 64, i16 64, i16 64, i16 64, i16 64, i16 64, i16 69, i16 70, i16 71, i16 72, i16 73, i16 74, i16 75, i16 76, i16 64, i16 77, i16 78, i16 79, i16 80, i16 81, i16 82, i16 83, i16 64, i16 64, i16 84, i16 85, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 86, i16 34, i16 34, i16 34, i16 34, i16 34, i16 87, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 88, i16 89, i16 90, i16 91, i16 34, i16 34, i16 34, i16 92, i16 34, i16 34, i16 34, i16 93, i16 94, i16 34, i16 34, i16 34, i16 34, i16 34, i16 95, i16 34, i16 34, i16 34, i16 96, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 97, i16 98, i16 99, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 100, i16 101, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 102, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 103, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 104, i16 34, i16 34, i16 34, i16 34, i16 100, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 103, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 105, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 106, i16 107, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 108, i16 109, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 110, i16 111, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 112, i16 34, i16 34, i16 113, i16 114, i16 115, i16 116, i16 117, i16 118, i16 119, i16 120, i16 121, i16 122, i16 123, i16 124, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 125, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 127, i16 128, i16 129, i16 130, i16 131, i16 132, i16 133, i16 34, i16 134, i16 135, i16 136, i16 137, i16 138, i16 139, i16 140, i16 141, i16 142, i16 143, i16 144, i16 145, i16 146, i16 147, i16 148, i16 149, i16 150, i16 144, i16 34, i16 34, i16 151, i16 144, i16 152, i16 153, i16 154, i16 155, i16 156, i16 157, i16 158, i16 159, i16 160, i16 161, i16 162, i16 144, i16 163, i16 144, i16 164, i16 144, i16 165, i16 166, i16 167, i16 168, i16 169, i16 170, i16 171, i16 144, i16 172, i16 173, i16 144, i16 174, i16 175, i16 176, i16 177, i16 144, i16 178, i16 179, i16 144, i16 144, i16 180, i16 181, i16 144, i16 144, i16 182, i16 183, i16 184, i16 185, i16 144, i16 186, i16 144, i16 144, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 187, i16 188, i16 34, i16 189, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 190, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 34, i16 34, i16 34, i16 34, i16 191, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 34, i16 34, i16 34, i16 34, i16 192, i16 193, i16 194, i16 195, i16 144, i16 144, i16 144, i16 144, i16 196, i16 197, i16 198, i16 199, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 34, i16 200, i16 34, i16 34, i16 34, i16 34, i16 34, i16 201, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 34, i16 34, i16 202, i16 34, i16 34, i16 203, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 204, i16 205, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 64, i16 206, i16 207, i16 208, i16 209, i16 210, i16 211, i16 144, i16 212, i16 213, i16 214, i16 215, i16 216, i16 217, i16 218, i16 219, i16 64, i16 64, i16 64, i16 64, i16 220, i16 221, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 222, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 34, i16 223, i16 224, i16 144, i16 144, i16 144, i16 144, i16 144, i16 225, i16 226, i16 144, i16 144, i16 227, i16 228, i16 144, i16 144, i16 229, i16 230, i16 231, i16 232, i16 233, i16 144, i16 64, i16 234, i16 64, i16 64, i16 64, i16 64, i16 64, i16 235, i16 236, i16 237, i16 238, i16 239, i16 240, i16 241, i16 242, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 144, i16 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i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 126, i16 262], align 16 +@index2 = internal unnamed_addr constant [33664 x i16] [i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 2, i16 3, i16 3, i16 3, i16 3, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 3, i16 3, i16 3, i16 2, i16 4, i16 5, i16 5, i16 5, i16 5, i16 5, i16 5, i16 6, i16 5, i16 5, i16 5, i16 5, i16 5, i16 5, i16 6, i16 5, i16 7, i16 8, i16 9, i16 10, i16 11, i16 12, i16 13, i16 14, i16 15, i16 16, i16 6, i16 5, i16 5, i16 5, i16 5, i16 5, i16 5, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 5, i16 5, i16 5, i16 6, i16 18, i16 6, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 5, i16 5, i16 5, i16 5, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 3, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 2, i16 5, i16 5, i16 5, i16 5, i16 5, i16 5, i16 5, i16 6, i16 5, i16 20, i16 5, i16 5, i16 21, i16 5, i16 6, i16 5, i16 5, i16 22, i16 23, i16 6, i16 24, i16 5, i16 25, i16 6, i16 26, i16 20, i16 5, i16 27, i16 27, i16 27, i16 5, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 5, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 28, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 5, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 29, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 32, i16 33, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 20, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 34, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 35, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 36, i16 37, i16 38, i16 30, i16 31, i16 30, i16 31, i16 39, i16 30, i16 31, i16 40, i16 40, i16 30, i16 31, i16 20, i16 41, i16 42, i16 43, i16 30, i16 31, i16 40, i16 44, i16 45, i16 46, i16 47, i16 30, i16 31, i16 48, i16 20, i16 46, i16 49, i16 50, i16 51, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 52, i16 30, i16 31, i16 52, i16 20, i16 20, i16 30, i16 31, i16 52, i16 30, i16 31, i16 53, i16 53, i16 30, i16 31, i16 30, i16 31, i16 54, i16 30, i16 31, i16 20, i16 55, i16 30, i16 31, i16 20, i16 56, i16 55, i16 55, i16 55, i16 55, i16 57, i16 58, i16 59, i16 57, i16 58, i16 59, i16 57, i16 58, i16 59, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 60, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 61, i16 57, i16 58, i16 59, i16 30, i16 31, i16 62, i16 63, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 64, i16 20, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 65, i16 30, i16 31, i16 66, i16 67, i16 68, i16 68, i16 30, i16 31, i16 69, i16 70, i16 71, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 72, i16 73, i16 74, i16 75, i16 76, i16 20, i16 77, i16 77, i16 20, i16 78, i16 20, i16 79, i16 80, i16 20, i16 20, i16 20, i16 77, i16 81, i16 20, i16 82, i16 20, i16 83, i16 84, i16 20, i16 85, i16 86, i16 84, i16 87, i16 88, i16 20, i16 20, i16 86, i16 20, i16 89, i16 90, i16 20, i16 20, i16 91, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 92, i16 20, i16 20, i16 93, i16 20, i16 20, i16 93, i16 20, i16 20, i16 20, i16 94, i16 93, i16 95, i16 96, i16 96, i16 97, i16 20, i16 20, i16 20, i16 20, i16 20, i16 98, i16 20, i16 55, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 99, i16 100, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 20, i16 101, i16 101, i16 101, i16 101, i16 101, i16 101, i16 101, i16 101, i16 101, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 101, i16 101, i16 6, i16 6, i16 6, i16 6, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 102, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 101, i16 101, i16 101, i16 101, i16 101, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 102, i16 6, i16 102, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 6, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 103, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 30, i16 31, i16 30, i16 31, i16 102, i16 6, i16 30, i16 31, i16 0, i16 0, i16 104, i16 50, i16 50, i16 50, i16 5, i16 105, i16 0, i16 0, i16 0, i16 0, i16 6, i16 6, i16 106, i16 25, i16 107, i16 107, i16 107, i16 0, i16 108, i16 0, i16 109, i16 109, i16 110, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 0, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 17, i16 111, i16 112, i16 112, i16 112, i16 113, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 114, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 19, i16 115, i16 116, i16 116, i16 117, i16 118, i16 119, i16 120, i16 120, i16 120, i16 121, i16 122, i16 123, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 30, i16 31, i16 124, i16 125, i16 126, i16 127, i16 128, i16 129, i16 5, i16 30, i16 31, i16 130, i16 30, i16 31, i16 20, i16 64, i16 64, i16 64, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 131, i16 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i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 21, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 25, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 0, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 1, i16 0, i16 0], align 16 + +define dso_local double @numba_PyUnicode_ToNumeric(i32 %0) local_unnamed_addr #0 { + switch i32 %0, label %145 [ + i32 3891, label %146 + i32 48, label %2 + i32 1632, label %2 + i32 1776, label %2 + i32 1984, label %2 + i32 2406, label %2 + i32 2534, label %2 + i32 2662, label %2 + i32 2790, label %2 + i32 2918, label %2 + i32 3046, label %2 + i32 3174, label %2 + i32 3192, label %2 + i32 3302, label %2 + i32 3430, label %2 + i32 3558, label %2 + i32 3664, label %2 + i32 3792, label %2 + i32 3872, label %2 + i32 4160, label %2 + i32 4240, label %2 + i32 6112, label %2 + i32 6128, label %2 + i32 6160, label %2 + i32 6470, label %2 + i32 6608, label %2 + i32 6784, label %2 + i32 6800, label %2 + i32 6992, label %2 + i32 7088, label %2 + i32 7232, label %2 + i32 7248, label %2 + i32 8304, label %2 + i32 8320, label %2 + i32 8585, label %2 + i32 9450, label %2 + i32 9471, label %2 + i32 12295, label %2 + i32 38646, label %2 + i32 42528, label %2 + i32 42735, label %2 + i32 43216, label %2 + i32 43264, label %2 + i32 43472, label %2 + i32 43504, label %2 + i32 43600, label %2 + i32 44016, label %2 + i32 63922, label %2 + i32 65296, label %2 + i32 65930, label %2 + i32 66720, label %2 + i32 68912, label %2 + i32 69734, label %2 + i32 69872, label %2 + i32 69942, label %2 + i32 70096, label %2 + i32 70384, label %2 + i32 70736, label %2 + i32 70864, label %2 + i32 71248, label %2 + i32 71360, label %2 + i32 71472, label %2 + i32 71904, label %2 + i32 72784, label %2 + i32 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%146 + +12: ; preds = %1 + br label %146 + +13: ; preds = %1, %1 + br label %146 + +14: ; preds = %1, %1 + br label %146 + +15: ; preds = %1 + br label %146 + +16: ; preds = %1, %1, %1, %1, %1, %1 + br label %146 + +17: ; preds = %1 + br label %146 + +18: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +19: ; preds = %1 + br label %146 + +20: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +21: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +22: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +23: ; preds = %1, %1, %1, %1, %1 + br label %146 + +24: ; preds = %1 + br label %146 + 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= %1 + br label %146 + +68: ; preds = %1, %1, %1, %1, %1, %1, %1 + br label %146 + +69: ; preds = %1 + br label %146 + +70: ; preds = %1 + br label %146 + +71: ; preds = %1 + br label %146 + +72: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +73: ; preds = %1, %1, %1, %1, %1, %1 + br label %146 + +74: ; preds = %1, %1, %1 + br label %146 + +75: ; preds = %1, %1, %1 + br label %146 + +76: ; preds = %1 + br label %146 + +77: ; preds = %1 + br label %146 + +78: ; preds = %1 + br label %146 + +79: ; preds = %1 + br label %146 + +80: ; preds = %1 + br label %146 + +81: ; preds = %1 + br label %146 + +82: ; preds = %1 + br label %146 + +83: ; preds = %1 + br label %146 + +84: ; preds = %1 + br label %146 + +85: ; preds = %1 + br label %146 + +86: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, 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%146 + +103: ; preds = %1 + br label %146 + +104: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +105: ; preds = %1 + br label %146 + +106: ; preds = %1 + br label %146 + +107: ; preds = %1, %1 + br label %146 + +108: ; preds = %1 + br label %146 + +109: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +110: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +111: ; preds = %1, %1, %1, %1, %1, %1, %1 + br label %146 + +112: ; preds = %1, %1, %1, %1, %1, %1 + br label %146 + +113: ; preds = %1 + br label %146 + +114: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +115: ; preds = %1 + br label %146 + +116: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +117: ; preds = %1, %1, %1, %1, %1 + br label %146 + +118: ; preds = %1, %1, %1 + br label %146 + +119: ; preds = %1, %1, %1 + br label %146 + +120: ; preds = %1 + br label %146 + +121: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +122: ; preds = %1 + br label %146 + +123: ; preds = %1 + br label %146 + +124: ; preds = %1 + br label %146 + +125: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +126: ; preds = %1, %1, %1, %1, %1 + br label %146 + +127: ; preds = %1, %1, %1 + br label %146 + +128: ; preds = %1, %1, %1 + br label %146 + +129: ; preds = %1 + br label %146 + +130: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +131: ; preds = %1 + br label %146 + +132: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +133: ; preds = %1, %1, %1, %1, %1 + br label %146 + +134: ; preds = %1, %1, %1 + br label %146 + +135: ; preds = %1, %1, %1 + br label %146 + +136: ; preds = %1 + br label %146 + +137: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +138: ; preds = %1 + br label %146 + +139: ; preds = %1 + br label %146 + +140: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1 + br label %146 + +141: ; preds = %1, %1, %1, %1, %1, %1 + br label %146 + +142: ; preds = %1, %1, %1 + br label %146 + +143: ; preds = %1, %1, %1 + br label %146 + +144: ; preds = %1 + br label %146 + +145: ; preds = %1 + br label %146 + +146: ; preds = %1, %145, %144, %143, %142, %141, %140, %139, %138, %137, %136, %135, %134, %133, %132, %131, %130, %129, %128, %127, %126, %125, %124, %123, %122, %121, %120, %119, %118, %117, %116, %115, %114, %113, %112, %111, %110, %109, %108, %107, %106, %105, %104, %103, %102, %101, %100, %99, %98, %97, %96, %95, %94, %93, %92, %91, %90, %89, %88, %87, %86, %85, %84, %83, %82, %81, %80, %79, %78, %77, %76, %75, %74, %73, %72, %71, %70, %69, %68, %67, %66, %65, %64, %63, %62, %61, %60, %59, %58, %57, %56, %55, %54, %53, %52, %51, %50, %49, %48, %47, %46, %45, %44, %43, %42, %41, %40, %39, %38, %37, %36, %35, %34, %33, %32, %31, %30, %29, %28, %27, %26, %25, %24, %23, %22, %21, %20, %19, %18, %17, %16, %15, %14, %13, %12, %11, %10, %9, %8, %7, %6, %5, %4, %3, %2 + %147 = phi double [ -1.000000e+00, %145 ], [ 9.000000e+05, %144 ], [ 9.000000e+04, %143 ], [ 9.000000e+03, %142 ], [ 9.000000e+02, %141 ], [ 9.000000e+01, %140 ], [ 4.500000e+00, %139 ], [ 7.500000e-01, %138 ], [ 9.000000e+00, %137 ], [ 8.000000e+05, %136 ], [ 8.000000e+04, %135 ], [ 8.000000e+03, %134 ], [ 8.000000e+02, %133 ], [ 8.000000e+01, %132 ], [ 0x3FE5555555555555, %131 ], [ 8.000000e+00, %130 ], [ 7.000000e+05, %129 ], [ 7.000000e+04, %128 ], [ 7.000000e+03, %127 ], [ 7.000000e+02, %126 ], [ 7.000000e+01, %125 ], [ 8.750000e-01, %124 ], [ 3.500000e+00, %123 ], [ 0x3FE2AAAAAAAAAAAB, %122 ], [ 7.000000e+00, %121 ], [ 6.000000e+05, %120 ], [ 6.000000e+04, %119 ], [ 6.000000e+03, %118 ], [ 6.000000e+02, %117 ], [ 6.000000e+01, %116 ], [ 5.000000e-01, %115 ], [ 6.000000e+00, %114 ], [ 5.000000e+05, %113 ], [ 5.000000e+04, %112 ], [ 5.000000e+03, %111 ], [ 5.000000e+02, %110 ], [ 5.000000e+01, %109 ], [ 6.250000e-01, %108 ], [ 0x3FEAAAAAAAAAAAAB, %107 ], [ 2.500000e+00, %106 ], [ 0x3FDAAAAAAAAAAAAB, %105 ], [ 5.000000e+00, %104 ], [ 4.900000e+01, %103 ], [ 4.800000e+01, %102 ], [ 4.700000e+01, %101 ], [ 4.600000e+01, %100 ], [ 4.500000e+01, %99 ], [ 4.400000e+01, %98 ], [ 4.320000e+05, %97 ], [ 4.300000e+01, %96 ], [ 4.200000e+01, %95 ], [ 4.100000e+01, %94 ], [ 4.000000e+05, %93 ], [ 4.000000e+04, %92 ], [ 4.000000e+03, %91 ], [ 4.000000e+02, %90 ], [ 4.000000e+01, %89 ], [ 8.000000e-01, %88 ], [ 0x3FD5555555555555, %87 ], [ 4.000000e+00, %86 ], [ 3.900000e+01, %85 ], [ 3.800000e+01, %84 ], [ 3.700000e+01, %83 ], [ 3.600000e+01, %82 ], [ 3.500000e+01, %81 ], [ 3.400000e+01, %80 ], [ 3.300000e+01, %79 ], [ 3.200000e+01, %78 ], [ 3.100000e+01, %77 ], [ 3.000000e+05, %76 ], [ 3.000000e+04, %75 ], [ 3.000000e+03, %74 ], [ 3.000000e+02, %73 ], [ 3.000000e+01, %72 ], [ 3.750000e-02, %71 ], [ 3.750000e-01, %70 ], [ 6.000000e-01, %69 ], [ 7.500000e-01, %68 ], [ 1.500000e-01, %67 ], [ 1.500000e+00, %66 ], [ 1.875000e-01, %65 ], [ 2.500000e-01, %64 ], [ 3.000000e+00, %63 ], [ 2.900000e+01, %62 ], [ 2.800000e+01, %61 ], [ 2.700000e+01, %60 ], [ 2.600000e+01, %59 ], [ 2.500000e+01, %58 ], [ 2.400000e+01, %57 ], [ 2.300000e+01, %56 ], [ 2.200000e+01, %55 ], [ 2.160000e+05, %54 ], [ 2.100000e+01, %53 ], [ 2.000000e+07, %52 ], [ 2.000000e+05, %51 ], [ 2.000000e+04, %50 ], [ 2.000000e+03, %49 ], [ 2.000000e+02, %48 ], [ 2.000000e+01, %47 ], [ 4.000000e-01, %46 ], [ 0x3FE5555555555555, %45 ], [ 0x3FC5555555555555, %44 ], [ 2.000000e+00, %43 ], [ 1.900000e+01, %42 ], [ 1.800000e+01, %41 ], [ 8.500000e+00, %40 ], [ 1.700000e+01, %39 ], [ 1.600000e+01, %38 ], [ 7.500000e+00, %37 ], [ 1.500000e+01, %36 ], [ 1.400000e+01, %35 ], [ 6.500000e+00, %34 ], [ 1.300000e+01, %33 ], [ 1.200000e+01, %32 ], [ 5.500000e+00, %31 ], [ 0x3FED555555555555, %30 ], [ 1.100000e+01, %29 ], [ 1.000000e+12, %28 ], [ 1.000000e+10, %27 ], [ 1.000000e+08, %26 ], [ 1.000000e+07, %25 ], [ 1.000000e+06, %24 ], [ 1.000000e+05, %23 ], [ 1.000000e+04, %22 ], [ 1.000000e+03, %21 ], [ 1.000000e+02, %20 ], [ 0x3FEAAAAAAAAAAAAB, %19 ], [ 1.000000e+01, %18 ], [ 0x3FBC71C71C71C71C, %17 ], [ 1.250000e-01, %16 ], [ 0x3FC2492492492492, %15 ], [ 0x3FC5555555555555, %14 ], [ 2.000000e-01, %13 ], [ 2.500000e-02, %12 ], [ 2.500000e-01, %11 ], [ 0x3FD5555555555555, %10 ], [ 5.000000e-02, %9 ], [ 5.000000e-01, %8 ], [ 6.250000e-03, %7 ], [ 6.250000e-02, %6 ], [ 0x3FB5555555555555, %5 ], [ 1.000000e-01, %4 ], [ 1.000000e+00, %3 ], [ 0.000000e+00, %2 ], [ -5.000000e-01, %1 ] + ret double %147 +} + +define dso_local i32 @numba_PyUnicode_IsWhitespace(i32 %0) local_unnamed_addr #0 { + switch i32 %0, label %2 [ + i32 9, label %3 + i32 10, label %3 + i32 11, label %3 + i32 12, label %3 + i32 13, label %3 + i32 28, label %3 + i32 29, label %3 + i32 30, label %3 + i32 31, label %3 + i32 32, label %3 + i32 133, label %3 + i32 160, label %3 + i32 5760, label %3 + i32 8192, label %3 + i32 8193, label %3 + i32 8194, label %3 + i32 8195, label %3 + i32 8196, label %3 + i32 8197, label %3 + i32 8198, label %3 + i32 8199, label %3 + i32 8200, label %3 + i32 8201, label %3 + i32 8202, label %3 + i32 8232, label %3 + i32 8233, label %3 + i32 8239, label %3 + i32 8287, label %3 + i32 12288, label %3 + ] + +2: ; preds = %1 + br label %3 + +3: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %2 + %4 = phi i32 [ 0, %2 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ] + ret i32 %4 +} + +define dso_local i32 @numba_PyUnicode_IsLinebreak(i32 %0) local_unnamed_addr #0 { + switch i32 %0, label %2 [ + i32 10, label %3 + i32 11, label %3 + i32 12, label %3 + i32 13, label %3 + i32 28, label %3 + i32 29, label %3 + i32 30, label %3 + i32 133, label %3 + i32 8232, label %3 + i32 8233, label %3 + ] + +2: ; preds = %1 + br label %3 + +3: ; preds = %1, %1, %1, %1, %1, %1, %1, %1, %1, %1, %2 + %4 = phi i32 [ 0, %2 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ], [ 1, %1 ] + ret i32 %4 +} + +define dso_local void @numba_gettyperecord(i32 %0, i32* nocapture %1, i32* nocapture %2, i32* nocapture %3, i8* nocapture %4, i8* nocapture %5, i16* nocapture %6) local_unnamed_addr #1 { + %8 = icmp ugt i32 %0, 1114111 + br i1 %8, label %22, label %9 + +9: ; preds = %7 + %10 = lshr i32 %0, 7 + %11 = zext i32 %10 to i64 + %12 = getelementptr inbounds [8704 x i16], [8704 x i16]* @index1, i64 0, i64 %11 + %13 = load i16, i16* %12, align 2 + %14 = zext i16 %13 to i32 + %15 = shl nuw nsw i32 %14, 7 + %16 = and i32 %0, 127 + %17 = or i32 %15, %16 + %18 = zext i32 %17 to i64 + %19 = getelementptr inbounds [33664 x i16], [33664 x i16]* @index2, i64 0, i64 %18 + %20 = load i16, i16* %19, align 2 + %21 = zext i16 %20 to i64 + br label %22 + +22: ; preds = %7, %9 + %23 = phi i64 [ %21, %9 ], [ 0, %7 ] + %24 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 0 + %25 = load i32, i32* %24, align 16 + store i32 %25, i32* %1, align 4 + %26 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 1 + %27 = load i32, i32* %26, align 4 + store i32 %27, i32* %2, align 4 + %28 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 2 + %29 = load i32, i32* %28, align 8 + store i32 %29, i32* %3, align 4 + %30 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 3 + %31 = load i8, i8* %30, align 4 + store i8 %31, i8* %4, align 1 + %32 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 4 + %33 = load i8, i8* %32, align 1 + store i8 %33, i8* %5, align 1 + %34 = getelementptr inbounds [497 x %struct.numba_PyUnicode_TypeRecord], [497 x %struct.numba_PyUnicode_TypeRecord]* @numba_PyUnicode_TypeRecords, i64 0, i64 %23, i32 5 + %35 = load i16, i16* %34, align 2 + store i16 %35, i16* %6, align 2 + ret void +} + +define dso_local i32 @numba_get_PyUnicode_ExtendedCase(i32 %0) local_unnamed_addr #0 { + %2 = sext i32 %0 to i64 + %3 = getelementptr inbounds [1236 x i32], [1236 x i32]* @numba_PyUnicode_ExtendedCase, i64 0, i64 %2 + %4 = load i32, i32* %3, align 4 + ret i32 %4 +} + +attributes #0 = { norecurse nounwind readnone uwtable willreturn "disable-tail-calls"="false" "frame-pointer"="none" "less-precise-fpmad"="false" "min-legal-vector-width"="0" "no-infs-fp-math"="false" "no-jump-tables"="false" "no-nans-fp-math"="false" "no-signed-zeros-fp-math"="false" "no-trapping-math"="true" "stack-protector-buffer-size"="8" "target-cpu"="x86-64" "target-features"="+cx8,+fxsr,+mmx,+sse,+sse2,+x87" "tune-cpu"="generic" "unsafe-fp-math"="false" "use-soft-float"="false" } +attributes #1 = { nofree norecurse nounwind uwtable willreturn writeonly "disable-tail-calls"="false" "frame-pointer"="none" "less-precise-fpmad"="false" "min-legal-vector-width"="0" "no-infs-fp-math"="false" "no-jump-tables"="false" "no-nans-fp-math"="false" "no-signed-zeros-fp-math"="false" "no-trapping-math"="true" "stack-protector-buffer-size"="8" "target-cpu"="x86-64" "target-features"="+cx8,+fxsr,+mmx,+sse,+sse2,+x87" "tune-cpu"="generic" "unsafe-fp-math"="false" "use-soft-float"="false" } diff --git a/setup.py b/setup.py index 577b3002..afa53520 100644 --- a/setup.py +++ b/setup.py @@ -66,7 +66,7 @@ def setup_package(): "Topic :: Software Development", ], packages=find_packages(), - package_data={'': ['*.thrift']}, + package_data={'': ['*.thrift', 'unicodetype_db.ll']}, install_requires=install_requires, tests_require=tests_require, )