xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

7d96309ca1db3f1bde1f826f3193ebf62648fa70

20,525

py

Python

launchkey/clients/organization.py

bgroveben/launchkey-python

c102d76040221059e7b87d96496edb1be3824d3b

[ "MIT" ]

1

2018-12-06T04:42:35.000Z

launchkey/clients/organization.py

bgroveben/launchkey-python

c102d76040221059e7b87d96496edb1be3824d3b

[ "MIT" ]

1

2018-12-11T22:31:03.000Z

launchkey/clients/organization.py

bgroveben/launchkey-python

c102d76040221059e7b87d96496edb1be3824d3b

[ "MIT" ]

null

from .base import BaseClient, api_call from launchkey.utils import iso_format from launchkey.entities.shared import PublicKey from launchkey.entities.service import Service, ServiceSecurityPolicy from launchkey.entities.directory import Directory from launchkey.entities.validation import DirectoryValidator, ServiceValidator, ServiceSecurityPolicyValidator, \ PublicKeyValidator try: from base64 import encodebytes as encodestring except ImportError: from base64 import encodestring class OrganizationClient(BaseClient): def __init__(self, subject_id, transport): super(OrganizationClient, self).__init__('org', subject_id, transport) @api_call def create_service(self, name, description=None, icon=None, callback_url=None, active=True): """ Creates an Organization Service :param name: Unique name that will be displayed in an Auth Request :param description: Optional description that can be viewed in the Admin Center or when retrieving the Service. :param icon: Optional URL to an icon that will be displayed in an Auth Request :param callback_url: URL that Webhooks will be sent to :param active: Whether the Service should be able to send Auth Requests :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.ServiceNameTaken - Service name already taken :return: String - ID of the Service that is created """ return self._transport.post("/organization/v3/services", self._subject, name=name, description=description, icon=icon, callback_url=callback_url, active=active).data['id'] @api_call def get_all_services(self): """ Retrieves all Services belonging to an Organization :return: List - launchkey.entities.service.Service object containing Service details """ return [Service(self._validate_response(service, ServiceValidator)) for service in self._transport.get("/organization/v3/services", self._subject).data] @api_call def get_services(self, service_ids): """ Retrieves Services based on an input list of Service IDs :param service_ids: List of unique Service IDs :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :return: List - launchkey.entities.service.Service object containing Service details """ return [Service(self._validate_response(service, ServiceValidator)) for service in self._transport.post("/organization/v3/services/list", self._subject, service_ids=[str(service_id) for service_id in service_ids]).data] @api_call def get_service(self, service_id): """ Retrieves a Service based on an input Service ID :param service_id: Unique Service ID :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :return: launchkey.entities.service.Service object containing Service details """ return Service(self._validate_response( self._transport.post("/organization/v3/services/list", self._subject, service_ids=[str(service_id)]).data[0], ServiceValidator)) @api_call def update_service(self, service_id, name=False, description=False, icon=False, callback_url=False, active=None): """ Updates a Service's general settings. If an optional parameter is not included it will not be updated. :param service_id: Unique Service ID :param name: Unique name that will be displayed in an Auth Request :param description: Description that can be viewed in the Admin Center or when retrieving the Service. :param icon: URL to an icon that will be displayed in an Auth Request :param callback_url: URL that Webhooks will be sent to :param active: Whether the Service should be able to send Auth Requests :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.ServiceNameTaken - Service name already taken :raise: launchkey.exceptions.ServiceNotFound - No Service could be found matching the input ID :return: """ kwargs = {"service_id": str(service_id)} if name is not False: kwargs['name'] = name if description is not False: kwargs['description'] = description if icon is not False: kwargs['icon'] = icon if callback_url is not False: kwargs['callback_url'] = callback_url if active is not None: kwargs['active'] = active self._transport.patch("/organization/v3/services", self._subject, **kwargs) @api_call def add_service_public_key(self, service_id, public_key, expires=None, active=None): """ Adds a public key to an Organization Service :param service_id: Unique Service ID :param public_key: String RSA public key :param expires: Optional datetime.datetime stating a time in which the key will no longer be valid :param active: Optional bool stating whether the key should be considered active and usable. :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.InvalidPublicKey - The public key you supplied is not valid. :raise: launchkey.exceptions.PublicKeyAlreadyInUse - The public key you supplied already exists for the requested entity. It cannot be yadded again. :return: MD5 fingerprint (key_id) of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 """ kwargs = {"service_id": str(service_id), "public_key": public_key} if expires is not None: kwargs['date_expires'] = iso_format(expires) if active is not None: kwargs['active'] = active return self._transport.post("/organization/v3/service/keys", self._subject, **kwargs).data['key_id'] @api_call def get_service_public_keys(self, service_id): """ Retrieves a list of Public Keys belonging to a Service :param service_id: Unique Service ID :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.ServiceNotFound - No Service could be found matching the input ID :raise: launchkey.exceptions.Forbidden - The Service you requested either does not exist or you do not have sufficient permissions. :return: List - launchkey.entities.shared.PublicKey """ return [PublicKey(self._validate_response(key, PublicKeyValidator)) for key in self._transport.post("/organization/v3/service/keys/list", self._subject, service_id=str(service_id)).data] @api_call def remove_service_public_key(self, service_id, key_id): """ Removes a public key from an Organization Service. You may only remove a public key if other public keys exist. If you wish for a last remaining key to no longer be usable, use update_service_public_key to instead and set it as inactive. :param service_id: Unique Service ID :param key_id: MD5 fingerprint of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.PublicKeyDoesNotExist - The key_id you supplied could not be found :raise: launchkey.exceptions.LastRemainingKey - The last remaining public key cannot be removed :raise: launchkey.exceptions.Forbidden - The Service you requested either does not exist or you do not have sufficient permissions. :return: """ self._transport.delete("/organization/v3/service/keys", self._subject, service_id=str(service_id), key_id=key_id) @api_call def update_service_public_key(self, service_id, key_id, expires=False, active=None): """ Removes a public key from an Organization Service :param service_id: Unique Service ID :param key_id: MD5 fingerprint of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 :param expires: datetime.datetime stating a time in which the key will no longer be valid :param active: Bool stating whether the key should be considered active and usable :raise: launchkey.exceptions.PublicKeyDoesNotExist - The key_id you supplied could not be found :raise: launchkey.exceptions.Forbidden - The Service you requested either does not exist or you do not have sufficient permissions. :return: """ kwargs = {"service_id": str(service_id), "key_id": key_id} if active is not None: kwargs['active'] = active if expires is not False: kwargs['date_expires'] = iso_format(expires) self._transport.patch("/organization/v3/service/keys", self._subject, **kwargs) @api_call def get_service_policy(self, service_id): """ Retrieves a Service's Security Policy :param service_id: Unique Service ID :raise: launchkey.exceptions.ServiceNotFound - No Service could be found matching the input ID :return: launchkey.entities.service.ServiceSecurityPolicy object containing policy details """ policy = ServiceSecurityPolicy() policy.set_policy(self._validate_response( self._transport.post("/organization/v3/service/policy/item", self._subject, service_id=str(service_id)).data, ServiceSecurityPolicyValidator)) return policy @api_call def set_service_policy(self, service_id, policy): """ Sets a Service's Security Policy :param service_id: Unique Service ID :param policy: launchkey.clients.shared.ServiceSecurityPolicy :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.ServiceNotFound - No Service could be found matching the input ID :return: """ self._transport.put("/organization/v3/service/policy", self._subject, service_id=str(service_id), policy=policy.get_policy()) @api_call def remove_service_policy(self, service_id): """ Resets a Service's Security Policy back to default :param service_id: Unique Service ID :raise: launchkey.exceptions.ServiceNotFound - No Service could be found matching the input ID :return: """ self._transport.delete("/organization/v3/service/policy", self._subject, service_id=str(service_id)) @api_call def create_directory(self, name): """ Creates a new Directory :param name: Name describing the Directory that can be viewed in the Admin Center :return: String - ID of the Directory that is created :raise: launchkey.exceptions.DirectoryNameInUse - Directory name already taken """ return self._transport.post("/organization/v3/directories", self._subject, name=name).data['id'] @api_call def get_all_directories(self): """ Retrieves all Directories belonging to an Organization :return: List - launchkey.entities.directory.Directory object containing Directory details """ return [Directory(self._validate_response(directory, DirectoryValidator)) for directory in self._transport.get("/organization/v3/directories", self._subject).data] @api_call def get_directories(self, directory_ids): """ Retrieves a list of Directories belonging to an Organization :param directory_ids: List of unique Directory IDs :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :return: List - launchkey.entities.directory.Directory object containing Directory details """ return [Directory(self._validate_response(directory, DirectoryValidator)) for directory in self._transport.post("/organization/v3/directories/list", self._subject, directory_ids=[str(directory_id) for directory_id in directory_ids]).data] @api_call def get_directory(self, directory_id): """ Retrieves a Directory based on an input Directory ID :param directory_id: Unique Directory ID :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :return: launchkey.entities.directory.Directory object containing Directory details """ return Directory(self._validate_response( self._transport.post("/organization/v3/directories/list", self._subject, directory_ids=[str(directory_id)]).data[0], DirectoryValidator)) @api_call def update_directory(self, directory_id, ios_p12=False, android_key=False, active=None): """ Updates a Directories's settings. If an optional parameter is not included it will not be updated. :param directory_id: Unique Directory ID :param ios_p12: MPNS P12 formatted push key containing both private key and cert (must be password free) :param android_key: GCM Push Key :param active: Boolean. Status preventing Directory Service Auths as well as other Directory related calls. :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :return: """ kwargs = {"directory_id": str(directory_id)} if ios_p12 is not False: kwargs['ios_p12'] = encodestring(ios_p12).decode('utf-8') if ios_p12 else ios_p12 if android_key is not False: kwargs['android_key'] = android_key if active is not None: kwargs['active'] = active self._transport.patch("/organization/v3/directories", self._subject, **kwargs) @api_call def get_directory_public_keys(self, directory_id): """ Retrieves a list of Public Keys belonging to a Directory :param directory_id: Unique Directory ID :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.Forbidden - The Directory you requested either does not exist or you do not have sufficient permissions. :return: List - launchkey.entities.shared.PublicKey """ return [PublicKey(self._validate_response(key, PublicKeyValidator)) for key in self._transport.post("/organization/v3/directory/keys/list", self._subject, directory_id=str(directory_id)).data] @api_call def add_directory_public_key(self, directory_id, public_key, expires=None, active=None): """ Adds a public key to an Directory :param directory_id: Unique Directory ID :param public_key: String RSA public key :param expires: Optional datetime.datetime stating a time in which the key will no longer be valid :param active: Optional bool stating whether the key should be considered active and usable. :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.InvalidPublicKey - The public key you supplied is not valid. :raise: launchkey.exceptions.PublicKeyAlreadyInUse - The public key you supplied already exists for the requested entity. It cannot be added again. :raise: launchkey.exceptions.Forbidden - The Directory you requested either does not exist or you do not have sufficient permissions. :return: MD5 fingerprint (key_id) of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 """ kwargs = {"directory_id": str(directory_id), "public_key": public_key} if expires is not None: kwargs['date_expires'] = iso_format(expires) if active is not None: kwargs['active'] = active return self._transport.post("/organization/v3/directory/keys", self._subject, **kwargs).data['key_id'] @api_call def remove_directory_public_key(self, directory_id, key_id): """ Removes a public key from a Directory. You may only remove a public key if other public keys exist. If you wish for a last remaining key to no longer be usable, use update_service_public_key to instead and set it as inactive. :param directory_id: Unique Directory ID :param key_id: MD5 fingerprint of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.PublicKeyDoesNotExist - The key_id you supplied could not be found. :raise: launchkey.exceptions.LastRemainingKey - The last remaining public key cannot be removed. :raise: launchkey.exceptions.Forbidden - The Directory you requested either does not exist or you do not have sufficient permissions. :return: """ self._transport.delete("/organization/v3/directory/keys", self._subject, directory_id=str(directory_id), key_id=key_id) @api_call def update_directory_public_key(self, directory_id, key_id, expires=False, active=None): """ Removes a public key from a Directory :param directory_id: Unique Directory ID :param key_id: MD5 fingerprint of the public key, IE: e0:2f:a9:5a:76:92:6b:b5:4d:24:67:19:d1:8a:0a:75 :param expires: datetime.datetime stating a time in which the key will no longer be valid :param active: Bool stating whether the key should be considered active and usable :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.PublicKeyDoesNotExist - The key_id you supplied could not be found. :raise: launchkey.exceptions.Forbidden - The Directory you requested either does not exist or you do not have sufficient permissions. :return: """ kwargs = {"directory_id": str(directory_id), "key_id": key_id} if active is not None: kwargs['active'] = active if expires is not False: kwargs['date_expires'] = iso_format(expires) self._transport.patch("/organization/v3/directory/keys", self._subject, **kwargs) @api_call def generate_and_add_directory_sdk_key(self, directory_id): """ Creates and retrieves a new Authenticator SDK Key for a Directory :param directory_id: Unique Directory ID :return: String - Newly generated Authenticator SDK Key :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct """ return self._transport.post("/organization/v3/directory/sdk-keys", self._subject, directory_id=str(directory_id)).data['sdk_key'] @api_call def remove_directory_sdk_key(self, directory_id, sdk_key): """ Removes an Authenticator SDK Key from a Directory :param directory_id: Unique Directory ID :param sdk_key: Authenticator SDK Key :raise: launchkey.exceptions.InvalidParameters - Input parameters were not correct :raise: launchkey.exceptions.LastRemainingSDKKey - The last remaining SDK key cannot be removed :raise: launchkey.exceptions.InvalidSDKKey - The input SDK key does not belong to the given Directory :return: """ self._transport.delete("/organization/v3/directory/sdk-keys", self._subject, directory_id=str(directory_id), sdk_key=sdk_key)

55.32345

120

0.670597

2,507

20,525

5.369366

0.099322

0.031424

0.078449

0.051779

0.814353

0.779065

0.748087

0.710571

0.669861

0.659461

0

0.012016

0.253934

20,525

370

121

55.472973

0.867041

0.515761

0

0.376712

0

0.115196

0.08392

0

1

0.164384

false

0

0.061644

0

0.328767

0

null

0

1

0

1

0

null

0

5

7dae98d9fb3c392969885afa6d636f3560350282

92

py

Python

user/admin.py

5akusei/test-project-django

c8a7108a5872dc9e396d48a59541c39dd8246f5c

[ "MIT" ]

null

user/admin.py

5akusei/test-project-django

c8a7108a5872dc9e396d48a59541c39dd8246f5c

[ "MIT" ]

null

user/admin.py

5akusei/test-project-django

c8a7108a5872dc9e396d48a59541c39dd8246f5c

[ "MIT" ]

null

from django.contrib import admin # from user.models import User # admin.site.register(User)

23

32

0.793478

14

92

5.214286

0.642857

0

0.119565

92

4

33

23

0.901235

0.586957

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7dd75e2596b176c0b98fb2377a8d0b02dd739e74

62

py

Python

parasol/__init__.py

digsy89/parasol

8e00382005e9894000e4401b90a4cfb3add1b280

[ "Apache-2.0" ]

4

2020-01-03T08:15:15.000Z

2020-01-05T08:09:32.000Z

parasol/__init__.py

digsy89/parasol

8e00382005e9894000e4401b90a4cfb3add1b280

[ "Apache-2.0" ]

1

2020-04-10T06:06:37.000Z

2020-04-10T06:42:27.000Z

parasol/__init__.py

digsy89/parasol

8e00382005e9894000e4401b90a4cfb3add1b280

[ "Apache-2.0" ]

1

2020-01-10T04:13:47.000Z

from .tokenize import Tokenizer from .compose import Composer

20.666667

31

0.83871

8

62

6.5

0.75

0

0.129032

62

2

32

31

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

81462b5a9b6567162f5b55bbd739182d14d894a6

899

py

Python

nistdataselection/utils/__init__.py

openforcefield/nistdataselection

d797d597f4ff528a7219d58daa8ef6508d438b24

[ "MIT" ]

3

2020-03-25T02:42:04.000Z

2020-07-20T10:39:35.000Z

nistdataselection/utils/__init__.py

openforcefield/nistdataselection

d797d597f4ff528a7219d58daa8ef6508d438b24

[ "MIT" ]

13

2019-09-05T00:20:03.000Z

2020-03-05T23:58:04.000Z

nistdataselection/utils/__init__.py

openforcefield/nistdataselection

d797d597f4ff528a7219d58daa8ef6508d438b24

[ "MIT" ]

null

from .pandas import data_set_from_data_frame from .utils import ( SubstanceType, analyse_functional_groups, chemical_environment_codes, find_parameter_smirks_matches, find_smirks_matches, get_atom_count, get_heavy_atom_count, get_molecular_weight, int_to_substance_type, invert_dict_of_iterable, invert_dict_of_list, property_to_type_tuple, smiles_to_pdf, standardize_smiles, substance_type_to_int, ) __all__ = [ SubstanceType, analyse_functional_groups, chemical_environment_codes, data_set_from_data_frame, find_parameter_smirks_matches, find_smirks_matches, get_atom_count, get_heavy_atom_count, get_molecular_weight, int_to_substance_type, invert_dict_of_iterable, invert_dict_of_list, property_to_type_tuple, smiles_to_pdf, standardize_smiles, substance_type_to_int, ]

23.657895

44

0.769744

115

899

5.321739

0.33913

0.084967

0.078431

0.04902

0.944444

0.879085

0.683007

0

0.187987

899

37

45

24.297297

0.838356

0

0.833333

0

1

0

false

0

0.055556

0

0.055556

0

null

0

1

0

1

0

1

0

null

0

5

81641a1af88b988f19863a83cbefa69a78980144

89

py

Python

LifeCycleAnalyzer/Simulators/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

LifeCycleAnalyzer/Simulators/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

LifeCycleAnalyzer/Simulators/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

from .MainSimulator import MainSimulator from .DummyRiskAnalyzer import DummyRiskAnalyzer

44.5

48

0.898876

8

89

10

0.5

0

0.078652

89

2

48

44.5

0.97561

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

816ab680c385c7123a90e5c4049365609a35433f

196

py

Python

heatmap/__init__.py

codepost-io/heatmap-viewer

a8edc17ac0a01b7aca22cb9e9ec897387272a5ff

[ "MIT" ]

1

2019-08-22T22:19:39.000Z

heatmap/__init__.py

codepost-io/heatmap-viewer

a8edc17ac0a01b7aca22cb9e9ec897387272a5ff

[ "MIT" ]

null

heatmap/__init__.py

codepost-io/heatmap-viewer

a8edc17ac0a01b7aca22cb9e9ec897387272a5ff

[ "MIT" ]

null

from . import util _logger = util.getLogger() _logger.debug("Pkg loading: Loading 'preprocess'...") from . import preprocess _logger.debug("Pkg loading: Loading 'draw'...") from . import draw

17.818182

53

0.714286

24

196

5.708333

0.416667

0.218978

0.20438

0.306569

0.408759

0

0.137755

196

10

54

19.6

0.810651

0

0.338462

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

null

0

1

0

5

817f356d4cfefcbc9fb8a7690a5c57902c42c7ad

131

py

Python

src/pathfinder/graph.py

FitzOReilly/pathfinder

0aa7516bdaa4c53d5cf8811d1cc4269e1841a475

[ "MIT" ]

null

src/pathfinder/graph.py

FitzOReilly/pathfinder

0aa7516bdaa4c53d5cf8811d1cc4269e1841a475

[ "MIT" ]

null

src/pathfinder/graph.py

FitzOReilly/pathfinder

0aa7516bdaa4c53d5cf8811d1cc4269e1841a475

[ "MIT" ]

null

class Graph: def __init__(self): self.edges = {} def neighbors(self, node_id): return self.edges[node_id]

18.714286

34

0.603053

17

131

4.294118

0.588235

0.246575

0

0.282443

131

6

35

21.833333

0.776596

0

1

0.4

false

0

0.2

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

81a33a4f22c9a0509dcdc544682593190f658da2

46

py

Python

problem/10000~19999/16480/16480.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

1

2019-04-19T16:37:44.000Z

problem/10000~19999/16480/16480.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

1

2019-04-20T11:42:44.000Z

problem/10000~19999/16480/16480.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

3

2019-04-19T16:37:47.000Z

2021-10-25T00:45:00.000Z

a,b=map(int,input().split()) print(a**2-2*a*b)

23

28

0.608696

12

46

2.333333

0.666667

0.142857

0

0.044444

0.021739

46

2

29

23

0.577778

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

81a4f1226cc91fd659330a712427e0c328fc7f6a

84

py

Python

pypvcell/__init__.py

kanhua/pypvcell

93c752e2067718f108fc9f6c6270abdac721c526

[ "Apache-2.0" ]

7

2017-07-08T07:16:22.000Z

2022-03-11T11:14:07.000Z

pypvcell/__init__.py

kanhua/pypvcell

93c752e2067718f108fc9f6c6270abdac721c526

[ "Apache-2.0" ]

null

pypvcell/__init__.py

kanhua/pypvcell

93c752e2067718f108fc9f6c6270abdac721c526

[ "Apache-2.0" ]

3

2020-10-13T09:23:38.000Z

2021-03-25T06:08:45.000Z

def main(): """Entry point for the application script""" print("pypvcell!")

21

48

0.630952

10

84

5.3

1

0

0.202381

84

4

49

21

0.791045

0.452381

0

0.225

0

1

0.5

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

81b9dd34f828b50ced722e70e64855db0cc79222

1,292

py

Python

backend/api/serializer.py

victor-42/pws-secrets

108aa442801e2133a954a3e55054c0a12e7f563b

[ "MIT" ]

3

2021-08-06T22:41:09.000Z

2021-12-23T10:28:39.000Z

backend/api/serializer.py

victor-42/pws-secrets

108aa442801e2133a954a3e55054c0a12e7f563b

[ "MIT" ]

null

backend/api/serializer.py

victor-42/pws-secrets

108aa442801e2133a954a3e55054c0a12e7f563b

[ "MIT" ]

null

from rest_framework import serializers from django.conf import settings from .models import SecretImage class LogInSecretSerializer(serializers.Serializer): username = serializers.CharField(max_length=500, required=True, allow_blank=False) password = serializers.CharField(max_length=500, required=True, allow_blank=False) def clean_username(self, value): return value.replace(settings.SEPERATOR, settings.SEPERATOR_REPLACEMENT) def clean_password(self, value): return value.replace(settings.SEPERATOR, settings.SEPERATOR_REPLACEMENT) class NoteSecretSerializer(serializers.Serializer): note = serializers.CharField(max_length=2000, required=True, allow_blank=False) def clean_note(self, value): return value.replace(settings.SEPERATOR, settings.SEPERATOR_REPLACEMENT) class ImageSecretSerializer(serializers.ModelSerializer): note = serializers.CharField(max_length=20000, allow_blank=True, allow_null=True) class Meta: model = SecretImage fields = ['image', 'note'] def clean_note(self, value): return value.replace(settings.SEPERATOR, settings.SEPERATOR_REPLACEMENT) def clean_image(self, value): value.name = value.name.replace(settings.SEPERATOR, settings.SEPERATOR_REPLACEMENT)

35.888889

91

0.768576

145

1,292

6.710345

0.303448

0.174717

0.12333

0.16444

0.625899

0.558068

0.504625

0.468654

0

0.013562

0.143963

1,292

35

92

36.914286

0.866184

0

0.26087

0

0.006966

0

1

0.217391

false

0.086957

0.130435

0.173913

0.869565

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c48e9887da6e1cf081f0183be7d044e776347867

5,044

py

Python

source_py3/combi/_python_toolbox/future_tools.py

cool-RR/combi

9c5c143a792ffd8fb38b6470f926268c8bacbc31

[ "MIT" ]

23

2015-01-16T03:45:10.000Z

2021-08-11T20:46:44.000Z

source_py3/combi/_python_toolbox/future_tools.py

cool-RR/combi

9c5c143a792ffd8fb38b6470f926268c8bacbc31

[ "MIT" ]

3

2015-01-30T15:59:45.000Z

2021-09-18T08:52:38.000Z

source_py3/combi/_python_toolbox/future_tools.py

cool-RR/combi

9c5c143a792ffd8fb38b6470f926268c8bacbc31

[ "MIT" ]

1

2021-08-11T19:57:47.000Z

# Copyright 2009-2017 Ram Rachum. # This program is distributed under the MIT license. ''' Defines tools related to the `concurrent.futures` standard library package. ''' import time import concurrent.futures from combi._python_toolbox import sequence_tools class BaseCuteExecutor(concurrent.futures.Executor): ''' An executor with extra functionality for `map` and `filter`. This is a subclass of `concurrent.futures.Executor`, which is a manager for parallelizing tasks. What this adds over `concurrent.futures.Executor`: - A `.filter` method, which operates like the builtin `filter` except it's parallelized with the executor. - An `as_completed` argument for both `.map` and `.filter`, which makes these methods return results according to the order in which they were computed, and not the order in which they were submitted. ''' def filter(self, filter_function, iterable, timeout=None, as_completed=False): ''' Get a parallelized version of `filter(filter_function, iterable)`. Specify `as_completed=False` to get the results that were calculated first to be returned first, instead of using the order of `iterable`. ''' if timeout is not None: end_time = timeout + time.time() def make_future(item): future = self.submit(filter_function, item) future._item = item return future futures = tuple(map(make_future, iterable)) futures_iterator = concurrent.futures.as_completed(futures) if \ as_completed else futures # Yield must be hidden in closure so that the futures are submitted # before the first iterator value is required. def result_iterator(): try: for future in futures_iterator: if timeout is None: result = future.result() else: result = future.result(end_time - time.time()) if result: yield future._item finally: for future in futures: future.cancel() return result_iterator() def map(self, function, *iterables, timeout=None, as_completed=False): ''' Get a parallelized version of `map(function, iterable)`. Specify `as_completed=False` to get the results that were calculated first to be returned first, instead of using the order of `iterable`. ''' if timeout is not None: end_time = timeout + time.time() futures = [self.submit(function, *args) for args in zip(*iterables)] futures_iterator = concurrent.futures.as_completed(futures) if \ as_completed else futures # Yield must be hidden in closure so that the futures are submitted # before the first iterator value is required. def result_iterator(): try: for future in futures_iterator: if timeout is None: yield future.result() else: yield future.result(end_time - time.time()) finally: for future in futures: future.cancel() return result_iterator() class CuteThreadPoolExecutor(concurrent.futures.ThreadPoolExecutor, BaseCuteExecutor): ''' A thread-pool executor with extra functionality for `map` and `filter`. This is a subclass of `concurrent.futures.ThreadPoolExecutor`, which is a manager for parallelizing tasks to a thread pool. What this adds over `concurrent.futures.ThreadPoolExecutor`: - A `.filter` method, which operates like the builtin `filter` except it's parallelized with the executor. - An `as_completed` argument for both `.map` and `.filter`, which makes these methods return results according to the order in which they were computed, and not the order in which they were submitted. ''' class CuteProcessPoolExecutor(concurrent.futures.ProcessPoolExecutor, BaseCuteExecutor): ''' A process-pool executor with extra functionality for `map` and `filter`. This is a subclass of `concurrent.futures.ThreadPoolExecutor`, which is a manager for parallelizing tasks to a process pool. What this adds over `concurrent.futures.ThreadPoolExecutor`: - A `.filter` method, which operates like the builtin `filter` except it's parallelized with the executor. - An `as_completed` argument for both `.map` and `.filter`, which makes these methods return results according to the order in which they were computed, and not the order in which they were submitted. '''

39.100775

79

0.615979

574

5,044

5.355401

0.216028

0.071893

0.023422

0.029278

0.749837

0.721535

0.709824

0

0.002327

0.318398

5,044

128

80

39.40625

0.891798

0.491475

0

0.571429

0

1

0.102041

false

0

0.061224

0

0.285714

0

null

0

1

0

null

0

5

c497d064842233abdb08c8657a8f12ef3a3636cd

191

py

Python

Live_Room/ihome/api_0_1/mode.py

LiuWei-heihei/ihome

e6df97b93b184234c9c5ef9a5da3b590b46060de

[ "Unlicense" ]

null

Live_Room/ihome/api_0_1/mode.py

LiuWei-heihei/ihome

e6df97b93b184234c9c5ef9a5da3b590b46060de

[ "Unlicense" ]

null

Live_Room/ihome/api_0_1/mode.py

LiuWei-heihei/ihome

e6df97b93b184234c9c5ef9a5da3b590b46060de

[ "Unlicense" ]

null

# -*- coding:utf—8 -*- # python源程序 todo # 作者：liuwei # 备注：未经本人允许请勿盗窃 http://www.baidu.com from . import api from ihome import models @api.route("/index") def index(): return "python"

15.916667

39

0.65445

29

191

4.344828

0.862069

0

0.006369

0.17801

191

11

40

17.363636

0.789809

0.434555

0

0.116505

0

0.090909

0

1

0.2

true

0

0.4

0.2

0.8

0

1

0

null

0

null

0

1

0

1

0

1

0

5

c4b8d91778b5597cab3c032749b71288b8607dcf

6,618

py

Python

src/dask_awkward/reducers.py

douglasdavis/dask-awkward-sandbox

901eec69a92957dc5c3e64339705567c970b55bf

[ "BSD-3-Clause" ]

21

2021-09-09T19:32:30.000Z

2022-03-01T15:42:06.000Z

src/dask_awkward/reducers.py

douglasdavis/dask-awkward-sandbox

901eec69a92957dc5c3e64339705567c970b55bf

[ "BSD-3-Clause" ]

14

2021-09-23T16:54:10.000Z

2022-03-23T19:24:53.000Z

src/dask_awkward/reducers.py

douglasdavis/dask-awkward-sandbox

901eec69a92957dc5c3e64339705567c970b55bf

[ "BSD-3-Clause" ]

3

2021-09-09T19:32:32.000Z

2021-11-18T17:27:35.000Z

from __future__ import annotations from typing import TYPE_CHECKING, Any, Callable, Union import awkward._v2 as ak from .core import TrivialPartitionwiseOp, pw_reduction_with_agg_to_scalar if TYPE_CHECKING: from .core import Array, Scalar LazyResult = Union[Array, Scalar] __all__ = ( "all", "any", "argmax", "argmin", "corr", "count", "count_nonzero", "covar", "linear_fit", "max", "mean", "min", "moment", "prod", "ptp", "softmax", "std", "sum", "var", ) _count_trivial = TrivialPartitionwiseOp(ak.count, axis=1) _count_nonzero_trivial = TrivialPartitionwiseOp(ak.count_nonzero, axis=1) _min_trivial = TrivialPartitionwiseOp(ak.min, axis=1) _max_trivial = TrivialPartitionwiseOp(ak.max, axis=1) _sum_trivial = TrivialPartitionwiseOp(ak.sum, axis=1) def all(array, axis=None, keepdims=False, mask_identity=False, flatten_records=False): NotImplementedError("TODO") def any(array, axis=None, keepdims=False, mask_identity=False, flatten_records=False): NotImplementedError("TODO") def argmax(array, axis=None, keepdims=False, mask_identity=True, flatten_records=False): NotImplementedError("TODO") def argmin(array, axis=None, keepdims=False, mask_identity=True, flatten_records=False): NotImplementedError("TODO") def corr( x, y, weight=None, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def count(array, axis=None, keepdims=False, mask_identity=False, flatten_records=False): if axis == 1: return _count_trivial( array, axis=axis, keepdims=keepdims, mask_identity=mask_identity, flatten_records=flatten_records, ) elif axis is None: trivial_result = _count_trivial( array, axis=1, keepdims=keepdims, mask_identity=mask_identity, flatten_records=flatten_records, ) return pw_reduction_with_agg_to_scalar( trivial_result, ak.sum, ak.sum, ) elif axis == 0 or axis == -1 * array.ndim: raise NotImplementedError(f"axis={axis} is not supported for this array yet.") else: raise ValueError("axis must be None or an integer.") def count_nonzero( array, axis=None, keepdims=False, mask_identity=False, flatten_records=False ): if axis is not None and axis == 1: return _count_nonzero_trivial( array, axis=1, keepdims=False, mask_identity=False, flatten_records=False, ) elif axis is None: trivial_result = _count_nonzero_trivial( array, axis=1, keepdims=False, mask_identity=False, flatten_records=False, ) return pw_reduction_with_agg_to_scalar( trivial_result, ak.sum, ak.sum, ) elif axis == 0 or axis == -1 * array.ndim: raise NotImplementedError(f"axis={axis} is not supported for this array yet.") else: raise ValueError("axis must be None or an integer.") def covar( x, y, weight=None, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def linear_fit( x, y, weight=None, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def max( array, axis=None, keepdims=False, initial=None, mask_identity=True, flatten_records=False, ): return _min_or_max( ak.max, array, axis, keepdims=keepdims, initial=initial, mask_identity=mask_identity, flatten_records=flatten_records, ) def mean( x, weight=None, axis=None, keepdims=False, mask_identity=True, flatten_records=False ): NotImplementedError("TODO") def min( array, axis=None, keepdims=False, initial=None, mask_identity=True, flatten_records=False, ): return _min_or_max( ak.min, array, axis, keepdims=keepdims, initial=initial, mask_identity=mask_identity, flatten_records=flatten_records, ) def moment( x, n, weight=None, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def prod(array, axis=None, keepdims=False, mask_identity=False, flatten_records=False): NotImplementedError("TODO") def ptp(arr, axis=None, keepdims=False, mask_identity=True, flatten_records=False): NotImplementedError("TODO") def softmax(x, axis=None, keepdims=False, mask_identity=False, flatten_records=False): NotImplementedError("TODO") def std( x, weight=None, ddof=0, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def sum(array, axis=None, keepdims=False, mask_identity=False, flatten_records=False): if axis is not None and axis < 0: axis = array.ndim + axis + 1 if axis == 1: return _sum_trivial( array, keepdims=False, mask_identity=False, flatten_records=False ) elif axis is None: return pw_reduction_with_agg_to_scalar(array, ak.sum, ak.sum) elif axis == 0: raise NotImplementedError(f"axis={axis} is not supported for this array yet.") else: raise ValueError("axis must be none or an integer") def var( x, weight=None, ddof=0, axis=None, keepdims=False, mask_identity=True, flatten_records=False, ): NotImplementedError("TODO") def _min_or_max( f: Callable, array: Array, axis: int | None = None, **kwargs: Any, ) -> LazyResult: # translate negative axis (array.ndim currently raises) if axis is not None and axis < 0 and array.ndim is not None: axis = array.ndim + axis + 1 # get the correct trivial callable tf = _min_trivial if f == ak.min else _max_trivial # generate collection based on axis if axis == 1: return tf(array, axis=axis, **kwargs) elif axis is None: return pw_reduction_with_agg_to_scalar(array, f, f, **kwargs) elif array.ndim is not None and (axis == 0 or axis == -1 * array.ndim): raise NotImplementedError(f"axis={axis} is not supported for this array yet.") else: raise ValueError("axis must be None or an integer.")

23.551601

88

0.637957

800

6,618

5.10125

0.125

0.088214

0.102426

0.122519

0.77138

0.751777

0.742465

0.726783

0.720902

0

0.005327

0.262466

6,618

280

89

23.635714

0.830772

0.018132

0

0.611354

0

0.072221

0

1

0.087336

false

0

0.021834

0.008734

0.152838

0

null

0

1

0

null

0

5

c4d139ac4854c1e913a5c2e72d7e171be5b058cd

344

py

Python

plantcv/plantcv/homology/__init__.py

jgerardhodge/plantcv

0e20ac55d9ef81e54536f466020eba6e0c70e7fb

[ "MIT" ]

null

plantcv/plantcv/homology/__init__.py

jgerardhodge/plantcv

0e20ac55d9ef81e54536f466020eba6e0c70e7fb

[ "MIT" ]

null

plantcv/plantcv/homology/__init__.py

jgerardhodge/plantcv

0e20ac55d9ef81e54536f466020eba6e0c70e7fb

[ "MIT" ]

null

from plantcv.plantcv.homology.acute import acute from plantcv.plantcv.homology.space import space from plantcv.plantcv.homology.starscape import starscape from plantcv.plantcv.homology.constella import constella from plantcv.plantcv.homology.constellaqc import constellaqc __all__ = ["acute", "space", "starscape", "constella", "constellaqc"]

43

69

0.825581

41

344

6.829268

0.243902

0.196429

0.321429

0.464286

0

0.081395

344

7

70

49.142857

0.886076

0

0.113372

0

1

0

false

0

0.833333

0

0.833333

0

null

0

1

0

1

0

null

0

1

0

1

0

5

f20758b9453d41b42065c7fa7a303c1fded713d9

215

py

Python

tests/conftest.py

luizklitzke1/cadastro_treinamento

96fbfc90be8fa846b614e4d6ea08c7accf2895c4

[ "MIT" ]

null

tests/conftest.py

luizklitzke1/cadastro_treinamento

96fbfc90be8fa846b614e4d6ea08c7accf2895c4

[ "MIT" ]

1

2021-03-04T22:31:34.000Z

2021-03-06T17:26:04.000Z

tests/conftest.py

luizklitzke1/cadastro_treinamento

96fbfc90be8fa846b614e4d6ea08c7accf2895c4

[ "MIT" ]

1

2021-04-25T14:27:09.000Z

import pytest from backend import create_app @pytest.fixture(scope="module") def app(): app=create_app(testing=True) yield app @pytest.fixture(scope="module") def client(app): return app.test_client()

17.916667

32

0.730233

31

215

4.967742

0.516129

0.116883

0.207792

0.272727

0.38961

0

0.144186

215

12

33

17.916667

0.836957

0

0.222222

0

0.055556

0

1

0.222222

false

0

0.222222

0.111111

0.555556

0

null

0

1

0

null

0

1

0

1

0

5

48202a90767996c8233ad9cbd625a054983ee144

51

py

Python

Ex 21.py

brunobendel/Exercicios-python-Pycharm

145ded6cb5533aeef1b89f0bce20f0a90e37216c

[ "MIT" ]

null

Ex 21.py

brunobendel/Exercicios-python-Pycharm

145ded6cb5533aeef1b89f0bce20f0a90e37216c

[ "MIT" ]

null

Ex 21.py

brunobendel/Exercicios-python-Pycharm

145ded6cb5533aeef1b89f0bce20f0a90e37216c

[ "MIT" ]

null

import playsound playsound.playsound('audio16.mp3')

25.5

34

0.843137

6

51

7.166667

0.666667

0.837209

0

0.061224

0.039216

51

2

34

25.5

0.816327

0

0.211538

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

4823acf04fda29df28f675c9ee600657bbfe04af

554

py

Python

2021/day2.py

kdassharma/AdventOfCode

b11f4b481e9f24be9957faac415dcd4d04d93cba

[ "Apache-2.0" ]

2

2020-12-02T06:01:37.000Z

2020-12-04T16:56:31.000Z

2021/day2.py

kdassharma/AdventOfCode2020

b11f4b481e9f24be9957faac415dcd4d04d93cba

[ "Apache-2.0" ]

null

2021/day2.py

kdassharma/AdventOfCode2020

b11f4b481e9f24be9957faac415dcd4d04d93cba

[ "Apache-2.0" ]

null

# Part 1 data = open('data/day2.txt') x = 0 y = 0 for line in data: curr = line.strip().split() if curr[0] == "forward": x += int(curr[1]) elif curr[0] == "up": y -= int(curr[1]) else: y += int(curr[1]) print(x*y) # Part 2 data = open('data/day2.txt') x = 0 y = 0 aim = 0 for line in data: curr = line.strip().split() if curr[0] == "forward": x += int(curr[1]) y += aim * int(curr[1]) elif curr[0] == "up": aim -= int(curr[1]) else: aim += int(curr[1]) print(x*y)

19.103448

32

0.476534

93

554

2.83871

0.258065

0.185606

0.212121

0.125

0.814394

0.700758

0.587121

0.416667

0

0.052632

0.314079

554

29

33

19.103448

0.642105

0.023466

0

0.769231

0

0.081633

0

1

0

false

0

0.076923

0

null

0

1

0

1

0

1

0

null

0

5

48444b04e894066c2f92648018ecd92b3ad89078

65

py

Python

lr_wkshp_helpers/__init__.py

billkellett/databricks-linear-regression-workshop-dbconnect

9c41c4c1d5bed701233ff786332cb4c253e6a611

[ "Apache-2.0" ]

null

lr_wkshp_helpers/__init__.py

billkellett/databricks-linear-regression-workshop-dbconnect

9c41c4c1d5bed701233ff786332cb4c253e6a611

[ "Apache-2.0" ]

null

lr_wkshp_helpers/__init__.py

billkellett/databricks-linear-regression-workshop-dbconnect

9c41c4c1d5bed701233ff786332cb4c253e6a611

[ "Apache-2.0" ]

null

from .initialization import setup from .cleanup import cleanup

21.666667

34

0.815385

8

65

6.625

0.625

0

0.153846

65

2

35

32.5

0.963636

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

48496b8d9a28618a936821b6db2cca1ad0173f91

70

py

Python

dexter/phys/__init__.py

WJM96/dexter

ca338e654bf37b7b9e53cf461a52d46eb2c80dea

[ "MIT" ]

null

dexter/phys/__init__.py

WJM96/dexter

ca338e654bf37b7b9e53cf461a52d46eb2c80dea

[ "MIT" ]

null

dexter/phys/__init__.py

WJM96/dexter

ca338e654bf37b7b9e53cf461a52d46eb2c80dea

[ "MIT" ]

null

from .vec2 import Vec2 from .box import Box # from .phys import Phys

14

24

0.742857

12

70

4.333333

0.416667

0

0.035714

0.2

70

4

25

17.5

0.892857

0.314286

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

48567938ce2026aa01ccd735aa9c7b840e87f36c

131

py

Python

spilljuice.py

moemyself3/SpillJuice

0fe711d84e4e491ee2c6671e901f7fc5078e2a29

[ "Unlicense" ]

null

spilljuice.py

moemyself3/SpillJuice

0fe711d84e4e491ee2c6671e901f7fc5078e2a29

[ "Unlicense" ]

null

spilljuice.py

moemyself3/SpillJuice

0fe711d84e4e491ee2c6671e901f7fc5078e2a29

[ "Unlicense" ]

null

#!/usr/bin/python import os #make Juice from sExtract os.system("python juice.py") #Spill Juice :D os.system("python spill.py")

13.1

28

0.717557

22

131

4.272727

0.590909

0.170213

0.297872

0

0.129771

131

9

29

14.555556

0.824561

0.412214

0

0.416667

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

6f7eba85ea33aafe8a81971a6d98916246c29eda

728

py

Python

tools/leetcode.264.Ugly Number II/leetcode.264.Ugly Number II.submission2.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

4

2015-10-10T00:30:55.000Z

2020-07-27T19:45:54.000Z

tools/leetcode.264.Ugly Number II/leetcode.264.Ugly Number II.submission2.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

tools/leetcode.264.Ugly Number II/leetcode.264.Ugly Number II.submission2.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

import heapq class Solution(object): def nthUglyNumber(self, n): """ :type n: int :rtype: int """ ugly_number = 0 heap = [] heapq.heappush(heap, 1) for _ in xrange(n): ugly_number = heapq.heappop(heap) if ugly_number % 2 == 0: heapq.heappush(heap, ugly_number * 2) elif ugly_number % 3 == 0: heapq.heappush(heap, ugly_number * 2) heapq.heappush(heap, ugly_number * 3) else: heapq.heappush(heap, ugly_number * 2) heapq.heappush(heap, ugly_number * 3) heapq.heappush(heap, ugly_number * 5) return ugly_number

728

0.505495

81

728

4.395062

0.358025

0.308989

0.33427

0.353933

0.474719

0.398876

0.314607

0

0.027335

0.396978

728

1

728

0.783599

0.032967

0

0.277778

0

1

0.055556

false

0

0.055556

0

0.222222

0

null

1

0

1

0

1

0

null

0

5

6fc4697f65b03cddf502efcb6ee1f7e198dd080e

4,512

py

Python

tests/test_0582-propagate-context-in-broadcast_and_apply.py

BioGeek/awkward-1.0

0cfb4e43c41d5c7d9830cc7b1d750485c0a93eb2

[ "BSD-3-Clause" ]

519

2019-10-17T12:36:22.000Z

2022-03-26T23:28:19.000Z

tests/test_0582-propagate-context-in-broadcast_and_apply.py

BioGeek/awkward-1.0

0cfb4e43c41d5c7d9830cc7b1d750485c0a93eb2

[ "BSD-3-Clause" ]

924

2019-11-03T21:05:01.000Z

2022-03-31T22:44:30.000Z

tests/test_0582-propagate-context-in-broadcast_and_apply.py

BioGeek/awkward-1.0

0cfb4e43c41d5c7d9830cc7b1d750485c0a93eb2

[ "BSD-3-Clause" ]

56

2019-12-17T15:49:22.000Z

2022-03-09T20:34:06.000Z

# BSD 3-Clause License; see https://github.com/scikit-hep/awkward-1.0/blob/main/LICENSE from __future__ import absolute_import import pytest # noqa: F401 import numpy as np # noqa: F401 import awkward as ak # noqa: F401 def test_toregular(): array = ak.Array( [ { "x": np.arange(2 * 3 * 5).reshape(2, 3, 5).tolist(), "y": np.arange(2 * 3 * 5 * 7).reshape(2, 3, 5, 7), } ] ) assert str(array.type) in ( '1 * {"x": var * var * var * int64, "y": var * var * var * var * int64}', '1 * {"y": var * var * var * var * int64, "x": var * var * var * int64}', ) assert str(ak.to_regular(array, axis=-1).type) in ( '1 * {"x": var * var * 5 * int64, "y": var * var * var * 7 * int64}', '1 * {"y": var * var * var * 7 * int64, "x": var * var * 5 * int64}', ) assert str(ak.to_regular(array, axis=-2).type) in ( '1 * {"x": var * 3 * var * int64, "y": var * var * 5 * var * int64}', '1 * {"y": var * var * 5 * var * int64, "x": var * 3 * var * int64}', ) assert str(ak.to_regular(array, axis=-3).type) in ( '1 * {"x": 2 * var * var * int64, "y": var * 3 * var * var * int64}', '1 * {"y": var * 3 * var * var * int64, "x": 2 * var * var * int64}', ) def test_cartesian(): one = ak.Array(np.arange(2 * 3 * 5 * 7).reshape(2, 3, 5, 7).tolist()) two = ak.Array(np.arange(2 * 3 * 5 * 7).reshape(2, 3, 5, 7).tolist()) assert ( str(ak.cartesian([one, two], axis=0, nested=True).type) == "2 * 2 * (var * var * var * int64, var * var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=1, nested=True).type) == "2 * var * var * (var * var * int64, var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=2, nested=True).type) == "2 * var * var * var * (var * int64, var * int64)" ) assert ( str(ak.cartesian([one, two], axis=3, nested=True).type) == "2 * var * var * var * var * (int64, int64)" ) assert ( str(ak.cartesian([one, two], axis=-1, nested=True).type) == "2 * var * var * var * var * (int64, int64)" ) assert ( str(ak.cartesian([one, two], axis=-2, nested=True).type) == "2 * var * var * var * (var * int64, var * int64)" ) assert ( str(ak.cartesian([one, two], axis=-3, nested=True).type) == "2 * var * var * (var * var * int64, var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=-4, nested=True).type) == "2 * 2 * (var * var * var * int64, var * var * var * int64)" ) with pytest.raises(ValueError): ak.cartesian([one, two], axis=-5, nested=True) assert ( str(ak.cartesian([one, two], axis=0).type) == "4 * (var * var * var * int64, var * var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=1).type) == "2 * var * (var * var * int64, var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=2).type) == "2 * var * var * (var * int64, var * int64)" ) assert ( str(ak.cartesian([one, two], axis=3).type) == "2 * var * var * var * (int64, int64)" ) assert ( str(ak.cartesian([one, two], axis=-1).type) == "2 * var * var * var * (int64, int64)" ) assert ( str(ak.cartesian([one, two], axis=-2).type) == "2 * var * var * (var * int64, var * int64)" ) assert ( str(ak.cartesian([one, two], axis=-3).type) == "2 * var * (var * var * int64, var * var * int64)" ) assert ( str(ak.cartesian([one, two], axis=-4).type) == "4 * (var * var * var * int64, var * var * var * int64)" ) with pytest.raises(ValueError): ak.cartesian([one, two], axis=-5) def test_firsts(): array = ak.Array([[[0, 1, 2], []], [[3, 4]], [], [[5], [6, 7, 8, 9]]]) assert ak.to_list(ak.firsts(array, axis=0)) == [[0, 1, 2], []] assert ak.to_list(ak.firsts(array, axis=1)) == [[0, 1, 2], [3, 4], None, [5]] assert ak.to_list(ak.firsts(array, axis=2)) == [[0, None], [3], [], [5, 6]] assert ak.to_list(ak.firsts(array, axis=-1)) == [[0, None], [3], [], [5, 6]] assert ak.to_list(ak.firsts(array, axis=-2)) == [[0, 1, 2], [3, 4], None, [5]] assert ak.to_list(ak.firsts(array, axis=-3)) == [[0, 1, 2], []] with pytest.raises(ValueError): ak.firsts(array, axis=-4)

35.527559

87

0.488254

649

4,512

3.368259

0.095532

0.197621

0.139982

0.153705

0.853156

0.799177

0.724154

0.721409

0.663312

0.62946

0

0.075901

0.299202

4,512

126

88

35.809524

0.615433

0.026152

0

0.318182

0

0.090909

0.296651

0

0.236364

1

0.027273

false

0

0.036364

0

0.063636

0

null

0

1

0

1

0

null

0

5

6fc70658bd9096a77efbc75a51175c77940aa11a

102

py

Python

backend/core/pedidos/exceptions.py

jklemm/menu-fullstack-challenge

519871e5889a827fbf39afd5dfb8944be8c21f3f

[ "Unlicense" ]

null

backend/core/pedidos/exceptions.py

jklemm/menu-fullstack-challenge

519871e5889a827fbf39afd5dfb8944be8c21f3f

[ "Unlicense" ]

null

backend/core/pedidos/exceptions.py

jklemm/menu-fullstack-challenge

519871e5889a827fbf39afd5dfb8944be8c21f3f

[ "Unlicense" ]

null

class PedidoNotFoundException(Exception): pass class RequiredDataException(Exception): pass

14.571429

41

0.784314

8

102

10

0.625

0.325

0

0.156863

102

6

42

17

0.930233

0

0.5

0

1

0

true

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

6fe83f560b02b17505b0c3745c17125337993c1a

57

py

Python

Python/Display Letters using Raspberry/main.py

janvi16/-HACKTOBERFEST2K20

aa9c8b6f7feb245793c0a003ba6fbea3fca9ca22

[ "Apache-2.0" ]

30

2020-10-07T09:16:29.000Z

2020-10-19T06:50:37.000Z

Python/Display Letters using Raspberry/main.py

janvi16/-HACKTOBERFEST2K20

aa9c8b6f7feb245793c0a003ba6fbea3fca9ca22

[ "Apache-2.0" ]

70

2020-10-07T03:26:13.000Z

2020-10-25T06:58:07.000Z

Python/Display Letters using Raspberry/main.py

janvi16/-HACKTOBERFEST2K20

aa9c8b6f7feb245793c0a003ba6fbea3fca9ca22

[ "Apache-2.0" ]

280

2020-10-07T03:39:21.000Z

2020-10-25T07:16:33.000Z

from letras import * from time import sleep setup_pin()

11.4

22

0.77193

9

57

4.777778

0.777778

0

0.175439

57

4

23

14.25

0.914894

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6fe9d973da535cbd5bdbc5ee385217f694eb401a

287

py

Python

config.py

stijnstijn/j2lsnek

2a8f9aeb6c48c3a9321fe6d863177ff1c8cbf8b3

[ "MIT" ]

4

2017-03-08T23:01:53.000Z

2022-03-19T17:33:41.000Z

config.py

stijnstijn/j2lsnek

2a8f9aeb6c48c3a9321fe6d863177ff1c8cbf8b3

[ "MIT" ]

null

config.py

stijnstijn/j2lsnek

2a8f9aeb6c48c3a9321fe6d863177ff1c8cbf8b3

[ "MIT" ]

1

2021-07-31T00:31:21.000Z

# this is just a dummy file that imports the local configuration file if it exists, or the defaults if it doesn't # this way other files can still import "config" and always get the right values from defaultconfig import * try: from localconfig import * except ImportError: pass

35.875

113

0.766551

46

287

4.782609

0.804348

0.036364

0

0.198606

287

8

114

35.875

0.956522

0.662021

0

1

0

true

0.2

0.6

0

0.6

0

null

0

1

0

null

0

1

0

1

0

5

d221808af80728294f21e0a986ac84ebef105874

119

py

Python

Zad_AbstractFactory/SterownikEkranu.py

Paarzivall/Wzorce-Projektowe

aa4136f140ad02c0fc0de45709b5a01ca42b417f

[ "MIT" ]

null

Zad_AbstractFactory/SterownikEkranu.py

Paarzivall/Wzorce-Projektowe

aa4136f140ad02c0fc0de45709b5a01ca42b417f

[ "MIT" ]

null

Zad_AbstractFactory/SterownikEkranu.py

Paarzivall/Wzorce-Projektowe

aa4136f140ad02c0fc0de45709b5a01ca42b417f

[ "MIT" ]

null

from abc import ABC, abstractmethod class SterownikEkranu(ABC): @abstractmethod def rysuj(self): pass

17

35

0.697479

13

119

6.384615

0.769231

0.409639

0

0.235294

119

7

36

17

0.912088

0

1

0.2

false

0.2

0

0.6

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

d27a2c9692ba5059ef266491c6cad47f7aab1409

123

py

Python

apps/slack/slack.py

jemand2001/knausj_talon

0b95e5c0a9c3af489d4e7f3e78b25be84be2e65b

[ "Unlicense" ]

2

2020-12-29T21:04:15.000Z

2021-03-02T14:30:38.000Z

apps/slack/slack.py

jemand2001/knausj_talon

0b95e5c0a9c3af489d4e7f3e78b25be84be2e65b

[ "Unlicense" ]

1

2021-03-11T15:00:25.000Z

apps/slack/slack.py

jemand2001/knausj_talon

0b95e5c0a9c3af489d4e7f3e78b25be84be2e65b

[ "Unlicense" ]

1

2020-12-28T16:14:04.000Z

from talon import Module mod = Module() apps = mod.apps apps.slack = "app.name: Slack" apps.slack = "app.name: Slack.exe"

17.571429

34

0.699187

20

123

4.3

0.5

0.209302

0.27907

0.372093

0.488372

0

0.154472

123

6

35

20.5

0.826923

0

0.276423

0

1

0

false

0

0.2

0

0.2

0

1

0

null

1

0

1

0

null

0

5

d281ed54e5bffecb117bc5bc0012d08d71547c32

34

py

Python

dash/config/settings.py

wjwwood/open-robotics-platform

c417f1e4e381cdbbe88ba9ad4dea3bdf9840d3d5

[ "MIT" ]

null

dash/config/settings.py

wjwwood/open-robotics-platform

c417f1e4e381cdbbe88ba9ad4dea3bdf9840d3d5

[ "MIT" ]

null

dash/config/settings.py

wjwwood/open-robotics-platform

c417f1e4e381cdbbe88ba9ad4dea3bdf9840d3d5

[ "MIT" ]

null

import sys, os # vim: ft=python

6.8

16

0.647059

6

34

3.666667

1

0

0.235294

34

4

17

8.5

0.846154

0.411765

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

96387baafe08d7ce8ef57e91c30820a3bbf9e3b4

127

py

Python

wechat_service/admin.py

qq525492738/movecar

4c565c4438cfd25e89f84ce58ef8f85ac4b09703

[ "Apache-2.0" ]

null

wechat_service/admin.py

qq525492738/movecar

4c565c4438cfd25e89f84ce58ef8f85ac4b09703

[ "Apache-2.0" ]

null

wechat_service/admin.py

qq525492738/movecar

4c565c4438cfd25e89f84ce58ef8f85ac4b09703

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import User_info # Register your models here. admin.site.register(User_info)

15.875

32

0.795276

19

127

5.210526

0.631579

0.161616

0

0.141732

127

7

33

18.142857

0.908257

0.204724

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

963ef2d19bce7b5954f5080dec52bd3574abd466

129

py

Python

zad6_1.py

kamilhabrych/python-semestr5-lista6

266bb9a858a62699f0d6b02576cbb5b2d319c662

[ "MIT" ]

null

zad6_1.py

kamilhabrych/python-semestr5-lista6

266bb9a858a62699f0d6b02576cbb5b2d319c662

[ "MIT" ]

null

zad6_1.py

kamilhabrych/python-semestr5-lista6

266bb9a858a62699f0d6b02576cbb5b2d319c662

[ "MIT" ]

null

s = 'Ala ma kota' lz = list(s) print(lz) print() for i in range(len(lz)): print(lz[i]) print() for i in lz: print(i)

9.214286

24

0.55814

26

129

2.769231

0.461538

0.291667

0.25

0.305556

0

0.255814

129

14

25

9.214286

0.75

0

0.222222

0

0.084615

0

1

0

false

0

0.555556

1

0

null

1

0

null

0

1

0

5

9647cdb6d81b7f03cf0c7ab77041200606430be9

134

py

Python

aspectizing-proto/.test6.py

amogorkon/pyuse

0e56b1cb9e88938499395f1482f86ff6fdd60a47

[ "MIT" ]

27

2021-06-14T22:48:47.000Z

2022-03-27T13:52:23.000Z

aspectizing-proto/.test6.py

amogorkon/justuse

0e56b1cb9e88938499395f1482f86ff6fdd60a47

[ "MIT" ]

375

2021-05-27T22:21:57.000Z

2022-03-31T17:27:54.000Z

aspectizing-proto/.test6.py

amogorkon/use

0e56b1cb9e88938499395f1482f86ff6fdd60a47

[ "MIT" ]

7

2021-06-13T17:54:43.000Z

2021-12-02T20:02:01.000Z

import numpy from aspectizing import any_callable, aspect, woody_logger aspect(numpy, any_callable, "", woody_logger, dry_run=True)

22.333333

59

0.80597

19

134

5.421053

0.631579

0.213592

0

0.11194

134

5

60

26.8

0.865546

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

9657d5034aeefcbb651563c36c9b4338371ffeb9

23

py

Python

sherlockpipe/__init__.py

franpoz/SHERLOCK

6c9e79405aa84e86cd1d6c41fa1cc45d5dbcfb46

[ "MIT" ]

20

2020-09-25T13:18:46.000Z

2022-03-09T14:01:03.000Z

sherlockpipe/__init__.py

franpoz/SHERLOCK

6c9e79405aa84e86cd1d6c41fa1cc45d5dbcfb46

[ "MIT" ]

74

2020-09-22T12:19:28.000Z

2022-01-12T13:53:35.000Z

sherlockpipe/__init__.py

franpoz/SHERLOCK

6c9e79405aa84e86cd1d6c41fa1cc45d5dbcfb46

[ "MIT" ]

5

2020-10-19T10:01:05.000Z

2021-12-16T10:23:24.000Z

__version__ = "0.25.10"

23

0.695652

4

23

3

1

0

0.238095

0.086957

23

1

23

0.333333

0

0.291667

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

965c03c30f15ae5b410954290d718796198b6e62

44

py

Python

module/__init__.py

l454124613/work_hours

d70c70d16521beb70015461e11c1978b4925d0f5

[ "MIT" ]

null

module/__init__.py

l454124613/work_hours

d70c70d16521beb70015461e11c1978b4925d0f5

[ "MIT" ]

null

module/__init__.py

l454124613/work_hours

d70c70d16521beb70015461e11c1978b4925d0f5

[ "MIT" ]

null

# -*- coding:utf-8 -*- # Author:lixuecheng

11

22

0.590909

5

44

5.2

1

0

0.027027

0.159091

44

3

23

14.666667

0.675676

0.863636

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

968e5a90b55abcbea4f9f0fa7a286870ffb42052

15,109

py

Python

src/tabs/insights.py

EthanG45/CSE412-HAML-Project

e6f754b2de35079453c1bf5e8814dc5fe4b6741c

[ "MIT" ]

1

2022-02-09T05:42:43.000Z

src/tabs/insights.py

EthanG45/CSE412-HAML-Project

e6f754b2de35079453c1bf5e8814dc5fe4b6741c

[ "MIT" ]

null

src/tabs/insights.py

EthanG45/CSE412-HAML-Project

e6f754b2de35079453c1bf5e8814dc5fe4b6741c

[ "MIT" ]

3

2020-11-28T23:06:03.000Z

2022-03-14T02:23:50.000Z

import PySimpleGUI as sg # import matplotlib.pyplot as plt # from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg from matplotlib.ticker import NullFormatter # useful for `logit` scale import matplotlib.pyplot as plt import numpy as np from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg import matplotlib matplotlib.use('TkAgg') from matplotlib.pyplot import figure ### #### #### #### #### #### #### #### #### ### # INSIGHTS TABLE TABS # ### #### #### #### #### #### #### #### #### ### class InsightsTab: def __init__(self, db): self.db = db self.top10SongByAverage = self.db.topTenSongsByAverage() self.top10SongByUser = self.db.topTenSongsByUser() self.top10AlbumByAverage = self.db.topTenAlbumsByAverage() self.top10AlbumByUser = self.db.topTenAlbumsByUser() self.top10WorstSongByAverage = self.db.topTenSongsByAverageWorst() self.top10WorstSongByUser = self.db.topTenSongsByUserWorst() self.top10WorstAlbumByAverage = self.db.topTenAlbumsByAverageWorst() self.top10WorstAlbumByUser = self.db.topTenAlbumsByUserWorst() def updateLists(self): self.top10SongByAverage = self.db.topTenSongsByAverage() self.top10SongByUser = self.db.topTenSongsByUser() self.top10AlbumByAverage = self.db.topTenAlbumsByAverage() self.top10AlbumByUser = self.db.topTenAlbumsByUser() self.top10WorstSongByAverage = self.db.topTenSongsByAverageWorst() self.top10WorstSongByUser = self.db.topTenSongsByUserWorst() self.top10WorstAlbumByAverage = self.db.topTenAlbumsByAverageWorst() self.top10WorstAlbumByUser = self.db.topTenAlbumsByUserWorst() def insightsTabGUI(self): top10Songs = sg.Tab( 'Top 10 Songs', [ [sg.Text("Top 10 Songs by Average Rating")], [sg.Table(values=self.top10SongByAverage, headings=['Song', 'Album', 'Artist', 'Genre', 'Duration', 'Link', 'Release Year', 'Average Rating', 'Listeners', 'Rating'], key='-AVG-TABLE-I01-', enable_events=True, size=(1220, 10), justification="left")], [sg.Text("Top 10 Songs by User Rating")], [sg.Table(values=self.top10SongByUser, headings=['Song', 'Album', 'Artist', 'Genre', 'Duration', 'Link', 'Release Year', 'Average Rating', 'Listeners', 'Rating'], key='-USER-TABLE-I01-', enable_events=True, size=(1220, 10), justification="left")] ], key='I01' ) # end of tab Record Label top10SongsGraph = sg.Tab( 'Top 10 Songs Graph', [ [sg.Text("Genres for Top 10 Songs")], [sg.Canvas(key='-USR-SONG-CANVAS-IO1-G-'), sg.Canvas(key='-AVG-SONG-CANVAS-IO1-G-')], ], key='I01-G' ) # end of tab Record Label top10Albums = sg.Tab( 'Top 10 Albums', [[sg.Text("Top 10 Albums by Average Rating")], [sg.Table(values=self.top10AlbumByAverage, headings=['Title', 'Album Duration', 'Cover Art URL', 'Averaqe Rating', 'Listeners', 'User Rating'], key='-AVG-TABLE-I02-', enable_events=True, size=(1220, 10), justification="left")], [sg.Text("Top 10 Albums by User Rating")], [sg.Table(values=self.top10AlbumByUser, headings=['Title', 'Album Duration', 'Cover Art URL', 'Averaqe Rating', 'Listeners', 'User Rating'], key='-USER-TABLE-I02-', enable_events=True, size=(1220, 10), justification="left")] ], key='I02' ) # end of tab Record Label top10AlbumsGraph = sg.Tab( 'Top 10 Albums Graph', [ [sg.Text("Listeners for Top 10 Albums")], [sg.Canvas(key='-USR-ALBUM-CANVAS-IO2-G-'), sg.Canvas(key='-AVG-ALBUM-CANVAS-IO2-G-')], ], key='I02-G' ) # end of tab Record Label top10WorstSongs = sg.Tab( 'Top 10 Worst Songs', [[sg.Text("Top 10 Worst Songs by Average Rating")], [sg.Table(values=self.top10WorstSongByAverage, headings=['Song', 'Album', 'Artist', 'Genre', 'Duration', 'Link', 'Release Year', 'Average Rating', 'Listeners', 'Rating'], key='-AVG-TABLE-I03-', enable_events=True, size=(1220, 10), justification="left")], [sg.Text("Top 10 Worst Songs by User Rating")], [sg.Table(values=self.top10WorstSongByUser, headings=['Song', 'Album', 'Artist', 'Genre', 'Duration', 'Link', 'Release Year', 'Average Rating', 'Listeners', 'Rating'], key='-USER-TABLE-I03-', enable_events=True, size=(1220, 10), justification="left")] ], key='I03' ) # end of tab Record Label top10WorstSongsGraph = sg.Tab( 'Top 10 Worst Songs Graph', [ [sg.Text("Genres for Top 10 Worst Songs")], [sg.Canvas(key='-USR-SONG-CANVAS-IO3-G-'), sg.Canvas(key='-AVG-SONG-CANVAS-IO3-G-')], ], key='I03-G' ) # end of tab Record Label top10WorstAlbums = sg.Tab( 'Top 10 Worst Albums', [[sg.Text("Top 10 Worst Albums by Average Rating")], [sg.Table(values=self.top10WorstAlbumByAverage, headings=['Title', 'Album Duration', 'Cover Art URL', 'Averaqe Rating', 'Listeners', 'User Rating'], key='-AVG-TABLE-I04-', enable_events=True, size=(1220, 10), justification="left")], [sg.Text("Top 10 Worst Albums by User Rating")], [sg.Table(values=self.top10WorstAlbumByUser, headings=['Title', 'Album Duration', 'Cover Art URL', 'Averaqe Rating', 'Listeners', 'User Rating'], key='-USER-TABLE-I04-', enable_events=True, size=(1220, 10), justification="left")] ], key='I04' ) # end of tab Record Label top10WorstAlbumsGraph = sg.Tab( 'Top 10 Worst Albums Graph', [ [sg.Text("Listeners for Top 10 Worst Albums")], [sg.Canvas(key='-USR-ALBUM-CANVAS-IO4-G-'), sg.Canvas(key='-AVG-ALBUM-CANVAS-IO4-G-')], ], key='I04-G' ) # end of tab Record Label ### #### #### #### #### #### #### #### #### ### # END OF INSIGHTS TABLE TABS # ### #### #### #### #### #### #### #### #### ### insightsTab = sg.Tab( 'Insights', [[sg.TabGroup( [[ top10Songs, top10SongsGraph, top10Albums, top10AlbumsGraph, top10WorstSongs, top10WorstSongsGraph, top10WorstAlbums, top10WorstAlbumsGraph ]], key='tabgroupInsights', enable_events=True ) # end of TabGroup ]], key='insights_tab' ) # end of tab insights return insightsTab def topTenAlbumsByUserPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) listData = [] listLabel = [] for elem in range(7): listData.append(db.topTenAlbumsByUser()[elem][4]) listLabel.append(db.topTenAlbumsByUser()[elem][0]) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Number of Listeners per Album Title By User Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenSongsByUserPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) label = ['Country', 'EDM', 'Heavy Metal', 'Hip Hop', 'Metal', 'Pop', 'Rap', 'Rock', 'Soundtrack'] data = {'Country': 0, 'EDM': 0, 'Heavy Metal': 0,'Hip Hop': 0, 'Metal': 0, 'Pop': 0, 'Rap': 0, 'Rock': 0,'Soundtrack': 0} listData = [] listLabel = [] for elem in db.topTenSongsByUser(): res = elem[3] data[res] = data[res] + 1. for i in label: for elem in data: if i == elem and data[elem] != 0.: listData.append(data[elem]) listLabel.append(elem) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Genre Distribution within Top 10 Songs by User Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenSongsByAveragePieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) label = ['Country', 'EDM', 'Heavy Metal', 'Hip Hop', 'Metal', 'Pop', 'Rap', 'Rock', 'Soundtrack'] data = {'Country': 0, 'EDM': 0, 'Heavy Metal': 0,'Hip Hop': 0, 'Metal': 0, 'Pop': 0, 'Rap': 0, 'Rock': 0,'Soundtrack': 0} listData = [] listLabel = [] for elem in db.topTenSongsByAverage(): res = elem[3] data[res] = data[res] + 1. for i in label: for elem in data: if i == elem and data[elem] != 0.: listData.append(data[elem]) listLabel.append(elem) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Genre Distribution within Top 10 Songs by Average Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenAlbumsByAveragePieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) listData = [] listLabel = [] for elem in range(7): listData.append(db.topTenAlbumsByAverage()[elem][4]) listLabel.append(db.topTenAlbumsByAverage()[elem][0]) ax.pie(listData, labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Number of Listeners per Album Title By Average Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenAlbumsByAverageWorstPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) listData = [] listLabel = [] for elem in range(7): listData.append(db.topTenAlbumsByAverageWorst()[elem][4]) listLabel.append(db.topTenAlbumsByAverageWorst()[elem][0]) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Number of Listeners per Album Title By Worst Average Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenAlbumsByUserWorstPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) listData = [] listLabel = [] for elem in range(7): listData.append(db.topTenAlbumsByUserWorst()[elem][4]) listLabel.append(db.topTenAlbumsByUserWorst()[elem][0]) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Number of Listeners per Album Title By Worst User Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenSongsByUserWorstPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) label = ['Country', 'EDM', 'Heavy Metal', 'Hip Hop', 'Metal', 'Pop', 'Rap', 'Rock', 'Soundtrack'] data = {'Country': 0, 'EDM': 0, 'Heavy Metal': 0,'Hip Hop': 0, 'Metal': 0, 'Pop': 0, 'Rap': 0, 'Rock': 0,'Soundtrack': 0} listData = [] listLabel = [] for elem in db.topTenSongsByUserWorst(): res = elem[3] data[res] = data[res] + 1. for i in label: for elem in data: if i == elem and data[elem] != 0.: listData.append(data[elem]) listLabel.append(elem) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Genre Distribution within Top 10 Songs by Worst User Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def topTenSongsByAverageWorstPieFigure(self, canvas, db): plt.close('all') figure, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal")) label = ['Country', 'EDM', 'Heavy Metal', 'Hip Hop', 'Metal', 'Pop', 'Rap', 'Rock', 'Soundtrack'] data = {'Country': 0, 'EDM': 0, 'Heavy Metal': 0,'Hip Hop': 0, 'Metal': 0, 'Pop': 0, 'Rap': 0, 'Rock': 0,'Soundtrack': 0} listData = [] listLabel = [] for elem in db.topTenSongsByAverageWorst(): res = elem[3] data[res] = data[res] + 1. for i in label: for elem in data: if i == elem and data[elem] != 0.: listData.append(data[elem]) listLabel.append(elem) ax.pie(listData,labels=listLabel, autopct='%1i%%',shadow=True) ax.set_title("Genre Distribution within Top 10 Songs by Worst Average Rating") figure_canvas_agg = FigureCanvasTkAgg(figure, canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1) def drawFigure(self, canvas, figureFunc, db): figure_canvas_agg = FigureCanvasTkAgg(figureFunc(db), canvas) figure_canvas_agg.draw() figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1)

44.833828

218

0.557151

1,601

15,109

5.193004

0.11243

0.050517

0.048713

0.03464

0.825716

0.792158

0.77135

0.727087

0.677051

0.675607

0

0.029173

0.298961

15,109

336

219

44.967262

0.755759

0.031504

0

0.496241

0

0.174803

0.013

0

1

0.045113

false

0

0.026316

0

0.078947

0

null

0

1

0

1

0

null

0

5

737d3ea68755a1f40b1fe00dcac14720ff327126

588

py

Python

course-2:combining-building-blocks/subject-1:collections/lesson-1:Lists.py

regnart-tech-club/python

069df070059de662d4104de8192e45407a7e94ce

[ "Apache-2.0" ]

null

course-2:combining-building-blocks/subject-1:collections/lesson-1:Lists.py

regnart-tech-club/python

069df070059de662d4104de8192e45407a7e94ce

[ "Apache-2.0" ]

null

course-2:combining-building-blocks/subject-1:collections/lesson-1:Lists.py

regnart-tech-club/python

069df070059de662d4104de8192e45407a7e94ce

[ "Apache-2.0" ]

1

2016-04-03T00:53:37.000Z

light_primary_colors = ['red', 'green', 'blue'] light_secondary_colors = ['cyan', 'magenta', 'yellow'] paint_primary_colors = ['red', 'yellow', 'blue'] paint_secondary_colors = ['orange', 'green', 'purple'] # adding lists together print(light_primary_colors + light_secondary_colors) print(light_primary_colors + paint_primary_colors) # appending new elements ink_primary_colors = light_secondary_colors ink_primary_colors.append('black') print(ink_primary_colors) # accessing list elements print light_primary_colors[0] print light_primary_colors[1] print dir(light_primary_colors)

28

54

0.794218

77

588

5.675325

0.363636

0.327231

0.24714

0.210526

0.15103

0

0.003745

0.091837

588

20

55

29.4

0.814607

0.115646

0

0.124031

0

null

0

null

0.5

0

null

1

0

null

0

1

0

1

0

5

738762a61f6d802bf7ab5fa3a33606126b21a3cf

8,242

py

Python

swig/x64dbgpy/pluginsdk/_scriptapi/register.py

limbernie/x64dbgpy

2e2f4108ddbb42cffb80fb444e3ac56924cf1f7a

[ "MIT" ]

1,279

2016-06-28T19:17:37.000Z

2022-03-29T02:43:01.000Z

swig/x64dbgpy/pluginsdk/_scriptapi/register.py

limbernie/x64dbgpy

2e2f4108ddbb42cffb80fb444e3ac56924cf1f7a

[ "MIT" ]

60

2016-07-04T18:27:24.000Z

2021-09-11T08:12:48.000Z

swig/x64dbgpy/pluginsdk/_scriptapi/register.py

limbernie/x64dbgpy

2e2f4108ddbb42cffb80fb444e3ac56924cf1f7a

[ "MIT" ]

72

2016-07-23T00:39:49.000Z

2022-01-19T05:08:55.000Z

from x64dbgpy.utils import is_64bit from .. import x64dbg def Size(): return x64dbg.Size() # x86 Registers def GetEAX(): return x64dbg.GetEAX() def SetEAX(value): return x64dbg.SetEAX(value) def GetAX(): return x64dbg.GetAX() def SetAX(value): return x64dbg.SetAX(value) def GetAH(): return x64dbg.GetAH() def SetAH(value): return x64dbg.SetAH(value) def GetAL(): return x64dbg.GetAL() def SetAL(value): return x64dbg.SetAL(value) def GetEBX(): return x64dbg.GetEBX() def SetEBX(value): return x64dbg.SetEBX(value) def GetBX(): return x64dbg.GetBX() def SetBX(value): return x64dbg.SetBX(value) def GetBH(): return x64dbg.GetBH() def SetBH(value): return x64dbg.SetBH(value) def GetBL(): return x64dbg.GetBL() def SetBL(value): return x64dbg.SetBL(value) def GetECX(): return x64dbg.GetECX() def SetECX(value): return x64dbg.SetECX(value) def GetCX(): return x64dbg.GetCX() def SetCX(value): return x64dbg.SetCX(value) def GetCH(): return x64dbg.GetCH() def SetCH(value): return x64dbg.SetCH(value) def GetCL(): return x64dbg.GetCL() def SetCL(value): return x64dbg.SetCL(value) def GetEDX(): return x64dbg.GetEDX() def SetEDX(value): return x64dbg.SetEDX(value) def GetDX(): return x64dbg.GetDX() def SetDX(value): return x64dbg.SetDX(value) def GetDH(): return x64dbg.GetDH() def SetDH(value): return x64dbg.SetDH(value) def GetDL(): return x64dbg.GetDL() def SetDL(value): return x64dbg.SetDL(value) def GetEDI(): return x64dbg.GetEDI() def SetEDI(value): return x64dbg.SetEDI(value) def GetDI(): return x64dbg.GetDI() def SetDI(value): return x64dbg.SetDI(value) def GetESI(): return x64dbg.GetESI() def SetESI(value): return x64dbg.SetESI(value) def GetSI(): return x64dbg.GetSI() def SetSI(value): return x64dbg.SetSI(value) def GetEBP(): return x64dbg.GetEBP() def SetEBP(value): return x64dbg.SetEBP(value) def GetBP(): return x64dbg.GetBP() def SetBP(value): return x64dbg.SetBP(value) def GetESP(): return x64dbg.GetESP() def SetESP(value): return x64dbg.SetESP(value) def GetSP(): return x64dbg.GetSP() def SetSP(value): return x64dbg.SetSP(value) def GetEIP(): return x64dbg.GetEIP() def SetEIP(value): return x64dbg.SetEIP(value) # x86 Debug Registers def GetDR0(): return x64dbg.GetDR0() def SetDR0(value): return x64dbg.SetDR0(value) def GetDR1(): return x64dbg.GetDR1() def SetDR1(value): return x64dbg.SetDR1(value) def GetDR2(): return x64dbg.GetDR2() def SetDR2(value): return x64dbg.SetDR2(value) def GetDR3(): return x64dbg.GetDR3() def SetDR3(value): return x64dbg.SetDR3(value) def GetDR6(): return x64dbg.GetDR6() def SetDR6(value): return x64dbg.SetDR6(value) def GetDR7(): return x64dbg.GetDR7() def SetDR7(value): return x64dbg.SetDR7(value) # x64 Registers if is_64bit(): def GetRAX(): return x64dbg.GetRAX() def SetRAX(value): return x64dbg.SetRAX(value) def GetRBX(): return x64dbg.GetRBX() def SetRBX(value): return x64dbg.SetRBX(value) def GetRCX(): return x64dbg.GetRCX() def SetRCX(value): return x64dbg.SetRCX(value) def GetRDX(): return x64dbg.GetRDX() def SetRDX(value): return x64dbg.SetRDX(value) def GetRSI(): return x64dbg.GetRSI() def SetRSI(value): return x64dbg.SetRSI(value) def GetSIL(): return x64dbg.GetSIL() def SetSIL(value): return x64dbg.SetSIL(value) def GetRDI(): return x64dbg.GetRDI() def SetRDI(value): return x64dbg.SetRDI(value) def GetDIL(): return x64dbg.GetDIL() def SetDIL(value): return x64dbg.SetDIL(value) def GetRBP(): return x64dbg.GetRBP() def SetRBP(value): return x64dbg.SetRBP(value) def GetBPL(): return x64dbg.GetBPL() def SetBPL(value): return x64dbg.SetBPL(value) def GetRSP(): return x64dbg.GetRSP() def SetRSP(value): return x64dbg.SetRSP(value) def GetSPL(): return x64dbg.GetSPL() def SetSPL(value): return x64dbg.SetSPL(value) def GetRIP(): return x64dbg.GetRIP() def SetRIP(value): return x64dbg.SetRIP(value) def GetR8(): return x64dbg.GetR8() def SetR8(value): return x64dbg.SetR8(value) def GetR8D(): return x64dbg.GetR8D() def SetR8D(value): return x64dbg.SetR8D(value) def GetR8W(): return x64dbg.GetR8W() def SetR8W(value): return x64dbg.SetR8W(value) def GetR8B(): return x64dbg.GetR8B() def SetR8B(value): return x64dbg.SetR8B(value) def GetR9(): return x64dbg.GetR9() def SetR9(value): return x64dbg.SetR9(value) def GetR9D(): return x64dbg.GetR9D() def SetR9D(value): return x64dbg.SetR9D(value) def GetR9W(): return x64dbg.GetR9W() def SetR9W(value): return x64dbg.SetR9W(value) def GetR9B(): return x64dbg.GetR9B() def SetR9B(value): return x64dbg.SetR9B(value) def GetR10(): return x64dbg.GetR10() def SetR10(value): return x64dbg.SetR10(value) def GetR10D(): return x64dbg.GetR10D() def SetR10D(value): return x64dbg.SetR10D(value) def GetR10W(): return x64dbg.GetR10W() def SetR10W(value): return x64dbg.SetR10W(value) def GetR10B(): return x64dbg.GetR10B() def SetR10B(value): return x64dbg.SetR10B(value) def GetR11(): return x64dbg.GetR11() def SetR11(value): return x64dbg.SetR11(value) def GetR11D(): return x64dbg.GetR11D() def SetR11D(value): return x64dbg.SetR11D(value) def GetR11W(): return x64dbg.GetR11W() def SetR11W(value): return x64dbg.SetR11W(value) def GetR11B(): return x64dbg.GetR11B() def SetR11B(value): return x64dbg.SetR11B(value) def GetR12(): return x64dbg.GetR12() def SetR12(value): return x64dbg.SetR12(value) def GetR12D(): return x64dbg.GetR12D() def SetR12D(value): return x64dbg.SetR12D(value) def GetR12W(): return x64dbg.GetR12W() def SetR12W(value): return x64dbg.SetR12W(value) def GetR12B(): return x64dbg.GetR12B() def SetR12B(value): return x64dbg.SetR12B(value) def GetR13(): return x64dbg.GetR13() def SetR13(value): return x64dbg.SetR13(value) def GetR13D(): return x64dbg.GetR13D() def SetR13D(value): return x64dbg.SetR13D(value) def GetR13W(): return x64dbg.GetR13W() def SetR13W(value): return x64dbg.SetR13W(value) def GetR13B(): return x64dbg.GetR13B() def SetR13B(value): return x64dbg.SetR13B(value) def GetR14(): return x64dbg.GetR14() def SetR14(value): return x64dbg.SetR14(value) def GetR14D(): return x64dbg.GetR14D() def SetR14D(value): return x64dbg.SetR14D(value) def GetR14W(): return x64dbg.GetR14W() def SetR14W(value): return x64dbg.SetR14W(value) def GetR14B(): return x64dbg.GetR14B() def SetR14B(value): return x64dbg.SetR14B(value) def GetR15(): return x64dbg.GetR15() def SetR15(value): return x64dbg.SetR15(value) def GetR15D(): return x64dbg.GetR15D() def SetR15D(value): return x64dbg.SetR15D(value) def GetR15W(): return x64dbg.GetR15W() def SetR15W(value): return x64dbg.SetR15W(value) def GetR15B(): return x64dbg.GetR15B() def SetR15B(value): return x64dbg.SetR15B(value) # Generic Registers def GetCIP(): return x64dbg.GetCIP() def SetCIP(value): return x64dbg.SetCIP(value) def GetCSP(): return x64dbg.GetCSP() def SetCSP(value): return x64dbg.SetCSP(value)

17.028926

36

0.6223

962

8,242

5.329522

0.179834

0.367466

0.258631

0

0.094721

0.262194

8,242

483

37

17.064182

0.748397

0.007886

0

1

0.495268

false

0

0.006309

0.495268

0.996845

0

null

1

0

null

0

1

0

1

0

5

73f99a8396e8867f5bf5f45ad88f1c0c715d78b7

51

py

Python

kmmi/enumeration/__init__.py

Decitizen/kMMI

921ef6e45fbec484251444886e246741d7f0120a

[ "MIT" ]

null

kmmi/enumeration/__init__.py

Decitizen/kMMI

921ef6e45fbec484251444886e246741d7f0120a

[ "MIT" ]

null

kmmi/enumeration/__init__.py

Decitizen/kMMI

921ef6e45fbec484251444886e246741d7f0120a

[ "MIT" ]

null

from kmmi.enumeration.graphlet_enumeration import *

51

0.882353

6

51

7.333333

0.833333

0

0.058824

51

1

51

0.916667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fb667e17ceb79273f603d2e99382b1aa31ff590b

116

py

Python

xbee/thread/zigbee.py

PowerFlex/python-xbee-intercept

0c07f3a5f16f479ad7c925cd31638598030cf5a7

[ "MIT" ]

65

2015-12-06T02:38:28.000Z

2017-09-05T16:46:07.000Z

xbee/thread/zigbee.py

PowerFlex/python-xbee-intercept

0c07f3a5f16f479ad7c925cd31638598030cf5a7

[ "MIT" ]

44

2015-10-23T15:33:54.000Z

2017-09-01T06:39:50.000Z

xbee/thread/zigbee.py

PowerFlex/python-xbee-intercept

0c07f3a5f16f479ad7c925cd31638598030cf5a7

[ "MIT" ]

43

2015-12-15T02:52:21.000Z

2017-06-24T17:14:53.000Z

from xbee.thread.base import XBeeBase import xbee.backend as _xbee class ZigBee(_xbee.ZigBee, XBeeBase): pass

16.571429

37

0.775862

17

116

5.176471

0.647059

0

0.155172

116

6

38

19.333333

0.897959

0

1

0

true

0.25

0.5

0

0.75

0

1

0

null

0

1

0

null

0

1

0

5

fb8443771c9e524decee3ae2c0fd056c0c2d0c02

122

py

Python

karp5/tests/parser/test_parser.py

spraakbanken/karp-backend-v5

bfca9d0f29a1243ee8d817c6a7db8b30a7da1097

[ "MIT" ]

4

2018-01-09T10:20:22.000Z

2019-11-21T12:26:56.000Z

karp5/tests/parser/test_parser.py

spraakbanken/karp-backend-v5

bfca9d0f29a1243ee8d817c6a7db8b30a7da1097

[ "MIT" ]

44

2018-03-23T13:59:13.000Z

2022-03-29T06:03:17.000Z

karp5/tests/parser/test_parser.py

spraakbanken/karp-backend-v5

bfca9d0f29a1243ee8d817c6a7db8b30a7da1097

[ "MIT" ]

2

2018-01-07T12:08:32.000Z

2019-08-21T08:05:17.000Z

from karp5.server.translator import parser from karp5.context import auth args = {} def test_empty_call(app): pass

13.555556

42

0.754098

18

122

5

0.833333

0.2

0

0.019802

0.172131

122

8

43

15.25

0.871287

0

1

0.2

false

0.2

0.4

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fbc8b5a30bce7a40ceb242dc188526ae77dbaa6c

64

py

Python

arxtools/__init__.py

stesla/arxtools

7f1a3b973e3d78faed4085d547b7d27ebcd9838d

[ "MIT" ]

null

arxtools/__init__.py

stesla/arxtools

7f1a3b973e3d78faed4085d547b7d27ebcd9838d

[ "MIT" ]

null

arxtools/__init__.py

stesla/arxtools

7f1a3b973e3d78faed4085d547b7d27ebcd9838d

[ "MIT" ]

null

from .export import export_clues from .fetch import fetch_clues

21.333333

32

0.84375

10

64

5.2

0.5

0

0.125

64

2

33

32

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fbcf476b2bb414abb1f00a526834f5f76b227e97

155

py

Python

amazon_credentials.example.py

javl/dashing

3d70fa0c6d775de5be20eb38867c0e262f953ac8

[ "MIT" ]

1

2021-12-06T13:20:00.000Z

amazon_credentials.example.py

javl/dashing

3d70fa0c6d775de5be20eb38867c0e262f953ac8

[ "MIT" ]

null

amazon_credentials.example.py

javl/dashing

3d70fa0c6d775de5be20eb38867c0e262f953ac8

[ "MIT" ]

1

2021-12-06T13:20:04.000Z

#!/usr/bin/env python AMAZON_ACCESS_KEY = 'YOUR_AMAZON_ACCESS_KEY' AMAZON_SECRET_KEY = 'YOUR_AMAZON_SECRET_KEY' AMAZON_ASSOC_TAG = 'YOUR_AMAZON_ASSOC_TAG'

31

44

0.83871

25

155

4.6

0.44

0.26087

0

0.070968

155

5

45

31

0.798611

0.129032

0

0.481481

0

1

0

false

0

1

0

null

1

0

1

0

1

null

0

5

83b8d29540c4c94bb72f8e361c2fc3c4db66b73e

44

py

Python

tests/pr/__init__.py

iamamutt/retrocookie

4cc4da83c5fc3751377730c06fcef746a06fe60a

[ "MIT" ]

15

2020-06-21T14:35:42.000Z

2022-03-30T15:48:55.000Z

tests/pr/__init__.py

iamamutt/retrocookie

4cc4da83c5fc3751377730c06fcef746a06fe60a

[ "MIT" ]

223

2020-05-22T14:35:05.000Z

2022-03-28T00:19:23.000Z

tests/pr/__init__.py

iamamutt/retrocookie

4cc4da83c5fc3751377730c06fcef746a06fe60a

[ "MIT" ]

4

2020-11-19T12:55:01.000Z

2022-03-15T14:24:25.000Z

"""Tests for the retrocookie.pr package."""

22

43

0.704545

6

44

5.166667

1

0

0.113636

44

1

44

0.794872

0.840909

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

83e09232e87458819bc0d517453a23907363c34a

62,540

py

Python

tests/app/main/views/test_manage_users.py

matthewford/notifications-admin

6c6be3851e4b3f01037dc66f6d227bd741f79fb9

[ "MIT" ]

null

tests/app/main/views/test_manage_users.py

matthewford/notifications-admin

6c6be3851e4b3f01037dc66f6d227bd741f79fb9

[ "MIT" ]

null

tests/app/main/views/test_manage_users.py

matthewford/notifications-admin

6c6be3851e4b3f01037dc66f6d227bd741f79fb9

[ "MIT" ]

null

import copy import uuid import pytest from flask import url_for import app from app.utils import is_gov_user from tests.conftest import ( ORGANISATION_ID, ORGANISATION_TWO_ID, SERVICE_ONE_ID, USER_ONE_ID, create_active_user_empty_permissions, create_active_user_manage_template_permissions, create_active_user_view_permissions, create_active_user_with_permissions, normalize_spaces, sample_uuid, ) @pytest.mark.parametrize('user, expected_self_text, expected_coworker_text', [ ( create_active_user_with_permissions(), ( 'Test User (you) ' 'Can See dashboard ' 'Can Send messages ' 'Can Add and edit templates ' 'Can Manage settings, team and usage ' 'Can Manage API integration' ), ( 'ZZZZZZZZ zzzzzzz@example.gov.uk ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration ' 'Change details for ZZZZZZZZ zzzzzzz@example.gov.uk' ) ), ( create_active_user_empty_permissions(), ( 'Test User With Empty Permissions (you) ' 'Cannot See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ), ( 'ZZZZZZZZ zzzzzzz@example.gov.uk ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ), ), ( create_active_user_view_permissions(), ( 'Test User With Permissions (you) ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ), ( 'ZZZZZZZZ zzzzzzz@example.gov.uk ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ) ), ( create_active_user_manage_template_permissions(), ( 'Test User With Permissions (you) ' 'Can See dashboard ' 'Cannot Send messages ' 'Can Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ), ( 'ZZZZZZZZ zzzzzzz@example.gov.uk ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ) ), ( create_active_user_manage_template_permissions(), ( 'Test User With Permissions (you) ' 'Can See dashboard ' 'Cannot Send messages ' 'Can Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ), ( 'ZZZZZZZZ zzzzzzz@example.gov.uk ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ) ), ]) def test_should_show_overview_page( client_request, mocker, mock_get_invites_for_service, mock_get_template_folders, mock_has_no_jobs, service_one, user, expected_self_text, expected_coworker_text, active_user_view_permissions, ): current_user = user other_user = copy.deepcopy(active_user_view_permissions) other_user['email_address'] = 'zzzzzzz@example.gov.uk' other_user['name'] = 'ZZZZZZZZ' other_user['id'] = 'zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz' mocker.patch('app.user_api_client.get_user', return_value=current_user) mock_get_users = mocker.patch('app.models.user.Users.client_method', return_value=[ current_user, other_user, ]) page = client_request.get('main.manage_users', service_id=SERVICE_ONE_ID) assert normalize_spaces(page.select_one('h1').text) == 'Team members' assert normalize_spaces(page.select('.user-list-item')[0].text) == expected_self_text # [1:5] are invited users assert normalize_spaces(page.select('.user-list-item')[6].text) == expected_coworker_text mock_get_users.assert_called_once_with(SERVICE_ONE_ID) def test_should_show_caseworker_on_overview_page( client_request, mocker, mock_get_invites_for_service, mock_get_template_folders, service_one, active_user_view_permissions, active_caseworking_user, ): service_one['permissions'].append('caseworking') current_user = active_user_view_permissions other_user = active_caseworking_user other_user['id'] = uuid.uuid4() other_user['email_address'] = 'zzzzzzz@example.gov.uk' mocker.patch('app.user_api_client.get_user', return_value=current_user) mocker.patch('app.models.user.Users.client_method', return_value=[ current_user, other_user, ]) page = client_request.get('main.manage_users', service_id=SERVICE_ONE_ID) assert normalize_spaces(page.select_one('h1').text) == 'Team members' assert normalize_spaces(page.select('.user-list-item')[0].text) == ( 'Test User With Permissions (you) ' 'Can See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ) # [1:5] are invited users assert normalize_spaces(page.select('.user-list-item')[6].text) == ( 'Test User zzzzzzz@example.gov.uk ' 'Cannot See dashboard ' 'Can Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' ) def test_should_show_overview_page_for_broadcast_service( client_request, mocker, mock_get_invites_for_service, mock_get_template_folders, service_one, active_user_view_permissions, active_user_with_permissions, ): service_one['permissions'].append('broadcast') mocker.patch('app.models.user.Users.client_method', return_value=[ active_user_with_permissions, active_user_view_permissions, ]) page = client_request.get('main.manage_users', service_id=SERVICE_ONE_ID) assert normalize_spaces(page.select('.user-list-item')[0].text) == ( 'Test User (you) ' 'Can Prepare and approve broadcasts ' 'Can Add and edit templates ' 'Can Manage settings and team' ) assert normalize_spaces(page.select('.user-list-item')[1].text) == ( 'Test User With Permissions (you) ' 'Cannot Prepare and approve broadcasts ' 'Cannot Add and edit templates ' 'Cannot Manage settings and team' ) @pytest.mark.parametrize('endpoint, extra_args, service_has_email_auth, auth_options_hidden', [ ( 'main.edit_user_permissions', {'user_id': sample_uuid()}, True, False ), ( 'main.edit_user_permissions', {'user_id': sample_uuid()}, False, True ), ( 'main.invite_user', {}, True, False ), ( 'main.invite_user', {}, False, True ) ]) def test_service_with_no_email_auth_hides_auth_type_options( client_request, endpoint, extra_args, service_has_email_auth, auth_options_hidden, service_one, mock_get_users_by_service, mock_get_template_folders ): if service_has_email_auth: service_one['permissions'].append('email_auth') page = client_request.get(endpoint, service_id=service_one['id'], **extra_args) assert (page.find('input', attrs={"name": "login_authentication"}) is None) == auth_options_hidden @pytest.mark.parametrize('service_has_caseworking', (True, False)) @pytest.mark.parametrize('endpoint, extra_args', [ ( 'main.edit_user_permissions', {'user_id': sample_uuid()}, ), ( 'main.invite_user', {}, ), ]) def test_service_without_caseworking_doesnt_show_admin_vs_caseworker( client_request, mock_get_users_by_service, mock_get_template_folders, endpoint, service_has_caseworking, extra_args, ): page = client_request.get( endpoint, service_id=SERVICE_ONE_ID, **extra_args ) permission_checkboxes = page.select('input[type=checkbox]') for idx in range(len(permission_checkboxes)): assert permission_checkboxes[idx]['name'] == 'permissions_field' assert permission_checkboxes[0]['value'] == 'view_activity' assert permission_checkboxes[1]['value'] == 'send_messages' assert permission_checkboxes[2]['value'] == 'manage_templates' assert permission_checkboxes[3]['value'] == 'manage_service' assert permission_checkboxes[4]['value'] == 'manage_api_keys' @pytest.mark.parametrize('endpoint, extra_args', [ ( 'main.edit_user_permissions', {'user_id': sample_uuid()}, ), ( 'main.invite_user', {}, ), ]) def test_broadcast_service_only_shows_relevant_permissions( client_request, service_one, mock_get_users_by_service, mock_get_template_folders, endpoint, extra_args, ): service_one['permissions'] = ['broadcast'] page = client_request.get( endpoint, service_id=SERVICE_ONE_ID, **extra_args ) assert [ (field['name'], field['value']) for field in page.select('input[type=checkbox]') ] == [ ('permissions_field', 'send_messages'), ('permissions_field', 'manage_templates'), ('permissions_field', 'manage_service'), ] @pytest.mark.parametrize('service_has_email_auth, displays_auth_type', [ (True, True), (False, False) ]) def test_manage_users_page_shows_member_auth_type_if_service_has_email_auth_activated( client_request, service_has_email_auth, service_one, mock_get_users_by_service, mock_get_invites_for_service, mock_get_template_folders, displays_auth_type ): if service_has_email_auth: service_one['permissions'].append('email_auth') page = client_request.get('main.manage_users', service_id=service_one['id']) assert bool(page.select_one('.tick-cross-list-hint')) == displays_auth_type @pytest.mark.parametrize('sms_option_disabled, mobile_number, expected_label', [ ( True, None, """ Text message code Not available because this team member has not added a phone number to their profile """, ), ( False, '07700 900762', """ Text message code """, ), ]) def test_user_with_no_mobile_number_cant_be_set_to_sms_auth( client_request, mock_get_users_by_service, mock_get_template_folders, sms_option_disabled, mobile_number, expected_label, service_one, mocker, active_user_with_permissions, ): active_user_with_permissions['mobile_number'] = mobile_number service_one['permissions'].append('email_auth') mocker.patch('app.user_api_client.get_user', return_value=active_user_with_permissions) page = client_request.get( 'main.edit_user_permissions', service_id=service_one['id'], user_id=sample_uuid(), ) sms_auth_radio_button = page.select_one('input[value="sms_auth"]') assert sms_auth_radio_button.has_attr("disabled") == sms_option_disabled assert normalize_spaces( page.select_one('label[for=login_authentication-0]').text ) == normalize_spaces(expected_label) @pytest.mark.parametrize('endpoint, extra_args, expected_checkboxes', [ ( 'main.edit_user_permissions', {'user_id': sample_uuid()}, [ ('view_activity', True), ('send_messages', True), ('manage_templates', True), ('manage_service', True), ('manage_api_keys', True), ] ), ( 'main.invite_user', {}, [ ('view_activity', False), ('send_messages', False), ('manage_templates', False), ('manage_service', False), ('manage_api_keys', False), ] ), ]) def test_should_show_page_for_one_user( client_request, mock_get_users_by_service, mock_get_template_folders, endpoint, extra_args, expected_checkboxes, ): page = client_request.get(endpoint, service_id=SERVICE_ONE_ID, **extra_args) checkboxes = page.select('input[type=checkbox]') assert len(checkboxes) == 5 for index, expected in enumerate(expected_checkboxes): expected_input_value, expected_checked = expected assert checkboxes[index]['name'] == 'permissions_field' assert checkboxes[index]['value'] == expected_input_value assert checkboxes[index].has_attr('checked') == expected_checked def test_invite_user_allows_to_choose_auth( client_request, mock_get_users_by_service, mock_get_template_folders, service_one, ): service_one['permissions'].append('email_auth') page = client_request.get('main.invite_user', service_id=SERVICE_ONE_ID) sms_auth_radio_button = page.select_one('input[value="sms_auth"]') assert sms_auth_radio_button.has_attr("disabled") is False def test_invite_user_has_correct_email_field( client_request, mock_get_users_by_service, mock_get_template_folders, ): email_field = client_request.get('main.invite_user', service_id=SERVICE_ONE_ID).select_one('#email_address') assert email_field['spellcheck'] == 'false' assert 'autocomplete' not in email_field def test_should_not_show_page_for_non_team_member( client_request, mock_get_users_by_service, ): client_request.get( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _expected_status=404, ) @pytest.mark.parametrize('submitted_permissions, permissions_sent_to_api', [ ( { 'permissions_field': [ 'view_activity', 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', ] }, { 'view_activity', 'send_messages', 'manage_service', 'manage_templates', 'manage_api_keys', } ), ( { 'permissions_field': [ 'view_activity', 'send_messages', 'manage_templates', ] }, { 'view_activity', 'send_messages', 'manage_templates', } ), ( {}, set(), ), ]) def test_edit_user_permissions( client_request, mocker, mock_get_users_by_service, mock_get_invites_for_service, mock_set_user_permissions, mock_get_template_folders, fake_uuid, submitted_permissions, permissions_sent_to_api, ): client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _data=dict( email_address="test@example.com", **submitted_permissions ), _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_set_user_permissions.assert_called_with( fake_uuid, SERVICE_ONE_ID, permissions=permissions_sent_to_api, folder_permissions=[] ) @pytest.mark.parametrize('submitted_permissions, permissions_sent_to_api', [ ( { 'permissions_field': [ 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', ] }, { 'view_activity', 'send_messages', 'manage_service', 'manage_templates', } ), ( { 'permissions_field': [ 'send_messages', ] }, { 'view_activity', 'send_messages', } ), ( { }, { 'view_activity', } ), ]) def test_edit_user_permissions_for_broadcast_service( client_request, service_one, mocker, mock_get_users_by_service, mock_get_invites_for_service, mock_set_user_permissions, mock_get_template_folders, fake_uuid, submitted_permissions, permissions_sent_to_api, ): service_one['permissions'] = 'broadcast' client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _data=dict( email_address="test@example.com", **submitted_permissions ), _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_set_user_permissions.assert_called_with( fake_uuid, SERVICE_ONE_ID, permissions=permissions_sent_to_api, folder_permissions=[] ) def test_edit_user_folder_permissions( client_request, mocker, service_one, mock_get_users_by_service, mock_get_invites_for_service, mock_set_user_permissions, mock_get_template_folders, fake_uuid, ): mock_get_template_folders.return_value = [ {'id': 'folder-id-1', 'name': 'folder_one', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-2', 'name': 'folder_one', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-3', 'name': 'folder_one', 'parent_id': 'folder-id-1', 'users_with_permission': []}, ] page = client_request.get( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=fake_uuid, ) assert [ item['value'] for item in page.select('input[name=folder_permissions]') ] == [ 'folder-id-1', 'folder-id-3', 'folder-id-2' ] client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _data=dict( folder_permissions=['folder-id-1', 'folder-id-3'] ), _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_set_user_permissions.assert_called_with( fake_uuid, SERVICE_ONE_ID, permissions=set(), folder_permissions=['folder-id-1', 'folder-id-3'] ) def test_cant_edit_user_folder_permissions_for_platform_admin_users( client_request, mocker, service_one, mock_get_users_by_service, mock_get_invites_for_service, mock_set_user_permissions, mock_get_template_folders, platform_admin_user, ): service_one['permissions'] = ['edit_folder_permissions'] mocker.patch( 'app.user_api_client.get_user', return_value=platform_admin_user ) mock_get_template_folders.return_value = [ {'id': 'folder-id-1', 'name': 'folder_one', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-2', 'name': 'folder_one', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-3', 'name': 'folder_one', 'parent_id': 'folder-id-1', 'users_with_permission': []}, ] page = client_request.get( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=platform_admin_user['id'], ) assert normalize_spaces(page.select('main p')[0].text) == 'platform@admin.gov.uk Change email address' assert normalize_spaces(page.select('main p')[2].text) == ( 'Platform admin users can access all template folders.' ) assert page.select('input[name=folder_permissions]') == [] client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=platform_admin_user['id'], _data={}, _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_set_user_permissions.assert_called_with( platform_admin_user['id'], SERVICE_ONE_ID, permissions={ 'manage_api_keys', 'manage_service', 'manage_templates', 'send_messages', 'view_activity', }, folder_permissions=None, ) def test_cant_edit_non_member_user_permissions( client_request, mocker, mock_get_users_by_service, mock_set_user_permissions, ): client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _data={ 'email_address': 'test@example.com', 'manage_service': 'y', }, _expected_status=404, ) assert mock_set_user_permissions.called is False @pytest.mark.parametrize('auth_type', ['email_auth', 'sms_auth']) def test_edit_user_permissions_including_authentication_with_email_auth_service( client_request, service_one, active_user_with_permissions, mock_get_users_by_service, mock_get_invites_for_service, mock_set_user_permissions, mock_update_user_attribute, auth_type, mock_get_template_folders ): service_one['permissions'].append('email_auth') client_request.post( 'main.edit_user_permissions', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={ 'email_address': active_user_with_permissions['email_address'], 'permissions_field': [ 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', ], 'login_authentication': auth_type, }, _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_set_user_permissions.assert_called_with( str(active_user_with_permissions['id']), SERVICE_ONE_ID, permissions={ 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', }, folder_permissions=[] ) mock_update_user_attribute.assert_called_with( str(active_user_with_permissions['id']), auth_type=auth_type ) def test_should_show_page_for_inviting_user( client_request, mock_get_template_folders, ): page = client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, ) assert 'Invite a team member' in page.find('h1').text.strip() assert not page.find('div', class_='checkboxes-nested') def test_should_show_page_for_inviting_user_with_email_prefilled( client_request, mocker, service_one, mock_get_template_folders, fake_uuid, active_user_with_permissions, active_user_with_permission_to_other_service, mock_get_organisation_by_domain, mock_get_invites_for_service, ): service_one['organisation'] = ORGANISATION_ID mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_user_with_permission_to_other_service, ]) page = client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, # We have the user’s name in the H1 but don’t want it duplicated # in the page title _test_page_title=False, ) assert normalize_spaces(page.select_one('title').text).startswith( 'Invite a team member' ) assert normalize_spaces(page.select_one('h1').text) == ( 'Invite Service Two User' ) assert normalize_spaces(page.select_one('main .govuk-body').text) == ( 'service-two-user@test.gov.uk' ) assert not page.select("input#email_address") or page.select("input[type=email]") def test_should_show_page_if_prefilled_user_is_already_a_team_member( mocker, client_request, mock_get_template_folders, fake_uuid, active_user_with_permissions, active_caseworking_user, ): mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_caseworking_user, ]) page = client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, ) assert normalize_spaces(page.select_one('title').text).startswith( 'This person is already a team member' ) assert normalize_spaces(page.select_one('h1').text) == ( 'This person is already a team member' ) assert normalize_spaces(page.select_one('main .govuk-body').text) == ( 'Test User is already member of ‘service one’.' ) assert not page.select("form") def test_should_show_page_if_prefilled_user_is_already_invited( mocker, client_request, mock_get_template_folders, fake_uuid, active_user_with_permissions, active_user_with_permission_to_other_service, mock_get_invites_for_service, ): active_user_with_permission_to_other_service['email_address'] = ( 'user_1@testnotify.gov.uk' ) mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_user_with_permission_to_other_service, ]) page = client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, ) assert normalize_spaces(page.select_one('title').text).startswith( 'This person has already received an invite' ) assert normalize_spaces(page.select_one('h1').text) == ( 'This person has already received an invite' ) assert normalize_spaces(page.select_one('main .govuk-body').text) == ( 'Service Two User has not accepted their invitation to ' '‘service one’ yet. You do not need to do anything.' ) assert not page.select("form") def test_should_403_if_trying_to_prefill_email_address_for_user_with_no_organisation( mocker, client_request, service_one, mock_get_template_folders, fake_uuid, active_user_with_permissions, active_user_with_permission_to_other_service, mock_get_invites_for_service, mock_get_no_organisation_by_domain, ): service_one['organisation'] = ORGANISATION_ID mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_user_with_permission_to_other_service, ]) client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _expected_status=403, ) def test_should_403_if_trying_to_prefill_email_address_for_user_from_other_organisation( mocker, client_request, service_one, mock_get_template_folders, fake_uuid, active_user_with_permissions, active_user_with_permission_to_other_service, mock_get_invites_for_service, mock_get_organisation_by_domain, ): service_one['organisation'] = ORGANISATION_TWO_ID mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_user_with_permission_to_other_service, ]) client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _expected_status=403, ) def test_should_show_folder_permission_form_if_service_has_folder_permissions_enabled( client_request, mocker, mock_get_template_folders, service_one ): mock_get_template_folders.return_value = [ {'id': 'folder-id-1', 'name': 'folder_one', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-2', 'name': 'folder_two', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-3', 'name': 'folder_three', 'parent_id': 'folder-id-1', 'users_with_permission': []}, ] page = client_request.get( 'main.invite_user', service_id=SERVICE_ONE_ID, ) assert 'Invite a team member' in page.find('h1').text.strip() folder_checkboxes = page.find('div', class_='selection-wrapper').find_all('li') assert len(folder_checkboxes) == 3 @pytest.mark.parametrize('email_address, gov_user', [ ('test@example.gov.uk', True), ('test@example.com', False) ]) def test_invite_user( client_request, active_user_with_permissions, mocker, sample_invite, email_address, gov_user, mock_get_template_folders, mock_get_organisations, ): sample_invite['email_address'] = 'test@example.gov.uk' assert is_gov_user(email_address) == gov_user mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) mocker.patch('app.invite_api_client.create_invite', return_value=sample_invite) page = client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, _data={ 'email_address': email_address, 'permissions_field': [ 'view_activity', 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', ] }, _follow_redirects=True, ) assert page.h1.string.strip() == 'Team members' flash_banner = page.find('div', class_='banner-default-with-tick').string.strip() assert flash_banner == 'Invite sent to test@example.gov.uk' expected_permissions = {'manage_api_keys', 'manage_service', 'manage_templates', 'send_messages', 'view_activity'} app.invite_api_client.create_invite.assert_called_once_with(sample_invite['from_user'], sample_invite['service'], email_address, expected_permissions, 'sms_auth', []) def test_invite_user_when_email_address_is_prefilled( client_request, service_one, active_user_with_permissions, active_user_with_permission_to_other_service, fake_uuid, mocker, sample_invite, mock_get_template_folders, mock_get_invites_for_service, mock_get_organisation_by_domain, ): service_one['organisation'] = ORGANISATION_ID mocker.patch('app.models.user.user_api_client.get_user', side_effect=[ # First call is to get the current user active_user_with_permissions, # Second call gets the user to invite active_user_with_permission_to_other_service, ]) mocker.patch('app.invite_api_client.create_invite', return_value=sample_invite) client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, user_id=fake_uuid, _data={ # No posted email address 'permissions_field': [ 'send_messages', ], }, ) app.invite_api_client.create_invite.assert_called_once_with( active_user_with_permissions['id'], SERVICE_ONE_ID, active_user_with_permission_to_other_service['email_address'], {'send_messages'}, 'sms_auth', [], ) @pytest.mark.parametrize('auth_type', [ ('sms_auth'), ('email_auth') ]) @pytest.mark.parametrize('email_address, gov_user', [ ('test@example.gov.uk', True), ('test@example.com', False) ]) def test_invite_user_with_email_auth_service( client_request, service_one, active_user_with_permissions, sample_invite, email_address, gov_user, mocker, auth_type, mock_get_organisations, mock_get_template_folders, ): service_one['permissions'].append('email_auth') sample_invite['email_address'] = 'test@example.gov.uk' assert is_gov_user(email_address) is gov_user mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) mocker.patch('app.invite_api_client.create_invite', return_value=sample_invite) page = client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, _data={ 'email_address': email_address, 'permissions_field': [ 'view_activity', 'send_messages', 'manage_templates', 'manage_service', 'manage_api_keys', ], 'login_authentication': auth_type, }, _follow_redirects=True, _expected_status=200, ) assert page.h1.string.strip() == 'Team members' flash_banner = page.find('div', class_='banner-default-with-tick').string.strip() assert flash_banner == 'Invite sent to test@example.gov.uk' expected_permissions = {'manage_api_keys', 'manage_service', 'manage_templates', 'send_messages', 'view_activity'} app.invite_api_client.create_invite.assert_called_once_with(sample_invite['from_user'], sample_invite['service'], email_address, expected_permissions, auth_type, []) @pytest.mark.parametrize('post_data, expected_permissions_to_api', ( ( { 'permissions_field': [ 'send_messages', 'manage_templates', 'manage_service', ] }, { 'view_activity', 'send_messages', 'manage_templates', 'manage_service', }, ), ( { 'permissions_field': [ 'view_activity', 'manage_api_keys', 'foo', ] }, { 'view_activity', }, ), )) def test_invite_user_to_broadcast_service( client_request, service_one, active_user_with_permissions, mocker, sample_invite, mock_get_template_folders, mock_get_organisations, post_data, expected_permissions_to_api, ): service_one['permissions'] = ['broadcast'] mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) mocker.patch('app.invite_api_client.create_invite', return_value=sample_invite) post_data['email_address'] = 'broadcast@example.gov.uk' client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, _data=post_data, ) app.invite_api_client.create_invite.assert_called_once_with( sample_invite['from_user'], sample_invite['service'], 'broadcast@example.gov.uk', expected_permissions_to_api, 'sms_auth', [], ) def test_invite_non_govt_user_to_broadcast_service_fails_validation( client_request, service_one, active_user_with_permissions, mocker, sample_invite, mock_get_template_folders, mock_get_organisations, ): service_one['permissions'] = ['broadcast'] mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) mocker.patch('app.invite_api_client.create_invite', return_value=sample_invite) post_data = { 'permissions_field': [ 'send_messages', 'manage_templates', 'manage_service', ], 'email_address': 'random@example.com' } page = client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, _data=post_data, _expected_status=200 ) assert app.invite_api_client.create_invite.called is False assert "Enter a public sector email address" in page.find_all('span', class_='govuk-error-message')[0].text def test_cancel_invited_user_cancels_user_invitations( client_request, mock_get_invites_for_service, sample_invite, active_user_with_permissions, mock_get_users_by_service, mock_get_template_folders, mocker, ): mock_cancel = mocker.patch('app.invite_api_client.cancel_invited_user') mocker.patch('app.invite_api_client.get_invited_user', return_value=sample_invite) page = client_request.get( 'main.cancel_invited_user', service_id=SERVICE_ONE_ID, invited_user_id=sample_invite['id'], _follow_redirects=True, ) assert normalize_spaces(page.h1.text) == 'Team members' flash_banner = normalize_spaces( page.find('div', class_='banner-default-with-tick').text ) assert flash_banner == f"Invitation cancelled for {sample_invite['email_address']}" mock_cancel.assert_called_once_with( service_id=SERVICE_ONE_ID, invited_user_id=sample_invite['id'], ) def test_cancel_invited_user_doesnt_work_if_user_not_invited_to_this_service( client_request, mock_get_invites_for_service, mocker, ): mock_cancel = mocker.patch('app.invite_api_client.cancel_invited_user') client_request.get( 'main.cancel_invited_user', service_id=SERVICE_ONE_ID, invited_user_id=sample_uuid(), _expected_status=404, ) assert mock_cancel.called is False @pytest.mark.parametrize('invite_status, expected_text', [ ('pending', ( 'invited_user@test.gov.uk (invited) ' 'Can See dashboard ' 'Can Send messages ' 'Cannot Add and edit templates ' 'Can Manage settings, team and usage ' 'Can Manage API integration ' 'Cancel invitation for invited_user@test.gov.uk' )), ('cancelled', ( 'invited_user@test.gov.uk (cancelled invite) ' # all permissions are greyed out 'Cannot See dashboard ' 'Cannot Send messages ' 'Cannot Add and edit templates ' 'Cannot Manage settings, team and usage ' 'Cannot Manage API integration' )), ]) def test_manage_users_shows_invited_user( client_request, mocker, active_user_with_permissions, mock_get_template_folders, sample_invite, invite_status, expected_text, ): sample_invite['status'] = invite_status mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) page = client_request.get('main.manage_users', service_id=SERVICE_ONE_ID) assert page.h1.string.strip() == 'Team members' assert normalize_spaces(page.select('.user-list-item')[0].text) == expected_text def test_manage_users_does_not_show_accepted_invite( client_request, mocker, active_user_with_permissions, sample_invite, mock_get_template_folders, ): invited_user_id = uuid.uuid4() sample_invite['id'] = invited_user_id sample_invite['status'] = 'accepted' mocker.patch('app.models.user.InvitedUsers.client_method', return_value=[sample_invite]) mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) page = client_request.get('main.manage_users', service_id=SERVICE_ONE_ID) assert page.h1.string.strip() == 'Team members' user_lists = page.find_all('div', {'class': 'user-list'}) assert len(user_lists) == 1 assert not page.find(text='invited_user@test.gov.uk') def test_user_cant_invite_themselves( client_request, mocker, active_user_with_permissions, mock_create_invite, mock_get_template_folders, ): page = client_request.post( 'main.invite_user', service_id=SERVICE_ONE_ID, _data={ 'email_address': active_user_with_permissions['email_address'], 'permissions_field': [ 'send_messages', 'manage_service', 'manage_api_keys' ] }, _follow_redirects=True, _expected_status=200, ) assert page.h1.string.strip() == 'Invite a team member' form_error = page.find('span', class_='govuk-error-message').text.strip() assert form_error == "Error: You cannot send an invitation to yourself" assert not mock_create_invite.called def test_no_permission_manage_users_page( client_request, service_one, mock_get_users_by_service, mock_get_invites_for_service, mock_get_template_folders, api_user_active, mocker, ): resp_text = client_request.get('main.manage_users', service_id=service_one['id']) assert url_for('.invite_user', service_id=service_one['id']) not in resp_text assert "Edit permission" not in resp_text assert "Team members" not in resp_text @pytest.mark.parametrize('folders_user_can_see, expected_message', [ (3, 'Can see all folders'), (2, 'Can see 2 folders'), (1, 'Can see 1 folder'), (0, 'Cannot see any folders'), ]) def test_manage_user_page_shows_how_many_folders_user_can_view( client_request, service_one, mock_get_template_folders, mock_get_users_by_service, mock_get_invites_for_service, api_user_active, folders_user_can_see, expected_message ): service_one['permissions'] = ['edit_folder_permissions'] mock_get_template_folders.return_value = [ {'id': 'folder-id-1', 'name': 'f1', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-2', 'name': 'f2', 'parent_id': None, 'users_with_permission': []}, {'id': 'folder-id-3', 'name': 'f3', 'parent_id': None, 'users_with_permission': []}, ] for i in range(folders_user_can_see): mock_get_template_folders.return_value[i]['users_with_permission'].append(api_user_active['id']) page = client_request.get('main.manage_users', service_id=service_one['id']) user_div = page.select_one("h2[title='notify@digital.cabinet-office.gov.uk']").parent assert user_div.select_one('.tick-cross-list-hint:last-child').text.strip() == expected_message def test_manage_user_page_doesnt_show_folder_hint_if_service_has_no_folders( client_request, service_one, mock_get_template_folders, mock_get_users_by_service, mock_get_invites_for_service, api_user_active, ): service_one['permissions'] = ['edit_folder_permissions'] mock_get_template_folders.return_value = [] page = client_request.get('main.manage_users', service_id=service_one['id']) user_div = page.select_one("h2[title='notify@digital.cabinet-office.gov.uk']").parent assert user_div.find('.tick-cross-list-hint:last-child') is None def test_manage_user_page_doesnt_show_folder_hint_if_service_cant_edit_folder_permissions( client_request, service_one, mock_get_template_folders, mock_get_users_by_service, mock_get_invites_for_service, api_user_active ): service_one['permissions'] = [] mock_get_template_folders.return_value = [ {'id': 'folder-id-1', 'name': 'f1', 'parent_id': None, 'users_with_permission': [api_user_active['id']]}, ] page = client_request.get('main.manage_users', service_id=service_one['id']) user_div = page.select_one("h2[title='notify@digital.cabinet-office.gov.uk']").parent assert user_div.find('.tick-cross-list-hint:last-child') is None def test_remove_user_from_service( client_request, active_user_with_permissions, api_user_active, service_one, mock_remove_user_from_service, mocker ): mock_event_handler = mocker.patch('app.main.views.manage_users.create_remove_user_from_service_event') client_request.post( 'main.remove_user_from_service', service_id=service_one['id'], user_id=active_user_with_permissions['id'], _expected_redirect=url_for('main.manage_users', service_id=service_one['id'], _external=True) ) mock_remove_user_from_service.assert_called_once_with( service_one['id'], str(active_user_with_permissions['id']) ) mock_event_handler.assert_called_once_with( user_id=active_user_with_permissions['id'], removed_by_id=api_user_active['id'], service_id=service_one['id'], ) def test_can_invite_user_as_platform_admin( client_request, service_one, platform_admin_user, active_user_with_permissions, mock_get_invites_for_service, mock_get_template_folders, mocker, ): mocker.patch('app.models.user.Users.client_method', return_value=[active_user_with_permissions]) page = client_request.get( 'main.manage_users', service_id=SERVICE_ONE_ID, ) assert url_for('.invite_user', service_id=service_one['id']) in str(page) def test_edit_user_email_page( client_request, active_user_with_permissions, service_one, mock_get_users_by_service, mocker ): user = active_user_with_permissions mocker.patch('app.user_api_client.get_user', return_value=user) page = client_request.get( 'main.edit_user_email', service_id=service_one['id'], user_id=sample_uuid() ) assert page.find('h1').text == "Change team member’s email address" assert page.select('p[id=user_name]')[0].text == "This will change the email address for {}.".format(user['name']) assert page.select('input[type=email]')[0].attrs["value"] == user['email_address'] assert normalize_spaces(page.select('main button[type=submit]')[0].text) == "Save" def test_edit_user_email_page_404_for_non_team_member( client_request, mock_get_users_by_service, ): client_request.get( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _expected_status=404, ) def test_edit_user_email_redirects_to_confirmation( client_request, active_user_with_permissions, mock_get_users_by_service, mock_get_user_by_email_not_found, ): client_request.post( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _expected_status=302, _expected_redirect=url_for( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _external=True, ), ) with client_request.session_transaction() as session: assert session[ 'team_member_email_change-{}'.format(active_user_with_permissions['id']) ] == 'test@user.gov.uk' def test_edit_user_email_without_changing_goes_back_to_team_members( client_request, active_user_with_permissions, mock_get_user_by_email, mock_get_users_by_service, mock_update_user_attribute, ): client_request.post( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={ 'email_address': active_user_with_permissions['email_address'] }, _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True ), ) assert mock_update_user_attribute.called is False @pytest.mark.parametrize('original_email_address', ['test@gov.uk', 'test@example.com']) def test_edit_user_email_can_change_any_email_address_to_a_gov_email_address( client_request, active_user_with_permissions, mock_get_user_by_email_not_found, mock_get_users_by_service, mock_update_user_attribute, mock_get_organisations, original_email_address, ): active_user_with_permissions['email_address'] = original_email_address client_request.post( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={ 'email_address': 'new-email-address@gov.uk' }, _expected_status=302, _expected_redirect=url_for( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _external=True ), ) def test_edit_user_email_can_change_a_non_gov_email_address_to_another_non_gov_email_address( client_request, active_user_with_permissions, mock_get_user_by_email_not_found, mock_get_users_by_service, mock_update_user_attribute, mock_get_organisations, ): active_user_with_permissions['email_address'] = 'old@example.com' client_request.post( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={ 'email_address': 'new@example.com' }, _expected_status=302, _expected_redirect=url_for( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _external=True ), ) def test_edit_user_email_cannot_change_a_gov_email_address_to_a_non_gov_email_address( client_request, active_user_with_permissions, mock_get_user_by_email_not_found, mock_get_users_by_service, mock_update_user_attribute, mock_get_organisations, ): page = client_request.post( 'main.edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={ 'email_address': 'new_email@example.com' }, _expected_status=200, ) assert 'Enter a public sector email address' in page.select_one('.govuk-error-message').text with client_request.session_transaction() as session: assert 'team_member_email_change-'.format(active_user_with_permissions['id']) not in session def test_confirm_edit_user_email_page( client_request, active_user_with_permissions, mock_get_users_by_service, mock_get_user, ): new_email = 'new_email@gov.uk' with client_request.session_transaction() as session: session[ 'team_member_email_change-{}'.format(active_user_with_permissions['id']) ] = new_email page = client_request.get( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], ) assert 'Confirm change of email address' in page.text for text in [ 'New email address:', new_email, 'We will send {} an email to tell them about the change.'.format(active_user_with_permissions['name']) ]: assert text in page.text assert 'Confirm' in page.text def test_confirm_edit_user_email_page_redirects_if_session_empty( client_request, mock_get_users_by_service, active_user_with_permissions, ): page = client_request.get( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _follow_redirects=True, ) assert 'Confirm change of email address' not in page.text def test_confirm_edit_user_email_page_404s_for_non_team_member( client_request, mock_get_users_by_service, ): client_request.get( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _expected_status=404, ) def test_confirm_edit_user_email_changes_user_email( client_request, active_user_with_permissions, api_user_active, service_one, mocker, mock_update_user_attribute, ): # We want active_user_with_permissions (the current user) to update the email address for api_user_active # By default both users would have the same id, so we change the id of api_user_active api_user_active['id'] = str(uuid.uuid4()) mocker.patch('app.models.user.Users.client_method', return_value=[api_user_active, active_user_with_permissions]) # get_user gets called twice - first to check if current user can see the page, then to see if the team member # whose email address we're changing belongs to the service mocker.patch('app.user_api_client.get_user', side_effect=[active_user_with_permissions, api_user_active]) mock_event_handler = mocker.patch('app.main.views.manage_users.create_email_change_event') new_email = 'new_email@gov.uk' with client_request.session_transaction() as session: session[ 'team_member_email_change-{}'.format(api_user_active['id']) ] = new_email client_request.post( 'main.confirm_edit_user_email', service_id=service_one['id'], user_id=api_user_active['id'], _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_update_user_attribute.assert_called_once_with( api_user_active['id'], email_address=new_email, updated_by=active_user_with_permissions['id'] ) mock_event_handler.assert_called_once_with( api_user_active['id'], active_user_with_permissions['id'], api_user_active['email_address'], new_email) def test_confirm_edit_user_email_doesnt_change_user_email_for_non_team_member( client_request, mock_get_users_by_service, ): with client_request.session_transaction() as session: session['team_member_email_change'] = 'new_email@gov.uk' client_request.post( 'main.confirm_edit_user_email', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _expected_status=404, ) def test_edit_user_permissions_page_displays_redacted_mobile_number_and_change_link( client_request, active_user_with_permissions, mock_get_users_by_service, mock_get_template_folders, service_one, mocker ): page = client_request.get( 'main.edit_user_permissions', service_id=service_one['id'], user_id=active_user_with_permissions['id'], ) assert active_user_with_permissions['name'] in page.find('h1').text mobile_number_paragraph = page.select('p[id=user_mobile_number]')[0] assert '0770 • • • • 762' in mobile_number_paragraph.text change_link = mobile_number_paragraph.findChild() assert change_link.attrs['href'] == '/services/{}/users/{}/edit-mobile-number'.format( service_one['id'], active_user_with_permissions['id'] ) def test_edit_user_permissions_with_delete_query_shows_banner( client_request, active_user_with_permissions, mock_get_users_by_service, mock_get_template_folders, service_one ): page = client_request.get( 'main.edit_user_permissions', service_id=service_one['id'], user_id=active_user_with_permissions['id'], delete=1 ) banner = page.find('div', class_='banner-dangerous') assert banner.contents[0].strip() == "Are you sure you want to remove Test User?" assert banner.form.attrs['action'] == url_for( 'main.remove_user_from_service', service_id=service_one['id'], user_id=active_user_with_permissions['id'] ) def test_edit_user_mobile_number_page( client_request, active_user_with_permissions, mock_get_users_by_service, service_one, mocker ): page = client_request.get( 'main.edit_user_mobile_number', service_id=service_one['id'], user_id=active_user_with_permissions['id'], ) assert page.find('h1').text == "Change team member’s mobile number" assert page.select('p[id=user_name]')[0].text == ( "This will change the mobile number for {}." ).format(active_user_with_permissions['name']) assert page.select('input[name=mobile_number]')[0].attrs["value"] == "0770••••762" assert normalize_spaces(page.select('main button[type=submit]')[0].text) == "Save" def test_edit_user_mobile_number_redirects_to_confirmation( client_request, active_user_with_permissions, mock_get_users_by_service, ): client_request.post( 'main.edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={'mobile_number': '07554080636'}, _expected_status=302, _expected_redirect=url_for( 'main.confirm_edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _external=True, ), ) def test_edit_user_mobile_number_redirects_to_manage_users_if_number_not_changed( client_request, active_user_with_permissions, mock_get_users_by_service, service_one, mocker, mock_get_user, ): client_request.post( 'main.edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _data={'mobile_number': '0770••••762'}, _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) def test_confirm_edit_user_mobile_number_page( client_request, active_user_with_permissions, mock_get_users_by_service, service_one, mocker, mock_get_user, ): new_number = '07554080636' with client_request.session_transaction() as session: session['team_member_mobile_change'] = new_number page = client_request.get( 'main.confirm_edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], ) assert 'Confirm change of mobile number' in page.text for text in [ 'New mobile number:', new_number, 'We will send {} a text message to tell them about the change.'.format(active_user_with_permissions['name']) ]: assert text in page.text assert 'Confirm' in page.text def test_confirm_edit_user_mobile_number_page_redirects_if_session_empty( client_request, active_user_with_permissions, mock_get_users_by_service, service_one, mocker, mock_get_user, ): page = client_request.get( 'main.confirm_edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=active_user_with_permissions['id'], _expected_status=302, ) assert 'Confirm change of mobile number' not in page.text def test_confirm_edit_user_mobile_number_changes_user_mobile_number( client_request, active_user_with_permissions, api_user_active, service_one, mocker, mock_update_user_attribute ): # We want active_user_with_permissions (the current user) to update the mobile number for api_user_active # By default both users would have the same id, so we change the id of api_user_active api_user_active['id'] = str(uuid.uuid4()) mocker.patch('app.models.user.Users.client_method', return_value=[api_user_active, active_user_with_permissions]) # get_user gets called twice - first to check if current user can see the page, then to see if the team member # whose mobile number we're changing belongs to the service mocker.patch('app.user_api_client.get_user', side_effect=[active_user_with_permissions, api_user_active]) mock_event_handler = mocker.patch('app.main.views.manage_users.create_mobile_number_change_event') new_number = '07554080636' with client_request.session_transaction() as session: session['team_member_mobile_change'] = new_number client_request.post( 'main.confirm_edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=api_user_active['id'], _expected_status=302, _expected_redirect=url_for( 'main.manage_users', service_id=SERVICE_ONE_ID, _external=True, ), ) mock_update_user_attribute.assert_called_once_with( api_user_active['id'], mobile_number=new_number, updated_by=active_user_with_permissions['id'] ) mock_event_handler.assert_called_once_with( api_user_active['id'], active_user_with_permissions['id'], api_user_active['mobile_number'], new_number) def test_confirm_edit_user_mobile_number_doesnt_change_user_mobile_for_non_team_member( client_request, mock_get_users_by_service, ): with client_request.session_transaction() as session: session['team_member_mobile_change'] = '07554080636' client_request.post( 'main.confirm_edit_user_mobile_number', service_id=SERVICE_ONE_ID, user_id=USER_ONE_ID, _expected_status=404, )

31.569914

118

0.664087

7,558

62,540

5.062186

0.049087

0.039205

0.042446

0.067956

0.834919

0.79702

0.754077

0.727522

0.695635

0.679378

0

0.005439

0.238583

62,540

1,980

119

31.585859

0.79777

0.02141

0

0.698692

0

0.229274

0.074227

0

0.065947

1

0.035247

false

0

0.00398

0

0.039227

0

null

0

1

0

1

0

null

0

5

f7b05c7bee5cdb3fa8f3a2f223d568af147986ed

351

py

Python

smlb/feature_selection/__init__.py

CitrineInformatics/smlb

28a3689bd36aa8d51031b4faf7e2331bbd8148a9

[ "Apache-2.0" ]

6

2020-07-27T21:08:55.000Z

2021-05-04T07:00:29.000Z

smlb/feature_selection/__init__.py

CitrineInformatics/smlb

28a3689bd36aa8d51031b4faf7e2331bbd8148a9

[ "Apache-2.0" ]

18

2020-09-01T00:47:04.000Z

2021-09-15T22:16:56.000Z

smlb/feature_selection/__init__.py

CitrineInformatics/smlb

28a3689bd36aa8d51031b4faf7e2331bbd8148a9

[ "Apache-2.0" ]

2

2020-08-24T21:50:16.000Z

2020-12-06T05:18:57.000Z

from .rfe_sklearn import RFESklearn from .rfecv_sklearn import RFECVSklearn from .select_from_model_sklearn import SelectFromModelSklearn from .select_from_total_importance import SelectFromTotalImportance from .select_percentile_sklearn import SelectPercentileSklearn from .sequential_feature_selector_sklearn import SequentialFeatureSelectorSklearn

50.142857

81

0.91453

37

351

8.324324

0.513514

0.211039

0.090909

0

0.068376

351

6

82

58.5

0.941896

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

5

f7b7eee72210b898a3e3df5387c34663388cca35

49

py

Python

Lessons/First lesson.py

cppshizoidS/Python

dfde647ba4a6fb828ef9a564924416bebd875929

[ "MIT" ]

5

2022-03-12T02:44:41.000Z

2022-03-24T10:33:28.000Z

Lessons/First lesson.py

cppshizoidS/Python

dfde647ba4a6fb828ef9a564924416bebd875929

[ "MIT" ]

1

2022-03-16T09:19:21.000Z

Lessons/First lesson.py

cppshizoidS/Python

dfde647ba4a6fb828ef9a564924416bebd875929

[ "MIT" ]

null

#my first program in Python print("Hello world")

16.333333

27

0.755102

8

49

4.625

1

0

0.142857

49

2

28

24.5

0.880952

0.530612

0

0.5

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

f7ca575df84cf1377556c34984951c78541b0b30

307

py

Python

mynamespace/mypackage/cmdline.py

dtolpin/python-project-skeleton

3cf8a7dcbf57c38751165ef99080669237a32e0d

[ "Unlicense" ]

null

mynamespace/mypackage/cmdline.py

dtolpin/python-project-skeleton

3cf8a7dcbf57c38751165ef99080669237a32e0d

[ "Unlicense" ]

null

mynamespace/mypackage/cmdline.py

dtolpin/python-project-skeleton

3cf8a7dcbf57c38751165ef99080669237a32e0d

[ "Unlicense" ]

null

"""Command line entry points. """ import argparse from . import __version__ def hello(): """ Hello world sample entry point. """ print("hello world version {}".format(__version__)) def gdbye(): """ Goodbye sample entry point. """ print("Goodbye version {}".format(__version__))

17.055556

55

0.641694

33

307

5.606061

0.515152

0.108108

0.172973

0.227027

0

0.208469

307

17

56

18.058824

0.761317

0.312704

0

0.208333

0

1

0.333333

true

0

0.333333

0

0.666667

0.333333

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f7dccc65795482c0598c45968bb3ff9b8f00b2f8

126

py

Python

src/CharmsTab/__init__.py

AndrewGrim/MonsterHunterWorldDatabase

a904647f5499926e46a64d884a2ffebe38dd5407

[ "MIT" ]

1

2020-02-17T00:16:01.000Z

src/CharmsTab/__init__.py

AndrewGrim/MonsterHunterWorldDatabase

a904647f5499926e46a64d884a2ffebe38dd5407

[ "MIT" ]

null

src/CharmsTab/__init__.py

AndrewGrim/MonsterHunterWorldDatabase

a904647f5499926e46a64d884a2ffebe38dd5407

[ "MIT" ]

1

2020-06-26T06:54:00.000Z

from .CharmsTab import * from .Charm import * from .CharmMaterial import * from .CharmSkill import * from .CharmUsage import *

25.2

28

0.769841

15

126

6.466667

0.466667

0.412371

0

0.150794

126

5

29

25.2

0.906542

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

79193c2031eaa86686fb3e4b57f4430d71a11959

207

py

Python

Lib/site-packages/win32comext/propsys/test/testpropsys.py

egorcompany/telegram-chat-members

19a7c2bffe2fb832b79a4475ca324c438d5f548d

[ "MIT" ]

3

2016-11-24T03:57:22.000Z

2019-02-27T15:19:50.000Z

Lib/site-packages/win32comext/propsys/test/testpropsys.py

egorcompany/telegram-chat-members

19a7c2bffe2fb832b79a4475ca324c438d5f548d

[ "MIT" ]

67

2016-10-19T01:23:47.000Z

2016-12-14T04:30:38.000Z

Lib/site-packages/win32comext/propsys/test/testpropsys.py

egorcompany/telegram-chat-members

19a7c2bffe2fb832b79a4475ca324c438d5f548d

[ "MIT" ]

1

2019-04-07T08:33:09.000Z

from win32com.propsys import propsys, pscon print("propsys was imported (sorry - that is the extent of the tests,") print("but see the shell folder_view demo, which uses this module)") # that's all folks!

51.75

72

0.753623

34

207

4.558824

0.823529

0

0.011494

0.15942

207

4

73

51.75

0.87931

0.082126

0

0.650538

0

1

0

true

0

0.666667

0

0.666667

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

792d4259773dfd09800dc1959ccf57d1f411f450

21,164

py

Python

Configuration/StandardSequences/python/Mixing.py

Purva-Chaudhari/cmssw

32e5cbfe54c4d809d60022586cf200b7c3020bcf

[ "Apache-2.0" ]

13

2015-11-30T15:49:45.000Z

2022-02-08T16:11:30.000Z

Configuration/StandardSequences/python/Mixing.py

Purva-Chaudhari/cmssw

32e5cbfe54c4d809d60022586cf200b7c3020bcf

[ "Apache-2.0" ]

640

2015-02-11T18:55:47.000Z

2022-03-31T14:12:23.000Z

Configuration/StandardSequences/python/Mixing.py

Purva-Chaudhari/cmssw

32e5cbfe54c4d809d60022586cf200b7c3020bcf

[ "Apache-2.0" ]

51

2015-08-11T21:01:40.000Z

2022-03-30T07:31:34.000Z

from __future__ import print_function Mixing = {} def addMixingScenario(label,dict): global Mixing if label in Mixing: print('duplicated definition of',label) else: #try: # m=__import__(dict['file']) #except: # raise Exception('no file'+dict['file']+'to be loaded') Mixing[label]=dict ##full sim section addMixingScenario("156BxLumiPileUp",{'file': 'SimGeneral.MixingModule.StageA156Bx_cfi'}) addMixingScenario("E10TeV_FIX_1_BX432",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 50, 'B': (-5,3), 'N': 1}) addMixingScenario("E10TeV_FIX_2_BX432",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 50, 'B': (-5,3), 'N': 2}) addMixingScenario("E10TeV_FIX_3_BX432",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 50, 'B': (-5,3), 'N': 3}) addMixingScenario("E10TeV_FIX_5_BX432",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 50, 'B': (-5,3), 'N': 5}) addMixingScenario("E10TeV_L13E31_BX432",{'file': 'SimGeneral.MixingModule.mix_E10TeV_L13E31_BX432_cfi'}) addMixingScenario("E10TeV_L21E31_BX432",{'file': 'SimGeneral.MixingModule.mix_E10TeV_L21E31_BX432_cfi'}) addMixingScenario("E14TeV_L10E33_BX2808",{'file': 'SimGeneral.MixingModule.mix_E14TeV_L10E33_BX2808_cfi'}) addMixingScenario("E14TeV_L28E32_BX2808",{'file': 'SimGeneral.MixingModule.mix_E14TeV_L28E32_BX2808_cfi'}) addMixingScenario("E7TeV_AVE_01_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 0.1}) addMixingScenario("E7TeV_AVE_02_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 0.2}) addMixingScenario("E7TeV_AVE_05_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 0.5}) addMixingScenario("E7TeV_AVE_1_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 1.}) addMixingScenario("E7TeV_AVE_2_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 2.}) addMixingScenario("E7TeV_AVE_5_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 5.}) addMixingScenario("E7TeV_AVE_10_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 10.}) addMixingScenario("E7TeV_AVE_20_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 20.}) addMixingScenario("E7TeV_AVE_50_BX2808",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 25, 'B': (-5,3), 'N': 50.}) addMixingScenario("E7TeV_AVE_1_BX156",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 1.}) addMixingScenario("E7TeV_AVE_2_BX156",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 2.}) addMixingScenario("E7TeV_AVE_3_BX156",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 3.}) addMixingScenario("E7TeV_AVE_5_BX156",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 5.}) addMixingScenario("E7TeV_AVE_2_8_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 50, 'B': (-3,2), 'N': 2.8}) addMixingScenario("E7TeV_AVE_2_8_BXgt50ns_intime_only",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi', 'BX': 450, 'B': (0,0), 'N': 2.8}) addMixingScenario("E7TeV_FIX_1_BX156",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 1}) addMixingScenario("E7TeV_FIX_2_BX156",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 2}) addMixingScenario("E7TeV_FIX_3_BX156",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 3}) addMixingScenario("E7TeV_FIX_5_BX156",{'file': 'SimGeneral.MixingModule.mix_FIX_average_cfi', 'BX': 450, 'B': (-5,3), 'N': 5}) addMixingScenario("E7TeV_L34E30_BX156",{'file': 'SimGeneral.MixingModule.mix_E7TeV_L34E30_BX156_cfi'}) addMixingScenario("E7TeV_L69E30_BX156",{'file': 'SimGeneral.MixingModule.mix_E7TeV_L69E30_BX156_cfi'}) addMixingScenario("E8TeV_AVE_4_BX_50ns",{'file':'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50,'B': (-3,2),'N': 4}) addMixingScenario("E8TeV_AVE_10_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,2), 'N': 10}) addMixingScenario("E8TeV_AVE_10_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,2), 'N': 10}) addMixingScenario("E8TeV_AVE_16_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,2), 'N': 16}) addMixingScenario("E8TeV_AVE_16_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,2), 'N': 16}) addMixingScenario("E8TeV_AVE_10_BX_50ns_300ns_spread",{'file':'SimGeneral.MixingModule.mix_E8TeV_AVE_10_BX_50ns_300ns_spread_cfi'}) addMixingScenario("E8TeV_AVE_10_BX_25ns_300ns_spread",{'file':'SimGeneral.MixingModule.mix_E8TeV_AVE_10_BX_25ns_300ns_spread_cfi'}) addMixingScenario("HiMix",{'file': 'SimGeneral.MixingModule.HiMix_cff'}) addMixingScenario("HiMixGEN",{'file': 'SimGeneral.MixingModule.HiMixGEN_cff'}) addMixingScenario("HiMixEmbGEN",{'file': 'SimGeneral.MixingModule.HiMixEmbGEN_cff'}) addMixingScenario("HiMixNoPU",{'file': 'SimGeneral.MixingModule.HiMixNoPU_cff'}) addMixingScenario("HighLumiPileUp",{'file': 'SimGeneral.MixingModule.mixHighLumPU_cfi'}) addMixingScenario("InitialLumiPileUp",{'file': 'SimGeneral.MixingModule.mixInitialLumPU_cfi'}) addMixingScenario("LowLumiPileUp",{'file': 'SimGeneral.MixingModule.mixLowLumPU_cfi'}) addMixingScenario("LowLumiPileUp4Sources",{'file': 'SimGeneral.MixingModule.mixLowLumPU_4sources_cfi'}) addMixingScenario("LowLumiPileUp4Sources_ProdStep1",{'file': 'SimGeneral.MixingModule.mixLowLumPU_4sources_mixProdStep1_cfi'}) addMixingScenario("LowLumiPileUp_ProdStep1",{'file': 'SimGeneral.MixingModule.mixLowLumPU_mixProdStep1_cfi'}) addMixingScenario("NoPileUp",{'file': 'SimGeneral.MixingModule.mixNoPU_cfi'}) addMixingScenario("Cosmics",{'file': 'SimGeneral.MixingModule.mixCosmics_cfi'}) addMixingScenario("E7TeV_ProbDist_2010Data_BX156",{'file': 'SimGeneral.MixingModule.mix_E7TeV_ProbDist_2010Data_BX156_cfi'}) addMixingScenario("E8TeV_ProbDist_2011EarlyData_50ns",{'file': 'SimGeneral.MixingModule.mix_E8TeV_ProbDist_2011EarlyData_50ns_cfi'}) addMixingScenario("E8TeV_FlatDist_2011EarlyData_50ns",{'file': 'SimGeneral.MixingModule.mix_E8TeV_FlatDist_2011EarlyData_50ns_cfi'}) addMixingScenario("E7TeV_FlatDist10_2011EarlyData_50ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_FlatDist10_2011EarlyData_50ns_cfi'}) addMixingScenario("E7TeV_FlatDist10_2011EarlyData_75ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_FlatDist10_2011EarlyData_75ns_cfi'}) addMixingScenario("E7TeV_FlatDist10_2011EarlyData_inTimeOnly",{'file': 'SimGeneral.MixingModule.mix_E7TeV_FlatDist10_2011EarlyData_inTimeOnly_cfi'}) addMixingScenario("E7TeV_Flat20_AllEarly_75ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Flat20_AllEarly_75ns_cfi'}) addMixingScenario("E7TeV_Flat20_AllLate_75ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Flat20_AllLate_75ns_cfi'}) addMixingScenario("E7TeV_Flat20_AllEarly_50ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Flat20_AllEarly_50ns_cfi'}) addMixingScenario("E7TeV_Flat20_AllLate_50ns",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Flat20_AllLate_50ns_cfi'}) addMixingScenario("E7TeV_FlatDist10_2011EarlyData_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_FlatDist10_2011EarlyData_50ns_PoissonOOT'}) addMixingScenario("E7TeV_FlatDist10_2011EarlyData_25ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_FlatDist10_2011EarlyData_25ns_PoissonOOT_cfi'}) addMixingScenario("E7TeV_Ave18p4_50ns", {'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,2), 'N': 18.4}) addMixingScenario("E7TeV_Ave23_50ns", {'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,2), 'N': 23}) addMixingScenario("E7TeV_Ave32_50ns", {'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,2), 'N': 32}) addMixingScenario("E7TeV_Ave25_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Ave25_50ns_PoissonOOTPU_cfi'}) addMixingScenario("E7TeV_Ave25_25ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Ave25_25ns_PoissonOOTPU_cfi'}) addMixingScenario("E7TeV_Fall2011ReDigi_prelim_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Fall2011ReDigi_prelim_50ns_PoissonOOT_cfi'}) addMixingScenario("E7TeV_Fall2011ReDigi_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Fall2011ReDigi_50ns_PoissonOOT_cfi'}) addMixingScenario("E7TeV_Fall2011ReDigi_25ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Fall2011ReDigi_25ns_PoissonOOT_cfi'}) addMixingScenario("E7TeV_Fall2011_Reprocess_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Fall2011_Reprocess_50ns_PoissonOOTPU_cfi'}) addMixingScenario("E7TeV_Chamonix2012_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_E7TeV_Chamonix2012_50ns_PoissonOOT_cfi'}) addMixingScenario("2012_lumiLevel_15_20_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012_lumiLevel_15_20_50ns_PoissonOOTPU_cfi'}) addMixingScenario("2012_peak11_25ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012_peak11_25ns_PoissonOOTPU_cfi'}) addMixingScenario("2012_peak26_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012_peak26_50ns_PoissonOOTPU_cfi'}) addMixingScenario("2012_Startup_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012_Startup_50ns_PoissonOOTPU_cfi'}) addMixingScenario("2012_Summer_50ns_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012_Summer_50ns_PoissonOOTPU_cfi'}) addMixingScenario("2012A_Profile_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012A_Profile_PoissonOOTPU_cfi'}) addMixingScenario("2012B_Profile_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012B_Profile_PoissonOOTPU_cfi'}) addMixingScenario("2012C_Profile_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012C_Profile_PoissonOOTPU_cfi'}) addMixingScenario("2012D_Profile_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2012D_Profile_PoissonOOTPU_cfi'}) addMixingScenario("2011_FinalDist_OOTPU",{'file': 'SimGeneral.MixingModule.mix_2011_FinalDist_OOTPU_cfi'}) addMixingScenario("E8TeV_2012_25nsRunning_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_E8TeV_2012_25nsRunning_PoissonOOTPU_cfi'}) addMixingScenario("E8TeV_2012_25nsRunning_TrainBackOOTPU",{'file': 'SimGeneral.MixingModule.mix_E8TeV_2012_25nsRunning_TrainBackOOTPU_cfi'}) addMixingScenario("E8TeV_2012_25nsRunning_TrainFrontOOTPU",{'file': 'SimGeneral.MixingModule.mix_E8TeV_2012_25nsRunning_TrainFrontOOTPU_cfi'}) addMixingScenario("2012_Summer_50ns_PoissonOOTPU_FixedInTime0",{'file': 'SimGeneral.MixingModule.mix_2012_Summer_50ns_PoissonOOTPU_FixedInTime0_cfi'}) addMixingScenario("2012_Summer_50ns_PoissonOOTPU_FixedInTime30",{'file': 'SimGeneral.MixingModule.mix_2012_Summer_50ns_PoissonOOTPU_FixedInTime30_cfi'}) addMixingScenario("E8TeV_2012_run198588_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_E8TeV_run198588_BX_50ns_cfi'}) addMixingScenario("E8TeV_2012_run203002_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_E8TeV_run203002_BX_50ns_cfi'}) addMixingScenario("E8TeV_2012_run209148_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_E8TeV_run209148_BX_25ns_cfi'}) addMixingScenario("E8TeV_2012_ZmumugSkim",{'file': 'SimGeneral.MixingModule.mix_E8TeV_zmmg_skim_BX_50ns_cfi'}) addMixingScenario("CSA14_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_CSA14_50ns_PoissonOOTPU_cfi'}) addMixingScenario("CSA14_inTimeOnly",{'file': 'SimGeneral.MixingModule.mix_CSA14_inTimeOnly_cfi'}) addMixingScenario("Phys14_50ns_PoissonOOT",{'file': 'SimGeneral.MixingModule.mix_Phys14_50ns_PoissonOOTPU_cfi'}) addMixingScenario("2015_25ns_HiLum_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2015_25ns_HiLum_PoissonOOTPU_cfi'}) addMixingScenario("2015_25ns_Startup_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2015_25ns_Startup_PoissonOOTPU_cfi'}) addMixingScenario("2015_50ns_Startup_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2015_50ns_Startup_PoissonOOTPU_cfi'}) addMixingScenario("2015_25ns_FallMC_matchData_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2015_25ns_FallMC_matchData_PoissonOOTPU_cfi'}) addMixingScenario("2015_25nsLowPU_matchData_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2015_25nsLowPU_matchData_PoissonOOTPU_cfi'}) addMixingScenario("2016_25ns_SpringMC_PUScenarioV1_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2016_25ns_SpringMC_PUScenarioV1_PoissonOOTPU_cfi'}) addMixingScenario("2016_25ns_Moriond17MC_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2016_25ns_Moriond17MC_PoissonOOTPU_cfi'}) addMixingScenario("2016_25ns_UltraLegacy_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2016_25ns_UltraLegacy_PoissonOOTPU_cfi'}) addMixingScenario("mix_2016_PoissonOOTPU_HighPUTrains_Fill5412",{'file': 'SimGeneral.MixingModule.mix_2016_PoissonOOTPU_HighPUTrains_Fill5412_cfi'}) addMixingScenario("2017_25ns_WinterMC_PUScenarioV1_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2017_25ns_WinterMC_PUScenarioV1_PoissonOOTPU_cfi'}) addMixingScenario("2017_25ns_UltraLegacy_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2017_25ns_UltraLegacy_PoissonOOTPU_cfi'}) addMixingScenario("2018_25ns_ProjectedPileup_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2018_25ns_ProjectedPileup_PoissonOOTPU_cfi'}) addMixingScenario("2018_25ns_JuneProjectionFull18_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2018_25ns_JuneProjectionFull18_PoissonOOTPU_cfi'}) addMixingScenario("2018_25ns_UltraLegacy_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_2018_25ns_UltraLegacy_PoissonOOTPU_cfi'}) addMixingScenario("Run3_Flat55To75_PoissonOOTPU",{'file': 'SimGeneral.MixingModule.mix_Run3_Flat55To75_PoissonOOTPU_cfi'}) addMixingScenario("ProdStep2",{'file': 'SimGeneral.MixingModule.mixProdStep2_cfi'}) addMixingScenario("fromDB",{'file': 'SimGeneral.MixingModule.mix_fromDB_cfi'}) addMixingScenario("2022_LHC_Simulation_10h_2h",{'file': 'SimGeneral.MixingModule.Run3_2022_LHC_Simulation_10h_2h_cfi'}) #scenarios for L1 tdr work addMixingScenario("AVE_4_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 4}) addMixingScenario("AVE_10_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 10}) addMixingScenario("AVE_10_BX_25ns_m8",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-8,3), 'N': 10}) addMixingScenario("AVE_20_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 20}) addMixingScenario("AVE_20_BX_50ns_m8",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-8,3), 'N': 20}) addMixingScenario("AVE_20_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 20}) addMixingScenario("AVE_25_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 25}) addMixingScenario("AVE_25_BX_50ns_m8",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-8,3), 'N': 25}) addMixingScenario("AVE_25_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 25}) addMixingScenario("AVE_30_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 30}) addMixingScenario("AVE_30_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 30}) addMixingScenario("AVE_35_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 35}) addMixingScenario("AVE_35_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 35}) addMixingScenario("AVE_40_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 40}) addMixingScenario("AVE_40_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 40}) addMixingScenario("AVE_45_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 45}) addMixingScenario("AVE_50_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 50}) addMixingScenario("AVE_50_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 50}) addMixingScenario("AVE_50_BX_25ns_m3p3",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,3), 'N': 50}) addMixingScenario("AVE_70_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 70}) addMixingScenario("AVE_70_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 70}) addMixingScenario("AVE_75_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 75}) addMixingScenario("AVE_75_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 75}) addMixingScenario("AVE_80_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 80}) addMixingScenario("AVE_100_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 100}) addMixingScenario("AVE_100_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 100}) addMixingScenario("AVE_125_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 125}) addMixingScenario("AVE_125_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 125}) addMixingScenario("AVE_150_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 150}) addMixingScenario("AVE_150_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 150}) addMixingScenario("AVE_175_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-12,3), 'N': 175}) addMixingScenario("AVE_175_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 175}) addMixingScenario("AVE_200_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,3), 'N': 200}) addMixingScenario("AVE_200_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,3), 'N': 200}) addMixingScenario("AVE_200_BX_25ns_m12p3",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 200}) addMixingScenario("AVE_200_BX_25ns_m6p6",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-6,6), 'N': 200}) addMixingScenario("AVE_140_BX_50ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':50, 'B': (-3,3), 'N': 140}) addMixingScenario("AVE_140_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,3), 'N': 140}) addMixingScenario("AVE_250_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,3), 'N': 250}) addMixingScenario("AVE_300_BX_25ns",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-3,3), 'N': 300}) addMixingScenario("AVE_140_BX_25ns_m12p3",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-12,3), 'N': 140}) addMixingScenario("AVE_140_BX_25ns_m6p6",{'file': 'SimGeneral.MixingModule.mix_POISSON_average_cfi','BX':25, 'B': (-6,6), 'N': 140}) addMixingScenario("flatPU_0_10",{'file': 'SimGeneral.MixingModule.mix_flat_0_10_cfi'}) addMixingScenario("Flat_20_50",{'file': 'SimGeneral.MixingModule.mix_Flat_20_50_cfi'}) addMixingScenario("Flat_20_50_50ns",{'file': 'SimGeneral.MixingModule.mix_Flat_20_50_50ns_cfi'}) addMixingScenario("Flat_0_50_25ns",{'file': 'SimGeneral.MixingModule.mix_Flat_0_50_25ns_cfi'}) addMixingScenario("Flat_0_50_50ns",{'file': 'SimGeneral.MixingModule.mix_Flat_0_50_50ns_cfi'}) addMixingScenario("Flat_10_50_25ns",{'file': 'SimGeneral.MixingModule.mix_Flat_10_50_25ns_cfi'}) addMixingScenario("Flat_10_50_50ns",{'file': 'SimGeneral.MixingModule.mix_Flat_10_50_50ns_cfi'}) MixingDefaultKey = '2012_Summer_50ns_PoissonOOTPU' def printMe(): global Mixing keys = sorted(Mixing.keys()) fskeys=[] for key in keys: print('addMixingScenario("%s",%s)'%(key,repr(Mixing[key]))) def defineMixing(dict): commands=[] if 'N' in dict: commands.append('process.mix.input.nbPileupEvents.averageNumber = cms.double(%f)'%(dict['N'],)) dict.pop('N') if 'BX' in dict: commands.append('process.mix.bunchspace = cms.int32(%d)'%(dict['BX'],)) dict.pop('BX') if 'B' in dict: commands.append('process.mix.minBunch = cms.int32(%d)'%(dict['B'][0],)) commands.append('process.mix.maxBunch = cms.int32(%d)'%(dict['B'][1],)) dict.pop('B') if 'F' in dict: commands.append('process.mix.input.fileNames = cms.untracked.vstring(%s)'%(repr(dict['F']))) dict.pop('F') return commands

103.239024

158

0.782981

2,696

21,164

5.751113

0.086424

0.14447

0.268301

0.271203

0.763302

0.624315

0.544728

0.357562

0.310545

0.308417

0

0.091242

0.044557

21,164

204

159

103.745098

0.675535

0.006615

0

0.010471

0

0.62949

0.507208

0

1

0.015707

false

0

0.005236

0

0.026178

0.020942

0

null

0

1

0

1

0

1

null

0

5

f72a5cd00105d9d13c7915d5db1087ad43337300

237

py

Python

src/fecc_object/ConstantObject.py

castor91/fecc

bc46059c0d7a428d15b95050b70dec374b4bea28

[ "MIT" ]

1

2018-02-04T14:48:15.000Z

src/fecc_object/ConstantObject.py

castor91/fecc

bc46059c0d7a428d15b95050b70dec374b4bea28

[ "MIT" ]

null

src/fecc_object/ConstantObject.py

castor91/fecc

bc46059c0d7a428d15b95050b70dec374b4bea28

[ "MIT" ]

null

from AbstractObject import * class ConstantObject(AbstractObject): def __init__(self, value): super(ConstantObject, self).__init__(value._value) def generate(self, out_code): out_code.append(PUSH(self._value))

23.7

58

0.7173

27

237

5.851852

0.555556

0.113924

0

0.177215

237

9

59

26.333333

0.810256

0

1

0

1

0.333333

false

0

0.166667

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

e38d354d915b9da3aa39534a2d179a6ac697286a

279,648

py

Python

Android/parser/ui/images/images.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

1

2020-05-31T08:46:45.000Z

Android/parser/ui/images/images.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

Android/parser/ui/images/images.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

#---------------------------------------------------------------------- # This file was generated by /home/pt/work/Useful-Shell/Android/parser/ui/images/encode_bitmaps.py # from wx.lib.embeddedimage import PyEmbeddedImage action_clean_history = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABgAAAAYCAYAAADgdz34AAABqklEQVRIS7VVW06DQBSVxyeJ" "dQXiH30ktivQrkCWoCsorsC6AusO2hXIDsQdtEl5/Ik7wIRPGjyXMGR4tUJhEkImM/ece+5r" "hIuGazweTwVBeIHZNgzDd9/3g2MQQhP8FPwTNoPUztrv9/POCCaTyRJg5D1bXyC474xgNBqt" "RFFc9EYABRbA7ziCVyggVbWraQ62SPBtbwRQEBdcnUMBqWqnQNM0VZKkBbyepgi5hMZxTIoC" "/H38N1VktSGqKMmTFQ2iJ9u21/zFSgJVVQeKonxz9X4SnF0AyQwkW7avJID3JiQ//BuVu0hh" "A8GslmA4HOqI+0cbcE7FM0hWtC8poMTKskwSL1uS/MJOZwlv1AdtCEsEqHUqRb5bG+MeDoed" "67pmZYiQ4GK3NiaAQTYEcwrS+FN5nrsC5OCqpADeGyjPt3PRyT6KohvP8/ycgo7Cw/xL5lRG" "0GF4GEEyyjOCLsNDDOjoDZrtkSdIqgcHPzi38NG7Sw/89ZGcUFNRU1qwo4nL308qiSdYA2xd" "HLnpVNVhnPQHgHb4LDydZtV4plDjzCCnHMcxeu/kP+6lrRl+VptjAAAAAElFTkSuQmCC") #---------------------------------------------------------------------- action_new = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABgAAAAYCAYAAADgdz34AAAAg0lEQVRIS+2UsQ2AMAwE/YyR" "SaAiWzAOYRyYAjomYY1HsdJGtiio7Dbnt3SyA3FW2sciwKo4uT3LXTyt8ECViQGmqVAUiroG" "oNsxCC1HpGQIsh6y8ATktHrqO9IxmeGeoB7zw4CqyFGEKpqbogt0KnJkKxKXbJoKRaGo/9mZ" "bhrwdYteLuygCEW2M9oAAAAASUVORK5CYII=") #---------------------------------------------------------------------- app_splash = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAAZAAAAD6CAYAAACPpxFEAALYtklEQVR42oy9V3tb17X97Q/z" "P+fEsa0uFrE3ECBIAiTYexVVLffe7dhyU2HvBSRIgp0EQJDqvVm2LBe5JO4tjktckue9nO8c" "c+21sUHJOediPGvtDVJObvDjmGPOtW578uP/jx7/6N+iRz/+Nz3Meuijf7F+pwc//M0Q72/8" "Rg988Bvdz8/3ffCr0o3f6R5e973/m6m731PPe9/9hXa/+0/a886vtOudn0V4hnbwZ1DLOz+x" "/knN13821fT2T6LGaz8aK979U54b3v6R6q/9EKW6t/5xk2rf/F5Uc/Xv5qpV/cZ3VPuG2le9" "+S0/fyOqvBpRxRtfU9WVr833FVe/pPI3vqDyK19Fqezyl1RxKSI8l135nEqufCYqvvypoU9u" "UtElJc/Fv/5HFV74OEoF5z9SuvCBqfzz74ncrLxz75vKPf8ur+9S7tl3ouQ48zblnL3O61tk" "P31NlH3mTV5ZZ65S9uk3yHbyDco+dVXWrFNKmccvU+YpJdupK5R54hKln7hIqYbSjl+Q57Tj" "5yj12HlKPnaaYgNHaMPUAq33z9NdE9Cs7ONDRyhh9QQlHjlJ21aPUvyRoxS3coziV45Q3PJR" "ilk+QltDvIZXaOtymLasLPMaWqNg1BoTCiotL7EWKDa8SNtWlvjfW+D/HjRHccF5Wbctq1X2" "4TlKWJmnxPA8JSzzu6VJWufrpTuHO+nOkXZWm2jDZC8lBscpeXlSlMZKD0+R/ci0KGd1mhwr" "U5QR9lFa0EfpoXFKXx4z5KUMXjNktWrYXLNCEWWvjPC/5RXZQ0OUPN3Gax85V4YpJzwkq3N5" "gPcDsuaF+1l9Ije/y+efzV/pZ/XKu8y5Q7Rt7EVK879M7pVuUcFqF7nCXZQX6qCClU6RJ9zB" "6hS5g21UEILa5b1tbj9tHLyH1vffQ4n+J8m29CqlzzxLCb5HaMvAPRQ/+hClTj1BKTNPUers" "05Q2/SQljT9CqeOPUubUk5Thf4JiB/fQhs56Wt9RR5t7t1O6/2FKn3iIYnpbaFNXA8UP7aLM" "mYcoa/ohyp55WJQxeS9ljt9Dtsn7yD71ACUN7aQtHZW0pbWUNreXUcrwdrKN76OYrmra2lZB" "8V1VZB/fS7lT95KTfwdrzuQ+ckzczft9rLspfbiJYvh3YzpKKK6zlDJHmvn9bkrsraTYNg/F" "tRdR1kgj5c/spbzpXZQ/tYtyJ3dQzvh2ck3uJLefn33bKbHHQ/GdbpFtuJpc/u2U3FdKCR1u" "Su4u4J+po+rFewzdLaqY201VC3upZmkvlc/vJMdQOdkG+L/X76G8sUoqn91BuSPllN1fRPaB" "YtlXzDZTzeJOql3YQVXzzbI2BHaLauZbqMBbRrmDBZQ3VEhFY2VUN7+dSsYryDVUQJ5hDxV7" "i6lupp5alnbJWjNVTbUztdS00Ei7gjuoZbGFKsZKqHjYTSXDhVQ26qGmmWoqGy4gV28OOTsz" "ydGZwXsblY8Vkmcwh/K6M+k2gOOxD/9FjzA0HgYo/kjv/4vuv/GrqXtv/GLC4x6GhtY+BgME" "gOx5RwHDCg/sAQ1ouwEMDQur8K7xugJIw1t6/UFkBQcAUXc1WlEAeUPrW3Nfc+U7/uxbgUP1" "1a9MiAgwLn9lquqNL9X+yhfR4ncaGFaAlF7+TKQBAkBoiBRd+pspEyIXFCAACry/FTQ8lz6i" "wosfqmdeI+B4n4Fxw9B75GJQKL1vCvDQAHGeuR4lQATAcJy6psChxaDQANESgJy4QrYTlynr" "ZEQZxy+yzjM0zgs0ABClc5Ry9AxD5DQlMSQ2zSzRuvFZAcid4zO0foK/yENhAUciSwASPiaK" "C6+KYhkwscsrrGhwxISsCkZLwKHgEWeVQGPBBEbc0gzFBaYpPjArz4AGlMwASeI1KThNW2dG" "DIC00R3Dh2Td4u+jlOCEKDU0yes4g2KCMpcn+It+hr/MpyhnZZJsK36Bh0DEAAggkRXykm15" "VIR9ZnBIZO5Dg5QVZAWGyMbQADicDBAAI3W2jWyBHoGFc3lIlL3QLcpd7hMBIlgBD5esvSLs" "cwPdlDH1OqVMvMTPPQIQ13In2WYZAv6XKGfxIBUud7DajZVBElLPAIi8Dx2kpNFHafPAfRTv" "e4LsC/spY+YF2ty/j+5sbaZ1Hc2U6HtYIJI2zRBhaKSxMrUmn6AE7320oaOB1rXW0ubuZkob" "f5AB8TBt5HcbW+tow+FaSvXdowDif5CyJu4n28SD5Jh+kJ/vlzVr4l6K7a5hgJQLMFIHWsju" "u1f2gAqU0FNHuf57yAHwjO3mda8BDwWQnMk9/OVfTbEMkPiuMkobbCDn+G6GSjHFHS6k2EMF" "lNhdRnn+3aydDI4mcvgaBR4FU0qu6Z2UPVLDoCimpK4iyhysFICk9JfQtnYXv3NTRn8xlc3s" "ZGDsoxL+naLJZgbELhMmAEnhZAPZ+0vJMVBGbl81Vc0xnIYrydbnEdkZLp7xWqpe2MlrDbkY" "FiUTtQwJBZF6fl8+WU+uwWKRZ7SU37UwNErJ1V9ABYMeVgGVjDJYZhuoeKSEPAyaEoZKw1w9" "7VjaTruXWqiRoVLOsIEqRoqoebaGSofclNuVTdmtqZTTmsZKocIBJ+V1MFDa0+m2teCAy3jg" "xr9E93+gBKdx//u/070Mi3sNYNxtaK/A4jcRgAHtegfu41fa+R7cRgQYAg0DHM0Cin8KGJR+" "tEhBo/5atDQ06t+MaC08IgD5zhRgYcLDdCMR9wG3oRUFDwMWpvi54vLnJjDKL36hXAer9NIX" "SgDIpU9NcJRc/JyKL3zGYIjAQ8OimN9pgPyh6wA8DFldhwLIeyZA8gyA5J99TxQByPsWgFzj" "PdzHNQGIOJHTb0fgcfKqSDsPEyAMDwADAIEyT1wQeKQfuyASYDA4Uo+dVc9Hzws88JzMSmAn" "oVzIIq2f5i/0pRV2BseVVpXziA0fFech4DAUw5CJC4fZhUQggv2t4BEHMTziwwHWouk6Iu5j" "gbYF52jrArsL/witnxymTdOjFLs0ZQIE8EgOzYgSA5O0ZWaQYddNG3xdFDM9QMnsTAAOKJmh" "kRJWLiRteZyyeO9Y9gtE4EKy4U5Co6b7SF/jOgAN03EERgQaAg8LQGwhw2lYXEduWAkgSZx8" "lRLHX6GcYDc7DeVCnAyM3OVediH9FvUKNPKDXZQbbDfdRm6gjdJ8z1Oy9xmyTe2nQv7Mw7Bw" "Lx2m/IWDVBBolWfRcisVsVxLByh96jnKnP0LA+QVyph9jh3FTrqrbTtDYbsAJm3qaUqeeIzi" "vPeyo7iPMiYeF3jAgWRMPkoJw/sobmAP/3f3Uab/EXYgD9Cm9jra2FYrSh7eQ1lTD1LKyG6K" "626kbb3NlMVQgfvQyhjl3+9rVvBgOGSP3W0ABQApYRCUk9N/NyX314vTiO+sUC7Dz46CAQI5" "xndR+lAjZYw0UM7Ebv53WhRQWgsMgJQwJHaTzdtACV3FtK2tkDIHqhgiLSZE3H52C74myhlt" "oILpHQKQ9P5ySuwsoJRuD2X2FlEpvwc47Pze1ltKzqEKqpzfQzULCiBVC7upbGo7lfubqWJm" "B1XP7yb3KLsohgdciINVPFkn0MjpKzAlEGFXUj/bQtUzjVTtr6cq/jlAookdShFDAOBwD7hF" "paMlVOYro0J+V8hggCoYJi2LzdTCIKmdqhAXUjdRQTtmGSwL9QyQfIFHdmsy2Q8lkfMwA6Q3" "mxyHkwUmtz348b/owQ/+LdLAgO5haAAct4TG+7/Snvd+MfSbwALSpSorMJreUSWoaFgoQNS9" "+TPVvcFwuPozw+BHhsOP/IX/A9Ve/Ylqr/won9Vc/cctVf3G91KO+k+qevPvDIVvRdWXlbCv" "vPqdKStArOUrEyAWCTxY5Zc+E1gAHCWXGRpXvhRhD2BoFV/63ARI8cVPolyIhsXa51uWrACM" "NWWrCDgiTkMDQ0HjPXKee4dh8a6Uq7BHyUrp7YhOrXEfpxRAxHFogBjwwAp4ZJ1U8EheOUMJ" "4ROsU5R8RAEjotPiQpKOnpIyFeCAstW25YjbAEDiV48reKyodyhdWSGiwbEltNaJBKNAAnjE" "GvCINQGyJIIDiQvOCjzuGh+k273d9KeRLlk3+IcoPjhFieFZBgiDIzRtrH5KCk1Q4sK4KCXg" "N+AxYUBDgQTwkGd2G+JAWM5VvziRrJUxKVsJQEIjJjxsyyMRgLCTADAyAwOUsdQvq4LHAENo" "mKE0qMpUK4NR8Mjlz9PnWtlVHBR3od2HbaGDMqcPUV6wJwoiAIhyHgoe7nAHu5M2/nJ/USCS" "M/e64Tra+cv7L5Tue5YcM/tNgBSxWynC5wyRguXDlLP0GtkXX6asuecphh3I+o4dtKl7N6WO" "P0bpDIutfXfTujZ2FO3NlDz6gAAkc/pxAUj6+MMCjqyph1mPigOJ6W6ijZ21tLWrnjJ8KFnd" "R7FdDbT5cBltOVxJyYMt5PAzPCbvp8yxfWQb3ctf+vdLaco+qUpUib21Ag5AJHWwkd/tFXBs" "ZaBACd1V5GTnAYhkebcLOACRfL8CCkpYqYO1lNTJjqKzlLJG6gUgqT0MoDY3xbW6KKHdQ3nj" "zeSeaqGcsXqysVPAimcABModb2TQlFFWXzHljdZS6Sw7mMFycRnZfSUicSXsNIr4S989VktF" "E3VUy06ibnEX1bAqZ5qoYKyK8kfKGSaVVDXbLGUqJ4PA0esWgBSOllPtXLM4jcKhInEYDfNN" "1LS4XVQzXcPvSqSEBVX7qxgiRexK8sg9mMdwyaOiQTc1ztdR6ZiH/418KhpyUdVYMbXwu8Zp" "Boq3gPI7MwQgjtZEgYe7P4tsrQmU3ZZItz3wYTQ47jPAcfcN5BlY/8XA+F1gEQHFbwwHdhjX" "lXa8/Qu7il/EVTQbuUXDm/8UCRzWSEMDq1WAxlrVvPEjVV/5QVR1+R+mKi9/J6q4+Hd2A99S" "+ZVvTJUxKESX/i5r6aVvLPpKVHL5K/nCL7v8tXq++KX5WfnFr0yXYXUg8m4NQDRETDEwis5/" "SkUXPzMBgr3KPDQs/nZLeNwKIgBH4fkPqPCcyj4iZSsFEJV/3KC8CzeiYALXoeGhFQUOyT/e" "FIBoASBwINp1CEBMcFwScCj3cZ7/mj9BMXOr/Fd6mLbOrlDMwoq8Sz2i8g8NkGSGB9ZEBgwg" "s23lpAKHAREIANHZx9bQqjgPVb5aUY4jvGJkIaGbylnIP/4IIOJIQkYJKzgjrgPQ+PMI1Ckl" "qtuHOyhm3scOZEbAoTRFSUE/O5EpVbICPBgyawEiGYdRqkIpy8afARy5RwCRCbKv+BRA4ERC" "I1EZB4SyFWAB14HyVdJcFyXPdknpys6AcDBA7Ow8spf7Tfehylcq98hhpwFQoEQFYZ82+Tpt" "G3mB7PP8RR/uFfdRsNInWUeBZB8KILpMlc9uI2/xkJF3tEvmkTrKDmKEv+zHnxFgFK+0i/PI" "mX2J19f43SHKD7xGDgYIhDJV8tjDlOJ7RFxGGruPdW1NdFdrLa1va6DEkfsEIElj90nWEdu9" "ndLG7xeA2KYAk4cYKvdTCoNBylfsPgCQrR01RlmK/6LvbxZ4wHnEd9VQXGe1uA9kHCL/PeJE" "Mka2U6Z3Jzkm9jBg9ghAYhgoMYcVQOA0MoabxGkg50gfrpWcQ8vpVzkHXEWeH05jNzuJUtrW" "XiBK6CgUgAAaiZ0eyTpSeorYiWynQjiN2V1K7CjgOkrYUZQxKHKGSsVNSK7BIKmY20klk03k" "GGSg9HvIOVhKpVONAhC4CuQdNfPNDA52FnPb+V0Lecb5f3+/ixx9+eTsL6RiXzlVTNUwEFyU" "15tH+fy+dKKc4dFEzUvNDJMGqp2pZkdSQw1ztdQ8X0/lvhJ2I7kmQEpGC6liAk7FSQX9OeQZ" "zJUSVdWEh2HiJFdXJuV0ppC7L5tKhhxUMcrQGbZT1uF40W33CjT+beh3Sxj+u5Sldr/9L9p1" "/V+08+3fBRQ73/qNdlz7jZqv/cqwYFfx1i8iAcZbVnj8wpD4I4D8zC7j5yho1Fz+wZQVGBVX" "GBZv/CBrFEAufS8CQACJ8ivfURm7idIrChgCDxb2JZeVii99bdl/KSq6+AV5LuBLH07hC+P9" "1/z+K1kL+XNI/zyky1VWcAAWpthtKMcRWT1/UK4qNmBiZh4WiNwqMNdlq/w1AMk9/z67jPdu" "AojKOyLOAyCxZh45pxVItPOwlq60+4hIASRl9axAY+v0Mm2eDvIKLTFMQuJIFDxOmYILAUgk" "MGd4IDxPYGAAGpJ7MDh07rE1oELzm7IPo4y1JRQ0QvOg/IzOPeJMLZirlK2WF8V9xCz66Y6x" "fgZGjwDkLnYg0B1DHQyWftN5AB4ABwRoACRW94HcA2tqyGeBR0T2lQmBh3PVJyvyDsADygyO" "CDQyAoMRgASHRdinLvZS+mKfAATwyF5GSaufspZ6KSfUbzoPWVf6o4JzCHlH9txhSve/xq6k" "08w6sucOUMo4oPK6OI/C1S4zKNdZBwR4FDJI4DzSxp4i+/RfxHW4g62U5X+G3zEgJp6iguCr" "VBQ+QLmLr5Bz8SWyzT/HruNxBskTKiyfeJxi+vbQ+vZ62tDRRMm++wUScBkbOupoU1s9JQ/t" "E4DY/QDIAyrv4J/Bs33qIck7EvqaxIFIzjHMf8VPPEgJPYBKmeQcsR0VZlAOt5E1ukPAgdJV" "/vQ97DTulhIVMg4JyoeaKJc/39ZZQrFtBVKqSubP4DLyZ3ZLvmEfa6D8iR0CjsLpXSLnaAO7" "kBIBRsZAhcACZar4tnwGiFL+RINAo2Cikdzjao+sA4LbKPYzkEaqpHxVNNkoZaqCsWqBBzIO" "lKtK/A0SjqNcBedRzMBAvlG/sEvW2rkWKpmopoLhUirmz2tmm6h8vFLAocRf/t4iAUeZgCJf" "ylRVk+XUvNhA2xcaqHGhlion+fe9yETcVDddTiUjLgaEgwFiJ09fDjnaUxkwNrK1J1LGwTjK" "PBTHEEmmci+DxZdPld5cyu1IpuxD2+i2exgU+yTD+Bfd/Q47Ddbu67/RrrfZXVz7RWCx/W0F" "jZa3fhVtZzg0vRVRI78DMLQAjjqGSK0BC7iIGpSjBBjGevUnAxSAR8RlACAaEoBD5QV2GOe/" "E5WfY1dx9htzFZ1hB/FHOv0VFZ3mL/0zavWc+4JB8aXAwnPhS0OfK4AAEhe+Mt8XsAoZIgXG" "HnKf/8KU69yn/MX9Ka9/4+dPRJ4Ln4rEcbDk+Q/AYTqP8x+bYbrpOKzwYLkYHC7ptrrB6/tm" "15UWnAfgAUnece6dSPnq9Fs3la40PBynr6quq1NXowCSefKKSGcf6LoCPDJOsvs4eYmSwqcZ" "HAoeet00FRDFLR0xwQHHoVdAI/nocdp29JjsARIBh5F7bA0ui+PACoD8X0LzWP4cmcdacGjn" "oUNzaOu8Asgd3j5WD7uPboEHtM4XAYgGhyntOoKT4jJSA+OUtDBCMf5e2jLZSfGzfZS86OWf" "9aq8g90GnEcewyP/yLiABCUrBQ8FEMk4gqp8JeUq3tuNspUqWQ2Z2uY/SHG+Vyl7qccECMCh" "gnIFEHRbWbMOETsOt6G0yf2U7H2W/9p/WQCC8Bzw0MBQZaoOgYUo3CYqYedRGG4ld+AgO4TH" "KWX0YXYlj1EBu47i8GHKX3xR3sN1ZE49pTIOVpZfBeZpk8g3UKp6XMLyzR31tLGtWiCSPLSX" "bNMPUcrIXnm3uaOW0sfuEXhIqcrIOpBtOMaVy8iZuNeARwltRdjdWSmwsI3tlJwD7xN6qhki" "DITpfVKq0iUrnXvkMWgAEOQZcBOpPRUShiMkT+woklIVHAdyDsBDl6asJapCBgJAEtfhYqi4" "xIEAIC5fPaV1FVAau5L07kJxIHAagAiyjcrZnZJ31CzsofolBpSP/7cOFpOjv5hyBoqlbAVJ" "9mGUqaqmG9g97KD62WYpVzWwG2lc4HVJlamqp2oFHBog6LYCMLB3sdPI73eK02haqBcXAngg" "69i+iIyjllrma6hqzEMFPTaRsz2ZncU2yu/NoPQDsZR+KJayDsSRjUFSPJhNnv4syjmcQI7W" "BHJ1pwEg/2aAMDyu/1sExyGu49rvAg0NkLXg0CUqSANEOQ4lgEOVpn42gPGzCRAI4ICzqL4U" "UdXF701QyKohYYXGua9k1ZAoOR2BBVRi1SmGhyHPKXYSJz+XVfanPhV5Tn8iKjjzGRWe/Vwg" "4zGh8bnIff4zQwDH56byzn0iyj/L65m/Ue7pv/Jf/B/xl/jH/ByRiyHhvgBFuq6sjmNti64L" "paoLH8tqdSD/Z4CcuW7kHu+tKVtFA8SEiFG6yj5hlK7Qonv8suxV6UoDRLXtIvtA6WrTTFBc" "yJapRVaANvqRNxw1AIL844y4jqRV5UCSjjA8jhyLKmFtWQzQ7eOT9Cefj1cfbZiflxKWFSI6" "89DOQ5et1gJEZR56nTM7rBCeo/Nq3cSQwOOukR7VYSUQ6aL14wPSeQUJQEKRsDxSrpoUiKQs" "jdJWP9zL67Ru5KBo82grbWOQpInTQJcVAOLjL3bWkUlyhH2m40DGYYblBkAcknUoxwHZwwMi" "BwMibb6VUmZaGTJdUrJSOUc7pc8cImdI5Rz/ESC8d8y+Rqljz8mqS1eOuZf5S/1Z/kt/v7To" "osuqyMhAVObRQcUCk8NSsrLPPE/pvsf4y/0p8gSUA4EjSRy6n+L674m06k6onEPWqUdEyDmQ" "ecQP7qQtnQ20tauRf+Z+yhp/gGI662lTa6UooW+7CQ50WmX57pacI9evhDJV2tB2dh7l4j6U" "49gt0NjKQEAHFdyGnR2Ek6GBUDxrlF3H5C6Bhy5TZbGjQMYBUKCzCi25CMcBD4AliUGSN95o" "5hmO0ToGSjO7khYpUxUzcOA0kHMgJM8ZrZJSVa63RsCR3skQ6XZRga/OBAeEPXKPOgYISlUV" "s9vZabCLGiqlMn89Q2WXdFPZGRx2Iygvm6gReMBpILtAMF4/12gpUzVJWcozXCCqm6mVZ8BD" "A8TFamBQFHtdvM8WtwFotMxW0875Wto+V03V424qGLCJ0/AMZwlA4D4yDm3lNVZcSGFfJmUd" "3Eq212PJdmCr6DY4j71vK0mZioEBeFgBAnigZNVklKtUyYqB8dYvqiT1ZnS+UWc4DKWfzb3K" "M35kd6GBwU7jwvdUfe4fVHme3QacBoOi/KzFYcj+22jXEQWQr24pDY6ik1+IPCcAkC9MkIiO" "s0s4+SkVnGSAnPyrsX4iYHGfNsRwKGBYuM9+xuun4jy0THicU+BwnvkrQ+Qj2eec/lik9h+q" "z0+pNY+hkH9OyX3uwyi3kc/P2nFocLgssx7RuhFp0xXHcT0KIJF5j3cMcFyLdiCn3jS7rkQM" "ENtx5TrEfVgAAheCdl1p2T16luIWjrLjCJnuY8PUEm2eDVHiykkpWenwHBDR7kMAAvexqjKP" "mECI7pyYpP8ZG6c/jY7R/3i99N+jo7RxYYE2RZWwFCy08zBLWAwPa/kqNjRvlq2wJvBzYmhW" "ABK/PEtbZn0GQFTpSpey0LKr4DET5T7Slv3GrIffCMonKGF+gNZ5D0QBZB3vNwy/TglzvUbW" "4aXs8JiCCLsQrNkI0QODlB7op9T5HpVvAB78XpWsFDwUTPqVggMy+yECCBgY6LJK8fN/y7uf" "HAsdRkDeJ6DIY8hAbgMgnnA3g8HIPoKtAgk4D1egldJGn5OcI3PieRMc6L7KnX+VncWrpgsB" "QEQMkcLQa6LS8OsMlVcpY+RhdiUP0Lahe8z8A4F5XP9ufrdHwnHb9GOSc2RPM0gQnDM0oJxp" "horvfgHIlsPsQNorKGlgh7iPdO9uimFXAmWN7lKzHAZAVNaxm7J9u6QlF3vMbgAeEPZ2304J" "x1G2wkxHan+VgMM1u4fyp/bITAcchuqm2i2dVBn9lQIQuBK05EoGwvBI6iqUnAOOAwDxzLQw" "QFqkRFU83Uwef7OsZfwepanMbo8CCDsRD7sSOBBAo2Z+hwCjcq5FQnIABKE58o3KuSbVTcXP" "FdONlDvgIceAW3KOWn6umWN3M+Sh3P5cyut1UsVEBcOjhZ1Io7ThqnyjUTIOqHqiXFyHQITh" "4Rl2Uf0MO61+hyi/D6UqOzXNlNN2fl87WUilo7lU4nVS2ViuqGAgi2yHYth9xApAsg/Fs0NJ" "tQBkM+830217LK5DA0PnHBocVniY+QbvUaaqezPadShgGDLdxg9GboGy1PeiygtwGwCHUsW5" "726CxFpFl6i+Ef1v4NAqNKXgUXDiMxEgUnDsUwFI4am/kfuEkuvUJ7Lmn/xYPsOax5/ns1tx" "nWF4GMo9+6mAQwNEgwOCE8k5a7w7+1fj8w/5i/uDiM7eoJwzN8h5WimX97nnDLcR5T6sjsPa" "cfWu5B8qMH/3Fs7jLUtoHgGICY3Tb0R08orZqqtzDwAEgvtAu65A5Ng5Slw+pVyIUbqCG4kP" "HZOwXHdfpQhETgtIkg0h+xAHwuvGuQW6fcwn0PjvkRFTd/r9tCkQXNNxFYwCiJ77iA2pwBzw" "EBcSXowqX21jgOgW3YTgjHRd3eHtotuHuxgEvbR5aogSA1OUEpgWaOj8Q8HDL84jPaS7riYo" "drpHALKetWH0IK+vCUDWjbxKWyYORwXmcB4aIHkrowIKdFpBynEMGyAZoMzFLllVeN5v7gEO" "gYe862MX0kPZi+i0OiDdV7rLyj53mFIn91P2/EEBCIQQHW7DbQ4HsqMwAnT71MsMj2cpZ/Zl" "s7sKmUfqGNzDE1QQPCAAKV5pFXh42HEUrxwU51Gyylp+jXJn2MGw88jmn3fMPssu4zGBx7q2" "GlrfXssQ2SXZB0LxtPF7+d++l2yTD0jpCpkHhKHAmM5amduwje6TMlVSr84+yhgI9UbGsU8c" "R6a3RWY4cqVr6m5xGrbRFkrprxN4oLPKyY4CLiOm3UPxrR5K7CihvGkFjxx2JJkDNeQcaxbn" "oQCyS54BibS+EhkIhPuwe6tpW3seJbS7KJnB4PY3CUDQWWUfLGPHUUXF/u3SposyVen0dumo" "Qs6RN1QpwKhicAg0eIWQcVRDDI4iXyWrWrINvAdEEJaXT9ZS6VgpVflrpFyFtty8ARcDRJWp" "ML/ROM9wGi9lR+Km4pFCqvZXSNstSlPbGSi1E2VU5isUNUxVStZR2G03HAhKUTbaPlVGld48" "yu1OpczWbeToSKYKr4MqfU4qHckmV08KOTsSRJ6+VCoeSKfsg1so+zAD5eAmBswWum332/9m" "twH3oQRoRILy3wzHwQBhiDRci+QcGh4659DwqH5TlarEacBhsBQs/h4lvKu88IMJEbwrZ4ho" "11HKMCk5GwHFHwEDJaz/BA5dsvLwZ7cCiJYGh0DjxKcCDPeJj3k1gHL8I9ZfKe8E9JHIyZ87" "WDknP4oCh3IeCiqOMx8rUGBl2U9/INIAyT51g7+83xPZTr0rq/3M+yyGAO+dp1VLLiBhnTCP" "KFK+Ut1WCiTKdbwjcx6RVt1rkY6rkxGAZJ1WZStp14UDOWaUr46rYUENED1lrgWIIPOIXVwV" "55FsdFoBICnagazyyu4jkaGBoUIMDmKP0Hzd9CwDZIL+i53Hf3lHRP9vZJhuHx+XsFy37uoM" "xOpGMPcBeCjNU8zSLENsXLIOPSCoAaIHBKWcFfCzExkVxc75KGFpQtxHalC5j7TQtAkPK0BU" "CctHm8bbTdexyXuQNo68Jrpr+BXaPH6If8Zo2TWCcgwC5h9lgBzxUm7YGwUOKCc8IiH5tonX" "ZTUdB8sR7BPXYQ92S4iuXEi3QATlK3EeYTUoCKAkjD5LWTOvSMahXEeHdFjBcejQ3AzPg23i" "OHTmAYBkT73AX/KPSK7hDr4q8EBgbp9+jkHzHBWHXmf3cdAQ79mNeAL7lZZfkewjpm+XwGN9" "ezXF9jRLUJ7k3SvtuShdJQ3tlpxDBeUKItKWO44w/AGBBQCi23FlIHDqXsk54rsqKRalp4F6" "AYdAxMg3kHUAHPrZNtZIsewmVFCu5jmcEy2yR5kK5au88eh5jvzJZpHuqHIyDBRA8mSmwzXZ" "KBBBmSq5I1eEwFznHHAhmCIvm25iJ9Ek4KiYB0RaZFpcC8/u0XIpUaFUVTFeY4TlLRKMo0QF" "d6HKVC38XC/tuMg5xIGMl1PdTDW5+/Monx0FuqrQfqsB0jhdRfX+MmqerZKMY8dcHa9VVDqU" "K224hX1ZVDGUQ41TxeTuSZfyVLo4jTgqGbLzz9koryORctvjyd2dxFDJpmpfDlWO2sl+aKuA" "AwCxH95It2lwoHwFqaBcwaNJAPKrCREzJOfnWoZJzVuAyK8Mjl/MjEPyDClN/SDSsBBQGM8a" "FuXn1PvI83dmyar03N8ZIGvhEYGFBkiRVWvgUbSmZLUWGgKO45/eJEBDg0O5kL8JPPKPsas4" "/rEBk48EJjm8Oo99JKvjBNzFRwKIbIEFAKIdh4IM9gIRhoQGhxUeUCbvs4x3WSev8/qOrNkn" "3+HfZUicfscEhXIf181Zj7UA0e26EYBcMwcGo9p2daeVUbrS5SsNkHTjqBIrQFSb7mlzBkTD" "Q6+qdfek5B5mcI5JcyM8v2tqRrkPiwMBQP40MaG6rYLLRtdVSHVcrRka1GH55vkput03SH/y" "9ktQvm7SKxBJNNwHjijRx5Todl2E5nAeqstq2ixbpYT9orXw0B1XyD/Wew+JA9Hw2DD8qihm" "/DCDY1iF5SHVmouAPO/IGENklPJXx0xwaJAAINlBdiVz7AoCEYDAkSRPHSD7UpcJEg0PR6BL" "3Ic52yHlq3aGx2sCDIEHuw3n/OuUMvocZU6+aMxxdBpBeWckMEfWAacRBlBeo6zJp8nBzsKz" "/DoVrx5ieKD76lH+kn+UCpf2U9nKgYiWUc56jcoZMpBr6UWGxb1yJAkGAwEOdFYBJBsPV9Fm" "diaY7ZCgfPphOZoEA4I57FCU7ieHn9+N75HjSOI6KyhjbIeUqlIHGyQ4R9aB1lw75jem90lL" "bvpwvcxw4BnSMx2ZwzWUxq7E4a2XQBzuAyUqtOOio0qG/zBRzsCwe2ulZCWtuFM7ZC2Yaubf" "rabsgVJxGx5/o0yNJ7XlUXKrkmu0To4mKZ5olulxdFZVzjSbrgNuA9CA44A0RDDLgXZcO0Og" "dKxcQnE4DsxzYPivbrZOMg5ISlXzdXL8SN1UlbgPAARlqnwpS6mgHPCoZVeBVtziAXzhF9Ku" "hTpDNdTMLqTW52EV047ZMqodL6DstgQpU6UfUOWqkmEbOdvipDwloDi8lcqGM6hm3MkQYbgM" "pJK7PY5cHXFUOpgEgESH5c2m8/jVlGQdb0W6q5R+lbVKuqnYeVz6id3GjyKAQkkD4h8CCy39" "XHaedZbhwSoTReAhADn97f+acUScx5cWl6Hzji8jecf/ESDaZbiOfaJ0XO2V8zA+43cASe7x" "DwUeeUc/YICwjt4gx5H3ZbXzs/3kh4br+ChKtpPsME7eMN2HFR4ifg+IKL3Df/1f5y/xt2UV" "Hb/GX+DXZG9jh5F95jrZz75tgUYk81B6M0q6ZIUOLGnXNdyHtWRlLV1pyblXDAoNkOjBwbNR" "QIH70K7DnDo3wnMNkM0LS/Q/Y2PiPJB//NfwMGuEncm06Ti2WLuuggGRAofKPLYuztCfx4fo" "v4d7Rbd7lTDzIY6DIYL8QwNkm9ltNWO6Dl26AjhUcO4384+MZXUsScYyOrDGJAPZMHpYlbAY" "GihdbRh5RfZJs70qLF8ajEyXhxQsAA9IuZBBgYe1hCWQCA5I5xUAkjJ9kLYMP0+pUwctAFHO" "A5PnTgaLyyhT6ZIV8g5xF6s9subMvErJw09T6uiTKs8wgIEpc+U+OlVQbpSw0HGl8w4IJSv7" "5FOU7n1YVLD4oso/Fl8ix+Tj/Bf941TC0CgPvUyV4VepJPgKOWafoozJB2W63DathgW3De2Q" "kHxzG0Ohu14dSzJxH4Ogjp1GpZSpAA84DZGE5uiaYhhMq+NHUofqJOMQgHSVScaBrANlKsxz" "JPVUCjhc03vFbbhnjL3l6BHMbwAcAAiyDcxyoFSV2lsqHVUoU7nYYQAenpmdknN4Zoycg98j" "+8AeOUdym1O6rZBzwHXgGJIMhoKtr1DacCsNYFQZ8FAQaTLl9haTo0fNbqCTCq236KBCzuHs" "c0obbjMciKhBuqh0xiHtuAwUtOK6jJC8ZKRATY573VKiQkdVEcMF0Ng9Xy05R5XPRQ1TpbRn" "rloAUjmWRzltiZJxAB6OtngqGsykrNZYcnUlU5XXQc7DMeTpSaQKhoi7M15cR177FqoYSaM6" "Xxbd1nL9dwGHgkcEGg3XFDgiecevouo3fxHHUfMGw+PyT1R5nsEBARgGLETnfhSVn/0hIgtE" "yjQ0zvxDVHrmO3Yc31Hxma9Z3xr6+iZFHMeXUYouU0X0v0ED5aq84wYgeM099rfIaparFDgU" "NJTgRqC8owZAjr5H9qMMhlW12rA/yk7gGEOCZTv+ngmNrFMf8qql3gEiIoYLlHVSuQ4NjXQL" "QAATACT12FvR6/GrlHnyLf73r4lTEXgYTkOXrayHJCI01+26a8GhdMEIzi+augkgR86Y8Egy" "sg9AA44jyQjMrV1Xun0XE+fotrqTYQGI/PeIV4Ty1ealJcugoGVYMBRUk+X6yBJ2H5vmJuh/" "RvrodojB8efRPlOb58bNDMQ858pwIABIGn+GkpW1dAW3kbE8JbIOCwIgyoV4KZEhsskXgQhK" "WYlT3ebZVjLbEYq060JwGvnhUf6iH6W8lSFzytxutO4i40CZCgIwbEudlDrDDiDYZcIja76N" "4rwvyJwHAIJZDx2aAx4KIN1GeN4hR5HAfQAk2nUg80jxPkHpvqfNsByDgkUMC48FHKXLh9ll" "HGLX8QpD5EnJO+A2Sthp5M08TZmjDAjvAwIRDZDS5ZfJvfisHIAIeEBq/wCDbAc7kXpK9e6S" "Lqu0kV0y36FKVWXm4YcyWT6+W+Y5VM6hIAJg4OyqhJ4KyTny5EDEeoptK5YyFYQjR5BzoDSF" "rio4DwTm7pk9DIU9AhGnr0GyDuQbUrqaapGQHGdXIevA4YcAB9pynSOVlDNcJe24AEgJOxII" "0HB7a+Sd7rDKGSihjM58yuxySXsuoIFA3ONV8xwYCER5Sqt6tl6chxr82y7dVEUjhar9FkDw" "egQe9bM1MuyHMhWOGdnBoBEtqKyjbrKUqifLzI6qsmGXBOQoUyHnaPAXUbk3l4rw3JslbbgN" "fg//nosdRS6Vj9glHEepqnQoU8pVCMjhPhwMDzvvC7sTxHU4Dm4iF0PGeWgjuTu2KoBsf1sB" "pMniOhqu/c7Q+M1wHr+Z8AA4qi8zPC7/zMD4WbmM8woiJjDO/2juK6zwYK2FBlRy5nsqPf29" "AZBvxHUAHrJn3QognlPKbVj3t4LHrQCyFhy5J1gn/yqrgMTyDhkHYKFXtf9QnAeg4Tz2AeUe" "uaEchwBDKfvIewISuBEBCiv7CAMBOqYh8YEJDwGIhsaJ96IAosGBNe2kUuqJa1FKOf4WJR97" "k7/E3+S//q+K0o69QenHr1DGMQAiekBQAHLqijnzoec9RMeUNETMzivzpN0L/4v7OGm6jwQG" "RoIFHIBJgjE8KEeWYNKcIYLW3bumpugO1pZAwBgajG7ZjbOed2U5omTL3KSCx4iCxh1jvTLr" "AZhsnPJazrmKgCPiPtTch4YH3Ac6rnDCru68MgGCNagmyzODowKSpIV+Spnvp7TFfnO+w3qO" "lXYZeto8a6GHckMj/IU/xKAYNILyPtVxxU5CFFTZR06AFVRuAyucR+ZcK8WPPEupE69QzmKn" "AARnW+UttJMroA49LFqO5Bxq3xFVrgJAUscel7A8b+EV03Eg47D5nyF34BUBR1TWEVadV+Wr" "B6k49Ao5Z55igNwnAMmdfIwB8hLrL/wX/+OU5btPTs5FiQrwsM8+wnpIXIdVmSO7xX3IibgM" "EZyUC2ggDMcJuWjVzR7boVwIWnCN8hQyDhe/g7tw+FoiMx3sRLJHGyXn0JPjmOtwjjVK+apo" "xhgMZGcBh6HbceE00vtK5OyqJJZ7vE66qSTnYJeR2JpLed4KmRoHPIqnGmQtZzeCMlWVkWng" "kEN7j4tyMBA4UcuQYAgNFZOt20lZXTnk8ZVR3UyTzHLUTLNDma6VcBylKZSkdCiO8lXBQL7M" "cjTN1YmzcBllKs9gvoBDwwNHjSDnADhQptq9WCslqpIBOwPDRmVDDmqcKqLSYQcV9qdLG25u" "T7KE4RVjDJneFMrvTGCnkkaVozaqm8hml5JFBV3byH5os+QcOew4ivsTKfvwZsrhdw/MV1A+" "wyO3bTOV9CUogDQZeYfKOH4zAYISVc1bv5qOo/oiC+A4H3EeJiwsjqP0LMPh3A8CEwEHYMHg" "ACSiXMfp700pcHxtcSC3ch1f3QSNWwMkUq5yn/r85ozjhMV5WKGhYWII4BAdi+QcknWwo1D6" "kOHxoQkOmwUiEXCwVhgaq9dNmSA5/p5ZqlLAeIcyj78rEFkLEAWOaCWfBDwUQFIYGFDS0atK" "q2+Iko9eEaUwFFKPX6IMHIZoDApmsiNBUK4OSLykjmo3waFdx3nTheCIEmsOosGhlShHlRyn" "2MAKbZ4P0ubZADuEAG1ZCMmwIDqvABA5KFEDJLiqnEYwGHXeFTqsIhPnIctBiQHLoOAC/9t+" "+rO33wSIQMSrps0BEDgQOSTROOtKOw/AA2v68kxUy+5N4bkMB47LibsAiDo5d1SkT9FNDynp" "+Q44DrTtQnAeOvOwhdRJuq6VYXYhI5J5pMweoozFdrPLSgPEscQwCXTLdDmOKIHTgOvImjlI" "9oVDkoHkL7fLKbrIOdJ8L5gAkdJUuCs652CXUYzhwaXD0m2FuY7CkGrRdS29TOneRyhj9BHK" "mXpG8g0AA6F5ceBlyTrKwyr3KOf3RUv7KXf6Ccrzo4T1ApWvvEwFs09Slvce/nf2ifJnn1BH" "sfv2UdroXgnJJeeYeUhWnJKLmY6kvjp2FDvUjMdgo5xZJceMwJWM7lCHHk7sINtYM7uTneIw" "AA+cX4U9oAG3kc1uBCfn2seazDIV8g77SJ3AAi27yDlyRuui2nEBEJSlHN5KyTuwh8NI6cyj" "pHanQATZRvFkvZyUi6NHXGNVVD7TLB1WqjTVIh1XAEfpeC1VTTdJZ5ULA4E9OQwQO7mHCwUY" "OPAQpSqAony8nOoZBA0zdVKiAjBq/ZWSc2DfxGDA+VT5RvutDsob56rkSHWUqMpH8qllrlwy" "DpSqWmYrqWm6hGrH3dQ8w45loZTKvHYBSH43g6B9K3kG0sjVk2RmHFgLe5P4d2xUzSBBzuHp" "3caKp/LBZKr0plHuYcBkA5X3pfJ+ozzn8/NtjW//ZnEdv0S5DdHlXxU4WFUXfmFw/NN0HAKH" "cxGVr3UcFqcBqEDiOIy1+PTfqeTU32UFNDxnGRbnvuP125ugUXD6S9bXDIqvTWC49VDgH7Tp" "4tnF+7zjChYaHBoWeSc/lVKVLltBzuN/MyUB+dG/inKO/dUCkA9NkNjZiaj1XUOqdAXHYQKE" "91Z42I5cE2WyMo5cZ5fA4DhxXeCRwfBI5zX9hIJHZFVlq4jeFnigfAXBfVilnQjgkXj0MiWx" "E4ESj16kpCMX+f0lhgoDgqECIeMAQCTvOH4xynFEylfnBRRWgODOD0gfV4IDE9dNztEdvmnR" "nT4/3THupw0zi+p8q5VV86Rd89BEw4lE7vYwnIdlxiPeGBrcthyQOQ896xG7OE3rxoeN7EOf" "c9UtENkqJaxps3RlLVulLCtF4AFo+M3BQT3/oRzIqHGXx5h5FLtVumSlj2DHbIdIzrIasZxp" "NSjlKpxpVcACJLaN7ZdSlZSuUKpieGSzu8hZRIlKz3b0mBAxZz3CyEAUQJJGnhbhPCvAAh1W" "KFs5Z1+jgkCbgEODpAR7Pdsh0+aq0yrL95gAxDX7vDiOouDL4jTsDAn34vMGRNiFrLxqSJWt" "lF4S94E2XMgx/gB55p8WUMR2qZwjvqdBjidB+coxrfKOnOl7+d/fa2Qf+xgkzRTHziOmtUjW" "nPEd0l2V1Fehcg5epR13Zq9kHAAISlNmO+7MHsk50nrK2H0UyjHrmOdAzoGylQrP1R0dhdPb" "BR4KIi1UMrNd9nAXcnLuYJlkHdk4Hh0n4fobyNZTQCmtDIRut+QcOhxXeUeTOhGXwQKnAZVN" "Vsl9HHm9LqryV0k3FdpznexKHJ3ZcqR6/Sw7kNl6CcVrZyppOz8DEjjMEFDB1DhcSPEwu5KJ" "YnYb9fwl75FuKpSqigayqWmqjHawM6hjqFSO5Qs49ixW0d6lKl4rqXGykF0Hf/F3bmOIbJNW" "3ZzWWGnHVR1VWyi3PZaqvMp9ONu3UEF3HFV7M6h+LItqxzLJw8+5bZsYHOvJeWgDFXXFUF7r" "Jrqt/joA8rtZqhJovPGbAselnwxw/MzO4xeGxs/sKn6migs/Ge7iJxMW2nVAGhalZ3+8CRpW" "ec4Y8GAVnf5mjb4S91F45iuRAkg0RPB8K3i4DOWfMlaGidVtWKVhoUEi4DimgOE4+rFI7xVA" "PhCAKCkXot0HQKGBYd1nMjig7KNviwCPrJW3KWv1LVnTwwyEFQUTwCNNnMd1YzUciAEOXbKC" "Uo9di0ADDsQCj6QjlwUeWNdq2+pFUfzRCxR35DzvzzJYzvNn5wUS0ZnHeePI9gvGHR9nKe3o" "aUo9oqbNNTx05rF1cTkCjzEFkD97Wb5J2rS4KACR/AMXRhlnXlnbdKOOLAE81hzVboWHPqI9" "dmGS7pwYigBktEfmPdBpBQeCbizAI2V51gQInIfOPwAOBY81AJE8ZIwhoeCRGfaxRkX6fg91" "HHukZCVuA85jeW3L7mAk6wgPSBnLtcpuZb5LjikBODAkiJZdXPyky1QaHihhmQAJdbD76BQH" "ghN1cZIuOq7cxrEkGAbEWVZpY89Q/uLrtziipFXNdzBE1P51diEvydEkmO8ow/P8C5Qx9hDr" "AcrxP0aloVcFIGXhV6gk9KJAo2rlFapmYUUJq3D+SXLPPk7FS8+QJ/CMACSuo1ZlHW3VlDm2" "V8Jyu59dyVCTHHwIeORN36PEbgNlK3RWYbYD8MAz4BHXXigrpsqlJZcdSToDJXu4Vlpw9dlV" "qiUXhyE2yBS5y2jJTexwS8aB1T5SJbDANHn2cLlkHeiw0hmHBOZTDVTor6Oi6QYqYZXyczaD" "AxkHBLehco56OSUXJ+OiNKXhgUubcGETTsStRvcUgwEAgfsAPBRA3JJxQAVyuKFT8oydiw0C" "Cg0S5BvNsxXSiotyVfmI28w4AJDmmVKqn/RI2aqY3wEQuxfLaO9CJe0NVND2GZd0UCHfUC25" "dsrriCPbgY3Slms/uJ5cnTFU3Jescg52KYBDcW+CAKRqKJlKemMYIjFUMZBIlYNJVDeSSm4G" "ym1wHg1X/0X1b/5LIKJzDkBDuqpQsrqonIcGiMCDVXbuJ4EIVgWLiErO/GB5/gcVn7sZIAKO" "U99FZAGIgsTXAgwldhxnFEDcp74SYa9hUXBCyQTGybWKOA8NC9GJaIhoeIiOKIAILAQgH1hc" "x4dRaxbDIsuAhW31XdN1ZPJeA0QE58FrBoMjgwGSvvKmAsgyAyH8FqWFr8p7Mxg3cg6r+9AA" "iYKHIe081kIDLkQL8IhjFxK7ek4AErNylrYyRGJWTvO7MwooR84aJatzxj0fkdwDk+hm7sFr" "kpF/aIAAHBogcB8ACAYGN8zORgJ0lK6ME3YjYXno5js+EJwb7gNDghogUELIuF0Qk+bBGZk0" "3+AfkRXPiWvch+k6cEyJcc6VFRrWoUEc0w73AXgogHhNeEQ7kGHTgUjZKqAcSKR0NSjuQ8MD" "51mpSfNBKlwZlNsDzbJVqFsUP/oSpYy/LCUrwANZB07XxUGJ+QwPAMQlAGkTF4I5D1fgsKzi" "PuZfoZTRx6T7Km/hNXPOA2UrtOnKNPkqg2T1kMo7jhwUiEiJavWgAKSQgZLpe1jCcgAE4EBY" "7px4lOwMFpSsqgx4VK3sZ5DspyqAZRlw+QuVL7/AMHmYUgZw8m2VCDmHOna9XnIPHEeCifK8" "6ftMgFgFpwFgxHcUmwcfuv175LDDlJ4SKVHpnAPgAEA8Rsahjx3Rbbn2wQoBSEqHS8BRNNUk" "LiO5PZ9S2vJl+K/U36yyjulGU6UzgEk9lfEeQ3+YDs8bLKJyBooMA47y/4eeXLJ1qXZczHAI" "QBgYAEi9TIrXi9PAWjNVKYN/mA6XnIOBUOUvo5zuLFHhQB7tCNSbuYYOx5FvoEwFoURVPpzD" "sMimGp9L3EYVTsntz2CnkUllDJXdCxUCEHRSubsTqKAnkWrGsql+IkeyjsrhNMpriyEHuwlk" "G2VDKZJ15BzcQDVDaVTWk0CFHVuoGj/XukHKVShbVTFAmsbTqXkig8oH4tmBGM6j+upvVHPl" "V6qB45AylZJyGz+bAiysAiCsAAE4tIrYmRSf/gc7Da2I49DwKDzzjSmBxslvRQWnDFmA4WJX" "Aleh9CVD4QuBg9VpaK2FhnVvLVPZDVjcynkINI5+aDoOOA0NDBsrm/c2vWeAZOp8Q2Ci3ce7" "EWCw5GcYEJkMDYAC4MAeIMlcuSpKC79BqctX+Iv6TbPLSjmPa4bzuLlshWcTHkb+oeGRcOTS" "TQJAAI84BgWgEb9yRkCidJq2hk/RluWT7BBOUdzKKXPCHMe160FBNV2uWnbVnMdJimMw4NbB" "20f9oj95J9kRTMjA4MaFpQg8zJJV+CZ4xFnhYeQeVvdhBUjysjqyBFfU6sBcZj9kgHD2ZngE" "p8wbBdeWrSIAGTdLV/qARH0ZVORWwREz54DLsPNnUORokmFzmjxtrl3mOtQBieoYdoTkcBwF" "KwMyCKjbc1XZqieqbOVcbKfEsecobvhJsi8cMJ0HgIEVx5RA6LoSLR8m59wr4kS068BkeebE" "EzLPkT/3PEPjsAgQKVlWLbgqKD8gAEHJqmD+L5Q7/RSVBpTbKF58nmze+0QO34NUFX5ZVBp4" "looWn2bAPM8/9yLVHGGgrL5EJUtPMQhwIOI9MmGuBgJ3y4DgVrn0qZgBstPsstLOQ2Y6jKNH" "dFiO6XGUo+RqWV5x3Iie50DOAYDAcaT1lVHWYKXKNqREtZNKZnaZjgNzHCUMF7gMACSlPVdy" "DtzRAWDAeSDjwAm5uIcDzqOMXQaAUTW7XcJxCBkHzqgq81WQo4d/v8up5jnm1SAgSla4g6Ni" "okwcBo4b0Wqcq5EQXKtutopye+zkZIDgnCo4jR1zVVQ56haXgWlxlKh2L1UrkCxWCTSgu41S" "Vf24m0oH0qlskL/Yh2z8+8XiNDDTIUN/7DSKepP457Il66jlz2rZXdSMZMhaPw73kkBOdh4o" "UUGezq1U0LmF9+uomPee9hj+fD01+lKociiBSrpi6La6q79Lyarm0m+WjENJylXnboZGyfmf" "2FH8+IfOIxoaERWe/p71nSkAAuAQh8F798lvRFZ4uE4o5Z/82oDGZyY09LPe55/4Yg1APou4" "DosAC4eh7DVlqrXSLkODw26AQ8HjfQMm7wswrAABOLIMgEj2YQAkwyhdaQcCgIgLAThWFTw0" "QNJZKWEFEgGG0W2lO64gMzQ3lHjkjShpYGxbPW8A46LhQNRz/Mo5gQcUFz4tUgA5I9ocOkGb" "lk/IGhM6SfGrOFn3lHm/h3YeckQ7v0fX1cbZpQg8DPdxp3+aNi8umwBR4FDSR7XDidxcsgpE" "uY+EkAZIZLo8yQKOJH2zYBgAmTYPSbTOfKQFeA1MWNyGFSCWrispW40a5atRC0BGyBYeNrus" "kHPooUCHpWSlAZIweYDS5zvMVl24DRkQDHQLOApXBiQsdxqBub6KVu27BSDJ4y9Q/MhTlD3/" "ugkQx+yrlDnzIuUHDqizrnCnBwPEHTokAbkE5yJVrrL5n6SM0UfJxWBQ8GAYzb0gTsM5/YxZ" "vgJEUK6qXH6dKlZfMfKOlxkgzzIM7iO77352Ig/z5/upgp1Gnv9BdiV38xf9Pipbepah8pIA" "BC6kNPAk62n+3ccpf/pBadeNM+7owFlVDmMg0HoXecZQfWSew49zq3Yb7bi7pFzlmthOab3l" "4kBSuospb0LlHICHtR0XBxwCIJA+u0oLpap8bzWld7korTOfXN5KuY+j0FdDqQwUZB04IRfg" "KJ+qMwDSbABElakAEJStUJYCLGqna2Seo5pdhrPbQfYOm9y7UTddSY2zChSyn64ScGBKvGm+" "Wg4zxNBf8XAu1Y0X8XOlzGtgGBAAKR10SJkKANm5oELyXfPlAg4NkN1z5fy7eVQ5Yqd6H/+8" "P49BkindVBBKU8g34D4AEnRXoRW3aiRN4NHIYKkZSSVX+yYpX8F1lPXHUX7bRmnbbWb30jRq" "o9yD66hmeBu5W9fJ/rbay78zPH6hqku/Sqmq4sI/TZUbECkzIKLBUXpWrWr/o+k2oJugcfYf" "VHDm+ygJPM58R+7T394k16lvoiTgMATHIaBgYChAaAei3cgXDIhP1+iTm5yHhgfch/0PwJFt" "SACiYXLkI8petYDkyA2GxA0TGLpMpR0IACKuA27DgAfKVVooV2mAABrpq1eU8+B9SohXVurK" "GwIR0apRojIgAv0neIhWFUDij16SzAOrdh9SwjKgARcCaXhsWT4t2hw+KfDYuHyMNgWPK4WO" "0dbQcYbBCdqKuY6VY8Y9H6fMQUFcYfvnsSlxHndMTgk85LIoY/5DASN80xW1UWUrlgJIBB5W" "gOgpcz3jEb2qjEPnHEmLEyLc7QGA4GTdjJsyDws8ZPZjzCxhqfBcXQSlXYc149DwsJun60ba" "dDFprjus5EiSQC+lzxymtOmD0qLrCqkraJ0yKNgl0IB03gE5A4fFfeQGD7NjUaWr5NGnKHHk" "MbLP7hdoAB4AhyuI+81flzvMcYYV4AGIuIMvsyt5wXAah6mIXUfGxCOUPvogZU8+RsWhV6li" "5QCVhPbzF/5fZK1aeU1UwbAAMApnn+Qv8sfEdaBshTVnnKHi3WsCpGaF4RF4hgpnHqbCuUcE" "HiVLT5Bn8RF2FvdK2Qp3kONWwFzjNsD4rhLJOeSYkb5KYwhwN9mGauSgQ5SpVNahSlX5DA2H" "t5ZyvXXm5Ljc2dHhFuFkXLiOwskmmeXQ93DonAOlKTiOgvFqmdtAiQpzG7gFML3DSWntOdKG" "W+avlbOpSnxVcuMfpsV1zgGAoEQlZar5BiXeV7LryO1hAHVnywm59TNV4jrKfEX8nEfVkyUC" "DQgQgeNA9xTAgcMNscf8RvGgnTy9mdKOu322TOCBUlXJYBZVe3NVmSpgaLGc9iyU0a65Qmqe" "clKTP4ddQhY5D2+hbHYTAAgyDemoat0qnVTO1o1U1BPP8MiixrEMqh5OoXJ2IWV92yT3aBhP" "p+KereQ8sJ5c/LPuwxvI1baeKvpjKPfQnZR3+C66rYqdR/VFhsf5tTnHzwIMBY6fqfjCz1R0" "/kcTHFKeMlYtwMKqAgnKIwBxn/67yPrsOvVdNDAEEF8a5aovFTg0SKJA8bm5t77T4MgRfXIz" "LCwAsTqQW8EDkhIVg8MqQAMgyb4JHu+qrqoj7xrv1HsJzFeM8By5hwGQDOQdhtKX3xClhJUA" "kpTQZUrmNSl0iZKDDILABdmnGCWqBAYOIPFH8AA4ABAVmF8ypfMP5T4AEVW6AjjWlrA2hhQ0" "tBMRkDBAsG4IHaX1DIWNDIVNuNODn83rafl543yQNswvCjyk8wqlKyP7EHiYIAndFJoLPEIh" "S9fVvAGQeaVbuA6rEJiL+2BobJ7so83jvbRpopdipgcpaclnug9r7qHhoaXgEXEdawGSveZc" "q8j5VkMMDX0syYAJDmdQCd1W6f4DIpSt5FZBHFPCTgMOA5mHQGS5k+GhYCElq+WIcJcHrp5N" "9T1FzoWXqTDMAAkeklsDbf7nKX/pZYGHAsgBVaqS8tQhdheHGBSHxXHkTD9JWeOPUO7s0xKU" "w3WgPTd7/GFp1QU4dM6hSlYvCTgk8+B9WeB5diPsSHz3kGf2CaoOv0g1oecpd2IfOcZ2kX10" "NxUxOEoCDJ3g47x/iFwMET3X4TLmPNIHayTjwDHrGAhE1pE1WE2J7aolV52Gy/BgeSZ3kMff" "Ijf/6ZwDAjQyeopFKFfhkENc4oScA2Uq53CZ5Bw4qwqlKmQbOiAvYVAAIDhWHZc5IefA5U3l" "7Coq/HWUN1BAjk4HFY2USJkKsBB4IAQ3cg4pT7HTqJ+ulpmOsrFidiPl4jIgnILr7M4QiKAV" "VwGjStwGTsZtniuTllwtdE9Vj7monld0U7XMlAg8SgYzqIzXnfMlknO0THvYdeRJWapx0k5N" "k7lSqqrz2ahkIImdRgwVdsVRzWgGlQ8msrvYbJapCto3U4Mvk0p749l9bBH3UdITZ+QcadTo" "S5PyVWH7BlFVfzyV98WS6/AdlH/oz3SbDsirLvwqJSwFkIjzUMD4SQSAFJ1nZ3HuBxGeAQr9" "bAWHOI017kMDRENEAeSbWwIkl4HhBBR4zcWz8T7vxFdK/JlT9JkBi88NgHxuwkNLw0MDBKsV" "EmvhoUHhsOxtEpTfYCC8b7iLG1GQMMFx9B1Z01ffMXSz89ChuRaeU0NviuA8UgESgcdlBobW" "JVFi8KLSMu9XrpgQkVKVsdfS3VY6NIcDUeWsSICuso9IyQqKXT4jAIH7kPKVsQIkAAeAsYHB" "sT54hAFyVLQO++AKbQgsmzAxu61wy2Bo1ZJ9hG++NMrarmvMfSh4RLKPxOUFU3IsSTgCENxp" "rifO9bBg8tIkbZ0YpLuG20ytG2lnmPTIxVD6iHYNERMcQSXdtquzDrNdNxjtQuQyqMAApc93" "RQ0ImkOCyDeWjVsF2W0AGihhqWnybjPrwGm6OBDRudRqdlppgOjrZnEkuwYIjiPJW3pdLnyC" "83AHXpeDEJO9D0tg7kE7LsOjgJ0HVLKsAKLOsnpdhOyjMKDcRkXoNWnLtY89QNmj90vWgTkP" "gKIixD+z+KysKE8BILWr+yXzgOsoCz7D4PgL1fN7ACTHt5vhsZMcIzvEeQAgnoUH+f0uyvbu" "iAKIDAhOItvAAYYtMs+B0hUue9JXyWayCyk0OqxsQ1WU1VcunVZy5MjsLvOYERxuqG8ERNaB" "DivMcyS15pjXxsJ55DIkcHFT0UStuA+UqCqMFRBB2aqSAVPJMMClTp7hYsrBQOCwRzIOVaqq" "liNHcBIuQnLMbpg5x0KtBORNi3UCDwADJar8nixpycUAII4ZqfK6qXDAwUDIldIUwLGTnYUp" "fobTAEB2MmBw0KHKOrJo10IpO44SqhjOosLuJGnFLRtg5zBhl7IUso4ahkO1N13gUT+eSZXD" "qRKGAx4oQSHngPPIO7Se97FU3B0v7xvGklXWMRBLnq6NVNqzmRqHE6llLJXqBuKp4PCdEYCo" "ktUvAg5VrtLwMMBx9kcGBGDxgwEMBQ6r61hbptJysfIZFHnsNLCuFRyILlFZS1baVZglLO0+" "GB54zj3+ZQQYvM8xXYeCieO4FRx/E+Uci4aH7djH5rMGSJTTYJehhWfAQytj5T1R+up7Agwt" "AAPgkL20516XFl0NCoEGO46U5Tel6yoleFWBY9kQuw+AQysKGiy4kCiF+F34sgAj/siVNblH" "NEA0NMSRGNkHHAfeAyIAxRZcFsXajFsHQ+xCwifEiYgDCR83nceGAAMjoBzIOgbHXYEw3bEY" "4jVEdy4FWcuyrl8K0Wb+THKPYNBwGxogN5et4Drig9Ftu+I8wgocyeFI6SoyYT5nlq5Sw3NG" "u+40Jcz7aP1Yl0BDAeQw71vpjsGDFD8zoG4ZXOM8ouHhMwNzZB6600ruLLfkHnhGmSprocuA" "xqBaQ8ZR7NqBhNSFUM7QmrZco1SVOf2qhOU5DBDAA7MeeYsH5eh1rBKUGxCRi5+M86sQmmuA" "ZPifFoDgQESUsfAuy/+UnLKbM/usKl+FIwCRzAN5hznT8Sp/mT8i8EDWAWBULL8oZSsHP+dO" "PsCweE4gUhNWTgQrylYASu3qi+xCXqDC2QfJObqL8sf3UnnwCdZjlMdQyeirp/TeOrkZ0DOz" "jwr8aqpcDwhCasZDHX6IbivkHM6xeilV5QzXyIwHylSYIFc5R4scqw6p52Y5Wh2lqsLxenEe" "CMUVLJrYbfD/ho48SmdXUuCtMABSJ05D5R1qUhxnVAEgKFdhjxKWPrcKrqNg0EXOLjsVoUzF" "TgTuA2dUAR6NC8p1bF+speaFGilXNc2oY9WxokyF03CRceR2p1FBb6a04iLbADAg7KE9CNAZ" "JMg7dswxwCYYNpP5dPcSO5bpAsrviiVnW4wE4JJzsPMo7U+UdtyC7ljppMKxI8g5GvgzlKng" "PBCQ144kSdbhPHAXlbHzKO/exmC4k2qHtgk08uA0DrNTabuLAZLAAEmhFm8KlXZtUgBRWYd2" "HQyQs79QyblfqPjsP0VFZ34mz1klAKSAnYb7LPQPEyjyXkpVStYylQbIWohgr5V78lspU0Hi" "PBgSkN6LCzH2AgtD8iyO4/NbAiRSvkKpSoEiApC/imxHPr6pRGWFB0pVmSsfKGl4HHmf0ldu" "CDyU3olyHLKGr4s0QKRFV7sOAyAaGNp9QChZmQAJXvqPANkWjOzhSKwggbatXI6CCEChIHIx" "KjwHPKAtK6cUOLTjWI4E6GsBIu6DdVdgVeARWUMCD8DkjsUA/Wlxif68sER38n6DOW0eCc71" "0exRZSujdKUvh9J5R9JNJ+taATIjwTngobuuts17ad1oJ4MjAhDozqFDtHWyx+I+jGNKjLKV" "mvfwCUBM92EMCuIuD2t4bp3xiNzlofIODAjiUERxHyxnmOER7hV46IxDwnK4jZA6XRfgyDEc" "iCvcYYTnj5Ntar/MeWj3AYAAHgCH0kEGyUFZMVmO03QFIOw80nyPUgIDIXPyURkQVJPmr5lT" "5sg9ULpC1gGAoGxVyq4ER5QAEOXBFxgcDwlA7GP3UOHcE8qFhF+kooUnqGD6EaoIPs8Q+Ysq" "YfFaF+bn0LOi2vAzVBV8XCbL0wZqKXOgTmBStvCQAASheeYw7iLHHMdeM0BHycqD40eM0hUA" "4hiqNuc5ABCBBwulKgz+4RZAgclEo5rnYInrYGhAgAWGANPacymjPUcAooLyBjmzSkpXk5VU" "NaMgUjtTLxPkkMo7GuXYkQYZCoQrscmhhsg49H3jOucAQHBtLASAiOsQqZwDuUbdRCHV+T3U" "NFsiGYfVfQhM5pQAEWQcyDr2BSoFHnsXi6nFny8uo5xdRHHvNqoYShXHgQMPdUdVIQMGAGli" "eDR6M6mJ3cj28Qx+zpRSVf1IsrgOF7uQ3NY7JCCvGUwQV1LMrmTPODuvtnVU2xsrACnhfRE7" "kMruLXSbdh161fCIAseZn8gNGeDA6mJQuKKg8b25KqlSlYYFIKFAEdlDzhPfmIo8f3VLYGg5" "jn1xk+xHPzdX0bFPTeehpSGiIPGxKNPYZ61+JJCwug4tEyAsAYYBD8BEA0SBwnAbKwY8lt9m" "cGipOQ8NDhMYoaviQpKDl6V8pTMPUeDW8AA4oPjA+YiCZ5XYkQAccauXKXblEgPiggGLCxR7" "9CLFHDlndlwpoJxRQbkhKzgk8wjpspXhPCzwWCfQWJXylYaIch4RgEAAiNbtC/O0bmmJNgcD" "cu6VnK4LeASVAI6EcFANC4ZvnXngOckSoEMAh1UIzhMWRhkgHQKPO4daFUBGDsqKO81xPHu6" "5YwrOI8IPEZFOJodg4Jp830UO/YabRl5mWJ8r1LqfJflOtpB8xIo6bQygJE+1yoQwWyH07hN" "EGUr3CQY1aprACSfgYIsxBloo+ylg5TLjiN7+mVKGXuacuZeE4DAhaA9N2vyOZn3ADw8clsg" "w4NBIMG51vLrIpvhQOzTT0tQrrOP7NEHKWecv/yXXzHdh9q/zIB4lfWyCEODcCD2sfskMC9e" "fFpKVwWzj5Jj9G6RZ+ohhsZfRLXLz0kZq55/pmHlBapnmAAirql7KHOomTL7G6hw+m6qCDwk" "Lbg4xwrhOVp1I5c87RABGiUME91Nhfs4sgbLydZfJjkH4OHy1VIqLn1qzZN2XIGGMdMhZ1cZ" "4NBC5gGIYPhPla7qpWyF+zkyOx2UP+gWeAAiAIaW3EVunl1VJ9fE1kxX8GfVUq4CROTgwz6H" "nIqrAnIla2COFt1d8xWmpEV34Q+0WEZ7lnCibqmhYgZJCe1hJ9KCsHzCQQ38BY+SFdQwkc1O" "wy5Oo240kyoHU+Q4kuYxG1UMJEv+kX94k7gQzHLs8GVQy0Q6VQzGScbh6VhPdew06ge3Sc5R" "1R1Pjy14KB9Q6YuhonYGzeE/UwF/Vth6J90Gx3GT6zj3TylTaQk4DIAIOE7/yGD4PmpvVd6p" "v0cp9+R3hgxoMES0ck5+Q44TX4uwhwARExYnviT78S9E2cc+l9UKCv3OBAfLdvQzsh37hLKP" "f8rAMFZWFsMj6+hHNwkQyVz5UCTAOPIhZax+wFLwyAjfUPAAOAylrbwb5UA0QAALvaYsX7MA" "5G3jXQQaUroKqj3gkWJkHXAficFLhqIBouGhAbKN3wtAlhgKgTMUu3RaQBIXAhwuCDh0+656" "Pmc6jq3hc0a56qTpPEyQsNsQx2EBiAaHwMN0H9p5hBkcK4YiAIHzuH1+UeBxBwAyt0D/MzfL" "z7P8+RxtZKBsCSwpkAQClnvNF8R5QLp0JSfrAh5aRrtuyrIqXaXzs+q6mpE5j5Slcdo43m1k" "H620zntI4LFhtJ2SFkYsJ+1Guq30tHl22Jj3CA6L64jxvU5bvftpM2vLyEu8f4UyFrolMNcA" "MSfNjbxDJDBRJatc3mNAMG70GbIvdUYfT4JuKwDEyD0ciwdZB/hdq8x7aNfhWjxE6RPPUcLI" "wzJtjvkOj3FjIC6BguA8cEAiDkMELAANd2C/DBBijwMRbRMPy2GIKFVhzgPgKAu+KLMepYHn" "jfB8P9UAIiv7ZUAQHVcQylVVy3+hnLF7Vfvu2B4DIM9TdfAZ8sw9REUzD7IreZoh8qyCCK+1" "y09S6fyDVDL3AFUGHjUBgolyXPSEbisAJH9iu7xDq67L12jCQ9pxjbzDqvyxGhMgtt5idXKu" "v4Hco1WUO1LGsKiRWQ4rQCqMrivkHAogtZQ/7JGhwKKxEmnPrTWmyct8ZdKi27QAiNSb51YB" "ILKfR5mqTgCCEhWuj4XTiEDD6LSaV8G5nF01r0tUAEXlLaEBxxFRicBj11wRtUy7qHHCKeAA" "MGT1ZUv2ATWxVLkqk5p5bR7PEuF5O/9c41gWlffGswtJo2ZfOjWNJFGdN5EaR5Np+yjepbAr" "SRCY5B28gzyH4DjuoqbheHIdvF0A4m7F+zvoNoDjViUruI4CXiHAw3X2JwWLUz9Q3mkl7LXy" "Tv4jSrknvo8WA8R54lslCzhyGCgaIGtlP/7VGkVAkn3kMwULAxSABt5BtlV+PvZXiz4RKYAo" "16H32mVoYGDVbgPgiIJG+P0ogETrehREAI+1AFHvLHmHBR5wINGZhwLI2pJVNDx4v3TeBEh8" "8LQAZOuSWmODp6XDCuDYuqomzs2Oq1XVdWUFCPablk9FAWRD8NhNZSsdmiP70PmHdh4ReIRM" "iGh4aAeiNEt/mp9huEzTnbxfvzBHWwPz/z9jb/3d13mt++YPuffse04bBpOYWRaYGSWZZKFF" "ZqaQnTjgoFFMX2aRnaTZbdM2aRtomBna7nP/gXnnM19Ya0nK2feHZ7xrLTnpGOkY+viZz5zz" "paxY2FO6MqG57bBywQPgULlHyOYepm1XBgWjY5QT7KUFA8/b8tWCvmcpx39TQvQSPeth5jxQ" "sjIAUV1Xalligf8FFzgeFaX1naecocdVWB7VW3T1mhIz62HWk5jMA8IyxOLRx6TjysCjKvw0" "lY5fYGfyrO62uizgWBp8Qs19xJ2yFYJzbNTFOnbcICgOhOFRG3qEykaOUTm7jFVxFZ4jNAdA" "vLogwoBgxeAh6bgCPFCuwj4rBOgYEgRIsKYEQ4FbZW3Jwzb3qGe4ICxfFzxGy0e6aeVwN20O" "HxfHsSF4iGoHWqi6D+WnLgEHHEg9O5D62DF2Jvy/FzmkAMLnKlwn279L8g51R7m6twOT5wjP" "K65u9sxyqClyvbdK5x9oz0XOAfexon+7uA+UrWR31eUaWtG3UXINNRSoOq0EHj6sY6+nzT7l" "NjaPbZX9VYAHVpCgZLV1ZAtVv7CUNg5sENexywUQlKzkjg6GB+Y6TFiOczZA4DpMd9VecR0q" "LG8Ob1FC1hFWIDHQEJBoeAAcTf41Mt+BOY/6gaVKcBqDFdJ1pRxIuQgQUfCopEZ2JChXoWzV" "MlZN+wLL2ZGUKYAMF0vese1GNm27lsUAKZSgfA/DpO5qFm16fhFtfmExNVzLoMb+PFr15L3i" "PlDCgu6wJSu4Dl2yMtBQ+jfD49+0/LVfLChqX1FyP9fc/vG/VfWtHxgM3wo0HHB8q/Vr0HBU" "Of2Vgse0chlyTih4lE9+JpL3yU9E5VOfaFB84pICiEBk4kMXPBRASmY5DUDEDRJApHiCz8l3" "qWjCCxCv23hLy+s+jAMxyo/92ZavHNfxx18tW81XulLO4zafr1AGS+DB7xnhW5TGSo+9Im4j" "I/WfchrngczDBOYAx6L4bYbFK+I6zOzHnLKVSw/EvQCZDxzGfQAa97ngAYkLYYi4tSDso8WR" "gFxRi1sFsaYkP6omy/OSDjiU/Lp8FdQbdsecuz1iI1QUUSvaAZHMsWui/FC/vdujNDkoz+4d" "V0amhFWeuEH5vssCEDc8MvoepuzBx9iFPE/F/qeV20hdkZXsZjFijR4OdADyst2qazKPFckX" "qNx/gbJ7T1JF4KK6jlaAcZn/3CX+dkG39j6lhgUlLL8kO65M9xUcSOX4Gcrv3S+lKrgNwAOO" "A8H5Mv9ZPWmubhDcyA4FrmNN5CytjZ4TgMBxIDwHQFCqWhM4IcDAoCDKVyt9/Es/fsYCBBIn" "wo5ka/SkLl2dswCpHWhmV9KpnEf0KD93iLaFD7NLOSLw2BzZT1vD+2lToIu2hLr4vZvdSZt0" "WiEoz2WALL2+1QIE60jKXl4rd5JjFYkJzu1dHSO7aCPDBfCAaq+tk7B8df8WcRkbGCK4hxzr" "SNCiu8W3QwACbfVtp23+OjkFHn5Vqqob5//9vjV2vTpgAWhIh5V2HhB2Vpmw3M54yGzHNgsP" "p2zldFY1hx33IdAIaOcR2SAuBJkHnAfgIe25w7W0rX8p1fUzRPqq+GRwDFTIziqUrTDTsYfh" "sWe4gsGhhGfIOJHGgRIpXanyVRm1ss5M1VHzIL4XUdNAMTVcz6aNLy5hLaa9DI7moXxqYW16" "7iFxHmuevlc5kLWv/+954SFuA9BgRwIte/WfjrvQwICzcMNhPmCI2wA4Zr63WjrzjZW7dDUb" "IAoYjiqmvhQZgMyWgYgXGI7KJj+28DBlK+U6PpgHHu8zLDQwXCpKvSfgmKu/U2FKuQwFE515" "8LeCpNd5eACi23QLon8WmORF/0S57ELQXQU3IkF53AUSdhxuAR5ZAg0GSPi2PrUDEc0IRNKi" "txkkTquuk3m8IloYYVcRmlAlq/jMnOxDOq5Y7rKVgYfjQGIMhZgHHgogBh4OOJR8cwDyUGic" "HgyO0YLgKC1ipYfH2JUomEjJKq6FNSXhUcoODVJOeEQGBN1rStSCRNeuK/6uQnN1OZQI4BCA" "MChSAyLpuHKtKkHOURh43gJEXMjNRwQgWf2PU0WUXUXkRQWOhCNp043rjCN5RcpXkJkwl6to" "k2qrLkLzkrFHGRhPyTsAUh1+kkqGzlHewGkqCzJEGCQYEMSshwnO12gh94ADATwwbb46/ri4" "jWX8DQsRcZvgysA5uQwKJSzMe2zEvR+xR+USKOy4ggNZEzytHMhQD22InBFAIDCv7O9kV9JJ" "a/xHFDzYkSidl44rnA2pcwIQhObrA/tpNcNjW+wo7Zg4RZsDB2jZ4F7RRl8P7UwynOJwIQdo" "a+wgbY9C+7W6aWOgVQYEkXWsHNql7u0YbaSi51dTweWVVPHyBtmYa1aSSN4BgIzuEHBsGlNl" "qg0j9XJPB54BC0BkZe8GKrlcScturFaug92HAUidbMTFAsStuh23wbOCRIABeITrLUxwjayB" "B5yGgYhyHc6QoGrP3SLOw91pZeEBkLDjQGtuS3i9SLKOkOq02jFUy46jWgR4KFVSXS/Do6+M" "dvSXC0R2GtcxUkl7RsqocbRczj0jJZJ1eKVcCKBxNLyWAVFKTUMlDJJiahosoGZ2ItuvptGe" "3hyGTAG1DOfRjuvptPn5BQyS+9iVLKY7VjNAIAMOnHAcK151wFH7yi9axnH8YgFRfesnff4w" "123MfG9/5gHI9HcWHpW3FCzmcx8CjRmXLEDM8yxwsMqmWNMKFo7j+NgDDwWMjxgSH4rwXswO" "BM4CTsSBh8t1GHhYgPxd8g8DkMLU2woUfCpovCkqTL2lzoTqsJI2XYAj8Rf+W7UDDbcMQAAP" "T/4BaER/Z5+zw68LPBREtDQ80sLsRkTsQEIMkeAkLWYtiUzrCfNXbVD+UGSS7hoM0m97fXT3" "aIRdwCQtis4KzgGPiMo9HhIlPdmHcR0ONJzg/L5waBY4vPB4MKBOlLLwDIA8GByhhwIj+hyS" "ez/MPecASdp4Hy3ofZkevPE860V6qO9Fyhq/IQAxk+YCDbOWnYXJcwOPsuSIDczLU0OiyuSQ" "dR4CEN1tVRa9QplDF5UDATx6+ew9T3mjl+wVtAYg5vrZnIHH+Jf+swKMFbZ19wW9psRxH3J3" "eULNfOAWQblJkAFSNo6ZkOMybV4pLuQiVYYep5rQBWnNlbAc2YfOP1C2AjigtTL/cVF2XhUN" "7BetCJ3R+ccFWc++fOwErWPAACCbZSXJowKRjTF2JAwElK0AkFX+o1TR1yH7rOBC4EA2x9jV" "DPfQMv62MXJSsg/kHNDu1HmBxq7UKT7P0O6J07QpdIBWDOwVrWewACB10SO0Yngv1fTvoDXj" "rQIOqC7WQ9uinbQp2CZr1hGiK4DspuIX1lDhsyup8spGcR4bGCrouqpm0KxiUMjyQw2QTVin" "LplHgz0BCjiP2uuraN3wRgHIVpSpGB5Ys479VYAHhPKVDcvlWZesQvXWfcimXOQaYdVpZTIO" "ByDqHSfKVu6SVYvutPJARDsQAxA4DwwJIuMALOA4Gvr188BSC5A6BghUzxBBcI6MAxDZM1gu" "DqRpqEzAAGjsHSkXcCiAMCgYIHuGihge/LMhhsRQIYOiiLr91XTp1d3UPspAGcoV7WBgbHjm" "ftbdtPPGYmofzKE7Vv3uv6RM5ZSqGByv/FPAUcMuxKiWf66cx88CkCp2IlW3GQ6v/KjOW78u" "lKgEGhoclbe8AhwEJLe/8QKDIVI+/aXW567nLy1Ayie/YGh8ocAxpSGigVE6xYCY/MBCww0P" "OacceJRMKoAU61IW4FEEeEwogBQl3rUgMZAARBQ8/uaSAonJPPITbwksjAASQEME95FUpSs8" "S+YReYMB8QeRLVeZDit36YqVFfqdLVcJSACP0Cue8lVaeFrAkTZLAIlxGoDHnb1j9Nu+cTnx" "biACWCzUw4KO+5hwhebe3AMORADC0BC5cw/JPHy6dOUXYIjr4GcI8FgQHHcAEhrmc4jPUf4+" "zI5kmBaHhyk9MEAP3Hye7r/xnADk/muXpVUXLbs5/DOUsEpT455dV3K3eXJYHIcqXQ1oUKiO" "K+U++u3EuWdRIkOiOPQiZfQ/JhCB+8gZfsIVnqstu5gyxzJEc3ugDApq14GBwbLxJ6kqqGY8" "AA/stEKrLspWKwQgL0jpCnMe6LAqHjpJVb5HqTYMeDxKhb5TlH6lk/J7D9EKdhCABq6fxcVP" "q+MKGtiqq/KPi7KiHa27FcOHbXiOq2lL2FGU9nVK/gGAbGQoIEAHRHDKRt2Es1l3+dghO/8B" "qGxgV1LbrybNV450Ul1c5Rwm69jFrmRn8rRABGqIHmXH0EFrhtupLnyY9iROittYerNBLoOq" "vlFH2yJdCiCR/fJcz9oW7mBINDF0msRtwHUs76uj1UPOSpKqKxuo8JkaKn95tawnMeBQrmOX" "SOChHYg4jnHlOsy6dQAEZaotI5sEHgIL102B5i5yQMMsQDTlK3enlYDCJVzwpOY5NssCxNlh" "ubTmMkxMi64AJKiGA6Hdoyus29jeV6G1VKBR31cpsIDzMGoQiCihXXdPX7mE5ChVidMYKRWJ" "yxjWYmDgBDSM4Dag/b4q2jdcSG0j+fyex8/51ONjx3M1nba8eD+1D2fTHStf/38ZHv+bwfFf" "Vste/beohl2IGyKARfUrP7v0owbIT9aBGLAsvfW9nFWvMDRufyswqJz5zqtbs4HhyFuy+kqg" "AVAIPGbM+2cugGiITHyqxAABPEomGRZT5vkDDZWPtONQ2Qcg4QaIgYeIweFWYfJdCxADDPc7" "4KH0pnUabrdhcg9xGy5wqMBcgyPihOQCisjrokw3PPDNAkQpw7qOVzRAptl9TImWsAxIlgQm" "aIEPV8kyFPxxuvOmAsdvbozQnTdGRfeNRQQcpk1XBebzBeemZBXzlK0k8xDnMTfzADiMjANB" "6Qrw8AJk1MIDWshOBHegPzB6k35z9Sm6+8rTdN/1y/RA72W6/+Yz9GDfZcry35CyFe40txPm" "pmSVcAAiMx7JAes6nNxDAUQcSLJPZj2gmtRNKVcV+56lEv9luyhRwGEk7uKKlipVASAoYdVE" "nqP8wfNUMvqYmvcQF3JZOq6caXPXjEfsWSvsuaoKX6CiEQBkH6Vd20cVwXPSgQVwrGS4LAud" "F/exMaGuoZWcI65Cc8k+AJvYI1Q5cohKB7oEICvGj6syVvS85B8I0eFA3PBQcx2PUB2/o2yF" "YcH1oeNUO9DG7qFJASShWnURmq8aaactwcMWIHAguxkqewCTxAmBB1QfPUQrBxup8sZ2quqt" "Z2j0CDjWsitZ1t8g0Nge6aSGcCdtDrTpwcBGEVaUyD4rdiXLbmyR+zmQd2yxrmMnrWNHglbd" "TQKVHTbvENehnQcyDyPARGmbdFupsHynCs4Ds11HvSv7cANE3QrYFFRLDwEMuI2m/1OLroaG" "mvFQbbp7fau166jylqu0AA+Ve1RYeOyU5zIRHIgFSG+JdFYhQO/yLae2sQoGRqk4D7gOgQaA" "MmIAUiACQACMjhF1to7kUje7ketvdNPFqe3UAaCwK7ljxe/mwqP2lX+Jql8xLkQ9u+FRyaCo" "ZEBAChoKHAYeblm3oaGBs2JaQQVn+dQ36lkchwMRwMHtOhxQzK/SyU+pZOITAUhp6hMFDz4B" "EONG8M3ARDIPC45/SHnKQATwACw84Ej+OkAKkn93wUMBxAuPN7WckpXHdWhlR+eHhwBEuxB5" "Dv/Ok3UAGmlagAe0RIPDlK8WMTgAj4X+SQYIg8E/QQ+MhOk314bptzfYgdwctbprNEQLIhMW" "GAYgTtlKgUOdcQceLnDgvF+cSEAAgrZdAww3RGYDBPmHgcfC0Jh1H+JA4EjG++h/Xn2G/uPF" "i/Q/r1ykO689SXddv8QgeZZyA30WHgoaoxYcAg99MRRKVqrryhucS+6R6LWDgkZqWeJ1NVGe" "UK27WNFupsxlUFCgoQSIAB5SqkpcEZjgKlp0XznLEp+m0uHzVD76iDgPs1HXSKbOY+ouD+Qf" "WJqYO3CYcgYOCkBqw4/LcsRi/lbYd0A26xp4yLxHTM18AB4b4mpl++rwObnfA/d6oNMKZauV" "vmNU1rtPrqSVez4YFAAIHAd2XaFlF+AASETxs7TOjyHALtoYPColrPrYCVo+2CJlKjiNXQwJ" "AGRn8iQ1xI/RzvhxBslJEQCyK3mMtoW6af1os8x5wJFsC3VSzfU6qry2hZYBKuxAGqIMqPA+" "uYMcEAE81LlHpspRssKEue2wYpeBtl3cz4GhwM3afchgIANkm79hFjS2eQCCezx2h3cJQIzz" "MLAwYbk78zDtudZxsFqt29gyt0V3FjwMQJTzWEt7xlZK3gG3oUpV3swDZSo4EOM4AA41HFiu" "wDFQyu8loj19pQoeWu2jS23OYQDSMVZpwdE6ArehHAeg0T6UJ5Ln4VzR2eRqOhqspn0jOdTF" "ELnDlK1qX/vnHHgYgOCsuq3KVpV8Ah4Vt34Wld/+WT//yLBwVMHgwLdyhsVslWlYACbl4i6+" "EohYacfhVimrhCFhVDr5uQiuo5hPJQUQo+IUO4/kxyrvmPzAuo5inXNATv6hQZJUAboHGMn5" "AKKUzxDJY3hAuYm3RO6yVV78TZEBiCfv0K4jJ/qGSJWt/kBZDI9Mt9PQkvZcBodIl66U3ABR" "pasloRkLEEBjkWhKpADCDsSfogfGovTblwdFv7kyJC7kN+xG7g/E9aR50gbmXoAkdGCuSlc2" "+3DBw3EePpEbGkZSvmJ4ODKuQzmPxaERWhQaYrc0KOfiMC6m6qO7+16k/2B4/D8vX2CIKN3b" "+wy7sj4G85DrRkHjPpwJczNlLsAQF9InJ+7zkFUl+m6PanEefaJq7ULQpguAYOdV3shFuU0Q" "E+YKICowN7kHnnEqqcwDp0ygJ56X0Lyg7xQV9p+2l0FBmPVAu668J59RK0vil2TvVWXwEdFS" "dh3VwUepbOwE5d7opvybPQITdF+tiT4q69lRrloTfkTdJoignIECbUg8IruvAA+UreA8AI/y" "vnZxImbmo2bkgCxKxLT5FndgjoHBxBmRZB8TfCZO0YqhVgHI6tF9DIozAo8t/v20bqyVNvg6" "aEfsmAOR5HFRY4rhEjtAdZFuqouygxncRTU3tvK5gx3IPgHINuQhgw0SmAMk6LQylz1tcrkO" "AxAsRkTr7prBjTYkBzgAEQMLdW4TmdyjHhdA+XWXVaDe06JrwKH035WttswjXbLSQ4MIy02L" "LgTXgfUk3nJVhe620q6jf6kAZIdHynEAIEqlatLcBQ90XcnZV2jbdPf2K+dxNrWJ2kfKJCA3" "ABFwABgaHvtG8kTybTBHnAccSMdwDt1hXAdcBsBRc5uhcYsBcltLg6RKg0MB5BcNjx+p7NZP" "FiBG5TM/KFDc+oFKZ74VlU1/r/WtSJyHgcf0V9Z9lFopaBjnUeLRZwKLUqvPqWjiMw88LEBw" "Tnw4j973PuuOK+U83hMVJd6bFyDKbSjlsdsANPL0swGJGx5Qbuwvc8JyAw4oW1p1de4RVxCZ" "40A88HjVlqoMRLwAUSWrJdp1LGZYGIAAHkYP+fiXf7+fAdJPv3mhl/4Xn/exK3kwkpJw3bTq" "Oh1X8TnT5t6cw9V1hczDlK7CTsuuhYfuuFLQMADRuUdgxMk9+F2EzbohgGSAIXKT7rx5WRwI" "4PHb60/SgvErlBa6yf+NehkkvVQYc9azl+nco0SDZHbuIeUqAMRcDqVdh/tmQXUh1A250xwA" "qQi/6Jr1eFlWsyP7wKS5GyDGcVjJbYLPy+2CVVjRHnpS77m6LDcLYsajfOScgMSsJxEXwj+r" "Cj9G1aGHBR7VoXPsRM7IrquykeO6ffei3Gte3NdFJb1dMu+BjisARDqvWAAIbhiUFe3sNjA4" "iFbd2tGDDIsTAhCE5wBKeV8Tg2SfrGffmsCg4BlRgw7OkXfsSp0RbY8coc3+Lsk5AJAdsePs" "BtoYKnto5WATNcQOW4DsjB2hXfHD1MQAaZ44ys8H2cV009bQPv6F38Luo53fO2lndJ+4jaVX" "N9Cqfv6lH26jLYFGBsdutcNKQwTlK9zXAYB4XAefynU0WPfhLld5AbLNAYeGiBscjgP5dYAI" "ROZxHXavlWs4EC26ajBwFTUM1nhKVtt6K+UUaDA8duiy1Q6dezglqxLlOgZKvfAwALEgwQ6r" "YpnvAEga+wqoiUHS5auhFnRdDeRT82ABtQ3m0vFwLR32VwgwULoCLAw8FECyqXM0k7pHsukO" "4zrEbTA4jAxA3MBwC84D8IAcF8LfZ34SgJTOfE8l09/J6ZYCiIJJKbuNkil2FpNfy7O88zO+" "GYDMdh5l2n0ADG6AmHcDD/MMiFhNfKidiAOQQl2uktwD5SoXQAoS88Aj8Y4jD0D+6gGIfIv/" "2cIjN6bLVrE/e8AhziP+Rw0QJeNA8JzhAsjs0pUBhnEiaa7gXAFEBehwGk7ZKukFyHiCf/Gy" "kxgOMEhwFS3/YvdF6cGQCsnvi6bo/tiEByAAx+zswzoPF0DcXVcAiOm8MmWrBQG/x3W48w50" "Xi2A8+BzSWhYBIDAgSwO99OSiILIAyMviRb6rlJ6uI/VSxkMEaNcVgF/L3FBxDgQ07aLWQ8D" "DXt6AOLAQ6SnzLEYUS1HVGWr6vALlIvZkLEndM7xsqwmUSG5yT2et1qVUsE5Oq9kOaIuY+X3" "HZVpc8x5GPexPHyBVkQu0vLY4wIOgYg+q4JnWecZROfZfTxGK/ks7uuRez5qxo4rgGBKnWGD" "62hXB07JuhLIdGBhaSJ2XuHE1bQASWV/G1X0tdKy4S7pvAJAMDhY098qbbpmTYlAREByyiM4" "jnW4DKofg33sSlLHRVsC3bQaLb2jLQKRxtQRBskRgQhcCFzHjliXaFesg4HSpC58Gt3NP9tH" "9dFW2h5ukns8kHVscQFkq3+n1WxwOKWrbV6Zziv/dgWNQIOSCx5o152deUBNJvOYlX2Y1lzr" "ODRAlPNQrqPZt05cB8pU23rLJSCXkNztOlw5R73OOCDZa6VLVgYcMhzIsBCIuKAhwMBwYG+R" "diEF7EAKqcmtgVwGSB619ObRxckddDa2VmACGWjAcXQNZ1EnQ6WT4YHzDpNvLNVOA/K4jGlH" "ZVM/8S90BQ2cUPGt7y1IyqZ/FClQABDfCUSMiqe+naWv+Zf4V/OqKPWlep78QspTgEexdhrm" "LGJAFKY+1fp4rhgQBcmP5LmIz6LUB1YFDIoCHZSbZwDDrTyGhFG+hkd+4m/qjL8tz/m6ZGWg" "kRP/K+tN1p8FGtkx5TRyY47jyI78UT3H/mBPAATQyNIAgfvIMMDQLbrmPSP0mriPdIaGUZpu" "1xXXISfDw2/goQCCzGNBIKXg4U+I4ECg+8fDrKg+GQK4ECoIWCiQIEx3wBF37biKedp11cR5" "cFbLruM+bMeVOI9xWhAe8wBkoS5ZmcwDz4BHWpjPiCphAR5LQv0KJHymsduAAA84kCXBG9aF" "ZISui3JC16ggctNu2ZV1JfF+G5RXu/MOXb5SLbrOqhKVf+jAPHlFl6yueuY71Ip2dZ/HSg2R" "Mt9FKhx+RHZboW1X8o6k7riKqcDcAATPuMdcDQkqgAAeJYPHKL/3gAJF5FGBBcBRHTgrIMF7" "rZzsXCIP0/LgaaoeO0lrow8LPNaHH5W1JZJ19HY64JBy1VkLDhOeQyhdrRjtkVZdhOkYGMSE" "OVa049yeOEl1CMSTp6ghfpx2JE5I2QrwQGhuwvKtwR4Lj8bUCVo/2kor+3cxAPawEzlkAbI3" "dYjdyX6BBCCySwME2hlrEzcC7Yq20Y5oi9wYuOzmRg0QFZRv8+2U9esOQOrkNDMeBhpwG3X+" "rbLHSm4K9G1TV836NTDmlK0UPNRyxG0iuavcVaZqmqc1192ia7qrMBQI11HXX2OhYcBhQ3J2" "HiIGyK7BSgGGAw1VrkLOYeABoVTlFgACWBhwwHXs7St0OZB8gQecR+tAnkAEau3LZ2VTS382" "tfXnUAd/OxlaQefDq6ltIJv2DWRSB/+soz9zLkCqXG5D3MTtn61Kpn/gX+QAxI8KIDM/eqRA" "8cP/WZPfWs0GhmjyK48AkKIJA4zPFCwmPxPlpz6igolP+fzkVwFinEd+gpV8XyRQSb4vKhCY" "fMCQ+If8TL4JPBRAcpPv2GfjOgxIcgUgf9PP8wMEpwGIAYecGhpGmRoYWa5Jc3kHPEwGwvBI" "0/DIsOWqaU/mYbKOJShVjSXpnhs+0YMjcXEfRui+eiiQoAd8MQ0QhsdoREMkKLpvLED3+bGG" "ZHbJKjZnQaIN0F3uA6H5fVKucsJzAxAnMFehOUAiAjw0QIzzsAARaAwqiAAcQQUQAxEAJFMr" "Q5eyMsMMk6CCSFbohgVJidzvoS6KQomqJtHruhCq1wIEd3xgVbuBh/tiKGzWnT0k6JYsRoyo" "jbr5g2cFIOpej8uyGHG55ByXZShQAvPkMw5MEs/oOY9npGW3mAFS0HdAgAEnUhN8mAoGDlL+" "QA+VscuoDpzhb2eVQqdpWfg8bYg8ZgcF1zNUyge6qexmh9z1oW4YfJhW6lLV8rEDcqe5gQcE" "x2E36ibOyZJEtaYEQ4GttC1+gn92gt1IB7uSPbR6iH+xx48oeEyckFJVI8OlUXdhNU4ep70T" "x6ku1CPwQIC+O3GIv6kS1lZfK20ea6bGeA/tjHcrcAAYLoDsiiiA7Iy1Ul1gt7qbPNQk18wC" "HjYo52esJNkmV8nuUNDgn9Wzy6jTwAA88Fzn26K6r9Cm6/dCA8AAKNBhBbndRmto+5ysQ1yH" "mS5HUB40gbkCB4SQXGUdSz0dVsg86mUgsEKF4wMOMFSZyoEHliOa8tSuASfrkAnz/hKRciCF" "dDi4mjrHqxkeBVrKdbT05yuISPkqj6HB8OjP4u+5Ag+odZCBwT97YmILPXurnuGRbdXFP7tj" "6e1/EVR5659KAMjML1R+SwvOY+Zn6ziMABIAQYHjBwsXnMVT31vBkTjuQ30rmvyGf7nDfXwz" "r/OYIwHI5xoc+jn1GcNDAcWApSD5iT4/UmIw5BtIABoMkUIXJAoYGgoc74nyrPNQyo0zQNhp" "ABg4obzY3ykv/lftOv6mgWGgoaTKVo77sADRynI5EVO6yp7Vopuud1p5sg8NEHfW4cBDuw4t" "lKvuvTZKd70wQL99cYDuuj5KD4zGbNlKAMLgwOm4D+VAHvCFBB73jgZF94zwcyBi5zzcLbv3" "maHBWaUrwOMBeyoJPPwMkcCYyABEuY9hBsiIOBCVdcyWch62hAVohAcEHBkuB+KGSFakTwGE" "ZeDh6Arlh69RafS6BOdVWpUumIgDkWWJV21wXhW7RuWB5/WMxxV9l/lLHoC4Q3Pptoo/R9Xh" "S1KyguA+KgMXqXjoNEPkKW9Yzs9r4US0+8B1tHjGTYM1gfP87YJoOQMi/eUWUeHAfgFHbfiM" "wAPrS2qCp9jJnKNVkXPqsigGBibNEZJjTYl0WbHzwB3n5b0tMmmOC6MADqwvWR85QRvCJ6Tj" "ytFp2hQ+Iu26G0MH2XmogcDVwy1U29sgpaptwYMCjl0MCnRe7UwdE5ggLIf72JM8Ko5jR3S/" "wKNx8qhkILvj+2XmY8NwIzVNYFakR8ABN7Ir3i4A2RFtpd187oor4XlvrF3O3eEmAYpkH+xA" "DDyc7qrt1oHUywyIyj7EfWiZGY/ZmYcBhzrrbKnKWYSIUtUWO9dhVrDLhU/60ieE5KbDaltv" "1awWXadk5QBET5YbtzELHo39ZSK05zqOA1PlSihZNUlYXiiT5eI4dLmqhQHSMVJC3SMVAo/W" "gQIFEHYhzX054j7gPNpcsOgZzuc/ny/uQzmQTHosvkYBBOCouK3F8AAwIADEwKOY3UgRYDD1" "owWFW25ozFbhtJKCx3dUMPUN5U9+zRD5cq40IAw8zDfAAm5DQcOA43OBBhyIVeJj5TZ+RXka" "GlBu/D3tSuYHSI4GB8pVOQwOKw0M5TgccGTH/jJLs4JyDQ8Bh1amdh9GGdpp2MzDBOYMDgAk" "fU5YPuMCyC3RIu0+7nxxiO58HuF4v3RZPTAYpoXjqmwF52EEcKjTVb5iuQEC3c1guScQsuDA" "Zl2bfwQDIgDEcR5+Cw87Za5bdr3B+aiFx8KwyTqc3APuQzkQBQ8I8EDmAXBkhueDx00Fj8g1" "VcIK3rDggLKDL1Nu8ArrJSqMXJWNuyhXubMOlK4EHEkFDwWQK3KfuZkyV11XyoWghLVc7jc3" "7btO7rEm+aIFCHKPyvHHpYUXwbjpvsJ+KyxKdJevABBs1oUwNIg2XQidVnk3uin7WieVDB1R" "DoRVys9Fvd1UNNApQFnGwuQ5HMgWPW2u5jzUPR9VQw5ANoRVUA5w4Ira5fxtC4NEVpZIeH5K" "ylbbJ05SfQqbdlG+Ok4bfd0SkmOyfHvksMx7bIscoDUjaNHlX/bJI+I8mgQixwQieIfz2Dt5" "hJpZjcmD1BBGiaqTWib4W+og7U3sZwgwGNhhiAMx8NAggRrZjexhwMgZaWY30igXQGGTLoYE" "IcBDAWSbp4RVb93HFrm3fDZA9oYaPDlHMzuOZu06zF4rd4eVyTlw1Sy0N4AdVuukXLVzeJlk" "HXAdCMgxUS4BuawnUYsRzWyHgQV2WzVYgDhBOZyHAYiCB2BRKp1VeJYuK4CEYWGERYhN+hnO" "46ivlh6ObxRotPUreIgDYe1jeBhwdAyq53Z2Jvt0+aq9P4P29aXRU9Ob6Y7KW/9mB/JfDI9/" "MzD+JSplF1JyS0EEZzFDBSpiN2IgUjypoGGeiybmh4cChoIGTrxDcCD5k19aKUA4MkApSH0h" "yoezsABRuYcpX7mVl/yY5QAjN/GBKC+uJO/Jf4gEIsl3LTgKrOtQytauI1cDxJxZ8bes03BL" "QeMtCxDjNLJcygQ05gGIAYYBiNtx4B1aEnyVf4netgBx4HHb40BM+erOlwbpruf6rQt5oD9E" "D44p1wFgPDgec4EkostWXngIQIb8dPfgGN01NEZ3jozT3WN+gYfIdl8FZrmPgC1XuXMP03WF" "+Q51+hQ4ZsMjMiKC4zDlK7fSIn0KIJG+ufAI9YrjMADJCjuuIzd8lc+X+HxZQ+QlUV7oRSri" "b6WxaxokvQyMmwIQR2raHN1W1TGVf5jVJNiyi/BcrWTXLbvJF2yIbsJytarksrTtwn2Y2Y9V" "/I47PooGDsud5saRGHhsSDwt69kBD7OiHVnHUt8pWho4LdlHdeAk5d5op8wX91D2i41yzzlW" "mKwInaLl/mMy47E+ckblHQjQGSZwHasCx+SOjy1xtc9qne8QVfY1U0X/XpnzUPd7nGbXcZi2" "sOOoY+cBgCDvwFqS+thRAQfUkGB3kThO6/zt7Ep2ijPZHu5haBwWcKBlF8+AB5xHswYIXAcy" "EMCjlX/exi6lZeIQbRvfS9t8e6RkZVyHkQWHPvfyn9kbbWGQNNKu8C7tNOosLOp1YG7ftcx9" "HvNnHwogAgx9j4fbdbS4Ln7a698g0MCtgUqrrOvwlqyqaMdAlSfn2DkLHtKSq3MPOA4E5O4O" "KxWOFzvA6DcqtCdcB9Tcq0tX7DZU2QrhODuK0TJVphKI5NDh8Uo6G1lNbb1ZAowO3XXVMZjl" "lK76MsR9dPZl0tHRYrqj7JV/CzwUNP5pVcxupJABYlTEbsS+T/1gVTCtNemFhqNvLDwMQHDm" "T37rcSECCg2PvIkvrAQeyc89ADFuBLBwoKGUm/hIJO/xjzzgMM/yzu4jJ/GenEZwHI7eFgEi" "2fG/iwAP+8wuJDf2loADMMmK/0XAArkBku0qZbmdB5QV/oOTfbjg4Za7fAUXks6wcOQtWykH" "Mi0O5KHxFN15dVQ7kF666+owPTgSlfLVbHg4ziMw13kwPO4ZGhcBItCdg6MCEnEdrtzDnXmY" "Fe0PBQOytkQyEB2cm7Dc5h6mdMXy5h4jOu9wylamdGXgIQrd9ADE5B6AiAMPJQBEyXEgeSEF" "kjwNkkIGjHIk16wDsfBABqLnPszEOVQ6dokKBh+1ATrAURu7zA7gGYbEcwKQNXEFkZWxZ3WA" "7gwLGoAU9h+iirHT4kDgPmqC5/j9JK3C/EbyklqGKCC5ROtjT8ichwnPAZDC/i7KvNJMuVeb" "aXnwOK0MnqCq8YOUf6OJCm800wrfEYbFaXEhCM0hubYWUEmp62jXBg7T0r420eaIGhTE4CA2" "7C4fapUliYAIQAGA7HQ/J45K6QqDgasGGmnFwC5ZT7I7dZQaYvtpHS6JGmIgxPdLcA5wGIg0" "Tx6i1knA4xC183cApJWdSUuyixoTHRYaKFtB5rkpruHBaoo3i/bG9zJUdsk0eYN2H/UuGecB" "7fBvmxcc7pKVXAJlL4LaZC+CwjPA0ehbT43+tQKORv9q0c7RWqofqplTrpINurPA0aBLVg0D" "5a7cw1uukpJVnypZqZyj6FcA4qi5L0/BAw4E5Sp2GOi0khPw4BMOBAA54ltK5+OrXQ4kU8pY" "nQNZGiLpDI90AYicA4voDgWPf3nhMfMvUeGMgkjB9E+eU8HjJ/3+owAkn8Ehmv7O4zQMPPDd" "/Cxv6lsNkG8ZEF+JGzFOY7YEHhogymU4riN34hPKSX1s5QaKAYnSLAcCxd53wBFTzmMOQOA2" "Yn/zlq9cEreR+KsLHEpo282JOl1YbueR6YKHyAWOjNl5BzsNNzwkOA9oBW+J8wAw0jQ03IOC" "MmU+HKG7GSK/ZXjcP8zOwq/AYYQhQuU8nNKVt2zls/BwA+Su4RHRnaOjdr8V5OQd7DZ0BmIV" "HpdV7QDGwsg4LQo7wbmBhxcgg57A3JatQgO6XVcpQzsQDzw0QEzZSkHkigcg+eErAo688EtK" "/Ixv+fwsCjxHOePPyPoSs+vK3bqr8g8z56FcCIBhcg/cLlg69igV9Jkhwct6z9VztvPKyN5v" "Hn9aAnNcCIUFiWuSF2W+A+H50vFTepOuutdDSllYT8J/fnnkrITmtQjPAyeoevwou4/j7DxO" "8PsxyrveTJkv7aS8q00y67Ga/8xadhzrI6c8obl0WqXO0dbEadoUPaHWtLP7wG2CK0f2UVXf" "boZII20OH5L8Q8DBrgKT5gYgmDBXYicSP8Q6wFA5TLvZmQAga0cYKuxKABCUrSAFkUN8HhRo" "AB5Q6+RBDZOD1JrqFljAaTQm9gk8FEBaHYBoeDQlWpQYItDeWKOsJJHg3LdVZJwHnnfK1tx6" "V2uuWo6IcpW7NbcJG3W109gDsdvYI46DT98aDzww12G253rKVP1L5zgPd97h5B5Oa64bIN5O" "K1W6wvp1acuVs0icBjbpomTVNbxUwAHnAZggIEfOAWjgGSe6rKRVF+DodcpWgMbJ4FK6/vsm" "OhuqFmgAIp0DGfxnF1PnYBo7kJl/CyyKbikBGkXTDI4px3EYcAAQHlhM/eh6dgRAuCFh3nPN" "ya4kd/Irfv6aciY+Z30pyk259bkVoJGX9DoNCNDITn5k5YXGRxYkOfEPtd4XCTxYOdF/iAtR" "eoeykqpslZmAFDyg7Ojf7DOUGWVoRP4qZ2bszVn6syiLAWJgYcCRwcCA0kO/p0wWACKdVRGl" "2e4DAEkPvqqkXQfKWIsZIIsCM6KFwRkpWSl4zMh+K8BDADIeV4E5ylbjKutYoM8HxyMWHqps" "FfHmHcN+FoNjeNSCQ9zH0LDIQmRokO7xjdlZD7ueJKxKWOJENDjcbgPlKguOWaG5AYfKOwY9" "zkMU6bMzH5nzlK4kMGd4ZAeu83/nq/z/wVVbvsoLXVWOgx2IByAWJC8yQF6grNGnaMnwE1QQ" "vEwlwedk4lxWtcdenHfS3A4IavcBLfVd8AAEzmNZ+Cmq8V+U1STSaaXbd9cmn3U6r8R9PCnC" "dbRYU1IxdJTWxtSa9hXB81Q2cJgqB4/KupLVkUdk9gOh+bLwKVWyCp4UBwKAFNxspewrjZR/" "bS8tHz/Mf/4kVQ53Ue6VXVR8nR1B+LidNDcr2VG22pY8I4sS0aqLFe21/U0ybb4FparUCdoS" "PCCXQWH6vC52SAJzAw+cu1OH5RnwQPkKpau6UBdt9e9T8EAHFgMC7bp1wTbpvmpKHhDXYdSW" "OkDtRhM91MxORCASbbHQcMTASDTJqWCiANIUbRQ1hndKqQqOw5G5s4Ph4d/m0hZ1nwduF/Rt" "YK0XlyHwGF8nbqMxuJYBs1ZKVQoca2nX2Cq7fgSnAQmAgbIVbg70dlkpgJhylZEHGnPAUeJy" "HiXSaaUC8iIGR7HAA8F450g5nUtuZEgU6M6qfDlNyaq9L1sk4NDvJu9QbbrZdMpfSVdf20Nn" "g1UCDqiHwXJ0tJAODGbQHQ48flGOY/rf7BL+pTT9CwPhZzkBkdnAcMMkj92G53nSC5CcCQbH" "hAMPIwWPz0W5k1+4vn1J2exAcpKfiRyAfCLKTQAejtNwOxEoK/GhhcpsgIgADyj2tnUdCh7v" "aoC87YGGhUncAUtG/G/WfUAWHvG/2GeAAw4kI/pHJQ2RDO1A0th1GJk2XaMlGh4AhoBDuw4D" "DwMQMyS40D8tAMHzg74UK2EBIue4yToUQFS7bljDIzwXICNeeNw9NCK6a3hIBHjcNTjI5wDd" "Nz7qmTS3AAk7QbmaMB+SQUE8/3cAkc4rAw+07DIk5H1W5uEA5IYHIDl+BZBMAYaCiAGIlYZG" "rgZHXuh5UUHQ6DIVhZ4VFQefpryRC1QZfV53Xb1o3YdbgMequHu77nN25qN8+GHKv3mMKn2P" "6IzjOeVE5GKoZ2idDs3Xx5Vwp/ny8MP8S19dEgXHUTFwhEp6e6i0b78dElwRPMfAOk41vmMC" "DggOZFVIgaTSd5BqfYdpDX9bE8LuqzbKY1eSc6WBqgb30cbYKRkWXBc8IpdCbdcbdrfrOQ+U" "rDDrsV27DQBk3WgHLevbJVJlquMCDDgOmTpPHNHug0HB8Gh0nXsSB9hBHGSAHKAdkQ7aMt5o" "AdKS6GF47BehfAX30WbF78lOamJ4NMaaRFKuYpehzt3iOPbiewzg2C1qieym5vAuOfdGHZDg" "+tk9vq0CDZwCjPFNol3j6y08DDTgOHYDHrpcpVzHSv7zy6VctX2gygMPc3ug13Go2Y7dA5Ue" "aKiso8IDDdOS65SovCWrpn7lNFCmQncVBHhAAAZmOgAQmevozaH9oyVqSLBXdVsBHDLrwa5E" "oDGoylUGIChX9UjuocpXXf0ZdC5STf1vtNK5cDndAXgUSKlKycAjf/KfSgyQPFY+QyRPAPKj" "nLmTP7BQjvpeTgAij78BHqKpbz3KYXDkpLQmvnaB4us5IMlOfaalAJKX+MwDDgMPBZCPBQ7G" "hQAcRtmxD1j/EGXG/8EO4z3+d/J78gP++fsCC3EeE+9q/UNpkv8cK2viHcoUvSvKTr0j39zK" "nPy7FrsSlzIn3qKMFDuSib/wySBJKmUk/uRRevwNSk8wSOK/pyWx1136T1oUeY3/pv6qaHGI" "FWZ4hKb5nJETsBBgBCZFAAicB8ABgFj3MRKl+8ecsBylK8x8OIG5Aw/lPJT7ELnKVg5AFETu" "Hhnm90Gre/n9Af843RcY9wAE2cf94/3024GrdM/QdQsRKVkFvbmHGRZ0A8SdeSh4KPeh2nR7" "nTbdoDqlfBVyylYIy/M0RACQfJSrIl6AIPcAQIwKQ1phBQ+chQyQ9P7zAhJABG4E7bzV/POa" "6LNqxxXgETMAeU53XWHSXEGkml1J6RA6ph63pSt0XVX54R4eFfdh4LEh/qRIXUWrnjfFLurr" "aA9Q7cgxNefBAFnG8EDuUXizXcpYgMfKCAMkrCAiZ1iVrtZET0n3VeHVPeJAVvh7+PtRWuHr" "ppIbu6iqt5Edx0GqT50WNWjJdHniuAXI9tAhWjPSKt1WKE/BdeDcON4qcx71YXw7ZAECB7Kb" "XQWe4TyaGC5NyUMCEXRdGdcBgBhgAB7NEwYiOBVAWhLtAondkUbWbq2dtEe0m93Gbn3upKaQ" "VniHPTFZLivZ0b7L4Ng9voXdw0YrgEMBRLkOE5DvYWCYspUpXdkOK4YH5C5dmbs7ZKJc7iN3" "HAcAsnvAgUdjv1GZ05Y7T85hWnSt8J0B0sqnSANEyemwUgApo3PRNbZVF26jpS+TDowUyXJE" "AxA4DcADwIDw3jWQRt2DS+h0sJyuvLaDzkeW0h1wHFA+oAHHIaDQ0NAQUe8/WgEeORMKHPMp" "T85vBBo4sxkS2QIKfk59JdCwDsPlNuZTTlK7kNQnAoycODuK2Cf8t3xW4iNPCSsrZc4P5Nmt" "THybYBcy9bEoe/Ijyph6n7JmjD6kzOkP7HvmNENn+j1R9pSjrMl31fM0A2TqbREAkjXF7kQL" "MIEyGCLq/IvWWwKUrEkXWCYZJBNvaP3RPqen/iBKSzJYEv8pWhx/nRYnXtPSV9BGb9HCmNKC" "sIGKLmEFFExQynK37MJxmLwDe6+M64DuGvIJQNBxZSTQGBy2zuPuIa0RfFPwuG9kQHQP//w+" "37CeMldX1MJ9/PbmS/Q/rjwjAkTM3R6z5z3c5SvMfUjm4dY8pSs3QLC6xN2uq4LyKyo0d5et" "AJSIKlsh8yiIKAeC08KDVRR8TjuQZ+aoDGAZf5Ky+s5RZfCSch4ueKD7CpPnxoEAGAjLzaJE" "U7aq8T9CRf2HZKcVHAfaddcyKFaJ83jE3m2OLbsACFwHJssxKLg5fpG2JB6nmrGj7CaaJOdY" "5jsq0ED5qnK4h6rHDgo8VoaOi/tYEzpCq4OHadlYj8ADz2v5W/VwKxVcqafiqw20YridtsaO" "S6vuptBBWufrorrEMWnbNcG5dGDFD8vwINwGAFIfPUCrBnbT8hsNtD3YKfCQeQ8GA1yHKVtB" "zanDAg4j4zrcQtkK4DAwATza2ZV0JLpoX3yfOJE90b20G1DQ8MA2XQMPfGuMMDjC9UrBBpGa" "KK+jlnAdtUbqJe8wJSuAYxc7DgOPxlmOQ+RbK/d1NAwu8wTkJt8wXVaAhlKFJyB3u449/HMb" "kLvgYQCCnKNRz3Q0DhQKNJq1sMeqZ7xKO45c3ZJbIF1WCh45FiCAhSlbtZq23L4s6hrMpWdm" "tkve0T2Uw++ZKufQeQeyDqhrYDF19i+i/QNL6JS/mA4PZyiAiOPQElgAGm5pgORO/iTwyJ76" "iX/pOy7EkfMORyIA0aeFCQPEACUb4DCy0PiMncKn8owzk5WllZ34VIEDQv4xwScrY/Jjypz6" "RJQ1zX9mGu8fafHPp40+kp+Zn2dPfWDhYQCiwKHgAVj8d1LweNsDE6OMCcDkTYFHOmDBp4ih" "IeDgb+mABaAxqZTG0FgCaLDUs/NutDj5O9arWr8TLWKoLNAg8UAlOiVLER8MM1BCKYZKku73" "JyRQvzeggHLPeGiOAxFwDDoAATAMQO4ZHhbdPTIkAjTuGekTGZDcNzYkE+aq82qY/uPKZYHH" "//3yJfpt/0tqs27AmfVQbbtDFh4m7wA03OG5GxzZ4ZsWHrZs5RoUtBAxXVcugJiwHM9FYUDj" "OVF++Dn9DHgogBSz+ygNK4jAheCUb8FnqMD3JGUOnqdS/yWqjT4r8FgeeVbmPGox4wH3kXR2" "XaFktc7svpI5j2dpeehxWVVSG3xYw+JJWc2OnKN88Ijst1J3eqhtugoaT9i7zLHTalXoNJX0" "dlBhb5u07MKBAB4FyD5e3sOwOCRZhwLIMXEcBiYoW0Er/V1UenMXlbELWTHWwZA6TJvCByX7" "qL3ZKPMebnig2wrQkM4rlgnOAQ7kHChRNUr+cZjqwp1yg+CuWI+Gx0FP1jEHHhoYpmxlIILT" "DZD2ZAe1JlqpJd6kXEeI4RHaIfAwguNojuwUgJjJ8uZIg5yAR3u8njpiO0Rt0QZqiWyjxsBG" "x31Yx7HGuo6G4eW6VFU7ZyBQsg4jDZCGWVmHU65yuQ6WU7IyOYeTdzRpF2IyDpxt/POu4Qod" "iqtylZ3rYHi0o2VXZxxwHTLP4ZrzMO26j8ZW0uGxYuoeYNcxlC7nkfESOjRUQN19i8R5dA+m" "CzwODqXR0fEMOu5LpzsKNEDypFz1Lw84cid+4b+p/6LBoaDh1fdaTsaBM1vKVPrUUj/7WgCS" "pZWZVODITH7OgPhcP39KGYlP5F2B43MLkowJhss069bnlDmjnrNnlLJuKWXOfKoh8qmCCr8r" "aagIJBxlzPxD5Hz7B4PF6NchkmnKWy5YOHrLCgABPNJTb+pvCiYCDX5OS/6JQfFHq/SJPwo4" "DEgWw3nAgQAeqddFBiBLUq9ZkCzCvebsSBbqWwYXai2ITes17OomQdlrJTcJOsK+K3ubYCBC" "9/jDdNe4X+Y90GklWciI24E4Zau7h/sZHAMaHqyhXqv7RwfpQf+wciB9L9P/deUS/Y+XLtG9" "g9fVdt2AU7YyMx9q7sMLD1PC8k6YezOP2ZPmTrvuVQsN07LruI6XZfZDla0UOJB5LLr5MOWN" "P23zj1INkBINDpzmvST0lKg0+BQ7kqepkt1Fue9xyu89RRWj56V0paQAsj7FENHv6xgeayVI" "vyTOw5Sv0G2FVezFvQdkKeIqBsum5JPsQBgi0Uf0rYFPKJDYhYgPy2VQq8OnaGX4pLgNrC7J" "e2m3ZB3VWMvO0FgbOczPnVTR30arAkf42yHRuhArgoxkP60N7qeNoQMMkIO0hmFQdHU7lV6t" "o7Xj6jpaDAqi+0qCcw0OnHAhAAbWkuAZzmOPLl3hhsHNY3sl53DDY17n4YGHAxCAw6gj0SEA" "6Ui2U3uqXc59iTZqDu+hvUENkIgqVVn3odUcqrdDgQAGwNEZ32nVwUDZF6tj8c8jWzVE1ujW" "3JVUN1jruafD3Vll9ljtggOxe6wq7T4rAw5o70ClwMPtPGYH5XtlU65S82CJDcnb+ES5SvKN" "gQLdilug9ljx++nIWgGImShHpxVO89wh8x05UqbCbIdxHVKq6s+gk74Suva7PXR5ZitDI50O" "sAM5MpZOx/0ZohOBTBYDJG/y3wKK2cqa+Jl/8Tuy7wyO7NQPIvX8Hf8i/U5AAmBAGamv+ds3" "HoBkJb8WARpGGYkv+JfoV/r9c6v01Of8nWEyyd+n2YlMfSFnBsBxix3M7S8URPCz6U9dkJhf" "xn0YpU+/L8qYUQCx71NKyEAyppTSJ98RWWC4lJF62wOO9NRfXaDQEng4AMEzoJGeUuUqQEO5" "DCW3A3EDxC24DbfzADwgwAIy4DB6KDLpuY7WC4+45zpacyXt/WY9ib4Uyirol4zjft8Y3Ts2" "IrmHciDKedzLQLl3WENk+DrdP3KDHvD3y30e9wxf4z9/VRyHutvDXbLydluZkhXe5+24YohI" "uSp4wyo3fF3LgQfKV/N1WwEgqkxlylfKdRQGnqes4Seo0PeMuI+SkAJFUeApC45fg0dp6Ekq" "C16kkrFHKa//NFUGH5PgHI4DZavKsXOykmRNSpWvAI8NiWfFcaDjSk2aX6KNKXWnR+XwcVo6" "clyCc5SvcBlUeW83VTBU1gYfFoBsTT3OELmg9ZiAZFX0pLTqVo8eooLrjexCdjMslAOpHWWo" "vNxA+VfqGSTtCh6Rg3weYIgoaGBNyQaGiHo+QMuGmqjyZgOt83fQ1vB+AQcyDgwJYsuugscx" "gQbyDQOOxonDdkDQKVmpIUHVYXXICxApUe2fx3kYcHQIOHB2pvbJM06oawIQaaVOdiPt8b0S" "mAMgjShPwW2Et1uhbGVk4NEVY3jE6qkr3iAn1BHdTl2J7fzzbXJbIIYCVclKt+j2OevW3c5j" "J3/bOVAxb0BuQnI7EGgC8z5dssIuKy2ZLncBBA6kpQ85h4KHhOSurEM5jxzZXXU2tkavX8+y" "bbmd/F3NdOTIHis8AxzqWcEDzgOh+ZGRPHr2lY30RHI5AyOLYZFNp/2Z9GSili5Ey/g5m04C" "IDlT/2aX8S+rrIl/WuWk/inggDJTPylN/OBR1uT3AhCAxAjvGalvGRjKheB0AyQj7hJDJD31" "pQjQyJgCNNihzHzNv9S/EAEWopkvLTgyppQLMUpnUMynNIZH+tTHIjynASBTH4oEKAyMtCkD" "kfc0RHC+qwAy/a6FiFsASHry7wKNX3MfgMZseLgBAuFZ4JF4g+EwX6lKC+CIv25l4LEw/qoF" "yMJZzgMlrYdMCWs2QLBlN5y0SxIVOKLOgkSz4yrsrCtREAnYC6Lu1/eYm/vMH/SNs+MYpQd8" "Q/TA2AA7EIbI6A2ByENj/bZ1FzCx93tERuw9H+7Q3Os8+pw2XQaHkgsecB2zAJIXuSaB+Xzt" "uvlStnpZSldwIe7MAwApDFxW8GABFoX+S7Sk96yE57PhURy8JPAoD10SGYhUBC5SVegJuTQK" "uQc27Bb2H6HS4RPSqqsA8pTqrIo/QesnFEA2pp6y60rU7YLqRkGUrtaGzskmXWiV/zTDQzkQ" "OA9s1N0UP2/v91gTPCkdVytDR2l18KiUqlCyqhnposJrO6jwagMtHWyW7APOY/l4By0baZN2" "3Q3agXgU7qHNkf1KwX0Cj5qb9bR2tMXJQOKHZdJcORAFDTdAEJhjylzJW75yh+ZKDjzaEp0i" "AMNIAMKuoyu5TwRwdCSbRd2JZv7Wwg6lkVpju53SFcOjOaJzD4YDBIAAHgCHEcDRyQ6kQ36+" "VRYhtiAD8a2mJr+aLt89XEu7hmo8mYfJPeA+fs11zG7PteUqvSVXZR7FHjW7Mg8VlBe7uq3y" "JO/A5U+Sewyq0hTKVR3m8qdBtVH3wuRmOjpeIZmHwKM/S8pVAo7BdMk5DvL7wdFMOjaeQyf8" "uQIO6CTrXLCAIu9009hf9tIj0UI640+jO7KmNDimtBgcmalf+G//Ch4ZEwocON2Sb6nvrQAO" "BYpvBR4GIHAj6clvKDMBKbeRlmBgJL/iv21/xb+MWdMQOxeGhlsGIFCmPtMYHFD6jCpXpQs8" "HIAY16Fg8Qkt0fBwK0NDJG3yA4EHtFgg8p51IXhOY4hYTbztAYi4D5cDkSxk8q8SomdNvWXl" "7c56k7JSKgPJmvqzzUFmB+nuAN2E6BKgG4CI63hNl6xuu8pXtzU0ZkQPRqY94DDwUCWrJEMg" "McuBRDx3exgncr8LHgYgpmUXwsS5BOY4zXNwXNaVyMQ57jMHNDQwMiNjlBEepbToMGtUJs4N" "QNCua7bsmtbdzLDTbZXhujDKzHpkB6/OBUjILV3CCr0oHVdoz80PvGBzELwbgJiyVXH4MsPi" "spSsAI6ckcfFhZRFnhFgABw5w+cpn91GSfAJAYeCx5MMjycFINBShshSBkpN6AKVjZ2imsCj" "DAp2JalnpGxV7T9HVbg5UO4u13eZY8pcDwsCIJsZMChZITxfPnaCakeOyD3mcB8oZ1UNdsuN" "gtisixUlmDJfFzmlW3aV4D4EJMHD4jwq+psZGl2Sc6BsVXStgQpf2Car2gGMTdp9eJ4ZIptE" "XbTW10IrhvfIWR/tkeWI9eFuWje0l3bwaVp24Tj2xvk5cVCevTMeh7wA8ZSvumzLrilZueFh" "AAJ1pzrEfQAeAEdXqpl6tPDckdhLbdGdjvOIsKNgtQootOuI7rDOw8ADK9ixPReXPkGAh1GL" "fzW1Bvn0LafGsVpqHKkW7Rmuot1DS+eAw+QduKfcOI+9fWXztukacJjn1v5ZANGuo32oiNoH" "8hVAZClijtplNaBD8qFcvYoEyqAToWo6OFZkncd+/vmZUAUdDxbSobEsOuLLE1AINLTrcAPk" "VDCLrr2+ma68tpnOh3MNQBQsjDImfvFCIvkj/zL7kTImf1Di73iXbwyO9AkDkB8sQDzAEH0j" "3wANAGPJxNf8y/sb/gX/LaXN8DnzlZyAiHpWUEmb+UKeM9h5pLsAsmSapeEhDmMe12HgAVgs" "ASz0N+M8lrDjWMwAEZBoiIgTmVQy78qJKEmwjrxk5h3pwsph5c68Lcq79Q7r76L822+L8m7/" "VX2b/pso/9ZfqWD6TavCmbcob+ZNj3IYLFA2QwXKAlTYoWSk/tMqLfU6y9WJpcFhBHBYiMwq" "WbkBcm8kactWswFyfyQsq9tx3qfvNZdJ84hWyO9azx7wwkMGBvUZHJWpcylX6cwjK+6jnLif" "cpIByk74KTvmY41RFgMlOzJEWeFBBsygnLNXtEMKHr0KHoHrcx1IULkPbNs1AEHbrtl5hTmP" "LN9lyglg5uOyQEOC84Ca+yjln5cKQNhtRC6L8FzGJ+ABwX08dOUwpfedotLAE0oaIOX+C1QZ" "fEIEgFSFn6RqrGCPXpABQsx8YE3JSgYCuq8gzHmgdAWArAw9LB1YeFZZhzpFuly1beIJ0frI" "Oars7xSALBs9SNsSalniav9xyT2Wjx/UobkK0NchB0HZik84D1O+Kr2+k4pfqpMWXgOMNeOd" "tHy4mVaPt2v30S0AwTMgAm0Nd8pd5tv5GSc26iLvQMcVoIFWXQAE7gMAwa4rTJsDHhgSdAfo" "bdaJdM0pX1mAMDBmAwTP3SmApJX2s7onWtQzn4CIOvdSV2KPOA7kGwBIm4DCUafJPcKb5I5y" "s37dAKQ5sFrJv0LBI7CS2oMr+VxBbVotvmXUPF5LTWM11MRAgfYOV9LegXIHGn3OjAdKV7PB" "YeGBVSQaGhYg1nUU0pFILXWNlKr8YxBLEPNsYA5wdOLmQFb3SC7tH8lj5ch5YDSXDo5n0alw" "BQ280UaXX9lMx33acUD8fCqYo8GRKQI81JlBZ4PZdCaYTmcCGXRHBrsOgCONnUc6OxEFEKX0" "FDuQ5M8WGEtwMjDS2G2kJX+QczGeWelJVbZSoFBKS3ytoDHBoJj8TkFjRoNDw2PJ9NceLZ6B" "vuTnLxUopr906XPrQNIk+/iMYaAyjrRf0eyfARgACgACB7JY3Me7tIhdhQBj5h82SAcscmfe" "F+Xd+oCB8A+X3tXQeMcCw4JDgwTKnfmbVd7ttxgiChoGIPlTf/Eob/LP6nn6T5Q39Qf+5/5E" "uZN/lGd5n/y9KHvq9/zf+3cM7Ff5fJWWJG8zUG5JgL4A8EDZSuuB8AQ7Ca/zMHIH6PeJ24ja" "y6LUs4ZJJMjgCKqracPmPvOAXVlilyaGlPNYFB53rS0Zt6UqtO/CccCFACJ5ySAVJP1UmArw" "OU4F8THKjw9TfmxUlBcbkjvO8yMDlBPpp+wwsg8lgUfQG57nha5rXbXrSWY7kNzgCwIPrCuB" "xIHwe67vaSldlUWMLosTUY5EZR/lYXYg4UviQOA+CsYfE2hAxYHHKXvgNOX0nbQAqQpfkFJW" "VeRx1kU5q1krYxdoVexJcSC1vjNqzoMdB6bN0X1VMXiI1gYfkZxDheUXXME5AKJk7jRfNnpY" "bdNN8j8TO0tLBzqo5EaT3PVhAIIV7Q44Dsszcg4IXVfLBlsEGgAIVN2/h0qubKaagUbtPHoE" "ItCWKJ4ZHgwLEcNjW7hDuq+2hzqk66oh2i1r2RtltuOQlQrP9ysXYsDxKwDZx+8GIJ3sRvZN" "7LMAkewj2abhobRfQ8ToQKpFdHCCQZLcS93J3dQd36UyD4Tm2nkAIFjFbrbpmsufDDxQwoLr" "sM5D4LFKoNHKEMHZ7l/GWiFQaQ8ul+c2Xy3tY6Ds81VT+3gVtTNQ2tiltA5XUAvuIh8qFbUO" "l4mcoLxYt+mWqMB8qIR/XiSuA/BoH2DXEKiknpFi2jdcSJ0j+dQzWkAHxqEiVh4dZBgc8heI" "Do/l02F/Hh0J5LNyRccDpfTU5Bp6NF7FAMkViJwM5NHFZAVdnlkp0ICQdwAWyDyQg5weT6Nz" "DJPHogV0R/okwAGA/DJHS1I/C0QWMyxEAIZ51lqS+N4qLa60hF1IGsJ0hsaSKf5n2FksmfnW" "nktufSOgAEAUMBwpkBhgfD0vRBZPfUZLJj+THETkgchHFhwoV5kS1hItuI4l2nUAIpm3PqSs" "2x+IshkSOfwNstCYJQMU+TlAwgDJFTEwXPAAMHKm/8rf31IOhGGBZygHTmPmL1a5039hR/Nn" "OQUgDA8oZ/oNhsYbfDrgMMqb+D3lTPwn/y3+dXZ/r4myUq+I8JzJQElLMlASyEIm2Y0oiNwX" "TNI9odkQiXsgYlzIAxYkIQGIgYcBiIGHLE1kcDxgoBFScu+6WgIXgtsGg06Aju6rPIYIAJLH" "yk+MUVF8xKPixCifw3yOWOF62uLYoFxVWxgZlAui8iI3RHAgc8pXs0CiylgvShnLTp37n1Pd" "V75LtnxlAnPjPtTz0yITmheH4DwuMlSeEICk3ThKadcOMjwuUnlIOZClDJGKwKMORMKPiZaF" "FEjWpZ4QqTXtj1FJ30GZMl8TOC/AQOlqZfAUrfKflGdkHwogT0gZa7NrTTsAsjF2hioYHLiO" "FgDBnAcyENxtXta7R66lXR86ysA5JiBRobkK0TexOzGlK4Cj8MoW2YG1JdQjAfqWEO4C6ZQT" "ELEAYXgAHGjhxYl3qC68TybNsaYdrkTlIO7s44AqXRkXMg9AAA4rDzwQnndICcs4kAMTbSK4" "DoADp3pu4rNJIAIdSDXSIXYnByYUUFoCm3WZap1ax86nAYfbgbRqaCjnoWTch8CDtQ9wYZh0" "+GuoM1ArJwAi774a6vLX8llF3f4qPpdSp7+CuhgGEJ678YxvrB5fGZ8lckL7/aV8ltABX6lo" "/3gJHWQQQEeCZfTk1AbWJjoaLqTDgUI6GiiiI/5CDQ4ND58CyTGGxQmGioKHch8n2Xlc/309" "Df+xmR4OFzEw0vlnSxggWQIPnA+HsunxWD5diGuAzAcPA5DFyZ8EFGkuaKTxN3mPf8e/oByA" "LMT7BDuN6R9Z32t960BDAwTfDCwcaMx2Il+qf2bqCwsPgMMtQARaPPEpQ+ETCwkFio/mnIsm" "PhSAABrZr3xslfPqR3x+SDm3PxSI5M4oWOTzuwcYBiC33hOJC9FuxEAkx+U4jHKkPKUBot+N" "DDhM6coI4DCaDyC5KQOPuQCBK8EJiEAZ7EzS2ZksSczQwmjKwuLuUJTuCSdYMW+Iri+Hut99" "Ra2Ur4K6jBVkeCi5AeLeeQXnYeBhVpYs0tPn7u4ruJG8+DjDw0eFiXEPOBQ8XOBIjopKE8Mi" "gESUGNB3nfeLiuM3qCh6jQqDBh7afYRNCcut53X2ocpXhcFnLEAADeQemPVwd2CZHMTkHuWR" "JwUWCM8LfY9Q4djDAhAIAMnqZahc76SywFkBh1xJG36caoP8HHqEasKPuDKQS7TMf1baeDEo" "CNexJnKeyocOUFl/D9UMHxWAABxGCNIBDrdW+45S7dB+ho4aElwdOETF13fLoCBmPUx4jgxE" "ABI5IpdFASBwH5tZG0LdtGK4jeHSpQHSzc8dVH5tK60Z2etxHwYcbngYgDRoiNRH2vlsl1sF" "m2JdsqZE4CGrS1Cq6tbi54lupWQHQ8SBB4CBjisAA+6jM9Wm31ttCctAwy0BiIaHAQgkbiSu" "Oq6gNixODKp7PNwlLOVA1gowWlHCYjXrs8233IJjX2C5qMO3jDrHWf7lAo4OwCJQLUDB2eWv" "ZlCwMLzH6glVUQ9O1v4QOwuGQU8QMGFQBMoUMHAGS9l5lLO7KKNDQf0eLqejIVaghM5El9Kp" "aLnAw4DjNP+Zx5MrGBzZDI0CPpXTOColqzxdusqzWcdTUzV0IVZOp0OZ4jwAkadSNRR8s5We" "nloq4LiYKGSnkkd3oHS1JPWL1eLkzx4tSvzE+lHre9HC+A8CCwONBQnWxLe0aAoug7/P8J+7" "ZfQtLZxR8Fg09bX8HM9G6ts3XjFUFk1/peHypUBk0eTntJDdxqLpL0QCFoYHvi+a/FS0ePJj" "K8DCAAOuJOvWJ5R5+1M53fCAMkUfCkSgrNvvM0je98BDAUOVrxRAlPPIuvUuZd9+h2HwtgbI" "26LsaQWTbHYhbmDAlUDZU28JPGYDxGQfKFsZASCmfJU1+Z/KebAAj8yJuQDJTCh4ZCXgQqbF" "iaSn1POSxASfk/z/7QT/f5mih2Ip6cQynVf3Bk3moYJzByaBOSUs984r3OuxKDx7ceKYZ9+V" "2bZr1rQrDVNmaIByYyNSvipmmIg0QAw0HHg4ALFKDooAj/JUHwPlJj/3UkWiX66sxS2DUFn8" "OpVEr7JreFGEQUGAQ6bNg84cSDFDxey/Sus7J+tLnNkP3bKL1t3wJXEe5ZGnRBXhJwUYbnhU" "BC7QkiuHaPHVTsofOiHlKwCkMnRW7jc395kDIiuij9JqvW1X5R5PCkDW8p/H6hK07wIgGCDc" "xuBYFzol5St0XZlLosya9jp2JPWASeI8rY8cY4AcobIbuyn/5Tp2JXt0+eowrRxpp6U391Ct" "gOIAbYkcsiWszVooXQEeENxH7cBOWjfWLPd8mOwDSxJRthInEukUGXgYgAAeDZEWagg1W+2J" "tFFTvINh0mk7r/Bs3IcMDDJAuvjdAMS4DSXHeQAeyDykbDXZ6nIgTQog8UbqSewWmcC8O7FD" "sg8IIBFJ6+4Wao9spPbQBtoXXEutPhWcK8ehINIWWOlxHoCGgIOhYSRug6EBYLjlhke3Bocb" "IPsZCAKMQIW4DoDCOA0872dYHA4UM0RKREeCJQINfFOndh3+Ynr2dj1df6OFjvmLBBSAyPGQ" "ggh0CpLMI1MAotxGtuQdEALzwd/voon3jtGV2+sVPFhPJYrojiXJf9EidhoLE7/QovgvGhg/" "yfPC+I+OkkoLEj9ofcfvDJAJfp7i7zMMFQbGwpnvBBIL8c5aJN8UGBZMfz0HFG4BGkaLp74S" "eBhY4ARAHH2qweEAZNHERwIPKVvNKFhkvfKZQEKejW5/ZMExGyCAR+YtlX/AjQAkotvvzdI7" "IgTqWbfetuAwktUmAIUGxq8ChGGBspUAZPoNyp1QALEwmfqjCODw6ncCDzxnTrwmMu7DAERp" "RgACLUnBiUyxI5nkc8IKUIEWxBL0YCTGoAgreOhOrPs8XVgKHHK/B78vZBeicg+fyKwvmX3P" "h917FRyxl0YZpQUHRTnRYSqKjYkAj8LkiAcecCEASFlyxMKjTMChVJ4aEJUm+qg83icAketq" "XXed444PCLcNQrjvHMLa9vLIiwyEF5QiqoXXdFyZEhYAkjvyMGUOnJHSFaABkAAgS0MGIE+o" "3CN8QcpXxWPnKG/gGJX7zws8akKPUe7AAcq81kEVvlP87WFRTfi8rGWXxYmxx6UDS7qvko8z" "AE4xPA5LK6+07zIsEJ6X9e6jmpEDunz1mAcgdfy8PaWuqF0XPk6rfD1UPdgmJ0pYyD4qru+i" "4pe3USXDZX2gR4GDISIdV6EDsnEXQvkKAEH+YWBiAGIEgEAKHp0CjnpxHkoN4TaByI5wiwIJ" "bhBk7eTnXaG9ci0tNu02J9rZkeyjtgSLXQYGBU320T3ZafMO40QEHMkWp2wFlwFoTDZLeI73" "nkSjZB4I0NvZaexzAaM7Vu/Ag7U/uZ21ld3JZv7ntoi6YpuoK7KBOsJrqD2whtoYJvsCq3S5" "aoUHGsZ1GHAox1GlpeHhBoh+NgARaDBADgYr5Rluwwiu4zA7E3EhDAuUreA8IHEcwSI6GizQ" "8CgUlwEH8nC0UpWo+Dt0MVHDrmIlu4wCKVsBIKrTCmF6ms470iUwR9Zx5dYaGvrjDno6WU5P" "JAvoCQbIwOsb6Y5FyX8KPKySCiA4F7DrWBD7YRY4fqCHkqxJfp5mhzHzs2jB9E8CkQUaHEYL" "Zr4TqAAebgEqC6bngmPh1JdWxm3MhscCdh7QwonPBCRSzmJgLEbnFQYHb32m9QllMCyyjDwA" "+dBCI1MrQ7IQBRDIwuPW+wIUj9h5KL1tAQLXYZxHlgDi7woieHZLMg8tA4tpFzBMB9bUnyiT" "nUfW5B8kNAcsTAkrZ+J3unz1ui1ZWfcRU2UrBQ7lQBYzSBYzQJYkpkT4np6aofRoijLiSf7n" "UiI8pzNIlsTitDgao4ciEQEK7vlwA8QE56Z8tTDid3VfOQBZpLMPCw/X/IfZfZUeGrIQyYwM" "SXgu5auUFyLKfWiAwHVo9wHnUZFwHAhcRykDozx+0wJEbhhklUde5l/8L/LzNREgUpu8Lnd9" "4Lpacy6NvkxLYy+yXrASiLDzQOdV2o0T4j6ULlEpO40y32PiOOA+LED0CcF9wGkAIFnXcfHT" "PiodPS7ggAspGzlGxUP8S338mNw2iGFCgAQQATTgPMyJ3KNqcD9VMETQfbVZMpBHaUPotJSv" "1vuP0/bYwwIRaGPkpDgOlKoAD5SrAJCaoVYqvrqDavqbZf4D8MC5crTVDg4abYv0eOQGiAnR" "HXh0avfRJqWrOj4NQAw8dkRbBB4Q4OEW9ltBzYkmUWuiWWSGBaVdV9Sm4JHQHVdJJQEHQwTg" "QJlqX7SB2sJ1MlneHt0m3VYGHj3xBlF3sk7cBwDSk9gm4ABEDvAJHWRXciC2mQ5GN4gOxTZQ" "T3Qd7Q+vFfWE1jAIVioFlol6gsv5rJlH1dQDWQeCchVch3Igyn2ozAOu41BAORI8n44uozOx" "5eI24DDEdfiKJO+Q3IMBctQHeORr5cp50pV7vPTaNhr40146FylWLiSYRWf4+zn5c5kMjkx6" "OJJHj8eKGTZKgAbKVwIQVt8fNs0FiEBjjn6gBxPf00Px72lB6kd6aEoBYyGDwwoA0RBZeOtH" "AYcBinpWemj6W6sFoq/53/cVv3+phGf9Dlg8NO2Aw3n+1IJj0QxD4/ZnlH77c0q79akoXd6V" "BCIupWOliQ7OszU0MmdBJP2WAxFp2701j24rgDglq3fmlK7+fwFEl7GMBBqTbzia+oN2IQYc" "pnSlXIfpxAI80I2VnuQzfpvSErfFcRjnoTQt4IADUad6Tk8k5cyMT2qQJPjfmeAzTlnxGP/7" "YvwLP8wwCc65KApOxABEXEjEbxcown0s0t1XZnWJc2XtkL04Sk2eD9lBQrTwovuqMKkgYvIP" "T/nKlq00OOID4jhQuoIAEMBjqQaHkXEfAIXcc568odxH6AUBBy6Kwo2DNfGXWS/JnR9GtXIf" "yPMMhadk1qMm+jT/+9T6kjx2JJk3GAAj52Xuo1qXs0yIXq3DcwMQzISUDh+TGwcBj6rgWcq9" "0U0ZV5opr7dD7jKHG8E9H+uwCwuLEzVAzNT5+vBZdibH5FpaKV/F2L0wTJbeaKGqm+20KXpG" "ylgQ7jMHQLCyRO24OkIbo+xoggdp+eg+WuvrtjMfa3z7qOxaPdUO7HbB44AGBwMj2m2hIc4j" "pF1IxOs+6jzAaFHuA4q2Cjx2hJsZFi2inZEm2hVtlnvNd8UAjz0irGvHYkRob2SPrCrBlDkG" "BNtjexgEe6mT1fX/Mfbe71FdWb63/4N770xP9/R0mna328Zgom1MUAAJoZyzBEgIENHYBpMR" "ORlMzhkTlSufc6pKEuBs45yzjTHZ9sy97+/r/a619z51StD3fX/4PHufUyW6n3nmqU9/19oh" "PAsCmKUTh15xFZ4hq63m+xtEHvMDk12ByC5zk0AiSiALI1OE560GLZBJtBgyWYRRYHlAIosj" "NaCallg1tDRcncSyUCUthVSWBMppSbBUWBoqo8WBIlBIi/wFMi7sznMFwvJQ0shKJBAWBycO" "ThrdCp4vRTJp8WXTKn+OW6pigayL5NOOeLVIRATCaIGwMFgeK7sZ1fPYHMyABPI9yeNJ2hsv" "olOvNNKW8DjaHGBZpEMaEIeVLsLgspWRx3Y7hXbb4+mBIdYvNDhyx2VIOMFj4ds0KHQL8oBA" "HIzR2yKPQfE7NDB2E6OSyeDYrQRIJSyHQT2K/tJ4LHbNZbCMV+kxyMILC+Sx2PfgW5GGkQs/" "s0CG93xHI3q/hyy+7cc3/eYJoTyp3xmBSFlLJxNTxjKrsZiRvYlS1n0lYk7qFWF8nCQQL7Kh" "kDcQRt9RwtAS4Y2EKmGopMGwQIw4jEg4fagEospYRh5PRi/TEw6E4SiBcLmK5cHi4OW8jBEH" "p4/HnT4RCJe0nrBVGctIw8zlGQJ5yrJEIKM9jAqFRCZPhII0ItgtpaukTYR+1QNRfZBE/yNJ" "IN2J40vUwYnm6tpzrkhkA6FPbR4cEzwjAvEmEG/5KsNTuuKRBcIJhAUi6YNLV3hmiSRQV9Ty" "LYPqpsETlMl9kI6dlBvUAgkfci+OYnEUW0fVPeeg2DpMxfZBKgF80i6fuFsU2UvjWzfSmJdW" "UVYnH6K4E1LYLhKZ0LUZiWSTJBAWBzfPeWRyfRshEFW6yu1SAnn80GxKPb1Q5FGIFJLD19Se" "eZ4mtC6hstB61TDXzXPug5jeBzfOeV7WtkQEkntqHtUFVtNkm+WxlkrbFlDB2aeprGuR2zBn" "gXAD3bvyistWld3PyfElJUghXKrypo4pgQWestVCJQyflgjPg8/JPpAG3TQ36aPBFYcikTz4" "DvO5Ig4XnT6aNeZ4dhaIOZqdD0dkkfA4x99EcwOQSmCqIGdd8XW0nZNAXeIOc7+CJWL6HiwP" "Th3MgnC9FshkSR+LtEAEnT6WhmtEHEssNV8WqQJKJEtCFQILg2F5LA6V0vMijHwlje7k9MGJ" "wwiER5aH0DFBlumyNFy6M6XX4fY7IAReosspZEukmI6/NlOSB/c4VvhS3NVVvPKKkweXqlgg" "kkK43wGRcPLgTYNru0bTcaSS6GcraU+8IJE6rEza31tIu6wMPKdICmF5MDt5FZYSyM8uLI3B" "oduuQATnNoQBkDQG9d6V8VGkDRZJkjw0j8WuJyShhWKeB8YVLBeRh04cShgg+oMC80EQhggF" "EhnS8z2SzQ/0eN+PIg9XIHjPZSue85iYfy3C6D+qzYZKIk8APmSRJcLJw+CViDqtV0njyZ5P" "XEbG1XEnLA4D90OejL+PUR3v/lTMlLKuJOShE4kSyNsQwVtu8uifPuSdK4/X8d1XJHGwPLwC" "4bKVlKwifS68L6S/QB53eqRsxU10M7rJI5xIICyQUbYlCWSUZgxSCTMqHBDGhIMyPu73SfLw" "Ht+e1EA3x5V0nU9KIG4S8ZkeSGL3OcMCecr3EpLI2aQE0l8g4/XqK5YIl66yLNNA1+kj8hLl" "QSK5WiATpfehrqhV19Qel1KWubJW3Xd+iMZDKKlnIQM7kUDU7YOH1LW1+qh2JRJ1cRSfd1Uc" "2O1eU5vd8QKNObmcJlxYT8XhnVSEFFKIJMGrr1yZ8J3m3APhRnrXWprIl0IF1lJhcL2kkNSX" "FtDIo3Mgl7lyy2Ap3vHu83p7sxKJrLryrMIKb6RK3yqqDqzR5av1VNK+hHLOzAWzqbQDwvC1" "iDSqpGHO8liqV18tketqZdOgbqCrpboL3QRiylYskkm+Be7SXdNEF4JKIEYWRiT95aHEoZgW" "nKsSiCuOGUokgWZP+piGUUnDwOddsUDm+BvlZsHG1kqaekHReL6CGs6VU9OFMmpqK6fpYFpr" "mYyzOqpoTkc1zemslE2DvOt8Xnc50kql8IyvClTQs74yehZpguH+x7MBpgTvS2lBd6lqlHep" "Hshz3QWaPIF7IFyuMquuFKoXwgIReXRk6bJVjgjESESlj4m02Kf6HkoehnS1t6MjVfocZrnu" "Kl+G6nuwJHxjaUMgiw5dnkJr8W9w6mB5rHab5k+JULhcxQ3zDSGWwgQ6EC+kbXYmbZPEMY7O" "vDGFop8vl34Hy2OnlUI7nFTajc95/sAgC2kiAjlE7iJt3BFYGo9CIIPsuyKKR1kYmoEaea/h" "NGJ4NPYTBHFdUNK4ToOiSCPRH0Ucj8Z+dD8bJKK4KqNhQPR7Ghj9TgTCqWMIpDHsIuj7Pomh" "vd9hvCrjcBYEUsZwLQovw3sVkkbM0SY9CbhH4t0LYvaDJPZ5fEJjk1ZhfeySevET2TiY2vsx" "pUAaTBpSR2r8XUqFPMbEE7vLec6M1snjKUftMjf9DiMNPsrEnUdfQ0J5VWB5sCwM5pl3pIss" "PMIw0lAlrLj7PByCSPRAVCPdm0BM+WqUbdMYCGQ0RGLEMcYK9SNAY+2wjKPCPhoZ7KIR/na9" "/6NDdqAPMXs+tEiG+c4l3XmuTts9l3zqri9x/tVTAYik+6RsIOS9IJksEAHyCJ/T4jin5XFW" "r7o6TdmRl+4pXeVK8tD9kLBKHyIMR8tEJHFUpY7QYRHImLNbJH0Y3CtrIRE+tp3FUWbtF8yl" "UebUXSbrwiYae2oZTWjbIEeXMLzvI6cTggiopbvFwc2y96MEIinUTfT8gEofPE9DGjFlrWL/" "Grmylu8755N2c88totrwBhHHJAhFGue6ed5gbRB5cPmKhZF/Zh4VnpsPOaj+B986WNL6DJgv" "yUP6HxDG5MBSmgSJ1IcWy4qsuuAimfdPIFy+4qNLjDAUqlnOY2NwvpSrmkLz3LJVkyuKZDh1" "NAO+IKpZpw8uX/GNgs3+ZvdI9pm+RpU6AD/PkZN2p8ptgg0XqiCPahHHNKa1nBovlIowWB4G" "EciFMr3Po1KW7JplutwYn8sNcoiE4bnQXaI3ByrUct1iiKOEnukuElgiXnn073f0xwhkcXeO" "Th3ZbtJgaWyIVNCmWDnkkKETxzg9ZujVV+nyzCuruIHOqYPLVqvxnstVLb5UpJJ8On9lPm2K" "TBRpyDJd2RyYQqt9o2SZ7gZ/Cr0QSZdylSQOh0tb46VstdVKo1Ov1VLskxV05vV6vBtLu51x" "EEca7Y/n0v7oRHpgYOQXehTy8AqE5wNsJYkBLneER+PJ8kgWCJ6jN5REuMQl4vhJpMHvFEog" "ag5pOFdpIBBxOFoeEMeg3qsij6Esib5rMh8CWTBDtUSklAVxGBJ9j29pVN83ao/HxW9pdN9X" "NObi10IKhJF6UZF26WtKv/SV4vIX95B26XPw6b30fSKM62U+ovGQSUavgp9d+j4A71N67/s0" "rsfwnuxAF3qvUHrf2xjfknlqz9vgTZeU+BuCWcJr9nw8ZakVWKbn4aaOSI8ShUaJIyalKxk9" "DXQjEKZ/+YoFMkoEEhGRGImMtiEOJ+wKRBGisZGAMCbcTU+FuumJYKdsHDSbBuX2we5z/S6P" "Oqvlca9ARroHKL7kHl/CO8/Tg+fcvR9GIFy6mmipEpZZecWpg0tXnDxMA53HCYGjMnLTPM9O" "JA+G3xVIqYolovodpnxlyPHvoLFn1svINw2WWQf1jYN7k+78KAnvkXecRPgQRT66hOXBx5dk" "ta2hlFOLKPP8CnVJFB9fYu+UAxX5GPdKSIVP3+W+By/fLQmsp9zWZXLLYAmSSXF3C40//Sw9" "daiZxoISyERWXkUgkuA6mhRaL3MpXVlKJI32RrnbnK+m5edaSIJ7HplHp8rxJUYgLIz64FKd" "Nrx4G+eeVVeQCZerJHGEFog4lEQgDgiEkdTBfRD/PFcg3uRhylbNBlcgM9XVtJ6yldwoyHd7" "+NTY3D0Z0qiFNKqRNCplNOmDBWLShkkfJoEwZqOgYW5XhayuMtJwJQJ59BfIM90lLiKOLq9A" "FKqJnhAIpw6Rhyd9KIFM1KhVV0YgiztVClmqNwgyK7ozaG0wV0pWLA/pd+ieh5Stusa6q6y4" "37EKKWWNCMXIYzSSRQ699GYT7Y4W0JZgOuQxHuLIgCwyZFR9jnSB5zvscXQIqWSnMx4JJY32" "Yjx5sYx6Pmuh1jcajUCURAaEf1YjyyP2sxbEnfvCUnkkdkuJBaORyYDYjQTOdVcoA+IJgQyI" "g+hVEYgRh0kgQ3p/FEQcIpDvJWmwMB7v+4GewLsnL35PIy/9QGNcvhPGXkyQdulbSOIr8I2M" "LAseWSBpl77SfC2jksnnlNqPtMuf9ZPHxzJy8mCUSJQsRB4sDC2P9J4PtTjeSyK9Vwsk9g6+" "cwXffduFn9N73nIZL+Mbwrj4m+B1JJzXKSX6qjA2+jJ+4F+mUc4lJJbkzYOy78PpUyutpFwV" "d5fwjrR0DySkl/JGLCUSWY0VEYmM0QJJwg7dJ4lomUAeTGrEJ/AxJXxciXuEiXt8uzeBKIGw" "SLwCeTJw2iORU+7hiSyR1OBpJRDePKgTiGqeJxLIvWWrk7JUd1zXfmmiizRsJRFunBuBFNrH" "RB7qnvNkgZQAvnUw7fwmdcKurZIH90AK/DvdspXcb67nfN9HpRycuNdNIDkdG2n8uZU0sW2V" "u/ucjy/h57z21SIQ3gNSb213jy/hkRvovNu8Ugsl7cRcSj85TwRSBbFUBlYjkTxHxW1IDuH1" "IpApzmaRB0ujIbKWpobXythgtUjvg48uyTs9y22e9xcIp4/JweeF+wokqHofJoGY5bqmWS6l" "Ky0Qk0BYGs3Bp12B8LLd+wnElLG492FSB5esZnTxNbSTaWpbnaQORYUWhxJIIxLGVJ08+PIn" "FseMVk1bKU1vL03aZc4pZK5HHrLb3FcqzAfJ8kgIw93rcR+BKIkk0ocpWy30pA/vcl0jEFmu" "26Ua6Es7TclKJZCW7izac3GyShzd41yBcApZ2eFtlhuRqL7Har3fY40fCaKniDreXUDHXpks" "paqt1jikj/G0N54PSWTpvkc6bUcK2Y6RBcLscSbQPny+z8mm470lFPlgAbW9OZUeYGE8HPkZ" "3KFHnJ/xg36XHgEDWCBMz12dPm4nwfJQArktAklGCUTkAVgej8Su4d+9rkbhqohkYBxJo+ea" "pIzhF38Unrh4VRh58Sfwo8jiKUhjFMbRl6+68PMoj0D6S2TspW8gjK8FIw9vAlGC0ULh574v" "ZPd5f5GkXPzsHoxEUi9+JBJJ7f3wHnkolDT6C4TPwkqPv4sE8o6bQrzyYNLinEJeo9TYayIO" "Fkh6/FVKY3kggbBARCLOZT2/5DLGuajHXmE0JDIGEhkFRjsxYYwdhSwcF5aHEQg30U0jnWUy" "lqUCWYyOBIVEAjH4RCApRiJWN6XZeBfpksMSnwy2SfN8GAQhez/859zmef+7z73ycI9v1wco" "8h0gKYGXpPfB8uAUwvs+vHs/uITlrrrS5NknBS5lSQKx1FLd1NadlBM+RPn2UWmgc/IwAlGN" "8yOqcY45l7D43nMuXTFctsrtepHSTq+h7M7NrkBMEuF7QFgecnS7pQ5Q5CPc+RBFlganjxoI" "pKBzLaWfWiBHmMgmQnuHCITvO+fVVzX2Vnf1lTq6hDcRrpWNhPXhzdL3KO5YRpkn51LumWcl" "hTTakIcuY00Or5M5wymE7zefFF6heiCQR61n0yDD8mBpcP+jPvS8IPJgmXgE4q668pSvGjzy" "SF51ZUpY8+6fQnjprn9WQhxJEmmiaV0NEMIkmtJWS5Nbq5Lk4e17GIG4ZSvIwisQlgdLRYmj" "TMujIkkeKnEo5vsUz7jzZHnwrvPk3kfB/Zfrgufx+WK8U2UrJRBXHHqVFS/VldTRkZw+pHne" "qSTC8jACWQUB7YxXy6m63Dg3mwNXdaVJClmt93iswXx9IJ22RibQ/r5SyGGipA5ukrM4/O8s" "oDOvNSBlZIgweJMgS4PZG82mA3Y2HXQmuhzrLaSjPXn0wCPWL/QP62f6h63E0Z+HnTvJRFkc" "SiAPR2+6InlEy+MRfidcFziFmLl55hQymPeC9P5Ej19WjLx8LRkWBwTyBNIIL9FlOHnIct2e" "7++z+srwlWf8KtE01/DVtaN6vxS4ec7Hl4yBPAxJAmGhuNLQqSMpgXwkAjF9EJaIyEMjMoFE" "TMmKheGdc+Lg0pXirXtQZSwWyBsazOOvJhJIXElkTMyg5JESY3n0yZgSuyzzVE16rBf/uXqM" "xSGjmJDqRIUU2wG2EoYpXYXD0jRX8vDruT9ZIGE/jdXpwwiESXf8IhI57yrcjlRywU0dfOe5" "ukhKH+P+TwSirq99SQRirq5N8Z9wU4iRSH+B5OhVWLnOaS2Q45TvnKAC55gIYyLfiX5hGxLL" "YZGHWaqbEzwAUWh56NVX7iost/+hrqrl1Vbjz/E+jh1StuLyFcsjp2OznHXFl0eZ8lWlsxNS" "2CUlK8V2gfsfcoBi60p17znfBQJx5LauoOwzi6gcsjDnXvEqLF59NZnPwsI4JbwFqWIz1QbX" "U/6FRVTUugjPG2la9AVqcjZRFR9l0r4Q6WM9Tbc3KCCVqZHVEMQyKWdx8vAKhHseRhwmgSgW" "JAvEn9z74L4HY+bSA/F7BBKaJyQLJFHCUg3zZi2QGTTN10QNHVOooa2eGs5DHBdAe61IhPsd" "SZyvkt7H9LYKKV9N79/3aPMIpF31P+SeD0/64MRxv5LV/QSSSCHF9zTPk3odnlVXRh5GIIny" "lRZIt0ofSzrHizTUrnK110OljgyVOnxKHit8adI43x4tl0a5WaLLq6vW4rM1PoxIHSyOjaFE" "mUqJY7zAzzvsCRT68Hm552NfLId2xzJlPPNyPZ26VEV7bSWN/dEJMh5yeJxAh2IT6IGHnV9J" "8bOLKw8tCx7v5abGO7+emDs/iTAeltSBJNJzXVZe8YqsYX3XIY0b9OQlBpK4eE1WVzGcRFTP" "40fVA+Emet9V3QP5Qc7IYqSsFf9W4OY5w3tChkESvKHQMDT+lX6HMfalCz8LfCKvvhdkhNxS" "+Km7yopXYJmNhKaBziJhZA5xmPThyoNThxYIN9QFb9/DS/xt3fdIxhymyCTkwb2QV0UoPDIs" "DZNEjEAYJY6LlKYFYubp0YtaHEoeipgwDhJJh0DGM1EbRFzS8cyk2iFKsYJuEmGRSPLQ6YMF" "kmIpkaRAGmM9AkmLdNI4Pjgx3CGMDra6vY+kmwjl9sHk9GEEwiUslgdLhA9NTIVExkdecs/A" "ygydoHF4P9GzcdArkHznlJKIpfofZtOgaaBz/4NFMur0JprYtcdddcUJJLGMVyUPg+p5KEzy" "yOt6gVJPt1DGhXXS/6h09olA+MIo762DNc4Ot//BmwbLQ1vk8EQWSFHnOko/87wcqljc0eLu" "/ZDTdk3jHAmFm+a8YZD7HZPxnuHGOScQTh7lbRDQufn4X//raJa9KUFsI82IrpUkMim0TKj1" "Jxrnqny1+J+XrwILFJ7ylRGIkYcIxE0d8zxNc1O+muP2O4w8eMVVU/dUEcdkJI7JbXUijsYL" "dSIRbwJRTfNqd2yCPKZrWBIMC8MIpLlNPTe3qwTCAvH2O+ZJuepeeXgF4i1hKUpoQWeR9Dye" "6869p2nOqeN5veeDR9M4V0t0EwKRVVZ6qS5vElzeOcFdspvYbZ4ud3dw+ljZpSTSEkiThrkp" "WXGDfHNkIp19+2k60FeD+QTawvLAyCT6HeNk1dUOpA9OIAf6iml/rAiSyKH98Ww6eqmMIh8u" "odiny6RsdSCWJU1zlgZzOKYk8sA/ev6bHor+Cn5Oksj9kkd/HordpH84N0QYPP6DpaH7IQN7" "byj6bgqDII1hmuEXb9CQi9eldDWo50d8T8GphN8N7rnq4fuknggv32Vp8LJer0CG9H4tsCxY" "JEYgcsRJ7Kskcci8R4llmPMZnj8XWCDD4p+68FHvfMy7Our9I7mdUPZ/6ONLxnju/mCB8Cos" "VyCSPN6T1Vj3lYfugySa56aB/rbbOOeDFL2NdBGIKV8BU7ryJhCvQJQ8LifShysQJY9x8T5X" "IuOicRGIYVzMARZlgHGOBbEwEcpwwjKOs8OUbgcpDcJIhUBS3OTBEukWeYzVZaw0HiGQdAgk" "PdQhpIXaKCV4AWI4R0/y1bXdShyy8grCeMLT+2B5JI5xP+k5dfe43PnBSUT6IBBIhv+Y9D8M" "uQ5L5KTb8zACMc1z6X8gjah+xzERyfjW7ZTj2+euuOJlu3nBPZTn3wtpJATCCaQ8wuxX8ojs" "lueS0E4af341TezYoN45uyGSHZR5YaVsHjQCqbV36RsId+iLo7bJ3efc96j0b5YDFFkgJb7E" "7YN55xdT1qlnZROhEQjTyBsGZfWVkof0Pbhh7muhhuBqmoVEMiu6WZgZRQqxVtPs6HqaYa+R" "+XRrldx1LmNoJZLCMqSGpfjbRB/Eu/PcyMPs+XDPugo+qySiNxGqvse98kikjtmyWXA65JEQ" "R53IY1JrraKtBtKo0cmjFvKocVdccfmK502QihJIInlI6mhX74w4ZnSUyMjJg0tY/ctX3rKV" "Ecc/bZoDIw+3XKX3ehgW+fJpiS+RPpZ05ehmuSlbqfny7iwRCLOjr1Y2CsoBiUgYnDg4fUjp" "CsmC5SEi8bE80pE00tzeBwtkSySXOj5YSIcu1dAL4UxXHi9CLNutbIwsjRzaE8ujvT25tC+a" "T7sgh70O5naepI+Dvbnke28uhd5/2i1bsTiO9eVI6UokEs+kBx6K/xf9PfYr/a3nF3oo/oua" "I338LXqb/u4oeG6e/wZRPGTfEGH8PYoxDpn0IKX03KQBSBmP9tyS5b48HwAZMAMhDZbIo70/" "uc8slIF4FuJXRSRq8+GPSQxE2mCJMIN6v5cU8lj8Gzx/q1IJC6bnW1cmnDgSfOkZk3EF0vOF" "CGVo9LNkYp9oeXwi94UwLBAWCb8fEf2QRkAOzBOx92TPhznnSo5xl0uj1FHupudh4Ps+5D4Q" "CCQ5dbzhjkYg3jtATPLgY0zGRD09EE4i8VfcElaaRyBcvpL04SYPb/roTUogCsgjyvKwXYFk" "YJ4RtSgTaWQCA4FkMkgkGZBIhhWg8YJfGAeRpAvdNM7SArG68KwkMg4CGRdqB22UHmyj1MAF" "Gu0/C2HwLnS18uoJvfpKSleQirkDZGz3SffOD3X/x1GZZwRPqoMTw4llu2oTIb7Tvkct2zWr" "riy921w3z41ASuxjgmqcH8b8iEgkH/IYe2YNpZ5dp8WhVmCpZbuKcp1GlFD2Sd+jwtNA50MS" "U19aTGmgPLRNX1m7Q24l5ARSbevLoyAW7n/IfeeWKlPJpkEH34M0+OIohi+MYoFw+uAd6HwH" "CK++aohCKs5GmupsArwCa7000rmcNRPMdjZTM743I7ye5sQ2ASWTabaSyAyMM/R8ur2SZjgr" "XJrtFXLXOV9ZyzcQTgstlGPazUm7supKy0RWYflVCeveTYNz3SNLpnbNoIbOqVTfOhnSmKLF" "Ua9hedTRlA5FQ3tdUuqQ3kdblTCtTSUQt2ylxcGpg+HmOYujub2EZraVuKuu5nVXJglkvjTO" "75UIJw1FP4F0Fbhlq4WSNvL1qFjUmeuWrRQ6dXRmyQm7S7Q01C7zDI80MtxSVQtSyFa7VMpV" "KwIpasUVN855pVVXmu55pEjZygiD7/TYClGwNF60s2kX5GB/vJq6rzwnez1YHvuieTIyvCyX" "n1kokkKiWhrRbOFADCOeQx/Op663pyKBTKQj8ayEQBQ/C0ogd6Uv8nfnrisUkQiE8Q8kjH/0" "3qaHLkIefXcUPdxcvymonsiNJIk8gnTB8JxFIrBMkC4eRdJgTBIRWCq9V7VAeLf6d4KRCUtE" "RCI71U356mslET7qpJ84Bvd8dV+ZqGTyOeYqhbA8hjif0pDox0oicR4/cpMIi4MlIgIBw6Pv" "uYxw3tG8J3egj4yqTYPmIEVzkZS5PErkEXsrqWRlJGKOcjeXRxmBmLQhCST6SuIZAlFpgwVy" "OSl9uOWrHszjcY9ANFoe40EGA6GMRwIZH1fiEIHEWCBhyCNMWWCCzYQo0woKLJEJNnBHP/Bh" "7sdn3QoIZHwY8gDjIY/xkIiMYT5A8QKlBM5BFmfoKS5h8W50Th/cPPep5vmYbuaERyBH1L3n" "ctPgUZFIjhaISR+883xs+y61edCkEIgjJ3BY9T64ea4FUmirFVelIpIjbumqEIKY0LqZsjte" "FHmURw7KmNO5jfK6X6SS4B5XHBVmdOWxlyohkMrwTspuX0s5rWtkuS4LhMWR27ZamudF3eul" "dOXeOhhRK7HM3R8sEV6FVXBhCVLI81QtJ/BupknBDVTYtoRyzj6Lz9dI+mCBGHHwyCKZys/W" "OumBsERYHk/HN9Pc+Eaaaa8ViRhxNNstwgynRaQx01kpNNvLaBbjLEV6WSY3DBr4HV8WNTu8" "QI5qbw4vpJmQyywmNF9SiBIHH5w4m6Z1NyNtTIMkJlPdhTotjMkyqtLVJNXvaK2T5MF9EFmy" "izQiaaO1SqePSvdZEkhHpVu+cuXRUablUSb3mfPd5nO1PLh0xSJJNM1L70kf3tVWkjg0fNIu" "7zBPpI98VxzSMHd7Hf3kgeQhJ+xCIHw0CaePFf4skceK7oRATKOcE8eevhraGMpXScOvluzy" "RsH1gQxa5x8PcbAocoXtTh7tQKrYHWNRFMrIdFx5ls69OYP2xwrwPl9WXh3uK6Njl6q1NHLo" "AKeLaC4EkSfiOBJngWRJueowxtMvlyGB5CB9ZNGR6AR6QCWOX+ivMQXPjUBEJj2cSu5gxDNE" "wbA8mL/33Zbnh3pUOcv0P/4hkrnlCkTJ4ydBvfOkE1cg1zRaJnElDx7NESf8bETiZbCIRJ2P" "5QrEIxFOGoN7vkRi+UrzhWAEcr/0YTDiUHyYhDeFGIEMt9/VXNEyeZsej16R8QnnTfc+dLnz" "I/p20g2E5tj2sTF1eKKSyKuYa1l4SO59eBvol0UgRiRSuopfuqd85ZVHQiBREQiLhEtY40Uc" "ikxOIA6nj5AC8mBZZEYgCoaFgTQywQmqEeKYiHcTHWDzZyyTLnxPA5lMiHRg3g6xtAnj+e6P" "0HlKDZ6jsXwDIZeuupVABC2QMZDHGKSPMd3m0qgjlOo/Bo5QRuiYrLpS+0DUqit317lOIPnh" "YzSubTdN9O9PEkiRo9IHy8MIhBNIse598JJdJRC194NXX41DKiny73QFwrvRuYTFfQ9OHpVa" "IBV6BZa5eZDhU3dZHumnF1Nhx1r39N3ybt5NvslddSUNdJNGrC3SA+GNg5OtzbJkN//CQpp4" "ej6V+1ZIAmmIbhJ5cA+kAdJgeYhA7DVIGiyLtdTsrJf0wUgpK7IqkUCcZIHMArMhEGaWPEMe" "znKabS2jeXaCp/HuaYjE3HXOd308zRdG2QtodgQiCc+XZbty9hWSx9TO6UggTdTY2QBU+YqZ" "0l6vaFMC4SW7hqbWhEC4hGXEwUxrr6Rmj0AkgUjZSiUPlgczu6PE3Sgou8/1ct3+6UPkwTvO" "O4vu2e8hyUMLxJSrkuTRpfsdncnNcnO21Vq7DCLIVafrsjj8WSIPVarKcFda8c7ylT61bFcS" "RzCdVgfGyy2C595+lo5cnkzbnALa4RQjZRTRnjiIldDuaLGcbcUCORAvxnOu9Di4XMXyMMmj" "68ocinz8PNJFAVJGriSRI3EWSI5mouDtexyKZuI7mXjOoAf+Gv2V/jP6s/AX8GAcQBoKiKT3" "Z+HBPgBpPKjF8TeMf4M0HnRuSVmLy1ksEemLxG8oepQwjDyMQB7uTUjk0V6dSjwCGQBZMI/G" "vxfMeVkDe/rL45t7JOKVyZDo1zQEglB8IbA0Hovz/LPEO484hsQ1SCCKDyWBKNRc3jkfiEQk" "ffDcfp+GIXWYNDLMuSIMt99Kmhset9+gJzS8I52PcTdX17JIzAGKLA+DJBCPQLw9ELN8Vwnk" "ohbIxf8fAom6AhGJSDlLlbDGS/kqQpksEMeGHCyRByeQLNtIJChkWfw+CGEElTRAthMAPsrB" "PAdjtt2NH3bgMF0u2U4H3gOrAz/+rfj3WimDL5aCSFKl94Ekws3zLl6BxdfYQh6cPHQCGdt9" "RCTCl0el8Wm7wWM0MXzCFYg5edfb+8jyH1SHJ7I8nGMikCzfXsoPHnTlISLRS3hLw4ek/6EE" "ovoffFRJdsdWWbpreh+Z59dRbudmzHeoxjmvvmIijBJIJfc45KKoLSKO3LZVVK4vj6oHE04v" "pZwzy5FaNieur9XymKTPwJpiq/4H34HOx5bw8SUsE7P3Y1JwFZW2Pk+TQ6tFHk2cQhzIw0EK" "cdYIzXieg+d5IpF1bgJhmTAsEZU8VAoRgVhKHLNZIhZSB2Mr5gqQh70YLBJ5zJFEosRhkAa6" "Z/f5TDkwsVn2fDAzfFMF3nk+vbuRZnY1KPA8o6Me1NL09hpIoUakwcxor1Q9D7PvgyXSWu4m" "DxaIkcjMtiI5poTv+ZivBSLpQx/Pnkgfnia5SR1mj4evUEg628qzVNfdKOgKZIKcd8UjH8e+" "OlIAgWTrtKEvhPKNE1lwqWq1P5PWBCCaIKeMLNoQmoAEMoE2hbNoqw0B9FTS2StzRSC7YqWg" "WDh0qY4OXayVd7slZRTRXkeVq0Qe8RyZ78dnPF54vQFMVekjpnaXn+grpVa8P4KEwunjCJer" "WCScOnomijwMD/wVwjD8Zw/G3l9cWCCCFsffkDZEKtHbIo6/Rm4ID0Ief48bedzSCUWJpH8p" "K8H1e0pcAyCPR7Q8Hol9L8hu9egPrkAeRcLgM7IGxb4W+j8PEkF8ifkXwmN4x89egZj5EOfz" "ZIFw+UoLRGQCQbgScZQ01Ds1Z4ZrWCBuKUsSyTtaHG9pPEKx3qQREcXwyGvCiMirkMorEMrr" "+giT19VR7vGERFgcpv+RKF95G+eX3dTBjI31KIH0qAZ6mgOBcLM8mkgebgJxPD0QBwJB4kis" "xIJIHJ1ApHQVlP7HBE2WAHFgnIhUMtFRZLM4bMYnAlHi6KZcJtpNeUwMQCJ50S7KdzrxY94h" "5NjtIpOJfAdI8Cyl+U8peXQd0wI5RmOROsYihYzuOkwj2w7QqM79cstgmv+wXByVpU/ezeNd" "5vaJxI5zfYS72X3OGwj5AEU+uiT9/Da170Mfmiji0HDfo9w+ACnsF0pk34daeVUaVrvOM86t" "gUTWIIlsc1NHOaRREd6elD7U7YPbqCr4AlXyXo/QVrV5EALJPK2a53wHCMuDl+zybvPKwFqq" "kfTxgizdlZN2I5vVng8pXamR+x/1Qfx3OL9ARNIQWUMNkAMzzVkl/Y5pzmpqsjHn0hVkMRPp" "RAlkNTWDWTxqgUjqYIFwErETAhFpiESWgMV4VuOsyPOQwnOQRaJ0ZTYMmnl/gcwKMs00OzSD" "5gYTzAlMp3lBBZ++O8c/hZ4OqNN1Gb7bY15gEs3116uDEv01cqvg03iWOTB3m5sbBvliqGfl" "vKsKerZbnXf1THepsEDGROnKu8rKjHxE+/NSrip0E8cSPCfhy6Wl/jxhWSAXQBYQRksgj1aH" "8mhVJI/WgLVWPq2L5MppunsuT6UXomW0Ae83RHIgjGzaaGfTZitbGuPbkDA4aex0yml3vAKU" "IVkoeXDqYHzvL9F9Dk4deRBIgYhDCUT3OxwlkAN4fzhaiPSRLz0OThycMHiDoPPpYjpxsVgE" "chTSONqbLfI42jPB5Vh8Aj3wl75f6M9IGAzPWSI89wrkr713pYT119ht+otzk/5qKx60VAJ5" "sIe5KaUslsffem9hrhKISSOcOrxJxJtITH9E8YMrkf5JZEDP9yIML0oeHoFoYRiBDORRpw4v" "g2Kf0+Do565MBkc/ld4HjzKHOAaLMLwCUXgF4hXJUEhjKAQy1JVHMkPtt0UeQyNvuKNgvUZD" "IJAhkVdosPWKjMPCr9DQ8CV63FFnYak+yCv3NNBV8/zlpFVXabJs14xMH6VxL8Tp8QhEJY90" "x5M+RBzcRLdBBCKJ6JVXCtP3UP0N3esQVNlKSSQhkCSJsECiHnE4asyPKQpAYayTimIdVBht" "h0Q82K1ICucom/d9BE9BEMcpRTfQJYkggYzm+827DuL9IUrhmwb9h2hc4IiSCJeuPMeWeEUi" "AgEF4cOU7dtHuf59iVN3rUNUGNpPhYG9VBzcT2VIIOUWo1JIadLZV3uoyL+Dcju2SAIpDrxI" "5eEdVAKR5HdtpPxOPpqdl+pulc2CVXxRVFitvJK+h+551IS3UlHnatltzrvOpf8BURS0LqXM" "k8/IOEk2CW4RYcjy3ehGmTOmfCVw+QpMs7gPsoaaLFPCWoX5KiUQkYhKHNN1GUvEIajexyxn" "hSpZsTx08pitk4cIBIljjvU8zULaaA48Q9P882m6n0tVc3Xj3KBWXc0MzhGa9XEls8IzIY6Z" "NA8imYfnJHkEZog8+LRdJZJGEYgAeXh5xkuoXpgfrJHbBZ8L1dGzwVpaEKwWlkTq5Y6PZeF6" "Whap9VDjsjxcJaftLo9UCCvw3BLGGCmjlVY5JMCUuawOK9bg/RqrWMpUa+0iWg/W4ZlZHymk" "deECWmcXYK6e1zuFIowXnTJ6wS5W8rBykTZy5Cra7bEyehHsipV7KFUpAwKRklUPkkZPMZ14" "uZ6OX2qQ9CH9D0jjcG8VnXm1SWTCK628AuHEwfAyXRYIC4PH472FKnVw+oAskuWRQUdjmQIE" "8l/0x55f6E+9v0Icv0IgvxK/E6HE79KfII6/RO/Qnx2Wx236s31D+M8opBG/Q3+BOB7UKHHc" "ktHAIhGZxBNwKmEejl3rx1UP32uuumlEiH9HA2LJDIx+o/kqgZZHfwbFNbHPtTg+78en9Jjz" "CeTxkQhkcEyJRGRif+DOFe/TY/Z7+NFXDHHepcGQhJchIo93RR6ClsaQ8Os0OAJCrwlGIEYi" "LuGXaVjkMrhII6xLcv4VH+cuInF3oL8su83N5kFTwkrl1CFNdE4evZhrgXDpyvEkEJaIo5OH" "YIk8xsmS3bAs3ZXEYYEIRBEJqKQBsuxE8zxL3qmeh4hE8FO2rcpX2UgauUgauZw4HJU88qM6" "fYCCaCcVQhiFWhyFTpumFXK5QEXR83h/jnLtM5DJKcoInaRxQd4PclTKV9xMT+GGevdBGtO1" "j0a37aa0zr1yiVRO+Ki+A+Qo0sZR6YMUQCSFEbX/g/d8JHagqwRSENxHWe3baELrC0gXvJLq" "gEikjHsgkjr2Jh2eyKWskuAugNQR3iUCKezeTFkXVtGE8y2U17meyoIQSBgJBOKogkyqQ1uT" "JFIr7zdTZXAj1UbU0e01oQ1U2L6cJp5dQPltS/G8niZH1HW1XLaq5x3nNtIIC8TZiKSxQeTR" "CFk0QhpNkXWQA4uD56tlnB5uoRmWksYMs4wXNPiWyhLeGdZyEYjqeSxXAgFzOHl4UsdMpI0Z" "4edoRlCJYxrEMU3EMfcegaijSlggs3TySMjDYMQhEvEn0oeiSS6GYnnwHR/qZkHIIjxFbhjk" "49m98ngmVCviYBaGalx5PA+psECWWpNEIMvDEEeoRsbl4RoIolZTrYA4WCY8ropUUotd4bLS" "0vKAUNZaFTKyQNZZpZBHCW2wSiCQEpGIwAKBPDhxbAgX0qYQ5GFDIlYepJFPm5E0mC0QxzbI" "oe3KAmp77/kkeajkUazLVIUyN41ylgaLggXC8tgHqfAmwb6vN9Cxviolj3iulKsO9ubTwXie" "2zBnWXACkQ2D3OeQclW2lK68yeNobLykjxPcA2FxiEA0JpH8EXL4c+wO/dEB1m1wk/4E/mzf" "glBu0X8ijTB/iWOMI5FogTzoEQqXtf7Wy+Wt68JDMQ/xa8K9ElEiGXXxe/rlf39JV+9epG/u" "BOmbux301d3T9OWdMxhP0dc/n5F3394N0bVfXqNf/883kInCK5FHnS/7CeRLVyCMSSTeJMIC" "EaIfuSWrZHEomTCDrHfpsci7SiL2OwKLhMUxRKeOIdZbkMZbGN+QuYhD81gYAgm/8k8FImlE" "C2Q4BMIM47s+rD6RCZ+DxSLho0vU8SWQiHBRUOUsJQ9XIPcrX7kCQfqw1T6P8bYSSKZJHpwy" "rKCIIwfzHCcIKXDq0MmD5WH5NEYkmLM8jEA0eXanwumkfBEKzzuQNNpBmxJItE0oirYimVyg" "YgikOHqOiiCRAkgkH+REXkLKOEETgsek98GpY5z/MKUhhfDy3dQOvob2AGUFDtFEvmWQZQLy" "gpw6+OBEHpPloThERRBGbvcOyul6kYoCe2QHelFoLxX4d8nO86IAEoY+uiSxjJf7IbupgoFA" "SvnI9o71lNO+loq6N0kC4dN3edUVH2FS0r0RwuDjSVgivNfDXBjFy3cTvY8KP77b2UKVPj6G" "hHsfG6k6uIZKu5bjXQue9aorXsILgTQhdXDaECzIg/d72JxCVkv6mGaItGBsgUhaRCZTQyuo" "IbCYGoOL8bwMglhGsyLLpfcxy+L5EpoZXkTNoedpenABTQs+S9MCiSW7U33zMM7Fu7me8pXa" "NKgwApkpzArPThKIyMOfnDy4dPVMiG8VVAJhefDlUM8EpwhGHHLHR3gShDFJ7vZQ1Io8DCyQ" "xQHIIqLlgXEFkgiz3FLiWGnVCSyP5Va1K5KVwCuQ1RDGKkdJQ8SBdwwnj/UCBOKUyijpgwVi" "FSShpJEPYRQInEC22aW0I1YhO8z399VKX2OXU6LkAans66mQPoeIBMLg5jnDn3HPY1+0UBrm" "u6Jqae7ZV6ZQxztz6HC0QDYJskBO9BXJ+0M9+SIT0zAXafTDlKtM8jgWzxBOxMfRA3/oUwJx" "if9Mf4jdVeKIeOQBcfwpigQSuyXSYHj+Z+empBAWyIMQyF/1/K9IGsyDev632E8uIpSe+wvk" "+q9v03c/t9NH13fSRz9tpo9uraUPboNb6+nD2xvAJvroDt7feUH44NZG4dPb2+izWwfph1+6" "6c5/fSTiuAckDDeFaHnwODD6mcAJxJWHFkiCDwSWhzd1JNBpREtE8TYNsiEP+02RR0Icb2qU" "QIT+yeM+CUSNaj403KMujtJ3nj9l99Eo+yKNxjjG6aOxzkVJILKM1xWIZ/e5Th7uxkFXIDp9" "aIFk2Eog3CRnibAssiGLXIgjNwqRRIOqXGVzAvEhnXQjpahRnm0euyCUTiEH0siFLHItr0CY" "Djy3KywWCMsDySN6AclEpQ8jkBIgIrHPUoF1hvL48EReuss7zPm+j9BxCOMITUAqmeA7RJlg" "gv8gZUEqE7r3y5jjP0R5oSMijwItj8KQTh8R3TiPHESq2E/FoX0qdXA5y79TmucTWjdRXhcf" "x74L7/mY9l1UFNyBcTu+iwRi7aRKJrKDygJbJXmo8hXmfCth22qaeGElFXauQ9rYIqWrmjAv" "1d0iKIG8QJMsfXEUXxgVgjjCmyV9cOmqli+K6uCj2VvkzCsWiOz/YIE466nJ5hVYa2iqlRBH" "o7WSpkaYFqQRtXFQYJHg/fTICmoMLKIp/gXU4F9IUwPPQxKQSWgxTYM0mmTvx3N6/weftsun" "7vJeD8U0SGS6iGNeUuPcCGSmEQiXr8AslkiwWcpXSWUrwLcOskBYHkogja40EiWrZIGwPBZK" "4lCp4zkRR52kDmZhQAlkRVgLxKrTAqkVgSiJeKRhV0EWVRBKpYwsjRa7XEYpVbEw9JzHdXal" "K5ANSBEbnGLayGUpTiJIHy/21dAmp0xShxApkLTxAj7nEtb2fqWqHXGMTpmnZFVMJ15tQjJ5" "FmkD76MFkjpUuUotz93XUwAKZZmuaZ4zUrbq4QSSBXlMoshHiyCSMqSQHEkaCWEAfsb3jvVm" "69SRKRJRZEj6ONYDgfwx/iuE8YvwH9Ff6ff2HfqDpeTxh/Bt+o/IbSUTJBIuZ4k0tET+FL2p" "5pAEp5D/ZGn0qNHgJpHYDQ8/QSo/0YPRa5JG+LiT7+5200c3XqQPrq+n926upPdvrhNEHDc8" "cwiERfLJ7c308a0N+llJ5eO7m+iTO+vpk1vr6LObe+jHO3EaYH9xH4l8jvEzwcxNIhkY/QTf" "+5gGOR/iM484Yh/qOYtC4RUIJ5FB4XdoEMTwGFIGo+ZX9PMbgpLGG5rXaCDE0V8gQ+xX3fQx" "OHJJeiHDrZdFHEOsi1omSiLMMPA4ZPIERPIkhPKU3UujRSJIH0Kv9D9YIOrsq6jCUSiJOMDW" "u8655xFy4ZVXE0E2BJIDWeQ4oSSUQNTSXXf/h4iEUUt2JzKWXm1l3yuPfCSOPKcV71ul58EU" "2hCHDVFAICUxwzkFi8Q6C85QkXUaInmJCiInNSfwfEL1OPj0XT6uhO875wTCq6/8vDmQ7/04" "Iquu8vz7Zed5PsbC0EGkjIMQwUGkiwNUAnGUyM5zjBBJIdJHTudWym7fQvlIJsWBnZJE8iET" "Pmk3r2szlQS3IYHwkSVGImrlVRUf384rsCCS4u4NkAcEgATCZaxqSKS0e50cW1LWvUYujVJH" "l7BIeORluy9AFFuAuvNjMpewkEImh3i5LqcP3jy4US3bdbh8xSuwkCq0PFgcDeFlNDW8AkAi" "4Ra37zFNC2QaC4Tv//A/R3Vd86mu82mqx8gXRzXwVbWB5wDkAYE0BZ8RkYhA9HEl07lZniQO" "TwIxjXOdQGZJ6phFc4JculKwQNwUwglErq6d5pavktOHTh2hhqT04RXIQq9A9B3mfJ+5iCOs" "0sdKq55W2IkEIuKwaiCKWmqRUYljtVUl8uifOlgYPK5zypPTh6VKVywRlgmXqbZCCrwpkJ9Z" "LFuiJbSNBdFTRzvwb3CDXOQRrfCUrCokgeyOl4hEDvRW09GXJ+nGuZLHkb5qant7DhJFOR3g" "Xkc830VWXemylZSu4nl0BCnl9MuVsqtclu1CFqpUpQTC/Q8zT4iDy1YGJZEH/qPnv+nfYz/T" "v9vAugth3BVp/D58SwmE+x8xVdL6Y/yW5o6I4w+xm65Q/gwJ/CV2wxWJ4a+uRK4npRCGBfLt" "7TB9eG0TvXN9Ob1zYym9f30lXflpOcYVMmc+uLEatNB7t1ZBJJDGjQ308e01kk5YLh/eXKO+" "c3sVfXRzo/oOS+XmZvr01j669t8X6ZHol/Sw8wVk9Rk9EvvMFQgzAMJgaTwKeZg5C8SbPAyD" "nPckaXglwiUsFy2MQZG3RSADrbfBmzKXZ0kcSiA8H/h/SSBS0rJU6kiUr4xA+mgopCEC4XtA" "wAi+A4QvkLL03efgKT591+KTd2OUYkUp1XYgDQ3m6Rbg0baBBYlogdiJ0tVEIxAhqEd+FxaB" "ZDvmO0Hpg6gk4oM0ujVdlIPEkRvpFIF4y1d5OnlI6QqpIx8SKeCeh3NBKAbl8Xaq7u0A7Zi3" "UhnkUQqxlEQgkAgEEjkNibyE8aRLMQQiQCJFYRDio9qPScmqMJToe7BAsrv20IROiMG3lwqC" "B5AqWB4sEZU+SsIQSHCfCKTIv1v2fRT6kDb8u6TnUejbDnlsoqzWdZTTvhFSQdoIb4dEtiN1" "6NVX3DTXByXWskz0nR/VYT6qfStV+TdTUXsL5Z1finElntVGQaZWdpvznR+baQo3z2UF1kaR" "iNswdzZJ/6ORG+ZIHk32Wmmaq/TB8xbMIYfIMpk3SQJZSU0sk4hhGQTDx7k/TzWQRkX7bKpo" "nQmaqap9FtV2zqFJ3fOQTviec7XrvMnsOu8nkBmuSOYmH9cuApntEQikEUxeeZVomCd6H8wz" "oan0TKCRng1McQWSkIhKH4pE38Mg6SNYKfJYjHGZ2+eoUzKxE7A8RCCaRPqocstUSh5IG45K" "HGucEi2OMlobUb0OVcIqlqQhPY8Il6wKaSu+y6utXoxWInFU0eHL0+nslYWQRpWUrbbHalTy" "gCy2cymKReKovR178PkebpzHi0Qoe2MKbpL3frmRTiJZ8EbBvVoi+/WGQR5ZHAbZYd6jVl7d" "TyCcQFyZxDPdBOKVx8me8fTA76K/iDx+B3n8u/UL/Q7JQ4kE8nAwRn+mP3BZyxXIHbc/YhKI" "KWX9CWmC+YsHI5K/xK4JnDxYJnf+91f0/tVddOXHRfT21WfpyvVFwjvXFuDdQrr06SJq722m" "rccRQ1dWUmFNJj2RPpz+/MiD9OCjD9OojCepojGXFm+qpJ2nJ1PozaX05vfrkF5W0/u31khZ" "iyXCKeWjm+vp8xsn6Oqv32mBfH6vQDh59BNIgveTYIFI4jDJw4t9RUvjPog03ugnE8Vg69X7" "CsTb/xhqXxJxKHo1Sh7DLTUfFonjOS7jiHCMRoSi9HjQoSfAqLBDYy0lDilZueKw8c4SgXD/" "g+XBO85N8shhUXDPww5qgQRpYlT1QHLl86CWCN5H9AZCFojVLeTa3ZBCN4Sgxny7i3It1QfJ" "ZZFY7ZI88gVulJ/Hd89L8iiLtlJ1TzvVgMp4G5UhhZQ6CYEUI4EUI4GUQCClNrBO4f1JJIaT" "VGadpHIGiaQcMimHTCpsnh/H58fw+TEI4igVcCLx7aeCANIH5FHEScS3RxrnhYHdEMdeKuMy" "lqY0uAfsdldfFcsd6C9Qbucm/N0WKkMCKQ/xRsGtVILn0sAW2X0uAmHCzDaB5cH9Dy5fVfg2" "SPoo962TXee1SBp8fAkfW1Le1UK1wQ0ijylmCa/NK6426WNLTPrg/sc6kcZUzTRuonMKgSSm" "W3wcyUqZTw0toymhpWAxTQkvQZJZRPVBvpnwOarqeprK22ZRWesMKrswjcpBBahun4lUMpum" "+ObRVO55+E3/Y55IZLp3v4eUreYmVl2xPLRAlDyaPfLgctV0fbe5Shzc+1Co/odXIG7qYHEE" "FQvCkwUjEO53iDzC9SIQLl0pgVS5AnHLVveRx0pJIpVaIBUiDLdkJfPEM0tkg1OuVluFi2ht" "sFSlDy5jWZxGymgzfvy3Ib28GK0WcWyPVdAOjLt6qmhP3yQRhvQ+YmUQRA0d7msSeeyMmuW6" "pWqzoF6yu1dvGmRZHIgW0dGLdZBDmQiEUwhz4fVpdORiqVu+YnnIbvMetWFQoXacu/Loj15x" "xfI4CZkwpyCPUz3p9MC/BZE8Qnchjp8VkMfvopBJHCMkwenkP2J3NUgm0Vsy/kG4KbBIBC0Q" "5s/RnwQlkmsJoYDvb/fS5e8W0mtX59LrV5+j1394lt7A+Na156j7tVm0dk89/WPwYHp8zDga" "9lQqDR2ZQk+MyaRhI7No2JiJNGI0GJVNw0enAXw2dhwNGj6Ghox8nDYfaqDo+0vog+sqnXxy" "e6P0UDiVfHBzq/RYBjgsjU8hk09l7M+jWiIDrY8gBIwQhuIDLZH3tDyUQAZG3kni0chbAkuD" "xwHhN4WBbup4w527fZF+AjEN9SSBWBfvkQeLYpgVl16IetZpBPJ4nAUCcQwPWBgtSMSm0RFb" "UgifupsJMpBExtvcODelK0tWXGVBIqrfcS9cxpL+hyuQsJIKi4RXXVmMSiC8cTDf9kEIPioC" "hVGWSJeswGJ5cCLJRfrItS8IvFw3zwI2N8rPSwIpRTIpRSophjiKnbMyltgsEcyFM5ifpjIG" "IimLnBJZVEEeVfYpJIGTVGkxJzAHGMuQSvg75RBJOVJJefiIInSISgL7KL97F+V1bYcQdoow" "KsL7kSQOUCXGcnP+FTfNw7uF0uAOiAOpI7QDaWMHvredSv1bqKgTicQHEQRekGW71UGIJLBV" "RiWQxOqr6tAWqgnyabubdPrYJJdFlXQso/LOFfhsnZSvGmTfxxYIg1H7Php0EnEFEkH6iHDP" "g0tYLSKMpjAfOdJCc6K8nLeFGlkgwSWAD0xkeSykOsiDBVLte5oqO2ZrgTQpzjchjbBEZlB9" "1yxq8M2BQOaJQGT1VWCe6n9w6vA0zmd6xpm6DzIroAQy958KZLorD9MDeTY4VXgu2KAF0qAS" "hxbI/RLI8+FaWhSqpSWhamFRmMcqyKJeCwM49a5AuGxlBLI6omiRPgg3zD3CYPDMPY/1mHPy" "2GiXS+p4sXcSHXx9Nm0IF9PGaAVtjVVLqthm1yB5VOFZJQ+WBacOJY0KVbbSpaszb84j/yer" "VflKL9flBMINdF6uuzdeSvsM0ULpe5jUwXMWBpe1ej5bQ+dfa5RbBVkeR/EZbxBkcSiJaHno" "noeXY/GJdLwnSzgZz1LygDjMeCKeRg/8tvtn+m33Hfqt7xb9LogRCeS3zh2RCPN7564rEJbH" "76N3NCySm/dKRIuES1oGIw8Wyhc3L9Ar382jl6/OEYFc/mEuvfL9XDrbM5mmPpdNT41jYWTS" "8FHjaQQE8vjY8cKI0Rk0fGwmDR2NZ8iE4XdPpGTQkNGpNHgUk0IDR4yitOzxNHdxMYXefobe" "ud5C7/20QlLIu9fXgA303d04PWIrgTxif5LEAJePRCACxGEEkpCJ4tHwFRcjkEfCkFRIcX+B" "eJKHK49/LhBTuhqqy1ZGFMN00hgWiblzkQd4AvOR4ElJIDYEYmNu05gwUoYVpQl2DAnDETIi" "ERpvccnKkoMSJ4Ici1NHWBrmvJoqCxLI0mdb8TtGGuhRLRZOJHiXZ7NUArJ5MNvmlOGDCJRA" "iqMA4ijmZbummQ555NgqgeRBGPmQB0tEcV7tAYlcoLwIhGKxLCAOpBOmRERyFuI4QxXOGapk" "IJFypBAWRjXEUQ2BVGJkaXAKMWM5BFIWYY5BKsfwnWP47jGqsY/i7w5TeXCfpAxemlsJWVRD" "HjWgOgKRIIWUSyrZIwnErLri3eY1jM3jDshkm0iEr6it5r4IN9Mhk+LO9dL7qOANhLIX5EWV" "RJBC6iJbhHphM6SxAT/ma6gmsE4ujprM6YMlEuFm+WZqEplskqW7DVy+iih5cNO8IbwCwlmG" "v1kuSYMTBpepeNUVY3oiDZJCltAkI5EgS2Q+VXfNpQokjvLW6QAppLUJSYQlMpWqMa/rbKbJ" "3TO1SPSyXfe0XU4cnqW7IU4dGrNpMMgJBBLhhrk0zhMCMfJ42pXHNEihSUkj2JBonAcUSiA6" "eegVWLzP458JRJWt6t0VVyyRFnlWCcTIQ7BM+UqnDt0wX6vFYQTCKUPGSAW94NSqpBGtU0Ag" "u/AbtyNe65audkJAfBnUbgjF2/fgPsgefGdfvFbKVLLaistV8Uo69spUjOUijv09ZbJhcE9c" "yYMPSTTNcz4U8SDmxy5X0mEIR/oeIo58EQefZ2XSh8hDH45oSlYsD0aljiw3eXgFIiUsFshv" "Om/Rv/nu0L+FQPi2kohGSls2j7fp353brkA4hShu0n9Ebwh/dBRGIn+EMBJp5EcpI138ehpd" "/G4mEsg0uvR9M0U+aKLFWwopJSsTCSKFBj+RTkPHpEMKaUgbGTQM6YJFYRCxYHx8TJYaIZfh" "KWlU1jCBnkzF9yGSoU8imYxKo/SccbRubw29eXUZvXdttdtTef+nNfTNLZ+bOJIF8pHLo5EP" "Fdb7ydJA6lC8IwyIXHFheQjBt0QgA0MQS5gTyT9JHRh5CW+SROzL7mZClUC0QMIQSFj1PYaG" "4hghjhDgMRyVcWgYIgnx9bVRGgmeYnEEQDBCTwUiNBbjuLANIUTxwx2FHGyaYEVoAiQy0Y7g" "R99Guojgxz0iAuHd5dLXiPhlz4fa9+FXS3dl13lQl7lClBcFnE54A6Gtdp7nc/KI+oUSCKQE" "CaTIUbvOc20lkDy77R6BqMZ5G77fhu9foAIIpAiUR1ulnFXFvRAIpByJpArURs9SnXCGap3T" "4JRQA4FUSSnrhAiDy1cqeUAe4WNUivRRFjyCH/sjkMMRqoNAJkWPUr1zGPODQr19iCaBeusg" "fvCVQCqQSsoCuyCaXfjbXZCMOq6kmsG8NrwT390u1EMmk/BcG3gR4thERbykt309lfs3630g" "agVWbVjJQ/Z/8LEl3ESPbJLTdieJPDap8pWmUR/d3hjhfsg6mhxeAwm0yB0fUwALpJGJmJVX" "yyCXZap8Za2UTYRNtkonU8NczlqkLpKCQOoC86mmew5VdEIgSBwsDhGISGQqVUIiVZjX8oGI" "Xc3U6JuFFDJHJKI2DM5J9D7clVcsjpnSNJ+j5TEnwMyQ9DHPoNPHs+HpbvowCUTkEZj8TwXC" "wlDUa2pFGly2YoEsjihM2coIhOVhBMLpY5VTDVlU0+qoEUe1jGafh5EIy4IFwg30TUgqW6JI" "GbFa2hqtTcgDsDROvPaMapZDGiyXHVLCqpGRJbKnx7PDHCM/7+kpFThxHL5UR6GPWmRjIO/v" "kPTBI0TBJSxegcVlq/29RSIPIaYSh/Q9evLdpvmxHr3yCvP+AuGVV8d7snXyyPSUrSYkyeNU" "bwY98JvAXWL+JXyHfhNS/Fv4rstvIRSWym9CkEz4JqRyy5XJ7+wbKomAPzq3kkRiBPJHkcd1" "+vjGaYp92UR93zXRxW+mUu83Myj+2XTKq06jx0ZkSaJ4YuwElS5YCqPGu7JQwsh0P5PvjVVJ" "hFPJU5l5tOEkxvQMkY8kE3xnxNixNAJSKZ2SSe/fWCbN+fdutkiP5P3rq5BEYvckkEcgDuZh" "60N6BHDqMMJ4xFYMiLzj4Yo7Gnk8HHrrvgJ5NPS6SCTR8/AK5BV5VvtAWCAvQwaMEshQnUCG" "QCBDIJAhEAXD0hiClDEUDAs5wnC+6xyMROIYyeIIWjQa8xSQHrFofATSsB3KRvpgYWQ7tsgj" "h6XhWEgTXJJS8jA7zLPsgN7vkUAlkaCszso2+0LknV+W8WZDEAUsjbifSplYAFKATEwfBJ9n" "W22Ug4SRG1FJo8C6gJRxnipi3PfohCg6qYwlwlJBAimDWKoglnJOIPxsnYFAzog8JsfO0hTQ" "ED8HMI+fofroS0gWXL46jvRxXMpVpQaIoyR4mIoDByGRgxDDIaq1j1BD7Bg1xY/TVB7BtLga" "G/GZkUhVcC9VhZA8IJDK4A6hCtRCHvUMEslkMMXaRVOQSCbbu6kujO9xT6Rrg1Du20yVgc1U" "gVRS7ttAFf71+Dc24t/YLAmEj2vnZbuy74MvjopskgTCEpnMF0pZGyCctVQTWoWEw433ZVQV" "WIa/X4b/DkgdEMO0cIscV9LEe0AgDEkkSBtTwkshoWVIMStEII0iEJ1CAjqBQCCVnSqBlEIa" "ZecbwBQIBJxXVGBe3TaV6jum0xSIpMk3ExKZLSfuem8bnBmAQAIzpXRlVl1J+tAJhMXxNJjP" "8kDamM/C+P8QiNv/4H0fSCYLtDCSBVJPS4K19whElu7qBNLiJpFE/4OFsdap0WUrLROzdFfk" "weWrKtoEEWyGBDZDGi/E6mhrvJ628QiB8MiwQLiMtad3ipJGXJW0uO9x5NJ02tlTIfD5VsmU" "S9pggbBUuN9x9PJkkQmnD5NCWl+fQScvTVHHlPQqcRyKF7mjSh0K0/dQIlECkRVXnh6IEUhS" "8tACYWkwL/VlAiSQfwn97IrjN0E1/9fgbRmVVG7Rv0aUQP41eBNcx/duguv0u+ANCEXx+8h1" "JJUbmp/o9851Gf9oX6PvbkfJ+aqe7C9rKf5FPUW/rKPDkVIaNXEMDR2diZSRLj/4QkoGkgTE" "MDrdLV1JKcsIREtE5AHBcEqZszaHnt6oU0qqlgfmo9Lz5G/53yqsHE+BN+fSu9eW07s3VtLb" "15bSlWtr6Pp/vaHKWdbHLl6BcPpgeQxw3hN5PGy9JzwSftcVx8NIIf+IvH1P+uC5EsgbngSS" "nEJYJl6BDIY4vAIZxgIJJ5ewhrq9Di5ZcepgeYCgI4wIRulxPHPj/ClIYzQSRxqkkQFpTLBZ" "FkoeOQInEVvm+VEHCUKnDyuMH/iw9DdyDVLS4jEo5DlqzDG9Eb3rnFddTbS6IAfeYd5NxTEf" "FcdZHgEqRhIpxrtCu5vyrE4kjnakC5ZGK5UiiRTbF4QySKIKAqmMd1Ap7wfhngivuJI+yDlZ" "ulsU4X7HS0gYZ5A0zkj6qIudoUmQx2SGn6NIIPYJCMT0OpA4mJBKHqXBQ1QKgZQGub+BxGEd" "oabocZrRc5Kae04IM5n4CZqOZNLoHIEUDuIH/AB+wPdBCnuoBhKphjyqQzuVOKy9+GHeQ00O" "RmcP/mYPNUAg9ZxKgtuo0r9F4GtrWR6lXevl+JLSrjVUEVgPISB1hFkeKoFw6aouskHOwaoJ" "rxOqgmshr9VU5ltBpb5lSDZL8PeL8e8tpho/3yTIQoBEIBJOH9PklN21spyX3zWARiArsSSd" "LIdYFkMgKoHU+lQCqYFAuOfBJSumBkmkCumj8kIjVRiJgOoLDVSPz6cgkUztnkHTu/Ud5yIO" "xSwtkNkskYARCGSCFML7PlggTwcNRiBTRR7Phaa7JSwRR1iNpnHOAlkUmSQYcSwKJQTCZaul" "YS5hVcmcl+6udCYlyUOW7YJVgIXhlYcrEO55IJ1sghS2xCeBOi2OycILHmkkAWGYxrmARHLo" "ciOde2uByELKWL2VtBfpgktV/E6N5W4CkSNLZKd5qZSuWCCcRrrff45OX56k5VEk0hCB8E7z" "WKLnofoe+bphnudJICqFsDQS6cMIJLl8dap3nIjDIAJJkkgSt1z+JXxLSwQCCd2gf9P8JvST" "jL8LXXf59zA/X5P57f/+HOKoo8gX5WR9WQF51NPBSBGNy0+VH/thY/BjnzKBRqYpHk/NoidT" "suSdSSQ8slS8yYNFM3xsFo2ZmEEH7EzKq0tLfDcly5UNf0+klJJNRfUZ1PVaM73F8vhxIcaF" "dOWHlfRf/8+3SfJ4RMuDJfIPyMLAojAp5CGI4yEkC1caHtz+B/dGQm/qpnqyQAZBFoN0AkmU" "r/j5FZGIEshl2QMyJHwRqPSh9n2olVYjII8RkMcITh5BW+QxnOUBRoZi9BQ+Gx1xKBVkWI6I" "IycagwxilIcxT+ThCHkQSAEEko8Ekm8rCjAviFpUGAM8RiP4PIzvhkUeZmVWDu9Mt/xA9T2y" "LW6edylBOF348e+SFVhFGLmMVQ6JVIByzKuiXVQT76J6UAeqkDbKnFYlEKSP2j4f1fV2U0W8" "XTYPFsjmwdOQySkqCp8SgVTbp6nGUVRp+F21o9JHla16IJW8Cit8nKpANeY1GGsix/B8BPI4" "RNXWYSSFozQd6WMmBMLMiiuB8LumqEohjdYhCII5iOcDSAX78CO/Bz/yLA8Wxl58dx9Nd0AM" "RPfSNDyzVCYjhdSFVdNcVmLxcl7fRirrXidU+TfICqyaEPc/NkIU6yGm9SKMyiAEE4I0Ai1a" "HMuFsu6lQiWohkDq/EgXISOJFbLvg48rmSUn7q5RS3gtXpHVgudVQpOtlvhKQz2wgCb5n6HJ" "vqdpSvdcagCNXXNoatdsasLY1Ik5mNIxk+rap0MqU6mmtZFqWyERvhSqo5EaO6fJke0zupup" "Galkph/y8DdrgTRrZkj5KiGPaSKP+SFOItPo2LlsunJwIEWPPZlooLM4Ig0yMiyPhZDGwsiU" "pNShVl7ViUSkhBVRvQ8jEj6yJJE+MHdqXYG4ez+iNXLeFUtjIz7fHKtX0ohNEThtKGngXZTL" "VpBHtEHSR3L/o0qnDh4rZeUVC2NvTzXt76tPSh37e6qo891ldLhH7TSXspZuoMvqK4iBd5nz" "0t390RJVvrpYJmmDy1cskIOxQr0Kq1Dmpv+hdpvn0SEnhw7iN/NgJIOORLLokJVFR62JGDPl" "/WEnk45Hszw9kExJHSd70uh4bzrQJawej0AM/yt024UTx/8KKTiNqASi+I3I44ZOJNfpt8Gf" "XFgqhstfLaPg5wUikMgXpdT5ThGNzRtFT6VnSToYk5NCI8dPpCfSExIxEpDn1ImCpIoUJRDz" "GQsivyaV9tlj8O+ovzPfZxGJPHSy4b8dnjKeShvzZOUXy+PtnxbTG1cX0sfXD7gC+bv1EdLE" "B4IIRI8P2++7EuEE8lBESSQpeXgE4jbX7xEI5AFpDPKUsAYnJRDdQA+zRJBEIJDBEMjgEAQS" "6gVx6X+YxMErrIb5IY+ATUN4HlAi4RVXI8O8dBfpA/LI5OTBwgB50agIg8WRbTvSB8lmaTg2" "fugVRZBHEaRRosfiGN5HwxBLSATiyoPTCASSB3nkceKw1XJdThnSMLc7NV1UivdlDgQCylgk" "MYiBiXZSdayTajBWxdox76DqeLukjyrud4CSKG8uPIfEcpbyI6epEOLgpbuVkAWXrybFuA9y" "BtI4TRW88spGMmGcl2QlluIkkspJqndOIZ2cpkbQEH2JGpyT4Diej9K02DGaGTtBs1kenEIg" "kBmQB7+f6qgEMtU+jHRxGP+r/hBNcw7hx5dFsh8pYx/SyV78W3vxb+2jGbH9SC4HaXb8kIzN" "eDeN5YI0MtXehb/ZSZN4FVaYm+ybIIkNUsKqCmyELDZQeQBSCaxFUlpL5ZBHORJHebBFCcS/" "AiyncgikOrCSahm8qw8sQ/pYro4n4ZN2MTYzEMdsZ51cHtUstw6yPFbIwYnTeVlvWF1hy7vQ" "GwO8A53Pt1pAc8KLaB54OryYng49jx/2hfiBf57mhfjCqGeoyQeRdM6gSW1NkEcDJDKZ6lon" "YT6JprQ3QDRNSCPTaaZvBiSi8fHzNJoF5gB1dEmidCW7zpE2fCfH0M0df6D39g+gxb7JrkBE" "HCHFwnCjFog6voQb5m7vQzfPF0dqIA0v1XK2lbf/YcpXq7RAuHm+1q6jdU49bYxCEnE+KXcK" "vdAz2UUJREnECOTYG/PpRUiGS1Y7IByTPrh5zhIxyNJdLQ2eq56HSh1dHy6ng7Kst1h2m+/R" "ez3kfCsIQcQhR7KrHecsCmY/n6pr5dG+cA7tCQJ/IW08M45WHRtNq4+PoTUnU2j96XR6sTOF" "dvpSaUd3Cu32pdF+fxrtC4HgePxdBu3pGksvXhhNm18aTRtOjKT1x5+kjSefoO0XUumAP4uO" "WONABp2IZtID/zP0CynuCv8jeMflfwZv0f+AJP5n+KYagwn+JfCTi0olShj/quH5+9dOku+j" "fPJ9XESBTwuo471cyqtVqUCkkDaRiprG0O7QSBqVlSvNcJaCEkYOjRitSloj0lKprGkiLdtR" "QeuP5dP6o0W08UgRtRwspO1txbRoe4Ys7eUlvSNTc1yRcHmLZSPJBULhzzjJVDWn0OVv5tDL" "PzxDr/84n177YT59+3Mf5PEx/S3yYZJEHgq/r0YI4+/hd7Q4dAIR3nYlMqntMH2380H6etdD" "9NnuR4WX94+lziPFAP+r4UQzLTuzkqa27RWJsDAe88qDRyOPsEce4WR5DEHCeAyiGOy3aIjP" "oqEYh0Miw7U8OI0MD1qy+ooFkgIyI6p0xaWqXEc10Ll0lW2pPkguyLcTAimJ2lQKaZRhLIvz" "cwQiCeOzEH7Ig/guE5CxQAio1VYQSIkIohtpwgcRIGVAEtUxP0YfVcY4gUAmmmJIo8hpoyLr" "Am07N5+iRybQa4fG0te7H6Zvdz9EX4HZ/hcpN3JWBMLLdtXKq7NUaZ9B6jhL9SKQc1QPidSw" "RCCGKlATTSQTSSOgjoURO0PT4mchBoD59NhL4CSALGLHpVzFKHlw+lAJZHqMOaZg2YDp0SOQ" "wmGMEEoUMnEOQDT7kUD204woy+MwrbC20Fd7H5Efw3/G1Z1/odVts6gqtJEqIA8WR6l/jVAW" "WouUtJ5qrfVIJxjD6+QcrBoIpR6JZHJ4LVIGr77icbUcmMhJg+/74OTRHFkt0mBmGpwWkch0" "a7nIozG4BAJZQk1IINMhi9ngGWc5LYquomXxtbQ8toaW4W+WRltoibOSFjnL6FlrMc0NLUDC" "mIdUMpMa2pvkWtr6C5Oo7nw9xnpqaJuMzxppRtc0mtnNNGl5NNFsMMffBIFMg0B4xVWTpA/V" "82iiw+dy6Dr+b/PTzj/SS2cyaUGwKUkeKn1MSRKIiEOvvlKlq2oljWC1IqxO2k2ceVUjAlkF" "VjuTII1JtB6i2IgksRnSUDTQJp06RByxBggF9Ch5bIMopHTVM0mtvtIYeey/ND0hD73vg0tV" "bvKIJ8pWatmuOjDx4ukR/9f/nxG5Hh5AWzsn0mr82K8/nUrb/1/S3vstqnTN+93v7Nnzzp53" "Zu+ZeWeH7janNttmRVFACSYwZ0XMgGJOmEUl55xzDkXlXICAudVuU+ccdn7PdZ0/4Hvu+36q" "Cmjo3WfO+eF7PWutWlQVRfF81vcOz2oNQaGFXIf73uZqiXZ1t0FuHiywBLmlttl9sPMosgSK" "8yi08HpXQeRAlosquGHQ4S8lu+Uy+svxEoJIvsYHP/u1UcHj18a/4FeGPw8BkD/+KED+Xa/g" "IeoHD4+07+9E89MQtL4XhBbSyWSV9GYXsWBpiLiQ+f6rsO7gdGSb5mPJquWY5x+EeX4hmOu/" "BGG7Q3CDgKF7uRmWLwLh+HIdbJ+uhf3zlbB+vgKmT1aj7XUg9B/6I7l5EbZFrZBqLgWLYC+M" "5ixdTq+3UgDC+/P8ViOtegvufHkYvV8eFd3/8hJGEzwYIBNMzwkcBBLDe6SnGGN8KiMDxAOR" "cQQMVn8H4gHIT/3RG0o2igPh7vMBHegmtfbV9B/AYzrBY7reSeAggOjtApDpDBCCB+uddhM5" "D4KIFx4Wgcd8g1nyH0s4/2HiyityG2YbAcOm8iA0Mkw4lLWGFEpwYYXZGBhmbLB7IGKm0Q0Q" "UhhBJJSgEUrQCLXqyGnoyV3o6TyWTkJUDIttBI+dTh12uUg07nBoaXIniJAT2UjuZANDxNpC" "UGjCbm0BnuXOGPLzyq4+gFUmbhisJWdRR66inqBQjx2kXdY6chMqgb7LXYXF4GA3ssOqKrK2" "iRtRJb07CSJ76LF9dlY1qZIm+3Ka/BUgDtkVOBRE2IFwLqRCtiNdlcqVcEiLk+v2EgHJQXIl" "hwgkh+xFNBYROPJpu4CcTCGinQQQSxKe58/E1wSJH/tOfJw9Hse1sVKFxRDZqFfuYyO5j60E" "h13SOJhIgHLLEo995tvkNG4TGOIRZU9ElC3efZ/z2+pug7abOGy7gUjrdUTyMu3mKwKPI3wj" "KTp+2MrHLhMwyH0YzsuaV4eMvNJuLI5ZLuIMwSKWwHHVeRPXXLdwzXlLtq84bxBUruG8/TJO" "EkiOkUOJ1p/AwfYo7G1RENlFLmR3405EEED2t0TgEDmRw26IRLWrpUqO0BitZXl6P/b3AUS3" "D1fbtuPDnLHy+XxP6iyehRttm5XzIHCcM+zADc1GxLetRVVdADQVC9FbNB0vc8fTxccofJ05" "fNDn/GXmCDwsnIzUtjXkNFTl1XVyGDcIDrfsDIoIgUaSWwyPZOc+BQyWfZeMAg5nOJJdu7xO" "hKuv+uc/eDuD3Ej9k7PI6dwtJbuZzm0ihobHeXD5bn+AyBpX9vVw1szHV1kj6Hd/80e/Nz0V" "s8h5hCLHsBIZ+iByEMHIMgYjz7QC+QSJXGMIcoyByGxfgZTm5YivW0paLEpsWITEOpaPKKlm" "IRKrF8p2equPOJMScRse0b7FF4WGxSg2+KDcsgQ/+5Xhr2AxSFgMES9IDAogvzJ+r0SgYP3Q" "gXil/8arp58Wo/FJIJqeBqH5WSD9QgHwWx2Chf7BSn4r+kT7K7bMRkLTLCxZE0jb61FExDN+" "6g/L58GwfrEati/XwP4Vj6tofyUdJ4B8tgz6j5dC99ESaD6Yi4YXs9D8aiE2RflJSIyT6OxA" "BrwWiR9btiYY+id70PVFtPShdH8eiY//5CKAPCdgvOeFxw81oZ8DmdC/bJe0oq0ZjcUb8TSb" "J4sRP/pHv1Fz3u08ftB9PgAgCh7TjC5MMzgJIo4+gOhsJCs5kL6wFTcMcsf5HIMFc/UmLCQH" "sogAsthoIgdihh9DxKyqr4LdYjeyikYFD4aIVcJY7ETCLAQNq0nAsZG0wW4k0T4BZB2JobGO" "ALKOAMLw2Ejw2GLXk9PQ0dW/BtvIdWwXgGix06G0nY+zMyGAbKZxE0Fkk6UVGy3NyKs5JFeb" "Q31erkK6mDCUIYwgsslcR1AgcNgaEG5vIDdRjwhRHW3XuUFSQ6BQ2i75kCop593OAKHt3QSR" "cHYitkrstVUQPMrd7sMDjwpEOSsRxcAQaKhR9ukxDmntI3iw9tuLxYUctCl4CDQIJEccxTjq" "LEaMqwQxHSRXsais+fCQv+OL3Ck4RtCIsKZitykJO4wJ0lDIt63da00iSKXQc6cSEFLIWSTT" "5J8kirYl46g9BcccqTjuTKaRtl3JtJ1I2/Gk26RbOMZ3HiRXEmOLwzF7nIIIwSSKoBJluojD" "Zs8tai+T87iKU+Q2ztB4znoNlx1xuOK46dUlZxwuEkTOO67gHEHktLiRswSAY+RGIiVstbc5" "QoGjbS8iGRqaA6JoDYPjII5qlVTz4AEvQDiMJRVXBtX3kd0Uii8yR/7kRdl/R19nDEdR8wrE" "WRkaEbht3494ggTDI5HGPql9BkmKI0IcCEMj684hpNNxdhwp5EK4cZAdiCfvwaErEQEjg2Ch" "RMBwqX3OfVTdP4LS7kOqfNeuAMLQ4O0s20akm0KRpluDDHMYcrQr8coN0h/KXjsfuXROhiYE" "yU3LkNIUKOGrXHIgcsMou1quvYjvcy4ih2INllwH35pWbk9rCxTXoZxHEMrtKvchDqRfEr3U" "EoBC7WLkNC5CdsMC2iaA/Kvhb/hXAgjrf+n/gn/z6k+iX+n/IPo3wx+826xf677rp2+8+g/d" "1wjr/QatT7aj+pE/6h8vQ92jAESc85ekeX9ozPdf4QUK93DsPjsXhXZ/1DxZCO2Hi2D4xA/G" "T5bD/FmIqA8gq2l/JUyfBso5uo8Wo/XDuWh6NYs0ExWPpuNcziL4rlC5EnY7ntfkUZxPQBDO" "p66TsuLuLw6g67N9uP/FZYwxv09O5D2MNjzDWP0zgcZYw2NRH0AIHu7Kq0nuxsH++Y8Fug70" "5i4e8g/+ecZouirL7Re6GggQFb7qwgyDynt43Md0Nzxm6VSSnGExW+cOW7kBoiCiALKA5GMw" "EUSMWKw3Yqk0EKpciCrhZffBwCBw2Gw0MkwsJDNWmxkQBA2rAscmhwmbCB488v56gQnJZiCY" "GOg8HT3OANGS69BhO407yIHsIoiwFEDa5dh2CWcpiGwVoLTR5FWJ9/JmDficXmVPxueZys19" "lDWBrlyTZNmSzeRAdloZHI3Y52jEftIBRwON9djL5bt2VX21m+Cxi5zIDoLFdoFHBXawTBUE" "kUpyLhUCkP3kQA47qggSVQKHSIFHBY64KnC0oxLRHnBIUl1VZUlOxMHlveQ+2IWQDtoYJIU0" "0ZPz4NAVgSTSUUjPVSQu5AjpKElbs3HoUAQ5lJOWFPqZLHquTBywpmO/NY2glEYwykCMM4ug" "kEWwSKfJPxVHCCQxNgZHGo470nGCdNKVhlOk0x1pONORSvtJOOFMoMdv4yg5jihyIkcJHAyR" "I7TN8Ig0XiLHcQkxBIxjpBO2azhN556hx8/Q9jnSJQLOVXEft8h9KF0mcWjrgv2ahLXO2mJx" "2g2Rw5w0Z2CQ42BIHNNF4rg+igAZiRjtIcToDtGxwyTa1rsT6N4kusp/KIDsFYhc1O5Ee/ki" "guwEchD//2HC7iTLsAm3bAyNvQKQBOdBchv7xH30B0iyGyAqZLWb9iOQ3RWJtI4IL0CSXe4Q" "FrmKVOd2pJIb4dCVBx6Zru0KIP3cR+W9owSQg7LmFUOD3UeacQMSNasIGuuQY9mAVEMogWQt" "8luD6D0P/r3ZmRjIReRZ6BzzGqRrAukifDlSW4KR3hZMroSciJFDVaslcc7gKJYkejCdvwzF" "1iAJXTFAeJ2rYtsyb+iqhJPsen/kan2R1boIGU2Lkdm8CMU6f1SQGaiix6usfvgZQ4P1L7o/" "kv7cDyAKIuJIjH9U27o/DQDIr7TfekflThREPvmDHWX3FqDs/iJU3/dFgX2xXPEvXL5ikPPg" "6iifAFJwCK6VL0b909lofjETmo8XkrvwFZfBoDB/FuQVh7MsNJo+DUD7B4vJ3fggoSYAxa75" "qH0+HtUvpqH82STcavCBX1iwhK/49fh1FgSobQbLml3LoHu+C64v9sH5aThcn+7Hd//nXYwg" "eIwkWIwyKoiM1T8RefIhnmT6hH4uRHo/3BCZr3URQBYN+eV9nTUJK9ubfgQeHoCQCzF0CUCm" "ETymETymEjimaa2S65in4x4PEoGEGwbnuHs/uNt8Nj0+W2fCHNI8nQIJNw9yGW8AAUQaCAka" "q212hJLCbMp5SPmuxUTuw4QwMzkNC4HCptzHJruZ4GGW7fUO5Uo22BU81tvIhZB43EzaaiWn" "QaDYSdpNoNhN4GDtIojsEpBoCCQaAcl2gYsGJQ1H6Z9h2IDPqapiGx7lzfWGLzIajmMzh61s" "Ch77HU00mbMacdCpIKIAUkfuQgFkN7mPXQQQdh0MjR0EKobIThIDJIJ0gCASZa9CFEEk2kHb" "DBAHA6QSR10KIJEuNzwIHKyDkgdxg8MjyYEUqNJdC8mcLVVX+625OGTPxxmCw1lrBvTV64f8" "Xtwt8cVxV4Fb+eQicgk8WfReMnCUdNyZiZOk4wwTe5qI4SHgcKbjtCuDoJGBCx1ZuNiVjdiu" "TJxnkLAbISdylKARTVAQ50GKsiiARJsIHBZ2HNcJHAQN+3WctbO7iMN5O4eq4pBkPodX+dPw" "kpRIkLjILsR+Ux4TgNivksiNEEROmjnJHkPgYFgQOHTRBIFonDIewUljNIEhmh6PojGKHouk" "bYIJQUT6PzyJdD0DhLXXW30lHejGCAlfnXHnQG5pNuFTgkH/z/HD7DG42b4BFwy7ZLXdy5YI" "XLXswQ1LOE3IW5Gl34KqlpVINO0W98EAYXCIAxnkPpQDSRaQRHhdiCdsleraLbDgHEhhz1Fk" "OFSnuceBMDzSXDvcANnmBYhUYNm3iDItm5HctgqJ2lWo7o1CRecBZBrWIYVDTppglOpWoEwb" "gi+yBkc0vqH/mebGpQQErrxaK+EqDmFxEp3FoJAbRfUTQ4OdBuc7GBweYDBAypzL1SKJ7pLd" "UhuHrPxQYqbXMCxBkW4Rys1+qKKLfA5fleh98LN/Nv4Vv9T/WeDBIPG4EZbHhXil+16cyL8Z" "vnMD4w/esNa/6Qgi2q8JMl+h8+NEFN6bh7K7i1HeOwfns1VVlU9AMHz8VyoxNGhc4BcI3+B1" "9KEFofbFFNS/mIpWchIcklIuxF8kEPl8uQIIh7VIHOKqfRCEhQF+WLAsGNtiQlD9bCJqXs5A" "GQGk+OlIXCxdSI+p0BnDg7UoYBUWL1stziSzZS2sH+2B7ZOdsH6yBa+/r8Ybbe/iDc0jr97U" "PBQN0z4WDdc9whj9I3El493w8IgB4t+mx4usaUNOFL15PvChiV7lP7q9Zbv9Nc1wB1PJgUzR" "uTBZ6yDZMbndhqntFszQmDGXHMcCAsY8I8GEAMK5j3f0HM6y4B2tRSXVde61r/TuKiyCRrDk" "OxgadgKBAxtI6+x2rLVZJXG+htxHKAFknZXdBcHDRuCwW7DZYVEAoVFExzZ5Q1sGyX1wCGuT" "tV2cxTbSDptyH+ECEAaJViQQYcDIMQ1NZIPdx5cZoxDbfBXm0lXeY50lyxFB0NhLOsDgcDXR" "xK4kAHE2kCOpp3MIIrZayXOEE0BYuwkgu9h1eFVBxxRA9tF42A0RBRCCBgPEqQDCIImmbdUL" "ouCx31qiqrCshe7wVbFKolvzEWHOQbgpU8p1edxHMDlpTMLL3Gl/96rYVB2Gkx2FONVRRCrE" "CYaII0fcRzTB4qiNgZEuEoCI8yCAONl1pOMsw6MzC5fv5OJqdx6u0BjbkYlz7EScifQzt8R5" "xHAoixwGO5AjBI4YyzWcpO1z5DIuMDQIDrHOm7hIDoN1hYByixzGi/wZ+Cx7LNIIEDmGIygm" "J3HZdVMl2B3XaLyCWNtlnLOcwynTKZr0Y3BMS6DQE0CMR3HGdIwUQ48dpf0jApRTAhQFEXEi" "niZC3T5ShHvhRG4e3EvAiPAmz8+4ldW0Bl/9IFT8WfZopOm34pr1AK6Sw7hm3Ycb9gOIs/O4" "R1zHTdse0W1yFvG2/QogDBOnBySe3EfEADFAuBKLez+U+9glAOGqq/zuQwSHcDpnm8CDnYi3" "8oqXLXFsRlbHFnEfWdZNAo5bzcFI0YfRPs1/xrVI065FsjZMQlhcumuvXfh3vzNfZI9AtWG5" "5EDyTCsFGumtK3G7xhc3K3wQV+knVVgpTcuQ1rYcWdpAZOuCkKMPQp52GXI1y5GtDZAxR+OP" "tOalkgOJr5iHW2Wk8rlIbViAfL3KhVRa2XkEoMbOWopqBzmQX+r+hl+2/1VJ+2f8q07BZLD+" "iP9FbuNfaRTpvxcxOP5V/zXpW9r+Gmt6vkHd3W3I7ZmNPIJHUcc8LApejoXLVmHRshUycYto" "EueJnMNYh26QW3k6EdXvEUBeTUPD66mofz6TAOIL3cc+KpRFbkPcCMn8OY8B0H60EDV3g7Eo" "MAxzl6zGpsggNH4wTeBR/t5klDybgoJHI7EvNghLglX4il+bwcXvZeHyEGyL2gT9i+0EkY3S" "6Hjn4/MKIKQ3GR7tfQBhvdX+QKntPt5s68Vbmh6M0NzDyPa7OFp1/Sfts6ZwNSbpuzGZNIWc" "xjTSVNIU0x1MJtcxSddBcmEigWMCQeNtjQWTSJM1VgWQdq644gorAoRBrXH1Dm1zUn0qwWOa" "5EWsEtbiMJePUS3ZHuheumQNAWQdAWSDGyBryYGsdec8wggeHLryOA8Gx1a3tjhpdFqVHFZ1" "jECyhRzJVocB20jb7Tpss7VLrmOnrY0ciHIf4QwPp9brRHbKSMed7UO6j2c507FXV4Dc+ph+" "SeaJuGDMI8fRLPA4TIrqaEaUq5km90ZxIgec9QSROuyz12KfJMrVuFdUTY6AZGVVifZZK2ni" "r8Ah0mE7Q8QtG7uQcjdIKhRI3D0hh+xlUn21z1pMcCgS53GYAHJYciEFApDdxgxZuiTclCW9" "INGOQsl/HHcW/6gDaanfhpOdRTjdwWKQEECcOeQ+MvsBRIWrGBzH3ABhnXSw00gnWLD7yMEl" "gge7kAud5EpcKQKQE+RCTtpvi47bbpLicJxgcsp6k1zHLQLHLQLHbYLCbVzpSCAloql5B135" "jsF7hTPFBSo3OAzfkexVQbjqvErnx+GS8zrBQ4WyzlljcZZcyinDMQUPchynCRpnzcdwznxc" "xtMEEq8rYSeid4ezJJS1j5wL3/cjnAASTgCJIIAoeJzWh3vhwcprXCP5jAEhYgJIhnEHweIQ" "rhMcGB5KBA4CA0ODnQcnzG/blANhYDA4Elz7FTxc+5BC28lu98Hg4NFTvsuOg8Xg8DiQ5H5N" "gwwOTpjzMu0lXVHeda+y7NvJBW3EjUYFjmwCSYouFDfq/JGhX4t82xbkWjYhy7QOcU3LkaRd" "IUu3V5hWECwGh7A+zhyBggZ/AgeHpdaoBRPta+QGUXyP80KbutNgMalEOs5XeJ1IiY2cjXUF" "ymmbcx6VkuugbVewOBDOgVTy6PBXPR/cC0IAYReSUe+DWyUzaFxADkT7VwwQweKX2j+59Wdx" "J/+s4+0/4JcEkH8haHi2BSgCkm+9+upvz1HUvQQ53TOQf3c2kvWzxB0sCloF3+Vr4BvoHt1a" "FxFM8JiC0mfjUPl0MhLapuNs3lTUPvIRF8IJck6UM0QUPJZ7AcJwaf/AF8mNK3E6NRg5Nh9U" "Pp+ECtb7E1HydCwKHo9HonEKfILCFMSCVvVBbPlKzPZbjsYHm6TJ0fLxRpg/2I3/839/7nYe" "j/AWOY63CCJ96gPIW5q7GNZ+zwuQlLLDPwmQW+VHMbatU6nVSbJjXJudRhvGtFgxutlK26QW" "C8a1mDGe9HarGZPaLJhC7mNqu5EgYsRM0iytqr7iRDqX9E5za4Y3L2KR5Uy4jDfApKquVrsd" "yFq7Q8ZQhoqFHIgAxKxyH+Q8GB7bCBY7nTaa8N0j7e+gcYfLju0uKz1uJnBYsN1ppHMM2GHX" "ewGy3cY5ECUVxmKItCt4ONWxSEstnuTPG/QZOYoCsMVSh2ttN/GlOw/CE1hh43EJWx12svNo" "FoBEd6iRncghciEHCSKHyIkcJpAcEtXSpD+UakjVpAqRVFk5PBChbXu5iCFylBxIjEu5Eg5v" "MUS4+mqfhauvSgggJXRuCW1zT0gegSMbewge7D4i7QWSTD/hKsFxgoiuet2Q34vylkPkQIpE" "7EBOkgM54cohiGQRLDIkdHWCYHLKycogaKQLOE46lTj3caZDOZHzHRy+yiCgqBDWGScrEWcc" "iTgrShCdcybgAinWwYonxxGPK64EXCN43OhMxo2OJDQ17cA3P7jKf507GbfMF3CJk+vOOFzm" "qix3LuQCuZDzlgvkNk4RHGJw2sDu4yhB45jAg8VuhKFyml0IgeSknsNZDJGDBA4CSHsEiQGy" "ByfJgZwiiJzSM0D24Bw5kQumfbhkPYiaxlUCswFhHQJKWdu6fgDZ5wVInCNCJc0dHrnB4egL" "XSW5wZHi2itjqnOvciCucJFUXtl2uQGys1/CfHtfAl3CWNtQci8S5b3R6ha1xq1I0KyRPEcu" "r5mlC5N8R6Z5A7KM6yXXkaBZIeGrHF6Z17IWudaNyLGsQ0GTPz7PHBzC+iBvLEpNnOMIRaFl" "ldyylvtA8rgPRBeIxHo/JNQtRULNEiTU+w5Qcq2vqrgiJdX4iNIaF5ET8UWxaTlKrctQavET" "cQhLZPCl11uMKsdiVNuWoMq2CD/7J52ChkirXIjSn7xSAHFDhORxIwP1jYxPv9YirXMisnve" "QWbnVJwvXCQTtxccNPLEvTh4NXxDViO+dQbBYwI5hrGI10yD78o1WBy0HhsP+7lDWfMFIrpP" "FUA4bMVioHCIi3MgrR8sRMOrmah7MR11H0xF+fsT5DkL3x2P/EfjkNU9DtHxy+h1V2BJYKjA" "wzdQhdIWBq0j+7ca+lfroH+9Vpoev/xLrwLIAHAMBsjwtrsCjxGaXgHIzbIYvMqchI8yJwz6" "YquY5XAcrLyJkU1OjGx0YGSDlWQhmTGy3kQyejWKNLregDENBoxvMuLtZiMmtRoxtY0BYsAs" "Asgcrcp1zNYZ8Y6WjtM+w+UdGmfR/mytyoP46FUl1jJ3L4gkz925jzWe/g+Lah70lO9uFIBY" "sJNAsdtlQzhBYzeJQbKdxm3iSJQ72eYwEjxIDh2NKoG+w65g4QWGixyHWwyScKcG+Y0n8W36" "4FLLwppD2GppQKShGM/7lfY6S1eI24h0NnsB0ieGSqMoyslqQDTBJIogEsmyqzHKrWgCS5Sj" "ho5Xk3uoUvCQ8FU/gJDjYOcRQw7kuKtKFOOsEqDw8SgnP15Ox8rpWBmOOBgkhThkzcNBUqQ9" "XxLnDA/WMVcRdFXrhqgKGoUs7VmcIHAcc+XR67By6GeycYIActKVhdO0fZZ0jnSGIHKagHLK" "mY5TBJFTTqXTrnS3GBxpdH6q6By5kHMEkfOkWNIlgsplOnaJdFm2E0kJAo+rHQyQJC9ASrWR" "g8qPOZSVbjxJ4LjpLuuNU30iDBDrJQljnaHHT+ljCBBHCBRHJXzF6oMIwyVGHmM3ckIfSQA5" "gKPte3GkLRxH23bjWLsCyFnjfpw378dF20FcsUfimi0SV62H0di4YvD/GAGktC2sHzyUOITl" "gcdNZx9E4sVlKHBwziPJ6zw8EIkQiEj1VedhSaAnW8MJFju9CXMvSNh5OJUDkeXbzVuRZNoo" "4EjRraXPbBNyrDvJCewTB8LwSGoPRYYhTKqtpOKKlzkxhglMss3r5QZSpe3Lh8yBPMkfL6Gp" "HP1qd6J8jajEHiryOA3Oe5TaVf6Dez5k3xoozkN1mwf3q7wKELHrqLIvlVxHsd4PWS0+yGyc" "h+zG+Sg1LEKFlR4zEUB+of0LfkGA8Oh/all/FP2zrm9b7f/BCxEWA+Nf2r/Hv2i/JX0tEHG9" "zkRSxwRkdM1AumsyIuMXw4cm60WBa2TyZjFIfJavxprwlcjtnUxOYTzKaMJP1E1D8OZQLAoO" "xbZjy9DyagbaXi2A5iNfCWepqiy/fgDxFYCwU2l+PVvgUf1yCrkPBZCCx+OQe38YMnuH43Lj" "SASsWgW/EHr9EIbUWiwJWYt5AWtwqyxUGh61L1dD8yIIz79tEoAo9/F4EESGaR6IFDyU+xAR" "SEa192JLXd6Q/SAfEFgCqkowvN6KEaw6s1smBZA6g1ItS49RpNF1eoKIHuMaDZjQbMDkVgOm" "awyYqSFAeCBCYljMkX2l+QSO+Vq1Aq8Pyddggp/RJA2F3Di4Wvo9rOQ4GByqcdADDs53bHKH" "rrazC3EoiPC4nQCyzekJbZlJJgKICdvJgey061R+ww2PXV65k+nOPh3+EffxWdY4nGm5jc2m" "Wmwz16KjeFnf55czha4+8yVsxc7jSEeLKIoULW6kCUfIiRwlxRBIjroaaIJn1RMYGCY81tFE" "T3Kyar2KIR1z0eiqpkm/SuVAGB5Ohkc1OYManOrs02lRteiMjJU43VFBk30ZPU8pOYcSEYPj" "jLMAD4t8/k5V0FjcNl6n8/MQ48il18zxAuRURw65imxcoDG2I1d0QY5lESQyvTrrVCMn0z0Q" "OUtQOUsu5DxB5DzBIlaAkYordOyaKJWAkUL7SW6IsAOJFwdynY6lWS/idf5UfEuT8rfuUBE7" "wa/pavjrzJEobz+EG3T+dcdtXLERRGzXcJ5+5hyHsIzHCQoMhyOS85AEujEKp0wEFLPblRA8" "TvPjOuVAYrgrXbMH0QQPBsgJbQTOmw7iovkwLlkO46olSuDBum6Pgr7OTzVh0nt5UjRN3htf" "uNU1r/SC46Zjv8CD3QdXW/W5DyWP8+CwlYJHhFRcpXTs6XMe9j0SxspxHUJe5yFyH7tVnsOx" "S1xHhtuFZNI+jymWjUjmRLh+AxIJEGnmzUjRhApI8gguRZxf0a2WKiuGBYep0gkCvJ1BbiVZ" "t5KgsgZtLUukifLHvjd3iydJ5VWadrnkPzgPwg2EJQwRx2pyDwQKS4gKUzFMzIHKXVhUua5K" "oAfJYxy+4u0iUwAKjUuR274YOc1LRIXtS+mxpXSOynvU2P1Q6/BHtdmXAfI39IeIAshAcPRX" "nzP5IUCUtO+eRqJ9LFJdU5Ha8TZ2ng3AkhWrvADhCdwveC18g8NwNncZSp6MQ/G7E1BETqH0" "6URcr1iIrScXoaTHBw0Eg+ZXPtC8Vk6DQ1mecJb2k6Vo+1CFuVqlfHcWagk4le9PIRgRlOg5" "s7umIyZzHI4kzMeilXMklMavuzgoFGv3B+BW80KUvTsLpY/nouE9P7Q9X4mm94Nw95NUAsjD" "HwWIByKDAcL5kB5EVsUN6UAeZM3CjOoGDK9jgFj64CEyCjhG1ZL7kNEgABlVpyUnosOYRh05" "ET0mtRgwlSAyo40hQk5ERDChkQEyl7RAq6DhozVjoY57QgggeiP8CSCBZu46t0ruY6PdTuLR" "SsCwkaNgONgkdCV5DqdyIaztzj6g7HBxKMsiYnhsc5rIfRiUA3Fo+uU4tNhD4jHcHcIS0TmZ" "TeeHdB/v5s7CzvY8bDRUYqupBlXVe7yPfUfnFzafRTQB5CgBI4bAcVTEMPEca8YxAomIIHKM" "IKLUSJOy2j8u+/Wi46QTHQ00UTcQCBoIBPW0XauA0aFAcbazDue66nD+Tj0ukGLvNOBidz0u" "iepw6Q6rlrZr6LEaOq+SnquCVC6KdeXjXslSbzhuUCw7ZyKumrhnQwGEk+cMkFPsNggW5xkc" "nbm46BZvnyeonCFncpbEuY9ztM86I2DJEJ2VkFaaVGNdIHBcZIB0KIBclZH3k8iJcAjrtiTN" "Lztv4xrt3+AwFinRfhnZ5CYM9WFq0irzRbzjGnIIEkmOONyic27S+dcd9LOcB7FcxFnTGQLD" "MUmeMzxOEDyOGzlZHin5DobJaQ9ASCqMxRVbh7whLOU+InDORM7DfIgAolwHw+OK/bDIXqlK" "5R8XT5e8B+c/eL+xMUglzgkeN50HBCKsPoDs9TYMqrLd/e5qq31ugOz1Ng56QlgSunLsdq+2" "y8DYhVTrDuR3RaHsbrQs0845jiT9eqSaNggsUg3rRUmtBAfzRmSQG0nSriHXsVr1epjXSb6D" "YZLYvlIl0wkg7ESyTGFob1pKv9MofJcxNEC6yqerqitTkDQN5ptXSt6DF0gsc6zx5jmUgkUK" "Kp5+D85zhKjRvVR7ObmPYnfVFTuPQoOfNA5W2nzFkZSZFyG/xQ/ZtfNQ1EIA+QftX/Hz9j/j" "5wSHfyT9U/sfBSC/0P1RxNDg8Z/a/+CVuBECxz8TMLyj24U0PD6ABNsYovNEgsgkbIpigKzB" "0qAw+IesEy0JWY9loWtxvWE6it4di6LH40UMEhXOmiyluJxQb3w9S7mQ1wvFcbAb8YS0tB/N" "Q/snC9D60XS0vSRqWqej2OmH3WcnYdiYmVi83J9edx3WbF2FpRtmSyMjAyxgXRjSu4Yj5+5I" "5D0agYJ3R6DmvZloeLYcDe8Ho+Pj6yppLrBQABnWLxci1VhegPS6RfBo68bIljs4WnZ1yD94" "e24gwcMi7mOkGyAj693hKwLIKBYBZDTBg53HqDp2IAwQLbkQLQFEh4nNesxuasa85mbMaNXj" "nTadjKxZBJX5BJClOgOWGixYQlqsNws82H0EGk2yfEkYuY+NNju2EEC2iqwEAs5xuMNUnONw" "8DErUpsvQ1++AXkNJxDfGodoE/dPtAs8GCrbOYRlN9Kol/6P7e5eD6myklCVDuEuHT2vVkJZ" "O50a7LPW42HB0BUmxuIQrNdVYBMBZJupGklNF/BNvxCKo2wVopzsNBRAYjqVGCQxXoAoiBzv" "aCQ4NJJjaCIQNLvVRPuNOMkScDTSJN9EgGjCBVEjzpPOdTXQ2ED7DW5gNOAy6UpPI671NOF6" "L6tRqadBqbcB13rrcbmnDhfvMEyq6edYVYjtrqT9CpiH6AN5v2A2Xb1n4gQ5lRMEkROuXHIy" "DJAcAoHHgShwsC6Qzgos3GEtGs8LaBRATpMTOeVSIS4VzupzIBedPCaTknDewTmQeFxwsAgg" "Du7xYIDEEzwS3GJHchul2sPkOkbhfuliAsZNxNFjN0lx9Hgc/ew1+01ctl5FrCWWHMgZnDGc" "JBdyjBQjrkOV8EaJCxGAGI+4AXJE8iSn9NGkSILGQXIe+0gMkHB6LAJnjHtx3nKQAHWYnAc7" "kMOiror5CsC54+h99SX6GSCeBHqcGx63CCQMEEmeu92HZ1s5j700ge/y5j08iXNPEj3FFo40" "hoYj3O08doqyXXuR00Hn6Tchvj0MKUaGBINgK9IIHJmGtVJxFd8UTDChbesGt8sgqGhXeG9Z" "y+Bg3WoJQnzzcoJ2GM1n65FP59cQJIZKomsqZiC5aQkSG5ciiZTZvhxZuhDJgRSYyYnYFDQ8" "DqSSwMKhKuU0CAxGX+TrAqQCi9e+Sqqdj8TquUggZbctQYVlGSqty8l1BIjqnOQ6nAQSq6+4" "jzrrEvzs5+1ugLj1j/1AomDC+/3gofGM34l+2f5NP32FivvbEG8ZhyT720TrtxEasVSA4b8i" "TJwHA2TpinVYuZ3s1oPxKHwyVnIVDBAei8mRMEAq3puCuhcz0PhyJlpeziGXMZscx2KBiP6j" "xajoXoK4qrm4XrISgevnIzQ8hBzOWnIXS7D9yDLsOB2IKw1TcK1lMpIsbyP93luITl4qIDuZ" "GYI02k+//ybyHgxHwaPh9LpjUP1kEarf9YPr40v9AOJxHDS2PZTcB8PDkwMZrr2LUeQ+hhE4" "2nJD/m4CPaMgXAAynOAhACF4jCB4jCBwjHCHrwa6D53bgSiAzKyrhzYvUNxNWsk+vNOqI2iQ" "aJzZpqVtPYJb63EvbwGe50zHgZY8uXnUMlKw0YyVJoskzNcRQDaRAxF4yGglANhogmeAOGh0" "EADscqyxKnyI5SBG4YYmSZwHh7G2OziJrlcNgwwXBgg3EbrzH7vc3eg7aH87gSWteWj3wRNA" "Zt1RbDfVYicp3EJuQJeDj7In9SVwc6bSVSk36DULRI529IdHEy7ai5HfHovWunDcLQ2gq/vJ" "eFq4EJecVTjb1Ywzbp3uahKYnCaQ8P65O83kLlpo4m8WXSJdvtNE0CBQdFWjuv0MHpf64aus" "sf3e7zB8nvM27pcHodhCE+rdBsSRrhFArohqcZV0rbcG1wgel8iZWGo2DXamJb408RfRZM/J" "8zycdOYSAHJxusMNEM5/OFX+4xwfc4e1zrjcLsQNk/7w4N4QyYs4+gBy0ZmIhqYdeJU31RuS" "+oOsNTUcH5EL0jRspEn1Oq67HUicGyDXCSDXRAomvH+DJPBw0TaB55rtBi6bryDWfAGljVvx" "NH+a5CP6/20/yR4LQ/kSXNTvkxLe01KFReBggBhUQv0UOxTdfpzQKYDIvc4N4ThjisAF834F" "D8shGR8VvzPk/5mjahGB4+CAMJa4jx+EsG7Zd8saV5Z6P1n25HnBJOR1HEDFw4sEkf1qyRIO" "Xzl3o6NqAb6hc8z1S8V9sAQi1u1I1G5AimEzbreS6zBtQnH7OnxcOIWcwzC0VC9Aumm99H4k" "6zhRvkrKeGv1q/Fpzmi8zBuHzOrFyDSGuu80uFHAwcnzPNMaJDQtQ071okE5kG8yh0FDk3yR" "aw2KOefBISvnKvfS7CulYZCrrkrt7EZUtVUF7YscIe6KK7UtFVjuSisGBYeqqvieH85gVPPy" "7iZ/5DT6IrF0DpJLZ6FEsxh1tqWos5MD+R/tfwHrHzSsPw3QzwkUDA+P+lzId6JfaL7HP7V9" "i3/SfC1iiFTd24bb5jFkDScQRCYgbK+f5BoYGgEr3QBZGUYT/kqUPnmbJu/RKHg4FvmPxkrO" "ggFS9O5oaQQsfzIeTa+noe7JLCS0vI08QyD2XViEtbt8sWrzMkybtxwb9q7FlsjVOJWyiijs" "izTLNJQ8mSjPk/doFHIeDENG75tI7/kNzpfOQFBoKM7kBSC19zdIu/smsu+/pSDyZDjKnsym" "L48vHB9cEWh4APLmAIj0AWRYay/ebOrEWw0deLPe9XcB8l3aMESWXZb8x3Bv+EqFsLwAIWiM" "rCVoeOR2IGMadBjLDqShHQnF++W5XmRNxuPsmQNCZZ9mjsX72VPV8h8FAQjSaxFgMCOIALKK" "4BFmNmMtaQO5kM0EEYbHflML6qsi8Cp3hreclsfPsibARXC2lK0dAI7rmmQV2pIcCOc+OHxl" "xC67HrsJIrsJIDu5B8TW5oZIm+RAOKzFlVkRBIUHP+I+Ps0aj3PaNAJHI/ZYG7CXxF3qj/qd" "z+DJaT6Dw45GrxPxhK501duGfN57JQG44KpGO0Hls+wJ3t/x0+yJ0NbtFricI4jEdhNASFcI" "Hld57G5GpS6W/tEn/WR1HU+Q3dVhiO+pxo0eBZHr5EYYKBnkHvg52El9nTl6iFBEEMGiWPpA" "TrgBctGWjPfzZ/Z1qhfOQawjVUFDIJKFWHsKjDVrCZRL8EHuFPrdxstrVDZHSG/IaYKIJNOd" "qbhhjcPjovk/+XvcK/OlCfcmbnBYShSP9oaB0HtYsoCO36JzbrsBchNXrNdw1XgeneRQvv+J" "13iWNxkXdfsFHkpH3ACJIhFA+Pa1+j198DDuIYXjrFFVYV22EBgIJk8Kp/0oQG4SQCR05Snd" "te2T0QOPBAljhYsqdOvxZdZIAd5Lgkh/uDIEPskdK+MXdE65PkzyHLxke7J5ExK0a5Gm3yzJ" "8nTdBiTp1xIwNuE+AUS+0wSJT7JHDVjP6nOCgQcI9zgMZePKK+48X0kOZDlStSEEkbXorpot" "P8dw++F6WF/Tz9fSfJfS7E/zXhCSGgKRVBeA5PpA6fvgJU0y2/qUrVmB9OZApDbSY7V+SKpZ" "LIqvnSfOI7edwCGJdD8JY3HJbplVOZBKm2oerCeo1NuXocFB244lKNP54Gc/0/xVAPIzzZ9J" "f8T/aHOL4MCjwISg8fP27xUw3BD5R20fQH6h+Rb/k+DBjqTu4T7cMg9HgnWchLK2HwmE/+q1" "CFixHstWbsCyVetof504Bu79yH8wBnkPxwhECh+RC3k8CsVPJ6Pq6Xhcq5iH6UsnS2LdJ3gl" "lob4wcd/NdZHbEORjW+eMgut5E7qX0xE44sFKHs8ARXP5qL0/bECIQZI9v3hBIrfI/PuG0jr" "GIUV24MRvM0PGd2/I1fyBnLuKYDkPRqGksdTUHbfF9bXsRK64jyI5EL6weONlrt4q/ku3mjs" "we8bOvFmbYdoZL0dN4siYc7xwxfpowZ9qT/KHI+VlbkKHqTpNY04WnqBdB4Lq8q9lVcMjVH9" "E+ik8QSQiY06TG7SYX9VHL7IGPWTE8GTnJnY0VqGQL0Zq4wKHBstZmwibbHS5E9KaokTUPy9" "5xnKKXxMjuCkpRq7CSThLjP2Os3Y5zJhr8OACIJIuF1LAGl394FwAr1NkujcG5LWfIH+QYde" "J+zd/HkCjAhbIw5bqlDQECPHfjghmcrDBCDRTk6WN+MYuZFjNJa1nBzyee+UBdMEvOBHf8f3" "Cubhqr2UHAi5DgLH1e5WXCN4tDcdHDCZ/L+BSE/latzorSWI1CGutwG37zYhgbazaNKvaz+J" "h6VLh2giXE9OqEgAcsNyS2DwOncqTTJ9bsdZEeyGh9tpcK6jIxP3S3yGeL5Qci2Z5FgyaEzD" "OQKJo2rgxQ33d5iqV+Gj3In4ii4MvnSD7fPscUi3nBNwXHex24hHV8Wygd+tojm45bhB8IjH" "TReHsMiBkHNpqV034G/FE7K53BfP8ybJ2nCfZY5yV52NQHbjJoFGH0SiSIcUPLh5kBzIKT2H" "sBgcETjLN4wiiJwjnTftxg3jLrzIUyscv8in//+WFZJMl793xVwBiNd1uNXX86FyH7cd4dIw" "mGnejg/yJvzk35d/Hy1NzkmmLbitCZWf47BVmnETEtv53uTbkKQNQ4p+Hcy1Pj8JUoFp/gQU" "6lT+I8fE4a5QgQcv2V5oJKdQ7wNbyYxBC0N+mT0SNXRBzUnzPEmgByHfGKSWLjEFI9cQjEJ9" "iJIhCAX6QBQZ3Ul0c6BUYVXYA92d5/6qz4NU41wmwCg1+iFXsxSZDfOl+qpYz6W7/qgyLREx" "PCqM8z0A+Rt4ZIh4AMLg8I4ME9I/ECAYJErfCkAYHv/Y9g1+0arU9vAErpvewG3beNy0jkL4" "JX/4rwgVaCxftVHEEAnbvRn59yYh6+5IpHe9hTTzdKw/OgybI5dgxbow6VQPCF0F/9B1OJMW" "hoSGxSh0zEcDAaL5xWy0vVZhrcaX70j5bu3zaSh/fyLK3nsbRU8JSO+OQu7Dkci6N0ycRkrv" "G0ju+T3WHQhAcNgm+hK9KftZ95SyH78p0Cm4Nxsdr9P6GgjdI4ev3mzqxRsN3fh9/R38rq4L" "b9R14K26TtGwenYhToKJY0gn8iRzOubU1Ak8llSX42m/TvWv00fgWOk5jObSXXcYy5MHGUea" "0KjHJILH6rp8PM+a0tfVnrsAW1tKEN5ShK5838FXk/T4Zk09wkxmrDeZsIkgsoXcx1abBZlN" "l/BVxuj/5iJ0o8glvI0Pc6bhrK0OhzodiOyyIYoU2WnF4Q4TDrj0BBSlCKeOgKIlabCHYHLI" "Su6jcNGPPr+ldDXyGo/hUf78vztxc2nvSWMhohwMkBac6GgltaC49Zwk2n94/id09c//zM8I" "FNdtuXBUrhs08bfVReB8F4euFEAa2k56QfdZztvQNh9AQlcZ4ggGxdbbeL94aBf1Hb3vprZj" "BJB63PQA5F4Tbt9rFLA8LPUb9DO1LQdxtqsEZzuLkWi6jq6y5bhfvGhA+aymfrOEqjhpruCh" "ZKlePej5rNVrcJHOjWWXQpBJsF0nUEwa8PtqGnegvmWPbL9fMAu9ZUu9Cf1Uy0UBCFdY3bLH" "4WnR3AHP/zJ/BpLtV3GrIwG33Uqk/fcLZg5c6I/cTHbzVukW/5DAZCjzdcNrFNJaeMl11SfC" "4ayThkjSQQLIPmkcFPfhbhw8a+JkOrkPXoGXRfC4od2Kl7lq0m9poCtwyx56X+p3fFQ8QwAi" "DYM2dwjL3UDI0LhlDUeyc7/qNrfvwqPSvlJxdiKathCUdu9FZ+U8cR4D/gcyR6CmPgAJbeuQ" "YdqORN06AUgSAYTDVxnkSmoalnonfHYOTwonoVC7Go2aIPp8BxdSPC2ZIuGqNN0qZBhWKYBY" "CCZ62ie4NDX4ErwGvo+P88eh3EzQMBF8tMFKGtVtnqFZhvS2AGS3BiCrxV+6zbNaApDTtgw5" "9HiRIcALEKVgchpB9HxqscR8zQIUtC8UiNRw3sPhh1qXyoHUWHwlhJXXuAClGp+hAPLnAQDx" "uhHRd16QsP6xrb++ETfifJmDa8bfi/u4YRmJw4nzELh6EwLXbEBQKAFk9XoErN6MFRs3Y88F" "H2yNXoIps+dh1eYQrNq0BttjQnEqfRFOZfkhv3MGap5PRvWzd1D/egKaXs9H06s5UnHF8Gh+" "rRZPrH9J572a2gcQcR8jBCCZD94SB5JEjiO+8z8RmTAPy8I242LjcMR3/xdSe3+HjPvkUB7+" "Hvnv/h55vVPx4LM6BQ7SG20PyHXcJ2j0CDjerLuDN2q78FZ9NwGDw1e0XecigJBqnSLNEAAx" "5foTDHSS+zhaGjvo8aa8lQQQE0HDnURnB1Krw9h6HSaQA5nR2ApTXkDfVXP2dKxorsC8diMW" "ao0Ibq3D/Zy5g563tPIAwcOCzWYjNllN4jyO6cvxOmfaEOWkE5DewjccaoOucsugDvH3aGK/" "QA5hf6cNh7sciL7jwLEeJ06wum042mVBFEHkUIeBQGLAfoLJPmc7wURL7oQrr37cfQylT+j9" "6MvCcLktnqCyoN+V4EikkpOJJBfCDuQkAeRUZyuydXE06Q4NxWcFc3HBVoTjnQ1IMKVJuGfg" "pDgT1+1lXoCkOfNxryIED2gyv91Zjus9TQSAJsTdZTUitaMAH+QPHYN/TRNpUkeRGyCNBBCl" "W3fr8KhsIEAYeNXtx+l1y3GxuwwXuopxrrMAWbozdEXd97tUt+z3JsrPul0Il/IaatcOev2H" "pYtxpTMHV+n8K53ZSLNcx+c54/vFz0eiXBuDFOsNvF8423ul/Hn2WDS27iFXkYibHUqptiv4" "MG/ywN8vfxrSHFeR0JmIpK5EJBBA0gggL/OnDzivrnEdLluO405Jn4vkxRA1VcsIHkcFIGcM" "nEjnPEgk6aAsnijLlrgbBwUgRoZIuIgBwg4ksX29LIooFxR5b6OeIPKVu9nuMQEk3nHI6zxU" "+EpVX3H3eZJjH/LvnpK+D0ODv/e9MSxaeSHCzr0ofBiJFAJMV/Vg5/qC3EqaZg2KXAeRauaE" "+HpybZskeZ5vXEufV59zfFn4NnL0a5FBzoRX163Uhnirxfq+A2+hvXahVF4xOAoc61FgXiv9" "HdkElZYm30HlvK8LJqDMqu40WGxdiXxDiIT42YkoLUeufrncaZDzICrvESRrXnlyIFXOFaJq" "exAphABC5xv8UaT1kwqsMtNSVa5rW4JS7XwUtMwhcMxDhWGh5EAaHG6A9NcggDAw2v/gHhVI" "2IEwNP5B8413mwHCev61EdcNv6E/3BjcMo/EmYpZCFpD0FixGSFrNxFAwsiFbEUgba/esQ37" "Y1ci+vZipNjfITcyGtn3RiL/8WiBQPGTUdLTwWtk1b6egrrX76Dh1TtoeTlT4NH4eqbs176e" "RgCZ7G4gHNcPIMMlx8EAYbfBwDhbNQZBKzbgZM5UJPT+Jx3/LZLu/k4B5NFbyO6ZgM++7xbX" "8buWe+Q4esltdBM0ugUcDBCvCCBKLoKIUzSu1ghHzpJBX7qSgk0Cj5E/6kDO9wGkzg0QAk5Y" "ZQZcOT5IKdkvOQ5vQr50P2a26VUZbzuX8OoRV3FsUPnw/Twf6ErX42NyDldbk8l9WFFddXDw" "ujrci9Ce4u0832s3oLMkZJADYd0pCcbBTrsA5ES3Eyd7aLxjQ0ynSQByuMOIgx0KIPtdWuxz" "tOOAvRF3i/omzw+yp+Bp/mDgfSzQINepTcMuSx2pHrtpbKnYMrBaqywUB611OELPe9zZjBME" "khuWfMlrDEr6Z41BsvYajrhqcdRVh/P2YjzPn/2DpORIlLRfwqXuZlzpbsG1HlazV9e7VeVV" "wp0yaJoP4YO8GT8aomAoNGhP4WaPAkhadzleFc4dOiySOQrlxsu41VuNuN4KXKXnj+0oRJ72" "tHzW6qp3JAp1pxDbmS8VWLEEhwudqvqqpnXfkAC5Tufd6MpFXFcO/W8l0KQ2dcA5HdUrEe9K" "IfeQSk4i2avbHUl96kxCifGEfH4DlwsZhxzrBXJkiUjsIvfRFY8k13U8LZ4z8H0Uz6O/yQlc" "sJ6SZUzOmGPUmlgMDtJZhoghmhRFsDhMOkiOZD8BZK+qvpIlSyJUCIvhYWZ4KIAka9YNuUKt" "J6SVZAnvcx0SvorwrnmVat1N73UGXFU+BMO+78uLgsnItu1GZs8BlD6NliXbS/UbJPfxw3uK" "dJXPwedZo9FdOVsA0t68jAD6Npzls7y3JeBRW7sIWZaNcs8PrrJKM65Bd8n0wS6keAqeFU/C" "F9k052kCkdwaCE3Fj99Q6nnJJJQ616HMuZbGNWqpdkuwlO6WD1iqZCUqCTJcfcUAqXKxVtLx" "IHEihe3+yGpYgvS6+aS55EB8UGNbruR2H9L7YVmCSqOPqNa2GLXWpQKVHwCknwNxQ8MDkH9w" "A+Qf+gGEw1hq+xuvvv3bB0gwTsNNyxjEmUfjctMYcR+7T2yWG0odu7UOIZs30rH12Hk8BCku" "ojlN7Fl3RyC95w3JWeQ9GKlyIQSQMgJC9ftvS4Mgu4yG19PR8GKGOA8GCPd+8PHql5MIIOMG" "ACTr4ZsEj9+Ky0jq/g1u3vl3XNKMJgcSiohrC+if69d0/H8jsfe/kHH3NwSv36HowQL86f/6" "FL9p6MFv3eB4s67HPfY5kD54KIBw+IoBMrlGizvZg8MbJ0vOegEyss4Mn+oKnCg5J/KrKiFY" "mDCmH0Am1mok/7Gn/AYeZr0jiXOvU8gYg921SQIQ1f+hx1zS5oZ8ybUMntCG4b3cWbjYloFw" "qw4PCgaHu/SVW3HSVE1XGLHIaeL7QjQiha78+5fQmsmV7Hc5sL/DjkPkQqIJIse7HTh+x44Y" "ch/RLiMOk/M45NSTA9EpeHAvCLmPlNbL+Kpf7ub9vHcG9EXcLfTFGV0GdlqbsNPSJEu277Q0" "eAHC5bz9Qzrv5b6Do7o8cku1iLbVI8begFhzMV4OcVMqW0WoNA4eFdXivLWE3NTgCV3TEIGL" "d5okec4Auc4Q6aWxtxmZ9mw8LF8uISrv3yFnIn0+6nf6iibZpyVLvFB5UroUCT3VBBCGSD1u" "99YTJGrxuMx/4GSc8zbyOjKReLcW8XercYsAUmS6hPulft6LAQZJofYMLhFALnXl4WIXNxTm" "iGpb9w8uCy6aS247HTe783CLdPtOHswNmwcAj7ffK5qHfMtFxHekkAgencn0c8myHe/ebmzb" "N+ii5POcccglgLD7SCL3kdBxi4ATR+fuGvD5qOU2JiGvfS8u2k4TSE7iHDmScwQRj86aYnDO" "eARnyYGcYYDo9xE8PADxwMPtQNwAuUAAKWhaMWgdLO9Vf95EJFt2K8fhdiH9l2nPM2/Hu8XT" "B1SJycVWS4h0muf0RKP22UlkkkPJNG7G+wVDF1Hw8iKOqnkSwjLWLJSFHAckywkGRe0rVY+H" "NlTud57r2Iz2loAhGwS53+N1wduo1QYh38FrY4VJZ3l7m9+g8+9XzxRwcOVVqX219H2UOVYp" "kTOpsJPbsa9AJbsMV4h3lV25tzlXXdkDUU0g4fAVO5Aq2zJUmpXbqHUsE4CU6gKQVrsASRXz" "kFM/D7UEkXrHYiXnQjR1LmaA/NmdQB8IkL6wlSf/0Re66u9A+uc/PBVZpd3rxH3cMI3GTeMo" "XCzzRcW7M1D57G1xCfHaBQjbSo5k02qyiWORRhM35yoy7o1A5t23aOIfofozHo2U9axKn41B" "5YsJAgpW3cup4jy4T8QDjz6AjEHhU3Ifj970AoRdRnw3qeO3uO36LVZu2YrV4UG4bv133Or6" "L7qS+o1UZWU8+A0anq3D78l1cMhKAaMHb9X3igY7j0680dghVVgSwiJNJYD0Zg+sdvk8fTS2" "VKb2A4iCiGogNHh7QMbUGxFdehHPMqfi3awZBJkyqcKaU10pEOlbEn4iVjaWYI6G+z70JAN8" "tAasbanC+9mDQ1MVlRFYb+F+DRuOmuvxKmf6oLLc8roYfNovoc6OJL/5Ij7pd0XvKF9Pk289" "uQyCRRc91x0rYsR50D45j0iGh4Pg4dSRtNjP4Su7BvvMDeju5z4YBB9lTx6QqM9oPIMYQz4u" "a+KRX3cUTZXb4CwOxHt5M/FJ1vhBV/sMo3iCyl5zFQ5YqsmN1OCEqRjP8ucMDuM1HfPCI4bG" "c7Y+gHyaPcF7pX+3dJn0fFwiiHCvBzuP213VcNVs6reY4Ft4VTAT5fpY+j4V0ra6Snxc5ods" "V7YAwQOXXNq/fU8B5BYBIo6A8sMQ1of505FFUEi8V0MQqUFydykeVCwXIHnyQDyBV2qicbkr" "X8QQuUy6QiBpbN476Pfl95famYr4ngK6OMpHUm8hXaTl4G5V8KDPkS8QXDVr6P/wlgIJQSOB" "AJLgBom5Yb0bkKPpKnmeuxN9FCoNR5B8h0NYBJBOAkhnnMhat2YQRKS4oHQh4ggUseaToouk" "S+RMLlpPINbCbiSSoHFgIDwMnuT5nn7hK+VACppWeQHyCb23JwV93ye+IyHfWjax44A0CaY4" "DyHVdRhpzsNId5Gz6DqEjI4o3Ksa+H9qal2D/K7jKOo9htanp5Ft3oMM0048KhkcqnxNbiNX" "twEZ5i3kWrZKiW6ZZgW5tRH94DkeRWZ1kyguzU1vW4W09tWoawuUOw3+8N4epobF9HgIUlsC" "kdqqVtDNaA9Cc+OiQTmQzoa5Ao9yZyhpNUocIbTPIalV7tLclVKmy2OlM1jcCCfTuecjvWkx" "UutYi0QFGj8CSKCAgxPl3GnO9/pgiNTb/aXqqsHpK66D+z9yyK3cov/LuOy5HgdCAGn7y08A" "5Lt+SfRvB4Su+gPknzVfwvrebVy1/l6S6Mm2GRJiqnz+tuQn1AKHwxCT6oPgtbtxQz9S9WTc" "pUmkZ5j0a3B1VNbDYVIdxW6i5Olo+tnxqHox0etEal5OF5AoqEwWgPA5fC6X5DJAsu+/Ic+V" "TO6DQXHD9R+44vwldp4JwtqIUMS2Dsctl4JIcg+5kN7fwv76mhcgnOfwwEOp2wsQrsDywENE" "7mN4nQsLq+vxMnPgFcvzzClYWFOjli/x9H/UmQcsXzLaDZCIsji5PzY7jgvFMQIQ3+oivMqc" "OAAgq5tKBR4LtAoevqQ17Y14kDu4VLOmIhwbuGyXAHKEJvMfAoSrqiprIwf9nLM0dABAPNLV" "RBA47DhCEDnSZUZkh1Fcxz6HEgOE4cGhq72ONsS33RjgPji38WNd2f8dacvCsNtYgXBubjRX" "ykq7d4r9B4cPm2Jk+ZKjbhdypp8DKW+Owd0S9TPPC+biuqsMF7vJhRBE4l10XlFfDPx7+idu" "bz7k7fOI6yyjx5Xb/DhvKk38gd4J+tvMkag1XhSA3ORy3p5acjJVgwDyonAOUu4UIIHcRyI9" "nnC3ir6vxciwJ9ME1Hcx0Nq0G5c78ggeBBFyIlcJINc6c2GvWTsEQGYRlDKQcrcQ2d0ZaNNG" "Q9t+CEXkFswtuwa4Su/fJHciSo0n6WIqBYlu8fa9cvV+H5csRL75jORJONxXo49C0p1EFb7q" "uII6zR60tWylq/tjaGjdNSjspS5KRqOqeSuu2s7jmltXyJnEcmjLeAin3PkPD0Ak/yEK76vA" "Il0w7kZtbV9l2IPCqShqCvYC5TO68k/RrkfO3XNI64hECim1i+BByuiKRmZ3FLK6j+FZ6cCk" "v7l9LQp6T6G85zh0715CgfUAaR96KhcNsZAhzWem7UjVbUKOfQeyrFtQ1xgwYKJ/nTsOObpV" "0jzIy7PzOlfsQn7s/h7GBh/JgRRxAyG5j3xeHJFGrWagA2HYWFt8CBhrRRzGKrOHodQWKs6D" "3QiPFXbVTMgJ8yLjMlnWhJcz4WosDmFxj0c1AafGESyqdS1HhckPBa2+yKpfJHceLNEsQbXJ" "H6Xti5BWMRP5jXPo4sEH9dblaCSw/EzA4VG/KixPGW8fTH4MIN8JPBgkXMbLAPno2zu4ah6N" "OMtIWdak6sVkWSW3nCZ4BkL+4+G40TZVAHKSSJZIEzdXSXmrpe69Kclv7uHIf3eYOIqS98aI" "e2EnwrBQ0JgiUKmiYxUEKD6n6Oko+RkGSDo5m5Qe5TAYEtcd/4nLtl/jWtsohGzYiuic8bju" "/Hc5Ht/1a6R0v4nX39sFIL+r75X8B4ODYfKGQOWOJM097qPPeSiA8PaCmsEA6cpeiCl17RjR" "wE2EZpJJNRC6AaIWTlQA4XDWq0x1FavLXYax9RrMqxnsQFY3lWBumx7zNORANAQZrR6bWivw" "fAgHUlR9WJZs32y3YrdNR/9wvoMAktJ0bUBJL1dotVXvGXKyKW27RO6Dk+ZWRHaacNBl9MJj" "n0Onch8EEQbIIVszeor8BzTfPc6fPyhB//9FT3Ln4KAuDzuN5dhFEAkniBjL1wz+/RuPIMpe" "g2hHjax7FWvOlXW1pFKteAk+zxrnnngmINGWRS6kkVwIuaaKlYMrxeq3C0AEIt11eFjq/6Pv" "T9d6EHF36+gqvQgvC+YMec6jsqW4ebeSXEolOZBqJBFAEmk7vqccD8v6Sn4flfjgSkcmLnao" "5UyukOJo/0nx4CTv68JZyLmTidzuLLwqmjOgQkxHIGnVx9AEP3YIiExCju0SQSFVAJLiuo3n" "RcphfZg3BffLfL3rTTVpIiT/kdwRhwfliwe4DVtNCAp1h/BxzoQh8lF0QUiP3XRewQ1HLK5Y" "T+OCLGviAQg5ECN3n3sAwvc+J3AYdhM8dgs8Ykl1dcv6OY4JeFA0td9ij6OQpg1Dgv2AlO4m" "kQNJvxND0DiK/LtnkNd7Enl3zuBh9cC7htrbN6LszilU3zkG89ObKOuIRjHpSfm8IQolJqPE" "tQdZlh3IMRM4nTsIqqsHOJAP8yag0LRWVtrluwxyBzrfqrauLWCQA/lOKu0WIMu4UhLnfI9z" "Y928oUvrCSY67VKUuUIFFpWOUJEKYanmQYEHwaLAFCj3Ns9t9xP3wcrWLpH7e3CjYK0zRNwH" "V2BxAr1Ep24UVWb0ITeyFEWtPihuXYKCZh/kN89GQaMPOZBFcrygyVPG26acxyCAeCDyI2W8" "P2/92pv78DQScjf6m8YvyQoGIc4wErcMdNXxfKoAhB0Cl9gyQOKNb2PV5u2ISfHH7Z7fIqHn" "d6TfSK4iiXs27qry2rzHbwkQ+OZQZe+NFbGbUeCYLEl2Dl15nluV776FrPu/k7AUP6e4j47/" "wjX7f+KS499wzfwrhO3cgKisqWSjf4Wrjv/AzY7fouyeHw71vkfw6PGGsFToSlVgSRWWFx5d" "buehAOKpwFpROTgPUZ0f5m4gVA5kuLeBsA8gY+oHOhD+ue7s+YgqjYU9Z7Ek2vvnQPbUJhFA" "tJjX1o6F7TosJYBENOfh48wJg/If8fUXsZ57QKwqjFVTc+gHyfGRuN0ajyOmGmQ3xiK76SJO" "muvgKAsbMkGcT47iCAEkqtMsCfMD7D6k4orLd3WyrUYtEjVxA9wHJ8/fLRjokuqqIxBuayW1" "YLe1WcnWRGrAbksDwvkWtpY6HNdm43XO5AFhrOv0XneQCxGImCvQULXlByGaEUhrPoMD1koc" "tFXJzaNiTRnkrN4e9LtxP0Se7grOd9Gkb80cMiH/pHgxbtyplC5zVk/FCm83d1vLQZpM+yY2" "e91mAk0VnVeJi3fKCUxleFA6sMDCUbsONwgWApB71XTxVKPUW46u2rB+5aOjUKQ9TvDIkSQ6" "jyW645KEHwyQ2QKPeuv5QY8/LV+CjHvFaDEcH/LiwNi8jZwFAaQzBdn2K/g4d+KQk1hr6066" "MEtAnu2c5EQGOqDpSLNfQrH5+IBeFo96KgNw23VNAHKZE+xShXXAmzxXy5fsEanmQTdADB6A" "7IKl/MebIrkUt1ATKkuVcBKdq64yuo4ip+cMyh5eRo3rCJ5U+uDrrIHVUPcblqO66yxa7l6D" "62UBanrOEkxO4NUQIaxnJTNRcucACjv2Itu6DZaGpfggf8KAECHnQEr1a8R1FDi2SBgr27gG" "mqalg3IanI9pavZFDgEm17JGbhLF9/cocoYR9P0HnP9l9gg0EhgYIJ4QFjsOdhjFpiByGMEo" "NCwn9+Mv8MjX+hNAlghQuBOdO89rnUHSbc6ug3s/+Da1hW1+SK9bSN8rP5S0LyBIcKnuEln3" "KqNqLvLIfbAT4QosTqrn/yRA+sPD3UzoUf/EOfeC9AfI/yQ9etmK22a6wjeOQs1zH294yQOQ" "tN6R2B8bitV71tKVzH8IOBLv/JeU23LFlKe8lp1E/qM3UPjucIEHJ8m5XJcdB6tcADJBch/F" "z0bLsiTcFMjhq1SCEAPkdsf/FoBcsf87Ltp+hYumX+PwLV/EtoyhY/+Bq/ZfkRP5PXo/rFHw" "GBTC6hZxD4gHHm823ZEudIGHuwqLQ1gby9Mk59H/y3Gh5Lg0EA7vtwbWCM8Cihy+csNjVVUu" "OY2Z/ZzLfEQSQDgfUlGwfsDzxpVFY1ZruwDEt12LAJ0eKVXHh15GnibRpsod2GHjJUdsOGWq" "HlTGaytdjR1WA7YQYBgyN9uSh+wT+TJzLBJ0GQQOi/R9HOxQ8JCSXQaHGx57CR4H7c3oLAka" "2JtSuESWI/Fe9dJV/zldZh88LAyQJtongFgbBSACEU6mE9QMZaEDnq+xfBO2ETx2kHaaypFd" "Hz0oV3Kr+QIizGWIsJRjv7WCrmRTvQC5X7QY9rIV3n/8+ob9OOmqRo72kjc3MqAhNHcKEhy5" "auHE7mrv0iQf5U5Ggi0dRboL3p+z164XaFyQHo8inOkoxL2SgQDRNe7AdQFIFZIIHKmkgq5c" "gsAcL7D7JqTxqNBE4aozHdWth2R/yDJiBkhPtuhV8UAHotceFoBk9+bh/ZLBxR6dtWuQfCdN" "XEglORUGF382HVUh6Kjuy6HoGzeJA0nrvI1HFUsGOBBn7Sp6jgSkdifhbvXywRAuXYD4DgKI" "/Twu8k2mjIeV+9APhIfqPmcHslukALLrJwHCk3F562pJonPlVbLrMNI7jxBUz6Cw9wLqyGV8" "VDQd71Utxmf9cicflMxC2/9D2luA2VWdbf/9pO1bgQIF2lJa2gItUqBoSIh7IMSQQFwIQYJD" "fOLuk3HPTMbt+DnjFncn7kYKldffT+/vfp611zl7hJb3/+e67mvtvc8+Fs6s374fWXvrXAT3" "rUPLyQKU7lqAcMN7uJTwmw6bRk+mPYiiurHIqJ+I6sJu/A3ci73Zj0WrsGTSLyvprq5DVtpN" "rnmJIHkFO3Mf/5rPfTcaCp5Fau0QZNQOR2bdMF2W3dcmiX4u8VcoklV2+XhW3VCFiIauqs3S" "7bpce1V/DVWJsqpkgcQ+ugaW5EMMQAbScdCZ0EkklnVFQnEXAsQsoJhS0Rm5oeeQL/mOIoHH" "k8jxdcWmYBcFyyrCc3XWoxrK+nqAtOsBiTkQaSB0A6T1ciYGIP/gOY+NdX0wP/hLbKj7jU7+" "kv/QENbuuwmHuzFlYS8MGvka1rXcheVNt2ufhowCEkl8y/Ij4kIEIpI3Sd9nk+rGcUhOxUpz" "K9Z97L5LO88lHCbhq0X1P8aCehO+ml19E2ZHfoh5/l9grv9n/EHepi5kY/OzuLPQgYcDkFgi" "3XEezigA+VmJ40CKG6IJdAHIq5sIkK/pRZC8xqkN9+PzDQ9gR8KTKE0epAol9tawlbvSShzH" "p5kfEyw+3FvkxUNFpQgmxcIluxMeR5/ibHQiQLr7/BjuKcDuxGfa3Br211hVOAPhzCFYVL4c" "rzkLJo6vq0NCWVwrQEh/RlLRJxhT7UdS8Wc4t7HjyelU4sOYWZ3vNA2G1HVMrCMwqMnqRGz1" "lZcTQFq7qqiGzAGt8h+1Wc8TFgYcY6tLFR7jqkSEB53HuIhUYxXSXYgKsJSOw+1odqU8g/H+" "FIwKZRMi2VhSOovf+55WAFnMY+PCWZjgQGR6MAaQ9JJ3EedfoYl6k/cZgPdqc7AksEyXlm/X" "TMkJNc0/l2DIw0zX4ojiQEqKJ2K7K6QlS5RMd24QFVe9GosiS3E4pfXte4s8b2MR3cbyHXlY" "vTMf63YVqDLrZfJ9HiW+aZpQ/7rO99NJD7brrTmW8Qw2bk/k62QgaftGeAPTEPC/jczmVYjf" "kYn4nRkcM9BS2P7uiLUEw5qW9VjdvA4VlZP0PSTvkRr+DDlBTqZO70VD/iC6lOVYvWUl1rcs" "Q6l/Crx0JWlVHxMOi7GiaQkBsxSeyjHt1/4icJY1xGF+zWeYFZ6Gz9R9GHiY8JXjPoIGHjZ0" "ZcNXApAd6Y/8bYBUDtbb1UoCXd1H80cKkIwdc7B59yIU712KsgNrsMM/yvU3cA+2Vk1F7eEU" "7DhTDu/elTjUwT1H9hf2xPbCXthe0B2bWt5Czta3kNU4WZdqT/EPxilXH8jR9AeRpp3l5iZR" "myr7tis/ljLhICfwgxkP8P/3QC3PFeVShZFB/H/SGvSnUu7D5pqBTsjqRaRHXkBKyNyeNt5D" "F1HRFRvoZuLLuxjnUdXXlO5Kw6Am2vvpmlf5df0IDDoJT1fkETjJZT2wSYDj7YaV6U/oulfS" "+5HjJ2gIkk08VxLqeSHCprwTNub9JwBik+iivwUQgcf3HIDsPO3FAv9dWFn1OwWI5CfS9t+j" "k7wkt2dmPIsXR43GB8lPYQmhIVrafJtqRfOPNX8heQxxE/Icqcoy/SG/UWAIOGT1XpEcS9l7" "jybeJQEvAJH+jmUtd2Bhw48xjwCZTVDMjvwIM8I3YU7wLrqjezDTT1cSuY0/mHzNe4gDsSEs" "2zyoKjaJc5v7aAsPC5BpWXP+f8f2JWE+LWsW4eE1KhZ50Dc/EYdcnej1SV0xrCgVI0vTUJ/S" "u32oILUbXg1VYkR1FV6tqcbIGmfRxLpaXSxxdcXfX8qkfUNeZ16he/BOUxXebAgrNCYIQGoF" "IDFNqvdoB/o7kU10N893mPPQSqqKhRin7sNCg+6DAJGw1Tgt4y2ks8jHaEeTAhkKjegfH2E0" "u3weXYgByLyyubjgAuP5jfcirnwBxhMgE6uyMakqC9MDa6IA8eW9jMimF6NX1ntTO+H9qiRM" "q0pBS0bPjm9LXDwWM5o2YXpzDsL5L33NJHYPCosn4OP6FMyqXodDqU90CKOs0Cws3rqJANms" "AFnjAGQ191ft4PFtWUgPx+Hz1PZhFKmMqs9vn/PZn92dTiaNr5OGyuA0HMrqggy6hfVybLvR" "xm2JOJL5bJv1lX6NwqoZWL8lgRd18WgoHBoFVfPmgWhyVXE1bu6v1VermpdxQpmmuZLs0PuE" "x1Isb1hsINK4CNtye7ULqZZXjHbcxwd0GFNN6a66D+d2taHxUfcxUzVOS3dnh8c7ABmHXel/" "+x7z5bI+VP3bWEd4JDR/gtStM5C5bTZydswnQJYoPPz71yG0YxFO5sVyglcS78eBhk9w8FQ5" "Dle8hOttKsrk36iq7k2U7JqFvC0fYlPjO8jeMpV6E1lNE+keRqG0rHerTvR9WY/QHYxAibc/" "4dL+omRf9qNIrR+GlEZxHC8jXZLiDSMQKe/abg0s0wPygCbOxZ2YhPkLesMokVk08QVTfSVq" "ekHhIaW84j7kfh+JFb2xrqgrlmU+iYTSzupEUio6aZVVUvHT2Bzug8KangoPyX3I+lc5vu5Y" "nPgYZq++DxmVz6C0sTNKGqIAudEaIH8j9xHrQo/BQ1fmlbWwou7jogJExjwSOi7wU100Ufo6" "JCGeuPtnWl4rYHl57ChMiOuJxQTGkqYfY3HjbVhEJ7Ks5cfqRCQMJaEsTajv/qX2h8gS8LJY" "Yuah+xQkIrt4ojQPbth5l+Y/Vm77qUJJ3UfdLZhV9SPaYAMQcR6Lg7/CrMqf8QriVXUf0fBV" "sQGJXbbk6wDSFh4GIHO/0UQsbuP4ht8qLMSNFCe/gPkZ76Lv5hRdOFE60H/jrMJrAXJvcSXW" "po37Rq+/K/lZTPblKjxeJjgkgS5VWK/X1GC0rrRrNKWqAsWbJ+HzpEdbTfLn4+/DgZRn28XJ" "G3KGEx41mNoo8Ag5y5ZIwtxnpACR6isvAVJJOFSoVpfNxsmE1h3NsqT7lMhmJ3TlAEQhYt1H" "oQJkdLgAoyP5dBl5qtT8KQqJ4wkPojGtB5aWfIZR4WzV+97V2ozoDpF94l+LN+T+55oHyeVv" "YG27HIhZLfZ3qMkeiI9CG/BmdQbPW8l/gyc7WD23O+bWJ2Gjfw6OtulGP83XqNz8qkJD4PFx" "XTKm121EdsXbdCT9NAdyOvFBTdxLCCqxZqk2EJocSL5CxORBcgmVTVi6LRPLmzfisBPSasod" "iAXNycj2f4QLdAbHU9o3pe3M7acAqSt9LTrh63IslW9g3ZZ4JDUuxw4CoG1J7568fkjcloIE" "auO2JAXR1/2+9mZ2UkiUV4zFVacDXIBYXfIS4hvmY0P9PNQVDG5X0nsk/XGsrP6UjuwjzAy/" "TVC8QXhMwmcBp/LKyXto7sNZvkTKdg1AxmGOaizmhUZhlX8Ekuk0Sgt68Hf5FHYTKmcSfqOT" "d0XJAKxrfBcJLR8htfkzZG2fY+CxZzkK965Cxf5VCO5egdr98djBx69t/PvL+lzha2+hQ6rc" "uRCVexeiZMds5BMiOY1TkdH0BtKbJ1LjkVw/CgeyHvkGa6fdhYOZDyGrZjBS5H7m9RK2GoH0" "upd1hd3C4ABsz3scB7MexEm6jkuy4GP83diX+4jmP2QF3lRxDoEButaVLFWSUNlTF0aU/IcJ" "WQ2Kug9dyl3uRBjmuQTDpqpeSCMYcqsIFj8dS+Gz2JjfCStSH9dEeUF1d6RVPK35j5xAZ4VK" "YU0XJBZIIv1prN/0+Nc4EBdA3AspuiGieY/Kqx0A5EIrgFz/0zmsl7jarnu101tLbHf9TBv3" "1m25E6PefgUj33+R0LgZCxtvxfz6H+mELzARJyKhLIGBLnxIiCTu/aWGqgQishR8+oH7zPbe" "3+jSJdKIKOeu0cQ8gdR8qybJJdchAJkevBmf+n/IH+wtWBT5JVbS7l3+4yF1HxYcBiJbVLLm" "lV3CJBbCauwwfCUak7MK69Im4r3sOeiZn43nCvLwaGGFkwMxJbz2BlKx6quwk0QP6t0H79XV" "d80KvPcSHvcWS1NhJZ7Pi1foyGKNqWmvYl+bBkMNW/Gx9XnvYXAogMHhsFZfSQ/IywSHgUit" "3vtjVK10nNdhHDW+gZIl3PnYmJoazZNMqK/lFUhcByWxM3ThxPG1Ab1J1EQHHm9o6a4vCpKJ" "BMiEWo9qvIgQmUIHEc4eoqASpRe+izHV5RhbU0o5EHEaCCVsNbqqQJd2HxXerHo9nIfXQpvw" "Ol3Na2Eq4iicw8eMpgQ48SU/iTPx92MfnW04azA+DCYQCHmaRJ8qAAmsxVECc3car6IKxmKx" "fwneq0nD27VZen/zqTXpVAafw7E6CSklU+lMntYke9vig9MJD/BquAtfZxQWhJbgg9pEBccn" "DalUCqY3pqpmNqVhVnM6ZjelI25LJhZsycLCrdmaQBct2S4uxCTSV+2USizJi2TRnWRgZcMa" "RIpe0g7zPO+7mN+STIgk8W8kHts2tc8x1Be/hDXbUzl5rsHB7L+/qJ88vnvzAKRt3YjkHelI" "3pmO1G0JaC4ejn053QmSbjid/BCBdZ+GswQKe7Oe1ebBVQ3z1GV8k/c4mPEk1tJ1xNV8glmR" "dwmJNwmMydGu8+kueEyP9nyYxkGbPBd4zA2PUcVFRmNe1RiVbM+vGosF1aaBcFXDFM17JGz5" "FClbZ2OTA4+SvatRSecR3L0G1QfWo+lQIs7nGgdyrqAfLmzmd+mgMOFMQR80HYhH1aGNCO1f" "i8CBtfDvWYEKCYdtn2VA0kQ30vAGQpUDNaQpyfztuU9od3lbJyHVWr7i57AxOFQT51FFnnfu" "LjhIbxAlkgUTM2pe1HyHNA/a5Lk0EMqy7elVg6h+mkTXG0fVDaIzMu5DXIg0DGZV9UWytzvW" "l3TWrvN0fw9dsiQ70EfzH+l8TMaMym4oquFvofw5TaJL+EoAInmPdM6V0kyYR8ciFViJhU+2" "BUgHeQ/tQr/mdJ5fb1W+6waIDV+1Bsh5fN9zCUcuNPEK4Cl1HwoQOgTpuZAE95QFfTF4zFAD" "D53ob9FxQcMtUSciPRprCJHEXXdpKEuaDGW5k9R9v4lK9sV9SPhq7XazUOKyllv5GrdEk+cz" "Izfjk8BNhMdN+NB/E1aFn8LJi9tauQ83QDSc1QYg0eor6hcORGwCPaqiOvyyuJZjDX7FUWT2" "q5zy3VAbgISiAJG7D96rEDG5DyO6j6JKzMycpjmUhsTO+ENBAR4qrsBjZZV4usKDqQUr9Ta6" "MqnNLl6MQcEwng9HMDhi7nc+nJJ7gNibSI2uM/f9kHudT2ysw0QHInJPENGE+hqEc1tXNJ3f" "eD/m+OLxerUPr1V7OXrM0u3cHs9jcqOp8bqUO49XV2J0dYVqDDW2RsYy7pdhfsUybE/rig8C" "KQoOhYeIzmOsAIQaTYCMUoDQeUTyDDAUGjlUNkZSAo+R1Ov2MQcio8OmImsCNalqEyZX5VKb" "VJJEf5N6qzZ2D/RpdZvwntz/vC6b+1l4uy6Tj2dgam063pR7nDt6h3qvLg3vq1LxXm0KptUm" "YVpNIo8n6R0FP6xPVnB82ijwSCM40g04rFoyMLclE/OaszCPEJnXYkaBiUBkmYStdMyhMxHQ" "pPEc6f9I4vMSOCZSCYjj/rL6NTjWZgFDmagrvFOxensyVm1PwvKt8cj1v4f9mZ015OU+T0p5" "BRB5NbMRv4POY0cqknel82IvjWMqNvL567duwOqW1U7T4HKsbF6GFc1LsbxpCR2I0cqmpcgO" "v4892V3VFV1vE2Y7mv4kCvxv8Nw4LKqbgbnVH6r7kHudfxacHOs4dyTOw8BjAsHhhK2CJnk+" "JzTGBZDWEFlEgCyumqi5DyndjW/5UPMe4j4kbFW6Zy18+9cjsm8tmg+nYO/pChw7lIarWc/g" "ehIvzI7l4xwvJi/96QSu/+U0zl3eiWubTKnvFe8YnLy2E8evbMXnF7bgyJkW1eEzjdh/ugZ7" "Toaw/VgFWg5sxrGyV3Et/h6czOuLyJ4U1OxPQ82BJNQczMKeyFvm4oNupqp2GgqbP+SEP56A" "GIm0quFIi4wgMIbo7Wn1FrWRF5DGUW5TK70emjBvGIq8+qG6TElmZJCuvpsa7uOstttfIaLg" "aHxB+z0yI32Q7OumCXOBhtyiNivYB5mB3kj3EAaVXbEm92kdpUkwl49JHmRN1tNagSUVV/lV" "XXQdrPjNz2g+JINwKa7t+fcBYkNYpvPc6QWpuGr6PxwXIu5DAPLtygscjfP4buU51fcquV95" "FjtP84e5+1emQ9wpsV2+5Ta8vf4RvDKOP4Kan+pEL4lurYwiROY33qKhLVnDSnpFxFnI2lbi" "RCRcJTkPgYdsm3t//FKT8wIQ6Txf0nKbgkiS5JL/EPfxsV8gQifiuw0NR1Jwe+H2KEBEsnyJ" "GyB3OgDR8JUriS5j2wosux7Wz4sMMO4u7gggoajuaQeQAOU3YatCCw6j3xAgonsLyvFY/mbc" "X1SOB4rL8fvSMjxeVoEhJZnYmdQJDSm9Mat4CZ4PhfECAfIiwSH3PZd7gEgz4ZiwF5kFnFCS" "O+GDICdacRuEiNX4hmq6kiq8TTdwKLl1+GZn6nMYGSzE0GAFhgXLMSJcjpfDZXg1XMGJvIIT" "eoVuvxyRx0rxUriE2yV0DKWEAeFBpyEAGc3tMbJfLfslBIaRwEMVKeLjJmwlruP1cC6dRw5G" "hrL5+lk6CiwMMBxHQmcyMsjjfOz1cDbGEDTjqPEEjVFWNA8ypTqHQNgUA0j9JrxbL/DI5jEC" "hPBQESTvRpWumibgIEAEHu/WJONdAuSdmo08lmAAIvfzoOP4VJ0HAdKYjplReBiAqLg/p8Uc" "n0PN47GFW7OwZFsOltJ9LOH2wi1yPEXhMZvgmE1wiOZwW5QUntmuYU/2s6tmYeXWJF6gJWDp" "lvVY1LwGCxpXU6t4obaaF1VrsKR5HS+wNmDFlnisotbQfayn69i4I4l/RylI3JGM+O0JWLd1" "HeGxShPmKwiPlU3LsKpluVZZrd6yAmu2rMQawmXdllWEzWpeGK7h89Zi47Z1HNfruIHH17QQ" "PI3zsbhuJuZVf0QH8g5mhKbwb1IAMqkVRGaEJxrn4bgOI5P7mKMSgHDOiLxOGYjMiYyiAxmD" "JTUT9Ja08Y0fIXfHcgQPb8a2k2EcurgDxy/vxekre3H+8gFcvvE5bvz5Ev78z9fxT//yFf76" "j1c5/hn/+q//in/+t3/Fv//Hv+Kf/vVf8BXB98e8PviqcSH+9Jcv8Oe/fIWvvvoKN27cUH3x" "xRe4du0arly5gsuXL+PypUu4dPEiLpw7iwunj+LcufM4f97owoULuLinHNcyOuFy4Qic2J2P" "g8dbsPtwENsOeLD1QCm27C9C894C1O7OhG/HUhQ1v4uc2teRSXhI3iOnYThyGocqRDKqBypc" "ZBHFVDoJ6TSX6isJWdkmwU2ETIqPjwV6ab5DnIesvJtEh5Fc+Rw25HbWZsGkoi7IDnbXMt2k" "4k7I9nVFOs8RiGRU9EReiAAqehbrc5/BRkIkla8llVnfsvcC+S9e9+KJ1/GtymutGgjbrr6r" "3ecEyLe9kjy/GJVARMAh7sNC5B8qzuH7HOtOLFGXsG7nnQqEFc230m7+DDM2PYmpG+7ViX5u" "9a3qFgxIblFnIiCQPhFpNJTkeLwmyn+pQLJK3vlrs57W9l9o9dXKlju1/0MBUvNDzI44zsP7" "fXwauIM/rKW4s2A77sjf5lRfbXc5kC0uoBiA/KSovnUfiAIjFsKy8Li7uE4l7kN0j4rgKK5W" "meVMwtH7f1iA3Os4kHsFIhq+8hpFIVLJcytwb2EF7iNEBCC/I0AeLCnFI4TIE6UV6EIn0tPr" "RT+/HwNCIQIkjBflJlIEyAjCY0RNFZaXLIje46M283ltLBxbR2jUV+siimMIj9G1EawtndPq" "XiCS/NyweRoGBUrpbkpUL1AvUkOpYeGYZH9IsIhjMYaHivGqQETWuFKVKTRG8dhrVcVUoWq0" "Og9Tqqu5D7krYWQzgZenrmJkKBOvBjPxCkcByMhQlpbvvq7AyFFwvMbHXtPjWXQuWXQiWXyN" "TL5GBl8vg6+bQYBkYlJ1Nl1ItkLk7ZocwiKbjiNbQ1hTqzPwZk063qpJV3C8V5+FDxqy8H59" "JpVB55FBUKRT4kJSCI5kvKcOJFHvZy4O5GPrQJrSFB5zmuk6tmRwzCQAMgiVNCe0layaye3Z" "zWk8Jx0LtmYSHJkKjwWEx7xmuo+WJAOPJkcOSIKF7W+PK4smbmxYTueRgGVbNmBxy1qCYyXm" "1S/X+53HNSzDvMYVvDhbqVAxMFmLZdo8uI4g2UCQxBMG8YTHekJiNf+WHHhI17mCYxUfW0Ot" "1XE9obGB2wqO7esInw2qBAJEjq3fKpBZghVN87CkfiYW1H6EOdXTCJGpBAUhEpqst639zOVA" "pAKrdfWVuI+xBiDqRkZjVtUoLCRoVlZNQSYhVn28FAfO7cTRC3tw/NI+nL30OS7dOI/rX17H" "H//0Ff70pz/hL3/5C/7xH/8R//zP/4x/+Zd/UWCI/u3f/g3/8R//gX//939XybZ9TM6T8+V5" "f/7zn/V1vvzyS/zxj3+MAuTq1asKkEsCEOoiISI6e/ZsFCBunTt3Lio5R8dzp3X77NlzOHX6" "BI6fPIBjp/fi0Ikt2HesGQc+r8fezyvRsDsepU1vRRPopnx3IHKqh1CDCI/+HAcgIyS5ju5Y" "X/AcUiq7qfPQsBXdit0XKOT4uyGzsgfSyroiqbQrliT9wXEePRFf+AySCZScwHPOIordkVb+" "OFZl/B4r054iQAIEiP9L1X/1Uf4b+G++L/BffM7iiR0kz6P3ACE8/rvnUiuAfMdxHzGAXIgC" "5Huec2g6vQqJ236nfR8SnlrccDsWhX+FBZW/wKwwJ/qq76tbmFX1QwWK5EMEIuJCJK8hDYay" "3IlARByH5D2SdplVfNdto/vY+nMNXwk8JI8iTiau5hbMjPwQn9KBzPH/GvWfJ9F57FSAqByA" "CDB0EcUSAUiLygJE170iWO4uMWEs033uAkdBfTR8Jbq7sFr1y6gi0VvZ2vCVu4HwXpUBiCTQ" "76MLuY8Aua84FsK6t7DSAMQFkQeKy/BwSRkeKy3HU+UVeM7jQS8/IRIIYBAh8jwh8kJEQBLG" "kKowRofKsDf52WhXeDh7OCdVD14jNF6T5d5rw3g3mIfDSa1DI0cTH8E4bypeCJUTHqUYSEgM" "8BcRKIV4nuMLBMYQwmJoiODgOITjELqVYdx+KSygKFXHMdZpFJSS3VF0GiPDhXQVm+kmCrgv" "0BDlYxyPCUBGS2iKzuJlwuPlQDplIKLAoNMQiIxyAGJgkmVKegUghMfocDoBkq4AGU9N5LHJ" "VVl4gwBRyTah8kZVBqZUpTt5jzQCJI1wIUToRKYRGu8JPKgPqA9V6dwXN+KEsWoTVOJEPqxP" "UohMb0rV5dnjJExFRzHXWar9U3Epes/zBIJG7m8uq+waiMS1pGGz5x1UFwzn38Z6xNFpxBEg" "GrriKKErObaqdjFOJz3UDiBb8gY68IhXlyGuI45AmVu3FHMbRIRI43IXROhKGlZiEbWU28ub" "6DaaV2NVs7iOlVhOaKxoMVpJeMjyJQKVtVtFa3RUiKhcDoTasI3nbKFbaV6E5Y3zsKxhFgHy" "GRbWfcyLw/f59/0u5lS9RZC8SZC8QWBMpibRmViAjOWcQFioxtBljMVCwmItX6Ng10acvnQC" "F6+dxaUrZ3Dp8jlc/+IyrhMYV29cxrUv6Q4IjRt0C1/+5Uv85a9f0mX8GX/9618VBP/0T/8U" "BYiFxv/4H/9DwWFloSLnyPnyPAGQdSDWeYjcALHwELlB0VYWHNF9AuTM2VMORMxjp1UXcOrs" "eZw5cxanT/OcM2dw8vQhfH5mH46dOYyDJ7eg6UACyhqnaI9HRqgPUiv7Yl3+c1ib3wkbip7R" "RRHTPb2QUtYbCcVdsSLrMazb3AlJhd2RG+Tx0qfViaRW9KDLeEqBIZVXy9MexfKUP2Bt9jN6" "F8Kyxh4o4OunlIgTEYCE/gRVmPAIfYlvO/rvwT+qvh34At9x9N3QdXw/dE31veBl1fdDV/CD" "IBW6HNVN1M3hS/hR6BJu5jk3BS44Osf9izh60Ys1zQ9ofkKS5ourf4WF3rvxqecf+EO6RXMV" "CpPqm9SFCEQENKY/5Ke6Zlb8tl8gfuc9KgGJuA85LlrV8jPtKVncaF5fSndnBm/F4tDD2Hch" "gNuLd+GOkp24o2gHbi/ZhjtKCZES0bZYH0ixgYjAw/R8NEdHmwdxV2FFk+kl9XQa9Rqy0rBV" "SW10+56SGvya+lVJhKPRb4ojdBpG93H/vtIw7i8L4belQfyuTBTA70r93PdFdX+pl/LgtyWV" "eKC0Eg/Rffye+gMB0rky5kIEIIMjIbwYNhpCDSckVpXOb9U7sDflWbzvT8VLER8WlC3GkcQ/" "tCu93Jj3FgaHKigDkAGBYr5HAfr5CgkSQoQgGexARPQit18MFClQRoTFhZTi9SoTwpLEuZTu" "CkRep9t4JZxPbSZM8rkvoatCBcmoyGbNbbxCILxEgLwUyFCQvEKHYYCR47gPJ6wVMpVYJgeS" "jTGEw1jCYSydx3iOE6uy1IGIJsgxAUsoDWNCKQRMCsZHUjCpKpUwEaVgSnUKgZKCqTWpdCdp" "BEkaQSLgsDmQWAjrreoNBM8GQmcDz9uIDxuS8JlAoYUA2ZKFOAJEQlif0nF8UJ+A92vj6WLi" "8XG93NuDLqQphQBJpUtJRUJ4toaiTtBNbKiaj3kEh+RBrBY1bcCO7B4dlg7n+t/H0pZ4aj0W" "S+iKEBBozK0z7sPAw2qFI3PP84VNy/jay7C4aSmWNC7B0iaqeQndyVKCZBmWtyxToCxXmKzk" "RSCdBd2INAyuaVllwlka1lpGLeXf4WL+Hc7H0obZBMcMhcfiuk+xiABZUPsB5te8h3nV7yCu" "+i3MrZqKuQTJbIJkdugNxAWnYGHkLayo+QBJTXEoJDBCh4vQeCyAHScacOTcPly/9hUn8eu4" "cp0O4NpFfHHjijqCqL6kQ6BTkMn+y69u6MQvzuEvf/2TwkRgIEARV2GdiYBC3IZIjsn5AgcJ" "P8mkfvLkSRw9ehT79+/Hzp07sWXLFjQ0NKCaDj/Evzcv//ZKS0tRUFCAvLw85ObmRrVp0yY9" "VlRUhIqKCn3O9u3bcejQIX3N48eP63js2DHdlvcSYJw+c1LBotsCkNPibMznOXXKHD9x5nOc" "Ok+dOo3PTx9G864y5BPGycVDCYUXkVDYD/EFXbEurzM2EhorMp/BqvRnsYwXk0uTH9PFEZck" "yrEumueQ5kGpskooeEJvHJUX6qlQSSSIlvFicn3uH7Ax/0kHIISHAcgfo/CQ8TtB0Q3Vd0UE" "yD+Er3G8GgXID4LXvgYgVxQgBiIXqfPcvoBbQxdxa5g27qv92Lz9Nf6YfooltXdpSe3swB34" "LHwTr0B+xPEHURcyv8asVyVNgdKpvlbWzdpmYCHOQ9yIAEUXY9zycz1HHMjiRrNMybyqO5HR" "OAoXvjqCuzz7Y/Luxc99Rnd3qN34hXc37vHuVP3CZ8Zf+XZx3IZf+7bjVxx/4zG617sd9/q2" "qu7ztkR1v8foPm8TfuehvA34nb8Rv/XW4/7KWvy2oha/E3H7AU+16kHqYU8VHvZGuB02qgxR" "QTxQGaD8lA8PVnjxULkHvy+vxKOSUCdAuvFH3IcA6a8QCeB5/rCHECSynIlUYkmVVUn+5G+8" "HlUkvT+G0k28QIA8HywjPErQ11eA3p4C9PHmoy8lEBkoIAkaVzKQjw8kYJ7nsRfViViQlBAi" "5XqDqSn1Ho7lmvd4XUJZhMZIEd2IuJKXQ5swIpiF4QTHMLoP0UvBDA1ljQwbByIaSbdhQ1uv" "OeW8oyMiAUgWxlHjq7MwgRofkXBWGkYHU/F6IBkj/Ul41Z+AVwMJeD2YQLeSyHMSCRiqKkE1" "idtTapLxluQ9CA4jwqMmgeDYSOeynuesIZhW09Ws4XnrCZgEfEQXIt3nM5tN3mMG4fBxYyLB" "s4HPXYdpNesVIp/QjcygE5nVlIzZTUm6TElV/jBNRstNpSKFL2F5wyosaE5AWngGDqV3fG+R" "g+lPYVn9CgJA4LEOixrXEAqrFCICCoFHXOMyBYaRBYkDEGpR41L+3RAgdCtLG42W8fjypuUE" "yTIFiR0ltKX5EEJDE+wtAppFfM48AiiOrzEHi+pnUtOpT7G4/hPqY25/zL/nD7GQLmRB7TQs" "rHkXS+o+wAo+vrZxFlL4OoW7U1F1qBxbjldjz+kWfH7+IM5dPoOLV87TcVzElatXoqGj69ev" "67ZM8jKZyqQqYSAJFclELBP0gQMHdJR9ubIX1yCQEagIRAQc1o1YJ2JDV/K4nCfny/uJy5DX" "lvf5/PPP9XUFKHv27MGuXbuwbds2NDc3o76+HrW1taipqUFVVRUikQiCwSD8/LsU0Hg8HgVJ" "eXk5SkpKFDoCms2bN6OsrEyfs3XrVuzduxe7d+9WyfvIe5rvGAOIuBLZ7kgnTx1H804PykKz" "kFs5EemFE7Ehpx9WpD5DaDyBlelPYkXa41iZ8QdtIFya/CgWxP8eC9Y/znMEJE8TKk9hbc5T" "Wo0VT7iI+0jIf9oA5L9GvlL3YQHy7UDHAPmH8BcKENH3glcdgBgH8sOw0c0uWYAYXcAt4YtR" "gNwaPocfh86h7lgiEho7Y2nkYcys+Ak+CvwQHwdv0mqpT4I/UDciIa25tT/SjvKlTXfSYv9U" "XYaARMHhLAO/hu5k9Za7+AMnQJp+wh/rz5DQ1AXbj2/GzyoPUPtawePrAPIL714Fx90egsIT" "A4jR9ihA2sLjPg/l3Yr7fdtaAeS33i1RgNzvAsgDPkq2PfWERj0e9NbhIW8tHvLVEBw1+D3H" "3/urORqQPOyJ4CGC5CFPiApyP4DfU494fHik0otHKzx4ggDpRHX1CEg86EH18klIy0/3ENT1" "sEY71VZZRR92uFyH23lUZg7BUN9mDCQ4RP3pPvr6i9GbzqOXtwC9PPnoTYD0ITD6qggUnt/H" "S3GU/f7+fAOTQIHCZAQdiiTWJ9RWYFJtuS5b8npVEV6mAxkeysPQQC5e9OdgsD8TL/jSqTS8" "6E3BUH+awuQldSHZeFVEwLwsCmRydByKKp1ASaMrSSdU0gmVNIwKpWJkMIWwSMLLhMYI70YM" "923AUM96jusxIrAerwQ20NlsoIuJJ2g2Ej4CkURMrk4iRBLxVk0SlaiaWkV4RNZjctVaOpc1" "mER4TKldh7cJhWmSVK9PJESSNB/yGR3GJ41SpZWIaQTM2zz3bT5nWvVafECgfFIfr7erlTsO" "pvg/xdHUx7Evo/M3vie7VN+lVfJKnqCZ37ia4FijyfPFzWuxuIUgaV6tEJnbsARzCQWBxnzC" "Y4Ejuff5Ih5bTC2hFB50I8sbperKhK8kB7K8aZnjThbz72wJgWEkJb1LGxcoOBbRcSyk41hY" "N536VGUBssTRUu6vaJiBNU1zkbx1BXJ3J6DyQB5qj/qw82Qzjp0/gPNXz+DydcLi2iU6jKtR" "YEhoSCbNffv2YceOHdHJVZxAOBzWiVomcDkmk7tcyQs0ZOIXCKgL+ctfo2EsCVX9z//5P/G/" "/tf/Uv2f//N/VAISkUBFzrFhLAGK5EEkByLwsuErm9uwk7lM9OImDh8+rBO/fF75TOJcBDLi" "XuRzihobGxU2kaqQQsbn8ylkBC4CE4GLBYt8v5aWFoWLjOJiDvN7WmCcOHFCv7Pd15DXyTPm" "mJNb2XWwCE2716B+1wKEtryPisZhKGnoibKm3iht7MaxJ8ob+6KiqR/3e2FT4FnE03HIirxS" "wiuJ9LVZzzgACZnw1X8Lx0JYHQPkWhQiBiBXowCxzsO6DzdAbglfdmQAckvwQhQgdmw56sGG" "0CDM8N6OjwP/YCBCgIgbmVNlkurSUb6k8Q5d7kQAIkugbNhmpLkPwmNVy91Y3fxLJDU/h4bD" "OfiJ7zB+4jngAOTANwKIOA+r1gDZ7gBkRxQgX+dA7vUZeNjRuBADkPujAGkwohN5gPB4UOFR" "i4d9Djx8hIe3Co/4qxQivydEfu8NExwh1e8JkUeoR70BPObx4jFC5HHC40le1TzFH9pT/PE9" "XVGOZyrL0dlTQaBU0j0E1I0MrwrTkYQwxZ8NX+ZQ7ZuI1rxzO5TWH2+WriQESuhm6DgCxRTh" "4ez39hZRhQRJgaqXyGtg0suzmdt53M5VkPR1XEo/nziVzRjEY4P9eRgW3IyXQvkq2R4c2ETH" "kkP3kkVlYoA3nUrDAE8Kn5NCkKTiRcJkiD8dQ/jYUGoY91X+VAImRcdhPG8Yt4f7kwmGJILB" "kT+RSuCxeJ5DcBAaQ72iddxex2PreN46wmcd4bMOr4fXEzobMCYUj3EEyoRIPJ3GBky2ovOY" "WLUOE8V9RFYTItKwuB5vVsfj7ZqNeNfJibyvIDESx/EOncdb1avxZmQlplJvV63CezVr8FHt" "WiwNxeGUs4Dhdece5SL37W3br876C1TmDcYn1Yswo3Yp5jSIq1hFiKxWiGgVVpPJhcyhs4iz" "8GhaqQn2hQTLQoXIMgORhpgDWSad5S3GbUgeRPaXKCwWcXuRgmOZuI4mwqNpHgFEeDTMJEAM" "PBbVCTg+JTA+I4xm8G9zLjZuXYKMHWtRsCcNkSOVaD5eS5exHUcvHMSZyydx8eoFgoPAuH5N" "oSETv0yEMhFbaMjVvYSKCgsL9epdruYlhFRXV68Ts5wjrkMmcZlABToWHhKycsNDICHg+N//" "+3+rBB4WJAIWm1yX8925EJtMt87EnQMRmFhnIKNM3iILlSNHjuj3EcAdPHgw6mAEMPLZBQ7y" "PQQsIvm+4kgC/PsVsFRUVKK4uFi/v4xyTEJiAhdxPAKp4yeOxZzI6c/NZ6AbOX1aAGNczImT" "R3HwaB12HszD1n1JqNs1F57mlxUa5c09qD4ob+qP8oZeRs3dUNrQVdfBSivrQoC4wlciG74y" "utEmhHXVFcK6Gst/OA7EDZCbCIqY8zDwuCVy3ogAuZ0uRMBxG/fv4Pbt3O7afB4HzwdQtucT" "rK7tjpneu/BZwIazbsK8upu1qkq61cVlSKmuLr5IcKxvehjZuwYjeGQBjl9rwIiW47jTe4jw" "OPSNANIaJMZ9aPjKAYiErww4zChqBQ4rVwjrXk9zK3j81ttsRp8LHlERID7HfVh4+Bxw+CNG" "vjAeoX6vIkC8BiCPKUB8eII/oqcIkif543qC8HhcRJAIUJ6mOnkq0c3nQe+AOBIvBgR9BIqH" "25VUOVWGfn7rMEoIhWL09FLcjsovx4r4GOHhLyRMCtWNKEi8EtYiQLwCkFwHIpujYS4ByEAB" "iC+PYNiE/p5s9PcSFt5s7mcZERz9qX6+DPQjIPp5UqkUnpvCxw1IBnmSMagiCYPKEzkm4IXK" "RLzgTcJg6gVvopEvgfsbOW4kdDYSOBTBIXqR4BiiWsfjBh5DfWsJnbWEzlpCZA1dzhq6mdWE" "yVqMDKzFa9Qobo8JrcbY0BqMD6/BhPCaKDwmhlerCxE3MoVQmUpIvF1LWBAY79aKIzF6p1bg" "QadStRKTw8sxKbQUbwSX4c3QcrwdWYFpPL7YPwt7057+u8159mZgGYWvYVpkHj6oWoBPaggR" "TZivUGiI81jYvMqEsBoEHIQFwbGoWSqw+BgBMl+OExjz6SwWKiAEIEsUFsualpibRTUvVtex" "pEngITePkl4QcyOppU0L+RzCg25iUcMsuo0ZGrZaTC2rn0mXMQ+JW5Yje+dGlOzPQehoBXad" "3YrDF/bj5KXjOHflLC5cuYAr1y/j6vUruHzlMk6dOa0Tq0yEcpVdV1eHcCSsV+cCClE1J1Q5" "LhOsTLZyrkzEMjFLqEomb5nQxSXIZG8T6BKWsuAQQLjBIZLt//t//6+OAhI5x4JEntcWJBLe" "shVZIlvSKyCRsJrARMJN8nmsO5HJXJyCfE6BiuQ+5HOLBHzWsUj4yobGxGm0tGzRfw9xW7V1" "1dHci8fjjYbCBCilHCs9dC+VFQoX+feR97EgE5ConM9xgkCR/SOf89/wSBX2HCpH4+6V8LQM" "J0x6aPK8opGupF6A0pPb3VFBuERzIP81Ig7kBgHyRbsQ1ncdSfLcAOTyfwIgl9oDxAGHAER0" "u6M7wmdxZ/AMfhI4g9zTtINf7MG20wXwHViE3C3jkbP1FUJiGPJ2DUfB7jEo3P4uag6vxN4L" "Fbj454MYTmjcUXlIdWflQYXHT72Ho/CIAsSBhwXIXd49UXj8wr8nGr5qDZDt7QDSChwugEgY" "q3UOxAldOeErDV3567hdr/B4kMceDNQrQB4mOB5WeMQA8jDh8YhKABLSMQaRAB71+PEHAuRJ" "/lCepp7h1dizVBeqK/ef88qS7150obr5vFql1SdgRaD4KwiCMoKj1LgLqhdB0csvwChVcPQg" "THr4itCdrkPU02fBEQNIHwKkr9fJi8i+zzgSgYi4kb4CDgcefQmP3pUZ6FWRrupdkcb9NPTx" "UF6jvqpUnpuCvpXJjpLQj8DoU56AfmUb0Z8aQIgMrNyIgR5uUwO98QTNRjxPcLzA7cHUi6oN" "RhYgXgcg3rV0NWswLCBaTYisxgjCY0RgFV4KrFS97F+JV6mR1OvBlRhNjQmtpDNZhfECkMgq" "BclkQuQNAuRNAmRq7QbVWzVGU6vXERyETHglgbMM40OLMT64COMDCzExsAiTA4sxJbQEb4WX" "EgjLscg3HdU5/XEy8cFWoaxL8ffgaPLDyC8YgY9DM/EO4fFuJA7vVc3FR9Xz8VntIsyql1DV" "MsxrMnkOU4G1VOGxtGUtlm0xSXZxInENi+lMFmFew0K6h0V0IEsc97HEAcQigmMhL9wkRLXQ" "AEQeo2R/cQPh0TBXQ1eS85BS3RWNcYjfsgxZhEbp/lxUHfFh68kG7Du7C2cvn8LF6wIME5q6" "xAn3DCfYQ4cPcZLcpkCo5lW0DeXIVXcoFNTwVE1NtT4uE+ru3Xs4ye5X0MgEbENVMnHLJH7D" "yXHIJC/QsDkOAYGFgjtkJdBwy8LEQkSAIwCxpb0WIOJoxInYXIx1IjakJfCwLkQma+tC5DNb" "cIgTsbkaKwGIGyIm/LVLHYrAZNs2AmWbCWPJv4nAVIASDkf4bxYkUCoUKPn5+RoCk3Fzfq66" "NXmtYycEIDGYWQnUTpw4iWMnj+Hw0d3Yf6gZW/ZuoDMZgrKmLoSJuJFuBEn3WAhLwldW1oF8" "V3MixoF8P/SFKwdypXUVlit5bvWjyOUYPAQaFiAKjfNRB+IGyE/D5xQgd/pP43bvSdxSeYL6" "HLdVHsetnuM6/tj7OW73HTPyHlXd4TuCOz2HW4vuwziQA+0B4kDk7q9NoLvyH9QvPTtaQUT0" "a+o+R63g4d8WDVu5E+gP0H0Y59HIMeY8FBzUQzz+kJ8OxG8ciAGJdSBuiETUhURFF/JopZ/y" "EiJePOERF0KACCwIip4BP3oEfOjh9+t2n2AA/UN+VT86kD50H70IkN4ESG9fqcJDFSBMAjKW" "oRfVgyDpToB084oK0cNrciAWILpN9ePxAYEiDKT6051IDqS3TxzJJrqTHIKB4tjbk4WeBEhP" "wqMn4dGzIpVKQa/KVD5GER69vbKdTCXxORTh0deTSIgkEiIESAUBQg3g9kBPggJkIMERhQfd" "htVglQGIgYdxIEP9hAhdx7DAWgcgazA8IPBYTXAQIEELkBV42bcCr3B8TSASMAAZS00gRCZJ" "CCsScyFvVFM1BiRvVq/HlPA6goNuRc4PLcM4gmIcoTE2sABjffMw1j8P46gJ1ET/fMJkAd4k" "WN7iOe8QNNPCS/AuNS3CsWox3qleiHfoON6umqcAmRaZqwD5kPq4eh4hsgAz6hdhdsNSDVvN" "JhTmUOJABBxLWtZxXK35DwVI/QLMrZ9PiMwnRMRRLFJQLFEZeCxqnE9IzI+CZIkcIzwWEh6L" "G+Zoqe665qVI274BRfs2IXzUi62nmnDw3F6cv3IOlwQYdBhXr19Vl3Hm7BmdPGUylMlPgCGT" "m1wxCzQEGDIhSvhG8gSSN5CJT4BhK5RkgparfJm0ZfKWSdyGqazbcCfHLTisy7DgkNH+5waI" "DWPZxLp1ILYnxJ0HsaErk3Mw4aqO3IUAwQ0FmxcxUNimo0jCWDaUJZAQubdt/qSpqUklEFFn" "4iTuDUzCmrSXf0/rTiSXkp2djczMTK0Mk397+WwWbFoBRjciruTzkwKSI4TNCRw9QeAdO4im" "vctR2TwAlS093TmQWAWWOA/jQGLhq+8Fr7dLon8/EEui39zKgVyKAkQhYp1H5Lwm0G8LOuBQ" "iJxx3Md5/CR0FncETuM27wmFhRsgVm6A/NgByO3e9uAwOhAFyF2eg5pEjybS/2YFVmuACDwM" "RFoDRBPnzqihrDb5D1VlswJEw1eS+6A6BIi/XgHyiN+Gr6oVHG1lIfIo4fEoHcijAhCPAMSH" "x/jHJ/oD9YTXg04+uhBC5Dm/D90IkV6ER19eyfULcyQ8egc9hEoFnUUFHUWZE6Ki+wg4AAmW" "ESIEC+HRi/s9/I4T0RCWVaEZJR9C9eP2QL80GZbi+WAxBvgLnKS6AYhRNnoJQDwEiIcAoevo" "SWj0IjB6KTxkFJgkESoJqt6EhMKD6k+YDPAmERYU9wcQHoM4DvJy9CUYePgJEWqwSMNWRkMI" "kSEORIb6DUQMPCR8RXjQeYgLGRFcFQXIyyLHhbzic1yIAITnjCU8xkXEhTgSQESMxlOTI2s0" "pCXwmCCOJbgMYwJLKMLDv4DjfIwhNMb451JxGOebQ83GeI4T/HMIkjhMCc7D1NB8OhMqItBY" "gLcEHnQb71TNxzRC5L2qOLyvAJlDFxKHj2sEIgsJkSWExzLCY5nJfzRIxdUKLJLwllZnES71" "CzGzbh5m1c3F7No4zKufpxBZLPBoWqIwWdxkASJ5jvkKj6WEyAo6lDUty5G4bT027c6A91Ap" "mk7UYf+5Pbhw/ZyGpa4RGFevXcHFSyb5LVfaMmHKpCeTnK1MklCMxPkFGDJBymQqTkOuwgUa" "MrlJ+EegYYEhJboyiVun0bZJ0OYvrOtom+twy8LDHcoSyfNsr4gbHrYXxPZ7yGcTWMhnlc8s" "n10kjsGdNLcTvchdqWUnfbds9ZaV7Lc9pyO5nycQkX9bgYg4Oqn8sjCRkmKp/MrKylKYyP8H" "+cwCuEOHDxAmpzSX8vmJgybcdvyw7sv/iwNHqmIAcec+BBp2/O43AMgPQ1dbVV8JQGwfiHEh" "F6PwuNVxHgIPo7MEyBnC4zzhcZbwOEW3cRK3VpzQ8bbKkzF4eE50AJDD7QByB2Eh8LAA+an3" "oELDAuRnnj3RsNXPvwYe0fBVBwAx8OgYIG3DVwKQ+yobo8lzcSHuBLoFiIFIW4BUdwgPCWFZ" "eJj8h19zIJpItxAhQJ4gQJ7yCUi8BIlAhG6E4OgeEHdSiee8FVQZnqPzEHUlQLpLjkNdiDiQ" "1uodKHYcSjH6+CRPIvmRIvRUN1KoDqQvXccgnjfY6VQfGCjUKqx+nlz0JUTEffQiQHoqQDL5" "vAwqXR1HH186+vgpn4SwjPvoVZFIJfB5dB3eZPSnDDySCYxkwkKURCXiea8ogfBI0NyHwsNP" "cPhN7sOAIwYPcR/D/C6ABAxAjPtYTWiswiuUjv5VCpFXFSB0IYHljgsxISyBxwQnjCVORAAy" "LrxcQ1sCkckS3pJzQsvVfYwlQMYEHIAExIHEqcYRGkaECMeJgTmYFJyNN0JxeDM0jwCZT4AQ" "HITHuzUL8F7NfLzP7Q/oOj5UxeEjcSEEyKd0IdPrFmFm/WINac1WLdZKrHmEyTxxJQ48ZtTO" "Uc2qnU2IzHUgItAQeIiMCxGQSNJ8tUJjA3J3Z8F7sAKNJxpw4Pw+nLpy0jiNL67iytVLOH/h" "PK/GT+iVt0ykMnnK5CbQEFU5eQyZWOVqW86RyVcgI5OUhFQEOnJlL9CQq303LGwy3CbERe5u" "cus6bIVVW4i41RYc9nx5LdtMaHtD5HNImErCU/IZrbuQyVe+h3wfAYR8NwGETXDLRG5Dc7bS" "SlRZWamSPIZM8G7JMVuN1dHjVta9Wdn3cMs+Jufa9xOYCEgkxGVhIg5FXrPBgfm+/XvUoShM" "HKciYxQgrauvbmjoSkJYsfxHDB6mmfBKFB4/iIatDEjMaCCi8HCkJbyUO4RlAHIOtwXOxODh" "yMDjZAwe3xAgUffhO6iyAIlC5G8ApF3+I1qF1dZ9tM6BSAlvW4DY8JXNgRh4NBmA+OsMQLgd" "FSEiAIkqUO2Awy26DwLkMX+IkDAA+YPPT/koL4958TjhYSVO5GlxIxrWqsSzvkp08pbjaU8Z" "nvGUcizGM95iHitCFwlP+RyA0IX0UZlQVl9nXxLrvXh+b8dx9PKY6itbgWV7QqQXRDRAmw0J" "EG8e3cMmdR89KzNVvQQgdCG9vQKNDDqVDPQLUH7KJ/mPFIIjmWMyn59CeJhEuoFHCqGRYgDi" "FxEi/kTCI1EBIvCQ0JXCw79BATJUK6+c6itqmLoPA5HhApDgWjqPNXgptFoT6BYgKt+qaA7k" "VYLjNUejNQ+yEhOrVqkmVa3GlGqTRJdxcvUaBcv48AqCw4SuxoboPkIL6UYWYBwBMo4AGReY" "62hOVOMDszEh4ECEeiM0F1MjczVs9S5h8R4B8j71AQHyYY2IAOFjH/ExAcgnjj6tlbzIfEyn" "ZlAz6xao65hdvwAz6DoEHNNrZ2FGzWxMr57JcRbm1MzB3Lo5mE/HsYAgWUy3IQsoStNg6s4k" "FOzNQ+CIDy0nm3HovFRPncLFaxdw+eplhYZMqjKhSiimLTTkilgmVZlkBRh6tesChoSABBgy" "Qds+D3EZctUviXCbBHfDwg2Mr5NNhLv33XBxg0Nk3YvtBZFEvLgO+Uy2D8Q2Fcr3sE2F9rta" "MMhELJO/VI3Zq37JSdi8hEgaDEXiAkRtGxA7Om6fY2VzHVKZJZL3sZL3FVDIZxDJtv1Mdt9+" "Nglx2c8iYS6R5FPs/zcBvPy/En3L9oB8O/RVNHFucx9RgISuOw6kNUBErfo+CA4NXTljNHnu" "hkewNUBuC57FLf7TuMVn4PEjrwMPwqSt+7i9A4DcwbGj/IeFR1uAuMNXd/v3tQtfdQQQ0/fh" "Bsh2hYiMboBI/qNtD8i9nsZWAJHwlQDkd4H61gBxXIgFR1R0IgKORwOiiJEFiI8AoeV8XOVT" "KUR8xoHEIFKJJz2iCqoUT1BPekpUTxEgok5UF4Khu1ZfGYAYFasUHk4IqztB09MTC1tp9VU0" "Wb5ZE+gCDgMPE8KSBLqEsTR0pQAx4ateVo4D6UuA9BfRifT3pbaSgUdKDB7+FMIiGS8EREmt" "4UG9qHLch98AZAidxzC3AgIPA5AR1EshU331klRguQHiuJCR4kAUHnQhwRV4nY5CNJoaE16G" "sQTFxKo1hMdaTKlZi0nVUqFlnMf40FKCYzHGBg08xosCMs7jY/N4ThzHOI5zMCE4l+CYq/Aw" "moWJ6kRm483wHLxVFYd3CIv3KQVItQOQGqnGmqdhrI+q5/L4HHysmq36hGD4rCYO02vEdcwl" "OAgPAQehMb1G4DEDM6pnYCY1m25kXv1crbxa27IaGbvSUHqwFLXHa7DjzHYcunAAJ+k4zl45" "i3MXzuHEqRg06nUiNTF4mUxteanARMI5Ev+30LBhKZv8FmDIRC1Ow0LDNvrZ5UVsXsKObrnX" "tHKDxr1EiX2tjuBjz7ONhOI6bK6jreuQ/IU4DglFyXeUEJAAQyZjTVo7k7Gd9HNycqL5B6uM" "jIyo0tPTkZaWpqPIHutI7ueI5LXEPVjJ+4jkPS185LPIZxJZeAlsLNDcYLOf3b6OfU/5bvId" "5f9nhwCxuY/vOPAwMqW7MrodiM17uBsJY/CIAURKd0U2/6E9IIGzuJmgEP2IuqUyBpC24St3" "CCuW+4gBJFp95UDEDY+vA8jPfR0DxMrtQCw8YgDZ3iFArAOREl6Bhxsg9zv5j1YAaRXCqtfQ" "VdR5BEwfyKMcBRyPBR2I0IU8ZiESCODxgB9PBAxAHveJA3G5EI+oktCoUD3pKW8FkCcJDnEh" "nbwGIN28Um1VSsUqr7Rs12/KeXvoOYXRRHpPr+NAPJsJhFzKKd0lOHSpExX3/bno7cuJhq5i" "+Y909KhM1RxIb3EdgXR1If05DhD506LwGOB2ID4TvlKA0H0MFgUSKQIksFGl8Ag48rsciILD" "wEMBElxjABISESDUK+pAjAsRiet41XEf6kCCKxQiBiDLqKWEyDKMCa2g21ilifUJdCbj6UrG" "ifsQuAg82gBkQkg0n+cSIuE4TAw5IkAmCUSCAo/ZBiCBmXQiMzE5MANvhmbh7cgcvEuQfGBD" "WDVuxVFSlSU5kdkEySy6kxnUTHxUNYsgIUwIiM9qZ6qmExwCEBlncpxDsCyuX4R1W9Yic1cm" "Kg5VoOlEIw4QGicun8Dpy6dx5tIZHD9zHAePHMT2nTtQ32gm0QCBIVVANgku0JBJdvee3Thw" "8ACOHjMVU7Y/Q67o3T0aFhjutarc4Si32q5dZSuk7JIkFhRWcsyW4LYNgdnFE63c617Z5UwE" "dtLDYV2HuCi5KhdI2tyCTL4yYVtQuCd5gUNbpaamtlJKSkq7Y/9ZtX0PCxj5LDLKZ+sIMhY0" "7lEkj8v57u8hr/Wt/xbuCCBftlq+RKBhly+REl53+OrmsO1CvxQDiLt50FZgRQFyVnVr4Axu" "9ohO4iaCQRzIzRxFMYA48PCecMHj81ahq1bhK0dSumvBYeBxMFa+ayuw6D7aA2T33wHI9nbw" "iHahe7dGQ1ixJHpTtPtc8iA2/yHwaAsQk0RvDxDjPiJRPea3ClFBwiNIeAQoA5En/I4Ikiec" "ENaTIh8diI8A8ZYTGmXqRKwDedobA0hXwqKrU2nVzVPAsYCOo4AgKTRSeBRE1YPq6clHD4Kj" "e6VoE4GQq70gffz56CsK0JkQIL0EIF4CxGtyH70diQORMFZff0YMHgRHTASIT+CRrPBoDZAk" "AxCFBxVMUL1IgFh4DPVbievYEHUeqqAZTejKAYjAI2TyIOI8XlXnsUpDVsZ9LHccCOERdAAS" "WIpR1JiAgGI5xvKccbpNqAQd56FVVwu18mpcwIEHwTGRAJkYknGuahIBMskJWxl4zOb2LIXH" "pMB0TPZPj0LkHUJEEugfqBPhqODgWEsHIgCh4/iQsPiAAHmfAPkgIppOkEynI5mBT2uMPqs2" "8JhdN0d7PJK2J6JgXwFCR0PYfno7jlw4SqdxHhev8QqcbuPI8aPYuWsnnUa99mdIgtZPyWjz" "GhI7l5yAuBJbZnv27GmdiK3TaAsNtzP4OmhY12Hdgy7B7oDBLZsXsVCx5bYiAYOEpOw6WHZd" "LFuaK9s2Sd7WdUjITVyUDc3Jd5ZcglzJ2yt2mVz/FiT+lv6/AuQ/8zw3WNyOxroYCxa35Lg8" "7v5O3/rvbRzIdzm2BYh1HgIQKeG1fR82bKU9IBxvitjy3SsKj1sjV1o5EAlhiQO5xXcu6jwE" "IDd7jdzuw8i4DgWIA4/bfcedEl4HHhquouPwHjHyGYD8zHeoHUAEGG6A3O0CyC90/+sB8mv/" "zihABBhugIgsQCSEJQC539dspGteNauiJbzSA9ImdNURQB7117SChwXI4z5RiKAIExpBR34j" "BYgXT/o9Rk4iXeWvpCq4TXnLCI9SwqMEzxAkneg2OitEivCcpxDPOS6jq8hnRtMDQqAQLF0J" "jW5Ud7qP7oRHN7qPrpU56Fph1K1SYJFDV7GJ4Nik2z292QqQXgRIb6qPj/JnKjgUHtQAlUDD" "DRG6DkJEoeF38h4ueEj4ygLkRYFHcKMDEAORoQ5EBB4CkeF0H8ODMY0IrSM81mnYSsDxspMD" "eSVIeARN+ErBEZQeEHEdThKd8BCIjNIQ1jKMJkDcGktwjKEzGRNeQogsputYhHGhhZr/mEBN" "DC/ApPB8SsJX8wiOeQYeIeM+VAqP2Q48RDMIj+l4I0iABGdiapAQCc3Ge+HZBMQcgmKuSt1H" "FCAGIh+JBCKExwdVn9GVfEqIfIbP6Djm1s3TlXjTpJLqiA/bzxIal4/i9DW6hOsXcYngkF6N" "/Qf2a/WULhwoSVnp03CS4bZ6yp3XkESrJMEtNGzllE2Euyf6tqW27sS3u5TWhqbciW03AKz7" "sC5DICGwkiS8OAmRfA5b9msbAO39PXTxRULGLqAo4BDXISC0ISub67AhK5s7cMNDJnQ7qdvt" "bzrJt4VOR8/7OjC1Pdf93m0/Q0efqa1zcbuXti5KHUj75Uu+1NV3Je/h7v/4XiTWPNh27Sub" "+zAOJOZCpOrKwuNW/3lC4qwLHmfoPowDaQsPCV8pNJzk+W2+z1XiPn7sdh+234PwkNG6D1OF" "tU9LeA1I3P0f+/724ome1kuYSA7EJs9t+a47fKUORPMfWzhuMaM4EMJCHYi/MdoDYl3Hb50k" "uibTqWgZbyBWwmvyIJGoBCB/CFQpPBQgreARJDCMC3mSEHkm6MXTHK2eIUyeJkCeJkBEz/jL" "8bSvDM/4SgmPEjwrIkA6e4oIEkJEnAih8pzPJNe7uKBi3AcBQpfRTeFBVQpANhmAlGejW0U2" "3Ug2nQlHTxa3M1Q9NOdh4NGX8OgXMOpPDQhmYYCM6kDSXRBJxcBAqkLk+UCK5jwGczTbLoAE" "YwAReFjnMcyl4YENhMYGQoPwCBl4GICs1dCVug+VgYdopMpJnIdWunIfy1SjRITFa8EldCGL" "CQ8BhtHosGgxtxdp6Eo0PrQI48McCZCJApCggGO+UYDbQXEgApA5jmIOZLKI8JgcnI4pHN8g" "TKZyfDs0E+8SIu8RIu/XzFUX8lHtXNXH1Cd1czVk9UnNLHxCt/FJtbiOWZhbvwCrmtcia3cO" "AsdC2HluF05cPYGLNy5rJdX5Sxe0fFNyFgIIudqurDQVPxK2kTi4AEXyHrZHI+Y2zkYT4W1z" "Gm0b+9xltm653YY7BOVel8qCQrbtEiNWAgRdFt2uZHvmTLtl1EXue3VY2Ak4bFmufH8BowDS" "Lisi8JAkue2tkDCPTLQyyf6nHEFaMsc0JKcnu4CTqsfsflr0/LToaycnJzvnOTBITUJSakp0" "2/369rwoMPQ928BFnuMc11Gel5GCtPSUDkNvDkBaV19ZfdtZvt1CxHaetwXID1sl0B05S5jo" "MiahcwYghIcbHHb7JidxLiEsdxXWjz2n2oStLDxaA0TdRxv91G8aCH/i+eYA+bl3T2vn4VpA" "0V191RYcse5zp/LKZwHSFJVJnsdKd6UDXZ2HU43Vqg/EnUB3ANLegYQ0hNUWIDaMJQB5yg2Q" "gEcBYlQRVSdCpBMh0skNEXEiVBdHnQmQZwmPzpUFhEgBIUL3ocqn8uhEclUCkG4EiJE4EAcc" "VDeCo2tFGpVKgKTRlWQ48MhCv2A2gZHlwCNLQSJJ9H6+GEAGigiQQQEBiJEAZLCMwWQCgwol" "UQkYEkrEEEJkaCABwwgRt4arCJFgPEY4EDHwkLyHSaC/QvchelUUBchKR8tVmv8Q5xF04BFa" "7ox0HhKuIjiM+zAAEfehlVeS+xB4BA1AjANZgMkEx2SBSNBxIAIQdSCzo5qsmkXNdER4hKY7" "IBGITDcQiczCe9Wz8QFdRxQeMkrOg/qMmlE3B/MaFmPt1g3I2ZOL0LEq7Dm/F6euncKlG1dw" "5foVnDl3RvMVcqVtr7JFUlkkuQ0borJuw718iK2gstVT9kZOHbmNr3McbrdhQ1Tu8JJdct29" "LpVdUsTeLVDyK+KA5LPZtafckmO2G9yWpdrqIoGM5DnsSrjiOqILHjrJcoGHVDK1DV21BUha" "WvrfcRtm0k5Kkwk8EanJmTrhJ6Yk66SekpqA5JREPZbMSVvOs8eT0uORkhmPtIwNSM5cy+0N" "up2etR6p6euRkibjxhh05HWicElrB4/oOWnxKvteX+dQFCCmeTAGj+8QHN9xch/iPsz9Pxz3" "Eb6quY+bIjb/YXIftnQ3mvtwch4KEAlZRd3GyShAfqTqKGwVg8ftHcBDJN3nraDhNXIDpKPk" "uYXHL6IVWLsVHhYg7d3H14PDdJ1vdUJWBhy68q5um7DVb12d5+7+j4cCTa1CWA8H6ug8/j5A" "JHwloas/BGLhK3EeMfmicgPk6QCBEahsp2cDZXjWX8qR8pcQGCUOQOg6fAQHYdHZk6/qYlWZ" "h84VuehSsQnPqfNwIKIiQLw56O7NVvXwySggcdwH4dFHQUFwBK0EIJmOTB7EJtAH+owEHoMk" "fMXxBQGHP1UB8mJQQCLwMO5jiECETmRo0ABEwlfDVA5A6E5GhOKNguvxUnCdwuOVMKUAcUPE" "7UAcFyIgCRMgYUIjTGhwHM390dweHTYAGeNotLgQcR+EyDgNYS104LGI8FjkAGQeJhIcFiAm" "eR6nyXMLj4kKjrYQmaFhrCmEyJuOpoYJkfAMTIvMxPt0Fx/VznHcxxx8yu2ZdXFY0LQE67dv" "RP6BAlSfqMFeguPM9TO4IuC4dlWTxNLkJ1fYdrlxu1Chu4pKJlWb25ArdZlwbULchoCs22ib" "DHcvJdI2r/F10HDnJdx5C/c6VDYsJe5BHJBd/dZ2egvsRLJtm/zEWdiucNshLs8TmNhucLs0" "u7vpMQqPkmKtWpJEc1ZWLHz19x1H2+MJOlELNBI5iYuTkMk7PWs1MgrikFn6IbIr30WOxyjL" "9zayA28gVzUJeYEJyAuNpyZyexw2BynfWGz2ct/Dxyun6FLuOeVjkVM2CZtKpyG76BNk5i1E" "WtZKhZEFiYWTwEy3/4aTijoQNzgUHk7Yyt5AysKjLUBuckp2bfe5wEOdB+Hxo8B5hcdNladV" "UcdBgFh4tA9dta24isHDlO8eUVmA2LJdC5BY8nx/K3hI/uPrqq5+7t2Fuz17/gY8DEB06RIH" "Gr/x79BwlQlZOfkOByBRcLhyH6IHHYDosiW+WA5E3IcFyKPBWBmv2TbVVyZp7sp9+P9zAJGQ" "Vmt4lKuepQsRiHS2IBF4+K2KCJNCdCFEnhP3QXg859lMgOQSIDkqAUg3OhGjXMJiE3r4c9Az" "sMlRDnr5swmObDqPbPSh+vroPPwxgNgwVj+/VGARHEHjPgYGYs7D6gW/4zwUHo77cAAi7mMo" "AWLgkdCB+yA83AChA5Hcx8vhdQTGWgLDgUc45kIEHK8FV1MGIhLCej28kuBY4cDDigBxO5BQ" "LP8xjhARaIwPLdRxgrqPheo+NAdicx/hOB0nh5yRMJkcmoPJ4Tl4IzwbU1SzVG/QbUwJzWgF" "D9Fb1DvUu5Hp+KB6Jj6S8lyCY17jEqzbnoDNB4tQc6oeBy4dIjjO4eofr+rSIidPncQ2Tpji" "LmzzmoDD7TbsYoVy5S5uwy4lIm7DndvoqIqqbTK8bW7Dhqjc9+CwrsKCSPYlj2FvDCXgsEu8" "2/t0yOcRsNl7ctilPmzXt5Vd5VYet0uEWMlzJWxlnyPgtPfysFC1PR32xlHu3EfrkNM3kYSv" "6Dw2rUF6GUERmIzs0DjkhEdjU9VI5Na+pPdA39wwGAVNQ1wahkKORS2DUdL8PPcHIq+hD/Lr" "e2FzXU/k1/ZEQV0vjj10LOJ+Ye1zKKzpQfVEUU1vFFQNQH74BWwODKdeQZ7vdWQXT0N6ziI6" "GQORv5V7+ZZZvuSL1s6D8PiOJM0j16NhK4GGNg26AOJeut3kPi7EQlcOQNR5WIAIOKLwMGrt" "PlyVVz4Dj9t8bngci8HDlTQ3DiQGjo7Ldvd1uGxJRwsn2rWv2lZetV6ufWsbgLhcR9R5NLYD" "iMise1XvUq3CoyMH8mgrgITaJM9N4rwjeFiAPOOzDiQWvnIDpBOhIXrGW4SnKgs4FhIkxeis" "IkD8BIjfSaSrCBEfIUK38RzVnfvd/fkKkC4V2VQmutJx9CA4egYJj4BRb0KlD8c+BEefgEAj" "G/2DoixVP6f/Y4ALILI9iC5kEF3GIM13iPtIITRSHTnwCCYZ9yG5DwlfcRwWdIev4mOhq0B8" "BwARB7JG9aooGsISgKyOAuR1UUjgYQAyOuo+TAhLAeKAY6w2DJqyXQlbSfJcADIh3Dp5bhQX" "kwMQkTQOvhESeFiAGHi8GZ7paAahMYPQmKHgEPfxdugz6lO8Q71PiMysnY9VW9cjb18R6k42" "4tClw7hw4yK++NMN3KBOnT2FxpZmTYbLpCiTo3Qsy4Qpk6dcgcuVuoBD3Ia7Z8Pd5GdXu23b" "r9E2v9FRJZW79Na9xpTIOg2RXWvK9mRYtyHgsAlvu9S7Xc5DZFfvFdllPazke8q5dikRCVHJ" "88WJ2KVAbFOgwENch226k9DVZqfhTiqUMjJN0llDQWnrNeQkTiIlJd1sS4hKwkFJTtgoMwHp" "JXMIideRUzsSOQ0jkNs4BHn1LyCfsJAxr2ko9aIqv2kwNjcOQm59P2yq62tU24f7vameqk11" "3QmPHioBicBDAVLfXW9JW1TXVSUgKZZtjkW1naMqrutijhEyqkg/5PuGISt/unEpTmjL5lm+" "1Sr3EXUexn38IHxdE+c/iLTOebRKnjsVV8Z5XIqC4ybfWfzAczYGDgGG54wrfCV5D7PulYSt" "2lZdWYD82H/M5UAMPCxAfuo54lRcHWlVtvtzOhJ1Hd4DRr59HYSuYjeOap/3sPf9IDjoNETq" "OBwH8pvANh1/69/aDiDu0JUJVwk0TLhKw1auiitxHWYBxfYAebSVIlGAtHYfHQPkaRc8OgaI" "4z7oOgQenYPlPK8ETxMiEsbqErAqVng8JwAhTLpx7OYvQLdAAbpTPaLKp+vYjK6ebDqSTMJE" "AGIcSC+qd8CBB6HR11G/YAwgNoSlAAlmKEAGBowGBdKiuQ9xHwYgaTGAqJIUHCZ8laAJ9Nbu" "w4GHQmOD6qWwiAAJxwCi8AivVicy0oGHBcjr1CgeHxVeRWCsjIJDR6cKa4x1HQoPOg+Fh5UD" "EKm+Ci3Q0l2Bx+TIfMqAZDIBohJ4hA1ApoRFcxz3IU2EBiBTHb2lMhB5h07kHQcgH0RmYXnL" "aviOBXDsyjFcvHEJ17/6An/80x9x4483dLIVOAgsNvMqWiZFmSRlwpQrbzc4xHG4V7q1YSqb" "25BJv6OejbZVVB0tSijQsLeVtT0XEo6ynefWbQgwJFQmALFu43JdM756qD/+9PPO+PLBftix" "qUChICEmmeztch3ewiKc6jdKz/vit71RvTFFj8vj8v3lfLvgoG16FBdil/+w4SrrOgQctns8" "2h+RkWoqlOTKXEM+GQoNlUy8GcuRlLEC8VmrkFA2CcmRHkiu6om02n7IahioyqgdgMzavoRJ" "P2TX9EVW3YCoNtX1d4ngIDRkzKU21/VWxxEbe6j7yK83DqSAx8R9qAiN4vpuUZgU1xMWhEZx" "fWdVSUMXlNYbldR1QlltJ5RWd0Z53bMoa+yEoupnke8fhezNC5CasVIAcqNN2MoNEOM2LDRs" "ktzded4RPH7oPefA42w0dPUjV/Lchq6029x7opVu9R5TWXi4w1bRxLmrXFdGN0AEHm5wRJdt" "9+5pkzTfFbtdrWu5kljHecx5WGC0BYiturrP396BaL+HDVnZfIfIV9fKfTzir3MAUh0t4ZXQ" "1WOOBCAWHv+PtveOjuu67n/113svcYqdxMlL7GU7cWxLllhAdIBoBDslkZKoziJS7L33hkIA" "RCU6AbAXkAABEsDMYNArQYC9d7DIsqpjVUtW7PzefnvvU+65dwaS4+K1vuvcGYAklLUyH3z3" "d+99OPdwACTQ7RJyOI+g2hoDINUcoNuch1m+couTcpAIdyVEoggg4eRGqg9x+SoKARKNAIm2" "waPcAMhB1AGIoVkPdBtx7gMoAZB4CRCGh9uEh5l/GPDQADHgoctWJVLFUkUIjUJ2HRPd+Tr7" "sMmdxwAR3VcIDo+AB5euNDwyJECEA3kZ9YrUqx4DHl4FjzSYws8p4pnXlGxnTanfztnHG97t" "rOn1ybJ0lSjLVtsQGgkMj5mNAiBKswgkDJAt7D4IIHNZCA/vRgscXgUPlGctu48F+EzbeJM6" "MuDY5eNw7tEFeOfX78HHn+EH9Mcf4Qfze3Cv/x5/OHrwg5I+DEn0QaocB5VzON/ggb8bOt9Q" "3VTvGyvSv2luwxmIK3B81nUGPnv/Aw2OX8l7ywkSateVuvFPva9KU+YdG/TenZ4+eC9kEvwy" "8BnwHirn/xa134kvm9q3H27HvwLv/SQOLr0wC07mFcH9iOfBk50v7s1AKDh3TBE0yI2Yaz6o" "TVeBgzqu1JCdmo0oLRXlq1Iq76ADKSyhgDsbivakQdH+JMgtXwC5NRMg3x0LBZ4YyHPFQL4n" "DF9H4xkFpY0jYE9jPINDwEOCBeGxt3W0FoHjgAQHuQ8BDeFADjbH8bOARpwGiQWPaBs4TBE4" "KugZYcLPbQSVUIYIwwNBUtUaAtUImarWIKjpjICarlHw2P/lfV/C410ND1G6MgAiIaI27vpO" "m8vNu663EBIPJDgEPDjzqL1ndWBJeDgBws6DSlcnbxi5x1Vb5mHCg/MPOQPinDanfVcq7/g3" "GzjO+t734XNdrYCHOfPB8LABpFu+J+DBqrEujbIBhOFhAcRZuiKAkBRACB5fCxAChwQIu44B" "AML3gvgApMovQBREIlyVhvuo4O6r0KqD3Hkl4CEdSJ0oW8XUCZDE4nMsOpBYhEgcDQzWITjc" "BwVA3BY8RkmAMDg8+1ijPfS8B8Z6ylAEjxKZfVD5qhTG16muKydA8NmF7qOuiMtXGh4sBY+d" "fD4vu64mEUBQL6AmI0BeRIC8hADR4KgXOYjIPmTpCt9neEiAvCbhocAhzhTOPhRASFO96EAa" "DIB4t/kAZFYDOpGGLQMC5M16CyDzvJsRIOsFPDzCdcz1IjTc69BxrIUlXgRHezYculgJPQ/6" "4NGHb8FHn34EH+GH9PvoOMhBEDjoN2z127QqVSnHQXdNqFIVt+H6yTdMcJihuOk4Buqk4k22" "Zy/Br58cA79enqidBZWhzFZfFYqrr1Huoaa/zStjqVuqz+2F/jFToG/xBjhZtlfnEupD3rMh" "iZ0HnbxtNnEH9LyxBC4+/6Ze56H2R6m9UcqNqfdNaJDjsK0j2VOKv4mLLitqd6W214KSLMjf" "vw2Kji2GvBMvQo5rBOz0EChiWASPPHeEFL7vHo5QiYKShhh0ICPYgZB2t44S0EDXQa8JKuw8" "EBwshASVr8h1HGyLYxE0yHFw9sEOJFZkHs1RCIQYlnAckXyzoHpmB0LPLZYDOd4WicCIlAAJ" "Z4CcQLDUdERDXVcseHri4LH/u+EDCY93dXAuOq4sgNBJmce3NDzszoP0d3WPZN4hSlffOing" "od2HWllSe5dbdv++Rt7xYboPKmWh+6Dcg5zHdx2huc4+NEAu+U6bm8F5jQLHhYHXtWvn0afL" "Vj9yzHvwxl33aRmc9+jsw8pAfPMPBRByHz9zLEwkcIjyVassXTVaAJElLAEPry5fETy0A7HN" "fkgn4g8gdWb77nEIptUlJ8oZHOEIlTCP6UIs56FFcyA081F7RIKD2nhFiE4zIDEMEYSHi3QI" "3YYECJWu3EIjUCM1QBAYCBQKzscSQOoJHvRMANkt5Falq1IZnBfDeITFBE+J3X1QKYvyDxe5" "jwIJDiECyXMkMzSv3ynmPuqt8tVks3xFZSvUKzrzEK6DAKJkASTFBg7uvKoXEm5DiCCi3AcB" "ZEZDgpZyICSGBQEE3QM7D5QoXW2QJwFElLEIIPO9AiIEDwLJxtYUqLh6Em68ix/6HzyAX32C" "H/TUsfSrDznoPt3by+UZVb83S1UUGpulKrOjyu/Q34e/gi/e+iV80dQ9YDD+5ekL8NVHH/vt" "ptJ3iV+7Ce/c67fBw3Qc6opY+jkIGPQzqvvNKcCnn5fC/ZNHyuHMrBVw/vWFUFlUostKanL6" "/KQZDJAbsS/CgeJd/N6R3AK48NxM2+oOcykhwYJAZC4zdO6worxDDNqVCXCUlkJuUQFsSZsP" "q7a/AGtyYmB1XiCsyguGFfnBsKZgCCoQ1hYEw/riobB+VwBs2x8EqYfDIOdEOOTVDodCdyTs" "8kaz6xAQGSNFz/EsW+7RFKtLVwQPciEi94g1SlixnH+oDESUr0QZq6LNcCIOeAhwRDA8CBx0" "EjxOdsWAuzsOXF0jwHtqggKIVbZicLjfFfd8qMAc33cODZrw+FvXIy5bKedBLsSa9RBuQ0+b" "M0Bu252HKl2ddN73cXVAeCiAWO26Qvbc4+vv+yAHooYELSn30Wu5D0fpyg4OAyCq88pYmmhu" "2yVgKIAQOJQDMe//GKxLWPTs4VMNDqoAPaDOZc8/0IEE4XOQBEkInuQ8Ql013H0V4j7B2Ucw" "ry45ytBgB+Kx4KGgEek+xtlHJGq4y8o9yH2QOESnwUEGiBA5kLg6AZARrgOo/RIi6D5Q5Dps" "APGBh9A4BMg4BMg4d4kQla8kPBRAnvXsEmKIFOGzAIjpQJ6Tep6VBy948hgaz0vRMzmQyd5s" "IzjP5LLVqzLveFmVrVCvI2Ss/MNyIFO8qVy6UuWr6XTLIO288qYwPEjCgSQa0EjQ2cds7zad" "gYjXW3Xpyixbkeax1sP8+vU685iDzmPvxaNw8RdX4P3P/ss2YEcfvFSGUXMK5Diozk+BsRr8" "o9ZV854NPb+BH+6/WroNfv32L+Hjvgvw8cpk+GTuRvjtrz+CLy9dh4+eGssfyh9HvwK/f+9D" "sbn2yk34bE0qfPL6Mv4afc9n5y7D5w2d/JpzCvw7GUqLt8C7x93i1sAbt+G/Il/U30Nf4xv9" "Ll6BD8NfgPenr4R3Js3mr91PzGF3RN1g6oIkKlH1zlwGt0a8zGDgMNtYTnhu4hvw7n/ib8vL" "NvAzgaRr6kJ4OHishoG/1R0EEvV3WQsPd1urP+RsB0EktygD1qW8AfM3j4VpawNgyprH4fW1" "P4XX8ZyC57T1P4M31j8B09f9DGZufBze3PQEzNz0nzBn2+OwKPkJWJoyGFZmDIbVWYNhTXYA" "rMkNgM1FwZCyPwxyj8dCqSeeQXKAnUg87G0W5aqDzTEyMBcB+qH2EQwQ4UAsgJDrKG+LYWgI" "xdgAQk6ES1ZUvmoJR1AMZ1UxUMIYJlS6qu2MYefhRni4ukZCfc84eOz/8X5gK12ZZSsVnv+t" "9x1HcC7nPdzCeajMQ4XmOveovSfdhgUP5UBMgKhJcwse1/S2XTXzoSbOzXZdMSx4SbbsOvMP" "EZh/z1a+EutKflArhwZr+3wAQoG5rXxVa4XnCh52cDhnPto1QH4qt+2qtl0BkGYWgYNciChh" "WevbVXA+REJETZ5bZSu31b7rdmn3oXIPzj5oiNB10gcg5EIUPEhUtiJ4DK7YB6E15QyPKHcF" "a7gCiASHFsGkVpWwFEBo1xXB4yDES4CQ8xhhBOcED1+A7JHlK+k+qIzltjuPZ/C15T6K7ZIA" "mUQZSH0Bl66el+CwIKIAkiudB8LDsxPBkQMverMZHi97RRnLAkimFZorgLD7sEpYBA8CxZQG" "AQwFDyHhPAgeM7xJWrMaEm3OQwBkC4NDwYPOOXxxlAUOciBzJEDIeSxE55HcuRNuvn8D3vv0" "V/DR55/CF599Dh//5jP+DZ46iVS+QbV9KlspcFCpygSHCsdVxsEdVfLD/BNPG3yaWcZQ+E1j" "F/z27Xfho6iX4Tcl5fC7dz9ggHw6ZTn898ef8Hv0ZwgYn3k7+Pu++uV78PnaNP57dMcUguFX" "EZPhg+wy+LC7j0NwAguvOUGofDB5Pjy6eQsenrvIAKFw/EL5cbiyJgneD30OTqMbp/8mtTGW" "PuibF61lOOwvKta7mlSb6dlnpzNAjiWk6OG3A1k7+X3fDbfWdltz55O/JYjU3ppfkgfrts+C" "mRsiYeraJ2AqAmLa+p+gHufXb2z8OcLiSZiBImjM2vITmL3pJzB363/C7I1PCG0ZBHM2/xTm" "bPkxzN3yU5i39eeon8GCBAJLAKxKD4ZVGUGwNgudS9YQ2Jg/GNIOhMCukwiRpngjOEdYGCWs" "cnQo5QgTVbYy4VHRFs3Q0PmHlOk+VPmKXp/E76/tiGV41HWi++iMB8+p0QiQMQgQ03nUC4AQ" "OJTUrMe3G34pJJ3H37nfgr+tfQh/Uy2cx9/U9IuylQEPBkjdPYaG5T7ExLm+3+OkuefKCMyl" "C+HNujUWQHzbdlXpytd92ByHBAiBgwDyg7ozqF6GCD2rstV/1Fn6SV2fUbaSzsO861wPD9rn" "PcwSlgkQAsfP3W0aHE+6BDjUOcgBD3+rS0yAWC5ELE8keBA4aOeVc3BQAYQh4q7mEpYCiHIf" "w12VEFmnzqOy++oIAgWh4S6HGLcM0QkiEiCxCiDkPtwIENYBBki8UbpS8Bgtc4/RGh4oN5Wu" "yuzBuU/ZqkQODaqp80LhPuqL4DkPqUDDQ0PEI589BI886Tx2Iizk3AdnINkaHlTCUg6EYaEA" "4s0Q4bnUFFYqTGtIlW4jhZ+nN9Iq9xTWTJuSWbPQkRBE5qAbmdOQxACZU49qEJqLr+c2bGHR" "nR/zaW27xypfketYht/jvY0f7J9Zt+998ulHnC9cuXxFl2HIeVDGQW2s5vAfgcPsqnKuGuGW" "2deWCoCQ67h8g53F7z/9DL4oParhokSlLArGP1m1nZ0K/UwqD/my7Bh8+uwc+PX4mQyGhzdu" "wjtt3ZyBfJizW6xtl26EgvG3mtoZKASO++3d8O5zc+CX89ZzZ9XFHfnQsy0d6jJ2colJt85K" "l3E9ZjLsyfedWTi5ajP/nOQ49mfmMEgIKASQb1o3ovZZFezKE1Phcn1IUXEebMlYALM2h8D0" "DYMRHD9HSDzO4Ji2/kmYjmB4c+vjMHvbYJi1dTDMTkAoJD4Fc7cNgoWJT8LchCdhftLP8fnn" "fC7eLpX8FCxKegrPQfy8ZPsgWJE+BAESCCvThyFMhsHKHQGwOg1dSvpQ1GDWxpwA2LEvBMrq" "ECCN8dy2S5nHkabhcvYjisUtvJR1SLfBbbuy++p463BWdctwUbZiRQhwIDQYHKp0dXoseBEe" "DXg+Zg4LKoBw15URnJtrSsSCxLe5bPXXJ/qNslU/Q0R3Whnw+LbUd/D1P8rWXX/w+G7ddQ2P" "77J8y1bW1LlVtvIdFnQsSqyR4bkM0IXrOAM/dPWhzrJoWaJ5z7kJEl/30ekLDwmQJ+oseJgA" "edIlwEHnIF6S2Mwy3Yd/gIjcYyCAOGc/htVUwVOVh9l18KS5W4Tnqn3XBEgkAmS4p5qzj+Ge" "4+J0CQWjK6Huq+G1sm0XIUIA4a6rOtmJZeYfbgMgHgSIZ78oX7EDQYC4Dfehg/PdEh5UuirT" "2cd4N5WsShEQQk6IMDwQHBOlCB4mQDQ45LOARx7D40VvrgGObB2gv2yUsHRoruFhAWRqg7jC" "dpo3DR1GqtaMhjTWzMZU1ptSc7yk7TbNbUyEeU1JDJG56EzmIVAW4nvzUXTOo6tqGzczUGZ5" "N8Bi72ZY05oCOWf2wcNP3oZP5byFyhT6792DY8cruV5PrkOtG6GuKso4CByUGVCGQPmB2VXl" "7w7x31y4yiUo0sfoJH7b0qPDcYIJuQtyIzrj+OBD+ORAFXx6sBp+98mn+p7xr1ytXOJ6t/8+" "A+T9rFL44IQXPjxyEt4vOcwwIWC8k14s9lA1tLLjeO/5uXDrwkX4xZy1cGvTDi6/9SxYC28N" "GcchuNo5pfZOtc5cygDZnZfvAwF6j75GADm6LYXBcTd0IoPk67bakoSTKRHQQOUVZ0BK3npY" "lDAKZm4aBjM3ByAggmHO1iH4/BRM2/CEgMcWdB5bB6EQHtsQHAgFgsYCDQi7lqYiLFKeZGBQ" "OWtpyhBYkobaMQiWZTwJq7OGwrqdwbA2JwjW4ykUCOtyhrIrWZc1CNZn4PekB6AGwWZ8nVIU" "BAXl4bDfFQ373CFwqCECjjRGwzEESgUH6cN5DoScCKslUkOE3MfJ9igJj3gbPMh1EEAaJEQe" "Ux1Xtq6ret9ravVlUeg+/qbuIXyr9oEBkHtyNbuQgoeWvCxKdV35dx4CIAoi/ocF7dPm/ibN" "v6dD8wt61oNLVj4A6WWA2O/56IUf43v/aYDE1oVV1+kDEFW+Muc9qPOKpNp3CRrKeQj3Yd06" "aLoPs4RFzkNoYICo7IPKVLT7inOQOlrbfhxCPQgOT604ESS0fdfmQDQ8qhgcSgogtH3Xyj4k" "PJRk+y7Dw30Y4YEOxEPgEO4j3i3goec+uPNKwGMsay9CY49wHSzhQAgiBA8FEKcD0fkHQkMA" "pIAB8nx9oQYIt+waAHnea8GD9HI9AsQjXMjLnmw9+/Gyx557KE1pUEo34CHu+5iBQJnJNxES" "OHYgMITmoBNRmotfm9uYLIRuZH7jdlQSLGhKZi1C0etFCJTFdKJDUedSBMzypm2Q01cGPe9c" "QGh8DJ98gY7jcwEPyi1okvrIkXI4Wl7OLaj027pzctzcU0W/6ZvgIAApcJgDgKokRSUqggLf" "vXHlJjsOlXOw0E181tTFUPls6gr4/37zhQbI76/f0XkJ5RzvX7/FEOF5jEWb+Wd5dP4SvLtg" "I9y7chXeSsmHh8m5/PNSme3q2mQ4vXAdl6u65q7iP0ehuAKHKlW1zFiiAaKAocpWJkToz5vv" "a6dhPBeVGADZJWY4CoqyIS13LaxNmwwzNgbAG5uDYea2QJi9NQDmJQ2DOYlDESQBDAwBj8dh" "Jp4Ej3noJuaiy1iQMkgDY1GqyD2WpqLrSHuKQUHPy1KHwPK0oeg6BrFWZjzFWp09CNbuHAKb" "8oNgY14gbMkLgs0FwXxuLRDakh/A2poXAAm5eOZY2pI9GHaUDYWio2FQWhUKZScC4aA3XJSu" "WuTZLLuuECrV7bEID5FzEDQYHigqW3lPj4eG3nHQiGrqGQ2P6bKVWlNiLkj0GPebS3iQ8yB4" "UN5BjsM2ZV5zX5eudN5Rd8cWmqtuK2rXVS275pS5CQ8uX52w5j18J86dk+YXRJmq7qI8lc6J" "slWtHSBUwvp3M0CvOW25DgMgP6nptQFELEnsYnCo8NwEiGrfVR1YBA8TIEICHk+6G6UjaRR3" "nbMDEfCg1SUq+yCAMDxqXeJ1nUsPDxIoODhH6b1XHjk8KPOPgOpyCKmpFF1XEiCRWlTGOipC" "dFnCiqo9amQfBAsLIPQcawLEowBygAEykjqvzPDcaN3VAKHQ3E2SLkS17SIonnaV+Clfldjg" "YTmQAulARNeVAsgL+B5Llq50+cojRCUsJ0Cslt0szj3IeUyVAJlqAETAI4PhocAxqykd5jZl" "sObjM2lBYzosxNcLECSkhc2prCUtaVIpQgiRpc3btZY3iTPtVAnU3W6Btz96Gz7/Ej/cP/8N" "5xz02zp1Jamc4wSCg0JlCs0JKBSQq3vFaacTgcZcp/5Nk+PcVSUzji+bT/kfAHzwFnxU4WKQ" "0XsKGk7Rn6F/j6BlTo2rdtwH3hZ2HQyV0Ofgcks7Oyea51BrQshZOS9nUuWlP/XiJbX/iTbh" "8v4p2mYrAVKIX0/duQ7W73gd5m6LgDc3hyAghqIQGglDGR5zE4PwORDmJw+DBdsDECYBMDth" "EJ6iVDU3cTDM3z4YFqYO4tIUuY1laYNYBIllGYNgeeZg1FDWsowhsAJdxarMQRyqkwgea3cO" "go35Q2FLUSAkFIVAQmEonkGQtCsIEouDUYGQuCsAkncNhbSSYbC9KACSiodAcuFg1FBIysev" "5w2FhLxBkFzwFGTtGwaFR0OguCIE9tSEoDsJh+PoOk50xMBJhEVt90iWgocIzceI0hXCgxxI" "0+lRAiDUZfW3anDQmDbXLbr1j7hsxa6j5h6fFJyLzisDIBIef1tnla/+vvY2A0SvKlEAUTuv" "ECDkOv6x7hpLAeT/xWeCx7+cvGIDiPOKWhWYc+mKwXHRBpDvS4Doez5q+9h5iAzkjN5zpYJz" "J0AIHnTHh5B9066ePDcAoi6MUp1XjzM42nQJ6yl3qx0ifgHSJLMPr2PnldW2qwASJMGhOq80" "NNwiB+FAvbaK4UGbd0XuUaUBEq4BYsGDFF13DF1GBQNEQSPOfZSf49xHGByx7kPsPuIQHiO4" "bGUHCINDrSzxKAdi77wSIJH5R61wH8+4BUAIGE73MdGAxyRvsS5fETQUPDRAZOlKA4RCcwMg" "7EI4QLcAwuCQ8FAAmdaYBdMbMlhvNGYiODIRGhkwuykTZjcLaMxrzoQFzVmwsCWbtag5Gxa3" "5MCS1mxY2pKBz6jWHbAUtaItg7W8NY21qjUDVrWko/C5LQXWd2bB0et1cPv9O/DpF8IdEEDo" "7Dt3Vncg0YS0y10L3ibVWdWrr4pV4BhoV5XpOJxDgOpe8IEmx9W6ETUASH8PAcSEiHqmf0dd" "yqRWkRA4qL2YchhzZTr9N1CnmLpbQ4FDZR1mmP2ngsO53NDcVFtUWAQ7i9NhY/osWJg0AoER" "xOWqmZsDRckqUYJi2zB4MwEhgiCZv11AhLQwdShDgzIQKl/NS36SHQi5jsWp6DzSB7PrWJH+" "JMODOrAIGHSuzB4qu7GGCHDkDIV1uaiCwbAhfzBsRhgwLEqDWallgZBSEgIppUH4HAxpu4Mg" "Hd/bURqon1mlw8R7JQGQhpBJKUYVDYE0VGZZAOQeCmGHsrcmCl0JAWQE1HTHMjzc3fEMDxMg" "5EAae0YSQN6xla7UckRxOdRbQobz+Gt0GQogatrczD2U8xDu457uuDJnPr6ufGXmHs47znnL" "bq3ovnKuKhEDgwIY3+dy1QWrbGU4kB/h95EDsQBy2nbHuRmgm/BQK0sUOJT7UABRwLCGB8UM" "iAkPZ/mKNMTdZNu8K7KPRoaHXl2iHYe686MOfnq0nK+uVavb2X2o2Q/3CS5lhblVCavKch46" "PK+SGchxrSj3ce6+InDEICyiPEc1PPjE17GeYwiKcnYdSiNYFkDiGSD7YZRnnwaHEx7j6vdy" "15VwIWUcnLML8djdx8T6MpmFIDykA1HZh1W6EjK7sBRAJntlBuLJYWAQRCjvsIYHhQMheLzq" "FfCYQmLXYcHjjcZshEYOKotF8JjTksngmN+SBfMbBTwW4zOBY1nrTtaK9p2wsg3P1hw8s2E1" "AmVNWw6sac+CtaSOTH5e35kJK9szIbW7FC5/eJ3bcr+kfAHBQSWr2/fuciBO4TiDAyGiros1" "W3LVokMCh3Id5nWxau2I6TicQ4AKGuauKnOWQw37qclxApITHiSCjbpHXE2OqyFAtTqdfl61" "UkVdB2uuCDHB8cdDouSbXYjhOlLyNsPixPEwZ2sYzNwYBG+oshVChGAxe9sQBgmVseYlBSA0" "hBuZnxwIC1PQiaQIN7IobQiC5Cl2I+RAFqUI57Fkx5PsPCyADJUQGcIAWZUzBNbkDGZwrM8L" "YG1A97GxYAhsKhwEW9BZJJHLKA1haOzYEwppe4M4SE/fGwxZe0NY2ftCIXt/MOSgsvcHsuvI" "3heErwMhcy8pQLzG79u5Nwyy9uCf2RsKuQdDoeAIOpPqcDjZis7j1AQEx9OocTo89/aMgoZT" "8QIg5roSfasgw0OUrb7lesjgUPD4Fq9nfyC7ru7bsw/ZuvttR7uuvhDKgIe1KPGaLftg92FM" "muv7zREg4qZBOzxsm3YdpSvlPmhoUIXnlnqtfVcGPJQDUTcMmnkH3+9R02krX/3MmDRXruMJ" "WbryBYi9dVfvu5KDg0M9ooQ1rK7Bz9ZdCyCs2ho9/6EcCF8chZAQbby+m3cJIBGeagMg1Ub2" "cUw4D3YaR7mdN9ooXZHzIBciTikDICPdlkZ59jM8xtXvZ43V5at9hvsQABnvKmMxSDzKfZQ6" "JAAy0Va6KrIBxMw+TAfC4bk7RwfnCiDkPl72ZtqcxxQEzFSpKehATIDMatqJjiMH5qDTIM1H" "l2G6jiUIjOVtuayVHfmwqj0fgZGHwMiFdR2kfFiP54aunayNndnsNtZ35sAWBI3rXht8/Pmv" "Oef44svP4Tdf/QY+/uxT6DzVza2rFI6bLbnqEieVc9Bv8+Y94+aiQ2fOMdDOKnUq1+EcAjSn" "x1XXFr1HrkUBhP4O+poqV5mug35GBQ+CHjkOCsnVtLeaw1A5x58KDxWEf537EAsPiyF/Vxas" "TJ0KMzYEwYyNwfCGPCkwfxPdx9yEQC5fzd4WxJqXGMSOQ5yBCA0BENLi1ABYuiOAz8WpCJIk" "EZJTzkEOhEtV6eKZSlcED1GyGipLVkMkQIZIeATARoTH5qKnYBu6hsITw6D6VCTkHAkU4Ngf" "ChkIgswDwQIch0LZVew8GMzKOxwMuYcDIe9QEOQfCcKvUcgeiq4jglV8LByhEQb5h8Mh90A4" "AgX//O4QyEewFBwKh4Mn4sDVMZ4DdJr/qD81ErynouEx3rQrQ3PlPggeVLL6Gzc5jocsBQ6C" "iChf9fsE57p1V7bqstRSRMflUHQ1rShZ3dCDggwPhIoCiLrbQ4ng8a+1l/zCwzf3uODXefjM" "fdC8h6tPQ4OGBc2Nu855D9+J8w7fgUGZeVgAsUpWNgfiWJioNu+aE+eB+F6g2yNFoblL3H3u" "qrWCc3If6ESGVB2HYSeOi9kPuXWXurDIeZjugwAS4an2AQgBQ7kPy4EcdQBEaISSBIgJjz8M" "IGUSIGUwwb0bxtMQoadEzn6U2MCh9Ixs2xXhuRMgCI76Ah94aPchg/MXG3IQGjREaAFEOQ+S" "gge5j+kNWQyOGU1ZCI9shEYOzG3ZCQvQYZAW4TOJwLFUQmN1RwFrbVcRa0NXIWzqLkIVsLb2" "7oKtp4pgS3chbDldAAmnCqDg/GG4/v4tBoa6qpVcx73+O2IZIIKDwnGa7yBwUEsuffjSbij6" "DZ4+kFVATkN4ynGonMMZkKtSlXPtiJK/RYeqXKUWGZIIGgQXKlGR46DXBCYCjMo5qONLlavI" "GalyFQX9BA61doTacs2cw3mvxv/mOthvvN6Vbu4rKdTgKCzKh9S8BJi/dRxCYyhCIwimrg2A" "6euHCZhsGgqztwbCLITHm5uC0X0gTBJVgB7AACHHIZxHECxJDYLlaQgQBAqF4kvTgmH5jsHs" "PJbveAqh8RQ7D4IHPYvcY5ANIOtyB7OobEXOQ8BjMGwtHIxwCITjXQHQdmME1J0Nh5zDYZCB" "kMg9GIHPIQyOvMMIgHIEADoJAkXB0RBW4bFgKDwaBruOR0BZ9XDYfSKKRc9lVVFQenw4lFSE" "w66j4VCGYCk5Fg1Fh6Og6EAkFO5H0BwcDodrR0Bt2yhwd0ZKB+K805xKWJ63JDAIHo+ETgoX" "Qu7j72se+g/Nbe26jq4rKXWvuSpZfbdOzHooeCj9q0sB5JIGiAaHsSxRDA1eNFzHBVvpiuGh" "AdIrWnbr+jRA1LwHd2DpjivpPFxdvHWXRK9/VtvFEvuuOnxadp0AGexq59yDJFp3W3ULr9p1" "pYJzfwAR3VYWQCxJcOBziOy+IonQ/KQPPMzgnKDhbN+l8hXDQwKESlVRnnI+RenqqA9ARroF" "POLrDzvgcZABYoeG3X2Mq9/tA5Dx9Vbn1dP4LMpXu2zdVwSNSV4CSb7P/Ic9OM+zz34gQAgc" "Aho5EiRZ6D4seCiATEPQkPN4ozmLy1Z2eOQiNPJgcWsuLEV3QVrWnsfwWNNZCBs6ihEaxbDp" "VAlrc88u2ILa1lMCifg69cxuSD5dAsmndkH+uSPgudMBv/rqU/zg/Qq++Oq3/MFNv91TBxX9" "du6tr2dwqHDcBId5AyCBg+cqjC256m7wgbbkmm5joIuczHIV/VzKURBYyG3Qn6HvUeChZ5V1" "EDxUzkGOg5wSdYcRFCnnINeh9ktZSwlLv/Ye8D85MHdc4bqzIBs2ZcyF6WsjGBhvrA+EaWuD" "UEMRJoFcwiJgUPmKXAjlIQQPciOzE4ZyB9a8ZAEOzj9SghgcS/B5WeowWLFjGENkuZzlWJYe" "wG6DnQd3XA3RwTlPoWcjPHYG6PLVhvxhwn0UBLD7SNkzFI60B0JFRxD03nsD+u7NgL3uWHQf" "6DbQOSh4kONgeDA00GlUhEBxZSiUVEUiLKJhz8lo2FsTw9pXGwv762JQUbC/JhoOnhyOimXX" "caB6BOyvwu+rjIE9FdEIlWjYhS6lCB1MaXkgPKbWlKhLoVjuty1o1FpdV9+SNwvyzqtaOzx0" "u648/7H2jq185TvzcdPKPFRAXnPNByD/7DLdxxUf5/G92gv+y1Z+AKIHBg2AmIG5BofrtF+A" "kBRAWAyQDp/cwyxdCWC02sBhA4ixOJHv/TABggry1Nu37kop5xEqASImzmts8x/KdTBAPFU+" "nVf2/MPuPggc0fVHDXgc9XEfCiCqfDXKJeAx2k3yDxCRfQiAsOsggKDTIHgogJDzIIBoB0LB" "uSxfETRE9mEHiD94cOuuN1e07yI0XmnYKaDRIF/XDwAQhMv0Jn/OI5fBsawtn7WyvQBWdRQy" "OBgenbtgc3cpOoxS2Na7GxJ79yAs9kBS314Ex37UXki/dAiyzx6Cypv1cP3DO/Dl736D4PgK" "vvzvr/CD/0POBwgYVKZicBilqq8Dh9qSa+YcZrnKdB3+Vqv721lFroP+XvOyJnIT9G/SnyXX" "QX+e/l369+jfoZMgo1wHuSMK9SnnIBdFXWMEj4PyHo2/VHfVQLf/KXjkF+fD9p2bYfG2F2DK" "6hCYsp5WkAxl5/H6ugCYKuHBAfqmYBZ3X20bxl1XVMLiTiwKzrcHcBZCJSwuXW0PZogQLKiM" "tSIrAOGBAMkehoAQJ8GESleUf5Dr4G4rCsx3BmhwUOlqU+Ew2Fw8BLbsGsoOZG99INSdC4aa" "0xFw6t5EuPDWfDjZ9Qxk7B+GzoSgEcHwIIgo50Hw2FUhHMeeEwgChMO+ujjY7xoBB1wCHgdc" "CA7XcDjkjoKj7nipUaxy10gor4uHIwiagwiefVXhCJRQOFAZhgDxqtsFf8EOhJwHl61OPtLl" "q7862c8A8S1XWcG5PfdwrGmvtZeufEJz233mCiBW6YryDwEPX4Bw55XLKl/9wHVe5x628pUR" "nit4/KjWPnWuhwURIEKnWD+t69LlK3YfsnRllrB+7jc4bxsQHgocg6T7MOHh3LprAkSBw5Z9" "+AEIScOjzt55ZQJElK+OOQDidB5CI76hfMUA4YlzUb5yOg+CB4ndhscOECVaXWJmHzo4lwBR" "wbnQwACh8JyGBgkgdAr3kQOvIiBeqRfweNlj5R9TOPMQ8HgDATOjSTiPuQgMgsdCdBqLEBpL" "2gpguQTH6vZCWNspHMfGrhJ0Grs1OFL69rHS+vbDjr6DkHl2P2SdOwCH7jZA31tXeAXJV9IV" "0Af4L/C3dmrNpdKOGgAkF0IXG5nhOH0wK3CYnVXmIKByHP7uHVfPCh4mOJzlKvr76d8hIBCw" "CAgkAhb9WRWU0/ear5XzoHIVwY/CfypXqe4qdYOfv5D8z+06fNzHLlG6WpcyB2auj0d4DIOp" "pDWB8OrqAHhtDT5L98HhOZ5U0iKAzNkm3AiVs6gDi3IP6r4SAbrMPlICWeQ4lqUHwYpMBEZW" "MKzeOZQHAdfmDUNIBMKa3GBUID8rYBAsGBhFgbC1JAC2lQ5DDYWEsgBI3DME1uc+BfXnR0NP" "/3Os7rvj4Mrb66D+zEuQdWgIZB4O4GyjkHKNY+HsOHZVhkNpFZWpBDj21godQCAcREgc8iAU" "3DFwGF1MuRdVPwIqvaPheMMorUrvSKhsoPdj4JhnOBz1hMOxugg4WhsOj/1dw7vGPR8UmL9l" "5B6qdPVQAkR0X1kQuevYb2XKEZ4bACH3oWY+VN5BZSzTfTgBIu76cGYf52XXlf/gXANkgPD8" "R46uK+E+EBjuXgbIj92+ALGCc9G661O+kgB5yt3+teG5ffLcBIjdgThLVzrzwGdz/kPvvMKT" "3QcH5ie/sfOK9TUAUfBQDsQJD2d4PtJtB4iVg+z9BoCo6fMy3+BcynIfRRogKv/wBYgAx4s2" "gJD7EADhyXOvHSBTyXk07oSZ3p0cmM9BcMxDgMxvy0NwCC1rK0R4FMPqziJ2HASOzafKYCvC" "I6FvD2zv3cvg2HHmAELjIGSfOQzZ5w9DzoVDUHO7GX7x2Tvw6X9/qT/A6YP76rXLDAwqU6mL" "nNQcxw15J4c/cJj3jg90N4cTHl9377jelCu34VIpSrkO+hnIHdF79HX6d+j76d+nU82C0M9B" "30flKnJRVK4i16G6q5TrUDmHs2T1FwGIbNMlZeenwdKtL8LrK8Lh1RXoNlYPgddXBcArDJBA" "BgqXsiRAOAfZSKF5CMODQ3SZgVDZiuBBLmRxWpAIzPFcnkUKRHggMHLDYF1+KGzMD4H1BSGw" "iQYAi8Jha3EYbClVCoFtJUECFLuHQfLeIEg5EAgp+4P5TD04jEV7sA42RsPZt15hgHTdHQk3" "3kmCyo6nIfvwUMg7FoRuIwhKqyPYYRyuHwNHG5+GiuZJUNUyGY63PKfPyuZnoaJpAlQ0joNj" "DaP55kESPR9vGANVjaOhpm0snGwdBdXN8XCiZSSeI6C6IRxO4M9Q3RAJla5gciAq83gbvlX3" "Cxs8/qbmkV6SaJauVPnKPm1+W+ce6m4P0Wl10xgavK5LVwSPfzSA8c8uId/8w1G+0gA5z87j" "+36Cc//Zh5AoX/VakuvaFUB+6u4xHMhpCZBTAhwSJE6API5gMAFCJSyRebTqgUF/8FBX1vLQ" "oASILfuwBehWiE7w4OyD23ddEIYSixMtgDA0FEBkcB6u84/jEFVfZStfmQBR7bp2gBjZh8u3" "fCUGB+0AGYPgUGJwePdpaKjTBIgIz+0AmVRfYgMI5R/P1xfbuq/MDGSykX2YAGFoGABhB+KV" "0+ZG5xW5D5V7KHgsaM+Hpa0FomyF4FjXtQvWdyM4unfDFoRHQs8eSO5xgAOhsfNcOey8fAyK" "LxyDM+9cgY++/Bx++zv8AP+t+ACnTIECcYKGs6OKSj/0W7wKx81ZDic4nLcB0mmuWfd3qROB" "Q4Xk/spVKsMgcKi2YIIX/cwEETrV9bL089HfQyE6vSYQ0iCgutRJZR0ED3MFyV9srsNPGy/B" "Y0duAszZOAEmLw+Cl1cNQtcxlCHy6upghgfBZMY6AY9p60QeQhAhcAh4iJIWtfISPFiUeaSH" "wNKMIFhCZaocdBsIjZU5CIyiUNhQGApbdwXD5sIISNodCQml4ZBYFgHJe8IgaV8kbD8QCamH" "oiD1cDikHQqGHYfCIKM8DLKOhUB2ZQjkVAbhKZR2EF1MxhBovvwsnH34Opx5OB9O354NR+qf" "BW/fm9B6fhG0nJuP5zLourIeeq5thJ6rm/HcAr03N0HfzQ2s01fx/cubxHllA5y6vBZ6L6+D" "Pvwzp6+tge7Ly6Hr8iLovrgQ2s7OAG/3S+DqnAAnWuNQkVBLCxebghAoQ+AxDtApMK95y+Y6" "xJzHQw0PHZpL2e/3uK3lnPUQJSshdc+Hmjp3QsOuSxoc5D64+8rsunJd9DtxruDBE+cSHv9e" "d1Zv2jVlLkykAN0ODLnrqs4CiJl5mN1XOjTXV9VaCxP5mloFDWMHllXGQsfh8crSVYPt5kEF" "jWC3m8HhdCE8JCjXt9PMhy0DkXMfKvtQnVd291EhA3QrOFdlK3twfpSnzrmEhecodCijPIfl" "7MchAyBqWeI+WweWch4T6mUZS60tIRfiKrOVrqzso9TWtsvwcFvug5yIuTiR4eHNF5mHLF9R" "UK7yDpGBZMuyVRZPm6v7PqbI7GM6fs+bDbnSfeQxPBah41jaXgwrOgphZZcoWW1CcGw+tQe2" "odtIPL0Xks/sgzR0GpnnjkDW+XLIPV8BBReOQ8nlKqi+1QLvfPkBfPV768P8i999xR/MBA81" "Na6245plKtVVpcJxf6Uq03F83U2AKp/w111F4FDDfupucXIR9DOS1M+hylkKLvRzqpkOdUc5" "5RwKHGqS3BmSO1tzbVtu/ww5B60j4YnyXeKkAcGErBUwdVUcvL4yhDVldRC8tmKIAMgKkX8Q" "NFiyA4tAMntrsG7b5dbd5EBYlBYCC1ODWcszCRZhsDwbwZETii4jDNYWhMJmBAWJgJG8ZziD" "Ink/QuQAPh8aDulHo1HDIQuVUzkcCk7GQe7JWMiuChf3g1RHQnHdSDjS/Byc7JkGjecXQsel" "lXDYPRd2FI2DPdUTYPeJOCg4MBncXUvg9M010Hd7OZy7uw7O39sIF+9vhYv3Noizfxtc7k+C" "q/eS4Fp/Mly5txUu9QtdvruFX1++g993NwEu3U2BK3eT8XUS6+LdreLrdzfhuQbO3VyMoJkO" "rb2TwNM2Ah0IOQ/XW/BXtVbuodyHKFeJjqtv43saII6WXWtZ4h3pRO4IaNTcke26t+R5wzY4" "aALEyj+u+DiPgQFywW/rrs2BaNchnMd/uPo0PL4OIKbM/OMJAyDmziuVeZituyZAxJyHBQ7r" "5kFyHvV695UCiN15ePxmICGyfVcBxBKVsKwMRM1+RMjuK+fwoB0gxxwAMcpXDItDwoG4jugO" "LArOefLcyD8sePgCxCxhWQCxz35MROdBk+bKeShp9zEgQAge/gCi3EeWBIhwH9TCq4NzAyAq" "91jSUQzLOopgdecuWEXdVd2lsLl3H8JjPyRSMN53ANLPHIJshEfehUpW0aXjcPBKDbT/4gJ8" "/NVn+oOdPuw/+vQTzjXMMpXpNtSdHOQE6ANZ3Q9udlYpcJiAUN1V5AIURMxylQkOVa4iIKly" "lXIdZsstwUGBQ10lq4YB6fvoeyiboc4wCvxVuUqtWjdXkPhdie6Axx8DkJIBVpOQ6yjYVQC5" "hTmwOmkmvLIsGIERClNWhcL0tWHw+gp0HSsC4bWVQfDKKhGeEzwoC5m+PpABwlmHBMjcxBDR" "orsjFBajlqaHwarsEFiTF86OY01eGAIjCjYWRcC2MnQaeyIhqWw47DgYBWlHhkPGsSgBjYoY" "yKmIg5yTMZB/IhYK6mKgrH4k7Gt4Bo60vQR1vXOh6eIKaL+2GrpurYXuW+vh1M310HtLqOvK" "WqhqmgMl5a/B7oopUN+zEOGxCs7iB/y5e5sRFolw6R4BA2HwAM/72xAaiXDtYTJcfZDE540H" "Ug+ThPD52sMU1vX721FJ4s+grj9IhKv9Ah5X764QurMKrt1byXrsr2stePhmHv0SIHZwfLuu" "35Z9KPch2nfvCIBIeDjBod2HDNCpdVfBg+42V6Ur/2UrEZqr4Nxv9uE6wxJhubFpV7kOBIU5" "98G5B36dbhxUoTnpZ64eG0C4bVcDxN59pQDyc3cLS5Wv1LZdExhOeAy2ZR8yRHe7vxEenIHU" "1Ql5JDQMiRKWAEgEuhILHNXsPJzwcAIkzm13IOQ8GB4KIG6Cx0HZsivads3SlRMeFjgsgFD7" "7tPcqqvKVmW22Q9eW+Ip1OBgaGg5sg8nQCQ8fPMPy32o7EPBg8pXs3lYMFe6j3yGxwqEyNru" "XbDhVKkMytF5UEB+5iDDI/PcUXQdR6HwYiW6jhNw8l47XPuvfvjyd1+y86APc3INajrcLFPR" "B7G6AdC8d5ygoderS3CYV8manVXOmQ5/K0jo3ycpcJgzHSokJ2AQFNTGXr7YSa4goZ9d5SEE" "GNWWS3MpZrlKheTODisnHJzg+JNdiHIfpUVQXFTE93Wk526HxVtfgVeXh8HLS4NgysowVIjW" "1NWkIG7bnY7wmC4dCGUebyaEMDTmJITC3O1h6DZCYFlGOCxBcCxD17E6NwLWF0ai24jkc+vu" "KNhchvDYi04DoUFKL49lYOysHgFZ1XGQfTwWcmvioaR+PBxseQ6OdrwOJ3rnQAuVjW5thh50" "AWfwt/9zd5KhD3/7P30b37u1CXpvbhAAkeepW+ug++oaOHVtLZy9sx7Oo4u4cE84jUv3BTiE" "trDLuIrvMzweWbr5cDvr+iNx3nqUYukt+Rrfv/GQ/vwaBMhqBoeCx/X+VXDj/mrhQP6q5pFt" "YFA5D98FidJxIEBU9kG5h4KG0D0bPMyuK9uadhWcG7Mf/4avFThsXVc+ALngCM9l2UrBw22B" "44cuh/MgeEiAsAPx6bhSku27cuJcTJt3aAdiznxY7oMA0qRXltgdR4MFDpo291jhuShhGdPn" "MgMJcnl8SldmxxXlHiwJEJF5yNzDc0K4Dg2PalvpiuSvddd/CUuUrpQDofIVaaT3kIaHGhy0" "Mg87PHychwQIORBr9xWVrUqt4NwGEAGOF7wSHlLOzqvJjuDcBIia+zABwq27CBCCCHVe0aQ5" "dV6pjiuCx5quEpF5nCqDbdSWi86D4JFx9jDsvFgO+RePQzGCY98VF3S8fRHe//JD/AAXH+r0" "IU4f1ndu32a3QR/K9AFMH9b9Dx/oPMHpNlTGwXuwvmEQ0N9Mh2rNVfBQroN+Fvp3VJahylUE" "DbU/S4X1ap7D6Tqo3Eahv7pfnbqrCB5q8aFzDYm/afKvA8gfCxFx0VMRDwluy1gH89ZOhJcW" "hzI82H0ocKwSTmQaOpE3N4XDjA2hPDBIk+fUbTU3MQzmpYQjOEJgfnIYLEoLheVZkbAiOwLP" "cFiTPxw2FkfBBtQmdB0Je2Mg6UA0QiMG0spj2GlkVMYiOOIg90Q8FLnGIDQmwOHOV6CqZxZ4" "Ly6HjptboOdeEvTeTYK+e9tRAhpnbm9DKCTAhf5kOHMvESGy1QKIVN+tjXDmzkb8vs0MDQbH" "g212gFB56r5wIFf7t7Cu4dfIcdx8lKwBQqC4/VaqhsftX9Brep/cxxa4gvC4eh+hcX8tA+M6" "OhEBj5Wsx77b9g781UnrRkGCh8g7HvoFiLnn6jtSJkAo/2DXoafN7S2735XZBw8PGq27JjjM" "ZYm8tsTRdfV1E+fqfg/Sf7jozg/f7MNWwtJdV6ds+QcDxLhlUJWtzHXtfD2t24LHk55mdB/N" "1s4rDsmbxakB0qBFpStb6y7lHkZw7g8e5DhMgHDmwQCR3VYIjvB6AyAaHtUaHjbngQCxnMcA" "ANEdV2pwULgOdXL5yrPfFpqP9x4w4LFbz32oifNxsuuKNu+K/KPMyj0ca0tsuYcBDxMgVv5h" "dF815OjJcwUQKlmZAFHlKxocnNmczZ1X2n20FcLKzl0cmpP72IrwIOexHV1H1tlyyL5wFOFR" "AYWXj0PljRa49V+P4NPffsau43/Idfzmc3iAH8LkNq7JVSNUMqIPZQGOd/R2XBWM0we9CscJ" "HAQCfwsPFUC+afGhyjqU61CtuWq9iBryo5Zbeq2mzM1hQHPxoWrLVa5DDQSad5GbQflAUPgm" "gPyhEBF5B5WuUCW5UFiUCxtSF8GUFTHw0pJgeBn16nIBECpXvc7OIwymrw2BmRsjGCCzNkfA" "nC2RMHtrGCzYHokKRYAILd4RBqtyImHlznBYtXM4rM4Lh80lMbAJtbksGhIPDIfUI7EMj/Rj" "8ZB1fCRkIzjyXfFQ7J4AlV3TofbMImi6sgba0U2cvpOI0EBY3EsV0GAJgPTeS4BzdxNZ5xEu" "BJCz9LW7CQwRciRnbm9Ch7IVv54gylUEDJTKOhRMLj9MYJELuXx/EwJlM79/BcFAECFY3Hgr" "TYIjTSpFg+UG/tlrD9YhPNbiuVoChJzHMgbItQf4/HAVPPa9U+/LQcGHLOE8DPfhdCDSeahp" "cydArLxDwMMJECpdqa4rlX1w6crhPJx3fVjOw5o0/wHnIOd49uOHdecdAOnTckKD1pWo+80F" "OIQDMa+rNW8YtKbN5bp2Agd3W7UYU+ctcuK8WZ/OvMMEiLNtN8Dt1fAg52Fv3XXZZj7EPR9i" "UaIAiN15EED8w8MoW7kqfCbP/c1+qOyDsg7SCD4FOChEN8tXpvuwA2Qvl650cF4/0NzHLqN8" "VQIT0W2Iriv/MuGhcw8DHk7nQfIBiFyYSFJzH/OkA1FdV8p9JPTuRXgcgB1nD0H2pUoouFAB" "RZdOQvODPnjvy490UE4f6AQC+mDmuzhu39CbcckFvKvu4/jwV7pMRR/05BTMrirnwkNnucq5" "ikTNdZjw8Neaa5ar6Oejn1NlL07XoWY/yHVQzkHgINehWnPVGhJ1yZPZnjtQUP6H6g8BSGFJ" "vmjT3VUI+UVFsGLbG+w6XlwcxAB5bTmF5mEMEILHa6tDYeqaUJi1KYqhMWtLGMzdFgXzE6Jh" "aVocLEuPhiU7ImFRRjgszkS3kRfLjoO0vigKtu6JhW1741DoOhAamcdHQ2p5HGQcR2jUjYa8" "2lFwoOMl8FxYhtBYD6fwA7/nXgpD4nT/djjTn4LazqWqM3ctgKj3CBwkBsl9BEh/AiqJgXEW" "wXEBzwv49QsEi/tJDIizd9dBz010NVcWQPPF16Hh3Evg7psE7t7nwX36OXCdfhrcPRPwnACe" "vmegqfclaD83DTrOT4e2i9Og9cJU6LxImg49V2bB+dsL4cr9FQiPFZb76F8LN++v4/M6guX6" "wxVw7eEyeOzfz3zAd5uLzOPRgPutFDy+o3XHBxwKHirr0LuuHIG5U2rHlb+y1ff9TJrzRVEK" "HIbjEGWrs7bQnM4fmyWruj5bycosW+lBwbouXbL6ucselj8u23QVNMhtqJOgMQSfSTxp7nEG" "5lZoTgpwN9qdB4rhUVenwWGuLLHAIbfsGtLrSsh5uIX7iKw/wbLD47jecRXrrjTadgeeOlfw" "IHAoqexjDEKE9TWlK+E+9uq1JSY8qOtKdF5Z60ooPFeyZR7sOCx4TMbTyj2sYcGXGneKjit2" "HNkGQKyyFe+/4nXt6QiPDJ46p/KVOfdBA4OrOfvYzaWr5D5RusqUgXnRVRf0vXcNPv/qS3QC" "/607oegDmD6Y6bd6NTWuFhyq5YPCcdjdhnMI8A8Bh9JA7bnkOtQaErNkReUqddGUAoezw4oc" "B8GDylW0LZcurFIlK9VhZbbmOktW/gDyv4XJN64kQXDQmbcrH95cMw4mLhgKkxYGwAsLh7L7" "EOAggODz6nCYtiZcuA10HbPxnJuAjiOZoBEDyzNHwIrMWFiZPQLW5MbChsI4zjjWFUbDenQc" "BI+k/XGQuD8Gth+Og5wTYyC9OhayT4yAXQ3PQvXZhdB8dSN0390KPXfToQd/8z/dj87ifgqc" "RhjQM4Hi7H0JEfl89kEyOw2VfxA8CBbn7iNQ7qeh0tFl7OCyVu+ttdB0fgbUdk+G6o5n4Fj7" "SKhoi0UNh+OdUXCsJY5fV7aOgMr2SFQ4VHaE8lnVFgM1XaOg7tQYBMs48JwaC57uCeDuGgfu" "7lF4jgRPRxzU8U2EUeDpigBXVzR4u0dAM8Kn59LLcLV/Ltx4sARuPliBQgfy43MfwHc8bzEw" "vo1OhGGhXAee5qyHyDus3EO166qsQ68n0VfTipLVP9Vdtc94UHjOl0JdZXBQy+6/1V1GMEg5" "g3J5asdBTqPuvAaG5TTMDisLGmrHlXO+w4JHl57x4AlzlxBPl7s74UlPOzzhEXmHKFu1yOdm" "PeehHYexpsS5osRSvXYdJkB4dYnhPqh9l8Eh4RFsgCOsXg4M4hnuqdFlK5KAhnAdEX66rZTz" "IMcRV19hgaOeXpfzunaSBY7DRlhuheYKHGO9B/Ssh5r3YGh45coSWlNiOA+zVZeen/GW6K4r" "CxrFLAUMXa6ygUO07L7UkMfQ0G6DwnIpnjxvyLItTCRwvNqwQ98ySDuv1MoSXpLYlgvLaCli" "p5j34CFBdB/UcUW5B2Ue5deb4K1P3hXdTv/ze3Yfn33+CX84q84q+hBWGYe6AVB9uOvrY+Vq" "dTPf+DpomOBQHVYD3dWhwGGuIVELDUlqMNAsVynXQT8/dYmpchWBg0pWavmhv0ueBsollPyV" "tP63AHHusyosLISU3G0wbeUYeGbBIHh2/hAEyBB0IEPhleXDhFYFwetrg+GN9WEIjSh2HOw6" "EmNg4XZ0HumxsConnrUmdxSsyx8Fm3aNgcS94yFh7yjYtmckQiMe0o6MhJTDeB4dgU5jPDqO" "Z6Cs4VVwn18K7Te3QsfNZOhBx0AlKnWS6yCA9PUn4rmdIUIi56EgQhIuJIVBQiLHcebeFui8" "uQI852ZC9akX4Xj301DVMw4qO0dBBQKioi1aiJ9jBTjao/Q1tcdaI/nka2o7hkN1Zxyc6BoB" "JztR+L0n8c/SzYPu7jEMj/rO0eDC76nB763tDIO6rkg8ESIdpFCoaw8BN77v7gyH+q4YcSPh" "j898CP/gfqDv87DmO6TjcPVr5/FPdXd1hxW5DTVhLjKP63rCXIDkJperVMnK35S5VbaSAJHg" "0PutXBdt+gFLlKpUlxXpP1zn7J1Wdf7vNLe5DVu3VZdeUULg+JlbgMPmPijrYIhIx+Exy1WO" "kpVx2nZceRptmQcDRHZc2a6p9ahhQTH/YZatNDA8dfKssbkOJRoUjKqv1EODMa7jtns+CB4x" "3mMMjREeU+WyTHXYlnWI8FzsuDJLVqJUtd8Ah+k60G14y4w9V3aAiIWJJTYJgBTrrqvJ6Ehe" "kBdGmfDwF5oL57HTDo/6TL/Ow3ZZVFMm3/ExV27XpX1Xy9uLYG13KbftEkCS+w5CCsKj6FI1" "ND3sg//64mOdP9AHOP2mTx/Kaq26Grwz142o2/vUPMZAZSoTFPRvKDkBYu6wIqm8Y6BpcrVG" "nX5OdS+6ch30deU6aOcWDQPSMkdaI6+yDucNgQQEf+Uqc6L8jyldmaKMw5z1oNZcvna2qIif" "t2asgykrRsCzCwez+3h+QQA6jwB4ZVkgw+PllYHw2poQmLKOAvIQmLMNHci2CJi3PQoWpMbA" "sow4WJU3ClbsjIe1eSNhfeFI2Fo2TsBjzzh0HOgyyp+G7ONPQ2blOMipngSl3pegonsBeC9v" "hrYb26D7TgKcupvGLoOC8VN3k6D33lYGgnAgFiQYJgY8qDxFJ4XpPbcToPMGOozL8+Hk6Rfh" "WNckqOx6Bo52jcdzAut45zNwohNB0jEW4RAvIYLAaI/B19HSdURJsMh7zvE1wwPdRXV7NN93" "fgL/TFV7BD5HIihi+dIour6W4FGDsCCAuDrC8AxleCgJgKC6QliP/eDUO/B3rn7bkKBwHP1G" "yeqODSCiZHVDAKROrSa5gS7jlg0c9rKVMd/huswiaPhzHs71JD90X9Lw4Kyj7ox0HPaSlfM+" "DzVhTqCw1pJYjoPBIQFCetzVyfB4UsGDoIHPDBMJEAGOVhs4rE27zX5bdU3noVwHOw6Xb7tu" "kMetJ81N96HKVuw8JEQi6k9q12HCI8IIzOmM9lRxuYrFSxKPaYCQ89Dg8JT7ZB7UaWWVrITr" "GF1vOQ8z6+BJc8N90NwHSYGEWnaFxKZdGzxo5kM7EBMghmTWYZatOCinSXMDHEKifPWq13If" "at+VuuOcSlcKIJx/0E2C6D6ofEW7rkT2IbquUvsOwd4bHjj33k347KvP9Yc4fWjTBzRlBPTB" "TL+902vlOpzXxyrHYJap/LkNExxmUD5Q3qFadJXzUEN/ZsmKfj4ChOk6zNZcgh+F5F6vV7sO" "BQ7nDYEDDQWa7uAPdRh/qAsRFz6JwcCCwp2wKW05vLw4isExcVEATELX8RLCg8JyCs7Jebyy" "JhjhESLhEQGzEsJZc1IiYHFaNKzMjoUVuTEIkXjYUIRuY/d42H5wAiv58Hh0HRMg9+QkKHa9" "Cgea5sKJ3lXQei0Jum7vQFBkIDB2sE7fJ4CInENnGv1p0PcglUUwoffP3t+Br3fw1+g9at9t" "ub4S3BfehOrelxEWz0IFAoJEz8e6J2h4CIBMYIBUd5ITQYi0xkvnEcfQEPAYzvCobI2AypZI" "qGqL0iJ4WIqUwBiO8IhFWMRADTuOMHYd5DTqugQwTIB4usI1SB77btMjdhxcviJ4OIJyggev" "JzG6rDjrcN3WIbk1WX5L5B11/tayX5OuQ7gNG0A0OC7Cv7kuwPfcsnxVe5ZLVj90X9DwIPFk" "ufuM7LQ6x91W/+4zEHha7rM6LQHSpfdasahMxQDplkOBonzFMx1UsmJotOhyFb1nB0cr77vy" "D44GbtMd6mlm10FtugoeKixX7bq0bfeb4CFuFrSXr7TrMPIOdVqrSirYhUR7LHgQMGjLrihX" "KQdilK1spSt0HPWH7HlHvVW6IniMldAgTajfp6FhwmN8vZV1fD08Cn1mPUx42CU6rkzX8VKj" "Va5S0NDP6DimyPvNVemKAEKXRdEVtbPpYqhWdCDtOzk8p11XtOcqoVcMC1bd7YCHH/1SfIj/" "n//DJ31Q0wczwUOVrOhDm37zd64cUfmGedufeYWsU+pWP6fzMMtWKu8w91iZLboEB/P2P3U3" "uvqaeckTrVGhkJzuHqGsQy0//LodVuYHvAKGEyB/DhdiQoQAQivY1yS9Ca8tQ3jMD4LnlhA8" "hsHkpQFiQHB1oFhPsjYIpq4P5qB8diLCIzEUZm4Pg7mpkRyUL98ZjYqClXlRsLooFjaXxrHj" "SDw4BlIRHjsqnoVdnlfg2KnFcLJ3A7Rfz8QP/Azo7c9C7UQQZMOZhznyRCA8zIIzDzLh3AN6" "Toez8vX5B/L9R9lw4WE2u5LGK8vAc3EOQuNVhMRzUN45Ecq7BDQIFAoiFaeeZhdS2TFewAPd" "CMGjqnusfj7ePhKOtcZAeXMkHG4MhSPNoVDeFAYVzRG6fFXVGcXuo7ojCoERzdA40SngcbIj" "HKpag+B4SzA+hzI4CCJ0mg5EQcPTYemx77jsXVbfqbPLDMrFOhK5HJHvML9hyzr8heW0jv1f" "Xdfh39xqzuOShggF5TrvcLgPn7zDyDzsIXmv39KVAMdpnwFB0W3Vqdt0nzBKV4/L8tVPXcZ9" "5tJxmF1WBAx1cmjusQJzf5kHz3l4vBZADNdB0LBkla9C8LUuW3GHlVm+sgDinDIngBA8or3V" "DA+154ohIt2HX4CowNwj1pRwxxVdUUvlK3Qh5DqU8xjt3a8dyLiG/QZADMdBz+g6WJ6SgeFh" "ZB/20LyQ8w+a+yBp19FQICVyDwUQggfJ6TrUswUPCyAkAgiVr+iGwYVtObC4bacOz7f0lHLZ" "iibKf/3lJ2K2Q5aO6IP3wuVLGh6qBVa15Tp3VSnH4S/T+EPhoa6YdbbpOp2HAoQa+KPcQ7UO" "m9PkBBRyHXQtLs10OEPyge7r+GPWrv8p8CguLeEBQfp7CB7Lt06DV5ZGwguLQ+DlpSHw4rIg" "LlnRWvbX1gTxRt3X1gXC1I0hDI95iZEwKwkBkhoB89LQeWRGcHfV8rxoWF0QA2sKY2FD6QgG" "x9aD8ZB0eATkHH8eDrfNA9eZDdByZTt0ETjuZyAIcuDM/VxxPrR07q10Ps8+ymARLM7y17Lw" "a5kMkK67G8F9fi5CYyoc63oeYTEJjnZP5LOik8AxEWHyjACGhIh4FgCp7hAAqewcDRUdMgdB" "HW2PRYBEMTwONgTB4aYQzj+4dIXQqGp3AmS4zDmiJDzw+xuHsCqbh8n8I5wBomBicyASHvX4" "tcfIeYhylZANIOgofKbKaatuneqwuqavo6W5ju+6JETc1+Ff3Fe1yIGY8NCZhy5bGXmHXst+" "0eY6VIuuAMdZ414Px3oS2aKrYGEBRJSr2HHI+zx4wpzAUdcCgd5OmHD6Ckw6ex2iWk7rLivV" "YcWzHZ42DQ4KzpXjGCoBwrIBpF47ECdAyHkIuaXzcLgP7TyM6XIJjq8rW4nso4qBQVItu6ps" "pe74MAESr5yHdB9iUPCgvlmQMw90Isp5WNPme2GCBoiv6xBlK8t5POMtswFkkhKC47mGIh8H" "ojMPIzQncLAad0rH4Zt7mADRpSu64xxBwWJ4pME0L6pxB7zRmM73my+UNwuu7iqE9ad28X6r" "mx/fhy9+/yUH5fQhTqWiK1cvwbnzZxgeamrbhIe/K2SV6/DnNpzgcALE390d/vZZmZ1WKggn" "d6FmO1RJSwXltC6edldRucrMOpyuw+yy+qNXjvwJ8CjelY9nKeSUZMKcdc/B5CWh8OKiMDzD" "ERyiy2rG+uHwxvoImLIhHBXK8HhjayjDY35yBJesCB6L0iNhbVE8AiQaVhXGwNriGNiwOw6S" "ERzbD41m13GgZQHUnFkHjRcTofVaMnTeTIdTd9O5TEUQ6SOhwxDOIwuBsQPOIiTOIjQIFuce" "7YSLj3LZgRBIOm5uhROnZ8DRzpfQaQi3cZQdx7MCICgBCnGS06DAnMtW3eOgomus6LZqjYdy" "BMaRllgob4uBoy3RqAg42hrOwCCIkDgPQXgQNJSqO2NYJzqj2XkQSKiMVd0WytCoaBrKYojg" "WaOBYQHE6T7YgdizDkd7rgrK68wuq5vwT66bGhZqtoOdhzyV4yBwqFKVAodZrtLwMKChgeGY" "7fC30+rH7jN6svzHrj7tOsRwYI8uWf3M3WkvW+m7PNrhSXwed+oSzLp+DxZcvwtzbqBu3oPJ" "Z68gANRa9hafRYjqtShToepbUE0QUN8kodGogaHl8fjAQ4DDPUDmUavLVSY0eM7DK7utvOQ6" "qjQ4RHAuXEeUsVXX7jrKbWUrZ+YxxnuQxa7DKx2H5wA7DrNkRdAwnYd2H3JFiT3zKPEpWz3X" "sEvD4wWvkiPzQLfxUmOhBsdLUi835drgIcCRbe+2qs+yu47GDBZBY3qD0Ex8ntmcyXeaL25G" "99GRD+u6i6Hsuhs+/O0nVunof77i3/ApI6AP3otXEB74Aa1WfqguK/NCJ3/gUHBQ94crOcGh" "4GHus1JlKxWYmzMeBC8THqp9WEFFDQ6S66AshO4codZc2l9lhuT+rpf9c9xN/sdARHV2kdNJ" "z02GaSvGwstLwuD5JSHoQMLh5RVhMGVVOLyxLpIBMnNDDMzaHA2zE2LgzW3hsCAtChamDIf5" "O/DMiIKl2cNhVX4sAiROgKM0FjbtjYeEw/GQU/U87GmYAzV9m6H+XBK0XU+Gjjs7oOteOmcd" "p++nQE9/qsw7trPEc4rormK4iE6qHgrU+5Oh5fpqqDj9OuxvmwD7EQoH0VEcQBdxsG08HGqf" "AIfRVQiNhUNtpNGswwiKI20j4EBrLBxqiWEdbo5haBxui4YjrcO1CBwEEQJHFbqSE11j8ByB" "imVgnOxCaHQIidKVEIXoBI+KpkCExlDtQEhV+JpU2xZsD879A8S3ZMVdVnS6bmvpNeyu67pV" "95+l87CvYb8uHcdl7Tpsrbm6XCWg8X3HLYI2gMjZjh8xKIR+ZEDjPyQ0lMxliGY4rlyHyjno" "5M6qulaYeO46zEZozEN4zL9xD5/v4InPt+/Di+cvQwCvKWmy7bQyn23ug2WHB+UdBA4lCx4W" "QMzSlXPWQ4FD7bTS95lLeCiAUMlKuQ5VrrINBtabHVd2gFjwOGKUqw5J52HNeDgBQmG5CY6n" "PXtkl1WZ3HFlLUZ05h0TJTjs8CjyCc1FzpGv4aFvE5TwMIcEzTZde8kq04BHhoaHAsibrZkw" "t1VkILSe3XW3Gz756gv9IU4f1jdv3ODOJFqCSF1KN277Og8THs45joEA4nQdJLO85by/w9mq" "q1awq9BcbcglYKgWXlW2IkdC8Kuvr+esQ7kOtXL9624J/HOuV/+mnKOktJil7vFIzNoAb6we" "By8uC2Hn8eKKUIRHCM910FW0b26Mhpkbh8OsbbHcpkvtuUvTRsGSjHhYmB4HizJjYWkWlavi" "YGNxPKzdNQI27hkBW/eNZMexr3k+VJ3eAO7zSdB4BT/4bySz42B43M+C7v4dMizPlGF5ijwF" "NHolRHofJEHXnS3QeHUpHOmejH/vKDjcPRwOdcTD3tbR+Fqce1pGwYG2eEut6nUc62BbLOsw" "AaQ9jk/SkdZoAyDRLHYc+GdPIjhY3aOg5tRohEc8Q6QKYcGlK+q+arMAUk2uhcExTGqIdCEB" "DI/K5sE+EKFTla5I3q4IAsgdW2DOwKBuKxmUC930BYjLWohIAFGlKnVyp1XtFVupynaDIMtw" "Gi4LGrTLSu2zImD8yN1ng4Z2HAZACB7KddjbdWWHVV23BEenbs0Na+qBmTcfwFx0HPNu3cPz" "Lj/TSTAhkIzuOifKVrzDSjiNQfXN+jlAOg+SAIjXL0CG4f/TKpm5hy5b6TmPWt2iawJErydx" "n9ADgiLnUCUrJV+AxNVbpz+AEDR4r1UDQeSABgid5ooSgobNgXiohCW27DI8CCT1pQ54lDny" "jlKYRM4D9RxLgEPtufLpupJ5hwaIN88HIOpeD848GjLgtUbLddAzSTkP5T5UCevNpnSY1ZzB" "+UfquSPQ98srfGfH7/7P//Bsx3sIB9o2S0sDe3t7GR70Qfzgocg8nM5Dla1Ud5Uz5xgIIOqZ" "TrN0peChNuqqmwOV+yB4maUr5YgUVOh9ggplHXQfOZWsFDycFz2pVST+psn/nBc9DQQPNRio" "4EHdVpvTVsKU5fHw4tIweGFZMLy0PFQ7jxnoPGiifMamaHhzaxQ7jwVJsbBsx2hYmjkKlmWN" "ghV5o2Fl/ihYXzwWtuwZDxt2x8P6vSMg5ehzUOyaAZVdq6HufCJ4LyVD47VUdh099zJY3f0I" "DBQBREGk94HouOLn+6JNl5wJgaPp2gp0HK/BvtbxsLt5JJR3RuLfOxwar49AIIwWEGkbBftb" "Rmt4HGwfCftb8evtIyyA4PMhFLkQAgk5ECpbHW6J0s6D3AiBo7qToDFWCMFxQgKk5tRIbt0l" "gFAGwiWrNtHCS/Ag53G0IYDhQdCobA7QZSwqYR1vFiCpxq/VtAbpDEQDpCuU9dg/uPrhH1x3" "WQO5Dg0OKlupUpVRtlKdVjrrkCfJt0XXGhD8vryC9oeecxZA8FlAQzgNp+NgKWjIqXLaZUXw" "MEWuQ7kPgocqXak17FS+iu8+x+UqAgYBZOGtfliAr+ff7tfPr5y/zpAgFyLKVCI0Z3CQ26hv" "kPBo1KUrlXeo6XIBDQWOeltoTmG5CszD6ut0m25Y/Qlb6YodiDldLkNyXb5yVxidVnZw2B0I" "OY6jEI9uQ0kBREFDgcNcTyJadvfZAvPxDWVG5lFiOA+VdQh4qNUkGh4ICuU+JjcU66BcAUTN" "eNCpMw9H2UoMCIquK9JrDdmONl0ESlMGZx7TmjIteNBzU5pQQ6qAR0s27L7mgnsfvwW//x+x" "Fp0gQKWgtrY2LvfQb+4KHupDmn77V2vWnWUrc1eVM99wlq9I9D+nAzFLV+ZiRPPaWXNQUHWA" "mVt2VYcV/TdQUG6uIqGSlTMk99dh9ZfQQO28+s7yghxYlTAPnl8UymUrAsiLy8Ph1VUR8Oqa" "SHhjHQJjSwzM2BwFM7dFwSx0HfO2R8Oy9JGwInM0LM8mcIyBtYVjYUPJGEg8NAm2HZgAqeUv" "QGHNLPxwXgs1Z7eB5wKBYwe03kiHzrvkONIZGiQGyYMMDQx2HA8ERAgap1E089F4fQ1UnZkK" "+9onwu7WMQyPw12RUNkRBJ5zY+DMgynguTQRwTES3Uc8n6brIIiY8KCTnIdyIdp9tERxt9Xx" "jhEIh9FcrjrRNRZhMR41ToOE4EEQITdyoiuW23cJGifaIlgVjcEMEIYIguJYyzAWwwNfEzxO" "NA8TTkTC5GRLoA9APN0MkLvsOJS+W2e6DgEOJbPL6l84KBeyl60u6w4rvY7EAIcS7bT6vlxH" "wo5DOhECxr97zhrgOOPjOmgoULmO//T4gkPBQ3RWdRruo4PzELWWZOzpCwwOAobSotv3GR6k" "RbfuwsyrtyC8pZMXJWrn4W6RuUeTDzyceQevJ7FBo17Dw9ltJSCCwPDW+gBEXQplzz0qJTyO" "G65DAINnPBoq/LbrjvQLjwM+UrmHs9OKA/PG3dpxONt0v855KNdhla8K/ZStEB4N+RoaPCQo" "y1dWWC6g8WqjkAbIAGUr030QPMiBTG9Mg4X4Z+vu98B7n3+sg3L6DZ9cB13JquBB916oyXL6" "gKYPcAUO03X4yzsGgsZAOYhZvlLuwwSIuZJdXQSlgKYGCAkolHXQpVVNTU3aeaguK/O+DrU5" "9y9RshrIuQhwWKAqLivWA4O5RRmwaPMUhscLS4bBS0sCuWz1yuoIeB1dx/QNw9F5xMCbW2IZ" "HnOT4mBeagws3REPa3LGwbKdI9l1rCsaA5tKJ0DSwYmw/fDzAhwtCI7TyfjBvgMaL6dDy/UM" "aL+TBV13s6TzQFD0C4icepDGz2rWo+fhDqt09SAV2m5shqq+mXCk5wXY0zYW4TEOytBdkKPw" "XAmF410h0HhpHJx9OAPOPZiP0IhBFzISQRNvK2FRiUvLcB/lrXF4xrH7OIqvKzpGsuMQ4Bij" "AaIdiAbIaAmQeKjpioeTnbEcnFe0UHvvMDjSGIDnUIRGEBxpVvAI8AEIwaOa3clgvn2wpm2Y" "Pwdih4fQTQ0QU8p5WNC4rp2Hz3Cgw3HYdV7f3aEAIspV53TWQbKF5PRs7LIicDgBoqfKVadV" "nQCGgEanWMMuBwOpRXdMz3mYd/sOqp8zDwIIuQ4SA+RmP8y7fgei207x5VC6XdfV7HAcjbzX" "SsiAh99WXXvpilyHnveQDkR1W5lr2YXzqDKuoq2wrWVXXVYmMOySeQdD44iEyCEuWelOKzVl" "Xm/Ne6hZj7FmWO4tsz8bbbrUaaVyD3Ye1J5LAJFlK5LKO9R6ksmyZZeuo53sEd1XNDBIcKFB" "QbXb6tXGXARKDp45CIwcGzyULHhkaXhMJXh409lxEDRI0xq2w6auPXDlg3747PdfiE4nBAh9" "INM8BH3gEjwoNKd7L1SrrvqgVgAx7+gwJ8kVRPw5DfN/ZunKDNDNtl3z7nK1WVd1XakymhMe" "dGkV7bBS/y1ql5VaR+KEx58rKP/frl5X7bnivSLIK86GmWsmwaQFIfAcgmPy0kB4YRkBJBgB" "EgLTNg6H2ZtjOe94MyEaZifFwryUOC5ZrcmfACt3joXVheNg9S6ER9k4SDnwAuQdnwWHGtfi" "h2gi1PamgvfiDmi5lg0dt3Kh534B9D4sgNMPcnm2gzIP7rjqF3lH9wPhRJQL6XmAsOlPhpqL" "CISu52Ffx9NwoHMiw4NU0jiGJ8e7bj8PbXfG4Pc+D+cezYSrb29BWEQxQPais7BKWKJ8ZQKE" "oEGugwAiwDFKggPh0P0sZx0Ej5rucXyaJayTEh61Pfj1UyMYIHTWnsK/qyUE/+8wGA42DOLz" "cMNQdCCBooSlACKhodwHPzcNRj3FEDnRMhQ8nSEWQKxy1W3dZeWEhhWO+4JDlawYHu4r8D33" "JQTDJT0MyCtI+D3HOhKZc/zIdYHBoeDxY0fJ6j8dnVYKGgogP607LdtzLffBjsPMPDxdKDlR" "js8/r+/g3VZRHb0CILesstXCG/dY5D6W3r7HAIlrPw1DXM26hCXU4AOPYZ4GlgrJh9X7A4c4" "w6RCCBrqNOc86mVoLrutogyAqG4rgkYUOo3oBgEQ2mtlD8uF4vF9LlvJ0pVyHSL3kN1WEh7K" "dUzA98ehqE13rGPOg3KPp7170YWUITB26/ZcOtUzOY7nGktEp5V2Hru062D52W31Mu2+as6G" "SQSHpkx+TdB4pTkPXm8U8BCySlZ2eKSLstUA7mOqN4UBktZ3DN7+zXucdai8gXIC+g2dSj1U" "ulLXzdIshbqb3F+rrr+y1UDOw9///DkQBRBzXYlyH2b2oVbBq/fo5yT3RHkH/TeQi6KVJOZk" "uVq97q9k9ZcuWylXop2HzDzozChMh9eWxsMz8wPguYVB8NLyYJi8PAThEcjweG1dMEzbFA5z" "EhEgiXEwd3ssLEyNh8WZ8bAubwKszh8Lq4rHwrrdY2H9nrGQduhF2OtdBhXtCXCiOxXcZ9Og" "5XImdFzPga47+QiNQoZH36NC1pkH9JyPZx636DI4+rO4XMVlK4RHx+3NcLyPylXPMDAOdk9E" "IIyHve3jYA+qqH40lLmGQ1//NOi7Px26+0fD5bdXwKV3lkNpfSSXsEz3oeFBIOESVjSU43Nl" "9xix+6rraZ79ECJQTJCQECUrJ0DqTgt4CICMhNruEfh+rFim2BnJbuMgw0MApNw7mKVC9Erp" "PkgEDxaDYzDDg1TTMkRD5DHhNETJyuk6/sV142vBodyGch7fc11hePg6jos649CdVtJxWAOC" "9nKVExoCHL22oFztsjLLVqrL6gl3l3QbXdp1sGiflQTIMG8nzLx++//n7S2868qyc9/6K+67" "I8nNDXWnu8ggyyBjmVFmZmZmZpJZsgWWLQssS7Ikg+iA8ICYDLJYll3NnXSShqqGvNzvrTnX" "nvuscyx3kpfOzRhz7L2PwFJ1tH7nm98EpTi67bSVKA8CCMX6l60YUeLVFVdF7qC0FU/Tta7i" "dwRSVhog9lDEIvI6CjllRfdabSj14ci3UlbPgjrMZSS7eB4mQLjiypGtwVH4GKMdWX2qDzHM" "Tc8j2O8IGOWh860IHDqSFEj0mBJpDJzuvGdFYkiDYMDzMBWHaZZLqS4vhnJE2yPZ51uvL3Bf" "wf7SHbhdsxCris9iYfHVIGgEroGUlWmaS9rKNM3tcF/C5rKbuNfiwC9//60ND3pXT7CgA5YO" "25KSEvj9fn4XT1CRDm45sGU0SWiprgmPj6WpPvZ/pgIREJnjSkIrr0hthG4XpNJd8jsobUWm" "P8HD7PMg34PKdMXz+NgAxP++SPhglwf7HbF3cPb6KSzZOx5Tt/ZD5Nb+DI55uwdh4T6tPBYe" "GozlR4eyWb7qxDClPEZh88Wx2HFlPPZFT8LBW1Nx4PYkHLk7FaeS5iLmyTpkFh9TB7BSC1WX" "UNQQhdJXUQoAN1DZoUDRc0cpg1jUvo9leGiQxDFEat/fVh9T196bqHt3i6+engt43rQdyRVz" "GRqJJZPV/XSkeiMZIJTCIoDEu8bh/INBKGiYphTNItT2LEXT14d5CGJ07kikWP4Hmel0TSsf" "j4flkxQ0JiCzYgo3EnJTYcVUHlWSo0BCE3bJ88i1fY4peMaAmBKkPPoCCKWvsisikF02jGdf" "UeluZlkY0ou+YIBokGiIPFTKJEPdU2RZ5byUziKA5BZ/wVdSIjnuTxkoBJFPAmZ5a3CFleVz" "9AUPEyBkkP+vvJc6+oDHXxrwsDvK2evQqiMAjgA8/toaSSL3ApBAb4ff7vX4boHPDklVCTRI" "dYjy+MycqlsUGMk+taqeFQhBg1NX7QSOdlYfBJCFDc0Y5Chjz2NAUWCbIKsPGopoGuYhPR6i" "QCRdJYY5qY1hChwED9M4J+XBaasis9cjJyhEfZjKw1QfYx1ZHxrmKsZ/4Hek2T6HHc4UVh1T" "LHgQOKYxPLTvMdWpTXINkcSPjyehtJUFjllOPZ79gz4Py+fQXsdta67VNewq3o/06tEobhuN" "5Kbl3PSn01YBpbFIwcH0PAggS93XLNP8sgaI1SxIamO56yJWuS/juC8JFT9qxu//7ff4nYLH" "t+rQf//jH/EhS6md/Px8TvlQ6ofexbe81rOtxJymg5sObNnbYS56Miuu/j3f42PwMAEi5bsE" "D1IfMq5ERsFLJRb9TPTzkUoi4FGlGKkPgiDNtCIg9pW6kq7y/7sA0aNIzFEntADq+OV9WLhr" "HKZvHYjIHf25w3zB3kGYt2+whsdBagyMwLpTI7D6ZARWn43AhvO6v4O8joNxU9gsP3FvNi4/" "WoF7BXvVYXmKU1Z5NVEMj+KW6/B03FSHugJFtwLF+3iGR13vHRUxlgqJ0eAggLyPtuIWStpP" "ILd+Ax76FuJx7TKkeOapmI1HVQsURGaxGnlQPg3J5QokSpVcfTwOJ+IGIqNsBnJ9s5HsGo2o" "tGFIck1CGveATFHfazqPLqFRJdn+qTzzKoOevRORreKxd7SC3wg8rYuAuyUcjhcRyPGPY2g8" "qdSmeRBA1FWDY4LtgeR6R/EYE1IfBBAy0jnKwvG4bJACRT8FDhMiX3BkWPeZrs+R6fzSSmHp" "0CD5jK/PyvoHA0TgIb0dBA178VNBKECC/Y5QePxlUIQAJGh/x4djSf7qeZUeiFhQa5ToWpVW" "xiRdAQgrkCB4eG142ADhQYgEkFIeTyIzrsKcZVj2skWDQ0Fke2uHgkcHdpCB3vwSo0u91mwr" "PddqQJHTahbU3eVm2iq8yGFFYZ+VViZACBxyDZ2syyrE8STI97DTVqQ8LPVBRjnFx2ZbaeWR" "xtN1NTzS7UZB2+sw9nlQqmoKgyPZgkiSna5igFhDEac5BBzxvI5WAMLKoyg4bTXHZTYKWvBQ" "z4HyXOuqALLBdQRp/lHILB+s3inOR33PKhz1HtR7PVwB41zgYY4oIYBQtdVKtwYHz7py6FJd" "6jS/0ZTDe8qpyooOaTqUaey6jCmng5bgQcqD4NH86iU6FTykn0LgIb6H9HqYo9f76ir/zwJE" "zHPxP2RkCf279O/L1kIK+pnELKcKMepRoZ+fRpOI+hDjXPaVm+tm/2/5HaEAieWd5bG4decG" "DpzdhtlbhmHm1jAFj4HseSzaG86eB6mPpYcHY+mxoVhzIgJraZ7V2eHcVb4xajh2XB+D/Xcm" "YF/cRJxOWoDbuduQ6jqm3r0rePjPIb/2MhzN11HaehO+rmilMmJR1RuP6ncJDJC6r3XqilQG" "wYNA0vC1vpIiqXx3Fa7Wg0j3L1dKYwEyqpYoaCxmgGSoa7p/IR765yHNN1fFbDz06qBqrJtZ" "E3EqbjRO3B6By8lf4YF7OnegZ/pnKWjMsq8U1H2eqsCT5fsKz2tGKvUyDPkN4cj2DcKT6gEo" "aR2K4jfD8LRmnE5hsVEeDJBnlnn+vHIcX6n6ineBWKHBMQQ5JUPxRP19ZZer71+imwgFIOmu" "fhY4+jE8MpyfMUCy3F/gsfNzZLu+UF/zhQURHRZACBRvrHhtl+d+kLbieVY6VfXn+XqqrigP" "8jzI6xC/wwSHGab6kCGINFlXoKFViLUxsFDPtCJ4/H1hlW2UcxT6deQH+x0mPMy01WfWPg8e" "ilikZ1yRMU7zrUaX+jGruh6L6l5gSV0zFtc2YYa/BhHOUobG54VOYyRJcLVVqO8ROtuK0lVD" "FFDI5xhmXUVxDCbV4XhugONZUJe5jGW3U1aStrJCA8RQHOp+rCMj4HdYAOHxJM6HVp+H0d8h" "wxGdgS7zUICY6mOq8y4rj0VlaVjnz+aY60qyO83Z97DSVTOtUl0CiA0Pqboy+jvmuay5VgVR" "iKuah/zGAcirHQlv+0y8+Ho30ps3YHGBVhyho0nMqitOWXGJbpR61lVWlLai5sDcLi9+/M0v" "uJucDnc6hOmQpZQODQ3sM21lKY++4PGx/eR/bDTJH4NI6OgSs3xXRpYINGS/OfkdVE5M8KCR" "KvRzUxqO1AeZ/32pD/I+TPUROvTwvyP4+/Modsv/oAVQsXG4eecqdpxcxfCYvq0/w4P6PFhx" "7NPwWHJoCMODVMe6MyOx/twIbLwwipXHluuj2Sg/HEcTc1cg/tlupLmPI9tzGs+qLqhD+Arc" "L26ivPUWfN13UP0+DjXv7zI8ar6OtxRIvA0OfdVqhKK86xwKXu5SgFiigDFfXUl9LEeadz6D" "I7N6iVIRC/BQfYzgQZVY1DxI8dA/B+lKmdx3RyLJOQMp5XpkCQ1NFHhk+iORVTkD6Uq9JOZN" "QHblcBQ1D0Ve/SA8KuuHFMeXeFDYD+5XX6GyaxZK2xRU6iOCAVI5yYBJoPKKej9YdVDqyjOU" "U1ccFQQPHaRCBCQ0yoQAkqbgke7SKSz2RAgk6p7gQRDJcn9mR7ZLxydmZ7mkrgQcf1bwhpWH" "HsFuqQ4FBoKHnbrKbw6qtGKAGJ3lDI2CRg4xzM2UFc20IkCEVzRhYl0rpjR28HVwaYNlllfj" "O0VG+kopju8VWOAo9NpXDY+A6iCznCDxfSttJRDRU3XL7cGI3+fRJKVcohvmKscQRznCikqD" "GgZ12sphqQ8jChwhneXa9yAFQkGeh/Y+tGEeXG2VF1J1paFC8JDU1QjT61DX0UUB5THS2uWh" "d3pkWWZ5RsAwt0t1A56HVh8P7TJdhkZRahA8prpSVDzQ6sOlFccUBQYyzKm6amf1c5x9WYIL" "LeU43+rFntp8zFFQMdNWFCZAxDgnn4ND4GHNtlpYdAuLn5zC0+Y1qOyerf5gFsLbMQOtP76E" "gtcbsDDvgp5v5bxi7/IwZ1stdV9mcFAsp/6O4sucsqKFUN4fvcAv//Ub/F4dzhT0jp3elZOZ" "TL4Apa0IHpS2Iv9A9nmYykMqrkzfI1R9hA5HDO0u/4+U70r6SvaDmJ3ndBUlQuk0MsvJ86Dy" "YqoSo1JjUR9UtkuFAGbDoIwoMWda/akB0uf3SogNeo5JuI0bsVFYf3guZmwLVxGGGdsHMDwI" "GosPDMH8/QokhwPw2HhuJLZfmYzT8ctxNnENzt5bjqMJkTh7fwFu5W7F3fx9SHUfRVb5cTyr" "PoOCxovq4L2B8vZo+LtiGRQEDhMeDQoodb1xWoFY4KDUVXVvNNwtSsXUrsPD6mWsPNJ8C1hx" "EDBSBSCV+pnUB6mQR/65ChDq3isgmaWHJUr4ZlrgUKqjUoGkcqaCTKRSTRPwIH84KjrGobxt" "DJwvhuBhcX8k5Co1UDIANT2LUd+7Timo6ShqFIBMsXs/TBWSYzUOMjzKh7BpzhCp0AAhYBA4" "aIAigYMm7z6rGIwnZTSJdyCDgwCSqWCRycBQysOh/RABCKsQhsf3OWyAkGFu9nb8P9ZAxP9Z" "+Dpgkhc026FTVs0WQBr79Dz6TluF9HYU1GFc9WssevMOy1rfYXnbeyxX90vf9GDh626M9NTj" "uwoInMLiq1YgAhEbIIV9p63M9JWEDEUUiPAKWhpRUhQYSaLN8hKjzyMYIKw8rAZBKdUleAQA" "Epy2kqqrgOfxIUBIhYxwPLUi11YeBA5SGnIdVRRQHoEO80dBngcb5s5HDBCqtDLBwbOunOaI" "kgc2QCRtZasPaygiNQrurMtHVIsPV9oqca2tiuNymx8bvI8Q6dLKY5blexA45rhiWXVwuG4H" "TdKVkIVQsx4eR2rtbFR3L4Ovc6b6g5mKtp9G427NMsx7eoGbBT+YqOvSvoeoDl15dVE9X8AB" "/330/MuPuJv83/7Pv7L6IDjQO3EKmgFFIz3o3TqZzpS2opSWOQZEusxD+z1CfQ9ztWxfSkSA" "8rHUlqk+zF0foatuyfOgn4t+Pvo5yfegn9n0Puj3oS2CBEb6HUlhUfpKGgb/9ABJ6Ps1KtGN" "jbV2eCi4JNzioYgXo89j6a6xmLk1HNO3DuIx7HN2DrRGkwxhBbLo0FAeirjqWAQ2XxqDrZe+" "wtm763A1eTuup29DXI4CRtE53Ms/giTHIaQVH0GW5wSe1Z5RCvYsHK8uobT9Orw9t7Ty6E0I" "AKQ3gb0PHQos73Uaiwx1f+81PGnYqYCwCBnVSm34FmpgVC5lxUHqgyKzeqkNDzt9RaqDwTGH" "I8MrVw2QADhm43GVViCJBVNwLj6C/Y2m95tR2ROJkjdD4Hw5FFkVA+BonKIAshy1b1eh4d0G" "pajGMzw0QKYENQ8SPOwVtlYIPAQgBAyCCCmQHAKHun/K13AOgcgj52eWCvkc2c5+OmxwfGGr" "DzLUP/kfIeAgYFDIMERSG+J1CDD+PKQsVwOkIcjz4B0eBXVB6Sqzv0MirLQJy9rfc6zo/AFW" "qesaFavae/l+Rfs7pUhaFCiqtc9hgYNSVXINBUdo6opHsheVBVJXhSWBUezWOHYpz/3SoZ6d" "xfZgRB0WOBxFNjiCu8sts7wPcJieR5BhTqkru2Ew4H0QPEY6n2A0RZGRurKqquzucmfGB/0d" "HBY8JrjS7bSVBkggeAWtMyUIHAKP6Up9zHA+0FVWjiQu0yXjfFFxKsNCwHG9vRo32ys5Trx0" "avXhSggBR5wNkIDyuG0NSIwxusuvY2bWKaxNmo/SlwtQ3bUU9W+3q3dkq7A6dT2nt5YUX7O9" "Dg0OMc2tXg8FkGXOC1hbcg3xr/Pwm9/9Sh3K/8aqg1QDvTunQ5SUB1UlOR0OLnMleEjaqsPy" "PGSToKStzC5zUR6hq2c/FqYqEYPdBEpfE3fNRVFSwkvwIOVBabV/T32E9n2YY9llsu6fyv9I" "+JgasXaVa0DF4HZcLE5fOY6F28bzznLyPGZyj0c493kQPJYcjGDlsez4cKw8NYKbAzdcGo2D" "0fNwJXUboh/txt3cE8gsvol8z331Dv0C0kuPIdt3Cs/rzqGg6SJcLVEo67iGiq4bCiA3UNl7" "S4VOYZEHIqkrAgj5HAITT/cVZNVtwgMFiFT/MqU4ViJFKQ2CCAGEoMIpKxUMEPI+/DpdRfc6" "haWAUTmPlQjFI/9sTlsJPB5XzbFiFu/9uJn1FS7eH4yy1jFoJIAo5V3eNh4V7WPh6ZiM6p6F" "DJWanqVofLdVAWQqV2OFlvFmV4xR6mt4EDAYGkqBSORWDFefOxTPPENZgdA9AYUAQvHMo+9z" "S8Ns74PTVw4dYqJ/AJDQSiv2OSQsvyMUIKZh/hfcENgQlKrioPEk1CBYqDvLSWmY4KAgkzyy" "sUOpjl4GBcXqjncKIL1Y3fYWa5QiWd32DktedeFTq8vcTl+J32HtLRdgfD9IbRA4KvhKneSf" "K0BQmOAQkJg9HgMcAhBDbRQG7s2UVZijkCO8qKBveAQBxBpRoiBBIfe0WVBSV6Q6CB5jHDl2" "ykrKdccWBvwO6jJnz6Ov0SRKeYxX4CD1MdGV9gE8AvGgT8M8UKZrTdVV1/WVORoeHdXWVcGj" "w8cAudLuwVx3vAWPODtdJWZ5sGkezfDgUPCgWFR8AwsKb2Jq7CEsi16Ia675uOSci8V3V2LW" "49Pse9ilusU6Vriv81gSu1xXqRBaAlXQU4Xf/OEbfPt//l91GP+eQUBeAB2gWVmP1cGaxwaz" "zLaiPg86iDv+iGHe11h2cw3tH4uPgaSvXR/ifci6W1EhpILo9yCwmepDvI9Q9SHpq9Cuc0lh" "/SkBEk89HX2krOyd5Ql3cOvOLRyP2os5W0dxiS43CW4PV8pjEJfqUtpq6eGhOo4NxYqTw3WZ" "7pWvsPnqaJy+twJ3Hh9BasEV5JREI997D67qFDytuoYs70mGR9GLC3AreJR3Xmd4+BQ8qDnQ" "9/Ya3/uUGql6pwEiqSsCCBnoZZ1n8bBmNcMjxbeU01ep3kUMDwJHVu1KCx4LkVO/goHxkIBR" "OR+Pqubpq38uB0GEoeELhocARK7kfVxNGY2LSQM0QJTCqH+3CnVv16qfbyVqlBL3kxLvnISG" "3i1o/nonXM3TNEAscOR6x/MaW95AaPV5BEa4K2h4RwRB5Ik3wgKHBkiugsYTrwERK3LLdCOh" "qI+soi8scATDI9f1KT75n4VvrAGILbo0t+ClbgjMf637OsTneP4iCB5ilov6IGCY8DABItN0" "bXAUapj8fWENlr7p1WkrCyJrLYCsau1leBBIVr7pVsrAbwPk+9T/UaAbBE3FoQ3yCiPK7PjC" "oVNXFLbqUGAx4WGDw1FsK4+Bjo8b5lqJ5CuAFAQBZFhRYRBAPuj1sABiQ8SoujLTVjwY0a64" "kqD01SOGR7BZHgDHeGsoIqkPEx6BibopNjT6hkciZrjuc0S67/PzxuontvK4xkrEr+4rOa61" "ezHfFR9QHkUBgJhjSWxwqCDlQR3mdF3o1n0d8/IuY3ryYYy7uQ0To/dhdvYZhgeX7bqiuLFw" "SfEVo99Dd5hTldXVmizU/OQNvv397/hQ/s1vv2WDOftJLh+g9G6cDlaqtKLDtqpWz7Yy19CG" "dpnLJkFzf7m5ilZCXuvrY6GQCU15UcjXybh22ZlOyof6TmS2lewuJ/VBqSuCn6gPAqKpPiR9" "FTq2RAz0/44hiQQLcyMhxfWYS9h5arUCxlBM39SfoTF7+xBOW0mlFaWrCByiPNacHcnw2KTg" "sfPWJNzM2ItHhbfwpOw28rzxKKpJQ1ljOp7XRjE8nC+jUPzmigLHNaUkbipo3IT/re4qZ3hY" "ECGgVL2NUe/obzE8tN9xFCmVK5Dkm49kBYmcurUMDUpdEUCy61ez50HPVMJLwxK1+pjD8GCY" "+OcFpatIeYj64Cor9blZBkiyq2hZ1XREPRiNs7FhKFUAoTRV9dv5SnXMYdPc1zkFns5xqOtZ" "gzc/Os8KJa96EquPbN94ZHnGWLvQh+FxxQhkK2jI5kEBSGjkeoZxsImu4KEjoEAIHrSBMK9i" "EM++4jEmhgIxAUL+RwhArCorGyBGGL7HX1rwkDWzMpokFB4S5jRdgYcA5HNnHVa0vmeArCBg" "dHzN8KBYRzBRUFnd3o1lLV34gtSGBQ9OXxUEp6w+6wMgBA2GB4OjxA4GhzXbaoCj1ACIi8Ex" "0ACIqUBM30NSVlJpJdfBRoe5hKSrdATgEbTnwwZIdsD3EO/DKtcd43yMrxwPddoqBCAEjwmu" "jKC0laSu2CgvSu1DeSTZzYIMEKNBcIbrHkekU3ear6zIUGqjmgFyw4AH3Z9vKdGjSQzPQwxz" "7jCXSiuBRxBAdJPgAtc1vl9SqK55ChYFV7HIEWUPRdQpq2sMEt1pfo2Vx4aSm0hqcaD3n3+C" "3/2bfmf/i3/5Z05NUe6fglJW5HeIWS4j2c01tAIPKZUV4zoUHnQNvf+PhEBCgGGCR7rNJaTv" "Q7rLTXiQwS9lu2T6m5VXpvowR7Wb+8xNgPS1fvZPUaJL6SuapHv55jlsPrIIs7cOxqxtgzBn" "Wzjv8pi9OxxzqVR3v4IHLYE6PgzLTkRgxakIrD0/AhujxmDbjbHYe2cazqetwf28M3hSGod8" "XwLDo6QpA6UvUpDXcAGuV1fUAXxDq4630fB2X1fwiGZgeHuu2gCppM5yih4Flu4bSqlcQl7z" "fqUqluGBfwHD45ECifY+FiBFvZZZQ8/a7yCIZNetstTHfA7xPug12vvxTH0806fVSLpfm+YE" "j8eVsy2AzOT0FT1Tj8iV5FE4dDmMJ/bSuJOq7rnwKnBUtE9Aefto+BVI2n5yEe0/uaIUyWpr" "5/lovmZWjOS0lYQAREPkQ3hwE6GCB6sPqsRiJTI4KIX13AoCSL4nHM/Lw7QScQUUiG4k/JwB" "Qg2FnxA0xPMIAocY5Xn6/i8KXwRMci7XbdTRh/Jg1VHUwKkrAUdo6upvC6sZIAwPBQvyPDRA" "3luhQNLRwwBZ8qqDARJIXen0lYwl+dSAxqe26qjQZnmRNswJHP1CdneQ2iDPgyDCqsPRh/dh" "KY9BBU7u8Qg2ygOpK1uBWE2CZpd5EDSs4LRVkYYIXQMj2i2AWIqDoEHPVJ7L6SvHw2Cz3IIH" "A8SCBxnmQcqjMMUu1Z1mNQrqiqsHmO5KYd+DvQ9LdQg8BCAUVGl1/nUZQ0O8j1udflxt9WFP" "TY5dpksprFDPY57rQ/UhQSNKSH2QCuF95tLvQTBxXsdyp05XLSu+zqpDV1/pZsFNpbfg7K0L" "Wvz07gdfw+Es5JJVOkDpMKWDlfwBMcvJ76B38V1ve4KaBE3lIVVPAo/QkNdFLcjhH/osIV9H" "KkSe5fNNo5yeCWCyKEr2fFDJruw3F+Oc1AcBkdSHNA6SeW4CRJZEmaPazUVN/1V43LXGkQQ1" "Carni9eOYeX+KZi1JRyL9ozE6kMTsOrYJKw4MgEL9kRg/oHBWHx0GFYcG47lDI8RDI8tUaOw" "8/oEHE9YiGvpWxCbuwf3Co7icdkVFNUmobzpEcpeJcPZHM1TdCVl5e2JYdOcUlXke9gAIXgo" "aFT13mBw0LO79Qwe1axTkFiMu+WzkVgxW0FkvuV7LGDvI71ysVIcK7l8l4BCJbzUB0LKgwFi" "+x9z8LxpPbwdp3k6b3nrQeRUEXQitQIJSV/xfeUMBYBpiM4YpwAyGLezByoFskJHz1IFj6+U" "AolEyw/PoPtnd5UCOat+34lILhjG8CDlkVE+gpUHbR5keJjbByl15R32AUAIHh8DyFNRH+r1" "Au9gDRBvOMOExpeIgU5NhNKNbgNEVId0lpuKg8BBPR5/Udhsg+N/FzYxOHTU2ukqMcxJcRA8" "/tpQGwyOImuaLgOkEt9XQcpjZZtOW+n01XulPN5jfVsP1rb38HVewxulFnzGPCtdeUWvfeHw" "WGrDw7AQgEi6iiqtRHmEeh2BcFtj2XWY4JCgTnMCiPY8AqNJguBhp6usLnNnng0QDYznH6iP" "QMOgnrJL3gdBYwx7H7raijYGjs9NwVLXCW7Ys0t2Q9JWoQCRiquAaZ5iKw8OKtMl5UFpKvd9" "GyCsQOy5VgnqqjvMV3nScKnVgxsdVToUQE69cmFJcaLdIGinsCxwhAJE1IcejHhLgeImQ2Op" "64YxFFEPS9R7PK6x5yHmORvmRZdxyH8fr37Ri1/94bdcaUUAae/qRFZONh+a0llOfodHHbB0" "2IrfQe/i36oDWSbr0igQgoeMKBHfw1QfAgbzwDdDgBMa5udI86GZpgr9HjIokX4u8mPENJcV" "tQQ/Ms5JRZH6oCVXVAxA6StSWebcK7P/QxZFmQD5UwcZ5bFx0Th8YScW7xyBGZvDMH9nBDYe" "m4XtZxZgx7lF2H1hCbadn6eUxwgFDu13rDytAHNuOBvmB6IjcSl5LaIz9yA+dz/in+1HsvMg" "0ktPINt3AXm1V3WPR8s1hoenO1orDwUOrw2PW5zCEniw6ui5xkBxtBxHsncJHlYvQXxppIqZ" "SKBOcu88JFfMwz0FlAe+OdwwSOojzfI+KH2VzqpDqZGqBRog6j6rehH8nWfQoP6tpnc30Nh7" "HcWv9wTBI2CgaxWSTVVYvhlIfD4Jp+8Mx87T/ZGrnild1fBuPV7/8JhSHpfR/fM7rD48bXPx" "IH8okh0jeIEUAYQUCAOEFcfoIIgQQMg0DzXRCR7PPBokuZ5gA91UIAQOHWEKJoP4mltG+9I/" "NwCi7z9hcBQ2293krDbU/Z8pSMhAxL+00lV/GZKq0h5HQHXoa40GyPMGNs7/7nk1qw2J7xBE" "FDj+1urxWNDcxUpjTVs3ex6Utlr35q0GiLqna2TdS3xO0Cgqx2cWNALKo8yIEivKgoxyBkdh" "qT2KRJRGP6fLAoY7uETXSlMRMAY7nEGd5SYwuMvcTlPlW/FhqspUGjLriqqt7NHshU/teVcj" "lNoYTh3nCgxj8h5hfsFFXPQsR2b9KJS+GYgHDbMwX73LJ0VCneUTLIBMdKVbEEkNKtU1oTHV" "UhoS0u+h4fGh6uAR7I7ARkGqtFpelozTL5y42laOw82FWKzgIemrBc44BYg7vIJ2QbFSIO6Y" "QFgpLN5lrtTFQkth2CNKrFQWgSSw1yPKDlIcUrJ7o/EJfvrNPwV5CAQIOiQpZWOW6Ep/B28R" "fPOG00Dkd8gmQYIHgYPe9YvnIQd8X5CQhU4S0uAnYXaKS5ifT0Ayv1b+TUlZETwkbSUbBgl4" "9LMTPOj3IBUlqSuCB/k6kr4yq69kcKIMTzQn7/5nS3UTjGGICUbfR1xsLHsfpD6i42Ow5+Q6" "zNs6hMtzyShffXAStp2ei53nF2L3xaXYd3klDl1bjZ0XI7H6zCisPjsSay+MwMZLY3HwzjxW" "HTGP9yHuyV4k5h3EA8cxPCo7jse+M3haexb51OOh4OFh1UEm+W0dDI8YDY9ubaJ7aZIuwUMd" "6p6eKyh4cxD3vQu4yupu+SzcVfCIL5uOhJJIBYdFuFc6DffLInGvYgZSq+YjqXwmkmlkiVIj" "WbWL7Z4PKdWlFBYNVqx5exFN769xEEAqu08bFVeByqvHFjxy/DP4PqV4Cq4lj8bBS+HYc/ZL" "NsWruhex3/HqB0dR926LUiNj8aBgIO5khuNRsZW2MgFCCsTaf26W7HIDoeV75HiHWOmrIRZA" "hgSBQ+Aha2vzfIMZGnm+QXxPEMn3hOFpaT/kOANNhHT/CcHjzwua7S7yP8tv5OAmQFYhDUEe" "hw0RTlNplaHhoaKoSikMdS3wMSx0Z3mtARACh0+Bw8dd5NTTMbbqBVa/0akqUR52KHVCC5+m" "VTdp5WFB49MQk1xSVaw0HKXWuPViozzX6umw5lmR18HgIM/D4Qoq06UIc+hxJLq6KpCqMnd4" "mNVVfcFDUlShqSrqNGdYOLVhPpyXQll7PQoVFPKSsNRxGWc8q5HdNIq7U3Oqw/CkKgxlbyLg" "bBmBXZ6DGKfUiQZIwPOY7LR6PpyW4nCp11zJNkAEGhIMDueDPtNWsxz3bHjMcuqx7Dxd1xXH" "TYIL3Am8GEqnrXQQ2BZYACFo9JW2Mn0PgsbS4lv2gER+VvdSpit9HhRUcbWl4jYetZXgn373" "K9uUJgDQu2+CB5nGZspKxpJQykf8DinTpfQQHdjiedBBLr0efUFDwCGQoCDwyEDDPxbyeRRS" "kiuLqGSmlez2IOVByoggJ/vNTXj0lboilWWqD2keNP2P/xpA+oaKpKvI77gacxmbjsxH5KZB" "mLM9DLO3DeRU1abjM7D73ELsvbgc+6JW4MDVVTh2Yw0O3pijADIC6y6OwraoSTiRsBQ3Mrbg" "toJHLMEj/5BSHkeRUXFaw6PmPAqaLlnKQxvlBA6/ggaFz/I9CBhsmqvQpvktVh55rw4hUSkM" "AggZ5gQPCUpXMTgUQBLLpyNVgYLAwUApncLKI7kikoNGt6f5ZrJJrgGyjNfZNn59Ew1fX0Pz" "u2uo776oQLFAeyBVgcii7nMVPGXXT0MTpypIjsOFxCHYdfpLbDv+PZxL+D4eOMPwqGIQ7ucN" "xKW7n+FmSgSSCyLs9JWZwsoxUlem2rCrsLxKbfiG4qlPKRCfrr567h2moUH3ChDPSG1YEKGl" "UQQNinz/ECudFWZDhIYoShUWA4RSVJSe+l9FeqbVXxe8wHdcOkR5UAc5q4v8OlttSIrqryVF" "ZU3OpVlTlFahdJNeOevnMSTUTU7Q+E6RHkHyvSI9x+pzpxcLX3bodJUCxsY2Uh9ddqx904XR" "njoGSCBVFQwPMcm5IbCoNACOwtIggNhKwwIHVViFFbnsyioCh4aHI6inI6hE9wPFkf+hSS6+" "RmEAIKIy7G2CTvE79LiSiPwMjMqMw373ejxt/opn4Tz2DkBKUX8k00iDZsqLTuORBheqN+h5" "Vpy6SuWKKw2LVBsc5HVMdaVZAEkyVEeKrUS4ysoZDA/e5+HUymM2AcTqMJ9lzLWa5aQuc2uD" "IBnkbg0SAoc82wCxSnXF79Cj2W9y6orKd5eYgxIJIJKqcl+3R5PQfKujVako/2ETvv3Dt5yy" "+uZ3v+UDlt5x0yFJ8KB7golZokuGM72Dl3HsdED3BY++0k8yNsQEhgwzpK+nQ1+u/17I50ll" "laTMZJIupatkBa34HWKYEwApbSUluwRGSV2J+jCrr6R8NzR9FQqQ/2wpb0Ifnec0z+r05YNY" "smcSp6youop6O6jaaun+Udhxdi72XFyMA1eU8ri+CkdvrcXJ2+uw98ZMpTrGY++tWbiQtBY3" "M3fidvYexD09gLt5h5HiOqbgcRI5lWfwpO4Cil5QpRX5HbfslBVdBSCSutKhFQhVWZFZTs2B" "5HXEs9exAAllSn2UzeDQgxHnMyxoPPuDillIrVxoP6d6yeeYxZN2KZIqpiq4TNNRMZ0/Vvpm" "H8Oj/n0Umnqj4G09okAxBxm+GSqm2fHIN1ldJ+ORd5IV45Fa/BXu5AzHubthOHKjH/Zf/BQH" "Ln2BozcG4FLCINx+NARJhcN4E6HA43GZVh5B8PCO4uD0FYUvwgjL81AAIZBQ6S4rD05TDbUV" "CPkfvP/cOzgoCBz5ngE6ymmk++dWJ7oFEOnp+L77BUZUdWFKYw/H8KoWfM/VpKupCpsMj8Pa" "21FQFbRi9m+LPFhXch73G+dhmec6H/o0joQAohWHz5phZT2Tp5Hvx/CKBix71YUNbwgg3Sq6" "WHmsUtepVY3o7/TYM6ykJJdSVQINqajSHoe1u9yCCJnkpDbCnG4MchBIrP3k4m84HVY5boGt" "OAYVBsAROkE3FByhpblBysPYX64N8qcMjBFWr8doZw5DZHjhIwxOS8COpxtQ2hHJdeEFjYOR" "5v4SCU++RHpJGPwdC1H7bh28CiLRDQt5vPp0dyamuB5ioltBRKmMCa6UIIhMcafYfoeoD5mw" "a5fpOu/bKStdcZVgp65IcUhnuagPHerZfRtzi+8wLER16FDQKL5tpKtu2Z6HVh03tUFupbHI" "OCdorC6JwdaKBGwpj8eqkpsMj2XFUVhTfB3RTU/R9o/vdK+EggdVWTU2NtlVRnRo0gFK78Yp" "rSNVVmaJLqWEQv0OUQCiPMwUlYDDVBiyRtZc3kSqwQxZKWvem59H31O+h/R2ENgoSB2J30Em" "v3SaEzxISZHyoEIAUh+ksEz1QX4PqQ9KX5nluwIQWVn7/2dpVJzV60Hj1ylVRUGvR8dGY9+Z" "dVi0Ywxmbh7IPR60w4OqrBbsHYylB5RavjiXVcfhG6sVPNbj1J31OB23GrtvROLQnUWIStmK" "6KxdiFHwiH2yXymPIwyPTAWP3CpqELyIgpdRcLUG4CGhIXLTNs0FIF7L+/B0R+Fx/XbcU4Ag" "nyPJs0Ddz2Xvg9JWiRXaEL9XOkMpkOlIKtOprAdKaSSWTOVrRvVCve9DgeOBgoZEsodgMxlJ" "5ZOQW7NE/c3uRkX7QQWTPXhSuxQpFZN4D/pDz3gO2vmR4qGlUWPxUEW6uqfIUK+nFo9S0ByJ" "mMfDcONRuIoh6r/HYNx9FoFU1yhk0hpaK3VFQSmrD9RHHwDh1JVPV1/l+cfBSWXAvuFcuisK" "RFJYbJ57hlrQGGQAZJAFEA2RQs9A5FVoiHAZbwAerzC5uQfz236IRW0/wuLWH2Be63tMqO9R" "EGnWuzsM5WFXVfHAw1oGxYKSaCR6xsCnDsGslrWYWJIRBBBuArSuPHqErrReVt2PLK9DZM0r" "LG1uw+IXLZhe04wRZdVKUZQHDUAMpKw0QD4v1MD40ppfpcty9c4OgsZknx+L6hqxrKERS1XM" "q63HV2UV2hh3aHgQOEx/w7wfYhnifakNsymwT4BYDYKm6qAQgIyyxpUMfXwfEbdP42H1VDS8" "2wR/10yUtA5BYVM4jzQoapiMqq6l3GDU0LsOj16uwq4GJ/Y3V2DXi3Ksqc7jclwGR5FeBEXK" "QwMj0GE+xZpvRaW6H6u2EnjYC6EkbeW2mgTdgX4PSlmx+rBUh05V3Q42zK30lVYcN231sdRK" "W9F1Q0UczjTn4EpLHq69fo7jtakKKNexrvQmnnT78ON//kf89g+/x+//8Fv85Oc/Y28jLSMN" "j7IyOWVF1UcykoT8DmqwM1NWMpZE4CE+hcDDTFGZ0DCVhgkN+n6yDVCClENoEBTMZ/o8+r6S" "pqKfTaAh4BC/g8x+6fUIhYeZuqLf3fQ+xDwnsJod6P8VgNgjSSyvg67nrp/meVbztw1G5KYw" "uzGQxrATPKi/Y/mhCGw5N4OVx/HodQoeG3Emfh1Oxq3A6XtrcDVtJ25m7EZs7j4kPD+A+wWH" "kew8jseecyiqvwX3y1i4Xt1Sfws3bHjodNVtAyS65yOgPsgDURDpikJGzSausIorn8kKJLVy" "ie19kPpI5hlXy5D/YieKXh9A0cvdXG11t0yrD0pdpXhnMUA0OKbwVasQDZAHFRN5PDupDVId" "VL4r8EjxTGBwCEDoms6hwSFBz7z7vHi0ijEMFLp/VDEGGeWSthrFqkNKdk1oiIEeqj4IIJTC" "ctZNQ13rZtS3bUFpwyzuRuf0lVWJRUqEAEI7zkPVh4aJxEAUVGiI0PV56Zf45H8rBfLXRc0Y" "X9+JhS3vsYQB8l7Hm3dY8OY9xta2Myj+yqimouqq71ggIU+D1qzeUf9Rk/IHoLJrPmp71uBw" "1RXuDJeZVfbYdXtuVaAR8O+pwc/lU4e+lxXHl84K7h7n2VWW4iBIyPXDyiqnUYrrRLizGPPr" "GrBJ/THubG/Dzo5W7GxT929asLnlNWZU+jhVNcBRYACk0F76JCHgiHAWqAju6YhwPguGBsHC" "+dQOeQ7AI4dNcrqK+qBej/CkaEyP24znzRPR9H4Hat4u4XQVRXnbZFR2LkJl91zUvl3EXal5" "rTtxrqMSFzprca6zDmfbarC13mkZ5gGATGeTPAAQ8jymmemqD3yPu4Hd5bbiSMAcq8t8PgNE" "h4wqIeNcp6zuhHget4OqrrjaquRWEEBoPMkKpVIuvH6G+HYXYjtUdLlxu82BS025aPxZO371" "22/wr2SUK4C8U4ctqQ1KzeTkZPGhyVVWHo89kkSqrOhApkNa4CEpK6m0MqFhKg76HBMaoiBI" "KUiKSRQDKRsJSjtJ0L9tXiUIFvQ9CWwUlKaiILVBQYpJwCF+BwGR0lb0+5G6ot+VYEmpOoIH" "KS/yPqR0lwBC/oeU7/aVvvrPprAIHgQRCqq0Onpxn1IdYzGLlj9tGYiZO8J5/eyifRogtPxp" "8eFhWH5iBFacGIVN56bjwM3FOBazhIchXkzaiivpuxket3N2MzySio6qQ/MEnlRehedNGuq6" "HqPpnQMvf/QMVW/vKzDEhMDjNvd7+O2S3Vu2B1LRdRnpvjVI8M5keJD6oE5zgklC2Uwklkfy" "PY0ocb46zNsGa3qjUN1zRf3NnVeqY4kCxEweT0KwEPVB0JD0VYpXQyS5fCLDIrV8PN/Lc5pS" "JhSiQB4SJFh1aIgQODLVNdMASmbFVwoYY9R1NEeGggJdqfeDTPPsilF2sN9BisM3Oqj6ihWG" "gEQpj2e+Uah9swmveg5x1LZuRL5/pK06TAXCEFHAIZAITPJ8A4MAQvCQKPD0wyd/42xCuOe1" "AkUvA2PRmx8q9fGeYylF2zu+H1DcxNVVBBJpBuR1swVe9jr2lu6G+9UwOJrC4O9ZpP4HWYfU" "F4fYcyBoULpKdnYwOIp8di/HZxZEPudNgaVcikvQIIAwJBxlDA1KR/Ecq6JA8580BQo8wpwl" "7G3Mr6/DjrZW7FJ/mHvaOlW0Y3drG3a1vsEeAoqCyZTyMgsaBjDUc0B1PDcAkmcBRJfjDnfk" "fQCLUIAMdwZUB0FDAGLCY1ReJgbFX8fc2LUofD0d9b0brXrwNUpxrOZ7aiiiaZzNX2/Hi693" "4lnbTlxsqcT5jjoOAsiFznos9+ayxzHtI1VXdpmu24KGVX01U70205WI2c7EEHhoz2O22d9h" "gYTBYZjmdvpKPI/iaGtMifgeSnGUaIjYaSwFkB2+e0jocHPEdapoc6Pg6yausuKdGAoc1F1O" "hymlYzQ8cvhdNx2idKjSu3NK80jKig5rSVnRgW3Cw6yKMiunxN8IBYeoC0kx0femw18UAwGA" "rhIEr9AgOMjn0veR10kliUFugoNUB/2+UqpLngf9nqQ8Qn0PgYd4H32lr0IB8p9OYVlG+Z3E" "2zhwZjMiNw/BjA3hmLetH2ZuG8DNgTyS5KDeHEhj2Km/Y8VJBZGTI7Hy9HBsuDhBKY9luJKy" "HTcUPG5l7sEdpTwS8/bjgeMIHpac5DJdf/sj1Hfl4tV7Fzp+WoGeX5Tj1U9yucLKa0HEDgUQ" "XXl1w24erOg+j/Tq1YivmIXYcgLILKRWL+XUFYGDYJJYMp2bBmnPR3nHaQWOS6jtvab+3q6p" "+wt41rSRlQeZ5cEAmWRBZIpSGVN4gZStNmjLYPk4dT9ZA6RiggLDRHvXebp3vAUQI7xfMUAy" "PF9ZIeAYbUMkizcKKhXiseARWq7rG62ViP0cYQBEQcA3Dg3tOxU8DjJAGjq2oKBylK1AnoeU" "8Ob7hinAhHMU+ii0gV7oGYQib5gCTP+g+GRgxWtMbezGwtavWXUs7tDwoAa/JW1fY3mHjhnN" "3QoWflYdpEDIFP87q7Lqb55U4ErZSm6C8XWvVO+WZ/Dwr8ev9qO/+kO3u8aLvBzSAEiG+Gcq" "CBb0/JlDqw0Chr4vtdUGX4tc9sRcAQgNPtSmeLEeO6KANba0DDvUH+au9lYOhkdHG/arP9oD" "KvapP+i9SpGsbai301RDncbIEaUsqIdDIsKOZxoMjmc6QpQGqw3XMxsa4nOI4ggKBY+vlGob" "XZCBsJgozIhZg8KX41Gn/vvRELWq7tkqFDg6ZvBwNRqo1vLDC0qhbMPDlqM40+HHhbZ6jksd" "tQokNdjfXIKZJQ/ZH5ki/R0faRIkeHA47zE8BCDBXkecXV1Fo0oEHvZsK05fGT0eBAsOnaoS" "xbHIftaxtFgHQeRM42OlPopxRymPpLfl8Pz4FX7zu99weS6B4xfq4KeDk95NZzzOCkpZhZbo" "yiRdqbIK7e8IVRuhisNMUQk4BBoEDCmpNQFA0JIgCJhBYKAwP05fR68RLCjVRkHwk7lWkq4S" "cNDvSKqDPA/6nUlx9QUPaRw0zXNJX5kd6KEACR098mHEc2/HlehL2Hl8MVbsncSd5XNswzyM" "4bFMgWPpIRpJEsHbAzedHoNVZ0ZgzblR2B41DecS1+Paw624zspjrw0PWgD1qPQMsv3n4XwR" "h6a3uXj9Awc6flaO7n/0ouefStH60+e8v9xn9XpQ70fVOw0PKtH1sw8Sg7LOS3jcuAVxCh7x" "VuoqyT9Hp64qpjM8EsqnqOdFPKadFEhF2xml6q+g/t1Npfwvo7o7Ck8a1uNR9XwDHlN0VExW" "0JisU1dlkwJqo2ICR3LFWFYidP9QwSPVG1AeHFa6SpQHqY4s7wRkeseqGMMQoau+H22pj5F2" "+orAoXs/InTKyjfS8j0CYVdiKYDQtN3n3uGoebOGAfKy+yCqX6/iKqznXKo71K7EooorXbZr" "xmCGSJFXIgxFvgEaHv4BfP/JhCYLHjRCncChYEHXZTY8rBHr6nO+KNbw+LuiKq6m0v6GH3+V" "5cCaRzvg7VysDr0FKO+egqYfHMRlz1H0e1qI7zsqNDysq8CD0lSfU6pKgeILjnI7NaWBoc3x" "gBke2EnOwHDqkly5DnDqKqoVL5s1NNQfK6kNCoLHfgUTM7a8agpq/gsojWd8He7KN+Chnt3P" "QhSGHr1uwoOexd8wATKC5lmpKzUKivqgPR4jCtIRFheFERe2IKNGAaRnLap65vA0Tm/bJLsr" "lbpRO392S0F6LWIbLuNcZw3DgxTI5c4GRHXW4fSbKiwuz9GVVg6drvpYykqCynUZHDY8Euyh" "iKw6iuM5ZdW38tA9HpSu4rAAopWHBogOXXEl4FhGKayS66xATjdlK/VRgty3VXjzi3dcZUXg" "+Oabb/kAp0NSusrpng5QOkzpgDVTVjKSxKyyIniYlVaiOKSMViqqxN8gcIR6E6IwSEUIMEwA" "0OFPAKOgezNISYSGqTAEGARBUhuUqpJ0FYGDVAf9rqQ6yPPoK20l8CDlIaW7H6qPAED63ERI" "o9cT9FXAISNJbty+glNXjmDjoYVYd3Ay1h6cgQW7RmDeTr3Dg0xz8jtWHrXgcUIvf1p3YaRS" "HeOwP3o+LiZtwbX0bbjxaBdiHh9AbO5BJOYfQIr7KNLLtPJ4XncZnvYH6k1SEdp+Xo6uf/Lh" "7T95VZTizU+ewd8TywpEl+/e5JlWnMJi/+MGitvOIqdxOxI88xge8R6lNjyzkVy5mJsDRX3c" "98ziPR/0TE2BpR2nlPq4wQqElEiVAsjT+vXcYf5AweO+V6euUrzTLc9jMqsOCkpREUQkXUUm" "ufY9Jthpq3QDIFR1JeCQYJgwQMbyRkK+egJpLEpfcQg4LPOclAcBRKuNADyohFdP3o2wzPKh" "cFRNRHXLegWSdXDWTFRgGGbDg+8NgJDaoLSV3LPvQQpEKZGiyoEMDTM+mUO+R/t7Gx4ECg51" "v6L9a6zs+AFWKphQk99I/ytrwZPf3ghI99/LUwf8nau46FiB0tYl8HeuQ3LNdkzKuozv55fa" "C54IHASRT605VaI4vrDUhigOSksRMDQ0QjvGLXhYioNDgaO/1cMx1OVkv2O/BY+9Ha0h4GjB" "AaVGDqrY1vLC7uMIqI1nQTHCqb0OUR2SqgqojlzbGBflMcr11FYdPFXX9ZiDu8wdlv/hzOJu" "8zGFmRicdBNfnj6AI9nTUP92LaetqnrmwdsxkeHx8usj6PqHRLz+8VkUtq7A+bpkBsfFtlr2" "QS511CuIUCqrCss8OZis4DHZAEhkaKOgW5fqUrDysKqtGCD2Lg9tmAs4WHm4ZBR7wDA34bGo" "JIbVx0ILHgIMAoju+QjAg2J5yRXsq3wA9w9foveX/4Bv/qCHD9JhT4dz1uMMPhA/lrIS1dFj" "dJWH+h2SsjJVh5jjUgklHoeZohJvQqBhppgEDnT4mwCgoJ/tPxKhwCAgEjREcZjpKvq9SXVQ" "tRX9d5BxJdLzIca5qI/Q3g8KUR+sQO7G2bAIMssTAsMVY+JicOnGGa6yWnMgEqsPTsHawzOw" "4cgcLNo3AvP3hLFZvuDAYB6GSABZeXwo1pwazlsDt1+ZisN3luNy8nZcTduFW1k7cPOxUh5P" "j+B+4RGklRzHo/ITyKm8gLz6KDheXlEqOwXt/1Cm4OGxAEIpLBde/DSL4eHpvW1VXWl4yIyr" "8q7LyG3axbBI8Mzh9NXdikgk+ebhgX8R31PDoIbGYjwon6Nem8o9H0Wv96BOqQ/yQaoIID3n" "kVu3UqsPBQUxzHVM+gAgcv9Qva4Vx/gPfA8TIAIRvlrgCMQYGyAUGh4jtfqgRVEEj4pRBkBG" "44kvYJ7zPZvngWm7BBBdcTVcQSFC+x0WQPL8+l73fITbTYMMD3+E1Qcy0E5lMUQIHKRErPiE" "0lX2Iqc2PRmXgEHjRRggbXrM+sq2t5hS3xpYJauUxHcdlXwlc/zvHj3FgDsXsOD+LixP3oHh" "iWfx3axndgOghoROWZngoCorVhuO0g+AYc6o0uEKQMMCh45CXVGlriNLihkUrDrUAbCv7Y0N" "jwMcLQwPum582cApqyFsiAfgYaeoHB8qjlCPQ1dU5dg+B6mLkQoWFBoSjwMAcWcb8Rhfqddo" "vtXQ9Hj0v3Icw0+uVf/PuBi171fxSANKA7768Sl0/Twa7T+5hqqu5bhZfRAnG504117NEKH0" "1cX2GlzqrMbh1xWYW5bO0KAxJbzXg+BRfD+QtrKgQVdRHnOstNUceyR7bJBZLua53d9BZboU" "JdHaLKd7y/cIpKwCJbusPlwWPGgoYslVjl0V8XjaU4V/+Oaf9XDBP/we/6gOd3rXTYeh7O6g" "d9yUvpHGQIKLCQ+zRNfs7zA9DtPnMCuqpIyWjHBRG6Y3YSoNMbVNENDBTwCQdFNomK/TvflM" "MBRj3IQG/a6kOCgIHKI6CBxUOBCqPEx4mKPbxfsITl/d7WNvhx5DopdAxeF63A3sP7MZq/fP" "UPCYjrX7p2P9oSnYeHQ2NhyL5PJcWvxE8Fh+ZDgvflp9cgRWnR6Nzee/wpFbC3AmfhMuP9iJ" "6+l7cCtzJ2KydyHuySHcKziM1OJj3CCo4XEJjhfXuNKquvceOn9epqCh4PELD6evOn5ehJqv" "E9k091pmOaWveNpu73WeqksgKe24iOyGbQoeczVAyucirWaJVXE1jVNY971zecIuVVhRFRaV" "79K03cKXO1HafgTO13v5PtUbqVNXfXgfaUrZPG1YhcLm9XhWt4QVh4SGxsQQeFhKxILHvwsQ" "U3lY/R4FNbNQ3LQURXVzLKUxUsGCvI8RAb/DDF+E1Tg43K64Yoj4Bgc1EDJIrNElZtVVWeM0" "VL1cgOK6yUEKhNNWAg9WIP3xCS1ykmm4MpeKFjnxKPUOHausCbmzGtvxqUM3AVIwPIo8+ppX" "ju9kFeJv7j3EdxIf4rvZz60KqgA0KFVF8aWVtpLucVYbRaXB5rg1Xr1PgFipqjClNnQE9nKM" "VgDZ066g0abjgKE+6P5QW4sdy+r8vJd8SFDqKgQi5HG4+gaIWZY7yqquEpNcoGHCg4EREjSa" "fcTT+xgcdwVfntiDceeWI9o1U6m42axEaKxB3fv1cLXNwY3yXThWnoVzLX42zbX6qMJlgoi6" "bqzO0/OtrJD5VgG/w1AdzsSQ1FWgx0MAYqoPGk2i43YQQOSeQMKDEa2Ule710NflTqvyinyP" "Yr27/Fh1Gvw/bsU33/6amwIJIPTOnw5ImWVFB2VoyooOdTrgQ/2OvsxyAUeo6hCfQ9JVkqqS" "3gv6NwgaUglF0BLFQLAQYMjhTwe/pJr+WNDnSJivEzAEGqQ2xOcwwWGmrMxyXRMeJkDM0l2z" "fDc0faVTVrfZ56Du8nM3TmDl3hmI3BKOGRvDsHD3CFYfG49Mw+YTs7Dy8FgsPTjE2lcewWb5" "2tMjeCwJrZ09m7AWcY9OIOHxJcTnnOHO8ju5uxD/7CBXWqUVn+DtgU+qzmvl8foGitu1t0Fp" "qsYfZqH9H93o+sditP3sGeq+Tgkq2a16f8eGR0X3FVT2RKu/k2iedUXVV2l1a9j7SK9bwcY5" "pa0IHne56W8hkmlXuVIjFNRESGmsZM8M7j6nHhDaPBjo9QiuuCJ4FL/eoVTKKVR2n0R110kU" "NK9GqmeqCq1A0nwaJOle62qlsQQcQWHAI8s3jq8B70MDxFE3H3Vd+9BIBnj3fjgb5hgVWFpx" "kPLg8A+3QzcMRhgKREMjKKzKK608dLirR+NF91a86dmNhvb1cFQOCwDEZ8JjABz+gRogojD0" "VQNklTXckABCXeI0l2puU4ceZOiQTYBefV9krJRVioKXPFGqyunhiioxys001RfOkiCPIzRN" "1V/Gqsu4EcvjYHgoaAxyOq1rEQNEJuQOdhRh+5vXrDD2t71maBy0UlYmPOhjUypcQR5HEDyc" "Vge5GOUurTgkeIZVUY7dUc6QcOUGTHIGRxYrDa02NEDGOR/zGBIdj/WU3YJ0jMiMx6Cbp9Dv" "yC4MPrgac68sxqHs6TiTNxPb0hdjwb392O/IwYmmMsv30OqDlMclpUCOvvFitjvVKtVN5Eor" "XW2l4SGqw1QegaqrgPoQ5WGDQ73OoeAh6SoTGvxsVVsFq49ALCzWI0qk0/x6wxO8/+XP8Otv" "v+FKq3/55tecEpLRG5KyovQNHdChXeWkOkg1mP0docrDVB0yoFB8DjHIJV0lhriAw1QbAo1Q" "Q1t8CUkxmQc/XeWeQj4mIZ8vX2t+PkGDUlUEDvpvQOAgqJISE9Uh8CDPI9T3MNWHrK81q6/6" "Bkg8YuJvYOeplZixYQimbBqIaRsHYPq2/ryznEzyBbuH6NTV/iFYdmQIG+Y0gp1SVjxF99Ik" "XE85gPiMk7ifHYW0ZzeRUXgHKYVnkZh3DA+KTiG99Awe+07psSSNUSh6dV3B4yY8vdGoeHsL" "FT134Hkbq2BwV6mMBE5Z6dSVBQ8yznt0z0dJ+2kFn9OBEe0KKOSFFLQc5llXNF2XfBBKXxE8" "kjxzeWRJEjUUlk/jKwGFmgXJ50ismMJDElN9M5Dsnc7geGCV7RJAKAqaNqD+7SUVF1HTew51" "PRfg6zzKwxIlhWUChCMEII98Y7Vxru4JGtr3GGOksMbYKSzaOtigwNHUcxwveo7h5dvjqO3c" "q1TGmID6MADC9/5hHLrrfJg2zL3DbK/DNs4t/4O9D+pA9+iqK0/DTLT0HkBb7168frubgfJB" "CssOpUBmverSo9QVQDQ0vtZj1WnAIT13vsW6jrfY0P4WM+pbdPmtVFIpeHxa6LWNcRluyIqj" "0PQ2pI9Dp6y4CVCBQ9bHakO8xAq3HdQIaKaqCBo6ihgUOgo5aEKudI/Pr/IpSEi66g0D47BS" "JYfaX+Fwm4rWFqxtrMEIdx6X5DIojLTVSGcg2Bh3PeEYaaSqzMoqSlONtKAhnocoDA2MkDAX" "QRVl8H6PcXkPMTw9GkPiTuKLywfR/8xO9Du1DYMvHsTQ22cwKuUSVnmycKZDA4PhYaWvTrzx" "YX7xQ7vyykxZSYmunbpyxdtmOTUHcoMgwcOtFchcd0CFUPqKnm3lIX0eBjwIHLrHIzgkdSXQ" "WKVUyKaSWBT01uLXv6eptL9j5fHLb3/DB2lqWjIy+hiEKF3lfaWsRHVIpZU5n8psAjSrq2Q0" "ujmkkPwNAof4GrJnQ5r2BBj0M4V6EnTQy2EvQYqBQp7lc+jzza8xQ75OgCEeh6k4JF0l0BDF" "QdAV09ysurL7PhLjOcyNgfYE3fjbuBRzHst3zcC09f0xab2Cx5YBmLmtHyJ3DOTlT/N2D9T7" "Ow7oEt2VxyMYHqvPjsami6Ow53okLj/YhsTH5/Dg6Xk8zItmeOQUxyGnPBpp7nPIKD+DnMpz" "eF5/DnlNUXC23ERxJ+3vuGONYg+EnnF1y0pZxdjd5lXvbjMsXO1nkVq5TimQKNS815N3BSKU" "ysqqX68bBqmjvDxSKZE5yK5fwUMSE5XaeFCh513Rjo97Sj3cq5imnmfjkQJIEnkcCiAc6nO5" "XJdN9KnwtB9Gbfd51HdfQG3vJdS9PYPKjpPIqZlnp67EBzFLdx8Z6SsCiKSwGCYWQOia5RvN" "18deitFKbcxjeLx8r+HxqveEUiFH8LxqPAMkVHWQ4giMK4lgz8MEhg0O/xBbhcjcK1IfBIrS" "2skKIHsYIM1dm5QCGaLB4R/E4fBr5aFjAD4Z7n+JJa099iKnNa1vGRo0l4rv27t4Ui4pkFHe" "OlYan7Lq8GloWOb4Z0aq6lNrMm6/gjK7osoMUR+iOCRFFVRN5dLjRwJpKg0OAki4y2EDhMeN" "yErZgnwMUSpklNuBzS+bOYXF4CDVoVTJwc7XDI8d6mNTy5zc08HQcOsgWATSU88wyvVcl+W6" "n1qpqmxtlrtzMa70CaaWPse0sueYXPwU44pzbeVhwmO8Uh4CjvEOisygLYKB+zSMLUzB6OwE" "jEy9gZEPrmBE0lWMSL2Grx7fxuTCB9wguNLzFPuaSnHytRcnXnmwp8mNBSXpmOpMZHhIuqov" "gBA8KDQwdMwq1tfZrDYSsLj0HhaV3A1UX7nv2ACx51sVWxVXBkCkLFcAQvAQgKxUCuVEbSbq" "ftRmj0ensSHkO9DBSIcgXaXKig5resffYO3uMLvKBR6h86xCBxuGmuQy3Va8DmncM+dMEaxE" "bZhKg6AhCsE0sumgl5ADXw59CnrN/Bz6/T4W9LkSoeAwFQelq0RxCDhEdQg8pOfDbBwk5SFd" "5GyYx93GtVtXsOvUOkxdOxhTN3ypY3N/zNw8iOFBDYJz9g3kBkHq8Vh0KALLTw7GqhPDsebc" "cGy6MA6Ho2fj/L3ViHl0GIlPziItLwoZzjhkq/8fyvMkorAyUR2Gl5FdfRFPG5TyeHkZzrbr" "KOmKQRkpDqUyKt7GsPogmBA8Kq2GQVIeFF57PW20Uh7neIPgg6oVqKbSW0p90QRc/poo9kMe" "1axiaFCz4L2Kmbwk6p53FgOE4r5nOjLVawQSggcpEtnt8cCquOJQH2OT3FIgFW2HFDTOob73" "PGreXuB7X9thZPojGSCSttIAGcvwSLPGlogC4d4PSlX5x3Ho1NUYGx4mQIrqZmn10UsK5BRf" "/W822Ob5B6krO2UVwUHGeRA8RIEYaSyCSb4d4dxAWN40HVUtC1BcP94y0TVAHJXhGhw+AYkC" "yKfOWkR4mrHoVae1i6OXU1YMDXWV4YbzmtrRz+ENAMShofF9h1Ycn1sluZ87y+w0lU5flWJY" "mR8TvdWY4q/GJPXHOVz9YQ5g0zywh0PKcUVt8OwqpwmOQIjqGFIUuApIBCaTyl1YWV+D7a+b" "sK/1Faesdre8wvrmOp26El8jBBxabTwz4klQECiWVLqx/UUN9r9uxKHWeux5XY0NdRWYrmAy" "xoKGBoikqbIsgGTaAJElUEHhTteraAuTMaEgCePz72N8YRKPKJniTuPrNG4QTMGc4jTMKUmx" "jXJdrns/UGXFIEm0ATJDQWKm2zDL3XfttBXBYr3vIQ7WPcXxF4U41pSPg7VPsNWXriAR8D0E" "IIF+j2i7VHdZSbSKW3aFlagQmm2V8NqJ9//yU14zS/Cgg57e7cvIDUrL0IEsgxDp3X+T+ri9" "+Mkq0SUFISPYBR7ieZijR0Krq2S67cdUh6SqZDWszJnqq/rJTCfRAU8/u6SVRCVQ0Gvmx+VZ" "4BIaH/teAg0Bh6k6THCY8AhSH1S6S53npDwSbiuQxOJObAyOXTyApXsiMWnNQEza0A/TN36B" "6ZsUNLaG8fbAmTvDMGfPQDbLlx4ehEWHh/D+jrVnIniK7paoqTh2Zw4u3F+Fy8lbEJd9GKl5" "F5DlvI3csnvqXW0KCmsS4W5IQ27NVTxvvAzHSz0QsbQ7BuVvY1FBZnjvHQaIryfWHs3Ofog1" "YVcPStRBi6DSqldxmW5y9Ur4uq8Era6t4R6RKKRVLbVSV5G854NW1JLyoLhfNpVTWeR9EDy4" "TFeBJKNmkR5PYgAk2e4+1wrE8WKTTl0pcBBAGt6eVa9tUKpD93xogBgmugJBeojvwQrE8jwC" "oYFhAoQaB2l9bcXLDex9kAdS07FNHfiTAmkrgoYJEWvfuYbIUMtA18+62mpYkIHO8KgczFFQ" "qSuxpApL7m2AUAlvpYaH0x9uK5FPqJLqe0XVCC+pw+Tql5jT1IYlLd16vLpSH8tb2jGz/hUG" "F1czNGQXh6SmPrOCjHEdZQGloT5ndKkXK5peY1trN3aq77e9vQPrXr7GzKoaDHMX23vHJWUl" "0BCfQ6AxxIpBzkIObgAsKrRjkEupD5fMrnrOJbkjXXmY6nNhbmUZ5lV5EOktwWi3HkcSWmkV" "SFkRKHKU+sjltNQY60rxlTMXq2vKlYppwon2lzjZ3oxTHU043daI4+0N2FTvwUQFGAKIVh6Z" "dgg8NCgyjEjHBJdEGiaqkE2CNJ59sjFpNzCaPTmww9wRWEVrdpdriOjQ4NBBimNucQIHgYMA" "srP6Ma60VuB6hwe3Oim8iO7y4XpbObZWPgyMJimxfI6SW7pZkMFxy24OlFJdKdclo7y4twm/" "+O0v7dWtBAJ6Vy9GuaSszHWzoV3l5kiSUHgIOKSL3KyuklWw5oBCU3WYTXvmbo3QZr1QD0Ig" "IR6EHPChIR8Xs1u+jiIUOKHfU76vlOUSNEJ9jlDVYRrmHzQNJugqq/M3zmHz0RWI3DBcwaM/" "Jq7vx8pjxuYBmL51IMODmgPn7BnE/R2Uslp2fAiWHKGU1TBsOjcGu69G4lT8ckQpeESlbsTV" "h1txJ2cvMhzX8FQp2EJfKlw1yShpTobrxT08b76OotdXUdp2E2VdBI872u/otRZBWWksnzWa" "JLDnQz9T+srVcRqpVau5u/yudy6S/Uu5abC46yyrDoJIzbsYOFoOKmjM16mq8jkKJouR5J2p" "jXNWHkvhfrWfZ17RuBJSIZk1yxQgqPJqot3zkeKdHBhXYgUtiXK92g5vxzH4uo6g+MUOpT6m" "c7oqlVNSk1WIEiGFMQWFDUtR8mozips3Iq9mnoLIBFYjBA6tQL4y0le685xgQkuiqNrqmYKI" "s34uXI3zeSe6dJwLOLjayiv+x3AUVk9G+YuFKGteoP43mK6+ntJaht9hle7a99R1bgGE1IeU" "9HIDIaWtvOG6+orTVwM/VCDUxyFTcskQ71dSgyHldRheUYeRnnoMLqtGP2elZYqX22rDNsQV" "MEh18LgRujqlh8ONiNIKrHlJs6g6sKOjk2M7jRFRz9tb27CssUkpgBLb6/hQcXwIkHCXoUCo" "f4N6P6iLXMFjqLtQB/d0WHOq1L3u5cgLzK4yqqzoY6FKg/o4CCAyt0rWzM7zOHCkpZHhcaKD" "4PFCQaSRIUJx5E095pTnKfWRGQQPGyCyt9yKie5MAyBpHAwNCVdg/azAI3S2lY7g7vK+ADK3" "ONH2Ohgg7niO5eUpiGqrQHSHX4WXQwByu92L86+LsKQk1uj1uMX9HotVLLLUhznbajGNYHfd" "RPyLIrz5+Tv88re/wre//Q1++Ztf87t+OohT0z9MWcm6WTrcxe8g1WA2BxIgPgYOUR1ikhM4" "RHVIdVVfqkMm2wo8QiufQqueRAlIGknUgBzyohAkpDpKvobChIz5uigMs6JK0lQfA0eo6ki4" "p+K+ZZYn3mXFQWtnY5T6OHh2F+btmIgJa8IxYW1/TF73JSZvHIDIrV9i+rYvWXXM3h1m7ytf" "fGQoVp5QCuT4cN5XTn7HwegFOJ2wCheT1uNq6ipcf7Qdt7K2Ie7JbqSr/+3zqpLUYZeO0qZ7" "6uBMQuGLaDhe37K3BxI8SH3YE3W779hmOc+14kbBaH6N1Af5HqUd55FSswbxntkc1Ntxz79Q" "3c/BQwWC7MbNPAwxr3kHr6Ml5UGpKlpZm0y7PxQkknmy7lJUdJ7hZkFaQeto3oUsBQ/qOn9g" "gEJSVqk+Y+aVR/d70LDEHPX52dVzFQim26W6tmluKRFKXbma16O+8wSaes6qOA1P2y5k+ycH" "NQ5qYASuFAwPLtcdHZi6K1VXRs+HAISbBhVA8qvGoa5jJ1693c9BwxMLqscHAFI5VMEhwgoB" "iA4NED3ChO6L/IMtgIR9AJCAAqEUlqvSXhX7PUpROSxznIKqqKx0lYZHud09bqsNI2XFuzic" "EsWIrK7FtrZO7OqgaFcAaed7nkml/qhpVtXql68worTEqq7SFVVSWRUwzC1gGCBhYDgLGBZD" "XHnWtQDDlBKhGO56zmFXVtGzjCFxPbeVR2iqSsPjqdEcaKkQ12PseVWPk50vGB50Pdmp1Edn" "s1Ig9QogDQyTJf5CjHVnKQWSpaGhrhOcVljg4FSVOwANHekBgNiKw1Id7hRrxlVS8Gyr4iQr" "tHEeaXgglLaa5bbGlLgTbK+DwgTIvobniOn08X5zAgfdx/BV30e9KcHqikTtd9id5TEMkUWW" "6iA1Mr9Y7zXf5o1HyftG/PhX/6RXwn77a/z6V7/i1JAcmnQom1VWZlc5HfZmia7AwzTM+wJH" "qM9B4JCeDlN1mJVV5mBCmWwrTXp9dXiLGjC9Bwk61M1n+rh8rgkYEyzmcyiMQv0NExym6tDw" "sAByLyFglsdr45xAcjnmAlbtmY/J6yMwdvVATFgXxmmrKZsGsPKYtb0/D0OcvWsI5h/ojwUH" "hmLBwSFYdXKIAoe6nh6JLZcm4NideTh3by0uPliHqLR1vACK4BH/dB8SC/Yjufg0MjxReF4T" "zWtnC15ch7P1Fko7YxQ8rrPqqOiNRUV3PMPCT+kqy/eQ0ez8utUoqJdBXUFq7VrEVWh4JJD6" "qFnM8IhXyoK8DWoYpBW15HfoVNVMvn9Uu0KPZi+frtTINDjf7OOmwRqlVmhkCXWel7Qd1lVX" "3ql2ykoAEgilRnwTOVVF9zplNdGquJpo+x8CEIJKpn8SGrqP2fBoencWVV1H8bR6ltUsONbw" "OwQg44IAIrOv9NTdEQwQ2+8I8T/IPC9tmo+W3iN4/fawikN42X1AqZfJDBAxzwkeokAKKoca" "Hkg4QyMYIINZbXD6igDiGxRkoDNAxpVW4rtOH75jwEPGjnxmz6jyMEw+t4DB8HCV6qBnl1Yd" "5GsIPAYXl2JN02tWG7s7VXS1M0QoZMQIzaeikSOz6mpseIQXa5CQUS7VVkHgCIHHMJdWHASF" "Ya7n1n0AIOxxuPM0JJwaInx1BMDBZblWlRUpDwlJXVEPx7SypwY4XihwvNTwUHGmvYGD7tfV" "lmCc65EGh6E2AvFhysoMW3m40/Q+D4JHcaq9RXCaO5kjCBwlSRwzXSZA7iuAJOlGQcvvmFV8" "NwARK860uFhpxHRWauXRoeFxu92DWAWQqwog671JGhisPkSBaLN8obXXg5ZAnajOQPs/vMOv" "vv0Vm+UUBAF6556clsoH8XNjlhV5DpKyInhIyurfg4c5LddUHVJhZZrkUporqkOqq0yfw1Qd" "5k4Ns0TWrHQKPdBFCcjhTtEXUP5YmJ9rQsn8nlJdFQDHvaBS3bjEOMTfi+dmwQRrY+D+czsw" "dd0IBY1wfLVGwWPtQKU6+mPq5oFcokvVVjSGnXZ4zN0bhoUHh2HRkcFYfJxGkoRj6ZkR2HFl" "PE7ELlbwWI1LyesRlboZ1zPXIPrxbsQq5XGvcA9SXSfUoXoOjysv4lmdrrRytSn10BXLJbqe" "7psKILGsQAga5H3oVbSx9mZBGVNCH+NO8+7LSKtew7CIs8aTJNcsxV2v7janabs0pp060O/7" "ZrPS0PCYwWqDdpxTiiqRhh4q+Hi7LvHYEpq6S53ndeqeAMIqg9NWAWhQX4d9r2CQ5pvEr6V5" "p+igZwURM22Vbs++Go8nVXMZHM1vz6Cx95y6nkNN1zHk18614DHONsuzfWODFYilPuwdH76R" "drDq8I8KKBC69+slUb4XKxkeNDSxpfewBkjNRKuMV8AREWScE0RMYBRY6SxRIAyNqjBtoFsA" "cVaGMTycCiyfZL5uwYySGvY2WGlYZbm0KZBTVS5dWfW54W9QukqUhoZGMQeV4UrD36jyCmxu" "UUqjU0GiUw8zpKvc7yWQdOmO8bm1NQyLcFcghljKwwQHpasEHuJzSLpqKKuMfL7y3CpHQHXo" "AYemx/EkqDSXPA+qrGJwWJ3idJVucurnWFbtxqmul5y2ojjT3oRzCiRnFVTOdjRynFOKZEt9" "uZWayviI1xECDXeqDuu5L3AINKYpaEwLUR08nqRYqYxirTbMyitSHhQmMOw0llub52ffuBU0" "PIjp9utQ0LjN6SsPg+RKWzFWexJseLD6MCqsKHW1vjwOqe1l+Nmvf6FUxzc8DPGf//lf0Piy" "EemZGfYE3VCjnFSHdJWbi5/ELJdKKwlzL4csY5JJuaHpKnMFrLlPI3QcuixjItVhgsMcCRJa" "HhsacoDLsxzwApa+woTCx8KEhPlvmR4HpafuhvR3xCRE42L0OSzfuxDj14Rj/NpBGLs2DOPW" "DcLEjWEMj2lbw7nKau6uAZyymrd/CBYeDsOSIyOw7MRQpTqGY9PF0dhxfRbO3F2Ni/eX43LK" "JkSlb8bNzI2IydmKhLy9uF+0H6nFR/DIcxbZNVfwrCGKzXJXWzTKuuO01/HuOsODejwYGL3X" "+ErPkqryW6krn7Xbg8aTZNRtRGz5HJ6oS8CgVbQPqhdqJaKCYEF+B20ZpIoreqZZV7RhkIxy" "Nsk9Op1FJboytl3HJV5D63i9U3ea2/CgEl8NCbo+9E3V9xY80r2TrJhgRwAgE9g0J48jr3YR" "q4/G3jN4+e4cQ6S24zCeVUfqRkHvV0aMZtNc1IeMKcnhlbQj7LHtTwxwhAapDJp59aJrv4LI" "UQZIbcdm5KmvzTP6Pux+ECvyrfSVCRBRI30pEIKHjoFwKbB80vW2B8Xqndp6Xx0GcPltRVCq" "6nPL42B40Dh1Z4kBkNAeDg2Qfk4XJni9epx6p6U01AFBYYJkX6cedEi7OQQgQ7lE98OUlVYc" "AeUhMcTay8H7OOg1lx63Ttv/hrufWErjSaBr3FIdXJrLkRukPMZIWONGpIt8fW259ju6tOoQ" "cGiIBACyua4EE4ots5x2lbuCPY4gpeHUAJlUrMFBV1pDS+CY5rZUR3GyDZDIkgdB4BDvQ6bp" "6qorHXPodU5d3bX6OwQigQGJdD3Y+Ez7Ht0EDr+Gh4o76jWKcy0FWFIabaevpFGQ1Meq4mic" "rc1E7Q9beaMfpayoPPf9j96zp0Dv3CVlRQe1u7QEFT5vkOqgA59M7tASXQJF6MrYvhRHaLrq" "Y4uYpMJKRqELOEIXMUlqqa++ir4a84IOc6l6CgFKKFgELn3BqC8whZbjmvc818ra7UGK4+qt" "S9h5ehOmrB+NcWvCNEDWh2PShjClPIZiyqZwTN8Wjkgq0d0zCAv2DMS8g0Ox8NBQLDlK49eH" "Mzy2XB6DozGLOGVFK2ejUtbhSsZ6XM/ajju523A3fw8eOA8ireQosrynkVMbhWdN1+B8dZU7" "y0s77rDaMJsECRqBHR7/H3PvAV5ldp37M44T+8Yl9j9xxv1e24md5J/Enhl6F02908vQy9A7" "SEK9S0gIgQRCAqHee+8S6gUk1HthYGAYYIpn4lxn4L17rf3to08axp7cG9vJk/V85xwdhDzo" "7N/3rneVcG22VaghbcXVV6O0STAQGR1HOF0lJ+va8JDEm41b5E4PoTz4KiBCJjmrDwGZKDLC" "b1mz+rheYcOmOcWNW7bIaHkTNf1uaB49L+Dhi9aJ87gzfgG57Xs0BTLpexA4VCjFMRUgEhaU" "wlKP1a6PRPGYzPGsRjuhOBzRNirTV3St6z+O9HpT2ShYu4TBMRUgarfHEkPaSh8ZLwNH/UIZ" "WuMgmeetfQcZHkXNJloj4WQpb542+0oCZCZfSYUYgFEvzXNpos9mv+OzAJHwYIAMjAxgcGQY" "LeJgd2u6jcXl9TrFMelzKGj8S5FUHQoWb5TImN4IaFxXi8MEj34tZdWnRb8EyGnxgadBh8cE" "ZIxrqriy6mWqg5+XTEJDeRzzdCkrZYqT6U25/h2VfjhZfQqbqkIYGipFNcXjUPDQALJE8zom" "4ZGm6yJP5TJdUh0EDoIGwcJ7qJ2veoDsbCrB8hIJDgLIqpekq6TKUNCI0UIDCKkOLUxLJUAs" "DSkrmaqa7DKf1uuhAEJVV9qIkskOc6k87HQAoQ7zbTU3caG/WqatBDjClQIhiAxW40Rjonif" "tse8ItRQnnugNgoxAzRy+74hZUXltKQo6ECmA5ju5smIpjt9Shkpo5w3BmqqQ3WVK+Whh8d0" "xaHfG66WOOnXv+q7yNXoEQUOvepQHd4qXaUfB6Lv5J7ekPeyhUzT42VAmQ6W6VCY/tr07/Oy" "v0ffVU7goIZAB++T2HDEFqt2zsXy7TMZHiv3zOb0lcne2QIecwQ8Zgt4zIHtcbn8icp01zku" "wCanBQyPrZ4LcThgFc5dXgfv67sMfkdQ4l5cSD2I8KzDiCwQd+0lQnVUUw8E7Sz3k5VW3RdQ" "NhCMysFwWabLlVYh0vsYCZtaoqsBZNL7kMMSaTxJdscpcehv0NJW0usglXGjdh2u31rNPR4E" "kejG9bhZv1amrW5JgMSI98U2rGHfQ8LDGolCtcTV2iO34y2hQnzQPB6INmpAHHZHStMmWbJr" "SGGZTAEIjygRkVBjKoN2mbPiMGaAJNYq43zFlHlXBJLCO5tQ1bUfNT2HUN19kJ+rvo/UumVT" "g2BSuxjZ9cuR12gh4LB8ivrQp7CmwmM+X7MbFnHFFUVR40rkNRhpnehztfSVbCokxWHwQ+pn" "cxWWPm01CZA3JgGi9YDQYwKIggcDpKa+hj+EQ8MD6BkZxE1x92ZfUYtflVQa4EEeB1dXCVD8" "svSzHeOGzvHSEg4GiFAgtAmQoUHqQ1MdNCX35OAATg3J8eq04GlZZZlUH0XTPY78yQorLVWl" "vA2VtiJFQepjed4NONYcQGi1Na6VLkZxhxGCWvZgeXmyTnFkYElppkFpGNHj0rTPDDs0KpNh" "GHgoYodQFpPw0IcEiLdQJx79LdhUm8MAWWVQHQlCZSSKiDekrPQAmZ6yYuXB15vT/I4bBqN8" "crLutUn1UXZFRISWtlIraMMN6So134rgoULNt3Joy+byXVIcBJDwoRqGh3dPAbZUXOJRJGq6" "LqkO37YM1N/vwbMPP8BHn3zMI0nefucBqw7lG6iUFd3x0wFOSkDNslK9HQQBVaKrVx4q6PnL" "ynL1Psf0dJUeHJSuop9J9XPoBxIq1TE9XfW7GvH+M4uYft/B//u+rv+7XjZ+RD2mxkDv8x7Y" "eXoTTPcuxrJtb3C6iqBB8DDeI9THvtkwe2uuAR52J2bB/uRsrHeYhfVCeVCVFcFjp9diHAu2" "5RJdnxtb4R+zB4FxOxCctAuX04UiyJV+x42ykwIejsho8EbmbW/kdwahtDcU5UOhqBoJEXGV" "Q6qPS4YRJcrrMPgfWp+H6vmoGTmP9PajrDQIHlSySwCJqt2AzPZDyOs+jcIuB+TdPYnMtr2I" "bdyAa7U2Bnhwz0ejVrZbY8H+R0z9ah5RQo/j6wVE7uxDVZ8jCjuPIq1VwIMrrbTGQU2FqPSV" "AohBeUwByKRpnqRBZApMamSPR1qdsVAdJnzlsl0a1U4Gee1SjtQ6rYlQKBBqHKzr2S/UwzHU" "dO1AToPJFAPdMPuKTPO6xQb1kd2wQEadah6cpwFjnm7e1TxD7wepjoLWWShpn4f8hjkoaJis" "wtJDRKmO3wmQ6LhoFJQUsPynVEL/0CBKeruxt7aRU1qUpiKA/Iv4EP6rQWlIYPyqpFRTHxpA" "NCP89ZJirBSHxsH+HgYI+R0EDRqjLpVHP6uPEwPdvBlwcXnxJDiKCifTVFySKyureBsgVVWV" "aldViisez8lMwomCfSjrtUFG/UwkVbyOxuGNiOnczYcxwUOlqJYoaGggmTKvqixtSiwzDEBM" "xsaGQngMSd/DS4DEW1yVAvEabIM3VWF1N8GuOn1KbwfBw5jgoaWqKG01HSDmxbFcZcWKg9JW" "WnkuKQ+romhDs6BZbihME3xhFuctrj4wS/eDRcZ5mGcFwSxTXs3peWYALLMCYSGuVhl+sEr2" "hnWSBywT3GCd4g7b/GDYl10yDEPcUnkdTneycFEokTChKi4NVSKwpwg7ayMNfR+kOnaUX0by" "UD3GnjzAx1rKitbCUsqIgEGpHzUE8WW9HfqUlV51KL/jZeDQl+VOH0Ey3SDXr34lxaPf3KfA" "oTb36feGKxP7MyNAvgA4pi9g+s9s+nsZEF4GDfW9qZOcpubqFz0ddT0Aq/0rpcexQ/oclLJa" "uWcmg4NSVub758D86FzYHJ0H+xNzYH96DneWb3IQcW4uG+U0gv3spQ3wuLaV4UEpq/Pxe3Ex" "+QAuZ+6bTFlVHBEHpBNSG125OTC/S5nlV1E5GiyBMXaFgzrI+bkIaZxf1MHjsiFlRY+rhy4g" "4/ZxxLYIeJBJTns9uOrKTqib4+I95znqaYT7+AXuOk9uobW15rIS65YlV2JF1wrg3LJg74PX" "0hI8xGvUMEhgoX6PjLZtiK2zkqW708zzKZVXWsUVGeYUyv+Qz6X60EODHhNM1KRdmnnFc6/q" "Zee5bCKUY0sIHJMKZCly6s0EOI6jY8xdhCvPvqru3D7FDyFoZOiqr/5t/Pv4t7Ef/uFidGpM" "TV+9JgHCudNrEXwAqF3SFJ2jgwi+3Y6ZpdVCdVTijcIyw/a/l6kPgoaMQh5FslB8ePd0d/D2" "P4KHVB2D8qrbzUGDD+eXTktdaeW4+pQVlerSlSqq9OW5FL+MCBV3IzZoGtmK2kFr1A+uRv3I" "RiT3nIB5eRynrAzAENclZTJd9bsAQvBYppuga1aeAceuFk5jsYHedwc+A3SV8KA41l4N87JE" "HTziOVR6Sg8Ns7J43WvRWEmDEGkRlAAIPef+j5yLWBnnCeMEAYxUAkSI+Ho4TEsixHuvwFxc" "aTSJZfEVbUxJOA9HtNF2esh1tGHieRjPt7IvEo8LQrA6zR+rUzxgk3gOdjEi0j25FHfvrSic" "aU3HmZYUbKu+qpXqyjJdl9Zk9D0Zx/uffGDwO6gXg+7w6e6dDmO6q59ulOt7O5RRTqpDwYMg" "QQDRj1jXKw7lc7ysGVC/+lX1dKh0lSrLnZ6uUitfp+/NeBk8vsj61/9XeHyR3eTqe/PE3Ai5" "m9w32At2+82F4piFpdteZ4CY7ZsHi/1LYLJvPkz3z4XZAfH8kBbH5gnlMQerT83D2jMLGBwb" "XRbwTCtqDnQK38hmud+NA0J5vIkLiYdkyipnLyIKTuFmyWkkVB0Th6EL0pvdGR6FvX4oHbgo" "K61GwiVARmSfh0xPXZBw0ABCqSp6vWb0yqQC0fpBsjvP4Eb9VkTVrREAkfCgaitKXd0a9UUD" "DUtkeATzYxpjUjLgKns+KHUlgJNIfogAh/Q+rMThb8fpq86xx8hqGkBESTuCMpvgk1LHEZzd" "gKjiNuQ0ipuah0+mwEOlrqYDRFVdxdetMgBEgSNZvGYAiDZtN7VuBUNCNgsuNxjnVHlFQV+j" "a2XHVoYGwePuuAvH7ZFTAhRLDSpkStmuUB5/UHi8DCCsQCb9D67CopI/9QtKHyL6QPJCnfEh" "kD+S1XkX1lXVQm0I5UH7yYslQGYKVfKGAR6FU2dWUSpLXNe1NLHHQarjzKCEx4mhPlYiauHT" "ltttmF2ch9llsglQpa8YIOK5AsjcUnmdX5ovIJI/2edRmIV/DQsS/9A2aBhejzoBkOp+Y7Tf" "O4KojjN8gEtwZBsaBBkgVGlFaaySaTs6dABR3eSkQJaWihBwWF+Xi6MCFE69TXDpa4GruLr1" "tuBsXwM2NeSw2jDWVIdx6SQkJktzlc9xU6uyijFsECRfwyw7DKvivWGe5AfTrDCYFUbAsihC" "KpL8y7BI8YVpnJtQIR6wiHcVVzdx9ZGR4AULARyLOHeYx7nALNYZlomeAhCBsC28gDXFobAv" "DIWVgMJabTHUuopLWJMXwBCxFUCxjnfGmkI/CQ7q66iJRMrgLTz56Ckb5NQQSAuaSA3QXbza" "Fqj2dijVoSbo6mdZKXioEl2VtiKAqF6O6Qa5fpWsKstVW/30I0j01VWkOhQ4fld1lQLHdP/h" "/xYE/xXwmKp4IqbuJRfgCL0UgoPOe7By53ws3f6a9Dp2zoSlAMebZ+yw6+xarDluDNNDc2F+" "ZD6sj82H1YkFsDk1H2u0/o4NTnMYHG96LMCB81ZwCbOGV+ReoTx2IyBuG0KSDyE0bR+u5J7E" "taIjiC4/xaojrVEcaG2uKGj3Q1FPCMpHAmSqSgChelSqjZpRCZNb4rBnf0OV6QrVcGtcfr1+" "PJyfy8bByyjocUJk7QbcaFzP4CAFcuWWLXecp9/ZJ9fWjkjlQQAheEignNeAYcPzruSkXUvu" "/SC1kdK8QRzmvdgUnI/lTkmYdewmZh+5zjGHroevYdahSCw/G41Dl/LQ0Dsu01Z1ChiTRjlB" "g4IAkaTgQekrbabVO4u/g3dWfA/3V6r47pR4sOqzr/3OWP49PFz0vckyXQ0a0vOYLxTLAt1h" "/6M/THxGgbw+JX1lUCD6X9zo6Jss//v7ezBEg+eEEqkRauFgQw2WqAm5PK9Kdo/z+JFS2bsx" "eZWPSYVsbb/DJrpKYZ0Z7GffY293J2wb67BIAIMAIrvI8wzB4ChTvR45htCnsLizvDgTv4y8" "jANJm1EztEEAxAq3xw/h9gM3nK5zN4DCEFqJ7nSjXMFDKg+tEbAkRXaR02OtHNdIQIFSVCZl" "SbCpTId9VRqsK9I4NUXAWKkzyidTVjFTfI7J59GwyLsKk/wrME4NgWVGqDi8w7GzOhF76zLE" "4zBYJQUI9REAk6wgmGaHwKogTEbhZZgXXoJlQSisiy7CJj9UQOIig8KuKAT2ZWHS/ygWX8sL" "gn2mH6wzvGCT7A7rJDfYZvkIRXIeawoCsbbwPDaWyqGIa0uCsCbfG1vE+90qY9Hx7jA++rVU" "HZSuokOeAEHg0A9BVF6HMsrpkFfj19Usq+kpKwUOek0PjunpKlVdpUxyfXWVGkGili+puVWq" "GVD5HPpd4aq66rPLliJ+b2rpjxJKcUSIz6X2cwRfDoKj/xmsPmSOpW++gcU7XsOyHTM5ZUU+" "B0GD4LHXaQN2nVsDi6MLBDjmC3AshO3pRQIc87DOQcDDUYDDfS77HSdCbOF+dSs8ozbBN5r8" "jn0ISd2F8KyjuJp/EpElBxFX7oCUOkdkNDkir90JBV1eKOm/IFTHeWmUj0lgkH+hGgV5BLt4" "rpoEFUAMZbtCccg0VCjye50QUbMOUfVrRazRUld2XIEV07COfQ5OXWnKo+nti9zL0SCiasiL" "1QeZ5jfrbGXZbqWF5nesQe/bz7DtYhGORlWioe8+HG9WC3hEM0BmHY4SQQCJwKwDVzH3SARO" "XC1EWZevUBcmBoUhrwIcdcZT1IZ8PDnX6m2zn2HC8u9wz+rvcc/i7/C25d9/JtTr961+zo9/" "V9y3+AXeNv3ZFK9jit/R8EUA8l+rQIoaXmeISJC8phRIxGcqSuhDlVuQjw5xCNAdIH2Y+4ZH" "cKXjDtZU13CTnxqvPr17fHapUCDi4J+lAWVheTHWNDUIkLRhe3srtna0wr7hFowqCnXd4woe" "OVNgIb2P7ClNgSpoGCIFmehzUmIxL/AsvPK2Ib11D/LvOsK/5hjMC65I1TENGqRAjAwxPW2V" "MgUgFGrkyPLyxGmzq7RUlZphpfM6lDlOneTS34jhtBQ/LomCSW44jHPCYJJ6HibpQVgtftZj" "DVlwa8zm8GzLh7uIQ9UJsM27JEBzkRWIeW4IexsqrDJkWKQJQKQHwDrTH9Y5QbDLFxApuAi7" "3ADY5wQIiIhrUTDPtbIrE18rFKDI9hVg8eBYm+OH1bl+WJsfBOeWJBSNtOIx9XUIcBA8qIGv" "s6cbeQIWyuugA5pUB8FDrZolBUvpJbX0aXqVlV516BWHfrnTy8pylUk+fdS6Slcp1aHmVr3M" "59CD4/ftyfhTAYR8Dn1a7PLly3ALcMW20+uxcsc8GG2V6arlO2V57qq9c2Dy1jysPWGCfec2" "Yr/LJmxztoPd8YUCHotgd2Yx7M8uwXqHeZyyIrN8n48Rzl5aA7dru+EVtQW+sbt4Z3lIyh4N" "Hsdxo/wYYqtPIKXBBVktLsgX8Cju8kZpfyDKRi+iYuSCNMsJCsMhDA1uFORyXDmGnceUsHke" "wq/R4yryQRge1IPhiuv1W3G11g43BCxIdRA4qDyXtgdShRWlsUr7XBgYjeNajAiQCMWT33mM" "wUGwIMVBPgjFzTprJLVuRF3Pfdh55yGpugf//h//gYq7Y5hz9AZmHiX1EaUpkAjMPiggcjAc" "6zyT0NxzjwGiFIcCiCFdpVVZKU9DmeUT5j9jeBAgGCQaCF4GjwfWv8B925/9zrgn3jtu9vcS" "ICKy6xZOVlv9ToD88A8GkOKG2ahoXYLypnmaApmpB4i+fFB+uBJTkjk9QAfB4JhQI+IwKKQd" "G82N4uAmeBQYglTHbAEMAghfywowqzSfr6QwFoqvLyorEqqicEoDoFIUKgypqTLxXAcM/ch1" "/egR6vVYVJiOWfHiLuKSM6xvHsWapHMwSg/DQqEelkwxxl8ODEpRUTA4NKVB1VsUxmUpIpI4" "FbayLFGrqJJVVQQMpTzI0zCojvJ4Ls3ldFVJtDaORD42ywmHaXoITDIvwjRNqIq0QKwvjMCZ" "hnR43S6Ce1M2PFpz4X2nEN5tBXBrzcOBmgShMAgipDguCcURZthdvqZEdpeT12HPr4ex6mCj" "PFcoj7xA2GQLOGT5C5BISNiREsn0wrqiIFmeWyZgUhCA/UKFxN4uQM+jETz9SFMdH/+aD3ZS" "pWpeE6WEVHmuGr1OBzspBL1RrmZZ6VNW0xXH54Fj+tBD8jkIHCpdpZ+Wqyblqh3hn+dzvGxS" "7R87ZfVFAEKpKkpZ+V/ww/5zu2G1fwV7HQQPTlntmi3g8Qab5CZvCYAcnAObI4ux6awltjhZ" "Yd3p5bA9sxCrTy/G2rOLsd5pMTa7LcA2j6U4cN4MjuGr4R31FnxubEdA7E4Bj30ITT0k4HEQ" "UYVHcbP8LBKrTyKtwRGZ7efEQe2Jkl5nHlxIwxArxeFfqakN9jNoCu5ouJbKuohaTi+pLnM5" "nqTl7Vjcvp/EGwYbJminhzd3mRMwrgsAXBew4JJdzTgn9RFZa89VVgnN27j6qmbIW4DIn5VH" "SZcjT9mNb1qD6Fppol+vs8CNWgtxE/kminqOM0BsvbNh7ZmB8KJ22PtkagokmhXITFIfmgKh" "sPNIQEPPBKsNFVPgoakPmcZabjDEs5utBSB++vnKw0r/+Gf4YPcv8OGefxLXf+R4tucX/JqM" "f8S7GwVoLMT7zX8q4VG/hAGiwJHTuPBzAPLD/9q01jSANHbao3N4N+70bUFlyxKU1M/GjKm/" "wKrEMJKv9EGLFR++QnH4D1LN/qjMY98e7kP03dvYUFPFkCBFwtVT4spNf/RcDTYslQBRSoMH" "IGoAYSAIUKhgSGgAmfJaaeZLOsi1xU5aQyB1jC/IjsP8zETMz4/n5zQ992XVVUZlEhorS1NZ" "YbDqKJvsGqdGQILFVGBIc1zCJNGgOMyEIlG+hkl5LMNj0uO4KSurqIIqP4KVhjFVS2WGwjjZ" "D2YZF2GRG4YjNYlwq8sQ8MiBb0cp/O9Wwq+rAj538uDRmAan6kRsyBHwyAzisMo+z2GbHcRq" "wyo7QDwO5Kt1ljds0jxhneohriLy/Axzq3jsSJGExeoCX6zJ8YRdpgvWZnkg9E4u2u4P4NEH" "TzlV9cHHH/BmPwIDKQ2lOuiQVhVWNbeq2IOYvmpW3xioh4cCB0FDgYMUin6l7HSfQ79KVu3o" "UOkqVV2ldmiodJXabEiqY/q02pf1VvwpgcF/v27JEwEkNDwUJz2PYc1hMwGOOTDa/oahPJfA" "sXzvTKx8azab5OR1kEludXQerE8SNJYwOOwdBDzOCXi4LGa/Y5uXEY6G2ODclU3sdfjE7BXg" "2IPgpH28cvZK9iHu77heeQ7JtWfY78hp90BBryeK+50FOLyE2lBpqyCuspIpKTlRl1NX4jWC" "h+rzoBQVjWG/+ygNA0/LMPykEgPv5eLuwxSktB1gYJDCiGneoA1KlACJqlvNHef0tUihMK7V" "WiGhaRMSmzcbIk68h5ZAxTWuZnCwcX7LHAkNq1HWe5a7zlsH38He8DJYeWfC0isDNp5psHZP" "h5lzAuYfjZ4EiFAfFPbuCajvnTCoj8nQAUQoEjbL2fswQnrDKtT2HcG9VT+dojQ4lcXg+MVU" "gIivT8JiEhp0fX/Xz/n6cJ14n6VQISt/KuEhQvkfvz+F9YcDSPfIIfRPHMPA+Am0dK2RCiSE" "9gNclSWCNLlTfqAipjQ40YcvKTkBre2thpTWyMgoagd74NhUjwVCWUgo5GvVUrL8dtIE15r+" "SrKkqhCPadS6HiBTljqVZhv6NribvHSyj0PvZ/DYdZ3HIZsAU7VRJKkcZH4vEcBYWpwkK6oI" "IOVJDBC9tzEJkISp0CiTvsZKrppK4FhVGj+tqkqmqGQPhxx+yCW45TdgSr0baRdhkhwkDfJY" "T5ilBwughMM4wQ8b80JZefj31CKgoxqutSlwrk5hJeJzuxiB3ZUI7KvH2dZsWJWEwbo0fLKq" "StseSH7H6pJQDjLH14hYXSgeF4RgjVAf9gSUFDfYJp6FXY4H1lXQWBK5p/xUdbS4a2zHo2fv" "4v2PPmS/g1QH/TvToUwHMd3J0+FMd/p016+aAgkudNDTga8q+OgGQ8FDAUONHdErDrXYiUJf" "lqvv51A+h0pXqVHr06urlOrQz62a7nP8qVTHy1fITkZ4uCzNpSt93eeiJzYetcOKHfOwdNtM" "rrAi1UEpK24KfGuuVmE1B+aHZsPysDTKbU+Q17GAU1ZrTy/CeudlWCdio7sRdvksw+lL6+Ee" "uQeekZsREH+EVQf5HZezBTzyD7HyiK44Lg5JJ2S2OHAauKjXixc4VQ15SHiMXJVd5aMXDeqD" "YTIeYvA3asaDtOqqK6w+2h5EMzhGn93CyLMK9D7JRPN4JPJ6HHFVKAwyzkmFKOVBTYNxTRu4" "NJdSWRECHgSRmwIMdKWu8+u1Ml2V1LIZkTXmrDooSIm0Dj9E8Z1RFLcPI6NxACF5d+Cf1Qz/" "9HoEZDQhIK0ep66XY6VDPKexyERnBSIAQgqkvrMVL96vxafPSvHiaRX+7aNeDRha1K9Acv0K" "A0DyWqzROuqKKqNXcN980gN5EHMBD5sqRVRrUcnxTmMFfjt6B/8xIkP/+DdFEQyQd9aS+vg7" "DJnO4JSV3v8g8zyrfp5QJPP+6B4IbSnsnzgiAHIEnYM7Udo4CzN2BZ1FwKUg7mSlpqTLEVem" "/PLzB+/GNVzXRjFQykJV1IyOjmF4fBj5vR2wrCo2qIxZpdmGAYesJmiYoRZKXSh4EBgWlmXp" "RovI4KqpMorMzw3yMpSfIR9P7+NIYWgYNgGWJGoKQ6oLUiASEolTFIe+BFemo1SXeDyrDLrK" "iDWMGpHXWFiI91HTH4HDPD8KJjc9WWmYpAfCJNGXm/9MUvxhnuAF88IwnLtTLKCRhHMVSXBv" "zuTR6hcG6xAyUMvwcCdlUhGD07TnPN4ZlkmusEqmfg5PgyFuFXdOhDOsYmUVFRnka0qCZAe5" "trtjY8llViFccZXkgK1CnaR0l+PxR+/j6Qfv4/2PP+LqqvefPeM0EaV96EBWfR1qAKLyOkgd" "6L0O+fswWWWlgqChN8f1o0f0jYCU/pq+h1ztICfFQeBQBvl0cLzMIP9Tp6p+l3/C3oaABn3e" "ZHVVBC6EBWP/uZ1Yvnkup6pIdahucuV1kOqgdJX5wflCdSyA5bGFsDm2iI1y8jlWOy7EGqel" "2ORixODY4rUC+/xN4XJtF8PDm/d37OYputQYSP0dEQUncKPoNGIqDnKJbmabO/I6TqO4zwsV" "I0EivFE57MTeRcUYdZgHCmBcZrXBvocASI1mplPllaFUl83yEHS9m8bwGHtWjaH3itB8L1Ko" "k0soHfRAZMN6XG9YK8FRa8dVV9FNa3i6LoGCDPKrAhSUzoqut2dwcNTIBVDU38Gexy0LjDx8" "H75ZbVgXXARTj1wR2TB1z4KpayZM3FNh4pIG03OpMHVOxirHBMw7NlmFRfCYeSCMFUhLSwI+" "7X4T6LTC8w5bfDpwAs8/uC3+2xgbUldp9doSqLoVyG9bg45xD3SMeU5JYb2THY3H7z3Ce7Tg" "7L3JeW702osXL14a/16TzCrk/uqfMUCyGxfL0KkOAkhe3QLkf6YK64efef6b8R9Pef1jjh/x" "9ZPxH3F8rHv/xxp41Ht+M/o/DfCgx70jhzEwcUpA5AQ6+rejrGk2Zqz2O4j1ngdw7oIPwsLE" "L3R4uKFZ6aqmSJQKUfN86MNLuW7qXh8dG8bw2CjujgzC73Y9rKuLWF0wMAgU5bkCCColpYNF" "efYUcCwsyzCMFlH9GovK0gx9G3pYGGmw0ANjWXn6ZHqqLGVKNZVReZxMVZUpeCR/xs8wKU80" "KAwODRwECnNaGWuAhoAFKYuKOAaGeXmMYdChJV+vw7QwChZZl7Ay0Zuvq+JcYZx1AaYZ52FB" "jYA5F2GVewmWQoE4N2fA724ZAnoq4HunBK634lmFeDZkwbMlD8Gd5TjfUwW39gLYFYUK9SGD" "K66KgmBffAm2AhRryi5qGwNDYJfrxx6HrYCEVdI5rE5145QV7SbfXxeF0PZC9D8aZ5/j2a8/" "xIcCHPSL3idgQEpDTc6lA5oObDq8SXWovg5SCfTvryqs1ATdl8FDDTtUqaqXgWN6ZZVSHKqL" "XCkOtTpWX101PV2lZk3933aQ/6dj2o7xLwSTCA0e4vULoRfh6H8Ktm+ZsdqgWLzzddkQSF7H" "vjkcq/aT1zEPZofnGVSH9ckFbJTbklHusBRrnZdgg6sRNnksxTafVTgcvIbh4XGdZlkd4v6O" "iymHEZZ5BOHZu3gQ4o2yE0isPo70Ridk3/FEYac7SnrPoXwwEOXDHqgcdEPlSCBXWFWOXNbS" "VwoYAXJUyfhlOUGXhiSOXtZmXIWwWd77uABj4o5++Gk52t+5adj5QQuibjRQJ7m9hIe4kudB" "sOB1tEJtUNyos+MqKwZHnQU3CcbU22nGuWaa11jCO6MNC52yMOtMOmadTBaRiDknEzD7hIiT" "sZh9PEYAIwZzjt6UPohmopOBPvvQFczeHwY7t3i0NEbjRYc10LoQaJ4HtIjrsAtSGrRej/oV" "DA4CCCuQZnvcGXVjiBBAyECntNWDm4EaNN7Dw+FePO7rwsO+Tjzq78J/PHvA8enTB4bHFJ+k" "+HE66/7qv9cAslCGzvvIqZ/P8PgiAFHxm/FJRfLJ6A/4+ccGaEzGdEXzyaj2eOTH4vGP0dxl" "j+6RA2jt3YCq1qWyjNcu4BBWuWyHkcNWvOV/hu+EKJ1FpYQRuuosfTqLQEJ3qJU11ejq7cHQ" "xCBGxscwMjEi1EgnTtWVw7qiQIKjWKkNbbhhqR4c2tj0UlleS4AwqAvx3qXiffTasvIMAziW" "lit4pHAogCwvSzVUUEmAyBJcqoraV+OGfdU+AhI3GRg8aoTAUZ4kQaELkwoJDxNdqNJbff+G" "qVAFFmUy6DUadGhVegPGhZekOZ4kQJEWKK5+bH6bJfvBPEO8nn+RO8jNqTcjLxQ+twvh0ZgB" "r8Zs+LUVwq+9SEQx/AU4Au6W8mOf1hwcLrsGq3RPQ5C/QYCwTfeCfYYv7PP8sJrLcgOwNj8A" "63IDsL44CBsqgoUSCcZbAjT+NfFoHOvEk/efCWh8yF7He8+eyukDleW86Emlq+gun3wGOsRJ" "dahucjr0VVOg3ihXfoceGkpxKHioklz6Hi/bCqivrPq8fg49OPRd5PrqqpeB4/+12e+LQOQz" "f8fLXo+Q6aqLYRfg4u+EzcdXC6UxF0u2aj6HVprL6ap98wQ45rFRTj4HgYMaAm2OL4DdyUVC" "dSzCaofFQnkswTqXpUJ1LMdmj2XYG2CJ02FvwvPGQfje2MdbA3mWVfJuXM46hqsFhxFVeASx" "VWeQVO+ItMajyL3riqIeH5T0nUX5kJ8IH6E+yDR3Z9Nclur6c9qqcvyKUCQXBEDOS/UhAELe" "h2ocJF+EntePh6LncS6nrjofJKJ+QkKFyngLehwFQCbVBxvnjWuk70EwIXgIJULwiK610tSH" "BAb5Hjf56xb8vGngHaw+XyzgkYnZp9MZHrNPJfJ11vF4EXHcA0LwUACZXsY7RymQhii8uGtp" "AMiLlrl40bkOz99vM8AjrV52lyfWLkVmoxkaBk8KgLgJcPzMUH31ToijQXW8fXaDAS6U4pIm" "+j9M8T8mrwI+dlTG+zNkUcVVo6q8WqRTIHIp1O9VIKO/3yP5+DOpK10lF/15AY/pVVjFjTRU" "8VcobXwdM9ZdPA1Tz92YKX6R5xy3FXcv++ETEsCVIPqSQv5Akgl5PWrKyOnsnEw+ALhkUwCE" "DozukSEk3r2DYw2VWF6aI03wsixtJtUkNNRsqqlpqEmlQeAgWExCQz5WamNZeapBdRBAOKh6" "SlyNKBVVHIsj1Q7IaF6IzLu2eOuWJ/dvKJ+DfQ0BiFVaioqCH4vXSGFIU1w/3DDGYI4r1cEQ" "IUVSEgXzrGAGhWmqP4zT/AVAAmTqKtUHFpnBDBAT8TUywi2yg2Ep3n+mPhk+zblCfRTCX8CE" "YOEtntNj3/Z8ViD+naXYWRHFPR72hSEcrDZoFEmJVB2riwKxWoCDy3GzvTjW5fpgd0koQu9k" "o2r0Lu4/e4SnQm0QOChtNTQ2hDpxaFMaiA5juqqGQP2yJzUAkcBBENAb5QQK1Vn+MnNcn65S" "BjmBY3ojoH6l7HSDXD9+hNJV+p3gn9fP8Xnewx87daU+Q+FK2V8Ng1eAJ3af3QqL3UuxaNtr" "MNo+i1NWRrtmYdkema4icDA8DpJRPp9HkVgen89Gud1JLWXltAhrzxkJ1bGC4bHVeyUOBNvC" "+eoe+MUchX/cYQQkHMCF9GO4mLqXByFeKz6DyMJ9iKs5jZQmV6S1nEJ+9zkU9XtzWokMcwaI" "UB9lw46oGhIqYySCZ1xRs2DleDgHeSKkPtSMK4YJgcMw4yqQtwmSYd71IFVr/AuRzYDie6Xd" "3itUx2oGR4QGDfI5yAtJbduD3K4TKOw6KcB2kOdbRdVbCTVixeojtsFewoTGkdRZCgAOYYlL" "NsNj9plUAY8UEUkSJEKBEEBIgRA8Zh6VfSCsPnQAoTTWzuB0jNwJFQpkFZ63zQea5koV0roc" "zx9msBeSzB7IMkOk1Rshv9UG1T17JTysJETedtvL6oPigesuhosy1z/PRKegiqz7Nn+vS2Et" "nJa+kvD4YimsSUh8Mv5ZiKgUl3zfD6elsyZTV5/o+0AaXxOhG2WyNuQETHwPif/4G/DaERtB" "ajvYOOyAU4iPLCcMD9d5IpPTQ1Vly40b0YiNu8lpBrqr5HTGuARJk5BuMXfbsL++DMt0qsNI" "UxpSUWQwFCQYMjTFIWN5RYbh8WSkTsJCB40V5WnsaVBw6krAY1eVl7ijWYqMulmoH9uE2M4D" "fPjLklxpik+qjHjN44jXQePmZMe4DhwEDEpVWQjVwVEUbgCHSYofN/6ZCpVB86kskv0FLC7w" "fCqzFB8BDfE4L4h7N8wz/PFmQRg82/KE2ijn8G7JhldzBnybM+ErYOLXlovDNTcZDjb5/rIs" "l3wM7u/ww5rsAKzO8oFdhjvs0lwYHKQ8tleF48LtHFQNtmH86X08+fB9Hn5IQaY2gYFgoR+5" "rtJV1VVVhtJcpTqU1zE9ZTUdGqp7XJnj00tyVWUV3XToBx6qdbL6/Rz6rYDTwUFeh94g53Wu" "/w2qqqbAIyJMpoUJXgIcgaF+2O+0i2dXGW2VBvmyHbM5VaVMcgmPOTA+MJ/9Dq6wOrKA4UFe" "h+zrWMRex3pOVy3DZk8jTlkdDd0INxpFEn8SwUmnEZh4EBfTjyM08zDCsvYhqtSBU1bx1YeR" "0eaFnA4X5HWdRemAL8oGfVHa7ySu3gIcPqgcdmb1QcqjfjQSrfev4/aDdNwau6otiAqenHNF" "ykMAgoBCqaxb3PgnlQZ7KQPeDBQ5sj1QwOEUT9KNqLVheJDquC5URaSAQ1r7fvG9/LhxkKbm" "0swr+rkSmzexEkloXstXhoe43hRgCS/vxuyzGQaAUApLKZDZJ+I5hUUQmXkkhgHCHemcwpJp" "LGoitHaJQ1JhPn47cAgvbi9iBfKiZZ6ESNMcvHg7itNYKQ3LdWGEtIalSK1fgvSGFVP7Po7a" "GhTIO/GXcO/MeqFENnH8Omgrx0cXtuHj4O3a4+14/+AvWZnctxJqxfznMmU1DSCUwvqiAFGP" "KV31awGA1uJXkRL5/3F0lP+NATDvD34fnVV/jTC/b8H1xNeRFPFXGGv9Lj4ZlukrpUJKmmaK" "eJ2vpY0zpQKxDjwEI899mOX4JuaI/5GzjloKaWcBo+PrcTDwnLhrkhVakxAJ5x0EtD6TPsD6" "jWmUWqADgZvHJkYxOjGO4XsjaB7qx82uFmyuKmBvQq8mCCAKDJMg0cMj9eXQKEs1AIODfQ3p" "bZBRblMuPrgN1ki79QZymhaheWQLGkf2YnNZAPdlKPVBsCC1wRNwy+M4+LXSGIM5bgAFpan4" "egPWFXIToHneRVYVpsneAho+MEvyFmC4ADMBB3NOX1EFlgss04K5l8Ms1QPWAiRW2SGwKwyD" "de557BLvcayMhVNpLFxKo+BSeUNEDDyq43GyNAzrMzxhk+ICO/F9bBNdeYaVVZIjA2Ndrj/W" "FV1g09xeqJBNIihV1TDRhXtP3mFwvPvR+2yQ0y9zY3sbp4LUbm46oLPzJtNVpEj0JrledShA" "kOpQocxzvdpQVVWqe5w8E5Wqmj4pVzUCKoN8+sBDfT/Hyyqr/lQjSL5I8A2YNmr9lOdJ2L1l" "wsb4om1vCHhIaBhpU3OVz2F8YC7MD86VXoeAhuUJoTqom1yAw46Ncpmu2uC2VIBjObZ4LcNO" "f3OcvboDXrFHcD7pFILTHVh1XMo8irCcY7iaewCRxUcFOM6Ju+gTSL/tKFSHFwp6nPmALx3w" "Yk+iYsCDU1dlI+LQH3TgAYe141fR+W4m+t4rxODTatx9lMXm+C2t94PHlZCRPhaq2+0RKG7Y" "LiK/11mohS2Ib9uKxNuHkNF+AglNu5HYupmhwQAhGAh4kHlOUJFzr6jT/DyaxfdtmKDxJeeR" "d/cwEls2cJPgjXqpPmggYnyDDQJz2hkgs86mGlJYFDMFPBY7pmDHxWI4xpTBLb4E7nElcIst" "NIR7TAH8k3JRXpuO3wy4AHdMGB7P26YBRPw8qY0rOMhEJ+VBkV4vAUIDEbkXRJXv7lg8uQjt" "yXtTFqN9non+walFrEIYQCL08JgOkS8CkI91z389+gM4Hv06/uY7M/C9V19BoMs3+etP+n+I" "m5e+iX/6xSv42jdm4C/+4hV8+9szsHT+n6Ol8DsMEaVACBykPqQCkSpkhlWoE+aeXo+Z57bi" "jbMbMPOUHWYessRrh80w55g9Nl1yR4j4cNIgN5oAKiu1pDeiKrP0Kzy55Fd86OkAGtMOG0pt" "kUdyd2wIUR1tsKnWjO+yJF211GTT3+cBg5TGJCgmQzb+aSW3WjXVxgJ/lPTZoKZ3FepG1qJh" "eC3aJ07jdMVxQ6pKehkSGNT4ZyOer6lMhF1FPIOCzHIyyQkYKggalhXRXE1lkX+ZFQfNnKIx" "IyYJnrDMPo/lSS6wSj/Pk3GtxGtWheHcNW6Z5A7rosu8p8MswRkmlw/ANPw4LMTr1Oj3Vo2A" "R20STorve0yomP3xLrC5chDGYfthGrIXppf3wfzaIVjGnsQa8eetbp6AxZUDIt6CdeRx+NyK" "R/v9QTx+9hjPnj2T1VXvC3iIoD6e9KxMxMXGGnwOOqzprp8XPWnDD+nfTd8QqNJVqqN8OjzU" "yBECh94gJ/ioSbn6YYfTO8g/r7JK73Pod3TofY4/ikn+e0Pr44gI58+HKj4hxUGPPYM8sOaA" "JSsOSlct2TFL+hzUSS6UB6sOTlfN4b4OE22GFcHDSoMHgYP7Okh1aKW5m72W4k2fZdgXaAGX" "G/tYdQQln0VwxhmE5jiy6ojIP8uDEK8VikO7zh2pTQ7IbD4jYCE+G/0+KOx1EldPlA6eF+HG" "KSzZLOghAOLG3sft+5kYeC8fg8/KMfq0Hv1PStD89hVplPN2wWC5YVDnfdDsqvJhd0TVbUZk" "3WpE1MsS3Yg6e1xvsMfN5tX8+tU6G0RRSqp1LVddpd3ezX+WhyVOBDJEGu4FonE8SPw8Ttw0" "qNJWpD7ixJ9PbLRHUF7HZxTIrJMJWOaShuDMagz1JeA/7vnj0wlPEe54PuYhwg3Px13x6ZgL" "XoyewYverXjRsYzVB8HDYKIrgIwHMDwm01dyFLsCCI1mJ4DwmBICiN0/awvRpsLjZQD5FMDz" "Tz/F+3v/Ce/v+gcJELOffEaBZDfM52CANMz7T6SwpAI5tvdr+LMvz8BX/8cr8Dr7DTbU67L/" "Fj/6wZcwY8YMfEMA5G//Zga+8tUZeOVLM7DW8qsYafwew4MgouAh1cdMlDW9gRkLrgditvd+" "Vh9znTdj5sk1QoVYY+4hM7x+2BjznLfDNjYUAdejcOmq+KBoHxIuP4ycHH1CEFG7nFXzFuWx" "e7q7DSkPNlXvUcXWMC511GFtdQ5MyqTKoN4M1dRnAMUUZZE8pdx2eumt7M2QFVQEkvVp4i6r" "azMax7bxfKz6kc3ouO+EXTknhfK4zoa6cVk0w2NDVSpOtZfDe6AJfgPN8BlqhGvfLRxsy8Nq" "oQIIGGrvuI34s1bFUTDLvACTWFehOCQ0TGPOcZrKNNGDu8XNEzwENIL4axbx52ApAGGVGwLT" "aydhFn4EVnGu4mvesIg5g1VXD8As+hRsxPewTHaFfY4v1hYGY33BRU5ZrSkIkj0deTJtRaNH" "7JKcsDrVBdszfHD+VgLax7vw3vvvMTgIGnSlX1YCQEFhHv+bxMVJnyM7O8fgc6ieDr1J3t3X" "K3fE6NJVqr9DQUMPDqU4pu8gJ9VB4CAwkcfxuwxyUh2fN/Dwv6KX4w/pf6hR65yyEnHx8mX4" "hwZg1+lNWLZ1HiuORdtnY+lOGct2C8Wxd64hVWUoyz0sBx9anVwIm9OLuJvcoDoEODa4ifBc" "hk3ey7DdbxUOXVgDj9iDrDqC0s7icrYTwgtccCX/jFAcDgIcxxFTfhxJdc5IbzuHnA5nFPZ4" "CHAIldHngpIed5QM+ggFIp73u7ISqRjwFSrkLHsc1CzYK4DR/zgHI09rMfSsCn1P8tHxKAk1" "E2qvecDkHnNOUflzGiyqbiNXVtF8KwLHtTpbvpLSuMbNgfaIrLdhmFxnT8MWud1H5bwrWjkr" "/v4WHpwYxEqkpO8kouutZQiAUOoqqdmeVUhEeY8ASJYEiKZA5pxOxqmblXg6egMvBrcAfdYC" "EpZAtwVedJviRaeJiFXA3ZVA+zKOF+1LBUCWyPQVpbF0AHk+cUVOztWUh4IHgYOuWeK1CfOf" "GJoFuRck4DjuB5/keBAkrkGnOD5OcDfEbx8MSYh8+JjVx5PtWgrMjBTIgs8oEOoByWmY+59Q" "INIDUQD50p8RQGYIgPwVfj38Q6REfpvhQaqE0lelyX+NE2/9JdbbfBUpEd/Ck+7v4uORH0xR" "IAogFDPm3RAACXPDbJft4j/+Wsxy3IDZx+0x84gZZh00wexD5pjjfwircmNxPPEmgq9HMjxI" "lhNM1IcoMlKqEbpTpMoY8kXkoRXHBxUdLFy1MyHuXqnRbGICHaMDiOhowP66PB5MSNNvCSIE" "C1IUUlXIaikZCbJyqixJNvSVJ0y5siFeIU1xk3hxsBZvwK3BdagftkXLyD4ho/fCIjVQ7uAo" "lRv/tt1Kh2tPPQKGmhDY38xXivOD4vlwM5y7K7H5VpIECE3ELb7C40cIEKbJnjBP9ZXQIG8j" "xYOVhnmyFyxzA7lnwyLRjdNWJuGHYC5gYSUAYXH9jHh+AObXj8u+jrhzDBKTmJNCXZyGWdQR" "mAqoWEYchlWkiIhDsIg4KF57C5ZX92P99RM4KJTN1cZMdIhfwEcfvsej1amHg8BBHgcd6tQ/" "QYcxBaWDKHVFh7Z+8CGllQzg0IYf6lWHAoZ6XT/cUF9NRT0cqppKmeKqa1yV4upLcvV7yKcv" "dvq8fo7PW7j0B41pZbr6dO5Ug/4yLoWHwTvYBweddsNk12INHDMFNGYaqqvIJKd0FYGD0lWk" "OsyE4jA/Ng+WAh6kOGxOL9ZKcxdzaa70Olaw17HFdwV2BZri1JUt8E04juAUB6E2HHAp95wA" "hhsiizzYKI8uc0LiLRckNZxAdocXCrp8UNDpgKJ+LwZGYZcjqw9SIjRrqnyAVIc7Kgc9UTHk" "wk2DtWOR6HkvDcNPqhkgw09LuJO893ERGsav4daYn6y2EvCoH5dGetmQG2Jad3CTYFSDvVQg" "AhysPgRMyChngFBTIKuRtUJVyIVQWXcPseqgfeUKIAyRUV9kt+9k1RFdZ87QSGyyQ0KjLW7U" "myOraQRLXXO4hFcqkESscM5AanmRUBkn8KLPVsDDahIgDI+pAGH1oQMI2hYZUlgvWpbh04eZ" "BtOc4EHeB4EjpW4xXzMajHDf/KdTOs7vbV2At3cvw9vbFk7pRv9wlxxhQn7H/57oBv3fb+/1" "sPp48uYv+M+Om/8MuVrKqqBlBYrbzFDcugqFjUsNHsjUvo4fT4PHZDUVqQdKYR3d85eaApkB" "D4dv4MPB7+NmiATIv/zTl5Ea8W086f0e7t1+FRNt38VHA+L7CnhQCS/5IPoUVlnTLKlA5t3w" "x7xIX8wPdcRshw1447RQIGfXYc5xa8w6sApz9q8SEDEVXz8D45J0OJXm4mJCjKF7nXO8EbLs" "N1J8yJUaUdNaVX0+HWB090n58KHxUUP1zvDEGO6MDCGpqwXnmsuxuSYbxhV6cEhAGHo2DM+1" "kltDz0aCoRSXALIs6wosrh2Bd+6biKjagsCSrdiUdAymuddYeZC/sboqEa7d1RIagy0MjMDh" "Jo6gIRnBgw0411WBNVUxPAGXjHJKOZklu8Mi3YuHGFqm+rASscik8SReMCdoxDrC9PppmF45" "DLMbZ2ARdRKmkcdZaZjFnYXFjVOwvuEIy7gzHFZxDrC6cVqARLwuQCLjNKzjT4uvncFqoWIO" "FIXApzoW6d230PfOMJ48fcxrZJ+JoCttBaSDnQChTGf9qHVKGZHvoJY8qXQVgYNST/q+DrX1" "j76m9m4QLAgOejBQCkqfftL3ZpAKVQc/wYGgoWZWvayyavrokf82M6sitL4oTcVEUNpKS1VJ" "1XEJPiHeOOx2ALZCuVNJ7uLt0iAneCifgwxy431zDSNIyOfgdBWrjgUGr4PAQSb5GtelWO9h" "hI1ey/Gm93Js9VmFty7YwjlqNwITTyIkTcAjR6qOyCJ3XC/3xPVKN8RWOyO50VUccmeRddsF" "hd2+KOx0Q0G3O4oFPIp7XFDU7cQgKe31QnHvGQNAygbOcc8HmeVkjve+l4PRZ3UCIFUYeJLG" "XeX97xagQSgQMrtpRDvBo04c9FXDnkho2ydAsQWxzVsR17RRVlrVyWqr6CaZwiLv4xp3l4vX" "6mV3eZRQIzSipGrQRdv3cYGn7pKRXtZ3AgnivVS2G1NriTihQgggcXVmSG5ex93na4NLxQ1w" "JgNk5qlkmHlko6whBxg+YAAIwePlCmSFVCF3JECmpLCa5+J51xY8/6iTAZLZYIz8VjsU3V7H" "kdNkKV5bLgCyBG+b/UQHip/hYU0+ZwEe9XdPmY2lr7z67QePGSD/freKnz/aKN9z3+SnnKqq" "aLPB7cED6Bg7hY7hY2joexMlzSuR2zhPZ5Lry3J/NK1M90eaB/JDHNlHKaxXNAUiU1ilqX+D" "r3/tFQbLknlfRszlb+Nuxat42Pl9/HpQV8orQqatZnGUNr/BQJkxP8oP86/5YsE1b8y7cApz" "z25gJcJxxBIzDwqAvLUccw6bwTL+Apy6m+HVegvB2akIuxbBakQ1Rem71+kQoBSEAom6s6RD" "gw44OrjIF5m4p1XziGvP6DAK+zsR3l6Hw/VFMK1IMKSpCBAreFihVjlF14rJUL0bhp6O4mgs" "TbyApeHnYBx6GCuuOGF5RijPpVIluPtacxE0ICAhwDElhPq4MNTMAOHrQD121ySwSU5qQ8JC" "Kg2LNB9YpXtLeMQ6wTTGEcZhh4XCOMLgML92ipWGRexZmAjlYBZ9FrYp7rBKcYb5TaE4xGuW" "10/B6uYpWCY6wSblHOySRSQ5wybRERuyPOFYcgUxTdlsjI89esBqg4BBPRxPnz7j/gs64Onu" "Xh3GnKoSB7UaP6LAoWZXKXCQmqA0lKqwoqDXSFXQe0mp0J+jP0M3AAQLdfjT30X/rnToqz3h" "ND02JCQEQUFB8PX1xfnz5xkGBBcCBwX9bJ83KZduQJTq+G9VVRUxWdaugEK/91RZddj1IOwP" "WAhgzGWfQ6Wq1MRcUhw0goQUB40hocoqAofF8fkG1aFMcgIHl+Zq6SoCB6mOHf6mOB62nlNW" "QcmncSnzHC7nOeNqkRuiyrwQXeWH2FpvcdB6IbXZHVntnsi87cjj16m/I7f9lOzzEIoj/+5Z" "cSh7chT3nEZZv7tMYfU5o2rInyuvqLqqasgXHQ9TGRqD7xVxDL9fzbOtuKqKtwmGcr9HtYBH" "8p39HLTfo2zAkRsS41t3swrhNFWDLaetpPqQACFwRNZZ8zVWvJbSslH8nKd5fErNsBunrpKa" "1iK6wUqOK6kx58bBG1XiWm0h/o5TrFh809ux4JxqJEw0AOTF8FsCIFr6qkdTIF3mgIAHA4RC" "S2ERQJ7foQqsxVoKa654bAQIVURVV+SBVHTuQMvQSdweccLtYUc0Dx1FacdGBsh9AsiUbvQY" "CRDxmSVTXX1Nzbx632EFnj//LaewflObMjnGhP6s2d8hv3EZ2oYOoWfcUYSTCGd0TTiioXvz" "lBTWx7o+D/VY73/IFNYPpAdiSGF9g/9sd82rWG3xFXzrW9L3+NrXX8GqJV9GiMc30VH6Kj4c" "mISIPnVlAMjCKC8sjPQBXedGemBh8AnMcliD2afsMeu0LWYdMcacfUaYvXcZLF024URVBtwH" "78KzqxkBVYW4fPO6IQc8fQYQp7R0aoTuQhVM6AChA4/SIFwCek+mtkiZDEyMonWkH7m9d+Hf" "Von1NWlsfJO3QVAx0Rr+KEy1q1ml7N2gBj9Dv0bRdRgXXMWq7DCYFERKeJABLsKmPBpnusuF" "+mhkxaEHCEEjZFjC48JwPXzvFOFMVSxM45xleirNC6axrnKMeqonr4s1jT0Fi5uOEhaJzjC7" "ekwAwgHmcU4wFyqE01FCSZgLhWETS2rjOKyjT8A84qgESexpBgZVWq3O8GC1EVWfjeqh20Jt" "jOL+04d4/PQJnj173wAQ6r2glBGZ4XpwqJJcNbeKVAPBQL+ngyBBikOpDroSVOh9ajkTKRa6" "klqhx3T4q4NfgYMOel50FBrK4CBg+Pn5wdvbm5/Tz0Q/z+etkv19ww7/lND4vJ4OiotXg3ng" "od1hcwGKeQwOUh1LdrxhKMlV4JD9HAu4n4NUB+/qOLlQgGMRp6vszi7Shh8accpKjiGR8NgW" "uAp7gsxx9to2+CWd5Aqr0GxnoTpcNdXhLcDhi8SGIGTcOY/UNg/kdfoj+64Lex5Ffb7I7ziH" "oi53FApgFHS7svdR1uctTfQ+R553RcqjfMBVwmNcdpxTWe6tiQg034tB24Mb6HyUizvvJHF/" "B+3oUL5H7bA/0tr3Ia51J/eN1I8KuIz7c3qrYtBTKJHNmnFuy6W6FFKNCOVBUW/FMIlpJLBY" "c1DFVXLbJsQ12rHnQbs+rpYYI7zQDKG5KxGcYYSoog3i8HZB/ZAXhh5+AM+0FmwMLoH9+QLs" "Di9H450CARBNgeg9kF4b8XwLXgzsAvq2C7Bs5XjRs1mok01A1waO510bxZ/3wIuPh5DesIz7" "Pe6M0MpZZ3Tw1kA33hzYMnQC2U0r8WDlj6eksN6JCWKA0CqEx+++i0dvj+DBdX98kncZzz/5" "gMEB+n9xpdcYIPbyz4+Z/U+U3bbC3TEH9E44iTjHV4JJy+AeFDYu+pxpvD+aBpUfGjrQpYn+" "yhSAfDD0A9TmfgeHdn8NM3/15/jmN1/BjBmv4NXvvIItq7+CtpLvsFcyCZDXOXWlynlnmNwM" "wIIoTywgeAiIzL/mgfnnjwopaIfZJywx97iFTGXtW4xVR02wKfAwnNor4TnQDs/eVnjfqUdI" "chzfjU0BiAYROgzogKA7TDp0VN+Bml1EXgnd1dLuEfJHCCRjb49h9O0JjN8fR7+Ayd2xQeT0" "3MGZpmKukDJW86gM0IiTI0UoKqINQw3puZk20JBepzJca4JH5U3YCyC49lYb0lUECwmPRg4C" "yEVKbbUX8KyqMyU3YJOqpaeoFDfDh9NUFgIUJgIMq8IPw+zaUVYdxqG7OBVFhrnllUMwvn4I" "5vEO7HOYhR+A8dV9sExwhm22pxx2mHgGlpFHsSnmHAKLIlA92IKRB2/j3uOHePfpu9LfeCJT" "VfSY0kuUQlLQoANZ3eHrFYcCB6Wg1PgRVZarVAc9J0CQ0lAzp5RPQVf6GqW/KDVFf5fqv9CD" "48KFCwgICGDF4enpyfAgGBAwlMehB4cqydWD479XZdXLFQgteLp05RKcfByE4rDhEesLt//K" "UF1F6Sq96iCTfJVQHcYHpeIw01SHVBxLtOqqpTJd5SKrq6TqWIk3/VcIeKzAvgvWcI/Zj/Op" "ZxgcYfkuMmUlVMfNKh+hOAKQ1hqEnM7LyOzwEXf/vijs9uYGwZI+PzbNc+6c4sGIxb2+vIOj" "mOFxTrzvjACMswCHGyuQymEajBgqNwfSgijyNQRAqsUdOMGgYVxO160l9UENgfw4iJv9rtWu" "Fd/Thct360b9+Eq9IFSGm9G+V4KDvQ9r3GgkWNgzOKIELLhBsJEUiY3sOG+0YrM8vt6WS3Zp" "yu6VImOGxvnUlXCNWgDnqwtxJX0LbuYdQXrlUZTfcUXjiLc44N9FY/8DoQ4e4dm7dXg+tH+a" "ByKibx1XYL24H4Tnbwfg+USgCH/xPBR4VoIXHzTh0/fr8eLDO7JUV8CD+jyoWZCg0TnhyQDp" "vOfM0TZyFrkN5hiZ+S1DCouvwSenVF+99ztmYX0S6yxLeK2lShlb+r9Q2WGP7jGhPibOaipE" "RuvQWyhqWmwAhmoE1M+8mmwOnBxLoqqwqMpKAYS+ThAZbXkVBfF/jbOH/xJv/OufMWS+LsLl" "+NfxXu8PXqJAZkmA7C4Qd+/RAVgY4YpFAh5LrriLqxsWeO/FvJPWmHfUAnMPSxViKu62VonH" "uyNd4DbQBq/BO/AclPvAA8tzcCkqQtylXZ3ij4RHTAUJQUNNeKUDkA4Vei0q+gZSxWHTIg6s" "0dEhQ4MaQWTs3gQHpWq6x0eQ0tuCc3V57GFYVibAoiJejhYRYGCAiDCtlEqDHltX3GRwUO+G" "uq6ujoNbTyV7HBQGcAw2c1wYaML5rnKcE9Ch+VROFbEwSfOVpneiK1ZdPsDVVGZXBSBC98Ai" "/CDMI8Xzy/vZFDcLPwSzK/vZNCd/wzx0N2xunsaaHG/YxjjARvw5++unsDPDG6GN2aid6MTD" "p+8wIOiOhSqqyOOg51RH/vC9hzw2hmDLMI6V86oyBDjoNTViXaWcyNBuvTNZkkuKg3wOtW+D" "UlKkNF424ZbMbXpM34Me06Gv0lTcUX35MoMjODiYweHj4wMPDw+Gx6VLlxgW08tx9Q2AaorB" "y8aO0PWPu8jp8zvWJxXHZS4a8bzogfWH7bBky0xNcczUFMccCQ7D3KrJDnIzDRyWxxfpFAdV" "VhlxdRUZ5NRJTuDY7CMUh98K7Aw0xs5gYxwJXwu/1KMIyXRieFwpdMP1Ek9EV/oi9pY/kpuD" "kNl+Afk9V1DUf1nr7fDlMey0P4PSV7RFsKTHk+FB6qOo1x3F/W4o6XYTADnF/R+UuqJmP/Y9" "xsO4Aos7y8flqtqaEa0JcDxMrqqlyqsJueujoPcsrtXTCJL1shprwo/9kMaJS2i4JyAyEYDs" "7kMMC0pd0TW2aTUb56w2ai05dUUd5uSHSKNcvNZow5VWlLIKLzXF+fRl8E1YAccr83H0/Bs4" "6j8b/le2IybfFoW3V4j/PUtR2mOEmv6tKOjYjIR6Uzz/daumQKylB9JDYabBZA3Qu1aoDnHt" "spchYPP8o9uGfg8Ch+r5IJO8ceAw7k44CoC48+iS9jFXNPWfRnXXm8hrWYK81vnsg0zZB7Jn" "Oe6HueNhVR7e7e3Eu48e4dPnv8Wnjyfwv7tr8G/p5/GRi5k2zv0fDJ3suc3zUdpmKQDiwNBg" "9TFxmq9NvdtQ0ChHmUjz/EefmXlFlVPvdn0P73R9Xzz+ET8nE52qsAgg3g7fZF/kce/30V/7" "Pdy/LautHnV+F1cCv4l/+Lsv4UuvzIDJsq9iou17/DXlgdBVNRXO2JeXgn35cbAWSsTomoBI" "hLOAiCsWXnXEAq8dmHtMqpCFR0xhJhSIxYEVMD9sin0JwXDvaxYQEQAZaod3/20ENNfgYloC" "wiLDp4xCUR9O1cWuTHaCCC2tUitH1R0uHUB0EFKqZWho2GC4M1Devof7AiRj9+9Jz2SgA8F3" "KnG0MQs7a9OwsTpRqIs4remPejeixDWKezgsBTioDJdiDYGhu8IADlYgAiTkdwQP1MDndgEc" "BWzcxfej1a5OdfEwj3aAafxZmFw9zFVVVEllHEbgOCZTUdSjIdSIyaW9nJKyTnBgZbE6xQkb" "k92xRYBjX4Kn+H7RSOqvRsvb/Typ89HT9xgaBAoCBkNDSF4CJh34dXX1fCDTfxv6b8Tg0C11" "KimXY0eU4iA4qDHr9N9QVUzR6wQXNS5EjQxR0FBGOKXEKPVFf4c+TUVwUP6GAgepDVIeBBT6" "2fSj1VUF2Mu2AerVxp9sdawu3Tr5M0TwrCpVlhtyOQTu512w9dQGGG2Zi0VbXtOGHs40+Bwr" "dwuA7J0N0/3ztZjLZbnmRxZKn+O4BAeV5pLiIHhQumq9qwCIx3JuCNzhvxIHLi7H3kvG2HfJ" "Cg43dnJpbli2C67muyKiyIu9DlYd9eeR1haC7LsXUdgfjtLhq8jt8RHKIpihkdV2ioFB6iP3" "zjlZutsjgNF1DsUCHEV9QoV0O/KSqNI+N1YgNDCRgEHqo2rYm6ft8lTdEX8BhiABDLma9taY" "z+RGwQEX3GxaL4ch1q/TlIm/gMYFnnvVMBHEz7M6jzA4SIVQKosek8IggNA1tslO9nc0yA5z" "ggepDwLJtTJjBGUvg3fcUpy9PB8H/V7DDud/xn7XWUgstUPHvSPofngE7fd3oXViE+qGzVHa" "uxiZZIb/ukUokH0MECrjZYCQkd5pPlmJNXwaeFoM9O8SQNmE50J9ZDQu5yDVQQDJbFzGAKnr" "fUsoGw80C2jUdO1C+V1zFHcsQtHdWUi99RoyG94wNBNOXyolhyxSg+FSfHjGyGCk65dJqR4Q" "2m6Y27QQ+U1L0TawT9w0n2GIdI06oHP0FMrbTJDfvICBQeNIPp6iQn7E6SryNi56fgO+jt9A" "c+F3MNT4t9i85qv48pdf4X6Pq+f/Cm/f+T6CPb6BLWu+gvNu30BX9d/ifvuriLv8LfzrPwqA" "fGkGVi7+CsabJUAodaUUCHejCxUyY09uCnZnJmBvxnWsiwnGimvOWBR+VgDkHBZdOiMhcsIK" "C4+bw+q0NawOGcNk/zJYHluFo5kRcO9vEhBpYoh4Dd2GX4+4oy/Nw4W469qeg89OK6WDQ5X8" "qhQMHYoEDpXqUL4J3QlTnp8qgChXPzFxDxMPhBq5P4H7D2iA3zg/Hr0/hsbRXmT3tSLsbjU8" "mgpxsjETe+tSsa0mGWuFgrCtkH0cpEDo8bmuMoaHQYUM1yOo/xa8b+fCuTqW1YfHrQQ4CwWz" "PdUPprFnGBamEUfYFKeUlblQFWYRB2F28zgso0/CNvYk1iU5Y1ecM07kXYJzyTUEFlxDUmMB" "bg3dweDDcQ0aT/DwyWM81RTHu+JKMpdgSWkluvsnVaFSPgRYSgWxOsjL48Of/AkCB/dxaOtk" "CRxqBaxq4lNKg2BDQdDQr3/VqwX6O+g99FwdrEptBAYGGvwNLy8v9jtoVIfaja4Hh4LG9HJc" "vTk+PVX1p0hbTYeX6nG6cCkIbr5O2HF2M1buWIKFW2dyLNj6umaSz9RmV0mfYyU1A9L4EaE6" "TMnnOLbQUF2lfA4CxxqnZaw6KLb6LsdboUvgELUIASkLEVs9DzeqFsA/YTsuZDmwSR5R7IHI" "Uk8GR3y9P1LagpDVESJURxhKRq6hfDRKAOSSUBZByOvyZN8jv8uNQZJ71wX5HS4CHp5snBd0" "OrHy4DSWBhA20Ad9USMUA6WsKgd9BEiCuc+D1ceoLysPMsulKgkUMAlFYZ+7XAQllMSVellp" "Vdh3hiFC8JDhx6W+yW072Ty/IcBA3gcpDQIFhfI4KFUl+zssEN8s1QeNbb9csBx+SUs5ZXXA" "Zya2nf3/sfHwPyLopin63vHC4OPzuHv/GBpGrVE/YoyaweWo7jfi64tP7uL52EEBBxtDFRYb" "6F2mbKAzQD5sBl78Bi8eJ+PTvm148es7Qn0I5dEkIULjSjLqlyG9zghZDZYoatqJsnZblHXN" "R37bG0iqfAPRBa+J+CVKO5fI1bYWP9ctl/rZlDlY+oVS0kwXENkmq68ertaaEM0IIIu4D6So" "xRj1vVsZJC3921DRZsHqgzyQj6dUYU12npNhnnjl23jjl1/G9747A6YrvoKNtl/D//rxl/DK" "jBncONhe9iq6br2KpYv+nNNVP/nJl2Bt+hfYtuGrWDj3y/jGX72CLwu1ckyolod3v8cqhoBR" "1jKbr+XNUo3M2FKcin0FIjLisC/tOjbFB8OYVEjYWcwPP4PFocewyPNNLDhsAmsHW1gLkJgK" "FWKyZxHsHO1xojQOngON8Blph88wqZHb8BlsxonqHJxKjERQpCx/5MbDiKtaiuvqlDHxyh+h" "w4cOIQqVN1fGO71GByrdQdPhODgyzGqEJ8A+uM+hFhjRa8MCLtRncmu4G3m9rUjsqseVu5UI" "ulMGz5YCODRlI6i3GlFjrbgy2oyw0QZcGq7j+VOkOlwrYuBdnwyHvHAcTQuAvVAY1gIcNgIa" "62PPYWuCGw4IqJzMuQDnvCvwLbqGS7dScKMmE1l3SlHZ1ybuVjoxLOD24PEjPHz87tR8qKY4" "SGlQrwWlmkhB0OFN/7v1i5zokKfyV/oapalIHVCfBakNNa9Kv4iJvg8pOPJCFCxUCa1SGqQu" "1IwplV6ix/R++u9NYCBw6NUGpahIbZAKoZsA+vn0FVUKHPS9XuZvfBFv42UH+vTXP+97MPCu" "hhke08gdfu2aBit92kpLVamdHKoIJORyMBy8TmP7yQ1YtXMpQ4P6OWS6Svoc1AhI4Fixbx6D" "gzwOBY6p6SqpOGwdlzI41rgu5k7ynX6L4XJzPi7lLmBopNbNEXevv0Lp3dmo6JuFhLqNiChw" "xTUBjhuVvoivDeB0VcadYKE0LqNo6KoAh4DHeCTKRq4gv98f+d0+Aioe4nfPAQXdHlyym9Ph" "ZFAe2W3HBTQ8+HH+3eNcykvmOaWuqOKKgFE1EiyUSACrEPJCKkdkmW7NhLamlst2L6J40B2x" "rW/iWoONbBKsXc1mOI0sIVXCkBHKo27UG/l9Z3m7IFVZRTfLtJUajEieh/Q9LGWDYIPs74gR" "7yGQXKs0R1CGETxjFuNY0Gy86fAvWL3/H8S/za9Q3ipUx8RBtIxt56gZWIXyntko752Dit65" "4joXtwaN8OmDEE5XveibLOOdVCCrgGEn4FkhMHgIz+/5IKVxKUODIEIprNQmCZDk6iUIT5+N" "+OJFqB2wFJ/vpSjpFM/LfoWIzH9GUsXraBzZYCjlfWAxVX3cs/qFoQrr6Y6fc7/Hw/U/xwPb" "n0/6JloD4pjpT1iBUB9IbuMcFDQsQnHzMqFIFnEHOr2W1zT/M/0e+pLdlqK/xWqLv+CqKhpP" "QpAgA/0vKH3l+HU86/8BnvT+AAlXv809IPyer8zA//jLGfjzvxDx5zNgtPDLaMh7FR8N/YgB" "QvCgKG+WEGEFYloQhy1FyThUnI79WXHYmXgFb8aeh/kVJyy9fAKLw05hCUHEfROsztiJD4UN" "zA+vgvH+JTDeuwD2bpvh3FgI36E2AY5WAZBm+A43YX19BqxKYrE9NwoeN68YlugYunavTpb9" "0iGjyn4JJupgosOT7o71I7zV1+gQpAOSDkxK8+g34FHQClWCirpSUNpr4N4Yuu+N4PbYIDon" "RnD3wSjuiLh9fwRt94dR09sm7l7aUdHfJj5QHSjtqEFhexVybpeisK0MJe3VqOyuF79A9ajT" "INE10ieANcbgevTokTbCYHKRDD1XQc/p56OfubHl//R2pkFVXmke70/dH7qmuqZqqnrS3dM9" "k670kk0jsu+bKIIg7htR40LUKO5LUHFXFHfZQUEgEUEUkEVZVbgXUEBRo6JIjFGTzNTM1HRN" "zYe2/3P+z7nn8nKD6enOVH946l14uVyu8vzO/9mOrm6iUzcTcc0mTnTwvE9o8vc0mzkRDpLf" "6Ox0bsDEe0yaW0eDEBYMTZkeDVMFZc1LmCooM56fP4/XTIpTbezbt0/UBsFBtcF/L/77EDTm" "dUzo8bvGjXyfxPhfEt6ywiLDshWB1Zy5uaw05/7jPDJUtXHnesxYMQkRC5TiiPeAH8GhoEEL" "WqCN4AhlroPVVU7F4Yvxif4CDl1dpZPkGhy6LHfq1lBMU8dVx/yR1+ylnJO3WtW+h+KG95Bf" "PRLnWr3VyjlCHN+F7ijp6chv2Yti236U3jgkSfKLd9NEdVx+nIOGx9nKMlHXd0Qpj10CkPPd" "m7UCubVDKq+oPlh9RXhQfTAHUtG9SkFknaiPxgd7JXHORDk3jBJ4PEkTaOhcR6rkPhiyopLg" "nCtO6i28vkCAkdUWJ8qDoalcpS6y26bglH2WUhwLcf7WMgW8ZUqlzNYd522OnIeU8mp4FLRP" "dIateOQ1w1cFjnEl6ZfH4GBpuFIfPkjYMQLTlv8OkXNfx7rdIWj9bAmu9cVKk7Dt4UzYH01T" "APFEbY8nKjpHK3PHxS5PvPyffrx8no4/9S3Dn+5NlUQ6+0CcZby3Y/Dy3jz88fNDePnfjwQc" "xiSMZdPzrvIu+mBX5khUd/nixsBCBafxqFewr+72QkmLB+p6ItDeP1Ng1vl4AbqCf6JAoNWH" "CV9pUPzast3tG4Nj3qNex6Pwv5fRJYRHZbu/AISgqOQ9m7eYXNu9UNXu/a15V9Zpuv/+8OcC" "ke3r/g6RoT9CgN8PMT3mR8g5+BN8ees1USlMrH/z2c9RX/oP2Ljixxgf/kME+/xIlMjOjT9G" "R/VP8R/3f+4cpqiVh4ejD8QBkJDaIoRX5mP25RKsri/H0vOFWFScifiTKYg9sRHBR1fA/0gi" "ApSN2z0fEzdMFhUydmkQxib4IXKxHyZvex87btQrBdKFfX12JN21SWKbGzGxIiqu5hSWluUo" "NZImyUgNk/RvrSpNiIN/1PnKGZmwFp0pzXU6q4mx0xnSSdKJMmzDLmo6cytM2J1t9uY2xsa7" "p8+ficm2q88czz3T+3ib+8Z4/eWL56Imnj9/LkB48dUzMd6zgmIISNQ5K57o+Onk6cgNDM1Q" "QwNFOnzT9GdNipvcBsHBkBWBYk18MxxlNlwyo0H4mfHzcm3Wo5MnNKwOnc/x38NUUzFERdVB" "JWLKro3aMMUP1q7xVw04/C5ofN/ch7x2dtawoHANkZk+FfNzzaDDE2nHsHb3akz5KA5B832U" "2nAXePDoCg5RHQ5wUHUQHJEr/BQ8fCVkFePY3Cl2YyDiPg7U4EjWPR3TkkKRsCcAZ67447Ja" "KVf3jFar1xHIOf8ucivfUepjDK4PzFcr6bGouRmmVuJbUNKZKnkOgqP2QQYu9StofJ4jyoPw" "aOjPUCv8FKWw9yjAbMW5jnW42LNdTEp4e7crYKzTPSC3N0sY68KtNdJESHg0PExRi6Sjkutg" "DqRpIFWUCFVG88O9juGIx0RNMHHO0l6W6mbbJun5VgoeRn3IqJJWfcyj0rDFOe8zdMU8B69z" "23SpLmGRZ492VlwxZFXYHiehLJ6z1yO9dgz2fRKCtYc8MX/TO5i06A1EzPgldqaFCzSuPIgQ" "u9YXg47+2bjcG4TzttH4pHGUAvNoZaNw9uooVF730OGsf6vCyxengGfH8fLZCfzx+Um8/NdK" "vPxDjyTNdd4jBGfbBwHC3MeZliAcO+OJnZnvKHUTiC6lfGwKWFQiBEnLvWi09umJF+2PZinA" "LEX9rQh0PlyLW19swePgnyqY/ErUiQ5xvS7g6B/7OvqDf6XVxnBGgCh4GIAQHsx9VNo91NHz" "W/D4g2V8CfMg//nwZ/haqYzPu17D4/af4mn3a6I8+DVreS+f++rOzxzPvSa5EaqT/3ow2IVO" "gJgmwiEAYW9FaE0+wi7mYU79WaxquIClFUVYWJSBOXn7MDVtI0IPL0Pg4aUIO7IcUw4sUX8k" "MYj5KAyRCUqFLFR/THNGYPLOedh9u0nCVzNt5QogBRjboEtrpUKq/iSmVOdia0GmDGNk9zpD" "WsPlR2hc/TJpSydrYvOmn4CO1nWfCNf5SSYcQ+fLJDJ7TQxUrBAhFAQc6vy5CyhovH7x1VN8" "8eKZQOP5iy/x1ddfSljq2VcvBA7GCAw+z5BUd3ePAlqTvEez0jcVaHxv5nfi72HCU0ZpGGiY" "keoED+/xGaMmzGdgQlIGGEZlWJ28yUPQsZtmP5MQp/F5OlOqDRpDV3yvBthW5WJCitYw1Xcp" "jleFpP5agPw5WDjNEb7Kys4YCjJHE+CR9KNqJbsOUQnh8J3jDp/495TieG8IOPwX6FBV6GIv" "i+rwsqgODQ7T08HqqombghG3OUTAMW1bCGbsClUWjNi1PthZ6KkgsRBX781USkOtJDu9cOri" "CBTVu6FNOaDrauV6fWAR6m9PRGn3FlTcPYba+5kKHJmS6xBwfJ6FxoEcAUjT5+kypoTwKO90" "hK56dyu1/DGqereg8tZmlCv1UXFrA6pvqdfrWa3O10vOg8qjoX+/nmnFTaL6dso5q6vYQCgK" "ZOCENAkyD9L8OAWnr38oqoMKIqNNjyghTFiKy/sZUlmlVIV9ogMeMXIUWNjiRIkQHqds0eoe" "jzqRTmCcVt/D0BWVCMNX3KaWpbvbT/lj5X43vL/mTcTMfwOR0/8ZB/LCBRrN90OUBeHqg3ES" "PrpyL0oS2Qwrnap5F6eUsiuoG4kzTaNRzuTvLW/53Bs+80ZLXyBa7k6GrW81ztk1PAgOmgEJ" "j+wyL24OwP4CN+zJGYmme8FKYSxUSuN9pTjmypEw4/u5ot7H9YEEdD9ZIYqk6/Em9D7dil4F" "EWO3nnyMS10TUNEeIMZJ4QYYF9p9nOeiQMy5Q5UQHhc7fER9GAUy3P7nrvt6UG1oxaFVxx+G" "7FT4iyG7FRplIpCRnQgd+4KoZ4YFCMeGcNe+MUolhFTmIP7Sp1jVdB6JF88g4ZNczM1REDm+" "DmEpCQhJ/RChB5cgfNtMjF+rVciYRX6yb/OYuaMRf2wVFttKpZw2srEA0fWFuv9CXcu9Jn2c" "W5GD3acycDRrMJzFfUfMqtBsYMXELVfB/MM3MXpTImocqFl5m4SwWXW7jscwoRc+Y0aX29ra" "JH/A8ti79+/hsweDAwRlRPnjfvT1P3Je33/YJ8+wDPbmnZu4fsOOlmtXpQqKEDC5CzMPzEy+" "peOlAzZhKaoGhpr4Pqgy+F6Y6DbQMBNr+QyfpwM3Zhy6cepWVWCdJWUNJZnR4keOHJHwFMNR" "VBrMb/B1+PnwGdP059q7YYXGcKNG/pL5VK4AcbXvgsb/BTBZDniYkSMyaiRDL1bS0o8j9dgB" "AUfs0mj4KHB4q/+3AfM8tM33HFQcC70EHOGOPIcOV/k5w1UCjtUBjgR5kDNBPm1zmIBj5o4I" "zNoVhtl7wwQmk1a7I/9SkFopL5LVa+M9H7E65dSu3Jss91r7ZyiILEHb/UWo5ph1pTjqB3IV" "NPJEedAaB7J0+GogXbrNGa6q6NkmAKnoTcb57k1SustEeqVSHrSLNzejsmc9Km8mShMhlQX3" "AOG2tEyec/MoVlWx0orjSwiMa0/SHUpkh6iRMz2JSG91wIL9HK3TBBAEgG4OjEW2fYKoipw2" "3TDIZ01zYI4DLITGabseya5hwZHsE5xlu4TH6VbOu4pCWvUYAUhiyijEr3sLkxb+BlHx/4ID" "JwmNCerz8xNrvh+qFMAUtD2cJKGr05feQ/aFd5BVro0gKaofidJrbrjY7SahrkYFEbG7oThP" "aLQF6pwHcx+2YAEHq68486qoyR/7T43G9uO/l9xHR/8HMt372v1JDnBECFjsSn3cebZNKZCP" "BAYs++0e2IDux7T16FHnHX3LlJoIVvDwdwLkglEcDoAQHkOsw9epPrR5O63aru2izQstt8aj" "93EiPhtIxO2Blbj7eCU67illpp6raR+F2g53pzGXUdfJnMZoMZ7raw9notyYgYYJXw0ByNim" "Yj0/ygER7uc9+3IxVreUY0XdGSwty8PC/IOYfiIJY/YpiOz9AMHKgrZMhc/SQPjO94Dv++/C" "e9rb8J31DoIPJCCKQwcbdE9GdH0BJihoyERbdZzg6NWYWncSy8oyFEjSBSSycVX6YP+IWb1y" "pUyI0OExnELHZXXKdHgmdEMnLiGdi1Wyx0V5xdAqI6ujpUO0xu7NOPpCS7OjWcXLs+q+cc7G" "TjvumefNe+LP4/sygDNNeVQYJglOQPBo9sQwCW8z6oOvZV7PvHcT0jPvazg1YIDBz4qfnamg" "Mh3ipvSWnyd/B+s+49bEuuvnM9xU3L9Fw9+r4GQNebp+TRYl2XpOFRXHkRNHsDt1BxK3LUPM" "kihRHL6sqIr3gM+8QcUR+IFRHD4IS/CVJHnEMl8BR+SKAAc4AgQcMWsCJc/BJPmkpBBpBJyW" "zH6OMMzcTXCMwZx9EZi3f6x0l09a6ybTXDv6F8iqtaM/XsIudDpUH9f6osQxMTzS+mgRapQK" "uPR5tgs8NECalNXcPyy5D25FW3Z9k1RcCUiur5XkecXNJFR0ER4KKDfX4FznEgljNShA1N3b" "JXt5SOK8L0XnPqRs97AoEeZACBOW8LKkt+z2KmTapiLHPlkrkDY9YVcnxfWUXSbU8+wxTlgQ" "ILzWuQ8NEQLjtAMiPKdRdRSp6/w2XYElVVhtUShSX0urCcf2fB+sOeyBRVtHYPaKNzFxwRtK" "CfgpgMQ4IOwnFVdtjybD3j8dFcoZEiAER0bZO0gvfxsZF96WKqnCy6NQcsUNVdfdUdfrKfCu" "6vFSkPVUKsQXpa0BAhGBh8N4XdQUiNRCd6zd8yZquv2U8oiXn0fFQRXUdC8ErQpenz1LwZ3n" "KUqRxKO4yQtVHWNQeyMadcpkGKKy6s4IXLAFCEAEHAKSocBgstwVIAYeBhgMYVGN1LR7qWtP" "AQjv118PRcONMKfVqe+tUY6+2j5aHbUZgGjTAOFoEn1uBYjbsCAZChAZBXJajNNpI2pzNUTq" "T2PV1XKsbShFYkUhEorSMDs9GVH7FiNwxywEb58F/48nwutDf3jMGQHPab+H59Tfwmva7xBy" "cDEia7McEMlzgmNCY55zjIhu6DuJ6XXZWFWSgT0nMyS0ZY1PWytw6AQZm6cTZIKXDtKoEuO0" "6XzpEJkToNOmQ+Yq3nrkfWveoOx8+ZD8Cq3McTSrfTptWf2XaRVhDR8ZM/AiKKgsWDZLWBAO" "hARhYUBhchd8HTNTyjhskxex9lGYr1n3/7YCgw7UNPhRZRhgEBLWRDiN14QKoWBVM9+1z7h1" "PpWr4vg+IanvCkFZw2H8uTnD7D0j71OdG2ha3wdzbYdOHMaWfUlYvHEBohPGwu99TwEHcxxU" "HByxHviBF4KV2jChqjEf+mhbYsChcxzjV/sjep0/JjhyHNZ+DibIp28LF3DM2hOO+JQxmJsa" "gQ8OR2LBoUjp95ix0RtnrgYLNKg2bGoFa+ufIo6HK1jGz2893YibX6xRTn0uavsOitJg2Irg" "aFIwaX6ij5cfHVPKY48Cw3ac70mW5DkBwhwIAVKprkvbVzjzH6XtS3Chaz0a+g6g/sF+qbZi" "3oNlupx9dfULR/+HgpbZFIolu4TJ+TsbBB4EhIxm577lhAjDT0o1EBYZtlg51wDR865ktlW7" "fkbCWoSFUigMX4nyEGhoNVJgc+zx0UaAROIT9X1UIewB2V8SgM1Z3lidOhofJr8loayk425o" "7J0olVdUBFf6wiWEZe+fqZyxhwUgb4nxPK9SqZLKkcpGIbf6PZyu90RRgw8Km7xR3OyHM9f8" "RG2U2UNQbg91Wpk9CGdaAiQHsv7A2zh6ZqSC/hwJXzHvcVWBn+rn9pdb0P9NHnqeJqG2O0yq" "tco5TVfKcf0GTUJWQ+HhBIhtePUxqDx8BRY17T4CkCpRFj4OgHhos4CimuCQc3cxgoMqg0fp" "JO+0Kg03J0yGwmWoIvkWQDgOhPkK5ik4/mNcbZ5y/tkyO2p63SmsvFKO9U3nsOpiMZaUZOGD" "3H2IO7ACwR9PQcCmiQjYEAu/RX7wnPUmPKb9FqPjfiUwCd6/EONrMhDVlO0ESExjNmIblCmQ" "iDXliMU15GBOdSYSSzORkjdYrZVhqdgyYGHM3pSVMtFLoNBxUiGYvEJJWalTmdCxExzi2Nl0" "p5w7E9R05DSeu5ppsqu7VOM8r3V8H8FgjIAw54QEVQVDUYSFNOupn2edVGvtcbGqGOu1VREZ" "Z2mdE2VW26Yb3IwSITAIB6MyCItt27aJ8ZqfG7+3wNHBbhSNazL8VdNw/78n4hpIGBVhAKG3" "Sc5zmtlnxnxWBrK8x+8xE3GtC4/UI/uxNnkVZqycitD3/eA/293Zx+EnOQ5PBC/Q4apBePgg" "dOlQxUGTklyH2ohV0Ij7OFgpDgWPzcGiOtgIOGNXuICDimPugbGYf2gcFh2LxuK0aHyYNgEJ" "KbFYtD0Kpy+PVeBQAOmPE8dDx8cVbIsyxs3vfpWCnicrUXd7tlIYx7TaUMCgmXOGrurupyq1" "sQOVXcmiPggQwqPElogLNzYKPGgcYXKuczkqbqwUcDT3paLx/n5Hjwe3pU2RTaCuPDmOpv79" "st0slQcB0vBoF0p7VyLLPkOAYaqudA4k1pH3iJWR7VQXhIOEsWwxOnRl130fUnllmyAwISgI" "GaM+2O/Be4TKKdt4USHF9gmiQAoVQPKaI3GsKkxBJAjbcr2x4Zg7Vu4fhfWHRuHslTECYjYO" "MoxkVAFzHcUN70oOJPv8SBw/OwJHPh2Bw8UjcbTEHUfLPJFV6Y3cOj8UNgTh0yu6bFfyHh3M" "gyiIdIZIXuRcO8NYemx7dpUPtmeMwLq9b+FsUwTaH82XfBX/3e58mYyHX2fgs+f70HJ3Kgou" "eeLTBl/Z0/yCPVAUh5gCx3kDEQc4NEgCnACxhrCq7AFyTyfOdeUVIWEUCMFhjEqkRjl6DQ13" "OR9q7g7zcIarNECsasPNARIP1Hd6ilkBorvPRzsBwvs/GM+u7YYCvfPe5XyZUssQFCEyriYL" "U2vysPraOSRdqcC6uhKsPHcSCQVHMPvEZozbolTIyjHwWx0OHwURr6m/h9ekX2N09C8EJuFH" "EhBzWUOC4CBA2MAX15Qr9yY2ZmFic7a6zpbzuIYsxFdnYFVpBlJz0p1lls6afcvARjpQU25K" "J7lp0yYkJSU5gUIHQydpQknWcBLViFEKBiR0+EYtGDOhJgMGY2ZzJAKEr2EgYaqrrECwOsNX" "2atCQ0ZZUG2ZKbdWdcHf1QqM5ORkbN26VcaK8D5DWHxt02PjGsKz9my8ChrWvgurKvxrYOI6" "ssRVXRhgGIBalYYBh4y9ITisOZQ0/f9k36G9WJL0oYSp/Gd4wHe6G3xmjILX9HfhM2eU7uNY" "MJjnkOS4MoaqTI5DKw5HSa4lxyF9HFvCRG1M3RaG6TvDBBwzd+tQ1fv7IzAvdRw+ODpegyMj" "Gom5k5Bcslgm6CbunYNDxePQ9nC6hKoYgmHoo+leIDofz0Pf10dx98UhUSXlN5agri9TQ+NJ" "phMghEd9/3GdOO/W8CjvSlLQSELRlQScv75BgWQ1zrQuRYVSHOXtiQIQQoPAYPKc5bpMjgs8" "Hh5E60Ca9Hk0PNwjFVet0v+Rgoo76xQIZiHTPskZlqL6yGkbzGnIfh8s0VUAyDXqw+aAhz1G" "ku1ScaVAQsCcbB8ESJHkQjQ4NDzGq3vRKLRF4nTbOBRcixQ1kn8lChnV4UgtDcSeYj/syvdF" "cp43Dp/1Rm1XiCg5rQjilRoJVr+/mwK1FzIrPHC81B3Hy72RXuGH7JpAnFLAKGwJRfG14MFe" "D1uwqA7Cg1bWGSZHgUe7ViB8prDeH4eK3BRA3sGmlLdRVBcgyoMhSJ1Un4f63kildNxxstIL" "564FCEAG8xz+jsS5hoZRIINqI0BCV8yDUHXweEFBgWXJVZ1ekgPRuQ4PCVdpBeI5DChebbUd" "HkPyIEaJONWFRYEYgAyCZhAgppyX9oMJzQWgRXO/i8Z8CTHJ9q2XcjC+LhuR1ekKIjlYb6/A" "5qsXsJGVWlVFWHYmC/Oy9yJKqRHfZYHwWewO70Ue8JjyG7hP+Cd4RP4j3GN/KTOhYpuyNCyU" "TWpWAGnJVsccsbiWHAEI4TFJAWZyfSamqPNZdZlYfdaRaM/KcDQhpjsHNVrLMa1jNqhK1q9f" "j+XLl4tt2LBBAEOnSydMh2XtNXlVQt61ysuAwTrDydWpul5bu/CtztP6vo0ZSJiptgQFk9x8" "34SkKa+1hqMIDBp/Zz5rDeuZHg1TJjzcZk3WCqo/1yU+3O/6ffIZVni4hqcMOGimoZLv24Sq" "rEn34xlHsTt1G+aum4nQuf7wnDpCqeGR8Jk9Gt4zRsB3phsC4tX57BFKgYxyluOaRkCGqsI/" "8kXECn+MW+mPyFV+iFoT4AhVBWFikq6qmrw1BNO2hws4TKiK4IjfG6HDVQoci46NF3Asy5mA" "dfkzcbBqDbLqt+NoRRI+zlyCTUemo/r6TOVw5qBrYCm6Pl+O3qfr8eCbE3j0TSa6niaisica" "JZ17pFGw2aE+mhVEmp/oqqvK3j24cHObgKO0c4PA49PW5Sjr0OqD8Ci1L0d55yrlJBdL8yBH" "lHCnwaYHB3SZ7qNDUsbLRDmrri7f26J7P5RxTHvVnbXK0c9BdttUZ5UVj8x95LTFOK8JEAKB" "liNKI05AYkAh/R4OUBAQDFHpUFaUKI0CW5TAh18jOIrbdQKd4KAV2cfjE3Uvv3kcsi6HI606" "BMergnCsMlh9piFIr/RHcbN28OwcL2gMRt7lIOQ3BuF0cwhOXwvBJ61h+LQtFGdsYQ4LEXgY" "cNAMLAxAzLUGSIiGSGsA8i56Y2/ue1i/712sSH4TWw+/hfSzbgoabkgrGYWU3LeRrlROSbOf" "I3wV+GcBUtURMCT3UaGgIfBQqoLhOEKxvjdIQcRHyne14vAWxVHboY9GfQwLDQWBWgGBsaEK" "xDUX4hrGclUhRnnQGjo88b9WFWkjLloA7wAAAABJRU5ErkJggg==") #---------------------------------------------------------------------- web_service_error = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABO0lEQVQ4T61TwVHDMBC881hO" "HszgJ48Q5J95ETpICXQAVJDQAakApwIoIR1AB4SX+eFJKMAJL6wZjotkh8hWzAP00tzerfbu" "Vgh/PFivT49AohAjQLxgTJZ4BkSzzoeaRDnkuzUWQXosrhDhDgBDtzDKieDmdKkeKnxLYIrx" "freQACb8suT4pRUnuq5INIGWHYjn+svxosC05w/R8x5tRZR31iratKMJXnsiAQ9HDdlET4DA" "7eCggX3RNH5XY6OgH2R8OXEl6ZiLHGgeL9S5UdAPuN3m2d+Cyd3g/0Owr4VWBUQv8VINWofY" "SmAN0axxztM+tPZdFBH4vnSsccVrlNs16k04jMThrCSUrUaqwNLKSV3JTzGt2Mpjp5WrpLcQ" "ws8DccsGGvKHOtNxHhghzrrrImn9TC4v/Bb7Bt+GjhHeCMaXAAAAAElFTkSuQmCC") #---------------------------------------------------------------------- web_service_info = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABBUlEQVQ4T62T4RGCMAyF7QS6" "gTiBuAEwgRuIE4gbyATiBDqCE4AbCBswgk5QX3opQq6UH9q7HL3m5SNJUzX7cSkZX1VVgLMD" "bAujPa0WdoflcRy/+jEDAIJTOM+wxUhiFHwE5Gb9HYCDryIw5yx24nxvIQbAaT/lnyFS8EUk" "EQDKZEXlWEDBdcvMHwwNHSVdAMgMoCzLVim1dIn4jJoqVw3AxmagXU3zlGDk5P8PYKwEXwZa" "6yZJktDbxIkSvk2kawSxRiPnohcrnoPBNUL7hjborpFnIcVXDlLLwECAh4NknTSNoBeOTIyE" "/5w5R7kHoXdwgjgCaM2BDfb0mArvY3LNwtTZB3S1ehErHUAZAAAAAElFTkSuQmCC") #---------------------------------------------------------------------- web_service_success = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABRUlEQVQ4T62TMVKDUBCGd5nB" "mVRSoo3kBJIGocsRvIF6gsQbmBMET2COkBvELhEL8AapoiVpIDM4Wfc98pIAL1goBcPs7vve" "v7s/CH98sH7ejn0HCxwA0S0iOiJPREtAnOZmPkp7SXp8pgKwI//eABxzgXVCWLoFevzyFhOV" "3wN2h18qB4lGgMAq8O44zpAHBZEAIdsoMK7fvPLmaL/7fYNwVlOUZmbeFe1IwEUUhPwxqMsm" "oFcEFO24zRw8f3rzYQl4C5aIcKUrEjEdnMMJK+xJwGUUkG5oLS3IcpH/H8CpFloVEH2sbhZu" "6xDbANzzYYjlGiHhcZ1X9m1SF77Baa6R1pm5cfZrlF4oXVgxkrSw2MLO0greMJJKlBAI60oO" "qmi9BRhqrayKrNi1OkXnCYn6fPW1jPPA+D3NzjZh68+k88JvsR/VA5gRxV2ExQAAAABJRU5E" "rkJggg==") #---------------------------------------------------------------------- task_done = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABFUlEQVQ4T6VTy43CMBB9s+wd" "SoAKWDrguAcOCQ2grQC2BDpIOoAGiA8gcSMlhAqAPha8bywMiRVQECNFsT3z3vwFgXxnUbcF" "TPk8FOBL1RYo+MvPQLqNzbEMoc1dRlmU8Kbgh0KyZBObX29wIxitogKC/jOw12lEJBno3RE0" "8VxDnK5jMxPN+RM4NPEc2vwBPXnFO0NfMuRJiSiVprlfgJ8PQDuwK9dCIyDxXazFibeOCNr+" "VcE8FyRQcKfSxpCASkPAXCxyJXkGdl2oS4EhLfil1Osg1Xp2UVjsHxZRSViwJc2yMOxKEd9u" "49uD5MNp2k6f+3ps3KK9vEzEuBH2jisE+nityYwVHt6Wi9XmOefoJuE6/wNAk2dc0tIk9QAA" "AABJRU5ErkJggg==") #---------------------------------------------------------------------- task_process = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABmElEQVQ4T6VSPU4CURCe2QXR" "wPpzApbEHugt4AZY01jYADZGezGhNLEC7PQGamKvHMAET8CLF5DskhAC7jjz4K27GMTE1+3M" "7Dfz/SD882H0f/eadtUpDqXmdscu0Cyr+5PMm6kv74sB5NqeChBaCFjlRskMD+oOuu1RAZB2" "VN3pRUHiF3R8kkIA8IpALVXffjDDbttvIsKFfBNAj4H0ghDA7folJHjmJk8Q07DKqpHphwAd" "r8KX3RORF5BdfT9JP8UB5ESgCp/ZB0z2VW1LxfSZU7jjBSNelFYNpxgD+IsZIjKk+FK5BBM5" "WaIpaIGAbg3qb2ACgqnRB4tVVjXnZQ5g+E8ye6vsitHp+H0gPBKNFgBjF2k2IKBDIEtFxVtH" "7dsFRmWFp1zYBytZ/CGiBOtzmgcbCxDgo1kSAmQ73jG7emMB2HJJLANavJHwzWuXF/xDF7Qw" "G8wLUUeXCC5Z0GY0A0R4xkE6kI2STNOLJTF0xLKHQiHHyTSDkr4gsK4sKzg3Kfw1B9rzTbFX" "XkIta7LygnWqL/e/AG0buBF+hM67AAAAAElFTkSuQmCC") #---------------------------------------------------------------------- task_paused = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAA3UlEQVQ4T72TwQ3CMAxF7YoL" "UsMMbMIKbEA5tr2QDdoNyoUzTAAjlA06gkeAcuJk3EKqqGpJKiRySqT42d/+RvjxoIlfHuo1" "Ap4ZoAScbSmekw/bBhwFsGmCmPkGEGSUhnsXxAI8Snms7IC2GkYtoGoM9BVgghgho1jlQxAv" "wFsWVBCAFlBpg7wBXTUABSVKm/dkQFsNSF+SsGju/wdIL3JKVTZZgoz0KgaL+gbzkMB3bkz1" "0dwfpctIg1lHxlh3VpY+S1aIKFlcJljZLBOf4Kl2pFH2wX06Ce6vwz9e0lJmERr5KdgAAAAA" "SUVORK5CYII=") #---------------------------------------------------------------------- task_waiting = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABhklEQVQ4T6WTUU4CQQyG22WH" "mMjDcgMeTXQDnsCdG8AJwBtwAz0CnkA8AXuD2RsIWXyWI2wiJsYdqe0o644gCbFvM9N+bf92" "EP5puI0vs5jYFnxRHGISQISI3ZBe2qhXhQcAIq30MjsEKM1FAohGJbmL/QGYWGjjUOfTQwBr" "4hFXMVE6jzzAu4mnDIj4oc9OfQqoWwfhBhcMT0sTpwwomjofeQAyZx2L6jmkzSXA66qEVia9" "ipNoo2CdAJyyT/AoPqif5h5ADtzfLSEOFW0G4sBnpwfrkpA575UYzJDogc+32+oqDappMIRF" "upEsFrAv9yFQKpm5lDsOHnut/RbMaYEw3AFAkBHCrJnk138CuOQJC5QosJz5rbDYmrkKaD0A" "OIlKCFMuOatXURvj13wrEbFlELDnRASaK7IMaUTfrVT7UgHqY3TiIV757VGmkqUWP7nfGSPP" "1y1SAzZzl2WPSXUfEHRYi3vexLY3RvkLssoh2JWFsLMXsH3bu8oCOMJ2PtMRsZ7rJ5V9yhGp" "KT8lAAAAAElFTkSuQmCC") #---------------------------------------------------------------------- task_generating = PyEmbeddedImage( "iVBORw0KGgoAAAANSUhEUgAAABIAAAAQCAYAAAAbBi9cAAABD0lEQVQ4T6WT0W2DMBCGP+MF" "MkI6QR1I3jsCG5QRGKEjMEJG6Ah5LwFGYAQGiOPqnKBaDlCiWEJCx/Hdf/efVZ1SoXjnlePo" "VZ0xaIuxmgr8e2U1rba8Wc0X8LmmhoAcUDooFAzKcXLKA8aYWQdK6R0c1yTP5SgR8ZNyOjR8" "vAISxiyoNWx3HX1YYCom32dB4qS+ctx1dJLYGjZwe2xCsW8owwKToBgiP5xTyuQGHlqDiWEP" "oCmIqLkmFFnj18MfgV0S8kPj3X1src7ItaUfW4rVhCCr2e7PfM/OKITd1eRZ87cevrUAsjzs" "uzJJCtVNQRZBo1My3Mj+TRz7F/TMgi4u5NMgsdzBqos5e9cU/S+816lG3zUC1gAAAABJRU5E" "rkJggg==")

78.420639

98

0.88326

10,186

279,648

24.247595

0.94944

0.001587

0

0.141357

0.063322

279,648

3,565

99

78.442637

0.801554

0.0031

0

0.000565

1

0.000847

0.909778

0.909548

0

1

0.000039

0

1

0

false

0

0.000282

0

0.000282

0

1

null

0

1

0

1

null

1

0

5

5815844d4c18b7be5e03e947ad098ac5dbc82131

161

py

Python

supplychain/admin.py

basp0/Mtech-refresher-DRF-assignment

e88795b38c87783ba8f302894cc1f1c9690fc0d4

[ "MIT" ]

null

supplychain/admin.py

basp0/Mtech-refresher-DRF-assignment

e88795b38c87783ba8f302894cc1f1c9690fc0d4

[ "MIT" ]

null

supplychain/admin.py

basp0/Mtech-refresher-DRF-assignment

e88795b38c87783ba8f302894cc1f1c9690fc0d4

[ "MIT" ]

null

from django.contrib import admin from .models import Customer,MangoFarm # Register your models here. admin.site.register(Customer) admin.site.register(MangoFarm)

32.2

38

0.832298

22

161

6.090909

0.545455

0.134328

0.253731

0

0.086957

161

5

39

32.2

0.911565

0.161491

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5822e0c80038b09e25985f8f92f9a72491054ec9

79

py

Python

atlas/foundations_contrib/src/foundations_contrib/working_directory_stack.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

296

2020-03-16T19:55:00.000Z

2022-01-10T19:46:05.000Z

atlas/foundations_contrib/src/foundations_contrib/working_directory_stack.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

57

2020-03-17T11:15:57.000Z

2021-07-10T14:42:27.000Z

atlas/foundations_contrib/src/foundations_contrib/working_directory_stack.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

38

2020-03-17T21:06:05.000Z

2022-02-08T03:19:34.000Z

from foundations_internal.working_directory_stack import WorkingDirectoryStack

39.5

78

0.936709

8

79

8.875

1

0

0.050633

79

2

78

39.5

0.946667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

586e71aad98105fe2961a96201fbea05eb7c4ddb

183

py

Python

nbgrader/nbgraderformat/__init__.py

sashabaranov/nbgrader

6d260e9f63cef15073a4540fe34ef196e36c4c94

[ "BSD-3-Clause-Clear" ]

null

nbgrader/nbgraderformat/__init__.py

sashabaranov/nbgrader

6d260e9f63cef15073a4540fe34ef196e36c4c94

[ "BSD-3-Clause-Clear" ]

1

2018-10-31T15:54:37.000Z

nbgrader/nbgraderformat/__init__.py

zonca/nbgrader

6d260e9f63cef15073a4540fe34ef196e36c4c94

[ "BSD-3-Clause-Clear" ]

null

from .common import ValidationError from .v1 import ValidatorV1 as Validator from .v1 import read_v1 as read, write_v1 as write from .v1 import reads_v1 as reads, writes_v1 as writes

36.6

54

0.814208

32

183

4.53125

0.375

0.110345

0.248276

0

0.051613

0.153005

183

4

55

45.75

0.883871

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

58740b47bc6b7117b702773896da667fdfc78ae4

181

py

Python

src/IDA/grap/idagrap/patterns/cryptography/stream/ModulesCryptoStream.py

AirbusCyber/grap

dbb037c4e37926e182d0489295b7d901bd0c7c3b

[ "MIT" ]

171

2017-11-09T00:37:58.000Z

2021-10-20T08:58:44.000Z

src/IDA/grap/idagrap/patterns/cryptography/stream/ModulesCryptoStream.py

QuoSecGmbH/grap

dbb037c4e37926e182d0489295b7d901bd0c7c3b

[ "MIT" ]

2

2018-01-09T12:13:39.000Z

2019-03-11T09:58:36.000Z

src/IDA/grap/idagrap/patterns/cryptography/stream/ModulesCryptoStream.py

AirbusCyber/grap

dbb037c4e37926e182d0489295b7d901bd0c7c3b

[ "MIT" ]

18

2017-11-09T01:17:23.000Z

2020-04-23T07:02:32.000Z

#!/usr/bin/env python from .rc4.RC4 import CRYPTO_STREAM_RC4 # Tuple of stream ciphers CRYPTO_STREAM = ( # RC4 deactivated (too many false positives) # CRYPTO_STREAM_RC4, )

18.1

47

0.734807

26

181

4.923077

0.653846

0.28125

0.351563

0

0.033557

0.176796

181

9

48

20.111111

0.825503

0.618785

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

58a01e7e46c44ffbffbd619bed0979539913263f

51,431

py

Python

hoomd/md/methods/methods.py

ianrgraham/hoomd-blue

a2f63502adc467f3ff555616d0e27bb25d5ca9fa

[ "BSD-3-Clause" ]

null

hoomd/md/methods/methods.py

ianrgraham/hoomd-blue

a2f63502adc467f3ff555616d0e27bb25d5ca9fa

[ "BSD-3-Clause" ]

null

hoomd/md/methods/methods.py

ianrgraham/hoomd-blue

a2f63502adc467f3ff555616d0e27bb25d5ca9fa

[ "BSD-3-Clause" ]

null

# Copyright (c) 2009-2022 The Regents of the University of Michigan. # Part of HOOMD-blue, released under the BSD 3-Clause License. """MD integration methods.""" from hoomd.md import _md import hoomd from hoomd.operation import _HOOMDBaseObject from hoomd.data.parameterdicts import ParameterDict, TypeParameterDict from hoomd.data.typeparam import TypeParameter from hoomd.data.typeconverter import OnlyTypes, OnlyIf, to_type_converter from hoomd.filter import ParticleFilter from hoomd.variant import Variant from collections.abc import Sequence class Method(_HOOMDBaseObject): """Base class integration method. Provides common methods for all subclasses. Note: Users should use the subclasses and not instantiate `Method` directly. """ def _attach(self): self._simulation.state.update_group_dof() super()._attach() def _detach(self): self._simulation.state.update_group_dof() super()._detach() class NVT(Method): r"""Constant volume, constant temperature dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. kT (`hoomd.variant.Variant` or `float`): Temperature set point for the Nosé-Hoover thermostat :math:`[\mathrm{energy}]`. tau (float): Coupling constant for the Nosé-Hoover thermostat :math:`[\mathrm{time}]`. `NVT` integrates integrates translational and rotational degrees of freedom in the canonical ensemble using the Nosé-Hoover thermostat. The thermostat is introduced as additional degrees of freedom in the Hamiltonian that couple with the velocities and angular momenta of the particles. The translational thermostat has a momentum :math:`\xi` and position :math:`\eta`. The rotational thermostat has momentum :math:`\xi_{\mathrm{rot}}` and position :math:`\eta_\mathrm{rot}`. Access these quantities using `translational_thermostat_dof` and `rotational_thermostat_dof`. `NVT` numerically integrates the equations of motion using the symplectic Martyna-Tobias-Klein formalism described refs. `G. J. Martyna, D. J. Tobias, M. L. Klein 1994 <http://dx.doi.org/10.1063/1.467468>`_ and `J. Cao, G. J. Martyna 1996 <http://dx.doi.org/10.1063/1.470959>`_. Note: The coupling constant `tau` should be set within a reasonable range to avoid abrupt fluctuations in the kinetic temperature and to avoid long time to equilibration. The recommended value for most systems is :math:`\tau = 100 \delta t`. Important: Ensure that your initial condition includes non-zero particle velocities and angular momenta (when appropriate). The coupling between the thermostat and the velocities and angular momenta occurs via multiplication, so `NVT` cannot convert a zero velocity into a non-zero one except through particle collisions. Examples:: nvt=hoomd.md.methods.NVT(filter=hoomd.filter.All(), kT=1.0, tau=0.5) integrator = hoomd.md.Integrator(dt=0.005, methods=[nvt], forces=[lj]) Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. kT (hoomd.variant.Variant): Temperature set point for the Nosé-Hoover thermostat :math:`[\mathrm{energy}]`. tau (float): Coupling constant for the Nosé-Hoover thermostat :math:`[\mathrm{time}]`. translational_thermostat_dof (tuple[float, float]): Additional degrees of freedom for the translational thermostat (:math:`\xi`, :math:`\eta`) rotational_thermostat_dof (tuple[float, float]): Additional degrees of freedom for the rotational thermostat (:math:`\xi_\mathrm{rot}`, :math:`\eta_\mathrm{rot}`) """ def __init__(self, filter, kT, tau): # store metadata param_dict = ParameterDict(filter=ParticleFilter, kT=Variant, tau=float(tau), translational_thermostat_dof=(float, float), rotational_thermostat_dof=(float, float)) param_dict.update( dict(kT=kT, filter=filter, translational_thermostat_dof=(0, 0), rotational_thermostat_dof=(0, 0))) # set defaults self._param_dict.update(param_dict) def _attach(self): # initialize the reflected cpp class if isinstance(self._simulation.device, hoomd.device.CPU): my_class = _md.TwoStepNVTMTK thermo_cls = _md.ComputeThermo else: my_class = _md.TwoStepNVTMTKGPU thermo_cls = _md.ComputeThermoGPU group = self._simulation.state._get_group(self.filter) cpp_sys_def = self._simulation.state._cpp_sys_def thermo = thermo_cls(cpp_sys_def, group) self._cpp_obj = my_class(cpp_sys_def, group, thermo, self.tau, self.kT) super()._attach() def thermalize_thermostat_dof(self): r"""Set the thermostat momenta to random values. `thermalize_thermostat_dof` sets a random value for the momentum :math:`\xi`. When `Integrator.integrate_rotational_dof` is `True`, it also sets a random value for the rotational thermostat momentum :math:`\xi_{\mathrm{rot}}`. Call `thermalize_thermostat_dof` to set a new random state for the thermostat. .. important:: You must call `Simulation.run` before `thermalize_thermostat_dof`. Call ``run(steps=0)`` to prepare a newly created `hoomd.Simulation`. .. seealso:: `State.thermalize_particle_momenta` """ if not self._attached: raise RuntimeError( "Call Simulation.run(0) before thermalize_thermostat_dof") self._simulation._warn_if_seed_unset() self._cpp_obj.thermalizeThermostatDOF(self._simulation.timestep) @hoomd.logging.log(requires_run=True) def thermostat_energy(self): """Energy the thermostat contributes to the Hamiltonian \ :math:`[\\mathrm{energy}]`.""" return self._cpp_obj.getThermostatEnergy(self._simulation.timestep) class NPT(Method): r"""Constant pressure, constant temperature dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. kT (`hoomd.variant.Variant` or `float`): Temperature set point for the thermostat :math:`[\mathrm{energy}]`. tau (float): Coupling constant for the thermostat :math:`[\mathrm{time}]`. S: Stress components set point for the barostat. In Voigt notation: :math:`[S_{xx}, S_{yy}, S_{zz}, S_{yz}, S_{xz}, S_{xy}]` :math:`[\mathrm{pressure}]`. In case of isotropic pressure P (:math:`[p, p, p, 0, 0, 0]`), use ``S = p``. Accepts: `tuple` [ `hoomd.variant.Variant` or `float`, ... ] or `hoomd.variant.Variant` or `float`. tauS (float): Coupling constant for the barostat :math:`[\mathrm{time}]`. couple (str): Couplings of diagonal elements of the stress tensor, can be "none", "xy", "xz","yz", or "xyz". box_dof(`list` [ `bool` ]): Box degrees of freedom with six boolean elements corresponding to x, y, z, xy, xz, yz, each. Default to [True,True,True,False,False,False]). If turned on to True, rescale corresponding lengths or tilt factors and components of particle coordinates and velocities. rescale_all (bool): if True, rescale all particles, not only those in the group, Default to False. gamma (float): Dimensionless damping factor for the box degrees of freedom, Default to 0. `NPT` integrates integrates translational and rotational degrees of freedom in the Isothermal-isobaric ensemble. The thermostat and barostat are introduced as additional degrees of freedom in the Hamiltonian that couple with the particle velocities and angular momenta and the box parameters. The translational thermostat has a momentum :math:`\xi` and position :math:`\eta`. The rotational thermostat has momentum :math:`\xi_{\mathrm{rot}}` and position :math:`\eta_\mathrm{rot}`. The barostat tensor is :math:`\nu_{\mathrm{ij}}`. Access these quantities using `translational_thermostat_dof`, `rotational_thermostat_dof`, and `barostat_dof`. By default, `NPT` performs integration in a cubic box under hydrostatic pressure by simultaneously rescaling the lengths *Lx*, *Ly* and *Lz* of the simulation box. Set the integration mode to change this default. The integration mode is defined by a set of couplings and by specifying the box degrees of freedom that are put under barostat control. Couplings define which diagonal elements of the pressure tensor :math:`P_{\alpha,\beta}` should be averaged over, so that the corresponding box lengths are rescaled by the same amount. Valid couplings are: - ``'none'`` (all box lengths are updated independently) - ``'xy`'`` (*Lx* and *Ly* are coupled) - ``'xz`'`` (*Lx* and *Lz* are coupled) - ``'yz`'`` (*Ly* and *Lz* are coupled) - ``'xyz`'`` (*Lx*, *Ly*, and *Lz* are coupled) Degrees of freedom of the box specify which lengths and tilt factors of the box should be updated, and how particle coordinates and velocities should be rescaled. The ``box_dof`` tuple controls the way the box is rescaled and updated. The first three elements ``box_dof[:3]`` controls whether the x, y, and z box lengths are rescaled and updated, respectively. The last three entries ``box_dof[3:]`` control the rescaling or the tilt factors xy, xz, and yz. All options also appropriately rescale particle coordinates and velocities. By default, the x, y, and z degrees of freedom are updated. ``[True,True,True,False,False,False]`` Note: If any of the diagonal x, y, z degrees of freedom is not being integrated, pressure tensor components along that direction are not considered for the remaining degrees of freedom. For example: - Specifying all couplings and x, y, and z degrees of freedom amounts to cubic symmetry (default) - Specifying xy couplings and x, y, and z degrees of freedom amounts to tetragonal symmetry. - Specifying no couplings and all degrees of freedom amounts to a fully deformable triclinic unit cell `NPT` numerically integrates the equations of motion using the symplectic Martyna-Tobias-Klein equations of motion for NPT. For optimal stability, the update equations leave the phase-space measure invariant and are manifestly time-reversible. See Also: * `G. J. Martyna, D. J. Tobias, M. L. Klein 1994 <http://dx.doi.org/10.1063/1.467468>`__ * `M. E. Tuckerman et. al. 2006 <http://dx.doi.org/10.1088/0305-4470/39/19/S18>`__ * `T. Yu et. al. 2010 <http://dx.doi.org/10.1016/j.chemphys.2010.02.014>`_ Note: The coupling constant `tau` should be set within a reasonable range to avoid abrupt fluctuations in the kinetic temperature and to avoid long time to equilibration. The recommended value for most systems is :math:`\tau = 100 \delta t`. Note: The barostat coupling constant `tauS` should be set within a reasonable range to avoid abrupt fluctuations in the box volume and to avoid long time to equilibration. The recommend value for most systems is :math:`\tau_S = 1000 \delta t`. Important: Ensure that your initial condition includes non-zero particle velocities and angular momenta (when appropriate). The coupling between the thermostat and the velocities and angular momenta occurs via multiplication, so `NPT` cannot convert a zero velocity into a non-zero one except through particle collisions. Examples:: npt = hoomd.md.methods.NPT(filter=hoomd.filter.All(), tau=1.0, kT=0.65, tauS = 1.2, S=2.0, couple="xyz") # orthorhombic symmetry npt = hoomd.md.methods.NPT(filter=hoomd.filter.All(), tau=1.0, kT=0.65, tauS = 1.2, S=2.0, couple="none") # tetragonal symmetry npt = hoomd.md.methods.NPT(filter=hoomd.filter.All(), tau=1.0, kT=0.65, tauS = 1.2, S=2.0, couple="xy") # triclinic symmetry npt = hoomd.md.methods.NPT(filter=hoomd.filter.All(), tau=1.0, kT=0.65, tauS = 1.2, S=2.0, couple="none", rescale_all=True) integrator = hoomd.md.Integrator(dt=0.005, methods=[npt], forces=[lj]) Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. kT (hoomd.variant.Variant): Temperature set point for the thermostat :math:`[\mathrm{energy}]`. tau (float): Coupling constant for the thermostat :math:`[\mathrm{time}]`. S (list[hoomd.variant.Variant]): Stress components set point for the barostat. In Voigt notation, :math:`[S_{xx}, S_{yy}, S_{zz}, S_{yz}, S_{xz}, S_{xy}]` :math:`[\mathrm{pressure}]`. Stress can be reset after the method object is created. For example, an isotropic pressure can be set by ``npt.S = 4.`` tauS (float): Coupling constant for the barostat :math:`[\mathrm{time}]`. couple (str): Couplings of diagonal elements of the stress tensor, can be "none", "xy", "xz","yz", or "xyz". box_dof(list[bool]): Box degrees of freedom with six boolean elements corresponding to x, y, z, xy, xz, yz, each. rescale_all (bool): if True, rescale all particles, not only those in the group. gamma (float): Dimensionless damping factor for the box degrees of freedom. translational_thermostat_dof (tuple[float, float]): Additional degrees of freedom for the translational thermostat (:math:`\xi`, :math:`\eta`) rotational_thermostat_dof (tuple[float, float]): Additional degrees of freedom for the rotational thermostat (:math:`\xi_\mathrm{rot}`, :math:`\eta_\mathrm{rot}`) barostat_dof (tuple[float, float, float, float, float, float]): Additional degrees of freedom for the barostat (:math:`\nu_{xx}`, :math:`\nu_{xy}`, :math:`\nu_{xz}`, :math:`\nu_{yy}`, :math:`\nu_{yz}`, :math:`\nu_{zz}`) """ def __init__(self, filter, kT, tau, S, tauS, couple, box_dof=[True, True, True, False, False, False], rescale_all=False, gamma=0.0): # store metadata param_dict = ParameterDict(filter=ParticleFilter, kT=Variant, tau=float(tau), S=OnlyIf(to_type_converter((Variant,) * 6), preprocess=self._preprocess_stress), tauS=float(tauS), couple=str(couple), box_dof=[ bool, ] * 6, rescale_all=bool(rescale_all), gamma=float(gamma), translational_thermostat_dof=(float, float), rotational_thermostat_dof=(float, float), barostat_dof=(float, float, float, float, float, float)) param_dict.update( dict(filter=filter, kT=kT, S=S, couple=couple, box_dof=box_dof, translational_thermostat_dof=(0, 0), rotational_thermostat_dof=(0, 0), barostat_dof=(0, 0, 0, 0, 0, 0))) # set defaults self._param_dict.update(param_dict) def _attach(self): # initialize the reflected c++ class if isinstance(self._simulation.device, hoomd.device.CPU): cpp_cls = _md.TwoStepNPTMTK thermo_cls = _md.ComputeThermo else: cpp_cls = _md.TwoStepNPTMTKGPU thermo_cls = _md.ComputeThermoGPU cpp_sys_def = self._simulation.state._cpp_sys_def thermo_group = self._simulation.state._get_group(self.filter) thermo_half_step = thermo_cls(cpp_sys_def, thermo_group) thermo_full_step = thermo_cls(cpp_sys_def, thermo_group) self._cpp_obj = cpp_cls(cpp_sys_def, thermo_group, thermo_half_step, thermo_full_step, self.tau, self.tauS, self.kT, self.S, self.couple, self.box_dof, False) # Attach param_dict and typeparam_dict super()._attach() def _preprocess_stress(self, value): if isinstance(value, Sequence): if len(value) != 6: raise ValueError( "Expected a single hoomd.variant.Variant / float or six.") return tuple(value) else: return (value, value, value, 0, 0, 0) def thermalize_thermostat_and_barostat_dof(self): r"""Set the thermostat and barostat momenta to random values. `thermalize_thermostat_and_barostat_dof` sets a random value for the momentum :math:`\xi` and the barostat :math:`\nu_{\mathrm{ij}}`. When `Integrator.integrate_rotational_dof` is `True`, it also sets a random value for the rotational thermostat momentum :math:`\xi_{\mathrm{rot}}`. Call `thermalize_thermostat_and_barostat_dof` to set a new random state for the thermostat and barostat. .. important:: You must call `Simulation.run` before `thermalize_thermostat_and_barostat_dof`. Call ``run(steps=0)`` to prepare a newly created `hoomd.Simulation`. .. seealso:: `State.thermalize_particle_momenta` """ if not self._attached: raise RuntimeError("Call Simulation.run(0) before" "thermalize_thermostat_and_barostat_dof") self._simulation._warn_if_seed_unset() self._cpp_obj.thermalizeThermostatAndBarostatDOF( self._simulation.timestep) @hoomd.logging.log(requires_run=True) def thermostat_energy(self): """Energy the thermostat contributes to the Hamiltonian \ :math:`[\\mathrm{energy}]`.""" return self._cpp_obj.getThermostatEnergy(self._simulation.timestep) @hoomd.logging.log(requires_run=True) def barostat_energy(self): """Energy the barostat contributes to the Hamiltonian \ :math:`[\\mathrm{energy}]`.""" return self._cpp_obj.getBarostatEnergy(self._simulation.timestep) class NPH(Method): r"""Constant pressure, constant enthalpy dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. S: Stress components set point for the barostat. In Voigt notation: :math:`[S_{xx}, S_{yy}, S_{zz}, S_{yz}, S_{xz}, S_{xy}]` :math:`[\mathrm{pressure}]`. In case of isotropic pressure P (:math:`[p, p, p, 0, 0, 0]`), use ``S = p``. Accepts: `tuple` [ `hoomd.variant.Variant` or `float`, ... ] or `hoomd.variant.Variant` or `float`. tauS (float): Coupling constant for the barostat :math:`[\mathrm{time}]`. couple (str): Couplings of diagonal elements of the stress tensor, can be "none", "xy", "xz","yz", or "all", default to "all". box_dof(`tuple` [ `bool` ]): Box degrees of freedom with six boolean elements corresponding to x, y, z, xy, xz, yz, each. Default to [True,True,True,False,False,False]). If turned on to True, rescale corresponding lengths or tilt factors and components of particle coordinates and velocities. rescale_all (bool): if True, rescale all particles, not only those in the group, Default to False. gamma (float): Dimensionless damping factor for the box degrees of freedom, Default to 0. `NPH` integrates translational and rotational degrees of freedom forward in time in the Isoenthalpic-isobaric ensemble. The barostat is introduced as additional degrees of freedom in the Hamiltonian that couple with the box parameters. The barostat tensor is :math:`\nu_{\mathrm{ij}}`. Access these quantities `barostat_dof`. See Also: Except for the thermostat, `NPH` shares parameters with `NPT`. See `NPT` for descriptions of the coupling and other barostat parameters. Examples:: dt = 0.005 tauS = 1000 * dt nph = hoomd.md.methods.NPH(filter=hoomd.filter.All(), tauS=tauS, S=2.0) # orthorhombic symmetry nph = hoomd.md.methods.NPH(filter=hoomd.filter.All(), tauS=tauS, S=2.0, couple="none") # tetragonal symmetry nph = hoomd.md.methods.NPH(filter=hoomd.filter.All(), tauS=tauS, S=2.0, couple="xy") # triclinic symmetry nph = hoomd.md.methods.NPH(filter=hoomd.filter.All(), tauS=tauS, S=2.0, couple="none", rescale_all=True) integrator = hoomd.md.Integrator(dt=dt, methods=[nph], forces=[lj]) Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. S (`tuple` [`hoomd.variant.Variant`, ...]): Stress components set point for the barostat totalling 6 components. In Voigt notation, :math:`[S_{xx}, S_{yy}, S_{zz}, S_{yz}, S_{xz}, S_{xy}]` :math:`[\mathrm{pressure}]`. Stress can be reset after method object is created. For example, an isotopic pressure can be set by ``nph.S = 4.`` tauS (float): Coupling constant for the barostat :math:`[\mathrm{time}]`. couple (str): Couplings of diagonal elements of the stress tensor, can be "none", "xy", "xz","yz", or "all". box_dof(tuple[bool, bool, bool, bool, bool, bool]): Box degrees of freedom with six boolean elements corresponding to x, y, z, xy, xz, yz, each. rescale_all (bool): if True, rescale all particles, not only those in the group. gamma (float): Dimensionless damping factor for the box degrees of freedom. barostat_dof (tuple[float, float, float, float, float, float]): Additional degrees of freedom for the barostat (:math:`\nu_{xx}`, :math:`\nu_{xy}`, :math:`\nu_{xz}`, :math:`\nu_{yy}`, :math:`\nu_{yz}`, :math:`\nu_{zz}`) """ def __init__(self, filter, S, tauS, couple, box_dof=(True, True, True, False, False, False), rescale_all=False, gamma=0.0): # store metadata param_dict = ParameterDict(filter=ParticleFilter, kT=Variant, S=OnlyIf(to_type_converter((Variant,) * 6), preprocess=self._preprocess_stress), tauS=float, couple=str, box_dof=(bool,) * 6, rescale_all=bool, gamma=float, barostat_dof=(float,) * 6) param_dict.update( dict(filter=filter, kT=hoomd.variant.Constant(1.0), S=S, tauS=float(tauS), couple=str(couple), box_dof=tuple(box_dof), rescale_all=bool(rescale_all), gamma=float(gamma), barostat_dof=(0.0, 0.0, 0.0, 0.0, 0.0, 0.0))) # set defaults self._param_dict.update(param_dict) def _attach(self): # initialize the reflected c++ class if isinstance(self._simulation.device, hoomd.device.CPU): cpp_cls = _md.TwoStepNPTMTK thermo_cls = _md.ComputeThermo else: cpp_cls = _md.TwoStepNPTMTKGPU thermo_cls = _md.ComputeThermoGPU cpp_sys_def = self._simulation.state._cpp_sys_def thermo_group = self._simulation.state._get_group(self.filter) thermo_half_step = thermo_cls(cpp_sys_def, thermo_group) thermo_full_step = thermo_cls(cpp_sys_def, thermo_group) self._cpp_obj = cpp_cls(cpp_sys_def, thermo_group, thermo_half_step, thermo_full_step, 1.0, self.tauS, self.kT, self.S, self.couple, self.box_dof, True) # Attach param_dict and typeparam_dict super()._attach() @staticmethod def _preprocess_stress(value): if isinstance(value, Sequence): if len(value) != 6: raise ValueError( "Expected a single hoomd.variant.Variant / float or six.") return tuple(value) else: return (value, value, value, 0, 0, 0) def thermalize_barostat_dof(self): r"""Set the barostat momentum to random values. `thermalize_barostat_dof` sets a random value for the barostat :math:`\nu_{\mathrm{ij}}`. Call `thermalize_barostat_dof` to set a new random state for the barostat. .. important:: You must call `Simulation.run` before `thermalize_barostat_dof`. Call ``run(steps=0)`` to prepare a newly created `hoomd.Simulation`. .. seealso:: `State.thermalize_particle_momenta` """ if not self._attached: raise RuntimeError("Call Simulation.run(0) before" "thermalize_thermostat_and_barostat_dof") self._simulation._warn_if_seed_unset() self._cpp_obj.thermalizeThermostatAndBarostatDOF( self._simulation.timestep) @hoomd.logging.log(requires_run=True) def barostat_energy(self): """Energy the barostat contributes to the Hamiltonian \ :math:`[\\mathrm{energy}]`.""" return self._cpp_obj.getBarostatEnergy(self._simulation.timestep) class NVE(Method): r"""Constant volume, constant energy dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. `NVE` integrates integrates translational and rotational degrees of freedom in the microcanonical ensemble. The equations of motion are derived from the hamiltonian: .. math:: H = U + K_\mathrm{translational} + K_\mathrm{rotational} `NVE` numerically integrates the translational degrees of freedom using Velocity-Verlet and the rotational degrees of freedom with a scheme based on `Kamberaj 2005`_. Examples:: nve = hoomd.md.methods.NVE(filter=hoomd.filter.All()) integrator = hoomd.md.Integrator(dt=0.005, methods=[nve], forces=[lj]) .. _Kamberaj 2005: http://dx.doi.org/10.1063/1.1906216 Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles on which to apply this method. """ def __init__(self, filter): # store metadata param_dict = ParameterDict(filter=ParticleFilter,) param_dict.update(dict(filter=filter, zero_force=False)) # set defaults self._param_dict.update(param_dict) def _attach(self): sim = self._simulation # initialize the reflected c++ class if isinstance(sim.device, hoomd.device.CPU): self._cpp_obj = _md.TwoStepNVE(sim.state._cpp_sys_def, sim.state._get_group(self.filter)) else: self._cpp_obj = _md.TwoStepNVEGPU(sim.state._cpp_sys_def, sim.state._get_group(self.filter)) # Attach param_dict and typeparam_dict super()._attach() class Langevin(Method): r"""Langevin dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (`hoomd.variant.Variant` or `float`): Temperature of the simulation :math:`[\mathrm{energy}]`. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. Defaults to None. tally_reservoir_energy (bool): If true, the energy exchange between the thermal reservoir and the particles is tracked. Total energy conservation can then be monitored by adding ``langevin_reservoir_energy_groupname`` to the logged quantities. Defaults to False :math:`[\mathrm{energy}]`. `Langevin` integrates particles forward in time according to the Langevin equations of motion. The translational degrees of freedom follow: .. math:: m \frac{d\vec{v}}{dt} &= \vec{F}_\mathrm{C} - \gamma \cdot \vec{v} + \vec{F}_\mathrm{R} \langle \vec{F}_\mathrm{R} \rangle &= 0 \langle |\vec{F}_\mathrm{R}|^2 \rangle &= 2 d kT \gamma / \delta t where :math:`\vec{F}_\mathrm{C}` is the force on the particle from all potentials and constraint forces, :math:`\gamma` is the drag coefficient, :math:`\vec{v}` is the particle's velocity, :math:`\vec{F}_\mathrm{R}` is a uniform random force, and :math:`d` is the dimensionality of the system (2 or 3). The magnitude of the random force is chosen via the fluctuation-dissipation theorem to be consistent with the specified drag and temperature, :math:`T`. About axes where :math:`I^i > 0`, the rotational degrees of freedom follow: .. math:: I \frac{d\vec{L}}{dt} &= \vec{\tau}_\mathrm{C} - \gamma_r \cdot \vec{L} + \vec{\tau}_\mathrm{R} \langle \vec{\tau}_\mathrm{R} \rangle &= 0, \langle \tau_\mathrm{R}^i \cdot \tau_\mathrm{R}^i \rangle &= 2 k T \gamma_r^i / \delta t, where :math:`\vec{\tau}_\mathrm{C} = \vec{\tau}_\mathrm{net}`, :math:`\gamma_r^i` is the i-th component of the rotational drag coefficient (`gamma_r`), :math:`\tau_\mathrm{R}^i` is a component of the uniform random the torque, :math:`\vec{L}` is the particle's angular momentum and :math:`I` is the the particle's moment of inertia. The magnitude of the random torque is chosen via the fluctuation-dissipation theorem to be consistent with the specified drag and temperature, :math:`T`. `Langevin` numerically integrates the translational degrees of freedom using Velocity-Verlet and the rotational degrees of freedom with a scheme based on `Kamberaj 2005`_. Langevin dynamics includes the acceleration term in the Langevin equation. This assumption is valid when underdamped: :math:`\frac{m}{\gamma} \gg \delta t`. Use `Brownian` if your system is not underdamped. You can set :math:`\gamma` in two ways: 1. Specify :math:`\alpha` which scales the particle diameter to :math:`\gamma = \alpha d_i`. 2. After the method object is created, specify the attribute `gamma` and `gamma_r` for rotational damping or random torque to assign them directly, with independent values for each particle type in the system. Examples:: langevin = hoomd.md.methods.Langevin(filter=hoomd.filter.All(), kT=0.2, alpha=1.0) integrator = hoomd.md.Integrator(dt=0.001, methods=[langevin], forces=[lj]) Examples of using `gamma` and `gamma_r`:: langevin = hoomd.md.methods.Langevin(filter=hoomd.filter.All(), kT=0.2) langevin.gamma.default = 2.0 langevin.gamma_r.default = [1.0,2.0,3.0] Warning: When restarting a simulation, the energy of the reservoir will be reset to zero. .. _Kamberaj 2005: http://dx.doi.org/10.1063/1.1906216 Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (hoomd.variant.Variant): Temperature of the simulation :math:`[\mathrm{energy}]`. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. Defaults to None. gamma (TypeParameter[ ``particle type``, `float` ]): The drag coefficient can be directly set instead of the ratio of particle diameter (:math:`\gamma = \alpha d_i`). The type of ``gamma`` parameter is either positive float or zero :math:`[\mathrm{mass} \cdot \mathrm{time}^{-1}]`. gamma_r (TypeParameter[``particle type``,[`float`, `float` , `float`]]): The rotational drag coefficient can be set. The type of ``gamma_r`` parameter is a tuple of three float. The type of each element of tuple is either positive float or zero :math:`[\mathrm{mass} \cdot \mathrm{time}^{-1}]`. """ def __init__(self, filter, kT, alpha=None, tally_reservoir_energy=False): # store metadata param_dict = ParameterDict( filter=ParticleFilter, kT=Variant, alpha=OnlyTypes(float, allow_none=True), tally_reservoir_energy=bool(tally_reservoir_energy), ) param_dict.update(dict(kT=kT, alpha=alpha, filter=filter)) # set defaults self._param_dict.update(param_dict) gamma = TypeParameter('gamma', type_kind='particle_types', param_dict=TypeParameterDict(1., len_keys=1)) gamma_r = TypeParameter('gamma_r', type_kind='particle_types', param_dict=TypeParameterDict((1., 1., 1.), len_keys=1)) self._extend_typeparam([gamma, gamma_r]) def _add(self, simulation): """Add the operation to a simulation. Langevin uses RNGs. Warn the user if they did not set the seed. """ if isinstance(simulation, hoomd.Simulation): simulation._warn_if_seed_unset() super()._add(simulation) def _attach(self): sim = self._simulation if isinstance(sim.device, hoomd.device.CPU): my_class = _md.TwoStepLangevin else: my_class = _md.TwoStepLangevinGPU self._cpp_obj = my_class(sim.state._cpp_sys_def, sim.state._get_group(self.filter), self.kT) # Attach param_dict and typeparam_dict super()._attach() class Brownian(Method): r"""Brownian dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (`hoomd.variant.Variant` or `float`): Temperature of the simulation :math:`[\mathrm{energy}]`. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. Defaults to ``None`` `Brownian` integrates particles forward in time according to the overdamped Langevin equations of motion, sometimes called Brownian dynamics or the diffusive limit. It integrates both the translational and rotational degrees of freedom. The translational degrees of freedom follow: .. math:: \frac{d\vec{r}}{dt} &= \frac{\vec{F}_\mathrm{C} + \vec{F}_\mathrm{R}}{\gamma}, \langle \vec{F}_\mathrm{R} \rangle &= 0, \langle |\vec{F}_\mathrm{R}|^2 \rangle &= 2 d k T \gamma / \delta t, \langle \vec{v}(t) \rangle &= 0, \langle |\vec{v}(t)|^2 \rangle &= d k T / m, where :math:`\vec{F}_\mathrm{C} = \vec{F}_\mathrm{net}` is the net force on the particle from all forces (`hoomd.md.Integrator.forces`) and constraints (`hoomd.md.Integrator.constraints`), :math:`\gamma` is the translational drag coefficient (`gamma`), :math:`\vec{F}_\mathrm{R}` is a uniform random force, :math:`\vec{v}` is the particle's velocity, and :math:`d` is the dimensionality of the system. The magnitude of the random force is chosen via the fluctuation-dissipation theorem to be consistent with the specified drag and temperature, :math:`T`. About axes where :math:`I^i > 0`, the rotational degrees of freedom follow: .. math:: \frac{d\mathbf{q}}{dt} &= \frac{\vec{\tau}_\mathrm{C} + \vec{\tau}_\mathrm{R}}{\gamma_r}, \langle \vec{\tau}_\mathrm{R} \rangle &= 0, \langle \tau_\mathrm{R}^i \cdot \tau_\mathrm{R}^i \rangle &= 2 k T \gamma_r^i / \delta t, \langle \vec{L}(t) \rangle &= 0, \langle L^i(t) \cdot L^i(t) \rangle &= k T \cdot I^i, where :math:`\vec{\tau}_\mathrm{C} = \vec{\tau}_\mathrm{net}`, :math:`\gamma_r^i` is the i-th component of the rotational drag coefficient (`gamma_r`), :math:`\tau_\mathrm{R}^i` is a component of the uniform random the torque, :math:`L^i` is the i-th component of the particle's angular momentum and :math:`I^i` is the i-th component of the particle's moment of inertia. The magnitude of the random torque is chosen via the fluctuation-dissipation theorem to be consistent with the specified drag and temperature, :math:`T`. `Brownian` uses the numerical integration method from `I. Snook 2007`_, The Langevin and Generalised Langevin Approach to the Dynamics of Atomic, Polymeric and Colloidal Systems, section 6.2.5, with the exception that :math:`\vec{F}_\mathrm{R}` is drawn from a uniform random number distribution. .. _I. Snook 2007: http://dx.doi.org/10.1016/B978-0-444-52129-3.50028-6 In Brownian dynamics, particle velocities and angular momenta are completely decoupled from positions. At each time step, `Brownian` draws a new velocity distribution consistent with the current set temperature so that `hoomd.md.compute.ThermodynamicQuantities` will report appropriate temperatures and pressures when logged or used by other methods. Brownian dynamics neglects the acceleration term in the Langevin equation. This assumption is valid when overdamped: :math:`\frac{m}{\gamma} \ll \delta t`. Use `Langevin` if your system is not overdamped. You can set :math:`\gamma` in two ways: 1. Specify :math:`\alpha` which scales the particle diameter to :math:`\gamma = \alpha d_i`. 2. After the method object is created, specify the attribute `gamma` and `gamma_r` for rotational damping or random torque to assign them directly, with independent values for each particle type in the system. Examples:: brownian = hoomd.md.methods.Brownian(filter=hoomd.filter.All(), kT=0.2, alpha=1.0) integrator = hoomd.md.Integrator(dt=0.001, methods=[brownian], forces=[lj]) Examples of using `gamma` and `gamma_r`:: brownian = hoomd.md.methods.Brownian(filter=hoomd.filter.All(), kT=0.2) brownian.gamma.default = 2.0 brownian.gamma_r.default = [1.0, 2.0, 3.0] Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (hoomd.variant.Variant): Temperature of the simulation :math:`[\mathrm{energy}]`. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. gamma (TypeParameter[ ``particle type``, `float` ]): The drag coefficient can be directly set instead of the ratio of particle diameter (:math:`\gamma = \alpha d_i`). The type of ``gamma`` parameter is either positive float or zero :math:`[\mathrm{mass} \cdot \mathrm{time}^{-1}]`. gamma_r (TypeParameter[``particle type``, [`float`, `float`, `float`]]): The rotational drag coefficient can be set. The type of ``gamma_r`` parameter is a tuple of three float. The type of each element of tuple is either positive float or zero :math:`[\mathrm{force} \cdot \mathrm{length} \cdot \mathrm{radian}^{-1} \cdot \mathrm{time}^{-1}]`. """ def __init__(self, filter, kT, alpha=None): # store metadata param_dict = ParameterDict( filter=ParticleFilter, kT=Variant, alpha=OnlyTypes(float, allow_none=True), ) param_dict.update(dict(kT=kT, alpha=alpha, filter=filter)) # set defaults self._param_dict.update(param_dict) gamma = TypeParameter('gamma', type_kind='particle_types', param_dict=TypeParameterDict(1., len_keys=1)) gamma_r = TypeParameter('gamma_r', type_kind='particle_types', param_dict=TypeParameterDict((1., 1., 1.), len_keys=1)) self._extend_typeparam([gamma, gamma_r]) def _add(self, simulation): """Add the operation to a simulation. Brownian uses RNGs. Warn the user if they did not set the seed. """ if isinstance(simulation, hoomd.Simulation): simulation._warn_if_seed_unset() super()._add(simulation) def _attach(self): sim = self._simulation if isinstance(sim.device, hoomd.device.CPU): self._cpp_obj = _md.TwoStepBD(sim.state._cpp_sys_def, sim.state._get_group(self.filter), self.kT, False, False) else: self._cpp_obj = _md.TwoStepBDGPU(sim.state._cpp_sys_def, sim.state._get_group(self.filter), self.kT, False, False) # Attach param_dict and typeparam_dict super()._attach() class Berendsen(Method): r"""Applies the Berendsen thermostat. Args: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (`hoomd.variant.Variant` or `float`): Temperature of the simulation. :math:`[energy]` tau (float): Time constant of thermostat. :math:`[time]` `Berendsen` rescales the velocities of all particles on each time step. The rescaling is performed so that the difference in the current temperature from the set point decays exponentially: `Berendsen et. al. 1984 <http://dx.doi.org/10.1063/1.448118>`_. .. math:: \frac{dT_\mathrm{cur}}{dt} = \frac{T - T_\mathrm{cur}}{\tau} .. attention:: `Berendsen` does not function with MPI parallel simulations. .. attention:: `Berendsen` does not integrate rotational degrees of freedom. Examples:: berendsen = hoomd.md.methods.Berendsen( filter=hoomd.filter.All(), kT=0.2, tau=10.0) integrator = hoomd.md.Integrator( dt=0.001, methods=[berendsen], forces=[lj]) Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. kT (hoomd.variant.Variant): Temperature of the simulation. :math:`[energy]` tau (float): Time constant of thermostat. :math:`[time]` """ def __init__(self, filter, kT, tau): # store metadata param_dict = ParameterDict(filter=ParticleFilter, kT=Variant, tau=float(tau)) param_dict.update(dict(filter=filter, kT=kT)) # set defaults self._param_dict.update(param_dict) def _attach(self): sim = self._simulation # Error out in MPI simulations if hoomd.version.mpi_enabled: if sim.device._comm.num_ranks > 1: raise RuntimeError( "hoomd.md.methods.Berendsen is not supported in " "multi-processor simulations.") group = sim.state._get_group(self.filter) if isinstance(sim.device, hoomd.device.CPU): cpp_method = _md.TwoStepBerendsen thermo_cls = _md.ComputeThermo else: cpp_method = _md.TwoStepBerendsenGPU thermo_cls = _md.ComputeThermoGPU self._cpp_obj = cpp_method(sim.state._cpp_sys_def, group, thermo_cls(sim.state._cpp_sys_def, group), self.tau, self.kT) super()._attach() class OverdampedViscous(Method): r"""Overdamped viscous dynamics. Args: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. Defaults to ``None`` `OverdampedViscous` integrates particles forward in time following Newtonian dynamics in the overdamped limit where there is no inertial term. (in the limit that the mass :math:`m` and moment of inertia :math:`I` go to 0): .. math:: \frac{d\vec{r}}{dt} &= \vec{v} \vec{v(t)} &= \frac{\vec{F}_\mathrm{C}}{\gamma} \frac{d\mathbf{q}}{dt} &= \vec{\tau} \tau^i &= \frac{\tau_\mathrm{C}^i}{\gamma_r^i} where :math:`\vec{F}_\mathrm{C} = \vec{F}_\mathrm{net}` is the net force on the particle from all forces (`hoomd.md.Integrator.forces`) and constraints (`hoomd.md.Integrator.constraints`), :math:`\gamma` is the translational drag coefficient (`gamma`) :math:`\vec{v}` is the particle's velocity, :math:`d` is the dimensionality of the system, :math:`\tau_\mathrm{C}^i` is the i-th component of the net torque from all forces and constraints, and :math:`\gamma_r^i` is the i-th component of the rotational drag coefficient (`gamma_r`). You can set :math:`\gamma` in two ways: 1. Specify :math:`\alpha` which scales the particle diameter to :math:`\gamma = \alpha d_i`. 2. After the method object is created, specify the attribute `gamma` and `gamma_r` for rotational damping or random torque to assign them directly, with independent values for each particle type in the system. Tip: `OverdampedViscous` can be used to simulate systems of athermal active matter, such as athermal Active Brownian Particles. Note: Even though `OverdampedViscous` models systems in the limit that :math:`m` and moment of inertia :math:`I` go to 0, you must still set non-zero moments of inertia to enable the integration of rotational degrees of freedom. Examples:: odv = hoomd.md.methods.OverdampedViscous(filter=hoomd.filter.All()) odv.gamma.default = 2.0 odv.gamma_r.default = [1.0, 2.0, 3.0] Attributes: filter (hoomd.filter.ParticleFilter): Subset of particles to apply this method to. alpha (float): When set, use :math:`\alpha d_i` for the drag coefficient where :math:`d_i` is particle diameter :math:`[\mathrm{mass} \cdot \mathrm{length}^{-1} \cdot \mathrm{time}^{-1}]`. gamma (TypeParameter[ ``particle type``, `float` ]): The drag coefficient can be directly set instead of the ratio of particle diameter (:math:`\gamma = \alpha d_i`). The type of ``gamma`` parameter is either positive float or zero :math:`[\mathrm{mass} \cdot \mathrm{time}^{-1}]`. gamma_r (TypeParameter[``particle type``, [`float`, `float`, `float`]]): The rotational drag coefficient can be set. The type of ``gamma_r`` parameter is a tuple of three float. The type of each element of tuple is either positive float or zero :math:`[\mathrm{force} \cdot \mathrm{length} \cdot \mathrm{radian}^{-1} \cdot \mathrm{time}^{-1}]`. """ def __init__(self, filter, alpha=None): # store metadata param_dict = ParameterDict( filter=ParticleFilter, alpha=OnlyTypes(float, allow_none=True), ) param_dict.update(dict(alpha=alpha, filter=filter)) # set defaults self._param_dict.update(param_dict) gamma = TypeParameter('gamma', type_kind='particle_types', param_dict=TypeParameterDict(1., len_keys=1)) gamma_r = TypeParameter('gamma_r', type_kind='particle_types', param_dict=TypeParameterDict((1., 1., 1.), len_keys=1)) self._extend_typeparam([gamma, gamma_r]) def _add(self, simulation): """Add the operation to a simulation. OverdampedViscous uses RNGs. Warn the user if they did not set the seed. """ if isinstance(simulation, hoomd.Simulation): simulation._warn_if_seed_unset() super()._add(simulation) def _attach(self): sim = self._simulation if isinstance(sim.device, hoomd.device.CPU): self._cpp_obj = _md.TwoStepBD(sim.state._cpp_sys_def, sim.state._get_group(self.filter), hoomd.variant.Constant(0.0), True, True) else: self._cpp_obj = _md.TwoStepBDGPU(sim.state._cpp_sys_def, sim.state._get_group(self.filter), hoomd.variant.Constant(1.0), True, True) # Attach param_dict and typeparam_dict super()._attach()

40.180469

80

0.60763

6,380

51,431

4.786677

0.098276

0.012967

0.020957

0.016242

0.795475

0.77013

0.74878

0.726055

0.701267

0.673598

0

0.012707

0.288464

51,431

1,279

81

40.211884

0.821806

0.645681

0

0.678679

0

0.031908

0.010916

0

1

0.09009

false

0

0.027027

0

0.168168

0

null

0

1

0

null

0

5

543e8b21599892b0fb3c577a9eff85dfe9bcf9c4

8,494

py

Python

tests/test_linear_model.py

slitayem/explainerdashboard

46ae301b4785ccf26fb13ddac182538aab5acf13

[ "MIT" ]

null

tests/test_linear_model.py

slitayem/explainerdashboard

46ae301b4785ccf26fb13ddac182538aab5acf13

[ "MIT" ]

null

tests/test_linear_model.py

slitayem/explainerdashboard

46ae301b4785ccf26fb13ddac182538aab5acf13

[ "MIT" ]

null

import unittest import pandas as pd import numpy as np from sklearn.metrics import r2_score, roc_auc_score import pdpbox import plotly.graph_objects as go from sklearn.linear_model import LinearRegression, LogisticRegression from explainerdashboard.explainers import RegressionExplainer, ClassifierExplainer from explainerdashboard.datasets import titanic_fare, titanic_survive, titanic_names class LinearRegressionTests(unittest.TestCase): def setUp(self): X_train, y_train, X_test, y_test = titanic_fare() self.test_len = len(X_test) train_names, test_names = titanic_names() _, self.names = titanic_names() model = LinearRegression() model.fit(X_train, y_train) self.explainer = RegressionExplainer(model, X_test, y_test, r2_score, shap='linear', cats=['Sex', 'Deck', 'Embarked'], idxs=test_names, units="$") def test_explainer_len(self): self.assertEqual(len(self.explainer), self.test_len) def test_int_idx(self): self.assertEqual(self.explainer.get_int_idx(self.names[0]), 0) def test_random_index(self): self.assertIsInstance(self.explainer.random_index(), int) self.assertIsInstance(self.explainer.random_index(return_str=True), str) def test_preds(self): self.assertIsInstance(self.explainer.preds, np.ndarray) def test_pred_percentiles(self): self.assertIsInstance(self.explainer.pred_percentiles, np.ndarray) def test_permutation_importances(self): self.assertIsInstance(self.explainer.permutation_importances, pd.DataFrame) self.assertIsInstance(self.explainer.permutation_importances_cats, pd.DataFrame) def test_metrics(self): self.assertIsInstance(self.explainer.metrics(), dict) self.assertIsInstance(self.explainer.metrics_markdown(), str) def test_mean_abs_shap_df(self): self.assertIsInstance(self.explainer.mean_abs_shap_df(), pd.DataFrame) def test_top_interactions(self): self.assertIsInstance(self.explainer.shap_top_interactions("Age"), list) self.assertIsInstance(self.explainer.shap_top_interactions("Age", topx=4), list) self.assertIsInstance(self.explainer.shap_top_interactions("Age", cats=True), list) self.assertIsInstance(self.explainer.shap_top_interactions("Sex", cats=True), list) def test_contrib_df(self): self.assertIsInstance(self.explainer.contrib_df(0), pd.DataFrame) self.assertIsInstance(self.explainer.contrib_df(0, cats=False), pd.DataFrame) self.assertIsInstance(self.explainer.contrib_df(0, topx=3), pd.DataFrame) def test_shap_base_value(self): self.assertIsInstance(self.explainer.shap_base_value, (np.floating, float)) def test_shap_values_shape(self): self.assertTrue(self.explainer.shap_values.shape == (len(self.explainer), len(self.explainer.columns))) def test_shap_values(self): self.assertIsInstance(self.explainer.shap_values, np.ndarray) self.assertIsInstance(self.explainer.shap_values_cats, np.ndarray) def test_mean_abs_shap(self): self.assertIsInstance(self.explainer.mean_abs_shap, pd.DataFrame) self.assertIsInstance(self.explainer.mean_abs_shap_cats, pd.DataFrame) def test_calculate_properties(self): self.explainer.calculate_properties(include_interactions=False) def test_pdp_result(self): self.assertIsInstance(self.explainer.get_pdp_result("Age"), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Sex"), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Age", index=0), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Sex", index=0), pdpbox.pdp.PDPIsolate) def test_get_dfs(self): cols_df, shap_df, contribs_df = self.explainer.get_dfs() self.assertIsInstance(cols_df, pd.DataFrame) self.assertIsInstance(shap_df, pd.DataFrame) self.assertIsInstance(contribs_df, pd.DataFrame) class LogisticRegressionTests(unittest.TestCase): def setUp(self): X_train, y_train, X_test, y_test = titanic_survive() train_names, test_names = titanic_names() model = LogisticRegression() model.fit(X_train, y_train) self.explainer = ClassifierExplainer( model, X_test, y_test, roc_auc_score, shap='linear', cats=['Sex', 'Cabin', 'Embarked'], labels=['Not survived', 'Survived'], idxs=test_names) def test_preds(self): self.assertIsInstance(self.explainer.preds, np.ndarray) def test_pred_percentiles(self): self.assertIsInstance(self.explainer.pred_percentiles, np.ndarray) def test_columns_ranked_by_shap(self): self.assertIsInstance(self.explainer.columns_ranked_by_shap(), list) self.assertIsInstance(self.explainer.columns_ranked_by_shap(cats=True), list) def test_permutation_importances(self): self.assertIsInstance(self.explainer.permutation_importances, pd.DataFrame) self.assertIsInstance(self.explainer.permutation_importances_cats, pd.DataFrame) def test_metrics(self): self.assertIsInstance(self.explainer.metrics(), dict) self.assertIsInstance(self.explainer.metrics_markdown(), str) def test_mean_abs_shap_df(self): self.assertIsInstance(self.explainer.mean_abs_shap_df(), pd.DataFrame) def test_contrib_df(self): self.assertIsInstance(self.explainer.contrib_df(0), pd.DataFrame) self.assertIsInstance(self.explainer.contrib_df(0, cats=False), pd.DataFrame) self.assertIsInstance(self.explainer.contrib_df(0, topx=3), pd.DataFrame) def test_shap_base_value(self): self.assertIsInstance(self.explainer.shap_base_value, (np.floating, float)) def test_shap_values_shape(self): self.assertTrue(self.explainer.shap_values.shape == (len(self.explainer), len(self.explainer.columns))) def test_shap_values(self): self.assertIsInstance(self.explainer.shap_values, np.ndarray) self.assertIsInstance(self.explainer.shap_values_cats, np.ndarray) def test_mean_abs_shap(self): self.assertIsInstance(self.explainer.mean_abs_shap, pd.DataFrame) self.assertIsInstance(self.explainer.mean_abs_shap_cats, pd.DataFrame) def test_calculate_properties(self): self.explainer.calculate_properties(include_interactions=False) def test_pdp_result(self): self.assertIsInstance(self.explainer.get_pdp_result("Age"), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Sex"), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Age", index=0), pdpbox.pdp.PDPIsolate) self.assertIsInstance(self.explainer.get_pdp_result("Sex", index=0), pdpbox.pdp.PDPIsolate) def test_pos_label(self): self.explainer.pos_label = 1 self.explainer.pos_label = "Not survived" self.assertIsInstance(self.explainer.pos_label, int) self.assertIsInstance(self.explainer.pos_label_str, str) self.assertEquals(self.explainer.pos_label, 0) self.assertEquals(self.explainer.pos_label_str, "Not survived") def test_get_prop_for_label(self): self.explainer.pos_label = 1 tmp = self.explainer.pred_percentiles self.explainer.pos_label = 0 self.assertTrue(np.alltrue(self.explainer.get_prop_for_label("pred_percentiles", 1)==tmp)) def test_pred_probas(self): self.assertIsInstance(self.explainer.pred_probas, np.ndarray) def test_metrics(self): self.assertIsInstance(self.explainer.metrics(), dict) self.assertIsInstance(self.explainer.metrics(cutoff=0.9), dict) def test_precision_df(self): self.assertIsInstance(self.explainer.precision_df(), pd.DataFrame) self.assertIsInstance(self.explainer.precision_df(multiclass=True), pd.DataFrame) self.assertIsInstance(self.explainer.precision_df(quantiles=4), pd.DataFrame) def test_lift_curve_df(self): self.assertIsInstance(self.explainer.lift_curve_df(), pd.DataFrame) def test_prediction_result_markdown(self): self.assertIsInstance(self.explainer.prediction_result_markdown(0), str)

42.47

111

0.721215

1,030

8,494

5.714563

0.121359

0.170065

0.228338

0.313965

0.786103

0.745158

0.664458

0.653925

0.587496

0.567448

0

0.003708

0.174476

8,494

199

112

42.683417

0.83571

0

0.531469

0

0.016484

0

0.461538

1

0.272727

false

0

0.104895

0

0.391608

0

null

0

1

0

1

0

null

0

1

0

1

0

5

544379ac2806b9b761334855fd288058a5ea9f0a

117

py

Python

causalml/inference/iv/__init__.py

rainfireliang/causalml

d58024d8de4ab6136c5519949b58a22dd885df29

[ "Apache-2.0" ]

2,919

2019-08-12T23:02:10.000Z

2022-03-31T21:59:34.000Z

causalml/inference/iv/__init__.py

rainfireliang/causalml

d58024d8de4ab6136c5519949b58a22dd885df29

[ "Apache-2.0" ]

317

2019-08-13T14:16:22.000Z

2022-03-26T08:44:06.000Z

causalml/inference/iv/__init__.py

rainfireliang/causalml

d58024d8de4ab6136c5519949b58a22dd885df29

[ "Apache-2.0" ]

466

2019-08-18T01:45:14.000Z

2022-03-31T08:11:53.000Z

from .iv_regression import IVRegressor from .drivlearner import BaseDRIVLearner, BaseDRIVRegressor, XGBDRIVRegressor

39

77

0.880342

11

117

9.272727

0.818182

0

0.08547

117

2

78

58.5

0.953271

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

547692de17496ebef5736eac9981417b26955f33

3,860

py

Python

test/unit/test_iam_token_manager.py

ricellis/python-sdk

f7be21f4e7cc55f079babb556d5e5a47523eee7b

[ "Apache-2.0" ]

1

2018-10-04T19:13:44.000Z

test/unit/test_iam_token_manager.py

SamArtGS/python-sdk

7be6a4fe75d4a9fd365ef626d6289c0dc8457f3a

[ "Apache-2.0" ]

5

2020-03-24T16:26:02.000Z

2021-04-30T20:44:47.000Z

test/unit/test_iam_token_manager.py

SamArtGS/python-sdk

7be6a4fe75d4a9fd365ef626d6289c0dc8457f3a

[ "Apache-2.0" ]

3

2019-08-20T11:37:29.000Z

2020-07-18T11:22:14.000Z

import responses from watson_developer_cloud import IAMTokenManager import time @responses.activate def test_request_token(): iam_url = "https://iam.bluemix.net/identity/token" response = """{ "access_token": "oAeisG8yqPY7sFR_x66Z15", "token_type": "Bearer", "expires_in": 3600, "expiration": 1524167011, "refresh_token": "jy4gl91BQ" }""" responses.add(responses.POST, url=iam_url, body=response, status=200) token_manager = IAMTokenManager("iam_apikey", "iam_access_token", iam_url) token_manager._request_token() assert responses.calls[0].request.url == iam_url assert responses.calls[0].response.text == response assert len(responses.calls) == 1 @responses.activate def test_refresh_token(): iam_url = "https://iam.bluemix.net/identity/token" response = """{ "access_token": "oAeisG8yqPY7sFR_x66Z15", "token_type": "Bearer", "expires_in": 3600, "expiration": 1524167011, "refresh_token": "jy4gl91BQ" }""" responses.add(responses.POST, url=iam_url, body=response, status=200) token_manager = IAMTokenManager("iam_apikey", "iam_access_token", iam_url) token_manager._refresh_token() assert responses.calls[0].request.url == iam_url assert responses.calls[0].response.text == response assert len(responses.calls) == 1 @responses.activate def test_is_token_expired(): token_manager = IAMTokenManager("iam_apikey", "iam_access_token", "iam_url") token_manager.token_info = { "access_token": "oAeisG8yqPY7sFR_x66Z15", "token_type": "Bearer", "expires_in": 3600, "expiration": int(time.time()) + 6000, "refresh_token": "jy4gl91BQ" } assert token_manager._is_token_expired() is False token_manager.token_info['expiration'] = int(time.time()) - 3600 assert token_manager._is_token_expired() @responses.activate def test_is_refresh_token_expired(): token_manager = IAMTokenManager("iam_apikey", "iam_access_token", "iam_url") token_manager.token_info = { "access_token": "oAeisG8yqPY7sFR_x66Z15", "token_type": "Bearer", "expires_in": 3600, "expiration": int(time.time()), "refresh_token": "jy4gl91BQ" } assert token_manager._is_refresh_token_expired() is False token_manager.token_info['expiration'] = int(time.time()) - (8 * 24 * 3600) assert token_manager._is_token_expired() @responses.activate def test_get_token(): iam_url = "https://iam.bluemix.net/identity/token" token_manager = IAMTokenManager("iam_apikey", iam_url=iam_url) token_manager.user_access_token = 'user_access_token' # Case 1: token = token_manager.get_token() assert token == token_manager.user_access_token # Case 2: token_manager.user_access_token = '' response = """{ "access_token": "hellohello", "token_type": "Bearer", "expires_in": 3600, "expiration": 1524167011, "refresh_token": "jy4gl91BQ" }""" responses.add(responses.POST, url=iam_url, body=response, status=200) token = token_manager.get_token() assert token == "hellohello" # Case 3: token_manager.token_info['expiration'] = int(time.time()) - (20 * 24 * 3600) token = token_manager.get_token() assert "grant_type=urn" in responses.calls[1].request.body token_manager.token_info['expiration'] = int(time.time()) - 4000 token = token_manager.get_token() assert "grant_type=refresh_token" in responses.calls[2].request.body # Case 4 token_manager.token_info = { "access_token": "dummy", "token_type": "Bearer", "expires_in": 3600, "expiration": int(time.time()) + 3600, "refresh_token": "jy4gl91BQ" } token = token_manager.get_token() assert token == 'dummy'

34.464286

80

0.673575

457

3,860

5.391685

0.142232

0.126623

0.03125

0.059659

0.860795

0.824675

0.79586

0.720779

0.654221

0.637175

0

0.047558

0.193782

3,860

111

81

34.774775

0.744216

0.007772

0

0.659574

0

0.304052

0.03085

0

0.159574

1

0.053191

false

0

0.031915

0

0.085106

0

null

0

1

0

1

0

null

0

5

549a0e2c4829f5959c617042b19b7efa0a409c1c

112

py

Python

web/credentials-sample.py

rvk007/Tanoshi

99778fe29dffb7f023f8fcddeea0a008a0c16f18

[ "MIT" ]

3

2021-01-15T14:51:51.000Z

2021-07-10T17:19:48.000Z

web/credentials-sample.py

rvk007/Tanoshi

99778fe29dffb7f023f8fcddeea0a008a0c16f18

[ "MIT" ]

9

2020-12-27T14:01:09.000Z

2021-06-16T17:21:16.000Z

web/credentials-sample.py

rvk007/Tanoshi

99778fe29dffb7f023f8fcddeea0a008a0c16f18

[ "MIT" ]

1

2021-09-06T21:12:57.000Z

AWS_BUCKET_NAME='aws-buckey-name' AWS_ACCESS_KEY='aws-access-key' AWS_SECRET_ACCESS_KEY='aws-secret-access-key'

28

45

0.830357

20

112

4.3

0.35

0.418605

0.348837

0.523256

0

0.026786

112

3

46

37.333333

0.788991

0

0.446429

0.1875

0

1

0

false

0

1

0

null

1

0

1

0

null

0

5

54a0880091198ffde1675b774980985f768cfad5

210

py

Python

tests/parsers/test_cobertura.py

relekang/frigg-coverage

ae7d29a8d94f3fe5405d5882cd4c4726ed638e97

[ "MIT" ]

3

2015-01-30T10:53:47.000Z

2015-04-13T16:55:30.000Z

tests/parsers/test_cobertura.py

relekang/frigg-coverage

ae7d29a8d94f3fe5405d5882cd4c4726ed638e97

[ "MIT" ]

4

2015-02-21T20:12:37.000Z

2015-11-24T18:06:49.000Z

tests/parsers/test_cobertura.py

relekang/frigg-coverage

ae7d29a8d94f3fe5405d5882cd4c4726ed638e97

[ "MIT" ]

2

2015-11-21T22:53:23.000Z

2018-03-05T17:38:43.000Z

# -*- coding: utf-8 -*- from frigg_coverage import parse_coverage def test_parse_coverage_report(): with open('fixtures/cobertura.xml') as f: assert parse_coverage(f.read(), 'cobertura') == 88.24

26.25

61

0.695238

29

210

4.827586

0.758621

0.278571

0

0.028409

0.161905

210

7

62

30

0.767045

0.1

0

0.165775

0.117647

0

0.25

1

0.25

true

0

0.25

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

49b2c488431cde5c0c17d791a7cff1c803c6d2c3

38,723

py

Python

ivy/stateful/layers.py

VedPatwardhan/ivy

7b2105fa8cf38879444a1029bfaa7f0b2f27717a

[ "Apache-2.0" ]

1

2022-02-13T19:35:02.000Z

ivy/stateful/layers.py

Arijit1000/ivy

de193946a580ca0f54d78fe7fc4031a6ff66d2bb

[ "Apache-2.0" ]

null

ivy/stateful/layers.py

Arijit1000/ivy

de193946a580ca0f54d78fe7fc4031a6ff66d2bb

[ "Apache-2.0" ]

null

"""Collection of Ivy neural network layers as stateful classes.""" # local import ivy from ivy.stateful.module import Module from ivy.stateful.initializers import Zeros, GlorotUniform # Linear # # -------# class Linear(Module): def __init__( self, input_channels, output_channels, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), with_bias=True, device=None, v=None, dtype=None, ): """ Linear layer, also referred to as dense or fully connected. The layer receives tensors with input_channels last dimension and returns a new tensor with output_channels last dimension, following matrix multiplication with the weight matrix and addition with the bias vector. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. with_bias Whether or not to include a bias term, default is True. device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._w_shape = (output_channels, input_channels) self._b_shape = (output_channels,) self._w_init = weight_initializer self._b_init = bias_initializer self._with_bias = with_bias Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """ Create internal variables for the layer Parameters ---------- device """ v = { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ) } if self._with_bias: v = dict( **v, b=self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ) ) return v def _forward(self, inputs): """ Perform forward pass of the Linear layer. Parameters ---------- inputs Inputs to process *[batch_shape, in]*. Returns ------- ret The outputs following the linear operation and bias addition *[batch_shape, out]* """ return ivy.linear(inputs, self.v.w, self.v.b if self._with_bias else None) # Dropout # # --------# class Dropout(Module): def __init__(self, prob, scale=True, dtype=None): """ Dropout layer. The layer randomly zeroes some of the elements of the input tensor with probability p using samples from a Bernoull distribution. Parameters ---------- prob The probability of zeroing out each array element. scale Whether to scale the output by 1/(1-prob), default is True. """ self._prob = prob self._scale = scale Module.__init__(self, None, None, dtype=dtype) def _create_variables(self, device, dtype): """ Create internal variables for the layer Parameters ---------- device """ return {} def _forward(self, inputs): """ Perform forward pass of the Linear layer. Parameters ---------- inputs Inputs to process *[batch_shape, in]*. Returns ------- ret The outputs following the linear operation and bias addition *[batch_shape, out]* """ return ivy.dropout(inputs, self._prob, self._scale) # Attention # # ----------# class MultiHeadAttention(Module): def __init__( self, query_dim, num_heads=8, head_dim=64, dropout_rate=0.0, context_dim=None, scale=None, with_to_q_fn=True, with_to_kv_fn=True, with_to_out_fn=True, device=None, v=None, build_mode="on_init", dtype=None, ): """ Multi Head Attention layer. Parameters ---------- query_dim The dimension of the attention queries. num_heads Number of attention heads. Default is 8. head_dim The dimension of each of the heads. Default is 64. dropout_rate The rate of dropout. Default is 0. context_dim The dimension of the context array. Default is None, in which case the query dim is used. scale The value by which to scale the query-key similarity measure. Default is head_dim^-0.5 with_to_q_fn Whether to include fully connected mapping from input x to queries. Default is True. with_to_kv_fn Whether to include fully connected mapping from input context to keys and values. Default is True. with_to_out_fn Whether to include fully connected mapping from output scaled dot-product attention to final output. Default is True. device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for the attention layer, as a container, constructed internally by default. build_mode How the Module is built, either on initialization (now), explicitly by the user by calling build(), or the first time the __call__ method is run. Default is on initialization. """ v_exists = ivy.exists(v) v = ivy.default(v, ivy.Container({"to_q": None, "to_kv": None, "to_out": None})) self._query_dim = query_dim self._inner_dim = head_dim * num_heads self._dropout_rate = dropout_rate self._context_dim = ivy.default(context_dim, query_dim) self._scale = ivy.default(scale, head_dim**-0.5) self._num_heads = num_heads self._with_to_q_fn = with_to_q_fn self._with_to_kv_fn = with_to_kv_fn self._with_to_out_fn = with_to_out_fn ivy.Module.__init__( self, device, v if v_exists else None, build_mode, with_partial_v=True, dtype=dtype, ) # noinspection PyAttributeOutsideInit def _build(self, *agrs, **kwargs): self._to_q = ( ivy.Linear( self._query_dim, self._inner_dim, device=self._dev, dtype=self._dtype ) if self._with_to_q_fn else None ) self._to_k = ( ivy.Linear( self._context_dim, self._inner_dim, device=self._dev, dtype=self._dtype ) if self._with_to_kv_fn else None ) self._to_v = ( ivy.Linear( self._context_dim, self._inner_dim, device=self._dev, dtype=self._dtype ) if self._with_to_kv_fn else None ) self._to_kv = lambda context, v=None: ( self._to_k(context, v=v.k if v else None), self._to_v(context, v=v.v if v else None), ) self._to_out = ( ivy.Sequential( ivy.Linear( self._inner_dim, self._query_dim, device=self._dev, dtype=self._dtype, ), ivy.Dropout(self._dropout_rate), device=self._dev, ) if self._with_to_out_fn else None ) def _create_variables(self, device, dtype=None): """ Parameters ---------- device """ return ivy.Container(to_kv={"k": self._to_k.v, "v": self._to_v.v}) def _forward(self, inputs, context=None, mask=None): """ Perform forward pass of the MultiHeadAttention layer. Parameters ---------- inputs The array to determine the queries from *[batch_shape,num_queries,x_feats]*. context The array to determine the keys and values from. Default is None. *[batch_shape,num_values,cont_feats]*. mask (Default value = None) Returns ------- ret The output following application of scaled dot-product attention. *[batch_shape,num_queries,out_feats]* The mask to apply to the query-key values. Default is None. *[batch_shape,num_queries,num_values]* """ return ivy.multi_head_attention( inputs, self._scale, self._num_heads, context, mask, self._to_q, self._to_kv, self._to_out, self.v.to_q, self.v.to_kv, self.v.to_out, ) # Convolutions # # -------------# class Conv1D(Module): def __init__( self, input_channels, output_channels, filter_size, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), data_format="NWC", dilations=1, device=None, v=None, dtype=None, ): """ 1D convolutional layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_size Size of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. data_format NWC" or "NCW". Defaults to "NWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_size = filter_size self._strides = strides self._padding = padding self._w_shape = ( (filter_size, input_channels, output_channels) if data_format == "NWC" else (input_channels, output_channels, self._filter_size) ) self._b_shape = (1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """ Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ), } def _forward(self, inputs): """ Perform forward pass of the Conv1D layer. Parameters ---------- inputs Inputs to process *[batch_size,w,d_in]* Returns ------- ret The outputs following the conv1d layer *[batch_size,new_w,d_out]* """ return ( ivy.conv1d( inputs, self.v.w, self._strides, self._padding, self._data_format, self._dilations, ) + self.v.b ) class Conv1DTranspose(Module): def __init__( self, input_channels, output_channels, filter_size, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), output_shape=None, data_format="NWC", dilations=1, device=None, v=None, dtype=None, ): """ 1D transpose convolutional layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_size Size of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. output_shape Shape of the output (Default value = None) data_format NWC" or "NCW". Defaults to "NWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_size = filter_size self._strides = strides self._padding = padding self._w_shape = ( (filter_size, input_channels, output_channels) if data_format == "NWC" else (input_channels, output_channels, filter_size) ) self._b_shape = (1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._output_shape = output_shape self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels ), } def _forward(self, inputs): """Perform forward pass of the Conv1DTranspose layer. Parameters ---------- inputs Inputs to process *[batch_size,w,d_in]* Returns ------- ret The outputs following the conv1d layer *[batch_size,new_w,d_out]* """ return ( ivy.conv1d_transpose( inputs, self.v.w, self._strides, self._padding, self._output_shape, self._data_format, self._dilations, ) + self.v.b ) class Conv2D(Module): def __init__( self, input_channels, output_channels, filter_shape, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), data_format="NHWC", dilations=1, device=None, v=None, dtype=None, ): """2D convolutional layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_shape Shape of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. data_format NHWC" or "NCHW". Defaults to "NHWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_shape = filter_shape self._strides = strides self._padding = padding self._w_shape = ( filter_shape + [input_channels, output_channels] if data_format == "NHWC" else [input_channels, output_channels] + filter_shape ) self._b_shape = (1, 1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ), } def _forward(self, inputs): """Perform forward pass of the Conv2D layer. Parameters ---------- inputs Inputs to process *[batch_size,h,w,d_in]*. Returns ------- ret The outputs following the conv1d layer *[batch_size,new_h,new_w,d_out]* """ return ( ivy.conv2d( inputs, self.v.w, self._strides, self._padding, self._data_format, self._dilations, ) + self.v.b ) class Conv2DTranspose(Module): def __init__( self, input_channels, output_channels, filter_shape, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), output_shape=None, data_format="NHWC", dilations=1, device=None, v=None, dtype=None, ): """2D convolutional transpose layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_shape Shape of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. output_shape Shape of the output (Default value = None) data_format NHWC" or "NCHW". Defaults to "NHWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_shape = filter_shape self._strides = strides self._padding = padding self._w_shape = ( filter_shape + [input_channels, output_channels] if data_format == "NHWC" else [input_channels, output_channels] + filter_shape ) self._b_shape = (1, 1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._output_shape = output_shape self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ), } def _forward(self, inputs): """Perform forward pass of the Conv2DTranspose layer. Parameters ---------- inputs Inputs to process *[batch_size,h,w,d_in]*. Returns ------- ret The outputs following the conv1d layer *[batch_size,new_h,new_w,d_out]* """ return ( ivy.conv2d_transpose( inputs, self.v.w, self._strides, self._padding, self._output_shape, self._data_format, self._dilations, ) + self.v.b ) class DepthwiseConv2D(Module): def __init__( self, num_channels, filter_shape, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), data_format="NHWC", dilations=1, device=None, v=None, dtype=None, ): """ Depthwise 2D convolutional layer. Parameters ---------- num_channels Number of input channels for the layer. filter_shape Shape of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. data_format NHWC" or "NCHW". Defaults to "NHWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._num_channels = num_channels self._filter_shape = filter_shape self._strides = strides self._padding = padding self._w_shape = ( filter_shape + [num_channels] if data_format == "NHWC" else [num_channels] + filter_shape ) self._b_shape = (1, 1, num_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._num_channels, self._num_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._num_channels, dtype=dtype ), } def _forward(self, inputs): """Perform forward pass of the DepthwiseConv2D layer. Parameters ---------- inputs Inputs to process *[batch_size,h,w,d_in]*. Returns ------- ret The outputs following the conv1d layer *[batch_size,new_h,new_w,d_out]* """ return ( ivy.depthwise_conv2d( inputs, self.v.w, self._strides, self._padding, self._data_format, self._dilations, ) + self.v.b ) class Conv3D(Module): def __init__( self, input_channels, output_channels, filter_shape, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), data_format="NDHWC", dilations=1, device=None, v=None, dtype=None, ): """3D convolutional layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_shape Shape of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. data_format NDHWC" or "NCDHW". Defaults to "NDHWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_shape = filter_shape self._strides = strides self._padding = padding self._w_shape = ( filter_shape + [input_channels, output_channels] if data_format == "NDHWC" else [input_channels, output_channels] + filter_shape ) self._b_shape = (1, 1, 1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._data_format = data_format self._dilations = dilations Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ), } def _forward(self, inputs): """Perform forward pass of the Conv3D layer. Parameters ---------- inputs Inputs to process *[batch_size,d,h,w,d_in]*. Returns ------- ret The outputs following the conv1d layer *[batch_size,new_d,new_h,new_w,d_out]* """ return ( ivy.conv3d( inputs, self.v.w, self._strides, self._padding, self._data_format, self._dilations, ) + self.v.b ) class Conv3DTranspose(Module): def __init__( self, input_channels, output_channels, filter_shape, strides, padding, weight_initializer=GlorotUniform(), bias_initializer=Zeros(), output_shape=None, data_format="NDHWC", dilations=1, device=None, v=None, dtype=None, ): """3D convolutional transpose layer. Parameters ---------- input_channels Number of input channels for the layer. output_channels Number of output channels for the layer. filter_shape Shape of the convolutional filter. strides The stride of the sliding window for each dimension of input. padding SAME" or "VALID" indicating the algorithm, or list indicating the per-dimension paddings. weight_initializer Initializer for the weights. Default is GlorotUniform. bias_initializer Initializer for the bias. Default is Zeros. output_shape Shape of the output (Default value = None) data_format NDHWC" or "NCDHW". Defaults to "NDHWC". dilations The dilation factor for each dimension of input. (Default value = 1) device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the linear layer, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._filter_shape = filter_shape self._strides = strides self._padding = padding self._w_shape = ( filter_shape + [input_channels, output_channels] if data_format == "NDHWC" else [input_channels, output_channels] + filter_shape ) self._b_shape = (1, 1, 1, 1, output_channels) self._w_init = weight_initializer self._b_init = bias_initializer self._output_shape = output_shape self._data_format = data_format self._dilations = dilations self.dtype = dtype Module.__init__(self, device, v, dtype=dtype) def _create_variables(self, device, dtype=None): """Create internal variables for the layer Parameters ---------- device """ return { "w": self._w_init.create_variables( self._w_shape, device, self._output_channels, self._input_channels, dtype=dtype, ), "b": self._b_init.create_variables( self._b_shape, device, self._output_channels, dtype=dtype ), } def _forward(self, inputs): """Perform forward pass of the Conv3DTranspose layer. Parameters ---------- inputs Inputs to process *[batch_size,d,h,w,d_in]*. Returns ------- ret The outputs following the conv1d layer *[batch_size,new_d,new_h,new_w,d_out]* """ return ( ivy.conv3d_transpose( inputs, self.v.w, self._strides, self._padding, self._output_shape, self._data_format, self._dilations, ) + self.v.b ) # LSTM # # -----# class LSTM(Module): def __init__( self, input_channels, output_channels, weight_initializer=GlorotUniform(), num_layers=1, return_sequence=True, return_state=True, device=None, v=None, dtype=None, ): """LSTM layer, which is a set of stacked lstm cells. Parameters ---------- input_channels Number of input channels for the layer output_channels Number of output channels for the layer weight_initializer Initializer for the weights. Default is GlorotUniform. num_layers Number of lstm cells in the lstm layer, default is 1. return_sequence Whether or not to return the entire output sequence, or just the latest timestep. Default is True. return_state Whether or not to return the latest hidden and cell states. Default is True. device device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu' etc. Default is cpu. v the variables for each of the lstm cells, as a container, constructed internally by default. """ self._input_channels = input_channels self._output_channels = output_channels self._w_init = weight_initializer self._num_layers = num_layers self._return_sequence = return_sequence self._return_state = return_state Module.__init__(self, device, v, dtype=dtype) # Public # def get_initial_state(self, batch_shape, dtype=None): """Get the initial state of the hidden and cell states, if not provided explicitly Parameters ---------- batch_shape """ batch_shape = list(batch_shape) return ( [ ivy.zeros((batch_shape + [self._output_channels]), dtype=dtype) for i in range(self._num_layers) ], [ ivy.zeros((batch_shape + [self._output_channels]), dtype=dtype) for i in range(self._num_layers) ], ) # Overridden def _create_variables(self, device, dtype=None): """Create internal variables for the layer Parameters ---------- device """ input_weights = dict( zip( ["layer_" + str(i) for i in range(self._num_layers)], [ { "w": self._w_init.create_variables( ( self._input_channels if i == 0 else self._output_channels, 4 * self._output_channels, ), device, self._output_channels, self._input_channels, dtype=dtype, ) } for i in range(self._num_layers) ], ) ) recurrent_weights = dict( zip( ["layer_" + str(i) for i in range(self._num_layers)], [ { "w": self._w_init.create_variables( (self._output_channels, 4 * self._output_channels), device, self._output_channels, self._input_channels, dtype=dtype, ) } for i in range(self._num_layers) ], ) ) return {"input": input_weights, "recurrent": recurrent_weights} def _forward(self, inputs, initial_state=None): """Perform forward pass of the LSTM layer. Parameters ---------- inputs Inputs to process *[batch_shape, t, in]*. initial_state 2-tuple of lists of the hidden states h and c for each layer, each of dimension *[batch_shape,out]*. Created internally if None. (Default value = None) Returns ------- ret The outputs of the final lstm layer *[batch_shape, t, out]* and the hidden state tuple of lists, each of dimension *[batch_shape, out]* """ if initial_state is None: initial_state = self.get_initial_state( inputs.shape[:-2], dtype=inputs.dtype ) h_n_list = list() c_n_list = list() h_t = inputs for h_0, c_0, (_, lstm_input_var), (_, lstm_recurrent_var) in zip( initial_state[0], initial_state[1], self.v.input.items(), self.v.recurrent.items(), ): h_t, c_n = ivy.lstm_update( h_t, h_0, c_0, lstm_input_var.w, lstm_recurrent_var.w ) h_n_list.append(h_t[..., -1, :]) c_n_list.append(c_n) if not self._return_sequence: h_t = h_t[..., -1, :] if not self._return_state: return h_t return h_t, (h_n_list, c_n_list)

29.948183

88

0.536141

4,083

38,723

4.835905

0.062699

0.05885

0.027349

0.799696

0.781666

0.763839

0.754419

0.743631

0.736592

0

0.004999

0.385275

38,723

1,292

89

29.971362

0.824483

0.353175

0

0.691358

0

0.005854

0

1

0.054012

false

0

0.00463

0

0.112654

0

null

0

1

0

null

0

5

49c96122a94a107ed428211dae2c996457d31d52

21

py

Python

qrtt/charts/__init__.py

leopoldsw/qrtt

271f23888847f9a0a9a7da360be22c5000b058ab

[ "MIT" ]

null

qrtt/charts/__init__.py

leopoldsw/qrtt

271f23888847f9a0a9a7da360be22c5000b058ab

[ "MIT" ]

null

qrtt/charts/__init__.py

leopoldsw/qrtt

271f23888847f9a0a9a7da360be22c5000b058ab

[ "MIT" ]

null

from .candle import *

21

0.761905

3

21

5.333333

1

0

0.142857

21

1

21

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

b723f9f2540bf92293cce40bd979f3a0b9529a6e

49

py

Python

MISSIONS/sr_tasks/__init__.py

Harold0/hmp

4745e1d3e56c7f08947c839526e6827daa3e6048

[ "MIT" ]

2

2022-02-25T12:04:55.000Z

2022-03-15T02:37:59.000Z

MISSIONS/sr_tasks/__init__.py

binary-husky/hmp2g

1a4f4093cd296f07348f4db4c7503aca6e1fb05c

[ "MIT" ]

null

MISSIONS/sr_tasks/__init__.py

binary-husky/hmp2g

1a4f4093cd296f07348f4db4c7503aca6e1fb05c

[ "MIT" ]

null

import sys sys.path.append('./MISSIONS/sr_tasks')

24.5

38

0.77551

8

49

4.625

0.875

0

0.040816

49

2

38

24.5

0.787234

0

0.38

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

3fcab22492fb5cece0bc64d31df41ee3df0a04f8

227

py

Python

rubedo/utils/dict.py

mkomet/rubedo

a85612a7632117ca27d3f29f93076b7fdab57277

[ "MIT" ]

null

rubedo/utils/dict.py

mkomet/rubedo

a85612a7632117ca27d3f29f93076b7fdab57277

[ "MIT" ]

2

2022-02-05T12:03:22.000Z

2022-02-05T12:10:23.000Z

rubedo/utils/dict.py

mkomet/rubedo

a85612a7632117ca27d3f29f93076b7fdab57277

[ "MIT" ]

null

from typing import Any class RubedoDict(dict): def __getattr__(self, item: str) -> Any: return self.__getitem__(item) def __setattr__(self, key: str, value: Any) -> None: self.__setitem__(key, value)

22.7

56

0.660793

29

227

4.62069

0.655172

0

0.22467

227

9

57

25.222222

0.761364

0

1

0.333333

false

0

0.166667

0.833333

0

1

0

null

0

1

0

null

0

1

0

1

0

5

b75981e69d42062a3c68809bad7d0e6c86c0652c

882

py

Python

TM1py/Objects/__init__.py

lotsaram/TM1py

71a2fd1e30211e497bb2644f0d11376abd2c29a7

[ "MIT" ]

null

TM1py/Objects/__init__.py

lotsaram/TM1py

71a2fd1e30211e497bb2644f0d11376abd2c29a7

[ "MIT" ]

null

TM1py/Objects/__init__.py

lotsaram/TM1py

71a2fd1e30211e497bb2644f0d11376abd2c29a7

[ "MIT" ]

1

2022-01-17T10:02:44.000Z

from TM1py.Objects.Annotation import Annotation from TM1py.Objects.Axis import ViewAxisSelection, ViewTitleSelection from TM1py.Objects.Chore import Chore from TM1py.Objects.ChoreFrequency import ChoreFrequency from TM1py.Objects.ChoreStartTime import ChoreStartTime from TM1py.Objects.ChoreTask import ChoreTask from TM1py.Objects.Cube import Cube from TM1py.Objects.Dimension import Dimension from TM1py.Objects.Element import Element from TM1py.Objects.ElementAttribute import ElementAttribute from TM1py.Objects.Hierarchy import Hierarchy from TM1py.Objects.MDXView import MDXView from TM1py.Objects.NativeView import NativeView from TM1py.Objects.Process import Process from TM1py.Objects.Rules import Rules from TM1py.Objects.Server import Server from TM1py.Objects.Subset import Subset, AnonymousSubset from TM1py.Objects.User import User from TM1py.Objects.View import View

44.1

68

0.866213

116

882

6.586207

0.224138

0.223822

0.397906

0

0.023632

0.088435

882

19

69

46.421053

0.926617

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

5

b76d57db0085a74fb9695bb52f76bb06e6464893

168

py

Python

docs/lfreleng/conf.py

fabiojna02/functest

329aef28d0d41e086deaf88776cc5f4ef3f13b0f

[ "Apache-2.0" ]

null

docs/lfreleng/conf.py

fabiojna02/functest

329aef28d0d41e086deaf88776cc5f4ef3f13b0f

[ "Apache-2.0" ]

null

docs/lfreleng/conf.py

fabiojna02/functest

329aef28d0d41e086deaf88776cc5f4ef3f13b0f

[ "Apache-2.0" ]

null

#!/bin/env python # pylint: disable=unused-wildcard-import,wildcard-import,redefined-builtin # pylint: disable=missing-docstring from docs_conf.conf import * # noqa

24

74

0.779762

22

168

5.909091

0.727273

0.2

0

0.10119

168

6

75

28

0.860927

0.761905

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b7755885d7d5b598f47c57f795355bff0b92faa3

89

py

Python

web/apps/lesson/admin.py

vitaliyharchenko/django_template

41fa00cb0b8be6c5cf67b7a334d4340163255160

[ "MIT" ]

3

2019-09-07T15:01:53.000Z

2020-01-15T09:17:47.000Z

web/apps/lesson/admin.py

vitaliyharchenko/django_template

41fa00cb0b8be6c5cf67b7a334d4340163255160

[ "MIT" ]

22

2020-06-05T22:53:41.000Z

2022-03-11T23:58:42.000Z

web/apps/lesson/admin.py

vitaliyharchenko/django_template

41fa00cb0b8be6c5cf67b7a334d4340163255160

[ "MIT" ]

2

2020-01-15T09:14:33.000Z

2020-10-25T19:02:53.000Z

from django.contrib import admin from .models import Lesson admin.site.register(Lesson)

17.8

32

0.820225

13

89

5.615385

0.692308

0

0.11236

89

4

33

22.25

0.924051

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b778dbb67733a826b270b9c983c00370a98dc108

77

py

Python

poetry/mixology/__init__.py

batisteo/poetry

0667c67a9ebcc9250ad8d70f74f0905cc9f20ab2

[ "MIT" ]

null

poetry/mixology/__init__.py

batisteo/poetry

0667c67a9ebcc9250ad8d70f74f0905cc9f20ab2

[ "MIT" ]

null

poetry/mixology/__init__.py

batisteo/poetry

0667c67a9ebcc9250ad8d70f74f0905cc9f20ab2

[ "MIT" ]

null

from .dependency_graph import DependencyGraph from .resolver import Resolver

25.666667

45

0.87013

9

77

7.333333

0.666667

0

0.103896

77

2

46

38.5

0.956522

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b79b42000af25b9be04a3bf0c76b57fc5595d9ff

116

py

Python

tests/unittests/Version.py

nemaniarjun/storyscript

1154e9cf2c365ce18ded20c70eb6f976edd8df76

[ "MIT" ]

null

tests/unittests/Version.py

nemaniarjun/storyscript

1154e9cf2c365ce18ded20c70eb6f976edd8df76

[ "MIT" ]

null

tests/unittests/Version.py

nemaniarjun/storyscript

1154e9cf2c365ce18ded20c70eb6f976edd8df76

[ "MIT" ]

null

# -*- coding: utf-8 -*- from storyscript.Version import version def test_version(): assert version == '0.9.0'

16.571429

39

0.655172

16

116

4.6875

0.75

0

0.042105

0.181034

116

6

40

19.333333

0.747368

0.181034

0

0.053763

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

5

b7bb95b72123d2996b9543b6ddeb5b735e9147f0

54

py

Python

WMIAdventure/backend/WMIAdventure_backend/IngameUsers/businesslogic/exceptions.py

emkarcinos/WMIAdventure

7ca057bb4e4d462b8626d53b66bed86e0125059a

[ "Apache-2.0" ]

2

2021-05-26T15:12:33.000Z

2021-12-09T17:17:19.000Z

WMIAdventure/backend/WMIAdventure_backend/IngameUsers/businesslogic/exceptions.py

emkarcinos/WMIAdventure

7ca057bb4e4d462b8626d53b66bed86e0125059a

[ "Apache-2.0" ]

558

2021-05-27T05:41:23.000Z

2022-02-27T21:50:54.000Z

WMIAdventure/backend/WMIAdventure_backend/IngameUsers/businesslogic/exceptions.py

emkarcinos/WMIAdventure

7ca057bb4e4d462b8626d53b66bed86e0125059a

[ "Apache-2.0" ]

4

2021-05-26T15:09:29.000Z

2022-03-13T15:28:07.000Z

class CannotUpgradeCardException(Exception): pass

18

44

0.814815

4

54

11

1

0

0.12963

54

2

45

27

0.93617

0

1

0

true

0.5

0

0.5

0

1

0

1

null

0

1

0

null

0

1

0

5

b7f7a00e50cc821edba4832b0130fdd045845f6c

188,377

py

Python

mysite/patterns/73.py

BioinfoNet/prepub

e19c48cabf8bd22736dcef9308a5e196cfd8119a

[ "MIT" ]

19

2016-06-17T23:36:27.000Z

2020-01-13T16:41:55.000Z

mysite/patterns/73.py

BioinfoNet/prepub

e19c48cabf8bd22736dcef9308a5e196cfd8119a

[ "MIT" ]

13

2016-06-06T12:57:05.000Z

2019-02-05T02:21:00.000Z

patterns/73.py

OmnesRes/GRIMMER

173c99ebdb6a9edb1242d24a791d0c5d778ff643

[ "MIT" ]

7

2017-03-28T18:12:22.000Z

2021-06-16T09:32:59.000Z

pattern_zero=[0.0, 0.0135109777, 0.0266466504, 0.0273972603, 0.0394070182, 0.0409082379, 0.0517920811, 0.0540439107, 0.0547945205, 0.063801839, 0.0668042785, 0.0683054982, 0.075436292, 0.0791893413, 0.081441171, 0.0821917808, 0.08669544, 0.0911990993, 0.0942015388, 0.0957027585, 0.0975792832, 0.1028335523, 0.1065866016, 0.1080878214, 0.1088384312, 0.1095890411, 0.1140927003, 0.1182210546, 0.1185963595, 0.121598799, 0.1231000188, 0.1249765434, 0.1279789829, 0.1302308125, 0.1339838619, 0.1354850816, 0.1362356915, 0.1369863014, 0.1373616063, 0.1414899606, 0.1456183149, 0.1459936198, 0.1463689248, 0.1489960593, 0.150497279, 0.1523738037, 0.1550009383, 0.1553762432, 0.1576280728, 0.1613811222, 0.1628823419, 0.1632576468, 0.1636329518, 0.1643835616, 0.1647588666, 0.1688872209, 0.1711390505, 0.1730155752, 0.1733908801, 0.173766185, 0.1763933196, 0.1778945393, 0.1786451492, 0.179771064, 0.1823981985, 0.1827735035, 0.1850253331, 0.185775943, 0.1887783824, 0.1902796022, 0.1906549071, 0.191030212, 0.1917808219, 0.1921561269, 0.1925314318, 0.1962844811, 0.1985363108, 0.1989116157, 0.2004128354, 0.2007881404, 0.2011634453, 0.2037905798, 0.2049164947, 0.2052917996, 0.2060424095, 0.2071683243, 0.2097954588, 0.2101707637, 0.2105460687, 0.2124225934, 0.2131732032, 0.2158003378, 0.2161756427, 0.2176768625, 0.2180521674, 0.2184274723, 0.2191780822, 0.2195533871, 0.2199286921, 0.2206793019, 0.2236817414, 0.2251829612, 0.225933571, 0.226308876, 0.2278100957, 0.2281854006, 0.2285607056, 0.2293113154, 0.2311878401, 0.2323137549, 0.2326890599, 0.2330643648, 0.2334396697, 0.2345655845, 0.2364421092, 0.2371927191, 0.237568024, 0.237943329, 0.2394445487, 0.2398198536, 0.2405704635, 0.2420716832, 0.243197598, 0.243572903, 0.2443235129, 0.2450741227, 0.2454494277, 0.2458247326, 0.2462000375, 0.2465753425, 0.2469506474, 0.2473259523, 0.2477012573, 0.2480765622, 0.2488271721, 0.2495777819, 0.2499530869, 0.2510790017, 0.2525802214, 0.2533308313, 0.2537061362, 0.255207356, 0.2555826609, 0.2559579658, 0.2567085757, 0.2585851004, 0.2597110152, 0.2600863201, 0.2604616251, 0.26083693, 0.2619628448, 0.2638393695, 0.2645899794, 0.2649652843, 0.2653405892, 0.266841809, 0.2672171139, 0.2679677238, 0.2694689435, 0.2705948583, 0.2709701633, 0.2717207731, 0.272471383, 0.2728466879, 0.2732219929, 0.2735972978, 0.2739726027, 0.2743479077, 0.2747232126, 0.2750985175, 0.2754738225, 0.2762244324, 0.2769750422, 0.2773503472, 0.278476262, 0.2799774817, 0.2807280916, 0.2811033965, 0.2826046163, 0.2829799212, 0.2833552261, 0.284105836, 0.2859823607, 0.2871082755, 0.2874835804, 0.2878588853, 0.2882341903, 0.2893601051, 0.2912366298, 0.2919872396, 0.2923625446, 0.2927378495, 0.2942390692, 0.2946143742, 0.2953649841, 0.2968662038, 0.2979921186, 0.2983674235, 0.2991180334, 0.2998686433, 0.3002439482, 0.3006192531, 0.3009945581, 0.301369863, 0.3017451679, 0.3021204729, 0.3024957778, 0.3028710828, 0.3036216926, 0.3043723025, 0.3047476074, 0.3058735222, 0.307374742, 0.3081253518, 0.3085006568, 0.3100018765, 0.3103771815, 0.3107524864, 0.3115030963, 0.3133796209, 0.3145055357, 0.3148808407, 0.3152561456, 0.3156314506, 0.3167573654, 0.31863389, 0.3193844999, 0.3197598048, 0.3201351098, 0.3216363295, 0.3220116345, 0.3227622443, 0.3242634641, 0.3253893789, 0.3257646838, 0.3265152937, 0.3272659035, 0.3276412085, 0.3280165134, 0.3283918184, 0.3287671233, 0.3291424282, 0.3295177332, 0.3298930381, 0.330268343, 0.3310189529, 0.3317695628, 0.3321448677, 0.3332707825, 0.3347720023, 0.3355226121, 0.3358979171, 0.3373991368, 0.3377744417, 0.3381497467, 0.3389003565, 0.3407768812, 0.341902796, 0.342278101, 0.3426534059, 0.3430287108, 0.3441546256, 0.3460311503, 0.3467817602, 0.3471570651, 0.3475323701, 0.3490335898, 0.3494088947, 0.3501595046, 0.3516607243, 0.3527866391, 0.3531619441, 0.353912554, 0.3546631638, 0.3550384688, 0.3554137737, 0.3557890786, 0.3561643836, 0.3565396885, 0.3569149934, 0.3572902984, 0.3576656033, 0.3584162132, 0.359166823, 0.359542128, 0.3606680428, 0.3621692625, 0.3629198724, 0.3632951773, 0.3647963971, 0.365171702, 0.3655470069, 0.3662976168, 0.3681741415, 0.3693000563, 0.3696753612, 0.3700506662, 0.3704259711, 0.3715518859, 0.3734284106, 0.3741790205, 0.3745543254, 0.3749296303, 0.3764308501, 0.376806155, 0.3775567649, 0.3790579846, 0.3801838994, 0.3805592044, 0.3813098142, 0.3820604241, 0.382435729, 0.382811034, 0.3831863389, 0.3835616438, 0.3839369488, 0.3843122537, 0.3846875586, 0.3850628636, 0.3858134734, 0.3865640833, 0.3869393883, 0.3880653031, 0.3895665228, 0.3903171327, 0.3906924376, 0.3921936573, 0.3925689623, 0.3929442672, 0.3936948771, 0.3955714018, 0.3966973166, 0.3970726215, 0.3974479264, 0.3978232314, 0.3989491462, 0.4008256709, 0.4015762807, 0.4019515857, 0.4023268906, 0.4038281103, 0.4042034153, 0.4049540251, 0.4064552449, 0.4075811597, 0.4079564646, 0.4087070745, 0.4094576844, 0.4098329893, 0.4102082942, 0.4105835992, 0.4109589041, 0.411334209, 0.411709514, 0.4120848189, 0.4124601239, 0.4132107337, 0.4139613436, 0.4143366485, 0.4154625633, 0.4169637831, 0.4177143929, 0.4180896979, 0.4195909176, 0.4199662226, 0.4203415275, 0.4210921374, 0.422968662, 0.4240945768, 0.4244698818, 0.4248451867, 0.4252204916, 0.4263464065, 0.4282229311, 0.428973541, 0.4293488459, 0.4297241509, 0.4312253706, 0.4316006755, 0.4323512854, 0.4338525052, 0.43497842, 0.4353537249, 0.4361043348, 0.4368549446, 0.4372302496, 0.4376055545, 0.4379808594, 0.4383561644, 0.4387314693, 0.4391067743, 0.4394820792, 0.4398573841, 0.440607994, 0.4413586039, 0.4417339088, 0.4428598236, 0.4443610433, 0.4451116532, 0.4454869582, 0.4469881779, 0.4473634828, 0.4477387878, 0.4484893976, 0.4503659223, 0.4514918371, 0.4518671421, 0.452242447, 0.4526177519, 0.4537436667, 0.4556201914, 0.4563708013, 0.4567461062, 0.4571214111, 0.4586226309, 0.4589979358, 0.4597485457, 0.4612497654, 0.4623756802, 0.4627509852, 0.463501595, 0.4642522049, 0.4646275099, 0.4650028148, 0.4653781197, 0.4657534247, 0.4661287296, 0.4665040345, 0.4668793395, 0.4672546444, 0.4680052543, 0.4687558641, 0.4691311691, 0.4702570839, 0.4717583036, 0.4725089135, 0.4728842184, 0.4743854382, 0.4747607431, 0.475136048, 0.4758866579, 0.4777631826, 0.4788890974, 0.4792644023, 0.4796397073, 0.4800150122, 0.481140927, 0.4830174517, 0.4837680616, 0.4841433665, 0.4845186714, 0.4860198912, 0.4863951961, 0.487145806, 0.4886470257, 0.4897729405, 0.4901482454, 0.4908988553, 0.4916494652, 0.4920247701, 0.4924000751, 0.49277538, 0.4931506849, 0.4935259899, 0.4939012948, 0.4942765997, 0.4946519047, 0.4954025145, 0.4961531244, 0.4965284293, 0.4976543442, 0.4991555639, 0.4999061738, 0.5002814787, 0.5017826984, 0.5021580034, 0.5025333083, 0.5032839182, 0.5051604429, 0.5062863577, 0.5066616626, 0.5070369675, 0.5074122725, 0.5085381873, 0.510414712, 0.5111653218, 0.5115406268, 0.5119159317, 0.5134171514, 0.5137924564, 0.5145430662, 0.516044286, 0.5171702008, 0.5175455057, 0.5182961156, 0.5190467255, 0.5194220304, 0.5197973353, 0.5201726403, 0.5205479452, 0.5209232501, 0.5212985551, 0.52167386, 0.5220491649, 0.5227997748, 0.5235503847, 0.5239256896, 0.5250516044, 0.5265528242, 0.527303434, 0.527678739, 0.5291799587, 0.5295552637, 0.5299305686, 0.5306811785, 0.5325577031, 0.5336836179, 0.5340589229, 0.5344342278, 0.5348095327, 0.5359354476, 0.5378119722, 0.5385625821, 0.538937887, 0.539313192, 0.5408144117, 0.5411897166, 0.5419403265, 0.5434415463, 0.5445674611, 0.544942766, 0.5456933759, 0.5464439857, 0.5468192907, 0.5471945956, 0.5475699005, 0.5479452055, 0.5483205104, 0.5486958154, 0.5490711203, 0.5494464252, 0.5501970351, 0.550947645, 0.5513229499, 0.5524488647, 0.5539500844, 0.5547006943, 0.5550759992, 0.556577219, 0.5569525239, 0.5573278289, 0.5580784387, 0.5599549634, 0.5610808782, 0.5614561831, 0.5618314881, 0.562206793, 0.5633327078, 0.5652092325, 0.5659598424, 0.5663351473, 0.5667104522, 0.568211672, 0.5685869769, 0.5693375868, 0.5708388065, 0.5719647213, 0.5723400263, 0.5730906361, 0.573841246, 0.5742165509, 0.5745918559, 0.5749671608, 0.5753424658, 0.5757177707, 0.5760930756, 0.5764683806, 0.5768436855, 0.5775942954, 0.5783449052, 0.5787202102, 0.579846125, 0.5813473447, 0.5820979546, 0.5824732595, 0.5839744793, 0.5843497842, 0.5847250891, 0.585475699, 0.5873522237, 0.5884781385, 0.5888534434, 0.5892287484, 0.5896040533, 0.5907299681, 0.5926064928, 0.5933571026, 0.5937324076, 0.5941077125, 0.5956089323, 0.5959842372, 0.5967348471, 0.5982360668, 0.5993619816, 0.5997372865, 0.6004878964, 0.6012385063, 0.6016138112, 0.6019891162, 0.6023644211, 0.602739726, 0.603115031, 0.6034903359, 0.6038656408, 0.6042409458, 0.6049915556, 0.6057421655, 0.6061174704, 0.6072433853, 0.608744605, 0.6094952149, 0.6098705198, 0.6113717395, 0.6117470445, 0.6121223494, 0.6128729593, 0.614749484, 0.6158753988, 0.6162507037, 0.6166260086, 0.6170013136, 0.6181272284, 0.620003753, 0.6207543629, 0.6211296679, 0.6215049728, 0.6230061925, 0.6233814975, 0.6241321073, 0.6256333271, 0.6267592419, 0.6271345468, 0.6278851567, 0.6286357666, 0.6290110715, 0.6293863764, 0.6297616814, 0.6301369863, 0.6305122912, 0.6308875962, 0.6312629011, 0.631638206, 0.6323888159, 0.6331394258, 0.6335147307, 0.6346406455, 0.6361418653, 0.6368924751, 0.6372677801, 0.6387689998, 0.6391443047, 0.6395196097, 0.6402702196, 0.6421467442, 0.643272659, 0.643647964, 0.6440232689, 0.6443985738, 0.6455244886, 0.6474010133, 0.6481516232, 0.6485269281, 0.6489022331, 0.6504034528, 0.6507787577, 0.6515293676, 0.6530305874, 0.6541565022, 0.6545318071, 0.655282417, 0.6560330268, 0.6564083318, 0.6567836367, 0.6571589416, 0.6575342466, 0.6579095515, 0.6582848564, 0.6586601614, 0.6590354663, 0.6597860762, 0.6605366861, 0.660911991, 0.6620379058, 0.6635391255, 0.6642897354, 0.6646650403, 0.6661662601, 0.666541565, 0.66691687, 0.6676674798, 0.6695440045, 0.6706699193, 0.6710452242, 0.6714205292, 0.6717958341, 0.6729217489, 0.6747982736, 0.6755488835, 0.6759241884, 0.6762994933, 0.6778007131, 0.678176018, 0.6789266279, 0.6804278476, 0.6815537624, 0.6819290674, 0.6826796772, 0.6834302871, 0.683805592, 0.684180897, 0.6845562019, 0.6849315068, 0.6853068118, 0.6856821167, 0.6860574217, 0.6864327266, 0.6871833365, 0.6879339463, 0.6883092513, 0.6894351661, 0.6909363858, 0.6916869957, 0.6920623006, 0.6935635204, 0.6939388253, 0.6943141302, 0.6950647401, 0.6969412648, 0.6980671796, 0.6984424845, 0.6988177895, 0.6991930944, 0.7003190092, 0.7021955339, 0.7029461437, 0.7033214487, 0.7036967536, 0.7051979734, 0.7055732783, 0.7063238882, 0.7078251079, 0.7089510227, 0.7093263276, 0.7100769375, 0.7108275474, 0.7112028523, 0.7115781573, 0.7119534622, 0.7123287671, 0.7127040721, 0.713079377, 0.7134546819, 0.7138299869, 0.7145805967, 0.7153312066, 0.7157065115, 0.7168324263, 0.7183336461, 0.719084256, 0.7194595609, 0.7209607806, 0.7213360856, 0.7217113905, 0.7224620004, 0.7243385251, 0.7254644399, 0.7258397448, 0.7262150497, 0.7265903547, 0.7277162695, 0.7295927941, 0.730343404, 0.730718709, 0.7310940139, 0.7325952336, 0.7329705386, 0.7337211484, 0.7352223682, 0.736348283, 0.7367235879, 0.7374741978, 0.7382248077, 0.7386001126, 0.7389754175, 0.7393507225, 0.7397260274, 0.7401013323, 0.7404766373, 0.7408519422, 0.7412272471, 0.741977857, 0.7427284669, 0.7431037718, 0.7442296866, 0.7457309064, 0.7464815162, 0.7468568212, 0.7483580409, 0.7487333458, 0.7491086508, 0.7498592606, 0.7517357853, 0.7528617001, 0.7532370051, 0.75361231, 0.7539876149, 0.7551135297, 0.7569900544, 0.7577406643, 0.7581159692, 0.7584912742, 0.7599924939, 0.7603677988, 0.7611184087, 0.7626196284, 0.7637455433, 0.7641208482, 0.7648714581, 0.7656220679, 0.7659973729, 0.7663726778, 0.7667479827, 0.7671232877, 0.7674985926, 0.7678738975, 0.7682492025, 0.7686245074, 0.7693751173, 0.7701257272, 0.7705010321, 0.7716269469, 0.7731281666, 0.7738787765, 0.7742540814, 0.7757553012, 0.7761306061, 0.7765059111, 0.7772565209, 0.7791330456, 0.7802589604, 0.7806342653, 0.7810095703, 0.7813848752, 0.78251079, 0.7843873147, 0.7851379246, 0.7855132295, 0.7858885344, 0.7873897542, 0.7877650591, 0.788515669, 0.7900168887, 0.7911428035, 0.7915181085, 0.7922687183, 0.7930193282, 0.7933946331, 0.7937699381, 0.794145243, 0.7945205479, 0.7948958529, 0.7952711578, 0.7956464628, 0.7960217677, 0.7967723776, 0.7975229874, 0.7978982924, 0.7990242072, 0.8005254269, 0.8012760368, 0.8016513417, 0.8031525615, 0.8035278664, 0.8039031713, 0.8046537812, 0.8065303059, 0.8076562207, 0.8080315256, 0.8084068306, 0.8087821355, 0.8099080503, 0.811784575, 0.8125351848, 0.8129104898, 0.8132857947, 0.8147870144, 0.8151623194, 0.8159129293, 0.817414149, 0.8185400638, 0.8189153687, 0.8196659786, 0.8204165885, 0.8207918934, 0.8211671983, 0.8215425033, 0.8219178082, 0.8222931132, 0.8226684181, 0.823043723, 0.823419028, 0.8241696378, 0.8249202477, 0.8252955526, 0.8264214674, 0.8279226872, 0.8286732971, 0.829048602, 0.8305498217, 0.8309251267, 0.8313004316, 0.8320510415, 0.8339275661, 0.835053481, 0.8354287859, 0.8358040908, 0.8361793958, 0.8373053106, 0.8391818352, 0.8399324451, 0.84030775, 0.840683055, 0.8421842747, 0.8425595797, 0.8433101895, 0.8448114093, 0.8459373241, 0.846312629, 0.8470632389, 0.8478138488, 0.8481891537, 0.8485644586, 0.8489397636, 0.8493150685, 0.8496903734, 0.8500656784, 0.8504409833, 0.8508162882, 0.8515668981, 0.852317508, 0.8526928129, 0.8538187277, 0.8553199475, 0.8560705573, 0.8564458623, 0.857947082, 0.8583223869, 0.8586976919, 0.8594483017, 0.8613248264, 0.8624507412, 0.8628260462, 0.8632013511, 0.863576656, 0.8647025708, 0.8665790955, 0.8673297054, 0.8677050103, 0.8680803153, 0.869581535, 0.8699568399, 0.8707074498, 0.8722086695, 0.8733345844, 0.8737098893, 0.8744604992, 0.875211109, 0.875586414, 0.8759617189, 0.8763370238, 0.8767123288, 0.8770876337, 0.8774629386, 0.8778382436, 0.8782135485, 0.8789641584, 0.8797147682, 0.8800900732, 0.881215988, 0.8827172077, 0.8834678176, 0.8838431225, 0.8853443423, 0.8857196472, 0.8860949521, 0.886845562, 0.8887220867, 0.8898480015, 0.8902233064, 0.8905986114, 0.8909739163, 0.8920998311, 0.8939763558, 0.8947269657, 0.8951022706, 0.8954775755, 0.8969787953, 0.8973541002, 0.8981047101, 0.8996059298, 0.9007318446, 0.9011071496, 0.9018577594, 0.9026083693, 0.9029836742, 0.9033589792, 0.9037342841, 0.904109589, 0.904484894, 0.9048601989, 0.9052355038, 0.9056108088, 0.9063614187, 0.9071120285, 0.9074873335, 0.9086132483, 0.910114468, 0.9108650779, 0.9112403828, 0.9127416026, 0.9131169075, 0.9134922124, 0.9142428223, 0.916119347, 0.9172452618, 0.9176205667, 0.9179958716, 0.9183711766, 0.9194970914, 0.9213736161, 0.9221242259, 0.9224995309, 0.9228748358, 0.9243760555, 0.9247513605, 0.9255019704, 0.9270031901, 0.9281291049, 0.9285044098, 0.9292550197, 0.9300056296, 0.9303809345, 0.9307562394, 0.9311315444, 0.9315068493, 0.9318821543, 0.9322574592, 0.9326327641, 0.9330080691, 0.9337586789, 0.9345092888, 0.9348845937, 0.9360105085, 0.9375117283, 0.9382623382, 0.9386376431, 0.9401388628, 0.9405141678, 0.9408894727, 0.9416400826, 0.9435166072, 0.944642522, 0.945017827, 0.9453931319, 0.9457684369, 0.9468943517, 0.9487708763, 0.9495214862, 0.9498967911, 0.9502720961, 0.9517733158, 0.9521486208, 0.9528992306, 0.9544004504, 0.9555263652, 0.9559016701, 0.95665228, 0.9574028898, 0.9577781948, 0.9581534997, 0.9585288047, 0.9589041096, 0.9592794145, 0.9596547195, 0.9600300244, 0.9604053293, 0.9611559392, 0.9619065491, 0.962281854, 0.9634077688, 0.9649089886, 0.9656595984, 0.9660349034, 0.9675361231, 0.967911428, 0.968286733, 0.9690373428, 0.9709138675, 0.9720397823, 0.9724150873, 0.9727903922, 0.9731656971, 0.9742916119, 0.9761681366, 0.9769187465, 0.9772940514, 0.9776693564, 0.9791705761, 0.979545881, 0.9802964909, 0.9817977106, 0.9829236254, 0.9832989304, 0.9840495403, 0.9848001501, 0.9851754551, 0.98555076, 0.9859260649, 0.9863013699, 0.9866766748, 0.9870519797, 0.9874272847, 0.9878025896, 0.9885531995, 0.9893038093, 0.9896791143, 0.9908050291, 0.9923062488, 0.9930568587, 0.9934321636, 0.9949333834, 0.9953086883, 0.9956839932, 0.9964346031, 0.9983111278, 0.9994370426, 0.9998123475] pattern_odd=[0.00018765247, 0.0005629574, 0.00168887221, 0.00356539689, 0.00431600676, 0.00469131169, 0.00506661663, 0.00656783637, 0.0069431413, 0.00769375117, 0.00919497091, 0.01032088572, 0.01069619066, 0.01144680053, 0.0121974104, 0.01257271533, 0.01294802027, 0.0133233252, 0.01369863014, 0.01407393507, 0.01444924001, 0.01482454494, 0.01519984988, 0.01595045975, 0.01670106962, 0.01707637455, 0.01820228936, 0.0197035091, 0.02045411897, 0.02082942391, 0.02233064365, 0.02270594858, 0.02308125352, 0.02383186339, 0.02570838807, 0.02683430287, 0.02720960781, 0.02758491274, 0.02796021768, 0.02908613248, 0.03096265716, 0.03171326703, 0.03208857197, 0.0324638769, 0.03396509664, 0.03434040158, 0.03509101145, 0.03659223119, 0.03771814599, 0.03809345093, 0.0388440608, 0.03959467067, 0.03996997561, 0.04034528054, 0.04072058548, 0.04109589041, 0.04147119535, 0.04184650028, 0.04222180522, 0.04259711015, 0.04334772002, 0.04409832989, 0.04447363483, 0.04559954963, 0.04710076938, 0.04785137925, 0.04822668418, 0.04972790392, 0.05010320886, 0.05047851379, 0.05122912366, 0.05310564834, 0.05423156315, 0.05460686808, 0.05498217302, 0.05535747795, 0.05648339276, 0.05835991743, 0.0591105273, 0.05948583224, 0.05986113717, 0.06136235692, 0.06173766185, 0.06248827172, 0.06398949146, 0.06511540627, 0.0654907112, 0.06624132107, 0.06699193094, 0.06736723588, 0.06774254081, 0.06811784575, 0.06849315069, 0.06886845562, 0.06924376056, 0.06961906549, 0.06999437043, 0.0707449803, 0.07149559017, 0.0718708951, 0.07299680991, 0.07449802965, 0.07524863952, 0.07562394446, 0.0771251642, 0.07750046913, 0.07787577407, 0.07862638394, 0.08050290861, 0.08162882342, 0.08200412835, 0.08237943329, 0.08275473823, 0.08388065303, 0.08575717771, 0.08650778758, 0.08688309251, 0.08725839745, 0.08875961719, 0.08913492212, 0.089885532, 0.09138675174, 0.09251266654, 0.09288797148, 0.09363858135, 0.09438919122, 0.09476449615, 0.09513980109, 0.09551510602, 0.09589041096, 0.09626571589, 0.09664102083, 0.09701632577, 0.0973916307, 0.09814224057, 0.09889285044, 0.09926815538, 0.10039407018, 0.10189528992, 0.10264589979, 0.10302120473, 0.10452242447, 0.10489772941, 0.10527303434, 0.10602364421, 0.10790016889, 0.10902608369, 0.10940138863, 0.10977669356, 0.1101519985, 0.11127791331, 0.11315443798, 0.11390504785, 0.11428035279, 0.11465565772, 0.11615687746, 0.1165321824, 0.11728279227, 0.11878401201, 0.11990992682, 0.12028523175, 0.12103584162, 0.12178645149, 0.12216175643, 0.12253706136, 0.1229123663, 0.12328767123, 0.12366297617, 0.1240382811, 0.12441358604, 0.12478889097, 0.12553950084, 0.12629011072, 0.12666541565, 0.12779133046, 0.1292925502, 0.13004316007, 0.130418465, 0.13191968474, 0.13229498968, 0.13267029461, 0.13342090449, 0.13529742916, 0.13642334397, 0.1367986489, 0.13717395384, 0.13754925877, 0.13867517358, 0.14055169826, 0.14130230813, 0.14167761306, 0.142052918, 0.14355413774, 0.14392944267, 0.14468005254, 0.14618127228, 0.14730718709, 0.14768249203, 0.1484331019, 0.14918371177, 0.1495590167, 0.14993432164, 0.15030962657, 0.15068493151, 0.15106023644, 0.15143554138, 0.15181084631, 0.15218615125, 0.15293676112, 0.15368737099, 0.15406267592, 0.15518859073, 0.15668981047, 0.15744042034, 0.15781572528, 0.15931694502, 0.15969224995, 0.16006755489, 0.16081816476, 0.16269468944, 0.16382060424, 0.16419590918, 0.16457121411, 0.16494651905, 0.16607243385, 0.16794895853, 0.1686995684, 0.16907487334, 0.16945017827, 0.17095139801, 0.17132670295, 0.17207731282, 0.17357853256, 0.17470444736, 0.1750797523, 0.17583036217, 0.17658097204, 0.17695627698, 0.17733158191, 0.17770688685, 0.17808219178, 0.17845749672, 0.17883280165, 0.17920810659, 0.17958341152, 0.18033402139, 0.18108463126, 0.1814599362, 0.182585851, 0.18408707075, 0.18483768062, 0.18521298555, 0.18671420529, 0.18708951023, 0.18746481516, 0.18821542503, 0.19009194971, 0.19121786452, 0.19159316945, 0.19196847439, 0.19234377932, 0.19346969413, 0.1953462188, 0.19609682867, 0.19647213361, 0.19684743854, 0.19834865829, 0.19872396322, 0.19947457309, 0.20097579283, 0.20210170764, 0.20247701257, 0.20322762244, 0.20397823231, 0.20435353725, 0.20472884218, 0.20510414712, 0.20547945206, 0.20585475699, 0.20623006193, 0.20660536686, 0.2069806718, 0.20773128167, 0.20848189154, 0.20885719647, 0.20998311128, 0.21148433102, 0.21223494089, 0.21261024583, 0.21411146557, 0.2144867705, 0.21486207544, 0.21561268531, 0.21748920998, 0.21861512479, 0.21899042972, 0.21936573466, 0.2197410396, 0.2208669544, 0.22274347908, 0.22349408895, 0.22386939388, 0.22424469882, 0.22574591856, 0.22612122349, 0.22687183337, 0.22837305311, 0.22949896791, 0.22987427285, 0.23062488272, 0.23137549259, 0.23175079752, 0.23212610246, 0.23250140739, 0.23287671233, 0.23325201726, 0.2336273222, 0.23400262714, 0.23437793207, 0.23512854194, 0.23587915181, 0.23625445675, 0.23738037155, 0.23888159129, 0.23963220116, 0.2400075061, 0.24150872584, 0.24188403078, 0.24225933571, 0.24300994558, 0.24488647026, 0.24601238506, 0.24638769, 0.24676299493, 0.24713829987, 0.24826421467, 0.25014073935, 0.25089134922, 0.25126665416, 0.25164195909, 0.25314317883, 0.25351848377, 0.25426909364, 0.25577031338, 0.25689622819, 0.25727153312, 0.25802214299, 0.25877275286, 0.2591480578, 0.25952336273, 0.25989866767, 0.2602739726, 0.26064927754, 0.26102458247, 0.26139988741, 0.26177519234, 0.26252580221, 0.26327641209, 0.26365171702, 0.26477763183, 0.26627885157, 0.26702946144, 0.26740476637, 0.26890598611, 0.26928129105, 0.26965659598, 0.27040720586, 0.27228373053, 0.27340964534, 0.27378495027, 0.27416025521, 0.27453556014, 0.27566147495, 0.27753799963, 0.2782886095, 0.27866391443, 0.27903921937, 0.28054043911, 0.28091574404, 0.28166635391, 0.28316757365, 0.28429348846, 0.2846687934, 0.28541940327, 0.28617001314, 0.28654531807, 0.28692062301, 0.28729592794, 0.28767123288, 0.28804653781, 0.28842184275, 0.28879714768, 0.28917245262, 0.28992306249, 0.29067367236, 0.29104897729, 0.2921748921, 0.29367611184, 0.29442672171, 0.29480202665, 0.29630324639, 0.29667855132, 0.29705385626, 0.29780446613, 0.29968099081, 0.30080690561, 0.30118221055, 0.30155751548, 0.30193282042, 0.30305873522, 0.3049352599, 0.30568586977, 0.3060611747, 0.30643647964, 0.30793769938, 0.30831300432, 0.30906361419, 0.31056483393, 0.31169074873, 0.31206605367, 0.31281666354, 0.31356727341, 0.31394257835, 0.31431788328, 0.31469318822, 0.31506849315, 0.31544379809, 0.31581910302, 0.31619440796, 0.31656971289, 0.31732032276, 0.31807093263, 0.31844623757, 0.31957215237, 0.32107337212, 0.32182398199, 0.32219928692, 0.32370050666, 0.3240758116, 0.32445111653, 0.3252017264, 0.32707825108, 0.32820416589, 0.32857947082, 0.32895477576, 0.32933008069, 0.3304559955, 0.33233252017, 0.33308313004, 0.33345843498, 0.33383373991, 0.33533495966, 0.33571026459, 0.33646087446, 0.3379620942, 0.33908800901, 0.33946331394, 0.34021392381, 0.34096453368, 0.34133983862, 0.34171514355, 0.34209044849, 0.34246575343, 0.34284105836, 0.3432163633, 0.34359166823, 0.34396697317, 0.34471758304, 0.34546819291, 0.34584349784, 0.34696941265, 0.34847063239, 0.34922124226, 0.3495965472, 0.35109776694, 0.35147307187, 0.35184837681, 0.35259898668, 0.35447551135, 0.35560142616, 0.35597673109, 0.35635203603, 0.35672734097, 0.35785325577, 0.35972978045, 0.36048039032, 0.36085569525, 0.36123100019, 0.36273221993, 0.36310752486, 0.36385813473, 0.36535935448, 0.36648526928, 0.36686057422, 0.36761118409, 0.36836179396, 0.36873709889, 0.36911240383, 0.36948770876, 0.3698630137, 0.37023831863, 0.37061362357, 0.3709889285, 0.37136423344, 0.37211484331, 0.37286545318, 0.37324075812, 0.37436667292, 0.37586789266, 0.37661850253, 0.37699380747, 0.37849502721, 0.37887033215, 0.37924563708, 0.37999624695, 0.38187277163, 0.38299868643, 0.38337399137, 0.3837492963, 0.38412460124, 0.38525051604, 0.38712704072, 0.38787765059, 0.38825295553, 0.38862826046, 0.3901294802, 0.39050478514, 0.39125539501, 0.39275661475, 0.39388252956, 0.39425783449, 0.39500844436, 0.39575905423, 0.39613435917, 0.3965096641, 0.39688496904, 0.39726027397, 0.39763557891, 0.39801088384, 0.39838618878, 0.39876149371, 0.39951210358, 0.40026271346, 0.40063801839, 0.4017639332, 0.40326515294, 0.40401576281, 0.40439106774, 0.40589228748, 0.40626759242, 0.40664289735, 0.40739350723, 0.4092700319, 0.41039594671, 0.41077125164, 0.41114655658, 0.41152186151, 0.41264777632, 0.414524301, 0.41527491087, 0.4156502158, 0.41602552074, 0.41752674048, 0.41790204541, 0.41865265528, 0.42015387502, 0.42127978983, 0.42165509476, 0.42240570464, 0.42315631451, 0.42353161944, 0.42390692438, 0.42428222931, 0.42465753425, 0.42503283918, 0.42540814412, 0.42578344905, 0.42615875399, 0.42690936386, 0.42765997373, 0.42803527866, 0.42916119347, 0.43066241321, 0.43141302308, 0.43178832802, 0.43328954776, 0.43366485269, 0.43404015763, 0.4347907675, 0.43666729218, 0.43779320698, 0.43816851192, 0.43854381685, 0.43891912179, 0.44004503659, 0.44192156127, 0.44267217114, 0.44304747607, 0.44342278101, 0.44492400075, 0.44529930569, 0.44604991556, 0.4475511353, 0.4486770501, 0.44905235504, 0.44980296491, 0.45055357478, 0.45092887972, 0.45130418465, 0.45167948959, 0.45205479452, 0.45243009946, 0.45280540439, 0.45318070933, 0.45355601426, 0.45430662413, 0.455057234, 0.45543253894, 0.45655845374, 0.45805967349, 0.45881028336, 0.45918558829, 0.46068680803, 0.46106211297, 0.4614374179, 0.46218802777, 0.46406455245, 0.46519046726, 0.46556577219, 0.46594107713, 0.46631638206, 0.46744229687, 0.46931882154, 0.47006943141, 0.47044473635, 0.47082004128, 0.47232126103, 0.47269656596, 0.47344717583, 0.47494839557, 0.47607431038, 0.47644961531, 0.47720022518, 0.47795083505, 0.47832613999, 0.47870144492, 0.47907674986, 0.4794520548, 0.47982735973, 0.48020266467, 0.4805779696, 0.48095327454, 0.48170388441, 0.48245449428, 0.48282979921, 0.48395571402, 0.48545693376, 0.48620754363, 0.48658284856, 0.48808406831, 0.48845937324, 0.48883467818, 0.48958528805, 0.49146181272, 0.49258772753, 0.49296303246, 0.4933383374, 0.49371364233, 0.49483955714, 0.49671608182, 0.49746669169, 0.49784199662, 0.49821730156, 0.4997185213, 0.50009382623, 0.5008444361, 0.50234565585, 0.50347157065, 0.50384687559, 0.50459748546, 0.50534809533, 0.50572340026, 0.5060987052, 0.50647401013, 0.50684931507, 0.50722462, 0.50759992494, 0.50797522987, 0.50835053481, 0.50910114468, 0.50985175455, 0.51022705949, 0.51135297429, 0.51285419403, 0.5136048039, 0.51398010884, 0.51548132858, 0.51585663352, 0.51623193845, 0.51698254832, 0.518859073, 0.5199849878, 0.52036029274, 0.52073559767, 0.52111090261, 0.52223681741, 0.52411334209, 0.52486395196, 0.5252392569, 0.52561456183, 0.52711578157, 0.52749108651, 0.52824169638, 0.52974291612, 0.53086883093, 0.53124413586, 0.53199474573, 0.5327453556, 0.53312066054, 0.53349596547, 0.53387127041, 0.53424657534, 0.53462188028, 0.53499718521, 0.53537249015, 0.53574779508, 0.53649840495, 0.53724901483, 0.53762431976, 0.53875023457, 0.54025145431, 0.54100206418, 0.54137736911, 0.54287858885, 0.54325389379, 0.54362919872, 0.54437980859, 0.54625633327, 0.54738224808, 0.54775755301, 0.54813285795, 0.54850816288, 0.54963407769, 0.55151060236, 0.55226121224, 0.55263651717, 0.55301182211, 0.55451304185, 0.55488834678, 0.55563895665, 0.55714017639, 0.5582660912, 0.55864139613, 0.55939200601, 0.56014261588, 0.56051792081, 0.56089322575, 0.56126853068, 0.56164383562, 0.56201914055, 0.56239444549, 0.56276975042, 0.56314505536, 0.56389566523, 0.5646462751, 0.56502158003, 0.56614749484, 0.56764871458, 0.56839932445, 0.56877462939, 0.57027584913, 0.57065115406, 0.571026459, 0.57177706887, 0.57365359355, 0.57477950835, 0.57515481329, 0.57553011822, 0.57590542316, 0.57703133796, 0.57890786264, 0.57965847251, 0.58003377744, 0.58040908238, 0.58191030212, 0.58228560706, 0.58303621693, 0.58453743667, 0.58566335147, 0.58603865641, 0.58678926628, 0.58753987615, 0.58791518109, 0.58829048602, 0.58866579096, 0.58904109589, 0.58941640083, 0.58979170576, 0.5901670107, 0.59054231563, 0.5912929255, 0.59204353537, 0.59241884031, 0.59354475511, 0.59504597486, 0.59579658473, 0.59617188966, 0.5976731094, 0.59804841434, 0.59842371927, 0.59917432914, 0.60105085382, 0.60217676863, 0.60255207356, 0.6029273785, 0.60330268343, 0.60442859824, 0.60630512291, 0.60705573278, 0.60743103772, 0.60780634265, 0.60930756239, 0.60968286733, 0.6104334772, 0.61193469694, 0.61306061175, 0.61343591668, 0.61418652655, 0.61493713642, 0.61531244136, 0.61568774629, 0.61606305123, 0.61643835616, 0.6168136611, 0.61718896604, 0.61756427097, 0.61793957591, 0.61869018578, 0.61944079565, 0.61981610058, 0.62094201539, 0.62244323513, 0.623193845, 0.62356914993, 0.62507036968, 0.62544567461, 0.62582097955, 0.62657158942, 0.62844811409, 0.6295740289, 0.62994933383, 0.63032463877, 0.6306999437, 0.63182585851, 0.63370238319, 0.63445299306, 0.63482829799, 0.63520360293, 0.63670482267, 0.6370801276, 0.63783073747, 0.63933195722, 0.64045787202, 0.64083317696, 0.64158378683, 0.6423343967, 0.64270970163, 0.64308500657, 0.6434603115, 0.64383561644, 0.64421092137, 0.64458622631, 0.64496153124, 0.64533683618, 0.64608744605, 0.64683805592, 0.64721336086, 0.64833927566, 0.6498404954, 0.65059110527, 0.65096641021, 0.65246762995, 0.65284293489, 0.65321823982, 0.65396884969, 0.65584537437, 0.65697128917, 0.65734659411, 0.65772189904, 0.65809720398, 0.65922311878, 0.66109964346, 0.66185025333, 0.66222555827, 0.6626008632, 0.66410208294, 0.66447738788, 0.66522799775, 0.66672921749, 0.6678551323, 0.66823043723, 0.6689810471, 0.66973165697, 0.67010696191, 0.67048226684, 0.67085757178, 0.67123287671, 0.67160818165, 0.67198348658, 0.67235879152, 0.67273409645, 0.67348470632, 0.67423531619, 0.67461062113, 0.67573653594, 0.67723775568, 0.67798836555, 0.67836367048, 0.67986489022, 0.68024019516, 0.68061550009, 0.68136610996, 0.68324263464, 0.68436854945, 0.68474385438, 0.68511915932, 0.68549446425, 0.68662037906, 0.68849690373, 0.68924751361, 0.68962281854, 0.68999812348, 0.69149934322, 0.69187464815, 0.69262525802, 0.69412647776, 0.69525239257, 0.6956276975, 0.69637830738, 0.69712891725, 0.69750422218, 0.69787952712, 0.69825483205, 0.69863013699, 0.69900544192, 0.69938074686, 0.69975605179, 0.70013135673, 0.7008819666, 0.70163257647, 0.7020078814, 0.70313379621, 0.70463501595, 0.70538562582, 0.70576093076, 0.7072621505, 0.70763745543, 0.70801276037, 0.70876337024, 0.71063989492, 0.71176580972, 0.71214111466, 0.71251641959, 0.71289172453, 0.71401763933, 0.71589416401, 0.71664477388, 0.71702007881, 0.71739538375, 0.71889660349, 0.71927190843, 0.7200225183, 0.72152373804, 0.72264965284, 0.72302495778, 0.72377556765, 0.72452617752, 0.72490148245, 0.72527678739, 0.72565209233, 0.72602739726, 0.7264027022, 0.72677800713, 0.72715331207, 0.727528617, 0.72827922687, 0.72902983674, 0.72940514168, 0.73053105648, 0.73203227622, 0.7327828861, 0.73315819103, 0.73465941077, 0.73503471571, 0.73541002064, 0.73616063051, 0.73803715519, 0.73916306999, 0.73953837493, 0.73991367987, 0.7402889848, 0.74141489961, 0.74329142428, 0.74404203415, 0.74441733909, 0.74479264402, 0.74629386376, 0.7466691687, 0.74741977857, 0.74892099831, 0.75004691312, 0.75042221805, 0.75117282792, 0.75192343779, 0.75229874273, 0.75267404766, 0.7530493526, 0.75342465753, 0.75379996247, 0.75417526741, 0.75455057234, 0.75492587728, 0.75567648715, 0.75642709702, 0.75680240195, 0.75792831676, 0.7594295365, 0.76018014637, 0.7605554513, 0.76205667105, 0.76243197598, 0.76280728092, 0.76355789079, 0.76543441546, 0.76656033027, 0.7669356352, 0.76731094014, 0.76768624507, 0.76881215988, 0.77068868456, 0.77143929443, 0.77181459936, 0.7721899043, 0.77369112404, 0.77406642897, 0.77481703884, 0.77631825859, 0.77744417339, 0.77781947833, 0.7785700882, 0.77932069807, 0.779696003, 0.78007130794, 0.78044661287, 0.78082191781, 0.78119722274, 0.78157252768, 0.78194783261, 0.78232313755, 0.78307374742, 0.78382435729, 0.78419966223, 0.78532557703, 0.78682679677, 0.78757740664, 0.78795271158, 0.78945393132, 0.78982923625, 0.79020454119, 0.79095515106, 0.79283167574, 0.79395759054, 0.79433289548, 0.79470820041, 0.79508350535, 0.79620942015, 0.79808594483, 0.7988365547, 0.79921185964, 0.79958716457, 0.80108838431, 0.80146368925, 0.80221429912, 0.80371551886, 0.80484143367, 0.8052167386, 0.80596734847, 0.80671795834, 0.80709326328, 0.80746856821, 0.80784387315, 0.80821917808, 0.80859448302, 0.80896978795, 0.80934509289, 0.80972039782, 0.81047100769, 0.81122161756, 0.8115969225, 0.81272283731, 0.81422405705, 0.81497466692, 0.81534997185, 0.81685119159, 0.81722649653, 0.81760180146, 0.81835241133, 0.82022893601, 0.82135485082, 0.82173015575, 0.82210546069, 0.82248076562, 0.82360668043, 0.8254832051, 0.82623381498, 0.82660911991, 0.82698442485, 0.82848564459, 0.82886094952, 0.82961155939, 0.83111277913, 0.83223869394, 0.83261399887, 0.83336460875, 0.83411521862, 0.83449052355, 0.83486582849, 0.83524113342, 0.83561643836, 0.83599174329, 0.83636704823, 0.83674235316, 0.8371176581, 0.83786826797, 0.83861887784, 0.83899418277, 0.84012009758, 0.84162131732, 0.84237192719, 0.84274723213, 0.84424845187, 0.8446237568, 0.84499906174, 0.84574967161, 0.84762619628, 0.84875211109, 0.84912741603, 0.84950272096, 0.8498780259, 0.8510039407, 0.85288046538, 0.85363107525, 0.85400638018, 0.85438168512, 0.85588290486, 0.8562582098, 0.85700881967, 0.85851003941, 0.85963595421, 0.86001125915, 0.86076186902, 0.86151247889, 0.86188778382, 0.86226308876, 0.8626383937, 0.86301369863, 0.86338900357, 0.8637643085, 0.86413961344, 0.86451491837, 0.86526552824, 0.86601613811, 0.86639144305, 0.86751735785, 0.86901857759, 0.86976918747, 0.8701444924, 0.87164571214, 0.87202101708, 0.87239632201, 0.87314693188, 0.87502345656, 0.87614937136, 0.8765246763, 0.87689998124, 0.87727528617, 0.87840120098, 0.88027772565, 0.88102833552, 0.88140364046, 0.88177894539, 0.88328016513, 0.88365547007, 0.88440607994, 0.88590729968, 0.88703321449, 0.88740851942, 0.88815912929, 0.88890973916, 0.8892850441, 0.88966034903, 0.89003565397, 0.8904109589, 0.89078626384, 0.89116156878, 0.89153687371, 0.89191217865, 0.89266278852, 0.89341339839, 0.89378870332, 0.89491461813, 0.89641583787, 0.89716644774, 0.89754175267, 0.89904297242, 0.89941827735, 0.89979358229, 0.90054419216, 0.90242071683, 0.90354663164, 0.90392193657, 0.90429724151, 0.90467254644, 0.90579846125, 0.90767498593, 0.9084255958, 0.90880090073, 0.90917620567, 0.91067742541, 0.91105273034, 0.91180334021, 0.91330455996, 0.91443047476, 0.9148057797, 0.91555638957, 0.91630699944, 0.91668230437, 0.91705760931, 0.91743291424, 0.91780821918, 0.91818352411, 0.91855882905, 0.91893413398, 0.91930943892, 0.92006004879, 0.92081065866, 0.9211859636, 0.9223118784, 0.92381309814, 0.92456370801, 0.92493901295, 0.92644023269, 0.92681553762, 0.92719084256, 0.92794145243, 0.92981797711, 0.93094389191, 0.93131919685, 0.93169450178, 0.93206980672, 0.93319572152, 0.9350722462, 0.93582285607, 0.93619816101, 0.93657346594, 0.93807468568, 0.93844999062, 0.93920060049, 0.94070182023, 0.94182773504, 0.94220303997, 0.94295364984, 0.94370425971, 0.94407956465, 0.94445486958, 0.94483017452, 0.94520547945, 0.94558078439, 0.94595608932, 0.94633139426, 0.94670669919, 0.94745730906, 0.94820791893, 0.94858322387, 0.94970913868, 0.95121035842, 0.95196096829, 0.95233627322, 0.95383749296, 0.9542127979, 0.95458810283, 0.9553387127, 0.95721523738, 0.95834115219, 0.95871645712, 0.95909176206, 0.95946706699, 0.9605929818, 0.96246950647, 0.96322011635, 0.96359542128, 0.96397072622, 0.96547194596, 0.96584725089, 0.96659786076, 0.9680990805, 0.96922499531, 0.96960030024, 0.97035091011, 0.97110151999, 0.97147682492, 0.97185212986, 0.97222743479, 0.97260273973, 0.97297804466, 0.9733533496, 0.97372865453, 0.97410395947, 0.97485456934, 0.97560517921, 0.97598048414, 0.97710639895, 0.97860761869, 0.97935822856, 0.9797335335, 0.98123475324, 0.98161005817, 0.98198536311, 0.98273597298, 0.98461249765, 0.98573841246, 0.9861137174, 0.98648902233, 0.98686432727, 0.98799024207, 0.98986676675, 0.99061737662, 0.99099268155, 0.99136798649, 0.99286920623, 0.99324451117, 0.99399512104, 0.99549634078, 0.99662225558, 0.99699756052, 0.99774817039, 0.99849878026, 0.99887408519, 0.99924939013, 0.99962469507] pattern_even=[0.0, 0.0003753049, 0.0007506099, 0.0011259148, 0.0015012197, 0.0022518296, 0.0030024395, 0.0033777444, 0.0045036592, 0.006004879, 0.0067554888, 0.0071307938, 0.0086320135, 0.0090073184, 0.0093826234, 0.0101332333, 0.0120097579, 0.0131356727, 0.0135109777, 0.0138862826, 0.0142615875, 0.0153875023, 0.017264027, 0.0180146369, 0.0183899418, 0.0187652468, 0.0202664665, 0.0206417714, 0.0213923813, 0.0228936011, 0.0240195159, 0.0243948208, 0.0251454307, 0.0258960405, 0.0262713455, 0.0266466504, 0.0270219553, 0.0273972603, 0.0277725652, 0.0281478701, 0.0285231751, 0.02889848, 0.0296490899, 0.0303996998, 0.0307750047, 0.0319009195, 0.0334021392, 0.0341527491, 0.034528054, 0.0360292738, 0.0364045787, 0.0367798837, 0.0375304935, 0.0394070182, 0.040532933, 0.0409082379, 0.0412835429, 0.0416588478, 0.0427847626, 0.0446612873, 0.0454118972, 0.0457872021, 0.046162507, 0.0476637268, 0.0480390317, 0.0487896416, 0.0502908613, 0.0514167761, 0.0517920811, 0.0525426909, 0.0532933008, 0.0536686057, 0.0540439107, 0.0544192156, 0.0547945205, 0.0551698255, 0.0555451304, 0.0559204354, 0.0562957403, 0.0570463502, 0.05779696, 0.058172265, 0.0592981798, 0.0607993995, 0.0615500094, 0.0619253143, 0.0634265341, 0.063801839, 0.0641771439, 0.0649277538, 0.0668042785, 0.0679301933, 0.0683054982, 0.0686808032, 0.0690561081, 0.0701820229, 0.0720585476, 0.0728091574, 0.0731844624, 0.0735597673, 0.0750609871, 0.075436292, 0.0761869019, 0.0776881216, 0.0788140364, 0.0791893413, 0.0799399512, 0.0806905611, 0.081065866, 0.081441171, 0.0818164759, 0.0821917808, 0.0825670858, 0.0829423907, 0.0833176956, 0.0836930006, 0.0844436104, 0.0851942203, 0.0855695252, 0.08669544, 0.0881966598, 0.0889472697, 0.0893225746, 0.0908237943, 0.0911990993, 0.0915744042, 0.0923250141, 0.0942015388, 0.0953274536, 0.0957027585, 0.0960780634, 0.0964533684, 0.0975792832, 0.0994558078, 0.1002064177, 0.1005817227, 0.1009570276, 0.1024582473, 0.1028335523, 0.1035841621, 0.1050853819, 0.1062112967, 0.1065866016, 0.1073372115, 0.1080878214, 0.1084631263, 0.1088384312, 0.1092137362, 0.1095890411, 0.109964346, 0.110339651, 0.1107149559, 0.1110902608, 0.1118408707, 0.1125914806, 0.1129667855, 0.1140927003, 0.1155939201, 0.1163445299, 0.1167198349, 0.1182210546, 0.1185963595, 0.1189716645, 0.1197222743, 0.121598799, 0.1227247138, 0.1231000188, 0.1234753237, 0.1238506286, 0.1249765434, 0.1268530681, 0.127603678, 0.1279789829, 0.1283542879, 0.1298555076, 0.1302308125, 0.1309814224, 0.1324826421, 0.133608557, 0.1339838619, 0.1347344718, 0.1354850816, 0.1358603866, 0.1362356915, 0.1366109964, 0.1369863014, 0.1373616063, 0.1377369112, 0.1381122162, 0.1384875211, 0.139238131, 0.1399887409, 0.1403640458, 0.1414899606, 0.1429911803, 0.1437417902, 0.1441170951, 0.1456183149, 0.1459936198, 0.1463689248, 0.1471195346, 0.1489960593, 0.1501219741, 0.150497279, 0.150872584, 0.1512478889, 0.1523738037, 0.1542503284, 0.1550009383, 0.1553762432, 0.1557515481, 0.1572527679, 0.1576280728, 0.1583786827, 0.1598799024, 0.1610058172, 0.1613811222, 0.162131732, 0.1628823419, 0.1632576468, 0.1636329518, 0.1640082567, 0.1643835616, 0.1647588666, 0.1651341715, 0.1655094765, 0.1658847814, 0.1666353913, 0.1673860011, 0.1677613061, 0.1688872209, 0.1703884406, 0.1711390505, 0.1715143554, 0.1730155752, 0.1733908801, 0.173766185, 0.1745167949, 0.1763933196, 0.1775192344, 0.1778945393, 0.1782698442, 0.1786451492, 0.179771064, 0.1816475887, 0.1823981985, 0.1827735035, 0.1831488084, 0.1846500281, 0.1850253331, 0.185775943, 0.1872771627, 0.1884030775, 0.1887783824, 0.1895289923, 0.1902796022, 0.1906549071, 0.191030212, 0.191405517, 0.1917808219, 0.1921561269, 0.1925314318, 0.1929067367, 0.1932820417, 0.1940326515, 0.1947832614, 0.1951585663, 0.1962844811, 0.1977857009, 0.1985363108, 0.1989116157, 0.2004128354, 0.2007881404, 0.2011634453, 0.2019140552, 0.2037905798, 0.2049164947, 0.2052917996, 0.2056671045, 0.2060424095, 0.2071683243, 0.2090448489, 0.2097954588, 0.2101707637, 0.2105460687, 0.2120472884, 0.2124225934, 0.2131732032, 0.214674423, 0.2158003378, 0.2161756427, 0.2169262526, 0.2176768625, 0.2180521674, 0.2184274723, 0.2188027773, 0.2191780822, 0.2195533871, 0.2199286921, 0.220303997, 0.2206793019, 0.2214299118, 0.2221805217, 0.2225558266, 0.2236817414, 0.2251829612, 0.225933571, 0.226308876, 0.2278100957, 0.2281854006, 0.2285607056, 0.2293113154, 0.2311878401, 0.2323137549, 0.2326890599, 0.2330643648, 0.2334396697, 0.2345655845, 0.2364421092, 0.2371927191, 0.237568024, 0.237943329, 0.2394445487, 0.2398198536, 0.2405704635, 0.2420716832, 0.243197598, 0.243572903, 0.2443235129, 0.2450741227, 0.2454494277, 0.2458247326, 0.2462000375, 0.2465753425, 0.2469506474, 0.2473259523, 0.2477012573, 0.2480765622, 0.2488271721, 0.2495777819, 0.2499530869, 0.2510790017, 0.2525802214, 0.2533308313, 0.2537061362, 0.255207356, 0.2555826609, 0.2559579658, 0.2567085757, 0.2585851004, 0.2597110152, 0.2600863201, 0.2604616251, 0.26083693, 0.2619628448, 0.2638393695, 0.2645899794, 0.2649652843, 0.2653405892, 0.266841809, 0.2672171139, 0.2679677238, 0.2694689435, 0.2705948583, 0.2709701633, 0.2717207731, 0.272471383, 0.2728466879, 0.2732219929, 0.2735972978, 0.2739726027, 0.2743479077, 0.2747232126, 0.2750985175, 0.2754738225, 0.2762244324, 0.2769750422, 0.2773503472, 0.278476262, 0.2799774817, 0.2807280916, 0.2811033965, 0.2826046163, 0.2829799212, 0.2833552261, 0.284105836, 0.2859823607, 0.2871082755, 0.2874835804, 0.2878588853, 0.2882341903, 0.2893601051, 0.2912366298, 0.2919872396, 0.2923625446, 0.2927378495, 0.2942390692, 0.2946143742, 0.2953649841, 0.2968662038, 0.2979921186, 0.2983674235, 0.2991180334, 0.2998686433, 0.3002439482, 0.3006192531, 0.3009945581, 0.301369863, 0.3017451679, 0.3021204729, 0.3024957778, 0.3028710828, 0.3036216926, 0.3043723025, 0.3047476074, 0.3058735222, 0.307374742, 0.3081253518, 0.3085006568, 0.3100018765, 0.3103771815, 0.3107524864, 0.3115030963, 0.3133796209, 0.3145055357, 0.3148808407, 0.3152561456, 0.3156314506, 0.3167573654, 0.31863389, 0.3193844999, 0.3197598048, 0.3201351098, 0.3216363295, 0.3220116345, 0.3227622443, 0.3242634641, 0.3253893789, 0.3257646838, 0.3265152937, 0.3272659035, 0.3276412085, 0.3280165134, 0.3283918184, 0.3287671233, 0.3291424282, 0.3295177332, 0.3298930381, 0.330268343, 0.3310189529, 0.3317695628, 0.3321448677, 0.3332707825, 0.3347720023, 0.3355226121, 0.3358979171, 0.3373991368, 0.3377744417, 0.3381497467, 0.3389003565, 0.3407768812, 0.341902796, 0.342278101, 0.3426534059, 0.3430287108, 0.3441546256, 0.3460311503, 0.3467817602, 0.3471570651, 0.3475323701, 0.3490335898, 0.3494088947, 0.3501595046, 0.3516607243, 0.3527866391, 0.3531619441, 0.353912554, 0.3546631638, 0.3550384688, 0.3554137737, 0.3557890786, 0.3561643836, 0.3565396885, 0.3569149934, 0.3572902984, 0.3576656033, 0.3584162132, 0.359166823, 0.359542128, 0.3606680428, 0.3621692625, 0.3629198724, 0.3632951773, 0.3647963971, 0.365171702, 0.3655470069, 0.3662976168, 0.3681741415, 0.3693000563, 0.3696753612, 0.3700506662, 0.3704259711, 0.3715518859, 0.3734284106, 0.3741790205, 0.3745543254, 0.3749296303, 0.3764308501, 0.376806155, 0.3775567649, 0.3790579846, 0.3801838994, 0.3805592044, 0.3813098142, 0.3820604241, 0.382435729, 0.382811034, 0.3831863389, 0.3835616438, 0.3839369488, 0.3843122537, 0.3846875586, 0.3850628636, 0.3858134734, 0.3865640833, 0.3869393883, 0.3880653031, 0.3895665228, 0.3903171327, 0.3906924376, 0.3921936573, 0.3925689623, 0.3929442672, 0.3936948771, 0.3955714018, 0.3966973166, 0.3970726215, 0.3974479264, 0.3978232314, 0.3989491462, 0.4008256709, 0.4015762807, 0.4019515857, 0.4023268906, 0.4038281103, 0.4042034153, 0.4049540251, 0.4064552449, 0.4075811597, 0.4079564646, 0.4087070745, 0.4094576844, 0.4098329893, 0.4102082942, 0.4105835992, 0.4109589041, 0.411334209, 0.411709514, 0.4120848189, 0.4124601239, 0.4132107337, 0.4139613436, 0.4143366485, 0.4154625633, 0.4169637831, 0.4177143929, 0.4180896979, 0.4195909176, 0.4199662226, 0.4203415275, 0.4210921374, 0.422968662, 0.4240945768, 0.4244698818, 0.4248451867, 0.4252204916, 0.4263464065, 0.4282229311, 0.428973541, 0.4293488459, 0.4297241509, 0.4312253706, 0.4316006755, 0.4323512854, 0.4338525052, 0.43497842, 0.4353537249, 0.4361043348, 0.4368549446, 0.4372302496, 0.4376055545, 0.4379808594, 0.4383561644, 0.4387314693, 0.4391067743, 0.4394820792, 0.4398573841, 0.440607994, 0.4413586039, 0.4417339088, 0.4428598236, 0.4443610433, 0.4451116532, 0.4454869582, 0.4469881779, 0.4473634828, 0.4477387878, 0.4484893976, 0.4503659223, 0.4514918371, 0.4518671421, 0.452242447, 0.4526177519, 0.4537436667, 0.4556201914, 0.4563708013, 0.4567461062, 0.4571214111, 0.4586226309, 0.4589979358, 0.4597485457, 0.4612497654, 0.4623756802, 0.4627509852, 0.463501595, 0.4642522049, 0.4646275099, 0.4650028148, 0.4653781197, 0.4657534247, 0.4661287296, 0.4665040345, 0.4668793395, 0.4672546444, 0.4680052543, 0.4687558641, 0.4691311691, 0.4702570839, 0.4717583036, 0.4725089135, 0.4728842184, 0.4743854382, 0.4747607431, 0.475136048, 0.4758866579, 0.4777631826, 0.4788890974, 0.4792644023, 0.4796397073, 0.4800150122, 0.481140927, 0.4830174517, 0.4837680616, 0.4841433665, 0.4845186714, 0.4860198912, 0.4863951961, 0.487145806, 0.4886470257, 0.4897729405, 0.4901482454, 0.4908988553, 0.4916494652, 0.4920247701, 0.4924000751, 0.49277538, 0.4931506849, 0.4935259899, 0.4939012948, 0.4942765997, 0.4946519047, 0.4954025145, 0.4961531244, 0.4965284293, 0.4976543442, 0.4991555639, 0.4999061738, 0.5002814787, 0.5017826984, 0.5021580034, 0.5025333083, 0.5032839182, 0.5051604429, 0.5062863577, 0.5066616626, 0.5070369675, 0.5074122725, 0.5085381873, 0.510414712, 0.5111653218, 0.5115406268, 0.5119159317, 0.5134171514, 0.5137924564, 0.5145430662, 0.516044286, 0.5171702008, 0.5175455057, 0.5182961156, 0.5190467255, 0.5194220304, 0.5197973353, 0.5201726403, 0.5205479452, 0.5209232501, 0.5212985551, 0.52167386, 0.5220491649, 0.5227997748, 0.5235503847, 0.5239256896, 0.5250516044, 0.5265528242, 0.527303434, 0.527678739, 0.5291799587, 0.5295552637, 0.5299305686, 0.5306811785, 0.5325577031, 0.5336836179, 0.5340589229, 0.5344342278, 0.5348095327, 0.5359354476, 0.5378119722, 0.5385625821, 0.538937887, 0.539313192, 0.5408144117, 0.5411897166, 0.5419403265, 0.5434415463, 0.5445674611, 0.544942766, 0.5456933759, 0.5464439857, 0.5468192907, 0.5471945956, 0.5475699005, 0.5479452055, 0.5483205104, 0.5486958154, 0.5490711203, 0.5494464252, 0.5501970351, 0.550947645, 0.5513229499, 0.5524488647, 0.5539500844, 0.5547006943, 0.5550759992, 0.556577219, 0.5569525239, 0.5573278289, 0.5580784387, 0.5599549634, 0.5610808782, 0.5614561831, 0.5618314881, 0.562206793, 0.5633327078, 0.5652092325, 0.5659598424, 0.5663351473, 0.5667104522, 0.568211672, 0.5685869769, 0.5693375868, 0.5708388065, 0.5719647213, 0.5723400263, 0.5730906361, 0.573841246, 0.5742165509, 0.5745918559, 0.5749671608, 0.5753424658, 0.5757177707, 0.5760930756, 0.5764683806, 0.5768436855, 0.5775942954, 0.5783449052, 0.5787202102, 0.579846125, 0.5813473447, 0.5820979546, 0.5824732595, 0.5839744793, 0.5843497842, 0.5847250891, 0.585475699, 0.5873522237, 0.5884781385, 0.5888534434, 0.5892287484, 0.5896040533, 0.5907299681, 0.5926064928, 0.5933571026, 0.5937324076, 0.5941077125, 0.5956089323, 0.5959842372, 0.5967348471, 0.5982360668, 0.5993619816, 0.5997372865, 0.6004878964, 0.6012385063, 0.6016138112, 0.6019891162, 0.6023644211, 0.602739726, 0.603115031, 0.6034903359, 0.6038656408, 0.6042409458, 0.6049915556, 0.6057421655, 0.6061174704, 0.6072433853, 0.608744605, 0.6094952149, 0.6098705198, 0.6113717395, 0.6117470445, 0.6121223494, 0.6128729593, 0.614749484, 0.6158753988, 0.6162507037, 0.6166260086, 0.6170013136, 0.6181272284, 0.620003753, 0.6207543629, 0.6211296679, 0.6215049728, 0.6230061925, 0.6233814975, 0.6241321073, 0.6256333271, 0.6267592419, 0.6271345468, 0.6278851567, 0.6286357666, 0.6290110715, 0.6293863764, 0.6297616814, 0.6301369863, 0.6305122912, 0.6308875962, 0.6312629011, 0.631638206, 0.6323888159, 0.6331394258, 0.6335147307, 0.6346406455, 0.6361418653, 0.6368924751, 0.6372677801, 0.6387689998, 0.6391443047, 0.6395196097, 0.6402702196, 0.6421467442, 0.643272659, 0.643647964, 0.6440232689, 0.6443985738, 0.6455244886, 0.6474010133, 0.6481516232, 0.6485269281, 0.6489022331, 0.6504034528, 0.6507787577, 0.6515293676, 0.6530305874, 0.6541565022, 0.6545318071, 0.655282417, 0.6560330268, 0.6564083318, 0.6567836367, 0.6571589416, 0.6575342466, 0.6579095515, 0.6582848564, 0.6586601614, 0.6590354663, 0.6597860762, 0.6605366861, 0.660911991, 0.6620379058, 0.6635391255, 0.6642897354, 0.6646650403, 0.6661662601, 0.666541565, 0.66691687, 0.6676674798, 0.6695440045, 0.6706699193, 0.6710452242, 0.6714205292, 0.6717958341, 0.6729217489, 0.6747982736, 0.6755488835, 0.6759241884, 0.6762994933, 0.6778007131, 0.678176018, 0.6789266279, 0.6804278476, 0.6815537624, 0.6819290674, 0.6826796772, 0.6834302871, 0.683805592, 0.684180897, 0.6845562019, 0.6849315068, 0.6853068118, 0.6856821167, 0.6860574217, 0.6864327266, 0.6871833365, 0.6879339463, 0.6883092513, 0.6894351661, 0.6909363858, 0.6916869957, 0.6920623006, 0.6935635204, 0.6939388253, 0.6943141302, 0.6950647401, 0.6969412648, 0.6980671796, 0.6984424845, 0.6988177895, 0.6991930944, 0.7003190092, 0.7021955339, 0.7029461437, 0.7033214487, 0.7036967536, 0.7051979734, 0.7055732783, 0.7063238882, 0.7078251079, 0.7089510227, 0.7093263276, 0.7100769375, 0.7108275474, 0.7112028523, 0.7115781573, 0.7119534622, 0.7123287671, 0.7127040721, 0.713079377, 0.7134546819, 0.7138299869, 0.7145805967, 0.7153312066, 0.7157065115, 0.7168324263, 0.7183336461, 0.719084256, 0.7194595609, 0.7209607806, 0.7213360856, 0.7217113905, 0.7224620004, 0.7243385251, 0.7254644399, 0.7258397448, 0.7262150497, 0.7265903547, 0.7277162695, 0.7295927941, 0.730343404, 0.730718709, 0.7310940139, 0.7325952336, 0.7329705386, 0.7337211484, 0.7352223682, 0.736348283, 0.7367235879, 0.7374741978, 0.7382248077, 0.7386001126, 0.7389754175, 0.7393507225, 0.7397260274, 0.7401013323, 0.7404766373, 0.7408519422, 0.7412272471, 0.741977857, 0.7427284669, 0.7431037718, 0.7442296866, 0.7457309064, 0.7464815162, 0.7468568212, 0.7483580409, 0.7487333458, 0.7491086508, 0.7498592606, 0.7517357853, 0.7528617001, 0.7532370051, 0.75361231, 0.7539876149, 0.7551135297, 0.7569900544, 0.7577406643, 0.7581159692, 0.7584912742, 0.7599924939, 0.7603677988, 0.7611184087, 0.7626196284, 0.7637455433, 0.7641208482, 0.7648714581, 0.7656220679, 0.7659973729, 0.7663726778, 0.7667479827, 0.7671232877, 0.7674985926, 0.7678738975, 0.7682492025, 0.7686245074, 0.7693751173, 0.7701257272, 0.7705010321, 0.7716269469, 0.7731281666, 0.7738787765, 0.7742540814, 0.7757553012, 0.7761306061, 0.7765059111, 0.7772565209, 0.7791330456, 0.7802589604, 0.7806342653, 0.7810095703, 0.7813848752, 0.78251079, 0.7843873147, 0.7851379246, 0.7855132295, 0.7858885344, 0.7873897542, 0.7877650591, 0.788515669, 0.7900168887, 0.7911428035, 0.7915181085, 0.7922687183, 0.7930193282, 0.7933946331, 0.7937699381, 0.794145243, 0.7945205479, 0.7948958529, 0.7952711578, 0.7956464628, 0.7960217677, 0.7967723776, 0.7975229874, 0.7978982924, 0.7990242072, 0.8005254269, 0.8012760368, 0.8016513417, 0.8031525615, 0.8035278664, 0.8039031713, 0.8046537812, 0.8065303059, 0.8076562207, 0.8080315256, 0.8084068306, 0.8087821355, 0.8099080503, 0.811784575, 0.8125351848, 0.8129104898, 0.8132857947, 0.8147870144, 0.8151623194, 0.8159129293, 0.817414149, 0.8185400638, 0.8189153687, 0.8196659786, 0.8204165885, 0.8207918934, 0.8211671983, 0.8215425033, 0.8219178082, 0.8222931132, 0.8226684181, 0.823043723, 0.823419028, 0.8241696378, 0.8249202477, 0.8252955526, 0.8264214674, 0.8279226872, 0.8286732971, 0.829048602, 0.8305498217, 0.8309251267, 0.8313004316, 0.8320510415, 0.8339275661, 0.835053481, 0.8354287859, 0.8358040908, 0.8361793958, 0.8373053106, 0.8391818352, 0.8399324451, 0.84030775, 0.840683055, 0.8421842747, 0.8425595797, 0.8433101895, 0.8448114093, 0.8459373241, 0.846312629, 0.8470632389, 0.8478138488, 0.8481891537, 0.8485644586, 0.8489397636, 0.8493150685, 0.8496903734, 0.8500656784, 0.8504409833, 0.8508162882, 0.8515668981, 0.852317508, 0.8526928129, 0.8538187277, 0.8553199475, 0.8560705573, 0.8564458623, 0.857947082, 0.8583223869, 0.8586976919, 0.8594483017, 0.8613248264, 0.8624507412, 0.8628260462, 0.8632013511, 0.863576656, 0.8647025708, 0.8665790955, 0.8673297054, 0.8677050103, 0.8680803153, 0.869581535, 0.8699568399, 0.8707074498, 0.8722086695, 0.8733345844, 0.8737098893, 0.8744604992, 0.875211109, 0.875586414, 0.8759617189, 0.8763370238, 0.8767123288, 0.8770876337, 0.8774629386, 0.8778382436, 0.8782135485, 0.8789641584, 0.8797147682, 0.8800900732, 0.881215988, 0.8827172077, 0.8834678176, 0.8838431225, 0.8853443423, 0.8857196472, 0.8860949521, 0.886845562, 0.8887220867, 0.8898480015, 0.8902233064, 0.8905986114, 0.8909739163, 0.8920998311, 0.8939763558, 0.8947269657, 0.8951022706, 0.8954775755, 0.8969787953, 0.8973541002, 0.8981047101, 0.8996059298, 0.9007318446, 0.9011071496, 0.9018577594, 0.9026083693, 0.9029836742, 0.9033589792, 0.9037342841, 0.904109589, 0.904484894, 0.9048601989, 0.9052355038, 0.9056108088, 0.9063614187, 0.9071120285, 0.9074873335, 0.9086132483, 0.910114468, 0.9108650779, 0.9112403828, 0.9127416026, 0.9131169075, 0.9134922124, 0.9142428223, 0.916119347, 0.9172452618, 0.9176205667, 0.9179958716, 0.9183711766, 0.9194970914, 0.9213736161, 0.9221242259, 0.9224995309, 0.9228748358, 0.9243760555, 0.9247513605, 0.9255019704, 0.9270031901, 0.9281291049, 0.9285044098, 0.9292550197, 0.9300056296, 0.9303809345, 0.9307562394, 0.9311315444, 0.9315068493, 0.9318821543, 0.9322574592, 0.9326327641, 0.9330080691, 0.9337586789, 0.9345092888, 0.9348845937, 0.9360105085, 0.9375117283, 0.9382623382, 0.9386376431, 0.9401388628, 0.9405141678, 0.9408894727, 0.9416400826, 0.9435166072, 0.944642522, 0.945017827, 0.9453931319, 0.9457684369, 0.9468943517, 0.9487708763, 0.9495214862, 0.9498967911, 0.9502720961, 0.9517733158, 0.9521486208, 0.9528992306, 0.9544004504, 0.9555263652, 0.9559016701, 0.95665228, 0.9574028898, 0.9577781948, 0.9581534997, 0.9585288047, 0.9589041096, 0.9592794145, 0.9596547195, 0.9600300244, 0.9604053293, 0.9611559392, 0.9619065491, 0.962281854, 0.9634077688, 0.9649089886, 0.9656595984, 0.9660349034, 0.9675361231, 0.967911428, 0.968286733, 0.9690373428, 0.9709138675, 0.9720397823, 0.9724150873, 0.9727903922, 0.9731656971, 0.9742916119, 0.9761681366, 0.9769187465, 0.9772940514, 0.9776693564, 0.9791705761, 0.979545881, 0.9802964909, 0.9817977106, 0.9829236254, 0.9832989304, 0.9840495403, 0.9848001501, 0.9851754551, 0.98555076, 0.9859260649, 0.9863013699, 0.9866766748, 0.9870519797, 0.9874272847, 0.9878025896, 0.9885531995, 0.9893038093, 0.9896791143, 0.9908050291, 0.9923062488, 0.9930568587, 0.9934321636, 0.9949333834, 0.9953086883, 0.9956839932, 0.9964346031, 0.9983111278, 0.9994370426, 0.9998123475] averages_even={0.0: [0.0], 0.6515293676: [0.7534246575342, 0.2465753424658], 0.4901482454: [0.0547945205479, 0.9452054794521], 0.4008256709: [0.6164383561644, 0.3835616438356], 0.487145806: [0.7534246575342, 0.2465753424658], 0.2364421092: [0.6164383561644, 0.3835616438356], 0.7584912742: [0.3013698630137, 0.6986301369863], 0.0851942203: [0.5205479452055, 0.4794520547945], 0.0243948208: [0.0547945205479, 0.9452054794521], 0.2747232126: [0.2602739726027, 0.7397260273973], 0.4961531244: [0.5205479452055, 0.4794520547945], 0.8215425033: [0.5616438356164, 0.4383561643836], 0.1279789829: [0.1506849315068, 0.8493150684932], 0.5250516044: [0.0958904109589, 0.9041095890411], 0.2323137549: [0.2876712328767, 0.7123287671233], 0.5408144117: [0.6027397260274, 0.3972602739726], 0.4725089135: [0.7808219178082, 0.2191780821918], 0.556577219: [0.1369863013699, 0.8630136986301], 0.8496903734: [0.1643835616438, 0.8356164383562], 0.4567461062: [0.1506849315068, 0.8493150684932], 0.5723400263: [0.0547945205479, 0.9452054794521], 0.8196659786: [0.5753424657534, 0.4246575342466], 0.2927378495: [0.3013698630137, 0.6986301369863], 0.0731844624: [0.1506849315068, 0.8493150684932], 0.7686245074: [0.3287671232877, 0.6712328767123], 0.3006192531: [0.027397260274, 0.972602739726], 0.6038656408: [0.5479452054795, 0.4520547945205], 0.1542503284: [0.6164383561644, 0.3835616438356], 0.7051979734: [0.6027397260274, 0.3972602739726], 0.7915181085: [0.0547945205479, 0.9452054794521], 0.8425595797: [0.0821917808219, 0.9178082191781], 0.0202664665: [0.6027397260274, 0.3972602739726], 0.3565396885: [0.1643835616438, 0.8356164383562], 0.3321448677: [0.5068493150685, 0.4931506849315], 0.9127416026: [0.1369863013699, 0.8630136986301], 0.4252204916: [0.7671232876712, 0.2328767123288], 0.6935635204: [0.1369863013699, 0.8630136986301], 0.9255019704: [0.7534246575342, 0.2465753424658], 0.9528992306: [0.7534246575342, 0.2465753424658], 0.7404766373: [0.2602739726027, 0.7397260273973], 0.9930568587: [0.7808219178082, 0.2191780821918], 0.1884030775: [0.6849315068493, 0.3150684931507], 0.0942015388: [0.041095890411, 0.958904109589], 0.3846875586: [0.5479452054795, 0.4520547945205], 0.2983674235: [0.0547945205479, 0.9452054794521], 0.1962844811: [0.0958904109589, 0.9041095890411], 0.3347720023: [0.6575342465753, 0.3424657534247], 0.9285044098: [0.0547945205479, 0.9452054794521], 0.7483580409: [0.1369863013699, 0.8630136986301], 0.6019891162: [0.027397260274, 0.972602739726], 0.7367235879: [0.0547945205479, 0.9452054794521], 0.2120472884: [0.6027397260274, 0.3972602739726], 0.9405141678: [0.0684931506849, 0.9315068493151], 0.0266466504: [0.027397260274, 0.972602739726], 0.2191780822: [0.0], 0.109964346: [0.1643835616438, 0.8356164383562], 0.7100769375: [0.5753424657534, 0.4246575342466], 0.5070369675: [0.6301369863014, 0.3698630136986], 0.9086132483: [0.0958904109589, 0.9041095890411], 0.2600863201: [0.013698630137, 0.986301369863], 0.5201726403: [0.5616438356164, 0.4383561643836], 0.881215988: [0.0958904109589, 0.9041095890411], 0.1339838619: [0.0547945205479, 0.9452054794521], 0.7577406643: [0.8082191780822, 0.1917808219178], 0.3310189529: [0.5342465753425, 0.4657534246575], 0.6335147307: [0.5068493150685, 0.4931506849315], 0.2462000375: [0.5616438356164, 0.4383561643836], 0.1231000188: [0.013698630137, 0.986301369863], 0.8722086695: [0.5890410958904, 0.4109589041096], 0.5749671608: [0.5616438356164, 0.4383561643836], 0.3167573654: [0.1095890410959, 0.8904109589041], 0.6845562019: [0.5616438356164, 0.4383561643836], 0.6278851567: [0.5753424657534, 0.4246575342466], 0.6530305874: [0.5890410958904, 0.4109589041096], 0.9649089886: [0.3424657534247, 0.6575342465753], 0.643647964: [0.013698630137, 0.986301369863], 0.3283918184: [0.5616438356164, 0.4383561643836], 0.2559579658: [0.1780821917808, 0.8219178082192], 0.4691311691: [0.5068493150685, 0.4931506849315], 0.3441546256: [0.1095890410959, 0.8904109589041], 0.6909363858: [0.3424657534247, 0.6575342465753], 0.5171702008: [0.3150684931507, 0.6849315068493], 0.6361418653: [0.3424657534247, 0.6575342465753], 0.98555076: [0.027397260274, 0.972602739726], 0.9401388628: [0.1369863013699, 0.8630136986301], 0.0277725652: [0.1643835616438, 0.8356164383562], 0.7487333458: [0.0684931506849, 0.9315068493151], 0.4383561644: [0.0], 0.4646275099: [0.7945205479452, 0.2054794520548], 0.1917808219: [0.0], 0.7802589604: [0.2876712328767, 0.7123287671233], 0.7960217677: [0.3287671232877, 0.6712328767123], 0.2251829612: [0.6575342465753, 0.3424657534247], 0.4473634828: [0.0684931506849, 0.9315068493151], 0.4124601239: [0.6712328767123, 0.3287671232877], 0.6207543629: [0.8082191780822, 0.1917808219178], 0.4203415275: [0.1780821917808, 0.8219178082192], 0.1050853819: [0.5890410958904, 0.4109589041096], 0.0262713455: [0.7945205479452, 0.2054794520548], 0.2597110152: [0.2876712328767, 0.7123287671233], 0.6676674798: [0.6438356164384, 0.3561643835616], 0.2180521674: [0.7945205479452, 0.2054794520548], 0.4064552449: [0.5890410958904, 0.4109589041096], 0.2743479077: [0.1643835616438, 0.8356164383562], 0.9544004504: [0.5890410958904, 0.4109589041096], 0.1129667855: [0.5068493150685, 0.4931506849315], 0.579846125: [0.0958904109589, 0.9041095890411], 0.9611559392: [0.5342465753425, 0.4657534246575], 0.4597485457: [0.7534246575342, 0.2465753424658], 0.9581534997: [0.027397260274, 0.972602739726], 0.9326327641: [0.5479452054795, 0.4520547945205], 0.4623756802: [0.6849315068493, 0.3150684931507], 0.4143366485: [0.5068493150685, 0.4931506849315], 0.1399887409: [0.5205479452055, 0.4794520547945], 0.7265903547: [0.7671232876712, 0.2328767123288], 0.2878588853: [0.6301369863014, 0.3698630136986], 0.719084256: [0.7808219178082, 0.2191780821918], 0.5941077125: [0.3013698630137, 0.6986301369863], 0.4098329893: [0.7945205479452, 0.2054794520548], 0.3036216926: [0.5342465753425, 0.4657534246575], 0.1557515481: [0.3013698630137, 0.6986301369863], 0.3115030963: [0.6438356164384, 0.3561643835616], 0.0285231751: [0.5479452054795, 0.4520547945205], 0.3193844999: [0.1917808219178, 0.8082191780822], 0.0409082379: [0.013698630137, 0.986301369863], 0.3272659035: [0.8767123287671, 0.1232876712329], 0.0818164759: [0.5616438356164, 0.4383561643836], 0.3561643836: [0.0], 0.5344342278: [0.6301369863014, 0.3698630136986], 0.1715143554: [0.2739726027397, 0.7260273972603], 0.4908988553: [0.5753424657534, 0.4246575342466], 0.6991930944: [0.7671232876712, 0.2328767123288], 0.6582848564: [0.2602739726027, 0.7397260273973], 0.1062112967: [0.6849315068493, 0.3150684931507], 0.1463689248: [0.1780821917808, 0.8219178082192], 0.730718709: [0.1506849315068, 0.8493150684932], 0.7464815162: [0.7808219178082, 0.2191780821918], 0.2979921186: [0.6849315068493, 0.3150684931507], 0.8504409833: [0.5479452054795, 0.4520547945205], 0.8151623194: [0.0821917808219, 0.9178082191781], 0.1977857009: [0.6575342465753, 0.3424657534247], 0.0607993995: [0.6575342465753, 0.3424657534247], 0.2807280916: [0.7808219178082, 0.2191780821918], 0.0033777444: [0.5068493150685, 0.4931506849315], 0.0514167761: [0.6849315068493, 0.3150684931507], 0.2056671045: [0.6301369863014, 0.3698630136986], 0.1028335523: [0.0821917808219, 0.9178082191781], 0.7716269469: [0.0958904109589, 0.9041095890411], 0.8733345844: [0.3150684931507, 0.6849315068493], 0.7641208482: [0.0547945205479, 0.9452054794521], 0.5787202102: [0.5068493150685, 0.4931506849315], 0.8673297054: [0.8082191780822, 0.1917808219178], 0.5764683806: [0.5479452054795, 0.4520547945205], 0.440607994: [0.5342465753425, 0.4657534246575], 0.3085006568: [0.2739726027397, 0.7260273972603], 0.3745543254: [0.1506849315068, 0.8493150684932], 0.9108650779: [0.7808219178082, 0.2191780821918], 0.127603678: [0.1917808219178, 0.8082191780822], 0.8947269657: [0.8082191780822, 0.1917808219178], 0.9303809345: [0.7945205479452, 0.2054794520548], 0.1354850816: [0.8767123287671, 0.1232876712329], 0.5550759992: [0.2739726027397, 0.7260273972603], 0.2398198536: [0.0821917808219, 0.9178082191781], 0.7145805967: [0.5342465753425, 0.4657534246575], 0.5708388065: [0.5890410958904, 0.4109589041096], 0.8969787953: [0.6027397260274, 0.3972602739726], 0.0619253143: [0.2739726027397, 0.7260273972603], 0.2477012573: [0.5479452054795, 0.4520547945205], 0.7648714581: [0.5753424657534, 0.4246575342466], 0.255207356: [0.1369863013699, 0.8630136986301], 0.6181272284: [0.1095890410959, 0.8904109589041], 0.8954775755: [0.3013698630137, 0.6986301369863], 0.3156314506: [0.7671232876712, 0.2328767123288], 0.910114468: [0.3424657534247, 0.6575342465753], 0.7063238882: [0.7534246575342, 0.2465753424658], 0.7003190092: [0.1095890410959, 0.8904109589041], 0.7382248077: [0.8767123287671, 0.1232876712329], 0.2281854006: [0.0684931506849, 0.9315068493151], 0.162131732: [0.5753424657534, 0.4246575342466], 0.0487896416: [0.7534246575342, 0.2465753424658], 0.4240945768: [0.2876712328767, 0.7123287671233], 0.1775192344: [0.2876712328767, 0.7123287671233], 0.6564083318: [0.7945205479452, 0.2054794520548], 0.0003753049: [0.1643835616438, 0.8356164383562], 0.3629198724: [0.7808219178082, 0.2191780821918], 0.1366109964: [0.5616438356164, 0.4383561643836], 0.7389754175: [0.027397260274, 0.972602739726], 0.9634077688: [0.0958904109589, 0.9041095890411], 0.3865640833: [0.5205479452055, 0.4794520547945], 0.6642897354: [0.7808219178082, 0.2191780821918], 0.1002064177: [0.1917808219178, 0.8082191780822], 0.0502908613: [0.5890410958904, 0.4109589041096], 0.4668793395: [0.5479452054795, 0.4520547945205], 0.1673860011: [0.5205479452055, 0.4794520547945], 0.4154625633: [0.0958904109589, 0.9041095890411], 0.9224995309: [0.1506849315068, 0.8493150684932], 0.4589979358: [0.0821917808219, 0.9178082191781], 0.8493150685: [0.0], 0.8241696378: [0.5342465753425, 0.4657534246575], 0.4312253706: [0.6027397260274, 0.3972602739726], 0.7990242072: [0.0958904109589, 0.9041095890411], 0.5479452055: [0.0], 0.2195533871: [0.1643835616438, 0.8356164383562], 0.4391067743: [0.2602739726027, 0.7397260273973], 0.6290110715: [0.7945205479452, 0.2054794520548], 0.4469881779: [0.1369863013699, 0.8630136986301], 0.6215049728: [0.3013698630137, 0.6986301369863], 0.4747607431: [0.0684931506849, 0.9315068493151], 0.9071120285: [0.5205479452055, 0.4794520547945], 0.3426534059: [0.6301369863014, 0.3698630136986], 0.5212985551: [0.2602739726027, 0.7397260273973], 0.4627509852: [0.0547945205479, 0.9452054794521], 0.133608557: [0.6849315068493, 0.3150684931507], 0.0022518296: [0.5342465753425, 0.4657534246575], 0.2750985175: [0.5479452054795, 0.4520547945205], 0.5501970351: [0.5342465753425, 0.4657534246575], 0.8774629386: [0.2602739726027, 0.7397260273973], 0.1414899606: [0.0958904109589, 0.9041095890411], 0.5685869769: [0.0821917808219, 0.9178082191781], 0.3287671233: [0.0], 0.9375117283: [0.3424657534247, 0.6575342465753], 0.5843497842: [0.0684931506849, 0.9315068493151], 0.9300056296: [0.8767123287671, 0.1232876712329], 0.9720397823: [0.2876712328767, 0.7123287671233], 0.3242634641: [0.5890410958904, 0.4109589041096], 0.1572527679: [0.6027397260274, 0.3972602739726], 0.6421467442: [0.041095890411, 0.958904109589], 0.7089510227: [0.3150684931507, 0.6849315068493], 0.8586976919: [0.1780821917808, 0.8219178082192], 0.6579095515: [0.1643835616438, 0.8356164383562], 0.1651341715: [0.2602739726027, 0.7397260273973], 0.6762994933: [0.3013698630137, 0.6986301369863], 0.6894351661: [0.0958904109589, 0.9041095890411], 0.3257646838: [0.0547945205479, 0.9452054794521], 0.5197973353: [0.027397260274, 0.972602739726], 0.7183336461: [0.3424657534247, 0.6575342465753], 0.7209607806: [0.1369863013699, 0.8630136986301], 0.6815537624: [0.3150684931507, 0.6849315068493], 0.3749296303: [0.3013698630137, 0.6986301369863], 0.3317695628: [0.5205479452055, 0.4794520547945], 0.0957027585: [0.013698630137, 0.986301369863], 0.0915744042: [0.1780821917808, 0.8219178082192], 0.3906924376: [0.2739726027397, 0.7260273972603], 0.4323512854: [0.7534246575342, 0.2465753424658], 0.3002439482: [0.7945205479452, 0.2054794520548], 0.0258960405: [0.8767123287671, 0.1232876712329], 0.0540439107: [0.027397260274, 0.972602739726], 0.1035841621: [0.7534246575342, 0.2465753424658], 0.2071683243: [0.1095890410959, 0.8904109589041], 0.7948958529: [0.1643835616438, 0.8356164383562], 0.5209232501: [0.1643835616438, 0.8356164383562], 0.7457309064: [0.3424657534247, 0.6575342465753], 0.0142615875: [0.7671232876712, 0.2328767123288], 0.3467817602: [0.1917808219178, 0.8082191780822], 0.9487708763: [0.6164383561644, 0.3835616438356], 0.6162507037: [0.013698630137, 0.986301369863], 0.9048601989: [0.2602739726027, 0.7397260273973], 0.376806155: [0.0821917808219, 0.9178082191781], 0.5524488647: [0.0958904109589, 0.9041095890411], 0.1107149559: [0.5479452054795, 0.4520547945205], 0.2334396697: [0.7671232876712, 0.2328767123288], 0.1167198349: [0.2739726027397, 0.7260273972603], 0.2739726027: [0.0], 0.1369863014: [0.0], 0.8391818352: [0.6164383561644, 0.3835616438356], 0.5610808782: [0.2876712328767, 0.7123287671233], 0.3820604241: [0.8767123287671, 0.1232876712329], 0.5768436855: [0.3287671232877, 0.6712328767123], 0.5926064928: [0.6164383561644, 0.3835616438356], 0.8707074498: [0.7534246575342, 0.2465753424658], 0.5813473447: [0.3424657534247, 0.6575342465753], 0.9435166072: [0.041095890411, 0.958904109589], 0.904109589: [0.0], 0.6241321073: [0.7534246575342, 0.2465753424658], 0.6305122912: [0.1643835616438, 0.8356164383562], 0.31863389: [0.6164383561644, 0.3835616438356], 0.6372677801: [0.2739726027397, 0.7260273972603], 0.1632576468: [0.7945205479452, 0.2054794520548], 0.3265152937: [0.5753424657534, 0.4246575342466], 0.8159129293: [0.7534246575342, 0.2465753424658], 0.9112403828: [0.2739726027397, 0.7260273972603], 0.8827172077: [0.3424657534247, 0.6575342465753], 0.7663726778: [0.027397260274, 0.972602739726], 0.1711390505: [0.7808219178082, 0.2191780821918], 0.9832989304: [0.0547945205479, 0.9452054794521], 0.3501595046: [0.7534246575342, 0.2465753424658], 0.3925689623: [0.0684931506849, 0.9315068493151], 0.2604616251: [0.6301369863014, 0.3698630136986], 0.7978982924: [0.5068493150685, 0.4931506849315], 0.5074122725: [0.7671232876712, 0.2328767123288], 0.7581159692: [0.1506849315068, 0.8493150684932], 0.7930193282: [0.8767123287671, 0.1232876712329], 0.8632013511: [0.6301369863014, 0.3698630136986], 0.8249202477: [0.5205479452055, 0.4794520547945], 0.4102082942: [0.027397260274, 0.972602739726], 0.7765059111: [0.1780821917808, 0.8219178082192], 0.4665040345: [0.2602739726027, 0.7397260273973], 0.4939012948: [0.2602739726027, 0.7397260273973], 0.538937887: [0.1506849315068, 0.8493150684932], 0.9791705761: [0.6027397260274, 0.3972602739726], 0.3700506662: [0.6301369863014, 0.3698630136986], 0.2052917996: [0.013698630137, 0.986301369863], 0.5445674611: [0.3150684931507, 0.6849315068493], 0.1065866016: [0.0547945205479, 0.9452054794521], 0.5434415463: [0.5890410958904, 0.4109589041096], 0.2735972978: [0.5616438356164, 0.4383561643836], 0.0855695252: [0.5068493150685, 0.4931506849315], 0.8973541002: [0.0821917808219, 0.9178082191781], 0.6597860762: [0.5342465753425, 0.4657534246575], 0.0690561081: [0.7671232876712, 0.2328767123288], 0.527303434: [0.7808219178082, 0.2191780821918], 0.944642522: [0.2876712328767, 0.7123287671233], 0.5299305686: [0.1780821917808, 0.8219178082192], 0.7611184087: [0.7534246575342, 0.2465753424658], 0.1429911803: [0.6575342465753, 0.3424657534247], 0.9619065491: [0.5205479452055, 0.4794520547945], 0.4946519047: [0.3287671232877, 0.6712328767123], 0.3017451679: [0.1643835616438, 0.8356164383562], 0.150872584: [0.6301369863014, 0.3698630136986], 0.568211672: [0.6027397260274, 0.3972602739726], 0.2769750422: [0.5205479452055, 0.4794520547945], 0.0881966598: [0.6575342465753, 0.3424657534247], 0.6323888159: [0.5342465753425, 0.4657534246575], 0.191405517: [0.5616438356164, 0.4383561643836], 0.3253893789: [0.6849315068493, 0.3150684931507], 0.8481891537: [0.7945205479452, 0.2054794520548], 0.0833176956: [0.5479452054795, 0.4520547945205], 0.2919872396: [0.1917808219178, 0.8082191780822], 0.4841433665: [0.1506849315068, 0.8493150684932], 0.5839744793: [0.1369863013699, 0.8630136986301], 0.0007506099: [0.2602739726027, 0.7397260273973], 0.3621692625: [0.6575342465753, 0.3424657534247], 0.5884781385: [0.2876712328767, 0.7123287671233], 0.7401013323: [0.1643835616438, 0.8356164383562], 0.1850253331: [0.0821917808219, 0.9178082191781], 0.8613248264: [0.041095890411, 0.958904109589], 0.1929067367: [0.5479452054795, 0.4520547945205], 0.0964533684: [0.7671232876712, 0.2328767123288], 0.3936948771: [0.6438356164384, 0.3561643835616], 0.8564458623: [0.2739726027397, 0.7260273972603], 0.2007881404: [0.0684931506849, 0.9315068493151], 0.3024957778: [0.5479452054795, 0.4520547945205], 0.4094576844: [0.8767123287671, 0.1232876712329], 0.8320510415: [0.6438356164384, 0.3561643835616], 0.3978232314: [0.7671232876712, 0.2328767123288], 0.4398573841: [0.6712328767123, 0.3287671232877], 0.3903171327: [0.7808219178082, 0.2191780821918], 0.9517733158: [0.6027397260274, 0.3972602739726], 0.0273972603: [0.0], 0.9348845937: [0.5068493150685, 0.4931506849315], 0.8951022706: [0.1506849315068, 0.8493150684932], 0.7637455433: [0.3150684931507, 0.6849315068493], 0.2533308313: [0.7808219178082, 0.2191780821918], 0.8853443423: [0.1369863013699, 0.8630136986301], 0.5959842372: [0.0821917808219, 0.9178082191781], 0.8031525615: [0.1369863013699, 0.8630136986301], 0.5513229499: [0.5068493150685, 0.4931506849315], 0.1384875211: [0.6712328767123, 0.3287671232877], 0.6286357666: [0.8767123287671, 0.1232876712329], 0.7671232877: [0.0], 0.0480390317: [0.0821917808219, 0.9178082191781], 0.4935259899: [0.1643835616438, 0.8356164383562], 0.1125914806: [0.5205479452055, 0.4794520547945], 0.7408519422: [0.5479452054795, 0.4520547945205], 0.9866766748: [0.1643835616438, 0.8356164383562], 0.6117470445: [0.0684931506849, 0.9315068493151], 0.3843122537: [0.2602739726027, 0.7397260273973], 0.6301369863: [0.0], 0.6391443047: [0.0684931506849, 0.9315068493151], 0.3216363295: [0.6027397260274, 0.3972602739726], 0.1647588666: [0.1643835616438, 0.8356164383562], 0.3373991368: [0.1369863013699, 0.8630136986301], 0.006004879: [0.6575342465753, 0.3424657534247], 0.9345092888: [0.5205479452055, 0.4794520547945], 0.7036967536: [0.3013698630137, 0.6986301369863], 0.3531619441: [0.0547945205479, 0.9452054794521], 0.7194595609: [0.2739726027397, 0.7260273972603], 0.9194970914: [0.1095890410959, 0.8904109589041], 0.7352223682: [0.5890410958904, 0.4109589041096], 0.9172452618: [0.2876712328767, 0.7123287671233], 0.6331394258: [0.5205479452055, 0.4794520547945], 0.0228936011: [0.5890410958904, 0.4109589041096], 0.7667479827: [0.5616438356164, 0.4383561643836], 0.9382623382: [0.7808219178082, 0.2191780821918], 0.78251079: [0.1095890410959, 0.8904109589041], 0.6920623006: [0.2739726027397, 0.7260273972603], 0.4661287296: [0.1643835616438, 0.8356164383562], 0.1989116157: [0.2739726027397, 0.7260273972603], 0.7498592606: [0.6438356164384, 0.3561643835616], 0.2679677238: [0.7534246575342, 0.2465753424658], 0.5547006943: [0.7808219178082, 0.2191780821918], 0.5471945956: [0.027397260274, 0.972602739726], 0.0536686057: [0.7945205479452, 0.2054794520548], 0.0011259148: [0.5479452054795, 0.4520547945205], 0.1073372115: [0.5753424657534, 0.4246575342466], 0.4372302496: [0.7945205479452, 0.2054794520548], 0.8132857947: [0.3013698630137, 0.6986301369863], 0.6635391255: [0.3424657534247, 0.6575342465753], 0.2225558266: [0.5068493150685, 0.4931506849315], 0.5017826984: [0.1369863013699, 0.8630136986301], 0.9033589792: [0.027397260274, 0.972602739726], 0.4105835992: [0.5616438356164, 0.4383561643836], 0.5175455057: [0.0547945205479, 0.9452054794521], 0.9559016701: [0.0547945205479, 0.9452054794521], 0.2653405892: [0.3013698630137, 0.6986301369863], 0.5306811785: [0.6438356164384, 0.3561643835616], 0.0341527491: [0.7808219178082, 0.2191780821918], 0.2732219929: [0.027397260274, 0.972602739726], 0.278476262: [0.0958904109589, 0.9041095890411], 0.2811033965: [0.2739726027397, 0.7260273972603], 0.6969412648: [0.041095890411, 0.958904109589], 0.6605366861: [0.5205479452055, 0.4794520547945], 0.4897729405: [0.3150684931507, 0.6849315068493], 0.4845186714: [0.3013698630137, 0.6986301369863], 0.2968662038: [0.5890410958904, 0.4109589041096], 0.2488271721: [0.5342465753425, 0.4657534246575], 0.1523738037: [0.1095890410959, 0.8904109589041], 0.0761869019: [0.7534246575342, 0.2465753424658], 0.6710452242: [0.013698630137, 0.986301369863], 0.9386376431: [0.2739726027397, 0.7260273972603], 0.9802964909: [0.7534246575342, 0.2465753424658], 0.6541565022: [0.3150684931507, 0.6849315068493], 0.4413586039: [0.5205479452055, 0.4794520547945], 0.8448114093: [0.5890410958904, 0.4109589041096], 0.4338525052: [0.5890410958904, 0.4109589041096], 0.3494088947: [0.0821917808219, 0.9178082191781], 0.3430287108: [0.7671232876712, 0.2328767123288], 0.0532933008: [0.8767123287671, 0.1232876712329], 0.0446612873: [0.6164383561644, 0.3835616438356], 0.0615500094: [0.7808219178082, 0.2191780821918], 0.365171702: [0.0684931506849, 0.9315068493151], 0.7329705386: [0.0821917808219, 0.9178082191781], 0.4428598236: [0.0958904109589, 0.9041095890411], 0.7539876149: [0.7671232876712, 0.2328767123288], 0.063801839: [0.0684931506849, 0.9315068493151], 0.7933946331: [0.7945205479452, 0.2054794520548], 0.3966973166: [0.2876712328767, 0.7123287671233], 0.9007318446: [0.3150684931507, 0.6849315068493], 0.8065303059: [0.041095890411, 0.958904109589], 0.6042409458: [0.3287671232877, 0.6712328767123], 0.713079377: [0.2602739726027, 0.7397260273973], 0.8834678176: [0.7808219178082, 0.2191780821918], 0.0525426909: [0.5753424657534, 0.4246575342466], 0.2101707637: [0.1506849315068, 0.8493150684932], 0.6121223494: [0.1780821917808, 0.8219178082192], 0.8538187277: [0.0958904109589, 0.9041095890411], 0.869581535: [0.6027397260274, 0.3972602739726], 0.7217113905: [0.1780821917808, 0.8219178082192], 0.110339651: [0.2602739726027, 0.7397260273973], 0.9011071496: [0.0547945205479, 0.9452054794521], 0.4571214111: [0.3013698630137, 0.6986301369863], 0.2285607056: [0.1780821917808, 0.8219178082192], 0.573841246: [0.8767123287671, 0.1232876712329], 0.4650028148: [0.027397260274, 0.972602739726], 0.1182210546: [0.1369863013699, 0.8630136986301], 0.9457684369: [0.7671232876712, 0.2328767123288], 0.4563708013: [0.8082191780822, 0.1917808219178], 0.5573278289: [0.1780821917808, 0.8219178082192], 0.5730906361: [0.5753424657534, 0.4246575342466], 0.4886470257: [0.5890410958904, 0.4109589041096], 0.2443235129: [0.5753424657534, 0.4246575342466], 0.5888534434: [0.013698630137, 0.986301369863], 0.4965284293: [0.5068493150685, 0.4931506849315], 0.3009945581: [0.5616438356164, 0.4383561643836], 0.9817977106: [0.5890410958904, 0.4109589041096], 0.0791893413: [0.0547945205479, 0.9452054794521], 0.1583786827: [0.7534246575342, 0.2465753424658], 0.8219178082: [0.0], 0.7757553012: [0.1369863013699, 0.8630136986301], 0.5115406268: [0.1506849315068, 0.8493150684932], 0.794145243: [0.5616438356164, 0.4383561643836], 0.9761681366: [0.6164383561644, 0.3835616438356], 0.6939388253: [0.0684931506849, 0.9315068493151], 0.0649277538: [0.6438356164384, 0.3561643835616], 0.788515669: [0.7534246575342, 0.2465753424658], 0.1628823419: [0.8767123287671, 0.1232876712329], 0.7254644399: [0.2876712328767, 0.7123287671233], 0.2762244324: [0.5342465753425, 0.4657534246575], 0.7412272471: [0.3287671232877, 0.6712328767123], 0.5025333083: [0.1780821917808, 0.8219178082192], 0.7569900544: [0.6164383561644, 0.3835616438356], 0.9315068493: [0.0], 0.4788890974: [0.2876712328767, 0.7123287671233], 0.3929442672: [0.1780821917808, 0.8219178082192], 0.6567836367: [0.027397260274, 0.972602739726], 0.2004128354: [0.1369863013699, 0.8630136986301], 0.4087070745: [0.5753424657534, 0.4246575342466], 0.4023268906: [0.3013698630137, 0.6986301369863], 0.7656220679: [0.8767123287671, 0.1232876712329], 0.4244698818: [0.013698630137, 0.986301369863], 0.585475699: [0.6438356164384, 0.3561643835616], 0.2161756427: [0.0547945205479, 0.9452054794521], 0.1080878214: [0.8767123287671, 0.1232876712329], 0.8778382436: [0.5479452054795, 0.4520547945205], 0.2754738225: [0.6712328767123, 0.3287671232877], 0.5051604429: [0.041095890411, 0.958904109589], 0.6883092513: [0.5068493150685, 0.4931506849315], 0.5419403265: [0.7534246575342, 0.2465753424658], 0.1302308125: [0.0821917808219, 0.9178082191781], 0.5235503847: [0.5205479452055, 0.4794520547945], 0.1471195346: [0.6438356164384, 0.3561643835616], 0.539313192: [0.3013698630137, 0.6986301369863], 0.9408894727: [0.1780821917808, 0.8219178082192], 0.0360292738: [0.1369863013699, 0.8630136986301], 0.1381122162: [0.5479452054795, 0.4520547945205], 0.95665228: [0.5753424657534, 0.4246575342466], 0.683805592: [0.7945205479452, 0.2054794520548], 0.284105836: [0.6438356164384, 0.3561643835616], 0.6988177895: [0.6301369863014, 0.3698630136986], 0.1459936198: [0.0684931506849, 0.9315068493151], 0.49277538: [0.5616438356164, 0.4383561643836], 0.7325952336: [0.6027397260274, 0.3972602739726], 0.2833552261: [0.1780821917808, 0.8219178082192], 0.2998686433: [0.8767123287671, 0.1232876712329], 0.9953086883: [0.0684931506849, 0.9315068493151], 0.6128729593: [0.6438356164384, 0.3561643835616], 0.8361793958: [0.7671232876712, 0.2328767123288], 0.2859823607: [0.041095890411, 0.958904109589], 0.6443985738: [0.7671232876712, 0.2328767123288], 0.0364045787: [0.0684931506849, 0.9315068493151], 0.6943141302: [0.1780821917808, 0.8219178082192], 0.6759241884: [0.1506849315068, 0.8493150684932], 0.8211671983: [0.027397260274, 0.972602739726], 0.6916869957: [0.7808219178082, 0.2191780821918], 0.9840495403: [0.5753424657534, 0.4246575342466], 0.9330080691: [0.3287671232877, 0.6712328767123], 0.8485644586: [0.027397260274, 0.972602739726], 0.9893038093: [0.5205479452055, 0.4794520547945], 0.3681741415: [0.041095890411, 0.958904109589], 0.5956089323: [0.6027397260274, 0.3972602739726], 0.3839369488: [0.1643835616438, 0.8356164383562], 0.7810095703: [0.6301369863014, 0.3698630136986], 0.4999061738: [0.7808219178082, 0.2191780821918], 0.7967723776: [0.5342465753425, 0.4657534246575], 0.2037905798: [0.041095890411, 0.958904109589], 0.1084631263: [0.7945205479452, 0.2054794520548], 0.075436292: [0.0821917808219, 0.9178082191781], 0.3704259711: [0.7671232876712, 0.2328767123288], 0.736348283: [0.3150684931507, 0.6849315068493], 0.875586414: [0.7945205479452, 0.2054794520548], 0.4417339088: [0.5068493150685, 0.4931506849315], 0.4443610433: [0.6575342465753, 0.3424657534247], 0.2221805217: [0.5205479452055, 0.4794520547945], 0.5002814787: [0.2739726027397, 0.7260273972603], 0.452242447: [0.6301369863014, 0.3698630136986], 0.516044286: [0.5890410958904, 0.4109589041096], 0.0334021392: [0.6575342465753, 0.3424657534247], 0.2672171139: [0.0821917808219, 0.9178082191781], 0.5475699005: [0.5616438356164, 0.4383561643836], 0.237943329: [0.3013698630137, 0.6986301369863], 0.5633327078: [0.1095890410959, 0.8904109589041], 0.4837680616: [0.8082191780822, 0.1917808219178], 0.5820979546: [0.7808219178082, 0.2191780821918], 0.0720585476: [0.6164383561644, 0.3835616438356], 0.2458247326: [0.027397260274, 0.972602739726], 0.8860949521: [0.1780821917808, 0.8219178082192], 0.9964346031: [0.6438356164384, 0.3561643835616], 0.3835616438: [0.0], 0.904484894: [0.1643835616438, 0.8356164383562], 0.081065866: [0.7945205479452, 0.2054794520548], 0.0799399512: [0.5753424657534, 0.4246575342466], 0.0206417714: [0.0821917808219, 0.9178082191781], 0.9029836742: [0.7945205479452, 0.2054794520548], 0.3276412085: [0.7945205479452, 0.2054794520548], 0.8526928129: [0.5068493150685, 0.4931506849315], 0.1677613061: [0.5068493150685, 0.4931506849315], 0.684180897: [0.027397260274, 0.972602739726], 0.6481516232: [0.8082191780822, 0.1917808219178], 0.6575342466: [0.0], 0.9690373428: [0.6438356164384, 0.3561643835616], 0.359166823: [0.5205479452055, 0.4794520547945], 0.3280165134: [0.027397260274, 0.972602739726], 0.2619628448: [0.1095890410959, 0.8904109589041], 0.1940326515: [0.5342465753425, 0.4657534246575], 0.1636329518: [0.027397260274, 0.972602739726], 0.0416588478: [0.7671232876712, 0.2328767123288], 0.7945205479: [0.0], 0.9585288047: [0.5616438356164, 0.4383561643836], 0.4038281103: [0.6027397260274, 0.3972602739726], 0.1009570276: [0.3013698630137, 0.6986301369863], 0.0427847626: [0.1095890410959, 0.8904109589041], 0.411709514: [0.2602739726027, 0.7397260273973], 0.2097954588: [0.1917808219178, 0.8082191780822], 0.7468568212: [0.2739726027397, 0.7260273972603], 0.852317508: [0.5205479452055, 0.4794520547945], 0.811784575: [0.6164383561644, 0.3835616438356], 0.1088384312: [0.027397260274, 0.972602739726], 0.2176768625: [0.8767123287671, 0.1232876712329], 0.8838431225: [0.2739726027397, 0.7260273972603], 0.7813848752: [0.7671232876712, 0.2328767123288], 0.1024582473: [0.6027397260274, 0.3972602739726], 0.1189716645: [0.1780821917808, 0.8219178082192], 0.5137924564: [0.0821917808219, 0.9178082191781], 0.0570463502: [0.5342465753425, 0.4657534246575], 0.9311315444: [0.5616438356164, 0.4383561643836], 0.8902233064: [0.013698630137, 0.986301369863], 0.9596547195: [0.2602739726027, 0.7397260273973], 0.9468943517: [0.1095890410959, 0.8904109589041], 0.4800150122: [0.7671232876712, 0.2328767123288], 0.2871082755: [0.2876712328767, 0.7123287671233], 0.9675361231: [0.1369863013699, 0.8630136986301], 0.5464439857: [0.8767123287671, 0.1232876712329], 0.8354287859: [0.013698630137, 0.986301369863], 0.603115031: [0.1643835616438, 0.8356164383562], 0.121598799: [0.041095890411, 0.958904109589], 0.0187652468: [0.3013698630137, 0.6986301369863], 0.7033214487: [0.1506849315068, 0.8493150684932], 0.1553762432: [0.1506849315068, 0.8493150684932], 0.840683055: [0.3013698630137, 0.6986301369863], 0.6346406455: [0.0958904109589, 0.9041095890411], 0.9727903922: [0.6301369863014, 0.3698630136986], 0.6504034528: [0.6027397260274, 0.3972602739726], 0.5937324076: [0.1506849315068, 0.8493150684932], 0.4586226309: [0.6027397260274, 0.3972602739726], 0.0829423907: [0.2602739726027, 0.7397260273973], 0.0180146369: [0.1917808219178, 0.8082191780822], 0.6094952149: [0.7808219178082, 0.2191780821918], 0.6819290674: [0.0547945205479, 0.9452054794521], 0.173766185: [0.1780821917808, 0.8219178082192], 0.4916494652: [0.8767123287671, 0.1232876712329], 0.3554137737: [0.027397260274, 0.972602739726], 0.359542128: [0.5068493150685, 0.4931506849315], 0.0908237943: [0.1369863013699, 0.8630136986301], 0.1816475887: [0.6164383561644, 0.3835616438356], 0.0454118972: [0.1917808219178, 0.8082191780822], 0.8339275661: [0.041095890411, 0.958904109589], 0.9772940514: [0.1506849315068, 0.8493150684932], 0.6879339463: [0.5205479452055, 0.4794520547945], 0.1895289923: [0.5753424657534, 0.4246575342466], 0.3869393883: [0.5068493150685, 0.4931506849315], 0.0240195159: [0.6849315068493, 0.3150684931507], 0.602739726: [0.0], 0.8185400638: [0.3150684931507, 0.6849315068493], 0.4361043348: [0.5753424657534, 0.4246575342466], 0.8887220867: [0.041095890411, 0.958904109589], 0.3647963971: [0.1369863013699, 0.8630136986301], 0.3662976168: [0.6438356164384, 0.3561643835616], 0.2158003378: [0.6849315068493, 0.3150684931507], 0.2709701633: [0.0547945205479, 0.9452054794521], 0.4394820792: [0.5479452054795, 0.4520547945205], 0.9322574592: [0.2602739726027, 0.7397260273973], 0.2236817414: [0.0958904109589, 0.9041095890411], 0.0559204354: [0.5479452054795, 0.4520547945205], 0.342278101: [0.013698630137, 0.986301369863], 0.2799774817: [0.6575342465753, 0.3424657534247], 0.5378119722: [0.6164383561644, 0.3835616438356], 0.1197222743: [0.6438356164384, 0.3561643835616], 0.2394445487: [0.6027397260274, 0.3972602739726], 0.7626196284: [0.5890410958904, 0.4109589041096], 0.5693375868: [0.7534246575342, 0.2465753424658], 0.8005254269: [0.3424657534247, 0.6575342465753], 0.7551135297: [0.1095890410959, 0.8904109589041], 0.1456183149: [0.1369863013699, 0.8630136986301], 0.2473259523: [0.2602739726027, 0.7397260273973], 0.2991180334: [0.5753424657534, 0.4246575342466], 0.3858134734: [0.5342465753425, 0.4657534246575], 0.6166260086: [0.6301369863014, 0.3698630136986], 0.225933571: [0.7808219178082, 0.2191780821918], 0.3148808407: [0.013698630137, 0.986301369863], 0.1598799024: [0.5890410958904, 0.4109589041096], 0.3227622443: [0.7534246575342, 0.2465753424658], 0.1613811222: [0.0547945205479, 0.9452054794521], 0.5265528242: [0.3424657534247, 0.6575342465753], 0.8759617189: [0.027397260274, 0.972602739726], 0.481140927: [0.1095890410959, 0.8904109589041], 0.8305498217: [0.1369863013699, 0.8630136986301], 0.7873897542: [0.6027397260274, 0.3972602739726], 0.7153312066: [0.5205479452055, 0.4794520547945], 0.655282417: [0.5753424657534, 0.4246575342466], 0.5824732595: [0.2739726027397, 0.7260273972603], 0.9848001501: [0.8767123287671, 0.1232876712329], 0.7532370051: [0.013698630137, 0.986301369863], 0.0825670858: [0.1643835616438, 0.8356164383562], 0.7761306061: [0.0684931506849, 0.9315068493151], 0.1786451492: [0.7671232876712, 0.2328767123288], 0.3989491462: [0.8904109589041, 0.1095890410959], 0.5111653218: [0.8082191780822, 0.1917808219178], 0.4015762807: [0.1917808219178, 0.8082191780822], 0.2694689435: [0.5890410958904, 0.4109589041096], 0.3355226121: [0.7808219178082, 0.2191780821918], 0.8084068306: [0.6301369863014, 0.3698630136986], 0.8046537812: [0.6438356164384, 0.3561643835616], 0.4702570839: [0.0958904109589, 0.9041095890411], 0.8583223869: [0.0684931506849, 0.9315068493151], 0.3381497467: [0.1780821917808, 0.8219178082192], 0.0547945205: [0.0], 0.1095890411: [0.0], 0.5468192907: [0.7945205479452, 0.2054794520548], 0.8898480015: [0.2876712328767, 0.7123287671233], 0.9923062488: [0.3424657534247, 0.6575342465753], 0.8189153687: [0.0547945205479, 0.9452054794521], 0.2585851004: [0.041095890411, 0.958904109589], 0.9213736161: [0.6164383561644, 0.3835616438356], 0.3460311503: [0.6164383561644, 0.3835616438356], 0.4672546444: [0.6712328767123, 0.3287671232877], 0.4120848189: [0.5479452054795, 0.4520547945205], 0.237568024: [0.1506849315068, 0.8493150684932], 0.4830174517: [0.6164383561644, 0.3835616438356], 0.1227247138: [0.2876712328767, 0.7123287671233], 0.2454494277: [0.7945205479452, 0.2054794520548], 0.1489960593: [0.041095890411, 0.958904109589], 0.3058735222: [0.0958904109589, 0.9041095890411], 0.620003753: [0.6164383561644, 0.3835616438356], 0.9859260649: [0.5616438356164, 0.4383561643836], 0.7678738975: [0.2602739726027, 0.7397260273973], 0.8399324451: [0.8082191780822, 0.1917808219178], 0.9243760555: [0.6027397260274, 0.3972602739726], 0.5757177707: [0.1643835616438, 0.8356164383562], 0.411334209: [0.1643835616438, 0.8356164383562], 0.0836930006: [0.6712328767123, 0.3287671232877], 0.0101332333: [0.6438356164384, 0.3561643835616], 0.5411897166: [0.0821917808219, 0.9178082191781], 0.8647025708: [0.1095890410959, 0.8904109589041], 0.2469506474: [0.1643835616438, 0.8356164383562], 0.3584162132: [0.5342465753425, 0.4657534246575], 0.0457872021: [0.1506849315068, 0.8493150684932], 0.3741790205: [0.1917808219178, 0.8082191780822], 0.7258397448: [0.013698630137, 0.986301369863], 0.191030212: [0.027397260274, 0.972602739726], 0.4717583036: [0.6575342465753, 0.3424657534247], 0.7772565209: [0.6438356164384, 0.3561643835616], 0.5993619816: [0.3150684931507, 0.6849315068493], 0.0994558078: [0.6164383561644, 0.3835616438356], 0.4642522049: [0.8767123287671, 0.1232876712329], 0.8087821355: [0.7671232876712, 0.2328767123288], 0.6545318071: [0.0547945205479, 0.9452054794521], 0.7393507225: [0.5616438356164, 0.4383561643836], 0.8076562207: [0.2876712328767, 0.7123287671233], 0.6072433853: [0.0958904109589, 0.9041095890411], 0.8560705573: [0.7808219178082, 0.2191780821918], 0.2131732032: [0.7534246575342, 0.2465753424658], 0.8012760368: [0.7808219178082, 0.2191780821918], 0.8358040908: [0.6301369863014, 0.3698630136986], 0.0562957403: [0.6712328767123, 0.3287671232877], 0.6230061925: [0.6027397260274, 0.3972602739726], 0.9555263652: [0.3150684931507, 0.6849315068493], 0.3775567649: [0.7534246575342, 0.2465753424658], 0.2330643648: [0.6301369863014, 0.3698630136986], 0.9453931319: [0.6301369863014, 0.3698630136986], 0.0153875023: [0.1095890410959, 0.8904109589041], 0.6695440045: [0.041095890411, 0.958904109589], 0.139238131: [0.5342465753425, 0.4657534246575], 0.6620379058: [0.0958904109589, 0.9041095890411], 0.5753424658: [0.0], 0.0735597673: [0.3013698630137, 0.6986301369863], 0.7858885344: [0.3013698630137, 0.6986301369863], 0.0367798837: [0.1780821917808, 0.8219178082192], 0.3021204729: [0.2602739726027, 0.7397260273973], 0.6387689998: [0.1369863013699, 0.8630136986301], 0.1550009383: [0.1917808219178, 0.8082191780822], 0.5066616626: [0.013698630137, 0.986301369863], 0.4942765997: [0.5479452054795, 0.4520547945205], 0.6440232689: [0.6301369863014, 0.3698630136986], 0.6489022331: [0.3013698630137, 0.6986301369863], 0.081441171: [0.027397260274, 0.972602739726], 0.9983111278: [0.041095890411, 0.958904109589], 0.6646650403: [0.2739726027397, 0.7260273972603], 0.8797147682: [0.5205479452055, 0.4794520547945], 0.9176205667: [0.013698630137, 0.986301369863], 0.6804278476: [0.5890410958904, 0.4109589041096], 0.8264214674: [0.0958904109589, 0.9041095890411], 0.2537061362: [0.2739726027397, 0.7260273972603], 0.7119534622: [0.5616438356164, 0.4383561643836], 0.8421842747: [0.6027397260274, 0.3972602739726], 0.7277162695: [0.1095890410959, 0.8904109589041], 0.0138862826: [0.6301369863014, 0.3698630136986], 0.9934321636: [0.2739726027397, 0.7260273972603], 0.8767123288: [0.0], 0.527678739: [0.2739726027397, 0.7260273972603], 0.7705010321: [0.5068493150685, 0.4931506849315], 0.8857196472: [0.0684931506849, 0.9315068493151], 0.8737098893: [0.0547945205479, 0.9452054794521], 0.8039031713: [0.1780821917808, 0.8219178082192], 0.4019515857: [0.1506849315068, 0.8493150684932], 0.9956839932: [0.1780821917808, 0.8219178082192], 0.0131356727: [0.2876712328767, 0.7123287671233], 0.2049164947: [0.2876712328767, 0.7123287671233], 0.4177143929: [0.7808219178082, 0.2191780821918], 0.0844436104: [0.5342465753425, 0.4657534246575], 0.2019140552: [0.6438356164384, 0.3561643835616], 0.5194220304: [0.7945205479452, 0.2054794520548], 0.1358603866: [0.7945205479452, 0.2054794520548], 0.5119159317: [0.3013698630137, 0.6986301369863], 0.7693751173: [0.5342465753425, 0.4657534246575], 0.8800900732: [0.5068493150685, 0.4931506849315], 0.2206793019: [0.6712328767123, 0.3287671232877], 0.7851379246: [0.8082191780822, 0.1917808219178], 0.1268530681: [0.6164383561644, 0.3835616438356], 0.0634265341: [0.1369863013699, 0.8630136986301], 0.1155939201: [0.6575342465753, 0.3424657534247], 0.02889848: [0.6712328767123, 0.3287671232877], 0.1347344718: [0.5753424657534, 0.4246575342466], 0.823419028: [0.3287671232877, 0.6712328767123], 0.2773503472: [0.5068493150685, 0.4931506849315], 0.8204165885: [0.8767123287671, 0.1232876712329], 0.4860198912: [0.6027397260274, 0.3972602739726], 0.1234753237: [0.6301369863014, 0.3698630136986], 0.150497279: [0.013698630137, 0.986301369863], 0.6057421655: [0.5205479452055, 0.4794520547945], 0.9292550197: [0.5753424657534, 0.4246575342466], 0.4195909176: [0.1369863013699, 0.8630136986301], 0.2874835804: [0.013698630137, 0.986301369863], 0.6308875962: [0.2602739726027, 0.7397260273973], 0.5295552637: [0.0684931506849, 0.9315068493151], 0.3220116345: [0.0821917808219, 0.9178082191781], 0.3298930381: [0.5479452054795, 0.4520547945205], 0.1688872209: [0.0958904109589, 0.9041095890411], 0.678176018: [0.0821917808219, 0.9178082191781], 0.7108275474: [0.8767123287671, 0.1232876712329], 0.9495214862: [0.1917808219178, 0.8082191780822], 0.8129104898: [0.1506849315068, 0.8493150684932], 0.9870519797: [0.2602739726027, 0.7397260273973], 0.046162507: [0.3013698630137, 0.6986301369863], 0.1846500281: [0.6027397260274, 0.3972602739726], 0.0923250141: [0.6438356164384, 0.3561643835616], 0.4743854382: [0.1369863013699, 0.8630136986301], 0.5486958154: [0.2602739726027, 0.7397260273973], 0.2953649841: [0.7534246575342, 0.2465753424658], 0.7674985926: [0.1643835616438, 0.8356164383562], 0.1925314318: [0.2602739726027, 0.7397260273973], 0.7112028523: [0.7945205479452, 0.2054794520548], 0.7491086508: [0.1780821917808, 0.8219178082192], 0.9908050291: [0.0958904109589, 0.9041095890411], 0.6507787577: [0.0821917808219, 0.9178082191781], 0.0544192156: [0.5616438356164, 0.4383561643836], 0.8147870144: [0.6027397260274, 0.3972602739726], 0.4139613436: [0.5205479452055, 0.4794520547945], 0.3693000563: [0.2876712328767, 0.7123287671233], 0.857947082: [0.1369863013699, 0.8630136986301], 0.4379808594: [0.5616438356164, 0.4383561643836], 0.0270219553: [0.5616438356164, 0.4383561643836], 0.562206793: [0.7671232876712, 0.2328767123288], 0.4297241509: [0.3013698630137, 0.6986301369863], 0.5719647213: [0.3150684931507, 0.6849315068493], 0.2188027773: [0.5616438356164, 0.4383561643836], 0.4454869582: [0.2739726027397, 0.7260273972603], 0.7517357853: [0.041095890411, 0.958904109589], 0.2525802214: [0.6575342465753, 0.3424657534247], 0.3880653031: [0.0958904109589, 0.9041095890411], 0.8515668981: [0.5342465753425, 0.4657534246575], 0.4612497654: [0.5890410958904, 0.4109589041096], 0.968286733: [0.1780821917808, 0.8219178082192], 0.5340589229: [0.013698630137, 0.986301369863], 0.2345655845: [0.1095890410959, 0.8904109589041], 0.0086320135: [0.1369863013699, 0.8630136986301], 0.8252955526: [0.5068493150685, 0.4931506849315], 0.4653781197: [0.5616438356164, 0.4383561643836], 0.8996059298: [0.5890410958904, 0.4109589041096], 0.2893601051: [0.1095890410959, 0.8904109589041], 0.9247513605: [0.0821917808219, 0.9178082191781], 0.6853068118: [0.1643835616438, 0.8356164383562], 0.3850628636: [0.6712328767123, 0.3287671232877], 0.8016513417: [0.2739726027397, 0.7260273972603], 0.2555826609: [0.0684931506849, 0.9315068493151], 0.643272659: [0.2876712328767, 0.7123287671233], 0.1643835616: [0.0], 0.8125351848: [0.8082191780822, 0.1917808219178], 0.6706699193: [0.2876712328767, 0.7123287671233], 0.7295927941: [0.6164383561644, 0.3835616438356], 0.6402702196: [0.6438356164384, 0.3561643835616], 0.6864327266: [0.3287671232877, 0.6712328767123], 0.7021955339: [0.6164383561644, 0.3835616438356], 0.0307750047: [0.5068493150685, 0.4931506849315], 0.9502720961: [0.3013698630137, 0.6986301369863], 0.3955714018: [0.041095890411, 0.958904109589], 0.1827735035: [0.1506849315068, 0.8493150684932], 0.3734284106: [0.6164383561644, 0.3835616438356], 0.3295177332: [0.2602739726027, 0.7397260273973], 0.1906549071: [0.7945205479452, 0.2054794520548], 0.0953274536: [0.2876712328767, 0.7123287671233], 0.510414712: [0.6164383561644, 0.3835616438356], 0.9604053293: [0.3287671232877, 0.6712328767123], 0.1985363108: [0.7808219178082, 0.2191780821918], 0.5348095327: [0.7671232876712, 0.2328767123288], 0.4049540251: [0.7534246575342, 0.2465753424658], 0.0251454307: [0.5753424657534, 0.4246575342466], 0.9776693564: [0.3013698630137, 0.6986301369863], 0.9179958716: [0.6301369863014, 0.3698630136986], 0.6747982736: [0.6164383561644, 0.3835616438356], 0.0067554888: [0.7808219178082, 0.2191780821918], 0.9592794145: [0.1643835616438, 0.8356164383562], 0.6826796772: [0.5753424657534, 0.4246575342466], 0.0555451304: [0.2602739726027, 0.7397260273973], 0.3107524864: [0.1780821917808, 0.8219178082192], 0.9018577594: [0.5753424657534, 0.4246575342466], 0.0641771439: [0.1780821917808, 0.8219178082192], 0.1283542879: [0.3013698630137, 0.6986301369863], 0.8770876337: [0.1643835616438, 0.8356164383562], 0.1163445299: [0.7808219178082, 0.2191780821918], 0.2326890599: [0.013698630137, 0.986301369863], 0.058172265: [0.5068493150685, 0.4931506849315], 0.1362356915: [0.027397260274, 0.972602739726], 0.3197598048: [0.1506849315068, 0.8493150684932], 0.5580784387: [0.6438356164384, 0.3561643835616], 0.2405704635: [0.7534246575342, 0.2465753424658], 0.1441170951: [0.2739726027397, 0.7260273972603], 0.0303996998: [0.5205479452055, 0.4794520547945], 0.967911428: [0.0684931506849, 0.9315068493151], 0.8286732971: [0.7808219178082, 0.2191780821918], 0.6485269281: [0.1506849315068, 0.8493150684932], 0.6211296679: [0.1506849315068, 0.8493150684932], 0.9600300244: [0.5479452054795, 0.4520547945205], 0.5742165509: [0.7945205479452, 0.2054794520548], 0.3557890786: [0.5616438356164, 0.4383561643836], 0.945017827: [0.013698630137, 0.986301369863], 0.846312629: [0.0547945205479, 0.9452054794521], 0.1703884406: [0.6575342465753, 0.3424657534247], 0.6590354663: [0.3287671232877, 0.6712328767123], 0.4931506849: [0.0], 0.1782698442: [0.6301369863014, 0.3698630136986], 0.7262150497: [0.6301369863014, 0.3698630136986], 0.5873522237: [0.041095890411, 0.958904109589], 0.3407768812: [0.041095890411, 0.958904109589], 0.741977857: [0.5342465753425, 0.4657534246575], 0.7603677988: [0.0821917808219, 0.9178082191781], 0.3801838994: [0.6849315068493, 0.3150684931507], 0.7386001126: [0.7945205479452, 0.2054794520548], 0.9221242259: [0.8082191780822, 0.1917808219178], 0.7701257272: [0.5205479452055, 0.4794520547945], 0.8207918934: [0.7945205479452, 0.2054794520548], 0.4353537249: [0.0547945205479, 0.9452054794521], 0.3028710828: [0.6712328767123, 0.3287671232877], 0.4169637831: [0.6575342465753, 0.3424657534247], 0.7431037718: [0.5068493150685, 0.4931506849315], 0.4248451867: [0.6301369863014, 0.3698630136986], 0.2124225934: [0.0821917808219, 0.9178082191781], 0.0093826234: [0.1780821917808, 0.8219178082192], 0.7115781573: [0.027397260274, 0.972602739726], 0.4758866579: [0.6438356164384, 0.3561643835616], 0.220303997: [0.5479452054795, 0.4520547945205], 0.1733908801: [0.0684931506849, 0.9315068493151], 0.4484893976: [0.6438356164384, 0.3561643835616], 0.3831863389: [0.5616438356164, 0.4383561643836], 0.5085381873: [0.8904109589041, 0.1095890410959], 0.1140927003: [0.0958904109589, 0.9041095890411], 0.0015012197: [0.6712328767123, 0.3287671232877], 0.0776881216: [0.5890410958904, 0.4109589041096], 0.8478138488: [0.8767123287671, 0.1232876712329], 0.9416400826: [0.6438356164384, 0.3561643835616], 0.8909739163: [0.7671232876712, 0.2328767123288], 0.9574028898: [0.8767123287671, 0.1232876712329], 0.9731656971: [0.7671232876712, 0.2328767123288], 0.2923625446: [0.1506849315068, 0.8493150684932], 0.2465753425: [0.0], 0.0375304935: [0.6438356164384, 0.3561643835616], 0.1501219741: [0.2876712328767, 0.7123287671233], 0.0750609871: [0.6027397260274, 0.3972602739726], 0.3081253518: [0.7808219178082, 0.2191780821918], 0.8433101895: [0.7534246575342, 0.2465753424658], 0.6293863764: [0.027397260274, 0.972602739726], 0.0319009195: [0.0958904109589, 0.9041095890411], 0.5021580034: [0.0684931506849, 0.9315068493151], 0.660911991: [0.5068493150685, 0.4931506849315], 0.817414149: [0.5890410958904, 0.4109589041096], 0.8553199475: [0.3424657534247, 0.6575342465753], 0.8099080503: [0.1095890410959, 0.8904109589041], 0.1763933196: [0.041095890411, 0.958904109589], 0.7528617001: [0.2876712328767, 0.7123287671233], 0.5182961156: [0.5753424657534, 0.4246575342466], 0.3606680428: [0.0958904109589, 0.9041095890411], 0.5239256896: [0.5068493150685, 0.4931506849315], 0.0296490899: [0.5342465753425, 0.4657534246575], 0.3152561456: [0.6301369863014, 0.3698630136986], 0.3764308501: [0.6027397260274, 0.3972602739726], 0.0960780634: [0.6301369863014, 0.3698630136986], 0.1921561269: [0.1643835616438, 0.8356164383562], 0.3921936573: [0.1369863013699, 0.8630136986301], 0.7843873147: [0.6164383561644, 0.3835616438356], 0.1658847814: [0.6712328767123, 0.3287671232877], 0.9896791143: [0.5068493150685, 0.4931506849315], 0.4079564646: [0.0547945205479, 0.9452054794521], 0.829048602: [0.2739726027397, 0.7260273972603], 0.034528054: [0.2739726027397, 0.7260273972603], 0.7134546819: [0.5479452054795, 0.4520547945205], 0.8763370238: [0.5616438356164, 0.4383561643836], 0.1092137362: [0.5616438356164, 0.4383561643836], 0.9337586789: [0.5342465753425, 0.4657534246575], 0.8920998311: [0.1095890410959, 0.8904109589041], 0.75361231: [0.6301369863014, 0.3698630136986], 0.4526177519: [0.7671232876712, 0.2328767123288], 0.226308876: [0.2739726027397, 0.7260273972603], 0.1298555076: [0.6027397260274, 0.3972602739726], 0.5325577031: [0.041095890411, 0.958904109589], 0.550947645: [0.5205479452055, 0.4794520547945], 0.4796397073: [0.6301369863014, 0.3698630136986], 0.1377369112: [0.2602739726027, 0.7397260273973], 0.3475323701: [0.3013698630137, 0.6986301369863], 0.7243385251: [0.041095890411, 0.958904109589], 0.2420716832: [0.5890410958904, 0.4109589041096], 0.9998123475: [0.013698630137, 0.986301369863], 0.0728091574: [0.1917808219178, 0.8082191780822], 0.4920247701: [0.7945205479452, 0.2054794520548], 0.7213360856: [0.0684931506849, 0.9315068493151], 0.1249765434: [0.1095890410959, 0.8904109589041], 0.2499530869: [0.5068493150685, 0.4931506849315], 0.5614561831: [0.013698630137, 0.986301369863], 0.6113717395: [0.1369863013699, 0.8630136986301], 0.5539500844: [0.3424657534247, 0.6575342465753], 0.7029461437: [0.8082191780822, 0.1917808219178], 0.6271345468: [0.0547945205479, 0.9452054794521], 0.3201351098: [0.3013698630137, 0.6986301369863], 0.382811034: [0.027397260274, 0.972602739726], 0.7157065115: [0.5068493150685, 0.4931506849315], 0.1640082567: [0.5616438356164, 0.4383561643836], 0.6586601614: [0.5479452054795, 0.4520547945205], 0.3358979171: [0.2739726027397, 0.7260273972603], 0.544942766: [0.0547945205479, 0.9452054794521], 0.9360105085: [0.0958904109589, 0.9041095890411], 0.5205479452: [0.0], 0.863576656: [0.7671232876712, 0.2328767123288], 0.8699568399: [0.0821917808219, 0.9178082191781], 0.3516607243: [0.5890410958904, 0.4109589041096], 0.1238506286: [0.7671232876712, 0.2328767123288], 0.4518671421: [0.013698630137, 0.986301369863], 0.179771064: [0.1095890410959, 0.8904109589041], 0.4293488459: [0.1506849315068, 0.8493150684932], 0.4954025145: [0.5342465753425, 0.4657534246575], 0.5652092325: [0.6164383561644, 0.3835616438356], 0.3632951773: [0.2739726027397, 0.7260273972603], 0.214674423: [0.5890410958904, 0.4109589041096], 0.7911428035: [0.3150684931507, 0.6849315068493], 0.9769187465: [0.8082191780822, 0.1917808219178], 0.7952711578: [0.2602739726027, 0.7397260273973], 0.4042034153: [0.0821917808219, 0.9178082191781], 0.2060424095: [0.7671232876712, 0.2328767123288], 0.8744604992: [0.5753424657534, 0.4246575342466], 0.4199662226: [0.0684931506849, 0.9315068493151], 0.7956464628: [0.5479452054795, 0.4520547945205], 0.7427284669: [0.5205479452055, 0.4794520547945], 0.4991555639: [0.3424657534247, 0.6575342465753], 0.0281478701: [0.2602739726027, 0.7397260273973], 0.4514918371: [0.2876712328767, 0.7123287671233], 0.8279226872: [0.3424657534247, 0.6575342465753], 0.5145430662: [0.7534246575342, 0.2465753424658], 0.916119347: [0.041095890411, 0.958904109589], 0.2638393695: [0.6164383561644, 0.3835616438356], 0.9318821543: [0.1643835616438, 0.8356164383562], 0.875211109: [0.8767123287671, 0.1232876712329], 0.0679301933: [0.2876712328767, 0.7123287671233], 0.3790579846: [0.5890410958904, 0.4109589041096], 0.6034903359: [0.2602739726027, 0.7397260273973], 0.5618314881: [0.6301369863014, 0.3698630136986], 0.1437417902: [0.7808219178082, 0.2191780821918], 0.3100018765: [0.1369863013699, 0.8630136986301], 0.2510790017: [0.0958904109589, 0.9041095890411], 0.5907299681: [0.1095890410959, 0.8904109589041], 0.2480765622: [0.6712328767123, 0.3287671232877], 0.7123287671: [0.0], 0.5775942954: [0.5342465753425, 0.4657534246575], 0.7738787765: [0.7808219178082, 0.2191780821918], 0.979545881: [0.0821917808219, 0.9178082191781], 0.4556201914: [0.6164383561644, 0.3835616438356], 0.66691687: [0.1780821917808, 0.8219178082192], 0.6395196097: [0.1780821917808, 0.8219178082192], 0.6789266279: [0.7534246575342, 0.2465753424658], 0.3895665228: [0.6575342465753, 0.3424657534247], 0.9829236254: [0.3150684931507, 0.6849315068493], 0.6984424845: [0.013698630137, 0.986301369863], 0.1778945393: [0.013698630137, 0.986301369863], 0.0889472697: [0.7808219178082, 0.2191780821918], 0.7877650591: [0.0821917808219, 0.9178082191781], 0.0821917808: [0.0], 0.3715518859: [0.8904109589041, 0.1095890410959], 0.185775943: [0.7534246575342, 0.2465753424658], 0.9270031901: [0.5890410958904, 0.4109589041096], 0.4687558641: [0.5205479452055, 0.4794520547945], 0.9052355038: [0.5479452054795, 0.4520547945205], 0.4282229311: [0.6164383561644, 0.3835616438356], 0.8035278664: [0.0684931506849, 0.9315068493151], 0.6560330268: [0.8767123287671, 0.1232876712329], 0.4109589041: [0.0], 0.835053481: [0.2876712328767, 0.7123287671233], 0.8508162882: [0.3287671232877, 0.6712328767123], 0.0683054982: [0.013698630137, 0.986301369863], 0.4263464065: [0.8904109589041, 0.1095890410959], 0.8665790955: [0.6164383561644, 0.3835616438356], 0.9863013699: [0.0], 0.2199286921: [0.2602739726027, 0.7397260273973], 0.5490711203: [0.5479452054795, 0.4520547945205], 0.4477387878: [0.1780821917808, 0.8219178082192], 0.8981047101: [0.7534246575342, 0.2465753424658], 0.2278100957: [0.1369863013699, 0.8630136986301], 0.7922687183: [0.5753424657534, 0.4246575342466], 0.5227997748: [0.5342465753425, 0.4657534246575], 0.463501595: [0.5753424657534, 0.4246575342466], 0.2705948583: [0.6849315068493, 0.3150684931507], 0.5933571026: [0.8082191780822, 0.1917808219178], 0.5569525239: [0.0684931506849, 0.9315068493151], 0.4792644023: [0.013698630137, 0.986301369863], 0.3471570651: [0.1506849315068, 0.8493150684932], 0.9742916119: [0.1095890410959, 0.8904109589041], 0.243572903: [0.0547945205479, 0.9452054794521], 0.8489397636: [0.5616438356164, 0.4383561643836], 0.8782135485: [0.3287671232877, 0.6712328767123], 0.6016138112: [0.7945205479452, 0.2054794520548], 0.307374742: [0.6575342465753, 0.3424657534247], 0.9878025896: [0.3287671232877, 0.6712328767123], 0.1576280728: [0.0821917808219, 0.9178082191781], 0.5847250891: [0.1780821917808, 0.8219178082192], 0.4210921374: [0.6438356164384, 0.3561643835616], 0.0183899418: [0.1506849315068, 0.8493150684932], 0.1655094765: [0.5479452054795, 0.4520547945205], 0.8373053106: [0.1095890410959, 0.8904109589041], 0.3389003565: [0.6438356164384, 0.3561643835616], 0.08669544: [0.0958904109589, 0.9041095890411], 0.9589041096: [0.0], 0.3546631638: [0.8767123287671, 0.1232876712329], 0.9874272847: [0.5479452054795, 0.4520547945205], 0.7224620004: [0.6438356164384, 0.3561643835616], 0.2214299118: [0.5342465753425, 0.4657534246575], 0.84030775: [0.1506849315068, 0.8493150684932], 0.5494464252: [0.3287671232877, 0.6712328767123], 0.6980671796: [0.2876712328767, 0.7123287671233], 0.4316006755: [0.0821917808219, 0.9178082191781], 0.4976543442: [0.0958904109589, 0.9041095890411], 0.7310940139: [0.3013698630137, 0.6986301369863], 0.4503659223: [0.041095890411, 0.958904109589], 0.5967348471: [0.7534246575342, 0.2465753424658], 0.7791330456: [0.041095890411, 0.958904109589], 0.4368549446: [0.8767123287671, 0.1232876712329], 0.422968662: [0.041095890411, 0.958904109589], 0.3047476074: [0.5068493150685, 0.4931506849315], 0.5134171514: [0.6027397260274, 0.3972602739726], 0.8789641584: [0.5342465753425, 0.4657534246575], 0.4387314693: [0.1643835616438, 0.8356164383562], 0.614749484: [0.041095890411, 0.958904109589], 0.8905986114: [0.6301369863014, 0.3698630136986], 0.017264027: [0.6164383561644, 0.3835616438356], 0.9063614187: [0.5342465753425, 0.4657534246575], 0.3550384688: [0.7945205479452, 0.2054794520548], 0.2311878401: [0.041095890411, 0.958904109589], 0.4376055545: [0.027397260274, 0.972602739726], 0.266841809: [0.6027397260274, 0.3972602739726], 0.5385625821: [0.8082191780822, 0.1917808219178], 0.1373616063: [0.1643835616438, 0.8356164383562], 0.0686808032: [0.6301369863014, 0.3698630136986], 0.3813098142: [0.5753424657534, 0.4246575342466], 0.2826046163: [0.1369863013699, 0.8630136986301], 0.1118408707: [0.5342465753425, 0.4657534246575], 0.0394070182: [0.041095890411, 0.958904109589], 0.9851754551: [0.7945205479452, 0.2054794520548], 0.0476637268: [0.6027397260274, 0.3972602739726], 0.2495777819: [0.5205479452055, 0.4794520547945], 0.9307562394: [0.027397260274, 0.972602739726], 0.6098705198: [0.2739726027397, 0.7260273972603], 0.6256333271: [0.5890410958904, 0.4109589041096], 0.5062863577: [0.2876712328767, 0.7123287671233], 0.1610058172: [0.6849315068493, 0.3150684931507], 0.5997372865: [0.0547945205479, 0.9452054794521], 0.6571589416: [0.5616438356164, 0.4383561643836], 0.2717207731: [0.5753424657534, 0.4246575342466], 0.4728842184: [0.2739726027397, 0.7260273972603], 0.6729217489: [0.1095890410959, 0.8904109589041], 0.6860574217: [0.5479452054795, 0.4520547945205], 0.9183711766: [0.7671232876712, 0.2328767123288], 0.6312629011: [0.5479452054795, 0.4520547945205], 0.5220491649: [0.3287671232877, 0.6712328767123], 0.1872771627: [0.5890410958904, 0.4109589041096], 0.3970726215: [0.013698630137, 0.986301369863], 0.382435729: [0.7945205479452, 0.2054794520548], 0.2649652843: [0.1506849315068, 0.8493150684932], 0.1951585663: [0.5068493150685, 0.4931506849315], 0.0975792832: [0.1095890410959, 0.8904109589041], 0.7937699381: [0.027397260274, 0.972602739726], 0.9577781948: [0.7945205479452, 0.2054794520548], 0.7731281666: [0.3424657534247, 0.6575342465753], 0.8594483017: [0.6438356164384, 0.3561643835616], 0.6778007131: [0.6027397260274, 0.3972602739726], 0.6717958341: [0.7671232876712, 0.2328767123288], 0.5456933759: [0.5753424657534, 0.4246575342466], 0.43497842: [0.6849315068493, 0.3150684931507], 0.0135109777: [0.013698630137, 0.986301369863], 0.7806342653: [0.013698630137, 0.986301369863], 0.6856821167: [0.2602739726027, 0.7397260273973], 0.2293113154: [0.6438356164384, 0.3561643835616], 0.823043723: [0.5479452054795, 0.4520547945205], 0.2942390692: [0.6027397260274, 0.3972602739726], 0.1185963595: [0.0684931506849, 0.9315068493151], 0.2371927191: [0.1917808219178, 0.8082191780822], 0.0592981798: [0.0958904109589, 0.9041095890411], 0.7337211484: [0.7534246575342, 0.2465753424658], 0.0701820229: [0.1095890410959, 0.8904109589041], 0.5760930756: [0.2602739726027, 0.7397260273973], 0.2450741227: [0.8767123287671, 0.1232876712329], 0.7397260274: [0.0], 0.2946143742: [0.0821917808219, 0.9178082191781], 0.9656595984: [0.7808219178082, 0.2191780821918], 0.1512478889: [0.7671232876712, 0.2328767123288], 0.3103771815: [0.0684931506849, 0.9315068493151], 0.6233814975: [0.0821917808219, 0.9178082191781], 0.9709138675: [0.041095890411, 0.958904109589], 0.6661662601: [0.1369863013699, 0.8630136986301], 0.4777631826: [0.041095890411, 0.958904109589], 0.5892287484: [0.6301369863014, 0.3698630136986], 0.0893225746: [0.2739726027397, 0.7260273972603], 0.6004878964: [0.5753424657534, 0.4246575342466], 0.341902796: [0.2876712328767, 0.7123287671233], 0.2912366298: [0.6164383561644, 0.3835616438356], 0.9660349034: [0.2739726027397, 0.7260273972603], 0.4924000751: [0.027397260274, 0.972602739726], 0.7127040721: [0.1643835616438, 0.8356164383562], 0.3576656033: [0.6712328767123, 0.3287671232877], 0.3655470069: [0.1780821917808, 0.8219178082192], 0.7093263276: [0.0547945205479, 0.9452054794521], 0.7442296866: [0.0958904109589, 0.9041095890411], 0.8624507412: [0.2876712328767, 0.7123287671233], 0.52167386: [0.5479452054795, 0.4520547945205], 0.7599924939: [0.6027397260274, 0.3972602739726], 0.730343404: [0.8082191780822, 0.1917808219178], 0.1932820417: [0.6712328767123, 0.3287671232877], 0.4075811597: [0.6849315068493, 0.3150684931507], 0.5982360668: [0.5890410958904, 0.4109589041096], 0.2011634453: [0.1780821917808, 0.8219178082192], 0.1005817227: [0.1506849315068, 0.8493150684932], 0.7055732783: [0.0821917808219, 0.9178082191781], 0.0090073184: [0.0684931506849, 0.9315068493151], 0.6061174704: [0.5068493150685, 0.4931506849315], 0.2090448489: [0.6164383561644, 0.3835616438356], 0.4180896979: [0.2739726027397, 0.7260273972603], 0.8680803153: [0.3013698630137, 0.6986301369863], 0.8226684181: [0.2602739726027, 0.7397260273973], 0.608744605: [0.3424657534247, 0.6575342465753], 0.8677050103: [0.1506849315068, 0.8493150684932], 0.2169262526: [0.5753424657534, 0.4246575342466], 0.0788140364: [0.6849315068493, 0.3150684931507], 0.666541565: [0.0684931506849, 0.9315068493151], 0.6012385063: [0.8767123287671, 0.1232876712329], 0.5291799587: [0.1369863013699, 0.8630136986301], 0.1110902608: [0.6712328767123, 0.3287671232877], 0.6170013136: [0.7671232876712, 0.2328767123288], 0.1309814224: [0.7534246575342, 0.2465753424658], 0.9281291049: [0.3150684931507, 0.6849315068493], 0.8939763558: [0.6164383561644, 0.3835616438356], 0.6834302871: [0.8767123287671, 0.1232876712329], 0.6297616814: [0.5616438356164, 0.4383561643836], 0.243197598: [0.6849315068493, 0.3150684931507], 0.4863951961: [0.0821917808219, 0.9178082191781], 0.3572902984: [0.5479452054795, 0.4520547945205], 0.9885531995: [0.5342465753425, 0.4657534246575], 0.301369863: [0.0], 0.6158753988: [0.2876712328767, 0.7123287671233], 0.040532933: [0.2876712328767, 0.7123287671233], 0.631638206: [0.3287671232877, 0.6712328767123], 0.6474010133: [0.6164383561644, 0.3835616438356], 0.6455244886: [0.1095890410959, 0.8904109589041], 0.0412835429: [0.6301369863014, 0.3698630136986], 0.2567085757: [0.6438356164384, 0.3561643835616], 0.0806905611: [0.8767123287671, 0.1232876712329], 0.1730155752: [0.1369863013699, 0.8630136986301], 0.7855132295: [0.1506849315068, 0.8493150684932], 0.7078251079: [0.5890410958904, 0.4109589041096], 0.353912554: [0.5753424657534, 0.4246575342466], 0.9131169075: [0.0684931506849, 0.9315068493151], 0.9056108088: [0.3287671232877, 0.6712328767123], 0.8500656784: [0.2602739726027, 0.7397260273973], 0.3696753612: [0.013698630137, 0.986301369863], 0.9228748358: [0.3013698630137, 0.6986301369863], 0.3377744417: [0.0684931506849, 0.9315068493151], 0.1887783824: [0.0547945205479, 0.9452054794521], 0.7682492025: [0.5479452054795, 0.4520547945205], 0.330268343: [0.6712328767123, 0.3287671232877], 0.2645899794: [0.1917808219178, 0.8082191780822], 0.5667104522: [0.3013698630137, 0.6986301369863], 0.3332707825: [0.0958904109589, 0.9041095890411], 0.7168324263: [0.0958904109589, 0.9041095890411], 0.0668042785: [0.041095890411, 0.958904109589], 0.0213923813: [0.7534246575342, 0.2465753424658], 0.5483205104: [0.1643835616438, 0.8356164383562], 0.8313004316: [0.1780821917808, 0.8219178082192], 0.0517920811: [0.0547945205479, 0.9452054794521], 0.0045036592: [0.0958904109589, 0.9041095890411], 0.8470632389: [0.5753424657534, 0.4246575342466], 0.8628260462: [0.013698630137, 0.986301369863], 0.272471383: [0.8767123287671, 0.1232876712329], 0.6950647401: [0.6438356164384, 0.3561643835616], 0.5032839182: [0.6438356164384, 0.3561643835616], 0.4537436667: [0.8904109589041, 0.1095890410959], 0.26083693: [0.7671232876712, 0.2328767123288], 0.8222931132: [0.1643835616438, 0.8356164383562], 0.4451116532: [0.7808219178082, 0.2191780821918], 0.9521486208: [0.0821917808219, 0.9178082191781], 0.0071307938: [0.2739726027397, 0.7260273972603], 0.5663351473: [0.1506849315068, 0.8493150684932], 0.2829799212: [0.0684931506849, 0.9315068493151], 0.3490335898: [0.6027397260274, 0.3972602739726], 0.6755488835: [0.8082191780822, 0.1917808219178], 0.9994370426: [0.2876712328767, 0.7123287671233], 0.3133796209: [0.041095890411, 0.958904109589], 0.6267592419: [0.3150684931507, 0.6849315068493], 0.2882341903: [0.7671232876712, 0.2328767123288], 0.3291424282: [0.1643835616438, 0.8356164383562], 0.8459373241: [0.3150684931507, 0.6849315068493], 0.6714205292: [0.6301369863014, 0.3698630136986], 0.7138299869: [0.3287671232877, 0.6712328767123], 0.6871833365: [0.5342465753425, 0.4657534246575], 0.9134922124: [0.1780821917808, 0.8219178082192], 0.3527866391: [0.6849315068493, 0.3150684931507], 0.5783449052: [0.5205479452055, 0.4794520547945], 0.4680052543: [0.5342465753425, 0.4657534246575], 0.5896040533: [0.7671232876712, 0.2328767123288], 0.0120097579: [0.041095890411, 0.958904109589], 0.1831488084: [0.3013698630137, 0.6986301369863], 0.7659973729: [0.7945205479452, 0.2054794520548], 0.9949333834: [0.1369863013699, 0.8630136986301], 0.1947832614: [0.5205479452055, 0.4794520547945], 0.3974479264: [0.6301369863014, 0.3698630136986], 0.7975229874: [0.5205479452055, 0.4794520547945], 0.7374741978: [0.5753424657534, 0.4246575342466], 0.0030024395: [0.5205479452055, 0.4794520547945], 0.4132107337: [0.5342465753425, 0.4657534246575], 0.9724150873: [0.013698630137, 0.986301369863], 0.2105460687: [0.3013698630137, 0.6986301369863], 0.9074873335: [0.5068493150685, 0.4931506849315], 0.428973541: [0.8082191780822, 0.1917808219178], 0.2184274723: [0.027397260274, 0.972602739726], 0.886845562: [0.6438356164384, 0.3561643835616], 0.0551698255: [0.1643835616438, 0.8356164383562], 0.9026083693: [0.8767123287671, 0.1232876712329], 0.5359354476: [0.8904109589041, 0.1095890410959], 0.5599549634: [0.041095890411, 0.958904109589], 0.1324826421: [0.5890410958904, 0.4109589041096], 0.4657534247: [0.0], 0.475136048: [0.1780821917808, 0.8219178082192], 0.2728466879: [0.7945205479452, 0.2054794520548], 0.9498967911: [0.1506849315068, 0.8493150684932], 0.1403640458: [0.5068493150685, 0.4931506849315], 0.3145055357: [0.2876712328767, 0.7123287671233], 0.5745918559: [0.027397260274, 0.972602739726], 0.3805592044: [0.0547945205479, 0.9452054794521], 0.9037342841: [0.5616438356164, 0.4383561643836], 0.6368924751: [0.7808219178082, 0.2191780821918], 0.5190467255: [0.8767123287671, 0.1232876712329], 0.3043723025: [0.5205479452055, 0.4794520547945], 0.5659598424: [0.8082191780822, 0.1917808219178], 0.8080315256: [0.013698630137, 0.986301369863], 0.1666353913: [0.5342465753425, 0.4657534246575], 0.6849315068: [0.0], 0.9142428223: [0.6438356164384, 0.3561643835616], 0.962281854: [0.5068493150685, 0.4931506849315], 0.1745167949: [0.6438356164384, 0.3561643835616], 0.8309251267: [0.0684931506849, 0.9315068493151], 0.3569149934: [0.2602739726027, 0.7397260273973], 0.05779696: [0.5205479452055, 0.4794520547945], 0.1823981985: [0.1917808219178, 0.8082191780822], 0.0911990993: [0.0684931506849, 0.9315068493151], 0.7900168887: [0.5890410958904, 0.4109589041096], 0.6023644211: [0.5616438356164, 0.4383561643836], 0.1902796022: [0.8767123287671, 0.1232876712329], 0.7742540814: [0.2739726027397, 0.7260273972603], 0.5336836179: [0.2876712328767, 0.7123287671233], 0.6049915556: [0.5342465753425, 0.4657534246575]} averages_odd={0.41077125164: [0.013698630137, 0.986301369863], 0.41865265528: [0.7534246575342, 0.2465753424658], 0.60630512291: [0.6164383561644, 0.3835616438356], 0.21261024583: [0.2739726027397, 0.7260273972603], 0.67198348658: [0.2602739726027, 0.7397260273973], 0.99549634078: [0.5890410958904, 0.4109589041096], 0.92644023269: [0.1369863013699, 0.8630136986301], 0.92493901295: [0.2739726027397, 0.7260273972603], 0.61944079565: [0.5205479452055, 0.4794520547945], 0.06398949146: [0.5890410958904, 0.4109589041096], 0.71927190843: [0.0821917808219, 0.9178082191781], 0.26252580221: [0.5342465753425, 0.4657534246575], 0.11615687746: [0.6027397260274, 0.3972602739726], 0.73503471571: [0.0684931506849, 0.9315068493151], 0.27040720586: [0.6438356164384, 0.3561643835616], 0.23625445675: [0.5068493150685, 0.4931506849315], 0.7594295365: [0.3424657534247, 0.6575342465753], 0.2782886095: [0.1917808219178, 0.8082191780822], 0.76656033027: [0.2876712328767, 0.7123287671233], 0.28617001314: [0.8767123287671, 0.1232876712329], 0.779696003: [0.7945205479452, 0.2054794520548], 0.03659223119: [0.5890410958904, 0.4109589041096], 0.49483955714: [0.1095890410959, 0.8904109589041], 0.15030962657: [0.5616438356164, 0.4383561643836], 0.30193282042: [0.7671232876712, 0.2328767123288], 0.81122161756: [0.5205479452055, 0.4794520547945], 0.0771251642: [0.1369863013699, 0.8630136986301], 0.82698442485: [0.3013698630137, 0.6986301369863], 0.64308500657: [0.027397260274, 0.972602739726], 0.84274723213: [0.2739726027397, 0.7260273972603], 0.00506661663: [0.3013698630137, 0.6986301369863], 0.85851003941: [0.5890410958904, 0.4109589041096], 0.16607243385: [0.1095890410959, 0.8904109589041], 0.87164571214: [0.1369863013699, 0.8630136986301], 0.78307374742: [0.5342465753425, 0.4657534246575], 0.88740851942: [0.0547945205479, 0.9452054794521], 0.49146181272: [0.041095890411, 0.958904109589], 0.48845937324: [0.0684931506849, 0.9315068493151], 0.35447551135: [0.041095890411, 0.958904109589], 0.85963595421: [0.6849315068493, 0.3150684931507], 0.85363107525: [0.1917808219178, 0.8082191780822], 0.93206980672: [0.7671232876712, 0.2328767123288], 0.37023831863: [0.1643835616438, 0.8356164383562], 0.54625633327: [0.041095890411, 0.958904109589], 0.04710076938: [0.3424657534247, 0.6575342465753], 0.56201914055: [0.1643835616438, 0.8356164383562], 0.19234377932: [0.7671232876712, 0.2328767123288], 0.57515481329: [0.013698630137, 0.986301369863], 0.12478889097: [0.3287671232877, 0.6712328767123], 0.09814224057: [0.5342465753425, 0.4657534246575], 0.59354475511: [0.0958904109589, 0.9041095890411], 0.77631825859: [0.5890410958904, 0.4109589041096], 0.99099268155: [0.1506849315068, 0.8493150684932], 0.83786826797: [0.5342465753425, 0.4657534246575], 0.62244323513: [0.3424657534247, 0.6575342465753], 0.67461062113: [0.5068493150685, 0.4931506849315], 0.10602364421: [0.6438356164384, 0.3561643835616], 0.65396884969: [0.6438356164384, 0.3561643835616], 0.43066241321: [0.3424657534247, 0.6575342465753], 0.66973165697: [0.8767123287671, 0.1232876712329], 0.43854381685: [0.6301369863014, 0.3698630136986], 0.68549446425: [0.7671232876712, 0.2328767123288], 0.95196096829: [0.7808219178082, 0.2191780821918], 0.69863013699: [0.0], 0.25351848377: [0.0821917808219, 0.9178082191781], 0.95721523738: [0.041095890411, 0.958904109589], 0.13004316007: [0.7808219178082, 0.2191780821918], 0.06699193094: [0.8767123287671, 0.1232876712329], 0.23437793207: [0.3287671232877, 0.6712328767123], 0.74329142428: [0.6164383561644, 0.3835616438356], 0.37887033215: [0.0684931506849, 0.9315068493151], 0.69825483205: [0.5616438356164, 0.4383561643836], 0.24225933571: [0.1780821917808, 0.8219178082192], 0.77481703884: [0.7534246575342, 0.2465753424658], 0.00769375117: [0.7534246575342, 0.2465753424658], 0.71401763933: [0.1095890410959, 0.8904109589041], 0.3060611747: [0.1506849315068, 0.8493150684932], 0.82210546069: [0.6301369863014, 0.3698630136986], 0.31394257835: [0.7945205479452, 0.2054794520548], 0.83111277913: [0.5890410958904, 0.4109589041096], 0.32182398199: [0.7808219178082, 0.2191780821918], 0.8510039407: [0.1095890410959, 0.8904109589041], 0.16419590918: [0.013698630137, 0.986301369863], 0.22837305311: [0.5890410958904, 0.4109589041096], 0.17207731282: [0.7534246575342, 0.2465753424658], 0.34546819291: [0.5205479452055, 0.4794520547945], 0.25989866767: [0.5616438356164, 0.4383561643836], 0.50985175455: [0.5205479452055, 0.4794520547945], 0.52561456183: [0.3013698630137, 0.6986301369863], 0.92981797711: [0.041095890411, 0.958904109589], 0.54137736911: [0.2739726027397, 0.7260273972603], 0.37436667292: [0.0958904109589, 0.9041095890411], 0.55714017639: [0.5890410958904, 0.4109589041096], 0.09589041096: [0.0], 0.3901294802: [0.6027397260274, 0.3972602739726], 0.58603865641: [0.0547945205479, 0.9452054794521], 0.58866579096: [0.5616438356164, 0.4383561643836], 0.39801088384: [0.2602739726027, 0.7397260273973], 0.84012009758: [0.0958904109589, 0.9041095890411], 0.40589228748: [0.1369863013699, 0.8630136986301], 0.37924563708: [0.1780821917808, 0.8219178082192], 0.87502345656: [0.041095890411, 0.958904109589], 0.00656783637: [0.6027397260274, 0.3972602739726], 0.21411146557: [0.1369863013699, 0.8630136986301], 0.66222555827: [0.1506849315068, 0.8493150684932], 0.10902608369: [0.2876712328767, 0.7123287671233], 0.67798836555: [0.7808219178082, 0.2191780821918], 0.68061550009: [0.1780821917808, 0.8219178082192], 0.13717395384: [0.6301369863014, 0.3698630136986], 0.12553950084: [0.5342465753425, 0.4657534246575], 0.05648339276: [0.1095890410959, 0.8904109589041], 0.99849878026: [0.8767123287671, 0.1232876712329], 0.98273597298: [0.6438356164384, 0.3561643835616], 0.22987427285: [0.0547945205479, 0.9452054794521], 0.47907674986: [0.5616438356164, 0.4383561643836], 0.46631638206: [0.7671232876712, 0.2328767123288], 0.27340964534: [0.2876712328767, 0.7123287671233], 0.75417526741: [0.2602739726027, 0.7397260273973], 0.06999437043: [0.3287671232877, 0.6712328767123], 0.14392944267: [0.0821917808219, 0.9178082191781], 0.63182585851: [0.1095890410959, 0.8904109589041], 0.29705385626: [0.1780821917808, 0.8219178082192], 0.49784199662: [0.1506849315068, 0.8493150684932], 0.80146368925: [0.0821917808219, 0.9178082191781], 0.15181084631: [0.5479452054795, 0.4520547945205], 0.81722649653: [0.0684931506849, 0.9315068493151], 0.07787577407: [0.1780821917808, 0.8219178082192], 0.80972039782: [0.6712328767123, 0.3287671232877], 0.15969224995: [0.0684931506849, 0.9315068493151], 0.6423343967: [0.8767123287671, 0.1232876712329], 0.02045411897: [0.7808219178082, 0.2191780821918], 0.86188778382: [0.7945205479452, 0.2054794520548], 0.33383373991: [0.3013698630137, 0.6986301369863], 0.94595608932: [0.2602739726027, 0.7397260273973], 0.34171514355: [0.027397260274, 0.972602739726], 0.78232313755: [0.6712328767123, 0.3287671232877], 0.3495965472: [0.2739726027397, 0.7260273972603], 0.7264027022: [0.1643835616438, 0.8356164383562], 0.52073559767: [0.6301369863014, 0.3698630136986], 0.79020454119: [0.1780821917808, 0.8219178082192], 0.36535935448: [0.5890410958904, 0.4109589041096], 0.53649840495: [0.5342465753425, 0.4657534246575], 0.93807468568: [0.6027397260274, 0.3972602739726], 0.37324075812: [0.5068493150685, 0.4931506849315], 0.54963407769: [0.1095890410959, 0.8904109589041], 0.29667855132: [0.0684931506849, 0.9315068493151], 0.26928129105: [0.0684931506849, 0.9315068493151], 0.81760180146: [0.1780821917808, 0.8219178082192], 0.09889285044: [0.5205479452055, 0.4794520547945], 0.02570838807: [0.041095890411, 0.958904109589], 0.62844811409: [0.041095890411, 0.958904109589], 0.41790204541: [0.0821917808219, 0.9178082191781], 0.43666729218: [0.041095890411, 0.958904109589], 0.42578344905: [0.5479452054795, 0.4520547945205], 0.65734659411: [0.013698630137, 0.986301369863], 0.43366485269: [0.0684931506849, 0.9315068493151], 0.00168887221: [0.1095890410959, 0.8904109589041], 0.67573653594: [0.0958904109589, 0.9041095890411], 0.90392193657: [0.013698630137, 0.986301369863], 0.88102833552: [0.1917808219178, 0.8082191780822], 0.65922311878: [0.1095890410959, 0.8904109589041], 0.01595045975: [0.5342465753425, 0.4657534246575], 0.66410208294: [0.6027397260274, 0.3972602739726], 0.46519046726: [0.2876712328767, 0.7123287671233], 0.73616063051: [0.6438356164384, 0.3561643835616], 0.06774254081: [0.027397260274, 0.972602739726], 0.27753799963: [0.6164383561644, 0.3835616438356], 0.11990992682: [0.3150684931507, 0.6849315068493], 0.28541940327: [0.5753424657534, 0.4246575342466], 0.78082191781: [0.0], 0.14730718709: [0.3150684931507, 0.6849315068493], 0.30118221055: [0.013698630137, 0.986301369863], 0.30906361419: [0.7534246575342, 0.2465753424658], 0.8254832051: [0.6164383561644, 0.3835616438356], 0.97222743479: [0.5616438356164, 0.4383561643836], 0.455057234: [0.5205479452055, 0.4794520547945], 0.85700881967: [0.7534246575342, 0.2465753424658], 0.47644961531: [0.0547945205479, 0.9452054794521], 0.17357853256: [0.5890410958904, 0.4109589041096], 0.50009382623: [0.0821917808219, 0.9178082191781], 0.90429724151: [0.6301369863014, 0.3698630136986], 0.08875961719: [0.6027397260274, 0.3972602739726], 0.51585663352: [0.0684931506849, 0.9315068493151], 0.82135485082: [0.2876712328767, 0.7123287671233], 0.1814599362: [0.5068493150685, 0.4931506849315], 0.93319572152: [0.1095890410959, 0.8904109589041], 0.36948770876: [0.5616438356164, 0.4383561643836], 0.54738224808: [0.2876712328767, 0.7123287671233], 0.56051792081: [0.7945205479452, 0.2054794520548], 0.38525051604: [0.1095890410959, 0.8904109589041], 0.57890786264: [0.6164383561644, 0.3835616438356], 0.86639144305: [0.5068493150685, 0.4931506849315], 0.99924939013: [0.027397260274, 0.972602739726], 0.59204353537: [0.5205479452055, 0.4794520547945], 0.60780634265: [0.3013698630137, 0.6986301369863], 0.51548132858: [0.1369863013699, 0.8630136986301], 0.62356914993: [0.2739726027397, 0.7260273972603], 0.20773128167: [0.5342465753425, 0.4657534246575], 0.63670482267: [0.6027397260274, 0.3972602739726], 0.42465753425: [0.0], 0.65246762995: [0.1369863013699, 0.8630136986301], 0.21561268531: [0.6438356164384, 0.3561643835616], 0.66823043723: [0.0547945205479, 0.9452054794521], 0.10977669356: [0.6301369863014, 0.3698630136986], 0.22349408895: [0.1917808219178, 0.8082191780822], 0.69975605179: [0.5479452054795, 0.4520547945205], 0.45355601426: [0.3287671232877, 0.6712328767123], 0.34396697317: [0.3287671232877, 0.6712328767123], 0.26064927754: [0.1643835616438, 0.8356164383562], 0.23137549259: [0.8767123287671, 0.1232876712329], 0.46931882154: [0.6164383561644, 0.3835616438356], 0.0005629574: [0.7671232876712, 0.2328767123288], 0.13754925877: [0.7671232876712, 0.2328767123288], 0.76018014637: [0.7808219178082, 0.2191780821918], 0.0707449803: [0.5342465753425, 0.4657534246575], 0.28429348846: [0.3150684931507, 0.6849315068493], 0.91780821918: [0.0], 0.91555638957: [0.5753424657534, 0.4246575342466], 0.2921748921: [0.0958904109589, 0.9041095890411], 0.80746856821: [0.027397260274, 0.972602739726], 0.07862638394: [0.6438356164384, 0.3561643835616], 0.83636704823: [0.2602739726027, 0.7397260273973], 0.32107337212: [0.3424657534247, 0.6575342465753], 0.80671795834: [0.8767123287671, 0.1232876712329], 0.32895477576: [0.6301369863014, 0.3698630136986], 0.01032088572: [0.3150684931507, 0.6849315068493], 0.88365547007: [0.0821917808219, 0.9178082191781], 0.34471758304: [0.5342465753425, 0.4657534246575], 0.89941827735: [0.0684931506849, 0.9315068493151], 0.35259898668: [0.6438356164384, 0.3561643835616], 0.91893413398: [0.5479452054795, 0.4520547945205], 0.36048039032: [0.1917808219178, 0.8082191780822], 0.93094389191: [0.2876712328767, 0.7123287671233], 0.36836179396: [0.8767123287671, 0.1232876712329], 0.94407956465: [0.7945205479452, 0.2054794520548], 0.18746481516: [0.1780821917808, 0.8219178082192], 0.48245449428: [0.5205479452055, 0.4794520547945], 0.5582660912: [0.3150684931507, 0.6849315068493], 0.04785137925: [0.7808219178082, 0.2191780821918], 0.97560517921: [0.5205479452055, 0.4794520547945], 0.1953462188: [0.6164383561644, 0.3835616438356], 0.99136798649: [0.3013698630137, 0.6986301369863], 0.6029273785: [0.6301369863014, 0.3698630136986], 0.94220303997: [0.0547945205479, 0.9452054794521], 0.20322762244: [0.5753424657534, 0.4246575342466], 0.61869018578: [0.5342465753425, 0.4657534246575], 0.01294802027: [0.027397260274, 0.972602739726], 0.63445299306: [0.1917808219178, 0.8082191780822], 0.77068868456: [0.6164383561644, 0.3835616438356], 0.37286545318: [0.5205479452055, 0.4794520547945], 0.99061737662: [0.1917808219178, 0.8082191780822], 0.81835241133: [0.6438356164384, 0.3561643835616], 0.45243009946: [0.1643835616438, 0.8356164383562], 0.71063989492: [0.041095890411, 0.958904109589], 0.22949896791: [0.3150684931507, 0.6849315068493], 0.72377556765: [0.5753424657534, 0.4246575342466], 0.49296303246: [0.013698630137, 0.986301369863], 0.05835991743: [0.6164383561644, 0.3835616438356], 0.73953837493: [0.013698630137, 0.986301369863], 0.06849315069: [0.0], 0.23738037155: [0.0958904109589, 0.9041095890411], 0.75792831676: [0.0958904109589, 0.9041095890411], 0.28054043911: [0.6027397260274, 0.3972602739726], 0.96359542128: [0.1506849315068, 0.8493150684932], 0.28842184275: [0.2602739726027, 0.7397260273973], 0.78682679677: [0.6575342465753, 0.3424657534247], 0.29630324639: [0.1369863013699, 0.8630136986301], 0.7020078814: [0.5068493150685, 0.4931506849315], 0.31206605367: [0.0547945205479, 0.9452054794521], 0.77744417339: [0.6849315068493, 0.3150684931507], 0.83411521862: [0.8767123287671, 0.1232876712329], 0.15931694502: [0.1369863013699, 0.8630136986301], 0.08162882342: [0.2876712328767, 0.7123287671233], 0.86301369863: [0.0], 0.97935822856: [0.7808219178082, 0.2191780821918], 0.01069619066: [0.0547945205479, 0.9452054794521], 0.1750797523: [0.0547945205479, 0.9452054794521], 0.39388252956: [0.3150684931507, 0.6849315068493], 0.35672734097: [0.7671232876712, 0.2328767123288], 0.53499718521: [0.2602739726027, 0.7397260273973], 0.53762431976: [0.5068493150685, 0.4931506849315], 0.38825295553: [0.1506849315068, 0.8493150684932], 0.58228560706: [0.0821917808219, 0.9178082191781], 0.98648902233: [0.6301369863014, 0.3698630136986], 0.39613435917: [0.7945205479452, 0.2054794520548], 0.59804841434: [0.0684931506849, 0.9315068493151], 0.40401576281: [0.7808219178082, 0.2191780821918], 0.91818352411: [0.1643835616438, 0.8356164383562], 0.10264589979: [0.7808219178082, 0.2191780821918], 0.6295740289: [0.2876712328767, 0.7123287671233], 0.64270970163: [0.7945205479452, 0.2054794520548], 0.64533683618: [0.3287671232877, 0.6712328767123], 0.0133233252: [0.5616438356164, 0.4383561643836], 0.66109964346: [0.6164383561644, 0.3835616438356], 0.67423531619: [0.5205479452055, 0.4794520547945], 0.1367986489: [0.013698630137, 0.986301369863], 0.8701444924: [0.2739726027397, 0.7260273972603], 0.68999812348: [0.3013698630137, 0.6986301369863], 0.4486770501: [0.3150684931507, 0.6849315068493], 0.70576093076: [0.2739726027397, 0.7260273972603], 0.25577031338: [0.5890410958904, 0.4109589041096], 0.71889660349: [0.6027397260274, 0.3972602739726], 0.72152373804: [0.5890410958904, 0.4109589041096], 0.23287671233: [0.0], 0.73465941077: [0.1369863013699, 0.8630136986301], 0.47232126103: [0.6027397260274, 0.3972602739726], 0.48170388441: [0.5342465753425, 0.4657534246575], 0.48020266467: [0.2602739726027, 0.7397260273973], 0.07149559017: [0.5205479452055, 0.4794520547945], 0.48808406831: [0.1369863013699, 0.8630136986301], 0.78194783261: [0.5479452054795, 0.4520547945205], 0.12366297617: [0.1643835616438, 0.8356164383562], 0.03771814599: [0.3150684931507, 0.6849315068493], 0.48620754363: [0.7808219178082, 0.2191780821918], 0.30831300432: [0.0821917808219, 0.9178082191781], 0.5060987052: [0.027397260274, 0.972602739726], 0.82660911991: [0.1506849315068, 0.8493150684932], 0.31619440796: [0.5479452054795, 0.4520547945205], 0.48883467818: [0.1780821917808, 0.8219178082192], 0.16269468944: [0.041095890411, 0.958904109589], 0.74404203415: [0.1917808219178, 0.8082191780822], 0.51398010884: [0.2739726027397, 0.7260273972603], 0.45543253894: [0.5068493150685, 0.4931506849315], 0.24638769: [0.013698630137, 0.986301369863], 0.51698254832: [0.6438356164384, 0.3561643835616], 0.91855882905: [0.2602739726027, 0.7397260273973], 0.18108463126: [0.5205479452055, 0.4794520547945], 0.5327453556: [0.8767123287671, 0.1232876712329], 0.56502158003: [0.5068493150685, 0.4931506849315], 0.09251266654: [0.3150684931507, 0.6849315068493], 0.54850816288: [0.7671232876712, 0.2328767123288], 0.56164383562: [0.0], 0.96584725089: [0.0821917808219, 0.9178082191781], 0.04822668418: [0.2739726027397, 0.7260273972603], 0.14993432164: [0.027397260274, 0.972602739726], 0.98161005817: [0.0684931506849, 0.9315068493151], 0.19684743854: [0.3013698630137, 0.6986301369863], 0.10039407018: [0.0958904109589, 0.9041095890411], 0.92006004879: [0.5342465753425, 0.4657534246575], 0.20472884218: [0.027397260274, 0.972602739726], 0.41602552074: [0.3013698630137, 0.6986301369863], 0.63783073747: [0.7534246575342, 0.2465753424658], 0.64045787202: [0.6849315068493, 0.3150684931507], 0.42390692438: [0.027397260274, 0.972602739726], 0.43178832802: [0.2739726027397, 0.7260273972603], 0.01369863014: [0.0], 0.68511915932: [0.6301369863014, 0.3698630136986], 0.4475511353: [0.5890410958904, 0.4109589041096], 0.7008819666: [0.5342465753425, 0.4657534246575], 0.12666541565: [0.5068493150685, 0.4931506849315], 0.42428222931: [0.5616438356164, 0.4383561643836], 0.71664477388: [0.1917808219178, 0.8082191780822], 0.72902983674: [0.5205479452055, 0.4794520547945], 0.72527678739: [0.027397260274, 0.972602739726], 0.27566147495: [0.1095890410959, 0.8904109589041], 0.06924376056: [0.2602739726027, 0.7397260273973], 0.31431788328: [0.027397260274, 0.972602739726], 0.24676299493: [0.6301369863014, 0.3698630136986], 0.79283167574: [0.041095890411, 0.958904109589], 0.80596734847: [0.5753424657534, 0.4246575342466], 0.15293676112: [0.5342465753425, 0.4657534246575], 0.5252392569: [0.1506849315068, 0.8493150684932], 0.82173015575: [0.013698630137, 0.986301369863], 0.45430662413: [0.5342465753425, 0.4657534246575], 0.31506849315: [0.0], 0.16081816476: [0.6438356164384, 0.3561643835616], 0.08237943329: [0.6301369863014, 0.3698630136986], 0.86901857759: [0.3424657534247, 0.6575342465753], 0.1686995684: [0.1917808219178, 0.8082191780822], 0.90054419216: [0.6438356164384, 0.3561643835616], 0.35184837681: [0.1780821917808, 0.8219178082192], 0.17658097204: [0.8767123287671, 0.1232876712329], 0.91630699944: [0.8767123287671, 0.1232876712329], 0.35972978045: [0.6164383561644, 0.3835616438356], 0.46218802777: [0.6438356164384, 0.3561643835616], 0.36761118409: [0.5753424657534, 0.4246575342466], 0.54100206418: [0.7808219178082, 0.2191780821918], 0.5901670107: [0.5479452054795, 0.4520547945205], 0.55939200601: [0.5753424657534, 0.4246575342466], 0.38337399137: [0.013698630137, 0.986301369863], 0.97410395947: [0.6712328767123, 0.3287671232877], 0.39125539501: [0.7534246575342, 0.2465753424658], 0.58829048602: [0.027397260274, 0.972602739726], 0.04972790392: [0.1369863013699, 0.8630136986301], 0.81422405705: [0.6575342465753, 0.3424657534247], 0.61718896604: [0.2602739726027, 0.7397260273973], 0.47006943141: [0.1917808219178, 0.8082191780822], 0.98198536311: [0.1780821917808, 0.8219178082192], 0.02683430287: [0.2876712328767, 0.7123287671233], 0.66447738788: [0.0821917808219, 0.9178082191781], 0.21861512479: [0.2876712328767, 0.7123287671233], 0.40664289735: [0.1780821917808, 0.8219178082192], 0.11127791331: [0.1095890410959, 0.8904109589041], 0.25089134922: [0.1917808219178, 0.8082191780822], 0.45167948959: [0.5616438356164, 0.4383561643836], 0.71176580972: [0.2876712328767, 0.7123287671233], 0.25877275286: [0.8767123287671, 0.1232876712329], 0.47795083505: [0.8767123287671, 0.1232876712329], 0.727528617: [0.3287671232877, 0.6712328767123], 0.13267029461: [0.1780821917808, 0.8219178082192], 0.01707637455: [0.5068493150685, 0.4931506849315], 0.27453556014: [0.7671232876712, 0.2328767123288], 0.75642709702: [0.5205479452055, 0.4794520547945], 0.14055169826: [0.6164383561644, 0.3835616438356], 0.89378870332: [0.5068493150685, 0.4931506849315], 0.7721899043: [0.3013698630137, 0.6986301369863], 0.24488647026: [0.041095890411, 0.958904109589], 0.78795271158: [0.2739726027397, 0.7260273972603], 0.12441358604: [0.5479452054795, 0.4520547945205], 0.80108838431: [0.6027397260274, 0.3972602739726], 0.80371551886: [0.5890410958904, 0.4109589041096], 0.03809345093: [0.0547945205479, 0.9452054794521], 0.75042221805: [0.0547945205479, 0.9452054794521], 0.83261399887: [0.0547945205479, 0.9452054794521], 0.91443047476: [0.6849315068493, 0.3150684931507], 0.32707825108: [0.041095890411, 0.958904109589], 0.86413961344: [0.5479452054795, 0.4520547945205], 0.42240570464: [0.5753424657534, 0.4246575342466], 0.34284105836: [0.1643835616438, 0.8356164383562], 0.67160818165: [0.1643835616438, 0.8356164383562], 0.17470444736: [0.3150684931507, 0.6849315068493], 0.50722462: [0.1643835616438, 0.8356164383562], 0.02233064365: [0.1369863013699, 0.8630136986301], 0.52036029274: [0.013698630137, 0.986301369863], 0.92456370801: [0.7808219178082, 0.2191780821918], 0.182585851: [0.0958904109589, 0.9041095890411], 0.36648526928: [0.3150684931507, 0.6849315068493], 0.53875023457: [0.0958904109589, 0.9041095890411], 0.55451304185: [0.6027397260274, 0.3972602739726], 0.56764871458: [0.3424657534247, 0.6575342465753], 0.97185212986: [0.027397260274, 0.972602739726], 0.93844999062: [0.0821917808219, 0.9178082191781], 0.19834865829: [0.6027397260274, 0.3972602739726], 0.59917432914: [0.6438356164384, 0.3561643835616], 0.40326515294: [0.3424657534247, 0.6575342465753], 0.61493713642: [0.8767123287671, 0.1232876712329], 0.20623006193: [0.2602739726027, 0.7397260273973], 0.6306999437: [0.7671232876712, 0.2328767123288], 0.64383561644: [0.0], 0.42690936386: [0.5342465753425, 0.4657534246575], 0.4347907675: [0.6438356164384, 0.3561643835616], 0.02758491274: [0.6301369863014, 0.3698630136986], 0.45055357478: [0.8767123287671, 0.1232876712329], 0.11428035279: [0.1506849315068, 0.8493150684932], 0.7200225183: [0.7534246575342, 0.2465753424658], 0.23250140739: [0.5616438356164, 0.4383561643836], 0.0591105273: [0.1917808219178, 0.8082191780822], 0.76205667105: [0.1369863013699, 0.8630136986301], 0.27866391443: [0.1506849315068, 0.8493150684932], 0.76731094014: [0.6301369863014, 0.3698630136986], 0.28654531807: [0.7945205479452, 0.2054794520548], 0.12216175643: [0.7945205479452, 0.2054794520548], 0.78044661287: [0.5616438356164, 0.4383561643836], 0.29442672171: [0.7808219178082, 0.2191780821918], 0.24826421467: [0.1095890410959, 0.8904109589041], 0.79620942015: [0.1095890410959, 0.8904109589041], 0.07524863952: [0.7808219178082, 0.2191780821918], 0.83524113342: [0.5616438356164, 0.4383561643836], 0.03959467067: [0.8767123287671, 0.1232876712329], 0.31807093263: [0.5205479452055, 0.4794520547945], 0.45655845374: [0.0958904109589, 0.9041095890411], 0.87239632201: [0.1780821917808, 0.8219178082192], 0.88815912929: [0.5753424657534, 0.4246575342466], 0.89078626384: [0.1643835616438, 0.8356164383562], 0.34696941265: [0.0958904109589, 0.9041095890411], 0.50234565585: [0.5890410958904, 0.4109589041096], 0.17808219178: [0.0], 0.98123475324: [0.1369863013699, 0.8630136986301], 0.36273221993: [0.6027397260274, 0.3972602739726], 0.53124413586: [0.0547945205479, 0.9452054794521], 0.53387127041: [0.5616438356164, 0.4383561643836], 0.37061362357: [0.2602739726027, 0.7397260273973], 0.95121035842: [0.6575342465753, 0.3424657534247], 0.37849502721: [0.1369863013699, 0.8630136986301], 0.56276975042: [0.5479452054795, 0.4520547945205], 0.26365171702: [0.5068493150685, 0.4931506849315], 0.68924751361: [0.1917808219178, 0.8082191780822], 0.19647213361: [0.1506849315068, 0.8493150684932], 0.39425783449: [0.0547945205479, 0.9452054794521], 0.05010320886: [0.0684931506849, 0.9315068493151], 0.60743103772: [0.1506849315068, 0.8493150684932], 0.20435353725: [0.7945205479452, 0.2054794520548], 0.623193845: [0.7808219178082, 0.2191780821918], 0.62582097955: [0.1780821917808, 0.8219178082192], 0.21223494089: [0.7808219178082, 0.2191780821918], 0.61306061175: [0.3150684931507, 0.6849315068493], 0.67048226684: [0.027397260274, 0.972602739726], 0.43891912179: [0.7671232876712, 0.2328767123288], 0.69938074686: [0.2602739726027, 0.7397260273973], 0.12629011072: [0.5205479452055, 0.4794520547945], 0.06511540627: [0.3150684931507, 0.6849315068493], 0.26177519234: [0.3287671232877, 0.6712328767123], 0.26965659598: [0.1780821917808, 0.8219178082192], 0.47044473635: [0.1506849315068, 0.8493150684932], 0.7466691687: [0.0821917808219, 0.9178082191781], 0.00431600676: [0.8082191780822, 0.1917808219178], 0.76243197598: [0.0684931506849, 0.9315068493151], 0.142052918: [0.3013698630137, 0.6986301369863], 0.07299680991: [0.0958904109589, 0.9041095890411], 0.79395759054: [0.2876712328767, 0.7123287671233], 0.12103584162: [0.5753424657534, 0.4246575342466], 0.61793957591: [0.3287671232877, 0.6712328767123], 0.80709326328: [0.7945205479452, 0.2054794520548], 0.30643647964: [0.3013698630137, 0.6986301369863], 0.59842371927: [0.1780821917808, 0.8219178082192], 0.15781572528: [0.2739726027397, 0.7260273972603], 0.83861887784: [0.5205479452055, 0.4794520547945], 0.32219928692: [0.2739726027397, 0.7260273972603], 0.85438168512: [0.3013698630137, 0.6986301369863], 0.86751735785: [0.0958904109589, 0.9041095890411], 0.3379620942: [0.5890410958904, 0.4109589041096], 0.88328016513: [0.6027397260274, 0.3972602739726], 0.34584349784: [0.5068493150685, 0.4931506849315], 0.89904297242: [0.1369863013699, 0.8630136986301], 0.87840120098: [0.1095890410959, 0.8904109589041], 0.9148057797: [0.0547945205479, 0.9452054794521], 0.18408707075: [0.3424657534247, 0.6575342465753], 0.92719084256: [0.1780821917808, 0.8219178082192], 0.94633139426: [0.5479452054795, 0.4520547945205], 0.95946706699: [0.7671232876712, 0.2328767123288], 0.19196847439: [0.6301369863014, 0.3698630136986], 0.57365359355: [0.041095890411, 0.958904109589], 0.39050478514: [0.0821917808219, 0.9178082191781], 0.58941640083: [0.1643835616438, 0.8356164383562], 0.39838618878: [0.5479452054795, 0.4520547945205], 0.60255207356: [0.013698630137, 0.986301369863], 0.40626759242: [0.0684931506849, 0.9315068493151], 0.10189528992: [0.3424657534247, 0.6575342465753], 0.62094201539: [0.0958904109589, 0.9041095890411], 0.94295364984: [0.5753424657534, 0.4246575342466], 0.6498404954: [0.3424657534247, 0.6575342465753], 0.94558078439: [0.1643835616438, 0.8356164383562], 0.43779320698: [0.2876712328767, 0.7123287671233], 0.68136610996: [0.6438356164384, 0.3561643835616], 0.25014073935: [0.6164383561644, 0.3835616438356], 0.22612122349: [0.0821917808219, 0.9178082191781], 0.25802214299: [0.5753424657534, 0.4246575342466], 0.72602739726: [0.0], 0.01670106962: [0.5205479452055, 0.4794520547945], 0.27378495027: [0.013698630137, 0.986301369863], 0.05948583224: [0.1506849315068, 0.8493150684932], 0.28166635391: [0.7534246575342, 0.2465753424658], 0.24188403078: [0.0684931506849, 0.9315068493151], 0.69712891725: [0.8767123287671, 0.1232876712329], 0.1229123663: [0.5616438356164, 0.4383561643836], 0.49821730156: [0.3013698630137, 0.6986301369863], 0.57027584913: [0.1369863013699, 0.8630136986301], 0.80484143367: [0.6849315068493, 0.3150684931507], 0.72264965284: [0.3150684931507, 0.6849315068493], 0.8371176581: [0.6712328767123, 0.3287671232877], 0.03996997561: [0.7945205479452, 0.2054794520548], 0.84950272096: [0.6301369863014, 0.3698630136986], 0.16382060424: [0.2876712328767, 0.7123287671233], 0.8626383937: [0.5616438356164, 0.4383561643836], 0.86526552824: [0.5342465753425, 0.4657534246575], 0.08388065303: [0.1095890410959, 0.8904109589041], 0.71289172453: [0.7671232876712, 0.2328767123288], 0.34209044849: [0.5616438356164, 0.4383561643836], 0.3240758116: [0.0684931506849, 0.9315068493151], 0.50572340026: [0.7945205479452, 0.2054794520548], 0.17958341152: [0.3287671232877, 0.6712328767123], 0.52411334209: [0.6164383561644, 0.3835616438356], 0.53724901483: [0.5205479452055, 0.4794520547945], 0.26327641209: [0.5205479452055, 0.4794520547945], 0.55301182211: [0.3013698630137, 0.6986301369863], 0.56877462939: [0.2739726027397, 0.7260273972603], 0.09701632577: [0.5479452054795, 0.4520547945205], 0.58191030212: [0.6027397260274, 0.3972602739726], 0.9861137174: [0.013698630137, 0.986301369863], 0.39726027397: [0.0], 0.5976731094: [0.1369863013699, 0.8630136986301], 0.88890973916: [0.8767123287671, 0.1232876712329], 0.23400262714: [0.5479452054795, 0.4520547945205], 0.61343591668: [0.0547945205479, 0.9452054794521], 0.20585475699: [0.1643835616438, 0.8356164383562], 0.10489772941: [0.0684931506849, 0.9315068493151], 0.64496153124: [0.5479452054795, 0.4520547945205], 0.46556577219: [0.013698630137, 0.986301369863], 0.81685119159: [0.1369863013699, 0.8630136986301], 0.02720960781: [0.013698630137, 0.986301369863], 0.44192156127: [0.6164383561644, 0.3835616438356], 0.68962281854: [0.1506849315068, 0.8493150684932], 0.44980296491: [0.5753424657534, 0.4246575342466], 0.70538562582: [0.7808219178082, 0.2191780821918], 0.70801276037: [0.1780821917808, 0.8219178082192], 0.12779133046: [0.0958904109589, 0.9041095890411], 0.88966034903: [0.027397260274, 0.972602739726], 0.00356539689: [0.6164383561644, 0.3835616438356], 0.95383749296: [0.1369863013699, 0.8630136986301], 0.47344717583: [0.7534246575342, 0.2465753424658], 0.75267404766: [0.027397260274, 0.972602739726], 0.2400075061: [0.2739726027397, 0.7260273972603], 0.14355413774: [0.6027397260274, 0.3972602739726], 0.78157252768: [0.2602739726027, 0.7397260273973], 0.29367611184: [0.3424657534247, 0.6575342465753], 0.30155751548: [0.6301369863014, 0.3698630136986], 0.15143554138: [0.2602739726027, 0.7397260273973], 0.94483017452: [0.5616438356164, 0.4383561643836], 0.0388440608: [0.5753424657534, 0.4246575342466], 0.82886094952: [0.0821917808219, 0.9178082191781], 0.31732032276: [0.5342465753425, 0.4657534246575], 0.8446237568: [0.0684931506849, 0.9315068493151], 0.3252017264: [0.6438356164384, 0.3561643835616], 0.42165509476: [0.0547945205479, 0.9452054794521], 0.04147119535: [0.1643835616438, 0.8356164383562], 0.7785700882: [0.5753424657534, 0.4246575342466], 0.87614937136: [0.2876712328767, 0.7123287671233], 0.34096453368: [0.8767123287671, 0.1232876712329], 0.8892850441: [0.7945205479452, 0.2054794520548], 0.08688309251: [0.1506849315068, 0.8493150684932], 0.5008444361: [0.7534246575342, 0.2465753424658], 0.50347157065: [0.3150684931507, 0.6849315068493], 0.17770688685: [0.5616438356164, 0.4383561643836], 0.9211859636: [0.5068493150685, 0.4931506849315], 0.50797522987: [0.5479452054795, 0.4520547945205], 0.02270594858: [0.0684931506849, 0.9315068493151], 0.93657346594: [0.3013698630137, 0.6986301369863], 0.54813285795: [0.6301369863014, 0.3698630136986], 0.95233627322: [0.2739726027397, 0.7260273972603], 0.09476449615: [0.7945205479452, 0.2054794520548], 0.56389566523: [0.5342465753425, 0.4657534246575], 0.9680990805: [0.5890410958904, 0.4109589041096], 0.19346969413: [0.1095890410959, 0.8904109589041], 0.57965847251: [0.1917808219178, 0.8082191780822], 0.99699756052: [0.0547945205479, 0.9452054794521], 0.80221429912: [0.7534246575342, 0.2465753424658], 0.4092700319: [0.041095890411, 0.958904109589], 0.67273409645: [0.6712328767123, 0.3287671232877], 0.37136423344: [0.3287671232877, 0.6712328767123], 0.42503283918: [0.1643835616438, 0.8356164383562], 0.65584537437: [0.041095890411, 0.958904109589], 0.10790016889: [0.041095890411, 0.958904109589], 0.6689810471: [0.5753424657534, 0.4246575342466], 0.97485456934: [0.5342465753425, 0.4657534246575], 0.2197410396: [0.7671232876712, 0.2328767123288], 0.68474385438: [0.013698630137, 0.986301369863], 0.02796021768: [0.7671232876712, 0.2328767123288], 0.70313379621: [0.0958904109589, 0.9041095890411], 0.25314317883: [0.6027397260274, 0.3972602739726], 0.26102458247: [0.2602739726027, 0.7397260273973], 0.73203227622: [0.3424657534247, 0.6575342465753], 0.26890598611: [0.1369863013699, 0.8630136986301], 0.05986113717: [0.3013698630137, 0.6986301369863], 0.76355789079: [0.6438356164384, 0.3561643835616], 0.2846687934: [0.0547945205479, 0.9452054794521], 0.48545693376: [0.3424657534247, 0.6575342465753], 0.35560142616: [0.2876712328767, 0.7123287671233], 0.01820228936: [0.0958904109589, 0.9041095890411], 0.79508350535: [0.7671232876712, 0.2328767123288], 0.1495590167: [0.7945205479452, 0.2054794520548], 0.80821917808: [0.0], 0.79921185964: [0.1506849315068, 0.8493150684932], 0.15744042034: [0.7808219178082, 0.2191780821918], 0.04034528054: [0.027397260274, 0.972602739726], 0.85288046538: [0.6164383561644, 0.3835616438356], 0.97297804466: [0.1643835616438, 0.8356164383562], 0.88440607994: [0.7534246575342, 0.2465753424658], 0.71739538375: [0.3013698630137, 0.6986301369863], 0.36085569525: [0.1506849315068, 0.8493150684932], 0.52749108651: [0.0821917808219, 0.9178082191781], 0.93169450178: [0.6301369863014, 0.3698630136986], 0.36873709889: [0.7945205479452, 0.2054794520548], 0.54325389379: [0.0684931506849, 0.9315068493151], 0.94745730906: [0.5342465753425, 0.4657534246575], 0.01444924001: [0.2602739726027, 0.7397260273973], 0.9605929818: [0.1095890410959, 0.8904109589041], 0.19159316945: [0.013698630137, 0.986301369863], 0.57477950835: [0.2876712328767, 0.7123287671233], 0.58791518109: [0.7945205479452, 0.2054794520548], 0.59054231563: [0.3287671232877, 0.6712328767123], 0.19947457309: [0.7534246575342, 0.2465753424658], 0.40026271346: [0.5205479452055, 0.4794520547945], 0.06736723588: [0.7945205479452, 0.2054794520548], 0.63520360293: [0.3013698630137, 0.6986301369863], 0.42127978983: [0.3150684931507, 0.6849315068493], 0.65096641021: [0.2739726027397, 0.7260273972603], 0.42916119347: [0.0958904109589, 0.9041095890411], 0.33946331394: [0.0547945205479, 0.9452054794521], 0.66672921749: [0.5890410958904, 0.4109589041096], 0.67986489022: [0.1369863013699, 0.8630136986301], 0.74892099831: [0.5890410958904, 0.4109589041096], 0.44492400075: [0.6027397260274, 0.3972602739726], 0.6956276975: [0.0547945205479, 0.9452054794521], 0.45280540439: [0.2602739726027, 0.7397260273973], 0.1292925502: [0.3424657534247, 0.6575342465753], 0.46068680803: [0.1369863013699, 0.8630136986301], 0.72715331207: [0.5479452054795, 0.4520547945205], 0.2336273222: [0.2602739726027, 0.7397260273973], 0.76768624507: [0.7671232876712, 0.2328767123288], 0.11878401201: [0.5890410958904, 0.4109589041096], 0.24150872584: [0.1369863013699, 0.8630136986301], 0.77181459936: [0.1506849315068, 0.8493150684932], 0.28879714768: [0.5479452054795, 0.4520547945205], 0.06136235692: [0.6027397260274, 0.3972602739726], 0.78757740664: [0.7808219178082, 0.2191780821918], 0.07449802965: [0.3424657534247, 0.6575342465753], 0.69412647776: [0.5890410958904, 0.4109589041096], 0.50835053481: [0.3287671232877, 0.6712328767123], 0.83486582849: [0.027397260274, 0.972602739726], 0.85588290486: [0.6027397260274, 0.3972602739726], 0.28917245262: [0.3287671232877, 0.6712328767123], 0.32820416589: [0.2876712328767, 0.7123287671233], 0.8637643085: [0.2602739726027, 0.7397260273973], 0.04184650028: [0.2602739726027, 0.7397260273973], 0.17132670295: [0.0821917808219, 0.9178082191781], 0.35785325577: [0.1095890410959, 0.8904109589041], 0.50684931507: [0.0], 0.17920810659: [0.5479452054795, 0.4520547945205], 0.92681553762: [0.0684931506849, 0.9315068493151], 0.01144680053: [0.5753424657534, 0.4246575342466], 0.18708951023: [0.0684931506849, 0.9315068493151], 0.97260273973: [0.0], 0.95834115219: [0.2876712328767, 0.7123287671233], 0.09551510602: [0.5616438356164, 0.4383561643836], 0.97147682492: [0.7945205479452, 0.2054794520548], 0.38862826046: [0.3013698630137, 0.6986301369863], 0.58303621693: [0.7534246575342, 0.2465753424658], 0.3965096641: [0.027397260274, 0.972602739726], 0.40439106774: [0.2739726027397, 0.7260273972603], 0.63032463877: [0.6301369863014, 0.3698630136986], 0.42015387502: [0.5890410958904, 0.4109589041096], 0.64608744605: [0.5342465753425, 0.4657534246575], 0.42803527866: [0.5068493150685, 0.4931506849315], 0.66185025333: [0.1917808219178, 0.8082191780822], 0.01407393507: [0.1643835616438, 0.8356164383562], 0.91105273034: [0.0821917808219, 0.9178082191781], 0.95458810283: [0.1780821917808, 0.8219178082192], 0.1165321824: [0.0821917808219, 0.9178082191781], 0.73803715519: [0.041095890411, 0.958904109589], 0.47269656596: [0.0821917808219, 0.9178082191781], 0.75117282792: [0.5753424657534, 0.4246575342466], 0.75379996247: [0.1643835616438, 0.8356164383562], 0.4805779696: [0.5479452054795, 0.4520547945205], 0.7669356352: [0.013698630137, 0.986301369863], 0.28767123288: [0.0], 0.00919497091: [0.5890410958904, 0.4109589041096], 0.15106023644: [0.1643835616438, 0.8356164383562], 0.7988365547: [0.1917808219178, 0.8082191780822], 0.07750046913: [0.0684931506849, 0.9315068493151], 0.78532557703: [0.0958904109589, 0.9041095890411], 0.84574967161: [0.6438356164384, 0.3561643835616], 0.04072058548: [0.5616438356164, 0.4383561643836], 0.86151247889: [0.8767123287671, 0.1232876712329], 0.33233252017: [0.6164383561644, 0.3835616438356], 0.84875211109: [0.2876712328767, 0.7123287671233], 0.34021392381: [0.5753424657534, 0.4246575342466], 0.58453743667: [0.5890410958904, 0.4109589041096], 0.8904109589: [0.0], 0.50459748546: [0.5753424657534, 0.4246575342466], 0.35597673109: [0.013698630137, 0.986301369863], 0.87727528617: [0.7671232876712, 0.2328767123288], 0.36385813473: [0.7534246575342, 0.2465753424658], 0.53349596547: [0.027397260274, 0.972602739726], 0.18521298555: [0.2739726027397, 0.7260273972603], 0.99399512104: [0.7534246575342, 0.2465753424658], 0.56239444549: [0.2602739726027, 0.7397260273973], 0.96659786076: [0.7534246575342, 0.2465753424658], 0.86451491837: [0.3287671232877, 0.6712328767123], 0.89266278852: [0.5342465753425, 0.4657534246575], 0.20097579283: [0.5890410958904, 0.4109589041096], 0.60968286733: [0.0821917808219, 0.9178082191781], 0.05122912366: [0.6438356164384, 0.3561643835616], 0.62544567461: [0.0684931506849, 0.9315068493151], 0.20885719647: [0.5068493150685, 0.4931506849315], 0.05047851379: [0.1780821917808, 0.8219178082192], 0.65697128917: [0.2876712328767, 0.7123287671233], 0.67010696191: [0.7945205479452, 0.2054794520548], 0.44004503659: [0.1095890410959, 0.8904109589041], 0.61606305123: [0.5616438356164, 0.4383561643836], 0.68849690373: [0.6164383561644, 0.3835616438356], 0.70163257647: [0.5205479452055, 0.4794520547945], 0.03171326703: [0.1917808219178, 0.8082191780822], 0.64421092137: [0.1643835616438, 0.8356164383562], 0.93920060049: [0.7534246575342, 0.2465753424658], 0.23888159129: [0.3424657534247, 0.6575342465753], 0.73315819103: [0.2739726027397, 0.7260273972603], 0.23512854194: [0.5342465753425, 0.4657534246575], 0.74629386376: [0.6027397260274, 0.3972602739726], 0.13867517358: [0.1095890410959, 0.8904109589041], 0.4794520548: [0.0], 0.24300994558: [0.6438356164384, 0.3561643835616], 0.77781947833: [0.0547945205479, 0.9452054794521], 0.96960030024: [0.0547945205479, 0.9452054794521], 0.06173766185: [0.0821917808219, 0.9178082191781], 0.29968099081: [0.041095890411, 0.958904109589], 0.61756427097: [0.5479452054795, 0.4520547945205], 0.80934509289: [0.5479452054795, 0.4520547945205], 0.31544379809: [0.1643835616438, 0.8356164383562], 0.90917620567: [0.3013698630137, 0.6986301369863], 0.85400638018: [0.1506849315068, 0.8493150684932], 0.16494651905: [0.7671232876712, 0.2328767123288], 0.86976918747: [0.7808219178082, 0.2191780821918], 0.04222180522: [0.5479452054795, 0.4520547945205], 0.33908800901: [0.3150684931507, 0.6849315068493], 0.93582285607: [0.1917808219178, 0.8082191780822], 0.51285419403: [0.3424657534247, 0.6575342465753], 0.91705760931: [0.027397260274, 0.972602739726], 0.9223118784: [0.0958904109589, 0.9041095890411], 0.02308125352: [0.1780821917808, 0.8219178082192], 0.54437980859: [0.6438356164384, 0.3561643835616], 0.37586789266: [0.3424657534247, 0.6575342465753], 0.49746669169: [0.1917808219178, 0.8082191780822], 0.56014261588: [0.8767123287671, 0.1232876712329], 0.09626571589: [0.1643835616438, 0.8356164383562], 0.57590542316: [0.7671232876712, 0.2328767123288], 0.72940514168: [0.5068493150685, 0.4931506849315], 0.58904109589: [0.0], 0.99324451117: [0.0821917808219, 0.9178082191781], 0.39951210358: [0.5342465753425, 0.4657534246575], 0.43404015763: [0.1780821917808, 0.8219178082192], 0.40739350723: [0.6438356164384, 0.3561643835616], 0.2069806718: [0.3287671232877, 0.6712328767123], 0.41527491087: [0.1917808219178, 0.8082191780822], 0.42315631451: [0.8767123287671, 0.1232876712329], 0.99286920623: [0.6027397260274, 0.3972602739726], 0.80859448302: [0.1643835616438, 0.8356164383562], 0.21486207544: [0.1780821917808, 0.8219178082192], 0.66522799775: [0.7534246575342, 0.2465753424658], 0.10940138863: [0.013698630137, 0.986301369863], 0.22274347908: [0.6164383561644, 0.3835616438356], 0.55226121224: [0.1917808219178, 0.8082191780822], 0.25126665416: [0.1506849315068, 0.8493150684932], 0.71251641959: [0.6301369863014, 0.3698630136986], 0.23062488272: [0.5753424657534, 0.4246575342466], 0.72827922687: [0.5342465753425, 0.4657534246575], 0.26702946144: [0.7808219178082, 0.2191780821918], 0.11728279227: [0.7534246575342, 0.2465753424658], 0.74141489961: [0.1095890410959, 0.8904109589041], 0.95909176206: [0.6301369863014, 0.3698630136986], 0.14468005254: [0.7534246575342, 0.2465753424658], 0.3837492963: [0.6301369863014, 0.3698630136986], 0.70013135673: [0.6712328767123, 0.3287671232877], 0.82022893601: [0.041095890411, 0.958904109589], 0.55563895665: [0.7534246575342, 0.2465753424658], 0.83336460875: [0.5753424657534, 0.4246575342466], 0.31957215237: [0.0958904109589, 0.9041095890411], 0.84912741603: [0.013698630137, 0.986301369863], 0.04109589041: [0.0], 0.33533495966: [0.6027397260274, 0.3972602739726], 0.25689622819: [0.3150684931507, 0.6849315068493], 0.47832613999: [0.7945205479452, 0.2054794520548], 0.3432163633: [0.2602739726027, 0.7397260273973], 0.60705573278: [0.1917808219178, 0.8082191780822], 0.35109776694: [0.1369863013699, 0.8630136986301], 0.25952336273: [0.027397260274, 0.972602739726], 0.92794145243: [0.6438356164384, 0.3561643835616], 0.09138675174: [0.5890410958904, 0.4109589041096], 0.18671420529: [0.1369863013699, 0.8630136986301], 0.55263651717: [0.1506849315068, 0.8493150684932], 0.02383186339: [0.6438356164384, 0.3561643835616], 0.56839932445: [0.7808219178082, 0.2191780821918], 0.26477763183: [0.0958904109589, 0.9041095890411], 0.58678926628: [0.5753424657534, 0.4246575342466], 0.09926815538: [0.5068493150685, 0.4931506849315], 0.20247701257: [0.0547945205479, 0.9452054794521], 0.61568774629: [0.027397260274, 0.972602739726], 0.41152186151: [0.7671232876712, 0.2328767123288], 0.98986676675: [0.6164383561644, 0.3835616438356], 0.64458622631: [0.2602739726027, 0.7397260273973], 0.64721336086: [0.5068493150685, 0.4931506849315], 0.75680240195: [0.5068493150685, 0.4931506849315], 0.7530493526: [0.5616438356164, 0.4383561643836], 0.0069431413: [0.0821917808219, 0.9178082191781], 0.69187464815: [0.0821917808219, 0.9178082191781], 0.45092887972: [0.7945205479452, 0.2054794520548], 0.70763745543: [0.0684931506849, 0.9315068493151], 0.03208857197: [0.1506849315068, 0.8493150684932], 0.45881028336: [0.7808219178082, 0.2191780821918], 0.13229498968: [0.0684931506849, 0.9315068493151], 0.73916306999: [0.2876712328767, 0.7123287671233], 0.06811784575: [0.5616438356164, 0.4383561643836], 0.75229874273: [0.7945205479452, 0.2054794520548], 0.27903921937: [0.3013698630137, 0.6986301369863], 0.12028523175: [0.0547945205479, 0.9452054794521], 0.28692062301: [0.027397260274, 0.972602739726], 0.78382435729: [0.5205479452055, 0.4794520547945], 0.29480202665: [0.2739726027397, 0.7260273972603], 0.48395571402: [0.0958904109589, 0.9041095890411], 0.94670669919: [0.6712328767123, 0.3287671232877], 0.81272283731: [0.0958904109589, 0.9041095890411], 0.31056483393: [0.5890410958904, 0.4109589041096], 0.82848564459: [0.6027397260274, 0.3972602739726], 0.31844623757: [0.5068493150685, 0.4931506849315], 0.84424845187: [0.1369863013699, 0.8630136986301], 0.64158378683: [0.5753424657534, 0.4246575342466], 0.86001125915: [0.0547945205479, 0.9452054794521], 0.04259711015: [0.3287671232877, 0.6712328767123], 0.89153687371: [0.5479452054795, 0.4520547945205], 0.78419966223: [0.5068493150685, 0.4931506849315], 0.90467254644: [0.7671232876712, 0.2328767123288], 0.08913492212: [0.0821917808219, 0.9178082191781], 0.518859073: [0.041095890411, 0.958904109589], 0.36310752486: [0.0821917808219, 0.9178082191781], 0.53462188028: [0.1643835616438, 0.8356164383562], 0.93619816101: [0.1506849315068, 0.8493150684932], 0.3709889285: [0.5479452054795, 0.4520547945205], 0.54775755301: [0.013698630137, 0.986301369863], 0.19009194971: [0.041095890411, 0.958904109589], 0.56614749484: [0.0958904109589, 0.9041095890411], 0.89341339839: [0.5205479452055, 0.4794520547945], 0.6678551323: [0.6849315068493, 0.3150684931507], 0.59504597486: [0.3424657534247, 0.6575342465753], 0.99662225558: [0.6849315068493, 0.3150684931507], 0.41039594671: [0.2876712328767, 0.7123287671233], 0.62657158942: [0.6438356164384, 0.3561643835616], 0.20848189154: [0.5205479452055, 0.4794520547945], 0.54362919872: [0.1780821917808, 0.8219178082192], 0.05310564834: [0.041095890411, 0.958904109589], 0.42615875399: [0.3287671232877, 0.6712328767123], 0.65809720398: [0.7671232876712, 0.2328767123288], 0.67123287671: [0.0], 0.94520547945: [0.0], 0.1101519985: [0.7671232876712, 0.2328767123288], 0.22424469882: [0.3013698630137, 0.6986301369863], 0.25426909364: [0.7534246575342, 0.2465753424658], 0.71589416401: [0.6164383561644, 0.3835616438356], 0.23212610246: [0.027397260274, 0.972602739726], 0.47082004128: [0.3013698630137, 0.6986301369863], 0.74741977857: [0.7534246575342, 0.2465753424658], 0.75004691312: [0.6849315068493, 0.3150684931507], 0.47870144492: [0.027397260274, 0.972602739726], 0.48658284856: [0.2739726027397, 0.7260273972603], 0.14618127228: [0.5890410958904, 0.4109589041096], 0.53086883093: [0.3150684931507, 0.6849315068493], 0.79470820041: [0.6301369863014, 0.3698630136986], 0.00469131169: [0.1506849315068, 0.8493150684932], 0.80784387315: [0.5616438356164, 0.4383561643836], 0.81047100769: [0.5342465753425, 0.4657534246575], 0.15406267592: [0.5068493150685, 0.4931506849315], 0.82360668043: [0.1095890410959, 0.8904109589041], 0.31469318822: [0.5616438356164, 0.4383561643836], 0.3304559955: [0.1095890410959, 0.8904109589041], 0.58040908238: [0.3013698630137, 0.6986301369863], 0.89979358229: [0.1780821917808, 0.8219178082192], 0.90242071683: [0.041095890411, 0.958904109589], 0.2591480578: [0.7945205479452, 0.2054794520548], 0.18033402139: [0.5342465753425, 0.4657534246575], 0.52974291612: [0.5890410958904, 0.4109589041096], 0.3698630137: [0.0], 0.54287858885: [0.1369863013699, 0.8630136986301], 0.18821542503: [0.6438356164384, 0.3561643835616], 0.55864139613: [0.0547945205479, 0.9452054794521], 0.70463501595: [0.3424657534247, 0.6575342465753], 0.97860761869: [0.6575342465753, 0.3424657534247], 0.19609682867: [0.1917808219178, 0.8082191780822], 0.4933383374: [0.6301369863014, 0.3698630136986], 0.33308313004: [0.1917808219178, 0.8082191780822], 0.20397823231: [0.8767123287671, 0.1232876712329], 0.414524301: [0.6164383561644, 0.3835616438356], 0.63482829799: [0.1506849315068, 0.8493150684932], 0.62507036968: [0.1369863013699, 0.8630136986301], 0.23587915181: [0.5205479452055, 0.4794520547945], 0.65059110527: [0.7808219178082, 0.2191780821918], 0.43816851192: [0.013698630137, 0.986301369863], 0.44604991556: [0.7534246575342, 0.2465753424658], 0.69787952712: [0.027397260274, 0.972602739726], 0.61981610058: [0.5068493150685, 0.4931506849315], 0.11315443798: [0.6164383561644, 0.3835616438356], 0.75192343779: [0.8767123287671, 0.1232876712329], 0.0324638769: [0.3013698630137, 0.6986301369863], 0.72677800713: [0.2602739726027, 0.7397260273973], 0.26627885157: [0.3424657534247, 0.6575342465753], 0.27416025521: [0.6301369863014, 0.3698630136986], 0.06886845562: [0.1643835616438, 0.8356164383562], 0.89191217865: [0.6712328767123, 0.3287671232877], 0.14167761306: [0.1506849315068, 0.8493150684932], 0.77406642897: [0.0821917808219, 0.9178082191781], 0.28992306249: [0.5342465753425, 0.4657534246575], 0.24601238506: [0.2876712328767, 0.7123287671233], 0.78982923625: [0.0684931506849, 0.9315068493151], 0.29780446613: [0.6438356164384, 0.3561643835616], 0.06248827172: [0.7534246575342, 0.2465753424658], 0.84237192719: [0.7808219178082, 0.2191780821918], 0.30568586977: [0.1917808219178, 0.8082191780822], 0.35147307187: [0.0684931506849, 0.9315068493151], 0.31356727341: [0.8767123287671, 0.1232876712329], 0.83449052355: [0.7945205479452, 0.2054794520548], 0.16006755489: [0.1780821917808, 0.8219178082192], 0.08200412835: [0.013698630137, 0.986301369863], 0.32933008069: [0.7671232876712, 0.2328767123288], 0.86601613811: [0.5205479452055, 0.4794520547945], 0.16794895853: [0.6164383561644, 0.3835616438356], 0.29067367236: [0.5205479452055, 0.4794520547945], 0.88177894539: [0.3013698630137, 0.6986301369863], 0.89491461813: [0.0958904109589, 0.9041095890411], 0.89754175267: [0.2739726027397, 0.7260273972603], 0.17583036217: [0.5753424657534, 0.4246575342466], 0.50910114468: [0.5342465753425, 0.4657534246575], 0.91330455996: [0.5890410958904, 0.4109589041096], 0.089885532: [0.7534246575342, 0.2465753424658], 0.52486395196: [0.1917808219178, 0.8082191780822], 0.03096265716: [0.6164383561644, 0.3835616438356], 0.38187277163: [0.041095890411, 0.958904109589], 0.97372865453: [0.5479452054795, 0.4520547945205], 0.98686432727: [0.7671232876712, 0.2328767123288], 0.79958716457: [0.3013698630137, 0.6986301369863], 0.39763557891: [0.1643835616438, 0.8356164383562], 0.60105085382: [0.041095890411, 0.958904109589], 0.20210170764: [0.3150684931507, 0.6849315068493], 0.61418652655: [0.5753424657534, 0.4246575342466], 0.6168136611: [0.1643835616438, 0.8356164383562], 0.10302120473: [0.2739726027397, 0.7260273972603], 0.62994933383: [0.013698630137, 0.986301369863], 0.94858322387: [0.5068493150685, 0.4931506849315], 0.20998311128: [0.0958904109589, 0.9041095890411], 0.64833927566: [0.0958904109589, 0.9041095890411], 0.94445486958: [0.027397260274, 0.972602739726], 0.68024019516: [0.0684931506849, 0.9315068493151], 0.67723775568: [0.3424657534247, 0.6575342465753], 0.94970913868: [0.0958904109589, 0.9041095890411], 0.22574591856: [0.6027397260274, 0.3972602739726], 0.70876337024: [0.6438356164384, 0.3561643835616], 0.25727153312: [0.0547945205479, 0.9452054794521], 0.45805967349: [0.3424657534247, 0.6575342465753], 0.72452617752: [0.8767123287671, 0.1232876712329], 0.13191968474: [0.1369863013699, 0.8630136986301], 0.46594107713: [0.6301369863014, 0.3698630136986], 0.7402889848: [0.7671232876712, 0.2328767123288], 0.03396509664: [0.6027397260274, 0.3972602739726], 0.75342465753: [0.0], 0.28091574404: [0.0821917808219, 0.9178082191781], 0.0718708951: [0.5068493150685, 0.4931506849315], 0.48958528805: [0.6438356164384, 0.3561643835616], 0.96547194596: [0.6027397260274, 0.3972602739726], 0.14768249203: [0.0547945205479, 0.9452054794521], 0.1240382811: [0.2602739726027, 0.7397260273973], 0.79808594483: [0.6164383561644, 0.3835616438356], 0.83599174329: [0.1643835616438, 0.8356164383562], 0.9733533496: [0.2602739726027, 0.7397260273973], 0.82961155939: [0.7534246575342, 0.2465753424658], 0.83223869394: [0.6849315068493, 0.3150684931507], 0.57703133796: [0.1095890410959, 0.8904109589041], 0.94070182023: [0.5890410958904, 0.4109589041096], 0.88703321449: [0.6849315068493, 0.3150684931507], 0.33345843498: [0.1506849315068, 0.8493150684932], 0.87689998124: [0.6301369863014, 0.3698630136986], 0.34133983862: [0.7945205479452, 0.2054794520548], 0.65321823982: [0.1780821917808, 0.8219178082192], 0.89003565397: [0.5616438356164, 0.4383561643836], 0.34922124226: [0.7808219178082, 0.2191780821918], 0.90579846125: [0.1095890410959, 0.8904109589041], 0.9084255958: [0.1917808219178, 0.8082191780822], 0.04447363483: [0.5068493150685, 0.4931506849315], 0.5199849878: [0.2876712328767, 0.7123287671233], 0.72490148245: [0.7945205479452, 0.2054794520548], 0.53312066054: [0.7945205479452, 0.2054794520548], 0.53574779508: [0.3287671232877, 0.6712328767123], 0.09288797148: [0.0547945205479, 0.9452054794521], 0.55151060236: [0.6164383561644, 0.3835616438356], 0.5646462751: [0.5205479452055, 0.4794520547945], 0.56126853068: [0.5616438356164, 0.4383561643836], 0.98461249765: [0.041095890411, 0.958904109589], 0.46744229687: [0.1095890410959, 0.8904109589041], 0.59617188966: [0.2739726027397, 0.7260273972603], 0.4017639332: [0.0958904109589, 0.9041095890411], 0.60930756239: [0.6027397260274, 0.3972602739726], 0.61193469694: [0.5890410958904, 0.4109589041096], 0.20547945206: [0.0], 0.41752674048: [0.6027397260274, 0.3972602739726], 0.64083317696: [0.0547945205479, 0.9452054794521], 0.6434603115: [0.5616438356164, 0.4383561643836], 0.42540814412: [0.2602739726027, 0.7397260273973], 0.43328954776: [0.1369863013699, 0.8630136986301], 0.67235879152: [0.5479452054795, 0.4520547945205], 0.05498217302: [0.6301369863014, 0.3698630136986], 0.22386939388: [0.1506849315068, 0.8493150684932], 0.44905235504: [0.0547945205479, 0.9452054794521], 0.58566335147: [0.3150684931507, 0.6849315068493], 0.11390504785: [0.1917808219178, 0.8082191780822], 0.71702007881: [0.1506849315068, 0.8493150684932], 0.26139988741: [0.5479452054795, 0.4520547945205], 0.23175079752: [0.7945205479452, 0.2054794520548], 0.7327828861: [0.7808219178082, 0.2191780821918], 0.13529742916: [0.041095890411, 0.958904109589], 0.06961906549: [0.5479452054795, 0.4520547945205], 0.23963220116: [0.7808219178082, 0.2191780821918], 0.89641583787: [0.6575342465753, 0.3424657534247], 0.12178645149: [0.8767123287671, 0.1232876712329], 0.90767498593: [0.6164383561644, 0.3835616438356], 0.78007130794: [0.027397260274, 0.972602739726], 0.49371364233: [0.7671232876712, 0.2328767123288], 0.30080690561: [0.2876712328767, 0.7123287671233], 0.80896978795: [0.2602739726027, 0.7397260273973], 0.15368737099: [0.5205479452055, 0.4794520547945], 0.0197035091: [0.3424657534247, 0.6575342465753], 0.32445111653: [0.1780821917808, 0.8219178082192], 0.8562582098: [0.0821917808219, 0.9178082191781], 0.08275473823: [0.7671232876712, 0.2328767123288], 0.87202101708: [0.0684931506849, 0.9315068493151], 0.16945017827: [0.3013698630137, 0.6986301369863], 0.04334772002: [0.5342465753425, 0.4657534246575], 0.91743291424: [0.5616438356164, 0.4383561643836], 0.90354663164: [0.2876712328767, 0.7123287671233], 0.17733158191: [0.027397260274, 0.972602739726], 0.91668230437: [0.7945205479452, 0.2054794520548], 0.36123100019: [0.3013698630137, 0.6986301369863], 0.52824169638: [0.7534246575342, 0.2465753424658], 0.36911240383: [0.027397260274, 0.972602739726], 0.94820791893: [0.5205479452055, 0.4794520547945], 0.1484331019: [0.5753424657534, 0.4246575342466], 0.96397072622: [0.3013698630137, 0.6986301369863], 0.57553011822: [0.6301369863014, 0.3698630136986], 0.97710639895: [0.0958904109589, 0.9041095890411], 0.39275661475: [0.5890410958904, 0.4109589041096], 0.5912929255: [0.5342465753425, 0.4657534246575], 0.36686057422: [0.0547945205479, 0.9452054794521], 0.40063801839: [0.5068493150685, 0.4931506849315], 0.60442859824: [0.1095890410959, 0.8904109589041], 0.21148433102: [0.3424657534247, 0.6575342465753], 0.8115969225: [0.5068493150685, 0.4931506849315], 0.94370425971: [0.8767123287671, 0.1232876712329], 0.91180334021: [0.7534246575342, 0.2465753424658], 0.21936573466: [0.6301369863014, 0.3698630136986], 0.68324263464: [0.041095890411, 0.958904109589], 0.44529930569: [0.0821917808219, 0.9178082191781], 0.69637830738: [0.5753424657534, 0.4246575342466], 0.69900544192: [0.1643835616438, 0.8356164383562], 0.45318070933: [0.5479452054795, 0.4520547945205], 0.71214111466: [0.013698630137, 0.986301369863], 0.2602739726: [0.0], 0.13342090449: [0.6438356164384, 0.3561643835616], 0.69262525802: [0.7534246575342, 0.2465753424658], 0.03434040158: [0.0821917808219, 0.9178082191781], 0.56314505536: [0.3287671232877, 0.6712328767123], 0.14130230813: [0.1917808219178, 0.8082191780822], 0.31656971289: [0.3287671232877, 0.6712328767123], 0.49258772753: [0.2876712328767, 0.7123287671233], 0.79095515106: [0.6438356164384, 0.3561643835616], 0.14918371177: [0.8767123287671, 0.1232876712329], 0.3049352599: [0.6164383561644, 0.3835616438356], 0.82248076562: [0.7671232876712, 0.2328767123288], 0.31281666354: [0.5753424657534, 0.4246575342466], 0.78119722274: [0.1643835616438, 0.8356164383562], 0.83561643836: [0.0], 0.08050290861: [0.041095890411, 0.958904109589], 0.77369112404: [0.6027397260274, 0.3972602739726], 0.32857947082: [0.013698630137, 0.986301369863], 0.63933195722: [0.5890410958904, 0.4109589041096], 0.33646087446: [0.7534246575342, 0.2465753424658], 0.88027772565: [0.6164383561644, 0.3835616438356], 0.08575717771: [0.6164383561644, 0.3835616438356], 0.50759992494: [0.2602739726027, 0.7397260273973], 0.51022705949: [0.5068493150685, 0.4931506849315], 0.9350722462: [0.6164383561644, 0.3835616438356], 0.09363858135: [0.5753424657534, 0.4246575342466], 0.55488834678: [0.0821917808219, 0.9178082191781], 0.19121786452: [0.2876712328767, 0.7123287671233], 0.57065115406: [0.0684931506849, 0.9315068493151], 0.0121974104: [0.8767123287671, 0.1232876712329], 0.98799024207: [0.1095890410959, 0.8904109589041], 0.39688496904: [0.5616438356164, 0.4383561643836], 0.60217676863: [0.2876712328767, 0.7123287671233], 0.61531244136: [0.7945205479452, 0.2054794520548], 0.93131919685: [0.013698630137, 0.986301369863], 0.41264777632: [0.1095890410959, 0.8904109589041], 0.63370238319: [0.6164383561644, 0.3835616438356], 0.64683805592: [0.5205479452055, 0.4794520547945], 0.6626008632: [0.3013698630137, 0.6986301369863], 0.21748920998: [0.041095890411, 0.958904109589], 0.67836367048: [0.2739726027397, 0.7260273972603], 0.05535747795: [0.7671232876712, 0.2328767123288], 0.69149934322: [0.6027397260274, 0.3972602739726], 0.45205479452: [0.0], 0.7072621505: [0.1369863013699, 0.8630136986301], 0.11465565772: [0.3013698630137, 0.6986301369863], 0.72302495778: [0.0547945205479, 0.9452054794521], 0.72565209233: [0.5616438356164, 0.4383561643836], 0.23325201726: [0.1643835616438, 0.8356164383562], 0.97035091011: [0.5753424657534, 0.4246575342466], 0.27228373053: [0.041095890411, 0.958904109589], 0.01482454494: [0.5479452054795, 0.4520547945205], 0.75455057234: [0.5479452054795, 0.4520547945205], 0.86338900357: [0.1643835616438, 0.8356164383562], 0.48095327454: [0.3287671232877, 0.6712328767123], 0.28804653781: [0.1643835616438, 0.8356164383562], 0.12253706136: [0.027397260274, 0.972602739726], 0.49671608182: [0.6164383561644, 0.3835616438356], 0.76881215988: [0.1095890410959, 0.8904109589041], 0.07562394446: [0.2739726027397, 0.7260273972603], 0.81497466692: [0.7808219178082, 0.2191780821918], 0.15518859073: [0.0958904109589, 0.9041095890411], 0.31169074873: [0.3150684931507, 0.6849315068493], 0.77143929443: [0.1917808219178, 0.8082191780822], 0.90880090073: [0.1506849315068, 0.8493150684932], 0.86226308876: [0.027397260274, 0.972602739726], 0.77932069807: [0.8767123287671, 0.1232876712329], 0.17095139801: [0.6027397260274, 0.3972602739726], 0.89116156878: [0.2602739726027, 0.7397260273973], 0.34847063239: [0.3424657534247, 0.6575342465753], 0.92081065866: [0.5205479452055, 0.4794520547945], 0.50534809533: [0.8767123287671, 0.1232876712329], 0.35635203603: [0.6301369863014, 0.3698630136986], 0.17883280165: [0.2602739726027, 0.7397260273973], 0.52111090261: [0.7671232876712, 0.2328767123288], 0.91067742541: [0.6027397260274, 0.3972602739726], 0.53424657534: [0.0], 0.91930943892: [0.6712328767123, 0.3287671232877], 0.37211484331: [0.5342465753425, 0.4657534246575], 0.9542127979: [0.0684931506849, 0.9315068493151], 0.37999624695: [0.6438356164384, 0.3561643835616], 0.09664102083: [0.2602739726027, 0.7397260273973], 0.38787765059: [0.1917808219178, 0.8082191780822], 0.98573841246: [0.2876712328767, 0.7123287671233], 0.39575905423: [0.8767123287671, 0.1232876712329], 0.99887408519: [0.7945205479452, 0.2054794520548], 0.01257271533: [0.7945205479452, 0.2054794520548], 0.6104334772: [0.7534246575342, 0.2465753424658], 0.67085757178: [0.5616438356164, 0.4383561643836], 0.20510414712: [0.5616438356164, 0.4383561643836], 0.10452242447: [0.1369863013699, 0.8630136986301], 0.47720022518: [0.5753424657534, 0.4246575342466], 0.65772189904: [0.6301369863014, 0.3698630136986], 0.05423156315: [0.2876712328767, 0.7123287671233], 0.67348470632: [0.5342465753425, 0.4657534246575], 0.2208669544: [0.1095890410959, 0.8904109589041], 0.68662037906: [0.1095890410959, 0.8904109589041], 0.96246950647: [0.6164383561644, 0.3835616438356], 0.95871645712: [0.013698630137, 0.986301369863], 0.37699380747: [0.2739726027397, 0.7260273972603], 0.44304747607: [0.1506849315068, 0.8493150684932], 0.0654907112: [0.0547945205479, 0.9452054794521], 0.46406455245: [0.041095890411, 0.958904109589], 0.47982735973: [0.1643835616438, 0.8356164383562], 0.76543441546: [0.041095890411, 0.958904109589], 0.01519984988: [0.3287671232877, 0.6712328767123], 0.75492587728: [0.6712328767123, 0.3287671232877], 0.24713829987: [0.7671232876712, 0.2328767123288], 0.79433289548: [0.013698630137, 0.986301369863], 0.15068493151: [0.0], 0.30793769938: [0.6027397260274, 0.3972602739726], 0.31581910302: [0.2602739726027, 0.7397260273973], 0.84162131732: [0.6575342465753, 0.3424657534247], 0.32370050666: [0.1369863013699, 0.8630136986301], 0.9797335335: [0.2739726027397, 0.7260273972603], 0.87314693188: [0.6438356164384, 0.3561643835616], 0.16907487334: [0.1506849315068, 0.8493150684932], 0.84762619628: [0.041095890411, 0.958904109589], 0.08650778758: [0.1917808219178, 0.8082191780822], 0.17695627698: [0.7945205479452, 0.2054794520548], 0.5136048039: [0.7808219178082, 0.2191780821918], 0.51623193845: [0.1780821917808, 0.8219178082192], 0.88590729968: [0.5890410958904, 0.4109589041096], 0.53199474573: [0.5753424657534, 0.4246575342466], 0.18483768062: [0.7808219178082, 0.2191780821918], 0.4614374179: [0.1780821917808, 0.8219178082192], 0.09438919122: [0.8767123287671, 0.1232876712329], 0.56089322575: [0.027397260274, 0.972602739726], 0.38412460124: [0.7671232876712, 0.2328767123288], 0.02908613248: [0.1095890410959, 0.8904109589041], 0.58979170576: [0.2602739726027, 0.7397260273973], 0.59241884031: [0.5068493150685, 0.4931506849315], 0.96922499531: [0.6849315068493, 0.3150684931507], 0.4156502158: [0.1506849315068, 0.8493150684932], 0.6370801276: [0.0821917808219, 0.9178082191781], 0.74441733909: [0.1506849315068, 0.8493150684932], 0.42353161944: [0.7945205479452, 0.2054794520548], 0.65284293489: [0.0684931506849, 0.9315068493151], 0.43141302308: [0.7808219178082, 0.2191780821918], 0.21899042972: [0.013698630137, 0.986301369863], 0.68436854945: [0.2876712328767, 0.7123287671233], 0.69750422218: [0.7945205479452, 0.2054794520548], 0.25164195909: [0.3013698630137, 0.6986301369863], 0.22687183337: [0.7534246575342, 0.2465753424658], 0.130418465: [0.2739726027397, 0.7260273972603], 0.41114655658: [0.6301369863014, 0.3698630136986], 0.26740476637: [0.2739726027397, 0.7260273972603], 0.74479264402: [0.3013698630137, 0.6986301369863], 0.47607431038: [0.3150684931507, 0.6849315068493], 0.7605554513: [0.2739726027397, 0.7260273972603], 0.28316757365: [0.5890410958904, 0.4109589041096], 0.76280728092: [0.1780821917808, 0.8219178082192], 0.29104897729: [0.5068493150685, 0.4931506849315], 0.12328767123: [0.0], 0.571026459: [0.1780821917808, 0.8219178082192], 0.4997185213: [0.6027397260274, 0.3972602739726], 0.8052167386: [0.0547945205479, 0.9452054794521], 0.50647401013: [0.5616438356164, 0.4383561643836], 0.15668981047: [0.3424657534247, 0.6575342465753], 0.83674235316: [0.5479452054795, 0.4520547945205], 0.8498780259: [0.7671232876712, 0.2328767123288], 0.16457121411: [0.6301369863014, 0.3698630136986], 0.33571026459: [0.0821917808219, 0.9178082191781], 0.88140364046: [0.1506849315068, 0.8493150684932], 0.34359166823: [0.5479452054795, 0.4520547945205], 0.89716644774: [0.7808219178082, 0.2191780821918], 0.04409832989: [0.5205479452055, 0.4794520547945], 0.51135297429: [0.0958904109589, 0.9041095890411], 0.52223681741: [0.1095890410959, 0.8904109589041], 0.52711578157: [0.6027397260274, 0.3972602739726], 0.54025145431: [0.3424657534247, 0.6575342465753], 0.94182773504: [0.6849315068493, 0.3150684931507], 0.92381309814: [0.6575342465753, 0.3424657534247], 0.38299868643: [0.2876712328767, 0.7123287671233], 0.57177706887: [0.6438356164384, 0.3561643835616], 0.97598048414: [0.5068493150685, 0.4931506849315], 0.0973916307: [0.3287671232877, 0.6712328767123], 0.58753987615: [0.8767123287671, 0.1232876712329], 0.19872396322: [0.0821917808219, 0.9178082191781], 0.39876149371: [0.3287671232877, 0.6712328767123], 0.60330268343: [0.7671232876712, 0.2328767123288], 0.61643835616: [0.0], 0.20660536686: [0.5479452054795, 0.4520547945205], 0.10527303434: [0.1780821917808, 0.8219178082192], 0.73541002064: [0.1780821917808, 0.8219178082192], 0.42765997373: [0.5205479452055, 0.4794520547945], 0.2144867705: [0.0684931506849, 0.9315068493151], 0.81534997185: [0.2739726027397, 0.7260273972603], 0.05460686808: [0.013698630137, 0.986301369863], 0.00018765247: [0.6301369863014, 0.3698630136986], 0.44342278101: [0.3013698630137, 0.6986301369863], 0.44267217114: [0.1917808219178, 0.8082191780822], 0.69525239257: [0.6849315068493, 0.3150684931507], 0.45130418465: [0.027397260274, 0.972602739726], 0.37661850253: [0.7808219178082, 0.2191780821918], 0.45918558829: [0.2739726027397, 0.7260273972603], 0.06624132107: [0.5753424657534, 0.4246575342466], 0.73991367987: [0.6301369863014, 0.3698630136986], 0.13642334397: [0.2876712328767, 0.7123287671233], 0.47494839557: [0.5890410958904, 0.4109589041096], 0.75567648715: [0.5342465753425, 0.4657534246575], 0.03509101145: [0.7534246575342, 0.2465753424658], 0.48282979921: [0.5068493150685, 0.4931506849315], 0.28729592794: [0.5616438356164, 0.4383561643836], 0.96322011635: [0.1917808219178, 0.8082191780822], 0.30305873522: [0.1095890410959, 0.8904109589041], 0.15218615125: [0.3287671232877, 0.6712328767123], 0.99962469507: [0.5616438356164, 0.4383561643836], 0.83899418277: [0.5068493150685, 0.4931506849315], 0.84499906174: [0.1780821917808, 0.8219178082192], 0.82623381498: [0.1917808219178, 0.8082191780822], 0.86076186902: [0.5753424657534, 0.4246575342466], 0.02082942391: [0.2739726027397, 0.7260273972603], 0.99774817039: [0.5753424657534, 0.4246575342466], 0.8765246763: [0.013698630137, 0.986301369863], 0.34246575343: [0.0], 0.78945393132: [0.1369863013699, 0.8630136986301], 0.08725839745: [0.3013698630137, 0.6986301369863], 0.50384687559: [0.0547945205479, 0.9452054794521], 0.17845749672: [0.1643835616438, 0.8356164383562], 0.46106211297: [0.0684931506849, 0.9315068493151], 0.04559954963: [0.0958904109589, 0.9041095890411], 0.53537249015: [0.5479452054795, 0.4520547945205], 0.9553387127: [0.6438356164384, 0.3561643835616], 0.09513980109: [0.027397260274, 0.972602739726], 0.97110151999: [0.8767123287671, 0.1232876712329], 0.38712704072: [0.6164383561644, 0.3835616438356], 0.58003377744: [0.1506849315068, 0.8493150684932], 0.73053105648: [0.0958904109589, 0.9041095890411], 0.39500844436: [0.5753424657534, 0.4246575342466], 0.59579658473: [0.7808219178082, 0.2191780821918]}

37,675.4

67,448

0.782112

23,766

188,377

6.199066

0.11689

0.002063

0.001568

0.013874

0.676597

0.159625

0.155518

0

0.834402

0.063049

188,377

5

67,448

37,675.4

0.000312

0

1

0

false

0

null

0

1

0

1

0

null

0

5

4d239763feb75c4ad138f216c1f8cd1eb6e44284

749

py

Python

regression_tests/selftest.py

GuoZiYi-astro/NuPyCEE

9d54ffa6aa120ef60f2a06de353d1bcbfee6ca16

[ "BSD-3-Clause" ]

22

2016-05-24T15:59:41.000Z

2021-08-16T08:32:31.000Z

regression_tests/selftest.py

GuoZiYi-astro/NuPyCEE

9d54ffa6aa120ef60f2a06de353d1bcbfee6ca16

[ "BSD-3-Clause" ]

15

2016-05-30T15:57:40.000Z

2022-01-23T14:20:54.000Z

regression_tests/selftest.py

GuoZiYi-astro/NuPyCEE

9d54ffa6aa120ef60f2a06de353d1bcbfee6ca16

[ "BSD-3-Clause" ]

14

2016-10-20T10:13:36.000Z

2022-03-13T09:14:49.000Z

import matplotlib matplotlib.use('agg') import unittest class TestModuleImports(unittest.TestCase): ''' Import tests. ''' def test_import_sygma(self): from NuPyCEE import sygma def test_import_omega(self): from NuPyCEE import omega def test_import_stellab(self): from NuPyCEE import stellab class TestDefaults(unittest.TestCase): ''' Test simulations with default variables. ''' def run_sygma(self): from NuPyCEE import sygma as s s1 = s.sygma() def run_omega(self): from NuPyCEE import omega as o o1 = o.omega() def run_stellab(self): from NuPyCEE import stellab as st st1 = st.stellab()

21.4

49

0.615487

88

749

5.136364

0.340909

0.106195

0.199115

0.278761

0.429204

0

0.005792

0.308411

749

34

50

22.029412

0.866795

0.077437

0

0.004559

0

1

0.3

false

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4d43c1249b215412805341ba1713ddf79e9ac215

258

py

Python

hrtfdata/torch/__init__.py

jpauwels/hrtfdata

cadcf1d72395de15d1d114fb88a3b64e283df899

[ "Apache-2.0" ]

null

hrtfdata/torch/__init__.py

jpauwels/hrtfdata

cadcf1d72395de15d1d114fb88a3b64e283df899

[ "Apache-2.0" ]

2

2022-03-10T18:11:54.000Z

2022-03-16T18:00:33.000Z

hrtfdata/torch/__init__.py

jpauwels/hrtfdata

cadcf1d72395de15d1d114fb88a3b64e283df899

[ "Apache-2.0" ]

1

2022-03-02T18:22:52.000Z

from torch.utils.data._utils.collate import default_collate def collate_dict_dataset(batch, features_key_name='features', target_key_name='target'): return [default_collate(x) for x in zip(*((d[features_key_name], d[target_key_name]) for d in batch))]

43

106

0.782946

42

258

4.5

0.5

0.148148

0.15873

0

0.096899

258

5

107

51.6

0.811159

0

0.054264

0

1

0.333333

false

0

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

5

4d752ee12ab8bb9f5cd63c0dab16613481ffe618

66

py

Python

plotter.py

Judithle98/BachelorThesis

263cd589b5bfc22bdecc304430fd76816d42101b

[ "CC0-1.0" ]

null

plotter.py

Judithle98/BachelorThesis

263cd589b5bfc22bdecc304430fd76816d42101b

[ "CC0-1.0" ]

null

plotter.py

Judithle98/BachelorThesis

263cd589b5bfc22bdecc304430fd76816d42101b

[ "CC0-1.0" ]

null

class Plotter: pass class PyplotPlotter(Plotter): pass

8.25

29

0.681818

7

66

6.428571

0.571429

0.488889

0

0.257576

66

8

30

8.25

0.918367

0

0.5

0

1

0

true

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

4d93db39d4a1e55a3b2602df6682cbfad59cc82d

56

py

Python

ko_noiser/__init__.py

ketzu/konoise

fd10dab36fe5ff026fdf23beaf2ce80e9e537182

[ "Apache-2.0" ]

null

ko_noiser/__init__.py

ketzu/konoise

fd10dab36fe5ff026fdf23beaf2ce80e9e537182

[ "Apache-2.0" ]

null

ko_noiser/__init__.py

ketzu/konoise

fd10dab36fe5ff026fdf23beaf2ce80e9e537182

[ "Apache-2.0" ]

null

from .config import Config from .konoise import Konoise

28

0.821429

8

56

5.75

0.5

0

0.142857

56

2

28

0.958333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4db50eae8463c78f40c507eb75f64f769f3b6d3a

70

py

Python

azmessaging/readers/sms/__init__.py

ali-zahedi/az-messaging

ecc626e6be3f58a9ec166923623c144c86d2734e

[ "MIT" ]

null

azmessaging/readers/sms/__init__.py

ali-zahedi/az-messaging

ecc626e6be3f58a9ec166923623c144c86d2734e

[ "MIT" ]

null

azmessaging/readers/sms/__init__.py

ali-zahedi/az-messaging

ecc626e6be3f58a9ec166923623c144c86d2734e

[ "MIT" ]

null

from .config import SMSConfig from .readermixin import SMSReaderMixin

23.333333

39

0.857143

8

70

7.5

0.75

0

0.114286

70

2

40

35

0.967742

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4dda9a53e2d4d061f98b7837858dc8d951dc2bd0

37

py

Python

game/game_code/asset_loader/__init__.py

RDGT/adventure-poc

e211491e5958d12a3347b3e279006d915d691d20

[ "MIT" ]

2

2018-04-23T15:03:41.000Z

2018-07-18T06:36:51.000Z

game/game_code/asset_loader/__init__.py

RDGT/adventure-poc

e211491e5958d12a3347b3e279006d915d691d20

[ "MIT" ]

6

2018-03-25T12:04:27.000Z

2018-09-14T09:08:34.000Z

game/game_code/asset_loader/__init__.py

RDGT/adventure-poc

e211491e5958d12a3347b3e279006d915d691d20

[ "MIT" ]

1

2018-07-22T09:46:55.000Z

import asset_base import json_parser

12.333333

18

0.891892

6

37

5.166667

0.833333

0

0.108108

37

2

19

18.5

0.939394

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

4df0d200f339af648f5057954cfc76ae178f9238

98

py

Python

tema.py

182354/Fabrica-Final

a2074951ae572bc8bc4b19193ac1da8030dc2085

[ "MIT" ]

null

tema.py

182354/Fabrica-Final

a2074951ae572bc8bc4b19193ac1da8030dc2085

[ "MIT" ]

1

2020-07-19T01:41:02.000Z

tema.py

182354/Fabrica-Final

a2074951ae572bc8bc4b19193ac1da8030dc2085

[ "MIT" ]

null

a=int(input('valor para A:',)) b=int(input('valor para B:',)) soma=a+b print('a soma eh:',soma)

14

30

0.612245

20

98

3

0.45

0.266667

0.433333

0.566667

0

0.122449

98

6

31

16.333333

0.697674

0

0.375

0

1

0

false

0

0.25

1

0

null

1

0

1

0

null

0

5

129289a649b9e5322f79b63708ddc2281603052f

125

py

Python

userbot/utils/converter/__init__.py

AppleBotz/Blvck-Userbot

eae12b6a0fdd980dcc4824a4432d74e468b6bcec

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

userbot/utils/converter/__init__.py

AppleBotz/Blvck-Userbot

eae12b6a0fdd980dcc4824a4432d74e468b6bcec

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

userbot/utils/converter/__init__.py

AppleBotz/Blvck-Userbot

eae12b6a0fdd980dcc4824a4432d74e468b6bcec

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

from os import listdir, mkdir if "raw_files" not in listdir(): mkdir("raw_files") from .converter import convert

17.857143

33

0.696

18

125

4.722222

0.666667

0.282353

0

0.216

125

6

34

20.833333

0.867347

0

0.151261

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

4209e01ec38db705bc8b2618290cee794282ed57

212

py

Python

office365/sharepoint/permissions/utility.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

544

2016-08-04T17:10:16.000Z

2022-03-31T07:17:20.000Z

office365/sharepoint/permissions/utility.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

438

2016-10-11T12:24:22.000Z

2022-03-31T19:30:35.000Z

office365/sharepoint/permissions/utility.py

rikeshtailor/Office365-REST-Python-Client

ca7bfa1b22212137bb4e984c0457632163e89a43

[ "MIT" ]

202

2016-08-22T19:29:40.000Z

2022-03-30T20:26:15.000Z

from office365.sharepoint.base_entity import BaseEntity class Utility(BaseEntity): def __init__(self, context, resource_path): super(Utility, self).__init__(context, resource_path, "SP.Utilities")

26.5

77

0.764151

25

212

6.04

0.72

0.198676

0.251656

0

0.016393

0.136792

212

7

78

30.285714

0.808743

0

0.056604

0

1

0.25

false

0

0.25

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

421e05495c3e9ff1c5627b42c9b6a84d7c600ea8

242

py

Python

py_elo_db/util/db_util.py

bradleycwojcik/py-elo-db

5d0294f1e4d0bc47c9ed5e6f3a2dd7d51f2b3e77

[ "MIT" ]

null

py_elo_db/util/db_util.py

bradleycwojcik/py-elo-db

5d0294f1e4d0bc47c9ed5e6f3a2dd7d51f2b3e77

[ "MIT" ]

4

2019-12-13T05:18:14.000Z

2019-12-13T05:27:38.000Z

py_elo_db/util/db_util.py

bradleycwojcik/py-elo-db

5d0294f1e4d0bc47c9ed5e6f3a2dd7d51f2b3e77

[ "MIT" ]

null

from py_elo_db.model.base import db from py_elo_db.model.match import Match from py_elo_db.model.player import Player def create_tables() -> None: """Initialize database tables.""" with db: db.create_tables([Player, Match])

24.2

41

0.727273

38

242

4.421053

0.421053

0.107143

0.160714

0.196429

0.285714

0

0.169421

242

9

42

26.888889

0.835821

0.11157

0

1

0.166667

true

0

0.5

0

0.666667

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

422b43b5fef205a85c446a92d0d720006f04d235

55

py

Python

ch07/echo.py

eroicaleo/LearningPython

297d46eddce6e43ce0c160d2660dff5f5d616800

[ "MIT" ]

1

2020-10-12T13:33:29.000Z

ch07/echo.py

eroicaleo/LearningPython

297d46eddce6e43ce0c160d2660dff5f5d616800

[ "MIT" ]

null

ch07/echo.py

eroicaleo/LearningPython

297d46eddce6e43ce0c160d2660dff5f5d616800

[ "MIT" ]

1

2016-11-09T07:28:45.000Z

#!/usr/local/bin/python3.3 import sys print(sys.argv)

11

26

0.727273

10

55

4

0.9

0

0.04

0.090909

55

4

27

13.75

0.76

0.454545

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4235bbb9ee1d29ac9edb4cd10e27ccc17004627b

659

py

Python

python/pyxir/contrib/target/DPUCAHX8L_external_quantizer.py

Xilinx/pyxir

bef661d6d77adcdbd2cf4163f2cf3a1d31d40406

[ "Apache-2.0" ]

25

2020-06-17T22:41:13.000Z

2022-03-22T16:28:22.000Z

python/pyxir/contrib/target/DPUCAHX8L_external_quantizer.py

Xilinx/pyxir

bef661d6d77adcdbd2cf4163f2cf3a1d31d40406

[ "Apache-2.0" ]

25

2021-03-16T06:26:44.000Z

2022-03-18T11:28:33.000Z

python/pyxir/contrib/target/DPUCAHX8L_external_quantizer.py

Xilinx/pyxir

bef661d6d77adcdbd2cf4163f2cf3a1d31d40406

[ "Apache-2.0" ]

19

2020-07-30T10:03:02.000Z

2021-06-29T01:18:16.000Z

import pyxir from .components.DPUCZDX8G.external_quantizer_tools import xgraph_dpu_external_quantizer from .components.DPUCZDX8G.external_quantizer_tools import xgraph_dpu_external_quantizer_optimizer from .components.DPUCZDX8G.dpucahx8l import xgraph_dpu_build_func from .components.DPUCZDX8G.dpucahx8l import xgraph_dpu_compiler # Register target pyxir.register_target('DPUCAHX8L', xgraph_dpu_external_quantizer_optimizer, xgraph_dpu_external_quantizer, xgraph_dpu_compiler, xgraph_dpu_build_func) # Register op support from .components.DPUCAHX8L import op_support

36.611111

98

0.770865

73

659

6.547945

0.260274

0.150628

0.192469

0.217573

0.610879

0.518828

0.322176

0

0.015009

0.191199

659

18

99

36.611111

0.881801

0.053111

0

0.014469

0

1

0

true

0

0.545455

0

0.545455

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4246111c9461a8f1b98f2f2cc9594d3cf67477da

122

py

Python

boosup/boosup/performance/signals/__init__.py

developertqw2017/migrationDjango

f7256ec2af51da1179d2f957e1aa896191b7b514

[ "MIT" ]

null

boosup/boosup/performance/signals/__init__.py

developertqw2017/migrationDjango

f7256ec2af51da1179d2f957e1aa896191b7b514

[ "MIT" ]

16

2020-02-11T23:19:19.000Z

2022-03-11T23:33:40.000Z

boosup/boosup/performance/signals/__init__.py

developertqw2017/migrationDjango

f7256ec2af51da1179d2f957e1aa896191b7b514

[ "MIT" ]

null

#!/usr/bin/env python #coding=utf8 ''' Created on 2016/9/24 @author: cloudy @description: ''' from performance import *

12.2

26

0.696721

17

122

5

1

0

0.07619

0.139344

122

9

27

13.555556

0.733333

0.680328

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

424d9b161a91f666fede844fe63f9ded61004b4d

185

py

Python

geode/random/__init__.py

jjqcat/geode

157cc904c113cc5e29a1ffe7c091a83b8ec2cf8e

[ "BSD-3-Clause" ]

75

2015-02-08T22:04:31.000Z

2022-02-26T14:31:43.000Z

geode/random/__init__.py

bantamtools/geode

d906f1230b14953b68af63aeec2f7b0418d5fdfd

[ "BSD-3-Clause" ]

15

2015-01-08T15:11:38.000Z

2021-09-05T13:27:22.000Z

geode/random/__init__.py

bantamtools/geode

d906f1230b14953b68af63aeec2f7b0418d5fdfd

[ "BSD-3-Clause" ]

22

2015-03-11T16:43:13.000Z

2021-02-15T09:37:51.000Z

"""random module""" from __future__ import (division,absolute_import) from geode import * Sobols = {1:Sobol1d,2:Sobol2d,3:Sobol3d} def Sobol(box): return Sobols[len(box.min)](box)

18.5

49

0.72973

27

185

4.814815

0.777778

0

0.03681

0.118919

185

9

50

20.555556

0.760736

0.07027

0

1

0.2

false

0

0.4

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

5

4270ce3d5e47c57844cfafd26fe70c2f48157121

127

py

Python

autokey_emacs/C-k.py

sherylynn/dotfile

3ed34180d6120b04f061038baed62492812baa00

[ "MIT" ]

4

2018-04-13T09:14:10.000Z

2021-04-08T03:46:46.000Z

autokey_emacs/C-k.py

sherylynn/dotfile

3ed34180d6120b04f061038baed62492812baa00

[ "MIT" ]

null

autokey_emacs/C-k.py

sherylynn/dotfile

3ed34180d6120b04f061038baed62492812baa00

[ "MIT" ]

null

# Enter script code # 单独 shift后接end是放开了，不是按住不放 # 发现不管怎么样都失败了 keyboard.send_keys("<shift>+<end>") keyboard.send_keys("<ctrl>+x")

25.4

35

0.748031

17

127

5.470588

0.823529

0.258065

0.344086

0

0.07874

127

5

36

25.4

0.794872

0.425197

0

0.3

0

1

0

true

0

1

0

null

1

0

1

0

null

0

1

0

5

427b59c4719af06fdc393332e9411274d8b1f2c6

36

py

Python

custom_components/p2000/__init__.py

Alfagek/Home-Assistant-Config

1109723483904a98ac494988e89ebdbe9c3aafba

[ "MIT" ]

null

custom_components/p2000/__init__.py

Alfagek/Home-Assistant-Config

1109723483904a98ac494988e89ebdbe9c3aafba

[ "MIT" ]

null

custom_components/p2000/__init__.py

Alfagek/Home-Assistant-Config

1109723483904a98ac494988e89ebdbe9c3aafba

[ "MIT" ]

null

"""The p2000 sensor integration."""

18

35

0.694444

4

36

6.25

1

0

0.125

0.111111

36

1

36

0.65625

0.805556

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

429de02f385c1bd324e3ef3820435d3518dd5c77

181

py

Python

modules/fapi/api.py

Bym24v/FAS

efbcf606c49dd591857e0e537bc5b9f082c13405

[ "MIT" ]

3

2018-02-11T11:34:30.000Z

2020-05-06T12:11:03.000Z

modules/fapi/api.py

Bym24v/FAS

efbcf606c49dd591857e0e537bc5b9f082c13405

[ "MIT" ]

null

modules/fapi/api.py

Bym24v/FAS

efbcf606c49dd591857e0e537bc5b9f082c13405

[ "MIT" ]

null

from bottle import route, run, template @route('/api/savedata') def api_savedata(): return "savedata" @route('/api/getdata') def api_getdata(): return "false"

12.928571

39

0.646409

22

181

5.227273

0.545455

0.13913

0

0.209945

181

13

40

13.923077

0.804196

0

0.209945

0

1

0.285714

true

0

0.142857

0.285714

0.714286

0

1

0

null

0

null

0

1

0

1

0

5

42af3a2c33d4011832897d4bdaf121ce956b0954

23

py

Python

hello/hellorh.py

wcj75019/DO400-apps-external

88e03de6c2c36ecff4d2244dd67612ce71542fdd

[ "Apache-2.0" ]

null

hello/hellorh.py

wcj75019/DO400-apps-external

88e03de6c2c36ecff4d2244dd67612ce71542fdd

[ "Apache-2.0" ]

null

hello/hellorh.py

wcj75019/DO400-apps-external

88e03de6c2c36ecff4d2244dd67612ce71542fdd

[ "Apache-2.0" ]

null

print("Hello RedHat!")

11.5

22

0.695652

3

23

5.333333

1

0

0.086957

23

1

23

0.761905

0

0.565217

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

35ea590eb2af2ab1e0236210731783a3118956a7

194

py

Python

python/launcherDevelopment/launcherTest.py

JuicyData/TheOrangeAlliance2016-2017

c0cd2731b9693db46b65f198fa0a3d191bcb1a54

[ "MIT" ]

null

python/launcherDevelopment/launcherTest.py

JuicyData/TheOrangeAlliance2016-2017

c0cd2731b9693db46b65f198fa0a3d191bcb1a54

[ "MIT" ]

2

2018-07-09T18:46:21.000Z

2018-12-23T05:57:10.000Z

python/launcherDevelopment/launcherTest.py

JuicyData/TheOrangeAlliance2016-2017

c0cd2731b9693db46b65f198fa0a3d191bcb1a54

[ "MIT" ]

null

#! /usr/bin/python import time import shlex, subprocess print 'I' args = ['python GetLauncherTest.py'] print args #p = subprocess.Popen(args) subprocess.Popen((args), shell=True) print 'I2'

13.857143

36

0.721649

27

194

5.185185

0.62963

0.214286

0.271429

0

0.005952

0.134021

194

13

37

14.923077

0.827381

0.221649

0

0.187919

0

null

0

0.285714

null

0.428571

1

0

null

1

0

null

0

1

0

1

0

5

35f9d11b0224eb6b84105fa2f4dd7e036b69ba03

390

py

Python

patches/cookiejar_add.py

vrchatapi/vrchatapi-python

996b7ddf2914059f1fd4e5def5e3555e678634c0

[ "MIT" ]

8

2021-08-25T02:35:30.000Z

2022-03-28T18:11:58.000Z

patches/cookiejar_add.py

vrchatapi/vrchatapi-python

afe5ec9fda298723e7408358473aafe343e27d18

[ "MIT" ]

1

2022-03-18T20:29:30.000Z

2022-03-18T20:35:05.000Z

patches/cookiejar_add.py

vrchatapi/vrchatapi-python

afe5ec9fda298723e7408358473aafe343e27d18

[ "MIT" ]

1

2022-01-11T10:49:12.000Z

# VRChatAPI: Build a mock Request object to work with from urllib.request import Request mock_request_object = Request(url=url, method=method, headers=headers) self.cookie_jar.add_cookie_header(mock_request_object) if "Cookie" in mock_request_object.unredirected_hdrs: headers["Cookie"] = mock_request_object.unredirected_hdrs["Cookie"]

48.75

79

0.720513

49

390

5.469388

0.489796

0.205224

0.317164

0.216418

0.246269

0

0.205128

390

7

80

55.714286

0.864516

0.130769

0

0.053571

0

null

0

0.2

null

0

null

1

0

1

0

null

0

1

0

5

c44194616fbcfcbcb3a976acc3e47a5b39b479d0

130

py

Python

django_api/user/admin.py

LonelVino/world-week-test

73d5201564cd1f3d7ece4ccb4aa5ba6baaf03f68

[ "MIT" ]

null

django_api/user/admin.py

LonelVino/world-week-test

73d5201564cd1f3d7ece4ccb4aa5ba6baaf03f68

[ "MIT" ]

null

django_api/user/admin.py

LonelVino/world-week-test

73d5201564cd1f3d7ece4ccb4aa5ba6baaf03f68

[ "MIT" ]

null

from django.contrib import admin from django_api.user import models # Register your models here. admin.site.register(models.User)

26

34

0.823077

20

130

5.3

0.6

0.188679

0

0.107692

130

5

35

26

0.913793

0.2

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c4526bd300033f33d0385010e258212e8867bbbd

89

py

Python

config.py

nfatkhiyev/Conjugate

a8991c3d56fcc6abedbafba7e1452d66a7c30b97

[ "MIT" ]

null

config.py

nfatkhiyev/Conjugate

a8991c3d56fcc6abedbafba7e1452d66a7c30b97

[ "MIT" ]

1

2020-02-10T16:45:45.000Z

config.py

nfatkhiyev/Conjugate

a8991c3d56fcc6abedbafba7e1452d66a7c30b97

[ "MIT" ]

null

from os import environ SQLALCHEMY_DATABASE_URI = environ.get('SQLALCHEMY_DATABASE_URI')

22.25

64

0.842697

12

89

5.916667

0.666667

0.507042

0.591549

0

0.089888

89

3

65

29.666667

0.876543

0

0.258427

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

c46a28d273ecabe3d2a1fde5e615af1cdf08418f

202

py

Python

tfuploader/__init__.py

sheppard/tfuploader

7d9c10e3bbc1d9e89eae6f937bd5cbaf674e8edb

[ "MIT" ]

null

tfuploader/__init__.py

sheppard/tfuploader

7d9c10e3bbc1d9e89eae6f937bd5cbaf674e8edb

[ "MIT" ]

null

tfuploader/__init__.py

sheppard/tfuploader

7d9c10e3bbc1d9e89eae6f937bd5cbaf674e8edb

[ "MIT" ]

null

from .tools import upload_from_queryset, list_groups_from_queryset from .zipfile import upload_zipfile __all__ = ( 'upload_from_queryset', 'list_groups_from_queryset', 'upload_zipfile', )

20.2

66

0.777228

25

202

5.64

0.36

0.340426

0.255319

0.312057

0.567376

0

0.148515

202

9

67

22.444444

0.819767

0

0.292079

0.123762

0

1

0

false

0

0.285714

0

0.285714

0

1

0

null

1

0

1

0

null

0

5

c47d04605ff564537e5212cbe074a37104ec728e

33

py

Python

website/webapp/json_api/__init__.py

ultimatecoder/dockerapi

0ae0a97aac5218b8eb07d589cd90b63c8fc2ea74

[ "MIT" ]

null

website/webapp/json_api/__init__.py

ultimatecoder/dockerapi

0ae0a97aac5218b8eb07d589cd90b63c8fc2ea74

[ "MIT" ]

null

website/webapp/json_api/__init__.py

ultimatecoder/dockerapi

0ae0a97aac5218b8eb07d589cd90b63c8fc2ea74

[ "MIT" ]

null

from .decorators import json_api

16.5

32

0.848485

5

33

5.4

1

0

0.121212

33

1

33

0.931034

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

67387e0c88733fc1b7d171dce4f4fd96a62b493b

1,160

py

Python

framework/behaviour/__init__.py

vitorascorrea/pokemon-vgc-engine

3925deb408a70d25c4c9e7b53e021ea5a25d3bda

[ "MIT" ]

1

2022-01-05T10:00:46.000Z

framework/behaviour/__init__.py

vitorascorrea/pokemon-vgc-engine

3925deb408a70d25c4c9e7b53e021ea5a25d3bda

[ "MIT" ]

null

framework/behaviour/__init__.py

vitorascorrea/pokemon-vgc-engine

3925deb408a70d25c4c9e7b53e021ea5a25d3bda

[ "MIT" ]

null

from abc import ABC, abstractmethod from typing import Any, Set from framework.DataObjects import PkmRoster, PkmTeamPrediction, PkmFullTeam, TeamValue, MetaData class Behaviour(ABC): @abstractmethod def get_action(self, s) -> Any: pass @abstractmethod def requires_encode(self) -> bool: pass @abstractmethod def close(self): pass class BattlePolicy(Behaviour): @abstractmethod def get_action(self, s) -> int: pass class SelectorPolicy(Behaviour): @abstractmethod def get_action(self, s) -> Set[int]: pass class TeamBuilderPolicy(Behaviour): @abstractmethod def get_action(self, s) -> PkmFullTeam: pass class TeamPredictor(Behaviour): @abstractmethod def get_action(self, s) -> PkmTeamPrediction: pass class DataAggregator(Behaviour): @abstractmethod def get_action(self, s) -> MetaData: pass class TeamValuator(Behaviour): @abstractmethod def get_action(self, s) -> TeamValue: pass class BalancePolicy(Behaviour): @abstractmethod def get_action(self, s) -> PkmRoster: pass

16.811594

96

0.667241

120

1,160

6.375

0.283333

0.222222

0.20915

0.271895

0.406536

0.366013

0

0.247414

1,160

68

97

17.058824

0.876289

0

0.487805

0

1

0.243902

false

0.243902

0.073171

0

0.512195

0

null

1

0

null

0

1

0

1

0

5

6762681c82b089ea00e95a0cdd0572d7abf7512e

238

py

Python

backend_poa_admin/apps/DeterminacionForm/admin.py

lizethlizi/proyecto_backend_POA

872488954c2a0db42b47a35dbe3f6d50becf9968

[ "MIT" ]

null

backend_poa_admin/apps/DeterminacionForm/admin.py

lizethlizi/proyecto_backend_POA

872488954c2a0db42b47a35dbe3f6d50becf9968

[ "MIT" ]

null

backend_poa_admin/apps/DeterminacionForm/admin.py

lizethlizi/proyecto_backend_POA

872488954c2a0db42b47a35dbe3f6d50becf9968

[ "MIT" ]

null

from django.contrib import admin from .models import Datosformulario,objetivos_gestion,formularios # Register your models here. admin.site.register(Datosformulario) admin.site.register(objetivos_gestion) admin.site.register(formularios)

29.75

65

0.852941

29

238

6.931034

0.482759

0.134328

0.253731

0

0.071429

238

7

66

34

0.909502

0.109244

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

67db3749da258de6d4dbbab4eb6927f05ccd9bbb

7,283

py

Python

MultiInput/custom_commands.py

JacobMillner/SmashTrainingBot

5aed112a7e802d7e1c8474f479f90c3e66d4d933

[ "MIT" ]

null

MultiInput/custom_commands.py

JacobMillner/SmashTrainingBot

5aed112a7e802d7e1c8474f479f90c3e66d4d933

[ "MIT" ]

null

MultiInput/custom_commands.py

JacobMillner/SmashTrainingBot

5aed112a7e802d7e1c8474f479f90c3e66d4d933

[ "MIT" ]

null

from mapping_generator import * def gen_rune_commands(): commands = [] cmd_help = [] runes = ['sphere bomb', 'cube bomb', 'magnesis', 'stasis', 'cryonis', 'camera'] for index, rune in enumerate(runes): command = ControllerCommand([rune]) with command.hold_dpad(DPAD_UP, delay=PRESS_DELAY): command.move_stick(STICK_RIGHT, STICK_MIN, STICK_CENTER, delay=128) for _ in range(index): command.press_buttons(BUTTON_R) commands.append(command) cmd_help.append( CommandHelp( name=rune, text='Switches to the %s rune' % rune, aliases=None, allowed=None ), ) return commands, cmd_help def gen_snowball(): commands = [] cmd_help = [] command = ControllerCommand(['snowball']) command.press_buttons(BUTTON_A, delay=18, release_delay=93) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=48) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=48) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=978) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=153) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=48) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=303) command.press_buttons(BUTTON_A, delay=18, release_delay=453) command.press_buttons(BUTTON_A, delay=18, release_delay=153) command.hold_stick(STICK_LEFT, STICK_MIN, STICK_CENTER, delay=129) command.hold_stick(STICK_LEFT, STICK_CENTER, STICK_MIN, delay=243) state = ControllerTransition() state.ly = STICK_MIN state.buttons_pressed = BUTTON_R state.delay = 78 command.add_state(state) state = ControllerTransition() state.ly = STICK_CENTER state.buttons_released = BUTTON_R state.delay = 93 command.add_state(state) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_B, delay=18, release_delay=48) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_B, delay=18, release_delay=1353) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.press_buttons(BUTTON_B, delay=18, release_delay=63) command.move_stick(STICK_LEFT, STICK_CENTER, STICK_MAX, delay=33, release_delay=63) command.press_buttons(BUTTON_A, delay=18, release_delay=153) command.hold_stick(STICK_LEFT, STICK_CENTER, STICK_MIN, delay=33) state = ControllerTransition() state.ly = STICK_MIN state.buttons_pressed = BUTTON_R state.delay = 78 command.add_state(state) state = ControllerTransition() state.ly = STICK_CENTER state.buttons_released = BUTTON_R state.delay = 528 command.add_state(state) for _ in range(35): command.press_buttons(BUTTON_B, delay=18, release_delay=63) total = 0 for c in command.transitions: total += c.delay print(c.delay) print(total) commands.append(command) cmd_help.append( CommandHelp( name='snowball', text='Cheeses the snowball game', aliases=None, allowed=None ), ) return commands, cmd_help def gen_custom_commands(): commands = [] cmd_help = [] rune_commands, rune_help = gen_rune_commands() commands += rune_commands cmd_help += rune_help snowball_commands, snowball_help = gen_snowball() commands += snowball_commands cmd_help += snowball_help command = ControllerCommand(['turn 180']) command.move_stick(STICK_RIGHT, STICK_MAX, None, delay=256) commands.append(command) cmd_help.append( CommandHelp( name='turn 180', text='Turns around 180 degrees', aliases=None, allowed=None ), ) command = ControllerCommand(['turn right 90', 'turn right', 'turn r']) command.move_stick(STICK_RIGHT, STICK_MAX, None, delay=128) commands.append(command) cmd_help.append( CommandHelp( name='turn 180', text='Turns around 180 degrees', aliases=None, allowed=None ), ) command = ControllerCommand(['turn left 90', 'turn left', 'turn l']) command.move_stick(STICK_RIGHT, STICK_MIN, None, delay=128) commands.append(command) cmd_help.append( CommandHelp( name='turn left 90', text='Turns left 90 degrees', aliases=None, allowed=None ), ) command = ControllerCommand(['next weapon', 'next wep']) with command.hold_dpad(DPAD_RIGHT, delay=PRESS_DELAY): command.press_buttons(BUTTON_ZR) commands.append(command) cmd_help.append( CommandHelp( name='next weapon', text='Switches to the next weapon', aliases=['next wep'], allowed=None ), ) command = ControllerCommand(['previous weapon', 'previous wep', 'prev weapon', 'prev wep']) with command.hold_dpad(DPAD_RIGHT, delay=PRESS_DELAY): command.press_buttons(BUTTON_ZL) commands.append(command) cmd_help.append( CommandHelp( name='previous weapon', text='Switches to the previous weapon', aliases=['previous wep', 'prev weapon', 'prev wep'], allowed=None ), ) command = ControllerCommand(['next shield', 'next arrow']) with command.hold_dpad(DPAD_LEFT, delay=PRESS_DELAY): command.press_buttons(BUTTON_ZR) commands.append(command) cmd_help.append( CommandHelp( name='next shield', text='Switches to the next shield. If a bow is equipped, switches to the next arrow instead.', aliases=['next arrow'], allowed=None ), ) command = ControllerCommand(['previous shield', 'prev shield', 'previous arrow', 'prev arrow']) with command.hold_dpad(DPAD_LEFT, delay=PRESS_DELAY): command.press_buttons(BUTTON_ZL) commands.append(command) cmd_help.append( CommandHelp( name='previous shield', text='Switches to the previous shield. If a bow is equipped, switches to the previous arrow instead.', aliases=['prev shield', 'previous arrow', 'prev arrow'], allowed=None ), ) command = ControllerCommand(['save']) command.press_buttons(BUTTON_B) command.press_buttons(BUTTON_PLUS) command.press_buttons(BUTTON_R) command.press_buttons(BUTTON_R) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_buttons(BUTTON_A) command.press_dpad(DPAD_UP) command.press_buttons(BUTTON_A) commands.append(command) cmd_help.append( CommandHelp( name='save', text='Saves the game.', aliases=None, allowed=None ), ) command = ControllerCommand(['load']) command.press_buttons(BUTTON_B) command.press_buttons(BUTTON_PLUS) command.press_buttons(BUTTON_R) command.press_buttons(BUTTON_R) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_DOWN) command.press_buttons(BUTTON_A) command.press_dpad(DPAD_UP) command.press_dpad(DPAD_UP) command.press_buttons(BUTTON_A) command.press_dpad(DPAD_UP) command.press_buttons(BUTTON_A) commands.append(command) cmd_help.append( CommandHelp( name='load', text='Loads the game.', aliases=None, allowed=None ), ) return 'Game-specific commands', commands, cmd_help

28.560784

105

0.754085

1,024

7,283

5.131836

0.113281

0.130162

0.151855

0.19981

0.821884

0.751094

0.706565

0.683539

0.664891

0.619791

0

0.025653

0.127557

7,283

255

106

28.560784

0.801385

0

0.640351

0

0.116694

0

1

0.013158

false

0

0.004386

0

0.030702

0.008772

0

null

0

1

0

1

0

null

0

5

67f7d3d2a1323b557a35bc5e92cc254954a5e0bf

50

py

Python

bep032tools/__init__.py

JuliaSprenger/BEP032tools

acf6a4cb6c4de804fbb8cbd94638fa146951042b

[ "MIT" ]

2

2021-12-06T10:07:36.000Z

2021-12-06T10:45:39.000Z

bep032tools/__init__.py

JuliaSprenger/BEP032tools

acf6a4cb6c4de804fbb8cbd94638fa146951042b

[ "MIT" ]

55

2021-01-04T09:34:16.000Z

2021-11-23T10:12:57.000Z

bep032tools/__init__.py

JuliaSprenger/BEP032tools

acf6a4cb6c4de804fbb8cbd94638fa146951042b

[ "MIT" ]

5

2021-01-18T15:07:00.000Z

2021-11-22T09:06:00.000Z

from bep032tools.validator import BEP032Validator

25

49

0.9

5

50

9

1

0

0.130435

0.08

50

1

50

0.847826

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5