content stringlengths 7 1.05M |
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# 形態素の解析結果格納用
class Morph():
def __init__(self, m_id, line):
self.id = 0 # 形態素のid
self.surface = "" # 形態素の表層
self.pos = "" # 品詞，品詞細分類1，品詞細分類2，品詞細分類3
self.pos1 = ""
self.pos2 = ""
self.pos3 = ""
self.pos4 = ""
self.base = "" # 基本形
self.read = "" # 読み
self.cform = "" # 活用形
self.ctype = "" # 活用型
self.ne = "" # 固有表現解析
self.tree = []
self.chunk = None
self.forms = []
self.initMorph(m_id, line)
def initMorph(self, m_id, line):
div1 = line.split("\t")
div2 = div1[1].split(",")
self.id = m_id
self.surface = div1[0]
if div2[0] != "*":
self.pos1 = div2[0]
if div2[1] != "*":
self.pos2 = div2[1]
if div2[2] != "*":
self.pos3 = div2[2]
if div2[3] != "*":
self.pos4 = div2[3]
if div2[4] != "*":
self.cform = div2[4]
if div2[5] != "*":
self.ctype = div2[5]
self.pos = self.getPos()
self.base = div2[6]
if len(div2) >= 8:
self.read = div2[7]
self.ne = div1[2]
def getPos(self):
pos = ""
if self.pos1 != "":
pos = pos + self.pos1
if self.pos2 != "":
pos = pos + "," + self.pos2
if self.pos3 != "":
pos = pos + "," + self.pos3
if self.pos4 != "":
pos = pos + "," + self.pos4
return pos
|
def insertShiftArray(arr, value):
mid = len(arr) // 2
new_arr = []
for i in range(0, mid):
new_arr.append(arr[i])
new_arr.append(value)
for i in range(mid, len(arr)):
new_arr.append(arr[i])
return new_arr
test = [1, 2, 3, 4, 5]
print(test)
print(insertShiftArray(test, 8))
test2 = [1,2,3,4]
print(test2, 8)
print(insertShiftArray(test2, 8))
|
# Index:
# ----------------------
# 1. General options
# 2. School sites
# 1. General Options
# ======================================================
api_token = "" # the token you took from t.me/botfather
log_channel = "" # insert an id to send features, bugs or errors
super_user = "" # for actions that just this user can do
db_name = "data.db" # where to save data
welcome_back = "Bentornato, {}, se vuoi cambiare le tue Informazioni, digita /setup"
bug_msg = "Descrivi il tuo bug con quanti più dettagli possibili:"
feature_msg = "Descrivi la tua richiesta con quanti più dettagli possibili:"
general_info = "Ciao, {}, sono UniToHelper, un bot creato apposta per semplificarti piccole azioni quotidiane, ti farò qualche domanda, in modo tale da automatizzare alcune funzioni..."
'''
2. School sites section
'''
# 2.1 Dipartimento di informatica
# ======================================================
di_first_years = "http://laurea.educ.di.unito.it/index.php/offerta-formativa/calendario/orari/orario-primi-anni?tipoLaurea={}&annoDiCorso={}&AA={}&semestre={}" # Primi anni (1, 2)
di_third_year = "http://laurea.educ.di.unito.it/index.php/offerta-formativa/calendario/orari/orario-curriculum?tipoLaurea={}&corso={}&AA={}&semestre={}" # Curricula terzo anno (3)
di_masterly = "http://magistrale.educ.di.unito.it/index.php/offerta-formativa/calendario/orari/orario-completo?tipoLaurea=M&completo=Magistrale&AA={}&semestre={}" # Magistrale (4, 5)
courses = {'A' : 'A', 'B' : 'B', 'E' : 'Informazione e conoscenza', 'N' : 'Linguaggi e Sistemi', 'S' : 'Reti e Sistemi Informatici', 'DI-STI' : 'Sistemi per il trattamento dell\'informazione', 'DI-RVM' : 'Realtà Virtuale e Multimedialità', 'DI-RSI' : 'Reti e Sistemi Informatici'}
|
"""
callfunc.py
The Frog Programming Language Operation & Keyword: call (func)
Development Leader: @RedoC
"""
class CALLFUNC:
"""
CALLFUNC is the multi class
>> example
run foo(boo)
run print("")
"""
def __init__(self, funcname: str, param: list):
self.funcname = funcname
self.param = param
def getCommandcode(self):
"""
getCommandcode(self)
get commandcode of function calling
:return:
"""
commandcode = "CALL ({funcname})({param})".format(funcname=self.funcname, param=",".join([str(e) for e in self.param])) # commandcode
return commandcode
if __name__ == '__main__':
# unit test
assign_ = CALLFUNC("print", ["hello, world!"])
print(assign_.getCommandcode())
|
class Hamming:
def distance(self, first, second):
num_of_errors = 0
if type(first) != str or type(second) != str:
return "Wrong type of strands"
if len(first) != len(second):
return "Strands should be the same length"
for i in range(len(first)):
if first[i] != second[i]:
num_of_errors += 1
return num_of_errors
|
"""
2021/06/01 Jeong Choi
Weight, inferenced embedding 을 위한 Path 생성 및 parsing 관련 함수
"""
def parse_weight_path(_path):
print('Loading from :', _path)
weight_folder = _path.split('/')[-2]
weight_file = _path.split('/')[-1] # 'w_ep-%05d_l-%.6f' % (epoch, epoch_loss)
epoch_from = int(weight_file.split('_')[1][3:])
exp_info = weight_folder.split('_')[0][4:]
model_info = weight_folder.split('_')[1]
input_repr = weight_folder.split('_')[2]
audio_encoder = weight_folder.split('_')[3]
loss_fn = weight_folder.split('_')[4]
pos_strategy = weight_folder.split('_')[5]
neg_strategy = weight_folder.split('_')[6]
if weight_folder.split('_')[7] == 'pos-wav-aug':
wav_aug = True
elif weight_folder.split('_')[7] == 'pos-no-aug':
wav_aug = False
emb_dim = weight_folder.split('_')[8][4:]
return exp_info, model_info, input_repr, audio_encoder, loss_fn, pos_strategy, neg_strategy, wav_aug, emb_dim, weight_file, epoch_from
def create_weight_folder_name(config):
if config.POS_WAV_AUG:
pos_wav_aug = 'wav-aug'
else:
pos_wav_aug = 'no-aug'
return 'exp-{}_{}_{}_{}_{}_{}_{}_pos-{}_emb-{}'.format(config.EXP_INFO,
config.MODEL_INFO,
config.AUDIO_REPR,
config.AUDIO_ENCODER,
config.LOSS_FN,
config.POS_STRATEGY,
config.NEG_STRATEGY,
pos_wav_aug,
config.EMB_DIM)
|
conditons = True
alcool = 0
gas = 0
disel = 0
while conditons :
T = int(input())
if T == 4:
conditons = False;
else:
if T == 1:
alcool +=1
if T == 2:
gas +=1
if T == 3:
disel +=1
print("MUITO OBRIGADO")
print(f"Alcool: {alcool}")
print(f"Gasolina: {gas}")
print(f"Diesel: {disel}") |
def estimator(data):
output = {'data':data, 'impact': {}, 'severeImpact': {}}
output['impact']['currentlyInfected'] = data['reportedCases'] * 10
output['severeImpact']['currentlyInfected'] = data['reportedCases'] * 50
if data['periodType'] == 'weeks':
data['timeToElapse'] = data['timeToElapse'] * 7
elif data['periodType'] == 'months':
data['timeToElapse'] = data['timeToElapse'] * 30
output['impact']['infectionsByRequestedTime'] = output['impact']['currentlyInfected'] * (2 ** (data['timeToElapse']//3))
output['severeImpact']['infectionsByRequestedTime'] = output['severeImpact']['currentlyInfected'] * (2 ** (data['timeToElapse']//3))
output['impact']['severeCasesByRequestedTime'] = int(15/100 * (output['impact']['infectionsByRequestedTime']))
output['severeImpact']['severeCasesByRequestedTime'] = int(15/100 * (output['severeImpact']['infectionsByRequestedTime']))
output['impact']['hospitalBedsByRequestedTime'] = int((35/100 * (data['totalHospitalBeds'])) - output['impact']['severeCasesByRequestedTime'])
output['severeImpact']['hospitalBedsByRequestedTime'] = int((35/100 * (data['totalHospitalBeds'])) - output['severeImpact']['severeCasesByRequestedTime'])
output['impact']['casesForICUByRequestedTime'] = int(5/100 * output['impact']['infectionsByRequestedTime'])
output['severeImpact']['casesForICUByRequestedTime'] = int(5/100 * output['severeImpact']['infectionsByRequestedTime'])
output['impact']['casesForVentilatorsByRequestedTime'] = int(2/100 * output['impact']['infectionsByRequestedTime'])
output['severeImpact']['casesForVentilatorsByRequestedTime'] = int(2/100 * output['severeImpact']['infectionsByRequestedTime'])
output['impact']['dollarsInFlight'] = int((output['impact']['infectionsByRequestedTime'] * data['region']['avgDailyIncomeInUSD'] * data['region']['avgDailyIncomePopulation']) /data['timeToElapse'])
output['severeImpact']['dollarsInFlight'] = int((output['severeImpact']['infectionsByRequestedTime'] * data['region']['avgDailyIncomeInUSD'] * data['region']['avgDailyIncomePopulation'])/data['timeToElapse'])
return output
|
# -*- coding: utf-8 -*-
"""Top-level package for Temp Monitor."""
__author__ = """Goncalo Magno"""
__email__ = 'goncalo@gmagno.dev'
__version__ = '0.4.0'
|
class TwitterSearchException(Exception):
"""
This class handles all exceptions directly based on TwitterSearch.
"""
# HTTP status codes are stored in TwitterSearch.exceptions due to possible on-the-fly modifications
_error_codes = {
1000 : 'Neither a list nor a string',
1001 : 'Not a list object',
1002 : 'No ISO 6391-1 language code',
1003 : 'No valid result type',
1004 : 'Invalid number',
1005 : 'Invalid unit',
1006 : 'Invalid callback string',
1007 : 'Not a date object',
1008 : 'Invalid boolean',
1009 : 'Invalid string',
1010 : 'Not a valid TwitterSearchOrder object',
1011 : 'No more results available',
1012 : 'No meta data available',
1013 : 'No tweets available',
1014 : 'No results available',
1015 : 'No keywords given',
1016 : 'Invalid dict',
}
def __init__(self, code, msg = None):
self.code = code
if msg:
self.message = msg
else:
self.message = self._error_codes.get(code)
def __str__(self):
return "Error %i: %s" % (self.code, self.message)
|
# -*- python -*-
load("@drake//tools/workspace:os.bzl", "determine_os")
def _impl(repository_ctx):
os_result = determine_os(repository_ctx)
if os_result.error != None:
fail(os_result.error)
if os_result.is_macos:
repository_ctx.symlink(
"/usr/local/opt/double-conversion/include",
"include",
)
repository_ctx.symlink(
Label(
"@drake//tools/workspace/double_conversion:package-macos.BUILD.bazel", # noqa
),
"BUILD.bazel",
)
elif os_result.is_ubuntu:
repository_ctx.symlink(
"/usr/include/double-conversion",
"include/double-conversion",
)
repository_ctx.symlink(
Label(
"@drake//tools/workspace/double_conversion:package-ubuntu.BUILD.bazel", # noqa
),
"BUILD.bazel",
)
else:
fail("Operating system is NOT supported", attr = os_result)
double_conversion_repository = repository_rule(
local = True,
configure = True,
implementation = _impl,
)
|
def linear_search(array, y):
for i in range(len(array)):
if array[i] == y:
return i
return -1
arrSize=int(input("Enter Array Size"))
array=[]
print("Enter Array Elements")
for i in range(arrSize):
array.append(int(input()))
y = int(input("Enter Number you want to find =:-"))
result = linear_search(array, y)
if(result == -1):
print("Element not found")
else:
print("Element found at index: ", result)
|
name={
'Aaliyah':'',
'Aaron':'',
'Abby':'',
'Abigail':'',
'Ada':'',
'Adalee':'',
'Adaline':'',
'Adalyn':'',
'Adalynn':'',
'Addilyn':'',
'Addilynn':'',
'Addison':'',
'Addisyn':'',
'Addyson':'',
'Adelaide':'',
'Adele':'',
'Adelina':'',
'Adeline':'',
'Adelyn':'',
'Adelynn':'',
'Adley':'',
'Adrian':'',
'Adriana':'',
'Adrianna':'',
'Aiden':'',
'Aila':'',
'Ailani':'',
'Aileen':'',
'Ainhoa':'',
'Ainsley':'',
'Aisha':'',
'Aitana':'',
'Alaia':'',
'Alaina':'',
'Alana':'',
'Alani':'',
'Alanna':'',
'Alannah':'',
'Alaya':'',
'Alayah':'',
'Alayna':'',
'Alden':'',
'Aleah':'',
'Aleena':'',
'Alejandra':'',
'Alena':'',
'Alessandra':'',
'Alessia':'',
'Alexa':'',
'Alexander':'',
'Alexandra':'',
'Alexandria':'',
'Alexia':'',
'Alexis':'',
'Alfred':'',
'Alia':'',
'Aliana':'',
'Alianna':'',
'Alice':'',
'Alicia':'',
'Alina':'',
'Alison':'',
'Alisson':'',
'Alivia':'',
'Aliya':'',
'Aliyah':'',
'Aliza':'',
'Allie':'',
'Allison':'',
'Allyson':'',
'Alma':'',
'Alondra':'',
'Alora':'',
'Alvin':'',
'Alyson':'',
'Alyssa':'',
'Amaia':'',
'Amalia':'',
'Amanda':'',
'Amani':'',
'Amara':'',
'Amari':'',
'Amaris':'',
'Amaya':'',
'Amayah':'',
'Amber':'',
'Amelia':'',
'Amelie':'',
'Amina':'',
'Amira':'',
'Amirah':'',
'Amiya':'',
'Amiyah':'',
'Amora':'',
'Amoura':'',
'Amy':'',
'Ana':'',
'Anahi':'',
'Anais':'',
'Analia':'',
'Anastasia':'',
'Anaya':'',
'Andi':'',
'Anand':'',
''
'Andrea':'',
'Andrew':'',
'Angel':'',
'Angela':'',
'Angelica':'',
'Angelina':'',
'Angie':'',
'Anika':'',
'Aniya':'',
'Aniyah':'',
'Ann':'',
'Anna':'',
'Annabella':'',
'Annabelle':'',
'Annalise':'',
'Anne':'',
'Annie':'',
'Annika':'',
'Ansley':'',
'Anson':'',
'Anthony':'',
'Antonella':'',
'Anya':'',
'April':'',
'Arabella':'',
'Archer':'',
'Arden':'',
'Ari':'',
'Aria':'',
'Ariadne':'',
'Ariah':'',
'Ariana':'',
'Arianna':'',
'Ariel':'',
'Ariella':'',
'Arielle':'',
'Ariya':'',
'Ariyah':'',
'Arlette':'',
'Armani':'',
'Arya':'',
'Asher':'',
'Ashley':'',
'Ashlyn':'',
'Ashlynn':'',
'Ashton':'',
'Aspen':'',
'Astrid':'',
'Athena':'',
'Aubree':'',
'Aubrey':'',
'Aubrie':'',
'Aubriella':'',
'Aubrielle':'',
'Audrey':'',
'August':'',
'Augustine':'',
'Aurelia':'',
'Aurora':'',
'Austin':'',
'Austyn':'',
'Autumn':'',
'Ava':'',
'Avalynn':'',
'Averi':'',
'Averie':'',
'Avery':'',
'Aviana':'',
'Avianna':'',
'Axel':'',
'Axton':'',
'Aya':'',
'Ayla':'',
'Ayleen':'',
'Aylin':'',
'Azalea':'',
'Azariah':'',
'Bailee':'',
'Bailey':'',
'Baker':'',
'Barbara':'',
'Baylee':'',
'Bear':'',
'Beatrice':'',
'Beatrix':'',
'Beau':'',
'Beckett':'',
'Beckham':'',
'Belen':'',
'Bella':'',
'Bellamy':'',
'Belle':'',
'Benjamin':'',
'Bennett':'',
'Benson':'',
'Bentley':'',
'Bethany':'',
'Bexley':'',
'Bianca':'',
'Billy':'',
'Blair':'',
'Blaire':'',
'Blake':'',
'Blakely':'',
'Blessing':'',
'Bobby':'',
'Boden':'',
'Bodhi':'',
'Bonnie':'',
'Braden':'',
'Bradley':'',
'Braelyn':'',
'Braelynn':'',
'Brandon':'',
'Branson':'',
'Braxton':'',
'Brayden':'',
'Braydon':'',
'Braylee':'',
'Bria':'',
'Briana':'',
'Brianna':'',
'Briar':'',
'Bridger':'',
'Bridget':'',
'Briella':'',
'Brielle':'',
'Briggs':'',
'Brinley':'',
'Bristol':'',
'Brittany':'',
'Brock':'',
'Brody':'',
'Bronson':'',
'Brooke':'',
'Brooklyn':'',
'Brooklynn':'',
'Brooks':'',
'Bruce':'',
'Brylee':'',
'Brynlee':'',
'Brynn':'',
'Bryson':'',
'Byron':'',
'Cade':'',
'Cadence':'',
'Caleb':'',
'Cali':'',
'Callie':'',
'Calliope':'',
'Callum':'',
'Cameron':'',
'Camila':'',
'Camilla':'',
'Camille':'',
'Camryn':'',
'Cannon':'',
'Carly':'',
'Carmen':'',
'Carolina':'',
'Caroline':'',
'Carolyn':'',
'Carson':'',
'Carter':'',
'Casey':'',
'Cash':'',
'Cassandra':'',
'Cassidy':'',
'Cataleya':'',
'Catalina':'',
'Catherine':'',
'Cecelia':'',
'Cecilia':'',
'Celeste':'',
'Celia':'',
'Celine':'',
'Chana':'',
'Chance':'',
'Chandler':'',
'Chanel':'',
'Charlee':'',
'Charleigh':'',
'Charles':'',
'Charley':'',
'Charli':'',
'Charlie':'',
'Charlotte':'',
'Chase':'',
'Chaya':'',
'Chelsea':'',
'Cheyenne':'',
'Chloe':'',
'Chris':'',
'Christian':'',
'Christina':'',
'Christine':'',
'Christopher':'',
'Claire':'',
'Clara':'',
'Clare':'',
'Clarissa':'',
'Clark':'',
'Clay':'',
'Clayton':'',
'Clementine':'',
'Cleo':'',
'Cody':'',
'Colby':'',
'Cole':'',
'Colette':'',
'Collins':'',
'Colter':'',
'Colton':'',
'Connor':'',
'Cooper':'',
'Cora':'',
'Coraline':'',
'Corinne':'',
'Crew':'',
'Crystal':'',
'Cynthia':'',
'Dahlia':'',
'Daisy':'',
'Dakota':'',
'Dalary':'',
'Daleyza':'',
'Dallas':'',
'Dalton':'',
'Damian':'',
'Damon':'',
'Dana':'',
'Dane':'',
'Dani':'',
'Daniel':'',
'Daniela':'',
'Daniella':'',
'Danielle':'',
'Danna':'',
'Daphne':'',
'Darwin':'',
'David':'',
'Davina':'',
'Davis':'',
'Dawson':'',
'Daxton':'',
'Dayana':'',
'Dayton':'',
'Dean':'',
'Deborah':'',
'Declan':'',
'Delaney':'',
'Delilah':'',
'Della':'',
'Demi':'',
'Denver':'',
'Destiny':'',
'Devon':'',
'Diana':'',
'Diego':'',
'Dior':'',
'Dixie':'',
'Dominic':'',
'Dorothy':'',
'Drake':'',
'Dream':'',
'Duke':'',
'Dulce':'',
'Dylan':'',
'Easton':'',
'Eden':'',
'Edgar':'',
'Edison':'',
'Edith':'',
'Edward':'',
'Edwin':'',
'Egypt':'',
'Eileen':'',
'Elaina':'',
'Elaine':'',
'Eleanor':'',
'Elena':'',
'Eli':'',
'Eliana':'',
'Elianna':'',
'Elias':'',
'Elijah':'',
'Elina':'',
'Elisa':'',
'Elisabeth':'',
'Elise':'',
'Eliza':'',
'Elizabeth':'',
'Ella':'',
'Elle':'',
'Ellen':'',
'Elliana':'',
'Ellianna':'',
'Ellie':'',
'Elliot':'',
'Elliott':'',
'Ellis':'',
'Ellison':'',
'Elodie':'',
'Eloise':'',
'Elora':'',
'Elsa':'',
'Elsie':'',
'Elyse':'',
'Emani':'',
'Ember':'',
'Emberly':'',
'Emelia':'',
'Emely':'',
'Emerald':'',
'Emerie':'',
'Emerson':'',
'Emersyn':'',
'Emery':'',
'Emilee':'',
'Emilia':'',
'Emily':'',
'Emma':'',
'Emmaline':'',
'Emmalyn':'',
'Emmalynn':'',
'Emmeline':'',
'Emmett':'',
'Emmie':'',
'Emmy':'',
'Emory':'',
'Ensley':'',
'Erika':'',
'Erin':'',
'Esme':'',
'Esmeralda':'',
'Esperanza':'',
'Estella':'',
'Estelle':'',
'Esther':'',
'Estrella':'',
'Ethan':'',
'Eva':'',
'Evan':'',
'Evangeline':'',
'Eve':'',
'Evelyn':'',
'Evelynn':'',
'Everett':'',
'Everlee':'',
'Everleigh':'',
'Everly':'',
'Evie':'',
'Ezekiel':'',
'Ezra':'',
'Fabian':'',
'Faith':'',
'Fallon':'',
'Fatima':'',
'Faye':'',
'Felicity':'',
'Felix':'',
'Fernanda':'',
'Fernando':'',
'Finley':'',
'Finn':'',
'Finnegan':'',
'Fiona':'',
'Fletcher':'',
'Flora':'',
'Florence':'',
'Ford':'',
'Forest':'',
'Forrest':'',
'Foster':'',
'Fox':'',
'Frances':'',
'Francesca':'',
'Francisco':'',
'Frank':'',
'Frankie':'',
'Franklin':'',
'Frederick':'',
'Freya':'',
'Freyja':'',
'Frida':'',
'Gabriel':'',
'Gabriela':'',
'Gabriella':'',
'Gabrielle':'',
'Gael':'',
'Galilea':'',
'Gary':'',
'Gavin':'',
'Gemma':'',
'Genesis':'',
'Genevieve':'',
'George':'',
'Georgia':'',
'Gerald':'',
'Gia':'',
'Giana':'',
'Gianna':'',
'Gianni':'',
'Giovanna':'',
'Giovanni':'',
'Giselle':'',
'Giuliana':'',
'Gloria':'',
'Grace':'',
'Gracelyn':'',
'Gracelynn':'',
'Gracie':'',
'Graham':'',
'Grant':'',
'Grayson':'',
'Greta':'',
'Greyson':'',
'Griffin':'',
'Guadalupe':'',
'Gwen':'',
'Gwendolyn':'',
'Hadassah':'',
'Hadlee':'',
'Hadleigh':'',
'Hadley':'',
'Hailee':'',
'Hailey':'',
'Haisley':'',
'Haley':'',
'Halle':'',
'Hallie':'',
'Halo':'',
'Hana':'',
'Hanna':'',
'Hannah':'',
'Harlee':'',
'Harleigh':'',
'Harley':'',
'Harlow':'',
'Harmoni':'',
'Harmony':'',
'Harper':'',
'Harriet':'',
'Harrison':'',
'Harvey':'',
'Hattie':'',
'Haven':'',
'Hayden':'',
'Hayes':'',
'Haylee':'',
'Hayley':'',
'Hazel':'',
'Heath':'',
'Heaven':'',
'Heavenly':'',
'Hector':'',
'Heidi':'',
'Helen':'',
'Helena':'',
'Hendrix':'',
'Henley':'',
'Henry':'',
'Holden':'',
'Holland':'',
'Holly':'',
'Hope':'',
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'Kalyenci̇':'',
'Turanoğlu':'',
'Orhan':'',
'Yilmaz':'',
'Kuş':'',
'Seri̇n':'',
'Keser':'',
'Şahi̇n':'',
'Yüzer':'',
'Özcanoğlu':'',
'Dere':'',
'Yeti̇z':'',
'Adisanli':'',
'Akel':'',
'Taşkin':'',
'Aydin':'',
'Akin':'',
'Öner':'',
'Uçar':'',
'Korkmazoğlu':'',
'Ni̇meti̇gi̇l':'',
'Arslan':'',
'Çinar':'',
'Tatli':'',
'Atci':'',
'Özer':'',
'Ulutaş':'',
'Karataş':'',
'Çi̇ftçi̇':'',
'Özüdoğru':'',
'Ökmen':'',
'Koptur':'',
'Dedemoğlu':'',
'Kaya':'',
'Özbeyler':'',
'Bağli':'',
'Dursun':'',
'Bekar':'',
'Koç':'',
'Özdemi̇r':'',
'Mendeş':'',
'Güngör Uzunoğlu':'',
'Yavuz':'',
'Hi̇çyilmaz':'',
'Aras':'',
'Teki̇n':'',
'Yeşi̇lfi̇dan':'',
'Saraç':'',
'Güveren':'',
'Kivrak':'',
'Erdağ':'',
'Seven':'',
'Gül':'',
'Yildiz':'',
'Aydemi̇r':'',
'Kaya':'',
'Saatçioğlu':'',
'Gençtürk':'',
'Yalçin':'',
'Aksu':'',
'Ceylan':'',
'Ayyildiz':'',
'Yildirim':'',
'Dağli':'',
'Mönür':'',
'Kesi̇k':'',
'Coşkun':'',
'Azar':'',
'Baran':'',
'Artuç':'',
'Yilmaz':'',
'Tiraş':'',
'Güneş':'',
'Bakar':'',
'Di̇nçer':'',
'Alici':'',
'Şi̇mşek':'',
'Ünal':'',
'Yilmaz':'',
'Doruk':'',
'Dağlioğlu':'',
'Kaan':'',
'Mavi̇':'',
'Tezel':'',
'Köylüoğlu':'',
'Erden':'',
'Seçki̇n':'',
'Kaylan':'',
'Ati̇k':'',
'Aslaner':'',
'Evci̇':'',
'Yücel':'',
'Aytaç':'',
'Mutlu':'',
'Coşgun':'',
'Sertel':'',
'Coşkun':'',
'Burak':'',
'Erdem':'',
'Baglars':'',
'Para':'',
'Caf':'',
'Sevi̇mli̇':'',
'Cantay':'',
'Kolsuz':'',
'Şahi̇n':'',
'İmali':'',
'Geçmen':'',
'Şenöz':'',
'Gül':'',
'Çelebi̇':'',
'Atar':'',
'Çalik':'',
'Kanat':'',
'Göktürk':'',
'Baştemi̇r':'',
'Almofti':'',
'Gedük':'',
'Köse':'',
'İlhan':'',
'Topcuoğlu':'',
'Peker':'',
'Yamak':'',
'Öztürk':'',
'Çolakerol':'',
'Avlanir':'',
'Keçeci̇':'',
'Koçoğlu':'',
'Akman':'',
'Dedeoğlu':'',
'Teki̇r':'',
'Tokmak':'',
'Ari':'',
'Aksaç':'',
'Arici':'',
'Önal':'',
'Baş':'',
'Gürel':'',
'Afşar':'',
'Bölükbaş':'',
'Altun':'',
'Kuday':'',
'Kartal':'',
'Eylen':'',
'Kilbacak':'',
'Memi̇ş':'',
'Güleç':'',
'Çamur':'',
'Bal':'',
'Cani̇k':'',
'Tozlu':'',
'Bi̇lgi̇n':'',
'Sancar':'',
'Uyar':'',
'İri̇s':'',
'Ersoy':'',
'Yardimci':'',
'Si̇vri̇':'',
'Arslan':'',
'Bi̇lge':'',
'Büyükceran':'',
'Ari':'',
'Akinci':'',
'Aydin':'',
'Parasiz':'',
'Yücel':'',
'İnce':'',
'Taşci':'',
'Bayramoğlu':'',
'Yilanli':'',
'Kavurgaci':'',
'Teği̇n':'',
'Güler':'',
'Karan':'',
'Öz':'',
'Kaykisiz':'',
'Di̇varci':'',
'Teği̇n':'',
'Pirti':'',
'Demi̇rcan':'',
'Yilmaz':'',
'Mi̇rza':'',
'Kisaoğlu':'',
'Yilmaz':'',
'Yeni̇ay':'',
'Yilmaz':'',
'Aktaş':'',
'Kunak':'',
'Erdoğan':'',
'Erdoğan':'',
'Güldamla':'',
'Atak':'',
'Çinarlik':'',
'Erken':'',
'Sakallioğlu':'',
'Karasu':'',
'Semerci̇':'',
'Kocayi̇ği̇t':'',
'Ati̇k':'',
'Deni̇z':'',
'Atçeken':'',
'Pazir':'',
'Ayranci':'',
'Çölbe':'',
'Topuz':'',
'Kala':'',
'Yanni̇':'',
'Yildiz':'',
'Özalp':'',
'Adali':'',
'Altunyaprak':'',
'Kaşikçi':'',
'Demi̇rbaş':'',
'Yilmaz':'',
'Seki̇n':'',
'Yönet':'',
'Küçükceran':'',
'Güven':'',
'İnan':'',
'Tani̇ş':'',
'Uğurlu':'',
'Şahan':'',
'Bolatkale':'',
'Keski̇n':'',
'Geyi̇k':'',
'Alaybeyoğlu':'',
'Sayyi̇ği̇t':'',
'Ceran':'',
'İzci̇':'',
'Höke':'',
'Sağlam':'',
'Seyrek':'',
'Erkan':'',
'Çeti̇n':'',
'Öztürk':'',
'Uzunca':'',
'Aydin':'',
'Uzuncan':'',
'Ünal':'',
'Pekdoğan':'',
'Kaya':'',
'Özdemi̇r':'',
'Ersöz':'',
'Alkiş':'',
'Zengi̇n':'',
'Yi̇ldi̇z':'',
'Şener':'',
'Büyükkalayci':'',
'Yilmaz':'',
'Demi̇rel':'',
'Moran':'',
'Çayli':'',
'Çangal':'',
'Vural':'',
'Kubat':'',
'Katran':'',
'Leymunçi̇çeği̇':'',
'Aydin':'',
'Bekar':'',
'Ünal':'',
'Pi̇ri̇':'',
'Bozkuş':'',
'Kinalioğlu':'',
'Tarakci':'',
'Ürkmez':'',
'Elgörmüş':'',
'Yağli':'',
'Çeli̇k':'',
'Özkaya':'',
'Yanardağ':'',
'Özhan':'',
'Karaağaç':'',
'Sezgi̇n':'',
'Kaplankiran':'',
'Ti̇lbe':'',
'Bayraktar':'',
'Topçu':'',
'Gökçek':'',
'Küçük':'',
'Gökçek':'',
'Yi̇ği̇t':'',
'Molla':'',
'Koç':'',
'Çankaya':'',
'Çevi̇k':'',
'Yildiz':'',
'İnce':'',
'Kasap':'',
'Yumak':'',
'Çeti̇nkaya':'',
'Karadaş':'',
'Kutan':'',
'Özdenoğlu':'',
'Yilmaz':'',
'Konuk':'',
'Turan':'',
'Akiş':'',
'Kizilmeşe':'',
'Çantay':'',
'Camci':'',
'Derhem':'',
'Ahçi':'',
'Öztürk':'',
'Pehli̇van':'',
'Temel':'',
'Kiran':'',
'Kiziltoprak':'',
'Kayihan':'',
'Demi̇r':'',
'Günyel':'',
'Özanlağan':'',
'Şerbetçi̇':'',
'Senemtaşi':'',
'Köse':'',
'Karadağ':'',
'Demi̇r':'',
'Güçlü':'',
'Çi̇çek':'',
'Tatli':'',
'Nozoğlu':'',
'Kartal':'',
'Bayram':'',
'Ateş':'',
'Yaprak':'',
'Genç':'',
'Kocabaş':'',
'Mutlu':'',
'Akyüz':'',
'İştar':'',
'Kilinç':'',
'Erdem':'',
'Arici':'',
'Okudan':'',
'Tunç':'',
'Yildiz':'',
'Barut':'',
'Kiliçcioğlu':'',
'Ertan':'',
'Yavuz':'',
'Çeli̇k':'',
'Yüksel':'',
'Güzel':'',
'Özdemi̇r':'',
'Koçar':'',
'Taşli':'',
'İstek':'',
'Temli̇':'',
'Arslankeçeci̇oğlu':'',
'Şengül':'',
'Çeti̇ner':'',
'Eroğlu':'',
'Dağdelen':'',
'Çete':'',
'Deni̇z':'',
'İsen':'',
'Karamahmutoğlu':'',
'İzgi̇':'',
'Duyu':'',
'Demi̇r':'',
'Balaban':'',
'Yildiz':'',
'İlker':'',
'Özkan':'',
'Gülsoy':'',
'Doğan':'',
'Gedi̇kli̇':'',
'Akgün':'',
'Karakaya':'',
'Taş':'',
'Toyran':'',
'İbi̇şoğlu':'',
'Duran':'',
'Teki̇nsoy':'',
'Yapar':'',
'Taş':'',
'Söylemez':'',
'Avci':'',
'Ünlü':'',
'Zengi̇n':'',
'Menekşe':'',
'Arici':'',
'Şahi̇n':'',
'Işik':'',
'Savğa':'',
'Akbaş':'',
'İli̇k':'',
'Yildiz':'',
'Keleş':'',
'Özkan':'',
'Di̇ncer':'',
'Turgut':'',
'Oğuzsoy':'',
'Aşan':'',
'Işik':'',
'Uçar':'',
'Akman':'',
'Teker':'',
'Yildirimçakar':'',
'Keser':'',
'Çeli̇k':'',
'Karakuş':'',
'Kisa':'',
'Akbaş':'',
'Yalinkiliç':'',
'Çi̇ftçi̇':'',
'Ayaz':'',
'Sadunoğlu':'',
'Güler':'',
'Kilinç':'',
'Ural':'',
'Gülteki̇n':'',
'Karaca':'',
'Kansu':'',
'Yağan':'',
'Büdün':'',
'Demi̇r':'',
'Yüce':'',
'Özdemi̇r':'',
'Yüksel':'',
'Öter':'',
'Kahraman':'',
'Duman':'',
'Kopan':'',
'Karaaslan':'',
'Kahreman':'',
'Avci':'',
'Kurul':'',
'Sağlam':'',
'Sansarci':'',
'Akkan':'',
'Pi̇rdoğan':'',
'Rençber':'',
'Dağdelen':'',
'Sülük':'',
'Köse':'',
'Yilmaz':'',
'Sağlam':'',
'Karaman':'',
'Mutluer':'',
'Erdem':'',
'Eyüp':'',
'Yakişan':'',
'Teki̇n':'',
'Nalbant':'',
'Yildirim':'',
'Erşen':'',
'Sarieki̇z':'',
'Çeti̇nkaya':'',
'Alkaç':'',
'Şen':'',
'Güleşen':'',
'Uyar':'',
'Güçlü':'',
'Yazici':'',
'Doğangüzel':'',
'Akkaya':'',
'Feyzullahoğlu':'',
'Şahi̇n':'',
'Rubalcaba':'',
'Sanders':'',
'Kubrick':'',
'Truman':'',
'Spielberg':'',
'Beatty':'',
'Dahl':'',
'Motian':'',
'İbrahimova':'',
"O'Connor":'',
'Hitler':'',
'Napolyon':'',
'Goebbels':'',
'Çiller':'',
'LaPalombara':'',
'Troçki':'',
'Stalin':'',
'Lenin':'',
'Primakov':'',
}
|
n1 = int(input('Digite o primeiro número: '))
n2 = int(input('Digite o segundo número: '))
n3 = int(input('Digite o terceiro número: '))
n4 = int(input('Digite o quarto número: '))
n5 = int(input('Digite o quinto número: '))
n6 = int(input('Digite o sexto número: '))
n7 = int(input('Digite o sétimo número: '))
n8 = int(input('Digite o oitavo número: '))
n9 = int(input('Digite o nono número: '))
n10 = int(input('Digite o décimo número: '))
media = (n1+n2+n3+n4+n5+n6+n7+n8+n9+n10)/10
print(f'A média é: {media}') |
γ = 0.5
A -= γ * grad_A
b -= γ * grad_b
C -= γ * grad_C
d -= γ * grad_d
U = relu(A@x+b)
q = softmax(C@U+d)
L = - np.log(q[y])
print("after update, L=", L) |
""" Driver args """
data_path = '/Users/aa56927-admin/Desktop/NLP_Done_Right/sentiment_classification/data/Rotten_Tomatoes/'
output_path = 'test-blind.output.txt'
model = 'RNN' # RNN, FFNN
run_on_test_flag = True
run_on_manual_flag = True
seq_max_len = 60 # also can be computed more systematically looking at length distribution in corpus
model_path = './model.pt'
if model == 'FFNN':
# training config
no_classes = 2
epochs = 5
batch_size = 64
lr_schedule = 'None' # None / CLR / CALR
optimizer = 'adam' # adagrad
initial_lr = 0.001
weight_decay = 1e-4
word_dropout_rate = 0.3
# network config
input_dim = 300
hidden_1 = 150
hidden_2 = 75
hidden_3 = 50
dropout = 0.2
elif model == 'RNN':
# training config
no_classes = 2
rec_unit = 'LSTM' # GRU
epochs = 30
batch_size = 64
lr_schedule = 'None' # None / CLR / CALR
optimizer = 'adam' # adagrad
initial_lr = 0.01
lr_decay = 0.1
weight_decay = 1e-4
dropout = 0.2
# Stacked RNN units
no_of_rec_units = 2
# inside RNN unit
hidden_size = 100
rnn_dropout = 0.05
""" ElMo Config """
""" BERT Config """
""" CNN Config """
|
# https://atcoder.jp/contests/abc194/tasks/abc194_b
N = int(input())
job_list = []
a_min_idx, b_min_idx = 0, 0
a_2nd, b_2nd = 0, 0
for i in range(N):
a, b = list(map(int, input().split()))
job_list.append([a, b])
if job_list[a_min_idx][0] > a:
a_2nd = a_min_idx
a_min_idx = i
if job_list[b_min_idx][1] > b:
b_2nd = b_min_idx
b_min_idx = i
ans = 0
if a_min_idx == b_min_idx:
ans = min(max(job_list[a_min_idx][0], job_list[b_2nd][1]), max(job_list[a_2nd][0], job_list[b_min_idx][1]),
job_list[a_min_idx][0] + job_list[b_min_idx][1])
print(ans)
exit()
ans = max(job_list[a_min_idx][0], job_list[b_min_idx][1])
print(ans)
|
# https://practice.geeksforgeeks.org/problems/get-minimum-element-from-stack/1#
# Approach is to store an array containing stack elements and minEle in separate variable
# For push
# if minEle is None add element to s and assign minEle - element
# if minEle <= element add element to s
# else add 2*x-minEle in s and assign minEle the element value
# For pop
# if s is empty return -1
# if last element of s is >= minEle return and remove last element of s
# else return minEle assign minEle = 2*minEle - last value of S, and also remove last element
# assign minEle None if size of s is 0
# For getMin
# return minEle if not None else -1
class Stack:
def __init__(self):
self.s = []
self.minEle = None
def push(self, x):
if self.minEle is None:
self.minEle = x
self.s.append(x)
else:
if self.minEle <= x:
self.s.append(x)
else:
self.s.append(2 * x - self.minEle)
self.minEle = x
def pop(self):
val = -1
if len(self.s) != 0:
if self.s[-1] >= self.minEle:
val = self.s[-1]
else:
val = self.minEle
self.minEle = 2 * self.minEle - self.s[-1]
del self.s[-1]
if len(self.s) == 0:
self.minEle = None
return val
def getMin(self):
return self.minEle if self.minEle is not None else -1
if __name__ == '__main__':
t = int(input())
for _ in range(t):
q = int(input())
arr = [int(x) for x in input().split()]
stk = Stack()
qi = 0
qn = 1
while qn <= q:
qt = arr[qi]
if qt == 1:
stk.push(arr[qi + 1])
qi += 2
elif qt == 2:
print(stk.pop(), end=' ')
qi += 1
else:
print(stk.getMin(), end=' ')
qi += 1
qn += 1
print()
|
class ListaMultimedia():
archivos = []
contar = 0
def __init__(self,archivos=[]):
self.archivos = archivos
def agregar(self,p):
self.archivos.append(p)
self.contar += 1
def mostrar(self):
for p in self.archivos:
print(p)
def cantidad(self):
return"""Total de objetos en la lista: {}""".format(self.contar) |
# MIT License
#
# Copyright (c) 2017 Matt Boyer
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
VALID_PAGE_SIZES = (1, 512, 1024, 2048, 4096, 8192, 16384, 32768)
SQLITE_TABLE_COLUMNS = {
'sqlite_master': ('type', 'name', 'tbl_name', 'rootpage', 'sql',),
'sqlite_sequence': ('name', 'seq',),
'sqlite_stat1': ('tbl', 'idx', 'stat',),
'sqlite_stat2': ('tbl', 'idx', 'sampleno', 'sample'),
'sqlite_stat3': ('tbl', 'idx', 'nEq', 'nLt', 'nDLt', 'sample'),
'sqlite_stat4': ('tbl', 'idx', 'nEq', 'nLt', 'nDLt', 'sample'),
}
# These are the integers used in ptrmap entries to designate the kind of page
# for which a given ptrmap entry holds a notional "child to parent" pointer
BTREE_ROOT_PAGE = 1
FREELIST_PAGE = 2
FIRST_OFLOW_PAGE = 3
NON_FIRST_OFLOW_PAGE = 4
BTREE_NONROOT_PAGE = 5
PTRMAP_PAGE_TYPES = (
BTREE_ROOT_PAGE,
FREELIST_PAGE,
FIRST_OFLOW_PAGE,
NON_FIRST_OFLOW_PAGE,
BTREE_NONROOT_PAGE,
)
OVERFLOW_PAGE_TYPES = (
FIRST_OFLOW_PAGE,
NON_FIRST_OFLOW_PAGE,
)
# These are identifiers used internally to keep track of page types *before*
# specialised objects can be instantiated
FREELIST_TRUNK_PAGE = 'freelist_trunk'
FREELIST_LEAF_PAGE = 'freelist_leaf'
PTRMAP_PAGE = 'ptrmap_page'
UNKNOWN_PAGE = 'unknown'
FREELIST_PAGE_TYPES = (
FREELIST_TRUNK_PAGE,
FREELIST_LEAF_PAGE,
)
NON_BTREE_PAGE_TYPES = (
FREELIST_TRUNK_PAGE,
FIRST_OFLOW_PAGE,
NON_FIRST_OFLOW_PAGE,
PTRMAP_PAGE,
)
|
def test_login_redirect(client):
"""
Test that all requests redirect to the login page
"""
URLS = [
"/web-ui/overview/",
"/web-ui/rq/create_sip",
"/api/list-frozen-objects"
]
for url in URLS:
result = client.get(url)
assert result.status_code == 302
assert "/web-ui/login?" in result.headers["Location"]
|
# #### We create a function cleanQ so we can do the cleaning and preperation of our data
# #### INPUT: String
# #### OUTPUT: Cleaned String
def cleanQ(query):
query = query.lower()
tokenizer = RegexpTokenizer(r'\w+')
tokens = tokenizer.tokenize(query)
stemmer=[ps.stem(i) for i in tokens]
filtered_Q = [w for w in stemmer if not w in stopwords.words('english')]
return filtered_Q
# #### We create a function computeTF so we can calculate the tf
# #### INPUT: Dictionary where the keys are the terms_id and the values are the frequencies of this term Id in the document
# #### OUTPUT: TF of the specific Term_id in the corresponding document
def computeTF(doc_words):
bow = 0
for k, v in doc_words.items():
bow = bow + v
tf_word = {}
for word, count in doc_words.items():
tf_word[word] = count / float(bow)
return tf_word
|
#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
# OpneWinchPy : a library for controlling the Raspberry Pi's Winch
# Copyright (c) 2020 Mickael Gaillard <mick.gaillard@gmail.com>
__version__ = "0.1.0"
|
lst = []
count_of_elements = int(input("How many elements want to store in list?"))
for i in range(count_of_elements):
element = input("Enter the element:")
lst.append(element)
print(lst)
|
"""
ende nose tests
project : Ende
version : 0.1.0
status : development
modifydate : 2015-05-06 19:30:00 -0700
createdate : 2015-05-05 05:36:00 -0700
website : https://github.com/tmthydvnprt/ende
author : tmthydvnprt
email : tmthydvnprt@users.noreply.github.com
maintainer : tmthydvnprt
license : MIT
copyright : Copyright 2015, project
credits :
"""
__all__ = ['test_data', 'test_file']
|
class Solution:
def groupAnagrams(self, strs: List[str]) -> List[List[str]]:
ans = []
one_hot = {}
for word in strs:
mapping = [0 for _ in range(26)]
for char in word:
representation = ord(char)
mapping[representation % 26] += 1
mapping = tuple(mapping)
if mapping not in one_hot:
one_hot[mapping] = []
one_hot[mapping].append(word)
for key, values in one_hot.items():
ans.append(values)
return ans
|
# -*- coding: utf-8 -*-
__author__ = 'Tommy Stallings'
__email__ = 'tommy.stallings2@gmail.com'
__version__ = '1.0'
|
def GetChargeLevel():
return {'data': 42, 'error': 'NO_ERROR'}
def GetBatteryTemperature():
return {'data': 25.4, 'error': 'NO_ERROR'}
def GetBatteryVoltage():
return {'data': 3111, 'error': 'NO_ERROR'}
def GetBatteryCurrent():
return {'data': 800, 'error': 'NO_ERROR'}
def GetIoVoltage():
return {'data': 5432, 'error': 'NO_ERROR'}
def GetIoCurrent():
return {'data': 300, 'error': 'NO_ERROR'}
def GetStatus():
return {'data': {
'powerInput': 'adapter connected',
'powerInput5vIo': 'powered'
}, 'error': 'NO_ERROR'}
|
print ("Digite uma sequência de números terminada por zero.")
soma = 0
valor = 1
while valor != 0:
valor = int(input("Digite o valor a ser somado: "))
soma = soma + valor
print("A soma da sequência é ", soma) |
def message_replier(messages):
for message in messages:
userid = message.from_user.id
banlist = redisserver.sismember('zigzag_banlist', '{}'.format(userid))
if banlist:
return
if userid in messanger_list:
bot.reply_to(message, MESSANGER_LEAVE_MSG, parse_mode="Markdown")
messanger_list.remove(userid)
bot.send_message("-" + str(SUPPORT_GP), "New feedback!:")
bot.forward_message("-" + str(SUPPORT_GP), message.chat.id, message.message_id)
return
if REPLIER:
if message.text in reply_message_list:
bot.reply_to(message, reply_message_list.get(message.text), parse_mode="Markdown")
if message.text == "Send feedback":
bot.reply_to(message, MESSANGER_JOIN_MSG, parse_mode="Markdown")
messanger_list.append(userid)
return
if userid in in_chat_with_support:
bot.forward_message("-" + str(SUPPORT_GP), message.chat.id, message.message_id)
return
if message.from_user.id in ADMINS_IDS:
if message.chat.id == -SUPPORT_GP:
try:
bot.forward_message(message.reply_to_message.forward_from.id, message.chat.id, message.message_id)
bot.reply_to(message, "REPLY SENT")
except:
bot.reply_to(message, "ERROR SENDING?")
|
"""
import time
import redis
from flask import render_template, request, current_app, jsonify, redirect, session
from init import app
from utils.interceptors import loginOptional, jsonRequest, loginRequiredJSON
from utils.jsontools import *
from utils.logger import log
from scraper.video import dispatch
from scraper.video.Twitter import Twitter
@app.route('/helper/get_twitter_info.do', methods = ['POST'])
@loginRequiredJSON
@jsonRequest
def ajax_helper_get_twitter_info(rd, user, data):
log(obj = {'url': data.url})
obj, cleanURL = dispatch(data.url)
if obj.NAME != 'twitter' :
log(obj = {'msg': 'NOT_TWITTER'})
return makeResponseFailed('NOT_TWITTER')
info = obj.get_metadata(obj, cleanURL)
if info["status"] != 'SUCCEED' :
log(obj = {'msg': 'FETCH_FAILED', 'info': info})
return makeResponseFailed('FETCH_FAILED')
return info
@app.route('/helper/get_ytb_info.do', methods = ['POST'])
@loginRequiredJSON
@jsonRequest
def ajax_helper_get_ytb_info(rd, user, data):
log(obj = {'url': data.url})
obj, cleanURL = dispatch(data.url)
if obj.NAME != 'youtube' :
log(obj = {'msg': 'NOT_YOUTUBE'})
return makeResponseFailed('NOT_YOUTUBE')
info = obj.get_metadata(obj, cleanURL)
if info["status"] != 'SUCCEED' :
log(obj = {'msg': 'FETCH_FAILED', 'info': info})
return makeResponseFailed('FETCH_FAILED')
return info
"""
|
average = float(input('Média no semestre: '))
absence = int(input('Frequência no semestre: '))
diff_average = 6 - average
diff_absence = 75 - absence
if average >= 6 and absence >= 75:
print(f'Conceito: aprovado')
if average < 6 and absence >= 75:
print(f'Conceito: exame especial')
print(f'Justificativa: média {diff_average:.2f} abaixo da mínima')
if absence < 75:
print(f'Conceito: reprovado por faltas')
print(f'Justificativa: frequência {diff_absence}% abaixo da mínima')
|
# -*- coding: utf-8 -*-
info = {
"%spellout-cardinal-feminine": {
"0": "null;",
"1": "ein;",
"2": "tvær;",
"3": "tríggjar;",
"4": "fýre;",
"(5, 19)": "=%spellout-cardinal-masculine=;",
"(20, 29)": "tjúgo[>>];",
"(30, 39)": "tríati[>>];",
"(40, 49)": "fýrati[>>];",
"(50, 59)": "fimmti[>>];",
"(60, 69)": "seksti[>>];",
"(70, 79)": "sjeyti[>>];",
"(80, 89)": "áttati[>>];",
"(90, 99)": "níti[>>];",
"(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];",
"(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];",
"(1000000, 1999999)": "ein millión[ og >>];",
"(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];",
"(1000000000, 1999999999)": "ein milliard[ og >>];",
"(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];",
"(1000000000000, 1999999999999)": "ein billión[ og >>];",
"(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];",
"(1000000000000000, 1999999999999999)": "ein billiard[ og >>];",
"(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];",
"(1000000000000000000, 'inf')": "=#,##0=;"
},
"%spellout-cardinal-masculine": {
"0": "null;",
"1": "ein;",
"2": "tveir;",
"3": "tríggir;",
"4": "fýre;",
"5": "fimm;",
"6": "seks;",
"7": "sjey;",
"8": "átta;",
"9": "níggju;",
"10": "tíggju;",
"11": "ellivu;",
"12": "tólv;",
"13": "trettan;",
"14": "fjúrtan;",
"15": "fímtan;",
"16": "sekstan;",
"17": "seytan;",
"18": "átjan;",
"19": "nítjan;",
"(20, 29)": "tjúgo[>>];",
"(30, 39)": "tríati[>>];",
"(40, 49)": "fýrati[>>];",
"(50, 59)": "fimmti[>>];",
"(60, 69)": "seksti[>>];",
"(70, 79)": "sjeyti[>>];",
"(80, 89)": "áttati[>>];",
"(90, 99)": "níti[>>];",
"(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];",
"(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];",
"(1000000, 1999999)": "ein millión[ og >>];",
"(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];",
"(1000000000, 1999999999)": "ein milliard[ og >>];",
"(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];",
"(1000000000000, 1999999999999)": "ein billión[ og >>];",
"(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];",
"(1000000000000000, 1999999999999999)": "ein billiard[ og >>];",
"(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];",
"(1000000000000000000, 'inf')": "=#,##0=;"
},
"%spellout-cardinal-neuter": {
"0": "null;",
"1": "eitt;",
"2": "tvey;",
"3": "trý;",
"4": "fýre;",
"(5, 19)": "=%spellout-cardinal-masculine=;",
"(20, 29)": "tjúgo[>>];",
"(30, 39)": "tríati[>>];",
"(40, 49)": "fýrati[>>];",
"(50, 59)": "fimmti[>>];",
"(60, 69)": "seksti[>>];",
"(70, 79)": "sjeyti[>>];",
"(80, 89)": "áttati[>>];",
"(90, 99)": "níti[>>];",
"(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];",
"(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];",
"(1000000, 1999999)": "ein millión[ og >>];",
"(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];",
"(1000000000, 1999999999)": "ein milliard[ og >>];",
"(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];",
"(1000000000000, 1999999999999)": "ein billión[ og >>];",
"(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];",
"(1000000000000000, 1999999999999999)": "ein billiard[ og >>];",
"(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];",
"(1000000000000000000, 'inf')": "=#,##0=;"
},
"%spellout-numbering": {
"(0, 'inf')": "=%spellout-cardinal-masculine=;"
},
"%spellout-numbering-year": {
"(0, 9999)": "=%spellout-numbering=;",
"(10000, 'inf')": "=%spellout-numbering=;"
}
} |
print("dame un número")
numero1=input()
print ("dame otro número")
numero2=input()
print (numero1,numero2)
print("dame tu nombre")
nombre=input()
print("dame tu apellido paterno")
apellidopaterno=input()
print("dame tu apellido materno")
apellidomaterno=input()
print(nombre,apellidopaterno,apellidomaterno)
print(nombre+apellidopaterno+apellidomaterno)
print(nombre,apellidopaterno,apellidomaterno)
print(type(nombre))
list=["matemáticas","español","historia"]
print(list) |
def maior_E_menor(x, y):
if x > y:
return x, y
return y, x
x = int(input())
y = int(input())
if(x == y):
print("0")
else:
maior, menor = maior_E_menor(x, y)
soma = 0
menor +=1
while(menor < maior):
if menor % 2 != 0:
soma += menor
menor += 1
print(soma) |
# TODO: Use a real tree structure
class ElsterXmlTreeNode(object):
"""
Our representation of the Elster XML data structure.
A Node can have a name and subelements.
Additionally, some nodes can be repeated and can be specific for one person.
"""
def __init__(self, name, sub_elements, is_person_specific=False, repetitions=1, is_repeatable=False):
self.name = name
self.sub_elements = sub_elements
self.is_person_specific = is_person_specific
self.repetitions = repetitions
self.is_repeatable = is_repeatable
_PERSON_A_FIELDS = ['E0100401', 'E0100201', 'E0100301', 'E0100402', 'E0101104', 'E0101206', 'E0101207', 'E0101301',
'E0100601', 'E0100602', 'E0100701', 'E0100702', 'E0100703', 'E0100704']
_PERSON_B_FIELDS = ['E0101001', 'E0100901', 'E0100801', 'E0101002', 'E0102105', 'E0102202', 'E0102203', 'E0102301',
'E0101701', 'E0101702']
# Persönliche Daten
_ALLG_A = ElsterXmlTreeNode(name='A', sub_elements=_PERSON_A_FIELDS)
_ALLG_B = ElsterXmlTreeNode(name='B', sub_elements=_PERSON_B_FIELDS)
_ALLG_BANK_INFORMATION = ElsterXmlTreeNode(name='BV', sub_elements=['E0102102', 'E0101601', 'E0102402'])
_ALLG_VLG_ART = ElsterXmlTreeNode(name='Vlg_Art', sub_elements=['E0101201'])
_EST1A_ALLG = ElsterXmlTreeNode(name='Allg', sub_elements=[_ALLG_A, _ALLG_B, _ALLG_VLG_ART, _ALLG_BANK_INFORMATION])
_EST1A_BELEGE = ElsterXmlTreeNode(name='Belege', sub_elements=['E0100012', 'E0100013'])
_EST1A_ART_ERKL = ElsterXmlTreeNode(name='Art_Erkl', sub_elements=['E0100001'])
# Behinderung
_BEH_GEH_STEH_BLIND_HILFL = ElsterXmlTreeNode(name='Geh_Steh_Blind_Hilfl', sub_elements=['E0109707', 'E0109706'])
_BEH_AUSW_RENTB_BESCH = ElsterXmlTreeNode(name='Ausw_Rentb_Besch', sub_elements=['E0109708'])
_AGB_BEH = ElsterXmlTreeNode(name="Beh", sub_elements=[_BEH_AUSW_RENTB_BESCH, _BEH_GEH_STEH_BLIND_HILFL],
is_person_specific=True, repetitions=2)
# Besondere Belastungen
_KRANKH_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161304', 'E0161305'])
_AND_AUFW_KRANKH = ElsterXmlTreeNode(name='Krankh', sub_elements=[_KRANKH_SUM])
_PFLEGE_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161404', 'E0161405'])
_AND_AUFW_PFLEGE = ElsterXmlTreeNode(name='Pflege', sub_elements=[_PFLEGE_SUM])
_BEH_AUFW_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161504', 'E0161505'])
_AND_AUFW_BEH_AUFW = ElsterXmlTreeNode(name='Beh_Aufw', sub_elements=[_BEH_AUFW_SUM])
_BEH_KFZ_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161604', 'E0161605'])
_AND_AUFW_BEH_KFZ = ElsterXmlTreeNode(name='Beh_Kfz', sub_elements=[_BEH_KFZ_SUM])
_BESTATT_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161704', 'E0161705'])
_AND_AUFW_BESTATT = ElsterXmlTreeNode(name='Bestatt', sub_elements=[_BESTATT_SUM])
_SONST_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0161804', 'E0161805'])
_AND_AUFW_SONST = ElsterXmlTreeNode(name='Sonst', sub_elements=[_SONST_SUM])
_AGB_AND_AUFW = ElsterXmlTreeNode(name='And_Aufw', sub_elements=[_AND_AUFW_KRANKH, _AND_AUFW_PFLEGE, _AND_AUFW_BEH_AUFW,
_AND_AUFW_BEH_KFZ, _AND_AUFW_BESTATT, _AND_AUFW_SONST])
# Haushaltsnahe Ausgaben
_HAUSHALT_EINZ = ElsterXmlTreeNode(name='Einz', sub_elements=['E0107206', 'E0107207'])
_HAUSHALT_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0107208'])
_HANDW_EINZ = ElsterXmlTreeNode(name='Einz', sub_elements=['E0111217', 'E0170601', 'E0111214'], is_repeatable=True)
_HANDW_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0111215'])
_ST_ERM_HAUSHALT = ElsterXmlTreeNode(name='Hhn_BV_DL', sub_elements=[_HAUSHALT_EINZ, _HAUSHALT_SUM])
_ST_ERM_HANDW = ElsterXmlTreeNode(name='Handw_L', sub_elements=[_HANDW_EINZ, _HANDW_SUM])
_ALLEINST_GEM_HH = ElsterXmlTreeNode(name='Pers_gem_HH', sub_elements=['E0104706'], is_repeatable=True)
_ST_ERM_ALLEINST = ElsterXmlTreeNode(name='Alleinst', sub_elements=['E0107606', _ALLEINST_GEM_HH])
_ST_ERM = ElsterXmlTreeNode(name='St_Erm', sub_elements=[_ST_ERM_HAUSHALT, _ST_ERM_HANDW, _ST_ERM_ALLEINST])
# Sonderausgaben
_VERS_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E2001803'])
_A_B_VERS = ElsterXmlTreeNode(name='U_HP_Ris_Vers', sub_elements=[_VERS_SUM])
_WEIT_A_B = ElsterXmlTreeNode(name='A_B_LP', sub_elements=[_A_B_VERS])
_VOR_WEIT = ElsterXmlTreeNode(name='Weit_Sons_VorAW', sub_elements=[_WEIT_A_B])
_INL_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0108105'])
_SP_MB_INL = ElsterXmlTreeNode(name='Foerd_st_beg_Zw_Inl', sub_elements=[_INL_SUM])
_POLIT_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0108701'])
_SP_MB_POLIT = ElsterXmlTreeNode(name='Polit_P', sub_elements=[_POLIT_SUM])
_ZUW_SP_MB = ElsterXmlTreeNode(name='Sp_MB', sub_elements=[_SP_MB_INL, _SP_MB_POLIT])
_SA_ZUW = ElsterXmlTreeNode(name='Zuw', sub_elements=[_ZUW_SP_MB])
_GEZAHLT_SUM = ElsterXmlTreeNode(name='Sum', sub_elements=['E0107601'])
_KIST_GEZAHLT = ElsterXmlTreeNode(name='Gezahlt', sub_elements=[_GEZAHLT_SUM])
_KIST_ERSTATTET = ElsterXmlTreeNode(name='Erstattet', sub_elements=['E0107602'])
_VOR_KIST = ElsterXmlTreeNode(name='KiSt', sub_elements=[_KIST_GEZAHLT, _KIST_ERSTATTET])
TOP_ELEMENT_ESTA1A = ElsterXmlTreeNode(name='ESt1A', sub_elements=[_EST1A_ART_ERKL, _EST1A_BELEGE, _EST1A_ALLG])
TOP_ELEMENT_SA = ElsterXmlTreeNode(name='SA', sub_elements=[_VOR_KIST, _SA_ZUW])
TOP_ELEMENT_AGB = ElsterXmlTreeNode(name='AgB', sub_elements=[_AGB_BEH, _AGB_AND_AUFW])
TOP_ELEMENT_HA35A = ElsterXmlTreeNode(name='HA_35a', sub_elements=[_ST_ERM])
TOP_ELEMENT_VOR = ElsterXmlTreeNode(name='VOR', sub_elements=[_VOR_WEIT])
|
def match(key, value):
return {"match": {key: value}}
def exists(field):
return {"exists": {"field": field}}
def add_to_dict(dict, key, value):
dict.update({key: value})
def build_more_like_this_query(count, content, language):
query_body = {"size": count, "query": {"bool": {}}} # initial empty query
must = []
if language:
more_like_this = {}
add_to_dict(more_like_this, "fields", ["content", "title"])
add_to_dict(more_like_this, "like", content)
add_to_dict(more_like_this, "min_term_freq", 1)
add_to_dict(more_like_this, "max_query_terms", 25)
must.append({"more_like_this": more_like_this})
must.append(match("language", language.name))
query_body["query"]["bool"].update({"must": must})
return query_body
def build_elastic_query(
count,
search_terms,
topics,
unwanted_topics,
user_topics,
unwanted_user_topics,
language,
upper_bounds,
lower_bounds,
es_scale="3d",
es_decay=0.8,
es_weight=4.2,
):
"""
Builds an elastic search query.
Does this by building a big JSON object.
Example of a final query body:
{'size': 20.0, 'query':
{'bool':
{
'filter':
{
'range':
{
'fk_difficulty':
{
'gt': 0,
'lt': 100
}
}
},
'should': [
{'match': {'topics': 'Sport'}},
{'match': {'content': 'soccer ronaldo'}},
{'match': {'title': 'soccer ronaldo'}}
],
'must': [
{'match': {'language': 'English'}}
],
'must_not': [
{'match': {'topics': 'Health'}},
{'match': {'content': 'messi'}},
{'match': {'title': 'messi'}}
]
}
}
}
"""
# must = mandatory, has to occur
# must not = has to not occur
# should = nice to have (extra points if it matches)
must = []
must_not = []
should = []
bool_query_body = {"query": {"bool": {}}} # initial empty bool query
if language:
must.append(match("language", language.name))
if topics:
should.append(match("topics", topics))
if not search_terms:
search_terms = ""
if not user_topics:
user_topics = ""
if search_terms or user_topics:
search_string = search_terms + " " + user_topics
should.append(match("content", search_string))
should.append(match("title", search_string))
if unwanted_topics:
must_not.append(match("topics", unwanted_topics))
if unwanted_user_topics:
must_not.append(match("content", unwanted_user_topics))
must_not.append(match("title", unwanted_user_topics))
must.append(exists("published_time"))
# add the must, must_not and should lists to the query body
bool_query_body["query"]["bool"].update(
{
"filter": {
"range": {"fk_difficulty": {"gt": lower_bounds, "lt": upper_bounds}}
}
}
)
bool_query_body["query"]["bool"].update({"should": should})
bool_query_body["query"]["bool"].update({"must": must})
bool_query_body["query"]["bool"].update({"must_not": must_not})
full_query = {"size": count, "query": {"function_score": {}}}
function1 = {
# original parameters by Simon & Marcus
# "gauss": {"published_time": {"scale": "365d", "offset": "7d", "decay": 0.3}},
# "weight": 1.2,
"gauss": {
"published_time": {"origin": "now", "scale": es_scale, "decay": es_decay}
},
"weight": es_weight,
}
full_query["query"]["function_score"].update({"functions": [function1]})
full_query["query"]["function_score"].update(bool_query_body)
print(full_query)
return full_query
|
# Want to extract domain hotmail.com
data = 'From ritchie_ng@hotmail.com Tues May 31'
at_position = data.find('@')
print(at_position)
space_position = data.find(' ', at_position)
# Starting from at_position, where's the next space
print(space_position)
host = data[at_position + 1: space_position]
print(host) |
def stable_sorted_copy(alist, _indices=xrange(sys.maxint)):
# the 'decorate' step: make a list such that each item
# is the concatenation of sort-keys in order of decreasing
# significance -- we'll sort this auxiliary-list
decorated = zip(alist, _indices)
# the 'sort' step: just builtin-sort the auxiliary list
decorated.sort()
# the 'undecorate' step: extract the items from the
# decorated, and now correctly sorted, auxiliary list
return [ item for item, index in decorated ]
def stable_sort_inplace(alist):
# if "inplace" sorting is desired, simplest is to assign
# to a slice-of-all-items of the original input list
alist[:] = stable_sorted_copy(alist)
|
def wellbracketed(s):
c=0
for i in range(0, len(s)):
if s[i] == "(":
c = c + 1
elif s[i] == ")":
c = c - 1
if c == 0:
return(True)
else:
return(False) |
INSERT_SQL = """
SET statement_timeout = 0;
SET lock_timeout = 0;
SET idle_in_transaction_session_timeout = 0;
SET client_encoding = 'UTF8';
SET standard_conforming_strings = on;
SELECT pg_catalog.set_config('search_path', 'public', false);
SET check_function_bodies = false;
SET xmloption = content;
SET client_min_messages = warning;
SET row_security = off;
INSERT INTO currency (id, name, iso_code, symbol) VALUES (1, 'UAE Dirham', 'AED', 'د.إ');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (2, 'Afghani', 'AFN', '؋');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (3, 'Lek', 'ALL', 'Lek');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (4, 'Armenian Dram', 'AMD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (5, 'Netherlands Antillian Guilder', 'ANG', 'ƒ');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (6, 'Kwanza', 'AOA', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (7, 'Argentine Peso', 'ARS', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (8, 'Australian Dollar', 'AUD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (9, 'Aruban Guilder', 'AWG', 'ƒ');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (10, 'Azerbaijanian Manat', 'AZN', 'ман');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (11, 'Convertible Marks', 'BAM', 'KM');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (12, 'Barbados Dollar', 'BBD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (13, 'Taka', 'BDT', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (14, 'Bulgarian Lev', 'BGN', 'лв');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (15, 'Bahraini Dinar', 'BHD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (16, 'Burundi Franc', 'BIF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (17, 'Bermudian Dollar', 'BMD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (18, 'Brunei Dollar', 'BND', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (19, 'Boliviano Mvdol', 'BOB BOV', '$b');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (20, 'Brazilian Real', 'BRL', 'R$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (21, 'Bahamian Dollar', 'BSD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (22, 'Pula', 'BWP', 'P');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (23, 'Belarussian Ruble', 'BYR', 'p.');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (24, 'Belize Dollar', 'BZD', 'BZ$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (25, 'Canadian Dollar', 'CAD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (26, 'Congolese Franc', 'CDF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (27, 'Swiss Franc', 'CHF', 'CHF');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (28, 'Chilean Peso Unidades de fomento', 'CLP CLF', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (29, 'Yuan Renminbi', 'CNY', '¥');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (30, 'Colombian Peso Unidad de Valor Real', 'COP COU', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (31, 'Costa Rican Colon', 'CRC', '₡');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (32, 'Cuban Peso Peso Convertible', 'CUP CUC', '₱');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (33, 'Cape Verde Escudo', 'CVE', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (34, 'Czech Koruna', 'CZK', 'Kč');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (35, 'Djibouti Franc', 'DJF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (36, 'Danish Krone', 'DKK', 'kr');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (37, 'Dominican Peso', 'DOP', 'RD$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (38, 'Algerian Dinar', 'DZD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (39, 'Kroon', 'EEK', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (40, 'Egyptian Pound', 'EGP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (41, 'Nakfa', 'ERN', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (42, 'Ethiopian Birr', 'ETB', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (43, 'Euro', 'EUR', '€');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (44, 'Fiji Dollar', 'FJD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (45, 'Falkland Islands Pound', 'FKP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (46, 'Pound Sterling', 'GBP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (47, 'Lari', 'GEL', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (48, 'Cedi', 'GHS', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (49, 'Gibraltar Pound', 'GIP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (50, 'Dalasi', 'GMD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (51, 'Guinea Franc', 'GNF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (52, 'Quetzal', 'GTQ', 'Q');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (53, 'Guyana Dollar', 'GYD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (54, 'Hong Kong Dollar', 'HKD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (55, 'Lempira', 'HNL', 'L');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (56, 'Croatian Kuna', 'HRK', 'kn');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (57, 'Gourde US Dollar', 'HTG USD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (58, 'Forint', 'HUF', 'Ft');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (59, 'Rupiah', 'IDR', 'Rp');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (60, 'New Israeli Sheqel', 'ILS', '₪');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (61, 'Indian Rupee', 'INR', '₹');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (62, 'Indian Rupee Ngultrum', 'INR BTN', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (63, 'Iraqi Dinar', 'IQD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (64, 'Iranian Rial', 'IRR', '﷼');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (65, 'Iceland Krona', 'ISK', 'kr');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (66, 'Jamaican Dollar', 'JMD', 'J$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (67, 'Jordanian Dinar', 'JOD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (68, 'Yen', 'JPY', '¥');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (69, 'Kenyan Shilling', 'KES', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (70, 'Som', 'KGS', 'лв');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (71, 'Riel', 'KHR', '៛');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (72, 'Comoro Franc', 'KMF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (73, 'North Korean Won', 'KPW', '₩');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (74, 'Won', 'KRW', '₩');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (75, 'Kuwaiti Dinar', 'KWD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (76, 'Cayman Islands Dollar', 'KYD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (77, 'Tenge', 'KZT', 'лв');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (78, 'Kip', 'LAK', '₭');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (79, 'Lebanese Pound', 'LBP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (80, 'Sri Lanka Rupee', 'LKR', '₨');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (81, 'Liberian Dollar', 'LRD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (82, 'Lithuanian Litas', 'LTL', 'Lt');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (83, 'Latvian Lats', 'LVL', 'Ls');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (84, 'Libyan Dinar', 'LYD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (85, 'Moroccan Dirham', 'MAD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (86, 'Moldovan Leu', 'MDL', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (87, 'Malagasy Ariary', 'MGA', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (88, 'Denar', 'MKD', 'ден');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (89, 'Kyat', 'MMK', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (90, 'Tugrik', 'MNT', '₮');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (91, 'Pataca', 'MOP', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (92, 'Ouguiya', 'MRO', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (93, 'Mauritius Rupee', 'MUR', '₨');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (94, 'Rufiyaa', 'MVR', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (95, 'Kwacha', 'MWK', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (96, 'Mexican Peso Mexican Unidad de Inversion (UDI)', 'MXN MXV', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (97, 'Malaysian Ringgit', 'MYR', 'RM');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (98, 'Metical', 'MZN', 'MT');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (99, 'Naira', 'NGN', '₦');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (100, 'Cordoba Oro', 'NIO', 'C$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (101, 'Norwegian Krone', 'NOK', 'kr');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (102, 'Nepalese Rupee', 'NPR', '₨');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (103, 'New Zealand Dollar', 'NZD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (104, 'Rial Omani', 'OMR', '﷼');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (105, 'Balboa US Dollar', 'PAB USD', 'B/.');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (106, 'Nuevo Sol', 'PEN', 'S/.');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (107, 'Kina', 'PGK', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (108, 'Philippine Peso', 'PHP', 'Php');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (109, 'Pakistan Rupee', 'PKR', '₨');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (110, 'Zloty', 'PLN', 'zł');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (111, 'Guarani', 'PYG', 'Gs');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (112, 'Qatari Rial', 'QAR', '﷼');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (113, 'New Leu', 'RON', 'lei');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (114, 'Serbian Dinar', 'RSD', 'Дин.');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (115, 'Russian Ruble', 'RUB', 'руб');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (116, 'Rwanda Franc', 'RWF', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (117, 'Saudi Riyal', 'SAR', '﷼');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (118, 'Solomon Islands Dollar', 'SBD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (119, 'Seychelles Rupee', 'SCR', '₨');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (120, 'Sudanese Pound', 'SDG', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (121, 'Swedish Krona', 'SEK', 'kr');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (122, 'Singapore Dollar', 'SGD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (123, 'Saint Helena Pound', 'SHP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (124, 'Leone', 'SLL', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (125, 'Somali Shilling', 'SOS', 'S');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (126, 'Surinam Dollar', 'SRD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (127, 'Dobra', 'STD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (128, 'El Salvador Colon US Dollar', 'SVC USD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (129, 'Syrian Pound', 'SYP', '£');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (130, 'Lilangeni', 'SZL', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (131, 'Baht', 'THB', '฿');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (132, 'Somoni', 'TJS', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (133, 'Manat', 'TMT', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (134, 'Tunisian Dinar', 'TND', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (135, 'Pa''anga', 'TOP', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (136, 'Turkish Lira', 'TRY', 'TL');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (137, 'Trinidad and Tobago Dollar', 'TTD', 'TT$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (138, 'New Taiwan Dollar', 'TWD', 'NT$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (139, 'Tanzanian Shilling', 'TZS', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (140, 'Hryvnia', 'UAH', '₴');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (141, 'Uganda Shilling', 'UGX', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (142, 'US Dollar', 'USD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (143, 'Peso Uruguayo Uruguay Peso en Unidades Indexadas', 'UYU UYI', '$U');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (144, 'Uzbekistan Sum', 'UZS', 'лв');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (145, 'Bolivar Fuerte', 'VEF', 'Bs');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (146, 'Dong', 'VND', '₫');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (147, 'East Caribbean Dollar', 'XCD', '$');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (148, 'Yemeni Rial', 'YER', '﷼');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (149, 'Rand', 'ZAR', 'R');
INSERT INTO currency (id, name, iso_code, symbol) VALUES (150, 'Rand Loti', 'ZAR LSL', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (151, 'Rand Namibia Dollar', 'ZAR NAD', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (152, 'Zambian Kwacha', 'ZMK', NULL);
INSERT INTO currency (id, name, iso_code, symbol) VALUES (153, 'Zimbabwe Dollar', 'ZWL', NULL);
INSERT INTO time_zone (id, name) VALUES (1, 'Europe/Andorra');
INSERT INTO time_zone (id, name) VALUES (2, 'Asia/Dubai');
INSERT INTO time_zone (id, name) VALUES (3, 'Asia/Kabul');
INSERT INTO time_zone (id, name) VALUES (4, 'America/Antigua');
INSERT INTO time_zone (id, name) VALUES (5, 'America/Anguilla');
INSERT INTO time_zone (id, name) VALUES (6, 'Europe/Tirane');
INSERT INTO time_zone (id, name) VALUES (7, 'Asia/Yerevan');
INSERT INTO time_zone (id, name) VALUES (8, 'Africa/Luanda');
INSERT INTO time_zone (id, name) VALUES (9, 'Antarctica/McMurdo');
INSERT INTO time_zone (id, name) VALUES (10, 'Antarctica/Casey');
INSERT INTO time_zone (id, name) VALUES (11, 'Antarctica/Davis');
INSERT INTO time_zone (id, name) VALUES (12, 'Antarctica/DumontDUrville');
INSERT INTO time_zone (id, name) VALUES (13, 'Antarctica/Mawson');
INSERT INTO time_zone (id, name) VALUES (14, 'Antarctica/Palmer');
INSERT INTO time_zone (id, name) VALUES (15, 'Antarctica/Rothera');
INSERT INTO time_zone (id, name) VALUES (16, 'Antarctica/Syowa');
INSERT INTO time_zone (id, name) VALUES (17, 'Antarctica/Troll');
INSERT INTO time_zone (id, name) VALUES (18, 'Antarctica/Vostok');
INSERT INTO time_zone (id, name) VALUES (19, 'America/Argentina/Buenos_Aires');
INSERT INTO time_zone (id, name) VALUES (20, 'America/Argentina/Cordoba');
INSERT INTO time_zone (id, name) VALUES (21, 'America/Argentina/Salta');
INSERT INTO time_zone (id, name) VALUES (22, 'America/Argentina/Jujuy');
INSERT INTO time_zone (id, name) VALUES (23, 'America/Argentina/Tucuman');
INSERT INTO time_zone (id, name) VALUES (24, 'America/Argentina/Catamarca');
INSERT INTO time_zone (id, name) VALUES (25, 'America/Argentina/La_Rioja');
INSERT INTO time_zone (id, name) VALUES (26, 'America/Argentina/San_Juan');
INSERT INTO time_zone (id, name) VALUES (27, 'America/Argentina/Mendoza');
INSERT INTO time_zone (id, name) VALUES (28, 'America/Argentina/San_Luis');
INSERT INTO time_zone (id, name) VALUES (29, 'America/Argentina/Rio_Gallegos');
INSERT INTO time_zone (id, name) VALUES (30, 'America/Argentina/Ushuaia');
INSERT INTO time_zone (id, name) VALUES (31, 'Pacific/Pago_Pago');
INSERT INTO time_zone (id, name) VALUES (32, 'Europe/Vienna');
INSERT INTO time_zone (id, name) VALUES (33, 'Australia/Lord_Howe');
INSERT INTO time_zone (id, name) VALUES (34, 'Antarctica/Macquarie');
INSERT INTO time_zone (id, name) VALUES (35, 'Australia/Hobart');
INSERT INTO time_zone (id, name) VALUES (36, 'Australia/Currie');
INSERT INTO time_zone (id, name) VALUES (37, 'Australia/Melbourne');
INSERT INTO time_zone (id, name) VALUES (38, 'Australia/Sydney');
INSERT INTO time_zone (id, name) VALUES (39, 'Australia/Broken_Hill');
INSERT INTO time_zone (id, name) VALUES (40, 'Australia/Brisbane');
INSERT INTO time_zone (id, name) VALUES (41, 'Australia/Lindeman');
INSERT INTO time_zone (id, name) VALUES (42, 'Australia/Adelaide');
INSERT INTO time_zone (id, name) VALUES (43, 'Australia/Darwin');
INSERT INTO time_zone (id, name) VALUES (44, 'Australia/Perth');
INSERT INTO time_zone (id, name) VALUES (45, 'Australia/Eucla');
INSERT INTO time_zone (id, name) VALUES (46, 'America/Aruba');
INSERT INTO time_zone (id, name) VALUES (47, 'Europe/Mariehamn');
INSERT INTO time_zone (id, name) VALUES (48, 'Asia/Baku');
INSERT INTO time_zone (id, name) VALUES (49, 'Europe/Sarajevo');
INSERT INTO time_zone (id, name) VALUES (50, 'America/Barbados');
INSERT INTO time_zone (id, name) VALUES (51, 'Asia/Dhaka');
INSERT INTO time_zone (id, name) VALUES (52, 'Europe/Brussels');
INSERT INTO time_zone (id, name) VALUES (53, 'Africa/Ouagadougou');
INSERT INTO time_zone (id, name) VALUES (54, 'Europe/Sofia');
INSERT INTO time_zone (id, name) VALUES (55, 'Asia/Bahrain');
INSERT INTO time_zone (id, name) VALUES (56, 'Africa/Bujumbura');
INSERT INTO time_zone (id, name) VALUES (57, 'Africa/Porto-Novo');
INSERT INTO time_zone (id, name) VALUES (58, 'America/St_Barthelemy');
INSERT INTO time_zone (id, name) VALUES (59, 'Atlantic/Bermuda');
INSERT INTO time_zone (id, name) VALUES (60, 'Asia/Brunei');
INSERT INTO time_zone (id, name) VALUES (61, 'America/La_Paz');
INSERT INTO time_zone (id, name) VALUES (62, 'America/Kralendijk');
INSERT INTO time_zone (id, name) VALUES (63, 'America/Noronha');
INSERT INTO time_zone (id, name) VALUES (64, 'America/Belem');
INSERT INTO time_zone (id, name) VALUES (65, 'America/Fortaleza');
INSERT INTO time_zone (id, name) VALUES (66, 'America/Recife');
INSERT INTO time_zone (id, name) VALUES (67, 'America/Araguaina');
INSERT INTO time_zone (id, name) VALUES (68, 'America/Maceio');
INSERT INTO time_zone (id, name) VALUES (69, 'America/Bahia');
INSERT INTO time_zone (id, name) VALUES (70, 'America/Sao_Paulo');
INSERT INTO time_zone (id, name) VALUES (71, 'America/Campo_Grande');
INSERT INTO time_zone (id, name) VALUES (72, 'America/Cuiaba');
INSERT INTO time_zone (id, name) VALUES (73, 'America/Santarem');
INSERT INTO time_zone (id, name) VALUES (74, 'America/Porto_Velho');
INSERT INTO time_zone (id, name) VALUES (75, 'America/Boa_Vista');
INSERT INTO time_zone (id, name) VALUES (76, 'America/Manaus');
INSERT INTO time_zone (id, name) VALUES (77, 'America/Eirunepe');
INSERT INTO time_zone (id, name) VALUES (78, 'America/Rio_Branco');
INSERT INTO time_zone (id, name) VALUES (79, 'America/Nassau');
INSERT INTO time_zone (id, name) VALUES (80, 'Asia/Thimphu');
INSERT INTO time_zone (id, name) VALUES (81, 'Africa/Gaborone');
INSERT INTO time_zone (id, name) VALUES (82, 'Europe/Minsk');
INSERT INTO time_zone (id, name) VALUES (83, 'America/Belize');
INSERT INTO time_zone (id, name) VALUES (84, 'America/St_Johns');
INSERT INTO time_zone (id, name) VALUES (85, 'America/Halifax');
INSERT INTO time_zone (id, name) VALUES (86, 'America/Glace_Bay');
INSERT INTO time_zone (id, name) VALUES (87, 'America/Moncton');
INSERT INTO time_zone (id, name) VALUES (88, 'America/Goose_Bay');
INSERT INTO time_zone (id, name) VALUES (89, 'America/Blanc-Sablon');
INSERT INTO time_zone (id, name) VALUES (90, 'America/Toronto');
INSERT INTO time_zone (id, name) VALUES (91, 'America/Nipigon');
INSERT INTO time_zone (id, name) VALUES (92, 'America/Thunder_Bay');
INSERT INTO time_zone (id, name) VALUES (93, 'America/Iqaluit');
INSERT INTO time_zone (id, name) VALUES (94, 'America/Pangnirtung');
INSERT INTO time_zone (id, name) VALUES (95, 'America/Atikokan');
INSERT INTO time_zone (id, name) VALUES (96, 'America/Winnipeg');
INSERT INTO time_zone (id, name) VALUES (97, 'America/Rainy_River');
INSERT INTO time_zone (id, name) VALUES (98, 'America/Resolute');
INSERT INTO time_zone (id, name) VALUES (99, 'America/Rankin_Inlet');
INSERT INTO time_zone (id, name) VALUES (100, 'America/Regina');
INSERT INTO time_zone (id, name) VALUES (101, 'America/Swift_Current');
INSERT INTO time_zone (id, name) VALUES (102, 'America/Edmonton');
INSERT INTO time_zone (id, name) VALUES (103, 'America/Cambridge_Bay');
INSERT INTO time_zone (id, name) VALUES (104, 'America/Yellowknife');
INSERT INTO time_zone (id, name) VALUES (105, 'America/Inuvik');
INSERT INTO time_zone (id, name) VALUES (106, 'America/Creston');
INSERT INTO time_zone (id, name) VALUES (107, 'America/Dawson_Creek');
INSERT INTO time_zone (id, name) VALUES (108, 'America/Fort_Nelson');
INSERT INTO time_zone (id, name) VALUES (109, 'America/Vancouver');
INSERT INTO time_zone (id, name) VALUES (110, 'America/Whitehorse');
INSERT INTO time_zone (id, name) VALUES (111, 'America/Dawson');
INSERT INTO time_zone (id, name) VALUES (112, 'Indian/Cocos');
INSERT INTO time_zone (id, name) VALUES (113, 'Africa/Kinshasa');
INSERT INTO time_zone (id, name) VALUES (114, 'Africa/Lubumbashi');
INSERT INTO time_zone (id, name) VALUES (115, 'Africa/Bangui');
INSERT INTO time_zone (id, name) VALUES (116, 'Africa/Brazzaville');
INSERT INTO time_zone (id, name) VALUES (117, 'Europe/Zurich');
INSERT INTO time_zone (id, name) VALUES (118, 'Africa/Abidjan');
INSERT INTO time_zone (id, name) VALUES (119, 'Pacific/Rarotonga');
INSERT INTO time_zone (id, name) VALUES (120, 'America/Santiago');
INSERT INTO time_zone (id, name) VALUES (121, 'America/Punta_Arenas');
INSERT INTO time_zone (id, name) VALUES (122, 'Pacific/Easter');
INSERT INTO time_zone (id, name) VALUES (123, 'Africa/Douala');
INSERT INTO time_zone (id, name) VALUES (124, 'Asia/Shanghai');
INSERT INTO time_zone (id, name) VALUES (125, 'Asia/Urumqi');
INSERT INTO time_zone (id, name) VALUES (126, 'America/Bogota');
INSERT INTO time_zone (id, name) VALUES (127, 'America/Costa_Rica');
INSERT INTO time_zone (id, name) VALUES (128, 'America/Havana');
INSERT INTO time_zone (id, name) VALUES (129, 'Atlantic/Cape_Verde');
INSERT INTO time_zone (id, name) VALUES (130, 'America/Curacao');
INSERT INTO time_zone (id, name) VALUES (131, 'Indian/Christmas');
INSERT INTO time_zone (id, name) VALUES (132, 'Asia/Nicosia');
INSERT INTO time_zone (id, name) VALUES (133, 'Asia/Famagusta');
INSERT INTO time_zone (id, name) VALUES (134, 'Europe/Prague');
INSERT INTO time_zone (id, name) VALUES (135, 'Europe/Berlin');
INSERT INTO time_zone (id, name) VALUES (136, 'Europe/Busingen');
INSERT INTO time_zone (id, name) VALUES (137, 'Africa/Djibouti');
INSERT INTO time_zone (id, name) VALUES (138, 'Europe/Copenhagen');
INSERT INTO time_zone (id, name) VALUES (139, 'America/Dominica');
INSERT INTO time_zone (id, name) VALUES (140, 'America/Santo_Domingo');
INSERT INTO time_zone (id, name) VALUES (141, 'Africa/Algiers');
INSERT INTO time_zone (id, name) VALUES (142, 'America/Guayaquil');
INSERT INTO time_zone (id, name) VALUES (143, 'Pacific/Galapagos');
INSERT INTO time_zone (id, name) VALUES (144, 'Europe/Tallinn');
INSERT INTO time_zone (id, name) VALUES (145, 'Africa/Cairo');
INSERT INTO time_zone (id, name) VALUES (146, 'Africa/El_Aaiun');
INSERT INTO time_zone (id, name) VALUES (147, 'Africa/Asmara');
INSERT INTO time_zone (id, name) VALUES (148, 'Europe/Madrid');
INSERT INTO time_zone (id, name) VALUES (149, 'Africa/Ceuta');
INSERT INTO time_zone (id, name) VALUES (150, 'Atlantic/Canary');
INSERT INTO time_zone (id, name) VALUES (151, 'Africa/Addis_Ababa');
INSERT INTO time_zone (id, name) VALUES (152, 'Europe/Helsinki');
INSERT INTO time_zone (id, name) VALUES (153, 'Pacific/Fiji');
INSERT INTO time_zone (id, name) VALUES (154, 'Atlantic/Stanley');
INSERT INTO time_zone (id, name) VALUES (155, 'Pacific/Chuuk');
INSERT INTO time_zone (id, name) VALUES (156, 'Pacific/Pohnpei');
INSERT INTO time_zone (id, name) VALUES (157, 'Pacific/Kosrae');
INSERT INTO time_zone (id, name) VALUES (158, 'Atlantic/Faroe');
INSERT INTO time_zone (id, name) VALUES (159, 'Europe/Paris');
INSERT INTO time_zone (id, name) VALUES (160, 'Africa/Libreville');
INSERT INTO time_zone (id, name) VALUES (161, 'Europe/London');
INSERT INTO time_zone (id, name) VALUES (162, 'America/Grenada');
INSERT INTO time_zone (id, name) VALUES (163, 'Asia/Tbilisi');
INSERT INTO time_zone (id, name) VALUES (164, 'America/Cayenne');
INSERT INTO time_zone (id, name) VALUES (165, 'Europe/Guernsey');
INSERT INTO time_zone (id, name) VALUES (166, 'Africa/Accra');
INSERT INTO time_zone (id, name) VALUES (167, 'Europe/Gibraltar');
INSERT INTO time_zone (id, name) VALUES (168, 'America/Godthab');
INSERT INTO time_zone (id, name) VALUES (169, 'America/Danmarkshavn');
INSERT INTO time_zone (id, name) VALUES (170, 'America/Scoresbysund');
INSERT INTO time_zone (id, name) VALUES (171, 'America/Thule');
INSERT INTO time_zone (id, name) VALUES (172, 'Africa/Banjul');
INSERT INTO time_zone (id, name) VALUES (173, 'Africa/Conakry');
INSERT INTO time_zone (id, name) VALUES (174, 'America/Guadeloupe');
INSERT INTO time_zone (id, name) VALUES (175, 'Africa/Malabo');
INSERT INTO time_zone (id, name) VALUES (176, 'Europe/Athens');
INSERT INTO time_zone (id, name) VALUES (177, 'Atlantic/South_Georgia');
INSERT INTO time_zone (id, name) VALUES (178, 'America/Guatemala');
INSERT INTO time_zone (id, name) VALUES (179, 'Pacific/Guam');
INSERT INTO time_zone (id, name) VALUES (180, 'Africa/Bissau');
INSERT INTO time_zone (id, name) VALUES (181, 'America/Guyana');
INSERT INTO time_zone (id, name) VALUES (182, 'Asia/Hong_Kong');
INSERT INTO time_zone (id, name) VALUES (183, 'America/Tegucigalpa');
INSERT INTO time_zone (id, name) VALUES (184, 'Europe/Zagreb');
INSERT INTO time_zone (id, name) VALUES (185, 'America/Port-au-Prince');
INSERT INTO time_zone (id, name) VALUES (186, 'Europe/Budapest');
INSERT INTO time_zone (id, name) VALUES (187, 'Asia/Jakarta');
INSERT INTO time_zone (id, name) VALUES (188, 'Asia/Pontianak');
INSERT INTO time_zone (id, name) VALUES (189, 'Asia/Makassar');
INSERT INTO time_zone (id, name) VALUES (190, 'Asia/Jayapura');
INSERT INTO time_zone (id, name) VALUES (191, 'Europe/Dublin');
INSERT INTO time_zone (id, name) VALUES (192, 'Asia/Jerusalem');
INSERT INTO time_zone (id, name) VALUES (193, 'Europe/Isle_of_Man');
INSERT INTO time_zone (id, name) VALUES (194, 'Asia/Kolkata');
INSERT INTO time_zone (id, name) VALUES (195, 'Indian/Chagos');
INSERT INTO time_zone (id, name) VALUES (196, 'Asia/Baghdad');
INSERT INTO time_zone (id, name) VALUES (197, 'Asia/Tehran');
INSERT INTO time_zone (id, name) VALUES (198, 'Atlantic/Reykjavik');
INSERT INTO time_zone (id, name) VALUES (199, 'Europe/Rome');
INSERT INTO time_zone (id, name) VALUES (200, 'Europe/Jersey');
INSERT INTO time_zone (id, name) VALUES (201, 'America/Jamaica');
INSERT INTO time_zone (id, name) VALUES (202, 'Asia/Amman');
INSERT INTO time_zone (id, name) VALUES (203, 'Asia/Tokyo');
INSERT INTO time_zone (id, name) VALUES (204, 'Africa/Nairobi');
INSERT INTO time_zone (id, name) VALUES (205, 'Asia/Bishkek');
INSERT INTO time_zone (id, name) VALUES (206, 'Asia/Phnom_Penh');
INSERT INTO time_zone (id, name) VALUES (207, 'Pacific/Tarawa');
INSERT INTO time_zone (id, name) VALUES (208, 'Pacific/Enderbury');
INSERT INTO time_zone (id, name) VALUES (209, 'Pacific/Kiritimati');
INSERT INTO time_zone (id, name) VALUES (210, 'Indian/Comoro');
INSERT INTO time_zone (id, name) VALUES (211, 'America/St_Kitts');
INSERT INTO time_zone (id, name) VALUES (212, 'Asia/Pyongyang');
INSERT INTO time_zone (id, name) VALUES (213, 'Asia/Seoul');
INSERT INTO time_zone (id, name) VALUES (214, 'Asia/Kuwait');
INSERT INTO time_zone (id, name) VALUES (215, 'America/Cayman');
INSERT INTO time_zone (id, name) VALUES (216, 'Asia/Almaty');
INSERT INTO time_zone (id, name) VALUES (217, 'Asia/Qyzylorda');
INSERT INTO time_zone (id, name) VALUES (218, 'Asia/Qostanay');
INSERT INTO time_zone (id, name) VALUES (219, 'Asia/Aqtobe');
INSERT INTO time_zone (id, name) VALUES (220, 'Asia/Aqtau');
INSERT INTO time_zone (id, name) VALUES (221, 'Asia/Atyrau');
INSERT INTO time_zone (id, name) VALUES (222, 'Asia/Oral');
INSERT INTO time_zone (id, name) VALUES (223, 'Asia/Vientiane');
INSERT INTO time_zone (id, name) VALUES (224, 'Asia/Beirut');
INSERT INTO time_zone (id, name) VALUES (225, 'America/St_Lucia');
INSERT INTO time_zone (id, name) VALUES (226, 'Europe/Vaduz');
INSERT INTO time_zone (id, name) VALUES (227, 'Asia/Colombo');
INSERT INTO time_zone (id, name) VALUES (228, 'Africa/Monrovia');
INSERT INTO time_zone (id, name) VALUES (229, 'Africa/Maseru');
INSERT INTO time_zone (id, name) VALUES (230, 'Europe/Vilnius');
INSERT INTO time_zone (id, name) VALUES (231, 'Europe/Luxembourg');
INSERT INTO time_zone (id, name) VALUES (232, 'Europe/Riga');
INSERT INTO time_zone (id, name) VALUES (233, 'Africa/Tripoli');
INSERT INTO time_zone (id, name) VALUES (234, 'Africa/Casablanca');
INSERT INTO time_zone (id, name) VALUES (235, 'Europe/Monaco');
INSERT INTO time_zone (id, name) VALUES (236, 'Europe/Chisinau');
INSERT INTO time_zone (id, name) VALUES (237, 'Europe/Podgorica');
INSERT INTO time_zone (id, name) VALUES (238, 'America/Marigot');
INSERT INTO time_zone (id, name) VALUES (239, 'Indian/Antananarivo');
INSERT INTO time_zone (id, name) VALUES (240, 'Pacific/Majuro');
INSERT INTO time_zone (id, name) VALUES (241, 'Pacific/Kwajalein');
INSERT INTO time_zone (id, name) VALUES (242, 'Europe/Skopje');
INSERT INTO time_zone (id, name) VALUES (243, 'Africa/Bamako');
INSERT INTO time_zone (id, name) VALUES (244, 'Asia/Yangon');
INSERT INTO time_zone (id, name) VALUES (245, 'Asia/Ulaanbaatar');
INSERT INTO time_zone (id, name) VALUES (246, 'Asia/Hovd');
INSERT INTO time_zone (id, name) VALUES (247, 'Asia/Choibalsan');
INSERT INTO time_zone (id, name) VALUES (248, 'Asia/Macau');
INSERT INTO time_zone (id, name) VALUES (249, 'Pacific/Saipan');
INSERT INTO time_zone (id, name) VALUES (250, 'America/Martinique');
INSERT INTO time_zone (id, name) VALUES (251, 'Africa/Nouakchott');
INSERT INTO time_zone (id, name) VALUES (252, 'America/Montserrat');
INSERT INTO time_zone (id, name) VALUES (253, 'Europe/Malta');
INSERT INTO time_zone (id, name) VALUES (254, 'Indian/Mauritius');
INSERT INTO time_zone (id, name) VALUES (255, 'Indian/Maldives');
INSERT INTO time_zone (id, name) VALUES (256, 'Africa/Blantyre');
INSERT INTO time_zone (id, name) VALUES (257, 'America/Mexico_City');
INSERT INTO time_zone (id, name) VALUES (258, 'America/Cancun');
INSERT INTO time_zone (id, name) VALUES (259, 'America/Merida');
INSERT INTO time_zone (id, name) VALUES (260, 'America/Monterrey');
INSERT INTO time_zone (id, name) VALUES (261, 'America/Matamoros');
INSERT INTO time_zone (id, name) VALUES (262, 'America/Mazatlan');
INSERT INTO time_zone (id, name) VALUES (263, 'America/Chihuahua');
INSERT INTO time_zone (id, name) VALUES (264, 'America/Ojinaga');
INSERT INTO time_zone (id, name) VALUES (265, 'America/Hermosillo');
INSERT INTO time_zone (id, name) VALUES (266, 'America/Tijuana');
INSERT INTO time_zone (id, name) VALUES (267, 'America/Bahia_Banderas');
INSERT INTO time_zone (id, name) VALUES (268, 'Asia/Kuala_Lumpur');
INSERT INTO time_zone (id, name) VALUES (269, 'Asia/Kuching');
INSERT INTO time_zone (id, name) VALUES (270, 'Africa/Maputo');
INSERT INTO time_zone (id, name) VALUES (271, 'Africa/Windhoek');
INSERT INTO time_zone (id, name) VALUES (272, 'Pacific/Noumea');
INSERT INTO time_zone (id, name) VALUES (273, 'Africa/Niamey');
INSERT INTO time_zone (id, name) VALUES (274, 'Pacific/Norfolk');
INSERT INTO time_zone (id, name) VALUES (275, 'Africa/Lagos');
INSERT INTO time_zone (id, name) VALUES (276, 'America/Managua');
INSERT INTO time_zone (id, name) VALUES (277, 'Europe/Amsterdam');
INSERT INTO time_zone (id, name) VALUES (278, 'Europe/Oslo');
INSERT INTO time_zone (id, name) VALUES (279, 'Asia/Kathmandu');
INSERT INTO time_zone (id, name) VALUES (280, 'Pacific/Nauru');
INSERT INTO time_zone (id, name) VALUES (281, 'Pacific/Niue');
INSERT INTO time_zone (id, name) VALUES (282, 'Pacific/Auckland');
INSERT INTO time_zone (id, name) VALUES (283, 'Pacific/Chatham');
INSERT INTO time_zone (id, name) VALUES (284, 'Asia/Muscat');
INSERT INTO time_zone (id, name) VALUES (285, 'America/Panama');
INSERT INTO time_zone (id, name) VALUES (286, 'America/Lima');
INSERT INTO time_zone (id, name) VALUES (287, 'Pacific/Tahiti');
INSERT INTO time_zone (id, name) VALUES (288, 'Pacific/Marquesas');
INSERT INTO time_zone (id, name) VALUES (289, 'Pacific/Gambier');
INSERT INTO time_zone (id, name) VALUES (290, 'Pacific/Port_Moresby');
INSERT INTO time_zone (id, name) VALUES (291, 'Pacific/Bougainville');
INSERT INTO time_zone (id, name) VALUES (292, 'Asia/Manila');
INSERT INTO time_zone (id, name) VALUES (293, 'Asia/Karachi');
INSERT INTO time_zone (id, name) VALUES (294, 'Europe/Warsaw');
INSERT INTO time_zone (id, name) VALUES (295, 'America/Miquelon');
INSERT INTO time_zone (id, name) VALUES (296, 'Pacific/Pitcairn');
INSERT INTO time_zone (id, name) VALUES (297, 'America/Puerto_Rico');
INSERT INTO time_zone (id, name) VALUES (298, 'Asia/Gaza');
INSERT INTO time_zone (id, name) VALUES (299, 'Asia/Hebron');
INSERT INTO time_zone (id, name) VALUES (300, 'Europe/Lisbon');
INSERT INTO time_zone (id, name) VALUES (301, 'Atlantic/Madeira');
INSERT INTO time_zone (id, name) VALUES (302, 'Atlantic/Azores');
INSERT INTO time_zone (id, name) VALUES (303, 'Pacific/Palau');
INSERT INTO time_zone (id, name) VALUES (304, 'America/Asuncion');
INSERT INTO time_zone (id, name) VALUES (305, 'Asia/Qatar');
INSERT INTO time_zone (id, name) VALUES (306, 'Indian/Reunion');
INSERT INTO time_zone (id, name) VALUES (307, 'Europe/Bucharest');
INSERT INTO time_zone (id, name) VALUES (308, 'Europe/Belgrade');
INSERT INTO time_zone (id, name) VALUES (309, 'Europe/Kaliningrad');
INSERT INTO time_zone (id, name) VALUES (310, 'Europe/Moscow');
INSERT INTO time_zone (id, name) VALUES (311, 'Europe/Simferopol');
INSERT INTO time_zone (id, name) VALUES (312, 'Europe/Kirov');
INSERT INTO time_zone (id, name) VALUES (313, 'Europe/Astrakhan');
INSERT INTO time_zone (id, name) VALUES (314, 'Europe/Volgograd');
INSERT INTO time_zone (id, name) VALUES (315, 'Europe/Saratov');
INSERT INTO time_zone (id, name) VALUES (316, 'Europe/Ulyanovsk');
INSERT INTO time_zone (id, name) VALUES (317, 'Europe/Samara');
INSERT INTO time_zone (id, name) VALUES (318, 'Asia/Yekaterinburg');
INSERT INTO time_zone (id, name) VALUES (319, 'Asia/Omsk');
INSERT INTO time_zone (id, name) VALUES (320, 'Asia/Novosibirsk');
INSERT INTO time_zone (id, name) VALUES (321, 'Asia/Barnaul');
INSERT INTO time_zone (id, name) VALUES (322, 'Asia/Tomsk');
INSERT INTO time_zone (id, name) VALUES (323, 'Asia/Novokuznetsk');
INSERT INTO time_zone (id, name) VALUES (324, 'Asia/Krasnoyarsk');
INSERT INTO time_zone (id, name) VALUES (325, 'Asia/Irkutsk');
INSERT INTO time_zone (id, name) VALUES (326, 'Asia/Chita');
INSERT INTO time_zone (id, name) VALUES (327, 'Asia/Yakutsk');
INSERT INTO time_zone (id, name) VALUES (328, 'Asia/Khandyga');
INSERT INTO time_zone (id, name) VALUES (329, 'Asia/Vladivostok');
INSERT INTO time_zone (id, name) VALUES (330, 'Asia/Ust-Nera');
INSERT INTO time_zone (id, name) VALUES (331, 'Asia/Magadan');
INSERT INTO time_zone (id, name) VALUES (332, 'Asia/Sakhalin');
INSERT INTO time_zone (id, name) VALUES (333, 'Asia/Srednekolymsk');
INSERT INTO time_zone (id, name) VALUES (334, 'Asia/Kamchatka');
INSERT INTO time_zone (id, name) VALUES (335, 'Asia/Anadyr');
INSERT INTO time_zone (id, name) VALUES (336, 'Africa/Kigali');
INSERT INTO time_zone (id, name) VALUES (337, 'Asia/Riyadh');
INSERT INTO time_zone (id, name) VALUES (338, 'Pacific/Guadalcanal');
INSERT INTO time_zone (id, name) VALUES (339, 'Indian/Mahe');
INSERT INTO time_zone (id, name) VALUES (340, 'Africa/Khartoum');
INSERT INTO time_zone (id, name) VALUES (341, 'Europe/Stockholm');
INSERT INTO time_zone (id, name) VALUES (342, 'Asia/Singapore');
INSERT INTO time_zone (id, name) VALUES (343, 'Atlantic/St_Helena');
INSERT INTO time_zone (id, name) VALUES (344, 'Europe/Ljubljana');
INSERT INTO time_zone (id, name) VALUES (345, 'Arctic/Longyearbyen');
INSERT INTO time_zone (id, name) VALUES (346, 'Europe/Bratislava');
INSERT INTO time_zone (id, name) VALUES (347, 'Africa/Freetown');
INSERT INTO time_zone (id, name) VALUES (348, 'Europe/San_Marino');
INSERT INTO time_zone (id, name) VALUES (349, 'Africa/Dakar');
INSERT INTO time_zone (id, name) VALUES (350, 'Africa/Mogadishu');
INSERT INTO time_zone (id, name) VALUES (351, 'America/Paramaribo');
INSERT INTO time_zone (id, name) VALUES (352, 'Africa/Juba');
INSERT INTO time_zone (id, name) VALUES (353, 'Africa/Sao_Tome');
INSERT INTO time_zone (id, name) VALUES (354, 'America/El_Salvador');
INSERT INTO time_zone (id, name) VALUES (355, 'America/Lower_Princes');
INSERT INTO time_zone (id, name) VALUES (356, 'Asia/Damascus');
INSERT INTO time_zone (id, name) VALUES (357, 'Africa/Mbabane');
INSERT INTO time_zone (id, name) VALUES (358, 'America/Grand_Turk');
INSERT INTO time_zone (id, name) VALUES (359, 'Africa/Ndjamena');
INSERT INTO time_zone (id, name) VALUES (360, 'Indian/Kerguelen');
INSERT INTO time_zone (id, name) VALUES (361, 'Africa/Lome');
INSERT INTO time_zone (id, name) VALUES (362, 'Asia/Bangkok');
INSERT INTO time_zone (id, name) VALUES (363, 'Asia/Dushanbe');
INSERT INTO time_zone (id, name) VALUES (364, 'Pacific/Fakaofo');
INSERT INTO time_zone (id, name) VALUES (365, 'Asia/Dili');
INSERT INTO time_zone (id, name) VALUES (366, 'Asia/Ashgabat');
INSERT INTO time_zone (id, name) VALUES (367, 'Africa/Tunis');
INSERT INTO time_zone (id, name) VALUES (368, 'Pacific/Tongatapu');
INSERT INTO time_zone (id, name) VALUES (369, 'Europe/Istanbul');
INSERT INTO time_zone (id, name) VALUES (370, 'America/Port_of_Spain');
INSERT INTO time_zone (id, name) VALUES (371, 'Pacific/Funafuti');
INSERT INTO time_zone (id, name) VALUES (372, 'Asia/Taipei');
INSERT INTO time_zone (id, name) VALUES (373, 'Africa/Dar_es_Salaam');
INSERT INTO time_zone (id, name) VALUES (374, 'Europe/Kiev');
INSERT INTO time_zone (id, name) VALUES (375, 'Europe/Uzhgorod');
INSERT INTO time_zone (id, name) VALUES (376, 'Europe/Zaporozhye');
INSERT INTO time_zone (id, name) VALUES (377, 'Africa/Kampala');
INSERT INTO time_zone (id, name) VALUES (378, 'Pacific/Midway');
INSERT INTO time_zone (id, name) VALUES (379, 'Pacific/Wake');
INSERT INTO time_zone (id, name) VALUES (380, 'America/New_York');
INSERT INTO time_zone (id, name) VALUES (381, 'America/Detroit');
INSERT INTO time_zone (id, name) VALUES (382, 'America/Kentucky/Louisville');
INSERT INTO time_zone (id, name) VALUES (383, 'America/Kentucky/Monticello');
INSERT INTO time_zone (id, name) VALUES (384, 'America/Indiana/Indianapolis');
INSERT INTO time_zone (id, name) VALUES (385, 'America/Indiana/Vincennes');
INSERT INTO time_zone (id, name) VALUES (386, 'America/Indiana/Winamac');
INSERT INTO time_zone (id, name) VALUES (387, 'America/Indiana/Marengo');
INSERT INTO time_zone (id, name) VALUES (388, 'America/Indiana/Petersburg');
INSERT INTO time_zone (id, name) VALUES (389, 'America/Indiana/Vevay');
INSERT INTO time_zone (id, name) VALUES (390, 'America/Chicago');
INSERT INTO time_zone (id, name) VALUES (391, 'America/Indiana/Tell_City');
INSERT INTO time_zone (id, name) VALUES (392, 'America/Indiana/Knox');
INSERT INTO time_zone (id, name) VALUES (393, 'America/Menominee');
INSERT INTO time_zone (id, name) VALUES (394, 'America/North_Dakota/Center');
INSERT INTO time_zone (id, name) VALUES (395, 'America/North_Dakota/New_Salem');
INSERT INTO time_zone (id, name) VALUES (396, 'America/North_Dakota/Beulah');
INSERT INTO time_zone (id, name) VALUES (397, 'America/Denver');
INSERT INTO time_zone (id, name) VALUES (398, 'America/Boise');
INSERT INTO time_zone (id, name) VALUES (399, 'America/Phoenix');
INSERT INTO time_zone (id, name) VALUES (400, 'America/Los_Angeles');
INSERT INTO time_zone (id, name) VALUES (401, 'America/Anchorage');
INSERT INTO time_zone (id, name) VALUES (402, 'America/Juneau');
INSERT INTO time_zone (id, name) VALUES (403, 'America/Sitka');
INSERT INTO time_zone (id, name) VALUES (404, 'America/Metlakatla');
INSERT INTO time_zone (id, name) VALUES (405, 'America/Yakutat');
INSERT INTO time_zone (id, name) VALUES (406, 'America/Nome');
INSERT INTO time_zone (id, name) VALUES (407, 'America/Adak');
INSERT INTO time_zone (id, name) VALUES (408, 'Pacific/Honolulu');
INSERT INTO time_zone (id, name) VALUES (409, 'America/Montevideo');
INSERT INTO time_zone (id, name) VALUES (410, 'Asia/Samarkand');
INSERT INTO time_zone (id, name) VALUES (411, 'Asia/Tashkent');
INSERT INTO time_zone (id, name) VALUES (412, 'Europe/Vatican');
INSERT INTO time_zone (id, name) VALUES (413, 'America/St_Vincent');
INSERT INTO time_zone (id, name) VALUES (414, 'America/Caracas');
INSERT INTO time_zone (id, name) VALUES (415, 'America/Tortola');
INSERT INTO time_zone (id, name) VALUES (416, 'America/St_Thomas');
INSERT INTO time_zone (id, name) VALUES (417, 'Asia/Ho_Chi_Minh');
INSERT INTO time_zone (id, name) VALUES (418, 'Pacific/Efate');
INSERT INTO time_zone (id, name) VALUES (419, 'Pacific/Wallis');
INSERT INTO time_zone (id, name) VALUES (420, 'Pacific/Apia');
INSERT INTO time_zone (id, name) VALUES (421, 'Asia/Aden');
INSERT INTO time_zone (id, name) VALUES (422, 'Indian/Mayotte');
INSERT INTO time_zone (id, name) VALUES (423, 'Africa/Johannesburg');
INSERT INTO time_zone (id, name) VALUES (424, 'Africa/Lusaka');
INSERT INTO time_zone (id, name) VALUES (425, 'Africa/Harare');
"""
|
class UCOMIMoniker:
""" Use System.Runtime.InteropServices.ComTypes.IMoniker instead. """
def BindToObject(self, pbc, pmkToLeft, riidResult, ppvResult):
"""
BindToObject(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker,riidResult: Guid) -> (Guid,object)
Uses the moniker to bind to the object it identifies.
pbc: A reference to the IBindCtx interface on the bind context object used in this binding operation.
pmkToLeft: A reference to the moniker to the left of this moniker,if the moniker is part of a composite
moniker.
riidResult: The interface identifier (IID) of the interface the client intends to use to communicate with
the object that the moniker identifies.
"""
pass
def BindToStorage(self, pbc, pmkToLeft, riid, ppvObj):
"""
BindToStorage(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker,riid: Guid) -> (Guid,object)
Retrieves an interface pointer to the storage that contains the object identified by the moniker.
pbc: A reference to the IBindCtx interface on the bind context object used during this binding
operation.
pmkToLeft: A reference to the moniker to the left of this moniker,if the moniker is part of a composite
moniker.
riid: The interface identifier (IID) of the storage interface requested.
"""
pass
def CommonPrefixWith(self, pmkOther, ppmkPrefix):
"""
CommonPrefixWith(self: UCOMIMoniker,pmkOther: UCOMIMoniker) -> UCOMIMoniker
Creates a new moniker based on the common prefix that this moniker shares with another moniker.
pmkOther: A reference to the IMoniker interface on another moniker to compare with this for a common
prefix.
"""
pass
def ComposeWith(self, pmkRight, fOnlyIfNotGeneric, ppmkComposite):
"""
ComposeWith(self: UCOMIMoniker,pmkRight: UCOMIMoniker,fOnlyIfNotGeneric: bool) -> UCOMIMoniker
Combines the current moniker with another moniker,creating a new composite moniker.
pmkRight: A reference to the IMoniker interface on the moniker to compose onto the end of this moniker.
fOnlyIfNotGeneric: If true,the caller requires a nongeneric composition,so the operation proceeds only if
pmkRight is a moniker class that this moniker can compose with in some way other than forming a
generic composite. If false,the method can create a generic composite if necessary.
"""
pass
def Enum(self, fForward, ppenumMoniker):
"""
Enum(self: UCOMIMoniker,fForward: bool) -> UCOMIEnumMoniker
Supplies a pointer to an enumerator that can enumerate the components of a composite moniker.
fForward: If true,enumerates the monikers from left to right. If false,enumerates from right to left.
"""
pass
def GetClassID(self, pClassID):
"""
GetClassID(self: UCOMIMoniker) -> Guid
Retrieves the class identifier (CLSID) of an object.
"""
pass
def GetDisplayName(self, pbc, pmkToLeft, ppszDisplayName):
"""
GetDisplayName(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker) -> str
Gets the display name,which is a user-readable representation of this moniker.
pbc: A reference to the bind context to use in this operation.
pmkToLeft: A reference to the moniker to the left of this moniker,if the moniker is part of a composite
moniker.
"""
pass
def GetSizeMax(self, pcbSize):
"""
GetSizeMax(self: UCOMIMoniker) -> Int64
Returns the size in bytes of the stream needed to save the object.
"""
pass
def GetTimeOfLastChange(self, pbc, pmkToLeft, pFileTime):
"""
GetTimeOfLastChange(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker) -> FILETIME
Provides a number representing the time the object identified by this moniker was last changed.
pbc: A reference to the bind context to be used in this binding operation.
pmkToLeft: A reference to the moniker to the left of this moniker,if the moniker is part of a composite
moniker.
"""
pass
def Hash(self, pdwHash):
"""
Hash(self: UCOMIMoniker) -> int
Calculates a 32-bit integer using the internal state of the moniker.
"""
pass
def Inverse(self, ppmk):
"""
Inverse(self: UCOMIMoniker) -> UCOMIMoniker
Provides a moniker that,when composed to the right of this moniker or one of similar structure,
composes to nothing.
"""
pass
def IsDirty(self):
"""
IsDirty(self: UCOMIMoniker) -> int
Checks the object for changes since it was last saved.
Returns: An S_OKHRESULT value if the object has changed; otherwise,an S_FALSEHRESULT value.
"""
pass
def IsEqual(self, pmkOtherMoniker):
"""
IsEqual(self: UCOMIMoniker,pmkOtherMoniker: UCOMIMoniker)
Compares this moniker with a specified moniker and indicates whether they are identical.
pmkOtherMoniker: A reference to the moniker to be used for comparison.
"""
pass
def IsRunning(self, pbc, pmkToLeft, pmkNewlyRunning):
"""
IsRunning(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker,pmkNewlyRunning: UCOMIMoniker)
Determines whether the object that is identified by this moniker is currently loaded and running.
pbc: A reference to the bind context to be used in this binding operation.
pmkToLeft: A reference to the moniker to the left of this moniker if this moniker is part of a composite.
pmkNewlyRunning: A reference to the moniker most recently added to the Running Object Table.
"""
pass
def IsSystemMoniker(self, pdwMksys):
"""
IsSystemMoniker(self: UCOMIMoniker) -> int
Indicates whether this moniker is of one of the system-supplied moniker classes.
"""
pass
def Load(self, pStm):
"""
Load(self: UCOMIMoniker,pStm: UCOMIStream)
Initializes an object from the stream where it was previously saved.
pStm: Stream from which the object is loaded.
"""
pass
def ParseDisplayName(self, pbc, pmkToLeft, pszDisplayName, pchEaten, ppmkOut):
"""
ParseDisplayName(self: UCOMIMoniker,pbc: UCOMIBindCtx,pmkToLeft: UCOMIMoniker,pszDisplayName: str) -> (int,UCOMIMoniker)
Reads as many characters of the specified display name as it understands and builds a moniker
corresponding to the portion read.
pbc: A reference to the bind context to be used in this binding operation.
pmkToLeft: A reference to the moniker that has been built out of the display name up to this point.
pszDisplayName: A reference to the string containing the remaining display name to parse.
"""
pass
def Reduce(self, pbc, dwReduceHowFar, ppmkToLeft, ppmkReduced):
"""
Reduce(self: UCOMIMoniker,pbc: UCOMIBindCtx,dwReduceHowFar: int,ppmkToLeft: UCOMIMoniker) -> (UCOMIMoniker,UCOMIMoniker)
Returns a reduced moniker which is another moniker that refers to the same object as this
moniker but can be bound with equal or greater efficiency.
pbc: A reference to the IBindCtx interface on the bind context to be used in this binding operation.
dwReduceHowFar: Specifies how far this moniker should be reduced.
ppmkToLeft: A reference to the moniker to the left of this moniker.
"""
pass
def RelativePathTo(self, pmkOther, ppmkRelPath):
"""
RelativePathTo(self: UCOMIMoniker,pmkOther: UCOMIMoniker) -> UCOMIMoniker
Supplies a moniker that,when appended to this moniker (or one with a similar structure),yields
the specified moniker.
pmkOther: A reference to the moniker to which a relative path should be taken.
"""
pass
def Save(self, pStm, fClearDirty):
"""
Save(self: UCOMIMoniker,pStm: UCOMIStream,fClearDirty: bool)
Saves an object to the specified stream.
pStm: The stream into which the object is saved.
fClearDirty: Indicates whether to clear the modified flag after the save is complete.
"""
pass
def __init__(self, *args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
|
medida = float(input("Uma distância em metros: "))
km = medida /1000
hm = medida /100
dam = medida /10
dm = medida *10
cm = medida*100
mm = medida *1000
print("A distância de {}m corresponde a\n {}km\n {}hm\n {}dam\n {}dm\n {}cm\n {}mm ".format(medida , km, hm, dam, dm, cm, mm))
|
score = int(input("성적을 입력하시오: "))
credit = 'F'
if score >= 90 :
credit = 'A'
elif score >= 80 :
credit = 'B'
elif score >= 70 :
credit = 'C'
elif score >= 60 :
credit = 'D'
print(f'{credit}학점입니다.') |
# https://www.tutorialspoint.com/python_data_structure/python_binary_tree.htm
class Node:
def __init__(self, data):
self.data = data
self.left = None
self.right = None
def insert(self, data):
if self.data:
if data < self.data:
if not self.left:
self.left = Node(data)
else:
self.left.insert(data)
elif data > self.data:
if not self.right:
self.right = Node(data)
else:
self.right.insert(data)
else:
self.data = data
def print_tree(self):
if self.left:
self.left.print_tree()
print(self.data)
if self.right:
self.right.print_tree()
def in_order_traversal(self, root):
"""left -> root -> right"""
res = []
if root:
res = self.in_order_traversal(root.left)
res.append(root.data)
res += self.in_order_traversal(root.right)
return res
def pre_order_traversal(self, root):
"""root -> left -> right"""
res = []
if root:
res.append(root.data)
res += self.pre_order_traversal(root.left)
res += self.pre_order_traversal(root.right)
return res
def post_order_traversal(self, root):
"""left -> right -> root"""
res = []
if root:
res = self.post_order_traversal(root.left)
res += self.post_order_traversal(root.right)
res.append(root.data)
return res
root = Node(27)
root.insert(14)
root.insert(35)
root.insert(10)
root.insert(19)
root.insert(31)
root.insert(42)
root.insert(20)
print("Print tree:")
root.print_tree()
print("In order traversal:")
print(root.in_order_traversal(root))
print("Pre order traversal:")
print(root.pre_order_traversal(root))
print("Post order traversal:")
print(root.post_order_traversal(root))
|
#!/usr/bin/env python3
# Get superior triangular matrix a)
n = 3
A = [[1, 1/2, 1/3], [1/2, 1/3, 1/4], [1/3, 1/4, 1/5]]
b = [-1, 1, 1]
for i in range(n):
pivot = A[i][i]
b[i] /= pivot
for j in range(n):
A[i][j] /= pivot
for j in range(i+1, n):
times = A[j][i]
b[j] -= times * b[i]
for k in range(n):
A[j][k] -= times * A[i][k]
print("A:", A)
print("b:", b)
# Get x b)
x = [0, 0, 0]
x[2] = b[2]
x[1] = b[1] - A[1][2] * x[2]
x[0] = b[0] - A[0][2] * x[2] - A[0][1] * x[1]
print("x:", x)
# EXTERNAL STABILITY
# A.dx = db - dA.x
# don't feel like importing copy
A = [[1, 1/2, 1/3], [1/2, 1/3, 1/4], [1/3, 1/4, 1/5]]
# calculate new b
dA = 0.05
db = 0.05
nA = [[dA, dA, dA], [dA, dA, dA], [dA, dA, dA]]
b = [db, db, db]
for i in range(n):
for j in range(n):
b[i] -= nA[i][j] * x[j]
# solve new system
for i in range(n):
pivot = A[i][i]
b[i] /= pivot
for j in range(n):
A[i][j] /= pivot
for j in range(i+1, n):
times = A[j][i]
b[j] -= times * b[i]
for k in range(n):
A[j][k] -= times * A[i][k]
print("\nA:", A)
print("b:", b)
# Get x (external stability)
x = [0, 0, 0]
x[2] = b[2]
x[1] = b[1] - A[1][2] * x[2]
x[0] = b[0] - A[0][2] * x[2] - A[0][1] * x[1]
print("stablity:", x)
# The one with the most sensitivity to erros is x3 (aka x[2] or z) d)
# abs(x[0] < x[1] < x[2])
print("most sensitive:", max(abs(i) for i in x))
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
###
# Name: Benjamin Seeley
# Student ID: 2262810
# Email: seele105@mail.chapman.edu
# Course: PHYS220/MATH220/CPSC220 Fall 2018
# Assignment: CW03
###
"""Contains helper functions that return lists of sequences.
"""
def fibonacci(n):
"""Returns n fibonacci numbers
Args:
n: number of fibonacci numbers to return
Returns:
List that contains n fibonacci numbers
Raises:
ValueError when n is not a positive integer
"""
if n < 1:
raise ValueError("n must be a positive integer")
output = []
f1 = 0
f2 = 1
fn = 1
count = 0
for i in range(n):
output.append(fn)
fn = f1 + f2
f1 = f2
f2 = fn
return output
|
class CustomerAddWebsitePermissionDenied(Exception):
pass
class ObjectDoesNotExist(Exception):
pass
|
soma = 0
vezes = 0
for c in range(1, 501):
if (c % 2 == 1):
if (c % 3 == 0):
soma += c
vezes += 1
print('A soma de todos os {} valores solicitados é {}'.format(vezes, soma))
|
"""
Handle
A wrapper meant to collect the python object belonging to a blizzard 'handle'.
"""
class Handle:
handles = {}
def __init__(self, handle):
# constructorfunc can be a function that returns a handle, or a handle directly
self._handle = handle
if Handle.get(handle) != None:
print("Warning: secondary object created for handle ", handle, "object", self)
Handle.handles[self._handle] = self
@staticmethod
def get(handle):
if handle in Handle.handles:
return Handle.handles[handle]
return None
def destroy(self):
del Handle.handles[self._handle]
self._handle = None
@property
def handle(self):
return self._handle
|
#!/bin/python3
def main(person_list):
users = []
for name, email in person_list:
if email.endswith('@gmail.com'):
users.append(name)
print(*sorted(users), sep='\n')
if __name__ == '__main__':
N = int(input())
persons = []
for N_itr in range(N):
firstName, emailID = input().split()
persons.append((firstName, emailID))
main(persons)
|
# basic example
class MetaSpam(type):
# notice how the __new__ method has the same arguments
# as the type function we used earlier.
def __new__(metaclass, name, bases, namespace):
name = 'SpamCreateByMeta'
bases = (int,) + bases
namespace['eggs'] = 1
return type.__new__(metaclass, name, bases, namespace)
# regular Spam
class Spam(object):
pass
print(Spam.__name__)
print(issubclass(Spam, int))
try:
Spam.eggs
except Exception as e:
print(e)
# meta Spam
class Spam(object, metaclass=MetaSpam):
pass
print(Spam.__name__)
print(issubclass(Spam, int))
print(Spam.eggs)
|
"""
232. Implement Queue using Stacks
Implement the following operations of a queue using stacks.
push(x) -- Push element x to the back of queue.
pop() -- Removes the element from in front of queue.
peek() -- Get the front element.
empty() -- Return whether the queue is empty.
Example:
MyQueue queue = new MyQueue();
queue.push(1);
queue.push(2);
queue.peek(); // returns 1
queue.pop(); // returns 1
queue.empty(); // returns false
Notes:
You must use only standard operations of a stack -- which means only push to top, peek/pop from top, size, and is empty operations are valid.
Depending on your language, stack may not be supported natively. You may simulate a stack by using a list or deque (double-ended queue), as long as you use only standard operations of a stack.
You may assume that all operations are valid (for example, no pop or peek operations will be called on an empty queue).
"""
class MyQueue:
def __init__(self):
"""
Initialize your data structure here.
"""
self.queue = []
def push(self, x: int):
"""
Push element x to the back of queue.
"""
self.queue.insert(0,x)
def pop(self):
"""
Removes the element from in front of queue and returns that element.
"""
return self.queue.pop()
def peek(self):
"""
Get the front element.
"""
return self.queue[-1]
def empty(self):
"""
Returns whether the queue is empty.
"""
return self.queue == []
# Your MyQueue object will be instantiated and called as such:
# obj = MyQueue()
# obj.push(x)
# param_2 = obj.pop()
# param_3 = obj.peek()
# param_4 = obj.empty() |
S = input()
for i in range(len(S)):
print(i + 1)
|
def c_to_f(c):
Farhenheite=(c*9/5)+32
return Farhenheite
n=int(input("Celcius="))
f=c_to_f(n)
print(f,"'F")
|
"""
Write a function that returns the lesser of two given numbers if both numbers are even,
but returns the greater if one or both numbers are odd.
Example 1:
lesser_of_two_evens(2, 4) output: 2
explanation:
the two parameters 2 and 4 are even numbers, therefore, we'll return the smallest even number
Example 2:
lesser_of_two_evens(2, 5) output: 5
explanation:
the first parameter 2 is even, but the second parameter 5 is odd, therefore, we'll return the greatest number
Example 3:
lesser_of_two_evens(7, 5) output: 7
explanation:
the two parameters are odd, therefore, we'll return the greatest number
"""
# write your code here
# don't forget to test your code
def lesser_of_two_evens(a, b):
pass |
class QueueOverflow(BaseException):
pass
# Node of a doubly linkedlist
class Node:
# constructor
def __init__(self, data=None):
self.data = data
self.next = None
self.prev = None
# method for setting the data field of the node
def setData(self, data):
self.data = data
# method for getting the data field of the node
def getData(self):
return self.data
# method for setting the next field of the node
def setNext(self, nextOne):
self.next = nextOne
# method for getting the next field of the node
def getNext(self):
return self.next
# return True if the node has a pointer to the next node
def hasNext(self):
return self.next is not None
# method for setting the next field of the node
def setPrev(self, prevOne):
self.prev = prevOne
# method for getting the prev field of the node
def getPrev(self):
return self.prev
# return True if the node has a pointer to the previous node
def hasPrev(self):
return self.prev is not None
'''
returns a copy of the current Node's data
if include_pointers is set to True, the pointers
next and prev will be added to the returned node
'''
def copy(self, include_pointers=False):
if include_pointers:
to_return = Node(self.data)
to_return.next = self.next
to_return.prev = self.prev
return to_return
return Node(self.data)
# Linked Queue
class Queue:
'''
Initialize method, creates Stack
:param limit, max amount of elements in stack
'''
def __init__(self, limit=None):
self.limit = limit
self.head = None
self.tail = None
'''
Used to convert data to Node if data is not already Node
:param data, the data converted
'''
def __toNode(self, data):
if isinstance(data, Node):
return data.copy()
return Node(data)
'''
Checks if stack has too many elements, and if it does, it raises
StackOverflow
'''
def __isError(self):
if self.limit is not None and self.limit <= self.Size():
raise QueueOverflow
'''
Add elements to end of stack
:param data, element to add to stack
'''
def Push(self, data):
self.__isError()
data = self.__toNode(data)
if self.head is None:
self.head = data
self.tail = data
else:
data.prev = self.tail
self.tail.next = data
self.tail = data
'''
Removes last element in stack, returns the element popped
'''
def Pop(self):
if self.head == self.tail:
to_return = self.head
self.head = None
self.tail = None
else:
to_return = self.head
self.head = self.head.next
self.head.prev = None
return to_return
'''
Returns the last element in stack
'''
def Front(self):
return self.head
'''
Returns the size of the stack
'''
def Size(self):
self.current = self.head
currentNum = 0
if self.current is not None:
while self.current.getNext() is not None:
currentNum += 1
self.current = self.current.getNext()
return currentNum+1
return currentNum
'''
Returns a boolean value if the stack is empty or not
'''
def isEmptyQueue(self):
return self.head is None
'''
Returns a boolean value depending on if the stack is full
'''
def isFullQueue(self):
if isinstance(self.limit, int):
if self.limit == self.Size():
return True
return False
'''
Do not use this, testing only
'''
def showAll(self):
self.current = self.head
currentNum = 0
if self.current is not None:
while self.current.getNext() is not None:
currentNum += 1
yield self.current.data
self.current = self.current.getNext()
yield self.current.data
'''
Returns a copy of the stack
'''
def copy(self):
newStack = Queue()
self.current = self.head
currentNum = 0
if self.current is not None:
while self.current.getNext() is not None:
currentNum += 1
newStack.Push(self.current.data)
self.current = self.current.getNext()
newStack.Push(self.current.data)
return newStack
def load_from_iterable(self, iterable):
for item in iterable:
self.Push(item)
'''
Returns length of Stack
'''
def __len__(self):
return self.Size()
def __repr__(self):
return self
def __str__(self):
return str(list(self.showAll()))
|
#!/usr/bin/python
'''
Copyright 2016 Aaron Stephens <aaron@icebrg.io>, ICEBRG
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
class CodeDirectory(object):
# Constructor
def __init__(self, version=None, flags=None, hash_offset=None,
ident_offset=None, n_special_slots=None, n_code_slots=None,
code_limit=None, hash_size=None, hash_type=None,
platform=None, page_size=None, scatter_offset=None,
team_id_offset=None, identity=None, team_id=None):
self.version = version
self.flags = flags
self.hash_offset = hash_offset
self.ident_offset = ident_offset
self.n_special_slots = n_special_slots
self.n_code_slots = n_code_slots
self.code_limit = code_limit
self.hash_size = hash_size
self.hash_type = hash_type
self._platform = platform
self.page_size = page_size
self._scatter_offset = scatter_offset
self._team_id_offset = team_id_offset
self.identity = identity
self._team_id = team_id
self.hashes = []
# Properties
@property
def platform(self):
if self.version >= 0x20200:
return self._platform
return None
@platform.setter
def platform(self, platform):
self._platform = platform
@property
def scatter_offset(self):
if self.version >= 0x20100:
return self._scatter_offset
return None
@scatter_offset.setter
def scatter_offset(self, scatter_offset):
self._scatter_offset = scatter_offset
@property
def team_id_offset(self):
if self.version >= 0x20200:
return self._team_id_offset
@team_id_offset.setter
def team_id_offset(self, team_id_offset):
self._team_id_offset = team_id_offset
@property
def team_id(self):
if self.version >= 0x20200 and self.team_id_offset != 0:
return self._team_id
return None
@team_id.setter
def team_id(self, team_id):
self._team_id = team_id
# Generators
def gen_hashes(self):
for i in self.hashes:
yield i
# Functions
def add_hash(self, hash): self.hashes.append(hash)
|
text = """
//------------------------------------------------------------------------------
// Explicit instantiation.
//------------------------------------------------------------------------------
#include "Geometry/Dimension.hh"
#include "GSPH/Limiters/SuperbeeLimiter.cc"
namespace Spheral {
template class SuperbeeLimiter<Dim< %(ndim)s > >;
}
"""
|
class ProfilePage:
BACK_TO_USERS = "Back to members"
EDIT_USER_BUTTON = "Change role"
USER_EMAIL = "Email"
USER_FIRST_NAME = "First name"
USER_LAST_NAME = "Last name"
USER_ROLE = "Role"
USER_STATUS = "Status"
USER_PENDING = "Pending"
USER_DEACTIVATE = "Deactivate member"
USER_REACTIVATE = "Reactivate member"
USER_NOT_ACTIVATED_YET = "This member hasn't signed in to their export control account."
class UsersPage:
MANAGE_ORGANISATIONS_MEMBERS_TAB = "Members"
USER_EMAIL = "Email"
USER_NAME = "Name"
USER_PENDING = "Pending"
USER_ROLE = "Role"
USER_STATUS = "Status"
class AddUserForm:
USER_ROLE_QUESTION = "Role"
USER_ADD_TITLE = "Add a member"
USER_EMAIL_QUESTION = "Email"
USER_ADD_FORM_BACK_TO_USERS = "Back to members"
ASSIGN_USER_QUESTION = "Assigned sites"
class EditUserForm:
USER_ROLE_QUESTION = "Role"
USER_EDIT_TITLE = "Change role"
USER_EDIT_FORM_BACK_TO_USER = "Back to member"
USER_EDIT_FORM_SAVE = "Save"
class AssignToSitesForm:
ASSIGN_USER_TO_SITES_TITLE = "Assign member to sites"
ASSIGN_USER_TO_SITES_DESCRIPTION = ""
|
'''Program to find the factorial of a number using recursion'''
def factorial_of_a_number(n):
if n<=1:
return 1
else:
return n * factorial_of_a_number(n-1)
#Taking number from user and passing it to the function
n = int(input())
print(factorial_of_a_number(n)) |
class EN:
START_TEXT = """
Hello {},
I am ROBOT.
"""
|
def dec_to_bin(n):
if n < 0:
return bin(n * -1)[2:]
return bin(n)[2:]
def trim_to(number, length):
zeroes = ''
for i in range(int(length) - len(number)):
zeroes += '0'
return zeroes + number
def bit_not(number):
negated = ''
for bit in number:
if bit == '1':
negated += '0'
elif bit == '0':
negated += '1'
return negated
def add_one(number, length):
addone = ''
carryover = ''
if number[len(number) - 1] == '0':
addone += number[:-1]
addone += '1'
return addone
else: #Not the best way to do a bitwise addition but it works
carryover = '1' #Because the number we start with is 1 and 1 + 1 = 0 with carryover 1
#We iterate through the number but in reversed order sind we start the addition from the end.
for bit in number[::-1]:
if bit == '0':
if carryover == '1':
addone += '1'
carryover = '0'
else:
addone += '0'
if bit == '1':
if carryover == '1':
addone += '0'
else:
addone += '1'
carryover = '0'
return trim_to(addone[::-1], length)
if __name__ == '__main__':
number = input('Enter the (decimal) number you want to convert to the Two\'s Complement: ')
bitlength = len(dec_to_bin(int(number)))
length = input('Enter the length to which your number should be trimmed to: ')
if bitlength > int(length):
print('You should use at least a length equal or greater then the binary number itself!')
else:
if int(number) >= 0:
bit = trim_to(dec_to_bin(int(number)), length)
print('\nConverting ' + number + ' using the bit length ' + length + ' to -> ' + bit)
print('Finally we get...')
print(trim_to(dec_to_bin(int(number)), length))
else:
bit = trim_to(dec_to_bin(int(number)), length)
not_bit = bit_not(bit)
print('\nConverting the positive number of ' + number + ' using the bit length ' + length + ' to -> ' + bit)
print('Negating ' + bit + ' to -> ' + not_bit)
print('Finally add 1 to the negated number and we get...')
print (add_one(not_bit, length))
print('\nEnd...') |
def printSet(set):
sorted(set)
print('{', end=" ")
for x in set :
print(x, end=" ")
print('}')
def main():
a = set("Hi There, Raghuram")
b = set("Hello, Nice to Meet you")
x = set('hello')
y = set('world')
printSet(a)
printSet(b)
printSet(x - y )
if __name__ == "__main__": main() |
with open('input.txt') as f:
lines = [int(i) for i in f.readlines()]
depth_increased = 0
for i in range(0, len(lines) - 3):
last_sum = sum(lines[i-1:i+2])
current_sum = sum(lines[i:i+3])
if (current_sum > last_sum):
depth_increased = depth_increased + 1
print(depth_increased) # 1600
|
"""
Datos de entrada
trabajador-->nombre-->str
horas trabajadas-->ht-->float
precio por hora-->ph-->float
horas extra-->hx-->float
precio hora extra-->phx-->float
Deducciones-->d-->float
paro forzoso->pf-->float
política habitacional-->polh-->float
caja de ahorro-->ch-->float
Asignaciones-->a-->float
actualización académica-->aa-->int
cantidad hijos-->ca-->int
asignación hijo-->ah-->int
pago por hijo-->pa-->int
prima hogar-->ap-->int
Salidas
sueldo normal-->s-->float
incremento hora extra-->ihx-->float
pago hora extra-->phx-->float
sueldo base-->sb-->float
sueldo de diciembre-->sd-->float
"""
#Entradas
nombre=str(input("Ingrese su nombre "))
ht=float(input("Digite las horas trabajadas "))
ph=float(input("Digite el precio por hora "))
hx=float(input("Digite las horas extra trabajadas "))
pf=float(input("Digite el porcentaje por paro forzoso "))
polh=float(input("Digite el porcentaje por política habitacional "))
ch=float(input("Digite el porcentaje por caja de ahorro "))
ca=int(input("Digite el número de hijos que tiene "))
aa=int(input("Digite la asignación de actuaización académica "))
ah=int(input("Digite la asignación por hijo "))
ap=int(input("Digite la asignación de la prima "))
#Caja negra
phx=(ph*0.25)+ph
s=ht*ph
ihx=hx*phx
sb=s+ihx
d=sb*(pf+polh+ch)
pa=ah*ca
a=aa+pa+ap
sd=(sb+a)-d
#Salidas
print(f"El total de asignaciones es: {a}")
print(f"El total de deduciones es: {d}")
print(nombre,(", su saldo neta para el mes de diciembre es: "+str(sd)))
|
# https://leetcode.com/problems/missing-number/description/
# Time: O(n) ~ O(n^2)
# Space: O(n)
# Given a string array words, find the maximum value of
# length(word[i]) * length(word[j]) where the two words
# do not share common letters. You may assume that each
# word will contain only lower case letters. If no such
# two words exist, return 0.
#
# Example 1:
# Given ["abcw", "baz", "foo", "bar", "xtfn", "abcdef"]
# Return 16
# The two words can be "abcw", "xtfn".
#
# Example 2:
# Given ["a", "ab", "abc", "d", "cd", "bcd", "abcd"]
# Return 4
# The two words can be "ab", "cd".
#
# Example 3:
# Given ["a", "aa", "aaa", "aaaa"]
# Return 0
# No such pair of words.
#
# Follow up:
# Could you do better than O(n2), where n is the number of words?
# V0
# V1
# https://blog.csdn.net/fuxuemingzhu/article/details/80932597
# IDEA : SET
class Solution:
def maxProduct(self, words):
"""
:type words: List[str]
:rtype: int
"""
word_dict = dict()
for word in words:
word_dict[word] = set(word)
max_len = 0
for i1, w1 in enumerate(words):
for i2 in range(i1+1, len(words)):
w2 = words[i2]
if not (word_dict[w1] & word_dict[w2]):
max_len = max(max_len, len(w1) * len(w2))
return max_len
# V1'
# https://blog.csdn.net/fuxuemingzhu/article/details/80932597
# IDEA : BIT MANIPULATION
class Solution(object):
def maxProduct(self, words):
"""
:type words: List[str]
:rtype: int
"""
res = 0
d = collections.defaultdict(int)
N = len(words)
for i in range(N):
w = words[i]
for c in w:
d[w] |= 1 << (ord(c) - ord('a'))
for j in range(i):
if not d[words[j]] & d[words[i]]:
res = max(res, len(words[j]) * len(words[i]))
return res
# V2
# Time: O(n) ~ O(n^2)
# Space: O(n)
class Solution(object):
def maxProduct(self, words):
"""
:type words: List[str]
:rtype: int
"""
def counting_sort(words):
k = 1000 # k is max length of words in the dictionary
buckets = [[] for _ in range(k)]
for word in words:
buckets[len(word)].append(word)
res = []
for i in reversed(range(k)):
if buckets[i]:
res += buckets[i]
return res
words = counting_sort(words)
bits = [0] * len(words)
for i, word in enumerate(words):
for c in word:
bits[i] |= (1 << (ord(c) - ord('a')))
max_product = 0
for i in range(len(words) - 1):
if len(words[i]) ** 2 <= max_product:
break
for j in range(i + 1, len(words)):
if len(words[i]) * len(words[j]) <= max_product:
break
if not (bits[i] & bits[j]):
max_product = len(words[i]) * len(words[j])
return max_product
# Time: O(nlogn) ~ O(n^2)
# Space: O(n)
# Sorting + Pruning + Bit Manipulation
class Solution2(object):
def maxProduct(self, words):
"""
:type words: List[str]
:rtype: int
"""
words.sort(key=lambda x: len(x), reverse=True)
bits = [0] * len(words)
for i, word in enumerate(words):
for c in word:
bits[i] |= (1 << (ord(c) - ord('a')))
max_product = 0
for i in range(len(words) - 1):
if len(words[i]) ** 2 <= max_product:
break
for j in range(i + 1, len(words)):
if len(words[i]) * len(words[j]) <= max_product:
break
if not (bits[i] & bits[j]):
max_product = len(words[i]) * len(words[j])
return max_product
|
class Bye:
def __init__(self):
self.foo = 'bar'
def is_hello(self):
return type(self) == Hello
class Hello:
def __init__(self):
self.value = 'foobar'
print(Bye().is_hello())
|
# Leetcode 70. Climbing Stairs
#
# Link: https://leetcode.com/problems/climbing-stairs/
# Difficulty: Easy
# Solution using DP
# Complexity:
# O(N) time | where N represent the number of steps of the staircase
# O(1) space
class Solution:
def climbStairs(self, n: int) -> int:
one, two = 1, 1
for i in range(n - 1):
one, two = one + two, one
return one
|
## Set to display confirmation dialog on exit. You can always use 'exit' or
# 'quit', to force a direct exit without any confirmation.
c.JupyterConsoleApp.confirm_exit = False
## Whether to display a banner upon starting the QtConsole.
c.JupyterQtConsoleApp.display_banner = False
## Start the console window with the menu bar hidden.
c.JupyterQtConsoleApp.hide_menubar = True
|
#66: Compute a Grade Point Average
a={'A+':4.0,'A':4.0,'A-':3.7,'B+':3.3,'B':3.0,'B-':2.7,'C+':2.3,'C':2.0,'C-':1.7,'D+':1.3,'D':1.0,'F':0}
add=lambda x,y:x+y
c=0
d=0
while True:
b=input("Enter the grade:")
if b=="":
break
c=add(c,a[b])
d+=1
print("Average grade point:",c/d)
|
"""
Given two arrays, write a function to compute their intersection.
Note:
- Each element in the result must be unique.
- The result can be in any order.
link: https://leetcode.com/problems/intersection-of-two-arrays/
"""
class Solution(object):
def intersection(self, nums1, nums2):
"""
Finds the intersection of two given array.
:type nums1: List[int]
:type nums2: List[int]
:rtype: List[int]
"""
return list(set(nums1).intersection(set(nums2)))
nums1 = [1, 2, 2, 1]
nums2 = [2, 2]
obj = Solution()
result = obj.intersection(nums1, nums2)
print(result)
|
def test_mining_property_tester(web3_tester):
web3 = web3_tester
assert web3.eth.mining is False
def test_mining_property_ipc_and_rpc(web3_empty, wait_for_miner_start,
skip_if_testrpc):
web3 = web3_empty
skip_if_testrpc(web3)
wait_for_miner_start(web3)
assert web3.eth.mining is True
|
# #072: Crie um programa que tenha uma dupla totalmente preenchida com uma contagem por extenso, de zero até vinte.
# # Seu programa deverá ler um número pelo teclado (entre 0 e 20) e mostrá-lo por extenso.
# n = ('zero', 'um', 'dois', 'três', 'quatro', 'cinco', 'seis', 'sete', 'oito', 'nove', 'dez', 'onze', 'oze', 'treze', 'quatorze', 'quinze', 'dezesseis','dezessete', 'dezoito', 'dezenove', 'vinte')
#
# c = int(input('Qual numeor voce quer que eu escreva por estenço:'))
#
# while True:
# if c >= 0 and c <= 20:
# break
# else:
# c = int(input('Qual numeor voce quer que eu escreva por estenço:'))
#
# print(f'Seu numero por extenço é:{n[c]}')
n = ('zero', 'um', 'dois', 'três', 'quatro', 'cinco', 'seis', 'sete', 'oito', 'nove', 'dez', 'onze', 'doze', 'treze', 'quatorze', 'quinze', 'dezesseis','dezessete', 'dezoito', 'dezenove', 'vinte')
while True:
c = int(input('Qual numeor voce quer que eu escreva por estenço:'))
while True:
if c >= 0 and c <= 20:
break
else:
c = int(input('Qual numeor voce quer que eu escreva por estenço:'))
print(f'Seu numero por extenço é:{n[c]}')
n1 = str(input('Você quer continuar[S/N]'))
if n1 in 'Nn':
break
|
class Solution:
def checkIfExist(self, arr):
exists = {}
for num in arr:
if (num * 2) in exists or ((num / 2) in exists and num % 2 == 0):
return True
exists[num] = True
return False |
#input
# 637 3371 327 67 924 968 2 6 6 77 5464 21813 70 5 67 74225 46 2 310 6156 50 4 623 87675 1702 3947 4927 9628 7 510 31 65 3321 23993 8406 88 -1
array = [int(x) for x in input().split()]
array.remove(-1)
swaps = 0
for i in range(0, len(array) - 1):
if array[i] > array[i+1]:
swaps += 1
t = array[i]
array[i] = array[i+1]
array[i+1] = t
checksum = 0
for num in array:
checksum += num
checksum *= 113
checksum %= 10000007
print(swaps, checksum) |
DEBUG = True
|
# Write a program that reads a word and prints the number of syllables in the word.
# For this exercise, assume that syllables are determined as follows: Each sequence of
# adjacent vowels a e i o u y , except for the last e in a word, is a syllable. However, if
# that algorithm yields a count of 0, change it to 1. For example,
# Word Syllables
# Harry 2
# hairy 2
# hare 1
# the 1
inputWord = str(input("Enter a word: "))
vowels = ('a','e','i','o','u','y','A','E','I','O','U','Y')
lastVowel = False
lastCons = False
currVowel = False
currCons = False
syllablesCount = 0
for i in range(len(inputWord)):
letter = inputWord[i]
if letter in vowels:
currVowel = True
currCons = False
else:
currVowel = False
currCons = True
if currCons == True and lastVowel == True:
syllablesCount += 1
lastVowel = currVowel
lastCons = currCons
lastStart = len(inputWord) - 1
lastEnd = len(inputWord)
last = inputWord[lastStart:lastEnd]
if last == "a" or last == "i" or last == "o" or last == "u" or last == "y" or last == "A" or last == "I" or last == "O" or last == "U" or last == "Y":
syllablesCount += 1
if syllablesCount == 0:
syllablesCount = 1
print("There are %d syllables" % syllablesCount) |
# Maximum number of images to keep in the database
MAX_FILES = 20
# Size of a JPEG minimum coded unit (MCU)
BLOCK_SIZE = 16
# Images will be resized to this width
IMAGE_WIDTH = 1200
# Image aspect ratio
ASPECT_RATIO = 3
|
# Source: https://leetcode.com/problems/contains-duplicate-iii/
# Better approach; Current time complexity: O(n * k)
class Solution:
def containsNearbyAlmostDuplicate(self, nums: List[int], k: int, t: int) -> bool:
if t == 0 and len(set(nums)) == len(nums):
return False
for i in range(len(nums)):
for j in range(i + 1, min(i + k + 1, len(nums))):
if abs(nums[i] - nums[j]) <= t:
return True
return False
|
response = sm.sendAskYesNo("Are you sure you want to leave?")
# sm.sendSay("Response was " + str(response) + "\r\rAnswer was " + str(answer))
if response:
sm.clearPartyInfo(401060000)
sm.dispose()
|
# -*- coding: utf-8 -*-
# Copyright 2019 Cohesity Inc.
class IndexingPolicy(object):
"""Implementation of the 'IndexingPolicy' model.
Specifies settings for indexing files found in an Object
(such as a VM) so these files can be searched and recovered.
This also specifies inclusion and exclusion rules that determine
the directories to index.
Attributes:
allow_prefixes (list of string): Array of Indexed Directories.
Specifies a list of directories to index.
deny_prefixes (list of string): Array of Excluded Directories.
Specifies a list of directories to exclude from indexing.
disable_indexing (bool): Specifies if the files found in an Object
(such as a VM) should be indexed. If false (the default), files
are indexed.
"""
# Create a mapping from Model property names to API property names
_names = {
"allow_prefixes":'allowPrefixes',
"deny_prefixes":'denyPrefixes',
"disable_indexing":'disableIndexing'
}
def __init__(self,
allow_prefixes=None,
deny_prefixes=None,
disable_indexing=None):
"""Constructor for the IndexingPolicy class"""
# Initialize members of the class
self.allow_prefixes = allow_prefixes
self.deny_prefixes = deny_prefixes
self.disable_indexing = disable_indexing
@classmethod
def from_dictionary(cls,
dictionary):
"""Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class.
"""
if dictionary is None:
return None
# Extract variables from the dictionary
allow_prefixes = dictionary.get('allowPrefixes')
deny_prefixes = dictionary.get('denyPrefixes')
disable_indexing = dictionary.get('disableIndexing')
# Return an object of this model
return cls(allow_prefixes,
deny_prefixes,
disable_indexing)
|
VISIT_DETAIL_FORM_CONSTANTS = {
'visit_date':{
'max_length': 100,
"data-dojo-type": "dijit.form.DateTextBox",
"data-dojo-props": r"'required' :true"
},
'op_surgeon':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' : true"
},
'referring_doctor':{
'max_length': 100,
"data-dojo-type": "dijit.form.ValidationTextBox",
"data-dojo-props": r"'required' :false"
},
'consult_nature':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' :true"
},
'status':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' :true"
},
'remarks':{
'max_length': 150,
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' :false"
}
}
VISIT_COMPLAINTS_FORM_CONSTANTS = {
#{"field" : 'visit_detail',
#'max_length' : '100' ,
#"data-dojo-type" : "dijit.form.Select",
# "data-dojo-props": r"'required' : false ,'readOnly':true,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'",
#'style':r"display:none;"
#},
#{"field" : 'parent_clinic',
#'max_length' : '100' ,
#"data-dojo-type" : "dijit.form.Select",
# "data-dojo-props": r"'required' : false ,'readOnly':true,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'",
#'style':r"display:none;"
#},
#{"field" : 'base_model',
#'max_length' : '100' ,
#"data-dojo-type" : "dijit.form.ValidationTextBox",
# "data-dojo-props": r"'required' : false ,'readOnly':true,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'",
#'style':r"display:none;"
#},
'complaint':{
'max_length': '100',
"data-dojo-type": "dijit.form.ValidationTextBox",
"data-dojo-props": r"'required' : false ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'",
},
'duration':{
'max_length': '100',
"data-dojo-type": "dijit.form.ValidationTextBox",
"data-dojo-props": r"'required' : false ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'",
}
}
VISIT_HPI_FORM_CONSTANTS = {
'hpi':{
'max_length': '1000',
"data-dojo-type": "dijit/form/SimpleTextarea",
"data-dojo-id": "visit_hpi",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-_:0-9#]+','invalidMessage' : 'Invalid Character'",
"style" : r"width: 70%;min-width:50%;"
}
}
VISIT_PAST_HISTORY_FORM_CONSTANTS = {
'past_history':{
'max_length': '1000',
"data-dojo-type": "dijit.form.SimpleTextarea",
"data-dojo-id": "visit_past_history",
"data-dojo-props": r"'required' : 'true' ,'regExp':'[a-zA-Z /-_:0-9#]+','invalidMessage' : 'Invalid Character'"
}
}
VISIT_IMAGING_FORM_CONSTANTS = {
'modality':{
'max_length': '100',
"data-dojo-type": "dijit.form.Select",
"data-dojo-id": "visit_imaging_imaging",
"data-dojo-props": r"'required' : 'true' ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'finding':{
'max_length': '1000',
"data-dojo-type": "dijit.form.SimpleTextarea",
"data-dojo-id": "visit_imaging_finding",
"data-dojo-props": r"'required' : 'true' ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
}
}
VISIT_INVESTIGATION_FORM_CONSTANTS = {
'investigation':{
'max_length': '100',
"data-dojo-type": "dijit.form.Select",
"data-dojo-id": "visit_investigation_investigation",
"data-dojo-props": r"'required' : 'true' ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'value':{
'max_length': '100',
"data-dojo-type": "dijit.form.ValidationTextBox",
"data-dojo-id": "visit_investigation_value",
"data-dojo-props": r"'required' : 'true' ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
}
}
VISIT_ROS_FORM_CONSTANTS = {
'const_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'eye_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'ent_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'cvs_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'resp_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'gi_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'gu_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'ms_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'integ_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'neuro_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'psych_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'endocr_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'immuno_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
'hemat_symp':{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
}
}
VISIT_FOLLOW_UP_FORM_CONSTANTS = {
'visit_date':{
'max_length': 100,
"data-dojo-type": "dijit.form.DateTextBox",
"data-dojo-props": r"'required' :true"
},
'op_surgeon':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' : true"
},
'consult_nature':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' :true"
},
'status':{
'max_length': 100,
"data-dojo-type": "dijit.form.Select",
"data-dojo-props": r"'required' :true"
},
"subjective":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"objective":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"assessment":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"plan":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
}
}
VISIT_SOAP_FORM_CONSTANTS = {
"subjective":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"objective":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"assessment":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
},
"plan":{
'max_length': '500',
"data-dojo-type": "dijit.form.Textarea",
"data-dojo-props": r"'required' : true ,'regExp':'[a-zA-Z /-:0-9#]+','invalidMessage' : 'Invalid Character'"
}
} |
def _merge_mro(seqs):
res = []
i = 0
while 1:
nonemptyseqs = [seq for seq in seqs if seq]
if not nonemptyseqs:
return res
i += 1
for seq in nonemptyseqs:
cand = seq[0]
nothead = [s for s in nonemptyseqs if cand in s[1:]]
if nothead:
cand = None
else:
break
if not cand:
raise GIError("Inconsistent hierarchy")
res.append(cand)
for seq in nonemptyseqs:
if seq[0] == cand:
del seq[0]
def _calc_mro(C):
return _merge_mro([[C]] + map(_calc_mro, C.__bases__) + [list(C.__bases__)])
def _mro(bases):
segs = []
for base in bases:
segs.append(_calc_mro(base))
return _merge_mro(segs)
if __name__ == '__main__':
class F(object): pass
class E(object): pass
class D(object): pass
class C(D, F): pass
class B(D, E): pass
class A(B, C): pass
print(_mro([A, D, E, F]))
|
def Skew(Genome):
res = [0]
for nuc in Genome:
to_app = res[-1]
if nuc == 'C':
to_app -= 1
elif nuc == 'G':
to_app += 1
res.append(to_app)
return res
def MinimumSkew(Genome):
min_val = 0
current_val = 0
min_pos = [0]
for i, nuc in enumerate(Genome):
if nuc == 'C':
current_val -= 1
elif nuc == 'G':
current_val += 1
if current_val < min_val:
min_pos = [i + 1]
min_val = current_val
elif current_val == min_val:
min_pos.append(i + 1)
return min_pos
Genome = 'GATGCAAAGGGCGCGGCCTGAATCATCTTTAAAACAAAACAATTCGGGTTTTTCTGGGGCAGCCGTCCTGACAACTCAATATCATTATTATTACGCGACCGCTAGGCCCTTTGCGATTGTAGGCGTTTCCAAGCTACAGGAGTACAACAAGTATGATCGGTTTAGATTATCTCGATGGACTGCGTCTACGTCTCTTGACGTCACCCTCCTTTGGGGCGTGCTCCTGCTCCGGCGTTTTGGCGTATGCAGCGGTTGACCGACCACCACACAGATATGCCGATATTTGAACCGAGCTGCACAAAATCGACTTATGTTGGAGTGGTCTACTACGCTATGCCACCGTGATCGTTATTCCTAAAAGTCTCAGACTTTCCTCTCGAGGGTTACAGGGGAAACACTTATCAGTCTCCCAGGGGCCCAACATTAGCTTCATCTATAGGTTTAAGCGGCGATTTGGCTTTGGCTAGGGACACTGTCAAAGTTGCGGTATGATGATCTCAGATTGTACCATCTAGGTAAGAGTGCGTAGAAGAATTGGAAAGTACGGAACGTGTTCATGAGGAACTTTCATTGCACGGTGGTTACCTCCACGCTGCCACAAGAGGACCGCTGTATCGTAGGGCGGATCGCGACACCGTCTTCTAGCTCCATATAGCAGAAGGTCCTTCGGGAGGTCTATCTACACTCAAAAAAAAGATTTCTCGACATCTAAGGGCCCATGAAACTTCGAAGGTAACGCACTCCCTTGCGCAGACACCTACAGCAAATCGCTTAAGTTGCGGAGATTGCTAATCTAGCTGTGCTTAGGGGGCTATACAGAGGGGATAATGCGGCCAACGTTCACACTTTGAAAAGTACACGATGCGGCCGGAAGGAACTTAGTTTAGGATATTACGTTTTTGACGTAACTAAAACTGATTTTGGCGAACCGAATCCTGCGTATTACTGCAGTTTCGTAACAGCCCCTTAGTCTCGGAGCGATATGCGTGTACAATGCAAGGCTAGAATTGTGACTAATGTCCAAGTATGTCACATGATCGGTGTGTCAAAGGGCGGGCAACACGTACGGACTTTACAAACAGGGTATTGAGCGTTGATCCCTCAAGCTTGACCGACGGCACGTTTACGCGCATTAGCTAGACACATAATAGCGTCAACGACCCCCACACTCGAGTCATCAACGCCGAGAGAACAAGCAGTGTACAGCACGCGGACGGATGCGGCTGTCGGGGAAGGATCGGACTTCAAGTAGTGTCGTCTGATTTACGGATTTAGCTGCTCCCCGAAATTCGCTAGTGAGAAACAGCGAGAAATCGAGCTGATTAGTGAGGGGGCACGACGGGGTCCGTTGAGTGCACACAAAGGGTCCCCGTGCGTCGGTTTGCACGCGATACGTCTTAGACCCATAGTACAGGTGACCCTACGCAAGGCGTGCACTTTGTCGTCTTACCCCCCAGTTAGAAGGCCTCTACAGAAGACAGCTTCAAGTTGCACAACACGATGTTTCGACGCGTAATAAAACGAGCTATATTGGAATACAGACTCTGCACGTGCTACGTATACCAGGACAGGGGACCTAGATCCGTGTCAATTCCCGGCTTCTCTTTTCAGTGACGACCAGTTCTCCAAAGGGCGAGGGTTGGCCAACGAACACTTAGGTTAGTATGGGACACGCTTTCTGTTCTTCTCCGTTATGCCTCTCAGCGGTAGTCTCGATGGACTCGCCACAGACGCATCTGACTTTTCGGATAAATCACATGAACAGTGGAGAAATAGAATAAGCCGGGTTTCTGATAGTGGAATTAGAGTCTCCAACGAGCTAAAGTCTGTTGCGTTCCATTGGCCTCCCTTTGTGGTACCCACGGGCTGGTGTTCCCACGATAGCTCAGCAAGCCGATGGTGACTAAGCTTGGCATACCAATGACAAGGCCGTCATGAAAATCATCCCTGGGCGCCGAGGGAAGGAGCGCTCTCCATGAAATGAGAGCGTTGGGAAGACATTATGCGACGCTCTGCGCAAAATACGCATGAGGGGATACCCAACTGGTTCGGCCGGGCTAACTAAAGTCTTATAGTACGCTCCCGAAGTTAGCCTCCAGCTTGTTCGTCGCTTGCAGGAGCATTATTTCCAAGCTCCAATTTCTTAAGCGCGTCAAGAGCACTGATACGGTGCAGCGTAGTTGTTGACATCCCGAGCCCTTCATCAACAGGTAACTCCAGTTGAGTCGTACCGAGGGCATGTAATCCAAACATCAACCGAAATAAATAAACTTCCCCCAGTCGCTAGTGTCCATATGTAGCATCCACAAGTCCTGCGCGCCAATAAGAGCATAATGGCATGTCTACTAATCGGGATGAAGTGCAGAGGAACACTAAGATGATAAATTAACCCCGTCGAATACGATTTCGCTGGAACATCTTAGTTGAGGTCTAAATCTCTATAGGGTCCGGGAAGAGTACGAAAAAGGGGGCTGATCGGAGCACCTGAGAAAACCGTAAGCGGTTTCGGTGAAATGAGCGATGTTTGTGACTGTTGCTCCGTCGAATGCTCCGAGTAGAATACAACGCCCGTTTAGACACGCGTTGGGGAAAGTATAAAGGGCGATGTATCACCTGTCCGCTCGCAAAGTTGGACGACACTGTTGAATGAAAACTTGCACAGGCACGACTGACCGGGTCTATTACCGCGAGCGAAATACGCCGTGTCCTGCACTGCATTATGAAACGCACGGACAGACATCAGTTGACATACTGAACCACTGAGTAAGCAATTTGCATCCCATCTGGGATAAATCAACACCCAGTACGCTACTTACCAAGAGGCGTCAGACCGACAATAAGCCTCACGGGGCCTTAAGTATCGCTCTCTTAAAATTCACTACACCGCCAGCTAGGGTAGGACACTCATCCCCAGGCATGGGGGTAATCGCTCTGTCCAGGGGTGAACTCGAGTCACGATTCGATTGTACAGAATCGCGAGATACTTCCTATCAACTCCAAAGACCTAATCGGTTCAGTCAAAGCCATGTCTAACTGACACACAGGCAGTATGTGAGAGGGCCCGCGTCTGGACGCCGATCTTGGTGAGGCGGCTCATGCATTGGGCCACATGAAAGGACAGTTCAACCGGATAAAGAACCCGACCGTTCCTTAAACCGCTAACTCAACAGGGCGAGTCCAAACGTAGACAAGACCAAACCGCATCACCAGGTGAAAATTGGAAGCGTCTACTCGTATGTTAGGAACAAATGAGCTTCGTATGAACTCCGATCGATCAAATAACCTGCATCGTACTGGGGGTGCTGTAGGTTTGCCTAGAGGGTCAGACGAAAACCAAATGGCGATGCTCTGGTTCCGTAGCGGGCCCCTCTTGCGGATGACATTGCAGGGAGCGGATCCTGCGCGTTTATATAACAGCGATCCTTGCAGGGCATTGACAGAGCAAATCAATCAACTGAACCGAACGCGTGCCCACTCATTGAGTCGACTTCGTATGGTCCTTCGGTCACAGTACTTGACGCGGGAATGATAAGGCCCGTGTGCACTCCCCTAGGTCAACATCTGTATCTACCTAGGAAGTAGGACGATTGCAAATTGGCGCATCAAAATCCGATGTAACTCTTAGATCTCGAGGATCGAGCTCGACCGTCGCGAGTGGAAAATACAAATGCCTCAGTGGCCCTTGTTCGGCTCAGTATGAGCTCCTTGTTTCCGCGACCGCATCTAATGTGATCCAACATCTTACCTCCTCTGGAGACGGAGGCTACAGATAGATGAGTCTAATTTTCTTACAACTAATAAATCGAAAATACGGCTCATGGCGTTGAGCAAGCAAAGTACGACACGTCCGTAAAAGTCGGATTCCTCAGCAAGTGTCTTGACCATCACAGAGAATATTTCAGCAAGCTGGCCCATGTAAAAACTACTGACACTTTCGACCTGTCACACCAGAACTTACAGAAAAAACTCTCCTGAGGGAGCCCCTAACTCCGGAAGATCTTAATGATCGATCGTGCAACCTGGATGCCGTGTGAGTGTGGCTACCTCATTCCTACGGGGCTGTCCGCAGGTTCGGTCGCGTAGGTCTGGCTGGCCAGTGTACTTGGATGGAAAAAGATTTACCAGCTCAGGACGCGCCCCTTAGAGACCTGCAAATCCGTATCAAATTCACTCGTCGAAAAACTCGCCTTGTAATTTTTGTGATCACATTATATTTACGATGCTGTCCAAGGTAATAGGGTATATCCCAGTATAACTGGTACACGCTCGCACACGTGCCGAGTACCAACTCCCTCGCTTGGTTGATCTATCAGGGGTAGGGAAGCTTCGAGGGCCAGGCGTAGCTCCAAATCTCAAGAACGGTTCTAATCCTCAACCCGTAGGATCTCTCGTTCATACGTCGCCCTACGACTCTCCGAAAGTATGGGCACACTCGCCATAAATATCTAAAAACGATCTTCGCGCACGTGCAACGGTCTGATGGCCTTATGCTGTAATTCGGTTTCTGTGGGAATTCGGTAACGGATAGTCACTGAGCTAGTGCCGGTCGCTGCTGGTTTAGATGAATGCAGGAGATCCGCATCAGCGCCGAGCGTTGCGGGCGTCTCGGCTGTAAGTTGTGGCCAATGCGGGCGTACTGTTATACATACAGGGGAATTGGCGTCAAACCGTTTATGCGAAATGCTGTCTATGCCAGGTGAGCATTACACACGTGAGATCGAATCGAACGTAGGAAAGGTGGTCGTATGGGAAACGTCATGTTGATGAGACTTCCATTAACGGGCCGAAACTAACGTCTTAGCGTCGTTGGTAAAGTTCAGCTGGGATACTTTTGAGGTCGCTCATCTCCCCGCGTCACTTAGCATCTACTCTAGCCTTTCTAGAGGGGTTAGTACTCCTGGGAGCCGCTCTGCAGATATTCAATGAAAGCCCAATTGAGGCGGCATGTGGATTGTAATTCACCCTCCGCCTACAGTAGACATAGAGCTGTGCTCAAATAGGTTGAGAGGGGCGCCATTAACCATCGTGGTACGGACCTATTTAGAGCGAATATCTAACCAGCAATTTCTCTCAGAGGATACATCCTACTCAAGATGCTGTACAGGCATTGCCAAATTACCGTGATTCCAAACTTTTGGGAGGCTTTCCCTTTTCTAGGTGGATAGTCACGTCCATACTATCAAGCTAAGAGCCACGCTGCTTTCTACTCCTAAATTTCTTAAAGAACTCTCTGTCCTAAGTTTGCCACAACGACTGCTACGCGCCAAAAAAACCGACCAGCACACACGGTTATCGACCTTTGATAACTGGCCGCCGGACAGATCAAATGGACCCCAGTCAAGCCCGGTAACTTATGCGCAAGTTTGCACAGGGGAACGACACGGACTCTGCCAATTATATACTACATGTAACTCGCGCAAATTGGCAGCATACGTACGTCTTCGTATGTCCTGCACCCGCATGCCGTAACGGACCTCAATTCGGCACCTTGAAGTTGCGTCTTTCTTCCCTATCGCCATTCTGTAGACAATCAGACTTGGTATTAGGTCCCGCTATTCAAACCCCCAACCGATCGCGCAGAGTAACGATTCCTGCAATTATGCGGAATGGTCGCCCACGGGCGGATTGGGTTCGTTGCAGACATTCAGTAGTTCTTCTGCATGACGTCGGGCTAATAGCACGACTTCCTTCAATACCGCAATCATCGGTCACCCCTCAGACCACTCTTTCCCAATAGCAGGACAGAACCCCATCTGCATTGGACTCAGGTTACTCTAACCGAAAGTTCCTTTCTTTAGTGACAGCGAGATGGGTATGCGGAGGGCGTGCAATCACTGTGACAAATTCCTCGTTTTTACCTGAAACTTTCCTTTGTAGGCGTCTCGGAAGTAGATTTCACCAACGTGATACCAACAGAATGGGTCAGACGTGGTGTATTCCAGGGTGAGGAAACCTCCCCTGAACCGAGGCGACGAACCTTAGATTACGTGTTGAGATTTCAAATCGTTTCTAGTGTGCGCACAATTACCTTGGCAGACCTAACTCTCACGCATACATAGGACACCTCACCATAGCCATTTGCGATGTTCCCCCGTACTGCCCTAGACAAGCTATACGACACCCCCTACGACATGACTCGTAACCCGTTTCCATGTAGGCCAGTTTATCATGATACATGAGTAAACACAATGTATAGTGAGCTTGTTAGTACTATCTCAGTGGGTGACGACTGCTAAAGCTCTCATAAAAAGTCGGGCGAAAACGACACTCGCATCCGATGGTTTCCGGTCTTTCGGGCTGCCCATGAAGGGGCCCCTATAACCGACAGTTAGTGAAGCGAATAGTGACTGTGCGCCGCAAAACGCGCGTACAAAGCGTAACCCATAACCTGGTGGTCCTCACATGATTCCAGAAGTGACAAACCAACAAGAATAGTTTATTCTGCTTTGCCCCGGGCGGTCTGTTCTCACTTTGTCCATATGCCGGCCGCGTTGGTCTCAGAACAGTGAAGATCTTTTTGAAAGTAAACCCATTCCGGATTTCGTGTCTATCCCGATTCATACCTCCGTCGGGCACTTGTTAAGGGGGACGATCCGCATATTGTACTGTAAGCTTAGATCACTTCGCGAGAAATGATAGATCGCAGTACACTTCCGTCTATACCAATACTTTGACTGCTGCAACCATCTAACGGCCCTGCGGGCCATAGCCGAAAATTATCAATGGTTGGTCCTGCGTGGGCACCCAGTACAAGATTTCTTCTAACCCCTGAGCAGTAACTATTGACCCTAGGTACAAAAACATACAGGACCTTGATCGATGATCAGAGAAGGACACAGATCCGGATTATATGCCTCTATAGTAACTCCGGAATAAGCGAAGGAACCTGGCTGACCCCTGAACAATCAGAGCGGAGGGCGATCTGTAAACTATAGAAAGCGTTCAATTCAATCGAAGACAGGCCGTATCCCATTTTGTACAAGGGTTGCCGGGACAGAAAATAGCCGGTCGAAGTTCCGGCATTCCAAAAGCAGTTTAGCAACGATACAATCAAGCGAGAGAGACTATATAGACAGGTAGTCCGGTCGTGGTTATCCGATTTCGTAGACACGGTACGGCCAAGCTGGGAAACGAACGGTGTGTTTGGGCATAAGTCTGTTGAGTCAGAAGGTCGCGGTTTCTAGATCGGTGAGGTCTGTGAAAAGGAGGTGTGACATGCTTAGGCATATTAAGAGTCTTCGAACACAATTGTGTTGACACGTTGCATACCGCTCTCTACTGAACGCACAGGCCGTGAGCGTTATATATACTGAACCAGCGCATAGGCCGTACCTTCCCCCAATAGTTCTTTGGCGAGGGAGAACCTATGAACAGGCCGAGTTTCTCTTTAATTAGTCTCGCGTCTAAACTCGGCCAGTTCTAGGCATTTATATTTACCAGAATCGGCAAAAGGGAAAATTAACATAGCAAAAACACATGGGTTCTATCGTTAGTTATAGGCGTATTTAATCGAGCCGTGCACGGTTCTCATTGCTATAGGAGGGTACTGCTATGCGACAATTACCGACAACAGCTATAACTGCTTATTATCATAACTGAGCAGTCAGCTTCACGTACGTAAGAACAGAAAGCCTCTTACGGACATACCATCCCTTTCGGAAAGACGTGCATAAGCATAGTGCGCTGGGCCTGGTCCACTTAGCGTCTAGTCCTCTAATCATCACCATACACACTATAATACGCCTCCCGAGCAAGATGGAATACACTGGTGAGGCTAATGCGCCAGCGGACGAGAGGGATGGTTCGCCATCGTATTATGACTATGCCGGTAGATAGGCCCTGGCCGACTAGGATAAGCCGCAAAAAGCTACGATGCGAAACTCCGAGACGAGCCGAAAGCGTATAACAGACGACGTCCAGGAACTCATGTACCCCCTCACGGGTACGTGCATGATGCTCACCGCGATCATCCCTCCCTTTAGGGCTGCCATTTATTGTTTGTGAATTCAAATCACAGTACACCTTATTTTACAGAAAGCCAGGCACCTCAGATGTGGCTGTTGCGTCGACTAGTGCAGGTCTAGAATGTGGTGTTACGCTAGGAAGACCCCGTCGGTAACAACCACAATGTGGGGTAGGTACATTGGGGCGTACCGTAGTGAAGCTGCATGCGAACTCCTTTGTCGCGTGAATTCAAACCCTGCGGACCGTTTTTTGGGGTGTATCCATGTCGAGAAGCTGCTAGGCTTGGTCGTATAAGGATAGAGTCACCTCCAATCTCTGGTCTAGTTTGGAGCTTACCGCATTGTTCGAGTGGTCATGCTCCGGTCGTTCGTACGAATATATACAGGAAAGCTTCTCATCGCGTATCTACTTGCCTCGTCGTCATTGCGTGATTCCAATCGTGCTTTACGCGAAAAGCAAGCAGCCCTCTCGAAGGCTTAAGAGGGGGTACTGATACCCTGGGATCCAAGATTGTGCGCGTTCGGTTTCAGAAATCATCTTTGCCTGCTTGGGTAAATGGCAAACCTAAAGCGAATATAATCTGCGCGACACTTTCTCCGACACTTCGTATTGCACGACCAAAGGATCCTCGGTCCTTTATTCTTTTGACTGAGGAATGCCACTCGAGCTTGTTTCTACAGCGACACCTTGAAGAGTTCTGCAATATCACGGAGTGTTGTTATAGGATGCCACCCTGTCTCTAATCCACACCCCACCGCTTGTTTCTATCTCAATCATCTGTGGGTTGCTGCTGGAGCAGCTACTTCTGCATGGGCCGCGAACTCCACAGTCTTGGGTAGCCCAGGAACTGCAACGGAATAACGCACGCGTCGGTTCTCCAGCAGTGATTTTATAGTTATGACTGGAGGTTTTAAAGAGGACCGGGCTGAGCGGGCTATCGTTTGACTGCTATGCAAGGGCTTAATCGAATCTAGCTAGAGGTCACCTGGAAAAACTGCTCTTTGTAGACAAAATCCGCGTCGGCGTAAATTGATATGGGAGCCAATTTGGGTCAACTTCGACAAACTACAATCGGGACCTAACAGACGCAGCGTATCTGTGCACATAGCTTTAGACACGTTGTCTTGAGCATTAGATGCGCAACTAATTATTCAACCACTGAATTCCTAAATCGCCGAGAAGACTCCTGTGAGCAGTTACAAATGAGAGGCATCGCCCTGCTGAACCGCCGTGCAAAGTATTAGCAGACGATTCGCGACTCAACATCGGGGCGGCGCGGGAAAAGCTCCGCCAATGCTACCGGAATAGATTAACGCAGAGGCTGCAGTGACTATAGTTTCCGTGGAAGGTTTACGCGATTCGATGGCTGGCCACAGGACTGCCGACAAAACGGAGCCGCATTCCGCATGCTACCAGGCATAATAGTGAAACGTCGATTTTTCTACATCCGGACCTGCTTTCGTTGAACCTCAGCCTTCGCAGGGCAGAAGTTCTGAGAAAAGCTAAAATGAGGTGTTTGACTAGCCTTTTGTGTAAGTGCGTGAGAGTTTTTATCCGTAACTGAGAGCGATACACGGCCATACCTAAACTAGAGGAGCGCCTTACCGTTTTACGTGCAGAGCGACAAACCAATTAGATCGGTGGATATCCAATTCATTGACTGCGTCGTCCAGTACAGTCAAGAGACGTGAATACCGTTCGAATTTCGTGCATAACTCCTGGGAGAAGAACTTACACGATAGCCATTCGGGTGGCCACTATAAGTTTGATAGCTGAGTTCAGTCCTGCCACACTAGGGGGTCGCTAACGAGCGACCTGCTACTGCGCTTGTCCGGCTGAACTTGTGGTCTGCGATCGCTCTTGCTCGTACCCCTACGGTTCGGTAGGAGCTTTGGGCTAGGTAGTACAGATGACTTATGCGAGCCCTCAAGCACATAGAGAAGGATGTTCGTAATCCACATAACTACTATACCTTCTAAGGGATCCCATCTTATCTCCCGGCGTAATGTTATCGTCTTGGCAAAAGTTCGACCGTGACTAAAAGAGACTCGATCGGTTTCAGCGTTTTGAGACATCCTCTTAGTGAGATGGTGACTCCACGAGGTAACGAAGACCCAGGGTTCTATCGTCCGTAGCGCTGGTACCGTTATTCACTTCAGTCTTCTATCGTGATTCTTATGTAAGCTAGTTAACCTGTTCAATTGGTAGAGCGCGCGCGAATCCTACGTATAAACGTTAACGTGGCGACATGTCAGGGCTGATTGCCATCGGCTTCCGCGGTTGCTACTCGGCCCACACGTCCTTTCGCGACGGATTATACAAAGGACGATCTCGCGCACGTGTATTCCGGAGGTAGTGCACCCAAGGAGGTATAAGTTTTATCAATGAGTGGGAATGCGGACTGGTGCACTAGGTTGCGGGTGGTGGTACACAAGAGTATGGTCCCTGTGGCTAGTACATTTACAGAGACAGCCTCAGGCGGGGGTCCCTCTCGCCTGTATGGAGCAGACTAACTCGGATTATCCTGCCAAGAGGCCCAGACGTGTGCGTTTTCAAACACTTAATATCCGGAGAACCGGCCAGTGCTAGTACCGGAACAGACACTGCACACATTGGAGGGGAGTACCAATAGAAACAATTCGCGTAAAGTGCCAAGTCAGGTCCACTCGAGCGCTCCAGAGACCAAGGTCATGCTTCGATTGGCTATTCATTGCCTTCTCCCACTCGTTACCTTGACTAGATCACGCTGTAACGGACGATTATATCGCGTTGTGTATCGAGTGCAACGGTTCAGTCCACCCGGAATACCATTTTACTCGGCGCCATGGGACATCCGGGGGCGAGCTGAGACGACTAAATTTCTAACCGGCCGCGCTCCAGAAAAAGGTCCGATCAGAAGACGGTTCTCCTCTCGACTGCCTTGATCTGGCCAAATCCGTTCACCTCTCAGCATTATAGGGGCACAAAGGACCTGTCTCTCAAACTACATCCGCCATGTTTGATGGCCAACTACCAACGTAAAAAGAGGTTCTCTCGAGTCGGCTCATACTTTGGTCGAACACCCACACCTTTGTTAGAAACTTGCATGCCACTACCTTCTGTCATCTAGCAAGAAACTACTGTCCAGCGAGCGCAGGCCCAATGCGAAGACCAGGATCTTTACCGCTATGGCCTGTCGCGGCGTCGTCTCAAGCAAAGCGTTAGTCTGCACTGGCTACGTAACTAAAGTGCGTGGAACGCGCCACCTCGGACGGGTTTTAGTGCTGGCCACGGAAGCATCTGGCATTGGTCGTGCCCATGCAATACGCGTAATTGAATCCATAAAACACGAACTTTTAAGCAGCGTACGGAACCTTTTTTCAGTCTCCCCCAATCCCGATTCTGTGGTACGGATGCCCGGGGGGGCGGTGTACCGTGCAGGCAGCAGGATAATGGGCAAATAAGAGAGCTACCATGCCGAGAGACCTAGCCTCCGACGTTATTTCGGAAGAATCGGATCATTGGACTGAGTAGAGCCCGTTGAATGGCTTGGCGTACGATCTGCCAATTGCGTAATCCTGCATTTCATGATTGAAAGCATCCCCTAAAACTTTGCTATCGGAGACTGCTAGACTACGTTATGGAGAGGAAGCTGACGGCGGTGCTAGGTCCTACGTCATAATATTGCCTGGATTACTGTTTAAGGATGGTCACTCCTATTGTAGCTCGTTCCTTTCGCACAGACCACGATCGGAGTATAGTATGCGGGAATGAAGATATATAAGTGCCTCTCTTGCTCTAATGGGACCGTTCATGCTACGTGAGTGAGTTTTATTAAGCCATACGAAATGCCGTGTGATCGTGCATAAGCTAGGAGTCTCGTGGAGCGCCTCCATGTCCGTAGGTGGGTACGATCTTTTCCTGTTTACTTAATCTATAACCACACCTGGTGCCACTCCTGAATAGATAACGTTTGTGTACCAGACGGCGCGCCCTTTGGCATGTCTTTCGGCCCCGAAAGAGCGGCTGGTTCGCTCTTGACTGGTGAAGTGGGAAATTGTGTTAAGAAGTGCCACGAGCTCCGTCTTTTCAATGCCCGTACGTGCTGTTGACGCGTTCAGACCCGGACGCTTTGTTGTTATACAGTGCTTCGTCCTAGGCCTCACTGTCCCGCGAGATAATCTTTACTGTGTGACTCAACCTTCGACTCGCCCTCTCATCCTTCCACATACTTGCACCTCAAACATCCTGATGTTACAGGCTAAAGAGAACTTGCTTCGCGTAACTCCGCACGCAACTGGTATCTACTTCGTGGGCTCGGCGGTGTCGCTTTTGAACCCCCCCCTCGCATGGCCCAGAAACCAGCCACCGCCCTTTACCCCACTAACCGATTTCTGGTAACTTCACCTGAAAAATACTCATACTATTCACCCAACACCTACCGGGTAATAACCTCGGGAGTAATCGCGTATCTGTACCTTGCAGGCAAATCAAGAACCTGCAAGAGACATGAGTACCAGCAGTTTCGCGCTGCAGGTCGGCCCAATTACGATCACATTGTCAAACTCCCCCGGTTTAATTACTCGGAGTGCTTATTAACCCTAATGTCGACCGCTGGCGTAGCTCTGCTTGACTAGAGCAGAAAGGCACCTACTACGCCAGATGAACCCGATCTCAATGCTTTCACCAAATCCTCCGTGATCATGTCCACAGGAAGGGCAAGGCCTTAGTCCAAGGCTATGAAGGGGCTATCAAAAAACCCTTACACGACAGCTCCGGCAAACATGCGGCCCAGGACGTAAGCCTGTACTAACAAGTCCCGTGAGCGGTCTCGTTGGTTGGTTGTATGTGTGTCGCCACGCGTACTGCGTGGAGCGGTCGATATGACATAAGCAGCAGGGACCGTTAAAATAAGCCTCGAGTTGGGGTTCCTCCCATTCCTGATTTTGACCTCGTAGTTTATCAGGTTATCATTACTTAGCTTATACGCCCACGAGTACGGAGTAAGTCGCCATGGCTATCCTTATCGTTTACCTACCCGTCCTCCGGTTCACACTACGGGATGGGACGCCAGGAAACACATATGGTGCAGCTGTGCTCTAGTAGGGTTCTGAACGGATTTCATGGGAGTTAGACATTGGGGATCACATGTCCTGTACAGACATGATAACGCTCCAAGCTGTGTGTAACAGGTGCGACTTAAAGCTATGGATCTTAGAGTTCGGTTGCCATGCTATTAGGGGTTCACATGTCTTAAATCTAGGGGATCCTAATTTCAAAACAGGACGTAAATGCTGTAAAGTGGTATAATCCTTCTCATACAAGATGTGGGAAAAAGGCCGATCCAGTTCCACCCTCGGATCTGCGTGAATTTAGAATTATGTATGTAGCAAATCAAGCTCCAGGCCACGCCCATGTCGACAGCTGAGGACGATGCCCGGCTAACCATTTAGGTGATCTCCGTTGAAGCGATCCGAAAAATAGGTGGGTCGGTTCCGGGCGAGACGAGTGATTCAATTCCCGTTAAAAAGTTCCTCGCGGTACGAGCCGGTCGCTCAGGCCCATGAAAGCTAAGACGGCACGTCGCGGTAAACTCGAATGGCTGTCTCGGAAAATACTAGAACCATTCCCAATGCTGCCTAGTGTTATACATGCTCACCTGGTCCTTAGATACAAGGTACCACAGCCGCATGGTGCAAGAGGAGCAGCCTCGTGGTGCTCATCACCGCAATCTTCGTATCGTCATATTCCCGTCGTGAAGGAAAGCGACTCGACTACCTAACCCTGTGCTCCGAGCAGCAACTTTTTTGCATTGCGTCAGGCATCTCTCCGACGAGAAGCCGGAGCGTAAGGGAAGCCATTACGGGCATGTGAGGCAGTTATTTCTGACTACACGATAGCGTCCATAGGCAAGTAGACACTGGCTTATCTCGATATGGGGTATAGCGAAGCTACCATCCATGGAGTCCTCAGTTAGGTCCCGCTACACTCGACTACCGACAGGAGCTAGCTCGTGTCTATACCCTGAACGGGAGCCGTCTTATGCCCAAGAATATATCCGTTATAACCGGCAGCCACGTGAATTACAGGACCAATGAGACTTATTCGTAGAACAACCGTCTGGTAGTACCCCTATGTATTGGCAGTGACAGGTCAACATATCTAGACATCTTGAGGAAGGGATCAAGAGGAGAGCAAAGTGCGTTCGATCTACTGTCCAATACATTCCACGTCACGAAGTGGACAATGGGTACGGACACCTTGGGACTCAAGCGGGCAACTATTCCATTCTATACATGATCGCAACTATTGTCAGTCTCGCACTCGAGGGTACGAACTCGGCGGGGAAGGGCTGTCAGTGCCGCATTTGCACTCACTTATCCCCGCCACCGTTAACAGGGTAACGTTTGCAAAATTGGTGAGTAAATCGGTCGATTGCATATCAGACGTGCGTGGCAGAATATAAGCCGATAGCTTCGACTATTGATTCCTCATCGTCCAGGGTTGTTGACTGGGGAGAGCTCATATCATGGGGCACCTACGTTGCTGGAACTGTTGGATACGCACTATAAACCTCATAGAGCTCTGCCCACGTCATAAGCCTTAAGCATGAAGCTCGCGTTTTGTGGCAGCCCAGGGTAACAAGCACATATGGTTGCCCGCGATACCTGAGATAGATGTTATCGCTATAACTATAGCTCCTATCAAGTCATTAATATCTATGCTACAGAAGAAAAGGTAAAGCATACTACCTCACTTAAACTACCTAGTCTTTGAAATGCCACTCCTGTCAAGGGGAGGTGTTACTCCACGCAGTATAGACTCCAGCATGATGGACGCCGGGAAACGCCTCGTCGTCTCTTAACGATAACGTTATTAGAAAGGGGACAGACGTTACGTTCGTGACGTGTTAGATAATGCGTGAGAAATTGTGTTCATCGTCAAAGTTAGTATATCGTATATCCCTGTTACCATTGCGTTTTTTAGTGGGAGGCTTAGCCCAGCCGTGTGACCACCGGCAGGTACATAACAAGTGTGACTCGGCGTGTGCATACACTGGCATCAGCTGGCTGACTTGCTCCATGACGAGCCACCCCTGAAACCTAGCAACTGACCTCATGCGGAATTTACGGGGTATTGAGTTCTTCACCCGAAGCTGCTGGTTAGTGTGTCCGATATGCGAGCTGCGAGGTCATTCTTGCTGAAACTAATATGCTTCGAACTTAATCGCTTTGAGTAGCTGGATGATTTGCTCATGCCGAGATGCGCGTTGATCGTTGTCGGCTCAGGTTTTCCCTTTACAACATCTTCTGGGATGAATCTGGAACACTCGCACGGTTCATACTAGAAATTCCTCGCAAGGAGAGAGGGCCTCCGTTCGGAAGAGTCCGATCGTTAGACTATGTTGTTCAGGTCGTTCCTGCATTGAAGAAAACCTACGAACCGGAAGGGCTACCCTCCTTCGTCTCATAGGTGCCTAAACCGTCCGGATTGCACTAGGCACGATACTGCGCATTTTACTTCTGCCTGGGTGCTATAGGAAGTGCCCGGTAGAGATCACGCCGAAGATTGATGTAATCAATAAGGCTGCTGAAATCTGTACAGACGGCCGTCAGGACATCAGGGGAAAACTCTCGTGAGTGAGTACAAAATTAAATGGCCCTGGGGAGACTGAACATTTAGACTAACGAAGTCACGGTCGTCGCGTCATAAGAAATTCGAACAGTGGCCTGGGCGACTAGGATCTCGGTAGCGATTAACACGGTATCGAATCGAACGTAACTATTGATCGGTAAATCCCCCGGGCTCTAGGGGTCGGGGGTATACTTTCCTTTTTAATAGGCCCGACCCCCGAAACTGGCTCATCGCATATCCCGTTTGCAATGGAAGCGGTAGTTTTGTATAATTACGATTCGTTATAAAGTACATGCCACTTCGAGCACCGTCATGTGATCACGCCAGAGCACTCCGTTTGGCTGTGGGCCGTGGCACCACCGTAGTTCATATTCATTGCGAGCTCTTAGAGTTCATGTCCTCACCGTAGACCGGAGCAGAACCGCTCACCACGAACGCTAGAAGGCGGCTGTGCTCGGCCAACTGAACCACCAGCAGGGCAGACGATGGTTAGTATGGACCTGCTGGTTATCGGTTTTCAACGGGCTGTCGCTAATATTGTGGCTACCTCGATTAAGCGCCGCCGCAGCATTCGCGGGAGGAAGACCAATAGTCCGTACCTATTGACGCTCCCCGTGTATCCGAAGACGCCAGGGACCCTCTTCTGGTCGCCGACCGAAAGAAAGAAATTACTGGGATTGGTAGCGTCCCGTGGTTGAGGCATCGGCAGGCGGGATCTTCTAGTTAGAACTAGAATTCGGTACCTGCGCCCTCATCATCTTTACCATTCCCGATGACCCCTTAGGCCGAGTCGAGGACGTTCCCTAAGTCAGATTAGCTCTAGCCTGAGAAGCTCTTTACGGGACCAACTACTTGAGTGGATCGTGCCTTTCTATATCCTTGTCGCTTATGAGTTTCGGGACCTCGAGTTTTTCTGCAACCACTTGGCTACGTTAGGACTGTTAAATTGGCCACTTAAGTCCCAGAGCGATGTAGACATAATAATTATCGCCTCTTTTCGAGATATAAAAAGTATTCTGTTCTAACATCGTAACATAATTACGTTGCGTCTGCTCCAGGACGGAGATGGATTACGCGGCTTGCCTTGGCGAATAAACCTGTCCGAAAGCTCCGCGCGTCGAATAGTAGCAGTCATAGTGCACCGTGGGTGATCTGGTACCGCAAACATAGGGGTTCCCTACTCGACTAGACATAGAGGAAAGTACCGACATACAGAAATTACTGGGCCCGGGATGGCTTCCTGATCTACAACGTTAGAAGGATCCTGTGCCCCCGCGGGGAATCCTGTTACGGACTCACGCGCTCAGACACTTGCGATTAAGCTGGAAACCTTCGCTTCGCCCCAATGCGAGTCCTGACTGGGCGGTACCACGACCGAAATGCGTTACGCGTGTGCGTAGGACGTGTCGCTTCCAAAATCGGAGGCATTTCCCAAGGTTCCTGAGGGGGGGTGCTGAGGGAAGCTAAGCAGTAGACGACGCGTGTTACGCGAGCGGATTACTTCCTGGAGTTCTTCGATTCTTCACAGATTCGATAATAGTCCAGCAGCCGATATGCTTAACCTGGAGTTGAGCATCTCGCTACAGCGATGTCTCTAGCCCATTTTCTCGTGTGCTTGAGTCTTCTCACACGCAAACACAGTTTCCTTCTACAGATAGTTGGCTATTTTCGGACCGGTGTGAGTGTCATGAGCCAAGGGCTCGCGCCCAGACCATGAAGTCGGAGAAGTCTGGTCAGGTCCCGCCCGATACGTGCTATGTTCAAGCAATTTGGCTAGCTCTTAGCGCCCCGAGTGAGTATACATTCTTTGACGCTGGGCCTCTGGCGACGCCAACGAGGGTCCAATATGGCTACCGTAAACTGCACCACGGGGTGGAGGTCAAAGATATCGGCCGCCTATAATGTTGCATCACCAACTCAAGATATAACTGCTACGAGCTACTGTGTCCCCCAGTAAATAAGCGACGGCTCGGCACAATTTGTGGGCAACCGAAGTGGCATTCTCTCACGGATTTACGATAATAAGAGCGACAGGCGAGTGCCTACTTAGGCTATCAATTTTAGACAAAGATACGTGGGTGGAGTAGTCTCTCGAAACCGGGAACCTATCGTATAAAGCTATTGACTAATTGACCTACTGCGAAGGTGACAGCAGCCGCCATCTATAAGTCCGCCCAGCAGTGATGTTTGCGCACTATTGACGGACGCACTCTTTCAATCTGCGAGAGACCAGCCCCCATGCATGGCGAGTGACCGACACGAGGATGGATTAACTCCTCGGCTGTATCTTTTGCCTGATGCGCATTCGACACGAAAGAGAGCTTTACTAGCAAAGGATCACCGTCTCAGTGTGTGAAGCCAAGTTCTTGCCTATGGAAAGATCGCGGTAGACAGCTTCTTGGCTATTACGAGGTGTTGCCCCGGCACGAGCCTACAGTCCTAGCCAGAGGCCATCCCTCAGGGTCACAAATGTGCGTCTCGCCGGGAGGGTTCATTAGAGTCCTGTGCCAACGTAAGAGTAAGACTTATCCGGCGAACTTTGTGTGAGTCTTATGGAAACACCATCGACGTTTATTATGTATATGCACGTGGCCTGACCTAGGAGCGTAGCGACATAATGGGCGGTGAGTTACCGCTCACGGTACTATTGCTGACTACAATAGTCATCGTAGAGTGATCAGTCCGAGGCGTATCACGTAAGTTAGATAGGTAAACGACATTAGGGCTACGATCCGGCCGAGGAGATAACTATGACTAAAGTCCTCCGCATAATTCAAGTCTCAACTTAATGATCGGACAAATACGTGGATTTTACTTCCGTTCGCGCGAAACCGTCGGGAACTCATCGTTACCCTGCGAGTTCCCGCCCCTGCGATACATGGAAATCCTGGAACCGTTCTACCACAGTAGAGTATGAAGTAACCGCATCGGTCCCGTGATCAGTCGCCAAACGAATTAGGAGTGGGTTTTTAACGATGCCACCTACGGCACTGCGAGGTGAAGGGGCCGCCCAACTATAGAGAAGAGGAAAGGTTTGACTGAAGGGCGTCCTGATAGCCGGCATATTGTTTAGGGGCAGTCGAGGGACCAGTCCAGCGTTCCAGCGGCACAGAAGGCTTGTAACATGTTAATTCCTGGCGAAAACTGTTACACGACAGCGGTGTAGTATCTAGTGTGGATGATATTGGTGTATATTCGAGTTTGGAGATTATCTATATTACAAGCAACCACAGGGTATCCATGGCAGGACACAACTTGCCTTCTAGTGCTATGTTATATGATTCGCCAGAGGTGCGGTCCTCCTTCAATGCATATGGGGCGATATTGTTTAGTTTAGGCTCGGTAGTAGTATTGTGTGATCTGAGGGCACACTGAGACTTTCATGCTGAACGGTCGTGACTGGCGAGATGAAAGTTAGTGTTTGAGCGGGGACCCGGCGAGATCTAAGATGCTAATGACACTGTGGTCCCGCGCCCGTAAAGAGTACCCCTATTGACCTACGGCCATAAGGATTGCCGTTGAGGTAAGGGTCCATAGGTCTCGAGCGGCACTTACCCTGGCTAGGCTGATGCTTTATCCTATATCCTCTGTGGATGTCACATGACGTTCGTTACTACTTATGACTTGCTTCCTTGAGGGTAGTGGAGTTGATTCGGGCACGTGATGCGCGCGCAGGCGGGCCACAGCAACCACGTCACCTCATCACAATGCCTCTAGACCGTTTTCCCATCATAGTTCAATATACACAATTGGCATGCAAGTCCGCACCTCTGTAGTACGATCGCAAGGGGGGTCCCATTTAGACGCCGCATTATACTAAGCTCATACTTCAGTGATTGATTCGTGGTCCCCACTCGGGACAACGTTTCTTCCCCACGCGAAAGTCTAAGCGGCTTTTTGTTTTCTCATCTAAAGATAGCTCCCATTATCAACAGAGACTGATCCTGCTGTTTGTGTTGTGTTAGACGGGGAAATGCAGTAACGTAGCGATCCTTATGGAATTATAACAGCAGTTAGTCCACCAATGAGCATTAGACCCTACGTAGGTCAACCTGAGATGGGTGATGGTTACCTATTCCTGCACAACAATTCTGTTCTGCACCGCATTCGCATTCTATGACGATTCTAAGGTGTGACCTCTAAAATGTTCTCCCGGGGAGGCTTATCACCGGAATAGTTAGCCTGACCCCCCACAATAGATGAATGGTGAGGATTAACTTTACTGCGATTAGAGTCGCATTGTTTTCCAGGCAATAGCGGCGGACCCCTTACTCCACTCAAGCAGGAGCTCGAGCCATGCGCTTCTCTGCATTCCACGCTAACCGCTGTCGATCTCTGAGAATGGTGCAGTATGCGACTCCAGTCCCTAGATAGTCGCTAAACCAGTGATGAACTCAGCTTAGATGGGTTTTGACTTCATGCAATAAACAAATGCATCAAACGGTGTGACTCGGTCATGATTGCCAGAGAATCGTGGAGGCAAATAATTACAGGAGCCGCACCCGAATTTCGGCAATGCTTCTGTCACAAGAATGGAAACATGACCTGTTTACAGTTATTCGCCTTACTGCCTCGTTCGATTGTACCTGCTTCTGAATGATACACGAGTTCGCTAACCGCGTTTGTTTTCAAGTAGAACGAACGATTGGTCTGTAAGCACAACCACTTCGCTTTGCACATGGCTCACGATGTCTCGTCCGCGTCGGTACGCGCGGTTGCCAGGCCAGTGCCAATCTATTACCCGTTGCCATTTTGGTGTCACTCACGTGTATAATTGCCATGGGATTCACGCCTGCGATACTAGACATCCTAAATTTTGAACTCAACTCATGAGGAGCATTTGCGTAACAGCGTTTCAGTACGCCCTTTTGTGCTTTTAATAGGCGCGTCGCCCATATCACGAGGTATCGGCTTGGGTATCGTCATGGCTCGAGGTGAGGCATCCTATCTGGCCAAGAAACTCAACGAAGACGGAGGCTGGTTTTATCTGTTTCTCTCTAACAGGCCCAGCGCGCTAGCCAAGGCCTCCGTCCCCAGCCATAATCCAAAGGCCTATGTTTATACTGTTGGTCTCTCTATAATTCTCGCTATTCGTATCTTGAGTAATTATTACCGGAGTATTGCTCGCTCAGAAGCCTATTATCTATCCCGTGTTGACAGTGCCACTTCTGTCCTCACTCTGGAGTGGCTTACCATGGAGAGATTGAAACAAATCTGGCTACCCTAGCAGATTATTACTAGTAGCTTAGCGAAGCATCGCGGTGAGGACGAGAGCATTCCGTGTCGCTACCAGGCCTCCCCGTCAGCACGACCTTGGAACGATAAAGCAATTAAATAATGAAGGTGCAAACGTGGATAGAATGAGAGGCCCACGCACTCATGAAAAGGGTCCACTTCGCTTGTCATATGATTTTCGCCCCCTATTTGAGTACACACCACTACTAAGGCCTAAAACCAACCGTACCGCTGGGACGTTTCACGGGACTCATACGGTTGTTGTTAAGAGGCCGTCATAAAAGGATGGCCGGCGATAATAGCTGCACTTGTGTCAACATGTATGTTAACAGTCACGCCGCTGGATAGTTAAAGTTGCCAGTTTAGATTTCGCCCCGTGATCCCATCTCTAACTCCCATCGGAGTTGCCGGATAATCCGGGTAGTCCAAAGCTATGTACATGCTGGATATGAATTAACCGCGATTTCACCTAGAGCTCGAGAGCTGTGGAGATCTGTATCGGAGCGCTGAAACCATTCTTACAATCATTGGAGACAGACATAGGGCATCCAGTCATAACAACACGTTTAATCACCATGACACTTTATCACTTGTCGGCGGGTGCAGCCCACCACGCGCCAAAAGGAGTCATCACAGTGTACTGTGGGTGTGGCGTAAGGTTAACCCCAGTTCAAAACGTGAAGAGACCAGGGGTCTTGCACGTGTAAGGATTTTCCGGTTTCTCATAGGTACTGTTTCCCATATAGGTTTAAACCGCTGACCGACGAAGGCTCGGGGCCCAACGTTACTCCATTGAAATACATTCGAGAGAATGAGATCGACGTACCCCTCTAAACTGGCTAATCTTATGCCCCAATGAAAGATCCCCCGGAATGACTATATTGATAGGTGGCCCGGCGGTAGTGTCAAGTGCCAAAGAGACCACTTAGGGCACAGACGAGATCCTGAAGTGGGTCAACCTCGACACCTTAGCAGAGGACGACGAGCGAGTGCGCCAGCCCTGAGCGCGCCTTCATCTTTGACTATTGATGGCGGCGACGTGTTTATCGGAGCATGCATTACATATGGGAGAGGTCCCGAGACGACGCAGTAACCAATTTAAGAGGCAAAACAAGATGACCGCCTAAGGATCTTACTTGGAGCACATCATCCCATGGTTAGGTGGCCAGAGAATAGGAGGTTTAACCCTGGACCGAGACGATCATATACAGCGCTTTAACTACCACGTTTCACGCGACTTAATAACCATTCTACGGGACCTATTAGGAGGCTATAGCGAGACAAACATGTTTTTTTGTCCTCTCCATCTGACTTGTTAGAGGGTAGACTTAGCGAGCTTACGAAGAAAAGCCGTCACCCTCCAACTGAAGCCGAATGTCCCTAGCCGTGAAGAAGAAGTAGAAACTTATGCGTTCTCCCTTAAGTAGCTGATCATTCGATTTGATCGGGTTGGACGATGTTCTAGCGCAAAAAGCAAGACTAGGGTTAAAATATTGCCGCTCCGGAATGCCGTTGATGCCTCTGCCGCACGATGCCCCTTGAGGCCCTACCAGCATTAGCACACTTGCTTTCCCTTTTGCGAGAACACGTAAAGCTAGACAGAATACTATCGACTGGGCGAATAGGCAGGGGAAATTTCGACGAGTCGGTAAAGAACTAGGGGGACTGAAATTTGTATATATCCCGTGCTTCTAAACCGGTTACTCGGTGAATGTAGTCGGTCTCCTAGGCAGTATTATAACACAGCGGTATATCTGGTCCATTAACCGAAGACTGTAGTAGGCGCCCGTGTTTAGGTACAGAGTCGGTGTGGGTAATCAGATACCTATACTGGGGTGGATTCCATCCCTTGCAGAAGTATTTAGGGTAAATGTAGAGGTGCTGTGTAGTCCTTAATCTTATGACCCTGCCTATGAAATGCTGTCAAATCCTCCGATACGTCTCTAAGGACTCGTACGCAATCCGGCATCTTGAAGCAACGCCTTCCGTATCGGCTTCAACGTAGCCATATGAGGCCTGTCTATAACGTATTCATGCCCCACGATTGGTTCAAGCGGGCCTTTTGATGCCGGTAGATAGTATCAACCCGTACATCTGACAAAAAAATTGTCACACCGGCCCAAAGCGACTGTAATGGACCCTGCTTATCGTGGTTTCAGTGCGGCAGAGATTTCGATTTGTCGTTGCTTTATACCTACAAACCACTGGAGCGTCCTACTACGGTCATCTTTAGTCGGTAGACTACTAAGTTAGATGACTTAAGTTAGGAATAGAGTGTCTCAGCATACATTGTGTGGACTACGTAAGCGCAAGAATAACTTAACAATAAAATGAACGAGCTCGTATCAGTGCGAGCGAACTGGGAGCACTGGCACCGTTCTGATATGGTCCAGTATTTGTACGAGCGTTGTCTAACAGCGATAGGGCTGGAGTACGAGACTGAACCGATCTTCGGTATCGTGCTTCTCACATCCACAGCGAAAACTGAGAGTTGCATCTTGGTGAATGCAGTCACCGGGAGTGACATCCTGCAGAAAATTACCGCTGTACCATCGCTTAACGCCGAGCCCTATACTTATTTACGTTGATAACGTGAGTGGAGAAGCAATCTGAAACGTAACTCCCAAAAACCCCTCATTGAGAATTCAGGCGACCCAAGACCGCCAACTTTCACCCATCTTATCTGATGTCACTTTAAACGAGCGACCTTGACCGAATGAGGGGCTTGCCACCACCTCCAACTCCAAGTCGGAGTTCGCTCGCACAGTGTTCTTCAAGTCGTGATGTTGATCTGTCTGGGGCCAATTATGCTAAATACTGTCGGTCGCCGTTGCTTTAATAAGCCGAAACACCAGCTTAAAAAAAAGCGACGGGCCTAGCAGCGATCAAGCGCGTACCTCGATAGGCTTGTGCATGCCTTCCAATGTTGAGGATCGAGGTCGGCAAATTACAGGCTTTATGGATCATTGTAATTCAAATCAGGTTGGTGAAAACCGTTACCTCTAGGCTCGTCAATGCGATCGGGGTCCAATGGCACGGGACATATAAGGGGGCTATGGGTGTGATTACGCACAAATATTGATTGAAATGGACAGTTTGGGTCATGCGCGCTCACCATGTGCACTGTGGGTAGACGCAGTAAGTCGAATTCCTTAGTTTCCGGCCGGTCCTGTGTCTAGAACACAGATGCAGCGTCTCAAACCGCTACACTAGCAGTGTTCGTAGGTAGACGTTCGACGACTTCACCAGTGCTCACGATAGCCACCGGGGTACACACCTTCACCTCAGGTGTTTAATTGGCAGCCAACCTCGGCTCTGTTCCCTGCTGGTCATGCTGAACTAGCCTAGCACTCCTGGACGAGAAGAGACTTGCGGCCGTCTCCTACACATGTCTACTTAGCAGGGTAACTGCCCATAATGGCCTCCTATTCCTGGAGGTCCATGGGTATACGCTTGGAACCACGCCTTTGTGAATTATGCGAAAGGGCACTACGCAATATCAGTGGGAACAAGTACGGCAATTCCGAATTATGCGATATTCAAGGCCCTCATCAGTTGCTAAACTGGGTACCGGTACGCGCACTCATCGGGAGACTCAGGTAGCGGGTCGCAGCTACCCACCGGTCCGTGAGTCCCAATACACAAACTTCCATCGGGCTCCCCGAAATAGTTGGCCGTCGCACTTTACTACCCCGCTGCGCATCTGAGCAGGATTGTTAGTTTGTTGGCATCAGGTAGTCGTTAGCTCCGCAGTAAACCATCATACCGTACAGAGTGAACCTGTTTATGTGGATTGTTTTACCTGCGATTAACGTTACTAAGAGAGGCGTGGTGTGCCAACTCAGCGAAACTTTAGGGCTGCGGAGTCAAGTTTTCGTGATTTACAGCCACTTCACGCGATGGTCTACTGTCACACTGAAATTACGCTCCAGAGAATGCAGTTAATGTAGGAGGAGGTCTTGCTTTACACTAGCCGACTAACAGGACTCTCGTATATCGATGTGCCATGTGCCACCTTGCCCCCCGTTACCTGTATGCATGGCATCTATGGATGCTGCTCTAGATATTGTGGTAATCTGCGGGCCCAGCACGCCGCACGACCTCCGCCCATTGATAGTGCATCAGGTGGTGCCTTTAAACCTCGATGTACCCGGGGTCGTCTACCTCAGGGCTTCACTAATGTGAGTACACATACAATCAAGCCCCACCACCGAATTTGTTGATATGCTCGACGAAGTTGCTTCAGATGACCGTGAGCAGTCGAATCTGCCCCGTACTCGGAATTGTGACAACTTAGTTGATACTTCGCTCGTGATGGTAGATGGTACGTACGCAATTTAGTAATTGTGAATCCTGGAGTTAGGACAAGTCTGCAAATCACTGCCCGCGAAGAAGTGTCGCAGCGCGAGTGTGTTCTCCGCGGGATAAGCATTGTATCCAGGAGCTTTGACGTTTAAACGCAATGACCCCAGTGTCGTCAGCTCGGCGTGCTTTCACGTATCAGCAAGAGGCTTCAATCTCCCTGCGGCTTAGGCCCAAGAAACCCGAGCACTATTGGGATTGTGCAGCGGCCCGCTCGGGATTTCACTCTTCATGTCCTGTTGTGTGTGTGGTATAGCGGCGAGTTATCAATATATATCGCTCCGAAGAACGGCAAACGATGAATAACGTACAACCGAATAGTGTTCGCTTTATCCCTCAGCTTAACTTGCAGGTGAACAGAGTTCCTCTCAGTCACAAGGTCTACGATACTTACAGTGGGGAATAGCGCGTTGATACCATATGTAAGTTCAGCCCCAGCCGGGGCCGCCGGACCCTCCGATTCGAGTCTGTATTCAGTGAGGGCGTAACGAAGTTCTGGCCGAGAAATCAAGCGGGTGAACGAGCGCTTGCGCGCGTCGAATTGTCAAGGAGAGAGCAAAAACGCTGTATTTAGCCCAATCCCGCAGCTCCTGCAGCGGGAATCTGGAGAGAGTTTGGCAGGAGGCCTTTCGAGTGCAAAGCTTTCACGGCAACGGTGATGATGCTCAGGCGGCCCTAGTCTGCTACAGGCACTCAAATGCACGGCTTACAGAGTTGTCGGAGACTCGCGTCATATACTTCTACCTGCCGTTTTGTGGGGTGAAGATGGGCGGATGACCCTTATCGACTATATCTTGAGGGGCAGTGGACGGCCGTCAGGGGAATTAATGATGAAAAATATTTAAAACGGGGGTGCTCCAGATGAAGCCGGGATTTACAACAGCAGGCCAACCCACCGCAAACTTACAGGAAGAATTTCACCCTTCTCGGGTAGAGTGACGAGTAAGCCGACCGAGACGCTCCTTCCATGGATTAGTACGAGTTCGGAGAAACAGGTATTCTAGAATTGCCACCAAAACGCGTCTCCACCTCCCAAAGATTAACACACTCGCATTGTGAGCCTTTTCAAGGGGCGCCTCACAAGGTCACCCACGTGGAATCGGTGATGACAAAGACGTATCAAAGAATCCTGACTGCTTCGGAGTGCTCTAAAAGAGTTATGATCAAGCAATCCTGGACGAATAGACCGCCGGGGCAGGGGGGACCGGCTCGGGGTAGCACGCACTAGCACTCGTCGTATTGGTCGCTCACAAGAGTCATTTGGCCATTGCACGGAGCGATCAGATGGGGATCGGCGCTTAGGGGATAATATTACTCTCACCAAGGAAAGCAACCTTCGAAAGGAGACGTTTGGAAAGCCATCGACGACGCCTCGGACTATAGAGCTTGAGGGAATACGCCAGCTATCAGCGCGGACCCCGAGCTTTTCGGCACGGTGTGAAGGGTAACAATCGATTACTCATGCGGTACAGACACAGTAGGTCAATCAGCACTTTTAAAGTGTTTCACAGAGCCCATAAAGTCTCTTCAGAGTCTAACGAAAGGAAGGTGTAACTGTGTTAGACTCCGGCCCGACCCCCAAAGCGGCCTCGATCGATCAGTTATCCTGTGATAAATGAGTATGGAATACCATACTTAATAGTAGCCTCAACTTGACGGCACCACCATACTCGACCGATCTCAAACAGGGCTAGGGACGCGCCGGGATACCTGGCCCGTTGTTCTACGGAAGCTTAAAGTGATATGCTGCATTAGGATTTTTGTCTTTTATGGGTACAACCTTTACCTGCGCAGTGTCTAGGTACCTGCGGTCGCCCTCAACAAGGTTGAGCATTTCACGGAAGACCTATCTCTATGACGCTCTGCTTAGTCGCCAAAAGTCGTTATTCTAACATCATACACCGAAAAAGTTGCTACCGGGGCGGCTTTGATCGACATATCGTTTAGGACTAAGAGCATTCATCTTTAGGTGCTGTGTAGAGTCACGTTCGCACCACTCAAACGCAGTCCGCCATAAAACAGCTCGGCAAGATCAGGATCCCCTTTTCGAGCCCCCCAACACTATATAATGCCTCAGGTTGGCATTAGTGTGGGATCATGAGTAGAGAGGAGTGAAGGCTTCGTCAAAGGAGGAACACAGGATTTAGGCGCAGATGTGTCATAAGTTCATTGCATCTGTGATGCCTCGGGGGTCGGGGTGGCTGCCTATGCAAAACACTATAAGAACTTTGTCCTTTTTGTGATTCGACCGCGCGGAGGCCAAACTCATAATCATCTCGAGCATCACGCCAGAATTGATCATCTCTCAAAGCTGGTAGATTGGCTCATCTGCCTACTGTACCGGCTCTATTAGACGGGTGATGACATCATAGGTATGAGAAGCAGTCAGTACAATCGATACTGTCCGATCCTCTTCAGCGAGTCGGCTAGCGCCAAAATTCGCTCAGCTGACCGTAGTGAGACTAATTCCGGTGAGAGCTAGCGCCGATATGTTGGAAACCGTTTTCAGCGGATTCTTAAAAGAACTCCCATGGCTATAGTAGTCACGCCTAACGGGCTGGGCAGAATTTTTCCAACCCGAACGAGATTTCCAGAATTGGCATGGCATGAGGCTATAAACCCGAGTTCTTTTGTGGGGTCTAACGACGAGGTTATCACACGACGACGGGCACACATAGGGATGGTGGATTTGTATGTATCTGCTTCTCAATTTTGGTAGCTGTAATACCATCCGGCAAGTGATCCGATACATCTGGTAGCGAATTGAACGCCCCTGGCTATCACACCATCTGAGCGCTAGTCCGTATGAGTAGTACCATTGATATTGTTGCGGGCGCCACACGGTTTACGCACTAAGCCTATGTTTTACAAGGTAGGAGCCCGCCGTAGAGTAAGATAGCCGCGTCTCCCCCCCACTCCAGTACGCCGCCGGAACGGTTCGTTATGCTGGAAACGACTTCCCGCCACTGGCAATAACTGCTAAGCGTAGTTTCCAGCTCAGCGACGCAGGGCACACGAGAGTGTTTCTGACTGACCGGATCAACGCTAGTTCACACGGCCCTGTACATGACGAGGCGCCCGTTCCTAACACTTTCAGGAAGGCAAGTGGGCGGTTCCAAAGGTTGTTGAGCTCCCCCGGTATGGCGTCTGCGAGCCGCGCCCGCCGCCACGCGCTTGCCAAACGATTACCGCGAGGGAGTGTAACCCGGTTTAGGATGATTTTATTTGATGGATTCAGTGAGTTAAGCTGTACTCAAGCCCCGTATCACTTACGCATATCATAGGGTTCAGTGGAACTAGATATGCGCCGTTTGGCGATGATGGAGATTACTGGGATCCAGGTCTGATTGTCATATCCCTGTGTCGTCAACTAGAGGGTTGAAAAGACCAATTCTCCTCACGTCGGTCCGATCGCCAGGACGAAACTAATGGATCCCTTATTTTTACCCGTAACTACATACGTTTAATACCAGAACCGCCAATCTACTGGCTCTGAGTTAGCGGCAGCCCGTTACTAAAATGACTGTACTTGTAGTACGCTTTCGACACTTTACGGAGAGCCTTTCTTCAGCCTTCCTGAACGAGTTTGCGATTCACGATGTTTGTCGCGTCATATTGGAGCTCTGGAAGAGAAGGGGAAAACATGCTTGGCCATAGAACGGAAACAGCTGGTTGGGCTGTCGTCTTATCGTTGGGAGACGCCATACCCACGCGCAACGCAGTCGGTCCTCATTGGAGTAATAATACCCGAGCGCAACGAGAGGACTTATAAACCATTGGAAAAATACAGAATAAAAAGCCACGAAGCCTGGAACAGCTTACCCCTTATAATCAGTCGCCTCCTCTTATCAACATAGATCAGGCCGTGCATTGATTACGTGAGCGAGGAGGCTAATCGATAATTTCGTTGTACGAGACGAACGGACGTAGCAGTACCTGGGGTCAATTACGCCTATATTGGTCAATAATTCAGGTCACCACGTGATTTGGGGTAGACTACCGGAGGTCCATTCACGGTAAGTGTCGGTTGAATCGCGATTCCGATGTCATCGTTACCGTTCTGCGTTTTTGAAATCGGACCTGCATTGGAGCGTTAACTATCCACTTGTACTGGAACCTTATGAGATCCAGCAGATCCTATCACCCGGGCTGAATCGTTGACAGCTTCTATTAGTGGCGGGGTTCTAGCAACCATTGAGTATTGAGAGGAAATGCAGACACTGATGCCGAAGTCACAGGAGATTCTTACTGCCATTCTCAGCACCAACTGAGGCTCCAGAAAGTTGGGCCAGGCCTAATTTAGCTAAGGTATGGAATACACGGTTCCGTTTAATAGGGGTAAATCTTTCGGAGGAGCTCGAAGTTAAACCTCTGTCGCTCAAATTCCCGGCGTTTCTCCCATTGTTCGACTGTTGATCGGTAGTGCCGTCCCGGGAAGCCCCAGGCATTTCAGCACATGTAACTGCCAATGGTAATTTTGTCTAGGCGCATCACGCAAAACTGTAGGCTCGAGGCACCAAGTTCCTAGTATCAGCAGTTTGTGGAAATGGGACGGTGACCTGAAGGTTACTACCATATAGCATTCAAACATTCTAGATGAAGTTCGTTTCGACCGCTTTTGACAACTGTCTTGGAGAACTAGCAAATTATGAAAGCAGGGTCCCCGCCAACCTCTGTAATCATTATGTACTCTTGGGTTCGAAAATGAAAACCCTGATACCTCAATAATAGCGGTTGGATGAGAGCACCTCCAGCAGTAAATCTATACGGTTCTAGGACGCTTAACACACCAAAATATACCGCTCCTTGCGTTGAAAAATCGACGAAAGCGTCCTCGGCCGGGCTAAGTACCTGTACAATATGTCGATGAAGCGGGACCGGTTTCTATTGACTTAATAAGGACCCCCGCACCTTATGCGGTCAGGCTCCTGACTCAAGCATTACCTAATCTGGTACGTGACGTTGTTTGTTGTGTTATAGAGAGTATTTAGAACACGAGACTGGCTTAACCTCCGGCTCAGCCAGCCAACCTGATTACATCGCCGGTGACATCCGAGCCCGAGAAATTTCCCCATCGGGTGCTTTGTATGGAAATGACTGTTTTAGCGGTTGACGGATTGGCTCAGTGAGCATTTCGCGCTTAGCGGGCAAGGCCGGGTCATTATTTACGCCGGGCTACCGAAGCGGATTTGATTGGGGAAATTTTTATGTAAGGGAATCCTAACGGCTGCCGTTGTGGAGCTTGCCGGATAGTGCGGACAAGCTCCAGCTAGCAGCACTTCCCAGCCTATATGCTACCAGTTGAGCATACCAGAATAGCTTTGCGGTGCACGAGTAGAGAGAAGGGCAGGATTCAGACAATACCTAAAAAGCCGTAAAGCAGCCTAGACGTCTATTGGTTTTCTCCGGTCTGGACGTCTTCCTTGTAGCGAAGTTCTACAAGTTCTAACACGATGATAGGGAGAACAAGAACCACTTTTCGATGTCATGGGAGTGTACTCCAATAAACTCTAGACCGGTTAATGAAGCATCACTGTCGGTTCTGCAGACACCCACCTAATGCGTTCGCTCTGCCAAACCTTCATCTCAGCGACTGTACACAATTCGCTGTTAAGAAACGTTTCATTTCGAAATCACGACGCTTACACCGACCTGAAGTGGAATTACTAGGTGAACAATAGAGTAGGCCAGAACGCGTACGACTAGGGAAGGTTTTCAGGCCATGAGGGCCTAGTTTATTTCACGAAATCTGGAAGTTCCACCATGAGTCTGACGGCTCGTGTCCGGCGTGCTGTAGGTCAATGCCGCTTAGCTGCGCCGAACTGGCGATTTATCCAAGGCAATGTGTAAAGGAAGTGTCTGTGCGGTGACGATGTTGGGGAATTACCCAGAGTTCAATTGGCCGTTAGATCCCCCCGCCGTCCTGACTGAGGACCAGCACTGCAGTTCTGTTGCCTCCCAAAGAGCCCTCCCCGGGTGACTGAGTAGCAGGGGCTGCAAGACAAGGCCCGACTAGCCGTTCTAGTGGCCGAGAACCCGGAGTTTTGTTGAGCCCGGGTCGCGAAGGTTCTTTATAACTGCCTTGGCCATCAATTGGTATAGCGTCCCCGTCATGTCGGTTTTAAGCTCGTCGGACCCTCATAAAGTCGATTCGTAAACCATCATTATATGCGCCACTGGGTCGTACGACTGCAGAGAGCCGGGCGGAACATAATTCCGAGCGTCGATTATCCCAGCACAGCACGCGTCGGGTTTTAAGCTACAGCTAGAGCCGTCACTAGATATTTAATCGGCATCGTATTAGGATGTCATCCATGCCAGTAAACGCCGCTCAGCTCTAATACGATCCTTGTGGTGAAGAGGACGAAGGCCGTTCTGATCTGTGTGGTCTATCTTGTCGAGATGGACATGATGCTCAACCTGAACCTTAGTTTCGTATAACGCTCGGAGCCTTGGGACAGCGAAGGTCAGAGCGTATTCTGTTATTTAGCTGGCAACGTTGCGCTTACCTAGGTGCGGCCTTAATGAAAGAATTTGAGTTCTCGTCGTTACAACTTTTGCACTCCCCAATTAGATACTTAGTGAACCCACTCCTACCAGCATACACACTATCACGATCTGGATTCAGGCCTTCGTTGATGTCTCATCGTTACGATCTTACCAAAACGGGATGGGGCAAACAGAAACTCACCAAACGGGCCCCCCTCCCGAGACCTACATCGGCACAATCATTAGTCCACAAAAGACAGATATGCAGCCAGCTCTTGAAGTTGGGATTTCGTAGTAATTCGTATACCTTCCCGGTATGCCGTACATGTGTGGTTAGCAGATCGGGATAAGAAATCGTCACCGGCAAGAAGGCTGATGGATTTAGGGTCGCGAGGGAAACGGGTAAGTGCTAGTCGTCTACGGCGAACTGTTTCCTAAAGGAGGCTATCGTAATTCCGAATCGGCCACCAAGTTCTATCGTGCTCCGTACGCTGGGTTAACACCAATGATTCGTTGTGTCCCGTCATTCGTTATAGGCCGATCAGCGTCGTTACTGAGTTATAATCGGGCCCGGACTTTCGAACATTCTCAGGGAGATGTGTGTGTAGAGAAGCTATTAGTGCACCAACAGTTCAAGAACTTGAATATCCCAAAGGGCCATAAGTTATGCGTATAAAGACGAGAGTTAATGTGAATGTTAGAGGGTGCTCTCTAGTATGAGGGCATCCTCCTGGCATTAAGTACTGCTGATAATCACCTGATCTAGGGACAACAGTAGCGCTTGGCAGTGGGGTTACACCTACATCGACGGTGCACAATGGAATTGGTAGGCCCTCGAACGTGTACCATATAGTCCTGCACGGACATTTTAATTATCAATTGCTACCTTACGGGACAACTATCCGGTATCAGTGAAGAGACATCCAGTGCATATCAGTAACACCTTCCGGAGGACGCTCACACTATCCCCCCGTTGCAACCTGAATTATCTTAGGAGGCTTACACGACCTGATATGGGGGAGCCCCTTTGCTGTAGGCACTTATTGCACTGTGATTGTAATCATAGACGTCCGAGTCTTCCCCGGCTGCTGCCATAACTCACGTGAGTTTAATGGAGTTGAGCAACTAGTAAGGGCTGGCGACGAGTAAAATGGTTCCTGTTACAGAAGGAGGGGTCTTGTAATAGGGTTGGTCGGCACATGTGGCAGGAACGTCTGGGGGGTTCCTCCAGTATCAAACCAGAATGACGCCGAATCTACACCTAACGTTTTGCGTGTCTACCTCTAATCATCTCAACTGACGCAAGACGACAAGCGCTGGCGTTGTACCTATCTAGACCCCTGCCTCCCAACAGACCGAATGTAAACTAGTATGATCAAAAGCTCGGTCTCATTTACACTTCAGGAACCGTGCACTCATAGCCGGCCTTAGGTCTATTGCGTAAGACCACGGGATAGATCCCTGATCTCCAAGCAGCTAAATGTTTTGCGATACTTGAGACTAGAATTTATGCTAACAATATAGATAGTGGGAAGGTAAAATGACGGCCCGGTAAATCCGACAGGTTTGCATCGGCGTCATTTAACGGAACTGGTCATTGTGGAGGGGTTGTGGTATAGATACGTCCGTTCATTGTTTAATTAGTTGTTTATAGGTTGACATTTCACGGGGACCCGTGAGTCCTAAATTTGGCACACTGTGCGGGCCGACGTCCTTTAGTGTCAAGGTCTAGTTAATTCCACACTTGAGCATCCTTTCACAGAACGAGCGACTGGCGAAGACAGTCTGTCCGTGCTTACTGGTGAAGGTATCCTGGATCTATGTGATGACTGAAGAAGCCTCCAACAGGTAGGACAGTTACAATTCATCGGCCAAACCGTACATGGACGGATTGTCCCCTGGAGTCTGATAGATAATAAAGGTCCCGTCAGCGTCCGAACGGGTTGCTCGCTCAGAGAGACAGATGACACAAGTATCCGGGTTGGCGTCCACTTCTGAGATCCAATGGGCTTCGCCAGCGGAGACATTCGGTTTAATAGGAGCGGCACATCGTTTTTATCCAAACTGACTCCCCCGGATTATAGCACGGCATCTGTTACTTCGTCTTCGTAATTAGCCGGTTATGAAGGTTGGCAGCAACGCCCCATGCAAGAATCAAGCCATCGATAAGCCATGCCTGATAGCCTTTTCTACCGGTGATGAGTTGAAGACTCCCAATCTCCATCCTTCGAGCGCGCCGTCGCTTACGGTGCATGCCGAGGGCTACGGCCTCCTGTACGCGTCCCTAGCTGTCGCGGAGTGTTATTTGTCATGTGGTACTACATTTCGCTGAAACCTACAGCGGGGGAGGCCTGACGTTAACTGGGAAAATCCTTCATCCCCTACGTCTTCTCTTGTGTACGAGTACTCCCCATTTAAGACTGGTTCTAACCCTACTATAGCCTGAGGCAGGACCAAGAGACGCAGCCGACACCAAAACCTACCAAGAGCGGCAGATTCGGTTACCCGCGGAAGCCTGAATTGTGGAAATAACTCAAGCACACACTCAGGGATACTCTTACCCGCCGGTGCGTTGCACGTGCGCCGACACTGTCCATCCCCCCACGGGAGTCGTCCATAATCCTCAAAGATATAATCCCTCGCAGGAGTGAGCCCGCGATATCGGCGTAACAGCGAATTACGTCGCGGGTTCGGGTAGAGACTAGACATGCAGGCGCGAAGACCTCGGTATTTCCCCGCGATGAATAGACGTCGTAGCGGAAATTGAACGATGGACCACGGACTTATACTAAATTTTCCCATATGCGAAAGTATTAGGAATGTCGACAACGCGCCATAGACACATCCCATAGTTTACTGACCTATCGACCCTAATAGATCCGCAGTATCTGATGTTTCTCTTACAAGAGACGCGCAGGTAACACTTGAGCCCTTCGCTTAGCGTGCATCTGAGCTAGGCAACGGCGCAAGCGTCTTTTTTGCTCTCGGGTGGGAAACCAGTTGGAGATCTCCATGACTAGAGACAGGGGTGATGACCTGGTCGGGAGTCCTCACGGGTGGCTGCAAGGACAAGCTTAATTAGGTTCACAACTATGAAACATAGGATTTATGAAGCAGGTGCTATCAGTTTTCATGGCTGGCATTTACTCTAATTCCACCTACTTGTGTGACCTAGGGGAACGTAACGTAGTTCAAAATGGCTTTCGCCCACTCTCAAGGGCAGCGAATCCTCAAATAATACCACGCCCTAACCGTATTGCTGTTTTGTGTAAGCTCTATGTGGCATGCAGGAGGCCTATCCAGTGATGAAATAGATCTGGAAATACTCTGACCATTGGAGGACCTGTCGTTAAAGAATACGGCTACAACCCAAGATACGTACCCGGCTTCGCGAATATGTTATAGATTGCCTGTGCAGCATTAAGTGATCTTCATACGAAATGAGGAGGACCTAGGAACGGATGTCGATAATGACCGCCGTAATTTGACTCCCCGGCGAAGTCACTGTGAGAACATCGCTTGCCCGCGCATCGCGTAGGGATAATATATGCAGTGCCGACTATGTCGCAGATAGTCCTATTTTAGTTGACCACACTACCGAGATAACTCGACAAGCGATGGGGGGGACGGAATGAGTCAGCCATCGTTCAAGATATGATAGAAGGGTATTTGGTCGCTCGCTACATACCGGTCAAATCCTGTCTCAATTCGTCGTCACGCTTCACAACGATGTATGATTAGAATTGATTCGGCACCGACTCAGACTAATAATAATCTGTTTAAGGGGGGGCTAATCTGAAGTGCGATCTAGGTGAGCTTGAGTCGCGAACGCGAGTTAGTGTTTATCGAAGTCTTAACACCGCTTGGTCATAGCAAAATTAGTTCGCTCACCCCTTCCTCCCGTATTCGCCGCACACCCCTTCCGGTCCGCAAGTGATCTCGAGAGGGAGTCGCGTTCAAGTGAGCACGCCGATCTAGGTCGACTAGCTGTCCCTTGGAAGACGTACAGCCAGGGTATTCGTAAGGCACAAAGTCGTGTGCTACTACTCAACCTGCCGAGGGAATGCACGAAATTACCGATCAAGAGCCAATCCTAGACGATTCGCAAATCTTGTAGACCACCCATCGGCCATGGGACAGGCGTGATATGTCTCCACAGATTCGGGGTCTAAGTTGTTGGCACAACATTAAAGTCCTTTCTTTCTTTTTTCCAGCGGGGAACTATTGCTTCTTGCCCCCTGTGATATTGGTTTAGTGAGCTATAGCGTCGATTATTCGTACAAGTCCGACGCTGCGGAGAGTTCGAAAAATAGGATCAATAGAACAGGACTAAGTCCCCTTCAACGCCCCATATGAACCTACGGATTTGTTATACACGGTCCGTCCGCTAAGGCAAACGTCGATAATAACGCATTAGTCGGATACAACCGCGTGGTCGGTGCTCAGATTGCCAGACGTTACAAGGCGGCACCAACAACAAATGCATCCATGATATATTTGAGCCGAATGACGAGCGCCAATAAGTGGCTTGGGTCGTGATGCCGCCCCCTACGGTCCGTTGAAGACTGAGTCTTGGAATTCGAGGGGGCCTGTGAACAGGTGTGTTGCCGATGTTTCACTGTGCACTCTGAGTCTGCTACACGAGCAAACAACAATATGCAACCTTCTTAGCGGCCCAAATCGCTTGGTTAAAGGCAGTTTGAAGTCACCATTGGTGAAGTCACGCCTGTGTTTAGGTGTGGTCCAGGGTATGGATATACCCCTCGTGAGACGCCAAACAAAGGATGTCTACTTTATGGCCCTATTTTCTAATTGAACATCGGCACTATCACGTCCTTCAGTTTGAAGGCAGGAGGGCTTAGTTATTAGGGGCTTCGCCGTTCTCCCGAAGACCTTTAGTGGGATCTATACATGGCGTCGTCTGTTGTTGGTGCTATCCTTTGAAAGTTCGAGTGGCGCCGAAACTTGAGCGGTCTGGAAGATGGAAACGCGACGTAACCAGGGATTTTAATGTATTTGCCGATATTAACAGCCGTAAGTCGGGATGACCTGGCCGAATGTTCGGGGAAATTATGGGGCCCGCCTAATGAAGTGCGCTTATCAGCAAAACCAGGCTTACACGATCCCGGTCGACCGCCCTGGTTATGAGGTGAACGCGGACCTGGCCTTCTTGACGTGTCTCTGCCCCAGGTAGGTTTGCAAAGGCTGATGTTGCGACATAGACTGTGGTGAGTAGTCCACGCGCCGACGTACCGGGCGAGCTATCGTACCCATCAGCTTGAGATAATGTGTCGCCCCTAAGCATAAAGATCTAACGAACAAGGTGGTTCGCACTACCATCTGCGGAGCTGAAGCACCTACCTACTGGCGCAACGGTATCAATGTTGTGGCAACTCCGCACGTATGAAGGAAGGGAGTCCTACCAACGGATTCGGTCATCTGTATACACGCTCATAACTAACCTACTCACCAACGTTAAATAAACGGATTTCGACAATGGACGCACTAAGGCATTGAAGTGACTACCTGGTAGGAGTAATTCGGTTCATTTACGAATATGTAATATTCGTTTATGGCTTATTTACTGTTAGGATGTGGTCGAACTCGCACTAGATATCATAGTAAAGGGCGGACTTTACTGTATCAGTGAGTTGACCTGGCAATTCAACAAAGCGTATGTCTCTAAAGAAATTAGCAACCGAGCCTCAAAACCTTATCGAGATCCTGGCATCCAAGGAGAGTGTCCTCATTGCTCCACAGCGAGACTTGCGACCCTGGACAGCATGCGGTTTAATGTGTTCGGGTACTGTTTATACGGGTGAGTTTACGGTTGATCACTTACAACTTCTATTGTCCCATACAGTTAAGCCCCGACGGTCTCTAAAGCCAGTTCGGAGCCATCTTTCGCTTGTGGGAGGCGCCAAGGGCCTACACACCGGATCCGCGCTCTGCCAAGGTCGCGGTACTGGAGAGTCGTGTTGTCGTAACACATGCTACCAATACCGATCTAAAAAACGCTAATAATTGTGTGCCGCAGGACCTTCTCTTAAGTCGACAGTCCTTGACTCCGTCTATGATCGCGCCGGCGTTGTACCAACGATTCTCCGCCGGGGAATGATCGATCAACATTGTCTGGCGAGCTAGCCAAATCAAGACCTTCAGCATAGACAAGTCGGCATAGTGTGGTATAGATAGCTCACCTCTACGCTTCCCTTCCTAGGCGTTCGGTCATCTCGTCGAGGGAGTGTGTACGTGTGTCTATGAGGCCAACATAGCCCTCTCTATTACTCAAGATGTCTGATACATTTACAATCCCACTATCCCCTCCGAGACGACGGGTACACTAAGTTGCTCGTCCCCGCGAAGACGCATACATTACCTGCGGTTATCCGGGGTTGCAACAGCCTGCAGGCGCTGGCTCATTACCTTTCCAAATGCAGCAATGTCCCACGTGATATCAACATGTGTGGGACAATGGCCTAAAGGTGGTTCCATACTAGCTTATACAGCGTCCAATAGCACCAGTTGCTTCTCAAGGAACGGTCTAGGGTTAGTAGCCCATTTGCCATCTGGACCCACCGTACCCGTTCCGGCAAAGGTCCAAAAAGCACATCGTGTTGAGCACTGTAAAGCCAAAGTGCAGCTGAAGACGAGATGTCCGGTGGACTGACAGAGTAGTCGTAGCAGTCTAGGCGACCGCTGAGACATCAAACAACCCCACGCGACTTTTTTCGCAAGCGCAAGGTTACACCTGTCTCCACATGCCACGCTAGGTCGTGCGAAACTGGTTTGAAGGCCGGGATAGATTACTCAATAACATACACCGCGTGTATCCAACTAGACACGCCGCTATTCCGGACTCAGTTGGGATTCCATAATCTCAGTCTGAATATTACAAGCCACACACCCGGCACCATGGAATTTTTCGGGAGGCAATCGCTATTTTAGCCGTCAACTCTTAGGATAGCAACGTCATGAGAAAGGTCTATCCTGGCGCTGAGCACAGAGTGGGCAACAAGTCGTTGCGGAACTTACCGCTGTCGGGTGCCGCTAGGCTTAGATTAAGTGACCAAGACATTGACCTCTCAACAATGGTCTGCACAGATTCCTGGGCCTCAAAACCAACTGTCGGTTCCTATCCTACATTGGGGGCGGTTCATCCAGTCGAACCGGTGCTTTAGTATCCGCGGTGACAGCGTTTGTTATGCACTATGTAGCGCCACGACTCGCCCGGAACTGGTCCGAAGTGGTTACAAACGAGTATCATTAATGCAATCCTTGTTGACCTAGTCATAAGTCCTAATTCAAGTTATTAAAGATACAGAGGGGATTTGCCTTTTATTTCAGCTTCCCGCCACGGATTTTCATGGGCCCGTTTTACCTAGATGCTGCCGTGTGCCCGTACTGTAATAGGCGGGGTGGAAAACAATTTCCTTTGTATTAAACGTTTATGCTGCTGGAGGCCCAATGGGACACACGACTCCCGTCATGAGAAGTTAGATTAGCGGATCTCGCGATGAACTTTGGGTCAGCCGGCCAAAACGCCCAAGAAGTCGGATTGAGTCAGAATGTCCCTGCACGCCGGGTCTGGCTGCGAAACGATACTGGGTGAGGAGAAACTGGCAAGCCAAACTCGGCTGTGTTCGTTCTAGTCACATATCCCTACTTGAGCTCACCCTTATGTCTATCATTGTCGATCTGTACTACGGCTAATTTATTAGATGAGTTGTTACAAGGCTTCATCATTCACACAGGACAAAGTAAGATGGGTCTTAAGCACCGGCAATGGATGCACATAAGAATAGCGACAGAACAGCAACAGCGCAGGTATGCGATAAGCACGAACCCTGTTATGCAGCATACCAACCCTCATATATGAGGGATCCTCTAGTTGCCGGGTGGCAACGTATGGGAGGTCCATCGCCTAGCGCGTGGTACGGTGAGTAGATCACACGCTTGTCCTGCCGCCATGCGGTAAAACAGAGAGTACTTGCTATTCAAGATGGTCGGTGGTTGTTTGTGTTAGGATGAGTGGATAGCCAAAGACTCGCTATGGGGATTAGTCCAAGCTGGATAGATAATCCGGATAAAGGGAATTTGACGTGGTCCCTTGCATGGCTCGCGGACCGCTAGTGATCTCCTAAATGCCGCCAAGTTCATAGAAGGTAGAGCGATAGACTGGTGGTAGCGGCTACTCAGACAGTAATATCCTCGAGGAAAGAGTAGGTAAGCATGGATACCCACCATTACGCCGTTTTTCTCGTCGGTCTATGGGATATTGTGGGTAGTATGACGTGGGGAGCCAGCGATCTACAACTCATAATTTACCATTAAACGCCTAGTTCGGTGTGGGTTTTCGAAAGGTAGGAATGTGCGATGTAGTAGGAGTGGGTTTAATACGGACAGTGCACACTACTGAGGCCACATACTCAGTATGAGTGGATGTCAGACTGAACTCGGCCTCGTAATCGATGCCAAGTCTGCCAAATTGTTCCTGTTCGCGTACCCGTATCATAGCCCCTTATGCTAGGAGAGTCTCGAGGATCCGTCTCACCAACTTTCGCAGACACTGGTTCTTAACGTAACGAATGAAAAGTTCGGGACATCGTACAATGTTGCGCAACATCCCGGATAAGAGGCACTCAAGTGGTCCAACGTGCGCCTCAAGTACCAGAAATTCTGCTTCGCCTAGCAGAGAACTCACACACACGCCCCTCCCCTGCACACGAGGCAACGGTCTAGGTTAGTTCGCCTGAGCAAAAGAATATCGCGTGGGGATGGTGCTTAGAGCCATGTCTGTTCTCTCATCAACTGTCTCTGAGCCTGCTATGCGGCTAATGAAAGTATCACCAAGCTGTCATATGAAACCCAAAAGTGTATCTGGTACGCAATTTAATCCTCCAAAAATTCCGTCCGTAGGGCTTCCGCTGCCACCGGGCCTTACAATAAGGACCTGGGAACCGAACCCATTGTACACGTCTTACCGGTTGTACAGTAATTGATACTTGGGTGCGTCGGGCACAGAGAGGGCCAGTCTTGGGCCGAATATACGTCTGAGTCCGTCCTTTCCGAGATCGGCGTATTAGATCCTTATATACGCCCCCGGCTGCAATGGAGGCCCGAGGAGGGCCTAAGCTTCCGCATATCAGGAGGAAAGATATTAAACATCATGAGCGCATGACGCCTGACCGCGATTGAAAAGGAATTTCTTCCAGCTAGAATACTACATGCGGCCATGAATACGCCGTTCACTCGCTCACCCGGTCGTATGTGACGCAATACTGCAATTCATCGGTCTGGCTATAGCGTGCGGGCGGGAAGGCCATAAGATCAACTCAAGTTCCAACAGCAAGAGGATTGGTCAGTCGGGTAGGTATGAGGCCAATTATAAGTACAGACGGGAGTCTCCTAAACTCACTCAGCGTATATATCAAGTGTTCGCGTTTTTCCATATCAAGCGAGACTCGGACCACCTCTGTTAATGCTACCATGAGTAAGTATGAGATCGAACCGTTGTAATTGAATAAAGTCGTTTATTCTAAAGCGATTGTGCGCTACACCGGGCGTAAAGAGCCACGTCTAATAACGAGCCGGTGGTTGATGCTCGTGTGGCTGCTATTAGTAATCCCTATCGAAAGGTTCGGCAATAGGTAACGCGTCGAGAGTGGGCCTCCACGATCTCTACTGACTGTACGCTTGATTGTTCGGTGCATATTATTACTAACCGGTTTGACAACCAACGTCATAGGTTGACAGCTAAGAGAATGTGATTCATTGGGCGAGTATGATCTAGGTCAAAGGGTTTAACGTATTTCGCGTAATACCCTTCACGAGTCGTGCTTATAGTCAGTAGGGGTGTGTATACTCCAGCCGCCGCTGAACCAGAGCGTTAACCCGTGGCCTATTAACACCGCCCTACTGTCCGCACCACTCATTTACCGGCGGAACCTAGACGCAGCTATATTAATGAACAGTCTCACGACGACCTTATAACTTGGCAAAATCGTTCTAACAAGATACGCCCTGGTTTATACTATTAGAGGGCGGAATATTCGTATACAACAAATAGGACAAGTCGGGACCTGCTATATTGGTTCATTCGTCACGTCCTATCACCGCTTGATCGATCTGACCATGTGCCGCTAGAACTTTCCGACATGGGCCCGCTTCTCGTACCAGTCTTCGAGTTCCTGTTCGTCCTTCTGACCTCCCCCACTATAGGGCGTCAACATCGGTATGAGGCAGACGTGAAATTTACTCGCGCTTTAGAGCTGGTGCTTGATTATTCGCCCCGTCCGACCTTAGCCAAGGATACTTCACGATTTTTCGTCCGGGCCCTAGGGACACCCCACATAACATCAACTGGAGTTTAGTGCTAACAGTGCGAAGAAAAAGTTGTGCCGACCACCAAGACGGGTCGACGAGATGATAATAGCGCGACACAGTGATAGCCATTAGGATCAATGGCGTTTAGACCGTAATAGCATTGCGGCCAAGCTCGACATTGTTACGTAGCACTCATGGTCGCTGTTGTTGCGGTTACGGACCCTCGACTGGTCATGGTATCGTGCTTACCCCCTGTCCGGGTGAATAACAAGACCGTGGTCAAGATAGCCCGTACGTGGTTGTCTGCTTTTCGGAATTGACCGCGGCTTTAAGAGACAGAGCGATTTGCGCTCTTAACAATGAAAGAGCGCCATAGACAATTGGTTTAGAGCCTGAATATCTTCTCTCGACGTGGGTTTATTCATGTGCGCCGCGCACTGTGCCCGCGGGTCCGCTTTTGGCGGGCTGTCCGGCAATTGGGGAGGGCCTAACTCGAAGGGAGTTCTCTTGAATCCTAGCTGATGATTCAGAACCTGGTTCACCACGTTGAACATTTAACATGGAGCGACGGCAGGAATGGGGCCTCCCAGCAGTGTATTATTGGCGGCCTGGGTACTAAAAAGAGACGCCTACGCGTGTTTGGAAGTCGGGATGAGACTTTCTTCGTTTCGGCGACATGGGCAAACCTCTCCACTTAAAGAATAAATCCAGCTGTTGCGTGAGCATCGTGTCGAACCGCTAGACTCCATTGCCGCTAGCAATTGGCCTGAGCGGAAAGACCCCACTGAAGTAGCAGACCAGTGGCGCGCCATGTATAAGGAGGACACCACTCCCAGTTTAAAGCCTCTTTGCAGTCATGCGTATTCCCTCTGAAGGTTTGCTGAAGCGACTGACGACCAGGTTTTTGGAATTGTATATCCTGTCCACATCAATGGTTCAGTTGACTTGTTTCTAAATTGACACCCCTTGATTTGAGGCTGACAGTATAACAGGTTGTAGCGCACACACAACAAGGAACTGAGTCTATATGGAAGTAGCCTATTTGAACTAGTCTTTGCTGATCTATGTAGCGGCGTACCGACGAATCTGTTGGAATACTATTGCGTCAACTACGGATCGAGCATGCCCATTAGAACCCAGACGAGATTCCCGAAAAGTTATTCAAGTTTGATCCGGTTTCTAGCGTGCTGATTTTATCTGGTGATGGATTTGGGGGTAGCCCACTGGTTTGATATCAGAAGGACAAACTTCTGACCGGTGACAACATTTGTCAAATGCAATCCTGAGATCTGAAGGAAAACTTTAGTTTGTCCCGGGCGTGTTAACCCTGGACCGAGCAGCAGAGATATGTTGCTCCAGGCTCGCGGCTGACATATGTTGGTGAGTAATCGGGCACTATTTATAATTTGCGCATTCATCTGCGCTACCTGGACACCGGCGCATGGTTTGGTGCTCCTAAAGCCTACCTTCCCGACCCCGAAGAAAAACATACCATTTGTGTTCTGGCACAGTTTAACTGACCTATGCGCACAGTCGAACAGAGGATATACCCATTTAACTCAAGGTTCACTATTCTTTATTATCCAGCTCGAGATGTTCTCCGTGTAAGACGCAGACTCGAATTCAAGTCGGGCCGAACTCCAAGGCAGCGGTGTGCACTTCGGCGTTCACCGAAACCGCGGTGACTTCAGGTCATGACGCTGAACCGATGGCTTTTTCCGGACCCCAGATCTAGCTATCCACAAGGGTTTTATTGCAATGGTGCGCATCGCCGCGGCTTGGAAGTTCATCGTAATTCGCGTCAAGGCTTAACTCTCTGCGTCGAACCCTACATTTGAGCAACCTGCGTAGTGTACTTGTCTTGCTCATGGTGCTTCTCCATGTATAATTGTTATACTCCTGTGTCATATGCATAATGCAAGCGATCCAGAGGAGTCGCGGTCGAGTTAAGCAACCATTGGTACCTGTGCGAGCCTGAATTAGTTTTGACAAGACCGGTCTAGTGGTCGGGCGTTTGACTGGAAACAGATACATACTTATCGACAATGTTATAACTGCAGTACGTTACTCGCGTGGACATCTTGTGTGCACTCTTGACGTAGCCAACATGCAGCATTCGTTAGTACGTGAATTCAACTGCATCACGCACATCGACAATGGTCATGAACTGTCCGTTGTCACCGTATCACCTTAGGAGTAGCGAGGATTTTGGGTGCCACTACAGACCCACCTTCTACTTTTAAAAACGCGAAACCCCTCGGTAAGAAGCCACTAAGAAACGACGTTGGTCTGACGAATGACATCTCCTCACATTAAAGTGAGAGTTAACATTCATCTGTATGCCCCTGGTGCCCACATTGCTAGTAACTGAGCCGGCTGTCACGGTTCTGACCTACCGCTTTGCGAGACAGAGTCATTTGGCGCCGAAGGACGTTGCGCCGCCTCCTCTCGATAGTGAGCCACCATCAGAGAGTCCCTTAGCGTCGCGGCGTGGCCGTTCGTACTGTCGCCACACAAAATACTACATTCCCCACTCGAACGGAGTAGGATTAGCACCCTCTATGCACTCTACCACTCATCCTAGGCCCCTCGACTGGACGTGCATCCCGGCAGCTGTTTTGGCGGCCTGCAATTATGCGAGTGGTAAGCTCCATCCAATGACCTCTTATGCAAAATCATAATATAGGCGAAAAGTTCTCTAGCCAGAGTTGGAGACATTGCTGACGGAGACCCCCCGACTGTTGTAACTGCAACTACAACCAGGAACCGGGCAAATTAACTAACGGGGGCAGTCGCGCGTAGGTCTCAGTAGGCGAGACGCTGTAAGGCCTAGCAATATCATAAGCGAGTCCACTCAACTTACACTAGCAAAATGGAGGGTTGATTACTACACCCTGCTTGATACTACGATCTCCTGGCATTTGTCATCGGTAGCTAATCTATTGCATAGAGCCCGACAGCGACCCAACCCGCAAGTAGATCACGGAAAAGCTGAGCCGGCCAAAGTATCCGCGGCTTTGGTTTCAGAGACACCTGCTACCAAGGTAGTGCCGAGTCGAGTCCATCATTACACTATTCCCTTGGCGCGTCATGAGTTCACTGATGGGATTGTCCTGCACGCCTATTGTCCTAACATTCGTTCTTGGGTCACGCAGTTCTACGCAGGTTAGACTAGGCGTTTGACAGCCCGGCCGTCGTCCAGTACACGGTTAAATATACGCTCAATACTAAACACGGGAAGTGGTGGAGCTGGCTCAAGTCACGGTTATTTAGGCCCATAAACACATTACATCAGAAGAGTAAGCACACTGGCCAGAGAGGTTTGGACCAACTCAAACGCCACAGCCGTGCCGTTCTTTTCCCTGGCGACCATATCTTATTTGTCCGGGTAGGGATCTTTGGGCAGCGTCCACCCTTTCCACTCACTCAGTGCCGATCTCGGACGGAGGCGGCTTGACGTTAACAAGCCTATACTAGGCAGAGTGGGGCCAGGTTACCGGTGCGAGACTACCTGAGCAACCCCTGGCTCGTCGTTCGCATCTATCCTGCCGCAAAGTCATAATCTTCATCAGGGGGCGAAGGCCCATCACGGGGTGCTGTTACTATAAGACCTAACGTAGCCTCGTAAGTTTTGGTCGCAGTTGAGAGTGTCACCTTTAGCAAAATATTTTGCCTACTCCTAGCCTGGTTAATGGGAGACCACGCTATTTGAGTGGTAACTGGAGAGACGTCCCAGTCCATACCCCGTCGGCACAATCCCCCGGCGCTCAGGAAACGGAGGCTTTTCAGAGCTCGCTGTATTGCAGCAGCGAGTCACTGCAATAAATGTTCCAACCCGGACCTCATCTGCAAACAGCTTGCAAACCTGCGTTTGCTTACTTCCCAATATTGAGTCCTATTAATACCGCAAGGACCACTGTAGAACAGCGTAAATGGGTACCTCGAAATTACACTTCCAGCCAGTACTTACCCCCCTTGTCCTCCTGACTTTCAGTCCAATATGGACAGATCGCGATTAGTTGCTGCGTCAACCGCGTTGACTCCTCTCAAGATGGATACTCTGGAAGAAACCTTACCGCGCGATAACAGTCCCGTATAGCTAAATTATACGCGCCGGCACATGGCTTTTTGGCTACTTGCCCACGTGGGACTAGTGGCAGCTGATTACTGAGACGATGTACTGGTAATACCTAGGGGATGCCTAGCACCACCTACGGATATCGGGAGTCTCGGCATGCCATCTGTATCGATGAATTAACTCACGTCCTCGCGTCTGACCATGATGCAGGCCAGGCTCTCGATATACAATAAGCATTGGTGTTACATATCAGTACAAAAATTGAGCTAAGGGTAAATTATTGAACCGGGAAAAGCTTCCAAAGTCGGCTCTAAGTAGTGGGCTTGAGGGGGATCTGATGATGCGGCTCTGAATAGTTCAGATCCTGGCCATAACGTGTCCTACGAACCATGCCGTACTGCAGGGCCATTCGCCACGGGGCCAACTGTAGAAGCCCCGGTCCCGCTGTGATATATTAGGGTAACCTAAGGGAGCCTCCGCTAAGCGTCCACCTCTTTGGGGTGAAGTCCGTCATCGGCCAGCGGCAATGGCCTCGAAACTTGTTGCTATTGAGCGGGATTGGCATCGGTTAGCGCGCTTAGTCTGGGATGCAATAGTGTTCAAGCAGGTAAAGAGCTCAAATTATGCAGGATCATGTGGTGCATTGAGACATTTTGAAAATGGGTATCTATTCTAGGGACACTCTATCTTTGTTCCATTATATAGCAGTAGGTTGTTACCACGAGTGGTGTTCTCCCTCGTGAGAAATACCAAGAGGGAGAACATCTTAGTATTTTTATTATACGACTCAATTTCCGCAACTGCCAGGATGAGCGCAGATTCAACCACGTCAAGATTCGGGGCATTACCGGTGGTCGTTAAGCAGCAGAACTGTGCCCGGCGCATTGTCGACCACCCATGCTCGGTAACTCTCTGCGGTCGACTGAAGAGCGTGGGAGGACGGATTGCGCGTAATCGTACGGTTTGCTGGACGTAGTAATTAAGACGCATCGACAGAACAATTACGCGGCATAGCACAGTGGACTCCCTAAAACGTCTATTTTCCTCGGATGGGCTTACATAGACTGTCCCCAGAATACGCACACGATGGGAGGTAGGTGACTCCAGACTAAGTCCCACAGGTTCACGTCCGTTGGGCACGCGAGTACCAGTTCCTCCATGGCCGCATGAACATTTTCCATGCTCGCGTCATCCAGAGCCATTCGAGGTACCGTGCACGATAGCGCTCACGTCCTCGTTGATACTCGGAGAGCTGTCGTGCCTAACGGGTGTGCTGACTTGCAAGAATTGTTGCCCGGGCAAGAAGGCAAATAGGTTCCCGCCGCAGCCGCGAGCACCTAAACCCGGTATCTTATGAAGTGGGTAAGGAAATGCTTTTAGACCACGAATAGTTATAGATCATCCTCCGAACTGATAACGAAAAGCCTACTATGCACGTACAGTCAATACCCAAATCCCCCTAACCGGCAGAAGATTTGTAGCGCATTCAGCAGGTGCACCGGAAGTGTGGGGCTTAGGGTTTGCTCATCAACGAATCTGTGAGATCGTTCCACTATGAAAAAGTAACCCCACAGATTCCGGGAATTCTGTTTATCGACGGAGCGGCATAATAACCATCGCGTGCCAACTCTTGAAAATCGGCTTAACCGACCTGCAAGAAGCTGGAAACCGACTTTGTTTTAAACGCACCCATAATTCCTGGCCGCACGAGGAAGGAGCAGACCCAAAAGGATTGAACGCACAAGCGCGCGACAGCTGACAAGGTAACCTTCGCGGTACGGACTAACACGGTGATCCTATTGGTGTCATGCAGCGCTTTGTAGTGTCAAAGGAGCCGTCGAGGACTTCGGCGTTGCAGAGGGGCATCAGAGGGCTGGAAAACAGGTTCCCTGGACTTGTAGGAATGTGGGTTGATACCAGCATGCTAAGCTAGGCACGTATCAGGTAAAAACCGTACCTTCACGTTAATGGTGCATCGAGCAGGACCGCAACGCTTTTAGTTAAGTTTTGAGGCCGCACGACTGTTGTGGCGTCTATTGATATTGAATTCAGACCGCTACTTAAAATCACAGCGAGGGCACACCGAATAGAGGCGCCGGAATCTGGATCTTACATACTGAAGAAAAAATTGTCATTCCCACTTTCAAACGCTGTTGATAGTAGTTGTGTTTATAGAGGTAACGAGGACGTCGACCGTAAGCCAAGAATGGTTTATCTTGGGATTCAAACCATTAAATCGCTGCTTCTGGACAATGATTCTAATAGCCGCCCCCGTTTAACCGAAAGGTGGTTGTCACGATACGCCTATCGAGGGGACGGATCCTCTCACTTCTTGCGCACCACTCGCGCAGGTATCCGAGCGTGGCCGCTTGTAACCATGAAATTTTCAAATTCATCACCCCTTCGAGATTATACAATGTTCTACTACCCTCCTATCGACAAATAACTCGTGCCATGATCGCACGTTTGTGCACCATGGTGGTCGAGCGGAAGTATCGCGTTCCGGACTTGCTAGGCTCGATTGTGTTGAACTAGGTCGGTGGTAAAGCATTATACCAGCGTCAGAGTTCTGCACAAAAATTTCGGTTCGAGGTCGCACGATAGAGGGGCCAGGAAACCGTAACCCCTATGGAGAACCTTGCCGGTGTCTACCAATGCGTAAGCTCAGACTCAGGCGACGTACCTTCACTCCCCATACTGAAACTCGTCGGGTACGTCGGTTATCAAGAGCCACCCGTGTGCACCGACATTTCAGGGTTCCTATGTTATCACTTTTAACTTCGTTGGAAAACGACAGTGTACCGGTCCTGTAGACAGCTATGACAGATTACGGTTACAACAGAGCATCAATGCTGCAGAGCTTCTAGCTTTCGGTATTCGATTGTGGACCGTTGGGGGCATACGGCCGTTGCATGGGTTTTGCTTCCACGATATGTTGGTGACGCCCACGCTCCCCATAGCGCAGAAATCATATACCCTGTCGCTGGTTCCGCAGTTTGGACACCCTACTCCCTGATCAGATCACTCGACTCGACCTAATGATAACAGCCCTGCCTCCATGAGACCATGCCGACATCGGCTAGTGTACAACAGACCCTCTTAGGCGATTTCATTCGGGTGTATGGGACGCCCCATCTGGAGTGGATCACGTGCCAATCAAAAGTGGTCGCAATGGGCGCCCTAAATACTCTGGCTCACCTCCCCCCAGGCGGGCTATGGCGATGATGACTCCGAGCGTCTGGCTATTTTGGGTCCACTAGCCAAGGTAATTGCCGATATTAAGGGGTCCATACGATATGTTACAAACACCGAGACGTTCGAACCAACAGATCACATTTTTACACGAAGGAGTAGAGTCAACAAGTTCCGGGGCACCATATAACTTTGTATTCAGCCCCAAGCTATGATGCAACTGAAACGTGTAAAAGAGGAAAAGGACCAACTGGAGCTGGGATCTTTTTTACGCTGCGGCTAGGAGCTATAGATCGCAAGGGTACCAAAATATAAAAGACAGGCTGGGGAATGCTGTGCAGTGCGTCCTGAGGTACTGGAACGCGCGGGCGGCAGTGTAGAACTGGAGGGGGAGCCAACAGGGGACCCGTAATCATGTGCTAAAGCACACTCGCGAGCCGTCCGAATCCTTCTCACATGTCTCAAGTGGTCCGGCGCGGCTATGGACACGACTTCTTTTTTGATGTAGGTATCAAACTCATGTGAGGTATGCAGGCCACTCGGCCACTAACATCCCACCCAGCTTAAAGAAAGCACAAAATGTCGCGGAGCTTCCCCCCCTACGATCCAGGTTGTCCTATGTATGATCAAGGCCCATGGGACGATTCACTGAGTCGAGTTTCAACACAGGATGCACAATAAGGTGACCTAACTCGAGAGTGCTCCAGTTTGGATAACCACCGTGCCCCCCCTTACAATGCGAACTATAAACACTTGCGACAAATCCCTCTGAAATGATCGGCGGTATCGCCGCTCCCATGCAGGCTGGGCGAGGACTCCAGCAATGTACACTACAAAGTTGACTTAGACTCCGGTGCGTCCGATCAATCTGGTTGGTCCCTGTGTACCCTAAGGGTGTATTTCCGATTACTATGACACCGTGACAATACTGGAGTGGACGAGATACTACAATAGCGTAACACTTGTGCGTTATAATCAACCGTGGGCAACATTTGTACCAGGCGACGCTGCTGTCCTTCCCCATTCTTTTCATCTTCCGCTAAGGTCCTAATTGTGGTACGTTAAGCGATGCATCGGCGCTCTATACGGATCCTAATCCTAGGTAAGCGAGCAACCTTTTTCTCACTTCTCCAGTTGTCCAAGCCAACCTTAAATGATATATGTAATATATAGTAGACCTGTCTCATTCCGGCAAATTCGGCAGGCTTGCCCTGGAAGTAAACCCAAATTGGTAAACGGGTAGCTGTGGTAATTGTTGGGGGTGGTATTACATGCCAACCCCAAGGTTTTAGTTGTGTCAGTAGAGCCAAACAAGGAGTTAGAATTCGTTGAGAAGTTACGGTCAGGAGAGCGTAGCACCCACGAACAGTTTCCGTCGCCGTACGTCGAGTGCCGTGCTGGCTTCGAGTGGCAAAGGACCATAGAGCTATGGAGACACGCGTGTAAGTGGTACTAGGTGTAGGTCCTGCCCTGTTGGGCCATCTATGGTCTAAGGCAGCATATTGGTGGTTGGTACTCGAGTAATGCCAAGAGAATGACACGCGAATTAATGTAAGAGATCCGTGAGAAGCTCGCGTGGGTTTGTAAGACTTTTCCAGAGCGGTTTCTCTATTCCTGGGAAAACGACTTGTCTAAAGACGAAATAATTCCCTAGTTGCATCGCCAAAATCGCCATGAGCAGTATCGTTAAAACTCCACTACGCGGTTAAGATAGGTGGGTCTCAGAATCCAGATTATTTCATTGGAGTCTGTTAACATCTCCTGGTATTACTCTAATGTATTTAGTTGTCACGATTAGCCACCCGATTCGGTCGATAATCAAATCACTCTAATCCTAAGGTTCAGCTTCACACGAATCCTATAATCAACGTGAATCAAAATGTAGGCTGTTCACAGAACACTGTAGTCGACAATTCAAGAACATCGACATACGGCACGACGGTTCCCATTGCAGATATATGGTGGAGAGACTTCTGAGGAGTACCCAGAAACATAAGATTAGTAGGGTCTGCTCCGAGTACGGAGGATTGCCAACAAGACAGGAATTGTATAGAACGAGGCTTTATGTATACCCTCTTGGCGCTCTATCGAGTGATCCCTGGGACACTAGGTTCAGTTCAACTAGACAAATGTACCGAGGAGGTCGCCGACCAGCTGTATAAGCTCCCGATTATAACGTCATGGTATGTCAAGACATAGTTCCGGTGGGTTGGTGTGTGACATAGCCCAACCGGACCCGGCCTGTGGACGAGCTTTGGTTTCATAGTTCGGTGGAGACACATCCAACTGAGGCGTTTTGGAATCTAAGTAAGGAAGCTATGTTCCCACTCATGTTCCGTGGTGTTGTTCCCCCTTCTAATCTGGTGGTACCAGCCACCGCCGGAGATTTGATGCGCTTGGCCCAGGACGGTAGACCCGACGACTAGCGAGTTCCAAGCTATTCTGCACGACACTAAGCTATGGCTGGATAGCTAATACACCACATATGAAGCGCACGGCCGTGCCGGATTCAGATGTGCGCACCGCGGCTTGGTGGCTGCGACTCAAGCATCCACTCCTACGCCCCTGGGCTACTAGAAGCGGCGCGCAATATATAGCAAGTGCGAACCATCGGATATATACCTGGGTAGGTCAGCTCATGTGAAAAGGCCTCTGGGGACTTACCCATATACTAGTGGTATGGTCTTCCTAGATCATCTGATAATGGGTTGTGGTGTTCAATATAAAATAGGACCGTACACAATCGAGTATCGCATTCCTATTCCTCGAGATCACCACCCCTAGCATCTGCGATTGATGGTACCTATCTGGATAGGAATAACCACCTCCGTTTGGGGTTTCCTTGAAAGCGATCGGCTATCCGCCAGAGCGTAAGTTCGGAAATGTCGTAATGGCGGTCCGTGCTTTGAAGGAAAACCCGACGTACTACATCTTCACTAGGCGGGATTGCGCCGATGCGAGGGTGAAGTATATGCCCGCGACGACGGTGCTAGCCGACTGAAGAGGTTAAGATCACACCGTCGTATAACAGGTTCCTTTTTCTTCTCAACCGACACCGCTGTCCTACCTTACATGCAATAAAGTATTGGCTCCTTCCCCGGTGAGACTCAGCTAGGGCGTAGCCTCCTTGGCTATGACATCAGAAAACGCAGCGTGCATTTGGAGTTATTTGCGCTGTTAGCCTCATATGTATTGTAATCTGCTGTCTTGTCTCACAAGAGCCCACACCTCGTTTAAAGGAGGCAAATCTTGAACTCTCGGCGATCAGATTATGGCTTATGTCTATCAGCCGTTTCGCAGTACTTCCGACCTTTATAGAGAGTACTATAGAACGATGCGGTGAGGATGAGTTTTAACAGATGTGATTTGTTATGCGTGCGGGCAAACCCAGATTATATACAACATTCAGGACAGAGCCTTTATGATTTAATCCAGTTTCTAGGTAGTAGGCTGTTTAATCCTCTCAATAAGTACCGGCTCCTTAATTTAGATAAAGGCAGAGTGCCAGCGTTTGCACAAACACTGGCAATCAAAGACGGCGCTGCATGGTCGCACGGTCGCTCGCTTGTTTTTTTTATTGCTAAGAACCACGTGTTGCTCTGAGAACGCCCCGTGCAAGCCACACAAGCAATTCGGCCGGTCTCTCGCTGATCACGGTCGTCACGTGAAATACGTGCATTTAGTACAGAAGTGTCGCTACCGTGGACACGGGCAATTTTACCGAGTTCCCATACACTATGTGCTGCCGTTACCTTTAGAGAGTAGAGCTAACAGGATCACAAATGTGTCTCACGCCCCAGGCGTTTCCGAGCGGCCTGTGTGCGGACTAGACCCGCCTCGCCTATGGGGCTTAACTTACAACCTCCCCACCGGCCCCTGCATCATATTTACCCCGCACAGCAGTTCTTACTAGAACTCCATTCATGAAGAGATACCTGAACGGTGCCCGGGAGAACCTTTTCAAACGGCCGGGTCGTTGAAAGTAGCCAAATTACACCTGACCTCGGTTGATTTCTGTGTTAGGCGACGAAGTTTTCCCACCTACGACAACAACGTCTACCACGGTGAAGGCTCGCCGGGAGTAGTGCCGTAACTAATGGAGCTGTGTAACTGCACCGTGCCTCATCACGTTACCACCGTGACCCAGACGATGACGATTGAAATTATCCATATGTGCTTAAGCGCCGTATTATGCGTGGAACCGTGTCCCGAAAACGATTGGCAGCTGTACCCACCTGCTAGCTCATACAGCAGCCAATGGTGAGTTAGCTTGGTATTCGACAAATTTGCATTGGAGAGTCACCAACGCCAGTCACCTTCTATCTGGACTCAGAGAGCAGCGTGGAGCTCGCCCTATAGACAGACTCGATCTTCTCTTACCTATGGAGAATCGCCCCGCCGCGAGGCGGTGCAAGATTGCATTACAGACCGGAGGCATGGAGACCTGCTCGAGAAAGGAACCGGGATTGGAAACCGAGTCACTGGCACAGATTATCTAGGACCCTTAGCCGCAGTGCCGCTCCACAAGGTCGTCGTTAATGGAATGTTGTAGCCCGCGTATTGATGAGATTAGCGAGGCTCCTGTGTTCATCACAGGCCTCCCGAATTAATTAAAGATGATGTACGGAGTGATAATATCATCTTCAGTATACAACCAGAAGCCGGAACTCCAACTCATAACCATCCAGAGACTGCCGCCCAGGTTGCTGTTCAGCTCCCCGCTTAAAATGTGGGCATAGGTGTTGACTCGAACCTCCAATGTCAACAAATATTGCTTGCCCCCGTGTTGTATGCGAGCGTGTTCAGTTCTCTCAGGATGAGATTTCGCGGCGATGGTCTTAATGTATTGGGTCATGCACTTTAGAGTGGTTCTCAGCATCTCCTGTTGAGCTTGGATGGCGTGTGACCCCTATCTGTGCAAGTTCTCAATTAGAGTAGGGTTATGAGATAGGTGCGCCCTATTACTTTCAGTCTCAGCAGGTCAGGGGTTGACCGGTGAGAGACCCCACTGACATAGTGCCGCCATAACCGGACAGCGCTGCGAGCAGAAAAAGTACTTCGGGGGCTATTGAAGTTGACGGTACGAGCTTCCAGTATATTGGAATGGGCCCCATTCGAGTCATTCTATTCATGAGGATTTAATTTCGAACCTTATACAGACTTACGCTCCGCTAGTGGCTCAGCTAAGGTTCATCGGAGCCACGTACTTACGATTATCGCAAGATACTCCCCCATTTGATGCCATACTTGCCCACCGCACGTTGCTACTAATGATAACAGCCTCGCCGTTATGGCGCCTAGGGAAGACATCAACCGCTGCAATGGGCAACAGATTTAGACTGTGCGGCACCAATTTCCCTGGATATCCGTTACAACATGCCGGCTCTCCGACAAGATTTGACATCCGCATCTCCTGCTGCTTCGACTGTCTAATACAGAGTAAGGGTCAGGTCATGTGTGACGGTTAATACGAGACGAAGGACAGGGTACGGCTCGGTGTGCTGCTCCTGCCTCTGAGCCCCACCGACTGGCGCAGCTGTCAGCCTTTTCCCATTTAGTCTGATGCTAAGGACGAACTCAGCAATCTACCCATGCATAGTAACCCCAAGATATAGATCCGGGAGACGTCTACTACACCTGATAGAGTGTGATCGTCTGGTTCATGCTAATCAGTGTCCCTCGCAACTGGGGCTATTCTGGTCGTACCAGGCCTAAGTCAGTGAGCTGTGCCTTGGAGCCACCAGGTAAGAGTAGTGTGCTTACACATGTTACGTCCTAGGGGGGACGCATGTCTACTCCTGCTCGCCTAATGAGAAGACCCAGAGACCGGAGTCTAGCGCGACCAAAAGTTGGGTATGCCAGCCCCAAGGGCCTCCTGGAATCTACATGCAAGATCGTTACCTATGAATACCTTCGCAATAATACTCAGTACTCGGTTCCAAACGTCAGACAGTAAAATATGAGACCCACTGGTGTCACTGACGTGGTTGTCTAGAGTAGGCCTCGACCCGCAATGCACGGCCTTCGTGACGTTGGCTGAAGCATATGGACTGTTTCTCCGCAAGTTGGGTGTGATTCCCCTTATAGGGTTAATGTAGGAGAGAAGAGTTGTGCCTTTTGGGTGGGTTTCACGCAAAGTTAGCCTATTATGTAAGGGCCACCCACAAGTCAGATAGTTTGAAAGACCCGAACCTAAATCGCACTCGGCTCACGTTCAAATGCTACCGGCCACCGGGATATTATAAGCGTACAATGCTCCAGACCCCTACGGTAAATAGGGGTTGTTGCACTGCCAGCGCAACTTCGTGATGGGGCTTGGATTTCACATATCTATCGAAGTCTTTGTTGGAATTGTAGTGGGGTCGCGCACCTTCGTCCATCCTCTTTGCCGGAGGAATGTGCTGATGAACGTGGGTGTAGCACATCAGCTGTATGTTCGGCATTACTGGAAAAGTCCGCCTTATAGCGTTGCGCTAGCGCAGAGAGAACGACTCATTAGTGTGGAACCCGGCGAGGAAAGCGGGAGGATAATAGCCACATGTCCGCGCTCCCGAGGGTGTAACTATTCGGGTCGTTGATAACAACTCGATTGAAGACGCAGCAGGAAGGGCGCATCCGTGGGACTGTAAACGCCCGGGGAATAAGCTTTCAGCTGTGAGTGCCTTATCACTTAACGCGTGAAGGTCCGTTTTGTGTAAATACCCGTTCTAAAGAGTGGATGCCTGGACGAGTCTGTCACAGATGCCCAATCACCTTCTCGTAAGTCGCGAATTTGAACTTGGTGAACTGTATCTAAGATGCGCCCTACCACGGTGGGCGCCGGGACTCCGCTAGTTTGACAGCATGTAGATGAGGGGAGACTCTTGACTGACTAAAGCGCTCCACTTCCGGTGGGCCCCTCGCGCCTCGACATATCAGGATAACAAGCCTCACACTGATCATCGGCTGTTAAGAAGCGTCGGTGGCATTAGTGATCCGACATTTGTCCGAGTTTACCTTTGACCTCGTAGGTTACTGAATAAATACAAAATTATGTTAGGTCGATGCAACGCAAGCAGCAAAGAATTCGATACCCAACTGGACGGCGCCATTAACGCTTCATTAGAAAATTTACAGTAGCCGACTTCTATCTCAATGAACGCCCCGGCCGTCACTTCAAGGAGAAACAACCGCTAATCTACAGTGCTTTTACTATCGCACCGGACCCTTCCACGCCGAAACGAAGTCATCTGATGTAAACGTTGGTCCGAGTTTAGCGGTATTGTCTTAAGCGTTCTAGCGGACTTGTAATTTAGGCAAAGCTGGCCGGTAAGGCCTTTCTGTTCACGACCTGTTACCTTCAGTCGCGGCACCCGAACGACGTGGACGTCTCGGAACGGGTATCAGATATAAGCTTATACCTGTAGCAGTCGCGAGTTGACCCTACTTCAAGATCGCATTCCGTTGCCATCCAATACGAAGCTCTCTCAGTCCATATCTCGCACCGTACTATGGGGAATCTACTACTCGGATGTAGTCCATTCAGCTTGTAGGGGGTCATGGTATATTTAATTCTCTACCTCAATCGTACGTTGAACTTACCGGTTGTTTCGTCATCATCGGTTGTACGTGGTAGGTATTTGAGGGCTGTCTGAGTCGCGACCTAAGTTAAGGTTCCGGGCTTTATATTTTACCATGGCTTTTGGAATTTCCGCACCACTAATCGGCTCTCAGGCGTTCGAAAATTCAGTAACGACAACCTAGCAGCGCAGTCTCTACGCTTACCAAGGGGCTGGGACTGCCGCAATTATAGTCGGGTTTTTACATCTTGAAGTGGCGTCATATAGTGTGCCTTGATGATGCTGCTTGCTTTCGCTTATGGTGGAATTATCTCGGGATAGGGCAACAGAATACGTGAGCCCCGTGGGGAAGGCCTCCATGAGAGCATGCGCCTTAAGCCTTCATGGGAATTTGGACTCAAAAAAATATCGCGTAGTTGAGAGTTCCTTTTCCACGTTACAGTGCCGGGGCCTTTCAGACCGGTGCTTCGGAGTGGTAGACGGCTCGAGGCTGACTGACCACGGTCGACCCATATCACAGGTAAATCTGGGGGTATTGAGTGACCTCACGGTTCCTACTAAACGTGGACGCTCTTATAACTGGACGGTGGTCTCAGCTAGAGGGAGTTCGGGGGAGTACGCTTAGGAGTTTTGCACGACAGTTTGTGTTAACTGTGAACGCGGTCGCATGACGGTGCACGCAGCAAGCTCCTATGGGCGATCTCTCTGTGTTTTACTAATTTAAAGCAGAGCTTGACCAACACTAGAGTCATCCCTCGATTCTCACTGTCATAATACGAACTCCATTGACATCTACGTCATCGGTTCCTCGATACATATCTAAACGAGGGACTTTCCAAGAGTCCCAGCCGTAGTCGGCTACTAAGGACCCGCGCTTTCCCGACATGCCAACACATCGACGACGGACTAGGTCCGAGCTTCATGTGTGCCACCAAAGTCGGCTAGACGGTGACCTTAAAAATCCCAACGTCAGTCCGCGGGCCAAAGCCGGCAGTTCAGGGGTGCAACCAGGGCTTGGTGGGATAGCCCCACTTAAGTTATTTTGGATAGCGTCTGAGGCGTAAGTCAACTAGACGTGAGTTCACCCAGGGGTGCTCCTATAACCCAAAACGAGTATGGTGCAACGTCGTGCCTTAAGACATAACTGCTCCGGAACGTCCATAAACTTTGCGTCTGCCCAGTCGTACCGTGGCGTGATCCTCGCAGAACCGAGATCGAAAACTCGTACTGACCGGCAAAACCACTGTGCGTTGTCTATGATATTCGCGACCTCGGACAACCCAGAACCAGCAATAAGGGGGTCCGTGTTGAGAGAGCCCGCATAAGAGCCGCGAATTATGCAGGAGTTTACTCGGGTTACATCGTGCTGTGACGTAAGCTGAGATAGGAGAACGGGCAATATGTTAACCTCCCACGTGCGTTCCATTATAGGGTCTCTCTTCCCGCGCGCGTAATCCAGAGGGGTCCGTGCGCATGGGTAGCACAGGACATTAGGTCGGGAACGATGTTTCAACCACCTATTAAGGCGCAGGAGCGCCGAGACAGCTTTCGAAGCATATCTAATGCTTTACGGGCCCGGGCAGCTACTACTTTACCCCCGTCTAAAAGTCTTCCCTGCCCGGTTCATTCTAACCAATCCCGTACACGAAATGAATGGGAATTAACCTTAGGGAGAATTTAAATTTGAAGGACGCACTAGAGGAGACATCGGGGGGAGGCGATCCGGTGCAAGTGAGTTCGTCCACGCCACTTGATAAGATAGGTTCATTCCATGACTTCCGTATCCGAAGAATGCTTCTTCGAGTCTTTACCGTATTAAAATTATATCTTCCGGGGATCTTCGGACGTGCTATACGTTCTGGGCCCTAAATAGCATCCGTACGGATAGATTTCTCCTTGCTCGACGAGCTAACTTCCTTTAACCCCACCGTAGTCAATGGCAACCAGTTCCTGTGATAGGTAAGCAGTCACCTGTATGGCCCTCTGGTGTCAACGATACATACTTATATCGTTGCAACAAATAAGAAAATGCGTTCCATCCCCTACTAATTCGCCCTAGAACCTTCAGTACGGGACCTCTAGACGGGTGTCAAAGGCTCGGCAAAGTTTTTGGATCCTTATATCAAACAGAGATAGTCAACATGTCGGGGAAGGATTAAGGCTCCATGCTCGAGCGTTTAACTGTCGTTGCGTGATAGTGCAGTCAATGATACATTGCGGTACCCAGTGTCAGGTTGGGATTCCGTTTAACGACTTAGTTCGTTTCCGTGCAGAGCCCACAGTCGATTCGCTAGTGTCAATTCAGATGCGGTGTCGCCTAGCCCCACGGCCCCTATCCGGAATGAACCGAGACTCTTACATGAGGTAGGTACGTTAACCGAATTAGCTCGCTCTCCACGAACACTGTCTTCGCACTTCACCTCGGGTATAAAGACTACTGCGCGACAGTAGCTGAGTCAGGCGTTACTAGTGTGTAGCGATCTTCGAAGTCTATGGTGACTCAGTCACGCTTGTAGCTATGAAATAGGAGAACGGGGTGGATTATATTGAGCCAGCCAGGTCCAATCTGAGGCTTTTCTCATACGACAACGCTGAGTACCACGCCCTAATCCATATCCCCCCCCCATTACTTTGACTGTATCCCTCTTTATGGTTGCATTCGTCAAGTATTAACCGAGTAGCCATACGTCTCCCTGAGAGAAGCGCTTATGCATTTGATATATAAAAAGCGTCCTGGCGCGACAGACCGATACAGGCCCCGTCGCAAGCTGGCGGTGAGAATTGACGGTTCGTCCAGGCATGCCACAAGATAGTGTCGGTCGTATACGGAGCATTAGCGATCACCGAAAATGTATGGTCCTCGCATACCGCGAGACCTAGAACGCACTAGTTCGCAGGCATCTGACAGAAAGGGCTCTTTGTGGGCTTGGCTAACGGTAACTCGGCCCAGCGGTCCGATTCTGACAGCACATACTTGATCCGGGCTATACATCGTCGATCCAGCAATGGTAACCAACACAGGGTTTATCGATATGAATCCCCAAGTACAGTGCCGCAAACTGCGTTATCCACGGAACATGATGGTTAGTAGGTGGCGACCAAGCAACAATGACTGTGAGCAACACATAGGTTAACACGCTAAATTCGAGCAATTCGAGAGCGTGTTCCAAATTTTGTCTTAAGTATATCTCGGAAGTAAATTAAATTTCACGTGATCCCACTATCATATATCTTCACACCCCATCTCAGCTGCCGTGATACCTAATACGCTTGATGGCTAGCGATGTTCTATGACAACCTAACGTGAGAGTTGAGAGTATTCTTGAAGGTGGGAAAGTTGAGGCCCTATCACGATCTTTACCGGGGGCTTATCCAAAAAATGCCTATGAGTATATTGTTGCGAAGGTCTAGGTGTTGAGATTTGTTACAGGCCTCAGCGATATGGTTAGATTAGAGTCCTGTTCATTCTCCCGCCTTGGTGTCCAAAGAAGCGCCTGGAACCGACAAGGAGGGGCACAAGTCTGCGAGGCCGAATCAACCTTCAGGAACATATAGTGTTTATACGTCACCCTGGTACGACATGCAGCCGTCCTGCTGAGCGAAAGGCAGGACCCGCAGCCGGTAACTCAGCGCGTTATGGGAGCGTTAGCTAGTTATAGTACAATTTATTTGATCAGACTACGCCTCCTACGTAGCTCATCTAATGTCCACTTTACATACCCACAACAAGTACATAGTGGGTCTCGCTCAGGTTAATCAAAGTGAGTACGAACGCGTGTACAATGTCAGAGGAAAAGACAATCAGGCAAGCCTGTACCCCCATATGCTTACGGCCAAGGCGGTAGTTTACATCCCTGTGGATAAGGCAGGGGGCCCGCGTAACAGCAAGGTGCCCTCAACGGCAGATCTCTCGGCCTATTGGTCTTGCTAGTTGTGCTGGGTAGTGGTGCCAATTGACTCGCGGCTACAGAGAGAGTGGCGAGTGCAGATCAATCTCGGATCGCGGAGTAACCGTAGCTAAAGGCTCGTCGGTGACGAACCCGTGACCATTGTATACGGGAGTTCCGATAAACTTGTCAAGAAGTTATATGTTACGATAGGCGGGACGCGTATGACTTGCCGATGACCGTCATTCCACCATAGTTGACCGGTTTAGGGCAATGGAGCACACCCCGCGCGGTTGCAAGCTGCCGGCAGCGCACGCGGTAATGGCTCAGGGAAGAATATGGGTGCACTACGCGTAGGTGGATCGTTAAGGTGAAGGCCTACTACAGCCCTAGCTCAGACTAAGAGGCTACGGCGCGGCGCCGCGTCCACTATATCCGCAGGGGTCGTCGTTCCAAACCGGGGGATGACGGACTCAGGAGGGAGCCTGCCCAGACTGGAGGAAGACGGGTTATCAAGGGGGTACCAGAATTCTAATGCGTAGTTTGTAAGAAATCAAGCGAACCCCCACTCAAACTGCCAGGGTGCCGAAGGTTGAAGCATCAGCATATCCCGCATTTTAGTGATAGCTTGGACCTACACCTCCCGAATATCCTCGTCTAGATGAGGGCGAGCTACGCGGCAGTTCAATCGACGCCTCAGCAGTATCGCAAAGCGACTACAAACGTGCTCTAGACAACAGAATGTCGCCTTAAATATAATCGAATGCCGTCTGACCGGAGCTAACGTCGTCCTCTCAAGCTCGCCACACCCCTGACGCGACCCCTAAGTGCTGTCGGGAGGTCGACGCTATGTTAACGTCCGTAACGGCGAAGTTGCATACGAATATTATTTTCGTGCCTTTGTAATCCGGAGTACTTGGAGAACCGGGAAACTTATCGCGCACAGGTCATTTCCCTTATGGGTAACTACGAGCGATGAGCAAGCAGCGTGCTGCCTTGAGTACGTTATCTCCTACATTACTTGAGACTGTCCTTTGCGGGGTCCATCATTGTTATCTCTCTCCAGCTGTGTGTTTCAAAGCAGTTAAAACAGTCTATATCGGGCCTGAGATGTTTTTTCTCGTAACGCAATGGTATTAGGGCTTGACTCTTGACTCGTTCCAAAGAAATTTCACGTGCATGTCGTATGCACAGGGGTATCTGAATTGCGAGCAGGAGAAATCTCGCTATCGGTTGGGAAGGGCACAATATCATCTGCGCCTAATCCGTATGGGATAGTATGACGATCTGGCGCACATTCTTAGCGTGGGATAGGATGTGTCGAATCCAGTTCGAAGACTATACCTGTTCCATTGCCAGTATACTACAAGTAGTCGGCCAACGTTACCTGAACAGGATCGCTCATTCTCTGGTATGTTTTCCCCGATGGCTCGCCCCACTCGGATAAGAAAACCAGAGCGATTTTTGCTTCGAAACGCGGCTCAGCAATTCGCGGTGTTGTACGCATATGGTGAGTCGGTCCAAACATGAGAATTCGTGTGAGGACAGAGATATCCCGTCGGAGGTACGGTTACTTGTATGGACATCCAAAGTAGGCTACCAAGTTCGCATTACGCGTAACGTAGCCACCGCCGCATTTGCGTACTGCATGGCCCAGTTCGAAAGGTTGATTATCCCCATAAACTTAAGTGATCAACTCTCAGGTGTTATTTAACGCTGTTATGGCGACCGACCCCGGCATTGGGTGCCCAAATGTACACGGTAGCCCATGCCTGAGGCGAACATTAAGGGCATCACTGTCAGTTTAGGCTGGGGATACCCCGATTGGGCCAGAAAATTCTTCGCTAAAACCATTCGATGCCTGCTTGGATATTACTAATGCGCAGTTTACCCTTCCACGAGATCGCCGGGCTCAACCGTAGCTGCACGGAGTGGGTGGCTGTTTGGTTTCCGAGGACCCGGCGGTTACCCGCGCGGGCGCTGTGGGAAGCTACGGCGAGCCCCACAGGCGATTAAAATCTTTCTGCTAACGATGCTGGTAGTACTAAATTGCTGAACAGTTGAGTCGGTCGCTACTGCCCTATCCGCATGGGAATTCTGTATAAGTGATTTCGGACGTTTTGTGGCCCGCTGTAGAGCCGAAGGATATGGAGTTAGGTGTCCTGGACTATTTGTATCCAAGCTCGCGTTGACTTCTATTACACACGACCTCTCTGTGTTGATCAACGGGCGTTGACAACGGGTTTCTGTACCCCCTGCTCGGCGGAATCGGGCCCTAGTCCACTTACAGCGAGTGTGGGCTTGGCTCTAGTTCATGATCCGACCTAAGAATGTGTCCATGCCGCCCTCAACTACAATAATGGTCAGTCCGATACACTAGCCTGTGCAGTTAGTCGGTCTAAGGTCTGTTCGCTCAAAACTACCAGTTACGTTAGGGCACCTAGATCCCCGCACGCCGTGGTCGTCCACCCCGCGGTCGGACGAGATCCATATAACGAAAGCATAAAGCATTTAAAGTATGTCTTGCAGGGGTCCGTCGTTGTCGCCTCAACGTTGTTAATTTACATTCAGATGTTAAGGTTAGCGGTATAGCCAGGATAGGAAGGAGATTGTCGGCTTTTGCGTCCACAGCAGTTTACGAGTAGCATGAAGGATTAGCACAATTAAGTCCCAGTGCCATCGAGTAATAGCAAAGGTGCCCAGAATGCATGGTCACTAGTAGTGTTAAGAGGCGCCTATTTAGGTCCGAATTTAAATGACGTTGTGTGAGTGCATGCCTTAATGATTTGTGGTGTTAGGCGATATCCTCCGTAGCCAGCTTGAGGCTCCTGATCAGTGTGTGTCCCCATGTGGCGGGCTATCCACACCGGATCTCTCCTGGCAGGTTTAAATGCTCCGGTTCGTATTTGGTCGCCAGCAGTACAGATATAAGTGTTCTAACATCACGGTCCGCCGATTAAACCCGCTACTCAGTAAATATCCACGTAGCTGCCAGAGACTTCCTAGCGCCAATCTGGTAAGGACCCTAAGCGATCCTACGTGCTAATGGCTAAATCTCAACAACACTCAATGTCTCTTGAGTTGATCACTAGACCCCGGATGCTCCAGGATTGCTAGTTGATGATTCCGCATCCTAGACCGGTTCAAATACATCCCTAAGTACCGGGGTACGGCGCAGATAGCCGAGAATCGATGACCAATAGTGGTCATAATACAGCGAGGAGGGGCAACATGCTTCACTTATAAGTAAACAATGCCGGGGTTCCATATAAACATGCTTTTTTGGTTGGCGCAGTTAAATTTCGTCCGTAGTAGAAACGCTCGTTAGTTATGTTACGCCAGTTCGAGGGTTATGCTCGGTACATGTCCTGGCTCAGTCTCGCTCTTCTATTAAGTGGCAGGGTTCGAACAGGTGCCCTGACAGTGTTGCACATGCCTCGACGCTTCCCTTTATAGCACTACTACTAGGCTGTATAGCATCGGAACCAAGGTGTTCCTCGCCTAATTTGGAGCTCGAGAAGGGCGGCGAAACACCCAATTTGAAATACATCGTGTGAACGTTGTCGAGAGTTCGTAGTGCGAGAAACCGATCAAGATATTGTGTACAACGCCCAATAGCCTCCTTCGCGATTATTCACCATGCCTACTACGCGCCGCTCATAACTTGCAAAGGCGTAATTCTTATGATAGATTGCGCACCGTGACCGGTTCAATCTTCTTGGAGACACATGACTAATAGCTTGTATCATACCACTTTGACTTTCTTGCTTCAGTTTTGTTCCAATTAGGCCTTGTGAAGACGCCTGCAGTATAAATAGTTGCTATCATCCATTTGTGATATATGCCGACGCGACCCAGCTGCAATATTGGCGTGTCGATATCGTAAAGGACTAAGACCATCACGCAAGACCGGTTTATTAAATGAGTACATTGCCTTTCAGTCCCCGTCAGTTCGCGTGATTACTGCCCATTCTTCCATCCTGATCCGCGTCATGTACTCAAGTACCAGAATGTGAACGATATTCCGGTAATCTTAGTGGGGGAGTATAACATGCCGTCACAGCTCGCGTACGGTACAGGCTAAGTACACGTAATGCTAGTGCAAGGGGGCATTATGTCGAGTATCGTTTCGTGGGATTATAAGTCCCTTGTTTCCCTAAATTCTCCGCGGCGTTTCTGTATCATTAACTTCAGAAGAATTCCGCTCGTCCAGGTGAGTGGTCTGGTATAGAGCTCCATTACAGGAGTCTTCATTTAGGTTCTGGATGTCAAGAACGGACCAGGATACTTACTGTAGCATGGTTCAGCACACCCAGAAGAGCCCTAGGTCCCTGCGACGCCTGGTGCAACTAATATAGAGGAACCTAGATTATTTGCGTCCATATGTTGTGAAAAAGATGCTATGAGAAGCTATGGTGCTTGGGGGCGTCGCTAGTCGTGCATAACACTGACGAGATAAGAGCCCGGCGCGAGAGGATCAACAATAATCAACACTCGCGTGCCCCTTGGGACTCAGCAACGACGGGTGGCTATTCTACATCCCGCTGCTAACGCTCCACCGCACCCTCCCGGCCTTCTGGTTCAAGGGTGGCTTGAGCCATTAAAGACTCAACCCCATCTAAAATAAATATCTGCGTAGACACTCTAGCGTAACTGCTCGAGGAGGACTCGTACGGAAGAATACAGATTCGTCTTCTGTCACCCTATTTAAGAAGGATATGGTAAGTGCTAGATTAAGCGTAATAATTCGCCTAAGATCATACGTTAGCCGACCTTCATCAAGGGAACGGGGTCTTGATTGCGTAGTGATTCTCGATTTCACAGTCGACATATAGTCGTGGAGCCCATGTAAAGTCGTTGTCGGCGGTTTTCTCAGCCTCGATCTACTTATCTGGCCCATCTTTCGTAATTACCTGAGCGGCAAGATATATTACCCCTCCCACCCAAACTTTCGTTAACACTAAGGTCCGCCACGTAAGTTAAAGTTATGGGGGCAATCTACGCAGGCGCAGCCACCCAATCGTGACGGGTCTGTCGCCCACGGCCTGCAAAAGGCGTGGGTTAGCTCAGTATTTACCTACATATTGGACGTAGACAGCCCGCCGTGATGCACTCAGGAATTGGGTAGTAAGGTCGATAGCTAGACCGTTACACTGGAAACTGAGATTAGTTTGTGCCAGTGTGTAGTCGACACACACACGTAGATCTACTTCGTCTAGCCGCGCCATTAACAAGCTTCCAAATGTGTCACTGCCCATTGGGCCACGGCATCCTAGTTGCTTTTAAACCGCCACCCAATTTCTCTGTCCACATGCTTAACATGAGAGTACGTAAGTCTTGCCGCCTCACACGCGTGTCCACTGGAATAGAGCTTTTCATCGTTTAAACTATAAAAACATCTGCAGTAATCATCGATGCACCAACCTGCGCAGAGTCAACACGGAGCCTGTTTCGGGCCACGTCACGTATAGGACGCTGACACCTGAGCAGATCCAACTCCTGGCAACCCGCAATATAAATGGCCCCGCCGTGTGAGGTCGTGTCCGGGATAGTAGAGCCGTTTATAGCTATAAATATCGGTACCAATGCAGAAGTCAATCGTCGTCAAAGTATACAATGTTGTGAGTATCACAAAAGCTTCCCTACTAACAGGCACAGCGCCGCGCGCGGCAATAGGGCGTGCACTCGAACGAACCGCATCGCAAGGCACATGCTTTGCGCTCTACCCGTAGCTAACCATTCACACACCGAACTTGTATATCTCCATAACAAATCTGTTGGCAACTACAGCGGTCTCGAGGACTATTAGCCACTACGGGGGAATTCAACGCTTGGAGTCAGGATATACTACCCAAAATGACTACTTTACTCCTCTTTAATAGGCTACATAGAGGGCTTTCGAGTGTCTTAGCTGAACTCGATTTGAGTAACGTTAGGGACTAACCGTCTCAAGCCGGCTCTTGTTTCAAGACTCCCGCGGCAATACACGTCTCACCTTCCTCTGACTCGTGATCAATCAGCTAAGGGCCTCGGGCACAAGAAAAAAACCTATTCGTCTATCCCTCGCGGGGGAGTTGCGTCGCTGCCAGAGTAATGTTTATTGTCTTCCTAGGATAGCGGGTACGAATCTCGCCTATTAAGAACCGTCTAATGATTAGAAACCGTTTTACCTCTATTCGAGCATAGTTATGCAAATCTCGCCCCAATGTCCGGAACGTGCTCAGAAGATCTATGGCGAGAAGGGGAGTTTAATACTGCTGACTATGCGTCGGAATTAATTCTACTCAAACTGGAGTTGCCAGTACTCACTAGACATCTACGCCTCTGGCAGCGGATTAGCTTCTATCAACGCGCACCGCGACCTTGTTACCCTGTAACTGAGTACTTTCGAGCCCGGTGTTTCGCCTGAGGTTAAGTTGACACCAGACAGGAGGTGTTAAGACAAAGTGAATATCCTCAAACCACCTCAATTGCGACGGACAGGGTGTGTGACCAAGAGGGGGGACAAAATAGGAAGCTCTTAGTTCGAGAAAATGCGCTATTCCACACAGGCCTCTAGCGGTGTAGGAGTCTATACCACGCGTGTTCTCAGTATCAGACGAGTTGCATAGAAACGTGATCGGTCAGATAACGAGAAGAACTGAACTCTGGTTAACATGAGTTGGTCGGTCCCACTCTAGGACGGGTAGCACATGCACTGAGACCCGCGGGCGTCTTTACGGTTGTATAAAACAAAAAGGTCTAACGAAGAGCTTCAAGAGATCAAGGCATGTGAACGTAATATGAATATGTGACGAGGCAAAGGTGCCCTAATTGGACAGTTGATCAAAGCATGGACTGAGAGAGGGGCATATAAAACTGGGTAATCGACGCCCTGCAGTAAGCCCTCGGCCCGTTGTAACTGGCCTCGCCGATCAGTTTACCATCTCTCTGCATACTAAAGGCTGGTTCGATTACCTAGCGTTACCCGACCACCTATGTTGCCAATCCTAACCGATTGATGTAAGACAATGGTTAATTAGCCTCAGACGCACAGCTCCGCAAAGAGGCTTCAGAACTGTCATGAGTTCAACGCATTCCGGCCAGGCTCTGAGGAACATCCCTCATGAAGTCCTGGCAGTCTTCGCGACTTTACTGCCATCTCCGCTAACTGGTGCTCGGTACTTCAGTTAGACATGATAGTGGTGTTTTAGAAAAAGTGTTCCGCACCGATATCCGGCAGAACGCGTAAGCTGTACACGACATATTCACAAGATGCGGACGCTGTGGCAATAGTCGCAGAAAGTTTTGAACATGTACAACGACGATCATTAGCGCAGAATGGTGAGCGTCGGACTTAGCTCCCAAGCGATTTGCTAGAAACAAGATGGTCCGATCGACGACACGCACCCCCACAGGGCTGTTCTTTCTGGCGATGCAGCCGTATCGAAGCATATCATATAATTTATCATAGGCACGGGCCTCTCACCAAGGGTCTAACAGATCGACCTTGGCCGACCACGAGTCAATTGGTCTCAAAACGGTCACTGTAAAATAAGGCACTAACAACACGGGGACCGGTAATACGGATGCCTGCGTATACTCGCTATACGATCTCCGGACGCACTGGGATGACACCGTCGTACACTCTTCATCAGGGGCGGTCACCGCAGTGCTACGGTGTGTCTTTTTTCACGATACGTAATGTAGTACCCATTACACGGACTCTTCAAAGGAGAAAATGGAGCGACCGCTTACATTCTGTTAAAATAGTTAGATACTCCCTACCGGTATTATAGCTCACCTACGGCTCTACCACACCGGACTCCCGTTGTTCGGGATGTAAAGAGGGGGGTTGAAGTATTGCTCAATAGTACTTCGGAAACTTAGAATAAAATGAGGTCTTCTCTGATCTGCGCCTAGATCCAATTGATGAGCGGTTCCTGTGAAACGCGGTACAATTCGACAGGTGACCAAGAATGAACGTGGCAACCACTGCTCTGCACCACGAATGCGAAAACATACGGAGTCTCCGACACTCTAGGATGACAACCCATAACTTCAAATACTAATTCACGACACGGTCGGGGGGCGCGTACCGACGGAGAACTTTCTACAGAGAAGCCCTGGCAGACGTTGTGGGGGCCTACTCTGCACGTTGGCGTTAGACAAGGCGGGACCAGACTTAGATCAACTTGTCTCCACTTATCGGTACGATACGGCCGCGTCGCACCAATTAAAATCCTGTTAGCCATCCTCTGGATGGGTGAAAGGGACAATGGCGACTATATGAGGGGCGGCTAGGCGCCGCTTATGTCGGGAGACCGGGGCTTACTCAGAGGATGACTGAACTACAAAATGCTGAGATAGCTTGGCGGTTGCATTTTGAGGTAGTCGTTGGGGAAACCTCTCTTCGTCTTACGGGATGAGTTTTGGGCCCAACCCTATATTGGGGCTCGGTGGTTGCTATTACTATGTCCCTTGTAAAAGCCTTTAGAATCTGACAACCAAACAGCCTGTAGACTCGGTGTGAGCCAACAAGTAGGGCGGCAGTGATCCTAGGTCAGGCTATTGTATGTCAATGCCCAGGAGTTGGGTCCCCCATTTGGTAGACGTTATTTCGACTAGCTCCCGTCGTACTTTGGTAGACGGACGGACGTCTAGTGCGGGTGCAACCGGTCAAAGATTTTCAAACTCCTCTTAAATGGGAGAAGGGGTAACAATCCGCTTTGAAGGCATAATTCGGTACCCGACTTATACGCCACCATTAGCGCGAACTACACATCTAGCTAGCGGGAGCAGCCCTAAGTTAGAGAATCCATCCGCGATTACCCTATCGATCCCCATCATCCATTCTTAGTATGTCCCATCCGCAGACCTTTAACACGGAGAAAGGGCTCTGTCCAACGCATCGCGTACTCAACTCATGCGCGGTCACAGTTTACAGATGACTAACACGAAGTAGGCGTCGCGCCCTTCACGGACATGGGCTGTCAATCAAGAGGTTTTGAGTGCGCATCAAGCGGGTATCACCTTCGCATTTAGCGTAGAGGATTTCTTCGATTATATATCGTCATGCAGTTATCGCCAATGGTGCATGGTGGCCTTTTTTCGTTCAGGTTGATGCTCGCTCACCTTCGTGCATACTTGCTTGACGTTGTGGAATCGAACCGAGTAGGAATAATTTATATTACCTCGTGATACTACCGATTGGACGTCACCGAGCCAACGTGGTGTACGATGTAGCCCCCTTGCGCTGACCTTCCGTTTGACTAGGGTAGATCAAAACGTATGCTGGTTTTGCCTGGCCGTGAACCTACGGATACACACACATTTACGTTGCTTATTAGGGGATTCCAGGTCCACAGCTTGCTCGGAAGGGGCGAGTGAGCGTTCCTTACCCGGTCCCAGGGGGGGCCTACACCTGCGGTACTTCCTACCTCGTCGAGTAGGGCATTTGGCCCGCGAGATTCTGAGAGTGATGAGTTCGCTTCGAGACTAGAACATCCCAAAGGGGGTAAGCCCGAAGTGATCCGCTACCTACACCGCATCATCCGTCGACAACGGGGCGGTTCAGTGGATGGACTTCTGCTCGGATCGTTTTTATGGTGCTACCTTACGTCCTGCAAAACTTCCAAAAGCCGAGCCTCATATGTGCTCAGGACCAGCCGTGACCGACATGTAAGCTGCCCCTGTCCTAGATCTGGGATCCTACCAGACATAGAACATGTTTTAGGTAGCATTGAGGTCGTTACTAATACAAGGTTCGTCCGGGCTTGGCCTTGGTACTTAAAGTGATGTTAGTTTGGTCTAATCCACGTATTGACGATTGTGTGGCTTGACTTAGATCGGCGGTGTTTGCCAGGAAGTTAGATCAGTAGATGTGCAGCTAAACAATGGAGGTGTTCGTGGCCTCTCGCCACTCTAATGTTGCCCACCTAGGGTCACAGGGGTTGAAGCGGGCTTGGATATACGTTGGCACTATACGTCCGGAGGACAGTAATGCCTCTAGATACAACGGTGGGGGGTCCTTGTGATGTATGGTTGATTTTGGCCCACTCACTTCCCTGCACCGGATATAACTGTGGCGATGTCCCAAATTACTGGATTCGTACTGGGATAGCGCGCAGGTTACATAACGCTTGGACGAGTGTGTGTACCCTGAAAGCGCATACAATACTGCAGGCAATTGCTATCAATACCCGTGAAGGTAAACGTTTGCCGAAGGGTGATTCTTCTACCTCGTCTTAGGCGTTTTAGCCGGATCGCGAAGACAAGAAATATAATCGCTTTTTCGAAACGTAGTAGATATGAATGGGGACTTGTCAGTTCAAATTAGACCTACATAGGCGTTATTCACGCAACTGTAAACACTTCCGGCAAACTATACACCCCAACGTTTCAAGTCGTCGAGGTTACACCATCATTCAGCGACTACGGACTCTTGTATCAGCCTAGAGAGATAAGTGCGAACCAGTCTATAAAACGCCCAGCCCAGGAGCTTAGGGCTCTAGGATTCTTCGTTGACACCCGCGGTCACTAAATCTCTGTTTGGCGAATTAGGGTCAATCGCTTCTGCTCGAGTGTCCCGGTGATGTTGCGGCTGCCAACGAGGGGCCCGCCCCGCTCAGGTGAGGTGGGAACTGGGCCGTCCACTTTAGCGCGATACACATCTCTACGATTAGGATCGGTTTTTCATCATCAGATCGCTCGATAAACTATATACGGGGAACCACCTCTCCTGACCATATCCAATAGAACATGTTGCCTAGGATGGCGAAGATTGCATGTTAAATTTTTAGAATACACCCTGATCGGTCTATAGGTATGACTCCCTTGAGACGGAAAGGAGGTGTCCTCGTTGTGCCTCTATCACGCACTAGCAAATAAGACCCCCCGCGTTTCGGGACACTTGGCGGCTTGCGACTCGTAGAAGCTTTGTTTCCGGTTTATCTGCTCTTATTGGAAAGTCTTTGCTGAATCCTGCCGGGTACCATGAATCGCTATTCATAACCACTGGTTACGACACATCAGAGTTACATTGGTCTTGGCATGATATGGTGCGCTCTCGCTGTCGGGATCACTAGCGGCAGAAGCGTGGAGCCACAGCTTAGAAAAAACCACAAGCAGAAGGGCGCTAGCCACGTCGTATCCCTGGTTACACTTCCCTACGTCCCACAGTAAAGTGTAGCCCTATCGCCAAGGCTGGTTTTCTAATTATTAGACGAAGTGCAGGCCTTCGAGGATCCGGAGGCACCTTCTTCTGGTCGTATCCCAGTAAACGTGTCCGGGACTCAGGCATATACTGCCCCTATTAGGTTCTCGGAGGTCTGAAGCTAAGCAAAATATGACCTTGGTTACGTACCGGGCCCGGATTAATGGACATGACTGGTCATGTGATCCCTATGTGACTTCATCTATTTGCGACGGCCAGAAACGGTGGGTCGATAACGAGCATCTGTAAGACGAGCCGACACTCCGGCAATCGATTGTACAAATGGACTATTTTTGCAATGCTATAACCTGTGCGGACAAATGAGTTTGAAACATCAAGATAAGAGTTCATGGTAACTCACAGTTCAACAAGTATCAAGGTCCGTCTGCGCTCGATGGACAATGATTGAGCACGGTCATTTGATTGCCGCTGAAGAACTAGAACTACGTAACGTCATTAAACCACAACCGACACCCTCATTACTGAGGACTTAACTGGTCGTCGAAAATCATCTTATTAAGAGAGAGAGCGTGTGCGGTAGGCCCATCTTTCACAATATTACCTGCCCAAATCTAGTGGTCTATAATCTCACGGAGTAATGTGCGACCGAGCGTCCTTTGCCCTCCTGGTGGTGCCGACGCGTCCACCGGAGCCAACTCCAGCTGTAGAGCACATCAAATTTATGGTAACACAACAGACCACCTCGACAACGGAGGTATAAAGCTAACGTTAGTAATGGACAGATAAGTGTATCAAAGAGACGAAAGTTATACCCTCGGCCATGACTCAACGCTCTCACATGGTAAAGAACTTACTTACATTTGTAGCCCTAAAAGAAATCCACGCCGAGAGGTTAGTGGTAATTTCGAAGTCTGGCTGAATCACTACTCGACATGCCAACGTAGCGAATCACGGTCCGTTCGATGAAGTGGCGCACGGAAAAGTCTTGCCCGGCTTGCGCAAGACCCGCGCTCGACGGAACCGGCTTTCACACATGAACTTAGTTTACGGAAATGCGCAGCAGAGTCCGAATAAGATACAGACCCCGAAGCTCACCAATGTCGAGCTATAGTGCTAAGACAGACCAATCAATCGGTCTCTCTCATGACGATAGGAGGCTGTGCGCACGAAGGGACATCATCGACATGTTGAGAAGAGGTCTTTTTGTGCAATACGACTTCATACGTCAATAACTAGTGTCGGCGTCGAATAGCTTTTACATCTAAGATGTCTGTAGTTCGAATGTATAATCGTACGGCGCTCCGGGCGGAGACTAATAGCAATACTAGCGTCTCCATGTTCTGAATCGTTGCCGCTTCTGTCTAATTAAAATGGAAATTTTATTCGAGGCCCTAAGATGAGCAGTAGTAGCTCATATGGTATCGATAGTCGGTACGAGAATTAATAGTCGTCTATAAAACTACTCGATCGCGTCGGTAGAGCCCTGGGACCTCCGTGACGTGTAGCTGGTTTAGCAAGGCGCAGTATCTGAAACTCCAGTCAAACGTCAGCTTCGTAAGCGACTAACCAGGCAGATGTGAACATCTCAAGATGCTAGAGATAGAATCATGAAATCACAACTATCGCGATTTGTAACAGTAAAGTATAGTGGTAATAGTGTGCTATCCTAACCCAATGTCAGTGTGGGTCTGTCTAAATAACACCATGAAAGGTGTTGGAACCCCCCCTAATATTCTTGCCGGACTGGAATTAGTGTAGTTGTCTCTGAAGAATTCCCCCTAGACTGATAAATCATCGTCGTACTCTAGAATATCTATTAGATTGAAACGCGAGAGCAACGAACAGAGGCTTTATACCGGTAACAGACGCCTCCAATATTGCTCACGACTCGCTAACACCTACCACCCCTCTGTAGATGTGTTCGGCTAGGAGAGTCCGTTTTTCGTCTGGCTGAACGCCTTCAGACACGGATTCCCGAATCGCTAGCAACGCCTTCGCCGAGTCTCTGTGGAATAAAACTACTGTGCCAGTCATAGCACACGCACACATTTAGCATAAGCTTCGAAACCCTAGAGTAGCAAAGGAACCTTTAATTCGCCCAAGGACACGGTGCTTAATGACGAGAGTGAGTGCTCATGAGCCGACGGTTAATGAACCATAAAGCGCCACTCGATCTATTTGATGAGAGCGGGTATGCAGGTGAATGGCCGTGGATAACCAACGCAGAGGGAACTGCATCTGGTTCGTTTTTTCGCGGCCCATTCGACCGATGATAACAGCAAGAGACGGCTGGGACTCCTATACAAGTTCGGCTACACGATGCTTCCTTGGGTTGACTGAGCTCTGCACTATATCAGCGTGACAGCGGCCTCCCGATGAGCAGTTTTAGCTTAATGGATAATGACACTGCTTAATGTGGCACTAACCCATCGCGTCGTACTAATAACCGCTAACTCCGTGTGTTTGCTCCTACGGGATATCCGCAATTAGTTTGAGAAACTCCGGGCGGACGGTCCGGGCAACTAAATACTGGACCGGTTATATCAGTGTGCGGAATGGTAGTGCGATTTCTTCTCAGACACCGAGGTCACCCAATCGTTTACCCTTTCTCGTAACGAAAAAGCAGGTGAGTGGGTCAGTGTCCTTGCCGTAAAAAGACTCGTCTTACATGCAAAAGAGGACACTAACAATGTTCAAGGCGGTCCTGACCCCAACTTTCTGGATTCGTCGGTACTATCGTGCTCATATCCCGGGCCAATTTGGTAGAACGCCTGCGTCCAAGTTTACTCCTGCTTACCCTCCACTAAGGACTGCACGGCGTCTTGCGCTGAGAACGAAATCTTATCAGCCTCTCCTCCCAGCTTAGTGTGGTAGTGCTCGAACAATTGCGTCTGCCAGTATCATTTTGCAAAACGGCATAACACTCAGCCTCGGATAGGATAGGGGTGAATCTGCTGAGAGTGTAGCTTAAATAGGTTGGTTCATGTGGTAATAACCTATTGAGTATATGACGACGTAGCCCAGTGCCAAACAAGTTATTAGGGCATCAACATCGGCCAAGGAAGGTGCGTCCGTCTCCCCTAGGATATGGACGGCGTATATTAGTGCACCTTCTGAGTATACAATCAGTCGGGAGTCCTCGAGAGAATCGGCAAATCAAGAGAGGAGGTCGCAGATGGAATTGCCCCGTAACTCACAGCGTGCCTTCTAAGTGACGCATGTACGTGCGAGTCCGAGAAAATTCGAAAGCATGGAGCAAAGGAGACATGGAGAGTCCTTTTCACAATCTATGACCACGTCCAGATCCAATTGAACTTGCGAGTTGTGTAGTTTCCGGTAAGGTTCCCCCCAATACTAGTTCGTTCATCCAAAGGGCTTCATCTGTGCTGAGAGGGATTACCATGACCGTGAACCAGCAACATGTTACCGCGTGCATAGGAGGTCGAACGATTGACGCCATCTTAATCATCCGGATGTTTGACGCCTTCAGAAAAGAACCCTATGGCGACGTACCATTATCACGGGGGTAACAATCAGGATAGTGGGGTTGGCATAAACCATGCTGCAGTACGCCAGAAAACGCTGGGACTTTGCCGCGGACCTACGTGCATTACGCAAGGAAAAATCGGAGATAGCTATTACCCGCCCTCCAACTAAAAACTTAACCATCTAATATACCTGATCAGATTGAAGGCCAGAAACTAAGTCCCCGATACCGCATGTAACGCAAGGTTAGGTGGCTTAGATAAACAACTAAGTCTTAATGATTCTTCGAGCCCGTTCTTGTAATGACTCCAGTTGCTAGGGGCGATCGGATGACGCCCATCATCGTCCTCGCCCCAGGCACTAATCCTTCCCAACTAAGGGCCGAAACGTATGTCCGGCCTTGACGCTTTGAAAGAGCGCCGTAAGCAAATCATGTTGGCGGGTCTCGATGATATGTTCGTTAACAAGTGGAAGACCGTCTCAATCCGGTAGCATCCCGTTTAGGAAATGGGGAAAGTTCGTGCCGTTGAGCCCTGCGTCCCGGATCTGTATTTCAAACCCTAAAACGACTCCTTTTCTTCGCGCACCTATTGCCGCGATTATATACTCTTTGCGGTTGAACCATAGCAGTAGGTTCACCAGGGCGGTCCGGGCTAGTACCGCATTGCATTGTTTTGGAACGTTGAGTGTGGCCACGTGATGCTCCGGGCATGTCGCCGGCTTGAGGACCTAACCATAAAGTTACGGGCATAACCCCAGTCCTATTGAGTTCGACCGGTTTGTTAATATCAGTAATGACGATCAGTACCAGCTTAACAACCCGACTCGACATCACCCTTTTTTTATATACGGTAACCCATTGCCAGTAATCTACCTCGCACTGTGGCGTGTAGGGGTCCCCTCAGTCAGGTCGATCAACTTTGATCGTGCATCCTTTGCTACCAGCACCGGTGGGGGTCCGCTTAGCACGCATCTCCAGATTTTCCCCATTCTGGTTTGCTTCGTACAGGCCATGGATGGGGTGGATTCTGTCGCACGGACACTCATTAGCCCGAAAGATCCAGGAGACAGGTACGACGTGACATATGATGGGGGCTCCTGCGACACTTGAAACGACAATCGCCCCCCAGATGTTGAAAGTGCAAGTTTGACTGACCCTTCAGGGGAAAATTTGGCTCCGGATGAACAGGAGCCTTCTCCGTTTATTGAAGATACGGTGTTGATTATGAGAAGAGTCCGTCTTCGAACGGTTTGTGAGCAGCGCGGTGAACCGGACTCGGGACGAGGGCCGTCAAGTAGGCTTTCTAAAATTTTACCACGTGATCCTCAGATGGACGTCTTGTATCCTAAAAACAACGCTGCAGAGGCACGCACCGCAAAAGTCCTATGGCGACAGGCGTGAACAATTCCGCTAGCCTTGAACTTGGCGAAGGGTTGGGGTCCTTTCTCTATAGAGAGGGCGCAGGAATGCATCACACAATCCCGCTAGATACCAAGCATCACCGAACCGTTCACCGTGTCTCAACTTTGAAACCCGCCCGAGTGTTCTACGCGTGTACTATTTGTACTACTCTGCTAGAAGCGACCCGAACCTCCCACCGGATGTACATGAACTGGCACCAGCGACTAACGAAAGATACCTATAATCTTGAGATGAAGGGGTCATAGCCACTCAGAGTCTCCCTGCGGATATCTTGCGGTAAGTCGACGCCGGCCTTTAAATGCAGTGCGTGATACCAGCTAAGTGGCACCCGGTTTCAGGAAGGGAGCTTCCGGTCTGGATGGGTGGGGAAGTCTTAAGACTTTGAAGTACTATGTTTTAACGATAATCGACCGGATCAAACCACCGCTCACTGCTCGGACATTCAACAGTAACGTACGCTATCTTCTACGGCGCTGGCTACATAGCCTTATTGCCTGACAAGTTAGGATACTTTTTGCAAAGGCTGAAAAGTTACGAGACCCGCATTTCTAAACTTCTAGAGATATGCTACTGGTAGCATTGCGTGGAACGAAAGATCAAAGTGTGGCATGGAGTCGCCATGCCACCCATTCAACTAAGTATAGCGGGGACCGTTAAATGGTGAAGTCCCTGAAGGCCACCCAATTTGCCCATGTTGATAACTACTCGAGCACCGCTCAGCCTTTCTCCTTGCGACTTGGAAGCACAGTGTGTCCGGTCCCTAGCGAAGGCGGAGCGCGGAGAATGCGAAGAGGCCTACCTGCCAGCGATTTAGAGCCTCGCGGGAGCGGCATTAGCGAGATCGTACCTGTTCAGGTTGCTACTTAGAGCATCTGGAGACAGATGGACGAATTAAACCTTTAATTTCGATGCGTCGTCCCTCGGTATGCCTCAGCCCGGCGTGGGATGGACCCTGCGTTTATCACAAAATGGCAATACCTATGCGGCTCAGGTTATTTTCAAGATAGCCCCCGTTCGTACCCGTACAAACCGCCCAAGTAGTACCGCTCTGGTGAAACGCGCTTCCTCTATGTAATGCTGTACCTTAATCGTCTGCCGGTTAATTATTGGATGTCTCTGAGTAGTCATACCCTGCGTTCAATCCTCGCGTTTTTTCCCGGAGCTTCATCAACAGCAAAAGGAAAAGTACATAGTACTGTACTGAGGGACAGAAATGCTGATACAACCGTGACAAACTGTGGGTTATAAAGAGCCACCACGAAACAGGATTACTAGCCCCAGTGGCGTTTGTACGCTCTCGATATTAGGGATAGAATGTATACCAGTTTGTCTCGTATAGACCAGCATATAATTCGCAATCCATTACATGTGTCAATCCCGTACTTTGCACACTCTGTAGTTTGTAGCAAAGGCTAACCTAGCGTCGCCAAGAGGCACTTAACCGCGATTTGGCGGCATTGACATCTAGAGTCTATCCTCACAATTCTACGCGCTGGCTACGGCTGCTGAGTCAGCAACGCCTTACGTCGTCCAGCGAACCACGGGTTACCCATTCAGATTGCCCGGCTGACTGGAAAACGTGGTAATTGCCGTACTCCACTCGGCATTAAGAAAATGGCGACGAGAGAACTTATGTAACCGTTTCCTTCAACCCTTAGATAAAGTTAGCATCCATCCATATGTTGAAAGGGCCTATAAAGACGCACAATGAGGCCGTGAGTCTTGCGGTATAGCTGACTTGACGGCAAAGTTACGCAATTGAACACGTCTACTCCTAGCTCCTTGTCAGTTAGTGAAGGACGACTCCTGTATTGACACCGGGCAGCTATCTAAACAGAGTAATGCGATCTTGTGTACACATTGGGCAAAATTGATGCGTCTTATGGTCTTCGTCACCTGCCCGTTTGGCTATGTTTAACATGGGCTGCTCCAGTATAGGGCGCCAGTGACAGCAGAAATTAACCAGTCAAACTTGCCTATACAGGTCTGATCGATCAGAGCTGCGTTGAAGTAAGATCCACATTAGCAGTGCAAAGTGCGGTGCTGCGCGGGCAGGTCTGGATTCTTCGACCTTCCACTCTTGACATCAAACAAAGGGCTGCGACAGGGAATCTTAATGGAGTGATCTTTGTACGAGTTTACCAGTATATCCGACCTCCTGATCCTCCCCGATGTGAGTCGCTACTAGACGGTAGGGCAATCGGTCGTATTAGAACCGGACTGGGTTTAGTTTAACTGGCTGACAGCCAGCGGGCCACTGGTACGCTAGAATAGCCGACAAGGTGTCGTAGATTCACTTAACCGGGAGAAAATACGGAGTCATCTTATGCAACATAGATGCACGTCAAGTCCTACACAGAGCCATTCAAATGAATTCCACTACGTGCCAACATAGTCGTTTTGGAACGAGCGTAGCGACGTAAATGGGCTCTCAGATTATAAAGGAATGCGGCCGGACGTACTTCCCCATCCGAACTGCTAACAATCAAGGGAGTCGGCGTCGCTCAAAGGGATCTGACCTCCTACTATAACATCGGGAAGCGGAGCAGTTCTTTGCATTATATGGACTCCCTATGTAGGCACGAGCTAGGAGTACATAACAACGATCTTTCGATGTTCCTGCCCATAAATGGCAAGACCGGGGAGGATATACCGATCACGTCATGGTTTTAGGTAAGATTTACCTGAGCAGCGCTGTACGAGTTGGATGCGCAAATTGTTCACGTCATAAATTGTGCCTGCTTCCAGTGCGGTAGCAATGTCTAACTAAATTTGGCTTGTCTGCCACTGAGCCACACCATCAGTCGATAAAATTTGCAACGAGCATCTTGTACAACAATCTGGTAAGTTACCTCTTCAACCAAGGCGCTACGAGTTACTAACAGCATATGTAGGATATAACCTAAATGTGGTTAAGAGTTCGAAGGTTGCGAGGTTGTGCAATTTATAACTACAGCGTTCGCTACTGAACCTTGTTTTTACTTACCCAGTCGCCTAACCCGGCAGTTGCGACTTGGATATAGATTAACTGCCCACCTACCGATACGGCCGCAGTTCCGGGTAAAATCACCCGTATGGGTATTAAAAAAATGAATAACACGTGACGTGTCCTGGCTTCAAGGTCGATGGGATGGATCCTAGCATTATCCTTATGGCGGTGATTCATATTCACAGCGTGGCCGCATAGTCTCTAACCCGGACGGCAGGCGATTGTCCCAGCCCCTAACCTTGAAATCGTGGGTGGGGGCGGGAATATTCCATCCTTCGCTCCCCGTCGGGGCGGGAGATCGGGCCATATCTGCCGTAAGCGCCACCCGGCACATAATACTTAATGATAGTCTCTAATTACACGCCAGCAGAGCGCTTGAAGCTCTAAGTCTAGAAGTTTGGTCGCGATCTCCTTAGCCGCAATTGGTCGCGCACAGTCTTTCCGGGGCAAACGAATTCTATTTCCACGATATAGAGTGCCAGGGATACAGAGTCACATCACTCGGGCCTTCGATTCGGCTTATAACACGTTAAGACTTGATAACCCCTTCCCCGTTCACCGTGGCCGCACGGTGACCAGTACAGTGACAGCCAACACATATCATCTTACTGTTACTACGCCGACCTTCGTGTGCCCGCTCGATTAAAAATGACTTGAGTGGTATAGTAACGGCGAAAGTAATGTCTGGATTTCTGGTGAGTAGTAGCGGGTGGGTTTCTACCAGCGGAGACACGCGCGGATTGCGGACGGAATGTGTTCTTGATGCAAATGGAAAGTTGCGCGGAAAGAGCTATCCGCTCCAGCTACACGTGGACTGAGTGATGATCATATCAGCATAGCCACAAGCTCTACAACTGTCATAACGACAGGTGGGGTCCGGGTACACTCAACAATACTGGAGGCCTAGGAGGGTCCGCAAGGCCAATTATTGGCCCTCCAGCACAAGCGTCATAAAGCGGTTGGTGACGTTCACATACGAGACGATTGTCCTATCAGACTATTATGGCCCACCTAACTTAAGACACGCATCCTTGGGGGCTAAGTTGGAGTTCGAGCGTCAGACATCGCACACCGAAGCAGTCAGCTCTAAATTTCGAGTAGGGTATCATAATTTCTACGTACCCTATGGTCACGCGCTTTCGAAATGTCTAGTGCAGACCGCTGTATCAGCGGCCTCAAGAGCCGCTGTAACGGTGGCGAGAGTATGCTAGTTTCGCCGGCTGGTCAATTCCAATTAACTAAGTGGGCGTCGAGCAGCGCTGCCACTATAGGCCACATGATTCATACCACATACCATATTCAAAACCTAGCTCGCCCGCGAATGACGAGCCATAACTGGCATACGCAGCGTCGTGTGACGGGGGGCTACATGGTAGACTGCATTGACCGATTCGTAGCGACGCGTGTTCTAGGGACACGGCAGCTAACGGTCTGTCACTCGACTTTGTCAAGAAGCGGTGCGGATCGAGGTATTCTGCTCGATCATAAGCCCCACGCACGAGAGTCTGCGAAAGAGGCGGTACCCTGCACCATACCCGTCCGCACGGGGCGTCCTAAAACTTAATCAATAAACTTGCGCTAGGCTAGTGTGTAAATAGAGAATTGCCGCGGCTCCAAGCTAGAGGACGTTTCAAAGCTTCGTGTTTATGCTTCCGCGCCACAACACGTCGCACGACTAGGTGCGACGGAATTGTACCACCGTCATGAGAGGTGAGGTGTCCTCTAATATTTGAACGTCTATGAAGATTTGCGCCGGTCATCATCGGGAGTGTGTCGCCTCAGGATATGACGTAGTGAGAGATTAGCAGGTCAGTGTGATTAATACCCGGCCGTTGGTGGGCTGTTGAACACAGAAGATGGGATAATATACCACGTAAGGCTGTTAGTCTCTGAGGTGGTCAGGGGAACGTGCCTACCCGTGGACTTCTCATACATCACTACGCGCGGCGAATGCGTTTCTTTACCTTAGATTTAGTCATACAACAAACAAGCATGAAGTGGGGGTGAGTTCTGATTCCGTAAAACCACTTGCGAACGAATGTATGTAGATCCCGATGATGCAATGACTTGTCGTAAACGTTATCATTTTAGCCGGCATCGTTATCTGCTCTACCGCCTGCTGTAATAGCAGTTAACCGCGTGTTACAGAGAATCAAGATGCTGATATGTAGTAACAATGTGACGTGGGGTAGCCGCTCCTTTAAACGGATAAAGTCCCATAGGAGCCCTCGCATTATCGATTTAATAGGGCTACCGAAGCTACAATAGTCTAAGACGGCTTAGGACTGGCATACGGAAAACCCCGAGATCGTTACAACAGGGAATAATATCACTAGCCGTGGTGCTCGGCAAGCGGAACATATTTTCTACCTTTTAGTGAGGTCGACAGCTGCAGCCGCTCAGCAGCATTTGGATTGTCCCCAGCAGTTCAGCGATCGTCATTGTCATCTCCAAATCTGAACTGAAATGTAGACGCTTCTGTGTCGTGACGCCCTGATCCCCCTGATACATCGCCTGGGGTGACGCAGATCGATGTTAAAGAATGAACCAAACAGTGAAACTAGGACCATGCCGTAGGTAGCCTATCGCGCTTTATATAGTAACGGTGTGCCTTCCAATCTATGGGACGTGTACATGGGCTCGTCAGGTTTCTGGTCATGCTGGAAAAGTCCGCGTAGCAAGGTCGCCTGCCGCATGCTGCCGAGTTTTTTGATCCAGACCCTTGTACATGCTAAGGCCTTCCTAGTTCTTCAGATATTTGTAAAGAATTGCTGTGGCAATGAACCCCATGATCCAGTTATCTCCATAAGCACCGTCCCCCACACCTGGTTATTCACAAGAATGCTCAACCCACAAGGACGTCTATAGTAATCGCCGTGGCCGAGGGTCCGTGATGGACTGTTGTACTCAGCACGGTTGGCTGTATTGTCGAGGCCACCTATTCTATCTTTCGAGACTTCTTACCCTCTCATAGTACACACAGGTTGGTCAATTGGGCACTTTCTTTCGCCTGAAGGTCGACAGTTTTTTAGAGCCTTCTAAAAGCCACTAGATTATTGGGCGGACGCTAGCGTCGAACTAGCTCACACTGCATCAGCAGGGATTTTAGAATGATGGATAAAGCCTACCGCACGACTCTCCTCGGGCTTGCCACCGAAGTGAATCGTATAATCACAGCGCATTCCCGAGGCTGCTTGGGGACTGATGGTGATGATTGAATTTGGTAGGGCTCGGCCATCGCCCGCAATCCTGTAATTACGAGTTGGCTAGACATCACAGCTGGGACTAATAGCAACGCGATTTTAGCCCCGCTAGGTTCAAGTATTTGTTGGTCGCACTGGCAATTCTATGCACCGACACAGCGTTGTGCACTAGAGACACTAATTCCCTTAGAGACCATTTCCCGTACTAGGAGGCGCTGCGGTATGATACCACCAGGAGACATTCACTGATGAAAGCCAGACTTTTGAGATTCCATGACTCAGCGAGGACACTACCTAACACCGCTTTTGGGGTCCAGAATACCTTATACTCCTCCTTCGCTCCGGGTCTTGCCGCCCCCCCTCCCTTTGAGTGATTTACGAAAAGGTAACAAGGGAAGCAAGACTTGGACCTAGATTCATCCCTGACCATATATCCAGCCAGCGTTTTATTAATAGTCTATTAGCAACCCTCTTCGCATTTCAGACAATAGCCCCACGGTTGCCACAGGTATAGTGTGCAGTTAATCCCTCCGCACGACTGTACCAAGGCTTGTCATAACTAACCGTCCTTCATACTAGGTGCCCGTAACACGGTGCAGTCATTTCCCATACTTTACTTTGCTGCTGACCAAATAGGTTCGCACATATATAGCTGGGATTGAGGCTTGTGATTGATGATATCTCGTGATCCCTTGGATAAATATGTGTAAGATGAGCTAGGACGCGCAAAAGTTTGAAACTGAAGATCGCCTCTATGCGGGGACAGAGAATCTTCTTAGACAAGGTATAGCTAACTGCTAATGGCTCTGTAGGGTTACAAGATCACCTACGTGGCAGACAGAGTAGTCCTTCGAGGGCAATATTTAGGCCGTTTCTGCCCGAGCTAGGGTACTACCGTGACCTTGTAGCAGATTTATTCTCTGGGTGCTTTTGCACCTGCAGCCGTGTCCCATAACGGCCGTTTGGTAATATAACCCTGTTCTGTCTCTGCCTTGAGTCGGACTGGCATTCTATCCTCACTACCCTTATAGCCAGGTGAGCTATCCCCTAATGCCGACAGCGTTTAGACTGCTTTTGAGAATATGCCGGCCCTTGGGGATTGAATAAGTTTATACTGCGACCCAACGGTGCATCCCAGCATTCCTATTCCTTTGGTATCAGGTGGCCTCCAGATAATCAATGTACAGCTTACCTTCTACGAAATTAGGTGACGGCCAGATCCCGGTTGCAGGATATTCGATGCTCCAGGGCTTGTACAATATTCCGAGAAGCGAGGTCGGACACGGTATACACTTTACCTTCTGTTAGAAACTGTACACATGGGCCTGGAGAAAGGCACAACCGACGTGGGTGCTGTTACGGGTCATAGGAGCACTGACGAGAGTTTGAAAAATCCCATGTAAGGTTCTACTGAGCCTGTCCACCAATACCGCACGGCAATGCGACGGTGTAGCTGCCCCTGATGACCAAGGAGAAGTGACTGTAACATACGGAATACCTTGTCGAAAAGTCTCTTACGTGCCGTAACCATACGTATCATACTAAAAGTAAGCGTATCTATTCTTTATTGACACCAGTACTGAGACGGAAGGGACGTTCGTCCAGGAACTCAGGTCTACCTCAACCGGACTTTGCTAGCTGCAACCTACCGTCTTTGCTATCCACTTTCTGCCGTGGGTGTTCGTAACTCTCACCACCTCACATATGGGGCCATGAGGCCACACCTCCCGCCCCCCGGCGCTTACCCGGAGTGGACATAATCTAGGAATACTGACCCACGGGTGCTTCTTTTGATTTCGAGGACTCTTGTTCTTAGAATAAGTCTAGAAGTCCTTATACCAAAAGCGTCGGATCTGCCAACCGTATACGTAAACTACATCCAGACGCCAGGAAGTTCCTTGCACCAAAATTCAAGATTCCATAATATGTAACGCCACCCAGACTGGGGACAAGTCACCTACTATGTCCACCGACGGGAGGGCCGAGAGGGCCGGTTCGTTAGGAGGTATTCCTTGTCACCCCCGGCGTAAGCTTTTTAGCGCCTTCTACTTTTCGGCAGATCAGCCACGGGTGAGAAGGGGCGTAACGCATTTACCCATATCTGAGAGATAACACATAAAATACTTTTGAACCTTAATATATCGCACATAGTACAACCAGACACCGCTGAATAATCTTACCCACGACGAACGGAATTCGGTTGTGGGATTACCTTGGTTACTGGCCGTAAGCCCCCGCCAAAGACGCTTACACGATCCAAGGAAGTTGGGTTCCCGCGAAACTACAGCTGATCTCATCTTACACGAGCAGGGTGCCTCCAGTTGGTAGGTTATAGGACTAAGCCGCGCCATTGTCGCTGATTCCTGACGAGCGCCCTACCCTCAAGCAAACACACTAAAAGGCATGGATCGTTCTCATGAAAGGAGTTCGAGCGAAGATCGATGTGTATGCACATAGAGGTTCTGTCACACACCTGTAATAAACTTGCATCACGAGTACCCGCATGATAAACTGTCGTAAACGTTCACATTGCCTTCGCAGCCCTGAGCTTCCCTGACTTACATTCCGTACCAGGTTGATAGCAGAAAACCGAGTCGGAGGCTCGGAAATGGGTTAACCCTTACAAAAAGTGTAAATTACGGATTCTTTGCTCGCCTTGGACCTAGACGAGTGGATTCGCCTCGAGACACTAGAGTCAGGACACCAAGCTCAAGAGTGTTTTTCAGTCCCGGGATTAGGGTGGCTCAAGGCTTCCAGCGGGAACTAAGCGTCTGCCTACCTGGTATTCCTTGCACATCGGGATGCTGACCACTCCGATCCGTACCAAGACATCGTGACCGTTTGGTCCTCGTCAGGGTGCCTTCGCGTACCCTCATGAATCCGGACCGCACTGCAACTTTATGTACCGGTATGCTGGTCCCGACGATGCACTTATGAAGATCGTGAACAGGGCGGCGCGCCAACTAAAGTTCCTCACTTGTCCATCTCAAAACTTCTATCCTCGCACAACGTCAGGTGATGCCTATCCGTCGATTTCTGGAACTTATGGACTAAGGCCCGATGCGTCCTAGTAGGCACGCATTTATTAGTGTTAACGAAATTACATCATTTGACAGCTCCATTCACTCAAACCTCCAGGCGACCCCTCTTACCAGCTCTTGTTATGCTAGAGCATCTTAAAAGGACATCTCTTATCCCCACACAAGGGTAAGGCATCTAGCGAGGGAACGGTAATCTGAATTTGATACGGACCTCGTAGACTCTGTTAACAAAAGACTAGGTCCGCCTCGTCCCACCCGTGCTCTACGTGCGTCCCAGTCAATTAATTGTGGGCACGGAGTACGAGCTTAGTAGACCGCAGAACATCCTCGGCGCGGGGCTTGGACAGACCTTACGCTGTGGTTACTAGTGGTCAACACCTGGAAGTACTAACCTCTCACATTGTCCCGAACATAGCTTTCGGACGTGGGCGAGCACGGGGTGGCTGCTTAAATGGACCAGGGTAACGCCCAGAAACACGGTATCATATTATCATCGGCAAGCGCCCTCCACAATATGTAAGATGACGGTCTTTACCGTCACGCGCCCAGTCTTCCCGTCGTGGGTCGTATTTATGCCACAATTCCCGAGTGGTTCTCCATCTCGTCCACGTCGCCGCGCAGGTCTCAACCTAAGACACCCCTCCCTTGCCCCAAGATAAAATTATAGTCATCCGCGCTAATGTCTAGGTATATGCTTGGCGGTAAGCTACTAGCGAACAAAACACTTTTTGCTCACTTCAACCTGGTTACGCGTCGAACAACCTCTCTGCGCGATGCTCGGTAACCGCTTGTAAAACTCCCGGCACACGAATCTGATGCTATTCAGTTGAGATTGAGACAATTCCATAAACACACCTCCTCGCCAGTGCAGATCCGGGTACACGTCATTGTAACTACGTCGGACGCCCCGTATGGATCGACAGACTACCCCTCCAGAGCGTTTCACTTATATCACATGTACCAGAGTGTATATGGTAGCCGACGTCTTAGGAAGGATCTAACCCTCAGTGAGCCCGGTAGCTTCGGGTAACCAAACCGGTCGTCGCGGGGAATCACCAGGCATAATTATAAAGAGGGTATCCCAGTTAAGGTTCCAATGTTGCTATCTGCCGCGCTAGATTTAACGCTGGCAATGTTTAGATTCGACAGTTCGGGTTTTTTCACTGCTTAATGCGGGCTCCTTCTCTAGTCCTCTTCGCGACAGAGCAATATAAATGTTAACCCGTTCACGACTGGGCAGGGGAACGCCGGCCAGTGAGCTTCGCCATGCAGATCCAGGCAGACTGGCATGAGTTAGGGGAGCGTACGTGGAAACGAGTAGCACGGCTTAACCAGTAGTTCCATATAACCAACGGGTTTATGGGTCAGAAGCGCTTTGACCCCGGTGCGGACGAGTGGCTCCCCCGTGACAGGTTCTGAGAGGCGGATCACCTCATCTCCAGAGTGCATATTAGGATTTGGGCCGGGGCGTTAACCGTGTCAGGACTTCCTAGACTTGGAAAACCGAACATGGAAACATCATCCCTCCTCAGTCAAGCTCCTTCCAAACGATTTCGGTACACCATTCAGCTCCATTACCGGTTCCTTTCTCAAATAATTCTTTACAGTGGTCAGTAAAAACACAATATCTAATCGCTCAGAGGGCTCGCCTTCACCTTGCACAAAAACCCGAGTGAGAGAGTGAGGCTGTCGGTGCTTACCTGGAGGGCTTGGTTCTGAGTTCTCACCGGATACAGAGTCTTTAGTCCTGGGGCTCTATCGAGCAGGGAAACGCTCGCACCAACTGGACGCCCTTTTAACCCATTAGGAAGTCATACGTGGGAAGCCGTGAACTGTGGGTAGGACGTGAACGTGAAATACCACAAATGATAATTACGTCGGGATTCGGATGGATGAAGAAAAACGGCCGCCCATCAGAATGGGCGAACGGTAGATTGATTCCAGCGAATGGAACCTCCATGCTAGGAGCGTACGCTTGTGTTGACTATTGATGCTAAGCGATGTTGGAGGCCATCATCCTGACCATCTGAAGATACTAATATGTTACGGGGGAGGCGCTCACGTAGTAACATAGCGCACACGCCCTGGTCCAAGTCGCGGGTCTTACTTTTAGGACCATGATTCGCGAACAAAACGATGTAGATCCTACTGGGGAGTGTAAAGCACCTTAGGTTGCAGCATGAGACCCCGAAAGCGTGAACGGTTCTAAAATAGTGTGGCCCAAGTCATGTGGAGCGCAAGTTATAAGTGTGGAGCGAAGATACGCACGCTGTAATGCGCGAATATAGGCGGCTACAGCTCAGGACCTGCTTACCGTTCGTTCAGGCACGAGCCTCAGCTATGGTCGTACTGAGCAGGGGGCTGTGTCGCAGATATTTGGGAGCAATATTTGCAAATAGTCCTACATAGTAACATTGGCGTCGAAACGGCTAGGAGAGCGGGCCGGATTTGCCATTCAAGCTGGGTTAGCGCAAACGACAATAAGCAGTCCCACGAGCAGAATGCGGGTGGGTACCCTCTCGACTAACATTTGCCCGTCTGTTGCCTACAGAACAACCCCTATTTGCGCAATTTACCTGCGTGTCAGACCGATGAATTTTCAGGTGTATGCTCTATGACGCAGCGAACACCTTAAAATCCCAGAGTAGCAAGCTTCCCCCGCATTATGGTGAGCAAACCTTGATCGCTCACCCGCGATCGCTTCTCCTTAATTAGCGAAACGGTTGCCTTCTCACTCTCTCAAGTCTAAATCCCTCCCCCGCCAAGCAGTCGGCGCTAGGATCTTGCAAAAACGGATTGGATCACTATGGTGAGGACTACTTGATTACAGCTGATTTCTAGCCGATGCCGGGAGATTCCGAAAGTGTTCGCGGGTTATAAGCTTCGAGACTGGTTTCTTCAACCCTAAGACAGTCGTTGCATCGCACAGGGAACCGCTTGCAGCGCCCAGCCTCTCATTGGGCTCATAGCCCGCAGTGAGACCACAGTCGATAACAGAATGGTTATCTGTTTACCGAGTACGGTACTCCGGACGTGATGCCAACTGGCTCCTAATTCGTATCCCTGATCTATGCTGGATCCATTGCGGAGGGTTCCGCCACCAAGCAGCGAGCAGTAGTCGGGATTTGTGTTCTAGACTACCCATTTACGCCAGGGTGTTTCATTTCAATCCACTATCGCTCAAATCCGCGTCAGCTAGTCCCGTCAGCGTGCTCCCACACCGACCGCCGATTCCCTGATATATTGCCAGCTCCGGATTCCATTGCTTGCTCGTCCCCCTATGCGCGGCATTACCGCGCATATTGTGGACCTGAGTCGTCTGCAATCCCGGGCCACTTGGCAATTACATTTTAAAGCGACAGGGTAGTGCAAGAGAGATCCGACAGGATCCTAAATCGTGAGTCTCATGTAGAGGCCCAGTCTTACAGACTATGATGTTCACGCCCGTAAATGACACACGGGAAAGATAGAGACTCAAGAGATGACTGTAACGATAGATGGCTTAGGAGCACGGGCATGGAGTCTACCGGCCGGACAGTGCAGCTGATGGGTAAATCTGTCGTGATATCGAGCCGATCTTGCACAAAGGCCGCACGCGACACCCCGGTCTTGCGCATACGCTCCTCGCCTGATACAGGTCGTGACCTGGTGTAATGCGGGGGTATAGCTTGACTGCGCCTTGTATCAGATCAAACCCAGCGAGTACGGTGAAGAAGTTGTTAAGTACGGATTTCCCGACGAAGCCTTTGTAGTACGTACCGCTAGAGCCAGGCGTTGGAGGAGATCGCTGGCGTTTCGGTCGATCAACTAGCTACCAAACCGGCCAATTAGGGGGAAGCTAATAGTGGCCAAGGGGATCGGAGCGTTGGCTAGGGCCAGCCGAAGGAGCAATCCCACGCGCCGTCCTTTTCTAGTTTGTCCCGCTTTTTAACTTGAACGCGCGGAGTGTCGAAGCTAGTCAGGTTCATAACAGAGGTCTGGGAGAATCCTATCGACACGCACATGCCATGCGAAAACTACAAGATACTTTGTCGCGCTACGAAGCAGAGAAGATGCTTATGTGAGATTTTTAAAGACTCTGTTTCGAATTCGTCTCTTAACACCTGGCGACCGGATTTATGGCGCTGTAAGGGACTGCAGGTGATCTATCAACTATACGTCATAGGGGCCAACGCAGTTTTCAGCTACGCTCGCCAAATACGGGCGTCATGCCGAACAGGCACTTATAAGAGGGCGATAACGTTCATTCCCGACTCCGCGACCAGCTATTAGCGATTTGATGCTGCTATAAGACAACTTATGAGACGGGTACTAGCGGTTGGCCTTTGGTTGAATAAATGCCCGCCACGATGGACTGGCTCAGATCAGCGGAGGCGCCCCTTGCACACGGCCCTATCGTTTGCACGCTTCGGTGATTCCGCGCATCGAACAACGCTTAGCGCGTCAATGTCAAAAGATCTACCCGTAGCCCCAAAGTATATCGTCACATGACAACGACGATGGTATACGCGTTTAAGCATGGTGATCGTTGTAGTACGGGTCCGACGCGCATACTTTGAGTTCCGCCGCATATTGTATTCCGTACGCGTTCTACCCCGCAATTATCTGGAGTTAGTGGGCCCAGTAAGGATATAAGTGGGAATCTCCACATACATCTTCAAATAAGGGGCCATGCCGCTCAGCCGAACTTTGGATCGATGGGATAGGTGAACCGAGGGCAAGTTGCCTACCACGTAGCACTCCGCAGGGCAAGCCTCGGATCGATGCCGACTCCCCAACATGTTTCTCTTAAAGTCTCTATAAACGGCCGTCTCCAGCTTCAGTGTTAAGATCTCATCTGAAATACTCCAAGGTAGATTGATCAAGGGAATGACGCACCGGCATCAATAATCAGACTCCACGCGTATGCAGCTACTAATTACCTGTGGCCTAAGCACGCGAGTCGGAAAGCGCAGCTGTGTCCAACACTGCACCCAGCAGTTATCGGGCCAAAGTCCAGGCCGGAATGGATTAGTGTGGATTTTGCCATTAATGAAATACCGGTTACAAATATCGACTCTCATAGGAAGGTGTATACAATTAGTCCGTCTACCGCCTTAGGTCATCTTTCATTACAAGCACAGCCTTTGCATGTCCGCCACCACCCCAAGATATTTGGTATCTGGAAAAAATTTTCATTATGTCGACTTATTGGGCCATCTTACGACGTACACCTTGTTAGTGCTTAGAATCTCGGAACATAGAGGAAATCTCCGACCTTTAAGAATATGTGTTCACCTTAAAGAGGCTAAAAGCGTGTGTTAGCCAGGTCGTAGTAGAGCGAATCTAAGGCAGTGTACTCGGAATCGATCGTTGACTGTAGGATACGCACGGGCTAACTTAGGAGCGACGATGCGTACTTGTGCACGCTAAAGCCGCGTCCGGCGTCAGAAACACTACGAAGTTGTGTTGCTCCTTTACACCCAGTCCTAGACCCCACTTTACGCACCTGGCCACGTGGGCCGAGCGTAACCGGCTTGCACCGCGAAGCTAGGCACCGCTTTGTCCTTAACCGTACAGCACTCCACGGTTCGACTTATCTTGTTGATGGATCTAAGAGTCATATGTAGGGTGGCGTCAGAATGACCTCCACATGAATTCCGCAGCCTTTAACGGCACTCATTTTGAGCGCAACTAAACGCCCCTGAGGTAATATCGAGCGTTGTGATGACAGCGCATCTTGTGGTAACTCAACCCAAACATATAGCGCGCTATCTTCGTTTGTCTCAGCCGTCATTCTCGGCAATAGCACTCACTCTGGGCGAAAGGGTATCCAGGTAGACTGGCACAGCCTCTACTTGTTGGGTGTTACCCCTGCGCCGGAGTACACAGTAGCACATACTAATCCGGGCCTCAGTGAACCTAGAAGGAGTATGTGTATACACACGAGTGAAACGTGCCAAGAGACTACCCAAGCGCGAATCCGCGTACACATAGGTCAGGGCATCCCCCACACTGTTATCCTAACGGCTCACGGTCATCAAATTACTGTGATGTTGGTCTATGGGTCTTGCTGGTGAGCCGGCACATTCAAGGTAGGACTGACTTAATCCTGCATGAATGCCCTAGCGGCATGCAAACCTAACTCCAAGTGGCGCTGGGGAAACTCATGAACTCGAAAACACTCATGCGAAGCCTACAGGAGCCGATGAGAATCGAAAGTAACCGCAAGCAGACGAGGTACAGCACTCTCAGATAATTTCTCGTTACGTCAAGAAATGACAAATTCCACTAAAGTTGAGTTAGAATCAACGTCCGCGACACCCAATAAGTGTCAAGGGCTCCCCGGAGACTGGGCGATGCTTTCTTGCTTGGGACCACGTTACATCCATGTGCGTTCAGAACCTCTATTAGGTGGCAGTGCCCGTCTGCCAGGAGTCGATAAGATCAGGTTTGATTACGATTTAGAATATTAATTAGAACCTCGGGCCGCTATTGAATCCACTGAATACTTACATCGCTTAACTGCGGCACGCCGCCTGTACGCTCATCCATTACGTCGGAGCTACACGTTTTTGTGACGACATGTTACATACCTGTATACGAGGGCTCAGGATTTCATCCGCCAGAGACATCTATGGGATAGTGTTCACGGGTGGGTACTCTGTAGGGGAGGGTGATGTATGTTGTCTCATCATCGTCAGAATAAATGAAGTTGTTCTCGGTGCTGACGATGCGTCATCTATTACACGCACCAGTAGCAATCTCGTCAGCTCCATTCTGTGCGTGGCAGGTTCCTTTCGCTGGACCAATGCAATCCTTTGATTACGGTGTACACGCATCTACAACGGCTCACTTTGTTGTGACATGCCTCGACCTGGTCTGAGGCTTTTGTACGTCCTATTCATGAGGGTAAGGTGCAATTCGAGGAGGCCGGCCACGGGCGGAACGTAACTCAACTTCGCACAATTGATCCCGTGCGCGGCCTCCAACTTATAGTTAATCCAGCAAGTCCCCTTAGAGTAGAGAAACAAATAGTATTTGATTTTCCCCTCTTCCTCATTTTAACGGCTACATCCCACTGCGGTCGTAATGACCGGACCGCGCGGGTCGTTTCATGACGCCCGCTCCATCCTCAAGGAGGGTGGCTTACTCTCCAGCAAGCGGTCAAGGGATTTCCGAGACGATACTCACTGTCTTTCGTGCTCTTTGGTTAGTGCTTGGCATACCGGCGTTAGAGCTCATCACAGCCGGCTACCCCATGACGAGTGCGATCCAGTCGTTGCGTTCGCTGTGTCGTATTGCTCTCACCCACTTTAGGACAGGCCACAAACCGCCAGGGTCCAACCGCGGCAAACAGAGTTGATTAGTCTAAATATGGTCTATAAGTACCAATCAATCTCAGCTGTCCGGAAATACCCGTGCATTCATTGTCCGGCAAACTTCGGAAGCTTTTCCAAGCGGCGGTTCTTAGGATGTTTTCGCAATAATTAGCGAATAGTGGTGGTTCCACCCCTTGGAGTTTAAACGGGACGCTGCCTTTAAACTCCTTGTCCTCGAGCTTAGGTATTAAACCTAGAAGGTCTCAAGACAAAATATTAGGTAAGTAACCTAACGATAAGGGCAATGATTCGGATTTATCACTCGGTCCATATATCGCTCATCTCTCTAAGCATTATCTGCCGGAGACGAACTAAGAGCTGGCGGGTCATACCACAAGCCGCGCAAATTAGATGCAACAATCTAGTCAACACTTGAAACATTTCACTCCTTACTCACTGCTCTGGCACTATGCGTACCACACATGGCGTAGCGACCGTTTGCCTGTGTCAGCAGGTGGAGTTGGTCTGTCATTCACAGCGCTGCAAGTAGGCTTAACTATAAGAATGCAATTAGTGTCAAGGGAACAGTCAAAGCACCCGTTCATGATAGTAAGTACGTTTCCAACCGCAGATCTTAAAGCCAGGCACCGTAGTATCTTGTCTGGGATCTTCAACTCACCAACTACATCACTCGGTTACTCTCCTTTGCCAGGTATCTAATGAGTGCGTATAGAATACATCAACAACAGGCAGTGTTGTGCACGAGTCCGGGCGCCCCATTGGGATCGTTACGTGCGCGCTGTGAGTGCGTCGGTTACTTTCGATGCACTACTTAACGGAGCCTCTCAAGCCAAACCCGTATGTGGTCCTTACAGTAAGCCATGTTGATATGAATCAAAACCGGCTCGGTTCATTAGCTCTGTATCGCCCTGGTCATCCCCGGTTATATTTCTAGCATTATGCAAGGCGAAATTGGAACTAGTGCCAGGGTTCACTTAGGCAGTATCATTCGTATCGCCAGTCTTCACAACTCTTACTGAAACTAGGCTACGTTAAGACGGAAGAAGCATTTTTTATTATAGGCCACAGTCGAGCCAGGCGCACAGAGGGCCTCCGCAATAGTGGGACAACTACGTGATGCGCCCGTCGGATATGACCCATAAACTGGTACTGTACCGGAGACCCTCGTCGTCCATCGGCGGATCTACGGCTCTCTAGGTCTGGGGTTTTACCATGCAGATGTCAGATTATTCTCTATCCTATGGTCCCCAAGGACTTTTAATTCCTTCGGTTTCAGCGAAACAAGTGTAACTGGCGCATGTCCAGAGCCCTGCTAACCTGGACGTCGTCCTCCCGATCTACTAAGCCACGCACGACTCCCGTCTAACGGGTGGTCTTACGAAGTTTTATAGGTATGTAGTGGCCTTGACTACCGGCGCCCACTCGGTCGAGTTCAAACACTTTCCACCTAGTGCATATTTAGTAGTTATTCAAGCTATCTGGCCCGAACCTGCAATACGCAAGCGTTTGGTTGCGAACTTATTTATGAAAGTCTTCGCGTACGCGCGTAAGTGACAAGATCTCGGGTACATCTAGTACAGAGTCAGCGGTTAGACTCGGTTTTCCATCTGCATAAGTCGCGCATTGTCTGGAATGTCCTTAACGTGCTTCGAACGAGTCCCTATGGTCCGACGGTTCGATCGTATAAATGACATTAGCCGCCAGCTGTCCTCCCGGAGCGACGCCTTAAGTTGCATGCTAATCGTCTATTGGGCCCCGCGCACGTGCCCTGTACGGGAGCACGTTTTCGTACCTGAGCGGTTCGAGACTCCCAAAAGAGACGCTTAGCGTCGTCTTTGTGAAGACCTATGCAGTTGCACGATAGAACATGCTTTACCCCACGCATTCGCGATAGAACGTTTTCCAACCTTTGGAAGATTAAAGCAGTGCACCAGAAAACCGGCCTGCATGGTTCGCTGTCGAGCGGGCTTTTGTTGATAAGAGGCTCAAACGTAACCGGCGGAGTAATAGCGGTGCTTATGGGTCAACCTTGGAGTTCATGGTCCAACCCGCACGACAACCAGTAGACTGGTCGACACAGTCACCCGATCTGTCGAGAAGCTCATAGGGTTCTATATCTAATAGCCCTAAGGTGGCGTACGCAATAGATATTGACTTCATTCTGTGGGACCTTGACTAGGGAGCGATTCGACTCATAGTCGGAATTTAAACCAGTTGCAGGCCTATTCGCCACCGTCGGACGACGGGAGATAGTCTTCTGACTCCTGACAGCAGGAGCCGCCCCTAGCCTATTGCCGTCAAGCATAGACTGGGTTTTGGAATGGTTACGGTGAGCGTCGCTTAAGCAGAGTGCAATGTACATACCAATGGTTGCCCTTACACCTGTGAGGCCATAGAACCAACCTAAATAGCCAGGATTGGACGCCATCGTTTATTCACCTTCTAATTAACACTTGACCACAAGGTAGGTGCTATGAGCGATGACTCGCTTATGAAAAACTGGATGCAGGCAGCAAGCGGTAATATAGGGGCAACACGTAAGGACCCTAGTTTTCTGAGAACGACGCACTGAAGTGGTAACACGCCCATAAGTTATATGGCACCGAAGACTGTCTTAACAAGCTGCATCTTCCTACCTTTTTCTATTAGCCTAGAATTGGCAGATGGAATCTTGATATGCTTGACGCTAGGAAGACGGTATTCTTCATACAAACGAATACAGTCTCGATCTCGCCGAACCATCAGTAGCTATTGACGGCTATCAATCAGGCCGGATTATTGTGGGCCTTTCATACTCCTCCCAGGCAATTTTCATCCTAGAAAAAACCAGTCATTTCAACTCATCTTCTTCGGTGGCCAGCGAGATGGGAATGCTACTATTCTCACCTGTGGTCACAAACAGCTTACGAATGGCTCTTACGCCGCTGTTATCTAGCTCTCTAATTCGCGCTCTTTCTCTACACGGGACAGTTAGAGATTTCTCTAGATGCTTCTCTGAAAATCCTGGCTTCATATGATTAGATCAAGATAGGTGCGTTCCAGGTCACATGAGCATGACACGTGGAGACAACAGATGCTGAGGGCTTGCTCTTGCTTCTACACGGCAAGGCGAGACCAAACAAGAGGGACCGACCGTTCGGATTTGTCCTCGGCGGAGCTCGATTTAGCTGGTACCCTATGATCCGGTCTTTCACCAGTCGCGAGCCGACTGGCGTGCGAGTTTTCAGAGACGAGCGCCCCGAAAGGGCACC'
result = MinimumSkew(Genome)
' '.join(map(str, result))
|
load("@bazel_tools//tools/cpp:cc_toolchain_config_lib.bzl", "tool_path", "action_config", "tool")
load("@bazel_tools//tools/build_defs/cc:action_names.bzl", "ACTION_NAMES")
def _impl(ctx):
tool_paths = [
tool_path(
name = "gcc",
path = "wrapper_cc.sh",
),
tool_path(
name = "g++",
path = "wrapper_cxx.sh",
),
tool_path(
name = "ld",
path = "/usr/bin/ld",
),
tool_path(
name = "ar",
path = "/usr/bin/ar",
),
tool_path(
name = "cpp",
path = "/usr/bin/cpp",
),
tool_path(
name = "gcov",
path = "/usr/bin/gcov",
),
tool_path(
name = "nm",
path = "/usr/bin/nm",
),
tool_path(
name = "objdump",
path = "/usr/bin/objdump",
),
tool_path(
name = "strip",
path = "/usr/bin/strip",
),
]
action_configs = [
action_config (
action_name = ACTION_NAMES.cpp_link_executable,
enabled = True,
tools = [
tool (path = "wrapper_cc_link.sh"),
]
),
]
return cc_common.create_cc_toolchain_config_info(
ctx = ctx,
toolchain_identifier = "cross-distcc-toolchain",
host_system_name = "i686-unknown-linux-gnu",
target_system_name = "distcc-unknown",
target_cpu = "cpudistcc",
target_libc = "unknown",
compiler = "distcccompile",
abi_version = "unknown",
abi_libc_version = "unknown",
tool_paths = tool_paths,
action_configs = action_configs,
cxx_builtin_include_directories = [
"/usr/lib/gcc/",
"/usr/local/include",
"/usr/include/",
"/usr/lib/gcc/x86_64-redhat-linux/7/include/",
]
)
cc_toolchain_config = rule(
implementation = _impl,
attrs = {},
provides = [CcToolchainConfigInfo],
)
|
class Graph():
def __init__(self, vertices):
self.V = vertices
self.graph = [[0 for column in range(vertices)] for row in range(vertices)]
def printSolution(self, dist):
print("Vertex \t Distance from source")
for node in range(self.V):
print(node, "\t", dist[node])
def minDistance(self, dist, sptSet):
minimum = float('inf')
min_index = 0
for v in range(self.V):
if dist[v] < minimum and sptSet[v] == False:
minimum = dist[v]
min_index = v
return min_index
# For a given source node in the graph, the algorithm finds the shortest path between that node and every other
def dijkstra(self, src):
dist = [float('inf')] * self.V
dist[src] = 0
sptSet = [False] * self.V
for cout in range(self.V):
u = self.minDistance(dist, sptSet)
sptSet[u] = True
for v in range(self.V):
if self.graph[u][v] > 0 and sptSet[v] == False \
and dist[v] > dist[u] + self.graph[u][v]:
dist[v] = dist[u] + self.graph[u][v]
self.printSolution(dist)
g = Graph(10)
g.graph = [[0, 4, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 5, 0, 0, 0, 6, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 10, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 2, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 10, 0, 0, 5, 0],
[0, 0, 0, 0, 0, 0, 4, 0, 0, 8],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
g.dijkstra(0)
|
# Colors.
white = '\033[97m'
green = '\033[92m'
red = '\033[91m'
yellow = '\033[93m'
# Symbols.
info = '\033[93m[!]\033[0m'
failure = '\033[91m[x]\033[0m'
success = '\033[92m[✓]\033[0m'
# Text modifiers.
def bold(t):
return str('\033[1m%s\033[0m' % t)
def italics(t):
return str('\033[3m%s\033[0m' % t)
# Remove formatting.
reset = '\033[0m'
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# 02. 文字列を交互に呼び出して結合する
p = "パトカー"
t = "タクシー"
print("".join([a + b for a, b in zip(p, t)]))
|
def setup_animation():
init_figure()
for line in lines:
self.line = self.mplCanvas.canvas.ax.plot([], [], [])
self.stopped = False |
def count_substring(string, sub_string):
# Init counter
counter = 0
# Find first index
ind = string.find(sub_string)
# Iterate over string
for i in string:
# If not found, return counter
if ind == -1:
return counter
else:
# Increment counter
counter += 1
# Throw the beginning of string until position of next unmatched part
string = string[ind + 1:]
# Try to find the string again
ind = string.find(sub_string)
if __name__ == '__main__':
string = input().strip()
sub_string = input().strip()
count = count_substring(string, sub_string)
print(count) |
# MIT License
#
# Copyright (c) 2021 [FacuFalcone]
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
def Factorial(number:int):
"""
Calculate the factorial of a positive integer
https://en.wikipedia.org/wiki/Factorial
>>> import math
>>> all(factorial(i) == math.factorial(i) for i in range(20))
True
>>> factorial(0.1)
Traceback (most recent call last):
...
ValueError: factorial() only accepts integral values
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: factorial() not defined for negative values
"""
if not isinstance(number, int):
raise ValueError("factorial() only accepts integral values")
if number < 0:
raise ValueError("factorial() not defined for negative values")
return 1 if number == 0 or number == 1 else number * Factorial(number - 1)
if __name__=="__main__":
print(Factorial(4)) |
def main() :
lstFriends = ("sharjeel", "GOPESH PANDEY", "Rupak")
print(lstFriends)
#Return the item in position 1
print(lstFriends[1])
#Tuples are unchangeabl: Once a tuple is created, you cannot change its values.
#lstFriends[1] = "AFFAN"
# The values will remain the same:
print(lstFriends)
#Use For loop : Iterate through the items and print the values
for frnd in lstFriends:
print(frnd)
#To determine how many items a list have, use the len() method
print(len(lstFriends))
"""Add Items
#Once a tuple is created, you cannot add items to it. Tuples are unchangeable.
lstFriends[3] = "affan" # This will raise an error
print(lstFriends)
#Remove and Item : The del keyword can delete the tuple completely
del lstFriends
print(lstFriends) #this will raise an error because the tuple no longer exists
#To execute above section, remove multiline comment (") and run the program
"""
#The tuple() Constructor : Using the tuple() method to make a tuple
lstFriends = tuple(("sharjeel", "gopesh", "affan")) # note the double round-brackets
print(lstFriends)
"""
Searches the tuple for a specified value and returns the position of where it was found
Definition and Usage
The index() method finds the first occurrence of the specified value.
The index() method raises an exception if the value is not found."""
friendName = lstFriends.index("gopesh")
print(friendName)
main()
|
s = input()
if s[0:3] == 'KIH':
s = 'A'+s
elif s[0:4] != 'AKIH':
print('NO')
exit(0)
if s[4:5] == 'B':
s = s[0:4]+'A'+s[4:]
elif s[4:6] != 'AB':
print('NO')
exit(0)
if s[5:7] == 'BR':
s = s[0:6]+'A'+s[6:]
elif s[5:7] != 'BA':
print('NO')
exit(0)
if (s[7:9] == 'RA' and len(s) == 9) or (s[7:8] == 'R' and len(s) == 8):
print('YES')
else:
print('NO')
|
def main():
file = open('6.txt')
banks = []
for line in file:
cells = [int(i) for i in line.split()]
banks.extend(cells)
all_banks = []
while banks not in all_banks:
all_banks.append(banks.copy())
i, m = max(enumerate(banks), key=lambda x: x[1])
banks[i] = 0
for x in range(m):
banks[(i + x + 1) % len(banks)] += 1
print(len(all_banks))
i = all_banks.index(banks)
print(len(all_banks) - i)
if __name__ == '__main__':
main()
|
def get_key(x, y):
return str(x)+"-"+str(y)
#input_line = input("Enter input:\n")
filename = "..\inputs\day_three_input.txt"
f = open(filename)
input_line = f.readline()
x = 0
y = 0
present_locations = {}
present_locations[get_key(x,y)]=1
for c in input_line:
if c == ">":
x += 1
elif c == "<":
x -= 1
elif c == "^":
y += 1
else:
y -= 1
present_locations[get_key(x,y)]=1
print("Unique houses: "+str(len(present_locations.keys())))
|
class PersegiPanjang(object) :
def __init__(self,p,l) :
self.panjang = p
self.lebar = l
def hitungLuas(self) :
return self.panjang * self.lebar
def cetakLuas(self) :
print('Panjang : ',self.panjang)
print('Lebar : ',self.lebar)
print('Luas : ',self.hitungLuas())
def main() :
test = PersegiPanjang(5,6)
test.cetakLuas()
if __name__ == '__main__' :
main() |
#this code gives the numbers of integers, floats, and strings present in the list
a= ['Hello',35,'b',45.5,'world',60]
i=f=s=0
for j in a:
if isinstance(j,int):
i=i+1
elif isinstance(j,float):
f=f+1
else:
s=s+1
print('Number of integers are:',i)
print('Number of Floats are:',f)
print("numbers of strings are:",s)
|
while True:
a, b = map(int, input().split())
if a == 0 and b == 0: break
print("Yes" if (a > b) else "No")
|
# initialize the compass points
NORTH, EAST, SOUTH, WEST = range(4)
class CompassPoints(object):
"""
initialize the class to have a default compass bearing of NORTH
left method subtracts a 'co-ordinate' point from the x axis
right method moves the robot +1 co-ordinate along the x-axis
"""
compass_points = [NORTH, EAST, SOUTH, WEST]
def __init__(self, c_bearing=NORTH):
self.c_bearing = c_bearing
def move_left(self):
self.c_bearing = self.compass_points[self.c_bearing - 1]
def move_right(self):
self.c_bearing = self.compass_points[(self.c_bearing + 1) % 4]
class Robot(object):
"""
Initialize the ROBOT to have a bearing of north and x,y coordinates at the origin
:compass_points is an instance(object) of the CompassPoints class
:robot_bearing finds the current bearing of the robot
:coordinates gets the current co-ordinates of the robot
:advance method moves the robot across the plane based on the robot bearing, adding and subtracting coordinates
:left_turn, right_turn moves the robot according to the input commands
"""
def __init__(self, robot_bearing=NORTH, x_cord=0, y_cord=0):
self.compass_points = CompassPoints(robot_bearing)
self.x_cord = x_cord
self.y_cord = y_cord
@property
def bearing(self):
return self.compass_points.c_bearing
@property
def coordinates(self):
return self.x_cord, self.y_cord
def advance(self):
if self.bearing == NORTH:
self.y_cord += 1
elif self.bearing == SOUTH:
self.y_cord -= 1
elif self.bearing == EAST:
self.x_cord += 1
elif self.bearing == WEST:
self.x_cord -= 1
def turn_left(self):
return self.compass_points.move_left()
def turn_right(self):
return self.compass_points.move_right()
def simulate(self, robot_commands):
instruct = {"A": self.advance, "R": self.turn_right, "L": self.turn_left}
for cmd in robot_commands:
if cmd in instruct:
instruct.get(cmd)()
|
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