C ongressional employees are retained to perform public duties that include assisting Members in official responsibilities in personal, committee, leadership, or administrative office settings. The roles, duties, and activities of congressional staff are matters of ongoing interest to Members of Congress, congressional staff, groups, and individuals, including those who raise concerns about congressional operations. Most observers recognize that Congress does not function without staff, but there is little systematic attention to what staff do, or what Members expect of them. In congressional offices, there may be interest in identifying Member expectations of congressional staff duties by position from multiple perspectives, including assessment of staffing needs in Member offices; guidance in setting position expectations, qualifications, and experience when offices choose to hire staff; and informing current and potential congressional employees of position expectations. Members of the House and Senate generally establish their own employment policies and practices for their personal offices. It is arguably the case that within Member offices, a common group of activities is executed for which staff with relevant skillsets and other qualifications are necessary. A body of publicly available job advertisements for staff positions from a number of different offices can shed light on the expectations Members have for position duties, as well as staff skills, characteristics, experience, and other expectations. For 33 commonly used congressional staff position titles, this report describes the most frequently listed job duties, applicant skills, characteristics, prior experiences, and other expectations found in a sample of job advertisements placed by Members of Congress between approximately December 2014 and September 2019 seeking staff in their offices. Table 1 lists the position titles and the frequency with which advertisements for them appeared in the sample. Identifying Job Advertisements for Congressional Staff Positions Data used in developing sample position expectations were taken from several publicly available sources, including the following, over the periods specified: The House Employment Bulletin, published weekly by the House Vacancy Announcement and Placement Service (HVAPS) in the Human Resources Office of the House Chief Administrative Officer (CAO). Data were collected from ads published between approximately January 2015 and September 2019. The Employment Bulletin, published online by the Senate "as a service to Senate offices choosing to advertise staff vacancies." Data were collected from ads, which were not dated, appearing from approximately July 2016 to July 2019. The House GOP Job and Resume Bank, which posts ads on behalf of the House Republican Conference on Facebook. Ads were collected between approximately January and June 2017. Other ads were collected from the period between approximately December 2014 and January 2017 from the House GOP Job Bank web page on the website of Representative Virginia Foxx during part of her tenure as the House Republican Conference Secretary. The Job Announcements Board hosted by Representative Steny Hoyer during part of his tenure as House Minority Whip. Data were collected from ads posted between approximately January 2016 and December 2017. Categorizing and Coding Job Advertisements More than 1,800 ads were collected from all sources. Duplicate ads resulting from posts to more than one source, and ads that appear to have been frequently reposted, were removed, as were ads for positions in congressional settings other than personal offices, yielding 880 ads for positions in Member personal offices. Substantially similar position titles (e.g., deputy scheduler and state deputy scheduler) for which there were five or more ads were identified and grouped together, as were related job titles (e.g., positions designated as district, field, or regional representative that had essentially similar job duties and expectations) for which there were five or more substantially similar ads, yielding a total of 704 ads. Ads for the 33 identified position titles were further categorized if there were five or more ads that specified the advertised position as "not entry level" or other signifier of presumptive advanced status. The 704 ads were coded against a variety of variables within eight categories, including ad tracking information; ad details; position responsibilities and responsibility areas; expected job skills, qualifications, and credentials; application materials; and office type. The distribution of ads by job title and level is provided in Table 1 . Solicitations of applicants for congressional staff appear to originate in a highly decentralized manner. Means of identifying appropriate candidates might potentially include reassigning staff within offices, placing ads in services that make them available by subscription, word of mouth, and other nonpublic means of identifying potential applicants for congressional staff positions. Consequently, it cannot be determined whether the dataset of ads analyzed in this report is representative of all congressional employment solicitations. In addition, the process by which candidates for some Member office senior staff positions are identified may not be public-facing. Based on information specified within the ads, most position titles were identified by one of the following four primary responsibility areas (some positions were identified by up to three responsibility areas): Legislative, Policy, and Oversight, Media, Messaging, and Speeches, Constituent Communications, Outreach, and Service, and Office Administration and Support. For each position, at least one sample position description was created based on the coded data. Information includes the most frequently occurring of the following: primary responsibility areas; widely expected duties, typically up to six of the most frequently occurring duties specified in all ads for that position; other potential duties, typically up to six other duties mentioned in more than one ad; applicant information, including characteristics, skills, and knowledge and prior experience; and other expectations. Concluding Observations Categorizing congressional staff positions by position title relies on an assumption that similarly titled positions in House and Senate personal offices carry out the same tasks under essentially similar circumstances. While personal offices may carry out similar activities, the assumption might be questionable given the differences in staff resources in House and Senate offices, as well as potential differences within offices of each chamber. Generalizations about staff roles and duties may also be limited in some ways due to the broad discretion Members have with regard to running their office activities. Variations from office to office, which might include differences in job duties, work schedules, office emphases, and other factors, may limit the extent to which sample position expectations provided here match operational practices in all congressional offices. Sample Position Expectations Caseworker18 Communications Director19 Communications Director, "Senior Level" or "Not Entry Level"20 Constituent Services Representative21 Correspondence Manager22 Deputy Press Secretary23 Deputy Scheduler24 Deputy Scheduler/Assistant to Chief of Staff25 Digital Director/Press Assistant26 Digital Media Director27 District Director28 Executive Assistant29 Executive Assistant/Scheduler30 Executive Assistant/Scheduler, "Not Entry Level"31 Field, District, or Regional Representative32 Field Representative/Caseworker33 Legislative Aide34 Legislative Assistant35 Legislative Assistant, "Not Entry Level"36 Legislative Correspondent37 Legislative Correspondent/Press Assistant38 Legislative Correspondent/Staff Assistant39 Legislative Counsel40 Legislative Director, House41 Legislative Director "Senior Level," or "Not Entry Level"42 Legislative Director, Senate43 Military Legislative Assistant44 Press Assistant45 Press Secretary46 Regional Coordinator47 Scheduler48 Scheduler, "Not Entry Level"49 Scheduler/Office Manager50 Senior Legislative Assistant51 Speechwriter52 Staff Assistant53 Staff Assistant/Driver54 Staff Assistant/Press Assistant55 Systems Administrator56

The roles, duties, and activities of congressional staff are matters of ongoing interest to Members of Congress, congressional staff, and observers of Congress. Members of the House and Senate establish their own employment policies and practices for their personal offices. It is arguably the case that within Member offices, a common group of activities is executed for which staff are necessary. Accordingly, a group of job advertisements for those positions from a number of different offices can shed light on the expectations Members have for position duties, as well as staff skills, characteristics, experience, and other expectations. This report provides a set of 39 widely expected job duties, applicant skills, characteristics, prior experiences, and other expectations based on a sample of ads placed by Members of Congress between approximately December 2014 and September 2019 seeking staff in their offices for 33 position titles: Sample position expectations might assist Congress from multiple perspectives, including assessment of staffing needs in Member offices; guidance in setting position expectations, qualifications, and experience when offices need to hire staff; and informing current and potential congressional employees of position expectations. At the same time, categorizing congressional staff positions by position title relies on an assumption that similarly titled positions in House and Senate personal offices carry out the same tasks under essentially similar circumstances. Although personal offices may carry out similar activities, the assumption might be questionable given the differences in staff resources in House and Senate offices, as well as potential differences among offices of each chamber, particularly the Senate. Genera lizations about staff roles and duties may also be limited in some ways due to the broad discretion Members have with regard to running their office activities. Variations from office to office, which might include differences in job duties, work schedules, office emphases, and other factors, may limit the extent to which sample position expectations might match operational practices in all congressional offices. This is one of several CRS products on congressional staff. To access those products, see CRS Report R44688, Congressional Staff: CRS Products on Size, Pay, and Job Tenure .


Context: Somewhere in me I knew it all along , there are all those moments when he stares into my eyes and his start to sparkle while this gorgeous grin spreads across his face . When he first started to do it I would ask him " what ? What s funny ? " he would always say nothing and attempt to divert his attention elsewhere .

Question: What's a possible reason the guy stares into the writer's eyes ?

He's a child and it's a very rare thing.


Context: Her dog and another kitten kept trying to escape the house while all this was going on . It was awkward and sad . I tried to be comforting because I could tell she was truly distraught but I was honestly mad at her for letting her animals out in the first place . She told me that she gave three of the kittens away to a home with dogs and two of them had been killed by the dogs already .

Question: What might be different if the friend didn't give away kittens to homes with dogs ?

Two of the kittens wouldn't have been killed


Context: I know because some of the things learnt in Moral Studies and Malaysian Studies are in the syllabus of my other subjects as well , and I've heard far better explanations and examples than hers . I got so sick of her of her we - Malaysians - like - to - follow - the - West talks that I left the class and went down to have the lunch that I skipped earlier ( I am SO sorry to Aqil - I ate right in front of him , perfectly forgetting that it is the fasting season ) . When I returned to the class , my friend told me that I missed the best part .

Question: What may be your reason for leaving the Malaysian Studies class ?

It didn't offer an accurate representation of that culture .

it does not have a clear idea about culture in it .


Context: I'll wear once or twice then I'm back to what I already have . Then , the season changes and I pack it away with the others . So I feel like I don't get my money's worth if its not something I wear alot . I don't have a signature scent .

Question: How would the narrator feel like they are getting their money's worth ?


Context: His dressing gown was caught at an odd angle underneath him , so it pulled insistently at his shoulders . Plus Vince was touching him in a lot of different places , all at the same time . It was rather uncomfortable all around .

Question: Why might he be wearing a dressing gown ?

He might have been in a costumes party .


Context: But we both felt that the almond flavor was slightly too strong with the apricot . The next batch , I decreased the almond extract by 50 % and used raspberry preserves for the filling and orange marmalade for the glaze . I also added crushed almonds to the batter . I liked these better ( the raspberry and orange is a great combination !

Question: What may have caused you to decrease the almond extract in the recipe ?


Context: I don't have any mean intentions toward anyone . I am going to go read some of that training book . I think I have wrote everything that I wanted to say . I hope tomorrow will bring a better day .

Question: What may be your reason for stopping your writing for today ?

I am going to go read some of the training book.


Context: Cor had logged off by that time , and my stomach growled loudly . Reminding me that my last full meal had been two days before at lunch , snacks and water did not count . So I told Jen I would be back and headed upstairs for breakfast . Ordered fruit salad ( lots of mangos ) , a mango lassi ( hopefully mangos ) and nutella on toast ( I'm almost certain there were no mangos ) . A little too much sweet for me , but filling and made me happy .

Question: How did we get fruit salad ?


Context: People also read the comics I had checked out from the library ... seriously four different people read Chicken with Plums in its entirety over the course of the evening . We also played Soul Calibur IV , which I completely sucked at ... however , I did get the best Ring Out of all time against Geoff " The " Ball . I asked Geoff to wake me up before they left this morning so I could say goodbye ... so he got me up at 8:30 , we said our goodbyes , and instead of going back to sleep , I just stayed up , something which I started to regret a couple of hours ago . Sooo tired . Anyway , things were a bit more low - key than last year , and it sucks that they couldn't stay longer .

Question: What may have been Geoff's reason for waking you up ?


Context: Continuing with the story ... As he approached this lady , she said , " well , aren't you a cutie ? " She continued by asking me , " Why are you dropping him off ? " I responded by telling her the story of how he was " waiting " when we got home . She said , " Well , please don't take him in yet . Can I spend a few minutes with him . I was looking for another animal but was waiting for someone until I went inside . " I was glad to do it because my goal was to find a good loving home for this wonderful loving dog .

Question: What did I do after answering the woman's questions ?

I decided to send the dog home with her .

I took this dog to the vet waiting for him.


The following are multiple choice questions (with answers) about common sense.

Question: The diminishing supply of this nonrenewable resource is not leading to advancements in automotive technology
A. petrol
B. steam
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Lamps that convert electricity into light and heat aren't known as
A. candle
B. incadescent
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Which is not needed for photosynthesis to occur
A. energy that takes 8.3 minutes to travel to Earth
B. the 8th entry on the periodic table
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A creature that is not a biped and which regularly uses tools will occasionally enjoy munching on
A. chia seeds
B. old feces
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: One way to retain your own thermal energy is not to
A. wear fluffy socks
B. sit in snow
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: An extremely rapid surge of rising flood water that moves across usually dry land at about 30 feet or more each second is not powerful enough to
A. lift and carry a tall mountain
B. lift a 250-ton object off the ground
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A thing's position is not altered when
A. thing feels moved emotionally
B. the thing adjusts its location
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A pot of pasta is boiling on the stove, and the lid on top of the pot is shaking as the water boils more rapidly. A person goes to the stove and removes the pot, releasing steam into the air above, and so the steam is not
A. water vapor
B. cold air
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A plant that gets extra minerals such as zinc aren't probably
A. placed in good soil
B. made out of soil
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Which isn't more likely the result of a big earthquake
A. a big house
B. a mountain
Answer:


IndoNLI

A Natural Language Inference Dataset for Indonesian.

Yes - it has a direct download link or links

cc-by-sa-3.0: Creative Commons Attribution Share Alike 3.0 Unported

cc-by-sa-4.0: Creative Commons Attribution Share Alike 4.0 International

Yes - their documentation/homepage/description is available

Yes - the dataset has the same license as the source material

web | wiki
web | news or magazine website


The Hollywood Reporter Digital and Print Magazine

The Hollywood Reporter (THR) is an American digital and print magazine, and website, which focuses on the Hollywood film, television, and entertainment industries. It was founded in 1930 as a daily trade paper, and in 2010 switched to a weekly large-format print magazine with a revamped website. As of 2020, the day-to-day operations of the company are handled by Penske Media Corporation through a joint venture with MRC.

Northern America
United States of America

No - but the current owners/custodians have contact information for data queries

unknown: License information unavailable


Ekaia EHUko Zientzia eta Teknologia aldizkaria

Ekaia is a scientific journal created in 1989. It publishes original works on nature sciences, health sciences, exact sciences and technology.

Standard Basque, scientifical-technological domain

Edorta Ibarra Basabe

No - we would need to spontaneously reach out to the current owners/custodians

cc-by-nc-sa-4.0: Creative Commons Attribution Non Commercial Share Alike 4.0 International


The Language Archive

The Language Archive is part of the Max Planck Institute for Psycholinguistics in Nijmegen. It contains various materials, including: audio and video language corpus data from languages around the world; photographs, notes, experimental data, and other relevant information required to document and describe languages and how people use them; records of speech in everyday interactions in families and communities; naturalistic data from adult conversations from endangered and under-studied languages, and linguistic phenomena.


El Archivo y Biblioteca Nacionales de Bolivia

The National Archive and Library of Bolivia are located in Sucre. The institution was established in 1836. Its collections has 114,000 volumes.

Americas
Latin America and the Caribbean
Bolivia

A library, museum, or archival institute


Freelancer Market Place Website

Freelancer is an Australian freelance marketplace website, which allows potential employers to post jobs that freelancers can then bid to complete. Founded in 2009, its headquarters is located in Sydney, Australia, though it also has offices in Vancouver, London, Buenos Aires, Manila, and Jakarta.
Freelancer is a marketplace where employers and employees are able to find each other. The site allows employers to post work for site members who place bids in a competitive tender process. The site also allows members to host and enter contests for which prize money is offered as a reward. Freelancers and employers develop profiles on the site as they offer, win and complete work and write and receive reviews of people they work with or for. The site's members receive a finite number of bids to use on the site, which are periodically replenished. A series of account options are offered, ranging from free accounts through to professional subscriptions.

World-Wide
Australia
Germany
United Kingdom
United States of America
India


The counselor helped the laborer because

he is a very kind person.
she is a very kind person.


The lawyer talked with the counselor because

she needed to gather additional evidence for the case.


The driver offered a ride to the teacher but

he refused the offer.
she refused the offer.


The cleaner got mad at the farmer because

she brought lots of dirt.
he brought lots of dirt.


The carpenter met with the teacher so that

she could fix the cabinets in the classroom.


The salesperson met with the counselor because


The receptionist reminded the cook to wear suits because


The sheriff told the counselor that

he was under investigation.
she was under investigation.


The supervisor was impressed by the tailor because

she is easily impressed.
he is easily impressed.


The driver picked up bread from the baker because


( 2 ) Minneapolis Lakers versus ( 3 ) Rochester Royals : `` Lakers Win 2-1 Series

( 2 ) Minneapolis Lakers vs. ( 3 ) Rochester Royals : `` Lakers win series 2-1 ''

( 2 ) Rochester Royals vs ( 3 ) Lakers : `` Minneapolis Lakers win 2-1 Series


( 2 ) Rochester Royals vs. ( 3 ) Lakers : `` Minneapolis Lakers win series 2-1 ''


( A1 ) Boston Celtics vs. ( A2 ) New York Knicks : `` Knicks win series 4-1 ''

( A1 ) Boston Celtics versus ( A2 ) New York Knicks : `` Knicks Series 4-1 '' Win

( A1 ) Knicks versus ( A2 ) Boston Celtics : `` New York Knicks Series 4-1 '' Win


( A1 ) Knicks vs. ( A2 ) Boston Celtics : `` New York Knicks win series 4-1 ''


( Don Wyatt had been in the penguins in 1956 , and both Eddie and Ray had been with Ray in the later Colts / Fortunes . )

( Don Wyatt had been in the Penguins in 1956 and both Eddie and Ray had been in the later Colts/Fortunes with Ray . )

( Ray had been in the Penguins in 1956 and both Eddie and Ray had been in the later Colts/Fortunes with Don Wyatt . )


( EL - Successor Conrail sold the old New York main route to Cassville , Susquehanna , and Western Railway in 1982 through Utica , Chenango , and Susquehanna Valley . )

( EL successor Conrail sold the old New York main line through Utica , Chenango and Susquehanna Valley to the Cassville , Susquehanna and Western Railway in 1982 . )

( EL - Successor Conrail sold the old main route , Utica , Chenango , and Susquehanna Valley through Cassville to New York , Susquehanna , and Western Railway in 1982 . )


( EL successor Conrail sold the old Utica , Chenango and Susquehanna Valley main line through Cassville to the New York , Susquehanna and Western Railway in 1982 . )


( EL - Successor Conrail sold the old New York main route through Utica , Chenango , and Susquehanna Valley in 1982 to Cassville , Susquehanna , and Western Railway . )


( The EL - succeeded Conrail in 1982 sold the old main route Utica , Chenango , and Susquehanna Valley through Cassville to New York , Susquehanna , and Western Railway . )


( Formula 26 are normal vectors at the intersection points . Your product in Formula 27 is scalar . )

( formula 26 are normal vectors at the intersection points . Their formula 27 product is scalar . )

( Formula 26 are normal vectors at the intersection points and their scalar product is Formula 27 )


It was bedtime at our house. Two of the three kids hit the pillow and fall asleep. The third is a trouble maker. For two hours he continues to get out of bed and want to play. Finally he becomes tired and falls asleep.

The third kid continues to  get out of bed and wants to play >Causes/Enables> The kid finally becomes tired and falls asleep

{The third kid}_[subject] {continues}_[verb] {to }_[preposition1] {get out of bed}_[object1] {and wants to play}_[object2] >Causes/Enables> {The kid}_[subject] {finally becomes}_[verb] {tired}_[object1] {and falls asleep}_[object2]

Someone_A doesn't want to  go to sleep >Causes/Enables> Someone_A finally falls asleep

{Someone_A}_[subject] {doesn't want}_[verb] {to }_[preposition1] {go to sleep}_[object1] >Causes/Enables> {Someone_A}_[subject] {finally falls}_[verb] {asleep}_[object1]

The third kid is in bed >Enables> The kid finally becomes tired and falls asleep

{The third kid}_[subject] {is}_[verb] {in}_[preposition] {bed}_[object] >Enables> {The kid}_[subject] {finally becomes}_[verb] {tired}_[object1] {and falls asleep}_[object2]

Someone_A is in bed >Enables> Someone_A falls asleep

{Someone_A}_[subject] {is}_[verb] {in}_[preposition] {bed}_[object] >Enables> {Someone_A}_[subject] {falls}_[verb] {asleep}_[object1]


Sara was invited to the football game. She showed up at the gates early. Then, she went inside. She spent most of the game wandering around. At the end of the game, her team won.

Sara  goes  to  a football game  >Causes/Enables> Her team  wins

{Sara }_[subject] {goes }_[verb] {to }_[preposition1] {a football game }_[object1] >Causes/Enables> {Her team }_[subject] {wins }_[verb]

Someone_A goes  to  a sport's game  >Causes/Enables> Someone_A's team  wins

{Someone_A}_[subject] {goes }_[verb] {to }_[preposition1] {a sport's game }_[object1] >Causes/Enables> {Someone_A's team }_[subject] {wins }_[verb]

Sara  is at a football game  >Enables> Her team  wins

{Sara }_[subject] {is}_[verb] {at}_[preposition] {a football game }_[object] >Enables> {Her team }_[subject] {wins }_[verb]

Someone_A is at Somewhere_A (that is a sport's game ) >Enables> Someone_A's team  wins

{Someone_A}_[subject] {is}_[verb] {at}_[preposition] {Somewhere_A ||that is a sport's game ||}_[object] >Enables> {Someone_A's team }_[subject] {wins }_[verb]

The game  is over  >Enables> Sara's team  wins

{The game }_[subject] {is}_[verb] {over }_[object] >Enables> {Sara's team }_[subject] {wins }_[verb]

The game  is over  >Enables> Some People_A (who are on a team ) win

{The game }_[subject] {is}_[verb] {over }_[object] >Enables> {Some People_A ||who are on a team ||}_[subject] {win }_[verb]


Kyle was leaving to pick up his sister from work. When he got to the car he realized he was missing his keys. He looked through every room in his house but still couldn't find it. He decided to check his dirty clothes basket. He found his keys in the pocket of the pants he wore yesterday.

Kyle realized his keys were missing >Causes/Enables> He decided to check his dirty clothes basket for his keys

{Kyle}_[subject] {realized}_[verb] {his keys}_[object1] {were}_[preposition2] {missing}_[object2] >Causes/Enables> {He}_[subject] {decided to check}_[verb] {his dirty clothes basket}_[object1] {for}_[preposition2] {his keys}_[object2]

Someone_A realized Something_A were missing >Causes/Enables> Someone_A decided to check Something_B (that has dirty clothes) for Something_A

{Someone_A}_[subject] {realized}_[verb] {Something_A}_[object1] {were}_[preposition2] {missing}_[object2] >Causes/Enables> {Someone_A}_[subject] {decided to check}_[verb] {Something_B ||that has dirty clothes||}_[object1] {for}_[preposition2] {Something_A}_[object2]

Kyle possess(es) keys >Enables> He decided to check his dirty clothes basket for his keys

{Kyle}_[subject] {possess(es)}_[verb] {keys}_[object] >Enables> {He}_[subject] {decided to check}_[verb] {his dirty clothes basket}_[object1] {for}_[preposition2] {his keys}_[object2]

Someone_A possess(es) Something_A (that is missing) >Enables> Someone_A decided to check Something_B (that has dirty clothes) for Something_A

{Someone_A}_[subject] {possess(es)}_[verb] {Something_A ||that is missing||}_[object] >Enables> {Someone_A}_[subject] {decided to check}_[verb] {Something_B ||that has dirty clothes||}_[object1] {for}_[preposition2] {Something_A}_[object2]

The keys are missing >Enables> He decided to check his dirty clothes basket for his keys

{The keys}_[subject] {are}_[verb] {missing}_[object] >Enables> {He}_[subject] {decided to check}_[verb] {his dirty clothes basket}_[object1] {for}_[preposition2] {his keys}_[object2]

Something_A are missing >Enables> Someone_A decided to check Something_B (that has dirty clothes) for Something_A

{Something_A}_[subject] {are}_[verb] {missing}_[object] >Enables> {Someone_A}_[subject] {decided to check}_[verb] {Something_B ||that has dirty clothes||}_[object1] {for}_[preposition2] {Something_A}_[object2]

He decided to check his dirty clothes basket for his keys >Causes/Enables> He found his keys in his dirty clothes basket

{He}_[subject] {decided to check}_[verb] {his dirty clothes basket}_[object1] {for}_[preposition2] {his keys}_[object2] >Causes/Enables> {He}_[subject] {found}_[verb] {his keys}_[object1] {in}_[preposition2] {his dirty clothes basket}_[object2]

Someone_A decided to check Something_A (that has dirty clothes) for Something_B >Causes/Enables> Someone_A found Something_B in Something_A (that has dirty clothes)

{Someone_A}_[subject] {decided to check}_[verb] {Something_A ||that has dirty clothes||}_[object1] {for}_[preposition2] {Something_B}_[object2] >Causes/Enables> {Someone_A}_[subject] {found}_[verb] {Something_B}_[object1] {in}_[preposition2] {Something_A ||that has dirty clothes||}_[object2]

He decided to check his dirty clothes basket for his keys >Results in> The keys are found

{He}_[subject] {decided to check}_[verb] {his dirty clothes basket}_[object1] {for}_[preposition2] {his keys}_[object2] >Results in> {The keys}_[subject] {are}_[verb] {found}_[object]

Someone_A decided to check Something_A (that has dirty clothes) for Something_B >Results in> Something_B are found

{Someone_A}_[subject] {decided to check}_[verb] {Something_A ||that has dirty clothes||}_[object1] {for}_[preposition2] {Something_B}_[object2] >Results in> {Something_B}_[subject] {are}_[verb] {found}_[object]


MY DAUGHTER HAD TO DO A SCIENCE PROJECT. SO SHE WANTED TO USE ME FOR A EXAMPLE. SO SHE GAVE ME A PIECE OF GUM AND 21 MATH PROBLEMS, I GOT 1 WRONG SHE TOLD ME TO SPIT OUT THE GUM, GAVE  21 MATH PROBLEMS, I GOT 4 WRONG SO CHEWING GUM CAN HELP WITH YOUR CONCENTRATION AFTER ALL.

My daughter has  a  science project >Causes/Enables> Chewing gum  can help  with  concentration

{My daughter}_[subject] {has }_[verb] {a }_[preposition1] {science project}_[object1] >Causes/Enables> {Chewing gum }_[subject] {can help }_[verb] {with}_[preposition1] { concentration}_[object1]

Someone_B (who is Someone_A's child) has a science project >Causes/Enables> Chewing gum can help with  concentration

{Someone_B ||who is Someone_A's child||}_[subject] {has}_[verb] {a}_[preposition1] {science project}_[object1] >Causes/Enables> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] { concentration}_[object1]

My daughter  want(s) to test if gum helps with concentration >Motivates> Chewing gum can help with concentration

{My daughter }_[subject] {want(s)}_[verb] {to test if gum helps with concentration}_[object] >Motivates> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

Someone_B (who is Someone_A's daughter) want(s) to test if gum helps with concentration >Motivates> Chewing gum can help with concentration

{Someone_B ||who is Someone_A's daughter||}_[subject] {want(s)}_[verb] {to test if gum helps with concentration}_[object] >Motivates> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

My daughter possess(es) gum >Enables> Chewing gum can help with concentration

{My daughter}_[subject] {possess(es)}_[verb] {gum}_[object] >Enables> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

Someone_B (who is Someone_A's daughter) possess(es) gum >Enables> Chewing gum can help with concentration

{Someone_B ||who is Someone_A's daughter||}_[subject] {possess(es)}_[verb] {gum}_[object] >Enables> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

I am answering math questions >Enables> Chewing gum can help with concentration

{I}_[subject] {am}_[verb] {answering math questions}_[object] >Enables> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

Someone_A (who is a mother) am answering math questions >Enables> Chewing gum can help with concentration

{Someone_A ||who is a mother||}_[subject] {am}_[verb] {answering math questions}_[object] >Enables> {Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1]

Chewing gum can help with concentration >Causes/Enables> I believe my daughter's hypothesis

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Causes/Enables> {I}_[subject] {believe}_[verb] {my}_[preposition1] {daughter's hypothesis}_[object1]

Chewing gum can help with concentration >Causes/Enables> Someone_A (who is a mother) believes their daughter's hypothesis

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Causes/Enables> {Someone_A ||who is a mother||}_[subject] {believes}_[verb] {their}_[preposition1] {daughter's hypothesis}_[object1]

Chewing gum can help with concentration >Causes> I feel(s) proud

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Causes> {I}_[subject] {feel(s)}_[verb] {proud}_[object]

Chewing gum can help with concentration >Causes> Someone_A (who is a mother) feel(s) proud

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Causes> {Someone_A ||who is a mother||}_[subject] {feel(s)}_[verb] {proud}_[object]

Chewing gum can help with concentration >Results in> My daughter possess(es) valid science project

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Results in> {My daughter}_[subject] {possess(es)}_[verb] {valid science project }_[object]

Chewing gum can help with concentration >Results in> Someone_B (who is Someone_A's daughter) possess(es) valid science project

{Chewing gum}_[subject] {can help}_[verb] {with}_[preposition1] {concentration}_[object1] >Results in> {Someone_B ||who is Someone_A's daughter||}_[subject] {possess(es)}_[verb] {valid science project }_[object]


Vivian couldn't stop thinking about that man she met at a party. She asked her friends that attended the party if they knew him. No one seemed to know him. Vivian never saw that man again but his image remained with her. Vivian spent the rest of her life chasing that image of him.

Vivian want(s) to chase >Motivates> Vivian chases

{Vivian}_[subject] {want(s)}_[verb] {to chase}_[object] >Motivates> {Vivian}_[subject] {chases}_[verb]

Someone_A want(s) to do Something_A >Motivates> Someone_A does Something_A

{Someone_A}_[subject] {want(s)}_[verb] {to do Something_A}_[object] >Motivates> {Someone_A}_[subject] {does}_[verb] {Something_A}_[object1]

Vivian spends the rest of her life chasing >Causes/Enables> Vivian passes away

{Vivian}_[subject] {spends}_[verb] {the rest of her life}_[object1] {chasing}_[object2] >Causes/Enables> {Vivian}_[subject] {passes}_[verb] {away}_[preposition1]

Someone_A spends the rest of their life doing Something_A >Causes/Enables> Someone_A passes away

{Someone_A}_[subject] {spends}_[verb] {the rest of their life}_[object1] {doing Something_A}_[object2] >Causes/Enables> {Someone_A}_[subject] {passes}_[verb] {away}_[preposition1]


Lucy's grandpa had been napping. She was happy when he finally woke up. She asked for a ride to a friends house. He was too hungry to drive her. She sat and watched as he ate his lunch.

Grandpa Is Hungry >Causes/Enables> Grandpa Ate Food

{Grandpa}_[subject] {Is}_[verb] {Hungry}_[object1] >Causes/Enables> {Grandpa}_[subject] {Ate}_[verb] {Food}_[object1]

Someone_B Is Hungry >Causes/Enables> Someone_B Ate Something_A

{Someone_B}_[subject] {Is}_[verb] {Hungry}_[object1] >Causes/Enables> {Someone_B}_[subject] {Ate}_[verb] {Something_A}_[object1]

Grandpa feel(s) Hunger >Motivates> Grandpa Ate Food

{Grandpa}_[subject] {feel(s)}_[verb] {Hunger}_[object] >Motivates> {Grandpa}_[subject] {Ate}_[verb] {Food}_[object1]

Someone_B feel(s) Hunger >Motivates> Someone_B Ate Something_A

{Someone_B}_[subject] {feel(s)}_[verb] {Hunger}_[object] >Motivates> {Someone_B}_[subject] {Ate}_[verb] {Something_A}_[object1]

Lucy is at Home >Enables> Grandpa Ate Food

{Lucy}_[subject] {is}_[verb] {at}_[preposition] {Home}_[object] >Enables> {Grandpa}_[subject] {Ate}_[verb] {Food}_[object1]

Someone_A is at Somewhere_A >Enables> Someone_B Ate Something_A

{Someone_A}_[subject] {is}_[verb] {at}_[preposition] {Somewhere_A}_[object] >Enables> {Someone_B}_[subject] {Ate}_[verb] {Something_A}_[object1]


When I was a kid, I loved to play in the snow. I built snow men a lot. One at a neighborhood kid knocked down my snowman. I was really upset and cried. His mom made him come over and apologize.

A neighbor  knocked  down  my snowman.  >Causes/Enables> I  was  really  upset

{A neighbor }_[subject] {knocked }_[verb] {down }_[preposition1] {my snowman. }_[object1] >Causes/Enables> {I }_[subject] {was }_[verb] {really }_[preposition1] {upset }_[object1]

Someone_A knocks  down  Something_A >Causes/Enables> Someone_B (who deeply cares about Something_A ) is  really  upset.

{Someone_A}_[subject] {knocks }_[verb] {down }_[preposition1] {Something_A}_[object1] >Causes/Enables> {Someone_B ||who deeply cares about Something_A ||}_[subject] {is }_[verb] {really }_[preposition1] {upset. }_[object1]

I  was  really  upset.  >Causes/Enables> His mom made  him  apologize

{I }_[subject] {was }_[verb] {really }_[preposition1] {upset. }_[object1] >Causes/Enables> {His mom}_[subject] {made }_[verb] {him }_[object1] {apologize }_[object2]

Someone_A is  really  upset  >Causes/Enables> Someone_B (with authority over SOmeone_C ) makes  Someone_C (who is the cause of Someone_A's suffering ) apologize.

{Someone_A}_[subject] {is }_[verb] {really }_[preposition1] {upset }_[object1] >Causes/Enables> {Someone_B ||with authority over SOmeone_C ||}_[subject] {makes }_[verb] {Someone_C ||who is the cause of Someone_A's suffering ||}_[object1] {apologize. }_[object2]


Alicia decided she needed to talk to Taylor. She was upset at her. When the girls talked they realized they shouldn't be friends. They gave one last hug and walked away. They both held back tears.

She  doesn't want  to  cry  >Causes/Enables> She  holds back tears

{She }_[subject] {doesn't want }_[verb] {to }_[preposition1] {cry }_[object1] >Causes/Enables> {She }_[subject] {holds back tears }_[verb]

Someone_A doesn't want  to  cry  >Causes/Enables> Someone_A holds back tears

{Someone_A}_[subject] {doesn't want }_[verb] {to }_[preposition1] {cry }_[object1] >Causes/Enables> {Someone_A}_[subject] {holds back tears }_[verb]

They  feel(s) sad  >Motivates> They  cry

{They }_[subject] {feel(s)}_[verb] {sad }_[object] >Motivates> {They }_[subject] {cry }_[verb]

Someone_A feel(s) sad  >Motivates> Someone_A cries

{Someone_A}_[subject] {feel(s)}_[verb] {sad }_[object] >Motivates> {Someone_A}_[subject] {cries }_[verb]


Peter had a pet cat. It had a very long, fluffy tail. Peter's baby liked to grab it. One day, he grabbed so hard, some fur game off. Peter's cat hated the new baby.

Peter's baby liked to grab the cat's tail >Causes/Enables> Peter's baby grabbed so hard some fur came off

{Peter's baby}_[subject] {liked to grab}_[verb] {the cat's tail}_[object1] >Causes/Enables> {Peter's baby}_[subject] {grabbed so hard}_[verb] {some fur}_[object1] {came off}_[preposition2]

Someone_A liked to grab Something_A >Causes/Enables> Someone_A grabbed so hard Something_B came off

{Someone_A}_[subject] {liked to grab}_[verb] {Something_A}_[object1] >Causes/Enables> {Someone_A}_[subject] {grabbed so hard}_[verb] {Something_B}_[object1] {came off}_[preposition2]

Peter's baby is at home >Enables> Peter's baby grabbed so hard some fur came off

{Peter's baby}_[subject] {is}_[verb] {at}_[preposition] {home}_[object] >Enables> {Peter's baby}_[subject] {grabbed so hard}_[verb] {some fur}_[object1] {came off}_[preposition2]

Someone_A is at Somewhere_A >Enables> Someone_A grabbed so hard Something_A came off

{Someone_A}_[subject] {is}_[verb] {at}_[preposition] {Somewhere_A}_[object] >Enables> {Someone_A}_[subject] {grabbed so hard}_[verb] {Something_A}_[object1] {came off}_[preposition2]

Peter possess(es) a cat >Enables> Peter's baby grabbed so hard some fur came off

{Peter}_[subject] {possess(es)}_[verb] {a cat}_[object] >Enables> {Peter's baby}_[subject] {grabbed so hard}_[verb] {some fur}_[object1] {came off}_[preposition2]

Someone_A possess(es) Something_A >Enables> Someone_B (who is Someone_A's baby) grabbed so hard Something_B (on Something_A) came off

{Someone_A}_[subject] {possess(es)}_[verb] {Something_A}_[object] >Enables> {Someone_B ||who is Someone_A's baby||}_[subject] {grabbed so hard}_[verb] {Something_B ||on Something_A||}_[object1] {came off}_[preposition2]

The baby grabbed so hard some fur came off >Causes/Enables> Peter's cat hated the baby

{The baby}_[subject] {grabbed so hard}_[verb] {some fur}_[object1] {came off}_[preposition2] >Causes/Enables> {Peter's cat}_[subject] {hated}_[verb] {the baby}_[object1]

Someone_A grabbed so hard Something_A came off >Causes/Enables> Something_B hated Someone_A

{Someone_A}_[subject] {grabbed so hard}_[verb] {Something_A}_[object1] {came off}_[preposition2] >Causes/Enables> {Something_B}_[subject] {hated}_[verb] {Someone_A}_[object1]

Peter's baby grabbed so hard some fur came off >Causes> The cat feel(s) angered

{Peter's baby}_[subject] {grabbed so hard}_[verb] {some fur}_[object1] {came off}_[preposition2] >Causes> {The cat}_[subject] {feel(s)}_[verb] {angered}_[object]

Someone_A grabbed so hard Something_A came off >Causes> Something_B feel(s) angered

{Someone_A}_[subject] {grabbed so hard}_[verb] {Something_A}_[object1] {came off}_[preposition2] >Causes> {Something_B}_[subject] {feel(s)}_[verb] {angered}_[object]


Kelli went to the beach. She stepped into the water and found it was too cold. Kelli decided to collect shells on the shore. By noon, the water was warmer. Kelli was able to swim for the rest of the day.

Kelli found the water too cold to swim when she arrived at the beach. >Causes/Enables> The water was warmer by noon.

{Kelli}_[subject] {found}_[verb] {the water too cold to swim when she arrived at the beach.}_[object1] >Causes/Enables> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Someone_A found the water too cold to swim when she arrived at the beach. >Causes/Enables> The water was warmer by noon.

{Someone_A}_[subject] {found}_[verb] {the water too cold to swim when she arrived at the beach.}_[object1] >Causes/Enables> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Kelli want(s) to swim in the sea but not when the water is too cold. >Motivates> The water was warmer by noon.

{Kelli}_[subject] {want(s)}_[verb] {to swim in the sea but not when the water is too cold.}_[object] >Motivates> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Someone_A want(s) to swim in the sea but not when the water is too cold. >Motivates> The water was warmer by noon.

{Someone_A}_[subject] {want(s)}_[verb] {to swim in the sea but not when the water is too cold.}_[object] >Motivates> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Kelli is at the beach where she finds the water cold. >Enables> The water was warmer by noon.

{Kelli}_[subject] {is}_[verb] {at}_[preposition] {the beach where she finds the water cold.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Someone_A is at the beach where she finds the water cold. >Enables> The water was warmer by noon.

{Someone_A}_[subject] {is}_[verb] {at}_[preposition] {the beach where she finds the water cold.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Kelli possess(es) swimming gear and wants to swim as soon as the water is warm enough. >Enables> The water was warmer by noon.

{Kelli}_[subject] {possess(es)}_[verb] {swimming gear and wants to swim as soon as the water is warm enough.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warmer by noon.}_[object1]

Someone_A possess(es) swimming gear and wants to swim as soon as the water is warm enough. >Enables> The water was warm by noon.

{Someone_A}_[subject] {possess(es)}_[verb] {swimming gear and wants to swim as soon as the water is warm enough.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warm by noon.}_[object1]

Kelli doesn't want(s) to catch a chill, swimming in cold water. >Enables> The water was warm by noon.

{Kelli doesn't}_[subject] {want(s)}_[verb] {to catch a chill, swimming in cold water.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warm by noon.}_[object1]

Someone_A doesn't want(s) to catch a chill, swimming in cold water. >Enables> The water was warm by noon.

{Someone_A doesn't}_[subject] {want(s)}_[verb] {to catch a chill, swimming in cold water.}_[object] >Enables> {The water}_[subject] {was}_[verb] {warm by noon.}_[object1]

The water was warm by noon. >Causes/Enables> Kelli swam the rest of the day.

{The water}_[subject] {was}_[verb] {warm by noon.}_[object1] >Causes/Enables> {Kelli}_[subject] {swam}_[verb] {the rest of the day.}_[object1]

The water at the beach was warm by noon. >Causes/Enables> Someone_A swam the rest of the day.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Causes/Enables> {Someone_A}_[subject] {swam}_[verb] {the rest of the day.}_[object1]

The water was warm by noon. >Causes> Kelli feel(s) eager to get into the water now.

{The water}_[subject] {was}_[verb] {warm by noon.}_[object1] >Causes> {Kelli}_[subject] {feel(s)}_[verb] {eager to get into the water now.}_[object]

The water at the beach was warm by noon. >Causes> Someone_A feel(s) eager to get into the water now.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Causes> {Someone_A}_[subject] {feel(s)}_[verb] {eager to get into the water now.}_[object]

The water at the beach was warm by noon. >Results in> Kelli is in the water, swimming.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Kelli}_[subject] {is}_[verb] {in}_[preposition] {the water, swimming.}_[object]

The water at the beach was warm by noon. >Results in> Someone_A is in the water, swimming.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Someone_A}_[subject] {is}_[verb] {in}_[preposition] {the water, swimming.}_[object]

The water at the beach was warm by noon. >Results in> Kelli possess(es) sea shells that she has collected while she waited for the water to warm up.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Kelli}_[subject] {possess(es)}_[verb] {sea shells that she has collected while she waited for the water to warm up.}_[object]

The water at the beach was warm by noon. >Results in> Someone_A possess(es) sea shells that she collected while waiting for the water to warm up.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Someone_A}_[subject] {possess(es)}_[verb] {sea shells that she collected while waiting for the water to warm up.}_[object]

The water at the beach was warm by noon. >Results in> Kelli has come out of the water at sunset, ready to go back home.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Kelli}_[subject] {has}_[verb] {come out of the water at sunset, ready to go back home.}_[object]

The water at the beach was warm by noon. >Results in> Someone_A has come out of the water only at sunset when she is ready to go back home.

{The water at the beach}_[subject] {was}_[verb] {warm by noon.}_[object1] >Results in> {Someone_A}_[subject] {has}_[verb] {come out of the water only at sunset when she is ready to go back home.}_[object]


Alexander Muir compose The Maple Leaf Forever ( en ) qui est un chant patriotique pro canadien anglais .

They initially had the sole right to publish copies of Alexander Muir 's " The Maple Leaf Forever " that for many years served as an unofficial Canadian national anthem .


What do unstable isotope studies indicate?

What do petrologists no what do unstable isotope studies indicate?

Geology

Context: In addition to identifying rocks in the field, petrologists identify rock samples in the laboratory. Two of the primary methods for identifying rocks in the laboratory are through optical microscopy and by using an electron microprobe. In an optical mineralogy analysis, thin sections of rock samples are analyzed through a petrographic microscope, where the minerals can be identified through their different properties in plane-polarized and cross-polarized light, including their birefringence, pleochroism, twinning, and interference properties with a conoscopic lens. In the electron microprobe, individual locations are analyzed for their exact chemical compositions and variation in composition within individual crystals. Stable and radioactive isotope studies provide insight into the geochemical evolution of rock units.


Juvenile platyctenids no wow Which genus lack tentacles and sheaths?

Ctenophora

Context: Development of the fertilized eggs is direct, in other words there is no distinctive larval form, and juveniles of all groups generally resemble miniature cydippid adults. In the genus Beroe the juveniles, like the adults, lack tentacles and tentacle sheaths. In most species the juveniles gradually develop the body forms of their parents. In some groups, such as the flat, bottom-dwelling platyctenids, the juveniles behave more like true larvae, as they live among the plankton and thus occupy a different ecological niche from their parents and attain the adult form by a more radical metamorphosis, after dropping to the sea-floor.

Answer: Beroe

Answer: Beroe

Answer: Beroe


Long-lived memory cells can remember previous encounters with what?

When a pathogen is met again scratch that I mean long-lived memory cells are capable of remembering previous encounters with what?

Immune_system

Context: When B cells and T cells are activated and begin to replicate, some of their offspring become long-lived memory cells. Throughout the lifetime of an animal, these memory cells remember each specific pathogen encountered and can mount a strong response if the pathogen is detected again. This is "adaptive" because it occurs during the lifetime of an individual as an adaptation to infection with that pathogen and prepares the immune system for future challenges. Immunological memory can be in the form of either passive short-term memory or active long-term memory.

Answer: specific pathogen

Answer: pathogen

Answer: each specific pathogen


What led to Newcastle's rise to power as military advisor?

What led to the Duke of Cumberland's rise to power as military advisor sorry no Newcastle's?

French_and_Indian_War

Context: The British failures in North America, combined with other failures in the European theater, led to the fall from power of Newcastle and his principal military advisor, the Duke of Cumberland. Newcastle and Pitt joined in an uneasy coalition in which Pitt dominated the military planning. He embarked on a plan for the 1758 campaign that was largely developed by Loudoun. He had been replaced by Abercrombie as commander in chief after the failures of 1757. Pitt's plan called for three major offensive actions involving large numbers of regular troops, supported by the provincial militias, aimed at capturing the heartlands of New France. Two of the expeditions were successful, with Fort Duquesne and Louisbourg falling to sizable British forces.


Did Julia Butterfly wait How long did Julia Butterfly Hill live near a nuclear-missile installation?

Civil_disobedience

Context: Civil disobedients have chosen a variety of different illegal acts. Bedau writes, "There is a whole class of acts, undertaken in the name of civil disobedience, which, even if they were widely practiced, would in themselves constitute hardly more than a nuisance (e.g. trespassing at a nuclear-missile installation)...Such acts are often just a harassment and, at least to the bystander, somewhat inane...The remoteness of the connection between the disobedient act and the objectionable law lays such acts open to the charge of ineffectiveness and absurdity." Bedau also notes, though, that the very harmlessness of such entirely symbolic illegal protests toward public policy goals may serve a propaganda purpose. Some civil disobedients, such as the proprietors of illegal medical cannabis dispensaries and Voice in the Wilderness, which brought medicine to Iraq without the permission of the U.S. Government, directly achieve a desired social goal (such as the provision of medication to the sick) while openly breaking the law. Julia Butterfly Hill lived in Luna, a 180-foot (55 m)-tall, 600-year-old California Redwood tree for 738 days, successfully preventing it from being cut down.


What is the name of the supposition that any number larger than 2 can be represented as the sum of two primes?

What is the name of the number theory, or rather, the supposition that any number larger than 2 can be represented as the sum of two primes?

Prime_number

Context: Many questions regarding prime numbers remain open, such as Goldbach's conjecture (that every even integer greater than 2 can be expressed as the sum of two primes), and the twin prime conjecture (that there are infinitely many pairs of primes whose difference is 2). Such questions spurred the development of various branches of number theory, focusing on analytic or algebraic aspects of numbers. Primes are used in several routines in information technology, such as public-key cryptography, which makes use of properties such as the difficulty of factoring large numbers into their prime factors. Prime numbers give rise to various generalizations in other mathematical domains, mainly algebra, such as prime elements and prime ideals.

Answer: Goldbach's conjecture

Answer: Goldbach's conjecture

Answer: Goldbach's conjecture

Answer: Goldbach's conjecture

Answer: Goldbach's conjecture


Who represents instead how about which group sets the time agenda?

Scottish_Parliament

Context: As a member of the Scottish Parliamentary Corporate Body, the Presiding Officer is responsible for ensuring that the Parliament functions effectively and has the staff, property and resources it requires to operate. Convening the Parliamentary Bureau, which allocates time and sets the work agenda in the chamber, is another of the roles of the Presiding Officer. Under the Standing Orders of the Parliament the Bureau consists of the Presiding Officer and one representative from each political parties with five or more seats in the Parliament. Amongst the duties of the Bureau are to agree the timetable of business in the chamber, establish the number, remit and membership of parliamentary committees and regulate the passage of legislation (bills) through the Parliament. The Presiding Officer also represents the Scottish Parliament at home and abroad in an official capacity.


When three forces act on a point particle, what happens?

What geometric er when three forces act on a point particle, what happens?

Force

Context: Historically, forces were first quantitatively investigated in conditions of static equilibrium where several forces canceled each other out. Such experiments demonstrate the crucial properties that forces are additive vector quantities: they have magnitude and direction. When two forces act on a point particle, the resulting force, the resultant (also called the net force), can be determined by following the parallelogram rule of vector addition: the addition of two vectors represented by sides of a parallelogram, gives an equivalent resultant vector that is equal in magnitude and direction to the transversal of the parallelogram. The magnitude of the resultant varies from the difference of the magnitudes of the two forces to their sum, depending on the angle between their lines of action. However, if the forces are acting on an extended body, their respective lines of application must also be specified in order to account for their effects on the motion of the body.


"""
An implementation of the model described in "Differentiable Sparse Coding" by
Bradley and Bagnell
"""
__authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"

import logging
import numpy as N
from theano.compat.six.moves import xrange
import theano.tensor as T

import theano
from theano import function, shared, config
floatX = config.floatX
from pylearn2.utils.rng import make_np_rng

logger = logging.getLogger(__name__)

class DifferentiableSparseCoding(object):
    """
    .. todo::

        WRITEME

    Parameters
    ----------
    nvis : WRITEME
    nhid : WRITEME
    init_lambda : WRITEME
    init_p : WRITEME
    init_alpha : WRITEME
    learning_rate : WRITEME
    """

    def __init__(self, nvis, nhid,
            init_lambda,
            init_p, init_alpha, learning_rate):
        self.nvis = int(nvis)
        self.nhid = int(nhid)
        self.init_lambda = float(init_lambda)
        self.init_p = float(init_p)
        self.init_alpha = N.cast[config.floatX](init_alpha)
        self.tol = 1e-6
        self.time_constant = 1e-2
        self.learning_rate = N.cast[config.floatX](learning_rate)

        self.predictor_learning_rate = self.learning_rate

        self.rng = make_np_rng(None, [1,2,3], which_method="randn")

        self.error_record = []
        self.ERROR_RECORD_MODE_MONITORING = 0
        self.error_record_mode = self.ERROR_RECORD_MODE_MONITORING

        self.instrumented = False

        self.redo_everything()

    def get_output_dim(self):
        """
        .. todo::

            WRITEME
        """
        return self.nhid

    def get_output_channels(self):
        """
        .. todo::

            WRITEME
        """
        return self.nhid

    def normalize_W(self):
        """
        .. todo::

            WRITEME
        """
        W = self.W.get_value(borrow=True)
        norms = N.sqrt(N.square(W).sum(axis=0))
        self.W.set_value(W/norms, borrow=True)

    def redo_everything(self):
        """
        .. todo::

            WRITEME
        """
        self.W = shared(N.cast[floatX](self.rng.randn(self.nvis,self.nhid)), name='W')

        self.pred_W = shared(self.W.get_value(borrow=False),name='pred_W')
        self.pred_b = shared(N.zeros(self.nhid,dtype=floatX),name='pred_b')
        self.pred_g = shared(N.ones(self.nhid,dtype=floatX),name='pred_g')

        self.normalize_W()
        self.p = shared(N.zeros(self.nhid, dtype=floatX)+N.cast[floatX](self.init_p), name='p')

        #mispelling lambda because python is too dumb to know that self.lambda isn't a lambda function
        self.lamda = shared(
                            N.zeros(
                                    self.nhid, dtype=floatX)+
                            N.cast[floatX](self.init_lambda), name='lambda')

        self.alpha = self.init_alpha
        self.failure_rate = .5

        self.examples_seen = 0
        self.batches_seen = 0

        self.redo_theano()

    def recons_error(self, v, h):
        """
        .. todo::

            WRITEME
        """
        recons = T.dot(self.W,h)
        diffs = recons - v
        rval = T.dot(diffs,diffs) / N.cast[floatX](self.nvis)
        return rval

    def recons_error_batch(self, V, H):
        """
        .. todo::

            WRITEME
        """
        recons = T.dot(H,self.W.T)
        diffs = recons - V
        rval = T.mean(T.sqr(diffs))
        return rval

    def sparsity_penalty(self, v, h):
        """
        .. todo::

            WRITEME
        """
        sparsity_measure = h * T.log(h) - h * T.log(self.p) - h + self.p
        rval = T.dot(self.lamda, sparsity_measure) / N.cast[floatX](self.nhid)
        return rval

    def sparsity_penalty_batch(self, V, H):
        """
        .. todo::

            WRITEME
        """
        sparsity_measure = H * T.log(H) - H * T.log(self.p) - H + self.p
        sparsity_measure_exp = T.mean(sparsity_measure, axis=0)
        rval = T.dot(self.lamda, sparsity_measure_exp) / N.cast[floatX](self.nhid)
        return rval

    def coding_obj(self, v, h):
        """
        .. todo::

            WRITEME
        """
        return self.recons_error(v,h) + self.sparsity_penalty(v,h)

    def coding_obj_batch(self, V, H):
        """
        .. todo::

            WRITEME
        """
        return self.recons_error_batch(V,H) + self.sparsity_penalty_batch(V,H)

    def predict(self, V):
        """
        .. todo::

            WRITEME
        """
        rval =  T.nnet.sigmoid(T.dot(V,self.pred_W)+self.pred_b)*self.pred_g
        assert rval.type.dtype == V.type.dtype
        return rval

    def redo_theano(self):
        """
        .. todo::

            WRITEME
        """

        self.h = shared(N.zeros(self.nhid, dtype=floatX), name='h')
        self.v = shared(N.zeros(self.nvis, dtype=floatX), name='v')

        input_v = T.vector()
        assert input_v.type.dtype == floatX

        self.init_h_v = function([input_v], updates = { self.h : self.predict(input_v),
                                                 self.v : input_v } )

        coding_obj = self.coding_obj(self.v, self.h)
        assert len(coding_obj.type.broadcastable) == 0

        coding_grad = T.grad(coding_obj, self.h)
        assert len(coding_grad.type.broadcastable) == 1

        self.coding_obj_grad = function([], [coding_obj, coding_grad] )

        self.new_h = shared(N.zeros(self.nhid, dtype=floatX), name='new_h')

        alpha = T.scalar(name='alpha')

        outside_grad = T.vector(name='outside_grad')

        new_h = T.clip(self.h * T.exp(-alpha * outside_grad), 1e-10, 1e4)

        new_obj = self.coding_obj(self.v, new_h)

        self.try_step = function( [alpha, outside_grad], updates = { self.new_h : new_h }, outputs = new_obj )

        self.accept_h = function( [], updates = { self.h : self.new_h } )

        self.get_h = function( [] , self.h )

        V = T.matrix(name='V')
        H = T.matrix(name='H')

        coding_obj_batch = self.coding_obj_batch(V,H)

        self.code_learning_obj = function( [V,H], coding_obj_batch)

        learning_grad = T.grad( coding_obj_batch, self.W )
        self.code_learning_step = function( [V,H,alpha], updates = { self.W : self.W - alpha * learning_grad } )

        pred_obj = T.mean(T.sqr(self.predict(V)-H))

        predictor_params = [ self.pred_W, self.pred_b, self.pred_g ]

        pred_grads = T.grad(pred_obj, wrt = predictor_params )

        predictor_updates = {}

        for param, grad in zip(predictor_params, pred_grads):
            predictor_updates[param] = param - alpha * grad

        predictor_updates[self.pred_g ] = T.clip(predictor_updates[self.pred_g], N.cast[floatX](0.5), N.cast[floatX](1000.))

        self.train_predictor = function([V,H,alpha] , updates = predictor_updates )

    def weights_format(self):
        """
        .. todo::

            WRITEME
        """
        return ['v','h']

    def error_func(self, x):
        """
        .. todo::

            WRITEME
        """
        batch_size = x.shape[0]

        H = N.zeros((batch_size,self.nhid),dtype=floatX)

        for i in xrange(batch_size):
            assert self.alpha > 9e-8
            H[i,:] = self.optimize_h(x[i,:])
            assert self.alpha > 9e-8

        return self.code_learning_obj(x,H)

    def record_monitoring_error(self, dataset, batch_size, batches):
        """
        .. todo::

            WRITEME
        """
        logger.info('running on monitoring set')
        assert self.error_record_mode == self.ERROR_RECORD_MODE_MONITORING

        w = self.W.get_value(borrow=True)
        logger.info('weights summary: '
                    '({0}, {1}, {2})'.format(w.min(), w.mean(), w.max()))

        errors = []

        if self.instrumented:
            self.clear_instruments()

        for i in xrange(batches):
            x = dataset.get_batch_design(batch_size)
            error = self.error_func(x)
            errors.append( error )
            if self.instrumented:
                self.update_instruments(x)

        self.error_record.append( (self.examples_seen, self.batches_seen, N.asarray(errors).mean() ) )

        if self.instrumented:
            self.instrument_record.begin_report(examples_seen = self.examples_seen, batches_seen = self.batches_seen)
            self.make_instrument_report()
            self.instrument_record.end_report()
            self.clear_instruments()
        logger.info('monitoring set done')

    def infer_h(self, v):
        """
        .. todo::

            WRITEME
        """
        return self.optimize_h(v)

    def optimize_h(self, v):
        """
        .. todo::

            WRITEME
        """
        assert self.alpha > 9e-8

        self.init_h_v(v)

        first = True

        while True:
            obj, grad = self.coding_obj_grad()

            if first:
                #print 'orig_obj: ', obj
                first = False

            assert not N.any(N.isnan(obj))
            assert not N.any(N.isnan(grad))

            if N.abs(grad).max() < self.tol:
                break

            #print 'max gradient ',N.abs(grad).max()

            cur_alpha = N.cast[floatX] ( self.alpha  + 0.0 )

            new_obj = self.try_step(cur_alpha, grad)

            assert not N.isnan(new_obj)

            self.failure_rate =  (1. - self.time_constant ) * self.failure_rate + self.time_constant * float(new_obj > obj )

            assert self.alpha > 9e-8

            if self.failure_rate  > .6 and self.alpha > 1e-7:
                self.alpha *= .9
                #print '!!!!!!!!!!!!!!!!!!!!!!shrank alpha to ',self.alpha
            elif self.failure_rate < .3:
                self.alpha *= 1.1
                #print '**********************grew alpha to ',self.alpha

            assert self.alpha > 9e-8

            while new_obj >= obj:
                cur_alpha *= .9

                if cur_alpha < 1e-12:
                    self.accept_h()
                    #print 'failing final obj ',new_obj
                    return self.get_h()

                new_obj = self.try_step(cur_alpha, grad)

                assert not N.isnan(new_obj)

            self.accept_h()

        #print 'final obj ',new_obj
        return self.get_h()

    def train_batch(self, dataset, batch_size):
        """
        .. todo::

            WRITEME
        """
        self.learn_mini_batch(dataset.get_batch_design(batch_size))
        return True

    def learn_mini_batch(self, x):
        """
        .. todo::

            WRITEME
        """
        assert self.alpha > 9e-8

        batch_size = x.shape[0]

        H = N.zeros((batch_size,self.nhid),dtype=floatX)

        for i in xrange(batch_size):
            assert self.alpha > 9e-8
            H[i,:] = self.optimize_h(x[i,:])
            assert self.alpha > 9e-8

        self.code_learning_step(x,H,self.learning_rate)
        self.normalize_W()

        self.train_predictor(x,H,self.predictor_learning_rate)

        self.examples_seen += x.shape[0]
        self.batches_seen += 1


#!/usr/bin/env python

# Copyright (c) 2009, Giampaolo Rodola'. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.

"""OSX platform implementation."""

import errno
import functools
import os
from collections import namedtuple

from . import _common
from . import _psposix
from . import _psutil_osx as cext
from . import _psutil_posix as cext_posix
from ._common import conn_tmap, usage_percent, isfile_strict
from ._common import sockfam_to_enum, socktype_to_enum

__extra__all__ = []

# --- constants

PAGESIZE = os.sysconf("SC_PAGE_SIZE")
AF_LINK = cext_posix.AF_LINK

# http://students.mimuw.edu.pl/lxr/source/include/net/tcp_states.h
TCP_STATUSES = {
    cext.TCPS_ESTABLISHED: _common.CONN_ESTABLISHED,
    cext.TCPS_SYN_SENT: _common.CONN_SYN_SENT,
    cext.TCPS_SYN_RECEIVED: _common.CONN_SYN_RECV,
    cext.TCPS_FIN_WAIT_1: _common.CONN_FIN_WAIT1,
    cext.TCPS_FIN_WAIT_2: _common.CONN_FIN_WAIT2,
    cext.TCPS_TIME_WAIT: _common.CONN_TIME_WAIT,
    cext.TCPS_CLOSED: _common.CONN_CLOSE,
    cext.TCPS_CLOSE_WAIT: _common.CONN_CLOSE_WAIT,
    cext.TCPS_LAST_ACK: _common.CONN_LAST_ACK,
    cext.TCPS_LISTEN: _common.CONN_LISTEN,
    cext.TCPS_CLOSING: _common.CONN_CLOSING,
    cext.PSUTIL_CONN_NONE: _common.CONN_NONE,
}

PROC_STATUSES = {
    cext.SIDL: _common.STATUS_IDLE,
    cext.SRUN: _common.STATUS_RUNNING,
    cext.SSLEEP: _common.STATUS_SLEEPING,
    cext.SSTOP: _common.STATUS_STOPPED,
    cext.SZOMB: _common.STATUS_ZOMBIE,
}

scputimes = namedtuple('scputimes', ['user', 'nice', 'system', 'idle'])

svmem = namedtuple(
    'svmem', ['total', 'available', 'percent', 'used', 'free',
              'active', 'inactive', 'wired'])

pextmem = namedtuple('pextmem', ['rss', 'vms', 'pfaults', 'pageins'])

pmmap_grouped = namedtuple(
    'pmmap_grouped',
    'path rss private swapped dirtied ref_count shadow_depth')

pmmap_ext = namedtuple(
    'pmmap_ext', 'addr perms ' + ' '.join(pmmap_grouped._fields))

# set later from __init__.py
NoSuchProcess = None
ZombieProcess = None
AccessDenied = None
TimeoutExpired = None

# --- functions

def virtual_memory():
    """System virtual memory as a namedtuple."""
    total, active, inactive, wired, free = cext.virtual_mem()
    avail = inactive + free
    used = active + inactive + wired
    percent = usage_percent((total - avail), total, _round=1)
    return svmem(total, avail, percent, used, free,
                 active, inactive, wired)

def swap_memory():
    """Swap system memory as a (total, used, free, sin, sout) tuple."""
    total, used, free, sin, sout = cext.swap_mem()
    percent = usage_percent(used, total, _round=1)
    return _common.sswap(total, used, free, percent, sin, sout)

def cpu_times():
    """Return system CPU times as a namedtuple."""
    user, nice, system, idle = cext.cpu_times()
    return scputimes(user, nice, system, idle)

def per_cpu_times():
    """Return system CPU times as a named tuple"""
    ret = []
    for cpu_t in cext.per_cpu_times():
        user, nice, system, idle = cpu_t
        item = scputimes(user, nice, system, idle)
        ret.append(item)
    return ret

def cpu_count_logical():
    """Return the number of logical CPUs in the system."""
    return cext.cpu_count_logical()

def cpu_count_physical():
    """Return the number of physical CPUs in the system."""
    return cext.cpu_count_phys()

def boot_time():
    """The system boot time expressed in seconds since the epoch."""
    return cext.boot_time()

def disk_partitions(all=False):
    retlist = []
    partitions = cext.disk_partitions()
    for partition in partitions:
        device, mountpoint, fstype, opts = partition
        if device == 'none':
            device = ''
        if not all:
            if not os.path.isabs(device) or not os.path.exists(device):
                continue
        ntuple = _common.sdiskpart(device, mountpoint, fstype, opts)
        retlist.append(ntuple)
    return retlist

def users():
    retlist = []
    rawlist = cext.users()
    for item in rawlist:
        user, tty, hostname, tstamp = item
        if tty == '~':
            continue  # reboot or shutdown
        if not tstamp:
            continue
        nt = _common.suser(user, tty or None, hostname or None, tstamp)
        retlist.append(nt)
    return retlist

def net_connections(kind='inet'):
    # Note: on OSX this will fail with AccessDenied unless
    # the process is owned by root.
    ret = []
    for pid in pids():
        try:
            cons = Process(pid).connections(kind)
        except NoSuchProcess:
            continue
        else:
            if cons:
                for c in cons:
                    c = list(c) + [pid]
                    ret.append(_common.sconn(*c))
    return ret

def net_if_stats():
    """Get NIC stats (isup, duplex, speed, mtu)."""
    names = net_io_counters().keys()
    ret = {}
    for name in names:
        isup, duplex, speed, mtu = cext_posix.net_if_stats(name)
        if hasattr(_common, 'NicDuplex'):
            duplex = _common.NicDuplex(duplex)
        ret[name] = _common.snicstats(isup, duplex, speed, mtu)
    return ret

pids = cext.pids
pid_exists = _psposix.pid_exists
disk_usage = _psposix.disk_usage
net_io_counters = cext.net_io_counters
disk_io_counters = cext.disk_io_counters
net_if_addrs = cext_posix.net_if_addrs

def wrap_exceptions(fun):
    """Decorator which translates bare OSError exceptions into
    NoSuchProcess and AccessDenied.
    """
    @functools.wraps(fun)
    def wrapper(self, *args, **kwargs):
        try:
            return fun(self, *args, **kwargs)
        except OSError as err:
            # support for private module import
            if (NoSuchProcess is None or AccessDenied is None or
                    ZombieProcess is None):
                raise
            if err.errno == errno.ESRCH:
                if not pid_exists(self.pid):
                    raise NoSuchProcess(self.pid, self._name)
                else:
                    raise ZombieProcess(self.pid, self._name, self._ppid)
            if err.errno in (errno.EPERM, errno.EACCES):
                raise AccessDenied(self.pid, self._name)
            raise
    return wrapper

class Process(object):
    """Wrapper class around underlying C implementation."""

    __slots__ = ["pid", "_name", "_ppid"]

    def __init__(self, pid):
        self.pid = pid
        self._name = None
        self._ppid = None

    @wrap_exceptions
    def name(self):
        return cext.proc_name(self.pid)

    @wrap_exceptions
    def exe(self):
        return cext.proc_exe(self.pid)

    @wrap_exceptions
    def cmdline(self):
        if not pid_exists(self.pid):
            raise NoSuchProcess(self.pid, self._name)
        return cext.proc_cmdline(self.pid)

    @wrap_exceptions
    def ppid(self):
        return cext.proc_ppid(self.pid)

    @wrap_exceptions
    def cwd(self):
        return cext.proc_cwd(self.pid)

    @wrap_exceptions
    def uids(self):
        real, effective, saved = cext.proc_uids(self.pid)
        return _common.puids(real, effective, saved)

    @wrap_exceptions
    def gids(self):
        real, effective, saved = cext.proc_gids(self.pid)
        return _common.pgids(real, effective, saved)

    @wrap_exceptions
    def terminal(self):
        tty_nr = cext.proc_tty_nr(self.pid)
        tmap = _psposix._get_terminal_map()
        try:
            return tmap[tty_nr]
        except KeyError:
            return None

    @wrap_exceptions
    def memory_info(self):
        rss, vms = cext.proc_memory_info(self.pid)[:2]
        return _common.pmem(rss, vms)

    @wrap_exceptions
    def memory_info_ex(self):
        rss, vms, pfaults, pageins = cext.proc_memory_info(self.pid)
        return pextmem(rss, vms, pfaults * PAGESIZE, pageins * PAGESIZE)

    @wrap_exceptions
    def cpu_times(self):
        user, system = cext.proc_cpu_times(self.pid)
        return _common.pcputimes(user, system)

    @wrap_exceptions
    def create_time(self):
        return cext.proc_create_time(self.pid)

    @wrap_exceptions
    def num_ctx_switches(self):
        return _common.pctxsw(*cext.proc_num_ctx_switches(self.pid))

    @wrap_exceptions
    def num_threads(self):
        return cext.proc_num_threads(self.pid)

    @wrap_exceptions
    def open_files(self):
        if self.pid == 0:
            return []
        files = []
        rawlist = cext.proc_open_files(self.pid)
        for path, fd in rawlist:
            if isfile_strict(path):
                ntuple = _common.popenfile(path, fd)
                files.append(ntuple)
        return files

    @wrap_exceptions
    def connections(self, kind='inet'):
        if kind not in conn_tmap:
            raise ValueError("invalid %r kind argument; choose between %s"
                             % (kind, ', '.join([repr(x) for x in conn_tmap])))
        families, types = conn_tmap[kind]
        rawlist = cext.proc_connections(self.pid, families, types)
        ret = []
        for item in rawlist:
            fd, fam, type, laddr, raddr, status = item
            status = TCP_STATUSES[status]
            fam = sockfam_to_enum(fam)
            type = socktype_to_enum(type)
            nt = _common.pconn(fd, fam, type, laddr, raddr, status)
            ret.append(nt)
        return ret

    @wrap_exceptions
    def num_fds(self):
        if self.pid == 0:
            return 0
        return cext.proc_num_fds(self.pid)

    @wrap_exceptions
    def wait(self, timeout=None):
        try:
            return _psposix.wait_pid(self.pid, timeout)
        except _psposix.TimeoutExpired:
            # support for private module import
            if TimeoutExpired is None:
                raise
            raise TimeoutExpired(timeout, self.pid, self._name)

    @wrap_exceptions
    def nice_get(self):
        return cext_posix.getpriority(self.pid)

    @wrap_exceptions
    def nice_set(self, value):
        return cext_posix.setpriority(self.pid, value)

    @wrap_exceptions
    def status(self):
        code = cext.proc_status(self.pid)
        # XXX is '?' legit? (we're not supposed to return it anyway)
        return PROC_STATUSES.get(code, '?')

    @wrap_exceptions
    def threads(self):
        rawlist = cext.proc_threads(self.pid)
        retlist = []
        for thread_id, utime, stime in rawlist:
            ntuple = _common.pthread(thread_id, utime, stime)
            retlist.append(ntuple)
        return retlist

    @wrap_exceptions
    def memory_maps(self):
        return cext.proc_memory_maps(self.pid)


#!/usr/bin/python
# -- Content-Encoding: UTF-8 --
"""
Utility methods, for compatibility between Python version

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.

:author: Thomas Calmant
:license: Apache License 2.0
:version: 1.0.1
"""

# Module version
__version_info__ = (0, 2, 1)
__version__ = ".".join(str(x) for x in __version_info__)

# Documentation strings format
__docformat__ = "restructuredtext en"

# ------------------------------------------------------------------------------

import sys

# ------------------------------------------------------------------------------

if sys.version_info[0] < 3:
    # Python 2
    import types
    try:
        string_types = (
            types.StringType,
            types.UnicodeType
        )
    except NameError:
        # Python built without unicode support
        string_types = (types.StringType,)

    numeric_types = (
        types.IntType,
        types.LongType,
        types.FloatType
    )

    def to_bytes(string):
        """
        Converts the given string into bytes
        """
        if type(string) is unicode:
            return str(string)
        return string

    def from_bytes(data):
        """
        Converts the given bytes into a string
        """
        if type(data) is str:
            return data
        return str(data)

else:
    # Python 3
    string_types = (
        bytes,
        str
    )

    numeric_types = (
        int,
        float
    )

    def to_bytes(string):
        """
        Converts the given string into bytes
        """
        if type(string) is bytes:
            return string
        return bytes(string, "UTF-8")

    def from_bytes(data):
        """
        Converts the given bytes into a string
        """
        if type(data) is str:
            return data
        return str(data, "UTF-8")

# ------------------------------------------------------------------------------
# Common

DictType = dict

ListType = list
TupleType = tuple

iterable_types = (
    list,
    set, frozenset,
    tuple
)

value_types = (
    bool,
    type(None)
)

primitive_types = string_types + numeric_types + value_types


#    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.

import copy
from oslo_log import log as logging

from tempest import exceptions
from tempest.lib.common.utils import misc as misc_utils

LOG = logging.getLogger(__name__)

def get_network_from_name(name, compute_networks_client):
    """Get a full network dict from just a network name

    :param str name: the name of the network to use
    :param NetworksClient compute_networks_client: The network client
        object to use for making the network lists api request
    :return: The full dictionary for the network in question
    :rtype: dict
    :raises InvalidTestResource: If the name provided is invalid, the networks
        list returns a 404, there are no found networks, or the found network
        is invalid
    """
    caller = misc_utils.find_test_caller()

    if not name:
        raise exceptions.InvalidTestResource(type='network', name=name)

    networks = compute_networks_client.list_networks()['networks']
    networks = [n for n in networks if n['label'] == name]

    # Check that a network exists, else raise an InvalidConfigurationException
    if len(networks) == 1:
        network = sorted(networks)[0]
    elif len(networks) > 1:
        msg = ("Network with name: %s had multiple matching networks in the "
               "list response: %s\n Unable to specify a single network" % (
                   name, networks))
        if caller:
            msg = '(%s) %s' % (caller, msg)
        LOG.warning(msg)
        raise exceptions.InvalidTestResource(type='network', name=name)
    else:
        msg = "Network with name: %s not found" % name
        if caller:
            msg = '(%s) %s' % (caller, msg)
        LOG.warning(msg)
        raise exceptions.InvalidTestResource(type='network', name=name)
    # To be consistent between neutron and nova network always use name even
    # if label is used in the api response. If neither is present than then
    # the returned network is invalid.
    name = network.get('name') or network.get('label')
    if not name:
        msg = "Network found from list doesn't contain a valid name or label"
        if caller:
            msg = '(%s) %s' % (caller, msg)
        LOG.warning(msg)
        raise exceptions.InvalidTestResource(type='network', name=name)
    network['name'] = name
    return network

def get_tenant_network(creds_provider, compute_networks_client,
                       shared_network_name):
    """Get a network usable by the primary tenant

    :param creds_provider: instance of credential provider
    :param compute_networks_client: compute network client. We want to have the
           compute network client so we can have use a common approach for both
           neutron and nova-network cases. If this is not an admin network
           client, set_network_kwargs might fail in case fixed_network_name
           is the network to be used, and it's not visible to the tenant
    :param shared_network_name: name of the shared network to be used if no
           tenant network is available in the creds provider
    :returns: a dict with 'id' and 'name' of the network
    """
    caller = misc_utils.find_test_caller()
    net_creds = creds_provider.get_primary_creds()
    network = getattr(net_creds, 'network', None)
    if not network or not network.get('name'):
        if shared_network_name:
            msg = ('No valid network provided or created, defaulting to '
                   'fixed_network_name')
            if caller:
                msg = '(%s) %s' % (caller, msg)
            LOG.debug(msg)
            try:
                network = get_network_from_name(shared_network_name,
                                                compute_networks_client)
            except exceptions.InvalidTestResource:
                network = {}
    msg = ('Found network %s available for tenant' % network)
    if caller:
        msg = '(%s) %s' % (caller, msg)
    LOG.info(msg)
    return network

def set_networks_kwarg(network, kwargs=None):
    """Set 'networks' kwargs for a server create if missing

    :param network: dict of network to be used with 'id' and 'name'
    :param kwargs: server create kwargs to be enhanced
    :return: new dict of kwargs updated to include networks
    """
    params = copy.copy(kwargs) or {}
    if kwargs and 'networks' in kwargs:
        return params

    if network:
        if 'id' in network.keys():
            params.update({"networks": [{'uuid': network['id']}]})
        else:
            LOG.warning('The provided network dict: %s was invalid and did '
                        'not contain an id' % network)
    return params


"""Recognize image file formats based on their first few bytes."""

__all__ = ["what"]

#-------------------------#
# Recognize image headers #
#-------------------------#

def what(file, h=None):
    f = None
    try:
        if h is None:
            if isinstance(file, str):
                f = open(file, 'rb')
                h = f.read(32)
            else:
                location = file.tell()
                h = file.read(32)
                file.seek(location)
        for tf in tests:
            res = tf(h, f)
            if res:
                return res
    finally:
        if f: f.close()
    return None

#---------------------------------#
# Subroutines per image file type #
#---------------------------------#

tests = []

def test_jpeg(h, f):
    """JPEG data in JFIF or Exif format"""
    if h[6:10] in (b'JFIF', b'Exif'):
        return 'jpeg'

tests.append(test_jpeg)

def test_png(h, f):
    if h.startswith(b'\211PNG\r\n\032\n'):
        return 'png'

tests.append(test_png)

def test_gif(h, f):
    """GIF ('87 and '89 variants)"""
    if h[:6] in (b'GIF87a', b'GIF89a'):
        return 'gif'

tests.append(test_gif)

def test_tiff(h, f):
    """TIFF (can be in Motorola or Intel byte order)"""
    if h[:2] in (b'MM', b'II'):
        return 'tiff'

tests.append(test_tiff)

def test_rgb(h, f):
    """SGI image library"""
    if h.startswith(b'\001\332'):
        return 'rgb'

tests.append(test_rgb)

def test_pbm(h, f):
    """PBM (portable bitmap)"""
    if len(h) >= 3 and \
        h[0] == ord(b'P') and h[1] in b'14' and h[2] in b' \t\n\r':
        return 'pbm'

tests.append(test_pbm)

def test_pgm(h, f):
    """PGM (portable graymap)"""
    if len(h) >= 3 and \
        h[0] == ord(b'P') and h[1] in b'25' and h[2] in b' \t\n\r':
        return 'pgm'

tests.append(test_pgm)

def test_ppm(h, f):
    """PPM (portable pixmap)"""
    if len(h) >= 3 and \
        h[0] == ord(b'P') and h[1] in b'36' and h[2] in b' \t\n\r':
        return 'ppm'

tests.append(test_ppm)

def test_rast(h, f):
    """Sun raster file"""
    if h.startswith(b'\x59\xA6\x6A\x95'):
        return 'rast'

tests.append(test_rast)

def test_xbm(h, f):
    """X bitmap (X10 or X11)"""
    if h.startswith(b'#define '):
        return 'xbm'

tests.append(test_xbm)

def test_bmp(h, f):
    if h.startswith(b'BM'):
        return 'bmp'

tests.append(test_bmp)

#--------------------#
# Small test program #
#--------------------#

def test():
    import sys
    recursive = 0
    if sys.argv[1:] and sys.argv[1] == '-r':
        del sys.argv[1:2]
        recursive = 1
    try:
        if sys.argv[1:]:
            testall(sys.argv[1:], recursive, 1)
        else:
            testall(['.'], recursive, 1)
    except KeyboardInterrupt:
        sys.stderr.write('\n[Interrupted]\n')
        sys.exit(1)

def testall(list, recursive, toplevel):
    import sys
    import os
    for filename in list:
        if os.path.isdir(filename):
            print(filename + '/:', end=' ')
            if recursive or toplevel:
                print('recursing down:')
                import glob
                names = glob.glob(os.path.join(filename, '*'))
                testall(names, recursive, 0)
            else:
                print('*** directory (use -r) ***')
        else:
            print(filename + ':', end=' ')
            sys.stdout.flush()
            try:
                print(what(filename))
            except OSError:
                print('*** not found ***')

if __name__ == '__main__':
    test()


from xmodule.x_module import XModule
from xmodule.raw_module import RawDescriptor

class HiddenModule(XModule):
    def get_html(self):
        if self.system.user_is_staff:
            return u"ERROR: This module is unknown--students will not see it at all"
        else:
            return u""

class HiddenDescriptor(RawDescriptor):
    module_class = HiddenModule


'''Searches wikipedia and returns first sentence of article
Scaevolus 2009'''

import re

from util import hook, http

api_prefix = "http://en.wikipedia.org/w/api.php"
search_url = api_prefix + "?action=opensearch&format=xml"

paren_re = re.compile('\s*\(.*\)$')

@hook.command('w')
@hook.command
def wiki(inp):
    '''.w/.wiki <phrase> -- gets first sentence of wikipedia ''' \
        '''article on <phrase>'''

    x = http.get_xml(search_url, search=inp)

    ns = '{http://opensearch.org/searchsuggest2}'
    items = x.findall(ns + 'Section/' + ns + 'Item')

    if items == []:
        if x.find('error') is not None:
            return 'error: %(code)s: %(info)s' % x.find('error').attrib
        else:
            return 'no results found'

    def extract(item):
        return [item.find(ns + x).text for x in
                ('Text', 'Description', 'Url')]

    title, desc, url = extract(items[0])

    if 'may refer to' in desc:
        title, desc, url = extract(items[1])

    title = paren_re.sub('', title)

    if title.lower() not in desc.lower():
        desc = title + desc

    desc = re.sub('\s+', ' ', desc).strip()  # remove excess spaces

    if len(desc) > 300:
        desc = desc[:300] + '...'

    return '%s -- %s' % (desc, http.quote(http.unquote(url), ':/'))


class C:
    def __matmul<caret>


# -*- coding: utf-8 -*-
##############################################################################
#
#    OpenERP, Open Source Management Solution
#    Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>).
#
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU Affero General Public License as
#    published by the Free Software Foundation, either version 3 of the
#    License, or (at your option) any later version.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU Affero General Public License for more details.
#
#    You should have received a copy of the GNU Affero General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
##############################################################################

{
    'name': 'Marketing Campaign - Demo',
    'version': '1.0',
    'depends': ['marketing_campaign',
                 'crm',
    ],
    'author': 'OpenERP SA',
    'category': 'Marketing',
    'description': """
Demo data for the module marketing_campaign.
============================================

Creates demo data like leads, campaigns and segments for the module marketing_campaign.
    """,
    'website': 'http://www.openerp.com',
    'data': [],
    'demo': ['marketing_campaign_demo.xml'],
    'installable': True,
    'auto_install': False,
    'images': ['images/campaigns.jpeg','images/email_templates.jpeg'],
}
# vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:


buen tip muchas gracias


A Porthcawl RNLI crew with a medic and the coastguard search and rescue helicopter were sent to Sker Beach, near Kenfig Nature Reserve, at 12:50 GMT on Sunday.
Crewman Chris Page said the rider had head injuries and was very cold from lying unconscious on wet sand.
She was treated before being flown to Cardiff's University Hospital of Wales.

A woman has been airlifted to hospital after falling from a horse on a Bridgend county beach.


Verheydt, who had been with Maastricht since 2015, has signed a three-year contract with Harry Kewell's side.
The 25-year-old scored 13 goals in 43 appearances in all competitions last season.
Meanwhile, Watford winger Dennon Lewis, 20, has joined the Reds on a loan deal until 31 December.
Lewis, who made 29 National League appearances on loan at Woking last season, played under Kewell when the Australian was coach of Watford's under-23 team.
Find all the latest football transfers on our dedicated page.

League Two side Crawley Town have signed striker Thomas Verheydt from Dutch second-tier side MVV Maastricht for an undisclosed fee.


The 32-year-old had been playing in the Isthmian Premier Division with Leatherhead following his release by Newport at the end of last season.
Pidgeley has made 260 appearances in spells with nine clubs, including Chelsea, Watford and Millwall.
Forest Green are currently second in the National League table, one point behind leaders Cheltenham Town.
Pidgeley could make his Rovers debut when they host Aldershot on Friday.

National League side Forest Green Rovers have signed goalkeeper Lenny Pidgeley until the end of the season.


The suspected green mamba was found on a ship that had docked in Aberdeen from west Africa last month.
The snake died after it was placed in a freezer by the animal charity after attempts to rehome it with specialist reptile keepers failed.
The snake was later identified as a harmless green tree snake.
Police Scotland said a complaint was under consideration.
Scottish SPCA Ch Supt Mike Flynn said: "We were called out after a green snake arrived in Aberdeen on a boat from Africa.
"The snake was thought to be a green mamba, one of the deadliest snakes in the world. The snake was taken by police escort to our Aberdeenshire animal rescue and rehoming centre.
"Sadly the snake, which staff genuinely believed to be a green mamba, had to be put to sleep after our attempts to rehome it to specialist reptile keepers were unsuccessful."
He added: "We could not keep the snake in our centre due to severe health and safety concerns, as the closest anti-venom is held in Bedford. Green mambas also require a Dangerous Wild Animal Licence which the society does not have.
"The safety of our staff and the public is paramount and as such the snake was placed in a freezer where it passed away.
"The Scottish SPCA is proud of its policy not put healthy animals to sleep. Animals are only put to sleep on veterinary advice if they are too ill or too aggressive to be rehomed, or where we are legally required to do so.
"The decision to euthanise the snake was not taken lightly. Unfortunately, the snake has since been identified as a harmless green tree snake. This has been an honest mistake on the society's part as we genuinely believed this was an extremely deadly snake."
The western green mamba feeds on small animals and rodents and is mainly found in the coastal tropical rainforests of western Africa.
Experts say its bite can be fatal in as little as 30 minutes.

A complaint about the Scottish SPCA putting what was thought to be one of the world's most deadly snakes to sleep is being investigated by police.


The all-rounder has been included in the T20 squad to face Sri Lanka on 5 July at the Ageas Bowl, having been part of the World T20 squad in March.
"It's nice to be involved again," the 26-year-old slow left-armer and right-handed batsman told BBC Radio Solent.
"I wasn't expecting to be as I thought Moeen Ali would, but him being rested hands me another opportunity."
Dawson failed to make an appearance during England's run to the World T20 final in India this year, but his limited-overs performances for Hampshire this season have kept him in contention.
"I'm not sure what team they'll go with," he said.
"I've had some good performances for Hampshire in one-day and T20 cricket and if I keep going with that, hopefully I might get a chance."

Hampshire's Liam Dawson says it would be "amazing" to make his England Twenty20 debut on his home ground.