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本文([考研类试卷]考研英语(二)模拟试卷134及答案与解析.doc)为本站会员(diecharacter305)主动上传,麦多课文库仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对上载内容本身不做任何修改或编辑。 若此文所含内容侵犯了您的版权或隐私,请立即通知麦多课文库(发送邮件至master@mydoc123.com或直接QQ联系客服),我们立即给予删除!

[考研类试卷]考研英语(二)模拟试卷134及答案与解析.doc

1、考研英语(二)模拟试卷 134 及答案与解析一、Section I Use of EnglishDirections: Read the following text. Choose the best word(s) for each numbered blank and mark A, B, C or D. (10 points) 0 We often tend to associate smiling as the result of a positive event or mood. But research demonstrates that the act of smiling, i

2、n and【 C1】_itself, can be the catalyst for joy. Wonderful things, ranging from an 【C2】_ mood to a better relationship, can be the result of the 【C3】_ act of smiling. Even better, it is a tool that is free, easy and always available.Even when you aren t feeling happy, smile can help【C4】_your mood. Da

3、rwin hypothesized, back in 1872, that making changes in our 【C5】_ expressions can influence our【C6】_experience, something he called facial feedback response theory. Psychological research has 【C7 】_ Darwin s assertion that expressions do not just result from moods, but actually influence them.Smilin

4、g more may actually【C8】_your lifespan. Research indicates that smiling may improve heart health by 【C9】_ heart rate after stressful events. So,【C10】_smiling to your health regime of eating well, getting enough sleep and exercising may just add【C11】_years to your life.People who smile more tend to be

5、 more【C12 】_, joyful and emotionally stable which lends itself to healthier relationships, and thus have longer and more successful【C13】_. An interesting study published in 2009 found a correlation between smiles in photographs and divorce rates. The larger the smile, the【C14】_likely divorce was lat

6、er in life.【C15】_, those with the smallest smiles or no smiles, were five times more likely to be divorced.When Mother Teresa said “Every time you smile at someone, it is . a【C16】_to that person, a beautiful thing“, she was right. One study【 C17】 _by Hewlett Packard found that seeing anothers smile

7、stimulated the heart and【C18】_more so than eating chocolate or receiving money. This was particularly true【C19 】_viewing the smile of a child. Additionally, research has demonstrated smiling may actually be easily diffused. Research published in the Scandinavian Journal of Psychology examined mimicr

8、y, the tendency to mimic the emotional expressions of those around us, and found that it is actually hard to【C20 】_when someone else is smiling.1 【C1 】(A)on(B) with(C) by(D)of2 【C2 】(A)impressed(B) improved(C) important(D)imposed3 【C3 】(A)pure(B) easy(C) simple(D)brief4 【C4 】(A)sack(B) shift(C) slip

9、(D)switch5 【C5 】(A)facial(B) superficial(C) external(D)inner6 【C6 】(A)inward(B) outward(C) emotional(D)explicit7 【C7 】(A)formalized(B) declared(C) implemented(D)validated8 【C8 】(A)execute(B) expand(C) examine(D)expect9 【C9 】(A)accelerating(B) decreasing(C) facilitating(D)increasing10 【C10 】(A)leadin

10、g(B) adding(C) contributing(D)resorting11 【C11 】(A)a little(B) little(C) few(D)a few12 【C12 】(A)optimistic(B) dispassionate(C) severe(D)cautious13 【C13 】(A)career(B) lifespan(C) marriage(D)friendship14 【C14 】(A)more(B) worse(C) less(D)better15 【C15 】(A)Consequently(B) Moreover(C) Conversely(D)Otherw

11、ise16 【C16 】(A)gift(B) regard(C) wish(D)grace17 【C17 】(A)discovered(B) converted(C) prepared(D)conducted18 【C18 】(A)stomach(B) brain(C) mindset(D)desire19 【C19 】(A)yet(B) when(C) though(D)unless20 【C20 】(A)sneer(B) blink(C) frown(D)breathePart ADirections: Read the following four texts. Answer the q

12、uestions below each text by choosing A, B, C or D. (40 points)20 Warren Buffett, who on May 3rd hosts the folksy extravaganza that is Berkshire Hathaways annual shareholders meeting, is an icon of American capitalism. At 83, he also embodies a striking demographic trend: for highly skilled people to

13、 go on working well into what was once thought to be old age. Across the rich world, well-educated people increasingly work longer than the less-skilled. Some 65% of American men aged 62-74 with a professional degree are in the workforce, compared with 32% of men with only a high-school certificate.

14、This gap is part of a deepening divide between the well-educated well-off and the unskilled poor that is slicing through all age groups. Rapid innovation has raised the incomes of the highly skilled while squeezing those of the unskilled. Those at the top are working longer hours each year than thos

15、e at the bottom. And the well-qualified are extending their working lives, compared with those of less-educated people. The consequences, for individuals and society, are profound.But the notion of a sharp division between the working young and the idle old misses a new trend, the growing gap betwee

16、n the skilled and the unskilled. Employment rates are falling among younger unskilled people, whereas older skilled folk are working longer. The divide is most extreme in America, where well-educated baby-boomers are putting off retirement while many less-skilled younger people have dropped out of t

17、he workforce.Policy is partly responsible. Many European governments have abandoned policies that used to encourage people to retire early. Rising life expectancy, combined with the replacement of generous defined-benefit pension plans with stingier defined-contribution ones, means that even the bet

18、ter-off must work longer to have a comfortable retirement. But the changing nature of work also plays a big role. Pay has risen sharply for the highly educated, and those people continue to reap rich rewards into old age because these days the educated elderly are more productive than their predeces

19、sors. Technological change may well reinforce that shift: the skills that complement computers, from management expertise to creativity, do not necessarily decline with age.This trend will benefit not just fortunate oldies but also, in some ways, society as a whole. Government budgets will be in bet

20、ter shape, as high earners pay taxes for longer. Rich countries with lots of well-educated older people will find the burden of ageing easier to bear than other places. At the other end of the social scale, however, things look grim. Nor are all the effects on the economy beneficial. Wealthy old peo

21、ple will accumulate more savings, which will weaken demand. Inequality will increase and a growing share of wealth will eventually be transferred to the next generation via inheritance, entrenching the division between winners and losers still further.21 According to the author, Warren Buffett hosti

22、ng the folksy extravaganza at 83 indicates that_.(A)the demographic development is shocking(B) he is the representative figure of American capitalism(C) the highly skilled continue to work as they grow older(D)Berkshire Hathaways shareholders meeting is held once a year22 The deepening divide betwee

23、n the well-educated well-off and the unskilled poor is revealed in the following aspects EXCEPT_.(A)revenue(B) working lives(C) working hours(D)the global population23 If well-educated folk postponed retirement, who would be influenced?(A)the unskilled young(B) the idle old(C) the working young(D)ba

24、by-boomers24 As mentioned in Paragraph 3 and 4, which is NOT the reason of the gap between the well-educated and the unskilled?(A)policy(B) country(C) labor skills(D)the changing nature of work25 In the following part immediately after this text, the author will most probably focus on_.(A)a vivid ac

25、count of global ageing(B) a detailed description of positive impact(C) other possible reasons for the deepening divide in U.S.(D)one likely solution such as imposing higher inheritance taxes25 Psychologists have known for a century that individuals vary in their cognitive ability. But are some group

26、s, like some people, reliably smarter than others? In order to answer that question, we grouped 697 volunteer participants into teams of two to five members. Each team worked together to complete a series of short tasks, which were selected to represent the varied kinds of problems that groups are c

27、alled upon to solve in the real world. One task involved logical analysis, another brainstorming; others emphasized coordination, planning and moral reasoning.Individual intelligence, as psychologists measure it, is defined by its generality: People with good vocabularies, for instance, also tend to

28、 have good math skills, even though we often think of those abilities as distinct. The results of our studies showed that this same kind of general intelligence also exists for teams. On average, the groups that did well on one task did well on the others, too. In other words, some teams were simply

29、 smarter than others.We found the smartest teams were distinguished by three characteristics. First, their members contributed more equally to the team s discussions, rather than letting one or two people dominate the group. Second, their members scored higher on a test called Reading the Mind in th

30、e Eyes, which measures how well people can read complex emotional states from images of faces with only the eyes visible. Finally, teams with more women outperformed teams with more men. This last effect, however, was partly explained by the fact that women, on average, were better at “mindreading“

31、than men.In a new study, we replicated these earlier findings. We randomly assigned each of 68 teams to complete our collective intelligence test in one of two conditions. Half of the teams worked face to face. The other half worked online, with no ability to see any of their teammates. We wanted to

32、 see whether groups that worked online would still demonstrate collective intelligence, and whether social ability would matter as much when people communicated purely by typing messages into a browser.And they did. Online and off, some teams consistently worked smarter than others. More surprisingl

33、y, the most important ingredients for a smart team remained constant regardless of its mode of interaction: members who communicated a lot, participated equally and possessed good emotion-reading skills.26 It can be inferred from the first paragraph that_.(A)some groups are really smarter than other

34、s(B) the 697 volunteer participants need to complete a series of short tasks together(C) the selected short tasks must have practical significance(D)logical analysis and brainstorming are important in each task27 According to psychologists, individual intelligence_.(A)is characterized by generality(

35、B) is related to math skills(C) is not related to teams(D)is key to smarter teams28 According to the author, the characteristics of smarter teams include all the following EXCEPT _.(A)the members have relatively equal contribution to the team s discussions(B) the members have a higher IQ(C) the memb

36、ers have a stronger ability of reading complex facial expressions(D)there are more female members than other teams29 In a new study, the other half of people work online because_.(A)it s necessary to ensure the accuracy of the experiment(B) online collaboration is becoming more and more important(C)

37、 the experimenters want to see whether collective intelligence will be showed(D)the experimenters want to prove social ability is vital to every team30 The best title for the passage may be_.(A)How to Develop a Smarter Team(B) Why Some Teams Are Smarter Than Others(C) The Characteristics of Smarter

38、Team(D)What Factors can Affect a Team30 Many of the tech industry s biggest companies, like Amazon, Google, IBM and Microsoft, are jockeying to become the leader for artificial intelligence(A.I.). In the industrys term, the companies are engaged in a “platform war.“A platform, in technology, is esse

39、ntially a piece of software that other companies build on and that consumers cannot do without. Become the platform and huge profits will follow. Microsoft dominated personal computers because its Windows software became the center of the consumer software world. Google has come to dominate the Inte

40、rnet through its ubiquitous search bar. If true believers in A.I. are correct that this long-promised technology is ready for the mainstream, the company that controls A.I. could steer the tech industry for years to come. “Whoever wins this race will dominate the next stage of the information age,“

41、said Pedro Domingos, a machine learning specialist and the author of “The Master Algorithm,“ a 2015 book that contends that A.I. and big-data technology will remake the world.In this fightno doubt in its early stagesthe big tech companies are engaged in tit-for-tat publicity stunts, circling the sam

42、e start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains. Fei-Fei Li, a Stanford University professor who is an expert in computer vision, said one of her Ph.D. candidates had an offer for a job paying more than $1 million a ye

43、ar, and that was only one of four from big and small companies.For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system wo

44、n a three-day match on the television trivia show “Jeopardy!“ Today, Watson is the centerpiece of IBMs A.I. efforts.By 2020, the market for machine learning applications will reach $40 billion, IDC, a market research firm, estimates. And 60 percent of those applications, the firm predicts, will run

45、on the platform software of four companiesAmazon, Google, IBM and Microsoft. Intelligent software applications will become commonplace, said Jeff Dean, a computer scientist who oversees Googles A.I. development. “And machine learning will touch every industry.“31 The reason for Microsoft controlling

46、 personal computers is that_.(A)it has formed a good platform(B) its software has gained a lot of money(C) its Windows software became popular among consumers(D)its software has been widely used in search bar32 Google can steer the tech industry in the future on premise that_.(A)it has controlled th

47、e Internet(B) A.I. has prepared to be the mainstream(C) it has won in the information age(D)A.I. and big-data technology have become mature33 The text takes “Fei-Fei Li“ as an example in Paragraph 3 to show that_.(A)the competition between tech companies is fierce(B) the candidates from famous unive

48、rsities are more popular(C) the higher the pay is, the more likely the candidate is to accept the offer(D)perhaps tech companies are striving for the same talents34 In which way the tech companies have used to show their progress?(A)Competitions between men and machines.(B) Chess games.(C) TV shows.

49、(D)The profitability of new products.35 Whats the author s attitude towards the future of A.I.?(A)Negative.(B) Positive.(C) Unclear.(D)Indifferent.35 “It s such a simple thing,“ said John Spitzer, managing director of equipment standards for the United States Golf Association. “Im amazed that so many people spend so much time and energy on trying to change it.“ The simple thing to which he refers is the humble

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