[外语类试卷]专业英语八级模拟试卷832及答案与解析.doc

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1、专业英语八级模拟试卷 832及答案与解析 SECTION A MINI-LECTURE In this section you will hear a mini-lecture. You will hear the mini-lecture ONCE ONLY. While listening to the mini-lecture, please complete the gap-filling task on ANSWER SHEET ONE and write NO MORE THAN THREE WORDS for each gap. Make sure the word(s) you

2、 fill in is (are) both grammatically and semantically acceptable. You may use the blank sheet for note-taking. You have THIRTY seconds to preview the gap-filling task. 0 The Gestural Theory of Language The initial language in hominids was gestural, and communication using the 【 T1】 _was actually the

3、 first form of language.【 T1】 _ I. The origin of language: sign and sound signs【 T2】 _: having to be looking at the signer【 T2】 _ 【 T3】 _: first associated with language because they draw attention【 T3】 _ II.【 T4】 _for gestural origin of sign language【 T4】 _ A. Sign languages: meeting all the langua

4、ges【 T5】 _【 T5】 _ including: large lexicons, massive gestures,【 T6】 _, being grammatical【 T6】 _ the order affects the meaning greatly B. A study on how we【 T7】 _sound【 T7】 _ sound and visual information combined in the nervous system the same meaning and【 T8】 _the same neutrons【 T8】 _ existing in a

5、phenomenon: the McGurk Effect C. An illustration to the McGurk Effect Seeing somebody speaking is different from hearing speech sounds. Hearing a sound with a set of【 T9】 _makes the difference.【 T9】 _ III. Gestures and visual input A. example: sounds sound【 T10】 _when eyes are open or closed the who

6、le【 T10】 _ time B. nervous system: having the ability to respond to sound and【 T11】 _【 T11】 _ C. mirror neuron: excited both by the sight and also by the sound neutron groups involved in human language【 T12】 _some of those in【 T12】 _ rhesus macaques D. a study on the hypoglossal canal humans having

7、very big hypoglossal canal overlaps with chimps a lot of axons: not sufficient for【 T13】 _【 T13】 _ studying the values in fossil record for necessity and【 T14】 _【 T14】 _ IV. The way to create sounds A. by looking at the【 T15】 _in hertz, which drops in puberty【 T15】 _ B. example: saying okay looking

8、at the tongue and larynx and air sacs and asking 1 【 T1】 2 【 T2】 3 【 T3】 4 【 T4】 5 【 T5】 6 【 T6】 7 【 T7】 8 【 T8】 9 【 T9】 10 【 T10】 11 【 T11】 12 【 T12】 13 【 T13】 14 【 T14】 15 【 T15】 SECTION B INTERVIEW In this section you will hear ONE interview. The interview will be divided into TWO parts. At the e

9、nd of each part, five questions will be asked about what was said. Both the interview and the questions will be spoken ONCE ONLY. After each question there will be a ten-second pause. During the pause, you should read the four choices of A , B , C and D , and mark the best answer to each question on

10、 ANSWER SHEET TWO. You have THIRTY seconds to preview the questions. （ A） She is one of the founders of Apple Company. （ B） She is the technology reporter of Wall Street Journal. （ C） She has interviewed lots of people in Apple Company. （ D） She has worked in Apple Company for two years. （ A） How St

11、eve Jobs led Apple to thrive. （ B） How Apple was going to survive. （ C） What kind of person Steve Jobs really is. （ D） What the best days of Apple are. （ A） What happens to Apple Company. （ B） What fascinating story Apple has told. （ C） How Apple stays at the top of its game. （ D） How Apple is handl

12、ing the transition. （ A） He disputes the content of the book. （ B） He prefers this book to other books. （ C） He thinks it captures Apple. （ D） He finds the book the same as other books. （ A） Much of her information was not correct. （ B） What she said was completely wrong. （ C） It was quite interesti

13、ng. （ D） Her words were very enlightening. （ A） It has grown for a long time. （ B） It has gone through leadership transition. （ C） It is facing big company issues. （ D） It would go well if Steve Jobs were alive. （ A） A person with vision of technology. （ B） A person with a good business sense. （ C）

14、A person with the power of persuasion. （ D） A person with a combination of different abilities. （ A） Its too haunted to predict. （ B） Its coming back up again. （ C） Its an important part of her book. （ D） Its an emotional seesaw. （ A） It is under the risk of bankruptcy. （ B） It is gaining more profi

15、ts. （ C） It is booming in stock market. （ D） It is in need of a new vision. （ A） It is hard to resolve. （ B） It will be solved pretty soon. （ C） It is kind of slander. （ D） It is unworthy of mention. SECTION A MULTIPLE-CHOICE QUESTIONS In this section there are several passages followed by fourteen

16、multiple-choice questions. For each multiple-choice question, there are four suggested answers marked A , B, C and D. Choose the one that you think is the best answer. 25 At Airbnbs headquarters in San Francisco, every meeting area is decorated to look, in remarkable detail, like some Airbnb rental

17、somewhere in the world. One conference room is modeled on the War Room in Dr. Strangelove. In New York City, product innovation company Quirkys offices in a former warehouse look like a cross between a hip nightclub and a giant preschool, outfitted with a conference table made from industrial fans a

18、nd a giant map that shows where your colleagues are going on vacation. The sign on the front entrance says: “Deliveries & humans: 7th Floor. Suits: Go away. “ Technology is giving the office an identity crisis. Even the word office now sounds like something your father went to. “Were going through a

19、 100-year shift in work,“ says Adam Pisoni, co-founder of Yammer, which is now part of Microsoft. “Theres a real tension today between old and new. “Or as a recent Herman Miller research project concluded: “ Long-established workplace norms are giving way to disruption and uncertainty. “Twenty years

20、 ago, the office existed because it was the only place to get real work done. The reason to go to the office was to access information and technology.and other employees. Like an old, single man with a fortune, offices didnt need to look good to attract talent. Cloud computing is throwing the last s

21、hovelfuls of dirt on the traditional office. All the information and software that used to be locked inside offices can be tapped into from anywhere. Think of all the other things you used to have to go to the office for: a computer, a long-distance phone line, copiers, fax machines, files, mail, an

22、 art department that could make foils to go in the overhead projector for presentations in pre-PowerPoint days. Now you can get all of that on a laptop while sitting in a Starbucks. Private offices, surveys show, are empty 77 percent of the time. Starbucks, by the way, has long billed itself as the

23、“ third place“ in American life. Home is the first place: office the second. Maybe Starbucks is going to suffer its own identity crisis when the third place becomes the second place. Companies such as Yammer, which makes a kind of intra-company Twitter, and Herman Miller, the furniture maker that in

24、vented the cubicle, have been trying to understand the next-generation office. It helps to start with historical context. If you go back long enough, there were no real offices. The Egyptians constructed pyramids, not office towers. In the Middle Ages, people in Europe erected cathedrals. In London

25、in 1729, the East India Company built perhaps the first office building. Still, in those days most professionals worked at home, in what they called a library. Thomas Jefferson had a library at Monticello. The offices of the 20th century reflected the technology driving business and society. The mid

26、dle part of the century was all about industry and production, so offices looked like Jack Lemmons workplace in The Apartmentrows of desks strung out like an assembly line. The 1960s gave birth to the Information Age, and workers were expected to hunker(蹲下 )down and think. Companies gave them cubicl

27、es. So what now? Information is a commodity. Technology is available everywhere to everybody. Employees dont have to go anywhere to access other employeesnot in the age of Yammer and Skype video calls and Google Hangouts. Companies arent even made up of just employees anymore. In this ultra-networke

28、d age, a lot of business gets done by a core group from the company connected to a matrix of contractors and freelancers. For many companies, then, the most valuable assets have become creativity and culture. The companies with the best ideas win. And the companies that can carve out an identity and

29、 image win. As designers look at those changes in business, theyre thinking that offices have to be someplace youd want to go for the same reasons you want to go to a bar, even though you can make a good whiskey sour at home: connections to people, a pleasing place to hang out, and maybe a getaway f

30、rom your spouse or from that laundry basket crying out to be emptied. Desks and offices are going away in favor of funky gathering spaces and corners where you can take a laptop and think on your own. It has to feel like a place where employees and outside partners enjoy bonding and collaborating, s

31、ays Ryan Anderson, Herman Millers director of future technology. Companies used to spread the corporate culture by infusing it into employees through training, memos, gatherings. IBM even had company songs in the 1930s and 40s. But if a company is now more of a constantly changing band of insiders a

32、nd outsiders, the office might be one of the most important tools for creating culture. 26 The description of Quirkys offices in New York is an example of_. （ A） the combination of art and work （ B） the new identity of office （ C） recycling the old material （ D） human-oriented working environment 27

33、 In the Information Age, the companies that are more likely to win should_. （ A） have their own identity and culture （ B） spare no efforts to create good offices （ C） sign more outside contractors （ D） pay more attention to employees families 28 According to Ryan Anderson, what should modern offices

34、 provide for employees? （ A） Connection to the society. （ B） A place to link the staff and clients. （ C） Training and equipment. （ D） Cross-cultural collaboration. 28 The National Ecological Observatory Network, funded by Congress for $434 million, will equip 106 U. S. sites with sensors to gather e

35、cological data all day, every day, for 30 years after it goes operational in 2017. The Human Brain Project, supported by $1.6 billion from the European Union, intends to create a supercomputer simulation of a working human brain, including all 86 billion neurons and 100 trillion synapses(神经键 ). The

36、International Cancer Genome(基因组 )Consortium, 74 research teams across 17 countries spending an estimated $ 1 billion, is compiling 25,000 tumor genome sequences from 50 types of cancers. Big data is big business in the life sciences, attracting lots of money and prestige. Its relatively young: the m

37、ove toward big data can be traced back to 1990, when researchers joined together to sequence all 3 billion letters in the human genome. That project concluded in 2003, and since then, the life sciences have become a data juggernaut(强大的破坏力 ), propelled forward by new sequencing and imaging technologi

38、es that accumulate data at astonishing speeds. But not all scientists think bigger is better. As of July 9, 2014, for example, more than 450 researchers had signed a public letter criticizing the Human Brain Project, citing a “significant risk“ that the project will fail to meet its goal. One neuros

39、cientist called the project “ a waste of money,“ while another bluntly said the idea of simulating the human brain is downright “crazy“. Other big data projects have also been criticized, especially for cost and lack of results. The core of recent criticisms against big data projects is the concern

40、that expensive, massive data sets on biological phenomenaincluding the brain, the genome, the biosphere(生物圈 )and morewont necessarily lead to scientific discoveries. “ One of the problems with ideas about big data is the implicit notion that simply having lots of data will answer questions for you,

41、and it wont,“ says J. Anthony Movshon, a neuroscientist at New York University. Large data sets are useful only when combined with the right tools and theories to interpret them, he says, and those have largely been lacking in the life sciences. Thats one reason biological data is piling up far fast

42、er than it is being analyzed. “We have an inability to slow down and focus,“ says Kenneth Weiss, an evolutionary geneticist at Penn State University. “I wouldnt say big data is bad, but its a fad, and were not learning a lesson from it. “ Other areas of science, such as physics and astronomy, have a

43、 rich history of big data, as well as the organization and infrastructure to use that data. Take the Hubble Space Telescope, which has made 1 million observations, amounting to over 100 terabytes of data, since its launch in 1990. More than 10,000 scientific articles have been published using that d

44、ata, including the discovery of dark energy and the age of the universe. Or consider the Large Hadron Collider, a particle accelerator that produces tens of terabytes of data each night. In 2012, that data confirmed the existence of the Higgs boson, also called the “ God particle,“ among other high-

45、profile discoveries in particle physics. The life sciences, on the other hand, have barreled(高速行进 )ahead in data collection without the ability to determine which types of data are most useful, how to share it, or how to reproduce results. Research and funding institutions recognize this limitation,

46、 says Philip Bourne, associate director for data science at the National Institutes of Health, and the NIH is working to set aside funding and manpower to find ways to make data usable. Bourne is optimistic: “ Making full use of very large amounts of data takes time, but I think it will come,“ he sa

47、ys. Bourne and others, like David Van Essen, lead investigator of the $40 million NIH-funded Human Connectome Project(HCP), believe that gathering data first and asking questions second is a new, exciting way to make discoveries about the natural world. The HCP, a consortium of 36 investigators at 1

48、1 institutions, is a big data effort to map the connections in the brain using high-resolution brain scans and behavioral information from 1,200 adults. According to the projects website, the HCP data set will “reveal much about what makes us uniquely human and what makes every person different from

49、 all others. “ On the other hand, theres not a single hypothesis in sight. This is a fundamentally different way of doing science from hypothesis-driven experiments, the traditional bedrock of the scientific method, and many researchers have their doubts about it. “ Science depends upon predictions being generated and those hypotheses being tested,“ says e