Section C Reading in Depth
Read the following three passages carefully and do the exercises below.
PASSAGE 1
Robots are increasingly being developed to think and act like humans. Some have performed better than humans in tests designed to measure machine intelligence. For example， we have reported on experiments involving robots competing against humans in a reading test and in a live debate. But one common human quality that has been difficult for engineers to recreate in machines is humor.
Kiki Hempelmann， a computational language expert （计算机语言学家） told the Associated Press： “The main problem is that robots completely miss the context of humor.Other experts agree that context is very important to understanding humor—both for humans and for robots.
Tristan Miller， a computer scientist and linguist （语言学家）， studied more than 10， 000 puns. Puns are a kind of joke that uses a word with two meanings. For example， you could say， “Balloons do not like pop music.” The word “pop” can be a way of saying popular music； or， “pop” can be the sound a balloon makes when it explodes. But a robot might not get the joke. Tristan Miller said that is because humor is a kind of creative language that is extremely difficult for computer intelligence to understand. “It's because it relies so much on real⁃world knowledge，” Miller said. This includes background knowledge and common sense knowledge. “A computer doesn't have these real⁃world experiences to draw on. It only knows what you tell it and what it draws from，” he added.
Allison Bishop， a computer scientist and a stand⁃up comedian （独角滑稽秀演员）analyzed the problem is that machines are trained to look for patterns. Comedy， on the other hand， relies on things that stay close to a pattern， but not completely within it. To be funny，humor must also not be predictable， Bishop said. This makes it much harder for a machine to recognize and understand what is funny.
Purdue University computer scientist Julia Rayz has spent 15 years trying to get computers to understand humor. The results， she said， have at times been laughable （可笑的）. In one experiment， she gave the computer two different groups of sentences. Some were jokes， others were not. The computer kept mistaking things as jokes that were not.
Despite the difficulties， Miller said there are good reasons to keep trying to teach humor to robots. It could make machines more relatable， especially if they can learn to understand sarcasm， he noted. Humans use sarcasm to say one thing but mean another.
But Kiki Hempelmann is not sure such attempts are a good idea. “Teaching AI systems humor is dangerous because they may find it where it isn't， and they may use it where it's inappropriate，” he said. “Maybe bad AI will start killing people because it thinks it is funny，”he added.
1. According to the passage， which one is NOT the key factor for our understanding of humor？
A. Real⁃world knowledge.
B. Background knowledge.
C. A sense of humor.
D. Common sense.
2. Which statement below can be considered a pun？
A. A horse is a brave animal.
B. A horse is a stable animal.
C. A horse is a speedy animal.
D. A horse is a meek animal.
3. To be a successful comedian， you need to try________.
A. not to tell your audience the meaning of the joke
B. to let your audience understand your jokes easily
C. not to let your audience see your jokes coming
D. to let your audience follow the pattern you create
4. Why does Miller believe it a good idea to teach robots humor？
A. It could let robots and humans have more in common.
B. It could help robots comprehend and apply sarcasms.
C. It could allow us to get more about machine learning.
D. It could improve the communication ability of robot.
5. Which is NOT the concern of Kiki in terms of teaching AI system humors？
A. Robots may mistake things as jokes that are not.
B. Robots may apply the humor in a wrong situation.
C. Robots may still not fully understand the context.
D. Robots may grow more intelligent than human.
PASSAGE 2
Exercise does of course add to your average life expectancy， but perceptions of exercise make a difference too. Scientists， for 21 years， at Stanford University in the US looked at mortality data for 61，000 adults and analyzed the various factors that might have contributed to the participants' health. They discovered that people who thought they weren't doing as much exercise as their peers died younger than those who thought they did more， even when the actual amount of exercise they did was the same. At least three possible reasons could explain this result.
The first is simply that we feel stressed if we think we're not active enough. Bombarded（被轰炸） by health messages and seeing everyone exercising all the time， might cause us to worry a lot and this kind of chronic stress could damage our health.
Or is it down to motivation？Thinking yourself as an athletic person encourages you to do even more exercise to fit in with this image. The research from 2015 showed if you believe you are less fit than your friends， you're less likely to be doing any exercise at all a year later.Considering what we know about group norms and how most of us like to do what we know other people are doing， this is surprising. But maybe we find it too discouraging if our friends do more than us and then we give up altogether.
A third explanation involves the opposite of the placebo effect —nocebo. If you have negative expectations， the physiological effect of a treatment is reduced. So perhaps people were in fact as active as their friends， but didn't realize it， and so they missed out on some of the benefits. Take hotel housekeepers for an example. Just by doing their daily work they are getting plenty of exercise. But they didn't count this as exercise. Then， Alia Crum， also from Stanford University told half these hotel housekeepers just how much exercise they were getting and why this benefitted them. Four weeks later， this group of housekeepers had lost weight and had lower blood pressure.Once they viewed work as an opportunity to exercise，it had more of a physical impact on them. Perhaps they began vacuuming more energetically or maybe it was down to the placebo effect.
Well， I'm going to make sure I appreciate the activity I do get around to doing， while avoiding any motivation⁃sapping conversations about exercise with ultramarathon⁃running friends.
1. What are the least expected words from the author to his athletic friends？
A. “I need to do more exercise.”
B. “I'm so unfit in front of you.”
C. “I admire your faith in sports.”
D. “You have been doing so well.”
2. How does “chronic stress” （Line 3， Para. 2） appear like？
A. It outbreaks overnight and gives you a hard attack.
B. It lasts for a long time and is difficult to get rid of.
C. It is severe but comparatively easy to copy with.
D. It haunts you wherever you go but is not severe.
3. If people consider themselves athletic， they tend to________.
A. maintain this image
B. promote sport spirit
C. slow down and relax
D. impact other people
4. The author is surprised by the fact that________.
A. group norms cannot articulate the impact of negative perceptions
B. most of us are likely to do what we know other people expect of us
C. negative perceptions can be so discouraging to break group norms
D. negative perceptions are too discouraging and make people give up
5. What does “placebo effect” （Line 1， Para. 4） refer to？
A. Physical effect of exercise will be reduced due to negative expectations.
B. Effect of exercise varies in accordance with your perceptions of exercise.
C. Hotel housekeepers can benefit more if they put more faith in their job.
D. Strong beliefs in the amount of exercise you have can increase its effect.
PASSAGE 3
“The main surprise is how pervasive the effects were，” says senior author Martin Genner， an evolutionary ecologist at the University of Bristol. “We found the same trend across all groups of marine life we looked at， from plankton to marine invertebrates （无脊椎动物）， and from fish to seabirds.”
The new study builds on earlier evidence for a prevailing effect of climate change on the distributions， abundance， and seasonality of marine species. Based on those findings，Genner's team reasoned that marine species should be doing well poleward but poorly equatorward. They also realized that existing databases of global species distributions could be used to test this hypothesis.
Based on a thorough search of available data in the literature，the researchers now report on a global analysis of abundance trends for 304 widely distributed marine species over the last century. The results show that—just as predicted—abundance increases have been most prominent where sampling has taken place at the poleward side of species ranges， while abundance declines have been most prominent where sampling has taken place at the equatorward side of species ranges.
The findings show that large⁃scale changes in the abundance of species are well underway. They also suggest that marine species haven't managed to adapt to warmer conditions. The researchers therefore suggest that projected sea temperature increases of up to 1.5 °C over pre⁃industrial levels by 2050 will continue to drive the latitudinal（纬度方向的）abundance shifts in marine species， including those of importance for coastal livelihoods.
“This matters because it means that climate change is not only leading to abundance changes， but affecting the performance of species locally，” Genner says. “We see species such as Emperor penguin becoming less abundant as water becomes too warm at their equatorward edge， and we see some fish such as European seabass thriving at their poleward edge where historically they were uncommon.”
The findings show that climate change is affecting marine species in a highly consistent and non⁃trivial way. “While some marine life may benefit as the ocean warms， the findings point toward a future in which we will also see continued loss of marine life，” Genner says.
The long⁃term data included in the study primarily represent the most well⁃studied regions of the world. The researchers say that more work is needed to understand how climate change has affected marine life in all regions of the world in greater detail.
“We aim to get a better understanding of precisely how climate change drives abundance shifts，” Genner says. “Is this mainly related to the physiological limits of the species， or instead due to changes in the species with which they interact？”
1. What does the current study find？
A. It finds an increase in the abundance of marine species toward the equator.
B. It finds a decrease in the abundance of marine species toward the poles.
C. It finds the same pattern in abundance changes across marine species.
D. It finds the insignificant impact of climate change on marine species.
2. How did the current study collect data？
A. Through conducting a careful analysis of literature.
B. Through interviewing the evolutionary ecologists.
C. Through tracking the distributions of marine species.
D. Through sampling the species ranges near the equator.
3. The word “hypothesis” （Line 5， Para. 2） is closest meaning to________.
A. an opinion based on complete evidence
B. an opinion based on incomplete evidence
C. an opinion believed by many people
D. an opinion believed by a few people
4. What is the main purpose of Para. 7？
A. To compare the sampling in the former and the current study.
B. To stress that the data was collected in a long period of time.
C. To explain the advantage of the data of the current study.
D. To present the limitation in the data of the current study.
5. What will be the focus of future study？
A. The impact of abundance shifts on coastal livelihoods.
B. The reasons behind the latitudinal abundance shifts.
C. The impact of abundance declines on coastal livelihoods.
D. The future abundance shifts across marine species.