1 . Many organizations learned in the past year that remote work can be highly effective,with 83% of employers surveyed saying that the shift to remote work has been successful for their company,according to a PwC(普华永道)study. In addition,54% of workers want to continue working remotely after the pandemic. Now that it's clear that where the work is done is not as important as people once thought,the other dimension of flexibility workers desire is the freedom to determine when the work is done. A 2019 study by the International Workplace Group found that 80% of workers would turn down a job that did not offer a flexible work schedule for one that did,and76% of workers said they'd consider staying at their current employer if they could work flexible hours.
According to a Microsoft Work Trend Report,the“9-to-5” workday is disappearing,as the increase in remote work has allowed for more flexible hours. Employees are increasingly working asynchronously,completing tasks on their own schedules,which may be different from those of their colleagues. Asynchronous work is now essential to being part of a modern,digital economy,staying competitive in the war for talent,and building a globally distributed workforce.
Tsedal Neeley,a Harvard Business School professor,told me,“Companies have to profoundly rethink what it means to be part of a modern work structure. This idea of‘9-to-5’or face-time culture is actually not helpful for a digitally advanced economy. ”She highlighted that underlying face-time culture is the need to monitor or see people in order to feel like work is advancing. However,this assumption that being productive requires seeing people do the work is not only limiting,but also wrong,as technology and automation are increasingly used to get work done and are inherently not as observable. Asynchronous work,she says,is“a completely new mindset in line with a digital economy”.
1. Why do workers prefer the job which can offer a flexible work schedule?A.Because the pandemic is still severe. |
B.Because where to work is not important. |
C.Because the remote work is more effective. |
D.Because they long to be free to decide when to work. |
A.Acting individually. |
B.Doing something together. |
C.Not happening at the same time. |
D.Getting the work done cooperatively. |
A.negative | B.approving | C.indifferent | D.neutral |
A.Improving Efficiency in Workplace |
B.Breaking Free from“9-to-5”Culture |
C.Protecting Employees from Pandemic |
D.Adjusting Yourself to Flexible Schedule |
2 . Doing one good deed turns into another coming your way. Liz’s life was
After they fought horrible
Touched, the two firefighters
Liz couldn't be too
A.created | B.changed | C.spent | D.disturbed |
A.met | B.ended | C.formed | D.started |
A.fire | B.flood | C.earthquake | D.hurricane |
A.satisfaction | B.reminder | C.surprise | D.inspiration |
A.interrupted | B.ignored | C.joined | D.overheard |
A.changing | B.educating | C.serving | D.attacking |
A.wrote | B.sent | C.introduced | D.shared |
A.make | B.take | C.keep | D.live |
A.Embarrassed | B.Encouraged | C.Determined | D.Threatened |
A.set up | B.take up | C.pick up | D.make up |
A.friendships | B.instructions | C.comments | D.donations |
A.talked | B.heard | C.thought | D.dreamed |
A.accessible | B.sensitive | C.helpful | D.grateful |
A.firefighter | B.community | C.campaign | D.family |
A.hopeless | B.similar | C.dangerous | D.various |
3 . Artificial intelligence (AI) still can’t see the future, but a new algorithm (算法) may come close: using nothing but written movie summaries, the AI can consistently tell which films will play well—or awfully—to critics and audiences. If the model can be further improved, it could one day help producers predict whether a movie will be a failure at the box office, before it’s even made.
To test several models, researchers used plot summaries of 42,306 movies from all over the world, many collected from Wikipedia. The models broke the summaries by sentence and used something called sentiment (情感) analysis to analyze each one. Sentences considered “positive”, such as “Thor loves his hammer”, would receive a rating closer to positive one. And sentences that were considered “negative”, like “Thor gets in a fight” would be rated closer to negative one.
Generally, successful movies such as 1951’s Alice in Wonderland—which scored 80% on the movie-rating website Rotten Tomatoes—have frequent waves in sentiment; unsuccessful ones, such as 2009’s The Limits of Control, vary less. It’s not important whether the films begin or end happily, the researchers say. What’s important is that the sentiments change frequently.
The sentiment ratings in each summary were then simplified into a single score to reflect how often the sentiment changed. The researchers tested three different methods of arriving at a final score. All three could predict fairly accurately whether a movie would be unpopular, and one method worked especially well for guessing which thrillers and comedies reviewers would hate.
The methods were not as efficient at guessing which movies would succeed, but they still predicted the results more accurately than random chance. In the future, the researchers say their methods could be bettered to predict the amount a movie could earn at the box office and help producers decide which movies to invest in. The system’s fair judgment might give an advantage to less well-known writers, the researchers add. It could also potentially save the public from having to sit through films like Jaws: The Revenge, which online critics and audience alike rate as terrible.
1. How can AI help foresee the future of movies?A.By testing plot models. | B.By using sentiment analysis. |
C.By writing summaries. | D.By consulting critics and audiences. |
A.A happy ending. | B.Famous movie stars. |
C.A well-known producer. | D.Frequent sentiment changes. |
A.Helping producers invest wisely. | B.Assessing a movie’s quality accurately. |
C.Increasing box office earnings. | D.Providing written summaries for critics. |
A.Doubtful. | B.Cautious. |
C.Optimistic. | D.Ambiguous. |
4 . Handwritten thank-you letters are such a simple way of making other people feel good, it is strange that so few people write them anymore. At work, a thank-you letter to employees is unbelievably effective. It costs little and has no side effects. The effort involved in writing letters very low. The pleasure on receiving them is very high.
Doug Conant, manager of Campbell’s Soup Company since 2001, knows the power of thank you letters. He said that every day he works with an assistant, searching the company for people deserving thanks.
In these days of such busy schedules and people running all over the place and trying to get ahead, sometimes we forget the simplest things in life are the most powerful and rewarding. You need to think to yourself about a time someone sent you a thank-you and how much it meant to you.
A.He then writes them a thank-you letter. |
B.Why are thank-you letters so important? |
C.You may ask what side effects exactly mean. |
D.This makes them an excellent way to reward and motivate staff. |
E.But if these letters are so inspiring, why don’t more managers write them? |
F.Always remember to “Do to others whatever you would like them to do to you!” |
G.Since no one ever writes them thank-you letters they don’t write any themselves. |
5 . Looking for a new poetry book to read? I’ve got you! We’re going to explore some of my favorite poetry collections, which range from the traditional all the way to the totally experimental. And though they differ in terms of tone and subject matter, they’ve all got we call "good parts".
Night Sky with Exit Wounds by Ocean Vuong
It is the first poetry collection from Ocean Vuong. Vuong’s style is well-suited to the heavy subjects he pursues, particularly when he reflects on the loss of his father and his experiences as a wartime refugee. There’s a certain wonderful quality to his writing.
Lunch Poems by Frank O’Hara
If you like a conversational style, Lunch Poems might be the poetry book for you. Personal, funny, and easy, the collection perfectly shows the casual voice of Frank O’Hara, an outstanding figure of the New School Movement in last-’50s New York. As the name suggests most of the poems were written during his lunch bread at work, bringing a realistic image by the writing.
100 Selected Poems by E. E. Cummings
It’s a shame that more people don’t take E. E. Cummings seriously. Yes, his poetry is sometimes experimental. Unconcerned with "rules", Cummings tried to capture emotion in its own form.
The Complete Poems by Elizabeth Bishop
In my opinion, any kind of fantastic poetry books must include Elizabeth Bishop. Highly skilled and highly influential, Bishop was one of the most powerful voices of the 20th century. She mostly worked within traditional forms, but the forms led to surprising effects, mixing classic style with modern ones.
1. Who experienced war?A.Frank O’Hara. | B.Ocean Vuong |
C.E. E. Cummings. | D.Elizabeth Bishop |
A.Lunch Poems. | B.100 Selected Poems |
C.The Complete Poems | D.Night Sky with Exit Wounds |
A.It is funny | B.It is personal |
C.It is excellent | D.It is experimental |
The Internet has brought great benefits to Wuzhen,
In 2016, the parking system for Wuzhen's WIC centre
We can remember events in our c
The Scream was painted by Edvard Munch in 1893. What makes it striking is that it shows a thin f
9 . Michael Evans was standing in line waiting to pay his taxes (税), when he heard a disturbing sound ahead of him. An elderly woman at the window was crying and so was the cashier (出纳员) helping her. Then Evans learned why: the woman was informed she would lose her house if she couldn’t pay the tax. He also heard the woman tell the cashier that her daughter had recently died.
Evans, a businessman who had just buried his father, couldn’t stand the idea of this woman losing her home right after losing her child. He approached the window and said to the cashier, “I’ll pay her taxes.” The two women were stunned. Their hopelessness turned to disbelief. Evans promised to go straight to the bank and come right back with the money. And he did.
But when he returned to the office, he asked someone else waiting in line to hand the check to the cashier. Evans was trying to slip away quietly. Obviously, he didn’t want the attention.
Of course, attention found him. It’s not every day that someone pays a stranger’s high tax bill. That said, Evans often finds himself on the giving end of charitable situations, though for years he went unrecognized for it. He is the president of a company which owns a variety of businesses, from restaurants to a mobile restroom company, most located in the inner city of Detroit. In 2015, when he saw a story on the news about a local boy with a severe disease, Evans held an event to raise money at his restaurant to help pay for the boy’s medical fee. He also gave away all the money the restaurant made that day to the boy’s family.
Why does Evans give so much to strangers? “Doing things with your money is better than putting it in the banks,” he says. As for paying for the elderly woman’s taxes, he says he did it “for no other reason but to make sure the lady was in her house.”
1. Why did Evans pay the woman’s tax?A.He felt pity for the woman. |
B.He was moved by the cashier. |
C.He didn’t want the disturbance. |
D.He felt sorry for the cashier’s mistake. |
A.Satisfied. | B.Thankful. |
C.Shocked. | D.Thoughtful. |
A.He is used to doing good deeds. |
B.He is well known for his charity work. |
C.He is president of a charity organization. |
D.He is an important figure in social reforms. |
A.Kind and Brave. | B.Generous and caring. |
C.creative and successful. | D.Energetic and warm-hearted. |
10 . A man saw an old lady whose car had broken down on the side of the road. He decided to help her, so he stopped his car next to hers and
The old lady was a bit
He went on to fix her car and became dirty and slightly
Later that evening the lady stopped at a small cafe. Although the waitress who served her was pregnant (怀孕的) and
She left a note on a napkin (餐巾) "You don' t have to return the
More
That night, the waitress went home
A.got out | B.pulled | C.got up | D.passed by |
A.depressed | B.disappointed | C.frightened | D.moved |
A.quickly | B.carefully | C.directly | D.curiously |
A.calm | B.bother | C.protect | D.greet |
A.bored | B.stressed | C.worried | D.injured |
A.receive | B.appreciate | C.seek | D.injure |
A.message | B.money | C.kindness | D.habit |
A.sick | B.poor | C.sad | D.tired |
A.asked | B.remembered | C.showed | D.wondered |
A.space | B.bills | C.change | D.napkins |
A.favor | B.note | C.call | D.feelings |
A.rest | B.share | C.end | D.suffer |
A.importantly | B.surprisingly | C.luckily | D.specifically |
A.saved | B.left | C.lent | D.raised |
A.safely | B.quietly | C.easily | D.early |