When I was 8 years old, I decided to run away from home after a quarrel with my mother. With my suitcase packed and some sandwiches in a bag, I started for the front door.
My mom asked where I was going. “I’m leaving home,” I said.
“What’s that you’re carrying?” she asked.
“Some clothes and food,” I replied.
“If you want to run away, that’s all right,” she said. “But you came into this home without anything and you can leave the same way.”
I threw my suitcase and sandwiches on the floor and started for the door again.
“Wait a minute,” Mom said. “You didn’t have any clothes on when you arrived, and I want them back.”
This infuriated me. I tore my clothes off — shoes, socks, underwear and all — and shouted, “Can I go now?”
“Yes,” my mom answered, “but once you close that door, don’t expect to come back.”
I was so angry that I shut the door forcefully and stepped out of my home. Then I noticed down the street two neighbor girls walking toward our house. I was so shy that I saw the big spruce (云杉) tree in our yard and jumped under the low-hanging branches (树枝). A pile of dried-up brown needles (针状物) were beneath the tree, and you can’t imagine the pain those sharp needles caused to my body.
After I was sure the girls had passed by, I ran to the front door and knocked at it loudly.
“It’s Billy! Let me in!”
The voice behind the door answered, “Billy doesn’t live here anymore. He ran away from home.”
Looking behind me to see if anyone else was coming down the street, I said, “Mom! I’m sorry. I’m still your son. Let me in!”
The door opened and Mom’s smiling face appeared. “Did you change your mind about running away?” she asked.
“What’s for supper?” I smiled back.
1.When the author was leaving home, his mother ordered him to _____.
A.stay at home B.take some sandwiches
C.leave everything behind D.check his suitcase carefully
2.The underlined word “infuriated” probably means “_____”.
A.surprised B.warned
C.encouraged D.angered
3.Why did the author jump under the low-hanging branches?
A.To avoid being seen. B.To find some needles.
C.To play a joke on the two girls. D.To attract the two girls’ attention.
4.The last sentence “What’s for supper?” mainly shows that the author _____.
A.changed his plan to leave home
B.felt very hungry at that time
C.wished to eat something before leaving
D.wanted to know what his mother prepared for supper
Smart Things on Their Way
Google Clips
Google Clips is designed to be put somewhere in a room to take pictures by itself. It can also be attached to an object or a person’s clothing.
Google says machine Learning helps the camera choose the best times and situations for taking pictures ancl videos. Interested buyers can join a waiting list for the product to be on the market.
GoPro Hero
GoPro also uses machine learning to power its QuikStories characteristic. This tool takes existing photos and videos and automatically （自动地）creates a finished video piece, complete with music and effects.
Snap Sunglasses
Messaging app Snapchat sells a pair of sunglasses with a built-in camera that can record short videos with the push of a button. Snap Inc. says the product is designed to “catch the moment, without taking you out of it."
The glasses can record short video clips that can be shared with Snapchat users. Snap Inc. has started selling its sunglasses online.
Apple iPhone X
Apple's new iPhone X has a new Face ID system that it says will unlock the phone just by having the user look at it. This replaces the Touch ID on previous ones that used a fingerprint to unlock the phone.
Apple says the system works by projecting more than 30, 000 dots on the face to create a kind of map. Apple says its facial recognition is even safe enough to allow payments through its Apple Pay service.
1.What is the special function of Google Clips?
A. It can share videos on the phone.
B. It can take pictures by itself.
C. It can change photos into videos.
D. It can provide music and effects.
2.Which is sure to be bought now on the Internet according to the passage?
A. Google Clips. B. GoPro Hero.
C. Snap Sunglasses. D. Apple iPhone X.
3.How does Apple iPhone X make facial recognition?
A. By replacing the user's fingerprint.
B. By projecting a map of the user's face.
C. By pressing a special button.
D. By allowing payments on the phone.
假如你是高中生李津，你的美国笔友James热爱中国传统文化，最近打算来中国工作生活一段时间，但是不确定应该去往哪个城市，写信向你咨询。请你给他写一封回信，主要内容包括：
（1）你推荐的城市（天津或北京选其一）；
（2）推荐的理由(不少于两条)；
（3）美好祝愿。
注意:（1）词数100左右；
（2）可以适当增加细节，以使行文连贯；
（3）开头结尾已经给好，不计入总字数。
Dear James,
_______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Yours sincerely,
Li Jin
阅读短文，并按照题目要求用英语回答问题。
“Tennis – I’m saying goodbye.” With these words, Russian tennis superstar Maria Sharapova, 32, has announced her retirement.
“How do you leave behind the only life you’ve ever known?” she asked herself. Several reasons played a role in Sharapova leaving the tennis court for good.
Over the last couple of years, she’s dealt with an injury in her right shoulder and inflammation (炎症) in her forearms that may have prevented her from returning to top form. In more recent news, the death of her longtime friend, US basketball legend Kobe Bryant, also played a factor in her decision to retire.
“As I think you’ve seen throughout my career, my perseverance ( 毅 力 ) has been my greatest tool, my greatest strength,” Sharapova said in an interview. “But I’ve started feeling like it was becoming a weakness, because the stubbornness (执着) that was keeping me going was keeping me going for wrong reasons.”
Sharapova rose to stardom (明星身份) at age 17 when she won Wimbledon in 2004. She won a total of four Grand Slam singles titles: the 2006 US Open, the 2008 Australian Open, and the 2012 and 2014 French Open. She also earned the Fed Cup title in Russia in 2008 and an Olympic silver medal in singles in 2012, among many other accomplishments.
For 16 straight years from 2004, Sharapova was the world’s highest-earning female athlete, according to Forbes. Off the court, she made millions of dollars from companies such as Evian and Nike, as well as starting her own candy company.
“Tennis showed me the world --- and it showed me what I was made of,” Sharapova wrote on Facebook on Feb 26, alongside a photo of herself as a young girl with a tennis racquet (球拍). “It’s how I tested myself and how I measured my growth. And so in whatever I might choose for my next chapter, my next mountain, I’ll still be pushing, I’ll still be climbing，I’ll still be growing.”
1.What made Maria Sharapova decide to retire at the age of 32? (no more than 10 words)
2.What does Para. 5 mainly talk about? (no more than 10 words)
3.How did Maria Sharapova become the world’s highest-earning female athlete? (no more than 20 words)
4.What does the underlined sentence mean in the last paragraph? (no more than 10 words)
5.Do you think perseverance (毅力) is always our greatest tool? Give your reason. (no more than 20 words)
Aristotle thought the face was a window onto a person’s mind. Cicero agreed. Two thousand years passed, and facial expressions are still commonly thought to be a universally valid way to judge other people’s feelings, irrespective of age, sex and culture. A raised eyebrow suggests confusion. A smile indicates happiness.
Or do they? An analysis of hundreds of research papers that examined the relationship between facial expressions and underlying ( 潜在的) emotions has uncovered a surprising conclusion: there is no good scientific evidence to suggest that there are such things as recognizable facial expressions for basic emotions which are universal across cultures. Just because a person is not smiling, the researchers found, does not mean that person is unhappy.
This may raise questions about the efforts of information-technology companies to develop artificial-intelligence algorithms (算法) which can recognize facial expressions and work out a person’s underlying emotional state. Microsoft, for example, claims its “Emotion API” is able to detect what people are feeling by examining video footage of them. Another of the study’s authors, however, expressed scepticism. Aleix Martinez, a computer engineer at Ohio State University, said that companies attempting to obtain emotions from images of faces have failed to understand the importance of context.
For a start, facial expression is but one of a number of non-verbal ways, such as body posture, that people use to communicate with each other. Machine recognition of emotion needs to take account of these as well. But context can reach further than that. Dr Martinez mentioned an experiment in which participants were shown a close-up picture of a man’s face, which was bright red with his mouth open in a scream. Based on this alone, most participants said the man was extremely angry. Then the whole picture was shown. It was a football player with his arms outstretched, celebrating a goal. His angry-looking face was, in fact, a show of pure joy.
Given that people cannot guess each other’s emotional states most of the time, Dr Martinez sees no reason computers would be able to. “There are companies right now claiming to be able to do that and apply this to places I find really scary and dangerous, for example, in hiring people,” he says. “Some companies require you to present a video resume, which is analyzed by a machine-learning system. And depending on your facial expressions, they hire you or not, which I find really shocking.”
1.We can learn from the second paragraph that ______.
A.facial expressions are universal across cultures
B.it is hard to recognize some facial expressions
C.emotions and facial expressions may not be related
D.common facial expressions convey similar meanings
2.In the passage, the word “scepticism” (paragraph 3) is closest in meaning to “______”.
A.great doubt B.similar interest
C.fierce anger D.strong support
3.The experiment mentioned by Dr Martinez may prove that .
A.facial expression is an important way to communicate
B.machine recognition of emotion is not reliable at all
C.facial expression is not the only way to detect feelings
D.people may misread facial expressions for lack of context
4.According to the text, which of the following statements is correct?
A.Facial expressions differ from person to person.
B.People with red face must be feeling extremely angry.
C.Artificial-intelligence algorithms can always work out a person’s inner emotional state.
D.Unbelievable to Dr Martinez is that job offers are decided by a machine-learning system.
5.What does this passage mainly tell us?
A.Facial expressions are among the most universal forms of body language.
B.Computers can detect people’s mind by analyzing their facial expressions.
C.Facial expressions may not be the reliable reflection of a person’s emotions.
D.Companies can depend on machine recognition of emotion to hire people.
A job is more than just a job, especially to the older generation. “It’s not the money that matters, but the sense of self-worth,” 56-year-old Cheng Wonlan said. So, every day Ms. Cheng carries a bag of parcels, letters and documents of all shapes and sizes and does her rounds in North Point. She’s a courier (快递人员).
Five years ago, Ms. Cheng was a nurse at a private clinic. She had worked there for almost 30 years but was made jobless when the doctor migrated ( 移 居 ). It was extremely difficult for her to find another job as a nurse. “People do not trust my ability when they learn how old I am,” she said. After two years of searching, the mother of two eventually found another nursing job. But then after two years, she quit. Why?
“My colleagues were young and they didn’t understand me because of my age. They often asked me, ‘You are so old, what are you working for?’ I was very unhappy.” She said. So while the rest of her family left for work, she was left to lonely boredom at home. Then, one of Ms. Cheng’s neighbours told her about Employee’s Retraining Board (ERB) offering retraining courses for older people on specific occupations, such as convenience store assistants, junior clerks and so on.
“I was interested in courier work. I didn’t think my age was a barrier because I was fit and healthy,” she said. Upon graduation from the ERB, Ms. Cheng was offered a job by the Speeding Shuttle Courier Service Company Limited. But then Ms. Cheng was caught between honour and employment. It took Ms. Cheng 24 hours to make up her mind and eventually she took heart and went off to work as a courier.
Ms. Cheng’s employer is delighted with her. “Ms. Cheng has been working with us for two months and has shown a good responsible attitude to work.” Anthony Chong, who runs the company, said. Mr. Chong said he hired older people because they were able and reliable. “Age is not an important factor but attitude is. Many old people are more capable than youngsters. They will not run from difficulties but young ones will,” he said. “It is not easy to recruit (招募) young people since they shy away from hardship and challenges.”
1.Why was it difficult for Ms. Cheng to find another nursing job?
A.Nursing clinics were hard to find.
B.She found it difficult to trust others.
C.People thought she was too old to work.
D.People didn’t think she had enough work experience.
2.Ms. Cheng left her second nursing job because .
A.it was too difficult
B.she was too old to do the job
C.she was bored with changeless jobs
D.the other staff made her feel uncomfortable
3.Employee’s Retraining Board is aimed at .
A.finding jobs for older people
B.teaching new skills to older people
C.training older people to be healthier
D.providing older people with chances to earn money
4.According to Anthony Chong, young people .
A.are able and reliable
B.are less experienced than the older ones
C.are fitter and stronger than the older ones
D.are more likely to give up than the older ones
5.From the text, we can learn Ms. Cheng is _____ .
A.determined and responsible
B.intelligent and confident
C.capable but stubborn
D.purposeful but lazy
