【題目】______ your strength, you have got to know who you are and listen to yourself before doing anything else.
A. Finding B. Found
C. To find D. Having found
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科目：高中英語 來源： 題型：
【題目】He didn't make _________ clear when and where the meeting would be held.
A. this B. that C. it D. these
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科目：高中英語 來源： 題型：
【題目】How to DIY Your Own Mask
During the outbreak of COVID-19, one of the must-have items is the mask. However, many countries are in bad need of medical masks and other protective equipment. 【1】 But we can make our own masks which can be used repeatedly. Now, let’s look at the most popular DIY method for soda bottle gas masks.
【2】 And it doesn’t require huge skills. With necessary materials and a little training, it can be made in 15 minutes.
To make such a mask project, you’ll require a sharp cutting tool, a market, glue, a 2-liter soda bottle, rubberized foam insulation strip (泡沫橡膠絕緣條) and one N95 mask. Total cost may be $5.
First, you’ll have to clean the 2-liter plastic bottle. After that, draw a U-shaped area using the marker. 【3】 Then start with a smaller cut and work your way up from there. Cut away the bottom of the bottle and you’ll end up with a basic shape.
Next, use the rubberized foam insulation as a seal for the edges of the bottle. 【4】 This will serve as a resting place for the N95 mask. Then cut off the N95 mask’s edging carefully. And place is inside the neck of the bottle. The elastic bands (橡皮筋) from the N95 mask will be used to secure the gas mask firmly on your face. Then a DIY gas mask is completed.
Do remember to keep the gas mask stored in a well sealed plastic bag. 【5】
A.In this way you can make good use of the bag.
B.This can prevent it from getting polluted.
C.The soda bottle gas mask is very simple to make.
D.In this situation it is hard for people to get enough masks.
E.It should be big enough to fit your face and yet not too big.
F.Actually, the idea of DIY gas masks dates back to WW II.
G.You should also make a circle of foam insulation inside the bottle.
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科目：高中英語 來源： 題型：
【題目】If I were Jia Ling, I ________ my figure to be a goddess, rather than a cow girl.
A. would have kept B. had kept
C. would keep D. kept
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【題目】It turned out that she won the first prize in the petition, which was beyond her .
A. expectations B. reputations
C. contributions D. celebrations
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科目：高中英語 來源： 題型：
【題目】Only after talking to two students that having strong motivation is one of the biggest factors in reaching goals.
A. I did discoverB. did I discover
C. I discoveredD. discovered
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【題目】I had hoped to take a holiday this year but I wasn’t able to ______.
A. get awayB. drop inC. check out D. hold on
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科目：高中英語 來源： 題型：
【題目】That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing. But MIT business scholars Erik Brynjolfsson and Andrew McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them.
They believe that technology increases productivity and makes societies wealthier, but it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers. Technologies like the Web, artificial intelligence, and big data are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared.
As evidence, Brynjolfsson and McAfee point to a chart on which separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. Then, beginning in 2000, the lines diverge; productivity continues to rise steadily, but employment suddenly shrinks. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation.
United States Productivity and Employment
But are these new technologies really responsible for a decade of lackluster (無生氣) job growth? David Autor, an economist at MIT who has studied the connections between jobs and technology, doubts that technology could account for such a sudden change in total employment. Moreover, he also doubts that productivity has, in fact, risen steadily in the United States in the past decade. If he’s right, it raises the possibility that poor job growth could be simply a result of a depressed economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but there’s not a lot of evidence that it’s linked to computers.” “To be sure, computer technologies are changing the types of jobs available, but that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
Lawrence Katz, a Harvard economist, says that while technological changes can be painful for workers whose skills no longer match the needs of employers, no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies. Though he expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
【1】Which period on the chart strongly supports McAfee’s claim?
A. 1947—1967. B. 1985—1987.
C. 1997—2000. D. 2011—2013.
【2】According to David Autor, the change in job growth ________.
A. is not necessarily caused by technology
B. results from a weakening economy
C. has no connection with productivity
D. affects the current types of jobs
【3】What is Lawrence Katz’s attitude towards the topic?
A. Optimistic. B. Defensive.
C. Objective. D. Disapproving.
【4】The main purpose of the passage is to ________.
A. show the relation between productivity and job creation
B. discuss the effect of technological advances on employment
C. argue against the wide use of artificial intelligence
D. explain the impact of technologies on productivity
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