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| A. price B. considerable C. shared D. ignore E. relieve F. measures G. fright H. fatal I. conditions J. criticized K. considerate |
ZOOOOM! A delivery man drives super fast past us, giving us a sudden, heart-stopping
Well, it turns out to be a complicated issue. Recently, an article titled “Delivery Drivers Stuck in the System” was
According to surveys online, few care much whether their deliveries are a few minutes late, with most believing that it is not worth risking someone’s life for. In response, Ele. me and Meituan have added a combination of features to extend delivery times for slow elevators or bad weather
| site, trap, nearby, overseas, damage, interrupt, measure, attempt, conduct, vehicle, base, prepare, honest, distance, captain, cheerful |
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| mental atmosphere jump to one’s feet be regarded as measure trap on the edge of break down strike award star in be stuck in |
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| break down； on the basis of； apart from； as for； star in； enable； strike； measure； protest； reward； trap； fail； |
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12. They predicted that a destructive earthquake
| A. reduce B. identity C. blogger D. theft E. guidelines F. rude G. surrounded H. achievements I. individual J. measures |
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9. It was foggy, so the driver had to
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| furniture, fortune, measure, drop out of, dormitory, guilty, turn one’s back on, be regarded as, charity, make little sense |
Sixteen years ago, Jason was a college professor with a huge six-bed room house and a
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6. The naught boy is fond of
7. I hope that my sister who just returned home from abroad will
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9. You should have attended the important meeting, why didn’t you
10. We all don’t like the people who always
| A. consisted B. composing C. measures D. account E. patterns F. limitations G. moderately H. progressed I. distribution J. significantly K. complement |
AI can distinguish between bots and humans based on Twitter activity
Artificial intelligence is being used to spot the difference between human users and fake accounts on Twitter.
Emilio Ferrara at the University of Southern California in the US, and his colleagues have trained an AI to detect bots on Twitter based on differences in
The team analysed two separate datasets of Twitter users, which had been classified either manually or by a pre-existing algorithm as either bot or human.
The manually verified dataset
The researchers found that human users replied four to five times more often to other tweets than bots did. Real users gradually become more interactive, with the fraction of replies increasing over the course of an hour-long session of Twitter use.
The length of tweets by human users also decreased as sessions
Bots, on the other hand, show no changes in their interactivity or the length of information they tweet over time.
The team also analysed the amount of time between any two consecutive (连读的) tweets from a single user. When this
The team then combined these
The algorithm could be used to
One of the study’s
