Lang Ping has set a good（1）exampleexample to us.As a player，she brought honour and glory to her country.She is loved by fans（2）who/thatwho/that come from all around the world.In 2015，the Chinese volleyball team was preparing for the World（3）butbuttwo important players left the team.Losing the match was （4）aabig challenge，but Lang Ping believed her young players could（5）winwin if they worked together as a team.
Michael Jordan，（6）knownknown as "Air Jordan"，changed basketball with his graceful moves and jumps.Jordan's skills were（7）impressiveimpressive ，but it was his mental strength that made（8）himhim unique.Jordan says the（9）secretsecret to his success is learning（10）fromfrom his failure.
【考點(diǎn)】人與自我．
【答案】example；who/that；but；a；win；known；impressive；him；secret；from
【解答】
【點(diǎn)評(píng)】
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發(fā)布：2024/4/20 14:35:0組卷：2引用：2難度：0.5
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1．
Before science became professionalized in the 19th century， （1）A.alarming B.properties C.revealed D.invasive E.rescue F.instrumental
G.households H.document I.concerned J.amateur K.initiativesnaturalists were collecting information and helping us understand the natural world.A 2009 study found that nearly 50% of UK （2）feed wild birds.The National Trust has more than 5 million members，and 60，000 active volunteers helping to protect the countryside as well as historic （3）.Now，with our environment arguably under greater threat than ever and species declining at a（n） （4）rate，volunteers are once again at the forefront of efforts to limit the damage.
Volunteers and enthusiasts can be powerful drivers for big changes.On the Isle of Man，more than 8，000 people （nearly 10% of the population） are involved in regular weekend beach cleans.At one recent event，123 volunteers turned up and removed 183 bags of litter in just a couple of hours.In view of （5）such as this，the island shares Unesco biosphere reserve status with the Galápagos，Yellowstone in the US，Uluru in Australia，and hundreds of other sites.
Recreational divers are making a real difference underwater too.They monitor the spread of （6）species，and record how native species respond.Divers also （7）levels of marine litter and other human impacts.Volunteer divers have played an important role in collecting information about marine conservation zones.Volunteers have also made a vital contribution to the conservation of basking sharks.The work of a citizen science Basking Shark Project in the 1980s and 90s was （8）in getting these sharks on the protected species list in the UK，while satellite tagging （9）the first recorded transatlantic crossing by a basking shark.
Volunteers and enthusiasts can be powerful drivers for big changes.No one can know better，or care more about，our most special places than the people who live in them and give up their free time to look after them.As a group of divers and （10）residents who lived on the shores of the bay，they took their campaign on to national and international stages and continue to inspire people who might otherwise feel powerless when faced with threats to the places that matter to them.發(fā)布：2024/12/30 1:0:8組卷：6引用：1難度：0.2 -
2．Shaking hands，American style
People often shake hands in the United States.American men shake hands with other men.American women often shake hands with men，and sometimes they shake hands with other women.Adults shake hands with children.And some people even teach their dogs to shake hands!（1）How do they shake hands just long enough？Just hard enough？Here are four little rules to remember.
1.Use your right hand.
2.Use good eye contact.Look at the person in the eye while you are shaking hands.
3.Don't shake too long.（2）Then let go and pull your hand back toward you.
4.（3）When a handshake is weak，Americans think the person may not be a hard worker or a good leader.When a handshake is too strong，Americans think the person is too rough or has bad manners.
（4）They shake hands when they meet for the first time.They shake hands to say congratulations.They shake hands when they meet after not seeing each other for a while.And they often shake hands when they say good-bye.In business，shaking hands shows agreement and honesty.
Handshakes are good everywhere.（5）So make sure to shake plenty of hands.
A.Offer your hand first.
B.Shake for no more than three seconds.
C.How do people shake hands correctly？
D.Don't shake too strongly or too weakly.
E.It is not polite to refuse a person's hand.
F.When do people in the United States shake hands？
G.Make sure your hands aren't sweaty when you do this.發(fā)布：2024/12/21 19:0:4組卷：2引用：1難度：0.5 -
3．Human memory is notoriously （眾所周知地） unreliable.Even people with the sharpest facial recognition skills can only remember so much.
It's tough to quantify how good a person is （1）remembering.No one really knows how many different faces someone can recall，for example，but various estimates tend to hover in the thousands – based on the number of acquaintances a person （2）have.
Machines aren't limited this way.Give the right computer a massive database of faces，and it can process what it sees – then recognize a face it （3）（tell） to find – with remarkable speed and precision.This skill is （4）supports the enormous promise of facial-recognition software in the 21st century.It is also what makes contemporary surveillance （監(jiān)控） systems so scary.
The thing is，machines sill have limitations when it comes to facial recognition.And scientists are only just beginning to understand what those constraints are. （5）（figure） out how computers are struggling，researchers at the University of Washington created a massive database of faces – they call it MegaFace – and （6）（test） a variety of facial-recognition algorithms（算法） as they scales up in complexity.The idea was to test the machines on a database that included up to 1 million different images of nearly 7，000 different people – and not just a large database （7）（feature） a relatively small number of different faces，more consistent with what's been used in other research.
As the databases grew，machine accuracy dipped across the board.Algorithms （8）were right 95% of the time when they were dealing with a 13，000-image database，for example，were accurate about 70% of the time when （9）（face） with 1 million images.That's still pretty good，says one of the researchers，Ira Kemelmacher-Shlizerman. "Much better than we expected，" she said，
Machines also had difficulty adjusting for people who look a lot alike –either doppelgangers （長(zhǎng)相極相似的人），whom the machine would have trouble （10）（identify） as two separate people，or the same person who appeared in different photos at different ages or in different lighting，whom the machine would incorrectly view as separate people.發(fā)布：2024/12/30 1:0:8組卷：4引用：1難度：0.5
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