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25.What caused Ciruela to translate the Chinese classic?What can we before the Breakthou Listen-proeeA.His passion for Spanish literature.A.It only searched a few stars.B His determination to popularize it.B.It found signs of intelligent life.C.The lack of its direet translation into Spanish.C.It stored a large number of signs.D.The lass of diversity in Spanish translation.What of the ramainlya boutD.It searched false data from many stars.Why are machine-learning-agorithm used to deal with dataA.Its barrier.B.Its principle.C.Its style.D.Its meaning.A.It is skilled in picking up signals.B.It can(decrease earthly interference.A.Meeting readers'needs.B.Targeting cultural phenomena.C.It's unnecessary to employ many people to do the job.C.Bridging the cultural gap.D.Being oyal to the original text.D.It can recognize signals from Earth efficiently.What can we infer from Jean-Luc Margot's words?Some of the world's largest telescopes are listening for signals from distant alien civilizaA.Scientists will abandonclassical algorithms.tions.The search is an effort to find artificial-looking signals that might have come fromB.It's ahard job to sort through a huge amount of datatechnologically advanced civilization in a far-away solar system.C.Machine-learning will replace classical approaches.It is a new time for the search for extraterrestrial(外星球的)intelligence research,D.Classical algorithms will continue to be adopted.known as SETI,which is opening up thanks to machine-learning technology.The problem ofDbig data is relatively new for SETI.For decades,the field had been limited by having hardlyAs the costs of fuel,groceries and housing increase suddenly around the world,scientistsany data at all.Astronomer Frank D.Drake pioneered SETI in 1960,when he pointed a tele-are fighting inflation通货膨张)at the bench..Almost all items needed to conduct science arescope towards two stars and listened for radio transmissions.Most of the SETI searches thamore expensive than they were just a year ago And that means that nearly every researcher isfollowed were also limited to a small number of stars.feeling the pressure."Nobody is immune to this economy"says Tola Olorunnisola.whoBut in 2015,the biggest SETI programme ever in California)the Breakthrough Listenleads innovation in the labat management company in Penn-proiect searched one million stars for signs of intelligent life.The project looks for radiosylvania.Olorunnisola visited labs in the Netherlands,Switzerland and Ireland to help re-searchers find ways to enlarge their budgets."Scientists are becoming more conscious ofcosts,”she says..phones,GPS and other aspects of modern life."The biggest challenge for us in looking forThe increase in lab costs has forced scientists to make some difficult choices.ScientificSETI signals is not at this point getting the data,"says Sofia Z.Sheikh,an astronomer at thebudgets are pretty fixed.If they pay double for something,it means they re not buying some-SETI Institute."The difficult part is to distinguish signals from human or Earth technologything else.Seientists can keep their research projects moving forward.but to avoid overspenfrom the kind of signals we'd be looking for from technology somewhere else out in the Galaxy.'ding on their budgets.they'll probably need to adjust their buying habits and take steps toGoing through millions of results of observation manually-()isn't practical.Amake their labs more efficient.common approach is to use algorithms ()Machine-learning algorithms are trained onJulien Sage,a cancer researcher and geneticist at Stanford University in California,large amounts of data and can learn to recognize features that are characteristic of carthlyestimates that lab supplies historically account for roughly 20%of his overall budget,but heinterference.☑says that the balance is shifting."Still,SETI will probably continue to use a mixture of classical and machine-learning.Without significant boosts in funding to keep pace with inflation,it's up to scientists toapproaches to sort through data,"says Jean-Luc Margot,a professor at UCLA."Classicalfind creative ways to diminish costs.One option is to rethink experimental design.algorithms remain excellent at picking up signals,and machine-learning can not solve all the"It will probably take more than discounts from lab-supply companies to truly protectproblems of particular situations."scientists from the impact of rising prices,"Sage says."Unless something is done on a large28.What had limited SETI for decades?scale to either stabilize costs or increase funding,science is likely to suffer.If you have lessA.Artificial-looking signals.B.Machine-learning technologymoney,you're going to have fewer people or be less productive,which means you're going toC.Being short of data.D.Dealing with big data.have fewer grants ()which means you're going to have fewer people.That's probably·23-456C·【高三英语第4页（共8页）】·23-456C【高三英语第3页（共8页）】周三许下课