| 2013年职称英语等级考试真题（理工类A级） |
| 第1部分：词汇选项（第1～15题，每题1分，共15分） 下面每个句子中均有1个词或短语划有横线，请为每处划线部分确定1个意义最为接近的选项。&nBsp; |
| 第1题： thE rulEs ArE too rigiD to Allow For humAn Error. A. inFlExiBlE B. gEnErAl C. ComplEx D. DirECt |
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| 第2题： this spECiEs hAs nEArly DiED out BECAusE its hABitAt is BEing DEstroyED. A. turnED DEAD B. pAssED By C. CArriED AwAy D. BEComE ExtinCt |
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| 第3题： thE ContrACt BEtwEEn thE two CompAniEs will ExpirE soon. A. shortEn B. EnD C. stArt D. rEsumE |
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| 第4题： thrEE worlD-ClAss tEnnis plAyErs CAmE to ContEnt For this titlE. A. ArguE B. ClAim C. wish D. CompEtE |
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| 第5题： thE mEthoDs oF CommuniCAtion usED During thE wAr wErE primitivE. A. simplE B. rEliABlE C. EFFECtivE D. AltErnAtivE |
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| 第6题： rEspECt For liFE is A CArDinAl prinCiplE oF thE lAw. A. morAl B. rEgulAr C. FunDAmEntAl D. hArD |
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| 第7题： thE Drinking wAtEr hAs BECAmE ContAminAtED with lEAD. A. pollutED B. trEAtED C. tEstED D. CorruptED |
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| 第8题： ComE out, or i’ll Bust thE Door Down. A. shut B. sEt C. BrEAk D. BEAt |
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| 第9题： shE shED A FEw tEArs At hEr DAughtEr’s wEDDing. A. wipED B. injECtED C. proDuCED D. rEmovED |
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| 第10题： thEy DiDn’t sEEm to ApprECiAtE thE mAgnituDE oF thE proBlEm. A. ExistEnCE B. importAnCE C. CAusE D. situAtion |
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| 第11题： thE towEr rEmAins intACt EvEr AFtEr two hunDrED yEArs. A. unknown B. unusuAl C. unDAmAgED D. unstABlE |
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| 第12题： mAny ExpErts rEmAin skEptiCAl ABout his ClAims. A. DouBtFul B. untouChED C. CErtAin D. silEnt |
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| 第13题： thE proposAl wAs EnDorsED thE mAjority oF mEmBErs. A. rEjECtED B. suBmittED C. ConsiDErED D. ApprovED |
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| 第14题： rumors BEgAn to CirCulAtE ABout his FinAnCiAl proBlEms. A. sEnD B. sprEAD C. hEAr D. ConFirm |
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| 第15题： thE poliCE will nEED to kEEp A wAry EyE on this ArEA oF town. A. nAkED B. CAutious C. BlinD D. privAtE |
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| 第2部分：阅读判断（第16～22题，每题1分，共7分） 下面的短文后列出了7个句子，请根据短文的内容对每个句子做出判断：如果该句提供的是正确信息，请选择A；如果该句提供的是错误信息，请选择B；如果该句的信息文中没有提及，请选择C。 |
| 第16、17、18、19、20、21、22题： kiCking thE hABit whAt is A BAD hABit? thE most DEFinition is thAt it is somEthing thAt wE Do rEgulArly, Almost without thinking ABout it, AnD whiCh hAs somE sort oF nEgAtivE ConsEquEnCE. this ConsEquEnCE CoulD AFFECt thosE ArounD us, or it CoulD AFFECt us pErsonAlly. thosE who DEny hAving BAD hABits ArE proBABly lying. BAD hABits ArE pArt oF whAt mAkEs us humAn. mAny EArly hABits, likE suCking out thumB, ArE BrokEn whEn wE ArE vEry young. wE ArE EithEr tolD to stop Doing it By our pArEnts, or wE ConsCiously or suBConsCiously oBsErvE thAt othErs Do not hAvE thE sAmE hABit, AnD wE grADuAlly grow out oF it. it is whEn wE intEntionAlly or unintEntionAlly piCk up nEw hABits in our lAtEr ChilDhooD or EArly ADulthooD thAt it BEComEs A proBlEm. unlEss wE CAn BrEAk thAt hABit EArly on, it BEComEs A pArt oF out liFE, AnD BEComEs “progrAmmED” into our BrAin. A rECEnt stuDy oF humAn mEmory suggEsts thAt no mAttEr how hArD wE try to ChAngE out hABits, it is thE olD wAys thAt tEnD to win, EspECiAlly in situAtions whErE wE ArE rushED, strEssED or ovErworkED. hABits thAt wE thought wE hAD got riD oF CAn suDDEnly ComE BACk. During thE stuDy progrAm, thE rEsEArChErs showED A group oF voluntEErs sEvErAl piCturEs, AnD gAvE thEm worDs to AssoCiAtE with thEm. thEy thEn showED thE voluntEErs thE sAmE piCturE AgAin, AnD gAvE thEm nEw worDs to AssoCiAtE with thEm. A FEw DAys lAtEr, thE voluntEErs wErE givEn A tEst. thE rEsEArChErs showED thEm thE piCturEs, AnD tolD thEm to rEsponD with onE oF thE worDs thEy hAD BEEn givEn For EACh onE. it CAmE As no surprisE thAt thEir AnswErs wErE split BEtwEEn thE First sEt oF worDs AnD sEConD. two wEEks lAtEr, thEy wErE givEn thE sAmE tEst AgAin. this timE, most oF thEm only gAvE thE First sEt oF worDs. thEy AppEArED to hAvE ComplEtEly ForgottEn thE sEConD sEt. thE stuDy ConFirms thAt thE rEsponsEs wE lEArn First ArE thosE thAt rEmAin strongEst ovEr timE. wE mAy try to ChAngE out wAys, But AFtEr A whilE, thE rEsponsE thAt ComEs to minD First is usuAlly thE First onE wE lEArnED. thE morE thAt rEsponsE is usED, thE morE AutomAtiC it BEComEs AnD thE hArDEr it BEComEs to rEsponD in Any othEr wAy. thE stuDy thErEForE suggEsts thAt ovEr timE, our BAD hABits Also BEComE AutomAtiC, lEArnED BEhAvior. this is not gooD nEws For pEoplE who piCk up BAD hABits EArly in liFE AnD now wAnt to ChAngE or BrEAk thEm. EvEn whEn wE try to put nEw, gooD intEntions into prACtiCE, thosE prEvious lEArnED hABits rEmAin strongEr in morE AutomAtiC, unConsCious Forms oF mEmory. 16. Boys usuAlly DEvElop BAD hABits whEn thEy ArE vEry young. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 17. wE CAn only BrEAk BAD hABits iF othErs tEll us to Do. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 18. BAD hABits mAy rEturn whEn wE ArE unDEr prEssurE. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 19. rEsEArChErs wErE surprisED By thE AnswEr thAt thE voluntEErs gAvE in thE First tEst. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 20. thE voluntEErs FounD thE tEst morE DiFFiCult whEn thEy DiD it thE sEConD timE. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 21. thE stuDy suggEsts thAt it is morE DiFFiCult to rEsponD whAt to gEt riD oF. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED 22. iF wE DEvElop BAD hABits EArly in liFE, thEy ArE hArDEr to gEt riD oF. A. right &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. wrong &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. not mEntionED |
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| 第3部分：概括大意与完成句子（第23～30题，每题1分，共8分） 下面的短文后有2项测试任务：（1）第23～26题要求从所给的6个选项中为第1～4段每段1选择个最佳标题；（2）第27～30题要求从所给的6个选项中为每个句子确定1个最佳选项。 |
| 第23、24、25、26、27、28、29、30题： BlACk holEs 1 BlACk holEs CAn BE BEst DEsCriBED As A sort oF vACuum, suCking up EvErything in spACE. sCiEntists hAvE DisCovErED thAt BlACk holEs ComE From An Explosion oF hugE stArs. stArs thAt ArE nEAr DEAth CAn no longEr Burn DuE to loss oF FuEl, AnD BECAusE its tEmpErAturE CAn no longEr Control thE grAvitAtionAl(重力的) ForCE, hyDrogEn EnDs up putting prEssurE onto thE stAr’s surFACE until it suDDEnly ExploDEs thEn CollApsEs. 2 BlACk holEs ComE From stArs thAt ArE mADE oF hyDrogEn, othEr gAsEs AnD A FEw mEtAls. whEn thEsE ExploDE it CAn turn into A stEllAr-mAss(恒星质量) BlACk holE, whiCh CAn only oCCur iF thE stAr is lArgE Enough (shoulD BE BiggEr thAn thE sun) For thE Explosion to BrEAk it into piECEs, AnD thE grAvity stArts to CompACt EvEry piECE into thE tiniEst pArtiClE. try to sEE AnD CompArE: iF A stAr thAt’s tEn timEs thE sizE oF thE sun EnD up BEing A BlACk holE thAt’s no longEr thAn 70 kilomEtErs, thEn thE EArth woulD BEComE BlACk holE thAt’s only A FrACtion oF An inCh! 3 oBjECts thAt gEt suCkED in A BlACk holE will AlwAys rEmAin thErE, nEvEr to BrEAk FrEE. But rEmEmBEr thAt BlACk holEs CAn only goBBlE up(吞噬) oBjECts within A spECiFiC DistAnCE to it. it’s possiBlE For A lArgE stAr nEAr thE sun to BEComE A BlACk holE, But thE sun will ContinuE to stAy in plACE. orBits(轨道) Do not ChAngE BECAusE thE nEwly FormED BlACk holE ContAins ExACtly thE sAmE Amount oF mAss As whEn it wAs A stAr, only this its mAss is totAlly ContrACtED thAt it CAn EnD up As no BiggEr thAn A stAtE. 4 so FAr, AstronomErs hAvE FigurED out thAt BlACk holEs Exist BECAusE oF AlBErt EinstEin’s thEory oF rElAtivity. in thE EnD, through numErous stuDiEs, thEy hAvE DisCovErED thAt BlACk holEs truly Exist. sinCE BlACk holEs trAp light AnD Do not givE oFF light, it is not possiBlE to DEtECt BlACk holEs viA A tElEsCopE. But AstronomErs ContinuE to ExplorE gAlAxiEs(银河系), spACE AnD thE solAr systEm to unDErstAnD how BlACk holEs. it is possiBlE thAt BlACk holEs CAn Exist For millions oF yEArs, AnD lAtEr ContriButE FurthEr proCEss in gAlAxiEs, whiCh CAn EvEntuAlly lEAD to CrEAtion oF nEw EntitiEs. sCiEntists Also CrEDit BlACk holEs As hElpFul in lEArning how gAlAxiEs BEgAn to Form. 23 pArAgrAph 1________ 24 pArAgrAph 2________ 25 pArAgrAph 3________ 26 pArAgrAph 4________ A is thErE prooF thAt BlACk holEs rEAlly Exist? B whAt ArE DiFFErEnt typEs oF BlACk holEs? C how ArE BlACk holEs FormED? D how wErE BlACk holEs nAmED? E whAt hAppEnED to thE oBjECts ArounD A BlACk holE? F whAt ArE BlACk holEs mADE oF? 27 BlACk holEs ArE FormED AFtEr______. 28 whEn A lArgE stAr ExploDEs, thE grAvity CompACts EvEry piECE into ______. 29 A nEwly FormED BlACk holE AnD thE stAr it ComEs From ArE oF______. 30 AlBErt EinstEin’s thEory oF rElAtivity hElps to provE______. A thE CrEAtion oF nEw EntitiEs B An Explosion oF hugE stAts C thE thinnEst pArtiClE D thE sAmE Amount oF mAss E thE ExistEnCE oF BlACk holEs F A FrACtion oF An inCh |
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| 第4部分：阅读理解（第31~45题，每题3分，共45分） 下面有3篇短文，每篇短文后有5道题，每道题后面有4个选项。请根据文章的内容，从每题所给的4个选项中选择1个最佳答案，涂在答题卡相应的位置上。 |
| 第31、32、33、34、35题： ForECAsting mEthoDs thErE ArE sEvErAl DiFFErEnt mEthoDs thAt CAn BE usED to CrEAtE A ForECAst. thE mEthoD A ForECAstEr ChoosEs DEpEnDs upon thE ExpEriEnCE oF thE ForECAstEr, thE Amount oF inFormAtion AvAilABlE to thE ForECAstEr, thE lEvEl oF&nBsp; DiFFiCulty thAt thE ForECAst situAtion prEsEnts, AnD thE DEgrEE oF ACCurACy or ConFiDEnCE nEEDED in thE ForECAst. thE First oF thEsE mEthoDs is thE pErsistEnCE mEthoD; thE simplEst wAy oF proDuCing A ForECAst. thE pErsistEnCE mEthoD AssumEs thAt thE ConDitions At thE timE oF thE ForECAst will not ChAngE, For ExAmplE, iF it is sunny AnD 87 DEgrEE toDAy, thE pErsistEnCE mEthoD prEDiCts thAt it will BE sunny AnD 87 DEgrEE tomorrow. iF two inChEs oF rAin FEll toDAy thE pErsistEnCE mEthoD woulD prEDiCt two inChEs oF rAin For tomorrow. howEvEr, iF wEAthEr ConDitions ChAngE signiFiCAntly From DAy to DAy, thE pErsistEnCE mEthoD usuAlly BrEAks Down AnD is not thE BEst ForECAsting mEthoD to usE. thE trEnDs mEthoD involvEs DEtErmining thE spEED AnD DirECtion oF movEmEnt For Fronts, high AnD low prEssurE CEntErs, AnD ArEAs oF ClouDs AnD prECipitAtion(降水量). using this inFormAtion, thE ForECAstEr CAn prEDiCt whErE hE or shE ExpECts thosE FEAturEs to BE At somE FuturE timE. For ExAmplE, iF A storm systEm is 1000 milEs wEst oF your loCAtion AnD moving to thE EAst At 250 milEs pEr DAy, using thE trEnDs mEthoD you woulD prEDiCt it to ArrivE in your ArEA in 4 DAys, thE trEnDs mEthoD works wEll whEn systEms ContinuE to movE At thE sAmE spEED in thE sAmE DirECtion For A long pErioD oF timE. iF thEy slow Down, spEED up, ChAngE intEnsity, or ChAngE DirECtion, thE trEnDs ForECAst will proBABly not work As wEll. thE ClimAtology(气候学) mEthoD is AnothEr simplE wAy oF proDuCing A ForECAst. this mEthoD involvEs AvErAging wEAthEr stAtistiCs ACCumulAtED ovEr mAny yEArs to mAkE thE ForECAst. For ExAmplE, iF you wErE using thE ClimAtologiC mEthoD to prEDiCt thE wEAthEr For nEw york City on july 4th, you woulD go through All thE wEAthEr DAtA thAt hAs BEEn rECorDED For EvEry july 4th AnD tAkE An AvErAgE. thE ClimAtologiC mEthoD only works wEll whEn thE wEAthEr pAttErn is similAr to thAt ExpECtED For thE ChosEn timE oF yEAr. iF thE pAttErn is quitE unusuAl For thE givEn timE oF yEAr, thE ClimAtologiC mEthoD will oFtEn FAil. thE AnAlog mEthoD is A slightly morE CompliCAtED mEthoD oF proDuCing A ForECAst. it involvEs ExAmining toDAy’s ForECAst sCEnArio(模式) AnD rEmEmBEring A DAy in thE pAst whEn thE wEAthEr sCEnArio lookED vEry similAr (An AnAlog) thE ForECAstEr woulD prEDiCt thAt thE wEAthEr in this ForECAst will BEhAvE thE sAmE As it DiD in thE pAst, thE AnAlog mEthoD is DiFFiCult to usE BECAusE it is virtuAlly impossiBlE to FinD A prEDiCt AnAlog. vArious wEAthEr FEAturEs rArEly Align thEmsElvEs in thE sAmE loCAtions thEy wErE in thE prEvious timE. EvEn smAll DiFFErEnCEs BEtwEEn thE CurrEnt timE AnD thE AnAlog CAn lEAD to vEry DiFFErEnt rEsults. 31 whiCh oF thE Following FACtors is not mEntionED in Choosing A ForECAsting mEthoD? A. nECEssAry Amount oF inFormAtion. B. DEgrEE oF DiFFiCulty involvED in ForECAsting. C. prACtiCAl knowlEDgE oF thE ForECAstEr. D. CrEAtivity oF thE ForECAstEr. 32 thE pErsistEnCE mEthoD FAils to work wEll whEn_____. A. it is rAiny B. it is sunny C. wEAthEr ConDitions stAy stABlE D. wEAthEr ConDitions ChAngE grEAtly 33 thE trEnDs mEthoD works wEll whEn_____. A. wEAthEr ConDitions ArE ConstAnt For A long pErioD oF timE B. wEAthEr ConDitions ArE DEFinED wEll Enough C. prEDiCtion on prECipitAtion ArE ACCurAtE D. thE spEED AnD DirECtion oF movEmEnt ArE prEDiCABlE 34 thE AnAlog mEthoD shoulD not BE usED in mAking A wEAthEr ForECAst whEn_____. A. thE AnAlog looks CompliCAtED B. thE CurrEnt wEAthEr sCEnArio is DiFFErEnt From thE AnAlog C. thE AnAlog is morE thAn 10 yEArs olD D. thE CurrEnt wEAthEr sCEnArio is ExACtly thE sAmE As thE AnAlog 35 historiCAl wEAthEr DAtA ArE nECEssAry in_____. A. thE pErsistEnCE mEthoD AnD thE trEnDs mEthoD B. thE trEnDs mEthoD AnD thE ClimAtology mEthoD C. thE ClimAtology mEthoD AnD thE AnAlog mEthoD D. thE pErsistEnCE mEthoD AnD thE AnAlog mEthoD |
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| 第36、37、38、39、40题： stuDEnts lEArn BEttEr with touChsCrEEn DEsks oBsErvE thE CritiCisms oF nEArly Any mAjor puBliC EDuCAtion systEm in thE worlD, AnD A FEw oF thE mAny ComplAints ArE morE or lEss univErsAl. tEChnology movEs FAstEr thAn thE EDuCAtion systEm. tEAChErs must tEACh At thE pACE oF thE slowEst stuDEnt rAthEr thAn thE FAstEst. AnD — pArtiCulArly in thE unitED stAtEs — grADE sChool ChilDrEn As A group Don’t CArE muCh For, or ExCEl At, mAthEmAtiCs. so it’s hEArtEning to lEArn thAt A nEw kinD oF “ClAssroom oF thE FuturE” shows promisE At mitigAting somE oF thEsE proBlEms, stArting with thAt FunDAmEntAl piECE oF ClAssroom FurniturE: thE DEsk. Auk stuDy involving roughly 400 stuDEnts, mostly AgED 8-10 yEArs, AnD A nEw gEnErAtion oF multi-touCh, multi-usEr, ComputErizED DEsktop surFACEs is showing thAt ovEr thE lAst thrEE yEArs thE tEChnology hAs ApprECiABly BoostED stuDEnts’ mAth skills CompArED to pEErs lEArning thE sAmE mAtEriAl viA thE ConvEntionAl pApEr-AnD-pEnCil mEthoD. how? through CollABorAtion, mostly, As wEll As By giving tEAChErs BEttEr tools By whiCh to miCromAnAgE inDiviDuAl stuDEnts who nEED somE ExtrA instruCtion whilE Allowing thE rEst oF thE ClAss to ContinuE moving ForwArD. sCiEnCE, ClAy Dillow, ClAssroom oF thE FuturE, EDuCAtion, EnginEEring, mAth, mAthEmAtiCs, synErgy nEt trADitionAl instruCtion still shows rEspECtABlE EFFiCACy(效力) At inCrEAsing stuDEnts FluEnCy in mAthEmAtiCs, EssEntiAlly through mEmorizAtion AnD prACtiCE — Dull, rEpEtitivE prACtiCE. But thE rEsEArChErs hAvE ConCluDED thAt thEsE nEw touCh sCrEEn DEsks Boost Both FluEnCy AnD FlExiBility — thE CritiCAl thinking skills thAt Allow stuDEnts to solvE ComplEx proBlEms not simply through knowing FormulAs AnD DEviCEs, But By BEing ABlE to FigurE out whAt thE rEAl proBlEm is AnD thE most EFFECtivE mEAns oF stripping it Down AnD solving it. onE rEAson For this, thE rEsEArChErs sAy, is thE multi-touCh AspECt oF thE tEChnology. stuDEnts working in thE nExt-gEn ClAssroom CAn work togEthEr At thE sAmE tABlEtop, EACh oF thEm ContriButing AnD EngAging with thE proBlEm As pArt oF A group. known As synErgy nEt, thE soFtwArE usEs ComputEr vision systEms thAt sEE in thE inFrArED(红外线) spECtrum to Distinguish BEtwEEn DiFFErEnt touChEs on DiFFErEnt pArts oF thE surFACE, Allowing stuDEnts to ACCEss AnD usE tools on thE sCrEEn, movE oBjECts AnD visuAl AiDs ArounD on thEir DEsktops, AnD othErwisE physiCAlly intErACt with thE numBErs AnD inFormAtion on thEir sCrEEns. By using thEsE sCrEEns CollABorAtivEly, thE rEsEArChErs sAy, thE stuDEnts ArE to somE ExtEnt tEAChing thEmsElvEs As thosE with A strongEr grAsp on DiFFiCult ConCEpts pull othEr stuDEnts ForwArD Along with thEm. 36 whiCh oF thE Following is not truE oF thE puBliC EDuCAtion systEm? A it DoEs not CAtCh up with thE DEvElopmEnt oF tEChnology. B tEAChErs pAy morE AttEntion to FAst lEArnErs thAn slow lEArnErs. C somE similAr ComplAints ABout it ArE hEArD in DiFFErEnt CountriEs. D mAny stuDEnts ArE not gooD At lEArning mAthEmAtiCs. 37 whAt hAs BEEn FounD AFtEr thE nEw tECh is EmployED? A tEAChErs ArE ABlE to givE inDiviDuAlizED AttEntion to stuDEnts in nEED. B stuDEnts BEComE lEss ACtivE in lEArning mAthEmAtiCs. C stuDEnts show prEFErEnCE to thE ConvEntionAl pApEr-AnD-pEnCil mEthoD. D thE gAp BEtwEEn slow lEArnErs AnD FAst lEArnErs gEts morE notiCEABlE. 38 whAt is thE BEnEFit stuDEnts gEt From thE nEw tECh? A it mAkEs thEm morE FluEnt in puBliC spEECh. www.zCEnglish.Com.Cn 6 B it oFFErs thEm morE FlExiBility in Choosing CoursEs. C it is EFFECtivE in hElping thEm solvE physiCAl proBlEms. D it EnABlEs thEm to DEvElop CritiCAl thinking ABility. 39 whAt hAppEns whEn stuDEnts ArE using thE DEsktop oF thE nEw tECh? A EvEry stuDEnt hAs An inDiviDuAl tABlE top. B stuDEnts usE DiFFErEnt tools to intErACt with EACh othEr. C thE multi-touCh FunCtion stimulAtEs stuDEnts. D thE soFtwArE instAllED AutomAtiCAlly iDEntiFiEs DiFFErEnt usErs. 40 how DoEs thE nEw tECh work to improvE stuDEnts’ mAthEmAtiCAl lEArning? A it hElps FAst lEArnErs to lEArn FAstEr. B it mAkEs tEAChErs’ instruCtion unnECEssAry. C it EnABlEs thEm to work togEthEr. D it Allows thE wholE ClAss to lEArn At thE sAmE timE. |
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| 第41、42、43、44、45题： on thE triAl oF thE honEy BADgEr on A rECEnt FiElD trip to thE kAlAhAri DEsErt, A tEAm oF rEsEArChErs lEArn A lot morE ABout honEy BADgErs. thE tEAm EmployED A loCAl wilDliFE ExpErt kitso khAmA to hElp thEm loCAtE AnD Follow thE BADgErs ACross thE DEsErt. thEir mAin Aim wAs to stuDy thE BADgErs’ movEmEnts AnD BEhAvior As DisCrEEtly(谨慎地) As possiBlE without FrightEning thEm AwAy or CAusing thEm to ChAngE thEir nAturAl BEhAvior. thEy Also plAnnED to trAp A FEw AnD stuDy thEm ClosE up BEForE rElEAsing thEm in viEw oF thE AnimAl’s rEputAtion, this wAs somEthing thAt EvEn khAmA wAs rEluCtAnt to Do. “thE proBlEm with honEy BADgErs is thEy ArE nAturAlly Curious AnimAls, EspECiAlly whEn thEy sEE somEthing nEw,” hE sAys. “thAt, ComBinED with thEir unprEDiCtABlE nAturE, CAn BE A DAngErous mixturE. iF thEy sEnsE you hAvE FooD, For ExAmplE, thEy won’t BE shy ABout Coming right up to you For somEthing to EAt. thEy’rE ACtuAlly quitE soCiABlE CrEAturEs ArounD humAns, But As soon As thEy FEEl thEy might BE in DAngEr, thEy CAn BEComE ExtrEmEly viCious(凶恶的). FortunAtEly this is rArE, But it DoEs hAppEn.” thE rEsEArCh ConFirmED mAny things thAt wErE AlrEADy known. As ExpECtED, honEy BADgErs AtE Any CrEAturEs thEy CoulD CAtCh AnD kill. EvEn poisonous snAkEs, FEArED AnD AvoiDED By most othEr AnimAls, wErE not sAFE From thEm. thE rEsEArChErs wErE surprisED, howEvEr, By thE AnimAl’s FonDnEss For loCAl mElons, proBABly BECAusE oF thEir high wAtEr ContEnt. prECiously rEsEArChErs thought thAt thE AnimAl got All oF its liquiD rEquirEmEnts From its prEy(猎物). thE tEAm Also lEArnt thAt, ContrAry to prEvious rEsEArCh FinDings, thE BADgErs oCCAsionAlly FormED loosE FAmily groups. thEy wErE Also ABlE to ConFirm CErtAin rEsults From prEvious rEsEArCh, inCluDing thE FACt thAt FEmAlE BADgErs nEvEr soCiAlizED with EACh othEr. Following somE oF thE mAlE BADgErs wAs A ChAllEngE, sinCE thEy CAn CovEr lArgE DistAnCEs in A short spACE oF timE. somE hunting tErritoriEs CovEr morE thAn 500 squArE kilomEtErs. Although thEy sEEm hAppy to shArE thEsE tErritoriEs with othEr mAlEs, thErE ArE oCCAsionAl Fights ovEr An importAnt FooD sourCE, AnD mAlE BADgErs CAn BE As AggrEssivE towArDs EACh othEr As thEy ArE towArDs othEr spECiEs. As thE BADgErs BECAmE ACCustomED to thE prEsEnCE oF pEoplE, it gAvE thE tEAm thE to gEt up ClosE to thEm without BEing thE suBjECt oF thE AnimAl’s Curiosity—or suDDEn AggrEssion. thE BADgErs’ EAting pAttErns, whiCh hAD BEEn DisruptED, to normAl. it Also AllowED thE tEAm to oBsErvE morE ClosEly somE oF thE othEr CrEAturEs thAt Form working AssoCiAtions with thE honEy BADgEr, As thEsE sEEmED to BADgErs’ rElAxED AttituDE whEn nEAr humAns. 41 why DiD thE wilD liFE ExpErts visit thE kAlAhAri DEsErt? A. to FinD whErE honEy BADgErs livE. B. to CAtCh somE honEy BADgErs For FooD. 7 C. to oBsErvE how honEy BADgErs BEhAvE. D. to FinD out why honEy BADgErs hAvE A BAD rEputAtion. 42 whAt DoEs kitso khAmA sAy ABout honEy BADgErs? A. thEy ArE AlwAys looking For FooD. B. thEy Do not Enjoy humAn CompAny. C. thEy show intErEst in things thEy ArE not FAmiliAr with. D. it is Common For thEm to AttACk pEoplE. 43 whAt DiD thE tEAm FinD out ABout honEy BADgErs? A. thErE wErE somE CrEAturEs thEy DiD not EAt. B. thEy wErE AFrAiD oF poisonous CrEAturEs. C. FEmAlE BADgErs DiD not mix with mAlE BADgErs. D. thEy mAy gEt somE oF thE wAtEr thEy nEEDED From Fruit. 44 whiCh oF thE Following is A typiCAl FEAturE oF mAlE BADgErs? A. thEy Don’t run vEry quiCkly. B. thEy DEFEnD thEir tErritory From othEr BADgErs. C. thEy hunt ovEr A vEry lArgE ArEA. D. thEy ArE morE AggrEssivE thAn FEmAlEs. 45 whAt hAppEnED whEn honEy BADgErs got usED to humAns ArounD thEm? A. thEy BECAmE lEss AggrEssivE towArDs othEr CrEAturEs. B. thEy lost intErEst in pEoplE. C. thEy stArtED EAting morE. D. othEr AnimAls stArtED working with thEm. |
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| 第5部分：补全短文（第46～50题，每题2分，共10分） 下面的短文有5处空白，短文后有6个句子，其中5个取自短文，请根据短文内容将其分别放回原有位置，以恢复文章原貌。 |
| 第46、47、48、49、50题： toADs ArE Arthritis AnD in pAin Arthritis(关节炎) is An illnEss thAt CAn CAusE pAin AnD swElling in your BonEs. toADs (蟾蜍), A Big proBlEm in thE north oF AustrAliA, ArE suFFEring From pAinFul Arthritis in thEir lEgs AnD BACkBonE, A nEw stuDy hAs shown. thE toADs thAt jump thE FAstEst ArE morE likEly to BE lArgEr AnD to hAvE longEr lEgs._______(46) thE lArgE yEllow toADs, nAtivE to south AnD CEntrAl AmEriCA, wErE introDuCED into thE north-EAstErn AustrAliAn stAtE oF quEEnslAnD in 1935 in An AttEmpt to stop BEEtlEs AnD othEr insECts From DEstroying sugArCAnE Crops. now up to 200 million oF thE poisonous toADs Exist in thE Country, AnD thEy ArE rApiDly sprEADing through thE stAtE oF northErn tErritory At A rAtE oF up to 60 km A yEAr. thE toADs CAn now BE FounD ACross morE thAn onE million squArE kilomEtrEs._______(47) A vEnEzuElAn poison virus wAs triED in thE 1990s But hAD to BE ABAnDonED AFtEr it wAs FounD to Also kill nAtivE Frog spECiEs. thE toADs hAvE sEvErEly AFFECtED ECosystEms in AustrAliA. AnimAls, AnD somEtimEs pEts, thAt EAt thE toADs DiE immEDiAtEly From thEir poison, AnD thE toADs thEmsElvEs EAt Anything thEy CAn Fit insiDE thEir mouth._______(48) A Co-Author oF thE nEw stuDy, riCk shinE, A proFEssor At thE univErsity oF syDnEy, sAys thAt littlE AttEntion hAs BEEn givEn to thE proBlEms thAt toADs FACE. riCk AnD his CollEAguEs stuDiED nEArly 500 toADs From quEEnslAnD AnD thE northErn tErritory AnD FounD thAt thosE in thE lAttEr stAtE wErE vEry DiFFErEnt. thEy wErE ACtivE, sprinting Down roADs AnD BrEEDing quiCkly. ACCorDing to thE rEsults oF thE stuDy, thE FAstEst toADs trAvEl nEArly onE kilomEtrE A night._______(49) But spEED AnD strEngth ComE At A priCE — Arthritis oF thE lEgs AnD BACkBonE DuE to ConstAnt prEssurE plACED on thEm. in lABorAtory tEsts, thE rEsEArChErs FounD thAt AFtEr ABout 15 minutEs oF hopping, ArthritiC toADs woulD trAvEl lEss &nBsp;DistAnCE with EACh hop (跳跃)._______(50) thEsE toADs ArE so progrAmmED to movE, AppArEntly, thAt EvEn whEn in pAin thE toADs trAvEllED As FAst AnD As FAr As thE hEAlthy onEs, Continuing thEir ConstAnt mArCh ACross thE lAnDsCApE. A. thE tAsk now FACing thE Country is how to rEmovE thE toADs. B. toADs ArE not Built to BE roAD run nErs —— thEy ArE Built to sit ArounD ponDs AnD wEt ArEAs. C. But this ADvAntAgE Also hAs A Big DrAwBACk — up to 10% oF thE BiggEst toADs suFFEr From Arthritis. D. toADs with longEr lEgs movE FAstEr AnD trAvEl longEr DistAnCEs whilE thE othErs ArE BEing lEFt BEhinD. E. But Arthritis DiDn’t slow Down toADs outsiDE thE lABorAtory thE rEsEArCh FounD. F. FurthErmorE, thEy soon tAkE ovEr thE nAturAl hABitAts oF AustrAliA’s nAtivE spECiEs. |
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| 第6部分：完形填空（第51~65题，每题1分，共15分） 阅读下面的短文，文中有15处空白，每处空白给出了4个选项，请根据短文的内容从4个选项中选择1个最佳答案，涂在答题卡相应的位置上。 |
| 第51、52、53、54、55、56、57、58、59、60、61、62、63、64、65题： BEttEr solAr EnErgy systEms: morE hEAt, morE light solAr photovoltAiC thErmAl EnErgy systEms, or pvts, gEnErAtE Both hEAt AnD ElECtriCity, But ____(51)____ now thEy hAvEn’t BEEn vEry gooD At thE hEAt-gEnErAting pArt CompArED to A stAnD-AlonE solAr thErmAl CollECtor. thAt’s BECAusE thEy opErAtE At low tEmpErAturEs to Cool CrystAllinE siliCon solAr CElls, ____(52)____ lEts thE siliCon gEnErAtE morE ElECtriCity But isn’t A vEry EFFiCiEnt wAy to gAthEr hEAt. thAt’s A proBlEm oF EConomiCs. gooD solAr hot-wAtEr systEms CAn hArvEst muCh morE EnErgy thAn A solAr-ElECtriC systEm At A suBstAntiAlly lowEr ____(53)____.AnD it’s Also A spACE proBlEm: photovoltAiC CElls CAn ____(54)____ up All thE spACE on thE rooF, lEAving littlE room For thErmAl AppliCAtions. in A pAir oF stuDiEs, joshuA pEArCE, An AssoCiAtE proFEssor oF mAtEriAls sCiEnCE AnD EnginEEring, hAs DEvisED A ____(55)____ in thE Form oF A BEttEr pvt mADE with A DiFFErEnt kinD oF siliCon. his rEsEArCh CollABorAtors ArE kunAl girotrA From thin siliCon in CAliForniA AnD miChAEl pAthAk AnD stEphEn hArrison From quEEn’s univErsity, CAnADA. most solAr pAnEls ArE mADE with CrystAllinE siliCon, But you CAn Also mAkE solAr CElls out oF Amorphous siliCon, Commonly known ____(56)____ thin-Film siliCon. thEy Don’t CrEAtE As muCh ElECtriCity, But thEy ArE lightEr, FlExiBlE, AnD ChEApEr. AnD, BECAusE thEy ____(57)____ muCh lEss siliCon, thEy hAvE A grEEnEr Footprint. ____(58)____, thin-Film siliCon solAr CElls ArE vulnErABlE to somE BAD-nEws physiCs in thE Form oF thE stAEBlEr-wronski EFFECt. “thAt mEAns thAt thEir EFFiCiEnCy Drops whEn you ____(59)____ thEm to light — prEtty muCh thE worst possiBlE EFFECt For A solAr CEll,” pEArCE ExplAins, whiCh is onE oF thE ____(60)____ thin- Film solAr pAnEls mAkE up only A smAll FrACtion oF thE mArkEt. howEvEr, pEArCE AnD his tEAm FounD A ____(61)____ to EnginEEr ArounD thE stAEBlEr-wronski EFFECt By inCorporAting thin-Film siliCon in A nEw ____(62)____ oF pvt. you Don’t hAvE to Cool Down thin-Film siliCon to mAkE it work. in FACt, pEArCE’s group DisCovErED thAt By hEAting it to solAr-thErmAl opErAting tEmpErAturEs, nEAr thE Boiling ____(63)____ oF wAtEr, thEy CoulD mAkE thiCkEr CElls thAt lArgEly ____(64)____ thE stAEBlEr-wronski EFFECt. whEn thEy AppliED thE thin-Film siliCon DirECtly to A solAr thErmAl EnErgy CollECtor, thEy Also FounD thAt By BAking thE CEll onCE A DAy, thEy ____(65)____ thE solAr CEll’s ElECtriCAl EFFiCiEnCy By ovEr 10 pErCEnt. 51. A. until &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. unlEss &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. whEn &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. iF 52. A. whAt &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. whiCh &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. thAt &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. who 53. A. rEwArD &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. Bill &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. pAy &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. Cost 54. A. movE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. sEt &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. livE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. tAkE 55. A. DECision &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. suggEstion&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. solution &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. quAliFiCAtion 56. A. For &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. By &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. with &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. As 57. A. rEtriEvE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. mErgE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. rEquirE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. ExChAngE 9 58. A. unFortunAtEly &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. CErtAinly &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. luCkily &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. immEDiAtEly 59. A. CovEr&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; B. rElAtE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. FACE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. ExposE 60. A. rEstriCtions&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; B. ADvAnCEs&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; C. rEAsons&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; D. strEngths 61. A. pArt &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. rEsult &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. suBjECt&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; D. wAy 62. A. typE&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; B. sizE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. shApE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. BrAnD 63. A. ArEA &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. point &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. plACE &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. ExtEnt 64. A. promotED &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;B. improvED &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. ovErCAmE&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; D. AssErtED 65. A. BoostED&nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp; B. DEFinED &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;C. wAstED &nBsp;&nBsp; &nBsp; &nBsp; &nBsp; &nBsp; &nBsp;D. lowEr |
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