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【商务英语阅读】
[大题] Online Cultural TrainingThe Internet can play an important role in preparing marketing people for the international marketplace.While it cannot replace real-life interaction as an experiential tool,it does provide a number of benefits including comparisons between cultural ways of behaving and can provide an opportunity to develop the skills needed to interact successfully with people from other cultures.Companies typically rely on the following elements in designing web-based training:Detailed Scenarios.Much of the training materials consists of a detailed,realistic story that is tied into elements of the learner's background;i.e.,the session becomes more than a briefing;it becomes a narrated experience full of learning moments for participants This is made possible by the ability of the web to store and circulate a lot of information instantaneously around the world.Gradual Delivery.The ability to control the flow of information to the participant supports the learning process in a number of ways.Firstly,the participant is allowed to fit the training into his/her schedule.Secondly,the real-life flow of information is mimicked(模仿)and a higher degree of realism is achieved.Support.A set of detailed materials is provided to the participants 24 hours a day.At any hour and at any location,participants can check their perceptions against the materials,reinforce learning from a dimly recalled lesson,or seek feedback on an important point or issue,Relevant Exercises.Participants can be provided with topical exercises and activities the level of which can be adjusted depending upon how the participant has invested in the training.Online Discussions.Sessions can be simulcast(同时播放)to hundreds of participants around the world.The lack of face-to-face interaction can be remedied by having discussing groups where participants can share their experiences with each other.The pooled(共享的)learning experience is stronger than one with a solitary(单个的)participant.
上传用户:zfy 上传时间:2025年06月27日
【动物营养与饲料】
[大题] (铜，钴，硒，净蛋白质，氧化，氢化，青贮饲料，全价配合饲料，精料，载体)
【家畜环境卫生与设施】
[大题] (家畜环境;佝偻病;甲烷;连续式;二氧化碳;对流;蒸发;生产工艺设计;工程工艺设计;耳号牌)
上传用户:zfy 上传时间:2025年07月01日
[大题] (紫外线；红外线；散热调节；产热调节；刮板式清粪机；传送带式清粪机；风冷指数；温湿指数；60~65；7~8)
[大题] (散热调节 断喙机(切嘴机) 产热调节 辐射 连续式 间歇式 非蒸发蒸发 甲烷 二氧化碳)
【古代汉语】
[大题] 把下面短文中画线的句子泽成现代汉语。左師觸龍言願見太后。_太后盛氣而胥之_。入而徐趨，至而自謝，曰：“老臣病足，曾不能疾走，不得見久矣，竊自恕，而恐太后玉體之有所郗也，故願望見太后。”太后曰：“老婦恃蕈而行。”曰：“_日會飲得無衰乎_?”曰：“恃鬻耳。”曰：“老臣今者殊不欲食，乃自强步，日三四里，_少益耆食_，和於身也。”太后日：“老婦不能。”太后之色少解。左師公曰：“_老臣贱息舒棋，最少，不肖_。而臣衰，竊愛憐之。願令得補黑衣之數， 以衡王宫。没死以閱。”太后曰：“敬諾。年幾何矣?”對曰：“十五幾矣。雖少，_願及未填溝壑而託之_。”太后曰：“丈夫亦爱憐其少子乎? ”對曰：“甚於婦人。”太后笑曰：“婦人異甚。”對曰：“老臣竊以爲之愛燕后賢於長安君。”曰：“_君過矣，不若長安君之甚_。”
上传用户:zfy 上传时间:2025年07月16日
[大题] 阅读下面一段古文，解答文后提出的问题。晉文公將與楚人戰，召舅犯問之，曰：“_吾將與楚人戰，彼眾我寡，為之奈何_？”舅犯曰：“臣聞之，繁禮君子，不_厭_忠信；戰陣之間，不厭詐偽。君其詐之而已矣。”文公辭舅犯，因召雍季而問之，曰：“我將與楚人戰，彼眾我寡，為之奈何？”雍季對曰：“焚林而田，偷取多獸，後必無獸；以_詐_遇民，偷取一時，後必無_復_。”文公曰：“善。”_辭雍季，以舅犯之謀與楚人戰以敗之_。歸而行爵，先雍季而後舅犯。群臣曰：“城濮之事，舅犯謀也。夫用其言而後其身，可乎？”文公曰：“此非_若_所知也。_夫_舅犯言，一時之權也；雍季言，萬世之利也。”仲尼聞之，曰：“文公之霸也，宜哉！_既_知一時之權，又知萬世之利。”
[大题] 把下面短文中画线的句子译成现代汉语。昔者晉獻公欲假道於虞以伐虢，荀息曰： “君其以垂棘之璧與屈產之乘賂虞公，求假道焉，必假我道。”君曰：“垂棘之璧，吾先君之寶也；屈產之乘，寡人之駿馬也。_若受吾幣不假之道，将奈何_?”荀息曰：“彼不假我道，必不敢受我幣。若受我幣而假我道,則是寶猶取之内府而藏之外府也，馬猶取之内厩而著之外厩也,君勿憂。”君曰：“諾。乃使荀息以垂棘之璧與屈產之乘賂虞公而求假道焉。_虞公貪利其璧與馬而欲許之_。宫之奇諫曰：“不可許。夫_虞之有虢也，如車之有輔_。輔依車，車亦依輔。虞虢之勢正是也。若假之道，則虢朝亡而虞夕從之矣。不可，願勿許。”虞公弗聽，遂假之道。荀息伐虢而還，反處三年，興兵伐虞，又勉之。荀息牽馬操璧而報獻公。獻公說，曰：“璧則猶是也。雖然，_馬齒亦益長矣_。”故處公之,兵殆而地削者何也?愛小利而不慮其害。故曰：_顧小利則大利之殘也_。
上传用户:zfy 上传时间:2025年07月22日
[大题] 阅读下面一段古文，解答文后提出的问题。晉文公曰：“吾弛關市之徵而緩刑羈，甚是以戰民乎?”狐子曰：“不足。”曰：“_然則_何如足以戰民乎?”狐子對曰：“令無得不戰。”公曰：“無得不戰奈何?”狐子對曰：“信賞必罰，其足以戰。”公曰：“刑罰之極_安_至?”對曰：“不_辟_親貴，法行所愛。”文公曰：“善。”_明日令田于圃陸，期以日中為期，後期者行軍法焉_。於是公有所愛者曰顛頡，後期，吏請其罪，文公隕_涕_而憂。吏曰：“請用事焉。”遂斬顛頡之脊以徇百姓，以，明法之信也。而後百姓皆懼曰：“_君於顛頡之貴重如彼甚也，而君猶行法焉_，況于我則何有矣。”文公見民之可戰也，於是遂興兵伐原，_克_之；伐衛，東其畝，取五鹿；攻陽，勝虢；伐曹；南圉鄭，反之陴；罷宋圉；還與荆人戰城濮，大敗荆人；返局踐土之盟，遂成衡雍之義。一舉而八有功。所以然者，無他故異物，從狐偃之謀，_假_顛頡之脊也。
【高级英语】
[大题] Read the following passage carefully and complete the succeeding three items II, II, IV.(1) ChatGPT's way with words raises questions about how humans acquire language. It has reignited a debate over the ideas of Noam Chomsky, the world's most famous linguist.(2) When Deep Blue, a chess computer, defeated Garry Kasparov, a world champion, in 1997, many gasped in fear of machines triumphing over mankind.__In the intervening years. artificial intelligence has done some astonishing things. but none has managed to capture the public imagination in quite the same way.__Now, though, the astonishment of the Deep Blue moment is back, because computers are employing something that humans consider their defining ability: language.(3) Or are they? Certainly, large language models (LLMs), of which the most famous is ChatGPT, produce what looks like impeccable human writing. __In other words. ChatGPT is not a general artificial intelligence. an independent thinking machine. It is. in the jargon, a large language model.__That means it is very good at predicting what kinds of words tend to follow which others, after being trained on a huge body of text——its developer, OpenAI, does not say exactly from where——and spotting patterns.(4) But a debate has ensued about what the machines are actually doing internally,what it is that humans, in turn, do when they speak——and, inside the academy,about the theories of the world's most famous linguist, Noam Chomsky.(5) Although Professor Chomsky's ideas have changed considerably since he rose to prominence in the 1950s, several elements have remained fairly constant.He and his followers argue that human language is different in kind (not just degree of expressiveness) from all other kinds of communication. All human languages are more similar to each other than they are to, say, whale song or computer code. Professor Chomsky has frequently said a Martian visitor would conclude that all humans speak the same language, with surface variation.(6) Perhaps most notably, Chomskyan theories hold that children learn their native languages with astonishing speed and ease despite “the poverty of the stimulus": the sloppy and occasional language they hear in childhooD.__The only explanation for this can be that some kind of predisposition for language is built into the human brain.__(7) Chomskyan ideas have dominated the linguistic field of syntax since their birth. But many linguists are strident anti-Chomskyans. And some are now seizing on the capacities of LLMs to attack Chomskyan theories anew.(8) Grammar has a hierarchical, nested structure involving units within other units.Words form phrases, which form clauses, which form sentences and so on.Chomskyan theory posits a mental operation, “Merge", which glues smaller units together to form larger ones that can then be operated on further (and so on). In a recent New York Times op-ed, the man himself (now 94) and two co-authors said “we know”that computers do not think or use language as humans do, referring implicitly to this kind of cognition. LLMs, in effect,merely predict the next word in a string of words.(9) Yet it is hard, for several reasons, to fathom what LLMs“think”. __Details of the programming and training data of commercial ones like ChatGPT are proprietary.__ And not even the programmers know exactly what is going on inside.(10)Linguists have, however, found clever ways to test LLMs’underlying knowledge, in effect tricking them with probing tests. And indeed, LLMs seem to learn nested, hierarchical grammatical structures, even though they are exposed to only linear input, i.e., strings of text. They can handle novel words and grasp parts of speech. Tell ChatGPT that“dax" is a verb meaningto eat a slice of pizza by folding it, and the system deploys it easily:“After a long day at work, I like to relax and dax on a slice of pizza while watching my favourite TV show.”(The imitative element can be seen in“dax on”,which ChatGPT probably patterned on the likes of“chew on”or“munchon”.)(11)What about the “poverty of the stimulus'? After all, GPT-3 (the LLM underlying ChatGPT until the recent release of GPT-4) is estimated to be trained on about 1,000 times the data a human ten-year-old is exposed to. __That leaves open the possibility that children have an inborn tendency to grammar,making them far more proficient than any LLM. __In a forthcoming paper in Linguistic Inquiry, researchers claim to have trained an LLM on no more text than a human child is exposed to, finding that it can use even rare bits of grammar. But other researchers have tried to train an LLM on a database of only child-directed language (that is, of transcripts of carers speaking to children). Here LLMs fare far worse. Perhaps the brain really is built for language, as Professor Chomsky says.(12)It is difficult to judge. Both sides of the argument are marshaling LLMs to make their case. The eponymous founder of his school of linguistics has offered only a brief response. For his theories to survive this challenge, his camp will have to put up a stronger defence.
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