上外英语MTI英语翻译基础外刊选材练习

　　外刊精读的好处：

　　上外高翻MTI考研真题中，翻译基础和翻硕英语两门科目的很多试题都是选自外刊，尤其是一些西方传统大刊，如经济学人、纽约时报、金融时报等。

　　同学们平时的备考中，通过对外刊的阅读和解析，可以帮助提高阅读速度、积累词汇和表达(包括缩略语)、增强语句理解力，了解中英思维差异，培养英语思维，掌握分析文章逻辑的能力，提高总结能力。

　　学习英文表达和句型，为汉译英和作文积累地道表达、写作素材、扩展思路，提高写作能力。

　　下面是高译老师从本周的外刊中选取的一些题材，同学们在备考中也要多多涉猎哦：

　　【汉译英练习】

　　Citywalk发源于英国伦敦，几个人在专业领队的带领下，以徒步的方式，围绕城市街道，游览一条旅游路线，从历史、地理、人文等各方面，了解一座城市的文化底蕴。走完全程之后，大家还会交流所思所想。有观点认为，从深层意义上来说，这是一种知识分享和社交行为。

　　Citywalk主打一个慢节奏。与“特种兵”旅游不一样的是，Citywalk无需计划，没有沉重的行囊，只需要一个周末甚至两三个小时，来一场说走就走的旅行。它过滤掉纷繁信息，更大程度上节约时间成本。在这个过程中，参与者更加注重旅游体验，强调用具身感受来理解这座城市。

　　Citywalk可遇见城市的各个侧面。常规的旅游团有固定景点，避免不了陷入“上车睡觉、下车方便、景区拍照”的乏味模式，而且好多导游讲解通常千篇一律。而Citywalk完全根据参与者自身需要，深入社区街道，去发掘当地人的生活面貌，感受一座城市既可以是繁华“高大上”的，也能是亲民“接地气”的。

　　参考译文

　　Citywalk took root in London, UK. It's a concept where a small group, guided by a professional guide, traverse through a city on foot. They journey along a tourist route, soaking in the city's cultural heritage by exploring its history, geography, and humanistic aspects. At the end of the expedition, participants often share their thoughts and reflections. Some argue that, at its heart, this is an exercise in knowledge exchange and social interaction.

　　Citywalk encourages slower-paced approach to tourism. It stands in stark contrast to "Commando" style tourism, a term that refers to the practice of cramming as many sightseeing spots as possible into a minimal time frame in China. There's no need for meticulous planning or lugging around heavy bags. A weekend or merely two or three hours, suffices for a spontaneous adventure. It sifts through the noise of overwhelming information, significantly cutting down time cost. Throughout the process, participants focus more on the experiential aspect of travel, emphasizing a tactile understanding of the city.

　　The experience offers a chance to encounter the city from various perspectives. Traditional tour groups typically follow a fixed tourist route, and often fall into a a tedious routine of "dozing on the bus, alighting for restroom breaks, photographing at attractions," with guides repeating the same spiels. In contrast, Citywalk is tailored according to the participants' preferences, as people immerse themselves in local neighborhoods to uncover the way of life of its residents. This approach allows participants to experience a city in its entirety, realizing that it can be simultaneously bustling and upscale, as well as homely and grounded.

　　【词条积累】

　　京杭大运河 the Beijing-Hangzhou Grand Canal

　　孔子学院 Confucius Institute

　　自杀式袭击 suicide attack

　　中国特色世界一流大学 world-class universities with Chinese characteristics

　　实事求是 seek truth from facts

　　中风 apoplexy

　　极端民族主义 Ultranationalism

　　狂热爱国主义 Superpatriotism

　　新纳粹主义 Neo-Nazism

　　白人至上 white supremacy

　　决策疲劳 decision fatigue

　　赤字开支 deficit spending

　　玻璃天花板:无形限制 glass ceiling

　　拆东墙补西墙 rob Peter to pay Paul

　　就业优先政策 pro-employment policies

　　线上招聘会 online recruiting events

　　高素质技术技能人才 high-quality technical professionals

　　宏观经济 macro economy

　　中国航天日 Space Day of China

　　探月精神 the lunar exploration spirit

　　………

　　【外刊选材阅读】

　　Health care：Wonder drugs

　　Big pharma is warming to the potential of artificial intelligence

　　【1】Paul Hudson, boss of Sanofi, is brandishing an iPhone. He is keen to show off the French drugmaker’s new artificial-intelligence (AI) app, plai. It draws on more than 1bn data points to provide “snackable” information, from warnings about low stocks of a drug to questions for a meeting with an ad agency or suggestions to set up clinical-trial sites that could expedite drug approvals. Like Netflix recommendations, plai delivers “nudges”, as Mr Hudson calls them, that are useful at that moment in time. He jokes that plai broke even in about four hours, and says the cost is “peanuts” compared with the $300m-400m that big consultancies charge for a project to curate a big company’s data. One in ten of Sanofi’s 80,000 staff uses it every day.

　　【2】AI is not new in drugmaking. Biotech firms have been tinkering with it for years. Now interest from big pharma is growing. Last year Emma Walmsley, chief executive of GSK, said it could improve the productivity of research and development, the industry’s most profound challenge. Moderna recently described itself as “laser-focused” on AI. Sanofi is “all in”. Morgan Stanley, an investment bank, reckons that within a decade the pharmaceutical industry may be spending $50bn a year on AI to speed up drug development.

　　【3】Most of the buzz revolves around AIs trained on biological data that could improve the hit-and-miss process of drug discovery. Drugs can take a decade to emerge, cost billions of dollars and succeed only 10% of the time. Even a small improvement in speed and efficiency would be hugely valuable. But scientists have struggled to tame biological big data with conventional statistical tools. Machine learning makes it possible to siftthrough piles of information, from clinical patient data and genome sequences to images of body scans. Last year DeepMind, an AI lab that is part of Google, made a breakthrough using its AlphaFold system to predict the structure of almost all proteins, which may one day help identify which molecules have therapeutic potential.

　　【4】Though only around a dozen drugs in development have so far involved the use of AI, the list may grow rapidly—especially for simple moleculeswith properties that are relatively easy to predict. In the case of these more straightforward chemistries, the future of medicine is looking ever more like a computational problem.

　　【5】Jim Weatherall, who oversees data science and AI at AstraZeneca, says the technology is used in 70% of the British firm’s small molecules in development. Using a technique called “reinforcement learning”, AstraZeneca’s AI is constantly tweaking its molecular suggestions and playing out how a tweaked molecule might react. Ali Mortazavi, boss of E-therapeutics, a biotech startup in London, says that knowing the sequences of all the genes in, say, the liver, lets his firm use software to design RNA molecules (which are more complex but, owing to their links to DNA, predictably so). AI algorithms then predict the activity of the molecules, which can stop the function of any disease-causing gene.

　　【6】Euan Ashley of Stanford University points to another AI application. “Knowledge graphs” are a kind of database that stores data about genes, proteins, diseases and drugs, as well as the biological pathways that connect them. They, too, can help identify new targets for drug development. “Generative” AI, meanwhile, is being trialled for suggesting entirely new chemical and biological structures for testing, just as ChatGPT can ingest text on the internet and spit out a new poem or essay. Beyond drug discovery, AIs like plai could help with the perennial problem of efficiency in a heavily regulated and labour-intensive sector.

　　【7】Some pharma bosses worry that generative AIs’ tendency to make stuff up could send researchers down blind alleys. More apocalyptically, Mr Hudson says half of the pharma CEOs he talks to about AI fear, like many people, the existential threats it poses. For his part, he foresees the next industrial revolution, not a robot uprising.

　　祝愿同学们都能圆梦上外，平时多多进行积累，提高备考效率和针对性的复习，奋力向前，实现梦想!

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