Как следует из отчета ББС по науке и технологиям обширные песчаные дюны вблизи северного полюса Марса не являются замороженными останками далекого прошлого, но как показывают данные цифровые камеры НАСА на борту орбитального спутника Великобритании каждый марсианский год меняются размеры полей дюн, которые являются одними из самых динамичных на Красной планете. Причиной, говорится в научном докладе, является углекислый газ, который содержится в дюнах и замораживает их каждую зиму. Весной все это тает, высвобождающийся газ дестабилизирует положение дюн и лавина песка движется. Дюнные поля в высоких северных широтах Марса были впервые замечены спутником Маринер 9, запущенным в 1971 году.
Но только с применением аппаратуры высокого разрешения на орбите Марса позволило осуществить мониторинг и выявить изменение полей. Как сказал Профессор Альфред Макьюэн планетарный геолог из Университета Аризона, который управляет командой HiRISE и осуществляет мониторинг сезонных процессов в течение нескольких лет, что уже в течение длительного времени эти странные пятна и полосы образуются на песчаных дюнах, когда они размораживаются». Серия снимков, сделанных на дюнных полях в течение двух марсианских лет - почти четыре года на Земле - ясно показывают меняющуюся картину марсианской поверхности после таяния и схода годового льда.
В последнее время ученые заметили, что эти песчаные дюны из года в год меняются, и год назад появились новые овраги, новые каналы на дюнах которые не были замечены ранее. Так что, марсианские дюнные поля демонстрируют высокую активность, особенно в летний период. Было много дебатов о том, могут ли эти особенности изменений быть следствием климата на Марсе, или они могут происходить в различных условиях.
Эти данные приводят к пониманию, где и когда песок движется, как это связано с погодными и поверхностными свойствами Марса, каким образом настроить и выбрать модели аппаратов, которые могут быть использованы для изучения прошлого и будущего Красной планеты.
III. Перепишите предложения, заполнив пропуски подходящим по смыслу словом:
1. It’s important to maintain proper operation of the …..
a) reactor; b) nuclear power station; c) engine; d) electricity.
2. Radioactive … are harmful to health.
a) chemicals; b) particles; c) substances; d) dust.
3. Nuclear weapons continue to pose a ….
a) danger; b) catastrophe; c) threat; d) problem.
4. The rise in sea levels has been predicted as a … of global warming.
a) consequence; b) result; c) cause; d) reason.
5. The 1987 hurricane was the worst natural … to hit England for decades.
a) accident; b) catastrophe; c) tragedy; d) disaster.
6. Britain is committed to a 30 per cent reduction in carbon dioxide … by 2005.
a) release; b) emissions; c) generation; d) production.
7. Mrs. Thatcher began to sell into private hands many publicly-owned production and service ….
a) plants; b) works; c) enterprises; d) firms.
8 The President knew that some congressmen would … him.
a) support; b) copy; c ) agree with; d) change.
9. Industrial and nuclear waste … in water rapidly.
a) lives; b) spreads; c) extends; d) stretches.
10. … and pesticides pollute the environment.
a) Substances; b) Remedies; c) Fertilizes; d) Chemicals.
11. We … to live in a small town but now we live in London.
a) used; b) get used; c) started; d) have.
12. He was … because he didn’t break the law.
a) imprisoned; b) arrested; c) taken to the prison; d) justified.
13. A doctor must … the wishes of patients.
a) ignore; b) respect; c) improve; d) change.
14. The summer was very dry and there was a … of fires in the forest.
a) threat; b) hope; c) expectance; d) believe.
15. He studied … physics at the university.
a) elementary; b) good; c) nuclear; d) well.
16. International Children’s Fund was … to improve the living conditions of children.
a) formed; b) closed; c) forgotten; d) managed.
17. A polyglot is a person who has … some languages.
a) invented; b) mastered; c) opened; d) heard.
18. They used … in road building.
a) nuclear bombs; b) chemical substances; c) explosives; d) instruments.
19. This … won the Nobel Prize for his discovery in Physics.
a) shop-assistant; b) engineer; c) pianist; d) scientist.
20. Alfred Nobel tried to … publicity.
a) avoid; b) enjoy; c) win; d) respect.
21. Alfred Nobel often thought about the … of his life.
a) meaning; b) beautiful; c) difficulties; d) end.
22. Michael Faraday is an English.… who was born in a poor labouring family.
a) computer programmer; b) artist; c) plumber; d) scientist.
23. Teach your children how to … their pets.
a) wait for; b) care for; c) laugh at; d) think of.
24. What … you leave the town so early?
a) makes; b) helps; c) hopes; d) walks.
25. They used … to cut the tunnel through the mountain.
a) wars; b) explosives; c) weapons; d) spades.
26. The hardest work in … is now performed by robots.
a) mines; b) schools; c) games; d) plays.
27. His … to work day and night was known to his colleagues.
a) knowledge; b) ability; c) behavior; d) fact.
28. I don’t know this word. Do you know … of this word?
a) the meaning; b) the plenty of; c) many; d) the influence.
29. She will … be here today. She promised to come.
a) never; b) probably; c) usually; d) too.
30. You shouldn’t … spiders just because you are afraid of them.
a) kill; b) like; c) avoid; d) admit.
31. The car accident took place in the street and many people were ….
a) found; b) respected; c) injured; d) avoided.
32. He realized that without the experiment his work would be....
a) useless; b) useful; c) successful; d) necessary.
33. I will finish my work … you are playing chess.
a) however; b) therefore; c) so; d) while.
34. If you learn by your own mistakes you will be able to … problems in future.
a) avoid; b) respect; c) occur; d) deserve.
35. Economists … the economy to grow by 5 % next year.
a) install; b) expect; c) threaten; d) abolish.
36. This student … an excellent mark. He knows so much.
a) deserves; b) develops; c) chooses; d) improves.
37. Atomic ice-breaker works on … energy.
a) electric; b) sun; c) nuclear; d) natural.
38. You must … the correct answer.
a) choose; b) avoid; c) restore; d) win.
39. Alfred Nobel’s wish was … a fund.
a) to justify; b) to form; c) to change; d) to decorate.
40. A Nobel did much for the … of permanent armies.
a) abolition; b) strengthening; c) development; d) improving.
IV. Вопросы для самопроверки:
1. Как излагается информация в реферате?
2. Какая дополнительная информация может указываться в реферате?
3. Что содержит текст реферата?
4. Каковы особенности употребления терминов и имен собственных в реферате?
5. Как составляется план реферата?
6. Можно ли использовать доказательства, рассуждения и исторические экскурсы при составлении реферата?
7. Что такое библиографическое описание?
Очень важной особенностью этих сетей является их адаптивный характер, в котором «обучение с помощью примера» заменяет «программирование» в решении проблем. Здесь «обучения» относится к автоматической регулировки параметров системы, так что система может генерировать правильную выход для данного входа; это процесс адаптации напоминает путь обучения происходит в мозге с помощью изменений в синаптических эффективностями нейронов. Эта особенность делает эти модели очень привлекательным в прикладных областях, где мало или неполное понимание решаемой задачи, но где обучение данные.
Искусственные нейронные сети являются параллельные вычислительные модели, включающие взаимосвязанные адаптивные плотно единиц обработки. Эти сети состоят из многих, но простых процессоров (по сравнению, скажем, с ПК, которые обычно имеют один, мощный процессор), действующей параллельно моделировать нелинейные статические или динамические системы, где сложные отношения существуют между входом и соответствующего производства,
Одним из примеров может быть, чтобы научить нейронную сеть, чтобы преобразовать напечатанный текст в речь. Здесь можно подобрать несколько статей из газеты и генерировать сотни учебных пар - вход и связанные с «лучшего» выхода звука - следующим образом: на вход нейронной сети будет строка из трех последовательных писем от данного слова в текст. Требуемый выходной, что сеть должна генерировать может быть затем звук второй буквы в строке ввода. Фаза обучения будет состоять из циклически через обучающих примеров и корректировки параметров сети - по сути, обучение - так что любая ошибка в выходной звук будет постепенно сведено к минимуму для всех примеров ввода. После обучения сеть, то может быть протестирован на новых статей. Идея заключается в том, что нейронная сеть будет «обобщить», будучи в состоянии правильно преобразовать новый текст в речь.
Еще одной ключевой особенностью является внутренняя параллельная архитектура, которая позволяет быстро расчета решений, когда эти сети, реализованных на параллельных цифровых компьютеров или, в конечном счете, при реализации в индивидуальных аппаратных средств. Во многих приложениях, однако, они реализуются в виде программ, которые работают на станции ПК или компьютера.
Искусственные нейронные сети являются жизнеспособными модели для широкого круга задач, в том числе классификации образов, распознавания и синтеза речи, адаптивных интерфейсов между человеком и сложных физических систем, функции приближения, сжатие изображений, прогнозирования и предсказания, и нелинейного моделирования системы.
Эти сети являются «нервной» в том смысле, что они, возможно, были вдохновлены мозга и неврологии, но не обязательно, потому что они верные модели биологической, нервной или когнитивных явлений. В самом деле, многие искусственные нейронные сети более тесно связаны с традиционными математическими и / или статистических моделей, таких как непараметрических классификаторов модели, алгоритмы кластеризации, нелинейных фильтров и статистических моделей регрессии, чем к нейробиологических моделей.
Вариант 2
I. Составьте аннотацию к статье на английском языке:
DNA Computer Works in Human Cells
By JR Minkel
Researchers have designed a new type of DNA computer that works in human cells, perhaps paving the way for a distant technology capable of picking out diseased cells from otherwise healthy tissue. The system runs on a process called RNA interference (RNAi) in which small molecules of RNA prevent a gene from producing protein.
The goal is to inject human cells with DNA that can determine whether a cell is cancerous or otherwise diseased, based solely on the mix of molecules inside the cell. Sensing disease, the DNA might trigger a pinpoint dose of treatment in response. That technology, however, is a long way off. For now, researchers are testing different ways of turning DNA into versatile computers that can detect certain combinations of molecules and respond by producing other molecules.
«The central challenge is how do you create a 'molecular computer' capable of making decisions», says bioengineer Yaakov Benenson of Harvard University. Researchers have designed powerful test tube DNA computers that could play tic-tac-toe or perform the basic tasks of logic, but getting them to work in human cells was likely to be tricky, Benenson says.
RNAi is something that cells do naturally. Cells produce what are known as short interfering RNA (siRNA) molecules, which recognize corresponding DNA sequences in genes and cause them to shut down.
Benenson and colleagues engineered a target gene to be sensitive to several different siRNAs of their own design. In the simplest case, they introduced a single siRNA molecule to switch off a target gene that encoded a fluorescent protein. In more complex cases, a pair of siRNAs or either of two siRNAs switched off another target gene, which in turn switched off a gene for a fluorescent protein. To make sure the system worked as intended, the researchers based their siRNAs on those of other species, they report in a paper published online today by Nature Biotechnology.
In principle, the RNAi technique can reach great heights of complexity, Benenson says, by making genes sensitive to more and more siRNAs in various combinations. «The scalability is very important, because eventually you want to make complex decisions», he says.
He says the next step is figuring out how to make the molecules inside a cell – such as those that are overproduced in cancer – trigger the production of siRNAs.
(«Scientific American», May, 2007)
II. Составьте реферат статьи на русском языке:
New Zealand scientists record «biodiversity breakdown»
By Neil Bowdler
Scientists in New Zealand say they have linked the modern-day decline of a common forest shrub with the local extinction of two pollinating birds over a century ago. They say the disappearance of two birds – the bellbird and stitch bird – from the upper North Island of the country has lead to a slow decline in common plants, including the forest shrub New Zealand gloxinia.
Ship rats and stoats imported into the country around the year 1870 are blamed for the birds' demise.
The researchers claim the study, published in the journal Science, offers rare experimental proof of a breakdown in a local ecosystem.
New Zealand gloxinia or Rhabdothamnus solandri is a gangly forest shrub, which grows in the shade to about 2m high and produces an orange tubular flower. It depends on three birds for pollination – the bellbird, stitch bird and the tui.
While the latter now seems only to feed higher up in the forest canopy, the former two vanished from upper North Island in the late 19th century. It is thought they were killed off by rats brought in by ships or by stoats introduced to control the local rabbit population.
The researchers wanted to observe the impact on New Zealand gloxinia of these disappearing bird populations and so compared the situation on the mainland with that of three nearby island bird sanctuaries where the birds remain abundant.
What they found was that pollination rates were vastly reduced on the mainland with seed production per flower 84 % lower compared with the islands.
While this has yet to fully manifest itself in the density of adult gloxinia populations on the mainland, the researchers found 55 % fewer juvenile plants per adult plant on the mainland vis-à-vis the islands.
The researchers could also quantify how often – or how little – birds visited the plant, as birds make distinct markings on the flower as they feed on the nectar.
«This plant is in trouble but it's a slow motion disaster», said Professor Dave Kelly of New Zealand's University of Canterbury, who led the research. «It hasn't been well pollinated for about the last 140 years – that's about when these birds disappeared off the North Island».
«In that time there haven't been enough seedlings coming through and so the plant is quietly crumbling away, fading away».
(«Science report», BBC News)
III. Перепишите предложения, заполнив пропуски подходящим по смыслу словом:
1. A Nobel never … any reward for what he had done.
a) expected; b) refused; c) noticed; d) avoided.
2. In Sweden A. Nobel began his own study of ….
a) weapon; b) explosives; c) substances; d) literature.
3. They found … old books in the library.
a) so; b) peace; c) plenty of; d) never.
4. I usually get up early in the morning go to the bathroom and … have breakfast.
a) then; b) too; c) yet; d) however.
5. It was an ordinary day but … an explosion occurred in the old mine.
a) few; b) really; c) nobody; d) suddenly.
6. He looked … and saw the dog running after him.
a) back; b) for; c) seldom; d) really.
7. He refused to give his … explanation.
a) meaning; b) own; c) opportunity; d) justice.
8. The explosion … in the old mine.
a) make; b) were; c) occurred; d) brought.
9. The students worked hard during the term and achieved … results.
a) excellent; b) bad; c) terrible; d) few.
10. When I have holidays I have … free time and can do anything.
a) little; b) a few; c) plenty of; d) huge.
11. His invention was used for war to kill and … people.
a) justify; b) avoid; c) injure; d) care for.
12. He realized that without the experiment his work would be....
a) useful; b) successful; c) necessary; d) useless.
13. It is important to take measures to … the risk of fire.
a) avoid; b) choose; c) need; d) win.
14. I … a good mark for the answer.
a) mastered; b) invented; c) deserved; d) passed.
15. When she was abroad she … her furniture in a warehouse.
a) left; b) sold; c) stored; d) gave.
16. That’s not the … way to stop the machine.
a) proper; b) necessary; c) reasonable; d) essential.
17. I couldn’t find a parking ….
a) territory; b) space; c) field; d) site.
18. The bag was covered with a sticky ….
a) substance; b) matter; c) component; d) mixture.
19. Have you anything … to this material but cheaper?
a) familiar; b) known; c) similar; d) same.
20. … nations sometimes try to control weaker countries.
a) Powerful; b) Advanced; c) Effective; d) Efficient.
21. The wire had … in half.
a) unite; b) divide; c) split; d) separate.
22. She gave us a short … of the rules before we started.
a) definition; b) explanation; c) annotation; d) description.
23. Many plants have medicinal ….
a) characteristics; b) qualities; c) features; d) properties.
24. The main … of the country’s industry is ship building.
a) branch; b) department; c) space; d) seat.
25. Scientists believe that ghosts do not ….
a) look; b) exist; c) believe; d) stay.
26. The company … twice last year.
a) doubled; b) established; c) founded; d) expanded.
27. The experiment gave us … data on this problem.
a) considerable; b) long; c) strong; d) huge;
28. The main … of the plane crash was bad weather.
a) question; b) substance; c) reason; d) problem.
29. The … of this system was held last year.
a) quality; b) improvement; c) quantity; d) problem.
30. The article was about how the scientists … the distance to the moon.
a) counted; b) enumerated; c) calculated; d) computed.
31. There are many cities with a … of over 2 million people.
a) people; b) inhabitants; c) population; d) residents.
32. Great spending on education is expected to lead to a large … in the number of students.
a) growth; b) rise; c) increase; d) escalation.
33. Our university has excellent sporting ….
a) facilities; b) equipment; c) conditions; d) resources.
34. I regret that a … meeting prevents me from accepting your invitation.
a) antecedent; b) future; c) early; d) previous.
35. It would … matters if you were more cooperative.
a) ease; b) help; c) facilitate; d) lighten.
36. Having read the message I came to a … decision.
a) brisk; b) hurried; c) prompt; d) rapid.
37. The house has many interesting … including a large Victorian fireplace.
a) feature; b) characteristic; c) property; d) peculiarity.
38. Is the story a complete invention, or is it … on fact?
a) written; b) told; c) founded; d) established.
39. A paint that gives woodwork … protection against the weather.
a) permanent; b) lasting; c) unending; d) stable.
40. A … of well-qualified people have recently left the company.
a) amount; b) digit; c) numeral; d) number.
IV. Вопросы для самопроверки:
1. Каковы основные способы достижения лаконичности при составлении реферата?
2. Можно ли давать субъективную оценку содержанию первичного текста при составлении реферата?
3. Можно ли пересказывать содержание документа (выводы, рекомендации, фактический материал) при составлении аннотации?
4. Какие аспекты содержания исходного документа вы включили в реферат?
5. Какие аспекты содержания включаются в аннотацию?
6. Чем отличается аннотация от реферата?
Вариант 3
I. Составьте аннотацию к статье на английском языке:
Harvard's Nano Sized «Lab in a Pocket» Could Speed Discovery of New Biofuels
By Tina Casey
Leave it to Harvard University to invent an entire laboratory the size of an iPod nano. The device, which actually is slightly smaller than an iPod nano, makes it possible to sort enzymes and compounds 1,000 times faster than the much larger equipment in use today, making it not only small but energy efficient, too.
The new device could precipitate a sea change in the way that new biofuels are developed. In particular, new biofuels based on microbes could be developed in a relatively short time, compared to a years-long sorting process with conventional equipment. And of course, that’s just a taste of things to come.
The invention, called a micro fluidic sorting device, is part of a trend toward finding more energy efficient, low cost, and sustainable methods of scientific investigation. Conventional sorting equipment is essentially a robotic process that requires energy and reagents. Harvard’s new device uses 10 million-fold less reagent and presumably far less energy; its inventors anticipate that it will reduce screening costs by one million-fold. The project was a team effort that also involved MIT, the Universite de Strasbourg, YNano LLc, the National Science Foundation, the Centre National de la Recherche Scientifique, the Massachusetts Life Sciences Center, and the Agence National de la Recherche. It takes a village, right?
Basically the name «microfluidic sorting device» says it all. In this process, microscopic drops of liquid pass through a sequence of nanotubes that fork in two directions. The drops are treated with a surfactant to prevent sticking and clumping, so they act more like marbles in a chute than normal drops of liquid. Trapped within each drop is an individual cell. When a drop reaches the fork, a laser measures the level of fluorescence in the cell. The higher the fluorescence, the higher the cell’s activity level, and the more desirable it is. The active cells are pulled into the «keep» fork by an electrical force called dielectrophoresis. The other cells drop off into the «discard» fork. In one demonstration, the device sorted 100 million (yes million) variants of a high-efficiency enzyme, evolving it into an enzyme that was even more efficient – so efficient that it practically reached its theoretical maximum (that would be an enzyme that has a production capacity equal to the number of substrates that it encounters).
The device could lead to a far more rapid means of identifying biofuel-producing organisms and improving their efficiency, possibly in a matter of months rather than years. Even with conventional lab technology, microorganisms are already elbowing crop-based biofuels aside. Just a couple of recent examples are MIT’s biofuel producing bacteria, and the glycerin-gobbling biofuel microorganisms developed by Rice University. The device also plays right into the EPA’s push for low cost, energy efficient ways to clean up contaminated sites – which in turn plays into the EPA’s newly, launched programs for reclaiming brown fields for renewable energy installations. Instead of digging up contaminated soil and dumping it elsewhere (which creates a huge carbon footprint), the new approach calls for using low cost, energy efficient on site solutions. This might include using vitamin B-12 or potassium lactate to stimulate the growth of soil dwelling microbes that «eat» pollutants. For that matter, specially engineered microbes can even be used to convert wastewater to bioplastics.
(«Scientific American»,March, 2010)
II. Составьте реферат статьи на русском языке:
