Mars sand dunes shift and change annually, images show

Вариант 1

I. Составьте аннотацию к статье на английском языке:

What is a neural network and how does its operation differ from that of a digital computer?

By Mohamad Hassoun

Artificial neural networks are parallel computational models, comprising densely interconnected adaptive processing units. These networks are composed of many but simple processors (relative, say, to a PC, which generally has a single, powerful processor) acting in parallel to model nonlinear static or dynamic systems, where a complex relationship exists between an input and its corresponding output.

A very important feature of these networks is their adaptive nature, in which «learning by example» replaces «programming» in solving problems. Here, «learning» refers to the automatic adjustment of the system's parameters so that the system can generate the correct output for a given input; this adaptation process is reminiscent of the way learning occurs in the brain via changes in the synaptic efficacies of neurons. This feature makes these models very appealing in application domains where one has little or an incomplete understanding of the problem to be solved, but where training data is available.

One example would be to teach a neural network to convert printed text to speech. Here, one could pick several articles from a newspaper and generate hundreds of training pairs – an input and its associated «desired» output sound – as follows: the input to the neural network would be a string of three consecutive letters from a given word in the text. The desired output that the network should generate could then be the sound of the second letter of the input string. The training phase would then consist of cycling through the training examples and adjusting the network parameters – essentially, learning – so that any error in output sound would be gradually minimized for all input examples. After training, the network could then be tested on new articles. The idea is that the neural network would «generalize» by being able to properly convert new text to speech.

Another key feature is the intrinsic parallel architecture, which allows for fast computation of solutions when these networks are implemented on parallel digital computers or, ultimately, when implemented in customized hardware. In many applications, however, they are implemented as programs that run on a PC or computer workstation.

Artificial neural networks are viable models for a wide variety of problems, including pattern classification, speech synthesis and recognition, adaptive interfaces between humans and complex physical systems, function approximation, image compression, forecasting and prediction, and nonlinear system modeling.

These networks are «neural» in the sense that they may have been inspired by the brain and neuroscience, but not necessarily because they are faithful models of biological, neural or cognitive phenomena. In fact, many artificial neural networks are more closely related to traditional mathematical and / or statistical models, such as nonparametric pattern classifiers, clustering algorithms, nonlinear filters and statistical regression models, than they are to neurobiological models.

(«Scientific American», May, 2007)

Abstract

This article was published in May 2007 in the «Scientific American». The author of this article is well-known scientist-programmer Mohamad Hassoun.

The article deals with neural networks, and shows distinct neural networks of the digital computer.

The peculiarity of this article is that, in my opinion, the neural network will be "generalized", being able to correctly convert the new text to speech.

The author suggests that artificial neural networks are a viable model for a wide range of tasks, including classification model, speech synthesis and recognition, adaptive interface between humans and complex physical systems, the approximation of functions, image compression, forecasting and prediction, and nonlinear system modeling.

II. Составьте реферат статьи на русском языке:

Mars sand dunes shift and change annually, images show

By Jason Palmer

Vast sand dunes near the northern pole of Mars are not frozen relics of a distant past, but shift and change every Martian year, data have shown. A hi-tech camera aboard Nasa's Mars Reconnaissance Orbiter has spotted UK-sized dune fields that are among the most dynamic on the Red Planet. Causes, says a report in Science, include carbon dioxide gas that freezes solid onto the dunes each winter. As it thaws in spring, the gas released destabilises, causing sand avalanches. The dune fields at high northern latitudes of Mars were first spotted by the Mariner 9 mission, launched in 1971. But only with the benefit of the High-Resolution Imaging Science Experiment (Hirise) orbiting Mars has the dynamic nature of the dunes finally been revealed. «Hirise has been monitoring seasonal processes for several years now and we've seen for a long time these strange spots and streaks that form, particularly on the sand dunes when they're defrosting», said Alfred McEwen, a planetary geologist at the University of Arizona who lead the Hirise team. A series of images taken of the dune fields over two Martian years – nearly four years on Earth – after the departure of the annual ice clearly show a changing picture of the Martian surface.

«What we've noticed more recently though is in looking at these sand dunes from year to year there are new gullies, new channels that form on the dunes, and we're seeing gullies only a year-old that have been repaired again – so there's a lot of activity we weren't aware of», Professor McEwen told BBC News. There's lots of debate about whether features we see on Mars could be produced in the current Mars climate or whether they require different conditions.

These findings lead to understanding where and when sand is moving, what that implies for both the weather and surface properties on Mars, and tweaking and calibrating various models that can be used to understand Mars in the past as well as today.

(«Science and technology report», BBC News)

Дюны поверхности планеты Марс по данным изображений ежегодно смещаются и изменяются

Джейсон Палмер

Обширные песчаные дюны вблизи северного полюса Марса не являются замороженными реликвии далекого прошлого, и меняются каждый год, данные показали. Высокотехнологической камерой с борта морсовской орбитральной стаанции НАСА была замечена дюна, которая является одной из наиболее динамичных на Красной планете. Причины, говорится в докладе, в науке, включают углекислый газ, который замерзает на твердой поверхности дюны каждую зиму. Дюна поля в высоких широтах северного полушария Марса были впервые замечены Маринер-9 миссии, начатой ​​в 1971 году. «HiRISE осуществляет мониторинг сезонных процессов в течение нескольких лет, и мы видели в течение длительного времени эти странные пятна и полосы, форму, в частности, на песчаных дюнах, когда они размораживаются», сказал Альфред Мак-Уэн, планетарный геолог из Университета Аризона, которые ведут команды HiRISE. Серия снимков, сделанных в дюнах полях в течение двух лет марсианского - около четырех лет на Земле - после ухода из ежегодного льда ясно показывают изменение картины поверхности Марса.

Эти результаты приводят к пониманию, где и когда песок движется, что это означает для погодных условий и свойств поверхности Марса, а также настройки и калибровки различных моделей, которые могут быть использованы для понимания Марса как в прошлом, так и сегодня.

(«Наука и технология, BBC News)

 

III. Перепишите предложения, заполнив пропуски подходящим по смыслу словом:

1. It’s important to maintain proper operation of the reactor.

a) reactor; b) nuclear power station; c) engine; d) electricity.

2. Radioactive particles are harmful to health.

a) chemicals; b) particles; c) substances; d) dust.

3. Nuclear weapons continue to pose athreat.

a) danger; b) catastrophe; c) threat; d) problem.

4. The rise in sea levels has been predicted as a consequence of global warming.

a) consequence; b) result; c) cause; d) reason.

5. The 1987 hurricane was the worst natural disaster 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 emissions 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 enterprises.

a) plants; b) works; c) enterprises; d) firms.

8 The President knew that some congressmen would agree with him.

a) support; b) copy; c) agree with; d) change.

9. Industrial and nuclear waste spreads in water rapidly.

a) lives; b) spreads; c) extends; d) stretches.

10.Fertilizes and pesticides pollute the environment.

a) Substances; b) Remedies; c) Fertilizes; d) Chemicals.

11. We get used to live in a small town but now we live in London.

a) used; b) get used; c) started; d) have.

12. He was arrested because he didn’t break the law.

a) imprisoned; b) arrested; c) taken to the prison; d) justified.

13. A doctor must respect the wishes of patients.

a) ignore; b) respect; c) improve; d) change.

14. The summer was very dry and there was a threat of fires in the forest.

a) threat; b) hope; c) expectance; d) believe.

15. He studied nuclear physics at the university.

a) elementary; b) good; c) nuclear; d) well.

16. International Children’s Fund was formed to improve the living conditions of children.

a) formed; b) closed; c) forgotten; d) managed.

17. A polyglot is a person who has mastered some languages.

a) invented; b) mastered; c) opened; d) heard.

18. They used instruments in road building.

a) nuclear bombs; b) chemical substances; c) explosives; d) instruments.

19. This scientist won the Nobel Prize for his discovery in Physics.

a) shop-assistant; b) engineer; c) pianist; d) scientist.

20. Alfred Nobel tried to avoid publicity.

a) avoid; b) enjoy; c) win; d) respect.

21. Alfred Nobel often thought about the meaning of his life.

a) meaning; b) beautiful; c) difficulties; d) end.

22. Michael Faraday is an English scientist who was born in a poor labouring family.

a) computer programmer; b) artist; c) plumber; d) scientist.

23. Teach your children how to care for their pets.

a) wait for; b) care for; c) laugh at; d) think of.

24. What makes you leave the town so early?

a) makes; b) helps; c) hopes; d) walks.

25. They used explosives to cut the tunnel through the mountain.

a) wars; b) explosives; c) weapons; d) spades.

26. The hardest work in mines is now performed by robots.

a) mines; b) schools; c) games; d) plays.

27. His ability 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 the meaning of this word?

a) the meaning; b) the plenty of; c) many; d) the influence.

29. She will probably be here today. She promised to come.

a) never; b) probably; c) usually; d) too.

30. You shouldn’t kill 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 injured.

a) found; b) respected; c) injured; d) avoided.

32. He realized that without the experiment his work would be useless.

a) useless; b) useful; c) successful; d) necessary.

33. I will finish my work while 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 avoid problems in future.

a) avoid; b) respect; c) occur; d) deserve.

35. Economists expect the economy to grow by 5 % next year.

a) install; b) expect; c) threaten; d) abolish.

36. This student deserves an excellent mark. He knows so much.

a) deserves; b) develops; c) chooses; d) improves.

37. Atomic ice-breaker works on nuclear energy.

a) electric; b) sun; c) nuclear; d) natural.

38. You must choose the correct answer.

a) choose; b) avoid; c) restore; d) win.

39. Alfred Nobel’s wish was to form a fund.

a) to justify; b) to form; c) to change; d) to decorate.

40. A Nobel did much for the abolition of permanent armies.

a) abolition; b) strengthening; c) development; d) improving.

 

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)

Аннотация

The article is called "DNA Computer Works in Human Cells". The author of the article is By JR Minkel. The article was published «Scientific American», May, 2007.

The article talks about 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 article highlights recent developments in the ucheny obslasi DNA computerization and discusses contemporary issues RNAi technique can reach great heights of complexity, Benenson says, by making genes sensitive to more and more siRNAs in various combinations.

II. Составьте реферат статьи на русском языке: