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1 create problems
Военный термин: создавать проблему -
2 create problems
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3 create problems
English-Russian dictionary of terms that are used in computer games > create problems
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4 create problems
v.crear problemas, causar problemas, crearse problemas, dar batalla. -
5 this eventually could create problems ...
• это в конечном счете могло бы вызвать проблемы...English-Russian dictionary of phrases and cliches for a specialist researcher > this eventually could create problems ...
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6 create
1. transitive verb1) schaffen; erschaffen (geh.); verursachen [Verwirrung]; machen [Eindruck]; [Sache:] mit sich bringen, [Person:] machen [Schwierigkeiten]2) (design) schaffen; kreieren [Mode, Stil]3) (invest with rank) ernennen2. intransitive verbcreate somebody a peer — jemanden zum Peer erheben od. ernennen
* * *[kri'eit]1) (to cause to exist; to make: How was the earth created?; The circus created great excitement.) (er-)schaffen•- academic.ru/17102/creation">creation- creative
- creatively
- creativeness
- creativity
- creator
- the Creator* * *cre·ate[kriˈeɪt]I. vt1. (make)who \created the world? wer hat die Welt erschaffen?2. (cause)▪ to \create sth etw erzeugen [o produzieren]unemployment \creates many social problems durch die Arbeitslosigkeit entstehen viele soziale Problemeto \create confusion Unruhe stiftento \create an impression einen Eindruck erweckento \create a precedent einen Präzedenzfall schaffento \create a sensation Aufsehen erregenhe was \createed first Earl of Cheshunt er wurde zum ersten Earl von Cheshunt ernannt* * *[kriː'eɪt]1. vt1) (= bring into existence) schaffen; new style, fashion also kreieren; the world, man erschaffen; draught, noise, fuss verursachen; difficulties machen; problems (person) schaffen; (action, event) verursachen, hervorbringen; impression machen; (COMPUT) file anlegen, erstellenpeers can only be created by the reigning monarch —
to create sb baron — jdn zum Baron erheben or ernennen
2. vi (Brit inf)Theater machen (inf)* * *create [kriːˈeıt; krı-] v/t1. (er)schaffen:2. schaffen, ins Leben rufen, hervorbringen, erzeugen:create jobs Arbeitsplätze schaffen3. einen Skandal etc hervorrufen, verursachen:create a demand einen Bedarf wecken;create an impression einen Eindruck machen;create an opportunity (a situation) eine Gelegenheit (eine Lage) schaffen;create a scoring chance SPORT eine Torchance herausspielen4. WIRTSCH, JURa) eine Gesellschaft gründen, errichten, ins Leben rufenb) eine Haftung etc begründenc) eine Hypothek bestellend) Geld, Kredit schöpfen5. THEAT etc, Mode: kreieren6. jemanden ernennen:7. jemanden erheben zu, machen zu:* * *1. transitive verb1) schaffen; erschaffen (geh.); verursachen [Verwirrung]; machen [Eindruck]; [Sache:] mit sich bringen, [Person:] machen [Schwierigkeiten]2) (design) schaffen; kreieren [Mode, Stil]3) (invest with rank) ernennen2. intransitive verbcreate somebody a peer — jemanden zum Peer erheben od. ernennen
* * *v.entwerfen v.erschaffen v.erstellen v.erzeugen v.hervorbringen v.kreieren v.schaffen v. -
7 create
cre·ate [kriʼeɪt] vt1) ( make)who \created the world? wer hat die Welt erschaffen?2) ( cause)to \create sth etw erzeugen [o produzieren];unemployment \creates many social problems durch die Arbeitslosigkeit entstehen viele soziale Probleme;to \create confusion Unruhe stiften;to \create an impression einen Eindruck erwecken;to \create a precedent einen Präzedenzfall schaffen;to \create a sensation Aufsehen erregen -
8 create no problems
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9 Leavitt’s Diamond
Gen Mgta model for analyzing management change, developed by Harold J. Leavitt. Leavitt’s Diamond is based on the idea that it is rare for any change to occur in isolation. Leavitt sees technology, tasks, people, and the organizational structure in which they function as four interdependent variables, visualized as the four points of a diamond. Change at any one point of the diamond will impact some or all of the others. Thus, a changed task will necessarily affect the people involved in it, the structure in which they work, and the technology that they use. Failure to manage these interdependencies at critical times of change can create problems. -
10 problem
n1) проблема; трудность2) задача3) вопрос•to add to a country's problems — увеличивать трудности, испытываемые страной
to address a problem — заниматься проблемой; браться за решение вопроса
to aggravate a problem — обострять / осложнять проблему
to appreciate the seriousness of the problem — осознавать / понимать серьезность проблемы
to bring up a problem — поднимать / ставить на обсуждение проблему
to compound the problems already facing smb — осложнять и без того трудные проблемы, стоящие перед кем-л.
to counteract a problem — принимать меры по какой-л. проблеме
to create a problem — создавать проблему / трудность
to deal successfully with problems — решать проблемы; успешно справляться с проблемами / с трудностями
to deal with a problem — подходить к вопросу; рассматривать проблему; справляться с трудностью
to deflect from one's internal problems — отвлекать внимание от своих внутренних проблем
to ease a problem — облегчать / упрощать решение проблемы
to get to grips with a problem — браться за решение проблемы / задачи
to handle a problem — решать проблему / задачу
to iron out a problem — урегулировать вопрос / проблему
to overcome a problem — разрешать проблему; преодолевать трудность
to put forward a problem — выдвигать / ставить проблему
to resolve a problem — решать задачу / проблему
to see eye to eye on a problem — иметь одинаковые взгляды по какому-л. вопросу
to solve a problem — решать / разрешать проблему
to tackle a problem — решать проблему; бороться за решение вопроса
- age-old problemto touch upon a problem — касаться проблемы; затрагивать проблему
- agrarian problem
- anticipated problem
- balance-of-payment problem
- basic problem
- border problem
- burning problem
- cardinal problem
- cash-flow problem
- chief problem
- common problem
- competitiveness problem
- complex problem
- complexity of a problem
- complicated problem
- comprehensive consideration of a problem
- conflict problem
- contentious problem
- controversial problem
- critical problem
- crucial problem
- cultural problem
- current problem
- daily problem
- dark problem
- debt problem
- deep problem
- deep-seated problem
- delicate problem
- difficult problem
- diplomatic problem
- disputable problem
- domestic problem
- drug problem
- easy ways out of economic problems
- economic problem
- education problem
- elaboration of economic problems
- employment problem
- endemic problem
- environmental problem
- ethnic problem
- farming problem
- financial liquidity problem
- financial problem
- focal problem
- food problem
- foreign debt problem
- formidable problem
- fuel and energy problem
- global problem
- grave problem
- growing problems
- hair-raising problem
- half-way solution of the problem
- hard core of a problem
- heart of the problem
- heavy problem
- high priority problem
- housing problem
- human problems
- human rights problem
- humanitarian problem
- immediate problem
- important problem
- inability to solve urgent problems
- incipient problems
- industrial problems
- infrastructure problem
- inherited problem
- insuperable problem
- insurmountable problem
- interconnected problems
- interdisciplinary problem
- interlinked problems
- internal problem
- international problem
- interrelated problems
- intractable problem
- intricate problem
- key part of the problem
- key problem
- kindred problem
- labor problems
- labor-shortage problem
- logistical problem
- long-standing problem
- long-term problem
- main problem
- major problem
- mammoth problem
- market problem
- massive problem
- minor problem
- monetary and financial problem
- nationalist problem
- nationality problem
- nation-wide problem
- number one problem
- outstanding problem
- painful problem
- pending problem
- perennial problem
- persistent problem
- personnel problem
- pivotal problem
- political problem
- pollution problem
- present-day problem
- pressing problem
- priority problem
- problem becomes more acute
- problem comes under scrutiny in most papers
- problem facing the country
- problem is compounded by smth
- problem of development
- problem of first priority
- problem of great concern for smb
- problem of instability
- problem of paramount importance
- problems demand the urgent attention of smb
- problems of mutual concern
- problems of peace, security and cooperation
- problems of the elderly
- problems of war and peace
- problems to be sorted out
- problems which face the world today
- range of problems
- regional problem
- related problem
- resolution of a problem
- root problem
- safety problem
- sale problem
- scientific problem
- sensitive problem
- serious problem
- settlement of a problem
- severe problem
- social problem
- socio-economic problem
- sociological problem
- solution of a problem
- solution to a problem
- solvable problem
- specific problem
- spectrum of problems
- stirring problem
- surmountable problem
- technical problem
- territorial problem
- Third World debt problem
- thorny problem
- topical problem
- touchy problem
- trading problem
- traditional problem
- transport problem
- universal problem
- unprecedented problem
- unresolved problem
- unsolved problem
- urgent problem
- vital problem
- world food problems
- world-wide problem -
11 problem
n1) проблема; вопрос2) проблема, затруднение3) задача
- allocation problem
- anticipated problems
- apparent problems
- assignment problem
- bottleneck problem
- budgetary problems
- cardinal problem
- classical transportation problem
- competition problem
- congestion problem
- cost minimizing problem
- current problem
- debt servicing problem
- decision problem
- development problems
- distribution problem
- econometric problem
- economic problem
- environmental problem
- estimation problem
- exchange control problem
- existing problem
- farm problems
- feasible problem
- financial problem
- financing problem
- fundamental problem
- global problem
- great problem
- housing problem
- immediate problem
- internal problem
- intractable problem
- inventory problem
- key problem
- long-standing problem
- major problem
- management problem
- marketing problem
- maximization problem
- minimization problem
- minor problem
- monetary and financial problem
- mutual problems
- optimization problem
- optimum problem
- original problem
- outstanding problem
- present-day problems
- pressing problem
- prevailing problem
- pricing problem
- production problem
- production control problem
- production setting problem
- product-mix problem
- programming problem
- replacement problem
- scheduling problem
- serious problem
- service problems
- servicing problems
- statistical problem
- stock-holding problem
- take-over problems
- technical problem
- transportation problem
- unforeseen problem
- unresolved problem
- unsettled problem
- unsolved problem
- urgent problem
- problems of common interest
- problem of pollution
- address problems
- alleviate a problem
- anticipate a problem
- assess a problem
- avoid problems
- bring up a problem
- cause a problem
- consider a problem
- cope with problems
- correct a problem
- create a problem
- deal with a problem
- eliminate a problem
- encounter a problem
- examine a problem
- experience a problem
- face a problem
- finalize a problem
- find a problem
- fix the problem
- foresee a problem
- get a problem off the ground
- give a problem
- handle a problem
- have a problem
- investigate a problem
- meet with a problem
- open a problem
- outline a problem
- overcome a problem
- prevent a problem
- put forward a problem
- raise a problem
- resolve a problem
- run into a problem
- simplify a problem
- solve a problem
- tackle a problemEnglish-russian dctionary of contemporary Economics > problem
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12 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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13 crear
crear ( conjugate crear) verbo transitivo to create; ‹ producto› to develop; ‹institución/comisión/fondo› to set up; ‹fama/prestigio› to bring; ‹ reputación› to earn;◊ crea muchos problemas it causes o creates a lot of problems;no quiero crear falsas expectativas I don't want to raise false hopes crearse verbo pronominal ‹ problema› to create … for oneself; ‹ enemigos› to make
crear verbo transitivo to create ' crear' also found in these entries: Spanish: falsificar - hacer - ilusionar - infundio - rompecabezas - constituir - formar - meter English: boat - bonding - create - fashion - never-never land - rapport - stage - afoot - develop - devise - disrupt - establish - illusion - set - you -
14 Bibliography
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Cambridge: Cambridge University Press.Historical dictionary of quotations in cognitive science > Bibliography
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15 Consciousness
Consciousness is what makes the mind-body problem really intractable.... Without consciousness the mind-body problem would be much less interesting. With consciousness it seems hopeless. (T. Nagel, 1979, pp. 165-166)This approach to understanding sensory qualia is both theoretically and empirically motivated... [;] it suggests an effective means of expressing the allegedly inexpressible. The "ineffable" pink of one's current visual sensation may be richly and precisely expressed as a 95Hz/80Hz/80Hz "chord" in the relevant triune cortical system. The "unconveyable" taste sensation produced by the fabled Australian health tonic Vegamite might be poignantly conveyed as a 85/80/90/15 "chord" in one's four channeled gustatory system.... And the "indescribably" olfactory sensation produced by a newly opened rose might be quite accurately described as a 95/35/10/80/60/55 "chord" in some six-dimensional space within one's olfactory bulb. (P. M. Churchland, 1989, p. 106)One of philosophy's favorite facets of mentality has received scant attention from cognitive psychologists, and that is consciousness itself: fullblown, introspective, inner-world phenomenological consciousness. In fact if one looks in the obvious places... one finds not so much a lack of interest as a deliberate and adroit avoidance of the issue. I think I know why. Consciousness appears to be the last bastion of occult properties, epiphenomena, and immeasurable subjective states-in short, the one area of mind best left to the philosophers, who are welcome to it. Let them make fools of themselves trying to corral the quicksilver of "phenomenology" into a respectable theory. (Dennett, 1978b, p. 149)When I am thinking about anything, my consciousness consists of a number of ideas.... But every idea can be resolved into elements... and these elements are sensations. (Titchener, 1910, p. 33)A Darwin machine now provides a framework for thinking about thought, indeed one that may be a reasonable first approximation to the actual brain machinery underlying thought. An intracerebral Darwin Machine need not try out one sequence at a time against memory; it may be able to try out dozens, if not hundreds, simultaneously, shape up new generations in milliseconds, and thus initiate insightful actions without overt trial and error. This massively parallel selection among stochastic sequences is more analogous to the ways of darwinian biology than to the "von Neumann" serial computer. Which is why I call it a Darwin Machine instead; it shapes up thoughts in milliseconds rather than millennia, and uses innocuous remembered environments rather than noxious real-life ones. It may well create the uniquely human aspect of our consciousness. (Calvin, 1990, pp. 261-262)To suppose the mind to exist in two different states, in the same moment, is a manifest absurdity. To the whole series of states of the mind, then, whatever the individual, momentary successive states may be, I give the name of our consciousness.... There are not sensations, thoughts, passions, and also consciousness, any more than there is quadruped or animal, as a separate being to be added to the wolves, tygers, elephants, and other living creatures.... The fallacy of conceiving consciousness to be something different from the feeling, which is said to be its object, has arisen, in a great measure, from the use of the personal pronoun I. (T. Brown, 1970, p. 336)The human capacity for speech is certainly unique. But the gulf between it and the behavior of animals no longer seems unbridgeable.... What does this leave us with, then, which is characteristically human?.... t resides in the human capacity for consciousness and self-consciousness. (Rose, 1976, p. 177)[Human consciousness] depends wholly on our seeing the outside world in such categories. And the problems of consciousness arise from putting reconstitution beside internalization, from our also being able to see ourselves as if we were objects in the outside world. That is in the very nature of language; it is impossible to have a symbolic system without it.... The Cartesian dualism between mind and body arises directly from this, and so do all the famous paradoxes, both in mathematics and in linguistics.... (Bronowski, 1978, pp. 38-39)It seems to me that there are at least four different viewpoints-or extremes of viewpoint-that one may reasonably hold on the matter [of computation and conscious thinking]:A. All thinking is computation; in particular, feelings of conscious awareness are evoked merely by the carrying out of appropriate computations.B. Awareness is a feature of the brain's physical action; and whereas any physical action can be simulated computationally, computational simulation cannot by itself evoke awareness.C. Appropriate physical action of the brain evokes awareness, but this physical action cannot even be properly simulated computationally.D. Awareness cannot be explained by physical, computational, or any other scientific terms. (Penrose, 1994, p. 12)Historical dictionary of quotations in cognitive science > Consciousness
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16 Thinking
But what then am I? A thing which thinks. What is a thing which thinks? It is a thing which doubts, understands, [conceives], affirms, denies, wills, refuses, which also imagines and feels. (Descartes, 1951, p. 153)I have been trying in all this to remove the temptation to think that there "must be" a mental process of thinking, hoping, wishing, believing, etc., independent of the process of expressing a thought, a hope, a wish, etc.... If we scrutinize the usages which we make of "thinking," "meaning," "wishing," etc., going through this process rids us of the temptation to look for a peculiar act of thinking, independent of the act of expressing our thoughts, and stowed away in some particular medium. (Wittgenstein, 1958, pp. 41-43)Analyse the proofs employed by the subject. If they do not go beyond observation of empirical correspondences, they can be fully explained in terms of concrete operations, and nothing would warrant our assuming that more complex thought mechanisms are operating. If, on the other hand, the subject interprets a given correspondence as the result of any one of several possible combinations, and this leads him to verify his hypotheses by observing their consequences, we know that propositional operations are involved. (Inhelder & Piaget, 1958, p. 279)In every age, philosophical thinking exploits some dominant concepts and makes its greatest headway in solving problems conceived in terms of them. The seventeenth- and eighteenth-century philosophers construed knowledge, knower, and known in terms of sense data and their association. Descartes' self-examination gave classical psychology the mind and its contents as a starting point. Locke set up sensory immediacy as the new criterion of the real... Hobbes provided the genetic method of building up complex ideas from simple ones... and, in another quarter, still true to the Hobbesian method, Pavlov built intellect out of conditioned reflexes and Loeb built life out of tropisms. (S. Langer, 1962, p. 54)Experiments on deductive reasoning show that subjects are influenced sufficiently by their experience for their reasoning to differ from that described by a purely deductive system, whilst experiments on inductive reasoning lead to the view that an understanding of the strategies used by adult subjects in attaining concepts involves reference to higher-order concepts of a logical and deductive nature. (Bolton, 1972, p. 154)There are now machines in the world that think, that learn and create. Moreover, their ability to do these things is going to increase rapidly until-in the visible future-the range of problems they can handle will be coextensive with the range to which the human mind has been applied. (Newell & Simon, quoted in Weizenbaum, 1976, p. 138)But how does it happen that thinking is sometimes accompanied by action and sometimes not, sometimes by motion, and sometimes not? It looks as if almost the same thing happens as in the case of reasoning and making inferences about unchanging objects. But in that case the end is a speculative proposition... whereas here the conclusion which results from the two premises is an action.... I need covering; a cloak is a covering. I need a cloak. What I need, I have to make; I need a cloak. I have to make a cloak. And the conclusion, the "I have to make a cloak," is an action. (Nussbaum, 1978, p. 40)It is well to remember that when philosophy emerged in Greece in the sixth century, B.C., it did not burst suddenly out of the Mediterranean blue. The development of societies of reasoning creatures-what we call civilization-had been a process to be measured not in thousands but in millions of years. Human beings became civilized as they became reasonable, and for an animal to begin to reason and to learn how to improve its reasoning is a long, slow process. So thinking had been going on for ages before Greece-slowly improving itself, uncovering the pitfalls to be avoided by forethought, endeavoring to weigh alternative sets of consequences intellectually. What happened in the sixth century, B.C., is that thinking turned round on itself; people began to think about thinking, and the momentous event, the culmination of the long process to that point, was in fact the birth of philosophy. (Lipman, Sharp & Oscanyan, 1980, p. xi)The way to look at thought is not to assume that there is a parallel thread of correlated affects or internal experiences that go with it in some regular way. It's not of course that people don't have internal experiences, of course they do; but that when you ask what is the state of mind of someone, say while he or she is performing a ritual, it's hard to believe that such experiences are the same for all people involved.... The thinking, and indeed the feeling in an odd sort of way, is really going on in public. They are really saying what they're saying, doing what they're doing, meaning what they're meaning. Thought is, in great part anyway, a public activity. (Geertz, quoted in J. Miller, 1983, pp. 202-203)Everything should be made as simple as possible, but not simpler. (Einstein, quoted in Minsky, 1986, p. 17)What, in effect, are the conditions for the construction of formal thought? The child must not only apply operations to objects-in other words, mentally execute possible actions on them-he must also "reflect" those operations in the absence of the objects which are replaced by pure propositions. Thus, "reflection" is thought raised to the second power. Concrete thinking is the representation of a possible action, and formal thinking is the representation of a representation of possible action.... It is not surprising, therefore, that the system of concrete operations must be completed during the last years of childhood before it can be "reflected" by formal operations. In terms of their function, formal operations do not differ from concrete operations except that they are applied to hypotheses or propositions [whose logic is] an abstract translation of the system of "inference" that governs concrete operations. (Piaget, quoted in Minsky, 1986, p. 237)[E]ven a human being today (hence, a fortiori, a remote ancestor of contemporary human beings) cannot easily or ordinarily maintain uninterrupted attention on a single problem for more than a few tens of seconds. Yet we work on problems that require vastly more time. The way we do that (as we can observe by watching ourselves) requires periods of mulling to be followed by periods of recapitulation, describing to ourselves what seems to have gone on during the mulling, leading to whatever intermediate results we have reached. This has an obvious function: namely, by rehearsing these interim results... we commit them to memory, for the immediate contents of the stream of consciousness are very quickly lost unless rehearsed.... Given language, we can describe to ourselves what seemed to occur during the mulling that led to a judgment, produce a rehearsable version of the reaching-a-judgment process, and commit that to long-term memory by in fact rehearsing it. (Margolis, 1987, p. 60)Historical dictionary of quotations in cognitive science > Thinking
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17 load
ləud
1. noun1) (something which is being carried: The lorry had to stop because its load had fallen off; She was carrying a load of groceries.) carga2) (as much as can be carried at one time: two lorry-loads of earth.) peso, cantidad3) (a large amount: He talked a load of rubbish; We ate loads of ice-cream.) montones de, montón de4) (the power carried by an electric circuit: The wires were designed for a load of 15 amps.) carga
2. verb1) (to take or put on what is to be carried (especially if heavy): They loaded the luggage into the car; The lorry was loading when they arrived.) cargar2) (to put ammunition into (a gun): He loaded the revolver and fired.) cargar3) (to put film into (a camera).) cargar•- loadedload1 n cargaload2 vb cargartr[ləʊd]1 (in general) carga2 (weight) peso1 cargar ( with, de)1 cargar\SMALLIDIOMATIC EXPRESSION/SMALLa load of... / loads of... familiar montones de..., un montón de...get a load of this! familiar ¡fíjate en esto!, ¡mira esto!load ['lo:d] vt: cargar, embarcarload n1) cargo: carga f2) weight: peso m3) burden: carga f, peso m4) loads npl: montón m, pila f, cantidad floads of work: un montón de trabajon.• carga s.f.• cargamento s.m.• cargazón s.m.• cargo s.m.• carguío s.m.• munición s.f.• peso s.m.• tiro s.m.v.• agobiar v.• armar v.• cargar v.• colmar v.• fletar v.• recargar v.ləʊd
I
four loads of washing — cuatro lavados or (Esp) coladas
the project will create a heavy administrative load — el proyecto generará mucho trabajo administrativo
to have a load on — (AmE colloq) estar* como una cuba (fam), estar* tomado (AmL fam)
2) (often pl) (colloq)a) (much, many) cantidad f, montón m (fam), pila f (AmS fam)I've done this loads of times — esto lo he hecho cantidad or montones or (AmS tb) pilas de veces (fam)
the play is a load of rubbish — la obra no vale nada or (fam) es una porquería
b) (as intensifier) (colloq)3) ( Civil Eng) carga fmaximum load 15 tons — peso máximo: 15 toneladas
II
1.
a) ( Transp) \<\<truck/plane\>\> cargar*b) ( charge) \<\<gun\>\> cargar*to load a program (into a computer) — cargar* un programa (en una computadora)
2.
vi cargar*Phrasal Verbs:- load up[lǝʊd]1. N1) (=cargo) carga f ; (=weight) peso mI put another load in the washing machine — puse otra colada a lavar or en la lavadora
shed Imaximum load: 17 tons — carga máxima: 17 toneladas
2) (fig) (=burden) carga fhe finds his new responsibilities a heavy load — sus nuevas responsabilidades le resultan una gran carga
she's taking some of the load off the secretaries — está aligerándoles la carga de trabajo a las secretarias
caseload, workloadthat's (taken) a load off my mind! — ¡eso me quita un peso de encima!
3) (Elec, Tech) (also of firearm) carga f4) loads * cantidad * f, un montón *we've got loads of time — tenemos cantidad or un montón de tiempo *
I've got loads (of them) at home — tengo cantidad or un montón en casa *
5)a load of >: the book is a load of rubbish * — el libro es una basura *, el libro no vale nada
they're just a load of kids — no son más que un hatajo or una panda de críos *
get a load of this! — (=look) ¡échale un vistazo a esto! *, ¡mírame esto!; (=listen) ¡escucha esto!
2. VT1) [+ lorry, washing machine, gun, camera] cargardo you know how to load this program? — (Comput) ¿sabes cómo cargar este programa?
2) (=weigh down)•
to be loaded with sth, we're loaded with debts — estamos cargados or agobiados de deudasher words were loaded with meaning — sus palabras estaban llenas or cargadas de significado
3) (=bias)•
the dice were loaded — los dados estaban cargadosthe dice are loaded against him — (fig) todo está en su contra
•
the situation is loaded in our favour — la situación se inclina a nuestro favor3. VI1) [lorry, ship] cargar2) [gun, camera] cargarsehow does this gun/camera load? — ¿cómo se carga esta pistola/cámara?
3) [person] cargarload! — ¡carguen armas!
4.CPDload factor N — (Elec, Aer) factor m de carga
load line N — (Naut) línea f de carga
- load up* * *[ləʊd]
I
four loads of washing — cuatro lavados or (Esp) coladas
the project will create a heavy administrative load — el proyecto generará mucho trabajo administrativo
to have a load on — (AmE colloq) estar* como una cuba (fam), estar* tomado (AmL fam)
2) (often pl) (colloq)a) (much, many) cantidad f, montón m (fam), pila f (AmS fam)I've done this loads of times — esto lo he hecho cantidad or montones or (AmS tb) pilas de veces (fam)
the play is a load of rubbish — la obra no vale nada or (fam) es una porquería
b) (as intensifier) (colloq)3) ( Civil Eng) carga fmaximum load 15 tons — peso máximo: 15 toneladas
II
1.
a) ( Transp) \<\<truck/plane\>\> cargar*b) ( charge) \<\<gun\>\> cargar*to load a program (into a computer) — cargar* un programa (en una computadora)
2.
vi cargar*Phrasal Verbs:- load up -
18 variety
[və'raɪətɪ]n1) разнообразие, различие, несходство, отличиеThere is no great variety in the manner of doing it. — В том, как это делается, нет большого разнообразия.
There is variety in everything she does. — Во всем, что она делает, есть разнообразие.
There is great variety in approaches to the problem. — Подходы к этой проблеме весьма разнообразны.
The device has a variety of uses. — Прибор имеет много применений.
- great variety of goods- great variety of books
- rare variety of stamps
- varieties of fortune
- variety in food
- variety of shapes
- variety of talk
- wide variety of problems
- flowers in great variety
- life full of variety
- for a variety of reasons
- try a variety of occupations
- create a variety of portraits
- look through a variety of newspapers
- give a beautiful variety to the landscape
- create variety
- lack variety
- life in the country lackes variety2) сорт- rare variety of wheat- every variety of tulips
- most common variety of cars
- produce a new variety of apple3) эстрада•USAGE:Существительное variety 1. в конструкции variety 1. of + существительное во множественном числе согласуется с формой множественного числа глагола: A great/wide variety of opinions (approaches, reasons) were expressed. Были выражены разные мнения (подходы, причины). -
19 make
A n ( brand) marque f ; what make is your car? de quelle marque est ta voiture? ; what make of computer is it? quelle est la marque de cet ordinateur?1 ( create) faire [dress, cake, coffee, stain, hole, will, pact, film, sketch, noise] ; to make the bed faire le lit ; to make a rule établir une règle ; to make the law faire or édicter fml les lois ; to make sth from faire qch avec ; wine is made from grapes le vin se fait avec du raisin ; to make sth for sb, to make sb sth faire qch pour qn ; to be made for sb être fait pour qn ; to be made for each other être fait l'un pour l'autre ; to make room/the time for sth trouver de la place/du temps pour qch ; to make sth out of faire qch en ; what is it made (out) of? en quoi est-ce fait? ; it's made (out) of gold c'est en or ; to see what sb is made of voir de quoi est fait qn ; let's see what he's made of voyons de quoi il est fait ; show them what you're made of! montre-leur de quel bois tu te chauffes ○ ! ; to be as clever as they make them être malin comme pas un ○ ; to make A into B faire B à partir de A ; to make fruit into jam faire de la confiture à partir des fruits ; to make a house into apartments transformer une maison en appartements ; made in France/by Macron fabriqué en France/par Macron ; God made man Dieu a créé l'homme ;2 (cause to be or become, render) se faire [friends, enemies] ; to make sb happy/jealous/popular rendre qn heureux/jaloux/populaire ; to make sb hungry/thirsty donner faim/soif à qn ; to make oneself available/ill se rendre disponible/malade ; to make oneself heard/understood se faire entendre/comprendre ; to make sth bigger agrandir qch ; to make sth better améliorer qch ; to make sth worse aggraver qch [problem, situation] ; to make sb's cold better soulager le rhume de qn ; to make exams easier, to make passing exams easier, to make it easier to pass exams faciliter les examens ; to make it easy/possible to do [person] faire en sorte qu'il soit facile/possible de faire ; that made it easy for me to leave cela a facilité mon départ ;3 ( cause to do) to make sb cry/jump/think faire pleurer/sursauter/réfléchir qn ; I made her smile je l'ai fait sourire ; to make sb do sth faire faire qch à qn ; I made her forget her problems/lose patience je lui ai fait oublier ses problèmes/perdre patience ; it makes me look fat/old ça me grossit/vieillit ; it makes me look ill ça me donne l'air malade ; to make sth do faire que qch fasse ; to make sth happen faire que qch se produise ; to make the story end happily faire en sorte que l'histoire se termine bien ; to make sth work [person] réussir à faire marcher qch [machine etc] ; to make sth grow/burn [person] réussir à faire pousser/brûler qch ; [chemical, product] faire pousser/brûler qch ; it makes your face look rounder ça fait paraître ton visage plus rond ; it makes her voice sound funny cela lui donne une drôle de voix ;4 (force, compel) to make sb do obliger qn à faire ; they made me (do it) ils m'ont obligé, ils m'ont forcé, ils m'y ont forcé ; to be made to do être obligé or forcé de faire ; he must be made to cooperate il faut qu'il coopère ; to make sb wait/talk faire attendre/parler qn ;5 ( turn into) to make sb sth, to make sth of sb faire de qn qch ; it's been made into a film on en a fait or tiré un film ; to make sb a star faire de qn une vedette ; we made him treasurer on l'a fait trésorier ; we made Tom treasurer on a choisi Tom comme trésorier ; to be made president for life être fait président à vie ; to make sb one's assistant faire de qn son adjoint ; to make a soldier/a monster of sb faire de qn un soldat/un monstre ; it'll make a man of you hum ça fera de toi un homme ; he'll never make a teacher il ne fera jamais un bon professeur ; she'll make a good politician elle fera une fine politicienne ; to make sb a good husband être un bon mari pour qn ; to make sth sth, to make sth of sth faire de qch qch ; to make a habit/a success/ an issue of sth faire de qch une habitude/une réussite/une affaire ; do you want to make something of it? ( threatening) tu veux vraiment qu'on en discute? ; to make too much of sth faire tout un plat de qch ○ ; that will make a good shelter/a good tablecloth cela fera un bon abri/une bonne nappe ;6 (add up to, amount to) faire ; three and three make six trois et trois font six ; how much does that make? ça fait combien? ; that makes ten altogether ça fait dix en tout ; that makes five times he's called ça fait cinq fois qu'il appelle ;7 ( earn) gagner [salary, amount] ; to make £300 a week gagner 300 livres sterling par semaine ; he makes more in a week than I make in a month il gagne plus en une semaine que je ne gagne en un mois ; how much ou what do you think she makes? combien crois-tu qu'elle gagne? ; to make a living gagner sa vie ; to make a profit réaliser des bénéfices ; to make a loss subir des pertes ;8 (reach, achieve) arriver jusqu'à [place, position] ; atteindre [ranking, level] ; faire [speed, distance] ; to make the camp before dark arriver au or atteindre le camp avant la nuit ; to make the six o'clock train attraper le train de six heures ; we'll never make it nous n'y arriverons jamais ; to make the first team entrer dans la première équipe ; to make the charts entrer au hit-parade ; to make the front page of faire la une ○ de [newspaper] ; to make six spades ( in bridge) faire six piques ; to make 295 ( in cricket) faire or marquer 295 ;9 (estimate, say) I make it about 30 kilometres je dirais 30 kilomètres environ ; I make the profit £50 les bénéfices doivent s'élever à 50 livres sterling ; I make it five o'clock il est cinq heures à ma montre ; what time do you make it? quelle heure as-tu? ; what do you make the distance (to be)? quelle est la distance à ton avis? ; let's make it six o'clock/five dollars disons six heures/cinq dollars ; can we make it a bit later? peut-on dire un peu plus tard? ; what do you make of it? qu'en dis-tu? ; what does she make of him? qu'est-ce qu'elle pense or dit de lui? ; I don't know what to make of it je ne sais quoi en penser ; I can't make anything of it je n'y comprends rien ;10 ( cause success of) assurer la réussite de [holiday, day] ; a good wine can make a meal un bon vin peut assurer la réussite d'un repas ; it really makes the room [feature, colour] ça rend bien ; that interview made her career as a journalist cette interview lui a permis de faire carrière dans le journalisme ; it really made my day ça m'a rendu heureux pour la journée ; ‘go ahead, make my day!’ iron ‘allez, vas-y!’ ; to make or break sb/sth décider de l'avenir de qn/qch ;11 ○ ( have sex with) se faire ◑ [woman] ;13 Elec fermer [circuit] ;1 ( act) to make as if to do faire comme si on allait faire ; she made as if to kiss him elle a fait comme si elle allait l'embrasser ; he made like ○ he was injured il a fait semblant d'être blessé ;3 ( shuffle cards) battre.to be on the make ○ ( for profit) avoir les dents longues ; ( for sex) être en chasse ○ ; to make it ○ (in career, life) y arriver ; (to party, meeting) réussir à venir ; ( be on time for train etc) y être ; ( have sex) s'envoyer en l'air ○ (with avec) ; I'm afraid I can't make it malheureusement je ne peux pas y aller ; if they don't make it by 10pm s'ils n'arrivent pas avant 10h.■ make after:▶ make after [sb] poursuivre.■ make at:▶ make at [sb] attaquer (with avec).■ make away with = make off.■ make do:▶ make do faire avec ; to make do with se contenter de qch ;▶ make [sth] do se contenter de.■ make for:▶ make for [sth]1 ( head for) se diriger vers [door, town, home] ;2 ( help create) permettre, assurer [easy life, happy marriage] ;▶ make for [sb]1 ( attack) se jeter sur ;2 ( approach) se diriger vers.■ make good:▶ make good réussir ; a poor boy made good un garçon pauvre qui a réussi ;▶ make good [sth]1 ( make up for) réparer [damage, omission, loss] ; rattraper [lost time] ; combler [deficit, shortfall] ;2 ( keep) tenir [promise].■ make off filer ○ ; to make off across the fields/towards the town s'enfuir à travers les champs/vers la ville ; to make off with sth/sb se tirer ○ avec qch/qn.■ make out:▶ make out1 ( manage) s'en tirer ○ ; how are you making out? comment ça marche ○ ? ;2 US ( grope) se peloter ○ ;3 ( claim) affirmer (that que) ; he's not as stupid as he makes out il n'est pas aussi bête qu'il (le) prétend ;▶ make out [sth], make [sth] out1 (see, distinguish) distinguer [shape, writing] ;2 ( claim) to make sth out to be prétendre que qch est ;3 (understand, work out) comprendre [puzzle, mystery, character] ; to make out if or whether comprendre si ; I can't make him out je n'arrive pas à le comprendre ;4 ( write out) faire, rédiger [cheque, will, list] ; to make out a cheque GB ou check US to sb faire un chèque à qn, signer un chèque à l'ordre de qn ; it is made out to X il est à l'ordre de X ; who shall I make the cheque out to? à quel ordre dois-je faire le chèque? ;5 ( expound) to make out a case for sth argumenter en faveur de qch ;▶ make oneself out to be prétendre être [rich, brilliant] ; faire semblant d'être [stupid, incompetent].■ make over:▶ make over [sth], make [sth] over1 ( transform) transformer [building, appearance] (into en) ;2 ( transfer) céder [property] (to à).■ make towards:▶ make towards [sth/sb] se diriger vers.■ make up:▶ make up1 ( put make-up on) to make oneself up se maquiller ;2 ( after quarrel) se réconcilier (with avec) ;3 to make up for ( compensate for) rattraper [lost time, lost sleep, missed meal, delay] ; combler [financial loss, deficit] ; compenser [personal loss, bereavement] ;4 to make up to ○ faire de la lèche à ○ [boss, person] ;▶ make up [sth], make [sth] up1 ( invent) inventer [excuse, story] ; you're making it up! tu inventes! ; to make sth up as one goes along inventer qch au fur et à mesure ;2 ( prepare) faire [parcel, bundle, garment, road surface, bed] ; préparer [prescription] ; composer [type] ; she had the fabric made up into a jacket elle s'est fait faire une veste avec le tissu ;3 ( constitute) faire [whole, personality, society] ; to be made up of être fait or composé de ; to make up 10% of constituer 10% de ;4 ( compensate for) rattraper [loss, time] ; combler [deficit, shortfall] ; to make the total up to £1,000 compléter la somme pour faire 1 000 livres au total ;5 ( put make-up on) maquiller [person, face, eyes] ;6 ( stoke up) alimenter, s'occuper de [fire] ;7 to make it up ( make friends) se réconcilier (with avec) ; I'll make it up to you somehow ( when at fault) j'essaierai de me faire pardonner ; ( when not at fault) je vais trouver quelque chose pour compenser.■ make with ○:▶ make it with [sb] se faire ◑. -
20 Nervi, Pier Luigi
[br]b. 21 June 1891 Sondrio, Italyd. 9 January 1979 (?), Italy[br]Italian engineer who played a vital role in the use and adaptation of reinforced concrete as a structural material from the 1930s to the 1970s.[br]Nervi early established a reputation in the use of reinforced concrete with his stadium in Florence (1930–2). This elegant concrete structure combines graceful curves with functional solidity and is capable of seating some 35,000 spectators. The stadium was followed by the aircraft hangars built for the Italian Air Force at Orvieto and Ortebello, in which he spanned the vast roofs of the hangars with thin-shelled vaults supported by precast concrete beams and steel-reinforced ribs. The structural strength and subtle curves of these ribbed roofs set the pattern for Nervi's techniques, which he subsequently varied and elaborated on to solve problems that arose in further commissions.Immediately after the Second World War Italy was short of supplies of steel for structural purposes so, in contrast to the USA, Britain and Germany, did not for some years construct any quantity of steel-framed rectangular buildinngs used for offices, housing or industrial use. It was Nervi who led the way to a ferroconcrete approach, using a new type of structure based on these materials in the form of a fine steel mesh sprayed with cement mortar and used to roof all kinds of structures. It was a method that resulted in expressionist curves instead of rectangular blocks, and the first of his great exhibition halls at Turin (1949), with a vault span of 240 ft (73 m), was an early example of this technique. Nervi continued to create original and beautiful ferroconcrete structures of infinite variety: for example, the hall at the Lido di Roma, Ostia; the terme at Chianciano; and the three buildings that he designed for the Rome Olympics in 1960. The Palazzetto dello Sport is probably the most famous of these, for which he co-operated with the architect Annibale Vitellozzi to construct a small sports palace seating 5,000 spectators under a concrete "big top" of 194 ft (59 m) diameter, its enclosing walls supported by thirtysix guy ropes of concrete; inside, the elegant roof displays a floral quality. In 1960 Nervi returned to Turin to build his imaginative Palace of Labour for the centenary celebrations of Garibaldi and Victor Emmanuel in the city. This vast hall, like the Crystal Palace in England a century earlier (see Paxton), had to be built quickly and be suitable for later adaptation. It was therefore constructed partly in steel, and the metal supporting columns rose to palm-leaf capitals reminiscent of those in ancient Nile palaces.Nervi's aim was always to create functional buildings that simultaneously act by their aesthetic qualities as an effective educational influence. Functionalism for Nervi never became "brutalism". In consequence, his work is admired by the lay public as well as by architects. He collaborated with many of the outstanding architects of the day: with Gio Ponti on the Pirelli Building in Milan (1955–9); with Zehrfuss and Breuer on the Y-plan UNESCO Building in Paris (1953–7); and with Marcello Piacentini on the 16,000-seat Palazzo dello Sport in Rome. Nervi found time to write a number of books on building construction and design, lectured in the Universities of Rio de Janiero and Buenos Aires, and was for many years Professor of Technology and Technique of Construction in the Faculty of Architecture at the University of Rome. He continued to design new structures until well into the 1970s.[br]Principal Honours and DistinctionsRIBA Royal Gold Medal 1960. Royal Institute of Structural Engineers Gold Medal 1968. Honorary Degree Edinburgh University, Warsaw University, Munich University, London University, Harvard University. Member International Institute of Arts and Letters, Zurich; American Academy of Arts and Sciences; Royal Academy of Fine Arts, Stockholm.Bibliography1956, Structures, New York: Dodge.1945, Scienza o Arte del Costruire?, Rome: Bussola.Further ReadingP.Desideri et al., 1979, Pier Luigi Nervi, Bologna: Zanichelli.A.L.Huxtable, 1960, Masters of World Architecture; Pier Luigi Nervi, New York: Braziller.DY
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