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1 Roe, Sir Edwin Alliott Verdon
SUBJECT AREA: Aerospace[br]b. 26 April 1877 Manchester, Englandd. 4 January 1958 London, England[br]English designer of one of the most successful biplanes of all time, the Avro 504.[br]A.V.Roe served an apprenticeship at a railway works, studied marine engineering at Kings College London, served at sea as an engineer, and then took a job in the motor-car industry. His hobby was flying: after studying bird-flight, he built several flying models and in 1907 one of these won a prize offered by the Daily Mail. With the prize money he built a full-size aeroplane loosely based on the Flyer of the Wright brothers, with whom he had corresponded. In September, Roe took his biplane to the motorracing circuit at Brooklands, in Surrey, but it made only a few hops and his activities were not welcomed. Roe then moved to Essex, where he assembled his new aeroplane under the arch of a railway bridge. This was a triplane design with the engine at the front (a "tractor"), and during 1909 it made several flights (this triplane is preserved by the Science Museum in London).In 1910 Roe and his brother Humphrey founded A.V.Roe \& Co. in Manchester, they described it the "Aviator's Storehouse". During the next three years Roe designed and built aeroplanes in Manchester, then transported them to Brooklands to fly (the authorities now made him more welcome). One of the most significant of these was his Type D tractor biplane of 1911, which led to the Avro 504 two-seater trainer of 1913. This was one of the most successful trainers of all time, as around 10,000 were built. In November 1914 a flight of Avro 504s carried out the first-ever bombing raid when they attacked German airship sheds as Friedrichshafen. A.V.Roe produced the first aeroplanes with enclosed cabins during 1912: the Type F monoplane and Type G biplane. After the war, his Avian was used for several record-breaking flights. In 1928 he sold his interest in the company bearing his name and joined forces with Saunders Ltd of Cowes, on the Isle of Wight, to found Saunders-Roe Ltd. "Saro" produced a series of flying boats, from the four-seat Cutty Sark of 1929 to the large, and ill-fated, Princess of 1952.[br]Principal Honours and DistinctionsKnighted 1929 (in 1933 he incorporated his mother's name to become Sir Alliott VerdonRoe). Honorary Fellow of the Royal Aeronautical Society 1948.Bibliography1939, The World of Wings and Things, London.Further ReadingL.J.Ludovic, 1956, the Challenging Sky.A.J.Jackson, 1908, Avro Aircraft since 1908, London (a detailed account).JDSBiographical history of technology > Roe, Sir Edwin Alliott Verdon
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2 precipitarse
1 (apresurarse) to rush, be hasty2 (caer) to fall; (arrojarse) to throw os* * *verb1) to rush2) rash* * *VPR1) (=arrojarse) to throw o.s., hurl o.s. ( desde from)precipitarse sobre algo — [pájaro] to swoop down on sth; [animal] to pounce on sth
precipitarse sobre algn — to throw o hurl o.s. on sb
2) (=correr) to rush, dash3) (=actuar sin reflexión) to act hastilyse ha precipitado rehusándolo — he acted hastily in rejecting it, it was rash of him to refuse it
* * *(v.) = plunge into, rush ahead, plunge into, gallop, rush, fall off, career, jump + the gun, careen, stampedeEx. Preliminary decisions must be taken before plunging into the accumulation of index terms, and analysis of relationships.Ex. Rather readers grow by fits and starts now rushing ahead, now lying fallow, and now moving steadily on.Ex. For the beginner, the intention has been to offer an immediate plunge into the world of reference work, though necessarily at one remove from the actual user with his real problems.Ex. We must ensure that IFLA is positioned to represent the world wide library and information profession as we gallop towards the information society = Debemos asegurarnos de que la IFLA pueda representar a la profesión de bibliotecario y documentalista de todo el mundo conforme nos precipitamos hacia la sociedad de la información.Ex. The computer can be a great boon to cataloging, but I don't think that we should rush at it in an overly simplistic way.Ex. The article has the title 'Bringing the mountain to Mohammed without falling off the cliff of unmanageable technology'.Ex. Juxtaposing harrowing scenes of a family in grief with high comedy, this film does not so much tread a delicate line between these two modes as career wildly between them like a drunken mourner.Ex. Because of EU tardiness, some countries, namely France, Holland and the UK, have jumped the gun in introducing aid for the pig sector in contravention of EU regulations.Ex. The jet ultimately shot up fully vertically -- at which point the wings snapped off and the whole works careened down into the ocean.Ex. The noise spooked the animals, and many stampeded over a cliff to their deaths.* * *(v.) = plunge into, rush ahead, plunge into, gallop, rush, fall off, career, jump + the gun, careen, stampedeEx: Preliminary decisions must be taken before plunging into the accumulation of index terms, and analysis of relationships.
Ex: Rather readers grow by fits and starts now rushing ahead, now lying fallow, and now moving steadily on.Ex: For the beginner, the intention has been to offer an immediate plunge into the world of reference work, though necessarily at one remove from the actual user with his real problems.Ex: We must ensure that IFLA is positioned to represent the world wide library and information profession as we gallop towards the information society = Debemos asegurarnos de que la IFLA pueda representar a la profesión de bibliotecario y documentalista de todo el mundo conforme nos precipitamos hacia la sociedad de la información.Ex: The computer can be a great boon to cataloging, but I don't think that we should rush at it in an overly simplistic way.Ex: The article has the title 'Bringing the mountain to Mohammed without falling off the cliff of unmanageable technology'.Ex: Juxtaposing harrowing scenes of a family in grief with high comedy, this film does not so much tread a delicate line between these two modes as career wildly between them like a drunken mourner.Ex: Because of EU tardiness, some countries, namely France, Holland and the UK, have jumped the gun in introducing aid for the pig sector in contravention of EU regulations.Ex: The jet ultimately shot up fully vertically -- at which point the wings snapped off and the whole works careened down into the ocean.Ex: The noise spooked the animals, and many stampeded over a cliff to their deaths.* * *
precipitarse ( conjugate precipitarse) verbo pronominal
1 (en decisión, juicio) to be hasty;
2 ( apresurarse) to rush;
precipitarsese A hacer algo to rush to do sth
3
■precipitarse verbo reflexivo
1 (con prisa) to hurry
2 (sin pensar) to rush
3 (en una caída) to plunge, hurl oneself: el autobús se precipitó al vacío, the bus plunged into the void
' precipitarse' also found in these entries:
Spanish:
embalarse
- atarantar
- atolondrar
- lanzar
English:
hurtle
- rush
- settle
- stampede
- conclusion
* * *vpr1. [caer] to plunge (down);se precipitó al vacío desde lo alto del edificio he threw himself from the top of the building3. [apresurarse] to rush ( hacia towards);el público se precipitó hacia las salidas de emergencia the audience rushed towards the emergency exits4. [obrar irreflexivamente] to act rashly;te precipitaste al anunciar los resultados antes de tiempo you were rash to announce the results prematurely;no nos precipitemos let's not rush into anything, let's not be hasty* * *v/r1 ( correr) rush2 figbe hasty* * *vr1) apresurarse: to rush2) : to act rashly3) arrojarse: to throw oneself* * *precipitarse vb1. (actuar sin reflexionar) to be hasty / to rush2. (caerse) to plunge -
3 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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4 MONEY
• Abundance of money ruins youth (/The/) - Богатство родителей - порча детям (Б)• All things are obedient to money - Мошна туга - всяк ей слуга (M)• He that has money in his purse cannot want a head for his shoulders - Есть чем звякнуть, так можно и крякнуть (E)• He that hordes up money pains for other men - Скупой богач беднее нищего (C)• If money go before, all ways lie open - Деньги все двери открывают (Д)• It is easy to spend someone else's money - Из чужого кармана платить легко (И), Чужим добром подноси вед ром (4)• Lack of money is the root of all evil (The) - Бедность не грех, а до греха доводит (Б), Пустой мешок введет в грешок (П)• Love of money is the root of all evil (The) - Деньги глаза слепят (Д)• Money begets (breeds, comes to, draws, gets, makes) money - Где много воды, там больше будет; где много денег - еще прибудет (Г), Деньги к деньгам идут (Д)• Money calls but does not stay; it is round and rolls away - Деньги - крылья (Д), Деньги, что вода (Д)• Money can't buy happiness - И через золото слезы текут (И)• Money doesn't get dirty - Деньги не пахнут (Д)• Money doesn't grow on trees - Денежки труд любят (Д), Деньги не щепки, на полу не подымешь (Д)• Money greases the axle - Не подмажешь - не поедешь (H)• Money has no smell - Деньги не пахнут (Д)• Money has wings - Деньги - крылья (Д)• Money is a universal language speaking any tongue - Деньги все двери открывают (Д)• Money is not everything - Не в деньгах счастье (H)• Money isn't everything in life - Не в деньгах счастье (H)• Money is power - Деньги все двери открывают (Д), Золото железо переедает (3), Золото не говорит, да много творит (3), Мошна туга - всяк ей слуга (M)• Money is round and rolls away - Деньги - крылья (Д), Деньги, что вода (Д)• Money is round - it truckles - Деньги - крылья (Д)• Money makes the man - Есть чем звякнуть, так можно и крякнуть (E)• Money makes the mare go - За деньги и поп пляшет (3)• Money makes the pot boil - Есть в мошне, так будет и в квашне (E)• Money makes the wheels (the world) go round - Деньги все двери открывают (Д)• Money masters all things - Деньги все двери открывают (Д), Золото железо переедает (3), Золото не говорит, да много творит (3)• Money runs the world - Деньги все двери открывают (Д), Золото не говорит, да много творит (3)• Money saved is money earned (got) - Сбережешь - что найдешь (C)• Money speaks - Деньги все двери открывают (Д)• Money spent on the brain is never spent in vain - Знание лучше богатства (3)• Money talks - Деньги все двери открывают (Д)• Never spend your money before you have it - Цыплят по осени считают (Ц)• That's money down the drain - Не в коня корм (H)• Those who have money have trouble about it - Много денег - много и хлопот (M)• Want of money is the root of all evil - Бедность не грех, а до греха доводит (Б), Пустой мешок введет в грешок (П)• When money flies out the window, love flies out the door - С деньгами мил, без денег постыл (C)• When money speaks, truth keeps its mouth shut (keeps silent) - Когда деньги говорят, тогда правда молчит (K)• You can't take money with you when you die - Умрем, так все останется (X)• You pay your money and you take your choice - Кто платит музыканту, тот и заказывает музыку (K) -
5 תשובה
תְּשוּבָהf. (b. h.; שוּב) 1) return to God, repentance. Ab. IV, 11, v. תָּרִיס. Pes.54a שבעה … תורה ת׳וכ׳ seven things were created before the world was made, they are: the Law, repentance Ib. 119a (ref. to Ez. 1:8) זה ידו … כדי לקבל בעלי ת׳ that is the hand of the Lord which is spread under the wings of the Ḥayoth (v. חַיָּה I) to receive the repentant sinners. Ber.34b מקום שבעלי ת׳ עומדין וכ׳ where the repentant sinners stand, the perfectly righteous are not permitted to stand, for it is said (Is. 57:19) Yeb.21a (in Chald. dict.) הני אפשר בת׳ הני לא אפשר בת׳ these sins (of incest) may be remedied by repentance, but those (of giving false measures) cannot be remedied by repentance (because you can make no restoration). Pesik. R. s. 28 (ref. to Ps. 137:2) בא ודאה עפרה … לת׳וכ׳ come and see (the power of the love of) the dust of the land of Israel for repentance: as long as they were in the land of Israel, Jeremiah said to them, do penance, ; a. fr. 2) reply, answer. Sabb.88b החזיר להן ת׳ give them an answer (refute their argument). Pes.94a מה ת׳ השיבתו בת קולוכ׳ what was the reply the divine voice gave to that wicked man (Nebuchadnezzar), when he said (Is. 14:13), I will rise ?; Ḥag.13a. Snh.91a החזירו לו ת׳ make your argument against him; לא מצאו ת׳ they could find nothing to reply. Ib. 105a, v. נִצֵּחַ. Ab. Zar.44b ת׳ גנובה, v. גָּנַב; a. fr.Pl. תְּשוּבוֹת. Yoma 12b שתי ת׳ בדבר חדאוכ׳ there are two arguments against it, first that ; Keth.87b; a. fr.Gen. R. s. 20 בעל ת׳, v. בַּעַל. -
6 תְּשוּבָה
תְּשוּבָהf. (b. h.; שוּב) 1) return to God, repentance. Ab. IV, 11, v. תָּרִיס. Pes.54a שבעה … תורה ת׳וכ׳ seven things were created before the world was made, they are: the Law, repentance Ib. 119a (ref. to Ez. 1:8) זה ידו … כדי לקבל בעלי ת׳ that is the hand of the Lord which is spread under the wings of the Ḥayoth (v. חַיָּה I) to receive the repentant sinners. Ber.34b מקום שבעלי ת׳ עומדין וכ׳ where the repentant sinners stand, the perfectly righteous are not permitted to stand, for it is said (Is. 57:19) Yeb.21a (in Chald. dict.) הני אפשר בת׳ הני לא אפשר בת׳ these sins (of incest) may be remedied by repentance, but those (of giving false measures) cannot be remedied by repentance (because you can make no restoration). Pesik. R. s. 28 (ref. to Ps. 137:2) בא ודאה עפרה … לת׳וכ׳ come and see (the power of the love of) the dust of the land of Israel for repentance: as long as they were in the land of Israel, Jeremiah said to them, do penance, ; a. fr. 2) reply, answer. Sabb.88b החזיר להן ת׳ give them an answer (refute their argument). Pes.94a מה ת׳ השיבתו בת קולוכ׳ what was the reply the divine voice gave to that wicked man (Nebuchadnezzar), when he said (Is. 14:13), I will rise ?; Ḥag.13a. Snh.91a החזירו לו ת׳ make your argument against him; לא מצאו ת׳ they could find nothing to reply. Ib. 105a, v. נִצֵּחַ. Ab. Zar.44b ת׳ גנובה, v. גָּנַב; a. fr.Pl. תְּשוּבוֹת. Yoma 12b שתי ת׳ בדבר חדאוכ׳ there are two arguments against it, first that ; Keth.87b; a. fr.Gen. R. s. 20 בעל ת׳, v. בַּעַל. -
7 FOOL
• Arguing with a fool shows there are two - Дурак, кто с дураком свяжется (Д)• As the fool thinks, so the bell clinks - Дурни думкой богатеют (Д)• Children and fools cannot lie - Глупый да малый всегда правду говорят (Г)• Children and fools have merry lives - Дураком на свете жить - ни о чем не тужить (Д)• Children and fools speak (tell) the truth - Глупый да малый всегда правду говорят (Г)• Dreams give wings to fools - Дурни думкой богатеют (Д)• Drunken man will get sober, but a fool will never get wise (A) - Пьяница проспится, а дурак - никогда (П)• Drunks sober up, fools remain fools - Пьяница проспится, а дурак - никогда (П)• Even a fool, when he holds his peace, is counted wise - Молчи - за умного сойдешь (M)• Every fool wants to give advice - Умный любит учиться, а дурак учить (У)• Every man has a fool in (up) his sleeve - Безумье и на мудрого бывает (Б), И на Машку бывает промашка (И), И на старуху бывает проруха (И), На всякого мудреца довольно простоты (H)• Fool always finds a bigger fool to praise him (A) - Дурак дурака хвалит (Д)• Fool always finds another fool (А) - Дураку всегда компания найдется (Д)• Fool always rushes to the fore (А) - Глупый ищет большого места (Г), Дурак времени не знает (Д)• Fool and his gold are soon parted (A) - У дурака в горсти дыра (У)• Fool and his money are soon parted (A) - Нет в голове, нет и в мошне (H), Счастье без ума - дырявая сума (C), У дурака в горсти дыра (У)• Fool can ask more questions in a minute than a wise man can answer in an hour (A) - На всякого дурака ума не напасешься (H)• Fool can ask more questions in an hour than a wise man can answer in seven years (A) - На всякого дурака ума не напасешься (H)• Fool can ask questions that wise men cannot answer (A) - На всякого дурака ума не напасешься (H)• Fool doth think he is wise, but the wise man knows himself to be a fool (The) - Умный любит учиться, а дурак учить (У)• Fool is born every minute (A) - Дуракам счету нет (Д), На наш век дураков хватит (H)• Fool is he who deals with a fool - Дурак, кто с дураком свяжется (Д)• Fool is he who deals with other fools (A) - Дурак, кто с дураком свяжется (Д)• Fool is known by his conversation (speech) (A) - Дурак сам скажется (Д), Осла знать по ушам, медведя - по когтям, а дурака - по речам (O)• Fool is known by his laughing (A) - Дурак сам скажется (Д), Смех без причины - признак дурачины (C)• Fool is wise in his own conceit (A) - Умный любит учиться, а дурак учить (У), Я не дурак - сказал дурак (Я)• Fool may ask more questions /in an hour/ than a wise man can answer /in seven years/ (A) - На всякого дурака ума не напасешься (H)• Fool may give a wise man counsel (А) - Дурак врет, врет, да и правду скажет (Д), Иной раз и дурак молвит слово в лад (H)• Fool may sometimes speak to the purpose (A) - Дурак врет, врет, да и правду скажет (Д), Иной раз и дурак молвит слово в лад (И)• Fool may throw a stone into a well which a hundred wise men cannot pull out (A) - Глупый поп свенчает, умному не развенчать (Г), Дурак кинет в воду камень, а десять умных не вынут (Д)• Fools and bairns should not see half - done work (things half - done) - Дуракам полработы не показывают (Д)• Fools and children cannot lie - У дурака что на уме, то и на языке (У)• Fools and children speak (tell) the truth - У дурака что на уме, то и на языке (У)• Fools and madmen speak the truth - У дурака что на уме, то и на языке (У)• Fools are born not made - Дурак не дурак, а от роду так (Д), Дураков не сеют, не жнут - сами родятся (Д)• Fools are fain of nothing - Дурни думкой богатеют (Д)• Fools are lucky - Дуракам везет (Д)• Fool's bolt is soon shot (A) - Дурак сам скажется (Д)• Fool's bolt may sometimes hit the mark (A) - Дурак врет, врет, да и правду скажет (Д), Иной раз и дурак молвит слово в лад (И)• Fools build houses and wise men buy them - Дурак дом построил, а умный купил (Д)• Fools build houses for wise men to live in - Дурак дом построил, а умный купил (Д)• Fools cannot hold their tongues - У дурака язык впереди ног бежит (У)• Fools do more hurt in this world than rascals (The) - Простота хуже воровства (П)• Fools for luck - Дуракам везет (Д)• Fools go in crowds - Дуракам счету нет (Д), Дураку всегда компания найдется (Д)• Fools grow of themselves without sowing or planting - Дураков не сеют, не жнут - сами родятся (Д)• Fools grow without watering - Дураков не сеют, не жнут - сами родятся (Д)• Fools have fortune - Дурак спит, а счастье в головах лежит (Д)• Fool's head never grows white (A) - Дураком на свете жить - ни о чем не тужить (Д)• Fools lade the water, and wise men catch the fish - Дурак дом построил, а умный купил (Д)• Fools live poor to die rich - Шуба висит, а тело дрожит (Ш)• Fools make feasts and wise men eat them - Дурак дом построил, а умный купил (Д), Медведь пляшет, а поводырь деньги берет (M)• Fools multiply folly - Глупость заразительна (Г)• Fool's name appears everywhere (is seen in many places) (A) - Глупый ищет большого места (Г)• Fools' names and fools' faces are always seen in public places - Глупый ищет большого места (Г)• Fools need no passport - Дурак сам скажется (Д)• Fools never prosper - Нет в голове, нет и в мошне (H), Счастье без ума - дырявая сума (C), У дурака в горсти дыра (У)• Fools rush in where angels fear to tread - Дуракам закон не писан (Д)• Fools set stools for wise folks to stumble - Глупый поп свенчает, умному не развенчать (Г), Дурак кинет в воду камень, а десять умных не вынут (Д)• Fools set stools for wise men to fall over (to stumble) - Глупый поп свенчает, умному не развенчать (Г), Дурак кинет в воду камень, а десять умных не вынут (Д)• Fools tie knots, and wise men loosen (loose) them - Глупый поп свенчает, умному не развенчать (Г), Дурак кинет в воду камень, а десять умных не вынут (Д)• Fool's tongue runs before his wit (A) - У дурака язык впереди ног бежит (У)• Fool talks when he should be listening (A) - Дурак времени не знает (Д)• Fool talks while a wise man thinks (A) - Глупый болтает, а умный думает (Г)• Fools will be fools /still/ - Дурака учить, что мертвого лечить (Д), Дурак дураком останется (Д), Дураком родился - дураком и помрешь (Д), Пьяница проспится, а дурак - никогда (П)• Fool when he is silent is counted wise (A) - Молчи - за умного сойдешь (M)• Fortune favo(u)rs fools - Дуракам везет (Д), Дурак спит, а счастье в головах лежит (Д)• God sends fortune to fools - Дуракам везет (Д)• Half a fool, half a knave - Дурак-дурак, а себе на уме (K)• He is not the fool that the fool is but he that with the fool deals - Дурак, кто с дураком свяжется (Д)• He who is born a fool is never cured - Дураком родился - дураком и помрешь (Д)• If all fools wore feathers, we should seem a flock of geese - Дуракам счету нет (Д)• If all fools wore white caps, we'd all look like (we should seem a flock of) geese - Дуракам счету нет (Д), На наш век дураков хватит (H)• If every fool held a bauble, fuel would be dear - Дуракам счету нет (Д)• If you argue with a fool, that makes two fools arguing - Дурак, кто с дураком свяжется (Д)• If you want the truth, go to a child or a fool - Глупый да малый всегда правду говорят (Г)• It's a trifle that makes fools laugh - Дураку все смех на уме (Д), Смех без причины - признак дурачины (C)• It takes a fool to know a fool - Рыбак рыбака видит издалека (P)• Let a fool hold his tongue, and he can pass for a sage - Молчи - за умного сойдешь (M)• Live a fool, die a fool - Дураком родился - дураком и помрешь (Д)• Never joke with a fool - С дураками не шутят (C)• Never show a fool half - done job - Дуракам полработы не показывают (Д)• No man is always a fool, but every man is sometimes - И на старуху бывает проруха (И)• Older the fool, the worse he is (The) - Старые дураки глупее молодых (C)• Old fool is worse than a young fool (An) - Старые дураки глупее молодых (C)• Once a fool, always a fool - Дурак не дурак, а от роду так (Д), Дураком родился - дураком и помрешь (Д)• One fool makes a hundred (many) - Глупость заразительна (Г)• One fool praises another - Дурак дурака хвалит (Д)• Only fools and horses work - От работы кони дохнут (O), Работа дураков любит (P)• Send a fool to France and he'll come a fool back - Ворона за море летала, а умнее не стала (B)• Send a fool to the market, and a fool he'll return - Ворона за море летала, а умнее не стала (B), Каков поехал, таков и приехал (K), Осла хоть в Париж, а он все будет рыж (O)• There is no fool like an (to the) old fool - Седина в голову, а бес в ребро (C), Старые дураки глупее молодых (C)• When a fool has bethought himself, the market's over - После поры не точат топоры (П), После свадьбы в барабаны не бьют (П), Спустя лето в лес по малину не ходят (C)• When a fool has made up his mind, the market has gone by - После поры не точат топоры (П), После свадьбы в барабаны не бьют (П), Спустя лето в лес по малину не ходят (C)• When a fool made up his mind, the market's over - После поры не точат топоры (П), После свадьбы в барабаны не бьют (П), Спустя лето в лес по малину не ходят (C)• Wise men have their mouth in their heart, fools their heart in their mouth - Глупый болтает, а умный думает (Г), Дурак кричит, умный молчит (Д)• Wise men silent, fools talk - Глупый болтает, а умный думает (Г), Дурак кричит, умный молчит (Д)• Wise seek wisdom; the fool has found it (The) - Умный любит учиться, а дурак учить (У)• World is full of fools (The) - Дуракам счету нет (Д), На наш век дураков хватит (H)• You can fool an old horse once, but you can't fool him twice - Старую лису дважды не проведешь (C)
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