form words silently

1) (of person) Mund, der; (of animal) Maul, das

2) (fig.) (entrance to harbour) [Hafen]einfahrt, die; (of valley, gorge, burrow, tunnel, cave) Eingang, der; (of bottle, cannon) Mündung, die

3) (of river) Mündung, die

* * *

1) (the opening in the head by which a human or animal eats and speaks or makes noises: What has the baby got in its mouth?) der Mund

2) (the opening or entrance eg of a bottle, river etc: the mouth of the harbour.) die Ein-, Ausfahrt

- academic.ru/48322/mouthful">mouthful

* * *

I. n

1. (of human) Mund m; of animal Maul nt

to have a big \mouth ein großes Mundwerk haben fam

to have five [hungry] \mouths to feed fünf hungrige Mäuler zu stopfen haben

to keep one's \mouth shut nichts sagen, seinen Mund halten fam

to make sb's \mouth water jdm das Wasser im Munde zusammenlaufen lassen

to shut one's \mouth (fam!) den Mund halten fam

oh just shut your \mouth, will you? jetzt halt mal den Mund!

2. (opening) Öffnung f; of a bottle, jar, well Öffnung f; of a cave Eingang m; of a volcano Krater m; of a river, bay, harbour Mündung f

▶ sb is all \mouth [and trousers] jd nimmt den Mund zu voll, jd hat eine große Klappe [und nichts dahinter] fam

▶ to be down in the \mouth niedergeschlagen sein

▶ to shoot one's \mouth off about sth ( fam: indiscreetly) etw überall herumerzählen; (annoyingly) jdm mit etw dat die Ohren volllabern [o ÖSTERR sudern] sl

▶ to watch one's \mouth aufpassen, was man sagt

II. vt

▪ to \mouth sth

1. (form words silently) etw lautlos sagen

the singers are only \mouthing the words die Sänger bewegen nur die Lippen

2. (say insincerely) etw heuchlerisch sagen

* * *

1. n

2. vt

* * *

mouth

A s [maʊθ] pl mouths [maʊðz]

1. Mund m:

she has three mouths to feed sie hat drei hungrige Mäuler zu stopfen;

give mouth Laut geben, anschlagen (Hund);

give mouth to one’s thoughts seinen Gedanken Ausdruck verleihen;

keep one’s mouth shut umg die oder seine Klappe halten;

place ( oder put) words into sb’s mouth

a) jemandem Worte in den Mund legen,

b) jemandem erklären, was er sagen soll;

take the words out of sb’s mouth jemandem das Wort aus dem Mund nehmen;

down in the mouth umg deprimiert;

from sb’s mouth aus jemandes Munde;

from mouth to mouth von Mund zu Mund;

in everybody’s mouth in aller Munde; → big A 1, button C 1, shut A 1, stop A 8, word Bes Redew, wrong A 2

2. ZOOL Maul n, Schnauze f, Rachen m: → horse A 1

3. Mündung f (eines Flusses, einer Schusswaffe etc):

the mouth of the river die Flussmündung

4. Öffnung f (einer Flasche, eines Sackes etc)

5. Ein-, Ausgang m (einer Höhle, Röhre etc)

6. Ein-, Ausfahrt f (Hafen etc)

7. → mouthpiece 1

8. Grimasse f

9. umg

a) Angeberei f

b) Gequassel n:

he’s all mouth der hört überhaupt nie auf zu reden

10. TECH

a) Mundloch n

b) Schnauze f

c) Mündung f, Öffnung f

d) Gichtöffnung f (des Hochofens)

e) Abstichloch n (am Hoch-, Schmelzofen)

f) pl Rostfeuerungen pl

g) (Schacht)Mundloch n, (Schacht)Mündung f

11. (beim Pferd) Maul n (Art der Reaktion auf Zügelhilfen):

with a good mouth weichmäulig

B v/t [maʊð]

1. etwas affektiert oder gespreizt (aus)sprechen

2. a) (aus-)sprechen

b) Worte (unhörbar) mit den Lippen formen

3. in den Mund oder ins Maul nehmen

4. sorgfältig kauen, im Mund herumwälzen

C v/i

1. (laut oder affektiert) sprechen

2. Grimassen schneiden (at dat)

* * *

1) (of person) Mund, der; (of animal) Maul, das

2) (fig.) (entrance to harbour) [Hafen]einfahrt, die; (of valley, gorge, burrow, tunnel, cave) Eingang, der; (of bottle, cannon) Mündung, die

3) (of river) Mündung, die

* * *

Mund ¨-er m.

Mündung -en f.

[maʊɵ] n

1) ( of human) Mund m; of animal Maul nt;

to have a big \mouth ein großes Mundwerk haben ( fam)

to have five [hungry] \mouths to feed fünf hungrige Mäuler zu stopfen haben;

to keep one's \mouth shut nichts sagen, seinen Mund halten ( fam)

to make sb's \mouth water jdm das Wasser im Munde zusammenlaufen lassen;

to shut one's \mouth (fam!) den Mund halten ( fam)

oh just shut your \mouth, will you? jetzt halt mal den Mund!

2) ( opening) Öffnung f; of a bottle, jar, well Öffnung f; of a cave Eingang m; of a volcano Krater m; of a river, bay, harbour Mündung f

to be down in the \mouth niedergeschlagen sein;

to shoot one's \mouth off about sth (fam: indiscreetly) etw überall herumerzählen;

( annoyingly) jdm mit etw dat die Ohren voll labern (sl)

to watch one's \mouth aufpassen, was man sagt;

sb is all \mouth [and trousers] jd nimmt den Mund zu voll, jd hat eine große Klappe [und nichts dahinter] ( fam) vt [maʊð];

1) ( form words silently) etw lautlos sagen;

the singers are only \mouthing the words die Sänger bewegen nur die Lippen

2) ( say insincerely) etw heuchlerisch sagen

   1) Programs and the Complexity of Human Mental Processes

   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)

   2) Artificial Intelligence Is an Engineering Discipline

   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)

   3) A Sceptical View of Artificial Intelligence

   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, Eventually

   Just 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 Program

   Many 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)

   6) The Meaning of a Symbolic Description

   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)

   7) The Principle of Artificial Intelligence

   [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)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   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 Form

   The 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)

    10) There Are Many Types of Reasoning

   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)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   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)

    12) The Synthesis of Man and Machine

   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)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   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 Formation

   It 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)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological 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.

   ♦ Weak Psychological AI

   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.

   ♦ Strong Psychological AI

... 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)

   ♦ Suprapsychological AI

   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 Contexts

   Even 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)

    17) Form and Content Are Not Fundamentally Different

   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)

    18) The Assumption That the Mind Is a Formal System

   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 Intelligence

   The 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)

    20) Mathematical Logic Provides the Basis for Theory in AI

   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 Propositions

   In 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)

    22) Definitions of Artificial Intelligence

   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)

    23) The Computer Can Not Be a Model of the Mind

   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)

    24) Computers Will Not Always Be Inferior to Human Brains

   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)

* * *

(gen. pl. augna), n.

1) eye;

lúka (bregða) upp augum, bregða augum í sundr, to open (lift up) the eyes;

lúka aptr augum, to shift the eyes;

renna (bregða, leiða) augum til e-s, to turn the eyes to;

leiða e-n augum, to measure one with the eyes;

berja augum í e-t, to take into consideration;

koma augum á e-t, to set eyes on, become aware of;

hafa auga á e-u, t have, keep, an eye upon;

segja e-t í augu upp, to one’s face, right in the face;

unna e-m sem augum í höfði sér, as one’s own eye-balls;

e-m vex e-t í augu, one has scruples about;

náit er nef augum, the nose is neighbor to the eyes;

gløggt er gests augat, a guest’s eye is sharp;

mörg eru dags augu, the day has many eyes;

eigi leyna augu, ef ann kona manni, the eyes cannot hide it if a woman loves a man;

2) hole, aperture in a needle (nálarauga), in a millstone (kvarnarauga) or an axe-head;

3) pit full of water.

* * *

n., gen. pl. augna, [Lat. oculus, a dimin. of an obsolete ocus; Gr. οφθαλμός (Boeot. οκταλμός); Sanskr. aksha: the word is common to Sanskrit with the Slavonic, Greek, Roman, and Teutonic idioms: Goth. augo; Germ, auge; A. S. eâge; Engl. eye; Scot. ee; Swed. öga; Dan. öje, etc. Grimm s. v. suggests a relationship to Lat. acies, acutus, etc. The letter n appears in the plur. of the mod. northern languages; the Swedes say ‘ögon,’ oculi, the Danes ‘öjne;’ with the article ‘ögonen’ and ‘öjnene;’ Old Engl. ‘eyne;’ Scot. ‘een’]

I. an eye. It is used in Icel. in a great many proverbs, e. g. betr sjá augu en auga, ‘two eyes see better than one,’ i. e. it is good to yield to advice: referring to love, unir auga meðan á sér, the eye is pleased whilst it can behold (viz. the object of its affection), Fas. i. 125, cp. Völs. rím. 4. 189; eigi leyna augu, ef ann kona manni, the eyes cannot bide it, if a woman love a man, i. e. they tell their own tale, Ísl. ii. 251. This pretty proverb is an απ. λεγ. l. c. and is now out of use; it is no doubt taken from a poem in a dróttkvætt metre, (old proverbs have alliteration, but neither rhymes nor assonance, rhyming proverbs are of a comparatively late date): medic., eigi er sá heill er í augun verkir, Fbr. 75; sá drepr opt fæti ( slips) er augnanna missir, Bs. i. 742; hætt er einu auganu nema vel fari, he who has only one eye to lose will take care of it (comm.); húsbóndans auga sér bezt, the master’s eye sees best; glögt er gests augat, a guest’s eye is sharp; mörg eru dags augu, the day has many eyes, i. e. what is to be hidden must not be done in broad daylight, Hm. 81; náið er nef augum, the nose is near akin to the eyes (tua res agitur paries quum proximus ardet), Nj. 21; opt verðr slíkt á sæ, kvað selr, var skotinn í auga, this often happens at sea, quoth the seal, when he was shot in the eye, of one who is in a scrape, Fms. viii. 402. In many phrases, at unna ( to love) e-m sem augum í höfði sér, as one’s own eye-balls, Nj. 217; þótti mér slökt it sætasta ljós augna minna, by his death the sweetest light of my eyes was quenched, 187: hvert grætr þú nú Skarphéðinn? eigi er þat segir Skarphéðinn, en hitt er satt at súrnar í augum, the eyes smart from smoke, 200: renna, líta augum, to seek with the eyes, to look upon: it is used in various connections, renna, líta ástaraugum, vánaraugum, vinaraugum, trúaraugum, öfundaraugum, girndarauga, with eyes of love, hope, friendship, faith, envy, desire: mæna a. denotes an upward or praying look; stara, fixed; horfa, attentive; lygna, blundskaka, stupid or slow; blína, glápa, góna, vacant or silly; skima, wandering; hvessa augu, a threatening look; leiða e-n a., to measure one with the eyes; gjóta, or skjóta hornauga, or skjóta a. í skjálg, to throw a side glance of dislike or ill-will; gjóta augum is always in a bad sense; renna, líta mostly in a good sense: gefa e-u auga, oculum adjicere alicui; hafa auga á e-u, to keep an eye on it; segja e-m e-t í augu upp, to one’s face, Orkn. 454; at augum, adverb. with open eyes, Hervar. S. (in a verse), etc. As regards various movements of the eyes; ljúka upp augum, to open the eyes; láta aptr augun, to shut the eyes; draga auga í pung, to draw the eye into a purse, i. e. shut one eye; depla augum, to blink; at drepa titlinga (Germ. äugeln, blinzen), to wink, to kill tits with the suppressed glances of the eye; glóðarauga, a suffusion on the eye, hyposphagma; kýrauga. proptosis; vagl á auga, a beam in the eye; skjálgr, Lat. limus; ský, albugo; tekinn til augnanna, with sunken eyes, etc., Fél. ix. 192; a. bresta, in death: hafa stýrur í augum, to have prickles in the eyes, when the eyes ache for want of sleep: vatna músum, ‘to water mice,’ used esp. of children weeping silently and trying to hide their tears. As to the look or expression of the eyes there are sundry metaph. phrases, e. g. hafa fékróka í augum, to have wrinkles at the corners of the eyes, of a shrewd money getting fellow, Fms. ii. 84, cp. Orkn. 330, 188, where krókauga is a cognom.; kvenna-króka, one insinuating with the fair sex; hafa ægishjalm í augum is a metaphor of one with a piercing, commanding eye, an old mythical term for the magical power of the eye, v. Grimm’s D. Mythol. under Ægishjalmr: vera mjótt á milli augnanna, the distance between the eyes being short, is a popular saying, denoting a close, stingy man, hence mjóeygr means close: e-m vex e-t í augu (now augum), to shrink back from, of a thing waxing and growing before one’s eyes so that one dares not face it. As to the shape, colour, etc. of the eye, vide the adj. ‘eygr’ or ‘eygðr’ in its many compds. Lastly we may mention the belief, that when the water in baptism touches the eyes, the child is thereby in future life prevented from seeing ghosts or goblins, vide the words úfreskr and skygn. No spell can touch the human eye; en er harm sá augu hans (that of Loki in the shape of a bird), þá grunaði hann (the giant) at maðr mundi vera, Edda 60; í bessum birni þykist hón kenna augu Bjarnar konungs sonar, Fas. i. 51, vide Ísl. Þjóðs.

II. meton. and metaph. auga is used in a great many connections:

α. astron.; þjaza augu, the eyes of the giant Thiazi, is a constellation, probably the Dioscuri, Castor and Pollux; the story is told in the Edda 47, cp. Harbarðsljóð 19; (Snorri attributes it to Odin, the poem to Thor.)

β. botan., auga = Lat. gemma, Hjalt. 38; kattarauga, cat’s eye, is the flower forget-me-not.

γ. the spots that form the numbers on dice, Magn. 530.

δ. the hole in a millstone; kvarnarauga, Edda 79, 221, Hkr. i. 121: the opening into which an axe handle is fastened, Sturl. ii. 91: a pit full of water, Fs. 45: nálarauga, a needle’s eye: vindauga, wind’s eye or window (which orig. had no glass in it), A. S. eag-dura (eye-door); also gluggi, q. v.: gleraugu, spectacles.

ε. anatom., the pan of the hip joint, v. augnakarl, Fms. iii. 392: gagnaugu, temples.

ζ. hafsauga, the bottom of the ocean, in the popular phrase, fara út í hafsauga, descendere ad tartara.

η. poët. the sun is called heimsauga, dagsauga, Jónas 119.

COMPDS either with sing. auga or pl. augna; in the latter case mod. usage sometimes drops the connecting vowel a, e. g. augn-dapr, augn-depra, augn-fagr, etc. auga-bragð (augna-), n. the twinkling of an eye, Hm. 77; á einu a., in the twinkling of an eye, Ver. 32, Edda (pref.) 146, Sks. 559, Rb. 568: a glance, look, snart a., Fms. ii. 174; mikit a., v. 335; úfagrligt a., Fs. 43; hafa a. af e-u, to cast a look at, Fbr. 49, Fms. xi. 424: in the phrase, at hafa e-n (or verða) at augabragði, metaph. to make sport of, to mock, deride, gaze at, Stj. 627, 567, Hm. 5, 29. auga-brun, f. the eye-brow. auga-staðr, m. an eye-mark; hafa a. á e-u, to mark with the eye. auga-steinn (augna-), m. the eye-ball, Hkr. iii. 365, Fms. v. 152. augna-bending, f. a warning glance, Pr. 452. augna-blik, n. mod. = augnabragð, s. augna-bólga, u, f. ophthalmia. augna-brá, f. the eye-lid, D. N. i. 216. augna-fagr and aug-fagr, adj. fair-eyed, Fas. ii. 365, Fms. v. 200. augna-fró, f. a plant, eye-bright, euphrasia, also augna-gras, Hjalt. 231. augna-fræ, n. lychnis alpina. augna-gaman, n. a sport, delight for the eyes to gaze at, Ld. 202, Bær. 17, Fsm. 5 (love, sweetheart). augna-gróm, n. (medic.) a spot in the eye; metaph., ekki a., no mere speck, of whatever can easily be seen. augna-hár, n. an eye-lash. augna-hvannr, m. the eye-lid. augna-hvita, u, f. albugo. augna-karl, n. the pan of the hip joint; slíta or slitna or augnaköllunum, Fas. iii. 392. augna-kast, n. a wild glance, Barl. 167. augna-kláði, a, m. psorophthalmi. augna-krókr, n. the corner of the eye. augna-lag, n. a look, Ld. 154. augna-lok, n. ‘eye-covers,’ eye-lids. augna-mein, n. a disease of the eye. augna-mjörkvi, a, m. dimness of the eye, Pr. 471. augna-ráð, n. expression of the eye. augna-skot, n. a look askance, Gþl. 286, Fs. 44 (of cats). augna-slím, n. glaucoma. augna-staðr, m. the socket of the eye, Magn. 532. augna-sveinn, m. a lad leading a blind man, Str. 46. augn-tepra, u, f. hippus. augna-topt, f. the socket of the eye. augna-verkr, m. pain in the eye, Hkr. ii. 257, Bs. i. 451, Pr. 471, Bjarn. 58. augna-vik, n. pl. = augnakrókr. augna-þungi, a, m. heaviness of the eye, Hkr. ii. 257.