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− E ( X 1 ) E ( X 2 X 3 ) − E ( X 2 ) E ( X 3 X 1 ) − E ( X 3 ) E ( X 1 X 2 ) + 2 E ( X 1 ) E ( X 2 ) E ( X 3 ) u 4 ( X 1 , X 2 , X 3 , X 4 ) = E ( X 1 X 2 X 3 X 4 ) − E ( X 1 ) E ( X 2 X 3 X 4 ) − E ( X 2 ) E ( X 1 X 3 X 4 ) − E ( X 3 ) E ( X 1 X 2 X 4 ) − E ( X 4 ) E ( X 1 X 2 X 3 ) − E ( X 1 X 2 ) E ( X 3 X 4 ) − E ( X 1 X 3 ) E ( X 2 X 4 ) − E ( X 1 X 4 ) E ( X 2 X 3 ) + 2 E ( X 1 X 2 ) E ( X 3 ) E ( X 4 ) + 2 E ( X 1 X 3 ) E ( X 2 ) E ( X 4 ) + 2 E ( X 1 X 4 ) E ( X 2 ) E ( X 3 ) + 2 E ( X 2 X 3 ) E ( X 1 ) E ( X 4 )
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{
"page_id": 19660624,
"title": "Ursell function"
}
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+ 2 E ( X 2 X 4 ) E ( X 1 ) E ( X 3 ) + 2 E ( X 3 X 4 ) E ( X 1 ) E ( X 2 ) − 6 E ( X 1 ) E ( X 2 ) E ( X 3 ) E ( X 4 ) {\displaystyle {\begin{aligned}u_{1}(X_{1})={}&\operatorname {E} (X_{1})\\u_{2}(X_{1},X_{2})={}&\operatorname {E} (X_{1}X_{2})-\operatorname {E} (X_{1})\operatorname {E} (X_{2})\\u_{3}(X_{1},X_{2},X_{3})={}&\operatorname {E} (X_{1}X_{2}X_{3})-\operatorname {E} (X_{1})\operatorname {E} (X_{2}X_{3})-\operatorname {E} (X_{2})\operatorname {E} (X_{3}X_{1})-\operatorname {E} (X_{3})\operatorname {E} (X_{1}X_{2})+2\operatorname {E} (X_{1})\operatorname {E} (X_{2})\operatorname {E} (X_{3})\\u_{4}\left(X_{1},X_{2},X_{3},X_{4}\right)={}&\operatorname {E} (X_{1}X_{2}X_{3}X_{4})-\operatorname {E} (X_{1})\operatorname {E} (X_{2}X_{3}X_{4})-\operatorname {E} (X_{2})\operatorname {E} (X_{1}X_{3}X_{4})-\operatorname {E} (X_{3})\operatorname {E} (X_{1}X_{2}X_{4})-\operatorname {E} (X_{4})\operatorname {E} (X_{1}X_{2}X_{3})\\&-\operatorname {E} (X_{1}X_{2})\operatorname {E} (X_{3}X_{4})-\operatorname {E} (X_{1}X_{3})\operatorname {E} (X_{2}X_{4})-\operatorname {E} (X_{1}X_{4})\operatorname {E} (X_{2}X_{3})\\&+2\operatorname {E} (X_{1}X_{2})\operatorname {E} (X_{3})\operatorname {E} (X_{4})+2\operatorname {E} (X_{1}X_{3})\operatorname {E} (X_{2})\operatorname {E} (X_{4})+2\operatorname {E} (X_{1}X_{4})\operatorname {E} (X_{2})\operatorname {E} (X_{3})+2\operatorname {E} (X_{2}X_{3})\operatorname {E} (X_{1})\operatorname {E} (X_{4})\\&+2\operatorname {E} (X_{2}X_{4})\operatorname {E} (X_{1})\operatorname {E} (X_{3})+2\operatorname {E} (X_{3}X_{4})\operatorname {E} (X_{1})\operatorname {E} (X_{2})-6\operatorname {E} (X_{1})\operatorname {E} (X_{2})\operatorname {E} (X_{3})\operatorname {E} (X_{4})\end{aligned}}} == Characterization == Percus (1975) showed that the Ursell functions, considered as multilinear functions of several random variables, are uniquely determined up to a constant by the fact that they vanish whenever the variables Xi can be divided into two nonempty independent sets. == See also == Cumulant == References == Glimm, James; Jaffe, Arthur (1987), Quantum physics (2nd ed.), Berlin, New York: Springer-Verlag, ISBN 978-0-387-96476-8, MR 0887102 Percus, J. K. (1975), "Correlation inequalities for Ising spin lattices" (PDF), Comm. Math. Phys., 40 (3): 283–308, Bibcode:1975CMaPh..40..283P, doi:10.1007/bf01610004, MR 0378683, S2CID 120940116 Ursell, H. D. (1927), "The evaluation of Gibbs phase-integral for imperfect gases", Proc. Cambridge Philos. Soc., 23 (6): 685–697, Bibcode:1927PCPS...23..685U, doi:10.1017/S0305004100011191, S2CID 123023251
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{
"page_id": 19660624,
"title": "Ursell function"
}
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Nicholas Kurti, (Hungarian: Kürti Miklós) (14 May 1908 – 24 November 1998) was a Hungarian-born British physicist who lived in Oxford, UK, for most of his life. == Career == Born in Budapest, Kurti went to high school at the Minta Gymnasium, but due to anti-Jewish laws he had to leave the country, gaining his master's degree at the Sorbonne in Paris. He obtained his doctorate in low-temperature physics in Berlin, working with Professor Franz Simon. Kurti and Simon continued to work together during 1931–1933 at the Technische Hochschule in Breslau. However, when Adolf Hitler rose to power, both Simon and Kurti left Germany, joining the Clarendon Laboratory in the University of Oxford, England. During World War II, Kurti worked on the Manhattan project, returning to Oxford in 1945. In 1955 he won the Fernand Holweck Medal and Prize. In 1956, Simon and Kurti built a laboratory experiment that reached a temperature of one microkelvin. This work attracted worldwide attention, and Kurti was elected a Fellow of the Royal Society. He later became the society's Vice-President from 1965 to 1967. Kurti became a Fellow of Brasenose College, Oxford, in 1947 and became Professor of Physics at Oxford in 1967, a post he held until his retirement in 1975. He was also Visiting Professor at City College in New York City, the University of California, Berkeley, and Amherst College in Massachusetts. Nicholas Kurti was elected as a Fellow of the Royal Society (FRS) in 1956, becoming vice-president in 1965, and was appointed as a Commander of the British Empire (CBE) in 1973. == Personal life == 1946 he married Giana (née Shipley, 1913–2017). They had two daughters, Susannah and Camilla. Kurti's hobby was cooking, and he was an enthusiastic advocate of applying scientific knowledge to culinary problems, a field known today
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{
"page_id": 1769304,
"title": "Nicholas Kurti"
}
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as gastrophysics. In 1969 he gave a talk at the Royal Institution titled "The physicist in the kitchen", in which he amazed the audience by using the recently invented microwave oven to make a "reverse Baked Alaska" — a Frozen Florida — hot liquor enclosed by a shell of frozen meringue. Over the years he organized several international workshops in Erice, Italy on "Molecular and Physical Gastronomy." == References == == Bibliography == But the Crackling is Superb: An Anthology on Food and Drink by Fellows and Foreign Members of The Royal Society of London ISBN 0-7503-0488-X == External links == The Nicholas Kurti European Prize The papers of Nicholas Kurti were catalogued by Anna-K Mayer and Timothy Powell, NCUACS, Bath (England), prior to being deposited in the Bodleian Library, Oxford Oral History interview transcript with Nicholas Kurti, 11 September 1968, American Institute of Physics, Niels Bohr Library and Archives Physics and joys of life by Professor Nicholas Kurti, 10 March 1989, on YouTube
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{
"page_id": 1769304,
"title": "Nicholas Kurti"
}
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Evolutionary ethics is a field of inquiry that explores how evolutionary theory might bear on our understanding of ethics or morality. The range of issues investigated by evolutionary ethics is quite broad. Supporters of evolutionary ethics have argued that it has important implications in the fields of descriptive ethics, normative ethics, and metaethics. Descriptive evolutionary ethics consists of biological approaches to morality based on the alleged role of evolution in shaping human psychology and behavior. Such approaches may be based in scientific fields such as evolutionary psychology, sociobiology, or ethology, and seek to explain certain human moral behaviors, capacities, and tendencies in evolutionary terms. For example, the nearly universal belief that incest is morally wrong might be explained as an evolutionary adaptation that furthered human survival. Normative (or prescriptive) evolutionary ethics, by contrast, seeks not to explain moral behavior, but to justify or debunk certain normative ethical theories or claims. For instance, some proponents of normative evolutionary ethics have argued that evolutionary theory undermines certain widely held views of humans' moral superiority over other animals. Evolutionary metaethics asks how evolutionary theory bears on theories of ethical discourse, the question of whether objective moral values exist, and the possibility of objective moral knowledge. For example, some evolutionary ethicists have appealed to evolutionary theory to defend various forms of moral anti-realism (the claim, roughly, that objective moral facts do not exist) and moral skepticism. == History == The first notable attempt to explore links between evolution and ethics was made by Charles Darwin in The Descent of Man (1871). In Chapters IV and V of that work Darwin set out to explain the origin of human morality in order to show that there was no absolute gap between man and animals. Darwin sought to show how a refined moral sense, or conscience,
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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could have developed through a natural evolutionary process that began with social instincts rooted in our nature as social animals. Not long after the publication of Darwin's The Descent of Man, evolutionary ethics took a very different—and far more dubious—turn in the form of Social Darwinism. Leading Social Darwinists such as Herbert Spencer and William Graham Sumner sought to apply the lessons of biological evolution to social and political life. Just as in nature, they claimed, progress occurs through a ruthless process of competitive struggle and "survival of the fittest," so human progress will occur only if government allows unrestricted business competition and makes no effort to protect the "weak" or "unfit" by means of social welfare laws. Critics such as Thomas Henry Huxley, G. E. Moore, William James, Charles Sanders Peirce, and John Dewey roundly criticized such attempts to draw ethical and political lessons from Darwinism, and by the early decades of the twentieth century Social Darwinism was widely viewed as discredited. The modern revival of evolutionary ethics owes much to E. O. Wilson's 1975 book, Sociobiology: The New Synthesis. In that work, Wilson argues that there is a genetic basis for a wide variety of human and nonhuman social behaviors. More recently, a number of evolutionary biologists, including Richard Alexander, Robert Trivers, and George Williams, have argued for a different relation between ethics and evolution. In Alexander's words: “Ethical questions, and the study of morality or concepts of justice and right and wrong, derive solely from the existence of conflicts of interest.” The latter, in turn, are inevitable consequences of genetic individuality. Alexander argued that "Because morality involves conflicts of interest, it cannot easily be generalized into a universal despite virtually continual efforts by utilitarian philosophers to do that; morality does not derive its meaning from sets of
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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universals or undeniable facts." Rather, he argued, The two major contributions that evolutionary biology may be able to make to this problem are, first, to justify and promote the conscious realization that it is conflicts of interest concentrated at the individual level which lead to ethical questions, and, second, to help identify the nature and intensity of the conflicts of interest involved in specific cases. This view runs contrary to that of the majority of philosophers who work on evolutionary ethics, since it denies the existence of an innate “moral sense” in humans. As an example of genetic conflict, parents are selected to direct their time and resources equally among their offspring, but any particular child is more strongly related to itself than to any of its siblings, and so will desire a greater amount of parental investment than either parent is selected to give. A consequence of this parent-offspring conflict is that natural selection is unable to instill a universal sense of what is "just" or "fair" with regard to treatment of siblings, since behavior that is most conducive to propagation of the parents' genes differs from what is most favorable for the child's genes. Alexander noted that a focus on conflicts of interest is common among biologists and other non-philosophers, but that "many moral philosophers do not approach the problem of morality and ethics as if it arose as an effort to resolve conflicts of interests." He defined what he called "moral systems" as societal (not evolved) responses to conflicts of interest. Among other examples, he cited societal rules or laws imposing monogamy. The behavioral conflicts that are addressed by such rules have their evolutionary origin in the (genetic) sexual conflict between men and women. == Descriptive evolutionary ethics == The most widely accepted form of evolutionary ethics
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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is descriptive evolutionary ethics. Descriptive evolutionary ethics seeks to explain various kinds of moral phenomena wholly or partly in genetic terms. Ethical topics addressed include altruistic behaviors, conservation ethics, an innate sense of fairness, a capacity for normative guidance, feelings of kindness or love, self-sacrifice, incest-avoidance, parental care, in-group loyalty, monogamy, feelings related to competitiveness and retribution, moral "cheating," and hypocrisy. A key issue in evolutionary psychology has been how altruistic feelings and behaviors could have evolved, in both humans and nonhumans, when the process of natural selection is based on the multiplication over time only of those genes that adapt better to changes in the environment of the species. Theories addressing this have included kin selection, group selection, and reciprocal altruism (both direct and indirect, and on a society-wide scale). Descriptive evolutionary ethicists have also debated whether various types of moral phenomena should be seen as adaptations which have evolved because of their direct adaptive benefits, or spin-offs that evolved as side-effects of adaptive behaviors. == Normative evolutionary ethics == Normative evolutionary ethics is the most controversial branch of evolutionary ethics. Normative evolutionary ethics aims at defining which acts are right or wrong, and which things are good or bad, in evolutionary terms. It is not merely describing, but it is prescribing goals, values and obligations. Social Darwinism, discussed above, is the most historically influential version of normative evolutionary ethics. As philosopher G. E. Moore famously argued, many early versions of normative evolutionary ethics seemed to commit a logical mistake that Moore dubbed the naturalistic fallacy. This was the mistake of defining a normative property, such as goodness, in terms of some non-normative, naturalistic property, such as pleasure or survival. More sophisticated forms of normative evolutionary ethics need not commit either the naturalistic fallacy or the is-ought fallacy. But
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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all varieties of normative evolutionary ethics face the difficult challenge of explaining how evolutionary facts can have normative authority for rational agents. "Regardless of why one has a given trait, the question for a rational agent is always: is it right for me to exercise it, or should I instead renounce and resist it as far as I am able?" == Evolutionary metaethics == Evolutionary theory may not be able to tell us what is morally right or wrong, but it might be able to illuminate our use of moral language, or to cast doubt on the existence of objective moral facts or the possibility of moral knowledge. Evolutionary ethicists such as Michael Ruse, E. O. Wilson, Richard Joyce, and Sharon Street have defended such claims. Some philosophers who support evolutionary meta-ethics use it to undermine views of human well-being that rely upon Aristotelian teleology, or other goal-directed accounts of human flourishing. A number of thinkers have appealed to evolutionary theory in an attempt to debunk moral realism or support moral skepticism. Sharon Street is one prominent ethicist who argues that evolutionary psychology undercuts moral realism. According to Street, human moral decision-making is "thoroughly saturated" with evolutionary influences. Natural selection, she argues, would have rewarded moral dispositions that increased fitness, not ones that track moral truths, should they exist. It would be a remarkable and unlikely coincidence if "morally blind" ethical traits aimed solely at survival and reproduction aligned closely with independent moral truths. So we cannot be confident that our moral beliefs accurately track objective moral truth. Consequently, realism forces us to embrace moral skepticism. Such skepticism, Street claims, is implausible. So we should reject realism and instead embrace some antirealist view that allows for rationally justified moral beliefs. Defenders of moral realism have offered two sorts of replies.
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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One is to deny that evolved moral responses would likely diverge sharply from moral truth. According to David Copp, for example, evolution would favor moral responses that promote social peace, harmony, and cooperation. But such qualities are precisely those that lie at the core of any plausible theory of objective moral truth. So Street's alleged "dilemma"—deny evolution or embrace moral skepticism—is a false choice. A second response to Street is to deny that morality is as "saturated" with evolutionary influences as Street claims. William Fitzpatrick, for instance, argues that "[e]ven if there is significant evolutionary influence on the content of many of our moral beliefs, it remains possible that many of our moral beliefs are arrived at partly (or in some cases wholly) through autonomous moral reflection and reasoning, just as with our mathematical, scientific and philosophical beliefs." The wide variability of moral codes, both across cultures and historical time periods, is difficult to explain if morality is as pervasively shaped by genetic factors as Street claims. Another common argument evolutionary ethicists use to debunk moral realism is to claim that the success of evolutionary psychology in explaining human ethical responses makes the notion of moral truth "explanatorily superfluous." If we can fully explain, for example, why parents naturally love and care for their children in purely evolutionary terms, there is no need to invoke any "spooky" realist moral truths to do any explanatory work. Thus, for reasons of theoretical simplicity we should not posit the existence of such truths and, instead, should explain the widely held belief in objective moral truth as "an illusion fobbed off on us by our genes in order to get us to cooperate with one another (so that our genes survive)." Combining Darwinism with moral realism does not lead to unacceptable results in epistemology.
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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No two worlds, that are non-normatively identical, can differ normatively. The instantiation of normative properties is metaphysically possible in a world like ours. The phylogenetic adoption of moral sense does not deprive ethical norms of independent and objective truth-values. A parallel with general theoretical principles exists, which being unchangeable in themselves are discovered during an investigation. Ethical a priori cognition is vindicated to the extent to which other a priori knowledge is available. Scrutinizing similar situations, the developing mind pondered idealized models subject to definite laws. In social relation, mutually acceptable behavior was mastered. A cooperative solution in rivalry among competitors is presented by Nash equilibrium. This behavioral pattern is not conventional (metaphysically constructive) but represents an objective relation similar to that of force or momentum equilibrium in mechanics. == See also == Animal faith – Ritual behavior in non-humansPages displaying short descriptions of redirect targets Appeal to nature – Rhetorical tactic and potential fallacy Bioethics – Study of the ethical issues emerging from advances in biology and medicine Eugenics – Effort to improve purported human genetic quality Evolution of morality – Emergence of human moral behavior over the course of human evolution Game theory – Mathematical models of strategic interactions Pragmatic ethics § Moral ecology – Theory that morality evolves like an ecosystem Social Darwinism – Group of pseudoscientific theories and societal practices Universal Darwinism – Application of Darwinian theory to other fields == Notes == == References == Huxley, Thomas Henry (1893). "Evolution and Ethics". In Nitecki, Matthew H.; Nitecki, Doris V. (eds.). Evolutionary Ethics. Albany: State University of New York (published 1993). ISBN 0-7914-1499-X. {{cite book}}: ISBN / Date incompatibility (help) Ruse, Michael (1995). "Evolutionary Ethics: A Phoenix Arisen". In Thompson, Paul (ed.). Issues in Evolutionary Ethics. Albany: State University of New York. ISBN 0-7914-2027-2. == Further
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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reading == Alexander, Richard D. (1979). Darwinism and Human Affairs. ISBN 0-295-95641-0. Curry, O. (2006). Who's afraid of the naturalistic fallacy? Evolutionary Psychology, 4, 234–247. Full text Dawkins, Richard (1976). The Selfish Gene. ISBN 1-155-16265-X. Duntley, J.D., & Buss, D.M. (2004). The evolution of evil. In A. Miller (Ed.), The social psychology of good and evil. New York: Guilford. 102–123. Full text Archived 20 May 2014 at the Wayback Machine Hauser, Marc (2006). Moral Minds. ISBN 0-06-078070-3. Hare, D., Blossey, B., & Reeve, H.K. (2018) Value of species and the evolution of conservation ethics. Royal Society Open Science, 5 (11). https://doi.org/10.1098/rsos.181038. Full text Huxley, Julian. Evolutionary Ethics 1893-1943. Pilot, London. In USA as Touchstone for ethics Harper, N.Y. (1947) [includes text from both T.H. Huxley and Julian Huxley] Katz, L. (Ed.) Evolutionary Origins of Morality: Cross-Disciplinary Perspectives Imprint Academic, 2000 ISBN 0-907845-07-X Kitcher, Philip (1995) "Four Ways of "Biologicizing" Ethics" in Elliott Sober (ed.) Conceptual Issues in Evolutionary Biology, The MIT Press Kitcher, Philip (2005) "Biology and Ethics" in David Copp (ed.) The Oxford Handbook of Ethical Theory, Oxford University Press Krebs, D. L. & Denton, K. (2005). Toward a more pragmatic approach to morality: A critical evaluation of Kohlberg's model. Psychological Review, 112, 629–649. Full text Krebs, D. L. (2005). An evolutionary reconceptualization of Kohlberg's model of moral development. In R. Burgess & K. MacDonald (Eds.) Evolutionary Perspectives on Human Development, (pp. 243–274). CA: Sage Publications. Full text Mascaro, S., Korb, K.B., Nicholson, A.E., Woodberry, O. (2010). Evolving Ethics: The New Science of Good and Evil. Exeter, UK: Imprint Academic. Richerson, P.J. & Boyd, R. (2004). Darwinian Evolutionary Ethics: Between Patriotism and Sympathy. In Philip Clayton and Jeffrey Schloss, (Eds.), Evolution and Ethics: Human Morality in Biological and Religious Perspective, pp. 50–77. Full text ISBN 0-8028-2695-4 Ridley, Matt (1996).
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
}
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The Origins of Virtue. Viking. ISBN 0-14-026445-0. Ruse, Michael (January 1993). "The New Evolutionary Ethics". In Nitecki, Matthew H.; Nitecki, Doris V. (eds.). Evolutionary Ethics. Albany: State University of New York (published 1993). ISBN 0-7914-1499-X. Shermer, Michael (2004). The Science of Good and Evil: Why People Cheat, Gossip, Care, Share, and Follow the Golden Rule. New York: Henry Holt and Company. ISBN 0-8050-7520-8. Teehan, J. & diCarlo, C. (2004). On the Naturalistic Fallacy: A conceptual basis for evolutionary ethics. Evolutionary Psychology, 2, 32–46. Full text de Waal, Frans (1996). Good Natured: The Origins of Right and Wrong in Humans and Other Animals. London: Harvard University Press. ISBN 0-674-35660-8. Walter, A. (2006). The anti-naturalistic fallacy: Evolutionary moral psychology and the insistence of brute facts. Evolutionary Psychology, 4, 33–48. Full text Wilson, D. S., E. Dietrich, et al. (2003). On the inappropriate use of the naturalistic fallacy in evolutionary psychology. Biology and Philosophy 18: 669–682. Full text Wilson, D. S. (2002). Evolution, morality and human potential. Evolutionary Psychology: Alternative Approaches. S. J. Scher and F. Rauscher, Kluwer Press: 55-70 Full text Wilson, E. O. (1979). On Human Nature. ISBN 0-671-54130-7. Wright, Robert (1995). The Moral Animal. ISBN 0-679-40773-1. == External links == Evolutionary Ethics at the Internet Encyclopedia of Philosophy FitzPatrick, William. "Morality and Evolutionary Biology". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy. Okasha, Samir. "Biological Altruism". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy.
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{
"page_id": 2490200,
"title": "Evolutionary ethics"
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This is a list of common β-lactam antibiotics—both administered drugs and those not in clinical use—organized by structural class. Antibiotics are listed alphabetically within their class or subclass by their nonproprietary name. If an antibiotic is a combination drug, both ingredients will be listed. == Penams == === Narrow-spectrum === ==== β-lactamase-sensitive ==== ==== β-lactamase-resistant ==== === Broad spectrum === === Extended spectrum (Antipseudomonal) === ==== Carboxypenicillins ==== ==== Ureidopenicillins ==== == Cephems == === First generation (moderate spectrum) === === Second generation (moderate spectrum) === cefuroxime, cefaclor, cefprozil ==== With anti-Haemophilus activity ==== ==== With anti-anaerobic activity ==== === Third generation (broad spectrum) === === Fourth generation (broad spectrum) === (With β-lactamase stability and enhanced activity against Gram-positive bacteria and Pseudomonas aeruginosa) === Fifth generation* (broad spectrum) === (activity against MRSA and variably VRE. *Not universally accepted nomenclature. NO Antipseudomonal activity, mostly ceftriaxone coverage with additional MRSA and some VRE) == Carbapenems and penems == (Broadest spectrum of β-lactam antibiotics) == Monobactams == == β-lactamase inhibitors ==
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{
"page_id": 33947481,
"title": "List of β-lactam antibiotics"
}
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In particle physics, the hypercharge (a portmanteau of hyperonic and charge) Y of a particle is a quantum number conserved under the strong interaction. The concept of hypercharge provides a single charge operator that accounts for properties of isospin, electric charge, and flavour. The hypercharge is useful to classify hadrons; the similarly named weak hypercharge has an analogous role in the electroweak interaction. == Definition == Hypercharge is one of two quantum numbers of the SU(3) model of hadrons, alongside isospin I3. The isospin alone was sufficient for two quark flavours — namely u and d — whereas presently 6 flavours of quarks are known. SU(3) weight diagrams (see below) are 2 dimensional, with the coordinates referring to two quantum numbers: I3 (also known as Iz), which is the z component of isospin, and Y, which is the hypercharge (defined by strangeness S, charm C, bottomness B′, topness T′, and baryon number B). Mathematically, hypercharge is Y = B + C − S + T ′ − B ′ . {\displaystyle Y=B+C-S+T'-B'~.} Strong interactions conserve hypercharge (and weak hypercharge), but weak interactions do not. == Relation with electric charge and isospin == The Gell-Mann–Nishijima formula relates isospin and electric charge Q = I 3 + 1 2 Y , {\displaystyle Q=I_{3}+{\tfrac {1}{2}}Y,} where I3 is the third component of isospin and Q is the particle's charge. Isospin creates multiplets of particles whose average charge is related to the hypercharge by: Y = 2 Q ¯ . {\displaystyle Y=2{\bar {Q}}.} since the hypercharge is the same for all members of a multiplet, and the average of the I3 values is 0. These definitions in their original form hold only for the three lightest quarks. == SU(3) model in relation to hypercharge == The SU(2) model has multiplets characterized by a quantum
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{
"page_id": 524124,
"title": "Hypercharge"
}
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number J, which is the total angular momentum. Each multiplet consists of 2J + 1 substates with equally-spaced values of Jz, forming a symmetric arrangement seen in atomic spectra and isospin. This formalizes the observation that certain strong baryon decays were not observed, leading to the prediction of the mass, strangeness and charge of the Ω− baryon. The SU(3) has supermultiplets containing SU(2) multiplets. SU(3) now needs two numbers to specify all its sub-states which are denoted by λ1 and λ2. (λ1 + 1) specifies the number of points in the topmost side of the hexagon while (λ2 + 1) specifies the number of points on the bottom side. == Examples == The nucleon group (protons with Q = +1 and neutrons with Q = 0 ) have an average charge of ++1/2, so they both have hypercharge Y = 1 (since baryon number B = +1 , and S = C = B′ = T′ = 0). From the Gell-Mann–Nishijima formula we know that proton has isospin I3 = ++1/2 , while neutron has I3 = −+1/2 . This also works for quarks: For the up quark, with a charge of ++2/3, and an I3 of ++1/2, we deduce a hypercharge of 1/3, due to its baryon number (since three quarks make a baryon, each quark has a baryon number of ++1/3). For a strange quark, with electric charge −+1/3, a baryon number of ++1/3, and strangeness −1, we get a hypercharge Y = −+2/3 , so we deduce that I3 = 0 . That means that a strange quark makes an isospin singlet of its own (the same happens with charm, bottom and top quarks), while up and down constitute an isospin doublet. All other quarks have hypercharge Y = 0 . == Practical obsolescence == Hypercharge was
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{
"page_id": 524124,
"title": "Hypercharge"
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a concept developed in the 1960s, to organize groups of particles in the "particle zoo" and to develop ad hoc conservation laws based on their observed transformations. With the advent of the quark model, it is now obvious that strong hypercharge, Y, is the following combination of the numbers of up (nu), down (nd), strange (ns), charm (nc), top (nt) and bottom (nb): Y = 1 3 n u + 1 3 n d + 4 3 n c − 2 3 n s + 4 3 n t − 2 3 n b . {\displaystyle Y={\tfrac {1}{3}}n_{\textrm {u}}+{\tfrac {1}{3}}n_{\textrm {d}}+{\tfrac {4}{3}}n_{\textrm {c}}-{\tfrac {2}{3}}n_{\textrm {s}}+{\tfrac {4}{3}}n_{\textrm {t}}-{\tfrac {2}{3}}n_{\textrm {b}}~.} In modern descriptions of hadron interaction, it has become more obvious to draw Feynman diagrams that trace through the individual constituent quarks (which are conserved) composing the interacting baryons and mesons, rather than bothering to count strong hypercharge quantum numbers. Weak hypercharge, however, remains an essential part of understanding the electroweak interaction. == References == Semat, Henry; Albright, John R. (1984). Introduction to Atomic and Nuclear Physics. Chapman and Hall. ISBN 978-0-412-15670-0.
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{
"page_id": 524124,
"title": "Hypercharge"
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A plant press is a set of equipment used by botanists to flatten and dry field samples so that they can be easily stored. A professional plant press is made to the standard maximum size for biological specimens to be filed in a particular herbarium. A flower press is a similar device of no standard size that is used to make flat dried flowers for pressed flower craft. Specimens prepared in a plant press are later glued to archival-quality card stock with their labels, and are filed in a herbarium. Labels are made with archival ink (or pencil) and paper, and attached with archival-quality glue. == Construction == A modern plant press consists of two strong outer boards with straps that can be tightened around them to exert pressure. Between the boards, fresh plant samples are placed, carefully labelled, between layers of paper. Further layers of absorbent paper and corrugated cardboard are usually added to help to dry the samples as quickly as possible, which prevents decay and improves colour retention. Layers of a sponge material can be used in order to prevent squashing parts of the specimens, such as fruit. Older plant presses and some modern flower presses have screws to supply the pressure, which often limits the thickness of the stack of samples that can be put into one press. == History == Luca Ghini (1490—1556) Italian physician and botanist, created the first recorded herbarium, and is considered the first person to have used drying under pressure to prepare a plant collection. William Withering English botanist, geologist, chemist and physician wrote popular books on British botany, and by describing the screw-down plant press (and the vasculum) he brought it to the attention of amateur naturalists in Britain around 1771. == References == == External links == Mary Gibby
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{
"page_id": 48955231,
"title": "Plant press"
}
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(18 November 2006), "New Voyage for Darwin's Plants", Lothian Life — illustrates use of a plant press.
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{
"page_id": 48955231,
"title": "Plant press"
}
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Pattern recognition is a very active field of research intimately bound to machine learning. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern. This procedure, known as training, corresponds to learning an unknown decision function based only on a set of input-output pairs ( x i , y i ) {\displaystyle ({\boldsymbol {x}}_{i},y_{i})} that form the training data (or training set). Nonetheless, in real world applications such as character recognition, a certain amount of information on the problem is usually known beforehand. The incorporation of this prior knowledge into the training is the key element that will allow an increase of performance in many applications. == Prior knowledge == Prior knowledge refers to all information about the problem available in addition to the training data. However, in this most general form, determining a model from a finite set of samples without prior knowledge is an ill-posed problem, in the sense that a unique model may not exist. Many classifiers incorporate the general smoothness assumption that a test pattern similar to one of the training samples tends to be assigned to the same class. The importance of prior knowledge in machine learning is suggested by its role in search and optimization. Loosely, the no free lunch theorem states that all search algorithms have the same average performance over all problems, and thus implies that to gain in performance on a certain application one must use a specialized algorithm that includes some prior knowledge about the problem. The different types of prior knowledge encountered in pattern recognition are now regrouped under two main categories: class-invariance and knowledge on the data. == Class-invariance == A very common type of prior knowledge in pattern recognition is the invariance of the
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{
"page_id": 6881120,
"title": "Prior knowledge for pattern recognition"
}
|
class (or the output of the classifier) to a transformation of the input pattern. This type of knowledge is referred to as transformation-invariance. The mostly used transformations used in image recognition are: translation; rotation; skewing; scaling. Incorporating the invariance to a transformation T θ : x ↦ T θ x {\displaystyle T_{\theta }:{\boldsymbol {x}}\mapsto T_{\theta }{\boldsymbol {x}}} parametrized in θ {\displaystyle \theta } into a classifier of output f ( x ) {\displaystyle f({\boldsymbol {x}})} for an input pattern x {\displaystyle {\boldsymbol {x}}} corresponds to enforcing the equality f ( x ) = f ( T θ x ) , ∀ x , θ . {\displaystyle f({\boldsymbol {x}})=f(T_{\theta }{\boldsymbol {x}}),\quad \forall {\boldsymbol {x}},\theta .} Local invariance can also be considered for a transformation centered at θ = 0 {\displaystyle \theta =0} , so that T 0 x = x {\displaystyle T_{0}{\boldsymbol {x}}={\boldsymbol {x}}} , by using the constraint ∂ ∂ θ | θ = 0 f ( T θ x ) = 0. {\displaystyle \left.{\frac {\partial }{\partial \theta }}\right|_{\theta =0}f(T_{\theta }{\boldsymbol {x}})=0.} The function f {\displaystyle f} in these equations can be either the decision function of the classifier or its real-valued output. Another approach is to consider class-invariance with respect to a "domain of the input space" instead of a transformation. In this case, the problem becomes finding f {\displaystyle f} so that f ( x ) = y P , ∀ x ∈ P , {\displaystyle f({\boldsymbol {x}})=y_{\mathcal {P}},\ \forall {\boldsymbol {x}}\in {\mathcal {P}},} where y P {\displaystyle y_{\mathcal {P}}} is the membership class of the region P {\displaystyle {\mathcal {P}}} of the input space. A different type of class-invariance found in pattern recognition is permutation-invariance, i.e. invariance of the class to a permutation of elements in a structured input. A typical application of this type of prior
|
{
"page_id": 6881120,
"title": "Prior knowledge for pattern recognition"
}
|
knowledge is a classifier invariant to permutations of rows of the matrix inputs. == Knowledge of the data == Other forms of prior knowledge than class-invariance concern the data more specifically and are thus of particular interest for real-world applications. The three particular cases that most often occur when gathering data are: Unlabeled samples are available with supposed class-memberships; Imbalance of the training set due to a high proportion of samples of a class; Quality of the data may vary from a sample to another. Prior knowledge of these can enhance the quality of the recognition if included in the learning. Moreover, not taking into account the poor quality of some data or a large imbalance between the classes can mislead the decision of a classifier. == Notes == == References == E. Krupka and N. Tishby, "Incorporating Prior Knowledge on Features into Learning", Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS 07)
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{
"page_id": 6881120,
"title": "Prior knowledge for pattern recognition"
}
|
Shion Uzuki (シオン・ウヅキ, Shion Uzuki) is the main protagonist of the Xenosaga trilogy for the PlayStation 2. In addition, she was in the DS game Xenosaga I & II, Xenosaga Freaks, as well as the anime Xenosaga: The Animation. == Character design == Shion Uzuki is the main character of the three episodes of Xenosaga, which have been referred to as "Shion's Arc" by Namco Bandai. While her role is less prominent in Xenosaga Episode II, which focuses on the character Jr., she is the lead character again in the DS remake Xenosaga I & II. While Shion's surname is "Uzuki", Takahashi has stated that she is not meant to be a distant relative of the character Citan Uzuki from Xenogears. She does, however, share his liking for science. Shion is portrayed as a girl who tries to overcome the tragic events of her past by "looking away from reality and truth". Takahashi compared the character's instinctive tendency to run away from things with his very own personality and mindset. A particular point he wanted to explore in the series was Shion "looking back at herself […] wondering how she should live her life". When he created Xenosaga, Takahashi made "life and death" a central theme of the story and gave each character a different outlook on it; Shion and Albedo were conceived as the two characters that eventually develop the "ideal compromise towards death". Xenosaga Episode I has an anime-like art style, while Episode II and III use a more realistic style, and thus she appears differently. She wears glasses in the first and third games. If the player loads a save file from Episode II in Episode III, Shion will obtain special armor that will change her outward appearance. Shion's main theme in Episode I is the ending
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{
"page_id": 1507174,
"title": "Shion Uzuki"
}
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song "Kokoro"(heart) performed by Joanne Hogg. The tracks "Shion's Crisis", "Shion ~Memories of the Past~" and "Shion ~Emotion~" were also written for scenes focusing on her. "Fighting KOS-MOS" plays during a scene that showcases KOS-MOS' power, but composer Yasunori Mitsuda chose to write the track from Shion's perspective for a twist. "Shion ~Emotion~" was first released on the "Kokoro" maxi-single as "Kokoro Piano Version", but Mitsuda changed the track's title in the Xenosaga Original Soundtrack as it fitted Shion best. == Appearances == === Xenosaga === Shion Uzuki was assigned to Vector Industries' First R&D Division at the young age of 18 in T.C. 4763. Her official title is "Chief Engineer of the KOS-MOS Project General Operation System Research Center, Vector Industries First R&D Division". She has a bright, cheerful personality and is ever the optimist, perhaps to hide the scars of losing both her parents as a child and her fiancé two years ago. In Episode I, it was revealed that she suffers from astraphobia, the result of two traumatic incidents which happened during lightning storms; losing her parents and later her fiancé, Kevin. She does not get along well with her brother, Jin Uzuki, who is thirteen years her senior. Shion ends up being swept, along with KOS-MOS and her co-worker Allen Ridgeley, into a conspiracy concerning the very fate of mankind itself. In addition to her intellect (a key factor in her usage of nanotechnology), she learned the same martial arts that Jin and Margulis are masters of as taught by her grandfather. However, unlike Jin and Margulis, she primarily focuses on hand-to-hand combat with the use of her M.W.S. Throughout the series, Shion has exhibited abilities unbecoming of most humans. During the Gnosis' assault on the Woglinde, she was caught in close proximity to an FAE
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{
"page_id": 1507174,
"title": "Shion Uzuki"
}
|
(fuel air explosion), which no ordinary human could possibly survive. Shion, however, was blown back by the explosion and left otherwise unscathed. Shion has also demonstrated the peculiar ability to hear the Song of Nephilim, something which only Realians and U.R.T.V.s should be capable of (chaos has also demonstrated this ability, but his status as a "human being" remains ambiguous at best). During a Gnosis assault on the Woglinde, Shion was caught by a Gnosis in its immaterial state, which was able to grip her. She was able to escape crystallization and mysteriously avoided the fate of those who did not survive such an encounter with a Gnosis, as those that come into physical contact with Gnosis usually transformed into one. Andrew Cherenkov, for instance, suffered such a fate. This could be due to her status as the "Maiden" or her possession of what Wilhelm referred to as the "Shining Will", which is a prerequisite to becoming a Testament; it is said that those with the Shining Will will not Gnosify. Shion can link to U-DO and can communicate with it, with U-DO responding to her through this power. During the Miltian Conflict (as a child), after seeing her parents killed by berserk realians she summons the Gnosis from her distress through the Zohar. When she once again experiences this as an adult she loses control and summons Abel’s Ark (a giant Gnosis). Shion also suffers from the same illness as her mother, which Kevin reveals is caused by communication with U-DO. Kevin confirms in Episode III that KOS-MOS is gradually killing Shion since KOS-MOS uses the Zohar and U-DO as an energy source. Had U-DO not chosen to let humanity live on, Shion would have ultimately died due to the extreme stress caused by these communications. She has also
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{
"page_id": 1507174,
"title": "Shion Uzuki"
}
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experienced several unusual perceptions, seeing visions of the young girl named "Nephilim" and of her deceased Realian nanny Febronia. It is also revealed in Xenosaga I & II and the database of III that she has the natural ability to see into the "Realm of Imaginary Numbers", where the Gnosis hail from. Her glasses inhibit this ability and allow her to experience relatively normal perceptions. However, as this sense of hers is not active all the time, and as she "has gotten used to it," she removes the glasses when they present an inconvenience to her daily life. Her consciousness has existed since the time of Lost Jerusalem as the maiden and close acquaintance of Mary Magdalene; her brief vision of the distant past was not through KOS-MOS' memory, but through her own. It can be deduced from KOS-MOS' last words that Shion's former self died as a result of being caught up in some larger occurrence and that KOS-MOS (Mary) had been unable to protect her. After discovering Allen's feelings for her on Michtam, Shion took the first step towards her independence. Shion, so caught up in the memories shared with Kevin Winnicot, had not truly realized the extent of Allen's love for her. Because Allen differs from Kevin in every conceivable way, including attitude, disposition, and personal history, Shion felt as though he would be the one able to offer comfort for her sorrowful heart. Thus begins Shion's journey to Lost Jerusalem, wherein humanity's collective consciousness awaits guidance and salvation. === Other appearances === Shion makes an appearance in Namco × Capcom, when she, M.O.M.O., and KOS-MOS appear in the middle of Shibuya during a series of dimensional disturbances, in time to help the main characters against a Gnosis attack. In the game, Shion is paired with MOMO
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{
"page_id": 1507174,
"title": "Shion Uzuki"
}
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as a single unit. Bandai has released Shion figurines as part of the Xenosaga Legend toy set. == Reception == Shion as seen in Xenosaga Episode I has been called "cute" and "likable" by critics. IGN also praised the more realistic character designs seen in Episode II, noting that Shion's design became "more flattering", having "been injected with ye old 'Babe Serum.'" RPGamer also praised the design change, though they felt that Shion's lack of glasses in that episode was "amusing". In a review of the first volume of Xenosaga: The Animation, GameSpot compared Shion and KOS-MOS to "the ultimate fanboy fan-service pair", feeling that Shion was an example of a "cute, yet smart glasses girl". Personalitywise, Shion has been described by GameSpot as being "pretty straightforward as a heroine, though maybe a little ditzy for someone who's supposedly one of the best scientists in the galaxy". On the other hand, IGN felt that the character was "more complicated than she first lets on". In a review of the Xenosaga anime, another reviewer from IGN noted that Shion's idealism and naivety were out of place considering her tragic past, and that it was annoying "since it seems to happen a lot with anime heroines". GameSpy echoed this concern, stating that Shion was "often naïve to the point of unbelievability". On voice acting, GameSpy felt Shion in Episode I was "excellent" despite the game not having "Hollywood-quality" acting. The site called the character a "calm center" around which the rest of the game is built. == References ==
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{
"page_id": 1507174,
"title": "Shion Uzuki"
}
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The term carboxypeptidase P may refer to: Lysosomal Pro-X carboxypeptidase Membrane Pro-X carboxypeptidase
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{
"page_id": 39255911,
"title": "Carboxypeptidase P"
}
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An epiphyseal line is an epiphyseal plate that has become ossified. The process of it forming from an epiphyseal plate is named epiphyseal closure. In adult humans, it marks the point of fusion between the epiphysis and the metaphysis. == Function == The epiphyseal line serves no function in the bone, being purely vestigial. However, it serves as an indicator of the boundary between the epiphysis and diaphysis. == References ==
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{
"page_id": 21888872,
"title": "Epiphyseal line"
}
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The Blaise reaction is an organic reaction that forms a β-ketoester from the reaction of zinc metal with an α-bromoester and a nitrile.[1][2][3] The reaction was first reported by Edmond Blaise (1872–1939) in 1901. The final intermediate is a metaloimine, which is then hydrolyzed to give the desired β-ketoester.[4] Bulky aliphatic esters tend to give higher yields. Steven Hannick and Yoshito Kishi have developed an improved procedure.[5] It has been noted[6][7] that free hydroxyl groups can be tolerated in the course of this reaction, which is surprising for reactions of organometallic halides. == Mechanism == The mechanism of the Blaise reaction involves the formation of an organozinc complex with the bromine alpha to the ester carbonyl. This makes the alpha carbon nucleophilic, allowing it to attack the electrophilic carbon of the nitrile. The negative nitrile nitrogen resulting from this attack complexes with the zinc monobromide cation. The β-enamino ester (tautomer of the imine intermediate pictured above) product is revealed by work-up with 50% K2CO3 aq. If the β-ketoester is the desired product, addition of 1 M hydrochloric acid hydrolyzes the β-enamino ester to turn the enamino into a ketone, forming the β-ketoester. == See also == Blaise ketone synthesis Reformatsky reaction == References == ^ Edmond E. Blaise; Compt. Rend. 1901, 132, 478. ^ Rinehart, K. L., Jr. Organic Syntheses, Coll. Vol. 4, p. 120 (1963); Vol. 35, p. 15 (1955). (Article) ^ Rao, H. S. P.; Rafi, S.; Padmavathy, K. Tetrahedron 2008, 64, 8037-8043. (Review) ^ Cason, J.; Rinehart, K. L., Jr.; Thorston, S. D., Jr. J. Org. Chem. 1953, 18, 1594. (doi:10.1021/jo50017a022) ^ Hannick, S. M.; Kishi, Y. J. Org. Chem. 1983, 48, 3833. (doi:10.1021/jo00169a053) [8] Marko, I.E. J. Am. Chem. Soc. 2007, ASAP doi:10.1021/ja0691728 [9] Wang, D.; Yue, J.-M. Synlett 2005, 2077-2079. == External links == Blaise
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{
"page_id": 2031464,
"title": "Blaise reaction"
}
|
Reaction - Details and Recent Literature
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{
"page_id": 2031464,
"title": "Blaise reaction"
}
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Neocatastrophism is the hypothesis that life-exterminating events such as gamma-ray bursts have acted as a galactic regulation mechanism in the Milky Way upon the emergence of complex life in its habitable zone. It is one of several proposed solutions to the Fermi paradox since it provides a mechanism which would have delayed the advent of intelligent beings in local galaxies near Earth. == The problem == It is estimated that Earth-like planets in the Milky Way started forming 9 billion years ago, and that their median age is 6.4 ± 0.7 Ga. Moreover, 75% of stars in the galactic habitable zone are older than the Sun. This makes the existence of potential planets with evolved intelligent life more likely than not to be older than that of the Earth (4.54 Ga). This creates an observational dilemma since even slower-than-lightspeed interstellar travel could in theory take only 5 to 50 million years to colonize the galaxy. This leads to a conundrum first posed in 1950 by the physicist Enrico Fermi in his namesake paradox: "Why are no aliens or their artifacts physically here?" == The neocatastrophism resolution == The hypothesis posits that astrobiological evolution is subject to regulation mechanisms that arrest or postpone the advent of complex creatures capable of interstellar communication and traveling technology. These regulation mechanisms act to temporarily sterilize planets of biology in the galactic habitable zone. The main proposed regulation mechanism is gamma-ray bursts. Part of the neocatastrophism hypothesis is that stellar evolution produces a decreasing frequency of such catastrophic events increasing the length of the "window" in which intelligent life might arise as galaxies age. According to modeling, this creates the possibility of a phase transition at which point a galaxy turns from a place that is essentially dead (with a few pockets of simple life)
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{
"page_id": 13041514,
"title": "Neocatastrophism"
}
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to one that is crowded with complex life forms. == See also == == References ==
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{
"page_id": 13041514,
"title": "Neocatastrophism"
}
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Genetic predisposition refers to a genetic characteristic which influences the possible phenotypic development of an individual organism within a species or population under the influence of environmental conditions. The term genetic susceptibility is often used synonymously with genetic predisposition and is further defined as the inherited risk for specific conditions, based on genetic variants. While environmental factors can influence disease onset, genetic predisposition plays a role in inherited risk of conditions, such as various cancers. At the molecular level, genetic predisposition often involves specific gene mutation, regulatory pathways, or epigenetic modifications that alter cellular processes, increasing disease risk. == How to predict genetic predisposition == There are several approaches commonly used in the field of genetics to predict a genetic predisposition toward a disease. Genome-Wide Association Studies (GWAS): studies that identify genetic variants linked to diseases by analyzing genomes across populations. This approach looks for single nucleotide polymorphisms (SNPs) associated with a specific disease or trait. Polygenic Risk Scores (PRS): approach that combines the influence of multiple genetic variants and provides a measurable score for an individual's likelihood of developing certain conditions. Research around this approach is focused on predicting heart disease, cancer, and psychiatric disorders. Machine learning algorithms: the use of algorithms that integrate genetic data that have improved prediction accuracy for certain conditions, including diabetes and some cancers. Nomogram models: technique that combines genetic markers and clinical indicators to produce personalized risk assessments. == Genetic predisposition at the molecular level == As individuals, one’s genetic makeup or genotype, which is passed down from their parents, defines how they look and what genetic conditions they could have inherited, or be at risk for. These traits are exclusive, and therefore one's susceptibility to specific diseases is unique as well. The inheritance of specific genes reflect phenotypes based on one allele
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{
"page_id": 2162538,
"title": "Genetic predisposition"
}
|
that comes from the mother and one from the father of each gene. Phenotypes that display genetic conditions are often caused by random mutations within the DNA sequence that makes up a gene. Somatic mutations are mutations that occur within the DNA of a non-reproductive cell post-conception, and therefore cannot be inherited, nor will they contribute to one’s genetic predisposition to disease. However, germline mutations occur within the DNA of reproductive cells and can be inherited by offspring, thereby influencing the individual's susceptibility to the specific genetic issue. Upon diagnosing individuals with particular conditions via genetic testing, their genetic predisposition can be measured with pedigree trees. These trees trace inheritance patterns throughout a family to see if the mutation of interest can also be found in other blood-related individuals. == Genetic disease inheritance patterns == Genetic diseases can be autosomal recessive, autosomal dominant, X chromosome-linked recessive, X chromosome-linked dominant or Y chromosome-linked. They will be inherited differently based on their composition. Autosomal inheritance patterns will affect specific autosomes, non-sex chromosomes, depending on the genetic disease. Autosomal recessive diseases occur only when both inherited alleles have the mutation, while autosomal dominant diseases will be demonstrated in individuals with only one mutant version of the allele. Therefore, besides solely inheritance, the type of disease that is being considered plays a large role in susceptiblity. Genetic predisposition can also be impacted by one’s gender, as sex chromosomes define inheritance of X-linked and Y-linked alleles. Males are far more likely to inherit X-linked recessive diseases, because they only have one copy of the X chromosome, while females have two and therefore need mutations in both for this phenotype to be demonstrated. X-linked dominant diseases are equally shown in both males and females, while Y-linked diseases will only be demonstrated in males, as females do
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{
"page_id": 2162538,
"title": "Genetic predisposition"
}
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not have a Y chromosome. == Predisposition to cancer == Cancers are a major consideration when examining genetic predisposition to diseases, as they often arise from inherited genetic mutations that trigger uncontrolled cell growth. As genetic diseases, these mutations can be passed down through families, increasing an individual's risk of developing various types of cancer. Understanding an individual's genetic predisposition to cancer plays a key role in managing risk among family members and optimizing treatment. === Breast cancer === Genetic predisposition to breast cancer is categorized into three main risk groups. The first group consists of high-penetrance genes, such as BRCA1, BRCA2, and TP53. Mutations in these genes are inherited and significantly increase an individual's susceptibility to breast cancer. The second group includes intermediate-penetrance genes, such as CHEK2 and ATM. These genes are identified through mutational screening of DNA repair genes and increase an individual's risk of breast cancer, though not as severely as high-penetrance genes. The last category consists of low-penetrance alleles, which are SNPs more commonly found in populations, however still contribute to a slight increase in susceptibility to breast cancer. Genetic testing for high penetrance genes serves as an important indicator of breast cancer risk. Having the knowledge of predisposition to these genes can allow precautional measures to be taken towards prevention and treatment options early on, rather than not knowing until the disease has already progressed. === Colorectal cancer === Individuals with a genetic predisposition to colorectal cancer can benefit greatly from early and consistent monitoring. Hereditary Colorectal Cancer (HCRC) is typically associated with several genetic syndromes, each characterized by specific gene mutations that play a critical role in diagnosis and risk assessment. Lynch Syndrome is the most common, and results from inherited pathogenic variants in DNA mismatch repair genes such as MLH1, MSH2, and MSH6.
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{
"page_id": 2162538,
"title": "Genetic predisposition"
}
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Inheriting these mutations impairs the body's ability to correct DNA replication errors, significantly increasing the risk of developing colorectal and other cancers. Familial adenomatous polyposis (FAP) is another hereditary condition, caused by pathogenic mutations in the APC gene. If left untreated, it leads to a severe risk of developing colorectal cancer, typically before the age of 50. Genetic testing and screening is essential for identifying individuals at increased risk, enabling early detection strategies such as regular colonoscopies and informing preventive care for both patients and their family members. Early implementation of these measures has been shown to improve long term outcomes for those with inherited susceptibility. == Behavioural predisposition == Genetic predisposition can also have an impact on psychological and behavioural phenotypes, as well as physical. An individual’s predisposition towards certain human behaviors can be examined in an attempt to identify behavioural patterns that appear to be historically and evolutionarily invariant within a variety of different cultures. Studies have shown that heritability and other genetic factors can greatly contribute to the risk of depression and suicidal behaviours. Genetic predisposition to depressive disorders is typically caused through interactions between specific genes with each other and their environment. More than 100 candidate genes have been identified that have the ability to increase risk of depression and contribute to its symptoms, which can be assessed via methodological approaches. Growing research is investigating how suicide can aggregate within families, further providing evidence that the alleles contributing to suicidal thoughts can be inherited. This has been further investigated through twin studies and adoption studies to measure the impacts of genetic information versus environment on one’s behaviour. == See also == == References == == External links == Genetic discrimination fact sheet from the National Human Genome Research Institute.
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{
"page_id": 2162538,
"title": "Genetic predisposition"
}
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A night safari is a nocturnal visit to a zoo or wildlife-spotting natural area. The term was first used by the Night Safari, Singapore, which opened in 1994. While the term generally applies to zoos or facilities that allow visitors to view animals within enclosures or fenced areas, the term is expanding to include viewing of wildlife in national parks and other natural areas, such as in Laos. == List of night safari parks == Chiang Mai Night Safari in Chiang Mai, Thailand Night Safari, Singapore South Luangwa National Park in Mfuwe, Zambia Zoo Taiping in Taiping, Perak, Malaysia Kukrail Forest Area in Lucknow, Uttar Pradesh, India == See also == Safari == References ==
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{
"page_id": 25034604,
"title": "Night safari"
}
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Hypomyces lateritius, the ochre gillgobbler, is a parasitic ascomycete fungus that grows on certain species of Lactarius mushrooms, improving their flavor and densifying the flesh. Hosts include L. camphoratus, L. chelidonium, L. controversus, L. deliciosus, Lactarius indigo, L. rufus, L. salmonicolor, L. sanguifluus, L. semisanguifluus, L. tabidus, L. trivialis, and L. vinosus. It is a microscopic fungus causing the formation of a macroscopic whitish subiculum over the hymenium of its host species, preventing gill formation. Presence of H. lateritius also often deforms the cap and stipe. Parasitization by H. lateritius does not prevent latex from forming when the flesh is cut. == Distribution == Hypomyces lateritius can be found wherever Lactarius species can be found, in North America from Alaska to Mexico and in Europe from the Iberian Peninsula to Ukraine. In Asia in Kazakhstan, Kyrgyzstan and Western Siberia. It has also been reported in New Zealand and South Africa. == Synonyms == Sphaeria lateritia Fries, Syst. Mycol. 2: 338. 1823. Hypocrea lateritia (Fr.) Fries, Summa Veg. Scand. 383.1849. Peckiella lateritia (Fr.) Maire, Ann. Mycol. 4: 331.1906. Byssonectria lateritia (Fr.) Petch, J. Bot. Lond. 75: 220.1937. Hypomyces volemi Peck, Bull. Torrey Club 27: 20. 1900. Peckiella hymenioides Peck, Bull. Torrey Club 34: 102.1907. Hypomyces camphorati Peck, New York State Bull. 205:23. 1905 (1906). Peckiella camphorati (Peck) Seaver, Mycologia 2: 68.1910. Hypomyces camphorati (syn. Peckiella camphorati) is sometimes treated as a separate species from H. lateritius. Subiculum of specimens with L. camphoratus host tends more yellowish, and displays slightly larger ascospores. More research is required to determine whether H. lateritius is a single species or a species complex. == References == == External links == Media related to Hypomyces lateritius at Wikimedia Commons [[Category:Fungi described in
|
{
"page_id": 68419434,
"title": "Hypomyces lateritius"
}
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Aplasmomycin is an antibiotic with antimalarial activity isolated from Streptomycete. == References ==
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{
"page_id": 40501095,
"title": "Aplasmomycin"
}
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KCC Corporation (renamed from Kumkang Korea Chemicals Co., Ltd. in 2005) is a South Korean chemical and auto parts manufacturer, headquartered in Seoul, South Korea. == Operations == KCC's products include various kinds of paints, float glass, soft sponges, silicon, chassis, and car parts. This company is the biggest provider of construction materials and paints in South Korea. Various types of industrial materials such as epoxy moulding compound, alumina metallizing, silicone etc. are produced in 13 domestic locations. KCC Corporation has 9 overseas liaison offices and 7 overseas factories over the world: KCC Houston (Texas, U.S. - Liaison Office) KCC Tokyo (Tokyo, Japan - Liaison Office) KCC Hong Kong (Hong Kong, China - Liaison Office) KCC Dubai (Dubai, U.A.E. - Liaison Office) KCC Greece (Piraeus, Greece - Liaison Office) KCC Hamburg (Hamburg, Germany - Liaison Office) KCC Iran (Teheran, Iran - Liaison Office) KCC Shanghai (Shanghai, China - Liaison Office) KCC Kunshan (Shanghai, China - Paint Factory) KCC Beijing (Beijing, China - Paint Factory) KCC Guangzhou (Guangzhou, China - Paint Factory) KCC Singapore (Singapore - Paint Factory) KCC Malaysia (Kuala Lumpur, Malaysia - Paint Factory) KCC India (Chennai, India - Paint Factory) KCC Turkey (Istanbul, Turkey - Paint Factory) KCC Poland (Lublin, Poland - Liaison Office) KCC Vietnam (Ho Chi Minh, VietNam - Liaison Office) == Acquisitions == In April 2011, Basildon Chemicals was purchased by the KCC Corporation. KCC expanded into silicone emulsification with the acquisition. In 2024, KCC Corporation acquired U.S.-based Momentive Performance Materials, Inc. for an undisclosed amount. == See also == Economy of South Korea Busan KCC Egis == References == == External links == Official website Business data for KCC:
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{
"page_id": 2817899,
"title": "KCC Corporation"
}
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Well poisoning is the act of malicious manipulation of potable water resources in order to cause illness or death, or to deny an opponent access to fresh water resources. Well poisoning has been historically documented as a strategy during wartime since antiquity, and was used both offensively (as a terror tactic to disrupt and depopulate a target area) and defensively (as a scorched earth tactic to deny an invading army sources of clean water). Rotting corpses (both animal and human) thrown down wells were the most common implementation; in one of the earliest examples of biological warfare, corpses known to have died from common transmissible diseases of the Pre-Modern era such as bubonic plague or tuberculosis were especially favored for well-poisoning. == History of implementation == === Instances of medieval usage === Well poisoning has been used as an important scorched earth tactic at least since medieval times. In 1462, for example, Prince Vlad III the Impaler of Wallachia utilized this method to delay his pursuing adversaries. Nearly 500 years later during the Winter War, the Finns rendered wells unusable by putting animal carcasses or feces in them in order to passively combat invading Soviet forces. === Instances of modern usage === During the 20th century, the practice of poisoning wells has lost most of its potency and practicality against an organized force as modern military logistics ensure secure and decontaminated supplies and resources. Nevertheless, German forces during First World War poisoned wells in France as part of Operation Alberich. After World War 2 Nakam, a paramilitary organisation of about fifty Holocaust survivors, sought revenge for the murder of six million Jews during the Holocaust. The group's leader Abba Kovner went to Mandatory Palestine in order to secure large quantities of poison for poisoning water mains to kill large numbers
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{
"page_id": 1179505,
"title": "Well poisoning"
}
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of Germans. His followers infiltrated the water system of Nuremberg. However, Kovner was arrested upon arrival in the British zone of occupied Germany and had to throw the poison overboard. Israel poisoned the wells and water supplies of certain Palestinian towns and villages as part of their biological warfare program during the 1948 Palestine war, including a successful operation that caused a typhoid epidemic in Acre in early May 1948, and an unsuccessful attempt in Gaza that was foiled by the Egyptians in late May. In the late 20th century, accusations of well-poisoning were brought up, most notoriously in relation to the Kosovo Liberation War. In the 21st century, Israeli settlers have been condemned due to suspicions of poisoning wells of villages in the occupied Palestine. == As libel against Jews == === Medieval accusations against Jews === Despite some vague understanding of how diseases could spread, the existence of viruses and bacteria was unknown in medieval times, and the outbreak of disease could not be scientifically explained. Any sudden deterioration of health was often blamed on poisoning. Europe was hit by several waves of the Black Death throughout the late Middle Ages. Crowded cities were especially hard hit by the disease, with death tolls as high as 50% of the population. In their distress, emotionally distraught survivors searched desperately for an explanation. The city-dwelling Jews of the Middle Ages, living in walled-up, segregated ghetto districts, aroused suspicion. An outbreak of plague thus became the trigger for Black Death persecutions, with hundreds of Jews burned at the stake, or rounded up in synagogues and private houses that were then set aflame. Walter Laqueur writes in his book The Changing Face of Anti-Semitism: From Ancient Times to the Present Day: There were no mass attacks against "Jewish poisoners" after the period
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{
"page_id": 1179505,
"title": "Well poisoning"
}
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of the Black Death, but the accusation became part and parcel of antisemitic dogma and language. It appeared again in early 1953 in the form of the "doctors' plot" in Stalin's last days, when hundreds of Jewish physicians in the Soviet Union were arrested and some of them killed on the charge of having caused the death of prominent Communist leaders... Similar charges were made in the 1980s and 1990s in radical Arab nationalist and Muslim fundamentalist propaganda that accused the Jews of spreading AIDS and other infectious diseases. === Modern instances of antisemitic libel === Allegations of well poisoning entwined with antisemitism have also emerged in the discourse around modern epidemics and pandemics such as swine flu, Ebola, avian flu, SARS, and COVID-19. EU address by Mahmoud Abbas In his address to the European Parliament on 23 June 2016, in Brussels, Palestinian Authority president and PLO chairman Mahmoud Abbas made an unsubstantiated allegation, "accusing rabbis of poisoning Palestinian wells". This was based on false media reports saying Israeli rabbis were inciting the poisoning of water of Palestinians, led by a rabbi Shlomo Mlma or Mlmad from the Council of Rabbis in the West Bank settlements. A rabbi by that name could not be located, nor is such an organization listed. Abbas said: "Only a week ago, a number of rabbis in Israel announced, and made a clear announcement, demanding that their government poison the water to kill the Palestinians ... Isn't that clear incitement to commit mass killings against the Palestinian people?" The speech received a standing ovation. The speech was described as "echoing anti-Semitic claims". A day later, on Saturday 26 June, Abbas admitted that "his claims at the EU were baseless". Abbas' further said that he "didn't intend to do harm to Judaism or to offend Jewish
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{
"page_id": 1179505,
"title": "Well poisoning"
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people around the world." Israeli Prime Minister Benjamin Netanyahu stated in reaction, that Abbas had spread a "blood libel" in his European Parliament address. == See also == Operation Cast Thy Bread Environmental impact of war Groundwater pollution In My Country There Is Problem Jonestown Nakam Water supply terrorism == References == == Works cited == Abu Sitta, Salman (2003). "Traces of Poison–Israel's Dark History Revealed". Al-Ahram Weekly. Retrieved 30 January 2024 – via Palestine Land Society. Ackerman, Gary; Asal, Victor (2008). "A Quantitative Overview of Biological Weapons: Identification, Characterization, and Attribution". In Clunan, Anne; Lavoy, Peter R.; Martin, Susan B. (eds.). Terrorism, War, or Disease?: Unraveling the Use of Biological Weapons. Stanford University Press. pp. 186–213. ISBN 978-0-8047-7981-4. Carus, W. Seth (2017). "A century of biological-weapons programs (1915–2015): reviewing the evidence". The Nonproliferation Review. 24 (1–2): 129–153. doi:10.1080/10736700.2017.1385765. ISSN 1073-6700. S2CID 148814757. Cohen, Avner (2001). "Israel and chemical/biological weapons: History, deterrence, and arms control". The Nonproliferation Review. 8 (3): 27–53. doi:10.1080/10736700108436862. ISSN 1073-6700. S2CID 219623831. Docker, John (2012). "Instrumentalising the Holocaust: Israel, Settler-Colonialism, Genocide (Creating a Conversation between Raphaël Lemkin and Ilan Pappé)". Holy Land Studies. 11 (1): 1–32. doi:10.3366/hls.2012.0027. ISSN 1474-9475. Martin, Susan B. (2010). "The Battlefield Use of Chemical, Biological and Nuclear Weapons from 1945 to 2008: Structural Realist Versus Normative Explanations". American Political Science Association 2010 Annual Meeting Paper. Leitenberg, Milton (2001). "Biological Weapons in the Twentieth Century: A Review and Analysis". Critical Reviews in Microbiology. 27 (4): 267–320. doi:10.1080/20014091096774. ISSN 1040-841X. PMID 11791799. S2CID 33988479. Morris, Benny; Kedar, Benjamin Z. (3 September 2023). "'Cast thy bread': Israeli biological warfare during the 1948 War". Middle Eastern Studies. 59 (5): 752–776. doi:10.1080/00263206.2022.2122448. ISSN 0026-3206. S2CID 252389726. Nashef, Hania A.M. (30 October 2018). Palestinian Culture and the Nakba: Bearing Witness. Taylor & Francis. ISBN 978-1-351-38749-1. Archived from the
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{
"page_id": 1179505,
"title": "Well poisoning"
}
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original on 14 January 2023. Retrieved 2 April 2021. Pappe, Ilan (2006). The Ethnic Cleansing of Palestine. Oneworld Publications. ISBN 978-1-78074-056-0. Sayigh, Rosemary (2009). "Hiroshima, al-Nakba: Markers of New Hegemonies" (PDF). Kyoto Bulletin of Islamic Area Studies. 3 (1): 151–169. == External links == Accusation of Well-Poisoning (Jewish Encyclopedia) The Virtual Jewish History Tour. Belgium
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{
"page_id": 1179505,
"title": "Well poisoning"
}
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Thermal physics is the combined study of thermodynamics, statistical mechanics, and kinetic theory of gases. This umbrella-subject is typically designed for physics students and functions to provide a general introduction to each of three core heat-related subjects. Other authors, however, define thermal physics loosely as a summation of only thermodynamics and statistical mechanics. Thermal physics can be seen as the study of systems with a large number of atoms. It unites thermodynamics and statistical mechanics. == Overview == Thermal physics, generally speaking, is the study of the statistical nature of physical systems from an energetic perspective. Starting with the basics of heat and temperature, thermal physics analyzes the first law of thermodynamics and second law of thermodynamics from the statistical perspective, in terms of the number of microstates corresponding to a given macrostate. In addition, the concept of entropy is studied via quantum theory. A central topic in thermal physics is the canonical probability distribution. The electromagnetic nature of photons and phonons are studied which show that the oscillations of electromagnetic fields and of crystal lattices have much in common. Waves form a basis for both, provided one incorporates quantum theory. Other topics studied in thermal physics include: chemical potential, the quantum nature of an ideal gas, i.e. in terms of fermions and bosons, Bose–Einstein condensation, Gibbs free energy, Helmholtz free energy, chemical equilibrium, phase equilibrium, the equipartition theorem, entropy at absolute zero, and transport processes as mean free path, viscosity, and conduction. == See also == Heat transfer physics Information theory Philosophy of thermal and statistical physics Thermodynamic instruments == References == == Further reading == Callen, Herbert B. (1985). Thermodynamics and an Introduction to Thermostatistics (2nd ed.). Wiley. ISBN 0-471-86256-8. Kroemer, Herbert; Kittel, Charles (1980). Thermal Physics (2nd ed.). W. H. Freeman Company. ISBN 0-716-71088-9. Schroeder, Daniel V.
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{
"page_id": 4063091,
"title": "Thermal physics"
}
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(1999). An Introduction to Thermal Physics. Addison Wesley. ISBN 0-201-38027-7. == External links == Thermal Physics Links on the Web
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{
"page_id": 4063091,
"title": "Thermal physics"
}
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In astrophysics, the Bonnor–Ebert mass is the largest mass that an isothermal gas sphere embedded in a pressurized medium can have while still remaining in hydrostatic equilibrium. Clouds of gas with masses greater than the Bonnor–Ebert mass must inevitably undergo gravitational collapse to form much smaller and denser objects. As the gravitational collapse of an interstellar gas cloud is the first stage in the formation of a protostar, the Bonnor–Ebert mass is an important quantity in the study of star formation. For a gas cloud embedded in a medium with a gas pressure p 0 {\displaystyle p_{0}} , the Bonnor–Ebert mass is given by M B E ( p 0 ) = 225 32 5 π c s 4 ( a G ) 3 / 2 1 p 0 {\displaystyle M_{BE}(p_{0})={225 \over {32{\sqrt {5\pi }}}}{c_{s}^{4} \over {(aG)}^{3/2}}{1 \over {\sqrt {p_{0}}}}} where G is the gravitational constant and c s ≡ k T / μ m H {\displaystyle c_{s}\equiv {\sqrt {kT/{\mu m_{H}}}}} is the isothermal sound speed ( γ = 1 {\displaystyle \gamma =1} ) with μ {\displaystyle \mu } as the molecular mass. a {\displaystyle a} is a dimensionless constant which varies based on the density distribution of the cloud. For a uniform mass density a = 1 {\displaystyle a=1} and for a centrally peaked density a ≈ 1.67 {\displaystyle a\approx 1.67} . == See also == Jeans mass == References ==
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{
"page_id": 14483315,
"title": "Bonnor–Ebert mass"
}
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Tropical vegetation is any vegetation in tropical latitudes. Plant life that occurs in climates that are warm year-round is in general more biologically diverse than in other latitudes. Some tropical areas may receive abundant rain the whole year round, but others have long dry seasons which last several months and may vary in length and intensity with geographic location. These seasonal droughts have a great impact on the vegetation, such as in the Madagascar spiny forests. Rainforest vegetation is categorized by five layers. The top layer being the emergents, or the upper tree layer. Here you will find the largest and widest trees in all the forest, commonly 165 feet (fifty meters) and higher. These trees tend to have very large canopies so they can be fully exposed to sunlight. A layer below that is the canopy, or middle tree layer, averaging 98 to 130 feet (30 to 40 meters) in height. Here you will find more compact trees and vegetation. These trees tend to be more skinny as they are trying to gain any sunlight they can. The third layer is the lower tree area. These trees tend to be around five to ten meters (16 to 33 feet) high and tightly compacted. The trees found in the third layer include young trees trying to grow into the larger canopy trees, and "palmoids" or "Corner Model Trees". The fourth layer is the shrub layer beneath the tree canopy. This layer is mainly populated by sapling trees, shrubs, and seedlings. The fifth and final layer is the herb layer which is the forest floor. The forest floor is mainly bare except for various plants, mosses, Lycopods and ferns. The forest floor is much more dense than above because of little sunlight and air movement. Plant species native to the tropics
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{
"page_id": 38797174,
"title": "Tropical vegetation"
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found in tropical ecosystems are known as tropical plants. Some examples of tropical ecosystems are the Guinean Forests of West Africa, the Madagascar dry deciduous forests and the broadleaf forests of the Thai highlands and the El Yunque National Forest in Puerto Rico. Dr. Ghillean Prance has estimated that, as of 1979, there are 155,000 known species of tropical plants, with 90,000 species in the Neotropics, 35,000 in southern Asia and the East Indies and 30,000 in Africa, about half of those in Madagascar. There are also 50,000 Neotropical Fungi and about 20,000 fungal species each from Asia and Africa. == Description == The term "tropical vegetation" is frequently used in the sense of lush and luxuriant, but not all the vegetation of the areas of the Earth in tropical climates can be defined as such. Despite lush vegetation, often the soils of tropical forests are low in nutrients making them quite vulnerable to slash-and-burn deforestation techniques, which are sometimes an element of shifting cultivation agricultural systems. Tropical vegetation may include the following habitat types: === Tropical rainforest === Tropical rainforest ecosystems include significant areas of biodiversity, often coupled with high species endemism. Rainforests are home to half of all the living animal and plant species on the planet and roughly two-thirds of all flowering plants can be found in rainforests. The most representative are the Borneo rainforest, one of the oldest rainforests in the world, the Brazilian and Venezuelan Amazon Rainforest, as well as the eastern Costa Paulon rainforests. === Tropical seasonal forest === Seasonal tropical forests generally receive high total rainfall, averaging more than 1000 mm per year, but with a distinct dry season. They include: the Congolian forests, a broad belt of highland tropical moist broadleaf forest which extends across the basin of the Congo River; Central
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{
"page_id": 38797174,
"title": "Tropical vegetation"
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American tropical forests in Panama and Nicaragua; the seasonal forests that predominate across much the Indian subcontinent, Indochina, and northern Australia: Queensland. === Tropical dry broadleaf forest === Tropical dry broadleaf forests are territories with a forest cover that is not very dense and has often an unkempt, irregular appearance, especially in the dry season. This type of forest often includes bamboo and teak as the dominant large tree species, such as in the Phi Pan Nam Range, part of the Central Indochina dry forests. They are affected by often long seasonal dry periods and, though less biologically diverse than rainforests, tropical dry forests are home to a wide variety of wildlife. === Tropical grasslands, savannas, and shrublands === Tropical grasslands, savannas, and shrublands are spread over a large area of the tropics with a vegetation made up mainly of low shrubs and grasses, often including sclerophyll species. Some of the most representative are the Western Zambezian grasslands in Zambia and Angola, as well as the Einasleigh upland savanna in Australia and the Everglades in United States of America. Tree species such as Acacia and baobab may be present in these ecosystems depending on the region. == See also == Biocoenosis Ecoregion Jungle Vegetation type == Further reading == Archibold, O. W. Ecology of World Vegetation. New York: Springer Publishing, 1994. Barbour, M.G, J.H. Burk, and W.D. Pitts. "Terrestrial Plant Ecology". Menlo Park: Benjamin Cummings, 1987. Breckle, S-W. Walter's Vegetation of the Earth. New York: Springer Publishing, 2002. Van der Maarel, E. Vegetation Ecology. Oxford: Blackwell Publishers, 2004. Geoff Tracey The Vegetation of the Humid Tropical Region of North Queensland. Australia: CSIRO 1982. Stork, N. E. & Turton, Stephen M. (2008). Living in a dynamic tropical forest landscape. Malden, MA : Blackwell Pub. Leonard Webb A Physiognomic Classification of Australian
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{
"page_id": 38797174,
"title": "Tropical vegetation"
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Rain Forests Journal of Ecology Vol. 47, No. 3, pp. 551-570 (British Ecological Society), 1959 == References == == External links == Classifying Vegetation Condition: Vegetation Assets States and Transitions (VAST)
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{
"page_id": 38797174,
"title": "Tropical vegetation"
}
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Robert Karplus (*February 23, 1927 Vienna; † March 20, 1990) was a theoretical physicist and leader in the field of science education. == Early life == Robert Karplus was born in Vienna, where he lived until the German occupation of Austria in 1938. He emigrated with his mother and brother to escape the Anschluss. After a six-month stay in Switzerland, the family moved to the United States and settled in the Boston area. He entered Harvard University in 1943 and completed his Ph.D at the age of twenty-one. His thesis under E. Bright Wilson was on microwave spectroscopy and included both experimental and theoretical work. He was recognized by those he worked with for his brilliance, originality, energy, and cheerful, positive outlook. His grandfather Johann Paul Karplus (1866–1936) was a highly acclaimed professor of psychiatry at the University of Vienna. He is nephew, by marriage, of the sociologist, philosopher and musicologist Theodor W. Adorno and grandnephew of the physicist Robert von Lieben. His brother is Nobel laureate Martin Karplus, a Harvard chemist. == Early career in physics == After completing his education Karplus worked at the Institute for Advanced Study in Princeton, where he became interested in the developing, but yet untested, theory of quantum electrodynamics (QED). The magnetic moment of the electron had been determined very precisely by means of a variety of experiments, but the best theoretical calculations of this quantity, based on quantum mechanics, were seriously at variance with the experimental results. There was great interest among physicists in knowing whether or not a calculation based on QED would agree with the experimental results, but because of the ambiguities and complexity of QED, no one had so far been able to do such a calculation. Karplus, in collaboration with Norman Kroll, used QED to calculate the value
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{
"page_id": 4390780,
"title": "Robert Karplus"
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of the magnetic moment of the electron. This was an extremely difficult calculation, requiring more than a year of intense effort from both men; the agreement between their result and the experimental measurements was the first, dramatic confirmation of QED. Karplus continued his work at the highest level in theoretical physics for more than 10 years, at Harvard from 1950 to 1954 and then at the University of California, Berkeley, publishing 50 research papers, mostly in QED but also in other areas of physics, including the Hall effect, Van Allen radiation, and cosmic rays. He also thoroughly enjoyed experimental work, investigating the chemistry of Land Camera instant pictures and setting up an experimental germanium purification assembly line for transistors. His paper, with J. M. Luttinger, Hall Effect in Ferromagnetics has over 1100 journal citations. == Family life == In 1948, Karplus married Elizabeth Frazier, whom he had met at an international folk dance group he organized while at Harvard. They had seven children born between 1950 and 1962. When the oldest child, Beverly, was 8, Karplus accepted her invitation to present a science lesson on electricity to her third-grade class, using the Wimshurst machine he had inherited from his grandfather. Unfortunately, while the children enjoyed the demonstration, the lesson was a conceptual disaster. This stimulated Karplus to think about how to teach science better, and as the other children entered school, he continued to visit their classes on a "show and tell" basis with various science experiments or demonstrations. Conversing with his children and their classmates, he became increasingly interested in children's learning, reasoning, and science concept development. His daughter Beverly Karplus Hartline became a noted physicist, science communicator, and academic administrator. == Second career in science education == Within a few years, Karplus had changed careers—from theoretical physics, to
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{
"page_id": 4390780,
"title": "Robert Karplus"
}
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research on science and math learning, and then to curriculum developer. Karplus quickly learned what was already known about the development of thinking and reasoning, studying various psychologists, especially Jean Piaget. Characteristically, Karplus also immediately began generating his own questions about children's thinking, collecting evidence, and developing his own interpretations and explanations of what he observed. Karplus’ new passion coincided, serendipitously, with the post-Sputnik wave of efforts to upgrade US science education. Beginning in the late 50s, many other scientists also devoted themselves to science education and the schools, but Karplus was from the start a leader at the elementary level. Initially there was substantial reluctance at the National Science Foundation (NSF) to fund science curriculum projects at the elementary level, but this was overcome in 1959, when Karplus and three colleagues received the first of many NSF grants for the improvement of science content at the elementary level. This work evolved into a monumental 15-year effort called the Science Curriculum Improvement Study (SCIS). Under the direction of Karplus and Herbert D. Thier, SCIS became a comprehensive, fully tested, hands-on, laboratory-based program in both physical and biological science for grades K-6. Robert Karplus realized the importance of converting the SCIS elementary science materials into a systematic teaching process that would enable teachers to successfully use these materials while enabling students to learn and enjoy science. He, along with others, developed the learning cycle instructional strategy. Karplus extended Piaget's theory to college students and adults; Piaget's theory included four stages, and he had documented children's thinking in great detail, finding that most children made the transition from the 3rd stage (concrete operations) to the 4th stage (abstract reasoning) by about 16 years of age. Karplus, however, extended Piaget's methodology to older groups and found that many of these individuals had important
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{
"page_id": 4390780,
"title": "Robert Karplus"
}
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gaps in their ability to use abstract reasoning in solving scientific, logical, and mathematical problems. His most famous test of proportional reasoning was the Mr. Tall-Mr. Short problem. Karplus further explored and documented the details of college students’ and adults’ thinking as they confronted the issues involved in this critical intellectual transition, finding that many of the issues and problems that he, Piaget, and others had discovered as critical for younger students were still relevant for older individuals, particularly when they were attempting to solve a problem in a discipline that was new to them. In 1977 Karplus was elected president of the American Association of Physics Teachers (AAPT), and in 1978 the National Science Teachers Association awarded him their Citation for Distinguished Service to Science Education. Karplus was chairman of the Graduate Group in Science and Mathematics Education (SESAME) from 1978 to 1980. In 1980 he was awarded the AAPT's highest honor, the Oersted Medal, "for his many contributions to physics teaching at all levels and especially for his work in revealing the implications for physics teaching of research in the development of reasoning." Karplus was appointed the dean of the UC Berkeley Graduate School of Education in 1980. The prestigious Karplus Prize in Chemical Physics at Harvard is named after him. == Later life == In June 1982 while jogging at Green Lake in Seattle, Washington, Karplus suffered a severe cardiac arrest that ended his academic career. After an eight-year illness, he died on March 20, 1990. == Appointments, honors and awards, and books == === Appointments === 1948-50 F. B. Jewett Fellow, Institute of Advanced Study, Princeton University 1950-54 Assistant professor of physics, Harvard University 1954-58 Associate professor of physics, University of California, Berkeley 1958-1982 Professor of Physics, University of California, Berkeley 1960-61 Guggenheim Fellow and Fulbright
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{
"page_id": 4390780,
"title": "Robert Karplus"
}
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Research Grantee 1962-63 Visiting professor, University of Maryland 1969-1982 Associate director, Lawrence Hall of Science 1973-74 Guggenheim Fellow and visiting professor, M. I. T. 1961-77 Director, Science Curriculum Improvement Study 1975-1982 Director, Intellectual Development Project 1976-77 Acting director, Lawrence Hall of Science 1976-1979 Director, CAUSE Project 1978-1980 Chairman, Graduate Group in Science and Mathematics Education (SESAME) 1980 Dean, School of education, University of California, Berkeley (1) (1) He resigned as dean within a few weeks when it became clear he would not be allowed to make changes he believed were necessary. === Honors and awards === Fellow of American Physical Society Distinguished Service Citation, American Association of Physics Teachers, 1972 National Science Teachers Association Award for Distinguished Service to Science Education, 1978 President, American Association of Physics Teachers, 1977 Honorary degree, Doctor of Philosophy, University of Gothenburg, 1980 Oersted Medal, American Association of Physics Teachers, 1981 === Books === R. Karplus and H. D. Thier., A New Look at Elementary School Science. Chicago: Rand McNally and Co., 1967. R. Karplus, Introductory Physics: A Model Approach. W. A. Benjamin, New York, 1969; reissued in 2003 by Fernand Brunschwig (editor), Captains Engineering Services (publisher). R. Karplus (Ed.), Physics and Man, W. A. Benjamin, Inc., New York, 1970. == References == == Further reading == Fuller, Robert G., ed. (2002). A Love of Discovery: Science Education—The Second Career of Robert Karplus. Springer. ISBN 978-0-306-46687-8. Burciaga, Juan R. (April 2007). "Review of A Love of Discovery: Science Education—The Second Career of Robert Karplus by Robert G. Fuller". Am. J. Phys. 75 (4): 383–384. Bibcode:2007AmJPh..75..383F. doi:10.1119/1.2710489. Karplus, Robert (2003). ""Robert Karplus—A Portrait". In Brunschwig, Fernand (ed.). Introductory Physics: A Model Approach (2nd ed.). Captains Engineering Services Inc.
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{
"page_id": 4390780,
"title": "Robert Karplus"
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In deep learning, weight initialization or parameter initialization describes the initial step in creating a neural network. A neural network contains trainable parameters that are modified during training: weight initialization is the pre-training step of assigning initial values to these parameters. The choice of weight initialization method affects the speed of convergence, the scale of neural activation within the network, the scale of gradient signals during backpropagation, and the quality of the final model. Proper initialization is necessary for avoiding issues such as vanishing and exploding gradients and activation function saturation. Note that even though this article is titled "weight initialization", both weights and biases are used in a neural network as trainable parameters, so this article describes how both of these are initialized. Similarly, trainable parameters in convolutional neural networks (CNNs) are called kernels and biases, and this article also describes these. == Constant initialization == We discuss the main methods of initialization in the context of a multilayer perceptron (MLP). Specific strategies for initializing other network architectures are discussed in later sections. For an MLP, there are only two kinds of trainable parameters, called weights and biases. Each layer l {\displaystyle l} contains a weight matrix W ( l ) ∈ R n l − 1 × n l {\displaystyle W^{(l)}\in \mathbb {R} ^{n_{l-1}\times n_{l}}} and a bias vector b ( l ) ∈ R n l {\displaystyle b^{(l)}\in \mathbb {R} ^{n_{l}}} , where n l {\displaystyle n_{l}} is the number of neurons in that layer. A weight initialization method is an algorithm for setting the initial values for W ( l ) , b ( l ) {\displaystyle W^{(l)},b^{(l)}} for each layer l {\displaystyle l} . The simplest form is zero initialization: W ( l ) = 0 , b ( l ) = 0 {\displaystyle W^{(l)}=0,b^{(l)}=0}
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{
"page_id": 78053249,
"title": "Weight initialization"
}
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Zero initialization is usually used for initializing biases, but it is not used for initializing weights, as it leads to symmetry in the network, causing all neurons to learn the same features. In this page, we assume b = 0 {\displaystyle b=0} unless otherwise stated. Recurrent neural networks typically use activation functions with bounded range, such as sigmoid and tanh, since unbounded activation may cause exploding values. (Le, Jaitly, Hinton, 2015) suggested initializing weights in the recurrent parts of the network to identity and zero bias, similar to the idea of residual connections and LSTM with no forget gate. In most cases, the biases are initialized to zero, though some situations can use a nonzero initialization. For example, in multiplicative units, such as the forget gate of LSTM, the bias can be initialized to 1 to allow good gradient signal through the gate. For neurons with ReLU activation, one can initialize the bias to a small positive value like 0.1, so that the gradient is likely nonzero at initialization, avoiding the dying ReLU problem.: 305 == Random initialization == Random initialization means sampling the weights from a normal distribution or a uniform distribution, usually independently. === LeCun initialization === LeCun initialization, popularized in (LeCun et al., 1998), is designed to preserve the variance of neural activations during the forward pass. It samples each entry in W ( l ) {\displaystyle W^{(l)}} independently from a distribution with mean 0 and variance 1 / n l − 1 {\displaystyle 1/n_{l-1}} . For example, if the distribution is a continuous uniform distribution, then the distribution is U ( ± 3 / n l − 1 ) {\displaystyle {\mathcal {U}}(\pm {\sqrt {3/n_{l-1}}})} . === Glorot initialization === Glorot initialization (or Xavier initialization) was proposed by Xavier Glorot and Yoshua Bengio. It was designed as
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{
"page_id": 78053249,
"title": "Weight initialization"
}
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a compromise between two goals: to preserve activation variance during the forward pass and to preserve gradient variance during the backward pass. For uniform initialization, it samples each entry in W ( l ) {\displaystyle W^{(l)}} independently and identically from U ( ± 6 / ( n l + 1 + n l − 1 ) ) {\displaystyle {\mathcal {U}}(\pm {\sqrt {6/(n_{l+1}+n_{l-1})}})} . In the context, n l − 1 {\displaystyle n_{l-1}} is also called the "fan-in", and n l + 1 {\displaystyle n_{l+1}} the "fan-out". When the fan-in and fan-out are equal, then Glorot initialization is the same as LeCun initialization. === He initialization === As Glorot initialization performs poorly for ReLU activation, He initialization (or Kaiming initialization) was proposed by Kaiming He et al. for networks with ReLU activation. It samples each entry in W ( l ) {\displaystyle W^{(l)}} from N ( 0 , 2 / n l − 1 ) {\displaystyle {\mathcal {N}}(0,{\sqrt {2/n_{l-1}}})} . === Orthogonal initialization === (Saxe et al. 2013) proposed orthogonal initialization: initializing weight matrices as uniformly random (according to the Haar measure) semi-orthogonal matrices, multiplied by a factor that depends on the activation function of the layer. It was designed so that if one initializes a deep linear network this way, then its training time until convergence is independent of depth. Sampling a uniformly random semi-orthogonal matrix can be done by initializing X {\displaystyle X} by IID sampling its entries from a standard normal distribution, then calculate ( X X ⊤ ) − 1 / 2 X {\displaystyle \left(XX^{\top }\right)^{-1/2}X} or its transpose, depending on whether X {\displaystyle X} is tall or wide. For CNN kernels with odd widths and heights, orthogonal initialization is done this way: initialize the central point by a semi-orthogonal matrix, and fill the other entries with
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{
"page_id": 78053249,
"title": "Weight initialization"
}
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zero. As an illustration, a kernel K {\displaystyle K} of shape 3 × 3 × c × c ′ {\displaystyle 3\times 3\times c\times c'} is initialized by filling K [ 2 , 2 , : , : ] {\displaystyle K[2,2,:,:]} with the entries of a random semi-orthogonal matrix of shape c × c ′ {\displaystyle c\times c'} , and the other entries with zero. (Balduzzi et al., 2017) used it with stride 1 and zero-padding. This is sometimes called the Orthogonal Delta initialization. Related to this approach, unitary initialization proposes to parameterize the weight matrices to be unitary matrices, with the result that at initialization they are random unitary matrices (and throughout training, they remain unitary). This is found to improve long-sequence modelling in LSTM. Orthogonal initialization has been generalized to layer-sequential unit-variance (LSUV) initialization. It is a data-dependent initialization method, and can be used in convolutional neural networks. It first initializes weights of each convolution or fully connected layer with orthonormal matrices. Then, proceeding from the first to the last layer, it runs a forward pass on a random minibatch, and divides the layer's weights by the standard deviation of its output, so that its output has variance approximately 1. === Fixup initialization === In 2015, the introduction of residual connections allowed very deep neural networks to be trained, much deeper than the ~20 layers of the previous state of the art (such as the VGG-19). Residual connections gave rise to their own weight initialization problems and strategies. These are sometimes called "normalization-free" methods, since using residual connection could stabilize the training of a deep neural network so much that normalizations become unnecessary. Fixup initialization is designed specifically for networks with residual connections and without batch normalization, as follows: Initialize the classification layer and the last layer of each
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{
"page_id": 78053249,
"title": "Weight initialization"
}
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residual branch to 0. Initialize every other layer using a standard method (such as He initialization), and scale only the weight layers inside residual branches by L − 1 2 m − 2 {\displaystyle L^{-{\frac {1}{2m-2}}}} . Add a scalar multiplier (initialized at 1) in every branch and a scalar bias (initialized at 0) before each convolution, linear, and element-wise activation layer. Similarly, T-Fixup initialization is designed for Transformers without layer normalization.: 9 === Others === Instead of initializing all weights with random values on the order of O ( 1 / n ) {\displaystyle O(1/{\sqrt {n}})} , sparse initialization initialized only a small subset of the weights with larger random values, and the other weights zero, so that the total variance is still on the order of O ( 1 ) {\displaystyle O(1)} . Random walk initialization was designed for MLP so that during backpropagation, the L2 norm of gradient at each layer performs an unbiased random walk as one moves from the last layer to the first. Looks linear initialization was designed to allow the neural network to behave like a deep linear network at initialization, since W R e L U ( x ) − W R e L U ( − x ) = W x {\displaystyle W\;\mathrm {ReLU} (x)-W\;\mathrm {ReLU} (-x)=Wx} . It initializes a matrix W {\displaystyle W} of shape R n 2 × m {\displaystyle \mathbb {R} ^{{\frac {n}{2}}\times m}} by any method, such as orthogonal initialization, then let the R n × m {\displaystyle \mathbb {R} ^{n\times m}} weight matrix to be the concatenation of W , − W {\displaystyle W,-W} . == Miscellaneous == For hyperbolic tangent activation function, a particular scaling is sometimes used: 1.7159 tanh ( 2 x / 3 ) {\displaystyle 1.7159\tanh(2x/3)} . This was sometimes called
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{
"page_id": 78053249,
"title": "Weight initialization"
}
|
"LeCun's tanh". It was designed so that it maps the interval [ − 1 , + 1 ] {\displaystyle [-1,+1]} to itself, thus ensuring that the overall gain is around 1 in "normal operating conditions", and that | f ″ ( x ) | {\displaystyle |f''(x)|} is at maximum when x = − 1 , + 1 {\displaystyle x=-1,+1} , which improves convergence at the end of training. In self-normalizing neural networks, the SELU activation function S E L U ( x ) = λ { x if x > 0 α e x − α if x ≤ 0 {\displaystyle \mathrm {SELU} (x)=\lambda {\begin{cases}x&{\text{if }}x>0\\\alpha e^{x}-\alpha &{\text{if }}x\leq 0\end{cases}}} with parameters λ ≈ 1.0507 , α ≈ 1.6733 {\displaystyle \lambda \approx 1.0507,\alpha \approx 1.6733} makes it such that the mean and variance of the output of each layer has ( 0 , 1 ) {\displaystyle (0,1)} as an attracting fixed-point. This makes initialization less important, though they recommend initializing weights randomly with variance 1 / n l − 1 {\displaystyle 1/n_{l-1}} . == History == Random weight initialization was used since Frank Rosenblatt's perceptrons. An early work that described weight initialization specifically was (LeCun et al., 1998). Before the 2010s era of deep learning, it was common to initialize models by "generative pre-training" using an unsupervised learning algorithm that is not backpropagation, as it was difficult to directly train deep neural networks by backpropagation. For example, a deep belief network was trained by using contrastive divergence layer by layer, starting from the bottom. (Martens, 2010) proposed Hessian-free Optimization, a quasi-Newton method to directly train deep networks. The work generated considerable excitement that initializing networks without pre-training phase was possible. However, a 2013 paper demonstrated that with well-chosen hyperparameters, momentum gradient descent with weight initialization was sufficient for training neural
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{
"page_id": 78053249,
"title": "Weight initialization"
}
|
networks, without needing either quasi-Newton method or generative pre-training, a combination that is still in use as of 2024. Since then, the impact of initialization on tuning the variance has become less important, with methods developed to automatically tune variance, like batch normalization tuning the variance of the forward pass, and momentum-based optimizers tuning the variance of the backward pass. There is a tension between using careful weight initialization to decrease the need for normalization, and using normalization to decrease the need for careful weight initialization, with each approach having its tradeoffs. For example, batch normalization causes training examples in the minibatch to become dependent, an undesirable trait, while weight initialization is architecture-dependent. == See also == Backpropagation Gradient descent Vanishing gradient problem == References == == Further reading == Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016). "8.4 Parameter Initialization Strategies". Deep learning. Adaptive computation and machine learning. Cambridge, Mass: The MIT press. ISBN 978-0-262-03561-3. Narkhede, Meenal V.; Bartakke, Prashant P.; Sutaone, Mukul S. (June 28, 2021). "A review on weight initialization strategies for neural networks". Artificial Intelligence Review. 55 (1). Springer Science and Business Media LLC: 291–322. doi:10.1007/s10462-021-10033-z. ISSN 0269-2821.
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{
"page_id": 78053249,
"title": "Weight initialization"
}
|
A masking agent is a reagent used in chemical analysis which reacts with chemical species that may interfere in the analysis. In sports a masking agent is used to hide or prevent detection of a banned substance or illegal drug like anabolic steroids or stimulants. Diuretics are the simplest form of masking agent and work by enhancing water loss via urine excretion and thus diluting the urine, which results in lower concentrations of the banned substance as more of it is being excreted from the body making it more difficult for laboratories to detect. == References == "Masking agent (chemistry) - Britannica Online Encyclopedia". Retrieved 2007-11-09.
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{
"page_id": 14155649,
"title": "Masking agent"
}
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In pharmacology, an antitarget (or off-target) is a receptor, enzyme, or other biological target that, when affected by a drug, causes undesirable side-effects. During drug design and development, it is important for pharmaceutical companies to ensure that new drugs do not show significant activity at any of a range of antitargets, most of which are discovered largely by chance. Among the best-known and most significant antitargets are the hERG channel and the 5-HT2B receptor, both of which cause long-term problems with heart function that can prove fatal (long QT syndrome and cardiac fibrosis, respectively), in a small but unpredictable proportion of users. Both of these targets were discovered as a result of high levels of distinctive side-effects during the marketing of certain medicines, and, while some older drugs with significant hERG activity are still used with caution, most drugs that have been found to be strong 5-HT2B agonists were withdrawn from the market, and any new compound will almost always be discontinued from further development if initial screening shows high affinity for these targets. Agonism of the 5-HT2A receptor is an antitarget because 5-HT2A receptor agonists are associated with hallucinogenic effects. According to David E. Nichols, "Discussions over the years with many colleagues working in the pharmaceutical industry have informed me that if upon screening a potential new drug is found to have serotonin 5-HT2A agonist activity, it nearly always signals the end to any further development of that molecule." There are some exceptions however, for instance efavirenz and lorcaserin, which can activate the 5-HT2A receptor and cause psychedelic effects at high doses. The growth of the field of chemoproteomics has offered a variety of strategies to identify off-targets on a proteome wide scale. == See also == Off-target activity == References ==
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{
"page_id": 24510339,
"title": "Antitarget"
}
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Most Favored Nation Drug Pricing is a policy advanced during the first and second Trump administrations in which drug prices in the United States are tied to foreign drug prices. == Background == Prescription drug prices in the United States are much higher than costs abroad. Many other countries have a centralized drug negotiation in which pharmaceutical companies are forced to give a single deal to the whole country. The US also has high costs from Pharmacy Benefit Managers which negotiate rebates which drug manufactures but do not pass these savings on to consumers. Trump framed the resulting system as the U.S. being forced to subsidize the cost of pharmaceutical research and other nations not paying their fair share. In between the two Trump terms, the Biden administration passed the Inflation Reduction Act which allowed Medicare to negotiate prices for some drugs. == First term == During Trump's first term he sought to bring American drug costs in line with other nations. Republican congressman Rick Scott introduced an MFN pricing bill to congress but failed to gain support. Democratic congresswoman Nancy Pelosi also introduced a bill for Medicare to negotiate prices with caps based on what other countries pay; however, she did not use the MFN terminology. HHS published new rules which applied MFN pricing to certain Medicare Part B drugs as a demonstration program on November 27, 2020. However, policy was quickly shut down by courts because the White House failed to follow the Administrative Procedures Act. The Biden administration subsequently removed the original MFN policy. PhRMA lobbyists opposed any form of structuring drug prices based on what other nations pay. == Second term == Executive Order 14297, titled Delivering Most-Favored-Nation Prescription Drug Pricing to American Patients, was signed on May 12, 2025. The order aims to reduce the
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{
"page_id": 80019332,
"title": "Most Favored Nation Drug Pricing"
}
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cost of prescription drugs by directing federal agencies to link U.S. prices to the lower prices paid for the same drugs in a group of other developed countries. He stated that the policy would reduce prescription drug prices significantly and end the U.S. "subsidizing the health care of foreign countries." He claimed prices could fall by 30% to 80% or even more. The order directs the Department of Health and Human Services to communicate price targets to pharmaceutical manufacturers and, if necessary, pursue rulemaking to impose MFN pricing across the U.S. healthcare system, including commercial markets, Medicare, and Medicaid. It also instructs the Department of Commerce, along with the U.S. Trade Representative, to take action against other nations that Trump claims are pursing unfair practices to keep down drug prices. A different EO, which Trump signed in April 2025, directed the Food and Drug Administration to open up a re-importation process to bring drugs from Canada to the United States. This new EO directs the FDA to expand the reimportation program to other nations. During the announcement for Executive Order 14297 Mehmet Oz, the Medicare and Medicaid administrator, noted that prices negotiated under existing Medicare rules still tend to be higher than what European systems pay. === Implementation === Prior to this Executive Order the Trump administration tried to pressure congress to include MFN pricing for Medicare in legislation, but Republican representatives opposed cutting Medicaid costs. PhRMA, the largest political force for the pharmaceutical industry, estimated that MFN pricing for Medicaid would cost the industry $1 trillion over the next decade. Stephen Ubl, the group's leader, particularly opposed the re-importation expansion. He said, "importing foreign prices from socialist countries would be a bad deal for American patients and workers". PhRMA did support Trump for targeting other countries that they believe
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{
"page_id": 80019332,
"title": "Most Favored Nation Drug Pricing"
}
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are not paying enough for drugs. AARP released a statement supporting the new EO, but the Wall Street Journal called out that important details were missing on how it could be implemented. Pharmaceutical industry executives and Republican representatives warned that reducing drug prices could stifle innovation. In a follow up interview, HHS Secretary Robert Kennedy stated he expects price reductions to apply to Medicare and private markets. On May 20, HHS released follow up guidance, "The MFN target price is the lowest price in an OECD country with a GDP per capita of at least 60 percent of the U.S. GDP per capita." It is unclear how these changes will impact the existing agenda for Medicare price negotiations. A Dutch expert noted that it may be difficult to compare US drug prices to prices paid by European countries as the specific price negotiated for a given drug is often kept secret. The impact on foreign drug manufactures is unclear. JP Morgan's analyst stated that the new policy would also be difficult to implement due to expected legal challenges. == References ==
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{
"page_id": 80019332,
"title": "Most Favored Nation Drug Pricing"
}
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The Urech hydantoin synthesis is the chemical reaction of amino acids with potassium cyanate and hydrochloric acid to give hydantoins. == Reaction mechanism == == See also == Bucherer–Bergs reaction == References == == External links == [1] English translation of 1873 German article 'on lactyl amino acids and lactyl ureas' by Friedrich Urech
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{
"page_id": 7536517,
"title": "Urech hydantoin synthesis"
}
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The Abdus Salam International Centre for Theoretical Physics (ICTP) is a research center for physical and mathematical sciences, located in Trieste, Friuli-Venezia Giulia, Italy. The center operates under a tripartite agreement between the Italian Government, UNESCO, and the International Atomic Energy Agency. It is located near the Miramare Park, about 10 kilometres from the downtown of Trieste city, Italy. The centre was founded in 1964 by Pakistani Nobel Laureate Abdus Salam. ICTP is part of the Trieste System, a network of national and international scientific institutes in Trieste, promoted by the Italian physicist Paolo Budinich. == Mission == Foster the growth of advanced studies and research in physical and mathematical sciences, especially in support of excellence in developing countries; Develop high-level scientific programmes keeping in mind the needs of developing countries, and provide an international forum of scientific contact for scientists from all countries; Conduct research at the highest international standards and maintain a conducive environment of scientific inquiry for the entire ICTP community. == Research == Research at ICTP is carried out by seven scientific sections: High Energy, Cosmology and Astroparticle Physics Condensed Matter and Statistical Physics Mathematics Earth System Physics Science, Technology and Innovation Quantitative Life Sciences New Research Areas (which includes studies related to Energy and Sustainability and Computing Sciences) The scientific community at ICTP includes staff research scientists, postdoctoral fellows and long- and short-term visitors engaged in independent or collaborative research. Throughout the year, the sections organize conferences, workshops, seminars and colloquiums in their respective fields. ICTP also has visitor programmes specifically for scientific visitors from developing countries, including programmes under federation and associateship schemes. == Postgraduate programmes == ICTP offers educational training through its pre-PhD programmes and degree programmes (conducted in collaboration with other institutes). Pre-PhD programmes Postgraduate diploma programmes in Condensed Matter Physics, High
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{
"page_id": 4194183,
"title": "International Centre for Theoretical Physics"
}
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Energy Physics, Mathematics, Earth System Physics, and Quantitative Life Sciences for students from developing countries. The Sandwich Training Educational Programme (STEP) for students from developing countries already enrolled in PhD programmes in the fields of physics and mathematics. In collaboration with other institutes, ICTP offers masters and doctoral degrees in physics and mathematics. Joint ICTP/SISSA PhD Programme in Physics and Mathematics Joint PhD Programme in Earth Science and Fluid Mechanics Joint Laurea Magistralis in Physics Joint ICTP/Collegio Carlo Alberto Program in Economics International Master, Physics of Complex Systems Master of Advanced Studies in Medical Physics Masters in High Performance Computing In addition, ICTP collaborates with local laboratories, including Elettra Synchrotron Light Laboratory, to provide fellowships and laboratory opportunities. == Prizes and awards == ICTP has instituted awards to honour and encourage high-level research in the fields of physics and mathematics. The Dirac Medal – For scientists who have made significant contributions to theoretical physics. The ICTP Prize – For young scientists from and working in developing countries. ICO/ICTP Gallieno Denardo Award – For significant contributions to the field of optics. The Ramanujan Prize – For young mathematicians from developing countries. The Walter Kohn Prize – Given jointly by ICTP and the Quantum ESPRESSO foundation, for work in quantum mechanical materials or molecular modelling, performed by a young scientist working in a developing country. == Partner institutes == One of ICTP's goals is to set up regional centres of excellence around the globe. The idea is to bring ICTP's unique blend of high-quality physics and mathematics education and high-level science meetings closer to scientists everywhere. On February 6, 2012, ICTP opened a partner institute (ICTP South American Institute for Fundamental Research) in São Paulo, Brazil. Its activities are modelled on those of the ICTP and include schools and workshops, as well
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{
"page_id": 4194183,
"title": "International Centre for Theoretical Physics"
}
|
as a visiting scientists programme. On October 18, 2018, a partner institute (ICTP-EAIFR, the East African Institute for Fundamental Research), was inaugurated in Kigali, Rwanda. In November 2018, ICTP opened the International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) in Beijing, China, in collaboration with the University of the Chinese Academy of Sciences. == Journal == In 2007 ICTP created the peer-reviewed open-access Journal "African Review of Physics" under the then name "African Physical Review". == See also == International School for Advanced Studies University of Trieste Joint Institute for Nuclear Research Institute for Theoretical Physics (disambiguation) Center for Theoretical Physics (disambiguation) == References == == External links == Media related to International Centre for Theoretical Physics at Wikimedia Commons Official website
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{
"page_id": 4194183,
"title": "International Centre for Theoretical Physics"
}
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Slime Rancher is a farm life sim video game developed and published by American indie studio Monomi Park. The game was released as an early access title in January 2016, with an official release on Windows, macOS, Linux and Xbox One on August 1, 2017. A PlayStation 4 version was released on August 21, 2018, and a Nintendo Switch version was released on August 11, 2021. A DLC named 'Slime Rancher: Secret Style Pack' was released on June 18, 2019 which added additional cosmetic appearances. A sequel, Slime Rancher 2, was released in early access on September 22, 2022, for Windows and Xbox Series X/S. A feature film adaptation is also in development. == Gameplay == The game is played in an open world and from a first-person perspective. The player controls a character named Beatrix LeBeau, a rancher who moves to a planet far from Earth called the Far Far Range to live the life of a "slime rancher", which consists of constructing her ranch and exploring the world of the Far Far Range in order to collect, raise, feed, and breed slimes. Slimes are gelatinous living organisms of various sizes and characteristics. To progress she has notes left by the former owner of the ranch that help her on her journey through the Far Far Range. The game's main economic aspect revolves around feeding slimes the appropriate food items so that they produce "plorts", which can then be sold in exchange for Newbucks, which can be used to purchase upgrades to the rancher's equipment or farm buildings. With the exception of the basic pink slime, slimes will only eat one of the three types of food; fruit, veggie, or meat. Each slime also has a favorite food, which will lead the slime to produce twice the amount of
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{
"page_id": 49348494,
"title": "Slime Rancher"
}
|
plorts when eaten. The player moves the character around a variety of environments and is able to collect a variety of slimes, food items, and plorts by sucking them up with their vacuum tool (called a "Vacpack", a portmanteau of vacuum and backpack). They can only store a limited number of items and item types at a time and must unload their collected items before being able to collect more. The player must buy and upgrade various enclosures to house their collected slimes and farms for storing their food. Upgrades can also be aesthetic upgrades to the character's home, Vacpack, and the ranch itself. Two types of slimes can be combined and enlarged by feeding a slime a plort from another species, making them noticeably larger, combining their physical characteristics, and allowing them to produce two plorts when fed, one plort of each of their base slimes. They also share the favorite food of each of their base slimes. These hybrid slimes are known as "Largos". However, if a Largo slime consumes a plort different from either species of slime it is made of, it becomes an aggressive malevolent black slime called the "Tarr", which converts attacked slimes around it to Tarrs, as well as being able to damage the player. The player can pump fresh water from ponds and springs to splash and disintegrate the Tarrs. There are different kinds of slimes in the game, each species differing in traits, ranging in complexity from simple ears, colors, wings, and tails, to the ability to teleport or grab items via a vine that emerges from the ground. Some of the types of slimes available in game include docile, harmful, non-farmable, and feral. Most slimes also have a "Gordo" version of themselves, which can be found in various hidden areas across
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{
"page_id": 49348494,
"title": "Slime Rancher"
}
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the Far Far Range. These Gordos are extremely large and cannot move around like regular or Largo slimes. Players can shoot food items at them until they explode (50 of their food type, or 25 of their favorite food), leaving behind normal versions of the Gordo slime's species and crates containing random loot and either a teleporter or "slime key" which allow access to new areas or shortcuts between known areas. == Development == Development of Slime Rancher started in Popovich's apartment. As Popovich was an artist and designer rather than a programmer, he relied on other people's code to create a prototype of the game. He eventually enlisted technical director Mike Thomas to help with the programming. They worked on the game for eight hours a day, a practice Popovich used with employees of Monomi Park to avoid crunch. The game was initially due to enter early access after a year, but was delayed by six months. == Reception == The Early Access version of the Slime Rancher received generally positive reviews. Heather Alexandra from Kotaku noticed some bugs, but gave the game a positive review, saying that "I'm not usually a fan of games with catharsis but when I return to my bright and goofy farm at the end of the day? I can't help but smile as wide as my slimy little friends." [sic] Steve Neilsen from Games Mojo awarded it 4.5 out of 5 stars, stating that "Slime Rancher is fun and addictive game, with a fun premise and cute creatures. The cartoon style graphics look amazing, and gameplay is clever and full of cute." The full release of the game got a score of 81/100 on Metacritic, with reviewers saying it had the ability to keep you hooked for hours. Reviewers also said it was
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{
"page_id": 49348494,
"title": "Slime Rancher"
}
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relaxing and cathartic, but quite repetitive, and successfully taps into the addictive nature of farming simulators. By May 2017, the game had sold over 800,000 copies. By February 28, 2019, the game had sold 2 million copies. By January 13, 2022, the game had sold over 5 million copies. In Game Informer's Reader's Choice Best of 2017 Awards, the game tied in third place along with Forza Motorsport 7 for "Best Microsoft Game", while it came in second place for "Best Simulation Game". The website also gave it the award for the latter category in their Best of 2017 Awards. === Accolades === == Film adaptation == In August 2023, Deadline reported that a film adaptation of the video game was in the works within Derek Kolstad, Dmitri M. Johnson, and Mike Goldberg's Story Kitchen. == References == == External links == Official website
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{
"page_id": 49348494,
"title": "Slime Rancher"
}
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Small RNA (sRNA) are polymeric RNA molecules that are less than 200 nucleotides in length, and are usually non-coding. RNA silencing is often a function of these molecules, with the most common and well-studied example being RNA interference (RNAi), in which endogenously (from within the organism) expressed microRNA (miRNA) or endogenously/exogenously (from outside the organism) derived small interfering RNA (siRNA) induces the degradation of complementary messenger RNA. Other classes of small RNA have been identified, including piwi-interacting RNA (piRNA) and its subspecies repeat associated small interfering RNA (rasiRNA). Small RNA "is unable to induce RNAi alone, and to accomplish the task it must form the core of the RNA–protein complex termed the RNA-induced silencing complex (RISC), specifically with Argonaute protein".: 366 Small RNA have been detected or sequenced using a range of techniques, including directly by MicroRNA sequencing on several sequencing platforms, or indirectly through genome sequencing and analysis. Identification of miRNAs has been evaluated in detecting human disease, such as breast cancer. Peripheral blood mononuclear cell (PBMC) miRNA expression has been studied as potential biomarker for different neurological disorders such as Parkinson's disease, Multiple sclerosis. Evaluating small RNA is useful for certain kinds of study because its molecules "do not need to be fragmented prior to library preparation".: 162 == Discovery == The first sRNA discovered was in 1984 where MicF was found to regulate the outer cell membrane in E. Coli by inhibiting the production of the protein ompF and ompC. The use of sRNA in regulation of gene expression was found alongside it's discovery. It was later discovered to be present across all eukaryotic organisms. In 1998 it was discovered that the sRNA can be transferred between organisms. It was later discovered in 2011 that sRNA are transferred from cell to cell inside an organism as well.
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{
"page_id": 196498,
"title": "Small RNA"
}
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== Types of Small RNA == microRNA (miRNA) - an RNA involved in RNAi through gene regulation as well as mRNA degradation Piwi-interacting RNA (piRNA) - an RNA that regulates the germ line, transposons, as well as histones. It also participates in the argonaute complex. QDE-2 interfering RNA (qiRNA) - an RNA that regulates gene expression after DNA damage Short hairpin RNA (shRNA) - an RNA that acts similarly to miRNA, regulating gene expression via RISC small interfering RNA (siRNA) - an RNA that regulates both gene expression with RISC and by histone modifications. small nuclear RNA (snRNA), also commonly referred to as U-RNA - an RNA integral to the splicosome, that also stabilizes mRNA small nucleolar RNA (snoRNA) - an RNA regulates the rRNA as well as aiding alternative splicing. It also aids in mRNA degradation. small rDNA-derived RNA (srRNA) - an RNA involved in multiple signaling pathways as well as the formation of Argonaute protein complexes. tRNA-derived stress induced RNA (tiRNA) - an RNA that regulates translation by binding to ribosomes. tRNA fragment (tRF) - an RNA fragment that regulates translation by binding to ribosomes and altering mRNA's caps. It can also combine with Argonaute protein complexes to degrade mRNA. Y RNA-derived small RNA (ysRNA) - an RNA that aids in initiaion of DNA replication as well as preventing mRNA from degrading. == In plants == The first known function in plants was discovered in mutants of Arabidopsis. Specifically with decline in function mutations for RNA-dependent RNA polymerase and DICER-like production. This impairment actually enhanced Arabidopsis resistance against Heterodera schachtii and Meloidogyne javanica. Similarly, mutants with reduced Argonaute function - ago1-25, ago1-27, ago2-1, and combined mutants with ago1-27 and ago2-1 - had greater resistance to Meloidogyne incognita. Altogether this demonstrates great dependence of nematode parasitism on plants' own
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{
"page_id": 196498,
"title": "Small RNA"
}
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small RNAs. == References ==
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{
"page_id": 196498,
"title": "Small RNA"
}
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Neptunium chloride may refer to: Neptunium(III) chloride (neptunium trichloride), NpCl3 Neptunium(IV) chloride (neptunium tetrachloride), NpCl4
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{
"page_id": 79495060,
"title": "Neptunium chloride"
}
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NeuroSolutions is a neural network development environment developed by NeuroDimension. It combines a modular, icon-based (component-based) network design interface with an implementation of advanced learning procedures, such as conjugate gradients, the Levenberg-Marquardt algorithm, and back-propagation through time. The software is used to design, train, and deploy artificial neural network (supervised learning and unsupervised learning) models to perform a wide variety of tasks such as data mining, classification, function approximation, multivariate regression and time-series prediction. == Neural network construction wizards == NeuroSolutions provides three separate wizards for automatically building neural network models: === Data Manager === The Data Manager module allows the user to import data from Microsoft Access, Microsoft Excel or text files and perform various preprocessing and data analysis operations. From the Data Manager, the user can load the data directly into a NeuroSolutions breadboard or use the data to create a new neural network. === NeuralBuilder === The NeuralBuilder centers the design specifications on the specific neural network architecture the user wishes to build. Some of the most common architectures include: Multilayer perceptron (MLP) Generalized feedforward Modular (programming) Jordan/Elman Principal component analysis (PCA) Radial basis function network (RBF) General regression neural network (GRNN) Probabilistic neural network (PNN) Self-organizing map (SOM) Time-lag recurrent network (TLRN) Recurrent neural network CANFIS network (Fuzzy logic) Support vector machine (SVM) Once the neural network architecture is selected, the user can customize parameters such as the number of hidden layers, the number of processing elements and the learning algorithm. A genetic algorithm can also be used to automatically optimize the settings. === Neural Expert === The Neural Expert centers the design specifications around the type of problem the user would like the neural network to solve (classification, prediction, function approximation or clustering). Given this problem type and the size of the user's data set,
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{
"page_id": 4390806,
"title": "NeuroSolutions"
}
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the Neural Expert automatically selects the neural network size and architecture that will likely produce a good solution. A beginner setting also exists which hides some of the more advanced operations such as cross validation and genetic optimization. === User-defined neural networks === NeuroSolutions is based on the concept that neural networks can be broken down into a fundamental set of neural components. Individually these components are relatively simplistic, but several components connected together can result in networks capable of solving very complex problems. The network construction wizards will connect these components based on the user's specifications. However, once the network is built, the interconnections can be arbitrarily changed and components can be added or removed. NeuroSolutions also allows for the integration of algorithms through dynamic link libraries (DLL). Every NeuroSolutions component implements a function conforming to a simple protocol in C. To add a new component, modify the template function for the base component and then compile the code into a DLL. == Neural network deployment == NeuroDimension, Inc. provides three ways for NeuroSolutions to deploy a custom neural network solution for applications: code generation, DLL generation, and OLE generation. === Code generation === NeuroSolutions can automatically generate C++ source code for a neural network designed within its graphical user interface. This provides the flexibility to customize the neural network code for that particular application. Since the generated code is ANSI-compliant, the user can deploy the neural network solution to other platforms such as UNIX. === DLL generation === The Custom Solution Wizard is an optional add-on product that will take a neural network designed within NeuroSolutions and encapsulate it into a dynamic link library (DLL) that conforms to a simple protocol. The DLL can then be embedded into the user's own C++, Visual Basic, Microsoft Excel, Microsoft Access
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{
"page_id": 4390806,
"title": "NeuroSolutions"
}
|
or Internet (ASP) application, without requiring advanced programming skills. === OLE automation === This technology provides the ability to programmatically control NeuroSolutions from any external application that supports automation, such as Microsoft Excel, Microsoft Access, and applications developed with Visual Basic or Visual C++. In the simplest case, the application developer could send NeuroSolutions the data to process, tell it to begin processing, and then retrieve the results back into the application. However, with its extensive protocol, NeuroSolutions can also do more complex tasks. == See also == Machine learning == References ==
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{
"page_id": 4390806,
"title": "NeuroSolutions"
}
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In systematics, an ideotype is a specimen identified as belonging to a specific taxon by the author of that taxon, but collected from somewhere other than the type locality. The concept of ideotype in plant breeding was introduced by Donald in 1968 to describe the idealized appearance of a plant variety. It literally means 'a form denoting an idea'. According to Donald, an ideotype is a biological model which is expected to perform or behave in a particular manner within a defined environment: "a crop ideotype is a plant model, which is expected to yield a greater quantity or quality of grain, oil or other useful product when developed as a cultivar." Donald and Hamblin (1976) proposed the concepts of isolation, competition and crop ideotypes. Market ideotype, climatic ideotype, edaphic ideotype, stress ideotype and disease/pest ideotypes are its other concepts. The term ideotype has the following synonyms: model plant type, ideal model plant type and ideal plan type. The term is also used in cognitive science and cognitive psychology, where Ronaldo Vigo (2011, 2013, 2014) introduced it to refer to a type of concept metarepresentation that is a compound memory trace consisting of the structural information detected by humans in categorical stimuli. == Notes ==
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{
"page_id": 13500312,
"title": "Ideotype"
}
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Frondosity (from Latin frondōsus meaning 'leafy') is the property of an organism that normally flourishes with fronds or leaf-like structures. Many frondose organisms are thalloid and lack the organization of tissues into organs, with the exception of ferns. Frondosity is significant mainly for distinguishing particular types of macroscopic algae, and in paleobotany and paleontology, by analyzing features present in fossil biota. Frondose macroalgae are relevant to the ecology of many marine and coastal ecosystems. Large frondose algae play an important role in the creation and functioning of healthy ecosystems from kelp forests to similar habitats. Yet, in coral reefs, frondose seaweed can be recognized as harmful due to the link between excessive blooms and coastal eutrophication. == Ediacaran biota == The fossil record from the Ediacaran Period is sparse, as more easily fossilized hard-shelled animals had yet to evolve. Most fossils of the time are only faint impressions, and the shapes of fronds are one of the few identifying traits available. Frondose fossils are the longest studied of any Ediacaran remains, but, despite this, their affinities and biology are amongst the most controversial, ranging from animal to protist to plant or stem fungi. The oldest members of the Ediacaran biota include discoid (disk-shaped) and frondose forms. Discoidal fossils had been classified as cnidarian medusae before being redefined as holdfasts of frondose organisms, that is, the roots or stalks that held them to the sea bed. Rangeomorphs consist of branching "frond" elements, each a few centimeters long, each of which is itself composed of many smaller branching tubes held up by a semi-rigid organic skeleton. This self-similar structure proceeds over four levels of fractality, and could have been formed using fairly simple developmental patterns. Rangeomorphs were radially symmetrical and likely sessile. == Bryozoans == Bryozoans, marine invertebrates, grow in colonial structures.
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{
"page_id": 57540506,
"title": "Frondose"
}
|
The patterns of growth may be used for identification. One of the identifiable forms of bryozoan colonies, is frondose. Frondose colonies are erect and have branches that are flattened like leaves. These frond-bearing bryozoans existed in both ancient and modern times. Large tree-like forms flourished in the Triassic and Cretaceous, although frondose forms saw a decline in the Jurassic. A notable modern bryozoan with seaweed-like fronds is Flustra foliacea. == References ==
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{
"page_id": 57540506,
"title": "Frondose"
}
|
The World Uranium Hearing was held in Salzburg, Austria in September 1992.Anti-nuclear speakers from all continents, including indigenous speakers and scientists, testified to the health and environmental problems of uranium mining and processing, nuclear power, nuclear weapons, nuclear tests, and radioactive waste disposal. People who spoke at the 1992 Hearing include: Thomas Banyacya, Katsumi Furitsu, Manuel Pino and Floyd Red Crow Westerman. They said they were deeply dismayed by the atomic bombings of Hiroshima and Nagasaki and highlighted what they called the inherently destructive nature of all phases of the nuclear supply chain. They recalled the disastrous impact of nuclear weapons testing in places such as the Nevada Test Site, Bikini Atoll and Eniwetok, Tahiti, Maralinga, and Central Asia. They highlighted the threat of radioactive contamination to all peoples, especially indigenous communities and said that their survival requires self-determination and emphasis on spiritual and cultural values. Increased renewable energy commercialization was advocated. The proceedings were published as a book, Poison fire, sacred earth testimonies, lectures, conclusions. The outcome document, the Declaration of Salzburg was accepted by the United Nations Working Group on Indigenous Populations. == See also == International Uranium Film Festival Uranium in the environment History of the anti-nuclear movement The Navajo People and Uranium Mining Uranium mining debate List of Nuclear-Free Future Award recipients Hibakusha == References ==
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{
"page_id": 40435613,
"title": "World Uranium Hearing"
}
|
Evert Johannes Willem Verwey, also Verweij, (April 30, 1905 in Amsterdam – February 13, 1981 in Utrecht) was a Dutch chemist, who also did research in physical chemistry. Verwey studied chemistry at the University of Amsterdam and obtained his MSc (Dutch: Doctoraal Examen) in 1929. From 1931 he worked as an assistant at the University of Groningen, where he obtained his PhD under the guidance of Hugo Rudolph Kruyt (1934, cum laude). In 1934 he moved to the Philips Laboratories in Eindhoven. He continued work on colloids, which was also the topic of his dissertation, and on oxides. The Verwey transition in magnetite is named after him. Some of his studies on transition metal oxides (carried out jointly with Jan Hendrik de Boer) showed that some transition-metal oxides had electrical properties that could not be explained on the basis of band theory. Between 1946 and 1967, together with physicist Hendrik Casimir and the engineer Herre Rinia, he was director of the Laboratories. He is known for DLVO theory, a theory of the interaction of charged surfaces in fluids, which has applications, for example, in the description of colloids. In 1949 he became a member of the Royal Netherlands Academy of Arts and Sciences. In 1967 he was awarded an honorary doctorate by the Delft University of Technology. He was also a curator at the University of Utrecht. He was married to the sociologist and politician Hilda Verwey-Jonker (1908–2004). == See also == Charge ordering Metal–insulator transition == References == == External links == Verwey's biography in the 1981-1982 Yearbook of the Dutch Royal Academy of Sciences (in Dutch)
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{
"page_id": 45547423,
"title": "Evert Verwey"
}
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The molecular formula C28H42O2 (molar mass: 410.63 g/mol, exact mass: 410.3185 u) may refer to: Tocotrienols β-Tocotrienol γ-Tocotrienol
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{
"page_id": 36175775,
"title": "C28H42O2"
}
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The A.N. Nesmeyanov Institute of Organoelement Compounds of Russian Academy of Sciences (INEOS RAS) (Russian: Институт элементоорганических соединений Российской Академии Наук им. А.Н. Несмеянова (ИНЭОС РАН)) is a research centre founded in 1954 by the president of the USSR Academy of Sciences, Alexander Nesmeyanov. After his exit, the institute was ran by A.V. Fokin from 1980 to 1988, M.E. Vol’pin (1989-1996), Yu.N.Bubnov (1996-2013), A.M. Muzafarov (2013-2018), and A.A. Trifonov (2018) In 2019 and 2020 scientific journal "Journal of Organometallic Chemistry" decided to publish two special issues on the occasion of the 120th anniversary of the famous Russian organometallic chemist Alexander N. Nesmeyanov and the occasion of the 70th birthday of professor Elena Shubina, to note the scientific contribution of scientists in organometallics and the field of non-covalent interactions (Shubina). == External links ==
|
{
"page_id": 29949856,
"title": "Nesmeyanov Institute of Organoelement Compounds"
}
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Isotropic radiation is radiation that has the same intensity regardless of the direction of measurement, such as what would be found in a thermal cavity. This can be electromagnetic radiation, sound, or elementary particles. == References ==
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{
"page_id": 1965987,
"title": "Isotropic radiation"
}
|
SH3BP2 (SH3 domain-binding protein 2) is a protein that comes from a gene located on Chromosome 4. It is widely expressed in hematopoietic cells, including: Macrophages, B and T lymphocytes, and osteoclast precursors. SH3BP2 has an N-terminal pleckstrin homology domain to bind differentially to the SH3 domains of certain proteins of signal transduction pathways, as well as a proline-rich domain and a C-terminal Src homology domain. It functions as an adaptor protein involved in signaling pathways, in concert with SRC kinases, SYK, and PLCγ, affecting immune cell activation, inflammatory signaling, and bone metabolism-- it is also associated with cherubism. It binds to phosphatidylinositol, linking the hemopoietic tyrosine kinase fes to the cytoplasmic membrane in a phosphorylation-dependent mechanism. == SH3BP2 Role in Osteoclast Genesis == A gain-of-function mutation in the protein's exon 9 region leads to several common mutations that affect its proline-rich domain, resulting in its hyperactivation. This upregulation of SH3BP2 increases osteoclast formation and activity, causing bone reabsorption and cyst-like lesions in a TNF-α-dependent mechanism. Mutated SH3BP2 can lead to upregulation of pro-inflammatory cytokines, including Tumor Necrosis Factor-alpha (TNF-α), interleukin 1-beta (IL-1β), and RANKL, creating a positive feedback loop furthering osteoclast activation. == SH3BP2 role in Gastrointestinal Stromal Tumors == SH3BP2 is a key regulator in the growth and survival of gastrointestinal stromal tumors. It supports the expression of two transcriptional factors, ETV1 and MITF, and receptor kinases, KIT and PDGFRA. There are certain therapies for GISTs that involve silencing SH3BP2 to reduce the expression of the receptor kinases KIT and PDGFRA, which are commonly mutated and drive GISTs development. The silencing of the adaptor protein, SH3BP2, also indirectly downregulates ETV1 and MITF, through miRNA-mediated post-transcriptional repression. == References == == See also == SH3 domain == External links == GeneReviews/NCBI/NIH/UW entry on Cherubism SH3BP2+protein,+human at the U.S. National
|
{
"page_id": 12255140,
"title": "SH3BP2"
}
|
Library of Medicine Medical Subject Headings (MeSH) Genetics Home Reference on SH3BP2
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{
"page_id": 12255140,
"title": "SH3BP2"
}
|
In molecular biology mir-544 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms. == See also == MicroRNA == References == == Further reading == == External links == Page for mir-544 microRNA precursor family at Rfam
|
{
"page_id": 36372394,
"title": "Mir-544 microRNA precursor family"
}
|
Antiviral drugs are different from antibiotics. Flu antiviral drugs are different from antiviral drugs used to treat other infectious diseases such as COVID-19. Antiviral drugs prescribed to treat COVID-19 are not approved or authorized to treat flu. == References ==
|
{
"page_id": 1703850,
"title": "List of antiviral drugs"
}
|
Diffusion-limited escape occurs when the rate of atmospheric escape to space is limited by the upward diffusion of escaping gases through the upper atmosphere, and not by escape mechanisms at the top of the atmosphere (the exobase). The escape of any atmospheric gas can be diffusion-limited, but only diffusion-limited escape of hydrogen has been observed in the Solar System, on Earth, Mars, Venus and Titan. Diffusion-limited hydrogen escape was likely important for the rise of oxygen in Earth's atmosphere (the Great Oxidation Event) and can be used to estimate the oxygen and hydrogen content of Earth's prebiotic atmosphere. Diffusion-limited escape theory was first used by Donald Hunten in 1973 to describe hydrogen escape on one of Saturn's moons, Titan. The following year, in 1974, Hunten found that the diffusion-limited escape theory agreed with observations of hydrogen escape on Earth. Diffusion-limited escape theory is now used widely to model the composition of exoplanet atmospheres and Earth's ancient atmosphere. == Diffusion-Limited Escape of Hydrogen on Earth == Hydrogen escape on Earth occurs at ~500 km altitude at the exobase (the lower border of the exosphere) where gases are collisionless. Hydrogen atoms at the exobase exceeding the escape velocity escape to space without colliding into another gas particle. For a hydrogen atom to escape from the exobase, it must first travel upward through the atmosphere from the troposphere. Near ground level, hydrogen in the form of H2O, H2, and CH4 travels upward in the homosphere through turbulent mixing, which dominates up to the homopause. At about 17 km altitude, the cold tropopause (known as the "cold trap") freezes out most of the H2O vapor that travels through it, preventing the upward mixing of some hydrogen. In the upper homosphere, hydrogen bearing molecules are split by ultraviolet photons leaving only H and H2 behind.
|
{
"page_id": 60817325,
"title": "Diffusion-limited escape"
}
|
The H and H2 diffuse upward through the heterosphere to the exobase where they escape the atmosphere by Jeans thermal escape and/or a number of suprathermal mechanisms. On Earth, the rate-limiting step or "bottleneck" for hydrogen escape is diffusion through the heterosphere. Therefore, hydrogen escape on Earth is diffusion-limited. By considering one dimensional molecular diffusion of H2 through a heavier background atmosphere, you can derive a formula for the upward diffusion-limited flux of hydrogen ( Φ l {\displaystyle \Phi _{l}} ): Φ l = C f T ( H ) {\displaystyle \Phi _{l}=Cf_{T}(\mathrm {H} )} C {\displaystyle C} is a constant for a particular background atmosphere and planet, and f T ( H ) {\displaystyle f_{T}(H)} is the total hydrogen mixing ratio in all its forms above the tropopause. You can calculate f T ( H ) {\displaystyle f_{T}(\mathrm {H} )} by summing all hydrogen bearing species weighted by the number of hydrogen atoms each species contains: f T ( H ) = f H + 2 f H 2 + 2 f H 2 O + 4 f C H 4 + . . . {\displaystyle f_{T}(\mathrm {H} )=f_{\mathrm {H} }+2f_{\mathrm {H_{2}} }+2f_{\mathrm {H_{2}O} }+4f_{\mathrm {CH_{4}} }+...} For Earth's atmosphere, C = 2.5 × 10 13 {\displaystyle C=2.5\times 10^{13}} cm−2⋅s−1, and, the concentration of hydrogen bearing gases above the tropopause is 1.8 ppmv (parts per million by volume) CH4, 3 ppmv H2O, and 0.55 ppmv H2. Plugging these numbers into the formulas above gives a predicted diffusion-limited hydrogen escape rate of Φ l = 4.3 × 10 8 {\displaystyle \Phi _{l}=4.3\times 10^{8}} H atoms cm−2⋅s−1. This calculated hydrogen flux agrees with measurements of hydrogen escape. Note that hydrogen is the only gas in Earth's atmosphere that escapes at the diffusion-limit. Helium escape is not diffusion-limited and instead escapes by
|
{
"page_id": 60817325,
"title": "Diffusion-limited escape"
}
|
a suprathermal process known as the polar wind. == Derivation == Transport of gas molecules in the atmosphere occurs by two mechanisms: molecular and eddy diffusion. Molecular diffusion is the transport of molecules from an area of higher concentration to lower concentration due to thermal motion. Eddy diffusion is the transport of molecules by the turbulent mixing of a gas. The sum of molecular and eddy diffusion fluxes give the total flux of a gas i {\displaystyle i} through the atmosphere: Φ i = Φ i mol + Φ i eddy {\displaystyle \Phi _{i}=\Phi _{i}^{\text{mol}}+\Phi _{i}^{\text{eddy}}} The vertical eddy diffusion flux is given by Φ i eddy = − K n d f i d z {\displaystyle \Phi _{i}^{\text{eddy}}=-Kn{\frac {df_{i}}{dz}}} K {\displaystyle K} is the eddy diffusion coefficient, n {\displaystyle n} is the number density of the atmosphere (molecules cm−3), and f i {\displaystyle f_{i}} is the volume mixing ratio of gas i {\displaystyle i} . The above formula for eddy diffusion is a simplification for how gases actually mix in the atmosphere. The eddy diffusion coefficient can only be empirically derived from atmospheric tracer studies. The molecular diffusion flux, on the other hand, can be derived from theory. The general formula for the diffusion of gas 1 relative to gas 2 is given by v → 1 − v → 2 = − D 12 ( n 2 n 1 n 2 ∇ ( n 1 n ) + m 2 − m 1 m ∇ ( ln P ) + α T ∇ ( ln T ) − m 1 m 2 m k T ( a → 1 − a → 2 ) ) {\displaystyle {\vec {v}}_{1}-{\vec {v}}_{2}=-D_{12}\left({\frac {n^{2}}{n_{1}n_{2}}}\nabla \left({\frac {n_{1}}{n}}\right)+{\frac {m_{2}-m_{1}}{m}}\nabla (\ln {P})+\alpha _{T}\nabla (\ln {T})-{\frac {m_{1}m_{2}}{mkT}}({\vec {a}}_{1}-{\vec {a}}_{2})\right)} Each variable is defined in
|
{
"page_id": 60817325,
"title": "Diffusion-limited escape"
}
|
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