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Metaphorical and metonymical compounds - novel and lexicalised ones alike - are remarkably abundant in language. Yet how can we be sure that when using an expression such as land fishing in order to speak about metal detecting, the referent will be immediately understood even if the hearer had not been previously familiar with the compound? Accordingly, this book sets out to explore whether the semantics of metaphorical and metonymical noun-noun combinations can be systematically analysed within a theoretical framework, where systematicity pertains to regularities in both the cognitive processes and the products of these processes, that is, the compounds themselves. Backed up by recent psycholinguistic evidence, the book convincingly demonstrates that such compounds are not semantically opaque as it has been formerly claimed: they can in fact be analysed and accounted for within a cognitive linguistic framework, by the combined application of metaphor, metonymy, blending, profile determinacy and schema theory; and represent the creative and associative word formation processes that we regularly apply in everyday language.
English language --- Metaphor. --- Parabole --- Figures of speech --- Reification --- Compound words. --- Noun phrase. --- Semantics. --- Semasiology --- Complex nominals --- Phrasal noun --- Subject --- Metaphor --- Compound words --- Noun phrase --- Semantics --- Lexicology. Semantics --- English language Semantics --- Germanic languages
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This book presents new work on the psycholinguistics and neurolinguistics of compound words and shows the insights it offers on natural language processing and the relation between language, mind, and memory.
Grammar, Comparative and general --- Comparative grammar --- Grammar --- Grammar, Philosophical --- Grammar, Universal --- Language and languages --- Philosophical grammar --- Linguistics --- Philology --- Compound words --- Psychological aspects. --- Grammar, Comparative --- Psychological aspects --- Lexicology. Semantics --- Psycholinguistics
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Organic water pollutants --- 543.3 --- afvalwaterverwerking --- organische stoffen --- polaire moleculen --- risicoanalyses --- waterverontreiniging --- Contaminants, Organic water --- Water pollutants, Organic --- Organic wastes --- Pollutants --- Water --- wateranalyse --- Organic compound content --- Purification --- Organic compounds removal
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Modern, industrialized societies depend on a wide range of chemical substances such as fuels, plastics, biocides, pharmaceuticals and detergents for maintaining the high quality lifestyle to which we aspire. The challenge is to ensure that while weenjoythebene?tsofthesesubstances,theirinevitablereleaseintoourbiosphere does not result in unwanted human and ecosystem exposures, and the risk of - verse effects. One response to this challenge has been the extensive effort to detect and analyze or monitor a multitude of chemicals in a variety of environmental media, especially toxic organic compounds in air, water, soils and biota. The c- ventionalmonitoringstrategyofsamplinglitersorkilogramsoftheenvironmental medium followed by analytical determination of the quantity of chemical in the sample extract has been the successful cornerstone of investigative environmental chemistry. No doubt, it will continue to be so. An extensive literature on these traditional techniques has evolved over the years. In parallel with conventional techniques, and I believe entirely complem- tary to them, a variety of in situ sensing systems have been developed which operate on the principle of the preferential partitioning of contaminants into a - vice, often at concentrations which are large multiples of environmental levels. Advocates point out that these partitioning devices have the advantage of integr- ing chemical concentrations over a prolonged period, thus “averaging” ambient levels. Their high partition coef?cients can yield signi?cant quantities of analyte and reduce problems arising from short-term pulses of concentration and from sample contamination.
Environmental engineering. --- Membranes (Technology) --- Organic water pollutants --- Environmental aspects. --- Contaminants, Organic water --- Water pollutants, Organic --- Organic wastes --- Pollutants --- Water --- Artificial membranes --- Separation (Technology) --- Technology --- Environmental control --- Environmental effects --- Environmental stresses --- Engineering --- Environmental health --- Environmental protection --- Pollution --- Sustainable engineering --- Organic compound content --- Purification --- Organic compounds removal --- Analytical biochemistry. --- Environmental pollution. --- Analytical Chemistry. --- Biogeosciences. --- Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. --- Chemical pollution --- Chemicals --- Contamination of environment --- Environmental pollution --- Contamination (Technology) --- Asbestos abatement --- Bioremediation --- Environmental engineering --- Environmental quality --- Factory and trade waste --- Hazardous waste site remediation --- Hazardous wastes --- In situ remediation --- Lead abatement --- Refuse and refuse disposal --- Analytic biochemistry --- Biochemistry --- Chemistry, Analytic --- Environmental aspects --- Bioanalytic chemistry --- Bioanalytical chemistry --- Analytical chemistry --- Analytical chemistry. --- Geobiology. --- Water pollution. --- Aquatic pollution --- Fresh water --- Fresh water pollution --- Freshwater pollution --- Inland water pollution --- Lake pollution --- Lakes --- Reservoirs --- River pollution --- Rivers --- Stream pollution --- Water contamination --- Water pollutants --- Water pollution --- Waste disposal in rivers, lakes, etc. --- Biology --- Earth sciences --- Biosphere --- Analysis, Chemical --- Analytic chemistry --- Chemical analysis --- Chemistry
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The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way or other. The area of potential applications goes beyond simple data analysis and extends to regression analysis and to non-linear time series analysis using Markov switching models. For more than the hundred years since Karl Pearson showed in 1894 how to estimate the five parameters of a mixture of two normal distributions using the method of moments, statistical inference for finite mixture models has been a challenge to everybody who deals with them. In the past ten years, very powerful computational tools emerged for dealing with these models which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers the most recent advances in the field, among them bridge sampling techniques and reversible jump Markov chain Monte Carlo methods. It is the first time that the Bayesian perspective of finite mixture modelling is systematically presented in book form. It is argued that the Bayesian approach provides much insight in this context and is easily implemented in practice. Although the main focus is on Bayesian inference, the author reviews several frequentist techniques, especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian approach. The aim of this book is to impart the finite mixture and Markov switching approach to statistical modelling to a wide-ranging community. This includes not only statisticians, but also biologists, economists, engineers, financial agents, market researcher, medical researchers or any other frequent user of statistical models. This book should help newcomers to the field to understand how finite mixture and Markov switching models are formulated, what structures they imply on the data, what they could be used for, and how they are estimated. Researchers familiar with the subject also will profit from reading this book. The presentation is rather informal without abandoning mathematical correctness. Previous notions of Bayesian inference and Monte Carlo simulation are useful but not needed. Sylvia Frühwirth-Schnatter is Professor of Applied Statistics and Econometrics at the Department of Applied Statistics of the Johannes Kepler University in Linz, Austria. She received her Ph.D. in mathematics from the University of Technology in Vienna in 1988. She has published in many leading journals in applied statistics and econometrics on topics such as Bayesian inference, finite mixture models, Markov switching models, state space models, and their application in marketing, economics and finance.
Mixture distributions (Probability theory) --- Markov processes. --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Compound distributions (Probability theory) --- Distributions, Mixture (Probability theory) --- Mixed distributions (Probability theory) --- Mixing distributions (Probability theory) --- Mixtures of distributions (Probability theory) --- Distribution (Probability theory) --- Distribution (Probability theory. --- Mathematical statistics. --- Econometrics. --- Computer science. --- Bioinformatics. --- Psychometrics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Probability and Statistics in Computer Science. --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Informatics --- Science --- Economics, Mathematical --- Statistics --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Distribution functions --- Frequency distribution --- Characteristic functions --- Measurement --- Scaling --- Methodology --- Data processing --- Statistical methods --- Probabilities. --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Probability --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk
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The oceans contain a great biodiversity of marine organisms. They include a rich variety of unusual genes and biochemistries and hence a diverse array of organic compounds ranging from colourful carotenoids and chlorophylls to lipids with structures ranging from the simple to the complex. This volume brings together ten chapters on the occurrence and identification of the lipid biomarkers and of pigments in marine waters. It describes how they can be used in conjunction with stable isotopes and molecular biology to ascertain the sources and fate of organic matter (both natural and pollutant) in the sea and underlying sediments. The authors are each experts in their field and the chapters provide both an overview of the state-of-the-art and knowledge gaps together with abundant detail to satisfy the needs of specialists and non-specialists alike.
Seawater --- Organic compound content --- Environmental sciences. --- Climatic changes. --- Environmental management. --- Ecology. --- Environmental pollution. --- Environment. --- Geoecology/Natural Processes. --- Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. --- Environmental Management. --- Climate Change. --- Chemistry - General --- Geology - General --- Geology --- Chemistry --- Physical Sciences & Mathematics --- Earth & Environmental Sciences --- Chemical pollution --- Chemicals --- Contamination of environment --- Environmental pollution --- Pollution --- Balance of nature --- Biology --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Environmental stewardship --- Stewardship, Environmental --- Changes, Climatic --- Climate change --- Climate changes --- Climate variations --- Climatic change --- Climatic changes --- Climatic fluctuations --- Climatic variations --- Global climate changes --- Global climatic changes --- Environmental science --- Environmental aspects --- Ecology --- Life sciences. --- Water-supply. --- Climate change. --- Geoecology. --- Environmental geology. --- Water pollution. --- Life Sciences. --- Life Sciences, general. --- Water Industry/Water Technologies. --- Environmental sciences --- Management --- Aquatic pollution --- Fresh water --- Fresh water pollution --- Freshwater pollution --- Inland water pollution --- Lake pollution --- Lakes --- Reservoirs --- River pollution --- Rivers --- Stream pollution --- Water contamination --- Water pollutants --- Water pollution --- Waste disposal in rivers, lakes, etc. --- Geoecology --- Environmental protection --- Physical geology --- Changes in climate --- Climate change science --- Climatology --- Climate change mitigation --- Teleconnections (Climatology) --- Availability, Water --- Water availability --- Water resources --- Natural resources --- Public utilities --- Water resources development --- Water utilities --- Biosciences --- Sciences, Life --- Science --- Contamination (Technology) --- Asbestos abatement --- Bioremediation --- Environmental engineering --- Environmental quality --- Factory and trade waste --- Hazardous waste site remediation --- Hazardous wastes --- In situ remediation --- Lead abatement --- Pollutants --- Refuse and refuse disposal --- Population biology --- Global environmental change --- Water --- Pollution.
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