Handbook of Intermediality

This handbook offers students and researchers compact orientation in their study of intermedial phenomena in Anglophone literary texts and cultures by introducing them to current academic debates, theoretical concepts and methodologies. By combining theory with text analysis and contextual anchoring, it introduces students and scholars alike to a vast field of research which encompasses concepts such as intermediality, multi- and plurimediality, intermedial reference, transmediality, ekphrasis, as well as related concepts such as visual culture, remediation, adaptation, and multimodality, which are all discussed in connection with literary examples. Hence each of the 30 contributions spans both a theoretical approach and concrete analysis of literary texts from different centuries and different Anglophone cultures.

A review of air–ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow

Snow in the environment acts as a host to rich chemistry and provides a matrix for physical exchange of contaminants within the ecosystem. The goal of this review is to summarise the current state of knowledge of physical processes and chemical reactivity in surface snow with relevance to polar regions. It focuses on a description of impurities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liquid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differences between the disordered air–ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The reactivity in these different compartments of surface snow is discussed using many experimental studies, simulations, and selected snow models from the molecular to the macro-scale. Although new experimental techniques have extended our knowledge of the surface properties of ice and their impact on some single reactions and processes, others occurring on, at or within snow grains remain unquantified. The presence of liquid or liquid-like compartments either due to the formation of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. Therefore, future experiments should include a detailed characterisation of the surface properties of the ice matrices. A further point that remains largely unresolved is the distribution of impurities between the different domains of the condensed phase inside the snowpack, i.e. in the bulk solid, in liquid at the surface or trapped in confined pockets within or between grains, or at the surface. While surface-sensitive laboratory techniques may in the future help to resolve this point for equilibrium conditions, additional uncertainty for the environmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occurring under certain environmental conditions. Due to these gaps in knowledge the first snow chemistry models have attempted to reproduce certain processes like the long-term incorporation of volatile compounds in snow and firn or the release of reactive species from the snowpack. Although so far none of the models offers a coupled approach of physical and chemical processes or a detailed representation of the different compartments, they have successfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed.

Ḳol rinah ṿe-torah : a handbook of Synagogue music for congregational singing

arr. and ed. for the choir committee of the Council of the United Synagogue by Francis L. Cohen ...

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Abundance of nodules, chemical and mineral compositions of nodules and sediments from the Central Pacific

The monograph considers facial conditions of ore-formation in the Central Equatorial Pacific, as well as lithostratigraphy and local variability of bottom sediments. Mineral composition of nodules, forms of occurrence of chemical elements in sediments and nodules, composition of interstitial waters, age of nodules, regularities and processes of ore formation in the radiolarian belt of the Pacific Ocean zone are also under consideration.

(Table 2) Concentrations of particulate chemical elements in waters of the Pechora Sea

Mineralogy of suspended matter from surface and bottom waters has been studied at two sites in the Barents Sea. Along with terrigenous minerals, particulate matter samples contain authigenic mineral phases of iron and manganese oxyhydroxides. Mn-feroxyhite, Fe-vernadite, goethite, and proto-ferrihydrite have been identified in samples from the surface waters, whereas birnessite and non-ferruginous vernadite have been found in samples from the bottom waters. Formation of suspended manganese minerals in the bottom waters is explained by an additional Mn supply from underlying reduced sediments during their early diagenesis and oxygen depletion in the near-bottom nepheloid layer. Bacteria are supposed to take part in the authigenic mineral formation.