998 resultados para Jeffrey Kroessler


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Australian scientist Shirley Jeffrey was a pioneer in oceanographic research, identifying the then theoretical chlorophyll c, and was a worldwide leader in the application of pigment methods in quantifying phytoplankton as the foundation of the oceanic food supply. Her research paved the way for the successful application of microalgae in aquaculture around the world. Jeffrey earned bachelor's and master's degrees at University of Sydney, majoring in microbiology and biochemistry, followed by a PhD from the King's College London Hospital Medical School. Returning to Sydney, she was hired by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to research chlorophyll c. Following this successful effort, she became a research fellow at the University of California, Berkeley from 1962 to 1964. She then became affiliated with the Scientific Committee on Oceanic Research. After a 1973 sabbatical at the Scripps Institution of Oceanography in San Diego, she returned to CSIRO, where she spent the rest of her career.

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Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. In practice, much of this work will be performed by multiple observers, and maximising inter-observer consistency is of particular importance. Another discipline where consistency in classification is vital is biological taxonomy. A classification tool of great utility, the binary key, is designed to simplify the classification decision process and ensure consistent identification of proper categories. We show how this same decision-making tool - the binary key - can be used to promote consistency in the classification of behaviour. The construction of a binary key also ensures that the categories in which behaviour is classified are complete and non-overlapping. We discuss the general principles of design of binary keys, and illustrate their construction and use with a practical example from education research.

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Traditional ceramic separation membranes, which are fabricated by applying colloidal suspensions of metal hydroxides to porous supports, tend to suffer from pinholes and cracks that seriously affect their quality. Other intrinsic problems for these membranes include dramatic losses of flux when the pore sizes are reduced to enhance selectivity and dead-end pores that make no contribution to filtration. In this work, we propose a new strategy for addressing these problems by constructing a hierarchically structured separation layer on a porous substrate using large titanate nanofibers and smaller boehmite nanofibers. The nanofibers are able to divide large voids into smaller ones without forming dead-end pores and with the minimum reduction of the total void volume. The separation layer of nanofibers has a porosity of over 70% of its volume, whereas the separation layer in conventional ceramic membranes has a porosity below 36% and inevitably includes dead-end pores that make no contribution to the flux. This radical change in membrane texture greatly enhances membrane performance. The resulting membranes were able to filter out 95.3% of 60-nm particles from a 0.01 wt % latex while maintaining a relatively high flux of between 800 and 1000 L/m2·h, under a low driving pressure (20 kPa). Such flow rates are orders of magnitude greater than those of conventional membranes with equal selectivity. Moreover, the flux was stable at approximately 800 L/m2·h with a selectivity of more than 95%, even after six repeated runs of filtration and calcination. Use of different supports, either porous glass or porous alumina, had no substantial effect on the performance of the membranes; thus, it is possible to construct the membranes from a variety of supports without compromising functionality. The Darcy equation satisfactorily describes the correlation between the filtration flux and the structural parameters of the new membranes. The assembly of nanofiber meshes to combine high flux with excellent selectivity is an exciting new direction in membrane fabrication.

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This article examines the importance of accurate classification and identification of risk with particular reference to the problem of adverse selection. It is argued that, historically, this concern was the paramount consideration influencing standard form contract formation and disclosure laws. The scope of its relevance today however is less apparent in that contemporary insurance contracting is conducted in a vastly different environment from that which prevailed at the time Lloyd's was better known as a coffee house. Accordingly, the second part of this article looks at the contemporary framework of information disclosure and those dynamics within it designed to elicit information weighing on risk forecasting : specifically, (a) direct inquiry and testing requirements; (b) signaling - or incentive based structuring of insurance contractual and (c) bargaining in the shadow of the utmost good faith doctrine. Finally, certain conclusions arising out of contemporary and historical economic considerations underpinning disclosure in insurance law are outlined.