845 resultados para Sociology, Theory and Methods|Psychology, Clinical


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The biplot has proved to be a powerful descriptive and analytical tool in many areas of applications of statistics. For compositional data the necessary theoretical adaptation has been provided, with illustrative applications, by Aitchison (1990) and Aitchison and Greenacre (2002). These papers were restricted to the interpretation of simple compositional data sets. In many situations the problem has to be described in some form of conditional modelling. For example, in a clinical trial where interest is in how patients’ steroid metabolite compositions may change as a result of different treatment regimes, interest is in relating the compositions after treatment to the compositions before treatment and the nature of the treatments applied. To study this through a biplot technique requires the development of some form of conditional compositional biplot. This is the purpose of this paper. We choose as a motivating application an analysis of the 1992 US President ial Election, where interest may be in how the three-part composition, the percentage division among the three candidates - Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethnic composition and on the urban-rural composition of the state. The methodology of conditional compositional biplots is first developed and a detailed interpretation of the 1992 US Presidential Election provided. We use a second application involving the conditional variability of tektite mineral compositions with respect to major oxide compositions to demonstrate some hazards of simplistic interpretation of biplots. Finally we conjecture on further possible applications of conditional compositional biplots

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This study helps develop an overall understanding as to why some students achieve where others don't. Debate on the effects of class on educational attainment is well documented and typically centres on the reproductive nature of class whilst studies of the effect of class on educational aspirations also predict outcomes that see education reinforcing and reproducing a student's class background.Despite a number of government initiatives to help raise higher education participation to 50 per cent by 2010, for the working class numbers have altered little. Using data from an ethnographic case study of a low-achieving girls school, the author explores aspirations and argues that whilst class is very powerful in explaining educational attainment, understanding educational aspirations is somewhat more complex. The purpose of this book, therefore, is to question and challenge popular assumptions surrounding class-based theory in making sense of girls' aspirations and to question the usefulness of the continued over reliance of such broad categorisations by both academics and policy makers

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The calculation of accurate and reliable vibrational potential functions and normal co-ordinates is discussed, for such simple polyatomic molecules as it may be possible. Such calculations should be corrected for the effects of anharmonicity and of resonance interactions between the vibrational states, and should be fitted to all the available information on all isotopic species: particularly the vibrational frequencies, Coriolis zeta constants and centrifugal distortion constants. The difficulties of making these corrections, and of making use of the observed data are reviewed. A programme for the Ferranti Mercury Computer is described by means of which harmonic vibration frequencies and normal co-ordinate vectors, zeta factors and centrifugal distortion constants can be calculated, from a given force field and from given G-matrix elements, etc. The programme has been used on up to 5 × 5 secular equations for which a single calculation and output of results takes approximately l min; it can readily be extended to larger determinants. The best methods of using such a programme and the possibility of reversing the direction of calculation are discussed. The methods are applied to calculating the best possible vibrational potential function for the methane molecule, making use of all the observed data.

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This book is a collection of articles devoted to the theory of linear operators in Hilbert spaces and its applications. The subjects covered range from the abstract theory of Toeplitz operators to the analysis of very specific differential operators arising in quantum mechanics, electromagnetism, and the theory of elasticity; the stability of numerical methods is also discussed. Many of the articles deal with spectral problems for not necessarily selfadjoint operators. Some of the articles are surveys outlining the current state of the subject and presenting open problems.

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Evolutionary developmental genetics brings together systematists, morphologists and developmental geneticists; it will therefore impact on each of these component disciplines. The goals and methods of phylogenetic analysis are reviewed here, and the contribution of evolutionary developmental genetics to morphological systematics, in terms of character conceptualisation and primary homology assessment, is discussed. Evolutionary developmental genetics, like its component disciplines phylogenetic systematics and comparative morphology, is concerned with homology concepts. Phylogenetic concepts of homology and their limitations are considered here, and the need for independent homology statements at different levels of biological organisation is evaluated. The role of systematics in evolutionary developmental genetics is outlined. Phylogenetic systematics and comparative morphology will suggest effective sampling strategies to developmental geneticists. Phylogenetic systematics provides hypotheses of character evolution (including parallel evolution and convergence), stimulating investigations into the evolutionary gains and losses of morphologies. Comparative morphology identifies those structures that are not easily amenable to typological categorisation, and that may be of particular interest in terms of developmental genetics. The concepts of latent homology and genetic recall may also prove useful in the evolutionary interpretation of developmental genetic data.

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This paper explores the social theories implicit in system dynamics (SD) practice. Groupings of SD practice are observed in different parts of a framework for studying social theories. Most are seen to be located within `functionalist sociology'. To account for the remainder, two new forms of practice are discussed, each related to a different paradigm. Three competing conclusions are then offered: 1. The implicit assumption that SD is grounded in functionalist sociology is correct and should be made explicit. 2. Forrester's ideas operate at the level of method not social theory so SD, though not wedded to a particular social theoretic paradigm, can be re-crafted for use within different paradigms. 3. SD is consistent with social theories which dissolve the individual/society divide by taking a dialectical, or feedback, stance. It can therefore bring a formal modelling approach to the `agency/structure' debate within social theory and so bring SD into the heart of social science. The last conclusion is strongly recommended.

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Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The recipe used to compute the symmetric energy-momentum tensor in the framework of ordinary field theory bears little resemblance to that used in the context of general relativity, if any. We show that if one stal ts fi om the field equations instead of the Lagrangian density, one obtains a unified algorithm for computing the symmetric energy-momentum tensor in the sense that it can be used for both usual field theory and general relativity.

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Background: Smoking is a well-known risk factor for destructive periodontal disease, but its relationship with periodontal status and subgingival microbiota remains unclear. Inherent limitations of microbiological methods previously used may partly explain these mixed results, and real-time polymerase chain reaction (PCR) has been presented as a valid alternative. The aim of the present study was to investigate the clinical condition and microbiological profile of patients with chronic periodontitis as related to the habit of smoking.Methods: Fifty patients (33 to 59 years old), 25 smokers and 25 never-smokers, constituted the sample. The visible plaque index (VPI), gingival bleeding index (GBI), bleeding on probing (BOP), periodontal probing depth (PD), clinical attachment loss (CAL), and gingival crevicular fluid (GCF) volume were recorded. Real-time PCR quantified Porphyromonas gingivalis, Micromonas micros, Dialister pneumosintes, Actinobacillus actinomycetemcomitans and total bacteria in subgingival samples.Results: Smokers and never-smokers showed similar values for VPI, GBI, and BOP. Smokers had deeper PD in buccal/lingual sites and higher CAL independently of the tooth surface. The GCF volume was smaller in smokers, independent of the PD. Similar amounts of total bacteria and P. gingivalis were observed for both groups. Significantly higher numbers of D. pneumosintes and M. micros were present in smokers and associated with moderate and deep pockets. When heavy smokers were considered, higher counts of total bacteria, M. micros, and D. pneumosintes were observed.Conclusions: Smoking seems to have a detrimental impact on the periodontal status and microbiological profile of patients with periodontitis. Compared to never-smokers, smokers had deeper pockets, greater periodontal destruction, and higher counts of some putative periodontal pathogens.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Física - IFT

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This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between 3 and 6 years of age, there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds’ spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds’ responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development, with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change.