967 resultados para Information analysis


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This article reports on the results of a study undertaken by the author together with her research assistant, Heather Green. The study collected and analysed data from all disciplinary tribunal decisions heard in Queensland since 1930 in an attempt to provide empirical information which has previously been lacking. This article will outline the main features of the disciplinary system in Queensland, describe the research methodology used in the present study and then report on some findings from the study. Reported findings include a profile of solicitors who have appeared before a disciplinary hearing, the types of matters which have attracted formal discipline and the types of orders made by the tribunal. Much of the data is then presented on a time scale so as to reveal any changes over time.

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The use of gate-to-drain capacitance (C-gd) measurement as a tool to characterize hot-carrier-induced charge centers in submicron n- and p-MOSFET's has been reviewed and demonstrated. By analyzing the change in C-gd measured at room and cryogenic temperature before and after high gate-to-drain transverse field (high field) and maximum substrate current (I-bmax) stress, it is concluded that the degradation was found to be mostly due to trapping of majority carriers and generation of interface states. These interface states were found to be acceptor states at top half of band gap for n-MOSFETs and donor states at bottom half of band gap for p-MOSFETs. In general, hot electrons are more likely to be trapped in gate oxide as compared to hot holes while the presence of hot holes generates more interface states. Also, we have demonstrated a new method for extracting the spatial distribution of oxide trapped charge, Q(ot), through gate-to-substrate capacitance (C-gb) measurement. This method is simple to implement and does not require additional information from simulation or detailed knowledge of the device's structure. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Objective: To describe and analyse the study design and manuscript deficiencies in original research articles submitted to Emergency Medicine. Methods: This was a retrospective, analytical study. Articles were enrolled if the reports of the Section Editor and two reviewers were available. Data were extracted from these reports only. Outcome measures were the mean number and nature of the deficiencies and the mean reviewers’ assessment score. Results: Fifty-seven articles were evaluated (28 accepted for publication, 19 rejected, 10 pending revision). The mean (± SD) number of deficiencies was 18.1 ± 6.9, 16.4 ± 6.5 and 18.4 ± 6.7 for all articles, articles accepted for publication and articles rejected, respectively (P = 0.31 between accepted and rejected articles). The mean assessment scores (0–10) were 5.5 ± 1.5, 5.9 ± 1.5 and 4.7 ± 1.4 for all articles, articles accepted for publication and articles rejected, respectively. Accepted articles had a significantly higher assessment score than rejected articles (P = 0.006). For each group, there was a negative correlation between the number of deficiencies and the mean assessment score (P > 0.05). Significantly more rejected articles ‘… did not further our knowledge’ (P = 0.0014) and ‘… did not describe background information adequately’ (P = 0.049). Many rejected articles had ‘… findings that were not clinically or socially significant’ (P = 0.07). Common deficiencies among all articles included ambiguity of the methods (77%) and results (68%), conclusions not warranted by the data (72%), poor referencing (56%), inadequate study design description (51%), unclear tables (49%), an overly long discussion (49%), limitations of the study not described (51%), inadequate definition of terms (49%) and subject selection bias (40%). Conclusions: Researchers should undertake studies that are likely to further our knowledge and be clinically or socially significant. Deficiencies in manuscript preparation are more frequent than mistakes in study design and execution. Specific training or assistance in manuscript preparation is indicated.

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Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

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For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

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To examine whether nucleolar organizer regions detected by argyrophilia (Ag-NOR counts) can be used as a prognostic indicator in phyllodes tumors of the breast, and to compare its usefulness with that of DNA flow cytometric analysis, 28 cases of breast phyllodes tumors (including 15 benign, two borderline and 11 malignant tumors) were subjected to Ag-NOR staining and counting as well as DNA flow cytometric analysis. S-phase fraction and DNA ploidy analysis showed useful trends for improving outcome predictions in malignant phyllodes tumors. However, high Ag-NOR counts were significant in predicting survival status (P = 0.013) and reached near statistical significance in predicting survival times (P = 0.07). In predicting survival status, results for Ag-NOR counts were significantly better than those for ploidy analysis (P = 0.02) and S-phase fraction (P < 0.01). Only S-phase fraction was significantly predictive of survival times (P = 0.025). It is concluded that Ag-NOR counts and DNA flow cytometric analysis, easily performed using paraffin sections, give information that can improve predictions made by histopathological classification. Ag-NOR counts are significant in predicting survival in the presence of histopathological features of malignancy.

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Within the information systems field, the task of conceptual modeling involves building a representation of selected phenomena in some domain. High-quality conceptual-modeling work is important because it facilitates early detection and correction of system development errors. It also plays an increasingly important role in activities like business process reengineering and documentation of best-practice data and process models in enterprise resource planning systems. Yet little research has been undertaken on many aspects of conceptual modeling. In this paper, we propose a framework to motivate research that addresses the following fundamental question: How can we model the world to better facilitate our developing, implementing, using, and maintaining more valuable information systems? The framework comprises four elements: conceptual-modeling grammars, conceptual-modeling methods, conceptual-modeling scripts, and conceptual-modeling contexts. We provide examples of the types of research that have already been undertaken on each element and illustrate research opportunities that exist.