981 resultados para Data Integrity


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This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

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Chlorophyll a fluorescence parameters and transmission electron microscopy (TEM) were used to assess the stress conditions in water hyacinth along the Paraiba do Sul River (PSR), an important River in southeastern Brazil. The data were obtained at the end of the dry season of 2005 and at the end of the wet season of 2006. Changes in F-o and F-m parameters were observed as differentiated responses, depending on the season. Non-photochemical dissipation (qN and NPQ) from plants was greater in the most industrialized region of the PSR in both seasons. However, F-v/F-m for all samples ranged between 0.77 and 0.81, showing that high maximum quantum yield was maintained. Although the F-v/F-m suggests that the plants were exhibiting normal photochemical activities, ultrastructural changes in chloroplasts showed thylakoids disorganization. Plants from the most industrialized region showed non-stacking grana thylakoids disposition. In spite of these alterations, the membrane integrity was maintained, suggesting an adaptation to adjustment to adverse environmental conditions. (C) 2008 Elsevier B.V. All rights reserved.

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Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

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The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

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It is well recognized that zinc is an essential trace element for all organisms, influencing growth and affecting the development and integrity of the immune system. It is also well known that the protective response against Trypanosoma cruzi depends on both innate and acquired immunity and for the control of the parasite load and host survival, the participation of special cells such natural killer (NK), T and B lymphocytes and macrophages are required. So the aims of this study were to evaluate the effects of zinc supplementation on the host`s immune response infected with T cruzi. Our data point in the direction that zinc supplementation triggered enhanced thymocyte and splenocyte proliferation as compared to unsupplied group of animals. It is also important to emphasize that interleukin-12 (IL-12) participates in the resistance to several intracellular pathogens including T cruzi. Our findings demonstrate an enhanced production of IL-12 during the acute phase of infection in zinc-supplied groups. So we conclude that zinc supplementation leads to an effective host`s immune response by up-modulating the host`s immune response, thus contributing in the reduction of blood parasites and the harmful pathogenic effects of the experimental Chagas` disease. (c) 2008 Elsevier B.V. All rights reserved.

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Background/Aims: It is a challenge to adapt traditional in vitro diffusion experiments to ocular tissue. Thus, the aim of this work was to present experimental evidence on the integrity of the porcine cornea, barrier function and maintenance of electrical properties for 6 h of experiment when the tissue is mounted on an inexpensive and easy-to-use in vitro model for ocular iontophoresis. Methods: A modified Franz diffusion cell containing two ports for the insertion of the electrodes and a receiving compartment that does not need gassing with carbogen was used in the studies. Corneal electron transmission microscopy images were obtained, and diffusion experiments with fluorescent markers were performed to examine the integrity of the barrier function. The preservation of the negatively charged corneal epithelium was verified by the determination of the electro-osmotic flow of a hydrophilic and non-ionized molecule. Results: The diffusion cell was able to maintain the temperature, homogenization, porcine epithelial corneal structure integrity, barrier function and electrical characteristics throughout the 6 h of permeation experiment, without requiring CO(2) gassing when the receiving chamber was filled with 25 m M of HEPES buffer solution. Conclusion: The system described here is inexpensive, easy to handle and reliable as an in vitro model for iontophoretic ocular delivery studies. Copyright (C) 2010 S. Karger AG, Basel

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This document records the process of migrating eprints.org data to a Fez repository. Fez is a Web-based digital repository and workflow management system based on Fedora (http://www.fedora.info/). At the time of migration, the University of Queensland Library was using EPrints 2.2.1 [pepper] for its ePrintsUQ repository. Once we began to develop Fez, we did not upgrade to later versions of eprints.org software since we knew we would be migrating data from ePrintsUQ to the Fez-based UQ eSpace. Since this document records our experiences of migration from an earlier version of eprints.org, anyone seeking to migrate eprints.org data into a Fez repository might encounter some small differences. Moving UQ publication data from an eprints.org repository into a Fez repository (hereafter called UQ eSpace (http://espace.uq.edu.au/) was part of a plan to integrate metadata (and, in some cases, full texts) about all UQ research outputs, including theses, images, multimedia and datasets, in a single repository. This tied in with the plan to identify and capture the research output of a single institution, the main task of the eScholarshipUQ testbed for the Australian Partnership for Sustainable Repositories project (http://www.apsr.edu.au/). The migration could not occur at UQ until the functionality in Fez was at least equal to that of the existing ePrintsUQ repository. Accordingly, as Fez development occurred throughout 2006, a list of eprints.org functionality not currently supported in Fez was created so that programming of such development could be planned for and implemented.

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The final-year project for Mechanical & Space Engineering students at UQ often involves the design and flight testing of an experiment. This report describes the design and use of a simple data logger that should be suitable for collecting data from the students' flight experiments. The exercise here was taken as far as the construction of a prototype device that is suitable for ground-based testing, say, the static firing of a hybrid rocket motor.

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A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

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This paper reports a comparative study of Australian and New Zealand leadership attributes, based on the GLOBE (Global Leadership and Organizational Behavior Effectiveness) program. Responses from 344 Australian managers and 184 New Zealand managers in three industries were analyzed using exploratory and confirmatory factor analysis. Results supported some of the etic leadership dimensions identified in the GLOBE study, but also found some emic dimensions of leadership for each country. An interesting finding of the study was that the New Zealand data fitted the Australian model, but not vice versa, suggesting asymmetric perceptions of leadership in the two countries.

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In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

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There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

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Background: This study used household survey data on the prevalence of child, parent and family variables to establish potential targets for a population-level intervention to strengthen parenting skills in the community. The goals of the intervention include decreasing child conduct problems, increasing parental self-efficacy, use of positive parenting strategies, decreasing coercive parenting and increasing help-seeking, social support and participation in positive parenting programmes. Methods: A total of 4010 parents with a child under the age of 12 years completed a statewide telephone survey on parenting. Results: One in three parents reported that their child had a behavioural or emotional problem in the previous 6 months. Furthermore, 9% of children aged 2–12 years meet criteria for oppositional defiant disorder. Parents who reported their child's behaviour to be difficult were more likely to perceive parenting as a negative experience (i.e. demanding, stressful and depressing). Parents with greatest difficulties were mothers without partners and who had low levels of confidence in their parenting roles. About 20% of parents reported being stressed and 5% reported being depressed in the 2 weeks prior to the survey. Parents with personal adjustment problems had lower levels of parenting confidence and their child was more difficult to manage. Only one in four parents had participated in a parent education programme. Conclusions: Implications for the setting of population-level goals and targets for strengthening parenting skills are discussed.

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