155 research outputs found

    Heroes and villains of world history across cultures

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    © 2015 Hanke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedEmergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.This research was supported by grant RG016-P-10 from the Chiang Ching-Kuo Foundation for International Scholarly Exchange (http://www.cckf.org.tw/). Religion Culture Entropy China Democracy Economic histor

    Validación de un documento de Word bajo la norma NTC1486 a partir de la metadata

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    Investigación TecnológicaEn el presente documento se encuentra contemplado el fundamento teórico de los tipos de datos y de los modelos de datos que se manejan en la actualidad, así como la web semántica y aspectos de ingeniería de software requeridos para la construcción de un prototipo de software que automatice el proceso de extracción de metadatos en un documento de Word, validando que la información contenida en este cumpla con la NTC 1486 en su totalidad, siendo una herramienta que facilite el proceso de calificación y caracterización de trabajos de grado y documentos de tipo investigativo. Esta investigación tiene un impacto dentro de la comunidad investigativa en la medida en que genera un prototipo de software que facilita el proceso de revisión de documentos investigativos en construcción.Glosario RESUMEN INTRODUCCIÓN 1.JUSTIFICACIÓN 2. PLANTEAMIENTO DEL PROBLEMA 3. OBJETIVO GENERAL 4. MARCO TEÓRICO 5. MARCO CONCEPTUAL 6. ESTADO DEL ARTE 7. METODOLOGÍA 8. RESULTADOS 9. CONCLUSIONES 10. TRABAJOS FUTUROS 11. BIBLIOGRAFÍAPregradoIngeniero de Sistema

    Predictive Models for the Diagnostic of Human Visceral Leishmaniasis in Brazil

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    Visceral leishmaniasis (VL) is a neglected tropical disease endemic to 65 countries, including Brazil, where the disease frequently occurs in remote locations and treatment is often performed on the basis of clinical suspicion. Predictive models based on scoring systems could be a helpful tool for the clinical management of VL. Based on clinical signs and symptoms, and five different serological tests of 213 patients with parasitologically confirmed (cases) and 119 with clinical suspicion of VL but with another confirmed etiology (non-cases), twelve prediction models using logistic regression and classification and regression trees (CART) for VL diagnosis were developed. The model composed of the clinical-laboratory variables and the rk39 rapid test showed the best performance in both logistic regression and CART (Sensitivity of 90.1% and specificity ranging from 97.2–97.4%). The scoring system is simple and based on the clinical-laboratory findings that are easily available in most clinical settings. The results suggest that those models might be useful in locations where access to available diagnostic methods is difficult, contributing to more efficient and more rational allocation of healthcare resources

    Bifactor analysis of motivation for charity sport event participation

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    The purpose of this study was to examine the utility of the existing subscales of charity sport events (CSEs) participation motivation by adopting both a second-order modeling and a bifactor modeling approaches. The results with 488 college students revealed that the bifactor model provided a better interpretation of the data compared to second-order model. The five-factor CSE motivation significantly predict the intention to participate in CSEs along with two domain-specific motivations, namely ‘sport and event’ and ‘cause’ while other three domain-specific motivations including ‘philanthropic’, ‘social interaction’, and ‘reference group’ are not statistically significant predictors. The results suggest that the bifactor model is more useful in predicting this group’s participation in charity sport events. © 2015, Springer-Verlag Berlin Heidelberg

    Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health

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    BACKGROUND: In this paper we compare the results in an analysis of determinants of caregivers' health derived from two approaches, a structural equation model and a log-linear model, using the same data set. METHODS: The data were collected from a cross-sectional population-based sample of 468 families in Ontario, Canada who had a child with cerebral palsy (CP). The self-completed questionnaires and the home-based interviews used in this study included scales reflecting socio-economic status, child and caregiver characteristics, and the physical and psychological well-being of the caregivers. Both analytic models were used to evaluate the relationships between child behaviour, caregiving demands, coping factors, and the well-being of primary caregivers of children with CP. RESULTS: The results were compared, together with an assessment of the positive and negative aspects of each approach, including their practical and conceptual implications. CONCLUSION: No important differences were found in the substantive conclusions of the two analyses. The broad confirmation of the Structural Equation Modeling (SEM) results by the Log-linear Modeling (LLM) provided some reassurance that the SEM had been adequately specified, and that it broadly fitted the data

    Evaluation of Urine CCA Assays for Detection of Schistosoma mansoni Infection in Western Kenya

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    Although accurate assessment of the prevalence of Schistosoma mansoni is important for the design and evaluation of control programs, the most widely used tools for diagnosis are limited by suboptimal sensitivity, slow turn-around-time, or inability to distinguish current from former infections. Recently, two tests that detect circulating cathodic antigen (CCA) in urine of patients with schistosomiasis became commercially available. As part of a larger study on schistosomiasis prevalence in young children, we evaluated the performance and diagnostic accuracy of these tests—the carbon test strip designed for use in the laboratory and the cassette format test intended for field use. In comparison to 6 Kato-Katz exams, the carbon and cassette CCA tests had sensitivities of 88.4% and 94.2% and specificities of 70.9% and 59.4%, respectively. However, because of the known limitations of the Kato-Katz assay, we also utilized latent class analysis (LCA) incorporating the CCA, Kato-Katz, and schistosome-specific antibody results to determine their sensitivities and specificities. The laboratory-based CCA test had a sensitivity of 91.7% and a specificity of 89.4% by LCA while the cassette test had a sensitivity of 96.3% and a specificity of 74.7%. The intensity of the reaction in both urine CCA tests reflected stool egg burden and their performance was not affected by the presence of soil transmitted helminth infections. Our results suggest that urine-based assays for CCA may be valuable in screening for S. mansoni infections

    Latent Class Analysis of Antisocial Behavior: Interaction of Serotonin Transporter Genotype and Maltreatment

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    To improve understanding about genetic and environmental influences on antisocial behavior (ASB), we tested the association of the 44-base pair polymorphism of the serotonin transporter gene (5-HTTLPR) and maltreatment using latent class analysis in 2,488 boys and girls from Wave 1 of the National Longitudinal Study of Adolescent Health. In boys, ASB was defined by three classes (Exclusive Covert, Mixed Covert and Overt, and No Problems) whereas in girls, ASB was defined by two classes (Exclusive Covert, No Problems). In boys, 5-HTTLPR and maltreatment were not significantly related to ASB. However, in girls, maltreatment, but not 5-HTTLPR, was significantly associated with ASB. A significant interaction between 5-HTTLPR and maltreatment was also observed, where maltreated girls homozygous for the short allele were 12 times more likely to be classified in the Exclusive Covert group than in the No Problems group. Structural differences in the latent structure of ASB at Wave 2 and Wave 3 prevented repeat LCA modeling. However, using counts of ASB, 5-HTTLPR, maltreatment, and its interaction were unrelated to overt and covert ASB at Wave 2 and only maltreatment was related to covert ASB at Wave 3. We discuss these findings within the context of sex differences in ASB and relevant models of gene-environment interplay across developmental periods
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