963 resultados para framework structure


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Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the "best fit" model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate.

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The purpose of this article is to introduce a Cartesian product structure into the social choice theoretical framework and to examine if new possibility results to Gibbard's and Sen's paradoxes can be developed thanks to it. We believe that a Cartesian product structure is a pertinent way to describe individual rights in the social choice theory since it discriminates the personal features comprised in each social state. First we define some conceptual and formal tools related to the Cartesian product structure. We then apply these notions to Gibbard's paradox and to Sen's impossibility of a Paretian liberal. Finally we compare the advantages of our approach to other solutions proposed in the literature for both impossibility theorems.

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In the framework of health services research sponsored by the Swiss National Science Foundation, a research was undertaken of the activity of the large majority of the public health nurses working in the Swiss cantons of Vaud and Fribourg (total population 700,000). During one week, 130 nurses gathered, with a specially devised instrument, data on 4165 patient visits. Studying the duration of the contacts, one has distinguished contact duration per se (DC), duration of the travel time preceding the contact (DD), and total duration in relation with the contact (DTC-addition of the first two). It was noted that the three durations increased significantly with patient age (as regard travel time, this is explained by the higher proportion of home visits in higher age groups, as compared with visits at a health center). Examined according to location of the visit, contact duration per se (without travel) is higher for visits at home and in nursing homes than for those taking place at a health center. Looked at in respect to the care given (technical care, or basic nursing care, or both simultaneously), our data show that the provision of basic nursing care (alone or with technical care) doubles contact duration (from 20 to 42-45'). The analyses according to patient age shows that, at an advanced age (beyond 80 years particularly), there is an important increase of the visits where both types of care are given. However, contact duration per se shows a significant raise with age only for the group "technical care only"; it can be demonstrated that this is due to the fact that older patients require more complex technical acts (e.g., bladder care, as compared with simpler acts such as injection). A model of the relationships between patient age and contact duration is proposed: it is because of the increase in the proportions of home visits, of visits including basic nursing care, and of more complex technical acts that older persons require more of the working time of public health nurses.

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This study examines the inter-industry wage structure of the organised manufacturing sector in India for the period 1973-74 to 2003-04 by estimating the growth of average real wages for production workers by industry. In order to estimate the growth rates, the study adopts a methodological framework that differs from other studies in that the time series properties of the concerned variables are closely considered in order to obtain meaningful estimates of growth that are unbiased and (asymptotically) efficient. Using wage data on 51 manufacturing industries at three digit level of the National Industrial Classification 1998 (India), our estimation procedure obtains estimates of growth of real wages per worker that are deterministic in nature by accounting for any potential structural break(s). Our findings show that the inter-industry wage structure in India has changed a lot in the period 1973-74 to 2003-04 and that it provides some evidence that the inter-industry wage differences have become more pronounced in the post-reforms period. Thus this paper provides new evidence from India on the need to consider the hypothesis that industry affiliation is potentially an important determinant of wages when studying any relationship between reforms and wages.

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We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

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This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.

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According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.

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The genetic population of Triatoma sordida group 1, a secondary vector of Chagas disease in Bolivia, was studied by multi-locus enzyme electrophoresis. A total of 253 nymphal and adult specimens collected from seven neighbouring localities in the Velasco Province, Department of Santa Cruz, were processed. The relatively low genetic variability was confirmed for this species (rate of polymorphism: 0.20). The absence of genetic disequilibrium detected within the seven localities was demonstrated. A geographical structuration appears between localities with distances greater than 20 km apart. Although T. sordida presents a relatively reduced dispersive capacity, its panmictic unit is wider than compared with T. infestans. Genetic distances between T. sordida populations were correlated with geographic distance. Gene flow between geographic populations of T. sordida provides an efficient framework for effective vigilance and control protocols.

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Los Frameworks constituyen el nuevo paradigma en cuanto al desarrollo de software se refiere. Entre sus principales características se encuentran la facilidad para la reutilización de código. En este marco específico proporcionados por la tecnología usaremos la tecnología JAVA y su extensión en cuanto a la persistencia de datos. El Framework de persistencia es el responsable de gestionar la lógica de acceso a los datos en un SGBD (Sistema de Gestión de Bases de Datos), ya sea de entrada o salida, y ocultando los detalles más pesados relativos a la estructura propia de la Base de Datos utilizada, de manera completa y transparentemente. En conclusión, este proyecto se basa en un análisis del los Frameworks existentes, analizando sus características y profundizando en los detalles concretos de su actividad y manejo en cuanto a la persistencia.

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The trend of closely related taxa to retain similar environmental preferences mediated by inherited traits suggests that several patterns observed at the community scale originate from longer evolutionary processes. While the effects of phylogenetic relatedness have been previously studied within a single genus or family, lineage-specific effects on the ecological processes governing community assembly have rarely been studied for entire communities or flora. Here, we measured how community phylogenetic structure varies across a wide elevation gradient for plant lineages represented by thirty-five families, using a co-occurrence index and net relatedness index (NRI). We propose a framework that analyses each lineage separately and reveals the trend of ecological assembly at tree nodes. We found prevailing phylogenetic clustering for more ancient nodes and overdispersion in more recent tree nodes. Closely related species may thus rapidly evolve new environmental tolerances to radiate into distinct communities, while older lineages likely retain inherent environmental tolerances to occupy communities in similar environments, either through efficient dispersal mechanisms or the exclusion of older lineages with more divergent environmental tolerances. Our study illustrates the importance of disentangling the patterns of community assembly among lineages to better interpret the ecological role of traits. It also sheds light on studies reporting absence of phylogenetic signal, and opens new perspectives on the analysis of niche and trait conservatism across lineages.

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This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role isto provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

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The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

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This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

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This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.