950 resultados para generalized assignment


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Generalized pustular psoriasis is an unstable inflammatory type of psoriasis, with widespread areas of erythema and sterile pustules, associated with fever and systemic symptoms. Infliximab is a monoclonal antibody with anti-TNFalpha activity, approved for use in psoriasis. We describe a male patient with a long history of stable arthropathic psoriasis, hospitalized with a generalized pustular psoriasis and acute exacerbation of articular complaints. The disease was resistant to multiple therapies (acitretin, methotrexate and corticosteroids), so the patient was started on infliximab, with a very rapid response of both cutaneous and articular symptoms. He had complete clearing of lesions at week 12, and marked improvement of the articular symptoms. No recurrence occurred at 8 months of follow-up with infliximab every 8 weeks. Infliximab had an extremely rapid therapeutic action response on a recalcitrant generalized pustular psoriasis. The articular response was also excellent, with significant improvement of quality of life.

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Biomol NMR Assign (2007) 1:81–83 DOI 10.1007/s12104-007-9022-3

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Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

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Contém resumo

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Total generalized lipodystrophy (Berardinelli--Seip Syndrome) is a rare hereditary disease characterized by insulin-resistant diabetes mellitus and a small quantity of adipose tissue and is of unknown origin. Common cardiovascular alterations related to this syndrome are cardiac hypertrophy and arterial hypertension. This article reports a case of Berardinelli--Seip syndrome and reviews the literature with special emphasis on the cardiovascular manifestations of this syndrome.

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Este proyecto propone extender y generalizar los procesos de estimación e inferencia de modelos aditivos generalizados multivariados para variables aleatorias no gaussianas, que describen comportamientos de fenómenos biológicos y sociales y cuyas representaciones originan series longitudinales y datos agregados (clusters). Se genera teniendo como objeto para las aplicaciones inmediatas, el desarrollo de metodología de modelación para la comprensión de procesos biológicos, ambientales y sociales de las áreas de Salud y las Ciencias Sociales, la condicionan la presencia de fenómenos específicos, como el de las enfermedades.Es así que el plan que se propone intenta estrechar la relación entre la Matemática Aplicada, desde un enfoque bajo incertidumbre y las Ciencias Biológicas y Sociales, en general, generando nuevas herramientas para poder analizar y explicar muchos problemas sobre los cuales tienen cada vez mas información experimental y/o observacional.Se propone, en forma secuencial, comenzando por variables aleatorias discretas (Yi, con función de varianza menor que una potencia par del valor esperado E(Y)) generar una clase unificada de modelos aditivos (paramétricos y no paramétricos) generalizados, la cual contenga como casos particulares a los modelos lineales generalizados, no lineales generalizados, los aditivos generalizados, los de media marginales generalizados (enfoques GEE1 -Liang y Zeger, 1986- y GEE2 -Zhao y Prentice, 1990; Zeger y Qaqish, 1992; Yan y Fine, 2004), iniciando una conexión con los modelos lineales mixtos generalizados para variables latentes (GLLAMM, Skrondal y Rabe-Hesketh, 2004), partiendo de estructuras de datos correlacionados. Esto permitirá definir distribuciones condicionales de las respuestas, dadas las covariables y las variables latentes y estimar ecuaciones estructurales para las VL, incluyendo regresiones de VL sobre las covariables y regresiones de VL sobre otras VL y modelos específicos para considerar jerarquías de variación ya reconocidas. Cómo definir modelos que consideren estructuras espaciales o temporales, de manera tal que permitan la presencia de factores jerárquicos, fijos o aleatorios, medidos con error como es el caso de las situaciones que se presentan en las Ciencias Sociales y en Epidemiología, es un desafío a nivel estadístico. Se proyecta esa forma secuencial para la construcción de metodología tanto de estimación como de inferencia, comenzando con variables aleatorias Poisson y Bernoulli, incluyendo los existentes MLG, hasta los actuales modelos generalizados jerárquicos, conextando con los GLLAMM, partiendo de estructuras de datos correlacionados. Esta familia de modelos se generará para estructuras de variables/vectores, covariables y componentes aleatorios jerárquicos que describan fenómenos de las Ciencias Sociales y la Epidemiología.

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The morphological characteristics of the mandible of adult Chaetophractus vellerosus (Gray, 1865) and Zaedyus pichiy (Desmarest, 1804) were studied to establish its generalized design and to identify inter- and intra- (sexual) specific differences. Morphological descriptions were complemented with the application of univariate and multivariate (analysis of correlation matrices, PCA, discriminant analysis) techniques. The mandible of both species is very similar, and is characterized by elevated condyle, well developed angular process, distinct coronoid process, tooth row which extends to the rear end of the angle between body and ramus, and unfused but firm symphysis. Although both armadillos are omnivorous, a more slender configuration of the jaw in Z. pichiy could be indicative of a better adaptation of its masticatory apparatus to insectivory. The PCA showed an almost total segregation of both species on PC1 (47.7% of the total variance), with C. vellerosus being associated to mandibles taller and with wider body and ramus. Zaedyus pichiy was characterized by heavy loadings of length parameters on PC2 (22.6% of the variance). A small degree of sexual dimorphism was found, with size-based differences in C. vellerosus (larger mandibles in females) and shape-based differences in Z. pichiy (taller mandibles in males, longer ones in females). Correlations between variables were higher in males of both species, indicating a more stable shape of the mandible than in females. The selected parameters to discriminate sexes were the body length of the mandible in C. vellerosus (correct classification: ca. 86% in males, 81% in females), and the height of the mandible at the level of the last tooth in Z. pichiy (near 85% of right assignment in both sexes). The inclusion of a new variable (body length) in the latter species improved the classification of the females to 100%. Teeth are typically 10 in C. vellerosus and 9 in Z. pichiy, but aberrancies in this basic number, such as unilateral or bilateral extra or fewer teeth, are common.

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"Vegeu el resum a l'inici del document del fitxer adjunt"

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We analyze situations in which a group of agents (and possibly a designer) have to reach a decision that will affect all the agents. Examples of such scenarios are the location of a nuclear reactor or the siting of a major sport event. To address the problem of reaching a decision, we propose a one-stage multi-bidding mechanism where agents compete for the project by submitting bids. All Nash equilibria of this mechanism are efficient. Moreover, the payoffs attained in equilibrium by the agents satisfy intuitively appealing lower bounds..

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There is a relation between the generalized Property R Conjecture and the Schoenflies Conjecture that suggests a new line of attack on the latter. The new approach gives a quick proof of the genus 2 Schoenflies Conjecture and suffices to prove the genus 3 case, even in the absence of new progress on the generalized Property R Conjecture.

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In this paper, a new class of generalized backward doubly stochastic differential equations is investigated. This class involves an integral with respect to an adapted continuous increasing process. A probabilistic representation for viscosity solutions of semi-linear stochastic partial differential equations with a Neumann boundary condition is given.

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We construct generating trees with with one, two, and three labels for some classes of permutations avoiding generalized patterns of length 3 and 4. These trees are built by adding at each level an entry to the right end of the permutation, which allows us to incorporate the adjacency condition about some entries in an occurrence of a generalized pattern. We use these trees to find functional equations for the generating functions enumerating these classes of permutations with respect to different parameters. In several cases we solve them using the kernel method and some ideas of Bousquet-Mélou [2]. We obtain refinements of known enumerative results and find new ones.

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There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.