913 resultados para Conners’ parent rating scale
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Programa Doutoral em Engenharia Mecânica.
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Dissertação de mestrado em Português Língua Não Materna (PLNM): Português Língua Estrangeira (PLE) Português Língua Segunda (PL2)
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Magdeburg, Univ., Fak. für Mathematik, Diss., 2013
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Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2013
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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014
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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014
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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014
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Magdeburg, Univ., Fak. für Mathematik, Diss., 2015
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In microeconomic analysis functions with diminishing returns to scale (DRS) have frequently been employed. Various properties of increasing quasiconcave aggregator functions with DRS are derived. Furthermore duality in the classical sense as well as of a new type is studied for such aggregator functions in production and consumer theory. In particular representation theorems for direct and indirect aggregator functions are obtained. These involve only small sets of generator functions. The study is carried out in the contemporary framework of abstract convexity and abstract concavity.
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This paper presents an outline of rationale and theory of the MuSIASEM scheme (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism). First, three points of the rationale behind our MuSIASEM scheme are discussed: (i) endosomatic and exosomatic metabolism in relation to Georgescu-Roegen’s flow-fund scheme; (2) the bioeconomic analogy of hypercycle and dissipative parts in ecosystems; (3) the dramatic reallocation of human time and land use patterns in various sectors of modern economy. Next, a flow-fund representation of the MUSIASEM scheme on three levels (the whole national level, the paid work sectors level, and the agricultural sector level) is illustrated to look at the structure of the human economy in relation to two primary factors: (i) human time - a fund; and (ii) exosomatic energy - a flow. The three levels representation uses extensive and intensive variables simultaneously. Key conceptual tools of the MuSIASEM scheme - mosaic effects and impredicative loop analysis - are explained using the three level flow-fund representation. Finally, we claim that the MuSIASEM scheme can be seen as a multi-purpose grammar useful to deal with sustainability issues.
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Acquired behavioral changes have essentially been described in advanced multiple sclerosis (MS). The present study was designed to determine whether behavioral modifications specifically related to the MS pathological process could be identified in the initial phase of the disease, as compared to control patients with chronic, relapsing and progressive inflammatory disorders not involving the central nervous system (CNS). Eighty-eight early MS patients (Expanded Disability Status Scale score <or= 2.5) and 48 controls were tested. Perceived changes by informants in behavioral control, goal-directed behavior, decision making, emotional expression, insight and interpersonal relationships were assessed using the Iowa Scale of Personality Change (ISPC). Executive behavioral disturbances were screened using the Dysexecutive Questionnaire (DEX). The mean change between the premorbid and postmorbid ISPC ratings was similar in the MS [12.2 (SD 15.6)] and in the control [11.5 (SD 15.1)] group. The perceived behavioral changes (PBCs) most frequently reported in both groups were lack of stamina, lability/moodiness, anxiety, vulnerability to stress and irritability. Pathological scores in the DEX were also similar in both groups. Correlations between PBCs and DEX scores were different in MS and control groups. MS patients with cognitive impairment had a marginally higher number of PBCs than control patients (p=0.056) and a significantly higher DEXp score (p=0.04). These results suggest that (1) PBCs occurring in early MS patients were not different from those induced by comparable chronic non-CNS disorders, (2) qualitative differences in the relationship between behavioral symptoms and executive-behavioral changes may exist between MS and control groups, and (3) behavioral symptoms seem associated with cognitive deficits in MS. We further plan to assess these observations longitudinally.
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Aim: Determine the frequency and predictors of sleep disorders in boys with Duchenne Muscular Dystrophy (DMD). Method: Cross-sectional study by postal questionnaire. Sleep disturbances were assessed using the Sleep Disturbance Scale for Children (validated on 1157 healthy children). A total sleep score and six sleep disturbance factors representing the most common sleep disorders were computed. Potential associations between pathological scores and personal, medical and environmental factors were assessed. Results: Sixteen of 63 boys (25.4%) had a pathological total sleep score compared with 3% in the general population. The most prevalent sleep disorders were disorders of initiating and maintaining sleep (DIMS) 29.7%, sleep-related breathing disorders 15.6% and sleep hyperhydrosis 14.3%. On multivariate analysis, pathological total sleep scores were associated with the need to be moved by a carer (OR = 9.4; 95%CI: 2.2-40.7; p = 0.003) and being the child of a single-parent family (OR = 7.2; 95%CI: 1.5-35.1; p = 0.015) and DIMS with the need to be moved by a carer (OR = 18.0; 95%CI: 2.9-110.6; p = 0.002), steroid treatment (OR = 7.7; 95%CI: 1.4-44.0; p = 0.021) and being the child of a single-parent family (OR = 7.0; 95%CI: 1.3-38.4; p = 0.025). Conclusion: Sleep disturbances are frequent in boys with DMD and are strongly associated with immobility. Sleep should be systematically assessed in DMD to implement appropriate interventions.
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PURPOSE: The Cancer Vaccine Consortium of the Cancer Research Institute (CVC-CRI) conducted a multicenter HLA-peptide multimer proficiency panel (MPP) with a group of 27 laboratories to assess the performance of the assay. EXPERIMENTAL DESIGN: Participants used commercially available HLA-peptide multimers and a well characterized common source of peripheral blood mononuclear cells (PBMC). The frequency of CD8+ T cells specific for two HLA-A2-restricted model antigens was measured by flow cytometry. The panel design allowed for participants to use their preferred staining reagents and locally established protocols for both cell labeling, data acquisition and analysis. RESULTS: We observed significant differences in both the performance characteristics of the assay and the reported frequencies of specific T cells across laboratories. These results emphasize the need to identify the critical variables important for the observed variability to allow for harmonization of the technique across institutions. CONCLUSIONS: Three key recommendations emerged that would likely reduce assay variability and thus move toward harmonizing of this assay. (1) Use of more than two colors for the staining (2) collect at least 100,000 CD8 T cells, and (3) use of a background control sample to appropriately set the analytical gates. We also provide more insight into the limitations of the assay and identified additional protocol steps that potentially impact the quality of data generated and therefore should serve as primary targets for systematic analysis in future panels. Finally, we propose initial guidelines for harmonizing assay performance which include the introduction of standard operating protocols to allow for adequate training of technical staff and auditing of test analysis procedures.
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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.