984 resultados para quasi-likelihood function


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Kinematic functional evaluation with body-worn sensors provides discriminative and responsive scores after shoulder surgery, but the optimal movements' combination has not yet been scientifically investigated. The aim of this study was the development of a simplified shoulder function kinematic score including only essential movements. The P Score, a seven-movement kinematic score developed on 31 healthy participants and 35 patients before surgery and at 3, 6 and 12 months after shoulder surgery, served as a reference.Principal component analysis and multiple regression were used to create simplified scoring models. The candidate models were compared to the reference score. ROC curve for shoulder pathology detection and correlations with clinical questionnaires were calculated.The B-B Score (hand to the Back and hand upwards as to change a Bulb) showed no difference to the P Score in time*score interaction (P > .05) and its relation with the reference score was highly linear (R(2) > .97). Absolute value of correlations with clinical questionnaires ranged from 0.51 to 0.77. Sensitivity was 97% and specificity 94%.The B-B and reference scores are equivalent for the measurement of group responses. The validated simplified scoring model presents practical advantages that facilitate the objective evaluation of shoulder function in clinical practice.

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We have studied the interaction between the low-lying transverse collective oscillations and the thermal excitations of an elongated Bose-Einstein condensate by means of perturbation theory. We consider a cylindrical trapped condensate and calculate the transverse elementary excitations at zero temperature by solving the linearized Gross-Pitaevskii equations in two dimensions (2D). We use them to calculate the matrix elements between the thermal excited states and the quasi-2D collective modes. The Landau damping of transverse collective modes is studied as a function of temperature. At low temperatures, the corresponding damping rate is in agreement with the experimental data for the decay of the transverse quadrupole mode, but it is too small to explain the observed slow decay of the transverse breathing mode. The reason for this discrepancy is discussed.

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For a few years now, the study of quantum field theories in partially compactified space-time manifolds has acquired increasing importance in several domains of quantum physics. Let me just mention the issues of dimensional reduction and spontaneous compactification, and the multiple questions associated with the study of quantum field theories in the presence of boundaries (like the Casimir effect) and on curved space-time (manifolds with curvature and nontrivial topology), a step towards quantum gravity.

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Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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OBJECTIVES: Tenofovir is associated with reduced renal function. It is not clear whether patients can be expected to fully recover their renal function if tenofovir is discontinued. METHODS: We calculated the estimated glomerular filtration rate (eGFR) for patients in the Swiss HIV Cohort Study remaining on tenofovir for at least 1 year after starting a first antiretroviral therapy regimen with tenofovir and either efavirenz or the ritonavir-boosted protease inhibitor lopinavir, atazanavir or darunavir. We estimated the difference in eGFR slope between those who discontinued tenofovir after 1 year and those who remained on tenofovir. RESULTS: A total of 1049 patients on tenofovir for at least 1 year were then followed for a median of 26 months, during which time 259 patients (25%) discontinued tenofovir. After 1 year on tenofovir, the difference in eGFR between those starting with efavirenz and those starting with lopinavir, atazanavir and darunavir was - 0.7 [95% confidence interval (CI) -2.3 to 0.8], -1.4 (95% CI -3.2 to 0.3) and 0.0 (95% CI -1.7 to 1.7) mL/min/1.73 m(2) , respectively. The estimated linear rate of decline in eGFR on tenofovir was -1.1 (95% CI -1.5 to -0.8) mL/min/1.73 m(2) per year and its recovery after discontinuing tenofovir was 2.1 (95% CI 1.3 to 2.9) mL/min/1.73 m(2) per year. Patients starting tenofovir with either lopinavir or atazanavir appeared to have the same rates of decline and recovery as those starting tenofovir with efavirenz. CONCLUSIONS: If patients discontinue tenofovir, clinicians can expect renal function to recover more rapidly than it declined.