4 resultados para Uncertainty and reasoning, Sets of probability measures, Bayesian networks, Multilinear programming.

em WestminsterResearch - UK


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CONTEXT: Existing data regarding the association between growth hormone deficiency (GHD) and liver fat content are conflicting. OBJECTIVE: We aimed i) to assess intrahepatocellular lipid (IHCL) content in hypopituitary adults with GHD compared to matched controls and ii) to evaluate the effect of growth hormone (GH) replacement on IHCL content. DESIGN: Cross-sectional comparison and controlled intervention study. PATIENTS, PARTICIPANTS: Cross-sectional comparison: 22 hypopituitary adults with GHD and 44 healthy controls matched for age, BMI, gender and ethnicity. Intervention study: 9 GHD patients starting GH replacement (GH Rx group), 9 GHD patients not starting replacement therapy (non-GH Rx group). INTERVENTION: Intervention study:GH replacement for 6 months in the GH Rx group, dosage was titrated to achieve normal IGF-1 levels. MAIN OUTCOME MEASURES: IHCL content determined by proton magnetic resonance spectroscopy (1 H MRS). RESULTS: Cross-sectional comparison: There was no difference in IHCL content between GHD patients and healthy controls (1.89% (0.30, 4.03) vs. 1.14% (0.22, 2.32); p=0.2), the prevalence of patients with hepatic steatosis (IHCL of ≥ 5.56%) was similar in the two groups (22.7% vs. 15.9%; chi square probability = 0.4). Intervention study: The change in IHCL content over 6 months did not differ between the GH Rx group and the non-GH Rx group (-0.63 ± 4.53% vs. +0.11 ± 1.46%; p=0.6). CONCLUSIONS: In our study liver fat content and the prevalence of hepatic steatosis did not differ between hypopituitary adults with GHD and matched controls. In GHD patients GH replacement had no effect on liver fat content.

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Previous research on the prediction of fiscal aggregates has shown evidence that simple autoregressive models often provide better forecasts of fiscal variables than multivariate specifications. We argue that the multivariate models considered by previous studies are small-scale, probably burdened by overparameterization, and not robust to structural changes. Bayesian Vector Autoregressions (BVARs), on the other hand, allow the information contained in a large data set to be summarized efficiently, and can also allow for time variation in both the coefficients and the volatilities. In this paper we explore the performance of BVARs with constant and drifting coefficients for forecasting key fiscal variables such as government revenues, expenditures, and interest payments on the outstanding debt. We focus on both point and density forecasting, as assessments of a country’s fiscal stability and overall credit risk should typically be based on the specification of a whole probability distribution for the future state of the economy. Using data from the US and the largest European countries, we show that both the adoption of a large system and the introduction of time variation help in forecasting, with the former playing a relatively more important role in point forecasting, and the latter being more important for density forecasting.

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Energy-using Products (EuPs) contribute significantly to the United Kingdom’s CO2 emissions, both in the domestic and non-domestic sectors. Policies that encourage the use of more energy efficient products (such as minimum performance standards, energy labelling, enhanced capital allowances, etc.) can therefore generate significant reductions in overall energy consumption and hence, CO2 emissions. While these policies can impose costs on the producers and consumers of these products in the short run, the process of product innovation may reduce the magnitude of these costs over time. If this is the case, then it is important that the impacts of innovation are taken into account in policy impact assessments. Previous studies have found considerable evidence of experience curve effects for EuP categories (e.g. refrigerators, televisions, etc.), with learning rates of around 20% for both average unit costs and average prices; similar to those found for energy supply technologies. Moreover, the decline in production costs has been accompanied by a significant improvement in the energy efficiency of EuPs. Building on these findings and the results of an empirical analysis of UK sales data for a range of product categories, this paper sets out an analytic framework for assessing the impact of EuP policy interventions on consumers and producers which takes explicit account of the product innovation process. The impact of the product innovation process can be seen in the continuous evolution of the energy class profiles of EuP categories over time; with higher energy classes (e.g. A, A+, etc.) entering the market and increasing their market share, while lower classes (e.g. E, F, etc.) lose share and then leave the market. Furthermore, the average prices of individual energy classes have declined over their respective lives, while new classes have typically entered the market at successively lower “launch prices”. Based on two underlying assumptions regarding the shapes of the “lifecycle profiles” for the relative sales and the relative average mark-ups of individual energy classes, a simple simulation model is developed that can replicate the observed market dynamics in terms of the evolution of market shares and average prices. The model is used to assess the effect of two alternative EuP policy interventions – a minimum energy performance standard and an energy-labelling scheme – on the average unit cost trajectory and the average price trajectory of a typical EuP category, and hence the financial impacts on producers and consumers.

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OBJECTIVE: To provide a detailed phenotype/genotype characterization of Bietti crystalline dystrophy (BCD). DESIGN: Observational case series. PARTICIPANTS: Twenty patients from 17 families recruited from a multiethnic British population. METHODS: Patients underwent color fundus photography, near-infrared (NIR) imaging, fundus autofluorescence (FAF) imaging, spectral domain optical coherence tomography (SD-OCT), and electroretinogram (ERG) assessment. The gene CYP4V2 was sequenced. MAIN OUTCOME MEASURES: Clinical, imaging, electrophysiologic, and molecular genetics findings. RESULTS: Patients ranged in age from 19 to 72 years (median, 40 years), with a visual acuity of 6/5 to perception of light (median, 6/12). There was wide intrafamilial and interfamilial variability in clinical severity. The FAF imaging showed well-defined areas of retinal pigment epithelium (RPE) loss that corresponded on SD-OCT to well-demarcated areas of outer retinal atrophy. Retinal crystals were not evident on FAF imaging and were best visualized with NIR imaging. Spectral domain OCT showed them to be principally located on or in the RPE/Bruch's membrane complex. Disappearance of the crystals, revealed by serial recording, was associated with severe disruption and thinning of the RPE/Bruch's membrane complex. Cases with extensive RPE degeneration (N = 5) had ERGs consistent with generalized rod and cone dysfunction, but those with more focal RPE atrophy showed amplitude reduction without delay (N = 3), consistent with restricted loss of function, or that was normal (N = 2). Likely disease-causing variants were identified in 34 chromosomes from 17 families. Seven were novel, including p.Met66Arg, found in all 11 patients from 8 families of South Asian descent. This mutation appears to be associated with earlier onset (median age, 30 years) compared with other substitutions (median age, 41 years). Deletions of exon 7 were associated with more severe disease. CONCLUSIONS: The phenotype is highly variable. Several novel variants are reported, including a highly prevalent substitution in patients of South Asian descent that is associated with earlier-onset disease. Autofluorescence showed sharply demarcated areas of RPE loss that coincided with abrupt edges of outer retinal atrophy on SD-OCT; crystals were generally situated on or in the RPE/Bruch's complex but could disappear over time with associated RPE disruption. These results support a role for the RPE in disease pathogenesis.