319 resultados para Error Function


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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

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OBJECTIVES: The objective of this study was to evaluate associations between aortic pulse wave velocity (PWV) and aortic and carotid vessel wall thickness (VWT) using cardiovascular magnetic resonance imaging (MRI) in patients with hypertension as compared with healthy adult volunteers. MATERIALS AND METHODS: Local medical ethics approval was obtained and the participants gave informed consent. Fifteen patients with hypertension (5 men and 10 women; mean [SD] age, 49 [14] years) and 15 age- and sex-matched healthy volunteers were prospectively included and compared. All participants underwent MRI examination for measuring aortic and carotid VWT and aortic PWV with well-validated MRI techniques at 1.5- and 3-T MRI systems: PWV was assessed from velocity-encoded MRI and VWT was assessed by using dual-inversion black-blood gradient-echo imaging techniques. Paired t tests were used for testing differences between the volunteers and the patients and Pearson correlation (r) and univariable and multivariable stepwise linear regression analyses were used to test associations between aortic and carotid arterial wall thickness and stiffness. RESULTS: Mean values for aortic PWV and aortic and carotid VWT (indexed for body surface area [BSA]) were all significantly higher in patients with hypertension as compared with the healthy volunteers (ie, aortic PWV, 7.0 ± 1.4 m/s vs 5.7 ± 1.3 m/s; aortic VWT/BSA, 0.12 ± 0.03 mL/m vs 0.10 ± 0.03 mL/m; carotid VWT/BSA, 0.04 ± 0.01 mL/m vs 0.03 ± 0.01 mL/m; all P < 0.01). Aortic PWV was highly correlated with aortic VWT/BSA (r = 0.76 and P = 0.002 in the patients vs r = 0.63 and P = 0.02 in the volunteers), and in the patients, aortic PWV was moderately correlated with carotid VWT/BSA (r = 0.50; P = 0.04). In the volunteers, correlation between aortic PWV and carotid VWT/BSA was not significant (r = 0.40; P = 0.13). In addition, aortic VWT/BSA was significantly correlated with carotid VWT/BSA, in both the patients (r = 0.60; P = 0.005) and volunteers (r = 0.57; P = 0.007). CONCLUSIONS: In the patients with hypertension and the healthy volunteers, the aortic PWV is associated more strongly with aortic wall thickness than with carotid wall thickness, reflecting site-specific coupling between vascular wall thickness and function.

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The CD8alphabeta heterodimer is integral to the selection of the class I-restricted lineage in the thymus; however, the contribution of the CD8beta chain to coreceptor function is poorly understood. To understand whether the CD8beta membrane proximal stalk region played a role in coreceptor function, we substituted it with the corresponding sequence from the CD8alpha polypeptide and expressed the hybrid molecule in transgenic mice in place of endogenous CD8beta. Although the stalk-swapped CD8beta was expressed on the cell surface as a disulfide-bonded heterodimer at equivalent levels of expression to an endogenous CD8beta molecule, it failed to restore selection of CD8(+) class I MHC-restricted T cells and it altered the response of peripheral T cells. Thus, the stalk region of the CD8beta polypeptide has an essential role in ensuring functionality of the CD8alphabeta heterodimer and its replacement compromises the interaction of CD8 with peptide-MHC complexes.

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CD8(+) T-cell functions are critical for preventing chronic viral infections by eliminating infected cells. For healthy immune responses, beneficial destruction of infected cells must be balanced against immunopathology resulting from collateral damage to tissues. These processes are regulated by factors controlling CD8(+) T-cell function, which are still incompletely understood. Here, we show that the interferon regulatory factor 4 (IRF4) and its cooperating binding partner B-cell-activating transcription factor (BATF) are necessary for sustained CD8(+) T-cell effector function. Although Irf4(-/-) CD8(+) T cells were initially capable of proliferation, IRF4 deficiency resulted in limited CD8(+) T-cell responses after infection with the lymphocytic choriomeningitis virus. Consequently, Irf4(-/-) mice established chronic infections, but were protected from fatal immunopathology. Absence of BATF also resulted in reduced CD8(+) T-cell function, limited immunopathology, and promotion of viral persistence. These data identify the transcription factors IRF4 and BATF as major regulators of antiviral cytotoxic T-cell immunity.