976 resultados para Macro scale distributions


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Postprint (published version)

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The purpose of this study was to assess the cross-cultural validity of the Marlowe-Crowne Social Desirability scale short form C, in a large sample of French-speaking participants from eight African countries and Switzerland. Exploratory and confirmatory analyses suggested retaining a two-factor structure. Item bias detection according to country was conducted for all 13 items and effect was calculated with R2. For the two-factor solution, 9 items were associated with a negligible effect size, 3 items with a moderate one, and 1 item with a large one. A series of analyses of covariance considering the acquiescence variable as a covariate showed that the acquiescence tendency does not contribute to the bias at item level. This research indicates that the psychometric properties of this instrument do not reach a scalar equivalence but that a culturally reliable measurement of social desirability could be developed.

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A laboratory investigation was undertaken to determine the limiting model Reynolds number above which the scour behavior of rock protected structures can be reproduced in hydraulic models scaled according to the Froude criterion. A submerged jet was passed over an initially full scour pocket containing uniform glass spheres and the rate of scour was measured as a function of time. The dimensions of the scour pocket and jet and the particle diameters were varied as needed to maintain strict geometric similarity. For each of two different Froude numbers the Reynolds number was varied over a wide range. The normalized scour rate was found to be practically independent of the Reynolds number, R, (based on the jet velocity and particle diameter) at values of R above about 2.5 x 10^3, and to decrease with Rat smaller values. A grid placed in the jet was found to have a very strong effect on the scour rate. In an attempt to explain the effect of R on the scour behavior, turbulent pressure and velocity fluctuations were measured in air flows and water flows, respectively, over rigid scour pockets having the same geometry as those formed in the scour experiments. The normalized spectra of the fluctuations were found to be nearly independent of R, but the flow pattern was found to be very sensitive to the inlet condition, the jet deflecting upward or downward in a not wholly explainable manner. This indicates that scour behavior can be modeled only if the approach flow is also accurately modeled.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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AIM: People suffering from mental illness are exposed to stigma. However, only few tools are available to assess stigmatization as perceived from the patient's perspective. The aim of this study is to adapt and validate a French version of the Stigma Scale (King et al., 2007 [8]). This self-report questionnaire has a three-factor structure: discrimination, disclosure and positive aspects of mental illness. Discrimination subscale refers to perceived negative reactions of others. Disclosure subscale refers mainly to managing disclosure to avoid discrimination and finally positive aspects subscale taps into how patients are becoming more accepting, more understanding toward their illness. METHOD: In the first step, internal consistency, convergent validity and test-retest reliability of the French adaptation of the 28-item scale were assessed in a sample of 183 patients. Results of confirmatory factor analyses (CFA) did not confirm the hypothesized structure. In the light of the failed attempts to validate the original version, an alternative 9-item short-form version of the Stigma Scale, maintaining the integrity of the original model, was developed based on results of exploratory factor analyses in the first sample and cross-validated in a new sample of 234 patients. RESULTS: Results of CFA did not confirm that the data fitted well to the three-factor model of the 28-item Stigma Scale (χ(2)/df=2.02, GFI=0.77, AGFI=0.73, RMSEA=0.07, CFI=0.77 and NNFI=0.75). Cronbach's α was excellent for discrimination (0.84) and disclosure (0.83) subscales but poor for potential positive aspects (0.46). External validity was satisfactory. Overall Stigma Scale total score was negatively correlated with the score on Rosenberg's Self-Esteem Scale (r=-0.49), and each subscale was significantly correlated with a visual analogue scale that referred to the specific aspect of stigma (0.43≤|r|≤0.60). Intraclass correlation coefficients between 0.68 and 0.89 indicated good test-retest reliability. The results of the CFA demonstrated that the items chosen for the short version of the Stigma Scale have the expected fit properties (χ(2)/df=1.02, GFI=0.98, AGFI=0.98, RMSEA=0.01, CFI=1.0 and NNFI=1.0). Considering the small number (three) of items in each subscale of the short version of the Stigma Scale, α coefficients for discrimination (0.57), disclosure (0.80) and potential positive aspects subscales (0.62) are considered as good. CONCLUSION: Our results suggest that the 9-item French short version of the Stigma Scale is a useful, reliable and valid self-report questionnaire to assess perceived stigmatization in people suffering from mental illness. The time of completion is really short and questions are well understood and accepted by the patients.

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The use of herbicides in agriculture may lead to environmental problems, such as surface water pollution, with a potential risk for aquatic organisms. The herbicide glyphosate is the most used active ingredient in the world and in Switzerland. In the Lavaux vineyards it is nearly the only molecule applied. This work aimed at studying its fate in soils and its transfer to surface waters, using a multi-scale approach: from molecular (10-9 m) and microscopic scales (10-6 m), to macroscopic (m) and landscape ones (103 m). First of all, an analytical method was developed for the trace level quantification of this widely used herbicide and its main by-product, aminomethylphosphonic acid (AMPA). Due to their polar nature, their derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl) was done prior to their concentration and purification by solid phase extraction. They were then analyzed by ultra performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). The method was tested in different aqueous matrices with spiking tests and validated for the matrix effect correction in relevant environmental samples. Calibration curves established between 10 and 1000ng/l showed r2 values above 0.989, mean recoveries varied between 86 and 133% and limits of detection and quantification of the method were as low as 5 and 10ng/l respectively. At the parcel scale, two parcels of the Lavaux vineyard area, located near the Lutrive River at 6km to the east of Lausanne, were monitored to assess to which extent glyphosate and AMPA were retained in the soil or exported to surface waters. They were equipped at their bottom with porous ceramic cups and runoff collectors, which allowed retrieving water samples for the growing seasons 2010 and 2011. Results revealed that the mobility of glyphosate and AMPA in the unsaturated zone was likely driven by the precipitation regime and the soil characteristics, such as slope, porosity structure and layer permeability discrepancy. Elevated glyphosate and AMPA concentrations were measured at 60 and 80 cm depth at parcel bottoms, suggesting their infiltration in the upper parts of the parcels and the presence of preferential flow in the studied parcels. Indeed, the succession of rainy days induced the gradual saturation of the soil porosity, leading to rapid infiltration through macropores, as well as surface runoff formation. Furthermore, the presence of more impervious weathered marls at 100 cm depth induced throughflows, the importance of which for the lateral transport of the herbicide molecules was determined by the slope steepness. Important rainfall events (>10 mm/day) were clearly exporting molecules from the soil top layer, as indicated by important concentrations in runoff samples. A mass balance showed that total loss (10-20%) mainly occurred through surface runoff (96%) and, to a minor extent, by throughflows in soils (4%), with subsequent exfiltration to surface waters. Observations made in the Lutrive River revealed interesting details of glyphosate and AMPA dynamics in urbanized landscapes, such as the Lavaux vineyards. Indeed, besides their physical and chemical properties, herbicide dynamics at the catchment level strongly depend on application rates, precipitation regime, land use and also on the presence of drains or constructed channels. Elevated concentrations, up to 4970 ng/l, observed just after the application, confirmed the diffuse export of these compounds from the vineyard area by surface runoff during main rain events. From April to September 2011, a total load of 7.1 kg was calculated, with 85% coming from vineyards and minor urban sources and 15% from arable crops. Small vineyard surfaces could generate high concentrations of herbicides and contribute considerably to the total load calculated at the outlet, due to their steep slopes (~10%). The extrapolated total amount transferred yearly from the Lavaux vineyards to the Lake of Geneva was of 190kg. At the molecular scale, the possible involvement of dissolved organic matter (DOM) in glyphosate and copper transport was studied using UV/Vis fluorescence spectroscopy. Combined with parallel factor (PARAFAC) analysis, this technique allowed characterizing DOM of soil and surface water samples from the studied vineyard area. Glyphosate concentrations were linked to the fulvic-like spectroscopic signature of DOM in soil water samples, as well as to copper, suggesting the formation of ternary complexes. In surface water samples, its concentrations were also correlated to copper ones, but not in a significant way to the fulvic-like signature. Quenching experiments with standards confirmed field tendencies in the laboratory, with a stronger decrease in fluorescence intensity for fulvic-like fluorophore than for more aromatic ones. Lastly, based on maximum concentrations measured in the river, an environmental risk for these compounds was assessed, using laboratory tests and ecotoxicity data from the literature. In our case and with the methodology applied, the risk towards aquatic species was found negligible (RF<1).

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Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

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The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

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This publication was prepared to describe how the Iowa State University distillery has been operating, including information on distillery size, equipment, tanks, condenser, heat exchanger, pumps and the process. Photos and diagrams are also included.

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Because self-reported health status [SRHS] is an ordered response variable, inequality measurement for SRHS data requires a numerical scale for converting individual responses into a summary statistic. The choice of scale is however problematic, since small variations in the numerical scale may reverse the ordering of a given pair of distributions of SRHS data in relation to conventional inequality indices such as the variance. This paper introduces a parametric family of inequality indices, founded on an inequality ordering proposed by Allison and Foster [Allison, R.A., Foster, J., 2004. Measuring health inequalities using qualitative data. Journal of Health Economics 23, 505-524], which satisfy a suitable invariance property with respect to the choice of numerical scale. Several key members of the parametric family are also derived, and an empirical application using data from the Swiss Health Survey illustrates the proposed methodology. [Authors]

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Connectivity among populations plays a crucial role in maintaining genetic variation at a local scale, especially in small populations affected strongly by genetic drift. The negative consequences of population disconnection on allelic richness and gene diversity (heterozygosity) are well recognized and empirically established. It is not well recognized, however, that a sudden drop in local effective population size induced by such disconnection produces a temporary disequilibrium in allelic frequency distributions that is akin to the genetic signature of a demographic bottleneck. To document this effect, we used individual-based simulations and empirical data on allelic richness and gene diversity in six pairs of isolated versus well-connected (core) populations of European tree frogs. In our simulations, population disconnection depressed allelic richness more than heterozygosity and thus resulted in a temporary excess in gene diversity relative to mutation drift equilibrium (i.e., signature of a genetic bottleneck). We observed a similar excess in gene diversity in isolated populations of tree frogs. Our results show that population disconnection can create a genetic bottleneck in the absence of demographic collapse.

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This paper introduces a mixture model based on the beta distribution, without preestablishedmeans and variances, to analyze a large set of Beauty-Contest data obtainedfrom diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a bettert of the experimental data, and more precision to the hypothesis that a large proportionof individuals follow a common pattern of reasoning, described as iterated best reply (degenerate),than mixture models based on the normal distribution. The analysis shows thatthe means of the distributions across the groups of experiments are pretty stable, while theproportions of choices at dierent levels of reasoning vary across groups.