966 resultados para Subgrid-scale Modelling


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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 scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows 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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Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as suitable for rare native species and also predicted as highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated to similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions

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L'objectif de l'étude présentée est d'adapter et de valider une version française de la Stigma Scale (King, 2007) auprès d'une population de personnes souffrant de troubles psychiques. Dans une première phase, la stabilité temporelle (fidélité test-retest), la cohérence interne et la validité convergente de l'instrument original à 28 items traduit en français ont été évaluées auprès d'un échantillon de 183 patients. Les résultats d'analyses factorielles confirmatoires ne nous ont pas permis de confirmer la structure originale de l'instrument. Nous avons donc proposé, sur la base des résultats d'une analyse factorielle exploratoire, une version courte de l'échelle de stigmatisation (9 items) qui conserve la structure en trois facteurs du modèle original. Dans une deuxième phase, nous avons examiné les qualités psychométriques et validé cette version abrégée de l'échelle de stigmatisation auprès d'un second échantillon de 234 patients. Les indices d'ajustements de notre analyse factorielle confirmatoire confirme la structure en trois facteurs de la version abrégée de la Stigma Scale. Les résultats suggèrent que la version française abrégée de l'échelle de stigmatisation constitue un instrument utile, fiable et valide dans l'autoévaluation de la stigmatisation perçue par des personnes souffrant de troubles psychiques. - 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, 2007). This self-report questionnaire has a three-factor structure: discrimination, disclosure and positive aspects of mental illness. Discrimination subscale refers to perceived negative reactions by 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 have been assessed on a sample of 183 patients. Results of confirmatory factor analyses (CFA) did not confirm the hypothesized structure. In 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 (χ2/άί=2.02, GFI=0.77, AGFI=0.73, RMSEA=0.07, CFI=0.77 et NNFI=0.75). Cronbach's α are excellent for discrimination (0.84) and disclosure (0.83) subscales but poor for potential positive aspects (0.46). External validity is satisfactory. Overall Stigma Scale total score is negatively correlated with score on Rosenberg's Self-Esteem Scale (r = -0.49), and each sub-scale is significantly correlated with a visual analogue scale that refers to the specific aspect of stigma (0.43 < |r| < 0.60). Intraclass correlation coefficients between 0.68 and 0.89 indicate good test- retest reliability. Results of CFA demonstrate that the items chosen for the short version of the Stigma Scale have the expected fit properties fa2/df=1.02, GFI=0.98, AGFI=0.98, RMSEA=0.01, CFI=1.0 et NNFI=1.0). Considering the small number (3 items) of items in each subscales of the short version of the Stigma Scale, a coefficients for the 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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Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

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OBJECTIVE: To determine the psychometric properties of an adapted version of the Falls Efficacy Scale (FES) in older rehabilitation patients. DESIGN: Cross-sectional survey. SETTING: Postacute rehabilitation facility in Switzerland. PARTICIPANTS: Seventy elderly persons aged 65 years and older receiving postacute, inpatient rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FES questions asked about subject's confidence (range, 0 [none]-10 [full]) in performing 12 activities of daily living (ADLs) without falling. Construct validity was assessed using correlation with measures of physical (basic ADLs [BADLs]), cognitive (Mini-Mental State Examination [MMSE]), affective (15-item Geriatric Depression Scale [GDS]), and mobility (Performance Oriented Mobility Assessment [POMA]) performance. Predictive validity was assessed using the length of rehabilitation stay as the outcome. To determine test-retest reliability, FES administration was repeated in a random subsample (n=20) within 72 hours. RESULTS: FES scores ranged from 10 to 120 (mean, 88.7+/-26.5). Internal consistency was optimal (Cronbach alpha=.90), and item-to-total correlations were all significant, ranging from .56 (toilet use) to .82 (reaching into closets). Test-retest reliability was high (intraclass correlation coefficient, .97; 95% confidence interval, .95-.99; P<.001). Subjects reporting a fall in the previous year had lower FES scores than nonfallers (85.0+/-25.2 vs 94.4+/-27.9, P=.054). The FES correlated with POMA (Spearman rho=.40, P<.001), MMSE (rho=.37, P=.001), BADL (rho=.43, P<.001), and GDS (rho=-.53, P<.001) scores. These relationships remained significant in multivariable analysis for BADLs and GDS, confirming FES construct validity. There was a significant inverse relationship between FES score and the length of rehabilitation stay, independent of sociodemographic, functional, cognitive, and fall status. CONCLUSIONS: This adapted FES is reliable and valid in older patients undergoing postacute rehabilitation. The independent association between poor falls efficacy and increased length of stay has not been previously described and needs further investigations.

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Reliable quantification of the macromolecule signals in short echo-time H-1 MRS spectra is particularly important at high magnetic fields for an accurate quantification of metabolite concentrations (the neurochemical profile) due to effectively increased spectral resolution of the macromolecule components. The purpose of the present study was to assess two approaches of quantification, which take the contribution of macromolecules into account in the quantification step. H-1 spectra were acquired on a 14.1 T/26 cm horizontal scanner on five rats using the ultra-short echo-time SPECIAL (spin echo full intensity acquired localization) spectroscopy sequence. Metabolite concentrations were estimated using LCModel, combined with a simulated basis set of metabolites using published spectral parameters and either the spectrum of macromolecules measured in vivo, using an inversion recovery technique, or baseline simulated by the built-in spline function. The fitted spline function resulted in a smooth approximation of the in vivo macromolecules, but in accordance with previous studies using Subtract-QUEST could not reproduce completely all features of the in vivo spectrum of macromolecules at 14.1 T. As a consequence, the measured macromolecular 'baseline' led to a more accurate and reliable quantification at higher field strengths.

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In this paper, a phenomenologically motivated magneto-mechanically coupled finite strain elastic framework for simulating the curing process of polymers in the presence of a magnetic load is proposed. This approach is in line with previous works by Hossain and co-workers on finite strain curing modelling framework for the purely mechanical polymer curing (Hossain et al., 2009b). The proposed thermodynamically consistent approach is independent of any particular free energy function that may be used for the fully-cured magneto-sensitive polymer modelling, i.e. any phenomenological or micromechanical-inspired free energy can be inserted into the main modelling framework. For the fabrication of magneto-sensitive polymers, micron-size ferromagnetic particles are mixed with the liquid matrix material in the uncured stage. The particles align in a preferred direction with the application of a magnetic field during the curing process. The polymer curing process is a complex (visco) elastic process that transforms a fluid to a solid with time. Such transformation process is modelled by an appropriate constitutive relation which takes into account the temporal evolution of the material parameters appearing in a particular energy function. For demonstration in this work, a frequently used energy function is chosen, i.e. the classical Mooney-Rivlin free energy enhanced by coupling terms. Several representative numerical examples are demonstrated that prove the capability of our approach to correctly capture common features in polymers undergoing curing processes in the presence of a magneto-mechanical coupled load.

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BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.

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A proposal to pilot nursing assessment of self harm in Accident and Emergency Departments (A&E) was developed by key stakeholders in nurse education and suicide prevention in the South East and submitted to the National Council for the Professional Development of Nursing and Midwifery in April 2002.The proposal included the introduction of a suicide intent scale. Following an initial training programme, a suicide intent scale was utilised by nursing staff in A&E and the Medical Assessment Unit (MAU),Wexford General Hospital and evaluated over a period of nine months. Four months into the study the National Suicide Research Foundation (NSRF) was invited to collaboratively prepare a successful submission to the Health Research Board (HRB) as part of ‘Building Partnerships for a Healthier Future Research Awards 2004’. The NSRF undertook independent scientific evaluation of the outcomes of the suicide awareness programme. The study is in line with priorities determined by Reach Out, the National Strategy for Action on Suicide Prevention 2005-2014 (HSE, 2005) and the HSE-South East Suicide Prevention Programme through raising nursing staff awareness of the public health issue of suicide/deliberate self harm and by improving the efficiency and quality of nursing services offered to persons who present to acute hospitals with deliberate self harm. The study findings indicate evidence to positively support nursing assessment of DSH using a suicide intent scale in terms of assessing behavioural characteristics of individual clients and their suicide risk. Enhanced confidence levels of nursing personnel in caring for suicidal clients was demonstrated by staff who participated in an education programme related to risk assessment and specifically the use of a suicide intent scale.This resource was contributed by The National Documentation Centre on Drug Use.