61 resultados para Applied psychometric


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The Constructive Thinking Inventory (CTI) measures cognitive coping strategies used in everyday problem solving. The main objective of this study was to assess the factorial structure, the internal consistency, the correspondence with the American normative values, and the discriminant validity of the French translation. A community sample of 777 students aged 12 to 26 years, recruited from schools, colleges and universities, answered the 108item selfreport CTI questionnaire during a class period. A sample of 60 male adolescent offenders aged 13 to 18 years, recruited from two institutions for juvenile offenders, answered the CTI during an individual interview. Results show that the French translation of the CTI follows an identical factorial structure as the Epstein's American version in both adolescents and young adults, and that its internal consistency is satisfactory. Differences in Constructive Thinking profiles according to gender and age and between Swiss and American samples, are discussed. Juvenile offenders differed from community youths on most of the scales, speaking for a good discriminant validity of the CTI. In conclusion, the French translation of the CTI appears to preserve the original version's psychometric properties. The present study provides normative values from a community sample of Swiss adolescents and young adults.

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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

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The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders.

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Melt-rock reaction in the upper mantle is recorded in a variety of ultramafic rocks and is an important process in modifying melt composition on its way from the source region towards the surface. This experimental study evaluates the compositional variability of tholeiitic basalts upon reaction with depleted peridotite at uppermost-mantle conditions. Infiltration-reaction processes are simulated by employing a three-layered set-up: primitive basaltic powder ('melt layer') is overlain by a 'peridotite layer' and a layer of vitreous carbon spheres ('melt trap'). Melt from the melt layer is forced to move through the peridotite layer into the melt trap. Experiments were conducted at 0.65 and 0.8 GPa in the temperature range 1,170-1,290 degrees C. In this P-T range, representing conditions encountered in the transition zone (thermal boundary layer) between the asthenosphere and the lithosphere underneath oceanic spreading centres, the melt is subjected to fractionation, and the peridotite is partially melting (T (s) similar to 1,260 degrees C). The effect of reaction between melt and peridotite on the melt composition was investigated across each experimental charge. Quenched melts in the peridotite layers display larger compositional variations than melt layer glasses. A difference between glasses in the melt and peridotite layer becomes more important at decreasing temperature through a combination of enrichment in incompatible elements in the melt layer and less efficient diffusive equilibration in the melt phase. At 1,290A degrees C, preferential dissolution of pyroxenes enriches the melt in silica and dilutes it in incompatible elements. Moreover, liquids become increasingly enriched in Cr(2)O(3) at higher temperatures due to the dissolution of spinel. Silica contents of liquids decrease at 1,260 degrees C, whereas incompatible elements start to concentrate in the melt due to increasing levels of crystallization. At the lowest temperatures investigated, increasing alkali contents cause silica to increase as a consequence of reactive fractionation. Pervasive percolation of tholeiitic basalt through an upper-mantle thermal boundary layer can thus impose a high-Si 'low-pressure' signature on MORB. This could explain opx + plag enrichment in shallow plagioclase peridotites and prolonged formation of olivine gabbros.

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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

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Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

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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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Plasmapheresis is an extracorporeal technique used to remove pathogenic macromolecules from the circulation, particularly autoantibodies. This is illustrated in 2 female patients. The first patient, aged 61 years, was treated successfully with non-selective plasmapheresis for acute humoral rejection shortly after receiving a renal allograft. In the second patient, aged 82 years, plasmapheresis for refractory myasthenia gravis had to be stopped because of bradycardia and hypotension during the procedure. She was treated successfully with immunoglobulins. Plasmapheresis is used to treat neurological, renal, haematological and systemic disorders. In nonselective plasmapheresis, the plasma is replaced with saline and albumin or donor plasma. In selective plasmapheresis a highly selective filter is used to remove a specific, pathogenic macromolecule. Adverse effects of the treatment include disturbances of the acid-base equilibrium or the coagulation, and allergic reactions. Most of these complications, however, can nowadays be avoided.

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Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

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The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

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Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.