The ability model of emotional intelligence: Searching for valid measures

Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

The four- vs. alternative six-factor structure of the French WISC-IV: Comparison using confirmatory factor analyses

Exploratory and confirmatory factor analyses reported in the French technical manual of the WISC-IV provides evidence supporting a structure with four indices: Verbal Comprehension (VCI), Perceptual Reasoning (PRI), Working Memory (WMI), and Processing Speed (PSI). Although the WISC-IV is more attuned to contemporary theory, it is still not in total accordance with the dominant theory: the Cattell-Horn-Carroll (CHC) theory of cognitive ability. This study was designed to determine whether the French WISC-IV is better described with the four-factor solution or whether an alternative model based on the CHC theory is more appropriate. The intercorrelations matrix reported in the French technical manual was submitted to confirmatory factor analysis. A comparison of competing models suggests that a model based on the CHC theory fits the data better than the current WISC-IV structure. It appears that the French WISC-IV in fact measures six factors: crystallized intelligence (Gc), fluid intelligence (Gf), short-term memory (Gsm), processing speed (Gs), quantitative knowledge (Gq), and visual processing (Gv). We recommend that clinicians interpret the subtests of the French WISC-IV in relation to this CHC model in addition to the four indices.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

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 a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic 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, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-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 downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled 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.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

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.

Structure and kinematics of the Jungfrau syncline, Faflertal (Valais, Alps), and its regional significance

The formation and structural evolution of the jungrau syncline is described, based on excellent outcrops occurring in the lotschental, in the central alps of switzerland. the quality of the outcrops allows us to demonstrate that the external massifs of the swiss alps have developed due to internal folding. The jungfrau suncline, which separates the autochtonous gastern dome from the aar massif basement gneiss folds, is composed of slivers of basement rocks with their mesozoic sedimentary cover. in the inner faflertal, a side valley of the lotschental, the 200 m thick syncline cp, roses fpir imots, the gastern massif with a reduced mesozoic sedimentary cover in a normal stratigraphic succession, two units of overturned basement rocks with their mesozoic sedimentary cover, and the overturned lower limn of the tschingelhorn gneiss fold of the aar massif with lenses of its sedimentary cover. stratigraphy shows that the lower units, related to the gastern massis, are condensed and that the upper units, deposited farther away from a gastern paleo-high, form a more complete sequence, linked to the doldenhorn meso-cneozoic basin fill. the integration of these local observations with published regional data leads to the following model. on the northern margin of the doldenhorn hbasin, at the northern fringe of the alpine tethuys, the pre-triassic crystalline basement and its mesozoic sedimentary cover were folded by ductile deformation at temperatures above 300 degrees C and in the presence of high fluid pressures, as the helveti c and penninic nappes were overthrusted towards the northwest during the main alpine deformation phase, the visosity contrast between the basement gneisses and the sediments caused the formation of large basement anticlines and tight sedimentary sunclines (mullion-type structures). The edges of basement blocks bounded buy pre-cursor se-dipping normal faults at the northwestern border of the doldenhorn basin were deformed bu simple shear, creating overturned slices of crystalline rocks with their sedimentary cover in what now forms the hungfrau syncline. the localisation of ductile deformation in the vicinity of pre-existing se-dipping faults is thought to have been helped by the circulation of fluids along the faults; these fluids would have been released from the mesozoic sediments by metamorphic dehydration reactions accompanied by creep and dynamic recrystallisation of quartz at temperatures above 300 degrees C. Quantification of the deformation suggests an strain ellipsoid with a ratio (1 + e(1)/+ e(3)) of approximately 1000. The jungfrau suncline was deformed bu more brittle nw-directed shear creating well-developed shear band cleavages at a late stage, after cooling by uplift and erosion. It is suggested that the external massifs of the apls are basement gneiss folds created at temperatures of 300 degrees C by detachment through ductile deformation of the upper crust of the european plate as it was underthrusted below the adriatic plate.

The influence of environmental spatial structure on the life history traits and diversity of species in a metacommunity

Several models have been proposed to understand how so many species can coexist in ecosystems. Despite evidence showing that natural habitats are often patchy and fragmented, these models rarely take into account environmental spatial structure. In this study we investigated the influence of spatial structure in habitat and disturbance regime upon species' traits and species' coexistence in a metacommunity. We used a population-based model to simulate competing species in spatially explicit landscapes. The species traits we focused on were dispersal ability, competitiveness, reproductive investment and survival rate. Communities were characterized by their species richness and by the four life-history traits averaged over all the surviving species. Our results show that spatial structure and disturbance have a strong influence on the equilibrium life-history traits within a metacommunity. In the absence of disturbance, spatially structured landscapes favour species investing more in reproduction, but less in dispersal and survival. However, this influence is strongly dependent on the disturbance rate, pointing to an important interaction between spatial structure and disturbance. This interaction also plays a role in species coexistence. While spatial structure tends to reduce diversity in the absence of disturbance, the tendency is reversed when disturbance occurs. In conclusion, the spatial structure of communities is an important determinant of their diversity and characteristic traits. These traits are likely to influence important ecological properties such as resistance to invasion or response to climate change, which in turn will determine the fate of ecosystems facing the current global ecological crisis.

Model-based Segmentation and Image Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

For radiotherapy treatment planning of retinoblastoma inchildhood, Computed Tomography (CT) represents thestandard method for tumor volume delineation, despitesome inherent limitations. CT scan is very useful inproviding information on physical density for dosecalculation and morphological volumetric information butpresents a low sensitivity in assessing the tumorviability. On the other hand, 3D ultrasound (US) allows ahigh accurate definition of the tumor volume thanks toits high spatial resolution but it is not currentlyintegrated in the treatment planning but used only fordiagnosis and follow-up. Our ultimate goal is anautomatic segmentation of gross tumor volume (GTV) in the3D US, the segmentation of the organs at risk (OAR) inthe CT and the registration of both. In this paper, wepresent some preliminary results in this direction. Wepresent 3D active contour-based segmentation of the eyeball and the lens in CT images; the presented approachincorporates the prior knowledge of the anatomy by usinga 3D geometrical eye model. The automated segmentationresults are validated by comparing with manualsegmentations. Then, for the fusion of 3D CT and USimages, we present two approaches: (i) landmark-basedtransformation, and (ii) object-based transformation thatmakes use of eye ball contour information on CT and USimages.

Factor structure of early smoking experiences and associations with smoking behavior: valence or sensitivity model?

The Early Smoking Experience (ESE) questionnaire is the most widely used questionnaire to assess initial subjective experiences of cigarette smoking. However, its factor structure is not clearly defined and can be perceived from two main standpoints: valence, or positive and negative experiences, and sensitivity to nicotine. This article explores the ESE's factor structure and determines which standpoint was more relevant. It compares two groups of young Swiss men (German- and French-speaking). We examined baseline data on 3,368 tobacco users from a representative sample in the ongoing Cohort Study on Substance Use Risk Factors (C-SURF). ESE, continued tobacco use, weekly smoking and nicotine dependence were assessed. Exploratory structural equation modeling (ESEM) and structural equation modeling (SEM) were performed. ESEM clearly distinguished positive experiences from negative experiences, but negative experiences were divided in experiences related to dizziness and experiences related to irritations. SEM underlined the reinforcing effects of positive experiences, but also of experiences related to dizziness on nicotine dependence and weekly smoking. The best ESE structure for predictive accuracy of experiences on smoking behavior was a compromise between the valence and sensitivity standpoints, which showed clinical relevance.

Model development for capercaillie (Tetrao urogallus) habitat in the Jura Mountains (Western Switzerland)

Capercaillie, Tetrao urogallus, is a threatened species in central Europe, and Swiss populations declined 40 to 50 % between 1970 and 1985. Capercaillie are sensitive to forest structure, and loss of habitat is a major cause of their decline. Knowledge of habitat characteristics is therefore essential for capercaillie conservation. Here, we present models predicting capercaillie probability of occurrence, based on relevant structural habitat variables. Models were built using multiple logistic regression analyses on capercaillie presence/absence data. Vegetation survey was carried out in July 1999 in a 170-km2 forested area (Jura mountains, canton de Vaud, western Switzerland) inhabited by capercaillie and presence/absence of the species was assessed according to dropping presence/absence. The survey was based on 10-m-radius sample plots each in a 1-km2 forest patch (n = 76 with capercaillie droppings, n = 80 without). A first model included seven out of 27 measured habitat variables and a second model only four. The latter model best represents practical needs. It includes three variables which had a negative impact on capercaillie presence: tree and shrub covers and spruce, Picea excelsa, shrub cover, and one which had a positive effect: bilberry, Vaccinium myrtillus, cover, highlighting that capaercaillie selected open forest with high bilberry abundance. The model can be used to map potential capercaillie habitat distribution and to manage the habitat in favour of capercaillie (protection and adapted forestry practices) in the Swiss Jura mountains.

Evaluating fear of falling among community-dwelling older people: A qualitative pattern model based on the experience of falls

This research was conducted in the context of the project IRIS 8A Health and Society (2002-2008) and financially supported by the University of Lausanne. It was aomed at developping a model based on the elder people's experience and allowed us to develop a "Portrait evaluation" of fear of falling using their examples and words. It is a very simple evaluation, which can be used by professionals, but by the elder people themselves. The "Portrait evaluation" and the user's guide are on free access, but we would very much approciate to know whether other people or scientists have used it and collect their comments. (contact: Chantal.Piot-Ziegler@unil.ch)The purpose of this study is to create a model grounded in the elderly people's experience allowing the development of an original instrument to evaluate FOF.In a previous study, 58 semi-structured interviews were conducted with community-dwelling elderly people. The qualitative thematic analysis showed that fear of falling was defined through the functional, social and psychological long-term consequences of falls (Piot-Ziegler et al., 2007).In order to reveal patterns in the expression of fear of falling, an original qualitative thematic pattern analysis (QUAlitative Pattern Analysis - QUAPA) is developed and applied on these interviews.The results of this analysis show an internal coherence across the three dimensions (functional, social and psychological). Four different patterns are found, corresponding to four degrees of fear of falling. They are formalized in a fear of falling intensity model.This model leads to a portrait-evaluation for fallers and non-fallers. The evaluation must be confronted to large samples of elderly people, living in different environments. It presents an original alternative to the concept of self-efficacy to evaluate fear of falling in older people.The model of FOF presented in this article is grounded on elderly people's experience. It gives an experiential description of the three dimensions constitutive of FOF and of their evolution as fear increases, and defines an evaluation tool using situations and wordings based on the elderly people's discourse.

Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis.

BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.