Existential values transformation in all organ transplantation : a qualitative prospective study

The aim of this qualitative study was to analyze psychological concerns in wait-listed patients T1 and six months after transplantation T2. Semi-structured interviews were conducted and qualitative analysis performed. T1 Kidney patients maintained apparent normality, building emotional protection, and a fatalist attitude. Liver patients set physical limits, reevaluation of life values was reported. Lung patients developed physical and psychological self-protection. Modified life values, fatalism and spirituality were mentioned. Heart patients husbanded ressources and self-protection. Modified life values, fatalist attitude were reported. T2 Kidney patients described new life perspectives and increase of empathy. Liver patients underlined positive identity and life values modifications. Lack of respect of life values generated anger. Heart and lung patients set their existential priorities and underlined increase in spirituality, greater openness and more closeness to significant ones. Lack of respect of human values induced negative feelings. TX comes with physical benefits, but also with positive existential values transformations and a humanistic, altruistic attitude.

Geostatistical determination of heavy-metal distribution in a contaminated site - A case study

A two stage sampling strategy is necessary in order to optimize the study of distribution of pollution in soils and groundwater. First, detailed sampling from a limited area coupled with statistical analysis of the data are used to determine the microvariability of the parameter(s). The results from this detailed analysis are then used to calculate the optimal spacing between samples for the larger scale study. This two stage sampling strategy can result in significant financial savings during subsequent soil or groundwater remediation. This combined sampling and statistical analysis approach is illustrated with an example from a heavy metal contaminated site.

LEVERAGING SANDBOX IMMERSIVE 3D VIRTUAL WORLDS TO DEVELOP DO-IT- YOURSELF TEACHING GAMES: IMPLEMENTATION TO MARKETING CASE STUDY TEACHING IN SECOND LIFE

Games are powerful and engaging. On average, one billion people spend at least 1 hour a day playing computer and videogames. This is even more true with the younger generations. Our students have become the < digital natives >, the < gamers >, the < virtual generation >. Research shows that those who are most at risk for failure in the traditional classroom setting, also spend more time than their counterparts, using video games. They might strive, given a different learning environment. Educators have the responsibility to align their teaching style to these younger generation learning styles. However, many academics resist the use of computer-assisted learning that has been "created elsewhere". This can be extrapolated to game-based teaching: even if educational games were more widely authored, their adoption would still be limited to the educators who feel a match between the authored games and their own beliefs and practices. Consequently, game-based teaching would be much more widespread if teachers could develop their own games, or at least customize them. Yet, the development and customization of teaching games are complex and costly. This research uses a design science methodology, leveraging gamification techniques, active and cooperative learning theories, as well as immersive sandbox 3D virtual worlds, to develop a method which allows management instructors to transform any off-the-shelf case study into an engaging collaborative gamified experience. This method is applied to marketing case studies, and uses the sandbox virtual world of Second Life. -- Les jeux sont puissants et motivants, En moyenne, un milliard de personnes passent au moins 1 heure par jour jouer à des jeux vidéo sur ordinateur. Ceci se vérifie encore plus avec les jeunes générations, Nos étudiants sont nés à l'ère du numérique, certains les appellent des < gamers >, d'autres la < génération virtuelle >. Les études montrent que les élèves qui se trouvent en échec scolaire dans les salles de classes traditionnelles, passent aussi plus de temps que leurs homologues à jouer à des jeux vidéo. lls pourraient potentiellement briller, si on leur proposait un autre environnement d'apprentissage. Les enseignants ont la responsabilité d'adapter leur style d'enseignement aux styles d'apprentissage de ces jeunes générations. Toutefois, de nombreux professeurs résistent lorsqu'il s'agit d'utiliser des contenus d'apprentissage assisté par ordinateur, développés par d'autres. Ceci peut être extrapolé à l'enseignement par les jeux : même si un plus grand nombre de jeux éducatifs était créé, leur adoption se limiterait tout de même aux éducateurs qui perçoivent une bonne adéquation entre ces jeux et leurs propres convictions et pratiques. Par conséquent, I'enseignement par les jeux serait bien plus répandu si les enseignants pouvaient développer leurs propres jeux, ou au moins les customiser. Mais le développement de jeux pédagogiques est complexe et coûteux. Cette recherche utilise une méthodologie Design Science pour développer, en s'appuyant sur des techniques de ludification, sur les théories de pédagogie active et d'apprentissage coopératif, ainsi que sur les mondes virtuels immersifs < bac à sable > en 3D, une méthode qui permet aux enseignants et formateurs de management, de transformer n'importe quelle étude de cas, provenant par exemple d'une centrale de cas, en une expérience ludique, collaborative et motivante. Cette méthode est appliquée aux études de cas Marketing dans le monde virtuel de Second Life.

Fear and anxiety at the basis of adolescent externalizing and internalizing behaviors: a case study.

Juvenile delinquency is rarely associated with success in psychotherapeutic treatment. Up until now, few data have been recorded regarding possible overlaps or common features of conduct disorders with anxiety disorders. This case report of a delinquent adolescent's presenting an obsessive-compulsive disorder discusses possible underlying common features of externalizing and internalizing disorders, mainly in terms of fear and anxiety regulation. The successful psychotherapy is discussed with regard to efficient psychological assessment and treatment of delinquent adolescents, and it underlies the importance of detailed analysis of psychopathology in cases of juvenile delinquency.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Development of a two-step screening ESI-TOF-MS method for rapid determination of significant stress-induced metabolome modifications in plant leaf extracts: the wound response in Arabidopsis thaliana as a case study.

To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Can we disentangle predator-prey interactions from species distributions at a macro-scale? A case study with a raptor species.

There is a debate on whether an influence of biotic interactions on species distributions can be reflected at macro-scale levels. Whereas the influence of biotic interactions on spatial arrangements is beginning to be studied at local scales, similar studies at macro-scale levels are scarce. There is no example disentangling, from other similarities with related species, the influence of predator-prey interactions on species distributions at macro-scale levels. In this study we aimed to disentangle predator-prey interactions from species distribution data following an experimental approach including a factorial design. As a case of study we selected the short-toed eagle because of its known specialization on certain prey reptiles. We used presence-absence data at a 100 Km2 spatial resolution to extract the explanatory capacity of different environmental predictors (five abiotic and two biotic predictors) on the short-toed eagle species distribution in Peninsular Spain. Abiotic predictors were relevant climatic and topographic variables, and relevant biotic predictors were prey richness and forest density. In addition to the short-toed eagle, we also obtained the predictor's explanatory capacities for i) species of the same family Accipitridae (as a reference), ii) for other birds of different families (as controls) and iii) species with randomly selected presences (as null models). We run 650 models to test for similarities of the short-toed eagle, controls and null models with reference species, assessed by regressions of explanatory capacities. We found higher similarities between the short-toed eagle and other species of the family Accipitridae than for the other two groups. Once corrected by the family effect, our analyses revealed a signal of predator-prey interaction embedded in species distribution data. This result was corroborated with additional analyses testing for differences in the concordance between the distributions of different bird categories and the distributions of either prey or non-prey species of the short-toed eagle. Our analyses were useful to disentangle a signal of predator-prey interactions from species distribution data at a macro-scale. This study highlights the importance of disentangling specific features from the variation shared with a given taxonomic level.