Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Food allergy: Evaluation of the quality of life in Swiss children

Background: Food allergy in children, an increasingly prevalent disease, significantly affects the quality of life. Its impact can be analyzed by the recently validated French version of the Food Allergy Quality of Life Questionnaire (FAQLQ). Objectives: The aim of our study was to evaluate the quality of life in a small sample of Swiss children with IgE-mediated food allergy. Methods: Information were collected with the questionnaire among 0-12 years old children and their parents during a scheduled allergy visit, and analysed in term of emotional impact, food anxiety and social and food limitations. Patients were divided according to the questionnaire in three age groups: group 1 from 0 to 3 years, group 2 from 4 to 6 years and group 3 from 7 up to 12 years. Results: 30 food allergic patients were included, with a girl/boy ratio of 1:1.14. Median age was 6 years. 56% suffered from or had a history of eczema, 23% of rhino-conjunctivitis, 30% of asthma, and 13% reported a drug allergy. None had insect venom allergy. 57% were known to be allergic to one food, 20% to two foods, 20% to 3 foods and 3% had 3 or more food allergies. Tree nuts (51% of all allergies) as well as eggs (28 %) were the major allergies. Emotional impact had a total score of 1.54 but showed differences between age groups. In group 1 it was lower with 0.23, in group 2 the score was 2.03 and 1.77 in group 3. Food anxiety total score was 1.9; 0.76 in group 1, 2.31 in group 2 and 2.23 in group 3. Social and food limitations showed similar results with a total score of 1.73 and 1.23 in group 1, 2.05 in group 2 and 1.68 for group 3. Conclusion: Food allergy affects the quality of life of Swiss children. Our preliminary results on a small sample are comparable to previously published data. We show that the impact of food allergy on daily life increases when the child starts school and social activities.

Key elements for, and indicators of, a successful transition: an international Delphi study.

PURPOSE: The purpose of this study was to reach an international consensus to determine what key elements should be part of a transition program and what indicators could be used to assess its success. METHODS: For this purpose, a Delphi study including an international panel of 37 experts was carried out. The study consisted of three rounds, with response rates ranging from 86.5% to 95%. At each round, experts were asked to assess key elements (defined as the most important elements for the task) and indicators (defined as quantifiable characteristics). At each round, panelists were contacted via e-mail explaining them the tasks to be done and giving them the Web link where to complete the questionnaire. At Round 3, each key element and indicator was assessed as essential, very important, important, accessory, or unnecessary. A 70% agreement was used as cutoff. RESULTS: At Round 3, more than 70% of panelists agreed on six key elements being essential, with one of them (Assuring a good coordination between pediatric and adult professionals) reaching an almost complete consensus (97%). Additionally, 11 more obtained more than 70% agreement when combined with the Very important category. Among indicators, only one (Patient not lost to follow-up) was considered almost unanimously (91%) as essential by the panelists and seven others also reached consensus when the Very important category was included. CONCLUSIONS: Using these results as a framework to develop guidelines at local, national, and international levels would allow better assessing and comparing transition programs.

Diversity of the Quality Criteria in Qualitative Research in the Health Sciences: Lessons from a Lexicometric Analysis Composed of 133 Guidelines

A review of health sciences literature shows a substantial increase in qualitative publications. This work incorporates a certain number of research quality guidelines. We present the results of the Alceste® lexicometric analysis, which includes 133 quality grids for qualitative research covering five disciplinary fields of the health sciences: medicine and epidemiology, public health and health education, nursing, health sociology and anthropology, psychiatry and psychology. This analysis helped to cross-check the disciplinary fields with the various objectives assigned to the different criteria in the grids examined. The results obtained with Alceste® show the variability of the objectives sought by the authors of the guidelines. These discrepancies are not directly associated to disciplinary fields, and appear to be more closely linked to different qualitative research conceptualizations within the disciplines, and with essential qualitative research validation criteria. These conceptualizations must be clarified to help users better understand the objectives targeted by the grids, and promote more appreciation for qualitative research in the health sciences.

Les déterminants de la prolongation des séjours en SSRG et les indicateurs du devenir des patients après leur sortie : Étude rétrospective au CHRU de Strasbourg [Determinants of prolonged stays in geriatric rehabilitation department and indicators of patient outcome after discharge: A retrospective study in Strasbourg university hospital]

Objectif. Analyser les déterminants de la prolongation des séjours hospitaliers en service de soins de suite et réadaptation gériatrique (SSRG) et identifier les indicateurs du devenir des patients après leur sortie. Méthode. Étude rétrospective au CHRU de Strasbourg de l'ensemble des séjours de durée supérieure à 90 jours entre le 1 janvier 2012 et le 30 septembre 2013. L'ensemble des données sociodémographiques, descriptives des séjours et de l'état de santé des patients ont été analysées. Les patients ont été suivis 9 mois après leur sortie. Les réhospitalisations, l'admission en institution et le décès ont été informés par un contact téléphonique auprès du médecin traitant ou de la famille. Résultats. Quarante-six séjours ont été analysés. Les patients étaient à 68,0 % des femmes. La moyenne d'âge était de 82,9 ± 5,8 ans. Quatre-vingt-dix-huit pour cent d'entre eux vivaient à domicile avant l'admission en milieu hospitalier. Les raisons justifiant la prolongation étaient d'ordre médical (60,8 %), psychique (45,6 %), social (65,2 %) et liées à la difficulté de trouver une solution d'aval (58,7 %). À la fin de leur séjour, 9 patients ont pu regagner leur domicile et 37 ont été admis directement en institution. Durant la période de suivi, 17 patients ont été réhospitalisés au moins une fois et 3 jusqu'à trois fois. Au 9e mois, 9 patients étaient décédés dans un délai moyen de 75 jours après la sortie du SSRG. Les résultats des analyses unifactorielles et multivariées ont permis d'identifier des indicateurs d'évolution défavorable (décès et/ou réhospitalisation). Aucune des variables sociodémographiques ou de syndrome gériatrique n'a été identifiée. Par contre un « motif d'hospitalisation pour une maladie infectieuse », ou pour « un trouble de la marche ou une chute », une « prolongation du séjour en SSRG pour raison médicale » et un « séjour prolongé en court séjour » étaient les facteurs identifiés. Conclusion. Dans la tendance actuelle à améliorer la rentabilité de l'utilisation des ressources de santé, ces résultats rappellent qu'il est important de maintenir un juste équilibre entre utilisation raisonnée des ressources et les besoins spécifiques des patients âgés.