Médecine de l'adolescence. La Guglera: une réponse nouvelle et originale aux adolescents gravement obèses et sans travail [Adolescent medicine in Guglera: a novel approach for unemployed, severely obese adolescents]

The Center "la Guglera", located in the canton of Fribourg (Switzerland) provides a novel approach to the care of severely obese adolescents who are currently unemployed. These young people, whose BMI is usually higher than 35 to 40 kg/m2 spend a 6 to 12 months long stay in an in-patient institution which also takes care of other unemployed non obese adolescents on an outpatient basis. Besides a nutritional education which is part of the everyday life of the institution, the program includes a generous amount of hours of physical activities and sports. The adolescents also participate in a rehabilitation training program which fosters the future integration in a professional milieu, such as an apprenticeship. The short term results of la Guglera seem very promising. The program is financially co-supported by the Swiss and cantonal administrations, the insurance companies and the parents.

Identification concept and the use of probabilities in forensic odontology--an approach by philosophical discussion.

This paper questions the practitioners' deterministic approach(es) in forensic identification and notes the limits of their conclusions in order to encourage a discussion to question current practices. With this end in view, a hypothetical discussion between an expert in dentistry and an enthusiastic member of a jury, eager to understand the scientific principles of evidence interpretation, is presented. This discussion will lead us to regard any argument aiming at identification as probabilistic.

Managing diabetes in Switzerland : a systemic approach

Executive summaryThe increasing prevalence of chronic diseases is one of the major causes of rising health expenditure, as stated by the WHO. Not only chronic diseases are very costly, but they are by far the leading cause of mortality in the world, representing 60% of all deaths. Diabetes in particular is becoming a major burden of disease. In Switzerland around 5% of the population suffer of type 2 diabetes and 5 to 10% of the annual health care budget is attributable to diabetes. If the predictions of WHO do realise, the prevalence of diabetes will double until 2030 and so is expected the attributable health expenditure.The objective of this thesis is to provide policy recommendations as to slow down the disease progression and its costly complication. We study the factors that influence diabetes dynamics and the interventions that improve health outcomes while decreasing costs according to different time horizon and use systems thinking and system dynamic.Our results show that managing diabetes requires using integrated care interventions that are effective on three fronts: (1) delaying the onset of complications, (2) slowing down the disease progression and (3) accelerating the time to diagnosis of diabetes and its complications. We recommend firstly the implementation of those interventions targeted at changing patients' behaviour which are also less expensive, but require a change in the delivery of care and medical practices. Then policies targeted at an earlier diagnosis of diabetes, its prevention and the diagnosis of complications are to be considered. This sequence of interventions allows saving money, as total costs decrease, even including the costs of interventions and result in longer life expectancy of diabetics in the long term.In diabetes management there is therefore a trade-off between medical costs and patients' benefits on the one hand and between the objectives of obtaining results in the short or long term on the other hand. Decision makers need to deliver acceptable outcomes in the short term. Considering this criterion, the preferred policy may be to focus only on diagnosed diabetics, thus attempting to slow down the progression of their disease, compared to an integrated care approach addressing all the aspects of the disease. Such a policy also yields desirable results in terms of costs and patients' benefits.

Approche multidisciptinaire des coûts humains des lombalgies [Human cost of low back pain: a multi-disciplinary approach]

The valuation of human costs is a necessity, but this task poses many problems of method. A team made of a philosopher, a psychologist and a physician has been working with economist researchers in order to look into the meaning that the preferences announced at the time of the inquiries on human costs by QALY methods could assume. These methods are often used to obtain a valuation of the impact of a health attack on people's quality of life. The methods--in the frame of the argument assumed by the economic theory on well-being--hypothesize that people's choices depend mainly on cognitive work. The qualitative interviews show that the psychological construction process for the announced preferences largely overlap this frame. In this paper the authors hastily tackle the factors which have an effect on the preferences. They conclude that the QALY methods don't seem to be able to assess the quality of life nori to valuate the damage that the quality of life could include.

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

A mixed approach for proving non-inferiority in clinical trials with binary endpoints

When a new treatment is compared to an established one in a randomized clinical trial, it is standard practice to statistically test for non-inferiority rather than for superiority. When the endpoint is binary, one usually compares two treatments using either an odds-ratio or a difference of proportions. In this paper, we propose a mixed approach which uses both concepts. One first defines the non-inferiority margin using an odds-ratio and one ultimately proves non-inferiority statistically using a difference of proportions. The mixed approach is shown to be more powerful than the conventional odds-ratio approach when the efficacy of the established treatment is known (with good precision) and high (e.g. with more than 56% of success). The gain of power achieved may lead in turn to a substantial reduction in the sample size needed to prove non-inferiority. The mixed approach can be generalized to ordinal endpoints.

Use of an in-house approach to study the three-dimensional structures of various outer membrane proteins: structure of the alcaligin outer membrane transporter FauA from Bordetella pertussis.

Bordetella pertussis is the bacterial agent of whooping cough in humans. Under iron-limiting conditions, it produces the siderophore alcaligin. Released to the extracellular environment, alcaligin chelates iron, which is then taken up as a ferric alcaligin complex via the FauA outer membrane transporter. FauA belongs to a family of TonB-dependent outer membrane transporters that function using energy derived from the proton motive force. Using an in-house protocol for membrane-protein expression, purification and crystallization, FauA was crystallized in its apo form together with three other TonB-dependent transporters from different organisms. Here, the protocol used to study FauA is described and its three-dimensional structure determined at 2.3 A resolution is discussed.

A new efficient approach to the direct restricted active space self-consistent field method

An implicitly parallel method for integral-block driven restricted active space self-consistent field (RASSCF) algorithms is presented. The approach is based on a model space representation of the RAS active orbitals with an efficient expansion of the model subspaces. The applicability of the method is demonstrated with a RASSCF investigation of the first two excited states of indole

A variational approach for calculating Franck-Condon factors including mode-mode anharmonic coupling

We have implemented our new procedure for computing Franck-Condon factors utilizing vibrational configuration interaction based on a vibrational self-consistent field reference. Both Duschinsky rotations and anharmonic three-mode coupling are taken into account. Simulations of the first ionization band of Cl O2 and C4 H4 O (furan) using up to quadruple excitations in treating anharmonicity are reported and analyzed. A developer version of the MIDASCPP code was employed to obtain the required anharmonic vibrational integrals and transition frequencies

A chemical Hamiltonian approach study of the basis set superposition error changes on electron densities and one- and two-center energy components

A comparision of the local effects of the basis set superposition error (BSSE) on the electron densities and energy components of three representative H-bonded complexes was carried out. The electron densities were obtained with Hartee-Fock and density functional theory versions of the chemical Hamiltonian approach (CHA) methodology. It was shown that the effects of the BSSE were common for all complexes studied. The electron density difference maps and the chemical energy component analysis (CECA) analysis confirmed that the local effects of the BSSE were different when diffuse functions were present in the calculations

A stratified approach for modeling the distribution of a threatened ant species in the Swiss National Park

We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.