E-learning initiatives in forensic interpretation: report on experiences from current projects and outlook

This paper reports on the purpose, design, methodology and target audience of E-learning courses in forensic interpretation offered by the authors since 2010, including practical experiences made throughout the implementation period of this project. This initiative was motivated by the fact that reporting results of forensic examinations in a logically correct and scientifically rigorous way is a daily challenge for any forensic practitioner. Indeed, interpretation of raw data and communication of findings in both written and oral statements are topics where knowledge and applied skills are needed. Although most forensic scientists hold educational records in traditional sciences, only few actually followed full courses that focussed on interpretation issues. Such courses should include foundational principles and methodology - including elements of forensic statistics - for the evaluation of forensic data in a way that is tailored to meet the needs of the criminal justice system. In order to help bridge this gap, the authors' initiative seeks to offer educational opportunities that allow practitioners to acquire knowledge and competence in the current approaches to the evaluation and interpretation of forensic findings. These cover, among other aspects, probabilistic reasoning (including Bayesian networks and other methods of forensic statistics, tools and software), case pre-assessment, skills in the oral and written communication of uncertainty, and the development of independence and self-confidence to solve practical inference problems. E-learning was chosen as a general format because it helps to form a trans-institutional online-community of practitioners from varying forensic disciplines and workfield experience such as reporting officers, (chief) scientists, forensic coordinators, but also lawyers who all can interact directly from their personal workplaces without consideration of distances, travel expenses or time schedules. In the authors' experience, the proposed learning initiative supports participants in developing their expertise and skills in forensic interpretation, but also offers an opportunity for the associated institutions and the forensic community to reinforce the development of a harmonized view with regard to interpretation across forensic disciplines, laboratories and judicial systems.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Reversal of activity-mediated spine dynamics and learning impairment in a mouse model of Fragile X syndrome.

Fragile X syndrome (FXS) is characterized by intellectual disability and autistic traits, and results from the silencing of the FMR1 gene coding for a protein implicated in the regulation of protein synthesis at synapses. The lack of functional Fragile X mental retardation protein has been proposed to result in an excessive signaling of synaptic metabotropic glutamate receptors, leading to alterations of synapse maturation and plasticity. It remains, however, unclear how mechanisms of activity-dependent spine dynamics are affected in Fmr knockout (Fmr1-KO) mice and whether they can be reversed. Here we used a repetitive imaging approach in hippocampal slice cultures to investigate properties of structural plasticity and their modulation by signaling pathways. We found that basal spine turnover was significantly reduced in Fmr1-KO mice, but markedly enhanced by activity. Additionally, activity-mediated spine stabilization was lost in Fmr1-KO mice. Application of the metabotropic glutamate receptor antagonist α-Methyl-4-carboxyphenylglycine (MCPG) enhanced basal turnover, improved spine stability, but failed to reinstate activity-mediated spine stabilization. In contrast, enhancing phosphoinositide-3 kinase (PI3K) signaling, a pathway implicated in various aspects of synaptic plasticity, reversed both basal turnover and activity-mediated spine stabilization. It also restored defective long-term potentiation mechanisms in slices and improved reversal learning in Fmr1-KO mice. These results suggest that modulation of PI3K signaling could contribute to improve the cognitive deficits associated with FXS.

Do riverine barriers, history or introgression shape the genetic structuring of a common shrew (Sorex araneus) population?

The common shrew (Sorex araneus) is subdivided into numerous chromosome races. The Valais and Cordon chromosome races meet and hybridize at a mountain river in Les Houches (French Alps). Significant genetic structuring was recently reported among populations found on the Valais side of this hybrid zone. In this paper, a phylogenetic analysis and partial Mantel tests are used to investigate the patterns and causes of this structuring. A total of 185 shrews were trapped at 12 localities. All individuals were typed for nine microsatellite loci. Although several mountain rivers are found in the study area, riverine barriers do not have a significant influence on gene flow. Partial Mantel tests show that our result is caused by the influence of the hybrid zone with the Cordon race. The geographical patterns of this structuring are discussed in the context of the contact zone, which appears to extend up to a group of two rivers. The glacier they originate from is known to have cut the Arve valley as recently as 1818. The recent history of this glacier, its moraine and possibly rivers, may therefore be linked to the history of this hybrid zone.

Qualitative analysis of barriers and facilitators encountered by HIV patients in an ART adherence programme.

Background Medication adherence is a complex, dynamic and changing behaviour that is affected by a variety of factors, including the patient's beliefs and life circumstances. Studies have highlighted barriers to medication adherence (e.g., unmanaged side effects or a lack of social support), as well as facilitators of medication adherence (e.g., technical simplicity of treatment and psychological acceptance of the disease). Since August 2004, in Lausanne (Switzerland), physicians have referred patients who are either experiencing or are at risk of experiencing problems with their HIV antiretroviral treatment (ART) to a routine interdisciplinary ART adherence programme. This programme consists of multifactorial intervention including electronic drug monitoring (MEMS(TM)). Objective This study's objective was to identify the barriers and facilitators encountered by HIV patients with suboptimal medication adherence (≤90 % adherence over the study period). Setting The community pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne (Switzerland). Method The study consisted of a retrospective, qualitative, thematic content analysis of pharmacists' notes that were taken during semi-structured interviews with patients and conducted as part of the ART adherence programme between August 2004 and May 2008. Main outcome measure Barriers and facilitators encountered by HIV patients. Results Barriers to and facilitators of adherence were identified for the 17 included patients. These factors fell into three main categories: (1) cognitive, emotional and motivational; (2) environmental, organisational and social; and (3) treatment and disease. Conclusion The pharmacists' notes revealed that diverse barriers and facilitators were discussed during medication adherence interviews. Indeed, the results showed that the 17 non-adherent patients encountered barriers and benefited from facilitators. Therefore, pharmacists should inquire about all factors, regardless of whether they have a negative or a positive impact on medication adherence, and should consider all dimensions of patient adherence. The simultaneous strengthening of facilitators and better management of barriers may allow healthcare providers to tailor care to a patient's specific needs and support each individual patient in improving his medication-related behaviour.

Penser la médecine communautaire s'apprend avec les pairs. [The spirit of community medicine: students learning from students].

At the University of Lausanne third-year medical students are given the task of spending a month investigating a question of community medicine. In 2009, four students evaluated the legitimacy of health insurers intervening in the management of depression. They found that health insurers put pressure on public authorities during the development of legislation governing the health system and reimbursement for treatment. This fact emerged during the scientific investigation led jointly by the team in the course of the "module of immersion in community medicine." This paper presents each step of their study. The example chosen illustrates the learning objectives covered by the module.

Stages of change, barriers, benefits, and preferences for exercise in RA patients: a cross-sectional study.

OBJECTIVES: To determine the distribution of exercise stages of change in a rheumatoid arthritis (RA) cohort, and to examine patients' perceptions of exercise benefits, barriers, and their preferences for exercise. METHODS: One hundred and twenty RA patients who attended the Rheumatology Unit of a University Hospital were asked to participate in the study. Those who agreed were administered a questionnaire to determine their exercise stage of change, their perceived benefits and barriers to exercise, and their preferences for various features of exercise. RESULTS: Eighty-nine (74%) patients were finally included in the analyses. Their mean age was 58.4 years, mean RA duration 10.1 years, and mean disease activity score 2.8. The distribution of exercise stages of change was as follows: precontemplation (n = 30, 34%), contemplation (n = 11, 13%), preparation (n = 5, 6%), action (n = 2, 2%), and maintenance (n = 39, 45%). Compared to patients in the maintenance stage of change, precontemplators exhibited different demographic and functional characteristics and reported less exercise benefits and more barriers to exercise. Most participants preferred exercising alone (40%), at home (29%), at a moderate intensity (64%), with advice provided by a rheumatologist (34%) or a specialist in exercise and RA (34%). Walking was by far the preferred type of exercise, in both the summer (86%) and the winter (51%). CONCLUSIONS: Our cohort of patients with RA was essentially distributed across the precontemplation and maintenance exercise stages of change. These subgroups of patients exhibit psychological and functional differences that make their needs different in terms of exercise counselling.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Se former à l'entretien motivationnel pour aider ses patients à changer: Les étudiants en médecine le confirment [Learning motivational interviewing to help patients change their health-related behaviors: medical students confirm it].

At the Lausanne University, 5th year medical students were trained in Motivational interviewing (MI). Eight hours of training improved their competence in the use of this approach. This experience supports the implementation of MI training in medical schools. Motivational interviewing allows the health professional to actively involve the patient in this behavior change process (drinking, smoking, diet, exercise, medication adherence, etc.), by encouraging reflection and reinforcing personal motivation and resources.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.