La mise en confiance des élèves à travers l’évaluation

We did an internship at Victor Hugo high school, located in the third borough of Marseille. At this occasion, we noticed that the students lacked self-confidence, specially regarding evaluations, this is why we have chosen to concentrate our research on this fact. The question we were interested in was how different kinds of feedback can’t promote self-confidence and learning. To answer that we imagined a protocol based on the comparison of the effects of two types of positive feedback, each one proposed in one of the group. In the first group the feedback is a personalized comment, assumed to promote self confidence in students, his effect can identify through classroom participation. In the second group, the feedback is a success criteria grid, assumed to promote learning, we can identify his effects through the evolution of grades. The results we’ve got show that students of the first group have tendency to increase classroom participation and the grades of the second group have increase during the three weeks. We have noticed in both groups that increase of grades and classroom participation were correlated. The work we did in this study seems to show that a positive feedback, in any form, promote both learning and self-confidence.Nous avons effectué un stage au lycée Victor Hugo situé dans le 3e arrondissement de Marseille. À cette occasion, nous avons constaté que nos élèves manquaient de confiance en eux, en particulier face aux évaluations, c’est pourquoi nous avons choisis d’axer notre mémoire sur ce point. La question à laquelle nous nous sommes intéressées est de savoir comment les différents types de Feedback positifs favorisent la confiance qu’ont les élèves en eux ainsi que leurs apprentissages. Pour y répondre, nous avons mis en place un dispositif basé sur la comparaison des effets de deux types de Feedback positifs réalisés dans chaque demi-groupe d’une classe de seconde. Dans le premier groupe, le Feedback est sous forme de commentaires personnalisés supposés favoriser la confiance en soi, effet que l’on observera via la fréquence de participation en classe. Dans le second groupe, le Feedback est sous forme de grilles d’évaluation supposées favoriser les apprentissages, effet que l’on évaluera grâce à l’évolution des moyennes. Les résultats obtenus montrent que les élèves du premier groupe ont tendance à plus participer en classe et que les moyennes individuelles des élèves du second groupe ont globalement augmenté au cours des séances. Nous avons constaté dans les deux groupes que l’augmentation des moyennes individuelles était corrélée à une augmentation de la participation et réciproquement. Le travail réalisé dans ce mémoire semble montrer qu’un Feedback positif, quel que soit sa forme, favorise à la fois les apprentissages et la confiance des élèves

Regional urban groundwater body risk assessment of contaminants using remotely sensed multi-resolution land-cover data

Contaminated sites are often the result of past relatively anarchic economical and industrial development. The last decades stakeholders are more aware of the risks posed by these sites. Within the Frac-Weco project an integrated framework for the assessment, at regional scale, of the risks posed by these contaminated sites on water resources and ecosystems has been developed. The methodology is based on the calculation of contaminant fluxes reaching the receptors providing a way of estimating the level of exposure/degradation of these receptors at the groundwater body scale. The most important contamination problems at regional scale are located around old urban and industrialized areas. The land-cover distribution in these zones is of prime importance because it determines the spatial variation of groundwater recharge, which is the main vector of contaminant leaching from soil surface to groundwater. To obtain detailed information about land cover for groundwater recharge modeling, a stratified satellite image classification approach was adopted combining land-cover mapping at pixel level for the studied area as a whole with sub-pixel estimation of imperviousness within built-up zones. The obtained land-cover data is used as an input in the WetSpass model to simulate groundwater recharge at high resolution in spatially complex urban areas. In the next step the simulated groundwater recharge is used as an input in a regional scale groundwater flow and transport model simulating contaminant dispersion through the aquifer. Modeling results are further used to calculate a quality index for the whole groundwater body based on threshold values defined specifically for each contaminant. The approach proposed has been applied on the RWM073 groundwater body corresponding to the alluvial deposits of the Meuse River, Liège (Belgium). The high-resolution groundwater recharge estimations obtained by integrating remote sensing in the modeling procedure allow a better identification of the potential sources of contaminants and enable a proper quantification of total fluxes of contaminants from brownfields into the groundwater. The developed framework for regional risk assessment results in a global quality indicator for the groundwater body which can be used as input for decision-making.Frac-Weco projec

Improving surface-subsurface water budgeting for brownfield study sites using high resolution satellite imagery

Countries around the world have problems with contaminated brownfield sites as resulting from a relatively anarchic economical and industrial development during the 19th and 20th centuries. Since a few decades policy makers and stakeholders have become more aware of the risk posed by these sites because some of these sites present direct public hazards. Water is often the main vector of the mobility of contaminants. In order to propose remediation measures for the contaminated sites, it is required to describe and to quantify as accurately as possible the surface and subsurface water fluxes in the polluted site. In this research a modelling approach with integrated remote sensing analysis has been developed for accurately calculating water and contaminant fluxes on the polluted sites. Groundwater pollution in urban environments is linked to patterns of land use, so to identify the sources of contamination with great accuracy in urban environments it is essential to characterize the land cover in a detailed way. The use of high resolution spatial information is required because of the complexity of the urban land use. An object-oriented classification approach applied on high resolution satellite data has been adopted. Cluster separability analysis and visual interpretation of the image objects belonging to each cluster resulted in the selection of 8 land-cover categories (water, bare soil, meadow, mixed forest, grey urban surfaces, red roofs, bright roofs and shadow).To assign the image objects to one of the 8 selected classes a multiple layer perceptron (MLP) approach was adopted, using the NeuralWorks Predict software. After a post-classification shadow removal and a rule-based classification enhancement a kappa-value of 0.86 was obtained. Once the land cover was characterized, the groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow was simulated with GMS 6.0 in order to identify and budget the water fluxes on the brownfield. The obtained land use map shows to have a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to a receiving river where independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modelling procedure. The developed methodology is applied to a case site in Vilvoorde, Brussels (Belgium).status: publishe

Improving surface–subsurface water budgeting using high resolution satellite imagery applied on a brownfield

The estimation of surface–subsurface water interactions is complex and highly variable in space and time. It is even more complex when it has to be estimated in urban areas, because of the complex patterns of the landcover in these areas. In this research a modeling approach with integrated remote sensing analysis has been developed for estimating water fluxes in urban environments. The methodology was developed with the aim to simulate fluxes of contaminants from polluted sites. Groundwater pollution in urban environments is linked to patterns of land use and hence it is essential to characterize the land cover in a detail. An objectoriented classification approach applied on high-resolution satellite data has been adopted. To assign the image objects to one of the land-cover classes a multiple layer perceptron approach was adopted (Kappa of 0.86). Groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow using MODFLOW in order to identify and budget water fluxes. The developed methodology is applied to a brownfield case site in Vilvoorde, Brussels (Belgium). The obtained land use map has a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to the receiving River Zenne were independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modeling procedure.status: publishe

Flux-based Risk Assessement of the impact of Contaminants on Water resources and ECOsystems

Final reportSSD-Science for a Sustanaible Development, Atmosphere and Terestrial and Marine Ecosystem

Chest computed tomography signs associated with pejorative evolution in COVID-19 patients

Purpose: The aim of this study was to evaluate how chest computed tomography (CT) can predict pejorative evolution in COVID-19 patients. Material and methods: Data on 349 consecutive patients who underwent a chest CT either for severe suspected COVID-19 pneumonia or clinical aggravation and with COVID-19 were retrospectively analysed. In total, 109 had laboratory-confirmed COVID-19 infection by a positive reverse-transcription polymerase chain reaction (RT-PCR) and were included. The main outcomes for pejorative evolution were death and the need for invasive endotracheal ventilation (IEV). All the CT images were retrospectively reviewed, to analyse the CT signs and semiologic patterns of pulmonary involvement. Results: Among the 109 COVID-19 patients, 73 (67%) had severe symptoms of COVID-19, 28 (25.7%) needed an IEV, and 11 (10.1%) died. The following signs were significantly associated with both mortality and need for IEV: traction bronchiectasis and total affected lung volume ≥ 50% (p < 10-3). Other CT signs were only associated with the need of IEV: vascular dilatation, air bubble sign, peribronchovascular thickening, interlobular thickening, and number of involved lobes ≥ 4 (p < 10-3). Conclusions: On a chest CT performed during the first week of the symptoms, the presence of traction bronchiectasis and high values of affected lung volume are associated with the need for IEV, and with mortality, in COVID-19 patients

Methodology for the integration of process studies and development of a decision support tool (FRAC-WECO Project Deliverable D1.2)

This deliverable allows one to clarify the objectives of the different partners involved in the FRAC-WECO project and how they are going to interact, to exchange data, research results and knowledge in order to meet the ambitious objectives of the project. Particularly, the complex interactions between researches dealing with physical processes and with socio-economic aspects have been described in details. The modelling applications will constitute the key interacting tools as they are going to integrate all the information on water and contaminant mass fluxes and on biogeochemical processes affecting the fate of contaminant in the field and they are also going to be used to produce all data required for risk assessment and for the socio-economic analysis which are two of the most important expected outcomes of the project. The deliverable also clarifies the use of flux-based concepts through the definition of risk assessment indicators in the form of contaminant mass fluxes and discharge at the various considered receptors. Finally, this document has also allowed one to clarify the scope and the limits of the researches foreseen in the FRAC-WECO project that will focus on the risk of contaminant leaching to groundwater, of contaminant dispersion through groundwater and on the impact of contaminant on groundwater and surface water as affected by groundwater discharge and on the impact on aquatic ecosystems.Flux-based Risk Assessment of the impact of Contaminants on Water resources and ECOsystems (FRAC-WECO

Pharmacomodulation of a ligand targeting the HBV capsid hydrophobic pocket

International audienceHepatitis B virus (HBV) is a small enveloped retrotranscribing DNA virus and an important human pathogen. Its capsid-forming core protein (Cp) features a hydrophobic pocket proposed to be central notably in capsid envelopment. Indeed, mutations in and around this pocket can profoundly modulate, and even abolish, secretion of enveloped virions. We have recently shown that Triton X-100, a detergent used during Cp purification, binds to the hydrophobic pocket with micromolar affinity. We here performed pharmacomodulation of pocket binders through systematic modifications of the three distinct chemical moieties composing the Triton X-100 molecule. Using NMR and ITC, we found that the flat aromatic moiety is essential for binding, while the number of atoms of the aliphatic chain modulates binding affinity. The hydrophilic tail, in contrast, is highly tolerant to changes in both length and type. Our data provide essential information for designing a new class of HBV antivirals targeting capsid-envelope interactions

Les partis politiques

Le numéro 16 des Cahiers de la recherche sur les droits fondamentaux permet de faire le point sur l'évolution contemporaine des partis politiques, à un moment où le paysage, tant français qu'international, se trouve marqué par une forte recomposition de l'offre partisane

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

BackgroundWe previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in similar to 80% of cases.MethodsWe report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded.ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P=1.1x10(-4)) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70[95%CI 1.3-8.2], P=2.1x10(-4)). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR=19.65[95%CI 2.1-2635.4], P=3.4x10(-3)), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR=4.40[9%CI 2.3-8.4], P=7.7x10(-8)). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10(-5)).ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old