Minimum-Volume Nonnegative Matrix Completion

peer reviewe

Utiliser l'art-thérapie auprès des aidants familiaux/naturels en USP

peer reviewedCet article retrace l’expérience clinique d’une art-thérapeute et psychologue clinicienne intervenant auprès des aidants proches de patients admis au sein d’une USP. L’objectif est de partager et d’illustrer, grâce à deux vignettes cliniques, les possibilités qu’offre l’art-thérapie auprès du public des aidants en contexte de fin de vie. L’art-thérapie, plus spécifiquement les Arts Plastiques, propose des pistes pour diminuer la sensation d’épuisement psychologique et physique de l’aidant proche. De plus, l’art-thérapie peut faciliter l’accompagnement de l’aidant dans son travail de pré-deuil auprès du proche admis en USP. L’article souhaite penser la place que pourrait prendre la production artistique dans l’accompagnement du pré-deuil. Ce travail permet de discuter de l’importance de l’accompagnement art-thérapeutique pour ces aidants offrant beaucoup, mais n’acceptant de recevoir que très peu

OhmPi: learn how to build an open-source resistivity meter

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Inclusivity in urban energy transitions: A methodological approach for mapping gendered energy vulnerability

peer reviewedEnergy poverty has become a notable concern within the European Union (EU), with adverse implications for the well-being and social inclusion of susceptible populations, particularly women. Despite an increasing focus on gender perspectives in the context of the energy transition in recent years, the assessment of the geographical distribution of energy vulnerability remains gender-blind. This paper introduces a simplified method for mapping gendered energy-vulnerable areas through a gender-responsive index. The proposed method enlightens the potential use of open-access data for evaluating energy vulnerability from a gender perspective. Additionally, the methodology cross-references previous energy poverty assessments to identify matching cases of gendered energy vulnerability, resulting in the Gendered Energy Vulnerability Index (GEVI). The GEVI enables the classification of areas based on their risk of experiencing gendered energy vulnerability. To illustrate the method, it is applied to the evaluation of a case study of Madrid, Spain. Findings estimate that 42 neighborhoods, representing 32 % of the total in the city, might be at risk of facing gendered energy vulnerability, with a pronounced impact on elderly women, single-parent households led by women, and women engaged in part-time employment or elementary occupations. The study also identifies specific spatial patterns and correlations within the city

La psychologie positive comme levier d'épanouissement des élèves ? Apports et limites

3. Good health and well-bein

Selectivity in the chiral self-assembly of nucleobase-arylazopyrazole photoswitches along DNA templates

peer reviewedThe control of supramolecular DNA assembly through external stimuli such as light represents a promising approach to control bioreactions, and modulate hybridization or delivery processes. Here, we report on the design of nucleobase-containing arylazopyrazole photoswitches that undergo chiral organization upon self-assembly along short DNA templates. Chiroptical spectroscopy shows that the specific nucleobases allow selectivity in the resulting supramolecular DNA complexes, and UV light irradiation triggers partial desorption of the arylazopyrazole photoswitches. Molecular modeling studies reveal the differences of binding modes between the two configurations in the templated assembly. Remarkably, our results show that the photoswitching behaviour controls the self-assembly process along DNA, opening the way to potential applications as nano- and biomaterials

Radiotolerance of N-cycle bacteria and their transcriptomic response to low-dose space-analogue ionizing irradiation.

peer reviewedThe advancement of regenerative life support systems (RLSS) is crucial to allow long-distance space travel. Within the Micro-Ecological Life Support System Alternative (MELiSSA), efficient nitrogen recovery from urine and other waste streams is vital to produce liquid fertilizer to feed food and oxygen production in subsequent photoautotrophic processes. This study explores the effects of ionizing radiation on nitrogen cycle bacteria that transform urea to nitrate. In particular, we assess the radiotolerance of Comamonas testosteroni, Nitrosomonas europaea, and Nitrobacter winogradskyi after exposure to acute γ-irradiation. Moreover, a comprehensive whole transcriptome analysis elucidates the effects of spaceflight-analogue low-dose ionizing radiation on the individual axenic strains and on their synthetic community o. This research sheds light on how the spaceflight environment could affect ureolysis and nitrification processes from a transcriptomic perspective

Efficient Generalized Electroencephalography-Based Drowsiness Detection Approach with Minimal Electrodes

peer reviewedDrowsiness is a main factor for various costly defects, even fatal accidents in areas such as construction, transportation, industry and medicine, due to the lack of monitoring vigilance in the mentioned areas. The implementation of a drowsiness detection system can greatly help to reduce the defects and accident rates by alerting individuals when they enter a drowsy state. This research proposes an electroencephalography (EEG)-based approach for detecting drowsiness. EEG signals are passed through a preprocessing chain composed of artifact removal and segmentation to ensure accurate detection followed by different feature extraction methods to extract the different features related to drowsiness. This work explores the use of various machine learning algorithms such as Support Vector Machine (SVM), the K nearest neighbor (KNN), the Naive Bayes (NB), the Decision Tree (DT), and the Multilayer Perceptron (MLP) to analyze EEG signals sourced from the DROZY database, carefully labeled into two distinct states of alertness (awake and drowsy). Segmentation into 10 s intervals ensures precise detection, while a relevant feature selection layer enhances accuracy and generalizability. The proposed approach achieves high accuracy rates of 99.84% and 96.4% for intra (subject by subject) and inter (cross-subject) modes, respectively. SVM emerges as the most effective model for drowsiness detection in the intra mode, while MLP demonstrates superior accuracy in the inter mode. This research offers a promising avenue for implementing proactive drowsiness detection systems to enhance occupational safety across various industries