Predictable quantum efficient detector based on n-type silicon photodiodes

The predictable quantum efficient detector (PQED) consists of two custom-made induced junction photodiodes that are mounted in a wedged trap configuration for the reduction of reflectance losses. Until now, all manufactured PQED photodiodes have been based on a structure where a SiO2 layer is thermally grown on top of p-type silicon substrate. In this paper, we present the design, manufacturing, modelling and characterization of a new type of PQED, where the photodiodes have an Al2O3 layer on top of n-type silicon substrate. Atomic layer deposition is used to deposit the layer to the desired thickness. Two sets of photodiodes with varying oxide thicknesses and substrate doping concentrations were fabricated. In order to predict recombination losses of charge carriers, a 3D model of the photodiode was built into Cogenda Genius semiconductor simulation software. It is important to note that a novel experimental method was developed to obtain values for the 3D model parameters. This makes the prediction of the PQED responsivity a completely autonomous process. Detectors were characterized for temperature dependence of dark current, spatial uniformity of responsivity, reflectance, linearity and absolute responsivity at the wavelengths of 488 nm and 532 nm. For both sets of photodiodes, the modelled and measured responsivities were generally in agreement within the measurement and modelling uncertainties of around 100 parts per million (ppm). There is, however, an indication that the modelled internal quantum deficiency may be underestimated by a similar amount. Moreover, the responsivities of the detectors were spatially uniform within 30 ppm peak-to-peak variation. The results obtained in this research indicate that the n-type induced junction photodiode is a very promising alternative to the existing p-type detectors, and thus give additional credibility to the concept of modelled quantum detector serving as a primary standard. Furthermore, the manufacturing of PQEDs is no longer dependent on the availability of a certain type of very lightly doped p-type silicon wafers.Peer reviewe

Prolonged sleep restriction induces changes in pathways involved in cholesterol metabolism and inflammatory responses

Sleep loss and insufficient sleep are risk factors for cardiometabolic diseases, but data on how insufficient sleep contributes to these diseases are scarce. These questions were addressed using two approaches: an experimental, partial sleep restriction study (14 cases and 7 control subjects) with objective verification of sleep amount, and two independent epidemiological cohorts (altogether 2739 individuals) with questions of sleep insufficiency. In both approaches, blood transcriptome and serum metabolome were analysed. Sleep loss decreased the expression of genes encoding cholesterol transporters and increased expression in pathways involved in inflammatory responses in both paradigms. Metabolomic analyses revealed lower circulating large HDL in the population cohorts among subjects reporting insufficient sleep, while circulating LDL decreased in the experimental sleep restriction study. These findings suggest that prolonged sleep deprivation modifies inflammatory and cholesterol pathways at the level of gene expression and serum lipoproteins, inducing changes toward potentially higher risk for cardiometabolic diseases.Peer reviewe

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies

Joint Observation of the Galactic Center with MAGIC and CTA-LST-1

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes (IACTs), designed to detect very-high-energy gamma rays, and is operating in stereoscopic mode since 2009 at the Observatorio del Roque de Los Muchachos in La Palma, Spain. In 2018, the prototype IACT of the Large-Sized Telescope (LST-1) for the Cherenkov Telescope Array, a next-generation ground-based gamma-ray observatory, was inaugurated at the same site, at a distance of approximately 100 meters from the MAGIC telescopes. Using joint observations between MAGIC and LST-1, we developed a dedicated analysis pipeline and established the threefold telescope system via software, achieving the highest sensitivity in the northern hemisphere. Based on this enhanced performance, MAGIC and LST-1 have been jointly and regularly observing the Galactic Center, a region of paramount importance and complexity for IACTs. In particular, the gamma-ray emission from the dynamical center of the Milky Way is under debate. Although previous measurements suggested that a supermassive black hole Sagittarius A* plays a primary role, its radiation mechanism remains unclear, mainly due to limited angular resolution and sensitivity. The enhanced sensitivity in our novel approach is thus expected to provide new insights into the question. We here present the current status of the data analysis for the Galactic Center joint MAGIC and LST-1 observations

Mise en oeuvre d'approches pédagogiques fondées sur des pratiques de l'industrie du logiciel pour l'apprentissage de la programmation

International audienceCet article présente un nouveau protocole d’apprentissage de la programmation dans lequel les séquences de travail sont structurées en cycles : d’abord l’étudiant développe individuellement une partie d’un logiciel spécifiée par un ensemble exhaustif de tests automatisés fournis par l’enseignant. Ensuite, afin de favoriser les interactions entre pairs,une ou plusieurs phases de revue de code sont introduites. Ces phases de revue sont orchestrées avec la plate-forme elaastic. L’orchestration du protocole est facilitée grâce à l’outil Git4School qui extrait des métriques d’apprentissage depuis les dépôts git des étudiants et les synthétise sous forme de graphiques permettant un suivi individualisé des étudiants

Git4School : un tableau de bord pour assister la prise de décisions de l'enseignant lors des cours de génie logiciel

Revue Sciences et Techniques de l'Information et de la Communication pour l'Éducation et la FormationNational audienceThis article presents Git4School, a dashboard for teachers providing visualizations based on data extracted from learners' Git repositories, combined with temporal contextual information. Based on several experiments, we show a good general feeling of learners about using Git in an educational context. We show how Git4School can be useful for identifying weaknesses in learning designs and for targeting their needs for improvement.Cet article présente Git4School, un tableau de bord pour les enseignants offrant des visualisations s'appuyant sur des données extraites des dépôts Git des apprenants, combinées à des informations contextuelles temporelles. Sur la base de plusieurs expérimentations, nous montrons un bon sentiment général des apprenants sur l’utilisation de Git dans un contexte éducatif. De plus, nous montrons comment Git4School peut être utile pour identifier les faiblesses des conceptions des situations d'apprentissage et cibler leur amélioration

Finding behavioral indicators from contextualized commits in software engineering courses with process mining

International audienceGit4School is a dashboard helping teachers to monitor and make decisions during Git-based lab sessions in higher education computer science programs. This tool makes it possible to visualize the commits made by students over time according to the context and, in particular, the type of pedagogical intervention by the teacher (discussions between students on the problem, dissemination of a solution, etc.). Despite its visualizations providing indicators for decision-making, the tool does not provide information about the student's behavior. There are existing studies dealing with Process Mining (PM) in education, specifically in computer science courses and using Git. Through an empirical exploratory study, we explore the possibility of taking advantage of these contextualized commits using PM. We analyzed data from 5 teaching units covering different higher education levels using the bupaR library. Firstly, we discovered promising indicators to predict students' behavior during a lab session. Secondly, we identified several possibilities for future research on PM and contextualized commits. Finally, we have established a set of recommendations to help analyze contextualized commits using PM

Traceability by design: design of an interactive system to improve the automatic generation of Git traces during a learning activity

International audienceLearning Analytics (LA) is collecting and analyzing traces of learners' activities in order to understand and improve learning. This paper focuses on traces generated using the version control system Git. Existing works on the topic have limitations regarding the quality of the traces they analyze: (1) the quantity and content are not always sufficient for in-depth analysis of student behavior, (2) their limited reliability can lead to a loss of exploitable data, and (3) the method of generating these traces is not generic. We propose a new interactive system based on Git and the observation of file modifications to generate automatically reliable and rich traces. This interactive system will soon be experimented with in an ecological context and is intended for diversified teaching contexts