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La cité étudiante ou les ambivalences de l’engagement et de la mobilité sociale
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La construction des rapports à la citoyenneté chez l’enfant dans le cadre de dispositifs d’éducation à la citoyenneté
No full textCarnet Hypothèses de la MSH BordeauxArticle issu du colloque : « L’âge de voter. Dépasser le droit de vote à 18 ans ? » Pôle Juridique et judiciaire Bordeaux, 19 septembre 2024, organisée dans le cadre de l’Appel à projets MSHBx 2024 L’âge de voter. Dépasser le droit de vote à 18 ans ? – AV-DDV18, organisé par Marion Paoletti et Charles-Édouard Sénac
Beyond green hydrogen production: Ground transport within Europe, the hidden environmental impacts
No full textInternational audienceAs Europe accelerates its transition to low-carbon energy, renewable hydrogen is expected to play a key role in decarbonizing hard-to-abate industrial sectors. While the environmental impacts of hydrogen production via electrolysis are starting to be well understood, those of its storage and transport remain poorly determined. Yet, they are crucial to overall sustainability. This study presents a comparative Life Cycle Assessment (LCA) of six land-based delivery pathways across Europe for green hydrogen produced via Proton Exchange Membrane (PEM) electrolysis powered by wind energy. The scenarios differ in storage and transport methods-compressed gas (by truck or pipeline), liquefied hydrogen, and three chemical vectors (dibenzyltoluene, ammonia and methanol) transported by truck. While the production phase of green hydrogen shows a low Global Warming (GW) impact, the delivery stages are far from negligible, leading in certain cases to an overall GW impact exceeding that of domestically produced blue or grey hydrogen. These findings are amplified by taking into account hydrogen leaks across the supply chain and their Global Warming Potential. However, results demonstrate that there is no one-size-fits-all hydrogen delivery solution; optimal pathways depend on supply chain parameters, mainly distance and hydrogen demand. Pipeline transport emerges as the most environmentally efficient option for largescale long-distance hydrogen transportation, whereas compressed gas hydrogen by truck is better suited for small-scale local delivery. Alternative delivery options, such as hydrogen liquefaction or conversion into chemical carriers with higher energy density, can lower transport-related emissions. These advantages often come with environmental trade-offs, as additional conversion steps shift part of the burden to other life-cycle stages and to other impact categories beyond GW, such as acidification and eutrophication. This study highlights the importance of integrating delivery considerations into hydrogen deployment strategies and policies. Finally, while the focus is on intra-European exchanges and ground transport, future work must investigate international hydrogen trade and maritime transport, along with their broader environmental and geopolitical implications
Towards a Novel Vertical Scaling Approach for Bursty Workloads in Kubernetes
No full textInternational audienceTraditional static computational resource allocation in cloud oron-premises clusters often results in inefficient overprovisioning.Users frequently lack precise knowledge of the memory and processors their applications require, leading them to request excessresources. This causes wasted capacity, higher costs, and, in sharedenvironments, longer queue waiting times. Dynamic resource allocation through autoscaling addresses this issue by adjusting resources at runtime. Kubernetes, a widely used container orchestration platform, supports autoscaling via Horizontal and Vertical PodAutoscalers. However, its default restart-based scaling can disruptstateful, long-running workloads without checkpointing. This workleverages Kubernetes’ new in-place scaling, which resizes resourceswithout restarts, to propose the Dynamic Resizing Strategy (DRS), anovel autoscaling approach that proactively manages contention bytemporarily throttling co-located pods to prioritize a bursting application. We evaluate it with NAS Parallel Benchmarks and syntheticworkloads in co-execution scenarios, showing improved efficiencyand stability, increasing success rates and reducing global averagewait time by over 18% compared to the Burstable QoS class
Markovian dynamics of single-rebit open quantum systems with applications to colour perception
No full textThis paper investigates the Markovian dynamics of open two-state quantum systems defined over the real numbers (rebits). Two main objectives are pursued. First, we present a comprehensive classification of Markovian rebit quantum channels, i.e. one-parameter semigroups of completely positive, trace-preserving (CPTP) maps acting on the rebit state space. We show that a full characterisation of their action can be achieved and that describing these channels as solutions of the GKSL equation allows us to explicitly identify the associated Lindblad generators and conditions for complete positivity. Second, we present an original application of this classification to colour perception. Using a recent model in which perceived colours arise from Lüders measurements on the rebit state space, we show how chromatic distortion induced by a non-neutral illuminant can be modelled by a Markovian rebit channel that progressively diminishes colour distinguishability. Other types of channels could be used to study colour vision deficiencies. These phenomena are illustrated by simulations on digital images, highlighting the relevance of rebit Markovian dynamics in modelling colour vision
Building pangenomes for domesticated and wild tree species: genomic complexity and strategies
No full textAbstract Long-read sequencing and pangenomics are revolutionizing crop research by providing more complete genome information and revealing crucial structural variations linked to important agricultural traits. Building on recent advances in intraspecific pangenome construction, this study addresses the challenge of creating broader, cross-taxon pangenomes, using the Armeniaca taxonomic section as a model. Leveraging a diverse panel of genome assemblies, we constructed a pangenome graph and cataloged associated single nucleotide polymorphisms (SNPs) and structural variants. We characterized the diversity of these variants and assessed the extent to which different taxa contribute to overall pangenome expansion. Additionally, we evaluated the performance of low-depth sample mapping to the graph-based reference, highlighting key technical limitations that may affect the quality of downstream analyses. We further identified specific subsets of SVs that exhibit associations with particular classes of transposable elements. As a case study illustrating the potential functional and phenotypic relevance of graph-derived SVs, we examined the genomic configuration of the DAM locus within the Armeniaca pangenome
MetaNetMap : cartographie automatique des données métabolomiques sur les réseaux métaboliques
No full textInternational audienceMetabolic networks represent genome-derived information about the biochemical reactions that cells are capable of performing. Mapping omic data onto these networks is important to refine model simulations. However, metabolomic data mapping remains very challenging due to difficulties in identifier reconciliation between annotation profiles and metabolic networks. MetaNetMap is a Python package designed to automatise the process of mapping metabolomic data onto metabolic networks. It includes several layers of identifier matching, the use of customisable databases, and molecular ontology integration to suggest the most matches between experimentally-identified metabolites and molecules defined in the network.Les réseaux métaboliques représentent les informations issues du génome concernant les réactions biochimiques que les cellules sont capables d'effectuer. La cartographie des données omiques sur ces réseaux est importante pour affiner les simulations de modèles. Cependant, la cartographie des données métabolomiques reste très difficile en raison des difficultés de rapprochement des identifiants entre les profils d'annotation et les réseaux métaboliques. MetaNetMap est un package Python conçu pour automatiser le processus de cartographie des données métabolomiques sur les réseaux métaboliques. Il comprend plusieurs niveaux de correspondance des identifiants, l'utilisation de bases de données personnalisables et l'intégration de l'ontologie moléculaire afin de suggérer les correspondances les plus pertinentes entre les métabolites identifiés expérimentalement et les molécules définies dans le réseau
New Metrics of Event-Related (De)Synchronization Temporal Variability Explain Motor Imagery-based BCI Performance
No full textMotor Imagery-based (MI) Brain-Computer Interface (BCI) detect imagined limb movements from ElectroEncephaloGraphy (EEG) to translate them into commands for various applications. They do so by analyzing sensorimotor EEG rhythms, typically event-related (de)synchronization (ERD/S) over the motor cortex. Despite MI task intuitiveness and their many BCI applications, not all users achieve sufficient MI classification accuracy, notably due to large intraand inter-user variability in ERD/S. Understanding this variability is thus crucial for finding ways to enhance BCI classification performance, but BCI variability metrics are lacking. Therefore, this paper proposes two new ERD/S variability metrics and studies, on a large MI-BCI dataset (N = 85 users), how these and two existing metrics can explain BCI performance.Results show that temporal variability of ERD/S—both within and across trials—negatively correlates (r = −0.28 to −0.34) with BCI performance in the within-user scenario (with a user-specific classifier). In the cross-users scenario (with a generic cross-user classifier), test users variability metrics, including ERD/S temporal and amplitude variability, were negatively correlated with performance (r = −0.30 to −0.39). These findings demonstrate the value of metrics to quantify ERD/S variability. They may also guide future design strategies for BCI user training or machine learning
Hadron Physics Opportunities at FAIR
No full textInternational audienceThis White Paper outlines a coordinated, decade-spanning programme of hadron and QCD studies anchored at the GSI/FAIR accelerator complex. Profiting from intense deuteron, proton and pion beams coupled with high-rate capable detectors and an international theory effort, the initiative addresses fundamental questions related to the strong interaction featuring confinement and dynamical mass generation. This includes our understanding of hadron-hadron interactions and the composition of hadrons through mapping the baryon and meson spectra, including exotic states, and quantifying hadron structure. This interdisciplinary research connects topics in the fields of nuclear, heavy-ion, and (nuclear) astro (particle) physics, linking, for example, terrestrial data to constraints on neutron star structure. A phased roadmap with SIS100 accelerator start-up and envisaged detector upgrades will yield precision cross sections, transition form factors, in-medium spectral functions, and validated theory inputs. Synergies with external programmes at international accelerator facilities worldwide are anticipated. The programme is expected to deliver decisive advances in our understanding of non-perturbative (strong) QCD and astrophysics, and high-rate detector and data-science technology