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Quelle place pour les réseaux de chaleur dans le système énergétique Européen de 2050 ?
No full textDistrict heating networks (DHNs) are the preferred solution for decarbonizing urban heat demand. Beyond their economicefficiency stemming from economies of scale, DHNs provide access to various renewable sources such as geothermalenergy, waste heat, or solar thermal energy. However, these sources will not be sufficient to meet the entire DHN demandand will have to be completed by technologies powered by biomass or electricity. This has significant implications for theenergy system, as decarbonization increases pressure on biomass resources and the power system. In this context, thisthesis aims to analyze the development potential of district heating networks and to assess their impacts on the entire energysystem by 2050.After a detailed review of the literature on the challenges of heat decarbonization, we present a geographic method for generatinglarge-scale DHN development scenarios, with an application to Europe. We then describe a method for aggregatingDHNs, enabling more accurate modeling in energy system models. Finally, these contributions make it possible to analyzethe impact of electrified DHNs on the European energy system through two studies. The first study shows that, by substitutingbiomass and biogas, electrified DHNs could reduce the total system costs by decreasing dependency on methane, whether itis imported biogas or produced by methanation. The second study analyzes and quantifies in depth the flexibility provided byDHNs to the power system compared to individual electric heating: this flexibility is significant at daily and weekly timescalesand helps to reduce loss-of-load energy.Les réseaux de chaleur (RdCs) constituent le premier choix pour décarboner la demande de chaleur dans les villes. Outreleur efficacité économique due aux économies d’échelle, les RdCs donnent accès à diverses sources renouvelables commela géothermie, la récupération de chaleur fatale, ou le solaire thermique. Mais ces sources ne seront pas suffisantes pouralimenter toute la demande de chaleur-réseau et devront être complétées par des moyens fonctionnant à la biomasse età l’électricité. Cela n’est pas sans conséquence sur un système énergétique où la décarbonation accroît les tensions surles ressources en biomasse et sur le système électrique. Dans ce contexte, cette thèse vise à analyser le potentiel dedéveloppement des réseaux de chaleur et à évaluer leurs impacts sur l’ensemble du système énergétique à horizon 2050.Après une revue détaillée de la littérature sur les enjeux de la décarbonation de la chaleur, nous présentons une méthodegéographique pour générer des scénarios de développement des RdCs à large échelle, avec une application sur l’Europe.Nous détaillons ensuite une méthode d’agrégation des RdCs permettant de les modéliser avec précision dans les modèles dusystème énergétique. Enfin, ces contributions permettent d’analyser l’impact des RdCs électrifiés sur le système énergétiqueeuropéen via deux études. La première étude montre, qu’en se substituant à de la biomasse et du biogaz, les RdCsélectrifiés pourraient réduire les coûts totaux du système en réduisant sa dépendance au méthane, qu’il soit du biogazimporté ou généré par méthanation. La seconde étude analyse et quantifie en profondeur la flexibilité fournie par les RdCs ausystème électrique comparé à du chauffage électrique individuel : cette fourniture est significative aux échelles journalières et hebdomadaires et permet de réduire la défaillance électrique
Des éthers de cellulose aux bio-aérogels : Vers des vecteurs de médicaments sans additifs
No full textThis thesis explores the potential of neat cellulose ethers, particularly carboxymethyl cellulose (CMC) and methylcellulose (MC), for making aerogels aimed at drug delivery applications and complex shape manufacturing via 3D printing. Despite the widespread use of cellulose ethers in medicine and industry, neat CMC or MC aerogels remain scarcely explored. Lightweight aerogels with high specific surface area (up to several hundred m²/g) were prepared through non-solvent induced phase separation followed by supercritical CO₂ drying. Alternative drying routes, such as freeze-drying and evaporative drying, were also used to produce cryogels and xerogels for comparative analysis. The structure and morphology of the materials were thoroughly characterized, and drug release behavior was assessed using a model drug (L-Ascorbic acid 2-phosphate) in simulated wound exudate. The results demonstrate that both CMC and MC aerogels are promising candidates for drug delivery. Mechanical properties of CMC aerogels and cryogels were evaluated via uniaxial compression tests combined with digital image correlation. Direct ink writing was successfully applied to neat CMC solutions without any additives or crosslinking, only by adjusting solutions' rheological properties. Aerogels were then made from the printed structures through drying with supercritical CO2. These findings provide an important basis for the design and manufacturing of customized biopolymer porous scaffolds for drug delivery, tissue engineering, and other related applications.Cette thèse explore le potentiel des éthers de cellulose purs, en particulier la carboxyméthylcellulose (CMC) et la méthylcellulose (MC), pour la fabrication d'aérogels destinés à des applications en administration de médicaments ainsi qu'à la production de formes complexes via l'impression 3D. Bien que les éthers de cellulose soient largement utilisés dans les domaines médical et industriel, les aérogels obtenus à partir de CMC ou de MC non modifiés restent très peu étudiés. Des aérogels légers, présentant une surface spécifique élevée (jusqu'à plusieurs centaines de m²/g), ont été préparés par séparation de phase induite par non-solvant, suivie d'un séchage au CO₂ supercritique. D'autres procédés de séchage, tels que la lyophilisation et le séchage évaporatif, ont également été utilisés pour produire respectivement des cryogels et des xérogels, dans un but comparatif. La structure et la morphologie des matériaux ont été caractérisées de manière approfondie, et le comportement de libération du médicament a été évalué à l'aide d'un médicament modèle (acide L-ascorbique 2-phosphate) dans un exsudat simulé de plaie. Les résultats montrent que les aérogels de CMC et de MC constituent des candidats prometteurs pour l'administration de médicaments. Les propriétés mécaniques des aérogels et des cryogels de CMC ont été mesurées par des essais de compression uniaxiale couplés à une analyse par corrélation d'images numériques. L'impression directe à l'encre a été appliquée avec succès, pour la première fois, à des solutions aqueuses de CMC sans aucun additif ni agent de réticulation, uniquement en ajustant leurs propriétés rhéologiques. Des aérogels ont ensuite été obtenus à partir des structures imprimées, par séchage au CO₂ supercritique. Ces résultats fournissent une base importante pour la conception et la fabrication de structures poreuses personnalisées à base de biopolymères, destinées à des applications en administration de médicaments, en ingénierie tissulaire et dans d'autres domaines biomédicaux connexes
Multiple-Frequencies Population-Based Training
No full textInternational audienceReinforcement Learning's high sensitivity to hyperparameters is a source of instability and inefficiency, creating significant challenges for practitioners. Hyperparameter Optimization (HPO) algorithms have been developed to address this issue, among them Population-Based Training (PBT) stands out for its ability to generate hyperparameters schedules instead of fixed configurations. PBT trains a population of agents, each with its own hyperparameters, frequently ranking them and replacing the worst performers with mutations of the best agents. These intermediate selection steps can cause PBT to focus on short-term improvements, leading it to get stuck in local optima and eventually fall behind vanilla Random Search over longer timescales. This paper studies how this greediness issue is connected to the choice of evolution frequency, the rate at which the selection is done. We propose Multiple-Frequencies Population-Based Training (MF-PBT), a novel HPO algorithm that addresses greediness by employing sub-populations, each evolving at distinct frequencies. MF-PBT introduces a migration process to transfer information between sub-populations, with an asymmetric design to balance short and long-term optimization. Contribution(s)1. We investigate the impact of evolution frequency on PBT and its connection to greediness.Context: PBT (Jaderberg et al., 2017) introduces a parameter, denoted t ready , which controls the evolution frequency of its genetic process. Previous extensions of PBT (Parker-</div
MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models
No full textHistopathological analysis is a cornerstone of cancer diagnosis, with Hematoxylin and Eosin (H&E) staining routinely acquired for every patient to visualize cell morphology and tissue architecture. On the other hand, multiplex immunofluorescence (mIF) enables more precise cell type identification via proteomic markers, but has yet to achieve widespread clinical adoption due to cost and logistical constraints. To bridge this gap, we introduce MIPHEI (Multiplex Immunofluorescence Prediction from H&E), a U-Net-inspired architecture that integrates state-of-the-art ViT foundation models as encoders to predict mIF signals from H&E images. MIPHEI targets a comprehensive panel of markers spanning nuclear content, immune lineages (T cells, B cells, myeloid), epithelium, stroma, vasculature, and proliferation. We train our model using the publicly available ORION dataset of restained H&E and mIF images from colorectal cancer tissue, and validate it on two independent datasets. MIPHEI achieves accurate cell-type classification from H&E alone, with F1 scores of 0.88 for Pan-CK, 0.57 for CD3e, 0.56 for SMA, 0.36 for CD68, and 0.30 for CD20, substantially outperforming both a state-of-the-art baseline and a random classifier for most markers. Our results indicate that our model effectively captures the complex relationships between nuclear morphologies in their tissue context, as visible in H&E images and molecular markers defining specific cell types. MIPHEI offers a promising step toward enabling cell-type-aware analysis of large-scale H&E datasets, in view of uncovering relationships between spatial cellular organization and patient outcomes
Leveraging Small Biodiversity Reserves to Prevent Zoonotic Disease: Insights from Dilution Effect and Pathogen Adaptation Theories
No full textInternational audienceCommunication Leveraging Small Biodiversity Reserves to Prevent Zoonotic Disease: Insights from Dilution Effect and Pathogen Adaptation Theories Audrey Arnal 1,2,3, Rodolphe Elie Gozlan 4, Nathalie Charbonnel 5, Marie Bouilloud 1,5, Andrea Chaves 6,7, Manon Lounnas 1,2, Michel Gauthier-Clerc 8, Ana L. Vigueras-Galván 2,3, Céline Arnathau 1,2, David Roiz 1,2, Ana I. Bento 9, Serge Morand 10,11,12, Chris Walzer 13,14, Gerardo Suzán 2,15, Rosa Elena Sarmiento Silva 2,3,*,† and Benjamin Roche 1,2,3,† 1 MIVEGEC, Université de Montpellier, IRD, CNRS, 34394 Montpellier, France 2 International Joint Laboratory IRD/UNAM ELDORADO, Merida 97000, Mexico 3 Departamento de Microbiología e Inmunología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México (UNAM), Ciudad de México 04510, Mexico 4 ISEM, University of Montpellier, CNRS, IRD, 34090 Montpellier, France 5 CBGP, INRAE, CIRAD, IRD, Institut Agro, Université de Montpellier, 34398 Montpellier, France 6 Centro Nacional de Innovaciones Biotecnológicas (CENIBiot), CeNAT, Conare, San José 1174-1200, Costa Rica 7 Escuela de Biología, Universidad de Costa Rica, San José 11501-206, Costa Rica 8&nbspFaculté des Sciences, Université de Genève, 30 Quai Ernest-Ansermet, CH-1211 Geneve, Switzerland 9 Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA 10 IRL Health DEEP, CNRS, Kasetsart University, Mahidol University Bangkok 10900, Thailand 11 Faculty of Veterinary Technology, Kasetsart University, Bangkok 10900, Thailand 12 Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand 13 Wildlife Conservation Society Southern Boulevard, Bronx, NY 10460, USA 14 Research Institute of Wildlife Ecology, University of Veterinary Medicine, 1210 Vienna, Austria 15 Departamento de Etología, Fauna Silvestre y Animales de Laboratorio, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México (UNAM), Ciudad de México 04360, Mexico * Correspondence: [email protected]; Tel.: +52-554-449-7749 † Co-last authors. Received: 22 February 2025; Revised: 12 March 2025; Accepted: 12 March 2025; Published: 2 April 2025 Abstract: In today’s landscape of zoonotic pathogen outbreaks, the dilution effect theory, i.e., the theory that greater biodiversity can help curb pathogen transmission among wildlife, has gained significant attention. However, the positive link between animal diversity and pathogen richness urges us to apply this concept with caution. It is crucial to explore how conservation biology can safeguard human health by preventing the emergence of zoonotic diseases. By investigating the implications of conservation strategies on animal communities and pathogen transmission as well as the adaptive capabilities of pathogens, we propose that biodiversity conservation based on small reserves can effectively reduce pathogen spread in wildlife, provided certain measurable conditions are met. Given the urgent need to tackle both zoonoses disease emergence and biodiversity loss, these interventions should be prioritized and implemented without delay
Actes du SDFIA 2025: Premier symposium doctoral francophone en intelligence artificielle
No full textInternational audienceLes actes du SDFIA 2025 rassemblent des travaux doctoraux francophones couvrant un large spectre de l’IA, de la vision par ordinateur aux systèmes multi‑agents, de l’IA explicable aux modèles robustes d’estimation, jusqu’aux applications sécurité réseau et énergie. Organisé le 9 octobre 2025 à l’issue de l’école d’automne RobIA’25, l’événement met l’accent sur la reproductibilité, la diffusion open source et la rigueur méthodologique. Les articles longs présentent des contributions expérimentales et comparatives (classification d’images, génération pour classes rares, détection d’intrusions), tandis que les articles courts explorent consensus du second ordre, ViT pour la détection de piétons, SSL pour obstacles routiers, et filtres de Kalman robustes. L’ensemble témoigne de la vitalité de la recherche doctorale francophone, avec des résultats applicables à l’agriculture, la mobilité, la cybersécurité, l’éducation et le photovoltaïque
SAT-374-YI Health related quality of life in patients with porto-sinusoidal vascular disorder
No full textInternational audienc
Life cycle assessment of algal products: A step-by-step guide to application
No full textThis information paper provides an accessible introduction to Life Cycle Assessment (LCA) for researchers, industry professionals, and policymakers in the algae sector, with limited or no experience in the methodology. Developed collaboratively by LCA experts and non-specialists, this information paper outlines key concepts, applications, and best practices for assessing the environmental performance of algae-based products. LCA is now a common component of EU-funded algae projects, with its range of applications expanding from the assessment of biofuels to high-value compounds and complex production systems. It plays a central role in corporate sustainability, policy development, and in evaluating algae’s contribution to the bioeconomy. However, applying LCA to algae production technologies and algae-based products presents unique challenges such as system variability, data availability, and methodological choices that can strongly influence results and limit comparability. Raising awareness of these issues within the algae community is essential to ensure that LCA outcomes are interpreted meaningfully and used effectively. This information paper supports newcomers in understanding key terminology and practices related to LCA in algae systems, enabling more informed decision-making as well as the development of innovative and sustainable algae-based products
Impact of renewable natural gas (biomethane) in a deep aquifer storage in the Paris Basin: multiphase reactive transport modeling of H2S reactivity
No full textInternational audienceThe increasing integration of renewable natural gas (biomethane) into natural gas grids has gained significant attention due to its potential to reduce greenhouse gas emissions and contribute to the transition to cleaner energy sources. The growing share of biomethane in transportation grids also means that the underground gas storage facilities, including those in deep saline aquifers, are cycling a growing fraction of biomethane gas. Unlike conventional natural gas, biomethane often contains up to 10000 ppm of oxygen gas (O2) due to industrial oxidative desulfurization processes. O2 reactivity can impact the integrity of the reservoir, as well as groundwater and gas quality [1]. Hydrogen sulfide H2S gas can also be present in the injected gas or produced through microbial sulfate reduction during injection/withdrawal cycles.Field data from a sandstone aquifer gas storage site in the Paris Basin (France) indicate the evolution of H2S content in the stored gas over several years. Additionally, the influence of co-injecting O2 into the gas reservoir is revealed for the first time. A modeling study is proposed to investigate the geochemical impacts of the injection of natural gas and biomethane blend in the reservoir, focusing on O2 and H2S reactivity during successive cycles of injection and withdrawal. Multiphase reactive transport simulations are performed using the HYTEC software [2] under 1D and 2D axisymmetric configurations. Microbial kinetic models are implemented mainly on H2S production by sulfate-reducing bacteria (SRB) but also on H2S consumption by O2. The key findings show that the H2S content decreases in response to different O2 levels and pH conditions within the reservoir close to the injection wells. The significant role of SRB in controlling long-term H2S levels deeper in the whole storage is demonstrated. These findings emphasize the importance of integrating microbial processes into multiphase reactive transport models to improve predictions of reservoir behavior and gas quality. More generally, the insights gained from this study contribute to a better understanding of the risks and resilience properties of storage facilities associated with biomethane in deep saline aquifers. [1] Banc et al., 2024 https://doi.org/10.1016/j.jgsce.2024.205381[2] Sin et al., 2017 https://doi.org/10.1016/j.advwatres.2016.11.01