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Molecular Scale Modeling of Coal and Its Behavior
No full textInternational audienceGeomechanics of Coal Seams explores the evolving role of coal, transitioning from a historically criticized energy source tied to the Industrial Revolution, to a material with the potential to play a significant role in achieving net-zero greenhouse gas emissions. Traditionally used as raw material, coal now serves as a reservoir for natural gas or carbon dioxide storage, offering a path toward reducing global greenhouse gas emissions. Despite its promise, challenges remain, particularly regarding its geomechanical behavior.This book delves into the unique properties of coal, covering everything from geological foundations to numerical modeling. Aimed at students, researchers, and engineers, the book provides valuable insights applicable to other microporous materials.This chapter focuses on the study of coal through molecular modeling and simulation. The molecular scale is the appropriate level for gaining a detailed understanding of adsorption mechanisms within nanopores. Experimental investigation of mechanics at this scale is highly limited, and molecular simulation offers a complementary approach to experiments, relying on elementary physical interactions between atoms and molecules. The chapter concerns with so-called classical simulations, which are based on empirical interaction potentials between atoms, as opposed to ab initio simulations. However, such simulations remain valuable in coal research, as they help calibrate the empirical interaction potentials used in classical simulations. Classical simulations are, in turn, limited to studying systems no larger than a few tens of nanometers. Molecular approaches enable quantitative predictions of fluid adsorption, both for pure fluids and mixtures in coal, while also helping to understand and model the unusual poro-mechanical couplings
Explorer la relation entre la cyclabilité perçue et l'usage inclusif de la micro-mobilité en fonction du genre. Approche comparative dans 53 villes françaises
No full textInternational audienceAs the utilization of micromobility continues to experience growth and diversification, while simultaneously gaining recognition as an environmentally-friendly mode of transportation, it remains predominantly male-dominated. Recent scientific literature has highlighted the importance of inclusive strategies, demonstrating a strong correlation between the gender gap in cycling participation and the overall cycling levels within a given area. This indirect relationship necessitates identifying the factors that promote gender-inclusive bicycle usage. Focusing on the French context, the key objectives of this empirical research are (i) measuring gender inequalities in the use of bike and emerging micromobility at the municipal level, (ii) assessing the influence of built environment and urban design on the gendered modal share of cyclists, and (iii) comparing and clustering the investigated French cities with the development of an index that takes into account gender equity, the modal share of cycling, and the perceived bikeability. By drawing from two distinct databases based on the use of micromobility and the subjective bikeability of cities and by conducting quantitative observations, this original study sheds light on the significant connection between gender-balanced cycling distribution, cycling modal share, cycling infrastructure presence and perceived bikeability. This paper concludes that encouraging women to embrace cycling is not solely dependent on achieving a critical mass of cyclists or building cycling lanes. Instead, it emphasizes the need for the development of a comprehensive ’bicycle system’ that takes into account all aspects of bikeability. This innovative outcome leads to the categorization of examined cities based on the development of a gender-inclusive with cycling quality index. This exploration underscores the vital role of urban planning and offers recommendations for stakeholders regarding future policy initiatives.Alors que l'usage du vélo et de la micro-mobilité continuent de connaître une croissance et une diversification, tout en gagnant en reconnaissance en tant que modes de déplacement respectueux de l'environnement, cette mobilité individuelle légère reste majoritairement dominée par les usagers masculins. La littérature scientifique récente a souligné l'importance de stratégies englobant l'ensemble de la population, révélant une corrélation significative entre la pratique du vélo en fonction du genre et la part modale de ce mode dans un territoire donné. Cette relation indirecte nécessite d'identifier les facteurs favorisant la parité dans l'usage du vélo. Se concentrant sur le contexte français, les principaux objectifs de cette recherche empirique sont (i) de mesurer les inégalités de genre dans l'utilisation du vélo et de la micro-mobilité émergente au niveau municipal, (ii) d'évaluer l'influence de l'environnement urbain sur la répartition genrée du vélo et (iii) de comparer et de regrouper les villes françaises étudiées avec le développement d'un indice prenant en compte l'équité de genre, la part modale du vélo et la cyclabilité perçue. En s'appuyant sur deux bases de données distinctes basées sur l'usage du vélo et la cyclabilité subjective des villes, et en conduisant des observations quantitatives, cette étude originale met en lumière le lien significatif entre la distribution équilibrée des cyclistes en fonction du genre, la part modale du vélo, la présence d'infrastructures cyclables et la cyclabilité perçue. Cette publication conclut que la participation féminine au vélo et à la micro-mobilité ne dépend pas seulement de l'atteinte d'une masse critique de cyclistes ou de l'aménagement d'itinéraires cyclables. Au lieu de cela, elle souligne la nécessité de développer un « système vélo » qui prend en compte tous les aspects de la cyclabilité. Cette approche a dès lors mené à la catégorisation des villes examinées en fonction du développement d'un indice de qualité cyclable en lien avec la parité. Cette exploration souligne le rôle crucial de l'action de l'urbanisme et offre des recommandations aux acteurs de la fabrique urbaine
LRP1 involvement in FHIT-regulated HER2 signaling in non-small cell lung cancer
No full textInternational audienceThe tumor suppressor fragile histidine triad (FHIT) is frequently lost in non-small cell lung cancer (NSCLC). We previously showed that a down-regulation of FHIT causes an up-regulation of the activity of HER2 associated to an epithelial-mesenchymal transition (EMT) and that lung tumor cells harboring a FHITlow/pHER2high phenotype are sensitive to anti-HER2 drugs. Here, we sought to decipher the FHIT-regulated HER2 signaling pathway in NSCLC. Transcriptomic analysis of tumor cells isolated from NSCLC revealed the endocytic receptor low density lipoprotein receptor-related protein 1 (LRP1), a central regulator of membrane trafficking and cell signaling, as a potential player of this signaling. In a cohort of 80 NSCLC assessed by immunohistochemistry, we found a significant association between a low FHIT expression and a high pHER2 and LRP1 expression by tumor cells. Experiments of FHIT silencing showed that FHIT regulated LRP1 expression both at the mRNA and protein levels in lung cell lines. Analyzing the relationship between LRP1 and HER2, we observed that an anti-HER2 targeted therapy reversed LRP1 overexpression induced by FHIT silencing whereas LRP1 silencing did not affect HER2 activity. Studying the functional role of LRP1, we showed that cell proliferation and invasion induced by FHIT silencing were LRP1-dependent. In addition, we found that the induction of vimentin upon FHIT inactivation was counteracted by LRP1 silencing. These results suggest that LRP1 acts downstream of HER2 to induce EMT and tumor progression following FHIT loss. Dual targeting of HER2 and LRP1 might represent a therapeutic strategy to more efficiently inhibit HER2 signaling in FHIT-negative NSCLC
Quantile Regression, Variational Autoencoders, and Diffusion Models for Uncertainty Quantification: A Spatial Analysis of Sub-seasonal Wind Speed Prediction
No full textInternational audienceThis study aims to improve the spatial representation of uncertainties when regressing surface wind speeds from large-scale atmospheric predictors for sub-seasonal forecasting. Sub-seasonal forecasting often relies on large-scale atmospheric predictors such as 500 hPa geopotential height (Z500), which exhibit higher predictability than surface variables and can be downscaled to obtain more localised information. Previous work by Tian et al. (2024) demonstrated that stochastic perturbations based on model residuals can improve ensemble dispersion representation in statistical downscaling frameworks, but this method fails to represent spatial correlations and physical consistency adequately. More sophisticated approaches are needed to capture the complex relationships between large-scale predictors and local-scale predictands while maintaining physical consistency. Probabilistic deep learning models offer promising solutions for capturing complex spatial dependencies. This study evaluates three probabilistic methods with distinct uncertainty quantification mechanisms: Quantile Regression Neural Network that directly models distribution quantiles, Variational Autoencoders that leverage latent space sampling, and Diffusion Models that utilise iterative denoising. These models are trained on ERA5 reanalysis data and applied to ECMWF sub-seasonal hindcasts to regress probabilistic wind speed ensembles. Our results show that probabilistic downscaling approaches provide more realistic spatial uncertainty representations compared to simpler stochastic methods, with each probabilistic model offering different strengths in terms of ensemble dispersion, deterministic skill, and physical consistency. These findings establish probabilistic downscaling as an effective enhancement to operational sub-seasonal wind forecasts for renewable energy planning and risk assessment
Improving Subseasonal Wind Speed Forecasts in Europe with a Nonlinear Model
No full textInternational audienceSubseasonal wind speed forecasts provide valuable guidance for wind power system planning and operations, yet the forecast skills of surface winds decrease sharply after 2 weeks. However, large-scale variables exhibit greater predictability on this time scale. This study explores the potential of leveraging nonlinear relationships between the 500-hPa geopotential height (Z500) and surface wind speed to improve subseasonal wind speed forecast skills in Europe. Our proposed framework uses a multiple linear regression (MLR) or a convolutional neural network (CNN) to regress the surface wind speed from Z500. Evaluations on ERA5 reanalysis indicate that the CNN performs better due to its nonlinearity. Applying these models to subseasonal forecasts from the European Centre for Medium-Range Weather Forecasts, various verification metrics demonstrate the advantages of nonlinearity. Yet, this is partly explained by the fact that these statistical models are underdispersive since they explain only a fraction of the target variable variance. Introducing stochastic perturbations to represent the stochasticity of the unexplained part from the signal helps compensate for this issue. The results show that the perturbed CNN performs better than the perturbed MLR only in the first weeks, while the perturbed MLR’s performance converges toward that of the perturbed CNN after 2 weeks. The study finds that introducing stochastic perturbations can address the issue of insufficient spread in these statistical models, with improvements from the nonlinearity varying with the lead time of the forecasts
L'effet des compétences scolaires sur les salaires futurs
No full textCe Focus propose une estimation de l'effet d'une amélioration des compétences scolaires sur les salaires futurs en France. Les politiques éducatives sont essentielles pour renforcer les compétences des élèves et optimiser la performance du système éducatif, contribuant ainsi à la formation du capital humain des générations à venir. En France, l'éducation représente le deuxième poste de dépenses publiques, ce qui renforce la nécessité d'en évaluer précisément l'efficacité. Parmi ces nombreux bénéfices, l'impact sur les revenus futurs des individus est particulièrement déterminant, en raison du lien étroit entre compétences scolaires et insertion professionnelle. Cependant, mesurer cet effet reste complexe, notamment en raison du délai entre la mise en place des politiques éducatives et leurs répercussions sur les trajectoires professionnelles. En exploitant les résultats des évaluations nationales des élèves de 6e de 1995, nous analysons leur influence sur les revenus d'entrée dans la vie active à l'aide de l'équation de Mincer. Cette estimation, peu documentée en France, est pourtant essentielle pour orienter les investissements publics dans l'éducation. Son estimation contribue à calibrer l'indicateur d'efficacité des dépenses publiques (EDP), permettant ainsi d'évaluer l'impact des politiques éducatives sur les revenus futurs des bénéficiaires. Nos résultats montrent qu'une amélioration d'un écart-type des compétences scolaires est associée à une hausse d'environ 10% des salaires futurs, soit un ordre de grandeur comparable à celui observé dans les études internationales. Bien que cette approche présente certaines limites méthodologiques, liées notamment au suivi restreint des trajectoires salariales, elle fournit une première estimation du rendement économique de l'éducation en France
A reversed Monte Carlo radiative transfer model for Titan PCM
No full textInternational audienceTitan and particularly its thick atmosphere, unique among solar system objects, has been a center of interest for many decades. Titan's atmosphere has been thoroughly studied, notably with the use of Global Climate Models (GCM) (Lebonnois et al. 2012; Lora et al. 2015; de Batz de Trenquelléon et al. 2025a; de Batz de Trenquelléon et al. 2025b). All of them currently consider a plane-parallel atmosphere for the radiative transfer calculation (Lora et al. 2015; de Batz de Trenquelléon et al. 2025a). However, this assumption has limitations in the case of Titan
In Search of Working Time? Hours Constraints, Firms and Mobility
No full textCan workers reach their ideal working hours over time? This paper provides novel empirical evidence on hours constraints-barriers for workers to work their desired hours at a given wage rate-by linking self-reported hour preferences from large-scale survey data with administrative employer-employee data between 2003 and 2023. Twenty percent of French salaried workers report wanting to increase their hours at their given wage. Leveraging the panel dimension of my data, I show that constrained workers switch employers more frequently and experience increases in hours and earnings through mobility. However, most constrained workers remain unable to adjust their hours to their desired level within 3 years after their report. Next, I develop a revealed preference method to quantify welfare effects associated with constraints and find that workers would on average accept a 10.2% reduction in hourly wages to work in a job offering their desired number of hours. These findings highlight the important role of hours worked as a job amenity in shaping labor market sorting
Projet Plasti-nium (2021-2025) - Macrodéchets plastiques dans le continuum Terre-Mer
No full textInternational audienc
Diurnal Temperature Variations and Migrating Thermal Tides in the Martian Lower Atmosphere Observed by the Emirates Mars InfraRed Spectrometer
No full textInternational audienceAbstract The Martian atmosphere experiences large diurnal variations due to the ∼24.6 hr planetary rotation and its low heat capacity. Understanding such variations on a planetary scale is limited due to the lack of observations, which are greatly addressed with the recent advent of the Emirates Mars Mission (EMM). As a result of its unique high‐altitude orbit, instruments onboard are capable of obtaining a full geographic and local time coverage of the Martian atmosphere every 9–10 Martian days, approximately ∼5° in solar longitude ( L S ). This enables investigations of the diurnal variation of the current climate on Mars on a planetary scale without significant local time (LT) gaps or confusions from correlated seasonal variations. Here, we present the results of diurnal temperature variations and thermal tides in the Martian atmosphere using temperature profiles retrieved from the Emirates Mars InfraRed Spectrometer (EMIRS) observations. The data during the primary mission is included, covering an entire Martian Year (MY) starting from MY 36 L S = 49°. The diurnal temperature patterns suggest a dominant diurnal tide in most seasons, while the semi‐diurnal tide presents a similar amplitude near the perihelion. The seasonal variation of the diurnal tide latitudinal distribution is well explained by the total vorticity due to zonal wind, while that of the semi‐diurnal tide following both dust and water ice clouds, and the ter‐diurnal tide following only dust. Comparison with the updated Mars Planetary Climate Model (PCM, version 6) suggests improvements in simulating the dust and water cycles, as well as their radiative processes