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La transmission des traces mémorielles dans un parcours muséographique. Le cas des procès du personnel du camp de Royallieu
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Identifying Retailscape Transformations: A Methodological Framework for Spatiotemporal Analysis in Urban Environment
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The Cyano group as a polarity switch: Enhancing dielectric anisotropy in hydrogen-bonded nOBAF:CNPy complexes
No full textInternational audienceThis study reports the preparation and characterization of a novel series of hydrogen-bonded liquid crystals formed between 4-cyanopyridine (acceptor) and 4-alkyloxy-2-fluorobenzoic acids (donor, alkyl chain length n = 9–14). The formation of the supramolecular O–H⋯N complex was unequivocally verified by FTIR spectroscopy. Thermal and mesomorphic investigations, conducted via DSC and POM, revealed that all complexes exhibit enantiotropic nematic and smectic G phases. The phase behavior was strongly dependent on the alkyl chain length; longer chains favored the SmG phase, while shorter chains stabilized the nematic phase over a wider range, as detailed in a constructed phase diagram. Crucially, dielectric properties measured in aligned cells showed a remarkable enhancement in dielectric anisotropy, with values exceeding Δε = 4.0 compared to Δε ≈ 0.6 for the pure acid. This dramatic increase is a direct result of the supramolecular structure, which aligns the strong molecular dipole of the cyano group along the director axis. These findings underscore the potential of hydrogen bonding for creating functional materials with tailored properties for electro-optic applications.Cette étude rend compte de la préparation et de la caractérisation d'une nouvelle série de cristaux liquides à liaison hydrogène formés entre la 4-cyanopyridine (accepteur) et les acides 4-alkyloxy-2-fluorobenzoïques (donneur, longueur de chaîne alkyle n = 9-14). La formation du complexe supramoléculaire O–H⋯N a été clairement vérifiée par spectroscopie FTIR. Des analyses thermiques et mésomorphiques, réalisées par DSC et POM, ont révélé que tous les complexes présentent des phases nématiques et smectiques G énantiotropiques. Le comportement de phase dépendait fortement de la longueur de la chaîne alkyle ; les chaînes plus longues favorisaient la phase SmG, tandis que les chaînes plus courtes stabilisaient la phase nématique sur une plage plus large, comme le montre le diagramme de phase construit. Il est important de noter que les propriétés diélectriques mesurées dans des cellules alignées ont montré une amélioration remarquable de l'anisotropie diélectrique, avec des valeurs dépassant Δε = 4,0 par rapport à Δε ≈ 0,6 pour l'acide pur. Cette augmentation spectaculaire est le résultat direct de la structure supramoléculaire, qui aligne le dipôle moléculaire fort du groupe cyano le long de l'axe directeur. Ces résultats soulignent le potentiel des liaisons hydrogène pour créer des matériaux fonctionnels aux propriétés adaptées aux applications électro-optiques
Comparison of different strategies based on β-casein dynamics to encapsulate curcumin in casein micelles
No full textInternational audienceCasein micelles (CM) are colloidal phospho-protein-mineral complexes naturally present in milk. Cooling inducesβ-casein dissociation from CM. The aim of the present research is to improve curcumin encapsulation in β-casein depleted CM. This study proposes an extraction and separation process including cooling, low acidification (pH 5.8) and membrane filtration at a pilot scale allowing a removal of 45 ±5 % of β-casein fraction from CM.Special care was taken to preserve the CM integrity. Investigation of the depleted CM topography by atomic force microscopy (AFM) reveals a swelling of the micellar structure with a mean width of 193 ±10 nm and a mean height of 80 ±5 nm. Concurrently, exploration of the elastic properties displays a stiffer nanomechanicalsignature compared to native CM, with a mean elasticity modulus of 195 ±17 kPa. The β-caseins extracted from CM were bound to curcumin prior to their encapsulation in depleted CM. This new encapsulation strategy was compared to two other methods, and the results show that it significantly increases the binding efficiency of curcumin to CM
Enhancing airline multimarket competition analysis with a pairwise competitive intensity index based on weighted Jaccard index
No full textInternational audienceWe advance the measurement of multimarket contact (MMC) in the airline competition literature by introducing a flight frequency weighted Jaccard index. Unlike conventional MMC measures that rely on binary market presence, our proposed index captures both market overlap and supply strategic similarity through flight frequency. Current airline competition research can be divided into market-based metrics (e.g., HHI, CR), which overlook relationships among firms, and airline-based metrics, of which MMC is the most prominent but only considers market overlap. Our index bridges this gap and describes the pairwise competitive intensity among airlines within a specific geographic region. We interpret the use of the index through three applications: unsupervised clustering of airline business models, detection of market shocks, and tracking changes in competitive relationships during disruptions. Our work will allow researchers to refine previous MMC related studies. This work provides policymakers with tools to monitor real-time market competition and may better inform competition regulation design. For airlines, they can leverage the index to identify rivals with the same or different business models, measure their competitive intensity, and choose their competition strategy accordingly
Interval Estimation for Linear Switched Systems Using Observer and Zonotopic Analysis
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Filtering and machine learning on Riemannian manifolds and Lie groups
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Dragani, A., 2026, "La clochardisation des étudiants touaregs francophones en Mauritanie. Entre exclusion linguistique, déclassement et logement précaire", in S. Corlean (éd.), Mobilité et migration dans l'espace francophone, Éditions de l'Université de Bucarest (in print)
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Regime-aware time weighting for physics-informed neural networks
No full textInternational audienceWe introduce a novel method to handle the time dimension when Physics-Informed Neural Networks (PINN) are used to solve time-dependent differential equations; our proposal focuses on how time sampling and weighting strategies affect solution quality. While previous methods proposed heuristic time-weighting schemes, our approach is grounded in theoretical insights derived from the Lyapunov exponents, which quantify the sensitivity of solutions to perturbations over time. This principled methodology automatically adjusts weights based on the stability regime of the system — whether chaotic, periodic, or stable. Numerical experiments on challenging benchmarks, including the chaotic Lorenz system and the Burgers’ equation, demonstrate the effectiveness and robustness of the proposed method. Compared to existing techniques, our approach offers improved convergence and accuracy without requiring additional hyperparameter tuning. The findings underline the importance of incorporating causality and dynamical system behavior into PINN training strategies, providing a robust framework for solving time-dependent problems with enhanced reliability
