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Christian Grataloup Vincent Lemire, 2025, Atlas historique du Moyen-Orient, Paris, L’histoire - Éditions les Arènes, 189 p.
No full textInternational audienceCompte-rendu de l'atlas historique du Moyen-Orient de Christian Grataloup et Vincent Lemire, mis en perspective avec l'atlas éponyme paru en 2020 par Florian Louis
Statistical learning on measures: an application to persistence diagrams
No full textInternational audienceWe consider a binary supervised learning classification problem where instead of having data in a finite-dimensional Euclidean space, we observe measures on a compact space . Formally, we observe data where is a measure on and is a label in . Given a set of base-classifiers on , we build corresponding classifiers in the space of measures. We provide upper and lower bounds on the Rademacher complexity of this new class of classifiers that can be expressed simply in terms of corresponding quantities for the class . If the measures are uniform over a finite set, this classification task boils down to a multi-instance learning problem. However, our approach allows more flexibility and diversity in the input data we can deal with. While such a framework has many possible applications, this work strongly emphasizes on classifying data via topological descriptors called persistence diagrams. These objects are discrete measures on , where the coordinates of each point correspond to the range of scales at which a topological feature exists. We will present several classifiers on measures and show how they can heuristically and theoretically enable a good classification performance in various settings in the case of persistence diagrams
Study of the Effects of Waves on the Evolution of Scour Under a Tidal Turbine by Two-Phase Numerical Modeling
No full textInternational audienceTidal turbines have emerged as a promising alternative to fossil-fuel-based energy generation, with estuarine environments identified as potential sites for their deployment. However, estuaries are sensitive ecosystems, and understanding the impacts of turbine installation on local hydrodynamics and sediment transport is critical. While previous studies have shown the influence of turbines on seabed morphology under steady current conditions, the effects of combined wave–current loading remain insufficiently explored. In this study, we present a novel numerical modeling framework to predict seabed evolution in the vicinity of tidal turbines subjected to wave–current interactions. The approach integrates Blade Element Theory (BET) to represent turbine-induced forces, an Euler–Euler multiphase model for sediment transport, and the first-order wave theory to capture wave dynamics, all implemented within the OpenFOAM-based solver. Wave effects are incorporated as source terms in the momentum equations, and wave velocities are added to the current field at the velocity inlet boundary condition. Results demonstrate that wave–current loading induces oscillatory sediment transport, but net scouring remains significant in the vicinity of the turbine. The proposed framework is validated component-wise (wave forcing and rotor loading) and then demonstrated on mobile-bed simulations to quantify how oscillatory wave–current forcing modifies near-bed transport and early-stage scour development around a tidal turbine. While the present simulations focus on short morphodynamic times, the approach provides a physics-based basis for exploring wave effects on turbine-induced sediment dynamics
Enantiopurity‐Dependent Peptide Coacervates and Asymmetric Organocatalysis
No full textInternational audienceABSTRACT Membraneless compartmentalization via liquid–liquid phase separation (LLPS) has emerged as a powerful strategy to organize biochemical reactions. Recently, peptide‐based coacervates demonstrated the potential to function as microreactors by enhancing reaction kinetics through increased local concentrations and altered microenvironments. Here, we introduce an O‐methylated diphenylalanine‐based tripeptide LLL PFF‐OCH 3 containing an N‐terminal proline, designed to undergo LLPS, and simultaneously function as an enantioselective organocatalyst. Comprehensive characterization via confocal microscopy, fluorescence recovery after photobleaching (FRAP), micro‐Raman and attenuated total reflection infrared (ATR‐IR) spectroscopy, diffusion‐surface plasmon resonance ( D ‐SPR), and molecular dynamics (MD) simulations revealed the formation of stable liquid droplets. In contrast, a racemic mixture of LLL PFF‐OCH 3 and DDD PFF‐OCH 3 failed to form liquid droplets and instead formed a solid precipitate, unveiling a critical role of enantiopurity in LLPS. Proof‐of‐concept catalytic studies proved enantioselective organocatalytic activity of the LLL PFF‐OCH 3 liquid coacervates. Beyond catalysis these results may have broader implications in understanding prebiotic chemistry and neurodegeneration
Network-Realised Model Predictive Control Part I: NRF-Enabled Closed-loop Decomposition
No full textInternational audienceA two-layer control architecture is proposed to enable scalable implementations for constraint-based decision strategies, such as model predictive controllers. The bottom layer is based upon a distributed feedback-feedforward scheme that directs the controlled network's information flow according to a pre-specified communication infrastructure. Explicit expressions for the resulting closed-loop maps are obtained, and an offline model-matching procedure is proposed for designing the first layer. The obtained control laws are deployed via distributed state-space-based implementations, and the resulting closed-loop models enable predictive control design for the constraint management procedure described in our companion paper
Water Isotope Model Intercomparison Project (WisoMIP): Present‐Day Climate
No full textInternational audienceAbstract We present the first results of the Water Isotope Model Intercomparison Project (WisoMIP), with Phase 1 focused on modern simulations (1979–2023) from a suite of isotope‐enabled atmospheric general circulation models nudged to ERA5 reanalyzes. Water sources, mixing, and rainout history influence the isotopic composition of vapor and precipitation, making these simulations powerful tools for tracing the global water cycle. By prescribing identical winds, sea surface temperatures, and sea ice conditions, we isolate differences in water isotope behavior across models, controlling for variability in atmospheric dynamics and mean climate. Our analyses show that the ensemble mean best matches observations, as individual model errors cancel out to yield a more accurate representation of Earth's isotope distributions. We also evaluate trends and responses to major climate modes during the recent warming period, highlighting regional and temporal sensitivities in the isotope signals. These diagnostics extend beyond traditional model evaluation metrics (e.g., temperature, precipitation) to reveal uncertainties in physical processes and guide improvements in model parameterizations. The resulting modern nudged ensemble data set serves as a benchmark for isotope‐enabled model development, satellite product comparison, and understanding of water cycle changes in a warming climate. Given its standardized design and broad participation, WisoMIP provides a valuable “isotope reanalysis” product for applications ranging from paleoclimate reconstruction to model tuning. Our work demonstrates the importance of coordinated isotope model evaluation in advancing the use of water isotopes as a diagnostic tool in climate science
In-core Gamma and Neutron Irradiation of Optical Materials used in the Design of an Optical Sensor for Pressurized Water Research Reactor
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Microbial computing: Review and Perspectives
No full textInternational audienceEngineering microbial computers has been a longstanding endeavor in synthetic biology. Like other unconventional computing disciplines, the goal is to bring computation into real-world scenarios. Several potential applications in bioproduction, bioremediation, and biomedicine highlight the promise of this discipline. The first biocomputers were bottom-up predictable circuits that relied on a monoculture-based digital logic and were able to emulate simple logic gates. Drawing from computer theory and extending the analogy with conventional hardware has enabled the engineering of more complex circuits. However, this abstraction soon reached its limits and introduced a semantic gap, which, alongside the constraints imposed by the monoculture paradigm, led to significant scalability limitations such as metabolic burden, orthogonality issues and noisy expression. This review outlines the strategies developed to overcome these issues and engineer more complex biodevices: (i) mitigation strategies that focus on the optimization of the circuits, (ii) multicellular computing that distributes the metabolic load across a consortium and (iii) the implementation of more energy-efficient computing frameworks, such as analog and neuromorphic architectures. While these bottom-up strategies have yielded significant progress, they remain insufficient to emulate the computational complexity of the cellular signal-processing system. In this review, we additionally introduce a new perspective on biocomputing with a top-down approach named reservoir computing. This framework leverages the inherent dynamical computational capabilities and functionalities of biosystems to solve more complex and diverse tasks, thus offering a promising new path for engineering the next generation of microbial computers
Profiling Protein-Binding Glycosaminoglycan Oligosaccharides Using a Simple Label-Free Electrophoretic Assay
No full textInternational audienceGlycosaminoglycans (GAGs) interact with numerous proteins to regulate key biological processes such as coagulation, cell migration, and growth factor signaling. Despite their biological importance, mapping these interactions and identifying the structural determinants that govern GAG–protein recognition remains analytically challenging, particularly in complex or polydisperse systems. Here, we introduce a simple, label-free carbohydrate polyacrylamide gel electrophoresis (C-PAGE) approach that visualizes GAG–protein complex formation through binding-induced signal suppression of GAG bands. Instead of tracking the mobility of protein–GAG complexes, as it is classically performed in gel-shift assays, C-PAGE directly monitors the disappearance of the free GAG bands stained with Stains-All. Using model high-affinity heparin-binding proteins, the chemokine stromal cell-derived factor 1 α (SDF-1α) and the basic fibroblast growth factor (FGF-2), we demonstrate that C-PAGE clearly distinguishes specific interactions with heparin oligosaccharides from non-binding controls. The method was successfully extended to a micromolar-affinity heparin-binding protein, the interleukin 8 (IL-8), and to complex mixtures such as low-molecular-weight heparins (LMWH), revealing the preferential disappearance of highly sulfated and/or longer GAG species. Competitive assays further enabled qualitative ranking of GAG binding affinities. Finally, the selective interaction of antithrombin III with 3-O-sulfated motifs was unambiguously detected, underscoring the remarkable sensitivity of C-PAGE to fine structural modifications. Altogether, C-PAGE provides a rapid, visual, and cost-effective screening tool to assess GAG–protein binding specificity and structure–activity relationships, complementing advanced biophysical and structural methods in fundamental and applied glycobiology