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Multivariate Functional Data Analysis Uncovers Behavioral Fingerprints in Invertebrate Locomotor Response to Micropollutants
No full textInternational audienceThe need for effective biomonitoring in wastewater has become clear due to the impracticality of continuously tracking all chemicals and emerging contaminants in the aquatic exposome. Effect-based biomonitoring provides a cost-effective solution. The ToxMate device, which uses videotracking of locomotor behavior in aquatic invertebrates, has proven efficient for real-time detection of micropollutant surges in effluents. To extend the approach, this proof-of-concept study evaluates the potential to formalize behavioral fingerprints from real-time videotracking data to characterize qualitative variations in effluent contamination. We present the first application of a functional data analysis (FDA) framework in ecotoxicology. Data were obtained by simultaneously tracking three sentinel organisms from distinct taxa (a crustacean, an annelid, and a gastropod) during pulse exposures to four chemicals in the laboratory (two metals, one pharmaceutical, and one insecticide). Individual and multispecies responses were analy-zed to determine whether combining species enhances the resolution of contamination fingerprints through multidimensional FDA. Applying the same data-driven approach to field data from a wastewater treatment plant (WWTP) revealed four recurring types of micropollution events. This proof of concept demonstrates the potential of behavioral fingerprints to improve wastewater monitoring and reduce pollutant transfer to the environment
Deep reinforcement learning for optimizing control law parameters on a smart beam with distributed piezoelectric transducers
No full textInternational audienceRecent research has focused on the design of adaptive structures with distributed transducers for efficient vibration mitigation. This study explored the optimization of a control strategy to enhance vibration mitigation in structures with multiple piezoelectric transducers. A key challenge lies in tuning control parameters while maintaining stability and robustness against environmental variations. Artificial intelligence, particularly neural networks, offers a promising approach for handling complex multi-input, multi-output control problems. In this work, deep reinforcement learning (DRL) is applied to autonomously tune positive position feedback controllers for a smart beam equipped with three pairs of collocated piezoelectric transducers. The training process prioritizes minimizing vibrations of the third bending mode, which is one of the most dominant. A pole-zero model, derived from experimental measurements, enables numerical learning process while preventing potential damage to the test bench. A comparative analysis is conducted between the DRL strategy and a simplex optimization method, both using the same objective function. A statistical analysis evaluates the reliability and effectiveness of both approaches, highlighting their advantages and limitations in achieving robust control
Bridging the Rossby number gap in rapidly rotating thermal convection
No full textInternational audienceGeophysical and astrophysical fluid flows are typically driven by buoyancy and strongly constrained at large scales by planetary rotation. Rapidly rotating Rayleigh–Bénard convection (RRRBC) provides a paradigm for experiments and direct numerical simulations (DNS) of such flows, but the accessible parameter space remains restricted to moderately fast rotation rates (Ekman numbers ), while realistic for geo- and astrophysical applications are orders of magnitude smaller. On the other hand, previously derived reduced equations of motion describing the leading-order behaviour in the limit of very rapid rotation ( ) cannot capture finite rotation effects, and the physically most relevant part of parameter space with small but finite has remained elusive. Here, we employ the rescaled rapidly rotating incompressible Navier–Stokes equations (RRRiNSE) – a reformulation of the Navier–Stokes–Boussinesq equations informed by the scalings valid for , recently introduced by Julien et al. (2024) – to provide full DNS of RRRBC at unprecedented rotation strengths down to and below, revealing the disappearance of cyclone–anticyclone asymmetry at previously unattainable Ekman numbers ( ). We also identify an overshoot in the heat transport as is varied at fixed , where is the Rayleigh number, associated with dissipation due to ageostrophic motions in the boundary layers. The simulations validate theoretical predictions based on thermal boundary layer theory for RRRBC and show that the solutions of RRRiNSE agree with the reduced equations at very small . These results represent a first foray into the vast, largely unexplored parameter space of very rapidly rotating convection rendered accessible by RRRiNSE
Simulation de la propagation acoustique par méthode WAPE pour le calcul des espaces actifs et de détection, application au suivi d'oiseaux de montagne
No full textBioacoustique et acoustique environnementale; GABE - Acoustique du Bâtiment et de l'Environnement: GBIO - BioacoustiqueNational audienceDans les environnements où la topographie ou les effets météorologiques influencent fortement la propagation acoustique, la détermination des espaces actifs et des espaces de détection n'est pas triviale. Un effort de modélisation de la propagation acoustique peut alors apporter des informations utiles pour comprendre l'influence du milieu sur les réseaux de communication, interpréter des données de terrain issues d'enregistrements sonores ou concevoir un réseau d'enregistreurs autonomes. Nous présenterons un modèle numérique de la propagation basé sur la résolution d'une équation parabolique grand angle (WAPE) pour le calcul de l'espace actif, puis de l'espace de détection en appliquant le principe de réciprocité. L'application au cas du suivi acoustique en milieu montagneux d'une population de lagopèdes alpins sera détaillée et discutée en référence à des données de terrain (topographie, météorologie, bruit de fond, enregistrements sonores, analyse de l'activité vocale)
Semi-analytical calculation of excess hysteresis losses in ferromagnetic laminates
No full textInternational audienceThe harmonic balance method is combined with a modal solver for the treatment of the hysteresis loss problem. To properly address the excess losses contribution, an supplementary term involving a fractional derivative operator is introduced in the classical formalism. The theoretical results will be compared with experimental data obtained for a nano-crystalline material.</div
Résonateur annulaire SiGe-sur-Si à facteur Q d'un million dans l'infrarouge moyen
No full textInternational audienceWe report Silicon Germanium (SiGe) Ring Resonators with quality factors reaching up to one million in the Mid-Infrared (MIR) wavelength range between 3.5 - 4.6 μm
Whole-cell aptamer-based techniques for rapid bacterial detection: Alternatives to traditional methods
No full textInternational audienceControlling the spread of bacterial infectious diseases is a major public health issue, particularly in view of the pandemic of bacterial resistance to antibiotics. In this context, the detection and identification of pathogenic bacteria is a prerequisite for the implementation of control measures. Current reference methods are mainly based on culture methods, which generate a delay in obtaining a result and requires equipment. Consequently, focusing on the detection of the whole bacterium represents a very attractive alternative, since no culture is required. Several techniques have already been deployed to identify whole-cell bacteria. In recent decades, growing interest in nucleic acid aptamers has emerged as a viable alternative to antibodies as recognition elements, offering preferable stability, cost-efficiency, good specificity and affinity. This review explores current alternative methods for the detection of whole-cell bacteria, with particular emphasis on aptamer-based assays. These assays have shown promising results in various transduction mechanisms, including optical, electrochemical, and mechanical approaches, enhancing their versatility in different diagnostic platforms. The integration of aptamers in these detection methods offers rapid, sensitive, versatile and portable solutions for pathogen identification, positioning them as valuable tools in the fight against bacterial infections
The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography
No full textInternational audienceSurface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a ``rough'' and a ``smooth'' surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking
SCALING RELATIONS FOR THE CLG'S CRITICAL EXPONENTS
No full textWe consider, in any dimension, the constrained lattice gas introduced by Rossi et al., which is an exclusion process on a d-dimensional lattice following the additional constraint that only particles with at least one occupied neighbour can jump. In dimension d=2, this model features self-organized criticality at some critical density of particles. Numerical simulations predict the existence of scaling exponents close to criticality, and several relations can be derived between these exponents. The goal of this article is to give a mathematical framework for these relations, which have been numerically established in a companion article
Velocity Trapping in the Lifted Totally Asymmetric Simple Exclusion Process and the True Self-Avoiding Random Walk
No full textInternational audienceWe discuss nonreversible Markov-chain Monte Carlo algorithms that, for particle systems, rigorously sample the positional Boltzmann distribution and that have faster than physical dynamics. These algorithms all feature a nonthermal velocity distribution. They are exemplified by the lifted totally asymmetric simple exclusion process (lifted TASEP), a one-dimensional lattice reduction of event-chain Monte Carlo. We analyze its dynamics in terms of a velocity trapping that arises from correlations between the local density and the particle velocities. This allows us to formulate a conjecture for its out-of-equilibrium mixing timescale, and to rationalize its equilibrium superdiffusive timescale. Both scales are faster than for the (unlifted) TASEP. They are further justified by our analysis of the lifted TASEP in terms of many-particle realizations of true self-avoiding random walks. We discuss velocity trapping beyond the case of one-dimensional lattice models and in more than one physical dimensions. Possible applications beyond physics are pointed out