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International audience; Herbicide impact is usually assessed as the result of a unilinear mode of action on a specific biochemical target with a typical dose-response dynamics. Recent developments in plant molecular signaling and crosstalk between nutritional, hormonal and environmental stress cues are however revealing a more complex picture of inclusive toxicity. Herbicides induce large-scale metabolic and gene-expression effects that go far beyond the expected consequences of unilinear herbicide-target-damage mechanisms. Moreover, groundbreaking studies have revealed that herbicide action and responses strongly interact with hormone signaling pathways, with numerous regulatory protein-kinases and -phosphatases, with metabolic and circadian clock regulators and with oxidative stress signaling pathways. These interactions are likely to result in mechanisms of adjustment that can determine the level of sensitivity or tolerance to a given herbicide or to a mixture of herbicides depending on the environmental and developmental status of the plant. Such regulations can be described as rheostatic and their importance is discussed in relation with herbicide use strategies, environmental risk assessment and global change assessment challenges. (C) 2016 Elsevier B.V. All rights reserved.

Porous media used in soundproofing systems can be modeled as a set of cylindrical per- forations. Starting from the classical expression of the acoustic impedance of cylindrical tubes which is proportional to a ratio of Bessel functions, this paper briefly presents the derivation of an equivalent expression depending only on the positive zeros of J 2 , the Bessel function of the first kind of order 2. In the frequency domain, such a derivation is of great prac- tical interest because it replaces the costly evaluation of transcendental functions by that of rational ones. In the time domain, the impulse response of the cylin- drical tube reduces to a Prony series of which only 10 terms prove sufficient to reliably describe it, for any values of physical parameters within the acous- tic model assumptions. The method applied in this use case from acoustics was primarily employed by Giusti and Mainardi (Meccanica 51(10): 2321–2330, 2016) in their study of pulse propagation within blood vessels and by Colombaro et al. (Meccanica 52(4–5):825–832, 2017) in their work on the Bessel models of linear viscoelasticity.

International audience; We propose an innovative approach to minimize the greenhouse gas impacts of additive manufactured structures over their entire life cycle. The novelty of our method lies in its simultaneous optimization of material selection, process selection, and design optimization. To fully leverage the potential benefits of additive manufacturing, we use topology optimization and compile a comprehensive database of printed materials and printing processes, which we share with the wider community. To account for the complex interdependence between materials and processes, our method employs a pairing system, which we efficiently reduce using topology optimization properties and a generalized form of Ashby indices. To enhance computational efficiency, we employ a meta-model. We validate our proposed method through successful testing on an aeronautical case and a pedestrian bridge, demonstrating its robustness even in the presence of environmental data uncertainty. The optimal material-process pair for the aeronautical structure is the cobalt-based super-alloy with the LENS process. Despite this pair having the highest material and processing emissions, the resulting lighter part lowers the use phase emissions. It appears that precise mechanical data is needed for the method to give accurate results: a 20% drop of Young's modulus totally disrupts the material-process pair ranking.

The decoration of carbon nanotubes (CNTs) by metal nanoparticles (NPs) combines the advantages of a high specific surface material with catalytic properties of metal nanocrystals. Little work has been devoted to the decoration of CNTs with copper NPs, and no evidence of copper atomic decoration of CNTs has shown up until now. Herein, we demonstrate that the strong acidic oxidation of double-walled CNTs (dwCNTs) is very efficient for the decoration of the carbon surface by copper NPs and atoms. This treatment severely degraded the CNT walls and generated a large amount of disordered sp3 carbon. This amorphous carbon film bears many chemically active functions like carboxyl and hydroxyl ones. In such conditions, the CNT walls behave as very efficient ligands for the stabilization of copper obtained by the thermolysis of the mesityl precursor in organic solution under mild dihydrogen pressure. In addition to copper NPs, we evidenced the presence of a regular coverage with copper atoms over the dwCNTs. This nanocomposite catalyzes the quantitative synthesis of propargylamines via one A3-type coupling reaction. Five consecutive catalytic cycles with 100% yield could be performed with no loss of activity, and the combination of Cu supported on dwCNTs allows a facile recycling of the catalytic material.

International audience; Obsolescence is the fact that an entity (physical or logical) is becoming outdated or no longer possesses the required level of performance. The objectives of this article are twofold. First, it is intended to contribute to the understanding of obsolescence propagation. Secondly, two supporting approaches for the Identification and Assessment phases are proposed: the House of Obsolescence and the System Obsolescence Criticality Analysis. The former allows the mapping of obsolescence propagation via dependencies, whether imposed changes are desired or imposed, by external actors to the system architecture. Whereas, the objective of the latter is to assign an obsolescence criticality index to the identified risks in order to prioritize them for solution or mitigation determination during the analysis phase. The tools make extensive use of the modeled system knowledge through the application of Systems Engineering. The application of these approaches is presented through an illustrative study.

International audience; The synthesis and characterization of cobalt(II) (3, 4) and acetato cobalt(III) (5) complexes with two tripodal tetradentate diamino-bis(phenolate) ligands (L1 and L2) are reported. The solid-state structures of proligand H2L1 and complexes 4 and 5 were determined by X-ray crystallography. Complex 4 crystallizes as a dimer via the formation of a Co2O2 core. Complex 5 is monomeric with a six-coordinated cobalt(III) center bearing a chelating acetate ligand. In both structures, the diamino-bis(phenolate) ligand (L1 or L2) is acting as a tetradentate dianionic κ4-(O2,N2) chelating ligand. The diamagnetic nature of complex 5 allowed its characterization by multinuclear NMR spectroscopic techniques. Complex 5 is not a competent unimolecular initiator for the radical polymerization of methyl acrylate or methyl methacrylate. Its cobalt(II) analog (3) did not act as an efficient OMRP moderator for the radical polymerization of activated (styrene, tert-butyl acrylate) and non-activated (vinyl acetate) monomers.

Earth observation through satellite images is crucial to help economic activities as well as to monitor the impact of human activities on ecosystems. Current satellite systems are subjected to strong computational complexity constraints. Thus, image compression is perfomed onboard with specifically tailored algorithms while image denoising is performed on the ground. In this letter, we intend to address satellite image compression and denoising with neural networks. The first proposed approach uses a single neural architecture for joint onboard compression and denoising. The second proposed approach sequentially uses a first neural architecture for onboard compression and a second one for on ground denoising. For both approaches, the onboard architectures are lightened as much as possible, following the procedure proposed in [1]. The two approaches are shown to outperform the current satellite imaging system and their respective pros and cons are discussed.

International audience; Nowadays, drones can be developed for a wide range of use cases, from infrastructure monitoring to sea rescue, urban mobility or military purposes. Which drone design is best suited for a specific mission? To answer this question, we need to solve a constrained optimization problem based on a multidisciplinary design model that takes the mission into account. The model generally being a computationally expensive numerical model whose gradients are not available all the time encourages us to consider a Bayesian optimization approach. Such strategy is well known to achieve a trade-off between exploitation and exploration in order to find interesting minimal area with a reduced number of function evaluations. A multi-fidelity approach can improve even more the computational efficiency of the Bayesian optimization strategy. In this work, we aim at designing a fixed-wing drone (fully electric) for long range surveillance mission. Two fidelity level electric drone models are developed. For a given mission requirement, the final battery state of charge is optimized with respect to drone design variables. Optimizations are performed on several missions using both a mono and a multi-fidelity Bayesian optimization strategy. The interest of using a multi-fidelity method for overall drone design has been assessed. The multi-fidelity super-efficient global optimization algorithm (MFSEGO) appeared to need less budget to reach convergence than the mono-fidelity algorithm and to be more robust to the initial design of experiments.

International audience; Graph Neural Networks have been applied to learn the flight and structural dynamics of an High Altitude Long Endurance aircraft in discrete gust. The graph network methodology allows building a model for structural displacements, loads and aircraft flight dynamics leveraging on the inductive bias given by the physical connections. The results show promising capabilities in model approximation and potential for symbolic identification of aerodynamics and structural forces.

It is unclear how gene order within the chromosome influences genome evolution. Bacteria cluster transcription and translation genes close to the replication origin (oriC). In Vibrio cholerae, relocation of s10-spc-α locus (S10), the major locus of ribosomal protein genes, to ectopic genomic positions shows that its relative distance to the oriC correlates to a reduction in growth rate, fitness, and infectivity. To test the long-term impact of this trait, we evolved 12 populations of V. cholerae strains bearing S10 at an oriC-proximal or an oriC-distal location for 1,000 generations. During the first 250 generations, positive selection was the main force driving mutation. After 1,000 generations, we observed more nonadaptative mutations and hypermutator genotypes. Populations fixed inactivating mutations at many genes linked to virulence: flagellum, chemotaxis, biofilm, and quorum sensing. Throughout the experiment, all populations increased their growth rates. However, those bearing S10 close to oriC remained the fittest, indicating that suppressor mutations cannot compensate for the genomic position of the main ribosomal protein locus. Selection and sequencing of the fastest-growing clones allowed us to characterize mutations inactivating, among other sites, flagellum master regulators. Reintroduction of these mutations into the wild-type context led to a ≈10% growth improvement. In conclusion, the genomic location of ribosomal protein genes conditions the evolutionary trajectory of V. cholerae. While genomic content is highly plastic in prokaryotes, gene order is an underestimated factor that conditions cellular physiology and evolution. A lack of suppression enables artificial gene relocation as a tool for genetic circuit reprogramming. Centre National de la Recherche Scientifique de Francia-UMR3525 French National Research Agency-ANR-10-BLAN593 131301y ANR-14-CE10-0007 International Centre for Genetic Engineering and Biotechnology (ICGEB)-CRP/ARG18-06_EC ECOS-SUD France-Argentina Program-18ST06 Gobierno francés-ANR-10-LABX-62-IBEID Agencia Nacional de Promoción de la Investigación, Desarrollo Tecnológico y la Innovación de Argentina-PICT-2017-0424, PICT-2020-0521 y PICT-2018-0476

International audience; It is sometimes desirable to delve further into how the inputs affect the output in design optimization and uncertainty analysis. Surrogate models such as Gaussian Process Regression and support vector regression are useful for such tasks and can be further enhanced by introducing advanced post-processing methods. This paper investigates Shapley Additive Explanation (SHAP) as a tool to aid surrogate-assisted data-driven analysis. In particular, surrogate-enabled SHAP analysis allows visualization of the input-output relationship in a meaningful way using summary SHAP plots and SHAP dependence plots. Some importantinformation that can be extracted and visualized from SHAP includes the importance of input variables (i.e., global sensitivity analysis), nonlinearity level, and level of interactions. The benefits of Shapley values for engineering analysis using surrogate models are demonstrated in three engineering test problems.

International audience; Many engineering problems are governed by complex governing equations that are difficult and typically require high computational costs to solve. Machine learning and surrogate modelling aid such an endeavour by providing a cheap-to-evaluate prediction model that acts as a replacement of the original model. While most research focuses on predicting scalar values (e.g., lift and drag), predicting the solution field is also of interest in many practical engineering and scientific applications. This paper proposes a Physics-Informed Proper Orthogonal Decomposition (POD) technique that improves the solution field prediction by enforcing governing equations as a loss penalty. The proposed idea utilizes a reduced-order modeling technique based on POD to decompose solution snapshots into singular vectors and values. A Gaussian Process Regression is then utilized to predict the singular values from variable parameters. The predicted singular values from the data of the problem are then adjusted via optimization to minimize the physics-informed loss and achieve better prediction. In this paper, we illustrate the efficacy of the proposed method on simple two-dimensional partial differential equations. The result clearly shows that the proposed physics-informed POD outperforms the conventional POD in terms of approximation error.

International audience; With the increasing availability of data for Prognostics and Health Management (PHM), Deep Learning (DL) techniques are now the subject of considerable attention for this application, often achieving more accurate Remaining Useful Life (RUL) predictions. However, one of the major challenges for DL techniques resides in the difficulty of obtaininglarge amounts of labelled data on industrial systems. To overcome this lack of labelled data, an emerging learning technique is considered in our work: Self-Supervised Learning, a sub-category of unsupervised learning approaches. This paper aims to investigate whether pre-training DL models in a self-supervised way on unlabelled sensors data can be useful for RUL estimation with only Few-Shots Learning, i.e. with scarce labelled data. In this research, a fatigue damage prognostics problem is addressed, through the estimation of the RUL of aluminum alloy panels (typical of aerospace structures) subject to fatigue cracks from strain gauge data. Synthetic datasets composed of strain data are used allowing to extensively investigate the influence of the dataset size on the predictive performance. Results show that the self-supervised pre-trained models are able to significantly outperform the non-pre-trained models in downstream RUL prediction task, and with less computational expense, showing promising results in prognostic tasks when only limited labelled data is available.

International audience; Bell's inequality violation experiments are becoming increasingly popular in the practical teaching of undergraduate and master's degree students. Bell's parameter S is obtained from 16 polarization correlation measurements performed on entangled photons pairs. We first report here a detailed analysis of the uncertainty u(S) of Bell's parameter taking into account coincidence count statistics and errors in polarizers' orientation. We show using both computational modeling and experimental measurement that the actual sequence of the polarizer settings has an unexpected and strong influence on the error budget. This result may also be relevant to measurements in other settings in which errors in parameters may have non-random effects in the measurement.

The anisotropic and heterogeneous N -dimensional wave equation, controlled and observed at the boundary, is considered as a port-Hamiltonian system. A recent structure-preserving mixed Galerkin method is applied, leading directly to a finite-dimensional port-Hamiltonian system: its numerical analysis is carried out in a general framework. Optimal choices of mixed finite elements are then proved to reach the best trade-off between the convergence rate and the number of degrees of freedom for the state error. Exta compatibility conditions are identified for the Hamiltonian error to be twice that of the state error, and numerical evidence is provided that some combinations of finite element families meet these conditions. Numerical simulations are performed in 2D to illustrate the main theorems among several choices of classical finite element families. Several test cases are provided, including non-convex domain, anisotropic or heterogeneous cases and absorbing boundary conditions.

International audience; The development of the aeronautical industry has brought about certain demands like the reduction of fuel consumption and, consequently, the weight of used structures. Therefore, topology analysis of aircraft components has played an important role in meeting these demands. Another factor widely studied in this context is the type of materials used in the manufacture of such components, hence, by presenting lower densities, composites have gained ground in this industry sector.Besides, an increasingly sought-after characteristic is the sustainability associated with the entire life cycle of any system or part, from its design, through the production phase, to its end of life. The assessment of such sustainability is often carried out by analysing the life cycle’s CO2 footprint, which tends to decrease when the raw materials used are less processed. Materials of natural origin, also known as "bio-materials", have therefore been the target of study, being the basis of the concept of eco-design. The accelerated development of 3D printing technologies has allowed the evolution of structural design methods. Additive manufacturing emerged in the 1980s and has since been expanding in the aerospace field. One of its great advantages is that it can be combined with the use of bio-composites, such as flax or hemp.The topology optimisation of any given structure brings great benefits in terms of the mitigation of the CO2 impact of a given part, as it translates into a reduction of its mass and fuel consumption. However, the combination of this method with the optimisation of the fibre path, in the 3D printing process, and the CO2 footprint of the part’s life cycle simultaneously can bring even more evident benefits. In this paper modifications to existing methods are proposed. In MATLAB, strategies are developed to study the topology and fibre orientation of potentially 3D printed thin structures.

International audience; The paper presents the results of dynamic crushing of sandwich tubes that had skins made of carbon or glass fibres-with epoxy resin-and an I214 poplar ply core. By increasing the number of poplar plies from two to six, the absorbed energy is doubled, showing the significant contribution of the wood. The Specific Energy Absorption of sandwiches with carbon fibre skins oscillated between 49.4 and 60 J/g while that with glass fibre skins varied from 35.4 to 43.3 J/g.

Sunflower oil hydrogenation was carried out in a 2 mm diameter jacketed capillary reactor coated with a Pd/Al2O3 catalyst, mimicking a channel of a heat exchanger monolith reactor. The operating conditions were chosen to ensure Taylor flow conditions and to evaluate their impact on the reaction selectivity. CFD simulations of the experiments were performed using the unit cell approach. They accounted for the dependence of viscosity on the degree of oil saturation, kinetic laws describing the effects of pressure on cis/trans selectivity, and bubble shrinkage along the channel using a moving mesh strategy. The model captured the experimental trends, in which the fraction of monounsaturated cis fatty acids did not exceed 35% (vs 30% originally). Poor selectivity is mainly due to the strong mass transfer resistance at the catalyst wall, either from fatty acids (favoring their complete saturation) and/or from hydrogen (due to bubble shrinkage, favoring cis to trans isomerization)

This work proposes a marginalised particle filter with variational inference for non‐linear state‐space models (SSMs) with Gaussian mixture noise. A latent variable indicating the component of the Gaussian mixture considered at each time instant is introduced to specify the measurement mode of the SSM. The resulting joint posterior distribution of the state vector, the mode variable and the parameters of the Gaussian mixture noise is marginalised with respect to the noise variables. The marginalised posterior distribution of the state and mode is then approximated by using an appropriate marginalised particle filter. The noise parameters conditionally on each particle system of the state and mode variable are finally updated by using variational Bayesian inference. A simulation study is conducted to compare the proposed method with state‐of‐the‐art approaches in the context of positioning in urban canyons using global navigation satellite systems.

The modeling of the fluidization or sedimentation velocity of a suspension of solid particles is revisited by examining experiments conducted in either a liquid or a gas. A general expression is found in the case of negligible fluid inertia, i.e. at low Reynolds or Archimedes number. It is built as the product of the velocity of an isolated particle by three non-dimensional corrections that each takes into account a specific physical mechanism. The first correction reflects the variation of the buoyancy with the particle concentration. The second correction describes how the drag force increases with the concentration in case of negligible particle inertia. The third one accounts for the further increase of the drag when the particle inertia is increased. Remarkably, each correction only relies on a single of the three independent non-dimensional groups that control the problem: (1) the particle volume fraction Φs; (2) the ratio Φs/Φpack where Φpack is the bed packing concentration; (3) the Stokes number S t 0 , which characterizes the inertia of the particles and controls their agitation. Moreover, the onset of the instability that separates the homogeneous regime from the heterogeneous one is found to be controlled similarly by the Stokes number. Empirical expressions of the corrections are given, which provide a reliable tool to predict fluidization and sedimentation velocities for all values of the three non-dimensional numbers. The present results emphasize the crucial role of particle inertia, which is often disregarded in previous modeling approaches, such as that of Richardson and Zaki.

The origin of this monograph lies in a simple fact: there is a paradigm with cast irons, namely that these alloys have been produced and cast for thousands of years, yet they are among the most complicated alloys if we consider the formation of their microstructure by solidification and transformations in the solid state. The positive side of this complexity is that it offers a wide range of possibilities for manipulating their microstructure. With the evolution of melting furnaces in the 19th century, the silicon content of cast irons increased, leading to the development of the silicon cast irons that are the subject of this monograph. The essential step, however, was the discovery in the middle of the 20th century that it is possible to change the shape of graphite by transforming the interconnected lamellae into discrete spheroids. In this way, cast iron became a material for safety parts and was no longer limited to construction. This historical development and the research effort during the first part of the 20th century have been described in reviews published in the 1960s. Since then, developments in metallographic analysis have led to a wealth of research aimed at describing and understanding graphite formation and the microstructure of cast irons during solidification and heat treatment. This monograph is not intended to be an exhaustive review of the literature of the last 50 years, but aims to propose a coherent vision of the formation of the microstructure of cast irons based on the work carried out jointly or in parallel by its authors. Current controversies are sometimes indicated but are not discussed in order to emphasize open questions. Finally, we should mention that our work has greatly benefited from the dynamism of the European Cast Iron group (ECI), an informal forum open to all (European academics and industrialists) for more than 10 years. It is in this same spirit of discussion that this monograph is freely available. \\// Cette monographie trouve son origine dans un fait simple : il existe un paradigme avec les fontes, à savoir que ces alliages sont produits et coulés depuis des milliers d'années, mais qu'ils comptent pourtant parmi les alliages métalliques les plus compliqués si l'on considère la formation de leur microstructure par solidification et transformations à l'état solide. Le côté positif de cette complexité est qu'elle offre un large éventail de possibilités pour la manipulation de leur microstructure. Avec l'évolution des fours de fusion au 19ème siècle, la teneur en silicium des fontes a augmenté conduisant au développement des fontes au silicium qui font l'objet de cette monographie. L'étape essentielle, cependant, a été la découverte au milieu du 20ème siècle qu'il est possible de changer la forme du graphite en transformant les lamelles interconnectées en sphéroïdes disjoints. Les fontes sont ainsi devenues un matériau pour pièces de sécurité et n'ont plus été limitées à la construction. Cette évolution historique et l'effort de recherche durant la première partie du 20ème siècle ont été décrits dans les revues publiées dans les années 1960. Depuis cette époque, l'évolution des analyses métallographiques a généré nombre de recherches destinées à décrire et comprendre la formation du graphite et de la microstructure des fontes lors de leur solidification et des traitements thermiques. Cette monographie ne se veut pas une revue exhaustive de la littérature de ces 50 dernières années, mais vise à proposer une vision cohérente de la formation de la microstructure des fontes graphitiques basée sur les travaux conduits en commun ou en parallèle par ses auteurs. Les controverses actuelles sont quelquefois indiquées mais ne sont pas discutées afin de mettre l'accent sur les questions ouvertes. Enfin, nous avons plaisir à mentionner que notre travail a largement profité du dynamisme du groupe européen de la fonte (ECI), forum informel ouvert à tous (universitaires et industriels européens) depuis plus de 10 ans. C'est dans ce même esprit de discussion que cette monographie est en accès libre.

Two separate experimental campaigns of a spatially developing turbulent boundary layer under approximately zero-pressure-gradient at moderate Reynolds numbers ([Formula: see text]) are conducted with stereoscopic Particle Image Velocimetry (PIV) and one component Hot Wire Anemometry. This range of Reynolds numbers is found to be of particular interest for turbulent boundary layer control investigations. The motivations behind this work rely on the lack of recent studies that provide a rigorous experimental database on a flat plate turbulent boundary layer, openly available online. This is critical as, in most of the cases, the modification of the statistics resulting from turbulent boundary layer control strategies are compared with a smooth baseline reference. The statistics of the velocity fields, obtained with the two techniques, show a good match with the direct numerical simulation in literature results. We focused on the skin friction evaluation by means of Clauser's chart technique. The near wall turbulence activity and the associated coherent structures are investigated by means of the Variable Interval Time Averaging technique using the hot wire signal. The influence of the acquisition and algorithm parameters as well as the effect of the Reynolds number are reported. The logarithmic and outer structures are investigated by applying the Uniform Momentum Zones technique to the PIV dataset. The hierarchical distribution of the uniform momentum zones as a function of the wall distance as well as their variation with the Reynolds number confirm the validity of the attached eddy model even at the moderate Reynolds numbers of the current investigation.

Model-Based Software Engineering (MBSE) is a development approach aiming to build correct-by-construction systems, provided the use of clear, unambiguous and complete models to describe them along the design process. The approach is supported by several engineering tools, such as the TASTE toolset. TASTE is a pragmatic and mature open-source toolset supported by European Space Agency that enables and provides automation for most of the phases of software system development: (i) heterogeneous system design through several modelling and programming languages, (ii) code generation, build and deployment of the binary application(s), and (iii) validation through static analysis and simulation. One topic left open in TASTE is the formal verification of a system design with respect to specified properties. In this paper we describe our approach based on the IF model-checker to enable the formal verification of properties on TASTE designs, as well as the results obtained and lessons learned.

International audience; Predictive maintenance techniques attempt to trigger a maintenance intervention at the right moment by estimating the life expectation. Predictive maintenance is increasingly implemented by automated approaches able to perform diagnostics and prognostics. The main part of recent research in these approaches is focused in machinelearning structures whose reasoning is implicit and cannot be easily explained. This poses a problem for theirimplementation in highly constrained area such as aeronautics. To overcome this constraint, explicit reasoningapproaches such as the Similarity-Based Model (SBM) can be implemented. The SBM has been widely used for fault diagnostics and the remaining useful life (RUL) estimation, but the development of SBM includes tasks that often rely on high skilled experts. For instance, data reduction techniques required for SBM are often performed by experts judgment whose outcomes are not always consistent. The produced features from these techniques are used to build the Health Index that can be used to create the degradation trends that serve as a reference for the SBM. To overcome these difficulties, an automatic and unsupervised approach based on the Kernel Principal Component Analysis is proposed to enhance the Health Index creation. It preserves as much of the sensor information as possible improving the similarity-based RUL estimation. Additionally, when estimating the RUL of a system, the most similar degradation trends stored in the SBM library are used to compute individual RULs, the final RUL is obtained by a fusion rule technique that combines all these individual RULs into a consolidated value. For the fusion rule techniques, a self-adaptive method that does not rely on human expertize is proposed. This fusion rule can benefit of the accumulated knowledge over the SBM operation. This unsupervised approach to develop a SBM is validated with promising results against an equivalent and supervised algorithm that came out best in the 2008 prognostic health management challenge.

International audience; Mechanical and electro-mechanical de-icing systems are low-energy ice protection solutions based on fracturemechanisms. It can, however, be difficult to obtain the protection of an entire surface due to the limited propagation of fractures for some mechanisms. This article shows how it is possible to reshape the substrate in orderto favor the propagation of adhesive fracture at the ice/substrate interface. The first part of the paper introducesan analytical beam theory approach for running computations quickly, making it possible to achieve parametricoptimization of the substrate thickness and maximize the propagation length. The optimization results werevalidated using FEM software and tests on an aluminum prototype. A second method is also studied in this paper,topology optimization is used on a 2D finite element model to minimize the substrate mass of the proposedsolution and adhesive crack propagation is assessed in comparison with the mass impact. For different boundaryconditions, propagation ranges can be increased by up to 150% with a mass increase limited to 50%. Usingtopology optimization, the additional mass could be reduced by 60% while maintaining the sameperformances.

In this study, a formal framework aiming to drive the interaction between a human operator and a team of unmanned aerial vehicles (UAVs) is experimentally tested. The goal is to enhance human performance by controlling the interaction between agents based on an online monitoring of the operator’s mental workload (MW) and performance. The proposed solution uses MW estimation via a classifier applied to cardiac features. The classifier output is introduced as a human MW state observation in a Partially Observable Markov Decision Process (POMDP) which models the human-system interaction dynamics, and aims to control the interaction to optimize the human agent’s performance. Based on the current belief state about the operator’s MW and performance, along with the mission phase, the POMDP policy solution controls which task should be suggested -or not- to the operator, assuming the UAVs are capable of supporting the human agent. The framework was evaluated using an experiment in which 13 participants performed 2 search and rescue missions (with/without adaptation) with varying workload levels. In accordance with the literature, when the adaptive approach was used, the participants felt significantly less MW, physical and temporal demands, frustration, and effort, and their flying score was also significantly improved. These findings demonstrate how such a POMDP-based adaptive interaction control can improve performance while reducing operator workload.

International audience; Herbicides and their degradation products contribute to soil pollution and to its impact on soil biodiversity and functioning. Soil herbicide pollution presents characteristics of global planetary threats, with harmful consequences for soil ecology, for ecosystem functions and services mediated by natural plant communities and for crop production sustainability. However, the range and the mechanisms of soil herbicide pollution effects on plants are not fully understood. Effects on roots, as a first line of pollutant exposure, and on root plasticity, as a driver of below-ground ecological processes, must be further characterized. Because of worldwide intensive use of atrazine, of persistence in the environment and of toxicological effects, atrazine and its derived metabolites are typical persistent organic pollutants of soils. The coherent chemical series consisting of atrazine, desethylatrazine and hydroxyatrazine was used to analyse potential effects of triazine xenobiotics on root plasticity processes. Responses to atrazine, desethylatrazine and hydroxyatrazine applied at root level were comparatively analyzed in the model plant Arabidopsis thaliana, which is highly responsive to triazine xenobiotics. We report that triazine xenobiotics, whether as herbicidally active compounds or as degradation products, affect root plasticity in terms of primary root growth, lateral root development and root hair development, and that these effects differentially interact with the light, carbon and cytokinin status of the plant. The adaptive significance of these effects and of their interactions is discussed in terms of toxicity of, or resistance to, residual soil contaminants and in terms of potential cascading impact on plant and ecosystem functioning.

The use of ML technology to design safety-critical systems requires a complete understanding of the neural network's properties. Among the relevant properties in an industrial context, the verification of partial monotony may become mandatory. This paper proposes a method to evaluate the monotony property using a Mixed Integer Linear Programming (MILP) solver. Contrary to the existing literature, this monotony analysis provides a lower and upper bound of the space volume where the property does not hold, that we denote ``Non-Monotonic Space Coverage''. This work has several advantages: (i) our formulation of the monotony property works on discrete inputs, (ii) the iterative nature of our algorithm allows for refining the analysis as needed, and (iii) from an industrial point of view, the results of this evaluation are valuable to the aeronautical domain where it can support the certification demonstration. We applied this method to an avionic case study (braking distance estimation using a neural network) where the verification of the monotony property is of paramount interest from a safety perspective.

Bi-functional water-soluble polymers have been investigated as bonding layers (BL) on aluminum surfaces to promote the adhesion of adhesives for structural bonding applications in the automotive sector. The BLs are located at the interface between two parts: the aluminum substrate and the adhesive (an epoxy-dicyandiamide). The formation and the morphology are studied mainly by transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). Many process parameters have been investigated such as: i) long or short immersion time in the treatment baths containing the polymers, ii) formulation using three different concentrations. The performances of the BLs under these different operating conditions are evaluated via several mechanical tests: micro-scratch, three-point bending, single lap shear. Results were compared with results obtained with already existing products, launched for the same application, surface treatment prior to structural adhesive bonding of aluminum in transportation.

International audience; Ti-stabilized austenitic stainless steel was carburized in sodium containing a high carbon activity at three different temperatures, 500 °C, 600 °C, and 650 °C during 1000 hours and 5000 hours. The carbon profile, the carbide volume fraction, and the lattice parameter evolution as function of depth were determined using high-energy X-ray diffraction and electron probe microanalysis. At 650 °C and 600 °C, the carbon precipitated as M23C6 and M7C3 carbides in the sample. The volume fraction of M7C3 carbides was lower than predicted by thermodynamic equilibrium using Thermo-Calc software®. At 500 °C, carbides almost did not form in the steel. Instead, high carbon supersaturation of the austenitic matrix occurred. Both results demonstrate that the carburization profile was strongly influenced by the kinetics of carbide formation at temperatures lower than 650 °C. High-energy X-ray diffraction measurements demonstrated that the austenite and carbide lattice parameters evolved along the carbon profile. Both measured lattice parameter profiles of austenite and M23C6 carbide were compared to the ones predicted from chemical changes of austenite and carbides.

International audience; This paper deals with an experimental study of angled fish-friendly trash racks with horizontal bars, using a physical model in an open channel. Head losses are investigated for 2 bar shapes, 3 ratios between bar spacing and bar thickness and 4 rack’s angles of orientation. The Froude and bar-Reynolds numbers were respectively 0.275 and 3600. The head loss coefficients decrease as the blockage ratio and the angle of orientation of the rack decrease. They are well predicted by the formula produced by Raynal et al. (2013a) for inclined rack with some adaptations. Velocity fields are characterized upstream and downstream of the racks, showing no effect of the angle of orientation and no heterogeneity over channel width. Consequently, the normal and tangential components of the velocity along the rack are in agreement with the theoretical values given by angular decomposition. These results serve to assess the compliance with biological criteria to avoid impingement risks and guide fish towards a bypass.

International audience; In this article, we report a facile precursor pyrolysis by sol-gel method to prepare spinel-type Cobalt-substituted zinc aluminate nanoparticles (Zn1–xCoxAl2O4, 0≤x≤1). The relationship between the degree of crystallinity and the optical properties under the effect of the calcination temperature was investigated. The synthesized powders were characterized by means of X-ray diffraction (XRD), Thermogravimetry and Differential thermal analysis (TG–DTA), field emission scanning electron microscopy (FE-SEM), Brunauer–Emmett–Teller analysis (BET), UV–Vis absorption spectroscopy analysis and colorimetric analysis (CIELab). A single-phase Zn1–xCoxAl2O4 (0≤x≤1) spinel was formed at an annealing temperature of 700°C. Structural refinement via the Rietveld method shows that an annealing temperature in excess of 700°C leads to a decrease in the amorphous phase rate. At 800 °C, the enrichment in 50% of cobalt leads to blue powders with a degree of crystallinity of approximately 92% and a quasi-spherical morphology of nanometric size less than 100 nm.

Porous carbonaceous materials have many important industrial applications including energy storage, water purification, and adsorption of volatile organic compounds. Most of their applications rely upon the adsorption of molecules or ions within the interior pore volume of the carbon particles. Understanding the behaviour and properties of adsorbate species on the molecular level is therefore key for optimising porous carbon materials, but this is very challenging owing to the complexity of the disordered carbon structure and the presence of multiple phases in the system. In recent years, NMR spectroscopy has emerged as one of the few experimental techniques that can resolve adsorbed species from those outside the pore network. Adsorbed, or "in-pore" species give rise to resonances that appear at lower chemical shifts compared to their free (or "ex-pore") counterparts. This shielding effect arises primarily due to ring currents in the carbon structure in the presence of a magnetic field, such that the observed chemical shift differences upon adsorption are nucleus-independent to a first approximation. Theoretical modelling has played an important role in rationalising and explaining these experimental observations. Together, experiments and simulations have enabled a large amount of information to be gained on the adsorption and diffusion of adsorbed species, as well as on the structural and magnetic properties of the porous carbon adsorbent. Here, we review the methodological developments and applications of NMR spectroscopy and related modelling in this field, and provide perspectives on possible future applications and research directions.

Near nozzle field behavior of round liquid jets injected through large injector diameter (ranging from 0.2 to 0.6m) into subsonic uniform gaseous crossflows is numerically investigated using the Volume of Fluid (VoF) method. The liquid jet to gas momentum ratio is ranging from 4.3 to 39 with a gas Weber number ranging from 1.6 × 10^4 to 5.3 × 10^4. The large scale liquid water column main properties, such as primary breakup process, liquid column penetration height, liquid column expansion and column breakup point location are studied. Effects of several parameters on the liquid column evolution are investigated, namely the diameter injector, the liquid jet injection velocity and the gaseous crossflow velocity. It has been found that the surface breakup and column breakup mechanisms are both contributing to the liquid column fragmentation. The fragmentation at large scale is characterized by the generation of a significant number of well developed arm and leg structures that align with the airflow on the side and at the bottom of the liquid column. Correlations for the main liquid jet properties are proposed and compared with results previously obtained for smaller size liquid jet. Liquid column penetration height, width and column breakup height follow the same type of power laws that those observed for liquid jet at smaller size. The liquid jet evolution is compared to the water jet generated by the B747 airtanker.

International audience; Dams and other man-made barriers impair upstream fish migration and thus threaten fish populations that need access to upper river reaches to complete their life cycle. For many years, fishways have been used to mitigate this impact. Fishways around the globe are typically built based on recommendations made for northern hemisphere species, particularly salmonids. These recommendations do not consider the locomotor characteristics and skills of other species, especially those living in the tropics. Among tropical species, freshwater eels and gobies of the Sicydiinae subfamily are important cultural and economic species that are particularly sensitive to the impact of man-made barriers. Our experimental study aimed to test different substrates and slopes for ramp-like fishways adapted to tropical eels and sicydiines. Among the five substrates tested for 368 eels Anguilla marmorata, elastomer pins appeared to be the most efficient. Elastomer pins also appeared to be more efficient than the fine concrete which is currently used in fishways for sicydiines (Sicyopterus lagocephalus, N = 1797, and Cotylopus acutipinnis, N = 1303). The slope had a lesser effect on the climbing success of sicydiines compared to substrate type, except for gradients greater than 50° that induced a slight decrease in success. Our results indicated that ramp-like fishways fitted with 1.0 cm diameter elastomer pins, positioned in staggered rows with a diagonal spacing of 1.3 cm, wetted with low-flow and angled less than 50°, are well adapted to accommodate the different locomotor characteristics and skills of tropical eels and sicydiines.

A cross‐laboratory study on microbial fuel cells (MFC) which involved different institutions around the world is presented. The study aims to assess the development of autochthone microbial pools enriched from domestic wastewater, cultivated in identical single‐chamber MFCs, operated in the same way, thereby approaching the idea of developing common standards for MFCs. The MFCs are inoculated with domestic wastewater in different geographic locations. The acclimation stage and, consequently, the startup time are longer or shorter depending on the inoculum, but all MFCs reach similar maximum power outputs (55±22 μW cm−2) and COD removal efficiencies (87±9 %), despite the diversity of the bacterial communities. It is inferred that the MFC performance starts when the syntrophic interaction of fermentative and electrogenic bacteria stabilizes under anaerobic conditions at the anode. The generated power is mostly limited by electrolytic conductivity, electrode overpotentials, and an unbalanced external resistance. The enriched microbial consortia, although composed of different bacterial groups, share similar functions both on the anode and the cathode of the different MFCs, resulting in similar electrochemical output., The famous five: A cross‐laboratory study involving five institutions is presented. Each team runs a triplicate identical single chamber microbial fuel cell for 6 weeks varying only the inoculum. Electrochemical and operational parameters are collected. Microbiological analysis is carried out on the influent and effluent and on the electrodes. All the data collected are correlated by using robust statistics.

Previous experimental results indicate that the humidification conditions at the anode have an impact on the liquid water distribution in the cathode gas diffusion layer. Numerical simulations are developed to reproduce and analyze this effect. Results consistent with the experimental results are first obtained by playing with the partition coefficients of an advanced pore network model computing the liquid water formation and transfer in the cathode gas diffusion layer (GDL) for a large range of operating conditions. Then, a model for the full anode – cathode assembly is developed by combining the pore network model of the cathode GDL and a 1D model describing the heat and water transfer in the various components of the anode-cathode assembly. This enables one to generalize the dry – wet regime diagram introduced in a previous work by incorporating the effect of the humidity condition at the anode.

In this paper, mixed categorical structural optimization problems are investigated. The aim is to minimize the weight of a truss structure with respect to cross-section areas, materials and cross-section type. The proposed methodology consists of using a bi-level decomposition involving two problems: master and slave. The master problem is formulated as a mixed integer linear problem where the linear constraints are incrementally augmented using outer approximations of the slave problem solution. The slave problem addresses the continuous variables of the optimization problem. The proposed methodology is tested on three different structural optimization test cases with increasing complexity. The comparison to state-of-the-art algorithms emphasizes the efficiency of the proposed methodology in terms of the optimum quality, computation cost, as well as its scalability with respect to the problem dimension. A challenging 120-bar dome truss optimization problem with 90 categorical choices per bar is also tested. The obtained results showed that our method is able to solve efficiently large scale mixed categorical structural optimization problems., Accepted for publication in Structural and Multidisciplinary Optimization, to appear 2022

Background: Antibodies against the P3 sequence (Gly1127-Cys1140) of LRP1 (anti-P3 Abs) specifically block cholesteryl ester (CE) accumulation in vascular cells. LRP1 is a key regulator of insulin receptor (InsR) trafficking in different cell types. The link between CE accumulation and the insulin response are largely unknown. Here, the effects of P3 peptide immunization on the alterations induced by a high-fat diet (HFD) in cardiac insulin response were evaluated. Methods: Irrelevant (IrP)- or P3 peptide-immunized rabbits were randomized into groups fed either HFD or normal chow. Cardiac lipid content was characterized by thin-layer chromatography, confocal microscopy, and electron microscopy. LRP1, InsR and glucose transporter type 4 (GLUT4) levels were determined in membranes and total lysates from rabbit heart. The interaction between InsR and LRP1 was analyzed by immunoprecipitation and confocal microscopy. Insulin signaling activity and glucose uptake were evaluated in HL-1 cells exposed to rabbit serum from the different groups. Findings: HFD reduces cardiac InsR and GLUT4 membrane levels and the interactions between LRP1/InsR. Targeting the P3 sequence on LRP1 through anti-P3 Abs specifically reduces CE accumulation in the heart independently of changes in the circulating lipid profile. This restores InsR and GLUT4 levels in cardiac membranes as well as the LRP1/InsR interactions of HFD-fed rabbits. In addition, anti-P3 Abs restores the insulin signaling cascade and glucose uptake in HL-1 cells exposed to hypercholesterolemic rabbit serum. Interpretation: LRP1-immunotargeting can block CE accumulation within the heart with specificity, selectivity, and efficacy, thereby improving the cardiac insulin response; this has important therapeutic implications for a wide range of cardiac diseases., Fundació MARATÓ TV3: grant 101521-10, Instiuto de Salud Carlos III (ISCIII) and ERDF PI18/01584, Fundación BBVA Ayudas a Equipos de Investigación 2019. SECyT-UNC grants PROYECTOS CONSOLIDAR 2018-2021; FONCyT, Préstamo BID PICT grant 2015-0807 and grant 2017-4497.