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Quand les animaux prennent la parole
No full textEmission radio CQFD RTSOn a longtemps cru que le langage était le propre de lʹêtre humain. Mais ces dernières années, les découvertes scientifiques ont mis en lumière des formes de vocabulaire, de syntaxe et même de dialectes régionaux chez dʹautres espèces. Alors, notre communication est-elle vraiment unique ? Ou sommes-nous simplement trop anthropocentrés pour saisir la richesse de celle des animaux ?On en parle avec Alban Lemasson et Maël Leroux, chercheurs à lʹUniversité de Rennes et auteurs de Quand les animaux prennent la parole !, paru aux éditions Apogée
Opportunities and Challenges in Combining Optical Sensing and Epidemiological Modelling
No full textInternational audiencePlant diseases impair yield and quality of crops and threaten the health of natural plant communities. Epidemiological models can predict disease and inform management. However, data are scarce, since traditional methods to measure plant diseases are resource intensive and this often limits model performance. Optical sensing offers a methodology to acquire detailed data on plant diseases across various spatial and temporal scales. Key technologies include multispectral, hyperspectral and thermal imaging, and light detection and ranging; the associated sensors can be installed on ground-based platforms, uncrewed aerial vehicles, aeroplanes and satellites. However, despite enormous potential for synergy, optical sensing and epidemiological modelling have rarely been integrated. To address this gap, we first review the state-of-the-art to develop a common language accessible to both research communities. We then explore the opportunities and challenges in combining optical sensing with epidemiological modelling. We discuss how optical sensing can inform epidemiological modelling by improving model selection and parameterisation and providing accurate maps of host plants. Epidemiological modelling can inform optical sensing by boosting measurement accuracy, improving data interpretation and optimising sensor deployment. We consider outstanding challenges in: A) identifying particular diseases; B) data availability, quality and resolution, C) linking optical sensing and epidemiological modelling, and D) emerging diseases. We conclude with recommendations to motivate and shape research and practice in both fields. Among other suggestions, we propose to standardise methods and protocols for optical sensing of plant health and develop open access databases including both optical sensing data and epidemiological models to foster cross-disciplinary work
A toy model for frequency cascade in the nonlinear Schrodinger equation
No full text24 pagesWe present an elementary approach to observe frequency cascade on forced nonlinear Schrödinger equations. The forcing term consists of a constant term, perturbed by a modulated Gaussian well. Algebraic computations provide an explicit frequency cascade when time and space derivatives are discarded from the nonlinear Schrödinger equation. We provide stability results, showing that when derivatives are incorporated in the model, the initial algebraic solution may be little affected, possibly over long time intervals. Numerical simulations are provided, which support the analysis
Security of Dynamically Reconfigurable RISC-V Systems: I/O Attack Focus
No full textInternational audienceDynamic Partial Reconfiguration (DPR) enhances flexibility in modern hardware but introduces security risks. This work demonstrates how a Malicious Hardware Accelerator (MHA) can exploit Direct Memory Access (DMA) to bypass Input Output Memory Management Unit (IOMMU) protections through device ID manipulation, enabling unauthorized memory access. This vulnerability exposes a fundamental security gap in the management of dynamically reconfigurable systems. By highlighting this issue and proposing mitigation strategies, we provide a conceptual framework to guide the development of security mechanisms for dynamically adaptable architectures
Development of an Innovative and Sustainable Technological Process for Biogas Purification Through the Reuse of Autoclaved Aerated Concrete Waste
No full textInternational audienceThis study demonstrated the effectiveness of using autoclaved aerated concrete AAC waste as a low-cost filtering material for removing hydrogen sulfide (H2S) from gas streams. A long-term experiment (89 days) was conducted in a packed bed reactor to purify synthetic biogas composed of N2, CO2, H2S, and O2. Optimal H2S removal efficiencies, reaching up to 100%, were achieved under highly acidic conditions (pH ≈ 1–3) and low oxygen concentrations (<1%). In the presence of oxygen, calcium oxides in the AAC waste react with H2S to form gypsum (CaSO4 2H2O). The simultaneous removal of both oxygen and H2S by AAC waste, following an approximate 2:1 molar ratio, may be particularly beneficial for biogas streams containing unwanted traces of oxygen. The transformation and lifespan of AAC waste were monitored through sulfur accumulation in the material and pressure drop measurements, which indicated structural changes in the AAC waste. At the end of its lifespan, the AAC waste exhibited an H2S removal capacity of 185 gH2S kgAAC−1. This innovative and sustainable process not only provides a cost-effective and environmentally sound solution for the simultaneous removal of H2S and O2 from biogas, but also promotes waste valorization and aligns with circular economy principles
Nickel-Doped Carbon Nanomaterial Catalyzed Transfer Hydrogenation of Unsymmetrical Urea Using Methanol as H2 Source
No full textInternational audienceBreaking the strong resonance effect of unsymmetrical ureas has been a significant challenge, particularly through catalytic hydrogenation. The Ni-dC heterogeneous catalyst was specifically designed to achieve the transfer hydrogenation of unsymmetrical ureas using methanol as a hydrogen source for the synthesis of aniline. In this work, we present a straightforward and effective heterogeneous Ni-dC catalyst as a promising candidate for the synthesis of amines by disrupting the resonance of unsymmetrical ureas. The Ni-dC material was prepared through pyrolysis, and its crystallinity, chemically functional pores, and structural variations were crucial for this transformation. The scope of this catalytic method was demonstrated using various unsymmetrical urea derivatives. A key advantage of this protocol is the reusability of the Ni-dC catalyst for up to five cycles, maintaining catalytic efficiency. The core of this approach lies in the ability of Ni-dC to generate hydrogen from methanol and destabilize the resonance of unsymmetrical ureas, leading to the selective formation of the corresponding amines
Automated dysphagia characterization in head and neck cancer patients using videofluoroscopic swallowing studies
No full textInternational audienceBackground: Dysphagia is one of the most common toxicities following head and neck cancer (HNC) radiotherapy (RT). Videofluoroscopic Swallowing Studies (VFSS) are the gold standard for diagnosing and assessing dysphagia, but current evaluation methods are manual, subjective, and time-consuming. This study introduces a novel framework for the automated analysis of VFSS to characterize dysphagia in HNC patients.Method: The proposed methodology integrates three key steps: (i) a deep learning-based labeling framework, trained iteratively to identify ten regions of interest; (ii) extraction of 23 swallowing dynamic parameters, followed by comparison across diverse cohorts; and (iii) machine learning (ML) classification of the extracted parameters into four dysphagia-related impairments.Results: The labeling framework achieved high accuracy, with a mean error of 1.6 pixels across the ten regions of interest in an independent test dataset. Analysis of the extracted parameters revealed significant differences in swallowing dynamics between healthy individuals, HNC patients before and after RT, and patients with non-HNC-related dysphagia. The ML classifiers achieved accuracies ranging from 0.60 to 0.87 for the four dysphagia-related impairments.Conclusions: Despite challenges related to dataset size and VFSS variability, our framework demonstrates substantial potential for automatically identifying ten regions of interest and four dysphagia-related impairments from VFSS. This work sets the foundation for future research aimed at refining dysphagia analysis and characterization using VFSS, particularly in the context of HNC RT
Athlètes aux Jeux d'hiver de l'Arctique (JHA): quelle identité sportive pour les participants aux sports non-autochtones?
No full textInternational audienceIntroduction : L’obsession de la victoire est une composante courante de l’identité des athlètes. Dans le cadre du concept de soi multidimensionnel, à la croisée du rôle social et de la perception de soi, l’identité sportive, définie comme le degré d’identification au rôle d’athlète (1), a été principalement étudiée chez les athlètes de haut niveau et retraités (2). Habituellement analysée en amont ou en aval d’une performance, son exploration pendant un événement sportif mêlant sport et culture, les JHA, pourrait offrir de nouvelles perspectives quant à sa construction chez de jeunes sportifs. Méthode : Une méthode mixte a été menée articulant une mesure de l’identité sportive de 152 athlètes canadiens de sports d’hiver et de toute saison via un questionnaire (AIMS-3G ;(3)), ainsi qu’une analyse des significations attribuées à cette identité au travers d’entretiens semi-directifs auprès de 31 athlètes. Des tests non-paramétriques de comparaison de moyennes, ainsi que l’identification de thèmes communs entre les différents cas, sont en cours de traitement. Résultats attendus : L’analyse statistique devrait montrer que les participants à ces jeux s’identifient au rôle d’athlète et que des différences émergent en fonction de l’âge, des années d’expérience dans le sport et du type de sport pratiqué. En complément, l’analyse thématique des entretiens devrait révéler que, compte tenu du contexte unique des régions circumpolaires, du statut en évolution de ces athlètes, ainsi que des aspirations de cet événement à une visibilité culturelle et à des interactions sociales entre habitants du Nord, la manière dont les athlètes perçoivent leur identité sportive ne devrait pas se limiter à un accent mis sur la performance. Implications pratiques : Cette étude vise ainsi à appréhender les expériences de jeunes sportifs en développement participant aux JHA afin d’éclairer la diversité des significations attribuées à l’identité sportive
VarDyn: Dynamical Joint-Reconstructions of Sea Surface Height and Temperature From Multi-Sensor Satellite Observations
No full textInternational audienceThe VarDyn hybrid methodology, which combines minimal physically based constraints with a variational scheme, is demonstrated to enhance the mapping of sea surface height (SSH) and sea surface temperature (SST). By synthesizing multi-modal satellite observations, VarDyn produces SSH and SST maps with improved accuracy compared to operational products, achieving reductions in Root Mean Square Error and enhancements in effective spatial resolution. While most improvements are observed in highly energetic ocean regions, SSH map accuracy also improves slightly in low-energy regions—a significant advancement over other methods. VarDyn SSH fields and the associated geostrophic velocities show strong agreement with newly available high-resolution instantaneous SWOT estimates. Notably, the assimilation of SST proves particularly beneficial for SSH reconstruction when only two altimeters are available. The VarDyn methodology potentially offers a robust framework for refining climate SSH records by jointly assimilating SSH data from two altimeters and SST data from microwave sensors.Key PointsVarDyn is a method using reduced physical models and a variational scheme to map sea surface height (SSH) and sea surface temperature (SST) from altimetric and microwave satellite dataTested against recent high-resolution data, VarDyn improves the accuracy of SSH and SST maps compared to operational productsSSH mapping especially benefits from SST for a two altimeters configuration, opening the way of refining climate SSH recordsPlain Language SummaryBy combining fundamental physical principles with advanced data processing techniques, the joint reconstruction of sea surface height (SSH) and sea surface temperature (SST) is demonstrated. Using satellite data, this approach systematically produces more accurate SSH and SST maps, with particularly noticeable improvements in highly dynamic ocean regions. Additionally, the method significantly enhances mapping performance in calmer ocean areas. The results align closely with new high-resolution satellite observations. Notably, when only two altimeter satellites are available, incorporating SST data significantly improves SSH mapping capabilities. This methodology offers a promising tool for refining climate records by consistently integrating previously available medium-resolution SST and altimeter measurements