HAL Université de Toulouse, et Toulouse INP
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Impact of wheat-legume mix intercrops on wheat epidemics by modelling
No full textInternational audienceHighlights: • Simulated intercropping decrease disease intensity and improve protectiveness while canopy indicators predict such effects. • Pea intercropped with wheat decreased disease intensity compared with faba bean. • Nitrogen fertilization increased disease intensity. • This study stressed the critical lack of experimental data on disease in intercropping.Abstract: Context : Intercropping is a promising strategy for integrated disease management and agroecological transition, although experimental and modelling studies are scarce.Objectives: This study aims to understand and quantify the impact of non-host species choice and nitrogen (N) fertilization on disease epidemics in the context of intercropping.Methods: We collected existing experimental data on LAI based on a literature survey of non-diseased wheat intercropped with different non-host legume species (pea and faba bean) and N fertilization treatments. Based on a foliar epidemic model for intercropping, we simulated epidemics directly on these experimental data of LAI. The model is parameterized for two wheat fungal diseases: Septoria tritici blotch, a rain-borne disease, and wheat leaf rust, an air-borne disease.Results: Our results indicate that intercropping can decrease disease intensity and improve protectiveness for both diseases. Effect depends however on species choice as pea intercropped with wheat leads to lower disease intensity and better intercropping protectiveness compared with faba bean, whereas N fertilization increased disease intensity. We also found that crop indicators describing wheat leaf area index (LAI) can predict disease intensity, whereas indicators describing companion LAI can better predict intercropping protectiveness.Conclusions: Intercropping can significantly reduce fungal epidemics on wheat, and intercropping management practices can be optimized for effective disease management in wheat-legume intercrops. The dilution effect is more related to disease intensity, while the barrier effect is more related to intercropping protectiveness.Implications: These findings pave the way for identifying field indicators to predict epidemics. However, this study also stressed the critical lack of experimental data on disease in intercropping
How PGL finds a sweet spot in phospholipid membranes: A combined multiscale MD and NMR study
No full textInternational audienceGlycolipids from pathogenic Mycobacterium tuberculosis play important roles during the interaction of the pathogen with macrophages and can shape the host cell's immune response by modulating its membrane structure and function.Here, we study the phenolic glycolipids (PGLs) present in the envelope of some hypervirulent strains of Mycobacterium tuberculosis and their impact on model membranes. By a combination of molecular modeling and simulations, and solid-state NMR experiments, we show that PGLs, such as the structurally related lipid phthiocerol dimycocerosate, adopt a conical shape in lipid membranes, which destabilizes the lamellar membrane phase and promotes a transition to a nonlamellar inverted-hexagonal phase. Unlike phthiocerol dimycocerosate, in our simulations, PGL remains anchored to the phosphate groups of the lipid bilayer by its sugar-carrying extremity, preventing lipid flip-flop. These findings shed new light on a potential biophysical role of PGLs through modulation of the properties of the host cell's membrane, in addition to the recognition of its sugar moiety by host cell immune receptors.</div
Embrittlement after high-temperature exposure to air of a near-γ TiAl alloy
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Habitat quality assessment of temperate forest ecosystems: An airborne LiDAR-based approach to predict the Index of Biodiversity Potential (IBP) at large scale
No full textInternational audienceThe Index of Biodiversity Potential (IBP) assesses the forest stand’s capacity to host species based on 10 structural, compositional, and environmental factors. Widely used by French forest managers, its reliance on in-situ surveys limits large-scale applications. While LiDAR-derived metrics can finely describe forest structure, their relationship with the IBP remains unexplored.We aimed to study these relationships with the IBP management factors, some of which reflect forest structure such as the number of large trees and vertical strata. Using a dataset of 1536 IBP plots across France, we computed LiDAR-derived structural metrics along with other variables (e.g., topographic, spectral). We then analysed their statistical relationships with the IBP factors, and calibrated predictive models using both regression and classification machine learning algorithms. Finally, we mapped the IBP management score for the first time over a 890 km area within the forests of the Ariege Pyrenees Regional Natural Park (France).The results revealed strong correlations between the IBP management score, its factors, and remote sensing metrics. LiDAR-derived metrics describing canopy height and vertical complexity were particularly important for prediction, as well as biomass and topographic metrics. Our best model, with an RMSE of 5.24 ± 0.63, predicts IBP within 5 points—a threshold beyond which variations reflect actual changes in species richness within the forest stand.These findings emphasise the relevance of remote sensing data, in particular LiDAR, for describing structural field metrics. They demonstrate that remote sensing offers a viable approach for large-scale IBP assessment
Orchestrating on-board sensors for global hybrid robust stabilization of unicycles
No full textWe consider mobile robots described through unicycle dynamics equipped with on-board range sensors and cameras, one facing forward and one facing backward, providing measurements of the distance and misalignment to a target. We propose a hybrid control law combining the two on-board measurements and discuss stability results for the closed-loop expressed in the on-board camerabased coordinates, using Lyapunov-based arguments. We prove robustness of the stability properties to uncertainties affecting the sensors and external perturbations acting on the robot. The results are illustrated via simulations
Seedling emergence vigor, establishment success, and biomass yield stability of cover crop mixtures compared to pure stands
No full textInternational audienceContext: Cover cropping has the potential to enhance the sustainability of cropping systems across temperate regions. However, poor establishment of cover crops (CCs), often driven by unfavorable weather conditions, remain a major barrier to their adoption. Sowing CC mixtures may mitigate the risks of poor establishment compared to pure stands, thereby lowering spatio-temporal variability in biomass production, which is critical for consistent ecosystem service provision. Yet, it is unclear whether CCs establish more successfully in mixtures than in pure stands, and whether a better establishment results in greater biomass production that enhances ecosystem services. Objective: We aimed to: i) analyze seedling emergence dynamics, final emergence rates, and emergence vigor (i. e., speed of emergence) in CC mixtures vs. pure stands; ii) determine the relationship between seedling establishment success and final biomass production; and iii) evaluate the effect of CC mixtures vs. pure stands on soil cover, weed suppression, nitrogen (N) catch crop, and N green manure services. Methods: A 2-year field experiment (2020-2022) was conducted in Southwestern France, testing 11 pure stands and six two-species mixtures of brassicas, legumes, and grasses. CCs were sown in autumn and grown for eight months, with a fallow treatment as control. Data were analyzed using analysis of variance. Results: Significant intra-(p < 0.001) and inter-annual (p < 0.001) variability was observed in CC seedling emergence dynamics. Brassica CCs showed the highest emergence vigor (77 ± 21 • Cd), and their establishment success was positively correlated with final biomass yield (0.4 ± 0.2-8.6 ± 0.6 t.ha -1 ; r = 0.61, p < 0.001). In contrast, legumes, such as faba bean, showed the lowest emergence vigor (147 ± 52 • Cd), and their biomass yield (3.1 ± 0.1-6.8 ± 0.4 t.ha -1 ) depended mainly on post-establishment climatic conditions. Seedling emergence vigor and establishment success did not differ significantly between CC mixtures and pure stands. Single species CC yielded more variable biomass between years, mixtures produced more stable yields (2.1 ± 0.1-9.9 ± 0.3 t. ha -1 ). Soil cover was similar between CC pure stands (75.0 ± 0.0-100.0 ± 0.0 %) and mixtures (66.7 ± 5.3-100.0 ± 0.0 %), whereas poor establishment reduced soil cover (25.0 ± 7.9-50 ± 0.0 %). All CCs effectively suppressed weeds (up to 100 % reduction in biomass) and supplied N through scavenging and/or green manuring (up to 203 ± 18 kgN.ha -1 ) compared to fallow. Implications: In systems dominated by monocultures or short rotations under high-input management and climatic uncertainty, Brassicaceae-Fabaceae mixtures represent a promising option to ensure good establishment, stable biomass production, and delivery of key ecosystem services
Simulation numérique directe de la combustion d'une particule d'aluminium isolée sous divers environnements
No full textThe authors acknowledge the French Defense Agency for funding L.P.’s scholarship and CALMIP supercomputing centre in Toulouse (France) for providing us computational resources.International audienceThis study presents a comprehensive numerical investigation of single aluminum particle combustion under varying convective oxidizing flow conditions, using Direct Numerical Simulations. A three-dimensional, boundary-layer-resolved model is developed to capture the complex interplay of gas-phase chemistry, surface reactions, and multiphase transport phenomena. The model incorporates aluminum evaporation, aluminum suboxide reactions at the particle's surface, and alumina formation both on the surface and in the gas phase. It also introduces an original scheme to account for the dissolution of alumina into the molten particle, based on parameters derived from molecular dynamics simulations. The model was validated against experimental burn time data. The unsteady combustion of a 125 μm-aluminum particle in various flowing O2/N2 conditions is then investigated in terms of standoff flame distance, gas-phase temperature and chemistry, particle temperature and surface chemistry. The results demonstrate that gas-phase reactions remain the dominant source of heat release, although surface reactions, particularly under highly oxygenated environments, play a significant role in modulating local combustion kinetics. The formation of liquid alumina at the particle's surface, its partial dissolution into the molten aluminum, and the limited surface coverage even at high O2 concentrations highlight the importance of coupling surface chemistry with thermal transport. While this mathematical model successfully reproduces the main macroscopic characteristics such as flame temperature, burn time-radius relationship, gas-phase composition, and fluxes, some discrepancies appear near the particle surface, i.e. at the microscale. These deviations can be attributed to radiative heat transfer effects which are not considered or to an incomplete understanding of surface reactions
Encapsulating textual contents into a MOC data structure for advanced applications
No full textInternational audienceThe Multi-Order Coverage map (MOC) is a widely adopted standard promoted by the International Virtual Observatory Alliance (IVOA) to support data sharing and interoperability within the Virtual Observatory (VO) ecosystem. This hierarchical data structure efficiently encodes and visualizes irregularly shaped regions of the sky, enabling applications such as cross-matching large astronomical catalogs, visualizing multi-wavelength and multi-messenger surveys, and facilitating collaborative research through seamless interoperability in big-data-driven exploration. This study aims to explore potential enhancements to the MOC data structure by encapsulating textual descriptions and semantic embeddings into sky regions. Specifically, we introduce “Textual MOCs”, in which textual content is encapsulated, and “Semantic MOCs” that transform textual content into semantic embeddings. These enhancements are designed to enable advanced operations such as similarity searches and complex queries and to integrate with generative artificial intelligence (GenAI) tools to improve context-aware interactions and response accuracy in astronomical data analysis, and support agent-based applications. We experimented with Textual MOCs by annotating detailed descriptions directly into the MOC sky regions, enriching the maps with contextual information suitable for interactive learning tools. For Semantic MOCs, we converted the textual content into semantic embeddings, numerical representations capturing textual meanings in multidimensional spaces, and stored them in high-dimensional vector databases optimized for efficient retrieval. The implementation of Textual MOCs enhances user engagement by providing meaningful descriptions within sky regions, facilitating the development of effective game-based learning. Semantic MOCs enable sophisticated query capabilities, such as similarity-based searches and context-aware data retrieval, enhancing astronomical data analyses. Integration with multimodal generative AI systems allows for more accurate and contextually relevant interactions supporting both spatial, semantic and visual operations for advancing astronomical data analysis capabilities. Through straightforward examples, we discuss the fundamentals of this new experimental implementation
Induction of human cytochrome P450 enzyme activities by metabolism disrupting chemicals in the hepatic cell line HepaRG
No full textInternational audienceMetabolism disrupting chemicals (MDCs) are a class of endocrine disrupting substances that promote metabolic changes leading to metabolic disorders in humans. Central to assessing their adverse effects is the need to better understand their modes of action (MoA). Cytochrome P450 (CYP) enzymes play a major role in xenobiotic metabolism, but also catalyse many endogenous metabolic reactions. Therefore, modulation of CYP functionality may impact homeostasis, contributing to adverse outcomes. At the functional level, alteration of the activity of human CYPs J o u r n a l P r e -p r o o f by MDCs largely remains unexplored. In this study we investigated the capability of six candidate MDCs, bisphenol A (BPA), perfluorooctanoic acid (PFOA), tributyltin (TBT), dichlorodiphenyldichloroethylene (p,p'-DDE), triclosan (TCS) and triphenylphosphate (TPP) to induce CYP1A2, CYP2B6 and CYP3A4 activities in the human hepatic HepaRG cell line. The CYP induction test method previously validated for pharmaceuticals was optimised and selected MDCs were tested in the context of the European Horizon 2020 GOLIATH project. Induction was revealed using a cocktail of CYP-selective probe substrates, followed by probe metabolite quantification by mass spectrometry. All MDCs except TCS induced CYP activities. PFOA, TBT, p,p'-DDE and TPP induced CYP1A2, TPP being the most potent inducer. BPA, PFOA, TBT and TPP induced CYP2B6, PFOA being the most potent inducer. BPA, PFOA, TBT, p,p'-DDE and TPP all induced CYP3A4, p,p'-DDE and BPA being the most potent inducers. These results highlight the capability of candidate MDCs to induce key CYP activities in a human hepatic relevant model, paving the way for a better understanding of MDCs mechanisms of action