Portail "HAL-Francophonie Afrique et Océan Indien"
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LE DISCOURS CHINOIS A L'EGARD DE L'AFRIQUE : Analyse discursive de la coopération sino-africaine à travers le
No full textInternational audienceDéclaration de divulgation : L'auteur n'a pas connaissance de quelconque financement qui pourrait affecter l'objectivité de cette étude. Conflit d'intérêts : L'auteur ne signale aucun conflit d'intérêts.</div
Probabilistic Taylor-type expansions of functions
No full textTaylor-Young and Maclaurin' series are widely used for approximating smooth functions around a given point. This study investigates an unied stochastic framework for Taylor-type expansions of functions by means of independent random variables. The proposed probabilistic expansions of a function are able to incorporate evaluations of derivatives at dierent points, leading to a global approach. Exact expansions are obtained for any order of available derivatives, and such Taylor-type expansions enable the statistical inference of the remainder terms. It appears that the traditional Taylor-Young and Maclaurin series are particular cases of the proposed approach thanks to the Dirac probability measure, and guidelines for using Taylor' series have been enhanced. Dierent ways of choosing the optimal distributions of random variables are provided, particularly when truncations are applied. Numerical comparisons are provided as well.</div
Uncertainty sources in a large ensemble of hydrological projections: Regional Climate Models and Internal Variability matter
No full textInternational audienceMulti-scenario, multi-model ensembles of hydrological projections are widely used to describe possible futures of regional hydrology and inform adaptation strategies. The Explore2 dataset is such an ensemble of river flow projections in Metropolitan France. It provides future simulations for 1735 catchments with modeling chains composed of different hydrological models forced by 36 regional climate projections based on bias-adjusted EUROCORDEX simulations. This study assesses the uncertainties of this ensemble with QUALYPSO, a method specifically designed to deal with incomplete ensembles and to disentangle and quantify all uncertainty sources, including that due to internal variability. Focusing on results obtained at the end of the century, this study shows a strong agreement between modeling chains towards decreases in low flows in a large southern part of France for a high-emission scenario, and very uncertain changes for the annual mean and high flows. Emission scenario uncertainty is the dominant source of uncertainty for low flows over the whole of France, and for mean annual flows in southeastern France. The contribution of the global and regional climate models is important for mean and high flows, especially in rainfall-dominated areas. Regional climate models contribute considerable uncertainty to low flows, much more than global models. The contribution of hydrological model uncertainty is large for low flows, moderate for mean annual flows, and small for high flows. For all climate and hydrological indicators, internal variability is often large and cannot be overlooked. It is often of the same order and sometimes larger than the uncertainty on the climate change response
Decoding Tocopherol-Polyphenol interactions in oil-in-water emulsions through combined WIM-CAT and CV assays
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/616786/) * Autres projets (id;sigle;titre): 101158035;PassIon;(EU) High Performance and Large-Scale Electrodes for Selective Ion Recovery//International audienceThe antioxidant interactions of α- and γ-tocopherol with curcumin and quercetin were assessed in an oil-in-water emulsion using the WIM-CAT assay, a method integrating Weibull interaction modeling with the conjugated autoxidizable triene technique. Synergistic effects were strongest for γ-tocopherol with curcumin and for α-tocopherol with quercetin, particularly at low tocopherol concentrations (0.2 μM in emulsion, 380 ppm in oil) and high molar ratios (3:1). Increasing tocopherol concentration to 0.6 μM in emulsion (1140 ppm in oil) reduced synergy, likely reflecting pro-oxidant activity. The presence of ferrous ions accelerated oxidation but did not influence synergistic interactions, while acidic conditions reduced tocopherol pro-oxidation and modified the effects of curcumin and quercetin. Weibull modeling revealed isoform-dependent differences during the propagation phase of oxidation. Cyclic voltammetry further suggested that the synergy of α-tocopherol may involve antioxidant regeneration mechanisms, whereas γ-tocopherol appears to act through alternative redox processes. Together, kinetic and electrochemical analyses provide complementary insights into the conditions governing antioxidant interactions
Mechanisms driving mesoscale latent heat flux variations and mixed layer heat content evaluation in the Northwest Tropical Atlantic
No full textInternational audienceIn this study, a high-resolution ocean-atmosphere coupled simulation is used to assess the effects of sea surface temperature (SST), surface currents, and ocean vertical stratification on the spatial variability of latent heat flux (LHF) and the stability of the marine atmospheric boundary layer (MABL) in the Northwest Tropical Atlantic during January and February 2020. The analysis focuses on the ocean mesoscale (O(50–250 km)) across the Northwest Tropical Atlantic (referred to as the EURECA region in this study) and within three sub-regions characterized by different ocean dynamical regimes: Amazon, Downstream, and Tradewind. Results indicate that the coupling between SST and wind speed (and specific humidity) is stronger (weaker) in the Amazon and Downstream regions, influenced by the warm coastal North Brazil Current eddy corridor and the Amazon River plume, than in the Tradewind region, representative of the open ocean, consistent with previous remote sensing studies. Overall, warmer SSTs are associated with increased wind speeds and variations in specific humidity, deviating from Clausius–Clapeyron expectations. We interpret this as the result of active ocean processes modifying the near-surface atmosphere, enhancing vertical motion in the MABL, and transporting momentum and drier air from the free troposphere toward the surface. To further investigate the impact of mesoscale SST features on LHF, we apply a linear, SST-based downscaling method. Results show that these mesoscale SST structures induce a substantial increase in LHF, 46.8 Wm-2K-1 on average in the Amazon and Downstream regions (warm eddy corridor). In the Tradewind region, the LHF sensitivity to SST is smaller, at about 35 Wm-2K-1. For the Amazon region, of the 46.7 Wm-2K-1 change in LHF associated with SST, approximately 7.8 Wm-2K-1 is attributed to direct mesoscale SST changes (thermodynamic contribution), while the remainder is linked to mesoscale SST-induced modifications in near-surface atmospheric circulation (dynamic contribution), mainly due to the mesoscale SST-induced humidity undersaturation imbalances. The influence of surface currents on LHF is weaker, with deviations not exceeding 15 W m−2. Finally, we focus on the SST mesoscale anomalies linked to the Amazon freshwater plume. We find them to be persistent throughout the period of study affecting LHF by the mechanisms described above. Lateral advection and heat loss to the atmosphere tend to dilute them with their environment by the end of the period of study. This work underscores the importance of a regionalized approach to mesoscale air-sea interaction studies in the Northwest Tropical Atlantic, as LHF sensitivity to SST and surface currents exhibits strong spatial variability driven by distinct oceanic dynamics. Submesoscale LHF sensitivity to SST and currents is not addressed here and will be the subject of future research
Responsabilité du contractant à l'égard des tiers : une confirmation et beaucoup de questions !
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The microbial strategies for the management of chemical pesticides: A comprehensive review
No full textInternational audienceChemical pesticides considered as one of the emerging environmental contaminants that severally affect the human health and soil and water ecosystem. Despite their well-documented adverse effects on fruit quality, soil structure, the emergence of pesticide-resistant pests, and human well-being, chemical pesticides are still widely used for crop protection, particularly in developing countries. Although to manage the chemical pesticides, various traditional approaches have been employed, however the higher cost, and the generation of toxic residues have shifted research attention toward eco-friendly and sustainable bioremediation strategies. Microorganisms including the bacteria, fungi, and algae play a crucial role in pesticide degradation by transforming toxic compounds into less toxic forms. However, to optimize microbial bioremediation, a comprehensive understanding of microbial metabolism and physiology is essential. In this context, omics technologies such as genomics, metagenomics, transcriptomics, proteomics, and metabolomics, offer powerful tools for elucidating the molecular mechanisms involved in pesticide degradation. These approaches facilitate the identification of microorganism, key genes, enzymes, and metabolic pathways responsible for the breakdown of pesticide compounds and their by-products. Furthermore, advanced technology like the gene editing can enhance the efficacy of pesticides biodegradation by knocking out undesirable genes or introducing beneficial ones in the microorganisms. The Artificial intelligence also plays a significant role in analysing big data, understanding microbial communities' structure, identifying nature of pesticides and selecting or predicting the microbial species with enhanced pesticides degrading efficacy
A DGRF 2020 candidate model only based on Swarm ASM experimental vector mode data improved through a dedicated post-calibration strategy
No full textInternational audienceThe ESA Swarm satellites carry a magnetometry payload consisting of an absolute scalar magnetometer (ASM), a fluxgate vector magnetometer (VFM), and a set of star trackers (STR). The primary role of the ASM is to provide 1 Hz absolute field intensity measurements, while the VFM and STR provide the additional data needed to reconstruct the attitude of the vector field and produce the official nominal Swarm L1b magnetic data. Each ASM instrument, however, can be run in an experimental mode tosimultaneously produce its own self-calibrated 1 Hz vector data. Such 1 Hz experimental vector data have been routinely produced ever since launch on Swarm Alpha and Bravo, except during one-week periods every month when the burst mode was activated in yet another experimental mode to produce 250 Hz scalar data. These 1 Hz experimental vector data have been used to produce the only DGRF 2020 candidate model only relying on such data. All other candidate models relied on either nominal Swarm L1b data, or data from other satellites and ground observatories. In this paper we report on the way we built our DGRF candidate model and on the postcalibration strategy that we used to identify and remediate a calibration issue found in both the ASM and VFM vector data. We show that this post-calibration improves the quality of the data and contributes to also improving our DGRF candidate model. Our final candidate model, only based on post-calibrated ASM data, turns out to be one of the DGRF 2020 candidate models closest to the final official DGRF model, a posteriori providing evidence of both the quality of the Swarm ASM experimental vector mode data and the value of our post-calibration strategy. This post-calibration strategy could be used to improve magnetic data from other past, present or future missions
