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Heat exchange and thermal interactions of twin energy tunnels in sand
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Enhancing the hydrological performance of Low Impact Development infrastructure through earthworm activity and vegetation dynamics for mitigating urban flooding
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une explication approfondie du rôle des polymères dans la synthèse en vrac du fluorure de magnésium (MgF₂) pour la fluoration du 2-chloropyridine
No full textInternational audienceMgF 2 is one of the most active catalysts for the Cl/F exchange in the transformation of 2‐chloropyridine. This study presents a more environmentally friendly and straightforward method for preparing bulk MgF 2 nanoparticles (NP) in aqueous solution. The presence of a structuring agent such as PMMA or Pluronic F68 as polymers, leads to a higher specific surface area after HF treatment (around 30%). It contributed to its preservation under hydrogen fluoride, reflecting the operating conditions for the fluorination of 2‐chloropyridine. Regarding the catalytic activity, no change was observed for NP MgF 2 synthesized in water with or without microwave heating. In contrast, an increase (around 20%) in activity for the transformation of 2‐chloropyridine was noted when a polymer was used during the preparation correlating with an increase of the specific surface area
Aging is modifiable: current perspectives on healthy aging in companion dogs and cats
No full textInternational audienceA ge is the most important cause of disability, dis- ease, and death in companion cats and dogs. The main proximate cause of death for these pets is euthanasia. 1,2 The lifespan of pets is therefore limited not only by disease, but also by caregivers' perceptions of discomfort, disability, poor quality of life, and advanced age, 3 as well as the caregiver's burden in terms of financial costs, logistical difficulties, affective/relational discomfort, guilt, and uncertainty. 4 The aging process has been defined as a "universal, irreversible, continuous, intrinsic, deleterious process that manifests itself in the form of a gradual</div
Unveiling the performance of ultrathin bimetallic Co<sub><i>x</i></sub>Ni<sub>1-<i>x</i></sub>(OH)<sub>2</sub> nanosheets for pseudocapacitors and oxygen evolution reaction
No full textInternational audienceThe rational design of highly efficient and stable electrodes is necessary for energy storage and electrocatalysis. Herein, we developed a nanometre thin bimetallic ultrathin CoxNi1−x(OH)2 nanosheet with a large lateral size by the ionic layer epitaxy (ILE) technique as an efficient bifunctional electrode material for pseudocapacitors and the oxygen evolution reaction. Its electrochemical performance was readily tuned by controlling the Co/Ni ratio. The nanosheet with a 1 : 3 Co : Ni ratio (termed Co1Ni3-NS) showed an excellent volumetric (areal) capacitance of 3783 F cm−3 (3 mF cm−2) at 0.3 mA cm−2 with 336 mW h cm−3 energy density at 256 W cm−3 power density and excellent stability, substantially outperforming other monometallic and bimetallic NSs. Moreover, as an electrocatalyst, Co1Ni3-NS delivered a lower overpotential (η10 = 318 mV) and Tafel slope (61 mV dec−1) in an alkaline environment. In situ Raman spectroscopy was employed to demonstrate the dynamic structural evolution of the catalyst during the OER process. Furthermore, DFT investigations further revealed that Co1Ni3-NS is a promising electrode with higher quantum capacitance and lower overpotential compared to other Co/Ni ratios. These findings pave a new way for controlled synthesis of highly efficient, bimetallic, and bifunctional electrode materials for pseudocapacitors and the OER
Modeling Complex Semantics Relation with Contrastively Fine-Tuned Relational Encoders
No full textInternational audienceModeling relationships between concepts and entities is essential for many applications. While Large Language Models (LLMs) capture relational and commonsense knowledge effectively, they are computationally expensive and often underperform in tasks requiring efficient relational encoding, such as relation induction, extraction, and information retrieval. Despite advancements in learning relational embeddings, existing methods often fail to capture nuanced representations and the rich semantics needed for high-quality embeddings. In this work, we propose different relational encoders designed to capture diverse relational aspects and semantic properties of entity pairs. Although several datasets exist for training such encoders, they often rely on structured knowledge bases or predefined schemas, which primarily encode simple and static relations. To overcome this limitation, we also introduce a novel dataset generation method leveraging LLMs to create a diverse spectrum of relationships. Our experiments demonstrate the effectiveness of our proposed encoders and the benefits of our generated dataset
Shifting preferences: COVID-19 and higher education application
No full textInternational audienceThis study provides descriptive evidence on how the COVID-19 pandemic influenced secondary school students’ application patterns to higher education in France, offering insights into the reallocation of preferences across academic fields and degree types. Using detailed administrative data, we document significant shifts in application shares during 2021, with increased interest in competitive tracks and concurrent declines in applications to bachelor’s and vocational programs. These findings suggest that students responded to the pandemic by favouring structured and selective pathways with clear labour market prospects, moving away from generalist degrees. Students’ share of applications to STEM degrees increased, while applications to health and business programs remained stable. We then analyse the probability of applying to at least one program in a given field or degree and find a decline in application diversification: students narrowed their choices to fewer fields, reflecting a more risk-averse and selective approach in response to the pandemic. Our analysis highlights substantial heterogeneity in these effects across demographic groups
Improved generality of wheat green LAI models through mitigation of the effect of leaf chlorophyll content variation with red edge vegetation indices
No full textInternational audienceThe retrieval of wheat green leaf area index (LAIG) from satellite imagery is critical for monitoring crop growth and assessing food security. Numerous vegetation indices (VIs) derived from spectral reflectance have been widely used to estimate LAIG. In particular, red edge VIs can mitigate the confounding effect of multiple factors, such as the soil background and leaf inclination angle variation, and typically are highly correlated with LAIG. However, their relationship to LAIG tends to be affected by variations in leaf chlorophyll content (LCC), because the position of the red edge of vegetation spectra shifts with changes in LCC. This issue directly limits the operational use of VI-LAIG models, especially those employing red-edge bands. Therefore, to reduce the sensitivity of VI-LAIG relationships to LCC variation, this study proposed an innovative approach, called the Difference Combination between Spectral Indices (DCSI). Using synthetic data simulated with the PROSAIL radiative transfer model, we tested the dependence of the algebraic difference between common VIs on LCC. The results show that many combinations of VIs are insensitive to LCC variation. The newly developed DCSI combination between the Sentinel-2 red edge position (S2REP) and B6-red edge band (RE2) (i.e., DCSI(S2REP&RE2)), produces the most accurate LAIG model when LCC varies. We also modified the constant of this DCSI combination, to develop the Sentinel-2 modified red edge position (S2MREP) for LAIG retrievals. In comparison to traditional VI-LAIG models, the S2MREP-LAIG model has higher accuracy, with Rcal2 of 0.76 in calibration, and in validation Rval2 of 0.72 and RRMSE of 23.61 %. In addition, the S2MREP-LAIG model (RRMSE=28.64 %) also outperforms the existing Sentinel-2 LAI product (RRMSE=38.20 %) in the retrieval of wheat LAIG. In summary, the proposed DCSI approach and S2MREP effectively mitigate the impact of LCC variations on LAIG retrievals, thus facilitating the large-scale retrieval of LAIG and the spatial mapping of wheat LA
Evaporation-Induced Reticular Growth of UiO-66_NH2 in Chitosan Films: Adsorption of Iodine
No full textInternational audienceMetal–organic frameworks (MOFs) combined with polymers as hybrid materials offer numerous advantages such as enhanced performances through synergistic effects at their interface. The primary challenge in developing polymer/MOF hybrid matrix films is ensuring optimal dispersion and strong adhesion of crystalline MOFs to the polymer without aggregation, weak interaction, or phase separation. In this study, hierarchically porous UiO-66_NH2/chitosan (ZrCSx-f) films were designed by crystallizing UiO-66_NH2 within a chitosan (CS) skeleton. The resulting ZrCSx-f films displayed remarkable homogeneity with high loadings of UiO-66_NH2 crystals, up to 45 wt %, coupled to a high adsorption capacity of iodine in gas phase, up to 317 mg.g–1