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Le projet européen ACTIVATE (2025-2028). Sur les traces des archives de l’engagement politique et social en Europe (XIXe-XXIe s.)
No full textInternational audienceÀ l’heure où les démocraties européennes se voient fragilisées, voire remises en cause dans un contexte international d’une extrême tension, il paraît essentiel de rappeler l’importance de la conservation, préservation et valorisation du patrimoine culturel européen que représentent les archives de l’engagement politique et social, du XIXe siècle à nos jours. Le projet Marie Skłodowska-Curie Staff Exchanges ACTIVATE (The Activist, the archivist and the researcher: novel collaborative strategies of Transnational research, archiving and exhibiting social and political dissent in Europe [19th -21st century]), est né de cette urgence. Lancé au 1er janvier 2025 pour une durée de quatre ans, il a pour objectif de favoriser des échanges entre partenaires venant du monde académique et non-académique, autour d’un projet de recherche commun et ce à l’échelle européenne. L’ambition est de contribuer à une réflexion qui fait dialoguer chercheuses et chercheurs, archivistes et militant·es autour des enjeux des archives sur les mobilisations de la société civile en Europe, en étroite relation avec les espaces non européens
SWOT Enhances Small‐Scale Eddy Detection in the Mediterranean Sea
No full textInternational audienceOcean currents are crucial in regulating Earth's climate, with a significant impact in the distribution of ocean properties. During the Calibration/Validation phase of the Surface Water and Ocean Topography (SWOT) satellite mission, we performed a high‐resolution, multi‐platform experiment to evaluate SWOT's ability to resolve small‐scale features, focusing on a ∼25 km‐radius anticyclonic eddy in the Western Mediterranean Sea. Acoustic Doppler Current Profiler (ADCP) recorded maximum velocities of 30 cm/s at 155 m depth and underwater glider data identified biconvex isopycnals, classifying the eddy as intrathermocline. SWOT successfully captured the sea level signal and surface geostrophic currents of the eddy, showing notable error reduction over conventional altimetry: 24% in sea level representation compared to glider observations, and 35% and 31% in horizontal velocity magnitude compared to Acoustic Doppler Current Profiler and drifter measurements, respectively. This study highlights SWOT's potential in resolving small‐scale ocean dynamics
Modelling of relative velocity, velocity fluctuations and their interactions for two-fluid models by Stationary Action Principle
No full textThe objective of this contribution is the derivation of a two-fluid model including a relative velocity between the two phases and velocity fluctuations, describing pseudo-turbulent effects, as internal variables based on Stationary Action Principle. The variational derivation, used to obtain the model, relies on the variation of a single trajectory related to the mass-weighted average velocity under the barotropic assumption. The model is hyperbolic, satisfies a second principle of thermodynamics, and admits either linearly degenerate or genuinely nonlinear characteristic fields. Moreover, the variational approach yields a fully closed model and its non-conservative products are uniquely defined for weak solutions in 1D, i.e. jump conditions can be derived. In the laminar case, when velocity fluctuations are negligible, we recover previously derived multi-fluid models which have been analyzed in several contributions. As such, the present framework allows for an original extension of the existing models to include velocity fluctuations of each phase for pseudo-turbulent flows, their coupling with the relative velocity between phases, as well as dissipative effects compatible with the thermodynamics of irreversible processes. Eventually, we provide a discussion of the limitations of the proposed model, especially regarding the extension to the open problem of non-barotropic flows
The In Ezzane volcanic field (Eastern Hoggar, Algeria) and its enigmatic circular structures
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High-performance mixed matrix membranes with very-high ZIF-8 loading for efficient CO2 capture
No full textInternational audienceAddressing the challenges of climate change and global warming, membrane separation processes are considered as innovative industrial solutions. Among different membrane materials, mixed matrix membranes are very promising for CO2 capture. In this work, a segmented poly(urea-imide) with high poly(ethylene oxide) content (70 % wt) was selected as a new rubbery polymer matrix and was doped with the metal organic framework ZIF-8. The new polymer matrix and the optimization of the “priming” method enabled to obtain very high ZIF-8 loadings up to 70 % vol. Various physicochemical methods were used to study the influence of filler/polymer interactions on the membrane's morphology. The CO2 and N2 permeation properties were evaluated by time-lag measurements for both pure gases under standard conditions for CO2 post-combustion capture (2 bar and 35 °C). Very promising membrane performances were achieved for the highest ZIF-8 loading (70 % vol) with a strong increase of the CO2 permeability PCO2 = 471 Barrer (x 8.5 compared to the pristine polymer) and a relatively high ideal selectivity αCO2/N2 = 30.2. The modeling of the MMM's performances was successfully achieved with Maxwell model up to high ZIF-8 content (60 % vol)
Characterization of Extracellular Vesicles at Parturition in Dairy Cows with Late Gestation Heat Stress
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A Distributed Inference Algorithm for Dirichlet Process Mixture Models with Exponential Family Components
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Quantification of CO<sub>2</sub> hotspot emissions from OCO-3 SAM CO<sub>2</sub> satellite images using deep learning methods
No full textInternational audienceThis paper presents the development and application of a deep-learning-based method for inverting CO 2 atmospheric plumes from power plants using satellite imagery of the CO 2 total column mixing ratios (XCO 2 ). We present an end-to-end convolutional neural network (CNN) approach, processing the satellite XCO 2 images to derive estimates of the power plant emissions, that is resilient to missing data in the images due to clouds or to the partial view of the plume owing to the limited extent of the satellite swath.The CNN is trained and validated exclusively on CO 2 simulations from eight power plants in Germany in 2015. The evaluation on this synthetic dataset shows an excellent CNN performance with relative errors close to 20 %, which is only significantly affected by substantial cloud cover. The method is then applied to 39 images of the XCO 2 plumes from nine power plants, acquired by the Orbiting Carbon Observatory-3 Snapshot Area Maps (OCO3 SAMs), and the predictions are compared to average annual reported emissions. The results are very promising, showing a relative difference in the predictions to reported emissions only slightly higher than the relative error diagnosed from the experiments with synthetic images. Furthermore, analysis of the area of the images in which the CNN-based inversion extracts the information for the quantification of the emissions, based on integratedgradient techniques, demonstrates that the CNN effectively identifies the location of the plumes in the OCO-3 SAM images. This study demonstrates the feasibility of applying neural networks that have been trained on synthetic datasets for the inversion of atmospheric plumes in real satellite imagery from XCO 2 and provides the tools for future applications
Using Wastewater to Monitor Suggested Changes in Dietary Intake: A Participatory Experiment
No full textInternational audienceThis study aimed to assess the feasibility of a participatory experiment involving residents of a Paris district, in which their dietary habits were monitored through the analysis of chemicals in wastewater. Unlike conventional sociological metrics, wastewater can be used to monitor the behavior of the entire population, regardless their participation, with an almost 100% response rate. The results revealed changes in the chemistry of wastewater during the experimental week, when residents were encouraged to consume "more fruits and vegetables”. A key challenge lies in understanding the possible influence of confounding factors that could affect the chemical dynamics and thus impact the results. These factors were also evaluated. For the first time, wastewater has demonstrated its potential as a monitoring medium for participatory experiments addressing issues of diet and health, which are critical components in shaping the trajectory of sustainable urban living for the future
