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Lactation persistency of dairy cows fed low metabolizable protein diets with two different starch contents and degradability levels crossed with rumen-protected amino acid supplies
No full textInternational audienceReducing the CP and MP content of diets allows to improve dairy cow nitrogen and MP efficiencies. However, when CP ( 13-14%) and MP (95 g/kg DM of Protein Digestible in the Intestine, PDI) contents are reduced, DMI, milk yield and milk component secretion generally decrease. Improving the balance of nutrient supplies (such as starch or AA) could limit these decreases in milk secretions. These effects have been tested during short-term experiments. The aim of our study was to analyze the effects of increasing the bypass starch content or better balancing AA supplies through rumen-protected AA (RP-AA: Lys, Met, and His), on lactation persistency and milk component secretions when the treatments were applied to Holstein dairy cows from 56 to 183 DIM. Forty-four dairy cows were assigned randomly to four groups according to a factorial arrangement of the four treatments (LSHDAA-: Low Starch High Degradable in the rumen without any AA supplementation; LSHDAA+: LSHD with RP-AA supplementation; HSLDAA-: High Starch Low Degradable in the rumen without RP-AA supplementation, and HSLDAA+: HSLD with RP-AA supplementation). Increasing the bypass starch content led to increases in milk yield through lactose and milk protein yield with starch time interactions: lactation persistency improved, as did all milk component secretions in HSLD vs. LSHD treatments. Increasing bypass starch slightly increased MP intake but decreased NEL intake. No changes in BCS and plasma insulin were observed when the bypass starch content was increased, probably because NEL content decreased. However, BW increased over time with a tendency to be higher with the higher bypass starch content. In addition, increasing bypass starch or RP-AA intakes increased Metabolic Energy (ME) efficiency (i.e. Milk Energy/ME). Increasing RP-AA supplies increased plasma Lys and Met concentrations, but the concentrations of plasma His only increased on LSHD. Milk protein yield as well as milk protein content and fat yield increased with RP-AA supplementation without any interaction with time. However, significant starch AA time interactions were observed for lactose and fat yields. These interactions mainly reflected lower lactation persistency and slopes of milk components in LSHDAA- than under the three other treatments. Interestingly, LSHDAA- corresponded to the lowest plasma His concentration compared to LSHDAA+, HSLDAA- and HSLDAA+. In multiparous cows (n = 32; 8 per dietary treatment), higher mammary cell proliferation, as measured by PCNA staining, was observed with both the HSLD vs. LSHD and the AA+ vs. AA- diets; however, only the two HSLD vs. LSHD diets gradually increased DMI and consequently whole nutrient supplies to sustain the higher milk persistency. Under a low MP content diet, the LSHDAA- diet proved to be a highly restrictive option for preserving lactation persistency; conversely, increasing the bypass starch content without increasing the NEL content appeared to be a promising solution to counter this negative effect on lactation persistency. Taking account of the type of nutrients (Starch or AA and specifically His) absorbed in dairy feeding systems seems important when reducing the MP supply
Gravitational Wave Scattering in Spinless WQFT
No full textInternational audienceWe develop the computational framework for gravitational wave - black hole scattering in worldline quantum field theory (WQFT) without spin. Crucially, we prove on general grounds that, in the absence of dissipation, the exponential representation of the -matrix maps -- through a partial-wave transformation -- directly onto the scattering phase shift from black hole perturbation theory (BHPT), indicating an exponentiation of the WQFT amplitude itself in partial-wave space. Computing explicitly, we reproduce the BHPT phase shift without spin up to from WQFT. While this result is expected, it lays the groundwork for higher-precision analyses involving non-minimal effects. Along the way, we outline our efficient diagram generation technique and include a pedagogical discussion on the computation of the required two-loop integrals
Les apports des textes du 5 janvier 2026 sur la commercialisation à distance de services financierss
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Analyse vidéographique de la motricité spontanée du nouveau-né et de l'enfant
No full textThe analysis of spontaneous motor activity in infants enables the early identification of neuromuscular and neurological disorders, providing a crucial tool for the diagnosis and management of severe diseases such as Spinal Muscular Atrophy (SMA). The clinical evaluation of this motor activity currently relies primarily on practitioners' expertise, highlighting the need for automated approaches based on video analysis and artificial intelligence.In this context, this thesis builds upon an initial proof of concept demonstrating the feasibility of video-based analysis for SMA detection. This preliminary work identified major methodological challenges, particularly the need for more robust data acquisition and improvements in movement extraction and analysis methods.The core focus of this thesis is addressing these challenges. Tools have been developed to structure and enhance a dedicated database while exploring new feature extraction and machine learning methodologies tailored to infant motor analysis. These methodological advances pave the way for broader clinical applications and strengthen the use of video analysis as a tool for the early diagnosis of motor disorders in infants.L'analyse de l'activité motrice spontanée chez le nourrisson permet d'identifier précocement des troubles neuromusculaires et neurologiques, offrant ainsi un levier essentiel pour le diagnostic et la prise en charge de maladies graves, comme l'Amyotrophie Spinale Infantile (ASI). L'évaluation clinique de cette motricité repose aujourd'hui principalement sur l'expertise des praticiens, soulignant l'intérêt d'approches automatisées basées sur l'analyse vidéo et l'intelligence artificielle.Dans ce contexte, cette thèse s'appuie sur une première preuve de concept démontrant la faisabilité de l'analyse vidéographique pour la détection de l'ASI. Ce travail initial a permis d'identifier des défis méthodologiques majeurs, notamment la nécessité d'une acquisition de données plus robuste et l'amélioration des méthodes d'extraction et d'analyse du mouvement.L'essentiel de cette thèse porte ainsi sur la réponse à ces problématiques. Des outils ont été développés pour structurer et enrichir une base de données dédiée, tout en explorant de nouvelles méthodologies d'extraction de caractéristiques et d'apprentissage automatique adaptées à l'analyse de la motricité infantile. Ces avancées méthodologiques ouvrent la voie à des applications cliniques plus larges et contribuent à renforcer l'utilisation de l'analyse vidéo comme outil d'aide au diagnostic précoce des troubles moteurs chez les nourrissons
First Detection of the Baryon Acoustic Oscillation (BAO) Feature in the 3-Point Correlation Function of DESI DR1 Luminous Red Galaxies
No full textInternational audienceWe present the first detection of the 3-Point Correlation Function (3PCF) Baryon Acoustic Oscillation (BAO) signal from the DESI Data Release 1 (DR1) sample of Luminous Red Galaxies (LRGs), which contains over 2.1 million galaxies. Our analysis is based on a tree-level redshift-space bispectrum template, which is then transformed to position space using the Fast Fourier Transform on Logarithmic scales (FFTLog) algorithm. We detect the BAO feature with a significance of approximately using the EZmock covariance matrix and using the analytical covariance matrix, for the full LRG redshift range (), denoted as the sample. We use the Abacus altMTL mocks, the most precise DESI DR1 mock catalogs currently available, to validate our model. We find that our model fits the mocks well, with a small offset of in the recovered BAO scale, which we treat as a systematic error due to modeling. We measure the angle-averaged distance, ( precision) when using the covariance matrix estimated from EZmocks and ( precision) when using the analytical Gaussian covariance matrix. Our results show excellent agreement with the DESI DR1 2PCF BAO measurements as well. We also explore several other ways to estimate the error and find between -- precision on the BAO scale from the EZmock covariance matrix and between -- precision from the analytical covariance matrix. This work represents the first detection of the BAO feature in the DESI 3PCF, establishing its ability to probe the expansion history of the Universe with future DESI 3PCF measurements
Reaching the quantum noise limit for interferometric measurement of optical nonlinearity in vacuum
No full textInternational audienceQuantum Electrodynamics predicts that the vacuum must behave as a nonlinear optical medium:the vacuum optical index should increase when vacuum is stressed by intense electromagnetic fields.The DeLLight (Deflection of Light by Light) project aims to measure it by using intense and ultra-short laser pulses delivered by the LASERIX facility at IJCLab (Paris-Saclay University). Theprinciple is to measure by interferometry the deflection of a low-intensity probe pulse when crossingthe vacuum optical index gradient produced by an external high-intensity pump pulse. The detectionof the expected signal requires measuring the position of the interference intensity profile with a highspatial resolution, limited by the ultimate quantum noise. However, the spatial resolution is highlydegraded by the phase noise induced by the mechanical vibrations of the interferometer. In order tosuppress this interferometric phase noise, we have developed a new method, named High-FrequencyPhase Noise Suppression (HFPNS) method, based on the use of a delayed reference signal to correctany noise-related signal appearing in the probe beam. In this work, we present the experimentalvalidation of this novel method. The results demonstrate a robust path toward picometer-scalesensitivity and provide a key step toward the observation of QED-induced vacuum refraction
Atomistically-informed cross-slip and slip-system transition modeling in uranium dioxide
No full textInternational audienceUnderstanding the mechanical behavior of uranium dioxide (UO2) at high-temperature is essential for assessing the structural integrity of nuclear fuel under reactor operating conditions. The pronounced plastic anisotropy observed in UO2 single crystals is believed to originate from the complex behavior of 1/2<110> screw dislocations and their ability to cross-slip between the various slip modes of the fluorite structure, as initially suggested by Sawbridge and Sykes more than fifty years ago. However, direct evidence supporting this hypothesis, either from atomicscale simulations or transmission electron microscopy, has so far been lacking, leaving the microscopic origin of cross-slip and its possible contribution to the plastic anisotropy unresolved. In this work, we combine molecular dynamics, theoretical modeling and discrete dislocation dynamics simulations to investigate the mobility of the 1/2<110> screw dislocation in UO2 as a function of temperature, stress and orientation. Atomistic simulations reveal that above ∼1500 K, the 1/2<110> screw dislocation progressively transitions from planar glide in {001} or {110} slip systems to frequent cross-slip in 1/2<110>{111}, ultimately leading to a full slip-system transition near 1700 K. This behavior correlates with a temperature-induced reorganization of the dislocation core, from a configuration electrostatically-confined within {001} to a {111} spreading state as the oxygen sublattice disorders. An atomistically-informed stochastic model of cross-slip and slip-system transition is then formulated and implemented in the discrete dislocation dynamics simulation, successfully reproducing atomistic simulations, experimental slip traces and the plastic anisotropy trends observed in UO2
Correlated release between Caesium and fission gases during LOCA type scenario
No full textInternational audienceDue to the potential significant radiological impact of fission products release out of the fuel rod, experimental data are needed both to mitigate the consequence and better understand fuel behavior LOCA type accidents. Numerous results exist on fission gas release and fuel fragmentation, enabling accurate modeling of these phenomena. However, data remain very limited on the behavior of volatile fission products such as caesium and iodine. To this end, heat treatments designed to improve understanding of the mechanisms associated with the release of volatile fission products were carried out on high-burnup UO2 fuel in the MERARG facility (LECA-STAR, CEA Cadarache), applying thermal ramps of 0.2°C/s up to 1,200°C. The release kinetics of several radionuclides (Kr, Xe, Cs, He) was measured online by gamma spectrometry and gas chromatography. Moreover, a camera was used to monitor on-line the evolution of the fuel surface. Specific filters were located at the top of the furnace to collect the released aerosols, at 900 and 1,200°C, which correspond to characteristic fission gases burst release. After the test, filters were analyzed by gamma spectrometry, SEM, EPMA, SIMS, and TEM. These experiments revealed correlated burst release of both fission gases and caesium in terms of kinetics. Each burst is also correlated with the appearance of new liquid phases on the fuel surface. These observations suggest the existence of a caesium release reservoir common to that of fission gases. Finally, analysis of filters also revealed the presence of iodine associated with caesium. These results represent a major advance in characterizing the release of volatiles fission products and in understanding the mechanisms behind the release of gases at these temperature levels
Subject fingerprinting and task classification rely on distinct functional connectivity features
No full textInternational audienceFunctional connectivity (FC) measured by functional magnetic resonance imaging (fMRI) has been shown to be a marker of individual brain characteristics, and also to reflect cognitive tasks. However, it remains unclear how the choice of FC measures affects the encoding of both subject and task properties. We address this question using a high-quality deepphenotyping dataset consisting of multiple naturalistic tasks (listening to a story, watching three different movies and playing a video game) and resting-state, while working on two classification problems: subject fingerprinting and task classification. We compare the performance of a combination of two FC measures and three covariance estimation methods. We then examine the similarity and subject specificity of FC across tasks and with structural connectivity (SC). We find that sparse partial correlation, obtained from the Graphical-Lasso estimator, performs best in subject identification tasks and is most similar to SC; it stands out as a marker of identity. In contrast, task information is better captured by Pearson correlation measures, as they account for distributed brain activity. Overall, we find that pairwise interactions captured by partial correlation are optimal for fingerprinting, while multi-way relationships underlying full correlation are an accurate marker of cognitive function
Exploring the human small intestinal luminal microbiome via a newly developed ingestible sampling device
No full textInternational audienceBecause accessing the small intestine is technically challenging, studies of the small intestinal microbiome are predominantly conducted in patients rather than in healthy individuals. Invasive clinical procedures, such as endoscopy or surgery, usually performed for therapeutic purposes, are typically required for sample collection. Although stomas offer a less invasive means for repeated sampling, their use remains restricted to patient populations. As a result, the small intestinal microbiome of healthy individuals remains largely understudied. This study evaluated a novel ingestible medical device for collecting luminal samples from the small intestine. A monocentric interventional trial (NCT05477069) was conducted on 15 healthy subjects. Metagenomics, metabolomics, and culturomics were used to assess the effectiveness of the medical device in characterizing the healthy small intestinal microbiome and identifying potential biomarkers. The small intestinal microbiota differed significantly from the fecal microbiota, displaying high inter-individual variability, lower species richness and reduced alpha diversity. A combined untargeted and semi-targeted LC-MS/MS metabolomics approach identified a distinct small intestinal metabolic footprint, with bile acids and amino acids being the most abundant metabolite classes. Host-and host/microbe-derived bile acids were particularly abundant in small intestinal samples. Using a fast culturomics approach on two small intestinal samples, we achieved species-level characterization and identified 90 bacterial species, including five potentially novel ones. This study demonstrates the efficacy of our novel sampling device in enabling comprehensive small intestinal microbiome analysis through an integrative, multi-omics approach. This approach allows distinct microbiome signatures to be identified between small intestinal and fecal samples.</div