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Magnetic Losses and Domain Wall Activities: A Study of Barkhausen Noise under Rotational Magnetization
No full textInternational audienceThis study investigates the magnetic Barkhausen noise (MBN) in non-oriented electrical steel under rotational magnetization conditions, focusing on its application to improve the understanding of magnetic losses and the behavior of ferromagnetic domains. MBN serves as a powerful tool for characterizing domain wall dynamics, and its use under rotational magnetization offers new insights into energy losses in electromagnetic devices. We developed an experimental setup to measure MBN under different levels of flux density and to compare the results with conventional alternating magnetization. For the first time, MBNenergy(H) hysteresis loops were plotted under rotational magnetization, offering unique perspectives on domain wall activity and domain structure kinetics. Our findings indicate a significant reduction in domain wall motion beyond a threshold magnetic flux density under rotational conditions. The differences observed between classical hysteresis loops and MBNenergy(H) loops under both unidirectional and rotational magnetization clarify the specific contributions of rotational magnetization, as well as the distinct roles of 180° and 90° domain wall motions
Geometry of Gauss digitized convex shapes
No full textInternational audienceThis paper studies how well we can infer the geometry of a (smooth or not) convex shape X from the convex hull Y h of its Gauss digitization with a given gridstep h. Without smoothness constraint, we first present results concerning the proximity of facet normal vectors to the shape normal vectors, as well as a relation between the number of lattice points just above a facet and its area. Then, further results can be obtained when X is smooth, that are valid in arbitrary dimension d. More precisely, we show that the boundary of Y h is Hausdorff-close to the boundary of X with distance less than √ dh, and that the vertices of Y h are even much closer (some O(h^(2d /d+1))). Finally we show that the geometric normal vectors to the facets of Y h tend to the smooth shape normals with a speed O(h^1/2 ), and the bound is tight
Omega-categorical groups and rings of finite dimension
No full textWe prove that a finite-dimensional omega-categorical group is finite-by-abelian-by-finite and that a finite-dimensional omega-categorical ring is virtually finite-by-null
Probing Fermi Energy and Temperature-Dependent Shifts in Doped Homo-Epitaxial GaN Layers Using Micro-Raman Spectroscopy
No full textInternational audienceGallium Nitride (GaN) has gained prominence in semiconductor applications due to its wide band gap, high electron velocity, excellent thermal conductivity, and a high critical electric field, positioning it as ideal material for high-power, high-frequency, and high-temperature applications. Vertical GaN transistors, particularly in power electronics, offer high breakdown voltage and low on-state resistance but face challenges such as self-heating, which can degrade performance. Accurate measurement of channel temperature is crucial for packaging design and thermal management, yet self-heating in vertical GaN transistors (FinFET and NWFET) remains unexplored. To explore this challenge, Raman spectroscopy is employed to quantify the impact of temperature and doping on E2(high) and A1(LO) Raman mode frequencies. The Raman spectra of Si-doped GaN homo-epitaxial layers exhibit distinct E2(high) and A1(LO) modes (Figure 1), with doping significantly affecting the latter. The A1(LO) mode undergoes a blue shift and broadening due to phonon-plasmon coupling up to ND=4.7×1017 cm-3 (Figure 2), while the E2(high) mode redshifts consistently, indicating possible induced stress effects. Temperature-dependent Raman spectra reveal expected shifts, with the E2(high) mode redshifting. The A1(LO) mode exhibits stronger shifts Δω=6.9 to 8.7 cm-1 and broadening from ΔΓ=4.7 to 35.4 cm-1 for ND=1×1015 cm-3 to ND=1.8×1018 cm-3 (Figure 3). A1(LO) fitting parameters show a linear correlation with doping, enabling temperature-doping estimation. The evolution of A1(LO) vs. E2(high) mode frequency reveals that A1(LO) is nearly twice as temperature-sensitive as E2(high) up to ND=4.7×1017 cm-3, while at ND=1.8×1018 cm-3, both modes provide equivalent temperature accuracy (Figure 4). A 3D representation (Figure 5) showing the (ωA1, ND, TL) enables temperature and doping estimation. Fano fitting of the A1(LO) mode reveals linewidth variations from ΔΓ_Fano= 15 cm-1 and Fano parameter with temperature (Figure 6, 7), serving as an indicator of Fermi level evolution in heavily doped GaN
Modelling of anti-inflammatory treatment in the Alzheimer disease: optimal regimen and outcome
No full textInternational audienceThe application of non-steroidal anti-inflammatory drugs (NSAIDs) for Alzheimer’s disease is considered to be a promising therapeutic approach. Epidemiological studies suggest potential benefits of NSAIDs; however, these findings are not consistently supported by clinical trials. This long-standing discrepancy has persisted for decades and remains a significant barrier to developing effective treatment strategies. To assess the efficacy of NSAIDs in Alzheimer’s disease, we have developed a mathematical model based on a system of ordinary differential equations. The model captures the dynamicsof key players in disease progression, including Aβ-monomers, oligomers, proinflammatory mediators (M1 microglial cells and pro-inflammatory cytokines), and anti-inflammatory mediators (M2 microglial cells and anti-inflammatory cytokines). The effects of NSAIDs are modeled through a reduction in the production rate of inflammatory cytokines (IC). While a single NSAID administration temporarily reduces IC levels, their concentration eventually returns to baseline due to drug elimination. The return time depends on the drug dose, resulting in a patient-specific return time function. By analyzing this function, we propose an optimal treatment regimen and identify conditions under which NSAID treatment is most effective in reducing IC levels. Our results suggest that NSAID efficacy in Alzheimer’s disease is influenced by the stage of the disease (with earlier intervention being more effective), patient-specific parameters, and the treatment regimen. The approach developed here can also be generalized to evaluate the efficacy of anti-inflammatory treatments for other diseases
Growth of hexagonal Ge on GaAs nanowires by molecular beam epitaxy
No full textInternational audienceHexagonal group-IV semiconductors are attracting increasing attention as they offer electronic and optical properties distinct from their cubic counterparts, with potential applications in nanophotonics and quantum technologies [1]. Here, we present recent progress on the molecular beam epitaxy (MBE) growth of hexagonal germanium (Ge) on GaAs nanowire templates [2]. Careful control of growth parameters enables the stabilization of the metastable hexagonal phase, as confirmed by structural characterization.The surface chemistry of the as-grown materials is investigated by X-ray photoelectron spectroscopy (XPS), revealing different As contamination pathways. Preliminary angle-resolved photoemission spectroscopy (ARPES) provides direct insight into the electronic band structure. Finally, we show recent advances in the fabrication of tailored structures achieved through selective chemical etching aimed at enhancing light matter interaction.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 801512. This work was supported by the LABEX iMUST of the University of Lyon (ANR-10-LABX-0064), created within the program « Investissements d'Avenir » set up by the french government and managed by the French National Research Agency (ANR).[1] E.M.T. Fadaly et al., Nature 580, 205 (2020)[2] T. Dursap, Nanotechnology 32, 155602 (2021)[3] I. Dudko, Cryst. Growth Des. 22, 32-36 (2021
Personalized Recommender System for Improving Urban Exploration and Experience Documentation of International Students
No full textInternational audienceInternational students often face challenges in adapting to new cultural and urban environments, which impacts their social integration and well-being. This study presents a novel personalized recommender system designed to support international students in documenting their urban experiences and enhancing social engagement. The system provides personalized prompts to guide students toward richer, more reflective documentation. We evaluated its impact by gathering quantitative data from user interaction logs and qualitative feedback from structured questionnaires. Our analysis reveals that the recommender system significantly enriches students' documentation by fostering deeper connections with their new surroundings, enhancing textual and emotional expression, and encouraging reflective and diverse entries. These findings demonstrate the system's potential to facilitate international students' adaptation, offering valuable insights for the development of future educational technologies and support services aimed at improving the integration and well-being of international students globally
Predicting real-world navigation performance from a virtual navigation task in older adults
No full textInternational audienceVirtual reality environments presented on tablets and smartphones offer a novel way of measuring navigation skill and predicting real-world navigation problems. The extent to which such virtual tests are effective at predicting navigation in older populations remains unclear. We compared the performance of 20 older participants (54-74 years old) in wayfinding tasks in a real-world environment in London, UK, and in similar tasks designed in a mobile app-based test of navigation (Sea Hero Quest). In a previous study with young participants (18-35 years old), we were able to predict navigation performance in real-world tasks in London and Paris using this mobile app. We find that for the older cohort, virtual navigation performance predicts real-world performance for medium difficulty, but not for the easy or difficult environments. Overall, our study supports the utility of using digital tests of spatial cognition in older age groups, while carefully adapting the task difficulty to the population
Uncertainty-Aware Online Extrinsic Calibration: A Conformal Prediction Approach
No full textInternational audienceAccurate sensor calibration is crucial for autonomous systems, yet its uncertainty quantification remains underexplored. We present the first approach to integrate uncertainty awareness into online extrinsic calibration, combining Monte Carlo Dropout with Conformal Prediction to generate prediction intervals with a guaranteed level of coverage. Our method proposes a framework to enhance existing calibration models with uncertainty quantification, compatible with various network architectures. Validated on KITTI (RGB Camera-LiDAR) and DSEC (Event Camera-LiDAR) datasets, we demonstrate effectiveness across different visual sensor types, measuring performance with adapted metrics to evaluate the efficiency and reliability of the intervals. By providing calibration parameters with quantifiable confidence measures, we offer insights into the reliability of calibration estimates, which can greatly improve the robustness of sensor fusion in dynamic environments and usefully serve the Computer Vision community
Peroxidase (POD) Mimicking Activity of Different Types of Poly(ethyleneimine)-Mediated Prussian Blue Nanoparticles
No full textInternational audiencePrussian blue nanoparticles (PBNPs) have been identified as a promising candidate for biomimetic peroxidase (POD)-like activity, specifically due to the metal centres (Fe3+/Fe2+) of Prussian blue (PB), which have the potential to function as catalytically active centres. The decoration of PBNPs with desired functional polymers (such as amino- or carboxylate-based) primarily facilitates the subsequent linkage of biomolecules to the nanoparticles for their use in biosensor applications. Thus, the elucidation of the catalytic POD mimicry of these systems is of significant scientific interest but has not been investigated in depth yet. In this report, we studied a series of poly(ethyleneimine) (PEI)-mediated PBNPs (PB/PEI NPs) prepared using various synthesis protocols. The resulting range of particles with varying size (~19–92 nm) and shape combinations were characterised in order to gain insights into their physicochemical properties. The POD-like nanozyme activity of these nanoparticles was then investigated by utilising a 3,3′,5,5′-tetramethylbenzidine (TMB)/H2O2 system, with the catalytic performance of the natural enzyme horseradish peroxidase (HRP) serving as a point of comparison. It was shown that most PB/PEI NPs displayed higher catalytic activity than the PBNPs, with higher activity observed in particles of smaller size, higher Fe content, and higher Fe2+/Fe3+ ratio. Furthermore, the nanoparticles demonstrated enhanced chemical stability in the presence of acid, sodium azide, or high concentrations of H2O2 when compared to HRP, confirming the viability of PB/PEI NPs as a promising nanozymatic material. This study disseminates fundamental knowledge on PB/PEI NPs and their POD-like activities, which will facilitate the selection of an appropriate particle type for future biosensor applications