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La politique des statistiques internationales du tourisme : Entre exigences financières et préoccupations environnementales
No full textInternational audienc
Scalable magnetic resonance fingerprinting: Incremental inference of high dimensional elliptical mixtures from large data volumes
No full textInternational audienceMagnetic Resonance Fingerprinting (MRF) is an emerging technology with the potential to revolutionize radiology and medical diagnostics. In comparison to traditional magnetic resonance imaging (MRI), MRF enables the rapid, simultaneous, non-invasive acquisition and reconstruction of multiple tissue parameters, paving the way for novel diagnostic techniques. In the original matching approach, reconstruction is based on the search for the best matches between in vivo acquired signals and a dictionary of high-dimensional simulated signals (fingerprints) with known tissue properties. A critical and limiting challenge is that the size of the simulated dictionary increases exponentially with the number of parameters, leading to an extremely costly subsequent matching. In this work, we propose to address this scalability issue by considering probabilistic mixtures of high-dimensional elliptical distributions, to learn more efficient dictionary representations. Mixture components are modelled as flexible ellipitic shapes in low dimensional subspaces. They are exploited to cluster similar signals and reduce their dimension locally cluster-wise to limit information loss. To estimate such a mixture model, we provide a new incremental algorithm capable of handling large numbers of signals, allowing us to go far beyond the hardware limitations encountered by standard implementations. We demonstrate, on simulated and real data, that our method effectively manages large volumes of MRF data with maintained accuracy. It offers a more efficient solution for accurate tissue characterization and significantly reduces the computational burden, making the clinical application of MRF more practical and accessible
Intermediation Platforms and Geopolitical Asymmetries, Lessons from a Pandemic
No full textInternational audienceTo a large extent, and particularly before vaccines became available, human societies owed their resilience during the COVID-19 pandemic to non-pharmaceutical interventions, i.e. social distancing combined with more invasive digital systems. In this paper, we consider the digital applications developed during 2020-2021, the two first years of the pandemic. We introduce a typology based on the services offered and the data flows they require, between both public and private actors. A detailed timeline of these developments shows that countries’ strategies have evolved in strong coherence with their overall digital policy. Our study demonstrates that this exogenous crisis has reinforced the critical role of intermediation platforms for maintaining society’s essential functions. Their increased centrality has contributed to intensifying information asymmetries and power imbalances, already at stake before the pandemic, both between platforms and states, as well as between countries, leading to new geopolitical equilibria
Stiffness-sensitive gene regulation in human mesenchymal stem cells: Modelling mechanotransduction to predict mineralization and bone protein expression
No full textInternational audienceThe goal of our study was to establish how a specific part of the bone Gene Regulatory Network (GRN) controls mineralization in response to stiffness. We hypothesized that a system of differential equations model stiffness-sensitive gene regulation in human mesenchymal stem cells through the epistatic genetic interactions between stiffness (e.g. WNT-β catenin pathway) and five of the main transcription factors and bone proteins (e.g. RUNX2, BSP, OSX, OC, and OPN). To test this hypothesis, we (i) performed in-vitro experiments culturing bone cells on different stiffness, (i) adapted our previously published model from being continuously time-dependent to continuously stiffness-sensitive, and (iii) simulated protein production in function of stiffness and other protein production from the best estimate of parameters coming from the experimental work. Our experimental findings reveal a non-parametric relationship between stiffness and RUNX2 production, with no discernible linear trends for other proteins. Modeling results demonstrate that continuous variations in stiffness enable simulation of bone GRN gene expression, fitting our novel experimental dataset. Specifically, our computational results indicate that OPN production peaks at low stiffness (8 kPa), while RUNX2, OSX, and OC achieve maximum production at higher stiffness levels (64 kPa). This alignment underscores the model's capacity to replicate experimental data accurately. Additionally, our approach predicts that WNT-β-catenin activation serves as an enhancer for OPN and BSP production. The model also highlights a negative feedback-like interaction between OC and BSP production. Stiffness variations were shown to have a significant impact on OC and BSP production and a moderate effect on OPN production. By employing a stiffness-sensitive gene regulation model, we provide insights into one of the mineralization patterns through the prediction of bone protein expression dynamics
Spreading properties of the Fisher--KPP equation when the intrinsic growth rate is maximal in a moving patch of bounded size
No full textInternational audienceThis paper is concerned with spreading properties of space-time heterogeneous Fisher–KPP equations in one space dimension. We focus on the case of everywhere favorable environment with three different zones, a left half-line with slow or intermediate growth, a central patch with fast growth and a right half-line with slow or intermediate growth. The central patch moves at various speeds. The behavior of the front changes drastically depending on the speed of the central patch. Among other things, intriguing phenomena such as nonlocal pulling and locking may occur, which would make the behavior of the front further complicated. The problem we discuss here is closely related to questions in biomathematical modelling. By considering several special cases, we illustrate the remarkable diversity of possible behaviors. In particular, when the central patch has constant size and constant speed, we provide a complete set of explicit formulas for the spreading speed
Investigation of lubricant flow in a planetary bearing cavity under stationary carrier condition
No full textPlanetary bearings are critical components in planetary transmission systems. As transmission systems evolve toward higher speeds, the lubrication of planetary bearings faces significant challenges. In this study, a specialized test rig was developed to visualize the oil flow in a planetary bearing cavity under a stationary carrier condition, a configuration featuring outer ring rotation and central oil supply. The experimental results reveal the oil flow patterns and distribution characteristics within the bearing cavity. Additionally, a dynamic-static fluid domain coupled numerical model was established to simulate the oil-air two-phase flow field in the rotating bearing domain. This model was used to analyze the variations in oil distribution inside the bearing cavity and the oil volume fraction(OVF) on component surfaces under different speeds. The research results indicate that the bearing cavity is fully filled with oil at low speeds. As the speed increases, the oil near the roller end faces on the inner ring side begins to decrease, and an arc-shaped oil film forms along the inner side of the cage. With further speed increase, this oil film expands radially outward. At 9000 r/min, only a small amount of oil remains distributed near the outer ring. Increasing the oil flow rate further enhances the OVF on these surfaces, which can alleviate oil starvation in the lubrication zone between the rollers and the inner ring under highspeed conditions. However, higher flow rates also lead to increased churning losses in the planetary bearing. The research results provide theoretical guidance for the lubrication design of planetary bearings in transmission systems
Amoeba Measures of Random Plane Curves
No full text41 pages, 1 figureInternational audienceWe prove that the expected area of the amoeba of a complex plane curve of degree is less than and once rescaled by , is asymptotically bounded from below by . In order to get this lower bound, given disjoint isometric embeddings of a bidisc of size in the complex projective plane, we lower estimate the probability that one of them is a submanifold chart of a complex plane curve. It exponentially converges to one as the number of bidiscs grow to
Deformation of surrounding rocks in salt caverns in compressed air energy storage plants: Insights from laboratory experiments and numerical simulations
No full textInternational audienc
Géométrie plane des q-rationnels et les opérations de Springborn
No full textInternational audienceWe study the geometry of q-rational numbers, introduced by Morier-Genoud and Ovsienko, for positive real q. In particular, we construct and analyse the deformed Farey triangulation and the deformed modular surface. We interpret every q-rational geometrically as a circle, similar to the famous Ford circles. Further, we define and study new operations on q-rationals, the Springborn operations, which can be seen as a quadratic version of the Farey addition. Geometrically, the Springborn operations correspond to taking the homothety centers of a pair of two circles. Contents 1. Introduction 1 2. From q-integers to q-rationals to q-reals 5 3. Hyperbolic geometry and deformed Farey tesselation 9 4. Deformed Farey determinants and operations 18 5. Classical Springborn operations 24 6. Springborn operations for q-rationals 32 7.</div