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Advancing High-Throughput Cellular Atomic Force Microscopy with Automation and Artificial Intelligence
No full textInternational audienceAtomic force microscopy (AFM) has reached a significant level of maturity in biology, demonstrated by the diversity of modes for obtaining not only topographical images but also insightful mechanical and adhesion data by performing force measurements on delicate samples with a controlled environment (e.g., liquid, temperature, pH). Numerous studies have applied AFM to describe biological phenomena at the molecular and cellular scales, and even on tissues. Despite these advances, AFM is not established as a diagnostic tool in the biomedical field. This article describes the reasons for this gap, focusing on one of the main weaknesses of bio-AFM: its low data throughput. We review current efforts to improve the automation of AFM measurements in particular on living cells, as well as the developments in automating data analysis. For the latter, artificial intelligence (AI) is progressively employed to classify data to distinguish healthy and diseased cells or tissues. Finally, we propose a roadmap to foster the application of bio-AFM into medical diagnostics
Some flocking properties for a model of collective dynamics with topological interactions
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Polynomial Optimization for Nonlinear Dynamics: Theory, Algorithms and Applications
No full textInternational audienceThis workshop focused on using computational tools of polynomial optimization to deduce information about nonlinear dynamical systems, including systems governed by ordinary or partial differential equations. This approach sits at the interface of various research areas, requiring combinations of applied nonlinear dynamics and control theory, polynomial optimization, real algebraic geometry, partial differential equations, and variational analysis. The workshop brought together researchers in these different areas to share recent advances and to build the connections required for further progress
L'impact des spires rapprochées sur la raideur du ressort hélicoïdal
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MEDICAL KNOWLEDGE INTEGRATION INTO REINFORCEMENT LEARNING ALGORITHMS FOR DYNAMIC TREATMENT REGIMES
No full textThe goal of precision medicine is to provide individualized treatment at each stage of chronic diseases, a concept formalized by Dynamic Treatment Regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness. Reinforcement Learning (RL) algorithms allow to determine these decision rules conditioned by individual patient data and their medical history. The integration of medical expertise into these models makes possible to increase confidence in treatment recommendations and facilitate the adoption of this approach by healthcare professionals and patients. In this work, we examine the mathematical foundations of RL, contextualize its application in the field of DTR, and present an overview of methods to improve its effectiveness by integrating medical expertise
Control of retained austenite stability during the heat treatment of the high performance steel Ferrium® M54®
No full textInternational audienceFerrium® M54® ultra-high-strength steel is an excellent candidate for landing gear applications due to its balance of UTS, KIC, and KISCC properties, which is among the best compared to steels currently in use. The tensile strength of Ferrium® M54® at room temperature is mainly provided by the martensitic structure formed during quenching and by the precipitation of molybdenum M2C carbides during tempering. However, a significant amount of retained austenite may remain after heat treatment. This study demonstrates that both the temperature and the delay between quenching and cryogenic treatment are critical parameters. Specifically, carbon diffusion during this period, even at room temperature, contributes to stabilizing the retained austenite. Austenite stabilization is modelled using the Johnson-Mehl-Avrami-Kolmogorov law to determine the maximum allowable dwell time between quenching and cryogenic treatment. This important finding helps in stabilizing the yield strength and preventing the transformation of retained austenite into fresh martensite under load
Automated growth of AlAs/GaAs Bragg mirror with real-time feedback reflectometry.
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Pinecones valorization: process intensification and eco-friendly extraction of antioxidant compounds
No full textInternational audienceConsidering the circular economy, this research addresses concerns about Tunisian pinecone valorization within the cosmetic industry. This study aims to optimize the extraction of antioxidant compounds from P. halepensis petals through maceration in water by analyzing rheological behavior and decantation phenomena to intensify the extraction process. Granulometry of samples raw, Cl1, Cl2 and Cl3, with a mean diameter in volume-weighted (D [4,3]) values of 1200, 1400, 1100 and 120 μm respectively, and concentrations of suspensions from 0 to 170 ghm/Lsus were analyzed on rheological behavior, settling kinetics, extraction yields, and antioxidant activity. The result showed that the viscosity increases with concentration and granulometry but decreases with increasing shear rate (ranging between 0.5 and 500 s−1), indicating shear-thinning behavior. Increasing concentration from 0 to 170 ghm/Lsus also raised the consistency factor (k), a measure of the fluid's resistance to flow or its internal friction (higher values indicate a more viscous or thicker suspension), from 0.003 to 8.525 Pa/sn and decreased the power-law index (n), quantifying the degree of shear-thinning (a lower n indicates a more intense shear-thinning behavior), from 1 to 0.11. Quemada equation, commonly used to describe the viscosity of suspensions, effectively modeled the behavior of dilute and semi-dilute regimes and identified two critical concentrations: CCrit1 34 ghm/Lsus (concentrated). The apparent viscosity suspension depends on particle concentration and physical properties (granulometry, morphology, density), as well as decantation kinetics impacted by particle-particle interactions. Suspension with coarser granulometry (Cl1) exhibited the highest viscosity (100 Pa.s) at = 1 s−1 and settling velocity (84.3 mm/h), necessitating a minimal pumping flow rate to balance superficial and settling velocities to select impeller and maintain suspension homogeneity. High value of sediment porosity (0.84) suggests a sediment water retention capacity of 80%, indicating the need for sediment filtration after extraction. Extraction yields are correlated with granulometry ranging from 50 (Cl1) to 215 (Cl3) mgES/gdm and plateaued after 5 h. Statistical analysis confirms the good fit of the order 1 model for all experimental data. Cl3 exhibited interesting antioxidant activity with IC50 of 8.89 µg/mL against DPPH. Intensification (concentration, granulometry and time) of maceration (water as green solvent) by optimizing the extraction of bioactive compounds, stands as a new way to valorize forestry byproduct (petal pinecones)
Beyond the Dailey–Townes Model: Chemical Information from the Electric Field Gradient
No full textInternational audienceIn this work, we reexamine the Dailey–Townes model by systematically investigating the electric field gradient (EFG) in various chlorine compounds, dihalogens, and the uranyl ion (UO22+). Through the use of relativistic molecular calculations and projection analysis, we decompose the EFG expectation value in terms of atomic reference orbitals. We show how the Dailey–Townes model can be seen as an approximation to our projection analysis. Moreover, we observe for the chlorine compounds that, in general, the Dailey–Townes model deviates from the total EFG value. We show that the main reason for this is that the Dailey–Townes model does not account for contributions from the mixing of valence p-orbitals with subvalence ones. We also find a non-negligible contribution from core polarization. This can be interpreted as Sternheimer shielding, as discussed in an appendix. The predictions of the Dailey–Townes model are improved by replacing net populations with gross ones, but we have not found any theoretical justification for this. Subsequently, for the molecular systems X–Cl (where X = I, At, and Ts), we find that with the inclusion of spin–orbit interaction, the (electronic) EFG operator is no longer diagonal within an atomic shell, which is incompatible with the Dailey–Townes model. Finally, we examine the EFG at the uranium position in UO22+, where we find that about half the EFG comes from core polarization. The other half comes from the combination of the U≡O bonds and the U(6p) orbitals, the latter mostly nonbonding, in particular with spin–orbit interaction included. The analysis was carried out with molecular orbitals localized according to the Pipek–Mezey criterion. Surprisingly, we observed that core orbitals are also rotated during this localization procedure, even though they are fully localized. We show in an appendix that, using this localization criterion, it is actually allowed
On the Complexity of p-Order Cone Programs
No full text21 pages, 2 tablesInternational audienceThis manuscript explores novel complexity results for the feasibility problem over -order cones, extending the foundational work of Porkolab and Khachiyan. By leveraging the intrinsic structure of -order cones, we derive refined complexity bounds that surpass those obtained via standard semidefinite programming reformulations. Our analysis not only improves theoretical bounds but also provides practical insights into the computational efficiency of solving such problems. In addition to establishing complexity results, we derive explicit bounds for solutions when the feasibility problem admits one. For infeasible instances, we analyze their discrepancy quantifying the degree of infeasibility. Finally, we examine specific cases of interest, highlighting scenarios where the geometry of -order cones or problem structure yields further computational simplifications. These findings contribute to both the theoretical understanding and practical tractability of optimization problems involving -order cones