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E4F1 coordinates pyruvate metabolism and the activity of the elongator complex to ensure translation fidelity during brain development
No full textInternational audiencePyruvate metabolism defects lead to severe neuropathies such as the Leigh syndrome (LS) but the molecular mechanisms underlying neuronal cell death remain poorly understood. Here, we unravel a connection between pyruvate metabolism and the regulation of the epitranscriptome that plays an essential role during brain development. Using genetically engineered mouse model and primary neuronal cells, we identify the transcription factor E4F1 as a key coordinator of AcetylCoenzyme A (AcCoA) production by the pyruvate dehydrogenase complex (PDC) and its utilization as an essential co-factor by the Elongator complex to acetylate tRNAs at the wobble position uridine 34 (U 34 ). E4F1-mediated direct transcriptional regulation of Dlat and Elp3, two genes encoding key subunits of the PDC and of the Elongator complex, respectively, ensures proper translation fidelity and cell survival in the central nervous system (CNS) during mouse embryonic development. Furthermore, analysis of PDH-deficient cells highlight a crosstalk linking the PDC to ELP3 expression that is perturbed in LS patients
Self-assembled GaAs quantum dashes for direct alignment of liquid crystals on a III-V semiconductor surface
No full textInternational audienceThe development of tunable photonic devices is strategic for miniaturized optical instrumentation and sensing systems. Exploiting the birefringence variation of liquid crystals (LCs) instead of MEMS actuation in such devices could bring better spectral stability and lower power consumption. However, aligning LCs inside a III-V semiconductor device is tricky. We demonstrate that self-assembled gallium arsenide (GaAs) quantum dashes (QDHs) could serve as direct planar aligners for LC nematic molecules. The alignment quality and birefringence variation of a LC-microcell embedding QDHs are shown to be similar to those of a polymer nanograting-based reference, with the added advantage of better electrical performance
Evolution of surface layers during the sliding wear of wheel and rail steel under very high load
No full textWOM 2025 - 25th International Conference on Wear of Materials, Sitges, Espagne, 13-17 avril 2025International audienceThe near-surface regions of the wheel-rail contact experience complex thermomechanical phenomena. In sharp curves, the sliding contact between the wheel flange and rail gauge corner is associated with elevated stresses and catastrophic wear. Understanding the evolution of tribologically transformed layers (TTLs) beneath the contact is key to explaining wear behavior. However, replicating the extreme conditions of this contact in laboratory tests remains a challenge. Conventional sliding wear testing setups, such as pin-on-disc, often fail to produce TTLs as thick as those found in serviced wheels due to limited normal loads. To achieve thicker TTLs, sliding wear tests were carried out under an 8 kN normal load (604 MPa) using a ring-on-disc configuration (disc: AAR Class D pearlitic wheel steel, 353 ± 7 HBW; ring: high-strength rail steel, 378 ± 3 HBW). The tests were carried out over increasing sliding distances, at 0.1 and 0.2 m/s. The evolution of the TTLs was observed through optical and scanning electron microscopy, and their hardnesses and thicknesses were evaluated. Average TTL thicknesses in the order of 100 μm were observed across tests, even at the smaller sliding distances. Significant hardening was observed in TTLs, with the presence of a hardness gradient towards the surface. The friction coefficient revolved around 0.3 in the steady state, and the wear data showed a large dispersion. At 0.1 m/s, seizure occurred at 132 m of sliding, marked by heavily oxidized wear tracks, severe wear, the thickest TTLs and a sudden increase in friction and temperature. These results indicate that high-load ring-on-disc tests can more accurately reproduce surface layers found in serviced wheels and rails
Measurement of skidding to determine the optimum ergonomic configuration of the racing wheelchair
No full textInternational audienc
Non-geodesic filament winding: Derivation process and resolution of a pair of ordinary differential equations in arc length based on vector projection
No full textInternational audienceNon-geodesic filament winding allows the manufacturing of various surfaces of revolution, including those once considered unsuitable for this process, such as Gaussian depressions (i.e., concavities), through numerical solutions of standard path equations without the need for ingenious workarounds. In this context, one of these mathematical models is thoroughly examined. It consists of an ordinary differential equation in arc length that has been exclusively applied to cylindrical geometries. The initial derivation technique is repeated with the aim of reformulating it in a more general manner, using intrinsic differential geometry concepts. As a result, a second equation, similar to the desired one but slightly more complex, is obtained. To verify its validity through comparison with the first equation, each is restated as a system of two differential equations that define the position of the path points of the fiber reinforcement, with the aid of cylindrical coordinates. Three geometries are chosen to validate the numerical solutions: a right circular cylinder, an exponential function that produces an axisymmetric Gaussian depression, and a third-degree polynomial that outlines a divergent nozzle. The solutions show that both systems of equations yield stable, predictable, and conventional results for all geometries, systems, and solving strategies. When the resolution is “forward” (i.e., the independent variable is the winding angle, the process is more elaborate. In contrast, it is straightforward when the resolution is “inverse”. Regarding the nozzle, comparison with an equation derived by another method, based on the geodesic and normal curvatures of the surface, reveals that the derived equation offers a broader solution range along the -axis and can handle higher friction coefficient values than those reported in the literature. Consequently, the newly derived equation demonstrates greater comprehensiveness and applicability. It is concluded that the derivation procedure is well-defined and that both equations are effective for advancing filament winding methods
A Deligne conjecture for prestacks
No full textComments are welcomeWe prove an analog of the Deligne conjecture for prestacks. We show that given a prestack , its Gerstenhaber--Schack complex is naturally an -algebra. This structure generalises both the known -algebra structure on , as well as the Gerstenhaber algebra structure on its cohomology . The main ingredient is the proof of a conjecture of Hawkins \cite{hawkins}, stating that the homology of the dg operad has vanishing homology in positive degrees. As a corollary, \Quilt is quasi-isomorphic to the operad encoding brace algebras. In addition, we improve the -structure on \Quilt be showing that it originates from a -structure lifting the -structure on in homology
A Review on Metallic Drilling Burrs: Geometry, Formation, and Effect on the Mechanical Strength of Metallic Assemblies
No full textInternational audienceMachining processes produce unwanted remainders of material on the free edges which arecalled burrs. In particular, the drilling process generates an entry burr and a typicallylarger exit burr. When drilling stacks of several workpieces, exit and entry burrs are producedsimultaneously at the interfaces. The presence of burrs can degrade the static andfatigue strength of the parts and assemblies containing them. An example concerns theburrs formed at the interface during the drilling of multistacks in One-Way-Assembly processes,where deburring is not systematically applied. The effect on fatigue can be significant.Reductions of up to 70% in fatigue life have been reported, even though theexplanatory rationale is not clear. This article reviews existing works on burrs, focusingon drilling burrs. A description of the morphology of different types of burrs and of measurementtechnologies is given. Burr formation mechanisms and their modeling arereviewed. Burr control strategies and the main deburring technologies are examined.The limited literature on the effects of burrs on the static and fatigue strength of mechanicalassemblies is also explored.<br /
Development of a numerical thermal-hydraulic model of the ELIPSE process
No full textInternational audienceWe developed a numerical solver to study the gas-liquid multiphase flow in the ELIPSE process developed at CEA Marcoule. The numerical strategy used to simulate its dynamics is particularly challenging because of the multi-scale nature of the flow, which involves both large gas pockets, formed during the injection of a submersed turbulent gas jet in a liquid flow, and small dispersed bubbles resulting from the breakup of these large-scale interfaces. To this purpose, the Volume Of Fluid method is coupled to a Lagrangian tracking of the emerging bubbles, by using an Adaptative Mesh Refinement strategy with a criterion of size to convert the smaller bubbles into Lagrangian objects. An LES model is used to describe the turbulent flow. By this way, we constructed the flow regime map as a function of the operating conditions of the reactor. Moreover, the heat balance is solved, and the numerical method is adapted to account for gas-liquid phase change occurring in the process. The whole simulation model allows investigating the influence of heat transfer on the flow features and gas distribution in the liquid bath
Towards Zero-Shot Cross-Agent Transfer Learning via Latent-Space Universal Notice Network
No full textInternational audienceDespite numerous improvements regarding the sample-efficiency of Reinforcement Learning (RL) methods, learning from scratch still requires millions (even dozens of millions) of interactions with the environment to converge to a high-reward policy. This is usually because the agent has no prior information about the task and its own physical embodiment. One way to address and mitigate this data-hungriness is to use Transfer Learning (TL). In this paper, we explore TL in the context of RL with the specific purpose of transferring policies from one agent to another, even in the presence of morphology discrepancies or different stateaction spaces. We propose a process to leverage past knowledge from one agent (source) to speed up or even bypass the learning phase for a different agent (target) tackling the same task. Our proposed method first leverages Variational Auto-Encoders (VAE) to learn an agent-agnostic latent space from paired, time-aligned trajectories collected on a set of agents. Then, we train a policy embedded inside the created agent-invariant latent space to solve a given task, yielding a task-module reusable by any of the agents sharing this common feature space. Through several robotic tasks and heterogeneous hardware platforms, both in simulation and on physical robots, we show the benefits of our approach in terms of improved sample-efficiency. More specifically we report zero-shot generalization in some instances, where performances after transfer are recovered instantly. In worst case scenarios, performances are retrieved after fine-tuning on the target robot for a fraction of the training cost required to train a policy with similar performances from scratch
Enabling quantitative analysis of in situ TEM experiments: A high-throughput, deep learning-based approach tailored to the dynamics of dislocations
No full textInternational audienceIn situ TEM is by far the most commonly used microscopy method for imaging dislocations, i.e., line-like defects in crystalline materials. However, quantitative image analysis so far was not possible, implying that also statistical analyses were strongly limited. In this work, we created a deep learning-based digital twin of an in situ TEM straining experiment, additionally allowing to perform matching simulations. As application we extract spatio-temporal information of moving dislocations from experiments carried out on a Cantor high entropy alloy and investigate the universality class of plastic strain avalanches. We can directly observe “stick–slip motion” of single dislocations and compute the corresponding avalanche statistics. The distributions turn out to be scale-free, and the exponent of the power law distribution exhibits independence on the driving stress. The introduced methodology is entirely generic and has the potential to turn meso-scale TEM microscopy into a truly quantitative and reproducible approach