Microfluidics: A Tool to Control the Size and Composition of Particles

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Publications associées (32)

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Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

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Energy-Efficient Particle Accelerators for Research

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Particle accelerators are the drivers for large-scale research infrastructures for particle physics but also for many branches of condensed matter research. The types of accelerator-driven research infrastructures include particle colliders, neutron, muon ...

2024

Models implemented in the methodological approach to design the initial STEP first wall contour

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The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is mana ...

Elsevier Science Sa2024

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

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Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

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Overview of fast particle experiments in the first MAST Upgrade experimental campaigns

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MAST-U is equipped with on-axis and off-axis neutral beam injectors (NBI), and these external sources of super-Alfv & eacute;nic deuterium fast-ions provide opportunities for studying a wide range of phenomena relevant to the physics of alpha-particles in ...

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Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

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Conventional techniques for purifying macromolecular conjugates often require complex and costly installments that are inaccessible to most laboratories. In this work, we develop a one-step micropreparative method based on a trilayered polyacrylamide gel e ...

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A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

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In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

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High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

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Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

EPFL2024

SC-TPTP: An Extension of the TPTP Derivation Format for Sequent-Based Calculus

Simon Guilloud

Motivated by the transfer of proofs between proof systems, and in particular from first order automated theorem provers (ATPs) to interactive theorem provers (ITPs), we specify an extension of the TPTP derivation text format to describe proofs in first-ord ...

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Residual-based attention in physics-informed neural networks

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Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Elsevier Science Sa2024

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High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Roya Moghaddasi Fereidani

EPFL2024

SC-TPTP: An Extension of the TPTP Derivation Format for Sequent-Based Calculus

Simon Guilloud

2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Elsevier Science Sa2024