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20012026
most citedA deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

615 citations

Showing 2022Show all

22 papers · 1 filter

nucl-ex2022

Measurement of the N(n,p)C cross section at the CERN n_TOF facility from sub-thermal energy to 800 keV

P. Torres-Sánchez, J. Praena, I. Porras +129

Background: The N(n,p)C reaction is of interest in neutron capture therapy, where nitrogen-related dose is the main component due to low-energy neutrons, and in astro…

cond-mat.mtrl-sci2022★ 24 cited

Machine Learned Interatomic Potential for Dispersion Strengthened Plasma Facing Components

E. L. Sikorski, M. A. Cusentino, M. J. McCarthy +3

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high britt…

nucl-th2022

A new three-ranged Gogny interaction in touch with pion exchange

L. Batail, D. Davesne, S. Péru +3

We present a new Gogny-type finite-range effective interaction including a third Gaussian in the central term. Based on simple arguments valid for an arbitrary radial form factor,…

physics.plasm-ph2022★ 4 cited

Global linear stability analysis of kinetic Trapped Ion Mode (TIM) turbulence in tokamak plasma using spectral method

D. Mandal, M. Lesur, E. Gravier +4

Trapped ion modes (TIM) belong to the family of ion temperature gradient (ITG) modes, which are one of the important ingredients in heat turbulent transport at the ion scale in tok…

nucl-ex2022★ 20 cited

Observation of a nuclear recoil peak at the 100 eV scale induced by neutron capture

CRAB Collaboration, NUCLEUS Collaboration, H. Abele +75

Coherent elastic neutrino-nucleus scattering and low-mass Dark Matter detectors rely crucially on the understanding of their response to nuclear recoils. We report the first observ…

cond-mat.mtrl-sci2022★ 14 cited

Ab initio Canonical Sampling based on Variational Inference

Alois Castellano, Francois Bottin, Johann Bouchet +2

Finite temperature calculations, based on ab initio molecular dynamics (AIMD) simulations, are a powerful tool able to predict material properties that cannot be deduced from groun…