On the physical consistency between three-dimensional and one-dimensional models in haemodynamics

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Publications associées (31)

Enhancement of brain atlases with region-specific coordinate systems: flatmaps and barrel column annotations

Felix Schürmann, Juan Bautista Hernando Vieites, Michael Reimann, Huanxiang Lu, Armando Romani, Sirio Bolaños Puchet, Aleksandra Zuzanna Teska

Digital brain atlases define a hierarchy of brain regions and their locations in three-dimensional space. They provide a standard coordinate system in which diverse datasets can be integrated for visualization and analysis. They also enable building of dat ...

2024

Deep Learning for 3D Surface Modelling and Reconstruction

Benoît Alain René Guillard

In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

EPFL2023

Lightning Localization Using Three-Dimensional Time Reversal MUltiple SIgnal Classification (TR-MUSIC) Algorithm

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

In this paper a three-dimensional (3D) Time Reversal MUltiple SIgnal Classification (TR-MUSIC) algorithm is proposed to localize lightning discharges. The performance of the proposed algorithm was evaluated considering different scenarios and taking into a ...

2023

A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart

Alfio Quarteroni, Luca Dede'

We propose a mathematical and numerical model for the simulation of the heart function that couples cardiac electrophysiology, active and passive mechanics and hemodynamics, and includes reduced models for cardiac valves and the circulatory system. Our mod ...

Wiley2023

Long-distance coherent propagation of magnon polarons in a ferroelectric-ferromagnetic heterostructure

Jean-Philippe Ansermet, Haiming Yu, Peng Chen, Song Liu, Jilei Chen, Jianyu Zhang, Jinlong Wang, Yao Zhang

We experimentally demonstrate the coherent propagation of magnon polarons, the hybridized excitations formed by the coupling of spin waves and Rayleigh/Love surface acoustic waves, in a heterostructure consisting of ferroelectric BaTiO3 and ferromagnetic L ...

Amer Physical Soc2023

A method and system for enforcing smoothness constraints on surface meshes from a graph convolutional neural network

Pascal Fua, Pamuditha Udaranga Wickramasinghe

A method for enforcing smoothness constraints on surface meshes produced by a Graph Convolutional Neural Network (GCNN) including the steps of reading image data from a memory, the image data including two-dimensional image data representing a three-dimens ...

2023

Light-Induced Halide Segregation in 2D and Quasi-2D Mixed-Halide Perovskites

Manuel Cordova, David Lyndon Emsley, Aditya Mishra, Michael Allan Hope

Photoinduced halide segregation hinders widespread application of three-dimensional (3D) mixed-halide perovskites. Much less is known about this phenomenon in lower-dimensional systems. Here, we study photoinduced halide segregation in lower-dimensional mi ...

AMER CHEMICAL SOC2023

Emergent U(1) symmetry in non-particle-conserving one-dimensional models

Frédéric Mila, Natalia Chepiga, Mohamed Zakaria Jouini, Loïc Jean Pierre Herviou

The properties of stable Luttinger liquid phases in models with a nonconserved number of particles are investigated. We study the Luttinger liquid phases in one-dimensional models of hard-core boson and spinless fermion chains where particles can be create ...

Amer Physical Soc2023

Validation of GBS plasma turbulence simulation of the TJ-K stellarator

Joaquim Loizu Cisquella, Paolo Ricci

We present a validation of a three-dimensional, two-fluid simulation of plasma turbulence in the TJ-K stellarator, a low temperature plasma experiment ideally suited for turbulence measurements. The simulation is carried out by the GBS code, recently adapt ...

IOP Publishing Ltd2023

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Bryan German Pantoja Rosero

Current post-earthquake damage assessment methodologies are not only time-consuming but also subjective in nature and difficult to document. Recent advancements in artificial intelligence and technological devices make it possible to accomplish this task a ...

EPFL2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

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