Peri-implant bone adaptations to overloading in rat tibiae: experimental investigations and numerical predictions

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Infancy is a key period for bone growth, determining bone strength later in life. Studies have provided early insights into the role that human milk oligosaccharides (HMOs) may play in growth, potentially through their effects on the microbiome. However, f ...

We study continuous-domain linear inverse problems that involve a general data-fidelity term and a regularisation term. We consider a regularisation that is formed by the sparsity-promoting total-variation norm, pre-composed with a differential operator th ...

We present a simple and versatile approach to test the accuracy of scattering calculations. Based on the Lorentz reciprocity relation, this criterion can be used for any scattering object, especially where a reference solution (e.g. from Mie theory) does n ...

In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...

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 ...

Estimating the stress of reinforcing bars and its variations in service conditions can be useful to determine the reserve capacity of structures or to assess the risk of fatigue in the reinforcement. This paper investigates the use crack width measurements ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

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 ...

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

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 ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

The exploration of electronically excited states and the study of diverse photochemical and photophysical processes are the main goals of molecular electronic spectroscopy. Exact quantum-mechanical simulation of such experiments is, however, beyond current ...

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

Total Flow Analysis (TFA) is a method for the worst-case analysis of time-sensitive networks. It uses service curve characterizations of the network nodes and arrival curves of flows at their sources; for tractability, the latter are often taken to be line ...

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 ...

This paper numerically evaluates the accuracy and performance of a stabilized finite element Reduced Order Modelling (ROM) approach that is designed to simulate pulsatile blood flows. The method is able to estimate fluid flow parametric solutions of intere ...

Self-tracking technologies open new doors to previously unimaginable scenarios. The diagnosis of diseases years in advance, or supporting the health of astronauts on missions to Mars are just some of many example applications. During the COVID-19 pandemic, ...

In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

Peri-implant bone adaptations to overloading in rat tibiae: experimental investigations and numerical predictions

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Intake of Neutral Core Human Milk Oligosaccharides (hmos) During Early Life Improves Long-term Bone Quality

Convergence analysis of the discretization of continuous-domain inverse problems

Testing the accuracy and convergence of scattering calculations using Lorentz reciprocity

From low-rank retractions to dynamical low-rank approximation and back

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

Estimation of the bar stress based on crack width measurements in reinforced concrete structures

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Residual-based attention in physics-informed neural networks

Iterative removal of sources to model the turbulent electromotive force

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

Reliable data-driven decision-making through optimal transport

Applications of the thawed Gaussian approximation to electronic spectroscopy

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

Efficient and Accurate Handling of Periodic Flows in Time-Sensitive Networks

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

Reduced order modeling of parametrized pulsatile blood flows: Hematocrit percentage and heart rate

Designing self-tracking experiences: A qualitative study of the perceptions of barriers and facilitators to adopting digital health technology for automatic urine analysis at home

Low-Rank Tensor Methods for High-Dimensional Problems

An equilibrated flux a posteriori error estimator for defeaturing problems