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In this paper, an innovative microwave imaging (MI) approach for breast tumor diagnosis is proposed that employs a differential formulation of the inverse scattering problem (ISP) at hand to exploit arbitrary-fidelity priors on the…

Signal Processing · Electrical Eng. & Systems 2024-01-08 Francesco Zardi , Luca Tosi , Marco Salucci , Andrea Massa

Survival of living tumor cells underlies many influences such as nutrient saturation, oxygen level, drug concentrations or mechanical forces. Data-supported mathematical modeling can be a powerful tool to get a better understanding of cell…

Dynamical Systems · Mathematics 2022-03-24 Sabrina Schönfeld , Alican Ozkan , Laura Scarabosio , Marissa Nichole Rylander , Christina Kuttler

A nonlinear Helmholtz (NLH) equation with high frequencies and corner singularities is discretized by the linear finite element method (FEM). After deriving some wave-number-explicit stability estimates and the singularity decomposition for…

Numerical Analysis · Mathematics 2024-05-28 Run Jiang , Haijun Wu , Yifeng Xu , Jun Zou

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heterogeneity that meaningfully impacts disease biology and treatment resistance. The dynamic…

The finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs). Here, we present $\textbf{Qu-FEM}$, a fault-tolerant era quantum algorithm for the finite element method. In contrast to…

Quantum Physics · Physics 2025-10-22 Ahmad M. Alkadri , Tyler D. Kharazi , K. Birgitta Whaley , Kranthi K. Mandadapu

We study the weak finite element method solving convection-diffusion equations. A weak finite element scheme is presented based on a spacial variational form. We established a weak embedding inequality that is very useful in the weak finite…

Numerical Analysis · Mathematics 2015-06-10 Tie Zhang , Yanli Chen

We investigate the dynamics of a nonlinear model for tumor growth within a cellular medium. In this setting the "tumor" is viewed as a multiphase flow consisting of cancerous cells in either proliferating phase or quiescent phase and a…

Analysis of PDEs · Mathematics 2015-03-31 Donatella Donatelli , Konstantina Trivisa

A distributed optimal control problem for a phase field system which physical context is that of tumor growth is discussed. The system we are going to take into account consists of a Cahn-Hilliard equation for the phase variable (relative…

Analysis of PDEs · Mathematics 2021-01-20 Andrea Signori

We propose an adaptive finite element method to approximate the solutions to reaction-diffusion systems on time-dependent domains and surfaces. We derive a computable error estimator that provides an upper bound for the error in the…

Numerical Analysis · Mathematics 2013-08-13 Chandrasekhar Venkataraman , Omar Lakkis , Anotida Madzvamuse

An adaptive finite element method is presented for the elastic scattering of a time-harmonic plane wave by a periodic surface. First, the unbounded physical domain is truncated into a bounded computational domain by introducing the…

Numerical Analysis · Mathematics 2016-05-30 Xue Jiang , Peijun Li , Junliang Lv , Weiying Zheng

In this paper, we address an optimal distributed control problem for a non-local model of phase-field type, describing the evolution of tumour cells in presence of a nutrient. The model couples a non-local and viscous Cahn-Hilliard equation…

Analysis of PDEs · Mathematics 2023-10-25 Matteo Fornoni

The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) and polynomial degree ($p$) to be used on each cell - has long been known to have better theoretical convergence properties than either $h$-…

Numerical Analysis · Mathematics 2023-09-14 Marc Fehling , Wolfgang Bangerth

Physics-informed neural networks (PINNs) are neural networks that embed the laws of dynamical systems modeled by differential equations into their loss function as constraints. In this work, we present a PINN framework applied to oncology.…

Machine Learning · Computer Science 2025-10-16 Kayode Olumoyin , Katarzyna Rejniak

It has been shown experimentally that contact interactions may influence the migration of cancer cells. Previous works have modelized this thanks to stochastic, discrete models (cellular automata) at the cell level. However, for the study…

Cell Behavior · Quantitative Biology 2009-03-26 Christophe Deroulers , Marine Aubert , Mathilde Badoual , Basil Grammaticos

The oversampling multiscale finite element method (MsFEM) is one of the most popular methods for simulating composite materials and flows in porous media which may have many scales. But the method may be inapplicable or inefficient in some…

Numerical Analysis · Mathematics 2012-11-16 Weibing Deng , Haijun Wu

In the optimization of turbomachinery components, shape sensitivities for fluid dynamical objective functions have been used for a long time. As peak stress is not a differential func- tional of the shape, such highly efficient procedures…

Numerical Analysis · Mathematics 2018-02-15 Hanno Gottschalk , Mohamed Saadi , Onur Tanil Doganay , Kathrin Klamroth , Sebastian Schmitz

Periodic micromagnetic finite element method (PM-FEM) is introduced to solve periodic unit cell problems using the Landau-Lifshitz-Gilbert equation. PM-FEM is applicable to general problems with 1D, 2D, and 3D periodicities. PM-FEM is based…

Numerical Analysis · Mathematics 2024-09-24 Fangzhou Ai , Jiawei Duan , Vitaliy Lomakin

We propose and study a strongly coupled PDE-ODE system with tissue-dependent degenerate diffusion and haptotaxis that can serve as a model prototype for cancer cell invasion through the extracellular matrix. We prove the global existence of…

Analysis of PDEs · Mathematics 2016-11-09 Anna Zhigun , Christina Surulescu , Aydar Uatay

A well-established approach for inferring full displacement and stress fields from possibly sparse data is to calibrate the parameter of a given constitutive model using a Bayesian update. After calibration, a (stochastic) forward…

Computational Engineering, Finance, and Science · Computer Science 2023-08-09 Vahab B. Narouie , Henning Wessels , Ulrich Römer

Statistical learning additions to physically derived mathematical models are gaining traction in the literature. A recent approach has been to augment the underlying physics of the governing equations with data driven Bayesian statistical…

Methodology · Statistics 2022-05-25 Connor Duffin , Edward Cripps , Thomas Stemler , Mark Girolami