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We provide a deep investigation of the notions of - and ${}^{\infty}$-hypoellipticity for partial differential operators with constant Colombeau coefficients. This involves generalized polynomials and fundamental solutions in the dual of a Colombeau algebra. Sufficient conditions and necessary conditions for - and ${}^{\infty}$-hypoellipticity are given

In this paper we combine the dual-mixed finite element method with a Dirichlet-to-Neumann mapping (given in terms of a boundary integral operator) to solve linear exterior transmission problems in the plane. As a model we consider a second order elliptic equation in divergence form coupled with the Laplace equation in the exterior unbounded region. We show that the resulting mixed variational formulation and an associated discrete scheme using Raviart-Thomas spaces are well posed, and derive the...

The paper deals with the dimensional reduction from 2D to 1D in magnetoelastic interactions. We adopt a simplified, but nontrivial model described by the Landau-Lifshitz-Gilbert equation for the magnetization field coupled to an evolution equation for the displacement. We identify the limit problem by using the so-called energy method.

In this article we survey some of the most important developments since the 1980 paper of A.P. Calderón in which he proposed the problem of determining the conductivity of a medium by making voltage and current measurements at the boundary.

This paper deals with the solution of problems involving partial differential equations in ${\mathbb{R}}^{3}$. For three dimensional case, methods are useful if they require neither domain boundary regularity nor regularity for the exact solution of the problem. A new domain decomposition method is therefore presented which uses low degree finite elements. The numerical approximation of the solution is easy, and optimal error bounds are obtained according to suitable norms.

$\Gamma $-convergence techniques and relaxation results of constrained energy functionals are used to identify the limiting energy as the thickness $\epsilon $ approaches zero of a ferromagnetic thin structure ${\Omega}_{\epsilon}=\omega \times (-\epsilon ,\epsilon )$, $\omega \subset {\mathbb{R}}^{2}$, whose energy is given by$${\mathcal{E}}_{\epsilon}\left(\overline{m}\right)=\frac{1}{\epsilon}{\int}_{{\Omega}_{\epsilon}}\left(W(\overline{m},\nabla \overline{m})+\frac{1}{2}\nabla \overline{u}\xb7\overline{m}\right)\phantom{\rule{0.166667em}{0ex}}\mathrm{d}x$$subject to$$\text{div}(-\nabla \overline{u}+\overline{m}{\chi}_{{\Omega}_{\epsilon}})=0\phantom{\rule{1.0em}{0ex}}\text{on}{\mathbb{R}}^{3},$$and to the constraint$$|\overline{m}|=1\text{on}{\Omega}_{\epsilon},$$where $W$ is any continuous function satisfying $p$-growth assumptions with $p\>1$. Partial results are also obtained in the case $p=1$, under an additional assumption on $W$.

Γ-convergence techniques and relaxation results of constrained energy functionals are used to identify the limiting energy as the thickness ε approaches zero of a ferromagnetic thin structure ${\Omega}_{\epsilon}=\omega \times (-\epsilon ,\epsilon )$, $\omega \subset {\mathbb{R}}^{2}$, whose energy is given by $${\mathcal{E}}_{\epsilon}\left(\overline{m}\right)=\frac{1}{\epsilon}{\int}_{{\Omega}_{\epsilon}}\left(W(\overline{m},\nabla \overline{m})+\frac{1}{2}\nabla \overline{u}\xb7\overline{m}\right)\phantom{\rule{0.166667em}{0ex}}\mathrm{d}x$$ subject to $$\text{div}(-\nabla \overline{u}+\overline{m}{\chi}_{{\Omega}_{\epsilon}})=0\phantom{\rule{1.0em}{0ex}}\phantom{\rule{4.0pt}{0ex}}\text{on}\phantom{\rule{4.0pt}{0ex}}{\mathbb{R}}^{3},$$ and to the constraint $$|\overline{m}|=1\phantom{\rule{4.0pt}{0ex}}\text{on}\phantom{\rule{4.0pt}{0ex}}{\Omega}_{\epsilon},$$ where W is any continuous function satisfying p-growth assumptions with p> 1. Partial results are also obtained in the case p=1, under an additional assumption on W.

In this paper, we introduce a set of methods for processing and analyzing long time series of 3D images representing embryo evolution. The images are obtained by in vivo scanning using a confocal microscope where one of the channels represents the cell nuclei and the other one the cell membranes. Our image processing chain consists of three steps: image filtering, object counting (center detection) and segmentation. The corresponding methods are based on numerical solution of nonlinear PDEs, namely...