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Imposing either Dirichlet or Neumann boundary conditions on the boundary of a smooth bounded domain $Omega$, we study the perturbation incurred by the voltage potential when the conductivity is modified in a set of small measure. We consider $left(gamma_{n}right)_{ninmathbb{N}}$, a sequence of perturbed conductivity matrices differing from a smooth $gamma_{0}$ background conductivity matrix on a measurable set well within the domain, and we assume $left(gamma_{n}-gamma_{0}right)gamma_{n}^{-1}left(gamma_{n}-gamma_{0}right)to0$ in $L^{1}(Omega)$. Adapting the limit measure, we show that the general representation formula introduced for bounded contrasts in citep{capdeboscq-vogelius-03a} can be extended to unbounded sequencesof matrix valued conductivities.
We consider a singularly-perturbed nonconvex energy functional which arises in the study of microstructures in shape memory alloys. The scaling law for the minimal energy predicts a transition from a parameter regime in which uniform structures are f
We study microstructure formation in two nonconvex singularly-perturbed variational problems from materials science, one modeling austenite-martensite interfaces in shape-memory alloys, the other one slip structures in the plastic deformation of crys
In this short note we prove two elegant generalized continued fraction formulae $$e= 2+cfrac{1}{1+cfrac{1}{2+cfrac{2}{3+cfrac{3}{4+ddots}}}}$$ and $$e= 3+cfrac{-1}{4+cfrac{-2}{5+cfrac{-3}{6+cfrac{-4}{7+ddots}}}}$$ using elementary methods. The first
In this work, we present a novel 3D-Convolutional Neural Network (CNN) architecture called I2I-3D that predicts boundary location in volumetric data. Our fine-to-fine, deeply supervised framework addresses three critical issues to 3D boundary detecti
We consider the inverse problem of recovering an isotropic electrical conductivity from interior knowledge of the magnitude of one current density field generated by applying current on a set of electrodes. The required interior data can be obtained