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In part I, we address the issue of existence of solutions for Cauchy problems involving nonlinear hyperbolic equations for initial data in Sobolev spaces with scaling subcritical regularity. In particular, we analyse nonlinear estimates for null-forms in t ...
Statistical analyses of the first pop-in stress data, obtained by spherical tip-nanoindentation experiments on different metallic glasses (MGs) with tip radius, R-i, loading rate, (P) over dot, and structural state of the glass as experimental variables, s ...
In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...
Most works on AOP technologies aimed at removing contaminants from water have focused on the influence of experimental variables on the overall removal rate of specific target contaminants. Few studies have been devoted to proposing detailed kinetic models ...
As a real-time optimization technique, modifier adaptation (MA) has gained much significance in recent years. This is mainly due to the fact that MA can deal explicitly with structural plant-model mismatch and unknown disturbances. MA is an iterative techn ...
Methods to assess sufficient cause interactions are well developed for binary outcomes. We extend these methods to handle time-to-event outcomes, which occur frequently in medicine and epidemiology. Based on theory for marginal structural models in continu ...
Computational optimization of diffractive elements is often limited by a large number of design parameters. Adjoint method allows the gradient of target function respect to all design variables to be calculated with only two electromagnetic simulations. We ...
The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...
Diffractive optical elements with a large diffraction angle require feature sizes down to sub-wavelength dimensions, which require a rigorous electromagnetic computational model for calculation. However, the computational optimization of these diffractive ...
The emission parameterization is a crucial part of numerical pollen dispersion models. This paper shows that Artificial Neural Networks (ANNs) can substantially improve the performance of the Ambrosia pollen emission in numerical pollen dispersion models s ...
