Inorganic nanoparticles: Possible solution for different problems

Formation and Controlled Growth of Bismuth Titanate Phases into Mesoporous Silica Nanoparticles: An Efficient Self-Sealing Nanosystem for UV Filtering in Cosmetic Formulation. Biocompatible tailored zirconia mesoporous nanoparticles with high surface area for theranostic applications. Structural and photophysical properties of rare-earth complexes encapsulated into surface modified mesoporous silica nanoparticlesUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Computational Methods for Sparse Solution of Linear Inverse Problems

The goal of the sparse approximation problem is to approximate a target signal using a linear combination of a few elementary signals drawn from a fixed collection. This paper surveys the major practical algorithms for sparse approximation. Specific attention is paid to computational issues, to the circumstances in which individual methods tend to perform well, and to the theoretical guarantees available. Many fundamental questions in electrical engineering, statistics, and applied mathematics can be posed as sparse approximation problems, making these algorithms versatile and relevant to a plethora of applications