There has been great interest in the development of non-invasive techniques for the diagnosis of liver fibrosis in chronic liver diseases, including ultrasound elastographic methods. Some of these methods have already been adequately studied for the non-invasive assessment of diffuse liver diseases. Others, however, such as two-dimensional Shear Wave Elastography (SWE), of more recent appearance, have yet to be validated and some aspects are for the moment incompletely elucidated. This review discusses some of the aspects related to two-dimensional SWE: the examination technique, the examination performance indicators, intra and interobserver agreement and clinical applications. Recommendations for a high-quality examination technique are formulated.

The goal of this paper is to evaluate non-parametric algorithms that achieve 3D texture synthesis from a single 2D sample. The algorithms under study are variants of the algorithm proposed by Wei and Levoy [1]. Several authors have proposed different algorithms that intend to better reproduce, in the output texture, the diversity learned in the input sample. Hence, we turn our attention to the improved algorithm proposed by Kopf et al. [2] and the particular histogram matching approach of Chen and Wang [3]. In addition, we propose to visit the voxels during synthesis according to the 3D extension of space filling curves. We investigate the algorithms capability to reproduce anisotropic textures. In particular we are interested in laminar textures, i.e. textures made of anisotropic sheets stacked along a given direction. Examples of such textures are snapshots of dense carbons observed by high resolution transmission electronic microscopy (HRTEM). Beyond the traditional subjective evaluation of the synthesized textures, we propose a genuine quantitative benchmark for the analysis of the synthesized textures which consists in comparing input and output gray level statistics and patterns morphology.

Polymer nanocomposites (PNCs) are functional hybrids lying at the interface of organic and inorganic realm, whose high versatility offers numerous possibilities to develop tailor-made materials with advanced material behaviors. Accordingly, a considerate combination of optically effective additive and particle-stabilizing polymer often opens up unique design possibilities, thereby offering momentous lead in creating advanced functional materials for targeted techno-commercial applications. Accordingly, optically effective nanofillers characterized by particle size and dielectric constant of the surrounding medium-dependent surface plasmon resonance effects may induce entirely new optical functionalities (UV and visible light absorption, optical dichroism, spectral manipulation, photonic emission and so forth) in the polymeric host. Herein, we discuss the major causative factors, which enable nanostructured materials to exhibit unique properties, general introduction to nanotechnology-enabled polymer-based nanocomposites and present a comprehensive review on functional properties and related applications of PNCs, with special emphasis on optical functionalities (photonic absorption encompassing UV shielding, color switching and refractive index engineering and photonic emission covering photoluminescence and spectral manipulations). This review also sheds light on the effect of nature of filler, filler morphology, filler size and filler composition and dispersion homogeneity on optical behaviors of polymer nanocomposites.

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Nanostructured coatings are extensively employed in aerospace applications as they unveil unique and excellent properties because of their nano-sized structural behavior. This article focusses on the study of preparation of yttrium (III) nitrate hexahydrate-based nano-sized structural coating obtained by sol-gel method and the analysis of their properties. The properties that are suitable for aerospace applications such as thermal stability, oxidation resistance ability, heat resistant nature, phase stability were analyzed using Scanning Electron Microscope (SEM), Energy Dispersive X-ray Analysis (EDX) characterization techniques.