A deep learning based framework for the classification of multi- class capsule gastroscope image in gastroenterologic diagnosis.

The purpose of this paper is to develop a method to automatic classify capsule gastroscope image into three categories to prevent high-risk factors for carcinogenesis, such as atrophic gastritis (AG). The purpose of this research work is to develop a deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. In this research work, we proposed deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image.

High coercivity PrFeB magnetic nanoparticles by a mechanochemical method.

NdFeB nanoparticles are widely used because of their outstanding hard magnetic properties. In fact, PrFeB has higher magneto-crystalline anisotropy than NdFeB, which makes Pr-Fe-B a promising magnetic material. However, the chemical synthesis route to PrFeB nanoparticles is challenging because of the higher reduction potential of Pr, as well as the complex annealing conditions.

Biaxial strain modulated the electronic structure of hydrogenated 2D tetragonal silicene.

Silicene-based materials have attracted great attention due to their easier incorporation into silicon-based devices and components. In addition to the reported hydrogenated 2D tetragonal silicene (γ-SiH), we propose two stable atomic configurations of hydrogenated 2D tetragonal silicene (α-SiH and β-SiH) based on first-principles calculation. The calculated results indicate hydrogenation can effectively open the band gap of 2D tetragonal silicene, α-SiH is a semiconductor with a direct band gap of 2.

A Highly Conductive MOF of Graphene Analogue Ni (HITP) as a Sulfur Host for High-Performance Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries have been considered as one of the most promising energy storage systems owing to their high theoretical capacity and energy density. However, their commercial applications are obstructed by sluggish reaction kinetics and rapid capacity degradation mainly caused by polysulfide shuttling. Herein, the first attempt to utilize a highly conductive metal-organic framework (MOF) of Ni (HITP) graphene analogue as the sulfur host material to trap and transform polysulfides for high-performance Li-S batteries is made.