A fault diagnosis method for rolling bearing based on gram matrix and multiscale convolutional neural network.

The safety and reliability of rotating machinery hinge significantly on the proper functioning of rolling bearings. In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. However, the vibration signals collected by machines are inevitably affected by irrelevant noise because of the complex working environments of bearings.

Mechanisms of breast cancer treatment using Gentiana robusta: evidence from comprehensive bioinformatics investigation.

This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.

A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images.

Weather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather recognition. However, previous studies have addressed few types of weather phenomena recognition from images with insufficient accuracy.

Substrate transport and drug interaction of human thiamine transporters SLC19A2/A3.

Thiamine and pyridoxine are essential B vitamins that serve as enzymatic cofactors in energy metabolism, protein and nucleic acid biosynthesis, and neurotransmitter production. In humans, thiamine transporters SLC19A2 and SLC19A3 primarily regulate cellular uptake of both vitamins. Genetic mutations in these transporters, which cause thiamine and pyridoxine deficiency, have been implicated in severe neurometabolic diseases.

Dual-role ion dynamics in ferroionic CuInPS: revealing the transition from ferroelectric to ionic switching mechanisms.

Due to its "ferroionic" nature, CuInPS combines switchable ferroelectric polarization with highly mobile Cu ions, allowing for multiple resistance states. Its conductive mechanism involves ferroelectric switching, ion migration, and corresponding intercoupling, which are highly sensitive to external electric field. Distinguishing the dominant contribution of either ferroelectric switching or ion migration to dynamic conductivity remains a challenge and the conductive mechanism is not clear yet.