Article describes how phase-specific damage tolerance was investigated for the AlCoCrFeNi2.1 high entropy alloy with a lamellar microstructure of L12 and B2 phases. Distinct differences in micro-scale deformation mechanisms were reflected in post-compression fractography, with L12-phase cantilevers showing typical characteristics of ductile failure, including the activation of multiple slip lanes, shear lips at the notch edge, and tearing inside the notch versus quasi-cleavage fracture with cleavage facets and a river pattern on the fracture surface for the B2-phase cantilevers.

Article describes how Aerosol Optical Depth (AOD)is a crucial atmospheric parameter in comprehending climate change, air quality, and its impacts on human health. This study presents a new solution to this challenge by providing a long-term, gapless satellite-derived AOD dataset for Texas from 2010 to 2022, utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) multi-angle implementation of atmospheric correction (MAIAC) products.

Article asserts that the nuclear receptor (NR) superfamily includes phylogenetically related ligand-activated proteins, which play a key role in various cellular activities. The authors developed Nuclear Receptor Prediction Tool (NRPreTo), a two-level NR prediction tool with a unique training approach where in addition to the sequence-based features used by existing NR prediction tools, six additional feature groups depicting various physiochemical, structural, and evolutionary features of proteins were utilized.

Article describes how Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers (PLC), play a crucial role in managing and regulating industrial processes. This article presents an overview of ICS security, covering its components, protocols, industrial applications, and performance aspects.

Article asserts that Alzheimer’s disease (AD) is a neurodegenerative disease that affects millions of people worldwide. The authors of the article propose two deep learning architectures based on RNN, namely Predicting Progression of Alzheimer’s Disease (PPAD) and PPAD-Autoencoder.