The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications

Reinforcement learning (RL) methods can successfully solve complex optimization problems. Our article gives a systematic overview of major types of RL methods, their applications at the field of Industry 4.0 solutions, and it provides methodological guidelines to determine the right approach that can be fitted better to the different problems, and moreover, it can be a point of reference for R&D projects and further researches.

l-Arginine and COVID-19: An Update

l-Arginine is involved in many different biological processes and recent reports indicate that it could also play a crucial role in the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, we present an updated systematic overview of the current evidence on the functional contribution of L-Arginine in COVID-19, describing its actions on endothelial cells and the immune system and discussing its potential as a therapeutic tool, emerged from recent clinical experimentations.

Distributed Computing Column 83 Five Ways Not To Fool Yourself

Overview. In this edition of the column, we have a very interesting and instructive contribution from Tim Harris (Microsoft, Cambridge, UK), whose goal is to provide a systematic overview of practical, "hands-on" techniques for the correct performance evaluation of a complex distributed system.