An expert’s journey to implementing best process control via instrumentation, control strategies and PID control ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

The recent commentary by Manning et al highlights difficulties comparing results of gastrointestinal microbiome cohort studies.1 They demonstrate how methodological heterogeneity can substantially ...

Abstract: Safe reinforcement learning (RL) aims to learn policy while also ensuring the safety constraints. An increasingly common approach is to design a safety filter based on control barrier ...

Objectives The central nervous system is a significant extraglandular target in primary Sjögren’s syndrome (pSS), often ...

Abstract: Many problems in science and engineering can be mathematically modeled using partial differential equations (PDEs), which are essential for fields like computational fluid dynamics (CFD), ...

Results of a systematic review and meta-analysis showed that many multivariable models for predicting GCA have methodological flaws.

It was introduced by Michele Caputo in his 1967 paper. [1] In contrast to the Riemann–Liouville fractional derivative, when solving differential equations using Caputo's definition, it is not ...

Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to ...