Drying is a complex process of simultaneous heat, mass, and momentum transport
phenomena with continuous phase changes. Numerical modelling is one of the most …

Deep learning is emerging in many industrial sectors in hand with big data analytics to
streamline production. In the biomanufacturing sector, big data infrastructure is lagging …

Hydrogen gas is a promising renewable energy storage medium when produced via water
electrolysis, but this process is limited by the sluggish kinetics of the anodic oxygen …

The motivation behind this study is to overcome the complex mathematical formulation and
time-consuming nature of traditional numerical methods used in solving differential …

In modern times, closed-loop control systems (CLCSs) play a prominent role in a wide
application range, from production machinery via automated vehicles to robots. CLCSs …

Recently, the use of machine‐learning (ML) models for pharmacokinetic (PK) modeling has
grown significantly. Although most of the current approaches use ML techniques as black …

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare
systems against pandemic situations. In response, many population-level computational …

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control
of infectious diseases, but addressing heterogeneity in the system poses a challenge. In this …

Interacting multi-scale physics in the Rotating Detonation Engine (RDE) lead to diverse
nonlinear dynamical behavior, including combustion wave mode-locking, modulation, and …

Systems biology tackles the challenge of understanding the high complexity in the internal
regulation of homeostasis in the human body through mathematical modelling. These …