Magnetoencephalographic source localization and reconstruction via deep learning.

Within this manuscript a deep learning algorithm designed to achieve both spatial and temporal source reconstruction based on signals captured by MEG devices is introduced. Brain signal estimation at source level is a significant challenge in magnetoencephalographic (MEG) data processing. Traditional algorithms offer excellent temporal resolution but are limited in spatial resolution due to the inherent ill-posed nature of the problem.

Impact of carbon nanotubes on chloride diffusion in cement mortar under temperature gradient conditions.

Reinforcement corrosion induced by chloride ingress is a major durability issue in cementitious materials, particularly in harsh marine environments. Incorporating carbon nanotubes (CNTs) has emerged as a promising solution to mitigate chloride ingress. However, their performance against chloride diffusion under elevated temperatures remains unexplored.