Graph Neural Networks for Parkinson's Disease Monitoring and Alerting.

Graph neural networks (GNNs) have been increasingly employed in the field of Parkinson's disease (PD) research. The use of GNNs provides a promising approach to address the complex relationship between various clinical and non-clinical factors that contribute to the progression of PD. This review paper aims to provide a comprehensive overview of the state-of-the-art research that is using GNNs for PD.

A high-performance capillary-fed electrolysis cell promises more cost-competitive renewable hydrogen.

Renewable, or green, hydrogen will play a critical role in the decarbonisation of hard-to-abate sectors and will therefore be important in limiting global warming. However, renewable hydrogen is not cost-competitive with fossil fuels, due to the moderate energy efficiency and high capital costs of traditional water electrolysers. Here a unique concept of water electrolysis is introduced, wherein water is supplied to hydrogen- and oxygen-evolving electrodes via capillary-induced transport along a porous inter-electrode separator, leading to inherently bubble-free operation at the electrodes.

A Novel Approach to Image Recoloring for Color Vision Deficiency.

In this paper, a novel method to modify color images for the protanopia and deuteranopia color vision deficiencies is proposed. The method admits certain criteria, such as preserving image naturalness and color contrast enhancement. Four modules are employed in the process.

Electronic structure modelling of the edge-functionalisation of graphene by MnO particles.

The use of graphenic carbon is attractive as a basal or intermediate support for catalytic particles in advanced catalytic electrodes. This popularity is motivated by its excellent electrical properties and ability to form foliated conformal coatings of exceptional surface area and flexibility. Surface- and edge-functionalisation of graphene sheets affords diverse routes to the covalent attachment of candidate catalytic species.