The idea that merely viewing nature can promote stress recovery has profound societal implications, driving the use of nature imagery in the design of environments where access to real nature is limited. Scientific support for this concept originates from a pioneering study by Ulrich et al. (1991), which …

This article focusses on the rise of agrogeological soil science in the early 20th century, especially in a Dutch-imperial context, as generating a novel geobiopolitical epistemology for the governance of natural and social worlds. Specifically, this article seeks to understand the consequences of agrogeologists’ …

Efficient hydrogen (H2) storage remains a major challenge for clean energy applications. This study presents an AI-driven methodology to optimize H2 storage in porous carbon adsorbents. A comprehensive dataset of 917 literature-derived entries was used to develop two machine learning models: Random Forest …

To broaden the application of biomethanation for energy storage and renewable integration, this study investigates the performance of a trickle-bed reactor (TBR) for hydrogen (H2) utilisation in biogas upgrading, using both pure Carbon dioxide (CO2) and biogas-derived CO2 as substrates for methane (CH4) …

Power-to-X technologies play a crucial role in accelerating the energy and material transition. A key opportunity lies in integrating these systems with existing bio-based infrastructures such as anaerobic digesters, providing a reliable source of biogenic carbon. Developing effective Power-to-Methanol …

Computed tomography (CT) at the third lumbar vertebra (L3) is widely used for muscle quantification, but manual segmentation is labor intensive. This study externally validates an AI model, trained on a public dataset, for automated L3 muscle segmentation using an independent cohort, including a subgroup …