The estimation and partitioning of evapotranspiration in a coniferous plantation in subtropical China.

Accurate estimations of forest evapotranspiration (ET) and its components, transpiration (T) and evaporation (E), are important for deep understanding and predicting the responses of forest water cycles to climate change. In this study, the improved Shuttleworth-Wallace model (SWH) was applied to estimate ET, T, and E during 2003-2014 in a subtropical planation, and the modeled results were verified using measurements by the eddy covariance technique, sap flow, and micro-lysimeter method. The study aimed to clarify whether it is feasible and reliable to use the SWH model to estimate and partition ET in forests.

Multi-modality artificial intelligence in digital pathology.

In common medical procedures, the time-consuming and expensive nature of obtaining test results plagues doctors and patients. Digital pathology research allows using computational technologies to manage data, presenting an opportunity to improve the efficiency of diagnosis and treatment. Artificial intelligence (AI) has a great advantage in the data analytics phase.

Carbon doping switching on the hydrogen adsorption activity of NiO for hydrogen evolution reaction.

Hydrogen evolution reaction (HER) is more sluggish in alkaline than in acidic media because of the additional energy required for water dissociation. Numerous catalysts, including NiO, that offer active sites for water dissociation have been extensively investigated. Yet, the overall HER performance of NiO is still limited by lacking favorable H adsorption sites.