Journal of chemical information and modeling
Jun 6, 2025
Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applicatio...
Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework. We inves...
The quality of the onion slices was statistically evaluated based on the variables of drying conditions, considering the following characteristics: drying time, color, shrinkage, water activity, and rehydration ratio, critical parameters in evaluatin...
Journal of chemical information and modeling
Jun 2, 2025
The black-box nature of deep learning has increasingly drawn attention to the reliability and uncertainty of predictive models. Currently, several uncertainty quantification (UQ) methods have been proposed and successfully applied in the fields of mo...
This study examines the water environmental factors of the Cangshan stream and benthic animal communities by using random forest, gradient boosting decision tree, and support vector machine models to analyze the complex response mechanisms of benthic...
Bamboo's native structure, defined by the vertical growth pattern of its vascular bundles and parenchyma cell tissue, limits its application in advanced engineering materials. Here we show an innovative method that controls localized moisture content...
Artificial Intelligence (AI) is applied in this research for the analysis of a novel green method for production of nanomedicine. The method is based on supercritical solvent for production of drug nanoparticles in which the AI was used to estimate t...
This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 mill...
Meta-analysis and machine learning is used to investigate factors influencing variation in biomass productivity in outdoor algal systems. Understanding these factors is essential for optimizing algal systems. Mean productivity across the analysed stu...
International journal of biometeorology
Apr 21, 2025
This study presents a comprehensive investigation into the interplay between machine learning (ML) models, morphological features, and outdoor thermal comfort (OTC) across three key indices: Universal Thermal Climate Index (UTCI), Physiological Equiv...
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