AIMC Topic: Temperature

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Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids.

Journal of chemical information and modeling
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...

Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus.

The New phytologist
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...

Predicting mass transfer activation energy and physicochemical properties of dried onion using numerical modeling and artificial intelligence.

Scientific reports
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...

Uncertainty Quantification and Temperature Scaling Calibration for Protein-RNA Binding Site Prediction.

Journal of chemical information and modeling
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...

Synergistic effects of environmental factors on benthic diversity: Machine learning analysis.

Water research
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...

Engineering transverse cell deformation of bamboo by controlling localized moisture content.

Nature communications
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...

Computational intelligence modeling and optimization of small molecule API solubility in supercritical solvent for production of drug nanoparticles.

Scientific reports
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...

Neural network conditioned to produce thermophilic protein sequences can increase thermal stability.

Scientific reports
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...

Unveiling the factors shaping variability in biomass productivity: Meta-analysis of outdoor pilot-scale microalgal cultures.

Bioresource technology
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...

A measurement-based framework integrating machine learning and morphological dynamics for outdoor thermal regulation.

International journal of biometeorology
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...