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A prediction model for electrical strength of gaseous medium based on molecular reactivity descriptors and machine learning method.
J Mol Model
January 2025
Hubei Key Laboratory·for High-Efficiency-Utilization of Solar Energy and Operation, Control of Energy-Storage System, Hubei-University of Technology, Wuhan, 430068, China.
Context: Ionization and adsorption in gas discharge are similar to electrophilic and nucleophilic reactions. The molecular descriptors characterizing reactions such as electrostatic potential descriptors are useful in predicting the electrical strength of environmentally friendly gases. In this study, descriptors of 73 molecules are employed for correlation analysis with electrical strength.
View Article and Find Full Text PDFEfficient Nitrate to Ammonia Conversion on Bifunctional IrCu Alloy Nanoparticles.
ACS Nano
January 2025
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518000, China.
Electrochemical nitrate reduction (NORR) to ammonia presents a promising alternative strategy to the traditional Haber-Bosch process. However, the competitive hydrogen evolution reaction (HER) reduces the Faradaic efficiency toward ammonia, while the oxygen evolution reaction (OER) increases the energy consumption. This study designs IrCu alloy nanoparticles as a bifunctional catalyst to achieve efficient NORR and OER while suppressing the unwanted HER.
View Article and Find Full Text PDFVGX: VGG19-Based Gradient Explainer Interpretable Architecture for Brain Tumor Detection in Microscopy Magnetic Resonance Imaging (MMRI).
Microsc Res Tech
January 2025
AIDA Lab. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia.
The development of deep learning algorithms has transformed medical image analysis, especially in brain tumor recognition. This research introduces a robust automatic microbrain tumor identification method utilizing the VGG16 deep learning model. Microscopy magnetic resonance imaging (MMRI) scans extract detailed features, providing multi-modal insights.
View Article and Find Full Text PDFSex-specific impacts of caffeine on body composition: commentary on a retrospective cohort study.
J Int Soc Sports Nutr
December 2025
University of Bologna-Alma Mater Studiorum, Department of Quality of Life Sciences, Bologna, Italy.
Background: Understanding the impact of caffeine intake on body composition is a topic of growing research interest. The article "Association Between Caffeine Intake and Fat-Free Mass Index: A Retrospective Cohort Study" by Tian et al. explored this relationship, highlighting a positive correlation between caffeine consumption and fat-free mass index (FFMI).
View Article and Find Full Text PDFAdvanced microgrid optimization using price-elastic demand response and greedy rat swarm optimization for economic and environmental efficiency.
Sci Rep
January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
In this paper, a comprehensive energy management framework for microgrids that incorporates price-based demand response programs (DRPs) and leverages an advanced optimization method-Greedy Rat Swarm Optimizer (GRSO) is proposed. The primary objective is to minimize the generation cost and environmental impact of microgrid systems by effectively scheduling distributed energy resources (DERs), including renewable energy sources (RES) such as solar and wind, alongside fossil-fuel-based generators. Four distinct demand response models-exponential, hyperbolic, logarithmic, and critical peak pricing (CPP)-are developed, each reflecting a different price elasticity of demand.
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