We show that the "|Δμ| big is good" principle holds at temperatures above absolute zero (the so-called "finite-T regime"). We also provide the first conditions hinting at the validity of this reactivity rule in cases where the chemical reactions involved have different signs in their chemical potential variations.
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http://dx.doi.org/10.1063/5.0107355 | DOI Listing |
Comput Methods Biomech Biomed Engin
January 2025
School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, Changzhou University, Changzhou, P.R. China.
Slow eye movements (SEMs) are a reliable physiological marker of drivers' sleep onset, often accompanied by EEG alpha wave attenuation. A parallel multimodal 1D convolutional neural network (PM-1D-CNN) model is proposed to classify SEMs. The model uses two parallel 1D-CNN blocks to extract features from EOG and EEG signals, which are then fused and fed into fully connected layers for classification.
View Article and Find Full Text PDFNiger Med J
January 2025
Department of Epidemiology & Community Health, University of Ilorin, Nigeria.
Background: Sleep is a very important physiologic process which is necessary to maintain a state of well-being. Obstructive Sleep Apnea (OSA) is prevalent among all age groups with variations in presentation and severity. It is often underreported, especially among young people in the Low- and Middle-Income Countries LMICs.
View Article and Find Full Text PDFTob Induc Dis
January 2025
Institute of Health and Environment, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Introduction: Smoking behaviors can be quantified using various indices. Previous studies have shown that these indices measure and predict health risks differently. Additionally, the choice of measure differs depending on the health outcome of interest.
View Article and Find Full Text PDFFront Big Data
January 2025
School of Information Science and Technology, Shihezi University, Xinjiang, China.
Predictions of student performance are important to the education system as a whole, helping students to know how their learning is changing and adjusting teachers' and school policymakers' plans for their future growth. However, selecting meaningful features from the huge amount of educational data is challenging, so the dimensionality of student achievement features needs to be reduced. Based on this motivation, this paper proposes an improved Binary Snake Optimizer (MBSO) as a wrapped feature selection model, taking the Mat and Por student achievement data in the UCI database as an example, and comparing the MBSO feature selection model with other feature methods, the MBSO is able to select features with strong correlation to the students and the average number of student features selected reaches a minimum of 7.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Dermatology, Michigan Medicine, Ann Arbor, MI, United States.
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