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Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.
J Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
View Article and Find Full Text PDFExploring the significance of medical humanities in shaping internship performance: insights from curriculum categories.
Med Educ Online
December 2025
Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan.
Background: Medical Humanities (MH) curricula integrate humanities disciplines into medical education to nurture essential qualities in future physicians. However, the impact of MH on clinical competencies during formative training phases remains underexplored. This study aimed to determine the influence of MH curricula on internship performance.
View Article and Find Full Text PDFEnhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFLeveraging molecular dynamics, physicochemical, and structural analysis to explore OMP33-36 protein as a drug target in Acinetobacter baumannii: An approach against nosocomial infection.
J Mol Graph Model
January 2025
Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow Campus, Gomtinagar Extension, Lucknow, 226028, India; Research Cell, Amity University Uttar Pradesh, Lucknow Campus, India. Electronic address:
The Acinetobacter baumannii is a member of the "ESKAPE" bacteria responsible for many serious multidrug-resistant (MDR) illnesses. This bacteria swiftly adapts to environmental cues leading to the emergence of multidrug-resistant variants, particularly in hospital/medical settings. In this work, we have demonstrated the outer membrane protein 33-36 (Omp33-36) porin as a potential therapeutic target in A.
View Article and Find Full Text PDFInfluence of family socioeconomic status on academic buoyancy and adaptability: Mediating effect of parental involvement.
Acta Psychol (Amst)
January 2025
School of Mathematical Sciences, Beijing Normal University, Beijing, China. Electronic address:
Prior studies highlight the importance of academic buoyancy and adaptability in educational trajectories, yet the influence of family-related factors remains less explored. Anchored in Bronfenbrenner's ecological systems theory, this research examines how family socioeconomic status (SES) influences academic buoyancy and adaptability, the predictive relation between family SES and parental involvement, and whether parental involvement mediates the impact of family SES on academic outcomes. We surveyed 1164 junior high school students from China.
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