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The SMART program improves students' memory, reasoning, and strategic thinking skills, crucial for academic success and career planning. This study explored the effect of Strategic Memory Advanced Reasoning Training (SMART) for final-year high school students, aiming to enhance their decision-making abilities and prepare them for University. Based on the literature, nine hypotheses were developed with SMART program implementation therapy as an independent variable with four sub-variables: cognitive skills, professional development, social skills, and academic skills, and their impact on the dependent variable, such as career decision-making. Using a smart partial least square-structural equation modeling (PLS-SEM) on 284 high school students, confirmatory factor analysis (CFA) and structural equation modeling (SEM) was implemented to confirm the measurement model. Path analysis was conducted to determine the relationship between independent and dependent variables. Results of the study revealed that SMART therapy significantly enhances cognitive abilities, academic performance, personal development, and social skills, collectively contributing to better career decision-making among final-year high school students. However, the direct impact of SMART on career decision-making was not supported, indicating that additional factors, such as social and emotional influences, play a role. These findings suggest that integrating SMART therapy into high school curricula can better prepare students for future challenges and career opportunities, aligning with Sustainable Development Goal 4 (Quality Education). A collaborative approach among stakeholders, policy support, and innovative practices are recommended to overcome potential obstacles and ensure the successful implementation of SMART therapy in educational settings.
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http://dx.doi.org/10.1186/s40359-025-02767-0 | DOI Listing |
Appl Radiat Isot
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Nuclear Engineering Department, School of Mechanical Engineering, Shiraz University, Shiraz, Iran.
Accurate determination of the parameters of each high purity germanium, HPGe detectors ensure the precision of quantitative results obtained from spectrum analysis. This study presents a comprehensive performance evaluation and long-term quality control assessment of a high-purity germanium (HPGe) gamma spectrometry system that has been operational for over 15 years. Key spectrometric measures were recorded, including energy resolution, peak shape ratios, asymmetry, peak-to-Compton ratio, relative efficiency, electronic noise, minimum detectable activity (MDA), and repeatability and reproducibility of the system.
View Article and Find Full Text PDFJACC Heart Fail
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Université de Lorraine, Inserm, Centre d'Investigations Cliniques Plurithématique 1433, Centre Hospitalier Régional Universitaire de Nancy, Nancy, France.
ACS Appl Mater Interfaces
September 2025
School of Materials and Energy, Guangdong University of Technology, Guangzhou 510006, China.
The development of anode materials for lithium-ion batteries must meet the demands for high safety, high energy density, and fast-charging performance. TiNbO is notable for its high theoretical specific capacity, low structural strain, and exceptional fast-charging capability, attributed to its Wadsley-Roth crystal structure. However, its inherently poor conductivity has hindered its practical application.
View Article and Find Full Text PDFJ Org Chem
September 2025
State Key Laboratory of Fine Chemicals, School of Chemical Engineering, Ocean and Life Sciences, Dalian University of Technology, Panjin 124221, P. R. China.
The Buchwald-Hartwig (B-H) reaction graph, a novel graph for deep learning models, is designed to simulate the interactions among multiple chemical components in the B-H reaction by representing each reactant as an individual node within a custom-designed reaction graph, thereby capturing both single-molecule and intermolecular relationship features. Trained on a high-throughput B-H reaction data set, B-H Reaction Graph Neural Network (BH-RGNN) achieves near-state-of-the-art performance with an score of 0.971 while maintaining low computational costs.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Department of Psychiatry, Helsinki University Hospital and Helsinki University, Helsinki, Finland.
Background: Internet-based cognitive behavioral therapies (iCBTs) are typically categorized into 2 types: therapist-assisted and self-guided. Both formats have accumulated substantial evidence supporting their cost-effectiveness and efficacy in treating a range of mental health conditions. However, therapist-assisted iCBTs tend to show lower dropout rates than self-guided versions.
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