Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
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Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

“…Ferroptosis, a novel form of programmed cell death, may play a key role in CS and AS. …”
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NOVEL KEY VARIABLES IN THE SURVIVAL OF PATIENTS WITH MYELODYSPLASTIC NEOPLASMS: A PRACTICAL APPROACH USING MACHINE LEARNING by PRC Passos, RDB Dias, SCC Carneiro, IB Nogueira, JMGF Lima, RC Venâncio, ACG Lavor, JVG Gama, RF Pinheiro, SMM Magalhães

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Interprofessional Differences in Multidimensional Self-Efficacy Associated With Professional Performance in Nephrology During Case-Based Learning by Chia-Ter Chao, Mei-Yi Wu, Kuan-Yu Hung, Mai-Szu Wu, Jyh-Chong Liang

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Data-Driven Insights into Concrete Flow and Strength: Advancing Smart Material Design Using Machine Learning Strategies by Muwaffaq Alqurashi

“…Compressive strength (CS) and workability (flow) are two important performance measures of concrete, and this paper investigates how two evolutionary machine learning methods, gene expression programming (GEP) and multi-expression programming (MEP), might be used for this purpose. …”
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Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns by Hua‐jing Yuan, Hui Yu, Yi‐ding Yu, Xiu‐juan Liu, Wen‐wen Liu, Yi‐tao Xue, Yan Li

“…Bioinformatics and machine learning algorithms were utilized to screen the HF key genes and PCD‐related HF hub genes, and an HF diagnostic model was constructed on this. …”
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A socio-constructivist framework for tactical development in team sports: fostering critical thinking through collaborative learning by Samuel Jose Octavio Gaviria Alzate, Wilder Valencia Sánchez, Elkin Arias Arias

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DIRECTIONS OF PREPARATION OF FUTURE TEACHERS TO THE USE OF DISTANCE LEARNING TECHNOLOGIES IN PROFESSIONAL ACTIVITY (PRAXIOLOGICAL ASPECT OF THE ACTIVITY APPROACH) by Tatyana A. Boronenko, Vera S. Fedotova

“…The system of training to implementation of the distance learning technologies in the teaching activity is developed and described, consisting of the following directions: realisation within the program of the principal educational program of specialised training courses in variable-based curriculum parts; the organisation of educational and research activity of students with the use of distance learning technologies; classroom-based and extracurricular independent work of students directed to designing of teaching and learning aids and materials on the basis of distance learning technologies; application of elements of distance learning technologies for students’ teaching; attraction of students to formation of corpus of multimedia educational resources of university. …”
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Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database. by Ryoya Tsunoda, Keitaro Kume, Rina Kagawa, Masaru Sanuki, Hiroyuki Kitagawa, Kaori Mase, Kunihiro Yamagata

“…A manual analysis of the diagnostic accuracy and machine learning was performed. For machine learning, the datasets were preprocessed in three patterns and assigned to the XGBoost program using five-fold cross-validation. …”
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An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Next, an ensemble of machine learning (ML) models comprises three classifiers such as hybrid kernel extreme learning machine (HKELM), extreme gradient boosting (XGBoost), and support vector regression (SVR) for predicting the financial cost. …”
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The Impact of Open and Distance Learning (ODL) on Students' Psychological Well‐Being in Bangladesh: A Cross‐Sectional Study by Shahima Jabin

“…ABSTRACT Background and Aim The move towards Open and Distance Learning (ODL) has changed students' overall lives and perspectives in Bangladesh. …”
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Understanding How AI Chatbots Influence EFL Learners’ Oral English Learning Motivation and Outcomes: Evidence From Chinese Learners by Wenbo Wei, An Zhao, Hongning Ma

“…Designers can use them to optimize language learning programs for AI chatbots.…”
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Critical thinking skills of prospective chemistry teachers in chemistry learning with Ethno-Socio-Scientific issues integrated inquiry by Ratna Kumala Dewi, Sri Rahayu, Muntholib Muntholib, Woro Sumarni

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Conceptual Framework of Inquiry-Creative-Process Learning Model to Promote Critical Thinking Skills of Physics Prospective Teachers by W. Wahyudi, N. N. S. P. Verawati, S. Ayub, S. Prayogi

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Unveiling processing–property relationships in laser powder bed fusion: The synergy of machine learning and high-throughput experiments by Mahsa Amiri, Zahra Zanjani Foumani, Penghui Cao, Lorenzo Valdevit, Ramin Bostanabad

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The effects of students’ previous learning on graph-comprehension in the English as second language (ESL) textbooks in a Pakistani university by Irfan A Rind, Sajjad Alhawsawi

“…The recent emphasis on the importance of English language teaching and learning in public universities in Pakistan has resulted in the introduction of a new English as Second Language (ESL) programme including revised textbooks. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Within the framework of computational biology and machine learning strategies, and against the backdrop of global multicenter sepsis cohort data, this study aims to deeply mine and screen specific biomarkers related to the immune microenvironment and programmed cell death in populations across different life stages (neonates, children, and adults). …”
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Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients by Tagayasu Anzai, Kenji Hirata, Ken Kato, Kohsuke Kudo

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Transfer learning radiomic model predicts intratumoral tertiary lymphoid structures in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Feng Yi, Shichao Long, Mengsi Li, Linhui Zhong, Wenguang Liu, Deng Pan, Ganmian Dai, Wenzheng Li, Yue Ruan, Bocheng Zou

“…After features dimensionality and selection, corresponding features were used to construct transfer learning radiomic (TLR) models for diagnosing iTLS, and model interpretability was explored with pathway analysis in The Cancer Genome Atlas-Liver HCC. …”
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Conceptualizing Coproduced Climate Research as Care: Practical Lessons Learned With Women Farmland‐Owners in the Central Midwest United States by Linda Shenk, Jean Eells, Jr. William J. Gutowski, Kristie Franz, Danielle Robinson

“…We outline the creation and evolution of a storytelling‐based conservation program that allowed our diverse group to discover how the language of care could integrate climate analysis, conservation, and relationship‐building to foster tangible solutions. …”
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