An Improved Multi-Objective Grey Wolf Optimizer for Aerodynamic Optimization of Axial Cooling Fans by Yanzhao Gong, Richard Amankwa Adjei, Guocheng Tao, Yitao Zeng, Chengwei Fan

“…Finally, associative learning was leveraged for archive updating, allowing for perturbative mutation of solutions in crowded regions of the archive to increase solution diversity and improve the algorithm’s search capability. …”
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ASSESSMENT OF WORKS AND POSITIONS AS A REGULATING ELEMENT OF A MODERN LABOR ORGANIZATION AT AN ENTERPRISE by I. M. Savitskaya

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Relationship Between the Results of Arm Swing Data From the OpenPose-Based Gait Analysis System and MDS-UPDRS Scores by Kenta Abe, Ken-Ichi Tabei, Keita Matsuura, Kazuyuki Kobayashi, Tomoyuki Ohkubo

“…Motor functions of individuals with Parkinson’s disease (PD) have been studied by many methods such as sensors, 3D measurement devices, smartphone applications, and deep learning tools. …”
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Design and Evaluation of ADANet: A High-Fidelity Motion Acquisition Framework for Assistive Gesture-Based Interfaces by Md Ettashamul Haque, Atique Tajwar, Akm Azad, Salem A. Alyami, Md Mehedi Hasan

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Identification and validation of aging related genes in osteoarthritis by Jian Du, Jian Du, Tian Zhou, Yanghui Dong, Yunchao Sun, Wei Peng

“…The DEGs were intersected with ARGs to identify differentially expressed aging related genes (DEARGs), which were then subjected to functional enrichment analysis, PPI network analysis, and machine learning algorithms (LASSO and RF) to identify key genes. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…<b>Background/Objectives</b>: Sarcopenia and cognitive decline (CD) are prevalent in aging populations, impacting functionality and quality of life. The early detection of these diseases is challenging, often relying on in-person screening, which is difficult to implement regularly. …”
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Application of predictive models in boosting power of Alzheimer's disease clinical trials: A post hoc analysis of phase 3 solanezumab trials by Ali Ezzati, Christos Davatzikos, David A. Wolk, Charles B. Hall, Christian Habeck, Richard B. Lipton

“…Features used in predictive models included baseline demographics, apolipoprotein E ε4 genotype, neuropsychological scores, functional scores, and volumetric magnetic resonance imaging. …”
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Integrated bioinformatics and experiment validation reveal cuproptosis-related biomarkers and therapeutic targets in sepsis-induced myocardial dysfunction by Xuemei Shi, Zhonghan Yan, Ruilin Ding, Fenfen Xia, Yan Du, Xiaojie Wang, Qing Peng

“…Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to assess biological functions and immune cell infiltration, respectively. ceRNA and transcription factor networks were constructed to explore gene regulatory mechanisms, while consensus clustering was employed to define cuproptosis-related subtypes. …”
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Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

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SLC3A2 as a key anoikis−related gene for prognosis and tumor microenvironment remodeling in melanoma by Xiaojin Liu, Jiaheng Xie, Yingying Xiao

“…The clinical relevance and functional role of SLC3A2 were further validated using the BEST database and in vitro experiments, including shRNA-mediated knockdown, colony formation, and Transwell migration assays. …”
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

“…Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. …”
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Leveraging Diverse Cell-Death Patterns to Decipher the Interactive Relation of Unfavorable Outcome and Tumor Microenvironment in Breast Cancer by Yue Li, Ting Ding, Tong Zhang, Shuangyu Liu, Jinhua Wang, Xiaoyan Zhou, Zeqi Guo, Qian He, Shuqun Zhang

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Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy by Tu‐Lan Vu‐Han, Vikram Sunkara, Rodrigo Bermudez‐Schettino, Jakob Schwechten, Robin Runge, Carsten Perka, Tobias Winkler, Sebastian Pokutta, Claudia Weiß, Matthias Pumberger

“…Here, we present a data‐driven machine learning approach to a rare disease data set to predict spinal muscular atrophy (SMA)‐associated scoliosis. …”
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Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression by Christofer N. Yalung, Doldet Tantraviwat

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TECHNOLOGY-ASSISTED TEACHING ACTIVITIES IN AN ESAP CONTEXT: AN ECOLOGICAL PERSPECTIVE by Adina-Maria MEZEI

“…Additionally, pedagogic decisions are taken in relation to “local realities” (Tudor 2003), such as, the targeted students’ general knowledge of English, attitudes to language learning, preferred modes of learning, relevant background knowledge and also with respect to the functionality of the digital tools examined. …”
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Supplementary motor area enhanced hemodynamic responses to loading after inhibitory cTBS by Yongjun Qiao, Dan Zhao, Jin Yan, Zhi Chen, Xiaohui Song, Ya Zong, Chaozhe Zhu, Qing Xie, Chuanxin M. Niu

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Recognition of signs of Parkinson's disease based on the analysis of voice markers and motor activity by U. A. Vishniakou, Xia Yiwei

“…The time-frequency function (the wavelet function) and the Meyer kepstral coefficient function, the KNN algorithm (k-Nearest Neighbors, KNN) and the algorithm of a two-layer neural network are used for training and testing on publicly available datasets on speech changes and motion retardation in Parkinson's disease. …”
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Kolmogorov GAM Networks Are All You Need! by Sarah Polson, Vadim Sokolov

“…They are the machine learning version of Kolmogorov’s superposition theorem (KST), which provides an efficient representation of multivariate functions. …”
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Automatic Identification of Calcareous Lithologies Using Support Vector Machines, Borehole Logs and Fractal Dimension of Borehole Electrical Imaging by Jorge Alberto Leal, Luis Hernan Ochoa, Carmen Cecilia Contreras

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Cognitive impairment across the schizophrenia spectrum: a comparative neuropsychological study by Xiao-Yan He, An-Pei Wei, Zhuo-Hui Huang, Fei Wang, Li Li Guo, Cai-Lan Hou

“…Verbal memory: Hopkins Verbal Learning Test-Revised (HVLT-R).Visual memory: Brief Visuospatial Memory Test-Revised (BVMT-R). …”
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