Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large‐scale soybean dataset by Hawlader A. Al‐Mamun, Monica F. Danilevicz, Jacob I. Marsh, Cedric Gondro, David Edwards

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Developing supervised machine learning algorithms to classify lettuce foliar tissue samples into interpretation zones for 11 plant essential nutrients by Patrick Veazie, Hsuan Chen, Kristin Hicks, Jake Holley, Nathan Eylands, Neil Mattson, Jennifer Boldt, Devin Brewer, Roberto Lopez, Brian Whipker

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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

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A Practical Method for Red-Edge Band Reconstruction for Landsat Image by Synergizing Sentinel-2 Data with Machine Learning Regression Algorithms by Yuan Zhang, Zhekui Fan, Wenjia Yan, Chentian Ge, Huasheng Sun

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A New Robust Algorithm for Fault-Plane Parameters Identification: The 2009 L’Aquila (Central Italy) Seismic Sequence Case by Annarita Mangiacapra, Zaccaria Petrillo, Sergio Scippacercola, Luisa Valoroso, Rosa Nappi, Giuliana Alessio, Simona Tripaldi

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Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan by Ying-Qiang Liu, Tzu-Wei Chang, Lung-Chun Lee, Chia-Yu Chen, Pi-Shan Hsu, Yu-Tse Tsan, Chao-Tung Yang, Wei-Min Chu

“…Ultimately, 6687 adults were included in the final analysis, where we implemented three different ML algorithms, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost) in order to predict diabetes. …”
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An M-DeepSORT Algorithm for Pedestrian Detection and Tracking Based on Video Images – A Case Study in Ji-nan Subway Station by Wei ZHANG, Chuang ZHU, Yunchao QU, Guanhua LIU, Der-Horng LEE

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Enhancing Security in DNP3 Communication for Smart Grids: A Segmented Neural Network Approach by Shahid Allah Bakhsh, Muhammad Shahbaz Khan, Oumaima Saidani, Nada Alasbali, S. Qasim Abbas, Muhammad Almas Khan, Jawad Ahmad

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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Results Regression models demonstrated moderate predictive performance, with random forest delivering the best performance (MAE: 134.0 µm, RMSE: 171.3 µm, Pearson’s correlation coefficient: 0.45). …”
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The abundance and sett ecological characteristics of the Asian badger (Meles leucurus) in the Northeast Tiger and Leopard National Park (NE China) by Jiawei Li, Dongrui Li, Yanwen Fu, Yiwen Ma, Jianping Ge, Limin Feng

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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

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Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal... by Abhijeet Das

“…The Mahanadi River Basin, a vital and largest river of Odisha, faces increasing surface water quality deterioration due to anthropogenic activities. …”
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Measuring Online Battery AC Resistance Using a DC-DC Converter With Time and Frequency Hybrid Method by Seong-Jong Kim, Hwa-Pyeong Park, Tae-Hwan Jin, In-Jun Lee

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A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy by Ilyas Nurmemet, Yilizhati Aili, Yang Xiang, Aihepa Aihaiti, Yu Qin, Bilali Aizezi

“…The random forest (RF) feature selection algorithm identified three optimal parameters: Huynen_vol (volume scattering component), RVI_Freeman (radar vegetation index), and NDSI (normalized difference salinity index). …”
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Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning by Yong Xu, Xuewei Zhang, Wenlong Xie, Shihong Zhang, Yaqiang Tian, Liansheng Chen

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Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis by Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat, Abdelhadi Limane, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review by Xiaojian Gai, Chang Xu, Yajia Liu, Qingchun Feng, Shubo Wang

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Chinese Massage (Tuina) Attenuates Knee Osteoarthritis by Modulating Autophagy-Related Cytokines: A Multidisciplinary Methodological Investigation by Wang Z, Zhao C, Li M, Zhang L, Diao J, Wu Y, Yang T, Shi M, Lei Y, Wang Y, Li M, Bian Y, Zhou Y, Xu H

“…Zhen Wang,1,* Chi Zhao,1,2,* Mengmeng Li,1,2,* Lili Zhang,1,* Jieyao Diao,1 Yiming Wu,2 Tao Yang,2 Mingwei Shi,2 Yang Lei,2 Yu Wang,3 Miaoxiu Li,4 Yanqin Bian,5 Yunfeng Zhou,1 Hui Xu1,2 1College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 2Acupuncture and Massage Department, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 3College of Computer Science, Xidian University, Xian, People’s Republic of China; 4College of Acupuncture and Massage, Shanghai University of Chinese Medicine, Shanghai, People’s Republic of China; 5Orthopaedic Research Laboratory, University of California, Davis, CA, USA*These authors contributed equally to this workCorrespondence: Hui Xu, Email 15036065036@163.comBackground: Tuina therapy has demonstrated its potential in modulating autophagy-related factors in knee osteoarthritis (KOA); however, its core therapeutic targets and specific mechanisms require systematic elucidation through interdisciplinary research.Objective: This study investigated the mechanism by which Tuina alleviates KOA progression using multidimensional approaches, including Mendelian randomization (MR), in vivo experiments, and machine learning.Methods: Genetic data from genome-wide association studies of 60 cytokines and KOA were analyzed using MR analysis to identify autophagy-related factors significantly associated with KOA. …”
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Pre-modulated multi-coset sampling system by Huang Zhen, Bai Zhengyao

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A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa) by Li-Tang Qin, Xue-Fang Tian, Jun-Yao Zhang, Yan-Peng Liang, Hong-Hu Zeng, Ling-Yun Mo

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