Differentiation characteristics and evolutionary mechanisms of agricultural regional functions in Loess Hilly and Gully Region by LONG Pei, WANG Yongsheng, LU Xue

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Integrating weighted gene co-expression network analysis and machine learning to elucidate neural characteristics in a mouse model of depression by Jinli Gao, Qinglang Wang, Jie Liu, Siqian Zheng, Jiahong Liu, Zhiyong Gao, Cheng Zhu

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Multi-Field-Coupled Model and Solution of Active Electronically Scanned Array Antenna Based on Model Reconstruction by Dan Han, Jin Huang, Jinzhu Zhou, Mei Wang, Sen Xu, Haitao Li, Shen Li

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An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan by Ghulam Abbas, Arshad Ali, Faizan Rashid, Naveed Ashraf, Zohaib Mushtaq, Muhammad Zubair

“…Assessing and effectively optimizing wind power potential for a wind site demands accurate calculation of Weibull parameters. In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). …”
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The Impact of Integrated Project-Based Learning and Flipped Classroom on Students’ Computational Thinking Skills: Embedded Mixed Methods by Muh Fitrah, Anastasia Sofroniou, Caly Setiawan, Widihastuti Widihastuti, Novi Yarmanetti, Melinda Puspita Sari Jaya, Jontas Gayuh Panuntun, Arfaton Arfaton, Septrisno Beteno, Ika Susianti

“…The findings indicate that PBL integrated with flipped classrooms significantly improved students’ decomposition, pattern recognition, and abstraction skills. The implementation of PBL, integrated with a flipped classroom, created an interactive learning environment, fostering active engagement and enhancing students’ understanding and skills in solving mathematical concepts. …”
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Distribution of Choroidal Thinning in High Myopia, Diabetes Mellitus, and Aging: A Swept-Source OCT Study by Francisco de Asís Bartol-Puyal, Carlos Isanta, Óscar Ruiz-Moreno, Beatriz Abadia, Pilar Calvo, Luis Pablo

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A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

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Development of a high-spatial-resolution annual emission inventory of greenhouse gases from open straw burning in Northeast China from 2001 to 2020 by Z. Song, Z. Song, L. Zhang, C. Tian, Q. Fu, Q. Fu, Z. Shen, R. Zhang, D. Liu, D. Liu, S. Cui, S. Cui

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Multiobjective Approach to the Transit Network Design Problem with Variable Demand considering Transit Equity by Su Jin Park, Seungmo Kang, Young-Ji Byon, Seung-Young Kho

“…Existing research on the transit network design problem has tended to focus on minimizing the various costs for both transit operators and users. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…Abstract With the rapid advancement of technology, aerial interaction patterns have become increasingly complex, making intelligent air combat a prominent and cutting-edge research area in multi-agent systems. …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
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Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting. by Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola

“…In recent years, numerous methods were developed for Supply Chain (SC) demand forecasting, which posed several limitations related to inadequate handling of dynamic time series patterns and data requirement problems. Thus, this research proposes a Migrative Armadillo Optimization-enabled one-dimensional Quantum convolutional neural network (MiA + 1D-QNN) for effective demand forecasting. …”
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Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Based on an empirical analysis of 3,135,675 social media dissemination data points from 94 corporate crisis incidents, this study explores effective crisis response patterns for enterprises through three dimensions: response timing, methods, and content. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…Deep learning-based models assist radiologists by detecting patterns, generating probability maps, and predicting outcomes like heart failure. …”
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Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage by Tingli Cheng, Minyou Chen, Yingxiang Wang, Bo Li, Muhammad Arshad Shehzad Hassan, Tao Chen, Ruilin Xu

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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…Specifically, the Intelligent Voyage Optimization algorithm effectively tunes the model hyperparameters and the deployment of hybrid features contributes to the proposed model to detect attack patterns effectively. …”
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Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…The review introduces an innovative clustering approach that provides a nuanced understanding of research trends and methodological gaps. In addition, we discuss the ethical implications of DL in RUL estimation, addressing concerns about privacy and algorithmic bias. …”
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Identification of Nicotinic Acetylcholine Receptor for N‐Acetylcysteine to Rescue Nicotine‐induced Injury Using Beating Cilia in Primary Tissue Derived Airway Organoids by Yichao Zheng, Qinyong Tian, Haowei Yang, Yongde Cai, Jiaxin Zhang, Yifen Wu, Shuo Zhu, Zuocheng Qiu, Yimin Lin, Jiangquan Hong, Yi Zhang, David Dockrell, Shaohua Ma

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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…Simulation results reveal that while the voltage Park's vector time behavior of a healthy system remains stable, it exhibits circular or mixed patterns under faulty conditions. These patterns enable the identification of four types of short circuit faults—single-line-to-ground (LG), line-to-line (LL), line-to-line-to-ground (LLG), and three-line (3L) faults—by analyzing 3D voltage Park's waveforms at network buses. …”
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