Stochastic Demand-Side Management for Residential Off-Grid PV Systems Considering Battery, Fuel Cell, and PEM Electrolyzer Degradation by Mohamed A. Hendy, Mohamed A. Nayel, Mohamed Abdelrahem

“…The simulation results indicate that the proposed method achieved total degradation cost reductions of 16.66% and 42.6% for typical summer and winter days, respectively, in addition to a reduction of the levelized cost of energy (LCOE) by about 22.5% compared to the average performance of 10,000 random operation scenarios.…”
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A temporal fusion method for modeling the rate of penetration during deep geological drilling by Yang ZHOU, Chengda LU, Min WU, Xin CHEN, Ningping YAO, Haitao SONG, Youzhen ZHANG

“…Post-temporal regulation, the ROP model yielded more accurate predicted trends for both well sections, with respective prediction accuracy reaching up to 80% and 87.5%. …”
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Cellular senescence defining the disease characteristics of Crohn’s disease by Wenyu Zhang, Xianzong Ma, Xianzong Ma, Wenqing Tian, Yongsheng Teng, Meihua Ji

“…The support vector machine (SVM) algorithm, random forest algorithm and LASSO regression analysis was used to construct a diagnostic model. …”
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The Potential Mechanism of Curcumin in Treating Oral Squamous Cell Carcinoma Based on Integrated Bioinformatic Analysis by Wu Siyuan, Lv Xiaozhi, Wu Jialin, Haigang Wei, Shiwei Liu, Chen Zou, Jing Song, Li Xia, Ai Yilong

“…The enrichment analysis was performed by the ClusterProfiler algorithm and Metascape, respectively. Then, a protein-protein interaction network was created, and the maximal clique centrality algorithm was used to identify the top 10 hub genes. …”
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Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Mustafa Alshwayyat, Tala Abdulsalam Alshwayyat, Siya sawan, Ghaith Heilat, Hanan M. Hammouri, Sara Mheid, Batool Al Shweiat, Hamdah Hanifa

“…To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using five Machine Learning (ML) algorithms to predict the 5-year survival. A validation method incorporating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate the accuracy and reliability of ML models. …”
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CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…By doing so, it provides more accurate time series modeling, optimizes algorithmic trading strategies, and facilitates investment portfolio risk warnings.ResultsExperiments conducted on four real-world financial datasets demonstrate that CMDMamba achieves a 10.4% improvement in prediction accuracy for multivariate forecasting tasks compared to state-of-the-art models.DiscussionMoreover, CMDMamba excels in both predictive accuracy and computational efficiency, setting a new benchmark in the field of financial time series forecasting.…”
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Optimized Tile Quality Selection in Multi-User 360° Video Streaming by Moatasim Mahmoud, Stamatia Rizou, Andreas S. Panayides, Nikolaos V. Kantartzis, George K. Karagiannidis, Pavlos I. Lazaridis, Zaharias D. Zaharis

“…Specifically, we formulate the problem of tile quality selection in multi-user bandwidth-constrained communications and propose an algorithm that assigns the quality levels of transmitted tiles. …”
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Potential of solar-induced chlorophyll fluorescence for monitoring long-term dynamics of soil salinity in Central Asia the Xinjiang Region China by Kuangda Cui, Kuangda Cui, Jianli Ding, Jianli Ding, Jinjie Wang, Jinjie Wang, Jiao Tan, Jiao Tan, Lijing Han, Jiangtao Li, Jiangtao Li

“…Solar-induced chlorophyll fluorescence (SIF), which reflects plant photosynthetic status and stress, shows promise for monitoring salinity but remains underutilized in this region.MethodsThis study integrated SIF-derived indices (SIFI) with soil salinity data to build a region-specific prediction model. Using a random forest algorithm, soil salinity was classified into five levels based on satellite data and ground references from 2000–2020. …”
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Toward Intelligent Financial Advisors for Identifying Potential Clients: A Multitask Perspective by Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

“…Thus, extracting useful information from various characteristics of users and further predicting their purchase inclination are urgent. However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. …”
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Artificial intelligence based analysis for magnetized casson fluid in partially heated cavity rooted with heated fin by Khalil Ur Rehman, Wasfi Shatanawi, Lok Yian Yian

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Single-image super-resolution of gamma-ray imaging system using deep denoiser prior based on plug-and-play framework by Guo-Guang Li, Liang Sheng, Bao-Jun Duan, Yang Li, Yan Song, Zi-Jian Zhu, Wei-Peng Yan, Dong-Wei Hei, Qing-Zi Xing

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Geoecological Analysis of the Effects of Pipeline Transport on the Environment of Transit Regions (Voronezh Region, Russia) by L. A. Mezhova, A. M. Lugovskoy, Yu. N. Gladkiy, A. B. Glazyeva, O. Yu. Sushkova, L. B. Vampilova, A. A. Sokolova, L. A. Lugovskaya

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Visible, near-infrared, and shortwave-infrared spectra as an input variable for digital mapping of soil organic carbon by Vahid Khosravi, Asa Gholizadeh, Radka Kodešová, Prince Chapman Agyeman, Mohammadmehdi Saberioon, Luboš Borůvka

“…Thirty rasters were then created using interpolation of the selected spectra and served as the input variables – with and without EPCs – to test and compare the developed models and SOC predictive maps with each other and with those retrieved from the third approach: iii) kriging using OK of the measured and ML-predicted SOC. …”
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Experimental Investigation and NSGA-III Multi-Criteria Optimization of 60CrMoV18-5 Cold-Work Tool Steel Machinability Under Dry CNC Hard Turning Conditions by Nikolaos A. Fountas, Ioannis G. Papantoniou, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

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On nonlinear coupled differential system for heat transfer in magnetized enclosure with T-shaped baffle by using machine learning by Khalil Ur Rehman, Wasfi Shatanawi, Lok Yian Yian

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Design Principles of a Flat-Pack Electronic Sensor Kit with Intelligent User Interface Calibrations: A Case Study of Monitoring Sedentary Behavior in Workplace by Ananda Maiti, Vanessa Ward, Amy Hilliard, Anjia Ye, Scott J. Pedersen

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A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
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AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

“…Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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Combining Near-Infrared Spectroscopy and Chemometrics for Rapid Recognition of an Hg-Contaminated Plant by Bang-Cheng Tang, Hai-Yan Fu, Qiao-Bo Yin, Zeng-Yan Zhou, Wei Shi, Lu Xu, Yuan-Bin She

“…The NIRS measurements of impacted sample powders were collected in the mode of reflectance. The DUPLEX algorithm was utilized to split the NIRS data into representative training and test sets. …”
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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

“…The framework analyzes the interactions between weather, soil, irrigation strategies, and other factors, enhancing cotton yield prediction. The results indicate that the intelligent decision-making algorithm outperforms traditional methods under data limitations, reducing the irrigation water consumption-yield ratio (Ui) by 3.99 %, while increasing yield by 8.5 % to 9724 kg/ha, thus achieving both water-saving and yield-enhancing objectives. …”
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