Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…The water production rate and the total annual cost rate were considered as two objective functions. Also, five design variables are selected after considering their effects on the objective functions. …”
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Gross Tonnage-Based Statistical Modeling and Calculation of Shipping Emissions for the Bosphorus Strait by Kaan Ünlügençoğlu

“…These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. …”
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rcprd: An R package to simplify the extraction and processing of Clinical Practice Research Datalink (CPRD) data, and create analysis-ready datasets. by Alexander Pate, Rosa Parisi, Evangelos Kontopantelis, Matthew Sperrin

“…Functions are available to extract common variable types (e.g., history of a condition, or time until an event occurs, relative to an index date), and more general functions for database queries, allowing users to define their own variables for extraction. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The Kolmogorov-Arnold Network (KAN) is a computational framework rooted in the Kolmogorov-Arnold representation theorem, which states that any continuous function of multiple variables can be expressed as a superposition of univariate functions. …”
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Effects of Different Irrigation Regimes on Root Growth and Physiological Characteristics of Mulch-Free Cotton in Southern Xinjiang by Feiyan Su, Ziyang Guo, Bingrong Wu, Jichuan Wang, Shuangrong Chen

“…It can be concluded that no mulching has a certain impact on cotton root distribution and leaf physiological function. When the irrigation amount is 450–525 mm and irrigation times is 10–12, it is beneficial for promoting root growth and plays a role in leaf physiological function, and the water use efficiency (WUE) is high, which can provide reference for the scientific water management of mulch-free cotton in production practice.…”
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Study on GPR Image Restoration for Urban Complex Road Surfaces Using an Improved CycleGAN by Xinxin Huang, Jialin Liu, Feng Yang, Xu Qiao, Liang Gao, Tingyang Fu, Jianshe Zhao

“…In urban road detection using Ground Penetrating Radar (GPR), challenges arise from complex and variable road structures and diversified detection environments. …”
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Data Mining of 24-Hour Cumulative Precipitation Data in Iran Using Machine Learning: Multilayer Perceptron Neural Network and Decision Tree by mozaffar faraji, Majid Rezaii Banafsheh Daragh, Behroz sarisarraf, Ali Mohammad Khorshid Dust

“…Results: The MLP model demonstrated efficiency in estimating monthly precipitation by minimizing MSE to 0.04. …”
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Optimal Operation of CCHP Smart Distribution Grid with Integration of Renewable Energy by Ghassan A. Bilal, Mohammed K. Al-Saadi, Ghaidaa A. Al-Sultany, Wisam Abed Kattea Al-Maliki

“…Recently, electric distribution grids supply not only electric loads but also heating and cooling loads simultaneously to increase the efficiency of the system and reduce the emission of greenhouse gases. …”
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Optimal Capacity Configuration of Residential Solar-Hydrogen Coupling Energy System with Hydrogen Vehicle Load by Zhenlan DOU, Chunyan ZHANG, Huirong ZHAO, Yuqi YAO, Daogang PENG

“…Secondly, by setting the capacity of the equipment in the system as the optimization variable, and the minimization of annual investment cost of the system as the objective function, the reliability of energy supply and other factors as the constraints, the system optimal capacity configuration model is established. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Canopy Cover (CC) is a key variable in agriculture, providing critical information on crop growth and health. …”
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A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…Notably, the approach achieves substantial reductions in power losses during peak demand periods with distributed generation incorporation while maintaining voltage profiles within the stringent operational bounds of 0.94 to 1.0 per unit, thus ensuring stability amidst variable load conditions. Comparative analyses further demonstrate that the hybrid method surpasses conventional optimization techniques, as evidenced by enhanced convergence rates and superior objective function outcomes. …”
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Food Supply Chain: A Framework for the Governance of Digital Traceability by Maria Bonaria Lai, Daniele Vergamini, Gianluca Brunori

“…Under the context of increasing demand for transparency, efficiency, and trust in food systems, digital traceability is emerging as a key strategy for improving value creation across agri-food supply chains. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…Industrial energy systems are increasingly required to reduce operating costs and CO₂ emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. …”
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Notice of Violation of IEEE Publication Principles: VVC/H.266 Intra Mode QTMT Based CU Partition Using CNN by Sameena Javaid, Safdar Rizvi, Muhammad Talha Ubaid, Abdullah Tariq

“…Finally, a variable threshold decision system is established to achieve the targeted low complexity and RD performance. …”
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Impact of municipal wastewater use on urban and peri‑urban agricultural productivity: the endogenous treatment-effects approach by Mohammed Abdulai, Mohammed Tanko, Alhassan Andani

“…Using survey data from 416 vegetable farmers, we employed a semi-log production function augmented with an endogenous binary-treatment effect equation to estimate the drivers and impact of MWW use on value of vegetable output, accounting for selection bias and omitted variable problem. …”
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Machine learning with hyperparameter optimization applied in facies-supported permeability modeling in carbonate oil reservoirs by Watheq J. Al-Mudhafar, Alqassim A. Hasan, Mohammed A. Abbas, David A. Wood

“…On the other hand, highly permeable fractures function as the main flow conduits within such reservoirs. …”
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Applications of mutagenesis methods on affinity maturation of antibodies in vitro by LIU Yuan, LIN Manman, ZHANG Xiao, XU Chongxin, JIAO Linxia, ZHONG Jianfeng, WU Aihua, LIU Xianjin

“…In chain shuffling, a variable heavy or light chain of a specific antibody is recombined with a complementary variable domain library. …”
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Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework by Yuyan Annie Pan, Jifu Guo, Yanyan Chen, Siyang Li, Wenhao Li

“…Traffic state estimation (TSE), which reconstructs the traffic variables (e.g., speed, flow) on road segments using partially observed data, plays an essential role in intelligent transportation systems. …”
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A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure by Chenfeng Li, Tenglong Jin, Zequan Chen, Guanchen Wei

“…Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. …”
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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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