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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Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

“…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
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Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome by Bin Liu, Zhiqi Mao, Xinyuan Yan, Hang Yang, Junpeng Xu, Zhebin Feng, Yanyang Zhang, Xinguang Yu

“…The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. …”
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Rehabilitation impact indices and their independent predictors: a systematic review by Amardeep Thind, Gerald Choon-Huat Koh, Robert Petrella, Cynthia Huijun Chen

“…Then, various names of the same formula were used to identify studies, limited to articles in English and up to 31 December 2011, including case–control and cohort studies, and controlled interventional trials where RIIs were outcome variable and matching or multivariate analysis was performed.Results The five RIIs identified were (1) absolute functional gain (AFG)/absolute efficacy/total gain, (2) rehabilitation effectiveness (REs)/Montebello Rehabilitation Factor Score (MRFS)/relative functional gain (RFG), (3) rehabilitation efficiency (REy)/length of stay-efficiency (LOS-EFF)/efficiency, (4) relative functional efficiency (RFE)/MRFS efficiency and (5) revised MRFS (MRFS-R). …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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A United Probabilistic Approach to Minimising the Sum of Absolute Values by Changyong Feng, Honghong Liu, Ethan Poon, Ge Feng

“…Methodology: The sum of absolute values can be standardized so that the sum of the coefficients equals 1. In this case, the sum of absolute values takes the form 𝐸𝐸|𝑋𝑋−𝑎𝑎|, where 𝑋𝑋 is a random variable. …”
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Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

“…PA was the most influential factor among all independent variables affecting ECW/TBW (B = −1.006, p < 0.001). …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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PileBetaGR: An R-based integrative tool for predicting the geometric reliability index of piles using load-displacement curves by Xing Zheng Wu

“…The application compiles a series of functions for analyzing load-displacement data: (i) a power law regression is used to fit each load-displacement curve, yielding a set of regression parameters for the site; (ii) a normal copula model is established to fit the joint distribution of these regression variables, allowing a geometric reliability index to be computed; (iii) the critical environmental contour is determined based on the joint probability density function and the limit state function. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
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Semantic ECG hash similarity graph by Yixian Fang, Shilin Zhang, Yuwei Ren

“…Abstract Graph-based methods have made significant progress in addressing the dependent correlations among ECG time series variables. However, most existing graph structures primarily focus on local similarity while overlooking global semantic correlation. …”
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Structural strength analysis and optimization of converter lug based on Kriging model by HE Guanqiang, LIU Yongjiang, LI Hua, CHEN Liming

“…In this paper, machine learning methods were considered to approximate the functional relationships between design variables and responses. …”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. The minimum manufacturing cost of ship hull shell plates (SHSPs) is the objective function, the rules and requirements for the seam position and the size of a single shell plate are the constraints, and the position and shape of the seam are the design variables. …”
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Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD by J. Alberto Neder, Giles Santyr, Brandon Zanette, Miranda Kirby, Marina Pourafkari, Matthew D. James, Sandra G. Vincent, Carrie Ferguson, Chu-Yi Wang, Nicolle J. Domnik, Devin B. Phillips, Janos Porszasz, William W. Stringer, Denis E. O’Donnell

“…Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients’ out-of-proportion dyspnea. …”
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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
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