An Investigation of Knee Injury Prevalence and its Mechanism among Premier League Soccer Referees in Iran by Hamid Mahdavi Mohtasham, Shahnaz Shahrbanian

“…Using the Pearson correlation coefficient, this study examined the relationships between different variables including KOS subscales as well as the current level of self-reported knee joint function and proprioception. …”
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Analysis of Mobile JKN Application Service Quality With E-GovQual Method and IPA by Randy Rizki Ananda, Indriani Noor Hapsari

“…The results of the coefficient of determination (R-Square) show that overall, the variables of ease of use, reliability, trust, content and appearance, functionality and interaction and citizen support significantly affect service quality by 88.6%. …”
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A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…Secondly, a two-stage feature-selection method is employed, in which the partial autocorrelation function (PACF) is used to select relevant lagged features, while the maximal information coefficient (MIC) is applied to identify key variables from both historical and external data. …”
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Donor Parameters and Platelet Yield during Plateletpheresis: A Cross-sectional Prospective Study by Ruchi Singh, Ganga S. Pilli, Ramadevi Vivek Wani

“…A relationship between pre-donation donor variables and platelet yield was studied using the Pearson correlation coefficient (r). …”
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Thermal and flow simulations of metal oxide trihybrid nanofluids over a vertical stretching cylinder by T. Giftlin Blessy, B. Rushi Kumar

“…By employing similarity variables, we transform the governing equations into dimensionless ordinary differential equations, which are then solved numerically using MATLAB's bvp4c function. …”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. …”
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Optimization of phosphorus adsorption on honeycomb briquette ash by application of response surface methodology by Yu Li, Jianfa Yang, Zemin Zhang, Jie Yuan

“…At these conditions, removal efficiency and desirability function were found to be 96% and 1.000, respectively. …”
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Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences by Alessandra Traini, Massimo Iorizzo, Harpartap Mann, James M. Bradeen, Domenico Carputo, Luigi Frusciante, Maria Luisa Chiusano

“…However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. …”
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Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

“…Compared to the simple C‐Q equation, this equation explained the temporal dynamics with an average increase of 0.17 in the Nash‐Sutcliffe efficiency coefficient. Global parameter estimation gave an objective estimate of baseflow with a plausible baseflow index ranging between 0.05 and 0.40 across catchments. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…SDKU-Net integrates dynamic kernel adjustment, a combined loss function incorporating Focal and Tversky Loss, and optimizer switching to effectively tackle class imbalance and improve segmentation quality. …”
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise by Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang

“…We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. …”
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Predicting heat transfer Performance in transient flow of CNT nanomaterials with thermal radiation past a heated spinning sphere using an artificial neural network: A machine learn... by S.R. Mishra, P.K. Pattnaik, Rupa Baithalu, P.K. Ratha, Subhajit Panda

“…An efficient heat transfer phenomenon using nanofluid have greater challenges in various industries, engineering application the recent trend. …”
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A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

“…Our approach integrates a VMD-based denoising mechanism, compressed into a more compact KAN model via knowledge distillation, to mitigate noise efficiently. It also incorporates a channel-independent KANs structure with a regularized weighted loss function to handle variable-specific degradation patterns. …”
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Trajectory Planning Method in Time-Variant Wind Considering Heterogeneity of Segment Flight Time Distribution by Man Xu, Jian Wang, Qiuqi Wu

“…This study aims to optimize a reliable and efficient trajectory by minimizing the Mean-Excess Flight Time (MEFT). …”
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Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis-Study of Treatment’s Echocardiographic Mechanisms (CLOVERS-STEM) by Michael J. Lanspa, MD, Akram Khan, MD, Patrick G. Lyons, MD, Michelle N. Gong, MD, Ali A. Naqvi, MD, Siddharth Dugar, MD, Abhijit Duggal, MD, Nicholas J. Johnson, MD, Jacob H. Schoeneck, MD, Lane Smith, MD, PhD, Somnath Bose, MD, MPH, Nathan I. Shapiro, MD, Tatyana Shvilkina, DO, Danielle Groat, MStat, Jason R. Jacobs, PhD, Troy D. Olsen, RCDS, Steven Cannavina, RCDS, Daniel B. Knox, MD, Eliotte L. Hirshberg, MD, Wesley H. Self, MD, Samuel M. Brown, MD

“…Receipt of fluid and vasopressors, common treatments in septic shock, may affect cardiac function. OBJECTIVES:. We sought to determine whether a liberal or restrictive fluid resuscitation strategy was associated with changes in cardiac function. …”
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Multimodality Data Integration in Epilepsy by Otto Muzik, Diane C. Chugani, Guangyu Zou, Jing Hua, Yi Lu, Shiyong Lu, Eishi Asano, Harry T. Chugani

“…Moreover, an effort was made to derive quantitative variables (such as the spatial proximity index, SPI) characterizing the relationship between complementing modalities on a more generic level as a prerequisite for efficient data mining strategies. …”
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On Complex Singularity Analysis for Some Linear Partial Differential Equations in by A. Lastra, S. Malek, C. Stenger

“…We construct these solutions with the help of series of functions with infinitely many variables which involve derivatives of all orders of X in one variable. …”
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Diversity and interdomain networks of bacterial, pico-protist and nano-protist communities in a marine ranching by Xinyi Zheng, Xin Guo, Xin Guo, Xiaoqing Lin, Cheng Huang, Lingfeng Huang

“…Although seasonal fluctuations in environmental variables generally influence microbial community dynamics, our comprehension of interdomain microbial co-occurrence patterns remains incomplete. …”
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Optimal Design Method of Integrated Energy Systems Considering Staged Planning and Equipment Replacement by Lei ZOU, Yiming TANG, Zhuping LIU, Zhengyong WU, Chao FANG, Chaoqun WANG, Fushuan WEN

“…Then, with the whole project cycle as the optimization time scale, the relationship between the equipment installation year and the current remaining life is modeled by introducing the equipment selection and operation decision variables. Finally, considering the influence of economic factors such as nominal interest rates and inflation rates, an objective function, involving investment costs, operating costs, and equipment residual value income, is constructed, with the optimal economical performance as the goal. …”
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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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