Mid-infrared milk screening as a phenotyping tool for feed efficiency in dairy cattle by Ludmila Zavadilová, Eva Kašná, Zuzana Krupová, Alena Pechová, Petr Fleischer, Soňa Šlosárková

“…Prediction accuracy varies across studies, depending on the mathematical method and model employed. Predictions based solely on FT-MIR data have demonstrated moderate accuracy (coefficient of determination), ranging from 0.19 to 0.40. …”
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Tunnel water inflow prediction using explainable machine learning and augmented partially missing dataset by Shengdong Ju, Guangzhao Ou, Tao Peng, Yanning Wang, Quanlin Song, Peng Guan

“…The results indicate that: (1) The constructed BO-XGBoost model exhibited exceptionally high predictive accuracy on the test set, with a root mean square error (RMSE) of 7.5603, mean absolute error (MAE) of 3.2940, mean absolute percentage error (MAPE) of 4.51%, and coefficient of determination (R2) of 0.9755; (2) Compared to the predictive performance of support vector mechine (SVR), decision tree (DT), and random forest (RF) models, the BO-XGBoost model demonstrates the highest R2 values and the smallest prediction error; (3) The input feature importance yielded by SHAP is groundwater level (h) > water-producing characteristics (W) > tunnel burial depth (H) > rock mass quality index (RQD). …”
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Prediction of myopia based on biometric parameters of 500,000 children and adolescents aged 3–18 years by Siyu Chen, Siyu Chen, Siyu Chen, Siyu Chen, Jingyu Mu, Jingyu Mu, Jingyu Mu, Jingyu Mu, Xiyue Tan, Xiyue Tan, Xiyue Tan, Xiyue Tan, Xiaoxiao Wu, Xiaoxiao Wu, Xiaoxiao Wu, Junguo Duan, Junguo Duan, Junguo Duan, Junguo Duan

“…Measured their uncorrected visual acuity (UCVA), non-cycloplegic autorefraction, axial length (AL), and corneal radius (CR), Pearson's correlation coefficient and Receiver operating characteristic (ROC) curve were used to determine the accuracy and calculate the cutoff for myopia detection.ResultsThe correlation between AL/CR ratio and SE was higher than that between AL and SE at different ages and refractive states. …”
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Evaluation of the applicability of fractal analysis to describe the surface of aluminium composites after drilling by Karolczak Paweł, Kowalski Maciej

“…The box-counting fractal dimension of the hole surfaces was also determined. Correlation coefficients between the fractal dimension and roughness parameters were calculated. …”
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Reactor modeling and kinetic parameters estimation for diethylbenzene (DEB) dehydrogenation reactions by M.E zeynali, H. Abedini, H. R. Sadri

“…Model equations for DEB dehydrogenation reactor have been solved by genetic algorithm (GA) method using MATLAB software. Reaction rate constants and absorption coefficients were determined at various temperatures. …”
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Activity of soil fluorescein diacetate (FDA) hydrolase under long-term fertilization by MA Xing-zhu

“…The activities of fluorescein diacetate (FDA) hydrolase in black soil and brown soil under different long-term fertilization experiments were determined by the spectrophotometric method and using fluorescein diacetate (FDA) as the substrate. …”
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Analysis and Modeling of Particle Velocities in Premixed Abrasive Water Jets by Weiqin Zuo, Cheng Huang, Yanwei Liu, Hongkai Han, Fuchang Hao, Fajun Zhao, Fei Huang

“…The real-time contrast interpolation method is employed to solve the problem of the variable drag coefficient. …”
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Drying characteristics of green pellets based on the Weibull and Dincer models by Xiaoping Zhang, Zihao Fan, Hongliang Wu, Junqiang Cong, Jialong Yang, Baoliang Wen

“…The Weibull and Dincer models can accurately describe the drying behavior of green pellets, providing a simple yet reliable method for determining the moisture diffusivity and mass transfer coefficient values during the drying process of green pellets. …”
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Histological analysis of the medial gastrocnemius muscle in young healthy children by Anke Andries, Jorieke Deschrevel, Karen Maes, Nathalie De Beukelaer, Marlies Corvelyn, Lauraine Staut, Hannah De Houwer, Domiziana Costamagna, Domiziana Costamagna, Domiziana Costamagna, Stefaan Nijs, Willem-Jan Metsemakers, Elga Nijs, Greet Hens, Eva De Wachter, Sandra Prinsen, Kaat Desloovere, Anja Van Campenhout, Ghislaine Gayan-Ramirez

“…These data may be used as a reference to determine disease impact and efficacy of therapeutic approach on the muscle.…”
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Exploring the optimal lower blood pressure boundary during endovascular thrombectomy in patients with large vessel occlusion by Yu-Ming Chang, Chun-Min Wang, Kang-Po Lee, Po-Chun Shen, Po-Yu Lin, Chi-Hung Liu, Sheng-Hsiang Lin, Chih-Hung Chen, Meng-Tsang Hsieh, Pi-Shan Sung

“…Background: Current guidelines advocate for maintaining BP level below 180/105 mmHg during EVT, determining the safe lower boundary remains primarily consensus-driven by experts. …”
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Fuzzy logic-based simulation of a weighted integrated GNSS receiver for mitigating blocking interference effects by K. Bahmani, M.R. Mosavi, A. Sadr

“…Through fuzzy rules, the WLS weighting coefficients are optimally determined. Experimental results indicate that the WLS method with fuzzy logic coefficients significantly enhances system performance. …”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…In addition, the relationship between morphological and agronomic traits related to seed yield was evaluated in this research using some advanced statistical methods to find possible traits suitable for indirect selection. …”
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Optimal Layout of the Head Drive for a Self-Supporting Bucket Elevator of High Productivity by Volodymyr Kurhan, Ihor Sydorenko, Viktor Kurgan, Ruslan Dudko, Svetlana Bershak

“…Three bucket elevators with different heights, productivity, and belt width were selected to determine the optimal layout. Four drive options were calculated for each design, and a comparative analysis was carried out using a graphical method. …”
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Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns by Junfeng Sun, Yong Fang, Hu Luo, Zhigang Yao, Long Xiang, Jianfeng Wang, Yubo Wang, Yifan Jiang

“…The results indicate that the proposed model outperforms other deep learning models, achieving favorable root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) values of 0.34 mm, 0.23 mm, and 0.94, respectively. …”
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Application of a Three-Stage Procedure for Extracting a Small-Sized Anchor Object on a Noisy Image by Sotnikov O.M., Vorobiov O.M., Udovenko S.G., Kobzev I.V., Vlasiuk V.V., Kurbatov A.A.

“…It is proposed to use the cross-correlation coefficient as a criterion for the degree of image matching. …”
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Phosphorus metabolism in the brain of cognitively normal midlife individuals at risk for Alzheimer's disease by Prodromos Parasoglou, Ricardo S. Osorio, Oleksandr Khegai, Zanetta Kovbasyuk, Margo Miller, Amanda Ho, Seena Dehkharghani, Thomas Wisniewski, Antonio Convit, Lisa Mosconi, Ryan Brown

“…We performed linear regression analysis to determine the relationship between 31P measurements and tracer uptake, and Dunn's multiple comparison tests to investigate regional differences in phosphorus metabolism. …”
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Predicting steady degradation in ship power system: A deep learning approach based on comprehensive monitoring parameters by Xingshan Chang, Xiaojian Xu, Bohua Qiu, Muheng Wei, Xinping Yan, Jie Liu

“…Compared to baseline models, YC2Model demonstrates superior performance on key performance indicators, including the highest coefficient of determination (R2) of 0.960717, and the lowest symmetric mean absolute percentage error of 0.015500, mean square error of 0.707211 × 10−4, root mean square error of 0.008410, and mean absolute error of 0.006519, proving its superior predictive accuracy. …”
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Adaptive hybrid synchronization control of grid-connected converters in renewable power plants and its small-signal stability analysis by GONG Kai, XIAO Huangqing, ZHANG Zhan, HE Hongliang, HUANG Ying, LI Yan

“…Subsequently， the corresponding small-signal model is developed， and based on the analysis results of small-signal stability， a method for determining adaptive parameter values is introduced. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…The results show that the model established in this paper is effective, the prediction results are accurate and the performance is stable, and then compared with the algorithms such as PSO-SVM, SVM, BP, etc, the coefficient of determination of the algorithm is greater than 0.994 in both the training set and the test set, and the average decision percentage error is around 1.88% in both.…”
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Creep Behavior and Quantitative Prediction of Marine Soft Clay Based on a Nonlinear Elasto-Plastic–Viscous Element Assembly Model by Yajun Liu, Ning Fang, Yang Zheng, Ke Wu, Rong Chen, Haijun Lu, Vu Quoc Vuong

“…The predicted–measured creep difference remained within 10%, and the surface-fit coefficient of determination reached R² = 0.97, enabling rapid estimation of deformation for the given stress and time conditions. …”
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