Grain Yield Prediction Based on the Improved Unbiased Grey Markov Model by Wu Yuan, Zhou Rui, Yu Bao, Huang Xiang, Li Bo

“…The results show that the prediction accuracy of the grey GM (1, 1) model and the unbiased grey GM (1, 1) model is basically the same, with an average error of 3.213%. The prediction accuracy of the unbiased grey Markov model is better, with an average error of 2.039%. …”
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X-Ray Polarization Study of the Neutron Star Low-mass X-Ray Binary GX 349+2 by Unnati Kashyap, Thomas J. Maccarone, Mason Ng, Eliot C. Pattie, Swati Ravi, Herman L. Marshall

“…We discovered that the X-ray source was polarized at a polarization degree of PD = 1.1% ± 0.3% (1 σ errors) with a polarization angle of PA = 32° ± 6° (1 σ errors). …”
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An integrated wireless system for dynamic strain monitoring of Einel-rad-Einelfahrwerk bogies for high-speed rail transport by FengLong Wang, Yating Yu, Zhiwen Luo, Lai Wei, Jing Zeng, Guiyun Tian

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Research on feature extraction and intelligent diagnosis method of reciprocating compressor bearing clearance fault by Feng Yan

“…The proposed method employs a generalized multi-scale permutation entropy (GMPE) algorithm, which utilizes a multi-scale mean coarse-graining strategy to effectively capture dynamic transitions in signals. To overcome the shortcomings of traditional binary tree support vector machine (BTSVM) classifiers—such as slow convergence and error accumulation due to early misclassifications—an enhanced BTSVM model is introduced to reduce error propagation. …”
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Detection of strawberry bloom phenology based on YOLO-RCMC and flower opening scale by Junquan Zhen, Yuke Wang, Xunhui Liu, Linfan Zhou, Shuqin Yang, Dong Wang

“…In addition, the RCM variants were integrated into the head of the model to reduce classification errors and improve detection accuracy. The experimental results identified the threshold for flower opening in both the Early and Full stages. …”
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Advancements in combustion technologies: A review of innovations, methodologies, and practical applications by Abdellatif M. Sadeq, Raad Z. Homod, Husam Abdulrasool Hasan, Bilal Naji Alhasnawi, Ahmed Kadhim Hussein, Ali Jahangiri, Hussein Togun, Masoud Dehghani-Soufi, Shahbaz Abbas

“…Multi-scale modeling techniques, such as hybrid DNS-LES models, achieve a 5 % error margin in flame speed predictions, and Adaptive Mesh Refinement (AMR) reduces computational costs by 50 % without compromising accuracy. …”
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Investigation of Metoprolol Concentrations in Plasma Using Automated Sample Preparation and LC-MS/MS Detection by Ionel-Bogdan Cioroiu, Mona-Elisabeta Dobrin, Marius Niculaua, Constantin-Bogdan Nechita, Valeriu V. Cotea

“…Precision and accuracy were evaluated both within and between runs, with a maximum coefficient of variation (CV%) of 10.28 and a maximum relative error (ER%) of 5.38. Linearity was demonstrated over the range of 5 ng/L to 1000 ng/L, with a lower limit of quantification at 0.042 ng/L, made possible by injecting larger sample volumes. …”
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Sõnavaratesti väljatöötamine arengulise keelepuude tuvastamiseks kakskeelsetel lastel by Adele Vaks, Marika Padrik, Virve Vihman

“…However, bilinguals face a greater risk of misdiagnosis, as the error types of typically developing bilinguals in their non-dominant language often resemble those of monolingual children with DLD (Boerma, Blom 2017). …”
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Thermo-mechanical assessment of high entropy (Fe-Ni-Cx (X=0.3-0.5), (Fe-Cr-Cx (X=0.3-0.5) ternary alloys system using calphad method by Waseem Ullah shah, Dil faraz khan khan, haiqing yin yin, saeed ullah jan jan

“…ERRATUM In the Kuwait Journal of Science, Vol.50, Issue No.(3A), July 2023, pp. 1-12 of the article titled, “Thermo-mechanical assessment of high entropy (Fe-Ni-Cx (X=0.3-0.5), (Fe-Cr-Cx (X=0.3-0.5) ternary alloys system using calphad method,” by Waseem Ullah Shah, Dil Faraz Khan, Haiqing Yin, and Saeed Ullah there has been an error in the alloying composition of Table 2 and Table 3. …”
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Additive Manufacturing as an Alternative to Core Sampling in Concrete Strength Assessment by Darya Anop, Marzhan Sadenova, Nail Beisekenov, Olga Rudenko, Zulfiya Aubakirova, Assel Jexembayeva

“…The core strengths were consistently lower than the cube strengths, but their ratios remained remarkably stable: the transition coefficient clustered between 0.82 and 0.85 (mean 0.83). …”
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Optimization of Remote Backup Protection Coordination Logic Based on Dynamic Identification of Faulty Components in Transmission Grids by LIN Xiangning, JI Jihao, DING Yifan, LI Zhengtian, WENG Hanli

“…[Results] The PSCAD simulation results indicate that the accuracy rate of the negative-sequence criterion for asymmetrical faults was 100%， with reliable identification possible with a transition resistance of 30 Ω. For symmetrical faults， the traveling wave ranging error is less than 100 m， and the location time is reduced by 90% compared with traditional methods. …”
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Neuro-Musculoskeletal Modeling for Online Estimation of Continuous Wrist Movements from Motor Unit Activities by Yunfei Liu, Xu Zhang, Haowen Zhao, Xiang Chen, Bo Yao

“…Decoding movement intentions from motor unit (MU) activities remains an ongoing challenge, which restricts our comprehension of the intricate transition mechanism from microscopic neural drive to macroscopic movements. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…This metric considered overestimation and underestimation scenarios compared to ground truth, setting error upper and lower bounds to penalize data points exceeding error tolerance limits. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…By comparing the prediction accuracy of the seven models, the results show that the Grid Search Method optimized SVR model performs the best in the light of prediction accuracy, with a Mean Absolute Percentage Error (MAPE) of 2.96%, a Mean Absolute Error (MAE) of 0.028 mm, a Root Mean Square Error (RMSE) of 0.032 mm, and a coefficient of determination (R2) of 0.995. …”
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Does fiscal decentralization foster renewable electricity generation? A panel data study of OECD countries by Serhiy Lyeonov, Oksana Okhrimenko, Artem Artyukhov, Mariia Saiensus, Iuliia Myroshnychenko, Yuliia Yehorova, Oleksii Havrylenko

“…Utilizing a panel dataset of 34 countries spanning 2000–2023, the analysis employs a fixed-effects regression model with Driscoll-Kraay standard errors. It includes a one-year lag of fiscal variables to ensure robustness. …”
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3D modelling and x-ray depth analysis map of the pulp with computer software via digital periapical radiography and cone beam computed tomography by Turgut Felek, Samed Satir, Selale Ozel, H. Kursat Celik

“…This rate decreased to 27% in the diagnosis of transitions from elliptical to oval form. A total of 5 and 19 linear formations observed in the form of depth decrease and increase, respectively, were accepted as image errors in XPAR. …”
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Effects of a combined nature-based and audio-based virtual mindfulness intervention on stress and wellbeing of COVID-19 healthcare workers: a randomized controlled trial by Polycarpe Bagereka, Rezvan Ameli, Ninet Sinaii, Marcelli Cristine Vocci, Angelina Mangiardi Coulter, Michael Neustedter, Ann Berger

“…This chronic stress may culminate into burnout, which has been associated with impaired patient care and increased medical errors. Exposure to nature-based programs have been shown to reduce levels of perceived stress and promote well-being. …”
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A novel hybrid TCN-TE-ANN model for high-precision solar irradiance prediction by Murat Isik

“…Utilizing a comprehensive dataset from three significant U.S. solar energy sites—Desert Sunlight, Copper Mountain, and Solar Star—spanning 22 years at a 30-min temporal resolution, the proposed model demonstrated superior performance metrics, with R2 ranging from 0.94768 to 0.97417, root mean square error (RMSE) between 0.04776 and 0.06543 W/m2, and mean absolute error (MAE) between 0.02510 and 0.03526 W/m2. …”
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Predicting biomass transportation costs: A machine learning approach for enhanced biofuel competitiveness by Ali Omidkar, Razieh Es’haghian, Hua Song

“…Comparative analysis unequivocally demonstrates the superior predictive performance of the random forest model, achieving a remarkable R-squared value of 97.4 % and a root mean square error of 165. Furthermore, this study delves into the relative importance of each independent variable in determining the overall transportation cost. …”
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Post-hoc Evaluation of Sample Size in a Regional Digital Soil Mapping Project by Daniel D. Saurette, Richard J. Heck, Adam W. Gillespie, Aaron A. Berg, Asim Biswas

“…The transition from conventional soil mapping (CSM) to digital soil mapping (DSM) not only affects the final map products, but it also affects the concepts of scale, resolution, and sampling intensity. …”
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