Exploring high-performance environmental barrier coatings for rare earth silicates: A combined approach of first principles calculations and machine learning by Yun Fan, Yuelei Bai, Zhiyao Lu, Zhaoxu Sun, Yuchen Liu, Simiao Sha, Yiran Li, Bin Liu

“…It is revealed the [O3SiOSiO3] structure and polyhedron distortion affect mechanical properties of RE2Si2O7, while criteria for selecting RE2Si2O7 with low thermal conductivity are identified, including complex crystal structures, chemical bond inhomogeneity, and strong non-harmonic lattice vibrations. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…The comparative analysis of model complexity confirmed that increasing the sophistication of the LSTM model significantly enhances predictive accuracy and generalization capabilities. …”
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Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…Furthermore, an LSF-based radio unit (RU) selection algorithm is employed to activate only the contributing RUs, allowing efficient utilization of network resources. …”
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Invasive common milkweed strongly simplifies insect flower-visiting networks by Edina Török, Riho Marja, Ágota Réka Szabó, Róbert Gallé, Péter Batáry

“…Functional complementarity and the cluster coefficient of networks were significantly higher in milkweed-invaded areas compared to control areas during milkweed flowering. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…Removing all attention mechanisms results in further performance degradation, with <italic>R</italic>² of 0.90 and <italic>MSE</italic> of 1.20, highlighting their importance in the prioritization of selective features. Removing the KAN network results in <italic>R</italic>² of 0.92 and <italic>MSE</italic> of 1.09, indicating its contribution to modeling complex time series patterns. …”
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Machine-Learning-Based Depression Detection Model from Electroencephalograph (EEG) Data Obtained by Consumer-Grade EEG Device by Kei Suzuki, Tipporn Laohakangvalvit, Midori Sugaya

“…The feature selection methods were Light Gradient Boosting Machine (LightGBM) feature importance, mutual information, ReliefF and ElasticNet coefficients. …”
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Comparison of the Regression Method and The Neural Network Method in Specific Cases of Engineering Practice by Križan Peter, Svátek Michal, Matúš Miloš, Hanko Lukáš

“…The aim of the analysis was to create models for both selected statistical methods that would sufficiently describe the given process and subsequently compare them. …”
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The use of big data on the labor market in HR business processes of organizations in the Republic of Belarus by Alena V. Vankevich, Iryna N. Kalinouskaya

“…A significant regional differentiation of wages was revealed (coefficient of variation 23.8 %), while the average wages in the metropolitan region exceeds the national average ones by 25 %. …”
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Dynamic Characteristics Analysis of the DI-SO Cylindrical Spur Gear System Based on Meshing Conditions by Yong Zhu, Shida Zhang, Shengnan Tang, Zhengxi Chang, Renyong Lin, Lingbo Zhang

“…In practical operation, the stability of the DI-SO cylindrical spur gear system is influenced by complex excitations. These excitations lead to nonlinear vibration, meshing instability, and noise, which affect the performance and reliability of the entire equipment. …”
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Solving Phosphorus Fertilization-Related Drip Irrigation Emitter Clogging by Adding Mn²⁺ by Tianyu Xu, Sanlin Bao, Qiuyue Yu, Yu Gao

“…The new precipitates were generated, which caused more severe and complex blockage of drip irrigation emitters. Songhua River water was selected as the irrigation water. …”
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Development and Evaluation of Machine Learning Models for Air-to-Land Temperature Conversion Using the Newly Established Kunlun Mountain Gradient Observation System by Yongkang Li, Qing He, Yongqiang Liu, Amina Maituerdi, Yang Yan, Jiao Tan

“…The results demonstrated that the CatBoost algorithm outperformed the others under complex terrain and climatic conditions, achieving a coefficient of determination (R²) of 0.997 and the lowest root mean square error (RMSE) of 0.627 °C, indicating superior robustness and accuracy. …”
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Determination, Mobility and Risk Assessment of Pesticides in Ginseng Wine Using Dispersive Liquid–Liquid Micro Extraction Combined with GC-MS/MS and LC-MS/MS by Xuanwei Xu, Dan Zhao, Min Zhang, Xinxin Meng, Ying Chen, Xu Leng, Shuang Liang, Yueru Li

“…In this work, DLLME was extended to complex residues in the ginseng wine matrix. This study first focused on the selection of an appropriate solvent that enabled the dissolution of analytes from ginseng wine. …”
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Modeling Organizational Justice and Job Satisfaction with the Mediating Role of Organizational Indifference by Ali soboohi, hadi hematian, Abolfazl danaee

“…Therefore, studying occupational behavior is one of the most difficult and complex tasks due to the multiplicity and overlap of variables that affect human behavior, interrelationships, and the instability of these variables. …”
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Influence of the nature of organic solvents on the process of separation of antioxidative additive in a transformer oil by a gas-chromatographic method by Duy Hung Nguyen, Yu. V. Snigireva, A. V. Taneeva, V. F. Novikov

“…The dependence of the relative retained volume of aliphatic alcohols on the selectivity coefficient of separation with Ionol is linear. …”
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State of Health Estimation for Lithium-Ion Batteries Based on TCN-RVM by Yu Zhao, Yonghong Xu, Yidi Wei, Liang Tong, Yiyang Li, Minghui Gong, Hongguang Zhang, Baoying Peng, Yinlian Yan

“…Firstly, five health factors are extracted from IC curves, and the strong correlation between these features and SOH is verified using both Pearson and Spearman coefficients, ensuring the physical rationality and statistical significance of feature selection. …”
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Microsatellite Diversity and Restriction Enzyme-based Polymorphisms of MHC Loci in Some Native Turkish Goats by Mehmet Aslan, Eymen Demir, Taki Karslı

“…Playing a key role in immunity and autoimmunity, Major Histocompatibility Complex (MHC) contains microsatellite regions and polymorphisms associated with resistance to several diseases and thermo-physiologic characteristics in farm animals. …”
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Relationship between Snow and Temperature over Some Iraqi Meteorological Stations by Zainab M. Abbood, Yasmin Q. Tawfeek, Salwa S. Naif, Osama T. Al-Taai, Ahmed S. Hassan, Monim H. Al-Jiboori, Zeinab Salah

“…Notably, Duhok City exhibited the strongest relationship between snow albedo and density, with a regression coefficient of 0.9699 compared to other regions. Conclusions: This study highlights the complex relationship between snow albedo and density in northern Iraq. …”
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Evaluation of various varieties of peas as raw material for deep processing by V. G. Goldstein, L. P. Nosovskaya, L. V. Adikaeva, V. A. Kovalenok

“…As evaluation criteria determining high technological properties, providing the most complete extraction of starch and protein isolate there have been selected coefficients of extraction of these components. …”
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In-Depth Analysis of Ka-Band Integrated Commercial Beamformer Non-Idealities in Phased Array Calibration and Pattern Prediction Methods for 5G Scenarios by Jorge Calatayud Maeso, Xiaoliang Sun, Alfonso Tomas Muriel-Barrado, Fernando Rodriguez Varela, Pablo Sanchez-Olivares, Jose-Manuel Fernandez-Gonzalez, Manuel Sierra Castaner

“…The Rotating-element Electric-field Vector (REV) and Control Circuit Encoding (CCE) methods are simulated using a synthetic array with spherical wave expansion driven by output coefficients measured from the beamformer. Simulations are executed to compare the REV method with a Selective-REV variant, designed to enhance coefficient prediction accuracy by leveraging a priori knowledge of phase-shifter amplitude deviations. …”
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Machine learning proteochemometric models for Cereblon glue activity predictions by Francis J. Prael, III, Jiayi Cox, Noé Sturm, Peter Kutchukian, William C. Forrester, Gregory Michaud, Jutta Blank, Lingling Shen, Raquel Rodríguez-Pérez

“…While promising, the complicated nature of this CRBN-glue-target ternary complex makes the rational design of molecular glue degraders challenging. …”
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