A Comprehensive Review: Molecular and Genealogical Methods for Preserving the Genetic Diversity of Pigs by Vladimir Margeta, Dubravko Škorput, Ivona Djurkin Kušec, Zlata Kralik, Goran Kušec, Kristina Gvozdanović

“…To reduce possible errors, it is necessary to combine genealogical data with molecular data. …”
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WISP: Workframe for Interferogram Signal Phase-Unwrapping by Timofey F. Khirianov, Aleksandra I. Khirianova, Egor V. Parkevich, Ilya Makarov

“…A key contribution is the proposed loss function for isophase fitting, which directly optimizes curve quality and enhances reconstruction accuracy. …”
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Scientific Machine Learning for Guided Wave and Surface Acoustic Wave (SAW) Propagation: PgNN, PeNN, PINN, and Neural Operator by Nafisa Mehtaj, Sourav Banerjee

“…Through theoretical analysis and problem-driven examples, the findings demonstrate that PINNs address key limitations of traditional methods, including discretization errors and computational inefficiencies, while offering robust predictive capabilities. …”
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Explainable Climate-Based Time Series Modeling for Predicting Chemical Compositions in Tobacco Leaves by Hong He, Yunwei Zhang, Bin Li, Chengjin Tao

“…The mean absolute percentage errors (MAPE) for total sugar, reducing sugar, and total nitrogen remain within 10%-20%, while nicotine and potassium exhibit errors in the range of 20%-30%. …”
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Machine Learning Reconstruction of Wyrtki Jet Seasonal Variability in the Equatorial Indian Ocean by Dandan Li, Shaojun Zheng, Chenyu Zheng, Lingling Xie, Li Yan

“…The XGBoost model demonstrated superior performance in reconstructing WJ’s seasonal variations, achieving coefficients of determination (<i>R</i>²) exceeding 0.97 across all seasons and maintaining root mean square errors (RMSE) below 0.2 m/s across all seasons. The reconstructed currents exhibited strong consistency with the Ocean Surface Current Analysis Real-time (OSCAR) dataset, showing errors below 0.05 m/s in spring and autumn and under 0.1 m/s in summer and winter. …”
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USER ACCEPTANCE OF MOBILE-JKN: INSIGHTS FROM THE TECHNOLOGY ACCEPTANCE MODEL by Ferina Septiani Damanik, Anna Wahyuni Widayanti, Chairun Wiedyaningsih

“…Despite its potential benefits, the implementation of this application faces various challenges, such as application errors, differing levels of digital literacy, and data security issues, necessitating an evaluation of its adoption and acceptance. …”
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Study of a face stepped milling cutter for finishing flat surfaces by H.M. Vyhovskyi, M.M. Plysak, Y.O. Koval

“…The proposed cutter design, with a finishing insert operating in the axial direction and maintaining elastic contact with a stationary profile follower, allows for compensation of elastic deformations, stabilization of the insert position, and reduction of machining errors. The obtained results can be used to optimize face milling cutter designs and machining parameters in order to improve machining accuracy and surface quality during milling operations.…”
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Efficient Deep Learning Model Compression for Sensor-Based Vision Systems via Outlier-Aware Quantization by Joonhyuk Yoo, Guenwoo Ban

“…These results confirmed the potential of OAQ for optimizing deep learning models in sensor-based vision applications.…”
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Applications of artificial intelligence in thoracic imaging: a review by Arjun Kalyanpur, Neetika Mathur

“…It provides an overview of AI applications in thoracic imaging, focusing on advancements in screening, early disease detection, triage and prioritization, automated image analysis, and workflow optimization. These points are supported by review articles published on the subject, including our own publications. …”
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Impact of Driver Age and Experience in Software Usage on Driving Safety and Usability of Car-Sharing Software by Chunhui Jing, Jinyi Zhi, Suixian Yang, Wei Wang

“…The variables of driving safety and usability were analyzed by two-way analysis of variance (ANOVA) and independent sample Kruskal–Wallis nonparametric test. …”
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Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips by Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Muhammad Shoaib, Rajesh Kumar, Syed Ibrar Hussain

“…In the current paper, an analysis of magnetohydrodynamic Williamson nanofluid boundary layer flow is presented, with multiple slips in a porous medium, using a newly designed human-brain-inspired Ricker wavelet neural network solver. …”
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Impact of digitization on educational management: Results of the introduction of a learning management system in a traditional school context by Alex Pacheco, Renato Yupanqui, Diana Mogrovejo, Joel Garay, Yrene Uribe-Hernández

“…The study was developed in four phases: Initiation, where the objectives and risks were defined, and the appropriate technological tool was selected; Elaboration, which included the definition of use cases and the creation of a preliminary solution; Development, focused on the implementation of the pending requirements; and Transition, which evaluated compliance with the requirements, corrected errors and conducted usability tests. Qualitative analysis methods were used to evaluate the usability and effectiveness of the system. …”
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Assessment of Global and Detailed Chemical Kinetics in Supercritical Combustion for Hydrogen Gas Turbines by Sylwia Oleś, Jakub Mularski, Halina Pawlak-Kruczek, Abhishek K. Singh, Artur Pozarlik

“…The results indicate good agreement between the global and detailed mechanisms, with average relative errors below 2% for supercritical argon and 4% for supercritical carbon dioxide. …”
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Soil Mapping of Small Fields with Limited Number of Samples by Coupling EMI and NIR Spectroscopy by Leonardo Pace, Simone Priori, Monica Zanini, Valerio Cristofori

“…Precision agriculture relies on highly detailed soil maps to optimize resource use. Proximal sensing methods, such as EMI, require a certain number of soil samples and laboratory analysis to interpolate the characteristics of the soil. …”
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Variable-Ratio Mode-Insensitive 1 &#x00D7; 2 Power Splitter Based on MMI Couplers and Phase Shifters by Fang Ren, Wei Chen, Tianwen Zhangsun, Yiying Zhang, Xiaojie Fan, Jianping Wang

“…The simulation results also show that the optimized power splitters have the advantages of high tolerance to fabrication errors and wide operating bandwidths, which indicates that the proposed structure can operate on multiple modes and would be suited to potential applications in on-chip optical communications.…”
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Prediction of Weld Geometry in Laser Overlap Welding of Low-Carbon Galvanized Steel by Kamel Oussaid, Narges Omidi, Abderrazak El Ouafi, Noureddine Barka

“…Results demonstrated a strong correlation between ANN predictions and experimental measurements, with R² values exceeding 95% for WS and DOP and 92% for WI, and mean errors below 7%. A comparative analysis between ANN, FEM, and experimental data confirmed the model’s reliability across different welding conditions. …”
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Intelligent power control strategy based on self-tuning fuzzy MPPT for grid-connected hybrid system by H. Chaib, S. Hassaine, Y. Mihoub, S. Moreau

“…Methods of this research includes a comprehensive analysis of several optimization techniques under varying weather scenarios. …”
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Calibration of DEM Parameters and Microscopic Deformation Characteristics During Compression Process of Lateritic Soil with Different Moisture Contents by Chao Ji, Wanru Liu, Yiguo Deng, Yeqin Wang, Peimin Chen, Bo Yan

“…The calibrated models demonstrated high fidelity, with average relative errors of 4.53%, 3.36%, 3.05%, 3.32%, and 7.60% for uniaxial compression simulations across the five moisture levels. …”
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Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets by Retinderdeep Singh, Sheifali Gupta, Ashraf Osman Ibrahim, Lubna A. Gabralla, Salil Bharany, Ateeq Ur Rehman, Seada Hussen

“…Furthermore, entropy-based uncertainty analysis quantifies prediction confidence, yielding an average entropy of 0.3093 and effectively identifying uncertain predictions to mitigate diagnostic errors. …”
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A review of SAR tomography by Xin Zhao, Jie Dong, Yanghai Yu, Mingsheng Liao, Lu Zhang, Jianya Gong

“…Then, three key aspects of tomographic processing—3D imaging algorithm, calibration of phase errors, and impact of temporal decorrelation – are detailed and analyzed. …”
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