A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

“…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
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AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing by Prakaimuk Saraithong, Peyton Krajcarski, Yukako Kusaka, Moe Yamada, Junichi Matsumoto, Hailey Cunningham, Sama Salih, Darby Jones, Devika Baddhan, Christian Hausner, Justus Anumonwo, Anthony Rosenzweig, Mary M. Navarro, Luis Villa Diaz, Joseph Criscione, Deok-Ho Kim, Todd J. Herron

“…This streamlined process preserves cardiomyocyte viability and function, offering a scalable and efficient solution for cardiac regenerative medicine, disease modeling, and drug discovery.…”
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Stability and vibration analyses of tapered columns resting on one or two-parameter elastic foundations by Masoumeh Soltani, Foudil Mohri

“…Then, the shape functions are obtained exactly by deriving the deformation shape of the column as power series form. …”
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A Novel Multiobjective Evolutionary Algorithm Based on Regression Analysis by Zhiming Song, Maocai Wang, Guangming Dai, Massimiliano Vasile

“…The result shows that MMEA-RA outperforms RM-MEDA and NSGA-II on the test instances with variable linkages. At the same time, MMEA-RA has higher efficiency than the other two algorithms. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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ABOUT SOME FEATURES OF TRANSMISSION MODE FOR ACTIVE POWER OF ELECTRICAL LINE by Paţiuc V., Berzan V.P., Anisimov V., Cabac S., Postotonca S.

“…It enteritis that for the active character load of the active power input and power output of the line, so functions , and functions that characterize developments efficiency , power factor at the input line and the load power factor when the variable z. …”
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Does charcoal act as a protective agent in fish nutrition to increase growth and physiological performance? A meta-analysis by Aliati Iswantari, Vitas Atmadi Prakoso, Nunak Nafiqoh, Rendy Ginanjar, Henti Hendalastuti Rachmat, Agung Irawan, Kurniawan Kurniawan, Mochammad Zamroni, Fathur Rochman, Danung Nur Adli, Mohammad Miftakhus Sholikin, Arif Wibowo, Anuraga Jayanegara

“…Charcoal notably reduced aspartate aminotransferase and increased immunoglobulin levels, suggesting benefits for liver function and immunity. Meta-regression revealed dose-dependent improvements with wood charcoal, whereas responses to bamboo and activated charcoal were variable. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Cognitive ability and motor performances in the elderly by Jovanović Stevan S., Stojanović-Jovanović Biljana N., Pavlović Aleksandra M., Milošević Radovan Lj., Pavlović Dragan M.

“…Clinicians should consider the association between cognitive function and physical-motor performances when dealing with functioning improvement in the elderly. …”
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Pilot study evaluating lipoma reduction with injected physiologic ice slurry by Kristen K. Arango, Cheryl A. London, William M. Karlin, Jacqueline Milton Hicks

“…Future studies could explore using coolants with more sustained coolant function and multiple injections to promote more efficient tumor reduction.…”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Triangular Fuzzy Finite Element Solution for Drought Flow of Horizontal Unconfined Aquifers by Christos Tzimopoulos, Nikiforos Samarinas, Kyriakos Papadopoulos, Christos Evangelides

“…The initial water table is assumed to be curvilinear, following the form of an inverse incomplete beta function. To account for uncertainties in the system, the hydraulic parameters—hydraulic conductivity (K) and porosity (S)—are treated as fuzzy variables, considering sources of imprecision such as measurement errors and human-induced uncertainties. …”
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The impact of digital economy on urban-rural income gap under government intervention by LE Yang, GAO Dongxi, ZHANG Yi, GUO Wei, CHEN Yi

“…Ordinary least squares (OLS) and instrumental variables-two stage least squares (IV-2SLS) estimation methods are used to empirically test the above mentioned-theoretical inferences from the empirical level based on the mediation effect model. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information by Zuhaib Nishter, Fangzong Wang

“…This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…This deep learning method is computationally efficient, fast, and reliable for synthetic image realizations. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…In this study, Support Vector Machine (SVM) models were trained for soil classification using 649 Cone Penetration Test (CPT) datasets, specifically utilizing cone tip resistance ( $$q_c$$ ) and sleeve friction ( $$f_s$$ ) as input variables. Pearson correlation and sensitivity analysis confirmed that these variables are highly correlated with the classification results. …”
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Wafer‐Scale Synthesis of Topological Insulator Sb2Te3 Thin Films by Ali Shafiei, Ahmad Fathi Hafshejani, Rehab M. G. Ahmed, Alessio Lamperti, Emanuele Longo, Lorenzo Locatelli, Christian Martella, Alessandro Molle, Graziella Tallarida, Carlo Zucchetti, Claudia Wiemer, Massimo Longo, Roberto Mantovan

“…Furthermore, comprehensive information on the variability of the functional properties of Sb2Te3 thin films with their morphological, chemical, and structural properties, as probed by scanning electron microscopy, X‐ray diffraction/reflectivity, atomic force microscopy, Raman spectroscopy, time‐of‐flight secondary ion mass spectrometry, and energy‐dispersive X‐ray analyses is reported. …”
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Enhancer chip: detecting human copy number variations in regulatory elements. by Marco Savarese, Giulio Piluso, Daniela Orteschi, Giuseppina Di Fruscio, Manuela Dionisi, Francesca del Vecchio Blanco, Annalaura Torella, Teresa Giugliano, Michele Iacomino, Marcella Zollino, Giovanni Neri, Vincenzo Nigro

“…Validation experiments have demonstrated that Enhancer Chip efficiently detects duplications and deletions covering enhancer loci, demonstrating that it is a powerful instrument to detect and characterize copy number variable enhancers.…”
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