Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In addition, the closed-form solutions of the optimized variables are obtained. Simulation results demonstrate that the proposed collaborative training scheme based on D2D can reduce the impact of heterogeneity on FL model performance and IRA can effectively reduce energy consumption while simultaneously enhancing training efficiency of FL.…”
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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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Impact of viscous dissipation, chemical reaction over a Carreau hybrid nanofluids flow across a permeable curved Riga surface by R. Mahesh, U.S. Mahabaleshwar, Basma Souayeh

“…Subsequently, the original partial differential equations are transformed using boundary layer approximations and similarity variables to produce a dimensionless ordinary differential equation. …”
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High-accuracy solution of pantograph differential equations subject to mixed boundary conditions via shifted Vieta–Lucas polynomials by R. M. Hafez, H. M. Ahmed

“…A Galerkin method (GM) is formulated for constant coefficient-type equations, and a spectral collocation method (SCM) is given for variable coefficient cases. …”
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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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Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
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Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
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Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests by Muhammad Junaid Ismail, Tika Ram Poudel, Akber Ali, Lingbo Dong

“…The model explained 71% of variability with significant trends in the residuals. …”
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Moral Development and Wisdom: The Mediating Role of Moral Intelligence and Emotional Intelligence by Heng Zheng, Jing Dong, Yang Lihua

“…Results: The results showed that the conceptual model of the study had an appropriate fit. Examining the coefficients of the effects of the research variables on each other, it seemed that moral development had a direct standardized effect coefficient of 0.53 on intelligence. …”
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COVID-19 recovery: benefits of multidisciplinary respiratory rehabilitation by Wim Janssens, Greet Hermans, Rik Gosselink, Daniel Langer, Thierry Troosters, Hilde Beyens, Stephanie Everaerts, Arne Heyns, Natalie Lorent

“…Impressive results on physical recovery were determined after 6 weeks and 3 months, with significant improvement of lung function, muscle force and exercise capacity variables. …”
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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.

“…Several MoCA items demonstrated relatively low variability, i.e., they proved to be too easy for most of the participants. …”
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Path model explaining the association between fear of falling and health-related quality of life in (pre-)frail older adults by Tjard Sattler, Sophie Gottschalk, Hans-Helmut König, Tobias Braun, Gisela Büchele, Michael Denkinger, Tim Fleiner, Corinna Nerz, Kilian Rapp, Martina Schäufele, Christian Werner, Judith Dams

“…Unlike previous studies that examined only few mediating variables, this study aimed to develop a more comprehensive path model explaining the association between FoF and HrQoL. …”
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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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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

“…Despite advances, existing diagnostic methods face challenges such as resource dependency, variability in accuracy, and limited accessibility, especially in underserved regions. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…While x-ray micro-computed tomography gives us three-dimensional images of the porous media, it is often impossible to quantify the variability of the pore, grains, structure, and orientation experimentally. …”
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Variations in Creatinine Generation Among Patients With Glomerular Disease: Evidence From the NEPTUNE and CureGN Studies by Shalini S. Ramachandra, Melody Chiang, Michael Arbit, Dorey A. Glenn, Laura H. Mariani, Jarcy Zee

“…Analytical Approach: The intraclass correlation coefficient illustrated crG variability within individuals. …”
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Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong, Chaohai Li

“…Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. …”
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Association between TSH Values and GFR Levels in Euthyroid Cases with Metabolic Syndrome by H. Keskin, K. Cadirci, K. Gungor, T. Karaaslan, T. Usta, A. Ozkeskin, A. Musayeva, F. Yesildal, F. Isman, H. Y. Zengin

“…Partial correlation coefficients were calculated to investigate the relationship between the eGFR values and several other numerical variables while controlling for age and BMI in addition to the adjusted gender effect. …”
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