Investigating the relationship between the monetary policy shock through the exchange rate channel on the management quality index in the banking system: by examining the productiv... by Farhad Sharifi Bagha, Jafar Haqiqat, Zahra Karimi Takanloo

“…During this time, the number of changes in the target variables by the variables themselves decreases and the changes in the variables caused by the shock of the exchange rate channel increase. …”
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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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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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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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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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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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PRODUCTION AND INCOME ANALYSIS OF DRIED FISH BUSINESS IN BENGKULU CITY by Bambang Sumantri, Irnad, Winta Septria, Melly Suryanti, Widya Kartika Laksmawati

“…R/C Ratio analysis obtained efficiency values of 2.13 and 1.91 respectively so the business is carried out proved to be efficient. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…Industrial energy systems are increasingly required to reduce operating costs and CO₂ emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. …”
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Notice of Violation of IEEE Publication Principles: VVC/H.266 Intra Mode QTMT Based CU Partition Using CNN by Sameena Javaid, Safdar Rizvi, Muhammad Talha Ubaid, Abdullah Tariq

“…Finally, a variable threshold decision system is established to achieve the targeted low complexity and RD performance. …”
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Impact of municipal wastewater use on urban and peri‑urban agricultural productivity: the endogenous treatment-effects approach by Mohammed Abdulai, Mohammed Tanko, Alhassan Andani

“…Using survey data from 416 vegetable farmers, we employed a semi-log production function augmented with an endogenous binary-treatment effect equation to estimate the drivers and impact of MWW use on value of vegetable output, accounting for selection bias and omitted variable problem. …”
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Machine learning with hyperparameter optimization applied in facies-supported permeability modeling in carbonate oil reservoirs by Watheq J. Al-Mudhafar, Alqassim A. Hasan, Mohammed A. Abbas, David A. Wood

“…On the other hand, highly permeable fractures function as the main flow conduits within such reservoirs. …”
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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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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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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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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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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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