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Electrospray technology in the cone-jet regime has been numerically studied with the development of computational fluid dynamics (CFD). A novel interpolation method, the hybrid averaging mean (HAM), is presented in the present work, aimed at enhancing the accuracy of numerical simulations in electrohydrodynamic (EHD) atomization. Traditional methods such as the weighted arithmetic mean (WAM) and Weighted Harmonic Mean (WHM) have been widely used; however, the limitations are exhibited in terms of stability and computational efficiency. The HAM method combines the strengths of WHM's stability and WAM's simplicity, providing a balanced method to improve the accuracy of capturing interfacial dynamics and charge characteristics in EHD atomization. Through comprehensive numerical and experimental benchmarks, the effectiveness of HAM is evaluated against WAM and WHM, focusing on charge distribution, meniscus evolution, and droplet formation across varying regimes. The findings reveal that HAM significantly improves the modeling of electric field distributions and interfacial forces. The predictive accuracy of the methods is quantified with HAM achieving 4.5% error in beam current calculations, while WHM at 10.4% and WAM at 17.5% error. For droplet diameter predictions, HAM shows 1.2% error, while WHM has 11.8% error, and WAM has 11.2% error. The results underscore the importance of selecting appropriate interpolation methods to enhance the simulation accuracy and reliability in complex electrohydrodynamic systems.
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http://dx.doi.org/10.1021/acs.langmuir.5c02028 | DOI Listing |
PLoS One
September 2025
School of Civil Engineering, Shandong Jianzhu University, Jinan, China.
In engineering structure performance monitoring, capturing real-time on-site data and conducting precise analysis are critical for assessing structural condition and safety. However, equipment instability and complex on-site environments often lead to data anomalies and gaps, hindering accurate performance evaluation. This study, conducted within a wind farm reinforcement project in Shandong Province, addresses these challenges by focusing on anomaly detection and data imputation for weld nail strain, anchor cable axial force, and concrete strain.
View Article and Find Full Text PDFDermatol Surg
September 2025
Cooper Center for Dermatologic Surgery, Division of Dermatology, Cooper University Health Care, Evesham, New Jersey.
Background: Staged interpolation flaps remain central to reconstructing complex facial defects, with traditional pedicle takedown occurring approximately 3 weeks postoperatively. However, prolonged pedicle duration may cause patient discomfort and impair quality of life.
Objective: To evaluate the safety and outcomes of early takedown (<21 days) versus conventional takedown (≥21 days) across 3 commonly used interpolation flaps: postauricular, melolabial, and paramedian forehead.
J Int AIDS Soc
September 2025
Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA.
Introduction: We previously published a systematic review evaluating retention in care after antiretroviral therapy initiation among adults in low- and middle-income countries from 2008 to 2013. This review evaluates retention after the implementation of Universal Test and Treat (UTT) in 2015.
Methods: We searched PubMed, ISI Web of Science, Cochrane Database of Systematic Reviews and EMBASE for studies published 1 January 2017, through 31 December 2024 and searched conference abstract repositories from AIDS, IAS and CROI from 2015 to 2024.
Adv Sci (Weinh)
September 2025
School of Control Science and Engineering, Shandong University, Jinan, 250061, China.
Real-time and accurate temperature monitoring has been widely recognized in both academia and industry to ensure battery operation safety. Traditional techniques are generally limited to incomplete information caused by discrete sampling points. Hence, the spiral-serpentine distributed optical fiber sensor (DOFS) layout is presented to realize in-situ full-range temperature measurement.
View Article and Find Full Text PDFPLoS One
September 2025
School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China.
In recent years, You Only Look Once (YOLO) models have gradually been applied to medical image object detection tasks due to their good scalability and excellent generalization performance, bringing new perspectives and approaches to this field. However, existing models overlook the impact of numerous consecutive convolutions and the sampling blur caused by bilinear interpolation, resulting in excessive computational costs and insufficient precision in object detection. To address these problems, we propose a YOLOv8-based model using Efficient modulation and dynamic upsampling (YOLO-ED) to detect lung cancer in CT images.
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