Gold Nanoparticles Array Growth from an Aqueous Solution on the Conductive Surface by V. Kusnezh, H. Ilchuk, F. Tsupko, M. Świniarski, Е.О. Zmiiovska

“…Surface morphology in the reflected and secondary electrons mode was investigated and AuNPs average size was determined. …”
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A Recognition Technology of Transmission Lines Conductor Break and Surface Damage by ZENG Jun, ZHAO Zi-gen, LIU Jing-li, LIU Hong-jun, CAO Lei, GENG Shao-bo, WAN Hong-yan

“…We analyze the performance of the technology by a series of experiments, and the results show that the proposed method can measure the conductor break and surface defects faults with the average accuracy of 90.45% and 92.05%, respectively.…”
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Hyperbolic Paraboloid Free-Surface Breakwaters: Hydrodynamic Study and Structural Evaluation by Hamid ElDarwich, Gaoyuan Wu, Krisna A Pawitan, Maria Garlock

“…Results indicate that hypar-faced FSBW produces increased wave attenuation compared to traditional flat-faced designs, particularly for shorter wave periods and smaller drafts. Furthermore, hypar surfaces exhibit up to three times lower principal stresses under wave loading compared to the flat counterpart, potentially allowing for thinner surfaces. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Insufficient knowledge and control of the surrounding environmental risks in the process of subway tunnel construction will lead to different degrees of surface settlement during construction, and it is of practical significance to grasp the impact of environmental risks on surface settlement and make predictions on this basis. …”
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Flow in Microchannels between Sealing Surfaces of Casing Connections: LBM Simulation by Feng Ye, Feng Chen, Wenchang Wang, Renliang Zhang, Xing Zhou, Ken Qin, Qinfeng Di

“…The in situ microscopic seal surfaces under complex loads are hard to be obtained due to the engagement characteristics of thread. …”
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Steel Surface Defect Detection Based on Improved GCHS-YOLO Algorithm by Ruiqiang Guo, Peiyong Ji, Yapin Zhang, Jingqi Hu, Wenlong Liu, Xuejian Li, Min Li

“…In this paper, we address challenges in steel surface defect inspection, such as missed detections and false detections, by proposing the GCHS-YOLO detection algorithm. …”
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Automated Sidewalk Surface Detection Using Wearable Accelerometry and Deep Learning by Do-Eun Park, Jong-Hoon Youn, Teuk-Seob Song

“…This data is then transformed into the frequency domain using Fast Fourier Transform (FFT), a Kalman filter, a low-pass filter, and a moving average filter. A deep learning model is subsequently utilized to classify the conditions of the sidewalk surfaces using this transformed data. …”
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Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models by Octavia Crompton, Gabriel Katul, Sally E. Thompson

“…Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.…”
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Designs for photovoltaic glass surface texturing to improve transmittance and minimize glare by Yangping Tan, Xilian Sun, Changxin Tang, Lang Zhou, Xiuqin Wei, Jikui Zhang, Wei Xia, Yaokai Liu, Zhiwei Li

“…The optimized hexagonal array structured surface could improve the average transmission by ∼5% relative to planar surface for AOIs of 0°–80°. …”
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Heavy metal distribution and ecological risk in surface sediments of the Bohai Sea. by Shilin Li, Jianlei Chen, Xuzhi Zhang, Jianshe Zhang, Yongjiang Xu, Yong Xu

“…This study investigated the spatial distribution, seasonal dynamics, and potential ecological risks of heavy metal contamination in the central Bohai Sea, with an emphasis on regulatory interventions and anthropogenic influences. The annual average concentrations of Cu, Zn, Pb, Cd, Hg and As in surface sediments were 15.951, 32.556, 15.234, 0.250, 0.028 and 2.628 mg/kg, respectively, all below China's Class I Marine Sediment Quality Standards. …”
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Smart system for real time monitoring and diagnosis of dengue surfaces in Bangladesh by Md. Shahriar Hossain Apu, Samsuddin Ahmed, Md. Toukir Ahmed

“…Leveraging a CBAM-enhanced YOLOv9 object detection framework, we present a UAV-based strategy for dengue surface monitoring, achieving an impressive mean Average Precision (mAP) of 99.5% for mAP50, 86.4% for mAP50-95, 94% for Intersection over Union (IoU), 45 FPS, 98% precision, and 90% recall. …”
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Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…However, the diverse types and significant size variations of defects on steel surfaces pose great challenges. Among these defects, small-sized defects are characterized by their subtle appearance on the surface, making them difficult to distinguish from the background. …”
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A Biomimetic Flexible Sliding Suction Cup Suitable for Curved Surfaces by Enhua Cui, Xiangcong Zhou, Yanqiang Liu, Jixiao Xue, Siyuan Xiong, Deyuan Zhang

“…Additionally, a friction reduction model for the matrix structure is designed to verify the effects of parameters such as load, protrusion size, and quantity on the friction coefficient of the matrix structure surface through friction tests. The sliding suction cup prototype presents an average crawling speed of about 0.4 m/s on a horizontal plane and 0.7 m/s for crawling on vertical walls and the inner surface of a cylindrical rail.…”
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Variation in Surface Solar Radiation and the Influencing Factors in Xinjiang, Northwestern China by Lili Jin, Zhenjie Li, Qing He, Alim Abbas

“…The variation of solar radiation has a profound effect on the surface energy balance and hydrological cycle. Although the relationship between solar radiation variation and its influencing factors has been extensively studied, they are seldom used in Xinjiang, the largest province in China. …”
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Preferential Hydrologic States and Tipping Characteristics of Global Surface Soil Moisture by Vinit Sehgal, Binayak P. Mohanty

“…However, observational and scaling constraints limit critical SM threshold estimation at the remote‐sensing (RS) footprint scale. Using global surface SM (θRS) from NASA’s Soil Moisture Active Passive (SMAP) satellite, we characterize the seasonal preferential hydrologic states of θRS and derive three tipping characteristics to estimate the intensity (Mean Tipping Depth, ε‾), frequency (Tipping Count, η), and duration (Mean Tipped Time, τ‾) of the excursion of θRS from wet‐ to dry‐average conditions. …”
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Steel surface defect detection and segmentation using deep neural networks by Sara Ashrafi, Sobhan Teymouri, Sepideh Etaati, Javad Khoramdel, Yasamin Borhani, Esmaeil Najafi

“…In summary, the results validate the efficient performance of the studied techniques for accurate defect detection on steel surfaces.…”
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Predictor Importance for Hydrological Fluxes of Global Hydrological and Land Surface Models by João Paulo L. F. Brêda, Lieke A. Melsen, Ioannis Athanasiadis, Albert VanDijk, Vinícius A. Siqueira, Anne Verhoef, Yijian Zeng, Martine van derPloeg

“…We analyzed the JULES, ORCHIDEE, HTESSEL, SURFEX, and PCR‐GLOBWB models for the relative importance of precipitation, climate, soil, land cover and topographic slope as predictors of simulated average evaporation, runoff, and surface and subsurface runoff. …”
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Steel Surface Defect Detection Technology Based on YOLOv8-MGVS by Kai Zeng, Zibo Xia, Junlei Qian, Xueqiang Du, Pengcheng Xiao, Liguang Zhu

“…Surface defects have a serious detrimental effect on the quality of steel. …”
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Analytical and numerical analysis of heat transfer from radial extended surface by AbdulKareem Mishaal A.

“…In addition, the second approach assumes the arithmetic average model to evaluate the thermal conductivity at the intersection of two neighbor control volumes. …”
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Detection of frictional meltwater on snow surface using a humidity indicator by Shiraz Ahmed Siddiqui, Michael Hasler, Martin Mössner, Joost van Putten, Kurt Schindelwig, Werner Nachbauer

“…For numerical evaluation of the data, we took a percentage change of the average ratios in the frames and then calculated the average for all ten runs. …”
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