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Xiaofei Gao,Guohua Jiang,Liming Ruan,Yanfang Sun,Khaydar E. Yunusov,Yanting Jing,Uladzislau E. Aharodnikau,Sergey O. Solomevich 한국섬유공학회 2023 Fibers and polymers Vol.24 No.2
Electrospun nanofibers represent a novel class of scaffold materials that show great potential in wound healing owing torelatively large surface area, better mimicry of native extracellular matrix, adjustable waterproofness and breathability, andprogrammable drug delivery process. In this work, electrospun polycaprolactone (PCL) and porcine acellular dermal matrix(PADM) composite nanofibrous membranes have been developed by electrospinning technology and inflated into threedimensional(3D) structural scaffold (PCL-PADM) by gas foaming method. The obtained PCL-PADM has higher thermalstability, hydrophilicity and better cell adhesion compared with PCL. In addition, ε-polylysine (ε-PL) is further attachedonto the surface of PADM/PCL to offer its good antibacterial properties. Moreover, the PADM/PCL fibrous scaffolds showexcellent cytocompatibility for promoting cell proliferation. In vivo models showed that the resultant PADM/PCL fibrousscaffolds exhibit an accelerating wound healing effect through promoting expression of vascular factor (CD31) and decreasingthe expression of tumor necrosis factor-α (TNF-α). These results indicate that the 3D fibrous scaffolds may be a potentialwound dressing for wound closure.
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Real Time Object Tracking with Sparse Prototypes
Dongxu Gao,Jiangtao Cao,Zhaojie Ju,Xiaofei Ji 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.4
Sparse representation (compressive sampling) has achieved impressive results in object tracking by looking for the best candidate with minimum reconstruction error using the target template. However, it may fail in some circumstances such as illumination changes, scale changes, the object color is similar with the surrounding region, and occlusion etc., in addition, high computational cost is required due to numerous calculations for solving an l1 norm related minimization problems. In order to resolve above problems, a novel method is introduced by exploiting an accelerated proximal gradient approach which aims to make the tracker runs in real time; moreover, both classic principal component analysis algorithm and sparse representation schemes are adapted for learning effective observation model and reduces the influence of appearance change. Both qualitative and quantitative evaluation demonstrate that the proposed tracking algorithm has favorably better performance than several state-of-the-art trackers using challenging benchmark image sequences, and significantly reduces the computing cost.
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