18,590 research outputs found

    Experimental investigation of the properties of electrospun nanofibers for potential medical application

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    Copyright © 2015 Anhui Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Polymer based nanofibers using ethylene-co-vinyl alcohol (EVOH) were fabricated by electrospinning technology. The nanofibers were studied for potential use as dressing materials for skin wounds treatment. Properties closely related to the clinical requirements for wound dressing were investigated, including the fluid uptake ability (FUA), the water vapour transmission rate (WVTR), the bacteria control ability of nanofibers encapsulated with different antibacterial drugs, and Ag of various concentrations. Nanofibre degradation under different environmental conditions was also studied for the prospect of long term usage. The finding confirms the potential of EVOH nanofibers for wound dressing application, including the superior performance compared to cotton gauze and the strong germ killing capacity when Ag particles are present in the nanofibers

    Morphological evolution of a 3D CME cloud reconstructed from three viewpoints

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    The propagation properties of coronal mass ejections (CMEs) are crucial to predict its geomagnetic effect. A newly developed three dimensional (3D) mask fitting reconstruction method using coronagraph images from three viewpoints has been described and applied to the CME ejected on August 7, 2010. The CME's 3D localisation, real shape and morphological evolution are presented. Due to its interaction with the ambient solar wind, the morphology of this CME changed significantly in the early phase of evolution. Two hours after its initiation, it was expanding almost self-similarly. CME's 3D localisation is quite helpful to link remote sensing observations to in situ measurements. The investigated CME was propagating to Venus with its flank just touching STEREO B. Its corresponding ICME in the interplanetary space shows a possible signature of a magnetic cloud with a preceding shock in VEX observations, while from STEREO B only a shock is observed. We have calculated three principle axes for the reconstructed 3D CME cloud. The orientation of the major axis is in general consistent with the orientation of a filament (polarity inversion line) observed by SDO/AIA and SDO/HMI. The flux rope axis derived by the MVA analysis from VEX indicates a radial-directed axis orientation. It might be that locally only the leg of the flux rope passed through VEX. The height and speed profiles from the Sun to Venus are obtained. We find that the CME speed possibly had been adjusted to the speed of the ambient solar wind flow after leaving COR2 field of view and before arriving Venus. A southward deflection of the CME from the source region is found from the trajectory of the CME geometric center. We attribute it to the influence of the coronal hole where the fast solar wind emanated from.Comment: ApJ, accepte

    Semileptonic BB Meson Decays Into A Highly Excited Charmed Meson Doublet

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    We study the heavy quark effective theory prediction for semileptonic BB decays into an orbital excited FF-wave charmed doublet, the (2+2^{+}, 3+3^{+}) states (D2D^{*'}_{2}, D3D_{3}), at the leading order of heavy quark expansion. The corresponding universal form factor is estimated by using the QCD sum rule method. The decay rates we predict are ΓBD2ν=1.85×1019GeV\Gamma_{B\to D^{*'}_{2}\ell\overline{\nu}}=1.85\times10^{-19} {GeV} and ΓBD3ν=1.78×1019GeV\Gamma_{B\to D_{3}\ell\overline{\nu}}=1.78\times10^{-19} {GeV}. The branching ratios are B(BD2ν)=4.6×107\mathcal {B}(B\to D_{2}^{*'}\ell\overline{\nu})=4.6\times10^{-7} and B(BD3ν)=4.4×107\mathcal {B}(B\to D_{3}\ell\overline{\nu})=4.4\times10^{-7}, respectively.Comment: 6 pages,2 figure

    Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition

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    In the recent year, state-of-the-art for facial micro-expression recognition have been significantly advanced by deep neural networks. The robustness of deep learning has yielded promising performance beyond that of traditional handcrafted approaches. Most works in literature emphasized on increasing the depth of networks and employing highly complex objective functions to learn more features. In this paper, we design a Shallow Triple Stream Three-dimensional CNN (STSTNet) that is computationally light whilst capable of extracting discriminative high level features and details of micro-expressions. The network learns from three optical flow features (i.e., optical strain, horizontal and vertical optical flow fields) computed based on the onset and apex frames of each video. Our experimental results demonstrate the effectiveness of the proposed STSTNet, which obtained an unweighted average recall rate of 0.7605 and unweighted F1-score of 0.7353 on the composite database consisting of 442 samples from the SMIC, CASME II and SAMM databases.Comment: 5 pages, 1 figure, Accepted and published in IEEE FG 201
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