Undulatory topographical waves for flow-induced foulant sweeping

Diverse bioinspired antifouling strategies have demonstrated effective fouling-resistant properties with good biocompatibility, sustainability, and long-term activity. However, previous studies on bioinspired antifouling materials have mainly focused on material aspects or static architectures of nature without serious consideration of kinetic topographies or dynamic motion. Here, we propose a magnetically responsive multilayered composite that can generate coordinated, undulatory topographical waves with controlled length and time scales as a new class of dynamic antifouling materials. The undulatory surface waves of the dynamic composite induce local and global vortices near the material surface and thereby sweep away foulants from the surface, fundamentally inhibiting their initial attachment. As a result, the dynamic composite material with undulating topographical waves provides an effective means for efficient suppression of biofilm formation without surface modification with chemical moieties or nanoscale architectures

타원체 입자의 원형관 내부 3차원 회전 거동 분석을 위한 홀로그래픽 현미경의 응용

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디지털 홀로그래픽 현미경과 인공지능 기반의 혈구성 질환 진단

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홀로그래픽 현미경과 기계학습형 인공 지능을 결합한 말라리아의 자동 진단 기술 개발

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Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic.115sciescopu

Digital stereo-holographic microscopy for studying three-dimensional particle dynamics

A digital stereo -holographic microscopy (DsHM) with two viewing angles is proposed to measure 3D information of microscale particles. This approach includes two volumetric recordings and numerical reconstruction, and it involves the combination of separately reconstructed holograms. The 3D positional information of a particle was determined by searching the center of the overlapped reconstructed volume. After confirming the proposed technique using static spherical particles, the 3D information of moving particles suspended in a Hagen-Poiseiulle flow was successfully obtained. Moreover, the 3D information of nonspherical particles, including ellipsoidal particles and red blood cells, were measured using the proposed technique. In addition to 3D positional information, the orientation and shape of the test samples were obtained from the plane images by slicing the overlapped volume perpendicular to the directions of the image recordings. This DsHM technique will be useful in analyzing the 3D dynamic behavior of various nonspherical particles, which cannot be measured by conventional digital holographic microscopy. (C) 2017 Elsevier Ltd. All rights reserved.11Nsciescopu

원형관 유동내 타원체의 회전 거동 분석을 위한 홀로그래픽 현미경의 응용

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Flow characteristics around a deformable stenosis under pulsatile flow condition

A specific portion of a vulnerable stenosis is deformed periodically under a pulsatile blood flow condition. Detailed analysis of such deformable stenosis is important because stenotic deformation can increase the likelihood of rupture, which may lead to sudden cardiac death or stroke. Various diagnostic indices have been developed for a nondeformable stenosis by using flow characteristics and resultant pressure drop across the stenosis. However, the effects of the stenotic deformation on the flow characteristics remain poorly understood. In this study, the flows around a deformable stenosis model and two different rigid stenosis models were investigated under a pulsatile flow condition. Particle image velocimetry was employed to measure flow structures around the three stenosis models. The deformable stenosis model was deformed to achieve high geometrical slope and height when the flow rate was increased. The deformation of the stenotic shape enhanced jet deflection toward the opposite vessel wall of the stenosis. The jet deflection in the deformable model increased the rate of jet velocity and turbulent kinetic energy (TKE) production as compared with those in the rigid models. The effect of stenotic deformation on the pulsating waveform related with the pressure drop was analyzed using the TKE production rate. The deformable stenosis model exhibited a phase delay of the peak point in the waveform. These results revealed the potential use of pressure drop waveform as a diagnostic index for deformable stenosis. Published by AIP Publishing.11sciescopu

초소수성 표면의 안정성에 대한 압력 구배의 영향

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