Reversibly assembled microfluidic devices are dismountable and reusable, which is useful for a number of applications such as micro- and nano-device fabrication, surface functionalization, complex cell patterning, and other biological analysis by means of spatial–temporal pattern. However, reversible microfluidic devices fabricated with current standard procedures can only be used for low-pressure applications. Assembling technology based on glass–PDMS–glass sandwich configuration provides an alternative sealing method for reversible microfluidic devices, which can drastically increase the sealing strength of reversibly adhered devices. The improvement mechanism of sealing properties of microfluidic devices based on the sandwich technique has not been fully characterized, hindering further improvement and broad use of this technique. Here, we characterize, for the first time, the effect of various parameters on the sealing strength of reversible PDMS/glass hybrid microfluidic devices, including contact area, PDMS thickness, assembling mode, and external force. To further improve the reversible sealing of glass–PDMS–glass microfluidic devices, we propose a new scheme which exploits mechanical clamping elements to reinforce the sealing strength of glass–PDMS–glass sandwich structures. Using our scheme, the glass–PDMS–glass microchips can survive a pressure up to 400 kPa, which is comparable to the irreversibly bonded PDMS microdevices. We believe that this bonding method may find use in lab-on-a-chip devices, particularly in active high-pressure-driven microfluidic devices. 相似文献
Multimedia Tools and Applications - Supervised hashing has achieved better accuracy than unsupervised hashing in many practical applications owing to its use of semantic label information. However,... 相似文献
Person re-identification plays important roles in many practical applications. Due to various human poses, complex backgrounds and similarity of person clothes, person re-identification is still a challenging task. In this paper, we mainly focus on the robust and discriminative appearance feature representation and proposed a novel multi-appearance method for person re-identification. First, we proposed a deep feature fusion method and get the multi-appearance feature by combining two Convolutional Neural Networks. Then, in order to further enhance the representation of the appearance feature, the multi-part model was constructed by combining the whole body and the six body parts. Additionally, we optimized the feature extraction process by adding a pooling layer. Comprehensive and comparative experiments with the state-of-the-art methods over publicly available datasets demonstrated that the proposed method can get promising results.
Atomic force microscopy (AFM) uses a very sharp pointed mechanical probe to collect real-space morphological information of
solid surfaces. AFM was used in this study to image the surface morphology of a biaxially oriented polypropylene film. The
polymer film is characterized by a nanometer-scale, fiberlike network structure, which reflects the drawing process used during
the fabrication of the film. AFM was used to study polymer-surface treatment to improve wettability by exposing the polymer
to ozone with or without ultraviolet (UV) irradiation. Surface-morphology changes observed by AFM are the result of the surface
oxidation induced by the treatment. Due to the topographic features of the polymer film, the fiberlike structure has been
used to check the performance of the AFM tip. An AFM image is a mixture of the surface morphology and the shape of the AFM
tip. Therefore, it is important to check the performance of a tip to ensure that the AFM image collected reflects the true
surface features of the sample, rather than contamination on the AFM tip. 相似文献
The growing size of multiprocessor systems increases the vulnerability to component failures. It is crucial to locate and replace faulty processors to maintain the system's high reliability. Processor fault diagnosis is essential to the reliability of a multiprocessor system and the diagnosabilities of many well-known networks (such as hierarchical hypercubes and crossed cubes [S. Zhou, L. Lin and J.-M. Xu, Conditional fault diagnosis of hierarchical hypercubes, Int. J. Comput. Math. 89(16) (2012), pp. 2152–2164 and S. Zhou, The conditional diagnosability of crossed cubes under the comparison model, Int. J. Comput. Math. 87(15) (2010), pp. 3387–3396]) have been investigated in the literature. A system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly t-diagnosable if it is t-diagnosable and can achieve (t+1)-diagnosability except for the case where a node's neighbours are all faulty. In addition, conditional diagnosability has been widely accepted as a new measure of diagnosability by assuming that any fault-set cannot contain all neighbours of any node in a multiprocessor system. In this paper, we determine the conditional diagnosability and strong diagnosability of an n-dimensional shuffle-cube SQn, a variant of hypercube for multiprocessor systems, under the comparison model. We show that the conditional diagnosability of shuffle-cube SQn (n=4k+2 and k≥2) is 3n?9, and SQn is strongly n-diagnosable under the comparison model. 相似文献