50 research outputs found

    Ultra-precise Micro-motion Stage for Optical Scanning Test

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    This study aims at the application of optical sensing technology in a 2D flexible hinge test stage. Optical fiber sensor which is manufactured taking advantage of the various unique properties of optical fiber, such as good electric insulation properties, resistance of electromagnetic disturbance, sparkless property and availability in flammable and explosive environment, has lots of good properties, such as high accuracy and wide dynamic range, repeatable, etc. and is applied in 2D flexible hinge stage driven by PZT. Several micro-bending structures are designed utilizing the characteristics of the flexible hinge stage. And through experiments, the optimal micro-bending tooth structure and the scope of displacement sensor trip under this optimal micro-bending tooth structure are derived. These experiments demonstrate that the application of optical fiber displacement sensor in 2D flexible hinge stage driven by PZT substantially broadens the dynamic testing range and improves the sensitivity of this apparatus. Driving accuracy and positioning stability are enhanced as well

    Detection of Hepatocyte Growth Factor (HGF) Ligand-c-MET Receptor Activation in Formalin-Fixed Paraffin Embedded Specimens by a Novel Proximity Assay

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    Aberrant activation of membrane receptors frequently occurs in human carcinomas. Detection of phosphorylated receptors is commonly used as an indicator of receptor activation in formalin-fixed paraffin embedded (FFPE) tumor specimens. FFPE is a standard method of specimen preparation used in the histological analysis of solid tumors. Due to variability in FFPE preparations and the labile nature of protein phosphorylation, measurements of phospho-proteins are unreliable and create ambiguities in clinical interpretation. Here, we describe an alternative, novel approach to measure receptor activation by detecting and quantifying ligand-receptor complexes in FFPE specimens. We used hepatocyte growth factor (HGF)-c-MET as our model ligand-receptor system. HGF is the only known ligand of the c-MET tyrosine kinase receptor and HGF binding triggers c-MET phosphorylation. Novel antibody proximity-based assays were developed and used to detect and quantify total c-MET, total HGF, and HGF-c-MET ligand-receptor interactions in FFPE cell line and tumor tissue. In glioma cells, autocrine activation of c-MET by HGF-c-MET increased basal levels of c-MET phosphorylation at tyrosine (Tyr) 1003. Furthermore, HGF-c-MET activation in glioma cell lines was verified by Surface Protein-Protein Interaction by Crosslinking ELISA (SPPICE) assay in corresponding soluble cell lysates. Finally, we profiled levels o

    Versioning model in dual housing markets and its application

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    Versioning model has been frequently used to explain information economy, yet its application in housing markets seems absent. As housing market is a crucial determinant in defining countries’ economic and social welfare status, in this paper, versioning model is modified to explain the general mechanisms of housing markets and housing welfare re-distribution systems. In particular, the key relevant policies and regulations (e.g. income ceiling restriction, resale restriction and subsidy plan) of Singapore are examined to verify the effectiveness of the model, as Singapore is superior to many major Asian housing markets in maintaining housing price and promoting housing welfare. Under the assumption of existence of only two types of consumers (high-end and low-end consumers), our results show that the modified versioning model is not only capable of explaining dual housing market in Singapore, but also a theoretical guidance which can be applied to other emerging housing market, such as China. This project also implies the possibility of promoting welfare public housing and maintaining private market sectors at the same time based on the modified versioning model and it will be able to contribute to future research and policy making on Asian housing marketsBachelor of Art

    Graphene-Ag Hybrids on Laser-Textured Si Surface for SERS Detection

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    Surface-enhanced Raman scattering (SERS) has been extensively investigated as an effective approach for trace species detection. Silver nanostructures are high-sensitivity SERS substrates in common use, but their poor chemical stability impedes practical applications. Herein, a stable and sensitive SERS substrate based on the hybrid structures of graphene/silver film/laser-textured Si (G/Ag/LTSi) was developed, and a simple, rapid, and low-cost fabrication approach was explored. Abundant nanoparticles were directly created and deposited on the Si surface via laser ablation. These aggregated nanoparticles functioned as hotspots after a 30 nm Ag film coating. A monolayer graphene was transferred to the Ag film surface to prevent the Ag from oxidation. The SERS behavior was investigated by detecting R6G and 4-MBT molecules. The experimental results indicate that the maximum enhancement factor achieved by the G/Ag/LTSi substrate is over 107 and less than 23% SERS signals lost when the substrate was exposed to ambient conditions for 50 days. The covering graphene layer played crucial roles in both the Raman signals enhancement and the Ag nanostructure protection. The stable and sensitive SERS performance of G/Ag/LTSi substrate evince that the present strategy is a useful and convenient route to fabricate large-area graphene-silver plasmonic hybrids for SERS applications

    Single-Phase Safe-Commutation Trans-Z-Source AC–AC Converter With Continuous Input Current

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    Data loss for PLC of nonlinear systems Iterative Learning Control Algorithm

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    When we use power line as data carrier, due to the complexity of the PLC network environment, data packet loss frequently, so the paper deal with the iterative learning control for a class of nonlinear systems with measurement dropouts in the PLC, and studies the P-type iterative learning control algorithm convergence issues, the data packet loss is described as a stochastic Bernoulli process, on this basis we given convergence conditions for the P-type iterative learning control algorithm. The theoretically analysis is supported by the simulation of a numerical example; the convergence of ILC can be guaranteed when some output measurements are missing

    Analysis of structure and control of the loop-locked ultra-precise 2D flexible hinge stage for optical measurement - art no 672338

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    Conference Name:3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies. Conference Address: Chengdu, PEOPLES R CHINA. Time:JUL 08-12, 2007.Although PZT driving stage is a practical and widely used component in optical scanning measurement, its creep, hysteresis, poor long-term stability and the vibration of stage hindered the promotion in driving and positioning accuracy. Based on feedback control, the stage can have nanometer level driving accuracy. For attaching the displacement feedback sensor, a special structure that is called expanded hinge is designed. For getting higher sensitivity, a shallow groove is cut in it. In order to confirm the effect of the additional structure on the performance of the stage, the finite element software is employed, the analysis had been completed, and the simulated results are presented. With the vibration model of the 2D flexible hinge stage, the mathematic model of the vibration control can be achieved, and the PID control system is set up. After the sensors are carefully attached to the corresponding spot and the processing circuit is completed, the simulation and test of the overall performance of the stage can be executed

    An Intelligent Method for Detecting Surface Defects in Aluminium Profiles Based on the Improved YOLOv5 Algorithm

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    In response to problems such as low recognition rate, random distribution of defects and large-scale differences in the detection of surface defects of aluminum profiles by other state-of-the-art algorithms, this paper proposes an improved MS-YOLOv5 model based on the YOLOv5 algorithm. First, a PE-Neck structure is proposed to replace the neck part of the original algorithm in order to enhance the model’s ability to extract and locate defects at different scales. Secondly, a multi-streamnet is proposed as the first detection head of the algorithm to increase the model’s ability to identify distributed random defects. Meanwhile, to overcome the problem of inadequate industrial defect samples, the training set is enhanced by geometric variations and image-processing techniques. Experiments show that the proposed MS-YOLOv5 model has the best mean average precision (mAP) compared to the mainstream target-detection algorithm for detecting surface defects in aluminium profiles, whereas the average single image recognition time is within 19.1FPS, meeting the real-time requirements of industrial inspection

    Data loss for PLC of nonlinear systems Iterative Learning Control Algorithm

    No full text
    When we use power line as data carrier, due to the complexity of the PLC network environment, data packet loss frequently, so the paper deal with the iterative learning control for a class of nonlinear systems with measurement dropouts in the PLC, and studies the P-type iterative learning control algorithm convergence issues, the data packet loss is described as a stochastic Bernoulli process, on this basis we given convergence conditions for the P-type iterative learning control algorithm. The theoretically analysis is supported by the simulation of a numerical example; the convergence of ILC can be guaranteed when some output measurements are missing
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