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  • Open Access

    ARTICLE

    Hierarchical Rigid Registration of Femur Surface Model Based on Anatomical Features

    Xiaozhong Chen*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 139-153, 2020, DOI:10.32604/mcb.2020.08933

    Abstract Existing model registration of individual bones does not have a high certainly of success due to the lack of anatomic semantic. In light of the surface anatomy and functional structure of bones, we hypothesized individual femur models would be aligned through feature points both in geometrical level and in anatomic level, and proposed a hierarchical approach for the rigid registration (HRR) of point cloud models of femur with high resolution. Firstly, a coarse registration between two simplified point cloud models was implemented based on the extraction of geometric feature points (GFPs); and then, according to the anatomic feature points (AFPs)… More >

  • Open Access

    ARTICLE

    Meta-Analysis of the Relationship between Normal Tension Glaucoma, Open-Angle Glaucoma, and Fractional Pressure Reserve

    Qi Li1,2, Ningli Wang3, Zhicheng Liu1,2, Lin Li1,2, Zhicheng Liu1,2, Wenjia Wang1,2, Xiaoxue Long1,2, Hongfang Song1,2,*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 119-137, 2020, DOI:10.32604/mcb.2020.09529

    Abstract Aim: To investigate the relationship between glaucoma and intraocular pressure (IOP), intracranial pressure (ICP), trans-laminar cribrosa pressure difference (TLCPD), and the newly proposed fractional pressure reserve (FPR). Methods: Ten articles were analyzed by meta-analysis, and subgroup analysis of three factors was conducted. Results: The patients with normal tension glaucoma (NTG) and open-angle glaucoma (OAG) have higher TLCPD and lower ICP than healthy subjects, with obvious heterogeneity. The greater heterogeneity may arise from different ICP measurements and from different countries or regions. FPR performs better than TLCPD in some ways. Conclusion: Both FPR and TLCPD can be used as indicators of… More >

  • Open Access

    ARTICLE

    Morphologies of Fibronectin Fibrils Formed under Shear Conditions and Their Cellular Adhesiveness Properties

    Phuong-Thao Nguyen-Thi1, Quoc Phong Le1, Volker R. Stoldt2, Ngoc Quyen Tran3,4, Anh Tho Le5, Khon Huynh1,*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 113-118, 2020, DOI:10.32604/mcb.2020.09643

    Abstract Fibrillar fibronectin (FFN) is a biological active form of FN which form linear and branched meshwork around cells and support cellular activities. Previous studies have demonstrated that shear stress can induce cell-free FN fibrillogenesis. In this study, we further examined the effect of shear stress conditions on morphology of formed FFN and preliminarily looked for relationship between FFN’s morphology and cell adhesion. Plasma FN at 50 µg/ml was perfused through channel slides at shear rates of 500 s-1 or 4000 s-1. Our results showed that there were four FFN structures formed: (1) FN nodules, (2) fibril in different sizes (3)… More >

  • Open Access

    ARTICLE

    Genetically Encoded FRET Biosensor Detects the Enzymatic Activity of Prostate-Specific Antigen

    Hui Yao1, Liqun Wang3, Jia Guo1, Weimin Liu4, Jingjing Li1, Yingxiao Wang2, Linhong Deng1,*, Mingxing Ouyang1,2,3,*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 101-111, 2020, DOI:10.32604/mcb.2020.09595

    Abstract Prostate cancer is the most common cancer among men beyond 50 years old, and ranked the second in mortality. The level of Prostate-specific antigen (PSA) in serum has been a routine biomarker for clinical assessment of the cancer development, which is detected mostly by antibody-based immunoassays. The proteolytic activity of PSA also has important functions. Here a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) technology was developed to measure PSA activity. In vitro assay showed that the biosensor containing a substrate peptide ‘RLSSYYSGAG’ had 400% FRET change in response to 1 µg/ml PSA within 90 min, and… More >

  • Open Access

    ARTICLE

    Information Classification and Extraction on Official Web Pages of Organizations

    Jinlin Wang1, Xing Wang1, *, Hongli Zhang1, Binxing Fang1, Yuchen Yang1, Jianan Liu2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2057-2073, 2020, DOI:10.32604/cmc.2020.011158

    Abstract As a real-time and authoritative source, the official Web pages of organizations contain a large amount of information. The diversity of Web content and format makes it essential for pre-processing to get the unified attributed data, which has the value of organizational analysis and mining. The existing research on dealing with multiple Web scenarios and accuracy performance is insufficient. This paper aims to propose a method to transform organizational official Web pages into the data with attributes. After locating the active blocks in the Web pages, the structural and content features are proposed to classify information with the specific model.… More >

  • Open Access

    ARTICLE

    Identification of Weather Phenomena Based on Lightweight Convolutional Neural Networks

    Congcong Wang1, 2, 3, Pengyu Liu1, 2, 3, *, Kebin Jia1, 2, 3, Xiaowei Jia4, Yaoyao Li1, 2, 3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2043-2055, 2020, DOI:10.32604/cmc.2020.010505

    Abstract Weather phenomenon recognition plays an important role in the field of meteorology. Nowadays, weather radars and weathers sensor have been widely used for weather recognition. However, given the high cost in deploying and maintaining the devices, it is difficult to apply them to intensive weather phenomenon recognition. Moreover, advanced machine learning models such as Convolutional Neural Networks (CNNs) have shown a lot of promise in meteorology, but these models also require intensive computation and large memory, which make it difficult to use them in reality. In practice, lightweight models are often used to solve such problems. However, lightweight models often… More >

  • Open Access

    ARTICLE

    Bilateral Collaborative Optimization for Cloud Manufacturing Service

    Bin Xu1, 2, Yong Tang1, Yi Zhu1, Wenqing Yan1, Cheng He3, Jin Qi1, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2031-2042, 2020, DOI:10.32604/cmc.2020.011149

    Abstract Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing, which directly affect the quality of Cloud Manufacturing services. However, the previous studies on the two components are carried out independently and thus ignoring the internal relations and mutual constraints. Considering the two components on both sides of the supply and the demand of Cloud Manufacturing services at the same time, a Bilateral Collaborative Optimization Model of Cloud Manufacturing (BCOM-CMfg) is constructed in this paper. In BCOM-CMfg, to solve the manufacturing service scheduling problem on the supply side, a new… More >

  • Open Access

    ARTICLE

    A Distributed Covert Channel of the Packet Ordering Enhancement Model Based on Data Compression

    Lejun Zhang1, Tianwen Huang1, Xiaoyan Hu1, Zhijie Zhang1, Weizheng Wang2, Donghai Guan3, *, Chunhui Zhao1, 4, Seokhoon Kim5

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2013-2030, 2020, DOI:10.32604/cmc.2020.011219

    Abstract Covert channel of the packet ordering is a hot research topic. Encryption technology is not enough to protect the security of both sides of communication. Covert channel needs to hide the transmission data and protect content of communication. The traditional methods are usually to use proxy technology such as tor anonymous tracking technology to achieve hiding from the communicator. However, because the establishment of proxy communication needs to consume traffic, the communication capacity will be reduced, and in recent years, the tor technology often has vulnerabilities that led to the leakage of secret information. In this paper, the covert channel… More >

  • Open Access

    ARTICLE

    A Recommendation Approach Based on Bayesian Networks for Clone Refactor

    Ye Zhai1, *, Dongsheng Liu1, Celimuge Wu2, Rongrong She1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1999-2012, 2020, DOI:10.32604/cmc.2020.09950

    Abstract Reusing code fragments by copying and pasting them with or without minor adaptation is a common activity in software development. As a result, software systems often contain sections of code that are very similar, called code clones. Code clones are beneficial in reducing software development costs and development risks. However, recent studies have indicated some negative impacts as a result. In order to effectively manage and utilize the clones, we design an approach for recommending refactoring clones based on a Bayesian network. Firstly, clone codes are detected from the source code. Secondly, the clones that need to be refactored are… More >

  • Open Access

    ARTICLE

    Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

    Kui Fu1, Jiansheng Peng1, 2, *, Hanxiao Zhang2, Xiaoliang Wang3, Frank Jiang4

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1977-1997, 2020, DOI:10.32604/cmc.2020.09882

    Abstract Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the… More >

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