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  • Open Access

    ARTICLE

    Skeleton-Based Volumetric Parameterizations for Lattice Structures

    Long Chen1,*, Shuxun Liang2, Nan Yan2, Xiangqian Yang2, Baotong Li3

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 687-709, 2023, DOI:10.32604/cmes.2022.021986 - 29 September 2022

    Abstract Lattice structures with excellent physical properties have attracted great research interest. In this paper, a novel volume parametric modeling method based on the skeleton model is proposed for the construction of three-dimensional lattice structures. The skeleton model is divided into three types of nodes. And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes. The unit-cell is assembled with distinct nodes according to the geometric features. The final lattice structure is created by the periodic arrangement of unit-cells. Several different types of volume parametric lattice structures are constructed to prove the More > Graphic Abstract

    Skeleton-Based Volumetric Parameterizations for Lattice Structures

  • Open Access

    ARTICLE

    Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition

    Motasem S. Alsawadi1,*, El-Sayed M. El-kenawy2,3, Miguel Rio1

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 19-36, 2023, DOI:10.32604/cmc.2023.032499 - 22 September 2022

    Abstract The ever-growing available visual data (i.e., uploaded videos and pictures by internet users) has attracted the research community's attention in the computer vision field. Therefore, finding efficient solutions to extract knowledge from these sources is imperative. Recently, the BlazePose system has been released for skeleton extraction from images oriented to mobile devices. With this skeleton graph representation in place, a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action. We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of More >

  • Open Access

    VIEWPOINT

    Poly(ADP-ribose), adherens junctions, vinculin and the actin cytoskeleton: Current evidence, future perspectives and implications

    LAURA LAFON-HUGHES1,2,*

    BIOCELL, Vol.46, No.12, pp. 2531-2535, 2022, DOI:10.32604/biocell.2022.022713 - 10 August 2022

    Abstract Poly(ADP-ribose) (PAR) is a highly negatively charged polymer. PAR is synthesized by poly(ADP-ribose)polymerases (PARPs) and is involved in the assembly and stabilization of macromolecular complexes. Here, the presence and putative roles of poly(ADP-ribosyl)ation (PARylation) associated to adherens junctions (AJ) and the actin cytoskeleton in epithelial and Schwann cells, is reviewed. The hypothesis generated by analogy, stating that PAR is associated to AJ in other cell types, is postulated. According to this hypothesis, PAR associated to puncta adherentia in chemical synapses would participate in plasticity, learning and memory. In turn, PAR associated to fascia adherens in cardiomyocytes, would affect More >

  • Open Access

    ARTICLE

    Skeleton Keypoints Extraction Method Combined with Object Detection

    Jiabao Shi1, Zhao Qiu1,*, Tao Chen1, Jiale Lin1, Hancheng Huang2, Yunlong He3, Yu Yang3

    Journal of New Media, Vol.4, No.2, pp. 97-106, 2022, DOI:10.32604/jnm.2022.027176 - 13 June 2022

    Abstract Big data is a comprehensive result of the development of the Internet of Things and information systems. Computer vision requires a lot of data as the basis for research. Because skeleton data can adapt well to dynamic environment and complex background, it is used in action recognition tasks. In recent years, skeleton-based action recognition has received more and more attention in the field of computer vision. Therefore, the keypoints of human skeletons are essential for describing the pose estimation of human and predicting the action recognition of the human. This paper proposes a skeleton point More >

  • Open Access

    VIEWPOINT

    The RhoA nuclear localization changes in replicative senescence: New evidence from in vitro human mesenchymal stem cells studies

    DANILA BOBKOV1,2,3,*, ANASTASIA POLYANSKAYA1, ANASTASIA MUSORINA1, GALINA POLJANSKAYA1

    BIOCELL, Vol.46, No.9, pp. 2053-2058, 2022, DOI:10.32604/biocell.2022.019469 - 18 May 2022

    Abstract All non-immortalized mesenchymal stem cells have a limited proliferative potential, that is, replicative senescence (RS) is an integral characteristic of the life of all mesenchymal stem cells (MSCs). It is known that one of the important signs of RS is a decrease of cell motility, and that violations of migration processes contribute to the deterioration of tissue regeneration. Therefore, the characterization of the properties of the cell line associated with RS is a prerequisite for the effective use of MSCs in restorative medicine. One of the key proteins regulating cell motility is the small GTPase More >

  • Open Access

    VIEWPOINT

    Mechanobiology of the cell surface: Probing its remodeling dynamics using membrane tether pulling assays with optical tweezers

    JULIANA SOARES1,2,#, DOUGLAS G. FREITAS1,3,#, PEDRO S. LOURENÇO1,4, JEFTE FARIAS1,5, BRUNO PONTES1,2,3,4,5,*

    BIOCELL, Vol.46, No.9, pp. 2009-2013, 2022, DOI:10.32604/biocell.2022.019969 - 18 May 2022

    Abstract Mammalian cell surfaces consist of the plasma membrane supported by an underneath cortical cytoskeleton. Together, these structures can control not only the shape of cells but also a series of cellular functions ranging from migration and division to exocytosis, endocytosis and differentiation. Furthermore, the cell surface is capable of exerting and reacting to mechanical forces. Its viscoelastic properties, especially membrane tension and bending modulus, are fundamental parameters involved in these responses. This viewpoint summarizes our current knowledge on how to measure the viscoelastic properties of cell surfaces employing optical tweezers-based tether assays, paving the way More >

  • Open Access

    ARTICLE

    Classification of Multi-Frame Human Motion Using CNN-based Skeleton Extraction

    Hyun Yoo1, Kyungyong Chung2,*

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 1-13, 2022, DOI:10.32604/iasc.2022.024890 - 15 April 2022

    Abstract Human pose estimation has been a major concern in the field of computer vision. The existing method for recognizing human motion based on two-dimensional (2D) images showed a low recognition rate owing to motion depth, interference between objects, and overlapping problems. A convolutional neural network (CNN) based algorithm recently showed improved results in the field of human skeleton detection. In this study, we have combined human skeleton detection and deep neural network (DNN) to classify the motion of the human body. We used the visual geometry group network (VGGNet) CNN for human skeleton detection, and More >

  • Open Access

    ARTICLE

    A Skeleton-based Approach for Campus Violence Detection

    Batyrkhan Omarov1,2,3,4,*, Sergazy Narynov1, Zhandos Zhumanov1,2, Aidana Gumar1,5, Mariyam Khassanova1,5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 315-331, 2022, DOI:10.32604/cmc.2022.024566 - 24 February 2022

    Abstract In this paper, we propose a skeleton-based method to identify violence and aggressive behavior. The approach does not necessitate high-processing equipment and it can be quickly implemented. Our approach consists of two phases: feature extraction from image sequences to assess a human posture, followed by activity classification applying a neural network to identify whether the frames include aggressive situations and violence. A video violence dataset of 400 min comprising a single person's activities and 20 h of video data including physical violence and aggressive acts, and 13 classifications for distinguishing aggressor and victim behavior were More >

  • Open Access

    REVIEW

    Microenvironment promotes cytoskeleton remodeling and adaptive phenotypic transition

    MARIANO BIZZARRI*, PAOLA PONTECORVI

    BIOCELL, Vol.46, No.6, pp. 1357-1362, 2022, DOI:10.32604/biocell.2022.018471 - 07 February 2022

    Abstract The cytoskeleton includes three main classes of networked filaments behaving as a coherent and complex structure that confers stability to cell shape while serving as sensor of internal/extracellular changes. Microenvironmental stimuli interfere with the non-linear dynamics that govern cytoskeleton architecture, namely by fostering symmetry breakings and transitions across different phenotypic states. Such process induces a wholecoherent adaptive response, involving the reprogramming of biochemical and gene-expression patterns. These characteristics are especially relevant during development, and in those conditions in which a deregulated crosstalk between cells and the stroma is at the core of the pathological process. More >

  • Open Access

    ARTICLE

    Skeleton Split Strategies for Spatial Temporal Graph Convolution Networks

    Motasem S. Alsawadi*, Miguel Rio

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4643-4658, 2022, DOI:10.32604/cmc.2022.022783 - 14 January 2022

    Abstract Action recognition has been recognized as an activity in which individuals’ behaviour can be observed. Assembling profiles of regular activities such as activities of daily living can support identifying trends in the data during critical events. A skeleton representation of the human body has been proven to be effective for this task. The skeletons are presented in graphs form-like. However, the topology of a graph is not structured like Euclidean-based data. Therefore, a new set of methods to perform the convolution operation upon the skeleton graph is proposed. Our proposal is based on the Spatial… More >

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