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  • Open Access

    REVIEW

    Do tensile and shear forces exerted on cells influence mechanotransduction through stored energy considerations?

    FREDERICK H. SILVER1,2,*, TANMAY DESHMUKH2

    BIOCELL, Vol.48, No.4, pp. 525-540, 2024, DOI:10.32604/biocell.2024.047965 - 09 April 2024

    Abstract All tissues in the body are subjected externally to gravity and internally by collagen fibril and cellular retractive forces that create stress and energy equilibrium required for homeostasis. Mechanotransduction involves mechanical work (force through a distance) and energy storage as kinetic and potential energy. This leads to changes in cell mitosis or apoptosis and the synthesis or loss of tissue components. It involves the application of energy directly to cells through integrin-mediated processes, cell-cell connections, stretching of the cell cytoplasm, and activation of the cell nucleus via yes-associated protein (YAP) and transcriptional coactivator with PDZ-motif… More >

  • Open Access

    PROCEEDINGS

    Ion dynamics and Manipulation Under Extreme Confinement

    Yahui Xue1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09724

    Abstract Ion dynamics and precise control in nanochannels play key roles in biological systems, energy conversation, and environmental engineering. However, the mechanics behaviors of ions and their manipulation mechanism under extreme confinement remain largely unexplored. Biological ion channels acting as life’s transistors can gate simultaneously fast and selective ion transport through atomic-scale filters to maintain vital life functions. This biological inspiration motivates the quest for artificial structures with simultaneous functions of ion selectivity, fast transport and electrical gating at the atomic scale. Here, we experimentally investigate the ion dynamics and electrical manipulation in graphene channels of… More >

  • Open Access

    ARTICLE

    Efficient Classification of Remote Sensing Images Using Two Convolution Channels and SVM

    Khalid A. AlAfandy1, Hicham Omara2, Hala S. El-Sayed3, Mohammed Baz4,*, Mohamed Lazaar5, Osama S. Faragallah6, Mohammed Al Achhab1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 739-753, 2022, DOI:10.32604/cmc.2022.022457 - 24 February 2022

    Abstract Remote sensing image processing engaged researchers’ attentiveness in recent years, especially classification. The main problem in classification is the ratio of the correct predictions after training. Feature extraction is the foremost important step to build high-performance image classifiers. The convolution neural networks can extract images’ features that significantly improve the image classifiers’ accuracy. This paper proposes two efficient approaches for remote sensing images classification that utilizes the concatenation of two convolution channels’ outputs as a features extraction using two classic convolution models; these convolution models are the ResNet 50 and the DenseNet 169. These elicited… More >

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