FREDERICK H. SILVER^1,2,*, TANMAY DESHMUKH²

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

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 (TAZ). These processes involve numerous… More >

Yahui Xue^1,*

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 3 angstrom size and report… More >

Khalid A. AlAfandy¹, Hicham Omara², Hala S. El-Sayed³, Mohammed Baz^4,*, 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

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 features have been used by… More >