Ms. Yanping Zhang Profile

Yanping Zhang

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Proceedings Article | 5 December 2024 Paper

Preparation and performance study of PLA @ PEO @ BT piezoelectric functional nanofibers

Mengzhu Liu, Yanping Zhang, Biyun Zhou, Zhaojie Wang, Tao Chen

Proceedings Volume 13418, 134180U (2024) https://doi.org/10.1117/12.3046873

KEYWORDS: Nanofibers, Elasticity, Tissue engineering, Piezoelectric materials, Polymers

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In recent years, piezoelectric functional nanofibers have been widely used in vascular tissue engineering. The preparation of nanofibers with good piezoelectric properties is beneficial for exploring the effects of mechanical signals induced electrical signals on cell behavior. The polylactic acid @ polyethylene oxide @ barium titanate (PLA @ PEO @BT) piezoelectric functional nanofiber successfully was prepared by electrospinning blending method. The nanofibers were characterized for their surface morphology, hydrophilicity, composition, mechanical properties, and piezoelectric properties using scanning electron microscopy, contact angle analyzer, x-ray diffractometer, ultra-high precision static micro force testing machine, and oscilloscope. PLA and PEO with different ratios in PLA @ PEO @ BT fibers formed a staggered porous network fiber structure and possessed different piezoelectric properties. When PLA: PEO=1:0, the output voltage was the highest, at 0.630V. As the proportion of PLA decreased, the output voltage was the lowest at 0.014V when PLA: PEO=1:1. Subsequently, due to the formation of numerous hydrogen bonds between the hydroxyl groups of PEO and BT, the output voltage gradually increased as the proportion of PEO increased. When PLA: PEO=0:1, the output voltage was 0.071V. The results indicated that PLA, PEO, and BT all exhibited synergistic piezoelectric effects. Therefore, these with different piezoelectric properties PLA @ PEO @ BT nanofibers were expected to be applied in vascular tissue engineering.

Proceedings Article | 8 October 2024 Paper

Effects of multiple factors on the transmission of excitatory postsynaptic current signals

Mengzhu Liu, YanPing Zhang, Tao Chen

Proceedings Volume 13271, 1327105 (2024) https://doi.org/10.1117/12.3038926

KEYWORDS: Neurons, Neural networks, Pulse signals, Interference (communication), Signal intensity, Complex systems, Matrices, Signal detection

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The propagation of subthreshold signals is an important part of information exchange in neural systems, but the propagation mechanism of subthreshold signals in neural networks and the influence of internal and external factors on propagation are still unclear. Based on this, firstly, a mathematical model for the transmission of subthreshold excitatory postsynaptic current (EPSC) signals in a multi-layer feedforward neural network is constructed. Each element is a HH neuron model. To simulate the connections between neurons in different layers of the cerebral cortex more closely, a multifactor WS small-world network (MF-WS) is proposed, which can form inter-layer differences by adjusting multiple factors. Then, according to the influence factors of MF-WS small-world network formation, explore its influence on EPSC signal transmission. Through research, the increase of synaptic coupling strength W, the number of neighbors K and the proportion of excitatory neurons R are conducive to the propagation of EPSC signals. With the increase of the respective weights of multiple factors, the optimal noise intensity conducive to the propagation of EPSC signals decreases. Finally, a multifactor-consistent BP neural network (MF-C-BP) is proposed to optimize the synaptic coupling strength and connection mode between layers, which increases the consistency of the neural network pulse discharge sequence after the EPSC signal transmission to real correlation (± 0.30 - ± 0.50) or significant correlation (± 0.50 - ± 0.80). By studying the propagation mechanism of EPSC signal and the consistency of pulse discharge, a more potential mechanism for EPSC signal coding in neural network is provided.

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