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532 results on '"Li, Xueyang"'

102. A strain-rate dependent engineering approximation of the temperature rise in plastically-deforming DP steel

Author

Li Xueyang, Roth Christian C., and Mohr Dirk

Subjects
Physics, QC1-999
Abstract

Experiments at ten strain rates ranging from 0.001/s to 4/s are carried out on uniaxial tension specimens extracted from DP800 metal sheets. Digital Image Correlation (DIC) is used to obtain surface strain fields and a high speed infrared (IR) camera is employed to measure the corresponding temperature rise due to plastic dissipation. A temperature rise of 60K is witnessed for the highest loading speed whereas minimal temperature rise (

Published
2021
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103. Plasticity and fracture of aluminium 7075 at high strain rates and elevated temperatures

Author

Li Xueyang, Pandya Kedar, Karathanasopoulos Nikos, Roth Christian C., and Mohr Dirk

Subjects
Physics, QC1-999
Abstract

Slow, intermediate and high strain rate experiments with UT geometries are performed on aluminum AA7075-T6 sheet metal at various temperatures. The comprehensive experimental program characterizes the plasticity response at temperatures ranging from 20°C to 360°C and at strain rates ranging from 0.001/s to 150/s. The elevated temperature - elevated strain rate experiments are performed on a hydraulic tensile testing machine and a Split Hopkinson Pressure Bar system with a Load Inversion Device along with a custom-made induction heating system. A machine learning based modified Johnson-Cook plasticity model is calibrated to capture the complex strain rate and temperature effect of the observed hardening response.

Published
2021
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104. 592 Gbps/<inline-formula><tex-math notation="LaTeX">$\uplambda$</tex-math></inline-formula> Capacity of Equivalent Fronthaul Channel Based on Time-Interleaved Digital-Analog Radio-Over-Fiber

Author

Cheng, Chen, Li, Xueyang, Wu, Qi, Hao, Yaguang, Wei, Jinlong, Yang, Yanfu, and Hu, Weisheng

Abstract

We propose a novel time-interleaved hybrid digital-analog radio-over-fiber (TI-DA-ROF) scheme and verify it through experiments in a coherent optical communication system. This scheme relies on the digital symbols to measure the channel dynamics, based on which compatible DSP algorithms are conceived to compensate for the impairments that affect all DA symbols, thus enabling a robust RoF scheme against degradations, including polarization rotation, frequency offset, and phase noise. We conduct a numerical analysis to evaluate the performance of the DA-RoF scheme in different digital resolutions and to show its ability to tolerate MHz laser linewidth. In the proof-of-concept experiment, we demonstrate a high SNR gain of 12 dB at halved spectral efficiency. We test 256-QAM to 16384-QAM signals and calculate the effective SNR and EVM, demonstrating the transmission of 256-QAM and 1024-QAM signals achieving record capacity of the equivalent fronthaul channel (CEFC) of 674.66 Gbps and 592.01 Gbps, respectively. The experimental results show that the time-interleaved coherent DA-RoF system is a promising solution for the future beyond-5G/6G (B5G/6G) fronthaul.

Published
2024
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110. Silicon Photonic Phase-diverse Receiver Enabling Transmission of >Net 250 Gbps/λ over 40 km for High-speed and Low-cost Short-Reach Optical Communications

Author

Hu, Yixiang, primary, Li, Xueyang, additional, Mao, Deng, additional, Alam, Md Samiul, additional, Berikaa, Essam, additional, Zhang, Jinsong, additional, Bernal, Santiago, additional, Samani, Alireza, additional, Mousa-Pasandi, Mohammad E., additional, O'Sullivan, Maurice, additional, and Plant, David V., additional

Published
2023
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112. Characterization of Neutralizing Monoclonal Antibodies and Identification of a Novel Conserved C-Terminal Linear Epitope on the Hemagglutinin Protein of the H9N2 Avian Influenza Virus

Author

Wang, Yanan, primary, Li, Xueyang, additional, Xu, Qianru, additional, Niu, Xiangxiang, additional, Zhang, Shenli, additional, Qu, Xiaotian, additional, Chu, Hongyan, additional, Chen, Jinxuan, additional, Shi, Qianqian, additional, Zhang, Erqin, additional, and Zhang, Gaiping, additional

Published
2022
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116. Exosomal microRNA⁃93⁃3p secreted by bone marrow mesenchymal stem cells downregulates apoptotic peptidase activating factor 1 to promote wound healing

Author

Shen, Caiqi, Tao, Changbo, Zhang, Aijun, Li, Xueyang, Guo, Yanping, Wei, Hanxiao, Yin, Qichuan, Li, Qiang, and Jin, Peisheng

Subjects
Keratinocytes, Bioengineering, exosomes, Models, Biological, apaf1, Applied Microbiology and Biotechnology, Cell Line, Cell Movement, HaCaT Cells, Humans, 3' Untranslated Regions, Cell Proliferation, Wound Healing, integumentary system, Mesenchymal Stem Cells, Hydrogen Peroxide, General Medicine, mir-93-3p, MicroRNAs, Apoptotic Protease-Activating Factor 1, bone marrow mesenchymal stem cell, skin wound healing, TP248.13-248.65, Research Article, Research Paper, Biotechnology
Abstract

Wounds are soft tissue injuries, which are difficult to heal and can easily lead to other skin diseases. Bone marrow mesenchymal stem cells (BMSCs) and the secreted exosomes play a key role in skin wound healing. This study aims to clarify the effects and mechanisms of exosomes derived from BMSCs in wound healing. Exosomes were extracted from the supernatant of the BMSCs. The expression of the micro-RNA miR-93-3p was determined by qRT-PCR analysis. HaCaT cells were exposed to hydrogen peroxide (H2O2) to establish a skin lesion model. MTT, flow cytometry, and transwell assays were conducted to determine cellular functions. The binding relationship between miR-93-3p and apoptotic peptidase activating factor 1 (APAF1) was measured using a dual luciferase reporter gene assay. The results showed that BMSC-derived exosomes or BMSC-exos promoted proliferation and migration and suppressed apoptosis in HaCaT cells damaged by H2O2. However, the depletion of miR-93-3p in BMSC-exos antagonized the effects of BMSC-exos on HaCaT cells. In addition, APAF1 was identified as a target of miR-93-3p. Overexpression of APAF1 induced the dysfunction of HaCaT cells. Collectively, the results indicate that BMSC-derived exosomes promote skin wound healing via the miR-93-3p/APAF1 axis. This finding may help establish a new therapeutic strategy for skin wound healing.

Published
2021

122. An Improved Immunochromatographic Strip Based on Plant-Derived E2 for Detection of Antibodies against Classical Swine Fever Virus

Author

Xu, Qianru, primary, Sun, Yaning, additional, Yang, Jifei, additional, Ma, Fanshu, additional, Wang, Yanan, additional, Zhang, Shenli, additional, Li, Xueyang, additional, Qu, Xiaotian, additional, Bai, Yilin, additional, Jia, Rui, additional, Wang, Li, additional, Zhang, Erqin, additional, and Zhang, Gaiping, additional

Published
2022
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125. Intelligent Dynamic Spectrum Access Using Deep Reinforcement Learning for VANETs

Author

Shao Ruiyu, Li Xueyang, Yonghua Wang, and Pin Wan

Subjects
Computer science, business.industry, Wireless ad hoc network, law.invention, Vehicle dynamics, Recurrent neural network, Transmission (telecommunications), Aloha, Relay, law, Reinforcement learning, Electrical and Electronic Engineering, business, Instrumentation, Communication channel, Computer network
Abstract

In vehicular ad hoc networks (VANETs), vehicles can communicate with other vehicles or devices through vehicle-to-X communication. However, with the rise of the Internet of Things, it is a real challenge to make the limited spectrum resource meet the increasing communication demands, i.e., the channel contention problem. To solve this problem, this paper proposes a strategy combining multi-hop forwarding through vehicles and dynamic spectrum access. Firstly, a group-based multi-hop broadcast protocol, G-hop, is proposed. G-hop classifies vehicles with similar characteristics such as moving speed and communication distance into same groups using the depth-first-search algorithm. Messages are forwarded within a group in priority and then across groups, which limits both the range and the number of relay vehicles, i.e., channel contenders. Further, we adopt deep reinforcement learning techniques to achieve dynamic spectrum access. We design a Global Optimization algorithm based on Experience Accumulation (GOEA) using deep reinforcement learning. In GOEA, a network structure combined with recurrent neural network and deep Q-network is proposed for learning the time-varying process, and then a reward method is applied to optimize the global utility. Vehicles that need to transmit messages select channels dynamically following the guidance of GOEA. The experimental results demonstrate that the G-hop protocol reduces the packet loss rate from 0.8 to about 0.1. Meanwhile, compared with Slotted Aloha and DQN, our GOEA algorithm reduces the collision probability and channel idle probability by 60%. Moreover, as the number of vehicles increases, the transmission success rate can be improved by 20%.

Published
2021

127. Dueling deep Q-networks for social awareness-aided spectrum sharing

Author

Le Chang, Li Xueyang, Xia Deng, Yonghua Wang, and Pin Wan

Subjects
021110 strategic, defence & security studies, Social network, business.industry, Computer science, Control (management), 0211 other engineering and technologies, 020206 networking & telecommunications, Computational intelligence, 02 engineering and technology, General Medicine, Transmitter power output, 0202 electrical engineering, electronic engineering, information engineering, Social relationship, Reinforcement learning, Social consciousness, Spectrum sharing, business, Computer network
Abstract

In overlapping spectrum sharing, due to the complexity of cognitive environment, it is a real challenge for a secondary user (SU) to correctly sense the usage of the spectrum in real time. To tackle this challenge, a social awareness-aided transmit power control policy for SUs is developed. First, a social network composed of a group of third-party sensing nodes that do not share the spectrum with the PU is established, which helps an SU collect the power information of the PU. Then, we design a Dueling Deep Q-Network (DQN) model to achieve efficient dynamic spectrum sharing between the PU and the SU with the power information collected in the social network. Experimental results show that the spectrum sharing success rate is higher and the comprehensive performance is improved with the sensing nodes selected by the social relationship. Moreover, compared with other deep reinforcement learning (DRL) algorithms, the performance of Dueling DQN is more stable on our targeted spectrum sharing problem.

Published
2021

139. Plasticity and fracture of AA7075 at elevated strain rates and temperatures

Author

Li, Xueyang, Roth, Christian, Pandya, Kedar Sanjay, Karathanasopoulos, Nikolaos, and Mohr, Dirk

Abstract

The accurate description of the strain rate and temperature dependent response of Aluminium alloys is a perpetual quest in the hot forming industry. In the present study, uniaxial tension, and notched tension experiments are conducted for an aluminium AA7075-T6 sheet metal at various temperatures and strain rates. The experimental campaign covers strain rates ranging from 0.001/s to 100/s, and temperatures ranging from 20°C to 360°C. We observe low strain rate sensitivity at room temperature, with an increase in strain rate sensitivity as temperature is increased up to 360°C. An YLD2000-3D model is employed to describe the anisotropy of the material. A machine learning based hardening model is employed to capture the complex strain rate and temperature effect on the observed hardening response. Counter-example regularization is utilized to guarantee a convergence in the numeric return-mapping algorithm. Comparing the experimental force-displacement curves with the numerical predictions, the neural network model accurately describes the large deformation response of the material in the post-necking range., IOP Conference Series: Materials Science and Engineering, 1238, ISSN:1757-8981, ISSN:1757-899X

Published
2022
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140. Large Deformation Behavior of High Strength Steel Under Extreme Loading Conditions: High Temperature and High Strain Rate Experiments and Modeling

Author

Li Xueyang, Roth Christian C., and Mohr Dirk

Subjects
Physics, QC1-999
Abstract

Plasticity and fracture experiments are carried out on flat smooth and notched tensile specimens extracted from DP800 steel sheets. A split Hopkinson pressure bar testing system equipped with a load inversion device is utilized to reach high strain rates. Temperature dependent experiments ranging from 20°C to 300°C are performed at quasi-static strain rates. The material exposes a monotonic strain hardening behaviour with a non-monotonic temperature dependency. The rate-independent material behaviour at room-temperature is described with a non-associated Hill’48 plasticity model and an Swift-Voce strain hardening. A machine learning based model is used multiplicatively to capture the rate and temperature responses. A good agreement between measured and simulated force-displacement curves as well as local surface is obtained. The loading paths to fracture are then extracted to facilitate further development of a temperature dependent fracture initiation model.

Published
2018
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142. Efficacy and Safety of Faecal Microbiota Transplantation for Acute Pancreatitis: A Randomised, Controlled Study

Author

Ding, Ling, primary, He, Cong, additional, Li, Xueyang, additional, Huang, Xin, additional, Lei, Yupeng, additional, Ke, Huajing, additional, Chen, Hongyan, additional, Yang, Qinyu, additional, Cai, Yan, additional, Liao, Yuanhang, additional, He, Wenhua, additional, Xia, Liang, additional, Xiong, Huifang, additional, Lu, Nonghua, additional, and Zhu, Yin, additional

Published
2022
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148. Unraveling the Excitonic Transition and Associated Dynamics in Confined Long Linear Carbon Chains with Time‐Resolved Resonance Raman Scattering

Author

Zhu, Jingyi, primary, Bernhardt, Robin, additional, Cui, Weili, additional, German, Raphael, additional, Wagner, Julian, additional, Senkovskiy, Boris V., additional, Grüneis, Alexander, additional, Pichler, Thomas, additional, Li, Yuxuan, additional, Li, Xueyang, additional, Wu, Kaifeng, additional, Liu, Rulin, additional, Zhu, Xi, additional, Van Loosdrecht, Paul H. M., additional, and Shi, Lei, additional

Published
2021
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