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336 results on '"Zhu, Liwen"'

53. Multi-objective Ant Colony Optimization Algorithm Based on Load Balance

Author

Zhu, Liwen, Tang, Ruichun, Tao, Ye, Ren, Meiling, Xue, Lulu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Xingming, editor, Liu, Alex, editor, Chao, Han-Chieh, editor, and Bertino, Elisa, editor

Published
2016
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60. SAR Imaging Modulation Based on Time-Modulated Corner Reflector With Wide-Angle Domain Control

Author

Sun, Guang, Zhu, Liwen, Xing, Shiqi, Wang, Junjie, Feng, Dejun, and Wang, Xuesong

Abstract

Time-modulated metasurfaces (TMMs) can dynamically control the electromagnetic (EM) wave in real-time, holding extraordinary potentials in the radar imaging modulation. However, achieving monostatic radar cross section (RCS) control in a wide-angle domain for traditional planar TMM poses considerably challenging. In this letter, a time-modulated corner reflector (TMCR) with periodic modulation based on the TMM is proposed to manipulate the spectrum distribution for countering synthetic aperture radar (SAR) imaging. The TMCR can flexibly control incident EM waves in real time, with excellent wide-angle domain stability and polarization insensitivity. The amplitude of the echo signal is dynamically controlled by applying periodic encoded waveforms to generate a discrete Doppler spectrum. Based on this, multiple discrete false targets around the actual target appear in SAR imaging. The simulation and experimental results demonstrate that the proposed TMCR has excellent EM modulation capability in the azimuth range of 0°–75° and pitch range of 0°–45°, enabling the monostatic RCS modulation in a wide-angle domain. Moreover, it can generate multiple false targets in the range direction of the radar, illustrating the validity of the proposed structural design.

Published
2023
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72. Cuproptosis‐Driven Enhancement of Thermotherapy by Sequentially Response Cu2‐xSe via Copper Chemical Transition.

Author

Chan, Leung, Liu, Yongkang, Chen, Muhe, Su, Yanhong, Guo, Junxian, Zhu, Liwen, Zhan, Meixiao, Chen, Tianfeng, and Lu, Ligong

Subjects
THERMOTHERAPY, MALEIC anhydride, REACTIVE oxygen species, TUMOR treatment, TRICARBOXYLIC acids, SEMIMETALS, COPPER
Abstract

Activation of cuproptosis pathway has been reported to hold great potential in the application of tumor treatment. But the efficacy of cuproptosis seriously limited by the insufficient accumulation in the tumor sites. Therefore, herein based on the strong stabilization effects of the metalloid element selenium (Se) on copper (Cu), a photothermic Cu2‐xSe nanoparticle encapsulated with bioresponsive dimethyl maleic anhydride (DMMA@Cu2‐xSe) as a copper‐carrier to improve the copper accumulation in tumor is constructed, thus achieving cuproptosis‐driven enhancement of thermotherapy. This nanosystem exhibits the enhancement of tumor cellular uptake by a weak acid‐triggered charge‐switching ability. Next step, the exposed Cu2‐xSe is oxidized and releases divalent copper by high‐level oxide. Then, the abundant copper induces more dihydrolipoamide S‐acetyltransferase oligomerization to down‐regulate FDX1 and tricarboxylic acid cycle‐related proteins, which leads to inhibiting aerobic respiration. Cuproptosis‐induced mitochondrial damage further improves thermotherapy by up‐regulating reactive oxygen species (ROS). In addition, the generated ROS also promotes copper release to strengthen cuproptosis, and eventually improves tumor thermotherapy in turn. In general, DMMA@Cu2‐xSe with sequentially triggered copper‐release, efficient cuproptosis, and appropriate photothermal is a self‐enhanced nanoplatform for cuproptosis‐driven enhancement of thermotherapy. [ABSTRACT FROM AUTHOR]

Published
2023
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77. Thickness-dependent flexoresistance in SrTiO3 thin films.

Author

Zhu, Liwen, Liang, Renhong, Ye, Mao, Shu, Longlong, Zheng, Renkui, and Ke, Shanming

Subjects
*THIN films, *STRAINS & stresses (Mechanics), *ATOMIC force microscopes, *THICK films, *SURFACE morphology, *RECEIVER operating characteristic curves, *FLEXOELECTRICITY
Abstract

We report a thickness-dependent flexoresistance effect caused by strain gradient in SrTiO3 (STO) epitaxial thin films. The strain gradient in STO was induced by using an atomic force microscope diamond-coated tip. The depolarization field caused by the strain gradient changes the electrical state of the film, resulting in a decrease in the resistance of the films by 4–6 orders of magnitude. By testing the current–voltage (I–V) curves of STO films with different thicknesses, it is found that the flexoresistance behavior of STO films is obvious thickness dependent: the thicker the film, the higher the force threshold to trigger the film to enter a highly conductive state. The comparison of the surface morphology before and after the I–V test with loading shows that only when the thickness of the STO film is below 8 nm, the film can enter the conductive state from the insulating state without damaging the surface. During the electrical state switching process, the strain gradient caused by tip loading play an important role in the modification of the film barrier. [ABSTRACT FROM AUTHOR]

Published
2023
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84. Variationally and Intrinsically motivated reinforcement learning for decentralized traffic signal control

Author

Zhu, Liwen, Peng, Peixi, Lu, Zongqing, Wang, Xiangqian, and Tian, Yonghong

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems, Machine Learning (cs.LG), Multiagent Systems (cs.MA)
Abstract

One of the biggest challenges in multi-agent reinforcement learning is coordination, a typical application scenario of this is traffic signal control. Recently, it has attracted a rising number of researchers and has become a hot research field with great practical significance. In this paper, we propose a novel method called MetaVRS~(Meta Variational RewardShaping) for traffic signal coordination control. By heuristically applying the intrinsic reward to the environmental reward, MetaVRS can wisely capture the agent-to-agent interplay. Besides, latent variables generated by VAE are brought into policy for automatically tradeoff between exploration and exploitation to optimize the policy. In addition, meta learning was used in decoder for faster adaptation and better approximation. Empirically, we demonstate that MetaVRS substantially outperforms existing methods and shows superior adaptability, which predictably has a far-reaching significance to the multi-agent traffic signal coordination control.

Published
2021
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87. Identification of a Long Noncoding RNA TRAF3IP2-AS1 as Key Regulator of IL-17 Signaling through the SRSF10–IRF1–Act1 Axis in Autoimmune Diseases

Author

He, Ruirui, primary, Wu, Songfang, additional, Gao, Ru, additional, Chen, Jianwen, additional, Peng, Qianwen, additional, Hu, Huijun, additional, Zhu, Liwen, additional, Du, Yanyun, additional, Sun, Wanwei, additional, Ma, Xiaojian, additional, Zhang, Huazhi, additional, Cui, Zhihui, additional, Wang, Heping, additional, Martin, Bradley N., additional, Wang, Yueying, additional, Zhang, Cun-jin, additional, and Wang, Chenhui, additional

Published
2021
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99. IL-37 Represses the Autoimmunity in Myasthenia Gravis via Directly Targeting Follicular Th and B Cells

Author

Liu, Zhuo, primary, Zhu, Liwen, additional, Lu, Zhengjuan, additional, Chen, Huiping, additional, Fan, Lizhen, additional, Xue, Qun, additional, Shi, Jianquan, additional, Li, Meiying, additional, Li, Hui, additional, Gong, Jie, additional, Shi, Jingping, additional, Wang, Tao, additional, Jiang, Mei-Ling, additional, Cao, Runjing, additional, Meng, Hailan, additional, Wang, Chenhui, additional, Xu, Yun, additional, and Zhang, Cun-Jin, additional

Published
2020
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