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963 results on '"Wu, Huijuan"'

10. Plinabulin plus docetaxel versus docetaxel in patients with non-small-cell lung cancer after disease progression on platinum-based regimen (DUBLIN-3): a phase 3, international, multicentre, single-blind, parallel group, randomised controlled trial

Author

Han, Baohui, Feinstein, Trevor, Shi, Yuankai, Cheng, Gongyan, Yao, Yu, Hu, Chunhong, Shi, Jianhua, Feng, Jifeng, Wu, Huijuan, Cheng, Ying, Guo, Qi-sen, Jie, Zhijun, Ye, Feng, Zhang, Yiping, Liu, Zhihua, Mao, Weidong, Zhang, Liangming, Lu, Junguo, Zhao, Jun, Bazhenova, Lyudmila, Ruiz, Jimmy, Kloecker, Goetz, Kalmadi, R Sujith, Oliff, Ira, Wong, Matthew, Liu, Bin, Wu, Yanping, Huang, Lan, Sun, Yan, Luo, Feng, Zhou, Jian-ying, Pan, Hongming, Wang, Huaqing, Liu, Chunling, Cao, Lejie, Huang, Chao Hui, Thara, Eddie, Li, Xiaoling, Jiang, Da, Mowat, Rex B, Hrom, John S, Nagrial, Adnan, Jain, Vikram, Karim, Nagla A, Shunyakov, Leonid V, Kiberu, Andrew, Jennens, Ross, Lloyd, Ken, Wang, Zhongkun, Du, Lihua, Li, Helen, Chen, Gongyan, Kloecker, Goetz H, Sujith, Kalmadi R, and Oliff, Ira A

Published
2024
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27. Effectiveness of one-week internet-delivered cognitive behavioral therapy for insomnia to prevent progression from acute to chronic insomnia: A two-arm, multi-center, randomized controlled trial

Author

Yang, Lulu, Zhang, Jihui, Luo, Xian, Yang, Yuan, Zhao, Yuhan, Feng, Fei, Liu, Shuai, Zhang, Chenxi, Li, Zhe, Wang, Chao, Wang, Wei, Jiang, Fan, Zhang, Yunshu, Hu, Yuanyuan, Su, Changjun, Wu, Huijuan, Yu, Huan, Li, Shirley Xin, Wing, Yun Kwok, Luo, Ying, and Zhang, Bin

Published
2023
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38. Integration of miRNA-lncRNA-mRNA profiles in liver tissue from EpCAM knockout mice

Author

Lei Zili, Lei Yuting, Chen Guibin, Liu Shaomin, Liu Wanwan, Huang Li, Yang Lanxiang, Wu Huijuan, and Yang Yanhong

Subjects
epithelial cell adhesion molecule (epcam), metabolism-related gene set domain bifurcated 2 (setdb2), mirna-lncrna-mrna regulatory network, mouse liver, Biology (General), QH301-705.5
Abstract

The epithelial cell adhesion molecule (EpCAM) is highly expressed in the liver during development and diseases. However, its role in the development and pathology of liver remains to be explored. The liver tissues of EpCAM-/- and wildtype (WT) mice at P0 stage were used for RNA sequencing. The differently expressed miRNAs, lncRNAs and mRNAs were selected and confirmed by qPCR. The expression of metabolism-related gene SET domain bifurcated 2 (Setdb2) was significantly increased in the liver of EpCAM-/- mice; the triglyceride (TG) and total cholesterol (TC) levels in the liver were also markedly decreased in EpCAM-/- mice. The microRNA (miRNA)-long noncoding RNA (lncRNA)-mRNA regulatory networks indicated that EpCAM may play important roles in glucose and lipid metabolism of the liver during development and in disease. The comprehensive miRNA, lncRNA and mRNA expression profiles in the developing liver of EpCAM-/- mice established here might help to elucidate functions and mechanisms of EpCAM during development and in diseases of the liver.

Published
2022
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46. Multi-Dimensional Information Extraction and Utilization in Smart Fiber-Optic Distributed Acoustic Sensor (sDAS)

Author

Wu, Huijuan, Liu, Xinyu, Wang, Xinlei, Wu, Yongxin, Liu, Yiyu, Wang, Yufeng, and Rao, Yunjiang

Abstract

Current fiber-optic distributed acoustic sensor (DAS) target recognition technologies continue to prioritize updating the feature learning tools while neglecting varying contributions of information from different dimensions. Few works focus on designing recognition algorithms from the perspective of multi-dimensional information extraction and utilization. In this paper, we introduce an end-to-end three-dimensional attention-assisted convolutional neural network (3-D ACNN) into DAS for the first time. This novel approach allows for automatic and concurrent extracttion of three-dimensional input in time, frequency, and space, aiming to cooperatively recognize sensing targets with higher accuracy. Our new scheme also includes comparative examination of 2-D and 3-D attention mechanisms to leverage the most efficient information in various dimensions, thereby enhancing recognition accuracy while maintaining computation efficiency. Field tests demonstrate that the 3-D CNN outperforms commonly used 2-D networks with only time-frequency (T-F), time-space (T-S), or space-frequency (S-F) inputs, improving recognition accuracy from 95.47% to 98.67%. Moreover, the proposed 3-D ACNN can further improve accuracy up to 99.33%, outperforming the basic 3-D CNN. It is also found that T-F information in DAS is richer and more recognized than T-S and S-F information. The use of 3-D attention yields better results than 2-D attention. Additionally, the processing time required for each spatial sensing point is only 0.22 ms on a commercial GPU (NVIDIA GeForce (R) GTX 1080 Ti), which is approximately 1/171 of the time required for the equivalent 2-D network with the same T-F input (38.52 ms). The 3-D ACNN enabled smart fiber-optic DAS (sDAS) represents a significant breakthrough, enabling fast and accurate multi-dimensional collaborative recognition. This advancement is expected to have a substantial impact for distributed sensing applications.

Published
2024
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50. Patterned 3D-graphene for self-powered broadband photodetector.

Author

Wang, Bingkun, Zhang, Jinqiu, Lian, Shanshui, Wu, Huijuan, Liu, Zhiduo, and Wang, Gang

Abstract

The remarkable ultra-wideband energy capabilities of zero-bandgap two-dimensional (2D) graphene have made it an outstanding material for photon absorption and charge carrier generation across a broad spectrum. However, atomically thick 2D-graphene only exhibits a light absorption efficiency of 2.3%, posing a challenge for graphene-based photodetectors to harness photon energy effectively. This study utilized plasma-enhanced chemical vapor deposition technology and a mask to create in situ patterned 3D-graphene/Si-based Schottky heterojunctions. The porous structure and natural nano-resonant cavities of the 3D-graphene enhanced the probability of light absorption, while the curved and sharp edges and corners of the patterned 3D-graphene concentrated the local electromagnetic field and induced localized surface plasmon resonance. Both theoretical and experimental analyses confirmed the improved light absorption mechanisms and charge transfer of photogenerated carriers under the built-in electric field. The photodetector based on the patterned 3D-graphene/Si Schottky structure exhibits excellent broadband response characteristics spanning from 380 to 1550 nm, with responsivity and specific detectivity of 68.47 A/W and 1.43 × 1012 Jones at a wavelength of 1550 nm. Furthermore, the photodetector demonstrated ultrafast microsecond-level response times (116/120 μs rise/fall times) along with exceptional stability and reliability. The potential applications of as-fabricated photodetector include logic devices such as "AND" and "OR" gates and information encryption. This research holds valuable scientific significance for the design of future optoelectronic devices and provides crucial insights and technical support for developing high-performance Si-based graphene detectors. [ABSTRACT FROM AUTHOR]

Published
2024
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