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492 results on '"Wang, Zhenyan"'

1. Rapid detection of phosphine resistance in the lesser grain borer, Rhyzopertha dominica (Coleoptera: Bostrychidae) from China using ARMS-PCR

Author

Lu, Yujie, Zhang, Chenguang, Wang, Zhenyan, Yan, Xiaoping, and Emery, Robert N.

Subjects
phosphine resistance, lesser grain borer, taqman@ probe, arms-pcr, dihydrolipoamide dehydrogenase, Agriculture, Botany, QK1-989
Abstract

The lesser grain borer, Rhyzopertha dominica is one of the serious cosmopolitan stored grain pests worldwide. High phosphine resistant R. dominica has been reported in several countries. The evolution of strong phosphine resistance is a major challenge for continuous application of the fumigant. Rapid detection of phosphine resistance level is a prime key to implement an appropriate strategy for control the stored-product pests. Dihydrolipoamide dehydrogenase (DLD) is a key metabolic enzyme mediating the phosphine resistance in population of R. dominica, Tribolium castaneum and Caenorhabditis elegans. Analysis of the DLD sequences deposited in GenBank revealed that the P45/49S mutation was the most common one in many PH3-resistant stored-product pest insects. This information now enables direct detection of resistance using molecular diagnosis in field populations. We herein propose a method for rapid detection of phosphine resistance in R. dominica according to P49S point mutation of the DLD gene. Our data provides evidence that the ARMS-PCR method can be used for early warning of phosphine resistance in R. dominica in field conditions.

Published
2018
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13. A Dual Model Control of Sensorless High Frequency Permanent Magnet Synchronous Motor Based on the Space Vector Pulse Width Modulation and Six-Step Mode

Author

He, Yanzhao, Wang, Zhenyan, Wang, Quanwu, Bu, Qingrui, Dai, Jufeng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Sun, Jiande, editor, Wang, Yue, editor, Huo, Mengyao, editor, and Xu, Lexi, editor

Published
2023
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41. Enhanced Hybrid Vision Transformer with Multi-Scale Feature Integration and Patch Dropping for Facial Expression Recognition.

Author

Li, Nianfeng, Huang, Yongyuan, Wang, Zhenyan, Fan, Ziyao, Li, Xinyuan, and Xiao, Zhiguo

Abstract

Convolutional neural networks (CNNs) have made significant progress in the field of facial expression recognition (FER). However, due to challenges such as occlusion, lighting variations, and changes in head pose, facial expression recognition in real-world environments remains highly challenging. At the same time, methods solely based on CNN heavily rely on local spatial features, lack global information, and struggle to balance the relationship between computational complexity and recognition accuracy. Consequently, the CNN-based models still fall short in their ability to address FER adequately. To address these issues, we propose a lightweight facial expression recognition method based on a hybrid vision transformer. This method captures multi-scale facial features through an improved attention module, achieving richer feature integration, enhancing the network's perception of key facial expression regions, and improving feature extraction capabilities. Additionally, to further enhance the model's performance, we have designed the patch dropping (PD) module. This module aims to emulate the attention allocation mechanism of the human visual system for local features, guiding the network to focus on the most discriminative features, reducing the influence of irrelevant features, and intuitively lowering computational costs. Extensive experiments demonstrate that our approach significantly outperforms other methods, achieving an accuracy of 86.51% on RAF-DB and nearly 70% on FER2013, with a model size of only 3.64 MB. These results demonstrate that our method provides a new perspective for the field of facial expression recognition. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Survival and prognostic factors of progressive multifocal leukoencephalopathy in people living with HIV in modern ART era

Author

Jiang, Rui, primary, Song, Zichen, additional, Liu, Li, additional, Mei, Xue, additional, Sun, Jianjun, additional, Qi, Tangkai, additional, Wang, Zhenyan, additional, Song, Wei, additional, Tang, Yang, additional, Yang, Junyang, additional, Xu, Shuibao, additional, Zhao, Bihe, additional, Shen, Yinzhong, additional, Zhang, Renfang, additional, and Chen, Jun, additional

Published
2023
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49. Antiretroviral therapy-naïve people living with HIV tend to have more severe symptoms of COVID-19

Author

Sun, Jinfeng, primary, Jiang, Rui, additional, Shao, Yueming, additional, Hu, Jingjing, additional, Zheng, Zhihang, additional, Wu, Luling, additional, Liu, Li, additional, Yang, Junyang, additional, Shen, Yinzhong, additional, Zhang, Renfang, additional, Qi, Tangkai, additional, Sun, Jianjun, additional, Wang, Zhenyan, additional, Tang, Yang, additional, Song, Wei, additional, Xu, Shuibao, additional, Zhao, Bihe, additional, and Chen, Jun, additional

Published
2023
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50. HIV-1 DNA levels in peripheral blood mononuclear cells of patients with HIV-related non-Hodgkin's lymphoma

Author

Wang, Zhenyan, primary, Xun, Jingna, additional, Song, Zichen, additional, Shen, Yinzhong, additional, Liu, Li, additional, Chen, Jun, additional, Qi, Tangkai, additional, Sun, Jianjun, additional, Song, Wei, additional, Tang, Yang, additional, Xu, Shuibao, additional, Yang, Junyang, additional, Zhao, Bihe, additional, and Zhang, Renfang, additional

Published
2023
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