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2,569 results on '"Zhang Tengfei"'

101. Design and Analysis of Simulation Experiment of Bidding Game for Power Suppliers in Electricity Market Teaching

Author

Wu, Juai, Deng, Shiyang, Zhu, Yuanmeng, Xie, Dongliang, Zhang, Tengfei, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Fox, Bob, editor, Zhao, Chuan, editor, and Anthony, Marcus T., editor

Published
2023
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114. Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

Author

Liu, Qian, Zhang, Jing, Guo, Chenchen, Wang, Mengcheng, Wang, Chenfei, Yan, Yilv, Sun, Liangdong, Wang, Di, Zhang, Lele, Yu, Huansha, Hou, Likun, Wu, Chunyan, Zhu, Yuming, Jiang, Gening, Zhu, Hongwen, Zhou, Yanting, Fang, Shanhua, Zhang, Tengfei, Hu, Liang, Li, Junqiang, Liu, Yansheng, Zhang, Hui, Zhang, Bing, Ding, Li, Robles, Ana I., Rodriguez, Henry, Gao, Daming, Ji, Hongbin, Zhou, Hu, and Zhang, Peng

Published
2024
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119. A Fur-like protein PerR regulates two oxidative stress response related operons dpr and metQIN in Streptococcus suis

Author

Zhang Tengfei, Ding Yi, Li Tingting, Wan Yun, Li Wei, Chen Huanchun, and Zhou Rui

Subjects
Microbiology, QR1-502
Abstract

Abstract Background Metal ions are important micronutrients in cellular metabolism, but excess ions that cause toxic reactive oxygen species are harmful to cells. In bacteria, Fur family proteins such as Fur, Zur and PerR manage the iron and zinc uptake and oxidative stress responses, respectively. The single Fur-like protein (annotated as PerR) in Streptococcus suis has been demonstrated to be involved in zinc and iron uptake in previous studies, but the reports on oxidative stress response and gene regulation are limited. Results In the present study, the perR gene deletion mutant ΔperR was constructed in Streptococcus suis serotype 2 strain SC-19, and the mutant strain ΔperR exhibited less sensitivity to H2O2 stress compared to the wild-type. The dpr and metQIN were found to be upregulated in the ΔperR strain compared with SC-19. Electrophoretic mobility shift assays showed that the promoters of dpr and metQIN could be bound by the PerR protein. These results suggest that dpr and metQIN are members of the PerR regulon of S. suis. dpr encodes a Dps-like peroxide resistance protein, and the dpr knockout strains (Δdpr and ΔdprΔperR) were highly sensitive to H2O2. MetQIN is a methionine transporter, and the increased utilization of methionine in the ΔperR strain indirectly affected the peroxide resistance. Using a promoter–EGFP gene fusion reporting system, we found that the PerR regulon was induced by H2O2, and the induction was modulated by metal ions. Finally, we found that the pathogenicity of the perR mutant was attenuated and easily cleared by mice. Conclusions These data strongly suggest that the Fur-like protein PerR directly regulates dpr and metQIN and plays a crucial role in oxidative stress response in S. suis.

Published
2012
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131. Comparison Network for One-Shot Conditional Object Detection

Author

Zhang, Tengfei, Zhang, Yue, Sun, Xian, Sun, Hao, Yan, Menglong, Yang, Xue, and Fu, Kun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The current advances in object detection depend on large-scale datasets to get good performance. However, there may not always be sufficient samples in many scenarios, which leads to the research on few-shot detection as well as its extreme variation one-shot detection. In this paper, the one-shot detection has been formulated as a conditional probability problem. With this insight, a novel one-shot conditional object detection (OSCD) framework, referred as Comparison Network (ComparisonNet), has been proposed. Specifically, query and target image features are extracted through a Siamese network as mapped metrics of marginal probabilities. A two-stage detector for OSCD is introduced to compare the extracted query and target features with the learnable metric to approach the optimized non-linear conditional probability. Once trained, ComparisonNet can detect objects of both seen and unseen classes without further training, which also has the advantages including class-agnostic, training-free for unseen classes, and without catastrophic forgetting. Experiments show that the proposed approach achieves state-of-the-art performance on the proposed datasets of Fashion-MNIST and PASCAL VOC., Comment: The paper is under revision now. Some problem are not well described. However, this paper has spread out. I think the impact of an imperfect first draft is not good, so we want to withdraw and revise

Published
2019

132. A Training-free, One-shot Detection Framework For Geospatial Objects In Remote Sensing Images

Author

Zhang, Tengfei, Zhang, Yue, Sun, Xian, Yan, Menglong, Wang, Yaoling, and Fu, Kun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning based object detection has achieved great success. However, these supervised learning methods are data-hungry and time-consuming. This restriction makes them unsuitable for limited data and urgent tasks, especially in the applications of remote sensing. Inspired by the ability of humans to quickly learn new visual concepts from very few examples, we propose a training-free, one-shot geospatial object detection framework for remote sensing images. It consists of (1) a feature extractor with remote sensing domain knowledge, (2) a multi-level feature fusion method, (3) a novel similarity metric method, and (4) a 2-stage object detection pipeline. Experiments on sewage treatment plant and airport detections show that proposed method has achieved a certain effect. Our method can serve as a baseline for training-free, one-shot geospatial object detection., Comment: 5 pages 4 figures

Published
2019

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