H
Hong Zhang
Researcher at Chinese Academy of Sciences
Publications - 482
Citations - 15856
Hong Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Synthetic aperture radar & Autophagy. The author has an hindex of 52, co-authored 384 publications receiving 11989 citations. Previous affiliations of Hong Zhang include Indiana University – Purdue University Indianapolis & ShanghaiTech University.
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Dietary S. maltophilia promotes fat storage by enhancing lipogenesis and ER-LD contacts in C. elegans
TL;DR: It is demonstrated that feeding Caenorhabditis elegans with the opportunistic pathogenic bacteria Stenotrophomonas maltophilia retards growth and promotes excessive fat storage, and delineates a new model for understanding microbial regulation of metazoan physiology.
Journal ArticleDOI
Automatic Monitoring Method for Surface Deformation of Coastal Area Based on Time Series Analysis
TL;DR: Liu et al. as mentioned in this paper proposed an automatic monitoring method of surface deforma tion in coastal areas based on time series analysis, and the distributed information reconstruction of surface deformation in coastal area is carried out by using phase space reconstruction and correlation coefficient mining methods.
Genomes & Developmental Control Transcription factor NFY globally represses the expression of the C. elegans Hox gene Abdominal-B homolog egl-5
Hansong Deng,Yinyan Sun,Yuxia Zhang,Xin Luo,Wenru Hou,Libo Yan,Yaoyao Chen,E Tian,Jinghua Han,Hong Zhang +9 more
TL;DR: In this article, the authors identify and clone the corresponding C. elegans orthologs of the components of the heterotrimeric transcription factor NFY, nfya-1, nfyb-1 and nfyc-1.
Proceedings ArticleDOI
SAR tomography via sparse representation of multiple snapshots and backscattering signals — The L1-SVD approach
TL;DR: This paper makes use of the truncation version of multiple snapshots of compressive sensing (MCS), called L1-SVD, for retrieving information in the urban area of TomoSAR, and achieves sparsity of the stadium using Radarsat-2 images of a stadium.
Journal ArticleDOI
Inversion of seismic source parameters from satellite InSAR data based on deep learning
TL;DR: Zhang et al. as mentioned in this paper proposed a deep learning approach of earthquake source parameters inversion using ResNet (abbreviated as ESPI-ResNet) from satellite InSAR data.