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868 results on '"Kang, Zhuang"'

20. Application of an Improved GPU Acceleration Strategy for the Smoothed Particle Hydrodynamics Method

Author

GUAN Yanmin, YANG Caihong, KANG Zhuang, ZHOU Li

Subjects
smoothed particle hydrodynamics (sph), parallel computing, dam breaking, computational efficiency, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

In order to solve the problem of graphics processing unit (GPU) memory access conflicts possibly caused by the disorder of particles and enhance the computation efficiency, an improved GPU acceleration strategy is proposed by establishing particle reorder technology. The acceleration strategy is applied to the smoothed particle hydrodynamics (SPH) method to simulate the dam breaking with obstacles in three dimensions, and the algorithm is verified by comparing with the experimental results, which obtained a high calculation accuracy. Based on this benchmark example of the SPH, the studies on the effect of particle renumbering and the solution efficiency of the algorithm are conducted by comparing the simulations of different hardware facilities. The results indicate that the particle reorder technology can ensure a stable single-step running time, and can effectively solve the problem of graphic card memory access conflicts that commonly exist in the GPU-SPH algorithm. Furthermore, the GPU parallel algorithm can greatly improve the solution efficiency of the SPH method, and with the increase of particle number, the advantage of drastically reducing the computation time becomes more obvious. The method proposed in this paper provides the possibility to expand the application of the SPH method to solve 3D numerical simulations.

Published
2023
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26. Preclinical and early clinical studies of a novel compound SYHA1813 that efficiently crosses the blood–brain barrier and exhibits potent activity against glioblastoma

Author

Liu, Yingqiang, Zhan, Zhengsheng, Kang, Zhuang, Li, Mengyuan, Lv, Yongcong, Li, Shenglan, Tong, Linjiang, Feng, Fang, Li, Yan, Zhang, Mengge, Xue, Yaping, Chen, Yi, Zhang, Tao, Song, Peiran, Su, Yi, Shen, Yanyan, Sun, Yiming, Yang, Xinying, Yao, Shanyan, Yang, Hanyu, Wang, Caixia, Geng, Meiyu, Li, Wenbin, Duan, Wenhu, Xie, Hua, and Ding, Jian

Published
2023
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35. Offshore Vessel

Author

Kang, Zhuang, Ni, Wen-Chi, Zhang, A-Man, Section editor, Cui, Weicheng, editor, Fu, Shixiao, editor, and Hu, Zhiqiang, editor

Published
2022
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36. Pedestrian Detection Algorithm Based on Improved YOLOv3_tiny

Author

Li, Guilan, Yang, Jie, Kang, Zhuang, 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, 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, and Deng, Zhidong, editor

Published
2022
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48. Screening recurrent glioblastoma-related genes and analyzing their gene expressions in association with clinicopathological parameters and prognosis

Author

LIN Yi, WANG Ce, KANG Xun, KANG Zhuang, CHEN Feng, JIANG Bo, LI Wenbin

Subjects
glioma, bioinformatics, survival, recurrence, histidine metabolism, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Background and purpose: Glioma is the most common and malignant primary brain tumor in the central nervous system (CNS). Glioblastoma is highly malignant and aggressive, and the prognosis of patients with recurrent glioblastoma is very poor. This study aimed to screen the genes related to the recurrent glioblastoma, and analyze the relationship between their expressions, clinicopathological parameters and prognosis in glioma. Methods: By mining the relevant datasets of the primary and recurrent cases of glioblastoma in the GEO database, the differentially expressed gene (DEG) in the samples of primary and recurrent glioblastomas were screened and analyzed. All DEGs analyses were carried out in ontology function and pathway enrichment. Protein-protein interaction (PPI) network was constructed and used for screening Hub gene. Key genes were intersected by PPI network and Venn diagram, and the Gene Expression Profiling Interactive Analysis (GEPIA) and Chinese Glioma Genome Atlas (CGGA) database were analyzed for association of key gene expressions and survival status. Key genes were furtherly analyzed to determine the relationship between their expressions and clinicopathological parameters of glioma. Results: There were 40 DEG screened in the dataset GSE62153, including 34 up-regulated genes and 6 down-regulated genes. There were 19 DEG screened in the dataset GSE58399, including 16 up-regulated genes and 3 down-regulated genes. Go functional analyses showed that the DEG of GSE62153 were mainly involved in 11 physiological processes, such as central nervous system development, myelin sheath, actin binding, central nervous system myelination. The DEG of GSE58399 were mainly enriched in the positive regulation of epithelial cell migration. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment showed that the datasets GSE62153 and GSE58399 were both enriched in histidine metabolism. By using the STRING database, the core of PPI network was constructed with 20 protein molecules. A total of 10 hub genes were screened, including MOBP, OPALIN, ERMN, PLP1, MOG, CLDN11, ASPA, TMEM125, KLK6 and NKX6-2 gene. The key genes for recurrent glioblastoma were ERMN, MOG and MOBP gene. Based on analyses using The Cancer Genome Atlas (TCGA) and CGGA databases, the prognosis of patients with high expressions of ERMN, MOG and MOBP was favorable compared with the low expression group. The expression levels of key genes in glioblastoma were lower compared with the control tissues (P

Published
2022
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