Zobrazeno 1 - 10
of 197
pro vyhledávání: '"Rong Hua, Li"'
Publikováno v:
Revista de Metalurgia, Vol 59, Iss 3 (2023)
Because the growth behaviors of fatigue cracks are crucial for the safe assessment of structural components, the crack propagation behaviors of coarse-grained copper (CG Cu) subjected to cyclic torsion combined with different axial static stresses we
Externí odkaz:
https://doaj.org/article/9418811c79a8440380d9df4f0a340252
Autor:
Yuan Cai, Zhen Hua Zhu, Rong Hua Li, Xu Yuan Yin, Ru Feng Chen, Li Juan Man, Wen Long Hou, Hong Liang Zhu, Jing Wang, Huiping Zhang, Qiu Fang Jia, Li Hui
Publikováno v:
BMC Psychiatry, Vol 23, Iss 1, Pp 1-8 (2023)
Abstract Background The effect of neuroinflammatory cytokines on cognitive deficits in patients with major depressive disorder (MDD) can be altered by selective serotonin reuptake inhibitors (SSRIs). This study aimed to examine serum interleukin-8 (I
Externí odkaz:
https://doaj.org/article/5a5d881ea0344e99a0203bfaaa0770aa
Autor:
Zhen Hua Zhu, Xiao Ying Song, Li Juan Man, Peng Chen, Zhen Tang, Rong Hua Li, Cai Fang Ji, Ning Bin Dai, Fang Liu, Jing Wang, Jianping Zhang, Qiu Fang Jia, Li Hui
Publikováno v:
Frontiers in Psychiatry, Vol 13 (2022)
ObjectiveThe interleukin-8 (IL-8) has been reported to play an important role in depression, which might be modulated by the selective serotonin reuptake inhibitors (SSRIs). Thus, the aim of this study was to investigate serum IL-8 levels, depressive
Externí odkaz:
https://doaj.org/article/7649376f82b4495491692feda27dbdc1
Publikováno v:
IEEE Transactions on Big Data. 9:37-50
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27b3fa9b64834a0ff0e4b44a29f0a94a
https://doi.org/10.1109/tbdata.2021.3093355
https://doi.org/10.1109/tbdata.2021.3093355
Publikováno v:
Data Science and Engineering, Vol 3, Iss 2, Pp 136-149 (2018)
Abstract Discovering dense subgraphs in a graph is a fundamental graph mining task, which has a wide range of applications in social networks, biology and visualization to name a few. Even the problem of computing most cohesive subgraphs is NP-hard (
Externí odkaz:
https://doaj.org/article/b2bbd25dd2d146c3b88c62afcfdf9ab0
Autor:
Guoren Wang, Yue Zeng, Rong-Hua Li, Hongchao Qin, Xuanhua Shi, Yubin Xia, Xuequn Shang, Liang Hong
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cb90e456ac9451743be0d09ae42c5ef
https://doi.org/10.1109/tkde.2023.3270460
https://doi.org/10.1109/tkde.2023.3270460
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe88dc120d9138d595d8878b5dba6518
https://doi.org/10.1109/tkde.2022.3233788
https://doi.org/10.1109/tkde.2022.3233788
Publikováno v:
Proceedings of the VLDB Endowment. 16:343-355
Consider an edge-weighted graph, and a number of properties of interests (PoIs). Each vertex has a probability of exhibiting each PoI. The joint probability that a set of vertices exhibits a PoI is the probability that this set contains at least one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::925c12cfa80bedd69f3b759aaa5034ea
https://doi.org/10.14778/3565816.3565834
https://doi.org/10.14778/3565816.3565834
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4313-4327
Community search that finds query-dependent communities has been studied on various kinds of graphs. As one instance of community search, intimate-core group (community) search over a weighted graph is to find a connected k-core containing all query
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::522c8a61a83c5ed9679aab3c7483df5d
https://doi.org/10.1109/tkde.2020.3040762
https://doi.org/10.1109/tkde.2020.3040762
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:3927-3945
Mining periodic communities are essential to understanding periodic group behaviors in temporal networks. Unfortunately, most previous studies for community mining in temporal networks ignore the periodic patterns of communities. In this paper, we st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43fec5eef501a8959c9f881ee066ec57
https://doi.org/10.1109/tkde.2020.3028025
https://doi.org/10.1109/tkde.2020.3028025