Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Qingjiu Zhang"'
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 2732-2744 (2023)
Low salinity water flooding (LSW) has been proven to be a low-cost and accessible enhanced oil recovery method in conventional reservoirs. However, its applications and potentials in tight reservoirs are mysterious in tight sandstone reservoirs due t
Externí odkaz:
https://doaj.org/article/cc89be5e6fa246c490a4f2e2428c46c3
Autor:
Yang Wu, Qing Hu, Xiaoliang Wang, Hongbo Cheng, Jiegang Yu, Yang Li, Jianing Luo, Qingjiu Zhang, Jianliang Wu, Gengshen Zhang
Publikováno v:
Frontiers in Immunology, Vol 14 (2023)
Microglial activation and subsequent inflammatory responses are critical processes in aggravating secondary brain injury after intracerebral hemorrhage (ICH). Pterostilbene (3’, 5’-dimethoxy-resveratrol) features antioxidant and anti-inflammation
Externí odkaz:
https://doaj.org/article/42a246f630d04e67ad279fd2edfd0bc0
Publikováno v:
Journal of Neurosurgery Case Lessons; Mar2024, Vol. 7 Issue 10, p1-4, 4p
Autor:
Xiang Peng, Qingjiu Zhang, Ruijiang Yu, Hui Yang, Bofeng Liu, Xinfa Li, Zhen Yang, Ting Li, Zhiqiang Han
Publikováno v:
Chemistry and Technology of Fuels and Oils. 58:1027-1034
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fcf052de1b82cc434a09df6d7b9fe269
https://doi.org/10.1007/s10553-023-01485-w
https://doi.org/10.1007/s10553-023-01485-w
Publikováno v:
Volume 3: Fluid-Structure Interaction; High Pressure Technology.
The generation of complex fracture networks by hydraulic fractures activating and connecting natural cleats and fractures during hydraulic fracturing is of great significance to the development of coalbed methane (CBM) reservoirs. Hydraulic fracturin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f6c85a093465faa7cb9feb8dca385c0
https://doi.org/10.1115/pvp2022-84411
https://doi.org/10.1115/pvp2022-84411
Publikováno v:
SpringerPlus
Objectives This study aimed to investigate the alteration of Neuropeptide Y (NPY) in the hypothalamus and its correlation with insulin, leptin and ghrelin during the development of a rat model of type 2 diabetes mellitus. Methods The type 2 diabetes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7c5ce3ceadfe631536fc4dbd14816e7
http://europepmc.org/articles/PMC5095108
http://europepmc.org/articles/PMC5095108
Publikováno v:
Molecular neurobiology. 55(2)
This study aimed to explore the effects of transient receptor potential melastatin 7 (TRPM7)/microRNA-34a (miR-34a) gene silencing on spatial cognitive function and hippocampal neurogenesis in mice with type 1 diabetes mellitus (T1DM). BALB/c mice we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8645ab0439fe5637a34c87d76df5868c
https://pubmed.ncbi.nlm.nih.gov/28185128
https://pubmed.ncbi.nlm.nih.gov/28185128
Publikováno v:
Molecular Medicine Reports. 7:223-228
The aim of this study was to investigate the syste-matic changes in ghrelin and leptin expression, as well as their correlation with insulin resistance (IR) during the development of type 2 diabetes mellitus (T2DM) in a rat model. T2DM was induced in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::750928a99b5157dbceca0d2bcb82e896
https://doi.org/10.3892/mmr.2012.1154
https://doi.org/10.3892/mmr.2012.1154
Autor:
Shiliang Sun, Qingjiu Zhang
Publikováno v:
Neural Processing Letters. 34:229-240
Some recent successful semi-supervised learning methods construct more than one learner from both labeled and unlabeled data for inductive learning. This paper proposes a novel multiple-view multiple-learner (MVML) framework for semi-supervised learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0c069faaf1c7793ee3e85d1fe05a1c1
https://doi.org/10.1007/s11063-011-9195-8
https://doi.org/10.1007/s11063-011-9195-8
Autor:
Qingjiu Zhang, Shiliang Sun
Publikováno v:
Pattern Recognition. 43:3113-3119
Generally, collecting a large quantity of unlabeled examples is feasible, but labeling them all is not. Active learning can reduce the number of labeled examples needed to train a good classifier. Existing active learning algorithms can be roughly di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5798677d845149f8c2de1929683b36d4
https://doi.org/10.1016/j.patcog.2010.04.004
https://doi.org/10.1016/j.patcog.2010.04.004