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Institution

Ocean University of China

EducationQingdao, China
About: Ocean University of China is a education organization based out in Qingdao, China. It is known for research contribution in the topics: Population & Sea surface temperature. The organization has 27604 authors who have published 27886 publications receiving 440181 citations. The organization is also known as: Zhōngguó Hǎiyáng Dàxué & OUC.


Papers
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Journal ArticleDOI
Baowei Su1, Tingting Wang1, Zongwen Wang1, Xueli Gao1, Congjie Gao1 
TL;DR: In this paper, a dynamic layer-by-layer (LBL) self-assembly was used to prepare as few as three to five bilayers of poly(diallyl-dimethylammonium chloride) (PDADMAC) and poly(styrene sulfonate) (PSS) on negatively charged polysulfone (PS) ultrafiltration (UF) membranes of 50kDa MWCO and compared with those of the static assembly membranes.

114 citations

Journal ArticleDOI
Andi Zhang1, Ya Liu1, Di Qin1, Mengjie Sun1, Ting Wang1, Xiguang Chen1 
TL;DR: The polymers suitable for hydrogel forming, and the appropriate molecular design of thehydrogel network for achieving self-healing properties are discussed, followed by the applications of self- healing hydrogels as wound dressing.

114 citations

Journal ArticleDOI
TL;DR: In this article, the merging of satellite infrared and microwave SST data is investigated, and the results demonstrate the practicality and advantages of merging SST measurements from various satellite sensors, such as GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared Spin Scan Radiometer), TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI) and VIRS (Visible and infrared Scanner).
Abstract: The Global Ocean Data Assimilation Experiment (GODAE) requires the availability of a global analyzed SST field with high-resolution in space (at least 10 km) and time (at least 24 hours). The new generation SST products would be based on the merging of SSTs from various satellites data and in situ measurements. The merging of satellite infrared and microwave SST data is investigated in this paper. After pre-processing of the individual satellite data, objective analysis was applied to merge the SST data from NOAA AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared Spin Scan Radiometer), TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI) and VIRS (Visible and Infrared Scanner). The 0.05° daily cloud-free SST products were generated in three regions, viz., the Kuroshio region, the Asia-Pacific Region and the Pacific, during one-year period of October 1999 to September 2000. Comparisons of the merged SSTs with Japan Meteorological Agency (JMA) buoy SSTs show that, with considerable error sources from individual satellite data and merging procedure, an accuracy of 0.95 K is achieved. The results demonstrate the practicality and advantages of merging SST measurements from various satellite sensors.

114 citations

Journal ArticleDOI
01 Apr 2019-Energy
TL;DR: In this article, the causalities between oil and agricultural commodity prices were explored to examine whether the vertical market integration model holds for global market. But the long-run nexus using full-sample data is found to be unstable, suggesting the causality test is not reliable.

114 citations

Journal ArticleDOI
TL;DR: Eighteen hybridomas secreting monoclonal antibodies against Japanese flounder Ig were obtained by immunisation of Balb/C mice with purified Ig preparations, which were selected on the basis of the double indirect enzyme-linked immunosorbent assay (D-ELISA), and two of them designated as 2D8 and 2H1 were cloned by limiting dilution and characterised with western blotting.

114 citations


Authors

Showing all 27836 results

NameH-indexPapersCitations
Guangming Zeng1461676100743
Bin Wang126222674364
Simon A. Wilde11839045547
Yusuke Yamauchi117100051685
Xiaoming Li113193272445
Baoshan Xing10982348944
Peng Wang108167254529
Jun Yang107209055257
Shang-Ping Xie10544136437
M. Santosh103134449846
Qi Li102156346762
Wei Liu102292765228
Tao Wang97272055280
Wei Wang95354459660
Peng Li95154845198
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023103
2022515
20213,161
20202,814
20192,480
20182,068