Institution
Zhejiang Gongshang University
Education•Hangzhou, China•
About: Zhejiang Gongshang University is a education organization based out in Hangzhou, China. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 8258 authors who have published 7670 publications receiving 90296 citations. The organization is also known as: Zhèjiāng Gōngshāng Dàxué.
Topics: Computer science, Chemistry, Adsorption, Catalysis, China
Papers published on a yearly basis
Papers
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TL;DR: The emergency resource allocation problem with constraints of multiple resources and possible secondary disasters is formulated, and a heuristic algorithm is designed to efficiently solve it based on linear programming and network optimization.
Abstract: Optimal allocation of emergency resources is a crucial content of emergency management. It is a key step in emergency rescue and assistance. Multiple resources and potential secondary disasters are often neglected in the existing methods, which desperately need to be improved. In this paper, we formulate the emergency resource allocation problem with constraints of multiple resources and possible secondary disasters, and model the multiple resources and multiple emergency response depots problem considering multiple secondary disasters by an integer mathematical programming. For the complexity, a heuristic algorithm is designed to efficiently solve it based on linear programming and network optimization. The algorithm modifies the solutions of the linear programming by setting a priority of preference for each location where the secondary disasters will take place with certain possibilities. The numerical simulation provides evidence for its effectiveness and efficiency. Our method and algorithm can also be implemented in the practical applications with large-scale scenario.
133 citations
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TL;DR: The aggregation of the different parts of MULTIMOORA which makes the technique more operational, especially in case of large-scale applications, and compared to those obtained by employing TOPSIS and VIKOR methods.
131 citations
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TL;DR: An ionic liquid-based ultrasonic-assisted extraction (ILUAE) method has been developed for the effective extraction of piperine from white pepper powder and indicates that both the characteristics of anions and cations have remarkable effects on the extraction efficiency.
131 citations
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TL;DR: Wang et al. as discussed by the authors presented a national assessment of the vulnerability of the Chinese coast using 8 physical variables: sea-level rise, coastal geomorphology, elevation, slope, shoreline erosion, land use, mean tide range, and mean wave height.
Abstract: Sea-level rise as a result of climate change increases inundation and erosion, which are affected by a complex interplay of physical environmental parameters at the coast. China’s coast is vulnerable to accelerated sea-level rise and associated coastal flooding because of physical and socio-economical factors such as its low topography, highly developed economy, and highly dense population. To identify vulnerable sections of the coast, this paper presents a national assessment of the vulnerability of the Chinese coast using 8 physical variables: sea-level rise, coastal geomorphology, elevation, slope, shoreline erosion, land use, mean tide range, and mean wave height. A coastal vulnerability index was calculated by integrating the differentially weighted rank values of the 8 variables, based on which the coastline is segmented into 4 classes. The results show that 3% of the 18,000-km-long Chinese coast is very highly vulnerable, 29% is highly vulnerable, 58% is moderately vulnerable, and 10% is in the low-vulnerable class. Findings further reveal that large amounts of land and population will be vulnerable to inundation by coastal flooding from sea level rise and storm surge. Finally, some suggestions are presented for decision makers and other concerned stakeholders to develop appropriate coastal zone management and mitigation measures.
131 citations
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TL;DR: The effect of prebiotic xylooligosaccharides on the growth performance and digestive enzyme activities of the allogynogenetic crucian carp, Carassius auratus gibelio, was investigated and the survival rate was not affected by the dietary treatments.
Abstract: The effect of prebiotic xylooligosaccharides (XOS) on the growth performance and digestive enzyme activities of the allogynogenetic crucian carp, Carassius auratus gibelio, was investigated. XOS was added to fish basal semi-purified diets at three concentrations by dry feed weight: diet 1, 50 mg kg−1; diet 2, 100 mg kg−1; diet 3, 200 mg kg−1, respectively. Twelve aquaria (n = 20) with three replicates for each treatment group (diets 1–3) and control treated without XOS were used. Weights of all collected carp from each aquarium were determined at the initial phase and at the end of the experiment, and the carp survival was also determined by counting the individuals in each aquarium. After 45 days, there were significant differences (P 0.05) by the dietary treatments. For enzymatic analysis, dissection produced a crude mixture of intestine and hepatopancreas of each segment to measure. The protease activity in the intestine and hepatopancreas content of fish in diet 2 (487.37 ± 20.58 U g−1 and 20.52 ± 1.93 U g−1) were significantly different (P < 0.05) from that in the control (428.13 ± 23.26 U g−1 and 12.81 ± 1.52 U g−1) and diet 3 (428.00 ± 23.78 U g−1 and 14.04 ± 1.59 U g−1). Amylase activity in the intestine was significantly higher for diet 2 compared to diet 1 and the control. As for amylase in the hepatopancreas, assays showed higher activity in diet 2 (P < 0.05) compared to the rest.
130 citations
Authors
Showing all 8318 results
Name | H-index | Papers | Citations |
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David Julian McClements | 131 | 1137 | 71123 |
Sajal K. Das | 85 | 1124 | 29785 |
Ye Wang | 85 | 466 | 24052 |
Xun Wang | 84 | 606 | 32187 |
Tao Jiang | 82 | 940 | 27018 |
Yueming Jiang | 79 | 452 | 20563 |
Mo Wang | 61 | 274 | 13664 |
Robert J. Linhardt | 58 | 1190 | 53368 |
Jiankun Hu | 57 | 493 | 11430 |
Xuming Zhang | 56 | 384 | 10788 |
Yuan Li | 50 | 352 | 8771 |
Chunping Yang | 49 | 173 | 8604 |
Duo Li | 48 | 329 | 9060 |
Matthew Campbell | 48 | 236 | 13448 |
Aiqian Ye | 48 | 163 | 6120 |