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Synonyms:
   Xirichthys dea 
   Xyrichtys dea (Apuron) 

Broader Terms:
   Perciformes (perch-likes) 
   Xirichthys 
   Xyrichtys 
 
 


External Resources:

Did you mean: Xyrichthys dea or Xyrichtys dea?

Common Names: Isdang bato, 红姑娘仔, Danlugan, Tamago, 红新娘, Maming, Apuron, Balaki, Mulmul, Maringyan, Molmol, Pirat-pirat, Verde verde, Lubay-lubay, Bungat, Banog, Bankilan, Lubay, Pilo-pilo, Lampalampa, Tausay, Tensu, Lupet, Labayan, Puron ....



1.  Efficiency evaluation of Brazilian airlines operations considering the Covid-19 outbreak.LinkIT
Pereira DDS, Soares de Mello JCCB
Journal of air transport management, 2021
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

2.  Influence of Cd on atrazine degradation and the formation of three primary metabolites in water under the combined pollution.LinkIT
Xie D, Chen C, Li C, Wang Q
Environmental science and pollution research international, 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

3.  Equity and efficiency of health care resource allocation in Jiangsu Province, China.LinkIT
Li Q, Wei J, Jiang F, Zhou G, Jiang R, Chen M, Zhang X, Hu W
International journal for equity in health, 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

4.  Correction to: Inhaled nitric oxide in patients admitted to intensive care unit with COVID-19 pneumonia.LinkIT
Tavazzi G, Pozzi M, Mongodi S, Dammassa V, Romito G, Mojoli F
Critical care (London, England), 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

5.  Chinese construction industry energy efficiency analysis with undesirable carbon emissions and construction waste outputs.LinkIT
Liang X, Lin S, Bi X, Lu E, Li Z
Environmental science and pollution research international, 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

6.  China's Provincial Eco-Efficiency and Its Driving Factors-Based on Network DEA and PLS-SEM Method. E8702 10.3390/ijerph17228702 This study aims to estimate the eco-efficiencies of China at provincial levels. The eco-efficiencies of production and treatment stages are disentangled by the network data envelopment analysis (DEA) method. The key driving factors are identified by the integrative use of driving force-pressure-state-impact-response frame model (DPSIR) model and partial least squares structural equation modeling (PLS-SEM) method. This study provides several important findings. In general, the eco-efficiencies of most regions in China are inefficient and show significant regional differences. All DPSIR factors have significant and strong impacts on the eco-efficiency of the treatment stage. The eco-efficiency of the production stage evidently outweighs the eco-efficiency in economically well-developed regions. The originality of this study lies in three aspects. First, using two-stage network DEA, this study dissects the overall eco-efficiency into production efficiency and treatment efficiency. Empirical results provide insights into the root cause of the low efficiency of each province (municipality). Second, on the basis of the DPSIR model, an expanded pool of driving factors is investigated. Third, using the PLS-SEM method to analyze eco-efficiency is more reliable and effective than applying other traditional regression models. Li Zhijun Z School of Economics and Management, Xidian University, Xi'an 710126, China. Wei Yigang Y School of Economics and Management, Beihang University, Beijing 100191, China. Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China. Li Yan Y Business School, Shandong University, Weihai 264209, China. Wang Zhicheng Z 0000-0001-7516-0728 Business School, Shandong University, Weihai 264209, China. Zhang Jinming J School of Political Studies, Nanjing Agricultural University, Nanjing 210095, China. eng 18YJC840041 the MOE (Ministry of Education in China) Project of Humanities and Social Sciences 71904009 National Natural Science Foundation of China 2019M652415 the Postdoctoral Science Foundation of China Journal Article 2020 11 23 Switzerland Int J Environ Res Public Health 101238455 1660-4601 IM DPSIR model PLS-SEM eco-efficiency environmental treatment network DEA 2020 09 16 2020 11 13 2020 11 16 2020 11 26 1 1 2020 11 27 6 0 2020 11 27 6 0 epublish 33238577 ijerph17228702 10.3390/ijerph17228702 33231983 NBK564313 StatPearls Publishing Treasure Island (FL) StatPearls 2020 01 2020 01 Internet New Mexico Medical Practice Act Review and UnderstandingLinkIT
Li Z, Wei Y, Li Y, Wang Z, Zhang J, , Mukkamalla SKR, Crookston KP
International journal of environmental research and public health, 2020 Nov 23 International journal of environmental research and public health Int J Environ Res Public Health China's Provincial Eco-Efficiency and Its Driving Factors-Based on Network DEA and PLS-SEM Method. E8702 10.3390/ijerph17228702 This study aims to estimate the eco-efficiencies of China at provincial levels. The eco-efficiencies of production and treatment stages are disentangled by the network data envelopment analysis (DEA) method. The key driving factors are identified by the integrative use of driving force-pressure-state-impact-response frame model (DPSIR) model and partial least squares structural equation modeling (PLS-SEM) method. This study provides several important findings. In general, the eco-efficiencies of most regions in China are inefficient and show significant regional differences. All DPSIR factors have significant and strong impacts on the eco-efficiency of the treatment stage. The eco-efficiency of the production stage evidently outweighs the eco-efficiency in economically well-developed regions. The originality of this study lies in three aspects. First, using two-stage network DEA, this study dissects the overall eco-efficiency into production efficiency and treatment efficiency. Empirical results provide insights into the root cause of the low efficiency of each province (municipality). Second, on the basis of the DPSIR model, an expanded pool of driving factors is investigated. Third, using the PLS-SEM method to analyze eco-efficiency is more reliable and effective than applying other traditional regression models. Li Zhijun Z School of Economics and Management, Xidian University, Xi'an 710126, China. Wei Yigang Y School of Economics and Management, Beihang University, Beijing 100191, China. Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China. Li Yan Y Business School, Shandong University, Weihai 264209, China. Wang Zhicheng Z 0000-0001-7516-0728 Business School, Shandong University, Weihai 264209, China. Zhang Jinming J School of Political Studies, Nanjing Agricultural University, Nanjing 210095, China. eng 18YJC840041 the MOE (Ministry of Education in China) Project of Humanities and Social Sciences 71904009 National Natural Science Foundation of China 2019M652415 the Postdoctoral Science Foundation of China Journal Article 2020 11 23 Switzerland Int J Environ Res Public Health 101238455 1660-4601 IM DPSIR model PLS-SEM eco-efficiency environmental treatment network DEA 2020 09 16 2020 11 13 2020 11 16 2020 11 26 1 1 2020 11 27 6 0 2020 11 27 6 0 epublish 33238577 ijerph17228702 10.3390/ijerph17228702 33231983 NBK564313 StatPearls Publishing Treasure Island (FL) StatPearls 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

7.  Impact of whey protein/surfactant mixture and oil type on the gastrointestinal fate of emulsions: Ingredient engineering.LinkIT
Gomes A, Costa ALR, Cardoso DD, Furtado GF, Cunha RL
Food research international (Ottawa, Ont.), 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

8.  Direct Analysis of Glyphosate, Glufosinate, and Their Metabolites in Palm Oil Using Liquid Chromatography with Tandem Mass Spectrometry.LinkIT
Shinde R, Halim N, Banerjee AK
Journal of AOAC International, 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0

9.  Economic, Social, Medical, Work Injury, and Environmental Efficiency Assessments.LinkIT
Fang Z, Chiu YH, Lin TY, Chang TH
Inquiry : a journal of medical care organization, provision and financing, 2020
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0



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