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Article ; Online: Complex System Models and Their Application in Industrial Cluster and Innovation Systems

Su Yi / Yang Zaoli / Xie Xuemei / Garg Harish

Complexity, Vol

2022 Volume 2022

Keywords	Electronic computers. Computer science ; QA75.5-76.95
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi-Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Under the different sectors

Shizhen Bai / Jiamin Zhou / Mu Yang / Zaoli Yang / Yongmei Cui

Frontiers in Public Health, Vol

the relationship between low-carbon economic development, health and GDP

2023 Volume 11

Abstract: Developing a modern low-carbon economy while protecting health is not only a current trend but also an urgent problem that needs to be solved. The growth of the national low-carbon economy is closely related to various sectors; however, it remains ... ...

Abstract	Developing a modern low-carbon economy while protecting health is not only a current trend but also an urgent problem that needs to be solved. The growth of the national low-carbon economy is closely related to various sectors; however, it remains unclear how the development of low-carbon economies in these sectors impacts the national economy and the health of residents. Using panel data on carbon emissions and resident health in 28 province-level regions in China, this study employs unit root tests, co-integration tests, and regression analysis to empirically examine the relationship between carbon emissions, low-carbon economic development, health, and GDP in industry, construction, and transportation. The results show that: First, China’s carbon emissions can promote economic development. Second, low-carbon economic development can enhance resident health while improving GDP. Third, low-carbon economic development has a significant positive effect on GDP and resident health in the industrial and transportation sector, but not in the construction sector, and the level of industrial development and carbon emission sources are significant factors contributing to the inconsistency. Our findings complement existing insights into the coupling effect of carbon emissions and economic development across sectors. They can assist policymakers in tailoring low-carbon policies to specific sectors, formulating strategies to optimize energy consumption structures, improving green technology levels, and aiding enterprises in gradually reducing carbon emissions without sacrificing economic benefits, thus achieving low-carbon economic development.
Keywords	carbon neutrality ; industry low-carbon economy ; health ; greenhouse gases ; economic growth ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Under the different sectors: the relationship between low-carbon economic development, health and GDP.

Bai, Shizhen / Zhou, Jiamin / Yang, Mu / Yang, Zaoli / Cui, Yongmei

Frontiers in public health

2023 Volume 11, Page(s) 1181623

Abstract	Developing a modern low-carbon economy while protecting health is not only a current trend but also an urgent problem that needs to be solved. The growth of the national low-carbon economy is closely related to various sectors; however, it remains unclear how the development of low-carbon economies in these sectors impacts the national economy and the health of residents. Using panel data on carbon emissions and resident health in 28 province-level regions in China, this study employs unit root tests, co-integration tests, and regression analysis to empirically examine the relationship between carbon emissions, low-carbon economic development, health, and GDP in industry, construction, and transportation. The results show that: First, China's carbon emissions can promote economic development. Second, low-carbon economic development can enhance resident health while improving GDP. Third, low-carbon economic development has a significant positive effect on GDP and resident health in the industrial and transportation sector, but not in the construction sector, and the level of industrial development and carbon emission sources are significant factors contributing to the inconsistency. Our findings complement existing insights into the coupling effect of carbon emissions and economic development across sectors. They can assist policymakers in tailoring low-carbon policies to specific sectors, formulating strategies to optimize energy consumption structures, improving green technology levels, and aiding enterprises in gradually reducing carbon emissions without sacrificing economic benefits, thus achieving low-carbon economic development.
MeSH term(s)	Economic Development ; Carbon/analysis ; Industry ; China ; Carbon Dioxide
Chemical Substances	Carbon (7440-44-0) ; Carbon Dioxide (142M471B3J)
Language	English
Publishing date	2023-07-20
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1181623
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Evaluation of the Sustainable Development of the Social-Economic-Natural Compound Ecosystem in the Guangdong-Hong Kong-Macao Greater Bay Area Urban Agglomeration (China)

Zhijun Feng / Zinan Chen / Hechang Cai / Zaoli Yang

Frontiers in Environmental Science, Vol

Based on Complex Network Analysis

2022 Volume 10

Abstract: In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a series of natural environmental, economic, and social issues have emerged sequentially in the process of rapid economic and social development. Therefore, for the sustainable development of the ... ...

Abstract	In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a series of natural environmental, economic, and social issues have emerged sequentially in the process of rapid economic and social development. Therefore, for the sustainable development of the GBA, how to closely integrate nature protection with economic and social development to improve the sustainable development level of the social-economic-natural compound ecosystem, and realize the coordinated development of the system is particularly important. Based on the perspective of complex network and the theory of compound ecosystem, this study proposes a set of sustainable development evaluation model based on complex network modeling to evaluate the sustainable development level of compound ecosystem in GBA from 2014 to 2018, and further analyze the coupling coordination degree. The major findings include: 1) For the sustainable development in the GBA, the development of the natural subsystem is an important foundation, and the synchronous development of the social and economic subsystems are the main driving force. 2) The sustainable development level in the GBA shows an overall steady upward trend; the average level of the compound ecosystem’s coupling coordination development is in a “good” state, and it shows an evident upward trend. 3) Whether it is within the GBA or the GBA and its surrounding regions, there are problems of unbalanced and insufficient regional development. Policy recommendations include increasing the emphasis on the sustainable development of the natural subsystem, promoting the coordinated development of the economic, social, and natural subsystems, and promoting the balanced development of cities within the GBA, as well as the GBA and surrounding regions.
Keywords	Guangdong-Hong Kong-Macao Greater Bay Area (GBA) ; social-economic-natural compound ecosystem ; sustainable development ; coupling coordination degree ; complex network ; node importance ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator

Yang, Zaoli / Chang, Jinping

Environmental research. 2021 Feb., v. 193

2021

Abstract: With the increase of the global population and the improvement of people's living standards, the output of garbage generated by human activities is also increasing day by day. Choosing an appropriate garbage disposal site is one of the key links for the ... ...

Abstract	With the increase of the global population and the improvement of people's living standards, the output of garbage generated by human activities is also increasing day by day. Choosing an appropriate garbage disposal site is one of the key links for the harmless disposal of garbage. However, due to the uncertainty and complexity of socio-economic development and the limited cognitive ability of decision-makers, how to rationally select the garbage disposal site has become a challenging task. This study drew a new multi-attribute decision-making method based on interval q-rung orthopair fuzzy weighted power Muirhead mean (Iq-ROFPWMM) operator to evaluate site selection scheme of garbage disposal plant, and support for garbage disposal site selection. In this method, firstly, power average and Muirhead mean operators are integrated and introduced into the interval q-rung orthopair fuzzy environment to construct an Iq-ROFPWMM operator. Meanwhile, some properties of idempotence, boundedness and monotonicity for the Iq-ROFPWMM operator are analyzed. Then, a multi-attribute decision-making method using Iq-ROFPWMM operator is established. After that, a practical case on the evaluation of garbage disposal site selection scheme is given to verify the effectiveness of the proposed method. Further, parameter analysis and comparative analysis are applied to demonstrate the superiority of our method. The results show that this method boasts wider space for evaluation information representation, more flexible adaptation to the environment evaluation, and stronger robustness of the evaluation results. Finally, some conclusions of this study are drawn and the development direction is revealed.
Keywords	algorithms ; cognition ; decision making ; environmental assessment ; humans ; municipal solid waste ; research ; socioeconomic development ; uncertainty
Language	English
Dates of publication	2021-02
Publishing place	Elsevier Inc.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2020.110385
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator.

Yang, Zaoli / Chang, Jinping

Environmental research

2020 Volume 193, Page(s) 110385

Abstract	With the increase of the global population and the improvement of people's living standards, the output of garbage generated by human activities is also increasing day by day. Choosing an appropriate garbage disposal site is one of the key links for the harmless disposal of garbage. However, due to the uncertainty and complexity of socio-economic development and the limited cognitive ability of decision-makers, how to rationally select the garbage disposal site has become a challenging task. This study drew a new multi-attribute decision-making method based on interval q-rung orthopair fuzzy weighted power Muirhead mean (Iq-ROFPWMM) operator to evaluate site selection scheme of garbage disposal plant, and support for garbage disposal site selection. In this method, firstly, power average and Muirhead mean operators are integrated and introduced into the interval q-rung orthopair fuzzy environment to construct an Iq-ROFPWMM operator. Meanwhile, some properties of idempotence, boundedness and monotonicity for the Iq-ROFPWMM operator are analyzed. Then, a multi-attribute decision-making method using Iq-ROFPWMM operator is established. After that, a practical case on the evaluation of garbage disposal site selection scheme is given to verify the effectiveness of the proposed method. Further, parameter analysis and comparative analysis are applied to demonstrate the superiority of our method. The results show that this method boasts wider space for evaluation information representation, more flexible adaptation to the environment evaluation, and stronger robustness of the evaluation results. Finally, some conclusions of this study are drawn and the development direction is revealed.
MeSH term(s)	Algorithms ; Decision Making ; Fuzzy Logic ; Humans ; Refuse Disposal ; Uncertainty
Language	English
Publishing date	2020-11-07
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2020.110385
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Article ; Online: Evaluating alternative low carbon fuel technologies using a stakeholder participation-based q-rung orthopair linguistic multi-criteria framework

Yang, Zaoli / Ahmad, Salman / Bernardi, Andrea / Shang, Wen-long / Xuan, Jin / Xu, Bing

Applied Energy. 2023 Feb., v. 332 p.120492-

2023

Abstract: It is widely believed that alternative low carbon fuels (ALCF) can be instrumental in achieving the transportation sector's decarbonization goal. Unlike conventional fossil-based fuels, ALCF can be produced through a combination of different chemical ... ...

Abstract	It is widely believed that alternative low carbon fuels (ALCF) can be instrumental in achieving the transportation sector's decarbonization goal. Unlike conventional fossil-based fuels, ALCF can be produced through a combination of different chemical processes and feedstocks. The inherent complexity of the problem justifies the multi-criteria decision-making (MCDM) approach to support decision-making in the presence of multiple criteria and data uncertainty. In this paper, we propose a novel stakeholder participation-based MCDM framework integrating experts' perspectives on ALCF production pathways using the analytics hierarchy process (AHP) and the q-rung orthopair linguistic partition Bonferroni mean (q-ROLPBM) operator. The key merit of our approach lies in treating criteria of different dimensions as heterogeneous indicators while considering the mutual influence between criteria within the same dimension. The proposed framework is applied to evaluate four ALCF production pathways against 13 criteria categorised under economic, environmental, technical, and social dimensions for the case of the United Kingdom (UK). Our analysis revealed the environmental and the economic dimensions to be the most important, followed by the social and technical evaluation dimensions. The e-fuel followed by the e-biofuel are found to be the two top-ranked production pathways that utilise the electrochemical reduction process and its combination with anaerobic digestion. These findings, along with our recommendations, provide decision-makers with guidelines on ALCF production pathway selection and formulate effective policies for investment.
Keywords	anaerobic digestion ; carbon ; electrochemistry ; energy ; feedstocks ; fuels ; multi-criteria decision making ; stakeholders ; transportation industry ; uncertainty ; United Kingdom ; e-fuels ; Alternative low carbon fuels (ALCF) ; UK transportation sector ; Analytics hierarchy process (AHP) ; q-rung orthopair linguistic partition Bonferroni mean operator ; MCDM
Language	English
Dates of publication	2023-02
Publishing place	Elsevier Ltd
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	2000772-3
ISSN	0306-2619
ISSN	0306-2619
DOI	10.1016/j.apenergy.2022.120492
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Reverse Knowledge Transfer in Cross-Border Mergers and Acquisitions in the Chinese High-Tech Industry under Government Intervention

Yi Su / Wen Guo / Zaoli Yang

Complexity, Vol

2021 Volume 2021

Abstract: The high-tech industry is the main force promoting the development of China’s national economy. As its industrial economic strength grows, China’s high-tech industry is increasingly using cross-border mergers and acquisitions (CBM&A) as an important way ... ...

Abstract	The high-tech industry is the main force promoting the development of China’s national economy. As its industrial economic strength grows, China’s high-tech industry is increasingly using cross-border mergers and acquisitions (CBM&A) as an important way to “go out.” To explore the rules governing the process and operation mechanism of reverse knowledge transfer (RKT) through the CBM&A of China’s high-tech industry under government intervention, a tripartite evolutionary game model of the government, the parent company, and the subsidiary as the main subjects is constructed in this paper. The strategies adopted by the three subjects in the RKT game process are analysed, and the factors influencing RKT through CBM&A under government intervention are simulated and analysed using Python 3.7 software. The results show that, under government intervention, the parent company and subsidiary have different degrees of influence on each other. Subsidiaries are highly sensitive to the compensation rate of RKT. Positive intervention by the government tends to foster stable cooperation between the parent company and the subsidiary. However, over time, the government gradually relaxes its intervention in the RKT and innovation of multinational companies.
Keywords	Electronic computers. Computer science ; QA75.5-76.95
Subject code	950
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi-Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatial variation in the community structure and response of benthic macroinvertebrates to multiple environmental factors in mountain rivers

Yang, Zaoli / He, Shufeng / Feng, Tao / Lin, Yuqing / Chen, Mo / Li, Qinyuan / Chen, Qiuwen

Journal of Environmental Management. 2023 Sept., v. 341 p.118027-

2023

Abstract: Exploring the response between benthic community changes and environmental variables has significance for restoring the health of river ecosystems. However, little is known of the impact on communities of interactions between multiple environmental ... ...

Abstract	Exploring the response between benthic community changes and environmental variables has significance for restoring the health of river ecosystems. However, little is known of the impact on communities of interactions between multiple environmental factors, and frequent changes in the flow of mountain rivers are different from those in the flow of plain river networks, which also impact differently the benthic community. Thus, there is a need for research on the response of benthic communities to environmental changes in mountain rivers under flow regulation. In this study, we collected samples from the Jiangshan River in the dry season (November 2021) and the wet season (July 2022) to investigate the aquatic ecology and benthic macroinvertebrate communities in the watershed. Multi-dimension analyses were used to analyze the spatial variation in the community structure and response of benthic macroinvertebrates to multiple environmental factors. In addition, the explanatory power of the interaction between multiple factors on the spatial variation of communities, and the distribution characteristics of benthic community and their causes were investigated. The results showed that herbivores are the most abundant forms in the benthic community of mountain rivers. The structure of benthic community in Jiangshan River was significantly affected by water quality and substrate, whereas the overall community structure was affected by river flow conditions. Furthermore, nitrite nitrogen and ammonium nitrogen were the key environmental factors impacting the spatial heterogeneity of communities during the dry and wet season, respectively. Meanwhile, the interaction between these environmental factors showed a synergistic effect, enhancing the influence of these environmental factors on community structure. Thus, controlling urban and agricultural pollution and releasing ecological flow would be effective strategies to improve benthic biodiversity. Our study showed that using the interaction of environmental factors was a suitable way to evaluate the association between environmental variables and variation in benthic macroinvertebrate community structure in river ecosystems.
Keywords	agricultural pollution ; ammonium nitrogen ; benthic organisms ; biodiversity ; community structure ; dry season ; environmental management ; macroinvertebrates ; nitrite nitrogen ; river flow ; rivers ; spatial variation ; synergism ; water quality ; watersheds ; wet season ; Benthic macroinvertebrates ; Spatial heterogeneity ; Environmental factors ; Impact ; Interaction ; Mountainous rivers
Language	English
Dates of publication	2023-09
Publishing place	Elsevier Ltd
Document type	Article ; Online
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2023.118027
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: NSCR-Based DenseNet for Lung Tumor Recognition Using Chest CT Image.

Tao, Zhou / Bingqiang, Huo / Huiling, Lu / Zaoli, Yang / Hongbin, Shi

BioMed research international

2020 Volume 2020, Page(s) 6636321

Abstract: Nonnegative sparse representation has become a popular methodology in medical analysis and diagnosis in recent years. In order to resolve network degradation, higher dimensionality in feature extraction, data redundancy, and other issues faced when ... ...

Abstract	Nonnegative sparse representation has become a popular methodology in medical analysis and diagnosis in recent years. In order to resolve network degradation, higher dimensionality in feature extraction, data redundancy, and other issues faced when medical images parameters are trained using convolutional neural networks. Lung tumors in chest CT image based on nonnegative, sparse, and collaborative representation classification of DenseNet (DenseNet-NSCR) are proposed by this paper: firstly, initialization parameters of pretrained DenseNet model using transfer learning; secondly, training DenseNet using CT images to extract feature vectors for the full connectivity layer; thirdly, a nonnegative, sparse, and collaborative representation (NSCR) is used to represent the feature vector and solve the coding coefficient matrix; fourthly, the residual similarity is used for classification. The experimental results show that the DenseNet-NSCR classification is better than the other models, and the various evaluation indexes such as specificity and sensitivity are also high, and the method has better robustness and generalization ability through comparison experiment using AlexNet, GoogleNet, and DenseNet-201 models.
MeSH term(s)	Algorithms ; Deep Learning ; Humans ; Lung/diagnostic imaging ; Lung Neoplasms/diagnostic imaging ; Radiographic Image Interpretation, Computer-Assisted/methods ; Tomography, X-Ray Computed/methods
Language	English
Publishing date	2020-12-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2698540-8
ISSN	2314-6141 ; 2314-6133
ISSN (online)	2314-6141
ISSN	2314-6133
DOI	10.1155/2020/6636321
Database	MEDical Literature Analysis and Retrieval System OnLINE

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