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Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Journal editors are putting a lot of effort into selecting appropriate reviewers for fair and reliable peer review of submitted manuscripts. Editors consider whether the reviewers have no affinity with any of the authors of manuscripts and have sufficient expertise in reviewing the manuscripts. The affinity can be evaluated by whether any of the reviewers has been a coauthor and/or a coworker in a common institution with any of the authors of the manuscript. The expertise depends on the similarity of the research topic between the reviewer’s published papers and the submitted manuscripts. In this paper we propose an algorithm to recommend appropriate reviewers to editors, based on the assessment of these scholarly activities and achievements. To implement this algorithm, TextRank and GenSim library are used to extract feature sets from abstract and introduction sections of both submitted manuscripts and the reviewer candidates’ papers. Based on the extracted feature sets, affinity and expertise check are implemented. An experiment has been conducted with a data set of over 1,000 papers in the field of DB research to evaluate the performance of this algorithm. The experiment consists of affinity check by using 2-mode network matrix operations and expertise check based on Max Similarity and/or topic clustering. Experimental results show that the recommendation algorithm is reasonable on the basis of scholarly activity assessment and achievements. Our method is designed to optimize the reviewer pool for each journal, client and this algorithm is designed with an open license and has the advantage of being free to use and operate. In addition, our algorithm has the advantage of journal-specific optimization by designing to adjust the expertise of the reviewer selection and the weights for exclusion of interests to reflect journal-specific policies.

Over the past three decades, there have been many comprehensive studies related to public–private partnerships (PPP), but the analysis at the macro level still lacks comprehensiveness and interpretability. Through the application of bibliometric analysis, 2-mode network, and strategic coordinate analysis, we systematically analyzed the derivative characteristics of the literature data and the coupling characteristics of countries and keywords. Moreover, through the frequency and betweenness centrality, etc., this paper determines the evolution path of keywords and the evolution direction of theme words and realizes the prediction of theme words and keywords in the future. The results show that: (1) Through the three-stage biclustering analysis, we determined the hot theme words and hot keywords for each stage and focused the theme direction and main research content of the evolution, which led to great interpretability of the data analysis in the literature characteristics; (2) Through the distribution characteristics of time and space, the USA, China, the UK and other mainstream publishing countries and their main research hotspots were determined. Among them, developing countries have strong willingness in academic cooperation and great potential for academic development; (3) According to the derivative characteristics of the literature data, it is predicted that the future research hotspots are: the integration of business economy and sustainability, the integration of policy support and innovative technology application, and the urbanization promotion of developing countries. Based on the findings, this study makes concrete and targeted research methods and provides reference value and application value for the future research and analysis of PPP. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the strategic emerging industrial cluster includes different types of subjects, their interaction will affect the industrial economy and innovation capacity. According lo the data of strategic emerging enterprises, this paper constructs the economic 2-mode network and innovative 2-mode network composed of the strategic emerging industries and regions, respectively, according to the main business income and the number of effective patents of enterprises. Using the centrality of social network analysis to measure the structural characteristics of the 2-mode network, this paper analyzes the development status and evolution trend of strategic emerging industrial clusters. Then the three-dimensional grey correlation model is used to evaluate the innovation ability of each region with strategic emerging industrial clusters. Finally, an empirical study is carried out with Jiangsu province's strategic emerging industrial cluster as a typical case. The results show that: (1)The new generation of informational technology, biological industry, and high-end equipment manufacturing industry all have high centrality in the network, and they are located in an important position in the network. It shows that these three industries have strong economic effects and innovation ability and have a strong ability to control inter-enterprise and inter-regional informational transfer, while the digital creative industry has low centrality and is still in its initial stage located at the edge of the network. (2) The network centrality of Nanjing and Suzhou has always ranked first and second, indicating that these two regions have the highest influence on the network. The strategic emerging industrial clusters of Nanjing and Suzhou are relatively well-developed, and the innovation and economy have formed a positive interaction effect in these industrial clusters. (3) The innovation ability Of strategic emerging industrial clusters in Suzhou, Wuxi, and Nanjing is relatively strong, while the innovation ability of strategic emerging industrial clusters iii Taizhou and Yancheng is relatively weak. There is a great difference between southern Jiangsui and northern Jiangsu. [ABSTRACT FROM AUTHOR]

Over the past three decades, there have been many comprehensive studies related to public–private partnerships (PPP), but the analysis at the macro level still lacks comprehensiveness and interpretability. Through the application of bibliometric analysis, 2-mode network, and strategic coordinate analysis, we systematically analyzed the derivative characteristics of the literature data and the coupling characteristics of countries and keywords. Moreover, through the frequency and betweenness centrality, etc., this paper determines the evolution path of keywords and the evolution direction of theme words and realizes the prediction of theme words and keywords in the future. The results show that: (1) Through the three-stage biclustering analysis, we determined the hot theme words and hot keywords for each stage and focused the theme direction and main research content of the evolution, which led to great interpretability of the data analysis in the literature characteristics; (2) Through the distribution characteristics of time and space, the USA, China, the UK and other mainstream publishing countries and their main research hotspots were determined. Among them, developing countries have strong willingness in academic cooperation and great potential for academic development; (3) According to the derivative characteristics of the literature data, it is predicted that the future research hotspots are: the integration of business economy and sustainability, the integration of policy support and innovative technology application, and the urbanization promotion of developing countries. Based on the findings, this study makes concrete and targeted research methods and provides reference value and application value for the future research and analysis of PPP.

A review of energy subsidy research from a bibliometric perspective was conducted. Based on the bibliometric method, a statistical analysis of energy subsidy–related publications from 1997 to 2016 was undertaken using the Science Citation Index (SCI) and Social Science Citation Index (SSCI) databases. A total of 1182 publications were retrieved, with a significant increase in the number of publications observed after 2006. The majority of these publications were within the disciplines of Energy & Fuels and Environmental Science & Ecology. Although the USA and China contributed the most papers, authors from 96 countries were involved in the various studies. The USA was the center of global collaborations, while other countries/territories mainly conducted bilateral or regional collaborations in their research activities. Five of the top 11 most productive institutes were from China, followed by the USA. The frequency of collaborations among institutes was relatively low. However, the institute–keyword 2-mode network showed that institutes had great potential to cooperate on a number of common topics. Five major themes were identified from the co-keywords analysis: general renewable energy research, bio-energies, sustainability, subsidies, and welfare. The findings, as a complement to previous conventional reviews, will be useful in future energy subsidy research. [ABSTRACT FROM AUTHOR]

Bipartite ecological networks are increasingly used to describe and model relationships between interacting species (e.g., plant-pollinator or host parasite). Here, we apply network methods developed in community ecology to quantify division of labor in insect societies. We consider 2 quantitative indices (d' and H2') derived from information theory that inform on how much the actual patterns of task performance deviates from the null expectation that workers perform tasks randomly. In addition, we computed network modularity to identify clusters of specialized individuals that are preferentially engaged in the completion of subset of available tasks. We analyzed both simple synthetic networks, varying in size and degree of specialization, and published datasets to introduce the metrics and to show that a bipartite approach provides useful insights into task allocation. Considering division of labor as a bipartite network offers a conceptual framework that could substantially increase our understanding of division of labor in animal societies. [ABSTRACT FROM AUTHOR]

Beijing is facing an increasing threat from environmental problems. Since the environment is a public resource, waste emissions from industries are non-competitive and non-exclusive, which indicates that there are competition relationships among industries in Beijing. In order to investigate these relationships in quantity, this paper employs a 2-mode network method to construct a competition network of Beijing's industries using data for 2011 and then analyses the competition network using network indices. Five kinds of wastes are considered: wastewater, waste gas, common solid waste, waste dust and hazardous emissions. Our main findings include: the manufacture of raw chemical materials and chemical products and the manufacture of non-metallic mineral products are under intense emission competition in Beijing. Industries are divided into three groups by waste emission. Two industries mainly discharge hazardous waste; six industries mainly discharge wastewater; and the remaining 12 industries discharge waste dust, common solid waste and waste gas. These relationships should be considered in industrial planning, and industries that discharge similar waste types should not be located close together. [ABSTRACT FROM AUTHOR]