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The purpose of this paper is to present the landscape of the cash-per-publication reward policy in China and reveal its trend since the late 1990s.

This study is based on the analysis of 168 university documents regarding the cash-per-publication reward policy at 100 Chinese universities.

Chinese universities offer cash rewards from USD30 to USD165,000 for papers published in journals indexed by Web of Science, and the average reward amount has been increasing for the past ten years.

The cash-per-publication reward policy in China has never been systematically studied and investigated before except for in some case studies. This is the first paper that reveals the landscape of the cash-per-publication reward policy in China.

The purpose of this paper is to lay the necessary conceptual and empirical groundwork that advances knowledge about paternalistic leadership (PL). PL is reinterpreted as a leadership style consisting of authoritative, moral and benevolent leadership. The mediating role of trust is examined, and a formal, unified construct model of PL is suggested through evidence of construct validity.

An on-site survey was used to collect data from 312 full-time employees in nine organizations in China. Factor analysis, reliability and validity test, and an analysis of bivariate correlations were conducted.

The new construct of PL achieved a positive alignment and coherence among the three dimensions. Subordinates’ trust was found to be critical for paternalistic leaders to be perceived as effective leaders.

Leadership and its effectiveness were examined only at the dyadic level. The levels of the supervisors and their effectiveness differ because some were from middle management, whereas others were from first line managers.

Trust is an important explanatory mechanism for the relationship between PL and employee performance, especially in China. It is a key factor that creates loyalty and builds a good relationship between leaders and subordinates.

Trust signals a strong sense of sharing within the relationship. It induces positive emotional feelings in their leader by the subordinates and, therefore, taps into positive evaluations about the effectiveness of their leader.

This study developed the theoretical underpinnings and provided measurement instruments for PL. It offered a formal, unified construct model of PL.

This paper aims to analyse how the top over-the-top (OTT) platform is becoming a preferred source of entertainment amongst young consumers over traditional Pay TV service (Cable TV/DTH) in India and what factors play a vital role in such preferences along with gamification of content. The study follows the theoretical framework of use and gratifications theory and Niche analysis.

The study establishes a conceptual framework of understanding the preference of consumers, which triggers the shift from old media to new. This research develops an approach to understanding the relevant implications in responses of consumers through a structured online survey conducted amongst different age groups by applying exploratory and confirmatory factor analysis. To further comprehend the relations between measured variables and constructs, the statistical technique is incorporated, i.e. logistic regression.

Empirical results and discussion insinuated the five factors which affect consumers’ choices concerning entertainment i.e. content and viewing behaviour, expenses incurred on services, shifts influenced by offerings/incentives, convenience and telecom. Logistic regression validated the strength of these factors which made content and viewing behaviour, expenses incurred on services and convenience the three most important factors.

This study analyses the driving factors that are revolutionising the entertainment industry and can be applied in designing a comfortable and engaging experience for a consumer in the future.

This research is original in nature and the findings of this study are valuable for online streaming services, video-on-demand services, Cable TV operators and entertainment content producers.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

This paper aims to examine the relationship between the audit of outgoing leading officials' natural resource accountability and environmental governance, as well as the internal mechanism of audit of outgoing leading officials' natural resource accountability that plays a role in national environmental governance.

Based on city-level panel data from 2012 to 2015, this paper adopts a difference-in-difference model to examine the role of government audit in national governance from an environmental perspective. Furthermore, using a mediating effect model, the study sheds light on the internal mechanism of audit of outgoing leading officials’ natural resource accountability that plays a role in national environmental governance.

This paper finds that: the implementation of the audit of outgoing leading officials’ natural resource accountability has significantly improved the water quality of the pilot area, but its effects on waste gas and smoke are not obvious; environmental supervision partly plays a mediating role in the improvement of regional environmental governance by the audit of outgoing leading officials’ natural resource accountability; the audit of outgoing leading officials’ natural resource accountability can complement the incentive mechanism of promotion. The older the local officials are, the more obvious the effect of the audit of outgoing leading officials’ natural resource accountability on the environmental quality of the pilot areas is.

This paper reveals the role of government audit from the perspective of environmental governance. It provides empirical evidence for policy regarding the audit of outgoing leading officials' natural resource accountability.

The purpose of this study was a longitudinal study on knowledge organization (KO) realm structure and cluster concepts and emerging KO events based on co-occurrence analysis.

This longitudinal study uses the co-occurrence analysis. This research population includes keywords of articles indexed in the Web of Science Core Collection 1975–1999 and 2000–2018. Hierarchical clustering, multidimensional scaling and co-occurrence analysis were used to conduct the present research. SPSS, UCINET, VOSviewer and NetDraw were used to analyze and visualize data.

The “Information Technology” in 1975–1999 and the “Information Literacy” in 2000–2018, with the highest frequency, were identified as the most widely used keywords of KO in the world. In the first period, the cluster “Knowledge Management” had the highest centrality, the cluster “Strategic Planning” had the highest density in 2000–2018 and the cluster “Information Retrieval” had the highest centrality and density. The two-dimensional map of KO’s thematic and clustering of KO topics by cluster analysis method indicates that in the periods examined in this study, thematic clusters had much overlap in terms of concept and content.

The present article uses a longitudinal study to examine the KO’s publications in the past half-century. This paper also uses hierarchical clustering and multidimensional scaling methods. Studying the concepts and thematic trends in KO can impact organizing information as the core of libraries, museums and archives. Also, it can scheme information organizing and promote knowledge management. Because the results obtained from this article can help KO policymakers determine and design the roadmap, research planning, and micro and macro budgeting processes.

The purpose of this paper is to address the problem of control in a typical chaotic power system. Chaotic oscillations cannot only extremely endanger the stabilization of the power system but they can also not be controlled by adding the traditional controllers. So, the sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of the power system, eliminating control signal chattering and also show less control effort in comparison with the methods considered in previous literatures.

The sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory.

Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of power system, eliminating control signal chattering and also less control effort in comparison with the methods considered in previous literatures.

Main contributions of the paper are as follows: the chaotic behavior of power systems with two uncertainty parameters and tracking reference signal for the control of generator angle and the controller signal are discussed; designing sliding mode control based on a fuzzy supervisor in order to practically implement for the first time; while the generator speed is constant, the proposed controller will enable the power system to go in any desired trajectory for generator angle at first time; stability of the closed-loop sliding mode control based on the fuzzy supervisor system is proved using the Lyapunov stability theory; simulation of the proposed controller shows that the chattering is low control signal.

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to traditional routing protocols. The limitations of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally, the correctness of the proposed algorithm in this paper is verified by simulation.

The limitations of the existing routing protocols under the condition of rapid data growth are elaborated and the routing problem is remodeled as a Markov decision process. Based on this, a deep reinforcement learning method is used to select the next-hop router for each data transmission task, thereby minimizing the length of the data transmission path while avoiding data congestion.

Simulation results show that the proposed method can significantly reduce the probability of data congestion and increase network throughput.

This paper proposes an intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era. With the help of deep reinforcement learning, it is possible to dynamically select the transmission jump router according to the current network state, thereby reducing the probability of congestion and improving network throughput.

The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location, etc. Color is an important factor in identifying stains. K/S value is used to analyze the color of textile fabric, and it has additivity. The purpose of the study is to explore its application in stain recognition is of great significance to intelligent washing.

A certain method used to stain the textile, then the K/S value of the textile before and after the stain was analyzed and tested by the color difference instrument. The K/S curve of the stain was calculated by the addition of K/S, and then the stain was identified and distinguished.

The K/S value of the textile stained with stains could be deducted by the K/S value of the color difference meter. After deducting the base cloth, the K/S curve of the same stain is basically the same. Then the stain can be identified and analyzed.

The K/S value can be used for stain analysis, but it needs to be analyzed and tested in the laboratory.

This study provides a simple method for stains identification.

In addition to common methods of stain identification, such as appearance, color, feel, smell, location, stain removal materials, breaking the substrate, IR, etc., K/S value can be used for stain analysis. Identifying stains and washing them in a targeted way to achieve a better washing effect could provide certain technical support for the development of smart washing and smart home appliances.

The purpose of this paper is to propose a modification of the Functional Requirements for Authority Data (FRAD) model to accommodate names in non-Roman languages with diverse writing systems.

The model modifies and clarifies the attributes and relationships regarding non-Roman languages of the current FRAD model, based on the definitions of transliteration, transcription, and Romanization in ISO 5127:2001. The modified model overcomes the problems inherent in the current FRAD model when handling writing systems in non-Roman languages.

The proposed model clearly shows the hierarchy of Controlled Access Points (CAPs). CAPs are either based directly on names or derived from other CAPs. For name or person identification, a CAP and its derivations should be treated as a set. The proposed model also resolves ambiguity in the definition of the word transliteration in the current FRAD model.

By establishing new relationships and amending the attributes of the FRAD model, the proposed model better expresses personal names in non-Roman languages as well as names in western languages. It also organizes complex writing systems of non-Roman languages. The proposed model could lead to an improved format for authority data and will facilitate international sharing of data.