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The oil film thickness provides a key performance indicator of a ball bearing lubrication condition. This paper aims to propose an approach to calculate and measure the oil film thickness of the bearing.

On a specially designed test rig, measurement of the capacitance is used to monitor the oil film thickness of ball bearing. A corrected film thickness formula taking account of the influences of non-Newtonian shear thinning and thermal is introduced to predict the oil film thickness of ball bearing. And then the film thickness distribution and the corresponding capacitances are calculated.

Measurement and calculation of oil film thickness in a ball bearing are carried out under various rotating speeds and external loads. By comparing the calculated capacitances with measured results, it can be concluded that the calculated results obtained by the amended film thickness formula are much closer to the test findings than the classical computed values according to Hamrock–Dowson.

A new corrected film thickness formula is introduced in predicting oil film thickness of ball bearing and verified by the series of experiments according to capacitance method.

Membrane biological reactor (MBR) is recognized as an efficient and steady wastewater treatment process. The purpose of this study is to reveal the research trends of scientific outputs on MBR for the past 32 years.

A method of bibliometric analysis was performed, based on the online version of the Science Citation Index Expanded, Web of Science, from 1982 to 2013. In total, 5,305 articles related to MBR were evaluated. A new method named “word cluster analysis” was also used for further analysis.

Results showed a rising trend of publications in this research field. English was the main language used in these articles. Journal of membrane science published the most articles, proving to be one of the most authoritative journals. China and Dalian University of Technology were the most productive country and institute, respectively. Except for “membrane bioreactor” and “MBR”, “membrane fouling” was the most cited keyword, indicating the research hotspot nowadays and future.

This study serves as an alternative and innovative way of revealing the research trends in MBR research.

The paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.

In total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.

Some models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.

Providing climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

Recent research has drawn attention to the tension between the Central and local governments in China regarding their roles in environmental protection. This paper aims to explore this tension and examine the extent to which local/provincial government’s environmental oversight has influenced the quality of corporate environmental disclosure in China.

A sample of 198 listed companies in heavily polluting industries were selected to examine the relationship between their environmental disclosure quality and the respective local government’s environmental oversight level.

The results provide evidence that local/provincial government’s environmental oversight significantly influences environmental disclosure in China. Despite the coercive pressure from the powerful Central government on corporate environmental disclosure, local/provincial governments are able to buffer the pressure and adjust the intensity of their environmental oversight on companies during the implementation of central policies to retain local economic and political interests. This may partially explain the persistent issue of low environmental disclosure quality in China.

This study enriches our understanding of the significant role of local governments in China in enhancing or sometimes discounting the regulatory enforcement of the Central government on corporate environmental disclosure, pointing to the need for concerted efforts by both local and Central governments to advance environmental disclosure development.

Research on environmental disclosure in developed countries has been well established in the literature. However, such research in developing nations is still limited, especially in China, the world largest developing country. The existing literature on environmental disclosure in China links it with either market demands, or regulatory enforcement from the Central government. The importance of local/provincial governments and their environmental oversight has long been ignored, which motivates this research.

The emergent field of Internet of Things (IoT) has been evolving rapidly with a geometric growth in the number of academic publications in this field. The purpose of this paper is to review the literature of IoT in past 16 years using rigorous bibliometric and network analysis tools, offering at the same time future directions for the IoT research community and implications for managers and decision makers.

The authors adopted the techniques of bibliometric and network analysis. The paper reviewed the articles published on IoT from 2000 to 2015.

This study identifies top contributing authors; key research topics related to the field; the most influential works based on citations and PageRank; and established and emerging research clusters. Scholars are encouraged to further explore this topic.

This study focusses only on vision and applications of IoT. Scholars may explore various other aspects of this area of research.

To the best of authors’ knowledge, this is the first study to review the literature on IoT by using bibliometric and network analysis techniques. The study is unique as it spans a long time period of 16 years (2000-2015). The study proposes a five-cluster classification of research themes that may inform current and future research in IoT.