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The purpose of this paper is to model the Chinese unique regulation changes with the supply-and-demand analytical framework and structure the relationship between initial public offerings (IPO) underpricing and institutional changes with the comparative static method. A well-functioning stock market is crucial to the transition into a market economy, but the Chinese stock market is somehow twisted with frequent government interventions, particularly the IPO market. Can the underpricing issue be mitigated in the changing institutional settings? Can the market-orientated incremental reform of regulations succeed in the Chinese stock market?

The theoretical analysis confirms that IPO underpricing becomes relatively better with dynamic changes of relaxation of the approval and pricing systems. Collecting and examining the data of newly listed firms from 1993 to 2010, the influence of institutional changes on IPO underpricing with regressions, such as ordinary least square (OLS), bootstrap and two stage least square (2SLS) estimation methods was further empirically examined.

The magnitude of the Chinese IPO underpricing during the past two decades is as high as 181.6 per cent on the average. The sizes of IPO underpricing significantly reduce with an increase in the issuing sizes and the ratios of price-earnings ratios. The dummy variables of government-approved regulations are negatively associated with IPO underpricing. The dummy variables of pricing regulations are positively related to IPO underpricing and the coefficients become smaller with newer regulations. Generally, the magnitude of the Chinese IPO underpricing decreases over time.

This paper enriches the IPO literature by dynamically examining the effect of institutional changes on IPO underpricing in Chinese primary markets. We argue that institutional changes characterized by incremental marketization can help to alleviate extreme IPO underpricing and to promote financial development. The Chinese transition from the planning system to the market system in the IPO market will be a long and strenuous process, but it works.

This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of clean energy in China.

This study contained a sample of 653 households in 8 provinces/regions by stratified, and random sampling in rural China. Descriptive analysis, exploratory factor analysis and confirmatory factor analysis techniques have been used for analytical purposes.

The empirical results indicate that financial incentive and social interaction have positive effects on rural residents’ adoption willingness, while village leaders’ engagement can indirectly influence their adoption willingness through social interaction and residents’ cognition.

This study mainly considers external and internal factors but ignores the effect of technical factors. In addition, the samples are just selected from the residents who have adopted solar PV.

This study is expected to be useful for the government, regulators, village leaders, village leaders and other institutions.

This study conducts a systematic analysis and clarifies the relationship between factors (external and internal) and rural residents’ adoption willingness. The village leaders’ engagement is first added to the conceptual model as an external factor, which is very essential in rural residents’ adoption in China.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.