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The purpose of this paper is to provide a safe control strategy for aloft hot-line assembly of connection fittings in 110kV intelligent substations, which is significant to research on hot-line working robots.

This paper addresses challenges of the task and establish the contact models of connection fittings. By using this control strategy, neither high precision vision positioning nor preset global reference coordinate system is required. Visual computing only needs to provide an approximately position for the manipulator end-effector, after which the connection fittings assembly task could be completed with the posture of the manipulator adjusted following the guidance by force-position control. The authors also analyze the influence of the intervention of manipulators on the very non-uniform electric field during the operation.

This strategy will be particularly useful for the hot-line assembly of connection fittings in 110kV intelligent substations as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This assembly strategy is tested in energized simulated experimental system. The experiment results show that the robot can replace the manual operation to complete the assembly task safely and efficiently.

This assembly strategy is able to achieve the assembly task of connection fittings. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

China is among one of the oldest civilizations in the world. The massive land mass of China also means that the Chinese people are subject to weather extremes as well as topographical variety in a country which cuts across alpine heights, treacherous deserts, lush valleys, dusty plains and lengthy rivers. With these weather extremes as the backdrop, it is crucial for the Chinese people to develop appropriate environmental control techniques for their dwellings as well as to ensure the structural integrity of their buildings. This paper discusses the protection, heating, anti‐seismic and dampness techniques developed and implemented in ancient China. It also documents the measures taken by the ancient Chinese to ensure the structural integrity of their buildings. The examples highlighted in this paper suggest that the building science principles adopted in ancient China remain relevant in the construction industry today.

The purpose of this paper is to extend game analysis to explore decision-making mechanisms for promoting a specific type of products, low energy consumption for individual one while the total energy consumption is huge due to the high quantity of sales, that is, low for individual and high for total (LIHT) in terms of energy consumption.

Game models are developed to compare decisions of optimal prices for newly developed and environmentally friendly (NDEF) and regular products as well as associated sales quantity, profits, carbon emissions under different governmental policies, along with a case of low energy-intensive broadband terminal products in the Chinese telecommunication industry under the carbon tax and subsidy policies.

For both NDEF and regular products, optimal prices decrease under the subsidy policy while both increase under the tax policy. Manufacturers’ decision of optimal prices is highly relevant with unit carbon tax/subsidy and the consumers’ preference. Both the tax and subsidy policies can improve consumption of NDEF products while the subsidy policy can be more effective at the current initial stage.

This paper provides decision support for manufacturers to promote sustainable consumption of LIHT products. Research ideas on models development and solutions for optimal prices can be applied to other LIHT products.

The results provide insights for governments on how to effectively evaluate and motivate sustainable consumption for LIHT products.

This paper first explores how to motivate sustainable consumption of LIHT products by developing models, examining effectiveness of potential governmental policies as well as associated carbon emissions.

This paper aims to investigate the influence of social interactions on mutual fund portfolios from the perspective of alumni network in China.

Based on a data set that consists of 162 actively managed equity funds in China during the time period of 2003–2014, this study employs multiple linear regression model to control for organization- and location-based interpersonal connections as well as other confounding factors and clarify the causality relationship between alumni networks of mutual fund managers and their portfolios.

After controlling for organization- and location-based interpersonal connections, we find that mutual fund managers who graduated from the same college/university have more similar stock holdings and are more likely to buy or sell the same stocks contemporaneously. As a result, alumni managers exhibit a higher correlation of fund returns. Moreover, the effect of alumni relationship on mutual fund investments becomes weaker when more managers are connected within the network. We also find that valuable information is shared among alumni managers: (1) the average returns for the alumni common holdings portfolios is significantly higher than those for non-alumni holdings portfolios and (2) a long-short strategy composed of stocks purchased minus sold by alumni managers yields positive and significant risk-adjusted returns.

The findings suggest that information dissemination among connected fund managers could be one of the driving forces for mutual fund herding behavior, and that a portfolio of funds whose managers are educationally connected could be highly exposed to certain stocks and risks.

This paper contributes to the growing finance literature addressing the influence of personal connections on information dissemination that specifically contributes to price formation. It corresponds more closely to Cohen et al. (2008), who investigate college alumni connections between fund managers and corporate board members. Since the authors simultaneously examine three potentially overlapped social networks, which are based on education, locality and fund family, the authors are able to disentangle their effects on fund managers' investment decisions. Moreover, the findings suggest that institutional investors make investment decisions based on share private information, and therefore, it also contributes to the literature on fund herding behaviors (Grinblatt et al., 1995; Wermers, 1999).

Under extensive pressure from normal market competition, frequent technological change and extreme exogenous shock, firms are facing severe challenge nowadays. How to withstand discontinuous crises and respond to normal risks through improving resilience (RE) is an important question worth researching. Thus, drawing on the strategic entrepreneurship theory, the purpose of this study is exploring the relationship between entrepreneurial orientation (EO) and RE, and combining digitization to discuss the role of digital business capability (DBC), digital business model innovation (DBMI) and environmental hostility (EH).

Based on survey data from 203 Chinese firms, using the methods of linear regression and bootstrap to test our hypothesis. Furthermore, fuzzy-set qualitative comparative analysis (FsQCA) is used to identify previously unknown combinations which lead to strong/weak RE in digital context.

First, EO positively influenced DBC and RE. Second, DBMI promoted RE, DBC and DBMI served as sequential mediators that linked EO and RE. Third, EH positively moderated the effects of EO on RE. Further the study revealed that different configuration of DBMI and dimensions of EO and DBC can explain RE.

The study explains mechanism of RE from perspective of digitization. The conclusion is good for further consolidating strategic entrepreneurship theory, and providing a new frame for firms to build the ability of antifragile.

The purpose of this paper is to investigate how the information about haze, a term used in China to describe the air pollution problem, is portrayed on Chinese social media by different types of organizations using the theoretical framework of the health belief model (HBM).

A content analysis was conducted based on the 756 posts retrieved from Sina Weibo, the top microbloging platform in China, following the simple random sampling method. χ2 analysis was conducted to examine the relationships across the three types of organizations (governmental organizations, non-governmental organizations, and corporations) and the use of the HBM concepts (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and cues to action) in terms of haze and its threat to health.

The results of this study indicated that corporations posted more Weibo messages categorized as perceived benefit and most of these posts are related to their products, while governmental organizations posted fewer Weibo messages categorized as perceived severity.

This study provides health decision makers and media consumers with knowledge about how to use social media more effectively in terms of haze-related issues.

Given the severity of air pollution and the influential role microblogging takes, the study aims to fill the gap in the limited literature on haze information dissemination on social media in China. In addition, this study aims to shed theoretical light on HBM as applied to a non-westernized context.

The purpose of this paper is to develop a kind of novel and high‐performance rheological additive, an eco‐friendly composite of anatase nano‐TiO₂ particles and xanthan gum (NTX), for interior wall coatings.

NTX was prepared through heating and refluxing the mixture of TiO₂ hydrosol and xanthan gum, and five interior wall coating samples were fabricated with different NTX contents. The morphology of nano‐TiO₂ hydrosol and NTX were characterised with TEM, and the stability and rheological properties of these coating samples were studied.

TEM images showed a core‐shell structure of NTX, and that nano‐TiO₂ particles in it were encapsulated by xanthan gum, which was anticipated to weaken Van der Waals force among nano‐TiO₂ particles thus preventing the aggregation of nano‐particles. All of the five coating samples were found to be non‐Newtonian pseudo‐plastic fluid, and showed excellent stability and thixotropic property.

This paper focused on the preparation, the characterisation of NTX additive and the study of the rheological behaviours of the coating samples with NTX. Some other aspects, such as coating durability, photocatalytic ability and film properties, will be studied in the future.

It was proven that NTX was an effective eco‐friendly rheological additive for interior wall coatings. Consequently, this paper threw light on developing eco‐friendly interior wall coatings.

A kind of novel and effective rheological additive was developed for interior wall coatings in the study reported in the paper. A method was also developed to introduce functional nano‐particles into coating in a good dispersion state.

The purpose of this study was to research how the reassembly (remanufacturing assembly) achieves a quality that is not lower than original production with different precision remanufactured parts based on the integration of mechanics, mathematics (measurement uncertainty) and management (optional classification). Remanufactured product quality is the soul of the remanufacturing project.

First, this paper studies the recycled parts features and reassembly features. Then, we build the mathematical sub-model with remanufactured parts and dimensional precision, which is proven that optional classification can effectively improve the reassembly accuracy mathematically. The optimization model of optional classification for reassembly is proposed under the constraint of a dimensional chain, and the solutions are studied based on particle swarm optimization. Finally, this method is applied in a remanufacturing enterprise and achieves good results.

The method can reduce the cost of quality loss and improve the quality of remanufactured products.

It provides a new solution and idea for reassembly with different precision remanufactured parts and promotes the healthy development of reverse logistics with a high level of customer satisfaction. This method can maximize the use of different levels of quality remanufactured parts and improve reassembly accuracy by mathematical proofs and examples.

High reliability and high power-to-weight ratio are the technical difficulties in the development of aviation piston heavy fuel engines. This paper aims to provide a design evaluation method of the aero piston engine block, which can help R&D personnel quickly evaluate the performance of engine block, including effective bearing capacity and fatigue deformation, save a lot of experimental time and shorten the R&D cycle.

In this paper, structural efficiency is used to evaluate the reliability and durability of the engine block. Structural efficiency is a new evaluation method that lists its corresponding connotation according to different objects. In this paper, the function of the engine block in the engine is explained in detail, and three quantifiable connotations of the structural efficiency of the engine block are put forward. In the subsequent calculation, the calculation is carried out according to the three indexes, and the calculation results are used as the indexes to evaluate the performance of the engine block.

The structural efficiency evaluation method proposed in this paper can quickly and effectively evaluate the performance of the block from many aspects. Under the same boundary conditions, the two design schemes are simulated and analyzed, and the durability test is carried out. The analysis and experimental results show that Scheme 2 has good performance, which verifies the feasibility of the evaluation method.

This paper provides a method for rapid evaluation of engine block performance.

Rotating machineries are widely used in manufacturing, petroleum, chemical, aircraft, and other industries. To accurately identify the operating conditions of such rotating machineries, this paper aims to propose a fault diagnosis method based on sensitive dimensionless parameters and particle swarm optimization (PSO)–support vector machine (SVM) for reducing the unexpected downtime and economic losses.

A relatively new hybrid intelligent fault classification approach is proposed by integrating multiple dimensionless parameters, the Fisher criterion and PSO–SVM. In terms of data pre-processing, a method based on wavelet packet decomposition (WPD), empirical mode decomposition (EMD) and dimensionless parameters is proposed for the extraction of the vibration signal features. The Fisher criterion is applied to reduce the redundant dimensionless parameters and search for the sensitive dimensionless parameters. Then, PSO is adapted to optimize the penalty parameter and kernel parameter for SVM. Finally, the sensitive dimensionless parameters are classified with the optimized model.

As two different time–frequency analysis methods, a method based on a combination of WPD and EMD used to extract multiple dimensionless parameters is presented. More vital diagnosis information can be obtained from the vibration signals than by only using a single time–frequency analysis method. Besides, a fault classification approach combining the sensitive dimensionless parameters and PSO-SVM classifier is proposed. The comparative experiment results show that the proposed method has a high classification accuracy and efficiency.

To the best of the authors’ knowledge, very few efforts have been performed for fault classification using multiple dimensionless parameters. In this paper, eighty dimensionless parameters have been studied intensively, which provides a new strategy in fault diagnosis field.