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This study aims to investigate the noise-inducing characteristics during the start-up process of a mixed-flow pump and the impact of different start-up schemes on pump noise.

This study conducted numerical simulations on the mixed-flow pump under different start-up schemes and investigated the flow characteristics and noise distribution under these schemes.

The results reveal that the dipole noise is mainly caused by pressure fluctuations, while the quadrupole noise is mainly generated by the generation, development and breakdown of vortices. Additionally, the noise evolution characteristics during the start-up process of the mixed-flow pump can be divided into the initial stage, stable growth stage, impulse stage and stable operation stage.

The findings of this study can provide a theoretical basis for the selection of start-up schemes for mixed-flow pumps, reducing flow noise and improving the operational stability of mixed-flow pumps.

For underwater hydraulic machinery, the unique structure significantly enhances the three-dimensional non-uniformity of turbulence within the flow domain and high Reynolds number turbulence introduces complex effects on the machinery. Therefore, studying the turbulent flow characteristics in underwater hydraulic machinery is crucial for system stability.

This paper conducts a numerical analysis on a specific type of underwater hydraulic machinery. A numerical calculation model is established under stable inflow conditions to analyze the flow trends and pressure changes at different flow speeds. Subsequently, structural modifications are made to the underwater hydraulic machinery, and the characteristics of the velocity field, pressure field and vorticity distribution under different model parameters are analyzed.

The results indicate that changes in internal structure have a certain impact on flow characteristics. When the structural changes are significant, the fluid flow becomes more complex and pressure fluctuations become more intense. The research findings provide a scientific basis and theoretical guidance for the structural design of underwater hydraulic machinery and have significant research implications for controlling fluid-induced noise.

Affected by the inherent structural characteristics of the flow channel structure, the flow direction of the high-speed water flow changes drastically in the flow channel, so it is of great significance to study its flow characteristics for the stability of the system.

This study tested a holistic model that investigated the interaction effect of negative mentoring experiences and moqi (pronounced “mò-chee”) with a mentor—where moqi refers to a situated state between two parties in which one party understands and cooperates well with the other party without saying a word—on the protégés’ turnover intention, along with the mediating role of protégés’ harmonious work passion.

Data were collected from 281 protégés through a three-wave questionnaire survey with a 1-month lag between waves. We used a hierarchical multiple regression and bootstrapping analysis to test our hypotheses.

Our results support the mediating effect of harmonious work passion on the positive relationship between protégés’ negative mentoring experiences and turnover intention. In addition, our analysis confirmed that moqi with the mentor amplifies both the impact of protégés’ negative mentoring experiences on harmonious work passion and the indirect effect of negative mentoring experiences on protégés’ turnover intention via harmonious work passion.

By demonstrating the interaction effect of protégés’ negative mentoring experiences and moqi with their mentor on turnover intention, as well as the mediating role of harmonious work passion, this study expands our understanding of the mechanism and boundary condition of the effect of negative mentoring experiences and provides inspiration and guidance for mentoring practices.

This paper aims to study the oxidation kinetics of the nanocrystalline Al ultrathin films. The influence of structure and composition evolution during thermal oxidation will be observed. The reason for the change in the oxidation activation energy on increasing the oxidation temperature will be discussed.

Al thin films are deposited on the silicon wafers as substrates by vacuumed thermal evaporation under the base pressure of 2 × 10⁻⁴ Pa, where the substrates are not heated. A crystalline quartz sensor is used to monitor the film thickness. The film thickness varies in the range from 30 to 100 nm. To keep the silicon substrate from oxidation during thermal oxidation of the Al film, a 50-nm gold film was deposited on the back side of silicon substrate. Isothermal oxidation studies of the Al film were carried out in air to assess the oxidation kinetics at 400-600°C.

The activation energy is positive and low for the low temperature oxidation, but it becomes apparently negative at higher temperatures. The oxide grains are nano-sized, and γ-Al₂O₃ crystals are formed at above 500°C. In light of the model by Davies, the grain boundary diffusion is believed to be the reason for the logarithmic oxidation rate rule. The negative activation energy at higher temperatures is apparent, which comes from the decline of diffusion paths due to the formation of the γ-Al₂O₃ crystals.

It is found that the oxidation kinetics of nanocrystalline Al thin films in air at 400-600°C follows the logarithmic law, and this logarithmic oxidation rate law is related to the grain boundary diffusion. The negative activation energies in the higher temperature range can be attributed to the formation of γ-Al₂O₃ crystal.

Since its inception in 2009, the growth of real-time bidding (RTB) advertising has been dramatic. Yet, there is a dearth of research in the information system (IS) literature despite the potential for negative e-commerce outcomes. The purpose of this paper is to identify salient antecedents of users’ attitude toward RTB advertisements.

A research model was constructed and tested with data from 437 respondents. SmartPLS 3.0, a partial least square (PLS) structural equation modeling (SEM) tool, was used to evaluate the research model and test the hypotheses.

The findings indicate that user attitude is determined by opposing influences from the cognitive and affective attributes of an RTB advertisement. A surprise is found to elicit greater perception of advertisement personalization, timeliness and relevance, as well as privacy and intrusiveness concerns. While RTB advertisement relevance appears to lessen the effect of advertisement intrusiveness, privacy concern is exacerbated when the advertisement is more personalized. The authors discuss the implications of this study for click-through intentions and e-commerce.

At this point in the evolution of RTB advertising, the findings indicate that the surprise generated by the appearance of an RTB advertisement is not currently a “bad” surprise. In addition, the formation of positive user attitude toward RTB is complex because cognitive factors interact with users' concerns to strengthen or weaken the negative effects. The authors also demonstrate that attitude and stimulus–organism–response (S–O–R) theories are useful theoretical bases for the development of causal models to predict RTB attitude and click-through intentions.

The purpose of this paper is to build a transient wear prediction model of surface topography of textured work roll, and then to investigate the wear performance of different original textured surfaces. The surface topography of steel sheets is one of the most important surface quality indexes, which is inherited from the textured work rolls in cold rolling. Surface topography of work roll is obviously changing in the cold rolling process. However, surface topography is difficult to measure in the industry production process.

This paper presents a numerical approach to simulate the wear process based on the mixed lubrication model of cold rolling interface developed by Wilson and Sheu (Sheu and Wilson, 1994). It is assumed that wear takes place at locations where the surfaces are in direct contact, and the volume is removed by an abrasive particle which is an abstract concept based on the wear phenomenon of textured work roll. At each simulation cycle, the distribution of the contact pressure is calculated by the lubrication model. The material is removed by an abstract abrasive particle and the surface topography is modified correspondingly. The renewed surface topography is then used for the next cycle.

Through comparative analysis, it can be found that the simulation results possess similar statistical characteristic with the measured data. A set of roughness parameters such as the amplitude, spacing and frequency-domain characteristics are introduced to analyze the wear performance of different textured surfaces. Numerical examples show that the surface topography has a significant effect on the wear performance of work roll in cold rolling.

The proposed model can accurately predict the wear process of the surface topography in the cold rolling process, which provides the foundation for optimization of original surface topography of textured work roll. The model can also be considered as a tool applicable for research on control of the surface topography of steel strip in the cold rolling process.

As an important participant in capital market, institutional investors play a principal role in improving corporate governance. Most existing studies have focused on institutional ownership and its economic consequences. Nevertheless, they have not provided sufficient insight on the governance behavior of institutional investors as well as the underlying incentive mechanism. This paper aims to analyze the governance role of institutional investors in information disclosure and provide related evidence.

The authors propose a novel theory to analyze the institutional investors’ behavior of active governance and shows that such behavior significantly improves the quality of corporate information disclosure. The authors then conduct an empirical test by using the hand-collected data of institutional investors’ corporate visits during 2009-2014 in ChiNext.

This paper finds that the firms visited by institutional investors are more likely to have a greater tendency of disclosing more information than the firms that have never been visited. In particular, a higher frequency of visits or a larger number of participating institutional investors leads to a higher degree of disclosure. Consistent with the notion that on-site visits endow institutional investors with more frequent and active interaction with the firms, the authors find that the results are stronger for firms which are visited on-site, when compared with other information acquisition activities such as online meetings, conference calls and investor meetings. In addition, the effect of a site visit is greater when the site visit is conducted by securities companies or funds rather than insurance companies or QFIIs. Finally, the test of the direction of causality suggests that visits conducted by institutional investors leads to more information disclosure, rather than the reverse. Collectively, these results show that institutional investors’ participation enhances corporate information disclosure.

This paper explores the internal mechanism that institutional investors affect corporate governance by improving information disclosure through their corporate visits. This is the first study to investigate the influence of institutional investors’ corporate visits and their economic consequences.

The accurate prediction of driving torque demand is essential for the development of motion controllers for mobile robots on complex terrains. This paper aims to propose a hybrid model of torque prediction, adaptive EC-GPR, for mobile robots to address the problem of estimating the required driving torque with unknown terrain disturbances.

An error compensation (EC) framework is used, and the preliminary prediction driving torque value is achieved using Gaussian process regression (GPR). The error is predicted using a continuous hidden Markov model to generate compensation for the prediction residual caused by terrain disturbances and uncertainties. As the final step, a gain coefficient is used to adaptively tune the significance of the compensation term through parameter resetting. The proposed model is verified on a sample set, including the driving torque of a mobile robot on three different sandy terrains with two driving modes.

The results show that the adaptive EC-GPR yields the highest prediction accuracy when compared with existing methods.

It is demonstrated that the proposed model can predict the driving torque accurately for mobile robots in an unconstructed environment without terrain identification.

Previous research has generally assumed that a homogeneous cultural value exists within a given country. This research aims to identify the regional differences in cultural value based on an urbanization dimension in China, which generate diversity with regard to perceived value and consumer decision‐making styles.

A large‐scale questionnaire was administered to freshmen from major colleges and universities across China to measure cultural value, perceived value, and consumer decision‐making style. The data were analyzed with a multi‐group structural equation model and a stepwise discrimination test.

Results demonstrated significant differences in cultural value, perceived value and consumer decision‐making style among regions with different degrees of urbanization and revealed antecedents and formation of the mechanism of decision‐making style.

Future research should explore more antecedents that influence consumer decision‐making styles and other market dimensions other than urbanization.

The research might provide prominent guidelines for marketers to understand Chinese consumers. Specifically, in regions with different degrees of urbanization, marketers should develop differential strategies to exploit the market given the distinctions in cultural value, perceived value and consumer decision‐making styles.

This study is the first to build a theoretical relational model of cultural value, perceived value and consumer decision‐making styles. And this model revealed the antecedents and formation of the mechanism of decision‐making style.

The purpose of this study is to develop a modified parameter identification method and a novel measurement method to calibrate a 3 degrees-of-freedom (3-DOF) parallel tool head. This parallel tool head is a parallel mechanism module in a five-axes hybrid machine tool. The proposed parameter identification method is named as the Modified Singular Value Decomposition (MSVD) method. It aims to overcome the difficulty of choosing the algorithm parameter in the regularization identification method. The novel measurement method is named as the vector projection (VP) method which is developed to expand the measurement range of self-made measurement implements.

Newton Iterative Algorithm based on Least Square Method is analyzed by using the Singular Value Decomposition method. Based on the analysis result, the MSVD method is proposed. The VP method transforms the angle measurement into the displacement measurement by taking full advantage of the ability that the 3-DOF parallel tool head can move in the X – Y plane.

The kinematic calibration approach is verified by calibration simulations, a Rotation Tool Center Point accuracy test and an experiment of machining an “S”-shaped test specimen.

The kinematic calibration approach with the MSVD method and VP method could be successfully applied to the 3-DOF parallel tool head and other 3-DOF parallel mechanisms.