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The velocity head is usually neglected in the energy equation for a pipeline junction when one-dimensional (1D) hydraulic transient flow is solved by method of characteristics. The purpose of this paper is to investigate the effect of velocity head on filling transients in a branched pipeline by an energy equation considering velocity head.

An interface tracking method is used to locate the air–water interface during pipeline filling. The pressured pipe flow is solved by a method of characteristics. A discrete gas cavity model is included to permit the occurrence of column separation. A universal energy equation is built by considering the velocity head. The numerical method is provisionally verified in a series pipeline and the numerical results and experimental data accord well with each other.

The numerical results show that some differences in filling velocity and piezometric head occur in the branched pipeline. These differences arise because the velocity head in the energy equation can become an important contributor to the hydraulic response of the system. It is also confirmed that a local high point in the profile is apt to experience column separation during rapid filling. Significantly, the magnitude of overpressure and cavity volume induced by filling transients at the local high point is predicted to increase with the velocity in the pipes.

The velocity head in the energy equation for a pipeline junction could play an important role in the prediction of filling velocity, piezometric head and column separation phenomenon, which should be given more attention in 1D hydraulic transient analysis.

This paper aims to report and analyze the lessons learnt from a case study of the implementation of the move from onsite to online learning at a Sino-Foreign higher education institution.

This paper reports a case study based on an analysis of three elements of the move to digital education during the COVID-19 pandemic. In suggesting three elements, it argues that the first and most immediate move away from onsite teaching should be thought of as emergency response teaching, and it is the lessons learnt from this vital and necessary stage that have informed the subsequent implementation of a more digitalization process.

The case study identifies the journey that the university is going through to deliver digitalized education, and how the pandemic hastened what had already been started. It illustrates how the pandemic has been useful in highlighting where we are, what decisions have been made and what still needs to be done with regard to readiness for the disruption likely by Industry 4.0.

The study was conducted at one institution, which along with eight other similar institutions is unique within China. Findings, especially the processes of making decisions, while relevant to the wider discussion on digitalization and Industry 4.0, should also be considered in this light.

While the focus of the paper is on COVID-19 and Rapid Digitalization of Learning and Teaching, the main implication is that universities need to better prepare their teaching staff for digitalized education, especially if they are wanting to engage with disruption brought about by Industry 4.0.

The paper is based on a single university case study of a rather unique university within China. The discussion illustrates the need for flexibility and decisiveness in making key decisions on managing disruption, but with strategic direction in mind, illustrated in the study by COVID-19, but with future digitalization initiatives also to the fore.

Employees’ bootlegging innovation behavior is common and plays an important role in enterprise management. Based on the resource conservation theory and self-regulation theory, the purpose of this study is to explore the influence mechanism of leaders’ abusive supervision on employees’ bootlegging innovation behavior, with psychological safety as a mediator and mindfulness at workplace as a moderator.

Survey data were gathered from 591 employees’ self-assessment questionnaires in China. Hierarchical regression analysis was used to test the research model through SPSS and AMOS.

This study found that the leaders’ abusive supervision negatively affects employees’ bootlegging innovation behavior; employees’ psychological safety completely mediates the negative effect of leaders’ abusive supervision on employees’ bootlegging innovation behavior; and mindfulness at work moderates the influence of leaders’ abusive supervision on employee’ bootlegging innovation behavior, as well as the influence of leaders’ abusive supervision on employees’ psychological safety.

This study has significant implications in passive leadership that affect employees’ innovation. Authors found that leaders’ abusive supervise, mindfulness at workplace play a crucial role in employees’ bootleg innovation through psychological safety.

Theoretically, this study has enriched the antecedent research on employees’ bootlegging innovation behavior from the perspective of negative leadership behavior and employee psychology. And this study considered mindfulness at workplace as a boundary condition.

Disinformation on social media is a serious issue. This study examines the effects of disinformation on COVID-19 vaccination decision-making to understand how social media users make healthcare decisions when disinformation is presented in their social media feeds. It examines trust in post owners as a moderator on the relationship between information types (i.e. disinformation and factual information) and vaccination decision-making.

This study conducts a scenario-based web survey experiment to collect extensive survey data from social media users.

This study reveals that information types differently affect social media users' COVID-19 vaccination decision-making and finds a moderating effect of trust in post owners on the relationship between information types and vaccination decision-making. For those who have a high degree of trust in post owners, the effect of information types on vaccination decision-making becomes large. In contrast, information types do not affect the decision-making of those who have a very low degree of trust in post owners. Besides, identification and compliance are found to affect trust in post owners.

This study contributes to the literature on online disinformation and individual healthcare decision-making by demonstrating the effect of disinformation on vaccination decision-making and providing empirical evidence on how trust in post owners impacts the effects of information types on vaccination decision-making. This study focuses on trust in post owners, unlike prior studies that focus on trust in information or social media platforms.

Thermopile infrared (IR) detectors are one of the most important IR devices. Considering that the surface area of conventional four-end-beam (FEB)-based thermopile devices cannot be effectively used and the performance of this type of devices is relatively low, this paper aims to present a double-end-beam (DEB)-based thermopile device with high duty cycle and performance. The paper aims to discuss these issues.

Numerical analysis was conducted to show the advantages of the DEB-based thermopile devices.

Structural size of the DEB-based thermopiles may be further scaled down and maintain relatively higher responsivity and detectivity when compared with the FEB-based thermopiles. The authors characterized the thermoelectric properties of the device proposed in this paper, which achieves a responsivity of 1,151.14 V/W, a detectivity of 4.15 × 108 cm Hz1/2/W and a response time of 14.46 ms sensor based on DEB structure.

The paper proposed a micro electro mechanical systems (MEMS) thermopile infrared sensor based on double-end-beam structure.

By utilizing boundary theory and distraction–conflict theory, this study attempted to examine the influential process of supportive teleworking practices granting work scheduling autonomy on work-to-family conflict (WFC) via the mediating mechanism of work interruption initiated from home.

The study conducted two-wave online questionnaire survey to obtain a final sample of 277 remote knowledge workers in Taiwan during the peak period of COVID-19 pandemic. Hypotheses were tested with partial least squares-structural equation modelling using SmartPLS 3.0 software.

The results revealed that supportive teleworking practices did not directly decrease the level of WFC while home-sourced work interruptions fully mediated the negative relationship between supportive teleworking practices and WFC.

This provides a more nuanced explanation for how and why supportive teleworking practices are beneficial for employees to cope with the challenge of work–home interferences under the new ways of working. The findings simultaneously address evidence-based practices to better deal with mandatory teleworking during potential societal crisis beyond the COVID-19 pandemic.

In traditional calibration methods of kinematics parameters of industrial robots, dozens of model parameters are identified together based on an optimization procedure. Due to different contributions of model parameter errors to the tool center point positioning error of industrial robots, obtaining good results for all model parameters is very difficult. Therefore, the purpose of this paper is to propose a sequential calibration method specifically for transmission ratio parameters, which includes reduction ratios and coupling ratios of industrial robot joints.

The ABB IRB 1410 industrial robot is considered as an example in this study. The transmission ratios for each joint of the robot are identified using the spatial circle fitting method based on spatial vectors, which fit the center and radius of joint rotation with the least squares optimization algorithm. In addition, a method based on the Rodrigues’ formula is designed and presented for identifying the actual coupling ratio of the robot. Subsequently, an experiment is carried out to verify the proposed sequential calibration method of transmission ratios.

In this experiment, the actual positions of the linkages before and after joint rotations are measured by a laser tracker. Accurate results of the reduction ratios and the coupling ratios are calculated, and the results are verified experimentally. The results show that by calibrating the reduction ratios and coupling ratios of the ABB robot, the rotation angle errors of the robot joints can be reduced.

The authors propose a sequential calibration method for transmission ratio parameters, including reduction ratios and coupling ratios of industrial robot joints. An experiment is carried out to verify this proposed sequential calibration method. This study may be beneficial for calibrating the kinematic parameters of industrial robots and improving their positioning accuracy.

This study aims to investigate the safety effects of work zone advisory systems. The traditional system includes a dynamic message sign (DMS), whereas the advanced system includes an in-vehicle work zone warning application under the connected vehicle (CV) environment.

A comparative analysis was conducted based on the microsimulation experiments.

The results indicate that the CV-based warning system outperforms the DMS. From this study, the optimal distances of placing a DMS varies according to different traffic conditions. Nevertheless, negative influence of excessive distance DMS placed from the work zone would be more obvious when there is heavier traffic volume. Thus, it is recommended that the optimal distance DMS placed from the work zone should be shortened if there is a traffic congestion. It was also revealed that higher market penetration rate of CVs will lead to safer network under good traffic conditions.

Because this study used only microsimulation, the results do not reflect the real-world drivers’ reactions to DMS and CV warning messages. A series of driving simulator experiments need to be conducted to capture the real driving behaviors so as to investigate the unresolved-related issues. Human machine interface needs be used to simulate the process of in-vehicle warning information delivery. The validation of the simulation model was not conducted because of the data limitation.

It suggests for the optimal DMS placement for improving the overall efficiency and safety under the CV environment.

A traffic network evaluation method considering both efficiency and safety is proposed by applying traffic simulation.

The purpose of this paper is to provide some insights on the interplay of organizational climate and job satisfaction, taking personality traits as a moderator.

The paper reviews the extant literature from which it develops a theoretical model which is then tested empirically in the Malaysian context, using hierarchical regression methodology.

The results imply that there are moderating effects of personality traits on the relationship between certain aspects of organizational climate and job satisfaction.

The cross-sectional nature of this study inhibits the testing of causality between the variables. The research model and hypotheses were tested, using data drawn only from companies operating in a single country.

The paper provides valuable information to leaders and managers in understanding which personality works better in the potential casual linkage between organizational climate and overall job satisfaction. This paper also helps practitioners to understand better why the same climate can have different impacts on different people.

It contributes to the conceptualization of the organizational climate by emphasizing Litwin and Stringer’s (1968) dimensions of organizational climate as the important determinants of the job satisfaction. Moreover, it expands the traditional discussion by incorporating the personal traits that moderates the relationship between organizational climate and the job satisfaction.

The purpose of this paper is to propose an availability modeling method of complex multiple units system (CMUS) based on the multi-agent technique.

Based on the multi-agent technique, this paper describes the availability model structure for CMUS and develops agent-based models of components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff, as well as the communication method among the different agents. On the basis of the agent-based availability modeling theory, the availability simulation scheme of CMUS is given using MATLAB. Thus, the availability modeling theory of CMUS and its simulation method are developed. To demonstrate the applicability of the proposed availability modeling method, a numerical example is given.

The proposed agent-based modeling method is applicable to availability modeling of CMUS, including the modeling of component failure, maintenance tools/fields/staff, maintenance policy, and structural/economic dependence among components.

As a bottom-top, modular, expandable, and reusable modeling theory, the agent-based modeling method might be useful for availability modeling of different CMUSs in reality.

The multi-agent technique is introduced into availability modeling of multi-component systems in this paper. Thus, it is possible to model failure of many components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff together for availability analysis of complex systems of equipment.