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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.

The purpose of this paper is to deal with the practical challenge faced by modern logistics enterprises to accurately evaluate driving performance with high computational efficiency under the disturbance of road smoothness and to identify significantly associated performance influence factors.

The authors cooperate with a logistics server (G7) and establish a driving grading system by constructing real-time inertial navigation data-enabled indicators for both driving behaviour (times of aggressive speed change and times of lane change) and road smoothness (average speed and average vibration times of the vehicle body).

The developed driving grading system demonstrates highly accurate evaluations in practical use. Data analytics on the constructed indicators prove the significances of both driving behaviour heterogeneity and the road smoothness effect on objective driving grading. The methodologies are validated with real-life tests on different types of vehicles, and are confirmed to be quite effective in practical tests with 95% accuracy according to prior benchmarks. Data analytics based on the grading system validate the hypotheses of the driving fatigue effect, daily traffic periods impact and transition effect. In addition, the authors empirically distinguish the impact strength of external factors (driving time, rainfall and humidity, wind speed, and air quality) on driving performance.

This study has good potential for providing objective driving grading as required by the modern logistics industry to improve transparent management efficiency with real-time vehicle data.

This study contributes to the existing research by comprehensively measuring both road smoothness and driving performance in the driving grading system in the modern logistics industry.

Sparrow search algorithm (SSA) is a novel global optimization method, but it is easy to fall into local optimization, which leads to its poor search accuracy and stability. The purpose of this study is to propose an improved SSA algorithm, called levy flight and opposition-based learning (LOSSA), based on LOSSA strategy. The LOSSA shows better search accuracy, faster convergence speed and stronger stability.

To further enhance the optimization performance of the algorithm, The Levy flight operation is introduced into the producers search process of the original SSA to enhance the ability of the algorithm to jump out of the local optimum. The opposition-based learning strategy generates better solutions for SSA, which is beneficial to accelerate the convergence speed of the algorithm. On the one hand, the performance of the LOSSA is evaluated by a set of numerical experiments based on classical benchmark functions. On the other hand, the hyper-parameter optimization problem of the Support Vector Machine (SVM) is also used to test the ability of LOSSA to solve practical problems.

First of all, the effectiveness of the two improved methods is verified by Wilcoxon signed rank test. Second, the statistical results of the numerical experiment show the significant improvement of the LOSSA compared with the original algorithm and other natural heuristic algorithms. Finally, the feasibility and effectiveness of the LOSSA in solving the hyper-parameter optimization problem of machine learning algorithms are demonstrated.

An improved SSA based on LOSSA is proposed in this paper. The experimental results show that the overall performance of the LOSSA is satisfactory. Compared with the SSA and other natural heuristic algorithms, the LOSSA shows better search accuracy, faster convergence speed and stronger stability. Moreover, the LOSSA also showed great optimization performance in the hyper-parameter optimization of the SVM model.

During the coronavirus disease 2019 (COVID-19) pandemic, ubiquitous social media has become a primary channel for information dissemination, social interactions and recreational activities. However, it remains unclear how social media usage influences nonpharmaceutical preventive behavior of individuals in response to the pandemic. This paper aims to explore the impacts of social media on COVID-19 preventive behaviors based on the theoretical lens of empowerment.

In this paper, survey data has been collected from 739 social media users in China to conduct structural equation modeling (SEM) analysis.

The results indicate that social media empowers individuals in terms of knowledge seeking, knowledge sharing, socializing and entertainment to promote preventive behaviors at the individual level by increasing each person's perception of collective efficacy and social cohesion. Meanwhile, social cohesion negatively impacts the relationship between collective efficacy and individual preventive behavior.

This study provides insights regarding the role of social media in crisis response and examines the role of collective beliefs in the influencing mechanism of social media. The results presented herein can be used to guide government agencies seeking to control the COVID-19 pandemic.

This paper aims to investigate the corrosion kinetics and corrosion behavior of NdFeB magnets with the addition of heavy rare earth dysprosium (Dy) for its inhibitory activity on poor corrosion resistance of NdFeB magnets.

To study the effect of dysprosium addition on corrosion behavior of NdFeB magnets and investigate its mechanism, potentiodynamic polarization, scanning electron microscopy (SEM), electrochemical impedance, energy dispersion spectrum (EDS) and scanning Kelvin probe force microscopy (SKPFM) were applied in the research. Besides, microstructures were observed by SEM equipped with EDS. Atomic force microscopy was introduced to analyze the morphology, potential image as well as the contact potential difference. The SKPFM mapping scan was applied to obtain the contact potential around Nd-rich phase at 0.1 Hz. The magnets were detected via X-ray diffraction.

Substitution of Nd with Dy led to improvement of corrosion resistance and reduced the potential difference between matrix and Nd-rich phase. Corrosion resistance is Nd-rich phase < the void < metal matrix; maximum potential difference between matrix and Nd-rich phase of Dy = 0, Dy = 3 and Dy = 6 Wt.% is 411.3, 279.4 and 255.8 mV, respectively. The corrosion rate of NdFeB magnet with 6 Wt.% Dy is about 67% of that without Dy at steady corrosion stage. The addition of Dy markedly enhanced the corrosion resistance of NdFeB magnets.

This research innovatively investigates the effect of adding heavy rare earth Dy to NdFeB permanent magnets on magnetic properties, as well as their effects on microstructure, phase structure and most importantly on corrosion resistance. Most scholars are studying the effect of element addition on magnetic properties but not on corrosion resistance. This paper creatively fills this research gap. NdFeB magnets are applied in smart cars, robotics, AI intelligence, etc. The in-depth research on corrosion resistance by adding heavy rare earths has made significant and outstanding contributions to promoting the rapid development of the rare earth industry.

This first chapter is the introduction to the book. The purpose of this book is to address and better understand why China tightly embraces modern sport in contemporary times. Some view this as an indicator of glocalisation and a result of Western industrial civilization putting pressure on China to showcase their strengths as a nation. Some important considerations to explore are China's mediated ability to play and compete with the west. Sport is also seen as a channel of observing global political and economic challenges, especially those in the current context of the COVID-19 pandemic and the intense tensions between communities, which certainly inspires further academic development. Given China's recently remarkable achievements in sport, it is high time to show the world more inside stories of sport development across the nation. The contributors of this collection bring foundational Chinese context to each chapter as they examine changing sport cultures at different scales.

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

The growing literature does not highlight the impact of high-performance work systems (HPWSs) on employee psychological well-being. This study aimed to test this influence by exploring the mediation of psychosocial safety and the moderation of supervisor support to overcome knowledge gaps in optimizing productivity in an increasingly dynamic workplace.

This study involved 395 service employees in Indonesia. Data were analyzed using the PROCESS macro approach.

The research findings indicate that while HPWS are perceived as organizational investments by employees, they do not directly impact employees’ psychological well-being in the service sector in Indonesia. Despite previous literature suggesting a positive relationship, this study emphasizes the importance of considering factors such as psychosocial safety and supervisor support in influencing employee perceptions.

This study extends the existing literature on the mechanisms of HPWS in promoting psychological well-being in the workplace. Furthermore, Psychological safety has also been identified as a strategic approach to reduce workplace bullying.

Organizations should prioritize creating a work environment that considers psychosocial safety and provides adequate supervisor support to enhance employees’ psychological well-being. Understanding the unique needs and perceptions of employees, including factors such as age and gender, is crucial in designing effective HPWS that foster a positive workplace culture and mitigate potential negative impacts.

The authors seek to explore the not yet fully understood relationship between HPWS, psychosocial safety, and supervisor support in promoting employee psychological well-being. This research also provides a broader view of how to prevent employees from feeling pressured and stressed in the workplace.

The post-COVID-19 era is characterised in the professional field by a deterioration in the psychological health of employees and by “The Great Resignation”. These phenomena require managers to rethink both organisational and HR strategies to protect their workers’ health, to retain them in their job and, in fine, to ensure the sustainability of the organisation. However, studies have demonstrated that high performance work systems (HPWS), which are currently the dominant approach in human resource management, are related to an intensification of work and consequently a deterioration of employees’ health (conflicting outcomes perspective). At the same time, workers’ well-being has been shown to be associated with numerous organisational outcomes, such as individual performance. However, relatively few articles have investigated win–win organisational practices or programmes that promote the well-being and consequently performance of workers. These include virtuous organisational practices (VOPs), which specifically aim to enhance employees’ well-being, considered not as a means to an end, but as an end in itself (mutual gains perspective). This paper aims to develop the general hypothesis that VOPs could increase employees’ performance by protecting their health and thus offer an alternative to HPWS.

We review relevant current research on psychological well-being and work performance and present innovative systems of organisational practices such as VOPs that create psychologically healthy workplaces and enhance workers’ optimal functioning (well-being and performance).

Based on theoretical arguments and empirical studies, we hypothesise that alternative practices such as VOPs can increase employees’ performance while protecting their health and encouraging them to stay in the organisation.

After this review, we discuss future avenues for research to encourage the scientific community to test this hypothesis.

Finally, we make a number of specific recommendations about how to (1) appraise, design and implement VOPs, (2) enhance organisational communication and managerial adherence to VOPs, and (3) train managers in R.I.G.H.T leadership behaviours.

Presentation of an original approach in this research field: the VOPs.