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The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

Mentoring was considered as an efficient way to facilitate staff attachment with hotels. Such a strong attachment has been demonstrated to reduce employees’ intention to quit. This study aims to investigate the mediating roles of organizational and occupational embeddedness in the relationships between mentoring functions and turnover intention.

The responses were collected from a sample of 354 employees in four hotels group across three Chinese provinces. A structural equation model (SEM) was applied to test the model and mediating roles of organizational and occupational embeddedness.

The results of SEM suggest that both organizational and occupational embeddedness mediated the relationships between mentoring functions (career and psychosocial support) and turnover intention. Specifically, employees who are able to receive successful mentoring can easily embed in their organization and occupation. Thus, these employees are reluctant to leave.

Although this study reveals the important role of mediation, it has several limitations. First, the data drawn from Hebei, Beijing and Zhejiang provinces may lack geography representativeness. Second, this paper neglects potential moderating role of certain personal or context factors. Third, the time lag between the three data collections are not the same.

Managers should retain proper employees by introducing mentoring programs. Furthermore, to increase organizational and occupational embeddedness, managers should also consider the person-organization/occupation attachments of this industry.

This study tests organizational and occupational embeddedness simultaneously as mediators between mentoring and turnover intention through data obtained from the Chinese hotels.

The purpose of this paper is to find a novel optimization selection method for hyper‐parameter of support vector classification (SVC), responsible for the classification of datasets from the UCI machine learning database repository.

A novel two‐stage optimization selection method for hyper‐parameters is proposed. It makes use of explicit information derived from issues and implicit knowledge extracted from the evolution process so as to improve the performance of classifier. In the first stage, the search extent of each hyper‐parameter is determined according to the requirements of issues. In the second stage, optimal hyper‐parameters are obtained by adaptive chaotic culture algorithm in the above search extent. Adaptive chaotic cultural algorithm uses implicit knowledge extracted from the evolution process to control mutation scale of chaotic mutation operator. This algorithm can ensure the diversity of population and exploitation in the latter evolution.

The rationality of the above optimization selection method is proved by the binary classification problem. Final confirmation of this approach is the classification results compared with other methods.

This optimization selection method can effectively avoid premature convergence and lead to better computation stability and precision. It is not related on the structure of functions. SVC model corresponding to optimal hyper‐parameters by this method has better generalization.

The purpose of this paper is to present a novel nitrile butadiene rubber (NBR) packaging structure, which can solve the problems of the low sensitivity, narrow frequency band and fluctuating frequency response curve of the MEMS bionic vector hydrophone.

A 0.05-mm-thick NBR sound-transparent cap was designed by theoretical analysis and simulation to reduce the signal attenuation caused by the packaging structure, and the frequency band of the hydrophone has been extended to 4 kHz. In this work, the vector hydrophone was fabricated by the MEMS technology and packaged with the NBR sound-transparent cap. The performance indicators were calibrated in the National Defence Underwater Acoustics Calibration Laboratory of China.

The results show that the sensitivity of NBR-packaged hydrophone reaches −170 dB (±2 dB), and the difference is less than 1 dB compared to bare chip. And the frequency band is 50 Hz-4 kHz. The hydrophone also has good directional pattern in the form of an 8-shape, and the pressure-resisting ability is more than 2 MPa.

The packaging structure significantly increases the sensitivity of the hydrophone and broadens the frequency band, providing a new method in the packaging design for MEMS hydrophone.

Cyberbullying is a globally pervasive problem and not novel in academia. Previous studies mainly focussed on the features, consequences and technological management of cyberbullying. However, most of the studies took cyberbullying examples in the West, and some issues still need to be addressed in the Chinese context. Thus, this study investigates how participants use cyberbullying words and why they use them in that particular way in China.

This study uses content analysis to summarise the typical features of cyberbullying words, revealing a positive relationship between cyberbullying words and sentimental expressions. This paper also uses the questionnaire (N = 705) to explore the prevalence of cyberbullying among Chinese Internet users and to compare the gender differences in the cognition of cyberbullying words and involvement in cyberbullying, in line with the social cognitive theory.

This study stated that people prefer repetitively using offensive words to achieve cyberbullying goals. Interestingly, this study does not find obvious gender differences in cyberbullying roles and cyberbullying language use. However, it explained the relationship between cognition and the use of cyberbullying words from a gender perspective.

Theoretically, this study expands cyberbullying studies into a new cultural environment, pointing to a novel term, “imbalanced relation,” for exploring cyberbullying behaviours. This study highlights the significance of technology and education in detecting and preventing cyberbullying, suggesting that educators and social media platforms can directly predict and prevent cyberbullying through textual perspectives and individuals' cognition of cyberbullying.

This study aims to examine cyberbullying linguistic and emotional features and individual differences in cyberbullying behaviour in a high-context culture like China. Its values include comparing the differences between cyberbullying in China and cyberbullying in the West from the linguistic and cultural directions and reconsidering the “power imbalance” feature of cyberbullying.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

Through the scientific and reasonable evaluation of the site selection of the emergency material reserve, the optimal site selection scheme is found, which provides reference for the future emergency decision-making research.

In this paper, we have chosen three primary indicators and twelve secondary indicators to construct an assessment framework for the determination of suitable locations for storing emergency material reserves. By mean of the improved entropy weight-order relationship weight determination method, the evaluation model of kullback leibler-technique for order preference by similarity to an ideal solution (KL-TOPSIS) emergency material reserve location based on relative entropy is established. On this basis, 10 regional storage sites in Beijing are selected for evaluation.

The results show that the evaluation model of the location of emergency material reserve not only respects the objective knowledge, but also considers the subjective information of the experts, which makes the ranking result of the location of the emergency material reserve more accurate and reliable.

Firstly, the modification factor is added to the calculation formula of traditional entropy weight method to complete the improvement of entropy weight method. Secondly, the order relation analysis method is used to assign subjective weights to the indicators. The principle of minimum information entropy is introduced to determine the comprehensive weight of the index. Finally, KL distance and TOPSIS method are combined to determine the relative entropy and proximity degree of alternative solutions and positive and negative ideal solutions, and the scientific and effective of the method is proved by case study.

The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.

The step effect and support structure generated by the manufacturing process of fused deposition molding parts increase the consumables cost and decrease the printing quality. Multiorientation printing helps improve the surface quality of parts and reduce support, but path interference exists between the printing layer and the layers printed. The purpose of this study is to design printing paths between different submodels to avoid interference when build orientation changed.

Considering support constraint, build orientation sequence is designed for submodels decomposed by model topology. The minimum printing angle between printing layers is analyzed. Initial path through the oriented bounding box is planned and slice interference relationship is then detected according to the projection topology mapping. Based on the relationship matrix of multiorientation slice, feasible path is calculated by directed graph (DG). Final printing path is determined under support constraint and checked by minimum printing angle. The simulation model of the robotic arm is established to verify the accessibility of printing path under the constraint of support and slice.

The proposed method can reduce support structure, decrease volume error and effectively solve the interference problem of the printing path for multiorientation slice.

The method based on projection topology mapping greatly improves the efficiency of interference detection. A feasible path calculated through DGs ensures the effectiveness of the printing path with the constraint of support and slice.