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Information is presented in various modalities such as text and images, and it can quickly and widely spread on social networks and among the general public through key communication nodes involved in public opinion events. Therefore, by tracking and identifying key nodes of public opinion, we can determine the direction of public opinion evolution and timely and effectively control public opinion events or curb the spread of false information.

This paper introduces a novel multimodal semantic enhanced representation based on multianchor mapping semantic community (MAMSC) for identifying key nodes in public opinion. MAMSC consists of four core components: multimodal data feature extraction module, feature vector dimensionality reduction module, semantic enhanced representation module and semantic community (SC) recognition module. On this basis, we combine the method of community discovery in complex networks to analyze the aggregation characteristics of different semantic anchors and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations.

The experimental results show that compared with its variants and the baseline models, the MAMSC model has better recognition accuracy. This study also provides more systematic, forward-looking and scientific decision-making support for controlling public opinion and curbing the spread of false information.

We creatively combine the construction of variant autoencoder with multianchor mapping to enhance semantic representation and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations. On this basis, our constructed MAMSC model achieved the best results compared to the baseline models and ablation evaluation models, with a precision of 91.21%.

The contemporary view of museums differs markedly from the traditional perception of scattered institutions, with urbanization and globalization reshaping their definitions and functions. This chapter explores the evolving roles of museums, particularly within the context of smart city development, with a focus on China. The chapter employs a structured methodology, first examining the positive aspects of museums, including their role in safeguarding natural heritage, promoting social responsibility, and facilitating education. Conversely, it scrutinizes the negative influences on museums, such as political and colonial interventions that impact pedagogical practices. A significant aspect of the discussion is the intersection of museum education with smart and adult education, heralding a renaissance in museum learning. A case study on the Danxiashan Geo-Museum illustrates the integration of cultural and heritage institutions into smart city initiatives, serving as a prototype for future endeavors. The chapter underscores the importance of incorporating smart and adult education into museum initiatives, along with smart innovation projects involving local museums and heritage sites. The implications extend to next-generation smart cities, offering insights into their societal, economic, and developmental impacts in the Gulf Region. Museum education emerges as a crucial yet understudied component within the framework of smart cities and education, providing a lens for reimagining future educational paradigms. By embracing the resurgence of museum education and integrating socio-cultural changes, including the rise of heritage education, smart cities can enhance their educational and societal contributions nationally and globally.

Sufficient sample data are the necessary condition to ensure high reliability; however, there are relatively poor fatigue test data in the engineering, which affects fatigue life's prediction accuracy. Based on this, this research intends to analyze the fatigue data with small sample characteristics, and then realize the life assessment under different stress levels.

Firstly, the Bootstrap method and the principle of fatigue life percentile consistency are used to realize sample aggregation and information fusion. Secondly, the classical outlier detection algorithm (DBSCAN) is used to check the sample data. Then, based on the stress field intensity method, the influence of the non-uniform stress field near the notch root on the fatigue life is analyzed, and the calculation methods of the fatigue damage zone radius and the weighting function are revised. Finally, combined with Weibull distribution, a framework for assessing multiaxial low-cycle fatigue life has been developed.

The experimental data of Q355(D) material verified the model and compared it with the Yao’s stress field intensity method. The results show that the predictions of the model put forward in this research are all located within the double dispersion zone, with better prediction accuracies than the Yao’s stress field intensity method.

Aiming at the fatigue test data with small sample characteristics, this research has presented a new method of notch fatigue analysis based on the stress field intensity method, which is combined with the Weibull distribution to construct a low-cycle fatigue life analysis framework, to promote the development of multiaxial fatigue from experimental studies to practical engineering applications.

Transporting hydrogen through natural gas pipelines in blended compositions has been proven to be a highly feasible solution in the short term. However, under hydrogen-rich environments, steel structures are prone to hydrogen-induced damage (HID). Additionally, uncertainties in various parameters can significantly impact the performance evaluation of hydrogen pipelines. Efficient reliability and sensitivity analyses of medium- to high-strength steel pipelines considering HID have become a challenge. Therefore, the primary aim of this study is to address this issue.

This study first establishes reliability analysis models for medium- to high-strength steels, represented by X65 and X80. In these models, the effect of HID is expressed by reduced stress, and its statistical parameters are calculated. Then, a highly efficient enhanced first order reliability method (FORM) is proposed for pipeline reliability analysis. This method overcomes the oscillation and convergence issues of traditional FORM when dealing with certain problems and can compute negative reliability indices. The proposed reliability analysis method is applied to solve the constructed reliability models. Finally, a reliability sensitivity analysis is conducted on the models to identify the key variables affecting the reliability of medium- to high-strength steel pipelines under HID.

First, two reliability analysis examples are used to validate the effectiveness of the proposed enhanced FORM. Then, using this method to solve the constructed reliability models for X65 and X80 steel pipelines under HID reveals that, for both types of steel, the reliability indices decrease significantly when considering HID compared to cases without HID. The decline is more pronounced for X80 steel than for X65 steel. As internal pressure increases, the reliability of both steels drops sharply, showing a concave parabolic trend. Moreover, the reliability sensitivity analysis shows that at a pressure of 10 MPa, for both X80 and X65, internal pressure, pipeline wall thickness and model error are the top three factors influencing reliability. As internal pressure increases, its influence becomes stronger, while the impact of other variables diminishes. Notably, for X80 steel, the presence of hydrogen amplifies the effect of internal pressure on pipeline reliability compared to when HID is not considered, but for X65, this trend is reversed.

Given the urgent need for safety evaluation studies on hydrogen transport through natural gas pipelines, this research provides new insights by constructing reliability models for X65 and X80 pipeline steels under HID and introducing an enhanced FORM method. The results of the reliability and sensitivity analyses of the models offer valuable insights and serve as a reference for engineering design.

In modern China, sports and nationalism always have close connection, and nationalism is the important reason for the promotion of Chinese sports. However, the relationship between Chinese sports and nationalism in globalised China could be much more examined by academics, as well as its influencing factors. This chapter selects the Beijing 2008 Olympic Games as the context and representative three Chinese sports heroes in the period of globalisation to study. The findings show that in some extent, Beijing 2008 Olympic Games and three Chinese sports heroes represent the national image of China in the globalised world, also bearing the burden of washing away historical humiliation and pursuing national glory. Furthermore, it is manifested that China have a complex nationalism in the process of hosting the 2008 Olympic Games. Under the influence of mass media, market economy and sports professionalisation, nationalism still exists in Chinese sports, but people gradually start to reflect on the ‘Juguo Tizhi’, the traditional Chinese sports system and the concept of ‘winning glory for the nation’. The relationship between Chinese nationalism and sports shows the important implications of rapid Chinese sports development.

Social media is booming in the digital age, and its rich availability provides many opportunities for companies to innovate across borders. In reality, how enterprises use social media to achieve cross-border innovation also faces important challenges such as breaking path dependency.

This paper explores how social media can facilitate cross-border innovation from the perspective of strategic capability, combined with the path dependency theory and attention-based view. Hierarchical regression analysis and bootstrap method are adopted to test the hypotheses based on survey data provided by 173 firms in China.

The findings show a positive relationship between social media strategic capability and cross-border innovation, with path dependency playing a mediating role. In addition, two internal and external contextual factors, namely customer embeddedness and competitive pressure, play moderating roles, with customer embeddedness negatively moderating the negative relationship between social media strategic capability and path dependency and competitive pressure negatively moderating the negative relationship between path dependency and cross-border innovation.

These findings provide not only new insights into social media and cross-border innovation but also theoretical guidance on how companies can effectively use social media in practice.

The purpose of this study is to (1) identify the factors that affect the adoption of virtual reality (VR) for spectator sports, (2) examine the differences in the factors among the four adopter categories (i.e. continuers, discontinuers, potentials and resistors) and (3) determine whether these factors are useful for discriminating among the adopter categories, based on the “diffusion of innovation” and “uses and gratification” theories.

In total, 216 participants were included in the analysis. Logistic regression and multiple analyses of variance were conducted to identify the factors that affect the adoption of VRS and examine the differences in the factors between adopter and non-adopter as well as between the continuers, discontinuers, potentials and resistors.

This study found that actualized innovativeness, complexity, companionship and gender significantly affect user adoption of VR for spectator sports. There were significant differences in the factors among the four adopter categories. The factors were also useful in discriminating between the four adopter categories.

This study highlights how individuals embrace emerging technologies differently based on their adopter category characteristics. From a marketing perspective, the insights gained from this study can inform the development of targeted strategies, campaigns and user experiences for VR spectator sports (VRS). This approach promises new revenue streams for the spectator sport industry and offers solutions to challenges like declining viewership and digital marginalization. It underscores the potential success of VR technology in transforming the spectator sport industry.

The brake pipe system was an essential braking component of the railway freight trains, but the existing E-type sealing rings had problems such as insufficient low-temperature resistance, poor heat stability and short service life. To address these issues, low-phenyl silicone rubber was prepared and tested, and the finite element analysis and experimental studies on the sealing performance of its sealing rings were carried out.

The low-temperature resistance and thermal stability of the prepared low-phenyl silicone rubber were studied using low-temperature tensile testing, differential scanning calorimetry, dynamic thermomechanical analysis and thermogravimetric analysis. The sealing performance of the low-phenyl silicone rubber sealing ring was studied by using finite element analysis software abaqus and experiments.

The prepared low-phenyl silicone rubber sealing ring possessed excellent low-temperature resistance and thermal stability. According to the finite element analysis results, the finish of the flange sealing surface and groove outer edge should be ensured, and extrusion damage should be avoided. The sealing rings were more susceptible to damage in high compression ratio and/or low-temperature environments. When the sealing effect was ensured, a small compression ratio should be selected, and rubbers with hardness and elasticity less affected by temperature should be selected. The prepared low-phenyl silicone rubber sealing ring had zero leakage at both room temperature (RT) and −50 °C.

The innovation of this study is that it provides valuable data and experience for the future development of the sealing rings used in the brake pipe flange joints of the railway freight cars in China.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

The purpose of this paper is to investigate the impact of demand information sharing on products’ greening levels with downstream competition. Specifically, this study examine two types of green products, “development-intensive” (DI) and “marginal-cost intensive” (MI), in a two-echelon supply chain where the manufacturer produces substitutable products, and competing retailers operate in a market with uncertain demand.

The authors adopt the manufacturer-led Stackelberg game-theoretic framework and consider a multistage game. This study consider how retailers receive private signals about uncertain demand and decide whether to share this information with the manufacturer, who then decides whether to acquire this information at a certain given cost. This paper considers backward induction and Bayesian Nash equilibrium to solve the model.

The authors find that in the absence of competition, information sharing is the only equilibrium and improves the greening level under DI, whereas no-information sharing is the only equilibrium and improves the greening level under MI, an increase in downstream competition drives higher investment in greening efforts by the manufacturer in both DI and MI and the manufacturer needs to offer a payment to the retailers to obtain demand information under both simultaneous and sequential contract schemes.

This paper contributes to the literature by examining how the nature of products (margin intensive green product or development intensive green product) influences green supply chain decisions under information asymmetry and downstream competition.