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This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

The purpose of this paper is to investigate the effects of political connections on the association between firms' business strategy and their tax aggressiveness in an emerging economy such as China.

The authors study a large sample of Chinese public firms from 2011 to 2017 using a panel regression model. In addition, a change analysis, an instrument variable test and alternative measures/samples are implemented as robustness tests.

Firms adopting innovative business strategy are more tax aggressive overall. However, innovative firms with political connections are less tax aggressive compared to those without political connections.

This paper contributes to the understanding of firms' tax behaviors in an emerging economy setting. It suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudies in the prior literature.

Constructing livable eco-civilized cities has become one of the important tasks of the reasonable planning of urban development. The construction of an ecological city aims to achieve the harmonious coexistence of society, resource, and environment. However, the current evaluation method system of an ecological building encounters problems from a defective evaluation index. Hence, a relatively perfect evaluation index system is built. First, the analytic network process (ANP) is combined with the existing standards online. Then, a rapid calculation of the index weight is performed using Super Decisions software. Based on the needs of complicated problems, the classical TOPSIS model algorithm is improved by introducing the weight coefficient; this improved TOPSIS algorithm is then taken as the core to build a whole set of comprehensive evaluation method system for ecological buildings. The ecological urban agglomeration in Qinling Mountains of Xi’an is used in this study as the example to perform verification in practice. Contrastive analysis is performed on the evaluation results of the new and old buildings using this method system; the results indicate that the ecological effect of the buildings in the new area is much better than that of buildings in the old area. These results are mostly consistent with the evaluation results given by the expert group. Thus, the comprehensive evaluation system proposed in this article is reliable, and effective, as well as practical to some extent. This method can be used in a wider range of building evaluation and further improved in future studies.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

This paper aims to explore the interlock-performance relationship among mainland Chinese firms listed in Hong Kong by taking advantage of a relationship-intensive context whereby such a link is likely to be especially important. Although strategic networks such as interlocking directorates have been found to affect a number of strategic behaviors, the link connecting board interlocks and corporate performance has remained ambiguous. Considerable light has been shed on the strategic networks of firms whose shares are listed abroad, which have been under-studied despite their rising importance in the global economy.

Data come from a particularly interesting historical period – the early 1990s prior to Hong Kong’s 1997 handover to China. Both quantitative and qualitative research have been used.

Empirically, it was found that good performance in an earlier period helps draw outside directors in a later period, and that network centrality and certain types of interlocks help improve performance, albeit with varying degrees. Overall, our results answer the question whether strategic networks such as interlocks matter for corporate performance with a qualified “yes”.

Taking advantage of a relationship-intensive context, this article explores the interlock-performance relationship among mainland Chinese firms listed in Hong Kong. Focus is specifically on the two years, 1993 and 1995, due to their specific historical importance because these two years represent the beginning of Chinese firms’ listing in Hong Kong.

The purpose of this paper on the one hand is to reduce the sintering temperature, shorten the sintering time and improve the electrical properties of the sample through the two-step flash sintering method and on the other hand is to study the effect of electric field on the phase structure, microstructure and electrical properties of the flash sintering sample.

In this paper, (Mg_1/3Ta_2/3)_0.01Ti_0.99O₂ giant dielectric ceramics were prepared by conventional sintering and two-step flash sintering, respectively. Further, the effect of electric field (600–750 V/cm) on the electrical properties of (Mg_1/3Ta_2/3)_0.01Ti_0.99O₂ giant dielectric ceramics was studied.

The results show that compared with the conventional sintering, the sintering temperature of the two-step flash sintering can be reduced by 200°C and the sintering time can be shortened by 12 times. All sintered samples were single rutile TiO₂ structure. Compared with conventional sintering, two-step flash sintering samples have finer grain size. The two-step flash sintered sample has similar dielectric properties to the conventional sintered sample. The dielectric constant of flash sintered samples decreases with the increase of electric field. When the electric field is 700 V/cm, the ceramic sample has the optimal dielectric properties, where the dielectric constant is approximately 5.5 × 10³ and the dielectric loss is about 0.18 at 1 kHz. Impedance spectroscopy analysis shows that the excellent dielectric properties are attributed to the internal barrier layer capacitance model.

This paper not only provides a new method for the preparation of co-doped TiO₂ giant dielectric ceramics but also has great potential in greatly improving efficiency and saving energy.

Course recommendations are important for improving learner satisfaction and reducing dropout rates on massive open online course (MOOC) platforms. This study aims to propose an interpretable method of analyzing students' learning behaviors and recommending MOOCs by integrating multiple data sources.

The study proposes a deep learning method of recommending MOOCs to students based on a multi-attention mechanism comprising learning records attention, word-level review attention, sentence-level review attention and course description attention. The proposed model is validated using real-world data consisting of the learning records of 6,628 students for 1,789 courses and 65,155 reviews.

The main contribution of this study is its exploration of multiple unstructured information using the proposed multi-attention network model. It provides an interpretable strategy for analyzing students' learning behaviors and conducting personalized MOOC recommendations.

The findings suggest that MOOC platforms must fully utilize the information implied in course reviews to extract personalized learning preferences.

This study is the first attempt to recommend MOOCs by exploring students' preferences in course reviews. The proposed multi-attention mechanism improves the interpretability of MOOC recommendations.

This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.

The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.

Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.

The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.

This paper aims to study the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ to improve the tribological properties of M50 bearing steel with microporous channels.

M50 matrix self-lubricating composites (MMSC) were designed and prepared by filling Sn–Ag–Cu and MXene–Ti₃C₂ in the microporous channels of M50 bearing steel. The tribology performance testing of as-prepared samples was executed with a multifunction tribometer. The optimum hole size and lubricant content, as well as self-lubricating mechanism of MMSC, were studied.

The tribological properties of MMSC are strongly dependent on the synergistic lubrication effect of MXene–Ti₃C₂ and Sn–Ag–Cu. When the hole size of microchannel is 1 mm and the content of MXene–Ti₃C₂ in mixed lubricant is 4 wt.%, MMSC shows the lowest friction coefficient and wear rate. The Sn–Ag–Cu and MXene–Ti₃C₂ are extruded from the microporous channels and spread to the friction interface, and a relatively complete lubricating film is formed at the friction interface. Meanwhile, the synergistic lubrication of Sn–Ag–Cu and MXene–Ti₃C₂ can improve the stability of the lubricating film, thus the excellent tribological property of MMSC is obtained.

The results help in deep understanding of the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ on the tribological properties of M50 bearing steel. This work also provides a useful reference for the tribological design of mechanical components by combining surface texture with solid lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0381/

Mega construction projects (MCPs), which play an important role in the economy, society and environment of a country, have developed rapidly in recent years. However, due to frequent social conflicts caused by the negative social impact of MCPs, social risk control has become a major challenge. Exploring the relationship between social risk factors and social risk from the perspective of risk evolution and identifying key factors contribute to social risk control; but few studies have paid enough attention to this. Therefore, this study aims to systematically analyze the impact of social risk factors on social risk based on a social risk evolution path.

This study proposed a social risk evolution path for MCPs explaining how social risk occurs and develops with the impact of social risk factors. To further analyze the impact quantitatively, a social risk analysis model combining structural equation model (SEM) with Bayesian network (BN) was developed. SEM was used to verify the relationship in the social risk evolution path. BN was applied to identify key social risk factors and predict the probabilities of social risk, quantitatively. The feasibility of the proposed model was verified by the case of water conservancy projects.

The results show that negative impact on residents’ living standards, public opinion advantage and emergency management ability were key social risk factors through sensitivity analysis. Then, scenario analysis simulated the risk probability results with the impact of different states of these key factors to obtain management strategies.

This study creatively proposes a social risk evolution path describing the dynamic interaction of the social risk and first applies the hybrid SEM–BN method in the social risk analysis for MCPs to explore effective risk control strategies. This study can facilitate the understanding of social risk from the perspective of risk evolution and provide decision-making support for the government coping with social risk in the implementation of MCPs.