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The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

The purpose of the study is to investigate the impact of implementing anti-dumping duties on imported Australian wine to China in the short- and long-run, respectively.

First, the Difference-in-Differences (DID) method is used in this study to evaluate the short-run causal effect of implementing anti-dumping duties on imported Australian wine to China. Second, a Bayesian ensemble method is used to predict 2023–2025 wine exports from Australia to China. The disparity between the forecasts and counterfactual prediction which assumes no anti-dumping duties represents the accumulated impact of the anti-dumping duties in the long run.

The anti-dumping duties resulted in a significant decline in red and rose, white and sparkling wine exports to China by 92.59%, 99.06% and 90.06%, respectively, in 2021. In the long run, wine exports to China are projected to continue this downward trend, with an average annual growth rate of −21.92%, −38.90% and −9.54% for the three types of wine, respectively. In contrast, the counterfactual prediction indicates an increase of 3.20%, 20.37% and 4.55% for the respective categories. Consequently, the policy intervention is expected to result in a decrease of 96.11%, 93.15% and 84.11% in red and rose, white and sparkling wine exports to China from 2021 to 2025.

The originality of this study lies in the creation of an economic paradigm for assessing policy impacts within the realm of wine economics. Methodologically, it also represents the pioneering application of the DID and Bayesian ensemble forecasting methods within the field of wine economics.

This study aims to investigate the factors that affect the intention to use public mobile libraries and enhance the quality of mobile library services to attract and retain users.

A questionnaire survey was conducted with 391 valid users in China. Based on the stimulus–response theory and user individual characteristics, a model was developed to examine the factors influencing the intention to use public mobile libraries. The model was tested using statistical software, such as SPSS 25.0 and AMOS 24.0.

The results indicate that technological factors, content factors, individual factors and psychological factors significantly influence the intention to use public mobile libraries. The impact of system quality and perceived ease of use in technological factors is relatively balanced. Among content factors, information quality is the most significant, while information literacy has a greater influence compared to subjective norms in individual factors. In psychological factors, perceived matching and perceived pleasure both positively influence usage intention, while perceived cost has a negative impact.

Firstly, this study only investigates users’ intention to use, but intention does not necessarily equate to actual usage behaviour (King and He,2006). Future research can introduce new variables to explore users’ adoption and continuous usage behaviours. Secondly, this study does not differentiate between different types of mobile library users. Future research can consider different user types, such as potential users and current users, to investigate the similarities and differences in their willingness to adopt mobile library services. Thirdly, this study is primarily cross-sectional. Future research can consider longitudinal studies to provide more in-depth insights into user behaviour.

This paper identifies external and internal stimulus factors and conducts a comprehensive investigation into the factors influencing the intention to use public mobile libraries, thus providing generalizable research findings. Unlike previous studies, this research introduces the information literacy variable, enriching the model of factors affecting users' intention to use mobile libraries and yielding more comprehensive conclusions. Consequently, the study aims to be grounded in the actual usage ideas and intentions of diverse user groups, constructing a model that highlights factors influencing the intention to use public mobile library services.

From a social perspective, this study offers four implications for improving the utilization of public mobile libraries. Firstly, it is crucial to integrate digital resources, enhance information quality in public mobile libraries and improve platform usability. Secondly, adopting a user-oriented approach is essential to improve the service level of public mobile libraries and stimulate residents’ participation. Thirdly, efforts should be made to strengthen user information literacy and increase information utilization. Fourthly, top-level design improvements, effective promotion efforts and user behaviour guidance are essential for the success of public mobile libraries.

This study contributes to the improvement of public mobile library services and the advancement of modern public cultural services by identifying the key factors that drive the intention to use such services. The findings have practical implications for promoting high-quality development and enhancing the popularity of public mobile libraries.

This paper aims to realize an in-situ quality inspection system rapidly for new injection molding (IM) tasks via transfer learning (TL) approach and automation technology.

The proposed in-situ quality inspection system consists of an injection machine, USB camera, programmable logic controller and personal computer, interconnected via OPC or USB communication interfaces. This configuration enables seamless automation of the IM process, real-time quality inspection and automated decision-making. In addition, a MobileNet-based deep learning (DL) model is proposed for quality inspection of injection parts, fine-tuned using the TL approach.

Using the TL approach, the MobileNet-based DL model demonstrates exceptional performance, achieving validation accuracy of 99.1% with the utilization of merely 50 images per category. Its detection speed and accuracy surpass those of DenseNet121-based, VGG16-based, ResNet50-based and Xception-based convolutional neural networks. Further evaluation using a random data set of 120 images, as assessed through the confusion matrix, attests to an accuracy rate of 96.67%.

The proposed MobileNet-based DL model achieves higher accuracy with less resource consumption using the TL approach. It is integrated with automation technologies to build the in-situ quality inspection system of injection parts, which improves the cost-efficiency by facilitating the acquisition and labeling of task-specific images, enabling automatic defect detection and decision-making online, thus holding profound significance for the IM industry and its pursuit of enhanced quality inspection measures.

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

Stainless-clad bimetallic steels (SCBS) are widely investigated in some extremely environmental applications areas, such as polar sailing area and tropical oil and gas platforms areas, because of their excellent anticorrosion performance and relatively lower production costs. However, the properties of SCBS, including the mechanical strength, weldability and the anticorrosion behavior, have a direct relation with the manufacturing process and can affect their practical applications. This paper aims to review the application and the properties requirements of SCBS in marine environments to promote the application of this new material in more fields.

In this paper, the manufacturing process, welding and corrosion-resistant properties of SCBS were introduced systematically by reviewing the related literatures, and some results of the authors’ research group were also introduced briefly.

Different preparation methods, such as rolling composite, casting rolling composite, explosive composite, laser cladding and plasma arc cladding, as well as the process parameters, including the vacuum degree, rolling temperature, rolling reduction ratio, volume ratios of liquid to solid, explosive ratio and the heat treatment, influenced a lot on the properties of the SCBS through changing the interface microstructures. Otherwise, the variations in rolling temperature, pass, reduction and the grain size of clad steel also brought the dissimilarities of the mechanical properties, microhardness, bonding strength and toughness. Another two new processes, clad teeming method and interlayer explosive welding, deserve more attention because of their excellent microstructure control ability. The superior corrosion resistance of SCBS can alleviate the corrosion problem in the marine environment and prolong the service life of the equipment, but the phenomenon of galvanic corrosion should be noted as much as possible. The high dilution rate, welding process specifications and heat treatment can weaken the intergranular corrosion resistance in the weld area.

This paper summarizes the application of SCBS in marine environments and provides an overview and reference for the research of stainless-clad bimetallic steel.

Wine producers and marketing professionals increasingly recognize the significance of online wine reviews. Emotions have long been acknowledged as influential in online review behaviors. However, considering the multisensory nature of the wine experience, consumers’ wine expertise also plays a substantial role. Hence, this study aims to examine the online review behaviors exhibited by wine consumers through the dual lens of wine expertise and emotionality.

Two studies were conducted to address the research question. Study 1 explored the relationship among expertise, emotionality and review behaviors using a panel data model, with a data set consisting of 4,600,922 reviews from Vivino.com. Study 2 used a multigroup structural equation modeling (SEM) analysis using data obtained from an online survey. Study 2 aimed to investigate the interactive impact of emotionality and expertise on online review intention mediated by customer engagement.

The findings from Study 1 demonstrated a positive correlation between emotionality and online wine reviews. In addition, expertise displayed a bell-shaped relationship with both emotionality and online wine reviews. Study 2, in turn, uncovered that novices and experts experienced a direct influence of emotionality on their review intentions. In contrast, for those classified as ordinary, the influence of emotionality on review intention occurred indirectly through the mediation of customer engagement.

This paper extends the current literature on online wine review by integrating the effect of emotion and expertise on online wine review behaviors, expanding the examination of Dunning–Kruger effect in the wine literature. It also adds value by introducing emotionality and the Evaluative Lexicon into the hospitality literature, extending the measurement of emotion from valence and extremity to a third dimension, emotionality, in hospitality and wine domains.

Supply chain resilience (SCR) has attracted much attention in the context of the high uncertainty caused by the coronavirus disease 2019 (COVID-19), local regional conflicts and natural disasters. Based on information processing theory (IPT), this study investigates the role of supply chain information processing capability in enhancing SCR through supply chain governance (SCG), under different conditions of environmental uncertainty.

The hypothetical model is tested by using hierarchical regression on the primary samples collected from the Chinese manufacturing industry.

The results indicate that supply chain information processing capability has a significant positive effect on SCR. Also, SCG plays a mediating role between supply chain information processing capability and SCR. Furthermore, environmental uncertainty positively moderates the effect of supply chain information acquisition and supply chain information analysis on relational governance. However, environmental uncertainty only positively moderates the effect of supply chain information analysis on contractual governance.

This is the first study to explain the effect of information processing capability on SCR from the supply chain perspective, while also exploring the mediating role of SCG between SCR and supply chain information processing capacity, based on IPT.

Off-site construction (OSC) has been regarded as a clean and efficient production approach to help the construction industry towards sustainability. Different levels of OSC technologies vary greatly in their implementations and adoptions. Compared to low OSC level technologies have been applied widely, the adoption of high OSC level technologies (HOSCLTs) in practice remains limited. The adoption mechanism for HOSCLTs by firms has not been clear, hindering their promotion. This study aims to explore the mechanism combining subjective and objective adoption for HOSCLTs.

This study developed an integrated model illustrating mechanism for HOSCLTs adoption based on the technology acceptance model (TAM), which has strong capacity to explain potential adopters' subjective intentions to adoption, and the task-technology fit (TTF) theory, which well describes the linkages between the task, technology and performance in technology adoption. The proposed model was then empirically evaluated through a survey of 232 practitioners in the Chinese OSC industry using partial least squares structural equation modeling.

The results indicate that both task characteristics (TAC) and technology characteristics (TEC) positively affect TTF of HOSCLTs. TAC, TTF, firm conditions and stakeholder influence have significant positive effects on perceived usefulness (PU), which further positively influence attitude towards adoption. TEC and firm conditions are significantly related to perceived ease of use (PEU). TTF, PEU and attitude towards adoption are good predictors of behavior intention to HOSCLTs adoption. PEU only significantly influences adoption intention and is not observed to influence attitudes and PU, unlike prior research on common OSC adoption.

This study contributes to the body of knowledge by exploring HOSCLTs adoption in the industry based on distinguishing the levels of OSC technologies and supplementing an integrated model for explaining the mechanism with the combination of subjective and objective adoption. The study also provides useful insights into understanding and promoting HOSCLTs adoption for policy makers and stakeholders actively involved in the OSC field.

A visual sweetness scale with an arrow pointing to a specific sweetness level is now required on all labels of AOC Alsace. The sweetness scale makes it easier for consumers to understand what is in the bottle. What is less clear, however, is whether such labeling is always effective. To fill this gap, the current research paper aims to examine the positive and negative effects (double-edged effects) of a visual sweetness scale and identify the boundary condition.

Two studies were conducted using a 2 (cue type: scale vs text) by 2 (consumer type: novices vs experienced wine consumers) between-subjects, quasi-experimental design.

The double-edged effects are only significant among wine novices. Specifically, though wine novices are more likely to purchase wine with a sweetness scale (vs text) due to perceived diagnosticity (Study 1), they are unwilling to pay more due to low perceived quality (Study 2).

The study findings provide practical implications for wine producers, marketers and restaurants regarding when and how to use the sweetness scale on wine labels and wine service.

To the best of the authors’ knowledge, this research is the first to reveal the impact of visualizing wine style on wine labels. More importantly, while most previous research demonstrates the positive effects of using visual cues, this research sheds light on its drawbacks and examines the underlying mechanisms.