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Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.

The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.

The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.

According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.

First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.

Building on the social leverage model (SLM), this study aims to examine the influence of event-related attributes on residents' perceived social impact of a major sport event, as mediated by event involvement. It also investigates the moderating effect of event rights holders' credibility on the relationship between event involvement and perceived social impact.

Using a two-wave, time-lagged survey, data were collected from 220 residents of a Super Bowl host city. Hypotheses were tested using structural equation modeling (SEM).

High celebratory atmosphere, social camaraderie and social responsibility as perceived before the event were associated with residents' perceptions of the social impact of the Super Bowl. Moreover, the association between social camaraderie and perceived social impact was mediated by event involvement. When appraising the rights holder as credible, involved residents reported an increased level of perceived social impact.

This study contributes to research on the SLM by demonstrating its application among indirect participants of major sport events. Additionally, it suggests the imperative role of rights holders' credibility in promoting the perceived social impact among involved residents.

This study tends to investigate how the outbreak of the coronavirus disease 2019 (COVID-19) pandemic has affected banks' contribution to systemic risk. In addition, the authors examine whether the impact of the pandemic may vary across advanced/emerging economies, and with banks with differed characteristics.

The authors construct the bank-specific conditional value at risk (CoVaR) and marginal expected shortfall (MES) to measure their contribution to systemic risk and define the outbreak of the COVID-19 pandemic by the timing when countries report more than 100 confirmed cases. The authors use the approach of difference-in-differences to assess the impact of the COVID-19 pandemic on banks' contribution to systemic risk. This sample comprises monthly panel data of around 900 listed commercial banks in 39 advanced and emerging economies.

The authors find that, firstly, the COVID-19 pandemic increased banks' contribution to systemic risk significantly around the world. Secondly, the impact of the COVID-19 virus was more pronounced in developed countries than in emerging economies. Finally, banks with a larger size and higher loan-to-deposit ratio are more greatly affected by the COVID-19 pandemic, while a higher capitalization for banks is insufficient to shelter them from the adverse impact of such pandemic.

The authors assess the impact of the COVID-19 pandemic on banks' contribution to systemic risk. Using the conditional value at risk (marginal expected shortfall) of banks as the measure, this study’s results suggest that banks' contribution to systemic risk increases by around 25% (48%) amid the COVID-19 pandemic. This study’s findings may shed some light on the potential policies that financial regulators may employ to ameliorate the adverse outcomes of the ongoing pandemic.

This paper aims to use artificial neural network (ANN) methods to predict stock price crashes in the Chinese equity market.

Three ANN models are developed and compared with the logistic regression model.

Results from this study conclude that the ANN approaches outperform the traditional logistic regression model, with fewer hidden layers in the ANN model having superior performance compared to the ANNs with multiple hidden layers. Results from the ANN approach also reveal that foreign institutional ownership, financial leverage, weekly average return and market-to-book ratio are the important variables when predicting stock price crashes, consistent with results from the traditional logistic model.

First, the ANN framework has been used in this study to forecast the stock price crashes and compared to the traditional logistic model in the world’s largest emerging market China. Second, the receiver operating characteristics curves and the area under the ROC curve have been used to evaluate the forecasting performance between the ANNs and the traditional approaches, in addition to some traditional performance evaluation methods.

The main objective of this paper is to illustrate an analytical view of different methods of 3D bioprinting, variations, formulations and characteristics of biomaterials. This review also aims to discover all the areas of applications and scopes of further improvement of 3D bioprinters in this era of the Fourth Industrial Revolution.

This paper reviewed a number of papers that carried evaluations of different 3D bioprinting methods with different biomaterials, using different pumps to print 3D scaffolds, living cells, tissue and organs. All the papers and articles are collected from different journals and conference papers from 2014 to 2022.

This paper briefly explains how the concept of a 3D bioprinter was developed from a 3D printer and how it affects the biomedical field and helps to recover the lack of organ donors. It also gives a clear explanation of three basic processes and different strategies of these processes and the criteria of biomaterial selection. This paper gives insights into how 3D bioprinters can be assisted with machine learning to increase their scope of application.

The chosen research approach may limit the generalizability of the research findings. As a result, researchers are encouraged to test the proposed hypotheses further.

This paper includes implications for developing 3D bioprinters, developing biomaterials and increasing the printability of 3D bioprinters.

This paper addresses an identified need by investigating how to enable 3D bioprinting performance.

Climate change and the COVID-19 pandemic are complex and have multifaceted effects on countries in an unpredictable and unprecedented manner. While both COVID-19 and the climate crisis share similarities, they also have some notable differences. Being both systemic in nature with knock-on and cascading effects that propagate due to high connectedness of countries, COVID-19, however, presents imminent and directly visible dangers, while the risks from climate change are gradual, cumulative and often distributed dangers. Climate change has more significant medium and long-term impacts which are likely to worsen over time. There is no vaccine for climate change compared to COVID-19. In addition, those most affected by extreme climatic conditions have usually contributed the least to the root causes of the crisis. This is in fact the case of island economies. The chapter thus investigates into the vulnerability and resilience of 38 Small Islands Developing States (SIDs) to both shocks. Adopting a comprehensive conceptual framework and data on various indices from the literature and global databases, we assess the COVID-19 and climate change vulnerabilities of SIDs on multiple fronts. The results first reveal a higher vulnerability across all dimensions for the Pacific islands compared to the other islands in the sample. There is also evidence of a weak correlation between climate change risk and the COVID-19 pandemic confirming our premise that there are marked differences between these two shocks and their impacts on island communities.

This study aims to improve the corrosion resistance of TA2-welded joints by superhydrophobic surface modification using micro-arc oxidation technology and low surface energy substance modification.

The microstructure and chemical state of the superhydrophobic film layer were analyzed using scanning electron microscopy, energy dispersive X-ray spectroscopy, three-dimensional morphology, X-ray diffraction, X-ray photoelectron spectroscopy and Fourier transform infrared absorption spectroscopy. The influence of the superhydrophobic film layer on the corrosion resistance of TA2-welded joints was investigated using classical electrochemical testing methods.

The characterization results showed that the super hydrophobic TiO₂ ceramic membrane was successfully constructed on the surface of the TA2-welded joint, and the construction of the super hydrophobic film greatly improved the corrosion resistance of the TA2-welded joint.

The superhydrophobic TiO₂ ceramic membrane has excellent corrosion resistance. The micro nanostructure in the superhydrophobic film can intercept air to form an air layer to prevent the corrosion medium from contacting the surface, thus, improving the corrosion resistance of the sample.

This paper aims to investigate the tribological properties of polytetrafluoroethylene (PTFE) composites modified by nano-serpentine and nano-lanthanum oxide in a seawater environment.

In this paper, seven PTFE composites were prepared by unified design method and vacuum thermoforming method, and their hardness, water absorption and tribological properties were measured under seawater environment. The modification effects and thermal stability of the materials were analyzed by Fourier transform infrared spectroscopy, thermal gravimetry and differential scanning calorimetry. This paper analyzed the wear mechanism of PTFE composites by scanning electron microscopy and energy spectroscopy.

The results showed that the hardness of the PTFE composites were all improved, but the water absorption was increased with the increase of additives. The modification of nano-serpentine was successful and the thermal stability of PTFE composites was better. The lowest coefficient and minimum wear rate are 0.0267 and 8.67 × 10⁻⁵ · mm³ · (N · m)⁻¹ respectively, which is 34.9% and 76% less than the pure PTFE.

The analysis showed that the wear mechanism of PTFE composites was abrasive wear and a small amount of adhesive wear, and when the additive content was appropriate, it easily formed a transfer film on the surface mating parts.

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine hesitancy by conducting content analysis and sentiment analysis of the perspectives expressed in comments on videos related to vaccine hesitancy uploaded from India on YouTube.

The assessment of the sentiments of the vaccine-hesitant population is done using Valence Aware Dictionary and sEntiment Reasoner sentiment analysis module implemented with Python’s NLTK library to automatically determine the sentiments of the comments. Manual content analysis was performed on 60.09% viewer comments randomly selected from the total comments in 238 videos on vaccine hesitancy originated from India and labelled each comment with labels “Anti”, “Pro”, “Confused”, “Not Applicable” and “Unrelated” labels.

The study found “Mistrust-Government policies”, “Fear-health related consequences”, “Mistrust-Scientific research”, “Vaccine effectiveness and efficacy” and “Misinformation/myths” as the top five determinants for vaccine hesitancy, whereas “Religious beliefs”, “Fear-Economic consequences”, “Side Effects- short-term” and “Fear-mode of administration” found to be the lesser cited reasons for vaccine hesitancy. However, the study also investigates changes in the inclination of Indian commenters towards vaccine hesitancy and revolving issues over time.

Public health policymakers and health communicators may find the study useful in determining vaccine hesitancy factors in India.

The originality of this study lies in its approach. To date, no sentiment analysis has been conducted on the content released on YouTube by Indian content creators regarding pro- and anti-vaccination videos. This inquiry seeks to fill this research gap.

The textile sector is one of the sectors where competition is intense and requires the production of high-value-added products. This study aims to conduct patent analysis to find the technology status, recent trends, applications and technological evaluations of protective textile technologies in practice.

More than 36,840 patent documents related to protective textile technologies are available for researchers, patent examiners and patent researchers. Patent analysis is conducted to report the technology status, recent trends and applications of protective textile technologies. This analysis provides insights into the possible future directions of protective textile technologies in practice. Additionally, association rule mining (ARM) is performed to find the hidden patterns among protective textile technologies.

The development of protective textile technologies is revealed by the technology evaluation in this study. In addition, the sub-technology classes affecting protective textile technologies are examined using the cooperative patent classification (CPC) codes of the patent documents. Technology status and recent trends of protective textile technologies are provided in detail. The results of this study show that (1) protective textile technologies are constantly being developed, (2) the working areas of medical protective textiles are increasing, (3) there are frequent studies on fabric structures for saving lives within the framework of human needs and (4) there are four technology classes, namely A41D, Y10T, B32B and A62B impacting the other technology classes related to textile technologies such as D10B, Y10T, F41H, A62D, D04H, Y10S and D10B.

To have a competitive advantage in the marketplace, evaluation of textile technologies is critical in developing “functionalized” and “technologized” textile products. In particular, evaluating technologies in developing protective textile products is extremely important to meet customer demands and present competitive products in the market. Examining these patents for technology developers, decision-makers and policymakers is an urgent and necessary job. However, studies examining the development of protective textile technologies with patent analysis are very limited in the literature. To fill this gap, technology status, recent trends and applications of protective textile technologies are reported based on patent analysis and ARM in this study.