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The purpose of this paper is to actively calibrate power density to match the application requirements with as small an actuator as possible. So, this paper introduces shape memory alloy to design variable stiffness elements. Meanwhile, the purpose of this paper is also to solve the problem of not being able to install sensors on shape memory alloy due to volume limitations.

This paper introduces the design, modeling and control process for a variable stiffness passive ankle exoskeleton, adjusting joint stiffness using shape memory alloy (SMA). This innovative exoskeleton aids the human ankle by adapting the precompression of elastic components by SMA, thereby adjusting the ankle exoskeleton’s integral stiffness. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function.

Using SMA as the driving force for stiffness modification in passive exoskeletons introduces several distinct advantages, inclusive of high energy density, programmability, rapid response time and simplified structural design. In the course of experimental validation, this ankle exoskeleton, endowed with variable stiffness, proficiently executed actions like squatting and walking and it can effectively increase the joint stiffness by 0.2 Nm/Deg.

The contribution of this paper is to introduce SMA to adjust the stiffness to actively calibrate power density to match the application requirements. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function.

The purpose of this study is to examine the association between audit committee expertise and asymmetric information in the US equity market.

The authors use measures of information asymmetry for 705 US firms (5,260 firm-year observations) over the period from 2007 to 2018, and use the theory of expertise (Ericsson and Smith, 1991) to examine the association between audit committee financial expertise and information asymmetry. The authors use multiple econometric approaches such as firm fixed-effect regression and two-stage ordinary least squares regression to control for possible endogeneity and reverse causality and find that the results remain the same.

The authors find that the existence of an audit committee with financial expertise is negatively and significantly associated with information asymmetry. The authors further provide empirical evidence through which audit committee financial expertise affects the firm’s informational environment. Additional analysis supports the argument that the audit committee’s financial expertise enhances the firm’s informational environment by increasing (decreasing) analyst following (dispersion).

One limitation to consider, like most studies on audit committees, is that the authors do not examine the actual role performed by the audit committee. The authors focus on the characteristics stipulated by the Sarbanes–Oxley Act 2002 and stock exchange rules regarding the financial expertise of audit committee members only.

This study is useful to policy makers, standard setters, investors, activists, managers, lenders and various stakeholders who rely on the financial statements of firms with an expert audit committee on board. The outcome of this study promotes recruiting audit committees with financial expertise due to the assumed benefits of this trait to the US firm.

The results of this study are not event-dependent and therefore have persistent effects, which is important to the evaluation of the usefulness of a regulation. This study promotes recruiting audit committees with financial expertise on boards because of the assumed benefits to the firm and investors.

This study is the first to document that financial expertise of audit committee characteristics is not only negatively related to the magnitude of information asymmetry but also driven by the financial expertise of audit committee members rather than chairs.

By market capitalisation, Bitcoin, which debuted in 2009, is the biggest cryptocurrency globally. A decentralised ledger system called blockchain is used in the creation, distribution, trading, and storage of Bitcoin, with the original goal being to address the shortcomings of fiat currency. This chapter highlights potential dangers and legal concerns when Bitcoin interacts with the actual economy and the traditional financial system. Besides, the details also discuss the platform’s design principles and attributes for a non-technical readership. When assessing its transactional potential, some recognise its potential for speculation, while others are doubtful of its admirable intent. The write-up also explores the potential of the adoption of cryptocurrencies in Southeast Asia due to the vast adoption of Bitcoins in countries such as Vietnam and the Philippines following the establishment of cryptocurrency technology and e-commerce. In addition, rankings of the cryptocurrency and legal stance from each country in Southeast Asia were exhibited as the solid foundation of cryptocurrencies existent for transaction purposes. The rise of central bank digital currencies (CBDC) and the future directions of Bitcoins were also highlighted in this write-up to spur the debate on whether cryptocurrency remains a fad of sensation or is legalised as the medium of exchange in an ever-growing digital world of commerce.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

The purpose of this paper is to examine how different types of user experience in TikTok impact purchase intention via commitment to the influencer and commitment to the platform, with customer type included to determine moderating effects. Three types of user experience are considered: information experience, entertainment experience and parasocial-relationship-based experience.

This study collected 458 valid questionnaires from TikTok users, employing the structural equation modeling approach to examine the proposed research model.

Information experience, entertainment experience and parasocial-relationship-based experience are found to critically stimulate user commitment to the influencer and commitment to the platform, in turn driving TikTok-based purchase intention. Tests incorporating customer type reveal that commitment to the influencer more strongly influences the purchase intention of repeat customers, with commitment to the platform more likely to stimulate purchase intention among potential customers.

On a theoretical level, the paper is among the first to examine TikTok-based user purchase intention with customer type as a moderator. On a practical level, the results can guide marketers to effectively promote products using TikTok and inspire TikTok managers to develop customized strategies to stimulate initial and repeat sales.

TikTok is moving to the stage of commercialization and monetization by introducing e-commerce features. Although this move should cultivate particularly fertile ground for companies to sell products, TikTok user purchase behavior has yet to receive sufficient research attention, with little currently known about their purchase motivations. The current study uncovers the significant antecedents of users' purchase intention through TikTok, and further reveals the motivational differences among potential and repeat customers.

Individuals show different environmental preferences, often influenced by their personality types. However, instances arise where the alignment of an individual’s personality and the architectural environment disappears, resulting in a mismatch. Consequently, the purpose of this study considers the urgent need to acknowledge and understand the complex interplay between architecture and individual personality traits.

The research method is based on the correlation between the variables, which is calculated by the significant assessment of the sample population and with SmartPLS. Finally, the findings and results of the research in relation to personality components and architectural aspects indicate the existence of a relationship. In the end, this study establishes correlations among variables and conclusions are drawn through systematic logical deductions.

The research findings underscore a compelling relationship between distinct personality components and various architectural facets. Furthermore, psychological cohesiveness within distinct social cohorts emerges as a pivotal factor influencing the relationship between individuals and architecture. In this regard, the main aspects of environmental preferences (surprise, cryptic, etc.) and personality types (neuroticism, extroversion, etc.) based on their significance and the factors affecting it in sub-components, create direct or indirect relationships. Additionally, the determination of the relationships created in each of these components is specified based on Image 12, and the path of creating architectural patterns can be considered according to that.

The results of the research show that the correlation between personality and physical components in different social groups is an effective issue in the relationship between human and the environment. It can also be considered as a factor for improving the quality of architectural design and creating a favorable cultural atmosphere in the environment. This issue has caused a connection between architecture and human personality, which creates the ground for improving the relationship between them. Also, architecture is placed by adapting to the personality and psychological needs of people and has an effective role in the quality of their relationships in organizing and expanding the environment.

This study seeks to investigate the impact of board attributes on environmental, social and governance (ESG) performance, along with exploring the mediating role of carbon emissions in this relationship.

To address this objective, the panel data approach was used to analyze the data were collected from 1,621 European companies from 2017 to 2021.

This study shows that board gender diversity, audit committee independence, expertise and board meeting attendance help enhance ESG performance. On the contrary, board size and composition do not affect ESG performance. The findings also showed that board gender diversity, audit committee independence, expertise and board meeting attendance are negatively related to carbon emissions performance. However, board size is related positively to carbon emissions performance. This indicates that the larger boards of directors may have diverse experiences that enhance the environmental performance of companies. Furthermore, the finding showed companies that contribute to lowering carbon emissions are more willing to improve their ESG performance. Also, carbon emissions mediate the relationship between the board's attributes and ESG performance.

The study's results have significant implications for firm managers in enhancing the efficiency of board decisions in determining environmental practices that matter to various groups of stakeholders. In addition, this study provides valuable input to regulators and policymakers regarding strengthening the regulations and controlling tools that enhance environmental performance.

The purpose of this study is to evaluate the tea stem natural dye was extracted from tea stem waste and applied to dyeing silk fiber, after which the properties of dyed samples were tested and analyzed.

The dyeing process was optimized using the response surface methodology (RSM) approach. Dyeing temperature, pH and time were chosen as variables and the color difference value as a response. The properties of dyed samples were tested and analyzed.

The optimized dyeing process was as follows: dyeing temperature 70°C, pH 3.5 and time 110 min. The K/S and color difference value of silk fiber dyed with the optimal process dye enzymatic oxidation with laccase was 1.4 and 27.8, respectively. The silk fiber dyed has excellent color fastness, antioxidant and antibacterial property, which greatly increases the added value of the dyed products. Furthermore, the optimized dyeing process did not significantly affect the strength properties and handle of the silk fiber.

Researchers have not used statistical analysis to optimize the process of dyeing process of silk fiber by tea stem natural dye enzymatic oxidation with laccase using response surface methodology. Additionally, this dyeing process was a low-temperature dyeing process, which not only saves energy consumption and reduces silk fiber damage but also obtains superbly dyeing results and biological functional properties, achieve the effects of waste utilization and clean dyeing.

Accurate mapping is crucial for the positioning and navigation of mobile robots. Recent advancements in algorithms and the accuracy of LiDAR sensors have led to a gradual improvement in map quality. However, challenges such as lag in closing loops and vignetting at map boundaries persist due to the discrete and sparse nature of raster map data. The purpose of this study is to reduce the error of map construction and improve the timeliness of closed loop.

In this letter, the authors introduce a method for dynamically adjusting point cloud distance constraints to optimize data association (ODA-d), effectively addressing these issues. The authors propose a dynamic threshold optimization method for matching point clouds to submaps during scan matching.

Large deviations in LiDAR sensor point cloud data, when incorporated into the submap, can result in irreparable errors in correlation matching and loop closure optimization. By implementing a data association framework with double constraints and dynamically adjusting the matching threshold, the authors significantly enhance submap quality. In addition, the authors introduce a dynamic fusion method that accounts for both submap size and the distance between submaps during the mapping process. ODA-d reduces errors between submaps and facilitates timely loop closure optimization.

The authors validate the localization accuracy of ODA-d by examining translation and rotation errors across three open data sets. Moreover, the authors compare the quality of map construction in a real-world environment, demonstrating the effectiveness of ODA-d.