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The Metaverse, an emergent Web 3.0 platform, offers users immersive virtual reality experiences. This study employs a case study approach to explore the concept of sustainability within the Metaverse. It examines the environmental, social, and economic implications of virtual interactions and the role of sustainable technologies in shaping user behavior and virtual economies. Through selected case studies, the research provides insights into the potential and challenges of integrating sustainable practices in the Metaverse, with implications for stakeholders ranging from policymakers to end-users.

This study aims to report the development and experimental evaluation of two kinds of PANI@semiconductor based photocathodic anti-corrosion coating, for application on stainless steel substrates.

PANI was in situ chemical polymerized on TiO₂ and BiVO₄ particles, and FT-IR and SEM/EDS were used to understand the characteristics and elemental distribution of the composite particles. Composite coatings, which consisted of epoxy, PANI@TiO₂ or PANI@BiVO₄ and graphene, were prepared on the 304L stainless steel. Photoelectrochemical response measurement, electrochemical tests and immersion tests were used to assess the anti-corrosion performance of the prepared coatings in 45°C 3.5 wt.% NaCl solution. And the corrosion protection mechanism was further explained by combining with surface observation.

The photoelectrochemical response tests revealed the good photocathodic effect of the coatings, and the reversible oxidation-reduction properties of PANI (pseudocapacitive effect) leading to the repeated usage of the coatings. Consequently, the anti-corrosion mechanism of the composite coating is attributed to the physical barrier effect of the coating, the anodic protection effect of PANI and the photocathodic and energy store effect.

These kind coatings could prevent corrosion from day to night for stainless steel, which has great engineering application prospects on stainless steel corrosion protection.

The aim was not to perform a systematic review but firstly to search in PubMed, Science Direct, Scopus and Web of Science databases on the papers published in the last five years using tools for reviewing the statement of preferred information item for systematic reviews without focusing on a randomized analysis and secondly to perform a bibliometric analysis on the properties of films and coatings added of tocopherol for food packaging.

On January 24, 2022, information was sought on the properties of films and coatings added of tocopherol for use as food packaging published in PubMed, Science Direct, Scopus and Web of Science databases. Further analysis was performed using bibliometric indicators with the VOSviewer tool.

The searches returned 33 studies concerning the properties of films and coatings added of tocopherol for food packaging, which were analyzed together for a better understanding of the results. Data analysis using the VOSviewer tool allowed a better visualization and exploration of these words and the development of maps that showed the main links between the publications.

In the area of food science and technology, the development of polymers capable of promoting the extension of the shelf life of food products is sought, so the knowledge of the properties is vital for this research area since combining a biodegradable polymeric material with a natural antioxidant active is of great interest for modern society since they associate environmental preservation with food preservation.

The recent COVID-19 pandemic underscores the need for educational innovation and digitalization during crises where many educational institutions were forced to shift to online and remote learning. This chapter is a discursive review of problems and solutions and key trends that have emerged because of crises. One of the key benefits of educational innovation and digitalization during crises is the ability to continue providing education and learning opportunities to students even when traditional face-to-face learning is not possible. Educational institutions need to invest in building resilient online learning ecosystems to ensure that education can continue uninterrupted even in the face of unforeseen disruptions. This ecosystem should include robust technological infrastructure, a diverse range of digital resources and tools, and training and support for educators. Ultimately, a resilient online learning ecosystem is not just a response to crises but a proactive investment in the future of education.

The purpose of this study was to validate the feasibility of the proposed microstructure-based model by comparing the simulation results with experimental data. The study also aimed to investigate the relationship between the orientation of graphite flakes and the failure behavior of the material under compressive loads as well as the effect of image size on the accuracy of stress–strain behavior predictions.

This paper presents a microstructure-based model that utilizes the finite element method (FEM) combined with representative volume elements (RVE) to simulate the hardening and failure behavior of ferrite-pearlite matrix gray cast iron under uniaxial loading conditions. The material was first analyzed using optical microscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) to identify the different phases and their characteristics. High-resolution SEM images of the undeformed material microstructure were then converted into finite element meshes using OOF2 software. The Johnson–Cook (J–C) model, along with a damage model, was employed in Abaqus FEA software to estimate the elastic and elastoplastic behavior under assumed plane stress conditions.

The findings indicate that crack initiation and propagation in gray cast iron begin at the interface between graphite particles and the pearlitic matrix, with microcrack networks extending into the metal matrix, eventually coalescing to cause material failure. The ferritic phase within the material contributes some ductility, thereby delaying crack initiation.

This study introduces a novel approach by integrating microstructural analysis with FEM and RVE techniques to accurately model the hardening and failure behavior of gray cast iron under uniaxial loading. The incorporation of high-resolution SEM images into finite element meshes, combined with the J–C model and damage assessment in Abaqus, provides a comprehensive method for predicting material performance. This approach enhances the understanding of the microstructural influences on crack initiation and propagation, offering valuable insights for improving the design and durability of gray cast iron components.

The rapid growth of professional esports has highlighted the lack of a universally recognised governing body to standardise operations and competition rules. This absence presents many challenges. A key concern is the well-being of professional esports players (e-pro-players), who often suffer from exhaustion. This study aims to examine the factors contributing to exhaustion among e-pro-players.

Using the conservation of resources theory, we developed a framework to explain the factors leading to e-pro-players’ exhaustion and the conditions under which it occurs. We tested this framework with 126 responses in a dyadic survey from e-pro-players and their coaches in China. Additionally, we gathered qualitative insights from 50 interviews with esports stakeholders to provide more context for our quantitative findings.

Our study found that e-pro-players’ intrinsic motivation to engage in training reduces their exhaustion, while their struggle to cope with uncertainty in esports environments (intolerance of uncertainty) increases it. The effect of intrinsic motivation is weaker for those who believe their talent for playing esports is fixed (entity belief) but stronger for those with high relational identification with their coaches. Additionally, the link between uncertainty intolerance and exhaustion is stronger in players with strong entity beliefs.

Our study sheds light on the factors contributing to e-pro-players’ exhaustion within the partially regulated professional esports environment, a phenomenon that significantly influences their overall well-being. Through the identification and examination of these factors and the conditions under which they affect exhaustion, we deepen the understanding of the drivers of exhaustion for e-pro-players who operate in an industry lacking standardised regulations.

Corporate donation behavior sends two financial-related signals, i.e. sufficient cash flow and self-confidence in future earnings. This paper aims to investigate whether these financial-related signals released by corporate donation drive investors to make more optimistic forecasts about the firm’s future earnings per share (EPS) and whether this effect varies across different historical earnings trends.

This study is based on a controlled online experiment with 553 MBA students.

The results demonstrate that a financial signaling mechanism works, but it is moderated by historical earnings trends. When the earnings trend is always increasing, the more the number of financial signals received, the higher the investors’ EPS forecast; when the earnings trend is fluctuating (down then up or up then down), investors’ EPS forecast is higher when they receive financial signal(s) than when they do not, but no additive effect occurs from receiving one signal to two signals; when the earnings trend is always decreasing, investors’ EPS forecast is irrelevant to the number of financial signals received.

To the best of the authors’ knowledge, this study is the first to experimentally investigate a possible mechanism to explain investors’ positive response to corporate social responsibility (CSR) (specifically, corporate donation) disclosures – the financial signaling mechanism. This study also extends the research on the impact of financial information on investors’ use of nonfinancial information by investigating the moderating role of historical earnings trends on the financial signaling mechanism of the CSR effect.

The purpose of this study is to systematically investigate the novel phenomenon of rail corrugation on small radius curves with rail joints in mountainous city metros, characterized by the coexistence of short and long wavelengths (30–40 mm and 150–200 mm) on the low rail.

The finite element model of the wheel-rail system in the section with rail joint is constructed based on field surveys. The friction-coupled vibration characteristics of the wheel-rail system are studied from the perspective of friction self-excited vibration of the wheel-rail system and feedback vibration of the rail irregularity.

The rail corrugation with short wavelength is primarily induced by the friction self-excited vibration of wheel-rail system. In contrast, the rail corrugation with long wavelength is predominantly caused by the feedback vibration of rail joint irregularity. Additionally, the feedback vibration of corrugated irregularity accelerates the progression of corrugation depth without triggering the emergence of rail corrugation with new wavelength.

The research advances the understanding of the vibration inducement behind rail corrugation in mountainous city metros.

This study aims to determine the impact of corporate digital transformation on the audit opinions of auditors in A-share nonfinancial listed companies in China. It also examines how corporate internal control and corporate social responsibility (CSR) disclosure levels moderate this effect. This study fills a gap in the literature by investigating the impact of digital transformation on business performance, especially in the Chinese context, where digital transformation is rapidly progressing. This study also offers practical guidance for practitioners on whether and how to undergo a digital transformation and enhance their internal governance and social responsibility practices.

This study uses a sample of 2,637 Chinese A-share nonfinancial listed companies from 2009–2022, after excluding firms with ST, ST* or PT status; negative revenue; and missing data for three or more consecutive years. Digital transformation index data is collected from firms’ annual reports, and the other microlevel data from the Wind and CSMAR databases. The authors winsorize the data at 1% for outliers, resulting in 17,305 firm-year observations. This study uses fixed-effects logistic regression with clustered robust standard errors to analyze the binary dependent variable. This study also performs various robustness checks, such as probit model, multilevel fixed effects model and IV 2SLS estimations, to confirm the validity of the results.

This study reveals that digital transformation leads to standard unqualified audit opinions, meaning that companies that invest more in digital technologies and capabilities has more tendency to receive standard unqualified audit opinions, which signify the reliability and credibility of their financial reporting. This study also finds that corporate internal control and CSR disclosure levels positively moderate the effect of digital transformation on audit opinions. This study further conducts heterogeneity analysis and shows that the positive effect is originated by the state-owned enterprises, firms audited by non-Big4 auditing firms, firms with high internal control levels and firms with low CSR disclosure levels. The results are robust to different econometric methods.

This study contributes to the literature by providing empirical evidence on how digital transformation influences audit quality and credibility and how internal governance and social responsibility practices strengthen this influence. This study also has practical implications for practitioners by providing advice on whether and how to pursue a digital transformation and improve their internal governance and social responsibility practices. This study demonstrates its originality by reviewing the existing literature from three theoretical perspectives: stakeholder, signaling and reputation, and identifying the research gap that the study addresses. This study also compares its findings with previous studies and discusses the implications and limitations of its research. This study also proposes directions for future research based on its findings.

The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.