Search results

The restoration and strengthening of QT600 is an industry bottleneck challenge. The Co-12 cladding layer has great wear and corrosion resistance. The purpose of this paper is to quantitatively reveal the transient evolution law of the corrosion process of Co-12 cladding layer on QT600 surface.

In this paper, a three-dimensional numerical model of the corrosion process of Co-12 cladding layer by QT600 laser cladding is established. The interaction between pitting pits and corrosion medium is considered to reveal the transient evolution of ion concentration, electrode potential, pH and corrosion rate at different locations.

The calculation shows that the ion concentration in pitting pit changes Cl⁻>Co²⁺>Na⁺, pH value decreases from top to bottom and corrosion rate at bottom is greater than that at top. The electrochemical corrosion test of Co-12 cladding layer was carried out. It is shown that the current density of QT600 increases by an order of magnitude compared to the Co-12 cladding layer, and the corrosion rate is 4.862 times higher than that of the cladding layer.

The results show that Co-12 cladding layer has great corrosion resistance, which provides an effective way for QT600 protection.

This study investigates the impact of ESG rating disagreements on stock performance in the Chinese A-share market, focusing on immediate and short-term market reactions and the risk of future stock price crashes. Using data from the Shanghai and Shenzhen stock exchanges, we analyze 17,006 firm-year observations from 2010 to 2021. Stock return data are sourced from the Wind database, while additional financial metrics are obtained from the China Stock Market and Accounting Research (CSMAR) database. Corporate governance information is drawn from the China National Research Data Service (CNRDS) database. Our findings indicate that higher levels of ESG divergence significantly increase the risk of future stock price crashes. Furthermore, the presence of independent directors moderates this relationship, reducing the likelihood of such crashes. Immediate market reactions to ESG rating disagreements are also significant, underscoring the need for transparency and alignment among rating agencies. The study highlights the importance of robust corporate governance and standardized ESG rating methodologies to mitigate associated risks. Policy recommendations include promoting transparency in ESG rating processes and enhancing the role of independent directors in corporate governance.

This study empirically tests the influence of key elements on intent to use electronic (E)-ticket through the “Stimulus–Organism–Response (SOR)” framework and structural equation model. Results highlight factors such as E-trust Technology, Ease of Use, E-satisfaction, Intention to Purchase E-ticket, Price Perception, and Usefulness; the study comprehensively analyzes the factors influencing the decision-making process of consumers when it comes to purchasing E-tickets. The research employs a hypothesis-driven approach and gathers survey results from 408 observants to find out the intention of consumers to use E-tickets for using transportation services, which help transportation providers understand the importance of its platform to benefit customers who are willing to change their perceptions from paper tickets to E-tickets, the reason customers buying E-ticket rather than paper ticket while using digitalization to help firms control their cost and building internal legitimacy by better managing their internal stakeholder.

This study aims to explore the spatio-temporal dynamic characteristics and influencing factors of the coordination degree of the three systems of digital economy, energy and human habitat in Western China and to provide academic research support for promoting coordinated and sustainable development in similar regions of the world.

Based on system theory and sustainable development theory, this study primarily uses the coupled coordination degree model to assess the degree of coordination between the three systems.

The findings of this study indicate that: The three systems’ overall coordination is low. The distribution of the degree of coordination has spatial differences and its coefficient of variation is small. The probability of the coordination type changing for the better is greater than that of the opposite, and neighboring provinces interact with one another. The old-age dependence ratio, the resident population’s urbanization rate and public budget expenditure have the strongest gray association with the degree of coordination.

This study’s findings will be valuable for policymakers in developing policies to promote the coordinated and sustainable growth of the region’s digital economy, energy and human habitat. Additionally, the findings will aid in facilitating regional exchanges and cooperation to enhance the level of sustainable development.

This study’s findings will contribute to increased social interest in coordinating sustainable growth in the digital economy, energy and human habitat.

This study examines the digital economy, energy and human habitat within the same framework and investigates spatial spillover effects using spatial Markov chains.

This study investigates the impact of residential type and neighborhood security on public trust in the police in Ghana, while controlling for demographic factors and police-related variables.

Data were collected during the ninth round of the Afro-Barometer survey conducted in Ghana between 2019 and 2021 with a sample size of 2,369 participants. The study employed binary logistic regression analysis to examine the relationship between the independent variables (residential type and neighborhood security) and the dependent variable (trust in the police).

The results indicate that living in traditional housing is associated with lower levels of trust in the police compared with other residential types. Unexpectedly, neighborhood security did not emerge as a statistically significant predictor of police trust. However, police corruption and the use of force were negatively associated with trust, whereas police professionalism positively predicted trust. Interestingly, unnecessary police stops were positively associated with trust, possibly reflecting a complex relationship between police visibility and public perceptions. This study also revealed ethnic and regional variations in police trust, highlighting the need for culturally sensitive policing approaches.

This study stands out in three key aspects. First, it represents one of the first attempts to examine how residential type and neighborhood security influence public trust in law enforcement agencies in Ghana. Second, this study is among the few to investigate the relationship between neighborhood conditions and trust in police using a sample that is representative of the entire nation. Finally, these findings contribute to the understanding of the multifaceted nature of public trust in the police within the Ghanaian context and offer insights for policymakers and law enforcement agencies to enhance police-community relations.

This paper aims to find a suitable solution to degrade the C.I. Reactive Red 24 (RR24) dyeing wastewater by using sodium persulphate to recycle water and inorganic salts.

The effects of temperature, the concentration of inorganic salts and Na₂CO₃ and the initial pH value on the degradation of RR24 were studied. Furthermore, the relationship between free radicals and RR24 degradation effect was investigated. Microscopic routes and mechanisms of dye degradation were further confirmed by testing the degradation karyoplasmic ratio of the product. The feasibility of the one-bath cyclic dyeing in the recycled dyeing wastewater was confirmed through the properties of dye utilization and color parameters.

The appropriate conditions were 0.3 g/L of sodium persulphate and treatment at 95°C for 30 min, which resulted in a decolorization rate of 98.4% for the dyeing wastewater. Acidic conditions are conducive to rapid degradation of dyes, while ·OH or SO₄⁻· have a destructive effect on dyes under alkaline conditions. In the early stage of degradation, ·OH played a major role in the degradation of dyes. For sustainable cyclic dyeing of RR24, inorganic salts were reused in this dyeing process and dye uptake increased with the times of cycles. After the fixation, some Na₂CO₃ may be converted to other salts, thereby increasing the dye uptake in subsequent cyclic staining. However, it has little impact on the dye exhaustion rate and color parameters of dyed fabrics.

The recommended technology not only reduces the quantity of dyeing wastewater but also enables the recycling of inorganic salts and water, which meets the requirements of sustainable development and clean production.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

Heterogeneous graphs, composed of diverse nodes and edges, are prevalent in real-world applications and effectively model complex web-based relational networks, such as social media, e-commerce and knowledge graphs. As a crucial data source in heterogeneous networks, Node attribute information plays a vital role in Web data mining. Analyzing and leveraging node attributes is essential in heterogeneous network representation learning. In this context, this paper aims to propose a novel attribute-aware heterogeneous information network representation learning algorithm, AAHIN, which incorporates two key strategies: an attribute information coverage-aware random walk strategy and a node-influence-based attribute aggregation strategy.

First, the transition probability of the next node is determined by comparing the attribute similarity between historical nodes and prewalk nodes in a random walk, and nodes with dissimilar attributes are selected to increase the information coverage of different attributes. Then, the representation is enhanced by aggregating the attribute information of different types of high-order neighbors. Additionally, the neighbor attribute information is aggregated by emphasizing the varying influence of each neighbor node.

This paper conducted comprehensive experiments on three real heterogeneous attribute networks, highlighting the superior performance of the AAHIN model over other baseline methods.

This paper proposes an attribute-aware random walk strategy to enhance attribute coverage and walk randomness, improving the quality of walk sequences. A node-influence-based attribute aggregation method is introduced, aggregating neighboring node attributes while preserving the information from different types of high-order neighbors.

Due to the close connection between urban cluster and carbon emissions (CEs) but a lack of study on it of the construction industry, this paper aims to explore the relationship between the polycentric spatial structure (PSS) of the urban clusters and CEs of the construction industry (CECI).

This research uses panel data of 10 Chinese urban clusters from 2006–2021, calculates their PSSs in the aspects of economy and employment and adopts a panel regression model to explore the effect of the spatiotemporal characteristics of the PSSs on the CECI.

First, the CECI in 10 Chinese urban clusters showed a rising trend in general, and the CECI in the Yangtze River Delta (YRD) was much higher than those in the rest of urban clusters. Second, both Shandong Peninsula (SP) and Guangdong-Fujian-Zhejiang (GFZ) exhibited high degrees of polycentric characteristics, while Beijing-Tianjin-Hebei (BTH) showed weaker degrees. Third, the results demonstrated that the polycentric development of urban clusters did not help reduce the CECI but rather promote the CE. The polycentric index, considering the linear distance from the main center to sub center, had a more significant impact on the CECI.

Previous studies have investigated the impact of urban spatial structure (USS) on CEs; however, few of them have studied in the field of construction industry. Moreover, most research of CEs have concentrated at the national and provincial levels, with fewer studies on urban clusters. This paper contributes to this knowledge by investigating how the PSS of urban cluster influence the CECI.

Amid the pressing global need for sustainable development and environmental protection, exploring effective pathways to foster green innovation has become crucial. This study aims to examine the impact of digitalization on green innovation by analyzing its interactions with micro and macro factors.

This paper adopts a multi-level perspective (MLP) with a multi-agent framework to study how different factors impact green innovation efficiency. This paper uses fuzzy-set qualitative comparative analysis (fsQCA) on 30 Chinese provinces from 2012 to 2021 to identify key conditions and pathways for green innovation efficiency.

The findings reveal that digitalization alone does not constitute a necessary condition for green innovation. Rather, digitalization needs to be configured with other factors to form dynamic causal paths. In 2012–2016, a single path type (digitalization coupled with regional innovation and marketization) exists. In 2017–2021, two causal path types [digitalization and foreign direct investment (FDI), digitalization and regional innovation] emerge.

The study has three theoretical contributions. First, while previous research studies often focus on single factors, the study examines the complexity of green innovation from a configurational perspective. Using the fsQCA method, this paper explores complex interactions and asymmetric causal relationships among multi-level factors. Second, this paper presents a novel theoretical framework that integrates the MLP framework with the multi-agent framework, facilitating a multi-dimensional analysis of green innovation. This synthesis elucidates the complex network of relationships, interactions and dependencies that propel green innovation. Third, responding to the call in international dynamic QCA research, this paper uses the multi-period QCA method. This allows for a detailed stage-by-stage comparative analysis, elucidating green innovation paths and revealing evolutionary trends of “configurational diversity” and “factor concentration.” This research offers practical insights for policymakers and stakeholders to develop more effective, tailored strategies for promoting green innovation.

Digitalization alone cannot fully drive green innovation; it must be combined with factors such as marketization, regional innovation and FDI. To achieve this, promote market-oriented reforms to enhance market mechanisms and encourage participation in green innovation projects through incentives. Increase investment in regional innovation, establish platforms for resource sharing and technological exchange and support cooperation between local governments and businesses. Additionally, it attracts FDI by creating favorable policies and a conducive business environment. Adapting policies to evolving conditions is crucial. Regularly assess and update policies to ensure their effectiveness and relevance in the face of changing technological and market landscapes. Optimize approval processes, reduce bureaucratic hurdles and improve policy implementation efficiency. Regions should also tailor strategies to their specific needs: those with high digitalization but lacking FDI should focus on building a robust research and development (R&D) personnel base, while regions with high FDI but insufficient local talent should attract skilled professionals through talent attraction programs and partnerships with international universities. Continuously adapting strategies ensures that regions can effectively drive sustainable development and green innovation.

The research advances the understanding of green innovation by examining multi-level configuration effects, introducing an integrated framework and conducting stage-by-stage comparative analysis. These contributions collectively enhance the theoretical foundation and practical applicability of promoting green innovation in an increasingly digitalized world.

This study offers invaluable theoretical insights and practical pathways for policymakers and decision-makers, providing tailored strategies to promote green innovation. By understanding the complex interactions between digitalization and other factors, decision-makers can better leverage digitalization for sustainable development and environmental protection.