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This study explores the interplay between the spirit of place, brand equity and tourists’ travel intentions within the context of culinary tourism at destinations influenced by Confucian culture. It examines how Confucian values, such as benevolence, righteousness, courtesy, wisdom and trust, shape the personality of culinary tourism destinations and how this personality influences tourists’ travel intentions both directly and indirectly through brand equity.

The researchers develop a conceptual framework highlighting dimensions of destination personality derived from Confucian values. These values serve as indicators of brand equity, focusing on dimensions like brand image, perceived quality and brand loyalty in the culinary tourism sector. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze data from 503 tourists, examining the relationships between the Confucian-inspired destination personality, brand equity and tourists’ travel intentions.

The results show that tourists resonate strongly with the five Confucian personality traits, which significantly influence their travel intentions either directly or indirectly through enhanced brand equity. The study highlights the pivotal role of Confucian culture in shaping the destination personality and brand equity, which, in turn, drives tourists’ travel behaviors.

This study reveals how the spirit of place influences tourist behavior through brand equity, providing new perspectives and practical strategies for destination branding and development.

This study is the first to examine the relationships between spirit of place, brand equity and travel intentions within a Confucian cultural context, expanding the theoretical understanding of culinary tourism branding.

The purpose of this study is to reveal the significant contribution of MXene on enhancing tribological properties and to obtain the influence mechanism of various factors on friction characteristics of rolling bearing under extreme conditions.

Under extreme working conditions, the friction characteristics of rolling bearings directly determine the safety and reliability of the transmission system. In this study, MXene is added to the origin lubricating grease (OLG) of rolling bearing to enhance their friction characteristics. Then, the effects of inner ring speed, radial load, grease filling volume and other factors on the friction coefficient of rolling bearing are analyzed using the Taguchi method.

The results indicate that the ranking of various factors affecting the friction coefficient is: radial load, inner ring speed, MXene additive content in grease and grease filling volume. Especially, the radial load and inner ring speed exhibit extremely significant effects, while the MXene additive content in grease (P < 0.05) has a significant influence on the friction coefficient of rolling bearing. The optimal condition for rolling bearing lubricated with MXene additives lubricating grease (MALG) achieves the lowest friction coefficient of 0.0049 under 1,000 rpm, 9 kN and 35% grease filling volume.

This study could offer reference solution for utilizing MXene nano-lubrication to fufill the demands of precision, heavy-load, or long-lifespan bearings. Furthermore, the lubrication approach has the potential to be expanded into aerospace, defense, and various industrial fields, thereby significantly promoting its practial engineering applications.

The digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.

This paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.

It is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.

This study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.

Apartments have become a representative urban housing type for mass housing construction; therefore, interest in low-rise residential areas has decreased. Low-rise residential areas have proved to be a poor residential environment for all aspects of life because of the density of the old buildings. Using the Moa Towns project as a case study, this research explores the steps for revitalizing low-rise residential environments, emphasizing communities.

The study first investigated the historical changes in urban housing types in Korea. Through a review of the related literature, a systematic analysis framework was developed. The residential environments of the case study and the questionnaire survey were analyzed through the framework, with a focus on the quality of housing.

To improve the quality of housing for residents, a housing plan is needed to ensure safety and comfort. To establish an accessible residential environment infrastructure, improve the quality of housing, and encourage social relationships between neighbors, community facilities within a 15-min walk should be installed. To increase interaction between neighbors, a circular pedestrian system can be created by establishing a community street.

This study is significant in that it focuses on people in revitalizing the community; identifies factors for physical improvement, exchange activities, and facility support; and presents a conceptual framework for building a residential environment in low-rise residential areas. The results are critical to the quality of housing and community facilities for low-rise residential development.

We aim to examine two issues. First, we intend to identify the best performing expected return proxies. Second, we investigate whether the expected return proxies for individual stocks can track the corresponding realized returns during extremely good or extremely bad times of the economic environment related to business conditions, stock market valuation and broad market performance.

We construct four sets of expected return proxies, including: (1) characteristic-based proxies; (2) standard risk-factor-based proxies; (3) risk-factor-based proxies that allow betas to vary with firm characteristics and (4) macroeconomic-variable-based proxies. First, we estimate expected returns for individual stocks using newly developed methods and evaluate the performance of these expected return proxies based on the minimum variance criterion of Lee et al. (2020). Second, we regress expected return proxies and realized returns on indicator variables that capture the extreme phases of the economic environment. Then we compare the estimated coefficients from these two sets of regressions and see if they are similar in magnitude via formal hypothesis testing.

We find that characteristic-based proxies and risk-factor-based proxies that allow betas to vary with firm characteristics are the two best performing proxies. Therefore, it is important to allow betas to vary with firm characteristics in constructing expected return proxies. We also find that model-based expected return proxies do a reasonably good job capturing actual returns during extremely bad and extremely good phases of business cycles measured by leading economic indicators, consumer confidence and business confidence. However, there is a large gap between the adjustment of model-based expected returns and realized returns during extreme episodes of stock market valuation or broad market performance.

We examine four types of expected return proxies and use the newly developed methodology as in Lee et al. (2020) to see which one is the best. In addition, we document whether model-based expected returns from individual stocks adjust partially or fully to keep pace with actual returns in response to changing economic conditions. No prior studies have examined these two issues.

Drawing on social information processing theory, this study investigates how platform leadership influences employees’ innovative behavior. Specifically, we propose a theoretical model that incorporates creative self-efficacy as a mediator and organizational identification as a moderator.

Multisource data were collected in three waves from 304 employees and their 65 leaders in China.

Hierarchical linear modeling (HLM) results reveal: (1) a positive association between platform leadership and subordinates’ innovative behavior; (2) creative self-efficacy as a mediator in the relationship between platform leadership and subordinates’ innovative behavior and (3) organizational identification as a moderator in the indirect relationship between platform leadership and subordinates’ innovative behavior through creative self-efficacy, with the indirect effect being stronger when organizational identification is high than when it is low.

From a cross-level perspective, our findings revealed the underlying mechanisms and boundary conditions under which platform leadership influences followers’ innovative behavior.

Current multi-source image fusion methods frequently overlook the issue of detailed features when employing deep learning technology, resulting in inadequate target feature information. In real-world mission scenarios, such as military information acquisition or medical image enhancement, the prominence of target feature information is of paramount importance. To address these challenges, this paper introduces a novel infrared-visible light fusion model.

Leveraging the foundational architecture of the traditional DenseFuse model, this paper optimizes the backbone network structure and incorporates a Unique Feature Encoder (UFE) to meticulously extract the distinctive features inherent in the two images. Furthermore, it integrates the Convolutional Block Attention Module (CBAM) and the Squeeze and Excitation Network (SE) to enhance and replace the original spatial and channel attention mechanisms.

Compared to other methods such as IFCNN, NestFuse, DenseFuse, etc., the values of entropy, standard deviation, and mutual information index of the method presented in this paper can reach 6.9985, 82.6652, and 13.6022, respectively, which are significantly improved compared with other methods.

This paper presents a UFEFusion framework that synergizes with the CBAM attention mechanism to markedly augment the extraction of detailed features relative to other methods. Moreover, the framework adeptly extracts and amplifies unique features from disparate images, thereby elevating the overall feature representation capability.

This study aims to systematically review and critically assess research methods for studying aging populations in tourism and hospitality. It identifies gaps and provides recommendations for advancing methodological innovation in response to emerging research agendas.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review of existing literature on aging populations in tourism and hospitality. Searches were performed in major databases, including Scopus and Web of Science, to collect peer-reviewed, English articles published in Social Sciences Citation Index (SSCI)-indexed tourism and hospitality journals from 1965 to 2025. The methodologies employed in the selected studies were thoroughly analyzed.

A total of 184 articles were included in the final analysis. The review revealed that current research methods predominantly rely on surveys and interviews, with limited methodological diversity. Gaps were identified, and a conceptual model was proposed to advance cross-disciplinary integration and foster innovative methods that could more comprehensively capture the complexities of senior tourists, particularly those with health conditions.

This paper is likely the first to synthesize research methodologies within this specific context, outlining a path forward for researchers to adopt more innovative, multidisciplinary approaches. This study lays the foundation for future empirical investigations into the behaviors and experiences of senior tourists, as well as the potential role of tourism in promoting healthy aging. Additionally, it provides valuable insights for tourism marketing practitioners to better accommodate this growing segment.

The purpose of this study is to explore the interfacial adhesion between superhydrophobic coatings FC-X (X = 1%, 2%, 3%, 4% and 5%) and the concrete substrate, along with the impact of FC-X on the water repellency characteristics of the concrete substrate.

One synthetic step was adopted to prepare novel F-SiO₂ NP hybrid fluororesin coating. The impact of varying mass fractions of F-SiO₂ NPs on the superhydrophobicity of FC-X was analyzed and subsequently confirmed through water contact angle (WCA) measurements. Superhydrophobic coatings were simply applied to the concrete substrate using a one-step spraying method. The interfacial adhesion between FC-X and the concrete substrate was analyzed using tape pasting tests and abrasion resistance measurements. The influence of FC-X on the water repellency of the concrete substrate was investigated through measurements of water absorption, impermeability and electric flux.

FC-4% exhibits excellent superhydrophobicity, with a WCA of 157.5° and a sliding angle of 2.3°. Compared to control sample, FC-X exhibits better properties, including chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

This study offers a thorough investigation into the practical implications of enhancing the durability and water repellency of concrete substrates by using superhydrophobic coatings, particularly FC-4%, which demonstrates exceptional superhydrophobicity alongside remarkable chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

Through the examination of the interfacial adhesion between FC-X and the concrete substrate, along with an assessment of FC-X’s impact on the water repellency of the concrete, this paper provides valuable insights into the practical application of superhydrophobic coatings in enhancing the durability and performance of concrete materials.

The purpose of this paper is to mesoscopically analyze the impact of parameter variations in the random pore structure on the stress distribution of layered-porous sintered silver used in high-power electronics, and to conduct a variable importance analysis of the parameter variations in the random pore structure.

Sintered silver, featuring a porous structure, improves thermal and mechanical performance by effectively absorbing stress and facilitating heat dissipation. To ensure the performance and scalability of layered-porous sintered silver, this paper uses Gaussian random fields to model the random pore structure and performs a sensitivity analysis on pore characteristic length and porosity, both of which significantly impact the stress distribution within the sintered silver layer. First, multiple sets of random pore models with varying characteristic lengths and porosities were generated using Gaussian random fields. Then, the maximum stress of the sintered silver layer containing random pores under power cycling conditions was extracted. Finally, the Morris screening method was used to perform a sensitivity analysis on the variables of the random pore structure that affect the maximum stress in the sintered silver layer. The systematic evaluation of the parameter variations in the random pore structure was conducted to assess their impacts on the maximum stress in the sintered silver layer.

Due to the high randomness of the pore structure generated by the Gaussian random field function, the maximum stress in the sintered layer fluctuates with different mesoscopic models. After systematic evaluation using the Morris screening method, it was found that the maximum stress in the sintered silver layer is most sensitive to the variation in the pore characteristic length in the x-direction. Reducing the length of pores in the x-direction can significantly decrease the stress concentration between pores in the sintered silver layer after power cycling.

This paper innovatively uses a Gaussian random field to model the mesoscopic structure of layered-porous sintered silver for high-power electronics, and applies the Morris screening method to perform variable importance analysis on the stress distribution results within the sintered silver layers. The mesoscopic study demonstrates that the maximum stress in the sintered silver layer is most sensitive to changes in the pore characteristic length in the x-direction.