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Awe is an important yet largely overlooked emotion in tourism. This paper aims to reveal the underlying mechanism of the effects of nature-inspired awe on stimulating tourists' environmentally responsible behavior (TERB) intention by delving into the serial mediation effect of state construal level, small-self perception and state connectedness to nature (CNT).

This research was built upon the appraisal theory of emotion. Study 1 was a scenario-induced quasi-experimental study to test the proposed model linking awe, small-self perception, state CNT and TERB intention. A total of 271 valid questionnaires were collected via an online questionnaire platform. Study 2 was a field study designed to replicate the findings of Study 1 and further uncover the mediating role of the state construal level. Study 2 was conducted in Baiyun Mountain Scenic Area, China. A total of 229 valid questionnaires were used for analysis.

This research deepens our understanding of the effects of nature-inspired awe in the tourism and travel fields. This research uncovers the underlying mechanism by which awe increases TERB intention through serial mediation. Specifically, awe inspires tourists to apply a higher level of construal, which makes tourists perceive a smaller self, making them feel more connected to nature and exert more intention to adopt ERB.

This research linked tourists' mindset (i.e. state construal level), internal (i.e. small-self perception) and external (i.e. state CNT) cognition in an integrated model, explaining how nature-inspired awe contributes to eliciting TERB intention. The findings add critical theoretical contributions to the travel and tourism literature and provide important implications for the tourism industry to inspire awe and benefit from such emotion.

敬畏在旅游中是一种十分重要的情绪, 但却鲜少被关注。本研究旨在深入研究解释水平状态、小我感知和自然关联感的链式中介效应, 揭示自然敬畏激发游客环境责任行为意向的内在作用机制。

本研究的基础理论为情绪评价理论。研究一通过场景诱导的准实验研究, 检验将敬畏、小我感知、自然关联感和游客责任行为意向的假设模型; 研究一以网络问卷平台收集的271份有效问卷数据进行分析。研究二是一项在中国白云山风景区开展的实地研究, 旨在检验研究一的研究结果, 并进一步揭示解释水平状态的中介效应; 研究二采用229份有效问卷数据进行分析。

本研究揭示了敬畏通过链式中介作用影响游客环境责任行为意向的内在作用机制, 深化了对自然敬畏在旅游和旅行领域价值的理解。具体而言, 本研究发现敬畏激发了游客启动更高的解释水平, 这使游客感知到更渺小的自我, 并促使他们感到与自然的联系更加紧密, 从而提升了游客的环境责任行为意向。

本研究将游客的心理定式（即解释水平状态）、内在认知（即小我感知）和外部认知（即自然关联感）整合到一个综合模型中, 解释了自然敬畏引发游客环境责任行为意向的作用机制。研究结果为旅游研究提供了重要的理论贡献, 也为旅游行业如何在实践中激发敬畏感并从中获得效益提供了重要的实践启示。

El asombro es una emoción importante pero en gran medida ignorada en el turismo. Esta investigación pretende revelar el mecanismo subyacente de los efectos del asombro inspirado por la naturaleza en la estimulación de la intención del comportamiento responsable con el medio ambiente (TERB) de los turistas, profundizando en el efecto mediador en serie del nivel de interpretación del estado, la percepción del pequeño yo y la conexión del estado con la naturaleza (CNT).

Esta investigación se basó en la teoría de la valoración de la emoción. El estudio 1 fue un estudio cuasiexperimental inducido por escenarios para probar el modelo propuesto que vincula el sentimiento de asombro, la percepción del pequeño yo, el estado CNT y la intención TERB. Se recogieron 271 cuestionarios válidos a través de una plataforma de cuestionarios en línea. El Estudio 2 fue un estudio de campo diseñado para replicar los hallazgos del Estudio 1 y descubrir más a fondo el papel mediador del nivel de interpretación del estado. El estudio 2 se llevó a cabo en la zona escénica de la montaña de Baiyun (China). Se utilizó un total de 229 cuestionarios válidos para el análisis.

Esta investigación profundiza en nuestra comprensión de los efectos del asombro inspirado por la naturaleza en los ámbitos del turismo y los viajes. Esta investigación descubre el mecanismo subyacente por el que el asombro aumenta la intención de TERB a través de la mediación en serie. En concreto, el asombro inspira a los turistas a aplicar un mayor nivel de interpretación, lo que hace que los turistas perciban un yo más pequeño, lo que les hace sentirse más conectados con la naturaleza y ejercer así una mayor intención de adoptar TERB.

Esta investigación vinculó la mentalidad de los turistas (es decir, el nivel de nterpretación del estado), la cognición interna (es decir, la percepción de un yo más pequeño) y la externa (es decir, la CNT del estado) en un modelo integrado, explicando cómo el asombro inspirado por la naturaleza contribuye a suscitar la intención TERB. Los hallazgos añaden contribuciones teóricas críticas a la literatura sobre viajes y turismo y proporcionan implicaciones importantes para que la industria turística inspire asombro y se beneficie de dicha emoción.

Bearings play a critical role in the reliable operation of induction machines, and their failure can lead to significant operational challenges and downtime. Detecting and diagnosing these defects is imperative to ensure the longevity of induction machines and preventing costly downtime. The purpose of this paper is to develop a novel approach for diagnosis of bearing faults in induction machine.

To identify the different fault states of the bearing with accurately and efficiently in this paper, the original bearing vibration signal is first decomposed into several intrinsic mode functions (IMFs) using variational mode decomposition (VMD). The IMFs that contain more noise information are selected using the Pearson correlation coefficient. Subsequently, discrete wavelet transform (DWT) is used to filter the noisy IMFs. Second, the composite multiscale weighted permutation entropy (CMWPE) of each component is calculated to form the features vector. Finally, the features vector is reduced using the locality-sensitive discriminant analysis algorithm, to be fed into the support vector machine model for training and classification.

The obtained results showed the ability of the VMD_DWT algorithm to reduce the noise of raw vibration signals. It also demonstrated that the proposed method can effectively extract different fault features from vibration signals.

This study suggested a new VMD_DWT method to reduce the noise of the bearing vibration signal. The proposed approach for bearing fault diagnosis of induction machine based on VMD-DWT and CMWPE is highly effective. Its effectiveness has been verified using experimental data.

The purpose of this study is to analyze the potential mediating role of employee engagement in the relationship between gratitude and subjective well-being (SWB) of employees working in the information technology (IT) sector in India. The study investigated a moderated mediation model for gratitude and SWB, treating employee engagement as a mediator and gender as a moderator.

Data was collected from 162 professionals working IT sector in India. Process Macro, AMOS and IBM SPSS 22 were used to analyze the mediation and moderation effects.

The results depicted that employee engagement fully mediates the positive association between gratitude practice and the SWB of employees as well as the demographic variable; gender also demonstrated a full moderation effect between them.

This research may be one of the few studies from the Indian context that explore whether gratitude practiced by employees working in the IT sector can play a significant role in impacting their SWB. Past research models had not introduced employee engagement’s indirect impact on the examined variables.

The advent of online live streaming platforms (OLSPs) and online health communities (OHCs) has expedited the integration of traditional medical services with Internet new media technology. Since the practice of physicians conducting live streaming is a relatively new phenomenon, the potential cross-platform effects of such physicians’ live streaming have not received adequate attention.

This study collected data from 616 physicians specializing in cardiology, obstetrics and gynecology and neurology between April and November 2022 on Live.Baidu.com and WeDoctor.com. It constructed a panel data set comprising a total of 4,928 observations over an 8-month period and validated the model using empirical analysis with the fixed-effects method.

We find evidence of cross-platform influence in online healthcare. Physicians’ live streaming behavior (whether live or not and the heat of their streams) on OLSPs positively impacts both their consultation and reputation on OHCs. Additionally, physicians’ ability positively moderates the relationships between live streaming heat and their performance (in terms of consultation volume and reputation) on OHCs. However, ability does not moderate the relationship between physicians’ live streaming status (live or not) and their performance (in terms of consultation and reputation) on OHCs. Furthermore, the attractive appearance of the physicians also significantly moderates the impact in a positive way.

This is one of the pioneering studies on physicians’ live streaming. The study offers vital guidance for physicians and patients utilizing dual platforms and holds significant reference value for platform operators (such as OLSPs and OHCs) aiming to optimize platform operations and for the government in policy formulation and industry regulation.

The purpose of this paper is to propose a new grey prediction model, GOFHGM (1,1), which combines generalised fractal derivative and particle swarm optimisation algorithms. The aim is to address the limitations of traditional grey prediction models in order selection and improve prediction accuracy.

The paper introduces the concept of generalised fractal derivative and applies it to the order optimisation of grey prediction models. The particle swarm optimisation algorithm is also adopted to find the optimal combination of orders. Three cases are empirically studied to compare the performance of GOFHGM(1,1) with traditional grey prediction models.

The study finds that the GOFHGM(1,1) model outperforms traditional grey prediction models in terms of prediction accuracy. Evaluation indexes such as mean squared error (MSE) and mean absolute error (MAE) are used to evaluate the model.

The research study may have limitations in terms of the scope and generalisability of the findings. Further research is needed to explore the applicability of GOFHGM(1,1) in different fields and to improve the model’s performance.

The study contributes to the field by introducing a new grey prediction model that combines generalised fractal derivative and particle swarm optimisation algorithms. This integration enhances the accuracy and reliability of grey predictions and strengthens their applicability in various predictive applications.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

Building Information Modeling (BIM) competitions are a beneficial approach to enhance BIM education, offering students practical experience in BIM application, including mastering workflows and technical tools. However, research exploring the individual perceptions influencing participation intentions and behaviors in BIM competitions is limited. Therefore, this study aims to investigate the factors affecting university students' behavioral intention and behavior in BIM competitions, providing theoretical support for BIM competitions and educational reform.

This study employs the Structural Equation Modeling (SEM) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to analyze the factors influencing BIM competition participation among 970 Architecture, Engineering, and Construction (AEC) university students.

The results of the study show that social influence, attitude, and self-efficacy play critical roles in shaping students' intentions to participate in BIM competitions. Furthermore, self-efficacy, facilitating conditions, and behavioral intention significantly influence students' actual engagement in such competitions. Surprisingly, effort expectancy negatively influences intentions, as less challenging tasks can lead students to perceive their participation as less impactful on their skills and learning, reducing their behavioral intention to participate.

This research provides valuable insights into the effectiveness of BIM competitions in enhancing BIM education for AEC students. Extending the UTAUT model to include self-efficacy and attitude, provides a novel perspective for understanding students' intentions and behaviors regarding BIM competitions. The study’s theoretical support proposes incorporating BIM competitions to augment BIM teaching methods and offers suggestions for advancing the efficacy of students' involvement in BIM competitions within higher education, thus contributing to educational reform in the AEC sector.

The purpose of this paper is to explore the determinants of entrepreneurs’ subjective social status perception (SSP) on firm international behaviors based on the upper echelons theory and social class theory.

To test the hypotheses, the authors studied a large sample of 10,823 small- and medium-sized private Chinese enterprises from 2006 to 2014.

The results showed that entrepreneurs with higher status perception prefer international activity and firms have higher export intensity and intention. In addition, the social capital of entrepreneurs and institutional environment amplifies the positive relationship between SSP and international behavior.

This paper contributes to research on the upper echelon of management and extends our understanding of how managerial social characteristics influence international strategic decision-making. Besides, it also contributes to the emerging stream of social status research in international expansion studies and expand researchers’ limited understanding of the effects of social status in business settings.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Health misinformation on social media threatens public health. A critical question that sheds light on the propagation of health misinformation across social media platforms revolves around identifying the specific types of social media users susceptible to this issue. This study provides an initial insight into this matter by examining the underlying psychological mechanism that renders users susceptible to health misinformation.

In this study, we developed an integrated model of susceptibility to health misinformation, drawing on the motivation-opportunity-ability theory and the elaboration likelihood model. We collected the data from a sample of 342 social media users in China. Furthermore, the fuzzy-set qualitative comparative analysis was adopted to examine the proposed model and uncover the causal recipes associated with susceptibility to health misinformation.

The results indicated that there are three configural types of users that are susceptible to health misinformation: the health-consciousness core-driven type, the popularity-driven core type and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing susceptibility to health misinformation.

This study contributes to the social media literature by identifying various psychological traits that lead to social media users’ susceptibility to health misinformation. Additionally, the study provides comprehensive guidance on how to mitigate the spread of health misinformation.