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This study is a pilot study exploring the usefulness and ease of use of a prototype VR PetCPR system and discusses the possibility of using it to facilitate pet healthcare skills acquisition. The designed VR PetCPR training system aims to provide pet healthcare professionals with an inexpensive, accessible and reliable CPR training tool and refine their skills in a controlled and simulated environment.

The study was conducted in a one-day workshop. The workshop consisted of the morning section (Section A) and the afternoon section (Section B). Section A was the knowledge acquisition stage. Section B is the VR PetCPR stage. Trainees were then given 30 min to experience the VR PetCPR set. When trainees were ready, they were required to complete two trials of dog CPR practice. After the practice, trainees completed the questionnaire and reported their attitudes toward VR PetCPR practice.

Overall, trainees held positive attitudes toward the effectiveness and usefulness of the VR PetCPR. After practicing skills via VR CPR, over half of the trainees responded that the system is effective in helping them understand the essential knowledge (e.g. operation status, operation positions, etc.) of performing CPR skills on a 30-pound dog. A significantly positive attitude was reported on trainees’ perceptions toward the ease of use of practicing their chest compression skills with the PetCPR. The positive attitudes significantly outnumbered the negative attitudes on explicit instruction and guidance, accessibility, convenience in practice and straightforward interface.

From data collected from 16 animal hospitals in the United States, Europe and Australia with 709 cases, 147 dogs (28%) and 58 cats (30%) temporarily attained ROSC during CPR, and 14 dogs (3%) and four cats (2%) survived to hospital discharge. Training veterinary CPR techniques and implementing RECOVER guidelines still have a long way to go. However, recent virtual reality simulations for CPR training were mainly designed for human patients CPR (Issleib et al., 2021; Liu et al., 2022; Almousa et al., 2019; Wong et al., 2018). The VR PetCPR remains a missing puzzle in the current VR training designs.

The purpose of this paper is to propose a mobile and social-based question-and-answer (Q&A) system that analyzes users' social relationships and past answering behavior, considers users' interest similarity and answer quality to infer suitable respondents and forwards the questions to users that are willing to give high quality answers.

This research applies first-order logic (FOL) inference calculation to generate question/interest ID that combines a users' social information, interests and social network intimacy to choose the nodes that can provide high-quality answers. After receiving a question, a friend can answer it, forward it to their friends according to the number of TTL (Time-to-Live) hops, or send the answer directly to the server. This research collected data from the TripAdvisor.com website and uses it for the experiment. The authors also collected previously answered questions from TripAdvisor.com; thus, subsequent answers could be forwarded to a centralized server to improve the overall performance.

The authors have first noticed that even though the proposed system is decentralized, it can still accurately identify the appropriate respondents to provide high-quality answers. In addition, since this system can easily identify the best answerers, there is no need to implement broadcasting, thus reducing the overall execution time and network bandwidth required. Moreover, this system allows users to accurately and quickly obtain high-quality answers after comparing and calculating interest IDs. The system also encourages frequent communication and interaction among users. Lastly, the experiments demonstrate that this system achieves high accuracy, high recall rate, low overhead, low forwarding cost and low response rate in all scenarios.

This paper proposes a mobile and social-based Q&A system that applies FOL inference calculation to analyze users' social relationships and past answering behavior, considers users' interest similarity and answer quality to infer suitable respondents and forwards the questions to users that are willing to give high quality answers. The experiments demonstrate that this system achieves high accuracy, high recall rate, low overhead, low forwarding cost and low response rate in all scenarios.

Based on social cognitive theory, this study aims to investigate the influence of perceived overqualification (POQ) on employees’ cyberloafing behavior. The mediating role of moral disengagement and the moderating roles of organizational identification (OID) and organizational decline are further examined.

The authors collected 740 valid questionnaires from participants across multiple organizations. To minimize common method bias (CMB) and enhance the reliability of the findings, data were gathered at two different time points, with a 30-day interval.

POQ positively impacts cyberloafing through the mechanism of moral disengagement. Additionally, the indirect relationship between POQ and cyberloafing via moral disengagement is moderated by OID and organizational decline. Specifically, a higher degree of OID weakens the indirect effect of POQ on cyberloafing, while a higher level of perceived organizational decline strengthens this effect.

While most existing studies on cyberloafing focus on insufficient resources, such as role conflict and workload, the authors propose that surplus personal resources, exemplified by POQ, can also lead to cyberloafing. This research contributes to a broader understanding of antecedents of cyberloafing, highlighting the mechanism of ethical considerations and the interplay between personal qualifications, organizational identification and organizational decline.

The purpose of this paper is to investigate the effect of reward redemption programs on donation amount, donation percentage and donation intention in the context of a bank credit card.

A 2 × 2 × 3 experiment is implemented with 1,070 consumers accessing a national US-based sample with a small compensation. The authors use general linear model to test the proposed hypotheses.

The findings show the main effects of reward types, limited-time message and value of reward redemptions on the percentage of donations and overall donation intention to charity. The type of reward (cash/points) is found to interact with the limited-time message and with the value of reward redemptions.

No prior studies have addressed the relationship between credit card redemption rewards and scarcity messages in the donation context. The study contributes to the understanding of the effectiveness of credit card redemption rewards with scarcity message in improving a consumer’s donation intention.

TikTok, a social media application (app), was originally positioned as a short music video community suitable for young users, and the app is user-generated content (UGC) short video of vertical music. Users can make their own creative videos. Following the rhythm of the music, users can shoot various video content, personal talents, life records, performances, dances, plot interpretations, etc. However, what are the profiles and preferences of TikTok users, whereby the social media app is mainly developed by UGC? What is the impact of TikTok on the development of social media? In addition, what is UGC's social media model for user interactions in social networks? The purpose of this paper is to address and study these proposed issues.

All questionnaire items are designed as nominal and ordinal scales (not Likert scale). The obtained data from questionnaires are put into the relational database (N = 2,011). This empirical study takes Taiwan TikTok users as the research object, implements data mining analytics to generate user profiles through clustering analysis and further uses association rules’ analysis to analyze social media apps in social network interaction and social apps’ development by proposing two patterns and several meaningful rules.

This study finds that social media apps is a valuable practical research topic on online social media development. In addition, besides the TikTok, the authors eagerly await subsequent research to provide more valuable findings of social media apps in both theory and practice.

This study presents the research evidences that social media apps such as TikTok will be able to transcend the current development pattern of social media and make good use of the media and technology innovation of apps in social development and social informatics.

This paper aims to present an overview of permanent magnet linear flux-switching machines (PMLFSM), field excited LFSM and hybrid excited LFSM (HELFSM) topologies as presented in literature for transportation systems such as high-speed trains and maglev systems.

The structural designs of different configurations are thoroughly investigated, and their respective advantages and disadvantages are examined. Based on the geometry and excitation sources, a detailed survey is carried out. Specific design and space issues, such as solid and modular structures, structure strength, excitation sources placement, utilization of PM materials, and flux leakage are investigated.

PMLFSM provide higher power density and efficiency than induction and DC machines because of the superior excitation capability of PMs. The cost of rare-earth PMs has risen sharply in the past few decades because of their frequent use, so the manufacturing cost of PMLFSM is increasing. Owing to the influence of high-energy PMs and magnetic flux concentration, the efficiency and power density are higher in such machines. PM is the only excitation source in PMLFSM and has constant remanence, limiting its applications in a wide speed operation range. Therefore, the field winding is added in the PMLFSM to flexibly regulate the magnetic field, making it a hybrid excited one. The HELFSM possess better flux linkage, high thrust force density and better flux controlling ability, leading to a wide speed range. However, the HELFSM have problems with the crowded mover, as PM, field excited and armature excitation are housed on a short mover. So, for better performance, the area of each excitation component has to compete with each other.

Transportation of goods and people by vehicles is becoming increasingly prevalent. As railways play a significant role in the transportation system and are an integral part of intercity transportation. So, this paper presents an overview of various linear machines that are presented in literature for rail transit systems to promote sustainable urban planning practices.

The purpose of this study is to assess the performance of United Arab Emirates (UAE) Government e-services by using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology, integrating insights from the balanced scorecard (BSC) framework across financial, customer, internal business and learning and growth perspectives.

Using the fuzzy TOPSIS method, this paper evaluate three e-services in the UAE against 12 criteria representing the balanced scorecard perspectives. Expert evaluation and sensitivity analysis are used to identify the most sustainable e-service alternative.

The study findings emphasize the importance of prioritizing customer-centric metrics, improving service reliability and efficiency, and investing in employee training to enhance e-government service performance in the UAE. Sensitivity analysis reinforces the robustness of our results and identifies key criteria influencing decision-making.

The data was collected only from experts in selected UAE Government departments. This may affect the generalization of the findings. Also, only three e-services were evaluated. Future studies could include various e-services not covered in this study and use different multi-criteria decision-making methods.

Prioritizing customer satisfaction: Priority should be given to customer satisfaction as it is a critical factor in evaluating e-services because of its importance. It also highlights the importance of considering user feedback and ensuring that e-services have a high level of friendliness and responsiveness to their needs. It follows that minimizing errors and ensuring quick and efficient transactions are crucial. Emphasizing reliability and transaction efficiency: Reliable services and transaction efficiency are also essential criteria for evaluating e-government services. This suggests that e-government services should be designed to minimize errors and ensure that transactions are completed quickly and efficiently. Managing IT costs: To deliver e-government services affordably, effective IT cost management is crucial. This emphasizes how crucial it is to effectively manage IT costs to guarantee the efficient delivery of e-government services.

From a customer perspective, adopting BSC can create a favorable customer attitude, encourage long-term customer support, and increase customer satisfaction and loyalty. These factors have significant social implications for UAE and expatriate individuals who are using such e-government services.

This study contributes to the literature by showcasing the applicability of the fuzzy TOPSIS methodology in evaluating UAE e-government service performance. By examining multiple perspectives of the BSC, this paper provide valuable insights into enhancing the efficiency and effectiveness of e-services in the UAE Government sector.

Studies have explored the determinants of customer advocacy because of customer advocacy's vital role in improving the efficiency and effectiveness of marketing. The current research complements the existing literature in the hospitality field by examining the association between restaurant innovativeness and customer advocacy while also investigating the mediating roles of self-image congruity and customer engagement.

The statistical software AMOS version 25 and bootstrapping were employed to test the hypotheses. Purposive sampling was employed for participant recruitment, and a self-administered questionnaire was used to collect data. Data were collected from Taiwanese customers who had dined at selected restaurants.

The results from 385 restaurant customers reported that self-image congruity had an indirect impact on customer advocacy through customer engagement. Customer advocacy was influenced by restaurant innovativeness through the mediation of customer engagement. The influence of restaurant innovativeness on customer advocacy was positively and sequentially mediated by self-image congruity and customer engagement.

Restaurant innovativeness is linked to customer advocacy through self-image congruity and customer engagement. Thus, restaurant managers should implement strategies focusing on innovativeness to improve self-image congruity and engagement among customers.

The current research may be the first to provide a research model that explores restaurant innovativeness, self-image congruity, customer engagement and customer advocacy in the hospitality context. This study also has practical implications for enhancing customer advocacy.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.

This paper aims to contribute to understanding Brazilian fashion consumer behavior. The subsequent research question is formulated as follows: How are the consumers purchasing new clothes and disposing of used ones, and how is their awareness of sustainable fashion consumption and disposal of used clothes?

An online questionnaire was sent to nearly one thousand e-mails. A database was formed with 182 complete answers to 13 questions concerning consumer behavior toward sustainability, especially clothing acquisition, use and disposal. A multimethod approach was used to analyze the initial attributes, applying descriptive statistics, cluster analysis and data mining.

This survey obtained valuable answers from Brazilian fashion consumers grouped into four clusters. Age and yearly income were more critical in determining the clusters. Only four attributes were chosen by the algorithm to build the trees (age, annual income, yearly spending on clothes and how long the clothes are worn). The consumer's profile may help the fashion industry redirect investments in sustainability. The most critical factor leading to the sustainability of clothing fashion was the duration of the clothes. The study dealt with a limited sample size that was not representative of Brazil's broader population. Despite numerous attempts to seek responses through e-mail, the participant pool was predominantly composed of highly educated individuals.

This assessment of Brazilian consumer behavior toward sustainability and fashion presents essential knowledge to understand the relationships among variables affecting the purchase and discharge of clothes.