Can Stronger Family Connections Alleviate the Adverse Effects of Unemployment on Happiness? Evidence from Asian Countries

This study aims to investigate whether and how the family connection is critical to alleviate the negative effect of unemployment on people’s happiness by employing the World Values Survey data set regarding people in Chinese culture-related regions for empirical work. Empirically, we found family connections constitute a crucial factor in determining people’s happiness level. Except for living with parents, other family variables are positively significant in the happiness determination equation. Taking related measurements for family connections in the happiness determination equation is important in reducing estimation bias. Moreover, family connection reduces the fear of being unemployed and psychological losses from recession due to the worsening of job opportunities in economy. Stronger family connections can facilitate overcoming the stress and fear of being unemployed during recessions. Among the family-related variables, considering family important is of the largest marginal effect in alleviating the adverse effects of unemployment on happiness. This finding is robust among various age cohorts and between genders and among different model specifications. However, the ability of family connection to alleviate the adverse effect of unemployment on the happiness level of an unemployed worker is supported less by the data. We found that certain types of family connections might diminish the happiness of unemployed people, although the regression results are of no statistical significance. Those types of family connections include living with parents and considering family a crucial part of life

Research on the Application of Online and Offline Mixed Teaching Mode of Marketing Course Based on the BOPPPS Model

BOPPPS teaching fully integrates the advantages of online self-study and offline courses. This kind of teaching has been widely used in college education, and has proved to have a positive effect on improving students’ ability to solve problems. It also has a significant effect on improving students’ sense of self-efficacy, stimulating learning interest and improving their ability to learn independently in practice. During the implementation of the research, the team explored and practiced the online and offline mixed teaching mode of marketing course with the wisdom tree teaching platform, and built teaching resources for students to learn and discuss on their own, which is a reference for future online mixed teaching

A Small Fan and a Small Handful of Fans Exploring the Acquisition of Count-mass Distinction in Mandarin

PACLIC 19 / Taipei, taiwan / December 1-3, 200

Prevalent Hallucinations during Medical Internships: Phantom Vibration and Ringing Syndromes

Background: Phantom vibration syndrome is a type of hallucination reported among mobile phone users in the general population. Another similar perception, phantom ringing syndrome, has not been previously described in the medical literature. Methods: A prospective longitudinal study of 74 medical interns (46 males, 28 females; mean age, 24.8±1.2 years) was conducted using repeated investigations of the prevalence and associated factors of phantom vibration and ringing. The accompanying symptoms of anxiety and depression were evaluated with the Beck Anxiety and Depression Inventories before the internship began, and again at the third, sixth, and twelfth internship months, and two weeks after the internship ended. Results: The baseline prevalence of phantom vibration was 78.1%, which increased to 95.9% and 93.2% in the third and sixth internship months. The prevalence returned to 80.8% at the twelfth month and decreased to 50.0% 2 weeks after the internship ended. The baseline prevalence of phantom ringing was 27.4%, which increased to 84.9%, 87.7%, and 86.3% in the third, sixth, and twelfth internship months, respectively. This returned to 54.2% two weeks after the internship ended. The anxiety and depression scores also increased during the internship, and returned to baseline two weeks after the internship. There was no significant correlation between phantom vibration/ringing and symptoms of anxiety or depression. The incidence of both phantom vibration and ringing syndromes significantly increased during the internship, and subsequent recovery. Conclusion: This study suggests that phantom vibration and ringing might be entities that are independent of anxiety or depression during evaluation of stress-associated experiences during medical internships

SOCIAL COGNITION AND THE EFFECT OF PRODUCT QUALITY ON ONLINE REPURCHASE INTENTION

An electronic commerce marketing channel is fully mediated by information technology, creating information asymmetry (i.e., limited information). Such asymmetry may impede consumers’ ability to effectively assess certain types of products, thus creating challenges for online sellers. Signaling theory can aid in the understanding of how extrinsic cues—signals—can be used by sellers to convey product quality information to consumers, reducing uncertainty and facilitating a purchase or exchange. This study proposes a model to investigate website quality as a potential signal of product quality and consider the moderating effects of product information asymmetries and signal credibility. The study also finds that perceived value and cognitive lock-in can predict consumer purchase intentions. Furthermore, personalized product recommendation (PPR) services offered by online retailers are found to influence consumer store loyalty. The results indicate that website quality influences consumers’ perceptions of product quality, and affects online purchase intentions. Website quality is found to have a greater influence on perceived product quality when consumers have higher information asymmetry. Signal credibility is found to strengthen the relationship between website quality and product quality perceptions for a high quality website. The implications of cognitive lock-in and product cues for increasing purchase intentions are discussed. Retailer learning reflected in higher quality PPRs is associated with both lower product screening cost and higher product evaluation cost. We also discuss which PPRs influence consumer repurchase intentions in electronic markets

What Factors Satisfy E-Book Platform Customers? Development of A Model to Evaluate E-Book User Behavior and Satisfaction

The use of e-book readers has become increasingly widespread; however, there are few studies to evaluate e-book user behavior and satisfaction on e-book platforms, and even fewer approaches the subject from the perspective of task-technology fit. In order to fill this gap, this study adopts task-technology fit theory to explore the factors that affect the behavior satisfaction of users on commercial e-book platforms. Our research model excludes utility and performance from task-technology fit theory to focus on individual user satisfaction measurement because general e-book platform users are not concerned about work performance issues in leisure activities. The results show that functional service, convenience, and searching task are important factors that influence users\u27 task-technology fit behavior. Moreover, task-technology fit may improve users\u27 satisfaction, flow and scanpath. Finally, satisfaction is affected by task-technology fit and flow factors. An analysis of the research explained 61 percent of the variance in users’ task-technology fit, and 59 percent of the variance in satisfaction to use e-book platform. These results provide a new perspective to e-book researchers and can help e-book platform managers and designers in making policies and designing platforms

MuraNet: Multi-task Floor Plan Recognition with Relation Attention

The recognition of information in floor plan data requires the use of detection and segmentation models. However, relying on several single-task models can result in ineffective utilization of relevant information when there are multiple tasks present simultaneously. To address this challenge, we introduce MuraNet, an attention-based multi-task model for segmentation and detection tasks in floor plan data. In MuraNet, we adopt a unified encoder called MURA as the backbone with two separated branches: an enhanced segmentation decoder branch and a decoupled detection head branch based on YOLOX, for segmentation and detection tasks respectively. The architecture of MuraNet is designed to leverage the fact that walls, doors, and windows usually constitute the primary structure of a floor plan's architecture. By jointly training the model on both detection and segmentation tasks, we believe MuraNet can effectively extract and utilize relevant features for both tasks. Our experiments on the CubiCasa5k public dataset show that MuraNet improves convergence speed during training compared to single-task models like U-Net and YOLOv3. Moreover, we observe improvements in the average AP and IoU in detection and segmentation tasks, respectively.Our ablation experiments demonstrate that the attention-based unified backbone of MuraNet achieves better feature extraction in floor plan recognition tasks, and the use of decoupled multi-head branches for different tasks further improves model performance. We believe that our proposed MuraNet model can address the disadvantages of single-task models and improve the accuracy and efficiency of floor plan data recognition.Comment: Document Analysis and Recognition - ICDAR 2023 Workshops. ICDAR 2023. Lecture Notes in Computer Science, vol 14193. Springer, Cha