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During the COVID-19 pandemic, understanding the effects of location information of patients has significant theoretical and practical implications for public crisis management and health communication. Based on fear appeal theories, this research proposed a chain reaction model that links physical distance to the nearest patients, which is informed by the location information of patients, citizens' anxiety, attention to information and preventive behaviors. To test the hypothesized model, we conducted a study during the COVID-19 outbreak in mainland China in March 2020. The survey of 2061 people from 244 cities across 30 provinces showed that physical distance to confirmed cases has a significant influence on citizens' anxiety, which in turn can improve their preventive behaviors through the mediating factor of attention to information. In addition, this research also revealed the twofold effects of vertical collectivism as a personality trait on anxiety. These findings will provide support to help governments take actions to reduce citizens' anxiety and promote preventive behaviors., Author(s): Guobin Wu [sup.1] , Xiaopeng Deng [sup.2] , Bingsheng Liu [sup.3] Author Affiliations: (1) grid.33763.32, 0000 0004 1761 2484, College of Management and Economics, Tianjin University, , 92 Weijin [...]

A pipeline robot suitable for miniature pipeline detection, namely π-II, was proposed in this paper. It features six wheel-leg mobile mechanisms arranged in a staggered manner, with a monocular fisheye camera located at the center of the front end. The proposed robot can be used to capture images during detection in miniature pipes with an inner diameter of 120 mm. To efficiently identify the robot's status within the pipeline, such as navigating in straight pipes, curved pipes, or T-shaped pipes, it is necessary to recognize and classify these specific pipeline landmarks accurately. For this purpose, the residual network model ResNet18 was employed to learn from the images of various pipeline landmarks captured by the fisheye camera. A detailed analysis of image characteristics of some common pipeline landmarks was provided, and a dataset of approximately 908 images was created in this paper. After modifying the outputs of the network model, the ResNet18 was trained according to the proposed datasets, and the final test results indicate that this modified network has a high accuracy rate in classifying various pipeline landmarks, demonstrating a promising application prospect of image detection technology based on deep learning in miniature pipelines. [ABSTRACT FROM AUTHOR]

Although expectations have emerged as a prominent research theme in public administration, little is known about whether and how expectations affect citizen satisfaction. We investigated the anchoring effects of expectations in shaping citizen satisfaction, utilizing a survey experiment involving 735 Chinese citizens. Specifically, we examined (1) the influence of citizens' normative expectations of what services should be on their satisfaction levels; (2) the anchoring effects that result from numerical anchors on expectations and satisfaction; and (3) the effectiveness of debiasing education in mitigating anchoring effects. The findings reveal a negative correlation between citizens' normative expectations and their satisfaction levels, highlighting the influence of anchoring effects on citizens' expectations and satisfaction. Debiasing education is effective in mitigating anchoring effects on expectations but not on satisfaction. These findings integrated cognitive bias into the expectancy disconfirmation model to a better understanding of citizen satisfaction. In this article, the authors focus on investigating the anchoring effects of expectations in shaping levels of citizen satisfaction. To achieve this, the study (1) examined the influence of citizens' normative expectations of what services should be on their satisfaction levels, utilizing a survey experiment involving 735 Chinese citizens; (2) tested the anchoring effects that result from numerical anchors on satisfaction; and (3) employed debiasing education to mitigate anchoring effects on satisfaction. The findings reveal a negative correlation between citizens' normative expectations and their satisfaction levels, highlighting the influence of anchoring effects on citizen satisfaction. Debias education is effective in mitigating bias on expectations but does not equally address issues related to satisfaction levels. These findings contribute to the cross-national generalizability of the expectancy disconfirmation model and citizen satisfaction literature. [ABSTRACT FROM AUTHOR]