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ABSTRACTWe compare traditional and open‐access scheduling policies for outpatient medical practices in terms of the number of patients served and financial performance. Under a traditional scheduling policy, a patient schedules an appointment in advance and there is a significant possibility of patient no‐shows. In response, doctors overbook patients to reduce the idle time created by no‐shows. Under an open‐access scheduling policy, all appointments are scheduled the day of the appointment, thereby eliminating patient no‐shows but creating more randomness in the daily number of appointments. In contrast to earlier works, we consider the optimal average number of patients served and find that the open‐access policy may lead doctors to serve a greater number of patients but that the traditional policy may be more profitable by providing doctors more control over their schedule and ability to limit overtime.

Online social networks (OSN) are becoming more important in people's daily life, however, all popular OSNs are centralized, and this raises a series of security, privacy and management issues. A decentralized architecture based on blockchain technology provides the ability to solve above issues. In this paper, an OSN service is developed based on blockchain technology in order to make it operate decentralized. Large volume of data normally required low-security requirements can be stored in Interplanetary Filesystem (IPFS) to make data decentralized. A decentralized autonomous organization is developed for user autonomy, users can self-manage the OSN in a democratic way.

A core assumption often heard in public health discourse is that increasing trust in national political leaders is essential for securing public health compliance during crises such as the COVID-19 pandemic (2019–ongoing). However, studies of national government trust are typically too coarse-grained to differentiate between trust in institutions versus more interpersonal trust in political leaders. Here, we present multiscale trust measurements for twelve countries and territories across the West, Oceania and East Asia. These trust results were used to identify which specific domains of government and social trust were most crucial for securing public health compliance (frequency of mask wearing and social distancing) and understanding the reasons for following health measures (belief in effectiveness of public health measures). Through the use of linear regression and structural equation modeling, our cross-cultural survey-based analysis (N = 3369 subjects) revealed that higher trust in national and local public health institutions was a universally consistent predictor of public health compliance, while trust in national political leaders was not predictive of compliance across cultures and geographical regions. Institutional trust was mediated by multiple types of transparency, including providing rationale, securing public feedback, and honestly expressing uncertainty. These results highlight the importance of distinguishing between components of government trust, to better understand which entities the public gives the most attention to during crises.