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Humanitarian medical response to natural and human-made disasters can be complicated by high clinician, staff, and patient turnover. While electronic medical records are being scaled up globally, their use remains limited in humanitarian response settings. The Fast Electronic Medical Record (fEMR) system is an open-source electronic health record system specifically designed for use in resource-limited settings and humanitarian crises.

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Background: Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB).

Methods: Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework.

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The development of artificial intelligence (AI) based medical Internet of Things (IoT) technology plays a crucial role in making the collection and exchange of medical information more convenient. However, security, privacy, and efficiency issues during information exchange have become pressing challenges. While many scholars have proposed solutions based on AI and blockchain to address these issues, few have focused on the impact of the slow consensus algorithm of blockchain on the efficiency of information exchange.

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A high-security, high-speed stream cipher for physical-layer-secure optical communication, based on optical-carrier-induced private chaos synchronization and RC4 algorithm, is proposed and numerically demonstrated. The high security and speed are achieved by combining physical true random numbers generated from synchronized chaos, used as the key for random DNA coding, with the RC4 pseudo-random numbers. Moreover, no third-party signal is required as the optical carrier itself serves as the common drive for chaos synchronization in semiconductor lasers.

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Background: Traditional in-clinic methods of collecting self-reported information are costly, time-consuming, subjective, and often limited in the quality and quantity of observation. However, smartphone-based ecological momentary assessments (EMAs) provide complementary information to in-clinic visits by collecting real-time, frequent, and longitudinal data that are ecologically valid. While these methods are promising, they are often prone to various technical obstacles.

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