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Background: Public health and governmental organizations are expected to provide guidance to the public on emerging health issues in accessible formats. It is, therefore, important to examine how such organizations are discussing cannabis online and the information that is being provided to the public about this increasingly legal and available substance. Methods: This paper presents a concise thematic analysis of both the volume and content of cannabis-related health information from selected (n = 13) national-level public health and governmental organizations in Canada and the U.S. on Twitter. Results: There were eight themes identified in Tweets including 1) health-related topics; 2) legalization and legislation; 3) research on cannabis; 4) special populations; 5) driving and cannabis; 6) population issues; 7) medical cannabis, and 8) public health issues. The majority of cannabis-related Tweets from the organizations studied came from relatively few organizations and there were substantial differences between the topics covered by U.S. and Canadian organizations. The organizations studied provided limited information regarding how to use cannabis in ways that will minimize health-related harms. Conclusions: Authoritative organizations that deal with public health may consider designing timely social media communications with emerging cannabis-related information, to benefit a general public otherwise exposed to primarily pro-cannabis content on Twitter. ; Arts, Faculty of ; Non UBC ; Psychology, Department of ; Social Work, School of ; Sociology, Department of ; Reviewed ; Faculty

AbstractNeuromorphic computing mimics the organizational principles of the brain in its quest to replicate the brain's intellectual abilities. An impressive ability of the brain is its adaptive intelligence, which allows the brain to regulate its functions "on the fly" to cope with myriad and ever-changing situations. In particular, the brain displays three adaptive and advanced intelligence abilities of context-awareness, cross frequency coupling, and feature binding. To mimic these adaptive cognitive abilities, we design and simulate a novel, hardware-based adaptive oscillatory neuron using a lattice of magnetic skyrmions. Charge current fed to the neuron reconfigures the skyrmion lattice, thereby modulating the neuron's state, its dynamics and its transfer function "on the fly." This adaptive neuron is used to demonstrate the three cognitive abilities, of which context-awareness and cross-frequency coupling have not been previously realized in hardware neurons. Additionally, the neuron is used to construct an adaptive artificial neural network (ANN) and perform context-aware diagnosis of breast cancer. Simulations show that the adaptive ANN diagnoses cancer with higher accuracy while learning faster and using a more compact and energy-efficient network than a nonadaptive ANN. The work further describes how hardware-based adaptive neurons can mitigate several critical challenges facing contemporary ANNs. Modern ANNs require large amounts of training data, energy, and chip area, and are highly task-specific; conversely, hardware-based ANNs built with adaptive neurons show faster learning, compact architectures, energy-efficiency, fault-tolerance, and can lead to the realization of broader artificial intelligence.