Search

Objective To conduct a systematic review of modern-era (post-millennium) clinical studies assessing the therapeutic effects of serotonergic psychedelics drugs for mental health conditions. Although the main focus was on efficacy and safety, study characteristics, duration of antidepressants effects across studies, and the role of the subjective drug experiences were also reviewed and presented. Method A systematic literature search (1 Jan 2000 to 1 May 2020) was conducted in PubMed and PsychINFO for studies of patients undergoing treatment with a serotonergic psychedelic. Results Data from 16 papers, representing 10 independent psychedelic-assisted therapy trials (psilocybin = 7, ayahuasca = 2, LSD = 1), were extracted, presented in figures and tables, and narratively synthesized and discussed. Across these studies, a total of 188 patients suffering either cancer- or illness-related anxiety and depression disorders (C/I-RADD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD) or substance use disorder (SUD) were included. The reviewed studies established feasibility and evidence of safety, alongside promising early data of efficacy in the treatment of depression, anxiety, OCD, and tobacco and alcohol use disorders. For a majority of patients, the therapeutic effects appeared to be long-lasting (weeks-months) after only 1 to 3 treatment session(s). All studies were conducted in line with guidelines for the safe conduct of psychedelic therapy, and no severe adverse events were reported. Conclusion The resurrection of clinical psychedelic research provides early evidence for treatment efficacy and safety for a range of psychiatric conditions, and constitutes an exciting new treatment avenue in a health area with major unmet needs.

Distributed systems are hard to get right, model, test, debug, and teach. Their textbook definitions, typically given in a form of replicated state machines, are concise, yet prone to introducing programming errors if naïvely translated into runnable implementations. In this work, we present Distributed Protocol Combinators (DPC), a declarative programming framework that aims to bridge the gap between specifications and runnable implementations of distributed systems, and facilitate their modeling, testing, and execution. DPC builds on the ideas from the state-of-the art logics for compositional systems verification. The contribution of DPC is a novel family of program-level primitives, which facilitates construction of larger distributed systems from smaller components, streamlining the usage of the most common asynchronous message-passing communication patterns, and providing machinery for testing and user-friendly dynamic verification of systems. This paper describes the main ideas behind the design of the framework and presents its implementation in Haskell. We introduce DPC through a series of characteristic examples and showcase it on a number of distributed protocols from the literature. This paper extends our preceeding conference publication (Andersen & Sergey, 2019a) with an exploration of randomized testing for protocols and their implementations, and an additional case study demonstrating bounded model checking of protocols.

Distributed systems are hard to get right, model, test, debug, and teach. Their textbook definitions, typically given in a form of replicated state machines, are concise, yet prone to introducing programming errors if naively translated into runnable implementations.

Smart mobile and wearable technology offers exciting opportunities to support people with dementia (PwD). Its ubiquity and popularity could even benefit user adoption – a great challenge for assistive technology (AT) for PwD that calls for user-centred design (UCD) methods. This study describes a user-centred approach to developing and testing AT based on off-the-shelf pervasive technologies. A prototype is created by combining a smartphone, smartwatch and various applications to offer six support features. This is tested among five end-users (PwD) and their caregivers. Controlled usability testing was followed by field testing in a real-world context. Data is gathered from video recordings, interaction logs, system usability scale questionnaires, logbooks, application usage logs and interviews structured on the unified theory of acceptance and use of technology model. The data is analysed to evaluate usability, usefulness and user acceptance. Results show some promise for user adoption, but highlight challenges to be overcome, emphasising personalisation and familiarity as key considerations. The complete findings regarding usability issues, usefulness of support features and four identified adoption profiles are used to provide a set of recommendations for practitioners and further research. These contribute toward UCD practices for improved smart, pervasive AT for dementia.

This paper helps reduce the cost of invariant checking in cases where access to data is expensive. Assume that a set of variables satisfy a given invariant and a request is received to update a subset of them. We reduce the set of variables to inspect, in order to verify that the invariant is still satisfied. We present a formal model of this scenario, based on a simple query language for the expression of invariants that covers the core of a realistic query language. We present an algorithm which simplifies a representation of the invariant, along with a mechanically verified proof of correctness. We also investigate the underlying invariant checking problem in general and show that it is co-NP hard, i.e., that solutions must be approximations to remain tractable. We have seen a factor of thirty performance improvement using this algorithm in a case study.