Blockchains may replace the institutions that safeguard commercial activities

As a 2nd Internet era, they may allow the secure exchange of value across networks, argues Melanie Swa

Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking

A new class of patient-driven health care services is emerging to supplement and extend traditional health care delivery models and empower patient self-care. Patient-driven health care can be characterized as having an increased level of information flow, transparency, customization, collaboration and patient choice and responsibility-taking, as well as quantitative, predictive and preventive aspects. The potential exists to both improve traditional health care systems and expand the concept of health care though new services. This paper examines three categories of novel health services: health social networks, consumer personalized medicine and quantified self-tracking

On Using Blockchains for Safety-Critical Systems

Innovation in the world of today is mainly driven by software. Companies need to continuously rejuvenate their product portfolios with new features to stay ahead of their competitors. For example, recent trends explore the application of blockchains to domains other than finance. This paper analyzes the state-of-the-art for safety-critical systems as found in modern vehicles like self-driving cars, smart energy systems, and home automation focusing on specific challenges where key ideas behind blockchains might be applicable. Next, potential benefits unlocked by applying such ideas are presented and discussed for the respective usage scenario. Finally, a research agenda is outlined to summarize remaining challenges for successfully applying blockchains to safety-critical cyber-physical systems

An overview of decentralized autonomous organizations on the blockchain

Blockchain technology has emerged as a new paradigm to build decentralized systems which do not require a central authority. It is most popular for enabling Bitcoin and other crypto-currencies. However, blockchain applications span beyond Finance, and recently it has been applied to decentralized governance. Blockchainenabled "Decentralized Autonomous Organizations" (DAOs) have emerged as a new form of collective governance, in which communities may organize themselves relying on decentralized infrastructure. In this article, we introduce the concept of DAO and review the main software platforms that offer DAO creation as a service, which simplifies the use of DAOs to non-blockchain experts; namely: Aragon, DAOstack, DAOhaus and Colony. These platforms will be compared by showing their key features. Finally, we will review the available visualisation tools for DAOs, and we will introduce our open-source tool to plot DAOs activity, DAOAnalyzer. We will illustrate its potential with the case of the DAO Genesis Alpha, which is the main DAO of the DAOstack project

Impact of Level of Effort on the Effects of Compliance with the 3-Hour Rule

Objective To determine if patients’ level of effort (LOE) in therapy sessions during traumatic brain injury (TBI) rehabilitation modifies the effect of compliance with the 3-Hour Rule of the Centers for Medicare & Medicaid Services. Design Propensity score methodology applied to the TBI-Practice-Based Evidence (TBI-PBE) database, consisting of multi-site, prospective, longitudinal observational data. Setting Acute inpatient rehabilitation facilities (IRF). Participants Patients (n=1820) who received their first IRF admission for TBI in the US and were enrolled for 3 and 9 month follow-up. Main Outcome Measures Participation Assessment with Recombined Tools-Objective-17, FIMTM Motor and Cognitive scores, Satisfaction with Life Scale, and Patient Health Questionnaire-9. Results When the full cohort was examined, no strong main effect of compliance with the 3-Hour Rule was identified and LOE did not modify the effect of compliance with the 3-Hour Rule. In contrast, LOE had a strong positive main effect on all outcomes, except depression. When the sample was stratified by level of disability, LOE modified the effect of compliance, particularly on the outcomes of participants with less severe disability. For these patients, providing 3 hours of therapy for 50%+ of therapy days in the context of low effort resulted in poorer performance on select outcome measures at discharge and up to 9 months post discharge compared to patients with <50% of 3-hr therapy days. Conclusions LOE is an active ingredient in inpatient TBI rehabilitation, while compliance with the 3-Hour Rule was not found to have a substantive impact on the outcomes. The results support matching time in therapy during acute TBI rehabilitation to patients’ LOE in order to optimize long-term benefits on outcomes

Taking Blockchain Seriously

In the present techno-political moment it is clear that ignoring or dismissing the hype surrounding blockchain is unwise, and certainly for regulatory authorities and governments who must keep a grip on the technology and those promoting it, in order to ensure democratic accountability and regulatory legitimacy within the blockchain ecosystem and beyond. Blockchain is telling (and showing) us something very important about the evolution of capital and neoliberal economic reason, and the likely impact in the near future on forms and patterns of work, social organization, and, crucially, on communities and individuals who lack influence over the technologies and data that increasingly shape and control their lives. In this short essay I introduce some of the problems in the regulation of blockchain and offer counter-narratives aimed at cutting through the hype fuelling the ascendency of this most contemporary of technologies

Targeted Greybox Fuzzing with Static Lookahead Analysis

Automatic test generation typically aims to generate inputs that explore new paths in the program under test in order to find bugs. Existing work has, therefore, focused on guiding the exploration toward program parts that are more likely to contain bugs by using an offline static analysis. In this paper, we introduce a novel technique for targeted greybox fuzzing using an online static analysis that guides the fuzzer toward a set of target locations, for instance, located in recently modified parts of the program. This is achieved by first semantically analyzing each program path that is explored by an input in the fuzzer's test suite. The results of this analysis are then used to control the fuzzer's specialized power schedule, which determines how often to fuzz inputs from the test suite. We implemented our technique by extending a state-of-the-art, industrial fuzzer for Ethereum smart contracts and evaluate its effectiveness on 27 real-world benchmarks. Using an online analysis is particularly suitable for the domain of smart contracts since it does not require any code instrumentation---instrumentation to contracts changes their semantics. Our experiments show that targeted fuzzing significantly outperforms standard greybox fuzzing for reaching 83% of the challenging target locations (up to 14x of median speed-up)