Summary Background To contribute to the WHO initiative, VISION 2020: The Right to Sight, an assessment of global vision impairment in 2020 and temporal change is needed. We aimed to extensively update estimates of global vision loss burden, presenting estimates for 2020, temporal change over three decades between 1990–2020, and forecasts for 2050. Methods We did a systematic review and meta-analysis of population-based surveys of eye disease from January, 1980, to October, 2018. Only studies with samples representative of the population and with clearly defined visual acuity testing protocols were included. We fitted hierarchical models to estimate 2020 prevalence (with 95% uncertainty intervals [UIs]) of mild vision impairment (presenting visual acuity ≥6/18 and <6/12), moderate and severe vision impairment (<6/18 to 3/60), and blindness (<3/60 or less than 10° visual field around central fixation); and vision impairment from uncorrected presbyopia (presenting near vision

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We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results.

Abstract-In the past ten years distributed ledgers such as Bitcoin and smart contracts that can run code autonomously have seen an exponential growth both in terms of research interest and in terms of industrial and financial applications. These find a natural application in the area of Sensor Networks and Cyber-Physical Systems. However, the incentive architecture of blockchains requires massive computational resources for mining, delays in the confirmation of transactions and, more importantly, continuously growing transaction fees, which are ill-suited to systems in which services may be provided by resource-limited devices and confirmation times and transaction costs should be kept minimal, ideally absent. We focus on a new block-less, feeless paradigm for distributed ledgers suitable for the WSN, IoT and CPS in which transactions are nodes of a directed acyclic graph, that overcomes the limitations of blockchains for these applications, and where e.g. sensors can be at the same time issuers of transactions and validators of previous transactions. In particular, we present and release open-source a simulation environment that can be easily extended and analysed, and confirms the available results on the performance of the network.