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We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e., by individuals, companies, or other groups actively using Bitcoin. BitConduite makes Bitcoin data accessible to nontechnical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts. [ABSTRACT FROM AUTHOR]

A primary objective of a distributed storage system is to reliably store huge amounts of source data for long periods of time using a large number of high storage capacity nodes. Storage nodes are prone to permanent failures, where such node failures cause all stored data to be permanently lost, and failed nodes are replaced with nodes that initially store no data. To maintain recoverability of the source data as storage nodes fail and are replaced, a total amount of storage capacity that is larger than the source data size is allocated to store the source data, and a repairer continually reads data from and writes data to the storage nodes as they fail and are replaced. We prove information-theoretic lower bounds on the rate at which a repairer reads data from the storage system as a function of the rate at which nodes fail and the amount by which the allocated storage capacity exceeds the source data size. These lower bounds hold for any repairer, i.e., any repairer that does not read data at or above the lower bound rate will provably not maintain recoverability of the source data. The bounds are provably tight asymptotically as the number of storage nodes grows and the allocated storage capacity approaches the source data size. [ABSTRACT FROM AUTHOR]

Whereas period life expectancy constitutes an intuitive indicator of the survival conditions prevailing at a particular period, this paper argues that, given the existence of welfare interdependencies, that widespread indicator is nonetheless an incomplete measure of the longevity achievements relevant for human well-being. The central importance of coexistence for human-beings implies that usual life expectancy measures should be complemented by joint life expectancy indicators, which measure the average coexistence time under particular survival conditions. After a study of the theoretical foundations of ‘single’ and ‘joint’ life expectancy indicators, it is shown that joint life expectancy measures tend to enrich significantly the comparison of longevity achievements across countries and periods. Moreover, the introduction of joint life expectancy indicators—as a complement to conventional life expectancy measures—into multi-variable indexes such as the United Nations’ HDI is also shown to affect international rankings of standards of living to a non negligible extent. [ABSTRACT FROM AUTHOR]