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Autonomous vehicles will "invade" our street in a not so far future. They must be coordinated in order to exploit the resources in a fair yet effective way. One of these resources, whose management is quite challenging, is represented by crossings: vehicles come and aim at passing the intersection, often as soon as possible, but they must compete with other vehicles. In this paper we propose an auction-based mechanism to coordinate the vehicles at a crossing, considering the presence of both human-driven and autonomous vehicles; moreover, we introduce an enhancement mechanism to take into consideration also the presence of vehicles in the lanes behind the first one. We analyze different strategies and, by means of simulation experiments, we compare them and show how waiting times change depending on the strategies. The results show that the cooperative strategy presents average waiting times lower for all vehicles than a competitive strategy. CCS CONCEPTS • Computing methodologies → Cooperation and coordination; Self-organization.

The pervasive impact of Alzheimer's disease on aging society represents one of the main challenges at this time. Current investigations highlight two specific misfolded proteins in its development: Amyloid-beta and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on a machine learning approach. The proposed method applies an autoregressive model, constrained by structural connectivity, to predict concentrations of Amyloid-beta two years after the provided baseline. In experiments, the autoregressive model generally outperformed the state-of-art models yielding the lowest average prediction error (mean squared-error 0.0062). Moreover, we assess its effectiveness and suitability for real case scenarios, for which we provide a web service for physicians and researchers. Despite predicting amyloid pathology alone is not sufficient to clinical outcome, its prediction can be helpful to further plan therapies and other cures.

The coordination of autonomous vehicles is an open field that is addressed by different researches comprising many different techniques. In this paper we focus on decentralized approaches able to provide adaptability to different infrastructural and traffic conditions. We formalize an Emergent Behavior Approach that, as per our knowledge, has never been performed for this purpose, and a Decentralized Auction approach. We compare them against existing centralized negotiation approaches based on auctions and we determine under which conditions each approach is preferable to the others.