Abstract
The retina is a unique region where the vascular condition can be observed in vivo. It is a window to the systemic vasculature, as the retinal blood vessels are exposed to the same stresses and pathologies as the whole vascular system. The retinal vasculature status can be evaluated with high-resolution eye fundus color images, and variations in the retinal microcirculation can be used as an indicator of a lesion in the cerebral microvasculature. The features measured on these images can characterize retinal arteriolar narrowing, which is a marker of hypertension, or diabetic retinopathy (DR).

Abstract
Decision rules are among the most expressive data mining models. We propose the first distributed streaming algorithm to learn decision rules for regression tasks. The algorithm is available in SAMOA (SCALABLE ADVANCED MASSIVE ONLINE ANALYSIS), an open-source platform for mining big data streams. It uses a hybrid of vertical and horizontal parallelism to distribute Adaptive Model Rules (AMRules) on a cluster. The decision rules built by AMRules are comprehensible models, where the antecedent of a rule is a conjunction of conditions on the attribute values, and the consequent is a linear combination of the attributes. Our evaluation shows that this implementation is scalable in relation to CPU and memory consumption. On a small commodity Samza cluster of 9 nodes, it can handle a rate of more than 3 0 0 0 0 instances per second, and achieve a speedup of up to 4.7 x over the sequential version.

Abstract
This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, theresults help electricity markets agents hedging against Market Clearing Price (MCP) volatility. © Springer Science+Business Media Dordrecht 2014.

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