Abstract
The complexity of modern software systems entails the need for reconfiguration mechanisms governing the dynamic evolution of their execution configurations in response to both external stimulus or internal performance measures. Formally, such systems may be represented by transition systems whose nodes correspond to the different configurations they may assume. Therefore, each node is endowed with, for example, an algebra, or a first-order structure, to precisely characterise the semantics of the services provided in the corresponding configuration. Hybrid logics, which add to the modal description of transition structures the ability to refer to specific states, offer a generic framework to approach the specification and design of this sort of systems. Therefore, the quest for suitable notions of equivalence and refinement between models of hybrid logic specifications becomes fundamental to any design discipline adopting this perspective. This paper contributes to this effort from a distinctive point of view: instead of focussing on a specific hybrid logic, the paper introduces notions of bisimilarity and refinement for hybridised logics, i.e. standard specification logics (e.g. propositional, equational, fuzzy, etc) to which modal and hybrid features were added in a systematic way.

Abstract
We present r..eal , a library that integrates the R statistical environment with Prolog. Due to R's functional programming affinity the interface introduced has a minimalistic feel. Programs utilising the library syntax are elegant and succinct with intuitive semantics and clear integration. In effect, the library enhances logic programming with the ability to tap into the vast wealth of statistical and probabilistic reasoning available in R. The software is a useful addition to the efforts towards the integration of statistical reasoning and knowledge representation within an AI context. Furthermore it can be used to open up new application areas for logic programming and AI techniques such as bioinformatics, computational biology, text mining, psychology and neuro sciences, where R has particularly strong presence. © 2013 Springer-Verlag.

Abstract
Background: Due to their different propagation times, visual and auditory signals from external events arrive at the human sensory receptors with a disparate delay. This delay consistently varies with distance, but, despite such variability, most events are perceived as synchronic. There is, however, contradictory data and claims regarding the existence of compensatory mechanisms for distance in simultaneity judgments. Principal Findings: In this paper we have used familiar audiovisual events - a visual walker and footstep sounds and manipulated the number of depth cues. In a simultaneity judgment task we presented a large range of stimulus onset asynchronies corresponding to distances of up to 35 meters. We found an effect of distance over the simultaneity estimates, with greater distances requiring larger stimulus onset asynchronies, and vision always leading. This effect was stronger when both visual and auditory cues were present but was interestingly not found when depth cues were impoverished. Significance: These findings reveal that there should be an internal mechanism to compensate for audiovisual delays, which critically depends on the depth information available.

Abstract
Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players' benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Abstract
An increasing number of real-time embedded applications present high computation requirements which need to be realized within strict time constraints. Simultaneously, architectures are becoming more and more heterogeneous, programming models are having difficulty in scaling or stepping outside of a particular domain, and programming such solutions requires detailed knowledge of the system and the skills of an experienced programmer. In this context, this paper advocates the transparent integration of a parallel and distributed execution framework, capable of meeting real-time constraints, based on OpenMP programming model, and using MPI as the distribution mechanism. The paper also introduces our modified implementation of GCC compiler, enabled to support such parallel and distributed computations, which is evaluated through a real implementation. This evaluation gives important hints, towards the development of the parallel/distributed fork-join framework for supporting real-time embedded applications.

Abstract
This book provides the latest models, methods and guidelines for networked enterprises to enhance their competitiveness and move towards innovative high performance and agile industrial systems. In the new global market, competitiveness and economic growth rely greatly on the move toward innovative high performance industrial systems and agile networked enterprises through the creation and consolidation of non-hierarchical manufacturing networks of multi-national SMEs as opposed to networks based on powerful large-scale companies. Network performance can be significantly improved through more harmonious and equitable peer-to-peer inter-enterprise relationships, conforming decentralized and collaborative decision-making models. Traditional hierarchical manufacturing networks are based on centralized models, where some of the actors involved must adapt themselves to the constraints defined by those who are most dominant. Real-world experiences of such models have revealed some major problems due to the centralized vision of the supply chain and the sub-optimal performance of centralized decision-making. For the current highly dynamic markets, this generates major inefficiencies in operation throughout the supply chain. This book collects the latest research regarding non-hierarchical manufacturing networks and provides enterprises with valuable models, methods and guidelines to improve their competitiveness. © 2013 by John Wiley & Sons, Inc.