Abstract
In this paper, we present a compositional semantics for the channel-based coordination language Reo that enables the analysis of quality of service (QoS) properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo Automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo Automata to Continuous-Time Markov Chains (CTMCs). This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions. In addition, we discuss to what extent Interactive Markov Chains (IMCs) can serve as an alternative semantic model for Stochastic Reo. We show that the semantics of Stochastic Reo cannot be specified compositionally using the product operator provided by IMCs.

Abstract
The advancement of knowledge on networks entails acknowledging the heterogeneity of their participants, more precisely, the organizations that lie beyond the scope of the activities of firms. Adopting a dynamic perspective of networks, and considering different types of innovation exchanges, we propose a hybrid and wider notion of industry which implies taking account of a set of local supporting organizations (LSOs) in domains such as research and technology, production factors, consultancy and training, and public support. Based on a rich data set built from face-to-face interviews with Portuguese automotive organizations, which resulted in a network comprising 867 organizations, we apply social network analysis techniques to analyse the structure, content and dynamics of the networks. The evidence gathered unveiled huge industry turbulence and significant changes in the boundaries of the Portuguese automotive networks over a 20-year period, with the emergence (and decline) of different prominent organizations. Specifically, following AutoEuropa major foreign direct investment (in 1995), the analyses reflect a clear increase in connectivity within the industry (from 524, before 1995, up to 2327 connections after 1995), with greater involvement among suppliers and between suppliers and LSOs, with the latter achieving top positions in the ranking of innovation networks.

Abstract
Airports have traditionally been considered as public utility providers, with little potential to develop significant market opportunities. Liberalisation of the air transport market around the globe has introduced new dynamics into the airport industry. The emergence of competition and the transition in ownership (towards privatisation or commercialisation) demand a different perspective in airport management. This paper aims at explaining the complexity of the airport business, in particular in what concerns the role of the airport as a firm that operates in a network of stakeholders, to produce a set of service packages targeted at several types of customers. (C) 2013 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Scientific Committee

Abstract
A magnetic field sensor using a non-adiabatic tapered optical fiber (NATOF) interacting with magnetic fluid (MF) nanoparticles is proposed and experimentally demonstrated. The NATOF is surrounded by a MF whose RI changes with external magnetic field which MF is as a cladding of tapered fiber. The Output interference spectrum is shifted by the change of the applied magnetic field intensity in the range up to 44 mT with a sensitivity of -7.17x10(-2) nm/ mT.

Abstract
While autonomous underwater vehicles (AUVs) are increasingly being used to perform mine countermeasures (MCM) operations, the capability of these systems is limited by the efficiency of the planning process. In this paper we study the problem of multiobjective MCM mission planning with an AUV. In order to overcome the inherent complexity of the problem, a multi-stage algorithm is proposed and evaluated. Our algorithm combines an evolutionary algorithm (EA) with a local search procedure based on simulated annealing (SA), aiming at a more flexible and effective exploration and exploitation of the search space. An artificial neural network (ANN) model was also integrated in the evolutionary procedure to guide the search. The results show that the proposed strategy can efficiently identify a higher quality solution set and solve the mission planning problem.

Abstract
The literature provides broad evidence for the seasonality of stock market returns, but is very scarce regarding the potential seasonality of investment funds performance. Using a sample of 5349 Equity Europe or Equity Eurozone investment funds, this article contributes to fill this gap by providing evidence that investment funds globally exhibit higher performances in the first than in the second 6 months of the year, and that they exhibit negative abnormal performances in the first compared to the intermediate and final months of each quarter. Finally, the article reports a summer holiday effect, such that investment funds outperform negatively in August compared to the other intermediate months of the quarter.