Abstract
The organizations ability to manage corporate environmental performance is emerging as a strategic issue for companies. Environmental decision-making requires an explicit methodology in which it must be possible to articulate the involvement of various stakeholders, incorporate multi-disciplinary knowledge, and integrate criteria involving trade-offs in order to deal with different opinions and heterogeneous factors. The choice of sustainable options for the company and the creation of commitments among stakeholders are a must for businesses. The main motivation of this paper is to present results from the initial steps of the development of a methodology to support decision-making of corporate environmental strategies. Illustrations from an ongoing case study are presented. (C) 2014 The Authors. Published by Elsevier B.V.

Abstract
Frequency blueshifting was recently observed in light pulses propagating on gas-filled hollow-core photonic crystal fibers where a plasma has been produced due to photoionization of the gas. One of the propagation models that is adequate to describe the actual experimental observations is here investigated. It is a nonlinear Schrodinger equation with an extra term, to which we applied a self-similar change of variables and found its accelerating solitons. As in other NLS-related models possessing accelerating solitons, there exist asymmetrical pulses that decay as they propagate in some parameter region that was here well defined.

Abstract
In this work, a remote curvature sensor using a standard OTDR as the interrogation system is presented. This approach uses a core diameter mismatch sensor which is formed by a short section of a multimode fiber, with a length of 3 mm, sandwiched between two singlemode fibers. In this case, the attenuation of the optical signal will vary as the fiber is bent allowing interrogating the sensor with OTDR technology. Preliminary results indicate a resolution range of similar to 0.0003 cm(-1), sensitivity in the range of similar to-208.46 dB/cm(-1) and a variation of 2.67 dB in the OTDR trace within the bend radius range.

Abstract
Organizations are increasingly seeking to improve their efficiency and effectiveness to obtain reliable and high quality product at a lower cost. To achieve this objective, the use of tools that facilitate the acquisition of knowledge about processes is a valuable support. In maintenance, recording data about corrective actions is essential to define proactive actions that aim to avoid or mitigate the effects of future failures. Several computer systems are commercially available for maintenance management. However, the degree of suitability of these systems is low, once they do not consider organizations particularities. This paper presents a computer system for collecting and analyzing data from the machines of the production lines of a semiconductor company. This project aims to provide the company with a tool adapted to its needs, able to perform a behavioral analysis of all the machines of the production lines based on the systematic record of failures occurrence and maintenance activities.

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.