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.

Abstract
This paper analyzes the impact of climate dynamics on vegetation growth for a rural mountainous region in northeastern Portugal. As a measure of vegetation growth, we use the normalized difference vegetation index (NDVI), which is based on the ten-day synthesis data set (S10) from Satellite Pour l'Observation de la Terre (SPOT-VEGETATION) imagery from 1998 to 2011. We test whether the dynamic growth pattern of the NDVI has changed due to climate variability, and we test the relationship of NDVI with temperature and available soil water (ASW). In order to do so, we use a time-frequency approach based on Kalman filter regressions in the time domain. The advantage of our approach is that it can be used even in the case where the sample size is relatively small. By estimating the important relationships in the time domain first and transferring them into the frequency domain, we are still able to derive a complete spectrum over all frequencies. In our example, we find a change of the cyclical pattern for the spring season and different changes if we take into account all seasons. In other words, we can distinguish between deterministic changes of the vegetation cycles and stochastic changes that only occur randomly. Deterministic changes imply that the data-generating process has changed (such as climate), whereas stochastic changes imply only temporary changes. We find that individual seasons undergo cyclical changes that are different from other seasons. Moreover, our analysis shows that temperature and ASW are the main drivers of vegetation growth. We can also recognize a shift of the relative importance away from temperature to soil water.