Abstract
Evolutionary Algorithms (EA) approach the genotype-phenotype relationship differently than does nature, and this discrepancy is a recurrent issue among researchers. Moreover, in spite of some performance improvements, it is a fact that biological knowledge has advanced faster than our ability to incorporate novel biological ideas into EAs. Recently, some researchers have started exploring computationally new comprehension of the multitude of the regulatory mechanisms that are fundamental in both processes of inheritance and of development in natural systems, by trying to include those mechanisms in the EAs. One of the first successful proposals was the Artificial Gene Regulatory Network (ARN) model, by Wolfgang Banzhaf. Soon after some variants of the ARN were tested. In this paper, we describe one of those, the Regulatory Network Computational Device, demonstrating experimentally its capabilities. The efficacy and efficiency of this alternative is tested experimentally using typical benchmark problems for Genetic Programming (GP) systems. We devise a modified factorial problem to investigate the use of feedback connections and the scalability of the approach. In order to gain a better understanding about the reasons for the improved quality of the results, we undertake a preliminary study about the role of neutral mutations during the evolutionary process.

Abstract
Image segmentation has been widely used in document image analysis for extraction of printed characters, map processing in order to find lines, legends, and characters, topological features extraction for extraction of geographical information, and quality inspection of materials where defective parts must be delineated among many other applications. In image analysis, the efficient segmentation of images into meaningful objects is important for classification and object recognition. This paper presents two novel methods for segmentation of images based on the Fractional-Order Darwinian Particle Swarm Optimization (FODPSO) and Darwinian Particle Swarm Optimization (DPSO) for determining the n-1 optimal n-level threshold on a given image. The efficiency of the proposed methods is compared with other well-known thresholding segmentation methods. Experimental results show that the proposed methods perform better than other methods when considering a number of different measures.

Abstract
This paper describes the layered control architecture and its software implementation developed and used at the Underwater Systems and Technology Laboratory. The architecture is implemented as a toolchain which consists on three main entities: DUNE onboard software, Neptus command and control software and a common IMC message-based communication protocol. The LSTS software toolchain has been tested throughout various field deployments where it was used to control heterogeneous autonomous vehicles like AUVs, ASVs, UAVs and ROVs in both single and multi-vehicle operations.

Abstract
This study develops a framework that combines different management science methods to provide insights concerning the performance of retailing stores. First, the framework enables to specify appropriate targets for stores of a retail network using data envelopment analysis. This involves comparing stores within homogenous groups, that is, supermarkets and hypermarkets. Second, the framework compares the overall performance of these two groups. This requires the combined use of a Malmquist-type index and statistical tests. This index is decomposed into sub-indices for comparing the differences between groups in terms of the efficiency spread in each group of stores and the productivity differences between the best-practice frontiers spanned by the benchmark stores from each group. The hypothesis tests are used to verify if the differences between groups captured by the sub-indices are statistically significant. Journal of the Operational Research Society (2012) 63, 631-645. doi:10.1057/jors.2011.63 Published online 13 July 2011

Abstract
This paper provides a review of the literature on applications of the Driving forces, Pressure, State, Impact, Response (DPSIR) framework to fisheries. The interpretation given to each DPSIR category differs in existing studies, and as a result the indicators used to support fisheries management also vary considerably. This impairs comparisons concerning the state of different fishery systems, and does not provide a common base of knowledge concerning potential management measures that can be adopted in a given context. This paper clarifies the interpretation of each DPSIR category and proposes a set of indicators that can be applied in fishery contexts. The set of indicators proposed is also classified according to sustainability dimensions. It is argued that organising the indicators according to the DPSIR framework and sustainability dimensions (ecologic, economic, social and governance) is a positive contribution to serve as a guideline for future applications to adopt standardized indicators and improve fisheries management.

Abstract
The current financial crisis highlights real problems profoundly related to the level of financial knowledge. Some studies suggest that many individuals, including small business owners, do not have adequate financial skills to be able to handle their finances. The term "financial literacy" summarizes the set of knowledge, skills and attitudes necessary to enable recognition and understanding of the foundations of personal finance. Informed and literate individuals are able to make responsible decisions. Our paper presents the preliminary results obtained with the Portuguese StudentFinance2012 survey. A total of 612 university students from seven different institutions agreed to participate and complete the survey. The sample has an average age of 23.67 years and is gender balanced. Students were classified in three course areas such as engineering, business and management, or design and tourism. Most respondents frequent a degree course, being the university mostly a public institution. A majority of our students has solely funded by their parents or family. By analyzing the total amount of financial products, we obtained an average of 2.57 financial products by student. To analyze financial literacy, our study developed measures such students' financial involvement, financial knowledge and parents influence and explore it as a function to issues such as age, gender, course area, course type, type of university and parental funding. The results suggest that the financial involvement of students evolves over time (as age increases, the financial involvement also increases) and confirm significant dependence with demographic variables such as gender, age, or course, among others. For the financial knowledge the results are encouraging, with students to show interesting levels of knowledge. We also identified relations of dependence with age, gender and course, among many others. Parental influence was analyzed by the level of agreement with statements related to the perceptions of the influence and behavior of parents about money, budgeting, saving and paying bills. The main results indicate that parents are a positive influence and that studentsare experiencing a financial behaviour that integrates the family.