Abstract

Abstract
This paper investigates the impact of internationalization and diversification strategies on the financial performance of construction industry companies. The results obtained can guide the design of strategies to pursue company growth and achieve competitive advantage. The evaluation of companies' performance is based on the use of the Data Envelopment Analysis technique to aggregate financial indicators using optimized weights. The impact of internationalization and diversification on company performance is explored using truncated regression, controlling for the effect of contextual factors such as company age, size and time. Data Envelopment Analysis and truncated regression were complemented with bootstrapping to ensure the robustness of the results obtained. The activity of Portuguese and Spanish contractors in the period 2002 to 2011 is used as case study. The empirical results show that internationalization has a positive impact on financial performance, although this effect is only statistically significant for Spanish contractors. Diversification has a nonlinear relationship with performance, benefiting companies with either a small number of core activities or companies with a broad scope of activities.

Abstract
OPTICON currently supports a Joint Research Activity (JRA) dedicated to providing easy to use image reconstruction algorithms for optical/IR interferometric data. This JRA aims to provide state-of-the-art image reconstruction methods with a common interface and comprehensive documentation to the community. These tools will provide the capability to compare the results of using different settings and algorithms in a consistent and unified way. The JRA is also providing tutorials and sample datasets to introduce the principles of image reconstruction and illustrate how to use the software products. We describe the design of the imaging tools, in particular the interface between the graphical user interface and the image reconstruction algorithms, and summarise the current status of their implementation.

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This paper presents a new solution approach to solve the resource-constrained project scheduling problem in the presence of three types of logical constraints. Apart from the traditional AND constraints with minimal time-lags, these precedences are extended to OR constraints and bidirectional (BI) relations. These logical constraints extend the set of relations between pairs of activities and make the RCPSP definition somewhat different from the traditional RCPSP research topics in literature. It is known that the RCPSP with AND constraints, and hence its extension to OR and BI constraints, is NP-hard. The new algorithm consists of a set of network transformation rules that removes the OR and BI logical constraints to transform them into AND constraints and hereby extends the set of activities to maintain the original logic. A satisfiability (SAT) solver is used to guarantee the original precedence logic and is embedded in a metaheuristic search to resource feasible schedules that respect both the limited renewable resource availability as well as the precedence logic. Computational results on two well-known datasets from literature show that the algorithm can compete with the multi-mode algorithms from literature when no logical constraints are taken into account. When the logical constraints are taken into account, the algorithm can report major reductions in the project makespan for most of the instances within a reasonable time.

Abstract
The aim of this study was to evaluate the effect of essential oils (EOs) of plants naturally occurring in northern Portugal on the spoilage of fresh Maronesa beef burgers stored at 2 and 8 degrees C under different packaging conditions. EOs were obtained from dried leaves of laurel (Laurus Nobilis L.) and rosemary (Rosmarinus officinallis L.) by hydro-distillation using a Clevenger-type apparatus. Analysis of volatile composition of essential oils of rosemary and laurel was achieved by Gas Chromatography-Mass Spectrometry (GC-MS) and Gas Chromatography-Thermal Conductivity Detection (GC-TCD) resulting in the detection of 95.8% and 89.4% of its compounds, respectively. Fresh beef (semitendinosus and semimembranosus) of DOP-Maronesa breed (males; n = 4) were obtained from local market and transported to the laboratory. Samples were stored at 2 and 8 degrees C in two different conditions: aerobiosis (A) and vacuum (V) and analyzed at 0,1, 2, 3, 5, 7,10,14, 21 and 28 days for Lactic acid bacteria (LAB), Enterobacteriaceae, Pseudomonas spp., Fungi, Total mesophilic (TM) and psychrotrophic (TP), color (L*a*b*) and pH. Laurel was the most effective EO keeping pH from increasing. Coordinates L* and a* were higher on samples containing laurel EO for both A and V packaging. Laurel also showed better effect in reducing microbiologic counts in samples packed in A at both 2 and 8 degrees C and packed in V at 8 degrees C. Rosemary was effective in reducing microbial counts on all V samples stored at 2 degrees C. This study allows to conclude that Laurel EO has significant effect in shelf-life, maintaining fresh beef color.

Abstract
There are a vast number of studies on the relationship between R&D and exports. However, the results are not always clear-cut. This study evaluates whether, in the case of a small, open and peripheral country in which exports are the engine of economic growth despite a noticeable laggardness in terms of R&D, the firms' R&D impacts on and/or is influenced by their exports, as well as whether the interrelation between R&D and exports impacts on the performance of firms. Using an unique dataset comprising all (more than 340 thousands) non-financial companies based in Portugal, over the period 2006-2012, estimations based on bivariate probit models, which provide the simultaneous estimation of the two decisions (R&D and exports), taking into account the correlation between the estimation errors of the equations for R&D and exports, confirm there is complementarity between R&D and exports, which means that engaging in R&D activities will increase the firm's probability of engaging in export activities. Additionally, engaging in export activities will also increase the probability of engaging in R&D. The results also provide support for the hypothesis that more productive firms self-select into exporting activities and also provide support for the learning-by-exporting hypothesis. Finally, based on a panel model we further found that R&D and exports have a positive effect on sales growth, which is enhanced when both activities occur simultaneously.