Abstract
A key issue in video object tracking is the representation of the objects and how effectively it discriminates between different objects. Several techniques have been proposed, but without a generally accepted method. While analysis and comparisons of these individual methods have been presented in the literature, their evaluation as part of a global solution has been overlooked. The appearance model for the objects is a component of a video object tracking framework, depending on previous processing stages and affecting those that succeed it. As a result, these interdependencies should be taken into account when analysing the performance of the object description techniques. We propose an integrated analysis of object descriptors and appearance models through their comparison in a common object tracking solution. The goal is to contribute to a better understanding of object description methods and their impact on the tracking process. Our contributions are threefold: propose a novel descriptor evaluation and characterisation paradigm; perform the first integrated analysis of state-of-the-art description methods in a scenario of people tracking; put forward some ideas for appearance models to use in this context. This work provides foundations for future tests and the proposed assessment approach contributes to the informed selection of techniques more adequately for a given tracking application context.

Abstract
Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

Abstract
Echinoderm Mutable Collagenous Tissues (MCTs) undergo nervously mediated, drastic and reversible changes in their passive mechanical properties. MCT mutability is involved in autotomy, posture maintenance and motility, and, as a consequence, it influences all aspects of echinoderm biology (nutrition, reproduction, habitat selection, self-defense and predatory behavior) representing a key-factor for the ecological success of the phylum. Besides this, MCT performance represents a topic of remarkable interest for many different applied fields. A biomimetic research route looks at MCTs as a source of inspiration for the development of smart and innovative biomaterials with great potential for in vitro and in vivo applications when controlled and reversible plasticization and/or stiffening of the extracellular matrix is required. The MIMESIS (Marine Invertebrate Models & Engineered Substrates for Innovative bio-Scaffolds) project has been developed within this scientific context. The selected echinoderm model is the common sea urchin Paracentrotus lividus. This project is based on a multidisciplinary approach combining functional biology with biomaterial engineering. A brief review of recent morphological, biomolecular, biomechanical and biochemical results on P lividus MCTs are here presented in a biotechnological perspective, taking into account also a promising application regarding the use of MCT-derived substrata for cell culture studies.

Abstract
This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results. © 2013, Springer Science+Business Media Dordrecht.

Abstract
The purpose of this study was to examine the internal reliability, factorial validity, and measurement invariance of a Brazilian-Portuguese version of the General Health Questionnaire-12 (GHQ-12) across clinical and nonclinical groups. The clinical sample consisted of 228 chronic hemodialysis patients (41.7% female), with a mean age of 48.23 (SD = 16.02) years, whereas the nonclinical sample comprised 350 university students (59.1% female), with a mean age of 21.15 (SD = 2.04) years. Initial model fit comparison of 16 factor structures reported in the literature, through confirmatory factor analysis (CFA), provided mixed results. Additional revisions based on CFA modification indices demonstrated that a reduced (8-item) one-factor model with three error covariances provided the best fit to the data in both samples (comparative fit index > .98 and root mean square error of approximation < .05) and acceptable internal reliability estimates (>.70). Pearson's correlations between the original and the reduced scale was .96 for both samples. Multigroup analysis supported partial strong measurement equivalence across groups. Latent mean differences showed an expected higher factor mean for the clinical sample. Overall results demonstrated that the 8-item one-factor of the GHQ-12 showed good psychometric properties in both samples and provided preliminary support for meaningful comparisons of factor means across clinical and nonclinical groups.

Abstract
In this work we present single-stage formulations for the integrated soft drink lot-sizing and scheduling problem with two-stage synchronization. It is a multi-product, multi-machine problem, with sequence-dependent setup times and costs. Without loss of generality, these single-stage reformulations address the problem correctly and, in general, reduce the size of the synchronized two-stage model of Ferreira, Morabito e Rangel (2009), regarding the number of variables and constraints. The preliminary computational experiments on real-world instances from a soft-drink company show the competitiveness of the single-stage models against other formulations and solution approaches reported in the literature.