Abstract
Industrial companies are faced today with strong competition and fast changing markets. To reduce the risk and evaluate alternatives, simulation is often considered to be an adequate tool. Industrial companies' simulation models must have enough internal detail to be useful but, at the same time, must take into account the external environmental behaviour. Distributed simulation has specific characteristics to allow the integration of these models but its complexity limits its use in industry as stated in the literature. To overcome these difficulties, a framework is proposed, using Agent-based Modelling and Simulation (ABMS) technique and offering communication and synchronization mechanisms, which allow the integration of simulation models in the industrial area. To promote semantic interoperability, a business language is also proposed based on the OASIS Universal Business Language (UBL). To validate the framework a prototype was developed. The experiments made with the prototype shows that a distributed simulation can be more efficient than a single computer simulation as the number of agents increases in the model.

Abstract
The conformational preferences of a series of hydroxyflavones were studied by Raman and FTIR spectroscopies, coupled to Density Functional Theory calculations. Special attention was paid to the effect of hydroxyl substitution, due to its importance on the biological activity of these compounds. Their conformational preferences were found to be determined mainly by the orientation of the hydroxylic groups at C-7 and within the catechol moiety, leading to the occurrence of distinct conformers in the solid state. A complete assignment of the experimental spectra was carried out for these molecules, in the light of their most stable conformers and the corresponding predicted vibrational pattern.

Abstract
Monitoring and managing traffic are vital elements to the operation of a network. Traffic prediction is an essential tool that captures the underlying behavior of a network and can be used, for example, to detect anomalies by defining acceptable data traffic thresholds. In this context, most current solutions are heavily based on historical time data, which makes it difficult to employ them in a dynamic environment such as cloud computing. We propose a traffic prediction approach based on a statistical model where observations are weighted with a Poisson distribution inside a sliding window. The evaluation of the proposed method is performed by assessing the Normalized Mean Square Error of predicted values over observed values from a real cloud computing dataset, collected by monitoring the utilization of Dropbox. Compared with other predictors, our solution exhibits the strongest correlation level and shows a close match with real observations.

Abstract
This paper describes the design and development of a tablet-based gaming platform targeting the senior population, aiming at improving their overall wellbeing by stimulating their cognitive capabilities and promoting social interaction between players. To achieve these goals, we started by performing a study of the specific characteristics of the senior user as well as what makes a game appealing to the player. Furthermore we investigated why the tablet proves to be an advantageous device to our target audience. Based on the results of our research, we developed a solution that incorporates cognitive and social mechanisms into its games, while performing iterative evaluations together with the final user by adopting a user-centered design methodology. In each design phase, a pre-selected group of senior participants experimented with the game platform and provided feedback to improve its features and usability. Through a series of short-term and a long-term evaluation, the game platform proved to be appealing to its intended users, providing an enjoyable gaming experience.

Abstract
A fiber loop mirror containing a section of high-birefringence suspended-core fiber is used for torsion sensing. The suspended-core fiber section has a triangular-shaped core with an in-circle diameter of approximately 1.8 mu m. Due to its small dimensions and geometric structure, it presents high birefringence and intermodal interference simultaneously. A torsion sensitivity of 59.0 pm/deg is obtained in a very large linear range of 900 deg with a resolution of 1.2 deg. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.OE.52.2.020501]

Abstract
The Arteriolar-to-Venular Ratio (AVR) is a well known index for the diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents a fully automatic AVR estimation method which uses a graph-based artery/vein classification approach to classify the retinal vessels by a combination of structural information taken from the vasculature graph with intensity features from the original color image. This method was evaluated on the images of the INSPIRE-AVR dataset. The mean error and the correlation coefficient of obtained results with respect to the reference AVR values were identical to the ones obtained by the second observer using a semi-automated system, which demonstrate the potential of the herein proposed solution for clinical application.