Abstract
The widespread availability of Customer Relationship Management applications in modern organizations, allows companies to collect and store vast amounts of high-detailed customer-related data. Making sense of these data using appropriate methods can yield insights into customers’ behaviour and preferences. The extracted knowledge can then be explored for marketing purposes. Social Network Analysis techniques can play a key role in business analytics. By modelling the implicit relationships among customers as a social network, it is possible to understand how patterns in these relationships translate into competitive advantages for the company. Additionally, the incorporation of the temporal dimension in such analysis can help detect market trends and changes in customers’ preferences. In this paper, we introduce a methodology to examine the dynamics of customer communities, which relies on two different time window models: a landmark and a sliding window. Landmark windows keep all the historical data and treat all nodes and links equally, even if they only appear at the early stages of the network life. Such approach is appropriate for the long-term analysis of networks, but may fail to provide a realistic picture of the current evolution. On the other hand, sliding windows focus on the most recent past thus allowing to capture current events. The application of the proposed methodology on a real-world customer network suggests that both window models provide complementary information. Nevertheless, the sliding window model is able to capture better the recent changes of the network.

Abstract
This paper presents an interactive apparatus to didactically explore Alberti's treatise on architecture, De re aedificatoria, as generative design systems, namely shape grammars. This apparatus allows users to interactively explore such architectonical knowledge in both appealing and informal ways, by enabling them to visualize and manipulate in real-time different design solutions. The authors identify the difficulties on encoding the architectural knowledge of a parametric design model into an interactive apparatus to be used by laypeople. At last, the authors discuss the results of a survey conducted to users that interacted with the prototype in order to assess its ability to communicate the knowledge of an architectural language.

Abstract
Background: Hydroxyethyl starch (HES) is one of the most used colloids for intravascular volume replacement during anesthesia. Aim: To investigate the existence of a chemical interaction between HES and the anesthetic propofol by in vitro propofol dosing, computational docking, and examination of a complex between propofol and HES by infrared (IR), ultraviolet (UV), and H-1 and C-13 nuclear magnetic resonance (NMR) spectroscopy. Methods: Ten samples with human plasma mixed with HES or lactated Ringers (n = 5 for each fluid) were prepared, and the propofol free fraction was quantified until 50 min, using gas chromatography-mass spectrometry. The docking study was performed between HES and propofol and compared with controls. The binding affinities between HES and the small molecules were evaluated by binding free energy approximation (Delta Gb, kJ mol(-1)). The IR, UV, and NMR spectra were measured for propofol, HES, and a mixture of both obtained by the kneading method. Results: Propofol concentrations were significantly lower in the HES samples than in the LR samples (p = .021). The spectroscopic characterization of propofol combined with HES revealed differences in spectra and docking studies reinforced a potential interaction between propofol and HES. Conclusions: Propofol and HES form a complex with different physical-bio-chemical behavior than the single drugs, which may be an important drug interaction. Further studies should evaluate its clinical effects.

Abstract
Reject option is a technique used to improve classifier's reliability in decision support systems. It consists on withholding the automatic classification of an item, if the decision is considered not sufficiently reliable. The rejected item is then handled by a different classifier or by a human expert. The vast majority of the works on this issue have been concerned with implementing a reject option by endowing a supervised learning scheme (e.g., Multilayer Perceptron, Learning Vector Quantization or Support Vector Machines) with a reject mechanism. In this paper we introduce variants of the Self-Organizing Map (SOM), originally an unsupervised learning scheme, to act as supervised classifiers with reject option, and compare their performances with that of the MLP classifier. © 2014 Springer International Publishing Switzerland.

Abstract
This paper presents a network router and transceiver for wearable, low-power, high-speed Body Area Networks (BAN) applications running in a mesh network of sensors embedded in textiles and connected to each other with conductive yarns functioning as bidirectional transmission channels. The routing of data packets from sensor nodes to a sink node is based on hybrid circuit and packet switching. In comparison with pure packet switching, hybrid routing decreases end-to-end delay, power consumption and buffer size. The proposed design uses independent sender, receiver and circuit switching modules, thereby allowing the nodes to simultaneously send and receive data. The simulation results show that circuit and hybrid switching modes significantly increase the performance of the system. In addition, implementing the complete packet process on FPGA, instead of using an external microcontroller as in previous work, enables a much faster routing process. The results are based on a Verilog description of the system, which has been synthesized for a low-power IGLOO FPGA with Libero Project Manager and simulated with ModelSim. The implementation operates successfully at a data rate of 20 Mbps.

Abstract
Entrepreneurship education is increasingly being promoted, driven by a wide consensus in modern societies concerning its benefits in fostering the development of several professional and personal attitudes and skills, such as business expertise, creativity, risk assessment or responsibility. In this context, several authorities have been actively developing policies and activities to empower entrepreneurship culture in young people. Serious Games are recognized as having an important role and potential in education and social networks emerged in the last decade as the platform preferred by many people to socialize, play games or conduct professional activities. This paper presents a proposal for BIZZY, a serious game to be developed and implemented as a Facebook application, to enable young people in the range 12-18 years old to learn entrepreneurial skills progressively, by guiding them to develop a business project from the early idea to the business plan.