Abstract
High fidelity interactive rendering is of major importance for footwear designers, since it allows experimenting with virtual prototypes of new products, rather than producing expensive physical mock-ups. This requires capturing the appearance of complex materials using image based approaches, such as the Bidirectional Texture Function (BTF), to allow subsequent interactive visualization, while still maintaining the capability to edit the materials' appearance. However, interactive global illumination rendering of compressed editable BTFs with ordinary computing resources remains to be demonstrated. In this paper we demonstrate interactive global illumination by using a GPU ray tracing engine and the Sparse Parametric Mixture Model representation of BTFs, which is particularly well suited for BTF editing. We propose a rendering pipeline and data layout which allow for interactive frame rates and provide a scalability analysis with respect to the scene's complexity. We also include soft shadows from area light sources and approximate global illumination with ambient occlusion by resorting to progressive refinement, which quickly converges to a high quality image while maintaining interactive frame rates by limiting the number of rays shot per frame. Acceptable performance is also demonstrated under dynamic settings, including camera movements, changing lighting conditions and dynamic geometry.

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Abstract
We evaluated a population of 7199 children between 2 and 19 years old to study the relations between the observed demographic and physiological features in the occurrence of a pathological/non-pathological heart condition. The data was collected at the Real Hospital Portugues, Pernambuco, Brazil, We performed a feature importance study, with the aim of categorizing the most relevant variables, indicative of abnormalities. Results show that second heart sound, weight, heart rate, height and secondary reason for consultation are important features, but not nearly as decisive as the presence of heart murmurs. Quantitatively speaking. systolic murmurs and a hyperphonetic second heart sound increase the odds of having a pathology by a factor of 320 and 6, respectively.

Abstract
While Cluster-Tree network topologies look promising for WSN applications with timeliness and energy-efficiency requirements, we are yet to witness its adoption in commercial and academic solutions. One of the arguments that hinder the use of these topologies concerns the lack of flexibility in adapting to changes in the network, such as in traffic flows. This paper presents a solution to provide these networks with the ability to self-adapt to different bandwidth and latency requirements, imposed by traffic flows, by changing the cluster's duty-cycle and scheduling. Importantly, our approach enables a network to change its cluster scheduling without requiring long inaccessibility times or the re-association of the nodes. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs without significant changes to the protocol. Finally, we analyze and demonstrate the validity of our methodology through a comprehensive simulation and experimental validation using commercially available technology on a Structural Health Monitoring application scenario.

Abstract
The growth in data availability and in the number of users from non-spatial disciplines has increased the concern with spatial data management and spatial data quality. This reality contextualizes the need and importance of data quality management throughout the spatial data cycle related to data editing and sharing in the context of knowledge networks. The development of standard concepts, procedures and tools may foster important advances in the improvement of spatial dataset production, use and management practices. The implementation of environmental monitoring programs implies a growing number and diversity of users with specific capabilities and responsibilities. In this context, spatial data quality evaluation and management promotes communication, optimizes processes of analysis and spatial modelling, and in this sense improves research and political and technical decision-making and action. This paper focuses on the methods and tools currently available to evaluate the external quality of datasets for environmental and ecological monitoring. A novel framework is presented that allows integrating and interconnecting spatial data quality evaluation with metadata geoportals in WebGIS platforms, facilitating evaluation by users with often limited expertise in this field. The advances achieved in this research highlight the relevance of developing capacities for different users to improve data collection, data models, spatial data processing and modelling, but also the need to inform and report on spatial data quality using adequate tools.

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