Abstract
The Human Immunodeficiency Virus (HIV) is an infectious agent that attacks the immune system cells. Without a strong immune system, the body becomes very susceptible to serious life threatening opportunistic diseases. In spite of the great progresses on medication and prevention over the last years, HIV infection continues to be a major global public health issue, having claimed more than 36 million lives over the last 35 years since the recognition of the disease. Monitoring, through registries, of HIV-AIDS cases is vital to assess general health care needs and to support long-term health-policy control planning. Surveillance systems are therefore established in almost all developed countries. Typically, this is a complex system depending on several stakeholders, such as health care providers, the general population and laboratories, which challenges an efficient and effective reporting of diagnosed cases. One issue that often arises is the administrative delay in reports of diagnosed cases. This paper aims to identify the main factors influencing reporting delays of HIV-AIDS cases within the portuguese surveillance system. The used methodologies included multilayer artificial neural networks (MLP), naive bayesian classifiers (NB), support vector machines (SVM) and the k-nearest neighbor algorithm (KNN). The highest classification accuracy, precision and recall were obtained for MLP and the results suggested homogeneous administrative and clinical practices within the reporting process. Guidelines for reductions of the delays should therefore be developed nationwise and transversally to all stakeholders.

Abstract
We propose and apply two methods to estimate pupil plane phase discontinuities for two realistic scenarios on the very large telescope (VLT) and Keck. The methods use both phase diversity and a form of image sharpening. For the case of VLT, we simulate the "low wind effect" (LWE) that is responsible for focal plane errors in the spectro-polarimetric high contrast exoplanet research (SPHERE) system in low wind and good seeing conditions. We successfully estimate the simulated LWE using both methods and show that they are complimentary to one another. We also demonstrate that single image phase diversity (also known as phase retrieval with diversity) is also capable of estimating the simulated LWE when using the natural defocus on the SPHERE/differential tip tilt sensor (DTTS) imager. We demonstrate that phase diversity can estimate the LWE to within 30-nm root mean square wavefront error (RMS WFE), which is within the allowable tolerances to achieve a target SPHERE contrast of 10-6. Finally, we simulate 153-nm RMS of piston errors on the mirror segments of Keck and produce NIRC2 images subject to these effects. We show that a single, diverse image with 1.5 waves (peak-to-valley) of focus can be used to estimate this error to within 29-nm RMS WFE, and a perfect correction of our estimation would increase the Strehl ratio of an NIRC2 image by 12%.

Abstract
One of the main challenges in power & energy systems is the development of decision support tools which approach the problem as a whole. In this scope, this work contributes to the increase of the interoperability between heterogeneous agent based systems through the use of ontologies, enabling semantic communications.

Abstract
Dysfunction problems with vascular access are a concern to patients and dialysis units. The vascular surgeon should analyse such dysfunction and perform a careful assessment of the vascular network in order to find new fistula layouts. We introduce and discuss the case of creation of a radiocephalic fistula with outflow into the forearm basilic vein through rotation of the forearm basilic vein toward the cephalic vein in the forearm of an 88-year-old hemodialysis male patient. This technique enables extending fistula patency and improves cost efficiency.

Abstract
In this work we address the problem of generating electricity through Kite Power Systems. We solve an optimal control problem which devises the trajectories and controls for the kite that maximize the total energy produced in a given interval. This is a highly nonlinear problem for which the optimization is challenging. We use a continuous time model of the kite and implement time mesh refinement strategies to solve the problem. We report results that show that with an adaptive mesh refinement strategy the problem can be solved with a high level of accuracy and (in simplified versions) much faster. (C) 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 4th International Conference on Energy and Environment Research.

Abstract