Abstract
We are developing a new method for the identification of rib boundaries in chest x-ray images. The identification of rib boundaries is important for radiologist diagnosis of lung diseases as TB. The radiologists use the ribs as reference for location and can be used to eliminate false positives in the detection of abnormalities. Our method automatically identifies rib boundaries from raw images through a sequence of steps using a combination of image processing techniques. Radiographs are still very relevant in practice because in Portugal and many other countries it is the first step for TB detection. We have access a large database of x-ray images provided by the pneumological screening centre (CDP) of Vila Nova de Gaia, in Portugal.

Abstract
The clinical relevance of pulse wave velocity (PWV), as an indicator of cardiac risk associated to arterial stiffness, has gained clinical relevance over the last years. Optic sensors are an attractive instrumental solution for this type of measurement due to their truly non-contact operation capability, which has the potential of an interference free measurement. The nature of the optically originated signals, however, poses new challenges to the designer, either at the probe design level as at the signal processing required to extract the timing information that yields PWV. In this work we describe the construction of two prototype optical probes and discuss their evaluation using three algorithms for pulse transit time (PTT) evaluation. Results, obtained in a dedicated test bench, that is also described, demonstrate the possibility of measuring pulse transit times as short as 1ms with less than 1% error. © Springer-Verlag Berlin Heidelberg 2013.

Abstract
Under a market framework, the development of optimal offering strategies is crucial for wind power producers to achieve maximum profit. In this paper, a two-stage stochastic programming approach is proposed, considering the uncertainties on wind power production and electricity market prices. An artificial intelligence model allows generating wind-price scenarios. Also, risk management is appropriately addressed. Results from a real-world case study are presented, in order to illustrate the proficiency of the proposed approach. Finally, conclusions are duly drawn.

Abstract
The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of health and healthcare smartphone apps (applications) on the market today, including emerging trends and market uptake. Platforms available today include Android, Apple iOS, RIM BlackBerry, Symbian, and Windows (Windows Mobile 6.x and the emerging Windows Phone 7 platform). The paper covers apps targeting both laypersons/patients and healthcare professionals in various scenarios, e. g., health, fitness and lifestyle education and management apps; ambient assisted living apps; continuing professional education tools; and apps for public health surveillance. Among the surveyed apps are those assisting in chronic disease management, whether as standalone apps or part of a BAN (Body Area Network) and remote server configuration. We describe in detail the development of a smartphone app within eCAALYX (Enhanced Complete Ambient Assisted Living Experiment, 20092012), an EU-funded project for older people with multiple chronic conditions. The eCAALYX Android smartphone app receives input from a BAN (a patient-wearable smart garment with wireless health sensors) and the GPS (Global Positioning System) location sensor in the smartphone, and communicates over the Internet with a remote server accessible by healthcare professionals who are in charge of the remote monitoring and management of the older patient with multiple chronic conditions. Finally, we briefly discuss barriers to adoption of health and healthcare smartphone apps (e. g., cost, network bandwidth and battery power efficiency, usability, privacy issues, etc.), as well as some workarounds to mitigate those barriers.

Abstract
Sub-millimetre distension waveforms (0.7 mm, max) are assessed using two new optical probes. The probes differ on the type of photo-detector used: planar photodiodes (PPD), in one case, and avalanche photodiodes (APD), in the other. Performance of the probes is evaluated in an especially developed test setup and in vivo, at the carotid site of humans. In the latter case, distension (associated to the pressure wave generated by the left ventricle contraction that propagates through the arterial system) carries clinically relevant information that can be extracted if, as will be shown, the waveforms are accurate and have enough resolution. An ultrasound image system, Vivid" e, was used as source of reference data for comparison. Along with the probes, a set of software routines was also developed to extract artefact-free data and evaluate the error. Results from the test setup demonstrate the possibility of waveform distension measurements with less than 6% error for both optical probes in this study. In comparison with an ultrasound system, the optical sensors allow the reproduction of the arterial waveform with a higher resolution, adequate to feed feature extraction algorithms.

Abstract
We present a simplified cycle model, using the available data, for the monthly sunspot number random variables {X-t}(t=1)(133), where 133 is taken as the mean duration of the Schwabe's cycle. We present a fit for the mean and standard deviation of X-t. In the descending and ascending phases, we analyse the probability histogram of the monthly sunspot number fluctuations.