Abstract
Congenital heart disease (CHD) is the most common congenital malformation and has high morbidity and mortality related to late diagnosis. Screening protocols are lacking and only 1% of murmurs are associated with CHD. The decline in auscultation skills highlights the need for better screening. This study aims to create and evaluate models for the detection of CHD using clinical data and sound features. These features were extracted using pure conventional MFCC and selected MFCC through matrix profiling and motif search. Four combinations of data were used to train decision trees (DT) and artificial neural networks (ANN), and the area under the curve (AUC) was compared. Posteriorly, models were also trained for the detection of any cardiac pathology. In both pathologies, the ANN model using clinical data and conventional MFCC showed the highest performance with AUC of 0.761 for CHD and 0.791 for any cardiac pathology. However, this is only a slight improvement when compared with the ANN models using only clinical data (0.747 and 0.789, respectively. Additionally, the inclusion of motif selected MFCC seems to worsen the model performance. Although further research is still needed, this is a potential improvement in CHD screening, particularly for primary care physicians.

Abstract
Internet voting has been trialed or introduced for several countries, including Norway, Portugal, United States, United Kingdom and Switzerland as an additional voting channel to increase voter turnout and, also to modernize the electoral process. However, only Estonia has successful introduced internet voting, deploying e-enabled elections in general governmental levels. This paper aims to provide an exploratory study on the Estonian internet voting model to identify pre-conditions for internet voting introduction in Portugal, addressing legal, technical and technological considerations. For doing so, it includes a cross-country comparative analysis in two perspectives. Firstly, an analysis in the Estonian electoral framework, highlighting the most important legal adaptations that make possible internet voting introduction to identify potential transformation for the Portuguese context. Secondly, to provide a technological overview towards the Portuguese e-government ecosystem to seek similar conditions that can make internet voting possible in Estonia.

Abstract
Multiple wearable devices for cardiovascular self-monitoring have been proposed over the years, with growing evidence showing their effectiveness in the detection of pathologies that would otherwise be unnoticed through standard routine exams. In particular, Electrocardiography (ECG) has been an important tool for such purpose. However, wearables have known limitations, chief among which are the need for a voluntary action so that the ECG trace can be taken, battery lifetime, and abandonment. To effectively address these, novel solutions are needed, which has recently paved the way for "invisible" (aka "off-the-person") sensing approaches. In this article we describe the design and experimental evaluation of a system for invisible ECG monitoring at home. For this purpose, a new sensor design was proposed, novel materials have been explored, and a proof-of-concept data collection system was created in the form of a toilet seat, enabling ECG measurements as an extension of the regular use of sanitary facilities, without requiring body-worn devices. In order to evaluate the proposed approach, measurements were performed using our system and a gold standard equipment, involving 10 healthy subjects. For the acquisition of the ECG signals on the toilet seat, polymeric electrodes with different textures were produced and tested. According to the results obtained, some of the textures did not allow the acquisition of signals in all users. However, a pyramidal texture showed the best results in relation to heart rate and ECG waveform morphology. For a texture that has shown 0% signal loss, the mean heart rate difference between the reference and experimental device was - 1.778 +/- 4.654 Beats per minute (BPM); in terms of ECG waveform, the best cases present a Pearson correlation coefficient above 0.99.

Abstract

Abstract

Abstract
Technological developments related to renewable energy led to a decrease on the prices of generation and allowed the penetration of distributed energy resources in power systems. This context, combined with other factors, such as the development of electric vehicles, enabled the rapid evolution of Smart Grids. As a consequence, Distribution System Operators (DSOs) have been investing in this field to keep up with its deployment. This work presents a case study that compares a set of European DSOs regarding their investment in Smart Grid projects. The methodology underlying this study is based on the construction of composite indicators using the Data Envelopment Analysis technique. Furthermore, we evaluate the evolution in the DSOs performance between 2013 and 2017 using a Malmquist index. The results are discussed in the light of their contribution to the definition of public policies in the energy field. © 2021, Springer Nature Switzerland AG.