Quantitative analysis of smartphone PPG data for heart monitoring

The field of app-based PPG monitoring of cardiac activity is promising, yet classification of heart rhythms in normal sinus rhythm (NSR) or atrial fibrillation (Afib) is difficult in the case of noisy measurements. In this work, we aim at characterizing a dataset of 1572 subjects, whose signals have been crowdsourced by collecting measurements via a dedicated smartphone app, using the embedded camera. We evaluate the distributions of three features of our signals: the peak area, amplitude and the time interval between two successive pulses. We evaluate if some factors affected the distributions, discovering that the strongest effects are for age and BMI groupings. We evaluate the results agreement between the R G B channels of acquisition, finding good agreement between the first two. After finding signal quality indexes in literature, we use a subset of them in a classification task, combined with dynamic time warping distance, a technique that matches a signal to a template. We achieve an accuracy of 89% on the test set, for binary quality classification. On the chaotic temporal series we evaluate the appearance of different types of rhythms on Poincaré plots and we quantify the results by a measure of their 3D spread. We perform this on a set of 20 subjects, 10 NSR and 10 Afib, finding significant differences between their 3D morphologies. We extend our analysis to the larger dataset, obtaining some significant results

Ground state for a massive scalar field in BTZ spacetime with Robin boundary conditions

We consider a real, massive scalar field in BTZ spacetime, a 2+1-dimensional black hole solution of the Einstein's field equations with a negative cosmological constant. First, we analyze the space of classical solutions in a mode decomposition and we characterize the collection of all admissible boundary conditions of Robin type which can be imposed at infinity. Secondly, we investigate whether, for a given boundary condition, there exists a ground state by constructing explicitly its two-point function. We demonstrate that for a subclass of the boundary conditions it is possible to construct a ground state that locally satisfies the Hadamard property. In all other cases, we show that bound state mode solutions exist and, therefore, such construction is not possible.Comment: 17 pages, 3 figure

Tunnelling processes for Hadamard states through a 2+1 dimensional black hole and Hawking radiation

We analyse the local behaviour of the two-point correlation function of a quantum state for a scalar field in a neighbourhood of a Killing horizon in a $2+1$-dimensional spacetime, extending the work of Moretti and Pinamonti in a $3+1$-dimensional scenario. In particular we show that, if the state is of Hadamard form in such neighbourhood, similarly to the $3+1$-dimensional case, under a suitable scaling limit towards the horizon, the two-point correlation function exhibits a thermal behaviour at the Hawking temperature. Since the whole analysis rests on the assumption that a Hadamard state exists in a neighbourhood of the Killing horizon, we show that this is not an empty condition by verifying it for a massive, real scalar field subject to Robin boundary conditions in the prototypic example of a three dimensional black hole background: the non-extremal, rotating BTZ spacetime.Comment: 16 pages, 1 figur

Regulación de las tarifas de electricidad durante el salazarismo

O objectivo de este trabalho é contribuir para a discussão sobre a intervenção do Governo na formulação dos sistemas tarifários de electricidade. Mostraremos a centralização progressiva na regulação tarifária durante o Estado Novo e os efeitos das políticas aplicadas que produziram diferentes estilos de vida, no que diz respeito ao uso doméstico de energia nas duas principais cidades portuguesas (Lisboa e Porto). Finalmente, mostraremos porque, do ponto de vista da procura, a estrutura tarifária em uso hoje (aplicada desde a nacionalização, c.1975) não é “mais social” do que as tarifas regressivas aplicadas durante o Salazarismo, ao contrário do que fora anunciado na altura da sua aplicação.The aim of this paper is to contribute to today’s discussion on Government’s implication on electrical rate systems. We show the progressive centralization in the regulation of electric rates that was in force during the ‘Estado Novo’ and the effects of certain policies that produced different lifestyles, in what regards the use of energy in the two main Portuguese cities (Lisbon and Oporto). Finally, we explain why, from the demand point of view, today’s electrical rate system (used since the nationalisation, c.1975) is not more “social”, as it was announced, than the former regressive rate system used during ‘Salazarism’

Automatic Procedures as Help for Optimal Cam Design

ABSTRACT In this work we suggest a synthesis of recent results obtained on the application of soft-computing techniques to solve typical automatic machines design problems. Particularly, here we show an optimization method based on the application of a specialized algorithms ruled by a generalized software procedures, which appears able to help the mechanical designer in the first part of the design process, when he has to choose among different wide classes of solutions. In this frame, among the different problems studied, we refer here about the choice of the best class of motion profiles, to be imposed to a cam follower, which must satisfy prefixed design specifications. A realistic behaviour of the system is considered and the parameter model identification is set up by a soft computing procedure. The design, based on theoretical knowledge, sometimes is not sufficient to fulfil desired dynamical performances, in this situation, a residual optimization is achieved with the help of another optimizing method. The problem of a cam-follower design is presented. A class of motion profiles and the best theoretical motion profile is selected by an evolutionary algorithm. A realistic model is considered and its parameter identification is achieved by a genetic algorithm. The residual optimization is achieved by a servomotor optimized by another genetic algorithm. Evolutionary approach is used during all the design process and, as was shown, it allows really interesting performance in terms of simplicity of the design process and in terms of performance of the product

Portugueses Gaúchos: socio-political transnationalism, integration and identities in the River Plate Region

Através da análise de entrevistas com emigrantes portugueses e os seus descendentes na região platina, o artigo explora as relações entre integração e participação em associações de emigrantes, e como elas se inter-relacionam com a identidade colectiva na sociedade de recepção. Examinamos o papel das associações de emigrantes na construção e reforço dos símbolos, referências e identidades nacionais, e como simultaneamente facilitam a integração. Sugerimos que a activação de identidades do país de origem não tem efeitos etnicizantes; pelo contrário, funciona como recurso efectivo da integração, promovendo as redes sociais abertas

AI slipping on tiles: data leakage in digital pathology

Reproducibility of AI models on biomedical data still stays as a major concern for their acceptance into the clinical practice. Initiatives for reproducibility in the development of predictive biomarkers as the MAQC Consortium already underlined the importance of appropriate Data Analysis Plans (DAPs) to control for different types of bias, including data leakage from the training to the test set. In the context of digital pathology, the leakage typically lurks in weakly designed experiments not accounting for the subjects in their data partitioning schemes. This issue is then exacerbated when fractions or subregions of slides (i.e. "tiles") are considered. Despite this aspect is largely recognized by the community, we argue that it is often overlooked. In this study, we assess the impact of data leakage on the performance of machine learning models trained and validated on multiple histology data collection. We prove that, even with a properly designed DAP (10x5 repeated cross-validation), predictive scores can be inflated up to 41% when tiles from the same subject are used both in training and validation sets by deep learning models. We replicate the experiments for $4$ classification tasks on 3 histopathological datasets, for a total of 374 subjects, 556 slides and more than 27,000 tiles. Also, we discuss the effects of data leakage on transfer learning strategies with models pre-trained on general-purpose datasets or off-task digital pathology collections. Finally, we propose a solution that automates the creation of leakage-free deep learning pipelines for digital pathology based on histolab, a novel Python package for histology data preprocessing. We validate the solution on two public datasets (TCGA and GTEx)