Automatic detection of the mental state in responses towards relaxation.

Nowadays, considering society's highly demanding lifestyles, it is important to consider the usefulness of relaxation from the perspective of both psychology and clinical practice. The response towards relaxation (RResp) is a mind-body interaction that relaxes the organism or compensates for the physiological effects caused by stress. This work aims to automatically detect the different mental states (relaxation, rest and stress) in which RResps may occur so that complete feedback about the quality of the relaxation can be given to the subject itself, the psychologist or the doctor.

A Generalization Performance Study Using Deep Learning Networks in Embedded Systems.

Deep learning techniques are being increasingly used in the scientific community as a consequence of the high computational capacity of current systems and the increase in the amount of data available as a result of the digitalisation of society in general and the industrial world in particular. In addition, the immersion of the field of edge computing, which focuses on integrating artificial intelligence as close as possible to the client, makes it possible to implement systems that act in real time without the need to transfer all of the data to centralised servers. The combination of these two concepts can lead to systems with the capacity to make correct decisions and act based on them immediately and in situ.

Recurrent coronary thrombotic events in a moderate case of COVID-19.

We describe the case of a healthy patient with moderate COVID-19 infection without thrombophilia nor coronary disease background who presented with a relapsing thrombotic occlusion of the right coronary artery despite normal oxygenation, adequate antiaggregation and prophylactic anticoagulation. Prophylactic anticoagulation recommendations in COVID-19 were inadequate for this patient. Further data are needed to propose full-dose therapeutic anticoagulation for patients with coronary thrombosis and COVID-19 infection.

Trocar-site incisional hernia after laparoscopic colorectal surgery: a significant problem? Incidence and risk factors from a single-center cohort.

Background: Trocar-site incisional hernia (TSIH) after laparoscopic surgery has been scarcely studied. TSIH incidence and risk factors have never been properly studied for laparoscopic colorectal surgery.

Methods: A retrospective analytic study in a tertiary hospital was performed including patients who underwent elective laparoscopic colorectal surgery between 2014 and 2016.

Characterization of e-Government adoption in Europe.

The digital divide in Europe has not yet been bridged and thus more contributions towards understanding the factors affecting the different dimensions involved are required. This research offers some insights into the topic by analyzing the e-Government adoption or practical use of e-Government across Europe (26 EU countries). Based on the data provided by the statistical office of the European Union (Eurostat), we defined two indexes, the E-Government Use Index (EGUI) and an extreme version of it taking into account only null or complete use (EGUI+), and characterized the use/non use of e-Government tools using supervised learning procedures in a selection of countries with different e-Government adoption levels.