The energy crossroads: Exploring the moderating role of the energy crisis on the acceptance of the development of a uranium mine.

The energy crisis caused by the lack of supply from some countries involved in armed conflicts, coupled with society's continuous demand for energy production, is leading to the proposal of new energy sources, such as the development of uranium mines to increase nuclear energy production. Mine projects (MPs) trigger numerous conflicts in the local societies involved. While for some people, they represent an opportunity for development and benefits, for others these proposals are perceived as a threat and a health risk.

Network analysis to examine sex differences linked to emotional well-being in cardiovascular disease.

Psychosocial dimensions are essential to guarantee an optimal approach to improve emotional well-being in patients with cardiovascular disease (CVD). There is evidence of sex differences regarding these dimensions. Thus, the connections between them are crucial to implement personalized therapies.

Driving anxiety and anxiolytics while driving: Their impacts on behaviour and cognition behind the wheel.

Introduction: The interaction between road safety and drivers' mental health is an important issue to take into consideration on transportation and safety research. The present review deals specifically with the link between anxiety and driving activity from two complementary points of view.

Method: A systematic review into primary studies, following the PRISMA statement, was carried out in four databases: Scopus, Web of Science, Transport Research International Documentation and Pubmed.

Explanatory model of the psychosocial variables related to the social acceptance of a uranium mine project in northwest Spain.

Introduction: The demographic growth and the development of the welfare system have been accompanied by an important social dilemma between preserving nature or promoting energy development by assuming the benefits and risks of both proposals. This research attempts to address this social dilemma by analyzing the psychosocial factors that influence the acceptance or rejection of a new uranium mining development and exploitation project. The main objective was to test an explanatory theoretical model of uranium mining project acceptance, based on the interrelation of sociodemographic variables (e.

Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals.

Background: Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique frequently used to measure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations.

Spontaneous Breathing Rate Variations Linked to Social Exclusion and Emotion Self-assessment.

The emotional reactions to social exclusion can be associated with physiological responses that could allow researchers to estimate the valence and intensity of the ongoing affective state. In this work, respiratory activity was analysed to verify whether breathing rate variations can be considered as predictive factors of subsequent positive and negative affect after inclusion and exclusion in young women. A standard Cyberball task was implemented and manipulated information was provided to the participants to create both conditions.

Cognitive and body manifestations of driving anxiety according to different onsets.

Driving anxiety can have deleterious effects not only on driving behavior, but also on life quality. The interaction between motor vehicle collision (MVC) experiences and driving anxiety has been studied from different standpoints. However, the comparison with other events triggering it has been scarcely considered.

The Arousal Effect of Exclusionary and Inclusionary Situations on Social Affiliation Motivation and Its Subsequent Influence on Prosocial Behavior.

Given the negative costs of exclusion and the relevance of belongingness for humans, the experience of exclusion influences social affiliation motivation, which in turn is a relevant predictor of prosocial behavior. Skin conductance is a typical measure of the arousal elicited by emotions. Hence, we argued that both inclusion and exclusion will increase skin conductance level due to the increase of either positive affect or anger affects, respectively.

Cortical Activity Linked to Clocking in Deaf Adults: fNIRS Insights with Static and Animated Stimuli Presentation.

The question of the possible impact of deafness on temporal processing remains unanswered. Different findings, based on behavioral measures, show contradictory results. The goal of the present study is to analyze the brain activity underlying time estimation by using functional near infrared spectroscopy (fNIRS) techniques, which allow examination of the frontal, central and occipital cortical areas.

Towards Mindless Stress Regulation in Advanced Driver Assistance Systems: A Systematic Review.

Stress can frequently occur in the driving context. Its cognitive effects can be deleterious and lead to uncomfortable or risky situations. While stress detection in this context is well developed, regulation using dedicated advanced driver-assistance systems (ADAS) is still emergent.

Hemodynamic responses to visual cues during attentive listening in autonomous versus manual simulated driving: A pilot study.

Emerging automation technologies could have a strong impact on the allocation of drivers' attentional resources. The first objective of this pilot study is to investigate the hemodynamic responses evoked to relevant visual stimuli in manual and autonomous driving. The second aim is to examine how the inclusion of a secondary task (attentive listening to a broadcast) modulates these hemodynamic responses in both driving situations.

Respiration and Heart Rate Modulation Due to Competing Cognitive Tasks While Driving.

Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver's activity and CW variations in driving.

Cardiovascular correlates of emotional state, cognitive workload and time-on-task effect during a realistic flight simulation.

In aviation, emotion and cognitive workload can considerably increase the probability of human error. An accurate online physiological monitoring of pilot's mental state could prevent accidents. The heart rate (HR) and heart rate variability (HRV) of 21 private pilots were analysed during two realistic flight simulator scenarios.

Spectral and spatiotemporal variability ECG parameters linked to catheter ablation outcome in persistent atrial fibrillation.

With the increasing prevalence of atrial fibrillation (AF), there is a strong clinical interest in determining whether a patient suffering from persistent AF will benefit from catheter ablation (CA) therapy at long term. This work presents several regression models based on noninvasive measures automatically computed from the standard 12-lead electrocardiogram (ECG) such as AF dominant frequency (DF), spectral concentration and spatiotemporal variability (STV). Sixty-two AF patients referred to CA were enrolled in this study.

Non-invasive prediction of catheter ablation outcome in persistent atrial fibrillation by fibrillatory wave amplitude computation in multiple electrocardiogram leads.

Background: Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging, and reported results are capable of improvement. A better patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation, especially for patients with low odds of favorable outcome. CA outcome can be predicted non-invasively by atrial fibrillatory wave (f-wave) amplitude, but previous works focused mostly on manual measures in single electrocardiogram (ECG) leads only.

Atrial signal extraction in atrial fibrillation electrocardiograms using a tensor decomposition approach.

Atrial fibrillation (AF) is the most common cardiac arrhythmia encountered in clinical practice and remains a major challenge in cardiology. The noninvasive analysis of AF usually requires the estimation of the atrial activity (AA) signal in surface electrocardiogram (ECG) recordings. The present contribution puts forward a tensor decomposition approach for noninvasive AA extraction in AF ECG recordings.

Empirical mode decomposition of multiple ECG leads for catheter ablation long-term outcome prediction in persistent atrial fibrillation.

Predictive models arouse increasing interest in clinical practice, not only to improve successful intervention rates but also to extract information of diverse physiological disorders. This is the case of persistent atrial fibrillation (AF), the most common cardiac arrhythmia in adults. Currently, catheter ablation (CA) is one of the preferred therapies to face this disease.

Disentangling the attention network test: behavioral, event related potentials, and neural source analyses.

Background: The study of the attentional system remains a challenge for current neuroscience. The "Attention Network Test" (ANT) was designed to study simultaneously three different attentional networks (alerting, orienting, and executive) based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks.

Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

Background: A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis.

Regions of interest computed by SVM wrapped method for Alzheimer's disease examination from segmented MRI.

Accurate identification of the most relevant brain regions linked to Alzheimer's disease (AD) is crucial in order to improve diagnosis techniques and to better understand this neurodegenerative process. For this purpose, statistical classification is suitable. In this work, a novel method based on support vector machine recursive feature elimination (SVM-RFE) is proposed to be applied on segmented brain MRI for detecting the most discriminant AD regions of interest (ROIs).