Guidelines for Managing Radon Hazards in Tourist Volcanic Caves in Spain.

Tourist volcanic caves are in high demand for ecotourism and geotourism lovers, as well as by sun and beach tourists as a complementary activity during their holidays. There are six tourist volcanic caves in the Canary Islands, all of them managed by the local administration of the island. The managers of these caves must ensure the safety of visitors and workers, who are exposed to natural hazards, such as radon, inherent to the environment in which the activity takes place.

Comparing the clinical applicability of wavefront phase imaging in keratoconus versus normal eyes.

The aim of this work is to quantitatively assess the wavefront phase of keratoconic eyes measured by the ocular aberrometer t·eyede (based on WaveFront Phase Imaging Sensor), characterized by a lateral resolution of 8.6 µm without requiring any optical element to sample the wavefront information. We evaluated the parameters: root mean square error, Peak-to-Valley, and amplitude of the predominant frequency (Fourier Transform analysis) of a section of the High-Pass filter map in keratoconic and healthy cohorts.

Effect of tourist activity on wastewater quality in selected wastewater treatment plants in the Balearic Islands (Spain).

Unregulated sewage discharge into the sea poses a considerable danger to marine ecosystems, with coastal regions being particularly vulnerable to this because of the impact of tourism. This issue is amplified during the summer season, as the Balearic Islands are a heavily frequented destination. This study aims to determine the water quality in five different wastewater treatment plants (WWTPs) representative on the islands.

Potentially harmful elements pollute soil and vegetation around the Atrevida mine (Tarragona, NE Spain).

Mining activity is one of the main sources to pollute soil, water and plants. An analysis of soil and plant samples around the Atrevida mining area in Catalonia (NE Spain) was preformed to determine potentially harmful elements (PHEs). Soil and plant samples were taken at eight locations around the mining area.

Retinal age as a predictive biomarker of the diabetic retinopathy grade.

Objective: To apply artificial intelligence (AI) techniques, through deep learning algorithms, for the development and optimization of a system for predicting the age of a person based on a color retinography and to study a possible relationship between the evolution of retinopathy diabetes and premature ageing of the retina.

Methods: A convolutional network was trained to calculate the age of a person based on a retinography. Said training was carried out on a set of retinographies of patients with diabetes previously divided into three subsets (training, validation and test).