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Byers Peninsula is considered one of the largest ice-free areas in maritime Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving the effects of climate change on biological life cycles, limnology, and microbiology. Soils from maritime Antarctica are generally weakly developed and have chemical, physical, and morphological characteristics that are strongly influenced by the parent material. However, biological activity during the short Antarctic summer promotes intense transference of nutrients and organic matter in areas occupied by different species of birds and marine mammals. Mapping and monitoring those areas that are highly occupied by various species could be very useful to create models prepared from satellite images of the edaphic properties. In this approach, deep learning and linear regression models of the soil properties and spectral indexes, which were considered as explicative variables, were used. We trained the models on soil properties closely related to biological activity such as dissolved organic carbon (DOC) and the iron fraction associated with the organic matter (Fe). We tested the best approach to model the spatial distribution of DOC, Fe, and pH by training the linear regression and deep learning models on Sentinel-2 and WorldView-2 images. The most robust models, the pH model built with the deep learning approach on Sentinel images (MAE of 0.51, RMSE of 0.70, and R2 with a residual of −0.49), the DOC model built with linear regression on Sentinel images (MAE of 189.39, RMSE of 342.23, and R2 with a residual of 0.0), and the organic Fe model built with deep learning (MAE of 116.20, RMSE of 209.93, and R2 of −0.05), were used to track possible areas with ornithogenic soils, as well as areas of Byers Peninsula that could be supporting the highest biological development. [ABSTRACT FROM AUTHOR]

This is an exercise to explore the concentration of lithium, lithium-7 isotope and the possible presence of black dirty ice on the lunar surface using spectral data obtained from the Clementine mission. The main interest in tracing the lithium and presence of dark ice on the lunar surface is closely related to future human settlement missions on the moon. We investigate the distribution of lithium and 7 Li isotope on the lunar surface by employing spectral data from the Clementine images. We utilized visible (VIS–NIR) imagery at wavelengths of 450, 750, 900, 950 and 1000 nm, along with near-infrared (NIR–SWIR) at 1100, 1250, 1500, 2000, 2600 and 2780 nm, encompassing 11 bands in total. This dataset offers a comprehensive coverage of about 80% of the lunar surface, with resolutions ranging from 100 to 500 m, spanning latitudes from 80°S to 80°N. In order to extract quantitative abundance of lithium, ground-truth sites were used to calibrate the Clementine images. Samples (specifically, 12045, 15058, 15475, 15555, 62255, 70035, 74220 and 75075) returned from Apollo missions 12, 15, 16 and 17 have been correlated to the Clementine VIS–NIR bands and five spectral ratios. The five spectral ratios calculated synthesize the main spectral features of sample spectra that were grouped by their lithium and 7 Li content using Principal Component Analysis. The ratios spectrally characterize substrates of anorthosite, silica-rich basalts, olivine-rich basalts, high-Ti mare basalts and Orange and Glasses soils. Our findings reveal a strong linear correlation between the spectral parameters and the lithium content in the eight Apollo samples. With the values of the 11 Clementine bands and the 5 spectral ratios, we performed linear regression models to estimate the concentration of lithium and 7 Li. Also, we calculated Digital Terrain Models (Altitude, Slope, Aspect, DirectInsolation and WindExposition) from LOLA-DTM to discover relations between relief and spatial distribution of the extended models of lithium and 7 Li. The analysis was conducted in a mask polygon around the Apollo 15 landing site. This analysis seeks to uncover potential 7 Li enrichment through spallation processes, influenced by varying exposure to solar wind. To explore the possibility of finding ice mixed with regolith (often referred to as 'black ice'), we extended results to the entire Clementine coverage spectral indices, calculated with a library (350–2500 nm) of ice samples contaminated with various concentrations of volcanic particles. [ABSTRACT FROM AUTHOR]

The aim of this work is to provide a full description of how air temperature and solar radiation induce changes in the land cover over an Antarctic site. We use shortwave broadband albedo (albedo integrated in the range 300–3000 nm) from a spaceborne sensor and from field surveys to calculate the monthly relative abundance of landscape units. Field albedo data were collected in January 2019 using a portable albedometer over seven landscape units: clean fresh snow; clean old snow; rugged landscape composed of dirty snow with disperse pyroclasts and rocky outcrops; dirty snow; stripes of bare soil and snow; shallow snow with small bare soil patches; and bare soil. The MODIS MCD43A3 daily albedo products were downloaded using the Google Earth Engine API from the 2000–2001 season to the 2020–2021 season. Each landscape unit was characterized by an albedo normal distribution. The monthly relative abundances of the landscape units were calculated by fitting a linear combination of the normal distributions to a histogram of the MODIS monthly mean albedo. The monthly relative abundance of the landscape unit consisting of rugged landscape composed of dirty snow with dispersed clasts and small rocky outcrops exhibits a high positive linear correlation with the monthly mean albedo (R2 = 0.87) and a high negative linear correlation with the monthly mean air temperature (R2 = 0.69). The increase in the solar radiation energy flux from September to December coincides with the decrease in the relative abundance of the landscape unit composed of dirty snow with dispersed clasts and small rocky outcrops. We propose a mechanism to describe the evolution of the landscape: uncovered pyroclasts act as melting centers favoring the melting of surrounding snow. Ash does not play a decisive role in the melting of the snow. The results also explain the observed decrease in the thaw depth of the permafrost on the island in the period 2006–2014, resulting from an increase in the snow cover over the whole island. [ABSTRACT FROM AUTHOR]

The increasing demand for energy-efficient and sustainable solutions in the building sector has driven the need for innovative approaches that integrate renewable energy sources and advanced control systems. This paper presents an integrated energy management solution for solar-powered smart buildings, combining a multifaceted physical system with advanced IoT- and cloud-based control systems. The physical system includes a heat pump, photovoltaics, solar thermal panels, and an innovative low-enthalpy radiant wall and ceiling, providing self-sufficient heating and cooling. The control system makes use of advanced IoT and communication engineering technologies, using Modbus, HTTP, and MQTT protocols for seamless interconnectivity, monitoring, and remote management. The successful implementation of this solution in an average-sized model house in Paris and a deep energy retrofit of a semidetached single-family house in Oviedo, northern Spain, demonstrates increased energy efficiency, improved thermal comfort, and reduced environmental impact compared with conventional alternatives. This study illustrates the potential of integrating solar energy, IoT, and communication technologies into smart buildings, contributing to the global effort to reduce the environmental impact of the building sector. [ABSTRACT FROM AUTHOR]

Mechanical contention (MC) is a restrictive, vital but controversial measure, prescribed in the majority of EU countries to handle patients with psycho-motor agitation that do not respond to other types of intervention, with an imminent risk of physical violence and aggression involved. This last resort approach implies risks for the somatic health of the contained individual that go from trauma injuries to, in some extreme cases, sudden death. Despite these risks, somatic supervision and the monitoring of patients under MC is limited, being periodically and manually carried out by nursing personnel with portable equipment. In this context, ensuring continuous monitoring using fully automated equipment is an uncovered yet urgent need. There are several devices already in the market capable of monitoring vital signs, but they are not specifically designed for these type of patients and they can be expensive and/or difficult to integrate with other systems from a software perspective. The work described in this paper gives answers to these necessities with the introduction of a low-cost system, targeted at psychiatric patients, for the acquisition and wireless transmission in real-time of physiological parameters, making use of micro-controllers for collecting and processing sensor data, and WiFi technology to upload the information to the server where a patient's profile with all the relevant vital parameters resides. In addition to data collection and processing, an application aimed at use by nursing staff has also been developed to raise alerts in case any critical condition is detected. [ABSTRACT FROM AUTHOR]