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This paper lays out the role of the first centre in the world for the integration into the electrical grid of electricity coming from renewable energy (the Spanish acronym for which is CECRE (Centro de Control de Energías Renovables; Control Centre for Renewable Energies)) and the industrial development of large energy suppliers and wind turbine manufacturers in Spain. These two initiatives enabled the development of one of the first integrated markets for this type of energy source. The key contributions were the development of two software programs (wind management and management of solar light incidence), their visual implementation, and centralized digital control. An economic and business history approach is used to show the rise and relative failure of the Spanish wind industry during the period 2004–2015, when Spain became the fourth country after China, the US, and Germany in terms of installed capacity of renewable energy and, in relative terms, the second country after Denmark. This study is unique in that it provides an integrated vision of the reasons for the relative fall of Spain in the world ranking of wind energy producers. The methodology of the economic analysis of industrial policies makes it possible to explain the fall in the relative importance of Spain in the international panorama of wind farms. [ABSTRACT FROM AUTHOR]

Over the last few decades, public programs have driven the gradual adoption of information and communication technologies (ICTs) in education. The most ambitious project in Spain so far was Escuela 2.0, which provided students from the regions that opted into the program with laptops. The objective of this paper is to evaluate the impact of this program on school performance and productivity. To do this, we developed a new methodological approach based on combining causal inference techniques and the analysis of production frontiers. We calculated the differences in productivity and performance between treated and control schools using the base-group Camanho–Dyson Malmquist index and the base-group performance gap index. We estimate the impact of the program as the variation of these differences, following the essence of the difference-in-differences analysis. The main results are that Escuela 2.0 had a negative impact on performance and productivity. [ABSTRACT FROM AUTHOR]

The aim of this paper is to statistically characterize gross beta activity concentrations in ground-level air in Bilbao (northern Spain) by analysing five years (2014–2018) worth of weekly measurements in aerosols collected in filters to analyse the impact of local meteorological parameters on concentrations. In addition, synoptic meteorological scenarios associated with anomalous beta surface activity concentrations were identified. Over this five-year period, beta activity concentrations ranged from 35.45 µBq/m3 to 1778 µBq/m3 with a mean of 520.12 ± 281.77 µBq/m3. A positive correlation was found with the alpha concentrations (0.67), with an average of 0.138 for the alpha/beta ratio, and a low correlation was found with 7Be (0.16). Statistical analysis identified a seasonal component in the time series, increasing, on average, beta activity concentrations from winter to autumn. The highest beta activity concentrations were measured under the arrival of southerly land winds with low wind speeds, while the wind analysis (surface winds and air masses) of two different seasonal periods (autumn 2015 and winter 2017) have highlighted how small variations in synoptic and local winds highly influence beta activity concentrations. These results are relevant to understand the meteorological factors affecting beta activity concentrations in this area and hence to define meteorological scenarios that are in favour to high/anomalous surface activity concentrations that are harmful to the environmental and public health. [ABSTRACT FROM AUTHOR]

This study provides an in-depth assessment of the environmental performance of five public schools in the transition towards a low-carbon economy and a more sustainable model of society. Life cycle assessment (LCA) methodology is used to conduct the study. The school system includes several activities and processes clustered in three subsystems: management of the school building, training and learning activities (T&L) and mobility and transport (M&T). A detailed primary data inventory of energy and resources consumption was collected in five schools located in Spain and Portugal. Findings on climate change (CC), water depletion (WD), particular matter (PM), acidification (Ac), and human health (HH), as well as associated external cost (EC), are reported per student in one school year as reference unit, allowing the schools' individual performance comparison and identify the potential improvements. Considering the sample of schools, findings reveal that peculiarities of the schools, such as location, specialization, and level of education, are crucial for the environmental performance. Buildings are a relevant contributor to CC as well as heating and electricity needs, although their relevance is dependent on multiple factors. The M&T subsystem also has relevant weight on the metrics evaluated. Educational activities have a lower impact in absolute terms but, in some schools, it becomes the main contributor to HH due to paper and electricity consumption and manufacturing of equipment. External costs results are in the range of 11 to 38 EUR/student·year mainly caused by heating, electricity and wastes from the building subsystem, and the M&T subsystem. [ABSTRACT FROM AUTHOR]

Islands are widely recognised as ideal pilot sites that can spearhead the transition to clean energy and development towards a sustainable and healthy society. One of the assumptions underpinning this notion is that island communities are more ready to engage with smart grids (SGs) than people on the mainland. This is believed to be due to the high costs of energy on islands and the idea that the sense of community and collective action is stronger on islands than on the mainland. This paper presents findings from a survey conducted to assess people's perception of, and readiness to engage with, SG and demand response (DR) in the communities of three islands taking part in a H2020 project called REACT. The main objective of the survey, conducted in 2020, was to inform the recruitment of participants in the project, which is piloting different technologies required for SGs and DR with communities on the three islands. The results show that many island residents are motivated to take part in SG, to engage with energy saving, and are willing to change some energy-related behaviours in their homes. However, the results also indicate that levels of ownership of, and knowledge and familiarity with, the SG and DR related technologies are extremely low, suggesting that the expected uptake of DR in islands might not be as high as anticipated. This brings into question the readiness of island dwellers for the SG, their role in the deployment of such schemes more widely and the validity of the assumptions often made about island communities. This has significant implications for the design of SGs and DR solutions for islands, including devoting sufficient efforts to build knowledge and awareness of the SG, investing in demonstration projects for that purpose and tailoring interventions based on island communities' motivations. [ABSTRACT FROM AUTHOR]

Disinformation does not always take the form of a fake news item, it also appears in much less evident formats which are subtly filtered into public opinion, thus making its detection more difficult. A method is proposed in this paper to address the study of "widespread" disinformation by combining social science methods with artificial intelligence and text mining. The case study chosen was the expression "right of self-determination" as a generator of disinformation within the context of the Catalan independence process. The main work hypothesis was that the (intentional or unintentional) confusion around the meaning and scope of this right has become widely extended within the population, generating negative emotions which favour social polarisation. The method utilised had three stages: (1) Description of the disinformation elements surrounding the term with the help of experts; (2) Detection of these elements within a corpus of tweets; (3) Identification of the emotions expressed in the corpus. The results show that the disinformation described by experts clearly dominates the conversation about "self-determination" on Twitter and is associated with a highly negative emotional load in which contempt, hatred, and frustration prevail. [ABSTRACT FROM AUTHOR]

Demand for niobium and tantalum is increasing exponentially as these are essential ingredients for the manufacture of, among others, capacitors in technological devices and ferroniobium. Mine tailings rich in such elements could constitute an important source of Nb and Ta in the future and alleviate potential supply risks. This paper evaluates the possibility of recovering niobium and tantalum from the slags generated during the tin beneficiation process of mine tailings from the old Penouta mine, located in Spain. To do so, a simulation of the processes required to beneficiate and refine both elements is carried out. After carbothermic tin reduction, the slags are sent to a hydrometallurgical process where niobium oxide and tantalum oxide are obtained at the end. Reagents, water, and energy consumption, in addition to emissions, effluents, and product yields, are assessed. Certain factors were identified as critical, and recirculation was encouraged in the model to maximise production and minimise reagents' use and wastes. With this simulation, considering 3000 production hours per year, the metal output from the tailings of the old mine could cover around 1% and 7.4% of the world annual Nb and Ta demand, respectively. [ABSTRACT FROM AUTHOR]

Understanding of energy consumption patterns is extremely important for optimization of resources and application of green trends. Traditionally, analyses were performed for large environments like regions and nations. However, with the advent of Smart Grids, the study of the behavior of smaller environments has become a necessity to allow a deeper micromanagement of the energy grid. This paper presents a data processing system to analyze energy consumption patterns in industrial parks, based on the cascade application of a Self-Organizing Map (SOM) and the clustering k-means algorithm. The system is validated with real load data from an industrial park in Spain. The validation results show that the system adequately finds different behavior patterns which are meaningful, and is capable of doing so without supervision, and without any prior knowledge about the data. [ABSTRACT FROM AUTHOR]

Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS), the chance-constrained programming-based strategy (CPS) and the multi-objective bidding strategy (ECPS). Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets. [ABSTRACT FROM AUTHOR]

Non-destructive methods are of great interest for the analysis of cultural heritage. Among the different possible techniques, this paper presents a low cost prototype based on the emission and reception of airborne ultrasound without direct contact with the test specimen. We successfully performed a method test for the detection of brick joints under a XVth century Renaissance fresco of the Metropolitan Cathedral of the city of Valencia (Spain). Both laboratory and in situ results are in agreement. Using this prototype system, an early moisture detection system has been installed in the dome that supports the fresco. The result is encouraging and opens interesting prospects for future research. [ABSTRACT FROM AUTHOR]

As a new technology, electric mobility has the potential to achieve a reduction in CO2 emissions and contribute to the transition from the current transportation system to a better one, environmentally speaking. The objective of the paper is to aid the necessary decision-making for the adoption and development of electric vehicles in Spain, taking the time horizon of 2020. This will be achieved by building a System Dynamics model for various scenarios that will be used for the analysis and comparison of various dynamic variables, as well as to determine how, and to what extent, they will influence the number of electric vehicles that will run on Spanish roads in the coming years, focusing on the cost variable. [ABSTRACT FROM AUTHOR]

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement. [ABSTRACT FROM AUTHOR]

This paper presents a novel system for automatic forest-fire measurement using cameras distributed at ground stations and mounted on Unmanned Aerial Systems (UAS). It can obtain geometrical measurements of forest fires in real-time such as the location and shape of the fire front, flame height and rate of spread, among others. Measurement of forest fires is a challenging problem that is affected by numerous potential sources of error. The proposed system addresses them by exploiting the complementarities between infrared and visual cameras located at different ground locations together with others onboard Unmanned Aerial Systems (UAS). The system applies image processing and geo-location techniques to obtain forest-fire measurements individually from each camera and then integrates the results from all the cameras using statistical data fusion techniques. The proposed system has been extensively tested and validated in close-to-operational conditions in field fire experiments with controlled safety conditions carried out in Portugal and Spain from 2001 to 2006. [ABSTRACT FROM AUTHOR]

This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM) and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas) on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat-TM5 and Landsat-ETM+7). Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM) comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS) in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas. [ABSTRACT FROM AUTHOR]

The interest in measuring physiological parameters (especially arterial blood gases) has grown progressively in parallel to the development of new technologies. Physiological parameters were first measured invasively and at discrete time points; however, it was clearly desirable to measure them continuously and non-invasively. The development of intensive care units promoted the use of ventilators via oral intubation ventilators via oral intubation and mechanical respiratory variables were progressively studied. Later, the knowledge gained in the hospital was applied to out-of-hospital management. In the present paper we review the invasive and non-invasive techniques for monitoring respiratory variables. [ABSTRACT FROM AUTHOR]

In this paper, we give an overview of the research on fluxgate magnetometers carried out in Spain. In particular we focus in the development of the planar-type instruments. We summarize the fabrication processes and signal processing developments as well as their use in complex systems and space. [ABSTRACT FROM AUTHOR]

Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous ,,cold chain? from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments. [ABSTRACT FROM AUTHOR]

Critical care units are equipped with commercial monitoring devices capable of sensing patients' physiological parameters and supervising the achievement of the established therapeutic goals. This avoids human errors in this task and considerably decreases the workload of the healthcare staff. However, at present there still is a very relevant physiological parameter that is measured and supervised manually by the critical care units' healthcare staff: urine output. This paper presents a patent-pending device capable of automatically recording and supervising the urine output of a critical care patient. A high precision scale is used to measure the weight of a commercial urine meter. On the scale's pan there is a support frame made up of Bosch profiles that isolates the scale from force transmission from the patient's bed, and guarantees that the urine flows properly through the urine meter input tube. The scale's readings are sent to a PC via Bluetooth where an application supervises the achievement of the therapeutic goals. The device is currently undergoing tests at a research unit associated with the University Hospital of Getafe in Spain. [ABSTRACT FROM AUTHOR]

In this paper we show a fast, specialized hardware implementation of the wavefront phase recovery algorithm using the CAFADIS camera. The CAFADIS camera is a new plenoptic sensor patented by the Universidad de La Laguna (Canary Islands, Spain): international patent PCT/ES2007/000046 (WIPO publication number WO/2007/082975). It can simultaneously measure the wavefront phase and the distance to the light source in a real-time process. The pipeline algorithm is implemented using Field Programmable Gate Arrays (FPGA). These devices present architecture capable of handling the sensor output stream using a massively parallel approach and they are efficient enough to resolve several Adaptive Optics (AO) problems in Extremely Large Telescopes (ELTs) in terms of processing time requirements. The FPGA implementation of the wavefront phase recovery algorithm using the CAFADIS camera is based on the very fast computation of two dimensional fast Fourier Transforms (FFTs). Thus we have carried out a comparison between our very novel FPGA 2D-FFTa and other implementations. [ABSTRACT FROM AUTHOR]

In this paper we present a stereo feature-based method using SIFT (Scale-invariant feature transform) descriptors. We use automatic feature extractors, matching algorithms between images and techniques of robust estimation to produce a DTM (Digital Terrain Model) using convergent shots of a rock glacier.The geomorphologic structure observed in this study is the Veleta rock glacier (Sierra Nevada, Granada, Spain). This rock glacier is of high scientific interest because it is the southernmost active rock glacier in Europe and it has been analyzed every year since 2001. The research on the Veleta rock glacier is devoted to the study of its displacement and cartography through geodetic and photogrammetric techniques. [ABSTRACT FROM AUTHOR]

Sensors provide robotic systems with the information required to perceive the changes that happen in unstructured environments and modify their actions accordingly. The robotic controllers which process and analyze this sensory information are usually based on three types of sensors (visual, force/torque and tactile) which identify the most widespread robotic control strategies: visual servoing control, force control and tactile control. This paper presents a detailed review on the sensor architectures, algorithmic techniques and applications which have been developed by Spanish researchers in order to implement these mono-sensor and multi-sensor controllers which combine several sensors. [ABSTRACT FROM AUTHOR]

In this paper, we propose a solution for gunshot location in national parks. In Spain there are agencies such as SEPRONA that fight against poaching with considerable success. The DiANa project, which is endorsed by Cabãneros National Park and the SEPRONA service, proposes a system to automatically detect and locate gunshots. This work presents its technical aspects related to network design and planning. The system consists of a network of acoustic sensors that locate gunshots by hyperbolic multi-lateration estimation. The differences in sound time arrivals allow the computation of a low error estimator of gunshot location. The accuracy of this method depends on tight sensor clock synchronization, which an ad-hoc time synchronization protocol provides. On the other hand, since the areas under surveillance are wide, and electric power is scarce, it is necessary to maximize detection coverage and minimize system cost at the same time. Therefore, sensor network planning has two targets, i.e., coverage and cost. We model planning as an unconstrained problem with two objective functions. We determine a set of candidate solutions of interest by combining a derivative-free descent method we have recently proposed with a Pareto front approach. The results are clearly superior to random seeding in a realistic simulation scenario. [ABSTRACT FROM AUTHOR]

The XXI century home should be a digital habitat, a connected residence, but at the same time it should be involved in sustainability and the environment. The location of new technologies at home, and its acceptance by the user, requires, among other actions, a significant diffusion and activity to be undertaken. This work proposes the development of a Smart House network designed for its integration into a sustainable and bioclimatic solar house. The paper focuses on a specific aspect of the house design, the control system bus, developed for the management of the different parameters, variables, sensors and actuators which coexist at home. Finally, the system has been installed in a laboratory bioclimatic house. Environmental variable experiments based on the control of passive elements, such as phase shift gels, are presented. Experimental results show that the system is able to benefit from the bioclimatic elements in the house by taking into account the user preferences. [ABSTRACT FROM AUTHOR]

This paper presents the design, construction and testing of a new photodiode-based pyranometer for the visible spectral range (approx. 400 to 750 nm), whose principal characteristics are: accuracy, ease of connection, immunity to noise, remote programming and operation, interior temperature regulation, cosine error minimisation and all this at a very low cost, tens of times lower than that of commercial thermopile-based devices. This new photodiode-based pyranometer overcomes traditional problems in this type of device and offers similar characteristics to those of thermopile-based pyranometers and, therefore, can be used in any installation where reliable measurement of solar irradiance is necessary, especially in those where cost is a deciding factor in the choice of a meter. This new pyranometer has been registered in the Spanish Patent and Trademark Office under the number P200703162. [ABSTRACT FROM AUTHOR]

Magnetic data consists of a sequence of collected points with spatial coordinates and magnetic information. The spatial location of these points needs to be as exact as possible in order to develop a precise interpretation of magnetic anomalies. GPS is a valuable tool for accomplishing this objective, especially if the RTK approach is used. In this paper the VRS (Virtual Reference Station) technique is introduced as a new approach for real-time positioning of magnetic sensors. The main advantages of the VRS approach are, firstly, that only a single GPS receiver is needed (no base station is necessary), reducing field work and equipment costs. Secondly, VRS can operate at distances separated 50-70 km from the reference stations without degrading accuracy. A compact integration of a GSM-19 magnetometer sensor with a geodetic GPS antenna is presented; this integration does not diminish the operational flexibility of the original magnetometer and can work with the VRS approach. The coupled devices were tested in marshlands around Gandia, a city located approximately 100 km South of Valencia (Spain), thought to be the site of a Roman cemetery. The results obtained show adequate geometry and high-precision positioning for the structures to be studied (a comparison with the original low precision GPS of the magnetometer is presented). Finally, the results of the magnetic survey are of great interest for archaeological purposes. [ABSTRACT FROM AUTHOR]

In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is based on the Spectral Mixture Analysis (SMA) technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixel elements, called Endmembers (EMs). These EMs were extracted from the image using three different methods: i) manual extraction using a land cover map, ii) Pixel Purity Index (PPI) and iii) Automated Morphological Endmember Extraction (AMEE). The different methodologies for FVC retrieval were applied to one PROBA/CHRIS image acquired over an agricultural area in Spain, and they were calibrated and tested against in situ measurements of FVC estimated with hemispherical photographs. The results obtained from VIs show that VARI correlates better with FVC than NDVI does, with standard errors of estimation of less than 8% in the case of VARI and less than 13% in the case of NDVI when calibrated using the in situ measurements. The results obtained from the SMA-LSU technique show Root Mean Square Errors (RMSE) below 12% when EMs are extracted from the AMEE method and around 9% when extracted from the PPI method. A RMSE value below 9% was obtained for manual extraction of EMs using a land cover use map. [ABSTRACT FROM AUTHOR]

Live fuel moisture content (LFMC) is an input factor in fire behavior simulation models highly contributing to fire ignition and propagation. Developing models capable of accurately estimating spatio-temporal changes of LFMC in different forest species is needed for wildfire risk assessment. In this paper, an empirical model based on multivariate linear regression was constructed for the forest cover classified as shrublands in the central part of the Valencian region in the Eastern Mediterranean of Spain in the fire season. A sample of 15 non-monospecific shrubland sites was used to obtain a spatial representation of this type of forest cover in that area. A prediction model was created by combining spectral indices and meteorological variables. This study demonstrates that the Normalized Difference Moisture Index (NDMI) extracted from Sentinel-2 images and meteorological variables (mean surface temperature and mean wind speed) are a promising combination to derive cost-effective LFMC estimation models. The relationships between LFMC and spectral indices for all sites improved after using an additive site-specific index based on satellite information, reaching a R2adj = 0.70, RMSE = 8.13%, and MAE = 6.33% when predicting the average of LFMC weighted by the canopy cover fraction of each species of all shrub species present in each sampling plot. [ABSTRACT FROM AUTHOR]

A functional urban area (FUA) is a geographic entity that consists of a densely inhabited city and a less densely populated commuting zone, both highly integrated through labor markets. The delineation of FUAs is important for comparative urban studies and it is commonly performed using census data and data on commuting flows. However, at the national scale, censuses and commuting surveys are performed at low frequency, and, on the global scale, consistent and comparable data are difficult to obtain overall. In this paper, we suggest and test a novel approach based on artificial light at night (ALAN) satellite data to delineate FUAs. As ALAN is emitted by illumination of thoroughfare roads, frequented by commuters, and by buildings surrounding roads, ALAN data can be used, as we hypothesize, for the identification of FUAs. However, as individual FUAs differ by their ALAN emissions, different ALAN thresholds are needed to delineate different FUAs, even those in the same country. To determine such differential thresholds, we use a multi-step approach. First, we analyze the ALAN flux distribution and determine the most frequent ALAN value observed in each FUA. Next, we adjust this value for the FUA's compactness, and run regressions, in which the estimated ALAN threshold is the dependent variable. In these models, we use several readily available, or easy-to-calculate, characteristics of FUA cores, such as latitude, proximity to the nearest major city, population density, and population density gradient, as predictors. At the next step, we use the estimated models to define optimal ALAN thresholds for individual FUAs, and then compare the boundaries of FUAs, estimated by modelling, with commuting-based delineations. To measure the degree of correspondence between the commuting-based and model-predicted FUAs' boundaries, we use the Jaccard index, which compares the size of the intersection with the size of the union of each pair of delineations. We apply the proposed approach to two European countries—France and Spain—which host 82 and 72 FUAs, respectively. As our analysis shows, ALAN thresholds, estimated by modelling, fit FUAs' commuting boundaries with an accuracy of up to 75–100%, being, on the average, higher for large and densely-populated FUAs, than for small, low-density ones. We validate the estimated models by applying them to another European country—Austria—which demonstrates the prediction accuracy of 47–57%, depending on the model type used. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a variable of the climatic system and hydrological cycle that plays an important role in biosphere–atmosphere–hydrosphere interactions. In this paper, remote sensing-based ET estimates with the simplified surface energy balance index (S-SEBI) model using Landsat 8 data were compared with in situ lysimeter measurements for different land covers (Grass, Wheat, Barley, and Vineyard) at the Barrax site, Spain, for the period 2014–2018. Daily estimates produced superior performance than hourly estimates in all the land covers, with an average difference of 12% and 15% for daily and hourly ET estimates, respectively. Grass and Vineyard showed the best performance, with an RMSE of 0.10 mm/h and 0.09 mm/h and 1.11 mm/day and 0.63 mm/day, respectively. Thus, the S-SEBI model is able to retrieve ET from Landsat 8 data with an average RMSE for daily ET of 0.86 mm/day. Some model uncertainties were also analyzed, and we concluded that the overpass of the Landsat missions represents neither the maximum daily ET nor the average daily ET, which contributes to an increase in errors in the estimated ET. However, the S-SEBI model can be used to operationally retrieve ET from agriculture sites with good accuracy and sufficient variation between pixels, thus being a suitable option to be adopted into operational ET remote sensing programs for irrigation scheduling or other purposes. [ABSTRACT FROM AUTHOR]

This paper analyzes the impact of the fall in household consumption after an economic crisis in Spain on greenhouse gas emissions. To this end, household consumption is differentiated by the age of the main provider by using a conversion matrix that relates consumption groups to activity sectors. A multisectoral model was used to quantify and compare the environmental impact caused by the consumption of each age group, indicating that the older the age of the main household provider, the smaller the reduction in GHG emissions associated with their consumption. The results facilitate an analysis of how the greenhouse gas emissions of the different sectors of the Spanish economy, associated with the population under study, varied before and after the 2008 crisis, and confirm that the sectors with the greatest reduction in emissions were, in this order, extractive industries, construction, manufacturing industry, wholesale and retail trade and transport and storage. This is relevant for decision making in the field of environmental policies in crises, akin to the one the world is currently experiencing. [ABSTRACT FROM AUTHOR]

This paper provides an accurate chronology of the Spanish reference business cycle adapting a multiple change-point model. In that approach, each combination of peaks and troughs dated in a set of economic indicators is assumed to be a realization of a mixture of bivariate Gaussian distributions, whose number of components is estimated from the data. The means of each of these components refer to the dates of the reference turning points. The transitions across the components of the mixture are governed by Markov chain that is restricted to force left-to-right transition dynamic. In the empirical application, seven recessions in the period from February 1970 to February 2020 are identified, which are in high concordance with the timing of the turning point dates established by the Spanish Business Cycle Dating Committee (SBCDC). [ABSTRACT FROM AUTHOR]

More than 50% of the world's population lives in cities. Its buildings consume more than a third of the energy and generate 40% of the emissions. This makes cities in general and their buildings in particular priority points of attention for policymakers and utilities. This paper uses population density as a variable to know its influence on energy consumption and emissions produced in buildings. Furthermore, to show its effect more clearly, the influence of the climate was eliminated. The usual energy consumption in buildings is thermal and electrical. The study was carried out at the city level, both per inhabitant and per household. The area actually occupied by the city was considered. The proposed method was applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption per inhabitant and household in buildings. The consumption of thermal energy is elastic, while that of electrical energy is inelastic, varying more than 100% between extreme groups. Regarding CO2 emissions, the higher the population density, the higher the emissions. Emissions of electrical origin barely vary by 2% and are greater than those of thermal origin. In addition, the proportion of emissions of electrical origin, with respect to the total, decreases with increasing population density from 74% to 55%. This research aims to help policymakers and utilities to take the appropriate measures that favor the use of renewable energies and reduce CO2 emissions. [ABSTRACT FROM AUTHOR]

Thermostatic load control systems are widespread in many countries. Since they provide heat for domestic hot water and space heating on a massive scale in the residential sector, the assessment of their energy performance and the effect of different control strategies requires simplified modeling techniques demanding a small number of inputs and low computational resources. Data-driven techniques are envisaged as one of the best options to meet these constraints. This paper presents a novel methodology consisting of the combination of an optimization algorithm, two auto-regressive models and a control loop algorithm able to virtually replicate the control of thermostatically driven systems. This combined strategy includes all the thermostatically controlled modes governed by the set point temperature and enables automatic assessment of the energy consumption impact of multiple scenarios. The required inputs are limited to available historical readings from smart thermostats and external climate data sources. The methodology has been trained and validated with data sets coming from a selection of 11 smart thermostats, connected to gas boilers, placed in several households located in north-eastern Spain. Important conclusions of the research are that these techniques can estimate the temperature decay of households when the space heating is off as well as the energy consumption needed to reach the comfort conditions. The results of the research also show that estimated median energy savings of 18.1% and 36.5% can be achieved if the usual set point temperature schedule is lowered by 1 °C and 2 °C, respectively. [ABSTRACT FROM AUTHOR]

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects. [ABSTRACT FROM AUTHOR]

Seasonality is a widely recognised and accredited phenomenon known to cause an imbalance in tourism activity throughout the year, prompting tourist destinations, both public and private, to consider how best to plan the use of their resources. One way of mitigating the economic imbalances that seasonality can cause is to find strategies for seasonal adjustment, such as travel programmes aimed at the elderly. This paper analyses the seasonality of tourism activity in some EU countries, and in particular in Spain. Different indicators are used to compare the results and carry out a sensitivity analysis. The study then focuses on tourism programmes for the elderly in Spain to see whether this type of programme helps to alleviate the seasonality of tourism activity. To corroborate this, an econometric model is specified and estimated, which enables the scope of these programmes to be compared. [ABSTRACT FROM AUTHOR]

Research on mathematics teachers' knowledge has generally focused more on mathematics concepts than mathematical processes. This paper addresses the latter with a focus on mathematical problem solving (PS). It reports on a study that investigated the pedagogical knowledge for PS of prospective elementary school teachers of mathematics (PTs). Participants were 149 PTs at a university in Spain. They were at the end of their teacher education program. Data sources consisted of a questionnaire on knowledge of learning PS and a questionnaire on knowledge of teaching PS. Findings indicated that the PTs held combination of different levels of knowledge of PS learning and teaching. Many of them demonstrated appropriate knowledge of many characteristics for (1) PS learning consisting of student as a problem-solver, PS as a worthwhile task, non-cognitive factor related to PS, and (2) PS teaching consisting of PS teaching approaches, discourse in PS, intervention during stuck state in PS, PS assessment, and PS resources. However, there were also contradictions and limitations to their knowledge with implications for teacher education. These combination of appropriate and inappropriate knowledge resulted in some conflicts that are related to teaching actions and would limit student' learning of PS. [ABSTRACT FROM AUTHOR]

Longevity risk is a major concern for governments around the world as they have to address social benefits, whether in the form of pensions, healthcare, or caring for dependents and providing long-term care, and so forth, which directly impact countries' budgets. This paper uses a single entropy index to measure this type of risk. This methodology is clearly different from the one traditionally used in the literature, which is nearly entirely based on measuring the evolution of mathematical life expectancy. The authors used the longest-living populations in the world, Japan and Spain, to create a database in order to analyse the virtue of the indicator. The aim was to establish whether the longevity of those populations is accelerating or decelerating, compared by sex, and whether that occurs at the same intensity at different stages of a person's life in each case. If the indicator showed differences in intensity, it would be a benchmark for the insurance and financial industry, providing it with information to market different products. [ABSTRACT FROM AUTHOR]

This paper provides a theoretical framework to explore how the support policies for renewable energies can promote rent-seeking incentives in private firms. We develop a political economy of rent-seeking that considers the link between the regulatory decisions of political agents and the potential scope of socially wasteful pursuits. We argue that systematic public support schemes bring rent-seeking as a perception shared by entrepreneurs that influencing political allocations of resources is an essential and potentially preferable source of private profit than other for-profit economic avenues. As evidence of our claims, the framework is applied to the case of Spain to illustrate the economic effects of support policies on the production and distribution of renewable energy. We find rent-seeking behavior in Spain's renewable energy industry, and precisely that: (i) political regulations have induced market concentration and rent-seeking in renewable energy firms, (ii) these firms have required increasing regulations and premiums to survive, and (iii) energy consumers are forced to pay rent-seeking through increasingly expensive electricity bills. The analysis reveals some challenges and opportunities to drive efficient market-based policies to strengthen entrepreneurial competition and curb rent-seeking behavior. These insights have relevant proposals for the Spanish energy industry in complying with the EU Green Deal through a sustainable transition and comprehensive growth. [ABSTRACT FROM AUTHOR]

Improving the energy performance of existing buildings is one of the main strategies defined by the European Union to reduce global energy costs. Amongst the actions to be carried out in buildings to achieve this objective is working with passive measures adapted to each type of climate. To assist designers in the process of finding appropriate solutions for each building and location, different tools have been developed and since the implementation of building information modeling (BIM), it has been possible to perform an analysis of a building's life cycle from an energy perspective and other types of analysis such as a comfort analysis. In the case of Spain, the first BIM environment tool has been implemented that deals with the global analysis of a building's behavior and serves as an alternative to previous methods characterized by their lack of both flexibility and information offered to designers. This paper evaluates and compares the official Spanish energy performance evaluation tool (Cypetherm) released in 2018 using a case study involving the installation of sunlight control devices as part of a building refurbishment. It is intended to determine how databases and simplifications affect the designer's decision-making. Additionally, the yielded energy results are complemented by a comfort analysis to explore the impact of these improvements from a users' wellbeing viewpoint. At the end of the process the yielded results still confirm that the simulation remains far from reality and that simulation tools can indeed influence the decision-making process. [ABSTRACT FROM AUTHOR]

To study the reasons of the low academic performance of students in Spain, authorities must consider emotional dimensions, such as well-being, which directly affect their learning achievement. Furthermore, it would be interesting to compare Spanish students with students from Finland, which stand out in international rankings. We analyze how to promote students' well-being in Spain as a mechanism to enhance their academic achievement. Using data from PISA 2018, four indicators are used to measure well-being according to variables describing the students' context. By means of econometric techniques, interval multiobjective linear programming problems are formulated for Spain and Finland and solved through a new methodological scheme proposed in this paper, assuring the generation of possibly and necessarily efficient solutions in interval multiobjective linear programming. The purpose is to determine which aspects would allow the best possible well-being to be reached. We found several differences between the students achieving optimal compromise levels in each country, and we analyzed how the improvement of one indicator might affect the remaining aspects of well-being. Spanish students can further enhance their well-being compared to Finnish students. Furthermore, the lowest improvement rate is associated with the bullying index, especially in Finland, highlighting the need to promote anti-bullying measures. [ABSTRACT FROM AUTHOR]

The role of the energy industry has always been central for one reason or another, being environmentalism the main motive in the last two decades. Therefore, attention and research have been directed in this sense. However, human resources—or human capital—have remained understudied, especially concerning the salaries received. Thus, this study is disruptive as it explored the factors that influence employee remuneration in the energy subsector, using Spain as a case study. For this, the PLS-SEM (Partial Least Squares Structural Equation Modelling) path modelling methodology was used, executing a traditional PLS analysis, bootstrapping and, finally, IPMA (Importance-Performance Analysis). Solid and significant relationships were found among labour conditions, human capital, market and wages, with the relationships between human capital and wages and between human capital and labour conditions being especially relevant. Besides, through IPMA, a series of considerations was made regarding the individual indicators according to their relative importance and performance. Consequently, this paper significantly contributes to the extant literature by analysing the composition of wages in the energy sector, which might allow taking valuable management decisions. Nevertheless, the main limitation of this study lies in the availability of data for Spain and, specifically, for workers in the energy supplying industries. [ABSTRACT FROM AUTHOR]

The paper will examine, in detail, (a) the norms that can be featured under the category "Green Deal" connected to the European Commission, (b) their application to Spain, and (c) the different patterns of action and development models that have been shaped by this framework over the last 20 years. These patterns are particularly relevant currently, as the COVID-19 crisis has highlighted the importance of advancing towards new patterns of local sustainability endowed with higher resilience. The notion of cognitive sustainability will be one of the added values to the current reflections on sustainability in general, and energetic sustainability in particular. [ABSTRACT FROM AUTHOR]

Conflicts of Interest The authors declare no conflict of interest. Reference 1 Torra J., Royo-Esnal A., Romano Y., Osuna M.D., León R.G., Recasens J. Amaranthus palmeri a New Invasive Weed in Spain with Herbicide Resistant Biotypes. The authors would like to make the following correction to the published paper [[1]]: Revise the content in Section 2.4 from "All mutations conferring ALS resistance in I A. palmeri i in positions Ser653, Trp574, Pro197, Pro197, Ala122 and Ala122 of CAD and BE domains" to "All mutations conferring ALS resistance in I A. palmeri i in positions Gly654, Ser653, Trp574, Ala205, Pro197 and Ala122 of CAD and BE domains". [Extracted from the article]

Archaeometric studies on mosaics often concentrate only on glass tesserae, while comprehensive studies including both stone and glass tesserae are scarce; however, both types of tesserae can sometimes bring relevant data to elaborate archaeological knowledge on a studied mosaic. In this paper, a representative set of tesserae from a large polychrome Roman mosaic retrieved in Barcelona (NE Spain) is investigated using various methods. Most of the techniques were directly applied on samples prepared as petrographic thin sections (including polarized-light, cathodoluminescence and electron microscopies, and synchrotron through-the-substrate μX-ray diffraction). The results indicate that, from the ten sampled stone tesserae, there are (i) seven limestones, one of them identified as Alveolina limestone (early Eocene) from the southern Pyrenees (ii) two sandstones from Barcelona's Montjuïc hill (Miocene) and, (iii) a Carrara white marble from the Apuan Alps (Italy). The profuse presence of tesserae of both local and imported materials with well-known uses in architecture, epigraphy, and sculpture could imply that tesserae were a by-product of their main use. Two different production technologies were identified for the three sampled glass tesserae. The concurrent use of antimony- and tin-based opacifiers is in agreement with the accepted archaeological chronology of the mosaic (4th century AD). [ABSTRACT FROM AUTHOR]

The installation of wind power technology is growing steadily and the trend can be expected to continue if the objectives proposed by the European Commission are to be achieved. In some countries a considerable percentage of installed wind power capacity is near the end of its useful lifetime. In the case of Spain, the figure is 50% within five years. Over the last 20 years, wind energy technology has evolved considerably and the expected capacity factor has improved, thus increasing annual energy production, and capital expenditure and operational expenditure have decreased substantially. This paper studies the optimal decision under uncertainty between life extension and full repowering for a generic wind farm installed in the Iberian Peninsula when the future hourly electricity prices and the capacity factor evolve stochastically and seasonally. The results show that in economic terms, full repowering is the best option, with a net present value of €702,093 per MW installed, while reblading is the second best option. The methodology can be transferred to other specific wind farms in different electricity markets and can be used to develop national wind energy policy recommendations to achieve projected shares in the electricity mix. [ABSTRACT FROM AUTHOR]

This work presents a full statistical analysis and accurate prediction of low-visibility events due to fog, at the A-8 motor-road in Mondoñedo (Galicia, Spain). The present analysis covers two years of study, considering visibility time series and exogenous variables collected in the zone affected the most by extreme low-visibility events. This paper has then a two-fold objective: first, we carry out a statistical analysis for estimating the fittest probability distributions to the fog event duration, using the Maximum Likelihood method and an alternative method known as the L-moments method. This statistical study allows association of the low-visibility depth with the event duration, showing a clear relationship, which can be modeled with distributions for extremes such as Generalized Extreme Value and Generalized Pareto distributions. Second, we apply a neural network approach, trained by means of the ELM (Extreme Learning Machine) algorithm, to predict the occurrence of low-visibility events due to fog, from atmospheric predictive variables. This study provides a full characterization of fog events at this motor-road, in which orographic fog is predominant, causing important traffic problems during all year. We also show how the ELM approach is able to obtain highly accurate low-visibility events predictions, with a Pearson correlation coefficient of 0.8 , within a half-hour time horizon, enough to initialize some protocols aiming at reducing the impact of these extreme events in the traffic of the A-8 motor road. [ABSTRACT FROM AUTHOR]

Plastic covered greenhouse (PCG) mapping via remote sensing has received a great deal of attention over the past decades. The WorldView-3 (WV3) satellite is a very high resolution (VHR) sensor with eight multispectral bands in the visible and near-infrared (VNIR) spectral range, and eight additional bands in the short-wave infrared (SWIR) region. A few studies have already established the importance of indices based on some of these SWIR bands to detect urban plastic materials and hydrocarbons which are also related to plastics. This paper aims to investigate the capability of WV3 (VNIR and SWIR) for direct PCG detection following an object-based image analysis (OBIA) approach. Three strategies were carried out: (i) using object features only derived from VNIR bands (VNIR); (ii) object features only derived from SWIR bands (SWIR), and (iii) object features derived from both VNIR and SWIR bands (All Features). The results showed that the majority of predictive power was attributed to SWIR indices, especially to the Normalized Difference Plastic Index (NDPI). Overall, accuracy values of 90.85%, 96.79% and 97.38% were attained for VNIR, SWIR and All Features strategies, respectively. The main PCG misclassification problem was related to the agricultural practice of greenhouse whitewash (greenhouse shading) that temporally masked the spectral signature of the plastic film. [ABSTRACT FROM AUTHOR]

This paper deals with the use of aerial photogrammetry and LiDAR techniques to analyze landslide activity over a long time span—just over 32 years. The data correspond to several aerial surveys (1984, 1996, 2001, 2005, 2009, 2010, 2011, 2013 and 2016) covering an area of about 50 km2 along highway A-44, near Jaén (Southern Spain). An ad hoc combined photogrammetric and LiDAR aerial survey of 2010 was established as the reference flight. This flight was processed by means of direct orientation methods and iterative adjustments between both data sets. Meanwhile, historical flights available in public geographical data servers were oriented by transferring ground control points from the reference flight. Then, digital surface models (DSMs) and orthophotographs were generated, as well as the corresponding differential models (DoDs), which, after the application of filters and taking into account the estimated uncertainty of ± 1 m, allowed us to identify true changes on the ground surface. This analysis, complemented by photointerpretation, led us to obtain a landslide multitemporal inventory in the study area that was analyzed in order to characterize the landslide type, morphology and activity. Three basic typologies were identified: rock falls–collapses, slides and flows. These types present different morphometric properties (area, perimeter and height interval) and are associated with different conditions (height, slope, orientation and lithology). Moreover, a set of monitoring areas, common for the different flights, was also used to analyze the activity throughout the study period. Thus, some more active periods were identified (2009–2010, 2010–2011, 2011–2013 and 1996–2001) among other less active ones (1984–1996, 2001–2005, 2005–2009 and 2013–2016), which are related to rainy events and dry years, respectively. [ABSTRACT FROM AUTHOR]

The aim of this paper is the imputation of missing data of COVID-19 hospitalized and intensive care curves in several Spanish regions. Taking into account that the curves of cases, deceases and recovered people are completely observed, a function-on-function regression model is proposed to estimate the missing values of the functional responses associated with hospitalized and intensive care curves. The estimation of the functional coefficient model in terms of principal components' regression with the completely observed data provides a prediction equation for the imputation of the unobserved data for the response. An application with data from the first wave of COVID-19 in Spain is developed after properly homogenizing, registering and smoothing the data in a common interval so that the observed curves become comparable. Finally, Canonical Correlation Analysis is performed on the functional principal components to interpret the relationship between hospital occupancy rate and illness response variables. [ABSTRACT FROM AUTHOR]

This paper draws on the study of the prehistoric art site of Penedo Gordo (NW Spain) resulting from a collaborative interdisciplinary research. One of its primary goals was to design and put into practice a multi-analytical protocol for characterising prehistoric rock paintings, combining in situ and laboratory analytical techniques. Thus, following the archaeological assessment of the site, the panels exhibiting red paintings were analysed by colour spectrophotometry and portable Raman spectroscopy. Analytical techniques were applied to a collection of samples exhumed from the excavation that simultaneously took place on site. These included three red accretions on different substrates (compact soil, white quartzite and grey quartzite) and stone fragments representative of the outcrop's petrographic variability, aiming to determine their mineralogical composition, texture and study the stone-paint boundaries. Moreover, colouring materials exhumed from the excavation and collected in the immediate surroundings of the rock outcrop were analysed in order to scrutinise the provenience rock art's raw materials. Laboratory analysis consisted of stereomicroscopy, X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy. One of the major outcomes was the discovery of a drop of red pigment preserved in an archaeological layer associated with Late Neolithic/Copper Age material remains. [ABSTRACT FROM AUTHOR]