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The article reports on the withdrawal of a research paper related to an analysis of a Spanish lake water pollution from the January 1, 2012 issue of the journal.

Simple Summary: The white mango scale Aulacaspis tubercularis is an invasive pest that causes important damage to mango crops in Southern Spain. The use of integrated management strategies (cultural, biological, and chemical control) is recommended for its effective and sustainable management. Among cultural control measures, fruit bagging technology is being widely used in some mango production regions prior to harvest to protect fruit from diseases, pests, and mechanical damage. However, despite the proven efficacy of bagging, its usefulness has still not been proved to control A. tubercularis infestations on mango fruits. In this study, we evaluated not only the mango bagging efficacy on A. tubercularis control but also its effects on the development and quality of bagged fruits. We tested two commercial types of bags (a yellow satin paper bag and a white muslin cloth bag) commonly used to cover several other fruits. Both bags were effective in reducing the pest incidence and damage caused by A. tubercularis when mango fruits were bagged before the scales migrated to them. Our findings indicate that the use of bags for the pre-harvest protection of mango fruits is feasible, and it may improve their development (weight and size) and quality (color and soluble solids). Aulacaspis tubercularis Newstead (Hemiptera: Diaspididae) is the main pest of mango, Mangifera indica L., in Spain, causing significant economic losses by aesthetic damage that reduce the commercial value of fruit. Bagging fruit with two commercial bags (a yellow satin paper and a white muslin cloth bag) was evaluated for control of A. tubercularis in two organic mango orchards during the 2020 cropping season in pursuit of the development of a mango IPM program to produce pest-free and residue-free fruits. Results from fruit damage evaluations at harvest showed that bagging significantly reduced pest incidence and fruit damage compared with non-bagged plots. Of the two bags evaluated, white muslin cloth bag provided higher levels of fruit protection from A. tubercularis damage, reducing the non-commercial fruit percentage by up to 93.42%. Fruit quality assessment indicated that weight and size of bagged fruit were significantly higher than the non-bagged. Paper-bagged mangoes showed higher whiteness and yellowness compared to the other treatments. Soluble solids content (ºBrix) was higher in paper-bagged fruit than all other treatment plots. The results from this study indicate that pre-harvest fruit bagging is effective at controlling A. tubercularis and should be integrated into an IPM program for Spanish mango production. [ABSTRACT FROM AUTHOR]

The traditional pottery industry was an important activity in Catalonia (NE Spain) up to the 20th century. However, nowadays only few workshops persist in small villages were the activity is promoted as a touristic attraction. The preservation and promotion of traditional pottery in Catalonia is part of an ongoing strategy of tourism diversification that is revitalizing the sector. The production of authenticable local pottery handicrafts aims at attracting cultivated and high-purchasing power tourists. The present paper inspects several approaches to set up a scientific protocol based on the chemical composition of both raw materials and pottery. These could be used to develop a seal of quality and provenance to regulate the sector. Six Catalan villages with a renowned tradition of local pottery production have been selected. The chemical composition of their clays and the corresponding fired products has been obtained by Energy dispersive X-ray fluorescence (EDXRF). Using the obtained geochemical dataset, a number of unsupervised and supervised machine learning methods have been applied to test their applicability to define geochemical fingerprints that could allow inter-site discrimination. The unsupervised approach fails to distinguish samples from different provenances. These methods are only roughly able to divide the different provenances in two large groups defined by their different SiO2 and CaCO3 concentrations. In contrast, almost all the tested supervised methods allow inter-site discrimination with accuracy levels above 80%, and accuracies above 85% were obtained using a meta-model combining all the predictive supervised methods. The obtained results can be taken as encouraging and demonstrative of the potential of the supervised approach as a way to define geochemical fingerprints to track or attest the provenance of samples. [ABSTRACT FROM AUTHOR]

The Galician coast (NW Spain) is a region that is strongly influenced by the presence of low pressure systems in the mid-Atlantic Ocean and the periodic passage of storms that give rise to severe sea states. Since its wave climate is one of the most energetic in Europe, the objectives of this paper were twofold. The first objective was to characterize the most extreme wave height events in Galicia over the wintertime of a two-year period (2015-2016) by using reliable high-frequency radar wave parameters in concert with predictions from a regional wave (WAV) forecasting system running operationally in the Iberia-Biscay-Ireland (IBI) area, denominated IBI-WAV. The second objective was to showcase the application of satellite wave altimetry (in particular, remote-sensed three-hourly wave height estimations) for the daily skill assessment of the IBI-WAV model product. Special attention was focused on monitoring Ophelia-one of the major hurricanes on record in the easternmost Atlantic-during its 3-day track over Ireland and the UK (15-17 October 2017). Overall, the results reveal the significant accuracy of IBI-WAV forecasts and prove that a combined observational and modeling approach can provide a comprehensive characterization of severe wave conditions in coastal areas and shows the benefits from the complementary nature of both systems. [ABSTRACT FROM AUTHOR]

Due to the relevant penetration of solar PV power plants, an accurate power generation forecasting of these installations is crucial to provide both reliability and stability of current grids. At the same time, PV monitoring requirements are more and more demanded by different agents to provide reliable information regarding performances, efficiencies, and possible predictive maintenance tasks. Under this framework, this paper proposes a methodology to evaluate different LoRa-based PV monitoring architectures and node layouts in terms of short-term solar power generation forecasting. A random forest model is proposed as forecasting method, simplifying the forecasting problem especially when the time series exhibits heteroscedasticity, nonstationarity, and multiple seasonal cycles. This approach provides a sensitive analysis of LoRa parameters in terms of node layout, loss of data, spreading factor and short time intervals to evaluate their influence on PV forecasting accuracy. A case example located in the southeast of Spain is included in the paper to evaluate the proposed analysis. This methodology is applicable to other locations, as well as different LoRa configurations, parameters, and networks structures; providing detailed analysis regarding PV monitoring performances and short-term PV generation forecasting discrepancies. [ABSTRACT FROM AUTHOR]

This paper explores the application of spatial models to non-life insurance data focused on the multi-risk home insurance branch. In the pricing modelling and rating process, spatial information should be considered by actuaries and insurance managers because frequencies and claim sizes may vary by region and the premium should be different considering this rating variable. In addition, it is relevant to examine the spatial dependence due to the fact that the frequency of claims in neighbouring regions is often expected to be more closely related than those in regions far from each other. In this paper, a comparison between spatial models, such as spatial autoregressive models (SAR), the spatial error model (SEM), and the spatial Durbin model (SDM), and a non-spatial model has been developed. The data used for this analysis are for a home insurance portfolio located in Spain, from which we have selected peril of water coverage. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the research activities undertaken by La Salle and the Ebro Observatory in the field of remote sensing. On 2003 we started a research project with two main objectives: implement a long-haul oblique ionospheric sounder and transmit the data from remote sensors located at the Spanish Antarctic station Juan Carlos I to Spain. The paper focuses on a study of feasibility of two possible physical layer candidates for the skywave link between both points. A DS-SS based solution and an OFDM based solution are considered to achieve a reliable low-power low-rate communication system between Antarctica and Spain. [ABSTRACT FROM AUTHOR]

Forest and rural fires are one of the main causes of environmental degradation in Mediterranean countries. Existing fire detection systems only focus on detection, but not on the verification of the fire. However, almost all of them are just simulations, and very few implementations can be found. Besides, the systems in the literature lack scalability. In this paper we show all the steps followed to perform the design, research and development of a wireless multisensor network which mixes sensors with IP cameras in a wireless network in order to detect and verify fire in rural and forest areas of Spain. We have studied how many cameras, sensors and access points are needed to cover a rural or forest area, and the scalability of the system. We have developed a multisensor and when it detects a fire, it sends a sensor alarm through the wireless network to a central server. The central server selects the closest wireless cameras to the multisensor, based on a software application, which are rotated to the sensor that raised the alarm, and sends them a message in order to receive real-time images from the zone. The camera lets the fire fighters corroborate the existence of a fire and avoid false alarms. In this paper, we show the test performance given by a test bench formed by four wireless IP cameras in several situations and the energy consumed when they are transmitting. Moreover, we study the energy consumed by each device when the system is set up. The wireless sensor network could be connected to Internet through a gateway and the images of the cameras could be seen from any part of the world. [ABSTRACT FROM AUTHOR]

This paper on Political Economic and Labour Economic Policies in the European Green Deal framework analyses the Recovery Plan and Resilience Facility. It pays attention to the effects on the design of new green jobs and the necessary skills to develop this type of new positions generated, with higher labour wellbeing. The paper is focused on the analysis of the green jobs' opportunity for Europe, at a country level, with a specific analysis made for the Spanish case. A systematisation of the concepts and calculations on the issue is made and analysed (attending the international institutions and forums proposals) to harmonise the recovery plans, apply them beyond the energy sector to other related green activities and align the public and private sector, and other critical stakeholders, in achieving this goal. The following research questions were formulated: (1) what is the estimated number of new green jobs that would be created as a consequence of the implementation of the Recovery Plan in Spain; (2) which new soft skills or re-skilling would be necessary to develop such new green jobs; (3) how much are the new jobs aligned with Wellbeing Economics? The research was conducted by applying a few research methods, i.e., secondary sources, the desk research method and the exploration method, critical and comparative analysis, inductive and deductive reasoning and some mathematical calculations. The research contribution can provide a valuable source of information to coordinate sectoral plans by the policymakers, particularly those responsible for the economy, business, green activities and education. [ABSTRACT FROM AUTHOR]

This paper studies the economically significant problem of the optimization of customs fraud control, which is a critical issue for many countries. The European Union (EU) alone handles 4693 tons of goods every minute (2018 figures). Even though 70% of goods are imported at zero tariff, the EU raised EUR 25.4 billions in 2018, and customs-related income transferred by member states to the EU accounts for nearly 13% of its overall budget. In this field, (a) the conflicting objectives are qualitative and cannot be reduced to a common measure (security and terrorism, health, drug market access control, taxes, etc.); (b) each submitted item has dozens of characteristics; (c) there are constraints; and (d) risk analysis systems have to make decisions in real time. Although the World Customs Organization has promoted the use of artificial intelligence to increase the precision of controls, the problem is very complex due to the data characteristics and interpretability, which is a requirement established by customs officers. In this paper, we propose a new Bayesian-based hybrid approach combining machine learning and multi-objective linear programming (MOLP), called multi-objective Bayesian with dynamic optimization (MOBADO). We demonstrate that it is possible to more than double (with a 237% increase) the precision of current inspection systems, freeing up almost 50% of human resources, and outperform past results with respect to each of the above objectives. MOBADO is an optimization technique that could be combined with any artificial intelligence approach capable of optimizing the quality of multi-objective risk analysis in real time. [ABSTRACT FROM AUTHOR]

Historically, the olive grove has been one of the most emblematic ecosystems in Mediterranean countries. Currently, in Andalusia, Spain, the land under olive grove cultivation exceeds 1.5 million hectares, approximately 17% of the regional surface. Its exploitation has traditionally been based on the use of the available land and heterogeneous plantations, with different species adapted to southern Mediterranean climatic conditions, and to the management of the traditional olive cultivation culture. The objective of this work is to characterize the mechanical behavior of the atmospheric surface boundary layer (SBL) (under neutral stability) interacting with different olive grove configurations. Experimental tests were carried out in the Boundary Layer Wind Tunnel (BLWT) of the Andalusian Institute for Earth System Research (IISTA), University of Granada. Three representative configurations of olive groves under neutral atmospheric conditions were tested. The wind flow time series were recorded at several distances and heights downwind the olive plantation models with a cross hot wire anemometry system. Herein, this paper shows the airflow streamwise, including the mean flow and the turbulent characteristics. The spatial variability of these two mechanical magnitudes depends on, among others, the size, the agro-forest length, the layout of the tree rows, the porosity, the tree height, the crown shape and the surface vegetation cover. The aerodynamic diameter and Reynolds number for each agro-forest management unit are proposed as representative variables of the system response, as these could be related to olive grove management. The plantation, in turn, conforms to a windbreak, which affects the microclimate and benefits the elements of the ecosystem. Detailed knowledge of these variables and the interaction between the ecosystem and the atmosphere is relevant to optimize the resources management, land use and sustainability of the overall crop. Thus, this paper presents preliminary work to relate atmospheric variables to environmental variables, some of which could be humidity, erosion, evapotranspiration or pollen dispersion. [ABSTRACT FROM AUTHOR]

Simple Summary: The aim of this paper is to analyse the heterogeneity and the performance of the value-creating strategies applied by dairy farms in their diversification initiatives. This is a pertinent topic to study because the Common Agricultural Policy provides a role for value-added diversification strategies as an alternative to ensure the economic viability of small farms. Furthermore, the fostering of specialised policy initiatives requires empirical evidence on specific diversification strategies. Nevertheless, there are still few quantitative studies analysing the factors that influence the success of value-added initiatives in terms of their contribution to economic performance, which may be due to the difficulty of obtaining databases such as the one handled in this study. Our findings confirm that the strategies are associated with different combinations of contexts and entrepreneurial capabilities. In fact, the results of this research present practical implications for future entrepreneurs and for policymakers, contributing towards understanding how an adequate alignment between contextual factors and entrepreneurial capabilities can enable the implementation and sustainability of new business initiatives in rural areas. We also conclude that the diversification ventures of dairy farms are an appropriate element for guaranteeing the survival of certain local breeds, making their use profitable. This paper explores different value-creating strategies (VCS) used by dairy farmers engaged in on-farm diversification ventures. In order to explicitly identify the informal strategies followed by 49 farmers in their value-added ventures, we applied a theoretically informed business model framework combining three dimensions: value proposition linked to local food, customer engagement via quality schemes and shorter supply chains, and the key capabilities of the entrepreneur. Using cluster analysis, four different types of VCS were identified and labelled as 'Ecological', 'Single-product', 'Innovative', and 'Traditional'. Whilst we found that these strategies are influenced by contextual factors and the owner's entrepreneurial skills, in general, we did not observe significant differences in performance between them. The results suggest that farmers respond entrepreneurially to sectorial changes adopting those VCS that tend to align with their entrepreneurial capabilities and context, thus enabling them to succeed with any of the strategies pursued. Hence, our work contributes towards clarifying the relationship between VCS, entrepreneurial capabilities, and context. This is important for farmers and policymakers because it reveals the diversity of farm management and the resilience of farm systems. As a result, the potential challenges for Single-product VCS and Traditional VCS are discussed. [ABSTRACT FROM AUTHOR]

Earth Observation (EO) imagery is difficult to find and access for the intermediate user, requiring advanced skills and tools to transform it into useful information. Currently, remote sensing data is increasingly freely and openly available from different satellite platforms. However, the variety of images in terms of different types of sensors, spatial and spectral resolutions generates limitations due to the heterogeneity and complexity of the data, making it difficult to exploit the full potential of satellite imagery. Addressing this issue requires new approaches to organize, manage, and analyse remote-sensing imagery. This paper focuses on the growing trend based on satellite EO and the analysis-ready data (ARD) to integrate two public optical satellite missions: Landsat 8 (L8) and Sentinel 2 (S2). This paper proposes a new way to combine S2 and L8 imagery based on a Local Nested Grid (LNG). The LNG designed plays a key role in the development of new products within the European EO downstream sector, which must incorporate assimilation techniques and interoperability best practices, automatization, systemization, and integrated web-based services that will potentially lead to pre-operational downstream services. The approach was tested in the Duero river basin (78,859 km2) and in the groundwater Mancha Oriental (7279 km2) in the Jucar river basin, Spain. In addition, a viewer based on Geoserver was prepared for visualizing the LNG of S2 and L8, and the Normalized Difference Vegetation Index (NDVI) values in points. Thanks to the LNG presented in this paper, the processing, storage, and publication tasks are optimal for the combined use of images from two different satellite sensors when the relationship between spatial resolutions is an integer (3 in the case of L8 and S2). [ABSTRACT FROM AUTHOR]

Environmental audio monitoring is a huge area of interest for biologists all over the world. This is why some audio monitoring system have been proposed in the literature, which can be classified into two different approaches: acquirement and compression of all audio patterns in order to send them as raw data to a main server; or specific recognition systems based on audio patterns. The first approach presents the drawback of a high amount of information to be stored in a main server. Moreover, this information requires a considerable amount of effort to be analyzed. The second approach has the drawback of its lack of scalability when new patterns need to be detected. To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard. These descriptors demonstrate it to be suitable to be used in the recognition of different patterns, allowing a high scalability. The proposed parameters have been tested to recognize different behaviors of two anuran species that live in Spanish natural parks; the Epidalea calamita and the Alytes obstetricans toads, demonstrating to have a high classification performance. [ABSTRACT FROM AUTHOR]

In this paper, we present Virtual Touch, a toolkit that allows the development of educational activities through a mixed reality environment such that, using various tangible elements, the interconnection of a virtual world with the real world is enabled. The main goal of Virtual Touch is to facilitate the installation, configuration and programming of different types of technologies, abstracting the creator of educational applications from the technical details involving the use of tangible interfaces and virtual worlds. Therefore, it is specially designed to enable teachers to themselves create educational activities for their students in a simple way, taking into account that teachers generally lack advanced knowledge in computer programming and electronics. The toolkit has been used to develop various educational applications that have been tested in two secondary education high schools in Spain. [ABSTRACT FROM AUTHOR]

Recently, the total net assets of mutual funds have increased considerably and turned them into one of the main investment instruments. Despite this increment, every year a considerable number of funds disappear. The main purpose of this paper is to determine if the neural networks can be a valid instrument to detect the survival capacity of a fund, using the traditional variables linked to the literature of disappearance funds: age, size, performance and volatility. This paper also incorporates annualized variation in return and the Sharpe ratio as variables. The data used is a sample of Spanish mutual funds during 2018 and 2019. The results show that the network correctly classifies funds into surviving and non-surviving with a total error of 13%. Moreover, it shows that not all variables are significant to determine the survival capacity of a fund. The results indicate that surviving and non-surviving funds differ in variables related to performance and its variation, volatility and the Sharpe ratio. However, age and size are not significant variables. As a conclusion, the neural network correctly predicts the 87% of survival capacity of mutual funds. Therefore, this methodology can be used to classify this financial instrument according to its survival or disappearance. [ABSTRACT FROM AUTHOR]

This paper intends to analyze the performance of mortars with reactive MgO, as a sustainable alternative to cement. Six different MgOs from Australia, Canada, and Spain were used in the production of mortars as partial substitutes for cement, namely 5%, 10%, 15%, 20%, and 25% (by weight). MgOs with different levels of reactivity were used to analyze its influence on the performance of MgO mortars. In order to evaluate the mechanical performance of these mortars, compressive strength, flexural strength, dynamic modulus of elasticity, and ultrasonic pulse velocity tests were performed. Compressive strength tests showed that the use of 25% reactive MgO can cause a decrease of this property of between 28% and 49%. The use of reactive MgO affected the other mechanical properties less. This paper also intends to analyze the durability performance of mortars with reactive MgO. To that effect, water absorption by capillarity was assessed. In this research, the effect of using MgO on the shrinkage was also analyzed. It was found that shrinkage may decrease by more than a half in some cases. [ABSTRACT FROM AUTHOR]

Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities which result in diverse socio-ecological consequences. In order to predict fire severity, spectral indices derived from remotely sensed images have been used extensively. Such spectral indices are usually used in combination with ground sampling to relate detected radiometric changes to actual fire effects. However, the potential of the tridimensional information captured by Airborne Laser Scanners (ALS) to severity mapping has been less explored. With the objective of addressing this question, in this paper, explanatory variables extracted from ALS point clouds are related to field estimations of the Composite Burn Index collected in four fires located in Aragón (Spain). Logistic regression models were developed and statistically tested and validated to map fire severity with up to 85.5% accuracy. The canopy relief ratio and the percentage of all returns above one meter height were the most significant variables and were therefore used to create a continuous map of severity levels. [ABSTRACT FROM AUTHOR]

Wind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France. [ABSTRACT FROM AUTHOR]

This paper aims at presenting and describing a dimensioning methodology for energy storage systems (ESS), in particular for one based on flywheels, applied for the specific application of reducing power oscillation in a wave energy conversion (WEC) plant. The dimensioning methodology takes into account the efficiency maps of the storage technology as well as the effect of the filtering control techniques. The methodology is applied to the case study of a WEC plant in operation in Spain, using real power generation profiles delivered into the electric grid. The paper firstly describes the calculation procedure of the efficiency maps for the particular technology of flywheels, although it could be extended to other storage technologies. Then, the influence of using future data values in the dimensioning process and the control of the ESS operation is analysed in depth. A moving average filter (MAF) is defined to compensate for power oscillations, studying the difference between considering prediction and not doing so. It is concluded that a filtering control using future values based on a number of samples equivalent to a 4-min time order provides an important reduction in the energy storage requirements for a power generation plant. Finally, and based on the selection of storage modules previously defined, the efficiency maps, and the MAF used for delivering the power into the grid, an optimal operation strategy is suggested for the storage modules, based on a stepped switching technique. The selection of four flywheel energy storage system (FESS) modules achieves a reduction of 50% in power oscillations, covering 85% of the frequency excursions at the grid. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to assess spatial and temporal irrigation performance in urban parks and can assist park manager/operator decisions in irrigation management. First, irrigation needs are estimated by traditional irrigation scheduling and the irrigation zones with similar water needs that share the same electric valve (hydrozones) are identified. Then, irrigation performance is calculated using the relative water supply (RWS) indicator and mapped (GIS software). This approach can be adapted to various spatial and temporal scales. In this study, it was applied to the Valdebebas urban development VBB (Madrid) between the 2017 and 2019 irrigation seasons. The results for the VBB parks showed high spatio-temporal variation in irrigation performance among plant typologies within an irrigation season, which can be explained by the landscape coefficient KL variation across the parks. Likewise, this variation was also observed among the three evaluated seasons; explained among other factors by differences in irrigation management. For each hydrozone, the estimation of the NDVI index by Sentinel-2A satellite images in 2019 showed a threshold on irrigation performance. Thus, the remote sensing data together with the proposed approach can be a valuable tool for helping park managers/technicians adopt better decisions on irrigation practices. [ABSTRACT FROM AUTHOR]

World agriculture is facing a great challenge since it is necessary to find a sustainable way to increase food production. Current trends in advancing the agriculture sector are based on leveraging remote sensing technology and the use of biostimulants. However, the efficient implementation of both of these on a commercial scale for the purposes of productivity improvement remains a challenge. Thus, by proposing a crop monitoring strategy based on remote sensing data, this paper aims to verify and anticipate the impact of applying a Glycinebetaine biostimulant (GB) on the final yield. The study was carried out in a rice-producing area in Eastern Spain (Valencia) in 2021. GB was applied by drone 33 days after sowing (tillering phase). Phenology was monitored and crop production parameters were determined. Regarding satellite data, Sentinel-2 cloud-free images were obtained from sowing to harvest, using the bands at 10 m. Planet data were used to evaluate the results from Sentinel-2. The results show that GB applied 33 days after sowing improves both crop productive parameters and commercial yield (13.06% increase). The design of the proposed monitoring strategy was based on the dynamics and correlations between the visible (green and red) and NIR bands. The analysis showed differences when comparing the GB and control areas, and permitted the determination of the moment in which the effect of GB on yield (tillering and maturity) may be greater. In addition, an index was constructed to verify the crop monitoring strategy, its mathematical expression being: NCMI = (NIR − (red + green))/(NIR + red + green). Compared with the other VIs (NDVI, GNDVI and EVI2), the NCMI presents a greater sensitivity to changes in the green, red and NIR bands, a lower saturation phenomenon than NDVI and a better monitoring of rice phenology and management than GNDVI and EVI2. These results were evaluated with Planet images, obtaining similar results. In conclusion, in this study, we confirm the improvement in rice crop productivity by improving sustainable plant nutrition with the use of biostimulants and by increasing the components that define crop yield (productive tillers, spikelets and grains). Additionally, crop monitoring using remote sensing technology permits the anticipation and understanding of the productive behavior and the evolution of the phenological stages of the crop, in accordance with crop management. [ABSTRACT FROM AUTHOR]

This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent mathematical solution. This methodology is applied to a real case study of the maintenance of large marine engines of vessels dedicated to coastal surveillance in Spain to illustrate its usefulness. It is shown that the use of right-censored failure data significantly decreases the value of the optimal preventive interval calculated by the model. In addition, that optimal preventive interval increases as we consider older failure data. In sum, applying the proposed methodology, the maintenance manager can modify the preventive maintenance interval, obtaining a noticeable economic improvement. The results obtained are relevant, regardless of the number of data considered, provided that data are available with a duration of at least 75% of the value of the preventive interval. [ABSTRACT FROM AUTHOR]

This paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2015 (February to June). The dataset included nine field estimations of agronomic parameters, 20 RADARSAT-2 images, and daily weather records. Ten polarimetric observables were retrieved and integrated to derive the six agronomic and monitoring variables, including the height, biomass, fraction of vegetation cover, leaf area index, water content, and soil moisture. The statistical methods applied, namely double smoothing, ARIMAX, and robust regression, allowed the adjustment and modelling of these field variables. The model equations showed a positive contribution of meteorological variables and a strong temporal component in the crop's development, as occurs in natural conditions. After combining different models, the results showed the best efficiency in terms of forecasting and the influence of several weather variables. The existence of a cointegration relationship between the data series of the same crop in different fields allows for adjusting and predicting the results in other fields with similar crops without re-modelling. [ABSTRACT FROM AUTHOR]

One of the basic assumptions of analytical dimensioning models of asphalt pavements is failure due to fatigue cracking of the bituminous layers. Furthermore, it is considered that the damaging effects of different traffic loads are linear and cumulative, per Miner's law. However, the analysis carried out on the effect of temperature, rest periods, and ageing of the bituminous materials questions considering fatigue failure as the only and main assumption for the calculation of the pavement life. Ageing of the pavement asphalt layers results in stiffening and transverse cracking. Consequently, these asphalt layers are no longer of infinite extent in the horizontal direction and their response resembles that of a slab. The application of this last calculation assumption provides pavement sections more in line with those used in Spain in the Catalogue of Structural Sections, which is based on experience gained from the real behavior of those sections. The calculation based on the fatigue laws results in undersized structures. This paper shows the results of a strain sweep test implemented at the UPC Roads Laboratory, which was used to analyse all the aforementioned effects and to propose a calculation procedure for heavy traffic pavements considering transverse cracking of the asphalt layers. [ABSTRACT FROM AUTHOR]

In this paper, the energy benefits of switchable insulation systems (SIS) are assessed when applied as shades for windows as well as dynamic insulation for exterior walls of residential buildings located in European countries including Belgium and Spain. A series of analyses is performed for detached houses and apartments representing common Belgian residential buildings to determine the energy performance of SIS when deployed to windows and exterior walls and operated using simplified rule-based controls. The analysis results indicate that SIS-integrated windows can achieve significant energy savings for both dwelling types in Belgium, including the elimination of any mechanical cooling and a reduction of up to 44% of heating energy end-use. Moreover, the results show that SIS can offer even more energy efficiency and thermal comfort benefits when deployed to both windows and exterior walls for residential buildings. These energy efficiency benefits are higher, especially for reducing heating needs, for the milder climates of Belgium and Spain. However, it should be noted that the energy performance of SIS could be affected substantially by windows' orientation and occupants' behavior. [ABSTRACT FROM AUTHOR]

In this paper, the use of HVAC systems and non-HVAC control measures to reduce virus-laden bioaerosol exposure in a highly occupied indoor space is investigated. A simulation tool was used to model the fate and transport of bioaerosols in an indoor space in the hotel industry (bar or pub) with three types of HVAC system (central air handling system (CAHS), dedicated outdoor air system (DOAS), and wall unit system (WUS)). Non-HVAC control measures such as portable air cleaners (PAC) and local exhaust fans were considered. Occupant exposure was evaluated for 1 μm bioaerosols, which transport SARS-CoV-2, for 3 h/day of continuous source and exposure. The combined effects of ventilation (400 l/s of outdoor air), recirculated air filtration (90% efficacy), and a PAC with a capacity up to 900 m3/h mitigated the (normalized) integrated exposure of the occupant by 0.66 to 0.51 (CAHS) and 0.43 to 0.36 (DOAS). In the case of WUS, the normalized integrated exposure was reduced by up to 0.2 when the PAC with a capacity of up to 900 m3/h was used. The corresponding electricity consumed increased by 297.4 kWh/year (CAHS) and 482.7 kWh/year (DOAS), while for the WUS it increased by 197.1 kWh/year. [ABSTRACT FROM AUTHOR]

The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community. [ABSTRACT FROM AUTHOR]

(1) Background: Using neuroscience to understand and influence consumer behavior often leads to ethical controversy. Thus, it is necessary to demystify the use of neuroscience for marketing purposes; the present paper, by accessing the worldwide academic performance in this domain, fulfills this objective. (2) Methods: All extant literature on neuromarketing indexed to the Scopus database—318 articles—was subjected to a bibliometric analysis through a mixed-method approach. (3) Results: The results show that Spain leads the ranks of the most productive countries, while Italian researchers clearly dominate in terms of collaboration. Regarding the most prominent topics, the connection between "Neuroscience" and "Advertising" is highlighted. The findings provide a better understanding of the state-of-the-art in neuromarketing studies, research gaps, and emerging research topics, and additionally provide a new methodological contribution by including SciVal topic prominence in the bibliometric analysis. (4) Conclusions: As practical implications, this study provides useful insights for neuromarketing researchers seeking funding opportunities, which are normally associated with topics within the top prominence percentile or emerging topics. In terms of originality, this study is the first to apply SciVal topic prominence to a bibliometric analysis of neuromarketing, and provides a new bibliometric indicator for neuromarketing research. [ABSTRACT FROM AUTHOR]

The analysis of factors influencing urban shrinkage is of great interest to spatial planners and policy makers. Population loss is usually the most relevant indicator of this shrinkage, but many other factors interact in complex ways over time. This paper proposes a multidimensional and spatio-temporal analysis of the shrinkage process in Spanish municipalities between 1991 and 2020. The method is based on the potentiality provided by self-organizing maps. The generated maps group municipalities according to hidden partial correlations among the data behind the variables characterizing the municipalities at different dates. In addition, as the number of map nodes is too big to allow for the detection of distinct types of municipalities, a Ward clustering algorithm is applied to identify homogeneous areas with a higher probability of shrinkage occurring over time. The results indicate that the municipalities with the lowest shrinkage are more stable and have a geographical concentration: they correspond to areas where peripheralization may occur (creation of surrounding districts close to main urban centers) and constitute the hinterland of large functional areas. The results also report a path of decline, with an important increase in the number of municipalities with higher shrinkage values. This approach has important implications for policy making since local governments may profit from shrinkage predictions. [ABSTRACT FROM AUTHOR]

The gender gap in STEM-related job positions is a fact, and it is closely related to the low percentage of women studying STEM degrees. This poses a problem because Europe, as well as the United States and the rest of the developed countries, keep demanding the best engineers and scientists to continue developing innovative products. This problem can thus be approached by answering, firstly, the following question: Why are women not studying STEM degrees? In this paper, we summarize the factors, found in literature, that influence students—both boys and girls—to not study STEM, particularly engineering, computer sciences and technology. We study these influence factors in a sample of N = 338 students from a secondary school placed in the south of Spain; we carry out a survey in order to find out if those students fill out the same answers other researchers have found and published in the related literature. Our main conclusions are as follows: The results confirm that the number of women in technical courses decreases when the level of the course increases; the lack of role models is not an impediment for girls to feel comfortable; unlike boys, girls will not choose engineering, even if their scoring in STEM is good; and we found that girls and women see themselves as not capable of studying an engineering degree more than boys and men do. These results contribute to a deeper understanding of the situation regarding the gender gap in STEM fields in ages in which both girls and boys must choose their future studies. [ABSTRACT FROM AUTHOR]

With the proliferation of unmanned aerial vehicles (UAVs) in different contexts and application areas, efforts are being made to endow these devices with enough intelligence so as to allow them to perform complex tasks with full autonomy. In particular, covering scenarios such as disaster areas may become particularly difficult due to infrastructure shortage in some areas, often impeding a cloud-based analysis of the data in near-real time. Enabling AI techniques at the edge is therefore fundamental so that UAVs themselves can both capture and process information to gain an understanding of their context, and determine the appropriate course of action in an independent manner. Towards this goal, in this paper, we take determined steps towards UAV autonomy in a disaster scenario such as a flood. In particular, we use a dataset of UAV images relative to different floods taking place in Spain, and then use an AI-based approach that relies on three widely used deep neural networks (DNNs) for semantic segmentation of images, to automatically determine the regions more affected by rains (flooded areas). The targeted algorithms are optimized for GPU-based edge computing platforms, so that the classification can be carried out on the UAVs themselves, and only the algorithm output is uploaded to the cloud for real-time tracking of the flooded areas. This way, we are able to reduce dependency on infrastructure, and to reduce network resource consumption, making the overall process greener and more robust to connection disruptions. Experimental results using different types of hardware and different architectures show that it is feasible to perform advanced real-time processing of UAV images using sophisticated DNN-based solutions. [ABSTRACT FROM AUTHOR]

Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the "Mar Menor", the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50,000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier. [ABSTRACT FROM AUTHOR]

This article presents and reviews the soil salinity data provided by a rescued vintage agronomic report on an irrigated area of 35,875 ha located in the center of the Ebro River basin, in the NE of mainland Spain. These data come from a soil sampling campaign conducted from May to the first half of July 1975 for the purpose of delineating saline and non-saline soils. The agronomic report was produced in response to demands from farmers to combat soil salinity, and represents the state of the art in those years for salinity studies. Our paper presents the scrubbed soil salinity data for this year, checking their consistency and locating the study sites. The main finding is the unearthing of this heritage report and the discussion of its soil salinity data. We show that the report supplies an assessment and a baseline for further soil salinity tracking by conducting new measurements either by direct soil sampling or by nondestructive techniques, providing an estimate of soil salinity at different locations. This task is feasible, as shown in our previously published articles involving nearby areas. A comparison of the salt amount in the soil over the years would provide a means to evaluate irrigation methods for sustainable land management. This comparison can be conducted simultaneously with analysis of other agricultural features described in the report for the irrigation district in 1975. [ABSTRACT FROM AUTHOR]

In recent years, there has been growing concern regarding energy efficiency in the building sector with energy requirements increasing worldwide and now responsible for about 40% of final energy consumption in Europe. Previous research has shown that ventilated façades help to reduce energy use when cooling buildings in hot and temperate climates. Of the different ventilated façade configurations reported in the literature, the configuration of ventilated façade with window rarely has been studied, and its 3D thermodynamic behavior is deserving of further analysis and modeling. This paper examines the thermal behavior of an opaque ventilated façade with a window, in experimentally and numerical terms and its impact in energy savings to get indoor comfort. Field measurements were conducted during the winter, spring and summer seasons of 2021 using outdoor full scale test cells located in Seville (southern Spain). The modeling of the ventilated façade was carried out using a three-dimensional approach taking into account the 3D behavior of the air flow in the air cavity due to the presence of the window. The validation and comparison process using experimental data showed that the proposed model provided good results from quantitative and qualitative point of view. The reduction of the heat flux was assessed by comparing the energy performance of a ventilated façade with that of an unventilated façade. Both experimental and numerical results showed that the ventilated façade provided a reduction in annual total energy consumption when compared to the unventilated façade, being compensated the winter energy penalization by the summer energy savings. This reduction is about 21 % for the whole typical climatic year showing the ability of the opaque ventilated façade studied to reduce energy consumption to insure indoor comfort, making its suitable for use in retrofitting the energy-obsolete building stock built in Spain in the middle decades of the 20 century. [ABSTRACT FROM AUTHOR]

In this paper, we addressed the chemical composition and main features of a glazed Almohad ceramic assemblage recovered from Puig de Sa Morisca, a rural Islamic site located in southwest Mallorca. The glazes were analyzed by means of scanning electron microscope equipped with energy-dispersive spectrometer (SEM-EDS). The archaeometrical analysis conducted allowed us to characterize the technological choices applied by potters from the end of the 12th century and the beginning of the 13th century. The exclusive use of lead-silica glazes was confirmed, which in some cases was opacified with tin. We also established that some tableware vessels, which were imported to the island, have shown glazes with a particular composition within the analyzed record. [ABSTRACT FROM AUTHOR]

Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities which result in diverse socio-ecological consequences. In order to predict fire severity, spectral indices derived from remotely sensed images have been used extensively. Such spectral indices are usually used in combination with ground sampling to relate detected radiometric changes to actual fire effects. However, the potential of the tridimensional information captured by Airborne Laser Scanners (ALS) to severity mapping has been less explored. With the objective of addressing this question, in this paper, explanatory variables extracted from ALS point clouds are related to field estimations of the Composite Burn Index collected in four fires located in Aragón (Spain). Logistic regression models were developed and statistically tested and validated to map fire severity with up to 85.5% accuracy. The canopy relief ratio and the percentage of all returns above one meter height were the most significant variables and were therefore used to create a continuous map of severity levels. [ABSTRACT FROM AUTHOR]

The goal of the research is to assess the minimum requirement of fast charging infrastructure to allow country-wide interurban electric vehicle (EV) mobility. Charging times comparable to fueling times in conventional internal combustion vehicles are nowadays feasible, given the current availability of fast charging technologies. The main contribution of this paper is the analysis of the planning method and the investment requirements for the necessary infrastructure, including the definition of the Maximum Distance between Fast Charge (MDFC) and the Basic Highway Charging Infrastructure (BHCI) concepts. According to the calculations, distance between stations will be region-dependent, influenced primarily by weather conditions. The study considers that the initial investment should be sufficient to promote the EV adoption, proposing an initial state-financed public infrastructure and, once the adoption rate for EVs increases, additional infrastructure will be likely developed through private investment. The Spanish network of state highways is used as a case study to demonstrate the methodology and calculate the investment required. Further, the results are discussed and quantitatively compared to other incentives and policies supporting EV technology adoption in the light-vehicle sector. [ABSTRACT FROM AUTHOR]

In this paper a methodology is proposed to elaborate landslide activity maps through the use of PS (Persistent Scatterer) data. This is illustrated through the case study of Tramuntana Range in the island of Majorca (Spain), where ALOS (Advanced Land Observing Satellite) images have been processed through a Persistent Scatterer Interferometry (PSI) technique during the period of 2007-2010. The landslide activity map provides, for every monitored landslide, an assessment of the PS visibility according to the relief, land use, and satellite acquisition parameters. Landslide displacement measurements are projected along the steepest slope, in order to compare landslide velocities with different slope orientations. Additionally, a ground motion activity map is also generated, based on active PS clusters not included within any known landslide phenomenon, but even moving, potentially referred to unmapped landslides or triggered by other kinds of geomorphological processes. In the Tramuntana range, 42 landslides were identified as active, four as being potential to produce moderate damage, intersecting the road Ma-10, which represents the most important road of the island and, thus, the main element at risk. In order to attest the reliability of measured displacements to represent landslide dynamics, a confidence degree evaluation is proposed. In this test site, seven landslides exhibit a high confidence degree, medium for 93 of them, and low for 51. A low confidence degree was also attributed to 615 detected active clusters with a potential to cause moderate damage, as their mechanism of the triggering cause is unknown. From this total amount, 18 of them intersect the Ma-10, representing further potentially hazardous areas. The outcomes of this work reveal the usefulness of landslide activity maps for environmental planning activities, being exportable to other radar data and different geomorphological settings. [ABSTRACT FROM AUTHOR]

Developing a regional power system to achieve a high level of integration of national systems requires sufficient development of the regional transmission grid. This is possible only with appropriate schemes for the complete cost–benefit analyses, and cost allocation of these transmission investments, which plays a critical role in the selection of the most efficient network investment and the proper assignment of their cost to the national systems. Network reinforcements affect the operation of power systems and, therefore, the externalities of power generation. This paper examines the impacts of integrating local air pollution damage from power production within the benefit assessment and cost allocation of transmission investments. The paper describes the methodology followed and illustrates its application in a real-life case study where a simplified version of a European network is considered. Within this case study, we have assessed the impact of considering the reduction in air pollution damage achieved through a particular HVDC project between France and Spain on the benefits, and benefit-driven cost allocation, computed for this project. In this case study, local pollution related benefits are a relevant fraction of the overall benefits of the considered transmission project. However, considering the local air pollution benefits of the project does not affect the net positive benefits of each country significantly, resulting in a limited change in the cost allocation of the project. [ABSTRACT FROM AUTHOR]

The development of Short-Term Forecasting Techniques has a great importance for power system scheduling and managing. Therefore, many recent research papers have dealt with the proposal of new forecasting models searching for higher efficiency and accuracy. Several kinds of artificial intelligence (AI) techniques have provided good performance at predicting and their efficiency mainly depends on the characteristics of the time series data under study. Load forecasting has been widely studied in recent decades and models providing mean absolute percentage errors (MAPEs) below 5% have been proposed. On the other hand, short-term generation forecasting models for photovoltaic plants have been more recently developed and the MAPEs are in general still far from those achieved from load forecasting models. The aim of this paper is to propose a methodology that could help power systems or aggregators to make up for the lack of accuracy of the current forecasting methods when predicting renewable energy generation. The proposed methodology is carried out in three consecutive steps: (1) short-term forecasting of energy consumption and renewable generation; (2) classification of daily pattern for the renewable generation data using Dynamic Time Warping; (3) application of Demand Response strategies using Physically Based Load Models. Real data from a small town in Spain were used to illustrate the performance and efficiency of the proposed procedure. [ABSTRACT FROM AUTHOR]

Solar maps are becoming a popular resource and are available via the web to help plan investments for the benefits of renewable energy. These maps are especially useful when the results have high accuracy. LiDAR technology currently offers high-resolution data sources that are very suitable for obtaining an urban 3D geometry with high precision. Three-dimensional visualization also offers a more accurate and intuitive perspective of reality than 2D maps. This paper presents a new method for the calculation and visualization of the solar potential of building roofs on an urban 3D model, based on LiDAR data. The paper describes the proposed methodology to (1) calculate the solar potential, (2) generate an urban 3D model, (3) semantize the urban 3D model with different existing and calculated data, and (4) visualize the urban 3D model in a 3D web environment. The urban 3D model is based on the CityGML standard, which offers the ability to consistently combine geometry and semantics and enable the integration of different levels (building and city) in a continuous model. The paper presents the workflow and results of application to the city of Vitoria-Gasteiz in Spain. This paper also shows the potential use of LiDAR data in different domains that can be connected using different technologies and different scales. [ABSTRACT FROM AUTHOR]

The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis. Integrated nested Laplace approximations (INLA) with stochastic partial differential equation (SPDE) methodology is a possible approach that allows the inclusion of covariates in an easy way. The current study has been conducted using INLA-SPDE to study soil moisture in the area of the Valencia Anchor Station (VAS), soil moisture validation site for the European Space Agency SMOS (Soil Moisture and Ocean Salinity). The data used were collected in a typical ecosystem of the semiarid Mediterranean conditions, subdivided into physio-hydrological units (SMOS units) which presents a certain degree of internal uniformity with respect to hydrological parameters and capture the spatial and temporal variation of soil moisture at the local fine scale. The paper advances the knowledge of the influence of hydrodynamic properties on VAS soil moisture (texture, porosity/bulk density and soil organic matter and land use). With the goal of understanding the factors that affect the variability of soil moisture in the SMOS pixel (50 km × 50 km), five states of soil moisture are proposed. We observed that the model with all covariates and spatial effect has the lowest DIC value. In addition, the correlation coefficient was close to 1 for the relationship between observed and predicted values. The methodology applied presents the possibility to analyze the significance of different covariates having spatial and temporal effects. This process is substantially faster and more effective than traditional kriging. The findings of this study demonstrate an advancement in that framework, demonstrating that it is faster than previous methodologies, provides significance of individual covariates, is reproducible, and is easy to compare with models. [ABSTRACT FROM AUTHOR]

Linking pensions to longevity developments at retirement age has been one of the most common policy responses of pension schemes to aging populations. The introduction of automatic stabilizers is primarily motivated by cost containment objectives, but there are other dimensions of welfare restructuring in the politics of pension reforms, including recalibration, rationalization, and blame avoidance for unpopular policies that involve retrenchments. This paper examines the policy designs and implications of linking entry pensions to life expectancy developments through sustainability factors or life expectancy coefficients in Finland, Portugal, and Spain. To address conceptual and specification uncertainty in policymaking, we propose and apply a Bayesian model averaging approach to stochastic mortality modeling and life expectancy computation. The results show that: (i) sustainability factors will generate substantial pension entitlement reductions in the three countries analyzed; (ii) the magnitude of the pension losses depends on the factor design; (iii) to offset pension cuts and safeguard pension adequacy, individuals will have to prolong their working lives significantly; (iv) factor designs considering cohort longevity markers would have generated higher pension cuts in countries with increasing life expectancy gap. [ABSTRACT FROM AUTHOR]

This paper assesses the health impact, in terms of the reduction of premature deaths associated with changes in air pollutant exposure, resulting from double-aim strategies for reducing emissions of greenhouse gases and air pollutants from the transport sector for the year 2030 in Spain. The impact on air quality of selected measures for reducing emissions from the transport sector (increased penetration of biofuel and electric car use) was assessed by air quality modeling. The estimation of population exposure to NO2, particulate matter (PM) and O3 allows for estimation of associated mortality and external costs in comparison with the baseline scenario with no measures. The results show that the penetration of the electric vehicle provided the largest benefits, even when the emissions due to the additional electricity demand were considered. [ABSTRACT FROM AUTHOR]

Beekeeping is an ancient activity that is gaining interest among practitioners and society in general. It is as an activity with positive impacts in the environmental, social and economic spheres, with the potential to reconnect these dimensions and contribute to sustainable development. Thus, it is important to determine the profiles of beekeepers across the world, and to understand the main social, economic or ecological drivers that shape their activities. Hofstede cross-cultural dimensions were used to better explain differences between countries. A survey was undertaken of beekeepers in different countries (Croatia, Estonia, Finland, Italy, Norway, Portugal, and Spain) in the native language of each nation. A total of 313 questionnaires, using an online platform or in paper form, was delivered face-to-face during training or dissemination events in 2019. Norway and Finland were the countries with the highest percentage of respondents with a university degree (>80%), while Spain (42%) and Croatia (48%) presented the lowest percentages. Most participants were experienced beekeepers (59% had more than five years of experience) with more than 50 colonies. With the exception of Italy, beekeeping appears to be a hobby or an additional professional activity. The main beekeeping products for these beekeepers were honey, wax, colonies and propolis, with an average honey production per season of 24.5 kg/hive. Crossing socio-demographic characteristics and Hofstede cross-cultural dimensions showed a relation among countries with higher Power Distance Index (PDI; this value expresses how society accepts and expects a certain inequality of power) and lower annual income and educational level (Croatia, Portugal, and Spain). A strong correlation appeared between Masculinity Femininity Index (MFI; this value refers to gender effects in society, with feminine societies meaning that the dominant values are caring for others and quality of life, as opposed to masculine societies, which are driven by competition, achievement and success) and age, income and education, with Norway presenting the most feminine society, with more educated and older beekeepers. The Uncertainty Aversion Index (UAI; this value explains how members of a society feel when dealing with unknown situations) was strongly associated with education. The results showed that increasing beekeepers' income will contribute to balancing the distribution of power among members of society, and that this might be achieved by training, especially in Croatia, Portugal, Spain, and Italy. [ABSTRACT FROM AUTHOR]

This paper analyses surface ozone measurements at five stations in an urban area (Valladolid) in the upper Spanish plateau over the period 2002–2020. Temporal evolutions, the relationship between ozone and other pollutants such as nitrogen oxides, and the assessment of the ozone concentration trend during the study period were analysed. Daily evolution of ozone at all the stations showed mean maximum concentrations in the afternoon, 15:00 GMT, with values ranging between 73.8 and 80.9 µg m−3, evidencing the influence of photochemical processes favoured by solar radiation in ozone formation. The lowest levels were recorded at night and in the early morning, 7:00 GMT, and were between 23.4 and 32.3 µg m−3, related with the reduction by NO reactions and deposition processes. A broad spring–summer peak between May and July was seen, with the highest values in the latter, with a mean value of up to 73.8 µg m−3. The variation in the monthly mean ozone concentrations of the different percentiles was analysed using a harmonic model. The empirical equation described the experimental values satisfactorily, with a confidence level of 95% and coefficients of determination above 80%, confirming the major decreasing trend in the ozone peak values over the study period. [ABSTRACT FROM AUTHOR]

Non-cooperative scheduling games can be used to coordinate residential loads in order to achieve a common goal while accounting for individual consumer's interests, privacy, and autonomy. However, a significant portion of the residential flexibility—Thermostatically Controlled Loads (TCLs) such as water and space heating/cooling appliances—has not been fully addressed under this game theoretic approach: their comfort constraints and integer control were not considered. This paper presents a method for properly including TCLs in this framework and discusses its application in energy communities. Specifically, we propose a general mathematical formulation for considering users' comfort in non-cooperative games. We model the integer nature of the TCLs control with binary variables and show that optimal or close to optimal (less than 1%) solutions are reached. Moreover, different total cost functions can be used depending on the market context and the objective of the demand management program. To illustrate and discuss these aspects in practical applications, we used a case study of an energy community in Spain. The results show that the TC solutions are optimal or only 0.80% worse than optimal; different total cost functions result in different results (load curve smoothing or peak load reduction); consumers' comfort is respected; and the proposed game model cooperates with consumers in order to minimize community's costs. [ABSTRACT FROM AUTHOR]

Pig slurry is considered a high-risk effluent that causes several environmental problems if it is not adequately managed and treated. White Iberian pig farms in the southeast of Spain treat their slurry in situ using separation, double filtration, decantation, and constructed wetland treatments. However, the pretreatment process does not successfully reduce solids, which leads to clogging in the constructed wetlands (CWs). The main objective of this research paper is to reduce the turbidity and chemical oxygen demand (COD) from the effluent to make it appropriate for CW treatment. Optimization of the coagulation–flocculation (CF) process using iron chloride and a cationic flocculent DKFLOCC-1598 was investigated by a central composite design method (CCD). The effects of coagulant concentration, pH, and flocculent on the COD and turbidity removal were evaluated. The best results were found using 0.024 mol L−1 iron chloride and 0.164 mL L−1 flocculent at pH 7.5, which reduced COD by 96% and delivered turbidity removal of 97%. Therefore, the results indicate the high efficiency of the treatment method in reducing the COD and suspended solids. [ABSTRACT FROM AUTHOR]

Simple Summary: Goats are important species due to their contributions to the development of rural areas. Spain has one of the largest goat populations in Europe; however, literature on goat carcasses is very scarce and, therefore, it is crucial to study the specific productive potential of each breed. Previous studies by our team on other Spanish goat breeds have shown some interactions between breed and rearing systems and, consequently, further analysis is necessary. This paper aims to contribute to the general knowledge on the subject. Since goat milk has a higher value than kid meat in Europe, some farmers rear kids with milk replacers, although some studies have stated that kids raised on natural milk yield higher-quality carcasses. Our previous studies showed some interactions between breed and rearing system on carcass and meat quality. This study evaluated the influence of the use of milk replacers on several carcass characteristics of suckling kids from eight Spanish goat breeds (Florida, Cabra del Guadarrama, Majorera, Palmera, Payoya, Retinta, Tinerfeña, and Verata). A total of 246 kids fed milk replacer (MR) or natural milk (NM) were evaluated. Carcass, head, viscera, and kidney fat weights, as well as several carcass measurements (round perimeter, forelimb width, carcass length, forelimb length, and carcass compactness index), were registered. Forelimbs were dissected to study tissue composition. For all studied variables, interactions were found between rearing system and breed. In general, the MR rearing system increased the head and visceral weights, as well as the length measurements and muscle percentages. Conversely, the NM rearing system increased carcass compactness and resulted in higher fat contents, independent of the deposit. The choice of one or another rearing system should be made according to the needs of the target market. [ABSTRACT FROM AUTHOR]