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Purpose: The Comprehensive assessment of Acceptance and Commitment Therapy (CompACT) is a 23-item questionnaire measuring psychological flexibility, a quality of life protective factor. An 18-item version was recently produced. We assessed validity and reliability of CompACT, and equivalence of paper and electronic (eCompACT) versions in people with multiple sclerosis (PwMS) in Italy, Germany and Spain. Methods: We used confirmatory factor analysis and assessed CompACT-23 and CompACT-18 measurement invariance between the three language versions. We assessed construct validity (Spearman's correlations) and internal consistency (Cronbach's alpha). Test–retest reliability (intraclass correlation coefficient, ICC) and equivalence of paper and eCompACT (ICC and linear regression model for repeated measures) were assessed in subsamples of PwMS. Results: A total of 725 PwMS completed the study. The three-factor structure of the CompACT-23 showed poor fit (RMSEA 0.07; CFI 0.82; SRMR 0.08), while the fit of the CompACT-18 was good (RMSEA 0.05; CFI 0.93; SRMR 0.05). Configural and partial metric invariance were confirmed, as well as partial scalar invariance (reached when five items were allowed to vary freely). The CompACT-18 showed good internal consistency (all alpha ≥ 0.78); and test–retest reliability (all ICCs ≥ 0.86). Equivalence between paper and eCompACT was excellent (all ICCs ≥ 0.86), with no mode, order, or interaction effects. Conclusion: Results support using the refined CompACT-18 as a three-factor measure of psychological flexibility in PwMS. Paper and eCompACT-18 versions are equivalent. CompACT-18 can be used cross-culturally, but sub-optimal scalar invariance suggests that direct comparison between the three language versions should be interpreted with caution. [ABSTRACT FROM AUTHOR]

This paper addresses the study of a pillow lava interbedded with Late Albian-Early Cenomanian sediments that crops out in Armintza (Bizkaia, Northern Spain). The lava flow is an alkaline basalt with abundant macrocrysts of clinopyroxene, kaersutite, Ca-rich plagioclase (50-86% An) and ilmenite, which display a variety of textures and complex zoning patterns indicative of open-system magmatic behaviour. Macrocryst cores are likely to be inherited antecrysts that underwent complex processes under deep pre-eruptive conditions (≈ 700-800 MPa). Microcrysts and macrocryst rims formed during magmatic ascent and emplacement at shallower levels (≈ 35 MPa). Hypothetical melts in equilibrium with clinopyroxenes and amphiboles have trace element compositions like metasomatic vein melts containing amphibole, and their patterns overlap with those of the Armintza pillow lava. This suggests a metasomatised lithospheric mantle with amphibole-rich veins as a potential source for the alkaline basaltic melt. It is even conceivable that the Armintza pillow lava and other alkaline volcanic manifestations of the Basque-Cantabrian Basin were part of the same magma plumbing system through which a series of time-limited eruptions of different batches of magma ascended from the lithospheric mantle to the upper crust during the Albian to the Santonian. [ABSTRACT FROM AUTHOR]

This paper offers an analysis of a group of glazed ceramics that comes from El Tolmo de Minateda site and have been dated in the second half of the ninth century and beginning of the tenth century, before the proclamation of the Umayyad Caliphate by Abderraman III (929 CE). Three technological groups have been distinguished: transparent glazes of one or two colours, transparent polychrome glazes (represented by two pieces) and opaque polychrome glazes (represented by two ceramics) studied by SEM-EDS analysis. After the study, different al-Andalus glaze workshops have been identified as providers of glazed ware to El Tolmo de Minateda site. The initial hypothesis was that the ware consumed in El Tolmo was manufactured in Pechina, the closest early production centre. However, after the archaeometric analysis, it has been discarded, and all the indications of this study seem to point to Córdoba as a significant supplier. The data of this study provides a new perspective on how the internal regional distribution and marketing of goods took place in Al-Andalus during the late Emiral period (c. 875–929 CE), a subject that has yet to be explored. [ABSTRACT FROM AUTHOR]

Background: Shortages of mechanical ventilation have become a constant problem in Emergency Departments (EDs), thereby affecting the timely deployment of medical interventions that counteract the severe health complications experienced during respiratory disease seasons. It is then necessary to count on agile and robust methodological approaches predicting the expected demand loads to EDs while supporting the timely allocation of ventilators. In this paper, we propose an integration of Artificial Intelligence (AI) and Discrete-event Simulation (DES) to design effective interventions ensuring the high availability of ventilators for patients needing these devices. Methods: First, we applied Random Forest (RF) to estimate the mechanical ventilation probability of respiratory-affected patients entering the emergency wards. Second, we introduced the RF predictions into a DES model to diagnose the response of EDs in terms of mechanical ventilator availability. Lately, we pretested two different interventions suggested by decision-makers to address the scarcity of this resource. A case study in a European hospital group was used to validate the proposed methodology. Results: The number of patients in the training cohort was 734, while the test group comprised 315. The sensitivity of the AI model was 93.08% (95% confidence interval, [88.46 − 96.26%]), whilst the specificity was 85.45% [77.45 − 91.45%]. On the other hand, the positive and negative predictive values were 91.62% (86.75 − 95.13%) and 87.85% (80.12 − 93.36%). Also, the Receiver Operator Characteristic (ROC) curve plot was 95.00% (89.25 − 100%). Finally, the median waiting time for mechanical ventilation was decreased by 17.48% after implementing a new resource capacity strategy. Conclusions: Combining AI and DES helps healthcare decision-makers to elucidate interventions shortening the waiting times for mechanical ventilators in EDs during respiratory disease epidemics and pandemics. [ABSTRACT FROM AUTHOR]

The paper explores the use of case law by Spanish administrative courts. Based on a database of 2964 sentences, a content analysis captures the integration of case law into the legal basis of court rulings. Even though case law is not listed as a source of law in the Spanish legal system, courts follow case law from either the same sentencing court (self-referential pattern) or higher courts (hierarchical pattern). The results of a logistic regression analysis point to a higher level of regulatory complexity and the configuration of the appellate procedures as incentives to integrate higher courts' case law. [ABSTRACT FROM AUTHOR]

This paper presents the results of a survey conducted among people walking the pilgrimage route to the shrine of St James in Santiago de Compostela. The aim of the research was to investigate how a pilgrimage on the Camino de Santiago among a married couple or family affects marital or familial relationships, whether walking the trail to Compostela together influences the behaviour of family members towards each other and whether it forms positive attitudes and behaviour. The empirical basis of the study is the results of a survey among respondents who made the Camino de Santiago pilgrimage, as well as in-depth interviews conducted with 24 spouses of pilgrims along the Way of St James. The study revealed that doing the pilgrimage as a married couple or family had a positive impact on intra-family relationships. According to the interviewees, going on the pilgrimage together helped to strengthen marital bonds and trust, improve communication and mutual connection, show care and affection and improve contact with children. [ABSTRACT FROM AUTHOR]

The global energy price crisis that started in 2021—then exacerbated by the Russian invasion of Ukraine in March 2022—has caused unprecedented increases in electricity and gas bills. To contrast this rise, EU Member States implemented several 'emergency measures' protecting energy consumers. This paper theoretically estimates the 2022 burden of energy bills on Spanish households, with a particular focus on vulnerable ones. This assessment is carried out by simulating alternative scenarios to evaluate the consequences of the energy prices rise and the effect of the national emergency measures implemented to counteract the energy crisis impact. A disproportionate expenditure indicator is also applied to the vulnerable consumer group that benefitted from the social tariffs to provide a first proxy of the 2022 energy poverty situation in Spain. The results show that these policies significantly reduced regulated market consumers' bills, the vulnerable ones being the most protected by them. However, the high energy burden estimated for the latter category of customers reflects the insufficient 'energy efficiency preparation' of these households to react to energy price shocks. The insights of this assessment might eventually advise policymakers on future decisions during emergency scenarios. [ABSTRACT FROM AUTHOR]

A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specific case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one of the most likely to be affected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the different processes at play in such a complex situation, and also in other different circumstances. [ABSTRACT FROM AUTHOR]

This paper offers some reflections on the effectiveness of the insolvency law measures adopted in Spain during the Covid crisis and on the provision of public funding during this crisis and the repayment of the corresponding claims. The analysis shows that the insolvency measures were inherently ill-suited for achieving the policy goal of preserving businesses, and that there was a good case for the provision of public funding. However, in the Spanish case this funding came too late, and there are now significant challenges associated with restructuring these funds where they were extended by way of loan or guarantee rather than as grant. With regard to the recovery of these funds, the paper concludes that there are no good reasons to insulate the State from the restructuring of debtors' liabilities in the context of a crisis with the characteristics of the pandemic crisis. On the contrary, credit risk should also be transferred to the State—as to other creditors—, and the State will then have to assume the role of loss absorber of last resort. [ABSTRACT FROM AUTHOR]

This paper explores the nature and extent of conflict in Late Neolithic Europe based on expanded skeletal evidence for violence from the San Juan ante Portam Latinam rockshelter in present-day Spain (ca. 3380–3000 cal. BC). The systematic osteological re-examination has identified 65 unhealed and 89 healed traumas—of which 77 were previously undocumented—consistent with aggression. They affect 23.1% of the 338 individuals represented. Adolescent and adult males are particularly affected (44.9% of the 107 identified), comprising 97.6% of unhealed trauma and 81.7% of healed trauma recorded in individuals whose sex could be estimated and showing higher frequencies of injuries per individual than other demographic subgroups. Results suggest that many individuals, essentially men, were exposed to violence and eventually killed in battle and raids, since warriorship is mainly restricted to this demographic in many societies. The proportion of casualties is likely to have been far greater than indicated by the 10.1% individuals exhibiting unhealed trauma, given the presence of isolated cases of unhealed postcranial trauma and of arrowheads potentially having impacted into soft tissues. This, together with skeletal indicators of poor health and the possible socioeconomic outcomes evidenced in the region, suggest wider social impacts, which may relate to a more sophisticated and formalized way of warfare than previously appreciated in the European Neolithic record. [ABSTRACT FROM AUTHOR]

This paper explores the nature and extent of conflict in Late Neolithic Europe based on expanded skeletal evidence for violence from the San Juan ante Portam Latinam rockshelter in present-day Spain (ca. 3380–3000 cal. BC). The systematic osteological re-examination has identified 65 unhealed and 89 healed traumas—of which 77 were previously undocumented—consistent with aggression. They affect 23.1% of the 338 individuals represented. Adolescent and adult males are particularly affected (44.9% of the 107 identified), comprising 97.6% of unhealed trauma and 81.7% of healed trauma recorded in individuals whose sex could be estimated and showing higher frequencies of injuries per individual than other demographic subgroups. Results suggest that many individuals, essentially men, were exposed to violence and eventually killed in battle and raids, since warriorship is mainly restricted to this demographic in many societies. The proportion of casualties is likely to have been far greater than indicated by the 10.1% individuals exhibiting unhealed trauma, given the presence of isolated cases of unhealed postcranial trauma and of arrowheads potentially having impacted into soft tissues. This, together with skeletal indicators of poor health and the possible socioeconomic outcomes evidenced in the region, suggest wider social impacts, which may relate to a more sophisticated and formalized way of warfare than previously appreciated in the European Neolithic record. [ABSTRACT FROM AUTHOR]

This paper presents a long-term analysis of ambient PM10 concentrations measured at a background station in Spain, using backward trajectories generated with the HYSPLIT model, together with the identification of synoptic patterns and a fuzzy clustering analysis, to identify the sources present and evaluate their relationship with meteorological variables such as wind speed and direction, temperature, and atmospheric pressure. Ambient PM10 presented maximum values during the summer with mean concentrations of approximately 14 µg m−3 for August, and minimum values during the winter with concentrations of 6 µg m−3 for January. The daily cycle presented two peaks—one in the morning and another in the afternoon—with this variability being associated with transport emissions. African air masses reached the study site extending vertically at least up to 2500 m.a.g.l, with a frequency of 43.5%, and are associated to a mean ground PM10 concentration of 41.3 µg m−3. During the episodes of Saharan intrusions, high pressures with unclassified synoptic patterns (U) prevailed over the Iberian Peninsula. Local, European, maritime and intermittent contributions were the four main sources of pollutants identified through fuzzy clustering analysis. These intermittent contributions are associated with Saharan dust intrusions, with a long-term average PM10 concentration of 1.7 µg m−3, which represents an important contribution of 11.2%. These sources affect seasonal variations of PM10 background concentrations, and reach their maximum when the greatest contributions of desert dust occur—mainly during the spring–summer months. These results provide useful information for future comparisons and environmental monitoring of PM10 levels. [ABSTRACT FROM AUTHOR]

Understanding the future patterns of precipitation behaviour in unique geographical areas, largely determined by their orography and local scale, can help lay the foundations for a new precipitation model for the design of the city's main urban drainage infrastructures (intensity-duration-frequency curves, mathematical functions that relate precipitation intensity to duration and frequency of occurrence, hereafter IDF, for the short-, medium- and long-term future). This will definitely contribute to the improvement of the city's resilience to the effects of climate change. In this paper, the projections of a subset of climate change models from both the sixth phase of the Coupled Model Intercomparison Project (CMIP6; with a total of 5 simulations) and Euro-CORDEX (for a set of 51 simulations) have been adjusted to the municipality of Alicante (in the southeast of Spain), using the Climadjust tool (climadjust.com). These projections contain different climatic variables. The rainfall variable has been used to derive a new framework of boundary conditions to help design more resilient infrastructure for torrential rainfall events and urban flooding. The projections corresponding to three climate change scenarios (CMIP6: SSP1-2.6, SSP2-4.5, SSP5-8.5; and Euro-CORDEX: RCP2.6, RCP4.5, RCP8.5) are considered with daily resolution and, by applying statistical techniques of temporal disaggregation (by means of a cascade model), hourly (and sub-hourly, reaching 30-min resolution) disaggregation. The results at hourly and 30-min resolutions are used to construct IDF curves of future climate, grouped into short-term (years 2015 to 2040), medium-term (years 2041 to 2070) and long-term (years 2071 to 2100) sub-scenarios. The selected future climate IDFs for an adverse climate change scenario (SSP2-4.5 and SSP5-8.5) show increases in rainfall intensities, higher the shorter the rainfall duration, for return periods greater than or equal to 25 years, whereas for return periods under 25 years the current IDFs can be representative of future scenarios. Current calculations and future projection of the torrentiality index for severe climate change scenarios, as well as the climate change factors, show an increase in the frequency and magnitude of the heaviest rainfall. This fact corroborates the hypotheses of greater general torrentiality in future rainfall in this specific area of the Spanish Mediterranean coast. [ABSTRACT FROM AUTHOR]

Spain is the third-largest producer of pork meat in the world, and many farms in several regions depend on the evolution of this market. However, the current pricing system is unfair, as some actors have better market information than others. In this context, historical pricing is an easy-to-find and affordable data source that can help all agents to be better informed. However, the time lag in data acquisition can affect their pricing decisions. In this paper, we study the effect that data acquisition delay has on a price prediction system using multiple prediction algorithms. We describe the integration of the best proposal into a decision support system prototype and test it in a real-case scenario. Specifically, we use public data from the most important regional pork meat markets in Spain published by the Ministry of Agriculture with a two-week delay and subscription-based data of the same markets obtained on the same day. The results show that the error difference between the best public and data subscription models is 0.6 Euro cents in favour of the data without delay. The market dimension makes these differences significant in the supply chain, giving pricing agents a better tool to negotiate market prices. [ABSTRACT FROM AUTHOR]

The ability of early hominins to overcome the constraints imposed by the characteristics of raw materials used for stone tool production is a key topic on the discussion about the evolution of hominin cognitive capabilities and technical behaviours. Thus, technological variability has been the centrepiece on this debate. However, the variability of lithic assemblages cannot be correctly interpreted without understanding site occupational models and function and considering that individual tools represent specific discard moments in a continuous reduction process. In Europe, the earliest technological record is represented by the scarce and scattered Mode 1 technologies, often deriving from occasional occupations or restricted activity areas yielding unrepresentative assemblages. In this paper, we approach the technological behaviours exhibited by Lower Palaeolithic hominins from the subunit TD6.2 of the Gran Dolina site (Atapuerca, Burgos) by including the perspective of reduction intensity studies on the analysis of technological variability. Gran Dolina TD6.2 is a unique and extremely significant archaeological context, as it represents the oldest multi-layered unit of domestic hominin occupations in the Early Pleistocene of Europe. We use the Volumetric Reconstruction Method (VRM) to estimate the original volume of the blanks and quantify the reduction intensity of each core individually to characterise the reduction distribution patterns using Weibull probability distribution functions. Our results suggest differential raw material management in terms of reduction intensity, according to the characteristics of each lithology. This could reflect a solid understanding of raw material qualities and a certain degree of planning. Altogether, the continuity between knapping strategies through reduction denotes constant adaptation to raw material constraints as well as particular knapping conditions, rather than specific compartmentalised mental schemes. In conclusion, Homo antecessor toolmakers would have been situational knappers whose technological behaviour would be highly adaptive. This research constitutes the first reduction approach for the European Early Pleistocene assemblages that will lead to a referential framework for other European Early Pleistocene sites. [ABSTRACT FROM AUTHOR]

This paper introduces the hhsmmR package, which involves functions for initializing, fitting, and predication of hidden hybrid Markov/semi-Markov models. These models are flexible models with both Markovian and semi-Markovian states, which are applied to situations where the model involves absorbing or macro-states. The left-to-right models and the models with series/parallel networks of states are two models with Markovian and semi-Markovian states. The hhsmm also includes Markov/semi-Markov switching regression model as well as the auto-regressive HHSMM, the nonparametric estimation of the emission distribution using penalized B-splines, prediction of future states and the residual useful lifetime estimation in the predict function. The commercial modular aero-propulsion system simulation (C-MAPSS) data-set is also included in the package, which is used for illustration of the application of the package features. The application of the hhsmm package to the analysis and prediction of the Spain's energy demand is also presented. [ABSTRACT FROM AUTHOR]

An updated and complete landslide inventory is the starting point for an appropriate hazard assessment. This paper presents an improvement for landslide mapping by integrating data from two well-consolidated techniques: Differential Synthetic Aperture Radar (DInSAR) and Landscape Analysis through the normalised channel steepness index (ksn). The southwestern sector of the Sierra Nevada mountain range (Southern Spain) was selected as the case study. We first propose the double normalised steepness (ksnn) index, derived from the ksn index, to remove the active tectonics signal. The obtained ksnn anomalies (or knickzones) along rivers and the unstable ground areas from the DInSAR analysis rapidly highlighted the slopes of interest. Thus, we provided a new inventory of 28 landslides that implies an increase in the area affected by landslides compared with the previous mapping: 33.5% in the present study vs. 14.5% in the Spanish Land Movements Database. The two main typologies of identified landslides are Deep-Seated Gravitational Slope Deformations (DGSDs) and rockslides, with the prevalence of large DGSDs in Sierra Nevada being first revealed in this work. We also demonstrate that the combination of DInSAR and Landscape Analysis could overcome the limitations of each method for landslide detection. They also supported us in dealing with difficulties in recognising this type of landslides due to their poorly defined boundaries, a homogeneous lithology and the imprint of glacial and periglacial processes. Finally, a preliminary hazard perspective of these landslides was outlined. [ABSTRACT FROM AUTHOR]

This paper studies the spatiotemporal variability of the IRt index (defined as the difference between the percentage of precipitation corresponding to warm days and cold days in year t) calculated at 35 stations in the Iberian Peninsula during 1951–2019. Spatial variability is estimated using cluster analysis (Euclidean distance, Ward's method), which allows regionalization of the data set for each year's season. For each cluster, the < IR > index is defined as the average of the indexes corresponding to each cluster element. The temporal evolution of the < IR > indices is analyzed by studying the appearance of trends using the Mann–Kendall test and the possible existence of various subperiods using the cumulative sum of deviations and the t-test for the difference between the means. The role of EA, EA/WR, NAO, SCAN and WeMO teleconnection patterns in modulating the relationship between temperature and precipitation is analyzed by applying multiple regression analysis. The results show a trend towards positive (or less negative) values in the relationship between temperatures and precipitation (of varying magnitude depending on the region and season) and the contribution of atmospheric dynamics to these changes. [ABSTRACT FROM AUTHOR]

In the present paper, an active landslide located to the southeast of the urban area of Alcoy (Alicante, Spain) is analysed. This landslide affects the N-340 road, as well as an area in which some industrial buildings dated from the fifteenth century and catalogued as Places of Cultural Interest are placed. This region is characterised by the existence of a steep relief composed of materials from the Miocene to the present, on which many gravitational movements are developed. The displacements have been analysed using high-resolution spotlight mode SAR images captured by the Spanish SAR satellite PAZ (which operates at X-band), which were processed by advanced differential SAR Interferometry (A-DInSAR). The behaviour of the instability has been determined using InSAR-derived time series displacement maps. Additionally, the study has been completed with a detailed geomorphological mapping at 1:2000 scale and an analysis of structural damage carried out in situ. The landslide was modelled in 3D, from a deterministic and probabilistic point of view, confirming the global instability of the area and the relationship of the landslide with rainfall and the construction of a new road. The integration of all this information obtained and its subsequent analysis has made possible to precisely define the extension of the instability, its kinematics, and to identify the main triggering factors. This information will be crucial for the proper management of this landslide by the local authorities. [ABSTRACT FROM AUTHOR]

Time series forecasting of meteorological variables, such as the hourly air temperature, has multiple benefits for industry, agriculture, and the environment. Due to the high accuracy required for the associated short-term predictions, traditional methods cannot satisfy the requirements and generally ignore spatial dependencies. This paper proposes a deep Graph Convolutional Long Short Term Memory Neural Network (GCN-LSTM) technique to tackle the time series prediction problem in air temperature forecasting. In the proposed methodology, temporal and spatial-based imputation approaches have been employed to recover the weather variables missing values. The proposed approach is validated using real, open weather data from 37 meteorological stations in Spain. Performed analysis indicates that GCN-LSTM showed superior performance when compared with various state-of-the-art Deep Learning based models found in the literature, resulting in a more robust and computationally efficient model for forecasting air temperature in many meteorological stations simultaneously. [ABSTRACT FROM AUTHOR]

Sexual dimorphism is the basis for sex estimation research in skeletal remains, helping the positive identification of individuals in forensic backgrounds. In this regard, it has been proved that the metrical analysis of the costal neck of the first four ribs in Spanish contemporary adult skeletons shows high sexual dimorphism, especially in the first rib. However, the validation of any method developed in identified skeletal collections must be compulsorily reproduced in other skeletonized sets to verify either its potential application in individuals from other locations, or the existence of possible biases associated with inter-population variation. Due to the geographical and socioeconomic proximity between Spain and Portugal, this paper aims to check the utility of the discriminant functions designed by Partido-Navadijo et al. (2021) in the two skeletal collections of the University of Coimbra (Portugal). Results show the utility of these discriminant functions in Portuguese population, with frequencies of cases correctly assigned reaching up to 93.6% in the Coimbra Identified Skeletal Collection (CISC); and up to 92.6% in the 21st Century Identified Skeletal Collection (CEI/XXI). However, two particularities between the Spanish and Portuguese osteological assemblages can be highlighted: the possible existence of secular changes in relation to the CISC collection (1904–1938); and a reversal in the degree of costal dimorphism, being the third and fourth ribs of the CEI/XXI collection more dimorphic than the first ones. [ABSTRACT FROM AUTHOR]

The COVID-19 is a "unique" stressor, which can produce physical and psychological trauma. Coping styles can buffer this psychological impact. Consequently, this paper aims to psychometrically adapt the Fear of COVID-19 scale (FCV-19S) to Spanish and examines the relationships between FCV-19S, stress response, and coping strategies. The sample comprised a convenience sample of 1146 participants (12–83 years), 880 from Spain (76.8%), and 266 from Dominican Republic (23.2%). Overall, the findings support a one-factor structure for FCV-19S, consisting of 7-items, and was invariant across age, sex, occupational status, and cross-national. Therefore, indicating evidences of construct validity. Evidences of reliability were also observed (Cronbach's α =.86, McDonald's ω =.86, Guttmann's λ6 =.86, greatest lower bound =.91, composite reliability =.85, and average variance extracted =.44). Moreover, as regards criterion-related validity, the mediation analysis indicated that the relationship between FCV-19S and acute stress was positive and high, with maladaptive coping styles mediating the relationship, and with a stronger mediation for men. The findings give evidences of the reliability and validity of the Spanish version of FCV-19S among Spanish-speaker participants, which provides the chance of cross-cultural studies. [ABSTRACT FROM AUTHOR]

Surveys are a fundamental tool of empirical research, but they suffer from errors: in particular, respondents can have difficulties recalling information of interest to researchers. Recent technological developments offer new opportunities to collect data passively (i.e., without participant's intervention), avoiding recall errors. One of these opportunities is registering online behaviors (e.g., visited URLs) through tracking software ("meter") voluntarily installed by a sample of individuals on their browsing devices. Nevertheless, metered data are also affected by errors and only cover part of the objective information, while subjective information is not directly observable. Asking participants about such missing information by means of web surveys conducted in the moment an event of interest is detected by the meter has the potential to fill the gap. However, this method requires participants to be willing to participate. This paper explores the willingness to participate in in-the-moment web surveys triggered by online activities recorded by a participant-installed meter. A conjoint experiment implemented in an opt-in metered panel in Spain reveals overall high levels of willingness to participate among panelists already sharing metered data, ranging from 69% to 95%. The main aspects affecting this willingness are related to the incentive levels offered. Limited differences across participants are observed, except for household size and education. Answers to open questions also confirm that the incentive is the key driver of the decision to participate, whereas other potential problematic aspects such as the limited time to participate, privacy concerns, and discomfort caused by being interrupted play a limited role. [ABSTRACT FROM AUTHOR]

General circulation models (GCM) show projections of climate variables that when downscaled can be applied to analyse future behaviour in different areas or places. Using them is possible not just to obtain expected values of climate variables but also to calculate their distributions and use those values to assess the effects of climate change at a local level. However, these calculations depend on the GCM selected. In this paper, daily maximum near-surface air temperatures from 21 climate models under representative concentration pathway (RCP) scenarios RCP 4.5 and RCP 8.5 and historic daily maximum temperatures (1990–2019) from nine cities in southern Spain are used with two objectives: first, to investigate past behaviour broken down into a deterministic part and a stochastic part; second, to compare historical data (2006–2019) with the information extracted from the 21 GCMs based on calculating goodness of fit in the period for both deterministic and stochastic parts. The methodology proposed may be useful in selecting a model or a range of models for use in a specific study. The results show positive historical and future trends in maximum daily temperature for these cities. The GCMs with the best fit for each city in this specific case are also presented. [ABSTRACT FROM AUTHOR]

Gravity models have been one of the mathematical models of choice for trip distribution modeling efforts during many decades. Their simplicity offset their drawbacks, as they usually provide a reasonably good rationale for how goods are distributed in a transportation network with relatively little information. These gravity models, however, rely on the definition of a deterrence function that acts as a counterweight of the levels of supply and demand. This function is usually picked from a series of off-the-shelf available functions that only depend on a handful of parameters that need to be calibrated. Because of the limited off-the shelf options, gravity models lack flexibility in some occasions. In this paper, we tackle the use of sparse regression techniques that can accommodate data more flexibly with a reduced number of terms. Using interregional freight origin–destination data from Spain, we test two alternatives, namely, best subset regression and lasso regression. We show that the first one performs better in finding parsimonious deterrence functions and we attain gravity models that fit the data up to 14.5% better than classical deterrence functions. [ABSTRACT FROM AUTHOR]

This paper seeks to reconstruct the management of food resources in the early Neolithic site of Cabecicos Negros in southeastern Spain. For this purpose, we have studied 29 potsherds from Cabecicos Negros (Andalusia, Spain). Applying the methods of gas chromatography and mass spectrometry we were able to recompose the daily use of the sherds related to the consumption and storage of food products. Among the results obtained in this work, we were able to show new evidence of the exploitation of dairy products in the south of the Iberian Peninsula, as well as provide information on the exploitation and management of the early domestic animals herds. To improve the archaeological results obtained, isotopic results were compared with a modern reference of 53 fat samples from the adipose tissue of domestic pigs and wild boars. [ABSTRACT FROM AUTHOR]

In this paper, we propose a twofold methodology for visual detection and recognition of different types of city dumpsters, with minimal human labeling of the image data set. Firstly, we carry out transfer learning by using Google Inception-v3 convolutional neural network, which is retrained with only a small subset of labeled images out of the whole data set. This first classifier is then improved with a semi-supervised learning based on retraining for two more rounds, each one increasing the number of labeled images but without human supervision. We compare our approach against both to a baseline case, with no incremental retraining, and the best case, assuming we had a fully labeled data set. We use a data set of 27,624 labeled images of dumpsters provided by Ecoembes, a Spanish nonprofit organization that cares for the environment through recycling and the eco-design of packaging in Spain. Such a data set presents a number of challenges. As in other outdoor visual tasks, there are occluding objects such as vehicles, pedestrians and street furniture, as well as other dumpsters whenever they are placed in groups. In addition, dumpsters have different degrees of deterioration which may affect their shape and color. Finally, 35% of the images are classified according to the capacity of the container, which contains a feature which is hard to assess in a snapshot. Since the data set is fully labeled, we can compare our approach both against a baseline case, doing only the transfer learning using a minimal set of labeled images, and against the best case, using all the labels. The experiments show that the proposed system provides an accuracy of 88%, whereas in the best case it is 93%. In other words, the method proposed attains 94% of the best performance. [ABSTRACT FROM AUTHOR]

The emergence of SARS-CoV-2 in China in December 2019 has posed a major challenge to health systems in all countries around the world. One of the most relevant epidemiological measures to consider during the course of a pandemic is the proportion of cases that eventually die from the disease (case fatality ratio, CFR). Monitoring the evolution of this indicator is of paramount importance because it allows for the assessment of both variations in the lethality of the virus and the effectiveness of the control measures implemented by health authorities. One of the problems with estimating the CFR in practice is that the available data only show daily or weekly counts of new cases and deaths; there is no information on when each deceased patient was infected and therefore it is not possible to know exactly how many cases there were at the time the patient became infected. Various approaches have been proposed for calculating the CFR by correcting for the time lag between infection and death. In this paper, we present a novel methodology to perform a non-parametric estimation of the evolution of the CFR by initially identifying an optimal time lag between infections and deaths. The goodness of this procedure is assessed by means of a simulation study and the method is applied to the estimation of the CFR in Spain in the period from July 2020 to March 2022. [ABSTRACT FROM AUTHOR]

The constant development of geomatics tools has driven the opening of their applications to multiple disciplines, including archaeology. The possibility of performing a 3D reconstruction of archaeological remains as well as a semantic classification of the 3D surface facilitates not only a better knowledge of the historical heritage but also an essential aid to the planning and development of restoration and preservation projects of this legacy. Different data exploitation strategies are needed to take advantage of the geospatial data provided by geomatics tools. In this paper, we have studied the current state of conservation of a medieval tower, Torre Benzalá in Jaén, southern Spain. The interesting thing about this study is that very high resolution RGB images, taken by a drone, have been used in order to show the current degree of deterioration of the tower, providing accurate and precise documentation of the current state. Thus, a highly detailed 3D reconstruction of the tower has been carried out. A dense point cloud was generated to obtain a digital elevation model (DEM) to identify and quantify the most critically deteriorated areas. The results are useful for the development of an architectural maintenance and restoration project to preserve this archaeological legacy. [ABSTRACT FROM AUTHOR]

In Spain, the youth unemployment rate is one of the highest in the European Union. With the pandemic caused by Covid-19, young people face high unemployment rates and are more vulnerable to a decrease in labour demand. This paper analyses and predicts youth unemployment using Google Trends indices in Spain for the period between the first quarter of 2004 and the second quarter of 2021, being the first work to carry out this study for Spain and the first to use the regional approach for the country. Vector autoregressive Bayesian models and vector error correction models have been used for national data, and Bayesian panel data models and fixed effects model for regional data. The results confirm that forecasts based on Google Trends data are more accurate in predicting the youth unemployment rate. [ABSTRACT FROM AUTHOR]

This paper provides new evidence on how intergenerational income inequality evolves during the period 2005–2019. Using the Continuous Sample of Working Histories (CSWH), which includes administrative data about working lives and personal characteristics of Spanish workers, we shed light on the effect of the Great Recession on income inequality between cohorts in Spain. As a proxy of income, we employ monthly earnings data, provided by the CSWH. From a life course approach, we use two age-period-cohort (APC) models which allow us to separately identify three components: cohort, age and period effects. First, we examine relative earnings which will reveal whether there are income differences between generations. Second, we measure how absolute earnings have developed over time. Our results suggest that some generations are more disadvantaged in terms of income by their year of birth than others. Likewise, the evidence points out that the economic context experienced by a generation in their transition to the labour market is a key factor in the development of their income. [ABSTRACT FROM AUTHOR]

In this paper, the main objective is the simulation of the electric supply for homes in remote areas located in Morocco (Oujda and Ouarzazate), Spain (Granada), and Algeria (Bechar). This simulation study is divided into two ideas, the first one is to optimize the hybrid system under a varied number of houses and the second part is to fix it in chosen values. This work relied on the particle swarm optimization (PSO) method to optimize and analyze the proposed stand-alone photovoltaic/wind/diesel/battery hybrid system. MATLAB software is used to run the simulations and to carry out the optimal solutions of the optimized system using a developed PSO algorithm. The PSO approach contains five principal operator axes, which are problem definition, PSO initial parameters, initialization, PSO main loop, and then run of the algorithm. Optimizing the system component sizes and reaching the minimum cost of energy (COE) were the function objectives of this optimization study. Moreover, calculation of the hydrogen production from the generated energy by PV and wind systems is performed. [ABSTRACT FROM AUTHOR]

The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the coronavirus disease 2019 (COVID-19) pandemic, in light of the hundreds of contradictory studies that have already been published on this issue in just a few months. In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic to the end of August 2020 is analysed using statistical models of diverse levels of complexity. Specifically, the possible effect of several environmental variables (solar exposure, mean temperature, and wind speed) on the number of cases is assessed. Thus, the first objective of the paper is to show how the choice of a certain type of statistical model to conduct the analysis can have a severe impact on the associations that are inferred between the covariates and the response variable. Secondly, it is shown how the use of spatio-temporal models accounting for the nature of the data allows understanding the evolution of the pandemic in space and time. The results suggest that even though the models fitted to the data correctly capture the evolution of COVID-19 in space and time, determining whether there is an association between the spread of the pandemic and certain environmental conditions is complex, as it is severely affected by the choice of the model. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), has led to the deepest global health and economic crisis of the current century. This dramatic situation has forced the public health authorities and pharmaceutical companies to develop anti-COVID-19 vaccines in record time. Currently, almost 80% of the population are vaccinated with the required number of doses in Spain. Thus, in this paper, COVID-19 incidence and lethality rates are analyzed through a segmented spatio-temporal regression model that allows studying if there is an association between a certain vaccination level and a change (in mean) in either the incidence or the lethality rates. Spatial dependency is included by considering the Besag–York–Mollié model, whereas natural cubic splines are used for capturing the temporal structure of the data. Lagged effects between the exposure and the outcome are also taken into account. The results suggest that COVID-19 vaccination has not allowed yet (as of September 2021) to observe a consistent reduction in incidence levels at a regional scale in Spain. In contrast, the lethality rates have displayed a declining tendency which has associated with vaccination levels above 50%. [ABSTRACT FROM AUTHOR]

Life expectancy at birth has attracted interest in various fields, as a health indicator that measures the quality of life. Its appeal relies on the ability to enclose and summarize all the factors affecting longevity. However, more granular information, provided by social indicators such as cause-of-death mortality rates, plays a crucial role in defining appropriate policies for governments to achieve well-being and sustainability goals. Unfortunately, their availability is not always guaranteed. Exploiting the relationship between life expectancy at birth and cause-of-death mortality rates, in this paper we propose an indirect model to produce estimates of death rates due to specific causes using the summary indicator of life expectancy at birth, thus the general levels of the observed mortality. By leveraging on a constrained optimization procedure, we ensure a robust framework where the cause-specific mortality rates are coherent to the aggregate mortality. The main advantage is that indirect estimations allow us to overcome the data availability problem: very often the cause-specific mortality data are incomplete, whereas data on the aggregate mortality are not. Using data from the Human Cause-of-Death Database, we show a numerical application of our model to two different countries, Russia and Spain, which have experienced a different evolution of life expectancy and different leading causes of death. In Spain, we detected the impact of several public health policies on the lowered levels of cancer deaths and related life expectancy increases. As regards the Russia, our results catch the effects of the anti-alcohol campaign of 1985–1988 on longevity changes. [ABSTRACT FROM AUTHOR]

Quality education is a key factor to improve people's lives and to achieve sustainable development. Using data from PISA 2009, 2012 and 2015, in this paper the level of educational poverty of the Spanish regions is calculated by applying the Adjusted Bourguignon Chakravarty index, B C a (Sánchez-García et al. in Soc Indicat Res 145(2): 479–501). A descriptive analysis of the differences in educational poverty by gender and the contribution of each region and subject to the national level of educational poverty is also provided. This information could certainly be considered a starting point to tackle educational poverty in Spain. [ABSTRACT FROM AUTHOR]

The Gloria storm rainfalls affected Catalonia from 20 to 23 January 2020 and triggered multiple landslides, some of which affected buildings and infrastructures (such as roads and railways). This paper presents the rainfall and landslide datasets collected during the event, and evaluates the performance of a regional landslide early warning system (LEWS) during the Gloria storm applying a fuzzy verification method. The majority of the inventoried landslides can be classified as slides, involving a limited volume of sediment (up to 10 m3), and were triggered in cut slopes along linear infrastructures. Rainfall accumulations were significant in the whole region, especially in the Montseny area, where over 450 mm were registered in 96 h. Generally, the LEWS computed moderate and high warnings in the areas where large rainfall amounts were recorded, and showed good correspondence with the locations where landslides were reported. The fuzzy verification method has been applied using neighbouring windows of different sizes to obtain scale-dependant information on the LEWS performance. The skill of the LEWS considerably improves when enlarging the neighbouring window size from 500 m to 1 km. [ABSTRACT FROM AUTHOR]

The archaeology of the Spanish Civil War (1936–39) has experienced an important development over the last two decades. Several field projects have studied aspects such as mass graves, forced labor camps, and battlefields. In this paper, we present a case study from the so-called "Northern Front" (Frente Norte). The impressive mountain of Monte Bernorio, situated at the foothills of the Cantabrian Mountains, controls one of the main communication routes between the central Spanish plateau (Meseta) and the Cantabrian Sea. Due to this strategic position, the site has played an important military role during two episodes of war separated by nearly 2,000 years: the Roman conquest of northern Iberia under Emperor Augustus in the 20s BCE, and the Spanish Civil War in the years 1936-37. The ongoing archaeological excavations and surveys are uncovering abundant remains of trenches, battering positions, barracks, and munitions belonging to the Civil War period, when Bernorio was a highly disputed position in the confrontation between "Republicans" and "Nationalists." Adopting an interdisciplinary approach, this paper combines archaeological evidence, oral history, and written documents that shed light on one of the main episodes of Franco's conquest of northern Spain. [ABSTRACT FROM AUTHOR]

The location, size, and structure of the farmlands and hydraulic systems built by the Indigenous inhabitants of Gran Canaria, Canary Islands, Spain, remain unknown. This hampers our ability to understand how they organized agricultural production and how European settlers transformed local landscapes to build commercial plantations in the late fifteenth century. This paper combines an analysis of archival sources with the study of agricultural landscapes and practices to identify and describe the fields that were employed by the first colonists of Agüimes and Temisas, and to derive information about the location, design, and management of the pre-Hispanic farmlands. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the temporal dependence in energy prices and demand using daily data of Portugal and Spain over the period 2007–2017. The methodology used is based on a stochastic Hidden Markov Model and the results indicate first that all significant relationships between energy prices and demands were found to be positive; second, spot prices are only time dependent on future prices and spot energy, while future energy is solely time dependent on spot energy behavior; third, future prices are not only autocorrelated but also time-dependent with spot energy and future energy demands level; and finally, spot energy is autocorrelated and time-dependent with future prices and future energy. Policy implications of the results obtained are presented at the end of the article. [ABSTRACT FROM AUTHOR]

The macroalgal flora of Cantabria (north of Spain) has attracted the interest of many researchers on past occasions. Currently published information only reflects occasional collections from sporadic field visits to this region of the Spanish Atlantic coast. To overcome this, a historical overview of research and publications, encompassing collections and presence data recording, has been undertaken. This work lists the resultant taxonomic records and provides information about macroalgal flora of Cantabria. A total of 425 species (25 Cyanobacteria, 55 Chlorophyta, 81 Ochrophyta, and 264 Rhodophyta) were identified. The number of specific, infraspecific taxa, and stages is 437: 25 Cyanobacteria, 57 Chlorophyta, 89 Ochrophyta, and 266 Rhodophyta. The floristic character of flora from the Cantabrian coast is compared over time and with nearby regions applying Cheney's ratio [(Rhodophyta+Chlorophyta)/ Ochrophyta, or (R+C)/O]. The present paper aims to provide an overview of the research that has been conducted in the Cantabrian coast, not only found in international publications but also in local publications as well as unpublished theses. [ABSTRACT FROM AUTHOR]

This paper analyses the seismic vulnerability of various rammed earth medieval fortifications situated in Southeastern Spain, where seismic events with intensity over VII have taken place in the last millennium, using the vulnerability index method. This method begins with the choice of a certain initial value, V0, of the vulnerability index, which is obtained from a preset range between maximum, V 0 max , and minimum, V 0 min , values, which are likely for vulnerability indices, according to the constructive material characteristics and based on expert judgments. Rammed earth structures have not yet been studied using the vulnerability index method, despite the fact that they are quite common medieval structures in Spain and other countries in the Mediterranean region, many of which are also heritage sites, and hence are legally protected. Intervention priorities on them have been determined from the results in this paper with the aim of reducing their seismic vulnerability. For the different rammed earth techniques, a proposed primary value Vp = 0.76 together with some other material modifiers (construction typology and quality, current material porosity and density, and superficial deterioration) make the range of values V0 vary between 0.58 and 1.02. Moreover, structural behavior modifiers (MK) have been adapted to the various defensive rammed earth structural typologies used for these fortifications allowing us to obtain individualized vulnerability index values. Three rammed earth fortifications damaged by historical earthquakes and located in SE Spain have been used to validate the method, in which values of V0med range between 35.2 and 89.1% and upwards and the vulnerability index IVmed may vary between 27.9 and 70.7% and upwards as compared to those used by other authors for castles. Besides, the proposed method has been used by carefully choosing six rammed earth fortifications (two towers, two walls and two castles) in SE Spain which are representative of different construction systems, structural typologies and topographies. Furthermore, the mean damage grade and the probability of its occurrence is determined for each fortification based on PGA data and site effects, taking into account a probabilistic seismic scenario for a 975 year return period, in accordance with existing legislation. In the end, direct relations are established between the seismic vulnerability and the types of material and the typology of the fortifications. We have carried out a sensibility analysis in order to learn about the influence of the constructive technique, the material condition and the structural typology on the damage grade value. The results show that lime-crusted rammed earth technique and tower typologies are the most vulnerable structures while topography is somehow less important. The results suggest that for half of the structures analyzed for the given scenario the probabilities are above 80% for damage grade 4 and 5 (EMS-98). [ABSTRACT FROM AUTHOR]

Summary: This paper demonstrates a large post-fracture anti-osteoporosis treatment gap in the period 2005 to 2015. The gap was stable in Denmark at around 88–90%, increased in Catalonia from 80 to 88%, and started to increase in the UK towards the end of our study. Improved post-fracture care is needed. Introduction: Patients experiencing a fragility fracture are at high risk of subsequent fractures, particularly within the first 2 years after the fracture. Previous studies have demonstrated that only a small proportion of fracture patients initiate therapy with an anti-osteoporotic medication (AOM), despite the proven fracture risk reduction of such therapies. The aim of this paper is to evaluate the changes in this post-fracture treatment gap across three different countries from 2005 to 2015. Methods: This analysis, which is part of a multinational cohort study, included men and women, aged 50 years or older, sustaining a first incident fragility fracture. Using routinely collected patient data from three administrative health databases covering Catalonia, Denmark, and the United Kingdom, we estimated the treatment gap as the proportion of patients not treated with AOM within 1 year of their first incident fracture. Results: A total of 648,369 fracture patients were included. Mean age 70.2–78.9 years; 22.2–31.7% were men. In Denmark, the treatment gap was stable at approximately 88–90% throughout the 2005 to 2015 time period. In Catalonia, the treatment gap increased from 80 to 88%. In the UK, an initially decreasing treatment gap—though never smaller than 63%—was replaced by an increasing gap towards the end of our study. The gap was more pronounced in men than in women. Conclusion: Despite repeated calls for improved secondary fracture prevention, an unacceptably large treatment gap remains, with time trends indicating that the problem may be getting worse in recent years. [ABSTRACT FROM AUTHOR]

Archaeological research in the Dolmen of El Pendón (Reinoso, Burgos, Spain) has brought to light the complex biography of a megalithic monument used throughout the 4th millennium cal. BC. The ossuary of this burial holds the bones of nearly a hundred individuals who suffered from diverse pathologies and injuries. This study presents the discovery of a skull with two bilateral perforations on both mastoid bones. These evidences point to a mastoidectomy, a surgical procedure possibly performed to relieve the pain this prehistoric individual may have suffered as a result of otitis media and mastoiditis. The hypothesis of surgical intervention is also supported by the presence of cut marks at the anterior edge of the trepanation made in the left ear. Furthermore, the results of this paper demonstrate the survival of the individual to both interventions. Given the chronology of this dolmen, this find would be the earliest surgical ear intervention in the history of mankind. [ABSTRACT FROM AUTHOR]

This paper aims at analyzing the effect of heat treatment using Concentrated Solar Energy (CSE) on the martensitic microstructure evolution of Ti-6Al-4V alloy manufactured by Selective Laser Melting (SLM) technology. The application of CSE, a renewable energy sources, in post-processing of SLMed Ti-6Al-4V alloy is discussed based on heat treatments performed at Plataforma Solar de Almeria, Spain, using solar furnace SF40. In SLM process of Ti-6Al-4V powder because of local high heating followed by a rapid cooling the microstructure consists of an acicular martensite (α′ phase). Decomposition of α′ martensite of SLMed Ti-6Al-4V after heat treatment in solar furnace, using CSE, by SEM, EDX, TEM, SAED, and XRD analyses, was investigated. It has been found that for treatment below β-transus at 705 °C, because of low temperature, the α′ martensite was not fully converted into α + β and the β phase was not identified by XRD analysis. Heat treatments below (940 °C followed by 650 °C) and above (1050 °C) β-transus have revealed that α′ martensite was converted into a lamellar α + β mixture and also β phase was identified by XRD and TEM analysis. In the analyzed areas, middle areas of the samples contain an area fraction of β phase greater than the top areas. Area fraction of β phase, after heat treatment above β-transus, at 1050 °C, is greater than that obtained after treatment below β-transus. [ABSTRACT FROM AUTHOR]

European countries struggled to fight against the second and the third waves of the COVID-19 pandemic, as the Test-Trace-Isolate (TTI) strategy widely adopted over the summer and early fall 2020 failed to contain the spread of the disease effectively. This paper sheds light on the effectiveness of such a strategy in two European countries (Spain and Italy) by analysing data from June to December 2020, collected via a large-scale online citizen survey with 95,251 and 43,393 answers in Spain and Italy, respectively. Our analysis describes several weaknesses in each of the three pillars of the TTI strategy: Test, Trace, and Isolate. We find that 40% of respondents had to wait more than 48 hours to obtain coronavirus tests results, while literature has shown that a delay of more than one day might make tracing all cases inefficient. We also identify limitations in the manual contact tracing capabilities in both countries, as only 29% of respondents in close contact with a confirmed infected individual reported having been contact traced. Moreover, our analysis shows that more than 45% of respondents report being unable to self-isolate if needed. We also analyse the mitigation strategies deployed to contain the second wave of coronavirus. We find that these interventions were particularly effective in Italy, where close contacts were reduced by more than 20% in the general population. Finally, we analyse the participants' perceptions about the coronavirus risk associated with different daily activities. We observe that they are often gender- and age-dependent, and not aligned with the actual risk identified by the literature. This finding emphasises the importance of deploying public-health communication campaigns to debunk misconceptions about SARS-CoV-2. Overall, our work illustrates the value of online citizen surveys to quickly and efficiently collect large-scale population data to support and evaluate policy decisions to combat the spread of infectious diseases, such as coronavirus. [ABSTRACT FROM AUTHOR]

Venta Micena, an Early Pleistocene site of the Baza Basin (SE Spain), preserves a rich and diverse assemblage of large mammals. VM3, the main excavation quarry of the site, has been interpreted as a den of the giant hyaena Pachycrocuta brevirostris in the plain that surrounded the Baza palaeolake. Taphonomic analysis of VM3 has shown that the hyaenas scavenged the prey previously hunted by the hypercarnivores, transported their remains to the communal den, and consumed the skeletal parts according to their marrow contents and mineral density. In a recent paper (Luzón et al. in Sci Rep 11:13977, https://doi.org/10.1038/s41598-021-93261-1, 2021), a small sample of remains unearthed from VM4, an excavation quarry ~ 350 m distant from VM3, is analysed. The authors indicate several differences in the taphonomic features of this assemblage with VM3, and even suggest that a different carnivore could have been the agent involved in the bone accumulation process. Here, we make a comparative analysis of both quarries and analyse more skeletal remains from VM4. Our results indicate that the assemblages are broadly similar in composition, except for slight differences in the frequency of megaherbivores, carnivores and equids according to NISP values (but not to MNI counts), the degree of bone weathering, and the intensity of bone processing by the hyaenas. Given that VM4 and VM3 were not coeval denning areas of P. brevirostris, these differences suggest that during the years when the skeletal remains were accumulated by the hyaenas at VM3, the rise of the water table of the Baza palaeolake that capped with limestone the bones was delayed compared to VM4, which resulted in their more in-depth consumption by the hyaenas. [ABSTRACT FROM AUTHOR]

This paper addresses a home healthcare routing problem in which doctors and nurses visit patients at their homes to provide services. We consider a real-world home healthcare service arising in a particular hospital in Spain. Doctors and nurses are distributed in teams and travel by taxi; taxis transport a pre-defined set of workers who travel together the whole route. The objective is to minimise the transportation costs related to the total taxi journey time, including travelling and waiting costs. The paper presents a mathematical model that considers these current policies and permits the problem to be solved optimally. The paper also explores, after reviewing the hospital's current model, the benefits that can be obtained by changing some of the current policies of the hospital. In this way, a new model is proposed based on two sustainable strategies that can be extended to other home service fields: (1) workers can walk between houses and (2) the workers transported by a taxi may change during the route. A complex nonlinear mathematical model is presented, and a metaheuristic is designed to provide quality solutions. Computational tests on a set of instances based on real-world data estimate the gap between the solutions of both models. [ABSTRACT FROM AUTHOR]

In this paper, we retrieve data about the frequent users of electronic commerce during the period 2011–2016 from the Spanish National Institute of Statistics. These data, coming from surveys, have intrinsic uncertainty that we describe using appropriate random variables. Then, we propose a stochastic model to study the dynamics of frequent users of electronic commerce. The goal of this paper is to solve the inverse problem that consists of determining the model parameters as suitable parametric random variables, in such a way the model output be capable of capturing the data uncertainty, at the time instants where sample data are available, via adequate probability density functions. To achieve the aforementioned goal, we propose a computational procedure that involves building a nonlinear objective function, based on statistical moment measures, to be minimized using a variation of the particle swarm optimization algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a low-complexity pseudo-inverse Legendre neural network (PILNNR) with radial basis function (RBF) units in the hidden layer for accurate wind power prediction on a short-term basis varying from 10- to 60-min interval. The random input weights between the expanded input layer using Legendre polynomials and the RBF units in the hidden layer are optimized with a metaheuristic firefly (FF) algorithm for error minimization and improvement of the learning speed. For comparison, two other forecasting models, namely pseudo-inverse RBF (PIRBFNN-FF) neural network and PILNNR [with tanh functions in the hidden layer (PILNNT-FF)] with input-to-hidden layer weights being optimized by FF algorithm, are also presented in this paper. Also the weights between the hidden layer and the output neuron of these neural models are obtained by Moore–Penrose pseudo-inverse algorithm. Further to improve the stability of the weight learning procedure, the L2-norm-regularized least squares (ridge regression) technique is used. A superior predictive ability test is performed on the three proposed wind power forecasting models using bootstrapping procedure in order to identify the best model. Several case studies using wind power data of the wind farms in the states of Wyoming and California in USA and Sotavento wind farm in Spain are presented in this paper. [ABSTRACT FROM AUTHOR]