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Simple Summary: In this paper, we present the zooarchaeological and taphonomic study of a new Bronze Age site in the inland of the Iberian Peninsula. This study represents a significant contribution within the studied area, as it analyses the Pista de Motos faunal collection, one of the few representative samples from this period. This paper significantly contributes to completing the scarce information available for the Bronze Archaeology in the Middle Tagus Valley, located inland of the Iberian Peninsula. The Bronze Age zooarchaeological research for the interior and other regions of the Iberian Peninsula is currently limited. Despite several sites with known zooarchaeological profiles from the period, the main issue is that most of these derive from fragmentary and unrepresentative faunal records or are biased profiles from old excavations. New work has yielded novel zooarchaeological results in recent years that could help fill the existing zooarchaeological information gap in the Iberian inland, particularly in the Middle Tagus Valley. However, these projects are in the initial research stages and have not published much of their results. This paper presents the zooarchaeological profile of the Pista de Motos Bronze Age site to help fill this information gap. It analyses the taxonomic representation, skeletal profiles, and human activity patterns associated with faunal use. These observations suggest that animal exploitation at the site followed two primary purposes. One was linked to economic activities, mainly to obtain meat, milk, wool, or animal labour. The other was probably associated with symbolic-ritual practices suggested by the complete animal burials in some excavated units. We contextualise these interpretations with evidence from other Bronze Age sites in the Middle Tagus Valley. Finally, the paper assesses to what extent Pista de Motos is a relevant site for the zooarchaeology of the Bronze Age in the Iberian inland. [ABSTRACT FROM AUTHOR]

Aim: Suicidal behavior is a serious public health problem and a major cause of death among adolescents. Three categories of major risk factors have been identified: psychological factors, stressful life events, and personality traits. Severe and objective stressful life events (SLEs), such as childhood mistreatment or abuse, have been clearly associated with higher rates of suicide risk. However, the relationship between suicide risk and adolescents' perceptions of the SLE impact is not as clear. This paper studies the relationship between SLE impact perception and suicide risk and the possible mediating role of perceived family functioning in this relationship. The need for longer-term or more intense psychological or psychiatric treatment in relation to SLE impact perception is also addressed. Method: One hundred forty-seven adolescents aged 11–17 were consecutively recruited from the Child and Adolescent Mental Health Outpatient Services Department of a general hospital in Madrid, Spain. Self-informed questionnaires were used to assess suicide risk, SLEs, and family functioning. In addition, the clinical records of the participants were consulted to collect information about their treatment histories, including the number of appointments and the duration of follow-up. Results: SLE impact perception correlates significantly with suicide risk, the number of clinical appointments, the duration of treatment, and the perceived level of family functioning. The mediation model of the family functioning perception variable in the relationship between SLE impact perception and suicide risk is significant. The linear regression model of SLE impact perception and family functioning perception on suicide risk is also significant, accounting for 25.7% of the variance. Conclusions: Beyond the clear and proven effect of serious and objective SLEs, the perceived impact of SLEs reported by adolescents is related to an increased risk of suicide and more intense psychological and/or psychiatric follow-up. This relationship is mediated by the perceived level of family functioning. Adolescents' perceptions of their life experiences and perceived family support may be key determinants of suicide risk prevention. [ABSTRACT FROM AUTHOR]

This study formulates a mathematical dynamic Computable General Equilibrium (CGE) model within a rational expectations framework, adhering to neo-classical principles. It emphasizes the significant role of agents' expectations in determining the broader economic trajectory over time. The model combines microeconomic and macroeconomic perspectives by merging the concept of intertemporal choice with savings behavior. Its mathematical foundations are derived and calibrated using data from a social accounting matrix to enhance its simulation capabilities. The paper presents a practical simulation investigating the economic implications of a strategic investment impact within an specific European region, Madrid as the case of study. Such demand shock affects sectors such as electronics, food, pharmaceuticals, and education. The study models the long-term effects of heightened investment and persistent demand-side shocks. The research demonstrates the CGE model's ability to forecast economic shifts toward a new equilibrium after an investment shock, proving its utility for assessing the impacts of extensive environmental policies within a European context. The work's originality lies in its detailed mathematical formulation, contributing to theoretical discourse and practical application in business analytics. [ABSTRACT FROM AUTHOR]

The manner in which individuals worldwide shared art during the most challenging months of the COVID-19 pandemic stands as one of the most significant instances of creative social resistance in recent history. As a collective tool of resistance against emotional trauma, and as a means to foster a sense of community and well-being, the study of this phenomenon offers a compelling avenue for research into creativity and its social functions. This paper presents a descriptive case study of a successful 50-day collective experience within a neighborhood community in Madrid, Spain, during a period when the city, as a notably exceptional case study for research, bore one of the heaviest burdens of COVID-19 in the world. Data were gathered through in-depth personal interviews and direct observations. Applying a connected approach drawing on the fields of the Sociology of Art and Media Studies, three key findings emerge: (1) participants emphasized shared live artistic performances as the primary catalyst for fostering a sense of community, collective resilience, and overall well-being; (2) their sense of togetherness was further bolstered by digital and media support, as recordings of live performances were shared with loved ones living elsewhere, as well as with journalists and on social networks. This network of communication played a pivotal role in connecting individuals; (3) the combined efforts of both initiatives contributed to the development of a more positive individual and shared narrative surrounding the crisis. [ABSTRACT FROM AUTHOR]

Students in their first year of computer science (CS1) at universities typically struggle to grasp fundamental programming concepts. This paper discusses research carried out using a Java-based visual execution environment (VEE) to introduce fundamental programming concepts to CS1 students. The VEE guides beginner programmers through the fundamentals of programming, utilizing visual metaphors to explain and direct interactive tasks implemented in Java. The study's goal was to determine if the use of the VEE in the instruction of a group of 63 CS1 students from four different groups enrolled in two academic institutions (based in Madrid, Spain and Galway, Ireland) results in an improvement in their grasp of fundamental programming concepts. The programming concepts covered included those typically found in an introductory programming course, e.g., input and output, conditionals, loops, functions, arrays, recursion, and files. A secondary goal of this research was to examine if the use of the VEE enhances students' understanding of particular concepts more than others, i.e., whether there exists a topic-dependent benefit to the use of the VEE. The results of the study found that use of the VEE in the instruction of these students resulted in a significant improvement in their grasp of fundamental programming concepts compared with a control group who received instruction without the use of the VEE. The study also found a pronounced improvement in the students' grasp of particular concepts (e.g., operators, conditionals, and loops), suggesting the presence of a topic-dependent benefit to the use of the VEE. [ABSTRACT FROM AUTHOR]

Respiratory viruses, such as COVID-19, are spread over time and space based on human-to-human interactions. Human mobility plays a key role in the propagation of the virus. Different types of sensors in smart cities are able to continuously monitor traffic-related human mobility, showing the impact of COVID-19 on traffic volumes and patterns. In a similar way, traffic volumes measured by smart traffic sensors provide a proxy variable to capture human mobility, which is expected to have an impact on new COVID-19 infections. Adding traffic data from smart city sensors to machine learning models designed to estimate upcoming COVID-19 incidence values should provide optimized results compared to models based on COVID-19 data alone. This paper proposes a novel model to extract spatio-temporal patterns in the spread of the COVID-19 virus for short-term predictions by organizing COVID-19 incidence and traffic data as interrelated temporal sequences of spatial images. The model is trained and validated with real data from the city of Madrid in Spain for 84 weeks, combining information from 4372 traffic measuring points and 143 COVID-19 PCR test centers. The results are compared with a baseline model designed for the extraction of spatio-temporal patterns from COVID-19-only sequences of images, showing that using traffic information enhances the results when forecasting a new wave of infections (MSE values are reduced by a 70% factor). The information that traffic data has on the spread of the COVID-19 virus is also analyzed, showing that traffic data alone is not sufficient for accurate COVID-19 forecasting. [ABSTRACT FROM AUTHOR]

This paper presents a life cycle assessment (LCA) analysis of a new, high-concentration photovoltaic (HCPV) technology developed as part of the HIPERION project of hybrid photovoltaics for efficiency record using an integrated optical technology. In the LCA calculations, the production stage of a full module was adopted as a functional unit. SimaPro version 9.00.49, the recent Ecoinvent database (3.8), and the IPCC 2021 GWP 100a environmental model were applied to perform the calculations. The environmental impact of the HCPV panel was determined for constructional data and for recycling of the main elements of the module. The results of the calculations show that recycling of PMMA, rubber, and electronic elements reduced the total carbon footprint by 17%, from 240 to 201 kg CO2-eq. The biggest environmental load was generated by the PV cells: 99.9 kg CO2eq., which corresponds to 49.8% (41.7% without recycling) of the total environmental load due to the large number of solar cells used in the construction. The emission of CO2 over a 25-year lifespan was determined from 17.1 to 23.4 g CO2-eq/kWh (20.4 to 27.9 without recycling), depending on the location. The energy payback time (EPBT) for the analyzed module is 0.87 and 1.19 years, depending on the location and the related insolation factors (Madrid: 470 kWh/m2, Lyon: 344 kWh/m2). The results of the calculations proved that the application of recycling and recovery methods for solar cells can improve the sustainability of the photovoltaic industry. [ABSTRACT FROM AUTHOR]

In this paper, we describe an educational experience in the context of the Master's degree that is compulsory in Spain to become a secondary education mathematics teacher. Master's students from two universities in Madrid (Spain) attended lectures that addressed—emphasizing the concourse of a dynamic geometry software package—some historical, didactic and mathematical issues related to linkage mechanisms, such as those arising in the 18th and 19th centuries during the development of the steam engine. Afterwards, participants were asked to provide three different kinds of feedback: (i) working on an assigned group task, (ii) individually answering a questionnaire, and (iii) proposing some classroom activity, imagining it would be addressed to their prospective pupils. All three issues focused on the specific topic of the attended lectures. In the framework of Mason's reflective discourse analysis, the information supplied by the participants has been analyzed. The objective was to explore what they have learned from the experience and what their perception is of the potential interest in linkages as a methodological instrument for their future professional activity as teachers. This analysis is then the basis upon which to reflect on the opportunities (and problems) that this particular bar-joint linkages methodological approach could bring towards providing future mathematics teachers with attractive tools that would contribute to enhancing a STEAM-oriented education. Finally, the students' answers allow us to conclude that the experience was beneficial for these pre-service teachers, both in improving their knowledge on linkages history, mathematics, industrial, technological and artistic applications, and in enhancing the use in the classroom of this very suitable STEAM context. [ABSTRACT FROM AUTHOR]

Understanding the characteristics that shape mobility could help to achieve more sustainable transport systems. A considerable body of scientific studies tries to determine these characteristics at the urban level. However, there is a lack of studies analyzing those factors for the heterogeneous zones existing in the suburbs of big cities. The study presented in this paper intends to fill this gap, in the context of two metropolitan corridors in the Madrid Region. Correlation analyses are used to examine how mobility patterns are affected by socioeconomic and urban form variables. Then, a cluster analysis is carried out to classify the types of zones we may find in the suburbs. Results show that the main characteristics leading towards higher car use are low urban density, few local activities, a high percentage of children, and a low percentage of seniors. As for the variable distance to the city center, it does not explain car use. Moreover, some remote areas have many walking trips. This is well understood in the cluster analysis; there are zones far away from the city center but that are dense and well provided for, which work as self-sufficient urban centers. Results reinforce the theories underlying polycentrism as a solution to the urban sprawl challenge. [ABSTRACT FROM AUTHOR]

The Olavide Museum in Madrid, which was founded in the 19th century, preserves one of the most important collections in the world of three-dimensional dermatological models made of polychrome beeswax. These models have been used for the training of numerous generations of dermatologists in Spain. Unfortunately, many of the figures were preserved in precarious conditions during the time that the museum was closed in the middle of the 20th century, and some could not be found after its reopening. In this paper, we show a method for the recovery of a missing model of which only the original plaster cast remains. For this purpose, we use the combination of a structured light scanner and 3D printing, together with traditional techniques, to reproduce a copy of the original cast, in order to prevent its deterioration during the wax casting. As a result of this study, a highly realistic figure was obtained, which represented, in great detail, the small superficial reliefs of the skin lesions, as well as their colour. The conclusion of this research is that it is possible to recreate, with precision, a didactic model in beeswax from its mould, without the need to use the mould in the process, which avoids any risk of deterioration in the process. [ABSTRACT FROM AUTHOR]

Energy efficiency is one of the most important current challenges, and its impact at a global level is considerable. To solve current challenges, it is critical that consumers are able to control their energy consumption. In this paper, we propose using a time series of window-based entropy to detect anomalies in the electricity consumption of a household when the pattern of consumption behavior exhibits a change. We compare the accuracy of this approach with two machine learning approaches, random forest and neural networks, and with a statistical approach, the ARIMA model. We study whether these approaches detect the same anomalous periods. These different techniques have been evaluated using a real dataset obtained from different households with different consumption profiles from the Madrid Region. The entropy-based algorithm detects more days classified as anomalous according to context information compared to the other algorithms. This approach has the advantages that it does not require a training period and that it adapts dynamically to changes, except in vacation periods when consumption drops drastically and requires some time for adapting to the new situation. [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]

The aim of this research is to help public transport managers to make decisions on the type of buses that should compose their public transport fleet, taking into account economic, environmental and social criteria from the point of view of sustainability. This paper fills a knowledge gap by including the social dimension of sustainability in addition to the economic and environmental dimensions. The original nature of this study lies in analyzing complementarities in the structuring of an efficiency and multicriteria problem. Our research analyzes Madrid public bus system data; the problem is structured in a comparative way between two analytical methods, a Data Envelopment Analysis (DEA) and an ELimination Et Choice Translating REality (ELECTRE) III. Our research results show that two main groups of vehicles could play a part in part the theoretical solution. The main conclusions of this research are that (a) plug-in and induction electric vehicles are not comparable to GNC and diesel–hybrid vehicles in terms of cost, pollution and service; and (b) the ELECTRE III model provides more information in solving this problem than the DEA model. [ABSTRACT FROM AUTHOR]

Solar-powered air conditioners offer a high potential for energy-efficient cooling with a high economic feasibility. They can significantly reduce the energy consumption in the building sector, which is essential to meet the greater ambition of reducing greenhouse gas emissions by 80% in the EU by 2050. This paper presents a computational model development capable of simulating the behaviour of a photovoltaic-assisted heat pump in different locations and working conditions. In addition, this model has been used to optimise a solar on-grid air conditioning system. The generated model has been validated with experimental data obtained in a real facility for a whole summer of operation (more than 100 tested days) in a Mediterranean climate (Alicante, Spain). According to the simulation results, the average Energy Efficiency Ratio (EER) of the system is 16.0, 10.7 and 7.8 in Barcelona, Madrid and Seville, respectively. The optimisation analysis has proven that the severity of the climatic region increases the costs as well as the optimum PV power to drive the AC unit. The obtained values for the the PV power and the annualised cost are 400 W and 506.2 € for Barcelona, 900 W and 536.7 € for Madrid, and 1300 W and 564.7 € for Seville. The annualised cost and the CO 2 emission levels are higher for the conventional system (no PV panels) than for the solar on-grid system, regardless of the installed PV power. This difference can be up to 66.64 € (10.55%) and 112.94 kg CO 2 (64.83%) per summer season in the case of Seville. [ABSTRACT FROM AUTHOR]