Search

The following paper proposes a novel machine learning approach to the segmentation of urban housing markets. We extract features from globally available satellite imagery using an unsupervised machine learning model called MOSAIKS, and apply a k-means clustering algorithm to the extracted features to identify sub-markets at multiple intra-urban scales within a case study of Madrid (Spain). To systematically explore scale effects on the resulting clusters, the analysis is repeated with varying sizes of satellite image patches. We assess the resulting clusters across scales using several internal cluster-evaluation metrics. Additionally, we use data from online listings portal Idealista to measure the homogeneity of housing prices within the clusters, to understand how well sub-markets can be differentiated by the image features. This paper evaluates the strengths and weakness of the method to identify urban housing sub-markets, a task which is important for planners and policy makers and is often limited by a lack of data. We conclude that the approach seems useful to divide large urban housing markets according to different attributes and scales. [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]

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]

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities. [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]

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]

The agri-food system needs to transition into a more balanced system that takes into account economic, social, and environmental factors. Young people are a key demographic group to consider as they are open to new trends of consumption, including sustainable buying practices. Public universities can play a significant role in promoting sustainable and healthy eating habits among students. In this paper, we focus on the perceptions of young people regarding sustainable food in the Madrid Region. We conducted a survey using a questionnaire-based approach among 1940 students in 2022. The results highlight that young consumers are highly concerned about food sustainability. They perceive sustainability as local and non-processed foods. However, this perception varies among young consumers, and we identified five different consumer profiles. Principal component analysis and cluster analysis provide insights into potential actions that universities can take to promote sustainable and healthy eating habits among students. [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]

The use of technologies that allow for the utilization of renewable energies wasted around buildings is one of the ways to ensure the decarbonization of the sector. Wastewater from buildings is a renewable source of thermal energy. Groundwater and rainwater are important components of wastewater that flow into sewerage systems. The main objective of this research is to estimate the thermal potential of wastewater for the heating and cooling of buildings. In this paper, an office building with a low-energy system (TABS) was studied for one year to assess the energy contribution of wastewater in a hybrid system that includes geothermal exchangers and a wastewater exchanger. This study shows that wastewater from sewerage systems that flows faster than 5 L/s can make enough heat to power an office building with a power demand of 45 kW (60 W/m2). The energy contribution of wastewater from the sewerage system is more favorable in heating scenarios than in cooling ones, improving the system efficiency by over 22% compared to geothermal systems. Rainwater enhances cooling efficiency by over 14% compared to geothermal systems. This finding could help to establish a predictive method or guidelines for the design and sizing of heat exchangers in sewerage systems. [ABSTRACT FROM AUTHOR]

There is a growing interest in finding new ways to address the difficult task of introducing programming to secondary students for the first time to improve students' computational thinking (CT) skills. Therefore, extensive research is required in this field. Worldwide, new ways to address this difficult task have been developed: visual execution environments and approaches by text programming or visual programming are among the most popular. This paper addresses the complex task by using a visual execution environment (VEE) to introduce the first programming concepts that should be covered in any introductory programming course. These concepts include variables, input and output, conditionals, loops, arrays, functions, and files. This study explores two approaches to achieve this goal: visual programming (using Scratch) and text programming (using Java) to improve CT. Additionally, it proposes an AI recommendation model into the VEE to further improve the effectiveness of developing CT among secondary education students. This integrated model combines the capabilities of an AI learning system module and a personalized learning module to better address the task at hand. To pursue this task, an experiment has been carried out among 23 preservice secondary teachers' students in two universities, one in Madrid, Spain, and the other in Galway, Ireland. The overall results showed a significant improvement in the Scratch group. However, when analyzing the results based on specific programming concepts, significance was observed only in the Scratch group, specifically for the Loop concept. [ABSTRACT FROM AUTHOR]

This paper addresses the Multifunctional and Territorialised Agri-Food Systems (MTLAFS) in areas of direct urban influence, focusing on the metropolitan region of Madrid. MTLAFS are contextualised as alternatives to the hegemonic global model of mass production and consumption. They are created by combining two conceptual and theoretical bodies of knowledge that share many elements: the study of Local Agri-Food Systems (LAFS), a critical approach to agri-food economies and the re-territorialisation of agri-food systems. The paper analyses the factors that negatively affect the resilience of LAFS and it describes re-territorialisation strategies that enable MTLAFS to be built. By using a multi-criteria methodology to identify agri-environmental and food governance indicators, the research identifies and describes the characteristics that allow the case studies selected in the region of Madrid to be classified as MTLAFS. This has been carried out by gathering the main discussion points on the fractures and relocation strategies that accentuate the vulnerability or, on the contrary, enhance the resilience of the cases analysed. The paper concludes with some recommendations for strengthening the socio-ecological resilience of MTLAFS by using the systemic basis provided by the agro-urban project. This agro-urban project brings together different public policies, governance tools, territorial and food planning, as well as agrarian practices anchored to each specific territory. All these agrarian practices contribute to the configuration of an alternative territorial agri-food model that ensures food security and a shift towards the sustainable development of our planet. [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 pay significant attention to the most vulnerable road users (i.e., people with disabilities) when interacting with cyclists. The special needs of these groups are studied by distributing an online questionnaire about their perception and interaction with cyclists besides conducting an on-road experiment to test the possibility of sharing cycling infrastructure with wheelchair users. In an authentic case study, 2 cyclists and 5 wheelchair users were asked to ride their vehicles on a cycling lane in Madrid, in order to evaluate wheelchair users' interaction with cyclists and reaction to the infrastructure by applying objective and subjective measures. The participants were provided with GPS, a speed sensor, and a head-mounted camera to record the experiment. The results show that people with disabilities feel threatened by cyclists who share the sidewalk with them; the respondents to the questionnaire suggested making the sidewalk free of cyclists to avoid conflict and improve safety. Moreover, the outputs of the experiment show positive feedback from wheelchair users when sharing cycling infrastructure regarding the improvement of speed and safety feeling. However, it is recommended to increase the number of wheelchair users to obtain more reliable and generalizable results. [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]

Nature-based solutions (NBS) are becoming popular in urban planning and policy making as cost-effective solutions capable of delivering multiple ecosystem services and addressing several societal challenges. So far, however, the cost-effectiveness of urban NBS projects has not been consistently quantified by built environment professionals, who lack user-friendly tools to account for the environmental costs and benefits of NBS. This paper presents a prototype online decision support tool (NBenefit$®) that calculates the negative and positive environmental impacts, externalities, and financial values of planned urban forests over their entire life cycle. NBenefit$ relies on a modelling framework that combines system dynamics, urban ecology, and life cycle thinking approaches, and it is presented as a visual web-based interface. An online map and a grid of cells is used to map the site of intervention, to delineate the size of the urban forest, and to define variations in abiotic, biotic, and management attributes in each site. Outputs are provided by year, for the entire site and NBS life cycle. The potential value of NBenefit$ as a supporting tool was exemplified with the calculation of 48 urban forest archetypes, a few of which were used to set scenarios for a hypothetical urban forest in Madrid (Spain). The results showcase the impact that decisions taken during the planning, design, or management of an NBS project may have on its long-term performance. Future works will expand the scope of NBenefit$, including other types of urban NBS. [ABSTRACT FROM AUTHOR]

In this paper, we experimented with a set of machine-learning classifiers for predicting the risk of a person being overweight or obese, taking into account his/her dietary habits and socioeconomic information. We investigate with ten different machine-learning algorithms combined with four feature-selection strategies (two evolutionary feature-selection methods, one feature selection from the literature, and no feature selection). We tackle the problem under a binary classification approach with evolutionary feature selection. In particular, we use a genetic algorithm to select the set of variables (features) that optimize the accuracy of the classifiers. As an additional contribution, we designed a variant of the Stud GA, a particular structure of the selection operator of individuals where a reduced set of elitist solutions dominate the process. The genetic algorithm uses a direct binary encoding, allowing a more efficient evaluation of the individuals. We use a dataset with information from more than 1170 people in the Spanish Region of Madrid. Both evolutionary and classical feature-selection methods were successfully applied to Gradient Boosting and Decision Tree algorithms, reaching values up to 79% and increasing the average accuracy by two points, respectively. [ABSTRACT FROM AUTHOR]

The historic water supply to large cities constitutes a constructed heritage characterised by comprising a range of public structures—dams, canals, tanks, siphons and aqueducts—over a large geographical area. Within this international context, this paper looks at the case of Canal de Isabel II (CYII) and its historic infrastructure, built in the second half of the 19th century and the early 20th century. The purpose of this study is to analyse how these water supply public works, which maintain their original use, have also taken on new functions through the conversion of some of their parts and added new values to the existing ones. In order to do this, an inventory was drawn up with the location and cultural value of each structure based on its historic, technological, landscape and symbolic features, as well as its use. The results establish the significance of the overall system, not only in functional terms but also as a cultural resource. It is essential to understand the historic water supply infrastructure as a whole, not just as individual components but rather as pieces of a network. This is also essential for the management and preservation of the system, both where the structures are still in use as part of the water supply and where they have been converted for other uses. [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]

Following a copious and famous snowfall in Madrid city (Spain) and its surrounding area, the tree masses were analysed to assess the impact of this snowfall. In this way, this paper proposes an approach towards urban forest impact inventory mapping as a consequence of the snowfall of January 2021, and the subsequent atmospheric stability, which kept surface temperatures in Madrid close to −10 °C. The study has been carried out using snowfall data from 1920 to 2020 and images from the Sentinel, Landsat and MODIS satellites. The results obtained by means of image changes in the NDVI reveal a clear impact on the trees, with 11% of the winter vegetation cover of the municipality being affected. Especially significant has been the damage detected both in the forest areas in the city and in the parks, gardens or urban roads. [ABSTRACT FROM AUTHOR]

Vehicle-sharing systems—such as bike-, car-, or motorcycle-sharing systems—have become increasingly popular in big cities in recent years. On the one hand, they provide a cheaper and environmentally friendlier means of transportation than private cars, and on the other hand, they satisfy the individual mobility demands of citizens better than traditional public transport systems. One of their advantages in this regard is their availability, e.g., the possibility of taking (or leaving) a vehicle almost anywhere in a city. This availability obviously depends on different strategic and operational management decisions and policies, such as the dimension of the fleet or the (re)distribution of vehicles. Agglutination problems—where, due to usage patterns, available vehicles are concentrated in certain areas, whereas no vehicles are available in others—are quite common in such systems, and need to be dealt with. Research has been dedicated to this problem, specifying different techniques to reduce imbalanced situations. In this paper, we present and compare strategies for recommending stations to users who wish to rent or return bikes in station-based bike-sharing systems. Our first contribution is a novel recommendation strategy based on queuing theory that recommends stations based on their utility to the user in terms of lower distance and higher probability of finding a bike or slot. Then, we go one step further, defining a strategy that recommends stations by combining the utility of a particular user with the utility of the global system, measured in terms of the improvement in the distribution of bikes and slots with respect to the expected future demand, with the aim of implicitly avoiding or alleviating balancing problems. We present several experiments to evaluate our proposal with real data from the bike sharing system BiciMAD in Madrid. [ABSTRACT FROM AUTHOR]

Featured Application: To determine the optimal locations of fire stations considering the risk of system collapse. Recent increases in incidents make it unlikely for emergency systems to be able to meet incident requirements. In this paper, we formulate a new territorial measurement approach for the reliability of fire departments, the collapse index, to help decision makers determine their response capability. This new index expresses the maximum simultaneous workload in a pixel over one year, measured over time. Based on this index, we propose a new fire station (FS) optimum location model by applying the simulated annealing method in conjunction with a geographic information system. The formulation of the cost function as the minimum standard deviation of the FS workload, combined with the constraint that the maximum collapse index in any pixel must be less than a certain threshold, are two contributions of this work. Five optimisation processes are developed to locate between up to five FS and create collapse index maps in the Madrid Region. The maximum collapse index in a pixel with a new FS decreases from its initial value of 10,485 min to 2500 min when five new FS are built. The conclusion is that the proposed optimisation model meets the need for reliability in the emergency services and that the collapse index is a good measure to prevent overlapping in the system. [ABSTRACT FROM AUTHOR]

This research is aimed to analyze textual descriptions of harassment situations collected anonymously by the Hollaback! project. Hollaback! is an international movement created to end harassment in all of its forms. Its goal is to collect stories of harassment through the web and a free app all around the world to elevate victims' individual voices to find a societal solution. Hollaback! pretends to analyze the impact of a bystander during a harassment in order to launch a public awareness-raising campaign to equip everyday people with tools to undo harassment. Thus, the analysis presented in this paper is a first step in Hollaback!'s purpose: the automatic detection of a witness intervention inferred from the victim's own report. In a first step, natural language processing techniques were used to analyze the victim's free-text descriptions. For this part, we used the whole dataset with all its countries and locations. In addition, classification models, based on machine learning and soft computing techniques, were developed in the second part of this study to classify the descriptions into those that have bystander presence and those that do not. For this machine learning part, we selected the city of Madrid as an example, in order to establish a criterion of the witness behavior procedure. [ABSTRACT FROM AUTHOR]

This paper examines the effect of the COVID-19 induced lockdown upon six pollutants, CO, NO, NO2, PM10, PM2.5, and O3, in the Spanish community of Madrid. The paper relies on clustering methods and multiple regression techniques to control for a battery of potential confounding factors. The results show that the nationwide lockdown, decreed on 13 March by the Spanish government, exerted a statistically significant effect upon most pollution indicators. The estimates range from approximately −82% (NO and NO2) to −3% (CO). Reversely, the COVID-19 induced lockdown raised O3 levels by an average of 20%. By using data from 43 stations spread out among the region, the paper provides a local level analysis. This analysis reveals substantial differences across areas and across pollutants. This observation indicates that any successful approach to improve air quality in the region must be multidimensional. [ABSTRACT FROM AUTHOR]

In 2007, the excavation of the M-30 ring road located in Madrid and the creation of a green corridor either side of the Manzanares river brought significant change to the metropolitan area. The corridor and linear park which it provided were designed to contribute to the regeneration of the fluvial ecosystem, establish links among residents on each side of the river and promote cultural and leisure activities. This paper provides a sustainability analysis of the excavation of the M-30 (involving the socio-economic and environmental impact) 14 years after its construction. In order to show such an impact, an analysis of the area both prior to the project and after completion, as well as a hypothetical solution that uses improved materials, has been performed. This entails use of the multi-criteria decision-making model named MIVES (initials in Spanish, modelo integrado de valor para una evaluación sostenible). The MIVES method is based on the application of value functions of sustainability indicators selected by socio-economic and environmental criteria, chosen by experts. Results from analysis showed that the excavation of the M-30 considerably improved the sustainability of the area (sustainable index 3.43 and 6.26 both before and after the excavation works). However, use of improved materials in contrast with the application of conventional materials slightly improved the sustainability of the work (Sustainability Index 6.26 and 6.74, respectively, of the conventional materials). [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the mechanical properties of Robinia pseudoacacia L. (black locust), Platanus × hybrida Brot. (London plane), Ulmus pumila L. (Siberian elm), and Populus alba L. (white poplar), estimated using ultrasound wave equipment (USLab y Sylvatest Duo) and impact wave equipment (Microsecond Timer) on standing trees, felled logs and on specimens obtained from different parts of the trees. Bending strength, axial compression strength and tension parallel to grain were determined for each specimen, in order to subsequently correlate the strength and stiffness with the acoustic properties determined in the standing tree. For the relationship between the static modulus of elasticity of the specimens and the dynamic modulus of elasticity determined in standing trees using the USLab, coefficients of determination were found to be between 0.30–0.92, between 0.52 and 0.80 using the Sylvatest Duo and between 0.60 and 0.94 with the Microsecond Timer. It would be necessary to determine whether the removal of bark for the correct coupling of the ultrasonic sensors would provide an entry route for pests or diseases that could affect the health of the tree. [ABSTRACT FROM AUTHOR]

While variation in the southern Peninsular Spanish affricate /tʃ/ has been considered in the context of deaffrication to [ʃ], this study examines an emergent variant [ts] in the context of sociolinguistic identity and style in political speech. Based on a corpus of public speech from Madrid and Andalusia, Spain, this study examines the phonetic and sociolinguistic characteristics of the affricate, finding variation in the quality of the frication portion of the segment through an analysis of segment duration (ms), the center of gravity (Hz), and a categorical identification of realization type. The results suggest that both linguistic variables, like phonetic environment, stress, lexical frequency, and following vowel formant height, as well as extralinguistic variables, like speaker city, gender, political affiliation, and speech context, condition use. Based on these findings, it appears that production of the alveolar affricate [ts] is an incipient sociolinguistic marker in the process of acquiring social meaning. It is particularly associated with female speech and prestige norms that transcend regional identification. This alveolar variant serves as an additional sociolinguistic resource accessible for identity development among politicians and offers insight into ongoing change in the affricate inventory of southern and northern-central Peninsular Spanish. [ABSTRACT FROM AUTHOR]

Managed aquifer recharge (MAR) is part of the palette of solutions to water shortage, water security, water quality decline, falling water tables, and endangered groundwater-dependent ecosystems. It can be the most economic, most benign, most resilient, and most socially acceptable solution, but frequently has not been implemented due to lack of awareness, inadequate knowledge of aquifers, immature perception of risk, and incomplete policies for integrated water management, including linking MAR with demand management. MAR can achieve much towards solving the myriad local water problems that have collectively been termed "the global water crisis". This special issue strives to elucidate the effectiveness, benefits, constraints, limitations, and applicability of MAR, together with its scientific advances, to a wide variety of situations that have global relevance. This special issue was initiated by the International Association of Hydrogeologists Commission on Managing Aquifer Recharge to capture and extend from selected papers at the 10th International Symposium on Managed Aquifer Recharge (ISMAR10) held in Madrid, Spain, 20–24 May 2019. [ABSTRACT FROM AUTHOR]

Innovation in the beer market focuses on research into the different ingredients that make up this popular and sought-after beverage. Some of these innovations have focused on the use of autochthonous ingredients, which bring added value to products, reduce production costs and environmental impact, and provide beers with special organoleptic characteristics. This study focuses on the use of autochthonous ingredients from the Community of Madrid and the design of four recipes that are suited to these ingredients and consumer demand. In terms of the ingredients used, the micromalting of barley grown in the CM was carried out, while hops (Cascade variety for bittering hops and wild hops Rayo verde Tajuña and Torreta Tajuña for aroma) and yeast strains (Saccharomyces cerevisiae G 520 and G 354) were selected from previous studies, which were also sourced from the CM. For the barley malt, parameters such as protein content were determined, which was at the maximum limit but did not affect the final quality of the beers. The content of α- and β-acids in the hops was also determined, being higher in the Cascade variety. Different physicochemical analyses (GC, aromatic compounds, bitterness, colour, SO2, polyphenols, and antioxidant capacity) were carried out to determine the quality of the beers obtained from the four recipes designed, as well as tastings by a panel of experts and consumers. Finally, two recipes were rated the best by a panel of experts and consumers, where the cereal, hop, and fruit flavours stood out for their aromatic profile. [ABSTRACT FROM AUTHOR]

In this study, a total of 34 Spanish minority varieties were studied during four seasons from 2020 to 2023, and their behavior was characterized according to their main phenological stages (bud break, bloom, veraison, and maturity) and complete cycle. We focused on the varieties prospected in the central Spanish plateau and conserved in the "El Encín" grapevine collection, aiming to identify the potential for adaptation of these varieties and for them to be considered by winegrowers as an alternative to current climate change conditions. The growing degree days required for the expression of the phenological stage, and the duration of each stage, were compiled. Characteristics of oenological interest were also monitored, such as °Brix, pH, and titratable acidity in must at the time of harvest. This study was carried out in years with atypical snowfall and cold spells (winter 2021), as well as with heat waves (summer 2022), with average temperatures 3–5 °C higher than normal and absolute maximum temperatures over 40 °C. Both cases also exceeded records of historical series (1957–2019). Veraison has been identified as the stage most susceptible to damage from high temperatures, in addition to the maturation and duration of the complete cycle. The varieties were classified into five groups according to the duration of each phenological stage (very early, early, medium, late, and very late). Some varieties with late or very late maturation and with must characteristics of 20–23 °Brix, 3–5 g/L of titratable acidity, and pH 3.5–4.5, as well as others, retained stability in their phenological periodicity and must quality. The results suggest that special attention should be given to thoroughly evaluating these varieties, and that the strategies contemplated should be considered as a feasible cultivation alternative in viticulture to mitigate the effects of climate change. [ABSTRACT FROM AUTHOR]

The variety of types that appear in kidney stones makes it necessary to describe them to try to understand their formation. The crystalline phases recognized in stones are classified according to their chemical composition. For this reason, a study using X-ray microdiffraction, Raman spectroscopy, SEM/EDX analysis, and cathodoluminescence (CL) is recommended, to identify their composition. In the present study, this was carried out on kidney stones collected from surgeries in hospitals from Spain. The samples were collected in two representative urban centers: one from a large city, Madrid; the other with a mostly rural population, in order to contrast the possible compositions of the kidney stones. In large cities, struvite appears more frequently, although calcium oxalates are very common in both areas. An attempt was made to provide a guide to the most frequent phases, accompanied by four analysis methods that make their identification possible. [ABSTRACT FROM AUTHOR]

In this work, an intelligent hybrid model is proposed to identify hazardous or inattentive driving manoeuvres on roads, with the final goal being to increase and ensure travellers' safety and comfort. The estimation is based on the effects that road geometry may have on vehicle accelerations, displacements and dynamics. The outputs of the intelligent systems proposed are how the type of driving can be characterized as normal, careless or distracted. The intelligent system consists of an LSTM (Long Short-Term Memory) neural network in a first step that distinguishes between normal and abnormal driving behaviour and then a second module that classifies abnormal forms of driving as aggressive or inattentive, with the latter implemented with another LSTM, a CNN (convolutional neural network) or the Hotelling transform. They are applied to some of the characteristics of vehicle dynamics to estimate the driving behaviour. Smartphone inertial sensors such as GPS, accelerometers and gyroscopes are used to measure these vehicle characteristics and to identify driving events in manoeuvres. Specifically, the critical acceleration due to the influence of the road geometry can be measured with inertial sensors, and then, this road acceleration with the lateral acceleration allows us to estimate the driver's perceived acceleration. This perceived acceleration affects the driving style and, consequently, the estimation of the appropriate speed to travel on that road. There is use of both a traditional two-lane and a motorway route located in the Madrid region of Spain. Driving behaviour is determined by considering how changes in road geometry may affect one's driving style and, consequently, the estimation of the proper speed. The results obtained with some of the proposed configurations of the intelligent hybrid system reach an accuracy of 97.21% in detecting dangerous driving or driving with a certain risk. This could allow generating real-time alerts for potentially dangerous or inattentive manoeuvres, leading to safer and more appropriate driving. [ABSTRACT FROM AUTHOR]

This article describes the objects in the barniz de Pasto collection at the Museo de América, Madrid. The barniz de Pasto technique will be described, as well as the historical documentary sources that have previously discussed this varnish. The article will also mention the historical reasons why Spain is the European country in which the greatest number of objects decorated with varnish have been found, in both religious and private collections. The main body of the article discusses all the barniz de Pasto objects held in the Museum collection, focuses on the history of their arrival at the Museum, and investigates their possible origin, with the help of ample photographs. The final section examines the Museum's three most recent acquisitions, completed in the second half of 2022, in detail. [ABSTRACT FROM AUTHOR]

Simple Summary: The rise of drug-resistant bacteria, particularly in animals, poses a major challenge in veterinary medicine. Antibiotic development lags behind the increasing resistance. To tackle this, alternative therapies have been explored, such as the use of natural products and plant extracts. This study evaluates the laboratory efficacy of plant derivatives of the Alliaceae group (which includes garlic and onion) as antimicrobial agents, with encouraging results. Although further research is needed, these findings suggest a potential role for these natural compounds in veterinary medicine. Background: The increase of multi-resistant bacteria, especially Staphylococcus spp. and Enterobacteriaceae, constitutes a challenge in veterinary medicine. The rapid growth of resistance is outpacing antibiotic discovery. Innovative strategies are needed, including the use of natural products like Allium species (Allium sativum L. and Allium cepa L.), which have been used empirically for centuries to treat infectious diseases in humans and farm and aquaculture animals due to their antibacterial properties. Methods: This study aimed to evaluate the in vitro activity of two Allium-derived compounds, propyl propane thiosulfinate (PTS) and propyl propane thiosulfonate (PTSO), against multi-resistant Staphylococcus spp. (n = 30) and Enterobacteriaceae (n = 26) isolated from dogs referred to a veterinary teaching hospital in Madrid. Results and Discussion: The results indicated the in vitro efficacy of PTSO/PTS against the tested bacterial strains, and 56.7% of Staphylococcus pseudintermedius and 53.8% of Enterobacteriaceae showed sensitivity to PTS and PTSO compared with classic antibiotics. In addition, 50% of S. pseudintermedius strains resistant to erythromycin, ibofloxacin, difloxacin and orbifloxacin and 50% of Enterobacteriaceae strains resistant to tetracycline and doxycycline were sensitive to PTS and PTSO. Although studies are needed to verify their efficacy in vivo, the combined use of PTS and PTSO exhibits promise in enhancing bacterial sensitivity against S. pseudintermedius and Enterobacteriaceae infections, providing a first insight into the potential of both compounds in veterinary practice. [ABSTRACT FROM AUTHOR]

The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses. [ABSTRACT FROM AUTHOR]

Starting from the contribution of such thinkers as the famous Giordano Bruno (1583) and the great mathematician and physicist Henri Poincaré (1889) and the surprising discovery of the meteorologist Edward Lorenz (1963), we consider the expansion of the mathematics of chaos in this article, paying attention to topology, qualitative geometry, and Catastrophe Theory, on the one hand, and addressing the possibilities derived from the new Computer Science as Quantum Algorithms and the advances in Artificial Intelligence, on the other. We especially highlight the section on computing chaos, which we consider to be new calculation and analysis instruments, such as machine learning and its algorithm called reservoir computing, through which we can know the dynamics of a chaotic system. With past data, with equations like Karamoto–Sivashinsky, one can improve predictions of the system eight times further ahead than in previous methods. Integrating the machine learning approach and traditional model-based prediction, one could obtain accurate predictions twelve Lyapunov times. As we know, in the framework of chaos theory, it is habitually accepted that the idea of long-term prediction seems impossible because we live under a veil of uncertainty. But with technological advances, the landscape begins to change, both in chaos theory and in its applications, especially in the field of economics, to which we devote particular attention, carrying out as an example the analysis of the evolution of the Madrid Stock Exchange in the 2006–2013 crisis. Above all this, a reflection of a general nature is necessary to enlighten us on the possibility of opening a new horizon. [ABSTRACT FROM AUTHOR]

Limited evidence has verified if ultrasound imaging (US) can detect post-exercise muscle damage based on size, shape, and brightness metrics. This study aimed to analyze the correlation between creatine kinase (CK) concentration and (as a biomarker of muscle damage) changes in US gray-scale metrics after an exercise-induced muscle damage protocol. An observational study was conducted at a private university lab located in Madrid. Twenty-five untrained and asymptomatic volunteers were enrolled in this study. Baseline demographic data and body composition metrics were collected. In addition, the rectus femoris US data and CK concentration were assessed at baseline and after inducing muscle damage (24 and 48 h later). After calculating time differences for all the outcomes, the correlation between the changes observed with US and biomarkers was assessed. Significant CK concentration increases were found 24 h (p = 0.003) and 48 h (p < 0.001) after exercise. However, no significant changes in muscle size, shape, or brightness were found in any location (p > 0.05 for all). In addition, no significant associations were found between CK changes and US changes (p > 0.05 for all). Gray-scale US is not a sensitive tool for detecting muscle damage, as a protocol of exercise-induced muscle damage confirmed with CK produced no significant gray-scale US changes after 24 or 48 h. In addition, US and CK changes after 24 and 48 h were not associated with each other. [ABSTRACT FROM AUTHOR]

In her triple condition of emigrant, artist and woman, the work of Spanish filmmaker Chus Gutiérrez is a privileged and singular object of study. Through her filmography it is possible to approach the changes that have taken place in the cities on both sides of the Atlantic. Chus Gutiérrez resided in New York during the decade of the 1980s and returned to Madrid to witness the changes that this city was undergoing: from being the epicenter of a dictatorship to a democratic city. Her vision of both places is clearly reflected in two of her films: Sublet (1992) and El Calentito (2005). The protagonists profiled by Chus Gutiérrez in these films are young women who move through complex metropolitan spaces at a critical moment of their lives. Cities become another character, illustrating, pushing, or limiting their course; spaces in which the protagonists accept their differences and begin the search for their individual and collective identity. [ABSTRACT FROM AUTHOR]

This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users' experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public. [ABSTRACT FROM AUTHOR]

Mumps is a vaccine-preventable disease caused by the mumps virus (MuV). However, MuV has re-emerged in many countries with high vaccine coverage. The World Health Organization (WHO) recommends molecular surveillance based on sequencing of the small hydrophobic (SH) gene. Additionally, the combined use of SH and non-coding regions (NCR) has been described in different studies, proving to be a useful complement marker to discriminate general patterns of circulation at national and international levels. The aim of this work is to test local-level usefulness of the combination of SH and MF-NCR sequencing in tracing hidden transmission clusters and chains during the last epidemic wave (2015–2020) in Spain. A database with 903 cases from the Autonomous Community of Madrid was generated by the integration of microbiological and epidemiological data. Of these, 453 representative cases were genotyped. Eight different SH variants and thirty-four SH haplotypes were detected. Local MuV circulation showed the same temporal pattern previously described at a national level. Only two of the thirteen previously identified outbreaks were caused by more than one variant/haplotype. Geographical representation of SH variants allowed the identification of several previously undetected clusters, which were analysed phylogenetically by the combination of SH and MF-NCR, in a total of 90 cases. MF-NCR was not able to improve the discrimination of geographical clusters based on SH sequencing, showing limited resolution for outbreak investigations. [ABSTRACT FROM AUTHOR]

We have studied the interference caused by amplitude and phase distortions induced by rain in ultra-wideband communication systems designed for using amplitude modulation in GeoSurf future satellite constellations. The results concern radio links simulated with the synthetic storm technique at Spino d'Adda (Italy), Madrid (Spain) and Tampa (Florida), which are sites located in different climatic regions. The conclusions are (a) the three sites, although in different climatic zones, are practically indistinguishable; (b) the channel signal-to-noise ratio can be increased or decreased by interference with equal probability. Channel theoretical capacity loss, even in the worst case, is very limited and rain, therefore, does not cause significant linear distortions in ultra-wideband channels at millimeter waves; therefore, these channels could be used at millimeter waves. [ABSTRACT FROM AUTHOR]

Airborne pollen monitoring datasets sometimes exhibit gaps, even very long, either because of maintenance or because of a lack of expert personnel. Despite the numerous imputation techniques available, not all of them effectively include the spatial relations of the data since the assumption of missing-at-random is made. However, there are several techniques in geostatistics that overcome this limitation such as the inverse distance weighting and Gaussian processes or kriging. In this paper, a new method is proposed that utilizes convolutional neural networks. This method not only shows a competitive advantage in terms of accuracy when compared to the aforementioned techniques by improving the error by 5% on average, but also reduces execution training times by 90% when compared to a Gaussian process. To show the advantages of the proposal, 10%, 20%, and 30% of the data points are removed in the time series of a Poaceae pollen observation station in the region of Madrid, and the airborne concentrations from the remaining available stations in the network are used to impute the data removed. Even though the improvements in terms of accuracy are not significantly large, even if consistent, the gain in computational time and the flexibility of the proposed convolutional neural network allow field experts to adapt and extend the solution, for instance including meteorological variables, with the potential decrease of the errors reported in this paper. [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]

Current evidence suggests that a group of patients who had survived coronavirus disease, 2019 (COVID-19) and developed post-COVID pain can exhibit altered nociceptive processing. The role of serological biomarkers and hospitalization treatments in post-COVID pain is unclear. This study aimed to investigate the association of serological biomarkers and treatments received during hospitalization with sensitization-associated symptoms in COVID-19 survivors with post-COVID pain. One hundred and eighty-three (n = 183) patients who had been hospitalized due to COVID-19 in one urban hospital of Madrid (Spain) during the first wave of the pandemic were assessed in a face-to-face interview 9.4 (SD 3.4) months after hospitalization. Levels of 19 serological biomarkers, hospitalization data, and treatments during hospitalization were obtained from hospital records. Sensitization-associated symptoms (Central Sensitization Inventory, CSI), sleep quality (Pittsburgh Sleep Quality Index, PSQI), pain catastrophism (Pain Catastrophizing Scale), and anxiety/depressive level (Hospital Anxiety and Depression Scale, HADS) were assessed. The prevalence of post-COVID pain was 40.9% (n = 75). Twenty-nine (38.6%) patients had sensitization-associated symptoms. Overall, no differences in hospitalization data and serological biomarkers were identified according to the presence of sensitization-associated symptoms. The analysis revealed that patients with sensitization-associated symptoms exhibited higher lymphocyte count and lower urea levels than those without sensitization-associated symptoms, but differences were small. Pain catastrophism and depressive levels, but not fatigue, dyspnea, brain fog, anxiety levels, or poor sleep, were higher in individuals with sensitization-associated symptoms. In conclusion, this study revealed that sensitization-associated post-COVID pain symptoms are not associated with serological biomarkers at hospital admission and hospitalization treatments received. [ABSTRACT FROM AUTHOR]

The Leadership in Energy and Environmental Design for Existing Buildings (LEED-EB) version 3 (v3) and version 4 (v4) gold-certified office space certification strategies in Spain have not yet been studied. The two purposes of this study were to evaluate (1) the impact of high or low achievements in the energy and atmosphere (EA) "optimize energy performance" credit (EAc1 for v3 and EAc8 for v4) on the compensation strategy for LEED "compensation group" credits and (2) the impact of EAc1-v3 or EAc8-v4 on the monotonic change in LEED "compensation group" credits. Data on a total of 77 LEED-EB v3 and 43 LEED-EB v4 gold-certified office space projects were collected. In the v3 group, 26 LEED-certified projects had the highest EAc1 achievements (v3 group 1), and 26 LEED-certified projects had the lowest EAc1 achievements (v3 group 2). In the v4 group, 15 LEED-certified projects had the highest EAc8 achievements (v4 group 1), and 15 LEED-certified projects had the lowest EAc8 achievements (v4 group 2). The exact Wilcoxon–Mann–Whitney test and Fisher's exact 2 × 2 with Lancaster's correction test were used to estimate the difference between groups 1 and 2. Spearman's rank-order correlation was used to assess monotonic change in LEED credits. The results show that v3 and v4 group 1 outperformed v3 and v4 group 2 in EAc1 and EAc8 (p < 0.0001, respectively). However, v3 and v4 group 2 outperformed v3 and v4 group 1 in "renewable energy" (EAc4 for v3 and EAc6 for v4, p = 0.0039 and 0.0088, respectively) and "building commissioning" (EAc2.2 for v3, p = 0.0015; EAc3 for v4, p = 0.0560, respectively). EAc1-v3 and LEED v3 "compensation group" credits showed a moderate negative correlation (rs = −0.53 and p < 0.0001). EAc8-v4 and LEED v4 "compensation group" credits showed a strong negative correlation (rs = −0.74 and p < 0.0001). As a result, increasing the share of renewable energy and performing building commissioning in LEED-EB v3- and v4-certified projects occurred only as a compensation strategy in response to the low achievement in the "optimize energy performance" credit. [ABSTRACT FROM AUTHOR]

Keratoconus is a corneal dystrophy that is one of the main causes of corneal transplantation and for which there is currently no effective treatment for all patients. The presentation of this disease in pediatric age is associated with rapid progression, a worse prognosis and, in 15–20% of cases, the need for corneal transplantation. It is a multifactorial disease with genetic variability, which makes its genetic study difficult. Discovering new therapeutic targets is necessary to improve the quality of life of patients. In this manuscript, we present the results of whole-exome sequencing (WES) of 24 pediatric families diagnosed at the University Hospital La Paz (HULP) in Madrid. The results show an oligogenic inheritance of the disease. Genes involved in the structure, function, cell adhesion, development and repair pathways of the cornea are proposed as candidate genes for the disease. Further studies are needed to confirm the involvement of the candidate genes described in this article in the development of pediatric keratoconus. [ABSTRACT FROM AUTHOR]

The current experiment employs a variational pragmatics perspective to explore how the contextual variables of power, distance, and imposition jointly affect social groups' and individuals' choice of verb forms in requests in Madrid, Spain. Using a mixed-method approach to explore the requests of 111 Spanish speakers from Madrid, quantitative analyses determined the level of significance and hierarchical order of the predictor variables of power, distance, and imposition on verb form and also the distribution of verb forms by gender, with male and female participants exhibiting significant differences. Additionally, certain participants demonstrated decreased sensitivity to contextual factors, adopting more categorically indirect or direct request strategies. The examination of both gendered request patterns and the stances that single participants adopt through their verb-form selections contributes to our understanding of the social moves that are made by all speakers, not just those who fall within the gendered norms. The results highlight the different frames and social meanings attached to these forms at the micro- and macro-social levels, providing new insight into the complex relationship among linguistic variables, contextual factors, and social groups and individuals. [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]