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A special‐purpose Committee on DNA Sequences as Types was established at the XIX International Botanical Congress (IBC) in Shenzhen, China, in 2017, with a mandate to report to the XX IBC in Madrid in 2024 with recommendations on a preferred course of action with respect to potential amendments of the International Code of Nomenclature for algae, fungi, and plants to allow DNA sequences as types. This is the first in an expected series of papers from the Special‐purpose Committee on this issue. We set out the background to the establishment of the Committee, explore key issues around typification that are pertinent to the question of DNA sequences as types, enumerate pros and cons of allowing DNA sequences as types, and foreshadow options for future discussion and potential recommendations. [ABSTRACT FROM AUTHOR]

What a huge relief and what great joy for all of us to be able to meet again in person after the two and a half years that had elapsed since the XXIst International Federation of Psychoanalytic Societies (IFPS) Forum held in Lisbon on February 5-8, 2020, with the beginning of the pandemic lockdown only about one month later! I enjoyed the very high quality of Juan Rodado's clinical work, the epistemological sophistication of Professor Rodríguez Sutil (see also Rodríguez Sutil, [12]), and the good articulation of clinical and epistemological aspects in the paper by Romulo Aguillaume. The Forum was also meant to celebrate the 60th anniversary of the foundation of IFPS (in Amsterdam on July 30, 1962), one of the topics of the historical panel that took place on the Friday morning. This featured two parallel panels, one central panel, and two final parallel panels. [Extracted from the article]

Copyright of Investigaciones Historicas is the property of Universidad de Valladolid, Facultad de Filosofia y Letras and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Documenta & Instrumenta is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Hospitality & Tourism Technology is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Place-based accessibility measures communicate the potential interaction with opportunities at a zone that populations can access. Recent research has explored the implications of how opportunities are counted by different accessibility methods. In conventional measures, opportunities are multiply counted if more than one zone offers access to the same opportunity. This multi-count of opportunities leads to values of accessibility that are difficult to interpret. A possible solution to enhance the meaning-making of accessibility results is by constraining the calculations to match a known quantity. This ensures all zonal values sum up to a predetermined quantity (i.e., the total number of opportunities). In this way, each value can be meaningfully related to this total. A recent effort that implements this solution is spatial availability, a singly-constrained accessibility measure. In this paper, we extend spatial availability for use in the case of multiple modes or more generally, heterogeneous population segments with distinct travel behaviors. After deriving a multimodal version of spatial availability, we proceed to illustrate its features using a synthetic example. We then apply it to an empirical example of low emission zones in Madrid, Spain. We conclude with suggestions for future research and its use in evaluating policy interventions. [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]

The growth of the International Baccalaureate (IB) worldwide is part of a global trend towards the internationalisation of education (IE). Its implementation, nonetheless, takes different forms depending on national and local contexts. This paper examines the recent expansion of the IB in Madrid, drawing upon the sociology of education policy enactments and recontextualisations and the Cultural Political Economy approach. Combining in-depth interviews, document analysis and secondary quantitative data, this paper shows why Madrid has led the expansion of IB schools in Spain in the last decade, an expansion, which has nonetheless remained relatively unnoticed. Our findings suggest that the growth and penetration of private international education initiatives such as the IB may be related to particular social factors, education system characteristics and education policy ensembles, with a particularly intense manifestation in decentralised systems where neoliberal and neoconservative policies foster autonomy, competition, internationalisation and 'excellence'. [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 document is an introduction to a special issue of the journal SERIEs, which is dedicated to honoring the influential economist Manuel Arellano. The special issue follows a conference held in Madrid in 2022, where presentations were given by past and present co-authors of Arellano. Arellano, a renowned econometrician, has made significant contributions to panel data econometrics and empirical microeconomics. The special issue includes a collection of research articles that showcase the breadth and impact of Arellano's work. The document also expresses gratitude to those involved in organizing the conference and the special issue. [Extracted from the article]

The paper attempts to investigate the capacity of agroecological cooperative supermarkets in Spain to promote scaling of food products by means of a double perspective. We first employ a vertical scaling approach to analyze the issues affecting the governance and collective organization of the Cooperative Supermarket Network (CSN), set up in May 2022 and comprising eleven Spanish supermarkets. Secondly, we employ a perspective of horizontal scaling to investigate the potential for increased numbers of members, as well as the geographic and sociodemographic variables at play which limit the abovementioned scaling: to this end we use the case study of the cooperative supermarket La Osa, opened in Madrid in December 2020. We adopt a methodology based on participatory action research throughout the years 2022 and 2023, in which the research team was involved in the real processes of creation and development of the CSN or of La Osa. The study confirms the hypothesis that agroecological cooperative supermarkets constitute a formula for efficient retail distribution for scaling sustainable food in Spain. As opposed to the first-generation options for responsible consumption, these supermarkets appear to contribute to generating significant economies of scale and scope. In terms of vertical scaling, joint provision of services, as well as the gaining of political influence in society, constitute the main advantages in relation to the functioning of the CSN. While the recruitment of new members has heretofore been considered a priority in horizontal scaling, particular emphasis should also be placed on loyalty strategies targeting existing members. [ABSTRACT FROM AUTHOR]

This paper examines the impact of the arrival of Airbnb on local consumption amenities in Madrid. We exploit the exogenous variation created by the timing and uneven distribution of Airbnb listings in the city to determine the impact on food and beverage establishments. Using an instrumental variable strategy, we find positive local effects on both the number of restaurants and their employees: an increase of 14 Airbnb rooms in a given census tract leads to almost one more restaurant, and the same increase in a given neighborhood generates 11 new tourist‐related employees. The results are robust to the specification and sample composition. This paper contributes to the literature on the economic impact of the platform economy on urban areas by providing evidence of market expansion externalities from short‐term rentals. [ABSTRACT FROM AUTHOR]

Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suffering a hypoglycemia (low value) event and, moreover, that the event will be prolonged in time. It is crucial to predict hyperglycemia (high value) and hypoglycemia events that may cause health damages in the short term and potential permanent damages in the long term. This paper describes our research on predicting hypoglycemia events at 30, 60, 90, and 120 minutes using machine learning methods. We propose using structured Grammatical Evolution and dynamic structured Grammatical Evolution to produce interpretable mathematical expressions that predict a hypoglycemia event. Our proposal generates white-box models induced by a grammar based on if-then-else conditions using blood glucose, heart rate, number of steps, and burned calories as the inputs for the machine learning technique. We apply these techniques to create three types of models: individualized, cluster, and population-based. They all are then compared with the predictions of eleven machine learning techniques. We apply these techniques to a dataset of 24 real patients of the Hospital Universitario Principe de Asturias, Madrid, Spain. The resulting models, presented as if-then-else statements that incorporate numeric, relational, and logical operations between variables and constants, are inherently interpretable. The True Positive Rate and True Negative Rate metrics are above 0.90 for 30-minute predictions, 0.80 for 60 min, and 0.70 for 90 min and 120 min for the three types of models. Individualized models exhibit the best metrics, while cluster and population-based models perform similarly. Structured and dynamic structured grammatical evolution techniques perform similarly for all forecasting horizons. Regarding the comparison of different machine learning techniques, on the shorter forecasting horizons, our proposals have a high probability of winning, a probability that diminishes on the longer time horizons. Structured grammatical evolution provides advanced forecasting models that facilitate model explanation, modification, and retesting, offering flexibility for refining solutions post-creation and a deeper understanding of blood glucose behavior. These models have been integrated into the glUCModel application, designed to serve people with diabetes. [ABSTRACT FROM AUTHOR]

Context. Problem of traffic prediction in a city is closely connected to the tasks of transportations in a city as well as air pollution detection in a city. Modern prediction models have redundant complexity when used for separate stations, require large number of measuring stations, long measurement period when predictions are made hourly. Therefore, there is a lack of method to overcome these constraints. The object of the study is a city traffic. Objective. The objective of the study is to develop a method for traffic prediction, providing models for traffic quantification at measuring stations in the future under data and resource constraints. Method. The method for agent-oriented traffic prediction under data and resource constraints was proposed in the paper. This method uses biLSTM models with input features, including traffic data obtained from agent, representing target station, and other agents, representing informative city stations. These agents are selected by ensembles of decision trees using Random Forest method. Input time period length is proposed to set using autocorrelation data. Results. Experimental investigation was conducted on traffic data taken in Madrid from 59 measuring stations. Models created by the proposed method had higher prediction accuracy with lower values of MSE, MAE, RMSE and higher informativeness compared to base LSTM models. Conclusions. Obtained models as study results have optimal number of input features compared to the known models, do not require complete system of city stations for all roads. It enables to apply these models under city traffic data and resource constraints. The proposed solutions provide high informativeness of obtained models with practically applicable accuracy level. [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]

The aim of this work is to analyze the applicability of a convex hyperbola chart's methodology to determine how many pumps should be working in a pumping station of a real case study to consume the least amount of energy. The applicability of the convex hyperbola charts is demonstrated, its effectiveness is shown, and a step-by-step exemplification is presented. Moreover, the order in which pumps should be activated is analyzed and discussed. The pumping station of the optimization is located in Tres Cantos, Madrid, Spain; it consists of a pumping station of four (+1 reserved) hydraulic pumps that take water from a reservoir and distribute it through a branched pipeline. The geometric height difference Hg of the case study is variable. This article also shows how the variability of Hg plays a major role in the optimal configuration of the pumping station. This paper also proves how the number of pumps to activate or disactivate does not necessarily need to be consecutive, meaning that activating or disactivating pumps one by one may not be the best solution. The convex hyperbola charts show how there can be circumstances in which skipping a certain number of pumps is the best solution. How the pump efficiency is distributed along the commercial pump plays a major role in determining which is the best configuration of active pumps. A straightforward and inexpensive optimization methodology for the optimization of the energy in a water supply system was proved and exemplified. This simple methodology can be applied by engineers in the operation of a water supply system when pumping is required, e.g., in agricultural systems or in underdeveloped areas where energy expenses need to be considered. [ABSTRACT FROM AUTHOR]

Ambitious goals to combat pollution should be supported in policies that discourage the use of private cars, notably old and more polluting vehicles. Price signals, such as a congestion tax, and traffic restrictions, such as low-emission zones (LEZ), are widely used tools among European cities to limit car use. In this paper, we look at the dissuasive effect of the implementation of the Madrid Central LEZ and analyze how traffic intensity has been affected in both the restricted area and in other zones of the city. Although the ultimate policy goal of LEZ is to reduce pollution, the instrument considered is traffic limitations, so it is important to know whether or not traffic intensity has been affected by traffic restrictions. Despite its limited extension and the adoption of long transitional periods, the LEZ of Madrid has been seriously questioned from its inception. The results show that traffic intensity has been reduced in the Madrid Central zone but has unfortunately increased in bordering areas. Previous studies on the effects of Madrid Central have not taken into account this potential substitution effect. The future design of a mobility policy in the metropolitan area of Madrid should address this undesirable outcome. [ABSTRACT FROM AUTHOR]

'Claudia' is neither a real name nor an owner who puts a room at the service of the collaborative economy. It is a pseudonym used by a transnational company which manages short-rentals apartments: 211 Airbnb listings in Madrid, 138 of which are in the city centre. This paper's main arguments are based on the fact that Madrid city centre is experiencing a process of airbnbisation which is driven by professional actors specialized in the short-term rental business. The analysis of this model includes an in-depth examination of the professionalization, concentration and monopolization of Airbnb in Madrid, from a temporal and territorial perspective. The paper concludes that Airbnb in Madrid is dominated by professional actors specialized in the business of renting apartments as short-term rentals, who mainly operate within the city's Central District, and whose activity does not comply with the principles of the sharing economy. This model has more to do with traditional forms of accommodation than with new hospitality models based on the sharing economy principles, and generates negative impacts on the economic sustainability of the city and its inhabitants. [ABSTRACT FROM AUTHOR]

A further gift is a translation of Cajal's paper, originally in French, which was presented at the XIV Concilium Ophtalmologicum, Madrid (Ramón y Cajal [6]). La Retina de los Vertebrados: Santiago Ramón y Cajal. The original work has been made available as translations into German (Ramón y Cajal [5]) and English (Ramón y Cajal [8], [9]), with some supplements by Cajal himself ([5]) and by the translators. The original French version, with supplements, was reprinted late in Cajal's life for the opening of the XIV Concilium Ophtalmologicum in Madrid (Ramón y Cajal [7]). [Extracted from the article]

Copyright of Hipogrifo: revista de literatura y cultura del siglo de oro is the property of Hipogrifo: revista de literatura y cultura del siglo de oro and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

This paper focuses on the visual representation of "the urban people" by the Spanish leftwing populist party Unidas Podemos (UP) during the campaign for regional elections in Madrid in 2021. The political environment was characterised by increasing polarisation and the hyper-leadership of two candidates, right-wing Isabel Díaz Ayuso and UP's national leader Pablo Iglesias. In this context, UP employed a diverse range of images and audiovisual material with a specific focus on the urban dimension. This paper explores how the populist logic and societal split--the people vs. the elite--deployed by UP are visually represented and connected with the urban space. Drawing on the central role of images in politics, this paper contributes to the emerging scholarship on the visual and spatial dimensions of populism by (a) exploring the connections between populist imaginary, space, and the visual; (b) advancing an empirical analysis of the image of "the people" in a left-wing political party; and (c) connecting the imaginary of populism to its geo-graphical dimension, stressing both the urban and class divide. [ABSTRACT FROM AUTHOR]

The platform economy is an ecosystem of algorithmically-organised social–technical relationships. In the specific area of home food delivery via digital platforms, algorithmic mediation motivates agents to act in specific ways based on algorithmic logic, creating a distinct form of subjectivity. Based on an ethnography carried out with delivery riders in the City of Madrid (Spain) between 2021 and 2023, in this paper we explore the concept of participatory subjectivity, proposing a distinction between three categories: (a) systems in which the delivery worker seeks algorithmic recognition, (b) systems in which users act in such a way as to be ignored by the algorithm and (c) systems in which it is the design of the algorithms themselves that fosters participation by users. We believe that the concept of participatory subjectivity contributes to the debate on algorithmic mediation in the platform economy, while also affording new perspectives on its effects on workers. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify potential causal relationships between macroeconomic variables and the stock market in Spain. Numerous articles recognize the influence of macroeconomic variables on the stock market and value this knowledge as essential for good investment management. However, there are very few empirical studies that justify the influence of disaggregated macroeconomic variables on the stock market in Spain and vice versa. This article uses the general index of the Madrid Stock Exchange as a proxy variable of the stock market and numerous macroeconomic variables, analyzing monthly data from January 2001 to December 2020 from various published data sources. A descriptive analysis is carried out and a vector autoregressive model (VAR) is applied. Finally, the causality is analyzed identifying the transmission of effects between them. The results confirm the impact of lagged interest rate, monetary aggregate M1 and unemployment rate on the stock market but also identify new features, such as the influence of the stock market on the interest rate, industrial production index, manufacturing activity index and economic sentiment index. This research is useful for Public Administration to detect possible risks in the economy, and it enables investors to better manage their investments. [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 paper focuses on climate actions through water activity and energy synergies supporting a water public operator—Canal de Isabel II—to fight against climate change in the region of Madrid. Actions for its mitigation such as the generation of electricity through water treatment activity are undoubtedly a great tool to face climate change and mitigate CO2 emissions. Led by the Strategic Plan of Canal, a water & energy cycle has been designed that, taking advantage of the different processes carried out, and thanks to the appropriate technologies, allows the generation of 100% renewable electrical energy. Through its solar energy plan, Canal is making an important technological effort to reduce energy consumption, taking advantage of the extensive area the water company has for its operations. At the same time, wastewater solutions ans possibilities are becoming more attractive. This paper explains how the Canal is transforming biogas from wastewater treatment plants into fuel for vehicles. On adaptation, this document describes measures for increasing the availability of resources, reducing water consumption, and preparing for new challenges, provided that water remains an essential resource affordable and accessible to all. In this sense, Canal's main contribution and responsibility is to ensure its availability in the event of water scarcity and to avoid the effects of extreme weather phenomena. In addition, the paper presents important projects related to such adaptations as the tariff structure to discourage high superfluous uses of water or the water reclaimed production. This integrated approach to water and energy production and consumption represents an unbeatable strategy that is recommended for dealing with this global problem in a sustainable way. Canal's activities prove that a water company can aspire to be more sustainable through the implementation of integrated projects on the water and energy nexus. [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]

Copyright of Regional Science Policy & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper focuses on the current situation and the historical development of Austrian Economics in Madrid. We will analyse the formation of this School as the result of the thesis defended by Joaquín Reig Albiol in the late fifties and the current economic debate surrounding the fractional reserve and other complex issues. In this half-century tour, we will explore three different generations of Austrian economists in Spain, whilst demonstrating that a distinct branch of the Austrian School is today live and well in Madrid. Eventually, we will discover how the Spanish Austrian economists have applied praxeology to contemporary political and economic problems and conclude that a vigorous and growing economic school of thought exists in Madrid. [ABSTRACT FROM AUTHOR]

Social media has become a basic source of information for visitors and its capacity to generate interest in touristic destinations gains relevance. This paper identifies elements capable of generating greater user engagement with the official accounts of four European capitals with a high number of tourists: London, Paris, Berlin and Madrid. Our findings, based on the 862 posts published by these cities on their Instagram accounts over the course of one year, show how various aspects of the content of these posts are crucial factors in generating engagement. They also reveal the potential of including in posts variables with elements of interaction between users' contents and official accounts. Moreover, the variables that may generate the most engagement are identified, and both differences and illustrative similarities between the strategies implemented by the cities are noted. These results suggest not only interesting theoretical conclusions, but also important implications for the tourism sector. [ABSTRACT FROM AUTHOR]

The COVID-19 virus continues to generate waves of infections around the world. With major areas in developing countries still lagging behind in vaccination campaigns, the risk of new variants that can cause re-infections worldwide makes the monitoring and forecasting of the evolution of the virus a high priority. Having accurate models able to forecast the incidence of the spread of the virus provides help to policymakers and health professionals in managing the scarce resources in an optimal way. In this paper, a new machine learning model is proposed to forecast the spread of the virus one-week ahead in a geographic area which combines mobility and COVID-19 incidence data. The area is divided into zones or districts according to the location of the COVID-19 measuring points. A traffic-driven mobility estimate among adjacent districts is proposed to capture the spatial spread of the virus. Traffic-driven mobility in adjacent districts will be used together with COVID-19 incidence data to feed a new deep learning LSTM-based model which will extract patterns from mobility-modulated COVID-19 incidence spatiotemporal data in order to optimize one-week ahead estimations. The model is trained and validated with open data available for the city of Madrid (Spain) for 3 different validation scenarios. A baseline model based on previous literature able to extract temporal patterns in COVID-19 incidence time series is also trained with the same dataset. The results show that the proposed model, based on the combination of traffic and COVID-19 incidence data, is able to outperform the baseline model in all the validation scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a cognitive ethnography on the variability of interpersonal coordination in defense against direct screens during basketball games. We collected data through observation of ten games of Estudiantes U18 Team during the 2014/2015 season in Madrid. We filmed the game and showed clips of specific direct screens to players while conducting semi-structured interviews. We analyzed the video and the discourse qualitatively following grounded theory principles. We identified three categories expressing variability: failure, partial repair, and functional variation. Even though communication was quoted by the interviewed players as a key element in their decision-making, other contextual elements – related to framing and joint attention- affected the degree of variation and success. Based on these findings, the paper offers some recommendations for coaching the tactical behaviour of defense against direct screens. [ABSTRACT FROM AUTHOR]

The geography of school choice critically shapes families' educational opportunities. Residential segregation, social inequalities and the educational marketplace interact in complex ways and produce spatialised educational opportunities for families. This paper analyses the link between these dimensions and how they structure families' educational opportunities in the city of Madrid. Based on several administrative datasets that capture students' residential location, their socio-economic position, the schools they attend and the characteristics of school supply, our analysis reveals the uneven spatial distribution of the different school modalities in Madrid, where advantaged families and neighbourhoods have more diversified and socio-economically homogenous nearby schooling options. The results also depict the way the city is spatially divided along a continuum of 'privileged' residential and educational assets. The paper reflects on how reforms expanding school choice and diversification of the educational market undertaken by the regional government may have increased the link between residential and school segregation. [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]

This paper aims to analyse human mobility in a university campus on the outskirts of the Madrid region. Several surveys which were distributed to students for completion during the 2017-2018, 2018-2019, and 2021-2022 courses were examined. Both an exploration of existing transport modes using clustering techniques and a statistical analysis on trip origins, travel times, and distances were performed. Not all municipalities with the highest number of trips were the closest to the university. The clustering analysis identified a lower variability in the use ratio of the transport modes in the 2017-2018 course. The private car, which exhibited a low sharing rate, was the most utilised transport mode. This was followed by public and university transportation. Similarities between the probability distributions of journeys using public and university transports were found. High and moderate correlations between the number of the existing stops and the amount of trips by subway and urban bus were detected. The lowest median values of travel distances corresponded to students, administrative staff, teachers, and researchers who exhibited very similar values. Considering the three analysed academic years as a whole, the most likely travel times were 30–60 minutes. It was detected that a higher gross annual income did not imply higher private car use. Residents in areas with the highest ozone concentrations also exhibited a high use of motorised vehicles. A low familiarisation with car-sharing and car-pooling platforms was also found. Globally, a high level of comfort during the trip was mostly perceived. [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]

The sharing economy has allowed people from all over the world to more effectively utilize their assets. Owners or controllers of assets in the sharing economy are free to set any price they want subject to prevailing market demand as long as they operate in an imperfectly competitive market environment. This paper examines how various characteristics of an Airbnb listing (size, number of photos, ratings, host responsiveness, superhost status, distance from city centre, etc.) affect the prices of accommodation and determines which factors strongly affect price using weighted least squares (WLS) and quantile regression. A hedonic pricing model was developed and applied to data from the cities of Barcelona, Madrid, and Seville to determine how the different characteristics of an Airbnb listing affect the price of accommodation in these major three Spanish tourist cities. The estimation results, which are resilient to various robustness checks, indicate that overall rating as well as characteristics indicative of the size of the accommodation have the strongest positive influence on price, while the number of reviews and distance from the city centre have the strongest negative influence on price. [ABSTRACT FROM AUTHOR]

Critical debates in human geography have interrogated the changing political landscapes of the post‐2008 crisis period and the post‐democratic imprint of neoliberal reconfigurations in Europe. Moreover, geographers have offered insights into politicisation processes that disrupted the post‐crisis consensus, attesting to the possibility inherent within forms of democratic politics. Contributing to these debates, this paper critically engages with Chantal Mouffes "agonistics" approach, aiming to deliberate on the implicit geographies of her thought and bring forward the complex, messy, and multi‐scalar geographies of democratic politics. In so doing, the paper offers an empirically informed comparative perspective of two exemplary cases of governance changes. Social solidarity economy (SSE) and housing inform our re‐conceptualisation of "agonistics," through a plural reading of the co‐existing and at times conflicting forms of political agency and democratic politics of this period. By conceptualising the multiple and heterogeneous spatialities, modalities, and temporalities of agonistics in Athens and Madrid, we acknowledge their mutual constitution and distinct analytical validity for geographical thinking. Comparing across uneven geographical contexts elicits crucial tensions emanating from the heterogeneity of the two contexts and further allows us to distillate the diverse, yet complementary, logics and analytical dimensions of agonistics. Eventually, our contribution aims to problematise the distinction between "politics" and "the political" – as either neatly spatialised around pre‐given state spaces or understood exclusively as disruptive moments and ruptural events – and draw the attention to actually existing forms of agonistic politics. The paper critically engages with Chantal Mouffe's "agonistics" approach, aiming to deliberate on the implicit geographies of her thought and bring forward the complex, messy, and multi‐scalar geographies of democratic politics. In so doing, it offers an empirically informed comparative perspective of two exemplary cases of governance changes in Athens and Madrid, which inform our re‐conceptualisation of "agonistics", through a plural reading of the spatialities, modalities, and temporalities of democratic politics. [ABSTRACT FROM AUTHOR]

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In IoT applications, prediction models have fundamental challenges such as real-time processing, producing results with considerable/without delay, and taking action against pattern drift. While existing models can excel when data statistics remain relatively stable, real-time systems may encounter difficulties, particularly when confronted with dynamic shifts in data behavior. Analyzing data streams generated by different IoT applications and detecting complex pattern on the fly has become an open area of research. Complex event processing with adaptivity is a must to get desired features in such models. To address this issue, a comprehensive model for prediction has been proposed in this paper. It consists of two phases: (1) the basic model is constructed using historical data, (2) a fast Fourier transform-based adaptive support vector regression (FFT-ASVR) approach is proposed to predict events embedded in IoT data streams. FFT-ASVR predicts abnormal events by experiencing a change in data streams with real-time model updation. The performance of FFT-ASVR with a similar existing method SVM-RBF is presented using real-time traffic data of Madrid city. The proposed approach has significant improvement in terms of mean absolute percentage error (MAPE) for prediction, is adaptive in nature, and is also capable of handling the issue of pattern drift. [ABSTRACT FROM AUTHOR]

Agent-based epidemiological simulators have been proven to be one of the most successful tools for the analysis of COVID-19 propagation. The ability of these tools to reproduce the behavior and interactions of each single individual leads to accurate and detailed results, which can be used to model fine-grained health-related policies like selective vaccination campaigns or immunity waning. One characteristic of these tools is the large amount of input data and computational resources that they require. This relies on the development of parallel algorithms and methodologies for generating, accessing, and processing large volumes of data from multiple data sources. This work presents a parallel workflow for extending the social modeling of EpiGraph, an agent-based simulator. We have included two novel parallel social generation stages that generate a detailed and realistic social model and one new visualization stage. This work also presents a description of the algorithms used in each stage, different optimization techniques that permit to reduce the application convergence time, and a practical evaluation of large workloads on HPC systems. Results show that this contribution can be efficiently executed in parallel architectures and the results allow to increase the simulation detail level, representing a significant advance in the simulator scenario modeling. As a summary of results, the first contribution of this paper is the development of two models (a spatial and a social one) that assign geographical and socioeconomic indicators to each simulated individual (i.e., agents), reproducing the real social distribution of the city of Madrid. The second contribution presents an improved parallel and distributed algorithm that executes the two aforementioned models using different parallelization strategies and preserving the load balance. [ABSTRACT FROM AUTHOR]

This paper aims to dissect the presence of female writers in the main four cultural supplements of Spanish reference press: Babelia (El país), Cultura/s (La vanguardia), El cultural (El mundo) and ABC cultural (ABC). For this, we analyzed the "books of the year" recommended between 2010 and 2021 (n = 1,286), as well as the juries in charge of elaborating these ranks. The results show the subsidiary role reserved for women in this sphere of cultural information: they barely author 25.3% of the selected books, although some degree is progress is observed in the historical series, after going from 4.8% in 2011 to 37.8% in 2020. The increase in the presence of women in the juries has contributed to this phenomenon --the correlation between ratio of women in both lists being statiscally significant (rs = 0.647, p < 0.001)--, together with the commitment of supplement such as Babelia and Cultura/s to literature written by women. On the contrary, there still seem to be pockets of exclusion in El cultural and ABC cultural, which reduce the visibility of work of female writers in Spain. According to our findings, women authors stand out for their youth (they are between 8 and 20 years younger than men, depending on the indicator), cosmopolitism (there are more foreign female writers, especially American, than Spanish) and origin (mainly, Madrid and Barcelona). This article evinces the collective imaginary, settled for centuries, by which literature was considered a men's affair, and reflects on the role of cultural journalism and its prescriptive function when it comes to breaking down gender stereotype --a task that, in view of the data provided in this paper, is still far from been completed. [ABSTRACT FROM AUTHOR]

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This paper investigates the unequal effect of Airbnb on the spatial organisation of economic activity in Madrid, Spain. Using establishment-level data from Madrid City Council and consumer-facing information from this short-term rental company, we find that Airbnb reshapes the urban space by encouraging tourist-oriented businesses, defined as businesses where tourists spend more than locals, at the expense of businesses primarily oriented to locals. These findings prove that short-term rentals do displace not only the local population but also resident-oriented businesses. Ultimately, our findings remain solid regardless of how we measure short-term rental activity and are not influenced by the growth of e-commerce or gentrification. [ABSTRACT FROM AUTHOR]

In the past ten years, cities have experienced a burst of micromobility services as they offer a flexible transport option that allows users to cover short trips or the first/last mile of longer trips. Despite their potential impacts on mobility and the fact that they offer a cleaner, more environmentally friendly alternative to private cars, few efforts have been devoted to studying patterns of use. In this paper we introduce new ways of visualizing and understanding spatiotemporal patterns of micromobility in Madrid based on the conceptual framework of Time-Geography. Hägerstrand's perspectives are taken and adapted to analyze data regarding use of micromobility, considering each trip departure location (origins) obtained from GPS records. The datasets are collected by three of the most important micromobility operators in the city. Trip origins (points) are processed and visualized using space–time cubes and then spatially analyzed in a GIS environment. The results of this analysis help to identify the landscape of micromobility in the city, detecting hotspot areas and location clusters that share similar behavior throughout space and time in terms of micromobility departures. The methods presented can have application in other cities and could offer insights for transport planners and micromobility operators to better inform urban planning and transportation policy. Additionally, the information could help operators to optimize vehicle redistribution and maintenance/recharging tasks, reducing congestion and increasing efficiency. [ABSTRACT FROM AUTHOR]

This paper analyzes patterns of residential segregation for many nationalities in Barcelona and Madrid during the 2008–2018 period. In the first year, the financial bubble burst, halting the exponential growth of immigrants and in the second, after the great recession, the arrival of immigrant population resumes. The multilevel analysis for the dissimilarity index is applied for the first time to Spanish cities. Complementing the results of global indices with the multilevel framework provides a richer and more detailed profile of segregation patterns. Based on these results, a typology of segregation patterns by nationalities was carried out. Global indices show higher segregation in Madrid than in Barcelona, and multilevel results evidence increasing and extending areas of high concentration of immigrants and mixing neighbourhoods. The cluster analysis demonstrates that, in this case, segregation patterns are not the same for continents or income levels of countries of origin. The results provide nuanced empirical evidence of place stratification and ethnic enclave models. [ABSTRACT FROM AUTHOR]

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