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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]

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]

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]

After studying the unpublished sketches of the Spanish artist Pablo Palazuelo, this essay proposes the existence of geometric patterns that order his designs. To illustrate the proposal, this paper selects three representative projects by Palazuelo that attempt to demonstrate the presence of a working process related to a mathematical substrate. Specifically, the use of an irregular tiling is proposed for the creation of the following architectural elements: the scenery for a composition by Kandinsky (1950–1954), and the plan for a hotel on Princesa Street, Madrid, (1961). This study also examines the use of regular tessellations in the design of the ceilings of the Huarte Residence in Madrid, (1965). The treatises by Bourgoin and Ghyka have been selected from the library of Palazuelo as the primary theoretical bases of this study. This methodology constitutes a line of further research to analyze different architectural projects. [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]

Very unhealthy air quality is consistently connected with numerous diseases. Appropriate extreme analysis and accurate predictions are in rising demand for exploring potential linked causes and for providing suggestions for the environmental agency in public policy strategy. This paper aims to model the spatial and temporal pattern of both moderate and extremely poor PM 10 concentrations (of daily mean) collected from 342 representative monitors distributed throughout mainland Spain from 2017 to 2021. We first propose and compare a series of Bayesian hierarchical generalized extreme models of annual maxima PM 10 concentrations, including both the fixed effect of altitude, temperature, precipitation, vapour pressure and population density, as well as the spatio-temporal random effect with the Stochastic Partial Differential Equation (SPDE) approach and a lag-one dynamic auto-regressive component (AR(1)). Under WAIC, DIC and other criteria, the best model is selected with good predictive ability based on the first four-year data (2017–2020) for training and the last-year data (2021) for testing. We bring the structure of the best model to establish the joint Bayesian model of annual mean and annual maxima PM 10 concentrations and provide evidence that certain predictors (precipitation, vapour pressure and population density) influence comparably while the other predictors (altitude and temperature) impact reversely in the different scaled PM 10 concentrations. The findings are applied to identify the hot-spot regions with poor air quality using excursion functions specified at the grid level. It suggests that the community of Madrid and some sites in northwestern and southern Spain are likely to be exposed to severe air pollution, simultaneously exceeding the warning risk threshold. [ABSTRACT FROM AUTHOR]

This paper illustrates how Machine Learning techniques can be used to assess the impact of environmental protocols that are sparsely activated over time. A case study is analysed: the impact of a protocol that sets traffic restrictions on NO2 levels in Madrid's urban area. The protocol specifies that these restrictions are active only when NO2 level reaches above a certain threshold. Since the protocol was first enacted, in 2017, restrictions have only been active for 59 days, never longer than ten consecutive days. Cross effects are identified: the protocol magnifies the effect of other relevant features, especially wind speed. Pollution decreases with wind speed. Consequently, episodes of high pollution levels generally occur when wind speed is low. The analysis shows that precisely at these low values of wind speed, an increase in the wind speed has a higher effect on pollution when the protocol is activated than when it is not. The analysis is carried out at a measuring station level, considering eight representative stations. The referred cross effect is clearer at centrally located stations across Madrid. Cross effects of the protocol with other weather features are weaker than that with wind speed. The assessment is based on the computation of Shapley values for classification trees that are built using XGBoost and rolling windows. [ABSTRACT FROM AUTHOR]

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]

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 aims to evaluate the impacts of the economic context on traffic congestion and its consequential effects on private vehicle accessibility. We conduct a long-term analysis of spatiotemporal traffic congestion patterns in Madrid (Spain), comparing two urban realms: the 2008 economic crisis and the following post-crisis situation. We apply TomTom Speed Profiles data to assess daily variations in traffic congestion and their changes between both periods, and Twitter data to capture spatial patterns of the daily pulse of the city. Increased traffic, a by-product of economic recovery, resulted in higher congestion, particularly during peak hours. Nevertheless, these changes are spatially uneven. In the city core, an increase in congestion is relatively temporally homogeneous, while in the peripheral suburban zones, there has been only a marginal increase in travel times. On the other hand, in the urban outskirts, increased traffic congestion is more severe but visibly different between north and south. These differences have strong social connotations: over 40% of the population experienced a dramatic increase in travel times (more than 25%) during peak hours. Moreover, low-income groups are more likely to live in the more affected southern districts, suffering most the negative consequences of increased congestion. [ABSTRACT FROM AUTHOR]

Using an original microeconomic database with information for around 200,000 individuals, this paper creates new estimates of internal migrations in Spain in a key moment of its economic history. Our analysis shows that internal migrations were not a linear process including both periods of stagnation and also rapid growth, and that the 1850s were a decade of surprising high mobility in the absence of modern transportation. We also conclude that the rise in mobility was geographically asymmetrical with traditional urban centres losing ground against the rise of Madrid and Barcelona. The modernisation of the country also had significant social impacts with the migratory gender gap being significantly reduced prior to 1870. An analysis of the determinants of internal migrations suggests that traditional push and pull factors described by the literature in the early twentieth century seem to be also behind the early migrations of the mid-nineteenth century. The modernisation of the country provided new opportunities in urban areas that, combined with falling transport and information costs, created the perfect conditions for the 'democratisation' of long-distance migrations. [ABSTRACT FROM AUTHOR]

Cities are certainly a key factor in the location of gambling facilities. This paper aims to map the location of gambling outlets in urban areas and to examine potential links between neighborhoods socioeconomic and demographic characteristics and gambling supply, taking into account spatial dependencies of neighboring areas. This correlation is of interest because neighborhood characteristics may attract sellers, and because the presence of gambling sellers may cause changes in neighborhood demographics. Using detailed official data from the city of Madrid for the year 2017, three spatial econometric approaches are considered: spatial autoregressive (SAR) model, spatial error model (SEM) and spatial lag of X (explicative variables) model (SLX). Empirical analysis finds a strong correlation between neighborhoods characteristics and co-location of gambling outlets, highlighting a specific geographic patterning of distribution within more disadvantaged urban areas. This may have interesting implications for gambling stakeholders and for local governments when it comes to the introduction and/or increase of gambling availability. [ABSTRACT FROM AUTHOR]

This paper investigates how the European Union and Spanish changes to the regulation and the declaration of some unfair terms in mortgage loan agreements have affected the valuation of the Spanish banking industry. This paper has a dual legal and economic focus, and could consequently be of interest not only to financial institutions but also to the administrator of justice, which oversees the correct functioning of the financial system and the protection of consumer rights, in this case, mortgage holders. The empirical analysis was carried out using a sample of Spanish companies composed of 11 financial institutions that are listed, or have been listed, on the Madrid stock exchange and 24 non-financial companies listed on the IBEX-35 index. The period analysed was from December 2009 to March 2019. One of the main conclusions was the observation that, in general, the abnormal negative returns of financial institutions are greater when dealing with a decision from the Court of Justice of the European Union rather than from the Spanish Supreme Court. The events referred to as unfair terms that have had the most impact as a whole on the returns of shareholders were, because of their impact of the valuation of financial institutions, in order of importance, those relating to default interest charges, followed by rounding up, and, in last place, the unfair terms of floor clauses, mortgage constitution expenses and multi-currency loans. [ABSTRACT FROM AUTHOR]

Objectives: The Police Districting Problem concerns the definition of patrol districts that distribute police resources in a territory in such a way that high-risk areas receive more patrolling time than low-risk areas, according to a principle of territorial fairness. This results in patrolling configurations that are efficient and effective at controlling crime but that, at the same time, might exacerbate racial disparity in police stops and arrests. In this paper, an Equitable Police Districting Problem that combines crime-reduction effectiveness with racial fairness is proposed. The capability of this model in designing patrolling configurations that find a balance between territorial and racial fairness is assessed. Also, the trade-off between these two criteria is analyzed. Methods: The Equitable Police Districting Problem is defined as a mixed-integer program. The objective function is formulated using Compromise Programming and Goal Programming. The model is validated on a real-world case study on the Central District of Madrid, Spain, and its solutions are compared to standard patrolling configurations currently used by the police. Results: A trade-off between racial fairness and crime control is detected. However, the experiments show that including the proposed racial criterion in the optimization of patrol districts greatly improves racial fairness with limited detriment to the policing effectiveness. Also, the model produces solutions that dominate the patrolling configurations currently in use by the police. Conclusions: The results show that the model successfully provides a quantitative evaluation of the trade-off between the criteria and is capable of defining patrolling configurations that are efficient in terms of both racial and territorial fairness. [ABSTRACT FROM AUTHOR]

In recent decades we have seen an increased interest in the use of seemingly unrelated regressions models (SUR) in a spatial context, with compelling case studies in different fields. This upsurge has favoured the development of new and more efficient inference techniques. At present, the user has a basic toolkit to deal with this kind of model, that is, however, in need of improvement. This paper focuses on the question of estimating, quickly and accurately, spatial SUR models. The most popular procedure is maximum likelihood (ML) which guarantees precision at the cost of a high computational burden. This is especially true in cases of large sample size and strong spatial structure. We explore simpler estimation algorithms such as instrumental variables (IV), which expedites calculation at the cost of a certain loss in quality of the estimates. We focus on the importance of sample size and the trade-off between accuracy and speed. To that end, we perform a comprehensive simulation experiment in which we compare ML and IV algorithms, looking for their strengths and weaknesses. The paper includes two applications to the case of Airbnb in the urban area of Madrid. First, we estimate a spatial SUR hedonic model of accommodation prices, using micro-data for three different cross sections à la Anselin, that is, considering temporal correlation plus spatial structure. Then, the data are aggregated by neighbourhoods. We specify a spatial SUR model with two equations (apartments and rooms) also using three cross sections. In both cases, the models are estimated by ML and IV using the spsur R package (Angulo et al. in spSUR: spatial seemingly unrelated regression models. R Package version 1.0.0.3, 2019), with the aim of illustrating its capabilities. [ABSTRACT FROM AUTHOR]

Context: The difficulty of analysing resilience and threshold responses to changing environmental drivers becomes evident in the social-ecological systems framework due to their inherent complexity. Research is needed to develop new tools able to deal with such challenges and determine potential thresholds for SES variables that primarily influence tipping point behaviour. Objectives: In this paper, a methodology based on the application of Bayesian Networks (BNs) has been developed to quantify the social-ecological resilience along an urban–rural gradient in Madrid Region, detecting the tipping point values of the main socioeconomic indicators implying critical transitions at landscape stability thresholds. Method: To do this, the spatial–temporal trends of the landscape in an urban–rural gradient from Region de Madrid (Spain) were identified, to then quantify the intensity of the changes and explain them using BNs based on regression models. Finally, through inference propagation the thresholds of landscape change were detected. Results: The results obtained for the study area indicate that the most resilient landscapes analysed are those where the traditional silvo-pastoral activity was maintained by elderly people and where there is cohesion between neighbouring rural municipalities. Conclusion: The method developed has allowed us to detect the tipping points from which small changes in socioeconomic indicators generate large changes at the landscape level. We demonstrate that the use of BNs is a useful tool to achieve an integrated social-ecological spatial planning. [ABSTRACT FROM AUTHOR]

Ride-hailing is an emerging service that is transforming door to door mobility in urban areas. Users can easily request a ride through a smartphone app that informs them of the pickup time, the location of the vehicle, and the fare that they will pay in advance. Even though it is well known that Uber implements a dynamic pricing approach depending mostly on supply, demand and competition with other services, there is still little empirical evidence on the main drivers explaining the fare strategy of the company. However, a deeper understanding of prices is essential to evaluate and establish a future scenario with smarter regulation and fairer competition between ridesourcing and taxi services. Using 10-month data from the Uber's application programming interface in the city of Madrid, this research studies the association of Uber fares with different explanatory variables. It also explores the main differences between Uber and taxi fares. The results indicate that trip distance, trip delay, day of the week, origin and destination of the trip, and rain precipitation have a statistically significant impact on Uber fares. The findings also show that on average, Uber fares are lower than taxi fares, with the exception of particular hours of the day, as well as Uber fares slightly increased during taxi strikes recently happened in Madrid. The paper concludes with some policy recommendations and insigths regarding the future of the hailing sector and the importance of prices in evaluating future changes and possibilities. [ABSTRACT FROM AUTHOR]

The problem of location is the cornerstone of strategic decisions in retail management. This decision is usually complex and multidimensional. One of the most relevant success factors is an adequate balanced tenancy, i.e., a complementary ecosystem of retail stores in the surroundings, both in planned and unplanned areas. In this paper, we use network theory to analyze the commercial spatial interactions in all the cities of Castile and Leon (an autonomous community in north-western Spain), Madrid, and Barcelona. Our approach encompasses different proposals both for the definition of the interaction networks and for their subsequent analyses. These methodologies can be used as pre-processing tools to capture features that formalize the relational dimension for location recommendation systems. Our results unveil the retail structure of different urban areas and enable a meaningful comparison between cities and methodologies. In addition, by means of consensus techniques, we identify a robust core of commercial relationships, independent of the particularities of each city, and thus help to distinguish transferable knowledge between cities. The results also suggest greater specialization of commercial space with city size. [ABSTRACT FROM AUTHOR]

In order to attract car users towards the public transport services in an urban and metropolitan context, contributing to a sustainable mobility in cities, it is fundamental to improve our knowledge of service quality perceptions, satisfaction and behavioral intentions toward transit from the point of view of private transport users. This paper is based on the data from a single survey—carried out in two European cities (Madrid and Lisbon)—of regular private vehicle users that use public transport at least occasionally. The questionnaire gathers information about 14 attributes of service quality, four indicators for satisfaction and four indicators for behavioral intentions; as well as several sociodemographic variables that are used in the models (household location, gender, age, education, dependent members in the family and income). The study uses confirmatory factor analysis to identify the most important service quality attributes for the car users; structural equation modeling for investigating the relationships among the three factors; and multi-group analysis (MGA) and a multiple-indicator and multiple-causes (MIMIC) approach to identify heterogeneity in the models because of geographical context or sociodemographic characteristics. Regular private vehicle users in both cities agree that punctuality, frequency, information and intermodality are among the five most important service quality attributes. Residents in Madrid also emphasize speed, while service hours would be a priority in Lisbon. The models for both cities agree on a complete mediator role of satisfaction between service quality and behavioral intentions. The MGA and MIMIC approaches show that the models do not present important differences tied to the sociodemographic characteristics, although differences are identified between Madrid and Lisbon. The MIMIC approach identified differences associated with city, household location and education for the pooled data; while household location, age and education were significant in Lisbon. [ABSTRACT FROM AUTHOR]

Is there a place in particular that international migrants would call home? How do they talk about it, where does it lie, and what characteristics is it expected to have, given their demographics and patterns of settlement? Similar questions are meaningful in themselves and in illuminating migrant biographical, family and housing trajectories. We address them, in this paper, through the categorization and multinomial analysis of the responses to a dedicated open-ended question in a survey on Ecuadorians in Madrid, Milan and London (n = 1175). This original dataset allows us to explore migrant views of home against the background of their demographics and of their migration and housing conditions. We analyse respondents' ways to articulate, spatialize and prioritize key aspects of home through a logit model, thereby assessing their association with age, length of stay, housing tenure, family networks and city of residence. Overall, their predominant construction of home points to a place in the country of settlement, but not necessarily to their own dwelling. Younger and newcomer immigrants see home as a primarily relational construct, whereas older and long-stayers emphasize its place-based and private dimension. Significant variations in the expected emplacement and bases of home can be found across cities of residence. However, no significant variations are associated either with gender or with migrants' transnational engagement. [ABSTRACT FROM AUTHOR]

Background: While many studies analyze the effect of extreme thermal events on health, little has been written about the effects of extreme cold on mortality. This scarcity of papers is particularly relevant when we search studies about extreme cold on the health of rural population. Therefore, we tried to analyze the effect of cold waves on urban areas and rural areas from Madrid and to test whether differentiated effects exist between both population classes. For this purpose, we analyzed data from the municipalities with over 10,000 inhabitants for the period from January 1, 2000 through December 31, 2013. Municipalities were classified as urban or rural (Eurostat), and they were grouped into similar climatological zones: Urban Metropolitan Centre (UMC), Rural Northern Mountains (RNM), Rural Centre (RC) and Southern Rural (SR). The dependent variable was the daily mortality rate due to natural causes per million inhabitants (CIE-X: A00-R99) that occurred between the months of November and March for the period. The independent variable was minimum daily temperature (ºC) (Tmin). Social and demographic contextual variables were used, including: population > age 64 (%), deprivation index and housing indicators. The analysis was carried out in three phases: (1) determination of the threshold temperature (Tthreshold) which defines the cold waves; (2) determination of the relative risk (RR) for cold waves using Poisson linear regression (GLM); and (3) using GLM of the binomial family, Odds Ratios (OR) were calculated to analyze the relationship between the frequency of the appearance of cold waves and the socioeconomic variables. Results: The UMC zone experienced 585 extreme cold events related to attributable increases in the mortality rate. The average number of cold waves in the rural zones was 319. The primary risk factor was the percentage of population over age 64, and the primary protective factor was housing rehabilitation. As a whole, the period experienced more cold waves (1542) than heat waves (1130). Conclusion: The UMC was more vulnerable than the rural areas. Furthermore, the results support the development of prevention policies, especially considering the fact that cold wave events were more frequent than heat waves. [ABSTRACT FROM AUTHOR]

This paper contributes to the literature on entrepreneurship and economic geography by identifying factors that determine the attractiveness of a site in a metropolitan area, as the basis for the emergence of high-tech firms' spatial concentration. The econometric model provides distinct advantages over the largely descriptive approaches that have been dominant in the point pattern analysis literature for clusters. We focus on the role of two types of knowledge spillovers on a firm's location choices: (1) those that arise from collocating with other companies from the same industry, and (2) universities' knowledge spillovers. A model is estimated using data on firm births in high and medium–high-technology manufacturing industries, during 2000–2016 in Madrid. Our results show that the main source through which firms benefit from knowledge spillovers is through proximity to firms in the same industry and not from universities. [ABSTRACT FROM AUTHOR]

During a homicide investigation in which fire has been used to reduce the size of the cadaver and conceal the evidence of injuries, the identification of perimortem trauma presents a challenge, in particular in cases when the perpetrator has dismembered the body followed by burning the remains. It is therefore important to understand the effects which heat causes on fresh bone. The aim of this paper is to perform a pilot study on the survival ratio of toolmarks in different anatomical regions associated with dismemberment, and a descriptive analysis of the variables that may potentially influence the post-burning survival and detection. To achieve this, three donated embalmed cadavers were used to simulate a case in which an attempted dismemberment and burning had occurred. Fifty-five pre-burning injuries were manually induced: 30 using a machete to inflict chopping trauma, and 25 with a serrated bread knife to inflict sharp force trauma, on the thigh, knee, ankle and wrist. The cadavers were cremated in a furnace at Madrid's Cementerio Sur and the burnt remains were analysed at the Laboratorio de Antropología y Odontología Forense of the Universidad Complutense de Madrid. Not all pre-burning injuries inflicted were visible after the cremation process; only 13% were detected in this experiment. Toolmarks can be masked, modified, destroyed or overlooked from the outset of the procedure due to several factors which influence the post-burning survival and detection of toolmarks and contribute to conceal the evidence of trauma. Additional research should be done to study further variables which affect the post-burning visibility of sharp force trauma. [ABSTRACT FROM AUTHOR]

Assessing energy use in healthcare buildings requires identifying consumption profiles regularly. Keeping this in mind, this paper studies the energy intensity of a hospital and sets specific energy performance indicators by healthcare area. The authors analysed a hospital located in the province of Madrid (Spain), equipped with 182 beds and an area of usage of 25,177 m2. The heating, ventilation and air-conditioning system (HVAC) and steam production equipment (63.0%) and medical equipment (18.8%)—which includes electromedicine (11.6%), radiology (4.2%), radiotherapy (0.7%) and nuclear medicine (2.4%)—accounted for 81.8% of the energy consumed. Throughout the analysis, the authors found that operating theatres and intensive care units demanded more than 1000 kWh/m2 per year, while catering and nuclear medicine required between 500 and 1000 kWh/m2 per year and radiology between 350 and 500 kWh/m2, and most of the other units did not exceed 250 kWh/m2. The wide variability of these results shows that each area's energy consumption should be studied separately for an appropriate energy management. These indicators are useful for benchmarking between hospitals, thus prioritising energetically efficient investments. [ABSTRACT FROM AUTHOR]

Focusing on the analysis of green spaces of urban and peri-urban borders, this paper puts into practice a methodology designed for the analysis of green areas and peri-urban spaces as green infrastructures, but from a multifunctional and integrating perspective, as it is stated in the European Strategy for Green Infrastructures and the 2030 Agenda for Sustainable Development goals. The deadline for implementing European legislation in this area means that strategic plans are being developed at local and regional level. In Spain there are municipal and regional strategies already developed and implemented but the national strategy has not yet been approved. To this end, the development of monitoring and evaluation tools such as the one presented in this article, can help not only in local decision-making, but also in the establishment of common criteria to help assess its future evolution. This research analyses the large peri-urban parks located in the southwest of the Community of Madrid (Spain). The evaluation is carried out from a local to a regional scale applying multifunctionality criteria to the planning, design, execution, maintenance and resilience phases. From the point of view of landscape structures, the findings of this study reflect a high environmental and social services delivery value, which makes it possible to understand the need to create networks to integrate the peri-urban spaces into the city and to attend to and understand the needs of all actors involved: citizens, political leaders, municipal technicians and private companies, providing them a common vision that improves the future of these spaces. This makes them core areas from which to design strategic plans for natural infrastructure and improvement of biodiversity in the urban area, being, likewise, an example that can be extrapolated and applied to large cities whose urban areas are adjoined and where peri-urban parks can be the starting point for designing supramunicipal strategies for open spaces. Based on these results we can conclude that south-west Madrid provides the ideal conditions for implementing a supra-municipal strategy for green infrastructures which, starting with its large forest parks, showcases the periurban areas which connect them with the urban green network. The Móstoles Green Network and Bosquesur are two strategic projects which, together with the forest parks, constitute a working framework based on which the Supra-municipal Strategy for Open Spaces in South-west Madrid can be devised. [ABSTRACT FROM AUTHOR]

This paper analyses the effects that public credit guarantees have on SME business activity and investment. We focus the study on the main regional mutual guarantee institution in the Spanish Region of Madrid, covering two distinct stages of the economic cycle and credit environments: first, the full range of the country's financial crisis with credit constraints (2009–2011), and later, the recovery stage with credit expansion (2012–2015). Using propensity score matching based on economic activity and company size, we show that guarantees allow for the relaxation of credit constraints, driving turnover and investment during both recession and growth. We also find that mutual guarantee schemes constituted a greater stimulus for firms during contraction; thus, they can act as countercyclical policies. Moreover, although guarantees had a substantial effect on all small companies (those with fewer than 50 employees), they had the greatest impact on microenterprises (those with fewer than 10 employees). We show the activities for which guarantees constitute a greater boost, which may inform public-policy designs for specific types of business. [ABSTRACT FROM AUTHOR]

This research analyzes the effect of carbon pricing policies in transport electrification. It combines a heuristic algorithm to solve the Green Vehicle Routing Problem with Multiple Technologies and Partial Recharges with an economic Total Cost of Ownership model. The paper compares the performance of battery electric (BEV) and internal combustion vehicles (ICEV) for last mile delivery, using real data of Madrid (Spain). The results show that carbon pricing is scarcely effective when daily mileage is low (precisely when BEVs require incentives), and its effectivity increases as mileage increases (precisely when it is not so necessary to incentivize BEVs). Hence, carbon pricing is not an effective tool for promoting electric vehicles in the short term, and as a result, any political decision to fix CO2 prices must be adopted with a long-term view in mind. Specifically for the case of Spain, this research shows that current aids to BEVs are insufficient, with the exception of some regions like Madrid, which complement national subsidies with regional ones. [ABSTRACT FROM AUTHOR]

The Madrid Regional Government (Central Spain) proposes a zone of the Guadarrama Mountains to be declared as a National Park. This paper reports on the zoning method developed to this end. The procedure followed considers compatibility of land uses with landscape characteristics and proposes protecting a part of the zone through declaration of National Park status and declaring another part as a Regional Park. The approach is based upon a multivariate environmental analysis aimed at zoning for optimal location of potential activities. The zoning permits the design of protected areas following the criteria underlying the declaration of these two categories in accordance with the Spanish environmental legislation in force. A practical tool for policy decision-making is provided. However, the final decision taken by policymakers in the design and zoning of protected areas differed from the model output used by the scientists. This is discussed in the paper to illustrate the interactions between political decision-making and scientific modelling. [ABSTRACT FROM AUTHOR]

This paper explores various theories of curriculum intending to provide a new approach—which we regard as a significant theoretical contribution—to examine the broad set of different discourses that have been shaping science education. We first introduce concepts and values that support traditional and critical curriculum theories and offer some examples of international science education discourses that could be in tune with each of these approaches. We then develop a post-critical perspective (Laclau, Emancipação e diferença, EdUERJ, Rio de Janeiro, 2011) on curriculum, with emphasis on discourse theory (Laclau and Mouffe, Hegemonía y estrategia socialista: hacia uma radicalización de la democracia, Siglo XXI, Madrid, 1987) and on categories such as discourse, articulation, nodal points, antagonism and hegemony, to identify hegemonic and counter-hegemonic discourses in the scope of Brazilian science education scholarship and teacher education. Our analysis suggests that articulations and nodal points such as scientific knowledge, method and assessment have been framing traditional curriculum features that boost the hegemony of knowledge itself. On the other hand, nodal points such as gender, society, nature, curriculum and power relations have been forging the critical curriculum perspective as a counter-hegemonic discourse in the struggle for the hegemony of knowledge to do something. Nonetheless, more important than this portrait is the disclosure that antihegemonic discourses can support researchers who work for reactivating contingency and new antagonisms to transform science education. [ABSTRACT FROM AUTHOR]

In the field of road transport, Advanced Traveller Information Systems represent a relevant tool to manage road traffic, improve drivers' utility and make a more efficient use of transport infrastructure. Due to the growing sources of en-route information available nowadays, it is crucial to understand better its influence on drivers' behaviour, particularly with regard to route choice. Previous research in this field has mainly focused on the provision of en-route information in toll-free environments. However, few researches have explored its influence when a tolled alternative is available. This paper is aimed at exploring the influence of variable message signs (VMS) information on drivers' route choice, made between a free highway and a competing tolled alternative. To that end, we develop a binary logit analysis based on empirical data from the metropolitan area of Madrid, Spain. Results show that the type of information provided to drivers through VMS panels significantly influences their route choice when one of the alternatives is tolled. Furthermore, some combinations of messages, such as adding travel time estimates together with incident messages, greatly increase the diversion rate to the tolled route. The research also offers evidence that the influence of the information provided changes according to the type of day, which may be related to traffic conditions, and to the different types of user characteristic of weekday and weekend mobility. [ABSTRACT FROM AUTHOR]

The psychological literature on the development of gestures during the first year of life has been limited. It has mainly focused on the development of pointing at around 11 months of age, considering it the gesture that allows triadic interactions. However, recent studies have argued for the importance of earlier ostensive gestures (showing and giving), not only as precursors of pointing, but also as important gestures for early cognitive and communicative development. These studies have also emphasized the mediating role of materiality and of others (adults and peers) in communicative acts, especially in pre-verbal interactions. This paper reports a longitudinal study of first-year infants in an Infant School classroom in Madrid. Through a microgenetic analysis both infants' gestures and teachers' educational actions related to gesture development were investigated. The results highlight (1) the central role of the teacher in the birth and configuration of infants' gestural repertoire; and (2) materiality as a configurative aspect of communicative interactions during this period as infants communicate not only about objects but through them. Among the types of gestures observed, self-directed gestures predominated, especially ostensive gestures, these being related to early self-regulation processes. Gesture development could be understood as a process of progressive distancing of the infant from or between the material world and himself/herself. In this process, the teacher can encourage, redirect, and structure the infant's productions through adjustment of their educational activity. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop a spatial group-wise heteroskedasticity test based on the scan approach, specifically developed for spatial autocorrelation regression models (spatial lag and spatial error models): the "scan-LM test." Based on the Lagrange multiplier (LM) principle, its main advantage lies in its comparative ease of implementation as it is not necessary to obtain the maximum likelihood estimations for the alternative hypothesis. Moreover, when rejecting the null hypothesis, this test identifies the shape and size of the spatial clusters with different residual variance, a feature which proves very useful for specification search of the regression model. Another important benefit of the scan-LM test is that it does not require the specification of a spatial weights matrix. An extensive Monte Carlo simulation confirms the good properties of the scan-LM test in terms of size and power. This test is also robust in the presence of non-normality and other forms of a spatial heteroskedasticity. We finally propose an application on housing prices in the agglomeration of Madrid for a specific submarket: the attics. [ABSTRACT FROM AUTHOR]

Information about the first conference of the European Philosophy of Science Association held in Madrid, Spain from November 14 to 17, 2007 is presented. Topics include styles in the philosophy of science, evolution of attempts to characterize scientific knowledge, and the role of relative a priori principles in the history of physics. Several philosophers of science attended the conference including Mauro Dorato, Miklos Redei and Ilkka Niiniluoto.

The proliferation of betting shops in Spanish cities is causing a heated social debate in response to the undesirable impacts that businesses of this kind can have. As a result, associations and social movements have emerged to try to stem their expansion and, at the same time, regulations have been introduced to prevent the uncontrolled opening of this type of premises. The limitations set out in the legislation include minimum distances between betting shops and schools. In order to understand the spatial dimension of this phenomenon and to find out the extent to which these businesses comply with the regulations in force, in this paper, we study the distribution of betting shops in the city of Madrid and their proximity to each other and to schools. The results reveal certain areas of the city with a high density of betting shops and with schools with high exposure to these businesses. Likewise, results show the significant number of businesses that would have to close (81%; n = 416) if the current moratorium on betting shops that opened their doors before the current legislation came into force did not exist. [ABSTRACT FROM AUTHOR]

This paper analyses the effect of access and egress time to train stations and airports on modal competition in the Madrid-Barcelona corridor, (Spain), where a new high speed train started to operate in the year 2008. The analysis is based on the estimation of a Nested Logit model that uses a mixed revealed/stated preference data set that provides information on travellers' behaviour in the available modes. We obtained the value of the different components of the travel time, as well as the willingness to pay for other service attributes. We then analysed demand response to different policies that consider variation in access time to train stations and airports and other attributes. The results highlight the important role that access time to terminals may play in terms of modal competition between rail and plane for interurban travel passengers. [ABSTRACT FROM AUTHOR]

The European Union Water Framework Directive establishes the obligation to all Member States to develop and implement catchment-scale management plans. These aim at reaching a good status of all water bodies in Member States by 2015 or, at the latest, by 2027. Numerical models provide a suitable approach to evaluate the possibilities of achieving this goal by enabling users to deal with complex hydrological interrelations in a dynamic manner. This paper presents a modelling-based approach to examine the past and future effects of groundwater-based urban supply in Metropolitan Madrid, Spain. Monthly scale model calibration is based on 32 years of water table observations. Care is taken to address the effect of intensive pumping on groundwater levels and streamflows, as well as the role of groundwater resources in meeting urban demands during dry spells. The paper concludes by reflecting on the implications and probabilities of meeting the aforementioned deadlines, as well as on the sustainability of past and future pumping trends. Policy considerations aside, modelling results suggest that groundwater extractions could be augmented considerably without causing a significant decrease in streamflows. [ABSTRACT FROM AUTHOR]

The University, as an income-expenditure flow, has positive effects in local economic development. These effects can be classified into two categories: supply effects—related to human capital and research—and demand-side effects—related to expenditure and its multiplier impact on local economy. This paper focuses on the demand-side effects of the University of Alcala (Madrid, Spain) using three different methods: (a) A simplified version of the ACE Model; (b) The Ryan short cut model and (c) the input-output technique taking into account the inside of I-O, a household sector to estimate the induced effects. The main objective of this paper is to show the advantages, limitations and scopes of each method. Finally, we propose a way to distribute territorially these effects in the Community of Madrid, using eleven intra-regional areas. [ABSTRACT FROM AUTHOR]

This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile. [ABSTRACT FROM AUTHOR]

The increasing use of online hospitality platforms provides firsthand information about clients preferences, which are essential to improve hotel services and increase the quality of service perception. Customer reviews can be used to automatically extract the most relevant aspects of the quality of service for hospitality clientele. This paper proposes a framework for the assessment of the quality of service in the hospitality sector based on the exploitation of customer reviews through natural language processing and machine learning methods. The proposed framework automatically discovers the quality of service aspects relevant to hotel customers. Hotel reviews from Bogotá and Madrid are automatically scrapped from Booking.com. Semantic information is inferred through Latent Dirichlet Allocation and FastText, which allow representing text reviews as vectors. A dimensionality reduction technique is applied to visualise and interpret large amounts of customer reviews. Visualisations of the most important quality of service aspects are generated, allowing to qualitatively and quantitatively assess the quality of service. Results show that it is possible to automatically extract the main quality of service aspects perceived by customers from large customer review datasets. These findings could be used by hospitality managers to understand clients better and to improve the quality of service. [ABSTRACT FROM AUTHOR]

Extreme heat events are more frequent and more intense globally due to climate change. The urban environment is an additional factor enhancing the effects of heat. Adults above 65 years old are especially at risk due to their poorer health, physiology and socio-economic situation. Yet, there is limited knowledge about their experiences of summer heat, their actual heat exposure and how they negotiate their thermal comfort through different adaptation practices. In conventional research on heat exposure and thermal comfort, very little attention is given to individual behaviour and subjective experiences. To understand how older adults feel the heat in the city we study their thermoception, which we conceptualise as an embodied knowledge about bodily sensations, thermal environments and adjustments to heat. This article stems from interdisciplinary research conducted in Warsaw and Madrid in the summers of 2021–2022. We combine and juxtapose data from ethnographic research and from physical measurements of temperature gathered in people's homes, to show on a microscale how we can study and understand the diversity in individual heat exposure more holistically. We demonstrate that to understand the consequences of heat for vulnerable populations it is crucial to study thermoception, the subjective experiences of heat, in addition to analysing their thermal environments. With the use of a unique methodology, this article shows how similar weather conditions are experienced differently by people from the same cities, depending on the materiality of their dwellings, availability of cooling devices, as well as everyday habits and their individual bodies. We discuss the social, material and temporal adjustments participants made to deal with heat, to showcase their agency in affecting their individual heat exposure. The article emphasises the role of social sciences and qualitative methods in research on individual heat exposure and argues for the co-production of knowledge on the topic. [ABSTRACT FROM AUTHOR]

Bike-sharing systems (BSS) are gaining popularity in cities worldwide, as a part of a generalized strategy to mitigate the problems derived from motorized transportation (congestion, pollution, noise, etc.). These systems have proved to have positive effects on cities, moreover, many of them have reached a performance peak and require improvements to attract/retain users and compete against emerging soft mobility alternatives. Whilst there are broad studies evaluating BSS demand and design, less attention has been paid to user satisfaction and the complexities underlying the relationships between the system attributes importance. This study proposes a novel combination of two methodologies for satisfaction assessment that allows decision-makers to identify the most influential system attributes on user satisfaction. The combined methods are the direct, explicit, Importance Performance Analysis (IPA), and the nonlinear, implicit Three-Factor Theory (3FT), which combined generate a three-dimensional scheme that facilitates the comprehension of the results. The combination was applied to a dataset of Madrid´s BSS to identify the attributes that perform poorly, and then assess their implicit influence on satisfaction to establish improvement priorities. The results suggest that station occupancy and bicycle availability and totem functioning are key service attributes to enhance satisfaction. Also, the combination of the two methodologies makes it possible to differentiate that maintenance is a priority for subscribers and network extension for occasional users. The pedelec system is a key attribute that might help overcome Madrid´s unfavorable cycling environment. This user-centric evaluation is a valuable tool that guides precise measure implementation, service operation, future design, and planning oriented to increase ridership. [ABSTRACT FROM AUTHOR]

In large cities, the decay of deprived neighborhoods externalizes the consequences of present-day urban social inequality. Residents of these areas often show discomfort with living in a poor environment. Adopting Hirschman's classic Exit, Voice and Loyalty model, this study analyzes the reactions of residents to dissatisfaction in San Diego, a deprived neighborhood in Madrid. A qualitative methodology was applied to analyze the discourses of residents by conducting fourteen focus groups with diverse profiles according to gender, age, socio-labor situation, and geographical origin. The results reflect that, in a deprived neighborhood, there are limits to reactions, so that exit (moving out) is only partially manifested, and voice (social mobilization) is only temporarily activated, conditioned by the situation and organizational capacity. Loyalty, on the contrary, appears as an option that improves coexistence, but it remains attached to long-term residents and hardly welcomes newcomers, especially immigrants. The explanatory capacity of Hirschman's model is here expanded by exploring the use of resistance as a complementary response. This strategy, as a political reaction, complements voice and reinforces agency by seeking concrete improvements in the daily life of the residents. These qualitative research results provide important insight into neighbors' reactions in deprived areas, where exit and voice, as main options, are limited, and resistance becomes a significant potential for them. [ABSTRACT FROM AUTHOR]

Three-dimensional manifold data arise in many contexts of geoscience, such as laser scanning, drilling surveys and seismic catalogs. They provide point measurements of complex surfaces, which cannot be fitted by common statistical techniques, like kriging interpolation and principal curves. This paper focuses on iterative methods of manifold smoothing based on local averaging and principal components; it shows their relationships and provides some methodological developments. In particular, it develops a kernel spline estimator and a data-driven method for selecting its smoothing coefficients. It also shows the ability of this approach to select the number of nearest neighbors and the optimal number of iterations in blurring-type smoothers. Extensive numerical applications to simulated and seismic data compare the performance of the discussed methods and check the efficacy of the proposed solutions. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate protozoan cysts and oocyts in the faecal pellets of the German cockroach (Blattella germanica), with emphasis on the prevalence of Lophomonas blattarum. Methods: Thirty adult Blattella germanica (12 males; 18 females) were trapped near Madrid, Spain. Expelled faecal pellets were collected in the laboratory over 5 days in two plastic containers. Protozoan cysts from one container were weighted and those in the other used for morphologically identification. Results: Protozoan cysts/oocysts per gram of faecal pellet were: Nyctotherus sp. (0.0019/g), Entamoeba (0.0007/g), Balantidium coli (0.0001/g), Lophomonas blattarum (0.00038/g). Observation of 189 protozoan cysts/oocysts indicated the following prevalence: Nyctotherus sp. 65 (34.4%); Gregarina spp. 34 (18%); Entamoeba sp. 24 (12.7%); Cryptosporidium sp. 17 (9%); Coccidia 16 (8.4%); Lophomonas blattarum 13 (6.8%); Balantidium coli 4 (2.1%); and unclassified 16 (8.4%). Conclusion: Lophomonas blattarum has previously been demonstrated in the gut of cockroaches, but this is the first assessment of the prevalence in Blattella germanica in faecal pellets. The presence of protozoa in faecal pellets provides some evidence for one step in a hypothesised route of respiratory infection whereby protozoa from household insects enter the respiratory tract. [ABSTRACT FROM AUTHOR]

Air pollutants harm human health and the environment. Nowadays, deploying an air pollution monitoring network in many urban areas could provide real-time air quality assessment. However, these networks are usually sparsely distributed and the sensor calibration problems that may appear over time lead to missing and wrong measurements. There is an increasing interest in developing air quality modelling methods to minimize measurement errors, predict spatial and temporal air quality, and support more spatially-resolved health effect analysis. This research aims to evaluate the ability of three feed-forward neural network architectures for the spatial prediction of air pollutant concentrations using the measures of an air quality monitoring network. In addition to these architectures, Support Vector Machines and geostatistical methods (Inverse Distance Weighting and Ordinary Kriging) were also implemented to compare the performance of neural network models. The evaluation of the methods was performed using the historical values of seven air pollutants (Nitrogen monoxide, Nitrogen dioxide, Sulphur dioxide, Carbon monoxide, Ozone, and particulate matters with size less than or equal to 2.5 μ m and to 10 μ m) from an urban air quality monitoring network located at the metropolitan area of Madrid (Spain). To assess and compare the predictive ability of the models, three estimation accuracy indicators were calculated: the Root Mean Squared Error, the Mean Absolute Error, and the coefficient of determination. FFNN-based models are superior to geostatistical methods and slightly better than Support Vector Machines for fitting the spatial correlation of air pollutant measurements. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the agreement rate between hysteroscopy and pathological examination in case of chronic endometritis. Methods: A retrospective observational study carried out at Gynecology and Obstetrics Department, Puerta de Hierro Hospital, Autónoma University of Madrid, Spain, from January 2021 to June 2022 was performed by obtaining data from 115 medical records of women who underwent office hysteroscopies that was compared with the findings of final histological examination of endometrial biopsy. Cohen's kappa index was used to evaluate this agreement rate. In addition, sensitivity, specificity, positive and negative predictive value and diagnostic accuracy were obtained. Results: The agreement between hysteroscopic findings and histological examination showed a modest result with a Cohen's kappa index of 34%. In addition, we obtained a specificity of 70% and a sensitivity of 64%. The positive and negative predictive value were 60.8% and 73.4%, respectively. An excellent agreement rate (100%) between histological and hysteroscopic results was observed in presence of hyperemia and micropolyps. Conclusion: Although the sample size is not as large as that of other studies published so far, the first glance of our experience is that hysteroscopic signs are not yet sufficient to make an accurate diagnosis of chronic endometritis, thus requiring a histopathological confirmation to make it. [ABSTRACT FROM AUTHOR]

This paper presents evaluation of a plan for surveillance of and controlling the effects of heat-related mortality (PSCEHW), implemented in Madrid in 2004 through a time series analysis conducted with ARIMA modeling. From the public health point of view, prevention plans should be implemented as adaptive measures to heat waves. In 2003, the impact attributable to the heat wave was an increase in mortality per °C of 22.39 %. All heat waves since 2003 have been of lower intensity, and yet, in 2005 there was a heat wave of lower intensity that had a greater impact, i.e. an increase in mortality per °C of 45.71 %. With the methodology used here, we cannot say whether implementation of PSCEHW has resulted in a decrease of mortality attributable to high temperatures in the city of Madrid. [ABSTRACT FROM AUTHOR]

Much work has been done in the context of the hedonic price theory to estimate the impact of air quality on housing prices. Research has employed objective measures of air quality, but only slightly confirms the hedonic theory in the best of cases: the implicit price function relating housing prices to air pollution will, ceteris paribus, be negatively sloped. This paper compares the performance of a spatial Durbin model when using both objective and subjective measures of pollution. On the one hand, we design an Air Pollution Indicator based on measured pollution as the objective measure of pollution. On the other hand, the subjective measure of pollution employed to characterize neighborhoods is the percentage of residents who declare that the neighborhood has serious pollution problems, the percentage being referred to as residents' perception of pollution. For comparison purposes, the empirical part of this research focuses on Madrid (Spain). The study employs a proprietary database containing information about the price and 27 characteristics of 11,796 owner-occupied single family homes. As far as the authors are aware, it is the largest database ever used to analyze the Madrid housing market. The results of the study clearly favor the use of subjective air quality measures. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose an integrated planning model to adequate the offered capacity and system frequencies to attend the increased passenger demand and traffic congestion around urban and suburban areas. The railway capacity is studied in line planning, however, these planned frequencies were obtained without accounting for rolling stock flows through the rapid transit network. In order to provide the problem more freedom to decide rolling stock flows and therefore better adjusting these flows to passenger demand, a new integrated model is proposed, where frequencies are readjusted. Then, the railway timetable and rolling stock assignment are also calculated, where shunting operations are taken into account. These operations may sometimes malfunction, causing localized incidents that could propagate throughout the entire network due to cascading effects. This type of operations will be penalized with the goal of selectively avoiding them and ameliorating their high malfunction probabilities. Swapping operations will also be ensured using homogeneous rolling stock material and ensuring parkings in strategic stations. We illustrate our model using computational experiments drawn from RENFE (the main Spanish operator of suburban passenger trains) in Madrid, Spain. The results show that through this integrated approach a greater robustness degree can be obtained. [ABSTRACT FROM AUTHOR]