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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 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 fatigue design of bus structures is directly dependent on the loads that the vehicle will support throughout its lifespan. The determination of such operational loads, obtained in form of accelerations through vehicle sensing, is usually done with proprietary and expensive acquisition systems. In this paper, a low-cost acquisition system is presented and studied, which is designed, calibrated, and oriented for this purpose, based on an Arduino UNO and a low-cost accelerometer. The acquisitions are adapted to obtain the operational loads of several urban bus lines in the city of Madrid. The obtained data is later processed in order to characterize the acceleration cycles in these structures, which can be used as an input for the appropriate structural design. As a result, it is proved that the low-cost acquisition system is adequate and provides a simple and cheap way to characterize the acceleration of these vehicles during ordinary service. [ABSTRACT FROM AUTHOR]

In civil aviation flight path planning, in order to effectively reduce the safety threat caused by the volcanic ash area to the civil aviation flight, factors such as the speed and acceleration of the aircraft in the volcanic ash area must be considered. In this paper, we propose an improved A-star algorithm by adopting the concept of potential collision set and using the velocity vector idea of optimal reciprocal collision avoidance (ORCA). The improved A-star algorithm selects the optimal speed range of the aircraft from the limited elements, obtains the speed and acceleration set of the aircraft in the volcanic ash area, calculates the flight path through the displacement increment, continuously refreshes the global starting point to the target point, and finally obtains the final path planning results by calculating the total cost value. The improved A-star algorithm is used to plan two flight paths from Madrid to Cairo and Algiers to Rome in volcanic ash areas. The verification results show that the improved A-star algorithm optimizes the flight path planning in the volcanic ash area and has the advantages of less search nodes, a small search range, and short computing time. [ABSTRACT FROM AUTHOR]

Summary: In the present paper, the economic feasibility of small‐scale solar organic Rankine cycle power applications which are assisted with auxiliary gas heaters is investigated. The system is analyzed using three different capacities of ORC system with R‐245fa (35, 65, and 110 kWe) in combination with solar water heating system (SWHS) using three models. Flat plate, compound parabolic and evacuated tube solar collectors were used to generate heat with overall heat transfer coefficient (FRUL) of 4.35, 1.57, and 2.23 W/m2. K respectively. System Advisor Model (SAM) is used to simulate the solar water heater system and optimize the tilt angle, collector area, volume of storage tank and capacity of auxiliary heater under the climatic conditions of Abu Dhabi, New Delhi, Larnaca, Madrid and Munich. The simulation results revealed that the evacuated tube and the compound parabolic collectors performed better than the flat plate collectors. The economic analysis showed that Solar ORC Power Plant is economically and technically feasible with all types of the thermal collectors in Famagusta/Larnaca, Munich and Madrid where the electricity tariff is higher than other cities. Levelized cost of energy (LCOE) is calculated using mathematical model and it ranges between 0.07 and 0.2 USD/kWh based on the plant capacity and type of thermal collectors. Moreover, the profit increase as the plant capacity increase where SIR is 1.05, 1.71, and 2.10 for 35, 65, and 110 kW plant capacity SORC with CPC. A sensitivity analysis is also performed to investigate the effect of operating hours, electricity tariff, ORC unit cost and ORC unit type on the feasibility of the system. According to the results, the electricity tariff and operating hours are the most important parameters because they have a large effect and Play important role on the economic feasibility of the system. [ABSTRACT FROM AUTHOR]

Nuclear fusion is the process by which two or more atomic nuclei join together to form a single heavier nucleus. This is usually accompanied by the release of large quantities of energy. This energy could be cheaper, cleaner, and safer than other technology currently in use. Experiments in nuclear fusion generate a large number of signals that are stored in huge databases. It is impossible to do a complete analysis of this data manually, and it is essential to automate this process. That is why machine learning models have been used to this end in previous years. In the literature, several popular algorithms can be found to carry out the automatic classification of signals. Among these, ensemble methods provide a good balance between success rate and internal information about models. Specifically, AdaBoost algorithm will allow obtaining an explicit set of rules that explains the class for each input data, adding interpretability to the models. In this paper, an innovative approach to perform an online classification, that is, to identify the discharge before it actually ends, using interpretable models is presented. In order to evaluate and reveal the benefits of rule-based models, an illustrative example has been implemented to perform an online classification of five different signals of the TJ-II stellarator fusion device located in Madrid, Spain. [ABSTRACT FROM AUTHOR]

Background and Objectives. Although pets are known to be beneficial for children, they could also imply risks for immunocompromised ones. We report the prevalence of children and young patients living with pets in a cohort of immunosuppressed pediatric patients and describe risk behaviors for acquiring zoonosis and compliance with veterinary recommendations. Methods. A cross-sectional, observational study was performed in a large tertiary hospital in Madrid, including immunosuppressed patients from different regions of Spain. The participants were asked to complete an online questionnaire. Results. Two hundred and eighty-four responses were received: 62.3% solid organ transplantation (177/284), 22.8% hematopoietic stem cell transplantation (65/284), and 14.8% inborn errors of immunity (42/284). The median age was 11 years (interquartile range 5.9-15.4), and 55% were boys (156/284). Up to 45% (130/284) of the respondents lived with 201 pets (74% of them dogs and cats). Half of the patients owning dogs or cats did not comply with at least one of the recommendations regarding vaccination, deworming, feeding, and/or veterinarian recommended controls. The poorest findings were related to deworming regimens. Only 42.8% (117/273) of the participants received specific recommendations from their healthcare professionals about companion animals. However, up to 97% of the families considering acquiring a pet did so when the professional did not contraindicate it (31/32), while 72% of the families having pets got rid of their pets when they were advised against animals (8/11). Conclusions. Pet ownership is frequent among immunocompromised children. They presented risky exposures for acquiring zoonoses, and basic veterinary recommendations were not frequently followed. The opinion of professionals significantly influenced the decision to acquire pets, but less than half of the families received recommendations in this regard. [ABSTRACT FROM AUTHOR]

Costa Rica has a low incidence of tuberculosis. Thus, identifying transmission hotspots is key to implement interventions. A tuberculosis outbreak was suspected in a prison in Costa Rica. Given the suboptimal quality of the samples received in our laboratory in Madrid, we applied alternative schemes for their analysis. In the first scheme, we bypassed the standard approach of applying systematic mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) and used a strain-specific polymerase chain reaction (PCR) that allowed identifying a cluster involving six cases (C1). The second scheme followed the canonical MIRU-VNTR path coupled with a whole-genomic amplification step, by which a second unsuspected overlapping cluster (C2), was detected in the same prison. These findings justified the implementation of a surveillance programme adapted to local resources based on a tailored multiplex allele-specific oligonucleotide (ASO)-PCR targeting C1 and C2. Presence of the C2 strain at a different prison was determined. ASO-PCR was applied extensively and alerted to the active circulation of one of the strains within and beyond prisons. Our study shows that alternative methodological strategies may provide useful data in settings with lack of resources for performing systematic standard molecular epidemiology programmes and/or with suboptimal material for analysis. [ABSTRACT FROM AUTHOR]

This paper presents a work whose objective is, first, to quantify the potential of the triticale biomass existing in each of the agricultural regions in the Madrid Community through a crop simulation model based on regression techniques and multiple correlation. Second, a methodology for defining which area has the best conditions for the installation of electricity plants from biomass has been described and applied. The study used a methodology based on compromise programming in a discrete multicriteria decision method (MDM) context. To make a ranking, the following criteria were taken into account: biomass potential, electric power infrastructure, road networks, protected spaces, and urban nuclei surfaces. The results indicate that, in the case of the Madrid Community, the Campiña region is the most suitable for setting up plants powered by biomass. A minimum of 17,339.9 tons of triticale will be needed to satisfy the requirements of a 2.2 MW power plant. The minimum range of action for obtaining the biomass necessary in Campiña region would be 6.6 km around the municipality of Algete, based on Geographic Information Systems. The total biomass which could be made available in considering this range in this region would be 18,430.68 t. [ABSTRACT FROM AUTHOR]

Phlebotomine sand flies are the only known vectors of Leishmania spp. protozoan which causes leishmaniasis in 98 countries. In Spain, 11 sand fly species are described, but only Phlebotomus perniciosus and Phlebotomus ariasi are proven vectors of the disease. On the other hand, Sergentomyia minuta is one of the most abundant and ubiquitous sand flies in this territory, although scarce information is available about this species. Sand flies from this genus are known for their preference to feed on cold‐blooded animals and are traditionally involved in the transmission of reptile Leishmania. However, studies have suggested that Sergentomyia spp. could be implicated in the transmission of human pathogenic Leishmania. This study analyses blood meal preferences and Leishmania sp. infection of S. minuta sand flies from the largest human leishmaniasis outbreak in Europe. Sand flies were collected during entomological surveillance carries out from 2012 to 2017 in the active season of these dipterans, from May to October. Molecular detection of Leishmania spp. showed 68 positive specimens of S. minuta out of 377 (18%). The analysis of blood meal preferences by amplification of 359 bp fragment of cytochrome b gene revealed that blood preference of S. minuta is not only limited to reptiles, but they also feed on mammals, including humans. Results suggest the presence of a Leishmania sp., related to Leishmania tarentolae, cycle in S. minuta from the studied area. Although there is no evidence about its incrimination in the L. infantum transmission more investigation is needed to elucidate the intravectorial cycle of Leishmania spp. in S. minuta sand flies, their feeding behaviour and their potential contribution in Leishmania spp. epidemiology in the country. [ABSTRACT FROM AUTHOR]

PM10‐bound polycyclic aromatic hydrocarbons (PAHs) levels were monitored at urban locations (outdoor/indoor) within the city of Madrid between May 2017 and April 2018. Fourteen PAH congeners were measured, potential emission sources were identified as were potential carcinogenic risks. The ΣPAHs averaged 0.577 and 0.186 ng/m3 in outdoor and indoor air, with a high linear correlation per individual mean PAH and month. The largest contributors to the ΣPAHs were the high‐molecular‐weight PAHs. Principal component analysis‐multiple linear regression results showed that emissions from diesel and vehicular processes explained 27% and 23% of the total variance of outdoor and indoor air, while combustion processes accounted for 30% and 25% in ambient and indoor air, respectively. During the cold season, biomass burning plus coal and wood combustion were additional sources of outdoor emissions. The heavy‐, medium‐ and light‐molecular‐weight PAH originating from outdoor sources accounted for 72%, 80%, and ~60% of the indoor levels of the three respective PAH groups. Average BaP concentration was 0.029 and 0.016 ng/m3 in outdoor and indoor air, respectively. Estimated BaPeq concentration averaged 0.072, 0.035, and 0.027 ng/m3 for outdoor, indoor, and indoor‐generated individual PAH concentrations, respectively. The estimated carcinogenic risk falls within the range of acceptable risk targeted by the US‐EPA. [ABSTRACT FROM AUTHOR]

In recent years, there has been a technological revolution affecting all areas of life, including health. Following this trend, a series of electronic devices called wearable technology have emerged with the aim of improving the quality of people's life. These devices are made up of tools that help to prevent the development of chronic diseases and fight against the aging of society by monitoring the vital signs of users. Despite the advantages of using these devices from medical and health points of view, it is necessary to know the opinion of users regarding their use. For this reason, this study has been proposed. The purpose of this study is to analyse the perceptions of the subjects involved in the research regarding the acceptance of wearable devices, taking into account variables, such as age and gender. To this end, a nonexperimental, ex post facto design has been composed that combines descriptive and inferential techniques, with a sample of 606 patients and relatives belonging to a public health centre in the community of Madrid. [ABSTRACT FROM AUTHOR]