A fast UTD-Based method for the analysis of multiple acoustic diffraction over a series of obstacles with arbitrary modeling, height and apacing

A uniform theory of diffraction (UTD)-based method for analysis of the multiple diffraction of acoustic waves when considering a series of symmetric obstacles with arbitrary modeling, height and spacing is hereby presented. The method, which makes use of graph theory, funicular polygons and Fresnel ellipsoids, proposes a novel approach by which only the relevant obstacles and paths of the scenario under study are considered, therefore simultaneously providing fast and accurate prediction of sound attenuation. The obstacles can be modeled either as knife edges, wedges, wide barriers or cylinders, with some other polygonal diffracting elements, such as doubly inclined, T- or Y-shaped barriers, also considered. In view of the obtained results, this method shows good agreement with previously published formulations and measurements whilst offering better computational effciency, thus allowing for the consideration of a large number of obstacles.This work has been funded by the Ministerio de Economía y Competitividad (MINECO), Spain (TEC2016-78028-C3-2-P), and by European Fonds Européen de Développement Économique et Régional (FEDER) funds

Traffic noise mitigation using single and double barrier caps of different shapes for an extended frequency range

The primary function of noise barriers is to shield inhabitants of affected areas from excessive noise generated by road traffic. To enhance the performance of noise barriers while simultaneously adhering to height restrictions, the attachment of structures (caps) of different shapes to the tops of conventional screens can be considered. These caps can significantly impact the diffracted sound energy, thereby increasing the desired global acoustic losses. This work presents a comprehensive study of the acoustic performance of noise barriers with single and double attached caps of different shapes through a calculation of their insertion losses (IL). This study comprehensively addresses and compares different types, sizes, combinations, and numbers of noise barrier caps for different scenarios (including sloping and absorbent grounds) and sources (“car” and “ambulance”) for an extended frequency band up to 10 kHz. To the best of the authors’ knowledge, this is a range that has not previously been analyzed. A variety of different cap shapes were considered including cylinders, rectangles, trapezoids, and Y/T-shaped forms. To calculate the IL, an innovative and fast uniform theory of diffraction (UTD)-based method developed by the authors was applied in all simulations. The results showed that the Y-shaped single and double barrier caps were, in general, the most effective at increasing IL without raising the height of the barrier, thereby successfully managing the aesthetic impact. The results also showed how the consideration of sloping and absorbent floors could also contribute to improved noise abatement.This work was funded by the Ministerio de Ciencia e Innovación, Spain (TEC2016-78028-C3-2-P and PID2019-107885GB-C33), and by the European Fonds Européen de Développement Économique et Régional (FEDER) funds

Análisis de métodos deterministas para el cálculo de pérdidas por propagación a 390 MHz con corrección morfográfica

This work is concerned with the assesment of two different predictive propagation loss models (ITU-R 526 - extended Epstein-Peterson and Deygout) taking into account morfographical data corrections. Comparison of the estimations with measurements have been made at 390 MHz

A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose levels every day, employing capillary glucometers for the monitoring of blood glucose dynamics. In recent years, advances in technology have allowed for the creation of revolutionary biosensors and continuous glucose monitoring (CGM) techniques. This has enabled the monitoring of a subject’s blood glucose level in real time. On the other hand, few attempts have been made to apply machine learning techniques to predicting glycaemia levels, but dealing with a database containing such a high level of variables is problematic. In this sense, to the best of the authors’ knowledge, the issues of proper feature selection (FS)—the stage before applying predictive algorithms—have not been subject to in-depth discussion and comparison in past research when it comes to forecasting glycaemia. Therefore, in order to assess how a proper FS stage could improve the accuracy of the glycaemia forecasted, this work has developed six FS techniques alongside four predictive algorithms, applying them to a full dataset of biomedical features related to glycaemia. These were harvested through a wide-ranging passive monitoring process involving 25 patients with DM1 in practical real-life scenarios. From the obtained results, we affirm that Random Forest (RF) as both predictive algorithm and FS strategy offers the best average performance (Root Median Square Error, RMSE = 18.54 mg/dL) throughout the 12 considered predictive horizons (up to 60 min in steps of 5 min), showing Support Vector Machines (SVM) to have the best accuracy as a forecasting algorithm when considering, in turn, the average of the six FS techniques applied (RMSE = 20.58 mg/dL)

MIMOGIS: herramienta SIG para el análisis de radiocanales MIMO

En este artículo se presenta la aplicación MIMOGIS, basada en un Sistema de Información Geográfica (SIG), cuyo fin es facilitar la simulación de canales MIMO (Multiple-Input Multiple-Output). MIMOGIS es capaz de estimar la capacidad máxima teórica MIMO en entornos de propagación microcelulares e indoor. El modelo de propagación para estimar la función de transferencia del canal está basado en Óptica Geométrica (OG) y en la Teoría Uniforme de la Difracción (UTD). MIMOGIS permite el uso de cualquier tipo de configuración de arrays de antenas, tanto en transmisión como en recepción, ya que el usuario es capaz de introducir las coordenadas en 3 dimensiones (3D) de cada uno de los elementos que forman ambos arrays.Dirección General de Investigación (Consejería de Educación y Cultura de la Comunidad Autónoma de la Región de Murcia) por su financiación de este trabajo a través del proyecto con referencia 2I05SU0031), y a las empresa TECNICA y 102NOVADOC

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Desarrollo y validación de modelos teóricos de estimación de pérdidas de ondas sonoras para la caracterización y mejora de entornos acústicos

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Actualmente, existen numerosas herramientas software de uso profesional capaces de estimar las pérdidas de propagación acústica de escenarios complejos si se dispone de ordenadores de cierta potencia computacional. No obstante, los métodos y herramientas existentes, o bien son incapaces de abordar, de manera eficiente, la estimación de las pérdidas de propagación acústica en entornos heterogéneos (con múltiples obstáculos de diferente forma, altura y localización), o bien el tiempo de cálculo para dicha predicción crece exponencialmente con el número de obstáculos o la frecuencia. El núcleo fundamental de esta tesis lo constituye el desarrollo de un método general, basado en la Teoría Uniforme de la Difracción (UTD), para el análisis de la difracción múltiple de ondas acústicas sobre series de obstáculos con formas, alturas y separaciones entre los mismos arbitrarios, desde un enfoque completamente diferente, haciendo uso de la teoría de grafos, definición de polígonos funiculares y elipsoides de Fresnel. Todo ello con el fin último de considerar sólo los obstáculos y caminos relevantes de un escenario complejo. El método desarrollado proporciona una predicción de la atenuación del sonido rápida y eficiente desde el punto de vista computacional, al mismo tiempo que precisa. Sobre esta base, es posible analizar, en un tiempo aceptable, un gran número de obstáculos (incluidos aquellos vecinos de igual altura) modelados como aristas, cuñas, barreras rectangulares o cilindros, así como otras estructuras poligonales, como por ejemplo en forma de “T” ó “Y”. El desarrollo de esta metodología se ha integrado en una aplicación software (PARDOS, Pérdidas Acústicas por Reflexión y Difracción de la Onda Sonora) que proporciona una interfaz gráfica al usuario sencilla y amigable que pueda ser útil tanto a estudiantes que se inicien en los fenómenos de propagación acústica como a profesionales de este sector, ya que permitirá analizar, diseñar y optimizar, acústicamente, la respuesta de escenarios complejos ante fuentes sonoras. De esta manera, con la aplicación desarrollada, se analizará, por ejemplo, el rendimiento de barreras acústicas para mitigación del ruido del tráfico en un rango de frecuencia extendido. Finalmente, con el fin de ampliar el análisis de la propagación de ondas sonoras en otro tipo de entornos acústicos, esta tesis también comprende el desarrollo de un software (SAILOR, Software for the Acoustic Insertion Loss Rate) para la estimación de las pérdidas de inserción en paneles monocapa o multicapa submarinos, así como una campaña de medidas experimentales encaminadas a validar dicho software. Las metodologías desarrolladas e integradas en las aplicaciones mencionadas permiten múltiples líneas de investigación futura para asistir en el diseño, estudio y optimización de escenarios, en el caso de PARDOS, o de materiales, mediante SAILOR, en términos de los requisitos acústicos que sea preciso satisfacer. Todo ello de forma rápida y precisa, sin costosos procesos de fabricación de muestras, o sin tener que disponer de entornos reales en los que medir extensamente con dispositivos calibrados. [ENG] This doctoral dissertation has been presented in the form of thesis by publication.La presente tesis doctoral se encuadra bajo la modalidad de compendio de publicaciones. A continuación, se refieren los artículos publicados: 1. D. Pardo-Quiles, J.-V. Rodríguez, R. Lozano-Giménez, L. Juan-Llácer and J. Pascual-García, “On the Influence of Obstacle Modeling in Multiple Diffraction of Acoustic Waves”, Acta Acustica united with Acustica, Vol. 105 (2019) 261 – 264; doi: 10.3813/AAA.919308. 2. D. Pardo-Quiles and J.-V. Rodríguez, “A Fast UTD-based Method for the Analysis of Multiple Acoustic Diffractions over a Series of Obstacles with Arbitrary Modeling, Height and Spacing”, Symmetry, 12 (654), 1-24 (2020); doi:10.3390/sym12040654. 3. D. Pardo-Quiles J.-V. Rodríguez, J.-.M. Molina García-Pardo and L. Juan-Llácer, “Traffic Noise Mitigation Using Single and Double Barrier Caps of Different Shapes for an Extended Frequency Range”, Applied Sciences, 2020, 10, 5746; doi:10.3390/app10175746. 4. D. Pardo-Quiles, J.-V. Rodríguez, G. Romero-Valiente, R. Lozano-Giménez and L. Juan-Llácer, “Theoretical and experimental calculation of underwater acoustic insertion loss of monolithic panels”, Applied Acoustics, 172 (2021) 107608. https://doi.org/10.1016/j.apacoust.2020.107608. 5. D. Pardo-Quiles, J.-V. Rodríguez, and I. Rodríguez-Rodríguez, “PARDOS: An Educational Software Tool for the Analysis of Sound Propagation”. IEEE Access, Vol. 8, (2020), doi: 10.1109/ACCESS.2020.3033894.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma Doctorado en Tecnologías de la Información y las Comunicacione

Applications of artificial intelligence, machine learning, big data and the internet of things to the COVID-19 pandemic : A scientometric review using text mining

The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic

Modeling and Forecasting Gender-Based Violence through Machine Learning Techniques

Gender-Based Violence (GBV) is a serious problem that societies and governments must address using all applicable resources. This requires adequate planning in order to optimize both resources and budget, which demands a thorough understanding of the magnitude of the problem, as well as analysis of its past impact in order to infer future incidence. On the other hand, for years, the rise of Machine Learning techniques and Big Data has led different countries to collect information on both GBV and other general social variables that in one way or another can affect violence levels. In this work, in order to forecast GBV, firstly, a database of features related to more than a decade&rsquo;s worth of GBV is compiled and prepared from official sources available due to Spain&rsquo;s open access. Then, secondly, a methodology is proposed that involves testing different methods of features selection so that, with each of the subsets generated, four techniques of predictive algorithms are applied and compared. The tests conducted indicate that it is possible to predict the number of GBV complaints presented to a court at a predictive horizon of six months with an accuracy (Root Median Squared Error) of 0.1686 complaints to the courts per 10,000 inhabitants&mdash;throughout the whole Spanish territory&mdash;with a Multi-Objective Evolutionary Search Strategy for the selection of variables, and with Random Forest as the predictive algorithm. The proposed methodology has also been successfully applied to three specific Spanish territories of different populations (large, medium, and small), pointing to the presented method&rsquo;s possible use elsewhere in the world