Análisis multifractal de series de datos pluviométricos en Andalucía

Esta tesis doctoral analiza series temporales de datos de precipitación usando las teorías de la Criticalidad Autoorganizada y de la Multifractalidad. Para ello, se seleccionan diversas localidades situadas en Andalucía. En la primera de las aplicaciones se estudia la influencia de la resolución temporal de los datos de lluvia en los resultados obtenidos al aplicar las citadas teorías. Para ello se trabaja con datos de precipitación horaria y diaria, buscando por un lado diferencias entre los resultados obtenidos con ambas resoluciones, y por otro, la posible influencia en los resultados de la forma de precipitación más características de cada lugar. Como segunda aplicación, se analiza el potencial uso de ambas teorías para validar modelos de lluvia, para lo que se selecciona un modelo climático regional y el modelo Multifractal Universal. Finalmente se evalúa el posible uso de la multifractaalidad a la hora de discriminar, tanto el mejor método de análisis de frecuencias para la precipitación, como el modelo de curva Intensidad-Duración-Frecuencia más adecuado para una determinada localidad. Para todo ello en la presente tesis se describen los fundamentos teóricos de las teorías usadas, las características climáticas más relevantes de las localidades andaluzas seleccionadas, los resultados obtenidos tras las diversas aplicaciones y las conclusiones más relevantes de todos los análisis llevados a cab

Multifractal Characterization of Seismic Activity in the Provinces of Esmeraldas and Manabí, Ecuador

Due to the enormous impact of seismic activity and the need to deepen knowledge of its behavior, this research work carries out an analysis of the multifractal nature of the magnitude, inter-distance and interevent time series of earthquakes that occurred in Ecuador during the years 2011–2017 in the provinces of Manabí and Esmeraldas, two areas with high seismic activity. For this study we use multifractal detrended fluctuation analysis (MF-DFA), which allows the detection of multifractality in a non-stationary series as well as in a series of parameters of non-linear characterization. The obtained results revealed that an interevent time series presents a higher degree of multifractality than the two previously mentioned. In addition, the Hurst exponent values were in a non-proportional function to (q), which is a weight value indicating the multifractal behavior of the dynamics of the earthquakes analyzed in this work. Finally, several multifractal parameters were calculated, and as a result all series were skewed to the right. This reveals that small variations in the analyzed series were more dominant than large fluctuations

Universal multifractal description of an hourly rainfall time series from a location in southern Spain

El formalismo multifractal de turbulencia ha sido usado para llevar a cabo el análisis de la estructura temporal, para escalas desde 1 hora hasta casi 6 meses, de la serie de datos de lluvia horaria registrada durante veinticuatro años en Córdoba, localidad situada en el sur de España. Los parámetros del modelo multifractal universal fueron estimados y se obtuvo la función teórica de los momentos estadísticos. Se encontró un buen ajuste a la función empírica para un intervalo de valores de momentos, demostrándose que el modelo multifractal universal resulta adecuado para describir estadísticamente la serie temporal de lluvia registrada en CórdobaMultifractal turbulence formalism has been used to perform an analysis for scales from 1 hour to almost 6 months of the time structure of the hourly rainfall series recorded during twenty-four years in Córdoba, a location in southern Spain. The parameters of the universal multifractal model were estimated and the theoretical moments scaling exponent function was obtained exhibiting an acceptable agreement with the empirical function for a range of moments. The universal multifractal model shown itself to be a suitable tool for describing the statistics of the rainfall series recorded in Córdob

Assessing Machine Learning Models for Gap Filling Daily Rainfall Series in a Semiarid Region of Spain

The presence of missing data in hydrometeorological datasets is a common problem, usually due to sensor malfunction, deficiencies in records storage and transmission, or other recovery procedures issues. These missing values are the primary source of problems when analyzing and modeling their spatial and temporal variability. Thus, accurate gap-filling techniques for rainfall time series are necessary to have complete datasets, which is crucial in studying climate change evolution. In this work, several machine learning models have been assessed to gap-fill rainfall data, using different approaches and locations in the semiarid region of Andalusia (Southern Spain). Based on the obtained results, the use of neighbor data, located within a 50 km radius, highly outperformed the rest of the assessed approaches, with RMSE (root mean squared error) values up to 1.246 mm/day, MBE (mean bias error) values up to −0.001 mm/day, and R2 values up to 0.898. Besides, inland area results outperformed coastal area in most locations, arising the efficiency effects based on the distance to the sea (up to an improvement of 63.89% in terms of RMSE). Finally, machine learning (ML) models (especially MLP (multilayer perceptron)) notably outperformed simple linear regression estimations in the coastal sites, whereas in inland locations, the improvements were not such significant

AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models

Accurately forecasting reference evapotranspiration (ET0) values is crucial to improve crop irrigation scheduling, allowing anticipated planning decisions and optimized water resource management and agricultural production. In this work, a recent state-of-the-art architecture has been adapted and deployed for multivariate input time series forecasting (transformers) using past values of ET0 and temperature-based parameters (28 input configurations) to forecast daily ET0 up to a week (1 to 7 days). Additionally, it has been compared to standard machine learning models such as multilayer perceptron (MLP), random forest (RF), support vector machine (SVM), extreme learning machine (ELM), convolutional neural network (CNN), long short-term memory (LSTM), and two baselines (historical monthly mean value and a moving average of the previous seven days) in five locations with different geo-climatic characteristics in the Andalusian region, Southern Spain. In general, machine learning models significantly outperformed the baselines. Furthermore, the accuracy dramatically dropped when forecasting ET0 for any horizon longer than three days. SVM, ELM, and RF using configurations I, III, IV, and IX outperformed, on average, the rest of the configurations in most cases. The best NSE values ranged from 0.934 in Córdoba to 0.869 in Tabernas, using SVM. The best RMSE, on average, ranged from 0.704 mm/day for Málaga to 0.883 mm/day for Conil using RF. In terms of MBE, most models and cases performed very accurately, with a total average performance of 0.011 mm/day. We found a relationship in performance regarding the aridity index and the distance to the sea. The higher the aridity index at inland locations, the better results were obtained in forecasts. On the other hand, for coastal sites, the higher the aridity index, the higher the error. Due to the good performance and the availability as an open-source repository of these models, they can be used to accurately forecast ET0 in different geo-climatic conditions, helping to increase efficiency in tasks of great agronomic importance, especially in areas with low rainfall or where water resources are limiting for the development of crops

A Simple Scaling Analysis of Rainfall in Andalusia (Spain) under Different Precipitation Regimes

A simple scaling analysis was performed in Andalusia (Spain) using daily records from 377 selected stations covering the temporal period between 1870 and 2018. Since Andalusia is a region of considerable climatic variety, with notably wet areas as well as extremely dry zones, this study is useful to investigate the relationship between the simple scaling parameter value and the characteristic rainfall regime of a place. Despite the great correspondence with the average annual precipitation (PRCPTOT), a clear dependence on rainfall irregularity was observed, revealed by the ratio of the maximum daily precipitation and PRCPTOT, as well the wet spells frequency index CWD. The spatial distribution of the simple scaling parameter captured the increasing influence of the Mediterranean Sea towards the East. The easternmost dry areas are clearly influenced by Mediterranean disturbances, with a high proportion of convective rainfall and an irregular rainfall pattern. Using a simple scaling parameter, the generalized equations of the intensity-duration-frequency (IDF) curves, of great hydrological interest were calculated for the eight Andalusian provincial capitals. Moreover, the temporal trends of this parameter in the four past decades were studied in the different areas with the aim of determining if changes in their rainfall patterns due to global warming could be detected

Gamification and cooperative learning to improve the acquisition of Engineering Projects Competences

El presente proyecto plantea una combinación de las novedosas metodologías docentes: gamificación y aprendizaje cooperativo con el objetivo principal de mejorar la adquisición de competencias en Ingeniería de Proyectos. Todo ello se ha llevado a cabo mediante la elaboración de una práctica audiovisual en formato podcast sin interrupción para su difusión on-line, basada en el temario de cada una de las asignaturas involucradas: Restauración Hidrológico-Forestal (Grado de Ingeniería Forestal) y Proyectos (Grado de Física). El impacto favorable del empleo de esta metodología se ha podido observar tras el análisis de los resultados obtenidos, ya que la mejora en la percepción de las competencias evaluadas fue notable. Además, el presente proyecto puede servir de base para la implementación de experiencias similares en otras asignaturas de los profesores y departamentos implicados.The present project proposes a combination of the new teaching methodologies: gamification and cooperative learning, being the main goal the improvement in the acquisition of competences in Projects Engineering. All this has been carried out through the development of an audiovisual practice in podcast format without interruption for on-line dissemination, based on the topics of each of the subjects involved: Hydrological-Forest Restoration (Forest Engineering Degree) and Projects (Degree in Physics). The favourable impact of the use of this methodology has been observed after the analysis of the results obtained, since the improvement in the perception of the evaluated competences was remarkable. In addition, the present project can serve as the basis for the implementation of similar experiences in other subjects of the professors and departments involved

Desmetilación activa del ADN: un mecanismo epigenético para la reactivación de genes silenciados

Los mecanismos de control epigenético son esenciales para una regulación estable de los patrones de expresión génica y desempeñan un papel central en los ciclos de vida de animales y plantas. La metilación de la citosina en el carbono 5 del anillo de pirimidina (5-meC) es una marca epigenética estable, pero reversible, que promueve el silenciamiento génico transcripcional. Comprender cómo se regula el estado de metilación del genoma a nivel global o local requiere una definición de los procesos enzimáticos que metilan y desmetilan el ADN. Sin embargo, aunque las enzimas responsables del establecimiento y mantenimiento de la metilación de ADN han sido bien caracterizadas, los mecanismos de desmetilación no se conocen con exactitud. Nuestro grupo, junto con otros, ha obtenido datos genéticos y bioquímicos que sugieren que dos proteínas de Arabidopsis con dominio ADN glicosilasa (ROS1 y DME) actúan como ADN desmetilasas capaces de activar la expresión de genes previamente silenciados. Nuestros resultados previos indican que ROS1 y DME catalizan la liberación de 5-meC del ADN mediante un mecanismo ADN glicosilasa. Estos resultados sugieren que una de las funciones de ROS1 y DME es iniciar el borrado de 5-meC mediante un proceso de escisión de bases y proporcionan una importante evidencia bioquímica a favor de la existencia de una ruta de desmetilación activa en plantas. En la actualidad, nuestro grupo de investigación se concentra en caracterizar funcionalmente este novedoso mecanismo de control epigenético mediante una aproximación multidisciplinar que combina metodologías del campo de la bioquímica, la genética y la biofísica. Este estudio suministrará una información esencial para entender los mecanismos responsables de la reprogramación epigenética en el núcleo celular, con aplicaciones potenciales en biotecnología y biomedicin

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele