Nuevos métodos de estudio de la erosión

La erosión constituye un grave problema tanto para la agricultura como para el ambiente. Sin embargo, es difícil obtener una estimación precisa del fenómeno erosivo por la complejidad de los procesos implicados. El objetivo fundamental de esta tesis es la propuesta de modelos que permitan describir tanto las pérdidas de suelo como sus patrones de redistribución. Para describir los procesos implicados en la erosión no hay un modelo único. Por ello, se aborda el estudio de la erosión desde dos perspectivas conceptualmente diferentes caracterizadas por su escala de trabajo: la primera de ellas que se puede calificar como macroscópica, está basada en un planteamiento de ecuaciones fundadas en observaciones experimentales que describen los fenómenos. La segunda, situada en el nivel mesoscópico, consiste en el establecimiento de un mundo ficticio compuesto de partículas simples y regido por reglas sencillas capaces de caracterizar el fenómeno incluyendo aspectos básicos como la conservación de la cantidad de movimiento y de la masa. El protagonista de esta segunda perspectiva es el modelo de malla de Boltzamann o "lattice Boltzmann model". En la primera parte de esta tesis se hace una aproximación macroscópica, revisando diversas propuestas para la ecuación de erosión y desarrollando el modelo TERON, diseñado para el estudio de la erosión mecánica. La solución analítica que determina la redistribución de suelo en torno a un obstáculo también es expuesta. La segunda parte comienza con una descripción del autómata celular y su evolución, el modelo de malla de Boltzmann denominado BGK, continuando con la obtención de los campos de velocidades de un flujo en presencia de obstáculos aislados o en grupo. La determinación de la redistribución de suelo en torno a una barrera se realiza desde dos puntos de vista. La primera de ellas se basa en el uso del modelo BGK para la advección y para la difusión, mientras que la segunda emplea el modelo anterior para el cálculo del campo de velocidades y la técnica del camino aleatorio para la componente difusiva. Los resultados obtenidos muestran que la aproximación mesoscópica para caracterizar los fenómenos erosivos es apropiada

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

Multifractal analysis application to the study of fat and its infiltration in Iberian ham: Influence of racial and feeding factors and type of slicing

This paper explores the multifractal features of different commercial designations of Iberian ham (acorn 100% Iberian ham, acorn Iberian ham, feed/pasture Iberian ham and feed Iberian ham). This study has been done by taking as input the fatty infiltration patterns obtained from digital image analysis of ham cuts comparing mechanic and manual slicing. The yielded results show the multifractal nature of fatty connective tissue in Iberian ham, only when knife cutting is applied, confirming the differences between the designations according to their genetics and feeding. Thus, the multifractal parameters presented in this work could be considered as additional information for checking Iberian ham quality by using non-destructive methods based on the combination of image analysis and predictive techniques. Meat industry can take advantage of these methods to evaluate meat products, especially when fat-connective tissue with complex pattern distribution is involved

Background PM10 atmosphere: In the seek of a multifractal characterization using complex networks

In the literature, several epidemiological studies have already associated respiratory and cardiovascular diseases to acute exposure of mineral dust. However, frail people are also sensitive to chronic exposure to particulate matter with an aerodynamic diameter 10μm or less (PM10). Consequently, it is crucial to better understand PM10 fluctuations at all scales. This study investigates PM10 background atmosphere in the Caribbean area according to African dust seasonality with complex network framework. For that purpose, the regular Visibility Graph (VG) and the new Upside-Down Visibility Graph (UDVG) are used for a multifractal analysis. Firstly, concentration vs degree (v-k) plots highlighted that high degree values (hubs behavior) are related to the highest PM10 concentrations in VG while hubs is associated to the lowest concentrations in UDVG, i.e. probably the background atmosphere. Then, the degree distribution analysis showed that VG and UDVG difference is reduced for high dust season contrary to the low one. As regards the multifractal analysis, the multifractal degree is higher for the low season in VG while it is higher for the high season in UDVG. The degree distribution behavior and the opposite trend in multifractal degree for UDVG are due to the increase of PM10 background atmosphere during the high season, i.e. from May to September. To sum up, UDGV is an efficient tool to perform noise fluctuations analysis in environmental time series where low concentrations play an important role as wel

Wet scavenging process of particulate matter (PM10): A multivariate complex network approach

Datos de investigación disponibles en: http://www.gwadair.frThis paper reports the results of research on PM10 wet scavenging by rainfall using a new multilayer complex networks called Multiplex Visibility Graphs (MVG). To the best of our knowledge, this work is the first to assess PM10 wet deposition using multivariate time series according to African dust seasonality. We considered 11 years of daily PM10 and rainfall data from the Guadeloupe archipelago. To analyse the impact of rainfall on PM10 behaviour, two MVG parameters were computed: the average edge overlap (ω) and the interlayer mutual information (IPM). On the 1-d scale, the ω results showed that the wet scavenging process was higher during the second half of the year when the high dust season and the rainy season are juxtaposed. This highlights a greater correlation between the microscopic structure of the signal, and the impact of rainfall on PM10 concentrations is more significant when the atmosphere is loaded with dust. The joint probability computed between the PM10 and rainfall nodes confirmed this trend. The IPM results indicated a correlation between PM10 and rainfall structures throughout the year. Furthermore, IPM values were higher during the transition periods between winter and summer (and vice versa). Our study showed that MVG is a powerful technique for investigating the relationship between at least two nonlinear time series using a multivariate time series

Checking complex networks indicators in search of singular episodes of the photochemical smog

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Hölder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature

Digital Image Filtering Optimization Supporting Iberian Ham Quality Prediction

Digital images of food for later analysis tend to be heterogeneous in terms of color and luminosity. Improving these images by using filters is necessary and crucial before further processing. This paper compares the non-use of filters and the use of high-pass filters in the images of hand-cut Iberian ham that will be used in a multifractal analysis for the study of fat and its infiltration. The yielded results show that with the use of a high-pass filter, more accurate fractal dimensions were obtained, which can be featured in predictive techniques of Iberian ham quality

Buenas prácticas de innovación docente en la Universidad de Córdoba

El proyecto presenta una aplicación informática basada en la visión estereoscópica para facilitar al profesorado y al alumnado la asimilación de conceptos aplicados en la Expresión Gráfica en la Ingeniería; su desarrollo ha contado con un presupuesto de unos 2.900 euros. Se trata, por tanto, de una solución sencilla con los anaglifos como principales protagonistas, que ofrece un nuevo sistema de aprendizaje sostenible en el tiempo y de gran portabilidad

Visibility graphs of ground-level ozone time series: A multifractal analysis

A recent method based on the concurrence of complex networks and multifractal analyses is applied for the first time to explore ground-level ozone behavior. Ozone time series are converted into complex networks for their posterior analysis. The searched purpose is to check the suitability of this transformation and to see whether some features of these complex networks could constitute a preliminary analysis before the more thorough multifractal formalism. Results show effectively that the exposed transformation stores the original information about the ozone dynamics and gives meaningful knowledge about the time series. Based on these results, the multifractal analysis of the complex networks is performed. Looking at the physical meaning of the multifractal properties (such as fractal dimensions and singularity spectrum), a relationship between those and the degree distribution of the complex networks is found. In addition to all the promising results, this novel connection between time series and complex networks can deal with both stationary and non-stationary time series, overcoming one of the main limitations of multifractal analysis. Therefore, this technique can be regarded as an alternative to give supplementary information within the study of complex signals

Relationships between Reference Evapotranspiration and Meteorological Variables in the Middle Zone of the Guadalquivir River Valley Explained by Multifractal Detrended Cross-Correlation Analysis

The multifractal relationship between reference evapotranspiration (ET0), computed by the Penmann-Monteith equation (PM), relative humidity (RH) and mean surface temperature (Tmean) was studied in the middle zone of the Guadalquivir River Valley (south Spain) in a previous study. This work extends that study to the average wind speed (U2) and solar radiation (SR), focusing on more recent years. All agro-meteorological variables were analyzed by multifractal detrended cross-correlation analysis (MFCCA) and multifractal detrended fluctuation analysis (MFDFA). The outcomes revealed persistent long-term autocorrelations, with Tmean and RH having the highest persistence (H>0.75). More precise results of multifractal properties than in the previous study were obtained for ET0, Tmean, and RH due to the elimination of trends in the signals. Only medium and large fluctuations in ET0 showed multifractal cross-correlations with its controlling factors, except for U2. Moreover, joint scaling exponents differed from individual exponents. These phenomena contrast with what has been observed in previous cross-correlation studies, revealing that some differences exist in the dynamics of multifractality among the analyzed variables. On the other hand, the Tmean–ET0 relation showed that extreme events in ET0 are mainly ruled by high temperature fluctuations, which match conclusions drawn in the previous study