Microplastics in snow of a high mountain national park: El Teide, Tenerife (Canary Islands, Spain)

Human activities have introduced high amounts of microplastics (MPs) into the atmosphere that can be transported long distances and be later deposited in terrestrial and aquatic ecosystems with precipitation (rain or snow). In this work, it has been assessed the presence of MPs in the snow of El Teide National Park (Tenerife, Canary Islands, Spain, 2150–3200 m above sea level) after two storm episodes (January–February 2021). The data set (63 samples) was divided into three groups: i) samples from “accessible areas” (after the first storm episode and in places with a strong previous/recent anthropogenic activity); ii) “pristine areas” (after the second storm episode, in places with no previous anthropogenic activity), and iii) “climbing areas” (after the second storm episode, in places with a soft recent anthropogenic activity). Similar pattern profiles were observed among sampling sites in terms of morphology, colour and size (predominance of blue and black microfibers of 250–750 μm length), as well as in composition (predominance of cellulosic -either natural or semisynthetic-, with a 62.7 %, polyester, 20.9 %, and acrylic, 6.3 %, microfibers); however, significant differences in MPs concentrations were found between samples collected in pristine areas (average concentration of 51 ± 72 items/L) and those obtained in places with a previous anthropogenic activity (average concentration of 167 ± 104 and 188 ± 164 items/L in “accessible areas” and “climbing areas”, respectively). This study shows, for the first time, the presence of MPs in snow samples from a high altitude protected area on an insular territory and suggests that the sources of these contaminants could be atmospheric transport and local human outdoor activitie

Molecular fingerprinting of Campylobacter and Arcobacter isolated from chicken and water

The potential of a fingerprinting method based on the single-enzyme amplified fragment length polymorphism (s-AFLP) technique was evaluated for its efficacy in detecting foodborne Campylobacter and Arcobacter species. Campylobacter and Arcobacter isolates from chicken and water samples were subjected to s-AFLP and pulsed-field gel electrophoresis (PFGE) profiling. Molecular typing revealed a high degree of heterogeneity. AFLP was found to be appropriate for differentiating minimal genomic variations, which makes this technique a valuable tool for the identification of isolates. PFGE was effective in showing epidemiological relationships among closely related isolates. Either technique allowed the discrimination of A. butzleri from A. cryaerophilus and A. skirrowii. When used together, s-AFLP and PFGE can be applied to determine taxonomic and epidemiological relationships among campylobacteria. [Int Microbiol 2007; 10(2):85-90

Recycled wastewater as a potential source of microplastics in irrigated soils from an arid-insular territory (Fuerteventura, Spain)

In this work, the occurrence of microplastics (MPs) in irrigation recycled wastewaters (RWWs) and a desalinated brackish water (DBW) from the arid territory of Fuerteventura (Canary Islands, Spain) was studied. Besides, the presence of MPs in two types of soils (sandy-loam and clay-loamy; with no mulch film or fertilization with sewage sludge applied) irrigated with both water qualities was addressed. Results showed the prevalence presence of cellulosic and polyester microfibers (between 84.4 and 100%) of blue and transparent colors (up to 55.6 and 33.3%, respectively), with an average length of 786.9 ± 812.1 μm in the water samples. DBW had the lowest MP concentration (2.0 ± 2.0 items·L−1) while RWW showed concentrations up to 40.0 ± 19.0 items·L−1. Similarities were also observed between the MPs types and sizes found in both soils top layer (0–5 cm), with an average concentration three times greater in soil irrigated with RWW than in soil under DBW irrigation (159 ± 338 vs. 46 ± 92 items·kg−1, respectively). In addition, no MPs were extracted from non-irrigated/non-cultivated soils, suggesting agricultural activities as the unique source of MPs in soils of this arid area. Results show that RWWs constitute a potential source of MPs in irrigated soils that should be considered among other pros and cons linked to the use of this water quality in agricultural arid land

Representing functional data in reproducing Kernel Hilbert spaces with applications to clustering, classification and time series problems

In modern data analysis areas such as Image Analysis, Chemometrics or Information Retrieval the raw data are often complex and their representation in Euclidean spaces is not straightforward. However most statistical data analysis techniques are designed to deal with points in Euclidean spaces and hence a representation of the data in some Euclidean coordinate system is always required as a previous step to apply multivariate analysis techniques. This process is crucial to guarantee the success of the data analysis methodologies and will be a core contribution of this thesis. In this work we will develop general data representation techniques in the framework of Functional Data Analysis (FDA) for classification and clustering problems. In Chapter 1 we motivate the problems to solve, describe the roadmap of the contributions and set up the notation of this work. In Chapter 2 we review some aspects concerning Reproducing Kernel Hilbert Spaces (RKHSs), Regularization Theory Integral Operators, Support Vector Machines and Kernel Combinations. In Chapter 3 we propose a new methodology to obtain finite-dimensional representations of functional data. The key idea is to consider each functional curve as a point in a general function space and then project these points onto a Reproducing Kernel Hilbert Space (RKHS) with the aid of Regularization theory. We will describe the projection methods, analyze its theoretical properties and develop an strategy to select appropriate RKHSs to represent the functional data. Following the functional data analysis approach, we develop in Chapter 4 a new procedure to deal with proximity (similarity or distance) matrices in classification problems by studying the connection between proximity measures and a certain class of integral operators. The idea is to come up with a methodology able to estimate an integral operator whose associated kernel function, evaluated at the sample, approximates the sample proximity matrix of the problem. To show the broad scope of application of the methodology,we will apply it to three cases: (1) classification problems where the only available information about the data is an asymmetric similarity matrix (2) partially labeled classification problems and (3) classification problems where several sources of information are available and can be combined to obtain the discrimination function. In Chapter 5 we propose an spectral framework for information fusion when the sources of information are given by a set of proximity matrices. Our approach is based on the simultaneous diagonalization of the original matrices of the problem and it represents a natural way to manage the redundant information involved in the fusion process. In particular, we define a new metric for proximity matrices and we propose a method that automatically eliminates the redundant information among a set of matrices when they are combined. We conclude the contributions of the thesis in Chapter 6 with a battery of simulated and real examples devoted to compare the performance of the proposed methodologies with the state of the art in representation methods. Finally, in Chapter 7 we include a discussion regarding the topics described above and we propose some future lines of research we believe are the natural extensions to the work developed in this thesis. ------------------------------------------------------------------------------------------------------------------------------------------------En áreas de análisis de datos tales como el Análisis de Imágenes, la Quimiometría o la Recuperación de Información los datos son complejos y su representación en espacios Euclídeos no es directa. Sin embargo, la mayoría de los procedimientos estadísticos están diseñados para trabajar con puntos en espacios Euclídeos. Por tanto, representar los datos en un sistema Euclídeo de coordenadas es el paso previo necesario al uso de técnicas estadísticas multivariantes. Este proceso es crucial a la hora de garantizar adecuadas soluciones a nuestros problemas y será el núcleo central de las contribuciones de esta tesis. En este trabajo desarrollaremos técnicas generales de representación de datos en problemas de clasificación y conglomerados en el marco del Análisis Funcional de Datos. En el Capítulo 1 motivaremos los problemas a resolver, describiremos las contribuciones y fijaremos la notación utilizada en este trabajo. En el Capítulo 2 revisamos algunos aspectos relacionados con los espacios de Hilbert de Núcleo reproductivo, la Teoría de Regularización, Operadores integrales, Máquinas de Vectores Soporte y métodos de Combinaciones de Núcleos. En el Capítulo 3, proponemos una nueva metodología para obtener representaciones de dimensión finita de datos funcionales. La idea clave es considerar cada dato funcional como un punto en un espacio general de funciones y posteriormente proyectar estos puntos en un espacio de Hilbert de Núcleo Reproductivo con la ayuda de la teoría de Regularización. En el Capítulo 3 describiremos el método de proyección, analizaremos sus propiedades teóricas y desarrollaremos una estrategia para seleccionar un espacio apropiado en el que representar los datos funcionales. Siguiendo el enfoque de análisis de datos funcionales, desarrollamos en el Capítulo 4 un nuevo procedimiento para trabajar con matrices de proximidades (similaridades o distancias) en problemas de clasificación y conglomerados estudiando la relación entre matrices de proximidad y cierta clase de operadores integrales. La idea es desarrollar una metodología capaz de estimar un operador integral cuya núcleo, evaluado en la muestra, aproxime la matriz de proximidad. Para mostrar la utilidad de la meteodología propuesta la aplicaremos en tres casos: (1) problemas de clasificación donde la información disponible sobre los datos es una matriz de similaridades asimétrica, (2) problemas de clasificación parcialmente etiquetados y (3) problemas de clasificación donde varias fuentes de infomación están disponibles y pueden ser combinadas para obtener el clasificador. En el Capítulo 5 proponemos un marco espectral para la fusión de infomación cuando las fuentes de información vienen dadas por un conjunto de matrices de proximidades. Nuestro enfoque está basado en la diagonalización simultánea de dichas matrices y representa un modo natural de tratar con la infomación redundante involucrada en el proceso de combinación. En particular, definiremos una nueva métrica para matrices de proximidades y propondremos un método que elimina automáticamente la infomación redundante de una serie de matrices cuando son combinadas. Concluimos las contribuciones de esta tesis en el Capítulo 6 con una batería experimentos reales y simulados cuyo objetivo es comparar la metodología propuesta con el estado de arte en métodos de representatión de objetos. Finalmente, en el Capítulo 7 incluimos una discusión sobre los temas tratados en anteriormente y futuras líneas de investigación que creemos son la prolongación natural de las contribuciones de esta tesis

Métodos numéricos con aplicaciones en Matlab

Métodos Numéricos es una disciplina de las Matemáticas en gran crecimiento gracias al avance tecnológico en las Ciencias Computacionales. Día tras día es más corriente su aprendizaje en estudiantes de Matemáticas, Ciencias e Ingeniería. Su desarrollo es una consecuencia natural de las necesidades que surgen de resolver problemas que tienen aplicación práctica en la vida real en áreas como: análisis financiero, ecuaciones diferenciales, estadística y probabilidades, geometría computacional, geometría de curvas y superficies, inteligencia artificial y redes neuronales, investigación operativa y simulación de sistemas, teoría de colas de optimización, tratamiento de imágenes en la robótica, ingeniería estructural o la aerodinámica de aviones, en la biología y medicina, entre otros tópicos de las matemáticas aplicadas

Creating and Disseminating Open Educational Resources (OER): Research Trends and the Basics for Newcomers

Distance-based courses offered through e-learning platforms are gaining in popularity and supporters, particularly those resources offered through the Internet due to their ability to transcend the limitations of time and space. In this context, it is essential that teachers and educational researchers become familiar with the main e-learning initiatives and the most outstanding content development software, particularly open source tools that facilitate free access to knowledge. The aim of this paper is to present a conceptual outline describing the most common topics addressed by e-learning researchers. Furthermore, we present some key points to consider in choosing the most appropriate design tools for digital learning objects, managing e-learning courses and preserving the copyright and integrity of developed contents. Finally, we offer a directory of some of the major open source initiatives that facilitate the access, use and exchange of Open Educational Resources (consortia, digital libraries and repositories).González Alcaide, G.; Hernández San Miguel, FJ. (2015). Creating and Disseminating Open Educational Resources (OER): Research Trends and the Basics for Newcomers. ICERI Proceedings. 8051-8055. http://hdl.handle.net/10251/575878051805

Microplastics determination in gastrointestinal tracts of european sea bass (Dicentrarchus labrax) and gilt-head sea bream (Sparus aurata) from Tenerife (Canary Islands, Spain)

Microplastic pollution has an extremely widespread distribution, to the extent that microplastics could be ingested by aquatic organisms, including species of commercial importance for fisheries and aquaculture. In this work, the anthropogenic particles content of the gastrointestinal tracts of 86 individuals of cultivated European sea bass (Dicentrarchus labrax, n = 45) and gilt-head sea bream (Sparus aurata, n = 41) from Tenerife (Canary Islands, Spain) was determined. Samples were bought at local markets and directly transported to the laboratory. After the dissection of the fishes and digestion of the gastrointestinal tracts in 10% KOH (w/v) at 60◦C for 24 h, the digests were filtered (50 µm stainless-steel mesh) and visualized under a stereomicroscope, finding that most of the items were colourless (47.7% for Dicentrarchus labrax and 60.9% for Sparus aurata) and blue (35.3% vs. 24.8%) microfibers, with an average length of 1957 ± 1699 µm and 1988 ± 1853 µm, respectively. Moreover, 15.3% of the microfibres were analysed by Fourier transform infrared spec-troscopy, showing the prevalence of cellulosic fibres together with polyester, polyacrylonitrile, and poly(ether-urethane). This pattern (microplastics shapes, colours, sizes, and composition) clearly agrees with previous studies carried out in the Canary Islands region regarding the determination of microplastics in the marine environmen

Botrylactone: new interest in an old moleculedreview of its absolute configuration and related compounds

The absolute configuration of botrylactone, a unique compound with an interesting polyketide lactone skeleton with two oxirane bridges previously isolated from Botrytis cinerea and described as a powerful antibiotic, has been reviewed on the basis of sign of the optical rotation, NOE experiments and NMR method. The isolation of 7-deoxybotrylactone and 5-hydroxy-7-(4-hydroxydec-2(3)-enoyl) botrylactone enables us to characterize an intriguing new family of compounds with this interesting polyketide skeleton. A common biosynthetic origin with botcinin derivatives is proposed