Near-Field Directionality Beyond the Dipole Approximation: Electric Quadrupole and Higher-Order Multipole Angular Spectra

Within the context of spin-related optical phenomena, the near-field directionality is generally understood from the quantum spin Hall effect of light, according to which the transverse spin of surface or guided modes is locked to the propagation direction. So far, most previous works have been focused on the spin properties of circularly polarized dipolar sources. However, in near-field optics, higher-order multipole sources (e.g., quadrupole, octupole, and so on) might become relevant, so a more in-depth formulation would be highly valuable. Building on the angular spectrum representation, we provide a general, analytical, and ready-to-use treatment in order to address the near-field directionality of any multipole field, particularizing to the electric quadrupole case. Besides underpinning and upgrading the current framework on spin-dependent directionality, our results may open up new perspectives for engineering light-matter coupling at the nanoscale.Comment: 7 pages, 2 figures. Supplemental Material (19 pages). Supplemental tools (calculator of angular spectra and animation) available at https://doi.org/10.5281/zenodo.267790

Detección automática de temperatura de personas en ambientes climatizados

Premio extraordinario de Trabajo Fin de Máster curso 2016-2017. Máster en Energías Renovables DistribuidasEl presente trabajo de fin de máster presenta un sistema para la segmentación automática de la frente de una persona para la recolección de temperaturas e interpretación de las mismas, que podrán ser tratados y estudiados en posteriores trabajos, como por ejemplo su inclusión en una unidad de control de climatización. La temperatura de la frente es conocida por estar altamente correlada con la temperatura corporal de una persona. El sistema de adquisición tiene la característica de ser no intrusivo y no influir ni modificar el comportamiento cotidiano de las actividades diarias de las personas. El sistema propuesto ha sido desarrollado para ser invariante en la medida de lo posible a diferentes cambios en la morfología de la cara de una persona, en la posición de la cabeza, y en la aparición de objetos externos. El método utilizado en el sistema propuesto ha sido optimizado en términos de tiempo de procesamiento. Además el presente sistema puede ser utilizado en otras aplicaciones en términos de tiempo real.This work presents a method for automatic segmentation of the person's forehead to obtain temperatures from this area and to analyze the data which could be used in future works. For instance, including this information inside of an air control unit. Temperature at the forehead is known to be highly correlated to the internal body temperature. Furthermore, the system has the feature to not be intrusive and not changing the daily habits of the people. The proposed system has been developed to be invariant to different changes in relation to the shape and position of the human face, and even in presence of external objects. The present method has been optimized in terms of time processing. Thus, it can be used in applications with real-time constraints. Keywords

Automatic system for pavement crack detection and classification

Las carreteras son un tipo de elemento urbanístico utilizado por millones de personas a diario, y su estado en condiciones óptimas favorece la disminución de la tasa de accidentes de tráfico. El estado de la superficie del asfalto se ve alterado por un amplio abanico de defectos, y en concreto, las grietas cobran un interés especial debido a que su tratamiento en fases tempranas pueden suponer un ahorro en el coste de reparación y tratamiento del defecto en etapas posteriores, así como evitar la aparición de defectos derivados de ellas. Por este motivo, el mantenimiento de los pavimentos juega un papel fundamental tanto en la seguridad de los usuarios de este tipo de vías, como en términos económicos. Sin embargo, a pesar de la importancia que tiene, existen millones de kilómetros que necesitan ser inspeccionados, y esta labor se realiza en la mayoría de los casos de forma manual mediante la inspección visual supervisada por expertos, siendo una tarea ineficiente en el tiempo. Por ello, esta Tesis Doctoral presenta un sistema para la detección y clasificación automática de defectos de grietas en pavimentos. Para ello, se aplican métodos de procesamiento de imágenes a las capturas tomadas de la superficie de los asfaltos para la extracción de características y su posterior optimización y representación a un nuevo espacio de atributos interpretables por una persona. Posteriormente estas características son utilizadas por un ensemble de modelos compuesto por varios algoritmos de aprendizaje automático, para realizar la clasificación de las grietas en sus tipos más comunes: grietas de tipo malla o cocodrilo, grietas longitudinales y grietas transversales. De acuerdo con los experimentos realizados y los resultados obtenidos, el sistema tiene la capacidad de trabajar en sistemas computacionales de recursos limitados, siendo susceptible de emplearse con restricciones de tiempo real, además de proporcionar mejores resultados frente a las propuestas existentes en la literatura científica. Esto hace posible que el sistema se pueda colocar en diferentes vehículos no especializados para la recolección y clasificación de los defectos en el mismo lugar donde ocurren, aliviando así la tareas llevadas a cabo por los expertos.Roads are a type of urban element used by millions of people every day, and the optimal surface condition contributes to the reduction of the rate of traffic accidents. The condition of the asphalt surface is affected by a wide range of defects, and particularly, cracks have a special interest because their treatment in early stages represent savings in the repairing costs. As this prevents the appearance of defects derived from them rather than treating the defects in later stages. For this reason, pavement maintenance is fundamental in economic terms and the safety of the users. Millions of kilometers need to be examined, however, this work is mostly done manually through visual inspection supervised by experts, which is a time inefficient task. For this reason, this Doctoral Thesis presents a system for the automatic detection and classification of cracking defects in pavements. For this purpose, image processing methods are applied to asphalt surface images extracting features of the cracks, reducing the number of features, and representing the cracks in a new interpretable space of attributes. These new attributes are used by an ensemble model composed of different automatic learning algorithms classifying the cracks into their most common types: mesh or alligator cracks, longitudinal cracks, and transverse cracks. According to the experiment results, the proposed system can work in computer systems with limited resources and could be used with real-time constraints. Also, the proposed methodology provides more accurate results compared to the existing proposals in the scientific literature. These features enable the system to be placed in non-specialized vehicles collecting and classifying the defects, in the same place where they occur, and simplifying the tasks carried out by experts

Learning to classify software defects from crowds: a novel approach

In software engineering, associating each reported defect with a cate- gory allows, among many other things, for the appropriate allocation of resources. Although this classification task can be automated using stan- dard machine learning techniques, the categorization of defects for model training requires expert knowledge, which is not always available. To cir- cumvent this dependency, we propose to apply the learning from crowds paradigm, where training categories are obtained from multiple non-expert annotators (and so may be incomplete, noisy or erroneous) and, dealing with this subjective class information, classifiers are efficiently learnt. To illustrate our proposal, we present two real applications of the IBM’s or- thogonal defect classification working on the issue tracking systems from two different real domains. Bayesian network classifiers learnt using two state-of-the-art methodologies from data labeled by a crowd of annotators are used to predict the category (impact) of reported software defects. The considered methodologies show enhanced performance regarding the straightforward solution (majority voting) according to different metrics. This shows the possibilities of using non-expert knowledge aggregation techniques when expert knowledge is unavailable

El empleo de la cascarilla de algodón en la alimentación de ganado bovino de cebo

Los autores realizan una experiencia de cebo sobre e1nco lotes de bovinos de raza frisona y retinta, con un total de 137 animlles, empleando como alimentos cascarilla de algodón, y cascarilla de algodón más un 30 por 100 de mazorca integral de maiz. Se obtienen incrementos diarios de 1,09 Kg con un consumo energético de 21,7 Mcal/cabeza y día. Los resultados satisfactorios obtenidos, deben atribuirse, fundamentalmente, al alto valor nutritivo de la cascarilla empleada

Petrology, geochemistry and origin of the Sierra de Baza ophiolites (Betic Cordillera, Spain)

In this work we present for the first time a petrological-geochemical and genetic study of the Sierra de Baza ophiolites, which represent one of the ophiolitic occurrences of the Betic Cordillera (Southern Spain). They are composed of ultramafic, mafic and sedimentary rocks, largely affected both by ocean floor and polyphasic metamorphism during the Alpine orogeny. Ultramafic rocks are serpentinized lherzolites and harzburgites, whereas the metabasites are meta-gabbros and meta-basalts. On the whole, Sierra de Baza ophiolites show striking geochemical similarities with those from other Betic occurrences, as well as with other Tethyan ophiolites of the Western Mediterranean (Calabria, Internal and External Ligurides, Platta, Corsica and Western Alps). In particular, metabasites show petrological and geochemical features similar to the E-MORB magmatism of the Atlantic Ridge between 45 and 63ºN generated under ultra-slow spreading ridge conditions. This process originated a strip of few hundreds km of ocean floor at the western end of the Tethys, located SE of the Iberian-European margin during the Mesozoic. The inversion of the stress regime in the European-Iberian and African geodynamics, starting from the Late-Middle Cretaceous, caused subduction and metamorphism in the eclogite facies of oceanic slices that were partially exhumed on the continental margin, forming the Betic Ophiolites. These ophiolites were disarticulated and dismembered as a result of the shift towards SW of the Alboran continental block, progressively separated from the AlKaPeCa (Alboran, Kabilias, Peloritani, Calabria) microplate, finally occupying their current position in the Betic Internal Zones

A KK-monopole giant graviton in AdS_5 x Y_5

We construct a new giant graviton solution in AdS_5 x Y_5, with Y_5 a quasi-regular Sasaki-Einstein manifold, consisting on a Kaluza-Klein monopole wrapped around the Y_5 and with its Taub-NUT direction in AdS_5. We find that this configuration has minimal energy when put in the centre of AdS_5, where it behaves as a massless particle. When we take Y_5 to be S^5, we provide a microscopical description in terms of multiple gravitational waves expanding into the fuzzy S^5 defined as an S^1 bundle over the fuzzy CP^2. Finally we provide a possible field theory dual interpretation of the construction.Comment: 11 pages, published versio

Association Between the Use of a Mobile Health Strategy App and Biological Changes in Breast Cancer Survivors: Prospective Pre-Post Study

The objectives of this study were to: (1) check whether it is feasible to find changes in inflammation biomarkers through an mHealth strategy app as a delivery mechanism of an intervention to monitor energy balance; and (2) discover potential predictors of change of these markers in breast cancer survivors (BCSs). Analyzing changes in inflammatory biomarker concentrations after using the mHealth app, differences between preassessment CRP (4899.04 pg/ml; SD 1085.25) and IL-6 (87.15 pg/ml; SD 33.59) and postassessment CRP (4221.24 pg/ml; SD 911.55) and IL-6 (60.53 pg/ml; SD 36.31) showed a significant decrease in both markers, with a mean difference of –635.25 pg/ml (95% CI –935.65 to –334.85; P<.001) in CRP and –26.61 pg/ml (95% CI –42.51 to –10.71; P=.002) in IL-6. Stepwise regression analyses revealed that changes in global quality of life, as well as uMARS score and hormonal therapy, were possible predictors of change in CRP concentration after using the mHealth app. In the same way, the type of tumor removal surgery conducted, as well as changes in weight and pain score, were possible predictors of change in IL-6 concentration after using the app. In conclusion, through the results of this study, we hypothesize that there is a possible association between an mHealth energy balance monitoring strategy and biological changes in BCSs. These changes could be explained by different biopsychosocial parameters, such as the use of the application itself, quality of life, pain, type of tumor removal surgery, hormonal treatment or obesity.The study was funded by the Spanish Ministry of Economy and Competitiveness (Plan Estatal de I+D+I 2013-2016), Fondo de Investigación Sanitaria del Instituto de Salud Carlos III (PI14/01627), Fondos Estructurales de la Unión Europea (FEDER), and by the Spanish Ministry of Education (FPU14/01069 and FPU17/00939)

Non-Invasive Forehead Segmentation in Thermographic Imaging

The temperature of the forehead is known to be highly correlated with the internal body temperature. This area is widely used in thermal comfort systems, lie-detection systems, etc. However, there is a lack of tools to achieve the segmentation of the forehead using thermographic images and non-intrusive methods. In fact, this is usually segmented manually. This work proposes a simple and novel method to segment the forehead region and to extract the average temperature from this area solving this lack of non-user interaction tools. Our method is invariant to the position of the face, and other different morphologies even with the presence of external objects. The results provide an accuracy of 90% compared to the manual segmentation using the coefficient of Jaccard as a metric of similitude. Moreover, due to the simplicity of the proposed method, it can work with real-time constraints at 83 frames per second in embedded systems with low computational resources. Finally, a new dataset of thermal face images is presented, which includes some features which are difficult to find in other sets, such as glasses, beards, moustaches, breathing masks, and different neck rotations and flexions

Type II pp-wave Matrix Models from Point-like Gravitons

The BMN Matrix model can be regarded as a theory of coincident M-theory gravitons, which expand by Myers dielectric effect into the 2-sphere and 5-sphere giant graviton vacua of the theory. In this note we show that, in the same fashion, Matrix String theory in Type IIA pp-wave backgrounds arises from the action for coincident Type IIA gravitons. In Type IIB, we show that the action for coincident gravitons in the maximally supersymmetric pp-wave background gives rise to a Matrix model which supports fuzzy 3-sphere giant graviton vacua with the right behavior in the classical limit. We discuss the relation between our Matrix model and the Tiny Graviton Matrix theory of hep-th/0406214.Comment: 18 page