Con2^{2}DA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations

In this work, we present Con$^{2}$DA, a simple framework that extends recent advances in semi-supervised learning to the semi-supervised domain adaptation (SSDA) problem. Our framework generates pairs of associated samples by performing stochastic data transformations to a given input. Associated data pairs are mapped to a feature representation space using a feature extractor. We use different loss functions to enforce consistency between the feature representations of associated data pairs of samples. We show that these learned representations are useful to deal with differences in data distributions in the domain adaptation problem. We performed experiments to study the main components of our model and we show that (i) learning of the consistent and contrastive feature representations is crucial to extract good discriminative features across different domains, and ii) our model benefits from the use of strong augmentation policies. With these findings, our method achieves state-of-the-art performances in three benchmark datasets for SSDA.Comment: 11 pages, 3 figures, 4 table

Reduction of Leaching Impacts by Applying Biomass Bottom Ash and Recycled Mixed Aggregates in Structural Layers of Roads

This research is focused on analyzing the environmental pollution potential of biomass bottom ashes as individual materials, as mixtures manufactured with biomass bottom ashes and granular construction aggregates, and these mixtures treated with cement. For the environmental assessment of all of the samples and materials mentioned, the following leaching procedures have been performed: the compliance batch test of UNE-EN 12457-3:2003 for aggregates and bottom ashes; the column test according to NEN 7343:1994 for the mixtures prepared in the laboratory; and the tank test by EA NEN 7375:2004 for analyzing the behavior of mixtures after their solidification/stabilization with 5% cement. After the discussion of the data, the reduction of the pollution load of the most hazardous biomass bottom ashes after their combination with different aggregates can be confirmed, which implies their possible application in civil infrastructures, such as filler embankments and road construction layers, without negatively impacting the environment. In addition, the positive effect of the stabilization/solidification of the cement-treated mixtures with a reduction of the heavy metals that were released at the highest levels, namely As, Hg Cr, Ni, Cu, Se and Mo, was prove

Evolution of the Correlation between Orthogonal Polarization Patterns in Broad-Area Lasers

We measure polarization-resolved instantaneous patterns in a large-aspect ratio quasi-isotropic Nd:YAG laser. High correlation between the instantaneous orthogonal polarization patterns recorded at the earlier stages of the laser pulse has been found due to the strong cross saturation between both polarization modes

Miedo al delito y vulnerabilidad entre la población andaluza: datos del Estudio PACIS 2019

Focused on fear of crime, this article analyzes the data about fear of crime gathered by the 9th Citizen Panel for Social Research in Andalusia (PACIS), a surveyimplemented by the Advanced Social Research Institute (IESA) in 2019. These analyses contribute to the literature related to fear of crime in several manners: (1) by exploring the three dimensions of fear of crime in the Andalusian population, (2) by distinguishing between external and internal locus of projection of the fear, and (3) by explaining these dimensions in relation to sociodemographic —victimization, gender, age, educational level, and economic situation— identified as covariant variables by the Vulnerability Model of fear of crime. To this end, first, this article sets the theoretical basis of the concept of fear of crime. Second, it describes the methodology applied in this investigation. Then, it presents the results obtained in the statistical analyses of the data and, finally, both the results and the conclusions are discussed.En este artículo se analizan los datos sobre miedo al delito recogidos en 2019 por la 9ª ola del Panel Ciudadano para la Investigación Social en Andalucía (PACIS), del Instituto de Estudios Sociales Avanzados (IESA). Estos análisis buscan contribuir a la literatura especializada de varias maneras: (1) explorando las tres dimensiones del miedo al delito en la población andaluza, (2) distinguiendo entre los locus de proyección interno y externo de dicho miedo y (3) explicando dichas dimensiones en base a variables sociodemográficas —victimización, género, edad, nivel de estudios y situación económica— identificadas como covariantes por las teorías de la vulnerabilidad. Con este fin, primero, se asientan las bases teóricas del concepto de miedo al delito. En segundo lugar, se comenta la metodología seguida en la investigación. A continuación, se exponen los resultados obtenidos en el análisis estadístico descriptivo y bivariable y, por último, se comentan dichos resultados y se exponen las conclusiones obtenidas de dichos análisis

Brønsted acid−catalyzed synthesis of tetrasubstituted allenes and polysubstituted 2H-chromenes from tertiary propargylic alcohols

A practical and environmentally benign Brønsted acid−catalyzed protocol for the preparation of all-carbon tetrasubstituted allenes, consisting in the direct SNˈ addition of tri- or dimethoxy arenes or allyltrimethylsilane to tertiary propargylic alcohols, has been developed. In addition, a straightforward synthesis of densely substituted 2H-chromenes by metal-free tandem allenylation/heterocyclization reaction of methoxyphenols and tertiary alkynols is presented.Junta de Castilla y León and FEDER (BU291P18) and Ministerio de Economía y Competitividad (MINECO) and FEDER (CTQ2016-75023-C2-1-P

Desarrollo de materiales poliméricos porosos mediante electrohilado

Si el diámetro de las fibras que forman una matriz de polímero se reduce desde una escala micrométrica a nanométrica, se produce una serie de características extraordinarias. Entre estas características se encuentran un gran aumento en el área superficial (del orden de 1000 veces mayor), una mayor flexibilidad de la funcionalidad de la superficie y una mejor resistencia mecánica (por ejemplo, rigidez, resistencia a la tracción). Estas propiedades hacen que las matrices de polímeros nanofibrilares sean excelentes candidatos en muchas aplicaciones de gran importancia, que incluyen aplicaciones químicas, alimentarias, farmacéuticas, electrónicas o biomédicas. Hay varios parámetros que están íntimamente relacionados con las propiedades y características de las fibras obtenidas mediante electrospinning, por lo que su control durante la ejecución del proceso es indispensable. Juegan un papel importante en la formación y estructura de las fibras. En el siguiente trabajo, procedemos a estudiar tres variables del proceso de electrohilado; en primer lugar, se estudiará el efecto de la concentración del disolvente; en segundo lugar, se estudiará cómo las nanofibras obtenidas afectan a un cambio en el valor de la diferencia de potencial aplicada; y, finalmente, se estudiará el efecto producido por la humedad en el ambiente.If the diameter of the fibers that form a polymer matrix is reduced from a micrometric to nanometric scale, a series of extraordinary features take place. Among these features are a huge increase in surface area (in the order of 1000 times higher), a greater flexibility of the surface functionality and a better mechanical resistance (e.g. rigidity, tensile strength). These properties make nanofibrillary polymer matrices excellent candidates in many applications of great importance, including chemical, food, pharmaceutical, electronic or biomedical applications. There are several parameters that are intimately related to the properties and characteristics of the fibers obtained by means of electrospinning, so their control during the execution of the process is indispensable. They play an important role in the formation and structure of fibers. In the following work we proceed to study three variables of the electrospinning process; firstly, the effect of the concentration of the solvent will be studied; secondly, it will be studied how the nanofibers obtained affect a change in the value of the applied potential difference; and, finally, the effect produced by humidity in the environment will be studied.Plan Propio de la Universidad de Sevilla Proyecto: 2017/00000962Ministerio de Economía y Competitividad (España) CTQ2015-71164-

Modeling of an Overactuated Vehicle in Simscape Multibody for the Characterization of Suspension and Steering Actuation Systems.

Overactuated systems are increasingly among us. They are used for applications in vehicles, aeronautics and robotics, among others [1, 2]. These systems have a number of advantages, among which we can mention that there are multiple (or infinite) solutions for a given problem. More specifically, in the case of overactuated vehicles, similar states of the system can be achieved in many different ways. These systems are still under development, especially in the field of vehicle dynamics. For example, there are various steer-by-wire algorithms, when the steering of the vehicles is independent, or brake blending strategies. In this work, a part of an overactuated vehicle is designed and validated. This multiphysics model allows to know the plant of the system in much more depth in order to develop control algorithms. More specifically, by modeling the delay of the systems and the nonlinear relationships inherent to multibody systems, much more accurate predictive control can be performed. These results allow a previous validation of the control algorithms in the test platform vehicle being manufactured and developed by the research group, greatly accelerating the control process of each of the overactuated systems of the vehicle.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Domain Adaptation via Minimax Entropy for Real/Bogus Classification of Astronomical Alerts

Time domain astronomy is advancing towards the analysis of multiple massive datasets in real time, prompting the development of multi-stream machine learning models. In this work, we study Domain Adaptation (DA) for real/bogus classification of astronomical alerts using four different datasets: HiTS, DES, ATLAS, and ZTF. We study the domain shift between these datasets, and improve a naive deep learning classification model by using a fine tuning approach and semi-supervised deep DA via Minimax Entropy (MME). We compare the balanced accuracy of these models for different source-target scenarios. We find that both the fine tuning and MME models improve significantly the base model with as few as one labeled item per class coming from the target dataset, but that the MME does not compromise its performance on the source dataset