93 research outputs found

    La conveniencia de regular la responsabilidad solidaria de los titulares de plataformas digitales en las relaciones de consumo

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    El presente trabajo de investigación se sumerge en la problemática de la responsabilidad administrativa que asumen los denominados marketplaces con respecto a las diversas relaciones de consumo electrónicas que albergan en sus infraestructuras digitales, al cumplir un determinado rol en dicha relación subyacente. Con ese objetivo, analizamos diversos conceptos multidisciplinarios como el de sociedad de la información, el comercio electrónico, la economía digital, la economía colaborativa y las plataformas digitales de intermediación. Específicamente, nos enfocamos en la definición y naturaleza jurídica de los marketplaces como un tipo de plataforma de intermediación bastante popular actualmente en el mercado, para posteriormente realizar un estudio concreto de las principales plataformas de este tipo que operan frente a consumidores nacionales y los términos contractuales que rigen sus relaciones comerciales. Producto de este análisis logramos uniformizar los usos y costumbres de estas plataformas, derivados de su autonomía privada, en base de los cuales podemos determinar el rol que cumplen estos agentes dentro de las relaciones comerciales electrónicas subyacentes. La naturaleza de la participación de estos agentes nos ayuda a determinar el nivel de responsabilidad que deben asumir respecto a los incumplimientos contractuales y normativos que perjudiquen a los consumidores. Para ello, nos apoyamos en la doctrina, jurisprudencia y legislación nacional e internacional que ya ha desarrollado respecto de la responsabilidad de los agentes intermediarios en las relaciones electrónicas. Finalmente, producto del desarrollo de la investigación, se propone una modificación normativa al Código de Protección y Defensa del Consumidor, como hipótesis ante nuestro problema de investigación, con el objetivo de incluir a la figura de los operadores de marketplaces y de esta forma contribuir con el aumento de la confianza en el comercio electrónico

    Fast identification of transits from light-curves

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    We present an algorithm that allows fast and efficient detection of transits, including planetary transits, from light-curves. The method is based on building an ensemble of fiducial models and compressing the data using the MOPED algorithm. We describe the method and demonstrate its efficiency by finding planet-like transits in simulated Pan-STARRS light-curves. We show that that our method is independent of the size of the search space of transit parameters. In large sets of light-curves, we achieve speed up factors of order of 10810^{8} times over the full χ2\chi2 search. We discuss how the algorithm can be used in forthcoming large surveys like Pan-STARRS and LSST and how it may be optimized for future space missions like Kepler and COROT where most of the processing must be done on board.Comment: 9 pages, 9 figure

    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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    Reconstruction of Events Recorded with the Water-Cherenkov and Scintillator Surface Detectors of the Pierre Auger Observatory

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    Status and performance of the underground muon detector of the Pierre Auger Observatory

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    Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

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    We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration

    A search for ultra-high-energy photons at the Pierre Auger Observatory exploiting air-shower universality

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    The Pierre Auger Observatory is the most sensitive detector to primary photons with energies above ∼0.2 EeV. It measures extensive air showers using a hybrid technique that combines a fluorescence detector (FD) with a ground array of particle detectors (SD). The signatures of a photon-induced air shower are a larger atmospheric depth at the shower maximum (Xmax_{max}) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced background. Using observables measured by the FD and SD, three photon searches in different energy bands are performed. In particular, between threshold energies of 1-10 EeV, a new analysis technique has been developed by combining the FD-based measurement of Xmax_{max} with the SD signal through a parameter related to its muon content, derived from the universality of the air showers. This technique has led to a better photon/hadron separation and, consequently, to a higher search sensitivity, resulting in a tighter upper limit than before. The outcome of this new analysis is presented here, along with previous results in the energy ranges below 1 EeV and above 10 EeV. From the data collected by the Pierre Auger Observatory in about 15 years of operation, the most stringent constraints on the fraction of photons in the cosmic flux are set over almost three decades in energy

    Study on multi-ELVES in the Pierre Auger Observatory

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    Since 2013, the four sites of the Fluorescence Detector (FD) of the Pierre Auger Observatory record ELVES with a dedicated trigger. These UV light emissions are correlated to distant lightning strikes. The length of recorded traces has been increased from 100 μs (2013), to 300 μs (2014-16), to 900 μs (2017-present), to progressively extend the observation of the light emission towards the vertical of the causative lightning and beyond. A large fraction of the observed events shows double ELVES within the time window, and, in some cases, even more complex structures are observed. The nature of the multi-ELVES is not completely understood but may be related to the different types of lightning in which they are originated. For example, it is known that Narrow Bipolar Events can produce double ELVES, and Energetic In-cloud Pulses, occurring between the main negative and upper positive charge layer of clouds, can induce double and even quadruple ELVES in the ionosphere. This report shows the seasonal and daily dependence of the time gap, amplitude ratio, and correlation between the pulse widths of the peaks in a sample of 1000+ multi-ELVES events recorded during the period 2014-20. The events have been compared with data from other satellite and ground-based sensing devices to study the correlation of their properties with lightning observables such as altitude and polarity

    Studies of the mass composition of cosmic rays and proton-proton interaction cross-sections at ultra-high energies with the Pierre Auger Observatory

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    In this work, we present an estimate of the cosmic-ray mass composition from the distributions of the depth of the shower maximum (Xmax) measured by the fluorescence detector of the Pierre Auger Observatory. We discuss the sensitivity of the mass composition measurements to the uncertainties in the properties of the hadronic interactions, particularly in the predictions of the particle interaction cross-sections. For this purpose, we adjust the fractions of cosmic-ray mass groups to fit the data with Xmax distributions from air shower simulations. We modify the proton-proton cross-sections at ultra-high energies, and the corresponding air shower simulations with rescaled nucleus-air cross-sections are obtained via Glauber theory. We compare the energy-dependent composition of ultra-high-energy cosmic rays obtained for the different extrapolations of the proton-proton cross-sections from low-energy accelerator data
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