1,871 research outputs found

    Milky way satellite census. II. Galaxy-halo connection constraints including the impact of the large magellanic cloud

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    Artículo escrito por un elevado número de autores, sólo se referencian el que aparece en primer lugar, los autores pertencientes a la UAM y el nombre del grupo de colaboración, si lo hubiereThe population of Milky Way (MW) satellites contains the faintest known galaxies and thus provides essential insight into galaxy formation and dark matter microphysics. Here we combine a model of the galaxy-halo connection with newly derived observational selection functions based on searches for satellites in photometric surveys over nearly the entire high Galactic latitude sky. In particular, we use cosmological zoom-in simulations of MW-like halos that include realistic Large Magellanic Cloud (LMC) analogs to fit the position-dependent MW satellite luminosity function. We report decisive evidence for the statistical impact of the LMC on the MW satellite population due to an estimated 6 ± 2 observed LMC-associated satellites, consistent with the number of LMC satellites inferred from Gaia proper-motion measurements, confirming the predictions of cold dark matter models for the existence of satellites within satellite halos. Moreover, we infer that the LMC fell into the MW within the last 2 Gyr at high confidence. Based on our detailed full-sky modeling, we find that the faintest observed satellites inhabit halos with peak virial masses below 3.2× 108 M· at 95% confidence, and we place the first robust constraints on the fraction of halos that host galaxies in this regime. We predict that the faintest detectable satellites occupy halos with peak virial masses above 106 M·, highlighting the potential for powerful galaxy formation and dark matter constraints from future dwarf galaxy searchesThe DES data management system is supported by the National Science Foundation under grant Nos. AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. The IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013), including ERC grant agreements 240672, 291329, and 30647

    A Robot Model of OC-Spectrum Disorders : Design Framework, Implementation and First Experiments

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    © 2019 Massachusetts Institute of TechnologyComputational psychiatry is increasingly establishing itself as valuable discipline for understanding human mental disorders. However, robot models and their potential for investigating embodied and contextual aspects of mental health have been, to date, largely unexplored. In this paper, we present an initial robot model of obsessive-compulsive (OC) spectrum disorders based on an embodied motivation-based control architecture for decision making in autonomous robots. The OC family of conditions is chiefly characterized by obsessions (recurrent, invasive thoughts) and/or compulsions (an urge to carry out certain repetitive or ritualized behaviors). The design of our robot model follows and illustrates a general design framework that we have proposed to ground research in robot models of mental disorders, and to link it with existing methodologies in psychiatry, and notably in the design of animal models. To test and validate our model, we present and discuss initial experiments, results and quantitative and qualitative analysis regarding the compulsive and obsessive elements of OC-spectrum disorders. While this initial stage of development only models basic elements of such disorders, our results already shed light on aspects of the underlying theoretical model that are not obvious simply from consideration of the model.Peer reviewe

    Hedonic Quality or Reward? A Study of Basic Pleasure in Homeostasis and Decision Making of a Motivated Autonomous Robot

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    © The Author (s) 2016. Published by SAGE. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).We present a robot architecture and experiments to investigate some of the roles that pleasure plays in the decision making (action selection) process of an autonomous robot that must survive in its environment. We have conducted three sets of experiments to assess the effect of different types of pleasure---related versus unrelated to the satisfaction of physiological needs---under different environmental circumstances. Our results indicate that pleasure, including pleasure unrelated to need satisfaction, has value for homeostatic management in terms of improved viability and increased flexibility in adaptive behavior.Peer reviewedFinal Published versio

    Influence of Prenatal Lead Exposure on Genomic Methylation of Cord Blood DNA

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    Background Fetal lead exposure is associated with adverse pregnancy outcomes and developmental and cognitive deficits; however, the mechanism(s) by which lead-induced toxicity occurs remains unknown. Epigenetic fetal programming via DNA methylation may provide a pathway by which environmental lead exposure can influence disease susceptibility. Objective This study was designed to determine whether prenatal lead exposure is associated with alterations in genomic methylation of leukocyte DNA levels from umbilical cord samples. Methods We measured genomic DNA methylation, as assessed by Alu and LINE-1 (long interspersed nuclear element-1) methylation via pyrosequencing, on 103 umbilical cord blood samples from the biorepository of the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study group. Prenatal lead exposure had been assessed by measuring maternal bone lead levels at the mid-tibial shaft and the patella using a spot-source 109Cd K-shell X-ray fluorescence instrument. Results We found an inverse dose–response relationship in which quartiles of patella lead correlated with cord LINE-1 methylation (p for trend = 0.01) and and tibia lead correlated with Alu methylation (p for trend = 0.05). In mixed effects regression models, maternal tibia lead was negatively associated with umbilical cord genomic DNA methylation of Alu (β= −0.027; p = 0.01). We found no associations between cord blood lead and cord genomic DNA methylation. Conclusions Prenatal lead exposure is inversely associated with genomic DNA methylation in cord blood. These data suggest that the epigenome of the developing fetus can be influenced by maternal cumulative lead burden, which may influence long-term epigenetic programming and disease susceptibility throughout the life course

    Transfer learning for galaxy morphology from one survey to another

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    © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of \sim5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy (\sim 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies (\sim500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

    The morphofunctional approach to emotion modelling in robotics

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    In this conceptual paper, we discuss two areas of research in robotics, robotic models of emotion and morphofunctional machines, and we explore the scope for potential cross-fertilization between them. We shift the focus in robot models of emotion from information-theoretic aspects of appraisal to the interactive significance of bodily dispositions. Typical emotional phenomena such as arousal and action readiness can be interpreted as morphofunctional processes, and their functionality may be replicated in robotic systems with morphologies that can be modulated for real-time adaptation. We investigate the control requirements for such systems, and present a possible bio-inspired architecture, based on the division of control between neural and endocrine systems in humans and animals. We suggest that emotional epi- sodes can be understood as emergent from the coordination of action control and action-readiness, respectively. This stress on morphology complements existing research on the information-theoretic aspects of emotion

    All-particle cosmic ray energy spectrum measured by the HAWC experiment from 10 to 500 TeV

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    We report on the measurement of the all-particle cosmic ray energy spectrum with the High Altitude Water Cherenkov (HAWC) Observatory in the energy range 10 to 500 TeV. HAWC is a ground based air-shower array deployed on the slopes of Volcan Sierra Negra in the state of Puebla, Mexico, and is sensitive to gamma rays and cosmic rays at TeV energies. The data used in this work were taken from 234 days between June 2016 to February 2017. The primary cosmic-ray energy is determined with a maximum likelihood approach using the particle density as a function of distance to the shower core. Introducing quality cuts to isolate events with shower cores landing on the array, the reconstructed energy distribution is unfolded iteratively. The measured all-particle spectrum is consistent with a broken power law with an index of 2.49±0.01-2.49\pm0.01 prior to a break at (45.7±0.1(45.7\pm0.1) TeV, followed by an index of 2.71±0.01-2.71\pm0.01. The spectrum also respresents a single measurement that spans the energy range between direct detection and ground based experiments. As a verification of the detector response, the energy scale and angular resolution are validated by observation of the cosmic ray Moon shadow's dependence on energy.Comment: 16 pages, 11 figures, 4 tables, submission to Physical Review

    Constraining the pˉ/p\bar{p}/p Ratio in TeV Cosmic Rays with Observations of the Moon Shadow by HAWC

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    An indirect measurement of the antiproton flux in cosmic rays is possible as the particles undergo deflection by the geomagnetic field. This effect can be measured by studying the deficit in the flux, or shadow, created by the Moon as it absorbs cosmic rays that are headed towards the Earth. The shadow is displaced from the actual position of the Moon due to geomagnetic deflection, which is a function of the energy and charge of the cosmic rays. The displacement provides a natural tool for momentum/charge discrimination that can be used to study the composition of cosmic rays. Using 33 months of data comprising more than 80 billion cosmic rays measured by the High Altitude Water Cherenkov (HAWC) observatory, we have analyzed the Moon shadow to search for TeV antiprotons in cosmic rays. We present our first upper limits on the pˉ/p\bar{p}/p fraction, which in the absence of any direct measurements, provide the tightest available constraints of 1%\sim1\% on the antiproton fraction for energies between 1 and 10 TeV.Comment: 10 pages, 5 figures. Accepted by Physical Review
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