30 research outputs found

    La imagen y la narrativa como herramientas para el abordaje psicosocial en escenarios de violencia. Departamentos de Casanare, Cauca, Norte de Santander y Santander

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    Este trabajo tiene como objetivo analizar las situaciones de violencia y crisis que se exponen en las diferentes narrativas encontradas dentro de la actividad, las cuales nos permiten evidenciar la cruda violencia que día a día afecta a nuestro país y a nuestros compatriotas, estas situaciones nos ayudan a realizar un análisis profundo sobre los impactos psicosociales que enfrentan las víctimas de la violencia y como por medio de la ayuda familiar, amigos e instituciones de carácter social han podido sobresalir a estas situaciones de adversidad de las cuales fueron ellos afectados. Por medio del análisis de estos casos y dando respuesta a las preguntas orientadoras podemos notar que la violencia se manifiesta de diferentes formas y afectan todo un contexto social, a pesar de estas situaciones dichos relatos nos ayudan a realizar una reflexión como psicólogos en formación sobre cómo podemos intervenir ante estas situaciones con el fin de proteger a las víctimas y su entorno social. Lo anterior se puede lograr por medio de la construcción y realización de procesos de acompañamientos que impliquen estilos o métodos de afrontamiento de los traumas y crisis que surgen a raíz de estos actos violentos, de la inclusión social, todo esto por medio de acciones psicosociales que están encaminadas a generar una mayor autoestima, resiliencia y otros aspectos individuales que ayudan a sanar esas heridas en cada una de ellas, todo esto con el firme propósito de mejorar su calidad y bienestar de vida. 4 Este proyecto que se encuentra en el presente trabajo tiene como propósito la inclusión social de la comunidad de Peñas Coloradas, afectada por la violencia, la falta de apoyo estatal y social, donde se busca por medio de acciones psicosociales como: dinámicas de autoestima, terapias de relajación, espacios de liberación emocional, fomento de proyectos de vida, adquisición de compromisos para que las personas víctimas de la violencia tengan una verdadera inclusión en los aspectos familiar, laboral y social, logrando un impacto de recuperación emocional, generando espacios de confianza y respeto mutuo, impulsando la formación de grupos de autoayuda a las diferentes personas que han vivido la violencia.This work aims to analyze the situations of violence and crisis that are exposed in the different narratives found within the activity, which allow us to show the raw violence that affects our country and our compatriots every day, these situations help us to carry out an in-depth analysis of the psychosocial impacts faced by victims of violence and how, through the help of family, friends and social institutions, they have been able to overcome these adversity situations from which they were affected. Through the analysis of these cases and responding to the guiding questions, we can notice that violence manifests itself in different ways and affects an entire social context, despite these situations, these stories help us to reflect as psychologists in training on how We can intervene in these situations in order to protect the victims and their social environment. The foregoing can be achieved through the construction and implementation of accompaniment processes that involve styles or methods of coping with the traumas and crises that arise as a result of these violent acts, of social inclusion, all this through psychosocial actions that They are aimed at generating greater self-esteem, resilience and other individual aspects that help heal those wounds in each one of them, all with the firm purpose of improving their quality and well-being of life. The purpose of this project found in this work is the social inclusion of the community of Peñas Coloradas, affected by violence, the lack of state and social support, where it is sought through psychosocial actions such as: self-esteem dynamics, therapies of relaxation, spaces of emotional liberation, promotion of life projects, acquisition of commitments so that the victims of violence have a true inclusion in the family, work and social aspects, achieving an impact of emotional recovery, generating spaces of trust and mutual respect, promoting the formation of self-help groups for the different people who have experienced violence

    Rationale, design, and baseline characteristics in Evaluation of LIXisenatide in Acute Coronary Syndrome, a long-term cardiovascular end point trial of lixisenatide versus placebo

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    BACKGROUND: Cardiovascular (CV) disease is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Furthermore, patients with T2DM and acute coronary syndrome (ACS) have a particularly high risk of CV events. The glucagon-like peptide 1 receptor agonist, lixisenatide, improves glycemia, but its effects on CV events have not been thoroughly evaluated. METHODS: ELIXA (www.clinicaltrials.gov no. NCT01147250) is a randomized, double-blind, placebo-controlled, parallel-group, multicenter study of lixisenatide in patients with T2DM and a recent ACS event. The primary aim is to evaluate the effects of lixisenatide on CV morbidity and mortality in a population at high CV risk. The primary efficacy end point is a composite of time to CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina. Data are systematically collected for safety outcomes, including hypoglycemia, pancreatitis, and malignancy. RESULTS: Enrollment began in July 2010 and ended in August 2013; 6,068 patients from 49 countries were randomized. Of these, 69% are men and 75% are white; at baseline, the mean ± SD age was 60.3 ± 9.7 years, body mass index was 30.2 ± 5.7 kg/m(2), and duration of T2DM was 9.3 ± 8.2 years. The qualifying ACS was a myocardial infarction in 83% and unstable angina in 17%. The study will continue until the positive adjudication of the protocol-specified number of primary CV events. CONCLUSION: ELIXA will be the first trial to report the safety and efficacy of a glucagon-like peptide 1 receptor agonist in people with T2DM and high CV event risk

    DUNE Offline Computing Conceptual Design Report

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    International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

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    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

    Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

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    International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

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    The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10310^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    No full text
    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

    DUNE Offline Computing Conceptual Design Report

    No full text
    This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    No full text
    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation
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