49 research outputs found

    Mercadeo de Servicio Gestión de la relación con los clientes

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    La presente investigación de carácter bibliográfica, tiene como tema mercadeo de servicios y sub tema gestión de la relación con los clientes, esto como parte de los ejes de investigación del departamento de administración de empresas de la facultad de ciencias económicas de la UNAN Managua. Se tiene como objetivo general el analizar la gestión de relación con los clientes (CRM: Customer Relationship Management) a través de las diferentes teorías relacionadas a desarrollar una buena estrategia en las organizaciones. La base teórica que sustenta este informe se hace énfasis en cuatro capítulos tales como capítulo uno introducción a la gestión de la relación con los clientes, capitulo dos la captación y el modelo de relación, capítulo tres técnicas estratégica para la gestión de relación de los clientes, capítulo cuatro fundamentos para establecer una estrategia CRM Las técnicas utilizadas para el desarrollo de este informe fueron la lectura y recolección de documentación bibliográfica basado en el mercadeo de servicios, así mismo la tabulación del informe se hará aplicando las normas APAs 6 de Javeriano. Los resultados o presentación del informe está basado en la normativa de presentación de seminario de graduación plan 2013 de la UNAN Managua. Los principales términos descriptores del informe, son la introducción, justificación, objetivos del informe, introducción del tema y sub tema, conclusiones y bibliografía

    Natural History of MYH7-Related Dilated Cardiomyopathy

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    BACKGROUND Variants in myosin heavy chain 7 (MYH7) are responsible for disease in 1% to 5% of patients with dilated cardiomyopathy (DCM); however, the clinical characteristics and natural history of MYH7-related DCM are poorly described. OBJECTIVES We sought to determine the phenotype and prognosis of MYH7-related DCM. We also evaluated the influence of variant location on phenotypic expression. METHODS We studied clinical data from 147 individuals with DCM-causing MYH7 variants (47.6% female; 35.6 +/- 19.2 years) recruited from 29 international centers. RESULTS At initial evaluation, 106 (72.1%) patients had DCM (left ventricular ejection fraction: 34.5% +/- 11.7%). Median follow-up was 4.5 years (IQR: 1.7-8.0 years), and 23.7% of carriers who were initially phenotype-negative developed DCM. Phenotypic expression by 40 and 60 years was 46% and 88%, respectively, with 18 patients (16%) first diagnosed at <18 years of age. Thirty-six percent of patients with DCM met imaging criteria for LV noncompaction. During follow-up, 28% showed left ventricular reverse remodeling. Incidence of adverse cardiac events among patients with DCM at 5 years was 11.6%, with 5 (4.6%) deaths caused by end-stage heart failure (ESHF) and 5 patients (4.6%) requiring heart transplantation. The major ventricular arrhythmia rate was low (1.0% and 2.1% at 5 years in patients with DCM and in those with LVEF of <= 35%, respectively). ESHF and major ventricular arrhythmia were significantly lower compared with LMNA-related DCM and similar to DCM caused by TTN truncating variants. CONCLUSIONS MYH7-related DCM is characterized by early age of onset, high phenotypic expression, low left ventricular reverse remodeling, and frequent progression to ESHF. Heart failure complications predominate over ventricular arrhythmias, which are rare. (C) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation

    First results from the AugerPrime Radio Detector

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    Update of the Offline Framework for AugerPrime

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    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

    Outreach activities at the Pierre Auger Observatory

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    The ultra-high-energy cosmic-ray sky above 32 EeV viewed from 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

    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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