1,335 research outputs found

    Relación entre test físicos específicos y rendimiento en gimnastas de elite

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    ResumenSe analizó la relación entre test físicos y rendimiento en Barras Paralelas (BP), Barra Fija (BF) y Caballo con Arcos (CA) en diez gimnastas varones de alto nivel. Se estimó la potencia media relativa al trepar 5m una cuerda (T5), la fuerza relativa al realizar máximas repeticiones de olímpicos desde escuadra (MRO), la flexibilidad activa (A) y pasiva (P) de flexión cadera (2A y 2P), y su abducción desde flexión a 90º (3A y 3P) y el rendimiento competitivo mediante el promedio de las notas finales (NF) en dos competiciones consecutivas. Existen relaciones significativas entre MRO con BP (r = 0,825; pAbstractWe analyzed the relationship between physical-test with the performance in Parallel Bar (BP), High Bar (BF) and Pommel Horse (CA) in ten elite gymnasts. The average power expressed on rope climbing 5m (T5) and the relative strength when performing maximum repetitions of L-support pike press to handstand (MRO) was estimated, the active (A) and passive (P) hip flexibility (2A and 2P), and his abduction from 90º hip-flexion (3A and 3P) and the competitive performance by averaging Final Score (NF) in two consecutive competitions. Significant relationships show between MRO with BP (r = 0.825; p doi:10.5232/ricyde2011.0220

    Criticality analysis for improving maintenance, felling and pruning cycles in power lines

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    16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 Bergamo, Italy, 11–13 June 2018. Edited by Marco Macchi, László Monostori, Roberto PintoThis paper deals with the process of criticality analysis in overhead power lines, as a tool to improve maintenance, felling & pruning programs. Felling & pruning activities are tasks that utility companies must accomplish to respect the servitudes of the overhead lines, concerned with distances to vegetation, buildings, infrastructures and other networks crossings. Conceptually, these power lines servitudes can be considered as failure modes of the maintainable items under our analysis (power line spans), and the criticality analysis methodology developed, will therefore help to optimize actions to avoid these as other failure modes of the line maintainable items. The approach is interesting, but another relevant contribution of the paper is the process followed for the automation of the analysis. Automation is possible by utilizing existing companies IT systems and databases. The paper explains how to use data located in Enterprise Assets Management Systems, GIS and Dispatching systems for a fast, reliable, objective and dynamic criticality analysis. Promising results are included and also discussions about how this technique may result in important implications for this type of businesse

    Strategic view of an assets health index for making long-term decisions in different industries

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    Libro en Open AccessAn Asset Health Index (AHI) is a tool that processes data about asset’s condition. That index is intended to explore if alterations can be generated in the health of the asset along its life cycle. These data can be obtained during the asset’s operation, but they can also come from other information sources such as geographical information systems, supplier’s reliability records, relevant external agent’s records, etc. The tool (AHI) provides an objective point of view in order to justify, for instance, the extension of an asset useful life, or in order to identify which assets from a fleet are candidates for an early replacement as a consequence of a premature aging. This paper develops a model applicable to different classes of equipment and industrial sectors. A review of the main cases where the asset health index has been applied is included. Likewise, advantages and disadvantages in the application of this kind of tools are revealed, providing a guide for a research line related to the general application of this tool

    Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off

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    Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful machine learning techniques are essential to deal with the large amount of information and overcome the curse of dimensionality. Artificial Neural Networks (ANNs) have achieved promising performance in EEG-based Brain-Computer Interface (BCI) applications, but they involve computationally intensive training algorithms and hyperparameter optimization methods. Thus, an awareness of the quality-cost trade-off, although usually overlooked, is highly beneficial. In this paper, we apply a hyperparameter optimization procedure based on Genetic Algorithms to Convolutional Neural Networks (CNNs), Feed-Forward Neural Networks (FFNNs), and Recurrent Neural Networks (RNNs), all of them purposely shallow. We compare their relative quality and energy-time cost, but we also analyze the variability in the structural complexity of networks of the same type with similar accuracies. The experimental results show that the optimization procedure improves accuracy in all models, and that CNN models with only one hidden convolutional layer can equal or slightly outperform a 6-layer Deep Belief Network. FFNN and RNN were not able to reach the same quality, although the cost was significantly lower. The results also highlight the fact that size within the same type of network is not necessarily correlated with accuracy, as smaller models can and do match, or even surpass, bigger ones in performance. In this regard, overfitting is likely a contributing factor since deep learning approaches struggle with limited training examples.Spanish Ministerio de Ciencia, Innovacion y Universidades PGC2018-098813-B-C31 PGC2018-098813-B-C32 PSI201565848-

    Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off

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    Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful machine learning techniques are essential to deal with the large amount of information and overcome the curse of dimensionality. Artificial Neural Networks (ANNs) have achieved promising performance in EEG-based Brain-Computer Interface (BCI) applications, but they involve computationally intensive training algorithms and hyperparameter optimization methods. Thus, an awareness of the quality-cost trade-off, although usually overlooked, is highly beneficial. In this paper, we apply a hyperparameter optimization procedure based on Genetic Algorithms to Convolutional Neural Networks (CNNs), Feed-Forward Neural Networks (FFNNs), and Recurrent Neural Networks (RNNs), all of them purposely shallow. We compare their relative quality and energy-time cost, but we also analyze the variability in the structural complexity of networks of the same type with similar accuracies. The experimental results show that the optimization procedure improves accuracy in all models, and that CNN models with only one hidden convolutional layer can equal or slightly outperform a 6-layer Deep Belief Network. FFNN and RNN were not able to reach the same quality, although the cost was significantly lower. The results also highlight the fact that size within the same type of network is not necessarily correlated with accuracy, as smaller models can and do match, or even surpass, bigger ones in performance. In this regard, overfitting is likely a contributing factor since deep learning approaches struggle with limited training examples

    Matrix metalloproteases and TIMPs as prognostic biomarkers in breast cancer patients treated with radiotherapy: A pilot study

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    Breast cancer (BC) is the most common tumour in women and one of the most important causes of cancer death worldwide. Radiation therapy (RT) is widely used for BC treatment. Some proteins have been identified as prognostic factors for BC (Ki67, p53, E‐cadherin, HER2). In the last years, it has been shown that variations in the expression of MMPs and TIMPs may contribute to the development of BC. The aim of this pilot work was to study the effects of RT on different MMPs (‐1, ‐2, ‐3, ‐7, ‐8, ‐9, ‐10, ‐12 and ‐13) and TIMPs (‐1 to ‐4), as well as their relationship with other variables related to patient characteristics and tumour biology. A group of 20 BC patients treated with RT were recruited. MMP and TIMP serum levels were analysed by immunoassay before, during and after RT. Our pilot study showed a slight increase in the levels of most MMP and TIMP with RT. However, RT produced a significantly decrease in TIMP‐1 and TIMP‐3 levels. Significant correlations were found between MMP‐3 and TIMP‐4 levels, and some of the variables studied related to patient characteristics and tumour biology. Moreover, MMP‐9 and TIMP‐3 levels could be predictive of RT toxicity. For this reason, MMP‐3, MMP‐9, TIMP‐3 and TIMP‐4 could be used as potential prognostic and predictive biomarkers for BC patients treated with RT.FUNDACIÓN PROGRESO Y SALUD, Grant/Award Number: PI‐730; Instituto de Salud Carlos III, Grant/Award Number: PIE16‐00045; Oncología Básica y Clínica, Grant/Award Number: CTS‐20

    Aerosol characterisation in the subtropical eastern North Atlantic region using long-term AERONET measurements

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    A comprehensive characterisation of atmospheric aerosols in the subtropical eastern North Atlantic has been carried out using long-term ground-based Aerosol Robotic NETwork (AERONET) photometric observations over the period 2005–2020 from a unique network made up of four stations strategically located from sea level to 3555 m on the island of Tenerife. This site can be considered a sentinel for the passage of airmasses going to Europe from Africa, and therefore the aerosol characterisation performed here adds important information for analysing their evolution during their path toward Northern Europe. Two of these stations (Santa Cruz de Tenerife – SCO – at sea level and La Laguna – LLO – at 580 m a.s.l.) are located within the marine atmospheric boundary layer (MABL), and the other two (Izaña – IZO – at 2373 m a.s.l. and Teide Peak – TPO – at 3555 m a.s.l.) are high mountain stations within the free troposphere (FT). Monthly climatology of the aerosol optical depth (AOD), Ångström exponent (AE), aerosol concentration, size distribution and aerosol optical properties has been obtained for the MABL and FT. Measurements that are quite consistent across the four sites have been used to categorise the main atmospheric scenarios, and these measurements confirm an alternation between predominant background conditions and predominant dust-loaded Saharan air mass conditions caused by seasonal dust transport over the subtropical North Atlantic. Background conditions prevail in the MABL and FT for most of the year, while dust-laden conditions dominate in July and August.The authors also acknowledge the support from ACTRIS, Ministerio de Ciencia e Innovación, Spain, through the projects SYNERA (PID2020-118793GA-I00) and ePOLAAR (RTI2018-097864-BI00) and from Junta de Castilla y León (grant no. VA227P20)

    Cinco años de experiencia en la utilización de la técnica del cono extendido

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    Fundamento: la utilización de mallas en la cirugía herniaria alcanzó su mayor popularidad a partir de los años 80. En el año 2007, en la Clínica Multiperfil de Luanda, Angola, se diseñó una nueva variante de colocación de la malla que cumple con todos los principios de la cirugía herniaria, basada en la oclusión del anillo herniario y el refuerzo de la pared del canal. En el año 2009 se introduce la técnica en el Hospital Enrique Cabrera en La Habana. Objetivo: mostrar los resultados de la aplicación de la técnica del cono extendido en el tratamiento de la hernia inguinal en el Hospital Docente Enrique Cabrera. Métodos: se realizó un estudio de serie de casos en 100 pacientes, en los cuales se operaron 110 hernias mediante una técnica protésica denominada cono extendido, durante los años 2009 al 2013 en el Hospital Enrique Cabrera de La Habana. Se utilizó la clasificación de Gilbert modificada por Rutkow y Robbin. Se analizó: edad, sexo, localización de la hernia, grado de la hernia según la clasificación de Gilbert, complicaciones e índice de recidivas. Resultados: hubo un predominó el sexo masculino. La localización más frecuente fue la región inguinal izquierda. Predominaron las hernias clasificadas como grado III según la clasificación de Gilbert. Hubo 15 complicaciones menores y hasta el momento no han ocurrido recidivas. Conclusiones: la técnica del cono extendido es una técnica segura y otra opción para el tratamiento de pacientes que presenten hernias inguinales del grado III, IV y VI de la clasificación de Gilbert modificada por Rutkow y Robbins

    Introducción al ecoturismo comunitario

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    Este libro presenta un análisis de los proyectos de turismo, y de la necesidad de reforzar todo aquello que los vuelva compatibles con la conservación, protección y restauración del entorno. Inicia con definiciones y conceptos que permitan la comprensión del ecoturismo; también se analizan los impactos económicos, sociales y ambientales del turismo convencional; para finalizar el apartado se cita al desarrollo sustentable como el modelo socioeconómico y ambiental que permitirá establecer un turismo menos lesivo al medio ambiente. Medio ambiente y cultura local han sido los componentes más sacrificados en el desarrollo de proyectos turísticos. Por eso se busca generar en los lectores una reflexión sobre aspectos que suelen considerarse complementarios, de poca relevancia o de difícil comprensión. Se hace la invitación a revisar cada capítulo, indagar en otros medios (libros, videos, internet, documentos, etc.) y buscar respuestas a las inquietudes que este texto les pueda dejar. Por último, se pretende despertar el interés de viajar y experimentar propuestas ecoturísticas que las comunidades rurales ofrecen a lo largo del país
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