885 resultados para Nevanlinna, Ines


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Este es un estudio descriptivo, retrospectivo de reporte de serie de casos con Síndrome de Turner (ST), en el periodo comprendido Agosto 2003 a 2005 en un Hospital especializado de Nivel III de Bogotá Colombia. Se analizó las frecuencias de los cariotipos, fenotipos, de las malformaciones y ciertos procesos asociados, en una población de 31 pacientes con síndrome de Turner. Además, hemos estudiado la relación entre los cariotipos encontrados y los demás aspectos analizados.

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material didáctico sobre la descripción de las enfermedades producidas por hongos y su identificación mediante técnicas de laboratorio, dirigido a los alumnos de la cátedra de Microbiología Médica que cursan cuarto semestre de Medicina

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Las obras geográficas de Manuel Ancízar y Felipe Pérez dan cuenta de la manera en la que la élite intelectual neogranadina se apropió y representó el aspecto físico y humano de la nación al inicio y final de la Comisión Corográfica (1850-1859). Un análisis comparativo de las obras mostrará la manera en la que la narración literaria y la geográfica influyen en la elaboración de imaginarios territoriales para unificar la nación y consolidar la identidad nacional a partir de la apropiación territorial en la segunda mitad del siglo XIX

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Los diferentes sectores de la economía ejercen múltiples actividades que impulsan el crecimiento socio-económico de los diferentes países, sin embargo dichas actividades tienen repercusiones importantes a nivel ambiental, dentro de las que se encuentran transformaciones irreversibles del planeta, tanto físicas como químicas. Gracias a esto, en la actualidad, las empresas y organizaciones han empezado a controlar con mayor responsabilidad sus respectivos procesos y operaciones, buscando no solo mitigar los impactos negativos ocasionados al medio ambiente y a la sociedad sino la optimización en el uso de recursos tanto físicos como económicos. El presente estudio tiene como finalidad analizar las operaciones que se realizan en una obra civil, con el fin de identificar cuáles son las principales causantes de contaminación, por otro lado se hará mención de como la normatividad y legislación colombiana aplica y ejerce control en cada uno de los mismos, finalmente se plantearán diferentes soluciones y alternativas para que dicha industria pueda implementarlas en sus quehaceres diarios. Para lograr lo anterior se utilizaron diferentes herramientas que facilitaron la obtención de datos e información para el estudio tales como: entrevistas a los miembros y participantes de la obra civil, visitas de campo, recopilación de información de estudios similares, realización de la matriz de aspectos e impactos y fichas ambientales, entre otras. Los resultados obtenidos permitieron entender que es inevitable que esta industria no genere ciertas contaminaciones e impactos negativos, además de identificar que la normativa del país en cuanto control ambiental se encuentra algo atrasada, factor que fue determinante a la hora de proponer distintas alternativas que buscan tanto facilitar las prácticas que el sector de la construcción tiene en el país como minimizar al máximo los impactos ambientales negativos ocasionados.

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Título del congreso: 'El español, lengua del mestizaje y la interculturalidad'

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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We present a new composite of geomagnetic activity which is designed to be as homogeneous in its construction as possible. This is done by only combining data that, by virtue of the locations of the source observatories used, have similar responses to solar wind and IMF (interplanetary magnetic field) variations. This will enable us (in Part 2, Lockwood et al., 2013a) to use the new index to reconstruct the interplanetary magnetic field, B, back to 1846 with a full analysis of errors. Allowance is made for the effects of secular change in the geomagnetic field. The composite uses interdiurnal variation data from Helsinki for 1845–1890 (inclusive) and 1893–1896 and from Eskdalemuir from 1911 to the present. The gaps are filled using data from the Potsdam (1891–1892 and 1897–1907) and the nearby Seddin observatories (1908–1910) and intercalibration achieved using the Potsdam–Seddin sequence. The new index is termed IDV(1d) because it employs many of the principles of the IDV index derived by Svalgaard and Cliver (2010), inspired by the u index of Bartels (1932); however, we revert to using one-day (1d) means, as employed by Bartels, because the use of near-midnight values in IDV introduces contamination by the substorm current wedge auroral electrojet, giving noise and a dependence on solar wind speed that varies with latitude. The composite is compared with independent, early data from European-sector stations, Greenwich, St Petersburg, Parc St Maur, and Ekaterinburg, as well as the composite u index, compiled from 2–6 stations by Bartels, and the IDV index of Svalgaard and Cliver. Agreement is found to be extremely good in all cases, except two. Firstly, the Greenwich data are shown to have gradually degraded in quality until new instrumentation was installed in 1915. Secondly, we infer that the Bartels u index is increasingly unreliable before about 1886 and overestimates the solar cycle amplitude between 1872 and 1883 and this is amplified in the proxy data used before 1872. This is therefore also true of the IDV index which makes direct use of the u index values.

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We present a new reconstruction of the interplanetary magnetic field (IMF, B) for 1846–2012 with a full analysis of errors, based on the homogeneously constructed IDV(1d)composite of geomagnetic activity presented in Part 1 (Lockwood et al., 2013a). Analysis of the dependence of the commonly used geomagnetic indices on solar wind parameters is presented which helps explain why annual means of interdiurnal range data, such as the new composite, depend only on the IMF with only a very weak influence of the solar wind flow speed. The best results are obtained using a polynomial (rather than a linear) fit of the form B = χ · (IDV(1d) − β)α with best-fit coefficients χ = 3.469, β = 1.393 nT, and α = 0.420. The results are contrasted with the reconstruction of the IMF since 1835 by Svalgaard and Cliver (2010).

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The recent identification of multiple dominant mutations in the gene encoding β-catenin in both humans and mice has enabled exploration of the molecular and cellular basis of β-catenin function in cognitive impairment. In humans, β-catenin mutations that cause a spectrum of neurodevelopmental disorders have been identified. We identified de novo β-catenin mutations in patients with intellectual disability, carefully characterized their phenotypes, and were able to define a recognizable intellectual disability syndrome. In parallel, characterization of a chemically mutagenized mouse line that displays features similar to those of human patients with β-catenin mutations enabled us to investigate the consequences of β-catenin dysfunction through development and into adulthood. The mouse mutant, designated batface (Bfc), carries a Thr653Lys substitution in the C-terminal armadillo repeat of β-catenin and displayed a reduced affinity for membrane-associated cadherins. In association with this decreased cadherin interaction, we found that the mutation results in decreased intrahemispheric connections, with deficits in dendritic branching, long-term potentiation, and cognitive function. Our study provides in vivo evidence that dominant mutations in β-catenin underlie losses in its adhesion-related functions, which leads to severe consequences, including intellectual disability, childhood hypotonia, progressive spasticity of lower limbs, and abnormal craniofacial features in adults

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In the concluding paper of this tetralogy, we here use the different geomagnetic activity indices to reconstruct the near-Earth interplanetary magnetic field (IMF) and solar wind flow speed, as well as the open solar flux (OSF) from 1845 to the present day. The differences in how the various indices vary with near-Earth interplanetary parameters, which are here exploited to separate the effects of the IMF and solar wind speed, are shown to be statistically significant at the 93% level or above. Reconstructions are made using four combinations of different indices, compiled using different data and different algorithms, and the results are almost identical for all parameters. The correction to the aa index required is discussed by comparison with the Ap index from a more extensive network of mid-latitude stations. Data from the Helsinki magnetometer station is used to extend the aa index back to 1845 and the results confirmed by comparison with the nearby St Petersburg observatory. The optimum variations, using all available long-term geomagnetic indices, of the near-Earth IMF and solar wind speed, and of the open solar flux, are presented; all with ±2sigma� uncertainties computed using the Monte Carlo technique outlined in the earlier papers. The open solar flux variation derived is shown to be very similar indeed to that obtained using the method of Lockwood et al. (1999).