864 resultados para fate and effect modelling


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ANTECEDENTES. La mortalidad neonatal se debe principalmente a procesos infecciosos y a prematurez. Se ha sugerido que el lavado corporal total con clorhexidina podría reducir la mortalidad neonatal relacionada con infección. No existen revisiones sistemáticas que exploren la eficacia de esta intervención. Objetivo. Evaluar la eficacia y seguridad de la limpieza corporal total con clorhexidina en la prevención de las infecciones asociadas al cuidado de la salud en neonatos de alto riesgo hospitalizados en cuidado intensivo neonatal. Metodología. Se realizó una revisión sistemática de la literatura. La búsqueda se hizo a través de las bases de datos Medline, Embase, LilaCS, Cochrane library y el registro de ensayos clínicos del Instituto Nacional de Salud de Estados Unidos. Se incluyeron ensayos clínicos publicados en los últimos 15 años hasta el 30 de enero del 2015. Las variables cualitativas se estimaron mediante OR o RR con sus IC95%. Las variables cuantitativas mediante diferencias de promedios o diferencias estandarizadas de promedios con sus IC95%. Resultados: Se incluyeron 3 estudios en el análisis cualitativo y cuantitativo. No se encontró evidencia concluyente que permita recomendar el uso de la limpieza corporal total con clorhexidina en los recién nacidos hospitalizados en cuidado intensivo neonatal. Conclusión: No existe evidencia que permita concluir que la limpieza corporal total con clorhexidina al 0.25% es mejor respecto a otras intervenciones en la prevención de sepsis neonatal asociada al cuidado de la salud . Es una intervención segura sin efectos adversos significativos.

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El canal lumbar estrecho de tipo degenerativo, es una enfermedad que se presenta en pacientes entre la quinta y la sexta década de vida; es la causa más común de cirugía lumbar después de los 65 años. Este trabajo busca determinar cuáles son los factores asociados a la presentación de eventos adversos o re-intervención en cirugía de canal lumbar estrecho en la Fundación Santa Fe de Bogotá en los años comprendidos entre 2003 y 2013. Métodos: se realizó un estudio de prevalencia de tipo analítico, en donde se analizaron 249 pacientes sometidos a intervención quirúrgica por cirugía de canal lumbar estrecho.

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G-Rex is light-weight Java middleware that allows scientific applications deployed on remote computer systems to be launched and controlled as if they are running on the user's own computer. G-Rex is particularly suited to ocean and climate modelling applications because output from the model is transferred back to the user while the run is in progress, which prevents the accumulation of large amounts of data on the remote cluster. The G-Rex server is a RESTful Web application that runs inside a servlet container on the remote system, and the client component is a Java command line program that can easily be incorporated into existing scientific work-flow scripts. The NEMO and POLCOMS ocean models have been deployed as G-Rex services in the NERC Cluster Grid, and G-Rex is the core grid middleware in the GCEP and GCOMS e-science projects.

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Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

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Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.

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We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stochastic physics schemes that have been proposed for use in general circulation models (GCMs). We argue that although single column tests cannot be definitive in exposing the full behaviour of a stochastic method in the full GCM, and although there are differences between SCM testing of deterministic and stochastic methods, SCM testing remains a useful tool. It is necessary to consider an ensemble of SCM runs produced by the stochastic method. These can be usefully compared to deterministic ensembles describing initial condition uncertainty and also to combinations of these (with structural model changes) into poor man's ensembles. The proposed methodology is demonstrated using an SCM experiment recently developed by the GCSS (GEWEX Cloud System Study) community, simulating transitions between active and suppressed periods of tropical convection.

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A water quality model is used to assess the impact of possible climate change on dissolved oxygen (DO) in the Thames. The Thames catchment is densely populated and, typically, many pressures are anthropogenic. However, that same population also relies on the river for potable water supply and as a disposal route for treated wastewater. Thus, future water quality will be highly dependent on future activity. Dynamic and stochastic modelling has been used to assess the likely impacts on DO dynamics along the river system and the probability distributions associated with future variability. The modelling predictions indicate that warmer river temperatures and drought act to reduce dissolved oxygen concentrations in lowland river systems

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Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

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We report the results of a multi-instrument, multi-technique, coordinated study of the solar eruptive event of 13 May 2005. We discuss the resultant Earth-directed (halo) coronal mass ejection (CME), and the effects on the terrestrial space environment and upper Earth atmosphere. The interplanetary CME (ICME) impacted the Earth’s magnetosphere and caused the most-intense geomagnetic storm of 2005 with a Disturbed Storm Time (Dst) index reaching −263 nT at its peak. The terrestrial environment responded to the storm on a global scale. We have combined observations and measurements from coronal and interplanetary remote-sensing instruments, interplanetary and near-Earth in-situ measurements, remote-sensing observations and in-situ measurements of the terrestrial magnetosphere and ionosphere, along with coronal and heliospheric modelling. These analyses are used to trace the origin, development, propagation, terrestrial impact, and subsequent consequences of this event to obtain the most comprehensive view of a geo-effective solar eruption to date. This particular event is also part of a NASA-sponsored Living With a Star (LWS) study and an on-going US NSF-sponsored Solar, Heliospheric, and INterplanetary Environment (SHINE) community investigation.

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The MarQUEST (Marine Biogeochemistry and Ecosystem Modelling Initiative in QUEST) project was established to develop improved descriptions of marine biogeochemistry, suited for the next generation of Earth system models. We review progress in these areas providing insight on the advances that have been made as well as identifying remaining key outstanding gaps for the development of the marine component of next generation Earth system models. The following issues are discussed and where appropriate results are presented; the choice of model structure, scaling processes from physiology to functional types, the ecosystem model sensitivity to changes in the physical environment, the role of the coastal ocean and new methods for the evaluation and comparison of ecosystem and biogeochemistry models. We make recommendations as to where future investment in marine ecosystem modelling should be focused, highlighting a generic software framework for model development, improved hydrodynamic models, and better parameterisation of new and existing models, reanalysis tools and ensemble simulations. The final challenge is to ensure that experimental/observational scientists are stakeholders in the models and vice versa.

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The surface structure of BaO(111) has been determined using STM and computer modelling. The BaO(111) surface was prepared in thin film form on Pt(111) and presents a surface with twice the lattice parameter expected for that of the bulk termination, i.e. a (2 x 2) reconstruction. Computer modelling indicates that the bulk termination is unstable, but that the (2 x 2) reconstructed BaO(111) surface has a low surface energy and is hence a stable surface reconstruction. The (2 x 2) reconstruction consists of small, three-sided pyramids with (100) oriented sides and either oxygen or barium ions at the apices. Less regular surface reconstructions containing the same pyramids are almost equally stable, indicating that we may also expect less regular regions to appear with a fairly random distribution of these surface species. The simulations further suggest that a regular (4 x 4) reconstruction built up of bigger pyramids is even more energetically favourable, and some evidence is found for such a structure in the STM. (c) 2006 Elsevier B.V. All rights reserved.

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