849 resultados para Triage Scales
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Acknowledgements This study is part of the first author’s PhD projects in 2010–2014, co-funded by the National Centre for Groundwater Research and Training in Australia and the China Scholarship Council. We give thanks to Zijuan Deng and Xiang Xu for their assistance in the field. Constructive comments and suggestion from the anonymous reviewers are appreciated for significant improvement of the manuscript.
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Peer reviewed
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The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.
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The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3?km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70?% parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3?km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.
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This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.
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Background: It is important to assess the clinical competence of nursing students to gauge their educational needs. Competence can be measured by self-assessment tools; however, Anema and McCoy (2010) contend that currently available measures should be further psychometrically tested.
Aim: To test the psychometric properties of Nursing Competencies Questionnaire (NCQ) and Self-Efficacy in Clinical Performance (SECP) clinical competence scales.
Method: A non-randomly selected sample of n=248 2nd year nursing students completed NCQ, SECP and demographic questionnaires (June and September 2013). Mokken Scaling Analysis (MSA) was used to investigate structural validity and scale properties; convergent and discriminant validity and reliability were also tested for each scale.
Results: MSA analysis identified that the NCQ is a unidimensional scale with strong scale scalability coefficients Hs =0.581; but limited item rankability HT =0.367. The SECP scale MSA suggested that the scale could be potentially split into two unidimensional scales (SECP28 and SECP7), each with good/reasonable scalablity psychometric properties as summed scales but negligible/very limited scale rankability (SECP28: Hs = 0.55, HT=0.211; SECP7: Hs = 0.61, HT=0.049). Analysis of between cohort differences and NCQ/SECP scores produced evidence of discriminant and convergent validity; good internal reliability was also found: NCQ α = 0.93, SECP28 α = 0.96 and SECP7 α=0.89.
Discussion: In line with previous research further evidence of the NCQ’s reliability and validity was demonstrated. However, as the SECP findings are new and the sample small with reference to Straat and colleagues (2014), the SECP results should be interpreted with caution and verified on a second sample.
Conclusions: Measurement of perceived self-competence could start early in a nursing programme to support students’ development of clinical competence. Further testing of the SECP scale with larger nursing student samples from different programme years is indicated.
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Anema, M., G and McCoy, JK. (2010) Competency-Based Nursing Education: Guide to Achieving Outstanding Learner Outcomes. New York: Springer.
Straat, JH., van der Ark, LA and Sijtsma, K. (2014) Minimum Sample Size Requirements for Mokken Scale Analysis Educational and Psychological Measurement 74 (5), 809-822.
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This work explores the development of MemTri. A memory forensics triage tool that can assess the likelihood of criminal activity in a memory image, based on evidence data artefacts generated by several applications. Fictitious illegal suspect activity scenarios were performed on virtual machines to generate 60 test memory images for input into MemTri. Four categories of applications (i.e. Internet Browsers, Instant Messengers, FTP Client and Document Processors) are examined for data artefacts located through the use of regular expressions. These identified data artefacts are then analysed using a Bayesian Network, to assess the likelihood that a seized memory image contained evidence of illegal activity. Currently, MemTri is under development and this paper introduces only the basic concept as well as the components that the application is built on. A complete description of MemTri coupled with extensive experimental results is expected to be published in the first semester of 2017.
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Programa de doctorado en Oceanografía. En portada: Institut de Ciènces del Mar. Instituto Español de Oceanografía. La fecha de publicación es la fecha de lectura
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As the global population becomes increasingly urban, research is needed to explore how local culture, land use, and policy will influence urban natural resource management. We used a broad-scale comparative approach and survey of residents within the Portland (Oregon)-Vancouver (Washington) metropolitan areas, USA, two states with similar geographical and ecological characteristics, but different approaches to land-use planning, to explore resident perceptions about natural resources at three scales of analysis: property level (“at or near my house”), neighborhood (“within a 20-minute walk from my house”), and metro level (“across the metro area”). At the metro-level scale, nonmetric multidimensional scaling revealed that the two cities were quite similar. However, affinity for particular landscape characteristics existed within each city with the greatest difference generally at the property-level scale. Portland respondents expressed affinity for large mature trees, tree-lined streets, public transportation, and proximity to stores and services. Vancouver respondents expressed affinity for plentiful accessible parking. We suggest three explanations that likely are not mutually exclusive. First, respondents are segmented based on preferences for particular amenities, such as convenience versus commuter needs. Second, historical land-use and tax policy legacies may influence individual decisions. Third, more environmentally attuned worldviews may influence an individual’s desire to produce environmentally friendly outcomes. Our findings highlight the importance of acknowledging variations in residents’ affinities for landscape characteristics across different scales and locations because these differences may influence future land-use policies about urban natural resources.