6,404 research outputs found

    Wild Horses

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    Photograph of Perry Como; Background illustration of horseshttps://scholarsjunction.msstate.edu/cht-sheet-music/6808/thumbnail.jp

    Clinical expectations: What facilitators expect from ESL students on clinical placement

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    Many nursing students for whom English is a second language (ESL) face challenges related to communication on clinical placement and although clinical facilitators are not usually trained language assessors, they are often in a position of needing to assess ESL students' clinical language performance. Little is known, however, about the particular areas of clinical performance facilitators focus on when they are assessing ESL students. This paper discusses the results of a study of facilitators' written assessment comments about the clinical performance of a small group of ESL nursing students over a two and a half year period. These comments were documented on students' clinical assessment forms at the end of each placement. The results provide a more detailed insight into facilitators' expectations of students' language performance and the particular challenges faced by ESL students and indicate that facilitators have clear expectations of ESL students regarding communication, learning styles and professional demeanour. These findings may help both ESL students and their facilitators better prepare for clinical placement. © 2011 Elsevier Ltd

    Assessing students' English language proficiency during clinical placement: A qualitative evaluation of a language framework

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    © 2015 Elsevier Ltd. The increase in nursing students for whom English is an additional language requires clinical facilitators to assess students' performance regarding clinical skills, nursing communication and English language. However, assessing language proficiency is a complex process that is often conflated with cultural norms and clinical skills, and facilitators may lack confidence in assessing English language. This paper discusses an evaluation of a set of guidelines developed in a large metropolitan Australian university to help clinical facilitators make decisions about students' English language proficiency. The study found that the guidelines were useful in helping facilitators assess English language. However, strategies to address identified language problems needed to be incorporated to enable the guidelines to also be used as a teaching tool. The study concludes that to be effective, such guidelines need embedding within a systematic approach that identifies and responds to students who may be underperforming due to a low level of English language proficiency

    Helminth species richness in wild wood mice, Apodemus sylvaticus, is enhanced by the presence of the intestinal nematode Heligmosomoides polygyrus

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    We analysed 3 independently collected datasets of fully censused helminth burdens in wood mice, Apodemus sylvaticus, testing the a priori hypothesis of Behnke et al. (2005) that the presence of the intestinal nematode Heligmosomoides polygyrus predisposes wood mice to carrying other species of helminths. In Portugal, mice carrying H. polygyrus showed a higher prevalence of other helminths but the magnitude of the effect was seasonal. In Egham, mice with H. polygyrus showed a higher prevalence of other helminth species, not confounded by other factors. In Malham Tarn, mice carrying H. polygyrus were more likely to be infected with other species, but only among older mice. Allowing for other factors, heavy residual H. polygyrus infections carried more species of other helminths in both the Portugal and Egham data; species richness in Malham was too low to conduct a similar analysis, but as H. polygyrus worm burdens increased, so the prevalence of other helminths also increased. Our results support those of Behnke et al. (2005), providing firm evidence that at the level of species richness a highly predictable element of co-infections in wood mice has now been defined: infection with H. polygyrus has detectable consequences for the susceptibility of wood mice to other intestinal helminth species

    The turbulent wake of a monopile foundation

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    publisher: Elsevier articletitle: The turbulent wake of a monopile foundation journaltitle: Renewable Energy articlelink: http://dx.doi.org/10.1016/j.renene.2016.02.050 content_type: article copyright: Copyright © 2016 Elsevier Ltd. All rights reserved

    Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

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    Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals.Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran’s I spatial autocorrelation, and Local Moran’s I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities).Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing

    Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada [version 1; peer review: awaiting peer review]

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    This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals

    Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures

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    Purpose. Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy. Methods. This study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-malignant blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to machine learning-based classifiers to predict radiation exposure in other hematological conditions. Results. Except for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8 to 54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thromboembolism, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death. Riboviral infections (for example, Influenza or Dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions. Conclusions. This approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures
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