2,718 research outputs found

    Listening to student voices through scenario design: Aligning learning.futures

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    This paper explores the preferred learning futures of students at the University of Technology Sydney and the alignments of students’ preferred futures with policy changes. The aim of the paper is to describe a different approach to listening to students’ voices and illuminate some possible ways in which the student voice can influence the implementation of higher education learning policies, with the aim of ultimately improving student learning experiences into the future. Students’ preferred futures were explored through a methodology of rapidly formulated collaborative scenario design, then coded thematically using open coding. Broad themes related to the changing context, learning environments, and independent learning, with students seeing ideal learning in higher education being a combination of personal, social and connected experiences. In order to offer a student perspective that is of use to policymakers, we discuss these preferred futures in relation to the University of Technology Sydney’s ‘learning.futures’ approach, which focuses on changing the way that learning happens in the university

    Structural validation of oral mucosal tissue using optical coherence tomography

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    Background: Optical coherence tomography (OCT) is a non-invasive optical technology using near-infrared light to produce cross-sectional tissue images with lateral resolution. Objectives: The overall aims of this study was to generate a bank of normative and pathological OCT data of the oral tissues to allow identification of cellular structures of normal and pathological processes with the aim to create a diagnostic algorithm which can be used in the early detection of oral disorders. Material and methods: Seventy-three patients with 78 suspicious oral lesions were referred for further management to the UCLH Head and Neck Centre, London. The entire cohort had their lesions surgically biopsied (incisional or excisional). The immediate ex vivo phase involved scanning the specimens using optical coherence tomography. The specimens were then processed by a histopathologist. Five tissue structures were evaluated as part of this study, including: keratin cell layer, epithelial layer, basement membrane, lamina propria and other microanatomical structures. Two independent assessors (clinician and pathologist trained to use OCT) assessed the OCT images and were asked to comment on the cellular structures and changes involving the five tissue structures in non-blind fashion. Results: Correct identification of the keratin cell layer and its structural changes was achieved in 87% of the cohort; for the epithelial layer it reached 93.5%, and 94% for the basement membrane. Microanatomical structures identification was 64% for blood vessels, 58% for salivary gland ducts and 89% for rete pegs. The agreement was “good” between the clinician and the pathologist. OCT was able to differential normal from pathological tissue and pathological tissue of different entities in this immediate ex vivo study. Unfortunately, OCT provided inadequate cellular and subcellular information to enable the grading of oral premalignant disorders. Conclusion: This study enabled the creation of OCT bank of normal and pathological oral tissues. The pathological changes identified using OCT enabled differentiation between normal and pathological tissues, and identification of different tissue pathologies. Further studies are required to assess the accuracy of OCT in identification of various pathological processes involving the oral tissues

    Real-time surveillance for abnormal events: the case of influenza outbreaks

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    This paper introduces a method of surveillance using deviations from probabilistic forecasts. Realised observations are compared with probabilistic forecasts, and the “deviation” metric is based on low probability events. If an alert is declared, the algorithm continues to monitor until an all‐clear is announced. Specifically, this article addresses the problem of syndromic surveillance for influenza (flu) with the intention of detecting outbreaks, due to new strains of viruses, over and above the normal seasonal pattern. The syndrome is hospital admissions for flu‐like illness, and hence, the data are low counts. In accordance with the count properties of the observations, an integer‐valued autoregressive process is used to model flu occurrences. Monte Carlo evidence suggests the method works well in stylised but somewhat realistic situations. An application to real flu data indicates that the ideas may have promise. The model estimated on a short run of training data did not declare false alarms when used with new observations deemed in control, ex post. The model easily detected the 2009 H 1N 1 outbreak. Copyright © 2016 John Wiley & Sons, Ltd

    Home Literacy Environments of Young Children With Down Syndrome Findings From a Web-Based Survey

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    Early home literacy experiences, including parent-child book reading, account for a significant amount of children\u27s later reading achievement. Yet there is a very limited research base about the home literacy environments and experiences of children with cognitive disabilities. The purpose of this study is to describe findings from a Web-based survey of home literacy environments of young children with Down syndrome. Respondents (n = 107) were mostly mothers; a majority were well educated. Findings suggest that respondents gave literacy a higher priority than reported in prior research on children with disabilities. More than 70% of respondents had 50 or more children\u27s books and also had literacy materials including flash cards, magnetic letters, and educational videos or computer games. Most parents read to their children and used these literacy materials 10 to 30 min per day. Respondents reported that their children had reached many important early literacy milestones, and they also described having relatively ambitious lifelong literacy goals for their children. Important implications for research and practice are discussed

    Evaluation of adipose tissue volume quantification with IDEAL fat-water separation

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    Purpose: To validate iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) for adipose tissue volume quantification. IDEAL allows MRI images to be produced only from adipose-containing tissues; hence, quantifying adipose tissue should be simpler and more accurate than with current methods. Materials and Methods: Ten healthy controls were imaged with 1.5 Tesla (T) Spin Echo (SE), 3.0T T1-weighted spoiled gradient echo (SPGR), and 3.0T IDEAL-SPGR. Images were acquired from the abdomen, pelvis, mid-thigh, and mid-calf. Mean subcutaneous and visceral adipose tissue volumes were compared between the three acquisitions for each subject. Results: There were no significant differences (P \u3e 0.05) between the three acquisitions for subcutaneous adipose tissue volumes. However, there was a significant difference (P = 0.0002) for visceral adipose tissue volumes in the abdomen. Post hoc analysis showed significantly lower visceral adipose tissue volumes measured by IDEAL versus 1.5T (P \u3c 0.0001) and 3.0T SPGR (P \u3c 0.002). The lower volumes given by IDEAL are due to its ability to differentiate true visceral adipose tissue from other bright structures like blood vessels and bowel content that are mistaken for adipose tissue in non-fat suppressed images. Conclusion: IDEAL measurements of adipose tissue are equivalent to established 1.5T measurement techniques for subcutaneous depots and have improved accuracy for visceral depots, which are more metabolically relevant. © 2011 Wiley-Liss, Inc

    When Models Interact with their Subjects: The Dynamics of Model Aware Systems

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    A scientific model need not be a passive and static descriptor of its subject. If the subject is affected by the model, the model must be updated to explain its affected subject. In this study, two models regarding the dynamics of model aware systems are presented. The first explores the behavior of "prediction seeking" (PSP) and "prediction avoiding" (PAP) populations under the influence of a model that describes them. The second explores the publishing behavior of a group of experimentalists coupled to a model by means of confirmation bias. It is found that model aware systems can exhibit convergent random or oscillatory behavior and display universal 1/f noise. A numerical simulation of the physical experimentalists is compared with actual publications of neutron life time and {\Lambda} mass measurements and is in good quantitative agreement.Comment: Accepted for publication in PLoS-ON

    The novel E. coli cell division protein, YtfB, plays a role in eukaryotic cell adhesion.

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    Characterisation of protein function based solely on homology searches may overlook functions under specific environmental conditions, or the possibility of a protein having multiple roles. In this study we investigated the role of YtfB, a protein originally identified in a genome-wide screen to cause inhibition of cell division, and has demonstrated to localise to the Escherichia coli division site with some degree of glycan specificity. Interestingly, YtfB also shows homology to the virulence factor OapA from Haemophilus influenzae, which is important for adherence to epithelial cells, indicating the potential of additional function(s) for YtfB. Here we show that E. coli YtfB binds to N'acetylglucosamine and mannobiose glycans with high affinity. The loss of ytfB results in a reduction in the ability of the uropathogenic E. coli strain UTI89 to adhere to human kidney cells, but not to bladder cells, suggesting a specific role in the initial adherence stage of ascending urinary tract infections. Taken together, our results suggest a role for YtfB in adhesion to specific eukaryotic cells, which may be additional, or complementary, to its role in cell division. This study highlights the importance of understanding the possible multiple functions of proteins based on homology, which may be specific to different environmental conditions
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