2,373 research outputs found

    Coastal erosion reveals a potentially unique Oligocene and possible periglacial sequence at present-day sea level in Port Davey, remote South-West Tasmania

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    Cut-back of a sea-cliff at Hannant Inlet in remote South-West Tasmania has exposed Oligocene clays buried under Late Pleistocene “colluvium” from which abundant wood fragments protrude. The two units are separated by a transitional interval defined by mixed Oligocene and Pleistocene microfloras. Microfloras preserved in situ in the clay provide a link between floras in Tasmania and other Southern Hemisphere landmasses following onset of major glaciation in East Antarctica during the Eocene-Oligocene transition (c. 34 Ma). The Late Pleistocene “colluvium” preserves abundant fossil pollen of the shrub conifer genus Pherosphaera (al. Microstrobos). Assuming the parent plants had the same upper subalpine-alpine ecology as living Pherosphaera hookeriana, the microflora provides evidence for cold, wet conditions in the Port Davey lowlands during a low sea-level stand. The same data highlight the failure of Pherosphaera to regain its Pleistocene distribution during the Postglacial period. Our data are inconclusive whether Late Pleistocene conditions in Hannant Inlet were periglacial, i.e., the Oligocene sediments were turbated by freeze-thaw processes, or have been reworked by fluvial processes into the Pleistocene “colluvium”. Nevertheless, the inferred cold-climate is consistent with the former hypothesis. The sequence is sealed under cross-bedded coarse quartzite gravels of presumed Last Glacial Stage age

    Results from a set of three-dimensional numerical experiments of a hot Jupiter atmosphere.

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    ArticleThis is the author accepted manuscript. The final version is available from EDP Sciences via the DOI in this record.We present highlights from a large set of simulations of a hot Jupiter atmosphere, nominally based on HD 209458b, aimed at exploring both the evolution of the deep atmosphere, and the acceleration of the zonal flow or jet. We find the occurrence of a super-rotating equatorial jet is robust to changes in various parameters, and over long timescales, even in the absence of strong inner or bottom boundary drag. This jet is diminished in one simulation only, where we strongly force the deep atmosphere equator–to–pole temperature gradient over long timescales. Finally, although the eddy momentum fluxes in our atmosphere show similarities with the proposed mechanism for accelerating jets on tidally-locked planets, the picture appears more complex. We present tentative evidence for a jet driven by a combination of eddy momentum transport and mean flow

    Assessing Professionalism: A theoretical framework for defining clinical rotation assessment criteria

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    Although widely accepted as an important graduate competence, professionalism is a challenging outcome to define and assess. Clinical rotations provide an excellent opportunity to develop student professionalism through the use of experiential learning and effective feedback, but without appropriate theoretical frameworks, clinical teachers may find it difficult to identify appropriate learning outcomes. The adage “I know it when I see it” is unhelpful in providing feedback and guidance for student improvement, and criteria that are more specifically defined would help students direct their own development. This study sought first to identify how clinical faculty in one institution currently assess professionalism, using retrospective analysis of material obtained in undergraduate teaching and faculty development sessions. Subsequently, a faculty workshop was held in which a round-table type discussion sought to develop these ideas and identify how professionalism assessment could be improved. The output of this session was a theoretical framework for teaching and assessing professionalism, providing example assessment criteria and ideas for clinical teaching. This includes categories such as client and colleague interaction, respect and trust, recognition of limitations, and understanding of different professional identities. Each category includes detailed descriptions of the knowledge, skills, and behaviors expected of students in these areas. The criteria were determined by engaging faculty in the development of the framework, and therefore they should represent a focused development of criteria already used to assess professionalism, and not a novel and unfamiliar set of assessment guidelines. The faculty-led nature of this framework is expected to facilitate implementation in clinical teaching

    Effects of Cognitive Behavioral Therapy on Daily Living Skills in Children with High-Functioning Autism and Concurrent Anxiety Disorders

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    CBT is a promising treatment for children with autism spectrum disorders (ASD) and focuses, in part, on children’s independence and self-help skills. In a trial of CBT for anxiety in ASD (Wood et al. in J Child Psychol Psychiatry 50:224–234, 2009), children’s daily living skills and related parental intrusiveness were assessed. Forty children with ASD (7–11 years) and their primary caregiver were randomly assigned to an immediate treatment (IT; n = 17) or 3-month waitlist (WL; n = 23) condition. In comparison to WL, IT parents reported increases in children’s total and personal daily living skills, and reduced involvement in their children’s private daily routines. Reductions correlated with reduced anxiety severity. These results provide preliminary evidence that CBT may yield increased independence and daily living skills among children with ASD

    Following spatial Aβ aggregation dynamics in evolving Alzheimer's disease pathology by imaging stable isotope labeling kinetics.

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    β-Amyloid (Aβ) plaque formation is the major pathological hallmark of Alzheimer’s disease (AD) and constitutes a potentially critical, early inducer driving AD pathogenesis as it precedes other pathological events and cognitive symptoms by decades. It is therefore critical to understand how Aβ pathology is initiated and where and when distinct Aβ species aggregate. Here, we used metabolic isotope labeling in APPNL-G-F knock-in mice together with mass spectrometry imaging to monitor the earliest seeds of Aβ deposition through ongoing plaque development. This allowed visualizing Aβ aggregation dynamics within single plaques across different brain regions. We show that formation of structurally distinct plaques is associated with differential Aβ peptide deposition. Specifically, Aβ1-42 is forming an initial core structure followed by radial outgrowth and late secretion and deposition of Aβ1-38. These data describe a detailed picture of the earliest events of precipitating amyloid pathology at scales not previously possible

    Deep learning to automate the labelling of head MRI datasets for computer vision applications

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    OBJECTIVES: The purpose of this study was to build a deep learning model to derive labels from neuroradiology reports and assign these to the corresponding examinations, overcoming a bottleneck to computer vision model development. METHODS: Reference-standard labels were generated by a team of neuroradiologists for model training and evaluation. Three thousand examinations were labelled for the presence or absence of any abnormality by manually scrutinising the corresponding radiology reports ('reference-standard report labels'); a subset of these examinations (n = 250) were assigned 'reference-standard image labels' by interrogating the actual images. Separately, 2000 reports were labelled for the presence or absence of 7 specialised categories of abnormality (acute stroke, mass, atrophy, vascular abnormality, small vessel disease, white matter inflammation, encephalomalacia), with a subset of these examinations (n = 700) also assigned reference-standard image labels. A deep learning model was trained using labelled reports and validated in two ways: comparing predicted labels to (i) reference-standard report labels and (ii) reference-standard image labels. The area under the receiver operating characteristic curve (AUC-ROC) was used to quantify model performance. Accuracy, sensitivity, specificity, and F1 score were also calculated. RESULTS: Accurate classification (AUC-ROC > 0.95) was achieved for all categories when tested against reference-standard report labels. A drop in performance (ΔAUC-ROC > 0.02) was seen for three categories (atrophy, encephalomalacia, vascular) when tested against reference-standard image labels, highlighting discrepancies in the original reports. Once trained, the model assigned labels to 121,556 examinations in under 30 min. CONCLUSIONS: Our model accurately classifies head MRI examinations, enabling automated dataset labelling for downstream computer vision applications. KEY POINTS: • Deep learning is poised to revolutionise image recognition tasks in radiology; however, a barrier to clinical adoption is the difficulty of obtaining large labelled datasets for model training. • We demonstrate a deep learning model which can derive labels from neuroradiology reports and assign these to the corresponding examinations at scale, facilitating the development of downstream computer vision models. • We rigorously tested our model by comparing labels predicted on the basis of neuroradiology reports with two sets of reference-standard labels: (1) labels derived by manually scrutinising each radiology report and (2) labels derived by interrogating the actual images

    Near-field examination of perovskite-based superlenses and superlens-enhanced probe-object coupling

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    A planar slab of negative index material works as a superlens with sub-diffraction-limited imaging resolution, since propagating waves are focused and, moreover, evanescent waves are reconstructed in the image plane. Here, we demonstrate a superlens for electric evanescent fields with low losses using perovskites in the mid-infrared regime. The combination of near-field microscopy with a tunable free-electron laser allows us to address precisely the polariton modes, which are critical for super-resolution imaging. We spectrally study the lateral and vertical distributions of evanescent waves around the image plane of such a lens, and achieve imaging resolution of wavelength/14 at the superlensing wavelength. Interestingly, at certain distances between the probe and sample surface, we observe a maximum of these evanescent fields. Comparisons with numerical simulations indicate that this maximum originates from an enhanced coupling between probe and object, which might be applicable for multifunctional circuits, infrared spectroscopy, and thermal sensors.Comment: 20 pages, 6 figures, published as open access article in Nature Communications (see http://www.nature.com/ncomms/
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