Moment properties of estimators for an extreme value regression model with type 2 censoring

An extreme value regression model for grouped data with type 2 censoring is considered. The response variable is taken to have a type 1 ext reme va lue d i s t r i b u t i on for sma l l e s t v a l ue s a nd a s tandar d linear regression model is assumed f o r t he means . Large sampl e approximations to the variances of the maximum likelihood estimators are derived. The small sample moment properties of the maximum likelihood estimators are evaluated by simulation for the case of simp l e l i n e a r r e g ress i o n . T h e r e sul t s s h o w t h a t t h e e stima t or o f the scale parameter has a s t rong bias in sma l l samples, particularly when ther e is a heavy degree of censoring. Final l y , sma l l sample variance and mean square error efficiences of the best linear unbiased estimators relative to the maximum likelihood estimators are assessed

Sediment-moss interactions on a temperate glacier: Falljökull, Iceland

Full text of this article can be found at: http://www.igsoc.org/annals/ Copyright IGS. DOI: 10.3189/172756408784700734We present the results of preliminary investigations of globular moss growth on the surface of Falljökull, a temperate outlet glacier of the Vatnajökull ice cap, southern Iceland. Supraglacial debris has provided a basis for moss colonization, and several large (>500 m2) patches of moss growth (Racomitrium spp.) are observed on the surface of the glacier. Each area of moss-colonized supraglacial debris shows a downslope increase in sphericity and moss cushion size and a decrease in percentage surface coverage of moss-colonized and bare clasts. It is suggested that moss growth on supraglacial debris allows preferential downslope movement of clasts through an associated increase in both overall mass and sphericity. Thermal insulation by moss cushions protects the underlying ice surface from melt, and the resulting ice pedestals assist in downslope sliding and toppling of moss cushions. The morphology and life cycle of supraglacial globular mosses is therefore not only closely linked to the presence and distribution of supraglacial debris, but also appears to assist in limited down-glacier transport of this debris. This research highlights both the dynamic nature of the interaction of mosses with supraglacial sedimentary systems and the need for a detailed consideration of their role within the wider glacial ecosystem.Peer reviewe

Accelerating global left-ventricular function assessment in mice using reduced slice acquisition and three-dimensional guide-point modelling

<p>Abstract</p> <p>Background</p> <p>To investigate the utility of three-dimensional guide-point modeling (GPM) to reduce the time required for CMR evaluation of global cardiac function in mice, by reducing the number of image slices required for accurate quantification of left-ventricular (LV) mass and volumes.</p> <p>Methods</p> <p>Five female C57Bl/6 mice 8 weeks post myocardial infarction induced by permanent occlusion of the left coronary artery, and six male control (un-operated) C57Bl/6 mice, were subject to CMR examination under isoflurane anaesthesia. Contiguous short axis (SAX) slices (1 mm thick 7-9 slices) were obtained together with two long axis (LAX) slices in two chamber and four chamber orientations. Using a mathematical model of the heart to interpolate information between the available slices, GPM LV mass and volumes were determined using full slice (all SAX and two LAX), six slice (four SAX and two LAX) and four slice (two SAX and two LAX) analysis protocols. All results were compared with standard manual volumetric analysis using all SAX slices.</p> <p>Results</p> <p>Infarct size was 39.1 ± 5.1% of LV myocardium. No significant differences were found in left ventricular mass and volumes between the standard and GPM full and six slice protocols in infarcted mice (113 ± 10, 116 ± 11, and 117 ± 11 mg respectively for mass), or between the standard and GPM full, six and four slice protocols in control mice, (105 ± 14, 106 ± 10, 104 ± 12, and 105 ± 7 mg respectively for mass). Significant differences were found in LV mass (135 ± 18 mg) and EF using the GPM four slice protocol in infarcted mice (p < 0.05).</p> <p>Conclusion</p> <p>GPM enables accurate analysis of LV function in mice with relatively large infarcts using a reduced six slice acquisition protocol, and in mice with normal/symmetrical left-ventricular topology using a four slice protocol.</p

New evidence on Allyn Young's style and influence as a teacher

This paper publishes the hitherto unpublished correspondence between Allyn Abbott Young's biographer Charles Blitch and 17 of Young's former students or associates. Together with related biographical and archival material, the paper shows the way in which this adds to our knowledge of Young's considerable influence as a teacher upon some of the twentieth century's greatest economists. The correspondents are as follows: James W Angell, Colin Clark, Arthur H Cole, Lauchlin Currie, Melvin G de Chazeau, Eleanor Lansing Dulles, Howard S Ellis, Frank W Fetter, Earl J Hamilton, Seymour S Harris, Richard S Howey, Nicholas Kaldor, Melvin M Knight, Bertil Ohlin, Geoffrey Shepherd, Overton H Taylor, and Gilbert Walker

4DFlowNet: Super-Resolution 4D Flow MRI Using Deep Learning and Computational Fluid Dynamics

4D flow magnetic resonance imaging (MRI) is an emerging imaging technique where spatiotemporal 3D blood velocity can be captured with full volumetric coverage in a single non-invasive examination. This enables qualitative and quantitative analysis of hemodynamic flow parameters of the heart and great vessels. An increase in the image resolution would provide more accuracy and allow better assessment of the blood flow, especially for patients with abnormal flows. However, this must be balanced with increasing imaging time. The recent success of deep learning in generating super resolution images shows promise for implementation in medical images. We utilized computational fluid dynamics simulations to generate fluid flow simulations and represent them as synthetic 4D flow MRI data. We built our training dataset to mimic actual 4D flow MRI data with its corresponding noise distribution. Our novel 4DFlowNet network was trained on this synthetic 4D flow data and was capable in producing noise-free super resolution 4D flow phase images with upsample factor of 2. We also tested the 4DFlowNet in actual 4D flow MR images of a phantom and normal volunteer data, and demonstrated comparable results with the actual flow rate measurements giving an absolute relative error of 0.6–5.8% and 1.1–3.8% in the phantom data and normal volunteer data, respectively