1,628 research outputs found
Fabrication and transport critical currents of multifilamentary MgB2/Fe wires and tapes
Multifilamentary MgB2/Fe wires and tapes with high transport critical current
densities have been fabricated using a straightforward powder-in-tube (PIT)
process. After annealing, we measured transport jc values up to 1.1 * 105 A/cm2
at 4.2 K and in a field of 2 T in a MgB2/Fe square wire with 7 filaments
fabricated by two-axial rolling, and up to 5 * 104 A/cm2 at 4.2 K in 1 T in a
MgB2/Fe tape with 7 filaments. For higher currents these multifilamentary wires
and tapes quenched due to insufficient thermal stability of filaments. Both the
processing routes and deformation methods were found to be important factors
for fabricating multifilamentary MgB2 wires and tapes with high transport jc
values.Comment: 13 pages, 7 figure
Transport Properties and Exponential n-values of Fe/MgB2 Tapes With Various MgB2 Particle Sizes
Fe/MgB2 tapes have been prepared starting with pre-reacted binary MgB2
powders. As shown by resistive and inductive measurements, the reduction of
particle size to a few microns by ball milling has little influence on Bc2,
while the superconducting properties of the individual MgB2 grains are
essentially unchanged. Reducing the particle size causes an enhancement of Birr
from 14 to 16 T, while Jc has considerably increased at high fields, its slope
Jc(B) being reduced. At 4.2K, values of 5.3*10^4 and 1.2*10^3 A/cm^2 were
measured at 3.5 and 10 T, respectively, suggesting a dominant role of the
conditions at the grain interfaces. A systematic variation of these conditions
at the interfaces is undertaken in order to determine the limit of transport
properties for Fe/MgB2 tapes. The addition of 5% Mg to MgB2 powder was found to
affect neither Jc nor Bc2. For the tapes with the highest Jc values, very high
exponential n factors were measured: n = 148, 89 and 17 at 3.5, 5 and 10T,
respectively and measurements of critical current versus applied strain have
been performed. The mechanism leading to high transport critical current
densities of filamentary Fe/MgB2 tapes based on MgB2 particles is discussed.Comment: Presented at ICMC 2003, 25-28 May 200
The U(1)A anomaly in noncommutative SU(N) theories
We work out the one-loop anomaly for noncommutative SU(N) gauge
theories up to second order in the noncommutative parameter .
We set and conclude that there is no breaking of the classical
symmetry of the theory coming from the contributions that are either
linear or quadratic in . Of course, the ordinary anomalous
contributions will be still with us. We also show that the one-loop
conservation of the nonsinglet currents holds at least up to second order in
. We adapt our results to noncommutative gauge theories with
SO(N) and U(1) gauge groups.Comment: 50 pages, 5 figures in eps files. Some comments and references adde
Vegetation Mapping of a Coastal Dune Complex Using Multispectral Imagery Acquired from an Unmanned Aerial System
Vegetation mapping, identifying the distribution of plant species, is important for analysing vegetation dynamics, quantifying spatial patterns of vegetation evolution, analysing the effects of environment changes on vegetation, and predicting spatial patterns of species diversity. Such analysis can contribute to the development of targeted land management actions that maintain biodiversity and ecological functions. This paper represents a methodology for 3D vegetation mapping of a coastal dune complex using a multispectral camera mounted on an Unmanned Aerial System (UAS) with particular reference to the Buckroney dune complex in Co. Wicklow, Ireland. UAS, also known as Unmanned Aerial Vehicles (UAV’s) or drones, have enabled high-resolution and high-accuracy ground-based data to be gathered quickly and easily on-site. The Sequoia multispectral camera used in this study has green, red, red-edge and near infrared wavebands, and a normal RGB camera, to capture both visible and NIR images of the land surface. The workflow of 3D vegetation mapping of the study site included establishing ground control points, planning the flight mission and camera parameters, acquiring the imagery, processing the image data and performing features classification. The data processing outcomes include an orthomosiac model, a 3D surface model and multispectral images of the study site, in the Irish Transverse Mercator coordinate system, with a planimetric resolution of 0.024m and a georeferenced Root-Mean-Square (RMS) error of 0.111m. There were 235 sample area (1m×1m) used for the accuracy assessment of the classification of the vegetation mapping. Feature classification was conducted using three different classification strategies to examine the efficiency of multispectral sensor data for vegetation mapping. Vegetation type classification accuracies ranged from 60% to 70%. This research illustrates the efficiency of data collection at Buckroney dune complex and the high-accuracy and high-resolution of the vegetation mapping of the site using a multispectral sensor mounted on UAS
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks
Predicting the future health information of patients from the historical
Electronic Health Records (EHR) is a core research task in the development of
personalized healthcare. Patient EHR data consist of sequences of visits over
time, where each visit contains multiple medical codes, including diagnosis,
medication, and procedure codes. The most important challenges for this task
are to model the temporality and high dimensionality of sequential EHR data and
to interpret the prediction results. Existing work solves this problem by
employing recurrent neural networks (RNNs) to model EHR data and utilizing
simple attention mechanism to interpret the results. However, RNN-based
approaches suffer from the problem that the performance of RNNs drops when the
length of sequences is large, and the relationships between subsequent visits
are ignored by current RNN-based approaches. To address these issues, we
propose {\sf Dipole}, an end-to-end, simple and robust model for predicting
patients' future health information. Dipole employs bidirectional recurrent
neural networks to remember all the information of both the past visits and the
future visits, and it introduces three attention mechanisms to measure the
relationships of different visits for the prediction. With the attention
mechanisms, Dipole can interpret the prediction results effectively. Dipole
also allows us to interpret the learned medical code representations which are
confirmed positively by medical experts. Experimental results on two real world
EHR datasets show that the proposed Dipole can significantly improve the
prediction accuracy compared with the state-of-the-art diagnosis prediction
approaches and provide clinically meaningful interpretation
Controlled formation and disappearance of creases
Soft, elastic materials are capable of large and reversible deformation, readily leading to various modes of instability that are often undesirable, but sometimes useful. For example, when a soft elastic material is compressed, its initially flat surface will suddenly form creases. While creases are commonly observed, and have been exploited to control chemical patterning, enzymatic activity, and adhesion of surfaces, the conditions for the formation and disappearance of creases have so far been poorly controlled. Here we show that a soft elastic bilayer can snap between the flat and creased states repeatedly, with hysteresis. The strains at which the creases form and disappear are highly reproducible, and are tunable over a large range, through variations in the level of pre-compression applied to the substrate and the relative thickness of the film. The introduction of bistable flat and creased states and hysteretic switching is an important step to enable applications of this type of instability.Engineering and Applied Science
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The role of substrate pre-stretch in post-wrinkling bifurcations
When a stiff film on a soft substrate is compressed, the surface of the film forms wrinkles, with tunable wavelengths and amplitudes that enable a variety of applications. As the compressive strain increases, the film undergoes post-wrinkling bifurcations, leading to period doubling and eventually to formation of localized folds or ridges. Here we study the post-wrinkling bifurcations in films on pre-stretched substrates. Through a combination of experiments and simulations, we demonstrate that pre-stretched substrates not only show substantial shifts in the critical strain for the onset of post-wrinkling bifurcations, but also exhibit qualitatively different post-wrinkled states. In particular, we report on the stabilization of wrinkles in films on pre-tensioned substrates and the emergence of ‘chaotic’ morphologies in films on pre-compressed substrates.Engineering and Applied Science
INSIGHT: A population-scale COVID-19 testing strategy combining point-of-care diagnosis with centralized high-throughput sequencing
We present INSIGHT [isothermal NASBA (nucleic acid sequence–based amplification) sequencing–based high-throughput test], a two-stage coronavirus disease 2019 testing strategy, using a barcoded isothermal NASBA reaction. It combines point-of-care diagnosis with next-generation sequencing, aiming to achieve population-scale testing. Stage 1 allows a quick decentralized readout for early isolation of presymptomatic or asymptomatic patients. It gives results within 1 to 2 hours, using either fluorescence detection or a lateral flow readout, while simultaneously incorporating sample-specific barcodes. The same reaction products from potentially hundreds of thousands of samples can then be pooled and used in a highly multiplexed sequencing–based assay in stage 2. This second stage confirms the near-patient testing results and facilitates centralized data collection. The 95% limit of detection is <50 copies of viral RNA per reaction. INSIGHT is suitable for further development into a rapid home-based, point-of-care assay and is potentially scalable to the population level
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