13,422 research outputs found
The Coronal Analysis of SHocks and Waves (CASHeW) Framework
Coronal Bright Fronts (CBF) are large-scale wavelike disturbances in the
solar corona, related to solar eruptions. They are observed in extreme
ultraviolet (EUV) light as transient bright fronts of finite width, propagating
away from the eruption source. Recent studies of individual solar eruptive
events have used EUV observations of CBFs and metric radio type II burst
observations to show the intimate connection between low coronal waves and
coronal mass ejection (CME)-driven shocks. EUV imaging with the Atmospheric
Imaging Assembly(AIA) instrument on the Solar Dynamics Observatory (SDO) has
proven particularly useful for detecting CBFs, which, combined with radio and
in situ observations, holds great promise for early CME-driven shock
characterization capability. This characterization can further be automated,
and related to models of particle acceleration to produce estimates of particle
fluxes in the corona and in the near Earth environment early in events. We
present a framework for the Coronal Analysis of SHocks and Waves (CASHeW). It
combines analysis of NASA Heliophysics System Observatory data products and
relevant data-driven models, into an automated system for the characterization
of off-limb coronal waves and shocks and the evaluation of their capability to
accelerate solar energetic particles (SEPs). The system utilizes EUV
observations and models written in the Interactive Data Language (IDL). In
addition, it leverages analysis tools from the SolarSoft package of libraries,
as well as third party libraries. We have tested the CASHeW framework on a
representative list of coronal bright front events. Here we present its
features, as well as initial results. With this framework, we hope to
contribute to the overall understanding of coronal shock waves, their
importance for energetic particle acceleration, as well as to the better
ability to forecast SEP events fluxes.Comment: Accepted for publication in the Journal of Space Weather and Space
Climate (SWSC
The Texas construction sector: the tail that wagged the dog
The boom-to-bust days of the Texas construction industry will linger in people's memory for many years. D'Ann Petersen, Keith Phillips, and Mine Yucel examine the factors that led to the rise and fall of the Texas construction industry and determine the role the industry played in the state's volatile economy during the 1970s and 1980s. ; Petersen, Phillips, and Yucel employ an econometric model to analyze the roles residential and nonresidential construction played in the state's economic fluctuations from 1976 through 1990. The authors find that, although large swings in oil prices were the greatest source of economic instability in the Texas economy, the construction sector also played an important and independent role in the changing fortunes of the state. The authors' results show that the homebuilding sector, in particular, had a large impact on the Texas economy. In addition, the authors find that the state's economy needs several years to adjust to shocks in the construction industry. Consequently, the current expansion in residential construction is likely to have positive economic effects in the years ahead.Construction industry ; Texas
Investigating the source of Planck-detected AME: high resolution observations at 15 GHz
The Planck 28.5 GHz maps were searched for potential Anomalous Microwave
Emission (AME) regions on the scale of or smaller, and several
new regions of interest were selected. Ancillary data at both lower and higher
frequencies were used to construct spectral energy distributions (SEDs), which
seem to confirm an excess consistent with spinning dust models. Here we present
higher resolution observations of two of these new regions with the Arcminute
Microkelvin Imager Small Array (AMI SA) between 14 and 18 GHz to test for the
presence of a compact (10 arcmin or smaller) component. For
AME-G107.1+5.2, dominated by the {\sc Hii} region S140, we find evidence for
the characteristic rising spectrum associated with the either the spinning dust
mechanism for AME or an ultra/hyper-compact \textsc{Hii} region across the AMI
frequency band, however for AME-G173.6+2.8 we find no evidence for AME on
scales of arcmin.Comment: 13 pages, 8 figures, 4 tables. Submitted to Advances in Astronomy AME
Special Issu
Benchmarking high fidelity single-shot readout of semiconductor qubits
Determination of qubit initialisation and measurement fidelity is important
for the overall performance of a quantum computer. However, the method by which
it is calculated in semiconductor qubits varies between experiments. In this
paper we present a full theoretical analysis of electronic single-shot readout
and describe critical parameters to achieve high fidelity readout. In
particular, we derive a model for energy selective state readout based on a
charge detector response and examine how to optimise the fidelity by choosing
correct experimental parameters. Although we focus on single electron spin
readout, the theory presented can be applied to other electronic readout
techniques in semiconductors that use a reservoir.Comment: 19 pages, 8 figure
Guidance on the use of the Mental Capacity Act for decisions regarding clinical treatment and care: An introduction
The Mental Capacity Act requirements when an individual lacks the mental capacity to consent to treatment and care
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An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data
As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations
Sequence fingerprints distinguish erroneous from correct predictions of Intrinsically Disordered Protein Regions
More than sixty prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the world-wide web. Nearly, all of these predictors give balanced accuracies in the ~65% to ~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally-determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm
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