206 research outputs found
A new perspective on GCRT J1745-3009
Two WSRT observations were performed and five archival VLA data were reduced
in order to redetect the enigmatic radio transient GCRT J1745-3009. The source
was not redetected. We were, however, able to extract important new information
from the discovery dataset. Our reanalysis excludes models that predict
symmetric bursts, but the transient white dwarf pulsar is favoured. Although we
now have more contraints on the properties of this source, we are still unsure
about its basic model.Comment: 11 pages, 5 figure
In vitro digestibility and Caco-2 cell bioavailability of sea lettuce (Ulva fenestrata) proteins extracted using pH-shift processing
Seaweed is a promising sustainable source of vegan protein as its farming does not require arable land, pesticides/insecticides, nor freshwater supply. However, to be explored as a novel protein source the content and nutritional quality of protein in seaweed need to be improved. We assessed the influence of pH-shift processing on protein degree of hydrolysis (%DH), protein/peptide size distribution, accessibility, and cell bioavailability of Ulva fenestrata proteins after in vitro gastrointestinal digestion. pH-shift processing of Ulva, which concentrated its proteins 3.5-times, significantly improved the %DH from 27.7\ub12.6% to 35.7\ub12.1% and the amino acid accessibility from 56.9\ub14.1% to 72.7\ub10.6%. Due to the higher amino acid accessibility, the amount of most amino acids transported across the cell monolayers was higher in the protein extracts. Regarding bioavailability, both Ulva and protein extracts were as bioavailable as casein. The protein/peptide molecular size distribution after digestion did not disclose a clear association with bioavailability
Detailed study of the GRB 030329 radio afterglow deep into the non-relativistic phase
We explore the physics behind one of the brightest radio afterglows ever, GRB
030329, at late times when the jet is non-relativistic. We determine the
physical parameters of the blast wave and its surroundings, in particular the
index of the electron energy distribution, the energy of the blast wave, and
the density (structure) of the circumburst medium. We then compare our results
with those from image size measurements. We observed the GRB 030329 radio
afterglow with the Westerbork Synthesis Radio Telescope and the Giant Metrewave
Radio Telescope at frequencies from 325 MHz to 8.4 GHz, spanning a time range
of 268-1128 days after the burst. We modeled all the available radio data and
derived the physical parameters. The index of the electron energy distribution
is p=2.1, the circumburst medium is homogeneous, and the transition to the
non-relativistic phase happens at t_NR ~ 80 days. The energy of the blast wave
and density of the surrounding medium are comparable to previous findings. Our
findings indicate that the blast wave is roughly spherical at t_NR, and they
agree with the implications from the VLBI studies of image size evolution. It
is not clear from the presented dataset whether we have seen emission from the
counter jet or not. We predict that the Low Frequency Array will be able to
observe the afterglow of GRB 030329 and many other radio afterglows,
constraining the physics of the blast wave during its non-relativistic phase
even further.Comment: 9 pages, 2 figures; accepted for publication in Astronomy &
Astrophysics after minor revisions; small changes in GMRT fluxes at 1280 MH
An automated archival VLA transients survey
In this paper we present the results of a survey for radio transients using
data obtained from the Very Large Array archive. We have reduced, using a
pipeline procedure, 5037 observations of the most common pointings - i.e. the
calibrator fields. These fields typically contain a relatively bright point
source and are used to calibrate `target' observations: they are therefore
rarely imaged themselves. The observations used span a time range ~ 1984 - 2008
and consist of eight different pointings, three different frequencies (8.4, 4.8
and 1.4 GHz) and have a total observing time of 435 hours. We have searched for
transient and variable radio sources within these observations using components
from the prototype LOFAR transient detection system. In this paper we present
the methodology for reducing large volumes of Very Large Array data; and we
also present a brief overview of the prototype LOFAR transient detection
algorithms. No radio transients were detected in this survey, therefore we
place an upper limit on the snapshot rate of GHz frequency transients > 8.0 mJy
to rho less than or equal to 0.032 deg^-2 that have typical timescales 4.3 to
45.3 days. We compare and contrast our upper limit with the snapshot rates -
derived from either detections or non-detections of transient and variable
radio sources - reported in the literature. When compared with the current Log
N - Log S distribution formed from previous surveys, we show that our upper
limit is consistent with the observed population. Current and future radio
transient surveys will hopefully further constrain these statistics, and
potentially discover dominant transient source populations. In this paper we
also briefly explore the current transient commissioning observations with
LOFAR, and the impact they will make on the field.Comment: Accepted for publication in MNRA
LOFAR MSSS:detection of a low-frequency radio transient in 400 h of monitoring of the North Celestial Pole
Identifying transient and variable sources in radio images
With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the information stored in the images are being developed, such as the LOFAR Transients Pipeline, outputting light curves and various transient parameters. These pipelines have a number of tuneable parameters that require training to meet the survey requirements. This paper utilises both observed and simulated datasets to demonstrate different machine learning strategies that can be used to train these parameters. We use a simple anomaly detection algorithm and a penalised logistic regression algorithm. The datasets used are from LOFAR observations and we process the data using the LOFAR Transients Pipeline; however the strategies developed are applicable to any light curve datasets at different frequencies and can be adapted to different automated pipelines. These machine learning strategies are publicly available as PYTHON tools that can be downloaded and adapted to different datasets (https://github.com/AntoniaR/TraP_ML_tools)
MeerCRAB: MeerLICHT classification of real and bogus transients using deep learning
Instrumentatio
- …