17,627 research outputs found
The influence of the cluster environment on the star formation efficiency of 12 Virgo spiral galaxies
The influence of the environment on gas surface density and star formation
efficiency of cluster spiral galaxies is investigated. We extend previous work
on radial profiles by a pixel-to pixel analysis looking for asymmetries due to
environmental interactions. The star formation rate is derived from GALEX UV
and Spitzer total infrared data. As in field galaxies, the star formation rate
for most Virgo galaxies is approximately proportional to the molecular gas
mass. Except for NGC 4438, the cluster environment does not affect the star
formation efficiency with respect to the molecular gas. Gas truncation is not
associated with major changes in the total gas surface density distribution of
the inner disk of Virgo spiral galaxies. In three galaxies, possible increases
in the molecular fraction and the star formation efficiency with respect to the
total gas, of factors of 1.5 to 2, are observed on the windward side of the
galactic disk. A significant increase of the star formation efficiency with
respect to the molecular gas content on the windward side of ram
pressure-stripped galaxies is not observed. The ram-pressure stripped
extraplanar gas of 3 highly inclined spiral galaxies shows a depressed star
formation efficiency with respect to the total gas, and one of them (NGC 4438)
shows a depressed rate even with respect to the molecular gas. The
interpretation is that stripped gas loses the gravitational confinement and
associated pressure of the galactic disk, and the gas flow is diverging, so the
gas density decreases and the star formation rate drops. However, the stripped
extraplanar gas in one highly inclined galaxy (NGC 4569) shows a normal star
formation efficiency with respect to the total gas. We propose this galaxy is
different because it is observed long after peak pressure, and its extraplanar
gas is now in a converging flow as it resettles back into the disk.Comment: 34 pages, 24 figures, accepted for publication by A&
Personalized Pancreatic Tumor Growth Prediction via Group Learning
Tumor growth prediction, a highly challenging task, has long been viewed as a
mathematical modeling problem, where the tumor growth pattern is personalized
based on imaging and clinical data of a target patient. Though mathematical
models yield promising results, their prediction accuracy may be limited by the
absence of population trend data and personalized clinical characteristics. In
this paper, we propose a statistical group learning approach to predict the
tumor growth pattern that incorporates both the population trend and
personalized data, in order to discover high-level features from multimodal
imaging data. A deep convolutional neural network approach is developed to
model the voxel-wise spatio-temporal tumor progression. The deep features are
combined with the time intervals and the clinical factors to feed a process of
feature selection. Our predictive model is pretrained on a group data set and
personalized on the target patient data to estimate the future spatio-temporal
progression of the patient's tumor. Multimodal imaging data at multiple time
points are used in the learning, personalization and inference stages. Our
method achieves a Dice coefficient of 86.8% +- 3.6% and RVD of 7.9% +- 5.4% on
a pancreatic tumor data set, outperforming the DSC of 84.4% +- 4.0% and RVD
13.9% +- 9.8% obtained by a previous state-of-the-art model-based method
Radio Galaxy Zoo: Cosmological Alignment of Radio Sources
We study the mutual alignment of radio sources within two surveys, FIRST and
TGSS. This is done by producing two position angle catalogues containing the
preferential directions of respectively and extended
sources distributed over more than and square degrees. The
identification of the sources in the FIRST sample was performed in advance by
volunteers of the Radio Galaxy Zoo project, while for the TGSS sample it is the
result of an automated process presented here. After taking into account
systematic effects, marginal evidence of a local alignment on scales smaller
than is found in the FIRST sample. The probability of this happening
by chance is found to be less than per cent. Further study suggests that on
scales up to the alignment is maximal. For one third of the sources,
the Radio Galaxy Zoo volunteers identified an optical counterpart. Assuming a
flat CDM cosmology with , we
convert the maximum angular scale on which alignment is seen into a physical
scale in the range Mpc . This result supports recent
evidence reported by Taylor and Jagannathan of radio jet alignment in the
deg ELAIS N1 field observed with the Giant Metrewave Radio Telescope. The
TGSS sample is found to be too sparsely populated to manifest a similar signal
H I-deficient galaxies in intermediate-density environments
Observations show that spiral galaxies in galaxy clusters tend to have on average less neutral hydrogen (H I) than galaxies of the same type and size in the field. There is accumulating evidence that such H I-deficient galaxies are also relatively frequent in galaxy groups. An important question is that which mechanisms are responsible for the gas deficiency in galaxy groups. To gain a better understanding of how environment affects the gas content of galaxies, we identified a sample of six H I-deficient galaxies from the H I Parkes All Sky Survey (HIPASS) using H I-optical scaling relations. One of the galaxies is located in the outskirts of the Fornax cluster, four are in loose galaxy groups and one is in a galaxy triplet. We present new high-resolution H I observations with the Australia Telescope Compact Array (ATCA) of these galaxies. We discuss the possible cause of H I-deficiency in the sample based on H I observations and various multi-wavelength data. We find that the galaxies have truncated H I discs, lopsided gas distribution and some show asymmetries in their stellar discs. We conclude that both ram-pressure stripping and tidal interactions are important gas removal mechanisms in low-density environments
Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-Organising Maps
With the advent of large scale surveys the manual analysis and classification
of individual radio source morphologies is rendered impossible as existing
approaches do not scale. The analysis of complex morphological features in the
spatial domain is a particularly important task. Here we discuss the challenges
of transferring crowdsourced labels obtained from the Radio Galaxy Zoo project
and introduce a proper transfer mechanism via quantile random forest
regression. By using parallelized rotation and flipping invariant Kohonen-maps,
image cubes of Radio Galaxy Zoo selected galaxies formed from the FIRST radio
continuum and WISE infrared all sky surveys are first projected down to a
two-dimensional embedding in an unsupervised way. This embedding can be seen as
a discretised space of shapes with the coordinates reflecting morphological
features as expressed by the automatically derived prototypes. We find that
these prototypes have reconstructed physically meaningful processes across two
channel images at radio and infrared wavelengths in an unsupervised manner. In
the second step, images are compared with those prototypes to create a
heat-map, which is the morphological fingerprint of each object and the basis
for transferring the user generated labels. These heat-maps have reduced the
feature space by a factor of 248 and are able to be used as the basis for
subsequent ML methods. Using an ensemble of decision trees we achieve upwards
of 85.7% and 80.7% accuracy when predicting the number of components and peaks
in an image, respectively, using these heat-maps. We also question the
currently used discrete classification schema and introduce a continuous scale
that better reflects the uncertainty in transition between two classes, caused
by sensitivity and resolution limits
NGC922 – a new drop-through ring galaxy
We have found the peculiar galaxy NGC 922 to be a new drop-through ring galaxy using multiwavelength (ultraviolet–radio) imaging and spectroscopic observations. Its ‘C’-shaped morphology and tidal plume indicate a recent strong interaction with its companion which was identified with these observations. Using numerical simulations we demonstrate that the main properties of the system can be generated by a high-speed off-axis drop-through collision of a small galaxy with a larger disc system, thus making NGC 922 one of the nearest known collisional ring galaxies. While these systems are rare in the local Universe, recent deep Hubble Space Telescope images suggest they were more common in the early Universe
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