Properties of dust in early-type galaxies

We report optical extinction properties of dust for a sample of 26 early-type galaxies based on the analysis of their multicolour CCD observations. The wavelength dependence of dust extinction for these galaxies is determined and the extinction curves are found to run parallel to the Galactic extinction curve, which implies that the properties of dust in the extragalactic environment are quite similar to those of the Milky Way. For the sample galaxies, value of the parameter $R_V$, the ratio of total extinction in $V$ band to selective extinction in $B$ & $V$ bands, lies in the range 2.03 - 3.46 with an average of 3.02, compared to its canonical value of 3.1 for the Milky Way. A dependence of $R_V$ on dust morphology of the host galaxy is also noticed in the sense that galaxies with a well defined dust lane show tendency to have smaller $R_V$ values compared to the galaxies with disturbed dust morphology. The dust content of these galaxies estimated using total optical extinction is found to lie in the range $10^4$ to 10^6 \rm M_{\sun}, an order of magnitude smaller than those derived from IRAS flux densities, indicating that a significant fraction of dust intermixed with stars remains undetected by the optical method. We examine the relationship between dust mass derived from IRAS flux and the X-ray luminosity of the host galaxies.The issue of the origin of dust in early-type galaxies is also discussed.Comment: 12 pages, 6 figures. Accepted for publication in Astronomy & Astrophysic

A deep level set method for image segmentation

This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types of medical imaging data (liver CT and left ven-tricle MRI data), we show that the integrated method achieves goodperformance even when little training data is available, outperformingthe FCN or the level set model alone

Tversky loss function for image segmentation using 3D fully convolutional deep networks

Fully convolutional deep neural networks carry out excellent potential for fast and accurate image segmentation. One of the main challenges in training these networks is data imbalance, which is particularly problematic in medical imaging applications such as lesion segmentation where the number of lesion voxels is often much lower than the number of non-lesion voxels. Training with unbalanced data can lead to predictions that are severely biased towards high precision but low recall (sensitivity), which is undesired especially in medical applications where false negatives are much less tolerable than false positives. Several methods have been proposed to deal with this problem including balanced sampling, two step training, sample re-weighting, and similarity loss functions. In this paper, we propose a generalized loss function based on the Tversky index to address the issue of data imbalance and achieve much better trade-off between precision and recall in training 3D fully convolutional deep neural networks. Experimental results in multiple sclerosis lesion segmentation on magnetic resonance images show improved F2 score, Dice coefficient, and the area under the precision-recall curve in test data. Based on these results we suggest Tversky loss function as a generalized framework to effectively train deep neural networks

The polar ring galaxy AM1934-563 revisited

We report long-slit spectroscopic observations of the dust-lane polar-ring galaxy AM1934-563 obtained with the Southern African Large Telescope (SALT) during its performance-verification phase. The observations target the spectral region of the Ha, [NII] and [SII] emission-lines, but show also deep NaI stellar absorption lines that we interpret as produced by stars in the galaxy. We derive rotation curves along the major axis of the galaxy that extend out to about 8 kpc from the center for both the gaseous and the stellar components, using the emission and absorption lines. We derive similar rotation curves along the major axis of the polar ring and point out differences between these and the ones of the main galaxy. We identify a small diffuse object visible only in Ha emission and with a low velocity dispersion as a dwarf HII galaxy and argue that it is probably metal-poor. Its velocity indicates that it is a fourth member of the galaxy group in which AM1934-563 belongs. We discuss the observations in the context of the proposal that the object is the result of a major merger and point out some observational discrepancies from this explanation. We argue that an alternative scenario that could better fit the observations may be the slow accretion of cold intergalactic gas, focused by a dense filament of galaxies in which this object is embedded (abridged).Comment: 19 pages, 13 figures, submitted to MNRAS. Some figures were bitmapped to reduce the size. Full resolution version is available from http://www.saao.ac.za/~akniazev/pub/AM1934_563.pd

Modeling of the Super-Eddington Phase for Classical Novae: Five IUE Novae

We present a light curve model for the super-Eddington luminosity phase of five classical novae observed with IUE. Optical and UV light curves are calculated based on the optically thick wind theory with a reduced effective opacity for a porous atmosphere. Fitting a model light curve with the UV 1455 \AA light curve, we determine the white dwarf mass and distance to be (1.3 M_sun, 4.4 kpc) for V693 CrA, (1.05 M_sun, 1.8 kpc) for V1974 Cyg, (0.95 M_sun, 4.1 kpc) for V1668 Cyg, (1.0 M_sun, 2.1 kpc) for V351 Pup, and (1.0 M_sun, 4.3 kpc) for OS And.Comment: 9 pages including 8 figures, to appear in the Astrophysical Journa

Automated Model Merge by Design Space Exploration

Industrial applications of model-driven engineering to develop large and complex systems resulted in an increasing demand for collaboration features. However, use cases such as model differencing and merging have turned out to be a difficult challenge, due to (i) the graph-like nature of models, and (ii) the complexity of certain operations (e.g. hierarchy refactoring) that are common today. In the paper, we present a novel search-based automated model merge approach where rule-based design space exploration is used to search the space of solution candidates that represent conflict-free merged models. Our method also allows engineers to easily incorporate domain-specific knowledge into the merge process to provide better solutions. The merge process automatically calculates multiple merge candidates to be presented to domain experts for final selection. Furthermore, we propose to adopt a generic synthetic benchmark to carry out an initial scalability assessment for model merge with large models and large change sets

Galaxy Candidates in the Zone of Avoidance

Motivated by recent discoveries of nearby galaxies in the Zone of Avoidance, we conducted a pilot study of galaxy candidates at low Galactic latitude, near Galactic longitude $l \sim 135^0$, where the Supergalactic Plane is crossed by the Galactic Plane. We observed with the 1m Wise Observatory in the I-band 18 of the `promising' candidates identified by visual examination of Palomar red plates by Hau et al. (1995). A few candidates were also observed in R or B bands, or had spectroscopic observations performed at the Isaac Newton Telescope and at the Wise Observatory. Our study suggests that there are probably 10 galaxies in this sample. We also identify a probable Planetary Nebula. The final confirmation of the nature of these sources must await the availability of full spectroscopic information. The success rate of $\sim 50$ in identifying galaxies at Galactic latitude $|b|<5^\circ$ indicates that the ZOA is a bountiful region to discover new galaxies.Comment: 11 pages; Latex + 5 figures (gif format), Submitted to MNRA