155 research outputs found
Stock Dividends as Income
In the case of Towne v. Eisner, the United States Supreme Court has recently held that under the Income Tax Law of 1913, the stock dividends received by a shareholder during the year 1914 could not be taxed upon their full par value, where the corporate surplus thus distributed all accrued prior to January I, 1913. The Treasury Department subsequently announced that the decision is not applicable to the Income Tax Law of 1916.1 It is the purpose of this article to review the case of Towvne v. Eisner,2 and then to discuss the soundness of the position taken by the Secretary of the Treasury. Thus two general questions are presented. The first is, Can the decision of the Supreme Court in the Towne Case be upheld? The second is, Is that section of the Income Tax Law of 1916 that states that stock dividends are income and taxable, constitutional? These questions will be dealt with in orde
Space Warps II. New Gravitational Lens Candidates from the CFHTLS Discovered through Citizen Science
We report the discovery of 29 promising (and 59 total) new lens candidates
from the CFHT Legacy Survey (CFHTLS) based on about 11 million classifications
performed by citizen scientists as part of the first Space Warps lens search.
The goal of the blind lens search was to identify lens candidates missed by
robots (the RingFinder on galaxy scales and ArcFinder on group/cluster scales)
which had been previously used to mine the CFHTLS for lenses. We compare some
properties of the samples detected by these algorithms to the Space Warps
sample and find them to be broadly similar. The image separation distribution
calculated from the Space Warps sample shows that previous constraints on the
average density profile of lens galaxies are robust. SpaceWarps recovers about
65% of known lenses, while the new candidates show a richer variety compared to
those found by the two robots. This detection rate could be increased to 80% by
only using classifications performed by expert volunteers (albeit at the cost
of a lower purity), indicating that the training and performance calibration of
the citizen scientists is very important for the success of Space Warps. In
this work we present the SIMCT pipeline, used for generating in situ a sample
of realistic simulated lensed images. This training sample, along with the
false positives identified during the search, has a legacy value for testing
future lens finding algorithms. We make the pipeline and the training set
publicly available.Comment: 23 pages, 12 figures, MNRAS accepted, minor to moderate changes in
this versio
Space Warps: I. Crowd-sourcing the Discovery of Gravitational Lenses
We describe Space Warps, a novel gravitational lens discovery service that
yields samples of high purity and completeness through crowd-sourced visual
inspection. Carefully produced colour composite images are displayed to
volunteers via a web- based classification interface, which records their
estimates of the positions of candidate lensed features. Images of simulated
lenses, as well as real images which lack lenses, are inserted into the image
stream at random intervals; this training set is used to give the volunteers
instantaneous feedback on their performance, as well as to calibrate a model of
the system that provides dynamical updates to the probability that a classified
image contains a lens. Low probability systems are retired from the site
periodically, concentrating the sample towards a set of lens candidates. Having
divided 160 square degrees of Canada-France-Hawaii Telescope Legacy Survey
(CFHTLS) imaging into some 430,000 overlapping 82 by 82 arcsecond tiles and
displaying them on the site, we were joined by around 37,000 volunteers who
contributed 11 million image classifications over the course of 8 months. This
Stage 1 search reduced the sample to 3381 images containing candidates; these
were then refined in Stage 2 to yield a sample that we expect to be over 90%
complete and 30% pure, based on our analysis of the volunteers performance on
training images. We comment on the scalability of the SpaceWarps system to the
wide field survey era, based on our projection that searches of 10 images
could be performed by a crowd of 10 volunteers in 6 days.Comment: 21 pages, 13 figures, MNRAS accepted, minor to moderate changes in
this versio
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