58,442 research outputs found
State Taxation of Unitary Businesses
The income taxation of multistate businesses has created problems for tax administrators, primarily with regard to the question of how to divide the income taxation amongst the multiple states. To address this, the concepts of unitary business and formula apportionment have been created. However, the non-uniform state taxation practices create difficulties even with the existence of these concepts. Some states have adopted the Multistate Tax Compact, but for it to be completely effective there still must be a uniform view adopted on what constitutes a unitary business. This note examines the constitutional issues attendant to developing a standard definition of a unitary business, an in-depth analysis of the unitary business concept and its origins, and proposes a workable definition of a unitary business
Efficient independent component analysis
Independent component analysis (ICA) has been widely used for blind source
separation in many fields such as brain imaging analysis, signal processing and
telecommunication. Many statistical techniques based on M-estimates have been
proposed for estimating the mixing matrix. Recently, several nonparametric
methods have been developed, but in-depth analysis of asymptotic efficiency has
not been available. We analyze ICA using semiparametric theories and propose a
straightforward estimate based on the efficient score function by using
B-spline approximations. The estimate is asymptotically efficient under
moderate conditions and exhibits better performance than standard ICA methods
in a variety of simulations.Comment: Published at http://dx.doi.org/10.1214/009053606000000939 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
In vivo therapeutic efficacy of frog skin-derived peptides against Pseudomonas aeruginosa-induced pulmonary infection
Pseudomonas aeruginosa is an opportunistic and frequently drug-resistant pulmonary pathogen especially in cystic fibrosis sufferers. Recently, the frog skin-derived antimicrobial peptide (AMP) Esc(1-21) and its diastereomer Esc(1-21)-1c were found to possess potent in vitro antipseudomonal activity. Here, they were first shown to preserve the barrier integrity of airway epithelial cells better than the human AMP LL-37. Furthermore, Esc(1-21)-1c was more efficacious than Esc(1-21) and LL-37 in protecting host from pulmonary bacterial infection after a single intra-tracheal instillation at a very low dosage of 0.1 mg/kg. The protection was evidenced by 2-log reduction of lung bacterial burden and was accompanied by less leukocytes recruitment and attenuated inflammatory response. In addition, the diastereomer was more efficient in reducing the systemic dissemination of bacterial cells. Importantly, in contrast to what reported for other AMPs, the peptide was administered at 2 hours after bacterial challenge to better reflect the real life infectious conditions. To the best of our knowledge, this is also the first study investigating the effect of AMPs on airway-epithelia associated genes upon administration to infected lungs. Overall, our data highly support advanced preclinical studies for the development of Esc(1-21)-1c as an efficacious therapeutic alternative against pulmonary P. aeruginosa infection
Understanding Compressive Adversarial Privacy
Designing a data sharing mechanism without sacrificing too much privacy can
be considered as a game between data holders and malicious attackers. This
paper describes a compressive adversarial privacy framework that captures the
trade-off between the data privacy and utility. We characterize the optimal
data releasing mechanism through convex optimization when assuming that both
the data holder and attacker can only modify the data using linear
transformations. We then build a more realistic data releasing mechanism that
can rely on a nonlinear compression model while the attacker uses a neural
network. We demonstrate in a series of empirical applications that this
framework, consisting of compressive adversarial privacy, can preserve
sensitive information
On Logarithmically Benford Sequences
Let be an infinite subset, and let
be a sequence of nonzero real numbers indexed by
such that there exist positive constants for which
for all . Furthermore, let be defined by for each , and suppose the 's are equidistributed in with
respect to a continuous, symmetric probability measure . In this paper, we
show that if is not too sparse, then the
sequence fails to obey Benford's Law with respect
to arithmetic density in any sufficiently large base, and in fact in any base
when is a strictly convex function of . Nonetheless,
we also provide conditions on the density of
under which the sequence satisfies Benford's Law
with respect to logarithmic density in every base.
As an application, we apply our general result to study Benford's Law-type
behavior in the leading digits of Frobenius traces of newforms of positive,
even weight. Our methods of proof build on the work of Jameson, Thorner, and
Ye, who studied the particular case of newforms without complex multiplication.Comment: 10 page
Spatial Correlation in Matter Wave Interference as a Measure of Decoherence, Dephasing and Entropy
The loss of contrast in double-slit electron-diffraction due to dephasing and
decoherence processes is studied. It is shown that the spatial correlation
function of diffraction patterns can be used to distinguish between dephasing
and decoherence. This establishes a measure of time-reversibility that does not
require the determination of coherence terms of the density matrix, while von
Neumann entropy, another measure of time-reversibility, does require coherence
terms. This technique is exciting in view of the need to understand and control
the detrimental experimental effects of contrast loss and for fundamental
studies on the transition from the classical to the quantum regime.Comment: 14 pages, 6 figures, submitted to Physical Review
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