14,967 research outputs found
Large Margin Multiclass Gaussian Classification with Differential Privacy
As increasing amounts of sensitive personal information is aggregated into
data repositories, it has become important to develop mechanisms for processing
the data without revealing information about individual data instances. The
differential privacy model provides a framework for the development and
theoretical analysis of such mechanisms. In this paper, we propose an algorithm
for learning a discriminatively trained multi-class Gaussian classifier that
satisfies differential privacy using a large margin loss function with a
perturbed regularization term. We present a theoretical upper bound on the
excess risk of the classifier introduced by the perturbation.Comment: 14 page
Nuclear fusion as a probe for octupole deformation in Ra
: Nuclear fusion has been shown to be a perfect probe to
study the different nuclear shapes. However, the possibility of testing
octupole deformation of a nucleus with this tool has not been fully explored
yet. The presence of a stactic octupole deformation in nuclei will enhanced a
possible permanent electric dipole moment, leading to a possible demonstration
of parity violation.
: To check whether static octupole deformation or octupole
vibration in fusion give qualitatively different results so that both
situations can be experimentally disentangled.
: Fusion cross sections are computed in the Coupled-Channels
formalism making use of the Ingoing-Wave Boundary Conditions (IWBC) for the
systems O+Ba and O+Ra.
: Barrier distributions of the two considered schemes show
different patterns. For the Ra case, the octupole deformation parameter
is large enough to create a sizeable difference.
: The measurement of barrier distributions can be an
excellent probe to clarify the presence of octupole deformation.Comment: Important changes from previous version, 6 pages, 5 figures, 2
tables, submitted to Phys. Rev.
Current Status of Defensins and Their Role in Innate and Adaptive Immunity
Naturally occurring antimicrobial cationic polypeptides play a major role in innate and adaptive immunity. These polypeptides are found to be either linear and unstructured or structured through disulfide bonds. Among the structured antimicrobial polypeptides, defensins comprise a family of cysteine-rich cationic polypeptides that contribute significantly to host defense against the invasion of microorganisms in animals, humans, insects and plants. Their wide-spread occurrence in various tissues of these diverse organisms, and their importance in innate and adaptive immunity have led to their identification, isolation and characterization. A large volume of literature is available on defensins’ occurrence, structural characterization, gene expression and regulation under normal and pathological conditions. Much has also been published regarding their antimicrobial, antiviral and chemoattractive properties, and their molecular and cellular interactions. In this review, we describe the current status of our knowledge of defensins with respect to their molecular, cellular and structural biology, their role in host defense, future research paradigms and the possibility of their utilization as a new class of non-toxic antimicrobial agents and immuno-modulators
Inferring Room Semantics Using Acoustic Monitoring
Having knowledge of the environmental context of the user i.e. the knowledge
of the users' indoor location and the semantics of their environment, can
facilitate the development of many of location-aware applications. In this
paper, we propose an acoustic monitoring technique that infers semantic
knowledge about an indoor space \emph{over time,} using audio recordings from
it. Our technique uses the impulse response of these spaces as well as the
ambient sounds produced in them in order to determine a semantic label for
them. As we process more recordings, we update our \emph{confidence} in the
assigned label. We evaluate our technique on a dataset of single-speaker human
speech recordings obtained in different types of rooms at three university
buildings. In our evaluation, the confidence\emph{ }for the true label
generally outstripped the confidence for all other labels and in some cases
converged to 100\% with less than 30 samples.Comment: 2017 IEEE International Workshop on Machine Learning for Signal
Processing, Sept.\ 25--28, 2017, Tokyo, Japa
Steady State Analysis and Heavy Traffic Limits for Regulated Markov Chains.
Consider a continuous time finite state irreducible Markov chain whose jump transitions are partitioned into one group that is regulated and the other group that is not. The regulated transitions are only allowed to occur if there is a token available. We collect the tokens in a buer and allow a regulated transition to occur simultaneously with the removal of a token from the buffer. New tokens are added to the buer at a constant Poisson rate but the regulated transitions will be blocked if they occur too quickly. We will apply matrix analysis to the joint distribution for the state of the Markov chain and the number of tokens in the buffer. We will give a simple stability condition for the joint process and show that its steady state distribution will have a matrix geometric distribution. Moreover, we obtain from our analysis a heavy traffic limit for this joint steady state distribution which has a product form structure. This Markov chain model and steady state analysis generalizes the work of many earlier papers on specific queueing systems such as Konheim and Reiser or Latouche and Neuts, but most significantly the work of Kogan and Puhalskii.Markov Chains, Matrix-Geometric Solution, Heavy-Traffic Limits, Product Form Solution, Tensor and Kronecker Products.
Large-scale Synthesis and Functional Elements for the Antimicrobial Activity of Defensins
Human neutrophil defensins, and their analogues incorporating anionic, hydrophobic or cationic residues at the N- and C-termini, were synthesized by solid-phase procedures. The synthetic defensins were examined for their microbicidal activity against Candida albicans, two Gram-negative bacteria (Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis) and two Gram-positive bacteria (Streptococcus gordonii and Streptococcus mutans). The human neutrophil peptide 1 (HNP1) and HNP2 were found to be potent candidacidal agents. HNP3, which differs by one amino acid at the N-terminus of its sequence, was totally inactive. The Gram-negative bacteria A. actinomycetemcomitans and P. gingivalis and the Gram-positive bacteria S. gordonii and S. mutans were insensitive to human defensins. However, the insertion of two basic residues, such as arginine, at both the N-terminus and the C-terminus of HNP2 significantly enhanced antifungal and antibacterial activity. The addition of anionic residues, such as aspartic acid, at the N- and C-termini rendered the molecule totally inactive. The presence of two hydrophobic amino acids, such as valine, at the N-terminus of HNP2 and of two basic arginine residues at its C-terminus resulted in molecules that were optimally active against these oral pathogens. The results suggest that the N- and C-terminal residues in defensin peptides are the crucial functional elements that determine their microbicidal potency. The three-dimensional structure of all defensins constitutes the same amphiphilic beta-sheet structure, with the polar face formed by the N- and C-terminal residues playing an important role in defining microbicidal potency and the antimicrobial spectrum. The enhanced microbicidal activity observed for defensin peptides with two basic residues at both the N- and C-termini could be due to optimization of the amphiphilicity of the structure, which could facilitate specific interactions with the microbial membranes
PUBLIC AND PRIVATE FOOD ASSISTANCE CHOICES OF FOOD NEEDY FAMILIES
A bivariate probit model was used to determine public and private food assistance participation among the population below 125 percent poverty level, using the Current Population Survey data. Food stamp use and food pantry use were complements. Household income, food insecurity status, household structure, and rural residence affected participation decisions.Food Security and Poverty,
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