2,084 research outputs found
An approximation scheme for an Eikonal Equation with discontinuous coefficient
We consider the stationary Hamilton-Jacobi equation where the dynamics can
vanish at some points, the cost function is strictly positive and is allowed to
be discontinuous. More precisely, we consider special class of discontinuities
for which the notion of viscosity solution is well-suited. We propose a
semi-Lagrangian scheme for the numerical approximation of the viscosity
solution in the sense of Ishii and we study its properties. We also prove an
a-priori error estimate for the scheme in an integral norm. The last section
contains some applications to control and image processing problems
Dynamics of Social Balance on Networks
We study the evolution of social networks that contain both friendly and
unfriendly pairwise links between individual nodes. The network is endowed with
dynamics in which the sense of a link in an imbalanced triad--a triangular loop
with 1 or 3 unfriendly links--is reversed to make the triad balanced. With this
dynamics, an infinite network undergoes a dynamic phase transition from a
steady state to "paradise"--all links are friendly--as the propensity p for
friendly links in an update event passes through 1/2. A finite network always
falls into a socially-balanced absorbing state where no imbalanced triads
remain. If the additional constraint that the number of imbalanced triads in
the network does not increase in an update is imposed, then the network quickly
reaches a balanced final state.Comment: 10 pages, 7 figures, 2-column revtex4 forma
An MPEG-7 scheme for semantic content modelling and filtering of digital video
Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users
The Endogenous Th17 Response in NO<inf>2</inf>-Promoted Allergic Airway Disease Is Dispensable for Airway Hyperresponsiveness and Distinct from Th17 Adoptive Transfer
Severe, glucocorticoid-resistant asthma comprises 5-7% of patients with asthma. IL-17 is a biomarker of severe asthma, and the adoptive transfer of Th17 cells in mice is sufficient to induce glucocorticoid-resistant allergic airway disease. Nitrogen dioxide (NO2) is an environmental toxin that correlates with asthma severity, exacerbation, and risk of adverse outcomes. Mice that are allergically sensitized to the antigen ovalbumin by exposure to NO2 exhibit a mixed Th2/Th17 adaptive immune response and eosinophil and neutrophil recruitment to the airway following antigen challenge, a phenotype reminiscent of severe clinical asthma. Because IL-1 receptor (IL-1R) signaling is critical in the generation of the Th17 response in vivo, we hypothesized that the IL-1R/Th17 axis contributes to pulmonary inflammation and airway hyperresponsiveness (AHR) in NO2-promoted allergic airway disease and manifests in glucocorticoid-resistant cytokine production. IL-17A neutralization at the time of antigen challenge or genetic deficiency in IL-1R resulted in decreased neutrophil recruitment to the airway following antigen challenge but did not protect against the development of AHR. Instead, IL-1R-/- mice developed exacerbated AHR compared to WT mice. Lung cells from NO2-allergically inflamed mice that were treated in vitro with dexamethasone (Dex) during antigen restimulation exhibited reduced Th17 cytokine production, whereas Th17 cytokine production by lung cells from recipient mice of in vitro Th17-polarized OTII T-cells was resistant to Dex. These results demonstrate that the IL-1R/Th17 axis does not contribute to AHR development in NO2-promoted allergic airway disease, that Th17 adoptive transfer does not necessarily reflect an endogenously-generated Th17 response, and that functions of Th17 responses are contingent on the experimental conditions in which they are generated. © 2013 Martin et al
Design and Initial Performance of the Askaryan Radio Array Prototype EeV Neutrino Detector at the South Pole
We report on studies of the viability and sensitivity of the Askaryan Radio
Array (ARA), a new initiative to develop a Teraton-scale ultra-high energy
neutrino detector in deep, radio-transparent ice near Amundsen-Scott station at
the South Pole. An initial prototype ARA detector system was installed in
January 2011, and has been operating continuously since then. We report on
studies of the background radio noise levels, the radio clarity of the ice, and
the estimated sensitivity of the planned ARA array given these results, based
on the first five months of operation. Anthropogenic radio interference in the
vicinity of the South Pole currently leads to a few-percent loss of data, but
no overall effect on the background noise levels, which are dominated by the
thermal noise floor of the cold polar ice, and galactic noise at lower
frequencies. We have also successfully detected signals originating from a 2.5
km deep impulse generator at a distance of over 3 km from our prototype
detector, confirming prior estimates of kilometer-scale attenuation lengths for
cold polar ice. These are also the first such measurements for propagation over
such large slant distances in ice. Based on these data, ARA-37, the 200 km^2
array now under construction, will achieve the highest sensitivity of any
planned or existing neutrino detector in the 10^{16}-10^{19} eV energy range.Comment: 25 pages, 37 figures, this version with improved ice attenuation
length analysis; for submission to Astroparticle Physic
A Regularized Graph Layout Framework for Dynamic Network Visualization
Many real-world networks, including social and information networks, are
dynamic structures that evolve over time. Such dynamic networks are typically
visualized using a sequence of static graph layouts. In addition to providing a
visual representation of the network structure at each time step, the sequence
should preserve the mental map between layouts of consecutive time steps to
allow a human to interpret the temporal evolution of the network. In this
paper, we propose a framework for dynamic network visualization in the on-line
setting where only present and past graph snapshots are available to create the
present layout. The proposed framework creates regularized graph layouts by
augmenting the cost function of a static graph layout algorithm with a grouping
penalty, which discourages nodes from deviating too far from other nodes
belonging to the same group, and a temporal penalty, which discourages large
node movements between consecutive time steps. The penalties increase the
stability of the layout sequence, thus preserving the mental map. We introduce
two dynamic layout algorithms within the proposed framework, namely dynamic
multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We
apply these algorithms on several data sets to illustrate the importance of
both grouping and temporal regularization for producing interpretable
visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material
(animations and MATLAB toolbox) available at
http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201
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