32,187 research outputs found
Enabling Data-Driven Transportation Safety Improvements in Rural Alaska
Safety improvements require funding. A clear need must be demonstrated to secure funding. For transportation safety, data, especially data about past crashes, is the usual method of demonstrating need. However, in rural locations, such data is often not available, or is not in a form amenable to use in funding applications. This research aids rural entities, often federally recognized tribes and small villages acquire data needed for funding applications. Two aspects of work product are the development of a traffic counting application for an iPad or similar device, and a review of the data requirements of the major transportation funding agencies. The traffic-counting app, UAF Traffic, demonstrated its ability to count traffic and turning movements for cars and trucks, as well as ATVs, snow machines, pedestrians, bicycles, and dog sleds. The review of the major agencies demonstrated that all the likely funders would accept qualitative data and Road Safety Audits. However, quantitative data, if it was available, was helpful
Long-term study of the impact of methotrexate on serum cytokines and lymphocyte subsets in patients with active rheumatoid arthritis: correlation with pharmacokinetic measures
Objective To describe changes in immune parameters observed during long-term methotrexate (MTX) therapy in patients with active rheumatoid arthritis (RA) and explore correlations with simultaneously measured MTX pharmacokinetic (PKC) parameters.
Design Prospective, open-label, long-term mechanism of action study.
Setting University clinic.
Methods MTX was initiated at a single weekly oral dose of 7.5 mg and dose adjusted for efficacy and toxicity for the duration of the study. Standard measures of disease activity were performed at baseline and every 6–36 months. Serum cytokine measurements in blood together with lymphocyte surface immunophenotypes and stimulated peripheral blood mononuclear cell (PBMC) cytokine production were assessed at each clinical evaluation.
Results Cytokine concentrations exhibited multiple significant correlations with disease activity measures over time. The strongest correlations observed were for interleukin (IL)-6 (r=0.45, p<0.0001 for swollen joints and r=0.32, p=0.002 for tender joints) and IL-8 (r=0.25, p=0.01 for swollen joints). Significant decreases from baseline were observed in serum IL-1B, IL-6 and IL-8 concentrations. The most significant changes were observed for IL-6 (p<0.001). Significant increases from baseline were observed in IL-2 release from PBMCs ex vivo (p<0.01). In parallel, multiple statistically significant correlations were observed between MTX PKC measures and immune parameters. The change in swollen joint count correlated inversely with the change in area under the curve (AUC) for MTX (r=−0.63, p=0.007).
Conclusions MTX therapy of patients with RA is accompanied by a variety of changes in serum cytokine expression, which in turn correlate strongly with clinical disease activity and MTX pharmacokinetics (PKCs). These data strongly support the notion that MTX mediates profound and functionally relevant effects on the immunological hierarchy in the RA lesion
Classification of interstitial lung disease patterns with topological texture features
Topological texture features were compared in their ability to classify
morphological patterns known as 'honeycombing' that are considered indicative
for the presence of fibrotic interstitial lung diseases in high-resolution
computed tomography (HRCT) images. For 14 patients with known occurrence of
honey-combing, a stack of 70 axial, lung kernel reconstructed images were
acquired from HRCT chest exams. A set of 241 regions of interest of both
healthy and pathological (89) lung tissue were identified by an experienced
radiologist. Texture features were extracted using six properties calculated
from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and
three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN)
classifier and a Multilayer Radial Basis Functions Network (RBFN) were
optimized in a 10-fold cross-validation for each texture vector, and the
classification accuracy was calculated on independent test sets as a
quantitative measure of automated tissue characterization. A Wilcoxon
signed-rank test was used to compare two accuracy distributions and the
significance thresholds were adjusted for multiple comparisons by the
Bonferroni correction. The best classification results were obtained by the MF
features, which performed significantly better than all the standard GLCM and
MD features (p < 0.005) for both classifiers. The highest accuracy was found
for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively).
The best standard texture features were the GLCM features 'homogeneity' (91.8%,
87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced
topological texture features can provide superior classification performance in
computer-assisted diagnosis of interstitial lung diseases when compared to
standard texture analysis methods.Comment: 8 pages, 5 figures, Proceedings SPIE Medical Imaging 201
Spatio-Temporal Low Count Processes with Application to Violent Crime Events
There is significant interest in being able to predict where crimes will
happen, for example to aid in the efficient tasking of police and other
protective measures. We aim to model both the temporal and spatial dependencies
often exhibited by violent crimes in order to make such predictions. The
temporal variation of crimes typically follows patterns familiar in time series
analysis, but the spatial patterns are irregular and do not vary smoothly
across the area. Instead we find that spatially disjoint regions exhibit
correlated crime patterns. It is this indeterminate inter-region correlation
structure along with the low-count, discrete nature of counts of serious crimes
that motivates our proposed forecasting tool. In particular, we propose to
model the crime counts in each region using an integer-valued first order
autoregressive process. We take a Bayesian nonparametric approach to flexibly
discover a clustering of these region-specific time series. We then describe
how to account for covariates within this framework. Both approaches adjust for
seasonality. We demonstrate our approach through an analysis of weekly reported
violent crimes in Washington, D.C. between 2001-2008. Our forecasts outperform
standard methods while additionally providing useful tools such as prediction
intervals
Characterization and limits of a cold atom Sagnac interferometer
We present the full evaluation of a cold atom gyroscope based on atom
interferometry. We have performed extensive studies to determine the systematic
errors, scale factor and sensitivity. We demonstrate that the acceleration
noise can be efficiently removed from the rotation signal allowing to reach the
fundamental limit of the quantum projection noise for short term measurements.
The technical limits to the long term sensitivity and accuracy have been
identified, clearing the way for the next generations of ultra-sensitive atom
gyroscopes
Fluctuations in superconducting rings with two order parameters
Starting from the Ginzburg-Landau energy functional, we discuss how the
presence of two order parameters and the coupling between them influence a
superconducting ring in the fluctuative regime. Our method is exact, but
requires numerical implementation. We also study approximations for which some
analytic expressions can be obtained, and check their ranges of validity. We
provide estimates for the temperature ranges where fluctuations are important,
calculate the persistent current in magnesium diboride rings as a function of
temperature and enclosed flux, and point out its additional dependence on the
cross-section area of the ring. We find temperature regions in which
fluctuations enhance the persistent currents and regions where they inhibit the
persistent current. The presence of two order parameters that can fluctuate
independently always leads to larger averages of the order parameters at Tc,
but only for appropriate parameters this yields larger persistent current. In
cases of very different material parameters for the two coupled condensates,
the persistent current is inhibited
Black hole evolution by spectral methods
Current methods of evolving a spacetime containing one or more black holes
are plagued by instabilities that prohibit long-term evolution. Some of these
instabilities may be due to the numerical method used, traditionally finite
differencing. In this paper, we explore the use of a pseudospectral collocation
(PSC) method for the evolution of a spherically symmetric black hole spacetime
in one dimension using a hyperbolic formulation of Einstein's equations. We
demonstrate that our PSC method is able to evolve a spherically symmetric black
hole spacetime forever without enforcing constraints, even if we add dynamics
via a Klein-Gordon scalar field. We find that, in contrast to
finite-differencing methods, black hole excision is a trivial operation using
PSC applied to a hyperbolic formulation of Einstein's equations. We discuss the
extension of this method to three spatial dimensions.Comment: 20 pages, 17 figures, submitted to PR
Spectral methods for the wave equation in second-order form
Current spectral simulations of Einstein's equations require writing the
equations in first-order form, potentially introducing instabilities and
inefficiencies. We present a new penalty method for pseudo-spectral evolutions
of second order in space wave equations. The penalties are constructed as
functions of Legendre polynomials and are added to the equations of motion
everywhere, not only on the boundaries. Using energy methods, we prove
semi-discrete stability of the new method for the scalar wave equation in flat
space and show how it can be applied to the scalar wave on a curved background.
Numerical results demonstrating stability and convergence for multi-domain
second-order scalar wave evolutions are also presented. This work provides a
foundation for treating Einstein's equations directly in second-order form by
spectral methods.Comment: 16 pages, 5 figure
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