19,973 research outputs found
Diagnostic reasoning techniques for selective monitoring
An architecture for using diagnostic reasoning techniques in selective monitoring is presented. Given the sensor readings and a model of the physical system, a number of assertions are generated and expressed as Boolean equations. The resulting system of Boolean equations is solved symbolically. Using a priori probabilities of component failure and Bayes' rule, revised probabilities of failure can be computed. These will indicate what components have failed or are the most likely to have failed. This approach is suitable for systems that are well understood and for which the correctness of the assertions can be guaranteed. Also, the system must be such that changes are slow enough to allow the computation
The Porphyromonas gingivalis hemagglutinins HagB and HagC are major mediators of adhesion and biofilm formation
Porphyromonas gingivalis is a bacterium associated with chronic periodontitis that possesses a family of genes encoding hemagglutinins required for heme acquisition. In this study we generated ΔhagB and ΔhagC mutants in strain W83 and demonstrate that both hagB and hagC are required for adherence to oral epithelial cells. Unexpectedly, a double ΔhagB/ΔhagC mutant had less severe adherence defects than either of the single mutants, but was found to exhibit increased expression of the gingipain-encoding genes rgpA and kgp, suggesting that a ΔhagB/ΔhagC mutant is only viable in populations of cells that exhibit increased expression of genes involved in heme acquisition. Disruption of hagB in the fimbriated strain ATCC33277 demonstrated that HagB is also required for stable attachment of fimbriated bacteria to oral epithelial cells. Mutants of hagC were also found to form defective single and multi-species biofilms that had reduced biomass relative to biofilms formed by the wild-type strain. This study highlights the hitherto unappreciated importance of these genes in oral colonization and biofilm formation
Calculating effective resistances on underlying networks of association schemes
Recently, in Refs. \cite{jsj} and \cite{res2}, calculation of effective
resistances on distance-regular networks was investigated, where in the first
paper, the calculation was based on stratification and Stieltjes function
associated with the network, whereas in the latter one a recursive formula for
effective resistances was given based on the Christoffel-Darboux identity. In
this paper, evaluation of effective resistances on more general networks which
are underlying networks of association schemes is considered, where by using
the algebraic combinatoric structures of association schemes such as
stratification and Bose-Mesner algebras, an explicit formula for effective
resistances on these networks is given in terms of the parameters of
corresponding association schemes. Moreover, we show that for particular
underlying networks of association schemes with diameter such that the
adjacency matrix possesses distinct eigenvalues, all of the other
adjacency matrices , can be written as polynomials of ,
i.e., , where is not necessarily of degree . Then, we use
this property for these particular networks and assume that all of the
conductances except for one of them, say , are zero to give a
procedure for evaluating effective resistances on these networks. The
preference of this procedure is that one can evaluate effective resistances by
using the structure of their Bose-Mesner algebra without any need to know the
spectrum of the adjacency matrices.Comment: 41 page
Intervening in the Case (or Controversy): Article III Standing, Rule 24 Intervention, and the Conflict in the Federal Courts
Intervening in the Case (or Controversy): Article III Standing, Rule 24 Intervention, and the Conflict in the Federal Courts
In vitro and in vivo studies of the trypanocidal properties of WRR-483 against Trypanosoma cruzi.
BackgroundCruzain, the major cysteine protease of Trypanosoma cruzi, is an essential enzyme for the parasite life cycle and has been validated as a viable target to treat Chagas' disease. As a proof-of-concept, K11777, a potent inhibitor of cruzain, was found to effectively eliminate T. cruzi infection and is currently a clinical candidate for treatment of Chagas' disease.Methodology/principal findingsWRR-483, an analog of K11777, was synthesized and evaluated as an inhibitor of cruzain and against T. cruzi proliferation in cell culture. This compound demonstrates good potency against cruzain with sensitivity to pH conditions and high efficacy in the cell culture assay. Furthermore, WRR-483 also eradicates parasite infection in a mouse model of acute Chagas' disease. To determine the atomic-level details of the inhibitor interacting with cruzain, a 1.5 A crystal structure of the protease in complex with WRR-483 was solved. The structure illustrates that WRR-483 binds covalently to the active site cysteine of the protease in a similar manner as other vinyl sulfone-based inhibitors. Details of the critical interactions within the specificity binding pocket are also reported.ConclusionsWe demonstrate that WRR-483 is an effective cysteine protease inhibitor with trypanocidal activity in cell culture and animal model with comparable efficacy to K11777. Crystallographic evidence confirms that the mode of action is by targeting the active site of cruzain. Taken together, these results suggest that WRR-483 has potential to be developed as a treatment for Chagas' disease
High-flux beam source for cold, slow atoms or molecules
We demonstrate and characterize a high-flux beam source for cold, slow atoms
or molecules. The desired species is vaporized using laser ablation, then
cooled by thermalization in a cryogenic cell of buffer gas. The beam is formed
by particles exiting a hole in the buffer gas cell. We characterize the
properties of the beam (flux, forward velocity, temperature) for both an atom
(Na) and a molecule (PbO) under varying buffer gas density, and discuss
conditions for optimizing these beam parameters. Our source compares favorably
to existing techniques of beam formation, for a variety of applications.Comment: 5 Pages, 4 figure
Buffer gas cooling and trapping of atoms with small magnetic moments
Buffer gas cooling was extended to trap atoms with small magnetic moment
(mu). For mu greater than or equal to 3mu_B, 1e12 atoms were buffer gas cooled,
trapped, and thermally isolated in ultra high vacuum with roughly unit
efficiency. For mu < 3mu_B, the fraction of atoms remaining after full thermal
isolation was limited by two processes: wind from the rapid removal of the
buffer gas and desorbing helium films. In our current apparatus we trap atoms
with mu greater than or equal to 1.1mu_B, and thermally isolate atoms with mu
greater than or equal to 2mu_B. Extrapolation of our results combined with
simulations of the loss processes indicate that it is possible to trap and
evaporatively cool mu = 1mu_B atoms using buffer gas cooling.Comment: 17 pages, 4 figure
Using machine learning techniques to automate sky survey catalog generation
We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data
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