287 research outputs found
Stability boundary approximation of periodic dynamics
We develop here the method for obtaining approximate stability boundaries in
the space of parameters for systems with parametric excitation. The monodromy
(Floquet) matrix of linearized system is found by averaging method. For system
with 2 degrees of freedom (DOF) we derive general approximate stability
conditions. We study domains of stability with the use of fourth order
approximations of monodromy matrix on example of inverted position of a
pendulum with vertically oscillating pivot. Addition of small damping shifts
the stability boundaries upwards, thus resulting to both stabilization and
destabilization effects.Comment: 9 pages, 2 figure
BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features
Abstract Background Understanding how biomolecules interact is a major task of systems biology. To model protein-nucleic acid interactions, it is important to identify the DNA or RNA-binding residues in proteins. Protein sequence features, including the biochemical property of amino acids and evolutionary information in terms of position-specific scoring matrix (PSSM), have been used for DNA or RNA-binding site prediction. However, PSSM is rather designed for PSI-BLAST searches, and it may not contain all the evolutionary information for modelling DNA or RNA-binding sites in protein sequences. Results In the present study, several new descriptors of evolutionary information have been developed and evaluated for sequence-based prediction of DNA and RNA-binding residues using support vector machines (SVMs). The new descriptors were shown to improve classifier performance. Interestingly, the best classifiers were obtained by combining the new descriptors and PSSM, suggesting that they captured different aspects of evolutionary information for DNA and RNA-binding site prediction. The SVM classifiers achieved 77.3% sensitivity and 79.3% specificity for prediction of DNA-binding residues, and 71.6% sensitivity and 78.7% specificity for RNA-binding site prediction. Conclusions Predictions at this level of accuracy may provide useful information for modelling protein-nucleic acid interactions in systems biology studies. We have thus developed a web-based tool called BindN+ (http://bioinfo.ggc.org/bindn+/) to make the SVM classifiers accessible to the research community
Large-Scale Fabrication of Boron Nitride Nanotubes via a Facile Chemical Vapor Reaction Route and Their Cathodoluminescence Properties
Cylinder- and bamboo-shaped boron nitride nanotubes (BNNTs) have been synthesized in large scale via a facile chemical vapor reaction route using ammonia borane as a precursor. The structure and chemical composition of the as-synthesized BNNTs are extensively characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, and selected-area electron diffraction. The cylinder-shaped BNNTs have an average diameter of about 100 nm and length of hundreds of microns, while the bamboo-shaped BNNTs are 100–500 nm in diameter with length up to tens of microns. The formation mechanism of the BNNTs has been explored on the basis of our experimental observations and a growth model has been proposed accordingly. Ultraviolet–visible and cathodoluminescence spectroscopic analyses are performed on the BNNTs. Strong ultraviolet emissions are detected on both morphologies of BNNTs. The band gap of the BNNTs are around 5.82 eV and nearly unaffected by tube morphology. There exist two intermediate bands in the band gap of BNNTs, which could be distinguishably assigned to structural defects and chemical impurities
Dimer Models and Integrable Systems
We explore various aspects of the correspondence between dimer models and
integrable systems recently introduced by Goncharov and Kenyon. Dimer models
give rise to relativistic integrable systems that match those arising from 5d
N=1 gauge theories studied by Nekrasov. We apply the correspondence to dimer
models associated to the Y^{p,0} geometries, showing that they give rise to the
relativistic generalization of the periodic Toda chain originally studied by
Ruijsenaars. The correspondence reduces the calculation of all conserved
charges to a straightforward combinatorial problem of enumerating
non-intersecting paths in the dimer model. We show how the usual periodic Toda
chain emerges in the non-relativistic limit and how the Lax operator
corresponds to the Kasteleyn matrix of the dimer model. We discuss how the
dimer models for general Y^{p,q} manifolds give rise to other relativistic
integrable systems, generalizing the periodic Toda chain and construct the
integrable systems for general Y^{p,p} explicitly. The impurities introduced in
the construction of Y^{p,q} quivers are identified with impurities in twisted
sl(2) XXZ spin chains. Finally we discuss how the physical concept of higgsing
a dimer model provides an efficient method for producing new integrable systems
starting from known ones. We illustrate this idea by constructing the
integrable systems for higgsings of Y^{4,0}.Comment: 29 pages, 16 figures. v2: typos fixe
Search for New Physics in e mu X Data at D0 Using Sleuth: A Quasi-Model-Independent Search Strategy for New Physics
We present a quasi-model-independent search for the physics responsible for
electroweak symmetry breaking. We define final states to be studied, and
construct a rule that identifies a set of relevant variables for any particular
final state. A new algorithm ("Sleuth") searches for regions of excess in those
variables and quantifies the significance of any detected excess. After
demonstrating the sensitivity of the method, we apply it to the semi-inclusive
channel e mu X collected in 108 pb^-1 of ppbar collisions at sqrt(s) = 1.8 TeV
at the D0 experiment during 1992-1996 at the Fermilab Tevatron. We find no
evidence of new high p_T physics in this sample.Comment: 23 pages, 12 figures. Submitted to Physical Review
Ratio of the Isolated Photon Cross Sections at \sqrt{s} = 630 and 1800 GeV
The inclusive cross section for production of isolated photons has been
measured in \pbarp collisions at GeV with the \D0 detector at
the Fermilab Tevatron Collider. The photons span a transverse energy ()
range from 7-49 GeV and have pseudorapidity . This measurement is
combined with to previous \D0 result at GeV to form a ratio
of the cross sections. Comparison of next-to-leading order QCD with the
measured cross section at 630 GeV and ratio of cross sections show satisfactory
agreement in most of the range.Comment: 7 pages. Published in Phys. Rev. Lett. 87, 251805, (2001
Rapidity and Centrality Dependence of Proton and Anti-proton Production from Au+Au Collisions at sqrt(sNN) = 130GeV
We report on the rapidity and centrality dependence of proton and anti-proton
transverse mass distributions from Au+Au collisions at sqrt(sNN) = 130GeV as
measured by the STAR experiment at RHIC. Our results are from the rapidity and
transverse momentum range of |y|<0.5 and 0.35 <p_t<1.00GeV/c. For both protons
and anti-protons, transverse mass distributions become more convex from
peripheral to central collisions demonstrating characteristics of collective
expansion. The measured rapidity distributions and the mean transverse momenta
versus rapidity are flat within |y|<0.5. Comparisons of our data with results
from model calculations indicate that in order to obtain a consistent picture
of the proton(anti-proton) yields and transverse mass distributions the
possibility of pre-hadronic collective expansion may have to be taken into
account.Comment: 4 pages, 3 figures, 1 table, submitted to PR
Search for Kaluza-Klein Graviton Emission in Collisions at TeV using the Missing Energy Signature
We report on a search for direct Kaluza-Klein graviton production in a data
sample of 84 of \ppb collisions at = 1.8 TeV, recorded
by the Collider Detector at Fermilab. We investigate the final state of large
missing transverse energy and one or two high energy jets. We compare the data
with the predictions from a -dimensional Kaluza-Klein scenario in which
gravity becomes strong at the TeV scale. At 95% confidence level (C.L.) for
=2, 4, and 6 we exclude an effective Planck scale below 1.0, 0.77, and 0.71
TeV, respectively.Comment: Submitted to PRL, 7 pages 4 figures/Revision includes 5 figure
The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites
Conductance-based neuron models are frequently employed to study the dynamics of biological neural networks. For speed and ease of use, these models are often reduced in morphological complexity. Simplified dendritic branching structures may process inputs differently than full branching structures, however, and could thereby fail to reproduce important aspects of biological neural processing. It is not yet well understood which processing capabilities require detailed branching structures. Therefore, we analyzed the processing capabilities of full or partially branched reduced models. These models were created by collapsing the dendritic tree of a full morphological model of a globus pallidus (GP) neuron while preserving its total surface area and electrotonic length, as well as its passive and active parameters. Dendritic trees were either collapsed into single cables (unbranched models) or the full complement of branch points was preserved (branched models). Both reduction strategies allowed us to compare dynamics between all models using the same channel density settings. Full model responses to somatic inputs were generally preserved by both types of reduced model while dendritic input responses could be more closely preserved by branched than unbranched reduced models. However, features strongly influenced by local dendritic input resistance, such as active dendritic sodium spike generation and propagation, could not be accurately reproduced by any reduced model. Based on our analyses, we suggest that there are intrinsic differences in processing capabilities between unbranched and branched models. We also indicate suitable applications for different levels of reduction, including fast searches of full model parameter space
PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context
Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community
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