TFBSTools: an R/bioconductor package for transcription factor binding site analysis.

Summary: The ability to efficiently investigate transcription factor binding sites (TFBSs) genome-wide is central to computational studies of gene regulation. TFBSTools is an R/Bioconductor package for the analysis and manipulation of TFBSs and their associated transcription factor profile matrices. TFBStools provides a toolkit for handling TFBS profile matrices, scanning sequences and alignments including whole genomes, and querying the JASPAR database. The functionality of the package can be easily extended to include advanced statistical analysis, data visualization and data integration. Availability and implementation: The package is implemented in R and available under GPL-2 license from the Bioconductor website (http://bioconductor.org/packages/TFBSTools/). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Coronae & Outflows from Helical Dynamos, Compatibility with the MRI, and Application to Protostellar Disks

Magnetically mediated disk outflows are a leading paradigm to explain winds and jets in a variety of astrophysical sources, but where do the fields come from? Since accretion of mean magnetic flux may be disfavored in a thin turbulent disk, and only fields generated with sufficiently large scale can escape before being shredded by turbulence, in situ field production is desirable. Nonlinear helical inverse dynamo theory can provide the desired fields for coronae and outflows. We discuss the implications for contemporary protostellar disks, where the MRI (magneto-rotational instability) can drive turbulence in the inner regions, and primordial protostellar disks, where gravitational instability drives the turbulence. We emphasize that helical dynamos are compatible with the magneto-rotational instability, and clarify the relationship between the two.Comment: 12 pages, LaTeX (with figs); version in press for "Proceedings of the International Workshop on Magnetic Fields and Star Formation: Theory vs. Observation" Madrid, Spain; April 200

Achieving Effective Innovation Based On TRIZ Technological Evolution

Organised by: Cranfield UniversityThis paper outlines the conception of effective innovation and discusses the method to achieve it. Effective Innovation is constrained on the path of technological evolution so that the corresponding path must be detected before conceptual design of the product. The process of products technological evolution is a technical developing process that the products approach to Ideal Final Result (IFR). During the process, the sustaining innovation and disruptive innovation carry on alternately. By researching and forecasting potential techniques using TRIZ technological evolution theory, the effective innovation can be achieved finally.Mori Seiki – The Machine Tool Compan

Forecasting international bandwidth capacity using linear and ANN methods

An artificial neural network (ANN) can improve forecasts through pattern recognition of historical data. This article evaluates the reliability of ANN methods, as opposed to simple extrapolation techniques, to forecast Internet bandwidth index data that is bursty in nature. A simple feedforward ANN model is selected as a nonlinear alternative, as it is flexible enough to model complex linear or nonlinear relationships without any prior assumptions about the data generating process. These data are virtually white noise and provides a challenge to forecasters. Using standard forecast error statistics, the ANN and the simple exponential smoothing model provide modestly better forecasts than other extrapolation methodsForecasting; international bandwidth capacity

Shubnikov-de Haas oscillations of a single layer graphene under dc current bias

Shubnikov-de Haas (SdH) oscillations under a dc current bias are experimentally studied on a Hall bar sample of single layer graphene. In dc resistance, the bias current shows the common damping effect on the SdH oscillations and the effect can be well accounted for by an elevated electron temperature that is found to be linearly dependent on the current bias. In differential resistance, a novel phase inversion of the SdH oscillations has been observed with increasing dc bias, namely we observe the oscillation maxima develop into minima and vice versa. Moreover, it is found that the onset biasing current, at which a SdH extremum is about to invert, is linearly dependent on the magnetic field of the SdH extrema. These observations are quantitatively explained with the help of a general SdH formula.Comment: 5 pages, 4 figures, A few references adde

Accelerating MCMC with active subspaces

The Markov chain Monte Carlo (MCMC) method is the computational workhorse for Bayesian inverse problems. However, MCMC struggles in high-dimensional parameter spaces, since its iterates must sequentially explore the high-dimensional space. This struggle is compounded in physical applications when the nonlinear forward model is computationally expensive. One approach to accelerate MCMC is to reduce the dimension of the state space. Active subspaces are part of an emerging set of tools for subspace-based dimension reduction. An active subspace in a given inverse problem indicates a separation between a low-dimensional subspace that is informed by the data and its orthogonal complement that is constrained by the prior. With this information, one can run the sequential MCMC on the active variables while sampling independently according to the prior on the inactive variables. However, this approach to increase efficiency may introduce bias. We provide a bound on the Hellinger distance between the true posterior and its active subspace- exploiting approximation. And we demonstrate the active subspace-accelerated MCMC on two computational examples: (i) a two-dimensional parameter space with a quadratic forward model and one-dimensional active subspace and (ii) a 100-dimensional parameter space with a PDE-based forward model and a two-dimensional active subspace

Inclusive Production Through AdS/CFT

It has been shown that AdS/CFT calculations can reproduce certain exclusive 2->2 cross sections in QCD at high energy, both for near-forward and for fixed-angle scattering. In this paper, we extend prior treatments by using AdS/CFT to calculate the inclusive single-particle production cross section in QCD at high center-of-mass energy. We find that conformal invariance in the UV restricts the cross section to have a characteristic power-law falloff in the transverse momentum of the produced particle, with the exponent given by twice the conformal dimension of the produced particle, independent of incoming particle types. We conclude by comparing our findings to recent LHC experimental data from ATLAS and ALICE, and find good agreement.Comment: JHEP version. Discussion, appendix, figures, and tables added. Conclusions and key results unchange

Graphene Dirac fermions in one-dimensional inhomogeneous field profiles: Transforming magnetic to electric field

We show that the low-energy electronic structure of graphene under a one-dimensional inhomogeneous magnetic field can be mapped into that of graphene under an electric field or vice versa. As a direct application of this transformation, we find that the carrier velocity in graphene is isotropically reduced under magnetic fields periodic along one direction with zero average flux. This counterintuitive renormalization has its origin in the pseudospin nature of graphene electronic states and is robust against disorder. In magnetic graphene superlattices with a finite average flux, the Landau level bandwidth at high fields exhibits an unconventional behavior of decreasing with increasing strength of the average magnetic field due to the linear energy dispersion of graphene. As another application of our transformation relation, we show that the transmission probabilities of an electron through a magnetic barrier in graphene can directly be obtained from those through an electrostatic barrier or vice versa.Comment: 19 pages, 6 figures. Revised versio