Remarks on the Classical Size of D-Branes

We discuss different criteria for `classical size' of extremal Dirichlet p-branes in type-II supergravity. Using strong-weak coupling duality, we find that the size of the strong-coupling region at the core of the (p<3)-branes, is always given by the asymptotic string scale, if measured in the weakly coupled dual string metric. We also point out how the eleven-dimensional Planck scale arises in the classical 0-brane solution, as well as the ten-dimensional Planck scale in the D-instanton solution.Comment: 8 pp, harvma

Preliminary results from the dust flux monitoring instrument during the encounter of Stardust spacecraft with Wild-2 comet

On January 2, 2004, the Stardust spacecraft successfully encountered the Wild-2 comet. The Dust Flux Monitoring Instrument (DFMI) provided quantitative measurements of dust particle fluxes and particle mass distributions throughout the entire flythrough

Coulomb screening in mesoscopic noise: a kinetic approach

Coulomb screening, together with degeneracy, is characteristic of the metallic electron gas. While there is little trace of its effects in transport and noise in the bulk, at mesoscopic scales the electronic fluctuations start to show appreciable Coulomb correlations. Within a strictly standard Boltzmann and Fermi-liquid framework, we analyze these phenomena and their relation to the mesoscopic fluctuation-dissipation theorem, which we prove. We identify two distinct screening mechanisms for mesoscopic fluctuations. One is the self-consistent response of the contact potential in a non-uniform system. The other couples to scattering, and is an exclusively non-equilibrium process. Contact-potential effects renormalize all thermal fluctuations, at all scales. Collisional effects are relatively short-ranged and modify non-equilibrium noise. We discuss ways to detect these differences experimentally.Comment: Source: REVTEX. 16 pp.; 7 Postscript figs. Accepted for publication in J. Phys.: Cond. Ma

Impact of imperfect test sensitivity on determining risk factors : the case of bovine tuberculosis

Background Imperfect diagnostic testing reduces the power to detect significant predictors in classical cross-sectional studies. Assuming that the misclassification in diagnosis is random this can be dealt with by increasing the sample size of a study. However, the effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate, especially if the outcome of the test influences behaviour. The aim of this paper is to investigate the impact of imperfect test sensitivity on the determination of predictor variables in a longitudinal study. Methodology/Principal Findings To deal with imperfect test sensitivity affecting the response variable, we transformed the observed response variable into a set of possible temporal patterns of true disease status, whose prior probability was a function of the test sensitivity. We fitted a Bayesian discrete time survival model using an MCMC algorithm that treats the true response patterns as unknown parameters in the model. We applied our approach to epidemiological data of bovine tuberculosis outbreaks in England and investigated the effect of reduced test sensitivity in the determination of risk factors for the disease. We found that reduced test sensitivity led to changes to the collection of risk factors associated with the probability of an outbreak that were chosen in the ‘best’ model and to an increase in the uncertainty surrounding the parameter estimates for a model with a fixed set of risk factors that were associated with the response variable. Conclusions/Significance We propose a novel algorithm to fit discrete survival models for longitudinal data where values of the response variable are uncertain. When analysing longitudinal data, uncertainty surrounding the response variable will affect the significance of the predictors and should therefore be accounted for either at the design stage by increasing the sample size or at the post analysis stage by conducting appropriate sensitivity analyses

Proceedings of the 1st Space Plasma Computer Analysis Network (SCAN) Workshop

The purpose of the workshop was to identify specific cooperative scientific study topics within the discipline of Ionosphere Magnetosphere Coupling processes and to develop methods and procedures to accomplish this cooperative research using SCAN facilities. Cooperative scientific research was initiated in the areas of polar cusp composition, O+ polar outflow, and magnetospheric boundary morphology studies and an approach using a common metafile structure was adopted to facilitate the exchange of data and plots between the various workshop participants. The advantages of in person versus remote workshops were discussed also

Hemiparasitic plant impacts animal and plant communities across four trophic levels

1.Understanding the impact of species on community structure is a fundamental question in ecology. There is a growing body of evidence that suggests that both sub-dominant species and parasites can have a disproportionately large impact. 2.Here we report the impacts of an organism that is both subdominant and parasitic, the hemiparasite Rhinanthus minor. Whilst the impact of parasitic angiosperms on their hosts and, to a lesser degree, co-existing plant species, have been well characterized, much less is known about their impacts on higher trophic levels. 3.We experimentally manipulated field densities of the hemiparasite Rhinanthus minor in a species rich grassland, comparing the plant and invertebrate communities in plots where it was removed, at natural densities or at enhanced densities. 4.Plots with natural and enhanced densities of R. minor had lower plant biomass than plots without the hemiparasite, but enhanced densities almost doubled the abundance of invertebrates within the plots across all trophic levels, with effects evident in herbivores, predators and detritivores. 5.The hemiparasite R. minor, despite being a sub-dominant and transient component within plant communities that it inhabits, has profound effects on four different trophic levels. These effects persist beyond the life of the hemiparasite, emphasizing its role as a keystone species in grassland communitie

Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected with measurement errors on discretized grids. In order to accurately smooth noisy functional observations and deal with the issue of high-dimensional observation grids, we propose a novel Bayesian method based on the Bayesian hierarchical model with a Gaussian-Wishart process prior and basis function representations. We first derive an induced model for the basis-function coefficients of the functional data, and then use this model to conduct posterior inference through Markov chain Monte Carlo. Compared to the standard Bayesian inference that suffers serious computational burden and unstableness for analyzing high-dimensional functional data, our method greatly improves the computational scalability and stability, while inheriting the advantage of simultaneously smoothing raw observations and estimating the mean-covariance functions in a nonparametric way. In addition, our method can naturally handle functional data observed on random or uncommon grids. Simulation and real studies demonstrate that our method produces similar results as the standard Bayesian inference with low-dimensional common grids, while efficiently smoothing and estimating functional data with random and high-dimensional observation grids where the standard Bayesian inference fails. In conclusion, our method can efficiently smooth and estimate high-dimensional functional data, providing one way to resolve the curse of dimensionality for Bayesian functional data analysis with Gaussian-Wishart processes.Comment: Under revie

Effect of positron-atom interactions on the annihilation gamma spectra of molecules

Calculations of gamma spectra for positron annihilation on a selection of molecules, including methane and its fluoro-substitutes, ethane, propane, butane and benzene are presented. The annihilation gamma spectra characterise the momentum distribution of the electron-positron pair at the instant of annihilation. The contribution to the gamma spectra from individual molecular orbitals is obtained from electron momentum densities calculated using modern computational quantum chemistry density functional theory tools. The calculation, in its simplest form, effectively treats the low-energy (thermalised, room-temperature) positron as a plane wave and gives annihilation gamma spectra that are about 40% broader than experiment, although the main chemical trends are reproduced. We show that this effective "narrowing" of the experimental spectra is due to the action of the molecular potential on the positron, chiefly, due to the positron repulsion from the nuclei. It leads to a suppression of the contribution of small positron-nuclear separations where the electron momentum is large. To investigate the effect of the nuclear repulsion, as well as that of short-range electron-positron and positron-molecule correlations, a linear combination of atomic orbital description of the molecular orbitals is employed. It facilitates the incorporation of correction factors which can be calculated from atomic many-body theory and account for the repulsion and correlations. Their inclusion in the calculation gives gamma spectrum linewidths that are in much better agreement with experiment. Furthermore, it is shown that the effective distortion of the electron momentum density, when it is observed through positron annihilation gamma spectra, can be approximated by a relatively simple scaling factor.Comment: 26 pages, 12 figure