PQCD Analysis of Parton-Hadron Duality

We propose an extraction of the running coupling constant of QCD in the infrared region from experimental data on deep inelastic inclusive scattering at Bjorken x -> 1. We first attempt a perturbative fit of the data that extends NLO PQCD evolution to large x values and final state invariant mass, W, in the resonance region. We include both target mass corrections and large x resummation effects. These effects are of order O(1/Q^2), and they improve the agreement with the Q^2 dependence of the data. Standard analyses require the presence of additional power corrections, or dynamical higher twists, to achieve a fully quantitative fit. Our analysis, however, is regulated by the value of the strong coupling in the infrared region that enters through large x resummation effects, and that can suppress, or absorb, higher twist effects. Large x data therefore indirectly provide a measurement of this quantity that can be compared to extractions from other observables.Comment: 10 pages, 3 figure

Anisotropic magnetoresistance contribution to measured domain wall resistances of in-plane magnetised (Ga,Mn)As

We demonstrate the presence of an important anisotropic magnetoresistance contribution to the domain wall resistance recently measured in thin-film (Ga,Mn)As with in-plane magnetic anisotropy. Analytic results for simple domain wall orientations supplemented by numerical results for more general cases show this previously omitted contribution can largely explain the observed negative resistance.Comment: 4 pages; submitted to Phys Rev

The in-vacuo torque performance of dry-lubricated ball bearings at cryogenic temperatures

The performance of dry-lubricated, angular contact ball bearings in vacuum at a temperature of 20 degrees K has been investigated, and is compared with the in-vacuo performance at room temperatures. Bearings were lubricated using dry-lubricant techniques which have been previously established for space applications involving operations at or near room temperature. Comparative tests were undertaken using three lubricants: molybdenum disulphide, lead, and PTFE. Results obtained using the three lubricants are presented

Soil sustainability in organic agricultural production

Traditionally, the assessment of soil sustainability and the potential impact of cultivation are based upon the application of chemical procedures. In the absence of a biological context, these measurements offer little in understanding longterm changes in soil husbandry. Detailed microcosm investigations were applied as a predictive tool for management change. The microcosms were designed with homogenised soils treated with organic amendments. Key soil functional relationships were quantified using stable isotope techniques, biochemical measurements and traditional approaches

Weight-Preserving Simulated Tempering

Simulated tempering is popular method of allowing MCMC algorithms to move between modes of a multimodal target density {\pi}. One problem with simulated tempering for multimodal targets is that the weights of the various modes change for different inverse-temperature values, sometimes dramatically so. In this paper, we provide a fix to overcome this problem, by adjusting the mode weights to be preserved (i.e., constant) over different inverse-temperature settings. We then apply simulated tempering algorithms to multimodal targets using our mode weight correction. We present simulations in which our weight-preserving algorithm mixes between modes much more successfully than traditional tempering algorithms. We also prove a diffusion limit for an version of our algorithm, which shows that under appropriate assumptions, our algorithm mixes in time O(d [log d]^2)

Enterprise profiles in deprived areas: Are they distinctive?

This paper examines the extent to which segmenting business activity on the basis of the relative deprivation of a given area provides additional understanding (in terms of analysis and policy) that is not obtained by alternative divisions, e.g., by sector, size, etc. The paper is primarily motivated by the explicit inclusion of a deprived area dimension to many UK small business/enterprise policies introduced since 1997. We use two datasets drawn from the customer records of Barclays Bank PLC to obtain an initial analysis of the business stocks and dynamics in deprived and non-deprived areas of England. The data indicate that the deprived areas of England vary systematically from the wider economy in terms of several business stock characteristics and associated dynamics. These differences include a lower proportion of business service firms, lower female involvement in the owner-manager base and a poorer risk profile. The analysis supports the view that there are likely to be benefits from the tailoring of small business/ enterprise policies to sub-national levels

MEXIT: Maximal un-coupling times for stochastic processes

Classical coupling constructions arrange for copies of the \emph{same} Markov process started at two \emph{different} initial states to become equal as soon as possible. In this paper, we consider an alternative coupling framework in which one seeks to arrange for two \emph{different} Markov (or other stochastic) processes to remain equal for as long as possible, when started in the \emph{same} state. We refer to this "un-coupling" or "maximal agreement" construction as \emph{MEXIT}, standing for "maximal exit". After highlighting the importance of un-coupling arguments in a few key statistical and probabilistic settings, we develop an explicit \MEXIT construction for stochastic processes in discrete time with countable state-space. This construction is generalized to random processes on general state-space running in continuous time, and then exemplified by discussion of \MEXIT for Brownian motions with two different constant drifts.Comment: 28 page

Use of tunable nanopore blockade rates to investigate colloidal dispersions

Tunable nanopores in elastomeric membranes have been used to study the dependence of ionic current blockade rate on the concentration and electrophoretic mobility of particles in aqueous suspensions. A range of nanoparticle sizes, materials and surface functionalities has been tested. Using pressure-driven flow through a pore, the blockade rate for 100 nm carboxylated polystyrene particles was found to be linearly proportional to both transmembrane pressure (controlled between 0 and 1.8 kPa) and particle concentration (between 7 x 10^8 and 4.5 x 10^10 mL^-1). This result can be accurately modelled using Nernst-Planck transport theory. Using only an applied potential across a pore, the blockade rates for carboxylic acid and amine coated 500 nm and 200 nm silica particles were found to correspond to changes in their mobility as a function of the solution pH. Scanning electron microscopy and confocal microscopy have been used to visualise changes in the tunable nanopore geometry in three dimensions as a function of applied mechanical strain. The pores observed were conical in shape, and changes in pore size were consistent with ionic current measurements. A zone of inelastic deformation adjacent to the pore has been identified as critical in the tuning process

MCMC methods for functions modifying old algorithms to make\ud them faster

Many problems arising in applications result in the need\ud to probe a probability distribution for functions. Examples include Bayesian nonparametric statistics and conditioned diffusion processes. Standard MCMC algorithms typically become arbitrarily slow under the mesh refinement dictated by nonparametric description of the unknown function. We describe an approach to modifying a whole range of MCMC methods which ensures that their speed of convergence is robust under mesh refinement. In the applications of interest the data is often sparse and the prior specification is an essential part of the overall modeling strategy. The algorithmic approach that we describe is applicable whenever the desired probability measure has density with respect to a Gaussian process or Gaussian random field prior, and to some useful non-Gaussian priors constructed through random truncation. Applications are shown in density estimation, data assimilation in fluid mechanics, subsurface geophysics and image registration. The key design principle is to formulate the MCMC method for functions. This leads to algorithms which can be implemented via minor modification of existing algorithms, yet which show enormous speed-up on a wide range of applied problems