Monte Carlo simulation of a mammographic test phantom

A test phantom, including a wide range of mammographic tissue equivalent materials and test details, was imaged on a digital mammographic system. In order to quantify the effect of scatter on the contrast obtained for the test details, calculations of the scatter-to-primary ratio (S/P) have been made using a Monte Carlo simulation of the digital mammographic imaging chain, grid and test phantom. The results show that the S/P values corresponding to the imaging conditions used were in the range 0.084-0.126. Calculated and measured pixel values in different regions of the image were compared as a validation of the model and showed excellent agreement. The results indicate the potential of Monte Carlo methods in the image quality-patient dose process optimisation, especially in the assessment of imaging conditions not available on standard mammographic unit

On discretization in time in simulations of particulate flows

We propose a time discretization scheme for a class of ordinary differential equations arising in simulations of fluid/particle flows. The scheme is intended to work robustly in the lubrication regime when the distance between two particles immersed in the fluid or between a particle and the wall tends to zero. The idea consists in introducing a small threshold for the particle-wall distance below which the real trajectory of the particle is replaced by an approximated one where the distance is kept equal to the threshold value. The error of this approximation is estimated both theoretically and by numerical experiments. Our time marching scheme can be easily incorporated into a full simulation method where the velocity of the fluid is obtained by a numerical solution to Stokes or Navier-Stokes equations. We also provide a derivation of the asymptotic expansion for the lubrication force (used in our numerical experiments) acting on a disk immersed in a Newtonian fluid and approaching the wall. The method of this derivation is new and can be easily adapted to other cases

Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics

A 24-member ensemble of 1-h high-resolution forecasts over the Southern United Kingdom is used to study short-range forecast error statistics. The initial conditions are found from perturbations from an ensemble transform Kalman filter. Forecasts from this system are assumed to lie within the bounds of forecast error of an operational forecast system. Although noisy, this system is capable of producing physically reasonable statistics which are analysed and compared to statistics implied from a variational assimilation system. The variances for temperature errors for instance show structures that reflect convective activity. Some variables, notably potential temperature and specific humidity perturbations, have autocorrelation functions that deviate from 3-D isotropy at the convective-scale (horizontal scales less than 10 km). Other variables, notably the velocity potential for horizontal divergence perturbations, maintain 3-D isotropy at all scales. Geostrophic and hydrostatic balances are studied by examining correlations between terms in the divergence and vertical momentum equations respectively. Both balances are found to decay as the horizontal scale decreases. It is estimated that geostrophic balance becomes less important at scales smaller than 75 km, and hydrostatic balance becomes less important at scales smaller than 35 km, although more work is required to validate these findings. The implications of these results for high-resolution data assimilation are discussed

Monte Carlo simulation of a mammographic test phantom

Monte Carlo simulation of a mammographic test phantom A test phantom, including a wide range of mammographic tissue equivalent materials and test details, was imaged on a digital mammographic system. In order to quantify the effect of scatter on the contrast obtained for the test details, calculations of the scatter-to-primary ratio (S/P) have been made using a Monte Carlo simulation of the digital mammographic imaging chain, grid and test phantom. The results show that the S/P values corresponding to the imaging conditions used were in the range 0.0844.126. Calculated and measured pixel values in different regions (if the image were compared as a validation of the model and showed excellent agreement. The results indicate the potential of Monte Carlo methods in the image quality-patient dose process optimisation, especially in the assessment of imaging conditions not available on standard mammographic units

Adaptive Evolution of the Myo6 Gene in Old World Fruit Bats (Family: Pteropodidae)

PMCID: PMC3631194This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Dual Ion Species Plasma Expansion from Isotopically Layered Cryogenic Targets

A dual ion species plasma expansion scheme from a novel target structure is introduced, in which a nanometer thick layer of pure deuterium exists as a buffer species at the target-vacuum interface of a hydrogen plasma. Modelling shows that by controlling the deuterium layer thickness, a composite H +/D+ ion beam can be produced by TNSA, with an adjustable ratio of ion densities, as high energy proton acceleration is suppressed by the acceleration of a spectrally peaked deuteron beam. Particle in cell modelling shows that a (4.3±0.7) MeV per nucleon deuteron beam is accelerated, in a directional cone of half angle 9◦ . Experimentally, this was investigated using state of the art cryogenic targetry and a spectrally peaked deuteron beam of (3.4±0.7) MeV per nucleon was measured in a cone of half angle 7-9◦ , whilst maintaining a significant TNSA proton component

Data assimilation with correlated observation errors: experiments with a 1-D shallow water model

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is needed. In this article, we consider several approaches to approximating observation error correlation matrices: diagonal approximations, eigendecomposition approximations and Markov matrices. These approximations are applied in incremental variational assimilation experiments with a 1-D shallow water model using synthetic observations. Our experiments quantify analysis accuracy in comparison with a reference or ‘truth’ trajectory, as well as with analyses using the ‘true’ observation error covariance matrix. We show that it is often better to include an approximate correlation structure in the observation error covariance matrix than to incorrectly assume error independence. Furthermore, by choosing a suitable matrix approximation, it is feasible and computationally cheap to include error correlation structure in a variational data assimilation algorithm

Three phylogenetic groups have driven the recent population expansion of Cryptococcus neoformans.

Cryptococcus neoformans (C. neoformans var. grubii) is an environmentally acquired pathogen causing 181,000 HIV-associated deaths each year. We sequenced 699 isolates, primarily C. neoformans from HIV-infected patients, from 5 countries in Asia and Africa. The phylogeny of C. neoformans reveals a recent exponential population expansion, consistent with the increase in the number of susceptible hosts. In our study population, this expansion has been driven by three sub-clades of the C. neoformans VNIa lineage; VNIa-4, VNIa-5 and VNIa-93. These three sub-clades account for 91% of clinical isolates sequenced in our study. Combining the genome data with clinical information, we find that the VNIa-93 sub-clade, the most common sub-clade in Uganda and Malawi, was associated with better outcomes than VNIa-4 and VNIa-5, which predominate in Southeast Asia. This study lays the foundation for further work investigating the dominance of VNIa-4, VNIa-5 and VNIa-93 and the association between lineage and clinical phenotype

Quantum-nondemolition criteria in traveling-wave second-harmonic generation

Using the full nonlinear equations of motion, we calculate the quantum-nondemolition (QND) correlations for the traveling-wave second-harmonic generation. We find that, after a short interaction length, these are qualitatively different from results calculated previously using a linearized fluctuation analysis. We demonstrate that, although individual QND criteria can be very good in certain regions, there is no region where all three of the standard criteria are perfect, as has previously been claimed. We also show that only the amplitude quadrature of the output field can be considered as a QND quantity, with the phase quadrature not satisfying all the criteria