Calculation of electronic properties of amorphous alloys

We describe the application of the locally-self-consistent-multiple-scattering (LSMS)[1] method to amorphous alloys. The LSMS algorithm is optimized for the Intel XP/S-150, a multiple-instruction-multiple-data parallel computer with 1024 nodes and 2 compute processors per node. The electron density at each site is determined by solving the multiple scattering equation for atoms within a specified distance of the atom under consideration. Because this method is carried out in real space it is ideal for treating amorphous alloys. We have adapted the code to the calculation of the electronic properties of amorphous alloys. In these calculations we determine the potentials in the atomic sphere approximation self consistently at each site, unlike previous calculations[2] where we determined the potentials self consistently at an average site. With these self-consistent potentials, we then calculate electronic properties of various amorphous alloy systems. We present calculated total electronic densities of states for amorphous Ni$_{80}$P$_{20}$ and Ni$_{40}$Pd$_{40}$P$_{20}$ with 300 atoms in a supercell.Comment: 10 pages, plain tex, 2 figures. Paper accepted for publication in Proceedings of LAM-9 and Journal of non-Crystalline Solids. Please request preprints from J.C. Swihart ([email protected]

Molecular evolution of the sheep prion protein gene

Transmissible spongiform encephalopathies (TSEs) are infectious, fatal neurodegenerative diseases characterized by aggregates of modified forms of the prion protein (PrP) in the central nervous system. Well known examples include variant Creutzfeldt-Jakob Disease (vCJD) in humans, BSE in cattle, chronic wasting disease in deer and scrapie in sheep and goats. In humans, sheep and deer, disease susceptibility is determined by host genotype at the prion protein gene (PRNP). Here I examine the molecular evolution of PRNP in ruminants and show that variation in sheep appears to have been maintained by balancing selection, a profoundly different process from that seen in other ruminants. Scrapie eradication programs such as those recently implemented in the UK, USA and elsewhere are based on the assumption that PRNP is under positive selection in response to scrapie. If, as these data suggest, that assumption is wrong, eradication programs will disrupt this balancing selection, and may have a negative impact on the fitness or scrapie resistance of national flocks

Autotract: Automatic cleaning and tracking of fibers

We propose a new tool named Autotract to automate fiber tracking in diffusion tensor imaging (DTI). Autotract uses prior knowledge from a source DTI and a set of corresponding fiber bundles to extract new fibers for a target DTI. Autotract starts by aligning both DTIs and uses the source fibers as seed points to initialize a tractography algorithm. We enforce similarity between the propagated source fibers and automatically traced fibers by computing metrics such as fiber length and fiber distance between the bundles. By analyzing these metrics, individual fiber tracts can be pruned. As a result, we show that both bundles have similar characteristics. Additionally, we compare the automatically traced fibers against bundles previously generated and validated in the target DTI by an expert. This work is motivated by medical applications in which known bundles of fiber tracts in the human brain need to be analyzed for multiple datasets

Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications

Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints. Recent developments in support vector machine and metaheuristics show many advantages of these techniques. In particular, particle swarm optimization is now widely used in solving tough optimization problems. In this paper, we use a combination of a recently developed Accelerated PSO and a nonlinear support vector machine to form a framework for solving business optimization problems. We first apply the proposed APSO-SVM to production optimization, and then use it for income prediction and project scheduling. We also carry out some parametric studies and discuss the advantages of the proposed metaheuristic SVM.Comment: 12 page

High performance Beowulf computer for lattice QCD

We describe the construction of a high performance parallel computer composed of PC components, as well as the performance test in lattice QCD.Comment: Lattice 2001 (Algorithms and Machines) 3 page

Axial vector current in an electromagnetic field and low-energy neutrino-photon interactions

An expression for the axial vector current in a strong, slowly varying electromagnetic field is obtained. We apply this expression to the construction of the effective action for low-energy neutrino-photon interactions.Comment: 6 pages, references updated, final version to appear in Phys. Rev.

MultisegPipeline: Automatic tissue segmentation of brain MR images with subject-specific atlases

Automated segmentation and labeling of individual brain anatomical regions is challenging due to individual structural variability. Although, atlas-based segmentation has shown its potential for both tissue and structure segmentation, the inherent natural variability as well as disease-related changes in MR appearance is often inappropriately represented by a single atlas image. In order to have a more accurate representation, several atlases may be used for the segmentation task in a given neuroimaging study. In this paper, we present the MultisegPipeline, it uses multiple atlases that have been visually inspected and capture the expected variability in a neonatal population. The MultisegPipeline transfers the labeled regions from each atlas to the target image using deformable registration (ANTs or QuickSilver is available for this task). Additionally, the set of labels are merged using a label fusion technique that reduces the errors produced by the registration. The final output is a single label map that combines the results produced by all atlases into a consensus solution. In our study, the MultisegPipeline is used to segment brain MR images from 31 infants, a leave-one-out strategy was used to test our framework. The average dice score coefficient was 0.89