A 7.6m /25-ft/ extreme environments simulator

Stainless steel cylindrical simulation chamber permits testing equipment under extreme cold, high partial vacuums, and intense solar radiation. Applications include heat balance and temperature distribution studies, investigations of subsystem interactions, tests of attitude control equipment and sensors, and acceptance tests of complete systems

Perturbation expansions for a class of singular potentials

Harrell's modified perturbation theory [Ann. Phys. 105, 379-406 (1977)] is applied and extended to obtain non-power perturbation expansions for a class of singular Hamiltonians H = -D^2 + x^2 + A/x^2 + lambda/x^alpha, (A\geq 0, alpha > 2), known as generalized spiked harmonic oscillators. The perturbation expansions developed here are valid for small values of the coupling lambda > 0, and they extend the results which Harrell obtained for the spiked harmonic oscillator A = 0. Formulas for the the excited-states are also developed.Comment: 23 page

Self-assembly of magnetic biofunctional nanoparticles

Spherical, ferromagnetic FePt nanoparticles with a particle size of 3 nm were prepared by the simultaneous polyol reduction of Fe(acac)3Fe(acac)3 and Pt(acac)2Pt(acac)2 in phenyl ether in the presence of oleic acid and oleylamine. The oleic acid ligands can be replaced with 11-mercaptoundecanoic acid, giving particles that can be dispersed in water. Both x-ray diffraction and transmission electron microscopy indicated that FePt particles were not affected by ligands replacement. Dispersions of the FePt particles with 11-mercaptoundecanoic acid ligands and ammonium counter ions gave self-assembled films consisting of highly ordered hexagonal arrays of particles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87511/2/10Q901_1.pd

Cognitive performance profiles by latent classes of drug use

Background and Objectives: The relationship between substance use and cognitive deficits is complex and requires innovative methods to enhance understanding. The present study is the first to use LCA to examine associations of drug use patterns with cognitive performance. Methods: Cocaine/heroin users (N = 552) completed questionnaires, and cognitive measures. LCA identified classes based on past-month drug use and adjusted for probabilities of group membership when examining cognitive performance. Latent indicators were: alcohol (ALC), cigarettes (CIG), marijuana (MJ), crack smoking (CS), nasal heroin (NH), injection cocaine (IC), injection heroin (IH), and injection speedball (IS). Age and education were included as covariates in model creation. Results: Bootstrap likelihood ratio test (BLRT) supported a 5-class model. Prevalent indicators (estimated probability of over 50%) for each class are as follows: “Older Nasal Heroin/Crack Smokers” (ONH/CS, n = 166.9): ALC, CIG, NH, CS; “Older, Less Educated Polysubstance” (OLEP, n = 54.8): ALC, CIG, CS, IH, IC, and IS; “Younger Multi-Injectors” (MI, n = 128.7): ALC, CIG, MJ, IH, IC, and IS; “Less Educated Heroin Injectors” (LEHI, n = 87.4): CIG, IH; and “More Educated Nasal Heroin” users (MENH, n = ALC, CIG, NH. In general, all classes performed worse than established norms and older, less educated classes performed worse, with the exception that MENH demonstrated worse cognitive flexibility than YMI. Discussion and Conclusions: This study demonstrated novel applications of a methodology for examining complicated relationships between polysubstance use and cognitive performance. Scientific Significance: Education and/or nasal heroin use are associated with reduced cognitive flexibility in this sample of inner city drug users

Variational analysis for a generalized spiked harmonic oscillator

A variational analysis is presented for the generalized spiked harmonic oscillator Hamiltonian operator H, where H = -(d/dx)^2 + Bx^2+ A/x^2 + lambda/x^alpha, and alpha and lambda are real positive parameters. The formalism makes use of a basis provided by exact solutions of Schroedinger's equation for the Gol'dman and Krivchenkov Hamiltonian (alpha = 2), and the corresponding matrix elements that were previously found. For all the discrete eigenvalues the method provides bounds which improve as the dimension of the basis set is increased. Extension to the N-dimensional case in arbitrary angular-momentum subspaces is also presented. By minimizing over the free parameter A, we are able to reduce substantially the number of basis functions needed for a given accuracy.Comment: 15 pages, 1 figur

Synthesis and magnetic properties of CoPt nanoparticles

High magnetocrystalline anisotropy CoPt particles with an average size of 8 nm were synthesized by the superhydride reduction of CoCl2CoCl2 and Pt(acac)2Pt(acac)2 at a high temperature. As-made particles showed a disordered face-centered cubic lattice and were superparamagnetic. Upon heat treatment at temperatures above 600 °C, the particles transformed to the L10L10 phase, as indicated by the appearance of the superlattice peaks in the x-ray diffraction and high magnetocrystalline anisotropy. The temperature dependence of the coercivity of nanoparticles annealed at 650 °C was measured from 10 to 300 K and analyzed using a Sharrock formula. After annealing at 650 °C, the anisotropy of the nanoparticles was K∼1.7×107 erg/cm3.K∼1.7×107 erg/cm3. © 2004 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69714/2/JAPIAU-95-11-6747-1.pd

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

First Multicharged Ion Irradiation Results from the CUEBIT Facility at Clemson University

A new electron beam ion trap (EBIT) based ion source and beamline were recently commissioned at Clemson University to produce decelerated beams of multi- to highly-charged ions for surface and materials physics research. This user facility is the first installation of a DREEBIT-designedsuperconducting trap and ion source (EBIS-SC) in the U.S. and includes custom-designed target preparation and irradiation setups. An overview of the source, beamline, and other facilities as well as results from first measurements on irradiated targets are discussed here. Results include extracted charge state distributions and first data on a series of irradiated metal-oxide-semiconductor (MOS) device targets. For the MOS devices, we show that voltage-dependent capacitance can serve as a record of theelectronic component of ion stopping power for an irradiated, encapsulated oxide target

Understanding the Random Displacement Model: From Ground-State Properties to Localization

We give a detailed survey of results obtained in the most recent half decade which led to a deeper understanding of the random displacement model, a model of a random Schr\"odinger operator which describes the quantum mechanics of an electron in a structurally disordered medium. These results started by identifying configurations which characterize minimal energy, then led to Lifshitz tail bounds on the integrated density of states as well as a Wegner estimate near the spectral minimum, which ultimately resulted in a proof of spectral and dynamical localization at low energy for the multi-dimensional random displacement model.Comment: 31 pages, 7 figures, final version, to appear in Proceedings of "Spectral Days 2010", Santiago, Chile, September 20-24, 201

Predicting 6-Year Mortality Risk in Patients With Type 2 Diabetes

OBJECTIVE—The objective of this study was to create a tool that predicts the risk of mortality in patients with type 2 diabetes