A model for making project funding decisions at the National Cancer Institute

This paper describes the development of a model for making project funding decisions at The National Cancer Institute (NCI). The American Stop Smoking Intervention Study (ASSIST) is a multiple-year, multiple-site demonstration project, aimed at reducing smoking prevalence. The initial request for ASSIST proposals was answered by about twice as many states as could be funded. Scientific peer review of the proposals was the primary criterion used for funding decisions. However, a modified Delphi process made explicit several criteria of secondary importance. A structured questionnaire identified the relative importance of these secondary criteria, some of which we incorporated into a composite preference function. We modeled the proposal funding decision as a zero-one program, and adjusted the preference function and available budget parametrically to generate many suitable outcomes. The actual funding decision, identified by our model, offers significant advantages over manually generated solutions found by experts at NCI.     

X-band Electron Spin Relaxation Times for Four Aromatic Radicals in Fluid Solution and Comparison with Other Organic Radicals

X-band electron spin relaxation times of BDPA (1:1 α,γ-bisdiphenylene-β-phenylallyl), galvinoxyl 2,6-di-tert-butyl-α-(3,5-di-tert-butyl-4-oxo-2,5-cyclohexadien-1-ylidene)-p-tolyloxy, DPPH (2,2-diphenyl-1-picrylhydrazyl) and thianthrene radicals in fluid solution were measured by electron spin echo and inversion recovery at ambient temperature. Tumbling correlation times are estimated to be in the range of 20–30 ps. In this fast tumbling regime T ₁ ~ T ₂. Relaxation times are compared with previously reported values for symmetrically substituted triarylmethyl, semiquinone, and nitroxide radicals. The concentration dependence of spin lattice relaxation for neutral BDPA in toluene is about 10³ times greater than for anionic trityl radicals in water. T ₁ decreases in the order carbon-center BDPA > galvinoxyl > DPPH > thianthrene. The dominant relaxation mechanisms are proposed to be a local mode for BDPA, spin rotation, local mode and modulation of anisotropic proton hyperfine coupling for galvinoxyl, modulation of anisotropic nitrogen hyperfine for DPPH, and spin rotation plus modulation of anisotropic proton hyperfine coupling for thianthrene.     

Exact and approximate solutions of Schrödinger’s equation for a class of trigonometric potentials

The asymptotic iteration method is used to find exact and approximate solutions of Schrödinger’s equation for a number of one-dimensional trigonometric potentials (sine-squared, double-cosine, tangent-squared, and complex cotangent). Analytic and approximate solutions are obtained by first using a coordinate transformation to reduce the Schrödinger equation to a second-order differential equation with an appropriate form. The asymptotic iteration method is also employed indirectly to obtain the terms in perturbation expansions, both for the energies and for the corresponding eigenfunctions.     

Field-cycled PEDRI imaging of free radicals with detection at 450 mT

This paper describes the design, construction and use of a field-cycled proton-electron double-resonance imaging (FC-PEDRI) system for the detection and imaging of free radicals. The unique feature of this imager is its use of a 450-mT detection magnetic field in order to achieve good image quality and sensitivity. The detection magnetic field is provided by a superconducting magnet, giving high stability and homogeneity. Field cycling is implemented by switching on and off the current in an internal, coaxial, resistive secondary magnet that partially cancels the superconducting magnet's field at the sample; the secondary magnet is actively shielded to avoid eddy currents. EPR irradiation takes place at approximately 5 mT, following which the field is switched to 450 mT in 40 ms for NMR signal detection. Full details of the imager's subsystems are given, and experiments to image the distribution of stable free radical contrast agents in phantoms and in anesthetized rats are described.     

Bayesian wavelet-based analysis of functional magnetic resonance time series

Wavelet methods for image regularization offer a data-driven alternative to Gaussian smoothing in functional magnetic resonance (fMRI) analysis. Their impact has been limited by the difficulties in integrating regularization in the wavelet domain and inference in the image domain, precluding the probabilistic decision on which areas are activated by a task. Here we present an integrated framework for Bayesian estimation and regularization in wavelet space that allows the usual voxelwise hypothesis testing. This framework is flexible, being an adaptation to fMRI time series of a more general wavelet-based functional mixed-effect model. Through testing on a combination of simulated and real fMRI data, we show evidence of improved signal recovery, without compromising test accuracy in image space.