Search NASA⌕ Search

Engineering topics

Thompson, J. R.

Publications and source records attributed to Thompson, J. R..

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Zinc and the iron donor frataxin regulate oligomerization of the scaffold protein to form new Fe–S cluster assembly centers

Early studies of the bacterial Fe–S cluster assembly system provided structural details for how the scaffold protein and the cysteine desulfurase interact. This work and additional work on the yeast and human systems elucidated a conserved mechanism for sulfur donation but did not provide any conclusive insights into the mechanism for iron delivery from the iron donor, frataxin, to the scaffold. We previously showed that oligomerization is a mechanism by which yeast frataxin (Yfh1) can promote assembly of the core machinery for Fe–S cluster synthesis both in vitro and in cells, in such a manner that the scaffold protein, Isu1, can bind to Yfh1 independent of the presence of the cysteine desulfurase, Nfs1. Here, in the absence of Yfh1, Isu1 was found to exist in two forms, one mostly monomeric with limited tendency to dimerize, and one with a strong propensity to oligomerize. Whereas the monomeric form is stabilized by zinc, the loss of zinc promotes formation of dimer and higher order oligomers. However, upon binding to oligomeric Yfh1, both forms take on a similar symmetrical trimeric configuration that places the Fe–S cluster coordinating residues of Isu1 in close proximity of iron-binding residues of Yfh1. This configuration is suitable for docking of Nfs1 in a manner that provides a structural context for coordinate iron and sulfur donation to the scaffold. Moreover, distinct structural features suggest that in physiological conditions the zinc-regulated abundance of monomeric vs. oligomeric Isu1 yields [Yfh1]·[Isu1] complexes with different Isu1 configurations that afford unique functional properties for Fe–S cluster assembly and delivery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Effect of neutron irradiation on the London penetration depth for polycrystalline Bi(1.8)Pb(0.3)Sr2Ca2Cu3O10 superconductor

Magnetization studies of polycrystalline Bi(1.8)Pb(0.3)Sr2Ca2Cu3O10 superconductor, prior to and after neutron irradiation, showed an increase in J(sub c) due to irradiation damage. Analysis of the equilibrium magnetization revealed significant increases in other more fundamental properties. In particular, the London penetration depth increased by approximately 15 percent following irradiation with 8 x 10(exp 16) neutrons/sq cm. Corresponding changes were observed in the upper critical magnetic field H(sub c2). However, the most fundamental thermodynamic property, the superconductive condensation energy F(sub c), was unaffected by the moderate level of neutron-induced damage.

Ossandon, J. G.↗
NASA NTRS1982

A data based random number generator for a multivariate distribution (using stochastic interpolation)

Let X be a K-dimensional random variable serving as input for a system with output Y (not necessarily of dimension k). given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.

Thompson, J. R.↗
NASA NTRS1974

Nonparametric maximum likelihood estimation of probability densities by penalty function methods

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.

Demontricher, G. F.↗
NASA NTRS1974

Classification by means of B-spline potential functions with applications to remote sensing

A method is presented for using B-splines as potential functions in the estimation of likelihood functions (probability density functions conditioned on pattern classes), or the resulting discriminant functions. The consistency of this technique is discussed. Experimental results of using the likelihood functions in the classification of remotely sensed data are given.

Bennett, J. O.↗
NASA NTRS1972

Power spectral density estimation by spline smoothing in the frequency domain

An approach, based on a global averaging procedure, is presented for estimating the power spectrum of a second order stationary zero-mean ergodic stochastic process from a finite length record. This estimate is derived by smoothing, with a cubic smoothing spline, the naive estimate of the spectrum obtained by applying FFT techniques to the raw data. By means of digital computer simulated results, a comparison is made between the features of the present approach and those of more classical techniques of spectral estimation.

Defigueiredo, R. J. P.↗
NASA NTRS1972

Power spectral density estimation by spline smoothing in the frequency domain.

An approach, based on a global averaging procedure, is presented for estimating the power spectrum of a second order stationary zero-mean ergodic stochastic process from a finite length record. This estimate is derived by smoothing, with a cubic smoothing spline, the naive estimate of the spectrum obtained by applying Fast Fourier Transform techniques to the raw data. By means of digital computer simulated results, a comparison is made between the features of the present approach and those of more classical techniques of spectral estimation.-

De Figueiredo, R. J. P.↗