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Full-Text Articles in Physical Sciences and Mathematics

Transplanting A Bacterial Immune System: Determining The Function Of A Novel Crispr System, Riannon Smith, Melena Garrett Jan 2018

Transplanting A Bacterial Immune System: Determining The Function Of A Novel Crispr System, Riannon Smith, Melena Garrett

Research on Capitol Hill

CRISPR (Clusters of Regularly Interspaced Short Palindromic Repeats) loci and cas (CRISPR-associated) genes provide adaptive immunity (see panel below) in bacteria and have recently been repurposed for genome editing.

Systems are structurally and functionally diverse.

  • 2 classes, 6 types, 33 subtypes
  • Very few have been studied experimentally
  • None of the Type IV systems have been characterized


Compilation And Comparison Of Electron Penetration Ranges As A Function Of Effective Number Of Valence Electrons, Teancum Quist Apr 2013

Compilation And Comparison Of Electron Penetration Ranges As A Function Of Effective Number Of Valence Electrons, Teancum Quist

Senior Theses and Projects

The continuous-slow-down approximation (CSDA) is used to create a simple composite analytical formula to estimate the range or maximum penetration depth of bombarding electrons into traditional materials including conductors, semiconductors, and insulators. This formula generates an approximation to the range using a single fitting parameter, Nv, described as the effective number of valence electrons. This applicability of the formulation extends to electrons with energies from 10MeV. These calculations are of great value for studies of high electron bombardment, such as electron spectroscopy or the vacuum of space. A list comprised of 187 materials has been collected that greatly …


Electron Penetration Ranges As A Function Of Effective Number Of Valence Electrons, Teancum Quist, Blake Moore, Greg Wilson, Jr Dennison Apr 2013

Electron Penetration Ranges As A Function Of Effective Number Of Valence Electrons, Teancum Quist, Blake Moore, Greg Wilson, Jr Dennison

Posters

The Continuous-Slow-Down Approximation (CSDA) is used to create a simple composite analytical formula to estimate the range or maximum penetration depth of incident electrons into diverse materials including conductors, semiconductors, and insulators. This formula generates an approximation to the range using a single fitting parameter, Nv, described as the effective number of valence electrons. This range of the formulation extends to electrons with energies from <10 eV to >10MeV, with 20% accuracy. A list comprised of 222 materials has been collected that greatly extends the applicability of this model. Several key material constants were compiled for each material, including the atomic …


Detecting A Stochastic Gravitational-Wave Background: The Overlap Reduction Function, Lee Samuel Finn, Shane L. Larson, Joseph D. Romano Jan 2009

Detecting A Stochastic Gravitational-Wave Background: The Overlap Reduction Function, Lee Samuel Finn, Shane L. Larson, Joseph D. Romano

All Physics Faculty Publications

Detection of a gravitational-wave stochastic background via ground or space-based gravitational-wave detectors requires the cross correlation of the response of two or more independent detectors. The cross correlation involves a frequency-dependent factor—the so-called overlap reduction function or Hellings-Downs curve—that depends on the relative geometry of each detector pair, i.e., the detector separations and the relative orientation of their antenna patterns (beams). An incorrect formulation of this geometrical factor has appeared in the literature, leading to incorrect conclusions regarding the sensitivity of proposed detectors to a stochastic gravitational-wave background. To rectify these errors and as a reference for future work we …


Correction Of Bias In Estimating Autocovariance Function, Len-Hong Wu May 1983

Correction Of Bias In Estimating Autocovariance Function, Len-Hong Wu

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The purpose of this thesis was to evaluate a method for reducing the bias of estimation for autocovariance estimators. Two methods are compared, one is the standard method and the other is an adjustment method. The Monte Carlo method is used within comparison.

The bias and the mean squared error of the estimated autocovariance is computed for several time series models and two variations of the adjustment method of estimation. The results indicate some improvement in bias and mean squared error for the new method.