Charles K. Bayne

Latent Variable Path Modeling With Partial Least Squares

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Chemical composition of fingerprints for gender determination.

This work investigates the chemical nature of fingerprints to ascertain whether differences in chemical composition or the existence of chemical markers can be used to determine personal traits, such as age, gender, and personal habits. This type of information could be useful for reducing the pool of potential suspects in criminal investigations when latent fingerprints are unsuitable for comparison by traditional methods. Fingertip residue that has been deposited onto a bead was extracted with a solvent such as chloroform. Samples were analyzed by gas chromatography/mass spectrometry (GC/MS). The chemical components identified include fatty acids, long chain fatty acid esters, cholesterol and squalene. The area ratios of ten selected components relative to squalene were calculated for a small preliminary experiment that showed a slight gender difference for three of these components. However, when the experiment was repeated with a larger, statistically designed experiment no significant differences between genders were detected for any of the component ratios. The multivariate Hotellings T2 test that tested all ten-component ratios simultaneously also showed no gender differences at the 5% significance level.

Forensic glass analysis by ICP-MS: a multi-element assessment of discriminating power via analysis of variance and pairwise comparisons

Glass fragments from 81 automobile side windows were collected and analyzed by the FBI Laboratory using ICP-AES in 1991. The FBI selected 9 elements (Al, Ba, Ca, Fe, Mg, Mn, Na, Sr and Ti) to use for discrimination among the glass samples. This multi-element discrimination showed a significant improvement in the discrimination statistics over using only refractive index (RI) measurements. Oak Ridge National Laboratory (ORNL) recently analyzed fragments from 76 of the original side window fragments using inductively coupled plasma mass spectrometry (ICP-MS). The ICP-MS analyses measured 45 elements using a hierarchical sampling scheme to estimate variances due to sampled population (VP), variance due to sample dissolution and within sample heterogeneity (VD), and variance due to replicate measurements (VM). The between-to-within ratio [B/W = VP/(VD + VM)] afforded a measure of the variance within the population to that in the analytical measurement, providing a first approximation of the discriminating power of each element. Florida International University updated the RI measurements on 72 available glass fragments. These RI measurements along with ICP-AES and ICP-MS elemental analyses were used for pairwise comparisons of all possible pairs of the 72 glasses that had a complete set of measurements. The pairwise comparisons used Tukeys HSD method to compare RI and element-by-element discrimination potential of ICP-AES and ICP-MS for analyzing glass in forensic casework.

Practical reporting times for environmental samples.

Preanalytical holding times for environmental samples are specified because chemical and physical characteristics may change between sampling and chemical analysis. For example, the Federal Register prescribes a preanalytical holding time of 14 days for volatile organic compounds in soil stored at 4{degrees}C. The American Society for Testing Materials (ASTM) uses a more technical definition that the preanalytical holding time is the day when the analyte concentration for an environmental sample falls below the lower 99% confidence interval on the analyte concentration at day zero. This study reviews various holding time definitions and suggest a new preanalytical holding time approach using acceptable error rates for measuring an environmental analyte. This practical reporting time (PRT) approach has been applied to nineteen volatile organic compounds and four explosives in three environmental soil samples. A PRT nomograph of error rates has been developed to estimate the consequences of missing a preanalytical holding time. This nomograph can be applied to a large class of analytes with concentrations that decay linearly or exponentially with time regardless of sample matrices and storage conditions.

Estimation procedures and error analysis for inferring the total plutonium (Pu) produced by a graphite-moderated reactor

Abstract Graphite isotope ratio method (GIRM) is a technique that uses measurements and computer models to estimate total plutonium (Pu) production in a graphite-moderated reactor. First, isotopic ratios of trace elements in extracted graphite samples from the target reactor are measured. Then, computer models of the reactor relate those ratios to Pu production. Because Pu is controlled under non-proliferation agreements, an estimate of total Pu production is often required, and a declaration of total Pu might need to be verified through GIRM. In some cases, reactor information (such as core dimensions, coolant details, and operating history) are so well documented that computer models can predict total Pu production without the need for measurements. However, in most cases, reactor information is imperfectly known, so a measurement and model-based method such as GIRM is essential. Here, we focus on GIRMs estimation procedure and its associated uncertainty. We illustrate a simulation strategy for a specific reactor that estimates GIRMs uncertainty and determines which inputs contribute most to GIRMs uncertainty, including inputs to the computer models. These models include a “local” code that relates isotopic ratios to the local Pu production, and a “global” code that predicts the Pu production shape over the entire reactor. This predicted shape is included with other 3D basis functions to provide a “hybrid basis set” that is used to fit the local Pu production estimates. The fitted shape can then be integrated over the entire reactor to estimate total Pu production. This GIRM evaluation provides a good example of several techniques of uncertainty analysis and introduces new reasons to fit a function using basis functions in the evaluation of the impact of uncertainty in the true 3D shape.

Multivariate Analysis of Quality: An Introduction

The authors set out to produce an undergraduate text and reference that focuses on what they feel are the most useful statistical tools encountered by practicing engineers. They succeeded in creating a valuable book rich in experimental design and response surface methods (458 pages, 10 chapters) augmented by standard coverage of quality control (134 pages) but with only minimal treatment of basic probability and statistics (132 pages). This is far more a book on experimental design application in industry than it is a general presentation of modern statistical methods for engineers as found in, for example, the books by Montgomery and Runger (1999) and Ostle, Turner, Hicks, and McElrath (1996). The book’s 5 parts and 18 chapters are as follows:

Elemental analysis of forensic glasses by inductively coupled plasma mass spectrometry

Flat glass is a common type of evidence collected from the scenes of crimes such as burglaries, vandalism, and hit-and- run accidents. The usefulness of such evidence lies in the ability to associate the glass from the scene (or a suspect) to the original source. Physical and chemical analysis of the glass can be used for discrimination between the possible sources of glass. If the sample is large enough, physical attributes such as fracture matches, density, color, and thickness can be employed for comparison between a recovered fragment(s) to the suspect source. More commonly, refractive index (RI) comparisons are employed. Due to the improved control over glass manufacturing processes, RI values often cannot differentiate glasses where approximately 6 - 9% of casework samples are not expected to be distinguished by RI alone even if they originated from different sources. Employing methods such as NAA, XRF, ICP-AES, and ICP-MS for the comparison of trace elemental compositions has been shown to be more discriminating than RI comparisons. The multielement capability and the sensitivity of ICP-AES and ICP-MS provide for excellent discrimination power. In this work, the sources of variability in ICP-MS of glass analysis are investigated to determine possible sources of variation. The sources of variation examined include errors due to sample preparation, instrument accuracy and precision, and interlaboratory reproducibility. Other sources of variation include inhomogeneity across a sheet of glass from the same source. Analysis of variance has been applied to our ICP-MS analysis of NIST standards and to the interlaboratory comparisons of float glass samples collected across a sheet in a production facility. The results of these experiments allows for a more accurate interpretation of forensic glass data and a better understanding of the discriminating power (absolute and practical) of ICP-MS.

Practical Guide to Chemometrics

An introduction for analytic chemists and other scientists who are involved with chemical analysis, to chemometrics, a developing technique that allows access to a greater amount of more reliable analytic information using existing instrumentation, than standard techniques. Focuses on laboratory ins