Alternating and Modified Alternating Least Squares Applied to Raman Spectra of Finished Gasolines.

Extraction of components from individual refinery streams (e.g., reformates and alkylates) in finished gasoline was undertaken using Raman spectroscopy to characterize the chemical content of the finished product.

Supervised discretization for decluttering classification models.

Presented here is the first demonstration of supervised discretization to 'declutter' multivariate classification data in chemical sensor applications. The performance of multivariate classification models is often limited by the non-informative chemical variance within each target class; decluttering methods seek to reduce within-class variance while retaining between-class variance. Supervised discretization is shown to declutter classes in a manner that is superior to the state-of-the-art External Parameter Orthogonalization (EPO) by constructing a more parsimonious model with fewer parameters to optimize and is, consequently, less susceptible to overfitting and information loss.

Raman Spectroscopy to Enhance Investigative Lead Information in Automotive Clearcoats.

A new method to determine the make and model of a vehicle from an automotive paint sample recovered at the crime scene of a vehicle-related fatality such as a hit-and-run using Raman microscopy has been developed. Raman spectra were collected from 118 automotive paint samples from six General Motors (GM) vehicle assembly plants to investigate the discrimination power of Raman spectroscopy for automotive clearcoats using a genetic algorithm for pattern recognition that incorporates model inference and sample error in the variable selection process. Each vehicle assembly plant pertained to a specific vehicle model.

Analysis of Automotive Paint Smears Using Attenuated Total Reflection Infrared Microscopy.

Paint smears represent a type of automotive paint sample found at a crime scene that is problematic for forensic automotive paint examiners to analyze as there are no reference materials present in automotive paint databases to generate hit-lists of potential suspect vehicles. Realistic paint smears are difficult to create in a laboratory and have also proven challenging to analyze because of the mixing of the various automotive paint layers. A procedure based on an impact tester has been developed to create smears to simulate paint transfer between vehicles during a collision.

Gluten Conformation at Different Temperatures and Additive Treatments.

The effect of temperature (25, 45, and 65 °C) on the gluten secondary structure was investigated by using Fourier transform infrared (FTIR) spectroscopy and modulation of disulfide and hydrogen bonds contributions (100 ppm ascorbic acid (AA), 0.6% diacetyl tartaric acid ester of monoglycerides (DATEM), and 0.25 mM dithiothreitol (DTT)).

Transmission Infrared Microscopy and Machine Learning Applied to the Forensic Examination of Original Automotive Paint.

Alternate least squares (ALS) reconstructions of the infrared (IR) spectra of the individual layers from original automotive paint were analyzed using machine learning methods to improve both the accuracy and speed of a forensic automotive paint examination. Twenty-six original equipment manufacturer (OEM) paints from vehicles sold in North America between 2000 and 2006 served as a test bed to validate the ALS procedure developed in a previous study for the spectral reconstruction of each layer from IR line maps of cross-sectioned OEM paint samples. An examination of the IR spectra from an in-house library (collected with a high-pressure transmission diamond cell) and the ALS reconstructed IR spectra of the same paint samples (obtained at ambient pressure using an IR transmission microscope equipped with a BaF cell) showed large peak shifts (approximately 10 cm) with some vibrational modes in many samples comprising the cohort.

Synthesis and Characterization of -Isopropylacrylamide Microspheres as pH Sensors.

Swellable polymer microspheres that respond to pH were prepared by free radical dispersion polymerization using -isopropylacrylamide (NIPA), ,-methylenebisacrylamide (MBA), 2,2-dimethoxy-2-phenylacetylphenone, -tert-butylacrylamide (NTBA), and a pH-sensitive functional comonomer (acrylic acid, methacrylic acid, ethacrylic acid, or propacrylic acid). The diameter of the microspheres was between 0.5 and 1.

Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils.

The peroxide value of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine peroxide values using field portable and process instrumentation; those efforts presented "best-case scenarios" with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique or combination thereof is best for predicting peroxide values.

EXPRESS: Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils.

The peroxide value (PV) of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine PVs using field portable and process instrumentation; those efforts presented âbest-caseâ scenarios with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique, or combination thereof, is best for predicting PVs.

Swellable Copolymers of -isopropylacrylamide and Alkyl Acrylic Acids for Optical pH Sensing.

Swellable polymers that respond to pH (including a portion of the physiological pH range) have been prepared from -isopropylacrylamide (NIPA) copolymerized with acrylic acid, methacrylic acid, ethacrylic acid or propacrylic acid by dispersion polymerization. When the swellable polymer particles are dispersed in a polyvinyl alcohol (PVA) hydrogel membrane, large changes occur in the turbidity of the membrane (which is measured using an absorbance spectrometer) as the pH of the buffer solution in contact with the hydrogel membrane is varied. The swelling of the NIPA copolymer is nonionic, as the ionic strength of the buffer solution in contact with the PVA membrane was increased from 0.

Differentiation of Edible Oils by Type Using Raman Spectroscopy and Pattern Recognition Methods.

The application of Raman spectroscopy and pattern recognition methods to the problem of discriminating edible oils by type was investigated. Two-hundred and eighty-six Raman spectra obtained from 53 samples spanning 15 varieties of edible oils were collected for 90 s at 2 cm resolution. Employing a Whittaker filter, all Raman spectra were baseline corrected after removing the high-intensity fluorescent background in each spectrum.

Analysis of gentisic acid and related renal cell carcinoma biomarkers using reversed-phase liquid chromatography with water-rich mobile phases.

The problem of longer retention times using water-rich mobile phases in reversed phase liquid chromatography (RPLC) has been addressed using hydrophobic alcohols such as butanol in very low quantities (approximately 0.1%) as the organic modifier. Advantages of water-rich mobile phases in RPLC for the separation of water-soluble and weakly retained compounds are improved separation of congeners and better tuning of RPLC separations.

Transmission infrared imaging microscopy and multivariate curve resolution applied to the forensic examination of automotive paints.

In the forensic examination of automotive paint, each layer of paint is analyzed individually by infrared (IR) spectroscopy. Laboratories in North America typically hand section each layer and present each separated layer to the spectrometer for analysis, which is time consuming. In addition, sampling too close to the boundary between adjacent layers can pose a problem as it produces an IR spectrum that is a mixture of the two layers.

Development of Infrared Library Search Prefilters for Automotive Clear Coats from Simulated Attenuated Total Reflection (ATR) Spectra.

A previously published study featuring an attenuated total reflection (ATR) simulation algorithm that mitigated distortions in ATR spectra was further investigated to evaluate its efficacy to enhance searching of infrared (IR) transmission libraries. In the present study, search prefilters were developed from transformed ATR spectra to identify the assembly plant of a vehicle from ATR spectra of the clear coat layer. A total of 456 IR transmission spectra from the Paint Data Query (PDQ) database that spanned 22 General Motors assembly plants and served as a training set cohort were transformed into ATR spectra by the simulation algorithm.

Development and Validation of High Performance Liquid Chromatographic Method for Determination of Gentisic Acid and Related Renal Cell Carcinoma Biomarkers in Urine.

A reversed phase liquid chromatographic (RPLC) method was developed to simultaneously detect and quantify creatinine, quinolinic acid, gentisic acid and 4-hydroxybenzoic acid in urine. These four bio-markers are present in relatively high concentrations in urine. Using a 5% methanol in water mobile phase with 0.

Chemometric Methods for Estimating the Strain Hardening Modulus in Polyethylene Resins.

The feasibility of using multiway or N-way partial least square (NPLS) methods to estimate physical properties of 1-butene and 1-hexene polyethylene (PE) copolymers directly from multidimensional data obtained from size exclusion chromatography coupled to a Fourier transform infrared detector (SEC FT-IR) was explored. Digital sample sets of horizontal slices (slabs) of two-dimensional data simulating the molecular weight distribution and the corresponding orthogonal FT-IR spectra were correlated to a particular Y-block response using NPLS. The NPLS results were compared to those obtained through separate estimations using various algorithms and exploratory response surface methods.

Library Search Prefilters for Vehicle Manufacturers to Assist in the Forensic Examination of Automotive Paints.

Pattern recognition techniques have been applied to the infrared (IR) spectral libraries of the Paint Data Query (PDQ) database to differentiate between nonidentical but similar IR spectra of automotive paints. To tackle the problem of library searching, search prefilters were developed to identify the vehicle make from IR spectra of the clear coat, surfacer-primer, and e-coat layers. To develop these search prefilters with the appropriate degree of accuracy, IR spectra from the PDQ database were preprocessed using the discrete wavelet transform to enhance subtle but significant features in the IR spectral data.

Boosting the Performance of Genetic Algorithms for Variable Selection in Partial Least Squares Spectral Calibrations.

A genetic algorithm (GA) for variable selection in partial least squares (PLS) regression that incorporates adaptive boosting to identify informative wavelengths in near-infrared (NIR) spectra has been developed. Three studies demonstrating the advantages of incorporating an adaptive boosting routine into a GA that employs the root mean square error of calibration as its fitness function are highlighted: (1) prediction of hydroxyl number of terpolymers from NIR diffuse reflectance spectra; (2) calibration of acetone from NIR transmission spectra of mixtures of water, acetone, t-butyl alcohol and isopropyl alcohol; and (3) determination of the active pharmaceutical ingredients in drug tablets from NIR diffuse reflectance spectra. The performance of the GA with adaptive boosting to select wavelengths was compared with one without adaptive boosting.

Pattern Recognition-Assisted Infrared Library Searching of the Paint Data Query Database to Enhance Lead Information from Automotive Paint Trace Evidence.

Multilayered automotive paint fragments, which are one of the most complex materials encountered in the forensic science laboratory, provide crucial links in criminal investigations and prosecutions. To determine the origin of these paint fragments, forensic automotive paint examiners have turned to the paint data query (PDQ) database, which allows the forensic examiner to compare the layer sequence and color, texture, and composition of the sample to paint systems of the original equipment manufacturer (OEM). However, modern automotive paints have a thin color coat and this layer on a microscopic fragment is often too thin to obtain accurate chemical and topcoat color information.

Evidential significance of automotive paint trace evidence using a pattern recognition based infrared library search engine for the Paint Data Query Forensic Database.

A prototype library search engine has been further developed to search the infrared spectral libraries of the paint data query database to identify the line and model of a vehicle from the clear coat, surfacer-primer, and e-coat layers of an intact paint chip. For this study, search prefilters were developed from 1181 automotive paint systems spanning 3 manufacturers: General Motors, Chrysler, and Ford. The best match between each unknown and the spectra in the hit list generated by the search prefilters was identified using a cross-correlation library search algorithm that performed both a forward and backward search.

Pattern recognition-assisted infrared library searching of automotive clear coats.

Pattern recognition techniques have been developed to search the infrared (IR) spectral libraries of the paint data query (PDQ) database to differentiate between similar but nonidentical IR clear coat paint spectra. The library search system consists of two separate but interrelated components: search prefilters to reduce the size of the IR library to a specific assembly plant or plants corresponding to the unknown paint sample and a cross-correlation searching algorithm to identify IR spectra most similar to the unknown in the subset of spectra identified by the prefilters. To develop search prefilters with the necessary degree of accuracy, IR spectra from the PDQ database were preprocessed using wavelets to enhance subtle but significant features in the data.

Search prefilters to assist in library searching of infrared spectra of automotive clear coats.

Clear coat searches of the infrared (IR) spectral library of the paint data query (PDQ) forensic database often generate an unusable number of hits that span multiple manufacturers, assembly plants, and years. To improve the accuracy of the hit list, pattern recognition methods have been used to develop search prefilters (i.e.

Simulation of attenuated total reflection infrared absorbance spectra: applications to automotive clear coat forensic analysis.

Attenuated total reflection (ATR) is a widely used sampling technique in infrared (IR) spectroscopy because minimal sample preparation is required. Since the penetration depth of the ATR analysis beam is quite shallow, the outer layers of a laminate or multilayered paint sample can be preferentially analyzed with the entire sample intact. For this reason, forensic laboratories are taking advantage of ATR to collect IR spectra of automotive paint systems that may consist of three or more layers.