Transformations for compositional data with zeros with an application to forensic evidence evaluation

In forensic science likelihood ratios provide a natural way of computing the value of evidence under competing propositions such as "the compared samples have originated from the same object" (prosecution) and "the compared samples have originated from different objects" (defence). We use a two-level multivariate likelihood ratio model for comparison of forensic glass evidence in the form of elemental composition data under three data transformations: the logratio transformation, a complementary log-log type transformation and a hyperspherical transformation. The performances of the three transformations in the evaluation of evidence are assessed in simulation experiments through use of the proportions of false negatives and false positives

Geochemical wolframite fingerprinting - the likelihood ratio approach for laser ablation ICP-MS data

Wolframite has been specified as a ‘conflict mineral’ by a U.S. Government Act, which obliges companies that use these minerals to report their origin. Minerals originating from conflict regions in the Democratic Republic of the Congo shall be excluded from the market as their illegal mining, trading, and taxation are supposed to fuel ongoing violent conflicts. The German Federal Institute for Geosciences and Natural Resources (BGR) developed a geochemical fingerprinting method for wolframite based on laser ablation inductively coupled plasma-mass spectrometry. Concentrations of 46 elements in about 5300 wolframite grains from 64 mines were determined. The issue of verifying the declared origins of the wolframite samples may be framed as a forensic problem by considering two contrasting hypotheses: the examined sample and a sample collected from the declared mine originate from the same mine (H 1 ), and the two samples come from different mines (H 2 ). The solution is found using the likelihood ratio (LR) theory. On account of the multidimensionality, the lack of normal distribution of data within each sample, and the huge within-sample dispersion in relation to the dispersion between samples, the classic LR models had to be modified. Robust principal component analysis and linear discriminant analysis were used to characterize samples. The similarity of two samples was expressed by Kolmogorov-Smirnov distances, which were interpreted in view of H 1 and H 2 hypotheses within the LR framework. The performance of the models, controlled by the levels of incorrect responses and the empirical cross entropy, demonstrated that the proposed LR models are successful in verifying the authenticity of the wolframite samples

Editorial : new approaches in forensic analytical chemistry

Some place their faith in forensic science to the degree that they are under the impression that it is absolute, infallible and unassailable. In truth it is a manmade construct, dependent on manmade machinery, man-calibrated accuracy, man-led action under manmade protocols and analyzed by man – an altogether human construct (American Academy of Forensic Sciences cited in Pyrek, 2007). People have always strived to discover and understand the world, and the scientific quest to provide explanations fuels technological progress. This drive has fuelled forensic chemistry, where information is obtained through the examination of various evidentialmaterials to assist the justice systempiece together stories of the past. Concurrently, the validity and reliability of the information provided by forensic experts, its ability to discriminate between the standpoints of defense and prosecution, is being questioned and challenged as never before (Pyrek, 2007; Fraser andWilliams, 2009)(...

Direct and indirect alcohol biomarkers data collected in hair samples - multivariate data analysis and likelihood ratio interpretation perspectives

The concentration values of direct and indirect biomarkers of ethanol consumption were detected in blood (indirect) or hair (direct) samples from a pool of 125 individuals classified as either chronic (i.e. positive) and non-chronic (i.e. negative) alcohol drinkers. These experimental values formed the dataset under examination (Table 1). Indirect biomarkers included: aspartate transferase (AST), alanine transferase (ALT), gamma-glutamyl transferase (GGT), mean corpuscular volume of the erythrocytes (MCV), carbohydrate-deficient-transferrin (CDT). The following direct biomarkers were also detected in hair: ethyl myristate (E14:0), ethyl palmitate (E16:0), ethyl stearate (E18:1), ethyl oleate (E18:0), the sum of their four concentrations (FAEEs, i.e. Fatty Acid Ethyl Esters) and ethyl glucuronide (EtG; pg/mg). Body mass index (BMI) was also collected as a potential influencing factor. Likelihood ratio (LR) approaches have been used to provide predictive models for the diagnosis of alcohol abuse, based on different combinations of direct and indirect alcohol biomarkers, as described in “Evaluation of direct and indirect ethanol biomarkers using a likelihood ratio approach to identify chronic alcohol abusers for forensic purposes

Modern Instrumental Limits of Identification of Ignitable Liquids in Forensic Fire Debris Analysis

Forensic fire debris analysis is an important part of fire investigation, and gas chromatography– mass spectrometry (GC-MS) is the accepted standard for detection of ignitable liquids in fire debris. While GC-MS is the dominant technique, comprehensive two-dimensional gas chromatography–mass spectrometry (GC GC-MS) is gaining popularity. Despite the broad use of these techniques, their sensitivities are poorly characterized for petroleum-based ignitable liquids. Accordingly, we explored the limit of identification (LOI) using the protocols currently applied in accredited forensic labs for two 75% evaporated gasolines and a 25% evaporated diesel as both neat samples and in the presence of interfering pyrolysate typical of fire debris. GC-MSD (mass selective detector (MS)), GC-TOF (time-of-flight (MS)), and GC GC-TOF were evaluated under matched conditions to determine the volume of ignitable liquid required on-column for correct identification by three experienced forensic examiners performing chromatographic interpretation in accordance with ASTM E1618-14. GC-MSD provided LOIs of ~0.6 pL on-column for both neat gasolines, and ~12.5 pL on-column for neat diesel. In the presence of pyrolysate, the gasoline LOIs increased to ~6.2 pL on-column, while diesel could not be correctly identified at the concentrations tested. For the neat dilutions, GC-TOF generally provided 2 better sensitivity over GC-MSD, while GC GC-TOF generally resulted in 10 better sensitivity over GC-MSD. In the presence of pyrolysate, GC-TOF was generally equivalent to GC-MSD, while GC GC-TOF continued to show 10 greater sensitivity relative to GC-MSD. Our findings demonstrate the superior sensitivity of GC GC-TOF and provide an important approach for interlaboratory benchmarking of modern instrumental performance in fire debris analysis

Improving discrimination of Raman spectra by optimising preprocessing strategies on the basis of the ability to refine the relationship between variance components

Discrimination of the samples into predefined groups is the issue at hand in many fields, such as medicine, environmental and forensic studies, etc. Its success strongly depends on the effectiveness of groups separation, which is optimal when the group means are much more distant than the data within the groups, i.e. the variation of the group means is greater than the variation of the data averaged over all groups. The task is particularly demanding for signals (e.g. spectra) as a lot of effort is required to prepare them in a way to uncover interesting features and turn them into more meaningful information that better fits for the purpose of data analysis. The solution can be adequately handled by using preprocessing strategies which should highlight the features relevant for further analysis (e.g. discrimination) by removing unwanted variation, deteriorating effects, such as noise or baseline drift, and standardising the signals. The aim of the research was to develop an automated procedure for optimising the choice of the preprocessing strategy to make it most suitable for discrimination purposes. The authors propose a novel concept to assess the goodness of the preprocessing strategy using the ratio of the between-groups to within-groups variance on the first latent variable derived from regularised MANOVA that is capable of exposing the groups differences for highly multidimensional data. The quest for the best preprocessing strategy was carried out using the grid search and much more efficient genetic algorithm. The adequacy of this novel concept, that remarkably supports the discrimination analysis, was verified through the assessment of the capability of solving two forensic comparison problems - discrimination between differently-aged bloodstains and various car paints described by Raman spectra - using likelihood ratio framework, as a recommended tool for discriminating samples in the forensics

Differentiation of oleoresin capsicum sprays based on their capsaicinoid profiles

Oleoresin capsicum (OC) sprays, often referred to as 'pepper sprays', contain a solution of active compounds, exerting an irritating effect on the human body. The active component of OC sprays are capsaicinoids, obtained by extraction from peppers. The profiles (quantitative relations) of natural capsaicinoids depend on the plant material, they were extracted from. Pepper spray is a non-lethal weapon that should only be used for self-defense but is often used by criminals to attack and incapacitate victims. Evidence related to these types of incidents, such as containers, clothes of victims or suspects, as well as traces of substances found at the scene, are submitted to the forensic laboratory. The purpose of the analysis is to identify the ingredients of the preparation (especially active components) and compare the traces found on objects from the victim or the scene of the incident with the preparation from the can or traces found on objects related to the suspect. The study aimed to investigate the possibility of differentiating OC gases based on capsaicinoid profiles recorded in GC-MS analyses. Sixty-four gases from 12 different manufacturers were purchased and tested. The likelihood ratio (LR) approach was applied to the data expressing the relative capsaicinoids contents computed by integrating GC-MS signals. Two hypotheses were assumed that stated either common or different origins of the samples. Several LR models have been developed, and their performance has been controlled by the number of false positives and false negatives as well as empirical cross entropy. The research results showed that differentiation was very successful, with more than 90% of correct responses. The results obtained show that OC sprays may be distinguished, even if they were produced by the same producer presumably if produced using different batches of pepper extract