Rapid and non-destructive differentiation of Shahtoosh from Pashmina/Cashmere wool using ATR FT-IR spectroscopy

Shahtoosh, the most expensive and sought-after wool in the illegal wildlife trade is obtained from the underfur of a critically endangered species-the Tibetan Antelope (Pantholops hodgsonii). It is often adulterated or mixed with the wool of Pashmina goat (Capra aegagrus hircus) for making shawls, scarves and other woolen articles to maximize the profit. The comparable fineness, color and texture, makes it a challenging task in wildlife forensics to differentiate them. In this study, an attempt has been made to differentiate 50 reference unprocessed underfur hairs from five individuals of each species using ATR FT-IR spectroscopy in combination with chemometric tools such as PCA, and PLS-DA. Results of PCA model demonstrated slight overlap and thus failed to distinguish hairs of these two species. Subsequently, PLS-DA model was employed, and also validation tests (external and blind testing) were carried out to ensure the predictive ability of the model, which resulted in 100% accuracy. The results of PLS-DA model exhibited complete differentiation between Shahtoosh, Pashmina and Angora (Oryctolagus cuniculus domesticus) wool used for external validation study with highly significant predictive ability (R-square value 0.99). This proof-of-concept study illustrates the potential of ATR FT-IR spectroscopy to complement current forensic microscopic and DNA based technique to analyze hair evidence in wildlife investigations owing to its rapid and non-destructive nature with high degree of confidence, and its ease-of-use with minimal to no sample preparation.     

Rapid and nondestructive analysis of lipstick on different substrates using ATR-FTIR spectroscopy and chemometrics

Lipstick can be an important piece of evidence in crimes like murders, rapes, and suicides. Due to its prevalence, it can be an important corroborative evidence in crime reconstruction. The analysis of such evidence can provide an evidentiary link between the suspect, the victim, object, or the crime scene. We report the use of nondestructive ATR-FTIR spectroscopy combined with chemometrics for the classification of 10 brands of lipsticks with nine samples each. Chemometric method of partial least square-discriminant analysis (PLS-DA) has been employed to interpret the data and classify the samples into their respective classes. The PLS-DA model provides an AUC figure above 0.99 in all brands except one; for which it is slightly less at 0.94. We have also tested the traces of these lipstick samples on different substrates treating them as unknowns in the already trained PLS-DA model. 100% of the samples on nine substrates viz. a cotton, nylon, plastic, dry tissue, denim (blue jeans), wet tissue, nitrile gloves, white paper, and polyester were correctly attributed to their source brand. In conclusion, the results suggest that ATR-FTIR combined with the chemometrics is a rapid, nondestructive, and accurate method for the discrimination and source attribution of lipstick. This study has potential for use in actual forensic casework conditions.     

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm(-1) and 2730-3600 cm(-1), provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.     

Rapid and non-destructive identification of claws using ATR-FTIR spectroscopy–A novel approach in wildlife forensics

Differentiation and identification of Royal Bengal Tiger (Panthera tigris tigris) and Indian Leopard (Panthera pardus fusca) claws is a challenging task in wildlife forensics, due to similarity in their morphology, anatomy and chemical compositions as both the species are closely related to each other genetically. ATR-FTIR spectroscopy, which offers a non-destructive and safe alternative technique to other conventional methods, has been employed in the present work to differentiate claws of Royal Bengal Tiger and Indian Leopard. An attempt has been made to differentiate 31 reference claw samples from 16 different Royal Bengal Tigers, 15 different Indian Leopards, and 10 fake claws using ATR-FTIR spectroscopy supplemented with PCA, PLS-DA, and LDA. PCA could not distinguish the samples of two closely related species among themselves as well as from the fake claws. On the other hand, PLS-DA and LDA models both yielded highly significant classification rate for differentiation among the samples of Royal Bengal Tiger, Indian Leopard, and their fake counterparts. Further, seven blind claw samples that were pretended to be unknown to the analyst of both the species are also examined and identified correctly to their respective groups. The R-Square value obtained for PLS-DA model to differentiate Royal Bengal Tiger, Indian Leopard, and fake claws is 0.99, which is highly significant for predictive accuracy. This study shows that ATR-FTIR spectroscopy with PLS-DA/LDA has a potential to present a rapid, non-destructive, reliable, and eco-friendly approach for the accurate identification and differentiation of Royal Bengal Tiger and Indian Leopard claws.     

Evaluation of genetic markers for the analysis of THC levels of Cannabis sativa samples using principal component analysis – A preliminary study

Cannabis sativa is a worldwide commercial plant used for medicinal purposes, food and fiber production, and also as a recreational drug. Therefore, the identification and differentiation between legal and illegal C. sativa is of great importance for forensic investigations. In this study, principal component analysis (PCA), an exploratory data analysis technique, was tested to correlate the specific genotype with the concentration of tetrahydrocannabinol (THC) in the samples. C. sativa samples were obtained from legal growers in Piedmont, Italy, and from illegal drug seizures in the Turin region. DNA was extracted, quantified, amplified with a 13-loci multiplex STR and finally analyzed with an automated sequencer. The results showed a trend in the analyzed samples as they differed by their THC content and allele profiles. PCA yielded two clusters of samples that differed by specific allele profiles and THC concentrations. Further validation studies are needed, but this study could provide a new approach to forensic investigation and be a valuable aid to law enforcement in significant marijuana seizures or in tracing illicit drug trafficking routes.     

Investigation of the new possibility of mathematical processing of Raman spectra for dating documents

The use of spectral analysis methods to determine the age of writing inks is an important forensic task. However, the use of spectral data for this purpose has a number of limitations and difficulties. This paper considers the application of the Raman spectroscopy method to an urgent forensic task. The known mechanisms of dye degradation are analyzed; Raman bands are identified that are related to the age of the sample. In a sample of 5 randomly selected writing inks, temporary markers were identified. Narrow sections of Raman spectra containing characteristic lines were used for analysis. It was shown that processing narrow sections of the Raman spectra using the PCA chemometric method allowed the separation of writing inks into groups (clusters) corresponding to different creation intervals.     

Automatic forensic face recognition from digital images.

Digital image evidence is now widely available from criminal investigations and surveillance operations, often captured by security and surveillance CCTV. This has resulted in a growing demand from law enforcement agencies for automatic person-recognition based on image data. In forensic science, a fundamental requirement for such automatic face recognition is to evaluate the weight that can justifiably be attached to this recognition evidence in a scientific framework. This paper describes a pilot study carried out by the Forensic Science Service (UK) which explores the use of digital facial images in forensic investigation. For the purpose of the experiment a specific software package was chosen (Image Metrics Optasia). The paper does not describe the techniques used by the software to reach its decision of probabilistic matches to facial images, but accepts the output of the software as though it were a 'black box'. In this way, the paper lays a foundation for how face recognition systems can be compared in a forensic framework. The aim of the paper is to explore how reliably and under what conditions digital facial images can be presented in evidence.     

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.     

Differentiation of Cosmetic Foundation Creams Using Attenuated Total Reflection Fourier-Transform Infrared Spectroscopy: A Rapid and NonDestructive Approach in Trace Evidence Analysis

Cosmetic foundation creams are encountered as evidentiary material in criminal investigations, particularly in cases related to sexual and physical assault against women. Analyzing foundation cream exhibit is a challenging task as the exhibit is recovered in trace quantity with similar hue. In the present study, ATR FTIR spectroscopy which is a rapid, nondestructive, sensitive, reliable, and safe alternative to other analytical techniques has been used to differentiate 31 cosmetic foundation creams belonging to 23 different brands supported by chemometric methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). The discriminating power of visual analysis is found to be 98.0%, while PCA and LDA further increased the discriminating power to 99.3% and 100%, respectively. The blind test is conducted with three unknown samples (pretended to be unknown to the analyst), which were correctly linked with their respective source. Further, the effect of substrate such as tissue paper (dry and wet) and white cotton cloth during sample analysis are also examined to simulate the actual forensic casework conditions. The stains on substrates could be identified and linked to its parent product as well. The reported method provides significant results for the differentiation of cosmetic foundation creams.     

A psychometric evaluation of the Defence Style Questionnaire-40 in a UK forensic patient population

Psychological defence mechanisms have been considered important personality processes in the onset, maintenance and recovery of mental disorders. More recently, their application to understanding presenting problems and as potential outcome indicators for forensic patients has been recommended. However, to date there have been no investigations into the reliability and factor structure of defence mechanism assessments for this population. The current study investigated the factor structure, internal consistency and test-retest reliability of the Defence Style Questionnaire-40 (DSQ) for 160 adult male UK forensic patients. The three-factor model of defences proposed by the DSQ-40 developers was not confirmed in the study sample. Reliability indices of the three factors indicated that the Immature factor was the most ‘acceptable’ in terms of internal consistency. Test-retest reliability coefficients ranged from .70 to .91. A revised three-factor structure that closely corresponds to the original validation study is recommended following an exploratory factor analysis. The findings are compared with previous reliability and factor analytic evaluations of the DSQ-40, and recommendations for its use with forensic patients are discussed.     

Discrimination of phenethylamine regioisomers and structural analogues by Raman spectroscopy

In this study, the Raman spectra of 21 phenethylamines were obtained using far‐red excitation (785 nm). The distinguishing ability of Raman for phenethylamines, especially for phenethylamine regioisomers and structural analogues, was investigated. Here, the evaluation of a cross section of Raman spectra demonstrated that all types of phenethylamines were distinguishable, even for certain structural analogues with high spectrum similarity. Raman exhibited high distinguishing ability for phenethylamine regioisomers that differ in the substitution position of halogen, methoxy, alkyl, or other substituted groups; as well as for structural analogues containing different groups, such as furanyl, 2,3‐dihydrofuranyl, halogen, and alkyl substituted at the same position. The Raman spectra for homologues with differences in only a methyl group were found to be highly similar; however, their spectra demonstrated small but detectable differences. Four analogue mixtures and 59 seized samples were also analyzed to study the practical use of the Raman method in forensic field. 95% of the seized samples were correctly identified, which significantly validated the ability of Raman method in identifying the correct isomers. Accordingly, this study provides a non‐destructive, high‐throughput and minimal sample preparation technique for the discrimination of phenethylamines.     

Multivariate analysis ('forensiometrics')--a new tool in forensic medicine. Findings on the victim of sharp-force homicide can predict the inter-relationship with the perpetrator.

A multivariate 'forensiometric' technique (PLS-DA) was used to create a model to predict the relationship between homicide victim and perpetrator on a five-level scale: strangers, acquaintances, drinking companions, relatives and spouses. The model is based on findings on the victim and at the venue, and uses the following ten variables as 'predictors', listed in falling order of covariation with instances of close relationship between victim and perpetrator: Victim found in home, female victim, a single sharp injury, injuries to the upper extremity, superficial sharp injuries to the chest ('scratches'), ten or more sharp injuries, presence of defence injuries, total number of sharp injuries, male victim, and victim found outdoors. The model was based on 87 sharp-force homicides (the model-set) and was validated on another set of 43 sharp-force homicides (the test-set). In this test-set validation, 17 of 39 cases (44%) were correctly predicted according to the results of earlier combined forensic and police investigations, and a prediction one step away from the correct level was given in another 17 cases. These results were significantly better than would have been obtained by chance.     

Variation of δ2H, δ18O & δ13C in crude palm oil from different regions in Malaysia: Potential of stable isotope signatures as a key traceability parameter

A total of 33 crude palm oil samples were randomly collected from different regions in Malaysia. Stable carbon isotopic composition (δ¹³C) was determined using Flash 2000 elemental analyzer while hydrogen and oxygen isotopic compositions (δ²H and δ¹⁸O) were analyzed by Thermo Finnigan TC/EA, wherein both instruments were coupled to an isotope ratio mass spectrometer. The bulk δ²H, δ¹⁸O and δ¹³C of the samples were analyzed by Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Unsupervised HCA and PCA methods have demonstrated that crude palm oil samples were grouped into clusters according to respective state. A predictive model was constructed by supervised OPLS-DA with good predictive power of 52.60%. Robustness of the predictive model was validated with overall accuracy of 71.43%. Blind test samples were correctly assigned to their respective cluster except for samples from southern region. δ¹⁸O was proposed as the promising discriminatory marker for discerning crude palm oil samples obtained from different regions. Stable isotopes profile was proven to be useful for origin traceability of crude palm oil samples at a narrower geographical area, i.e. based on regions in Malaysia. Predictive power and accuracy of the predictive model was expected to improve with the increase in sample size. Conclusively, the results in this study has fulfilled the main objective of this work where the simple approach of combining stable isotope analysis with chemometrics can be used to discriminate crude palm oil samples obtained from different regions in Malaysia. Overall, this study shows the feasibility of this approach to be used as a traceability assessment of crude palm oils.     

Raman Spectroscopy as a Simple,Rapid, Nondestructive Screening Test for Methamphetamine in Clandestine Laboratory Liquids

Raman spectroscopy has found increased use in the forensic controlled substances laboratory in recent years due to its rapid and nondestructive analysis capabilities. Here, Raman spectroscopy as a screening test for methamphetamine in clandestine laboratory liquid samples is discussed as a way to improve the efficiency of a laboratory by identifying the most probative samples for further workup among multiple samples submitted for analysis. Solutions of methamphetamine in ethanol, diethyl ether, and Coleman fuel were prepared in concentrations ranging from 0.5% to 10% w/v, and Raman spectra of each were collected. A concentration‐dependant Raman peak was observed at 1003 per cm in each solution in 4% w/v and greater solutions. Case samples were analyzed and also found to reliably contain this diagnostic peak when methamphetamine was present. The use of this diagnostic indicator can save the forensic controlled substances laboratory time and materials when analyzing clandestine laboratory liquid submissions.     

Characterization of Blue Pigments Used in Automotive Paints by Raman Spectroscopy

Micro‐Raman spectroscopy was applied to forensic identification of pigments in paint chips and provided differentiation between paint samples. Sixty‐six blue automotive paint samples, 26 solid and 40 metallic were examined. It was found that the majority of the collected Raman spectra provided information about the pigments present. However, in some cases, fluorescence precluded pigment identification. Using laser excitation at longer wavelengths or pretreatment to effect photobleaching often resulted in reduced fluorescence, particularly for solid color samples, and allowed pigment identification. The examined samples were compared pairwise taking into account number, location, and intensity of absorption bands in their infrared spectra. The estimated discrimination power ranged from 97% for solid paint samples to 99% for metallic paint samples.     

Analysis of friction ridge evidence for trace amounts of paracetamol in various pharmaceutical industries by Raman spectroscopy

The detection of potentially harmful substances presents a multifaceted challenge. On one hand, it can directly save lives, on the other, it can significantly aid and enhance police work, thereby increasing the effectiveness of investigations. The research conducted in this study primarily aims to identify paracetamol in fingerprints, considering situations involving direct contact of a person with paracetamol either chronically or in a single dose. The identification procedure presented, utilizing Raman spectroscopy, aims to rapidly detect the xenobiotic following ingestion by an individual, which involves touching the tablet with their fingers—this can be termed as touch evidence in forensic science investigations. Additionally, the authors focus on assessing the impact of additives present in drugs containing paracetamol as the main active ingredient. The screening results obtained will enable us to analyze the composition of drugs in terms of potentially toxic substances, and their influence on the physicochemical activity of the active substance. We successfully identified the paracetamol molecule using a noninvasive forensic trace detection method. Samples in the form of common drugs containing 500 mg of paracetamol were studied. Throughout the study, comprehensive validation of the method was ensured through the utilization of a statistical model, which excluded sensitivity to the presence of other substances, whether additives or from the external environment. The proposed approach to trace the content of substances in fingerprint using Raman scattering analysis provides a useful starting point to enhance current analytical methods not only in forensic science but also in toxicology.     

A multivariate statistical approach to for the evaluation of the biogeographical ancestry information from traditional STRs

The capability to achieve biogeographic ancestry (BGA) information from DNA profiles have been largely explored in forensic genetics because of its potential usefulness in providing investigative clues. For law enforcement and security purposes, when genetic data have been obtained from unknown evidence, but no reference samples are available and no hints come out from DNA databases, it would be extremely useful at least to infer the ethno-geographic origin of the stain donor by just examining traditional STRs DNA profiles.Current protocols for ethnic origin estimation using STRs profiles are usually based on Principal Component Analysis approaches and Bayesian methods. The present study provides an alternative approach that involves the use of target multivariate data analysis strategies for estimation of the BGA information from unknown biological traces. A powerful multivariate technique such as Partial Least Squares-Discriminant Analysis (PLS-DA) has been applied on NIST U.S. population datasets containing, for instance, the allele frequencies of African-American, Asian, Caucasian and Hispanic individuals. PLS-DA approach provided robust classifications, yielding high sensitivity and specificity models capable of discriminating the populations on ethnic basis. Finally, a real casework has been examined by extending the developed model to smaller and more geographically-restricted populations involving, for instance, Albanian, Italian and Montenegrian individuals.     

In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science

The emergence of new psychoactive substances (NPS) has raised many issues in the context of law enforcement and public drug policies. In this scenario, interdisciplinary studies are crucial to the decision-making process in the field of criminal science. Unfortunately, information about how NPS affect people's health is lacking even though knowledge about the toxic potential of these substances is essential: the more information about these drugs, the greater the possibility of avoiding damage within the scope of a harm reduction policy. Traditional analytical methods may be inaccessible in the field of forensic science because they are relatively expensive and time-consuming. In this sense, less costly and faster in silico methodologies can be useful strategies. In this work, we submitted computer-calculated toxicity values of various amphetamines and cathinones to an unsupervised multivariate analysis, namely Principal Component Analysis (PCA), and to the supervised techniques Soft Independent Modeling of Class Analogy and Partial Least Square-Discriminant Analysis (SIMCA and PLS-DA) to evaluate how these two NPS groups behave. We studied how theoretical and experimental values are correlated by PLS regression. Although experimental data was available for a small amount of molecules, correlation values reproduced literature values. The in silico method efficiently provided information about the drugs. On the basis of our findings, the technical information presented here can be used in decision-making regarding harm reduction policies and help to fulfill the objectives of criminal science.     

Three-dimensional computer visualization of forensic pathology data

Despite a decade of use in US courtrooms, it is only recently that forensic computer animations have become an increasingly important form of communication in legal spheres within the United Kingdom. Aims Research at the University of Nottingham has been influential in the critical investigation of forensic computer graphics reconstruction methodologies and techniques and in raising the profile of this novel form of data visualization within the United Kingdom. The case study presented demonstrates research undertaken by Aims Research and the Department of Forensic Pathology at the University of Sheffield, which aims to apply, evaluate, and develop novel 3-dimensional computer graphics (CG) visualization and virtual reality (VR) techniques in the presentation and investigation of forensic information concerning the human body. The inclusion of such visualizations within other CG or VR environments may ultimately provide the potential for alternative exploratory directions, processes, and results within forensic pathology investigations.     

Multivariate analysis (`Forensiometrics')—A new tool in forensic medicine: Differentiation between sharp force homicide and suicide

Multivariate projective statistical methods (PCA, PLS-DA) and logistic regression analysis were used to create models to make predictions regarding whether a certain fatality shows similarities to homicide or suicide. The `model set' consisted of 174 deaths due to sharp force injuries that in previous medicolegal investigation had been judged as homicides and 105 as suicides. The models were then validated on a new set of 40 homicides and 27 suicides that had not been used to create the models (test set validation). The model based on the PLS-DA technique had regarding its ability to identify homicides a sensitivity of 40/40=100% and a specificity of 25/27=93%. The model's predictions agreed with previously performed medicolegal investigations except in two suicides which according to the model were likely to be homicides. The reliability of this model was somewhat better than predictions achieved by means of logistic regression analysis, where six otherwise proven homicides were wrongly classified as suicides and two actual suicides were misclassified as homicides. The technique not only identifies variables but also ranks their importance. Ranked according to falling positive correlation (falling `importance' of a finding) to the dependent variable `death caused by homicide', the predictors were: Injuries to clothing, blood alcohol level, presence of defence injuries, injuries due to other type of violence than sharp force, chest stabs with vertical axis of the entrance wound, sharp force injuries to the upper extremity (except wrist and crook of the arm), sharp force injuries to the head and back. Ranked in increasing positive correlation to `death caused by suicide' were the predictors: sharp force injuries to the crook of the arm, venue being the victim's home, presence of farewell letter, victim's age, sharp force injuries to the wrist, known suicidal ideation and presence of tentative injuries.