Research on detection techniques for pattern modifications of playing cards used in illegal gambling operations

We investigated pattern-modified marked cards used in fraudulent gambling cases in Korea. These cards are printed with modifications to some of the repeated marks on the back, revealing the hand on the front and enabling fraudsters to deceive their victims. We proposed a method for identifying the modified part by first enhancing the card's color difference using an image processing technique and then calculating the similarity between the repeated basic patterns with a Siamese network. This method is fast and convenient, as it can determine the deformation with only 1 or 2 cards and can be implemented in mobile applications, allowing law enforcement officers to investigate quickly. The proposed method serves as a useful tool to aid document examiners in making judgments, as it does not require expensive equipment and effectively visualizes the alterations.     

Prevalence and blood concentrations of benzodiazepines and opioids in opioid-positive death investigations in Ontario,Canada, from 2017 to 2021

The aim of this study was to investigate the incidence of benzodiazepines in opioid-positive death investigations, including trends in frequency and combination of drugs, as well as demographic data and blood concentrations, where available. Additionally, naloxone concentrations in polysubstance compared to opioid-only cases were analyzed. This was a retrospective study that consisted of all post-mortem toxicology cases in Ontario, Canada, from January 01, 2017, to December 31, 2021, with an opioid finding in any analyzed autopsy specimen. There were 11,033 death investigations identified. The overall rate of benzodiazepine co-involvement was 54.5%. Males accounted for the majority of cases (71%), and the most affected age group was 30- to 39-year-olds. The most frequently detected opioid was fentanyl and the most frequently detected benzodiazepine was etizolam, which was also the most frequently observed opioid/benzodiazepine combination. Findings related to differences in concentrations of opioids when naloxone was also present were mostly non-significant, except for methadone. The rate of benzodiazepine detection with opioids grew faster than opioid detections overall, potentially due to the increasingly toxic drug supply. Detection of novel psychoactive drugs fluctuated more unpredictably than opioids and benzodiazepines associated with clinical use. These findings can help inform policy decisions by public health agencies in exploring harm reduction efforts, for example, education and drug-checking services.     

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.     

Phenibut screening and quantification with liquid chromatography–tandem mass spectrometry and its application to driving cases

An analytical strategy for identification by an LC–MS/MS multitarget screening method and a suitable LC–MS/MS based quantification were developed for the psychotropic drug phenibut. The samples analyzed were collected during traffic control and were associated with driving under the influence of drugs. A positive sample for phenibut was identified in a single case of driving under the influence. The quantification revealed a drug concentration of 1.9 μg/mL. An interaction with blood alcohol (BAC = 0.10%) was discussed as the explanation of the way of driving and deficit manifestations observed (swaying, nystagmus, quivering of the eyelid, and reddened eyes). According to the available information, the quantified phenibut concentration could be explained by an intake of four tablets (self-reported) during the day containing 250 mg of the drug. Chromatography was performed with a Luna 5 μm C18 (2) 100 A, 150 mm × 2 mm analytical column, and a buffer system consisted of 10 mM ammonium acetate and 0.1% acetic acid (v/v) included in mobile phases marked as A (H₂O/methanol = 95/5, v/v) and B (H₂O/methanol = 3/97, v/v). An effective limit of detection (LOD = 0.002 μg/mL) could be achieved for the multitarget screening method. The quantification of phenibut was performed on a second LC–MS/MS system with LOD/LOQ values of 0.22/0.40 μg/mL. Since phenibut quantification data are rare, the presented information can be used with caution for evaluation of positive cases in the future.     

Effects of language mismatch in automatic forensic voice comparison using deep learning embeddings

In forensic voice comparison, deep learning has become widely popular recently. It is mainly used to learn speaker representations, called embeddings or embedding vectors. Speaker embeddings are often trained using corpora mostly containing widely spoken languages. Thus, language dependency is an important factor in automatic forensic voice comparison, especially when the target language is linguistically very different from that the model is trained on. In the case of a low-resource language, developing a corpus for forensic purposes containing enough speakers to train deep learning models is costly. This study aims to investigate whether a model pre-trained on multilingual (mostly English) corpus can be used on a target low-resource language (here, Hungarian), not represented by the model. Often multiple samples are not available from the offender (unknown speaker). Samples are therefore compared pairwise with and without speaker enrollment for suspect (known) speakers. Two corpora are used that were developed especially for forensic purposes and a third that is meant for traditional speaker verification. Speaker embedding vectors are extracted by the x-vector and ECAPA-TDNN techniques. Speaker verification was evaluated in the likelihood-ratio framework. A comparison is made between the language combinations (modeling, LR calibration, and evaluation). The results were evaluated by Cllr_min and EER metrics. It was found that the model pre-trained on a different language but on a corpus with a significant number of speakers can be used on samples with language mismatch. Sample duration and speaking style also seem to affect the performance.     

Lead isotope measurement of primer gunshot residues and likelihood ratio predictions for forensic cartridge discrimination and individualization in China

Gunshot residues (GSR), cartridge projectiles, and casings are frequently encountered evidence in gun-related forensic investigations. However, in circumstances where the investigation of striation marks is impossible, such as unrecovered or deformed projectiles and cartridge casings, GSR deposited on the hands or clothes of the shooter and victim-related items can provide information to establish a link between the suspect, the firearms used, and the victim. Since the formula of primers used by all cartridge manufacturers in China is identical, links based on the conventional morphological and compositional analysis of GSR are difficult to establish. However, the abundance of lead isotopes in primer components of lead styphnate varies significantly, and a fundamental understanding of these differences may facilitate the validation of primer (p)GSR evidence in forensic investigations. Here, 44 pGSR samples were characterized by Pb isotope ratios of ²⁰⁶Pb/²⁰⁴Pb, ²⁰⁷Pb/²⁰⁴Pb, and ²⁰⁸Pb/²⁰⁴Pb using laser ablation multicollector inductively coupled plasma mass spectrometry. There was no obvious mass fractionation of the lead isotope ratios of the primers from individual cartridges analyzed before and after the shooting process, thereby establishing a basis for the comparison of pGSR and unfired cartridges. Evaluation of the results using univariate likelihood ratio (LR) computations revealed low rates of misleading evidence (<0.53%) The results demonstrated that lead isotope ratio analysis of pGSR and LR predictions can provide a practicable method for forensic cartridge discrimination and individualization.     

Copycatting the smell of death: Deciphering the role of cadaveric scent components used by detection dogs to locate human remains

Human remains detection dogs (HRDD) are commonly used by law enforcement agencies to search for cadavers. Biological material is typically used as a training stimulus, also called aids, to train dogs to recognize the smell of cadavers. While HRDD training approaches have received extensive attention, information remains limited on the olfactory cues used to train them. Here, we aimed to decipher the chemical basis of detection dog olfaction. Five specific objectives were explored to precise whether the composition or the concentration of the training aids drives the HRDDs responses. We recorded the behavioral responses of four HRDDs exposed to different cadaveric-like smells. We found that HRDDs recognized a simplified synthetic aid composed of cadaveric compounds. The lowest concentration at which HRDDs continued to perceive the cadaveric smell was determined. HRDDs were not impacted by slight modifications to the chemical composition of a blend of odors that they have been trained with. HRDDs associated sulfur and nitrogen compounds as human cadaver. Our findings highlight a lack of specificity of HRDDs to cadaveric compounds, which could lead to error of detection. Moreover, all dogs did not positively respond to the same blends, despite being trained with the same aids and procedure. However, we confirmed that dogs could be trained with a simplified blend of molecules. The chemical composition of a training aid has, therefore, high consequences on the performance of the trained animal, and this conclusion opens additional questions regarding olfaction-based detection animals.