Forensic science international最新文献

A growing number of studies in forensic voice comparison have explored how elements of phonetic analysis and automatic speaker recognition systems may be integrated for optimal speaker discrimination performance. However, few studies have investigated the evidential value of long-term speech features using forensically-relevant speech data. This paper reports an empirical validation study that assesses the evidential strength of the following long-term features: fundamental frequency (F0), formant distributions, laryngeal voice quality, mel-frequency cepstral coefficients (MFCCs), and combinations thereof. Non-contemporaneous recordings with speech style mismatch from 75 male Australian English speakers were analyzed. Results show that 1) MFCCs outperform long-term acoustic phonetic features; 2) source and filter features do not provide considerably complementary speaker-specific information; and 3) the addition of long-term phonetic features to an MFCCs-based system does not lead to meaningful improvement in system performance. Implications for the complementarity of phonetic analysis and automatic speaker recognition systems are discussed.

From the beginnings of Silk Road in 2011, anonymous online marketplaces have continued to grow despite the best efforts of law enforcement. While these ever-present marketplaces remain flooded with illicit drugs and related paraphernalia, the sale and distribution of fraudulent identity documents remains a persistent problem, with these items consistently appearing for sale on both the open and dark web. While fraudulent Australian documents are some of the most popular products for sale, there is still much that is unknown about the Australian criminal market and its place within anonymous online marketplaces. Given the success of previous research in understanding the illicit drug trade through examining these marketplaces, this work examines two markets to gain an understanding of where Australian document fraud sits within this digital ecosystem. Two anonymous online marketplaces were crawled across 2020 and 2021, White House Market (WHM), and Empire Market. This data was extracted and examined to identify trends within both the international online market and the online market specifically for Australian documents, both of which have been relatively underexplored in the online space. To help illuminate the features of the market, the types of documents for sale, supply and demand trends, and trafficking flows along with vendor-related trends (e.g. product diversification and presence across markets) were examined. Each market was examined individually and then, where possible, comparisons were drawn to gain a more holistic understanding of the online fraudulent document market, with a specific focus on Australian products. Results indicate that, while the fraudulent document portion of the market is small, it is diverse, with numerous different identity-related products for sale, the most common being driver’s licences from the United States (U.S.) and Australia, with digital documents dominating the whole marketplace. Overall, the most popular U.S. products were those that could be used to facilitate identity fraud, with the most popular Australian products being driver’s licences and ID packs, likely linked to the presence of the 100-point identity check system used in Australia. This study demonstrates that anonymous online marketplaces have thus far been under-utilised in the study of the fraudulent document market, and that to properly understand the illicit market for fraudulent documents and personal information both the online and physical sides of the market should be considered. This information, if properly utilised, can improve the current understanding of this persistent criminal environment, building on previous research and assisting policymakers in making informed decisions.

An improved automated bloodstain pattern analysis method has been developed and validated, which utilises computer vision techniques to identify bloodstains on a plain background within a digital image. The method generates metrics relating to the individual stains as well as the overall pattern, including bloodstain pattern specific metrics such as the gamma angle, circularity, solidity, area of convergence, stain density and pattern linearity. This method provides an objective approach to the analysis of bloodstains and bloodstain patterns and can generate a wealth of quantitative data that is currently not obtainable using manual techniques or other image-based programs currently utilised in the discipline. This method will be useful to analysts and researchers investigating the application of quantitative methods to bloodstain pattern analysis.

Knowledge of opioid tolerance in a deceased person is important for distinguishing between therapeutic and toxic opioid concentrations for that particular individual when interpreting postmortem toxicological results. However, no biomarkers for opioid tolerance are currently available. This review aimed to study the existing literature on mechanisms or changes in signaling pathways related to chronic opioid use, which could be relevant for further studies to identify biomarkers for opioid tolerance. We performed a systematic literature search using the PRISMA 2020 guidelines using the MeSH terms "opioid tolerance AND biomarkers” in PubMed, Embase, WebofScience, and the Cochrane library. A review of the search results yielded seven studies on animal models or humans, identifying and evaluating thirteen possible biomarkers in terms of specificity for changes induced by opioids and other aspects to be considered as potential biomarkers. We evaluated nine potential biomarkers as unlikely to be specific for opioid tolerance, and one had contradictory results in terms of upregulation or downregulation. However, methylation of the promoter region of the μ-opioid receptor gene, increased activity of soluble puromycin-sensitive aminopeptidase, altered miRNA profile, or other multiple component profiling may be interesting to study further as biomarkers for opioid tolerance in forensic postmortem cases.

Evaluating sharp force trauma (SFT) injuries to bone inflicted by a larger class of chopping/hacking tools (i.e., swords, axes, hatchets, machetes, and cleavers) is a growing area within the field of forensics. Previous studies have demonstrated promise regarding tool differentiation through the utilization of microscopic cut mark characteristics. However, this is an area that warrants additional investigation as there has yet to be a comprehensive study that incorporates the majority of these microscopic chopping/hacking cut mark characteristics into one analysis. The purpose of the current research was to analyze a large sample of microscopic cut mark characteristics derived from the current chopping/hacking literature to determine if differentiation of tool type could be made based on the microscopic cut mark characteristics. An additional goal of the current research is to develop standardization guidelines for the assessment of cut marks, focusing on a comprehensive suite of microscopic cut mark characteristics commonly observed in the existing literature. The skeletal sample for the current research was derived from a previous macroscopic cut mark characteristic experiment where trauma was inflicted to 20 partially fleshed domestic pig (Sus scrofa domesticus) limbs utilizing four chopping/hacking tools (i.e., axe, hatchet, machete, and cleaver) as well as a large carving knife for comparison. Cut marks were evaluated for 15 microscopic cut mark characteristics to assess statistical significance. Utilizing a chi-square analysis, nine of the 15 microscopic cut mark characteristics demonstrated statistically significant differences in relation to the tool utilized, indicating moderate to relatively strong effect sizes. For example, it should be possible to use a combination of microscopic cut mark characteristics to potentially indicate which chopping/hacking tool inflicted trauma when analyzing bones. In particular, examining the characteristics such as regularity of the cut mark edges along with the occurrence of uprising, fossae/depressions, and microscopic fractures can suggest or exclude tool class within forensic contexts.

High Kinetic Energy Ion Mobility Spectrometry (HiKE-IMS) is a technique for rapid and reliable detection of trace compounds down to ppb_V-levels within one second. Compared to classical IMS operating at ambient pressure and providing the ion mobility at low electric fields, HiKE-IMS can also provide the analyte-specific field dependence of the ion mobility and a fragmentation pattern at high reduced electric field strengths. The additional information about the analyte obtained by varying the reduced electric field strength can contribute to reliable detection. Furthermore, the reduced number of ion-molecule reactions at the low operating pressure of 10 – 40 mbar and the shorter reaction times reduce the impact of competing ion-molecule reactions that can cause false negatives. In this work, we employ HiKE-IMS for the analysis of phenyl-2-propanone (P2P) and other precursor chemicals used for synthesis of methamphetamine and amphetamine. The results show that the precursor chemicals exhibit different behavior in HiKE-IMS. Some precursors form a single significant ion species, while others readily form a fragmentation pattern. Nevertheless, all drug precursors can be distinguished from each other, from the reactant ions and from interfering compounds. In particular, the field-dependent ion mobility as an additional separation dimension aids identification, potentially reducing the number of false positive alarms in field applications. Furthermore, the analysis of a seized illicit P2P sample shows that even low levels of P2P can be detected despite the complex background present in the headspace of real samples.

Improvised explosive devices (IEDs) can be assembled directly from daily items and are easily purchasable and distributable internationally, owing to the absence of government export permits. Hence, their origins are not readily revealed, and they can pose significant adverse effects despite their low manufacturing costs. In this study, the feasibility of identifying fingerprints and deoxyribo nucleic acid (DNA) profiles in various IEDs and samples is investigated. Additionally, the relative positions of debris are identified to set the scope of on-site inspection at terrorist scenes. All samples are categorized into porous and non-porous materials, and LMG test, extraction, quantification, and short tandem repeat (STR) analysis are conducted to view the DNA profile. For fingerprinting, 1,2-IND and CA are utilized for development, followed by quality-control analysis. Although sample acquisition is impossible in some experiments, DNA profiling and fingerprint analysis are possible for all, thus allowing mapping to be performed. This study shows that even when terrorist bombing occurs, if evidence with minimal damage is detected at the scene, then STR profiles and fingerprints can be obtained at a level suitable for AFIS usage. Furthermore, accumulating mapping results from numerous experiments significantly aids in determining the scope of evidence acquisition.

More than 1200 civilians and military were killed in cities and villages by the Hamas attack on October 7th, 2023. The bodies and body-parts had to be identified and released for burial. This report outlines the challenges and mode of operation of the massive disaster victim identification (DVI) efforts.

Bodies were delivered to a central mortuary. Each body was coded and undressed for external inspection and documentation of physical elements. Digital fingerprints were recorded and blood or toenails sampled for DNA. Odontology exams were performed by dentists describing dentition, aided by computerized tomography (CT). Whole-body CT was performed in cases the bodies were disfigured or burned from the second week.

Simultaneously, families of missing civilians provided physical elements to the police to extract the DNA for antemortem documentation. The police took the responsibility over the reconciliation, which was based on comparison of the ante-mortem and post-mortem fingerprints, aided by DNA profile matching, odontology examination, clinical and/or radiological findings performed by forensic practitioners. Secondary identification elements were used assure the families regarding the identification. Precise scientific identification a was a priority, even if it slowed the rate of bodies release. Families were allowed to view their relative either at the mortuary or before burial.

The DVI process required cooperation between several governmental agencies and police. To maximize the effectiveness, a synchronized approach should be adopted, specifying communication channels between the partners and dividing the responsibilities. The DVI should be led by a single, experienced authority to ensure interdisciplinary teamwork. This catastrophe required personal resilience of the teams for rapid and efficient functioning and communication between the partners.

This research highlights the underestimated significance of cigarette paper as evidence at crime scenes. The primary objective is to distinguish cigarette paper from similar-looking alternatives, addressing the first research objective. The second objective involves identifying cigarette paper brands using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and machine learning (ML) algorithms. Accurate differentiation of cigarette paper from normal paper is emphasized. ATR-FTIR spectroscopy, coupled with principal component analysis (PCA) for dimensionality reduction, is employed for brand identification. Among fifteen ML algorithms compared, the CatBoost classifier excels for both objectives. This research presents a non-destructive, effective method for studying cigarette paper, contributing valuable insights to crime scene investigations.

Printer source prediction is an important task when examining questioned documents. While some research has provided methods to predict the source printer of documents, with the advent of compatible consumables, printer prediction could become more complex and difficult. Predicting the source printer after replacing cartridges and identifying the source of printer cartridges are unresolved issues that are rarely addressed in current research. Herein, we introduce a novel technique to predict the manufacturer, model, and cartridges of laser printers (i.e., compatible, and original cartridges) used to produce a given document. Document samples produced using eight laser printers and 247 cartridges were collected to establish a dataset. Common manufacturers included HP, Canon, Lenovo, and Epson. After obtaining white-light images and three-dimensional profile images of printed characters, a morphological analysis was conducted by questioned document examiners (QDEs) using microscopy. Microscopic image features across a series of images were also extracted and analyzed using algorithms. Then, six high-dimensional reduction algorithms were used to obtain between- and within-printer variations as well as between- and within-cartridge variations. Finally, we conducted principal component analysis (PCA) and discriminant analysis. For 40 % of the samples, mixed discrimination analysis (MDA) and fixed discrimination analysis (FDA) were employed to predict the manufacturer, model and cartridge of laser printers used to produce the questioned printed document; the remaining 60 % samples comprised the training dataset. In the prediction of manufacturer, model and cartridge, our method achieved mean accuracies of 95.5 %, 97.5 %, and 90.2 %, respectively. Hence, this technique could reasonably aid in predicting the manufacturer, model, and cartridge of a laser printer, even if different cartridges are loaded into printers.