Science & Justice最新文献

Compared to popular handguns and rifle bullets, quantitative and empirical-based ricochet studies using shotgun pellet ricochets are observed to be far fewer. This empirical study examines the ricochet behaviour and impact evidence when shotgun pellets (Buckshot) ricochet off standard floor tiles, providing a series of novel findings related to the resultant ricochet marks. Among these findings, a novel and statistically significant relationship between the lengths and widths of individual ricochet marks and the shot impact angles is demonstrated, offering useful forensic application. Ricochet mark shapes and morphologies highlighted in this study at different impact angles demonstrate the interactions between the ricocheting spherical pellets and tile surfaces, and the effects of acting frictional forces and degree of energy transfer in the production of impact evidence on the tile surface. Relationships with high statistical significance were also reported between the shot spreads on the tile surfaces and the post-ricochet cardboard witness screens, with shot impact angles. Finally, this work reports on the first documented observations of ’Pinch Points’ and ’Nucleus’ ricochet marks with shotgun pellet ricochets as angle-specific phenomena.

Verifying the speaker of a speech fragment can be crucial in attributing a crime to a suspect. The question can be addressed given disputed and reference speech material, adopting the recommended and scientifically accepted likelihood ratio framework for reporting evidential strength in court. In forensic practice, usually, auditory and acoustic analyses are performed to carry out such a verification task considering a diversity of features, such as language competence, pronunciation, or other linguistic features. Automated speaker comparison systems can also be used alongside those manual analyses. State-of-the-art automatic speaker comparison systems are based on deep neural networks that take acoustic features as input. Additional information, though, may be obtained from linguistic analysis. In this paper, we aim to answer if, when and how modern acoustic-based systems can be complemented by an authorship technique based on frequent words, within the likelihood ratio framework. We consider three different approaches to derive a combined likelihood ratio: using a support vector machine algorithm, fitting bivariate normal distributions, and passing the score of the acoustic system as additional input to the frequent-word analysis. We apply our method to the forensically relevant dataset FRIDA and the FISHER corpus, and we explore under which conditions fusion is valuable. We evaluate our results in terms of log likelihood ratio cost ($C_{\mathrm{llr}}$) and equal error rate (EER). We show that fusion can be beneficial, especially in the case of intercepted phone calls with noise in the background.

Fly colonization patterns and development are crucial in estimating the post-mortem interval (PMI) of decomposing corpses. Understanding the potential effects of xenobiotics on species development in cadaveric entomofauna is essential for accurate PMI estimation, given their presence in decomposing bodies. Benzodiazepines, commonly prescribed for their anxiolytic, hypnotic, and muscle relaxant effects, are of forensic interest due to their potential for abuse, dependence, intoxication, and overdose-related deaths. This study aimed to explore the effect of clonazepam and its metabolites on Megaselia scalaris, a species commonly used to estimate PMI, the alteration of which could impact the accuracy of said estimation. The S9 biotransformation fraction, an in vitro model consisting of an array of metabolic enzymes, was used to generate phase I and II metabolites for evaluating their effect on M. scalaris development, representing an innovative approach to this type of study. Megaselia scalaris larvae were reared in synthetic growth media under controlled conditions. The study compared different groups: control, clonazepam, and clonazepam with S9 fraction. Larvae were measured daily to determine growth rate, and clonazepam concentrations were analyzed using HPLC-DAD. Results showed that larvae grown in media containing clonazepam or clonazepam with S9 fraction developed faster than control larvae, reaching their pupal stage earlier. Growth rates were also altered in treated groups. In conclusion, the presence of clonazepam and its metabolites accelerated the life cycle of M. scalaris, potentially impacting the accuracy of PMI estimation. These findings underscore the importance of considering xenobiotics in forensic entomological studies for precise post-mortem interval determination.

Classifying bloodstains is an essential part of Bloodstain Pattern Analysis. Various experts have developed methods. Each method considers the same basic bloodstain pattern types. These use either terminology based on the observable characteristics or the mechanistic cause of the bloodstain patterns as part of the classification process. This review paper considers ten classification methods from fourteen sources, which are used to classify bloodstain patterns. There are fundamental differences in how the patterns are classified, how differentiated the classification is, and whether the classification process uses clear, unambiguous criteria, and is susceptible to contextual bias. Experts have also reported issues with classifying bloodstains that have indistinguishable features. These differences expose key limitations with current classification methods: mechanistic terminology is too heavily relied on, and the classification process is susceptible to contextual bias. The development of an unambiguous classification method, based on directly observable characteristics within bloodstain patterns is recommended for future work.

Tattoos serve as a valuable tool for identification. In the forensic context, it is vital to establish a systematic approach for documenting tattoo-related information to facilitate efficient and fast comparisons, especially in postmortem cases. Despite some countries failing to recognize the potential significance of tattoos, this study presents a methodological framework for gathering comprehensive data on this form of body modification. This article presents the results of an investigation made in Mexico during 2019–2022. The proposed methodology introduces a systematic and distinct classification system tailored to the country in which it will be implemented. The proposal is accompanied by applying the methodology in a Forensic Medical Service (SEMEFO) in Mexico for a week to test its effectiveness and speed under high workloads and stressful conditions. The novelty of this article lies in emphasizing the need for established, replicable, and homologous methodologies for tattoo codification. Additionally, it presents a more in-depth codification, where the details of the tattoos to be classified are thoroughly analyzed.

Environmental DNA (eDNA) is widely used in biodiversity, conservation, and ecological studies but despite its successes, similar approaches have not yet been regularly applied to assist in wildlife crime investigations. The purpose of this paper is to review current eDNA methods and assess their potential forensic application in freshwater environments considering collection, transport and persistence, analysis, and interpretation, while identifying additional research required to present eDNA evidence in court. An extensive review of the literature suggests that commonly used collection methods can be easily adapted for forensic frameworks providing they address the appropriate investigative questions and take into consideration the uniqueness of the target species, its habitat, and the requirements of the end user. The use of eDNA methods to inform conservationists, monitor biodiversity and impacts of climate change, and detect invasive species and pathogens shows confidence within the scientific community, making the acceptance of these methods by the criminal justice system highly possible. To contextualise the potential application of eDNA on forensic investigations, two test cases are explored involving i) species detection and ii) species localisation. Recommendations for future work within the forensic eDNA discipline include development of suitable standardised collection methods, considered collection strategies, forensically validated assays and publication of procedures and empirical research studies to support implementation within the legal system.

In today’s biometric and commercial settings, state-of-the-art image processing relies solely on artificial intelligence and machine learning which provides a high level of accuracy. However, these principles are deeply rooted in abstract, complex “black-box systems”. When applied to forensic image identification, concerns about transparency and accountability emerge. This study explores the impact of two challenging factors in automated facial identification: facial expressions and head poses. The sample comprised 3D faces with nine prototype expressions, collected from 41 participants (13 males, 28 females) of European descent aged 19.96 to 50.89 years. Pre-processing involved converting 3D models to 2D color images (256 × 256 px). Probes included a set of 9 images per individual with head poses varying by 5° in both left-to-right (yaw) and up-and-down (pitch) directions for neutral expressions. A second set of 3,610 images per individual covered viewpoints in 5° increments from −45° to 45° for head movements and different facial expressions, forming the targets. Pair-wise comparisons using ArcFace, a state-of-the-art face identification algorithm yielded 54,615,690 dissimilarity scores. Results indicate that minor head deviations in probes have minimal impact. However, the performance diminished as targets deviated from the frontal position. Right-to-left movements were less influential than up and down, with downward pitch showing less impact than upward movements. The lowest accuracy was for upward pitch at 45°. Dissimilarity scores were consistently higher for males than for females across all studied factors. The performance particularly diverged in upward movements, starting at 15°. Among tested facial expressions, happiness and contempt performed best, while disgust exhibited the lowest AUC values.