Forensic Sciences Research最新文献

The possible tendency of subjects to decrease, hide, or omit symptomatic aspects of their mental functioning is one of the main problems in forensic psychological and psychiatric evaluations. We aimed at verifying the possible existence of significant differences in the Millon Clinical Multiaxial Inventory-III (MCMI-III) scales scores between a sample of dissimulators (n = 40) and their non-dissimulator counterpart matched by age, sex, and diagnosis. Cases and comparisons were retrieved from the archive of a single university forensic psychiatric centre between 2013 and 2022. Results showed statistically significant higher scores in the sample of dissimulators in the Desirability, Histrionic, Narcissistic, and Compulsive MCMI-III scales than in the comparison sample. Point biserial correlation test disclosed a strong positive correlation between the Desirability, Histrionic, Narcissistic, and Compulsive scales of the MCMI-III and being in the dissimulator group of subjects while a negative correlation emerged for all the other scales except drug dependence.

Key points: The forensic setting can affect a subject's behaviour.Dissimulation is a mechanism of minimization or concealment of a psycho-pathological condition.The MCMI-III can be a useful tool for a forensic psychiatrist or forensic psychologist in assessing dissimulation.

Bullet ricochets are common occurrences during shooting incidents and can provide a wealth of information useful for shooting incident reconstruction. However, there have only been a small number of studies that have systematically investigated bullet ricochet impact site morphology. Here, this study reports on an experiment that examined the plan-view morphology of 297 ricochet impact sites in concrete that were produced by five different bullet types shot from two distances. This study used a random forest machine learning algorithm to classify bullet types with morphological dimensions of the ricochet mark (impact) with length and perimeter-to-area ratio emerging as the top predictor variables. The 0.22 LR leaves the most distinctive impact mark on the concrete, and overall, the classification accuracy using leave-one-out cross-validation is 62%, considerably higher than a random classification accuracy of 20%. Adding in distance to the model as a predictor increases the classification accuracy to 66%. These initial results are promising, in that they suggest that an unknown bullet type can potentially be determined, or at least probabilistically assessed, from the morphology of the ricochet impact site alone. However, the substantial amount of overlap this study documented among distinct bullet types' ricochet mark morphologies under highly controlled conditions and with machine learning suggests that the human identification of ricochet marks in real-world shooting incident reconstructions may be on occasion, or perhaps regularly, in error.

Key points: Bullet ricochet impact sites can help with shooting incident reconstruction.A random forest machine learning algorithm classified bullet type from ricochet morphology.Results suggest that unknown bullets can potentially be determined from ricochet impact site morphology.Human identification of bullet types from ricochet sites may be erroneous.

The identification of historical military remains by Unrecovered War Casualties-Army (UWC-A) currently relies on Y-chromosome Short Tandem Repeat (Y-STR) testing when maternal relatives are not available, or when a mitochondrial DNA match does not provide sufficient certainty of identification. However, common Y-STR profiles (using Yfiler™) between sets of remains or families often prevent identification. To resolve these cases, an investigation of additional Y-DNA markers is needed for their potential inclusion into the DNA identification strategy. The number of genetic transmissions between missing soldiers and their living relatives needs to be considered to avoid false exclusions between paternal relatives. Analysis of 236 World War I/II (WWI/II) era pairs of relatives identified up to seven genetic transmissions between WWII soldiers and their living relatives, and nine for WWI. Previous Y-STR meta-analyses were published approximately 10 years ago when rapidly mutating markers were relatively new. This paper reports a contemporary literature review and meta-analysis of 35 studies (which includes 23 studies not previously used in meta-analysis) and 23 commonly used Y-STR's mutation rates to inform the inclusion of additional loci to UWC-A's DNA identification strategy. Meta-analysis found mutation data for a given Y-STR locus could be pooled between studies and that the mutation rates were significantly different between some loci (at P < 0.05). Based on this meta-analysis, we have identified two additional markers from PowerPlex® Y23 for potential inclusion in UWC-A's identification strategy. Further avenues for potential experimental exploration are discussed.

Key points: From 236 UWC-A pairs of relatives, we observed up to nine genetic transmissions between WWI soldiers and their living relatives, and seven for WWII.MedCalc® software for meta-analysis utilizing the Freeman-Tukey transformation was run, which analysed 35 published studies and 23 commonly used loci. Previous Y-STR mutation rate meta-analyses are now 10 years old; this paper includes 23 studies that were not included in previous meta-analyses.Through meta-analysis, we identify two markers from PowerPlex® Y23 for potential inclusion in UWC-A's historical remains identification strategy (alongside Yfiler™). We discuss potential next steps for experimental exploration of additional Y-DNA markers.

Every year, people drown after falling through ice on rivers and lakes. In some cases, the body of the victim floats up to the underside of the ice, making detection and recovery difficult using traditional search methods with divers. A robust and contact-less sensing system is required to locate drowning victims that does not put rescue teams at risk of falling through the ice themselves. In this paper, we demonstrate the feasibility of a ground penetrating radar (GPR) for detecting deceased drowning victims that have floated up to the underside of the ice. We placed three euthanized pigs simulating drowning victims under ice ranging in thickness from 5 to 26 cm. We dragged a GPR at 500 MHz and 1 GHz across the ice to detect the simulated victims using an autocorrelation-based detection technique. Results showed that both frequencies were able to detect the rough shape of the simulated victims at ice thicknesses up to 42 cm, with the 1-GHz data showing slightly more resolution than the 500-MHz data. These results show promise and suggest future development of an autonomous drone-based GPR detection system.

Key points: Floating bodies are successfully detected under both ice and snow using a commercial ground penetrating radar system with ice depths reaching up to 26 cm in a controlled environment.The differences between using radar systems operating at/around 500 MHz and 1 GHz were not pronounced from the point of view of detection.Future studies should investigate the capabilities for detecting bodies in more realistic settings.