Forensic Sciences

Background/Objectives: Determination of the biological profile, particularly sex and stature, constitutes an essential component for individual identification in forensic and archaeological anthropology; however, validation of anthropometric equations remains inadequately implemented in contemporary research. This study addresses two limitations: the isolated development of sex and stature estimation methods and the lack of rigorous validation using independent samples. Methods: In this research, we analyzed 400 well-preserved scapulae from a Northeastern Thai population divided into training (n = 300: 150 male scapulae, 150 female scapulae) and validation (n = 100: 50 male scapulae, 50 female scapulae) groups. Eight standardized measurements were used for both sex and stature estimation. Results: All measurements demonstrated significant sexual dimorphism, with males exhibiting larger dimensions. For sex estimation, a multivariate model incorporating the maximum scapular height, maximum length of the spine, and scapula weight achieved 96.3% accuracy in the training samples and maintained 95.0% accuracy in independent validation. For stature estimation, a three-variable equation combining scapula weight, longitudinal scapular length, and maximum scapular breadth was strongly correlated (R = 0.769, SEE = 5.32 cm) with consistent performance across validation samples. Conclusions: Validation testing confirmed the high accuracy, reliability, and stability of both equations when applied to independent samples, with no significant differences in performance metrics between training and validation groups. These validated equations provide reliable standards for forensic practitioners analyzing scapular remains in practical applications within the northeastern Thai population.

Background: The analysis of gunshot residue (GSR) is crucial for gaining information on how a crime occurred. This study presents an innovative proof of concept for measuring shooting distances by performing Flash-Pulse active Thermography (FPT). Compared to conventional chemical methods, FPT offers a significant advantage by digitalizing the residue pattern in a non-destructive manner. Methods: Thermal images of cotton canvases, both white and colored, were analyzed to quantify the distribution of gunshot residues after shooting from several distances, specifically focusing on smoke and semi-burnt powders. The proposed approach uses contrast and radial intensity profiles to extract exponential coefficients, which are dependent on the shooting distance. Results: Employing a sigmoid model to fit the coefficients over distance and to derive a characteristic feature used as a classification metric, firing distances can be classified into short, medium, and long range and can be predicted with an uncertainty of less than 5 cm for distances between 18 and 38 cm under the tested conditions. Considerations regarding the influence of different weapons and ammunition are reported, suggesting the potential for a general approach. Conclusions: The methodology has been validated on several samples, demonstrating its feasibility for specific forensic applications. Its most robust use is as a weapon- and ammunition-specific calibration tool, supporting case-specific distance estimation analysis.

Background: The DASH risk assessment scheme is used across the UK to identify and manage instances of domestic abuse. Recent studies have questioned whether the scheme can identify offenders who go on to commit further acts of domestic abuse, in particular serious violence, and therefore whether it is fit for purpose. Methods: We therefore tested the ability of the DASH to predict future instances of deadly or persistent domestic abuse. From a database of ≈25,000 incidents, we compared DASH assessments which preceded an incident of “deadly violence” or was the first in a series of “persistent abuse”. These groups were compared to a control group where there was no further incident of domestic abuse. Results: The proportion of “high-risk” stratifications was approximately 5 times higher in the deadly violence group compared to the control group. Prediction accuracy assessed via signal detection theory showed the DASH was a moderate predictor of deadly violence (AUC = 0.67). The DASH also showed predictive accuracy in identifying persistent offenders (AUC = 0.62). While these results are encouraging and are similar in efficacy to other risk assessment schemes used in the prediction of domestic violence, the results identified that many individual items of the DASH were not predictive. The inclusion of non-predictive items within the DASH adds “noise” and error into the risk evaluation. The development of a shortened version of the DASH, removing these ineffectual items, was shown to have even higher predictive value for deadly violence (AUC = 0.80). Conclusions: We stress, however, that the role of risk assessment is not to predict violence per se, but to prevent violence via the accurate identification of dangerous perpetrators and via effective intervention and safeguarding of victims. Despite this, research such as this is imperative to evaluate if the risk assessment schemes selected by practitioners and police are fit for purpose.