Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact.

(1) Teeth, in humans, represent the most resilient tissues. However, exposure to concentrated acids might lead to their dissolving, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper aims to introduce a novel method for the 3D reconstruction of dental patterns as a crucial step for the digital identification of dental records. (2) With a combination of modern methods, including micro-computed tomography, cone-beam computer tomography, and attenuated total reflection, in conjunction with Fourier transform infrared spectroscopy and artificial intelligence convolutional neural network algorithms, this paper presents a method for 3D-dental-pattern reconstruction, and human remains identification. Our research studies the morphology of teeth, bone, and dental materials (amalgam, composite, glass-ionomer cement) under different periods of exposure to 75% sulfuric acid. (3) Our results reveal a significant volume loss in bone, enamel, dentine, as well as glass-ionomer cement. The results also reveal a significant resistance by the composite and amalgam dental materials to the impact of sulfuric acid, thus serving as strong parts in the dental-pattern mosaic. This paper also probably introduces the first successful artificial intelligence application in automated-forensic-CBCT segmentation. (4) Interdisciplinary cooperation, utilizing the mentioned technologies, can solve the problem of human remains identification with a 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

Size factor as one of the problems in the sex estimation of skulls: upper palaeolithic sample from Predmostí (Czech Republic) as an example.

In this study we estimate sex and population affinity of Gravettian Predmostí (P) skulls using linear and geometric discriminant analysis (DA), and compare them with results of 2D geometric morphometrics (GM). We used the measurements of P3 and P9 males, P4 and P10 females, as originally estimated by Matiegka (1934), as well as two databases--the recent skull database of Howells and the fossil data of Henke. DA classifies the P skulls as robust and belonging to the "male" region, loosing the sensitivity of inter-population differences influenced by size factor. That is why this approach could not be applied. The geographic inter-population differences according to DA do not define P skull shapes as extreme. The influence of geographic variability could be stronger than the inter-sexual differences. Despite the chronological differences between databases and Gravettian skulls, these differences are a component of regional inter-population variability. According to our results, GM is more successful methodological approach than DA. Our previous sex estimation of P skulls with help of GM is completely in accordance with the classical morphoscopic estimation. However, an appropriate reference database is necessary in both the GM and DA approaches. For the sexing of skull with unknown population affinity, and with absence of appropriate reference database, we suggest to use the application of more subjective visual scoring methods.