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Finally, a robustness and reproducibility of the pyrosequencing technique would enable this approach to be the part of an age prediction in forensic investigation.<br /><br /> False start analysis is the examination of incomplete saw marks created on bone in an effort to establish information on the saw that created them. The present study aims to use quantitative data from micro-CT cross-sections to predict the thickness of the saw blade used to create the mark. Random forest statistical models are utilised for prediction to present a methodology that is useful to both forensic researchers and practitioners.<br /><br /> 340 false starts were created on 32 fleshed cadaveric leg bones by 38 saws of various classes. False starts were micro-CT scanned and seven measurements taken digitally. A regression random forest model was produced from the measurement data of all saws to predict the saw blade thickness from false starts with an unknown class. A further model was created, consisting of three random forests, to predict the saw blade thickness when the class of the saw is known. The predictive capability of the models was tested using a second sample of data, consisting of measurements takeess from empirical data and offers a significant step towards reduced subjectivity and database formation in false start analysis. Application of this methodology to false start analysis, with a more complete database, will allow complementary results to current analysis techniques to provide more information on the saw used in dismemberment casework.Plant science has been more and more utilized in forensic investigation, although its full potential is still to be reached. Plant macroremains are a powerful tool to link a body or other evidence back to a primary crime scene as they can provide detailed information about its previous ecological and geographic location. However, plant macroremains are often poorly preserved and difficult to identify, as diagnostic elements are seldom present within the assemblage occurring on the scene. Plant fragments most likely to be found are those exposed to the environment and resistant to degradation. The bark of woody plants meets these requirements but the possibility of its identification at species level from small fragments is not known. Starting from a real homicide case, where bark splinters were found on the victim, we aimed to assess the forensic potential of bark identification from small fragments like those likely to occur on a crime scene. Two identification keys were prepared for 16 common lowland tree species from Northern Italy; one key used all the available anatomical traits, the second only those from the outer bark. The second key was not able to discriminate some couples of species unambiguously, but could identify the bark fragments of the homicide as Robinia pseudoacacia, as confirmed from direct comparison with a reference sample. [https://www.selleckchem.com/products/ddr1-in-1.html this website] Bark fragments deserve to be included into the macroremains to be analyzed during an investigation, but small samples could easily lack diagnostic traits, and the building of a reference collection should be encouraged.<br /><br /> The teeth have been used as a supplementary tool for sex differentiation as they are resistant to post-mortem degradation. The present study aimed to develop a new novel informatics framework for predicting sex from linear tooth dimension measurements achieved from cone beam computed tomography (CBCT) images.<br /><br /> A clinical workflow using different machine learning methods was employed to predict the sex in the present study. The CBCT images of 485 subjects (245 men and 240 women) were evaluated for sex differentiation. Nine parameters were measured in both buccolingual and mesiodistal aspects of the teeth. We applied our dataset to Naïve Bayesian (NB), Random Forest (RF), and Support Vector Machine (SVM) as classifiers for prediction. Genetic feature selection was used to discover real features associated with sex classification.<br /><br /> The 10-fold cross-validation results indicated that NB had higher accuracy than SVM and RF for sex classification. The genetic algorithm (GA) indicated that the model could fit the data without using the enamel thickness and pulp height. The average classification accuracy of our clinical workflow was 92.31 %.<br /><br /> The results showed that NB was the best method for sex classification. The application of the first molar teeth in sex prediction indicated an acceptable level of sexual classification. Therefore, these odontometric parameters can be applied as an additional tool for sex determination in forensic anthropology.<br /><br />The results showed that NB was the best method for sex classification. The application of the first molar teeth in sex prediction indicated an acceptable level of sexual classification. Therefore, these odontometric parameters can be applied as an additional tool for sex determination in forensic anthropology.<br /><br /> The decomposition process of human bodies in marine environment is not well understood, and it is influenced by external variables related to the geographical area where the body is submerged. We report the application of two decomposition scores, the Heaton's score and the van Daalen's score, on a casuistry of human bodies recovered from the Northern Adriatic Sea. The aims of this study are to verify whether the marine environment of a Mediterranean climate area may affect the applicability of both scores and to develop a prediction model that can be applied on bodies recovered in salt water.<br /><br /> A retrospective study was performed on 61 human bodies recovered between 2005 and 2019 from coastal water of the Northern Adriatic Sea nearby the Italian regions Emilia-Romagna and Marche. For each of the 61 cases included, the Total Aquatic Decomposition Score (TADS) was calculated with the Heaton's score and the Van Daalen's score. The prediction model was assessed through multiple regression analyses, and the detnment of the Northern Adriatic Sea.<br /><br />The proposed prediction models are not significantly influenced by seasonality, contrarily to what observed on bodies recovered in fresh water in the same climate area. However, the ADD model, which also consider the water temperature, should be preferred for higher decomposition stages. This study helps increase the accuracy of PMSI estimation in bodies recovered from a marine environment of the Northern Adriatic Sea.