A geophysical and biochemical investigation of buried remains in contrasting soil textures in southern Ontario
Notice bibliographique
Résumé
Ground penetrating radar (GPR) is a non-invasive, geophysical tool used for the\ndetection of clandestine graves. GPR operates by detecting density differences in soil by\nthe transmission of high frequency electromagnetic (EM) waves from an antenna. A 500\nMegahertz (MHz) frequency antenna is typically used for forensic investigations, as it\nprovides a suitable compromise between depth of penetration and sub-surface\nresolution. Domestic pig (Sus scrofa) carcasses were clothed in 100% cotton t-shirts and\n50% cotton/50% polyester briefs, and buried at a consistent depth at three field sites of\ncontrasting soil texture (silty clay loam, fine sand and fine sandy loam) in southern\nOntario. GPR was used to detect and monitor the graves for a period of 14 months post\nburial. Analysis of collected data revealed that GPR had applicability in the detection of\nclandestine graves containing remains in silty clay loam and fine sandy loam soils, but\nwas not suitable for detection in fine sandy soil. Specifically, within a fine sandy loam\nsoil, there is the potential to estimate the post burial interval (PBI), as hyperbolic grave\nresponse was well defined at the beginning of the 14 month burial duration, but\nbecame less distinctive near the completion of the study.\nFollowing the detection of a clandestine grave containing a carcass, collection of\ngravesoil, tissue and textile samples is important for the estimation of the stage of\ndecomposition and the post burial interval (PBI) of the remains. Throughout the\ndecomposition process of a carcass, adipose tissue is subjected to hydrolytic enzymes\nthat convert triglycerides to their corresponding unsaturated, saturated and salts of\nfatty acids. The composition of fatty acids in the decomposed tissue will vary with the\npost mortem period, but it is unknown what affect the soil texture has on lipid\ndegradation. As decomposition proceeds, fatty acids can leach from the tissues into the\nsurrounding burial environment. Fatty acid analysis of gravesoil, tissue and textile\nsamples, exhumed at two, eleven and fourteen month post burial intervals, was\nconducted using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS),\nattenuated total reflectance ??? Fourier transform infrared (ATR-FTIR) spectroscopy and\ngas chromatography ??? mass spectrometry (GC-MS). Infrared (IR) spectroscopy analysis\nof the samples provided a qualitative profile of lipid degradation. Analysis of gravesoil\nsamples did not reveal IR spectroscopy bands attributable to fatty acid degradation or\nadipocere formation. IR spectroscopy analysis of tissue samples is applicable for the\nestimation of carcass decomposition in all of the soil textures tested. Results of textile IR\nspectroscopy analysis revealed limited potential to estimate the stage of carcass\ndecomposition in silty clay loam soil. GC-MS was used to quantify the peak area ratio\n(area/int std area) (PAR) of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1), stearic\n(C18:0) and oleic (C18:1) acids. GC-MS results revealed that analysis of both tissue and\ntextile samples can be useful in the estimation of the stage of decomposition and the\nPBI of carcasses in all three of the soil textures tested.\nThe results of this research may have applicability within forensic investigations\ninvolving decomposing bodies by aiding in the location of clandestine graves in silty clay\nloam and fine sandy loam soil through the use of GPR. Infrared spectroscopy and GC-MS\nanalysis of the fatty acid composition of tissue and textile samples may also be\nincorporated into investigational protocols to aid in the estimation of the stage of\ndecomposition and the PBI of a body.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».