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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Direct Analysis of Human Hair Before and After Cosmetic Modification Using a Recent Data Fusion Method

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Author(s):
Santos, Monica C. [1] ; Pereira, V, Fabiola M.
Total Authors: 2
Affiliation:
[1] V, Univ Estadual Paulista, UNESP, Inst Quim, BR-14800060 Araraquara, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: Journal of the Brazilian Chemical Society; v. 31, n. 1, p. 33-39, JAN 2020.
Web of Science Citations: 0
Abstract

The cosmetic modification of hair is a very common procedure used to mask or cover evidence at a crime scene. Deoxyribonucleic acid (DNA) tests are expensive and require good-quality collection of samples and a database profile. To overcome these challenges, direct analysis was performed on a large set of hair strands collected from individuals, denoted original samples, and the data were compared with those of the same samples after cosmetic modification performed by bleaching the samples in the laboratory. A total of 127 samples were evaluated in this study using two analytical techniques, wavelength-dispersive X-ray fluorescence (WDXRF) and laser-induced breakdown spectroscopy (LIBS). Instead of testing many algorithms to develop classification models for the original and bleached samples, a recent method was applied that combines information from 17 classifiers. Data fusion was also evaluated to improve the accuracy of the classification model, which was higher than 99.2%, with no requirements to select eigenvectors or thresholds. (AU)

FAPESP's process: 16/00779-6 - Direct obtaining of chemical information with commercial purposes from several solid analytical matrices using laser induced breakdown spectroscopy (LIBS) and Chemometrics
Grantee:Hideko Yamanaka
Support Opportunities: Regular Research Grants
FAPESP's process: 17/05550-0 - New chemometric strategies using Tikhonov regularization for improvement of multivariate calibration models
Grantee:Fabiola Manhas Verbi Pereira
Support Opportunities: Scholarships abroad - Research