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Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis

机译:使用傅里叶变换红外光谱法和化学计量学方法对体液进行软而稳健的鉴定以进行法医分析

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摘要

Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.
机译:体液(BF)识别是刑事调查的重要组成部分,因为它具有暗示犯罪行为和提供可靠DNA来源的能力。与当前使用血清学和生化技术的方法相比,振动光谱方法为法医高炉鉴定提供了替代优势,例如对各种高炉类型和分析兴趣的无损检测和通用性。但是,仍有待实际研究应用在法医上。例如,需要将特定的高炉与所有其他可疑物质以及其他高炉区分开,该方法甚至应适用于老化的高炉样品。在此,我们描述了一种创新的建模方法,用于区分包括周围血液,唾液,精液,尿液和汗液在内的各种BF的ATR FT-IR光谱,以满足上述实际需求。通过采用Q统计技术,有效地排除了非预期的非高炉样品的光谱,将其作为离群值。通过使用带有分层聚类的二分类分类树的判别方案,大大提高了模型对老化高炉的鲁棒性。本研究进展了振动光谱学和化学计量学方法用于法医高炉鉴定的发展。

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