Laser-Induced Breakdown Spectroscopy as an Accurate Forensic Tool for Bone Classification and Individual Reassignment

激光诱导击穿光谱 稳健性(进化) 计算机科学 光谱学 元素分析 激光烧蚀 模式识别(心理学) 生物系统 材料科学 人工智能 数据挖掘 机器学习 激光器 化学 光学 物理 生物 量子力学 基因 有机化学 生物化学
作者
J. Cárdenas-Escudero,David Galán-Madruga,Jorge O. Cáceres
出处
期刊:Applied Spectroscopy [SAGE]
标识
DOI:10.1177/00037028241277897
摘要

This article provides a detailed discussion of the evidence available to date on the application of laser-induced breakdown spectroscopy (LIBS) and supervised classification methods for the individual reassignment of commingled bone remains. Specialized bone chemistry studies have demonstrated the suitability of bone elemental composition as a distinct individual identifier. Given the widely documented ability of the LIBS technique to provide elemental emission spectra that are considered elemental fingerprints of the samples analyzed, the analytical potential of this technique has been assessed for the investigation of the contexts of commingled bone remains for their individual reassignment. The LIBS bone analysis consists of the direct ablation of micrometric portions of bone samples, either on their surface or within their internal structure. To produce reliable, accurate, and robust bone classifications, however, the available evidence suggests that LIBS spectral information must be processed by appropriate methods. When comparing the performance of seven different supervised classification methods using spectrochemical LIBS data for individual reassociation, those employing artificial intelligence-based algorithms produce analytically conclusive results, concretely individual reassociations with 100% accuracy, sensitivity, and robustness. Compared to LIBS, other techniques used for the purpose of interest exhibit limited performance in terms of robustness, sensitivity, and accuracy, as well as variations in these results depending on the type of bones used in the classification. The available literature supports the suitability of the LIBS technique for reliable individual reassociation of bone remains in a fast, simple, and cost-effective manner without the need for complicated sample processing.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Owen应助侯mm采纳,获得10
刚刚
minisword发布了新的文献求助10
1秒前
1秒前
1秒前
1秒前
李健应助舒适皮皮虾采纳,获得10
1秒前
科研r发布了新的文献求助10
1秒前
ran发布了新的文献求助10
4秒前
4秒前
张莹发布了新的文献求助10
5秒前
liu完成签到,获得积分10
6秒前
天真纹完成签到,获得积分10
6秒前
7秒前
8秒前
liu发布了新的文献求助10
8秒前
123发布了新的文献求助10
10秒前
10秒前
奋斗的夏柳完成签到,获得积分10
10秒前
10秒前
11秒前
善学以致用应助科研r采纳,获得10
11秒前
无语完成签到 ,获得积分10
12秒前
岁月如歌完成签到,获得积分10
13秒前
马里奥好难完成签到 ,获得积分10
14秒前
浮生发布了新的文献求助10
15秒前
传奇3应助张莹采纳,获得10
16秒前
欢呼小蚂蚁完成签到,获得积分10
21秒前
御景风发布了新的文献求助20
22秒前
22秒前
wanci应助浮生采纳,获得10
23秒前
所所应助ran采纳,获得10
23秒前
colddie发布了新的文献求助10
23秒前
24秒前
25秒前
默念发布了新的文献求助10
30秒前
Hello应助asd采纳,获得10
30秒前
默念完成签到,获得积分10
36秒前
37秒前
luanzhaohui完成签到,获得积分10
38秒前
自然的听寒完成签到 ,获得积分10
38秒前
高分求助中
Sustainability in Tides Chemistry 2000
Bayesian Models of Cognition:Reverse Engineering the Mind 800
Essentials of thematic analysis 700
A Dissection Guide & Atlas to the Rabbit 600
Very-high-order BVD Schemes Using β-variable THINC Method 568
Внешняя политика КНР: о сущности внешнеполитического курса современного китайского руководства 500
Revolution und Konterrevolution in China [by A. Losowsky] 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3124628
求助须知:如何正确求助?哪些是违规求助? 2774894
关于积分的说明 7724629
捐赠科研通 2430451
什么是DOI,文献DOI怎么找? 1291102
科研通“疑难数据库(出版商)”最低求助积分说明 622063
版权声明 600323