Infrared Spectra of U.S. Automobile Original Finishes (Post – 1989). VIII: In Situ Identification of Bismuth Vanadate Using Extended Range FT‐IR Spectroscopy,Raman Spectroscopy,and X‐Ray Fluorescence Spectrometry

Chrome Yellow (PbCrO₄·xPbSO₄) was a common pigment in U.S. automobile OEM finishes for more than three decades, but in the early 1990s its use was discontinued. One of its main replacements was Bismuth Vanadate (BiVO₄·nBi₂MoO₆, n = 0–2), which was commercially introduced in 1985, as this inorganic pigment also produces a very bright hue and has excellent outdoor durability. This paper describes the in situ identification of Bismuth Vanadate in automotive finishes using FT‐IR and dispersive Raman spectroscopy and XRF spectrometry. Some differentiation of commercial formulations of this pigment is possible based on far‐infrared absorptions, Raman data, and elemental analysis. The spectral differences arise from the presence or absence of molybdenum, the use of two crystal polymorphs of BiVO₄, and differences in pigment stabilizers. Bismuth Vanadate is usually not used alone, and it is typically found with Isoindoline Yellow, hydrous ferric oxide, rutile, Isoindolinone Yellow 3R, or various combinations of these.     

A Radiographic Study on the Utility of Cranial Vault Outlines for Positive Identifications

A standard method for positive identification is the use of antemortem and postmortem radiographic comparisons. The purpose of this research is to test the visual accuracy of antemortem and postmortem radiographic comparisons of cranial vault outlines and to evaluate their uniqueness using geometric morphometric methods. A sample of 106 individuals with varying levels of education and forensic case experience participated in a visual accuracy test. Of the 106 individuals, only 42% correctly assigned all of the radiographs, with accuracy rates ranging from 70 to 93% for each radiographic comparison. Vault shape was further examined using elliptic Fourier analysis, and paired t‐tests were computed on the first 10 principal components accounting for 100% of the variance, which found no significant differences. The visual accuracy test and elliptic Fourier analysis shows that vault outlines may not be unique enough for positive identifications when used as a sole indicator.     

The 2013 CLSR-LSPI seminar on electronic identity: The global challenge – Presented at the 8th International Conference on Legal,Security and Privacy issues in IT Law (LSPI) November 11–15, 2013, Tilleke & Gibbins International Ltd., Bangkok,Thailand

We are the middle of a global identity crisis. New notions of identity are made possible in the online world where people eagerly share their personal data and leave ‘digital footprints’. Multiple, partial identities emerge distributed across cyberspace divorced from the physical person. The representation of personal characteristics in data sets, together with developing technologies and systems for identity management, in turn change how we are identified. Trustworthy means of electronic identification is now a key issue for business, governments and individuals in the fight against online identity crime. Yet, along with the increasing economic value of digital identity, there are also risks of identity misuse by organisations that mine large data sets for commercial purposes and in some cases by governments. Data proliferation and the non-transparency of processing practices make it impossible for the individual to track and police their use. Potential risks encompass not only threats to our privacy, but also knowledge-engineering that can falsify digital profiles attributed to us with harmful consequences. This panel session will address some of the big challenges around identity in the digital age and what they mean for policy and law (its regulation and protection). Questions for discussion include: What does identity mean today? What types of legal solutions are fit for purpose to protect modern identity interests? What rights, obligations and responsibilities should be associated with our digital identities? Should identity management be regulated and who should be held liable and for what? What should be the role of private and public sectors in identity assurance schemes? What are the global drivers of identity policies? How can due process be ensured where automated technologies affect the rights and concerns of citizens? How can individuals be more empowered to control their identity data and give informed consent to its use? How are biometrics and location-tracking devices used in body surveillance changing the identity landscape?     

微滴式数字PCR技术用于生物样品种属鉴定和绝对定量

目的 运用微滴式数字PCR技术进行生物样品的种属鉴定和绝对定量.方法 选择人mtDNA两个编码基因ND4和16S rRNA,设计特异性引物与探针,用人来源及常见动物样本验证种属特异性,再用重组质粒和2组共16份人来源生物检材,倍比稀释.使用微滴式数字PCR技术进行种属检验和绝对定量,验证其灵敏度和稳定性.结果 人重组质粒FAM （ND4）可进行人来源样品的检测,其检测结果与各级稀释梯度基本吻合,微滴式数字PCR技术可以检测出反应体系中低至单拷贝的DNA.结论 微滴式数字PCR技术可以进行生物样品的种属鉴定和绝对定量,并具有很高的灵敏度和特异性,可应用于日常法医物证检验.     

浅谈医学会医疗损害鉴定专家出庭作证

《侵权责任法》统一了＂医疗事故＂和＂医疗过错＂在民事赔偿标准上二元化和医疗诉讼的诉讼案由及法律适用。然而,医疗损害鉴定的模式应如何走向,《侵权责任法》却没有提及。江苏省医学会大胆革新,开展医疗损害鉴定,在新修订的《民事诉讼法》进一步强调鉴定人出庭作证的背景下,江苏省医学会适应新形势组织医疗损害鉴定专家出庭作证,改变了以往医学会鉴定专家不署名、不出庭的历史,提高了鉴定公信力。     

道路交通事故痕迹鉴定中常见问题分析

道路交通事故痕迹鉴定是道路交通事故技术鉴定中的重要鉴定项目之一,也是道路交通事故技术鉴定其他鉴定项目的基础,除应用手、足、工、枪、特等刑事技术传统痕迹的基础理论和方法外,还需要结合力学、道路工程学、道路安全学、车辆工程学、法医学等多学科知识综合评判的一门鉴定科学门类。道路交通事故痕迹鉴定的步骤主要分为合同评审、痕迹勘验、比对分析、作出评判、形成文书五个方面,在其发展的十几年时间里,出现了许多亟待解决的问题,根据道路交通事故痕迹鉴定实践工作中遇到的常见问题,重点归纳这些问题并提出解决方案。     

Empirical validation of a family-member prioritization approach to maximize statistical power in missing person cases

In order to prioritize the exhumation of the most informative reference relatives to increase the statistical power of a reference group, a conditional simulation approach for missing person identification that combines both exclusion and inclusion power in reference families has been previously developed. The aim of this study is to empirically validate this approach by comparing its predicted theoretical prioritization model with the observed changes in statistical power in real cases of our laboratory, in which new relatives had already been added. We conclude that this approach is a reliable tool to choose the most appropriate reference relatives to complete a family group and improve the identification power of a Missing Person (MP).     

Fingerprint error rate on close non‐matches

The accuracy of fingerprint identifications is critically important to the administration of criminal justice. Accuracy is challenging when two prints from different sources have many common features and few dissimilar features. Such print pairs, known as close non‐matches (CNMs), are increasingly likely to arise as ever‐growing databases are searched with greater frequency. In this study, 125 fingerprint agencies completed a mandatory proficiency test that included two pairs of CNMs. The false‐positive error rates on the two CNMs were 15.9% (17 out of 107, 95% C.I.: 9.5%, 24.2%) and 28.1% (27 out of 96, 95% C.I.: 19.4%, 38.2%), respectively. These CNM error rates are (a) inconsistent with the popular notion that fingerprint evidence is nearly infallible, and (b) larger than error rates reported in leading fingerprint studies. We conclude that, when the risk of CNMs is high, the probative value of a reported fingerprint identification may be severely diminished due to an elevated false‐positive error risk. We call for additional CNM research, including a replication and expansion of the present study using a representative selection of CNMs from database searches.     

Dental hygiene students' matching accuracy when comparing antemortem dental radiographs and oral photographs to simulated postmortem WinID3® odontograms

Matching dental antemortem (AM) and postmortem (PM) data for human identification is especially challenging when the workforce is limited. Dental hygienists have served mass fatality incidents (MFIs) due to dental-related expertise. However, forensics within dental hygiene education and research on transferable skills is limited. This qualitative balance design study assessed senior dental hygiene students' match accuracy of simulated cases varying in dental identifiers based on AM full mouth series (FMS) radiographs and oral photographs to PM WinID3^® odontograms to demonstrate possible disaster victim identification (DVI) transferable skills gained during formal education. A convenience sample of senior dental hygiene students (n = 31) was presented information on WinID3^® interpretation, then presented with 5 mismatched cases and asked to visually interpret each to make 10 total matches; five based on AM FMS with simulated PM WinID3^® odontograms and five based on AM photographs with PM WinID3^® odontograms. Match accuracy scores ranged from 41.9% to 58.1% for cases with 1–10 identifiers, and 77.4% to 93.5% for cases with 11–40 identifiers. Accuracy when matching AM radiographs to PM odontograms versus AM photographs to PM odontograms was compared and revealed no statistical differences in match accuracy depending on image type (p = 0.388 to 1.000). Results of this pilot study suggests transferable match accuracy skills resulted from the participants' dental hygiene formal education. These baseline skills with additional specialized training support the rationale for dental hygienists serving on DVI teams. More research is needed in education and practice when preparing dental hygienists for forensic-based service.     

Automated detection of regions of interest in cartridge case images using deep learning

This paper explores a deep-learning approach to evaluate the position of circular delimiters in cartridge case images. These delimiters define two regions of interest (ROI), corresponding to the breech face and the firing pin impressions, and are placed manually or by an image-processing algorithm. This positioning bears a significant impact on the performance of the image-matching algorithms for firearm identification, and an automated evaluation method would be beneficial to any computerized system. Our contribution consists in optimizing and training U-Net segmentation models from digital images of cartridge cases, intending to locate ROIs automatically. For the experiments, we used high-resolution 2D images from 1195 samples of cartridge cases fired by different 9MM firearms. Our results show that the segmentation models, trained on augmented data sets, exhibit a performance of 95.6% IoU (Intersection over Union) and 99.3% DC (Dice Coefficient) with a loss of 0.014 for the breech face images; and a performance of 95.9% IoU and 99.5% DC with a loss of 0.011 for the firing pin images. We observed that the natural shapes of predicted circles reduce the performance of segmentation models compared with perfect circles on ground truth masks suggesting that our method provide a more accurate segmentation of the real ROI shape. In practice, we believe that these results could be useful for firearms identification. In future work, the predictions may be used to evaluate the quality of delimiters on specimens in a database, or they could determine the region of interest on a cartridge case image.