Bayesian networks and the value of the evidence for the forensic two-trace transfer problem*

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.     

论高校收入分配制度改革背景下教师职业幸福感的建立

在高校收入分配制度改革背景下,教师职业幸福感是检验高校管理和发展成效的重要标尺,也是当今建设幸福校园的一个全新课题.通过分析高校分配制度改革对教师职业幸福感的影响因素,揭示教师职业幸福感的科学内涵,探究教师的职业幸福感建立的内在机理,对探寻高校收入分配制度改革背景下教师职业幸福感的实现路径有着重要的价值.     

Investigation of Different Ways in Which the CODIS 7.0 May be Used in Mass Disaster Identification

DNA analysis is a key method for the identification of human remains in mass disasters. Reference samples from relatives may be used to identify missing persons by kinship analysis. Different methods of applying the CODIS in disaster victim identification (DVI) were investigated. Two searches were evaluated: (i) relating family relatives to a pedigree tree (FPT) and (ii) relating unidentified human remains to a pedigree tree (UPT). A joint pedigree likelihood ratio (JPLR) and rank were calculated for each search. Both searches were similar in average JPLR and rank. In exceptional cases, namely the existence of a mutation different from the CODIS model, a nonbiological father, a mistake in STR, or incorrect profile association, the UPT search returned one true rank, whereas the FPT search returned no results. This paper suggests a novel strategy to overcome these limitations and increase efficiency in conducting identification of mass disaster victims.     

Refining Stable Oxygen and Hydrogen Isoscapes for the Identification of Human Remains in Mississippi,

Isoscape refinement is an essential component for accurately predicting region‐of‐origin in forensic investigations involving isotope analysis of unidentified human remains. Stable oxygen (δ¹⁸O) and hydrogen (δ²H) isotopes were measured from 57 tap water samples collected across Mississippi to model refined isoscapes for the state. A tap water conversion equation, δ¹⁸O_tw=1.64 δ¹⁸Op?31.35, was developed for the southeastern USA to test the prediction accuracy of the δ¹⁸O_tw isoscape using individuals with known residential histories. A local Mississippi resident (USAFA‐134) was assigned with 90% probability to the correct region‐of‐origin reported by the participant. Assignments for Georgia residents (USAFA‐118 and USAFA‐205) had variable results, predicting USAFA‐118 from Mississippi and USAFA‐205 as a nonlocal resident. Stable isotope values often overlap geographically and a multi‐isotope approach should be used when narrowing region(s)‐of‐origin(s). This study demonstrates the utility of refining isoscapes and the importance of tissue calibration in prediction assignments of human remains.     

WHAT IF ALL THE MONEY CAME HOME?

Since its inception, the public child support program has functioned primarily as a welfare cost recovery mechanism: $2.1 billion of child support collected annually for current and former welfare families is kept by the government to repay welfare costs. However, Wisconsin research findings suggest that low-income fathers pay more support and are less likely to work in the underground economy when support payments are passed through to their children. Regular support reduces poverty and welfare use, and increases child well-being. A consensus has emerged to reform distribution rules so that more child support is paid to the families, not to the government.     

Women are more likely than men to blame structural factors for women's political under-representation: Evidence from 27 countries

Over time, gender and politics research has made progress in identifying those factors that result in low numbers of women in political institutions and in making evidence-informed suggestions about how to ameliorate them. These factors include discrimination in party recruitment processes, male-dominated political culture and broader gender inequalities in society. In contrast, little is known about public opinion regarding these drivers of women's political under-representation, especially whether to who or what women assign blame for the under-representation of women in politics differs from men. This article provides the first discussion and analysis of blame assignment for women's numeric under-representation in politics. In doing so, it outlines and operationalises a framework that distinguishes between meritocratic explanations of women's under-representation, whereby the blame for women not holding political office in greater numbers is assigned to women themselves, and structural explanations, whereby social forces external to women are seen to result in their numeric under-representation. Cross-national data from 27 European countries is used to show that women are significantly more likely than men to assign blame for women's numeric under-representation to structural factors. The hierarchical nature of the dataset is exploited using multilevel models and significant differences in levels of structural blame assignment between countries is found as well as between-country variation in the probability of women assigning blame to structural explanations for women's under-representation. Finally, the category of structural explanations is disaggregated in order to assess their relative prominence and to provide strong corroborative evidence that women predominantly assign blame for women's under-representation to political culture over other structural blame factors. The article concludes with a discussion of the implications of the study's findings for policy makers contemplating the pursuit of gender equality policies aimed at increasing women's political representation and makes suggestions for the direction of future research in this area.     

Error Rates,Likelihood Ratios,and Jury Evaluation of Forensic Evidence

Forensic examiners regularly testify in criminal cases, informing the jurors whether crime scene evidence likely came from a source. In this study, we examine the impact of providing jurors with testimony further qualified by error rates and likelihood ratios, for expert testimony concerning two forensic disciplines: commonly used fingerprint comparison evidence and a novel technique involving voice comparison. Our method involved surveying mock jurors in Amazon Mechanical Turk (N = 897 laypeople) using written testimony and judicial instructions. Participants were more skeptical of voice analysis and generated fewer “guilty” decisions than for fingerprint analysis (B = 2.00, OR = 7.06, p = <0.000). We found that error rate information most strongly decreased “guilty” votes relative to no qualifying information for participants who heard fingerprint evidence (but not those that heard voice analysis evidence; B = −1.16, OR = 0.32, p = 0.007). We also found that error rates and conclusion types led to a greater decrease on “guilty” votes for fingerprint evidence than voice evidence (B = 1.44, OR = 4.23, p = 0.021). We conclude that these results suggest jurors adjust the weight placed on forensic evidence depending on their prior views about its reliability. Future research should develop testimony and judicial instructions that can better inform jurors of the strengths and limitations of forensic evidence.     

Likelihood Ratios for Deep Neural Networks in Face Comparison

In this study, we aim to compare the performance of systems and forensic facial comparison experts in terms of likelihood ratio computation to assess the potential of the machine to support the human expert in the courtroom. In forensics, transparency in the methods is essential. Consequently, state-of-the-art free software was preferred over commercial software. Three different open-source automated systems chosen for their availability and clarity were as follows: OpenFace, SeetaFace, and FaceNet; all three based on convolutional neural networks that return a distance (OpenFace, FaceNet) or similarity (SeetaFace). The returned distance or similarity is converted to a likelihood ratio using three different distribution fits: parametric fit Weibull distribution, nonparametric fit kernel density estimation, and isotonic regression with pool adjacent violators algorithm. The results show that with low-quality frontal images, automated systems have better performance to detect nonmatches than investigators: 100% of precision and specificity in confusion matrix against 89% and 86% obtained by investigators, but with good quality images forensic experts have better results. The rank correlation between investigators and software is around 80%. We conclude that the software can assist in reporting officers as it can do faster and more reliable comparisons with full-frontal images, which can help the forensic expert in casework.     

《民法典》抵押物转让规则新解——兼评《民法典》第406条

《民法典》第406条修改了原《物权法》第191条关于禁止抵押物转让的规则,允许抵押人在设定抵押权后转让抵押物.新规则虽然有利于促进物尽其用,鼓励交易,但是由此也可能给抵押权人监管抵押物或实现抵押权造成困难.因此有必要赋予禁止转让特约以公示能力,在违反经公示的禁止转让特约后,转让合同有效但不能发生物权变动的效力,从而兼顾...     

Performance Study of a Score‐based Likelihood Ratio System for Forensic Fingermark Comparison

In this article, the performance of a score‐based likelihood ratio (LR) system for comparisons of fingerprints with fingermarks is studied. The system is based on an automated fingerprint identification system (AFIS) comparison algorithm and focuses on fingerprint comparisons where the fingermarks contain 6–11 minutiae. The hypotheses under consideration are evaluated at the level of the person, not the finger. The LRs are presented with bootstrap intervals indicating the sampling uncertainty involved. Several aspects of the performance are measured: leave‐one‐out cross‐validation is applied, and rates of misleading evidence are studied in two ways. A simulation study is performed to study the coverage of the bootstrap intervals. The results indicate that the evidential strength for same source comparisons that do not meet the Dutch twelve‐point standard may be substantial. The methods used can be generalized to measure the performance of score‐based LR systems in other fields of forensic science.