三联体亲权指数的统一算法及其扩展应用

目的 介绍一种在生母参与情形下,孩子与被鉴定人间常用亲缘关系指数的统一算法.方法 以计算三联体亲权指数(paternity index in trios,PIT)的公式为基础,分析不同亲缘关系指数计算公式中的公因子,并以此公因子对不同情形下PIT计算公式进行统一描述,采用叔伯指数定律和亲缘系数(r)将上述PIT统一计算公式扩展至祖孙、半同胞、叔侄及第一代堂兄弟等不同情形下的亲缘关系指数的运算.结果 以状态一致性等位基因的频率倒数加1为公因子,在引入亲缘系数(r)的情形下,获得了可计算在生母参与时,孩子与被鉴定人间任意亲缘关系指数的两个公式.结论 在生母参与情形下,孩子与被鉴定人间亲缘关系指数的统一算法简化了运算过程,有利于编程实现批量计算.     

三联体亲权指数的统一算法及其扩展应用

目的介绍一种在生母参与情形下,孩子与被鉴定人间常用亲缘关系指数的统一算法。方法以计算三联体亲权指数（paternity index in trios,PIT）的公式为基础,分析不同亲缘关系指数计算公式中的公因子,并以此公因子对不同情形下PIT计算公式进行统一描述,采用叔伯指数定律和亲缘系数（r）将上述PIT统一计算公式扩展至祖孙、半同胞、叔侄及第一代堂兄弟等不同情形下的亲缘关系指数的运算。结果以状态一致性等位基因的频率倒数加1为公因子,在引入亲缘系数（r）的情形下,获得了可计算在生母参与时,孩子与被鉴定人间任意亲缘关系指数的两个公式。结论在生母参与情形下,孩子与被鉴定人间亲缘关系指数的统一算法简化了运算过程,有利于编程实现批量计算。     

增加检测STR和引入参考样本对叔侄关系鉴定的效能分析

目的 基于模拟数据和真实样本的检测结果,探讨增加STR数量及引入不同参考样本对叔侄关系鉴定模型系统效能的影响,为叔侄关系鉴定选择适宜的STR数量和参考样本提供参考。方法 针对引入不同的参考样本构建5种常见的叔侄关系鉴定模型,每种模型分别模拟10 000对叔侄关系与10 000对对应的无关个体在检测19、39、55个STR时的似然比及不同阈值下的系统效能。收集浙江汉族家系样本,使用SiFaSTR^TM23plex身份鉴定系统、Goldeneye^?DNA身份鉴定系统22NC和AGCU 21+1 STR荧光检测试剂盒进行55个常染色体STR分型,计算每种模型在检测19、39、55个STR时的似然比及不同阈值下的系统效能,并与模拟结果进行比较。结果 在同一检测系统下,模拟数据与对应的真实样本的计算结果基本一致。在同一模型中,叔侄关系鉴定的系统效能与检测STR数量呈正相关关系,且引入亲属时的系统效能均较仅对叔侄两个体进行鉴定时有不同程度的提高。引入亲属的优先顺序为叔的全同胞(或母亲)、侄的全同胞(或母亲)。结论 增加检测STR数量和引入已知亲属均可提高叔...     

常染色体STR鉴定叔侄关系的应用

PCR-STR分型技术,尤其是高度多态性的特征,在特殊的亲缘关系鉴定中也能发挥作用,并且逐渐在各类亲缘关系鉴定中尝试和应用。对于叔侄关系鉴定,除了Y-STR能提供排除信息外,常染色体也能提供排除信息,但仅凭据Y-STR不能确定叔侄关系。因此,检测常染色体STR基因座,根据PI和W值能否确定叔侄关系是一个值得探索的问题。本文将已确定叔侄血缘关系的样本作29个常染色体STR基因座分型,用ITO法计算叔侄亲权关系指数,探讨其中规律以指导检案。1材料与方法1.1样本已确定叔侄血缘关系的40例(20对);无关个体对40例(20对)作为假设叔侄对照。1.2…     

常染色体STR和X染色体STR联合应用于姑侄和叔侄关系鉴定

目的通过对常染色体STR和X染色体STR基因座进行分型检验,探讨姑侄、叔侄关系的鉴定策略。方法提取案例中被检女孩和另外3名个体（女性2名,疑为被检女孩的姑姑;男性1名,疑为被检女孩的叔父）的血样DNA,采用Goldeneye 20A系统和AGCU 21＋1系统分别进行常染色体STR基因座的复合PCR扩增,用Mentype○RArgus X-12试剂盒和本室自主研制的16重X染色体STR扩增体系分别进行X染色体STR基因座的复合PCR扩增,用3130 XL遗传分析仪进行毛细管电泳和基因型分析。结果依据常染色体STR基因型结果及姑侄、叔侄关系指数计算结果,不排除2名被检姑姑和与被检女性存在姑侄关系;不排除被检叔叔和与被检女性存在叔侄关系,X染色体STR分型结果支持此鉴定意见。结论对于姑侄、叔侄关系鉴定案例,X染色体STR基因座是常染色体STR基因座的良好补充,两者联合运用可获得可靠的鉴定意见。     

两个个体间常用亲缘关系指数的统一算法

目的 介绍仅有两名被鉴定人时二者间常见亲缘关系指数的统一算法.方法 以ITO法计算二联体亲权指数(paternity index in duos,PID)、全同胞指数(full sibling index,FSI)、半同胞指数(half sibling index,HSI)、叔侄指数(avuncular index,A...     

精神疾病司法鉴定重新鉴定研究

目的探索精神疾病司法鉴定中重新鉴定的相关问题，为提高鉴定质量提出一定建议。方法对司法部司法鉴定中心2001度进行的精神疾病司法鉴定重新鉴定案例进行回顾性统计分析。对重新鉴定的发生率、一致性等问题进行研究。结果重新鉴定的发生率为15．79％。一致性为42％，其中仅精神疾病诊断不一致者10例。仅法律相关问题评定不一致者12例，两者均不一致者18例。结论重新鉴定的一致性较差。需要进一步完善鉴定工作。提高鉴定质量。     

精神疾病重新鉴定分析

目的探索精神疾病司法鉴定中重新鉴定的相关问题,为提高鉴定质量提出一定建议。方法对司法部司法鉴定中心2001度进行的精神疾病司法鉴定重新鉴定案例进行回顾性统计分析,对重新鉴定的发生率、一致性等问题进行研究。结果重新鉴定的发生率为15.79%,一致性为42%,其中仅精神疾病诊断不一致者10例,仅法律相关问题评定不一致者12例,两者均不一致者18例。结论重新鉴定的一致性较差,需要进一步完善鉴定工作,提高鉴定质量。     

双亲皆疑亲子鉴定父权指数的计算方法

<正>目前,《亲权鉴定技术规范》(SF/Z JD0105001—2016)对标准三联体及二联体父权指数(paternity index,PI)的计算方法进行了详细举例说明,其中标准三联体的PI计算方法与公安部发布的《法庭科学DNA亲子鉴定规范》(GA/T 965—2011)中的计算方法一致。而对于在法庭科学亲子鉴定领域占有一定比例的未知名尸体身源认定、失踪孩子寻找父母等双亲皆疑     

法医学亲缘关系鉴定方法和研究热点

亲缘关系鉴定在司法鉴定实践中有广泛的应用需求。本文梳理了亲缘关系相关的概念，综述了状态一致性法、似然比法、矩量法和血缘一致性片段法等亲缘关系分析方法的基本原理、优缺点和应用范围，并对疑难生物检材的亲缘关系鉴定、复杂亲缘关系鉴定、法医学系谱分析、非人源生物检材等研究热点进行了讨论。     

Evaluation of DNA match probability in criminal case

The new emphasis on quantification of evidence has led to perplexing courtroom decisions and it has been difficult for forensic scientists to pursue logical arguments. Especially, for evaluating DNA evidence, though both the genetic relationship for two compared persons and the examined locus system should be considered, the understanding for this has not yet drawn much attention. In this paper, we suggest to calculate the match probability by using coancestry coefficient when the family relationship is considered, and thus the performances of the identification values depending on the calculation of match probability are compared under various situations.     

How reliable is the sub-population model in DNA testimony?

The performance of the sub-population model first proposed by Balding and Nichols [D.J. Balding, R.A. Nichols, DNA profile match probability calculation: how to allow for population stratification, relatedness, database selection and single bands. Forensic Sci. Int. 64 (1994) 125-140] is examined using a simulation approach. This work extends the investigations of Curran et al. [J.M. Curran, J.S. Buckleton, and C.M. Triggs, What is the magnitude of the sub-population effect? Forensic Sci. Int. 135 (2003) 1-8]. In particular the effect of underestimating the coancestry coefficient, theta, and the effect of departures from the modelling assumptions were investigated. The model tends to give strongly conservative estimates if the estimate for the coancestry coefficient is accurate. If this coefficient is underestimated then a larger fraction of cases give non-conservative estimates. Departures from the modelling assumption that the sub-population is in Hardy-Weinberg and linkage equilibria appear to have very little effect.     

A Manifesto on Enforcing Law in the Age of ‘Artificial Intelligence’

Building upon A Manifesto In Defense of Democracy and the Rule of Law in the Age of ‘Artificial Intelligence’, we, the Transatlantic Reflection Group on Democracy and the Rule of Law in the Age of ‘Artificial Intelligence’, have reconvened to draft a second consensus manifesto that calls for the effective and legitimate enforcement of laws concerning AI systems. In doing so, we recognise the important and complementary role of standards and compliance practices. Whereas the first manifesto focused on the relationship between democratic law-making and technology, this second manifesto shifts focus from the design of law in the age of AI to the enforcement of law. Concretely, we offer 10 recommendations for addressing the key enforcement challenges shared across transatlantic stakeholders. We call on those who support these recommendations to sign this manifesto. The Fifth Edition of The Athens Roundtable on AI and the Rule of Law will take place on November 30th and December 1st, 2023. It will delve into pressing governance challenges posed by foundation models and generative AI across jurisdictions.     

Rediscovering artificial intelligence and law: an inadequate jurisprudence?

Headlines suggesting that Google scientists had developed the first computer programme capable of learning a wide variety of tasks independently, in what has been hailed as a significant step towards ‘true artificial intelligence’¹1 Accessed February 26, 2015. http://www.theguardian.com/technology/2015/feb/25/google-develops-computer-program-capable-of-learning-tasks-independently. may or may not presage a new era of artificial intelligence (AI) research. Nevertheless, they suggest a need to reconsider the story of AI in law. While significant changes have taken place in the application of information technology to law-work, these have resulted mainly from ordinary information technology processes such as data processing, data storage, retrieval and management in combination with the information rich, rapid and global communication and networking capabilities of the Internet. However, when information technology has been applied to deeper legal processes, which involve the very nature of law, the result has not been very successful. This is especially so in relation to the application of AI systems to law. Philip Leith blamed the meagre and unsatisfactory results of costly AI and law research on faulty jurisprudence and especially on almost exclusive reliance on analytical positivism and ignorance of user needs and requirements. Many involved with AI and law still refuse to acknowledge that there are underlying problems with the way they conceptualise the nature of legal reasoning. Does AI in law have a future then? This article explores recent nuanced approaches to AI and law research and suggests the need for rethinking the jurisprudence that underpins AI and law and in particular to consider the realist social economic and political context in which AI and law works.     

德国人工智能创造物的知识产权法保护及其启示

人工智能时代的到来,有关其创造物的知识产权法保护问题给现有的法律理念与规则带来了巨大挑战。因而比较法视阈欧盟背景下的德国经验或许有一定参考意义;即先通过评介欧盟层面与人工智能相关的法政策与伦理准则,再从德国层面整理其创造物知识产权法保护上的实务经验与理论讨论。进而从中获得对我国的启示:一方面,呼吁今后在我国人工智能创造物知识产权法保护的外部,进一步细化相关的法政策,并着手制定相适应的伦理准则;另一方面,在其内部,基于当前现行法修改实际,分别从专利法、著作权法二个主要维度提出具体的完善建议。并强调内外规制体系间的协调配合,以期塑造既具体可行又灵活完整的我国人工智能创造物的知识产权法保护体系。     

Explainable AI and the philosophy and practice of explanation

Considerations of the nature of explanation and the law are brought together to argue that computed accounts of AI systems’ outputs cannot function on their own as explanations of decisions informed by AI. The important context for this inquiry is set by Article 22(3) of GDPR. The paper looks at the question of what an explanation is from the point of view of the philosophy of science – i.e. it asks not what counts as explanatory in legal terms, or what an AI system might compute using provenance metadata, but rather what explanation as a social practice consists in, arguing that explanation is an illocutionary act, and that it should be considered as a process, not a text. It cannot therefore be computed, although computed accounts of AI systems are likely to be important inputs to the explanatory process.     

利用车辆动力性原理计算事故车车速误差的探究

目的高速公路上追尾事故时有发生,事故责任判定常要求鉴定被追尾车的车速,尤其对超载货车的车速鉴定。方法本文利用车辆动力性与车速的关系对发生追尾事故的事故车车速计算问题进行了研究。结果应用此法明确了功率平衡方程中主要参数的不同取值对最终车速计算误差的不同影响程度。结论研究表明,滚动阻力系数与坡度两者的取值误差对车速计算结果影响明显,应予高度重视。     

Humans forget,machines remember: Artificial intelligence and the Right to Be Forgotten

This article examines the problem of AI memory and the Right to Be Forgotten. First, this article analyzes the legal background behind the Right to Be Forgotten, in order to understand its potential applicability to AI, including a discussion on the antagonism between the values of privacy and transparency under current E.U. privacy law. Next, the authors explore whether the Right to Be Forgotten is practicable or beneficial in an AI/machine learning context, in order to understand whether and how the law should address the Right to Be Forgotten in a post-AI world. The authors discuss the technical problems faced when adhering to strict interpretation of data deletion requirements under the Right to Be Forgotten, ultimately concluding that it may be impossible to fulfill the legal aims of the Right to Be Forgotten in artificial intelligence environments. Finally, this article addresses the core issue at the heart of the AI and Right to Be Forgotten problem: the unfortunate dearth of interdisciplinary scholarship supporting privacy law and regulation.