从传统合同到智能合同:由事后法院裁判到事前自动履行的转变

传统合同需要当事人履行具体义务以促使合同目的的实现,且允许各方在现实环境发生变化时加入新的合意或对原合同条款进行修改,产生纠纷后也可以依据法院的裁判机制使权利义务关系趋于平衡。但是,区块链技术的兴起使智能合同能够自动履行当事人约定的各项内容,对纠纷的解决也可以按照合同订立时确定的救济方式自动进行,甚至无需法院的裁判支持。从传统合同到智能合同,最显著的变革在于由事后法院裁判到事前自动履行的转变。技术的进步使法院裁判机制作为权利保障后盾的重要地位受到冲击,智能合同的事前自动履行具有高效率、低成本的优势,为商业世界的交易活动提供新的可能,具有极大的发展潜力。     

基于miRNA相对表达量自动判别月经血和外周血

目的探索有效区分月经血和外周血的miRNA最优标记组合及最佳分类模型,并构建简便快速的自动化判别软件。方法对10种miRNA(miR-451a、miR-205-5p、miR-203a-3p、miR-214-3p、miR-144-3p、miR144-5p、miR-654-5p、miR-888-5p、miR-891a-5p、miR-124-3p)在200余份月经血和外周血样本中的相对表达量以实时荧光定量PCR检测,并以7种算法模型(核密度估计、K-最近邻、逻辑回归、线性判别分析、支持向量机、神经网络、随机森林)进行数据分析,选出鉴别效果最好的标记组合及算法模型,进而构建自动判别软件。结果月经血和外周血中差别最大的三种miRNA为miR-205-5p、miR-203a-3p和miR-214-3p,使用miR144-5p与上述miRNA中的一种或两种组合可达较好区分效果,其中基于miR-144-5p、miR-203a-3p和miR205-5p所形成的“最优特征项组合一”稳健性最强。7种算法模型中最佳分类模型为核密度估计模型,其次为逻辑回归模型。结论本研究建立的自动判别软件界面友好、使用简单,适合辅助法医检验关于月经血和/或外周血判别分析的计算,便利于法医物证工作,有较大的推广应用价值。     

FTA-DNA直接提取法的研究与应用

目的建立一种简约且易于自动化操作的Whatman FTA卡血样DNA提取方法。方法取直径1．2mm FTA卡血样，分别用FTA-DNA直接提取法及FTA常规提取方法提取DNA，AB-Identifiler^TM试剂盒分别进行10山和25山体系检测比较，并筛选批量grA卡血样DNA自动化提取程序。结果200份grA卡血样分别采用2种方法提取DNA模板，25μl体系PCR-STR检测，分型结果均良好。10μl体系检测，FTA-DNA直接提取法优于FTA常规提取方法，图谱RFU值为1000～2000，采用自动化工作站运行该提取程序较手工操作DNA分型图谱均衡性更佳；采用FTA常规提取方法检测，图谱RFU值100～2000，小片段优先扩增现象明显，且有19％的样本出现丢峰现象，采用自动化工作站运行该程序对其结果改善不明显。经工作站运行FTA-DNA直接提取法自动程序及10山体系检测本2万余份FTA卡采集的血样，均获得16个STR基因座DNA分型结果。结论本文建立的FTA-DNA直接提取法适用于FTA卡血样自动化DNA建库。     

对指纹自动识别系统检索方法的探讨

指纹自动识别系统的建立和普及,逐步实现了指纹管理的自动化和网络化。要充分发挥系统的作用,必须熟悉系统的功能,了解库存指纹的情况,提高指纹专业技术人员的素质,加强指纹系统标准化管理建设。只有这样,才能用好、用活系统,准确、快速破案。     

Microscopic Saw Mark Analysis: An Empirical Approach

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62–17.82%.     

Establishing an integrated pipeline for automatic and efficient detection of trace DNA encountered in forensic applications

The analysis of trace DNA is a crucial component in forensic applications. Biological materials containing low-level DNA collected at crime scenes, such as fingerprints, can be valuable as evidence. Automatic detection of biological samples has been largely embraced in forensic applications to meet the increasing throughput requirements. However, the amount of DNA automatically retrieved from trace evidence often tends to be small and unstable, ultimately resulting in poor detection of DNA profiles. Thus, in this work, we introduced a robust DNA extraction and purification platform named Bionewtech® BN3200 (Bionewtech®, Shanghai, China) with the goal of constructing a rapid automatic detection system for trace DNA. The establishment of automatic detection system for trace DNA mainly encompassed two parts: assessing the sensitivity of automatic extraction platform and screening the optimal short tandem repeat (STR) typing kit. The sensitivity of Bionewtech® BN3200 platform based on Ultra-sensitive DNA Extraction kit was initially estimated, demonstrating that this extraction platform might contain large potential in the trace DNA extraction. For the amplification part, three sets of commercial multiplex STR typing kits were selected as candidates, and the amplified products were further genotyped on the Applied Biosystems 3500xl Genetic Analyzer. After comparation, SiFa™ 23 Plex Kit was determined as the most suitable amplification system for trace DNA. Eventually, the newly exploited trace DNA detection system was successfully implemented in the detection of fingerprints derived from glass surfaces with the five-seconds contact time. As a result, the DNA recovered from the fingerprints fluctuated approximately from 57.60 pg to 18.05 ng, in addition, over 70% of the total STR loci were detected in 75% of the fingerprint samples.     

方言识别网络模型的声学信息表征研究

目的研究语音识别网络模型在声学信息中的表征能力,并对方言自动分类应用进行最优单模型筛选。方法使用python仿真实现SOM、RNN、LSTM与CNN模型,并选择合适的分类器进行方言分类任务的训练与分类验证实验。结果实验结果显示,多分类评价指标PRF条件下,LSTM模型取得了宏平均和微平均的最优评价得分。同时CNN模型则在低信噪比条件下显示了较好的抗噪鲁棒性。结论LSTM+CNN框架下方言信息表征能力较好且兼具强鲁棒性,可满足方言自动分类任务的二次开发应用。     

The Role of Language in the Automatic Coding of Political Texts

Automatic approaches to coding party manifestos and other political texts have become more widespread. This research note addresses the question to what extent the source language of a text affects the results. To do so, Swiss manifestos in German and French are coded automatically, comparing a keyword‐based dictionary approach and Wordscores. Because of language differences, both stemming and particularly stop words are important to obtain comparable results for Wordscores. If both are used, the predicted scores are almost identical in both languages. With the right preparations, the challenge of language differences can thus be overcome.