Additional predictions for forensic DNA phenotyping of externally visible characteristics using the ForenSeq and Imagen kits

Multiplex DNA typing methods using massively parallel sequencing can be used to predict externally visible characteristics (EVCs) in forensic DNA phenotyping through the analysis of single-nucleotide polymorphisms. The focus of EVC determination has focused on hair color, eye color, and skin tone as well as visible biogeographical ancestry features. In this study, we researched off-label applications beyond what is currently marketed by the manufacturer of the Verogen ForenSeq kit primer set B and Imagen primer set E SNP loci. We investigated additional EVC predictions by examining published genome wide sequencing studies and reported allele-specific gene expression and predictive values. We have identified 15 SNPs included in the ForenSeq kit panel and Imagen kits that have additional EVC prediction capabilities beyond what is published in the Verogen manuals. The additional EVCs that can be predicted include hair graying, ephelides hyperpigmented spots, dermatoheliosis, facial pigmented spots, standing height, pattern balding, helix-rolling ear morphology, hair shape, hair thickness, facial morphology, eyebrow thickness, sarcoidosis, obesity, vitiligo, and tanning propensity. The loci can be used to augment and refine phenotype predictions with software such as MetaHuman for missing persons, cold case, and historic case investigations.     

以改革创新精神推进改革创新的事业

新时期最可贵的精神是改革创新精神。改革创新精神无愧于新时期开创和推进中国特色社会主义事业的伟大的时代精神。学习贯彻十七大精神和总结改革开放历史经验必须准确理解和把握改革创新精神,必须大力弘扬改革创新精神,不断推进中国特色社会主义这一改革创新的事业。     

中国特色协商民主与民主党派参政议政制度保障的思考

协商民主是中国特色社会主义民主政治制度的一种形式,是在新的历史条件下,对我国基本政治制度的坚持和完善,是现代民主形式的一种创新和发展。民主党派参政议政是中国特色协商民主的主要形式,中国特色协商民主则为党派参政议政提供了深厚的制度资源。     

论中国特色社会主义制度的法理基础

中国特色社会主义制度的法理基础系于马克思主义。立足于坚持马克思主义在意识形态领域指导地位的根本制度,在帝制崩溃、经学瓦解一百多年以后的今天,建构"马克思主义四书",有助于夯实中国特色社会主义制度的法理基础。在马克思主义文献体系中,《家庭、私有制和国家的起源》《共产党宣言》《党章总纲》《宪法序言》占据了特殊的地位。根据马克思主义及其中国化的这一条基本线索,从坚持和完善中国特色社会主义制度的实际情况出发,可以把这四篇文献汇集起来,作为"马克思主义四书",以之为中国特色社会主义制度的法理基础,进行精准奠基。     

Presentation of acoustic characteristics with network models for dialect identification

Objective To explore the presentation of acoustic characteristics with network models for dialect identification so as to screen out the optimal singular model for automatic dialect classifier. Methods Four selected typical neural network models for acoustic feature extraction, SOM (self-organizing feature Map), RNN (recurrent neural network), LSTM (long short-term memory network) and CNN (convolutional neural network), were individually simulated through python. With the dataset containing typical dialects (6036 samples of 105 persons’ spoken voices) from 13 cities in Jiangsu province, three aggregates were respectively built up for purpose of training, verification and test at the division ratio of 6:2:2. The test aggregate was then edited into sub-aggregates of 3 and 10 seconds, having each further added of white noise to form the sub-aggregates owning signal-to-noise ratio (SNR) of 3 and 10 dB. Thus, 4 test aggregates were thereby produced, with each containing 1207 samples. The appropriate classifiers were chosen to evaluate the performance of four above-selected models into their operations of training, verification and test. For the dialect identification, every selected network model was verified of its ability to extract features from the test aggregates owning different SNR and duration. Results With the previously-normalized data and network parameters, the confusion matrices of models were obtained from the output data of 4 neural network models processing into 4 test aggregates, having resulted in the Macro-F1 and Micro-F1 scores that are useful and eligible for evaluation of multi-classification problem. The results showed that LSTM and CNN are significantly better of performance than SOM and RNN. SOM is obviously more sensitive to the SNR of test samples, though having poor identification accuracy with the 3dB test aggregate. RNN has the improved accuracy for dialect identification, yet having the insufficient representation ability to key information of long-term samples. LSTM achieves the optimal evaluation scores of 93.1% (Macro-F1)/92.7% (Micro-F1) with 10dB/10s test aggregate, excelling in overcoming the bug of RNN with its characteristic structural unit. CNN is stable of identification accuracy, not easily affected with the length of speech fragments, thereby having better performance in noise-resistibility for substandard recordings. Owning the nonlinear transformation operations of convolution and pooling, CNN model is of good nonlinear expression ability to demonstrate nice fitting performance for information representation in dialect classification although it is incompetent in real-time presentation with the identified material. Conclusions LSTM+CNN framework is of better acoustic characteristics performance and robustness, capable of meeting the further updating development and application of automatic dialect identification. Besides, the audio sample duration and SNR are still the key for a model (singular or coalesced from two or more) to improve its identification accuracy. © 2021, Editorial Office of Forensic Science and Technology. All rights reserved.     

基于过程解析法的同机添加打印文件鉴别方法

利用喷墨打印机二次添加打印,特别是同机添加打印变造文件,是文件检验工作中的难题。喷墨打印机采用串行接字方式,内部结构复杂,喷嘴数目多,同一型号打印机又有多种质量模式。因此,在打印图文上往往留有较多的打印特征,如对接重叠线、对接错位线、横向白线、卫星墨点、墨点错位等。分析爱普生、惠普、佳能三个品牌的20台喷墨打印机不同质量模式的打印文件,发现这些特征重复再现频率较高,不同台打印机打印文件特征差异较大,同一台打印机在不同质量模式下特征出现的位置也不尽相同。通过提取打印文件上的打印特征,分析字车运行方向和打印图文pass数值,分解打印过程并制作检验图谱,判断打印文件的可疑区域是否符合打印规律,为确定二次添加打印提供帮助,提升检验过程的规范性、检验意见的准确性和结果依据的可读性。     

我国文化创意产业发展与著作权制度的完善

文化创意产业是以知识产权为核心资产的新兴产业门类,同时也是最契合知识经济时代的产业形式。文章从著作权制度在文化创意产业发展中的基本功能入手,分析了我国文化创意产业发展的现状及著作权保护制度对文化创意产业发展的影响,讨论了我国著作权制度对文化创意产业发展的作用和现实意义,并分析提出了我国现行著作权制度在文化创意产业发展中的不足及其修改完善的建议。     

解析济南的总部经济

区域经济的发展对济南这个内陆城市显得日益重要。总部经济作为区域经济的一种,其形态上有销售总部、采购中心、研发总部、结算中心等,是一种高端经济,也是一种地缘文化经济,它在济南还是个新事物,许多方面有待深入研究和来自政府的支持。     

后红利时代中国人口红利走势的影响因素及特征

中国人口红利刘易斯拐点正在到来,在后红利时代,中国人口红利的影响因素不断发生改变。这些因素直接体现在企业层面、政府层面、市场层面、社会层面和国际层面,影响到人口红利的获得与实现、数量和质量变化、空间和时间分布、国际和国内的分配,这些因素及其导致的特征对中国未来产业结构调整和收入分配制度的改革将会产生影响。