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关键词： Discriminant analysis   Forensic Science   FTIR   Milk   Principal component analysis  

摘要： In the present study, we have utilized attenuated total reflectance Fourier transform infrared spectroscopy for the examination of raw, pasteurized and adulterated milk samples. Principal component analysis and discriminant analysis have been applied for discrimination and classification purposes. According to the observations and the model of "goodness of fit", the obtained results explain 100% of the original classification of the dataset and leave one out cross-validation provides 93.74% of accurate classification.

关键词： Antimicrobial resistance (AMR)   One health   Metagenomics   Enterobacteriaceae  

摘要： Background: Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (similar to 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, 'ResPipe'. Results: Taxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve < 1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike of Thermus thermophilus DNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment. Conclusions: Sequencing depth and profiling

关键词： Bioethics   quantitative research   social science   survey  

摘要： Disease advocacy organizations (DAOs) have traditionally focused on raising awareness of rare diseases, providing educational resources to patients, and supporting patients and families. Previous research has described how scientists collaborate with DAOs, but few empirical data are available regarding the extent to which physicians interact with DAOs and how those interactions impact patient care. We conducted a national survey of 230 board-certified pediatric neurologists to assess their engagement with DAOs and their beliefs about the impact of DAOs on patient care. In that context, we evaluated a set of 24 items describing interactions between physicians and DAOs. Exploratory factor analysis produced a 19-item model capturing four types of physician–DAO engagement: (1) accessing or distributing DAO-produced materials (6 items, alpha = 0.80);(2) consulting on DAO activities (5 items, alpha = 0.81);(3) collaborating with DAOs on research activities (6 items, alpha = 0.80);and (4) co-producing scholarly materials with DAOs (2 items, alpha = 0.80). Our data indicate that physicians engage with DAOs in more frequent and diverse ways than has been previously reported. Almost all physicians in our sample had interacted directly with a DAO in some way, from low-effort activities such as visiting a DAO’s website to deeper forms of engagement including coauthoring journal articles. These findings may provide a framework for bioethicists to characterize the nature and extent of physician interactions with advocacy organizations, which is critical for evaluating the ethical implications of physician–DAO relationships. © 2019, © 2019 Taylor & Francis Group, LLC.

关键词： 审计结果公开   媒体反腐报道   反腐报道效能   反腐报道风险   腐败治理  

摘要： 党的十九大以来,依法依规公告审计结果已经成为完善审计结果运用机制的重要内容。加大审计结果公开力度已成为各界共识。审计法修订草案(征求意见稿)关于审计结果公开的规定正发生变化,审计结果公开实务得到了更大的发展。媒体反腐报道是社会反腐的组成部分,本文以认知心理学理论为基础,从受众角度研究了媒体对审计结果公开的行为反应以及审计结果公开对媒体反腐报道意愿的影响。理论分析表明,审计结果公开会通过提高媒体反腐效能感、降低媒体反腐风险感而提高媒体反腐报道意愿。实证结果表明,审计结果公开力度越大、媒体反腐报道意愿越高。本文揭示了审计结果公开对媒体反腐的作用,拓展了政府审计结果公开作用的研究领域、丰富了媒体反腐影响理论,为各级审计机关进一步强化审计结果公开提供了新的依据。

关键词： 检验   环境试验   软件测试   风险识别   数据分析   故障分析  

摘要： 复杂电子产品在进行检验时受技术手段、资源和周期等诸多限制难以做到穷尽式测试。通过分析检验机构积累的历史数据,以提高风险识别的准确性。基于风险,合理安排检验资源和时间,对高风险检验内容给予重点关注或采取预防措施,既可以提高检验的工作效率,又可以提高检验的有效性。提出了需求牵引和数据推动2种数据分析模式,结合典型案例进行了分析。

关键词： 网络平台   精品资源共享   临床微生物学检验  

摘要： 《临床微生物学检验技术》是一门应用性及实践性极强的医学检验技术专业的主干课程,与临床工作的关系密切,在医学检验与临床中发挥着非常重要的衔接作用。有效利用网络平台加强精品资源共享课建设,对学生合理、高效利用现代教育技术,发挥资源共享作用,培养学习力及掌握临床微生物学检验的基本理论、基本知识、基本技能有很好的促进作用。

关键词： 风险投资   高铁开通   成功退出   专利研发  

摘要： 中国风险投资市场日趋成熟,风险投资在我国资本市场到底起到了什么作用还值得探讨。本文基于2006-2016年所有风险投资和私募股权投资事件,选取了具有中国特色的高铁开通这一外生冲击,从成功退出的概率和专利研发两方面检验了10年间我国风险投资的增值作用。研究表明:高铁开通证实风险投资存在增值作用,而且节约旅行时间和增加出行便利有助于增强风险投资的增值作用;领投比跟投的增强作用更大;此效应在高铁开通的"大照顾"中更大。

关键词： 高校   快递包装   回收箱   绿色物流  

摘要： 本文针对目前快递包装回收率低的社会现状,设计一种供高校师生群体分类回收快递包装的室内外晴雨两用的回收箱.设计的目的在于将拆除的快递包装分类处理,减少资源消耗,降低环境污染.与此同时,将师生群体的环保思想化为有效的实际行动,以此提升快递包装回收率.

关键词： 静电纺丝   抗菌包装   活性包封   聚合物   研究进展  

摘要： 随着现代食品工业对产品抗菌包装的要求不断提高,纳米技术和材料的改进与应用逐渐成为研究热点。其中静电纺丝技术是一种新兴的活性物质包埋技术,同时对活性物质也有较好的缓释效果,利用该技术制备的纳米纤维在食品工业中具有潜在的应用价值。该文从天然聚合物(蛋白质、多糖)和合成聚合物(聚乙烯醇、聚氧化乙烯、聚乳酸、聚丙烯)两方面分别综述了静电纺丝技术在食品封装抗菌物质中的应用现状,并展望了静电纺丝在食品科学领域中的应用前景。静电纺丝技术与食品抗菌包装的结合,在未来将得到更加广泛的应用,抗菌包装也将朝着更加多元化的方向发展。

关键词： Classifier network   Computational complexity   Dataset size reduction   Euclidean distance   Nuclear power plant  

摘要： The computational complexity rate augments on training a classifier for a dataset with training samples as large as that of a nuclear power plant (NPP). Hence, there has been a constant focus to have classifiers with low training time. One of the methods to tackle such issue is using training dataset size reduction (TDR) techniques. TDR method leads to lowering memory requirements as well as training time. This paper delineates on the implementation of TDR method using Euclidean distance (TDR-ED) with the intention of crafting a hypothetical boundary which selects the necessary samples from the training data set and dumps the rest. This approach is considered to be effective only if the accuracy of the classifier is not compromised even after reduction in the volume of the dataset. This is tested in this paper using some of the real world datasets to investigate the feasibility and efficiency of the TDR-ED approach using the combined effect of the classification accuracy and percentage reduction in the training dataset. Eventually, the feasibility of TDR-ED techniques for classification of some of the transients in a NPP is also inspected in this paper. (C) 2019 Elsevier Ltd. All rights reserved.