A biomonitoring framework to support exposure and risk assessments

Background

Biomonitoring is used in exposure and risk assessments to reduce uncertainties along the source-to-outcome continuum. Specifically, biomarkers can help identify exposure sources, routes, and distributions, and reflect kinetic and dynamic processes following exposure events. A variety of computational models now utilize biomarkers to better understand exposures at the population, individual, and sub-individual (target) levels. However, guidance is needed to clarify biomonitoring use given available measurements and models.

Objective

This article presents a biomonitoring research framework designed to improve biomarker use and interpretation in support of exposure and risk assessments.

Discussion

The biomonitoring research framework is based on a modified source-to-outcome continuum. Five tiers of biomonitoring analyses are included in the framework, beginning with simple cross-sectional and longitudinal analyses, and ending with complex analyses using various empirical and mechanistic models. Measurements and model requirements of each tier are given, as well as considerations to enhance analyses. Simple theoretical examples are also given to demonstrate applications of the framework for observational exposure studies.

Conclusion

This biomonitoring framework can be used as a guide for interpreting existing biomarker data, designing new studies to answer specific exposure- and risk-based questions, and integrating knowledge across scientific disciplines to better address human health risks.     

ROUGH KNOWLEDGE DISCOVERY FOR NUCLEAR SAFETY

Large amounts of data are generated in the investigating and maintaining of nuclear energy. Making full use of this data to gain useful insights into, for example, safety issues, presents a tremendous challenge. It is well-known that rough set theory can be applied successfully to rough classification and knowledge discovery. Our work is concerned with finding methods for using rough sets to identify classes in datasets, finding dependencies in relations and discovering rules which are hidden in databases. We believe that these methods can be used to understand and control aspects of nuclear energy generation. So in this paper we illustrate the use of our rough discovery methods by means of a running example using data on nuclear safety from the Belgian Nuclear Reactor 1 (BR1).     

动态硫化EVA/BR热塑性弹性体的增强研究

采用动态硫化法制备了乙烯-醋酸乙烯共聚物(EVA)/顺丁橡胶(BR)共混型热塑性弹性体(TPE),通过在树脂相中添加HDPE的方式对复合体系进行增强,对其力学性能及断面微观结构进行了研究。结果表明,对于动态硫化EVA/BR共混型TPE,当HDPE填充量在0～30phr的范围内,其动态硫化产物均表现出TPE的特征;随着树脂相中HDPE用量的提高,复合体系的拉伸强度、撕裂强度、邵氏硬度趋于显著提高,断裂伸长率趋于缓慢增加,而扯断永久形变则始终低于25%;FE-SEM的观察表明,动态硫化TPE的拉伸断面上两相界面结合良好;刻蚀样品表面的硫化胶粒子的尺寸在5mm左右且均匀分散。     

A review of the antioxidant potential of medicinal plant species

Some researchers suggest that two-thirds of the world's plant species have medicinal value; in particular, many medicinal plants have great antioxidant potential. Antioxidants reduce the oxidative stress in cells and are therefore useful in the treatment of many human diseases, including cancer, cardiovascular diseases and inflammatory diseases. This paper reviews the antioxidant potential of extracts from the stems, roots, bark, leaves, fruits and seeds of several important medicinal species. Synthetic antioxidants such as butylated hydroxytoluene (BHT) and butylated hydroxylanisole (BHA) are currently used as food additives, and many plant species have similar antioxidant potentials as these synthetics. These species include Diospyros abyssinica, Pistacia lentiscus, Geranium sanguineum L., Sargentodoxa cuneata Rehd. Et Wils, Polyalthia cerasoides (Roxb.) Bedd, Crataeva nurvala Buch-Ham., Acacia auriculiformis A. Cunn, Teucrium polium L., Dracocephalum moldavica L., Urtica dioica L., Ficus microcarpa L. fil., Bidens pilosa Linn. Radiata, Leea indica, the Lamiaceae species, Uncaria tomentosa (Willd.) DC, Salvia officinalis L., Momordica Charantia L., Rheum ribes L., and Pelargonium endlicherianum. The literature reveals that these natural antioxidants represent a potentially side effect-free alternative to synthetic antioxidants in the food processing industry and for use in preventive medicine.     

Enhancing TRU burning and Am transmutation in Advanced Recycling Reactor

This paper presents about conceptual designs of Advanced Recycling Reactor (ARR) focusing on enhancement in transuranics (TRU) burning and americium (Am) transmutation. The design has been conducted in the context of the Global Nuclear Energy Partnership (GNEP) seeking to close nuclear fuel cycle in ways that reduce proliferation risks, reduce the nuclear waste in the US and further improve global energy security. This study strives to enhance the TRU burning and the Am transmutation, assuming the development of related technologies in this study, while the ARR based on mature technologies was designed in the previous study. It has followed that the provided TRU burning core is designed to burn TRU at 28 kg/TW_thh, by adding moderator pins of B₄C (Enriched B-11) and the Am transmutation core will be able to transmute Am at 34 kg/TW_thh, by locating Am blanket of AmN around the TRU burning core. It indicates that these concepts improve TRU burning by 40-50% than the previous core and can transmute Am effectively, keeping the void reactivity acceptable.     

Determination of azinphos-methyl and parathion-methyl in honey by stripping voltammetry

An electrochemical method for the determination of azinphos-methyl and parathion-methyl in honey is presented. The determination is established by adsorptive stripping differential pulse voltammetry at hanging mercury working electrode.In contrast to the chromatographic methods for the determination of pesticide residues, the sample preparation of the proposed method is minimal; analytes were extracted from honey samples with a mixture of (acetone):(Britton-Robinson buffer) and then were analyzed without any additional pretreatment.The response of the analytes either individually or as a mixture was studied for a series of deposition time and molar ratio. Two quantitation protocols were compared, using either the external calibration or the standard addition method. Accuracy was tested with spiked honey samples obtaining good recovery values. The limit of detection for the honey sample (for deposition time of 10 s) was calculated 51.71 μg kg⁻¹ for MeP and 65.87 μg kg⁻¹ for AzMet.     

基于身份的可认证多方密钥协商新方案

认证密钥协商协议允许通信方在公开的网络环境里进行认证,并协商一个安全的共享会话密钥。在McCullagh-Barreto方案的基础上,提出了一个基于身份的可认证多方密钥协商新方案。引入密钥种子更新临时公私钥对,实现了认证功能,提高了安全性,成功抵抗了Reveal查询攻击和密钥泄漏扮演攻击,且具有无密钥控制、等献性等特性。     

煤炭资源型城市生态风险评价及预测:以鄂尔多斯市为例

 以鄂尔多斯市为研究对象,采用资料分析法、GIS空间数据处理技术,对研究区自然、社会、经济等各项指标进行分析和深入了解。在此基础上应用PSR模型,选取24个指标构建研究区生态风险评价指标体系,采用模糊综合评价法对研究区2005—2015年生态风险程度进行评价。运用BP神经网络方法构建滚动预测模型,对研究区未来5年的生态风险进行预测评价。研究结果表明：1）2005—2015年鄂尔多斯市生态风险程度经历较高（2005—2008年）、一般（2009—2011年）、较低（2012—2015年）3个水平,生态风险级别特征值随时间发展呈现波动上升的良性变化趋势;2）未来鄂尔多斯市生态风险级别特征值会有波动性下降,但整体仍将维持在较低生态风险水平,2017年鄂尔多斯市风险级别特征预测值为5894 5,处于一般风险状态,2020年鄂尔多斯市风险级别特征预测值为6026 6,处于较低风险状态;3）导致鄂尔多斯市生态风险程度恶化的压力因素主要为环境压力,具体包括工业污染物排放量等指标,状态因素主要为经济状态和环境状态,具体包括第三产业在GDP中所占比重和降水量等指标,响应因素主要为人文响应,具体包括万人在学校大学生数和万人拥有医疗机构床位数等指标。为预防生态风险程度由2017年起进一步恶化,未来应当着重控制人口发展、工业污染物排放、草原退化与沙漠化,增加医疗、教育发展的投入。     

基于主题模型的个性化图书推荐算法

针对传统推荐算法精准度不高的问题,在潜在狄利克雷分布(LDA)主题挖掘模型的基础上提出了一种新的适用于图书推荐(BR)的数据挖掘模型——BR_LDA模型。通过对目标借阅者的历史借阅数据与其他图书数据进行内容相似度分析,得到与目标借阅者历史借阅图书内容相似度较高的其他图书。通过对目标借阅者的历史借阅数据及其他借阅者的历史借阅数据进行相似性分析,得到最近邻借阅者的历史借阅数据。通过求解图书被推荐的概率,最终得到目标借阅者潜在感兴趣的图书。特别地,当推荐数量为4000时,BR_LDA模型比基于多特征方法和关联规则方法精准度分别提高了6.2%、4.5%;当推荐数量为500时,BR_LDA模型比协同过滤的近邻方法和矩阵分解方法分别提高了2.1%、0.5%。实验表明本模型能够更准确地向目标借阅者推荐历史感兴趣类别的新图书及潜在感兴趣的新类别的图书。     

BR0代数的Fuzzy理想与Fuzzy素理想

引入了BR0代数的Fuzzy理想,Fuzzy素理想的概念．讨论了BR0代数的Fuzzy理想和Fuzzy素理想的若干性质,给出了BR0代数的Fuzzy集是Fuzzy理想的充要条件,证明了Fuzzy理想和Fuzzy素理想在BR0代数同构下的不变性．