X荧光光谱法测定锡酸铅TDI还原型催化剂中锡和铅含量

报道了一种准确度高、分析步骤简单的锡酸铅TDI还原型催化剂中锡和铅含量的X射线荧光光谱方法（XRF）．设计制备了标准样品,研究了仪器测试条件下元素峰位的选择和背景扣除方法．结果表明：X荧光光谱法在不破坏样品的前提下完成对二氧化锡和铅含量的同时测定,重复实验10次,Pb实验相对标准偏差为0．37％;SnO2实验相对标准偏差0．61％。     

气相色谱-质谱联用技术用于利尿剂的快速初筛和确证

利用微波辅助衍生及宏程序技术,对反兴奋剂条例的禁用列表中的一系列利尿剂药物进行了研究。建立了同时分析尿样中9种利尿剂的气相色谱-质谱联用(GC/MS)测定以及抽检尿样的初筛、确证的新方法。在GC-MS的选择离子监测(SIM)模式下,所建立定量方法的检出限为0.3~6.6μg/L;尿样中的提取回收率为37.6%~96.8%;RSD小于9.7%。由于采用了微波衍生样品前处理技术和宏程序数据处理方法,显著提高了分析效率,不但检测灵敏度完全能满足国际奥委会的要求,而且检测时间缩短3 h以上。方法成功地应用于口服吲达帕胺后尿样的检测,探讨了人尿中吲达帕胺代谢情况,有效进行兴奋剂监控提供了依据。     

中红外光谱法在无创血糖检测技术中的应用

构建了中红外无创血糖检测的实验方案,利用傅里叶红外光谱仪对葡萄糖溶液及手指进行了中红外光谱检测并进行分析,得到葡萄糖的中红外特征吸收峰在1000cm^-1附近,证实了中红外光谱在无创血糖检测中的可实现性,选择激光器和光导探测器进行特征峰处的光电检测实验,并得到了有效信号。     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

电感耦合等离子体原子发射光谱法同时测定槲寄生中的微量元素

采用硝酸-双氧水对槲寄生全药及煎煮液进行湿法消解,用电感耦合等离子体原子发射光谱法(ICP-AES)同时测定试样中Cu,Mg,Zn,Mn,Ni,Se,K,Na,Ca和Fe等元素的含量。该法的的加标回收率为91.6％～108.9％,变异系数为0.47％～4.59％,具有良好的准确度和精密度。结果表明：槲寄生中含有丰富的K和Ca元素,Na和Mg的含量也相对丰富,为进一步研究槲寄生的药理提供了科学的数据。     

A Comprehensive Review on the Benefits and Problems of Curcumin with Respect to Human Health

Curcumin is the most important active component in turmeric extracts. Curcumin, a natural monomer from plants has received a considerable attention as a dietary supplement, exhibiting evident activity in a wide range of human pathological conditions. In general, curcumin is beneficial to human health, demonstrating pharmacological activities of anti-inflammation and antioxidation, as well as antitumor and immune regulation activities. Curcumin also presents therapeutic potential in neurodegenerative, cardiovascular and cerebrovascular diseases. In this review article, we summarize the advancements made in recent years with respect to curcumin as a biologically active agent in malignant tumors, Alzheimer’s disease (AD), hematological diseases and viral infectious diseases. We also focus on problems associated with curcumin from basic research to clinical translation, such as its low solubility, leading to poor bioavailability, as well as the controversy surrounding the association between curcumin purity and effect. Through a review and summary of the clinical research on curcumin and case reports of adverse effects, we found that the clinical transformation of curcumin is not successful, and excessive intake of curcumin may have adverse effects on the kidneys, heart, liver, blood and immune system, which leads us to warn that curcumin has a long way to go from basic research to application transformation.     

高分子基质作用下多孔碳酸钙的仿生合成

依据生物矿化的基本原理,通过仿生合成的方法,以聚丙烯酰胺作为基质合成了一种有机、无机复合的多孔碳酸钙材料.用X射线粉末衍射(XRD)分析、扫描电子显微镜(SEM)、傅里叶变换红外吸收光谱(FT-IR)和电导率测定等手段对所得复合碳酸钙进行了表征,结果发现该多孔CaCO3晶体为方解石型,并且在结晶过程中,聚丙烯酰胺与CaCO3之间存在着相互作用,本文讨论了这种作用的可能机理.     

含酰胺结构超低膨胀聚酰亚胺薄膜的热膨胀行为

采用联苯二酐与3种含酰胺结构二胺制备了具有不同取代基团的聚酰胺-酰亚胺薄膜,考察了酰胺结构对薄膜力学、耐热及尺寸稳定性的影响,研究了聚集态结构与薄膜热膨胀行为的关系和规律.该系列薄膜具有超高强度和优异的耐热性能,拉伸强度高达280. 5 MPa,玻璃化转变温度在389～409℃,并在30～300℃温度范围内表现出超低负膨胀,热膨胀系数(CTE,ppm/℃,即106cm·cm-1·℃-1)在-3. 05～-1. 74ppm/℃之间.聚集态分析结果表明,酰胺结构使分子链间形成了强氢键相互作用,分子链在薄膜面内方向高度有序取向,并在膜厚方向堆积更为紧密,使薄膜表现出热收缩现象.通过不同体积大小的取代基团进一步调控分子链间相互作用及排列堆积,可实现薄膜在高温下近乎零尺寸形变,为设计制备超低膨胀聚合物基板材料提供了新思路.     

基于截断δ-冲击模型的不完全维修更换策略

本文在截断δ-冲击模型的基础上,考虑了因系统劣化而导致的冲击失效门限值与维修时间的变化,扩充失效状态,从而提出一种新的截断δ-冲击模型。以最小费用为目标,稳态可用度为约束条件,建立N型更换策略的不完全维修更换策略模型,并给出三种常用冲击到达间隔分布的期望寿命。最后通过算例验证模型的有效性,并对参数进行灵敏度分析。