虚拟原子探针随机采样法用于氨基酸结构描述及其构效关系研究

考虑药物与蛋白质受体的3类非键作用模式, 利用8类虚拟原子探针和Monte Carlo随机采样技术, 得到了一套新的氨基酸侧链表面静电、立体及疏水势能场(ASSPF)参数. 在此基础上对苦味二肽和血管舒缓激五肽进行了结构表征和QSAR研究, 所建模型复相关系数R2和留一法交互检验复相关系数QLOOCV2分别为0.8457, 0.851和0.7688, 0.7952, 同时分析了肽链不同位置上氨基酸侧链对活性的影响, 取得较好的结果.     

一类随机环境中的随机游动

研究了在环境平稳遍历时,右半直线上可逗留的随机环境中的随机游动的常返性和非常返性,给出非常返、正常返、零常返的充要条件,并讨论了极限性质.作为推论,给出P独立同分布时的相应结论.     

Nonequilibrium Time Reversibility with Maps and Walks

Time-reversible dynamical simulations of nonequilibrium systems exemplify both Loschmidt’s and Zermélo’s paradoxes. That is, computational time-reversible simulations invariably produce solutions consistent with the irreversible Second Law of Thermodynamics (Loschmidt’s) as well as periodic in the time (Zermélo’s, illustrating Poincaré recurrence). Understanding these paradoxical aspects of time-reversible systems is enhanced here by studying the simplest pair of such model systems. The first is time-reversible, but nevertheless dissipative and periodic, the piecewise-linear compressible Baker Map. The fractal properties of that two-dimensional map are mirrored by an even simpler example, the one-dimensional random walk, confined to the unit interval. As a further puzzle the two models yield ambiguities in determining the fractals’ information dimensions. These puzzles, including the classical paradoxes, are reviewed and explored here.     

一种可能的简并谱NNS分布

To expose the statistical properties of the degenerated spectrum, with the aid of the random matrix theory,a possible form of the NNS distribution function of the degenerate spectrum was proposed by providing a solution in terms of the same-degeneracy case. The results indicate that the target spectrum is transformed into two sub-spectra: a random one and a regular one, and that the repulsion level of the regular spectrum is also decreased.     

保费收入随机化的风险模型

本文推广了龚日朝(2001)的风险模型,把保费随机化,利用鞅方法讨论了保单来到过程与索赔来到过程均为Po isson过程的破产概率.接着又讨论了G erber-Sh iu期望折现函数,推导出了其满足的积分方程,以及L ap lace变换.最后利用随机游动的知识,讨论了当保单来到过程与索赔来到过程为同一更新过程时的破产概率.     

LIBS中药材石斛等级识别研究

石斛是一种常用的中药材,经常使用新鲜的或干燥的茎条入药,有益胃生津、滋阴清热的效果。近年来,药理学研究探索出石斛具有抗白内障、抗氧化、抗肿瘤、提高免疫力的作用,其在许多病例中疗效显著,引起了国内外学者的关注,然而不同时间采集的石斛中氨基酸、微量元素等含量各不同,其对应药用价值,价格也不同,因此石斛价格等级分辨的研究具有重要意义。为快速鉴别不同价格、不同药效的石斛,研究了随机森林分类模型结合激光诱导击穿光谱技术(LIBS)对石斛价格等级进行分析建模。选取5个等级的石斛样品进行建模,为了对样品进行精确稳定分析,所有石斛样品均通过粉碎压片减小实验误差。采用1 064 nm波长的Nd∶YAG脉冲激光器作为激发光源,设置激光脉冲能量50 mJ,探测延时1μs,采集五个等级石斛样本的光谱数据,每个等级的样本采集40组光谱,共200组数据,并采用归一化处理,使所有的光谱数据转换到-1~1之间。采用归一化处理后的光谱数据进行主成分分析,通过主成分分析获得前7个主成分的得分矩阵,其累计解释95.24%的光谱信息。将选取的7个主成分作为输入,建立波段为220~880 nm的随机森林鉴别模型。并将石斛样本编号打乱,任意选取50%的光谱数据作为训练集,剩下50%的光谱数据作为测试集,默认决策树个数ntree为500,分裂属性集中属性个数mtry为5,建立模型对不同等级的石斛进行分类。等级一、二、三、四、五的识别率分别为95.45%, 100%, 78.26%, 94.12%和85%,平均识别率为90.57%。为提高识别率,研究了不同的ntree和mtry对分类模型的影响,利用袋外数据误差率估计对随机森林的两个参数进行了优化。选择ntree为300,mtry为1,等级一、二、三、四、五的识别率分别为100%, 100%, 92.31%, 100%和90%,平均识别率为96.46%,识别率提高了5.89%。综上所述,采用LIBS技术结合优化后的随机森林模型鉴别石斛等级具有一定的可行性,为未来快速鉴定不同价格的石斛等级分类提供了可行性的判别系统。     

含对甲氧基苯氧羰基偶氮苯基团的侧链液晶高分子的合成与表征

报道了新型的含对甲氧基苯氧羰基偶氮苯基团的甲基丙烯酸酯单体与含对甲氧基苯氧羰基苯基团的甲基丙烯酸酯单体的合成及其自由基共聚合．利用１Ｈ ＮＭＲ、ＩＲ、ＵＶ Ｖｉｓ、元素分析、ＧＰＣ、ＴＧ ＤＴＡ、ＰＯＭ及Ｘ 射线衍射等手段对偶氮单体及聚合物的结构与性能进行了表征,证明两种单体的共聚合产物为无规共聚物,而且各聚合物均具有较好的热稳定性．研究结果还表明,偶氮单体与聚合物在升温过程中均显示出向列相液晶织构,且聚合物的液晶相范围随偶氮含量的增加而变宽．     

An ensemble learning framework for potential miRNA-disease association prediction with positive-unlabeled data

To explore the pathogenic mechanisms of MicroRNA (miRNA) on diverse diseases, many researchers have concentrated on discovering the potential associations between miRNA and disease using machine learning methods. However, the prediction accuracy of supervised machine learning methods is limited by lacking of experimentally-validated uncorrelated miRNA-disease pairs. Without these negative samples, training a highly accurate model is much more difficult. Different from traditional miRNA-disease prediction models using randomly selected unknown samples as negative training samples, we propose an ensemble learning framework to solve this positive-unlabeled (PU) learning problem. The framework incorporates two steps, i.e., a novel semi-supervised Kmeans (SS-Kmeans) to extract reliable negative samples from unknown miRNA-disease pairs and subagging method to generate diverse training sample sets to make full use of those reliable negative samples for ensemble learning. Combined with effective random vector functional link (RVFL) network as prediction model, the proposed framework showed superior prediction accuracy comparing with other popular approaches. A case study on lung and gastric neoplasms further confirms the framework’s efficacy at identifying miRNA disease associations.     

用含氟丙烯酸酯无规共聚物制备超疏水膜

用微乳液聚合法制备了丙烯酸全氟烷基乙酯和甲基丙烯酸甲酯的无规共聚物,并对其进行了表征.采用溶剂挥发成膜法一步制备了具有超疏水性的该聚合物膜,水滴在该聚合物膜上的静态接触角可达151°~160°,滚动角小于3°.通过扫描电子显微镜观察发现该聚合物膜表面分布了许多乳突状突起和微孔洞,并具有微米和纳米尺度相结合的复合杂化结构.该类超疏水表面的形成是由适度粗糙的表面和低表面能相互结合引起的.探讨了该类超疏水膜的形成机理.