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.     

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.     

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.     

A Strong Limit Theorem on Random Selection

In this paper, the idea of random selection in the theorem on gambling system is extended to Markov chains, by using the notion likelihood ratio and an analytic technique. A strong limit theorem on the relative frequency of ordered couple under random selection is established.AMS Subject Classification (2001) primary 60F15 Secondary 60J10     

Stability and other limit laws for exit times of random walks from a strip or a halfplane

We show that the passage time, T^*(r), of a random walk S_n above a horizontal boundary at r (r≥0) is stable (in probability) in the sense that as r→∞ for a deterministic function C(r)>0, if and only if the random walk is relatively stable in the sense that as n→∞ for a deterministic sequence B_n>0. The stability of a passage time is an important ingredient in some proofs in sequential analysis, where it arises during applications of Anscombe's Theorem. We also prove a counterpart for the almost sure stability of T^*(r), which we show is equivalent to E|X|<∞, EX>0. Similarly, counterparts for the exit of the random walk from the strip {|y|≤r} are proved. The conditions arefurther related to the relative stability of the maximal sum and the maximum modulus of the sums. Another result shows that the exit position of the random walk outside the boundaries at ±r drifts to ∞ as r→∞ if and only if the random walk drifts to ∞.     

Almost-Sure Results for a Class of Dependent Random Variables

The aim of this note is to establish almost-sure Marcinkiewicz-Zygmund type results for a class of random variables indexed by _d ⁺ —the positive d-dimensional lattice points—and having maximal coefficient of correlation strictly smaller than 1. The class of applications include filters of certain Gaussian sequences and Markov processes.     

On the distribution of the length of the longest increasing subsequence of random permutations

The authors consider the length, , of the longest increasing subsequence of a random permutation of numbers. The main result in this paper is a proof that the distribution function for , suitably centered and scaled, converges to the Tracy-Widom distribution of the largest eigenvalue of a random GUE matrix. The authors also prove convergence of moments. The proof is based on the steepest descent method for Riemann-Hilbert problems, introduced by Deift and Zhou in 1993 in the context of integrable systems. The applicability of the Riemann-Hilbert technique depends, in turn, on the determinantal formula of Gessel for the Poissonization of the distribution function of .