猪传染性胃肠炎病毒聚合酶基因反义RNA对病毒的抑制作用

通过PCR扩增出猪传染性胃肠炎病毒(TGEV)聚合酶部分片段,反向插入逆转录病毒表达载体pLXSN中,用脂质体法将重组质粒plxas-pol转染PA317细胞,经抗生素G418筛选出稳定的产毒细胞克隆,分别扩大培养后,取其上清液感染小鼠成纤维细胞NIH3T3,细胞克隆产生的重组病毒效价达9.0×105CFU/mL。用高效价假病毒感染IBRS2细胞,再经抗生素G418筛选,提取细胞克隆总RNA,经RT-PCR证明plxas-pol整合入IBRS2细胞。以TGEV感染IBRS2细胞和具有抗性的IBRS2细胞所产生的细胞病变为指标,证明该反义RNA对病毒有明显抑制作用,抑制率约为80%。用2×103和4×102TCID50/mL剂量的TGEV感染时,引起细胞死亡的时间分别为21 h和27 h,与对照组相比,抗性细胞系可明显延迟因病毒感染引起细胞死亡的时间。     

Jensen’s Inequality for Backward Stochastic Differential Equations

Abstract Under the Lipschitz assumption and square integrable assumption on g, the author proves that Jensen’s inequality holds for backward stochastic differential equations with generator g if and only if g is independent of y, g(t, 0) ≡ 0 and g is super homogeneous with respect to z. This result generalizes the known results on Jensen’s inequality for g- expectation in [4, 7–9]. *Project supported by the National Natural Science Foundation of China (No.10325101) and the Science Foundation of China University of Mining and Technology.     

Non-Parametric Regression Methods

The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore, it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).     

Hajek—Renyi不等式的推广及其应用

对Hajek-Renyi不等式进行了推广，利用推广的不等式给出了随机变量序列绝对平均意义下的强大数定律的一个条件．     

关于矩阵和算子迹的一组不等式

给出关于半正定矩阵迹和正算子迹的一组不等式,得到与邱贤忠关于实数的不等式的类似结果.     

Some results on quasipolyhedral convexity

The objective of this paper is to analyze under what well-known operations the class of quasipolyhedral convex functions, which can be regarded as an extension of that of polyhedral convex functions, is closed. The operations that will be considered are those that preserve polyhedral convexity, such that the image and the inverse image under linear transformations, right scalar multiplication (including the case where λ=0⁺) and pointwise addition.      

Global Parametric Sufficient Optimality Conditions for Semi-infinite Discrete Minmax Fractional Programming Problems Involving Generalized （η,ρ）-invex Functions

In this paper,we discuss a large number of sets of global parametric sufficient optimality condi-tions under various gcneralized (η,ρ)-invexity assumptions for a semi-infinite minmax fractional programmingproblem.     

On interpolatory divergence-free wavelets

We construct interpolating divergence-free multiwavelets based on cubic Hermite splines. We give characterizations of the relevant function spaces and indicate their use for analyzing experimental data of incompressible flow fields. We also show that the standard interpolatory wavelets, based on the Deslauriers-Dubuc interpolatory scheme or on interpolatory splines, cannot be used to construct compactly supported divergence-free interpolatory wavelets.

     

Pearson-χ~2距离的若干性质

本文对数理统计中常用的 Pearson- χ2距离的分析特性进行了讨论 ,得到了这一距离的一些解析性质 ,最后我们还给出了几个常用距离的关系 .