Construction and anti-tumor effects of recombinant fowlpox virus expressing Newcastle disease virus hemagglutinin-neuramidinase gene

Hemagglutinin-neuramidinase (HN), a Newcastle disease virus-derived protein, not only mediates receptor recognition but also possesses neuraminidase (NA) activity, the ability to cleave a component of those receptors, N-acetylneuraminic acid (NAcneu, sialic acid). It is known that this protein in mammalian species, including human beings, has interesting anti-neoplastic as well as immune stimulating properties. To explore the use of the HN gene in cancer gene therapy, we constructed a recombi-nant fowlpox virus expressing the HN protein (vFV-HN) and compared the anti-tumor activity of the recombinant virus with that of wild-type fowlpox virus (FPV) in vivo and in vitro. Here we found that although B16 cells were somewhat resistant to the basal cytotoxic effect of wild-type fowlpox virus, infection with vFV-HN caused a pronounced cytotoxic effect and, the survival of tumor-bearing mice immunized with vFV-HN was significantly increased compared with the survival of mice immunized with the FPV alone. Furthermore, the immunization of mice with vFV-HN elicited a B16 tumor-specific cytotoxic T lymphocyte (CTL) response and clonal expansion of both CD4 and CD8 T cell populations in vivo. In addition, T cells from lymph nodes of mice vaccinated with vFV-HN secreted high levels of the Th1 cytokine IL-2 and IFN-γ, indicating that the regression of tumor cells is related to a Th1-type dominant immune response. These results demonstrate that vaccination with vFV-HN may be a potential strategy for cancer gene therapy.     

Ability to detect weak effective seismic signals by utilizing chaotic vibrator system

Taking the advantage of CVS (Chaotic Vibrator System) sensitivity of large-scale periodic phase-state response to quasi-periodic or periodic signals,a series of numerical experiments were made to understand the ability of CVS to detect weak effective seismic signals in the common-shot seismic record distorted by strong stochastic noise. The re-sults demonstrate that the large-scale periodic phase-states of CVS are correlated with the signal composition of the quasi-periodic wavelet sequence constructing from horizontal moveout of seismic events,noise strength and the noise distortion de-gree to signal. For the same kind of events,the higher the noise distortion degree is,the lower the detectable SNR can be reached by CVS. For seismic data with the same noise distortion degree,the closer the scanning seismic velocity (the trial moveout ve-locity) approaches to the accurate velocity,the higher the detectable SNR can be reached by CVS. More-over,the truncating scanning velocities form an asymmetric belt,which indirectly makes CVS achieve a large-scale periodic phase-state and then the ratio of wavelet distortion coefficients in events can be a biggish variable scope.     

Wind vector retrieval using dual polarization imagery of ASAR

A new algorithm for retrieving wind vector using dual polarization imagery of advanced synthetic aperture radar (ASAR) is developed and tested. Based on the combination of co-polarization and cross-polarization, this new algorithm effectively eliminates the 180° ambiguity which occurs when using single imagery of the ASAR to retrieve wind vector. This algorithm also solves the problem that the retrieval results will break down on very small spatial scales. The results retrieved from dual polarization imagery of ASAR show that the wind speed and direction are in agreement with the data from Quikscat and buoy measurements. The root mean square errors of wind direction and speed between the retrieved results and data from Quikscat are 2.21° and 0.53 m/s, respectively. Comparisons between the new method and the traditional method show that the new methods fit the buoy data and Quikscat data a little better than the traditional method in this image.     

支持向量机学习方法的选择与应用

介绍支持向量机中的核函数及其参数的选择和相关应用技术，以及SVM的应用研究。在不同的学习方法下进行了仿真实验，并对4种不同方法的分类特性进行了对比分析，给出了在不同模式识别问题中不同方法的选择条件。     

一种角速率激光陀螺惯导系统高精度姿态算法

在分析圆锥误差补偿通式的基础上,提出了利用角速率求取角增量的拟合算法,并给出了该算法的数学证明.详细推导了基于纯角速率输入的圆锥误差补偿算法的补偿系数和误差主项通式,并从理论上对精度进行了分析.结合激光陀螺频谱特性的仿真对比结果表明,纯角速率输入圆锥误差补偿算法优于常规的四阶龙格库塔算法,能够提高纯角速率输出的捷联惯性导航系统的姿态精度.     

一种基于支持向量机的非参数双响应曲面法

现有非参数双响应曲面法只注重提高模型的拟合性能而忽视提高泛化性能，对于复杂工业过程的质量优化和稳健设计应用效果不佳．为此提出了一种新的非参数双响应曲面法．首先采用均匀空间网格形式取样，然后利用支持向量机来拟合过程的均值和方差响应，并且通过比较不同拟合模型的泛化误差上界来优化支持向量机的参数．与基于核函数和基于人工神经网络的非参数双响应曲面法对比结果表明：实验设计方式相同时，该方法的平均泛化误差分别降低了31．0％和51．8％；而泛化误差相近时，平均样本量分别降低了35．0％和48．6％；对不同取样方法的泛化性能研究表明，在没有先验知识时，均匀空间网格是一种可接受的实验设计方式．由此说明了该方法的适用性与优越性.     

基于支持向量机的机场检测算法

提出了一种新的机场检测算法．该算法通过把机场跑道的几何特征与其所在区域的纹理特征相结合来描述机场特征，其中由灰度的平均值和方差、区域的光滑性、直方图的偏斜度、区域的一致性、图像的随机性、图像的梯度平均和方差等8个特征组成机场的纹理特征向量．先通过直线检测找到机场跑道的候选区域，然后用基于高斯核函数的支持向量机作为分类函数，对候选区域的特征向量进行分类，由此判别机场跑道．实验表明，与传统的仪通过形状判断机场的方法比较，该算法对机场的误检率较低，检测率比刘德红的方法高近10倍，几乎能实时完成一幅图像的检测．     

电机控制中电压空间矢量脉宽调制算法的探究

分析了电压空间矢量脉宽调制（SVPWM）算法中变换矩阵系数k与输出电压Uout的关系，指出在正弦波条件下，k为2／3时，Uout为相电压，k为（2／3）^1／2时，Uout为线电压．建立了绝缘栅双极晶体管开通和关断的动态过程模型，推导出开关损耗与开关频率的关系式，指出开关损耗与开关频率成正比而与占空比无关．研究结果表明，以000矢量开始和结束的开关模式在扇区切换过程中没有开关状态的变化，因而在扇区切换过程中没有产生开关损耗，5段式SVPWM的开关损耗比7段式的少了1／3，在其他开关模式中，由于存在扇区切换过程的开关损耗，5段式SVPWM的开关损耗比7段式的少将近1／3．上述结论为有关技术人员在设计系统时选择最佳算法提供了依据．     

基于模糊遗传优化支持向量机的系统辨识研究

在实际应用中支持向量机的参数选取问题一直没有得到很好地解决,限制了其应用。为了能够自动获取最优的支持向量机参数,提出了基于模糊遗传算法的SVM参数选择方法,用模糊逻辑在线调整遗传算法的交叉概率pc和变异概率pm,并采用基于模糊遗传优化的支持向量机回归和BP神经网络对非线性系统辨识问题进行了研究。仿真结果表明,在小样本情况下,支持向量机比神经网络具有更高的系统辨识精度和更好的泛化能力。     

DNA分子标记及其在作物遗传育种中的应用

对DNA分子标记技术：RFLP、RAPD、AFLP、SSR、ISSR、SNP等的原理和特点，以及不同DNA分子标记在作物亲缘关系与遗传多样性、指纹图谱的建立、遗传图谱的构建与基因定位、及分子标记辅助选择育种等方面所取得的应用效果进行了较为详尽的论述，充分展示这项技术的发展具有巨大的应用潜力和广阔的应用前景．