Statistical inference in a panel data semiparametric regression model with serially correlated errors

We consider a panel data semiparametric partially linear regression model with an unknown vector β of regression coefficients, an unknown nonparametric function g(·) for nonlinear component, and unobservable serially correlated errors. The correlated errors are modeled by a vector autoregressive process which involves a constant intraclass correlation. Applying the pilot estimators of β and g(·), we construct estimators of the autoregressive coefficients, the intraclass correlation and the error variance, and investigate their asymptotic properties. Fitting the error structure results in a new semiparametric two-step estimator of β, which is shown to be asymptotically more efficient than the usual semiparametric least squares estimator in terms of asymptotic covariance matrix. Asymptotic normality of this new estimator is established, and a consistent estimator of its asymptotic covariance matrix is presented. Furthermore, a corresponding estimator of g(·) is also provided. These results can be used to make asymptotically efficient statistical inference. Some simulation studies are conducted to illustrate the finite sample performances of these proposed estimators.     

Dynamical behaviors of Hopfield neural network with multilevel activation functions

When the activation function possesses multilevel property, the Hopfield neural network has some novel dynamical behaviors, and it is worthwhile to study. First, some properties about the activation function are obtained, on this foundation, some theoretical analysis about the quasi-equilibrium points has been made. From local and global view, some theorems about the boundedness are presented. Finally, two theorems about the first derivative of trajectory with respect to time are found, the first theorem indicates that the trajectory cannot keep increasing or decreasing for time t > t₀, the second theorem is about the complete stability of the trajectory.     

飞机机翼气动外形优化设计研究

本文首先对某飞机原机翼外形进行了详尽的气动分析计算,然后确定了设计思路和方案,探讨了后掠角变化对机翼气动性能的影响,研究选定了减小外翼后掠角的机翼新平面形状,采用先进的CFD软件优化机翼的气动设计,根据不同设计思想进行了多个机翼的外形优化,包括新的翼剖面和弯扭配置,最后将优化设计结果与原机翼进行了对比,对比结果表明,以Q5-M2T和Q5-N2T为代表的优化结果取得了十分理想的改进效果,优化机翼提高了气动性能,机翼升阻比提高了20%-30%,满足了飞机载弹量增大后性能仍可以全面提高的设计要求。     

淬火处理对原位TiCp／Fe复合材料组织及耐磨性的影响

研究了淬火处理对原位ＴｉＣｐ／Ｆｅ复合材料组织和耐磨性的影响。结果表明,复合材料经淬火处理后,其基体组织转变为马氏体,且进一步析出了一定量的细小ＴｉＣ颗粒,这种组织变化使复合材料的冲击韧性下降,但其硬度和耐磨性均显著提高,且其耐磨性是高铬白口铸铁的１．３倍,用扫描电镜和能谱观察分析发现,在淬火复合材料的磨损表面上,ＴｉＣ颗粒未剥落,因而能继续起抑制磨料磨损的作用。     

材料物性参数识别的梯度正则化方法

本文对梯度正则化方法（Ｇｒａｄｉｅｎｔ－Ｒｅｇｕｌａｒｉｚａｔｉｏｎ Ｍｅｔｈｏｄ）作了进一步的研究,给出一种建立了梯度正则化迭代算法和选择正参数的简明实用方法。文中椭圆算子方程参数识别算例不仅说明了ＧＲ法具有广泛的适应性和一定的抗噪声能力,而且收敛速度较快,具有较大的收敛范围。     

局部对称黎曼流形中的极小子流形

In this paper, we discuss the compact minimal submanifolds in locally symmetric Riemannian manifolds. Two Pinching theorems are obtained and two corresponding results of Chern, S. S. and Yau S. T. are generalized.     

下层独立的一主多从双层随机线性规划问题研究

Herminia I.Calvete等研究了一主多从双层确定性线性规划问题,证明了这类问题等价于一类常规的双层线性规划问题.本文在此基础上,推广确定型的问题到随机型优化情况,考虑了一类下层优化相互独立的一主多从双层随机优化问题(SLBMFP).在特定的随机变量分布条件下,理论上证明了该类问题可以转化为一主一从双层确定性优化问题.本文的研究对于求解一主多从双层随机优化模型,解决此类模型在实际应用中的问题具有一定的意义.     

大黄素联合5AzA-cdR对胰腺癌抑癌基因p16、RASSF1A去甲基化作用研究

目的研究大黄素是否可增强5AzA-cdR对胰腺癌Panc1细胞抑癌基因p16、RASSF1A的去甲基化作用。方法采用细胞增殖实验检测不同浓度大黄素对Panc1细胞的生长抑制情况,焦磷酸盐测序PCR（BSP）分别检测大黄素、5AzA-cdR及大黄素联合5AzA-cdR对Panc1细胞抑癌基因p16、RASSF1A甲基化状态的影响,并用荧光定量PCR（FQ-PCR）和Westernblot分别检测p16、RASSF1A及甲基转移酶DNMT1、DNMT3a在mRNA和蛋白水平的表达情况。结果大黄素以时间和浓度梯度依赖性抑制Panc1细胞生长。BSP结果显示大黄素具有微弱的去甲基化作用,5AzA-cdR具有一定程度的去甲基化作用,当两者联用时,去甲基化作用更加显著;FQ-PCR和Westernblot结果显示大黄素与5AzA-cdR联用时,p16、RASSF1A的表达水平均较空白对照明显增高（均P＜0.05）,DNMT1、DNMT3a的表达水平均较空白对照明显降低（均P＜0.05）。结论大黄素与5AzA-cdR联用可通过降低DNMT1和DNMT3a的表达水平来增强5AzA-cdR对胰腺癌抑癌基因p16、RASSF1A的去甲基化作用。     

Möbius Homogeneous Hypersurfaces with One Simple Principal Curvature in Sn+1

Let Möb(Sⁿ⁺¹) denote the Möbius transformation group of Sⁿ⁺¹. A hypersurface f:Mⁿ → Sⁿ⁺¹ is called a Möbius homogeneous hypersurface, if there exists a subgroup G ? Möb(Sⁿ⁺¹) such that the orbit G(p)={φ(p)|φ ∈ G}=f(Mⁿ), p ∈ f(Mⁿ). In this paper, we classify the Möbius homogeneous hypersurfaces in Sⁿ⁺¹ with at most one simple principal curvature up to a Möbius transformation.     

基于滑模控制理论的车辆横向稳定性控制

针对车辆在极限运动工况下转弯或变道行驶时的横向稳定性控制问题,建立以车辆横向速度、横摆角速度及车身侧倾角为状态变量的3自由度非线性动力学模型.在动力学分析的基础上,探讨依靠施加各车轮不同纵向制动力而产生辅助横摆力矩的方法来提高车辆在极限工况下的操纵稳定性.考虑到作为车辆状态变量之一的质心侧偏角难以测量,设计了基于车辆动力学模型及运动学关系相结合的质心侧偏角估计器.运用滑模控制理论,以车辆横摆角速度和质心侧偏角与相应的理想横摆角速度和质心侧偏角之差,作为车辆稳定性控制系统的两类控制输入变量,以车轮纵向制动力矩和方向盘转角为控制目标建立了联合滑模控制系统,通过计算机仿真表明,该控制方法可以有效改善车辆横向稳定性.