1930年代沪上文坛独特的“新感觉”--南洋华侨作家黑婴的“乡愁”书写

史称“新感觉派”后起之秀的黑婴是唯一一位跻身于1930年代中国主流文坛的南洋华侨作家。这位生于荷印棉兰，长于广东梅县，深造于“魔都”上海的新一代南洋华侨，在“民国时态”浓郁的南洋氛围中登陆沪上文坛。在此跨文化的激烈碰撞与深度融合中，黑婴经由“乡愁”的激发与引领，讲述了新一代南洋华侨青年的苦难、迷惘以及艰难的蜕变。今天看来，这种包含着独特生命体验和丰富历史痛感的文化乡愁，正是南侨作家黑婴在“华文文学”和“海派文学”的脉络之外，贡献给中国现代文学真正而独特的“新感觉”。     

悼红轩里增删遍,料定知音旷代存——拜读贺信民先生《红情绿意——<红楼梦>点面论》

三十多年的耕耘,《红情绿意——〈红楼梦〉点面论》的面世,成为贺信民先生贡献于红学界的又一丰硕成果。书中宏观运幄与微观烛照兼长,用生命体验来感悟红楼,在慧眼洞察的缕缕新意之中折射着贺信民先生“研红”的风雨征程,折射着红学界积火传薪的优良学术传承。     

具有反馈控制的Logistic扩散系统周期解的存在与稳定

利用上下解，Ｂｒｏｕｗｅｒ不动点原理及Ｌｙａｐｕｎｏｖ泛函方法，讨论了一类具有反馈控制的Ｌｏｇｉｓｔｉｃ扩散系统的周期解问题；获得了周期解存在且稳定的判别条件．     

Conditional Likelihood Estimators for Hidden Markov Models and Stochastic Volatility Models

ABSTRACT.  This paper develops a new contrast process for parametric inference of general hidden Markov models, when the hidden chain has a non-compact state space. This contrast is based on the conditional likelihood approach, often used for ARCH-type models. We prove the strong consistency of the conditional likelihood estimators under appropriate conditions. The method is applied to the Kalman filter (for which this contrast and the exact likelihood lead to asymptotically equivalent estimators) and to the discretely observed stochastic volatility models.     

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

三个两两相外切圆的内公切圆与外公切圆

在适当的直角坐标系下求出了三个两两相外切圆的内公切圆与外公切圆之圆心坐标和半径,并得到了诸半径之间的优美关系式。     

在线社交网络虚假信息交互量最小化的边阻断策略研究

在线社交媒体的蓬勃发展改变了人们获取信息的模式,大量的信息通过社交平台传播,信息内容的真实性把关弱化,各类虚假信息依托社交媒体野蛮生长,网络空间治理,培育健康的网络生态意义重大。本文通过最小化用户之间的虚假信息交互量,研究社交网络中虚假信息传播路径的阻断策略。给定在线社交网络G=（V,E,P,H）,H表示用户之间信息交互量,已知虚假信息传播源集合S⊆V,虚假信息交互量最小化问题是从E中选取哪K条边,使得这些边被阻断之后,虚假信息在用户之间的交互总量最小。首先证明了该问题是NP-困难的,进而证明了问题的目标函数计算是#P-困难。其次,证明了该问题目标函数既不是次模函数也不是超模函数。再次,提出了两阶段贪婪算法（TSGA）来解决该问题,即先获取候选集合E^sa,然后选取阻断集合E'。最后,通过实际在线社交网络数据对模型和算法的有效性进行了分析,实验表明本文提出的算法比现有算法更加有效。     

非退化扩散过程极性的充分条件

讨论了多维非退化扩散过程样本轨道的性质,得到了其极性的充分条件     

企业产品创新的扩散与采纳者的行为决策模式研究

在SIR模型基础上,根据信息经济学理论从个体层面研究了产品创新扩散过程中采纳者行为决策的决定因子及其行为选择方式,同时得出了一些促进产品创新扩散的重要结论.     

Local composite quantile regression estimation of time-varying parameter vector for multidimensional time-inhomogeneous diffusion models

This paper is dedicated to the study of the composite quantile regression (CQR) estimations of time-varying parameter vectors for multidimensional diffusion models. Based on the local linear fitting for parameter vectors, we propose the local linear CQR estimations of the drift parameter vectors, and verify their asymptotic biases, asymptotic variances and asymptotic normality. Moreover, we discuss the asymptotic relative efficiency (ARE) of the local linear CQR estimations with respect to the local linear least-squares estimations. We obtain that the local estimations that we proposed are much more efficient than the local linear least-squares estimations. Simulation studies are constructed to show the performance of the estimations proposed.