从人道主义向自然主义迈进的福克纳——读《我弥留之际》

美国南方流派的代表作家威廉·福克纳是一位实验性的作家,在他的文学生涯中,他做过多种尝试,他的早期长篇小说《我弥留之际》是其中非常重要的一次。这部作品的创作思想显示福克纳在上世纪30年代从人道主义向自然主义迈进。     

Seemingly unrelated regression on the autoregressive (Ar(p)) singular equation system

This paper studies the estimation of seemingly unrelated regressions (SUR) of singular equation systems with an autoregressive error process (AR(p)) for each equation.Parameter estimates of the autoregressive singular equation system are not generally invariant to the equation deleted. Under the model specification restriction on the autoregressive parameters, the invariance property is preserved, and this paper shows that a single equation generalized least squares (GLS) estimation for a general autoregressive error process is equivalent to the SURGLS estimation of the AR(p) singular equation system.     

海上救助公约的发展及其主要影响

1989年通过的国际救助公约对传统的“无效果无报酬”原则所作的例外规定,引起了海运界和贸易界的极大关注,从而导致某些国际规则和国内法的修订。本文运用比较的方法对海上救助公约的发展及其对英国劳氏标准救助契约、国际共同海损理算规则和我国海商法的影响作了论述,并且提出了我国当前海商法应作修改补充的几点建议。     

抚顺天湖大桥索夹安装方法

抚顺天湖大桥是一座自锚式悬索桥，主缆材料采用钢丝绳，索夹安装前通过主缆与索夹摩阻系数试验，深入研究了高强螺栓预紧力损失的规律，获得了索夹安装的一系列控制参数；介绍了无猫道施工悬索桥使用移动平台安装索夹的方法和索夹安装时高强螺栓的施拧方案。     

股票市场状态的动力学过程分析

就股票市场呈现的变化归纳为四种状态,即随机游走态、扩散漂移态、混沌震荡态、连贯平稳态,并对每一状态给出了动力学过程的数学描述,研究了各种"过程"下方程的解,以及各种状态下对股市价格带来的系统效应.从股市的微观结构出发,探讨了四种状态下的股市特征表现及投资者的操作策略,为实时地预测股市发展提供了辅助决策.     

功能梯度材料中反平面Yoffe型运动裂纹

用积分变换方法研究了功能梯度弹性材料中反平面Yoffe型运动裂纹问题 .首先采用余弦变换求解功能梯度材料的基本方程 ,然后根据混合边值条件建立Yoffe型运动裂纹的对偶积分方程 ,再把对偶积分方程化为第二类Fredholm积分方程 .文末的数值算例表明功能梯度材料的梯度参数及裂纹的运动速度对动应力强度因子有较大的影响 .     

组合预测误差信息矩阵研究

研究组合预测误差信息矩阵的结构与组合预测方法性质之间的联系,首次提出冗余信息概念,对最优组合预测方法的组合结构进行了研究。     

New methods for fitting multiple sinusoids from irregularly sampled data

A novel framework is proposed for the estimation of multiple sinusoids from irregularly sampled time series. This spectral analysis problem is addressed as an under-determined inverse problem, where the spectrum is discretized on an arbitrarily thin frequency grid. As we focus on line spectra estimation, the solution must be sparse, i.e. the amplitude of the spectrum must be zero almost everywhere. Such prior information is taken into account within the Bayesian framework. Two models are used to account for the prior sparseness of the solution, namely a Laplace prior and a Bernoulli–Gaussian prior, associated to optimization and stochastic sampling algorithms, respectively. Such approaches are efficient alternatives to usual sequential prewhitening methods, especially in case of strong sampling aliases perturbating the Fourier spectrum. Both methods should be intensively tested on real data sets by physicists.