关于地基极限承载力的理论计算

讨论了地基极限承载力的理论公式及其在使用时应注意的几个问题。     

生活意义感的道德记忆基础

生活意义感的生成标示着主体的存在状态与存在本质的统一。人作为道德存在者,道德记忆能力是其本质能力,它既是 我们能够拥有道德生活的“根”,也是生活意义感得以生成的“源”。简单地将道德记忆与道德生活经历混同起来,则会造成生 活意义感的形式化或异化。生活意义感的增进基于主体日益强大的道德记忆能力,一个拥有卓越道德记忆能力的人,能够通 过合乎道德的记忆或遗忘建构出富有道德价值的道德记忆内容,这对其生活意义感的增进具有关键作用。     

Public school accountability,workplace culture,and teacher morale

Educational scholars claim that teacher morale has suffered from accountability pressures and constrained professionalism, but exactly what is most diminished by these pressures remains unclear. Drawing on recent theoretical work on public school organizational culture, we hypothesize that accountability pressures hurt teacher morale and increase the risk of turnover by undermining the professional culture of the school and by diminishing teacher cooperation and trust. We find support for this hypothesis in a national sample of teachers in 2011–12, and a follow-up survey from 2012–13. The analyses test whether a collective pedagogical teacher culture, comprised of professional culture and teacher collaboration, buffers the impact of these pressures that diminish teacher morale. Counter to past research, we find that a strong collective pedagogical teacher culture does not buffer teachers from the ill effects of negative workplace conditions in the form of accountability pressures. We also find that accountability pressures in the form of district dismissals are associated with a higher likelihood of teachers leaving their school, and this relationship is not mitigated by strong professional culture. We conclude that accountability pressures partly undermine goals of improving performance and equity in public schools by sowing seeds of teacher dissatisfaction and contributing to teacher turnover, thus thwarting student achievement in struggling schools.     

Statistical properties of detrended fluctuation analysis

The main goal of this work is to consider the detrended fluctuation analysis (DFA), proposed by Peng et al. [Mosaic organization of DNA nucleotides, Phys. Rev. E. 49(5) (1994), 1685–1689]. This is a well-known method for analysing the long-range dependence in non-stationary time series. Here we describe the DFA method and we prove its consistency and its exact distribution, based on the usual i.i.d. assumption, as an estimator for the fractional parameter d. In the literature it is well established that the nucleotide sequences present long-range dependence property. In this work, we analyse the long dependence property in view of the autoregressive moving average fractionally integrated ARFIMA(p, d, q) processes through the analysis of four nucleotide sequences. For estimating the fractional parameter d we consider the semiparametric regression method based on the periodogram function, in both classical and robust versions; the semiparametric R/S(n) method, proposed by Hurst [Long term storage in reservoirs, Trans. Am. Soc. Civil Eng. 116 (1986), 770–779] and the maximum likelihood method (see [R. Fox and M.S. Taqqu, Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series, Ann. Statist. 14 (1986), 517–532]), by considering the approximation suggested by Whittle [Hypothesis Testing in Time Series Analysis (1953), Hafner, New York].     

Piecewise FARIMA models for long-memory time series

We consider the problem of modelling a long-memory time series using piecewise fractional autoregressive integrated moving average processes. The number as well as the locations of structural break points (BPs) and the parameters of each regime are assumed to be unknown. A four-step procedure is proposed to find out the BPs and to estimate the parameters of each regime. Its effectiveness is shown by Monte Carlo simulations and an application to real traffic data modelling is considered.     

Obtaining prediction intervals for FARIMA processes using the sieve bootstrap

The sieve bootstrap (SB) prediction intervals for invertible autoregressive moving average (ARMA) processes are constructed using resamples of residuals obtained by fitting a finite degree autoregressive approximation to the time series. The advantage of this approach is that it does not require the knowledge of the orders, p and q, associated with the ARMA(p, q) model. Up until recently, the application of this method has been limited to ARMA processes whose autoregressive polynomials do not have fractional unit roots. The authors, in a 2012 publication, introduced a version of the SB suitable for fractionally integrated autoregressive moving average (FARIMA (p,d,q)) processes with 0<d<0.5 and established its asymptotic validity. Herein, we study the finite sample properties this new method and compare its performance against an older method introduced by Bisaglia and Grigoletto in 2001. The sieve bootstrap (SB) method is a numerically simpler alternative to the older method which requires the estimation of p, d, and q at every bootstrap step. Monte-Carlo simulation studies, carried out under the assumption of normal, mixture of normals, and exponential distributions for the innovations, show near nominal coverages for short-term and long-term SB prediction intervals under most situations. In addition, the sieve bootstrap method yields better coverage and narrower intervals compared to the Bisaglia–Grigoletto method in some situations, especially when the error distribution is a mixture of normals.     

On the use of partial confounding for the construction of alternative regular two-level blocked fractional factorial designs

In this paper, we consider experimental situations in which a regular fractional factorial design is to be used to study the effects of m two-level factors using n=2^m−k experimental units arranged in 2^p blocks of size 2^m−k−p. In such situations, two-factor interactions are often confounded with blocks and complete information is lost on these two-factor interactions. Here we consider the use of the foldover technique in conjunction with combining designs having different blocking schemes to produce alternative partially confounded blocked fractional factorial designs that have more estimable two-factor interactions or a higher estimation capacity or both than their traditional counterparts.     

Aggregation of isotropic autoregressive fields

This note constitutes a corrigendum to the article of Azomahou [2009, Memory properties and aggregation of spatial autoregressive models. J. Statist. Plann. Inference, 139, 2581-2597]. The aggregation of isotropic four nearest neighbors autoregressive models on the lattice Z², with random coefficient, is investigated. The spectral density of the resulting random field is studied in details for a large class of law of the AR coefficient. Depending on this law, the aggregated field may exhibit short memory or isotropic long memory.     

引入持仓量的沪铜指数长记忆波动性研究

通过协整关系检验、误差修正模型、向量自回归模型、格兰杰因果关系检验、脉冲响应函数证明了在建立模型时引入持仓量序列的必要性。运用修正R/S分析,建立了沪铜指数收益率波动的ARFIMA、FI-GARCH、ARFIMA-FIGARCH模型,并运用此种模型对沪铜指数的收益率序列rt、收益率波动序列｜rt｜及残差序列｜εt｜进行相关研究和分析,结果表明：ARFIMA（0,d1,0）-FIGARCH（1,d2,1）模型的预测效果比较好。     

创伤与记忆——西尔维娅·普拉斯诗歌透视

纵观西尔维娅.普拉斯的一生,她在多重创伤下痛苦、绝望、疯狂乃至自杀。她在自白诗里大胆地表达了对死亡的沉迷以及对再生的渴望。疯狂赤裸的自白,既是普拉斯创伤后应激障碍的典型症状,也是其重构创伤经历,试图摆脱创伤的煎熬,渴望灵魂新生和呼唤新时代的表现。普拉斯倾其一生用自白唱响了一首死而复生的悲歌。