浅析南宁市的城市道路绿化设计

分析当前城市道路景观绿化设计的基本含义和主要特点,指出城市道路景观绿化面临的突出问题。总结近年来南宁市道路绿化的发展和已建道路绿化的风格和特点,阐明道路绿化建设的新概念。在观念意识上转变"就景观论景观"的传统思维,对城市道路景观的总体考虑和设计手法的理论方法上探讨"把个体或整体景观建设与更大范围内的城市综合发展紧密联系"的可能性与必要性,创造大城市大园林的新理念。     

Bullying and the Need to Belong: Early Adolescents' Bullying-Related Behavior and the Acceptance they Desire and Receive from Particular Classmates

Based on the notion that one of the motives underlying children's antisocial behavior is their need to belong to particular peers, it was examined how each of four types of bullying‐related behavior would be related to the acceptance that 10 to 13‐year‐old children desired and received from same‐ and other‐sex children with different bullying‐related behavioral styles. Bullying‐related behavior was assessed using a peer nomination procedure. Children rated the importance of being accepted by each particular classmate and their own acceptance of these same classmates. Among boys, antisocial involvement in bullying was related to a desire to be accepted by other antisocial boys and to actually being rejected by boys in general. Among girls, antisocial involvement in bullying was related to a desire to be accepted by boys in general.     

On the estimation of serial correlation in Markov-dependent production processes

In this paper, we present a study about the estimation of the serial correlation for Markov chain models which is used often in the quality control of autocorrelated processes. Two estimators, non-parametric and multinomial, for the correlation coefficient are discussed. They are compared with the maximum likelihood estimator [U.N. Bhat and R. Lal, Attribute control charts for Markov dependent production process, IIE Trans. 22 (2) (1990), pp. 181–188.] by using some theoretical facts and the Monte Carlo simulation under several scenarios that consider large and small correlations as well a range of fractions (p) of non-conforming items. The theoretical results show that for any value of p≠0.5 and processes with autocorrelation higher than 0.5, the multinomial is more precise than maximum likelihood. However, the maximum likelihood is better when the autocorrelation is smaller than 0.5. The estimators are similar for p=0.5. Considering the average of all simulated scenarios, the multinomial estimator presented lower mean error values and higher precision, being, therefore, an alternative to estimate the serial correlation. The performance of the non-parametric estimator was reasonable only for correlation higher than 0.5, with some improvement for p=0.5.     

Strong consistency of the regularized least-squares estimates of infinite autoregressive models

Our main interest is on-line parameter estimation of infinite AR models with exponentially decaying coefficients. The practical importance of the problem follows from the fact that the class of such models includes (but not limited to) all causal invertible ARMA(p,q$p,q$) models. On-line parameter estimation means that the length of the observed data sample is not known a priori and may indefinitely increase. Hence, the parameter estimates should be refined upon arrival of every new observation. So use of the maximum likelihood (ML) method is not feasible due to the high computational burden, and recursive estimation procedures are preferable.     

“课岗证赛”融合式学前教育学课程实施的创新

以往的学前教育学课程忽视了将"课岗证赛"内容的融合,使得学生在学习中出现了"为课而学""为岗而学""为证而学""为赛而学"的重复性学习的现象。这种学习既浪费了教学资源,也增加了教师和学生的压力。改变上述现象的关键是实施"课岗证赛"融合式课程。此课程具有整合性、实用性和实训性的特点。在实施时可以通过"三阶段八环节"的流程,即社会调查、专业研讨和制定实施课程计划等环节来完成教学和实训任务,以提高学生的专业素质,满足"课岗证赛"对人才的专业素质需求。     

A dynamic and cyclical model of bounded ethicality

We introduce a new model of bounded ethicality which helps explain three persistent puzzles of ethical behavior: when moral awareness is or is not present, when ethical behavior is more or less consistent with past behavior, and when blind spots obscure our ethical failures. The original conception of bounded ethicality (Chugh, Banaji, & Bazerman, 2005) described the systematic psychological constraints on ethical behavior and has contributed to our field's understanding of the phenomena of everyday, “ordinary” unethical behavior. In this more detailed model, we delineate these systematic processes and mechanisms and show how concepts of automaticity, self-view, and self-threat play critical roles in our ethical decision-making. The model describes distinct, asymmetric patterns of (un)ethical behavior and pinpoints the contingency which determines which pattern is more likely to unfold, including when we will trend to more or less automaticity and more or less ethical behavior. Our model integrates and synthesizes many of the key models and findings in recent behavioral ethics research into a single, overarching model of ethical decision-making, offering an anchor for new questions and a new realm of study.     

Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors

Accurate volatility forecasting is a key determinant for portfolio management, risk management and economic policy. The paper provides evidence that the sum of squared standardized forecast errors is a reliable measure for model evaluation when the predicted variable is the intra-day realized volatility. The forecasting evaluation is valid for standardized forecast errors with leptokurtic distribution as well as with leptokurtic and asymmetric distributions. Additionally, the widely applied forecasting evaluation function, the predicted mean-squared error, fails to select the adequate model in the case of models with residuals that are leptokurtically and asymmetrically distributed. Hence, the realized volatility forecasting evaluation should be based on the standardized forecast errors instead of their unstandardized version.     

Switching nonparametric regression models

We propose a methodology to analyse data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate x according to an unobserved state z. The states form a stochastic process and their possible values are j=1,?…?, J. If z equals j the expected response of y is one of J unknown smooth functions evaluated at x. We call this model a switching nonparametric regression model. We develop an Expectation–Maximisation algorithm to estimate the parameters of the latent state process and the functions corresponding to the J states. We also obtain standard errors for the parameter estimates of the state process. We conduct simulation studies to analyse the frequentist properties of our estimates. We also apply the proposed methodology to the well-known motorcycle dataset treating the data as coming from more than one simulated accident run with unobserved run labels.     

Rates of convergence of autocorrelation estimates for periodically correlated autoregressive Hilbertian processes

Autoregressive Hilbertian (ARH) processes are of great importance in the analysis of functional time series data and estimation of the autocorrelation operators attracts the attention of various researchers. In this paper, we study estimators of the autocorrelation operators of periodically correlated autoregressive Hilbertian processes of order one (PCARH(1)), which is an extension of ARH(1) processes. The estimation method is based on the spectral decomposition of the covariance operator and considers two main cases: known and unknown eigenvectors. We show the consistency in the mean integrated quadratic sense of the estimators of the autocorrelation operators and present upper bounds for the corresponding rates.