城市历史建筑保护对策研究——以粤港为例

随着经济和商业社会的发展,城市开发建设不同程度地蚕食历史建筑,破坏历史街区的整体风貌。历史建筑是人类发展痕迹的见证,一定程度上反映着地域文化。保护历史建筑也是保护地域文化。粤港政府在历史建筑保护工作方面积累了不少经验,通过分析粤港两地历史建筑保护措施,提出对城市历史建筑保护与利用的对策建议。     

浅析高校校园体育文化的内涵与作用

狭义体育文化观点认为,体育文化就是以身体活动为基本形式,以身体竞争为特殊手段,以身体完善为主要目标的体育活动过程和活动过程中人的精神生活。当代高校校园体育文化建设应该定位为重品行、催智力、助身心、促审美、推良习、造氛围等交汇一体的校园文化。     

量子的实在性

物理学概念基础的变革往往是人类思维方式变革的前兆,量子概念就是架起从经典物理学通往量子力学的概念之一,也是科学哲学实在论和反实在论两大阵营对峙的概念基点。本文追溯了量子概念出现的历史画面,指出时量子概念引发的两种关于量子与实在之间关系的理解,并从语境方法论的教义对量子概念赋予其实在性。     

略谈新形势下高校青年志愿者服务工作

本文分析当前大学生青年志愿服务工作面临的机遇和挑战,并提出建设高校青年志愿服务工作的应对措施。     

Posterior Analysis for Normalized Random Measures with Independent Increments

Abstract.  One of the main research areas in Bayesian Nonparametrics is the proposal and study of priors which generalize the Dirichlet process. In this paper, we provide a comprehensive Bayesian non-parametric analysis of random probabilities which are obtained by normalizing random measures with independent increments (NRMI). Special cases of these priors have already shown to be useful for statistical applications such as mixture models and species sampling problems. However, in order to fully exploit these priors, the derivation of the posterior distribution of NRMIs is crucial: here we achieve this goal and, indeed, provide explicit and tractable expressions suitable for practical implementation. The posterior distribution of an NRMI turns out to be a mixture with respect to the distribution of a specific latent variable. The analysis is completed by the derivation of the corresponding predictive distributions and by a thorough investigation of the marginal structure. These results allow to derive a generalized Blackwell–MacQueen sampling scheme, which is then adapted to cover also mixture models driven by general NRMIs.     

An Examination of the Dual Model of Perfectionism and Adolescent Athlete Burnout: A Short-Term Longitudinal Research

The dual model of perfectionism (Slade and Owens, Behav Modificat 22(3):372–390, 1998) is adopted to examine the influence of adaptive and maladaptive perfectionism on adolescent athlete burnout in Taiwan. Participants were 188 high school adolescent student-athletes (M = 16.48, SD = .59). They were administered the Multidimensional Inventory of Perfectionism in Sport (Stoeber et al., Pers Individ Dif 43(1):131–141, 2007) and the Chinese Athlete Burnout Questionnaire (ABQ) (Lu et al., Phys Educ J 39(3):83–94, 2006). A field longitudinal design was used. In cross-sectional analyses, hierarchical multiple regressions indicated that adaptive perfectionism negatively predicted athlete burnout while maladaptive perfectionism had an inverse relationship with burnout. However, after controlling for the initial scores of burnout, neither adaptive nor maladaptive perfectionism significantly predicted athlete burnout after a three month interval. Possible mechanisms of this relation, limitations, and practical implications are discussed.     

Modified genetic algorithm-based clustering for probability density functions

This article modifies two internal validity measures and applies them to evaluate the quality of clustering for probability density functions (pdfs). Based on these measures, we propose a new modified genetic algorithm called GA-CDF to establish the suitable clusters for pdfs. The proposed algorithm is tested by four numerical examples including two synthetic data sets and two real data sets. These examples illustrate the superiority of proposed algorithm over some existing algorithms in evaluating the internal or external validity measures. It demonstrates the feasibility and applicability of the GA-CDF for practical problems in data mining.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

Generalized correlation and kernel causality with applications in development economics

New generalized correlation measures of 2012, GMC(Y|X), use Kernel regressions to overcome the linearity of Pearson's correlation coefficients. A new matrix of generalized correlation coefficients is such that when |r*_ij| > |r*_ji|, it is more likely that the column variable X_j is what Granger called the “instantaneous cause” or what we call “kernel cause” of the row variable X_i. New partial correlations ameliorate confounding. Various examples and simulations support robustness of new causality. We include bootstrap inference, robustness checks based on the dependence between regressor and error, and on the out-of-sample forecasts. Data for 198 countries on nine development variables support growth policy over redistribution and Deaton's criticism of foreign aid. Potential applications include Big Data, since our R code is available in the online supplementary material.     

Comparison of preliminary test estimators based on generalized order statistics from proportional hazard family using Pitman measure of closeness

In this article, based on generalized order statistics from a family of proportional hazard rate model, we use a statistical test to generate a class of preliminary test estimators and shrinkage preliminary test estimators for the proportionality parameter. These estimators are compared under Pitman measure of closeness (PMC) as well as MSE criteria. Although the PMC suffers from non transitivity, in the first class of estimators, it has the transitivity property and we obtain the Pitman-closest estimator. Analytical and graphical methods are used to show the range of parameter in which preliminary test and shrinkage preliminary test estimators perform better than their competitor estimators. Results reveal that when the prior information is not too far from its real value, the proposed estimators are superior based on both mentioned criteria.