生物灾害的防治与社会变迁——青海省东部牧区的个案分析

在社会变迁的大背景下,青海牧区频发的鼠虫灾害是生态环境日趋恶化的产物,是由于人类不恰当的活动所造成的生态灾难的一种表现形式。因此,牧区鼠虫灾害的防治,还需要从保持和维护生物多样性的高度,以科学的发展观为指导,通过科技创新,建立和完善生态补偿机制等具有针对性的举措,以实现人、社会与自然的协调发展。唯此,才能从根本上解决鼠虫等生物灾害的历史难题。     

中国人口学会第七届会员代表大会暨第九次全国人口科学讨论会综述及学会领导机构名单

2007年12月28～29日,中国人口学会第七届会员代表大会暨第九次全国人口科学讨论会在北京中苑宾馆隆重开幕.参加会议的有第九届全国人大常委会副委员长、中国人口学会第六届会长彭佩云,国家人口计生委主任张维庆,国家人口计生委党组书记、副主任李斌,副主任王培安以及各地人口学会的代表.会议主要由三部分组成:开幕式,学术研讨会和换届选举.大会结束后,第七届学会常务理事会举行了第一次会议.     

农村社会变迁中女性对家务分工的期望及其影响因素研究--基于安徽居巢农村地区的调查研究

本文利用西安交通大学人口与发展研究所2005年对安徽居巢农村居民调查获得的数据．分析了以女性要求丈夫分担家务为代表的农村女性对家务分工的期望及其影响因素。研究结果发现,随着农村社会变迁,女性对丈夫分担家务的期望和要求在改变。资源因素,如收入和教育,会转化为协商权力,是影响女性要求丈夫分担家务的重要因素。性别意识因素则没有显著影响。时间可及性因素,如家庭是否非农经营和子女数,家庭生命周期因素,如是否是桉心家庭和居住地,对女性要求丈夫分担家务有显著影响。     

The Age of Migration in China

Using data from the 1987 and 1995 China One Percent Population Sample Surveys, this article examines migration patterns during 1982–95, a period of sweeping social and economic changes in China. Several major patterns are evident: the increase in overall migration and especially in temporary migration, the increasing importance of inter‐provincial migration, and the concentration of migrants in the coastal region. Over time, migrants of rural origin were more likely to choose cities as destinations than towns. The consequences and implications of the changes in migration patterns are explored.     

论沈德潜诗学的“中庸”特征

沈德潜的格调论是儒家诗论的总结,合"道"的中庸性是其诗论的总特征,他的诗学思想在传统文化语境中近乎完美。沈德潜"温柔敦厚"的诗教合乎理学驯化人格道德的要求,反对过度激越的情感抒发。他能够抑平唐宋之争,避免明七子的门户之见,诗论中坚持思想性和艺术性的统一,识见超出了一般的儒家诗论。     

文化旅游产品开发的路径与模式研究

对文化概念的正确理解和文化区别特征中旅游元素的合理挖掘是文化旅游资源产品开发的首要问题。研究发现,旅游者对现代性的感知程度与对旅游真实性的追求呈现U型曲线关系而非L型曲线关系,这主要是受旅游者自身文化以及由此引发旅游者体验动机差异的影响。这一点是正确分析文化旅游产品市场需求和产品定位的关键。通过综合运用社会空间理论、旅游体验模式和原真性理论等,笔者提出5种文化旅游产品开发模式,即文化遗址遗迹类旅游产品、文化历史建筑群类旅游产品、文化景观遗产类旅游产品、文化主题公园类旅游产品、文化演艺类旅游产品,并对不同模式产品开发的形式、内容和条件进行深度分析。     

Testing homogeneity in semiparametric mixture case–control models

Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test the homogeneity in these models. However, hypothesis testing is non standard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case–control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (2011 Qin, J., Liang, K.Y. (2011). Hypothesis testing in a mixture case–control model. Biometrics 67(1):182–198.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], biometrics), and they proposed a modified score statistic for testing homogeneity. In this article, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among the proposed and existing approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite-sample performance of the supremum test statistics was evaluated in simulation studies.     

A new confidence interval in measurement error model with the reliability ratio known

For the slope parameter of the measurement error model with the reliability ratio known, this article constructs a fiducial generalized confidence interval (FGCI) which is proved to have correct asymptotic coverage. Simulation results demonstrate that the FGCI often outperforms the existing intervals in terms of empirical coverage probability, average interval length, and false parameter coverage rate. Two examples are also provided to illustrate our approach.     

Parallel and interacting stochastic approximation annealing algorithms for global optimisation

We present the parallel and interacting stochastic approximation annealing (PISAA) algorithm, a stochastic simulation procedure for global optimisation, that extends and improves the stochastic approximation annealing (SAA) by using population Monte Carlo ideas. The efficiency of standard SAA algorithm crucially depends on its self-adjusting mechanism which presents stability issues in high dimensional or rugged optimisation problems. The proposed algorithm involves simulating a population of SAA chains that interact each other in a manner that significantly improves the stability of the self-adjusting mechanism and the search for the global optimum in the sampling space, as well as it inherits SAA desired convergence properties when a square-root cooling schedule is used. It can be implemented in parallel computing environments in order to mitigate the computational overhead. As a result, PISAA can address complex optimisation problems that it would be difficult for SAA to satisfactory address. We demonstrate the good performance of the proposed algorithm on challenging applications including Bayesian network learning and protein folding. Our numerical comparisons suggest that PISAA outperforms the simulated annealing, stochastic approximation annealing, and annealing evolutionary stochastic approximation Monte Carlo.     

t-Type corrected-loss estimation for error-in-variable model

In this article, we consider a linear model in which the covariates are measured with errors. We propose a t-type corrected-loss estimation of the covariate effect, when the measurement error follows the Laplace distribution. The proposed estimator is asymptotically normal. In practical studies, some outliers that diminish the robustness of the estimation occur. Simulation studies show that the estimators are resistant to vertical outliers and an application of 6-minute walk test is presented to show that the proposed method performs well.