汉代蝗灾论略

蝗灾是中国古代一种非常严重的自然灾害。汉代蝗灾在时间分布上有明显的季节性 ,空间分布上有明显的地域性 ;成灾面积广阔 ,灾情严重 ;蝗灾具有群发性、连锁性特点。对后世开展治蝗、灭蝗工作有一定的借鉴意义。     

辽宁部分高中田径选项课的现状及发展对策

采用问卷调查、专家访谈、文献资料等方法,对辽宁省重点、普通中学高中开设田径选项课的现状进行了调查分析.研究发现,当前辽宁省重点、普通高中田径选项课正面临困境.究其原因,主要是教师对田径选项课的价值认识不足;此外,当前的田径选项课缺乏趣味性,使学生产生厌学情绪.结合健康体育教育及终身体育教育,对田径选项课在中学体育课中的地位与作用进行了论述,并针对中学田径选项课的发展提出积极的对策和建议;同时,为解决高校田径选项课中的问题提供了参考与借鉴.     

铸件凝固温度场数值模拟中动态边界条件的通用化

本文将铸件以外的一切影响因素视为一种假想的特殊介质,结合生产实际获得了三种砂型冷却条件下的两种动态边界条件,在求解区域只包括铸件的计算凝固温度场的算法中,所给动态边界条件的准确性决定着该种算法的成败,而动态边界条件的通用性则决定着该种算法的应用前景。笔者在提出上述两种动态边界条件的基础上,又提出模数修正法,使得两种动态边界条件在铸件形状不同的条件下通用,且修正后计算误差最大不超过0.27%。而且使用该动态边界条件进行数值模拟,与传统的摸拟方法相比,可节省计算机内存和机时60—80%。     

城市哈萨克族的宴请活动与多元文化

本文从城市哈萨克族的人口规模入手,探讨了城市哈萨克族宴请活动的目的、模式、共时性质、历时变化,由此得出结论城市哈萨克的宴请文化和其他民族宴请文化一起,共同构成新疆独特的文化资源优势,研究它旨在努力将它转化为开发项目,以便在开发大西北战略目标实施过程中,逐步将其转化为新疆人民的共同财富。     

A Note on High-Dimensional Linear Regression With Interactions

The problem of interaction selection in high-dimensional data analysis has recently received much attention. This note aims to address and clarify several fundamental issues in interaction selection for linear regression models, especially when the input dimension p is much larger than the sample size n. We first discuss how to give a formal definition of “importance” for main and interaction effects. Then we focus on two-stage methods, which are computationally attractive for high-dimensional data analysis but thus far have been regarded as heuristic. We revisit the counterexample of Turlach and provide new insight to justify two-stage methods from the theoretical perspective. In the end, we suggest new strategies for interaction selection under the marginality principle and provide some simulation results.     

Who Is the Residential Parent? Understanding Discrepancies in Unmarried Parents' Reports

Research examining parental reports of children's living arrangements has often relied on information about legally ordered custody agreements following divorce. This analysis used data from matched pairs of parents (N = 1,156) in the Fragile Families and Child Wellbeing Study who live apart to compare mother and father reports of their child's residence 5 years after a nonmarital birth. The authors found that over one third of unmarried parents disagreed about who their child lived with and that conflicting reports were much more likely when fathers spent nights with the mother (an indicator of part‐time cohabitation) and had overnights with the child on their own. The results further suggest that discrepancies in unmarried parents' reports were more closely associated with the complexity and ambiguity of their living situations than with the quality of their relationships with each other. Implications for measuring children's living arrangements in families formed outside of marriage are discussed.     

《周易》与儒释道

《周易》是我国传统文化的根干,儒家奉为群经之首,道家奉为道藏三玄之首。佛教传入中国,与儒道合而为一,并构成中国传统文化的基础。易家的太极、儒家的天命、道家的道、佛家的空,皆是宇宙全息图的不同体现方式,是宇宙万有生存准则的不同表述。     

城市居家老人生活质量研究——以上海为例

本文针对城市居家老人的需要和特点,从评估城市居家老人生活质量的六个维度即经济状况与消费水平、居住条件与家庭设施、躯体健康与心理健康、社会支持、闲暇生活质量、生活满意度方面入手,深入开发了上海市老年人口状况与意愿跟踪调查数据资料,使用分等级加权评分法综合评估了城市居家老人生活质量以及分性别和年龄的老人生活质量。     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.