中国古代文人的“鸡肋意识”及其人生选择

中国古代文人士大夫的文学作品中屡屡涉及"鸡肋"一词,"鸡肋"被文士赋予之身体、个人,乃至名利、功业、仕宦,甚至人生意味等多重内蕴,展现出文士对世俗价值的矛盾心态及其身处"势"与"道"之间两难的人生困境,并由古代文人不同的人生选择见出"吏隐"的局限性,体现出正直士大夫舍身求法的历史进步意义。     

非通用语工程师培养的教学与实践--以北航中法工程师学院为例

中国高等教育国际化引出了高等教育与非通用语国家的合作新模式。通过分析非通用语工程师培养的特点指出,一方面,工程师培养模式下的非通用语教学与中国现有的外语专业教学与第二外语教学都存在差别,另一方面,工程师专业课程非通用语授课也不同于国内理工科专业课程的双语教学。针对非通用语工程师人才培养中存在的问题,以北京航空航天大学中法工程师学院为例,从课程设置、课程融合以及教学组织形式等方面来加强非通用语的工程师培养,旨在为中国非通用语国际教育合作提供新的思路。     

VARIABLE SELECTION AND REGRESSION ANALYSIS FOR GRAPH-STRUCTURED COVARIATES WITH AN APPLICATION TO GENOMICS

Graphs and networks are common ways of depicting information. In biology, many different biological processes are represented by graphs, such as regulatory networks, metabolic pathways and protein-protein interaction networks. This kind of a priori use of graphs is a useful supplement to the standard numerical data such as microarray gene expression data. In this paper, we consider the problem of regression analysis and variable selection when the covariates are linked on a graph. We study a graph-constrained regularization procedure and its theoretical properties for regression analysis to take into account the neighborhood information of the variables measured on a graph, where a smoothness penalty on the coefficients is defined as a quadratic form of the Laplacian matrix associated with the graph. We establish estimation and model selection consistency results and provide estimation bounds for both fixed and diverging numbers of parameters in regression models. We demonstrate by simulations and a real dataset that the proposed procedure can lead to better variable selection and prediction than existing methods that ignore the graph information associated with the covariates.     

当代大学生学习特点浅析

通过对大学生学习特点的分析和归纳,旨在帮助大学生能尽快适应大学的教学规律,掌握大学的学习特点,选择适合自己的高效的学习方法,从而圆满地完成大学学业,为适应社会需要奠定坚实的基础。     

An Additive Genetic Gamma Frailty Model for Linkage Analysis of Diseases with Variable Age of Onset Using Nuclear Families

Many late-onset complex diseases exhibit variable age of onset. Efficiently incorporating age of onset information into linkage analysis can potentially increase the power of dissecting complex diseases. In this paper, we treat age of onset as a genetic trait with censored observations. We use multiple markers to infer the inheritance vector at the disease susceptibility (DS) locus in order to extract information about the inheritance pattern of the disease allele in a pedigree. Given the inheritance distribution at the DS locus, we define the genetic frailty for each individual within a nuclear family as the sum of frailties due to a putative major disease gene and a polygenic effect due to any remaining DS loci. Conditioning on these frailties we use the proportional hazards model for the risk of developing disease. We show that a test of linkage can be formulated as a test of zero variance due to a specific locus of the additive gamma frailties. Maximum likelihood estimation, using the EM algorithm, and likelihood ratio tests are employed for parameter estimation and tests of linkage. A simulation study presented indicates that the proposed method is well behaved and can be more powerful than the currently available allele-sharing based linkage methods. A breast cancer data example is used for illustration.     

员工持股计划、企业金融化与企业创新关系的实证研究

在我国加快推进社会主义现代化的背景下，企业创新是推进我国经济发展转型的关键变量。员工持股计划对企业创新具有明显的促进作用，但由于实体投资见效慢、回报率低，导致企业管理者将闲置资金过度投放至金融行业，从而挤占创新资源，使得企业脱实向虚现象严重。金融资产投资作为公司内部资金管理的一部分，其在员工持股计划与企业创新的关系中所发挥的作用值得探讨。文章选取2014—2021年A股上市公司为研究样本，实证研究了员工持股计划与企业创新的影响机制。研究结果显示，实施员工持股计划对企业创新具有显著促进作用；实施员工持股计划能够抑制企业金融化从而促进企业创新；员工持股计划在非国有企业的创新激励效应更显著。     

The Sparse Laplacian Shrinkage Estimator for High-Dimensional Regression

We propose a new penalized method for variable selection and estimation that explicitly incorporates the correlation patterns among predictors. This method is based on a combination of the minimax concave penalty and Laplacian quadratic associated with a graph as the penalty function. We call it the sparse Laplacian shrinkage (SLS) method. The SLS uses the minimax concave penalty for encouraging sparsity and Laplacian quadratic penalty for promoting smoothness among coefficients associated with the correlated predictors. The SLS has a generalized grouping property with respect to the graph represented by the Laplacian quadratic. We show that the SLS possesses an oracle property in the sense that it is selection consistent and equal to the oracle Laplacian shrinkage estimator with high probability. This result holds in sparse, high-dimensional settings with p ? n under reasonable conditions. We derive a coordinate descent algorithm for computing the SLS estimates. Simulation studies are conducted to evaluate the performance of the SLS method and a real data example is used to illustrate its application.     

Ascertainment-Adjusted Maximum Likelihood Estimation for the Additive Genetic Gamma Frailty Model

The additive genetic gamma frailty model has been proposed for genetic linkage analysis for complex diseases to account for variable age of onset and possible covariates effects. To avoid ascertainment biases in parameter estimates, retrospective likelihood ratio tests are often used, which may result in loss of efficiency due to conditioning. This paper considers when the sibships are ascertained by having at least two affected sibs with the disease before a given age and provides two approaches for estimating the parameters in the additive gamma frailty model. One approach is based on the likelihood function conditioning on the ascertainment event, the other is based on maximizing a full ascertainment-adjusted likelihood. Explicit forms for these likelihood functions are derived. Simulation studies indicate that when the baseline hazard function can be correctly pre-specified, both approaches give accurate estimates of the model parameters. However, when the baseline hazard function has to be estimated simultaneously, only the ascertainment-adjusted likelihood method gives an unbiased estimate of the parameters. These results imply that the ascertainment-adjusted likelihood ratio test in the context of the additive genetic gamma frailty may be used for genetic linkage analysis.