战略性粮食产品的界定及其流通控制力

提高我国战略性粮食产品流通控制力,要完善战略性粮食产品的流通支持政策,加强对战略性粮食产品的质量监控和品牌培育,加大对各地区粮油龙头企业的支持力度;完善战略性粮食产品流通市场准入政策,进一步明确粮食收购、粮食和植物油等产品的批发、零售、配送等限制类产业的具体实施细节;加强对战略性粮食产品中薄弱品种和薄弱环节的监管;大力培育有国际竞争力的粮食流通企业,支持国有粮食流通企业"走出去",在全球市场配置资源,实现国内、国际市场互动。     

三维价值链视阈下科技成果转化知识供给体系研究

科技成果转化知识供给是指知识沿价值链不同维度，经过耦合与交流，形成知识供给体系，对其探索可推动知识的精准供给和有序流动。基于全程价值链视角，从3个维度剖析科技成果转化知识供给体系的特征与机理。在纵向维度中，知识供给纵贯创意→设计→实验→中试→量产→销售等价值环节，并经历知识分化、加工、增值、包装与应用；在横向维度中，科技成果转化知识供给内含于各价值模块中，具有半自律化特征；在网络维度中，知识供给嵌于价值网络中，具有开放组合性、跨领域交叉性与跨疆界性。     

Selection of influential variables in ordinal data with preponderance of zeros

Presence of excess zero in ordinal data is pervasive in areas like medical and social sciences. Unfortunately, analysis of such kind of data has so far hardly been looked into, perhaps for the reason that the underlying model that fits such data, is not a generalized linear model. Obviously some methodological developments and intensive computations are required. The current investigation is concerned with the selection of variables in such models. In many occasions where the number of predictors is quite large and some of them are not useful, the maximum likelihood approach is not the automatic choice. As, apart from the messy calculations involved, this approach fails to provide efficient estimates of the underlying parameters. The proposed penalized approach includes ?₁ penalty (LASSO) and the mixture of ?₁ and ?₂ penalties (elastic net). We propose a coordinate descent algorithm to fit a wide class of ordinal regression models and select useful variables appearing in both the ordinal regression and the logistic regression based mixing component. A rigorous discussion on the selection of predictors has been made through a simulation study. The proposed method is illustrated by analyzing the severity of driver injury from Michigan upper peninsula road accidents.     

Optimal model averaging forecasting in high-dimensional survival analysis

This article considers ultrahigh-dimensional forecasting problems with survival response variables. We propose a two-step model averaging procedure for improving the forecasting accuracy of the true conditional mean of a survival response variable. The first step is to construct a class of candidate models, each with low-dimensional covariates. For this, a feature screening procedure is developed to separate the active and inactive predictors through a marginal Buckley–James index, and to group covariates with a similar index size together to form regression models with survival response variables. The proposed screening method can select active predictors under covariate-dependent censoring, and enjoys sure screening consistency under mild regularity conditions. The second step is to find the optimal model weights for averaging by adapting a delete-one cross-validation criterion, without the standard constraint that the weights sum to one. The theoretical results show that the delete-one cross-validation criterion achieves the lowest possible forecasting loss asymptotically. Numerical studies demonstrate the superior performance of the proposed variable screening and model averaging procedures over existing methods.     

Semiparametric time series regression modeling with a diverging number of parameters

Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite‐sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.     

一种利用均匀圆阵对称特性的近场源酉变换估计算法

针对现有均匀圆阵的近场源三维参数估计算法运算量大的缺点，提出了一种基于均匀圆阵对称特性的近场源酉变换估计算法。该算法利用均匀圆阵对称特性将阵列导向矢量进行酉变换和对角化分离处理，消除距离参数，把三维搜索问题化简为二维搜索问题，同时把复值方向矢量转化为实值方向矢量。计算机仿真结果显示,所提算法估计性能优于相关序列降维估计方法，与三维多重信号分类算法性能相当，且通过矩阵分离降维和实值化处理，减少了运算量，有利于工程实时处理。     

Existence of Lévy term structure models

Lévy driven term structure models have become an important subject in the mathematical finance literature. This paper provides a comprehensive analysis of the Lévy driven Heath–Jarrow–Morton type term structure equation. This includes a full proof of existence and uniqueness in particular, which seems to have been lacking in the finance literature so far.      

Structural measurement errors in nonseparable models

This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly. We explore the consequences of limited recall for the identification of marginal effects. Our identification approach is entirely nonparametric, using Matzkin-type nonseparable models that nest a large class of potential structural models. We show that measurement error due to limited recall will generally exhibit nonstandard behavior, in particular be nonclassical and differential, even for left-hand side variables in linear models. We establish that information reduction by individuals is the critical issue for the severity of recall measurement error. In order to detect information reduction, we propose a nonparametric test statistic. Finally, we propose bounds to address identification problems resulting from recall errors. We illustrate our theoretical findings using real-world data on food consumption.     

非遗保护中政府角色和路径研究——以壮锦为例

生产方式和生活方式的变迁使得非物质文化遗产在民间的自发保护传承难以为继,而市场化道路也导致了这种保护传承面临危机。党和政府是民族优秀传统文化的忠实传承者和弘扬者,因而在民族优秀传统文化或非遗保护传承工作上,必须将自己定位于主角,做领导者和组织者。要从非遗对象的静态、动态和意态几个层面,从实物保存、技艺传习和精神内涵阐发等角度实施全方位的保护,走立体保护传承路径。     

OpenGL矿山虚拟设计及其应用

设计了系统的基本思路,在Visual Studio 2008数据库的基础上,利用OpenGL对矿山巷道,硐室设计等进行三维可视化虚拟,并通过数学模型,对矿井设计进行分析与纠错处理,用C#实现系统的功能。