《全国主体功能区规划》实施阻力及其解决路径探讨

《全国主体功能区规划》的出台,完善了中国国土规划体系,并从制度上落实了区域协调发展理念,具有重要战略意义。但是,《规划》的落实因为缺乏全国可比的标准,无法建立可行的利益补偿机制而遇到了受限地方不配合的内在阻力以及来自制度环境的外在阻力。为了化解这两重阻力,在《规划》框架内,提出了省级分区及其开发强度确定的思路与方法,从而明确划分出补偿区域和受偿区域及其补偿标准,为构建合理科学的区域补偿机制提供科学依据,最终实现区域利益均衡,推进《规划》的执行与落实。     

Mixed integer programming formulations for clustering problems related to structural balance

In this work, we study graph clustering problems associated with structural balance. One of these problems is known in computer science literature as the correlation-clustering (CC) problem and another (RCC) can be viewed as its relaxed version. The solution of CC and RCC problems has been previously used in the literature as tools for the evaluation of structural balance in a social network. Our aim is to solve these problems to optimality. We describe integer linear programming formulations for these problems which includes the first mathematical formulation for the RCC problem. We also discuss alternative models for the relaxed structural balance and the solution of clustering problems associated with these new models. Numerical experiments are carried out with each formulation on a set of benchmark instances available in the literature.     

离婚案件中专利申请权分割

专利申请权的期限较长,在此期间,申请专利的夫妻婚姻破裂时就会遇到专利申请权的分割分配问题。我国《婚姻法》及其《司法解释》仅对夫妻双方离婚时已获得专利权的收益进行了规定,而对正在审批过程中的专利申请权是否应该分割以及如何分割的规定不明确。专利申请权具有自身价值,并可取得相应的经济利益,在离婚案件中,其财产权利应作为夫妻共同财产进行分割。     

Confidence Intervals and the Within-the-Bar Bias

Bar graphs displaying means have been shown to bias interpretations of the underlying distributions: viewers typically report higher likelihoods for values within a bar than outside of a bar. One explanation is that viewer attention is driven by the whole bar, rather than only the edge that provides information about an average. This study explored several approaches to correcting this bias. Bar graphs with 95% confidence intervals were used with different levels of contrast to manipulate attention directed to the bar. Viewers showed less bias when the salience of the bar itself was reduced. Response latencies were lowest and bias was eliminated when participants were presented with only a confidence interval and no bar.     

Minimum entropy coloring

We study an information-theoretic variant of the graph coloring problem in which the objective function to minimize is the entropy of the coloring. The minimum entropy of a coloring is called the chromatic entropy and was shown by Alon and Orlitsky (IEEE Trans. Inform. Theory 42(5):1329–1339, 1996) to play a fundamental role in the problem of coding with side information. In this paper, we consider the minimum entropy coloring problem from a computational point of view. We first prove that this problem is NP-hard on interval graphs. We then show that, for every constant ε>0, it is NP-hard to find a coloring whose entropy is within (1−ε)log n of the chromatic entropy, where n is the number of vertices of the graph. A simple polynomial case is also identified. It is known that graph entropy is a lower bound for the chromatic entropy. We prove that this bound can be arbitrarily bad, even for chordal graphs. Finally, we consider the minimum number of colors required to achieve minimum entropy and prove a Brooks-type theorem. S. Fiorini acknowledges the support from the Fonds National de la Recherche Scientifique and GERAD-HEC Montréal. G. Joret is a F.R.S.-FNRS Research Fellow.     

On the upper total domination number of Cartesian products of graphs

In this paper we continue the investigation of total domination in Cartesian products of graphs first studied in (Henning, M.A., Rall, D.F. in Graphs Comb. 21:63–69, 2005). A set S of vertices in a graph G is a total dominating set of G if every vertex in G is adjacent to some vertex in S. The maximum cardinality of a minimal total dominating set of G is the upper total domination number of G, denoted by Γ _t (G). We prove that the product of the upper total domination numbers of any graphs G and H without isolated vertices is at most twice the upper total domination number of their Cartesian product; that is, Γ _t (G)Γ _t (H)≤2Γ _t (G □ H). Research of M.A. Henning supported in part by the South African National Research Foundation and the University of KwaZulu-Natal.     

Large sample results for permutation tests of association

This paper deals with the asymptotics of permutation tests based on a certain rather general class of measures of association for R by C contingency tables, given marginal totals. This class includes the classical chi-square test, the T _b and γ indices of Goodman and Kruskall (1954) and the popular Rand (1971) index. The asymptotic distribution of this class of permutation tests for association is a weighted sum of non-central (gen-erally speaking) chi-squares. The formulae for the asymptotic moments of such tests are also given. If non-centrality holds under the null hypothe-sis of independence, the distribution in question converges to the normal distribution. The efficacies for such measures of association are obtained. Several applications are analysed in detail, including the above mentioned indices. Approximations to the permutation distribution are also discussed.     

Information dependency: Strong consistency of Darbellay–Vajda partition estimators

The Darbellay–Vajda partition scheme is a well known method to estimate the information dependency. This estimator belongs to a class of data-dependent partition estimators. We would like to prove that with some simple conditions, the Darbellay–Vajda partition estimator is a strong consistency for the information dependency estimation of a bivariate random vector. This result is an extension of 20 and 21 work which gives some simple conditions to confirm that the Gessaman's partition estimator and the tree-quantization partition estimator, other estimators in the class of data-dependent partition estimators, are strongly consistent.     

Mantel-Haenszel estimators for irregular sparse K2×J tables

This paper deals with sparse K2×J(J>2)$K2\times J(J>2)$ tables. Projection-method Mantel–Haenszel (MH) estimators of the common odds ratios have been proposed for K2×J$K2\times J$ tables, which include Greenland's generalized MH estimator as a special case. The method projects log-transformed MH estimators for all K2×2$K2\times 2$ subtables, which were called naive MH estimators, onto a linear space spanned by log odds ratios. However, for sparse tables it is often the case that naive MH estimators are unable to be computed. In this paper we introduce alternative naive MH estimators using a graph that represents K2×J$K2\times J$ tables, and apply the projection to these alternative estimators. The idea leads to infinitely many reasonable estimators and we propose a method to choose the optimal one by solving a quadratic optimization problem induced by the graph, where some graph-theoretic arguments play important roles to simplify the optimization problem. An illustration is given using data from a case–control study. A simulation study is also conducted, which indicates that the MH estimator tends to have a smaller mean squared error than the MH estimator previously suggested and the conditional maximum likelihood estimator for sparse tables.     

新城市引力模型下辽宁省城市圈的划分

新城市引力模型引入城市职能参数,人口修正参数和经济距离修正参数,改进原来简单的城市引力模型,深入探讨城市职能对城市引力的影响。并运用新城市引力模型对辽宁省14个城市进行数据分析,并以沈阳与大连两个优势城市为中心计算城市引力。最终对辽宁省14个城市进行城市圈进行了划分,形成以沈阳为中心,大连为次中心的城市圈布局。