妇产科教学如何应对新的医疗环境

近年来，患者维权意识增强，医患关系紧张，妇产科教学面临着缺乏实践教学对象，教学任务不能落实的尴尬局面。只有在教学中渗透医德教育，提高医疗风险意识，加强教师素质培训，尽力协调好医患关系，应用先进科学的教学方法，才能保证教学质量，从而使妇产科教学落到实处。     

A Repetitive Branch-and-Bound Procedure for Minimum Within-Cluster Sums of Squares Partitioning

Minimization of the within-cluster sums of squares (WCSS) is one of the most important optimization criteria in cluster analysis. Although cluster analysis modules in commercial software packages typically use heuristic methods for this criterion, optimal approaches can be computationally feasible for problems of modest size. This paper presents a new branch-and-bound algorithm for minimizing WCSS. Algorithmic enhancements include an effective reordering of objects and a repetitive solution approach that precludes the need for splitting the data set, while maintaining strong bounds throughout the solution process. The new algorithm provided optimal solutions for problems with up to 240 objects and eight well-separated clusters. Poorly separated problems with no inherent cluster structure were optimally solved for up to 60 objects and six clusters. The repetitive branch-and-bound algorithm was also successfully applied to three empirical data sets from the classification literature.     

A branch-and-bound algorithm for fitting anti-robinson structures to symmetric dissimilarity matrices

The seriation of proximity matrices is an important problem in combinatorial data analysis and can be conducted using a variety of objective criteria. Some of the most popular criteria for evaluating an ordering of objects are based on (anti-) Robinson forms, which reflect the pattern of elements within each row and/or column of the reordered matrix when moving away from the main diagonal. This paper presents a branch-and-bound algorithm that can be used to seriate a symmetric dissimilarity matrix by identifying a reordering of rows and columns of the matrix optimizing an anti-Robinson criterion. Computational results are provided for several proximity matrices from the literature using four different anti-Robinson criteria. The results suggest that with respect to computational efficiency, the branch-and-bound algorithm is generally competitive with dynamic programming. Further, because it requires much less storage than dynamic programming, the branch-and-bound algorithm can provide guaranteed optimal solutions for matrices that are too large for dynamic programming implementations.     

中国经济伦理学研究中的若干问题——兼论经济伦理学的学科性质

中国经济伦理学的研究虽然成果显著,但还存在着需要进一步澄清的三个相互关联的重要问题,即“理论性”与“应用性”问题、“伦理学”与“经济学”问题、以及“理想性”与“现实性”问题。这三个问题的正确理解有助于关于经济伦理学学科性质的合理界定,也有助于中国经济伦理学研究的继续深入。     

An evaluation of exact methods for the multiple subset maximum cardinality selection problem

The maximum cardinality subset selection problem requires finding the largest possible subset from a set of objects, such that one or more conditions are satisfied. An important extension of this problem is to extract multiple subsets, where the addition of one more object to a larger subset would always be preferred to increases in the size of one or more smaller subsets. We refer to this as the multiple subset maximum cardinality selection problem (MSMCSP). A recently published branch‐and‐bound algorithm solves the MSMCSP as a partitioning problem. Unfortunately, the computational requirement associated with the algorithm is often enormous, thus rendering the method infeasible from a practical standpoint. In this paper, we present an alternative approach that successively solves a series of binary integer linear programs to obtain a globally optimal solution to the MSMCSP. Computational comparisons of the methods using published similarity data for 45 food items reveal that the proposed sequential method is computationally far more efficient than the branch‐and‐bound approach.     

Payback: Effects of relationship and cultural norms on reciprocity

This experimental investigation explores differences in reciprocal norms between friends and strangers and the effects of culture on reciprocity. Based on altruistic and strong reciprocity theories, a hybrid trust‐dictator game tested the influence of relationship (i.e. friends vs. strangers), treatment (i.e. positive vs. negative) and culture (i.e. collectivistic vs. individualistic) on reciprocation. The results show that participants reciprocated more positively when treated positively in general. However, the results demonstrate intercultural differences in reciprocal norms, specifically in the negative treatment condition. Participants from the individualistic culture provided stronger punishment to the norm violator, compared to participants from the collectivistic culture. We discuss implications of the impact of relationship and culture on reciprocation with respect to the olive branch response.     

妇科手术微创化趋势的人文思考

妇科患者是一个普遍而又特殊的病患群体,心理敏感细腻,追求外在美及女性特征,要求保护个人隐私,对于人文关怀有更高的要求。微创化妇科手术在最小创伤的基础上,最大程度地解除了患者的痛苦,体现了高度的人文关怀,也暴露出一些问题,值得我们关注和思考。     

妇科内分泌疾病诊疗的从优选择

妇科内分泌疾病是常见病,包括功能失调性子宫出血、痛经、闭经及多囊卵巢综合征,等等.优化诊疗措施,即依据这些患者的具体情况有选择地应用药物及其它处理方法.文章对该类疾病诊疗的基本内容和措施进行了理性的分析.     

Optimal Partitioning of a Data Set Based on the p-Median Model

Although the K-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The p-median model is an especially well-studied clustering problem that requires the selection of p objects to serve as cluster centers. The objective is to choose the cluster centers such that the sum of the Euclidean distances (or some other dissimilarity measure) of objects assigned to each center is minimized. Using 12 data sets from the literature, we demonstrate that a three-stage procedure consisting of a greedy heuristic, Lagrangian relaxation, and a branch-and-bound algorithm can produce globally optimal solutions for p-median problems of nontrivial size (several hundred objects, five or more variables, and up to 10 clusters). We also report the results of an application of the p-median model to an empirical data set from the telecommunications industry.     

浅谈科主任非权力性影响力的培养

科主任的非权力性影响力是由本人的素质和行为造成的,也可以说是个人的影响、威望和威信,这主要靠领导者具有良好的品格、素质和能力。本文就科主任应具备的良好的职业道德和人格魅力、丰富的才能和渊博的知识、良好的自制能力和人际关系、严谨的工作作风和高超的专业技术等这些非权力影响力进行了分析,并对如何提高这些素质进行了阐述。