University−Urban High School Partnership: Math and Science Professional Learning Communities

This study focused on science and math professional learning communities (PLCs) that were implemented through a university‐urban high school partnership. These PLCs were part of mandated school‐wide, content‐based PLCs implemented as part of the reform efforts initiated in an urban school to address the school's failure to meet Adequate Yearly Progress (AYP) for four years consecutively and low graduation rate (less than 25%) for male students. The key issues were (a) students had continually earned low test scores; (b) there was continuous principal turnover; (c) faculty morale was at an all‐time low, and the quality of teaching was very poor; and (d) the students were not effectively disciplined. The study examined the impact that university faculty‐led mandated PLCs have on teachers' practices and students' learning and achievement. Analysis of data revealed practices that were effective in developing and implementing these successful math and science PLCs. Three themes emerged: ethics of care, teacher agency, and aesthetics of professional interactions. Each theme contained key features that appeared to contribute to the implementation of a successful PLC.     

专业学习共同体对化学全日制教育硕士课堂教学的影响

收集3位化学全日制教育硕士在中学实践过程中文本、视频等资料,采用个案研究、文本分析、课堂观察的质化方法,利用化学课堂教学系统构造模型对专业学习共同体多元成员的干预以及实践过程中化学全日制教育硕士的课堂教学进行分析和比较。结果表明:化学全日制教育硕士的课堂教学在专业学习共同体的干预下,发生了显著的变化,构造模型中的各个教学要素均有不同程度的提升,专业学习共同体中不同成员对全日制教育硕士教学的干预内容、作用效果、影响程度有所差异,并在此基础上建立教学变化模型。多元成员的专业学习共同体可以促进全日制教育硕士的教学发展,为教育硕士的培养改革提供了一种可供参考的实践干预范式。     

Detect local communities in networks with an outside rate coefficient

In this paper, we present a local method for detecting communities in networks. We define an outside rate coefficient _ψout${\psi }_{out}$ in our method. _ψout${\psi }_{out}$ has a very simple form and is easy to calculate. The local community enclosing a starting node can be detected by agglomerating the node with the smallest _ψout${\psi }_{out}$ at each time step. When there are two or more nodes having the same smallest outside rate coefficient _ψout${\psi }_{out}$, we agglomerate the node with the largest _kin$k_{in}$. This operation is remarkably beneficial to the accuracy of our method, and simulations on benchmark networks and real networks demonstrate that our local method is efficient to detect communities in networks.     

Detection of community overlap according to belief propagation and conflict

Most existing methods for detection of community overlap cannot balance efficiency and accuracy for large and densely overlapping networks. To quickly identify overlapping communities for such networks, we propose a new method that uses belief propagation and conflict (PCB) to occupy communities. We first identify triangles with maximal clustering coefficients as seed nodes and sow a new type of belief to the seed nodes. Then the beliefs explore their territory by occupying nodes with high assent ability. The beliefs propagate their strength along the graph to consolidate their territory, and conflict with each other when they encounter the same node simultaneously. Finally, the node membership is judged from the belief vectors. The PCB time complexity is nearly linear and its space complexity is linear. The algorithm was tested in extensive experiments on three real-world social networks and three computer-generated artificial graphs. The experimental results show that PCB is very fast and highly reliable. Tests on real and artificial networks give excellent results compared with three newly proposed overlapping community detection algorithms.     

基于社团结构的城市地铁网络模型研究

本文运用复杂网络理论, 对我国北京、上海、广州和深圳等城市的地铁网络进行了实证研究. 分别研究了地铁网络的度分布、聚类系数和平均路径长度. 研究表明, 该网络具有高的聚类系数和短的平均路径长度, 显示小世界网络的特征, 其度分布并不严格服从幂律分布或指数分布, 而是呈多段的分布, 显示层次网络的特征. 此外, 它还具有重叠的社团结构特征. 基于实证研究的结果, 提出一种基于社团结构的交通网络模型, 并对该模型进行了模拟分析, 模拟结果表明, 该模型的模拟结果与实证研究结果相符. 此外, 该模型还能解释其他类型的复杂网络(如城市公共汽车交通网络)的网络特性. 关键词： 复杂网络 地铁网络 小世界 社团     

Efficient overlapping community detection in huge real-world networks

The detection of overlapping community structure in networks can give insight into the structures and functions of many complex systems. In this paper, we propose a simple but efficient overlapping community detection method for very large real-world networks. Taking a high-quality, non-overlapping partition generated by existing, efficient, non-overlapping community detection methods as input, our method identifies overlapping nodes between each pair of connected non-overlapping communities in turn. Through our analysis on modularity, we deduce that, to become an overlapping node without demolishing modularity, nodes should satisfy a specific condition presented in this paper. The proposed algorithm outputs high quality overlapping communities by efficiently identifying overlapping nodes that satisfy the above condition. Experiments on synthetic and real-world networks show that in most cases our method is better than other algorithms either in the quality of results or the computational performance. In some cases, our method is the only one that can produce overlapping communities in the very large real-world networks used in the experiments.     

多元时间序列复杂网络流型动力学分析

针对气液两相流流动特性,利用有限元分析方法设计变曲率对壁式电导传感器.采用设计加工的传感器在多相流装置上进行气液两相流动态实验,并测得多组对应于不同流型的电导波动信号. 基于测量数据,采用多元时间序列复杂网络构建算法构建对应于不同流型的复杂网络.在此基础上, 对网络的社团特性进行了分析, 研究发现,不同的社团结构对应于不同的流型,而社团内部网络特征可有效刻画不同流型内在动力学特性.多元时间序列复杂网络分析可为两相流流型演化动力学特性研究及流型识别提供新理论、开拓新途经.     

电生物还原降解二氯酚的动力学特性及功能菌解析

采用电辅助微生物(电生物)体系对二氯酚(2,4-DCP)进行了还原降解研究, 应用聚合酶链式反应-单链构象多肽技术(PCR-SSCP)对微生物群落结构进行解析, 并通过16S rRNA基因克隆及测序构建了系统进化树. 结果表明, 电生物体系对二氯酚的降解符合零级反应动力学特征, 体系中主要以肠球菌(Enterococcus)、 假单胞菌(Pseudomonas)和拟杆菌(Bacteroidales)为优势菌群, 这些菌群在电子传递中起着主要作用. 电生物体系中存在着电极与细胞色素c和脱氢酶的辅酶(NAD)及污染物间的逆向电子传递途径, 可实现电极-微生物-污染物多相界间的长程电子传递.     

台湾地区社区营造探析

在全面分析台湾地区社区营造的发展阶段、营造内容和机制、制度保障和面临困境等内容基础上,从规划内容、规划宗旨和规划机制等3个方面指出中国大陆社区规划的发展方向：社区规划的目标应该是社区的可持续发展,而不能仅局限于物质空间建设;社区规划的首要任务是培养社区感,建立邻里认同;社区规划必须采取自上而下与自下而上相结合的公私协力模式,建立政府部门、非政府组织和社区的合作伙伴关系．     

Detecting Communities by Revised Max-flow Method in Networks

A ubiquitous phenomenon in networks is the presence of communities within which the network connections are dense and between which they are sparser. This paper proposes a max-flow algorithm in bipartite networks to detect communities in general networks. Firstly, we construct a bipartite network in accordance with a general network and derive a revised max-flow problem in order to uncover the community structure. Then we present a local heuristic algorithm to find the optimal solution of the revised max-flow problem. This method is applied to a variety of real-world and artificial complex networks, and the partition results confirm its effectiveness and accuracy.