百花山主要树种对环境的响应研究

北京市面积最大的保护区.北京百花山自然保护区不仅有利于京西生态系统的稳定和生物多样性保护,同时对于建设北京西部生态屏障,改善和保护北京生态环境,实现绿色奥运,具有十分重要的意义.通过对百花山不同海拔,不同林相的多个样方内多种主要植物叶性状(叶干物质和比叶面积)的测定,运用统计学方法对样方中主要树种对环境的响应进行了研究.     

Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space

Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.     

口述史作为社区研究的方法

口述史在社会学中的意义,不仅在于可以通过口述记忆研究个人在大叙事中的生命沉浮,更在于它提供了深挖人的精神世界的社会性的方法。其主要研究对象,可称之为记忆社区的问题。记忆社区至少包括三个维度：地点、时间和人物。它以个人的口述为起点,基于人的生命实践,富含主体性和情感性特征,但其勾勒出的是一个囫囵的整体,有极强的社会性特征,蕴含丰富的社会和文化意义。口述记忆中的文化是一种经由个体化实践而感悟出的文化感,家庭中的“义务感”是它的一个典型形式,其表现为社会力的方式,成为黏合社区的重要机制。记忆社区本质上是人和物的混融,它呈现的社区形象是一个有机整体。口述史能够作为社区研究方法,不仅在于它呈现了独特的记忆社区,还在于指明了社会建设和基层社会治理的深层机制,这便是从人心的角度,揭示了人之安所遂生的社区力量。记忆社区概念提醒我们,历史上积淀下来的社区文化和社会底蕴是值得探究和善用的凝聚社区的相对稳固的机制。     

支持性氛围对顾客参与共创意愿的影响研究——基于顾客间服务共创体验的中介作用

从社群氛围的角度出发,研究影响社群成员参与价值共创意愿的前置因素。以顾客间共创的服务体验为中介变量,提出支持性社群氛围正向影响成员参与共创意愿的假设。研究结果显示,支持性社群氛围正向影响顾客参与共创意愿,顾客间服务共创体验起到部分中介作用;创新氛围对顾客参与意愿的影响最为显著。     

浅谈城市小区中的图书馆建设

我国城市化的高速发展改变了城市居民生活环境的形式和内容,小区模式已逐渐取代传统的街道模式。调查了小区图书馆的建设情况,分析了建设城市小区图书馆的意义,探讨了小区图书馆建设的相关问题。     

基于社区性训练的助行康复系统研究与实现

为了循序渐进地恢复脊髓损伤患者受损部分神经及下肢运动功能,在已有早期减重步行训练的基础上,增加减重模式下空间运动功能。构建可根据患者下肢运动功能损伤程度实现不同模式康复训练、状态监测和助行功能的系统,进行包括减重、助行装置、移动平台和控制模块的结构设计。集成平地行走和上下楼梯训练步态轨迹模型,通过对比正常髋、膝关节的运动角度数据,验证应用该轨迹的可行性与合理性,并进行了设定行走路线的社区任务导向性训练轨迹规划试验。研究结果表明,助行系统支持患者自主设定模拟社区任意行走模式,有助于帮助患者恢复部分肢体运动功能,以尽快融入社会。     

中老年人社区参与对生活满意度的影响机制

社区作为中老年人活动的常驻空间,承载居民日常活动、公共交往等需求,活动参与多样性对中老年人的健康水平具有积极影响。从多维度参与形式出发,基于太原市社区调查数据,构建结构方程模型,对中老年人参与途径与体系进行综合性分析,认识其差异性与关联性,并分析其潜在关系及对生活满意度的影响机制。研究发现,场所依恋可正向调节中老年人的生活满意水平,直接和间接产生总效应值0.595,且场所认同感有助于提高社区参与活力;社区线下参与对生活满意度产生总效应值0.132,线上参与产生总效应值0.059,社区线下参与可影响线上参与,且二者为正向促进关系;人口学变量也可在一定程度上影响中老年人的生活满意度,且影响程度从大到小依次为受教育程度、居住方式、工作类型、年龄、性别。根据研究结果提出中老年人社区参与提升的优化策略,可为城市社区参与活力的激发和提升提供参考。     

顺义滨河森林公园林内小气候及人体舒适度效应分析

为探究城市绿地调节小气候、缓解城市热岛作用,以顺义滨河森林公园绿地为对象,选择硬质铺装为对照,于2022年3—11月,对不同植物群落空气温度、相对湿度、风速进行实地监测,以此研究不同植物群落间小气候及人体舒适度的改善提升效应。结果表明：春季降温效果最好（2.74℃）,其次是夏季（2.05℃）,一天内在14:00前时段降温效果最为显著;夏季增湿效果最高（6.88%）,其次是秋季（5.62%）;在减弱风速效果中春季幅度最高（0.2 m/s）,其次是夏季（0.07 m/s）,上午时间段内减弱风速程度较大。春夏秋三季均能不同程度提高人体舒适度,其中夏季最高（1.54）,其次是春季（0.54）,夏季全天及春季、秋季的12:00—14:00时间内可为人们提供一个较为舒适的环境。可见植物群落优化提升对于提高城市绿地生态效益发挥、改善城市生态环境均有着重要的作用,研究结果可为城市绿地植物群落结构优化提升、经营管理及市民休闲出行供借鉴参考。     

Detecting community structure using label propagation with consensus weight in complex network

Community detection is a fundamental work to analyse the structural and functional properties of complex networks.The label propagation algorithm(LPA) is a near linear time algorithm to find a good community structure. Despite various ubsequent advances, an important issue of this algorithm has not yet been properly addressed. Random update orders within the algorithm severely hamper the stability of the identified community structure. In this paper, we executed the asic label propagation algorithm on networks multiple times, to obtain a set of consensus partitions. Based on these onsensus partitions, we created a consensus weighted graph. In this consensus weighted graph, the weight value of the dge was the proportion value that the number of node pairs allocated in the same cluster was divided by the total number f partitions. Then, we introduced consensus weight to indicate the direction of label propagation. In label update steps,y computing the mixing value of consensus weight and label frequency, a node adopted the label which has the maximum mixing value instead of the most frequent one. For extending to different networks, we introduced a proportion parameter o adjust the proportion of consensus weight and label frequency in computing mixing value. Finally, we proposed an pproach named the label propagation algorithm with consensus weight(LPAcw), and the experimental results showed that he LPAcw could enhance considerably both the stability and the accuracy of community partitions.     

Properties of asymmetrically evolved community networks

This paper studies a simple asymmetrically evolved community network with a combination of preferential attachment and random properties. An important issue about community networks is to discover the different utility increments of two nodes, where the utility is introduced to investigate the asymmetrical effect of connecting two nodes. On the other hand, the connection of two nodes in community networks can be classified as two nodes belonging to the same or to different communities. The simulation results show that the model can reproduce a power-law utility distribution P(u)～u^-σ, σ = 2 + 1/p, which can be obtained by using mean-field approximation methods. Furthermore, the model exhibits exponential behaviour with respect to small values of a parameter denoting the random effect in our model at the low-utility region and a power-law feature with respect to big values of this parameter at the high-utility region, which is in good agreement with theoretical analysis. This kind of community network can reproduce a unique utility distribution by theoretical and numerical analysis.