广州城市河段和湖泊轮虫群落结构的研究

2005年12月-2006年11月,对珠江广州河段及天河、流花公园内湖泊轮虫群落结构进行了初步研究.经鉴定,共发现轮虫21属77种(包括亚种).其中湖泊的优势种分别为暗小异尾轮虫(Trichocerca pusilla)、微型多突轮虫(Liliferotrocha subtilis)、裂痕龟纹轮虫(Anuraeopsis fissa)和剪形臂尾轮虫(Brachionus forficula),而广州河段则是微型多突轮虫(Liliferotrocha subtilis)、裂痕龟纹轮虫(Anuraeopsis fissa)、暗小异尾轮虫(Trichocerca pusilla)、角突臂尾轮虫(Brachionus angularis)和尾突臂尾轮虫(Brachionus caudatus).轮虫数量的两次高峰分别出现在春末夏初和8月份.全年最高密度为5 494 ind./L(中大采样点,2005年12月),最低密度为117 ind./L(中大采样点,2006年7月).枯水期,轮虫密度较高,丰水期,轮虫密度较低.4个采样点轮虫年平均密度以天河采样点最高(1 260 ind./L),中大采样点次之(1 123 ind./L),黄埔采样点再次(737 ind./L),流花采样点最低(718 ind./L).径流量、盐度、温度是造成河口和湖泊轮虫密度以及种类组成区别的重要因素.研究结果表明轮虫在河流和湖泊生态系统中具有重要作用.     

红山诸文化"神鸟"崇拜与萨满"鸟神"

鸟崇拜是人类原始图腾崇拜的普遍形式.距今8000～5000年的红山诸文化曾经有过十分发达的“神鸟“崇拜.在考古发现的遗物中有许多各类鸟形纹样、鸟形雕塑和以石、陶、泥、木、玉等材质制成的鸟形器和佩饰物.鸟是北方诸族萨满的主神或主要保护神,在北方古代游牧民族中鸟崇拜和鸟祖神话十分流行.红山诸文化的“神鸟“崇拜与北方民族的“鸟神“崇拜,特别是萨满“鸟神“有诸多相似之处.     

An interpretation of COVID-19 in Tokyo using a combination of SIR models

A year and a half has passed since the outbreak of the COVID-19 pandemic. Mathematical models to predict infection are expected and many studies have been conducted. In this study, a new interpretation was created that could reproduce the daily positive cases in Tokyo using only a simple SIR model. In addition, the data on the ratio of transfer to delta variants could also be simulated. It is anticipated that this interpretation will be a basis for the development of forecasting methods.     

TLP-CCC: Temporal Link Prediction Based on Collective Community and Centrality Feature Fusion

In the domain of network science, the future link between nodes is a significant problem in social network analysis. Recently, temporal network link prediction has attracted many researchers due to its valuable real-world applications. However, the methods based on network structure similarity are generally limited to static networks, and the methods based on deep neural networks often have high computational costs. This paper fully mines the network structure information and time-domain attenuation information, and proposes a novel temporal link prediction method. Firstly, the network collective influence (CI) method is used to calculate the weights of nodes and edges. Then, the graph is divided into several community subgraphs by removing the weak link. Moreover, the biased random walk method is proposed, and the embedded representation vector is obtained by the modified Skip-gram model. Finally, this paper proposes a novel temporal link prediction method named TLP-CCC, which integrates collective influence, the community walk features, and the centrality features. Experimental results on nine real dynamic network data sets show that the proposed method performs better for area under curve (AUC) evaluation compared with the classical link prediction methods.     

Epistemic Communities under Active Inference

The spread of ideas is a fundamental concern of today’s news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between an agent’s beliefs and observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviours of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g., ‘tweets’) while reading the socially observable claims of other agents that lend support to one of two mutually exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network’s perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated using the freely available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.     

萍乡市社区体育的发展现状及对策研究

社区体育是家庭体育、学校体育和社会体育的桥梁,是实施全民健身计划的载体,也是落实两个文明建设到基层的重要途径。为了促进萍乡市社区体育活动的良性发展,通过调查访问的方法全面了解萍乡市社区体育的现状和存在问题,并提出具体的建议。     

从可持续设计到绿色生态住宅

通过对可持续发展观点的起源，概念，特点的分析，结合我国住宅产业目前的实际情况，阐述了绿色生态住宅小区的基本要求与特点。     

城市社区体育与高校学校体育的互动研究

通过对社区体育和学校体育资源的优势分析,得出二者互动可以提高社区体育服务水平、缓解体育场馆的不足,还有助于拓展学校的项目资源、丰富教学和科研实践活动的结论,提出了实现社区学校互动的学区体育模式、校企合作模式和校市合作模式.     

榆次猫儿岭战国熊鸟纹青铜带钩的文化内涵

晋中市榆次区猫儿岭战国古墓出土的熊鸟纹青铜带钩以其独特的装饰、秀美的造型和精湛的工艺而成为艺术精品.此带钩钩体肖熊形,钩首模拟鸟形;采用高浮雕形式,结合模拟、写意、图案化等多种手法完美地将熊、鸟饰于一件器物之上,体现了设计者丰富的想象力和创造力,同时也赋予其丰富的文化内涵.     

浅析虚拟学习社区归属感

网络环境下的虚拟学习社区包含网络环境和学习共同体两个要素,学习共同体中的学习者更是虚拟学习社区的核心。目前虚拟学习社区的建设重在构建网络环境和丰富学习资源,极少关注学习者在网络学习过程中的情感体验,导致学习者归属感缺失,使得虚拟学习社区学习绩效低下。