在线社交网络虚假信息交互量最小化的边阻断策略研究

在线社交媒体的蓬勃发展改变了人们获取信息的模式,大量的信息通过社交平台传播,信息内容的真实性把关弱化,各类虚假信息依托社交媒体野蛮生长,网络空间治理,培育健康的网络生态意义重大。本文通过最小化用户之间的虚假信息交互量,研究社交网络中虚假信息传播路径的阻断策略。给定在线社交网络G=（V,E,P,H）,H表示用户之间信息交互量,已知虚假信息传播源集合S⊆V,虚假信息交互量最小化问题是从E中选取哪K条边,使得这些边被阻断之后,虚假信息在用户之间的交互总量最小。首先证明了该问题是NP-困难的,进而证明了问题的目标函数计算是#P-困难。其次,证明了该问题目标函数既不是次模函数也不是超模函数。再次,提出了两阶段贪婪算法（TSGA）来解决该问题,即先获取候选集合E^sa,然后选取阻断集合E'。最后,通过实际在线社交网络数据对模型和算法的有效性进行了分析,实验表明本文提出的算法比现有算法更加有效。     

超声波提取胡椒中有效成分条件优化

试验研究温度、时间、超声波频率对超声波-食用乙醇提取胡椒有效成分的影响,以胡椒粗提取物的提取率为指标,正交实验确定较适宜提取条件为,温度55℃、时间55 min,超声波频率60 KHz,胡椒粗提取物的提取率为4.29%.     

时间序列平稳性分类识别研究

平稳性检验是时间序列回归分析的一个关键问题,已有的检验方法在处理海量时间序列数据时显得乏力,检验准确率有待提高。采用分类技术建立平稳性检验的新方法,可以有效地处理海量时间序列数据。首先计算时间序列自相关函数,构建一个充分非必要的判定准则;然后建立序列收敛的量化分析方法,研究收敛参数的最优取值,并提取平稳性特征向量;最后采用k-means聚类建立平稳性分类识别方法。采用一组模拟数据和股票数据进行分析,将ADF检验、PP检验、KPSS检验进行对比,实证结果表明新方法的准确率较高。     

Trend estimation of multivariate time series with controlled smoothness

This paper extends the univariate time series smoothing approach provided by penalized least squares to a multivariate setting, thus allowing for joint estimation of several time series trends. The theoretical results are valid for the general multivariate case, but particular emphasis is placed on the bivariate situation from an applied point of view. The proposal is based on a vector signal-plus-noise representation of the observed data that requires the first two sample moments and specifying only one smoothing constant. A measure of the amount of smoothness of an estimated trend is introduced so that an analyst can set in advance a desired percentage of smoothness to be achieved by the trend estimate. The required smoothing constant is determined by the chosen percentage of smoothness. Closed form expressions for the smoothed estimated vector and its variance-covariance matrix are derived from a straightforward application of generalized least squares, thus providing best linear unbiased estimates for the trends. A detailed algorithm applicable for estimating bivariate time series trends is also presented and justified. The theoretical results are supported by a simulation study and two real applications. One corresponds to Mexican and US macroeconomic data within the context of business cycle analysis, and the other one to environmental data pertaining to a monitored site in Scotland.     

中日史前拔牙年龄和次数比较研究

探讨史前拔牙个体的年龄和次数,对了解史前社会生活和社会意识、宗教信仰具有重要意义。认为中国和日本新石器时代的原生拔牙应该是青春期或成年期拔牙。中国新石器时代只存在一次拔牙现象,而日本新石器时代存在多次拔牙现象。这说明虽然同处新石器时代,但社会结构和社会意识有所不同。     

Multiple imputation for missing edge data: A predictive evaluation method with application to Add Health

Recent developments have made model-based imputation of network data feasible in principle, but the extant literature provides few practical examples of its use. In this paper, we consider 14 schools from the widely used In-School Survey of Add Health (Harris et al., 2009), applying an ERGM-based estimation and simulation approach to impute the network missing data for each school. Add Health's complex study design leads to multiple types of missingness, and we introduce practical techniques for handing each. We also develop a cross-validation based method – Held-Out Predictive Evaluation (HOPE) – for assessing this approach. Our results suggest that ERGM-based imputation of edge variables is a viable approach to the analysis of complex studies such as Add Health, provided that care is used in understanding and accounting for the study design.     

紫草色素的分离纯化及超细化研究

本文利用索氏提取法从紫草根中提取了紫草色素,利用柱层析和重结晶技术进行了分离纯化,得到了,ββ-二甲基丙烯酰紫草素.利用熔点、紫外、红外、质谱等测试手段对该化合物的组成和结构进行了表征.利用超临界流体快速膨胀法对化合物β,β-二甲基丙烯酰紫草素进行了超细化研究,得到了紫草色素的超细微粒.     

万寿菊中叶黄素的提取与强化工艺研究

本文研究了从万寿菊中提取叶黄素的强化工艺条件，对提取剂、皂化液浓度及皂化时间进行了考察．并确定出以二氯甲烷作提取剂、皂化液浓度为4％，皂化时澡为2h的适宜工艺条件．粗提物经柱层析分离，重结晶，再经过超临界流体沉淀处理后，可提高叶黄素的纯度．     

轮和完全等二部图联图的若干染色问题

图的染色理论是图论的一个重要分支。本文使用分析的方法得到了轮和完全等二部图联图的全色数、均匀全色数和邻点可区别边色数。     

膜分离技术在液相色谱样品前处理中的应用

膜分离技术近年来广泛应用于液相色谱检测样品的前处理，加速了膜技术的进步。概述了膜分离技术的优点，重点综述了多孔膜和非孔膜分离技术原理和模型，以及 pH、温度、压力、膜组成等因素对分离性能的影响。介绍了膜分离技术在环境工程、食品工业和生物医药领域液相色谱检测样品前处理过程中的应用与其存在问题。同时指出如果能解决膜材料、膜分离装置和自动在线联用技术等制约因素，膜分离技术将在人类社会的发展史上起到不可替代的作用。