A1 Qaeda and the radical Islamic challenge to western strategy

The September 11 global crisis prompted by the attacks on the World Trade Center and the Pentagon raises major questions concerning the nature and trajectory of terrorism in the post-Cold War global order. Hitherto, terrorism has been largely debated by analysts at the level of nation states. Terrorist and insurgent movements have also been largely anchored in nationalist and ethnic power bases even when they have sought to mobilise a transnational ideological appeal on religious or class grounds. There have been a few exceptions to this pattern such as the alliance between the German Baader-Meinhof group and the Japanese Red Army Faction, but even such international alliances as this did not, until at least the 1980s, presage anything like a global terrorist network necessitating a global strategic response. This study examines terrorism and global strategic responses.     

高中生饮酒行为及心理影响因素研究——以石河子市某高中为例

目的：研究高中生饮酒现状及相关心理影响因素。方法：采用问卷调查的方法,对在石河子市某高中就读的500名学生进行问卷调查研究工具：酒精使用障碍筛查量表（AUDIT）。UCLA孤独量表（第三版）。焦虑自评量表（SAS）结果：①高中生中不饮酒者323人,占受调查人数”．9％,饮酒学生114人;占受调查人数26．1％。饮酒者中男生74人,占39．6％,女性40人。占16％。②高中生饮酒情况因年级、性别、母亲饮酒、朋友饮酒而有所差异（P〈0．05）。具体表现为：男性、高年缴、母亲饮酒者、朋友饮酒者,其自身饮酒情况较重。③高中生饮酒与孤独感负相关,与焦虑正相关（上述结果p〈0．05）。     

利用多时间尺度卷积的视频行为识别网络

基于2D的行为识别网络通常融合多张视频帧的分类结果识别不同的行为,但其在卷积过程中缺少对时空特征提取。针对该问题,基于时间位移模块(temporal shift module,TSM)的思想设计了一组多时间尺度卷积,包含不同设计的卷积核以提取融合不同时间尺度的时空信息。通过控制多时间尺度卷积嵌入ResNet50网络的位置及其模块的参数设置,寻找最优的基于多时间尺度卷积的行为识别网络。使用PyTorch深度学习框架训练模型,在大型开源数据集Something-Somethingv2上进行了实验研究。结果表明,基于多时间尺度卷积的行为识别网络对行为识别准确率达到了59.47%,优于TSM等网络。     

Reaction characteristic of PTFE/Al/Cu/Pb composites and application in shaped charge liner

In this paper, the reaction characteristic and its application in shaped charge warhead of a novel reactive material, which introduced copper (Cu) and plumbum (Pb) into traditional polytetrafluoroethylene/aluminum (PTFE/Al), are studied. The thermal analysis and chemical reaction behavior of the PTFE/Al/Cu/Pb mixture are investigated by Differential Scanning Calorimetry (DSC),Thermo-gravimetry (TG), and X-ray Diffraction (XRD) techniques. Then, the shaped charge liners with PTFE/Al/Cu/Pb reactive materials are fabricated, and the X-ray experiments show that they could form reactive jets with excellent performance under the detonation effects of the shaped charge. Based on that, the penetration experiments of shaped charge with PTFE/Al/Cu/Pb reactive liner against steel plates are carried out, and the results demonstrate that the PTFE/Al/Cu/Pb reactive jets could produce a deeper penetration depth compared to the traditional PTFE/Al reactive jets. Meanwhile, the PTFE/Al/Cu/Pb reactive jets also show significant inner-blast effects, leading to dramatically cracking or fragmentation behavior of the penetrated steel plates. This new PTFE/Al/Cu/Pb reactive liner shaped charge presents enhanced penetration behavior for steel targets that incorporates the penetration capability of a high-density and ductility jet, and the chemical energy release of PTFE-matrix reactive materials.     

Modeling of unsupervised knowledge graph of events based on mutual information among neighbor domains and sparse representation

Text event mining, as an indispensable method of text mining processing, has attracted the extensive attention of researchers. A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper, i.e. UKGE-MS. Specifically, UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information, and solves the problems of traditional unsupervised feature selection methods, which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples. Firstly, considering the influence of local information of samples in feature correlation evaluation, a feature clustering algorithm based on average neighborhood mutual information is proposed, and the feature clusters with certain event correlation are obtained; Secondly, an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation, so as to enhance the generalization ability of the selected feature items. Finally, the events knowledge graph is constructed by means of sparse representation and l₁ norm. Extensive experiments are carried out on five real datasets and synthetic datasets, and the UKGE-MS are compared with five corresponding algorithms. The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection, and has some advantages over other methods in text event recognition and discovery.     

道德认同视角下的亲社会行为培养机制探析

十八大报告提出了推进公民道德建设工程的重大任务,而亲社会行为的培养正是公民道德建设工程的重要目标。道德认同是激发亲社会行为的重要动机,增进道德认同是培养社会成员亲社会行为的根本途径,因而亟须在道德认同视角下深入探讨亲社会行为的培养机制。当前社会背景下,完善亲社会行为的社会规则认同机制、社会归属认同机制、社会责任认同机制、社会支持暖化机制、社会回报强化机制和社会实践固化机制是针对现存突出问题应做出的理性选择。     

论道德教育对亲社会行为的培养作用——以“向陈洲贵同志学习”为例

亲社会行为具有无私增进他人利益的道德属性.亲社会行为与道德的这种特殊关系,决定了亲社会行为培养离不开道德教育的作用.事实上,道德教育对亲社会行为培养具有诸多正向作用.如道德榜样教育激发亲社会行为模仿,道德知识传授解释亲社会行为的合理性,道德舆论宣传创设亲社会行为的情境氛围等,通过考察这些正向作用,为亲社会行为的伦理培养提供有益思考.     

Social capital and terrorism

Many studies of terrorism explain the use of violence against civilians with political or economic forces, often relegating social variables to the margins. Social factors, specifically societal-level social capital, play a far more important role in explaining patterns of terrorist activity than previously recognized. Social capital can exert pressures that act as both restraint and catalyst for terrorism, making explicit exposition of these differential effects critical. Analysis shows that higher stocks of social capital positively correlate with the number of terrorist groups, but the average attack activity of those groups increase as measures of social capital decline. The complex relationship makes it difficult to draw simple policy implications, but it does offer insight into the role that social dynamics play in terrorist activity.     

SAR微动目标的稀疏贝叶斯成像方法

SAR微动信息能够反映出目标的属性信息,其微动图像可作为雷达目标识别的一种重要手段。基于SAR微动目标回波的稀疏特性,建立了在过完备词典下的稀疏表示模型,提出一种新的稀疏贝叶斯重构方法——方差成分扩张压缩,该方法仅赋予有重要意义的信号元素不同的方差分量,拥有更少的参数。仿真结果表明,方差成分扩张压缩方法能较精确地估计出SAR目标微动参数,同时能够获得低信噪比条件下较好的微动目标像。