Reaction potential map analysis of chemical reactivity—III

Reaction potential maps (RPM) have been introduced as a new tool for the study of molecular reactivity. The equipotential energy maps, which are created on given planes around a molecule, define reaction contours towards specific counter-reagent models and are evaluated by perturbation theory. Since the calculated interaction energy involves electrostatic, polarization, exchange, and charge transfer energies, the RPM's can be used to predict site selectivity in a variety of chemical reactions. We found that the calculated RPM's of the SCN^– anion explained well the experimental observations that it reacts at the S atom with soft electrophiles and at the N atom with hard electrophiles. The difference in reactivity between SCN^– and OCN^– was clearly shown by the RPM's of these anions. The ambident nucleophilic nature of the NO ₂ ^– and the CH₂CHO^– anions was also well represented by their RPM's.     

高中有机化学教材“烃类化合物”的国际比较研究

基于闫春更等建立的二维度四指标教材难度微观评价模型，重点对中国、美国、新加坡、澳大利亚、日本、英国的高中化学教材中"烃类化合物"内容的整合广度、表征深度进行测评和比较。研究发现6国教材内容的整合广度整体上差异不大，但其表征深度差异明显；美国教材注重学生认识物质的思路和方法的渗透，日本教材注重基本知识与技能的掌握，中国教材将概念诠释与样例分析相融合；英国、新加坡、美国教材注重情境推理或比较等信息处理策略的运用，对学习者学习的引导性较强。     

可调移动重叠分离图法用于高效液相色谱多台阶梯度分离条件优化的研究

计算机辅助高效液相色谱（HPLC）分离条件优化可以低成本、快速地得到优化的分离条,因而已较为广泛地用于复杂样品的分离分析。基于移动重叠分离图方法,又发展了一种新型的多台阶梯度分离条件的优化方法可调移动重叠分离图法。该方法通过预测不同流动相条件下各组分的保留时间、峰宽和分离度,绘制出对于样品中各组分的重叠分离区域图。在对当前台阶流动相组成进行优化的同时,考虑其对后面一到两个台阶上流出组分保留的影响,实时地重新绘制对于后面台阶上流出组分的重叠分离区域图。通过观察当前台阶流动相条件对当前台阶和后面台阶上流出组分分离的影响,综合考虑样品中所有组分的分离情况,找到更接近全局最优的分离条件。通过扫描的方法对优化得到的分离条件进行微调,能够进一步提高分离效果。采用文献数据对可调移动重叠分离图法的应用加以说明,在二元流动相体系下,证明了该方法在HPLC方法建立方面的优越性。     

共聚高分子混合物的分子热力学模型

以硬球链流体的分子热力学模型为基础 ,引入方阱位能相互作用的贡献 ,建立了共聚高分子混合物的分子热力学模型 .模型中具有物理意义的链节参数 (链节数、链节直径和链节间的相互作用能 )由纯物质的pVT关系拟合得到 ,而用来校正交叉作用能和交叉碰撞直径的可调参数需由液液平衡的实验数据回归得到 .采用了相对简单的处理方法来确定这些可调参数 .对所选共聚高分子混合物的共存曲线、互溶窗和互溶图等相行为的关联结果令人满意 .     

Assembly maps,K-theory, and hyperbolic groups

Following Connes and Moscovici, we show that the Baum-Connes assembly map forK _*(C*v) is rationally injective when is word-hyperbolic, implying the Equivariant Novikov conjecture for such groups. Using this result in topologicalK-theory and Borel-Karoubi regulators, we also show that the corresponding generalized assembly map in algebraicK-theory is rationally injective.     

GPS电子地图坐标转换算法研究

GPS车载导航系统现在已经运用得十分广泛,然而GPS采用的是WGS-84坐标系,目前我国的各类地图均采用54北京坐标或是80西安坐标,两者的差距可达0～120m.要使用各类电子导航装置就需要把WGS-84坐标转换到54北京坐标系下,并和电子地图中的像素点对应起来.本文主要介绍一种坐标转换算法,并且通过实测检验,证实算法效果良好.     

Learning hierarchical spatio-temporal pattern for human activity prediction

Human activity prediction has become increasingly valuable in many applications. This paper, initially from the perspective of cognition science, presents a novel approach to learning a hierarchical spatio-temporal pattern of human activities to predict ongoing activities from videos that contain only the onsets of the activities. Spatio-temporal pattern can be learned by a Hierarchical Self-Organizing Map (HSOM), which consists of two self-organizing maps (i.e., action map and actionlet map) connected via associative links trained by Hebbian learning. Ongoing activities can be predicted by Variable order Markov Model (VMM), which provides the means for capturing both large and small order Markov dependencies based on the training actionlet sequences. Experiments of the proposed method on four challenging 3D action datasets captured by commodity depth cameras show promising results.     

A novel video abstraction method based on fast clustering of the regions of interest in key frames

Online video nowadays has become one of the top activities for users and has become easy to access. In the meantime, how to manage such huge amount of video data and retrieve them efficiently has become a big issue. In this article, we propose a novel method for video abstraction based on fast clustering of the regions of interest (ROIs). Firstly, the key-frames in each shot are extracted using the average histogram algorithm. Secondly, the saliency and edge maps are generated from each key-frame. According to these two maps, the key points for the visual attention model can be determined. Meanwhile, in order to expand the regions surrounding the key points, several thresholds are calculated from the corresponding key-frame. Thirdly, based on the key points and thresholds, several regions of interest are expanded and thus the main content in each frame is obtained. Finally, the fast clustering method is performed on the key frames by utilizing their ROIs. The performance and effectiveness of the proposed video abstraction algorithm is demonstrated by several experimental results.     

A novel multi-group exploiting modification direction method based on switch map

In this paper, we proposed a novel adjustable data hiding method. Our proposed method, which is based on exploiting modification direction (EMD) method, is called the “multi-group exploiting modification direction” method. In the multi-group method, we combine several pixel-groups to embed secret data according to the constructed switch map to simply avoid the conversion redundancy of the EMD method and the spatial redundancy of the section-wise strategy, as well as to efficiently increase the probability of achieving larger embedding capacity. According to the experimental results and mathematical justification, we verified that the multi-group method can achieve higher embedding payload and better visual quality of the image than the EMD method and section-wise strategy for simulated and real secret data.