可数余定向极大集的若干性质

基于对偶可数连续格对可数余定向极大集进行研究.讨论了对偶可数连续格的一些内部刻画,获得了对偶可数连续格构成完全分配格的一个充分条件,并探究了完全分配格的若干个内部刻画.     

论《哈姆雷特》中的“复仇”与“反复仇”

《哈姆雷特》的主题不是封建主义的"复仇",而是基于人文主义与基督教义的"反复仇",这是莎士比亚后期人文主义思想的具体表现。哈姆雷特行动中的延宕与疯癫,是其在新旧道德观念下对其使命正义性的来回掂量的表现。在无法得出正解的情况下,哈姆雷特顺从"他者"的安排参与决斗,在决斗中杀死仇人,为父报仇,最终又对自己处以死亡的终极惩罚。这正是其对"复仇"使命道德性依据求而不得所做出的投降之举,而其同意福丁布拉斯称王的临终举动,又暗示其内心潜层"反复仇"的答案。哈姆雷特的主体欲望与最终命运亦从而是与反复仇相呼应的。     

从文风入手改进教育方法提高立德树人水平——以习近平总书记系列重要讲话为例

言为心声，习近平同志质朴哲理的语言，显示了他热爱祖国人民的炽热情感和包容世界的宽广胸怀；显示了他睿智沉稳的平和心态和深邃伟大的思想理念。学习习近平文风，对深化高校改革，改进教育方法，提高立德树人水平具有深刻的指导意义。     

丁酸甲酯高温分解的过渡态理论研究(英文)

选取了丁酸甲酯高温分解的十三个反应路径中较为重要的两个反应:CH3OCO=CH3+CO2(R1)和CH3OCO=CH3O+CO(R2).使用密度泛函理论方法在B3LYP/TZVP基组水平上寻找了反应的过渡态,并且得到了两个反应的势能曲线.R1的势垒高度远远低于R2,同时R1的产物CH3和CO2拥有较低的能量,处于相对稳定的状态.因此,反应CH3OCO=CH3+CO2更容易发生.结论为丁酸甲酯的动力学模型研究提供了一定的理论依据.     

GaN分子光谱特性及其势能曲线的理论研究

采用从头计算组态相互作用方法研究了GaN分子的基态和较低的电子激发态的势能曲线,通过数值求解分子的原子核运动薛定谔方程,获得了束缚电子态的光谱参数.对GaN分子光谱参数研究的结果可为以后的实验研究提供理论支持.     

基于规则提升的 Agent 系统异常处理方法

基于进化计算理论中的重组思想, 提出一种基于规则提升的Agent系统异常处理方法, 处理Agent系统中违背执行规则的异常. 该方法根据规则间的相互触发和执行情况分析得到规则处于异常状态的原因, 重组处于异常状态的规则, 提升规则向适应环境的方向进化. 实验结果表明, 该方法能处理规则的异常状态, 增强了规则的触发条件, 保证了规则达到预期的后置条件, 提高了Agent系统在开放环境下的异常处理能力.     

烃族组成对柴油储存安定性影响研究

针对柴油储存过程中质量衰变问题，利用典型柴油样品，开展烃化合物对中国成品柴油储存安定性影响规律研究。烃组成分析测定结果表明，柴油中总芳烃和链烷烃之间存在很强的相关性（相关系数为0.90）。综合采用相关分析、逐步线性回归等方法，建立了安定性指标与烃组成的关联模型，拟合验证表明模型可靠，可以直接用于柴油储存安定性预测；研究确定了柴油储存安定性的主要影响物质，按照对储存安定性指标影响的严重程度将烃类物质分为三个等级，其中苊烯和三环芳烃对柴油质量衰变影响最大，链烷烃对十六烷值和热值影响最大。     

基于高效液相色谱法的帕瑞昔布钠位置异构体测定

建立以高效液相色谱法(HPLC)测定帕瑞昔布钠位置异构体的方法.以硅烷键合硅胶为填充剂(Agela Technologies silica 4.6×250 mm,5μm);以正己烷—异丙醇(85∶15)为流动相,流速,1.0 m L/min,柱温,30℃,检测波长,215 nm.实验表明,帕瑞昔布钠与位置异构体分离度为1.86,理论塔板数分别为8 041和8 929;在0.04μg/m L~0.64μg/m L范围内,帕瑞昔布钠异构体线性关系良好(A=70.647c-1.401,r=0.9998);重复性良好(RSD为0.12%);平均回收率为94.47%(RSD为3.03%,n=9).采用HPLC法测定帕瑞昔布钠中的位置异构体,操作简单,准确度高且灵敏度好,可为控制帕瑞昔布钠质量提供依据.     

Evolutionary game analysis of low-carbon behavior credit supervision of logistics enterprises

Based on the low-carbon obligation fulfillment of Chinese logistics enterprises, this study constructs a tripartite evolutionary game model to analyze the evolutionary process of the interaction between the local government, logistics enterprises and the public in the process of low-carbon behavior credit supervision. Then using Netlogo software, a parameter simulation experiment is conducted to determine the optimal policy for improving the effect of supervision. The results are as follows: ① The combined influence of the local government and the public can effectively change the strategic choice of enterprises and promote the low-carbon behavior of enterprises. ② In terms of improving the effect of supervision, reducing the cost of government supervision would have a highly significant effect, and reducing the cost of the public would be counterproductive. ③ Increasing the government subsidies to enterprises and the government’s fines to enterprises both have a significant effect, and the effect of improving the former is better. However, increasing the severity of higher-level governments punishing local governments will reduce the stability of the system. ④ Supervision can be more effective by increasing the public’s impact on enterprises’ earnings rather than by increasing government subsidies to the public.     

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

Some classical penalty function algorithms may not always be convergent under big penalty parameters in Matlab software, which makes them impossible to find out an optimal solution to constrained optimization problems. In this paper, a novel penalty function (called M-objective penalty function) with one penalty parameter added to both objective and constrained functions of inequality constrained optimization problems is proposed. Based on the M-objective penalty function, an algorithm is developed to solve an optimal solution to the inequality constrained optimization problems, with its convergence proved under some conditions. Furthermore, numerical results show that the proposed algorithm has a much better convergence than the classical penalty function algorithms under big penalty parameters, and is efficient in choosing a penalty parameter in a large range in Matlab software.