Analyzing the Homeland Security of the U.S.-Mexico Border

We develop a mathematical optimization model at the intersection of homeland security and immigration, that chooses various immigration enforcement decision variables to minimize the probability that a terrorist can successfully enter the United States across the U.S.-Mexico border. Included are a discrete choice model for the probability that a potential alien crosser will attempt to cross the U.S.-Mexico border in terms of the likelihood of success and the U.S. wage for illegal workers, a spatial model that calculates the apprehension probability as a function of the number of crossers, the number of border patrol agents, and the amount of surveillance technology on the border, a queueing model that determines the probability that an apprehended alien will be detained and removed as a function of the number of detention beds, and an equilibrium model for the illegal wage that balances the supply and demand for work and incorporates the impact of worksite enforcement. Our main result is that detention beds are the current system bottleneck (even after the large reduction in detention residence times recently achieved by expedited removal), and increases in border patrol staffing or surveillance technology would not provide any improvements without a large increase in detention capacity. Our model also predicts that surveillance technology is more cost effective than border patrol agents, which in turn are more cost effective than worksite inspectors, but these results are not robust due to the difficulty of predicting human behavior from existing data. Overall, the probability that a terrorist can successfully enter the United States is very high, and it would be extremely costly and difficult to significantly reduce it. We also investigate the alternative objective function of minimizing the flow of illegal aliens across the U.S.-Mexico border, and obtain qualitatively similar results.     

以策略训练为基础的外语教学对阅读理解的影响

以策略训练为基础的外语教学能有效地提高学生的阅读能力，尤其在理解文章中心思想和判断推理能力方面有较大提高。对提高学生自主学习能力有积极作用。该研究还为大学英语教学提供了可借鉴的启示。     

考虑合作程度的电信数据业务合作创新模型研究

基于模型试验，对堆载诱发型边坡滑坡的变形机理及演化过程进行研究。研究结果表明: （1）堆载诱发型滑坡的变形演化规律可归纳为：后缘压缩阶段→蠕动变形阶段→加速滑动阶段→剧滑阶段，且剧滑启动之前的加速变形过渡时间极短；（2）利用FLAC3D软件进行堆载滑坡演化过程的动态数值分析，模拟过程中坡体应力场和位移场的演化特征表现为从上向下逐步贯通，与模型边坡破坏过程相符；（3）堆载诱发型滑坡破坏过程历时短、突发性强，在坡脚产生持续位移时即应做出滑坡预警。     

基于可信性理论下的EPQ问题的期望值模型

基于可信性理论,本文给出了不允许缺货的经济生产量(EPQ)问题的期望值模型;研究了当单位生产准备费、单位储存费均为模糊变量且相互独立的情况下EPQ 问题的最佳期望单位存储费用、最佳期望单位生产批量及最佳期望生产周期,并得出了一些重要的结论;特殊情况下,讨论了当模型中的模糊参数分别为三角模糊变量、梯形模糊变量及正态模糊变量情况下的EPQ 问题的最优存储策略;最后,针对上述三种情况本文分别给出了一些数值例子验证了模型的有效性和合理性;本文所得到的结果为求解EPQ 问题设计算法提供了理论依据.     

对范·路文兹瓦特翻译比较模式的再思考

文章从理论阐述、译例选取两方面突出了范·路文兹瓦特（Kitty Van Leuven—Zwart）的比较模式在翻译转换中的理论意义和实用价值，结合东西方不同翻译理论流派的观点，从其可操作性和理论根源上剖析了比较模式的合理性、科学性以及存在的缺陷。     

强化学习型匝道控制模型的研究

高速公路上的交通堵塞造成了道路利用效率低下，并伴随着能源消耗和环境污染问题，因此各种各样的高速公路控制方法应用于缓解交通堵塞。本文提出强化学习型匝道控制模型，该模型以交通流模拟为预测工具，以人工智能的强化学习为最优化选择模型，并具有一定的自主性、有记忆功能和性能反馈功能，且是一种动态的过程。应用JAVA针对不同的交通状态进行模拟再现，模拟结果表明匝道控制模型对于减少交通堵塞具有显著的效果。     

对高校动漫人才培养的思考

随着动漫产业的高速发展，其人才的培养也越来越受到业界和相关部门的高度重视。高校作为培养动漫人才的重要基地，是发展动漫产业与培养动漫人才的孵化器，文章针对高校培养动漫人才教育问题进行了讨论，并提出了若干对策建议。     

西安新农村建设规划的地域特色研究

模糊的建设目标，非根植性的规划模式，急功近利的建设速度等致使西安新农村建设羁绊丛丛。针对西安新农村建设所存在的问题，结合西安新农村建设的现实基础，明确提出了西安新农村建设的目标体系，归纳总结了近年来西安新农村建设的适宜模式，并初步提出了提高西安新农村建设规划综合效益的改进策略，以期高效推进西安新农村建设的有序开展。     

理工高校法律人才培养模式之检讨

通过抽样考察,可窥见我国理工高校法律人才培养模式总体现状欠佳,其主要存在这样几个问题:一是培养模式未彰显特色,培养目标指向趋于同质,定位模糊;二是培养机制缺乏制度化支撑,长久动力不足,人才培养缺乏竞争优势。理工高校应以应用复合型卓越法律人才培养目标的确立,特定法律人才培养机制的建构,特色法律专业课程的设计和教学方法的创新,以及法律人才培养模式的制度化保障等四个方面为进路,尽快改变理工高校法律人才培养的欠佳状况。     

Mapping Invasive Species Risks with Stochastic Models: A Cross-Border United States-Canada Application for Sirex noctilio Fabricius

Nonindigenous species have caused significant impacts to North American forests despite past and present international phytosanitary efforts. Though broadly acknowledged, the risks of pest invasions are difficult to quantify as they involve interactions between many factors that operate across a range of spatial and temporal scales: the transmission of invading organisms via various pathways, their spread and establishment in new environments. Our study presents a stochastic simulation approach to quantify these risks and associated uncertainties through time in a unified fashion. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. We simulate new potential entries of S. noctilio as a stochastic process, based on recent volumes of marine shipments of commodities from countries where S. noctilio is established, as well as the broad dynamics of foreign marine imports. The results are then linked with a spatial model that simulates the spread of S. noctilio within the geographical distribution of its hosts (pines) while incorporating existing knowledge about its behavior in North American landscapes. Through replications, this approach yields a spatial representation of S. noctilio risks and uncertainties in a single integrated product. The approach should also be appealing to decisionmakers, since it accounts for projected flows of commodities that may serve as conduits for pest entry. Our 30-year forecasts indicate high establishment probability in Ontario, Quebec, and the northeastern United States, but further southward expansion of S. noctilio is uncertain, ultimately depending on the impact of recent international treatment standards for wood packing materials.