Access to Land,Rural Development and Public Action: The When and the How

After being marginalised in the 1980s, land‐reform policies came back to national and international development agendas during the 1990s, resulting in a revival of academic research on the subject. This article reviews the empirical literature on access to land, rural development and public action for evidence on when and how the state should intervene in the allocation of rural land. The review suggests that positive impacts are obtained if, and only if, public actions on the allocation of land are carried out under certain conditions and in a certain way. The article ends by highlighting the need to elaborate empirical models that take into consideration opportunity costs and interactions, and that integrate individual responses with aggregate effects.     

网络舆论倾向性的动态跟踪方法及实证研究

从统计学视角审视网络舆论倾向性的监测问题,提出了以粗糙分类器为基础建立舆论倾向性分类模型,将复杂的预警指标体系简化为单一直观的跟踪统计量,并通过跟踪统计量动态跟踪舆论倾向性变化轨迹的研究方法。实证研究以2011年"郭美美事件"相关新闻跟帖为对象。分析表明,网络舆论的消极倾向性在整个事件发展过程中呈持续增长,与基本事实相符,证实了方法的可行性和适用性。     

Online strategic communication: A cross-cultural analysis of U.S. and Chinese corporate websites

This study applied a cultural divergence approach to examine online marketing interactivity and corporate public image on corporate websites. It analyzed different online strategic communication of corporate websites from two different nations—the United States and China. Results indicated that U.S. corporations were more likely to highlight online marketing interactivity and social responsibility, which integrated marketing and public relations as their online communication strategy. Chinese corporations provided more online spaces for the consumer–consumer interactions and emphasized corporation-oriented information.     

基于网络环境的交互式教学模式在课堂中的应用研究

随着互联网技术的发展,通过网络进行学习已成为一种趋势。基于网络环境的交互式教学模式在各类教学中广泛应用,为现代教育带来了新观念、新方法和新技术。交互式教学方式自由、灵活,学生获取信息快捷、简便,教师的主导作用明显,教学效率高。     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

混合学习法前向网络多属性储层参数预测

应用前向网络描述地震属性和储层参数间的非线性映射关系时，经典的误差反向传播算法存在收敛速度慢，易陷入局部极值等诸多不足。研究了融合粒子群优化算法和误差反向传播算法的混合学习法前向网络多属性储层参数预测技术。粒子群优化算法是一种群体随机搜索演化计算技术，具有较快的收敛速度和较强的全局搜寻能力；误差反向传播算法本质上是梯度下降算法，注重局部搜索。混合学习法为两种学习算法交替执行，首先以粒子群优化算法训练网络，当误差能量在规定的迭代次数内不再发生变化时，采用误差反向传播算法实现局部寻优。理论函数逼近测试和实际储层参数预测实验说明了混合学习法具有学习时间短、求解效率高、可靠性强的优点，具有良好的应用前景。     

The Effects of a Computer Network on Pediatric Pain and Anxiety

SUMMARY

The objective of this study was to test the impact of an enhanced version of STARBRIGHT World (SBW2)-a private computer network for hospitalized children. The impact of SBW2 was assessed with a series of 44 replicated single system designs. Utilizing an ecological momentary assessment approach, self-reports were obtained regarding children's perceptions of their pain intensity, pain aversive-ness and anxiety. The results from the single system designs were aggregated using meta-analysis. Children experienced significantly less pain intensity, pain aversiveness, and anxiety in the SBW2 condition. These findings provide evidence regarding the effectiveness of SBW2 and demonstrate the utility of employing meta-analysis with single system designs.     

丙烯精馏塔的建模及其先进控制方法研究

精馏过程是化工、石油、医药等领域常见的生产过程，由于其非线性、时变性和强耦合等特点，使建模、控制与优化成为理论与实践研究中的难点。本文以一个二元丙烯精馏塔为研究对象，在由物料及能量平衡原理推导出精馏过程数学模型的基础之上，采用基于集结法的动力学模型降阶处理方法对原模型进行降阶，最后为该精馏塔模型设计了基于PID神经网络的解耦控制器。     

基于神经网络的学生党员考核评价系统的开发

为了高效率、低成本地评价高校学生党员的综合素质,采用BP神经网络技术,开发了学生党员考棱评价系统.该神经网络使用专家提供的100组数据进行训练,训练结果的相对误差为0.4％,采用20组非训练数据进行检验,相对误差为0％.实践表明,即使专家的评价规则很复杂,无法用数学模型直观表达,神经网络也能够仿真专家的思维逻辑,对党员素质进行公平、公正的评价.     

A Bayesian Evidence Synthesis for Estimating Campylobacteriosis Prevalence

Stakeholders making decisions in public health and world trade need improved estimations of the burden‐of‐illness of foodborne infectious diseases. In this article, we propose a Bayesian meta‐analysis or more precisely a Bayesian evidence synthesis to assess the burden‐of‐illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden‐of‐illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo‐data. The result is a global estimation of the burden‐of‐illness parameters with their accompanying uncertainty.