城市生态绿化项目的政府投资方式改革——基于绿地建设与房产开发商的利益互动关系研究

通过对公共产品的内涵分析表明，仅由政府提供公共产品经常会出现不经济现象；只要解决外部性问题，公共产品是可以由私人提供的。以上海公共绿地为例，在分析目前公共绿地政府投资方式的基础上，研究绿地建设与房产开发商的利益互动关系，探讨城市绿地外部效应内部化的投资方式改革，提出房产与绿地联合开发建议，以期减轻政府建设城市绿地的资金压力，为实现城市公共绿地的最优投资提供理论上的依据。     

A study of Bayesian local robustness with applications in actuarial statistics

Local or infinitesimal Bayesian robustness is a powerful tool to study the sensitivity of posterior magnitudes, which cannot be expressed in a simple manner. For these expressions, the global Bayesian robustness methodology does not seem adequate since the practitioner cannot avoid using inappropriate classes of prior distributions in order to make the model mathematically tractable. This situation occurs, for example, when we compute some types of premiums in actuarial statistics in order to fix the premium to be charged to an insurance policy. In this paper, analytical and simple expressions that allow us to study the sensitivity of premiums, which are usually used in automobile insurance are provided by using the local Bayesian robustness methodology. Some examples are examined by using real automobile claim insurance data.     

Notes on authors

Social network analysis (SNA), a method which can be used to explore networks in various contexts, has received increasing attention. Drawing on the development of European smoke-free policy, this paper explores how a mixed-method approach to SNA can be utilised to investigate a complex policy network. Textual data from public documents, consultation submissions and websites were extracted, converted and analysed using plagiarism detection software and quantitative network analysis and qualitative data from public documents and 35 interviews were thematically analysed. While the quantitative analysis enabled understanding of the network’s structure and components, the qualitative analysis provided in-depth information about specific actors’ positions, relationships and interactions. The paper establishes that SNA is suited to empirically testing and analysing networks in EU policy-making. It contributes to methodological debates about the antagonism between qualitative and quantitative approaches and demonstrates that qualitative and quantitative network analysis can offer a powerful tool for policy analysis.     

Water Adherence Factors for Human Skin

On incidental dermal exposure to chemicals in water, a key exposure factor is the amount of water adhering to skin. Although soil adherence factors have been developed for risk assessment, measurements of water adherence on human skin have not been described. In the Environmental Protection Agency's (EPA's) dermal risk assessment guidance, dermal dose from environmental exposures is based upon the flux rate across the skin, which assumes that an unlimited amount of chemical is available for absorption. This assumption is applicable to certain exposure scenarios such as swimming and bathing. However, exposures to contaminated water frequently involve scenarios where the available chemical is limited by the amount of water adhering to the skin, for example, during accidental splashes. We conducted studies in human volunteers to investigate water adherence per unit area of skin after brief contact with water. In two sets of experiments, either water was applied with a micropipette to 10‐cm² areas of the lower leg, foot, and hand, or the foot and hand were briefly immersed in water. In males, using a micropipette, water adherence ranged from 1.93 (foot) to 7.13 μL/cm² (lower leg). In females, it ranged from 1.10 (lower leg) to 4.83 μL/cm² (hand). Hand and foot immersion resulted in relatively higher values of 6.89 and 5.17 μL/cm², respectively, in males, and 5.40 and 6.39 μL/cm² in females. Water adherence was affected by amount of body hair and type of exposure. Water adherence factors can be used to calculate the applied dose per unit area for exposures involving intermittent water contact.     

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.