BOOST－PFC电路反馈环节的优化设计

介绍了平均电流控制ＢＯＯＳＴ─ＰＦＣ电路的原理，建立了电流环和电压环的小信号简化模型，讨论了双环反馈环节的设计原则和方法，提出最优设计的思想和数学模型，并以一种ＢＯＯＳＴ─ＰＦＣ电路为例进行优化设计，计算模拟结果显示优化后有关指标好于优化前。     

Quadratic estimation in mixed linear models with two variance components

Explicit expressions for Bayes invariant quadratic estimates, biased and unbiased, are presented and proved to cover the entire class of admissible estimates in the considered classes. An unbalanced genetic model is studied for demonstration.     

一类模式系统的观控性

具有共轭复数重特征值的系统（Ａ，Ｂ，Ｃ）经状态变换为模式系统（Ｍ，Ｂ～，Ｃ～）且公式地写出ｅＭｔ。在此基础上，导出了系统的观控性判据，从而有效地避免了不必要地把系统化为对角型或Ｊｏｒｄａｎ标准型来决定观控性。且暗示出一种把系统（Ａ，Ｂ，Ｃ），特别是无论特征值相同或相重与否，也无论同一个特征值组成多个Ｊｏｒｄａｎ块与否的对角型或Ｊｏｒｄａｎ标准型状态变换为模式系统（Ｍ，Ｂ～，Ｃ～的方法     

Asymptotic properties of a generalized regression-type predictor of a finite population variance in probability sampling

A system of predictors for estimating a finite population variance is defined and shown to be asymptotically design-unbiased (ADU) and asymptotically design-consistent (ADC) under probability sampling. An asymptotic mean squared error (MSE) of a generalized regression-type predictor, generated from the system, is obtained. The suggested predictor attains the minimum expected variance of any design-unbiased estimator when the superpopulation model is correct. The generalized regression-type predictor and the predictor suggested by Mukhopadhyay (1990) are compared.     

"假象"背后的均衡及信息的代价研究

通过库诺特模型可以说明,“假象”的存在将改变均衡结果:如果信息获取是无成本的,那么“假象”将使信息占优一方的均衡利润增加,其对手的均衡利润可能减少,也可能增加;如果获取对手的信息是有代价的,根据我们给出的信息投资的边界条件,当获取信息的代价大于这一边界条件时,获取对手信息是有必要的,反之,应该放弃对信息的投资。     

Combining Food Frequency and Survey Data to Quantify Long-Term Dietary Exposure: A Methyl Mercury Case Study

Twenty-four-hour recall data from the Continuing Survey of Food Intake by Individuals (CSFII) are frequently used to estimate dietary exposure for risk assessment. Food frequency questionnaires are traditional instruments of epidemiological research; however, their application in dietary exposure and risk assessment has been limited. This article presents a probabilistic method of bridging the National Health and Nutrition Examination Survey (NHANES) food frequency and the CSFII data to estimate longitudinal (usual) intake, using a case study of seafood mercury exposures for two population subgroups (females 16 to 49 years and children 1 to 5 years). Two hundred forty-nine CSFII food codes were mapped into 28 NHANES fish/shellfish categories. FDA and state/local seafood mercury data were used. A uniform distribution with minimum and maximum blood-diet ratios of 0.66 to 1.07 was assumed. A probabilistic assessment was conducted to estimate distributions of individual 30-day average daily fish/shellfish intakes, methyl mercury exposure, and blood levels. The upper percentile estimates of fish and shellfish intakes based on the 30-day daily averages were lower than those based on two- and three-day daily averages. These results support previous findings that distributions of "usual" intakes based on a small number of consumption days provide overestimates in the upper percentiles. About 10% of the females (16 to 49 years) and children (1 to 5 years) may be exposed to mercury levels above the EPA's RfD. The predicted 75th and 90th percentile blood mercury levels for the females in the 16-to-49-year group were similar to those reported by NHANES. The predicted 90th percentile blood mercury levels for children in the 1-to-5-year subgroup was similar to NHANES and the 75th percentile estimates were slightly above the NHANES.     

Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.

Interdependency analysis in the context of this article is a process of assessing and managing risks inherent in a system of interconnected entities (e.g., infrastructures or industry sectors). Invoking the principles of input-output (I-O) and decomposition analysis, the article offers a framework for describing how terrorism-induced perturbations can propagate due to interconnectedness. Data published by the Bureau of Economic Analysis Division of the U.S. Department of Commerce is utilized to present applications to serve as test beds for the proposed framework. Specifically, a case study estimating the economic impact of airline demand perturbations to national-level U.S. sectors is made possible using I-O matrices. A ranking of the affected sectors according to their vulnerability to perturbations originating from a primary sector (e.g., air transportation) can serve as important input to risk management. For example, limited resources can be prioritized for the "top-n" sectors that are perceived to suffer the greatest economic losses due to terrorism. In addition, regional decomposition via location quotients enables the analysis of local-level terrorism events. The Regional I-O Multiplier System II (RIMS II) Division of the U.S. Department of Commerce is the agency responsible for releasing the regional multipliers for various geographical resolutions (economic areas, states, and counties). A regional-level case study demonstrates a process of estimating the economic impact of transportation-related scenarios on industry sectors within Economic Area 010 (the New York metropolitan region and vicinities).     

Role of Comparative Risk Assessment in Addressing Environmental Security in the Middle East

During the 21st century, environmental challenges are likely to intensify across the world and possibly lead to violent conflicts. Strategies for conflict avoidance will be incomplete unless they recognize, discuss, and mitigate regional environmental stress factors. Comparative risk assessment (CRA) is one of the most critical tools emerging to influence modern environmental policies and is increasingly used to create a common language to help reconcile competing interests in development and environmental disputes around the world. This article considers the environmental challenges facing the Middle East in light of their "transboundary" nature and proposes CRA as a framework for setting environmental priorities and reducing tensions in the region.     

集团军山地进攻作战减员预计模型

收集了我军以往作战军减员的经验数据,建立军减员率的时间序列模型,提出计算机模拟的方法。在此基础上,着重分析影响减员的多种因素,对交战双方武器装备数量及技术等级,作战地区的地形和气候条件等因素进行了定量描述。运用专家咨询方法筛选了社会经济行为等"软"指标,用群体层次分析法确定各指标的权重,建立了量化指标体系,并运用该指标体系对我军今后主要作战对象进行了量化。结合以上因素对计算机模拟生成的数据进行修正,建立相应的调整算法。     

灰色动态预测模型在货币供应量预测中的应用

在对金融系统中货币供应量的预测进行相关研究的基础上,介绍了符合金融系统预测规律的灰色系统动态预测法,并根据中国货币供应量的实际数据进行了实证的预测检验。结果显示,这种方法简单,不需要借助于其他任何时间序列数据,需要数据量少,预测精确度高,对于近期预测尤其准确,也可进行中长期预测;实证预测结果也符合我国金融系统中货币供应量预测的实际。