基于NURBS方法的转子表面造型技术

采用双三次NURBS方法对某型号转子进行几何造型,对造型过程中出现的曲面延伸、求交和裁剪等问题进行了研究.根据叶片的形状特征,以曲线的几何形式为基础,提出了一种简单实用的曲线曲面延伸方法,实现了切矢量连续的叶片型面的延伸.对于两相交面分别为自由曲面和解析曲面的求交问题,提出了一种简化的跟踪算法,实现了转子叶片型面和圆台面的准确求交和裁剪,从而实现转子精确的几何造型.     

Nonparametric Estimation of Duration Dependence in Militarized Interstate Disputes

A militarized interstate dispute (MID) involves military conflict between states with diplomatic ties and exists because two or more states have failed to resolve their differences through diplomatic channels. Jones et al. (1996) characterize an MID as the threat, display or use of military force short of war. They analyze over 2000 disputes spanning two centuries across the globe and conclude that disputes tend to be persistent once established. In this paper, I find that the passage of time can be a favorable factor in dispute resolution, and thus historical mechanisms for dispute resolution favor ending, not extending, militarized disputes. I emphasize the use of non-parametric procedures first to estimate the hazard function and then to estimate the benefits of negotiated settlements.     

Distribution-Free Inference for Welfare Indices under Complete and Incomplete Information

The data available for estimating welfare indicators are often inconveniently incomplete data: they may be censored or truncated. Furthermore, for robustness reasons, researchers sometimes use trimmed samples. By using the statistical tool known as the Influence Function we derive distribution-free asymptotic variances for wide classes of welfare indicators not only in the complete data case, but also in the important cases where the data have been trimmed, censored or truncated.     

Comparing variances and means when distributions have non-identical shapes

The paper compares several methods for computing robust 1-α confidence intervals for σ ₁ ²-σ ₂ ², or σ ₁ ²/σ ₂ ², where σ ₁ ² and σ ₂ ² are the population variances corresponding to two independent treatment groups. The emphasis is on a Box-Scheffe approach when distributions have different shapes, and so the results reported here have implications about comparing means. The main result is that for unequal sample sizes, a Box-Scheffe approach can be considerably less robust than indicated by past investigations. Several other procedures for comparing variances, not based on a Box-Scheffe approach, were also examined and found to be highly unsatisfactory although previously published papers found them to be robust when the distributions have identical shapes. Included is a new result on why the procedures examined here are not robust, and an illustration that increasing σ ₁ ²-σ ₂ ² can reduce power in certain situations. Constants needed to apply Dunnett’s robust comparison of means are included.     

Robust procedures for multi-sample location problems with unequal group variances

Robust procedures are proposed for testing the equality of several group means without assuming the equality of group variances. These statistics are obtained by modifying Welch's W and Brown-Forsythe's F^* using a trimmed mean and a sine-wave M estimator.Approximate distributions of these new statistics are obtained under normality. Their performances are evaluated by Monte Carlo sampling experiments under various long-tailed symmetric distributions     

A comparison of reweighting estimators of average treatment effects in real world populations

Regulatory agencies typically evaluate the efficacy and safety of new interventions and grant commercial approval based on randomized controlled trials (RCTs). Other major healthcare stakeholders, such as insurance companies and health technology assessment agencies, while basing initial access and reimbursement decisions on RCT results, are also keenly interested in whether results observed in idealized trial settings will translate into comparable outcomes in real world settings—that is, into so-called “real world” effectiveness. Unfortunately, evidence of real world effectiveness for new interventions is not available at the time of initial approval. To bridge this gap, statistical methods are available to extend the estimated treatment effect observed in a RCT to a target population. The generalization is done by weighting the subjects who participated in a RCT so that the weighted trial population resembles a target population. We evaluate a variety of alternative estimation and weight construction procedures using both simulations and a real world data example using two clinical trials of an investigational intervention for Alzheimer's disease. Our results suggest an optimal approach to estimation depends on the characteristics of source and target populations, including degree of selection bias and treatment effect heterogeneity.     

Pesticides,Neurodevelopmental Disagreement,and Bradford Hill’s Guidelines

Neurodevelopmental disorders such as autism affect one-eighth of all U.S. newborns. Yet scientists, accessing the same data and using Bradford-Hill guidelines, draw different conclusions about the causes of these disorders. They disagree about the pesticide-harm hypothesis, that typical United States prenatal pesticide exposure can cause neurodevelopmental damage. This article aims to discover whether apparent scientific disagreement about this hypothesis might be partly attributable to questionable interpretations of the Bradford-Hill causal guidelines. Key scientists, who claim to employ Bradford-Hill causal guidelines, yet fail to accept the pesticide-harm hypothesis, fall into errors of trimming the guidelines, requiring statistically-significant data, and ignoring semi-experimental evidence. However, the main scientists who accept the hypothesis appear to commit none of these errors. Although settling disagreement over the pesticide-harm hypothesis requires extensive analysis, this article suggests that at least some conflicts may arise because of questionable interpretations of the guidelines.