Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

Squashed dreams and rare breeds: ableism and the arbiters of life and death

The week beginning 29 June 2015 is not just historic for the closure of the Independent Living Fund in the United Kingdom, but for me was the week they decided that my life is not worth investing in; they being NHS England, NICE and, with them, the Department of Health. They chose not to support the enzyme replacement therapy that has been not only keeping me alive, but giving me a quality of life – enabling me to return to finish my Disability Studies PhD exploring how Christian leaders explain disability, where ethics have become the main topic, and to rebuild my career – or so I thought.     

Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Optimal cut-off for rare events and unbalanced misclassification costs

This paper develops a method for handling two-class classification problems with highly unbalanced class sizes and misclassification costs. When the class sizes are highly unbalanced and the minority class represents a rare event, conventional classification methods tend to strongly favour the majority class, resulting in very low detection of the minority class. A method is proposed to determine the optimal cut-off for asymmetric misclassification costs and for unbalanced class sizes. Monte Carlo simulations show that this proposal performs better than the method based on the notion of classification accuracy. Finally, the proposed method is applied to empirical data on Italian small and medium enterprises to classify them into default and non-default groups.     

稀土元素卤化物△_fH_m~θ的拓扑化学研究

根据拓扑理论，提出了一个新的健参数拓扑指数YM，并用YM对86个稀土元素卤化物的标准生成焓（）进行拟合，相关系数为0．9983．新方法能较好地描述了稀土元素卤化物的与其结构之间的定量递变规律     

中国封建社会历史周期率问题管窥——基于唯物史观的角度

本文探讨了中国封建社会历史周期率的发生特点、发生形式等；从唯物史观的角度，揭示了这一周期率发生的本质原因——中国封建社会基本矛盾运动。在此基础上，得出了一些有助于社会主义中国跳出历史周期率的启示。     

稀土对材料强韧性的影响及细观机理探讨

通过对钝切口小试样在扫描电镜下的加载观察与分析，认为稀土Ce能较大幅度地提高Al－Mg－Si变形铝合金的起裂COD值。细观分析表明，与平面应变断裂情况不同，稀土不是通过影响粒子形态进而对裂纹产生屏蔽效应来提高材料的宏观断裂性能，而主要是强化了晶界，迫使裂纹转向晶内并在裂尖产生较大的塑性变形，消耗更多的能量。     

Dy—Gly—V_(B_6)三元配合物的合成与表征

用无水稀土氯化物与甘氨酸(Gly)、维生素 B_6(V_B_6)在一定条件下反应制得了 Dy—Gly—V_B_6三元配合物。经元素分析,IR 与荧光分析,摩尔电导及粉晶 X射线衍射对配合物进行了表征。     

8-羟基喹啉-丙烯酸三元稀土配合物的合成及表征

在乙醇溶液中，以稀土氯化物，丙稀酸与8-羟基喹啉为原料合成了15种三元稀土配合物，经过元素分析、EDTA配位滴定分析、红外光谱表征，确定了稀土配合物的组成．并推测了其分子结构，经差热热重（DTA TG）测定，分析了配合物的热稳定性和热分解行为。