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.     

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.     

稀土硝酸盐与甘氨酸配合物的合成和表征

在水溶液体系中合成了镧、镨、钐和钆四种稀土硝酸盐与甘氨酸的固态配合物,化学分析表明,它们的化学组成分别是L_0(NO_3)_3·(Gly)_3·H_2O,Pr(NO_3)_3·(Gly)_3·H_2O,Sm(NO_3)_3·(Gly)_3·3H_2O和Gd(NO_3)_3·(Gly)_3·3H_2O,用红外光谱法和x射线衍射法测定了配合物的结构特征,表明它们是一类完全不同于稀土硝酸盐和甘氨酸的新化合物,同时考察了配合物在几种常见溶剂中的溶解性。     

水杨酸-邻菲罗啉三元稀土配合物的合成、表征及抑菌作用

在无水乙醇溶液中合成了六种水杨酸-邻菲罗啉-三元稀土配合物,采用元素分析,红外光谱,差热热重等测试方法进行表征,确定配合物的化学组成为RE(Phen)2(Sa l)2C l.H2O(RE=L a3+,P r3+,N d3+,Sm3+,G d3+,D y3+).研究了稀土配合物的抑菌活性,结果表明三元稀土配合物的抑菌效果较单独的稀土氯化物、邻菲罗啉和水杨酸好.     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.     

上海市空气污染造成人群健康经济损失的研究

文章通过对上海市空气污染季节性状况的描述 ,分析了各种污染物的污染程度和变化趋势 ,并利用对上海某市级医院的实地调查数据 ,对空气污染物与医院呼吸系统疾病患者日门诊量之间的相关关系进行研讨 ,建立了多元分析模型 ,探讨了患者健康经济损失的计量方法 ,并对由空气污染造成呼吸系统疾病患者健康经济损失进行了估算。研究表明 ,在其他条件不变的情况下 ,NOX 日指数每增长 10 % ,被调查医院呼吸系统疾病患者的日门诊人次增加 7 7人次 ,而这些疾病患者由于患病产生的年度健康经济损失为 2 11万元。据此作保守的推断估计 ,上海市一年内因NOX 超标而发生的呼吸系统疾病门诊行为造成的健康经济损失可以达到 4 2亿元。同样 ,SO2 和TSP造成门诊患者的健康经济损失分别为 1 5亿元和 0 86亿元     

稀土元素Ce对Al－Mg－Si合金断裂韧性的改善及其细观机理分析

用三点弯曲（ＴＰＢ）裂纹试件测定平面应变条件下的断裂韧性Ｊ１ｃ与ＪＲ，试验结果表明，稀土Ｃｅ较大地提高了Ａｌ－Ｍｇ－Ｓｉ合金的起裂韧度值Ｊ１ｃ，特别是，显著地改善了合金的裂纹扩展抗力ＪＲ。金相显微观察和电镜分析表明，稀土Ｃｅ改善了材料的初始细观结构（材料在加载前的组织结构），改变了材料的细观损伤特点，发展了材料的含损伤塑性。     

Analysis of Regional Scale Risk of Whirling Disease in Populations of Colorado and Rio Grande Cutthroat Trout Using a Bayesian Belief Network Model

Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.     

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.