The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an int...The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.展开更多
Injection wells have been used for disposal of fluids for nearly 100 years. Design of injection well systems has advanced over the years, but environmental concerns due to the potential for migration of injected fluid...Injection wells have been used for disposal of fluids for nearly 100 years. Design of injection well systems has advanced over the years, but environmental concerns due to the potential for migration of injected fluids remain. Fluids range from hazardous materials, to mining waste to treated wastewater. This paper presents an evaluation of wells injecting treated wastewater to assess which create the greatest risk to migration potential. Prior studies have looked at the risks of Class I injection wells for wastewater disposal, but limited data were available at that time. This research involved collecting data and evaluating the differences as a means to predict the potential for fluid migration in the wells. There were four issues that might portend migration: well depth-shallower wells tended to have more migration;the tightness of the confining unit immediately above the injection zone;well age;and the use of tubing and packers. Florida is moving away from tubing and packer wells which may be an indicative of this issue. The results provide a pathway to investigate injection wells in other states.展开更多
Let R（t）=u＋ct-∑ I=1^N（t） Xi,t≥0 be the renewal risk model, with Fx（x）being the distribution function of the claim amount X. Let ψ（u） be the ruin probability with initial surplus u. Under the condition of F...Let R（t）=u＋ct-∑ I=1^N（t） Xi,t≥0 be the renewal risk model, with Fx（x）being the distribution function of the claim amount X. Let ψ（u） be the ruin probability with initial surplus u. Under the condition of Fx（x） ∈ S^＊（γ）,y ≥ 0, by the geometric sum method, we derive the local asymptotic behavior for ψ（u,u ＋ z] for every 0 （ z （ oo, On one hand, the asymptotic behavior of ψ（u） can be derived from the result obtained. On the other hand, the result of this paper can be applied to the insurance risk management of an insurance company.展开更多
Proper understanding of global distribution of infectious diseases is an important part of disease management and policy making. However, data are subject to complexities caused by heterogeneities across host classes ...Proper understanding of global distribution of infectious diseases is an important part of disease management and policy making. However, data are subject to complexities caused by heterogeneities across host classes and space-time epidemic processes. This paper seeks to suggest or propose Bayesian spatio-temporal model for modeling and mapping tuberculosis relative risks in space and time as well identify risks factors associated with the tuberculosis and counties in Kenya with high tuberculosis relative risks. In this paper, we used spatio-temporal Bayesian hierarchical models to study the pattern of tuberculosis relative risks in Kenya. The Markov Chain Monte Carlo method via WinBUGS and R packages were used for simulations and estimation of the parameter estimates. The best fitting model is selected using the Deviance Information Criterion proposed by Spiegelhalter and colleagues. Among the spatio-temporal models used, the Knorr-Held model with space-time interaction type III and IV fit the data well but type IV appears better than type III. Variation in tuberculosis risk is observed among Kenya counties and clustering among counties with high tuberculosis relative risks. The prevalence of HIV is identified as the determinant of TB. We found clustering and heterogeneity of TB risk among high rate counties and the overall tuberculosis risk is slightly decreasing from 2002-2009. We proposed that the Knorr-Held model with interaction type IV should be used to model and map Kenyan tuberculosis relative risks. Interaction of TB relative risk in space and time increases among rural counties that share boundaries with urban counties with high tuberculosis risk. This is due to the ability of models to borrow strength from neighboring counties, such that nearby counties have similar risk. Although the approaches are less than ideal, we hope that our study provide a useful stepping stone in the development of spatial and spatio-temporal methodology for the statistical analysis of risk from tuberculosis in Kenya.展开更多
文摘The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.
文摘Injection wells have been used for disposal of fluids for nearly 100 years. Design of injection well systems has advanced over the years, but environmental concerns due to the potential for migration of injected fluids remain. Fluids range from hazardous materials, to mining waste to treated wastewater. This paper presents an evaluation of wells injecting treated wastewater to assess which create the greatest risk to migration potential. Prior studies have looked at the risks of Class I injection wells for wastewater disposal, but limited data were available at that time. This research involved collecting data and evaluating the differences as a means to predict the potential for fluid migration in the wells. There were four issues that might portend migration: well depth-shallower wells tended to have more migration;the tightness of the confining unit immediately above the injection zone;well age;and the use of tubing and packers. Florida is moving away from tubing and packer wells which may be an indicative of this issue. The results provide a pathway to investigate injection wells in other states.
基金Supported by the National Natural Science Foundation of China (70273029)
文摘Let R（t）=u＋ct-∑ I=1^N（t） Xi,t≥0 be the renewal risk model, with Fx（x）being the distribution function of the claim amount X. Let ψ（u） be the ruin probability with initial surplus u. Under the condition of Fx（x） ∈ S^＊（γ）,y ≥ 0, by the geometric sum method, we derive the local asymptotic behavior for ψ（u,u ＋ z] for every 0 （ z （ oo, On one hand, the asymptotic behavior of ψ（u） can be derived from the result obtained. On the other hand, the result of this paper can be applied to the insurance risk management of an insurance company.
文摘Proper understanding of global distribution of infectious diseases is an important part of disease management and policy making. However, data are subject to complexities caused by heterogeneities across host classes and space-time epidemic processes. This paper seeks to suggest or propose Bayesian spatio-temporal model for modeling and mapping tuberculosis relative risks in space and time as well identify risks factors associated with the tuberculosis and counties in Kenya with high tuberculosis relative risks. In this paper, we used spatio-temporal Bayesian hierarchical models to study the pattern of tuberculosis relative risks in Kenya. The Markov Chain Monte Carlo method via WinBUGS and R packages were used for simulations and estimation of the parameter estimates. The best fitting model is selected using the Deviance Information Criterion proposed by Spiegelhalter and colleagues. Among the spatio-temporal models used, the Knorr-Held model with space-time interaction type III and IV fit the data well but type IV appears better than type III. Variation in tuberculosis risk is observed among Kenya counties and clustering among counties with high tuberculosis relative risks. The prevalence of HIV is identified as the determinant of TB. We found clustering and heterogeneity of TB risk among high rate counties and the overall tuberculosis risk is slightly decreasing from 2002-2009. We proposed that the Knorr-Held model with interaction type IV should be used to model and map Kenyan tuberculosis relative risks. Interaction of TB relative risk in space and time increases among rural counties that share boundaries with urban counties with high tuberculosis risk. This is due to the ability of models to borrow strength from neighboring counties, such that nearby counties have similar risk. Although the approaches are less than ideal, we hope that our study provide a useful stepping stone in the development of spatial and spatio-temporal methodology for the statistical analysis of risk from tuberculosis in Kenya.
文摘目的探索山东省不同性别老年人群中可改变心血管危险因素(modifiable cardiovascular risk factors,MCVRFS)的聚集模式,并评估其与脑卒中发生的关联性。方法基于齐鲁全生命周期电子健康研究型数据库(Cheeloo Lifespan Electronic Health Research Data-library,Cheeloo LEAD),纳入2015年6月1日至12月31日期间具有完整健康体检记录、电子病历记录和公共卫生建档记录的≥60岁老年人,构建包含58633名参与者的随访队列,随访期为7年,研究终点为脑卒中事件。通过潜在类别分析(latent class analysis,LCA)探索MCVRFS的聚集模式,采用Cox比例风险回归模型评估不同聚集模式与脑卒中的关联性。结果本研究通过LCA在不同性别亚群中均识别出4种MCVRFS聚集模式。男性人群低风险组、吸烟饮酒组、超重肥胖组和代谢综合征组的占比分别为39.02%、16.41%、36.34%和8.22%;女性人群中,低风险组、吸烟饮酒组、体质量及血脂异常组和代谢综合征组的占比分别为41.00%、0.44%、46.76%和11.80%。男性人群中,新发脑卒中6764例,发病密度为0.04947/人年;女性新发脑卒中8141例,发病密度为0.04273/人年。校正混杂因素后,Cox回归结果显示,男性人群中,吸烟饮酒组、超重肥胖组、代谢综合征组发生脑卒中的风险分别为低风险组的1.13倍(HR=1.13,95%CI=1.05~1.21)、1.16倍(HR=1.16,95%CI=1.09~1.23)和2.20倍(HR=2.20,95%CI=2.04~2.38);女性人群中,体质量及血脂异常组和代谢综合征组发生脑卒中的风险分别为低风险组的1.16倍(HR=1.16,95%CI=1.10~1.21)和2.39倍(HR=2.39,95%CI=2.25~2.54)。结论本研究在山东省不同性别老年人群中均识别出4种MCVRFS的聚集模式,男性人群中,超重肥胖组、吸烟饮酒组和代谢综合征组均增加脑卒中风险;女性人群中,体质量及血脂异常组和代谢综合征组均增加脑卒中发生风险。针对不同聚集模式的个体化干预策略可能有助于降低老年人脑卒中的发生率,减轻其疾病负担。
