Bayesian testing for trend in a power model for clustered binary data

Developmental toxicity studies are widely used to investigate the potential risk of environmental hazards. In dose–response experiments, subjects are randomly allocated to groups receiving various dose levels. Tests for trend are then often applied to assess possible dose effects. Recent techniques for risk assessment in this area are based on fitting dose–response models. The complexity of such studies implies a number of non-trivial challenges for model development and the construction of dose-related trend tests, including the hierarchical structure of the data, litter effects inducing extra variation, the functional form of the dose–response curve, the adverse event at dam or at fetus level, the inference paradigm, etc. The purpose of this paper is to propose a Bayesian trend test based on a non-linear power model for the dose effect and using an appropriate model for clustered binary data. Our work is motivated by the analysis of developmental toxicity studies, in which the offspring of exposed and control rodents are examined for defects. Simulations show the performance of the method over a number of samples generated under typical experimental conditions.     

On Uncertain Sightings and Inference about Extinction

The extinction of many species can only be inferred from the record of sightings of individuals. Solow et al. (2012, Uncertain sightings and the extinction of the Ivory‐billed Woodpecker. Conservation Biology 26: 180–184) describe a Bayesian approach to such inference and apply it to a sighting record of the Ivory‐billed Woodpecker (Campephilus principalis). A feature of this sighting record is that all uncertain sightings occurred after the most recent certain sighting. However, this appears to be an artifact. We extended this earlier work in 2 ways. First, we allowed for overlap in time between certain and uncertain sightings. Second, we considered 2 plausible statistical models of a sighting record. In one of these models, certain and uncertain sightings that are valid arise from the same process whereas in the other they arise from independent processes. We applied both models to the case of the Ivory‐billed Woodpecker. The result from the first model did not favor extinction, whereas the result for the second model did. This underscores the importance, in applying tests for extinction, of understanding what could be called the natural history of the sighting record. Sobre Avistamientos Inciertos e Inferencia de la Extinción     

矿山地质环境安全评估的Bayes判别分析法及应用

从矿山地质环境的实际特性出发,应用Bayes判别分析方法评估矿山地质环境问题。选用13项影响矿山地质环境的区域地质条件、环境现状、矿产资源开发规划、生态恢复治理状况的具体评估指标,以大量实测资料作为学习样本,并按各总体的样本比例确定先验概率,建立了矿山地质环境评估的Bayes判别分析模型。将该模型用于预测样本的评估中,采用回代估计法对判别结果进行验证,误判率为零,判别结果和实际一致。研究结果表明,Bayes判别分析模型是一种结构稳定、判别准确率很高的评估模型,能够用于矿山地质环境的评估。     

Recursive residuals and model diagnostics for normal and non-normal state space models

Model diagnostics for normal and non-normal state space models are based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various diagnostic tools are suggested to check, for example, for wrong observation distributions and for autocorrelation. The paper also discusses such topics as model diagnostics for discrete time series and model discrimination via Bayes factors. The case studies cover environmental applications such as analysing a time series of the number of daily rainfall occurrences and a time series of daily sulfur dioxide emissions.     

Investigating the impacts of crash prediction models on quantifying safety effectiveness of Adaptive Signal Control Systems

Introduction: Adaptive Signal Control System (ASCS) can improve both operational and safety benefits at signalized corridors. Methods: This paper develops a series of models accounting for model forms and possible predictors and implements these models in Empirical Bayes (EB) and Fully Bayesian (FB) frameworks for ASCS safety evaluation studies. Different models are validated in terms of the ability to reduce the potential bias and variance of prediction and improve the safety effectiveness estimation accuracy using real-world crash data from non-ASCS sites. This paper then develops the safety effectiveness of ASCS at six different corridors with a total of 65 signalized intersections with the same type of ASCS, in South Carolina. Results: Validation results show that the FB model that accounts for traffic volume, roadway geometric features, year factor, and spatial effects shows the best performance among all models. The study findings reveal that ASCS reduces crash frequencies in the total crash, fatal and injury crash, and angle crash for most of the intersections. The safety effectiveness of ASCS varies with different intersection features (i.e., AADT at major streets, number of legs at an intersection, the number of through lanes on major streets, the number of access points on minor streets, and the speed limit at major streets). Conclusions: ASCS is associated with crash reductions, and its safety effects vary with different intersection features. Practical Applications: The findings of this research encourage more ASCS deployments and provide insights into selecting ASCS deployment sites for reducing crashes considering the variation of the safety effectiveness of ASCS.     

茄科雷尔氏菌蛋白质相互作用网络预测及分析

细菌性青枯病是由茄科雷尔氏菌(Ralstonia solanacearum)引起的一种世界范围的细菌性土传病害.该细菌基因组序列的完全测序,使得从蛋白质组角度来分析其蛋白质相互作用网络成为可能.本文通过朴素贝叶斯模型整合系统发生谱法、基因邻近法、基因融合法、操纵子法、同源映射法、微阵列法、域相互作用法等7种方法,并根据约豋指数确定的阙值,预测了可信的茄科雷尔氏菌的蛋白质相互作用网络.对网络中的分泌子网络和信号转导进行了分析,提出可能的药物作用靶点(cyaB、pilD、Fli、Rsp1526、VsrA、VsrB、PilH).对于未注释的蛋白依据蛋白相互作用推测了部分蛋白质的功能.本文也提供了完全免费的在线数据库支持,提供了方便的茄科雷尔氏菌的蛋白相互作用的查询及相互作用数据和推测的蛋白质功能数据的查询和下载(http://www.scbmp.org.cn/rsoppi.php).     

Influence of indoor transport and mixing time scales on the performance of sensor systems for characterizing contaminant releases

Optimizing real-time sensor systems to detect and identify relevant characteristics of an indoor contaminant event is a challenging task. The interpretation of incoming sensor data is confounded by uncertainties in building operation, in the forces driving contaminant transport, and in the physical parameters governing transport. In addition, simulation tools used by the sensor interpretation algorithm introduce modeling uncertainties. This paper explores how the time scales inherent in contaminant transport influence the information that can be extracted from real-time sensor data. In particular, we identify three time scales (within room mixing, room-to-room transport, and removal from the building) and study how they affect the ability of a Bayesian Monte Carlo (BMC) sensor interpretation algorithm to identify the release location and release mass from a set of experimental data, recorded in a multi-floor building. The research shows that some limitations in the BMC approach do not depend on details of the models or the algorithmic implementation, but rather on the physics of contaminant transport. These inherent constraints have implications for the design of sensor systems.     

Investigating the influence on safety of retrofitting Italian motorways with barriers meeting a new EU standard

Objective: A new European Union (EU) regulation for safety barriers, which is based on performance, has encouraged road agencies to perform an upgrade of old barriers, with the expectation that there will be safety benefits at the retrofitted sites. The new class of barriers was designed and installed in compliance with the 1998 (European Norm) EN 1317 standards for road restraint systems, which lays down common requirements for the testing and certification of road restraint systems in all countries of the European Committee for Standardization (CEN). Both the older and new barriers are made of steel and are installed in such a way as to avoid vehicle intrusion, but the older ones are thought to be only effective at low speeds and large angles of impact. The new standard seeks to remedy this by providing better protection at higher speeds. This article seeks to quantify the effect on the frequency of fatal and injury crashes of retrofitting motorways with barriers meeting the new standards.

Methods: The estimation of the crash modification was carried out by performing an empirical Bayes before–after analysis based on data from the A18 Messina–Catania motorway in Italy. The methodology has the great advantage to account for the regression to the mean effects. Besides, to account for time trend effects and dispersion of crash data, a modified calibration methodology of safety performance was used.

Results: This study, based on data collected on 76 km of motorway in the period 2000–2012, derived Crash Modification Factor point estimates that indicate reductions of 72% for run-off-road fatal and injury crashes and 38% in total fatal and injury crashes that could be expected by upgrading an old safety barrier by complying with new EU 1317 standards. The estimated benefit-cost ratio of 5.57 for total crashes indicates that the treatment is cost effective.

Conclusions: The magnitude of this benefit indicates that the retrofits are cost-effective even for total crashes and should continue in any European country inasmuch as the estimated Crash Modification Factors are based on treatment sites that are reasonably representative of all European motorways.     

An empirical bayes safety evaluation of tram/streetcar signal and lane priority measures in Melbourne

Objective: Streetcars/tram systems are growing worldwide, and many are given priority to increase speed and reliability performance in mixed traffic conditions. Research related to the road safety impact of tram priority is limited. This study explores the road safety impacts of tram priority measures including lane and intersection/signal priority measures.

Method: A before–after crash study was conducted using the empirical Bayes (EB) method to provide more accurate crash impact estimates by accounting for wider crash trends and regression to the mean effects. Before–after crash data for 29 intersections with tram signal priority and 23 arterials with tram lane priority in Melbourne, Australia, were analyzed to evaluate the road safety impact of tram priority.

Results: The EB before–after analysis results indicated a statistically significant adjusted crash reduction rate of 16.4% after implementation of tram priority measures. Signal priority measures were found to reduce crashes by 13.9% and lane priority by 19.4%. A disaggregate level simple before–after analysis indicated reductions in total and serious crashes as well as vehicle-, pedestrian-, and motorcycle-involved crashes. In addition, reductions in on-path crashes, pedestrian-involved crashes, and collisions among vehicles moving in the same and opposite directions and all other specific crash types were found after tram priority implementation.

Conclusions: Results suggest that streetcar/tram priority measures result in safety benefits for all road users, including vehicles, pedestrians, and cyclists. Policy implications and areas for future research are discussed.