Investigating injury severity interaction between urban and urban-rural fringe areas: a grouped random parameters seemingly unrelated bivariate probit approach.

Urban-rural integration is the critical process of urbanization, while during this process there are various corresponding problems generated, safety is the most important one, especially at urban-rural fringe areas due to mixed traffic flow and complicated land use. This study intended to investigate the injury severity interaction between urban area and urban-rural fringe area, and explore the correlation within injury severity levels and heterogeneity attributed to unobserved factors. To address the correlation and heterogeneity issues, a grouped random parameters seemingly unrelated bivariate (SUB) probit model was proposed, in which the SUB probit model addressed the correlation of residuals, while the random parameters model accommodated the heterogeneity due to unobserved factors.

Data-driven crash prediction by injury severity using a recurrent neural network model based on Keras framework.

With the development of big data technology and the improvement of deep learning technology, data-driven and machine learning application have been widely employed. By adopting the data-driven machine learning method, with the help of clustering processing of data sets, a recurrent neural network (RNN) model based on Keras framework is proposed to predict the injury severity in urban areas. First, with crash data from 2014 to 2017 in Nevada, OPTICS clustering algorithm is employed to extract the crash injury in Las Vegas.

Investigating interaction pattern between urban-rural integration and transport network: A dynamic evolution model.

With the progress of urbanization and urban-rural integration (URI), the interaction between URI and urban-rural transport network is becoming stronger, thus it is necessary to investigate the interactive relationship between URI and transport network. By assuming certain functions and principles, evolution model was proposed to explain the relationship between URI space development scale and urban-rural transport network scale, and then by considering the interaction between URI and transport network, dynamic evolution model was presented. Stability analysis was performed to verify the interaction relations with three patterns and elasticity simulation provided the optimal value of urban-rural transport network scale configuration.

Correction: Investigation of injury severity in urban expressway crashes: A case study from Beijing.

[This corrects the article DOI: 10.1371/journal.pone.

Investigation of injury severity in urban expressway crashes: A case study from Beijing.

Urban expressway is the main artery of traffic network, and an in-depth analysis of the crashes is crucial for improving the traffic safety level of expressways. This study intended to address the injury severity of expressways in Beijing by proposing Bayesian ordered logistic regression model. Crash data were collected from urban express rings and expressways in 2015 and 2016.

The role of striking and struck vehicles in side crashes between vehicles: Bayesian bivariate probit analysis in China.

Objective: Side crashes between vehicles which usually lead to high casualties and property loss, rank first among total crashes in China. This paper aims to identify the factors associated with injury severity of side crashes at intersections and to provide suggestions for developing countermeasures to mitigate the levels of injuries.

Method: In order to investigate the role of striking and struck vehicles in side crashes simultaneously, bivariate probit model was proposed and Bayesian approach was employed to evaluate the model, compared to the corresponding univariate probit model.

Accident severity levels and traffic signs interactions in state roads: a seemingly unrelated regression model in unbalanced panel data approach.

This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia, and explore the correlation within accident severity levels and heterogeneity attributed to unobserved factors. The data from 410 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, a seemingly unrelated regression (SUR) model in unbalanced panel data approach was proposed, in which the seemingly unrelated model addressed the correlation of residuals, while the panel data model accommodated the heterogeneity due to unobserved factors.

Identifying the safety factors over traffic signs in state roads using a panel quantile regression approach.

Objective: This study intended to investigate the interactions between accident rate and traffic signs on state roads located in Croatia and accommodate the heterogeneity attributed to unobserved factors. Data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia's Ministry of the Interior.

Methods: To address the heterogeneity, a panel quantile regression model was proposed, in which a quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, and the panel data model accommodates the heterogeneity attributed to unobserved factors.

A Heckman selection model for the safety analysis of signalized intersections.

Purpose: The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously.

Methods: This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively.

[Correlation of hepatocyte expression of hepatitis B viral core antigen and the clinicopathological characters in chronic hepatitis B patients].

Objective: To investigate the relationship between the expression of hepatitis B virus (HBV) core antigen and viral replication and liver tissue inflammation damage in chronic hepatitis B (CHB) patients, and to analyze the relationship of core antigen expression differences with clinical and pathological features in e antigen-negative and e antigen-positive CHB patients.

Methods: Sixty-three treatment-naive patients diagnosed with CHB who underwent liver biopsy were included in this retrospective analysis. Liver pathology was assessed, and the karyotype, pulp type, and pulp karyotype were determined.

Identifying access management factors associated with safety of urban arterials mid-blocks: a panel data simultaneous equation models approach.

Objective: The objective of this study was to evaluate the safety impact of selected access management techniques in urban areas because access management techniques play an important role in urban roadway safety on the roadway network.

Methods: In order to correct the interdependency between safety and mobility for heterogeneous mid-block segments, simultaneous equation models were adopted. The panel data structure of the model was used to address the heterogeneity issue for mid-block segments along a corridor.