Analysis and Prediction of Pedestrians’ Violation Behavior at the Intersection Based on a Markov Chain

Pedestrian violations pose a danger to themselves and other road users. Most previous studies predict pedestrian violation behaviors based only on pedestrians’ demographic characteristics. In practice, in addition to demographic characteristics, other factors may also impact pedestrian violation behaviors. Therefore, this study aims to predict pedestrian crossing violations based on pedestrian attributes, traffic conditions, road geometry, and environmental conditions. Data on the pedestrian crossing, both in compliance and in violation, were collected from 10 signalized intersections in the city of Jinhua, China. We propose an illegal pedestrian crossing behavior prediction approach that consists of a logistic regression model and a Markov Chain model. The former calculates the likelihood that the first pedestrian who decides to cross the intersection illegally within each signal cycle, while the latter computes the probability that the subsequent pedestrians who decides to follow the violation. The proposed approach was validated using data gathered from an additional signalized intersection in Jinhua city. The results show that the proposed approach has a robust ability in pedestrian violation behavior prediction. The findings can provide theoretical references for pedestrian signal timing, crossing facility optimization, and warning system design

Quantitative research of microsurgical anatomy of transfrontal approach for cavernous sinus by virtual reality skill

Objective To evaluate the microsurgical characteristics of different exposure for cavernous sinus through transfrontal approach by Dextroscope virtual reality system quantitatively. Methods Three ⁃ dimensional anatomic models of cavernous sinus were constructed in the Dextroscope virtual reality system according to CT and MRI of five adult cadaver heads. Triangular facets were made by lining landmark points selected on the calvaria and skull base to simulate craniotomy window and regions exposed for cavernous sinus (triangular facet A, B, and C), respectively. Results As comparison showed for areas of different triangular facets of exposed region, facet B was largest with significant difference (P = 0.000, for all). Comparison did not show significant difference among facet A, B, and C for volume of operative space and brain tissue involved (P > 0.05). Volume of anterior clinoid process drilled before cavernous sinus was larger for facet C than facet B and A (P = 0.000, for all). Volume of exposed internal carotid artery and its branches before surgical entry to cavernous sinus was larger for facet B than facet C and A (P = 0.000, for all). Volume of anterior clinoid process drilled after entering cavernous sinus was larger for facet B than facet C (P = 0.000). Volume of cranial nerves and internal carotid artery in the exposed region of cavernous sinus : facet B > facet C > facet A (P = 0.000, for all). There was no significant difference between facet A and facet B as to the volume of pituitary in the exposed region of cavernous sinus (P > 0.05), and pituitary was not exposed through facet C. Conclusion Convenience, vivid manifestation, quantitative measurement, and repeated utilization are prominent advantages of virtual reality technique to simulate transfrontal approach for exposure of cavernous sinus. DOI：10.3969/j.issn.1672-6731.2011.06.00

Transient Global Amnesia following Neural and Cardiac Angiography May Be Related to Ischemia

Introduction. Transient global amnesia (TGA) following angiography is rare, and the pathogenesis has not been illustrated clearly till now. The aim of this research is to explore the pathogenesis of TGA following angiography by analyzing our data and reviewing the literature. Methods. We retrospectively studied 20836 cases with angiography in our hospital between 2007 and 2015 and found 9 cases with TGA following angiography. The data of these 9 cases were analyzed. Results. We found all 9 cases with TGA following neural angiography (5 in 4360) or cardiac angiography (4 in 8817) and no case with TGA following peripheral angiography (0 in 7659). Statistical difference was found when comparing the neural and cardiac angiography group with peripheral group (p=0.022). Two cases with TGA were confirmed with small acute infarctions in hippocampus after angiography. This might be related to the microemboli which were rushed into vertebral artery following blood flow during neural angiography or cardiac angiography. There was no statistical difference when comparing the different approaches for angiography (p=0.82) and different contrast agents (p=0.619). Conclusion. Based on the positive findings of imaging study and our analysis, we speculate that ischemia in the medial temporal lobe with the involvement of the hippocampus might be an important reason of TGA following angiography

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement