In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed a...In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.展开更多
Purpose:Traumatic brain injury(TBI)is one of the leading causes of disability and death in modern times,whose evaluation and prognosis prediction have been one of the most critical issues in TBI management.However,the...Purpose:Traumatic brain injury(TBI)is one of the leading causes of disability and death in modern times,whose evaluation and prognosis prediction have been one of the most critical issues in TBI management.However,the existed models for the abovementioned purposes were defective to varying degrees.This study aims to establish an ideal brain injury state clinical prediction model(BISCPM).Methods:This study was a retrospective design.The six-month outcomes of patients were selected as the end point event.BISCPM was established by using the split-sample technology,and externally validated via different tests of comparison between the observed and predicted six-month mortality in validating group.TBI patients admitted from July 2006 to June 2012 were recruited and randomly divided into establishing model group and validating model group.Twenty-one scoring indicators were included in BISCPM and divided into three parts,A,B,and C.Part A included movement,pupillary reflex and diameter,CT parameters,and secondary brain insult factors,etc.Part B was age and part C was medical history of the patients.The total score of part A,B and C was final score of BISCPM.Results:Altogether 1156 TBI patients were included with 578 cases in each group.The score of BISCPM from validating group ranged from 2.75 to 31.94,averaging 13.64±5.59.There was not statistical difference between observed and predicted mortality for validating group.The discrimination validation showed that the BISCPM is superior to international mission for prognosis and analysis of clinical trials(IMPACT)lab model.Conclusion:BISCPM is an effective model for state evaluation and prognosis prediction of TBI patients.The use of BISCPM could be of great significance for decision-making in management of TBI.展开更多
基金The Soft Science Research Project of Ministry of Housing and Urban-Rural Development of China (No. 2008-k5-14)
文摘In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.
基金Dr.Xia Li has received two grants from Xijing Hospital(No.XJZT10Y15 and No.XJZT14R15)one grant from the Scientific Department of Shaanxi Province,China(No.2014SF314).
文摘Purpose:Traumatic brain injury(TBI)is one of the leading causes of disability and death in modern times,whose evaluation and prognosis prediction have been one of the most critical issues in TBI management.However,the existed models for the abovementioned purposes were defective to varying degrees.This study aims to establish an ideal brain injury state clinical prediction model(BISCPM).Methods:This study was a retrospective design.The six-month outcomes of patients were selected as the end point event.BISCPM was established by using the split-sample technology,and externally validated via different tests of comparison between the observed and predicted six-month mortality in validating group.TBI patients admitted from July 2006 to June 2012 were recruited and randomly divided into establishing model group and validating model group.Twenty-one scoring indicators were included in BISCPM and divided into three parts,A,B,and C.Part A included movement,pupillary reflex and diameter,CT parameters,and secondary brain insult factors,etc.Part B was age and part C was medical history of the patients.The total score of part A,B and C was final score of BISCPM.Results:Altogether 1156 TBI patients were included with 578 cases in each group.The score of BISCPM from validating group ranged from 2.75 to 31.94,averaging 13.64±5.59.There was not statistical difference between observed and predicted mortality for validating group.The discrimination validation showed that the BISCPM is superior to international mission for prognosis and analysis of clinical trials(IMPACT)lab model.Conclusion:BISCPM is an effective model for state evaluation and prognosis prediction of TBI patients.The use of BISCPM could be of great significance for decision-making in management of TBI.
