To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive co...To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.展开更多
OBJECTIVE To identify risk factors for relapse and death in patients with T1 to T2 breast cancer with 0-3 positive axillary lymph nodes.METHODS The case files of 540 breast cancer patients with T1-T2 tumors with 0-3 p...OBJECTIVE To identify risk factors for relapse and death in patients with T1 to T2 breast cancer with 0-3 positive axillary lymph nodes.METHODS The case files of 540 breast cancer patients with T1-T2 tumors with 0-3 positive nodes were reviewed retrospectively. Ten-year locoregional recurrence （LRR）, distant recurrence （DR）, disease-free survival （DFS） and overall survival （OS） of the patients were analyzed. Univariate statistical analysis and Cox proportional hazards models were carried out with SPSS so ware v.16.0.RESULTS The median follow-up of all the patients was 7.2 years. On multivariate analysis, 〉 20% positive axillary nodes was the only variable that influenced LRR adversely （hazard ratio[HR], 12.816; 95% confidence interval, 4.657-35.266, P 〈 0.001）; 〉 20% positive axillary nodes and ductal carcinoma were variables that influenced DR adversely （HR, 11.088, 95% confidence interval, 3.807-32.297, P 〈 0.001; HR, 0.390, 95% confidence interval, 0.179-0.851, P = 0.018）; 1-3 positive axillary nodes and 〉 20% positive axillary nodes were the only variables that had negative e. ect on 10-year OS （HR, 2.110, 95% confi dence interval, 1.364-3.264, P = 0.001; HR, 10.244, 95% confidence interval, 3.497-30.011, P 〈 0.001） and they were also adverse prognostic variables on 10-year DFS （HR, 1.634, 95% confidence interval, 1.171-2.279, P = 0.004; HR, 7.339, 95% confi dence interval,2.906-18.530, P 〈 0.001）.CONCLUSION Axillary lymph nodal status is the only risk factor with a signifi cant impact on 10-year LRR, DR, OS and DFS.Patients with T1-T2 breast cancer with 0-3 positive lymph nodes have the LRR and DR of over 10 years, and the OS and DFS of less than 10 years, compared to patients with negative lymph nodes.Histology in primary tumors is a signifi cant prognostic factor for the 10-year DR.展开更多
基金The National Natural Science Foundation of China(No.51108079)
文摘To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.
文摘OBJECTIVE To identify risk factors for relapse and death in patients with T1 to T2 breast cancer with 0-3 positive axillary lymph nodes.METHODS The case files of 540 breast cancer patients with T1-T2 tumors with 0-3 positive nodes were reviewed retrospectively. Ten-year locoregional recurrence （LRR）, distant recurrence （DR）, disease-free survival （DFS） and overall survival （OS） of the patients were analyzed. Univariate statistical analysis and Cox proportional hazards models were carried out with SPSS so ware v.16.0.RESULTS The median follow-up of all the patients was 7.2 years. On multivariate analysis, 〉 20% positive axillary nodes was the only variable that influenced LRR adversely （hazard ratio[HR], 12.816; 95% confidence interval, 4.657-35.266, P 〈 0.001）; 〉 20% positive axillary nodes and ductal carcinoma were variables that influenced DR adversely （HR, 11.088, 95% confidence interval, 3.807-32.297, P 〈 0.001; HR, 0.390, 95% confidence interval, 0.179-0.851, P = 0.018）; 1-3 positive axillary nodes and 〉 20% positive axillary nodes were the only variables that had negative e. ect on 10-year OS （HR, 2.110, 95% confi dence interval, 1.364-3.264, P = 0.001; HR, 10.244, 95% confidence interval, 3.497-30.011, P 〈 0.001） and they were also adverse prognostic variables on 10-year DFS （HR, 1.634, 95% confidence interval, 1.171-2.279, P = 0.004; HR, 7.339, 95% confi dence interval,2.906-18.530, P 〈 0.001）.CONCLUSION Axillary lymph nodal status is the only risk factor with a signifi cant impact on 10-year LRR, DR, OS and DFS.Patients with T1-T2 breast cancer with 0-3 positive lymph nodes have the LRR and DR of over 10 years, and the OS and DFS of less than 10 years, compared to patients with negative lymph nodes.Histology in primary tumors is a signifi cant prognostic factor for the 10-year DR.
