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The bottleneck model has been widely used in the past fifty years to analyze the morning commute. To reduce the complexity of analysis, most previous studies adopted discontinuous scheduling preference (DSP). However, this handling destroys the continuity in departure rate and differentiability in travel time and cumulative departures. This paper considers an exponential scheduling preference (ESP), which supposes the unit schedule delay cost for commuters exponentially changes with time. With this scheduling preference, we analytically derive solutions and economic properties of user equilibrium and social optimum in the bottleneck model. The first-best, time-varying toll and the optimal single-step toll scheme with ESP are also studied. Results indicate that ESP eliminates the discontinuity in departure rate and non-differentiability in travel time and cumulative departures, which makes the process of morning commute smooth. The ignorance of ESP will lead to underestimation in the queueing time and bias in travel behavior analysis and policymaking.

Valuing travel time reliability is an important element of travel choice modeling. In this paper, we introduce the notion of variation cost in the utility function, capturing the variations in both...

Few longitude cohort studies investigated the risk of the duration of nighttime sleep and naps to the new-onset common chronic disease conditions (CDCs) in middle-aged (45-60) and the elderly (age ≥ 60) populations using an age-stratified strategy.The 7025 participants from The China Health and Retirement Longitudinal Study were screened as eligible subjects. Established 13 cohorts with CDCs, acquired their' sleep records in 2011, and obtained new-onset incidents of CDCs during follow-up in 2011-2018. Performed risk association analyses between sleep duration and 13 new-onset CDCs respectively.New-onset risk of four CDCs decreased with increasing nighttime sleep (p-nonlinear0.05). The risk threshold was approximately 7 hours in middle-aged people and 6 hours in the elderly. For the middle-aged population, compared with 7-9hours sleep,5hour and 5-7hours nighttime sleep were associated with 1.312∼1.675 times more risk of hypertension, kidney disease, diabetes or high blood sugar status, and multimorbidity; Compared with no nap, a 0-30 min nap was associated with 1.413(1.087∼1.837) times the heart disease risk. In the elderly,5 hours of night sleep was a significant risk factor for four CDCs including kidney disease and multimorbidity, etc. A long night's sleep (9 hours) was connected with 61.2% reduction in risk of memory disease, a90 min nap increased 62% risk of memory disease, and a 0-30 min nap was associated with higher risks of heart disease, hypertension, and a lower kidney disease risk.Nighttime sleep and daytime naps may have their own implications for the new-onset CDCs' risk in the aging process.

Background and Purpose: With the aging of society, stroke has become a vital health problem for the middle-aged and elderly. Amounts of stroke's new risk factors have been found recently. It is necessary to develop a predictive risk stratification tool containing multi-dimensional risk factors for identifying high-risk people.Methods: The study included 5844 people (Age≥45) who participated in the China Health and Retirement Longitudinal Study, in 2011 and follow-up to 2018. Randomly divided the population into training and validation set by 1:1. Lasso Cox screened predictors for new-onset stroke. Developed a nomogram and stratified the population according to the score calculated in the nomogram through the X-tile program. Internal and external verification of nomogram was performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.Results: Lasso COX regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance, triglyceride-glucose index, etc., were included in the nomogram. The nomogram's overall performance was good in both internal and external validation (AUCs of three-year, five-year, seven-year in the training set was 0.71, 0.71, 0.71, and 0.67, 0.65, 0.66 in the validation set, respectively). The nomogram was proven to could excellently discriminate between low-, moderate-, and high-risk groups with the 7-year new-onset stroke of 3.36%, 8.32%, and 20.13%, respectively (PConclusions: This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke incidents in 7-years in the middle-aged and elderly Chinese.

Diabetes has a high incidence in China, which may cause stroke and depression. However, the relationship between diabetes and the incidence of new-onset stroke and depression has not been fully studied.The data from the China Longitudinal Study on Health and Retirement (CHARLS) from 2013 to 2018 were used. A total of 8530 respondents aged ≥45 years old were included in the follow-up study. Logistic regression model, Cox regression, and Mediation analyses were used to explore the association between diabetes, depression, and new-onset stroke.The depression score of patients with diabetes history was higher (HR,95%CI = 1.02, 1.01-1.04) and were more likely to experience new-onset stroke events (HR, 95%CI = 1.046, 1.02-1.07). With a history of hypertension (HR,95%CI = 1.747, 1.381-2.208), older (HR,95%CI = 1.033, 1.020-1.046) with high BMI (HR,95%CI = 1.056, 1.027-1.086) have a high risk of new-onset stroke. In the combined subgroup analysis, the incidence of new-onset stroke in the subgroup with diabetes depression was higher than in others. The mediating effect of depression on new-onset stroke events in diabetic patients is more pronounced in the medium to long term (3 years) after adjusting covariates.We defined new-onset stroke by patient self-report, there might be some memory bias. In addition, new-onset stroke was not classified in the CHARLS questionnaire, which would hinder us to evaluate the mediating effect of depression on different types of new-onset stroke.Our results showed that depression has a partial mediating effect between diabetes and new-onset stroke in the middle-aged and elderly population in China.

This paper sets up a rational inattention model for the choice of departure time for a traveler facing random travel time. In this model, the traveler chooses in advance an information strategy for the travel time outcome, and then chooses departure time each day given the information received that day. The model describes how cheaper information allows the traveler to expand his/her consideration set and adapt more flexibly to changing conditions. This increases the traveler's payoff. The marginal cost of travel time variability is always positive. The ability to choose the information strategy reduces the cost of travel time variability compared to neoclassical travelers whose information is exogenously given.

This paper analyzes the impact of road pricing for the bottleneck model with endogenous random delay. We extend the widely used scheduling model by integrating trip scheduling, endogenous traffic c...

This paper analyzes the impact of road pricing for the bottleneck model with endogenous random delay. We extend the widely used scheduling model by integrating trip scheduling, endogenous traffic congestion, travel time variability (TTV), and road pricing into one modeling framework to analyze the role of road pricing in addressing TTV. This paper examines the social economic benefits under TTV, defines the value of travel time variability accordingly, and derives analytical results to illustrate properties of the model, including the impact of road pricing and TTV on travelers and the system performance. For travelers, the presence of TTV leads to spreading in their departure profile, hence reduction in queuing cost, at the expense of increases in scheduling cost and random delay cost. As for the system, TTV reduces the social surplus. This study shows that road pricing can be used as a means to compensate or mitigate the social surplus loss due to TTV.

This paper sets up a rational inattention model for the route choice problem in a stochastic network where travelers face random travel time. Previous research has assumed that travelers incorporate all provided information without effort. This study assumes that information is costly and that travelers rationally choose how much information to acquire prior to choosing route. We begin with a single traveler and then extend the model to heterogeneous travelers where rationally inattentive user equilibrium (RIUE) is achieved. From the perspective of a single traveler, more information always reduces the impact of travel time variability and increases the probability of choosing a less costly route. However, in RIUE, more information may reduce the social welfare in some scenarios.

Landslide warning and forecasting is essential to landslide risk management. This paper establishes a GIS-based landslide warning and forecasting model of Shenzhen where rainfall-trigged landslides have caused great property and life loss. Based on the high-resolution observation data of rainfall and landslide occurrences in Shenzhen, Kriging interpolation model is applied to derive the regional rainfall data prior to the occurrence of landslides. The binary logistic model is then trained by the forward stepwise method, in which the precipitation of the first, second and fourth day prior to the occurrences of landslide are selected as significant explanatory factors. Then, the confusion matrix and AUC/ROC are calculated to verify the model. Finally the critical precipitation of landslide warning and forecasting of Shenzhen is determined. This paper may provide concrete support for landslide risk management work in Shenzhen and helpful reference for related studies.