The Effect of COVID-19 on Mobility and Equity: A Case Study on Transit Users in Baltimore, Maryland

69A43551747123This study investigates the effect of the COVID-19 pandemic on the public transport ridership of the Maryland Transit Administration and nine self-identified peer agencies using data collected from National Transit Data (NTD), General Transit Feed Specification (GTFS), American Community Survey (ACS), and the Bureau of Labor Statistics (BLS). The analysis is based on passenger trips, vehicle revenue hours, and vehicles operated in maximum service. A comparison analysis is conducted by mode from March to December of 2020 (during the pandemic) versus February of 2020 (before the pandemic). The comparison between 2020 and 2019 is performed separately for each month. This study also investigates transit riders\u2019 and operators\u2019 behavior and experience during and before the pandemic via an online survey questionnaire. A dashboard was also developed to show the effect of COVID-19 on employment, mobility, transit ridership, and transit services. Based on the NTD analysis, the fewest passenger trips happened in April 2020 for most cities. The largest maximum ridership decline happened in Washington, D.C., (82.2% bus; 93.7% rail), and the smallest maximum ridership decline occurred in St. Louis (47.9% bus, 60.8% rail) and Baltimore (53.2% bus, 93.6% rail) compared to February 2020. Unlike rail, bus ridership in the 10 agencies was not correlated to the service metrics and faced a smaller decline in ridership than the rail mode, probably because of having more captive riders. While reducing bus services is financially justified, it is a more critical service. This study highlights at least one difficult decision that transit agencies have to make: where service reductions should be implemented to have the least impact on captive transit riders/essential workers

The Effect of Vitamin D Supplementation on Anthropometric Indices and Total Testosterone in Women with Polycystic Ovary Syndrome Treated with Low Calorie Diet: A Randomized Clinical Trial

Background and Objectives: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in reproductive age women. In the present study, the effect of weight loss diet and vitamin D supplementation was investigated on total testosterone, anthropometric indices, and body composition in patients PCOS.   Methods: In this controlled clinical trial, 60 PCOS women with vitamin D deficiency, were randomly received vitamin D3 supplementation orally at the dose of 50000IU/week along with weight-loss intervention or one placebo/week along with weight-loss diet for 12 weeks. At the beginning and the end of the study, indices, such as anthropometric, body composition, serum level of 25-hydroxyvitamin D3, and total testosterone, were measured using parametric and non-parametric tests.   Results: After a 12-week intervention, the median of serum 25-hydroxyvitamin D3 significantly increased from 18.5 to 42.69ng/ml in vitamin D group compared to the placebo group (p<0.001). Moreover, the mean of weight, body mass index (BMI), Waist circumference, hip circumference, waist to hip ratio, and fat mass significantly decreased in both groups, but was not different between the two groups. The mean of total testosterone decreased from 0.7 to 0.5ng/ml in vitamin D group, which was not statistically significant.   Conclusion: According to the results of this study, vitamin D supplementation in combination with low-calorie diet had no effect on total testosterone

Integrated Optimization of Vehicle Trajectories and Traffic Signal Timings: System Development and Testing

69A43551747123This research develops a two-layer optimization approach that provides energy-optimal control for vehicles and traffic signal controllers. The first layer optimizes the traffic signal timings to minimize the total energy consumption levels of approaching vehicles from upstream traffic. The traffic signal optimization can be easily implemented in real-time signal controllers, and it overcomes the issues in the traditional Webster\u2019s method of overestimating the cycle length when the traffic volume-to-capacity ratio exceeds 50 percent. The second layer optimizer is the vehicle speed controller, which calculates the optimal vehicle brake and throttle levels to minimize the energy consumption of individual vehicles. The A-star dynamic programming method is used to solve the formulated optimization problem in the second layer to expedite the speed computation so that the optimal vehicle trajectories can be computed in real time and easily implemented in a simulation software for testing. The proposed integrated controller is first tested on an isolated signalized intersection, and then on an arterial network with multiple intersections to investigate the performance of the proposed controller under various traffic demand levels. The test results demonstrate that the proposed integrated controller can greatly improve energy efficiency with fuel savings of up to 17.7%. It can also enhance traffic mobility by reducing traffic delays by up to a 47.2% and reducing vehicle stops by up to 24.8%. Moreover, the data collected from 70 participants in the driving simulator demonstrates that the proposed speed guidance system can reduce emissions by up to 20% in uphill scenarios and up to 7% in downhill scenarios. Lastly, different types of speed guidance options have been investigated in the simulator tests, and the color-coded option is the most favorable choice for participants