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This article describes a robust and large-scale synthesis of the ketosteroid building block 11β-hydroxyandrosterone (2) from cheap and readily available hydrocortisone (1). The initial discovery route, which was conducted on a gram scale and achieved a 3–6% yield over eight steps, is also described. Key to the route redesign was the incorporation of two stereoselective steps setting the desired 5α-H and 3α-OH chiral centers and optimization to minimize chromatographic purification. The process route was then conducted at the kilogram scale and achieved a 21–28% yield over four steps.

Because through trips can be a significant portion of travel in a study area, estimating them is an important part of travel demand modeling. In the past through trips were often estimated by using external surveys. External surveys were recently suspended in Texas, so Texas transportation planners need a way to estimate through trips without using external surveys. Previous research has focused on study areas with populations of less than 200,000, but many Texas study areas have populations of more than 200,000. This research developed a set of two logit models to estimate through trips for a wide range of study area sizes. The first model estimates the portion of all trips at an external station that are through trips. The second model estimates the external stations at which the trips originated. The models produce separate results for commercial and noncommercial vehicles, and these results can be used to develop through-trip tables. For predictor variables, the models use results from a simple gravity model, the average daily traffic at each external station as a proportion of the total average daily traffic at all external stations, the number of turns on the routes between external station pairs, and whether the route passes through the study area and does not pass through any other external stations. Evaluations of the models' performance showed that the predictions fit the observations reasonably well, indicating that the models can be useful for practical applications.

A driver approaching a signalized intersection at which the light has turned yellow must make a decision whether to stop or proceed. A signal that is properly timed will generally provide an opportunity for a safe and legal maneuver. As approach speeds increase, however, executing a safe maneuver becomes more difficult. One countermeasure used to provide advance warning of an approaching intersection or an impending signal change at such an intersection is an advance warning signal (AWS). Several AWS systems have been installed throughout the United States, including four in Utah. The effectiveness of the Utah systems has been evaluated as a function of intersection safety by using crash history, speed distribution, and red-light running (RLR) metrics. The results of the research suggest that the contribution of the AWS systems to the safety and operation of the intersections can be interpreted as both positive and negative. The AWS systems have helped to maintain higher operating speeds and may also have improved capacity when vehicles do not need to stop. Meanwhile, speeds have been reduced in the time just before the onset of the yellow interval. However, the additional information provided to drivers may have encouraged some drivers to attempt to beat the light, as evidenced by an increase in RLR even with shortening of the lead flash time. The increase in RLR, however, has not led to an increase in the overall crash frequency or crash rate at these intersections.