Impact of Playing Surface on Concussion Symptoms in Young American Football Players

ObjectiveTo identify differences in symptoms following sports-related concussion (SRC) on natural grass vs artificial turf in youth and adolescent football players.BackgroundThere is continued interest in reducing risk of SRC in football, with playing surface being one potentially modifiable factor. It is estimated that 15–30% of concussions result from helmet-to-ground contact, and some studies have suggested a higher incidence of SRC on grass in competitive contact sports compared to turf. To our knowledge, our study is the first to investigate reported post-concussive symptoms after SRC as they relate to playing surface.Design/MethodsData were prospectively collected from the North Texas Concussion Registry (ConTex), a longitudinal multi-institutional concussion database. We selected male football players between the ages of 10 and 24 who sustained a helmet-to-ground SRC (GCS 13–15) on either grass or turf. Pre-injury information and post-concussive symptoms (Graded Symptom Checklist from the SCAT-5) were collected at an initial in-person visit within 2 weeks of injury and via electronic follow up at 3 months.ResultsFifty-eight participants were included (grass = 32, turf = 26), and groups were similar in age (p = 0.089), time since injury (p = 0.500), history of headache (χ2 = 0.167), and prior history of concussion (χ2 = 0.868). Athletes who sustained SRC on grass reported significantly higher scores on the Graded Symptom Checklist (p = 0.018, mean 26.0 vs 11.4) and higher numbers of distinct symptoms (p = 0.013, mean 10.2 vs 5.5) compared to those who sustained SRC on turf. Symptoms that were rated significantly higher after SRC on grass included headache (p = 0.010), phonophobia (p = 0.014), dizziness (p = 0.001), fatigue (p = 0.021), blurred vision (p = 0.001), feeling “in a fog” (p = 0.014), difficulty remembering (p = 0.004), and feeling emotional (p = 0.041).ConclusionsYouth and adolescent football players who sustain SRC on grass report higher post-concussive symptom severity and burden. Elucidating differential effects of SRC on grass vs turf is important, as competitive playing surface is a modifiable risk factor.

Optimal Pooling, Batching, and Pasteurizing of Donor Human Milk

Human breast milk provides nutritional and medicinal benefits that are important to infants, particularly those who are premature or ill. Donor human milk, collected, processed, and dispensed via milk banks, is the standard of care for infants in need whose mothers cannot provide an adequate supply of milk. In this paper, we focus on streamlining donor human milk processing at nonprofit milk banks. On days that milk is processed, milk banks thaw frozen deposits, pool together milk from multiple donors to meet nutritional specifications of predefined milk types, bottle and divide the pools into batches, and pasteurize the batches using equipment with various degrees of labor requirements. Limitations in staffing and equipment and the need to follow strict healthcare protocols require productive, expedient, and frugal pooling strategies. We formulate integer programs that optimize the batching-pasteurizing decisions and the integrated pooling-batching-pasteurizing decisions by minimizing labor and meeting target production goals. We further strengthen these formulations by establishing valid inequalities for the integrated model. Numerical results demonstrate a reduction in the optimality gap through the strengthened formulation versus the basic integer programming formulation. A case study at Mothers’ Milk Bank of North Texas demonstrates significant improvement in meeting milk type production targets and a modest reduction in labor compared with former practice. The model is in use at Mothers’ Milk Bank of North Texas and has effectively improved their production balance across different milk types.

Business Behavior in the Face of Severe Weather: Studying the Effects of Deterministic and Probabilistic Warning Systems

Tornadoes are nature’s most violent storm and annually cause billions in damage along with the threat of fatalities and injuries. To improve tornado warnings, the National Weather Service is considering a change from a deterministic to a probabilistic paradigm. While studies have been conducted on how individual behavior may change with the new While studies have been conducted on how individual behavior may change with the new businesses. This project is a response to the Weather Research and Forecasting Innovation Act of 2017, H.R. 353, which calls for the use of social and behavioral science to study and improve storm warning systems. The goal is to discuss business response to probabilistic tornado warnings through descriptive and regression-based statistics using a survey administered to businesses in North Texas. Prior to release, the survey was vetted by a focus group comprised of businesses in Grayson County, TX who assisted in the creation of a behavior ranking scale. The scale ranked behaviors from low to high effort. Responses allowed for determining if the business reacted to the warning in a passive or active manner. Returned surveys came from large and small businesses in North Texas and represent a wide variety of industries. Regression analysis explores which variables have the greatest influence on businesses’ behavior and show that beyond increases in probability from the probabilistic warnings, trust in the warning provides the most significant change to behavior.

Microgrid for a Cluster of Grid Independent Buildings Powered by Solar and Wind Energy

The reduction of CO2 emissions and the avoidance of Global Climate Change necessitate the conversion of the electricity generation industry to rely on non-carbon sources. Additionally, the mitigation of the duck-curve effects in microgrids requires the development of grid-independent buildings. Computations were performed for a cluster of one thousand grid-independent buildings in the North Texas area, where air-conditioning demand is high in the summer months. The electricity demand is balanced with energy supply generated from wind turbines, photovoltaic cells, or stored energy in hydrogen tanks. The results indicate that with one wind turbine operating, each building must be fitted with 10.2 kW rating photovoltaics capacity and a tank with 5.2 m3 of hydrogen storage capacity to satisfy the hourly demand of the buildings’ community. The addition of more wind turbines significantly reduces the needed PV rating but increases the required storage. Investing in energy conservation measures in the buildings significantly reduces both the needed storage capacity and the PV cell ratings.