The purpose of this study was to preliminarily develop novel self-administered measures to assess nutrition security and choice in dietary characteristics. Measures were piloted in a convenience sample of households at risk for food insecurity in the United States. The survey included the new measures, construct validation variables (household food security, self-reported general health, and dietary variables), and demographic questions. Exploratory factor analysis was used to assess dimensionality, internal (Cronbach's alpha (CA)), and construct validity were assessed (Spearman's correlation). Multivariate logistic regression models were used to assess added utility of the new measures beyond food security measurement. Finally, brief screener versions of the full measures were created. Participants in the analytic sample (n = 380) averaged 45 years old, 71% experiencing food insecurity, 42% with high school diploma or less, 78% were women, and racially/ethnically diverse. Scores for the Household Nutrition Security (CA = 0.85; Mean = 2.58 (SD = 0.87)), Household Healthfulness Choice (CA = 0.79; Mean = 2.47 (SD = 0.96)), and Household Dietary Choice (CA = 0.80; Mean = 2.57 (SD = 0.90)) were positively associated with food security (0.401-0.657), general health (0.194-0.290), fruit and vegetable intake frequency (0.240-0.280), and "scratch-cooked" meal intake (0.328-0.350), and negatively associated with "processed" meal intake (-0.162 to -0.234) and an external locus of nutrition control (-0.343 to -0.366). Further, findings show that the new measures are useful for assessing risk for poor dietary and health outcomes even after controlling for household food security status and sample characteristics. These findings are encouraging and support reliability, construct validity, and utility of these new measures. Following further testing, such as Confirmatory Factor Analysis in future samples, these measures may be used in various applications to contribute to a better understanding of households' limitations for accessing healthful foods and foods that meet their preferences.

Individuals with Parkinson’s Disease (PD) experience significant limitations in motor function, functional gait, postural stability, and balance. These limitations often lead to higher incidences of falls, which have significant complications for individuals with PD. Yoga may improve these functional deficits in individuals with PD. The objective of this study was to determine changes in motor function, functional gait, postural stability, and balance control for community dwelling individuals with PD. This randomized, wait‐list controlled pilot study examined the influence of an 8‐week yoga intervention for people with PD who met the following inclusion criteria: endorsing a fear of falling, being able to speak English, scoring 4/6 on the minimental state exam, and being willing to attend the intervention twice weekly for 8‐weeks. Participants in the yoga group (n=15) experienced improvements in motor function, postural stability, functional gait, and freezing gait, as well as reductions in fall risk. Participants in the wait‐list control (n=12) also significantly improved in postural stability, although their fall risk was not reduced. Individuals in the yoga group significantly reduced their fall risk. An 8‐week yoga intervention may reduce fall risk and improve postural stability, and functional and freezing gait in individuals with PD. This clinical trial is registered as protocol record Pro00041068 in clinicaltrials.gov.

Water quality assessment programs for the management of water resources require the collection of water samples for physical, chemical, and biological analyses. Lack of personnel, accessibility of water bodies, and time constraints, especially after natural disasters and emergencies, are some of the challenges of water sampling. To overcome these challenges, a custom-made thief-style water sampling mechanism was developed and mounted on a multirotor unmanned aerial vehicle (UAV) for autonomous water sampling. The payload capacity and endurance of the UAV were determined using an indoor test station. The UAV was equipped with floatation, and electronic components were coated to prevent water damage in the event of a forced landing or for sample collection. Water samples from a 1.1 ha pond were collected with the developed UAV-assisted water sampling system and traditional manual methods. Dissolved oxygen (DO), electrical conductivity (EC), pH, temperature and chloride measurements were made on samples collected with both UAV-assisted and manual methods and compared. Percent differences between the two sampling methods for DO, EC, pH, and temperature were minimal except for chloride level. Percent differences between the two sampling methods for DO, EC, pH, and temperature measurements were 3.6%, 2.3%, 0.76%, and 0.03%, respectively. Measured chloride levels for the manual and UAV-assisted sampling methods were 3.97 and 5.46 mg/L. UAV-assisted water sampling may prove faster and safer than manual water sampling from large surface waters and from difficult to access water bodies.

Recent construction trends on college campuses have demonstrated a shift to designing buildings with features focused on sustainability. However, few studies have investigated indoor air quality in institutions of higher education, particularly in sustainably designed buildings. The objective of this study was to evaluate the association of building and occupancy on indoor air quality within and between higher education buildings. We measured particulate matter, formaldehyde, carbon dioxide, and nitrogen oxides in LEED certified, retrofitted, and conventional building types on a college campus. Three size fractions of particulate matter were measured in each building. We conducted multi-zonal, 48-h measurements when the buildings were occupied and unoccupied. Outdoor particulate matter was significantly higher (PM2.5 = 4.76, PM4 = 17.1, and PM100 = 21.6 µg/m³) than in classrooms (PM2.5 = 1.7, PM4 = 4.2, and PM100 = 6.7 µg/m³) and common areas (PM2.5 = 1.3, PM4 = 4.2, and PM100 = 4.8 µg/m³; all p < 0.001). Additionally, concentrations of carbon dioxide and particulate matter were significantly higher (p < 0.05) during occupied sampling. The results suggest that occupancy status and building zone are major predictors of indoor air quality in campus buildings, which can, in turn, increase the concentration of contaminants, potentially impacting occupant health and performance. More research is warranted to reveal building features and human behaviors contributing to indoor exposures.