Testing and Improving a UAV-Based System Designed for Wetland Methane Source Measurements

Wetlands are the single highest emitting methane source category, but the magnitude of wetland fluxes remains difficult to fully characterize due to their large spatial extent and heterogeneity. Fluxes can vary with land surface conditions, vegetation type, and seasonal changes in environmental conditions. Unmanned aerial vehicles (UAVs) are an emerging platform to better characterize spatial variability in these natural ecosystems. While presenting some advantages over traditional techniques like towers and flux chambers, in that they are mobile vertically and horizontally, their use is still challenging, requiring continued improvement in sensor technology and field measurement approaches. In this work, we employ a small, fast response laser spectrometer on a Matrice 600 hexacopter. The system was previously deployed successfully for 40 flights conducted in a four-day period in 2018 near Fairbanks, Alaska. These flights revealed several potential areas for improvement, including: vertical positioning accuracy, the need for sensor health indicators, and approaches to deal with low wind speeds. An additional set of flights was conducted this year near Antioch in California. Flights were conducted several meters above ground up to 15-25 m in a curtain pattern. These curtains were flown both upwind and downwind of a tower site, allowing us to calculate a mass balance methane flux estimate that can be compared to eddy covariance fluxes from the tower. Testing will better characterize the extent to which altitude drifts in-flight and how GPS values compare with measurements from the onboard LIDAR, as well as the agreement between two-dimensional wind speed and direction on the ground versus measured onboard the UAV. Hardware improvements to the sensor and GPS are being considered to help reduce these sources of uncertainty. Results of this testing and how system performance relates to needs for quantifying wetland fluxes, will be presented

Substantial improvements not seen in health behaviors following corner store conversions in two Latino food swamps.

BackgroundThe effectiveness of food retail interventions is largely undetermined, yet substantial investments have been made to improve access to healthy foods in food deserts and swamps via grocery and corner store interventions. This study evaluated the effects of corner store conversions in East Los Angeles and Boyle Heights, California on perceived accessibility of healthy foods, perceptions of corner stores, store patronage, food purchasing, and eating behaviors.MethodsHousehold data (n = 1686) were collected at baseline and 12- to 24-months post-intervention among residents surrounding eight stores, three of which implemented a multi-faceted intervention and five of which were comparisons. Bivariate analyses and logistic and linear regressions were employed to assess differences in time, treatment, and the interaction between time and treatment to determine the effectiveness of this intervention.ResultsImprovements were found in perceived healthy food accessibility and perceptions of corner stores. No changes were found, however, in store patronage, purchasing, or consumption of fruits and vegetables.ConclusionsResults suggest limited effectiveness of food retail interventions on improving health behaviors. Future research should focus on other strategies to reduce community-level obesity

Nutrition Campaign Knowledge and Dietary Behavior in Middle School Students

Background and Purpose: Federal nutrition campaigns are designed to make dietary recommendations accessible but have not been extensively evaluated. This paper explores whether knowledge of nutrition campaigns is associated with dietary behavior among young adolescents. Methods: Cross-sectional survey data were collected from 4,773 middle school students in Southern California. Hierarchical logistic regression models were used to assess the association between dietary behaviors and nutrition campaign knowledge, controlling for gender and ethnicity. Results: Knowledge of the Fruit & VeggiesMore Matters campaign was associated with increased odds of high fruit and vegetable consumption, knowledge of the MyPlate campaign was associated with neither, and both were associated with increased odds of not consuming soda. Conclusion: Overall, low percentages of students demonstrated knowledge of nutrition campaigns, and knowledge was associated with some dietary behaviors. More research is needed to examine the impact of nutrition campaigns while also accounting for other psychosocial and environmental factors that may affect soda, fruit, and vegetable consumption

Quantifying uncertainties from mobile-laboratory-derived emissions of well pads using inverse Gaussian methods

Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian-derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites,  ∼ 93&thinsp;% were sampled with an average of 2 transects in  &lt; 5&thinsp;min (standard sampling),  ∼ 5&thinsp;% were sampled with an average of 10 transects in  &lt; 15&thinsp;min (replicate sampling) and  ∼ 2&thinsp;% were sampled with an average of 20 transects in 15–60&thinsp;min. For sites sampled with 20 transects, a tower was simultaneously deployed to measure high-frequency meteorological data (intensive sampling). Five of the intensive sampling sites were modeled using large eddy simulation (LES) to reproduce CH4 concentrations in a turbulent environment. The LES output and LES-derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian-derived emission rates agreed within a factor of 2 in all except one case; the average difference was 25&thinsp;%. A controlled release was also used to investigate sources of bias in either technique. The Gaussian method agreed with the release rate more closely than the LES, underlining the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to determine an optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1&thinsp;min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30&thinsp;min. Sources of uncertainty from source location, wind speed, background concentration and atmospheric stability were also analyzed. The largest contribution to the total uncertainty was from atmospheric variability; this is caused by insufficient averaging of turbulent variables in the atmosphere (also known as random errors). Atmospheric variability was quantified by repeat measurements at individual sites under relatively constant conditions. Accurate quantification of atmospheric variability provides a reasonable estimate of the lower bound for emission uncertainty. The uncertainty bounds calculated for this work for sites with  &gt; 50&thinsp;ppb enhancements were 0.05–6.5q (where q is the emission rate) for single-transect sites and 0.5–2.7q for sites with 10+ transects. More transects allow a mean emission rate to be calculated with better precision. It is recommended that future mobile monitoring schemes quantify atmospheric variability, and attempt to minimize it, under representative conditions to accurately estimate emission uncertainty. These recommendations are general to mobile-laboratory-derived emissions from other sources that can be treated as point sources.</p

Rhythm Returns: Movement and Cultural Theory

This introduction charts several of rhythm's various returns as a way of laying out the theoretical and methodological field in which the articles of this special issue find their place. While Henri Lefebvre’s rhythmanalysis is perhaps familiar to many, rhythm has appeared in a wide repertoire of guises, in many disciplines over the decades and indeed the centuries. This introduction attends to the particular roles of rhythm in the formation of modernity ranging from the processes of industrialization and the proliferation of new media technologies to film and literary aesthetics as well as conceptualizations of human psychology, social behaviour and physiology. These are some of the historical antecedents to the contemporary understandings of rhythm within body studies to which most of the contributions to this issue are devoted. In this respect, the introduction outlines recent approaches to rhythm as vibration, a force of the virtual, and an intensive excess outside consciousness

Bayesian Finite Population Modelingfor Spatial Process Settings

We develop a Bayesian model-based approach to finite population estimation accounting for spatialdependence. Our innovation here is a framework that achieves inference for finite population quantities inspatial process settings. A key distinction from the small area estimation setting is that we analyze finitepopulations referenced by their geographic coordinates (point-referenced data). Specifically, we consider atwo-stage sampling design in which the primary units are geographic regions, the secondary units arepoint-referenced locations, and the measured values are assumed to be a partial realization of a spatialprocess. Traditional geostatistical models do not account for variation attributable to finite populationsampling designs, which can impair inferential performance. On the other hand, design-based estimateswill ignore the spatial dependence in the finite population. This motivates the introduction of geostatisticalprocesses that will enable inference at arbitrary locations in our domain of interest. We demonstrate usingsimulation experiments that process-based finite population sampling models considerably improve modelfit and inference over models that fail to account for spatial correlation. Furthermore, the process basedmodels offer richer inference with spatially interpolated maps over the entire region. We reinforce theseimprovements and demonstrate scaleable inference for groundwater Nitrate levels in the population ofCalifornia Central Valley wells by offering estimates of mean Nitrate levels and their spatially interpolatedmaps

Supplemental Table 1.

This supplemental table contains meta-regressions for the manuscript titled "Meta-Analysis of the Efficacy and Adverse Effects of Acalabrutinib in the Management of Relapsed/Refractory Chronic Lymphocytic Leukemia"</p

Data from: How the zebra got its stripes: a problem with too many solutions

The adaptive significance of zebra stripes has thus far eluded understanding. Many explanations have been suggested, including social cohesion, thermoregulation, predation evasion and avoidance of biting flies. Identifying the associations between phenotypic and environmental factors is essential for testing these hypotheses and substantiating existing experimental evidence. Plains zebra striping pattern varies regionally, from heavy black and white striping over the entire body in some areas to reduced stripe coverage with thinner and lighter stripes in others. We examined how well 29 environmental variables predict the variation in stripe characteristics of plains zebra across their range in Africa. In contrast to recent findings, we found no evidence that striping may have evolved to escape predators or avoid biting flies. Instead, we found that temperature successfully predicts a substantial amount of the stripe pattern variation observed in plains zebra. As this association between striping and temperature may be indicative of multiple biological processes, we suggest that the selective agents driving zebra striping are probably multifarious and complex