Efficiency Mapping and Determination of Reliability, Resiliency and Vulnerability of Atmospheric Water Generators in the United States

Atmospheric Water Generators (AWG) extract water from the air using one of three available technologies: refrigeration, sorption, and fog harvesting. A refrigeration device works like a dehumidifier and works best in conditions above 60% relative humidity. A sorption device utilizes a desiccant to extract the water vapor from the air and works in very low humidity levels. A fog harvesting device utilizes a mesh to capture the water vapor from the air and requires 100% relative humidity. In this research, I analyze two refrigeration-based devices and one sorption-based device and their efficacy in providing supplemental water supply. Due to climatological and technological constraints, not all regions in the world would see the same water production from an AWG as production is driven by high relative humidity and temperature. This climatological reliance also subjects them to dramatic changes in performance depending on the season. By using previously established hydrologic performance indicators and weather data for the United States, I determine the year-round efficiency metrics of the typical residential sized refrigeration AWG. Using these efficiency metrics, I also determined the reliability, resiliency, and vulnerability of the AWG to produce potable water seasonally across the United States. By evaluating several different devices and mapping the efficiency on the country-scale, this research determines the regional efficacy in adopting AWG technology to supplement potable water supply. This study was the first to look at the performance of atmospheric water generators with such granularity, as well as comparing specific devices predicted water production output to each other and over the years and calculating their Hashimoto’s hydrological indicators

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe