Study of the state-of-the-art of the hermetic seals for secondary alkaline spacecraft cells Quarterly report, Sep. 20 - Dec. 20, 1967

Manufacturing methods, cost estimates, advantages, and limitations of various types of hermetic seals for secondary alkaline spacecraft cell

Impact of Topographic and Data Resolution on Hydrologic and Nonpoint-Source Pollution Modeling in a Karst Terrane

To prevent or reduce the contamination of ground water from agricultural sources, Best Management Practices (BMP’s) such as land-use changes, modifications to control surface runoff, various tillage methods, variations in rates and kinds of chemical applications, and handling procedures for chemicals are being employed and analyzed for effectiveness. The effectiveness of a BMP is often estimated before implementation by evaluating the BMP through the use of computer simulation models. The interactions between surface water and ground water that are unique to karst terranes are not incorporated into the frequently used predictive models. The purpose of this study was to document the impact of topographic data resolution on model input and performance in a karst setting. An analysis of the impacts of topographic data resolution on data collection and output for the AGNPS computer model revealed that the sinkhole drainage area for two karst catchments located in the Blue Grass Region of central Kentucky is approximately doubled when using a 2-ft contour interval instead of a 10-ft interval. This doubling of the subsurface drainage was caused by a threefold increase in the number of sinks identified on the 2-ft contour interval map. The increase in the subsurface drainage was the most significant factor affecting model results, and resulted in significant differences between predicted runoff volumes, peak runoff rates, sediment yields, and nutrient yields for 2-ft contour interval data compared with 10-ft contour interval data

Channel, a Model of Channel Erosion by Shear, Scour and Channel Headwall Propagation: Part 1. Model Development

In the research conducted under this project, models were developed which predict channel erosion resulting from shear in gradually varied flow, shearing forces resulting from submerged jets and hydraulic jumps, and shearing forces resulting from free jets impinging a plunge pool. These models are linked with a runoff routing algorithm to develop the CHANNEL model. This model predicts general channel erosion resulting from time varying gradually varied now as well as predicts the development and propagation of channel headwalls. At this writing, the model still has some problems handling the transition from open channel now to a free jet within the scour hole

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studie

Task ll Report, Part 2: Evaluation of Water Supplies in the Red River, Dix River, and Mainstem Watersheds of the Kentucky River

This study was part of a larger study of water supplies throughout the Kentucky River Basin conducted by the Kentucky Water Resources Research Institute for the Kentucky River Authority. This report examines municipal and private water supplies in the Red River, Dix River, and mainstem Kentucky River watersheds. Municipal supplies which depend on the mainstem Kentucky River, and municipal and private supplies in the North, South, and Middle Fork watersheds of the Kentucky River basin are examined in separate reports

Generalized Geologic Map for Land-Use Planning: Pike County, Kentucky

This map is not intended to be used for selecting individual sites. Its purpose is to inform land-use planners, government officials, and the public in a general way about geologic bedrock conditions that affect the selection of sites for various purposes. The properties of thick soils may supercede those of the underlying bedrock and should be considered on a site-to-site basis. At any site, it is important to understand the characteristics of both the soils and the underlying rock

Water Quality Impacts of Naturals Riparian Grasses Part 2: Modeling Effects of Channelization on Sediment Trapping

A methodology is developed to determine expected sediment trapping in riparian vegetative filter strips considering channelization of flow. The framework consists of defining the channel network stochastically, with deposition/detachment in each channel being modeled deterministically. The two approaches were then combined to develop a model which could predict expected trapping efficiencies for vegetative filters under known field conditions. The model was then extended to include conditions such as rainfall on the filter so as to make it applicable to generic field situations. Field and laboratory studies were conducted to collect and estimate data to develop and evaluate the model. sediment concentrations were measured for natural vegetative filters located on a slope of 8.7%, subjected to inflows from upslope bare soil plots. Surface elevations were measured for the filter. Flow networks and channel shapes were defined by applying the digital elevation model to the micro-relief data. Actual distributions and standard fitted distributions for channel flows and channel shapes were developed. Model evaluation was done for selected values of Manning\u27s n to give predicted filter trapping efficiencies within 2% of the observed, indicating model validity. Sensitivity analysis was conducted using the general model and the fitted probability distributions

Statistical Procedures for Evaluating Daily and Monthly Hydrologic Model Predictions

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the Rr2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one

Reach-Scale Model of Aquatic Vegetation Quantifies N Fate in a Bedrock-Controlled Karst Agroecosystem Stream

In-stream fate of nutrients in karst agroecosystems remains poorly understood. The significance of these streams is recognized given spring/surface water confluences have been identified as hotspots for biogeochemical transformations. In slow-moving streams high in dissolved inorganic nutrients, benthic and floating aquatic macrophytes are recognized to proliferate and drastically impact nutrient fate; however, models that quantify coupled interactions between these pools are limited. We present a reach-scale modeling framework of nitrogen dynamics in bedrock-controlled streams that accounts for coupled interactions between hydrology, hydraulics, and biotic dynamics and is validated using a multi-year, biweekly dataset. A fluvial N budget with uncertainty was developed to quantify transformation dynamics for the dissolved inorganic nitrogen (DIN) pool using a GLUE-like modeling framework, and scenario analyses were run to test for model function over variable environmental conditions. Results from a 10,000 run uncertainty analysis yielded 195 acceptable parameter sets for the calibration period (2000–2002), 47 of which were acceptable for the validation period (2003) (Nash-Sutcliffe Efficiency (NSE) \u3e 0.65; percent bias (PBIAS) \u3c ±15), with significantly different posterior parameter spaces for parameters including denitrification coefficients and duckweed growth factors. The posterior solution space yielded model runs with differing biomass controls on DIN, including both algae and duckweed, but suggested duckweed denitrifies at a rate that would place the bedrock agroecosystem stream on the high-end of rates reported in the literature, contradicting the existing paradigm about bedrock streams. We discuss broader implications for watershed-scale water quality modeling and implementation strategies of management practices for karst agroecosystems, particularly with respect to stream restoration