Sacred Matter: Animacy and Authority in the Americas

Sacred Matter: Animacy and Authority in the America

Supersonic through-flow fan design

The NASA Lewis Research Center has embarked on a program to experimentally prove the concept of a supersonic through-flow fan which is to maintain supersonic velocities throughout the compression system with only weak shock-wave flow losses. The detailed design of a supersonic through-flow fan and estimated off-design performance with the use of advanced computational codes are described. A multistage compressor facility is being modified for the newly designed supersonic through-flow fan and the major aspects of this modification are briefly described

Workforce planning : preparing for the future

The objective of this project is identifying and attracting a higher quality pool of applicants for the South Carolina Highway Patrol. The goals of data collection and analysis surround the identification of and information regarding three areas: Improve Recruiting and Retention ; Forecast Future Staffing Needs ; Identify Proven Recruiting Techniques and Initiatives

Reference Sediment Selection in the Lower Mississippi Delta

Floodplain deposition has been a critical part in the evolution of Arkansas\u27 Delta ecoregion, and because ofits high potential for such events, this region is highly enriched and extremely fertile. Historically, water quality in the area has been the subject ofscientific study, and as a result littlehas been published on the effects of underlying sediment with associated benthic communities. Sediment analysis is critical to many of the ongoing aquatic studies because ofits significance as both a habitat for benthic organisms and a sink for contaminants. Seven rivers and one creek within the Delta ecoregion were examined for water chemistry, sediment characterization, and sediment toxicity to determine survival and growth of Chironomus tentans. Greatest midge growth occurred insediment collected from Black River site A; additionally, those sediments were high in silt content (\u3e80%) and supported high midge survival. The results of combined characterization and biological test methods indicated that the Black River (site A) was the sediment that met criteria set by the researchers and was suitable to use as a reference control sediment forfuture Delta toxicity testing

Aglite: A 3-Wavelength Lidar System for Quantitative Assessment of Agricultural Air Quality and Whole Facility Emissions

Ground based remote sensing technologies such as scanning lidar systems (light detection and ranging) are increasingly being used to characterize ambient aerosols due to key advantages (i.e., wide area of regard (10 km2), fast response time (s-1), high spatial resolution (\u3c10 \u3em) and high sensitivity). Scanning lidar allows for 3D imaging of atmospheric motion and aerosol variability, which can be used to quantitatively evaluate particulate matter (PM) concentrations and emissions. Space Dynamics Laboratory, in conjunction with USDA ARS, has developed and successfully deployed a lidar system called Aglite to characterize PM in diverse settings. Aglite is a portable scanning elastic lidar system with three wavelengths (355, 532, and 1064 nm), 6 m long range bins, and an effective range from 0.5 to 15 km. Filter-based PM samplers, optical particle counters, and various meteorological instruments were deployed to provide environmental and PM conditions for use in the lidar retrieval method. The developed retrieval algorithm extracts aerosol optical parameters, which were constrained by the point measurements, and converts return signals to PM concentrations. Once calibrated, the Aglite system can map the spatial distribution and temporal variation of the PM concentrations. Whole facility or operation-based emission rates were calculated from the lidar PM data with a mass balance approach. Concentration comparisons with upwind and downwind point sensors were made to verify data quality; lidar-derived PM levels were usually in good agreement with point sensor measurements. Comparisons of lidar-based emissions with emissions estimated through other methods using point sensor data generally show good agreement

Elite male Flat jockeys display lower bone density and lower resting metabolic rate than their female counterparts: implications for athlete welfare

To test the hypothesis that daily weight-making is more problematic to health in male compared with female jockeys, we compared the bone-density and resting metabolic rate (RMR) in weight-matched male and female Flat-jockeys. RMR (kcal.kg-1 lean mass) was lower in males compared with females as well as lower bone-density Z-scores at the hip and lumbar spine. Data suggest the lifestyle of male jockeys’ compromise health more severely than females, possibly due to making-weight more frequently

Effects of Training and Testosterone on Muscle-Fiber Types and Locomotor Performance in Male Six-Lined Racerunners (\u3cem\u3eAspidoscelis sexlineata\u3c/em\u3e)

Testosterone (T) is thought to affect a variety of traits important for fitness, including coloration, the size of sexual ornaments, aggression, and locomotor performance. Here, we investigated the effects of experimentally elevated T and locomotor training on muscle physiology and running performance in a nonterritorial male lizard species (Aspidoscelis sexlineata). Additionally, several morphological attributes were quantified to examine other characters that are likely affected by T and/or a training regimen. Neither training alone nor training with T supplementation resulted in increased locomotor performance. Instead, we found that T and training resulted in a decrease in each of three locomotor performance variables as well as in hematocrit, ventral coloration, and testis size. Strikingly, neither the size nor the fiber composition of the iliofibularis or gastrocnemius muscles was different among the two treatments or a group of untrained control animals. Hence, the relationships among T, training, and associated characters are not clear. Our results offer important insights for those hoping to conduct laboratory manipulations on nonmodel organisms and highlight the challenges of studying both training effects and the effects of steroid hormones on locomotor performance

Emissions Calculated from Particulate Matter and Gaseous Ammonia Measurements from Commercial Dairy in California, USA

Emission rates and factors for particulate matter (PM) and gaseous ammonia (NH3) were estimated from measurements taken at a dairy in June 2008. Concentration measurements were made using both point and remote sensors. Filter-based PM samplers and optical particle counters (OPCs) characterized aerodynamic and optical properties, while a scanning elastic lidar measured particles around the facility. The lidar was calibrated to PM concentration using the point measurements. NH3 concentrations were measured using 23 passive samplers and 2 open-path Fourier transform infrared spectrometers (FTS). Emission rates and factors were estimated through both an inverse modeling technique using AERMOD coupled with measurements and a mass-balance approach applied to lidar PM data. Mean PM emission factors ± 95% confidence interval were 3.8 ± 3.2, 24.8 ± 14.5, and 75.9 ± 33.2 g/d/AU for PM2.5, PM10, and TSP, respectively, from inverse modeling and 1.3 ± 0.2, 15.1 ± 2.2, and 46.4 ± 7.0 g/d/AU for PM2.5, PM10, and TSP, respectively, from lidar data. Average daily NH3 emissions from the pens, liquid manure ponds, and the whole facility were 143.4 ± 162.0, 29.0 ± 74.7, and 172.4 ± 121.4 g/d/AU, respectively, based on the passive sampler data and 190.6 ± 55.8, 16.4 ± 8.4, and 207.1 ± 54.7 g/d/AU, respectively, based on FTS measurements. Liquid manure pond emissions averaged 5.4 ± 13.9 and 3.1 ± 1.6 g/m2/d based on passive sampler and FTS measurements, respectively. The calculated PM10 and NH3 emissions were of similar magnitude as those found in literature. Diurnal emission patterns were observed

Particulate-Matter Emission Estimates from Agricultural Spring-Tillage Operations Using LIDAR and Inverse Modeling

Particulate-matter (PM) emissions from a typical spring agricultural tillage sequence and a strip–till conservation tillage sequence in California’s San Joaquin Valley were estimated to calculate the emissions control efficiency (η) of the strip–till conservation management practice (CMP). Filter-based PM samplers, PM-calibrated optical particle counters (OPCs), and a PM-calibrated light detection and ranging (LIDAR) system were used to monitored upwind and downwind PM concentrations during May and June 2008. Emission rates were estimated through inverse modeling coupled with the filter and OPC measurements and through applying a mass balance to the PM concentrations derived from LIDAR data. Sampling irregularities and errors prevented the estimation of emissions from 42% of the sample periods based on filter samples. OPC and LIDAR datasets were sufficiently complete to estimate emissions and the strip–till CMP η, which were ∼90% for all size fractions in both datasets. Tillage time was also reduced by 84%. Calculated emissions for some operations were within the range of values found in published studies, while other estimates were significantly higher than literature values. The results demonstrate that both PM emissions and tillage time may be reduced by an order of magnitude through the use of a strip–till conservation tillage CMP when compared to spring tillage activities

Lidar Based Emissions Measurement at the Whole Facility Scale: Method and Error Analysis

Particulate emissions from agricultural sources vary from dust created by operations and animal movement to the fine secondary particulates generated from ammonia and other emitted gases. The development of reliable facility emission data using point sampling methods designed to characterize regional, well-mixed aerosols are challenged by changing wind directions, disrupted flow fields caused by structures, varied surface temperatures, and the episodic nature of the sources found at these facilities. We describe a three-wavelength lidar-based method, which, when added to a standard point sampler array, provides unambiguous measurement and characterization of the particulate emissions from agricultural production operations in near real time. Point-sampled data are used to provide the aerosol characterization needed for the particle concentration and size fraction calibration, while the lidar provides 3D mapping of particulate concentrations entering, around, and leaving the facility. Differences between downwind and upwind measurements provide an integrated aerosol concentration profile, which, when multiplied by the wind speed profile, produces the facility source flux. This approach assumes only conservation of mass, eliminating reliance on boundary layer theory. We describe the method, examine measurement error, and demonstrate the approach using data collected over a range of agricultural operations, including a swine grow-finish operation, an almond harvest, and a cotton gin emission study