Infrared radiometer for measuring thermophysical properties of wind tunnel models

An infrared radiometer is described which was developed to measure temperature rises of wind tunnel models undergoing transient heating over a temperature range of -17.8 C to 260 C. This radiometer interfaces directly with a system which measures the effective thermophysical property square root of rho ck. It has an output temperature fluctuation of 0.26 C at low temperatures and 0.07 C at high temperatures, and the output frequency response of the radiometer is from dc to 400 hertz

Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) in South Carolina, USA. First,we used high density LiDAR data (10 returns/m2) to predict detailed forest attributes at 20-mresolution across the entire SRS using a complementary application of nonlinear seemingly unrelated regression andmultiple linear regressionmodels. Next,we expanded on previous applications of LiDAR by constructing 95% joint prediction confidence intervals to quantify prediction error at various spatial aggregations and habitat thresholds to determine a biologically and statistically meaningful grain size. Finally,we used aggregations of 20-m cells and associated confidence interval boundaries to demonstrate a newapproach to produce maps of RCWforaging habitat conditions based on the guidelines described in the species\u27 recovery plan. Predictive power (R2) of regression models developed to populate raster layers ranged from 0.34 to 0.81, and prediction error decreased as aggregate size increased, but minimal reductions in prediction error were observed beyond 0.64-ha (4 × 4 20-m cells) aggregates. Mapping habitat quality while accounting for prediction error provided a robust method to determine the potential range of habitat conditions and specific attributes that were limiting in terms of the amount of suitable habitat. The sequential steps of our analytical approach provide a useful framework to extract detailed and reliable habitat attributes for a forest-dwelling habitat specialist, broadening the potential to apply LiDAR in conservation and management of wildlife populations. A zipped folder of Google maps is attached below as a related file

Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) in South Carolina, USA. First,we used high density LiDAR data (10 returns/m2) to predict detailed forest attributes at 20-mresolution across the entire SRS using a complementary application of nonlinear seemingly unrelated regression andmultiple linear regressionmodels. Next,we expanded on previous applications of LiDAR by constructing 95% joint prediction confidence intervals to quantify prediction error at various spatial aggregations and habitat thresholds to determine a biologically and statistically meaningful grain size. Finally,we used aggregations of 20-m cells and associated confidence interval boundaries to demonstrate a newapproach to produce maps of RCWforaging habitat conditions based on the guidelines described in the species\u27 recovery plan. Predictive power (R2) of regression models developed to populate raster layers ranged from 0.34 to 0.81, and prediction error decreased as aggregate size increased, but minimal reductions in prediction error were observed beyond 0.64-ha (4 × 4 20-m cells) aggregates. Mapping habitat quality while accounting for prediction error provided a robust method to determine the potential range of habitat conditions and specific attributes that were limiting in terms of the amount of suitable habitat. The sequential steps of our analytical approach provide a useful framework to extract detailed and reliable habitat attributes for a forest-dwelling habitat specialist, broadening the potential to apply LiDAR in conservation and management of wildlife populations. A zipped folder of Google maps is attached below as a related file

Time Interval Between Cover Crop Termination and Planting Influences Corn Seedling Disease, Plant Growth, and Yield

Experiments were established in a controlled-growth chamber and in the field to evaluate the effect of the length of time intervals between winter rye cover crop termination and corn planting on corn seedling disease, corn growth, and grain yield in 2014 and 2015. Rye termination dates ranged from 25 days before planting (DBP) to 2 days after planting (DAP) corn in the field and from 21 DBP to 1 DAP in controlled studies. Results were similar in both environments. In general, shorter intervals increased seedling disease and reduced corn emergence, shoot growth, and grain yield of corn following winter rye compared with corn planted 10 or more days after rye termination or without rye. Incidence of Pythium spp. increased with shorter intervals (less than 8 DBP); incidence of Fusarium spp. was not consistent between runs and experiments. In 2014, in the 1-DAP treatment, number of ears and grain yield were reduced (P = 0.05 and 0.02, respectively). In 2015, all termination intervals reduced plant population, number of ears, and yield (P = 0.01), with the 2-DBP treatment causing the biggest decrease. A 10- to 14-day interval between rye termination and corn planting should be followed to improve corn yield following a rye cover crop

Manganese superoxide dismutase Ala-9Val polymorphism and risk of breast cancer in a population-based case–control study of African Americans and whites

INTRODUCTION: A polymorphism in the manganese superoxide dismutase (MnSOD) gene, Ala-9Val, has been examined in association with breast cancer risk in several epidemiologic studies. Results suggest that the Ala allele increases the risk of breast cancer and modifies the effects of environmental exposures that produce oxidative damage to DNA. METHODS: We examined the role of the MnSOD Ala-9Val polymorphism in a population-based case–control study of invasive and in situ breast cancer in North Carolina. Genotypes were evaluated for 2025 cases (760 African Americans and 1265 whites) and for 1812 controls (677 African Americans and 1135 whites). RESULTS: The odds ratio for MnSOD Ala/Ala versus any MnSOD Val genotypes was not elevated in African Americans (odds ratio = 0.9, 95% confidence interval = 0.7–1.2) or in whites (odds ratio = 1.0, 95% confidence interval = 0.8–1.2). Greater than additive joint effects were observed for the Ala/Ala genotype and smoking, radiation to the chest, and occupational exposure to ionizing radiation. Antagonism was observed between the Ala/Ala genotype and the use of nonsteroidal anti-inflammatory drugs. CONCLUSIONS: The MnSOD genotype may contribute to an increased risk of breast cancer in the presence of specific environmental exposures. These results provide further evidence for the importance of reactive oxygen species and of oxidative DNA damage in the etiology of breast cancer

Avian response to microclimate in canopy gaps in a bottomland hardwood forest.

Abstract - Microclimate may infl uence use of early successional habitat by birds. We assessed the relationships between avian habitat use and microclimate (temperature, light intensity, and relative humidity) in experimentally created canopy gaps in a bottomland hardwood forest on the Savannah River Site, SC. Gaps were 2- to 3-year-old group-selection timber harvest openings of three sizes (0.13, 0.26, 0.50 ha). Our study was conducted from spring through fall, encompassing four bird-use periods (spring migration, breeding, post-breeding, and fall migration), in 2002 and 2003. We used mist netting and simultaneously recorded microclimate variables to determine the influence of microclimate on bird habitat use. Microclimate was strongly affected by net location within canopy gaps in both years. Temperature generally was higher on the west side of gaps, light intensity was greater in gap centers, and relative humidity was higher on the east side of gaps. However, we found few relationships between bird captures and the microclimate variables. Bird captures were inversely correlated with temperature during the breeding and postbreeding periods in 2002 and positively correlated with temperature during spring 2003. Captures were high where humidity was high during post-breeding 2002, and captures were low where humidity was high during spring 2003. We conclude that variations in the local microclimate had minor infl uence on avian habitat use within gaps. Instead, habitat selection in relatively mild regions like the southeastern US is based primarily on vegetation structure, while other factors, including microclimate, are less important

Using self-definition to predict the influence of procedural justice on organizational, interpersonal, and job/task-oriented citizenship behaviors

An integrative self-definition model is proposed to improve our understanding of how procedural justice affects different outcome modalities in organizational behavior. Specifically, it is examined whether the strength of different levels of self-definition (collective, relational, and individual) each uniquely interact with procedural justice to predict organizational, interpersonal, and job/task-oriented citizenship behaviors, respectively. Results from experimental and (both single and multisource) field data consistently revealed stronger procedural justice effects (1) on organizational-oriented citizenship behavior among those who define themselves strongly in terms of organizational characteristics, (2) on interpersonal-oriented citizenship behavior among those who define themselves strongly in terms of their interpersonal relationships, and (3) on job/task-oriented citizenship behavior among those who define themselves weakly in terms of their distinctiveness or uniqueness. We discuss the relevance of these results with respect to how employees can be motivated most effectively in organizational settings

Reversing Blood Flows Act through klf2a to Ensure Normal Valvulogenesis in the Developing Heart

Heart valve anomalies are some of the most common congenital heart defects, yet neither the genetic nor the epigenetic forces guiding heart valve development are well understood. When functioning normally, mature heart valves prevent intracardiac retrograde blood flow; before valves develop, there is considerable regurgitation, resulting in reversing (or oscillatory) flows between the atrium and ventricle. As reversing flows are particularly strong stimuli to endothelial cells in culture, an attractive hypothesis is that heart valves form as a developmental response to retrograde blood flows through the maturing heart. Here, we exploit the relationship between oscillatory flow and heart rate to manipulate the amount of retrograde flow in the atrioventricular (AV) canal before and during valvulogenesis, and find that this leads to arrested valve growth. Using this manipulation, we determined that klf2a is normally expressed in the valve precursors in response to reversing flows, and is dramatically reduced by treatments that decrease such flows. Experimentally knocking down the expression of this shear-responsive gene with morpholine antisense oligonucleotides (MOs) results in dysfunctional valves. Thus, klf2a expression appears to be necessary for normal valve formation. This, together with its dependence on intracardiac hemodynamic forces, makes klf2a expression an early and reliable indicator of proper valve development. Together, these results demonstrate a critical role for reversing flows during valvulogenesis and show how relatively subtle perturbations of normal hemodynamic patterns can lead to both major alterations in gene expression and severe valve dysgenesis