Quantification of atherosclerotic plaque volume in coronary arteries by computed tomographic angiography in subjects with and without diabetes.

BackgroundDiabetes mellitus (DM) is considered a cardiovascular risk factor. The aim of this study was to analyze the prevalence and volume of coronary artery plaque in patients with diabetes mellitus (DM) vs. those without DM.MethodsThis study recruited consecutive patients who underwent coronary computed tomography (CT) angiography (CCTA) between October 2016 and November 2017. Personal information including conventional cardiovascular risk factors was collected. Plaque phenotypes were automatically calculated for volume of different component. The volume of different plaque was compared between DM patients and those without DM.ResultsAmong 6381 patients, 931 (14.59%) were diagnosed with DM. The prevalence of plaque in DM subjects was higher compared with nondiabetic group significantly (48.34% vs. 33.01%, χ = 81.84, P < 0.001). DM was a significant risk factor for the prevalence of plaque in a multivariate model (odds ratio [OR] = 1.465, 95% CI: 1.258-1.706, P < 0.001). The volume of total plaque and any plaque subtypes in the DM subjects was greater than those in nondiabetic patients significantly (P < 0.001).ConclusionThe coronary artery atherosclerotic plaques were significantly higher in diabetic patients than those in non-diabetic patients

Characterizing changes in soybean spectral response curves with breeding advancements

Citation: Christenson, Brent S., William T. Schapaugh, Nan An, Kevin P. Price, and Allan K. Fritz. “Characterizing Changes in Soybean Spectral Response Curves with Breeding Advancements.” Crop Science 54, no. 4 (2014): 1585–97. https://doi.org/10.2135/cropsci2013.08.0575.Soybean (Glycine max (L.) Merr.) crop yield has steadily increased in the past 60 yr due in part to breeding advances. Relations between canopy spectral reflectance to specific plant functions may help characterize the impact of breeding on soybean cultivar development. The objectives of this study were to: 1) find specific regions of the soybean canopy spectral reflectance response curves that show genotypic differences; and 2) determine the effect of the breeding process on spectral reflectance response curves of soybean cultivars. Canopy spectral reflectance measurements were taken on 20 maturity group III (MGIII) and 20 maturity group IV (MGIV) soybean cultivars ranging in release year from 1923 to 2010 (arranged in a randomized complete block design) in 2011 and 2012 in Manhattan, KS. Large genotypic differences were found among cultivars, especially in the green (500 nm–600 nm), red (600 nm–700 nm), and red-edge (700nm–730 nm) portions of the spectra. Reflectance in the visible (VIS) (400–700 nm), red-edge (700–730 nm), and near-infrared (NIR) (730–1305) portions of the spectra varied with year of release (YOR) among cultivars. The more recently released cultivars tended to have lower reflectance values in the VIS and red-edge spectra portions and higher values in the NIR portion of the spectra than earlier-released cultivars. Results also indicate that spectral reflectance in the NIR portion of the spectra are highly confounded with maturity and other agronomic traits. These results indicate that breeding advancement has had an impact on canopy spectral reflectance curves and the VIS and red-edge portions of the spectra may be a source of variation for further cultivar development and advancement

Mass transport phenomena between bubbles and dissolved gases in liquids under reduced gravity conditions

The experimental and analytical work that was done to establish justification and feasibility for a shuttle middeck experiment involving mass transfer between a gas bubble and a liquid is described. The experiment involves the observation and measurement of the dissolution of an isolated immobile gas bubble of specified size and composition in a thermostatted solvent liquid of known concentration in the reduced gravity environment of earth orbit. Methods to generate and deploy the bubble were successful both in normal gravity using mutually buoyant fluids and under reduced gravity conditions in the NASA Lear Jet. Initialization of the experiment with a bubble of a prescribed size and composition in a liquid of known concentration was accomplished using the concept of unstable equilibrium. Subsequent bubble dissolution or growth is obtained by a step increase or decrease in the liquid pressure. A numerical model was developed which simulates the bubble dynamics and can be used to determine molecular parameters by comparison with the experimental data. The primary objective of the experiment is the elimination of convective effects that occur in normal gravity

Local transformation of mixed states of two qubits to Bell diagonal states

The optimal entanglement manipulation for a single copy of mixed states of two qubits is to transform it to a Bell diagonal state. In this paper we derive an explicit form of the local operation that can realize such a transformation. The result obtained is universal for arbitrary entangled two-qubit states and it discloses that the corresponding local filter is not unique for density matrices with rank $n=2$ and can be exclusively determined for that with $n=3$ and 4. As illustrations, a four-parameters family of mixed states are explored, the local filter as well as the transformation probability are given explicitly, which verify the validity of the general result.Comment: 5 pages, to be published in Phys. Rev.

ESTIMATING ANNUAL NET PRIMARY PRODUCTIVITY OF THE TALLGRASS PRAIRIE ECOSYSTEM OF THE CENTRAL GREAT PLAINS USING AVHRR NDVI

Aboveground Net Primary Productivity (ANPP) is indicative of an ecosystem's ability to capture solar energy and store it in the form of carbon (or biomass). Annual and interannual ecosystem variation in ANPP is often linked to climatic dynamics and anthropogenic influences. The Great Plains grasslands occupy over 1.5 million km2 and are a primary resource for livestock production in North America. The tallgrass prairies are the most productive of the grasslands of the region and the Flint Hills of North America represent the largest contiguous area of unplowed tallgrass prairie (1.6 million ha) (Knapp and Seastead, 1998). Measurements of ANPP are of critical importance to the proper management and understanding of climatic and anthropogenic influences on tallgrass prairie, yet accurate, detailed, and systematic measurements of ANPP over large geographic regions of this system do not exist. For these reasons, this study was conducted to investigate the use of the Normalized Difference Vegetation Index (NDVI) to model ANPP for the tallgrass prairie. Many studies have established a positive relationship between the NDVI and ANPP, but the strength of this relationship is influenced by vegetation types and can significantly vary from year-to-year depending on land use and climatic conditions. The goal of this study is to develop a robust model using the Advanced Very High Resolution Radiometer (AVHRR) biweekly NDVI values to predict tallgrass ANPP. This study was conducted using the Konza Prairie Biological Station as the primary study area with data also from the Rannells Flint Hills Prairie Preserve and other sites near Manhattan, Kansas. The dominant study period was 1989 to 2005. The optimal period for estimating ANPP using AVHRR NDVI composite datasets is prairie 30 (late July). The Tallgrass ANPP Model (TAM) explained 53% (r2 = 0.53, r = 0.73) of the year-to-year variation. Efforts to validate the TAM results were frustrated by considerable variations among existing remote sensing based ANPP model estimates and in situ clipplot measurements of peak season tallgrass production. These findings support the conclusion that ecosystem specific ANPP models are needed to improve global scale ANPP estimates. The creation of 1 km x 1 km resolution ANPP maps for a four county (~7,000 ha) for years 1989 - 2007 showed considerable variation in annual and interannual ANPP spatial patterns suggesting complex interactions among factors influencing ANPP spatially and temporally. The observed patterns on these maps would be lost using the much coarser resolution ground weather recording stations