Dating Clinopyroxene Phenocrysts in Submarine Basalts Using ^(40)Ar/^(39)Ar Geochronology

Dating submarine basalts using ^(40)Ar/^(39)Ar geochronology is often hindered by a lack of potassium‐bearing phenocrystic phases and severe alteration in the groundmass. Clinopyroxene is a common phenocrystic phase in seafloor basalts and is highly resistive to low‐temperature alteration. Here we show that clinopyroxene phenocrysts separated from marine basalts are a viable phase for ^(40)Ar/^(39)Ar incremental heating age determinations. We provide results from a pilot study comprising 16 age experiments from nine clinopyroxene separates, five of which from samples with dated coeval phases. The clinopyroxene ages range from 11.5 to 112 Ma with relatively high uncertainties (ranging from 0.8% to 7.1%; median of 1.9%) compared to more traditional phases. The clinopyroxene age plateaus form at low to moderate temperature steps and are characterized by relatively elevated K/Ca of 0.002–0.4, suggesting that other K‐bearing phases hosted within the clinopyroxene are likely degassing to yield the ^(40)Ar/^(39)Ar age information. There are three possible origins for the K and corresponding ^(40)Ar* including films of trapped melt/nanomineral inclusions along grain defects, secondary melt inclusion bands, or variations in degassing behaviors between lower and higher crystalline Ca pyroxene phases. Regardless of the source of the K, the age determinations are successful with 75% of the experiments producing long plateaus (>60% ^(39)Ar released) with mean square of the weighted deviations ranging from 0.6 to 1.5 and probability of fit values >0.05. We conclude that clinopyroxene dating by the ^(40)Ar/^(39)Ar method has the potential to provide a wealth of information for previously undated, altered seafloor lithologies and continental equivalents

Dating Clinopyroxene Phenocrysts in Submarine Basalts Using ^(40)Ar/^(39)Ar Geochronology

Dating submarine basalts using ^(40)Ar/^(39)Ar geochronology is often hindered by a lack of potassium‐bearing phenocrystic phases and severe alteration in the groundmass. Clinopyroxene is a common phenocrystic phase in seafloor basalts and is highly resistive to low‐temperature alteration. Here we show that clinopyroxene phenocrysts separated from marine basalts are a viable phase for ^(40)Ar/^(39)Ar incremental heating age determinations. We provide results from a pilot study comprising 16 age experiments from nine clinopyroxene separates, five of which from samples with dated coeval phases. The clinopyroxene ages range from 11.5 to 112 Ma with relatively high uncertainties (ranging from 0.8% to 7.1%; median of 1.9%) compared to more traditional phases. The clinopyroxene age plateaus form at low to moderate temperature steps and are characterized by relatively elevated K/Ca of 0.002–0.4, suggesting that other K‐bearing phases hosted within the clinopyroxene are likely degassing to yield the ^(40)Ar/^(39)Ar age information. There are three possible origins for the K and corresponding ^(40)Ar* including films of trapped melt/nanomineral inclusions along grain defects, secondary melt inclusion bands, or variations in degassing behaviors between lower and higher crystalline Ca pyroxene phases. Regardless of the source of the K, the age determinations are successful with 75% of the experiments producing long plateaus (>60% ^(39)Ar released) with mean square of the weighted deviations ranging from 0.6 to 1.5 and probability of fit values >0.05. We conclude that clinopyroxene dating by the ^(40)Ar/^(39)Ar method has the potential to provide a wealth of information for previously undated, altered seafloor lithologies and continental equivalents

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3%lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost

Heliogyro Solar Sail Research at NASA

The recent successful flight of the JAXA IKAROS solar sail has renewed interest within NASA in spinning solar sail concepts for high-performance solar sailing. The heliogyro solar sail, in particular, is being re-examined as a potential game-changing architecture for future solar sailing missions. In this paper, we present an overview of ongoing heliogyro technology development and feasibility assessment activities within NASA. In particular, a small-scale heliogyro solar sail technology demonstration concept will be described. We will also discuss ongoing analytical and experimental heliogyro structural dynamics and controls investigations and provide an outline of future heliogyro development work directed toward enabling a low cost heliogyro technology demonstration mission ca. 2020

UHTC composites for hypersonic applications

A dream for many scientists, engineers and sci-fi enthusiasts is of an aerospace vehicle that can take off from an airport, fly through the atmosphere and travel to the other side of the earth at hypersonic speeds, and then return through the atmosphere to the same or another airport. Thanks to programs like DARPA’s Falcon Hypersonic Technology Vehicle 2 program (Figure 1), the dream is taking form

Rabies Encephalitis in Malaria-Endemic Area, Malawi, Africa

In a malaria-endemic area of Africa, rabies was an important cause of fatal central nervous system infection, responsible for 14 (10.5%) of 133 cases. Four patients had unusual clinical manifestations, and rabies was only diagnosed postmortem. Three (11.5%) of 26 fatal cases were originally attributed to cerebral malaria

First gene-edited calf with reduced susceptibility to a major viral pathogen

Bovine viral diarrhea virus (BVDV) is one of the most important viruses affecting the health and well-being of bovine species throughout the world. Here, we used CRISPR-mediated homology-directed repair and somatic cell nuclear transfer to produce a live calf with a six amino acid substitution in the BVDV binding domain of bovine CD46. The result was a gene-edited calf with dramatically reduced susceptibility to infection as measured by reduced clinical signs and the lack of viral infection in white blood cells. The edited calf has no off-target edits and appears normal and healthy at 20 months of age without obvious adverse effects from the on-target edit. This precision bred, proof-of-concept animal provides the first evidence that intentional genome alterations in the CD46 gene may reduce the burden of BVDV-associated diseases in cattle and is consistent with our stepwise, in vitro and ex vivo experiments with cell lines and matched fetal clones

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3%lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost

Transcriptome-Based Differentiation of Closely-Related Miscanthus Lines

BACKGROUND: Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations. RESULTS: A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence. CONCLUSIONS: Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation